From 8d8e20c69a4018129a0ff4111f7d46f4ecddafb3 Mon Sep 17 00:00:00 2001 From: Roman Bredehoft Date: Thu, 14 Sep 2023 17:52:05 +0200 Subject: [PATCH] chore: simplify post processing for classifiers --- src/concrete/ml/sklearn/base.py | 35 +- src/concrete/ml/sklearn/linear_model.py | 6 - src/concrete/ml/sklearn/qnn.py | 6 - src/concrete/ml/sklearn/rf.py | 6 - src/concrete/ml/sklearn/svm.py | 6 - src/concrete/ml/sklearn/tree.py | 6 - src/concrete/ml/sklearn/xgb.py | 6 - .../CNV_2W2A_2W2A_20221114_131345/log.txt | 79514 +++++++++++++++- 8 files changed, 79533 insertions(+), 52 deletions(-) diff --git a/src/concrete/ml/sklearn/base.py b/src/concrete/ml/sklearn/base.py index 3245efb66..ca35a82dd 100644 --- a/src/concrete/ml/sklearn/base.py +++ b/src/concrete/ml/sklearn/base.py @@ -701,6 +701,13 @@ class BaseClassifier(BaseEstimator): @property def target_classes_(self) -> Optional[numpy.ndarray]: # pragma: no cover + """Get the model's classes. + + Using this attribute is deprecated. + + Returns: + Optional[numpy.ndarray]: The model's classes. + """ warnings.warn( "Attribute 'target_classes_' is now deprecated. Please use 'classes_' instead.", category=UserWarning, @@ -710,7 +717,14 @@ def target_classes_(self) -> Optional[numpy.ndarray]: # pragma: no cover return self.classes_ @property - def n_classes_(self) -> Optional[numpy.ndarray]: # pragma: no cover + def n_classes_(self) -> int: # pragma: no cover + """Get the model's number of classes. + + Using this attribute is deprecated. + + Returns: + int: The model's number of classes. + """ warnings.warn( "Attribute 'n_classes_' is now deprecated. Please use 'len(classes_)' instead.", category=UserWarning, @@ -719,10 +733,6 @@ def n_classes_(self) -> Optional[numpy.ndarray]: # pragma: no cover return len(self.classes_) - def _set_post_processing_params(self): - super()._set_post_processing_params() - self.post_processing_params.update({"classes_": self.classes_}) - def fit(self, X: Data, y: Target, **fit_parameters): X, y = check_X_y_and_assert_multi_output(X, y) @@ -765,17 +775,16 @@ def predict(self, X: Data, fhe: Union[FheMode, str] = FheMode.DISABLE) -> numpy. def post_processing(self, y_preds: numpy.ndarray) -> numpy.ndarray: y_preds = super().post_processing(y_preds) - # Retrieve the number of target classes - classes = self.post_processing_params["classes_"] + # If the prediction array is 1D, which happens with some models such as XGBCLassifier or + # LogisticRegression models, we have a binary classification problem + n_classes = y_preds.shape[1] if y_preds.ndim > 1 and y_preds.shape[1] > 1 else 2 - # If the predictions only has one dimension (i.e., binary classification problem), apply the - # sigmoid operator - if len(classes) == 2: + # For binary classification problem, apply the sigmoid operator + if n_classes == 2: y_preds = numpy_sigmoid(y_preds)[0] - # If the prediction array is 1D (which happens with some models such as XGBCLassifier - # models), transform the output into a 2D array [1-p, p], with p the initial - # output probabilities + # If the prediction array is 1D, transform the output into a 2D array [1-p, p], + # with p the initial output probabilities if y_preds.ndim == 1 or y_preds.shape[1] == 1: y_preds = numpy.concatenate((1 - y_preds, y_preds), axis=1) diff --git a/src/concrete/ml/sklearn/linear_model.py b/src/concrete/ml/sklearn/linear_model.py index 484cc794a..b50a51a1f 100644 --- a/src/concrete/ml/sklearn/linear_model.py +++ b/src/concrete/ml/sklearn/linear_model.py @@ -525,9 +525,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["_q_bias"] = self._q_bias metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # Scikit-Learn metadata["penalty"] = self.penalty metadata["dual"] = self.dual @@ -565,9 +562,6 @@ def load_dict(cls, metadata: Dict): obj._q_bias = metadata["_q_bias"] obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # Scikit-Learn obj.penalty = metadata["penalty"] obj.dual = metadata["dual"] diff --git a/src/concrete/ml/sklearn/qnn.py b/src/concrete/ml/sklearn/qnn.py index 8730f1704..3d31f8c20 100644 --- a/src/concrete/ml/sklearn/qnn.py +++ b/src/concrete/ml/sklearn/qnn.py @@ -547,9 +547,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["quantized_module_"] = self.quantized_module_ metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # skorch attributes that cannot be serialized # FIXME: https://github.com/zama-ai/concrete-ml-internal/issues/3550 # Disable mypy as running isinstance with a Callable type unexpectedly raises an issue: @@ -636,9 +633,6 @@ def load_dict(cls, metadata: Dict): obj.quantized_module_ = metadata["quantized_module_"] obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # skorch obj.lr = metadata["lr"] obj.max_epochs = metadata["max_epochs"] diff --git a/src/concrete/ml/sklearn/rf.py b/src/concrete/ml/sklearn/rf.py index fea79fa54..00685a047 100644 --- a/src/concrete/ml/sklearn/rf.py +++ b/src/concrete/ml/sklearn/rf.py @@ -85,9 +85,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["framework"] = self.framework metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # Scikit-Learn metadata["n_estimators"] = self.n_estimators metadata["bootstrap"] = self.bootstrap @@ -129,9 +126,6 @@ def load_dict(cls, metadata: Dict): ) obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # Scikit-Learn obj.n_estimators = metadata["n_estimators"] obj.bootstrap = metadata["bootstrap"] diff --git a/src/concrete/ml/sklearn/svm.py b/src/concrete/ml/sklearn/svm.py index 5bcf8c112..1636a0061 100644 --- a/src/concrete/ml/sklearn/svm.py +++ b/src/concrete/ml/sklearn/svm.py @@ -192,9 +192,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["_q_bias"] = self._q_bias metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # Scikit-Learn metadata["penalty"] = self.penalty metadata["loss"] = self.loss @@ -230,9 +227,6 @@ def load_dict(cls, metadata: Dict): obj._q_bias = metadata["_q_bias"] obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # Scikit-Learn obj.penalty = metadata["penalty"] obj.loss = metadata["loss"] diff --git a/src/concrete/ml/sklearn/tree.py b/src/concrete/ml/sklearn/tree.py index 68ba0176a..b81558b77 100644 --- a/src/concrete/ml/sklearn/tree.py +++ b/src/concrete/ml/sklearn/tree.py @@ -85,9 +85,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["framework"] = self.framework metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # Scikit-Learn metadata["criterion"] = self.criterion metadata["splitter"] = self.splitter @@ -124,9 +121,6 @@ def load_dict(cls, metadata: Dict): ) obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # Scikit-Learn obj.criterion = metadata["criterion"] obj.splitter = metadata["splitter"] diff --git a/src/concrete/ml/sklearn/xgb.py b/src/concrete/ml/sklearn/xgb.py index 3b208001b..86301a5cb 100644 --- a/src/concrete/ml/sklearn/xgb.py +++ b/src/concrete/ml/sklearn/xgb.py @@ -126,9 +126,6 @@ def dump_dict(self) -> Dict[str, Any]: metadata["framework"] = self.framework metadata["post_processing_params"] = self.post_processing_params - # Classifier - metadata["classes_"] = self.classes_ - # XGBoost metadata["max_depth"] = self.max_depth metadata["learning_rate"] = self.learning_rate @@ -183,9 +180,6 @@ def load_dict(cls, metadata: Dict): ) obj.post_processing_params = metadata["post_processing_params"] - # Classifier - obj.classes_ = metadata["classes_"] - # XGBoost obj.max_depth = metadata["max_depth"] obj.learning_rate = metadata["learning_rate"] diff --git a/use_case_examples/cifar_brevitas_training/experiments/CNV_2W2A_2W2A_20221114_131345/log.txt b/use_case_examples/cifar_brevitas_training/experiments/CNV_2W2A_2W2A_20221114_131345/log.txt index 669b0682f..28c2133c3 100644 --- a/use_case_examples/cifar_brevitas_training/experiments/CNV_2W2A_2W2A_20221114_131345/log.txt +++ b/use_case_examples/cifar_brevitas_training/experiments/CNV_2W2A_2W2A_20221114_131345/log.txt @@ -1,3 +1,79511 @@ -version 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(1.115) Loss Time 0.000 (0.000) Loss 0.3135 (0.2980) Prec@1 36.000 (42.500) Prec@5 89.000 (88.500) +2022-11-14 13:14:07,523 Test: [2/100] Model Time 0.006 (0.745) Loss Time 0.000 (0.000) Loss 0.2785 (0.2915) Prec@1 44.000 (43.000) Prec@5 94.000 (90.333) +2022-11-14 13:14:07,535 Test: [3/100] Model Time 0.007 (0.561) Loss Time 0.000 (0.000) Loss 0.2855 (0.2900) Prec@1 44.000 (43.250) Prec@5 92.000 (90.750) +2022-11-14 13:14:07,543 Test: [4/100] Model Time 0.006 (0.450) Loss Time 0.000 (0.000) Loss 0.2715 (0.2863) Prec@1 48.000 (44.200) Prec@5 90.000 (90.600) +2022-11-14 13:14:07,552 Test: [5/100] Model Time 0.006 (0.376) Loss Time 0.000 (0.000) Loss 0.2628 (0.2824) Prec@1 47.000 (44.667) Prec@5 97.000 (91.667) +2022-11-14 13:14:07,561 Test: [6/100] Model Time 0.005 (0.323) Loss Time 0.000 (0.000) Loss 0.2915 (0.2837) Prec@1 40.000 (44.000) Prec@5 90.000 (91.429) +2022-11-14 13:14:07,570 Test: [7/100] Model Time 0.005 (0.283) Loss Time 0.000 (0.000) Loss 0.2941 (0.2850) Prec@1 44.000 (44.000) Prec@5 92.000 (91.500) +2022-11-14 13:14:07,577 Test: [8/100] Model Time 0.005 (0.252) Loss Time 0.000 (0.000) Loss 0.2756 (0.2840) Prec@1 45.000 (44.111) Prec@5 89.000 (91.222) +2022-11-14 13:14:07,584 Test: [9/100] Model Time 0.005 (0.228) Loss Time 0.000 (0.000) Loss 0.2755 (0.2831) Prec@1 50.000 (44.700) Prec@5 93.000 (91.400) +2022-11-14 13:14:07,591 Test: [10/100] Model Time 0.005 (0.207) Loss Time 0.000 (0.000) Loss 0.2738 (0.2823) Prec@1 47.000 (44.909) Prec@5 90.000 (91.273) +2022-11-14 13:14:07,599 Test: [11/100] Model Time 0.005 (0.190) Loss Time 0.000 (0.000) Loss 0.2855 (0.2825) Prec@1 43.000 (44.750) Prec@5 93.000 (91.417) +2022-11-14 13:14:07,607 Test: [12/100] Model Time 0.005 (0.176) Loss Time 0.000 (0.000) Loss 0.2937 (0.2834) Prec@1 40.000 (44.385) Prec@5 93.000 (91.538) +2022-11-14 13:14:07,615 Test: [13/100] Model Time 0.005 (0.164) Loss Time 0.000 (0.000) Loss 0.2811 (0.2832) Prec@1 42.000 (44.214) Prec@5 94.000 (91.714) +2022-11-14 13:14:07,624 Test: [14/100] Model Time 0.005 (0.153) Loss Time 0.000 (0.000) Loss 0.2471 (0.2808) Prec@1 49.000 (44.533) Prec@5 96.000 (92.000) +2022-11-14 13:14:07,631 Test: [15/100] Model Time 0.005 (0.144) Loss Time 0.000 (0.000) Loss 0.2928 (0.2816) Prec@1 39.000 (44.188) Prec@5 91.000 (91.938) +2022-11-14 13:14:07,638 Test: [16/100] Model Time 0.005 (0.136) Loss Time 0.000 (0.000) Loss 0.2803 (0.2815) Prec@1 43.000 (44.118) Prec@5 90.000 (91.824) +2022-11-14 13:14:07,645 Test: [17/100] Model Time 0.005 (0.129) Loss Time 0.000 (0.000) Loss 0.2764 (0.2812) Prec@1 43.000 (44.056) Prec@5 92.000 (91.833) +2022-11-14 13:14:07,652 Test: [18/100] Model Time 0.005 (0.122) Loss Time 0.000 (0.000) Loss 0.2712 (0.2807) Prec@1 53.000 (44.526) Prec@5 86.000 (91.526) +2022-11-14 13:14:07,659 Test: [19/100] Model Time 0.005 (0.116) Loss Time 0.000 (0.000) Loss 0.3012 (0.2817) Prec@1 37.000 (44.150) Prec@5 92.000 (91.550) +2022-11-14 13:14:07,666 Test: [20/100] Model Time 0.005 (0.111) Loss Time 0.000 (0.000) Loss 0.2486 (0.2801) Prec@1 56.000 (44.714) Prec@5 91.000 (91.524) +2022-11-14 13:14:07,673 Test: [21/100] Model Time 0.006 (0.106) Loss Time 0.000 (0.000) Loss 0.2631 (0.2794) Prec@1 51.000 (45.000) Prec@5 92.000 (91.545) +2022-11-14 13:14:07,681 Test: [22/100] Model Time 0.005 (0.102) Loss Time 0.000 (0.000) Loss 0.2864 (0.2797) Prec@1 46.000 (45.043) Prec@5 90.000 (91.478) +2022-11-14 13:14:07,691 Test: [23/100] Model Time 0.006 (0.098) Loss Time 0.000 (0.000) Loss 0.2718 (0.2793) Prec@1 43.000 (44.958) Prec@5 93.000 (91.542) +2022-11-14 13:14:07,701 Test: [24/100] Model Time 0.005 (0.094) Loss Time 0.000 (0.000) Loss 0.2767 (0.2792) Prec@1 47.000 (45.040) Prec@5 91.000 (91.520) +2022-11-14 13:14:07,710 Test: [25/100] Model Time 0.006 (0.091) Loss Time 0.000 (0.000) Loss 0.3236 (0.2809) Prec@1 33.000 (44.577) Prec@5 91.000 (91.500) +2022-11-14 13:14:07,717 Test: [26/100] Model Time 0.005 (0.088) Loss Time 0.000 (0.000) Loss 0.2682 (0.2805) Prec@1 48.000 (44.704) Prec@5 92.000 (91.519) +2022-11-14 13:14:07,726 Test: [27/100] Model Time 0.005 (0.085) Loss Time 0.000 (0.000) Loss 0.2983 (0.2811) Prec@1 36.000 (44.393) Prec@5 90.000 (91.464) +2022-11-14 13:14:07,734 Test: [28/100] Model Time 0.005 (0.082) Loss Time 0.000 (0.000) Loss 0.2905 (0.2814) Prec@1 41.000 (44.276) Prec@5 90.000 (91.414) +2022-11-14 13:14:07,742 Test: [29/100] Model Time 0.006 (0.079) Loss Time 0.000 (0.000) Loss 0.2567 (0.2806) Prec@1 52.000 (44.533) Prec@5 94.000 (91.500) +2022-11-14 13:14:07,751 Test: [30/100] Model Time 0.006 (0.077) Loss Time 0.000 (0.000) Loss 0.2647 (0.2801) Prec@1 45.000 (44.548) Prec@5 95.000 (91.613) +2022-11-14 13:14:07,759 Test: [31/100] Model Time 0.005 (0.075) Loss Time 0.000 (0.000) Loss 0.2605 (0.2795) Prec@1 52.000 (44.781) Prec@5 94.000 (91.688) +2022-11-14 13:14:07,767 Test: [32/100] Model Time 0.005 (0.073) Loss Time 0.000 (0.000) Loss 0.2695 (0.2792) Prec@1 48.000 (44.879) Prec@5 94.000 (91.758) +2022-11-14 13:14:07,776 Test: [33/100] Model Time 0.005 (0.071) Loss Time 0.000 (0.000) Loss 0.2696 (0.2789) Prec@1 44.000 (44.853) Prec@5 91.000 (91.735) +2022-11-14 13:14:07,784 Test: [34/100] Model Time 0.005 (0.069) Loss Time 0.000 (0.000) Loss 0.2827 (0.2790) Prec@1 46.000 (44.886) Prec@5 88.000 (91.629) +2022-11-14 13:14:07,792 Test: [35/100] Model Time 0.006 (0.067) Loss Time 0.000 (0.000) Loss 0.2641 (0.2786) Prec@1 47.000 (44.944) Prec@5 92.000 (91.639) +2022-11-14 13:14:07,801 Test: [36/100] Model Time 0.006 (0.065) Loss Time 0.000 (0.000) Loss 0.2958 (0.2791) Prec@1 42.000 (44.865) Prec@5 84.000 (91.432) +2022-11-14 13:14:07,809 Test: [37/100] Model Time 0.006 (0.064) Loss Time 0.000 (0.000) Loss 0.2847 (0.2792) Prec@1 42.000 (44.789) Prec@5 86.000 (91.289) +2022-11-14 13:14:07,819 Test: [38/100] Model Time 0.006 (0.062) Loss Time 0.000 (0.000) Loss 0.2631 (0.2788) Prec@1 47.000 (44.846) Prec@5 94.000 (91.359) +2022-11-14 13:14:07,828 Test: [39/100] Model Time 0.006 (0.061) Loss Time 0.000 (0.000) Loss 0.2745 (0.2787) Prec@1 42.000 (44.775) Prec@5 90.000 (91.325) +2022-11-14 13:14:07,837 Test: [40/100] Model Time 0.006 (0.060) Loss Time 0.000 (0.000) Loss 0.2692 (0.2785) Prec@1 49.000 (44.878) Prec@5 92.000 (91.341) +2022-11-14 13:14:07,846 Test: [41/100] Model Time 0.006 (0.058) Loss Time 0.000 (0.000) Loss 0.2871 (0.2787) Prec@1 46.000 (44.905) Prec@5 89.000 (91.286) +2022-11-14 13:14:07,856 Test: [42/100] Model Time 0.006 (0.057) Loss Time 0.000 (0.000) Loss 0.2701 (0.2785) Prec@1 47.000 (44.953) Prec@5 92.000 (91.302) +2022-11-14 13:14:07,864 Test: [43/100] Model Time 0.006 (0.056) Loss Time 0.000 (0.000) Loss 0.2751 (0.2784) Prec@1 46.000 (44.977) Prec@5 88.000 (91.227) +2022-11-14 13:14:07,873 Test: [44/100] Model Time 0.005 (0.055) Loss Time 0.000 (0.000) Loss 0.2929 (0.2787) Prec@1 41.000 (44.889) Prec@5 90.000 (91.200) +2022-11-14 13:14:07,881 Test: [45/100] Model Time 0.006 (0.054) Loss Time 0.000 (0.000) Loss 0.2848 (0.2788) Prec@1 38.000 (44.739) Prec@5 95.000 (91.283) +2022-11-14 13:14:07,890 Test: [46/100] Model Time 0.006 (0.053) Loss Time 0.000 (0.000) Loss 0.2792 (0.2788) Prec@1 46.000 (44.766) Prec@5 93.000 (91.319) +2022-11-14 13:14:07,898 Test: [47/100] Model Time 0.006 (0.052) Loss Time 0.000 (0.000) Loss 0.2891 (0.2791) Prec@1 42.000 (44.708) Prec@5 95.000 (91.396) +2022-11-14 13:14:07,907 Test: [48/100] Model Time 0.006 (0.051) Loss Time 0.000 (0.000) Loss 0.2612 (0.2787) Prec@1 53.000 (44.878) Prec@5 94.000 (91.449) +2022-11-14 13:14:07,915 Test: [49/100] Model Time 0.006 (0.050) Loss Time 0.000 (0.000) Loss 0.2624 (0.2784) Prec@1 45.000 (44.880) Prec@5 93.000 (91.480) +2022-11-14 13:14:07,922 Test: [50/100] Model Time 0.006 (0.049) Loss Time 0.000 (0.000) Loss 0.2649 (0.2781) Prec@1 53.000 (45.039) Prec@5 91.000 (91.471) +2022-11-14 13:14:07,930 Test: [51/100] Model Time 0.006 (0.048) Loss Time 0.000 (0.000) Loss 0.2781 (0.2781) Prec@1 45.000 (45.038) Prec@5 93.000 (91.500) +2022-11-14 13:14:07,937 Test: [52/100] Model Time 0.005 (0.047) Loss Time 0.000 (0.000) Loss 0.2911 (0.2784) Prec@1 40.000 (44.943) Prec@5 91.000 (91.491) +2022-11-14 13:14:07,944 Test: [53/100] Model Time 0.005 (0.047) Loss Time 0.000 (0.000) Loss 0.2762 (0.2783) Prec@1 47.000 (44.981) Prec@5 90.000 (91.463) +2022-11-14 13:14:07,951 Test: [54/100] Model Time 0.005 (0.046) Loss Time 0.000 (0.000) Loss 0.2908 (0.2785) Prec@1 42.000 (44.927) Prec@5 89.000 (91.418) +2022-11-14 13:14:07,958 Test: [55/100] Model Time 0.005 (0.045) Loss Time 0.000 (0.000) Loss 0.2847 (0.2787) Prec@1 48.000 (44.982) Prec@5 89.000 (91.375) +2022-11-14 13:14:07,964 Test: [56/100] Model Time 0.005 (0.044) Loss Time 0.000 (0.000) Loss 0.2710 (0.2785) Prec@1 51.000 (45.088) Prec@5 93.000 (91.404) +2022-11-14 13:14:07,971 Test: [57/100] Model Time 0.005 (0.044) Loss Time 0.000 (0.000) Loss 0.2617 (0.2782) Prec@1 45.000 (45.086) Prec@5 93.000 (91.431) +2022-11-14 13:14:07,978 Test: [58/100] Model Time 0.005 (0.043) Loss Time 0.000 (0.000) Loss 0.2928 (0.2785) Prec@1 40.000 (45.000) Prec@5 91.000 (91.424) +2022-11-14 13:14:07,987 Test: [59/100] Model Time 0.005 (0.042) Loss Time 0.000 (0.000) Loss 0.2649 (0.2782) Prec@1 48.000 (45.050) Prec@5 92.000 (91.433) +2022-11-14 13:14:07,994 Test: [60/100] Model Time 0.005 (0.042) Loss Time 0.000 (0.000) Loss 0.2869 (0.2784) Prec@1 41.000 (44.984) Prec@5 91.000 (91.426) +2022-11-14 13:14:08,001 Test: [61/100] Model Time 0.005 (0.041) Loss Time 0.000 (0.000) Loss 0.2872 (0.2785) Prec@1 45.000 (44.984) Prec@5 92.000 (91.435) +2022-11-14 13:14:08,010 Test: [62/100] Model Time 0.006 (0.041) Loss Time 0.000 (0.000) Loss 0.2883 (0.2787) Prec@1 44.000 (44.968) Prec@5 94.000 (91.476) +2022-11-14 13:14:08,020 Test: [63/100] Model Time 0.005 (0.040) Loss Time 0.000 (0.000) Loss 0.2724 (0.2786) Prec@1 42.000 (44.922) Prec@5 92.000 (91.484) +2022-11-14 13:14:08,028 Test: [64/100] Model Time 0.005 (0.040) Loss Time 0.000 (0.000) Loss 0.3102 (0.2791) Prec@1 39.000 (44.831) Prec@5 86.000 (91.400) +2022-11-14 13:14:08,038 Test: [65/100] Model Time 0.006 (0.039) Loss Time 0.000 (0.000) Loss 0.2955 (0.2793) Prec@1 43.000 (44.803) Prec@5 89.000 (91.364) +2022-11-14 13:14:08,048 Test: [66/100] Model Time 0.006 (0.039) Loss Time 0.000 (0.000) Loss 0.2855 (0.2794) Prec@1 46.000 (44.821) Prec@5 87.000 (91.299) +2022-11-14 13:14:08,057 Test: [67/100] Model Time 0.006 (0.038) Loss Time 0.000 (0.000) Loss 0.3009 (0.2797) Prec@1 39.000 (44.735) Prec@5 88.000 (91.250) +2022-11-14 13:14:08,064 Test: [68/100] Model Time 0.005 (0.038) Loss Time 0.000 (0.000) Loss 0.2901 (0.2799) Prec@1 39.000 (44.652) Prec@5 91.000 (91.246) +2022-11-14 13:14:08,073 Test: [69/100] Model Time 0.006 (0.037) Loss Time 0.000 (0.000) Loss 0.3154 (0.2804) Prec@1 37.000 (44.543) Prec@5 88.000 (91.200) +2022-11-14 13:14:08,082 Test: [70/100] Model Time 0.005 (0.037) Loss Time 0.000 (0.000) Loss 0.2657 (0.2802) Prec@1 48.000 (44.592) Prec@5 95.000 (91.254) +2022-11-14 13:14:08,091 Test: [71/100] Model Time 0.006 (0.036) Loss Time 0.000 (0.000) Loss 0.2611 (0.2799) Prec@1 57.000 (44.764) Prec@5 93.000 (91.278) +2022-11-14 13:14:08,100 Test: [72/100] Model Time 0.006 (0.036) Loss Time 0.000 (0.000) Loss 0.2551 (0.2796) Prec@1 50.000 (44.836) Prec@5 96.000 (91.342) +2022-11-14 13:14:08,109 Test: [73/100] Model Time 0.006 (0.036) Loss Time 0.000 (0.000) Loss 0.2716 (0.2795) Prec@1 48.000 (44.878) Prec@5 95.000 (91.392) +2022-11-14 13:14:08,118 Test: [74/100] Model Time 0.007 (0.035) Loss Time 0.000 (0.000) Loss 0.2724 (0.2794) Prec@1 44.000 (44.867) Prec@5 93.000 (91.413) +2022-11-14 13:14:08,127 Test: [75/100] Model Time 0.006 (0.035) Loss Time 0.000 (0.000) Loss 0.2818 (0.2794) Prec@1 51.000 (44.947) Prec@5 89.000 (91.382) +2022-11-14 13:14:08,136 Test: [76/100] Model Time 0.006 (0.034) Loss Time 0.000 (0.000) Loss 0.2692 (0.2793) Prec@1 47.000 (44.974) Prec@5 91.000 (91.377) +2022-11-14 13:14:08,149 Test: [77/100] Model Time 0.006 (0.034) Loss Time 0.000 (0.000) Loss 0.2646 (0.2791) Prec@1 48.000 (45.013) Prec@5 95.000 (91.423) +2022-11-14 13:14:08,158 Test: [78/100] Model Time 0.006 (0.034) Loss Time 0.000 (0.000) Loss 0.2822 (0.2791) Prec@1 45.000 (45.013) Prec@5 91.000 (91.418) +2022-11-14 13:14:08,166 Test: [79/100] Model Time 0.006 (0.033) Loss Time 0.000 (0.000) Loss 0.2920 (0.2793) Prec@1 39.000 (44.938) Prec@5 93.000 (91.438) +2022-11-14 13:14:08,175 Test: [80/100] Model Time 0.006 (0.033) Loss Time 0.000 (0.000) Loss 0.2636 (0.2791) Prec@1 44.000 (44.926) Prec@5 92.000 (91.444) +2022-11-14 13:14:08,184 Test: [81/100] Model Time 0.006 (0.033) Loss Time 0.000 (0.000) Loss 0.2930 (0.2793) Prec@1 39.000 (44.854) Prec@5 92.000 (91.451) +2022-11-14 13:14:08,192 Test: [82/100] Model Time 0.005 (0.032) Loss Time 0.000 (0.000) Loss 0.3063 (0.2796) Prec@1 38.000 (44.771) Prec@5 89.000 (91.422) +2022-11-14 13:14:08,200 Test: [83/100] Model Time 0.006 (0.032) Loss Time 0.000 (0.000) Loss 0.2860 (0.2797) Prec@1 41.000 (44.726) Prec@5 95.000 (91.464) +2022-11-14 13:14:08,207 Test: [84/100] Model Time 0.006 (0.032) Loss Time 0.000 (0.000) Loss 0.2959 (0.2799) Prec@1 46.000 (44.741) Prec@5 87.000 (91.412) +2022-11-14 13:14:08,215 Test: [85/100] Model Time 0.005 (0.031) Loss Time 0.000 (0.000) Loss 0.2747 (0.2798) Prec@1 46.000 (44.756) Prec@5 94.000 (91.442) +2022-11-14 13:14:08,222 Test: [86/100] Model Time 0.006 (0.031) Loss Time 0.000 (0.000) Loss 0.3056 (0.2801) Prec@1 37.000 (44.667) Prec@5 91.000 (91.437) +2022-11-14 13:14:08,230 Test: [87/100] Model Time 0.005 (0.031) Loss Time 0.000 (0.000) Loss 0.2875 (0.2802) Prec@1 40.000 (44.614) Prec@5 90.000 (91.420) +2022-11-14 13:14:08,237 Test: [88/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.2802 (0.2802) Prec@1 44.000 (44.607) Prec@5 90.000 (91.404) +2022-11-14 13:14:08,244 Test: [89/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.2696 (0.2801) Prec@1 48.000 (44.644) Prec@5 91.000 (91.400) +2022-11-14 13:14:08,251 Test: [90/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.2831 (0.2801) Prec@1 44.000 (44.637) Prec@5 92.000 (91.407) +2022-11-14 13:14:08,260 Test: [91/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.2672 (0.2800) Prec@1 46.000 (44.652) Prec@5 97.000 (91.467) +2022-11-14 13:14:08,268 Test: [92/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.2624 (0.2798) Prec@1 51.000 (44.720) Prec@5 94.000 (91.495) +2022-11-14 13:14:08,275 Test: [93/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.2936 (0.2799) Prec@1 42.000 (44.691) Prec@5 86.000 (91.436) +2022-11-14 13:14:08,283 Test: [94/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.2901 (0.2800) Prec@1 40.000 (44.642) Prec@5 90.000 (91.421) +2022-11-14 13:14:08,290 Test: [95/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.2785 (0.2800) Prec@1 46.000 (44.656) Prec@5 93.000 (91.438) +2022-11-14 13:14:08,296 Test: [96/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.2849 (0.2801) Prec@1 42.000 (44.629) Prec@5 87.000 (91.392) +2022-11-14 13:14:08,304 Test: [97/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.2945 (0.2802) Prec@1 41.000 (44.592) Prec@5 90.000 (91.378) +2022-11-14 13:14:08,311 Test: [98/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.2720 (0.2801) Prec@1 49.000 (44.636) Prec@5 94.000 (91.404) +2022-11-14 13:14:08,318 Test: [99/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.2557 (0.2799) Prec@1 53.000 (44.720) Prec@5 95.000 (91.440) +2022-11-14 13:14:08,365 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:14:08,606 Epoch: [2][0/500] Time 0.018 (0.018) Data 0.189 (0.189) Loss 0.2632 (0.2632) Prec@1 54.000 (54.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:08,770 Epoch: [2][10/500] Time 0.014 (0.015) Data 0.001 (0.018) Loss 0.2967 (0.2800) Prec@1 43.000 (48.500) Prec@5 86.000 (89.500) +2022-11-14 13:14:08,940 Epoch: [2][20/500] Time 0.014 (0.015) Data 0.001 (0.010) Loss 0.2920 (0.2840) Prec@1 38.000 (45.000) Prec@5 91.000 (90.000) +2022-11-14 13:14:09,104 Epoch: [2][30/500] Time 0.017 (0.015) Data 0.001 (0.007) Loss 0.2556 (0.2769) Prec@1 56.000 (47.750) Prec@5 96.000 (91.500) +2022-11-14 13:14:09,269 Epoch: [2][40/500] Time 0.014 (0.015) Data 0.001 (0.006) Loss 0.2475 (0.2710) Prec@1 58.000 (49.800) Prec@5 95.000 (92.200) +2022-11-14 13:14:09,435 Epoch: [2][50/500] Time 0.014 (0.015) Data 0.001 (0.005) Loss 0.3062 (0.2769) Prec@1 33.000 (47.000) Prec@5 97.000 (93.000) +2022-11-14 13:14:09,605 Epoch: [2][60/500] Time 0.014 (0.015) Data 0.001 (0.004) Loss 0.2533 (0.2735) Prec@1 56.000 (48.286) Prec@5 93.000 (93.000) +2022-11-14 13:14:09,773 Epoch: [2][70/500] Time 0.017 (0.015) Data 0.001 (0.004) Loss 0.2580 (0.2716) Prec@1 54.000 (49.000) Prec@5 87.000 (92.250) +2022-11-14 13:14:09,983 Epoch: [2][80/500] Time 0.019 (0.015) Data 0.001 (0.004) Loss 0.2936 (0.2740) Prec@1 41.000 (48.111) Prec@5 85.000 (91.444) +2022-11-14 13:14:10,154 Epoch: [2][90/500] Time 0.014 (0.015) Data 0.002 (0.003) Loss 0.2616 (0.2728) Prec@1 45.000 (47.800) Prec@5 91.000 (91.400) +2022-11-14 13:14:10,320 Epoch: [2][100/500] Time 0.014 (0.015) Data 0.001 (0.003) Loss 0.2641 (0.2720) Prec@1 46.000 (47.636) Prec@5 94.000 (91.636) +2022-11-14 13:14:10,489 Epoch: [2][110/500] Time 0.014 (0.015) Data 0.001 (0.003) Loss 0.2789 (0.2726) Prec@1 47.000 (47.583) Prec@5 89.000 (91.417) +2022-11-14 13:14:10,656 Epoch: [2][120/500] Time 0.014 (0.015) Data 0.001 (0.003) Loss 0.2545 (0.2712) Prec@1 48.000 (47.615) Prec@5 92.000 (91.462) +2022-11-14 13:14:10,824 Epoch: [2][130/500] Time 0.016 (0.015) Data 0.001 (0.003) Loss 0.2565 (0.2701) Prec@1 48.000 (47.643) Prec@5 93.000 (91.571) +2022-11-14 13:14:11,011 Epoch: [2][140/500] Time 0.012 (0.015) Data 0.001 (0.003) Loss 0.2360 (0.2678) Prec@1 57.000 (48.267) Prec@5 95.000 (91.800) +2022-11-14 13:14:11,175 Epoch: [2][150/500] Time 0.014 (0.015) Data 0.001 (0.003) Loss 0.2982 (0.2697) Prec@1 40.000 (47.750) Prec@5 88.000 (91.562) +2022-11-14 13:14:11,379 Epoch: [2][160/500] Time 0.018 (0.015) Data 0.001 (0.002) Loss 0.2736 (0.2700) Prec@1 45.000 (47.588) Prec@5 90.000 (91.471) +2022-11-14 13:14:11,569 Epoch: [2][170/500] Time 0.014 (0.015) Data 0.002 (0.002) Loss 0.2797 (0.2705) Prec@1 43.000 (47.333) Prec@5 94.000 (91.611) +2022-11-14 13:14:11,747 Epoch: [2][180/500] Time 0.013 (0.015) Data 0.001 (0.002) Loss 0.2572 (0.2698) Prec@1 52.000 (47.579) Prec@5 93.000 (91.684) +2022-11-14 13:14:11,945 Epoch: [2][190/500] Time 0.015 (0.016) Data 0.002 (0.002) Loss 0.2457 (0.2686) Prec@1 57.000 (48.050) Prec@5 94.000 (91.800) +2022-11-14 13:14:12,142 Epoch: [2][200/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.2625 (0.2683) Prec@1 46.000 (47.952) Prec@5 91.000 (91.762) +2022-11-14 13:14:12,328 Epoch: [2][210/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2203 (0.2661) Prec@1 59.000 (48.455) Prec@5 93.000 (91.818) +2022-11-14 13:14:12,512 Epoch: [2][220/500] Time 0.017 (0.016) Data 0.001 (0.002) Loss 0.2487 (0.2654) Prec@1 51.000 (48.565) Prec@5 93.000 (91.870) +2022-11-14 13:14:12,726 Epoch: [2][230/500] Time 0.020 (0.016) Data 0.002 (0.002) Loss 0.2415 (0.2644) Prec@1 57.000 (48.917) Prec@5 93.000 (91.917) +2022-11-14 13:14:12,940 Epoch: [2][240/500] Time 0.016 (0.016) Data 0.002 (0.002) Loss 0.2821 (0.2651) Prec@1 43.000 (48.680) Prec@5 89.000 (91.800) +2022-11-14 13:14:13,122 Epoch: [2][250/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.2468 (0.2644) Prec@1 50.000 (48.731) Prec@5 94.000 (91.885) +2022-11-14 13:14:13,288 Epoch: [2][260/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2316 (0.2632) Prec@1 57.000 (49.037) Prec@5 95.000 (92.000) +2022-11-14 13:14:13,457 Epoch: [2][270/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2344 (0.2621) Prec@1 54.000 (49.214) Prec@5 92.000 (92.000) +2022-11-14 13:14:13,654 Epoch: [2][280/500] Time 0.020 (0.016) Data 0.002 (0.002) Loss 0.2394 (0.2614) Prec@1 55.000 (49.414) Prec@5 94.000 (92.069) +2022-11-14 13:14:13,843 Epoch: [2][290/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2392 (0.2606) Prec@1 57.000 (49.667) Prec@5 94.000 (92.133) +2022-11-14 13:14:14,012 Epoch: [2][300/500] Time 0.013 (0.016) Data 0.001 (0.002) Loss 0.2746 (0.2611) Prec@1 43.000 (49.452) Prec@5 92.000 (92.129) +2022-11-14 13:14:14,186 Epoch: [2][310/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2436 (0.2605) Prec@1 56.000 (49.656) Prec@5 93.000 (92.156) +2022-11-14 13:14:14,369 Epoch: [2][320/500] Time 0.019 (0.016) Data 0.002 (0.002) Loss 0.2692 (0.2608) Prec@1 46.000 (49.545) Prec@5 91.000 (92.121) +2022-11-14 13:14:14,552 Epoch: [2][330/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2591 (0.2607) Prec@1 48.000 (49.500) Prec@5 89.000 (92.029) +2022-11-14 13:14:14,718 Epoch: [2][340/500] Time 0.013 (0.016) Data 0.001 (0.002) Loss 0.2415 (0.2602) Prec@1 53.000 (49.600) Prec@5 93.000 (92.057) +2022-11-14 13:14:14,886 Epoch: [2][350/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2695 (0.2604) Prec@1 47.000 (49.528) Prec@5 93.000 (92.083) +2022-11-14 13:14:15,051 Epoch: [2][360/500] Time 0.013 (0.016) Data 0.001 (0.002) Loss 0.2545 (0.2603) Prec@1 45.000 (49.405) Prec@5 93.000 (92.108) +2022-11-14 13:14:15,215 Epoch: [2][370/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2606 (0.2603) Prec@1 49.000 (49.395) Prec@5 91.000 (92.079) +2022-11-14 13:14:15,384 Epoch: [2][380/500] Time 0.017 (0.016) Data 0.001 (0.002) Loss 0.2423 (0.2598) Prec@1 50.000 (49.410) Prec@5 92.000 (92.077) +2022-11-14 13:14:15,556 Epoch: [2][390/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.2420 (0.2594) Prec@1 56.000 (49.575) Prec@5 95.000 (92.150) +2022-11-14 13:14:15,721 Epoch: [2][400/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2329 (0.2587) Prec@1 61.000 (49.854) Prec@5 92.000 (92.146) +2022-11-14 13:14:15,883 Epoch: [2][410/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2565 (0.2587) Prec@1 50.000 (49.857) Prec@5 93.000 (92.167) +2022-11-14 13:14:16,048 Epoch: [2][420/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2426 (0.2583) Prec@1 55.000 (49.977) Prec@5 95.000 (92.233) +2022-11-14 13:14:16,211 Epoch: [2][430/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2441 (0.2580) Prec@1 52.000 (50.023) Prec@5 93.000 (92.250) +2022-11-14 13:14:16,376 Epoch: [2][440/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2524 (0.2579) Prec@1 53.000 (50.089) Prec@5 88.000 (92.156) +2022-11-14 13:14:16,539 Epoch: [2][450/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2439 (0.2576) Prec@1 51.000 (50.109) Prec@5 87.000 (92.043) +2022-11-14 13:14:16,703 Epoch: [2][460/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2396 (0.2572) Prec@1 45.000 (50.000) Prec@5 94.000 (92.085) +2022-11-14 13:14:16,867 Epoch: [2][470/500] Time 0.014 (0.016) Data 0.001 (0.002) Loss 0.2213 (0.2564) Prec@1 54.000 (50.083) Prec@5 94.000 (92.125) +2022-11-14 13:14:17,031 Epoch: [2][480/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2577 (0.2565) Prec@1 52.000 (50.122) Prec@5 89.000 (92.061) +2022-11-14 13:14:17,199 Epoch: [2][490/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2132 (0.2556) Prec@1 59.000 (50.300) Prec@5 96.000 (92.140) +2022-11-14 13:14:17,383 Epoch: [2][499/500] Time 0.018 (0.016) Data 0.002 (0.002) Loss 0.2513 (0.2555) Prec@1 50.000 (50.294) Prec@5 89.000 (92.078) +2022-11-14 13:14:17,646 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.2262 (0.2262) Prec@1 52.000 (52.000) Prec@5 95.000 (95.000) +2022-11-14 13:14:17,656 Test: [1/100] Model Time 0.007 (0.012) Loss Time 0.000 (0.000) Loss 0.2641 (0.2451) Prec@1 45.000 (48.500) Prec@5 96.000 (95.500) +2022-11-14 13:14:17,665 Test: [2/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.2393 (0.2432) Prec@1 51.000 (49.333) Prec@5 94.000 (95.000) +2022-11-14 13:14:17,676 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2559 (0.2464) Prec@1 48.000 (49.000) Prec@5 92.000 (94.250) +2022-11-14 13:14:17,683 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.2362 (0.2443) Prec@1 55.000 (50.200) Prec@5 96.000 (94.600) +2022-11-14 13:14:17,689 Test: [5/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.2249 (0.2411) Prec@1 57.000 (51.333) Prec@5 92.000 (94.167) +2022-11-14 13:14:17,697 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2298 (0.2395) Prec@1 59.000 (52.429) Prec@5 94.000 (94.143) +2022-11-14 13:14:17,706 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2555 (0.2415) Prec@1 50.000 (52.125) Prec@5 92.000 (93.875) +2022-11-14 13:14:17,713 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2432 (0.2417) Prec@1 54.000 (52.333) Prec@5 92.000 (93.667) +2022-11-14 13:14:17,720 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.2014 (0.2376) Prec@1 63.000 (53.400) Prec@5 92.000 (93.500) +2022-11-14 13:14:17,729 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2354 (0.2374) Prec@1 53.000 (53.364) Prec@5 93.000 (93.455) +2022-11-14 13:14:17,737 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2326 (0.2370) Prec@1 60.000 (53.917) Prec@5 94.000 (93.500) +2022-11-14 13:14:17,744 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2705 (0.2396) Prec@1 44.000 (53.154) Prec@5 91.000 (93.308) +2022-11-14 13:14:17,752 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.2611 (0.2411) Prec@1 48.000 (52.786) Prec@5 92.000 (93.214) +2022-11-14 13:14:17,760 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2040 (0.2387) Prec@1 62.000 (53.400) Prec@5 91.000 (93.067) +2022-11-14 13:14:17,768 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2623 (0.2401) Prec@1 51.000 (53.250) Prec@5 90.000 (92.875) +2022-11-14 13:14:17,776 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2380 (0.2400) Prec@1 58.000 (53.529) Prec@5 88.000 (92.588) +2022-11-14 13:14:17,784 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2336 (0.2397) Prec@1 57.000 (53.722) Prec@5 92.000 (92.556) +2022-11-14 13:14:17,791 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2146 (0.2383) Prec@1 60.000 (54.053) Prec@5 94.000 (92.632) +2022-11-14 13:14:17,799 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2613 (0.2395) Prec@1 50.000 (53.850) Prec@5 88.000 (92.400) +2022-11-14 13:14:17,806 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2352 (0.2393) Prec@1 52.000 (53.762) Prec@5 93.000 (92.429) +2022-11-14 13:14:17,814 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2487 (0.2397) Prec@1 52.000 (53.682) Prec@5 89.000 (92.273) +2022-11-14 13:14:17,821 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2474 (0.2400) Prec@1 51.000 (53.565) Prec@5 94.000 (92.348) +2022-11-14 13:14:17,829 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2438 (0.2402) Prec@1 51.000 (53.458) Prec@5 92.000 (92.333) +2022-11-14 13:14:17,837 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2478 (0.2405) Prec@1 53.000 (53.440) Prec@5 90.000 (92.240) +2022-11-14 13:14:17,844 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2487 (0.2408) Prec@1 50.000 (53.308) Prec@5 91.000 (92.192) +2022-11-14 13:14:17,852 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2269 (0.2403) Prec@1 59.000 (53.519) Prec@5 95.000 (92.296) +2022-11-14 13:14:17,860 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2413 (0.2403) Prec@1 47.000 (53.286) Prec@5 93.000 (92.321) +2022-11-14 13:14:17,867 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2513 (0.2407) Prec@1 52.000 (53.241) Prec@5 92.000 (92.310) +2022-11-14 13:14:17,874 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2298 (0.2404) Prec@1 54.000 (53.267) Prec@5 95.000 (92.400) +2022-11-14 13:14:17,881 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2274 (0.2399) Prec@1 59.000 (53.452) Prec@5 95.000 (92.484) +2022-11-14 13:14:17,890 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2278 (0.2396) Prec@1 56.000 (53.531) Prec@5 93.000 (92.500) +2022-11-14 13:14:17,897 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2314 (0.2393) Prec@1 54.000 (53.545) Prec@5 92.000 (92.485) +2022-11-14 13:14:17,904 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2473 (0.2395) Prec@1 50.000 (53.441) Prec@5 91.000 (92.441) +2022-11-14 13:14:17,910 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2308 (0.2393) Prec@1 61.000 (53.657) Prec@5 87.000 (92.286) +2022-11-14 13:14:17,917 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2254 (0.2389) Prec@1 51.000 (53.583) Prec@5 94.000 (92.333) +2022-11-14 13:14:17,925 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2557 (0.2394) Prec@1 45.000 (53.351) Prec@5 89.000 (92.243) +2022-11-14 13:14:17,932 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2370 (0.2393) Prec@1 56.000 (53.421) Prec@5 92.000 (92.237) +2022-11-14 13:14:17,940 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2180 (0.2388) Prec@1 61.000 (53.615) Prec@5 96.000 (92.333) +2022-11-14 13:14:17,947 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2423 (0.2388) Prec@1 54.000 (53.625) Prec@5 93.000 (92.350) +2022-11-14 13:14:17,955 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2338 (0.2387) Prec@1 59.000 (53.756) Prec@5 92.000 (92.341) +2022-11-14 13:14:17,963 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2234 (0.2384) Prec@1 61.000 (53.929) Prec@5 92.000 (92.333) +2022-11-14 13:14:17,972 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2228 (0.2380) Prec@1 57.000 (54.000) Prec@5 94.000 (92.372) +2022-11-14 13:14:17,980 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2342 (0.2379) Prec@1 59.000 (54.114) Prec@5 92.000 (92.364) +2022-11-14 13:14:17,989 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2322 (0.2378) Prec@1 55.000 (54.133) Prec@5 93.000 (92.378) +2022-11-14 13:14:17,998 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2522 (0.2381) Prec@1 50.000 (54.043) Prec@5 94.000 (92.413) +2022-11-14 13:14:18,007 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2351 (0.2380) Prec@1 53.000 (54.021) Prec@5 95.000 (92.468) +2022-11-14 13:14:18,015 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2437 (0.2382) Prec@1 55.000 (54.042) Prec@5 91.000 (92.438) +2022-11-14 13:14:18,025 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2133 (0.2376) Prec@1 54.000 (54.041) Prec@5 94.000 (92.469) +2022-11-14 13:14:18,034 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2341 (0.2376) Prec@1 55.000 (54.060) Prec@5 89.000 (92.400) +2022-11-14 13:14:18,043 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2296 (0.2374) Prec@1 58.000 (54.137) Prec@5 90.000 (92.353) +2022-11-14 13:14:18,052 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2497 (0.2377) Prec@1 52.000 (54.096) Prec@5 91.000 (92.327) +2022-11-14 13:14:18,062 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2507 (0.2379) Prec@1 48.000 (53.981) Prec@5 92.000 (92.321) +2022-11-14 13:14:18,072 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2548 (0.2382) Prec@1 52.000 (53.944) Prec@5 90.000 (92.278) +2022-11-14 13:14:18,081 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2466 (0.2384) Prec@1 51.000 (53.891) Prec@5 93.000 (92.291) +2022-11-14 13:14:18,090 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2562 (0.2387) Prec@1 58.000 (53.964) Prec@5 89.000 (92.232) +2022-11-14 13:14:18,099 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2531 (0.2389) Prec@1 58.000 (54.035) Prec@5 92.000 (92.228) +2022-11-14 13:14:18,108 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2110 (0.2385) Prec@1 66.000 (54.241) Prec@5 94.000 (92.259) +2022-11-14 13:14:18,117 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2662 (0.2389) Prec@1 48.000 (54.136) Prec@5 88.000 (92.186) +2022-11-14 13:14:18,126 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2346 (0.2389) Prec@1 51.000 (54.083) Prec@5 92.000 (92.183) +2022-11-14 13:14:18,136 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2377 (0.2388) Prec@1 57.000 (54.131) Prec@5 94.000 (92.213) +2022-11-14 13:14:18,145 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2403 (0.2389) Prec@1 52.000 (54.097) Prec@5 89.000 (92.161) +2022-11-14 13:14:18,154 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2692 (0.2393) Prec@1 45.000 (53.952) Prec@5 89.000 (92.111) +2022-11-14 13:14:18,163 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2089 (0.2389) Prec@1 59.000 (54.031) Prec@5 97.000 (92.188) +2022-11-14 13:14:18,173 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2116 (0.2384) Prec@1 59.000 (54.108) Prec@5 97.000 (92.262) +2022-11-14 13:14:18,182 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2506 (0.2386) Prec@1 55.000 (54.121) Prec@5 89.000 (92.212) +2022-11-14 13:14:18,191 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2539 (0.2389) Prec@1 51.000 (54.075) Prec@5 94.000 (92.239) +2022-11-14 13:14:18,198 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2504 (0.2390) Prec@1 47.000 (53.971) Prec@5 93.000 (92.250) +2022-11-14 13:14:18,205 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2624 (0.2394) Prec@1 47.000 (53.870) Prec@5 91.000 (92.232) +2022-11-14 13:14:18,213 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2974 (0.2402) Prec@1 41.000 (53.686) Prec@5 88.000 (92.171) +2022-11-14 13:14:18,221 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2465 (0.2403) Prec@1 55.000 (53.704) Prec@5 95.000 (92.211) +2022-11-14 13:14:18,230 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2316 (0.2402) Prec@1 56.000 (53.736) Prec@5 89.000 (92.167) +2022-11-14 13:14:18,239 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2101 (0.2397) Prec@1 63.000 (53.863) Prec@5 94.000 (92.192) +2022-11-14 13:14:18,250 Test: [73/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2271 (0.2396) Prec@1 54.000 (53.865) Prec@5 97.000 (92.257) +2022-11-14 13:14:18,260 Test: [74/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2470 (0.2397) Prec@1 54.000 (53.867) Prec@5 94.000 (92.280) +2022-11-14 13:14:18,270 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2169 (0.2394) Prec@1 60.000 (53.947) Prec@5 92.000 (92.276) +2022-11-14 13:14:18,278 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2268 (0.2392) Prec@1 58.000 (54.000) Prec@5 94.000 (92.299) +2022-11-14 13:14:18,288 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2414 (0.2392) Prec@1 53.000 (53.987) Prec@5 90.000 (92.269) +2022-11-14 13:14:18,299 Test: [78/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2447 (0.2393) Prec@1 55.000 (54.000) Prec@5 91.000 (92.253) +2022-11-14 13:14:18,310 Test: [79/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2313 (0.2392) Prec@1 53.000 (53.987) Prec@5 92.000 (92.250) +2022-11-14 13:14:18,322 Test: [80/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2167 (0.2389) Prec@1 63.000 (54.099) Prec@5 94.000 (92.272) +2022-11-14 13:14:18,332 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2438 (0.2390) Prec@1 56.000 (54.122) Prec@5 91.000 (92.256) +2022-11-14 13:14:18,343 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2517 (0.2391) Prec@1 55.000 (54.133) Prec@5 96.000 (92.301) +2022-11-14 13:14:18,352 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2494 (0.2393) Prec@1 50.000 (54.083) Prec@5 92.000 (92.298) +2022-11-14 13:14:18,364 Test: [84/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2446 (0.2393) Prec@1 50.000 (54.035) Prec@5 94.000 (92.318) +2022-11-14 13:14:18,373 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2405 (0.2393) Prec@1 50.000 (53.988) Prec@5 91.000 (92.302) +2022-11-14 13:14:18,381 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2500 (0.2395) Prec@1 50.000 (53.943) Prec@5 92.000 (92.299) +2022-11-14 13:14:18,388 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2365 (0.2394) Prec@1 56.000 (53.966) Prec@5 92.000 (92.295) +2022-11-14 13:14:18,398 Test: [88/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2393 (0.2394) Prec@1 54.000 (53.966) Prec@5 91.000 (92.281) +2022-11-14 13:14:18,407 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2245 (0.2393) Prec@1 58.000 (54.011) Prec@5 94.000 (92.300) +2022-11-14 13:14:18,415 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2295 (0.2392) Prec@1 55.000 (54.022) Prec@5 95.000 (92.330) +2022-11-14 13:14:18,422 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2046 (0.2388) Prec@1 64.000 (54.130) Prec@5 96.000 (92.370) +2022-11-14 13:14:18,429 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2242 (0.2386) Prec@1 59.000 (54.183) Prec@5 87.000 (92.312) +2022-11-14 13:14:18,436 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2565 (0.2388) Prec@1 49.000 (54.128) Prec@5 90.000 (92.287) +2022-11-14 13:14:18,443 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2420 (0.2388) Prec@1 50.000 (54.084) Prec@5 90.000 (92.263) +2022-11-14 13:14:18,450 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2311 (0.2388) Prec@1 57.000 (54.115) Prec@5 90.000 (92.240) +2022-11-14 13:14:18,457 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2465 (0.2388) Prec@1 53.000 (54.103) Prec@5 90.000 (92.216) +2022-11-14 13:14:18,463 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2677 (0.2391) Prec@1 51.000 (54.071) Prec@5 90.000 (92.194) +2022-11-14 13:14:18,470 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2394 (0.2391) Prec@1 52.000 (54.051) Prec@5 94.000 (92.212) +2022-11-14 13:14:18,477 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2357 (0.2391) Prec@1 54.000 (54.050) Prec@5 92.000 (92.210) +2022-11-14 13:14:18,529 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:14:18,801 Epoch: [3][0/500] Time 0.028 (0.028) Data 0.194 (0.194) Loss 0.2405 (0.2405) Prec@1 52.000 (52.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:18,987 Epoch: [3][10/500] Time 0.018 (0.017) Data 0.001 (0.019) Loss 0.2563 (0.2484) Prec@1 50.000 (51.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:19,210 Epoch: [3][20/500] Time 0.024 (0.018) Data 0.002 (0.011) Loss 0.2259 (0.2409) Prec@1 57.000 (53.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:19,405 Epoch: [3][30/500] Time 0.014 (0.018) Data 0.001 (0.008) Loss 0.2234 (0.2365) Prec@1 60.000 (54.750) Prec@5 90.000 (92.250) +2022-11-14 13:14:19,578 Epoch: [3][40/500] Time 0.018 (0.018) Data 0.001 (0.006) Loss 0.2337 (0.2360) Prec@1 50.000 (53.800) Prec@5 93.000 (92.400) +2022-11-14 13:14:19,758 Epoch: [3][50/500] Time 0.020 (0.017) Data 0.001 (0.005) Loss 0.2459 (0.2376) Prec@1 52.000 (53.500) Prec@5 93.000 (92.500) +2022-11-14 13:14:19,963 Epoch: [3][60/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.2484 (0.2392) Prec@1 51.000 (53.143) Prec@5 94.000 (92.714) +2022-11-14 13:14:20,129 Epoch: [3][70/500] Time 0.015 (0.017) Data 0.001 (0.004) Loss 0.2539 (0.2410) Prec@1 48.000 (52.500) Prec@5 95.000 (93.000) +2022-11-14 13:14:20,301 Epoch: [3][80/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.2514 (0.2422) Prec@1 54.000 (52.667) Prec@5 90.000 (92.667) +2022-11-14 13:14:20,478 Epoch: [3][90/500] Time 0.015 (0.017) Data 0.001 (0.004) Loss 0.2420 (0.2421) Prec@1 53.000 (52.700) Prec@5 93.000 (92.700) +2022-11-14 13:14:20,687 Epoch: [3][100/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.2108 (0.2393) Prec@1 66.000 (53.909) Prec@5 96.000 (93.000) +2022-11-14 13:14:20,866 Epoch: [3][110/500] Time 0.014 (0.017) Data 0.001 (0.003) Loss 0.2226 (0.2379) Prec@1 59.000 (54.333) Prec@5 94.000 (93.083) +2022-11-14 13:14:21,041 Epoch: [3][120/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.2595 (0.2396) Prec@1 48.000 (53.846) Prec@5 94.000 (93.154) +2022-11-14 13:14:21,210 Epoch: [3][130/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.2482 (0.2402) Prec@1 52.000 (53.714) Prec@5 92.000 (93.071) +2022-11-14 13:14:21,391 Epoch: [3][140/500] Time 0.018 (0.016) Data 0.002 (0.003) Loss 0.2226 (0.2390) Prec@1 57.000 (53.933) Prec@5 95.000 (93.200) +2022-11-14 13:14:21,596 Epoch: [3][150/500] Time 0.013 (0.017) Data 0.002 (0.003) Loss 0.2233 (0.2380) Prec@1 57.000 (54.125) Prec@5 93.000 (93.188) +2022-11-14 13:14:21,765 Epoch: [3][160/500] Time 0.016 (0.016) Data 0.001 (0.003) Loss 0.1999 (0.2358) Prec@1 62.000 (54.588) Prec@5 97.000 (93.412) +2022-11-14 13:14:21,947 Epoch: [3][170/500] Time 0.020 (0.016) Data 0.002 (0.003) Loss 0.2346 (0.2357) Prec@1 58.000 (54.778) Prec@5 90.000 (93.222) +2022-11-14 13:14:22,158 Epoch: [3][180/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.2536 (0.2367) Prec@1 49.000 (54.474) Prec@5 96.000 (93.368) +2022-11-14 13:14:22,350 Epoch: [3][190/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.2528 (0.2375) Prec@1 47.000 (54.100) Prec@5 90.000 (93.200) +2022-11-14 13:14:22,561 Epoch: [3][200/500] Time 0.020 (0.017) Data 0.001 (0.002) Loss 0.2300 (0.2371) Prec@1 60.000 (54.381) Prec@5 94.000 (93.238) +2022-11-14 13:14:22,739 Epoch: [3][210/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2164 (0.2362) Prec@1 59.000 (54.591) Prec@5 93.000 (93.227) +2022-11-14 13:14:22,928 Epoch: [3][220/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.2384 (0.2363) Prec@1 51.000 (54.435) Prec@5 94.000 (93.261) +2022-11-14 13:14:23,122 Epoch: [3][230/500] Time 0.018 (0.017) Data 0.002 (0.002) Loss 0.2097 (0.2352) Prec@1 62.000 (54.750) Prec@5 94.000 (93.292) +2022-11-14 13:14:23,314 Epoch: [3][240/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.2289 (0.2349) Prec@1 52.000 (54.640) Prec@5 95.000 (93.360) +2022-11-14 13:14:23,505 Epoch: [3][250/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.2433 (0.2352) Prec@1 58.000 (54.769) Prec@5 84.000 (93.000) +2022-11-14 13:14:23,683 Epoch: [3][260/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2072 (0.2342) Prec@1 59.000 (54.926) Prec@5 96.000 (93.111) +2022-11-14 13:14:23,878 Epoch: [3][270/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.2359 (0.2342) Prec@1 54.000 (54.893) Prec@5 94.000 (93.143) +2022-11-14 13:14:24,069 Epoch: [3][280/500] Time 0.020 (0.017) Data 0.002 (0.002) Loss 0.1993 (0.2330) Prec@1 59.000 (55.034) Prec@5 93.000 (93.138) +2022-11-14 13:14:24,300 Epoch: [3][290/500] Time 0.019 (0.017) Data 0.002 (0.002) Loss 0.2192 (0.2326) Prec@1 59.000 (55.167) Prec@5 94.000 (93.167) +2022-11-14 13:14:24,480 Epoch: [3][300/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.2252 (0.2323) Prec@1 53.000 (55.097) Prec@5 93.000 (93.161) +2022-11-14 13:14:24,668 Epoch: [3][310/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.1980 (0.2313) Prec@1 65.000 (55.406) Prec@5 97.000 (93.281) +2022-11-14 13:14:24,865 Epoch: [3][320/500] Time 0.020 (0.017) Data 0.002 (0.002) Loss 0.2148 (0.2308) Prec@1 56.000 (55.424) Prec@5 97.000 (93.394) +2022-11-14 13:14:25,075 Epoch: [3][330/500] Time 0.024 (0.017) Data 0.002 (0.002) Loss 0.2372 (0.2310) Prec@1 51.000 (55.294) Prec@5 91.000 (93.324) +2022-11-14 13:14:25,312 Epoch: [3][340/500] Time 0.025 (0.017) Data 0.002 (0.002) Loss 0.2187 (0.2306) Prec@1 61.000 (55.457) Prec@5 91.000 (93.257) +2022-11-14 13:14:25,561 Epoch: [3][350/500] Time 0.021 (0.017) Data 0.002 (0.002) Loss 0.2343 (0.2307) Prec@1 59.000 (55.556) Prec@5 93.000 (93.250) +2022-11-14 13:14:25,748 Epoch: [3][360/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.2164 (0.2303) Prec@1 58.000 (55.622) Prec@5 96.000 (93.324) +2022-11-14 13:14:25,941 Epoch: [3][370/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.2293 (0.2303) Prec@1 59.000 (55.711) Prec@5 93.000 (93.316) +2022-11-14 13:14:26,114 Epoch: [3][380/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2329 (0.2304) Prec@1 52.000 (55.615) Prec@5 97.000 (93.410) +2022-11-14 13:14:26,282 Epoch: [3][390/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.2321 (0.2304) Prec@1 57.000 (55.650) Prec@5 96.000 (93.475) +2022-11-14 13:14:26,453 Epoch: [3][400/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2018 (0.2297) Prec@1 65.000 (55.878) Prec@5 94.000 (93.488) +2022-11-14 13:14:26,621 Epoch: [3][410/500] Time 0.014 (0.017) Data 0.001 (0.002) Loss 0.2008 (0.2290) Prec@1 60.000 (55.976) Prec@5 94.000 (93.500) +2022-11-14 13:14:26,790 Epoch: [3][420/500] Time 0.014 (0.017) Data 0.002 (0.002) Loss 0.2220 (0.2289) Prec@1 60.000 (56.070) Prec@5 88.000 (93.372) +2022-11-14 13:14:26,959 Epoch: [3][430/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2139 (0.2285) Prec@1 63.000 (56.227) Prec@5 95.000 (93.409) +2022-11-14 13:14:27,127 Epoch: [3][440/500] Time 0.014 (0.017) Data 0.002 (0.002) Loss 0.2282 (0.2285) Prec@1 55.000 (56.200) Prec@5 92.000 (93.378) +2022-11-14 13:14:27,294 Epoch: [3][450/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2044 (0.2280) Prec@1 62.000 (56.326) Prec@5 93.000 (93.370) +2022-11-14 13:14:27,465 Epoch: [3][460/500] Time 0.014 (0.017) Data 0.001 (0.002) Loss 0.2198 (0.2278) Prec@1 56.000 (56.319) Prec@5 93.000 (93.362) +2022-11-14 13:14:27,648 Epoch: [3][470/500] Time 0.014 (0.017) Data 0.002 (0.002) Loss 0.2055 (0.2274) Prec@1 55.000 (56.292) Prec@5 96.000 (93.417) +2022-11-14 13:14:27,832 Epoch: [3][480/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2269 (0.2273) Prec@1 55.000 (56.265) Prec@5 99.000 (93.531) +2022-11-14 13:14:28,005 Epoch: [3][490/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2384 (0.2276) Prec@1 49.000 (56.120) Prec@5 93.000 (93.520) +2022-11-14 13:14:28,155 Epoch: [3][499/500] Time 0.014 (0.017) Data 0.001 (0.002) Loss 0.2109 (0.2272) Prec@1 60.000 (56.196) Prec@5 91.000 (93.471) +2022-11-14 13:14:28,401 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.2610 (0.2610) Prec@1 48.000 (48.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:28,408 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2861 (0.2735) Prec@1 46.000 (47.000) Prec@5 95.000 (94.000) +2022-11-14 13:14:28,416 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2383 (0.2618) Prec@1 55.000 (49.667) Prec@5 95.000 (94.333) +2022-11-14 13:14:28,425 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2845 (0.2675) Prec@1 43.000 (48.000) Prec@5 96.000 (94.750) +2022-11-14 13:14:28,432 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2614 (0.2663) Prec@1 49.000 (48.200) Prec@5 94.000 (94.600) +2022-11-14 13:14:28,438 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.2508 (0.2637) Prec@1 52.000 (48.833) Prec@5 95.000 (94.667) +2022-11-14 13:14:28,445 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2835 (0.2665) Prec@1 45.000 (48.286) Prec@5 89.000 (93.857) +2022-11-14 13:14:28,453 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2735 (0.2674) Prec@1 48.000 (48.250) Prec@5 89.000 (93.250) +2022-11-14 13:14:28,461 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2411 (0.2645) Prec@1 51.000 (48.556) Prec@5 93.000 (93.222) +2022-11-14 13:14:28,468 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2359 (0.2616) Prec@1 55.000 (49.200) Prec@5 94.000 (93.300) +2022-11-14 13:14:28,476 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2730 (0.2626) Prec@1 45.000 (48.818) Prec@5 87.000 (92.727) +2022-11-14 13:14:28,483 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2653 (0.2629) Prec@1 49.000 (48.833) Prec@5 93.000 (92.750) +2022-11-14 13:14:28,490 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2370 (0.2609) Prec@1 54.000 (49.231) Prec@5 91.000 (92.615) +2022-11-14 13:14:28,497 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2575 (0.2606) Prec@1 48.000 (49.143) Prec@5 94.000 (92.714) +2022-11-14 13:14:28,504 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1938 (0.2562) Prec@1 65.000 (50.200) Prec@5 94.000 (92.800) +2022-11-14 13:14:28,512 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2821 (0.2578) Prec@1 43.000 (49.750) Prec@5 89.000 (92.562) +2022-11-14 13:14:28,519 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2526 (0.2575) Prec@1 51.000 (49.824) Prec@5 90.000 (92.412) +2022-11-14 13:14:28,526 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2620 (0.2577) Prec@1 48.000 (49.722) Prec@5 92.000 (92.389) +2022-11-14 13:14:28,534 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2226 (0.2559) Prec@1 58.000 (50.158) Prec@5 88.000 (92.158) +2022-11-14 13:14:28,541 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2869 (0.2574) Prec@1 43.000 (49.800) Prec@5 92.000 (92.150) +2022-11-14 13:14:28,548 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2817 (0.2586) Prec@1 45.000 (49.571) Prec@5 92.000 (92.143) +2022-11-14 13:14:28,555 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2458 (0.2580) Prec@1 50.000 (49.591) Prec@5 94.000 (92.227) +2022-11-14 13:14:28,562 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2639 (0.2583) Prec@1 49.000 (49.565) Prec@5 88.000 (92.043) +2022-11-14 13:14:28,569 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2831 (0.2593) Prec@1 42.000 (49.250) Prec@5 89.000 (91.917) +2022-11-14 13:14:28,577 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2401 (0.2585) Prec@1 55.000 (49.480) Prec@5 88.000 (91.760) +2022-11-14 13:14:28,584 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2487 (0.2582) Prec@1 55.000 (49.692) Prec@5 92.000 (91.769) +2022-11-14 13:14:28,591 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2581 (0.2582) Prec@1 46.000 (49.556) Prec@5 90.000 (91.704) +2022-11-14 13:14:28,598 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2735 (0.2587) Prec@1 46.000 (49.429) Prec@5 89.000 (91.607) +2022-11-14 13:14:28,606 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2682 (0.2590) Prec@1 52.000 (49.517) Prec@5 91.000 (91.586) +2022-11-14 13:14:28,613 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2430 (0.2585) Prec@1 51.000 (49.567) Prec@5 94.000 (91.667) +2022-11-14 13:14:28,621 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2385 (0.2579) Prec@1 54.000 (49.710) Prec@5 95.000 (91.774) +2022-11-14 13:14:28,629 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2519 (0.2577) Prec@1 50.000 (49.719) Prec@5 92.000 (91.781) +2022-11-14 13:14:28,637 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2515 (0.2575) Prec@1 52.000 (49.788) Prec@5 93.000 (91.818) +2022-11-14 13:14:28,645 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2677 (0.2578) Prec@1 50.000 (49.794) Prec@5 90.000 (91.765) +2022-11-14 13:14:28,652 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2473 (0.2575) Prec@1 53.000 (49.886) Prec@5 89.000 (91.686) +2022-11-14 13:14:28,660 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2339 (0.2568) Prec@1 53.000 (49.972) Prec@5 94.000 (91.750) +2022-11-14 13:14:28,667 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2729 (0.2573) Prec@1 45.000 (49.838) Prec@5 91.000 (91.730) +2022-11-14 13:14:28,675 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2635 (0.2574) Prec@1 51.000 (49.868) Prec@5 86.000 (91.579) +2022-11-14 13:14:28,683 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2243 (0.2566) Prec@1 57.000 (50.051) Prec@5 93.000 (91.615) +2022-11-14 13:14:28,691 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2386 (0.2561) Prec@1 52.000 (50.100) Prec@5 93.000 (91.650) +2022-11-14 13:14:28,699 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2249 (0.2554) Prec@1 60.000 (50.341) Prec@5 95.000 (91.732) +2022-11-14 13:14:28,707 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2564 (0.2554) Prec@1 50.000 (50.333) Prec@5 86.000 (91.595) +2022-11-14 13:14:28,715 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2440 (0.2551) Prec@1 57.000 (50.488) Prec@5 94.000 (91.651) +2022-11-14 13:14:28,723 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2422 (0.2548) Prec@1 53.000 (50.545) Prec@5 90.000 (91.614) +2022-11-14 13:14:28,730 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2636 (0.2550) Prec@1 48.000 (50.489) Prec@5 92.000 (91.622) +2022-11-14 13:14:28,737 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2579 (0.2551) Prec@1 51.000 (50.500) Prec@5 96.000 (91.717) +2022-11-14 13:14:28,744 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2517 (0.2550) Prec@1 52.000 (50.532) Prec@5 95.000 (91.787) +2022-11-14 13:14:28,752 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2677 (0.2553) Prec@1 44.000 (50.396) Prec@5 89.000 (91.729) +2022-11-14 13:14:28,759 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2394 (0.2550) Prec@1 56.000 (50.510) Prec@5 98.000 (91.857) +2022-11-14 13:14:28,770 Test: [49/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2638 (0.2551) Prec@1 51.000 (50.520) Prec@5 91.000 (91.840) +2022-11-14 13:14:28,780 Test: [50/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2515 (0.2551) Prec@1 52.000 (50.549) Prec@5 92.000 (91.843) +2022-11-14 13:14:28,790 Test: [51/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2766 (0.2555) Prec@1 43.000 (50.404) Prec@5 88.000 (91.769) +2022-11-14 13:14:28,797 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2317 (0.2550) Prec@1 58.000 (50.547) Prec@5 97.000 (91.868) +2022-11-14 13:14:28,805 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2446 (0.2548) Prec@1 49.000 (50.519) Prec@5 94.000 (91.907) +2022-11-14 13:14:28,813 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2737 (0.2552) Prec@1 49.000 (50.491) Prec@5 92.000 (91.909) +2022-11-14 13:14:28,820 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2965 (0.2559) Prec@1 43.000 (50.357) Prec@5 86.000 (91.804) +2022-11-14 13:14:28,827 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2605 (0.2560) Prec@1 46.000 (50.281) Prec@5 92.000 (91.807) +2022-11-14 13:14:28,834 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2460 (0.2558) Prec@1 56.000 (50.379) Prec@5 92.000 (91.810) +2022-11-14 13:14:28,841 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.3063 (0.2567) Prec@1 40.000 (50.203) Prec@5 94.000 (91.847) +2022-11-14 13:14:28,850 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2376 (0.2564) Prec@1 57.000 (50.317) Prec@5 92.000 (91.850) +2022-11-14 13:14:28,858 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2571 (0.2564) Prec@1 49.000 (50.295) Prec@5 92.000 (91.852) +2022-11-14 13:14:28,865 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2483 (0.2562) Prec@1 52.000 (50.323) Prec@5 91.000 (91.839) +2022-11-14 13:14:28,873 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2673 (0.2564) Prec@1 47.000 (50.270) Prec@5 93.000 (91.857) +2022-11-14 13:14:28,880 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2462 (0.2563) Prec@1 50.000 (50.266) Prec@5 92.000 (91.859) +2022-11-14 13:14:28,887 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2642 (0.2564) Prec@1 47.000 (50.215) Prec@5 88.000 (91.800) +2022-11-14 13:14:28,895 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.3021 (0.2571) Prec@1 39.000 (50.045) Prec@5 87.000 (91.727) +2022-11-14 13:14:28,903 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2850 (0.2575) Prec@1 46.000 (49.985) Prec@5 87.000 (91.657) +2022-11-14 13:14:28,910 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2848 (0.2579) Prec@1 43.000 (49.882) Prec@5 91.000 (91.647) +2022-11-14 13:14:28,918 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2915 (0.2584) Prec@1 42.000 (49.768) Prec@5 93.000 (91.667) +2022-11-14 13:14:28,926 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2948 (0.2589) Prec@1 48.000 (49.743) Prec@5 89.000 (91.629) +2022-11-14 13:14:28,934 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2285 (0.2585) Prec@1 56.000 (49.831) Prec@5 94.000 (91.662) +2022-11-14 13:14:28,942 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2485 (0.2583) Prec@1 56.000 (49.917) Prec@5 89.000 (91.625) +2022-11-14 13:14:28,950 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2314 (0.2580) Prec@1 60.000 (50.055) Prec@5 96.000 (91.685) +2022-11-14 13:14:28,957 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2620 (0.2580) Prec@1 45.000 (49.986) Prec@5 94.000 (91.716) +2022-11-14 13:14:28,964 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2523 (0.2579) Prec@1 54.000 (50.040) Prec@5 90.000 (91.693) +2022-11-14 13:14:28,971 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.2564 (0.2579) Prec@1 49.000 (50.026) Prec@5 90.000 (91.671) +2022-11-14 13:14:28,979 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2531 (0.2579) Prec@1 49.000 (50.013) Prec@5 92.000 (91.675) +2022-11-14 13:14:28,989 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2419 (0.2577) Prec@1 51.000 (50.026) Prec@5 91.000 (91.667) +2022-11-14 13:14:29,000 Test: [78/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2732 (0.2579) Prec@1 46.000 (49.975) Prec@5 96.000 (91.722) +2022-11-14 13:14:29,012 Test: [79/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2899 (0.2583) Prec@1 42.000 (49.875) Prec@5 89.000 (91.688) +2022-11-14 13:14:29,023 Test: [80/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2441 (0.2581) Prec@1 53.000 (49.914) Prec@5 92.000 (91.691) +2022-11-14 13:14:29,034 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2609 (0.2581) Prec@1 47.000 (49.878) Prec@5 90.000 (91.671) +2022-11-14 13:14:29,043 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2634 (0.2582) Prec@1 47.000 (49.843) Prec@5 92.000 (91.675) +2022-11-14 13:14:29,052 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2914 (0.2586) Prec@1 43.000 (49.762) Prec@5 84.000 (91.583) +2022-11-14 13:14:29,062 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2687 (0.2587) Prec@1 48.000 (49.741) Prec@5 89.000 (91.553) +2022-11-14 13:14:29,071 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2567 (0.2587) Prec@1 49.000 (49.733) Prec@5 92.000 (91.558) +2022-11-14 13:14:29,081 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2783 (0.2589) Prec@1 45.000 (49.678) Prec@5 89.000 (91.529) +2022-11-14 13:14:29,093 Test: [87/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2760 (0.2591) Prec@1 49.000 (49.670) Prec@5 87.000 (91.477) +2022-11-14 13:14:29,103 Test: [88/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2475 (0.2590) Prec@1 51.000 (49.685) Prec@5 95.000 (91.517) +2022-11-14 13:14:29,115 Test: [89/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2608 (0.2590) Prec@1 48.000 (49.667) Prec@5 92.000 (91.522) +2022-11-14 13:14:29,126 Test: [90/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2450 (0.2588) Prec@1 54.000 (49.714) Prec@5 95.000 (91.560) +2022-11-14 13:14:29,137 Test: [91/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2204 (0.2584) Prec@1 60.000 (49.826) Prec@5 94.000 (91.587) +2022-11-14 13:14:29,148 Test: [92/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2429 (0.2582) Prec@1 56.000 (49.892) Prec@5 90.000 (91.570) +2022-11-14 13:14:29,158 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2544 (0.2582) Prec@1 48.000 (49.872) Prec@5 91.000 (91.564) +2022-11-14 13:14:29,167 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2683 (0.2583) Prec@1 49.000 (49.863) Prec@5 95.000 (91.600) +2022-11-14 13:14:29,176 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2460 (0.2582) Prec@1 54.000 (49.906) Prec@5 90.000 (91.583) +2022-11-14 13:14:29,187 Test: [96/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.2686 (0.2583) Prec@1 51.000 (49.918) Prec@5 83.000 (91.495) +2022-11-14 13:14:29,198 Test: [97/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.2663 (0.2584) Prec@1 52.000 (49.939) Prec@5 88.000 (91.459) +2022-11-14 13:14:29,211 Test: [98/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.2638 (0.2584) Prec@1 46.000 (49.899) Prec@5 89.000 (91.434) +2022-11-14 13:14:29,223 Test: [99/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.2527 (0.2584) Prec@1 53.000 (49.930) Prec@5 90.000 (91.420) +2022-11-14 13:14:29,296 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:14:29,578 Epoch: [4][0/500] Time 0.025 (0.025) Data 0.214 (0.214) Loss 0.2048 (0.2048) Prec@1 66.000 (66.000) Prec@5 93.000 (93.000) +2022-11-14 13:14:29,762 Epoch: [4][10/500] Time 0.021 (0.017) Data 0.001 (0.021) Loss 0.2192 (0.2120) Prec@1 61.000 (63.500) Prec@5 96.000 (94.500) +2022-11-14 13:14:29,945 Epoch: [4][20/500] Time 0.014 (0.017) Data 0.001 (0.012) Loss 0.2143 (0.2128) Prec@1 61.000 (62.667) Prec@5 97.000 (95.333) +2022-11-14 13:14:30,129 Epoch: [4][30/500] Time 0.020 (0.017) Data 0.001 (0.008) Loss 0.1951 (0.2084) Prec@1 63.000 (62.750) Prec@5 94.000 (95.000) +2022-11-14 13:14:30,310 Epoch: [4][40/500] Time 0.015 (0.017) Data 0.001 (0.007) Loss 0.2397 (0.2146) Prec@1 59.000 (62.000) Prec@5 96.000 (95.200) +2022-11-14 13:14:30,497 Epoch: [4][50/500] Time 0.021 (0.017) Data 0.001 (0.006) Loss 0.2217 (0.2158) Prec@1 62.000 (62.000) Prec@5 95.000 (95.167) +2022-11-14 13:14:30,703 Epoch: [4][60/500] Time 0.022 (0.017) Data 0.001 (0.005) Loss 0.2608 (0.2222) Prec@1 51.000 (60.429) Prec@5 92.000 (94.714) +2022-11-14 13:14:30,927 Epoch: [4][70/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.1871 (0.2178) Prec@1 66.000 (61.125) Prec@5 95.000 (94.750) +2022-11-14 13:14:31,113 Epoch: [4][80/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.2086 (0.2168) Prec@1 57.000 (60.667) Prec@5 97.000 (95.000) +2022-11-14 13:14:31,290 Epoch: [4][90/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.2218 (0.2173) Prec@1 58.000 (60.400) Prec@5 96.000 (95.100) +2022-11-14 13:14:31,463 Epoch: [4][100/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.2151 (0.2171) Prec@1 62.000 (60.545) Prec@5 98.000 (95.364) +2022-11-14 13:14:31,639 Epoch: [4][110/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.1897 (0.2148) Prec@1 63.000 (60.750) Prec@5 93.000 (95.167) +2022-11-14 13:14:31,825 Epoch: [4][120/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.1862 (0.2126) Prec@1 66.000 (61.154) Prec@5 96.000 (95.231) +2022-11-14 13:14:32,002 Epoch: [4][130/500] Time 0.014 (0.017) Data 0.002 (0.003) Loss 0.1955 (0.2114) Prec@1 64.000 (61.357) Prec@5 100.000 (95.571) +2022-11-14 13:14:32,172 Epoch: [4][140/500] Time 0.014 (0.016) Data 0.001 (0.003) Loss 0.1825 (0.2095) Prec@1 67.000 (61.733) Prec@5 95.000 (95.533) +2022-11-14 13:14:32,394 Epoch: [4][150/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.1940 (0.2085) Prec@1 67.000 (62.062) Prec@5 97.000 (95.625) +2022-11-14 13:14:32,621 Epoch: [4][160/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.1976 (0.2079) Prec@1 67.000 (62.353) Prec@5 97.000 (95.706) +2022-11-14 13:14:32,798 Epoch: [4][170/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.2168 (0.2084) Prec@1 62.000 (62.333) Prec@5 93.000 (95.556) +2022-11-14 13:14:32,982 Epoch: [4][180/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.1801 (0.2069) Prec@1 68.000 (62.632) Prec@5 95.000 (95.526) +2022-11-14 13:14:33,159 Epoch: [4][190/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.2151 (0.2073) Prec@1 56.000 (62.300) Prec@5 96.000 (95.550) +2022-11-14 13:14:33,338 Epoch: [4][200/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.2107 (0.2074) Prec@1 63.000 (62.333) Prec@5 95.000 (95.524) +2022-11-14 13:14:33,514 Epoch: [4][210/500] Time 0.014 (0.017) Data 0.002 (0.003) Loss 0.2107 (0.2076) Prec@1 61.000 (62.273) Prec@5 96.000 (95.545) +2022-11-14 13:14:33,694 Epoch: [4][220/500] Time 0.020 (0.017) Data 0.002 (0.002) Loss 0.2214 (0.2082) Prec@1 53.000 (61.870) Prec@5 90.000 (95.304) +2022-11-14 13:14:33,871 Epoch: [4][230/500] Time 0.014 (0.017) Data 0.001 (0.002) Loss 0.1808 (0.2071) Prec@1 65.000 (62.000) Prec@5 94.000 (95.250) +2022-11-14 13:14:34,052 Epoch: [4][240/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.2109 (0.2072) Prec@1 58.000 (61.840) Prec@5 93.000 (95.160) +2022-11-14 13:14:34,228 Epoch: [4][250/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.2182 (0.2076) Prec@1 52.000 (61.462) Prec@5 94.000 (95.115) +2022-11-14 13:14:34,407 Epoch: [4][260/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.1663 (0.2061) Prec@1 70.000 (61.778) Prec@5 99.000 (95.259) +2022-11-14 13:14:34,583 Epoch: [4][270/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2163 (0.2065) Prec@1 59.000 (61.679) Prec@5 96.000 (95.286) +2022-11-14 13:14:34,764 Epoch: [4][280/500] Time 0.019 (0.016) Data 0.001 (0.002) Loss 0.2121 (0.2067) Prec@1 57.000 (61.517) Prec@5 97.000 (95.345) +2022-11-14 13:14:34,940 Epoch: [4][290/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.1936 (0.2062) Prec@1 66.000 (61.667) Prec@5 97.000 (95.400) +2022-11-14 13:14:35,120 Epoch: [4][300/500] Time 0.020 (0.016) Data 0.001 (0.002) Loss 0.2123 (0.2064) Prec@1 59.000 (61.581) Prec@5 94.000 (95.355) +2022-11-14 13:14:35,297 Epoch: [4][310/500] Time 0.015 (0.016) Data 0.002 (0.002) Loss 0.1963 (0.2061) Prec@1 64.000 (61.656) Prec@5 96.000 (95.375) +2022-11-14 13:14:35,475 Epoch: [4][320/500] Time 0.019 (0.016) Data 0.001 (0.002) Loss 0.1932 (0.2057) Prec@1 64.000 (61.727) Prec@5 97.000 (95.424) +2022-11-14 13:14:35,654 Epoch: [4][330/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2430 (0.2068) Prec@1 54.000 (61.500) Prec@5 89.000 (95.235) +2022-11-14 13:14:35,835 Epoch: [4][340/500] Time 0.019 (0.016) Data 0.001 (0.002) Loss 0.2440 (0.2079) Prec@1 49.000 (61.143) Prec@5 95.000 (95.229) +2022-11-14 13:14:36,040 Epoch: [4][350/500] Time 0.020 (0.016) Data 0.001 (0.002) Loss 0.2023 (0.2077) Prec@1 63.000 (61.194) Prec@5 91.000 (95.111) +2022-11-14 13:14:36,224 Epoch: [4][360/500] Time 0.020 (0.016) Data 0.001 (0.002) Loss 0.2056 (0.2077) Prec@1 64.000 (61.270) Prec@5 94.000 (95.081) +2022-11-14 13:14:36,409 Epoch: [4][370/500] Time 0.018 (0.016) Data 0.001 (0.002) Loss 0.1916 (0.2072) Prec@1 66.000 (61.395) Prec@5 96.000 (95.105) +2022-11-14 13:14:36,593 Epoch: [4][380/500] Time 0.019 (0.016) Data 0.002 (0.002) Loss 0.1942 (0.2069) Prec@1 66.000 (61.513) Prec@5 94.000 (95.077) +2022-11-14 13:14:36,776 Epoch: [4][390/500] Time 0.017 (0.016) Data 0.001 (0.002) Loss 0.2015 (0.2068) Prec@1 62.000 (61.525) Prec@5 94.000 (95.050) +2022-11-14 13:14:36,957 Epoch: [4][400/500] Time 0.019 (0.016) Data 0.001 (0.002) Loss 0.1966 (0.2065) Prec@1 64.000 (61.585) Prec@5 96.000 (95.073) +2022-11-14 13:14:37,134 Epoch: [4][410/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.1883 (0.2061) Prec@1 66.000 (61.690) Prec@5 95.000 (95.071) +2022-11-14 13:14:37,314 Epoch: [4][420/500] Time 0.019 (0.016) Data 0.002 (0.002) Loss 0.2233 (0.2065) Prec@1 57.000 (61.581) Prec@5 93.000 (95.023) +2022-11-14 13:14:37,490 Epoch: [4][430/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.1878 (0.2061) Prec@1 66.000 (61.682) Prec@5 96.000 (95.045) +2022-11-14 13:14:37,669 Epoch: [4][440/500] Time 0.019 (0.016) Data 0.002 (0.002) Loss 0.2000 (0.2059) Prec@1 64.000 (61.733) Prec@5 97.000 (95.089) +2022-11-14 13:14:37,873 Epoch: [4][450/500] Time 0.017 (0.016) Data 0.001 (0.002) Loss 0.1872 (0.2055) Prec@1 64.000 (61.783) Prec@5 97.000 (95.130) +2022-11-14 13:14:38,053 Epoch: [4][460/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.2102 (0.2056) Prec@1 59.000 (61.723) Prec@5 97.000 (95.170) +2022-11-14 13:14:38,235 Epoch: [4][470/500] Time 0.016 (0.016) Data 0.002 (0.002) Loss 0.1770 (0.2050) Prec@1 67.000 (61.833) Prec@5 97.000 (95.208) +2022-11-14 13:14:38,430 Epoch: [4][480/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.1582 (0.2041) Prec@1 71.000 (62.020) Prec@5 100.000 (95.306) +2022-11-14 13:14:38,638 Epoch: [4][490/500] Time 0.022 (0.016) Data 0.002 (0.002) Loss 0.1779 (0.2035) Prec@1 70.000 (62.180) Prec@5 97.000 (95.340) +2022-11-14 13:14:38,806 Epoch: [4][499/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.2511 (0.2045) Prec@1 57.000 (62.078) Prec@5 96.000 (95.353) +2022-11-14 13:14:39,080 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2003 (0.2003) Prec@1 62.000 (62.000) Prec@5 92.000 (92.000) +2022-11-14 13:14:39,088 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2189 (0.2096) Prec@1 57.000 (59.500) Prec@5 95.000 (93.500) +2022-11-14 13:14:39,096 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2214 (0.2135) Prec@1 58.000 (59.000) Prec@5 94.000 (93.667) +2022-11-14 13:14:39,107 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2214 (0.2155) Prec@1 56.000 (58.250) Prec@5 91.000 (93.000) +2022-11-14 13:14:39,115 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2458 (0.2216) Prec@1 52.000 (57.000) Prec@5 95.000 (93.400) +2022-11-14 13:14:39,122 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1974 (0.2175) Prec@1 63.000 (58.000) Prec@5 92.000 (93.167) +2022-11-14 13:14:39,129 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2266 (0.2188) Prec@1 58.000 (58.000) Prec@5 96.000 (93.571) +2022-11-14 13:14:39,137 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2559 (0.2235) Prec@1 51.000 (57.125) Prec@5 89.000 (93.000) +2022-11-14 13:14:39,144 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2346 (0.2247) Prec@1 54.000 (56.778) Prec@5 96.000 (93.333) +2022-11-14 13:14:39,151 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1672 (0.2190) Prec@1 66.000 (57.700) Prec@5 99.000 (93.900) +2022-11-14 13:14:39,159 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2246 (0.2195) Prec@1 57.000 (57.636) Prec@5 96.000 (94.091) +2022-11-14 13:14:39,167 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2319 (0.2205) Prec@1 60.000 (57.833) Prec@5 95.000 (94.167) +2022-11-14 13:14:39,175 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2057 (0.2194) Prec@1 60.000 (58.000) Prec@5 96.000 (94.308) +2022-11-14 13:14:39,184 Test: [13/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2187 (0.2193) Prec@1 58.000 (58.000) Prec@5 94.000 (94.286) +2022-11-14 13:14:39,192 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1716 (0.2161) Prec@1 70.000 (58.800) Prec@5 97.000 (94.467) +2022-11-14 13:14:39,202 Test: [15/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2447 (0.2179) Prec@1 47.000 (58.062) Prec@5 93.000 (94.375) +2022-11-14 13:14:39,210 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2026 (0.2170) Prec@1 64.000 (58.412) Prec@5 92.000 (94.235) +2022-11-14 13:14:39,218 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2120 (0.2167) Prec@1 64.000 (58.722) Prec@5 96.000 (94.333) +2022-11-14 13:14:39,228 Test: [18/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1822 (0.2149) Prec@1 68.000 (59.211) Prec@5 94.000 (94.316) +2022-11-14 13:14:39,240 Test: [19/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.2671 (0.2175) Prec@1 49.000 (58.700) Prec@5 92.000 (94.200) +2022-11-14 13:14:39,251 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2334 (0.2183) Prec@1 54.000 (58.476) Prec@5 97.000 (94.333) +2022-11-14 13:14:39,261 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2231 (0.2185) Prec@1 58.000 (58.455) Prec@5 93.000 (94.273) +2022-11-14 13:14:39,270 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2169 (0.2184) Prec@1 62.000 (58.609) Prec@5 93.000 (94.217) +2022-11-14 13:14:39,281 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2132 (0.2182) Prec@1 55.000 (58.458) Prec@5 96.000 (94.292) +2022-11-14 13:14:39,293 Test: [24/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2409 (0.2191) Prec@1 55.000 (58.320) Prec@5 96.000 (94.360) +2022-11-14 13:14:39,303 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2664 (0.2209) Prec@1 51.000 (58.038) Prec@5 93.000 (94.308) +2022-11-14 13:14:39,313 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2343 (0.2214) Prec@1 53.000 (57.852) Prec@5 93.000 (94.259) +2022-11-14 13:14:39,327 Test: [27/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.2283 (0.2217) Prec@1 58.000 (57.857) Prec@5 94.000 (94.250) +2022-11-14 13:14:39,339 Test: [28/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2314 (0.2220) Prec@1 57.000 (57.828) Prec@5 91.000 (94.138) +2022-11-14 13:14:39,351 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.2217) Prec@1 62.000 (57.967) Prec@5 98.000 (94.267) +2022-11-14 13:14:39,364 Test: [30/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.2206) Prec@1 68.000 (58.290) Prec@5 92.000 (94.194) +2022-11-14 13:14:39,377 Test: [31/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1942 (0.2198) Prec@1 65.000 (58.500) Prec@5 93.000 (94.156) +2022-11-14 13:14:39,387 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2160 (0.2197) Prec@1 62.000 (58.606) Prec@5 89.000 (94.000) +2022-11-14 13:14:39,399 Test: [33/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.2230 (0.2198) Prec@1 59.000 (58.618) Prec@5 93.000 (93.971) +2022-11-14 13:14:39,409 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2283 (0.2200) Prec@1 59.000 (58.629) Prec@5 93.000 (93.943) +2022-11-14 13:14:39,421 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1882 (0.2191) Prec@1 66.000 (58.833) Prec@5 93.000 (93.917) +2022-11-14 13:14:39,434 Test: [36/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.2089 (0.2189) Prec@1 63.000 (58.946) Prec@5 93.000 (93.892) +2022-11-14 13:14:39,445 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2401 (0.2194) Prec@1 56.000 (58.868) Prec@5 90.000 (93.789) +2022-11-14 13:14:39,457 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.2182) Prec@1 65.000 (59.026) Prec@5 95.000 (93.821) +2022-11-14 13:14:39,469 Test: [39/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.2272 (0.2184) Prec@1 55.000 (58.925) Prec@5 95.000 (93.850) +2022-11-14 13:14:39,480 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1902 (0.2178) Prec@1 66.000 (59.098) Prec@5 97.000 (93.927) +2022-11-14 13:14:39,491 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2184 (0.2178) Prec@1 57.000 (59.048) Prec@5 95.000 (93.952) +2022-11-14 13:14:39,501 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1659 (0.2166) Prec@1 69.000 (59.279) Prec@5 97.000 (94.023) +2022-11-14 13:14:39,511 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1785 (0.2157) Prec@1 69.000 (59.500) Prec@5 93.000 (94.000) +2022-11-14 13:14:39,522 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2429 (0.2163) Prec@1 55.000 (59.400) Prec@5 93.000 (93.978) +2022-11-14 13:14:39,532 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2180 (0.2163) Prec@1 56.000 (59.326) Prec@5 92.000 (93.935) +2022-11-14 13:14:39,543 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2111 (0.2162) Prec@1 56.000 (59.255) Prec@5 96.000 (93.979) +2022-11-14 13:14:39,553 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2241 (0.2164) Prec@1 59.000 (59.250) Prec@5 92.000 (93.938) +2022-11-14 13:14:39,564 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2003 (0.2161) Prec@1 61.000 (59.286) Prec@5 94.000 (93.939) +2022-11-14 13:14:39,574 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1960 (0.2157) Prec@1 66.000 (59.420) Prec@5 96.000 (93.980) +2022-11-14 13:14:39,584 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2086 (0.2155) Prec@1 64.000 (59.510) Prec@5 95.000 (94.000) +2022-11-14 13:14:39,594 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2397 (0.2160) Prec@1 57.000 (59.462) Prec@5 93.000 (93.981) +2022-11-14 13:14:39,603 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2138 (0.2159) Prec@1 65.000 (59.566) Prec@5 96.000 (94.019) +2022-11-14 13:14:39,613 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2368 (0.2163) Prec@1 58.000 (59.537) Prec@5 93.000 (94.000) +2022-11-14 13:14:39,624 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2313 (0.2166) Prec@1 56.000 (59.473) Prec@5 97.000 (94.055) +2022-11-14 13:14:39,635 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2529 (0.2173) Prec@1 55.000 (59.393) Prec@5 92.000 (94.018) +2022-11-14 13:14:39,646 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2089 (0.2171) Prec@1 60.000 (59.404) Prec@5 94.000 (94.018) +2022-11-14 13:14:39,657 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2224 (0.2172) Prec@1 55.000 (59.328) Prec@5 94.000 (94.017) +2022-11-14 13:14:39,669 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2636 (0.2180) Prec@1 51.000 (59.186) Prec@5 93.000 (94.000) +2022-11-14 13:14:39,679 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2146 (0.2179) Prec@1 62.000 (59.233) Prec@5 93.000 (93.983) +2022-11-14 13:14:39,690 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2504 (0.2185) Prec@1 53.000 (59.131) Prec@5 95.000 (94.000) +2022-11-14 13:14:39,700 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2225 (0.2185) Prec@1 60.000 (59.145) Prec@5 94.000 (94.000) +2022-11-14 13:14:39,711 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2209 (0.2186) Prec@1 56.000 (59.095) Prec@5 96.000 (94.032) +2022-11-14 13:14:39,723 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2323 (0.2188) Prec@1 56.000 (59.047) Prec@5 93.000 (94.016) +2022-11-14 13:14:39,734 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2098 (0.2186) Prec@1 62.000 (59.092) Prec@5 96.000 (94.046) +2022-11-14 13:14:39,745 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2270 (0.2188) Prec@1 54.000 (59.015) Prec@5 95.000 (94.061) +2022-11-14 13:14:39,754 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2369 (0.2190) Prec@1 53.000 (58.925) Prec@5 95.000 (94.075) +2022-11-14 13:14:39,764 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2378 (0.2193) Prec@1 56.000 (58.882) Prec@5 92.000 (94.044) +2022-11-14 13:14:39,774 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2284 (0.2194) Prec@1 57.000 (58.855) Prec@5 94.000 (94.043) +2022-11-14 13:14:39,788 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.2496 (0.2199) Prec@1 56.000 (58.814) Prec@5 92.000 (94.014) +2022-11-14 13:14:39,801 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.2339 (0.2201) Prec@1 56.000 (58.775) Prec@5 96.000 (94.042) +2022-11-14 13:14:39,813 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1949 (0.2197) Prec@1 63.000 (58.833) Prec@5 93.000 (94.028) +2022-11-14 13:14:39,823 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1881 (0.2193) Prec@1 65.000 (58.918) Prec@5 95.000 (94.041) +2022-11-14 13:14:39,833 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2088 (0.2191) Prec@1 63.000 (58.973) Prec@5 95.000 (94.054) +2022-11-14 13:14:39,843 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2311 (0.2193) Prec@1 57.000 (58.947) Prec@5 92.000 (94.027) +2022-11-14 13:14:39,853 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1848 (0.2189) Prec@1 68.000 (59.066) Prec@5 95.000 (94.039) +2022-11-14 13:14:39,862 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2405 (0.2191) Prec@1 56.000 (59.026) Prec@5 92.000 (94.013) +2022-11-14 13:14:39,873 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1993 (0.2189) Prec@1 64.000 (59.090) Prec@5 93.000 (94.000) +2022-11-14 13:14:39,885 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2585 (0.2194) Prec@1 55.000 (59.038) Prec@5 95.000 (94.013) +2022-11-14 13:14:39,896 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2111 (0.2193) Prec@1 57.000 (59.013) Prec@5 98.000 (94.062) +2022-11-14 13:14:39,907 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1947 (0.2190) Prec@1 64.000 (59.074) Prec@5 97.000 (94.099) +2022-11-14 13:14:39,918 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2327 (0.2191) Prec@1 54.000 (59.012) Prec@5 96.000 (94.122) +2022-11-14 13:14:39,928 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2062 (0.2190) Prec@1 62.000 (59.048) Prec@5 96.000 (94.145) +2022-11-14 13:14:39,937 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2131 (0.2189) Prec@1 61.000 (59.071) Prec@5 93.000 (94.131) +2022-11-14 13:14:39,945 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2326 (0.2191) Prec@1 59.000 (59.071) Prec@5 93.000 (94.118) +2022-11-14 13:14:39,952 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2098 (0.2190) Prec@1 63.000 (59.116) Prec@5 92.000 (94.093) +2022-11-14 13:14:39,961 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2224 (0.2190) Prec@1 59.000 (59.115) Prec@5 92.000 (94.069) +2022-11-14 13:14:39,970 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2266 (0.2191) Prec@1 61.000 (59.136) Prec@5 94.000 (94.068) +2022-11-14 13:14:39,979 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2300 (0.2192) Prec@1 53.000 (59.067) Prec@5 92.000 (94.045) +2022-11-14 13:14:39,987 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2376 (0.2194) Prec@1 57.000 (59.044) Prec@5 90.000 (94.000) +2022-11-14 13:14:39,996 Test: [90/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2177 (0.2194) Prec@1 58.000 (59.033) Prec@5 95.000 (94.011) +2022-11-14 13:14:40,004 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1550 (0.2187) Prec@1 73.000 (59.185) Prec@5 95.000 (94.022) +2022-11-14 13:14:40,012 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1799 (0.2183) Prec@1 64.000 (59.237) Prec@5 97.000 (94.054) +2022-11-14 13:14:40,020 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2366 (0.2185) Prec@1 53.000 (59.170) Prec@5 91.000 (94.021) +2022-11-14 13:14:40,029 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2359 (0.2187) Prec@1 56.000 (59.137) Prec@5 96.000 (94.042) +2022-11-14 13:14:40,037 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1697 (0.2182) Prec@1 68.000 (59.229) Prec@5 96.000 (94.062) +2022-11-14 13:14:40,045 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2129 (0.2181) Prec@1 56.000 (59.196) Prec@5 91.000 (94.031) +2022-11-14 13:14:40,055 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2502 (0.2184) Prec@1 52.000 (59.122) Prec@5 91.000 (94.000) +2022-11-14 13:14:40,064 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2177 (0.2184) Prec@1 57.000 (59.101) Prec@5 95.000 (94.010) +2022-11-14 13:14:40,074 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2243 (0.2185) Prec@1 64.000 (59.150) Prec@5 91.000 (93.980) +2022-11-14 13:14:40,131 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:14:40,418 Epoch: [5][0/500] Time 0.021 (0.021) Data 0.211 (0.211) Loss 0.2310 (0.2310) Prec@1 57.000 (57.000) Prec@5 99.000 (99.000) +2022-11-14 13:14:40,596 Epoch: [5][10/500] Time 0.014 (0.016) Data 0.001 (0.020) Loss 0.1817 (0.2064) Prec@1 69.000 (63.000) Prec@5 95.000 (97.000) +2022-11-14 13:14:40,772 Epoch: [5][20/500] Time 0.016 (0.016) Data 0.001 (0.011) Loss 0.1962 (0.2030) Prec@1 63.000 (63.000) Prec@5 98.000 (97.333) +2022-11-14 13:14:40,974 Epoch: [5][30/500] Time 0.018 (0.017) Data 0.002 (0.008) Loss 0.1993 (0.2021) Prec@1 64.000 (63.250) Prec@5 95.000 (96.750) +2022-11-14 13:14:41,177 Epoch: [5][40/500] Time 0.015 (0.017) Data 0.001 (0.007) Loss 0.2070 (0.2031) Prec@1 64.000 (63.400) Prec@5 94.000 (96.200) +2022-11-14 13:14:41,364 Epoch: [5][50/500] Time 0.016 (0.017) Data 0.001 (0.006) Loss 0.2032 (0.2031) Prec@1 64.000 (63.500) Prec@5 95.000 (96.000) +2022-11-14 13:14:41,546 Epoch: [5][60/500] Time 0.015 (0.017) Data 0.001 (0.005) Loss 0.1950 (0.2019) Prec@1 69.000 (64.286) Prec@5 98.000 (96.286) +2022-11-14 13:14:41,719 Epoch: [5][70/500] Time 0.014 (0.017) Data 0.001 (0.004) Loss 0.2238 (0.2047) Prec@1 63.000 (64.125) Prec@5 95.000 (96.125) +2022-11-14 13:14:41,895 Epoch: [5][80/500] Time 0.015 (0.016) Data 0.001 (0.004) Loss 0.2044 (0.2046) Prec@1 63.000 (64.000) Prec@5 95.000 (96.000) +2022-11-14 13:14:42,072 Epoch: [5][90/500] Time 0.013 (0.016) Data 0.002 (0.004) Loss 0.1909 (0.2033) Prec@1 66.000 (64.200) Prec@5 95.000 (95.900) +2022-11-14 13:14:42,266 Epoch: [5][100/500] Time 0.021 (0.016) Data 0.002 (0.004) Loss 0.2136 (0.2042) Prec@1 62.000 (64.000) Prec@5 96.000 (95.909) +2022-11-14 13:14:42,510 Epoch: [5][110/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.1799 (0.2022) Prec@1 69.000 (64.417) Prec@5 97.000 (96.000) +2022-11-14 13:14:42,739 Epoch: [5][120/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.1713 (0.1998) Prec@1 67.000 (64.615) Prec@5 97.000 (96.077) +2022-11-14 13:14:42,981 Epoch: [5][130/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.1792 (0.1983) Prec@1 68.000 (64.857) Prec@5 93.000 (95.857) +2022-11-14 13:14:43,236 Epoch: [5][140/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.1860 (0.1975) Prec@1 69.000 (65.133) Prec@5 95.000 (95.800) +2022-11-14 13:14:43,495 Epoch: [5][150/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.1868 (0.1968) Prec@1 63.000 (65.000) Prec@5 94.000 (95.688) +2022-11-14 13:14:43,755 Epoch: [5][160/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.2109 (0.1977) Prec@1 66.000 (65.059) Prec@5 95.000 (95.647) +2022-11-14 13:14:44,017 Epoch: [5][170/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.1702 (0.1961) Prec@1 69.000 (65.278) Prec@5 99.000 (95.833) +2022-11-14 13:14:44,284 Epoch: [5][180/500] Time 0.028 (0.019) Data 0.003 (0.003) Loss 0.1945 (0.1960) Prec@1 62.000 (65.105) Prec@5 96.000 (95.842) +2022-11-14 13:14:44,536 Epoch: [5][190/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.1754 (0.1950) Prec@1 65.000 (65.100) Prec@5 99.000 (96.000) +2022-11-14 13:14:44,803 Epoch: [5][200/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.1668 (0.1937) Prec@1 69.000 (65.286) Prec@5 99.000 (96.143) +2022-11-14 13:14:45,071 Epoch: [5][210/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.1892 (0.1935) Prec@1 62.000 (65.136) Prec@5 97.000 (96.182) +2022-11-14 13:14:45,329 Epoch: [5][220/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.2303 (0.1951) Prec@1 54.000 (64.652) Prec@5 91.000 (95.957) +2022-11-14 13:14:45,583 Epoch: [5][230/500] Time 0.022 (0.020) Data 0.002 (0.003) Loss 0.1971 (0.1951) Prec@1 61.000 (64.500) Prec@5 97.000 (96.000) +2022-11-14 13:14:45,840 Epoch: [5][240/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.2329 (0.1967) Prec@1 56.000 (64.160) Prec@5 97.000 (96.040) +2022-11-14 13:14:46,051 Epoch: [5][250/500] Time 0.016 (0.020) Data 0.001 (0.003) Loss 0.1519 (0.1949) Prec@1 69.000 (64.346) Prec@5 94.000 (95.962) +2022-11-14 13:14:46,244 Epoch: [5][260/500] Time 0.015 (0.020) Data 0.001 (0.002) Loss 0.2005 (0.1951) Prec@1 66.000 (64.407) Prec@5 94.000 (95.889) +2022-11-14 13:14:46,441 Epoch: [5][270/500] Time 0.018 (0.020) Data 0.002 (0.002) Loss 0.1758 (0.1945) Prec@1 71.000 (64.643) Prec@5 95.000 (95.857) +2022-11-14 13:14:46,636 Epoch: [5][280/500] Time 0.015 (0.020) Data 0.002 (0.002) Loss 0.2023 (0.1947) Prec@1 66.000 (64.690) Prec@5 95.000 (95.828) +2022-11-14 13:14:46,863 Epoch: [5][290/500] Time 0.027 (0.020) Data 0.003 (0.002) Loss 0.1606 (0.1936) Prec@1 68.000 (64.800) Prec@5 98.000 (95.900) +2022-11-14 13:14:47,088 Epoch: [5][300/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.1880 (0.1934) Prec@1 66.000 (64.839) Prec@5 93.000 (95.806) +2022-11-14 13:14:47,296 Epoch: [5][310/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1644 (0.1925) Prec@1 75.000 (65.156) Prec@5 97.000 (95.844) +2022-11-14 13:14:47,488 Epoch: [5][320/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.2041 (0.1929) Prec@1 61.000 (65.030) Prec@5 95.000 (95.818) +2022-11-14 13:14:47,735 Epoch: [5][330/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.1679 (0.1921) Prec@1 67.000 (65.088) Prec@5 96.000 (95.824) +2022-11-14 13:14:47,935 Epoch: [5][340/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.2109 (0.1927) Prec@1 61.000 (64.971) Prec@5 93.000 (95.743) +2022-11-14 13:14:48,204 Epoch: [5][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.1763 (0.1922) Prec@1 63.000 (64.917) Prec@5 93.000 (95.667) +2022-11-14 13:14:48,466 Epoch: [5][360/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.2057 (0.1926) Prec@1 61.000 (64.811) Prec@5 97.000 (95.703) +2022-11-14 13:14:48,733 Epoch: [5][370/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1733 (0.1921) Prec@1 70.000 (64.947) Prec@5 96.000 (95.711) +2022-11-14 13:14:48,991 Epoch: [5][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.1520 (0.1910) Prec@1 73.000 (65.154) Prec@5 97.000 (95.744) +2022-11-14 13:14:49,249 Epoch: [5][390/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.1913 (0.1910) Prec@1 67.000 (65.200) Prec@5 96.000 (95.750) +2022-11-14 13:14:49,475 Epoch: [5][400/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.1824 (0.1908) Prec@1 69.000 (65.293) Prec@5 92.000 (95.659) +2022-11-14 13:14:49,721 Epoch: [5][410/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.2024 (0.1911) Prec@1 64.000 (65.262) Prec@5 94.000 (95.619) +2022-11-14 13:14:49,981 Epoch: [5][420/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.1764 (0.1908) Prec@1 70.000 (65.372) Prec@5 97.000 (95.651) +2022-11-14 13:14:50,220 Epoch: [5][430/500] Time 0.020 (0.020) Data 0.002 (0.002) Loss 0.2016 (0.1910) Prec@1 64.000 (65.341) Prec@5 97.000 (95.682) +2022-11-14 13:14:50,481 Epoch: [5][440/500] Time 0.022 (0.020) Data 0.003 (0.002) Loss 0.1808 (0.1908) Prec@1 68.000 (65.400) Prec@5 97.000 (95.711) +2022-11-14 13:14:50,709 Epoch: [5][450/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1729 (0.1904) Prec@1 68.000 (65.457) Prec@5 96.000 (95.717) +2022-11-14 13:14:50,917 Epoch: [5][460/500] Time 0.019 (0.020) Data 0.002 (0.002) Loss 0.1731 (0.1900) Prec@1 70.000 (65.553) Prec@5 97.000 (95.745) +2022-11-14 13:14:51,142 Epoch: [5][470/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1736 (0.1897) Prec@1 67.000 (65.583) Prec@5 97.000 (95.771) +2022-11-14 13:14:51,352 Epoch: [5][480/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1766 (0.1894) Prec@1 67.000 (65.612) Prec@5 99.000 (95.837) +2022-11-14 13:14:51,573 Epoch: [5][490/500] Time 0.020 (0.020) Data 0.003 (0.002) Loss 0.1634 (0.1889) Prec@1 69.000 (65.680) Prec@5 98.000 (95.880) +2022-11-14 13:14:51,766 Epoch: [5][499/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1804 (0.1887) Prec@1 70.000 (65.765) Prec@5 98.000 (95.922) +2022-11-14 13:14:52,041 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.1955 (0.1955) Prec@1 61.000 (61.000) Prec@5 96.000 (96.000) +2022-11-14 13:14:52,052 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.2113 (0.2034) Prec@1 60.000 (60.500) Prec@5 94.000 (95.000) +2022-11-14 13:14:52,064 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.2086 (0.2051) Prec@1 61.000 (60.667) Prec@5 97.000 (95.667) +2022-11-14 13:14:52,081 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.2260 (0.2103) Prec@1 56.000 (59.500) Prec@5 96.000 (95.750) +2022-11-14 13:14:52,093 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2150 (0.2113) Prec@1 61.000 (59.800) Prec@5 96.000 (95.800) +2022-11-14 13:14:52,104 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1668 (0.2039) Prec@1 68.000 (61.167) Prec@5 98.000 (96.167) +2022-11-14 13:14:52,115 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.2447 (0.2097) Prec@1 54.000 (60.143) Prec@5 96.000 (96.143) +2022-11-14 13:14:52,128 Test: [7/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.2361 (0.2130) Prec@1 55.000 (59.500) Prec@5 85.000 (94.750) +2022-11-14 13:14:52,137 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2246 (0.2143) Prec@1 53.000 (58.778) Prec@5 98.000 (95.111) +2022-11-14 13:14:52,148 Test: [9/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2121 (0.2141) Prec@1 55.000 (58.400) Prec@5 93.000 (94.900) +2022-11-14 13:14:52,158 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2081 (0.2135) Prec@1 62.000 (58.727) Prec@5 94.000 (94.818) +2022-11-14 13:14:52,169 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2118 (0.2134) Prec@1 63.000 (59.083) Prec@5 95.000 (94.833) +2022-11-14 13:14:52,180 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1912 (0.2117) Prec@1 63.000 (59.385) Prec@5 98.000 (95.077) +2022-11-14 13:14:52,190 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1922 (0.2103) Prec@1 64.000 (59.714) Prec@5 97.000 (95.214) +2022-11-14 13:14:52,201 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1779 (0.2081) Prec@1 66.000 (60.133) Prec@5 96.000 (95.267) +2022-11-14 13:14:52,210 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2605 (0.2114) Prec@1 52.000 (59.625) Prec@5 93.000 (95.125) +2022-11-14 13:14:52,219 Test: [16/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2026 (0.2109) Prec@1 66.000 (60.000) Prec@5 94.000 (95.059) +2022-11-14 13:14:52,231 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2023 (0.2104) Prec@1 60.000 (60.000) Prec@5 100.000 (95.333) +2022-11-14 13:14:52,243 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1641 (0.2080) Prec@1 71.000 (60.579) Prec@5 95.000 (95.316) +2022-11-14 13:14:52,254 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2547 (0.2103) Prec@1 52.000 (60.150) Prec@5 92.000 (95.150) +2022-11-14 13:14:52,266 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.2122 (0.2104) Prec@1 61.000 (60.190) Prec@5 94.000 (95.095) +2022-11-14 13:14:52,277 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1896 (0.2095) Prec@1 66.000 (60.455) Prec@5 95.000 (95.091) +2022-11-14 13:14:52,288 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2208 (0.2099) Prec@1 58.000 (60.348) Prec@5 94.000 (95.043) +2022-11-14 13:14:52,300 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2293 (0.2108) Prec@1 57.000 (60.208) Prec@5 93.000 (94.958) +2022-11-14 13:14:52,312 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1941 (0.2101) Prec@1 65.000 (60.400) Prec@5 98.000 (95.080) +2022-11-14 13:14:52,322 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2524 (0.2117) Prec@1 54.000 (60.154) Prec@5 93.000 (95.000) +2022-11-14 13:14:52,332 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2151 (0.2118) Prec@1 58.000 (60.074) Prec@5 98.000 (95.111) +2022-11-14 13:14:52,341 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2159 (0.2120) Prec@1 61.000 (60.107) Prec@5 97.000 (95.179) +2022-11-14 13:14:52,351 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2242 (0.2124) Prec@1 58.000 (60.034) Prec@5 97.000 (95.241) +2022-11-14 13:14:52,361 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1945 (0.2118) Prec@1 61.000 (60.067) Prec@5 93.000 (95.167) +2022-11-14 13:14:52,369 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2043 (0.2116) Prec@1 58.000 (60.000) Prec@5 96.000 (95.194) +2022-11-14 13:14:52,379 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1995 (0.2112) Prec@1 62.000 (60.062) Prec@5 96.000 (95.219) +2022-11-14 13:14:52,388 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1954 (0.2107) Prec@1 62.000 (60.121) Prec@5 96.000 (95.242) +2022-11-14 13:14:52,397 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2119 (0.2107) Prec@1 58.000 (60.059) Prec@5 94.000 (95.206) +2022-11-14 13:14:52,407 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2148 (0.2109) Prec@1 57.000 (59.971) Prec@5 94.000 (95.171) +2022-11-14 13:14:52,416 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2289 (0.2114) Prec@1 58.000 (59.917) Prec@5 93.000 (95.111) +2022-11-14 13:14:52,425 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2259 (0.2118) Prec@1 58.000 (59.865) Prec@5 96.000 (95.135) +2022-11-14 13:14:52,435 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2275 (0.2122) Prec@1 54.000 (59.711) Prec@5 91.000 (95.026) +2022-11-14 13:14:52,444 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1779 (0.2113) Prec@1 67.000 (59.897) Prec@5 95.000 (95.026) +2022-11-14 13:14:52,453 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1870 (0.2107) Prec@1 68.000 (60.100) Prec@5 94.000 (95.000) +2022-11-14 13:14:52,463 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2039 (0.2105) Prec@1 65.000 (60.220) Prec@5 95.000 (95.000) +2022-11-14 13:14:52,472 Test: [41/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2279 (0.2109) Prec@1 61.000 (60.238) Prec@5 92.000 (94.929) +2022-11-14 13:14:52,481 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1915 (0.2105) Prec@1 67.000 (60.395) Prec@5 98.000 (95.000) +2022-11-14 13:14:52,491 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1950 (0.2101) Prec@1 66.000 (60.523) Prec@5 90.000 (94.886) +2022-11-14 13:14:52,501 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2007 (0.2099) Prec@1 64.000 (60.600) Prec@5 96.000 (94.911) +2022-11-14 13:14:52,509 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2438 (0.2107) Prec@1 53.000 (60.435) Prec@5 95.000 (94.913) +2022-11-14 13:14:52,521 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2069 (0.2106) Prec@1 61.000 (60.447) Prec@5 96.000 (94.936) +2022-11-14 13:14:52,534 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2131 (0.2106) Prec@1 63.000 (60.500) Prec@5 91.000 (94.854) +2022-11-14 13:14:52,548 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2047 (0.2105) Prec@1 56.000 (60.408) Prec@5 99.000 (94.939) +2022-11-14 13:14:52,562 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1865 (0.2100) Prec@1 65.000 (60.500) Prec@5 97.000 (94.980) +2022-11-14 13:14:52,577 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2034 (0.2099) Prec@1 64.000 (60.569) Prec@5 95.000 (94.980) +2022-11-14 13:14:52,590 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2234 (0.2102) Prec@1 53.000 (60.423) Prec@5 95.000 (94.981) +2022-11-14 13:14:52,603 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1899 (0.2098) Prec@1 64.000 (60.491) Prec@5 96.000 (95.000) +2022-11-14 13:14:52,620 Test: [53/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1865 (0.2093) Prec@1 65.000 (60.574) Prec@5 96.000 (95.019) +2022-11-14 13:14:52,635 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2173 (0.2095) Prec@1 60.000 (60.564) Prec@5 93.000 (94.982) +2022-11-14 13:14:52,649 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2351 (0.2099) Prec@1 57.000 (60.500) Prec@5 91.000 (94.911) +2022-11-14 13:14:52,664 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2204 (0.2101) Prec@1 63.000 (60.544) Prec@5 95.000 (94.912) +2022-11-14 13:14:52,678 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2220 (0.2103) Prec@1 56.000 (60.466) Prec@5 96.000 (94.931) +2022-11-14 13:14:52,694 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.2408 (0.2108) Prec@1 52.000 (60.322) Prec@5 97.000 (94.966) +2022-11-14 13:14:52,708 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2049 (0.2107) Prec@1 58.000 (60.283) Prec@5 95.000 (94.967) +2022-11-14 13:14:52,720 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1948 (0.2105) Prec@1 62.000 (60.311) Prec@5 98.000 (95.016) +2022-11-14 13:14:52,729 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1928 (0.2102) Prec@1 64.000 (60.371) Prec@5 98.000 (95.065) +2022-11-14 13:14:52,738 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2066 (0.2101) Prec@1 61.000 (60.381) Prec@5 98.000 (95.111) +2022-11-14 13:14:52,747 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1926 (0.2099) Prec@1 65.000 (60.453) Prec@5 96.000 (95.125) +2022-11-14 13:14:52,756 Test: [64/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2167 (0.2100) Prec@1 59.000 (60.431) Prec@5 95.000 (95.123) +2022-11-14 13:14:52,765 Test: [65/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2330 (0.2103) Prec@1 57.000 (60.379) Prec@5 94.000 (95.106) +2022-11-14 13:14:52,775 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1794 (0.2099) Prec@1 70.000 (60.522) Prec@5 95.000 (95.104) +2022-11-14 13:14:52,784 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2394 (0.2103) Prec@1 54.000 (60.426) Prec@5 96.000 (95.118) +2022-11-14 13:14:52,793 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2052 (0.2102) Prec@1 67.000 (60.522) Prec@5 95.000 (95.116) +2022-11-14 13:14:52,802 Test: [69/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2228 (0.2104) Prec@1 62.000 (60.543) Prec@5 96.000 (95.129) +2022-11-14 13:14:52,812 Test: [70/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2430 (0.2109) Prec@1 51.000 (60.408) Prec@5 94.000 (95.113) +2022-11-14 13:14:52,821 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1741 (0.2104) Prec@1 69.000 (60.528) Prec@5 97.000 (95.139) +2022-11-14 13:14:52,831 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2084 (0.2103) Prec@1 59.000 (60.507) Prec@5 98.000 (95.178) +2022-11-14 13:14:52,840 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2114 (0.2103) Prec@1 62.000 (60.527) Prec@5 95.000 (95.176) +2022-11-14 13:14:52,849 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1858 (0.2100) Prec@1 65.000 (60.587) Prec@5 98.000 (95.213) +2022-11-14 13:14:52,859 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1948 (0.2098) Prec@1 65.000 (60.645) Prec@5 97.000 (95.237) +2022-11-14 13:14:52,868 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1979 (0.2097) Prec@1 66.000 (60.714) Prec@5 92.000 (95.195) +2022-11-14 13:14:52,876 Test: [77/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1887 (0.2094) Prec@1 62.000 (60.731) Prec@5 95.000 (95.192) +2022-11-14 13:14:52,886 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2246 (0.2096) Prec@1 61.000 (60.734) Prec@5 96.000 (95.203) +2022-11-14 13:14:52,895 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2096 (0.2096) Prec@1 57.000 (60.688) Prec@5 95.000 (95.200) +2022-11-14 13:14:52,904 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2029 (0.2095) Prec@1 61.000 (60.691) Prec@5 98.000 (95.235) +2022-11-14 13:14:52,914 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2205 (0.2096) Prec@1 62.000 (60.707) Prec@5 98.000 (95.268) +2022-11-14 13:14:52,923 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2261 (0.2098) Prec@1 56.000 (60.651) Prec@5 96.000 (95.277) +2022-11-14 13:14:52,932 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2314 (0.2101) Prec@1 57.000 (60.607) Prec@5 97.000 (95.298) +2022-11-14 13:14:52,942 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2180 (0.2102) Prec@1 59.000 (60.588) Prec@5 95.000 (95.294) +2022-11-14 13:14:52,951 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2273 (0.2104) Prec@1 56.000 (60.535) Prec@5 95.000 (95.291) +2022-11-14 13:14:52,960 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2386 (0.2107) Prec@1 55.000 (60.471) Prec@5 94.000 (95.276) +2022-11-14 13:14:52,969 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2290 (0.2109) Prec@1 56.000 (60.420) Prec@5 94.000 (95.261) +2022-11-14 13:14:52,979 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2142 (0.2110) Prec@1 58.000 (60.393) Prec@5 97.000 (95.281) +2022-11-14 13:14:52,987 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2123 (0.2110) Prec@1 58.000 (60.367) Prec@5 94.000 (95.267) +2022-11-14 13:14:52,997 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2126 (0.2110) Prec@1 62.000 (60.385) Prec@5 96.000 (95.275) +2022-11-14 13:14:53,006 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2001 (0.2109) Prec@1 62.000 (60.402) Prec@5 98.000 (95.304) +2022-11-14 13:14:53,015 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2004 (0.2108) Prec@1 62.000 (60.419) Prec@5 96.000 (95.312) +2022-11-14 13:14:53,023 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2088 (0.2107) Prec@1 58.000 (60.394) Prec@5 97.000 (95.330) +2022-11-14 13:14:53,031 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2278 (0.2109) Prec@1 57.000 (60.358) Prec@5 96.000 (95.337) +2022-11-14 13:14:53,040 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1649 (0.2104) Prec@1 70.000 (60.458) Prec@5 93.000 (95.312) +2022-11-14 13:14:53,049 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2142 (0.2105) Prec@1 61.000 (60.464) Prec@5 93.000 (95.289) +2022-11-14 13:14:53,058 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2440 (0.2108) Prec@1 51.000 (60.367) Prec@5 97.000 (95.306) +2022-11-14 13:14:53,067 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1893 (0.2106) Prec@1 64.000 (60.404) Prec@5 94.000 (95.293) +2022-11-14 13:14:53,076 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2467 (0.2110) Prec@1 54.000 (60.340) Prec@5 94.000 (95.280) +2022-11-14 13:14:53,129 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:14:53,420 Epoch: [6][0/500] Time 0.026 (0.026) Data 0.211 (0.211) Loss 0.2560 (0.2560) Prec@1 53.000 (53.000) Prec@5 90.000 (90.000) +2022-11-14 13:14:53,622 Epoch: [6][10/500] Time 0.016 (0.019) Data 0.002 (0.020) Loss 0.2026 (0.2293) Prec@1 63.000 (58.000) Prec@5 95.000 (92.500) +2022-11-14 13:14:53,826 Epoch: [6][20/500] Time 0.015 (0.018) Data 0.002 (0.012) Loss 0.1702 (0.2096) Prec@1 70.000 (62.000) Prec@5 96.000 (93.667) +2022-11-14 13:14:54,030 Epoch: [6][30/500] Time 0.020 (0.018) Data 0.001 (0.008) Loss 0.2099 (0.2097) Prec@1 59.000 (61.250) Prec@5 98.000 (94.750) +2022-11-14 13:14:54,230 Epoch: [6][40/500] Time 0.014 (0.018) Data 0.002 (0.007) Loss 0.1612 (0.2000) Prec@1 72.000 (63.400) Prec@5 94.000 (94.600) +2022-11-14 13:14:54,430 Epoch: [6][50/500] Time 0.018 (0.018) Data 0.001 (0.006) Loss 0.1740 (0.1956) Prec@1 66.000 (63.833) Prec@5 99.000 (95.333) +2022-11-14 13:14:54,628 Epoch: [6][60/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.1667 (0.1915) Prec@1 72.000 (65.000) Prec@5 97.000 (95.571) +2022-11-14 13:14:54,820 Epoch: [6][70/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.2068 (0.1934) Prec@1 57.000 (64.000) Prec@5 96.000 (95.625) +2022-11-14 13:14:55,014 Epoch: [6][80/500] Time 0.018 (0.018) Data 0.001 (0.004) Loss 0.2000 (0.1941) Prec@1 61.000 (63.667) Prec@5 99.000 (96.000) +2022-11-14 13:14:55,230 Epoch: [6][90/500] Time 0.021 (0.018) Data 0.002 (0.004) Loss 0.1760 (0.1923) Prec@1 69.000 (64.200) Prec@5 99.000 (96.300) +2022-11-14 13:14:55,456 Epoch: [6][100/500] Time 0.018 (0.018) Data 0.002 (0.004) Loss 0.1898 (0.1921) Prec@1 66.000 (64.364) Prec@5 95.000 (96.182) +2022-11-14 13:14:55,660 Epoch: [6][110/500] Time 0.020 (0.018) Data 0.001 (0.003) Loss 0.1645 (0.1898) Prec@1 73.000 (65.083) Prec@5 98.000 (96.333) +2022-11-14 13:14:55,861 Epoch: [6][120/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.1791 (0.1890) Prec@1 66.000 (65.154) Prec@5 99.000 (96.538) +2022-11-14 13:14:56,094 Epoch: [6][130/500] Time 0.033 (0.018) Data 0.002 (0.003) Loss 0.1671 (0.1874) Prec@1 69.000 (65.429) Prec@5 96.000 (96.500) +2022-11-14 13:14:56,314 Epoch: [6][140/500] Time 0.015 (0.018) Data 0.001 (0.003) Loss 0.2105 (0.1889) Prec@1 64.000 (65.333) Prec@5 97.000 (96.533) +2022-11-14 13:14:56,516 Epoch: [6][150/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.1750 (0.1881) Prec@1 68.000 (65.500) Prec@5 96.000 (96.500) +2022-11-14 13:14:56,710 Epoch: [6][160/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.2093 (0.1893) Prec@1 59.000 (65.118) Prec@5 93.000 (96.294) +2022-11-14 13:14:56,910 Epoch: [6][170/500] Time 0.015 (0.018) Data 0.002 (0.003) Loss 0.1640 (0.1879) Prec@1 70.000 (65.389) Prec@5 97.000 (96.333) +2022-11-14 13:14:57,161 Epoch: [6][180/500] Time 0.018 (0.018) Data 0.002 (0.003) Loss 0.1951 (0.1883) Prec@1 65.000 (65.368) Prec@5 96.000 (96.316) +2022-11-14 13:14:57,355 Epoch: [6][190/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.1421 (0.1860) Prec@1 73.000 (65.750) Prec@5 98.000 (96.400) +2022-11-14 13:14:57,616 Epoch: [6][200/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.1882 (0.1861) Prec@1 66.000 (65.762) Prec@5 95.000 (96.333) +2022-11-14 13:14:57,815 Epoch: [6][210/500] Time 0.017 (0.019) Data 0.001 (0.003) Loss 0.1983 (0.1866) Prec@1 62.000 (65.591) Prec@5 96.000 (96.318) +2022-11-14 13:14:58,014 Epoch: [6][220/500] Time 0.017 (0.019) Data 0.001 (0.003) Loss 0.1517 (0.1851) Prec@1 74.000 (65.957) Prec@5 99.000 (96.435) +2022-11-14 13:14:58,208 Epoch: [6][230/500] Time 0.017 (0.019) Data 0.001 (0.002) Loss 0.1779 (0.1848) Prec@1 67.000 (66.000) Prec@5 97.000 (96.458) +2022-11-14 13:14:58,402 Epoch: [6][240/500] Time 0.016 (0.018) Data 0.002 (0.002) Loss 0.1842 (0.1848) Prec@1 64.000 (65.920) Prec@5 97.000 (96.480) +2022-11-14 13:14:58,667 Epoch: [6][250/500] Time 0.018 (0.019) Data 0.001 (0.002) Loss 0.1698 (0.1842) Prec@1 69.000 (66.038) Prec@5 97.000 (96.500) +2022-11-14 13:14:58,872 Epoch: [6][260/500] Time 0.018 (0.019) Data 0.001 (0.002) Loss 0.1563 (0.1832) Prec@1 73.000 (66.296) Prec@5 96.000 (96.481) +2022-11-14 13:14:59,125 Epoch: [6][270/500] Time 0.017 (0.019) Data 0.001 (0.002) Loss 0.1460 (0.1819) Prec@1 74.000 (66.571) Prec@5 96.000 (96.464) +2022-11-14 13:14:59,338 Epoch: [6][280/500] Time 0.021 (0.019) Data 0.002 (0.002) Loss 0.1445 (0.1806) Prec@1 74.000 (66.828) Prec@5 97.000 (96.483) +2022-11-14 13:14:59,602 Epoch: [6][290/500] Time 0.021 (0.019) Data 0.002 (0.002) Loss 0.1564 (0.1798) Prec@1 70.000 (66.933) Prec@5 97.000 (96.500) +2022-11-14 13:14:59,834 Epoch: [6][300/500] Time 0.020 (0.019) Data 0.002 (0.002) Loss 0.1901 (0.1801) Prec@1 64.000 (66.839) Prec@5 98.000 (96.548) +2022-11-14 13:15:00,049 Epoch: [6][310/500] Time 0.017 (0.019) Data 0.002 (0.002) Loss 0.1991 (0.1807) Prec@1 63.000 (66.719) Prec@5 96.000 (96.531) +2022-11-14 13:15:00,264 Epoch: [6][320/500] Time 0.020 (0.019) Data 0.002 (0.002) Loss 0.1485 (0.1797) Prec@1 78.000 (67.061) Prec@5 96.000 (96.515) +2022-11-14 13:15:00,590 Epoch: [6][330/500] Time 0.018 (0.019) Data 0.003 (0.002) Loss 0.1740 (0.1795) Prec@1 68.000 (67.088) Prec@5 96.000 (96.500) +2022-11-14 13:15:00,848 Epoch: [6][340/500] Time 0.018 (0.019) Data 0.002 (0.002) Loss 0.1746 (0.1794) Prec@1 68.000 (67.114) Prec@5 95.000 (96.457) +2022-11-14 13:15:01,125 Epoch: [6][350/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.2097 (0.1802) Prec@1 58.000 (66.861) Prec@5 98.000 (96.500) +2022-11-14 13:15:01,364 Epoch: [6][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.1844 (0.1804) Prec@1 66.000 (66.838) Prec@5 98.000 (96.541) +2022-11-14 13:15:01,609 Epoch: [6][370/500] Time 0.017 (0.020) Data 0.002 (0.002) Loss 0.1904 (0.1806) Prec@1 65.000 (66.789) Prec@5 95.000 (96.500) +2022-11-14 13:15:01,896 Epoch: [6][380/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.1459 (0.1797) Prec@1 72.000 (66.923) Prec@5 99.000 (96.564) +2022-11-14 13:15:02,244 Epoch: [6][390/500] Time 0.032 (0.020) Data 0.002 (0.002) Loss 0.1718 (0.1795) Prec@1 65.000 (66.875) Prec@5 98.000 (96.600) +2022-11-14 13:15:02,596 Epoch: [6][400/500] Time 0.034 (0.020) Data 0.002 (0.002) Loss 0.1873 (0.1797) Prec@1 61.000 (66.732) Prec@5 96.000 (96.585) +2022-11-14 13:15:02,864 Epoch: [6][410/500] Time 0.034 (0.020) Data 0.002 (0.002) Loss 0.1758 (0.1796) Prec@1 66.000 (66.714) Prec@5 97.000 (96.595) +2022-11-14 13:15:03,089 Epoch: [6][420/500] Time 0.017 (0.020) Data 0.002 (0.002) Loss 0.1723 (0.1795) Prec@1 70.000 (66.791) Prec@5 98.000 (96.628) +2022-11-14 13:15:03,349 Epoch: [6][430/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.1626 (0.1791) Prec@1 74.000 (66.955) Prec@5 98.000 (96.659) +2022-11-14 13:15:03,551 Epoch: [6][440/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1834 (0.1792) Prec@1 66.000 (66.933) Prec@5 99.000 (96.711) +2022-11-14 13:15:03,766 Epoch: [6][450/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.1631 (0.1788) Prec@1 67.000 (66.935) Prec@5 96.000 (96.696) +2022-11-14 13:15:03,982 Epoch: [6][460/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1603 (0.1784) Prec@1 69.000 (66.979) Prec@5 98.000 (96.723) +2022-11-14 13:15:04,180 Epoch: [6][470/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1817 (0.1785) Prec@1 66.000 (66.958) Prec@5 96.000 (96.708) +2022-11-14 13:15:04,378 Epoch: [6][480/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1571 (0.1781) Prec@1 71.000 (67.041) Prec@5 97.000 (96.714) +2022-11-14 13:15:04,571 Epoch: [6][490/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1982 (0.1785) Prec@1 67.000 (67.040) Prec@5 97.000 (96.720) +2022-11-14 13:15:04,801 Epoch: [6][499/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.1805 (0.1785) Prec@1 67.000 (67.039) Prec@5 97.000 (96.725) +2022-11-14 13:15:05,080 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.1946 (0.1946) Prec@1 63.000 (63.000) Prec@5 98.000 (98.000) +2022-11-14 13:15:05,090 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1988 (0.1967) Prec@1 68.000 (65.500) Prec@5 97.000 (97.500) +2022-11-14 13:15:05,100 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2202 (0.2045) Prec@1 55.000 (62.000) Prec@5 96.000 (97.000) +2022-11-14 13:15:05,115 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.2102 (0.2060) Prec@1 60.000 (61.500) Prec@5 92.000 (95.750) +2022-11-14 13:15:05,125 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2048 (0.2057) Prec@1 64.000 (62.000) Prec@5 93.000 (95.200) +2022-11-14 13:15:05,134 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1787 (0.2012) Prec@1 70.000 (63.333) Prec@5 98.000 (95.667) +2022-11-14 13:15:05,143 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2474 (0.2078) Prec@1 50.000 (61.429) Prec@5 94.000 (95.429) +2022-11-14 13:15:05,156 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.2215 (0.2095) Prec@1 65.000 (61.875) Prec@5 89.000 (94.625) +2022-11-14 13:15:05,166 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1981 (0.2083) Prec@1 66.000 (62.333) Prec@5 92.000 (94.333) +2022-11-14 13:15:05,175 Test: [9/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2035 (0.2078) Prec@1 63.000 (62.400) Prec@5 97.000 (94.600) +2022-11-14 13:15:05,185 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2023 (0.2073) Prec@1 62.000 (62.364) Prec@5 93.000 (94.455) +2022-11-14 13:15:05,197 Test: [11/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1909 (0.2059) Prec@1 65.000 (62.583) Prec@5 95.000 (94.500) +2022-11-14 13:15:05,208 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2042 (0.2058) Prec@1 67.000 (62.923) Prec@5 93.000 (94.385) +2022-11-14 13:15:05,217 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1674 (0.2031) Prec@1 74.000 (63.714) Prec@5 98.000 (94.643) +2022-11-14 13:15:05,226 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1910 (0.2023) Prec@1 67.000 (63.933) Prec@5 100.000 (95.000) +2022-11-14 13:15:05,239 Test: [15/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.2144 (0.2030) Prec@1 59.000 (63.625) Prec@5 98.000 (95.188) +2022-11-14 13:15:05,249 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1853 (0.2020) Prec@1 64.000 (63.647) Prec@5 96.000 (95.235) +2022-11-14 13:15:05,258 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1858 (0.2011) Prec@1 65.000 (63.722) Prec@5 97.000 (95.333) +2022-11-14 13:15:05,268 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2037 (0.2012) Prec@1 64.000 (63.737) Prec@5 91.000 (95.105) +2022-11-14 13:15:05,277 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2432 (0.2033) Prec@1 56.000 (63.350) Prec@5 94.000 (95.050) +2022-11-14 13:15:05,286 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2094 (0.2036) Prec@1 62.000 (63.286) Prec@5 94.000 (95.000) +2022-11-14 13:15:05,296 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1751 (0.2023) Prec@1 67.000 (63.455) Prec@5 96.000 (95.045) +2022-11-14 13:15:05,305 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2243 (0.2033) Prec@1 60.000 (63.304) Prec@5 92.000 (94.913) +2022-11-14 13:15:05,314 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2015 (0.2032) Prec@1 67.000 (63.458) Prec@5 93.000 (94.833) +2022-11-14 13:15:05,324 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1922 (0.2028) Prec@1 65.000 (63.520) Prec@5 92.000 (94.720) +2022-11-14 13:15:05,334 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2334 (0.2039) Prec@1 58.000 (63.308) Prec@5 94.000 (94.692) +2022-11-14 13:15:05,342 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1883 (0.2033) Prec@1 64.000 (63.333) Prec@5 96.000 (94.741) +2022-11-14 13:15:05,352 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2145 (0.2037) Prec@1 60.000 (63.214) Prec@5 96.000 (94.786) +2022-11-14 13:15:05,361 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2011 (0.2037) Prec@1 63.000 (63.207) Prec@5 97.000 (94.862) +2022-11-14 13:15:05,372 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1854 (0.2031) Prec@1 63.000 (63.200) Prec@5 92.000 (94.767) +2022-11-14 13:15:05,383 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1647 (0.2018) Prec@1 68.000 (63.355) Prec@5 96.000 (94.806) +2022-11-14 13:15:05,393 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2109 (0.2021) Prec@1 66.000 (63.438) Prec@5 96.000 (94.844) +2022-11-14 13:15:05,406 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1934 (0.2018) Prec@1 63.000 (63.424) Prec@5 98.000 (94.939) +2022-11-14 13:15:05,417 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2262 (0.2025) Prec@1 59.000 (63.294) Prec@5 97.000 (95.000) +2022-11-14 13:15:05,427 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1932 (0.2023) Prec@1 60.000 (63.200) Prec@5 97.000 (95.057) +2022-11-14 13:15:05,437 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1998 (0.2022) Prec@1 63.000 (63.194) Prec@5 94.000 (95.028) +2022-11-14 13:15:05,447 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2339 (0.2031) Prec@1 57.000 (63.027) Prec@5 93.000 (94.973) +2022-11-14 13:15:05,457 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2160 (0.2034) Prec@1 62.000 (63.000) Prec@5 92.000 (94.895) +2022-11-14 13:15:05,466 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1699 (0.2025) Prec@1 67.000 (63.103) Prec@5 98.000 (94.974) +2022-11-14 13:15:05,476 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.2018) Prec@1 70.000 (63.275) Prec@5 95.000 (94.975) +2022-11-14 13:15:05,486 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1763 (0.2012) Prec@1 71.000 (63.463) Prec@5 97.000 (95.024) +2022-11-14 13:15:05,498 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1936 (0.2010) Prec@1 68.000 (63.571) Prec@5 93.000 (94.976) +2022-11-14 13:15:05,508 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1810 (0.2005) Prec@1 66.000 (63.628) Prec@5 98.000 (95.047) +2022-11-14 13:15:05,519 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1837 (0.2002) Prec@1 65.000 (63.659) Prec@5 93.000 (95.000) +2022-11-14 13:15:05,529 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2075 (0.2003) Prec@1 64.000 (63.667) Prec@5 97.000 (95.044) +2022-11-14 13:15:05,541 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2527 (0.2015) Prec@1 56.000 (63.500) Prec@5 93.000 (95.000) +2022-11-14 13:15:05,553 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1968 (0.2014) Prec@1 65.000 (63.532) Prec@5 95.000 (95.000) +2022-11-14 13:15:05,564 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2287 (0.2019) Prec@1 57.000 (63.396) Prec@5 93.000 (94.958) +2022-11-14 13:15:05,574 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1918 (0.2017) Prec@1 67.000 (63.469) Prec@5 97.000 (95.000) +2022-11-14 13:15:05,585 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2056 (0.2018) Prec@1 64.000 (63.480) Prec@5 95.000 (95.000) +2022-11-14 13:15:05,597 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1858 (0.2015) Prec@1 68.000 (63.569) Prec@5 97.000 (95.039) +2022-11-14 13:15:05,607 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1980 (0.2014) Prec@1 66.000 (63.615) Prec@5 94.000 (95.019) +2022-11-14 13:15:05,618 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1952 (0.2013) Prec@1 68.000 (63.698) Prec@5 95.000 (95.019) +2022-11-14 13:15:05,627 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1955 (0.2012) Prec@1 65.000 (63.722) Prec@5 97.000 (95.056) +2022-11-14 13:15:05,637 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2207 (0.2016) Prec@1 58.000 (63.618) Prec@5 95.000 (95.055) +2022-11-14 13:15:05,645 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2276 (0.2020) Prec@1 60.000 (63.554) Prec@5 89.000 (94.946) +2022-11-14 13:15:05,654 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2086 (0.2021) Prec@1 64.000 (63.561) Prec@5 97.000 (94.982) +2022-11-14 13:15:05,664 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1728 (0.2016) Prec@1 70.000 (63.672) Prec@5 99.000 (95.052) +2022-11-14 13:15:05,674 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2306 (0.2021) Prec@1 60.000 (63.610) Prec@5 91.000 (94.983) +2022-11-14 13:15:05,683 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2050 (0.2022) Prec@1 64.000 (63.617) Prec@5 95.000 (94.983) +2022-11-14 13:15:05,693 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1997 (0.2021) Prec@1 60.000 (63.557) Prec@5 97.000 (95.016) +2022-11-14 13:15:05,702 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1987 (0.2021) Prec@1 65.000 (63.581) Prec@5 95.000 (95.016) +2022-11-14 13:15:05,712 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2204 (0.2024) Prec@1 59.000 (63.508) Prec@5 92.000 (94.968) +2022-11-14 13:15:05,722 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1872 (0.2021) Prec@1 63.000 (63.500) Prec@5 93.000 (94.938) +2022-11-14 13:15:05,731 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2123 (0.2023) Prec@1 63.000 (63.492) Prec@5 91.000 (94.877) +2022-11-14 13:15:05,740 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2220 (0.2026) Prec@1 56.000 (63.379) Prec@5 93.000 (94.848) +2022-11-14 13:15:05,749 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1801 (0.2022) Prec@1 69.000 (63.463) Prec@5 97.000 (94.881) +2022-11-14 13:15:05,758 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2213 (0.2025) Prec@1 62.000 (63.441) Prec@5 89.000 (94.794) +2022-11-14 13:15:05,767 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2034 (0.2025) Prec@1 59.000 (63.377) Prec@5 96.000 (94.812) +2022-11-14 13:15:05,777 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2319 (0.2030) Prec@1 58.000 (63.300) Prec@5 91.000 (94.757) +2022-11-14 13:15:05,786 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2079 (0.2030) Prec@1 64.000 (63.310) Prec@5 99.000 (94.817) +2022-11-14 13:15:05,796 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1854 (0.2028) Prec@1 64.000 (63.319) Prec@5 97.000 (94.847) +2022-11-14 13:15:05,804 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2102 (0.2029) Prec@1 64.000 (63.329) Prec@5 96.000 (94.863) +2022-11-14 13:15:05,812 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2008 (0.2029) Prec@1 65.000 (63.351) Prec@5 95.000 (94.865) +2022-11-14 13:15:05,822 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2111 (0.2030) Prec@1 63.000 (63.347) Prec@5 95.000 (94.867) +2022-11-14 13:15:05,832 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2254 (0.2033) Prec@1 61.000 (63.316) Prec@5 91.000 (94.816) +2022-11-14 13:15:05,841 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1820 (0.2030) Prec@1 69.000 (63.390) Prec@5 94.000 (94.805) +2022-11-14 13:15:05,851 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1937 (0.2029) Prec@1 69.000 (63.462) Prec@5 96.000 (94.821) +2022-11-14 13:15:05,861 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1918 (0.2027) Prec@1 65.000 (63.481) Prec@5 97.000 (94.848) +2022-11-14 13:15:05,869 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2246 (0.2030) Prec@1 58.000 (63.413) Prec@5 95.000 (94.850) +2022-11-14 13:15:05,879 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1883 (0.2028) Prec@1 66.000 (63.444) Prec@5 95.000 (94.852) +2022-11-14 13:15:05,889 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2423 (0.2033) Prec@1 55.000 (63.341) Prec@5 96.000 (94.866) +2022-11-14 13:15:05,898 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2476 (0.2038) Prec@1 52.000 (63.205) Prec@5 95.000 (94.867) +2022-11-14 13:15:05,908 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2037 (0.2038) Prec@1 64.000 (63.214) Prec@5 97.000 (94.893) +2022-11-14 13:15:05,917 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2205 (0.2040) Prec@1 62.000 (63.200) Prec@5 91.000 (94.847) +2022-11-14 13:15:05,926 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2238 (0.2043) Prec@1 58.000 (63.140) Prec@5 96.000 (94.860) +2022-11-14 13:15:05,936 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2259 (0.2045) Prec@1 58.000 (63.080) Prec@5 94.000 (94.851) +2022-11-14 13:15:05,945 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1941 (0.2044) Prec@1 64.000 (63.091) Prec@5 95.000 (94.852) +2022-11-14 13:15:05,955 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1870 (0.2042) Prec@1 71.000 (63.180) Prec@5 94.000 (94.843) +2022-11-14 13:15:05,965 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2209 (0.2044) Prec@1 61.000 (63.156) Prec@5 96.000 (94.856) +2022-11-14 13:15:05,974 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1719 (0.2040) Prec@1 70.000 (63.231) Prec@5 98.000 (94.890) +2022-11-14 13:15:05,984 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1577 (0.2035) Prec@1 70.000 (63.304) Prec@5 96.000 (94.902) +2022-11-14 13:15:05,993 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2218 (0.2037) Prec@1 60.000 (63.269) Prec@5 94.000 (94.892) +2022-11-14 13:15:06,002 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2000 (0.2037) Prec@1 64.000 (63.277) Prec@5 98.000 (94.926) +2022-11-14 13:15:06,012 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2228 (0.2039) Prec@1 59.000 (63.232) Prec@5 92.000 (94.895) +2022-11-14 13:15:06,020 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1878 (0.2037) Prec@1 68.000 (63.281) Prec@5 92.000 (94.865) +2022-11-14 13:15:06,029 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1925 (0.2036) Prec@1 67.000 (63.320) Prec@5 96.000 (94.876) +2022-11-14 13:15:06,038 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2283 (0.2038) Prec@1 60.000 (63.286) Prec@5 92.000 (94.847) +2022-11-14 13:15:06,048 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2036 (0.2038) Prec@1 61.000 (63.263) Prec@5 94.000 (94.838) +2022-11-14 13:15:06,058 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2136 (0.2039) Prec@1 57.000 (63.200) Prec@5 94.000 (94.830) +2022-11-14 13:15:06,125 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:15:06,427 Epoch: [7][0/500] Time 0.024 (0.024) Data 0.221 (0.221) Loss 0.2022 (0.2022) Prec@1 66.000 (66.000) Prec@5 94.000 (94.000) +2022-11-14 13:15:06,634 Epoch: [7][10/500] Time 0.019 (0.019) Data 0.002 (0.022) Loss 0.1669 (0.1846) Prec@1 64.000 (65.000) Prec@5 96.000 (95.000) +2022-11-14 13:15:06,843 Epoch: [7][20/500] Time 0.022 (0.019) Data 0.002 (0.012) Loss 0.1758 (0.1816) Prec@1 67.000 (65.667) Prec@5 96.000 (95.333) +2022-11-14 13:15:07,047 Epoch: [7][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.2094 (0.1886) Prec@1 61.000 (64.500) Prec@5 98.000 (96.000) +2022-11-14 13:15:07,250 Epoch: [7][40/500] Time 0.020 (0.018) Data 0.002 (0.007) Loss 0.1495 (0.1808) Prec@1 74.000 (66.400) Prec@5 98.000 (96.400) +2022-11-14 13:15:07,452 Epoch: [7][50/500] Time 0.015 (0.018) Data 0.002 (0.006) Loss 0.1864 (0.1817) Prec@1 66.000 (66.333) Prec@5 97.000 (96.500) +2022-11-14 13:15:07,653 Epoch: [7][60/500] Time 0.018 (0.018) Data 0.002 (0.005) Loss 0.1545 (0.1778) Prec@1 71.000 (67.000) Prec@5 97.000 (96.571) +2022-11-14 13:15:07,866 Epoch: [7][70/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.1421 (0.1733) Prec@1 75.000 (68.000) Prec@5 98.000 (96.750) +2022-11-14 13:15:08,069 Epoch: [7][80/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.2046 (0.1768) Prec@1 62.000 (67.333) Prec@5 93.000 (96.333) +2022-11-14 13:15:08,278 Epoch: [7][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.1679 (0.1759) Prec@1 68.000 (67.400) Prec@5 98.000 (96.500) +2022-11-14 13:15:08,492 Epoch: [7][100/500] Time 0.018 (0.018) Data 0.001 (0.004) Loss 0.1433 (0.1730) Prec@1 73.000 (67.909) Prec@5 100.000 (96.818) +2022-11-14 13:15:08,725 Epoch: [7][110/500] Time 0.021 (0.019) Data 0.002 (0.004) Loss 0.1724 (0.1729) Prec@1 70.000 (68.083) Prec@5 97.000 (96.833) +2022-11-14 13:15:08,943 Epoch: [7][120/500] Time 0.016 (0.019) Data 0.002 (0.003) Loss 0.1794 (0.1734) Prec@1 67.000 (68.000) Prec@5 96.000 (96.769) +2022-11-14 13:15:09,145 Epoch: [7][130/500] Time 0.016 (0.019) Data 0.001 (0.003) Loss 0.1282 (0.1702) Prec@1 76.000 (68.571) Prec@5 97.000 (96.786) +2022-11-14 13:15:09,340 Epoch: [7][140/500] Time 0.016 (0.019) Data 0.002 (0.003) Loss 0.1677 (0.1700) Prec@1 69.000 (68.600) Prec@5 97.000 (96.800) +2022-11-14 13:15:09,552 Epoch: [7][150/500] Time 0.017 (0.019) Data 0.002 (0.003) Loss 0.1885 (0.1712) Prec@1 69.000 (68.625) Prec@5 95.000 (96.688) +2022-11-14 13:15:09,759 Epoch: [7][160/500] Time 0.017 (0.019) Data 0.001 (0.003) Loss 0.1591 (0.1705) Prec@1 70.000 (68.706) Prec@5 97.000 (96.706) +2022-11-14 13:15:10,042 Epoch: [7][170/500] Time 0.035 (0.019) Data 0.002 (0.003) Loss 0.1427 (0.1689) Prec@1 79.000 (69.278) Prec@5 97.000 (96.722) +2022-11-14 13:15:10,285 Epoch: [7][180/500] Time 0.018 (0.019) Data 0.001 (0.003) Loss 0.1710 (0.1690) Prec@1 70.000 (69.316) Prec@5 96.000 (96.684) +2022-11-14 13:15:10,539 Epoch: [7][190/500] Time 0.017 (0.019) Data 0.001 (0.003) Loss 0.1421 (0.1677) Prec@1 74.000 (69.550) Prec@5 98.000 (96.750) +2022-11-14 13:15:10,769 Epoch: [7][200/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.1853 (0.1685) Prec@1 72.000 (69.667) Prec@5 96.000 (96.714) +2022-11-14 13:15:10,992 Epoch: [7][210/500] Time 0.019 (0.019) Data 0.003 (0.003) Loss 0.1561 (0.1680) Prec@1 74.000 (69.864) Prec@5 98.000 (96.773) +2022-11-14 13:15:11,226 Epoch: [7][220/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.1693 (0.1680) Prec@1 66.000 (69.696) Prec@5 94.000 (96.652) +2022-11-14 13:15:11,439 Epoch: [7][230/500] Time 0.018 (0.019) Data 0.002 (0.003) Loss 0.1565 (0.1675) Prec@1 70.000 (69.708) Prec@5 99.000 (96.750) +2022-11-14 13:15:11,770 Epoch: [7][240/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.1933 (0.1686) Prec@1 63.000 (69.440) Prec@5 93.000 (96.600) +2022-11-14 13:15:12,096 Epoch: [7][250/500] Time 0.032 (0.020) Data 0.002 (0.003) Loss 0.1847 (0.1692) Prec@1 60.000 (69.077) Prec@5 94.000 (96.500) +2022-11-14 13:15:12,394 Epoch: [7][260/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.1668 (0.1691) Prec@1 72.000 (69.185) Prec@5 95.000 (96.444) +2022-11-14 13:15:12,687 Epoch: [7][270/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.1885 (0.1698) Prec@1 63.000 (68.964) Prec@5 97.000 (96.464) +2022-11-14 13:15:12,991 Epoch: [7][280/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.1660 (0.1697) Prec@1 67.000 (68.897) Prec@5 97.000 (96.483) +2022-11-14 13:15:13,251 Epoch: [7][290/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.1581 (0.1693) Prec@1 74.000 (69.067) Prec@5 95.000 (96.433) +2022-11-14 13:15:13,531 Epoch: [7][300/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.1545 (0.1688) Prec@1 73.000 (69.194) Prec@5 97.000 (96.452) +2022-11-14 13:15:13,785 Epoch: [7][310/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.1701 (0.1688) Prec@1 70.000 (69.219) Prec@5 96.000 (96.438) +2022-11-14 13:15:13,988 Epoch: [7][320/500] Time 0.018 (0.021) Data 0.001 (0.002) Loss 0.1953 (0.1696) Prec@1 61.000 (68.970) Prec@5 98.000 (96.485) +2022-11-14 13:15:14,247 Epoch: [7][330/500] Time 0.018 (0.021) Data 0.001 (0.002) Loss 0.1730 (0.1697) Prec@1 73.000 (69.088) Prec@5 94.000 (96.412) +2022-11-14 13:15:14,451 Epoch: [7][340/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.1667 (0.1696) Prec@1 68.000 (69.057) Prec@5 97.000 (96.429) +2022-11-14 13:15:14,661 Epoch: [7][350/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.1675 (0.1696) Prec@1 69.000 (69.056) Prec@5 94.000 (96.361) +2022-11-14 13:15:14,860 Epoch: [7][360/500] Time 0.017 (0.021) Data 0.001 (0.002) Loss 0.1402 (0.1688) Prec@1 75.000 (69.216) Prec@5 98.000 (96.405) +2022-11-14 13:15:15,056 Epoch: [7][370/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.1748 (0.1690) Prec@1 66.000 (69.132) Prec@5 97.000 (96.421) +2022-11-14 13:15:15,253 Epoch: [7][380/500] Time 0.017 (0.021) Data 0.001 (0.002) Loss 0.1893 (0.1695) Prec@1 68.000 (69.103) Prec@5 92.000 (96.308) +2022-11-14 13:15:15,450 Epoch: [7][390/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.1598 (0.1692) Prec@1 73.000 (69.200) Prec@5 96.000 (96.300) +2022-11-14 13:15:15,666 Epoch: [7][400/500] Time 0.019 (0.021) Data 0.001 (0.002) Loss 0.1549 (0.1689) Prec@1 77.000 (69.390) Prec@5 94.000 (96.244) +2022-11-14 13:15:15,890 Epoch: [7][410/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.1894 (0.1694) Prec@1 68.000 (69.357) Prec@5 97.000 (96.262) +2022-11-14 13:15:16,100 Epoch: [7][420/500] Time 0.018 (0.020) Data 0.002 (0.002) Loss 0.1583 (0.1691) Prec@1 66.000 (69.279) Prec@5 99.000 (96.326) +2022-11-14 13:15:16,302 Epoch: [7][430/500] Time 0.017 (0.020) Data 0.002 (0.002) Loss 0.1786 (0.1693) Prec@1 67.000 (69.227) Prec@5 96.000 (96.318) +2022-11-14 13:15:16,501 Epoch: [7][440/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1726 (0.1694) Prec@1 69.000 (69.222) Prec@5 98.000 (96.356) +2022-11-14 13:15:16,700 Epoch: [7][450/500] Time 0.018 (0.020) Data 0.002 (0.002) Loss 0.1668 (0.1693) Prec@1 73.000 (69.304) Prec@5 99.000 (96.413) +2022-11-14 13:15:16,905 Epoch: [7][460/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1852 (0.1697) Prec@1 67.000 (69.255) Prec@5 97.000 (96.426) +2022-11-14 13:15:17,115 Epoch: [7][470/500] Time 0.017 (0.020) Data 0.002 (0.002) Loss 0.1722 (0.1697) Prec@1 68.000 (69.229) Prec@5 97.000 (96.438) +2022-11-14 13:15:17,311 Epoch: [7][480/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1243 (0.1688) Prec@1 80.000 (69.449) Prec@5 99.000 (96.490) +2022-11-14 13:15:17,506 Epoch: [7][490/500] Time 0.018 (0.020) Data 0.001 (0.002) Loss 0.1476 (0.1684) Prec@1 71.000 (69.480) Prec@5 96.000 (96.480) +2022-11-14 13:15:17,681 Epoch: [7][499/500] Time 0.017 (0.020) Data 0.001 (0.002) Loss 0.1937 (0.1689) Prec@1 65.000 (69.392) Prec@5 94.000 (96.431) +2022-11-14 13:15:17,975 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1923 (0.1923) Prec@1 66.000 (66.000) Prec@5 96.000 (96.000) +2022-11-14 13:15:17,983 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2276 (0.2099) Prec@1 55.000 (60.500) Prec@5 94.000 (95.000) +2022-11-14 13:15:17,991 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1836 (0.2012) Prec@1 65.000 (62.000) Prec@5 95.000 (95.000) +2022-11-14 13:15:18,002 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2188 (0.2056) Prec@1 58.000 (61.000) Prec@5 93.000 (94.500) +2022-11-14 13:15:18,011 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2047 (0.2054) Prec@1 65.000 (61.800) Prec@5 95.000 (94.600) +2022-11-14 13:15:18,019 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1738 (0.2001) Prec@1 68.000 (62.833) Prec@5 94.000 (94.500) +2022-11-14 13:15:18,027 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2056 (0.2009) Prec@1 62.000 (62.714) Prec@5 96.000 (94.714) +2022-11-14 13:15:18,037 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2356 (0.2052) Prec@1 56.000 (61.875) Prec@5 91.000 (94.250) +2022-11-14 13:15:18,046 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2201 (0.2069) Prec@1 59.000 (61.556) Prec@5 96.000 (94.444) +2022-11-14 13:15:18,055 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2155 (0.2078) Prec@1 57.000 (61.100) Prec@5 92.000 (94.200) +2022-11-14 13:15:18,064 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1649 (0.2039) Prec@1 69.000 (61.818) Prec@5 96.000 (94.364) +2022-11-14 13:15:18,074 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2178 (0.2050) Prec@1 59.000 (61.583) Prec@5 97.000 (94.583) +2022-11-14 13:15:18,083 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2071 (0.2052) Prec@1 64.000 (61.769) Prec@5 96.000 (94.692) +2022-11-14 13:15:18,092 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1874 (0.2039) Prec@1 66.000 (62.071) Prec@5 95.000 (94.714) +2022-11-14 13:15:18,101 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2039 (0.2039) Prec@1 61.000 (62.000) Prec@5 96.000 (94.800) +2022-11-14 13:15:18,111 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2184 (0.2048) Prec@1 61.000 (61.938) Prec@5 92.000 (94.625) +2022-11-14 13:15:18,119 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1904 (0.2040) Prec@1 61.000 (61.882) Prec@5 93.000 (94.529) +2022-11-14 13:15:18,129 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1999 (0.2037) Prec@1 63.000 (61.944) Prec@5 97.000 (94.667) +2022-11-14 13:15:18,137 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2031 (0.2037) Prec@1 59.000 (61.789) Prec@5 92.000 (94.526) +2022-11-14 13:15:18,146 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.2025) Prec@1 66.000 (62.000) Prec@5 93.000 (94.450) +2022-11-14 13:15:18,155 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2274 (0.2036) Prec@1 61.000 (61.952) Prec@5 91.000 (94.286) +2022-11-14 13:15:18,164 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2114 (0.2040) Prec@1 58.000 (61.773) Prec@5 96.000 (94.364) +2022-11-14 13:15:18,172 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2083 (0.2042) Prec@1 66.000 (61.957) Prec@5 89.000 (94.130) +2022-11-14 13:15:18,181 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2048 (0.2042) Prec@1 62.000 (61.958) Prec@5 94.000 (94.125) +2022-11-14 13:15:18,190 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2194 (0.2048) Prec@1 59.000 (61.840) Prec@5 96.000 (94.200) +2022-11-14 13:15:18,199 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2480 (0.2065) Prec@1 57.000 (61.654) Prec@5 91.000 (94.077) +2022-11-14 13:15:18,208 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1925 (0.2060) Prec@1 64.000 (61.741) Prec@5 97.000 (94.185) +2022-11-14 13:15:18,217 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1832 (0.2051) Prec@1 61.000 (61.714) Prec@5 99.000 (94.357) +2022-11-14 13:15:18,227 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.2046) Prec@1 66.000 (61.862) Prec@5 96.000 (94.414) +2022-11-14 13:15:18,236 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2167 (0.2050) Prec@1 61.000 (61.833) Prec@5 89.000 (94.233) +2022-11-14 13:15:18,244 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1812 (0.2042) Prec@1 65.000 (61.935) Prec@5 96.000 (94.290) +2022-11-14 13:15:18,254 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2063 (0.2043) Prec@1 63.000 (61.969) Prec@5 90.000 (94.156) +2022-11-14 13:15:18,263 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2003 (0.2041) Prec@1 67.000 (62.121) Prec@5 92.000 (94.091) +2022-11-14 13:15:18,272 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2446 (0.2053) Prec@1 50.000 (61.765) Prec@5 91.000 (94.000) +2022-11-14 13:15:18,280 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2216 (0.2058) Prec@1 58.000 (61.657) Prec@5 96.000 (94.057) +2022-11-14 13:15:18,290 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1991 (0.2056) Prec@1 63.000 (61.694) Prec@5 95.000 (94.083) +2022-11-14 13:15:18,299 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2028 (0.2055) Prec@1 66.000 (61.811) Prec@5 95.000 (94.108) +2022-11-14 13:15:18,307 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2350 (0.2063) Prec@1 58.000 (61.711) Prec@5 94.000 (94.105) +2022-11-14 13:15:18,316 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2056 (0.2063) Prec@1 64.000 (61.769) Prec@5 90.000 (94.000) +2022-11-14 13:15:18,326 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1965 (0.2060) Prec@1 60.000 (61.725) Prec@5 95.000 (94.025) +2022-11-14 13:15:18,334 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1908 (0.2057) Prec@1 66.000 (61.829) Prec@5 96.000 (94.073) +2022-11-14 13:15:18,344 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1843 (0.2052) Prec@1 70.000 (62.024) Prec@5 94.000 (94.071) +2022-11-14 13:15:18,353 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1629 (0.2042) Prec@1 73.000 (62.279) Prec@5 98.000 (94.163) +2022-11-14 13:15:18,362 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1913 (0.2039) Prec@1 64.000 (62.318) Prec@5 97.000 (94.227) +2022-11-14 13:15:18,372 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2033 (0.2039) Prec@1 65.000 (62.378) Prec@5 96.000 (94.267) +2022-11-14 13:15:18,381 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2166 (0.2042) Prec@1 59.000 (62.304) Prec@5 92.000 (94.217) +2022-11-14 13:15:18,389 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1654 (0.2033) Prec@1 71.000 (62.489) Prec@5 97.000 (94.277) +2022-11-14 13:15:18,401 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1727 (0.2027) Prec@1 72.000 (62.688) Prec@5 94.000 (94.271) +2022-11-14 13:15:18,412 Test: [48/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1773 (0.2022) Prec@1 65.000 (62.735) Prec@5 96.000 (94.306) +2022-11-14 13:15:18,421 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2060 (0.2023) Prec@1 58.000 (62.640) Prec@5 96.000 (94.340) +2022-11-14 13:15:18,429 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1873 (0.2020) Prec@1 66.000 (62.706) Prec@5 96.000 (94.373) +2022-11-14 13:15:18,437 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2177 (0.2023) Prec@1 61.000 (62.673) Prec@5 95.000 (94.385) +2022-11-14 13:15:18,445 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1890 (0.2020) Prec@1 61.000 (62.642) Prec@5 94.000 (94.377) +2022-11-14 13:15:18,454 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1976 (0.2019) Prec@1 62.000 (62.630) Prec@5 95.000 (94.389) +2022-11-14 13:15:18,463 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1976 (0.2018) Prec@1 61.000 (62.600) Prec@5 98.000 (94.455) +2022-11-14 13:15:18,473 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2092 (0.2020) Prec@1 61.000 (62.571) Prec@5 95.000 (94.464) +2022-11-14 13:15:18,483 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1818 (0.2016) Prec@1 71.000 (62.719) Prec@5 96.000 (94.491) +2022-11-14 13:15:18,493 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1859 (0.2014) Prec@1 65.000 (62.759) Prec@5 95.000 (94.500) +2022-11-14 13:15:18,503 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2187 (0.2017) Prec@1 58.000 (62.678) Prec@5 98.000 (94.559) +2022-11-14 13:15:18,513 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1888 (0.2014) Prec@1 65.000 (62.717) Prec@5 96.000 (94.583) +2022-11-14 13:15:18,523 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1814 (0.2011) Prec@1 67.000 (62.787) Prec@5 94.000 (94.574) +2022-11-14 13:15:18,532 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2278 (0.2015) Prec@1 52.000 (62.613) Prec@5 91.000 (94.516) +2022-11-14 13:15:18,541 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1888 (0.2013) Prec@1 62.000 (62.603) Prec@5 100.000 (94.603) +2022-11-14 13:15:18,549 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1906 (0.2012) Prec@1 63.000 (62.609) Prec@5 96.000 (94.625) +2022-11-14 13:15:18,559 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2380 (0.2017) Prec@1 56.000 (62.508) Prec@5 93.000 (94.600) +2022-11-14 13:15:18,569 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1901 (0.2016) Prec@1 65.000 (62.545) Prec@5 97.000 (94.636) +2022-11-14 13:15:18,578 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2046 (0.2016) Prec@1 64.000 (62.567) Prec@5 94.000 (94.627) +2022-11-14 13:15:18,587 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2434 (0.2022) Prec@1 60.000 (62.529) Prec@5 95.000 (94.632) +2022-11-14 13:15:18,597 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1912 (0.2021) Prec@1 65.000 (62.565) Prec@5 96.000 (94.652) +2022-11-14 13:15:18,606 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2422 (0.2026) Prec@1 57.000 (62.486) Prec@5 90.000 (94.586) +2022-11-14 13:15:18,616 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.2028) Prec@1 60.000 (62.451) Prec@5 97.000 (94.620) +2022-11-14 13:15:18,627 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1900 (0.2026) Prec@1 67.000 (62.514) Prec@5 97.000 (94.653) +2022-11-14 13:15:18,639 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1896 (0.2024) Prec@1 64.000 (62.534) Prec@5 96.000 (94.671) +2022-11-14 13:15:18,649 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1706 (0.2020) Prec@1 70.000 (62.635) Prec@5 94.000 (94.662) +2022-11-14 13:15:18,658 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2236 (0.2023) Prec@1 57.000 (62.560) Prec@5 95.000 (94.667) +2022-11-14 13:15:18,667 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2220 (0.2025) Prec@1 56.000 (62.474) Prec@5 94.000 (94.658) +2022-11-14 13:15:18,676 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2353 (0.2030) Prec@1 55.000 (62.377) Prec@5 95.000 (94.662) +2022-11-14 13:15:18,685 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.2028) Prec@1 67.000 (62.436) Prec@5 97.000 (94.692) +2022-11-14 13:15:18,693 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1994 (0.2027) Prec@1 68.000 (62.506) Prec@5 96.000 (94.709) +2022-11-14 13:15:18,701 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2135 (0.2029) Prec@1 59.000 (62.462) Prec@5 93.000 (94.688) +2022-11-14 13:15:18,709 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1666 (0.2024) Prec@1 70.000 (62.556) Prec@5 94.000 (94.679) +2022-11-14 13:15:18,717 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1964 (0.2023) Prec@1 65.000 (62.585) Prec@5 92.000 (94.646) +2022-11-14 13:15:18,726 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1847 (0.2021) Prec@1 65.000 (62.614) Prec@5 95.000 (94.651) +2022-11-14 13:15:18,735 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2321 (0.2025) Prec@1 60.000 (62.583) Prec@5 94.000 (94.643) +2022-11-14 13:15:18,745 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2125 (0.2026) Prec@1 56.000 (62.506) Prec@5 93.000 (94.624) +2022-11-14 13:15:18,753 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1875 (0.2024) Prec@1 68.000 (62.570) Prec@5 90.000 (94.570) +2022-11-14 13:15:18,763 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2136 (0.2026) Prec@1 64.000 (62.586) Prec@5 95.000 (94.575) +2022-11-14 13:15:18,772 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2193 (0.2027) Prec@1 60.000 (62.557) Prec@5 95.000 (94.580) +2022-11-14 13:15:18,781 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2339 (0.2031) Prec@1 56.000 (62.483) Prec@5 92.000 (94.551) +2022-11-14 13:15:18,789 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2049 (0.2031) Prec@1 61.000 (62.467) Prec@5 95.000 (94.556) +2022-11-14 13:15:18,798 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2126 (0.2032) Prec@1 62.000 (62.462) Prec@5 95.000 (94.560) +2022-11-14 13:15:18,807 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1555 (0.2027) Prec@1 73.000 (62.576) Prec@5 94.000 (94.554) +2022-11-14 13:15:18,816 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2331 (0.2030) Prec@1 60.000 (62.548) Prec@5 95.000 (94.559) +2022-11-14 13:15:18,824 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2238 (0.2033) Prec@1 58.000 (62.500) Prec@5 94.000 (94.553) +2022-11-14 13:15:18,833 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1922 (0.2031) Prec@1 61.000 (62.484) Prec@5 96.000 (94.568) +2022-11-14 13:15:18,842 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1686 (0.2028) Prec@1 67.000 (62.531) Prec@5 97.000 (94.594) +2022-11-14 13:15:18,850 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1895 (0.2026) Prec@1 65.000 (62.557) Prec@5 98.000 (94.629) +2022-11-14 13:15:18,859 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2606 (0.2032) Prec@1 51.000 (62.439) Prec@5 90.000 (94.582) +2022-11-14 13:15:18,867 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1998 (0.2032) Prec@1 63.000 (62.444) Prec@5 93.000 (94.566) +2022-11-14 13:15:18,876 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1955 (0.2031) Prec@1 66.000 (62.480) Prec@5 91.000 (94.530) +2022-11-14 13:15:18,932 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:15:19,230 Epoch: [8][0/500] Time 0.025 (0.025) Data 0.213 (0.213) Loss 0.1392 (0.1392) Prec@1 79.000 (79.000) Prec@5 99.000 (99.000) +2022-11-14 13:15:19,442 Epoch: [8][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.1822 (0.1607) Prec@1 68.000 (73.500) Prec@5 98.000 (98.500) +2022-11-14 13:15:19,657 Epoch: [8][20/500] Time 0.019 (0.019) Data 0.002 (0.012) Loss 0.1459 (0.1558) Prec@1 76.000 (74.333) Prec@5 98.000 (98.333) +2022-11-14 13:15:19,857 Epoch: [8][30/500] Time 0.018 (0.019) Data 0.001 (0.008) Loss 0.1751 (0.1606) Prec@1 63.000 (71.500) Prec@5 97.000 (98.000) +2022-11-14 13:15:20,053 Epoch: [8][40/500] Time 0.020 (0.018) Data 0.001 (0.007) Loss 0.1585 (0.1602) Prec@1 75.000 (72.200) Prec@5 99.000 (98.200) +2022-11-14 13:15:20,251 Epoch: [8][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.1672 (0.1613) Prec@1 71.000 (72.000) Prec@5 97.000 (98.000) +2022-11-14 13:15:20,444 Epoch: [8][60/500] Time 0.018 (0.018) Data 0.001 (0.005) Loss 0.1313 (0.1570) Prec@1 74.000 (72.286) Prec@5 99.000 (98.143) +2022-11-14 13:15:20,637 Epoch: [8][70/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.1921 (0.1614) Prec@1 64.000 (71.250) Prec@5 98.000 (98.125) +2022-11-14 13:15:20,843 Epoch: [8][80/500] Time 0.018 (0.018) Data 0.001 (0.004) Loss 0.1679 (0.1621) Prec@1 68.000 (70.889) Prec@5 99.000 (98.222) +2022-11-14 13:15:21,044 Epoch: [8][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.1660 (0.1625) Prec@1 68.000 (70.600) Prec@5 96.000 (98.000) +2022-11-14 13:15:21,316 Epoch: [8][100/500] Time 0.030 (0.019) Data 0.002 (0.004) Loss 0.1545 (0.1618) Prec@1 70.000 (70.545) Prec@5 94.000 (97.636) +2022-11-14 13:15:21,515 Epoch: [8][110/500] Time 0.017 (0.019) Data 0.001 (0.004) Loss 0.1643 (0.1620) Prec@1 69.000 (70.417) Prec@5 95.000 (97.417) +2022-11-14 13:15:21,713 Epoch: [8][120/500] Time 0.020 (0.018) Data 0.001 (0.003) Loss 0.1280 (0.1594) Prec@1 80.000 (71.154) Prec@5 100.000 (97.615) +2022-11-14 13:15:21,919 Epoch: [8][130/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.1336 (0.1575) Prec@1 81.000 (71.857) Prec@5 97.000 (97.571) +2022-11-14 13:15:22,111 Epoch: [8][140/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.1893 (0.1597) Prec@1 65.000 (71.400) Prec@5 95.000 (97.400) +2022-11-14 13:15:22,305 Epoch: [8][150/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.1726 (0.1605) Prec@1 68.000 (71.188) Prec@5 98.000 (97.438) +2022-11-14 13:15:22,498 Epoch: [8][160/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.1624 (0.1606) Prec@1 71.000 (71.176) Prec@5 96.000 (97.353) +2022-11-14 13:15:22,695 Epoch: [8][170/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.1384 (0.1594) Prec@1 78.000 (71.556) Prec@5 98.000 (97.389) +2022-11-14 13:15:22,895 Epoch: [8][180/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.1902 (0.1610) Prec@1 67.000 (71.316) Prec@5 94.000 (97.211) +2022-11-14 13:15:23,101 Epoch: [8][190/500] Time 0.018 (0.018) Data 0.002 (0.003) Loss 0.1661 (0.1612) Prec@1 69.000 (71.200) Prec@5 97.000 (97.200) +2022-11-14 13:15:23,300 Epoch: [8][200/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.1929 (0.1627) Prec@1 64.000 (70.857) Prec@5 97.000 (97.190) +2022-11-14 13:15:23,580 Epoch: [8][210/500] Time 0.031 (0.018) Data 0.002 (0.003) Loss 0.2088 (0.1648) Prec@1 61.000 (70.409) Prec@5 93.000 (97.000) +2022-11-14 13:15:23,784 Epoch: [8][220/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.1490 (0.1641) Prec@1 73.000 (70.522) Prec@5 98.000 (97.043) +2022-11-14 13:15:23,984 Epoch: [8][230/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.1830 (0.1649) Prec@1 66.000 (70.333) Prec@5 95.000 (96.958) +2022-11-14 13:15:24,209 Epoch: [8][240/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.1750 (0.1653) Prec@1 63.000 (70.040) Prec@5 99.000 (97.040) +2022-11-14 13:15:24,408 Epoch: [8][250/500] Time 0.018 (0.018) Data 0.001 (0.002) Loss 0.1829 (0.1660) Prec@1 68.000 (69.962) Prec@5 97.000 (97.038) +2022-11-14 13:15:24,640 Epoch: [8][260/500] Time 0.022 (0.018) Data 0.002 (0.002) Loss 0.1489 (0.1654) Prec@1 70.000 (69.963) Prec@5 97.000 (97.037) +2022-11-14 13:15:24,885 Epoch: [8][270/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.1866 (0.1661) Prec@1 65.000 (69.786) Prec@5 98.000 (97.071) +2022-11-14 13:15:25,135 Epoch: [8][280/500] Time 0.021 (0.019) Data 0.002 (0.002) Loss 0.1267 (0.1648) Prec@1 78.000 (70.069) Prec@5 99.000 (97.138) +2022-11-14 13:15:25,384 Epoch: [8][290/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.1348 (0.1638) Prec@1 76.000 (70.267) Prec@5 99.000 (97.200) +2022-11-14 13:15:25,635 Epoch: [8][300/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.1547 (0.1635) Prec@1 75.000 (70.419) Prec@5 98.000 (97.226) +2022-11-14 13:15:25,956 Epoch: [8][310/500] Time 0.035 (0.019) Data 0.002 (0.002) Loss 0.1902 (0.1643) Prec@1 67.000 (70.312) Prec@5 94.000 (97.125) +2022-11-14 13:15:26,190 Epoch: [8][320/500] Time 0.021 (0.019) Data 0.002 (0.002) Loss 0.1776 (0.1647) Prec@1 65.000 (70.152) Prec@5 98.000 (97.152) +2022-11-14 13:15:26,439 Epoch: [8][330/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.1809 (0.1652) Prec@1 67.000 (70.059) Prec@5 97.000 (97.147) +2022-11-14 13:15:26,690 Epoch: [8][340/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.1651 (0.1652) Prec@1 69.000 (70.029) Prec@5 95.000 (97.086) +2022-11-14 13:15:26,941 Epoch: [8][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1561 (0.1649) Prec@1 71.000 (70.056) Prec@5 98.000 (97.111) +2022-11-14 13:15:27,189 Epoch: [8][360/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.2014 (0.1659) Prec@1 63.000 (69.865) Prec@5 96.000 (97.081) +2022-11-14 13:15:27,437 Epoch: [8][370/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1750 (0.1662) Prec@1 70.000 (69.868) Prec@5 100.000 (97.158) +2022-11-14 13:15:27,684 Epoch: [8][380/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.1561 (0.1659) Prec@1 71.000 (69.897) Prec@5 95.000 (97.103) +2022-11-14 13:15:27,933 Epoch: [8][390/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1482 (0.1655) Prec@1 79.000 (70.125) Prec@5 98.000 (97.125) +2022-11-14 13:15:28,181 Epoch: [8][400/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.1584 (0.1653) Prec@1 70.000 (70.122) Prec@5 98.000 (97.146) +2022-11-14 13:15:28,434 Epoch: [8][410/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1179 (0.1642) Prec@1 83.000 (70.429) Prec@5 95.000 (97.095) +2022-11-14 13:15:28,683 Epoch: [8][420/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.1523 (0.1639) Prec@1 71.000 (70.442) Prec@5 99.000 (97.140) +2022-11-14 13:15:28,934 Epoch: [8][430/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1530 (0.1636) Prec@1 71.000 (70.455) Prec@5 100.000 (97.205) +2022-11-14 13:15:29,184 Epoch: [8][440/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.1554 (0.1635) Prec@1 76.000 (70.578) Prec@5 97.000 (97.200) +2022-11-14 13:15:29,433 Epoch: [8][450/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.1761 (0.1637) Prec@1 65.000 (70.457) Prec@5 100.000 (97.261) +2022-11-14 13:15:29,680 Epoch: [8][460/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.2132 (0.1648) Prec@1 63.000 (70.298) Prec@5 97.000 (97.255) +2022-11-14 13:15:29,931 Epoch: [8][470/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.1440 (0.1643) Prec@1 71.000 (70.312) Prec@5 99.000 (97.292) +2022-11-14 13:15:30,183 Epoch: [8][480/500] Time 0.018 (0.020) Data 0.002 (0.002) Loss 0.1659 (0.1644) Prec@1 69.000 (70.286) Prec@5 100.000 (97.347) +2022-11-14 13:15:30,429 Epoch: [8][490/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.1730 (0.1646) Prec@1 68.000 (70.240) Prec@5 97.000 (97.340) +2022-11-14 13:15:30,652 Epoch: [8][499/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.1873 (0.1650) Prec@1 67.000 (70.176) Prec@5 95.000 (97.294) +2022-11-14 13:15:30,923 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1770 (0.1770) Prec@1 68.000 (68.000) Prec@5 95.000 (95.000) +2022-11-14 13:15:30,933 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1766 (0.1768) Prec@1 68.000 (68.000) Prec@5 95.000 (95.000) +2022-11-14 13:15:30,943 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1753 (0.1763) Prec@1 70.000 (68.667) Prec@5 96.000 (95.333) +2022-11-14 13:15:30,955 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1895 (0.1796) Prec@1 66.000 (68.000) Prec@5 98.000 (96.000) +2022-11-14 13:15:30,964 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1848 (0.1806) Prec@1 67.000 (67.800) Prec@5 95.000 (95.800) +2022-11-14 13:15:30,972 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1725) Prec@1 73.000 (68.667) Prec@5 98.000 (96.167) +2022-11-14 13:15:30,980 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1880 (0.1747) Prec@1 66.000 (68.286) Prec@5 98.000 (96.429) +2022-11-14 13:15:30,990 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2100 (0.1791) Prec@1 67.000 (68.125) Prec@5 94.000 (96.125) +2022-11-14 13:15:30,998 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2059 (0.1821) Prec@1 61.000 (67.333) Prec@5 89.000 (95.333) +2022-11-14 13:15:31,007 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1386 (0.1778) Prec@1 74.000 (68.000) Prec@5 93.000 (95.100) +2022-11-14 13:15:31,016 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1454 (0.1748) Prec@1 78.000 (68.909) Prec@5 94.000 (95.000) +2022-11-14 13:15:31,025 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1924 (0.1763) Prec@1 61.000 (68.250) Prec@5 95.000 (95.000) +2022-11-14 13:15:31,034 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1834 (0.1768) Prec@1 65.000 (68.000) Prec@5 97.000 (95.154) +2022-11-14 13:15:31,045 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1549 (0.1753) Prec@1 71.000 (68.214) Prec@5 95.000 (95.143) +2022-11-14 13:15:31,055 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1542 (0.1739) Prec@1 71.000 (68.400) Prec@5 96.000 (95.200) +2022-11-14 13:15:31,064 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2161 (0.1765) Prec@1 60.000 (67.875) Prec@5 94.000 (95.125) +2022-11-14 13:15:31,073 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1787 (0.1766) Prec@1 67.000 (67.824) Prec@5 93.000 (95.000) +2022-11-14 13:15:31,083 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1855 (0.1771) Prec@1 66.000 (67.722) Prec@5 97.000 (95.111) +2022-11-14 13:15:31,092 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1782 (0.1772) Prec@1 65.000 (67.579) Prec@5 96.000 (95.158) +2022-11-14 13:15:31,101 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2154 (0.1791) Prec@1 61.000 (67.250) Prec@5 92.000 (95.000) +2022-11-14 13:15:31,111 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2093 (0.1805) Prec@1 63.000 (67.048) Prec@5 93.000 (94.905) +2022-11-14 13:15:31,120 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1804 (0.1805) Prec@1 70.000 (67.182) Prec@5 97.000 (95.000) +2022-11-14 13:15:31,130 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1800 (0.1805) Prec@1 67.000 (67.174) Prec@5 92.000 (94.870) +2022-11-14 13:15:31,139 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1605 (0.1797) Prec@1 68.000 (67.208) Prec@5 94.000 (94.833) +2022-11-14 13:15:31,149 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1667 (0.1792) Prec@1 67.000 (67.200) Prec@5 98.000 (94.960) +2022-11-14 13:15:31,157 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2017 (0.1800) Prec@1 69.000 (67.269) Prec@5 93.000 (94.885) +2022-11-14 13:15:31,165 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1798) Prec@1 66.000 (67.222) Prec@5 95.000 (94.889) +2022-11-14 13:15:31,174 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1825 (0.1799) Prec@1 67.000 (67.214) Prec@5 94.000 (94.857) +2022-11-14 13:15:31,183 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1839 (0.1801) Prec@1 68.000 (67.241) Prec@5 93.000 (94.793) +2022-11-14 13:15:31,192 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1612 (0.1794) Prec@1 70.000 (67.333) Prec@5 98.000 (94.900) +2022-11-14 13:15:31,200 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1614 (0.1789) Prec@1 73.000 (67.516) Prec@5 93.000 (94.839) +2022-11-14 13:15:31,208 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1675 (0.1785) Prec@1 72.000 (67.656) Prec@5 97.000 (94.906) +2022-11-14 13:15:31,216 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1783) Prec@1 66.000 (67.606) Prec@5 96.000 (94.939) +2022-11-14 13:15:31,226 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2167 (0.1794) Prec@1 59.000 (67.353) Prec@5 91.000 (94.824) +2022-11-14 13:15:31,235 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1781 (0.1793) Prec@1 72.000 (67.486) Prec@5 94.000 (94.800) +2022-11-14 13:15:31,244 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1661 (0.1790) Prec@1 71.000 (67.583) Prec@5 95.000 (94.806) +2022-11-14 13:15:31,254 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1956 (0.1794) Prec@1 67.000 (67.568) Prec@5 94.000 (94.784) +2022-11-14 13:15:31,263 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1770 (0.1794) Prec@1 71.000 (67.658) Prec@5 94.000 (94.763) +2022-11-14 13:15:31,272 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1537 (0.1787) Prec@1 70.000 (67.718) Prec@5 95.000 (94.769) +2022-11-14 13:15:31,282 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1421 (0.1778) Prec@1 77.000 (67.950) Prec@5 94.000 (94.750) +2022-11-14 13:15:31,291 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1615 (0.1774) Prec@1 73.000 (68.073) Prec@5 93.000 (94.707) +2022-11-14 13:15:31,300 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2001 (0.1779) Prec@1 66.000 (68.024) Prec@5 91.000 (94.619) +2022-11-14 13:15:31,310 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1410 (0.1771) Prec@1 79.000 (68.279) Prec@5 95.000 (94.628) +2022-11-14 13:15:31,319 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1796 (0.1771) Prec@1 69.000 (68.295) Prec@5 95.000 (94.636) +2022-11-14 13:15:31,328 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1861 (0.1773) Prec@1 73.000 (68.400) Prec@5 95.000 (94.644) +2022-11-14 13:15:31,337 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2006 (0.1778) Prec@1 62.000 (68.261) Prec@5 90.000 (94.543) +2022-11-14 13:15:31,347 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1846 (0.1780) Prec@1 68.000 (68.255) Prec@5 96.000 (94.574) +2022-11-14 13:15:31,356 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1529 (0.1775) Prec@1 76.000 (68.417) Prec@5 93.000 (94.542) +2022-11-14 13:15:31,365 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1427 (0.1767) Prec@1 73.000 (68.510) Prec@5 95.000 (94.551) +2022-11-14 13:15:31,374 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2000 (0.1772) Prec@1 66.000 (68.460) Prec@5 94.000 (94.540) +2022-11-14 13:15:31,383 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1504 (0.1767) Prec@1 73.000 (68.549) Prec@5 95.000 (94.549) +2022-11-14 13:15:31,393 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1717 (0.1766) Prec@1 71.000 (68.596) Prec@5 95.000 (94.558) +2022-11-14 13:15:31,402 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1656 (0.1764) Prec@1 70.000 (68.623) Prec@5 93.000 (94.528) +2022-11-14 13:15:31,411 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1521 (0.1759) Prec@1 72.000 (68.685) Prec@5 94.000 (94.519) +2022-11-14 13:15:31,420 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1948 (0.1763) Prec@1 67.000 (68.655) Prec@5 95.000 (94.527) +2022-11-14 13:15:31,430 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1823 (0.1764) Prec@1 71.000 (68.696) Prec@5 89.000 (94.429) +2022-11-14 13:15:31,439 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1600 (0.1761) Prec@1 70.000 (68.719) Prec@5 93.000 (94.404) +2022-11-14 13:15:31,448 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1692 (0.1760) Prec@1 66.000 (68.672) Prec@5 95.000 (94.414) +2022-11-14 13:15:31,456 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2294 (0.1769) Prec@1 60.000 (68.525) Prec@5 87.000 (94.288) +2022-11-14 13:15:31,464 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1774 (0.1769) Prec@1 69.000 (68.533) Prec@5 91.000 (94.233) +2022-11-14 13:15:31,472 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2016 (0.1773) Prec@1 61.000 (68.410) Prec@5 97.000 (94.279) +2022-11-14 13:15:31,481 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1920 (0.1775) Prec@1 64.000 (68.339) Prec@5 94.000 (94.274) +2022-11-14 13:15:31,490 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1854 (0.1777) Prec@1 67.000 (68.317) Prec@5 96.000 (94.302) +2022-11-14 13:15:31,500 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1585 (0.1774) Prec@1 71.000 (68.359) Prec@5 97.000 (94.344) +2022-11-14 13:15:31,509 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1472 (0.1769) Prec@1 74.000 (68.446) Prec@5 98.000 (94.400) +2022-11-14 13:15:31,518 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1899 (0.1771) Prec@1 66.000 (68.409) Prec@5 92.000 (94.364) +2022-11-14 13:15:31,527 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1728 (0.1770) Prec@1 70.000 (68.433) Prec@5 99.000 (94.433) +2022-11-14 13:15:31,536 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2356 (0.1779) Prec@1 58.000 (68.279) Prec@5 91.000 (94.382) +2022-11-14 13:15:31,545 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1829 (0.1780) Prec@1 70.000 (68.304) Prec@5 94.000 (94.377) +2022-11-14 13:15:31,554 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2018 (0.1783) Prec@1 67.000 (68.286) Prec@5 91.000 (94.329) +2022-11-14 13:15:31,563 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1732 (0.1782) Prec@1 69.000 (68.296) Prec@5 91.000 (94.282) +2022-11-14 13:15:31,573 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1407 (0.1777) Prec@1 74.000 (68.375) Prec@5 98.000 (94.333) +2022-11-14 13:15:31,583 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1847 (0.1778) Prec@1 69.000 (68.384) Prec@5 93.000 (94.315) +2022-11-14 13:15:31,591 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1543 (0.1775) Prec@1 71.000 (68.419) Prec@5 93.000 (94.297) +2022-11-14 13:15:31,601 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1896 (0.1776) Prec@1 67.000 (68.400) Prec@5 94.000 (94.293) +2022-11-14 13:15:31,610 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1716 (0.1776) Prec@1 68.000 (68.395) Prec@5 94.000 (94.289) +2022-11-14 13:15:31,619 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1625 (0.1774) Prec@1 73.000 (68.455) Prec@5 96.000 (94.312) +2022-11-14 13:15:31,627 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1727 (0.1773) Prec@1 72.000 (68.500) Prec@5 92.000 (94.282) +2022-11-14 13:15:31,637 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2034 (0.1776) Prec@1 68.000 (68.494) Prec@5 93.000 (94.266) +2022-11-14 13:15:31,645 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1745 (0.1776) Prec@1 66.000 (68.463) Prec@5 94.000 (94.263) +2022-11-14 13:15:31,654 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1560 (0.1773) Prec@1 76.000 (68.556) Prec@5 96.000 (94.284) +2022-11-14 13:15:31,663 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2120 (0.1778) Prec@1 61.000 (68.463) Prec@5 89.000 (94.220) +2022-11-14 13:15:31,673 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2089 (0.1781) Prec@1 63.000 (68.398) Prec@5 93.000 (94.205) +2022-11-14 13:15:31,682 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1996 (0.1784) Prec@1 66.000 (68.369) Prec@5 92.000 (94.179) +2022-11-14 13:15:31,691 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1920 (0.1786) Prec@1 69.000 (68.376) Prec@5 94.000 (94.176) +2022-11-14 13:15:31,701 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1793 (0.1786) Prec@1 71.000 (68.407) Prec@5 93.000 (94.163) +2022-11-14 13:15:31,710 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2175 (0.1790) Prec@1 60.000 (68.310) Prec@5 91.000 (94.126) +2022-11-14 13:15:31,719 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1954 (0.1792) Prec@1 67.000 (68.295) Prec@5 95.000 (94.136) +2022-11-14 13:15:31,728 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1638 (0.1790) Prec@1 71.000 (68.326) Prec@5 93.000 (94.124) +2022-11-14 13:15:31,737 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1955 (0.1792) Prec@1 62.000 (68.256) Prec@5 93.000 (94.111) +2022-11-14 13:15:31,747 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1706 (0.1791) Prec@1 67.000 (68.242) Prec@5 97.000 (94.143) +2022-11-14 13:15:31,756 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.1786) Prec@1 77.000 (68.337) Prec@5 96.000 (94.163) +2022-11-14 13:15:31,765 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1753 (0.1786) Prec@1 68.000 (68.333) Prec@5 95.000 (94.172) +2022-11-14 13:15:31,774 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1899 (0.1787) Prec@1 66.000 (68.309) Prec@5 96.000 (94.191) +2022-11-14 13:15:31,784 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1889 (0.1788) Prec@1 67.000 (68.295) Prec@5 94.000 (94.189) +2022-11-14 13:15:31,793 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1377 (0.1784) Prec@1 73.000 (68.344) Prec@5 96.000 (94.208) +2022-11-14 13:15:31,802 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1581 (0.1782) Prec@1 72.000 (68.381) Prec@5 98.000 (94.247) +2022-11-14 13:15:31,811 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2192 (0.1786) Prec@1 65.000 (68.347) Prec@5 95.000 (94.255) +2022-11-14 13:15:31,819 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1876 (0.1787) Prec@1 65.000 (68.313) Prec@5 97.000 (94.283) +2022-11-14 13:15:31,828 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1969 (0.1788) Prec@1 67.000 (68.300) Prec@5 90.000 (94.240) +2022-11-14 13:15:31,894 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:15:32,188 Epoch: [9][0/500] Time 0.025 (0.025) Data 0.210 (0.210) Loss 0.1544 (0.1544) Prec@1 72.000 (72.000) Prec@5 99.000 (99.000) +2022-11-14 13:15:32,383 Epoch: [9][10/500] Time 0.017 (0.018) Data 0.002 (0.020) Loss 0.1441 (0.1493) Prec@1 73.000 (72.500) Prec@5 100.000 (99.500) +2022-11-14 13:15:32,574 Epoch: [9][20/500] Time 0.015 (0.017) Data 0.001 (0.011) Loss 0.1447 (0.1478) Prec@1 77.000 (74.000) Prec@5 95.000 (98.000) +2022-11-14 13:15:32,768 Epoch: [9][30/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.1734 (0.1542) Prec@1 71.000 (73.250) Prec@5 94.000 (97.000) +2022-11-14 13:15:32,960 Epoch: [9][40/500] Time 0.015 (0.017) Data 0.001 (0.007) Loss 0.1132 (0.1460) Prec@1 83.000 (75.200) Prec@5 97.000 (97.000) +2022-11-14 13:15:33,149 Epoch: [9][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.1531 (0.1472) Prec@1 70.000 (74.333) Prec@5 96.000 (96.833) +2022-11-14 13:15:33,342 Epoch: [9][60/500] Time 0.015 (0.017) Data 0.001 (0.005) Loss 0.1551 (0.1483) Prec@1 71.000 (73.857) Prec@5 96.000 (96.714) +2022-11-14 13:15:33,531 Epoch: [9][70/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.1269 (0.1456) Prec@1 77.000 (74.250) Prec@5 97.000 (96.750) +2022-11-14 13:15:33,744 Epoch: [9][80/500] Time 0.022 (0.017) Data 0.001 (0.004) Loss 0.1574 (0.1469) Prec@1 69.000 (73.667) Prec@5 97.000 (96.778) +2022-11-14 13:15:33,996 Epoch: [9][90/500] Time 0.023 (0.018) Data 0.001 (0.004) Loss 0.1723 (0.1495) Prec@1 64.000 (72.700) Prec@5 98.000 (96.900) +2022-11-14 13:15:34,247 Epoch: [9][100/500] Time 0.022 (0.018) Data 0.002 (0.004) Loss 0.1546 (0.1499) Prec@1 69.000 (72.364) Prec@5 97.000 (96.909) +2022-11-14 13:15:34,499 Epoch: [9][110/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.1724 (0.1518) Prec@1 68.000 (72.000) Prec@5 96.000 (96.833) +2022-11-14 13:15:34,751 Epoch: [9][120/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.1448 (0.1513) Prec@1 76.000 (72.308) Prec@5 95.000 (96.692) +2022-11-14 13:15:35,006 Epoch: [9][130/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.1590 (0.1518) Prec@1 71.000 (72.214) Prec@5 95.000 (96.571) +2022-11-14 13:15:35,259 Epoch: [9][140/500] Time 0.022 (0.019) Data 0.002 (0.003) Loss 0.1944 (0.1547) Prec@1 64.000 (71.667) Prec@5 96.000 (96.533) +2022-11-14 13:15:35,511 Epoch: [9][150/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.1548 (0.1547) Prec@1 72.000 (71.688) Prec@5 97.000 (96.562) +2022-11-14 13:15:35,765 Epoch: [9][160/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.1543 (0.1546) Prec@1 72.000 (71.706) Prec@5 95.000 (96.471) +2022-11-14 13:15:36,016 Epoch: [9][170/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.1556 (0.1547) Prec@1 68.000 (71.500) Prec@5 98.000 (96.556) +2022-11-14 13:15:36,268 Epoch: [9][180/500] Time 0.023 (0.020) Data 0.001 (0.003) Loss 0.1449 (0.1542) Prec@1 74.000 (71.632) Prec@5 97.000 (96.579) +2022-11-14 13:15:36,526 Epoch: [9][190/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.1595 (0.1545) Prec@1 68.000 (71.450) Prec@5 97.000 (96.600) +2022-11-14 13:15:36,778 Epoch: [9][200/500] Time 0.021 (0.020) Data 0.002 (0.003) Loss 0.1810 (0.1557) Prec@1 66.000 (71.190) Prec@5 95.000 (96.524) +2022-11-14 13:15:37,034 Epoch: [9][210/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.1604 (0.1559) Prec@1 74.000 (71.318) Prec@5 98.000 (96.591) +2022-11-14 13:15:37,290 Epoch: [9][220/500] Time 0.022 (0.020) Data 0.002 (0.003) Loss 0.2093 (0.1582) Prec@1 62.000 (70.913) Prec@5 94.000 (96.478) +2022-11-14 13:15:37,543 Epoch: [9][230/500] Time 0.023 (0.021) Data 0.001 (0.003) Loss 0.1577 (0.1582) Prec@1 69.000 (70.833) Prec@5 97.000 (96.500) +2022-11-14 13:15:37,800 Epoch: [9][240/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.1039 (0.1561) Prec@1 83.000 (71.320) Prec@5 98.000 (96.560) +2022-11-14 13:15:38,058 Epoch: [9][250/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.1390 (0.1554) Prec@1 73.000 (71.385) Prec@5 98.000 (96.615) +2022-11-14 13:15:38,313 Epoch: [9][260/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.1729 (0.1560) Prec@1 69.000 (71.296) Prec@5 91.000 (96.407) +2022-11-14 13:15:38,569 Epoch: [9][270/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.1690 (0.1565) Prec@1 72.000 (71.321) Prec@5 97.000 (96.429) +2022-11-14 13:15:38,824 Epoch: [9][280/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.1946 (0.1578) Prec@1 67.000 (71.172) Prec@5 94.000 (96.345) +2022-11-14 13:15:39,079 Epoch: [9][290/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.1356 (0.1571) Prec@1 77.000 (71.367) Prec@5 99.000 (96.433) +2022-11-14 13:15:39,338 Epoch: [9][300/500] Time 0.018 (0.021) Data 0.002 (0.002) Loss 0.1819 (0.1579) Prec@1 62.000 (71.065) Prec@5 99.000 (96.516) +2022-11-14 13:15:39,596 Epoch: [9][310/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.1473 (0.1576) Prec@1 75.000 (71.188) Prec@5 96.000 (96.500) +2022-11-14 13:15:39,849 Epoch: [9][320/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.1947 (0.1587) Prec@1 62.000 (70.909) Prec@5 92.000 (96.364) +2022-11-14 13:15:40,157 Epoch: [9][330/500] Time 0.038 (0.021) Data 0.003 (0.002) Loss 0.1699 (0.1590) Prec@1 71.000 (70.912) Prec@5 94.000 (96.294) +2022-11-14 13:15:40,403 Epoch: [9][340/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.1833 (0.1597) Prec@1 71.000 (70.914) Prec@5 97.000 (96.314) +2022-11-14 13:15:40,657 Epoch: [9][350/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.1776 (0.1602) Prec@1 67.000 (70.806) Prec@5 96.000 (96.306) +2022-11-14 13:15:40,912 Epoch: [9][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.1361 (0.1595) Prec@1 76.000 (70.946) Prec@5 100.000 (96.405) +2022-11-14 13:15:41,165 Epoch: [9][370/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.1579 (0.1595) Prec@1 69.000 (70.895) Prec@5 98.000 (96.447) +2022-11-14 13:15:41,419 Epoch: [9][380/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.1788 (0.1600) Prec@1 63.000 (70.692) Prec@5 97.000 (96.462) +2022-11-14 13:15:41,673 Epoch: [9][390/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.1679 (0.1602) Prec@1 69.000 (70.650) Prec@5 94.000 (96.400) +2022-11-14 13:15:41,928 Epoch: [9][400/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.1572 (0.1601) Prec@1 77.000 (70.805) Prec@5 99.000 (96.463) +2022-11-14 13:15:42,182 Epoch: [9][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.1909 (0.1609) Prec@1 64.000 (70.643) Prec@5 97.000 (96.476) +2022-11-14 13:15:42,488 Epoch: [9][420/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.1487 (0.1606) Prec@1 73.000 (70.698) Prec@5 97.000 (96.488) +2022-11-14 13:15:42,727 Epoch: [9][430/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.1391 (0.1601) Prec@1 75.000 (70.795) Prec@5 97.000 (96.500) +2022-11-14 13:15:42,980 Epoch: [9][440/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.1853 (0.1606) Prec@1 63.000 (70.622) Prec@5 98.000 (96.533) +2022-11-14 13:15:43,234 Epoch: [9][450/500] Time 0.021 (0.022) Data 0.002 (0.002) Loss 0.1665 (0.1608) Prec@1 69.000 (70.587) Prec@5 95.000 (96.500) +2022-11-14 13:15:43,512 Epoch: [9][460/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.1463 (0.1605) Prec@1 75.000 (70.681) Prec@5 96.000 (96.489) +2022-11-14 13:15:43,767 Epoch: [9][470/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.1388 (0.1600) Prec@1 73.000 (70.729) Prec@5 97.000 (96.500) +2022-11-14 13:15:44,023 Epoch: [9][480/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.2342 (0.1615) Prec@1 57.000 (70.449) Prec@5 93.000 (96.429) +2022-11-14 13:15:44,313 Epoch: [9][490/500] Time 0.021 (0.022) Data 0.002 (0.002) Loss 0.1778 (0.1619) Prec@1 67.000 (70.380) Prec@5 94.000 (96.380) +2022-11-14 13:15:44,535 Epoch: [9][499/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.1358 (0.1613) Prec@1 75.000 (70.471) Prec@5 98.000 (96.412) +2022-11-14 13:15:44,812 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1551 (0.1551) Prec@1 70.000 (70.000) Prec@5 98.000 (98.000) +2022-11-14 13:15:44,825 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1474 (0.1513) Prec@1 74.000 (72.000) Prec@5 98.000 (98.000) +2022-11-14 13:15:44,833 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1675 (0.1567) Prec@1 70.000 (71.333) Prec@5 100.000 (98.667) +2022-11-14 13:15:44,845 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1475 (0.1544) Prec@1 73.000 (71.750) Prec@5 100.000 (99.000) +2022-11-14 13:15:44,853 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1851 (0.1605) Prec@1 66.000 (70.600) Prec@5 97.000 (98.600) +2022-11-14 13:15:44,862 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1374 (0.1567) Prec@1 77.000 (71.667) Prec@5 99.000 (98.667) +2022-11-14 13:15:44,871 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1880 (0.1612) Prec@1 65.000 (70.714) Prec@5 98.000 (98.571) +2022-11-14 13:15:44,881 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1852 (0.1642) Prec@1 64.000 (69.875) Prec@5 95.000 (98.125) +2022-11-14 13:15:44,890 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1608 (0.1638) Prec@1 68.000 (69.667) Prec@5 97.000 (98.000) +2022-11-14 13:15:44,899 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1432 (0.1617) Prec@1 75.000 (70.200) Prec@5 96.000 (97.800) +2022-11-14 13:15:44,909 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1651 (0.1620) Prec@1 64.000 (69.636) Prec@5 99.000 (97.909) +2022-11-14 13:15:44,918 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1346 (0.1597) Prec@1 77.000 (70.250) Prec@5 99.000 (98.000) +2022-11-14 13:15:44,928 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1648 (0.1601) Prec@1 70.000 (70.231) Prec@5 94.000 (97.692) +2022-11-14 13:15:44,938 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1593) Prec@1 76.000 (70.643) Prec@5 99.000 (97.786) +2022-11-14 13:15:44,948 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1591) Prec@1 70.000 (70.600) Prec@5 98.000 (97.800) +2022-11-14 13:15:44,958 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1689 (0.1597) Prec@1 74.000 (70.812) Prec@5 95.000 (97.625) +2022-11-14 13:15:44,966 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1713 (0.1604) Prec@1 68.000 (70.647) Prec@5 96.000 (97.529) +2022-11-14 13:15:44,976 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1694 (0.1609) Prec@1 65.000 (70.333) Prec@5 99.000 (97.611) +2022-11-14 13:15:44,986 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1691 (0.1613) Prec@1 70.000 (70.316) Prec@5 96.000 (97.526) +2022-11-14 13:15:44,995 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1991 (0.1632) Prec@1 59.000 (69.750) Prec@5 93.000 (97.300) +2022-11-14 13:15:45,004 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1966 (0.1648) Prec@1 63.000 (69.429) Prec@5 95.000 (97.190) +2022-11-14 13:15:45,014 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1891 (0.1659) Prec@1 64.000 (69.182) Prec@5 95.000 (97.091) +2022-11-14 13:15:45,023 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1773 (0.1664) Prec@1 68.000 (69.130) Prec@5 98.000 (97.130) +2022-11-14 13:15:45,032 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1601 (0.1661) Prec@1 67.000 (69.042) Prec@5 98.000 (97.167) +2022-11-14 13:15:45,042 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1733 (0.1664) Prec@1 67.000 (68.960) Prec@5 96.000 (97.120) +2022-11-14 13:15:45,052 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1741 (0.1667) Prec@1 70.000 (69.000) Prec@5 95.000 (97.038) +2022-11-14 13:15:45,062 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1408 (0.1658) Prec@1 73.000 (69.148) Prec@5 100.000 (97.148) +2022-11-14 13:15:45,071 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1774 (0.1662) Prec@1 71.000 (69.214) Prec@5 95.000 (97.071) +2022-11-14 13:15:45,081 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1659) Prec@1 75.000 (69.414) Prec@5 95.000 (97.000) +2022-11-14 13:15:45,090 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1521 (0.1654) Prec@1 75.000 (69.600) Prec@5 98.000 (97.033) +2022-11-14 13:15:45,100 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1312 (0.1643) Prec@1 77.000 (69.839) Prec@5 99.000 (97.097) +2022-11-14 13:15:45,110 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1885 (0.1651) Prec@1 65.000 (69.688) Prec@5 97.000 (97.094) +2022-11-14 13:15:45,119 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1495 (0.1646) Prec@1 72.000 (69.758) Prec@5 98.000 (97.121) +2022-11-14 13:15:45,128 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1785 (0.1650) Prec@1 65.000 (69.618) Prec@5 96.000 (97.088) +2022-11-14 13:15:45,137 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1784 (0.1654) Prec@1 68.000 (69.571) Prec@5 98.000 (97.114) +2022-11-14 13:15:45,145 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.1643) Prec@1 79.000 (69.833) Prec@5 97.000 (97.111) +2022-11-14 13:15:45,155 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1647) Prec@1 70.000 (69.838) Prec@5 98.000 (97.135) +2022-11-14 13:15:45,166 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1739 (0.1649) Prec@1 67.000 (69.763) Prec@5 95.000 (97.079) +2022-11-14 13:15:45,178 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1439 (0.1644) Prec@1 71.000 (69.795) Prec@5 96.000 (97.051) +2022-11-14 13:15:45,191 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1644) Prec@1 74.000 (69.900) Prec@5 95.000 (97.000) +2022-11-14 13:15:45,203 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1640) Prec@1 73.000 (69.976) Prec@5 97.000 (97.000) +2022-11-14 13:15:45,213 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1563 (0.1638) Prec@1 74.000 (70.071) Prec@5 96.000 (96.976) +2022-11-14 13:15:45,222 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.1630) Prec@1 76.000 (70.209) Prec@5 98.000 (97.000) +2022-11-14 13:15:45,232 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1613 (0.1630) Prec@1 70.000 (70.205) Prec@5 98.000 (97.023) +2022-11-14 13:15:45,242 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1423 (0.1625) Prec@1 76.000 (70.333) Prec@5 97.000 (97.022) +2022-11-14 13:15:45,251 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2096 (0.1636) Prec@1 57.000 (70.043) Prec@5 97.000 (97.022) +2022-11-14 13:15:45,261 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1520 (0.1633) Prec@1 74.000 (70.128) Prec@5 99.000 (97.064) +2022-11-14 13:15:45,273 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1824 (0.1637) Prec@1 68.000 (70.083) Prec@5 97.000 (97.062) +2022-11-14 13:15:45,283 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1631) Prec@1 77.000 (70.224) Prec@5 99.000 (97.102) +2022-11-14 13:15:45,293 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1757 (0.1634) Prec@1 64.000 (70.100) Prec@5 98.000 (97.120) +2022-11-14 13:15:45,305 Test: [50/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1632) Prec@1 72.000 (70.137) Prec@5 97.000 (97.118) +2022-11-14 13:15:45,316 Test: [51/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1675 (0.1633) Prec@1 67.000 (70.077) Prec@5 97.000 (97.115) +2022-11-14 13:15:45,326 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1515 (0.1631) Prec@1 70.000 (70.075) Prec@5 100.000 (97.170) +2022-11-14 13:15:45,335 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1654 (0.1631) Prec@1 66.000 (70.000) Prec@5 94.000 (97.111) +2022-11-14 13:15:45,348 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1918 (0.1636) Prec@1 63.000 (69.873) Prec@5 97.000 (97.109) +2022-11-14 13:15:45,359 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1722 (0.1638) Prec@1 67.000 (69.821) Prec@5 96.000 (97.089) +2022-11-14 13:15:45,368 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.1639) Prec@1 65.000 (69.737) Prec@5 98.000 (97.105) +2022-11-14 13:15:45,379 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1502 (0.1637) Prec@1 75.000 (69.828) Prec@5 97.000 (97.103) +2022-11-14 13:15:45,392 Test: [58/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1958 (0.1642) Prec@1 62.000 (69.695) Prec@5 97.000 (97.102) +2022-11-14 13:15:45,404 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1738 (0.1644) Prec@1 69.000 (69.683) Prec@5 96.000 (97.083) +2022-11-14 13:15:45,415 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1509 (0.1642) Prec@1 75.000 (69.770) Prec@5 96.000 (97.066) +2022-11-14 13:15:45,427 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1692 (0.1643) Prec@1 67.000 (69.726) Prec@5 96.000 (97.048) +2022-11-14 13:15:45,442 Test: [62/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1728 (0.1644) Prec@1 69.000 (69.714) Prec@5 94.000 (97.000) +2022-11-14 13:15:45,455 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1503 (0.1642) Prec@1 74.000 (69.781) Prec@5 100.000 (97.047) +2022-11-14 13:15:45,468 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1840 (0.1645) Prec@1 68.000 (69.754) Prec@5 91.000 (96.954) +2022-11-14 13:15:45,481 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1646 (0.1645) Prec@1 70.000 (69.758) Prec@5 99.000 (96.985) +2022-11-14 13:15:45,492 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1727 (0.1646) Prec@1 67.000 (69.716) Prec@5 96.000 (96.970) +2022-11-14 13:15:45,505 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1642 (0.1646) Prec@1 70.000 (69.721) Prec@5 97.000 (96.971) +2022-11-14 13:15:45,517 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1569 (0.1645) Prec@1 71.000 (69.739) Prec@5 97.000 (96.971) +2022-11-14 13:15:45,530 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1952 (0.1649) Prec@1 66.000 (69.686) Prec@5 94.000 (96.929) +2022-11-14 13:15:45,542 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1692 (0.1650) Prec@1 70.000 (69.690) Prec@5 99.000 (96.958) +2022-11-14 13:15:45,555 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1761 (0.1651) Prec@1 71.000 (69.708) Prec@5 97.000 (96.958) +2022-11-14 13:15:45,569 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1810 (0.1654) Prec@1 68.000 (69.685) Prec@5 98.000 (96.973) +2022-11-14 13:15:45,581 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1679 (0.1654) Prec@1 67.000 (69.649) Prec@5 98.000 (96.986) +2022-11-14 13:15:45,593 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.1655) Prec@1 67.000 (69.613) Prec@5 96.000 (96.973) +2022-11-14 13:15:45,606 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1686 (0.1655) Prec@1 71.000 (69.632) Prec@5 100.000 (97.013) +2022-11-14 13:15:45,617 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1542 (0.1654) Prec@1 73.000 (69.675) Prec@5 98.000 (97.026) +2022-11-14 13:15:45,628 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1851 (0.1657) Prec@1 65.000 (69.615) Prec@5 98.000 (97.038) +2022-11-14 13:15:45,638 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1528 (0.1655) Prec@1 74.000 (69.671) Prec@5 97.000 (97.038) +2022-11-14 13:15:45,647 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1960 (0.1659) Prec@1 64.000 (69.600) Prec@5 94.000 (97.000) +2022-11-14 13:15:45,657 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1541 (0.1657) Prec@1 72.000 (69.630) Prec@5 95.000 (96.975) +2022-11-14 13:15:45,666 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1759 (0.1658) Prec@1 67.000 (69.598) Prec@5 97.000 (96.976) +2022-11-14 13:15:45,676 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1828 (0.1661) Prec@1 70.000 (69.602) Prec@5 96.000 (96.964) +2022-11-14 13:15:45,688 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2035 (0.1665) Prec@1 62.000 (69.512) Prec@5 96.000 (96.952) +2022-11-14 13:15:45,698 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1879 (0.1667) Prec@1 65.000 (69.459) Prec@5 95.000 (96.929) +2022-11-14 13:15:45,709 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1935 (0.1671) Prec@1 67.000 (69.430) Prec@5 99.000 (96.953) +2022-11-14 13:15:45,722 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1826 (0.1672) Prec@1 69.000 (69.425) Prec@5 96.000 (96.943) +2022-11-14 13:15:45,734 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2015 (0.1676) Prec@1 61.000 (69.330) Prec@5 95.000 (96.920) +2022-11-14 13:15:45,743 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1496 (0.1674) Prec@1 74.000 (69.382) Prec@5 97.000 (96.921) +2022-11-14 13:15:45,753 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1568 (0.1673) Prec@1 75.000 (69.444) Prec@5 96.000 (96.911) +2022-11-14 13:15:45,765 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1370 (0.1670) Prec@1 79.000 (69.549) Prec@5 98.000 (96.923) +2022-11-14 13:15:45,776 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1149 (0.1664) Prec@1 79.000 (69.652) Prec@5 98.000 (96.935) +2022-11-14 13:15:45,785 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1874 (0.1666) Prec@1 65.000 (69.602) Prec@5 98.000 (96.946) +2022-11-14 13:15:45,795 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2073 (0.1671) Prec@1 64.000 (69.543) Prec@5 94.000 (96.915) +2022-11-14 13:15:45,805 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1455 (0.1668) Prec@1 74.000 (69.589) Prec@5 99.000 (96.937) +2022-11-14 13:15:45,814 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1573 (0.1667) Prec@1 74.000 (69.635) Prec@5 94.000 (96.906) +2022-11-14 13:15:45,824 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1480 (0.1665) Prec@1 74.000 (69.680) Prec@5 98.000 (96.918) +2022-11-14 13:15:45,832 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2259 (0.1672) Prec@1 59.000 (69.571) Prec@5 100.000 (96.949) +2022-11-14 13:15:45,840 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.1674) Prec@1 62.000 (69.495) Prec@5 98.000 (96.960) +2022-11-14 13:15:45,848 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1679 (0.1674) Prec@1 70.000 (69.500) Prec@5 100.000 (96.990) +2022-11-14 13:15:45,904 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:15:46,204 Epoch: [10][0/500] Time 0.030 (0.030) Data 0.213 (0.213) Loss 0.1761 (0.1761) Prec@1 65.000 (65.000) Prec@5 95.000 (95.000) +2022-11-14 13:15:46,438 Epoch: [10][10/500] Time 0.026 (0.021) Data 0.002 (0.021) Loss 0.1483 (0.1622) Prec@1 74.000 (69.500) Prec@5 97.000 (96.000) +2022-11-14 13:15:46,693 Epoch: [10][20/500] Time 0.017 (0.022) Data 0.002 (0.012) Loss 0.1557 (0.1600) Prec@1 75.000 (71.333) Prec@5 96.000 (96.000) +2022-11-14 13:15:46,946 Epoch: [10][30/500] Time 0.022 (0.022) Data 0.002 (0.009) Loss 0.1961 (0.1691) Prec@1 65.000 (69.750) Prec@5 96.000 (96.000) +2022-11-14 13:15:47,179 Epoch: [10][40/500] Time 0.021 (0.022) Data 0.002 (0.007) Loss 0.1581 (0.1669) Prec@1 72.000 (70.200) Prec@5 99.000 (96.600) +2022-11-14 13:15:47,413 Epoch: [10][50/500] Time 0.020 (0.022) Data 0.002 (0.006) Loss 0.1033 (0.1563) Prec@1 81.000 (72.000) Prec@5 98.000 (96.833) +2022-11-14 13:15:47,629 Epoch: [10][60/500] Time 0.018 (0.021) Data 0.002 (0.005) Loss 0.1495 (0.1553) Prec@1 71.000 (71.857) Prec@5 96.000 (96.714) +2022-11-14 13:15:47,848 Epoch: [10][70/500] Time 0.016 (0.021) Data 0.002 (0.005) Loss 0.1485 (0.1545) Prec@1 74.000 (72.125) Prec@5 100.000 (97.125) +2022-11-14 13:15:48,070 Epoch: [10][80/500] Time 0.021 (0.021) Data 0.002 (0.005) Loss 0.1397 (0.1528) Prec@1 75.000 (72.444) Prec@5 97.000 (97.111) +2022-11-14 13:15:48,339 Epoch: [10][90/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.1720 (0.1547) Prec@1 67.000 (71.900) Prec@5 95.000 (96.900) +2022-11-14 13:15:48,618 Epoch: [10][100/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.1543 (0.1547) Prec@1 73.000 (72.000) Prec@5 97.000 (96.909) +2022-11-14 13:15:48,886 Epoch: [10][110/500] Time 0.027 (0.022) Data 0.002 (0.004) Loss 0.1542 (0.1547) Prec@1 71.000 (71.917) Prec@5 96.000 (96.833) +2022-11-14 13:15:49,206 Epoch: [10][120/500] Time 0.033 (0.022) Data 0.002 (0.004) Loss 0.1635 (0.1553) Prec@1 71.000 (71.846) Prec@5 95.000 (96.692) +2022-11-14 13:15:49,461 Epoch: [10][130/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.1615 (0.1558) Prec@1 70.000 (71.714) Prec@5 97.000 (96.714) +2022-11-14 13:15:49,756 Epoch: [10][140/500] Time 0.022 (0.022) Data 0.002 (0.003) Loss 0.2050 (0.1591) Prec@1 65.000 (71.267) Prec@5 96.000 (96.667) +2022-11-14 13:15:50,050 Epoch: [10][150/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.1499 (0.1585) Prec@1 67.000 (71.000) Prec@5 97.000 (96.688) +2022-11-14 13:15:50,332 Epoch: [10][160/500] Time 0.041 (0.023) Data 0.001 (0.003) Loss 0.1423 (0.1575) Prec@1 77.000 (71.353) Prec@5 95.000 (96.588) +2022-11-14 13:15:50,621 Epoch: [10][170/500] Time 0.023 (0.023) Data 0.001 (0.003) Loss 0.1212 (0.1555) Prec@1 79.000 (71.778) Prec@5 98.000 (96.667) +2022-11-14 13:15:50,894 Epoch: [10][180/500] Time 0.026 (0.023) Data 0.001 (0.003) Loss 0.1452 (0.1550) Prec@1 76.000 (72.000) Prec@5 98.000 (96.737) +2022-11-14 13:15:51,174 Epoch: [10][190/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.1172 (0.1531) Prec@1 82.000 (72.500) Prec@5 99.000 (96.850) +2022-11-14 13:15:51,451 Epoch: [10][200/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.1424 (0.1526) Prec@1 77.000 (72.714) Prec@5 99.000 (96.952) +2022-11-14 13:15:51,727 Epoch: [10][210/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.1342 (0.1517) Prec@1 79.000 (73.000) Prec@5 100.000 (97.091) +2022-11-14 13:15:51,998 Epoch: [10][220/500] Time 0.025 (0.023) Data 0.001 (0.003) Loss 0.1596 (0.1521) Prec@1 72.000 (72.957) Prec@5 99.000 (97.174) +2022-11-14 13:15:52,268 Epoch: [10][230/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.1517 (0.1521) Prec@1 71.000 (72.875) Prec@5 98.000 (97.208) +2022-11-14 13:15:52,541 Epoch: [10][240/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.1228 (0.1509) Prec@1 76.000 (73.000) Prec@5 98.000 (97.240) +2022-11-14 13:15:52,812 Epoch: [10][250/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.1361 (0.1503) Prec@1 74.000 (73.038) Prec@5 99.000 (97.308) +2022-11-14 13:15:53,087 Epoch: [10][260/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.1471 (0.1502) Prec@1 76.000 (73.148) Prec@5 95.000 (97.222) +2022-11-14 13:15:53,362 Epoch: [10][270/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.1455 (0.1500) Prec@1 75.000 (73.214) Prec@5 96.000 (97.179) +2022-11-14 13:15:53,631 Epoch: [10][280/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.1361 (0.1496) Prec@1 74.000 (73.241) Prec@5 98.000 (97.207) +2022-11-14 13:15:53,903 Epoch: [10][290/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.1623 (0.1500) Prec@1 68.000 (73.067) Prec@5 98.000 (97.233) +2022-11-14 13:15:54,178 Epoch: [10][300/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.1613 (0.1503) Prec@1 67.000 (72.871) Prec@5 97.000 (97.226) +2022-11-14 13:15:54,452 Epoch: [10][310/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.1683 (0.1509) Prec@1 67.000 (72.688) Prec@5 99.000 (97.281) +2022-11-14 13:15:54,725 Epoch: [10][320/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1263 (0.1502) Prec@1 82.000 (72.970) Prec@5 100.000 (97.364) +2022-11-14 13:15:54,996 Epoch: [10][330/500] Time 0.024 (0.024) Data 0.002 (0.002) Loss 0.1832 (0.1511) Prec@1 66.000 (72.765) Prec@5 97.000 (97.353) +2022-11-14 13:15:55,269 Epoch: [10][340/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1414 (0.1509) Prec@1 76.000 (72.857) Prec@5 98.000 (97.371) +2022-11-14 13:15:55,544 Epoch: [10][350/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.1812 (0.1517) Prec@1 64.000 (72.611) Prec@5 95.000 (97.306) +2022-11-14 13:15:55,820 Epoch: [10][360/500] Time 0.026 (0.024) Data 0.001 (0.002) Loss 0.1758 (0.1524) Prec@1 68.000 (72.486) Prec@5 97.000 (97.297) +2022-11-14 13:15:56,092 Epoch: [10][370/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1536 (0.1524) Prec@1 69.000 (72.395) Prec@5 98.000 (97.316) +2022-11-14 13:15:56,365 Epoch: [10][380/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.1596 (0.1526) Prec@1 71.000 (72.359) Prec@5 98.000 (97.333) +2022-11-14 13:15:56,637 Epoch: [10][390/500] Time 0.024 (0.024) Data 0.002 (0.002) Loss 0.1254 (0.1519) Prec@1 78.000 (72.500) Prec@5 99.000 (97.375) +2022-11-14 13:15:56,916 Epoch: [10][400/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.1607 (0.1521) Prec@1 70.000 (72.439) Prec@5 98.000 (97.390) +2022-11-14 13:15:57,189 Epoch: [10][410/500] Time 0.026 (0.024) Data 0.001 (0.002) Loss 0.1794 (0.1528) Prec@1 71.000 (72.405) Prec@5 94.000 (97.310) +2022-11-14 13:15:57,465 Epoch: [10][420/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.1238 (0.1521) Prec@1 77.000 (72.512) Prec@5 99.000 (97.349) +2022-11-14 13:15:57,736 Epoch: [10][430/500] Time 0.024 (0.024) Data 0.001 (0.002) Loss 0.1358 (0.1517) Prec@1 76.000 (72.591) Prec@5 96.000 (97.318) +2022-11-14 13:15:58,008 Epoch: [10][440/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.1460 (0.1516) Prec@1 73.000 (72.600) Prec@5 96.000 (97.289) +2022-11-14 13:15:58,283 Epoch: [10][450/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1402 (0.1513) Prec@1 74.000 (72.630) Prec@5 97.000 (97.283) +2022-11-14 13:15:58,555 Epoch: [10][460/500] Time 0.024 (0.024) Data 0.002 (0.002) Loss 0.1477 (0.1513) Prec@1 73.000 (72.638) Prec@5 95.000 (97.234) +2022-11-14 13:15:58,828 Epoch: [10][470/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1340 (0.1509) Prec@1 78.000 (72.750) Prec@5 97.000 (97.229) +2022-11-14 13:15:59,104 Epoch: [10][480/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.1445 (0.1508) Prec@1 76.000 (72.816) Prec@5 98.000 (97.245) +2022-11-14 13:15:59,377 Epoch: [10][490/500] Time 0.026 (0.024) Data 0.001 (0.002) Loss 0.1663 (0.1511) Prec@1 72.000 (72.800) Prec@5 97.000 (97.240) +2022-11-14 13:15:59,625 Epoch: [10][499/500] Time 0.025 (0.024) Data 0.001 (0.002) Loss 0.1545 (0.1511) Prec@1 74.000 (72.824) Prec@5 95.000 (97.196) +2022-11-14 13:15:59,896 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1693 (0.1693) Prec@1 71.000 (71.000) Prec@5 97.000 (97.000) +2022-11-14 13:15:59,904 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1704 (0.1698) Prec@1 69.000 (70.000) Prec@5 97.000 (97.000) +2022-11-14 13:15:59,912 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1612 (0.1670) Prec@1 71.000 (70.333) Prec@5 99.000 (97.667) +2022-11-14 13:15:59,925 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1895 (0.1726) Prec@1 65.000 (69.000) Prec@5 98.000 (97.750) +2022-11-14 13:15:59,933 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1905 (0.1762) Prec@1 64.000 (68.000) Prec@5 94.000 (97.000) +2022-11-14 13:15:59,942 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1671 (0.1747) Prec@1 67.000 (67.833) Prec@5 99.000 (97.333) +2022-11-14 13:15:59,951 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.1692) Prec@1 76.000 (69.000) Prec@5 96.000 (97.143) +2022-11-14 13:15:59,962 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1727 (0.1697) Prec@1 68.000 (68.875) Prec@5 97.000 (97.125) +2022-11-14 13:15:59,971 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1995 (0.1730) Prec@1 64.000 (68.333) Prec@5 98.000 (97.222) +2022-11-14 13:15:59,979 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1430 (0.1700) Prec@1 75.000 (69.000) Prec@5 96.000 (97.100) +2022-11-14 13:15:59,987 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1448 (0.1677) Prec@1 75.000 (69.545) Prec@5 97.000 (97.091) +2022-11-14 13:15:59,995 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1797 (0.1687) Prec@1 69.000 (69.500) Prec@5 98.000 (97.167) +2022-11-14 13:16:00,003 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1687) Prec@1 69.000 (69.462) Prec@5 96.000 (97.077) +2022-11-14 13:16:00,013 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1683 (0.1686) Prec@1 66.000 (69.214) Prec@5 98.000 (97.143) +2022-11-14 13:16:00,022 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1469 (0.1672) Prec@1 75.000 (69.600) Prec@5 97.000 (97.133) +2022-11-14 13:16:00,031 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2067 (0.1696) Prec@1 58.000 (68.875) Prec@5 97.000 (97.125) +2022-11-14 13:16:00,041 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1599 (0.1691) Prec@1 69.000 (68.882) Prec@5 93.000 (96.882) +2022-11-14 13:16:00,050 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1694) Prec@1 67.000 (68.778) Prec@5 98.000 (96.944) +2022-11-14 13:16:00,059 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1705 (0.1694) Prec@1 71.000 (68.895) Prec@5 98.000 (97.000) +2022-11-14 13:16:00,068 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2115 (0.1715) Prec@1 63.000 (68.600) Prec@5 95.000 (96.900) +2022-11-14 13:16:00,077 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2154 (0.1736) Prec@1 60.000 (68.190) Prec@5 95.000 (96.810) +2022-11-14 13:16:00,087 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1896 (0.1744) Prec@1 63.000 (67.955) Prec@5 97.000 (96.818) +2022-11-14 13:16:00,096 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1843 (0.1748) Prec@1 65.000 (67.826) Prec@5 95.000 (96.739) +2022-11-14 13:16:00,105 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1892 (0.1754) Prec@1 69.000 (67.875) Prec@5 95.000 (96.667) +2022-11-14 13:16:00,114 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1918 (0.1760) Prec@1 66.000 (67.800) Prec@5 97.000 (96.680) +2022-11-14 13:16:00,124 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2360 (0.1784) Prec@1 55.000 (67.308) Prec@5 89.000 (96.385) +2022-11-14 13:16:00,133 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1684 (0.1780) Prec@1 71.000 (67.444) Prec@5 96.000 (96.370) +2022-11-14 13:16:00,142 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1936 (0.1785) Prec@1 65.000 (67.357) Prec@5 95.000 (96.321) +2022-11-14 13:16:00,152 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1672 (0.1782) Prec@1 71.000 (67.483) Prec@5 98.000 (96.379) +2022-11-14 13:16:00,161 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1730 (0.1780) Prec@1 68.000 (67.500) Prec@5 98.000 (96.433) +2022-11-14 13:16:00,170 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1690 (0.1777) Prec@1 70.000 (67.581) Prec@5 99.000 (96.516) +2022-11-14 13:16:00,179 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1975 (0.1783) Prec@1 68.000 (67.594) Prec@5 96.000 (96.500) +2022-11-14 13:16:00,189 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1907 (0.1787) Prec@1 62.000 (67.424) Prec@5 95.000 (96.455) +2022-11-14 13:16:00,198 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2053 (0.1795) Prec@1 60.000 (67.206) Prec@5 94.000 (96.382) +2022-11-14 13:16:00,207 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2071 (0.1803) Prec@1 61.000 (67.029) Prec@5 94.000 (96.314) +2022-11-14 13:16:00,216 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1712 (0.1800) Prec@1 69.000 (67.083) Prec@5 100.000 (96.417) +2022-11-14 13:16:00,225 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1880 (0.1802) Prec@1 66.000 (67.054) Prec@5 97.000 (96.432) +2022-11-14 13:16:00,235 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1738 (0.1801) Prec@1 68.000 (67.079) Prec@5 95.000 (96.395) +2022-11-14 13:16:00,244 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1631 (0.1796) Prec@1 69.000 (67.128) Prec@5 96.000 (96.385) +2022-11-14 13:16:00,253 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1529 (0.1790) Prec@1 76.000 (67.350) Prec@5 96.000 (96.375) +2022-11-14 13:16:00,263 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1577 (0.1784) Prec@1 74.000 (67.512) Prec@5 96.000 (96.366) +2022-11-14 13:16:00,271 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1556 (0.1779) Prec@1 72.000 (67.619) Prec@5 96.000 (96.357) +2022-11-14 13:16:00,280 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1532 (0.1773) Prec@1 73.000 (67.744) Prec@5 97.000 (96.372) +2022-11-14 13:16:00,288 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1759 (0.1773) Prec@1 72.000 (67.841) Prec@5 95.000 (96.341) +2022-11-14 13:16:00,296 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1489 (0.1767) Prec@1 74.000 (67.978) Prec@5 100.000 (96.422) +2022-11-14 13:16:00,304 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1641 (0.1764) Prec@1 71.000 (68.043) Prec@5 93.000 (96.348) +2022-11-14 13:16:00,312 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1455 (0.1757) Prec@1 76.000 (68.213) Prec@5 98.000 (96.383) +2022-11-14 13:16:00,321 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1659 (0.1755) Prec@1 71.000 (68.271) Prec@5 98.000 (96.417) +2022-11-14 13:16:00,330 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1645 (0.1753) Prec@1 68.000 (68.265) Prec@5 100.000 (96.490) +2022-11-14 13:16:00,339 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2177 (0.1761) Prec@1 62.000 (68.140) Prec@5 97.000 (96.500) +2022-11-14 13:16:00,348 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1489 (0.1756) Prec@1 71.000 (68.196) Prec@5 98.000 (96.529) +2022-11-14 13:16:00,356 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2031 (0.1761) Prec@1 65.000 (68.135) Prec@5 95.000 (96.500) +2022-11-14 13:16:00,366 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1657 (0.1759) Prec@1 72.000 (68.208) Prec@5 97.000 (96.509) +2022-11-14 13:16:00,374 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2183 (0.1767) Prec@1 63.000 (68.111) Prec@5 95.000 (96.481) +2022-11-14 13:16:00,383 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1971 (0.1771) Prec@1 67.000 (68.091) Prec@5 97.000 (96.491) +2022-11-14 13:16:00,392 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1716 (0.1770) Prec@1 71.000 (68.143) Prec@5 95.000 (96.464) +2022-11-14 13:16:00,402 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1609 (0.1767) Prec@1 74.000 (68.246) Prec@5 99.000 (96.509) +2022-11-14 13:16:00,411 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1927 (0.1770) Prec@1 62.000 (68.138) Prec@5 97.000 (96.517) +2022-11-14 13:16:00,420 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1949 (0.1773) Prec@1 64.000 (68.068) Prec@5 97.000 (96.525) +2022-11-14 13:16:00,429 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1812 (0.1774) Prec@1 67.000 (68.050) Prec@5 96.000 (96.517) +2022-11-14 13:16:00,438 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2045 (0.1778) Prec@1 65.000 (68.000) Prec@5 98.000 (96.541) +2022-11-14 13:16:00,447 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1789 (0.1778) Prec@1 71.000 (68.048) Prec@5 96.000 (96.532) +2022-11-14 13:16:00,456 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1817 (0.1779) Prec@1 69.000 (68.063) Prec@5 96.000 (96.524) +2022-11-14 13:16:00,464 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1740 (0.1778) Prec@1 69.000 (68.078) Prec@5 99.000 (96.562) +2022-11-14 13:16:00,472 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1910 (0.1780) Prec@1 67.000 (68.062) Prec@5 97.000 (96.569) +2022-11-14 13:16:00,481 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2177 (0.1786) Prec@1 57.000 (67.894) Prec@5 94.000 (96.530) +2022-11-14 13:16:00,491 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1871 (0.1788) Prec@1 65.000 (67.851) Prec@5 96.000 (96.522) +2022-11-14 13:16:00,501 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1946 (0.1790) Prec@1 67.000 (67.838) Prec@5 96.000 (96.515) +2022-11-14 13:16:00,511 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1798 (0.1790) Prec@1 70.000 (67.870) Prec@5 96.000 (96.507) +2022-11-14 13:16:00,521 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1830 (0.1791) Prec@1 66.000 (67.843) Prec@5 94.000 (96.471) +2022-11-14 13:16:00,529 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1775 (0.1790) Prec@1 67.000 (67.831) Prec@5 96.000 (96.465) +2022-11-14 13:16:00,539 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1636 (0.1788) Prec@1 70.000 (67.861) Prec@5 97.000 (96.472) +2022-11-14 13:16:00,547 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1684 (0.1787) Prec@1 70.000 (67.890) Prec@5 98.000 (96.493) +2022-11-14 13:16:00,555 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1512 (0.1783) Prec@1 70.000 (67.919) Prec@5 97.000 (96.500) +2022-11-14 13:16:00,563 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1463 (0.1779) Prec@1 74.000 (68.000) Prec@5 95.000 (96.480) +2022-11-14 13:16:00,572 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1783 (0.1779) Prec@1 66.000 (67.974) Prec@5 94.000 (96.447) +2022-11-14 13:16:00,580 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1850 (0.1780) Prec@1 67.000 (67.961) Prec@5 95.000 (96.429) +2022-11-14 13:16:00,588 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1718 (0.1779) Prec@1 67.000 (67.949) Prec@5 96.000 (96.423) +2022-11-14 13:16:00,596 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1903 (0.1781) Prec@1 66.000 (67.924) Prec@5 96.000 (96.418) +2022-11-14 13:16:00,605 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1566 (0.1778) Prec@1 72.000 (67.975) Prec@5 97.000 (96.425) +2022-11-14 13:16:00,613 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1771 (0.1778) Prec@1 69.000 (67.988) Prec@5 96.000 (96.420) +2022-11-14 13:16:00,623 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1932 (0.1780) Prec@1 66.000 (67.963) Prec@5 96.000 (96.415) +2022-11-14 13:16:00,631 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1503 (0.1776) Prec@1 72.000 (68.012) Prec@5 99.000 (96.446) +2022-11-14 13:16:00,639 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1836 (0.1777) Prec@1 65.000 (67.976) Prec@5 97.000 (96.452) +2022-11-14 13:16:00,648 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2047 (0.1780) Prec@1 63.000 (67.918) Prec@5 95.000 (96.435) +2022-11-14 13:16:00,657 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1795 (0.1780) Prec@1 67.000 (67.907) Prec@5 96.000 (96.430) +2022-11-14 13:16:00,665 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1928 (0.1782) Prec@1 64.000 (67.862) Prec@5 96.000 (96.425) +2022-11-14 13:16:00,673 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1870 (0.1783) Prec@1 64.000 (67.818) Prec@5 97.000 (96.432) +2022-11-14 13:16:00,682 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1511 (0.1780) Prec@1 75.000 (67.899) Prec@5 94.000 (96.404) +2022-11-14 13:16:00,691 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1598 (0.1778) Prec@1 70.000 (67.922) Prec@5 96.000 (96.400) +2022-11-14 13:16:00,701 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1630 (0.1776) Prec@1 68.000 (67.923) Prec@5 98.000 (96.418) +2022-11-14 13:16:00,709 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1271 (0.1771) Prec@1 79.000 (68.043) Prec@5 97.000 (96.424) +2022-11-14 13:16:00,719 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1771 (0.1771) Prec@1 67.000 (68.032) Prec@5 97.000 (96.430) +2022-11-14 13:16:00,728 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1903 (0.1772) Prec@1 62.000 (67.968) Prec@5 95.000 (96.415) +2022-11-14 13:16:00,737 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1674 (0.1771) Prec@1 68.000 (67.968) Prec@5 97.000 (96.421) +2022-11-14 13:16:00,745 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1730 (0.1771) Prec@1 68.000 (67.969) Prec@5 96.000 (96.417) +2022-11-14 13:16:00,755 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1478 (0.1768) Prec@1 74.000 (68.031) Prec@5 96.000 (96.412) +2022-11-14 13:16:00,763 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2213 (0.1772) Prec@1 57.000 (67.918) Prec@5 90.000 (96.347) +2022-11-14 13:16:00,771 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1576 (0.1770) Prec@1 74.000 (67.980) Prec@5 98.000 (96.364) +2022-11-14 13:16:00,780 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1921 (0.1772) Prec@1 66.000 (67.960) Prec@5 95.000 (96.350) +2022-11-14 13:16:00,834 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:16:01,145 Epoch: [11][0/500] Time 0.035 (0.035) Data 0.221 (0.221) Loss 0.1440 (0.1440) Prec@1 72.000 (72.000) Prec@5 97.000 (97.000) +2022-11-14 13:16:01,361 Epoch: [11][10/500] Time 0.019 (0.021) Data 0.001 (0.022) Loss 0.1465 (0.1452) Prec@1 76.000 (74.000) Prec@5 98.000 (97.500) +2022-11-14 13:16:01,587 Epoch: [11][20/500] Time 0.021 (0.020) Data 0.001 (0.012) Loss 0.1773 (0.1559) Prec@1 67.000 (71.667) Prec@5 94.000 (96.333) +2022-11-14 13:16:01,820 Epoch: [11][30/500] Time 0.018 (0.021) Data 0.002 (0.009) Loss 0.1408 (0.1522) Prec@1 73.000 (72.000) Prec@5 98.000 (96.750) +2022-11-14 13:16:02,037 Epoch: [11][40/500] Time 0.020 (0.020) Data 0.001 (0.007) Loss 0.1248 (0.1467) Prec@1 80.000 (73.600) Prec@5 100.000 (97.400) +2022-11-14 13:16:02,301 Epoch: [11][50/500] Time 0.027 (0.020) Data 0.002 (0.006) Loss 0.1558 (0.1482) Prec@1 70.000 (73.000) Prec@5 97.000 (97.333) +2022-11-14 13:16:02,606 Epoch: [11][60/500] Time 0.028 (0.022) Data 0.002 (0.005) Loss 0.1245 (0.1448) Prec@1 79.000 (73.857) Prec@5 98.000 (97.429) +2022-11-14 13:16:02,942 Epoch: [11][70/500] Time 0.032 (0.023) Data 0.002 (0.005) Loss 0.1692 (0.1479) Prec@1 69.000 (73.250) Prec@5 96.000 (97.250) +2022-11-14 13:16:03,247 Epoch: [11][80/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.1385 (0.1468) Prec@1 75.000 (73.444) Prec@5 99.000 (97.444) +2022-11-14 13:16:03,559 Epoch: [11][90/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.1446 (0.1466) Prec@1 78.000 (73.900) Prec@5 99.000 (97.600) +2022-11-14 13:16:03,854 Epoch: [11][100/500] Time 0.025 (0.024) Data 0.001 (0.004) Loss 0.1661 (0.1484) Prec@1 66.000 (73.182) Prec@5 97.000 (97.545) +2022-11-14 13:16:04,147 Epoch: [11][110/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.1549 (0.1489) Prec@1 73.000 (73.167) Prec@5 94.000 (97.250) +2022-11-14 13:16:04,460 Epoch: [11][120/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.1397 (0.1482) Prec@1 78.000 (73.538) Prec@5 96.000 (97.154) +2022-11-14 13:16:04,761 Epoch: [11][130/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.1607 (0.1491) Prec@1 69.000 (73.214) Prec@5 94.000 (96.929) +2022-11-14 13:16:05,071 Epoch: [11][140/500] Time 0.036 (0.025) Data 0.002 (0.003) Loss 0.1136 (0.1467) Prec@1 80.000 (73.667) Prec@5 98.000 (97.000) +2022-11-14 13:16:05,360 Epoch: [11][150/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.1147 (0.1447) Prec@1 79.000 (74.000) Prec@5 98.000 (97.062) +2022-11-14 13:16:05,657 Epoch: [11][160/500] Time 0.026 (0.025) Data 0.002 (0.003) Loss 0.1230 (0.1435) Prec@1 83.000 (74.529) Prec@5 97.000 (97.059) +2022-11-14 13:16:05,955 Epoch: [11][170/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.1583 (0.1443) Prec@1 69.000 (74.222) Prec@5 97.000 (97.056) +2022-11-14 13:16:06,254 Epoch: [11][180/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.1847 (0.1464) Prec@1 67.000 (73.842) Prec@5 96.000 (97.000) +2022-11-14 13:16:06,550 Epoch: [11][190/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.1519 (0.1467) Prec@1 71.000 (73.700) Prec@5 99.000 (97.100) +2022-11-14 13:16:06,850 Epoch: [11][200/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.1727 (0.1479) Prec@1 66.000 (73.333) Prec@5 98.000 (97.143) +2022-11-14 13:16:07,162 Epoch: [11][210/500] Time 0.026 (0.025) Data 0.002 (0.003) Loss 0.1985 (0.1502) Prec@1 64.000 (72.909) Prec@5 97.000 (97.136) +2022-11-14 13:16:07,468 Epoch: [11][220/500] Time 0.037 (0.025) Data 0.003 (0.003) Loss 0.1363 (0.1496) Prec@1 72.000 (72.870) Prec@5 97.000 (97.130) +2022-11-14 13:16:07,756 Epoch: [11][230/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.1575 (0.1499) Prec@1 75.000 (72.958) Prec@5 94.000 (97.000) +2022-11-14 13:16:08,051 Epoch: [11][240/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.2015 (0.1520) Prec@1 62.000 (72.520) Prec@5 95.000 (96.920) +2022-11-14 13:16:08,353 Epoch: [11][250/500] Time 0.025 (0.025) Data 0.002 (0.003) Loss 0.1811 (0.1531) Prec@1 71.000 (72.462) Prec@5 93.000 (96.769) +2022-11-14 13:16:08,655 Epoch: [11][260/500] Time 0.025 (0.026) Data 0.002 (0.003) Loss 0.1586 (0.1533) Prec@1 70.000 (72.370) Prec@5 96.000 (96.741) +2022-11-14 13:16:08,957 Epoch: [11][270/500] Time 0.036 (0.026) Data 0.002 (0.003) Loss 0.1628 (0.1537) Prec@1 70.000 (72.286) Prec@5 99.000 (96.821) +2022-11-14 13:16:09,247 Epoch: [11][280/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.1646 (0.1540) Prec@1 67.000 (72.103) Prec@5 93.000 (96.690) +2022-11-14 13:16:09,559 Epoch: [11][290/500] Time 0.023 (0.026) Data 0.002 (0.002) Loss 0.1759 (0.1548) Prec@1 69.000 (72.000) Prec@5 97.000 (96.700) +2022-11-14 13:16:09,852 Epoch: [11][300/500] Time 0.027 (0.026) Data 0.002 (0.002) Loss 0.1771 (0.1555) Prec@1 65.000 (71.774) Prec@5 93.000 (96.581) +2022-11-14 13:16:10,159 Epoch: [11][310/500] Time 0.029 (0.026) Data 0.002 (0.002) Loss 0.1532 (0.1554) Prec@1 71.000 (71.750) Prec@5 98.000 (96.625) +2022-11-14 13:16:10,455 Epoch: [11][320/500] Time 0.022 (0.026) Data 0.002 (0.002) Loss 0.1656 (0.1557) Prec@1 71.000 (71.727) Prec@5 98.000 (96.667) +2022-11-14 13:16:10,759 Epoch: [11][330/500] Time 0.027 (0.026) Data 0.002 (0.002) Loss 0.1598 (0.1558) Prec@1 70.000 (71.676) Prec@5 99.000 (96.735) +2022-11-14 13:16:11,063 Epoch: [11][340/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.1835 (0.1566) Prec@1 67.000 (71.543) Prec@5 95.000 (96.686) +2022-11-14 13:16:11,358 Epoch: [11][350/500] Time 0.026 (0.026) Data 0.002 (0.002) Loss 0.1573 (0.1567) Prec@1 74.000 (71.611) Prec@5 97.000 (96.694) +2022-11-14 13:16:11,649 Epoch: [11][360/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.1656 (0.1569) Prec@1 72.000 (71.622) Prec@5 96.000 (96.676) +2022-11-14 13:16:11,951 Epoch: [11][370/500] Time 0.030 (0.026) Data 0.002 (0.002) Loss 0.1576 (0.1569) Prec@1 74.000 (71.684) Prec@5 97.000 (96.684) +2022-11-14 13:16:12,247 Epoch: [11][380/500] Time 0.028 (0.026) Data 0.001 (0.002) Loss 0.1338 (0.1563) Prec@1 74.000 (71.744) Prec@5 97.000 (96.692) +2022-11-14 13:16:12,545 Epoch: [11][390/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.1151 (0.1553) Prec@1 81.000 (71.975) Prec@5 96.000 (96.675) +2022-11-14 13:16:12,840 Epoch: [11][400/500] Time 0.027 (0.026) Data 0.002 (0.002) Loss 0.1530 (0.1552) Prec@1 72.000 (71.976) Prec@5 97.000 (96.683) +2022-11-14 13:16:13,140 Epoch: [11][410/500] Time 0.027 (0.026) Data 0.002 (0.002) Loss 0.1789 (0.1558) Prec@1 67.000 (71.857) Prec@5 96.000 (96.667) +2022-11-14 13:16:13,439 Epoch: [11][420/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.1519 (0.1557) Prec@1 72.000 (71.860) Prec@5 97.000 (96.674) +2022-11-14 13:16:13,790 Epoch: [11][430/500] Time 0.022 (0.026) Data 0.002 (0.002) Loss 0.1349 (0.1552) Prec@1 76.000 (71.955) Prec@5 97.000 (96.682) +2022-11-14 13:16:14,073 Epoch: [11][440/500] Time 0.027 (0.026) Data 0.002 (0.002) Loss 0.1589 (0.1553) Prec@1 74.000 (72.000) Prec@5 94.000 (96.622) +2022-11-14 13:16:14,387 Epoch: [11][450/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.1712 (0.1557) Prec@1 66.000 (71.870) Prec@5 99.000 (96.674) +2022-11-14 13:16:14,700 Epoch: [11][460/500] Time 0.023 (0.026) Data 0.002 (0.002) Loss 0.1644 (0.1559) Prec@1 71.000 (71.851) Prec@5 97.000 (96.681) +2022-11-14 13:16:15,078 Epoch: [11][470/500] Time 0.029 (0.026) Data 0.002 (0.002) Loss 0.1407 (0.1555) Prec@1 71.000 (71.833) Prec@5 97.000 (96.688) +2022-11-14 13:16:15,357 Epoch: [11][480/500] Time 0.025 (0.026) Data 0.002 (0.002) Loss 0.1670 (0.1558) Prec@1 73.000 (71.857) Prec@5 96.000 (96.673) +2022-11-14 13:16:15,698 Epoch: [11][490/500] Time 0.024 (0.026) Data 0.001 (0.002) Loss 0.1358 (0.1554) Prec@1 76.000 (71.940) Prec@5 99.000 (96.720) +2022-11-14 13:16:15,969 Epoch: [11][499/500] Time 0.029 (0.026) Data 0.001 (0.002) Loss 0.1582 (0.1554) Prec@1 74.000 (71.980) Prec@5 96.000 (96.706) +2022-11-14 13:16:16,245 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1834 (0.1834) Prec@1 70.000 (70.000) Prec@5 96.000 (96.000) +2022-11-14 13:16:16,252 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1776 (0.1805) Prec@1 69.000 (69.500) Prec@5 96.000 (96.000) +2022-11-14 13:16:16,261 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1991 (0.1867) Prec@1 61.000 (66.667) Prec@5 92.000 (94.667) +2022-11-14 13:16:16,274 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1666 (0.1817) Prec@1 68.000 (67.000) Prec@5 98.000 (95.500) +2022-11-14 13:16:16,285 Test: [4/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1835 (0.1820) Prec@1 68.000 (67.200) Prec@5 91.000 (94.600) +2022-11-14 13:16:16,295 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1567 (0.1778) Prec@1 72.000 (68.000) Prec@5 97.000 (95.000) +2022-11-14 13:16:16,304 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1979 (0.1807) Prec@1 64.000 (67.429) Prec@5 94.000 (94.857) +2022-11-14 13:16:16,313 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1894 (0.1818) Prec@1 65.000 (67.125) Prec@5 93.000 (94.625) +2022-11-14 13:16:16,324 Test: [8/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1920 (0.1829) Prec@1 60.000 (66.333) Prec@5 98.000 (95.000) +2022-11-14 13:16:16,336 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1754 (0.1822) Prec@1 64.000 (66.100) Prec@5 94.000 (94.900) +2022-11-14 13:16:16,346 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1786 (0.1818) Prec@1 70.000 (66.455) Prec@5 92.000 (94.636) +2022-11-14 13:16:16,355 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1990 (0.1833) Prec@1 68.000 (66.583) Prec@5 94.000 (94.583) +2022-11-14 13:16:16,368 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1541 (0.1810) Prec@1 72.000 (67.000) Prec@5 97.000 (94.769) +2022-11-14 13:16:16,377 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1266 (0.1771) Prec@1 77.000 (67.714) Prec@5 98.000 (95.000) +2022-11-14 13:16:16,386 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1881 (0.1779) Prec@1 65.000 (67.533) Prec@5 94.000 (94.933) +2022-11-14 13:16:16,395 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1876 (0.1785) Prec@1 61.000 (67.125) Prec@5 93.000 (94.812) +2022-11-14 13:16:16,403 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1407 (0.1762) Prec@1 76.000 (67.647) Prec@5 97.000 (94.941) +2022-11-14 13:16:16,413 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1744 (0.1761) Prec@1 66.000 (67.556) Prec@5 94.000 (94.889) +2022-11-14 13:16:16,422 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1830 (0.1765) Prec@1 66.000 (67.474) Prec@5 94.000 (94.842) +2022-11-14 13:16:16,429 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2192 (0.1786) Prec@1 61.000 (67.150) Prec@5 89.000 (94.550) +2022-11-14 13:16:16,437 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2122 (0.1802) Prec@1 62.000 (66.905) Prec@5 95.000 (94.571) +2022-11-14 13:16:16,445 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1728 (0.1799) Prec@1 72.000 (67.136) Prec@5 96.000 (94.636) +2022-11-14 13:16:16,455 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1843 (0.1801) Prec@1 67.000 (67.130) Prec@5 96.000 (94.696) +2022-11-14 13:16:16,463 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2042 (0.1811) Prec@1 60.000 (66.833) Prec@5 97.000 (94.792) +2022-11-14 13:16:16,472 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2021 (0.1819) Prec@1 66.000 (66.800) Prec@5 97.000 (94.880) +2022-11-14 13:16:16,482 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2324 (0.1839) Prec@1 59.000 (66.500) Prec@5 92.000 (94.769) +2022-11-14 13:16:16,492 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1836) Prec@1 67.000 (66.519) Prec@5 98.000 (94.889) +2022-11-14 13:16:16,500 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1831) Prec@1 70.000 (66.643) Prec@5 95.000 (94.893) +2022-11-14 13:16:16,510 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1827) Prec@1 68.000 (66.690) Prec@5 93.000 (94.828) +2022-11-14 13:16:16,519 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1631 (0.1821) Prec@1 72.000 (66.867) Prec@5 95.000 (94.833) +2022-11-14 13:16:16,528 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1818) Prec@1 67.000 (66.871) Prec@5 97.000 (94.903) +2022-11-14 13:16:16,537 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1837 (0.1819) Prec@1 69.000 (66.938) Prec@5 96.000 (94.938) +2022-11-14 13:16:16,547 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1812 (0.1819) Prec@1 68.000 (66.970) Prec@5 91.000 (94.818) +2022-11-14 13:16:16,556 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1812) Prec@1 72.000 (67.118) Prec@5 94.000 (94.794) +2022-11-14 13:16:16,565 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2062 (0.1819) Prec@1 62.000 (66.971) Prec@5 96.000 (94.829) +2022-11-14 13:16:16,575 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1842 (0.1820) Prec@1 69.000 (67.028) Prec@5 95.000 (94.833) +2022-11-14 13:16:16,585 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1834 (0.1820) Prec@1 69.000 (67.081) Prec@5 93.000 (94.784) +2022-11-14 13:16:16,595 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1899 (0.1822) Prec@1 65.000 (67.026) Prec@5 96.000 (94.816) +2022-11-14 13:16:16,605 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1599 (0.1817) Prec@1 72.000 (67.154) Prec@5 96.000 (94.846) +2022-11-14 13:16:16,615 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1490 (0.1808) Prec@1 73.000 (67.300) Prec@5 95.000 (94.850) +2022-11-14 13:16:16,624 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1700 (0.1806) Prec@1 71.000 (67.390) Prec@5 96.000 (94.878) +2022-11-14 13:16:16,635 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1756 (0.1805) Prec@1 66.000 (67.357) Prec@5 95.000 (94.881) +2022-11-14 13:16:16,645 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1427 (0.1796) Prec@1 77.000 (67.581) Prec@5 94.000 (94.860) +2022-11-14 13:16:16,654 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1641 (0.1792) Prec@1 70.000 (67.636) Prec@5 95.000 (94.864) +2022-11-14 13:16:16,664 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1824 (0.1793) Prec@1 70.000 (67.689) Prec@5 94.000 (94.844) +2022-11-14 13:16:16,673 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1915 (0.1796) Prec@1 63.000 (67.587) Prec@5 96.000 (94.870) +2022-11-14 13:16:16,683 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1791) Prec@1 73.000 (67.702) Prec@5 98.000 (94.936) +2022-11-14 13:16:16,695 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1875 (0.1793) Prec@1 64.000 (67.625) Prec@5 93.000 (94.896) +2022-11-14 13:16:16,709 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1788) Prec@1 73.000 (67.735) Prec@5 96.000 (94.918) +2022-11-14 13:16:16,725 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1365 (0.1779) Prec@1 75.000 (67.880) Prec@5 98.000 (94.980) +2022-11-14 13:16:16,738 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1850 (0.1781) Prec@1 69.000 (67.902) Prec@5 96.000 (95.000) +2022-11-14 13:16:16,751 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1721 (0.1779) Prec@1 68.000 (67.904) Prec@5 98.000 (95.058) +2022-11-14 13:16:16,766 Test: [52/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1713 (0.1778) Prec@1 68.000 (67.906) Prec@5 97.000 (95.094) +2022-11-14 13:16:16,782 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1724 (0.1777) Prec@1 71.000 (67.963) Prec@5 94.000 (95.074) +2022-11-14 13:16:16,797 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1978 (0.1781) Prec@1 62.000 (67.855) Prec@5 97.000 (95.109) +2022-11-14 13:16:16,813 Test: [55/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1760 (0.1780) Prec@1 69.000 (67.875) Prec@5 94.000 (95.089) +2022-11-14 13:16:16,828 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1688 (0.1779) Prec@1 69.000 (67.895) Prec@5 99.000 (95.158) +2022-11-14 13:16:16,843 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1599 (0.1776) Prec@1 67.000 (67.879) Prec@5 97.000 (95.190) +2022-11-14 13:16:16,854 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2084 (0.1781) Prec@1 59.000 (67.729) Prec@5 97.000 (95.220) +2022-11-14 13:16:16,864 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1958 (0.1784) Prec@1 66.000 (67.700) Prec@5 97.000 (95.250) +2022-11-14 13:16:16,874 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1833 (0.1785) Prec@1 69.000 (67.721) Prec@5 94.000 (95.230) +2022-11-14 13:16:16,883 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1784) Prec@1 67.000 (67.710) Prec@5 95.000 (95.226) +2022-11-14 13:16:16,893 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1772 (0.1784) Prec@1 72.000 (67.778) Prec@5 95.000 (95.222) +2022-11-14 13:16:16,901 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1770 (0.1784) Prec@1 66.000 (67.750) Prec@5 96.000 (95.234) +2022-11-14 13:16:16,910 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2088 (0.1788) Prec@1 64.000 (67.692) Prec@5 93.000 (95.200) +2022-11-14 13:16:16,920 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1975 (0.1791) Prec@1 68.000 (67.697) Prec@5 92.000 (95.152) +2022-11-14 13:16:16,930 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1987 (0.1794) Prec@1 63.000 (67.627) Prec@5 97.000 (95.179) +2022-11-14 13:16:16,939 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1737 (0.1793) Prec@1 68.000 (67.632) Prec@5 94.000 (95.162) +2022-11-14 13:16:16,949 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2091 (0.1798) Prec@1 62.000 (67.551) Prec@5 97.000 (95.188) +2022-11-14 13:16:16,957 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1992 (0.1800) Prec@1 66.000 (67.529) Prec@5 94.000 (95.171) +2022-11-14 13:16:16,965 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1636 (0.1798) Prec@1 76.000 (67.648) Prec@5 99.000 (95.225) +2022-11-14 13:16:16,974 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1796) Prec@1 71.000 (67.694) Prec@5 95.000 (95.222) +2022-11-14 13:16:16,984 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1794) Prec@1 77.000 (67.822) Prec@5 94.000 (95.205) +2022-11-14 13:16:16,993 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1662 (0.1792) Prec@1 70.000 (67.851) Prec@5 99.000 (95.257) +2022-11-14 13:16:17,001 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1858 (0.1793) Prec@1 70.000 (67.880) Prec@5 95.000 (95.253) +2022-11-14 13:16:17,010 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1908 (0.1795) Prec@1 64.000 (67.829) Prec@5 96.000 (95.263) +2022-11-14 13:16:17,019 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1973 (0.1797) Prec@1 63.000 (67.766) Prec@5 97.000 (95.286) +2022-11-14 13:16:17,028 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1792) Prec@1 72.000 (67.821) Prec@5 98.000 (95.321) +2022-11-14 13:16:17,037 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.1793) Prec@1 66.000 (67.797) Prec@5 95.000 (95.316) +2022-11-14 13:16:17,046 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1860 (0.1794) Prec@1 67.000 (67.787) Prec@5 94.000 (95.300) +2022-11-14 13:16:17,055 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1738 (0.1793) Prec@1 74.000 (67.864) Prec@5 93.000 (95.272) +2022-11-14 13:16:17,065 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1617 (0.1791) Prec@1 72.000 (67.915) Prec@5 98.000 (95.305) +2022-11-14 13:16:17,075 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1784 (0.1791) Prec@1 65.000 (67.880) Prec@5 98.000 (95.337) +2022-11-14 13:16:17,084 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2052 (0.1794) Prec@1 65.000 (67.845) Prec@5 94.000 (95.321) +2022-11-14 13:16:17,092 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2050 (0.1797) Prec@1 65.000 (67.812) Prec@5 92.000 (95.282) +2022-11-14 13:16:17,102 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1907 (0.1798) Prec@1 64.000 (67.767) Prec@5 92.000 (95.244) +2022-11-14 13:16:17,111 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1758 (0.1798) Prec@1 68.000 (67.770) Prec@5 97.000 (95.264) +2022-11-14 13:16:17,120 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2006 (0.1800) Prec@1 66.000 (67.750) Prec@5 93.000 (95.239) +2022-11-14 13:16:17,130 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1800) Prec@1 69.000 (67.764) Prec@5 95.000 (95.236) +2022-11-14 13:16:17,139 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2033 (0.1802) Prec@1 65.000 (67.733) Prec@5 95.000 (95.233) +2022-11-14 13:16:17,148 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1799) Prec@1 69.000 (67.747) Prec@5 93.000 (95.209) +2022-11-14 13:16:17,158 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1333 (0.1794) Prec@1 79.000 (67.870) Prec@5 97.000 (95.228) +2022-11-14 13:16:17,166 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1815 (0.1795) Prec@1 69.000 (67.882) Prec@5 94.000 (95.215) +2022-11-14 13:16:17,175 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1844 (0.1795) Prec@1 69.000 (67.894) Prec@5 98.000 (95.245) +2022-11-14 13:16:17,185 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1909 (0.1796) Prec@1 70.000 (67.916) Prec@5 95.000 (95.242) +2022-11-14 13:16:17,194 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.1795) Prec@1 71.000 (67.948) Prec@5 96.000 (95.250) +2022-11-14 13:16:17,204 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1723 (0.1794) Prec@1 69.000 (67.959) Prec@5 95.000 (95.247) +2022-11-14 13:16:17,214 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2105 (0.1797) Prec@1 60.000 (67.878) Prec@5 95.000 (95.245) +2022-11-14 13:16:17,223 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1861 (0.1798) Prec@1 68.000 (67.879) Prec@5 94.000 (95.232) +2022-11-14 13:16:17,233 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1723 (0.1797) Prec@1 69.000 (67.890) Prec@5 93.000 (95.210) +2022-11-14 13:16:17,316 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:16:17,627 Epoch: [12][0/500] Time 0.024 (0.024) Data 0.221 (0.221) Loss 0.1504 (0.1504) Prec@1 69.000 (69.000) Prec@5 97.000 (97.000) +2022-11-14 13:16:17,836 Epoch: [12][10/500] Time 0.021 (0.019) Data 0.002 (0.022) Loss 0.1362 (0.1433) Prec@1 75.000 (72.000) Prec@5 99.000 (98.000) +2022-11-14 13:16:18,063 Epoch: [12][20/500] Time 0.031 (0.019) Data 0.002 (0.012) Loss 0.1697 (0.1521) Prec@1 69.000 (71.000) Prec@5 97.000 (97.667) +2022-11-14 13:16:18,330 Epoch: [12][30/500] Time 0.021 (0.021) Data 0.001 (0.009) Loss 0.1539 (0.1526) Prec@1 69.000 (70.500) Prec@5 97.000 (97.500) +2022-11-14 13:16:18,680 Epoch: [12][40/500] Time 0.031 (0.023) Data 0.002 (0.007) Loss 0.1478 (0.1516) Prec@1 76.000 (71.600) Prec@5 99.000 (97.800) +2022-11-14 13:16:18,988 Epoch: [12][50/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.1661 (0.1540) Prec@1 70.000 (71.333) Prec@5 96.000 (97.500) +2022-11-14 13:16:19,284 Epoch: [12][60/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.1645 (0.1555) Prec@1 68.000 (70.857) Prec@5 97.000 (97.429) +2022-11-14 13:16:19,597 Epoch: [12][70/500] Time 0.024 (0.025) Data 0.002 (0.005) Loss 0.1400 (0.1536) Prec@1 78.000 (71.750) Prec@5 95.000 (97.125) +2022-11-14 13:16:19,905 Epoch: [12][80/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.1569 (0.1539) Prec@1 76.000 (72.222) Prec@5 97.000 (97.111) +2022-11-14 13:16:20,298 Epoch: [12][90/500] Time 0.043 (0.026) Data 0.003 (0.004) Loss 0.1402 (0.1526) Prec@1 73.000 (72.300) Prec@5 98.000 (97.200) +2022-11-14 13:16:20,691 Epoch: [12][100/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.1471 (0.1521) Prec@1 74.000 (72.455) Prec@5 95.000 (97.000) +2022-11-14 13:16:21,060 Epoch: [12][110/500] Time 0.045 (0.028) Data 0.002 (0.004) Loss 0.1434 (0.1514) Prec@1 75.000 (72.667) Prec@5 99.000 (97.167) +2022-11-14 13:16:21,397 Epoch: [12][120/500] Time 0.023 (0.028) Data 0.002 (0.004) Loss 0.1792 (0.1535) Prec@1 70.000 (72.462) Prec@5 97.000 (97.154) +2022-11-14 13:16:21,734 Epoch: [12][130/500] Time 0.035 (0.028) Data 0.002 (0.004) Loss 0.1366 (0.1523) Prec@1 74.000 (72.571) Prec@5 100.000 (97.357) +2022-11-14 13:16:22,026 Epoch: [12][140/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1370 (0.1513) Prec@1 73.000 (72.600) Prec@5 98.000 (97.400) +2022-11-14 13:16:22,328 Epoch: [12][150/500] Time 0.026 (0.028) Data 0.002 (0.003) Loss 0.1274 (0.1498) Prec@1 76.000 (72.812) Prec@5 98.000 (97.438) +2022-11-14 13:16:22,632 Epoch: [12][160/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1754 (0.1513) Prec@1 65.000 (72.353) Prec@5 94.000 (97.235) +2022-11-14 13:16:22,939 Epoch: [12][170/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1203 (0.1496) Prec@1 79.000 (72.722) Prec@5 99.000 (97.333) +2022-11-14 13:16:23,242 Epoch: [12][180/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1500 (0.1496) Prec@1 75.000 (72.842) Prec@5 96.000 (97.263) +2022-11-14 13:16:23,579 Epoch: [12][190/500] Time 0.025 (0.028) Data 0.002 (0.003) Loss 0.1403 (0.1491) Prec@1 78.000 (73.100) Prec@5 95.000 (97.150) +2022-11-14 13:16:23,874 Epoch: [12][200/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1640 (0.1498) Prec@1 68.000 (72.857) Prec@5 97.000 (97.143) +2022-11-14 13:16:24,179 Epoch: [12][210/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.1698 (0.1507) Prec@1 69.000 (72.682) Prec@5 96.000 (97.091) +2022-11-14 13:16:24,503 Epoch: [12][220/500] Time 0.026 (0.028) Data 0.002 (0.003) Loss 0.1913 (0.1525) Prec@1 68.000 (72.478) Prec@5 96.000 (97.043) +2022-11-14 13:16:24,866 Epoch: [12][230/500] Time 0.037 (0.028) Data 0.002 (0.003) Loss 0.1362 (0.1518) Prec@1 74.000 (72.542) Prec@5 100.000 (97.167) +2022-11-14 13:16:25,145 Epoch: [12][240/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1599 (0.1521) Prec@1 71.000 (72.480) Prec@5 99.000 (97.240) +2022-11-14 13:16:25,444 Epoch: [12][250/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1957 (0.1538) Prec@1 69.000 (72.346) Prec@5 98.000 (97.269) +2022-11-14 13:16:25,747 Epoch: [12][260/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1946 (0.1553) Prec@1 63.000 (72.000) Prec@5 92.000 (97.074) +2022-11-14 13:16:26,046 Epoch: [12][270/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1544 (0.1553) Prec@1 72.000 (72.000) Prec@5 99.000 (97.143) +2022-11-14 13:16:26,350 Epoch: [12][280/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1236 (0.1542) Prec@1 83.000 (72.379) Prec@5 98.000 (97.172) +2022-11-14 13:16:26,666 Epoch: [12][290/500] Time 0.026 (0.028) Data 0.002 (0.003) Loss 0.1624 (0.1545) Prec@1 68.000 (72.233) Prec@5 97.000 (97.167) +2022-11-14 13:16:26,981 Epoch: [12][300/500] Time 0.026 (0.028) Data 0.002 (0.003) Loss 0.1233 (0.1535) Prec@1 77.000 (72.387) Prec@5 99.000 (97.226) +2022-11-14 13:16:27,303 Epoch: [12][310/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.1404 (0.1531) Prec@1 77.000 (72.531) Prec@5 99.000 (97.281) +2022-11-14 13:16:27,609 Epoch: [12][320/500] Time 0.026 (0.028) Data 0.002 (0.003) Loss 0.1631 (0.1534) Prec@1 71.000 (72.485) Prec@5 97.000 (97.273) +2022-11-14 13:16:27,909 Epoch: [12][330/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1367 (0.1529) Prec@1 76.000 (72.588) Prec@5 97.000 (97.265) +2022-11-14 13:16:28,210 Epoch: [12][340/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1150 (0.1518) Prec@1 85.000 (72.943) Prec@5 97.000 (97.257) +2022-11-14 13:16:28,557 Epoch: [12][350/500] Time 0.035 (0.028) Data 0.002 (0.002) Loss 0.1992 (0.1531) Prec@1 64.000 (72.694) Prec@5 97.000 (97.250) +2022-11-14 13:16:28,864 Epoch: [12][360/500] Time 0.032 (0.028) Data 0.002 (0.002) Loss 0.1164 (0.1521) Prec@1 77.000 (72.811) Prec@5 99.000 (97.297) +2022-11-14 13:16:29,173 Epoch: [12][370/500] Time 0.027 (0.028) Data 0.002 (0.002) Loss 0.1516 (0.1521) Prec@1 71.000 (72.763) Prec@5 98.000 (97.316) +2022-11-14 13:16:29,524 Epoch: [12][380/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.1615 (0.1523) Prec@1 71.000 (72.718) Prec@5 96.000 (97.282) +2022-11-14 13:16:29,859 Epoch: [12][390/500] Time 0.042 (0.028) Data 0.002 (0.002) Loss 0.1599 (0.1525) Prec@1 70.000 (72.650) Prec@5 100.000 (97.350) +2022-11-14 13:16:30,148 Epoch: [12][400/500] Time 0.028 (0.028) Data 0.002 (0.002) Loss 0.1759 (0.1531) Prec@1 69.000 (72.561) Prec@5 100.000 (97.415) +2022-11-14 13:16:30,481 Epoch: [12][410/500] Time 0.025 (0.028) Data 0.002 (0.002) Loss 0.1224 (0.1524) Prec@1 80.000 (72.738) Prec@5 97.000 (97.405) +2022-11-14 13:16:30,789 Epoch: [12][420/500] Time 0.028 (0.028) Data 0.002 (0.002) Loss 0.1802 (0.1530) Prec@1 69.000 (72.651) Prec@5 98.000 (97.419) +2022-11-14 13:16:31,145 Epoch: [12][430/500] Time 0.025 (0.028) Data 0.002 (0.002) Loss 0.1350 (0.1526) Prec@1 77.000 (72.750) Prec@5 96.000 (97.386) +2022-11-14 13:16:31,439 Epoch: [12][440/500] Time 0.028 (0.028) Data 0.002 (0.002) Loss 0.1731 (0.1531) Prec@1 65.000 (72.578) Prec@5 96.000 (97.356) +2022-11-14 13:16:31,741 Epoch: [12][450/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.1478 (0.1529) Prec@1 72.000 (72.565) Prec@5 96.000 (97.326) +2022-11-14 13:16:32,059 Epoch: [12][460/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.1365 (0.1526) Prec@1 77.000 (72.660) Prec@5 97.000 (97.319) +2022-11-14 13:16:32,358 Epoch: [12][470/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.1432 (0.1524) Prec@1 75.000 (72.708) Prec@5 96.000 (97.292) +2022-11-14 13:16:32,665 Epoch: [12][480/500] Time 0.028 (0.028) Data 0.002 (0.002) Loss 0.1267 (0.1519) Prec@1 79.000 (72.837) Prec@5 99.000 (97.327) +2022-11-14 13:16:32,977 Epoch: [12][490/500] Time 0.031 (0.028) Data 0.001 (0.002) Loss 0.1816 (0.1525) Prec@1 68.000 (72.740) Prec@5 99.000 (97.360) +2022-11-14 13:16:33,264 Epoch: [12][499/500] Time 0.025 (0.028) Data 0.002 (0.002) Loss 0.1518 (0.1525) Prec@1 72.000 (72.725) Prec@5 97.000 (97.353) +2022-11-14 13:16:33,552 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1387 (0.1387) Prec@1 75.000 (75.000) Prec@5 96.000 (96.000) +2022-11-14 13:16:33,560 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1769 (0.1578) Prec@1 67.000 (71.000) Prec@5 96.000 (96.000) +2022-11-14 13:16:33,570 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1755 (0.1637) Prec@1 70.000 (70.667) Prec@5 96.000 (96.000) +2022-11-14 13:16:33,584 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1605 (0.1629) Prec@1 71.000 (70.750) Prec@5 98.000 (96.500) +2022-11-14 13:16:33,596 Test: [4/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1969 (0.1697) Prec@1 65.000 (69.600) Prec@5 97.000 (96.600) +2022-11-14 13:16:33,605 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1398 (0.1647) Prec@1 75.000 (70.500) Prec@5 97.000 (96.667) +2022-11-14 13:16:33,615 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1510 (0.1628) Prec@1 72.000 (70.714) Prec@5 98.000 (96.857) +2022-11-14 13:16:33,627 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1848 (0.1655) Prec@1 62.000 (69.625) Prec@5 98.000 (97.000) +2022-11-14 13:16:33,637 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1834 (0.1675) Prec@1 65.000 (69.111) Prec@5 97.000 (97.000) +2022-11-14 13:16:33,646 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1287 (0.1636) Prec@1 75.000 (69.700) Prec@5 98.000 (97.100) +2022-11-14 13:16:33,657 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1606 (0.1633) Prec@1 71.000 (69.818) Prec@5 98.000 (97.182) +2022-11-14 13:16:33,668 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1740 (0.1642) Prec@1 68.000 (69.667) Prec@5 96.000 (97.083) +2022-11-14 13:16:33,679 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1536 (0.1634) Prec@1 71.000 (69.769) Prec@5 97.000 (97.077) +2022-11-14 13:16:33,689 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1703 (0.1639) Prec@1 67.000 (69.571) Prec@5 98.000 (97.143) +2022-11-14 13:16:33,699 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1653 (0.1640) Prec@1 67.000 (69.400) Prec@5 98.000 (97.200) +2022-11-14 13:16:33,710 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1759 (0.1647) Prec@1 69.000 (69.375) Prec@5 94.000 (97.000) +2022-11-14 13:16:33,721 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1283 (0.1626) Prec@1 74.000 (69.647) Prec@5 95.000 (96.882) +2022-11-14 13:16:33,732 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1707 (0.1630) Prec@1 68.000 (69.556) Prec@5 99.000 (97.000) +2022-11-14 13:16:33,742 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1520 (0.1625) Prec@1 73.000 (69.737) Prec@5 94.000 (96.842) +2022-11-14 13:16:33,753 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1803 (0.1634) Prec@1 67.000 (69.600) Prec@5 94.000 (96.700) +2022-11-14 13:16:33,763 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2090 (0.1655) Prec@1 63.000 (69.286) Prec@5 97.000 (96.714) +2022-11-14 13:16:33,773 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1681 (0.1656) Prec@1 68.000 (69.227) Prec@5 96.000 (96.682) +2022-11-14 13:16:33,784 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1900 (0.1667) Prec@1 64.000 (69.000) Prec@5 97.000 (96.696) +2022-11-14 13:16:33,794 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1727 (0.1670) Prec@1 69.000 (69.000) Prec@5 94.000 (96.583) +2022-11-14 13:16:33,805 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1774 (0.1674) Prec@1 70.000 (69.040) Prec@5 96.000 (96.560) +2022-11-14 13:16:33,816 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1803 (0.1679) Prec@1 66.000 (68.923) Prec@5 97.000 (96.577) +2022-11-14 13:16:33,826 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1869 (0.1686) Prec@1 68.000 (68.889) Prec@5 97.000 (96.593) +2022-11-14 13:16:33,836 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1785 (0.1689) Prec@1 72.000 (69.000) Prec@5 92.000 (96.429) +2022-11-14 13:16:33,846 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1832 (0.1694) Prec@1 65.000 (68.862) Prec@5 94.000 (96.345) +2022-11-14 13:16:33,856 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1586 (0.1691) Prec@1 67.000 (68.800) Prec@5 94.000 (96.267) +2022-11-14 13:16:33,866 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1428 (0.1682) Prec@1 76.000 (69.032) Prec@5 93.000 (96.161) +2022-11-14 13:16:33,878 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1878 (0.1688) Prec@1 66.000 (68.938) Prec@5 95.000 (96.125) +2022-11-14 13:16:33,890 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1573 (0.1685) Prec@1 69.000 (68.939) Prec@5 97.000 (96.152) +2022-11-14 13:16:33,901 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2228 (0.1701) Prec@1 61.000 (68.706) Prec@5 93.000 (96.059) +2022-11-14 13:16:33,913 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1747 (0.1702) Prec@1 71.000 (68.771) Prec@5 96.000 (96.057) +2022-11-14 13:16:33,923 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1587 (0.1699) Prec@1 71.000 (68.833) Prec@5 98.000 (96.111) +2022-11-14 13:16:33,935 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1744 (0.1700) Prec@1 70.000 (68.865) Prec@5 95.000 (96.081) +2022-11-14 13:16:33,948 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1853 (0.1704) Prec@1 69.000 (68.868) Prec@5 96.000 (96.079) +2022-11-14 13:16:33,958 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1408 (0.1697) Prec@1 72.000 (68.949) Prec@5 98.000 (96.128) +2022-11-14 13:16:33,969 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1587 (0.1694) Prec@1 73.000 (69.050) Prec@5 95.000 (96.100) +2022-11-14 13:16:33,978 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1891 (0.1699) Prec@1 68.000 (69.024) Prec@5 92.000 (96.000) +2022-11-14 13:16:33,988 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1672 (0.1698) Prec@1 71.000 (69.071) Prec@5 92.000 (95.905) +2022-11-14 13:16:33,999 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1605 (0.1696) Prec@1 70.000 (69.093) Prec@5 98.000 (95.953) +2022-11-14 13:16:34,009 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1665 (0.1695) Prec@1 69.000 (69.091) Prec@5 98.000 (96.000) +2022-11-14 13:16:34,020 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1292 (0.1686) Prec@1 75.000 (69.222) Prec@5 98.000 (96.044) +2022-11-14 13:16:34,030 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1507 (0.1682) Prec@1 78.000 (69.413) Prec@5 94.000 (96.000) +2022-11-14 13:16:34,041 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1561 (0.1680) Prec@1 73.000 (69.489) Prec@5 97.000 (96.021) +2022-11-14 13:16:34,051 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1747 (0.1681) Prec@1 67.000 (69.438) Prec@5 96.000 (96.021) +2022-11-14 13:16:34,064 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1439 (0.1676) Prec@1 72.000 (69.490) Prec@5 98.000 (96.061) +2022-11-14 13:16:34,076 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1909 (0.1681) Prec@1 65.000 (69.400) Prec@5 94.000 (96.020) +2022-11-14 13:16:34,088 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1733 (0.1682) Prec@1 67.000 (69.353) Prec@5 94.000 (95.980) +2022-11-14 13:16:34,099 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1596 (0.1680) Prec@1 72.000 (69.404) Prec@5 95.000 (95.962) +2022-11-14 13:16:34,111 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1481 (0.1676) Prec@1 71.000 (69.434) Prec@5 99.000 (96.019) +2022-11-14 13:16:34,122 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1972 (0.1682) Prec@1 60.000 (69.259) Prec@5 96.000 (96.019) +2022-11-14 13:16:34,132 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1948 (0.1687) Prec@1 66.000 (69.200) Prec@5 95.000 (96.000) +2022-11-14 13:16:34,145 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1646 (0.1686) Prec@1 71.000 (69.232) Prec@5 95.000 (95.982) +2022-11-14 13:16:34,156 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1923 (0.1690) Prec@1 64.000 (69.140) Prec@5 95.000 (95.965) +2022-11-14 13:16:34,167 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1430 (0.1686) Prec@1 73.000 (69.207) Prec@5 98.000 (96.000) +2022-11-14 13:16:34,178 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2216 (0.1695) Prec@1 61.000 (69.068) Prec@5 96.000 (96.000) +2022-11-14 13:16:34,188 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1745 (0.1695) Prec@1 64.000 (68.983) Prec@5 93.000 (95.950) +2022-11-14 13:16:34,199 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1721 (0.1696) Prec@1 71.000 (69.016) Prec@5 96.000 (95.951) +2022-11-14 13:16:34,208 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1615 (0.1695) Prec@1 69.000 (69.016) Prec@5 99.000 (96.000) +2022-11-14 13:16:34,219 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1532 (0.1692) Prec@1 70.000 (69.032) Prec@5 99.000 (96.048) +2022-11-14 13:16:34,230 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1536 (0.1690) Prec@1 75.000 (69.125) Prec@5 98.000 (96.078) +2022-11-14 13:16:34,243 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1810 (0.1691) Prec@1 65.000 (69.062) Prec@5 96.000 (96.077) +2022-11-14 13:16:34,254 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1618 (0.1690) Prec@1 69.000 (69.061) Prec@5 94.000 (96.045) +2022-11-14 13:16:34,265 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1665 (0.1690) Prec@1 69.000 (69.060) Prec@5 96.000 (96.045) +2022-11-14 13:16:34,276 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2049 (0.1695) Prec@1 55.000 (68.853) Prec@5 96.000 (96.044) +2022-11-14 13:16:34,287 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1774 (0.1696) Prec@1 66.000 (68.812) Prec@5 93.000 (96.000) +2022-11-14 13:16:34,300 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1886 (0.1699) Prec@1 67.000 (68.786) Prec@5 95.000 (95.986) +2022-11-14 13:16:34,312 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1666 (0.1699) Prec@1 71.000 (68.817) Prec@5 96.000 (95.986) +2022-11-14 13:16:34,322 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1856 (0.1701) Prec@1 62.000 (68.722) Prec@5 97.000 (96.000) +2022-11-14 13:16:34,333 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1756 (0.1702) Prec@1 66.000 (68.685) Prec@5 97.000 (96.014) +2022-11-14 13:16:34,342 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1444 (0.1698) Prec@1 74.000 (68.757) Prec@5 99.000 (96.054) +2022-11-14 13:16:34,354 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1842 (0.1700) Prec@1 64.000 (68.693) Prec@5 96.000 (96.053) +2022-11-14 13:16:34,364 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1357 (0.1695) Prec@1 74.000 (68.763) Prec@5 98.000 (96.079) +2022-11-14 13:16:34,375 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1762 (0.1696) Prec@1 69.000 (68.766) Prec@5 97.000 (96.091) +2022-11-14 13:16:34,386 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1848 (0.1698) Prec@1 61.000 (68.667) Prec@5 95.000 (96.077) +2022-11-14 13:16:34,396 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1822 (0.1700) Prec@1 65.000 (68.620) Prec@5 97.000 (96.089) +2022-11-14 13:16:34,407 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1867 (0.1702) Prec@1 67.000 (68.600) Prec@5 94.000 (96.062) +2022-11-14 13:16:34,416 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1410 (0.1698) Prec@1 72.000 (68.642) Prec@5 97.000 (96.074) +2022-11-14 13:16:34,426 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1772 (0.1699) Prec@1 65.000 (68.598) Prec@5 96.000 (96.073) +2022-11-14 13:16:34,438 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1599 (0.1698) Prec@1 70.000 (68.614) Prec@5 93.000 (96.036) +2022-11-14 13:16:34,449 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1690 (0.1698) Prec@1 70.000 (68.631) Prec@5 97.000 (96.048) +2022-11-14 13:16:34,460 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1810 (0.1699) Prec@1 67.000 (68.612) Prec@5 96.000 (96.047) +2022-11-14 13:16:34,471 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1521 (0.1697) Prec@1 74.000 (68.674) Prec@5 98.000 (96.070) +2022-11-14 13:16:34,481 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1926 (0.1700) Prec@1 62.000 (68.598) Prec@5 98.000 (96.092) +2022-11-14 13:16:34,494 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1680 (0.1700) Prec@1 69.000 (68.602) Prec@5 97.000 (96.102) +2022-11-14 13:16:34,507 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1424 (0.1696) Prec@1 75.000 (68.674) Prec@5 97.000 (96.112) +2022-11-14 13:16:34,518 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1602 (0.1695) Prec@1 74.000 (68.733) Prec@5 97.000 (96.122) +2022-11-14 13:16:34,527 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1539 (0.1694) Prec@1 73.000 (68.780) Prec@5 97.000 (96.132) +2022-11-14 13:16:34,537 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.1688) Prec@1 82.000 (68.924) Prec@5 97.000 (96.141) +2022-11-14 13:16:34,549 Test: [92/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1777 (0.1689) Prec@1 66.000 (68.892) Prec@5 93.000 (96.108) +2022-11-14 13:16:34,558 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1688) Prec@1 70.000 (68.904) Prec@5 94.000 (96.085) +2022-11-14 13:16:34,569 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1399 (0.1685) Prec@1 77.000 (68.989) Prec@5 97.000 (96.095) +2022-11-14 13:16:34,581 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1511 (0.1683) Prec@1 72.000 (69.021) Prec@5 95.000 (96.083) +2022-11-14 13:16:34,590 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1679) Prec@1 77.000 (69.103) Prec@5 95.000 (96.072) +2022-11-14 13:16:34,600 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.1681) Prec@1 65.000 (69.061) Prec@5 97.000 (96.082) +2022-11-14 13:16:34,612 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1902 (0.1683) Prec@1 67.000 (69.040) Prec@5 96.000 (96.081) +2022-11-14 13:16:34,623 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1614 (0.1682) Prec@1 72.000 (69.070) Prec@5 96.000 (96.080) +2022-11-14 13:16:34,679 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:16:35,004 Epoch: [13][0/500] Time 0.030 (0.030) Data 0.235 (0.235) Loss 0.1750 (0.1750) Prec@1 68.000 (68.000) Prec@5 96.000 (96.000) +2022-11-14 13:16:35,220 Epoch: [13][10/500] Time 0.016 (0.020) Data 0.002 (0.023) Loss 0.1216 (0.1483) Prec@1 79.000 (73.500) Prec@5 97.000 (96.500) +2022-11-14 13:16:35,427 Epoch: [13][20/500] Time 0.018 (0.019) Data 0.001 (0.013) Loss 0.1955 (0.1640) Prec@1 69.000 (72.000) Prec@5 95.000 (96.000) +2022-11-14 13:16:35,826 Epoch: [13][30/500] Time 0.045 (0.024) Data 0.002 (0.009) Loss 0.1527 (0.1612) Prec@1 73.000 (72.250) Prec@5 96.000 (96.000) +2022-11-14 13:16:36,332 Epoch: [13][40/500] Time 0.045 (0.029) Data 0.002 (0.007) Loss 0.1394 (0.1568) Prec@1 73.000 (72.400) Prec@5 97.000 (96.200) +2022-11-14 13:16:36,956 Epoch: [13][50/500] Time 0.072 (0.035) Data 0.002 (0.006) Loss 0.1834 (0.1612) Prec@1 66.000 (71.333) Prec@5 96.000 (96.167) +2022-11-14 13:16:37,639 Epoch: [13][60/500] Time 0.073 (0.040) Data 0.002 (0.006) Loss 0.1520 (0.1599) Prec@1 72.000 (71.429) Prec@5 97.000 (96.286) +2022-11-14 13:16:38,113 Epoch: [13][70/500] Time 0.042 (0.040) Data 0.002 (0.005) Loss 0.1213 (0.1551) Prec@1 79.000 (72.375) Prec@5 98.000 (96.500) +2022-11-14 13:16:38,584 Epoch: [13][80/500] Time 0.044 (0.040) Data 0.002 (0.005) Loss 0.1410 (0.1535) Prec@1 77.000 (72.889) Prec@5 100.000 (96.889) +2022-11-14 13:16:39,067 Epoch: [13][90/500] Time 0.035 (0.041) Data 0.002 (0.004) Loss 0.1313 (0.1513) Prec@1 77.000 (73.300) Prec@5 98.000 (97.000) +2022-11-14 13:16:39,419 Epoch: [13][100/500] Time 0.023 (0.040) Data 0.002 (0.004) Loss 0.1678 (0.1528) Prec@1 73.000 (73.273) Prec@5 98.000 (97.091) +2022-11-14 13:16:39,718 Epoch: [13][110/500] Time 0.029 (0.039) Data 0.002 (0.004) Loss 0.1710 (0.1543) Prec@1 67.000 (72.750) Prec@5 97.000 (97.083) +2022-11-14 13:16:40,029 Epoch: [13][120/500] Time 0.029 (0.038) Data 0.002 (0.004) Loss 0.1327 (0.1527) Prec@1 77.000 (73.077) Prec@5 97.000 (97.077) +2022-11-14 13:16:40,340 Epoch: [13][130/500] Time 0.027 (0.037) Data 0.002 (0.004) Loss 0.1523 (0.1526) Prec@1 68.000 (72.714) Prec@5 99.000 (97.214) +2022-11-14 13:16:40,649 Epoch: [13][140/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.1431 (0.1520) Prec@1 78.000 (73.067) Prec@5 99.000 (97.333) +2022-11-14 13:16:40,959 Epoch: [13][150/500] Time 0.029 (0.036) Data 0.002 (0.003) Loss 0.1547 (0.1522) Prec@1 71.000 (72.938) Prec@5 98.000 (97.375) +2022-11-14 13:16:41,268 Epoch: [13][160/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.1663 (0.1530) Prec@1 74.000 (73.000) Prec@5 97.000 (97.353) +2022-11-14 13:16:41,590 Epoch: [13][170/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.1301 (0.1517) Prec@1 79.000 (73.333) Prec@5 97.000 (97.333) +2022-11-14 13:16:41,895 Epoch: [13][180/500] Time 0.029 (0.034) Data 0.001 (0.003) Loss 0.1554 (0.1519) Prec@1 73.000 (73.316) Prec@5 96.000 (97.263) +2022-11-14 13:16:42,209 Epoch: [13][190/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1289 (0.1508) Prec@1 77.000 (73.500) Prec@5 99.000 (97.350) +2022-11-14 13:16:42,520 Epoch: [13][200/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.1316 (0.1499) Prec@1 76.000 (73.619) Prec@5 96.000 (97.286) +2022-11-14 13:16:42,833 Epoch: [13][210/500] Time 0.030 (0.033) Data 0.001 (0.003) Loss 0.1501 (0.1499) Prec@1 74.000 (73.636) Prec@5 97.000 (97.273) +2022-11-14 13:16:43,160 Epoch: [13][220/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.1647 (0.1505) Prec@1 68.000 (73.391) Prec@5 99.000 (97.348) +2022-11-14 13:16:43,511 Epoch: [13][230/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.1780 (0.1517) Prec@1 69.000 (73.208) Prec@5 95.000 (97.250) +2022-11-14 13:16:43,873 Epoch: [13][240/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.1762 (0.1526) Prec@1 68.000 (73.000) Prec@5 96.000 (97.200) +2022-11-14 13:16:44,157 Epoch: [13][250/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.1220 (0.1515) Prec@1 79.000 (73.231) Prec@5 96.000 (97.154) +2022-11-14 13:16:44,480 Epoch: [13][260/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.1342 (0.1508) Prec@1 79.000 (73.444) Prec@5 99.000 (97.222) +2022-11-14 13:16:44,790 Epoch: [13][270/500] Time 0.028 (0.032) Data 0.002 (0.003) Loss 0.1432 (0.1505) Prec@1 76.000 (73.536) Prec@5 95.000 (97.143) +2022-11-14 13:16:45,098 Epoch: [13][280/500] Time 0.026 (0.032) Data 0.003 (0.003) Loss 0.1551 (0.1507) Prec@1 70.000 (73.414) Prec@5 97.000 (97.138) +2022-11-14 13:16:45,416 Epoch: [13][290/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.1435 (0.1505) Prec@1 74.000 (73.433) Prec@5 98.000 (97.167) +2022-11-14 13:16:45,727 Epoch: [13][300/500] Time 0.028 (0.032) Data 0.002 (0.003) Loss 0.1299 (0.1498) Prec@1 76.000 (73.516) Prec@5 99.000 (97.226) +2022-11-14 13:16:46,102 Epoch: [13][310/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.1767 (0.1506) Prec@1 66.000 (73.281) Prec@5 95.000 (97.156) +2022-11-14 13:16:46,474 Epoch: [13][320/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.1439 (0.1504) Prec@1 79.000 (73.455) Prec@5 96.000 (97.121) +2022-11-14 13:16:46,803 Epoch: [13][330/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.1685 (0.1510) Prec@1 70.000 (73.353) Prec@5 97.000 (97.118) +2022-11-14 13:16:47,169 Epoch: [13][340/500] Time 0.021 (0.032) Data 0.003 (0.003) Loss 0.1645 (0.1514) Prec@1 70.000 (73.257) Prec@5 96.000 (97.086) +2022-11-14 13:16:47,533 Epoch: [13][350/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.1211 (0.1505) Prec@1 79.000 (73.417) Prec@5 96.000 (97.056) +2022-11-14 13:16:47,837 Epoch: [13][360/500] Time 0.028 (0.032) Data 0.002 (0.002) Loss 0.1407 (0.1503) Prec@1 74.000 (73.432) Prec@5 99.000 (97.108) +2022-11-14 13:16:48,150 Epoch: [13][370/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.1367 (0.1499) Prec@1 73.000 (73.421) Prec@5 100.000 (97.184) +2022-11-14 13:16:48,462 Epoch: [13][380/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.1368 (0.1496) Prec@1 73.000 (73.410) Prec@5 98.000 (97.205) +2022-11-14 13:16:48,772 Epoch: [13][390/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.1453 (0.1495) Prec@1 74.000 (73.425) Prec@5 96.000 (97.175) +2022-11-14 13:16:49,089 Epoch: [13][400/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.1415 (0.1493) Prec@1 73.000 (73.415) Prec@5 98.000 (97.195) +2022-11-14 13:16:49,405 Epoch: [13][410/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.1320 (0.1488) Prec@1 79.000 (73.548) Prec@5 98.000 (97.214) +2022-11-14 13:16:49,721 Epoch: [13][420/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.1272 (0.1483) Prec@1 73.000 (73.535) Prec@5 100.000 (97.279) +2022-11-14 13:16:50,042 Epoch: [13][430/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.1897 (0.1493) Prec@1 68.000 (73.409) Prec@5 95.000 (97.227) +2022-11-14 13:16:50,359 Epoch: [13][440/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.1312 (0.1489) Prec@1 79.000 (73.533) Prec@5 98.000 (97.244) +2022-11-14 13:16:50,670 Epoch: [13][450/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.1490 (0.1489) Prec@1 72.000 (73.500) Prec@5 97.000 (97.239) +2022-11-14 13:16:50,985 Epoch: [13][460/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.1587 (0.1491) Prec@1 69.000 (73.404) Prec@5 98.000 (97.255) +2022-11-14 13:16:51,300 Epoch: [13][470/500] Time 0.030 (0.031) Data 0.001 (0.002) Loss 0.1443 (0.1490) Prec@1 75.000 (73.438) Prec@5 98.000 (97.271) +2022-11-14 13:16:51,616 Epoch: [13][480/500] Time 0.030 (0.031) Data 0.001 (0.002) Loss 0.1494 (0.1490) Prec@1 70.000 (73.367) Prec@5 98.000 (97.286) +2022-11-14 13:16:51,936 Epoch: [13][490/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.1533 (0.1491) Prec@1 73.000 (73.360) Prec@5 93.000 (97.200) +2022-11-14 13:16:52,214 Epoch: [13][499/500] Time 0.025 (0.031) Data 0.002 (0.002) Loss 0.1352 (0.1488) Prec@1 76.000 (73.412) Prec@5 100.000 (97.255) +2022-11-14 13:16:52,486 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1594 (0.1594) Prec@1 68.000 (68.000) Prec@5 95.000 (95.000) +2022-11-14 13:16:52,494 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1589 (0.1592) Prec@1 71.000 (69.500) Prec@5 98.000 (96.500) +2022-11-14 13:16:52,506 Test: [2/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1768 (0.1651) Prec@1 67.000 (68.667) Prec@5 97.000 (96.667) +2022-11-14 13:16:52,520 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1698 (0.1663) Prec@1 71.000 (69.250) Prec@5 97.000 (96.750) +2022-11-14 13:16:52,527 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1943 (0.1719) Prec@1 64.000 (68.200) Prec@5 96.000 (96.600) +2022-11-14 13:16:52,534 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1537 (0.1688) Prec@1 71.000 (68.667) Prec@5 97.000 (96.667) +2022-11-14 13:16:52,545 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1870 (0.1714) Prec@1 65.000 (68.143) Prec@5 98.000 (96.857) +2022-11-14 13:16:52,557 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1812 (0.1726) Prec@1 67.000 (68.000) Prec@5 96.000 (96.750) +2022-11-14 13:16:52,566 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2024 (0.1759) Prec@1 62.000 (67.333) Prec@5 99.000 (97.000) +2022-11-14 13:16:52,575 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1567 (0.1740) Prec@1 74.000 (68.000) Prec@5 95.000 (96.800) +2022-11-14 13:16:52,588 Test: [10/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1675 (0.1734) Prec@1 70.000 (68.182) Prec@5 98.000 (96.909) +2022-11-14 13:16:52,600 Test: [11/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1796 (0.1739) Prec@1 68.000 (68.167) Prec@5 97.000 (96.917) +2022-11-14 13:16:52,609 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1761 (0.1741) Prec@1 66.000 (68.000) Prec@5 98.000 (97.000) +2022-11-14 13:16:52,618 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1949 (0.1756) Prec@1 62.000 (67.571) Prec@5 96.000 (96.929) +2022-11-14 13:16:52,628 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1542 (0.1742) Prec@1 74.000 (68.000) Prec@5 99.000 (97.067) +2022-11-14 13:16:52,637 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2276 (0.1775) Prec@1 57.000 (67.312) Prec@5 95.000 (96.938) +2022-11-14 13:16:52,646 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1500 (0.1759) Prec@1 72.000 (67.588) Prec@5 96.000 (96.882) +2022-11-14 13:16:52,656 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1740 (0.1758) Prec@1 66.000 (67.500) Prec@5 96.000 (96.833) +2022-11-14 13:16:52,665 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1539 (0.1746) Prec@1 70.000 (67.632) Prec@5 96.000 (96.789) +2022-11-14 13:16:52,674 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1896 (0.1754) Prec@1 64.000 (67.450) Prec@5 96.000 (96.750) +2022-11-14 13:16:52,683 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1752 (0.1754) Prec@1 68.000 (67.476) Prec@5 97.000 (96.762) +2022-11-14 13:16:52,693 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1994 (0.1765) Prec@1 63.000 (67.273) Prec@5 92.000 (96.545) +2022-11-14 13:16:52,702 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1915 (0.1771) Prec@1 66.000 (67.217) Prec@5 94.000 (96.435) +2022-11-14 13:16:52,711 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1760 (0.1771) Prec@1 70.000 (67.333) Prec@5 95.000 (96.375) +2022-11-14 13:16:52,720 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1560 (0.1762) Prec@1 72.000 (67.520) Prec@5 96.000 (96.360) +2022-11-14 13:16:52,729 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2023 (0.1772) Prec@1 56.000 (67.077) Prec@5 92.000 (96.192) +2022-11-14 13:16:52,739 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1821 (0.1774) Prec@1 65.000 (67.000) Prec@5 99.000 (96.296) +2022-11-14 13:16:52,748 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1684 (0.1771) Prec@1 70.000 (67.107) Prec@5 95.000 (96.250) +2022-11-14 13:16:52,757 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1835 (0.1773) Prec@1 63.000 (66.966) Prec@5 92.000 (96.103) +2022-11-14 13:16:52,768 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2042 (0.1782) Prec@1 63.000 (66.833) Prec@5 96.000 (96.100) +2022-11-14 13:16:52,776 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1826 (0.1783) Prec@1 65.000 (66.774) Prec@5 95.000 (96.065) +2022-11-14 13:16:52,785 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1498 (0.1775) Prec@1 70.000 (66.875) Prec@5 99.000 (96.156) +2022-11-14 13:16:52,794 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1565 (0.1768) Prec@1 70.000 (66.970) Prec@5 94.000 (96.091) +2022-11-14 13:16:52,804 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1974 (0.1774) Prec@1 64.000 (66.882) Prec@5 94.000 (96.029) +2022-11-14 13:16:52,813 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1841 (0.1776) Prec@1 68.000 (66.914) Prec@5 94.000 (95.971) +2022-11-14 13:16:52,822 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1681 (0.1773) Prec@1 72.000 (67.056) Prec@5 96.000 (95.972) +2022-11-14 13:16:52,831 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1654 (0.1770) Prec@1 70.000 (67.135) Prec@5 94.000 (95.919) +2022-11-14 13:16:52,843 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2131 (0.1780) Prec@1 61.000 (66.974) Prec@5 95.000 (95.895) +2022-11-14 13:16:52,854 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1452 (0.1771) Prec@1 76.000 (67.205) Prec@5 96.000 (95.897) +2022-11-14 13:16:52,863 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1601 (0.1767) Prec@1 70.000 (67.275) Prec@5 99.000 (95.975) +2022-11-14 13:16:52,872 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.1762) Prec@1 75.000 (67.463) Prec@5 96.000 (95.976) +2022-11-14 13:16:52,881 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1645 (0.1759) Prec@1 70.000 (67.524) Prec@5 95.000 (95.952) +2022-11-14 13:16:52,890 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1350 (0.1749) Prec@1 77.000 (67.744) Prec@5 98.000 (96.000) +2022-11-14 13:16:52,899 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1558 (0.1745) Prec@1 75.000 (67.909) Prec@5 95.000 (95.977) +2022-11-14 13:16:52,908 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1481 (0.1739) Prec@1 74.000 (68.044) Prec@5 99.000 (96.044) +2022-11-14 13:16:52,917 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1736) Prec@1 72.000 (68.130) Prec@5 99.000 (96.109) +2022-11-14 13:16:52,926 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1734) Prec@1 66.000 (68.085) Prec@5 98.000 (96.149) +2022-11-14 13:16:52,936 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1710 (0.1734) Prec@1 72.000 (68.167) Prec@5 92.000 (96.062) +2022-11-14 13:16:52,944 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1677 (0.1732) Prec@1 67.000 (68.143) Prec@5 100.000 (96.143) +2022-11-14 13:16:52,953 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.1737) Prec@1 67.000 (68.120) Prec@5 95.000 (96.120) +2022-11-14 13:16:52,962 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1411 (0.1731) Prec@1 66.000 (68.078) Prec@5 100.000 (96.196) +2022-11-14 13:16:52,971 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1857 (0.1733) Prec@1 64.000 (68.000) Prec@5 93.000 (96.135) +2022-11-14 13:16:52,979 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1708 (0.1733) Prec@1 72.000 (68.075) Prec@5 99.000 (96.189) +2022-11-14 13:16:52,988 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1720 (0.1733) Prec@1 70.000 (68.111) Prec@5 98.000 (96.222) +2022-11-14 13:16:52,997 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1797 (0.1734) Prec@1 69.000 (68.127) Prec@5 99.000 (96.273) +2022-11-14 13:16:53,006 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1918 (0.1737) Prec@1 65.000 (68.071) Prec@5 96.000 (96.268) +2022-11-14 13:16:53,014 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1557 (0.1734) Prec@1 74.000 (68.175) Prec@5 96.000 (96.263) +2022-11-14 13:16:53,024 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1589 (0.1731) Prec@1 70.000 (68.207) Prec@5 98.000 (96.293) +2022-11-14 13:16:53,033 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2141 (0.1738) Prec@1 62.000 (68.102) Prec@5 95.000 (96.271) +2022-11-14 13:16:53,042 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1753 (0.1739) Prec@1 68.000 (68.100) Prec@5 96.000 (96.267) +2022-11-14 13:16:53,052 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1777 (0.1739) Prec@1 69.000 (68.115) Prec@5 98.000 (96.295) +2022-11-14 13:16:53,061 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1737) Prec@1 74.000 (68.210) Prec@5 99.000 (96.339) +2022-11-14 13:16:53,070 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1631 (0.1735) Prec@1 74.000 (68.302) Prec@5 96.000 (96.333) +2022-11-14 13:16:53,080 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1409 (0.1730) Prec@1 75.000 (68.406) Prec@5 98.000 (96.359) +2022-11-14 13:16:53,088 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2004 (0.1734) Prec@1 63.000 (68.323) Prec@5 94.000 (96.323) +2022-11-14 13:16:53,097 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1785 (0.1735) Prec@1 69.000 (68.333) Prec@5 97.000 (96.333) +2022-11-14 13:16:53,106 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1733) Prec@1 70.000 (68.358) Prec@5 98.000 (96.358) +2022-11-14 13:16:53,115 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1822 (0.1734) Prec@1 69.000 (68.368) Prec@5 97.000 (96.368) +2022-11-14 13:16:53,123 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1725 (0.1734) Prec@1 68.000 (68.362) Prec@5 96.000 (96.362) +2022-11-14 13:16:53,131 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1892 (0.1736) Prec@1 64.000 (68.300) Prec@5 97.000 (96.371) +2022-11-14 13:16:53,139 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1890 (0.1738) Prec@1 68.000 (68.296) Prec@5 97.000 (96.380) +2022-11-14 13:16:53,147 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1852 (0.1740) Prec@1 64.000 (68.236) Prec@5 96.000 (96.375) +2022-11-14 13:16:53,155 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1699 (0.1739) Prec@1 73.000 (68.301) Prec@5 98.000 (96.397) +2022-11-14 13:16:53,165 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1596 (0.1737) Prec@1 70.000 (68.324) Prec@5 98.000 (96.419) +2022-11-14 13:16:53,174 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1721 (0.1737) Prec@1 65.000 (68.280) Prec@5 96.000 (96.413) +2022-11-14 13:16:53,184 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1696 (0.1737) Prec@1 73.000 (68.342) Prec@5 98.000 (96.434) +2022-11-14 13:16:53,193 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1786 (0.1737) Prec@1 69.000 (68.351) Prec@5 97.000 (96.442) +2022-11-14 13:16:53,202 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1905 (0.1739) Prec@1 65.000 (68.308) Prec@5 95.000 (96.423) +2022-11-14 13:16:53,211 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1774 (0.1740) Prec@1 68.000 (68.304) Prec@5 99.000 (96.456) +2022-11-14 13:16:53,221 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1662 (0.1739) Prec@1 73.000 (68.362) Prec@5 93.000 (96.412) +2022-11-14 13:16:53,229 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1608 (0.1737) Prec@1 75.000 (68.444) Prec@5 96.000 (96.407) +2022-11-14 13:16:53,239 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1575 (0.1735) Prec@1 75.000 (68.524) Prec@5 93.000 (96.366) +2022-11-14 13:16:53,248 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1655 (0.1734) Prec@1 74.000 (68.590) Prec@5 99.000 (96.398) +2022-11-14 13:16:53,257 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1608 (0.1733) Prec@1 69.000 (68.595) Prec@5 97.000 (96.405) +2022-11-14 13:16:53,267 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1602 (0.1731) Prec@1 70.000 (68.612) Prec@5 94.000 (96.376) +2022-11-14 13:16:53,277 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1711 (0.1731) Prec@1 64.000 (68.558) Prec@5 95.000 (96.360) +2022-11-14 13:16:53,285 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1808 (0.1732) Prec@1 65.000 (68.517) Prec@5 97.000 (96.368) +2022-11-14 13:16:53,295 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1782 (0.1733) Prec@1 71.000 (68.545) Prec@5 96.000 (96.364) +2022-11-14 13:16:53,304 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1728) Prec@1 76.000 (68.629) Prec@5 97.000 (96.371) +2022-11-14 13:16:53,313 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.1729) Prec@1 69.000 (68.633) Prec@5 97.000 (96.378) +2022-11-14 13:16:53,322 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1665 (0.1728) Prec@1 68.000 (68.626) Prec@5 96.000 (96.374) +2022-11-14 13:16:53,332 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1376 (0.1724) Prec@1 78.000 (68.728) Prec@5 95.000 (96.359) +2022-11-14 13:16:53,341 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1937 (0.1726) Prec@1 66.000 (68.699) Prec@5 95.000 (96.344) +2022-11-14 13:16:53,351 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1806 (0.1727) Prec@1 69.000 (68.702) Prec@5 98.000 (96.362) +2022-11-14 13:16:53,359 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1545 (0.1725) Prec@1 72.000 (68.737) Prec@5 94.000 (96.337) +2022-11-14 13:16:53,368 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1585 (0.1724) Prec@1 71.000 (68.760) Prec@5 96.000 (96.333) +2022-11-14 13:16:53,377 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1721) Prec@1 76.000 (68.835) Prec@5 96.000 (96.330) +2022-11-14 13:16:53,386 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2237 (0.1727) Prec@1 60.000 (68.745) Prec@5 92.000 (96.286) +2022-11-14 13:16:53,394 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1864 (0.1728) Prec@1 66.000 (68.717) Prec@5 94.000 (96.263) +2022-11-14 13:16:53,403 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1740 (0.1728) Prec@1 67.000 (68.700) Prec@5 97.000 (96.270) +2022-11-14 13:16:53,474 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:16:53,795 Epoch: [14][0/500] Time 0.025 (0.025) Data 0.233 (0.233) Loss 0.1416 (0.1416) Prec@1 78.000 (78.000) Prec@5 96.000 (96.000) +2022-11-14 13:16:54,012 Epoch: [14][10/500] Time 0.016 (0.020) Data 0.002 (0.023) Loss 0.1366 (0.1391) Prec@1 74.000 (76.000) Prec@5 100.000 (98.000) +2022-11-14 13:16:54,231 Epoch: [14][20/500] Time 0.025 (0.020) Data 0.002 (0.013) Loss 0.1328 (0.1370) Prec@1 76.000 (76.000) Prec@5 97.000 (97.667) +2022-11-14 13:16:54,447 Epoch: [14][30/500] Time 0.016 (0.020) Data 0.002 (0.009) Loss 0.1480 (0.1398) Prec@1 76.000 (76.000) Prec@5 98.000 (97.750) +2022-11-14 13:16:54,740 Epoch: [14][40/500] Time 0.037 (0.021) Data 0.002 (0.007) Loss 0.1594 (0.1437) Prec@1 67.000 (74.200) Prec@5 99.000 (98.000) +2022-11-14 13:16:55,148 Epoch: [14][50/500] Time 0.038 (0.024) Data 0.002 (0.006) Loss 0.1524 (0.1451) Prec@1 71.000 (73.667) Prec@5 96.000 (97.667) +2022-11-14 13:16:55,551 Epoch: [14][60/500] Time 0.038 (0.026) Data 0.002 (0.006) Loss 0.1176 (0.1412) Prec@1 78.000 (74.286) Prec@5 100.000 (98.000) +2022-11-14 13:16:55,961 Epoch: [14][70/500] Time 0.040 (0.027) Data 0.002 (0.005) Loss 0.1070 (0.1369) Prec@1 84.000 (75.500) Prec@5 99.000 (98.125) +2022-11-14 13:16:56,363 Epoch: [14][80/500] Time 0.036 (0.028) Data 0.002 (0.005) Loss 0.1306 (0.1362) Prec@1 77.000 (75.667) Prec@5 98.000 (98.111) +2022-11-14 13:16:56,766 Epoch: [14][90/500] Time 0.037 (0.029) Data 0.002 (0.004) Loss 0.1359 (0.1362) Prec@1 77.000 (75.800) Prec@5 98.000 (98.100) +2022-11-14 13:16:57,170 Epoch: [14][100/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.1540 (0.1378) Prec@1 74.000 (75.636) Prec@5 96.000 (97.909) +2022-11-14 13:16:57,573 Epoch: [14][110/500] Time 0.040 (0.030) Data 0.002 (0.004) Loss 0.1404 (0.1380) Prec@1 70.000 (75.167) Prec@5 98.000 (97.917) +2022-11-14 13:16:57,976 Epoch: [14][120/500] Time 0.037 (0.031) Data 0.002 (0.004) Loss 0.2082 (0.1434) Prec@1 63.000 (74.231) Prec@5 95.000 (97.692) +2022-11-14 13:16:58,390 Epoch: [14][130/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.1702 (0.1453) Prec@1 67.000 (73.714) Prec@5 97.000 (97.643) +2022-11-14 13:16:58,851 Epoch: [14][140/500] Time 0.052 (0.032) Data 0.002 (0.003) Loss 0.1497 (0.1456) Prec@1 74.000 (73.733) Prec@5 93.000 (97.333) +2022-11-14 13:16:59,269 Epoch: [14][150/500] Time 0.039 (0.032) Data 0.001 (0.003) Loss 0.1226 (0.1442) Prec@1 78.000 (74.000) Prec@5 99.000 (97.438) +2022-11-14 13:16:59,673 Epoch: [14][160/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.1439 (0.1442) Prec@1 74.000 (74.000) Prec@5 98.000 (97.471) +2022-11-14 13:17:00,071 Epoch: [14][170/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.1621 (0.1452) Prec@1 67.000 (73.611) Prec@5 99.000 (97.556) +2022-11-14 13:17:00,466 Epoch: [14][180/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.1261 (0.1442) Prec@1 73.000 (73.579) Prec@5 96.000 (97.474) +2022-11-14 13:17:00,869 Epoch: [14][190/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.1514 (0.1445) Prec@1 74.000 (73.600) Prec@5 98.000 (97.500) +2022-11-14 13:17:01,265 Epoch: [14][200/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.1420 (0.1444) Prec@1 73.000 (73.571) Prec@5 98.000 (97.524) +2022-11-14 13:17:01,662 Epoch: [14][210/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.1368 (0.1441) Prec@1 77.000 (73.727) Prec@5 97.000 (97.500) +2022-11-14 13:17:02,061 Epoch: [14][220/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.1701 (0.1452) Prec@1 73.000 (73.696) Prec@5 97.000 (97.478) +2022-11-14 13:17:02,487 Epoch: [14][230/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.1441 (0.1451) Prec@1 73.000 (73.667) Prec@5 96.000 (97.417) +2022-11-14 13:17:02,774 Epoch: [14][240/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.1549 (0.1455) Prec@1 70.000 (73.520) Prec@5 97.000 (97.400) +2022-11-14 13:17:03,036 Epoch: [14][250/500] Time 0.021 (0.033) Data 0.002 (0.003) Loss 0.1606 (0.1461) Prec@1 72.000 (73.462) Prec@5 97.000 (97.385) +2022-11-14 13:17:03,306 Epoch: [14][260/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.1467 (0.1461) Prec@1 75.000 (73.519) Prec@5 96.000 (97.333) +2022-11-14 13:17:03,592 Epoch: [14][270/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.1466 (0.1461) Prec@1 75.000 (73.571) Prec@5 98.000 (97.357) +2022-11-14 13:17:03,882 Epoch: [14][280/500] Time 0.019 (0.032) Data 0.002 (0.003) Loss 0.1285 (0.1455) Prec@1 78.000 (73.724) Prec@5 98.000 (97.379) +2022-11-14 13:17:04,141 Epoch: [14][290/500] Time 0.025 (0.032) Data 0.002 (0.003) Loss 0.1489 (0.1457) Prec@1 74.000 (73.733) Prec@5 97.000 (97.367) +2022-11-14 13:17:04,412 Epoch: [14][300/500] Time 0.027 (0.031) Data 0.002 (0.003) Loss 0.1464 (0.1457) Prec@1 75.000 (73.774) Prec@5 97.000 (97.355) +2022-11-14 13:17:04,701 Epoch: [14][310/500] Time 0.025 (0.031) Data 0.002 (0.003) Loss 0.1549 (0.1460) Prec@1 72.000 (73.719) Prec@5 95.000 (97.281) +2022-11-14 13:17:04,997 Epoch: [14][320/500] Time 0.027 (0.031) Data 0.002 (0.003) Loss 0.1728 (0.1468) Prec@1 67.000 (73.515) Prec@5 97.000 (97.273) +2022-11-14 13:17:05,310 Epoch: [14][330/500] Time 0.024 (0.031) Data 0.002 (0.003) Loss 0.1375 (0.1465) Prec@1 75.000 (73.559) Prec@5 98.000 (97.294) +2022-11-14 13:17:05,621 Epoch: [14][340/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.1665 (0.1471) Prec@1 70.000 (73.457) Prec@5 97.000 (97.286) +2022-11-14 13:17:05,892 Epoch: [14][350/500] Time 0.023 (0.031) Data 0.002 (0.003) Loss 0.1223 (0.1464) Prec@1 74.000 (73.472) Prec@5 98.000 (97.306) +2022-11-14 13:17:06,154 Epoch: [14][360/500] Time 0.026 (0.030) Data 0.002 (0.003) Loss 0.1522 (0.1465) Prec@1 72.000 (73.432) Prec@5 97.000 (97.297) +2022-11-14 13:17:06,460 Epoch: [14][370/500] Time 0.037 (0.030) Data 0.003 (0.003) Loss 0.1508 (0.1467) Prec@1 72.000 (73.395) Prec@5 97.000 (97.289) +2022-11-14 13:17:06,713 Epoch: [14][380/500] Time 0.024 (0.030) Data 0.002 (0.002) Loss 0.1450 (0.1466) Prec@1 76.000 (73.462) Prec@5 94.000 (97.205) +2022-11-14 13:17:07,000 Epoch: [14][390/500] Time 0.023 (0.030) Data 0.002 (0.002) Loss 0.1633 (0.1470) Prec@1 73.000 (73.450) Prec@5 96.000 (97.175) +2022-11-14 13:17:07,271 Epoch: [14][400/500] Time 0.029 (0.030) Data 0.002 (0.002) Loss 0.1713 (0.1476) Prec@1 70.000 (73.366) Prec@5 100.000 (97.244) +2022-11-14 13:17:07,545 Epoch: [14][410/500] Time 0.025 (0.030) Data 0.002 (0.002) Loss 0.1483 (0.1476) Prec@1 73.000 (73.357) Prec@5 99.000 (97.286) +2022-11-14 13:17:07,849 Epoch: [14][420/500] Time 0.028 (0.030) Data 0.002 (0.002) Loss 0.1747 (0.1483) Prec@1 67.000 (73.209) Prec@5 97.000 (97.279) +2022-11-14 13:17:08,115 Epoch: [14][430/500] Time 0.023 (0.030) Data 0.002 (0.002) Loss 0.1970 (0.1494) Prec@1 66.000 (73.045) Prec@5 90.000 (97.114) +2022-11-14 13:17:08,418 Epoch: [14][440/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.1464 (0.1493) Prec@1 78.000 (73.156) Prec@5 99.000 (97.156) +2022-11-14 13:17:08,665 Epoch: [14][450/500] Time 0.024 (0.029) Data 0.001 (0.002) Loss 0.1464 (0.1492) Prec@1 77.000 (73.239) Prec@5 96.000 (97.130) +2022-11-14 13:17:08,948 Epoch: [14][460/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.1403 (0.1491) Prec@1 75.000 (73.277) Prec@5 97.000 (97.128) +2022-11-14 13:17:09,326 Epoch: [14][470/500] Time 0.035 (0.029) Data 0.002 (0.002) Loss 0.0987 (0.1480) Prec@1 84.000 (73.500) Prec@5 100.000 (97.188) +2022-11-14 13:17:09,766 Epoch: [14][480/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1677 (0.1484) Prec@1 68.000 (73.388) Prec@5 98.000 (97.204) +2022-11-14 13:17:10,143 Epoch: [14][490/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.1340 (0.1481) Prec@1 76.000 (73.440) Prec@5 95.000 (97.160) +2022-11-14 13:17:10,588 Epoch: [14][499/500] Time 0.048 (0.030) Data 0.002 (0.002) Loss 0.1385 (0.1479) Prec@1 74.000 (73.451) Prec@5 99.000 (97.196) +2022-11-14 13:17:10,870 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1738 (0.1738) Prec@1 70.000 (70.000) Prec@5 92.000 (92.000) +2022-11-14 13:17:10,883 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.2254 (0.1996) Prec@1 59.000 (64.500) Prec@5 92.000 (92.000) +2022-11-14 13:17:10,894 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.2233 (0.2075) Prec@1 66.000 (65.000) Prec@5 94.000 (92.667) +2022-11-14 13:17:10,907 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1959 (0.2046) Prec@1 67.000 (65.500) Prec@5 93.000 (92.750) +2022-11-14 13:17:10,915 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2204 (0.2078) Prec@1 60.000 (64.400) Prec@5 93.000 (92.800) +2022-11-14 13:17:10,922 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2106 (0.2082) Prec@1 66.000 (64.667) Prec@5 95.000 (93.167) +2022-11-14 13:17:10,932 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2028 (0.2075) Prec@1 62.000 (64.286) Prec@5 97.000 (93.714) +2022-11-14 13:17:10,944 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2695 (0.2152) Prec@1 55.000 (63.125) Prec@5 89.000 (93.125) +2022-11-14 13:17:10,953 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2550 (0.2196) Prec@1 51.000 (61.778) Prec@5 93.000 (93.111) +2022-11-14 13:17:10,961 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1445 (0.2121) Prec@1 76.000 (63.200) Prec@5 95.000 (93.300) +2022-11-14 13:17:10,970 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1536 (0.2068) Prec@1 72.000 (64.000) Prec@5 94.000 (93.364) +2022-11-14 13:17:10,979 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1934 (0.2057) Prec@1 68.000 (64.333) Prec@5 95.000 (93.500) +2022-11-14 13:17:10,989 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2313 (0.2077) Prec@1 59.000 (63.923) Prec@5 92.000 (93.385) +2022-11-14 13:17:10,998 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2030 (0.2073) Prec@1 66.000 (64.071) Prec@5 93.000 (93.357) +2022-11-14 13:17:11,006 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2264 (0.2086) Prec@1 58.000 (63.667) Prec@5 94.000 (93.400) +2022-11-14 13:17:11,014 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.2461 (0.2110) Prec@1 56.000 (63.188) Prec@5 89.000 (93.125) +2022-11-14 13:17:11,022 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1785 (0.2090) Prec@1 66.000 (63.353) Prec@5 96.000 (93.294) +2022-11-14 13:17:11,031 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1995 (0.2085) Prec@1 66.000 (63.500) Prec@5 95.000 (93.389) +2022-11-14 13:17:11,040 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2054 (0.2084) Prec@1 62.000 (63.421) Prec@5 90.000 (93.211) +2022-11-14 13:17:11,049 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2379 (0.2098) Prec@1 55.000 (63.000) Prec@5 93.000 (93.200) +2022-11-14 13:17:11,060 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1850 (0.2086) Prec@1 70.000 (63.333) Prec@5 96.000 (93.333) +2022-11-14 13:17:11,070 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2075 (0.2086) Prec@1 60.000 (63.182) Prec@5 94.000 (93.364) +2022-11-14 13:17:11,081 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2160 (0.2089) Prec@1 59.000 (63.000) Prec@5 95.000 (93.435) +2022-11-14 13:17:11,093 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1701 (0.2073) Prec@1 69.000 (63.250) Prec@5 94.000 (93.458) +2022-11-14 13:17:11,105 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2050 (0.2072) Prec@1 66.000 (63.360) Prec@5 93.000 (93.440) +2022-11-14 13:17:11,119 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2534 (0.2090) Prec@1 55.000 (63.038) Prec@5 93.000 (93.423) +2022-11-14 13:17:11,133 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2328 (0.2099) Prec@1 59.000 (62.889) Prec@5 92.000 (93.370) +2022-11-14 13:17:11,147 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1954 (0.2093) Prec@1 66.000 (63.000) Prec@5 92.000 (93.321) +2022-11-14 13:17:11,160 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1991 (0.2090) Prec@1 65.000 (63.069) Prec@5 95.000 (93.379) +2022-11-14 13:17:11,172 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1971 (0.2086) Prec@1 63.000 (63.067) Prec@5 93.000 (93.367) +2022-11-14 13:17:11,183 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2230 (0.2091) Prec@1 62.000 (63.032) Prec@5 93.000 (93.355) +2022-11-14 13:17:11,196 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1904 (0.2085) Prec@1 65.000 (63.094) Prec@5 96.000 (93.438) +2022-11-14 13:17:11,207 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2090 (0.2085) Prec@1 63.000 (63.091) Prec@5 89.000 (93.303) +2022-11-14 13:17:11,220 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2511 (0.2097) Prec@1 57.000 (62.912) Prec@5 91.000 (93.235) +2022-11-14 13:17:11,231 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2318 (0.2104) Prec@1 60.000 (62.829) Prec@5 93.000 (93.229) +2022-11-14 13:17:11,244 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2149 (0.2105) Prec@1 61.000 (62.778) Prec@5 94.000 (93.250) +2022-11-14 13:17:11,256 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2254 (0.2109) Prec@1 61.000 (62.730) Prec@5 94.000 (93.270) +2022-11-14 13:17:11,266 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1943 (0.2105) Prec@1 63.000 (62.737) Prec@5 94.000 (93.289) +2022-11-14 13:17:11,277 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.2099) Prec@1 66.000 (62.821) Prec@5 97.000 (93.385) +2022-11-14 13:17:11,288 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1942 (0.2095) Prec@1 63.000 (62.825) Prec@5 94.000 (93.400) +2022-11-14 13:17:11,301 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2190 (0.2097) Prec@1 66.000 (62.902) Prec@5 93.000 (93.390) +2022-11-14 13:17:11,314 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1750 (0.2089) Prec@1 68.000 (63.024) Prec@5 95.000 (93.429) +2022-11-14 13:17:11,327 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1894 (0.2085) Prec@1 65.000 (63.070) Prec@5 96.000 (93.488) +2022-11-14 13:17:11,339 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2110 (0.2085) Prec@1 62.000 (63.045) Prec@5 92.000 (93.455) +2022-11-14 13:17:11,350 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2014 (0.2084) Prec@1 63.000 (63.044) Prec@5 92.000 (93.422) +2022-11-14 13:17:11,361 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.2084) Prec@1 61.000 (63.000) Prec@5 94.000 (93.435) +2022-11-14 13:17:11,371 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2135 (0.2086) Prec@1 64.000 (63.021) Prec@5 95.000 (93.468) +2022-11-14 13:17:11,380 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1933 (0.2082) Prec@1 65.000 (63.062) Prec@5 95.000 (93.500) +2022-11-14 13:17:11,389 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1686 (0.2074) Prec@1 66.000 (63.122) Prec@5 97.000 (93.571) +2022-11-14 13:17:11,398 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2195 (0.2077) Prec@1 62.000 (63.100) Prec@5 90.000 (93.500) +2022-11-14 13:17:11,408 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1873 (0.2073) Prec@1 69.000 (63.216) Prec@5 93.000 (93.490) +2022-11-14 13:17:11,417 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2140 (0.2074) Prec@1 59.000 (63.135) Prec@5 94.000 (93.500) +2022-11-14 13:17:11,427 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2131 (0.2075) Prec@1 58.000 (63.038) Prec@5 94.000 (93.509) +2022-11-14 13:17:11,436 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2200 (0.2077) Prec@1 58.000 (62.944) Prec@5 90.000 (93.444) +2022-11-14 13:17:11,445 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2011 (0.2076) Prec@1 61.000 (62.909) Prec@5 96.000 (93.491) +2022-11-14 13:17:11,454 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2101 (0.2077) Prec@1 64.000 (62.929) Prec@5 91.000 (93.446) +2022-11-14 13:17:11,464 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2203 (0.2079) Prec@1 59.000 (62.860) Prec@5 95.000 (93.474) +2022-11-14 13:17:11,474 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1985 (0.2077) Prec@1 65.000 (62.897) Prec@5 95.000 (93.500) +2022-11-14 13:17:11,483 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2406 (0.2083) Prec@1 59.000 (62.831) Prec@5 93.000 (93.492) +2022-11-14 13:17:11,492 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2382 (0.2088) Prec@1 58.000 (62.750) Prec@5 90.000 (93.433) +2022-11-14 13:17:11,501 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2077 (0.2088) Prec@1 54.000 (62.607) Prec@5 96.000 (93.475) +2022-11-14 13:17:11,511 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1989 (0.2086) Prec@1 64.000 (62.629) Prec@5 95.000 (93.500) +2022-11-14 13:17:11,519 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1862 (0.2082) Prec@1 67.000 (62.698) Prec@5 95.000 (93.524) +2022-11-14 13:17:11,528 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2054 (0.2082) Prec@1 68.000 (62.781) Prec@5 94.000 (93.531) +2022-11-14 13:17:11,538 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2371 (0.2086) Prec@1 62.000 (62.769) Prec@5 88.000 (93.446) +2022-11-14 13:17:11,547 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1781 (0.2082) Prec@1 68.000 (62.848) Prec@5 95.000 (93.470) +2022-11-14 13:17:11,556 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2245 (0.2084) Prec@1 57.000 (62.761) Prec@5 96.000 (93.507) +2022-11-14 13:17:11,565 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1937 (0.2082) Prec@1 63.000 (62.765) Prec@5 93.000 (93.500) +2022-11-14 13:17:11,574 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1985 (0.2081) Prec@1 65.000 (62.797) Prec@5 94.000 (93.507) +2022-11-14 13:17:11,583 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2543 (0.2087) Prec@1 53.000 (62.657) Prec@5 89.000 (93.443) +2022-11-14 13:17:11,593 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2158 (0.2088) Prec@1 61.000 (62.634) Prec@5 91.000 (93.408) +2022-11-14 13:17:11,602 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1837 (0.2085) Prec@1 70.000 (62.736) Prec@5 95.000 (93.431) +2022-11-14 13:17:11,613 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2074 (0.2085) Prec@1 64.000 (62.753) Prec@5 92.000 (93.411) +2022-11-14 13:17:11,622 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2103 (0.2085) Prec@1 62.000 (62.743) Prec@5 92.000 (93.392) +2022-11-14 13:17:11,632 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1971 (0.2083) Prec@1 65.000 (62.773) Prec@5 93.000 (93.387) +2022-11-14 13:17:11,640 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1883 (0.2081) Prec@1 65.000 (62.803) Prec@5 98.000 (93.447) +2022-11-14 13:17:11,650 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1891 (0.2078) Prec@1 68.000 (62.870) Prec@5 98.000 (93.506) +2022-11-14 13:17:11,658 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1979 (0.2077) Prec@1 66.000 (62.910) Prec@5 96.000 (93.538) +2022-11-14 13:17:11,667 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1840 (0.2074) Prec@1 70.000 (63.000) Prec@5 95.000 (93.557) +2022-11-14 13:17:11,675 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2232 (0.2076) Prec@1 59.000 (62.950) Prec@5 93.000 (93.550) +2022-11-14 13:17:11,683 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2064 (0.2076) Prec@1 65.000 (62.975) Prec@5 88.000 (93.481) +2022-11-14 13:17:11,692 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1931 (0.2074) Prec@1 68.000 (63.037) Prec@5 91.000 (93.451) +2022-11-14 13:17:11,700 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1736 (0.2070) Prec@1 67.000 (63.084) Prec@5 100.000 (93.530) +2022-11-14 13:17:11,709 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2258 (0.2072) Prec@1 62.000 (63.071) Prec@5 90.000 (93.488) +2022-11-14 13:17:11,719 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2317 (0.2075) Prec@1 61.000 (63.047) Prec@5 93.000 (93.482) +2022-11-14 13:17:11,728 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2223 (0.2077) Prec@1 63.000 (63.047) Prec@5 95.000 (93.500) +2022-11-14 13:17:11,737 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2132 (0.2077) Prec@1 64.000 (63.057) Prec@5 91.000 (93.471) +2022-11-14 13:17:11,746 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2118 (0.2078) Prec@1 63.000 (63.057) Prec@5 97.000 (93.511) +2022-11-14 13:17:11,756 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1879 (0.2076) Prec@1 65.000 (63.079) Prec@5 94.000 (93.517) +2022-11-14 13:17:11,765 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2132 (0.2076) Prec@1 64.000 (63.089) Prec@5 92.000 (93.500) +2022-11-14 13:17:11,774 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2001 (0.2075) Prec@1 62.000 (63.077) Prec@5 96.000 (93.527) +2022-11-14 13:17:11,783 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1789 (0.2072) Prec@1 64.000 (63.087) Prec@5 93.000 (93.522) +2022-11-14 13:17:11,792 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2030 (0.2072) Prec@1 59.000 (63.043) Prec@5 96.000 (93.548) +2022-11-14 13:17:11,802 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.2071) Prec@1 62.000 (63.032) Prec@5 94.000 (93.553) +2022-11-14 13:17:11,811 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1875 (0.2069) Prec@1 69.000 (63.095) Prec@5 95.000 (93.568) +2022-11-14 13:17:11,821 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1904 (0.2067) Prec@1 68.000 (63.146) Prec@5 97.000 (93.604) +2022-11-14 13:17:11,830 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1760 (0.2064) Prec@1 69.000 (63.206) Prec@5 96.000 (93.629) +2022-11-14 13:17:11,839 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2229 (0.2066) Prec@1 59.000 (63.163) Prec@5 94.000 (93.633) +2022-11-14 13:17:11,848 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2240 (0.2067) Prec@1 64.000 (63.172) Prec@5 96.000 (93.657) +2022-11-14 13:17:11,858 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2034 (0.2067) Prec@1 66.000 (63.200) Prec@5 90.000 (93.620) +2022-11-14 13:17:11,911 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:17:12,205 Epoch: [15][0/500] Time 0.022 (0.022) Data 0.212 (0.212) Loss 0.1391 (0.1391) Prec@1 77.000 (77.000) Prec@5 100.000 (100.000) +2022-11-14 13:17:12,445 Epoch: [15][10/500] Time 0.028 (0.021) Data 0.002 (0.021) Loss 0.1250 (0.1320) Prec@1 79.000 (78.000) Prec@5 100.000 (100.000) +2022-11-14 13:17:12,716 Epoch: [15][20/500] Time 0.021 (0.023) Data 0.002 (0.012) Loss 0.1257 (0.1299) Prec@1 79.000 (78.333) Prec@5 98.000 (99.333) +2022-11-14 13:17:12,919 Epoch: [15][30/500] Time 0.018 (0.021) Data 0.001 (0.009) Loss 0.1165 (0.1266) Prec@1 81.000 (79.000) Prec@5 97.000 (98.750) +2022-11-14 13:17:13,210 Epoch: [15][40/500] Time 0.030 (0.022) Data 0.002 (0.007) Loss 0.0957 (0.1204) Prec@1 84.000 (80.000) Prec@5 99.000 (98.800) +2022-11-14 13:17:13,556 Epoch: [15][50/500] Time 0.036 (0.024) Data 0.002 (0.006) Loss 0.1351 (0.1229) Prec@1 79.000 (79.833) Prec@5 99.000 (98.833) +2022-11-14 13:17:13,906 Epoch: [15][60/500] Time 0.033 (0.025) Data 0.002 (0.005) Loss 0.1027 (0.1200) Prec@1 85.000 (80.571) Prec@5 99.000 (98.857) +2022-11-14 13:17:14,249 Epoch: [15][70/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.1342 (0.1218) Prec@1 77.000 (80.125) Prec@5 97.000 (98.625) +2022-11-14 13:17:14,595 Epoch: [15][80/500] Time 0.032 (0.026) Data 0.002 (0.004) Loss 0.1167 (0.1212) Prec@1 78.000 (79.889) Prec@5 100.000 (98.778) +2022-11-14 13:17:14,976 Epoch: [15][90/500] Time 0.051 (0.027) Data 0.002 (0.004) Loss 0.1455 (0.1236) Prec@1 71.000 (79.000) Prec@5 98.000 (98.700) +2022-11-14 13:17:15,333 Epoch: [15][100/500] Time 0.031 (0.028) Data 0.001 (0.004) Loss 0.1351 (0.1247) Prec@1 77.000 (78.818) Prec@5 97.000 (98.545) +2022-11-14 13:17:15,681 Epoch: [15][110/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.1240 (0.1246) Prec@1 77.000 (78.667) Prec@5 97.000 (98.417) +2022-11-14 13:17:16,027 Epoch: [15][120/500] Time 0.032 (0.028) Data 0.002 (0.004) Loss 0.1409 (0.1259) Prec@1 78.000 (78.615) Prec@5 96.000 (98.231) +2022-11-14 13:17:16,372 Epoch: [15][130/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.1761 (0.1295) Prec@1 68.000 (77.857) Prec@5 99.000 (98.286) +2022-11-14 13:17:16,714 Epoch: [15][140/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.1203 (0.1288) Prec@1 80.000 (78.000) Prec@5 99.000 (98.333) +2022-11-14 13:17:17,060 Epoch: [15][150/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.1604 (0.1308) Prec@1 69.000 (77.438) Prec@5 96.000 (98.188) +2022-11-14 13:17:17,404 Epoch: [15][160/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.1337 (0.1310) Prec@1 76.000 (77.353) Prec@5 99.000 (98.235) +2022-11-14 13:17:17,814 Epoch: [15][170/500] Time 0.023 (0.029) Data 0.002 (0.003) Loss 0.1403 (0.1315) Prec@1 74.000 (77.167) Prec@5 95.000 (98.056) +2022-11-14 13:17:18,153 Epoch: [15][180/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.1693 (0.1335) Prec@1 70.000 (76.789) Prec@5 97.000 (98.000) +2022-11-14 13:17:18,497 Epoch: [15][190/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.1304 (0.1333) Prec@1 75.000 (76.700) Prec@5 100.000 (98.100) +2022-11-14 13:17:18,840 Epoch: [15][200/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.1429 (0.1338) Prec@1 76.000 (76.667) Prec@5 96.000 (98.000) +2022-11-14 13:17:19,186 Epoch: [15][210/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.1356 (0.1339) Prec@1 72.000 (76.455) Prec@5 97.000 (97.955) +2022-11-14 13:17:19,618 Epoch: [15][220/500] Time 0.040 (0.030) Data 0.002 (0.003) Loss 0.1259 (0.1335) Prec@1 77.000 (76.478) Prec@5 96.000 (97.870) +2022-11-14 13:17:19,968 Epoch: [15][230/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.1455 (0.1340) Prec@1 73.000 (76.333) Prec@5 98.000 (97.875) +2022-11-14 13:17:20,310 Epoch: [15][240/500] Time 0.033 (0.030) Data 0.001 (0.003) Loss 0.1608 (0.1351) Prec@1 76.000 (76.320) Prec@5 94.000 (97.720) +2022-11-14 13:17:20,652 Epoch: [15][250/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.1420 (0.1354) Prec@1 78.000 (76.385) Prec@5 96.000 (97.654) +2022-11-14 13:17:21,084 Epoch: [15][260/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1385 (0.1355) Prec@1 75.000 (76.333) Prec@5 99.000 (97.704) +2022-11-14 13:17:21,471 Epoch: [15][270/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.1369 (0.1355) Prec@1 74.000 (76.250) Prec@5 99.000 (97.750) +2022-11-14 13:17:21,810 Epoch: [15][280/500] Time 0.029 (0.030) Data 0.002 (0.003) Loss 0.1468 (0.1359) Prec@1 71.000 (76.069) Prec@5 99.000 (97.793) +2022-11-14 13:17:22,142 Epoch: [15][290/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.1741 (0.1372) Prec@1 68.000 (75.800) Prec@5 96.000 (97.733) +2022-11-14 13:17:22,487 Epoch: [15][300/500] Time 0.027 (0.030) Data 0.002 (0.003) Loss 0.1776 (0.1385) Prec@1 68.000 (75.548) Prec@5 95.000 (97.645) +2022-11-14 13:17:22,830 Epoch: [15][310/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.1436 (0.1386) Prec@1 75.000 (75.531) Prec@5 95.000 (97.562) +2022-11-14 13:17:23,176 Epoch: [15][320/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1386 (0.1386) Prec@1 76.000 (75.545) Prec@5 97.000 (97.545) +2022-11-14 13:17:23,513 Epoch: [15][330/500] Time 0.031 (0.030) Data 0.002 (0.002) Loss 0.1558 (0.1392) Prec@1 76.000 (75.559) Prec@5 99.000 (97.588) +2022-11-14 13:17:23,859 Epoch: [15][340/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1430 (0.1393) Prec@1 77.000 (75.600) Prec@5 98.000 (97.600) +2022-11-14 13:17:24,207 Epoch: [15][350/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1374 (0.1392) Prec@1 77.000 (75.639) Prec@5 98.000 (97.611) +2022-11-14 13:17:24,553 Epoch: [15][360/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1555 (0.1397) Prec@1 71.000 (75.514) Prec@5 97.000 (97.595) +2022-11-14 13:17:24,901 Epoch: [15][370/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1482 (0.1399) Prec@1 75.000 (75.500) Prec@5 98.000 (97.605) +2022-11-14 13:17:25,275 Epoch: [15][380/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1420 (0.1399) Prec@1 77.000 (75.538) Prec@5 99.000 (97.641) +2022-11-14 13:17:25,612 Epoch: [15][390/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1730 (0.1408) Prec@1 69.000 (75.375) Prec@5 96.000 (97.600) +2022-11-14 13:17:25,958 Epoch: [15][400/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1515 (0.1410) Prec@1 73.000 (75.317) Prec@5 99.000 (97.634) +2022-11-14 13:17:26,303 Epoch: [15][410/500] Time 0.033 (0.030) Data 0.001 (0.002) Loss 0.1415 (0.1410) Prec@1 74.000 (75.286) Prec@5 96.000 (97.595) +2022-11-14 13:17:26,641 Epoch: [15][420/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1824 (0.1420) Prec@1 66.000 (75.070) Prec@5 93.000 (97.488) +2022-11-14 13:17:26,984 Epoch: [15][430/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1372 (0.1419) Prec@1 76.000 (75.091) Prec@5 96.000 (97.455) +2022-11-14 13:17:27,327 Epoch: [15][440/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.1365 (0.1418) Prec@1 76.000 (75.111) Prec@5 98.000 (97.467) +2022-11-14 13:17:27,668 Epoch: [15][450/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1477 (0.1419) Prec@1 77.000 (75.152) Prec@5 93.000 (97.370) +2022-11-14 13:17:28,013 Epoch: [15][460/500] Time 0.031 (0.030) Data 0.003 (0.002) Loss 0.1893 (0.1429) Prec@1 64.000 (74.915) Prec@5 92.000 (97.255) +2022-11-14 13:17:28,363 Epoch: [15][470/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1225 (0.1425) Prec@1 80.000 (75.021) Prec@5 98.000 (97.271) +2022-11-14 13:17:28,702 Epoch: [15][480/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1317 (0.1423) Prec@1 76.000 (75.041) Prec@5 96.000 (97.245) +2022-11-14 13:17:29,039 Epoch: [15][490/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.1628 (0.1427) Prec@1 71.000 (74.960) Prec@5 94.000 (97.180) +2022-11-14 13:17:29,350 Epoch: [15][499/500] Time 0.032 (0.030) Data 0.001 (0.002) Loss 0.1607 (0.1430) Prec@1 71.000 (74.882) Prec@5 97.000 (97.176) +2022-11-14 13:17:29,626 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.2004 (0.2004) Prec@1 64.000 (64.000) Prec@5 92.000 (92.000) +2022-11-14 13:17:29,633 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1653 (0.1828) Prec@1 72.000 (68.000) Prec@5 95.000 (93.500) +2022-11-14 13:17:29,642 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1857 (0.1838) Prec@1 65.000 (67.000) Prec@5 95.000 (94.000) +2022-11-14 13:17:29,655 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1774 (0.1822) Prec@1 68.000 (67.250) Prec@5 98.000 (95.000) +2022-11-14 13:17:29,664 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1698 (0.1797) Prec@1 67.000 (67.200) Prec@5 97.000 (95.400) +2022-11-14 13:17:29,671 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1744) Prec@1 77.000 (68.833) Prec@5 95.000 (95.333) +2022-11-14 13:17:29,679 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1817 (0.1755) Prec@1 69.000 (68.857) Prec@5 94.000 (95.143) +2022-11-14 13:17:29,688 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2164 (0.1806) Prec@1 57.000 (67.375) Prec@5 91.000 (94.625) +2022-11-14 13:17:29,697 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1773 (0.1802) Prec@1 72.000 (67.889) Prec@5 95.000 (94.667) +2022-11-14 13:17:29,707 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1480 (0.1770) Prec@1 75.000 (68.600) Prec@5 94.000 (94.600) +2022-11-14 13:17:29,716 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1432 (0.1739) Prec@1 74.000 (69.091) Prec@5 94.000 (94.545) +2022-11-14 13:17:29,725 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1799 (0.1744) Prec@1 67.000 (68.917) Prec@5 89.000 (94.083) +2022-11-14 13:17:29,735 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1740) Prec@1 71.000 (69.077) Prec@5 96.000 (94.231) +2022-11-14 13:17:29,744 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1740) Prec@1 69.000 (69.071) Prec@5 93.000 (94.143) +2022-11-14 13:17:29,754 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1734) Prec@1 70.000 (69.133) Prec@5 91.000 (93.933) +2022-11-14 13:17:29,762 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2038 (0.1753) Prec@1 60.000 (68.562) Prec@5 95.000 (94.000) +2022-11-14 13:17:29,771 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1742) Prec@1 75.000 (68.941) Prec@5 92.000 (93.882) +2022-11-14 13:17:29,781 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1726 (0.1741) Prec@1 70.000 (69.000) Prec@5 95.000 (93.944) +2022-11-14 13:17:29,790 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1878 (0.1748) Prec@1 65.000 (68.789) Prec@5 93.000 (93.895) +2022-11-14 13:17:29,799 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.1759) Prec@1 69.000 (68.800) Prec@5 93.000 (93.850) +2022-11-14 13:17:29,808 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1678 (0.1755) Prec@1 69.000 (68.810) Prec@5 95.000 (93.905) +2022-11-14 13:17:29,817 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1839 (0.1759) Prec@1 66.000 (68.682) Prec@5 95.000 (93.955) +2022-11-14 13:17:29,826 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1752 (0.1759) Prec@1 71.000 (68.783) Prec@5 96.000 (94.043) +2022-11-14 13:17:29,836 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1914 (0.1765) Prec@1 67.000 (68.708) Prec@5 92.000 (93.958) +2022-11-14 13:17:29,845 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1855 (0.1769) Prec@1 68.000 (68.680) Prec@5 98.000 (94.120) +2022-11-14 13:17:29,853 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1779 (0.1769) Prec@1 68.000 (68.654) Prec@5 91.000 (94.000) +2022-11-14 13:17:29,862 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1654 (0.1765) Prec@1 73.000 (68.815) Prec@5 94.000 (94.000) +2022-11-14 13:17:29,872 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1749 (0.1764) Prec@1 69.000 (68.821) Prec@5 97.000 (94.107) +2022-11-14 13:17:29,880 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1764) Prec@1 68.000 (68.793) Prec@5 95.000 (94.138) +2022-11-14 13:17:29,889 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1412 (0.1752) Prec@1 74.000 (68.967) Prec@5 97.000 (94.233) +2022-11-14 13:17:29,898 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1769 (0.1753) Prec@1 69.000 (68.968) Prec@5 91.000 (94.129) +2022-11-14 13:17:29,908 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1814 (0.1755) Prec@1 66.000 (68.875) Prec@5 96.000 (94.188) +2022-11-14 13:17:29,917 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1747) Prec@1 74.000 (69.030) Prec@5 94.000 (94.182) +2022-11-14 13:17:29,926 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2075 (0.1757) Prec@1 58.000 (68.706) Prec@5 93.000 (94.147) +2022-11-14 13:17:29,935 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1908 (0.1761) Prec@1 68.000 (68.686) Prec@5 91.000 (94.057) +2022-11-14 13:17:29,944 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1554 (0.1755) Prec@1 74.000 (68.833) Prec@5 98.000 (94.167) +2022-11-14 13:17:29,954 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1736 (0.1755) Prec@1 69.000 (68.838) Prec@5 97.000 (94.243) +2022-11-14 13:17:29,963 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2088 (0.1763) Prec@1 61.000 (68.632) Prec@5 92.000 (94.184) +2022-11-14 13:17:29,972 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1574 (0.1758) Prec@1 70.000 (68.667) Prec@5 94.000 (94.179) +2022-11-14 13:17:29,981 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1714 (0.1757) Prec@1 71.000 (68.725) Prec@5 96.000 (94.225) +2022-11-14 13:17:29,991 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1863 (0.1760) Prec@1 67.000 (68.683) Prec@5 93.000 (94.195) +2022-11-14 13:17:30,000 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1434 (0.1752) Prec@1 74.000 (68.810) Prec@5 95.000 (94.214) +2022-11-14 13:17:30,009 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1503 (0.1746) Prec@1 74.000 (68.930) Prec@5 95.000 (94.233) +2022-11-14 13:17:30,019 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1772 (0.1747) Prec@1 66.000 (68.864) Prec@5 91.000 (94.159) +2022-11-14 13:17:30,027 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1239 (0.1736) Prec@1 77.000 (69.044) Prec@5 97.000 (94.222) +2022-11-14 13:17:30,037 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1714 (0.1735) Prec@1 67.000 (69.000) Prec@5 95.000 (94.239) +2022-11-14 13:17:30,047 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1810 (0.1737) Prec@1 66.000 (68.936) Prec@5 96.000 (94.277) +2022-11-14 13:17:30,055 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1868 (0.1740) Prec@1 68.000 (68.917) Prec@5 93.000 (94.250) +2022-11-14 13:17:30,065 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.1732) Prec@1 76.000 (69.061) Prec@5 99.000 (94.347) +2022-11-14 13:17:30,074 Test: 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0.1990 (0.1752) Prec@1 62.000 (68.518) Prec@5 95.000 (94.250) +2022-11-14 13:17:30,138 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2131 (0.1759) Prec@1 60.000 (68.368) Prec@5 97.000 (94.298) +2022-11-14 13:17:30,146 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1961 (0.1763) Prec@1 66.000 (68.328) Prec@5 96.000 (94.328) +2022-11-14 13:17:30,155 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1997 (0.1767) Prec@1 66.000 (68.288) Prec@5 91.000 (94.271) +2022-11-14 13:17:30,165 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1839 (0.1768) Prec@1 65.000 (68.233) Prec@5 93.000 (94.250) +2022-11-14 13:17:30,174 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1642 (0.1766) Prec@1 68.000 (68.230) Prec@5 96.000 (94.279) +2022-11-14 13:17:30,184 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1660 (0.1764) Prec@1 73.000 (68.306) Prec@5 97.000 (94.323) +2022-11-14 13:17:30,193 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1836 (0.1765) Prec@1 66.000 (68.270) Prec@5 96.000 (94.349) +2022-11-14 13:17:30,202 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1580 (0.1762) Prec@1 70.000 (68.297) Prec@5 96.000 (94.375) +2022-11-14 13:17:30,212 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1804 (0.1763) Prec@1 70.000 (68.323) Prec@5 92.000 (94.338) +2022-11-14 13:17:30,220 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1979 (0.1766) Prec@1 66.000 (68.288) Prec@5 97.000 (94.379) +2022-11-14 13:17:30,229 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1549 (0.1763) Prec@1 73.000 (68.358) Prec@5 95.000 (94.388) +2022-11-14 13:17:30,239 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1424 (0.1758) Prec@1 72.000 (68.412) Prec@5 96.000 (94.412) +2022-11-14 13:17:30,250 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2157 (0.1764) Prec@1 60.000 (68.290) Prec@5 92.000 (94.377) +2022-11-14 13:17:30,260 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.1767) Prec@1 65.000 (68.243) Prec@5 92.000 (94.343) +2022-11-14 13:17:30,268 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2110 (0.1772) Prec@1 62.000 (68.155) Prec@5 97.000 (94.380) +2022-11-14 13:17:30,277 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1864 (0.1773) Prec@1 64.000 (68.097) Prec@5 96.000 (94.403) +2022-11-14 13:17:30,286 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1555 (0.1770) Prec@1 71.000 (68.137) Prec@5 98.000 (94.452) +2022-11-14 13:17:30,296 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1678 (0.1769) Prec@1 69.000 (68.149) Prec@5 99.000 (94.514) +2022-11-14 13:17:30,305 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1760 (0.1768) Prec@1 70.000 (68.173) Prec@5 93.000 (94.493) +2022-11-14 13:17:30,313 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1804 (0.1769) Prec@1 69.000 (68.184) Prec@5 98.000 (94.539) +2022-11-14 13:17:30,323 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1770 (0.1769) Prec@1 69.000 (68.195) Prec@5 98.000 (94.584) +2022-11-14 13:17:30,331 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1574 (0.1766) Prec@1 71.000 (68.231) Prec@5 95.000 (94.590) +2022-11-14 13:17:30,340 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1920 (0.1768) Prec@1 63.000 (68.165) Prec@5 95.000 (94.595) +2022-11-14 13:17:30,350 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.1768) Prec@1 71.000 (68.200) Prec@5 92.000 (94.562) +2022-11-14 13:17:30,360 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1674 (0.1767) Prec@1 72.000 (68.247) Prec@5 97.000 (94.593) +2022-11-14 13:17:30,369 Test: 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0.1921 (0.1775) Prec@1 63.000 (68.114) Prec@5 91.000 (94.534) +2022-11-14 13:17:30,433 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1645 (0.1773) Prec@1 72.000 (68.157) Prec@5 93.000 (94.517) +2022-11-14 13:17:30,442 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1891 (0.1775) Prec@1 70.000 (68.178) Prec@5 92.000 (94.489) +2022-11-14 13:17:30,450 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1648 (0.1773) Prec@1 70.000 (68.198) Prec@5 99.000 (94.538) +2022-11-14 13:17:30,459 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1767) Prec@1 78.000 (68.304) Prec@5 99.000 (94.587) +2022-11-14 13:17:30,469 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1871 (0.1769) Prec@1 66.000 (68.280) Prec@5 92.000 (94.559) +2022-11-14 13:17:30,478 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2008 (0.1771) Prec@1 63.000 (68.223) Prec@5 93.000 (94.543) +2022-11-14 13:17:30,486 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1630 (0.1770) Prec@1 70.000 (68.242) Prec@5 95.000 (94.547) +2022-11-14 13:17:30,494 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1617 (0.1768) Prec@1 73.000 (68.292) Prec@5 95.000 (94.552) +2022-11-14 13:17:30,504 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1456 (0.1765) Prec@1 77.000 (68.381) Prec@5 96.000 (94.567) +2022-11-14 13:17:30,512 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2402 (0.1771) Prec@1 53.000 (68.224) Prec@5 93.000 (94.551) +2022-11-14 13:17:30,520 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1925 (0.1773) Prec@1 65.000 (68.192) Prec@5 93.000 (94.535) +2022-11-14 13:17:30,529 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1524 (0.1770) Prec@1 73.000 (68.240) Prec@5 94.000 (94.530) +2022-11-14 13:17:30,584 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:17:30,887 Epoch: [16][0/500] Time 0.024 (0.024) Data 0.218 (0.218) Loss 0.1568 (0.1568) Prec@1 70.000 (70.000) Prec@5 96.000 (96.000) +2022-11-14 13:17:31,089 Epoch: [16][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.1441 (0.1504) Prec@1 77.000 (73.500) Prec@5 96.000 (96.000) +2022-11-14 13:17:31,290 Epoch: [16][20/500] Time 0.021 (0.018) Data 0.001 (0.012) Loss 0.1566 (0.1525) Prec@1 75.000 (74.000) Prec@5 98.000 (96.667) +2022-11-14 13:17:31,529 Epoch: [16][30/500] Time 0.025 (0.019) Data 0.002 (0.009) Loss 0.1349 (0.1481) Prec@1 74.000 (74.000) Prec@5 99.000 (97.250) +2022-11-14 13:17:31,843 Epoch: [16][40/500] Time 0.032 (0.021) Data 0.002 (0.007) Loss 0.1363 (0.1457) Prec@1 73.000 (73.800) Prec@5 99.000 (97.600) +2022-11-14 13:17:32,158 Epoch: [16][50/500] Time 0.029 (0.023) Data 0.002 (0.006) Loss 0.1572 (0.1476) Prec@1 76.000 (74.167) Prec@5 93.000 (96.833) +2022-11-14 13:17:32,472 Epoch: [16][60/500] Time 0.032 (0.023) Data 0.002 (0.005) Loss 0.1387 (0.1464) Prec@1 74.000 (74.143) Prec@5 97.000 (96.857) +2022-11-14 13:17:32,797 Epoch: [16][70/500] Time 0.023 (0.024) Data 0.002 (0.005) Loss 0.1548 (0.1474) Prec@1 76.000 (74.375) Prec@5 99.000 (97.125) +2022-11-14 13:17:33,125 Epoch: [16][80/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.1602 (0.1488) Prec@1 73.000 (74.222) Prec@5 98.000 (97.222) +2022-11-14 13:17:33,441 Epoch: [16][90/500] Time 0.027 (0.025) Data 0.001 (0.004) Loss 0.1532 (0.1493) Prec@1 69.000 (73.700) Prec@5 97.000 (97.200) +2022-11-14 13:17:33,807 Epoch: [16][100/500] Time 0.042 (0.026) Data 0.002 (0.004) Loss 0.1718 (0.1513) Prec@1 68.000 (73.182) Prec@5 96.000 (97.091) +2022-11-14 13:17:34,099 Epoch: [16][110/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.1532 (0.1515) Prec@1 74.000 (73.250) Prec@5 96.000 (97.000) +2022-11-14 13:17:34,420 Epoch: [16][120/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.1442 (0.1509) Prec@1 80.000 (73.769) Prec@5 97.000 (97.000) +2022-11-14 13:17:34,738 Epoch: [16][130/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.1425 (0.1503) Prec@1 75.000 (73.857) Prec@5 97.000 (97.000) +2022-11-14 13:17:35,051 Epoch: [16][140/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.1760 (0.1520) Prec@1 66.000 (73.333) Prec@5 97.000 (97.000) +2022-11-14 13:17:35,375 Epoch: [16][150/500] Time 0.038 (0.027) Data 0.002 (0.003) Loss 0.1326 (0.1508) Prec@1 73.000 (73.312) Prec@5 97.000 (97.000) +2022-11-14 13:17:35,687 Epoch: [16][160/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.1518 (0.1509) Prec@1 73.000 (73.294) Prec@5 98.000 (97.059) +2022-11-14 13:17:36,046 Epoch: [16][170/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1206 (0.1492) Prec@1 77.000 (73.500) Prec@5 100.000 (97.222) +2022-11-14 13:17:36,349 Epoch: [16][180/500] Time 0.028 (0.027) Data 0.001 (0.003) Loss 0.1584 (0.1497) Prec@1 70.000 (73.316) Prec@5 98.000 (97.263) +2022-11-14 13:17:36,688 Epoch: [16][190/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.1243 (0.1484) Prec@1 82.000 (73.750) Prec@5 99.000 (97.350) +2022-11-14 13:17:36,986 Epoch: [16][200/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.1302 (0.1475) Prec@1 79.000 (74.000) Prec@5 97.000 (97.333) +2022-11-14 13:17:37,311 Epoch: [16][210/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.1531 (0.1478) Prec@1 73.000 (73.955) Prec@5 96.000 (97.273) +2022-11-14 13:17:37,637 Epoch: [16][220/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1282 (0.1469) Prec@1 78.000 (74.130) Prec@5 100.000 (97.391) +2022-11-14 13:17:37,958 Epoch: [16][230/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1405 (0.1467) Prec@1 76.000 (74.208) Prec@5 94.000 (97.250) +2022-11-14 13:17:38,280 Epoch: [16][240/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1658 (0.1474) Prec@1 69.000 (74.000) Prec@5 100.000 (97.360) +2022-11-14 13:17:38,603 Epoch: [16][250/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1461 (0.1474) Prec@1 76.000 (74.077) Prec@5 96.000 (97.308) +2022-11-14 13:17:38,920 Epoch: [16][260/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1868 (0.1488) Prec@1 67.000 (73.815) Prec@5 97.000 (97.296) +2022-11-14 13:17:39,237 Epoch: [16][270/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.1267 (0.1480) Prec@1 79.000 (74.000) Prec@5 98.000 (97.321) +2022-11-14 13:17:39,552 Epoch: [16][280/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.1441 (0.1479) Prec@1 74.000 (74.000) Prec@5 98.000 (97.345) +2022-11-14 13:17:39,872 Epoch: [16][290/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.1236 (0.1471) Prec@1 76.000 (74.067) Prec@5 98.000 (97.367) +2022-11-14 13:17:40,187 Epoch: [16][300/500] Time 0.025 (0.028) Data 0.002 (0.002) Loss 0.1150 (0.1461) Prec@1 82.000 (74.323) Prec@5 97.000 (97.355) +2022-11-14 13:17:40,518 Epoch: [16][310/500] Time 0.029 (0.028) Data 0.001 (0.002) Loss 0.1123 (0.1450) Prec@1 83.000 (74.594) Prec@5 100.000 (97.438) +2022-11-14 13:17:40,835 Epoch: [16][320/500] Time 0.027 (0.028) Data 0.002 (0.002) Loss 0.1341 (0.1447) Prec@1 75.000 (74.606) Prec@5 96.000 (97.394) +2022-11-14 13:17:41,148 Epoch: [16][330/500] Time 0.026 (0.028) Data 0.002 (0.002) Loss 0.1104 (0.1437) Prec@1 82.000 (74.824) Prec@5 99.000 (97.441) +2022-11-14 13:17:41,466 Epoch: [16][340/500] Time 0.026 (0.028) Data 0.002 (0.002) Loss 0.1031 (0.1425) Prec@1 83.000 (75.057) Prec@5 100.000 (97.514) +2022-11-14 13:17:41,796 Epoch: [16][350/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1430 (0.1425) Prec@1 73.000 (75.000) Prec@5 99.000 (97.556) +2022-11-14 13:17:42,108 Epoch: [16][360/500] Time 0.027 (0.028) Data 0.002 (0.002) Loss 0.1464 (0.1426) Prec@1 74.000 (74.973) Prec@5 98.000 (97.568) +2022-11-14 13:17:42,437 Epoch: [16][370/500] Time 0.039 (0.028) Data 0.002 (0.002) Loss 0.1949 (0.1440) Prec@1 64.000 (74.684) Prec@5 98.000 (97.579) +2022-11-14 13:17:42,761 Epoch: [16][380/500] Time 0.034 (0.028) Data 0.002 (0.002) Loss 0.1546 (0.1443) Prec@1 72.000 (74.615) Prec@5 98.000 (97.590) +2022-11-14 13:17:43,081 Epoch: [16][390/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1434 (0.1443) Prec@1 73.000 (74.575) Prec@5 97.000 (97.575) +2022-11-14 13:17:43,399 Epoch: [16][400/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1545 (0.1445) Prec@1 73.000 (74.537) Prec@5 96.000 (97.537) +2022-11-14 13:17:43,718 Epoch: [16][410/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1498 (0.1446) Prec@1 73.000 (74.500) Prec@5 97.000 (97.524) +2022-11-14 13:17:44,037 Epoch: [16][420/500] Time 0.028 (0.028) Data 0.002 (0.002) Loss 0.1902 (0.1457) Prec@1 67.000 (74.326) Prec@5 98.000 (97.535) +2022-11-14 13:17:44,359 Epoch: [16][430/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1228 (0.1452) Prec@1 81.000 (74.477) Prec@5 100.000 (97.591) +2022-11-14 13:17:44,697 Epoch: [16][440/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1889 (0.1461) Prec@1 65.000 (74.267) Prec@5 96.000 (97.556) +2022-11-14 13:17:45,022 Epoch: [16][450/500] Time 0.028 (0.028) Data 0.001 (0.002) Loss 0.1376 (0.1460) Prec@1 77.000 (74.326) Prec@5 97.000 (97.543) +2022-11-14 13:17:45,338 Epoch: [16][460/500] Time 0.032 (0.028) Data 0.002 (0.002) Loss 0.1315 (0.1456) Prec@1 76.000 (74.362) Prec@5 97.000 (97.532) +2022-11-14 13:17:45,647 Epoch: [16][470/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.1137 (0.1450) Prec@1 80.000 (74.479) Prec@5 98.000 (97.542) +2022-11-14 13:17:45,973 Epoch: [16][480/500] Time 0.032 (0.028) Data 0.001 (0.002) Loss 0.1298 (0.1447) Prec@1 79.000 (74.571) Prec@5 97.000 (97.531) +2022-11-14 13:17:46,298 Epoch: [16][490/500] Time 0.027 (0.028) Data 0.002 (0.002) Loss 0.1427 (0.1446) Prec@1 78.000 (74.640) Prec@5 98.000 (97.540) +2022-11-14 13:17:46,584 Epoch: [16][499/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.1253 (0.1443) Prec@1 76.000 (74.667) Prec@5 100.000 (97.588) +2022-11-14 13:17:46,883 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.1790 (0.1790) Prec@1 67.000 (67.000) Prec@5 100.000 (100.000) +2022-11-14 13:17:46,894 Test: [1/100] Model Time 0.009 (0.013) Loss Time 0.000 (0.000) Loss 0.2060 (0.1925) Prec@1 63.000 (65.000) Prec@5 100.000 (100.000) +2022-11-14 13:17:46,902 Test: [2/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.2064 (0.1971) Prec@1 65.000 (65.000) Prec@5 92.000 (97.333) +2022-11-14 13:17:46,915 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1820 (0.1934) Prec@1 67.000 (65.500) Prec@5 99.000 (97.750) +2022-11-14 13:17:46,926 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.2198 (0.1986) Prec@1 59.000 (64.200) Prec@5 97.000 (97.600) +2022-11-14 13:17:46,935 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1986 (0.1986) Prec@1 61.000 (63.667) Prec@5 99.000 (97.833) +2022-11-14 13:17:46,943 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1714 (0.1947) Prec@1 72.000 (64.857) Prec@5 94.000 (97.286) +2022-11-14 13:17:46,952 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2320 (0.1994) Prec@1 58.000 (64.000) Prec@5 93.000 (96.750) +2022-11-14 13:17:46,962 Test: [8/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.2344 (0.2033) Prec@1 55.000 (63.000) Prec@5 97.000 (96.778) +2022-11-14 13:17:46,971 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1639 (0.1994) Prec@1 67.000 (63.400) Prec@5 99.000 (97.000) +2022-11-14 13:17:46,980 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1638 (0.1961) Prec@1 71.000 (64.091) Prec@5 98.000 (97.091) +2022-11-14 13:17:46,991 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1643 (0.1935) Prec@1 73.000 (64.833) Prec@5 97.000 (97.083) +2022-11-14 13:17:47,001 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1715 (0.1918) Prec@1 66.000 (64.923) Prec@5 95.000 (96.923) +2022-11-14 13:17:47,012 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1750 (0.1906) Prec@1 67.000 (65.071) Prec@5 97.000 (96.929) +2022-11-14 13:17:47,022 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2229 (0.1927) Prec@1 64.000 (65.000) Prec@5 96.000 (96.867) +2022-11-14 13:17:47,032 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2423 (0.1958) Prec@1 56.000 (64.438) Prec@5 93.000 (96.625) +2022-11-14 13:17:47,042 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1532 (0.1933) Prec@1 71.000 (64.824) Prec@5 96.000 (96.588) +2022-11-14 13:17:47,053 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1667 (0.1919) Prec@1 66.000 (64.889) Prec@5 95.000 (96.500) +2022-11-14 13:17:47,063 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1954 (0.1920) Prec@1 65.000 (64.895) Prec@5 93.000 (96.316) +2022-11-14 13:17:47,074 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1987 (0.1924) Prec@1 60.000 (64.650) Prec@5 94.000 (96.200) +2022-11-14 13:17:47,085 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1823 (0.1919) Prec@1 70.000 (64.905) Prec@5 98.000 (96.286) +2022-11-14 13:17:47,097 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1974 (0.1921) Prec@1 65.000 (64.909) Prec@5 96.000 (96.273) +2022-11-14 13:17:47,109 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1963 (0.1923) Prec@1 61.000 (64.739) Prec@5 98.000 (96.348) +2022-11-14 13:17:47,119 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1913) Prec@1 70.000 (64.958) Prec@5 97.000 (96.375) +2022-11-14 13:17:47,131 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1979 (0.1915) Prec@1 66.000 (65.000) Prec@5 95.000 (96.320) +2022-11-14 13:17:47,143 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2355 (0.1932) Prec@1 56.000 (64.654) Prec@5 94.000 (96.231) +2022-11-14 13:17:47,153 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2101 (0.1938) Prec@1 61.000 (64.519) Prec@5 97.000 (96.259) +2022-11-14 13:17:47,165 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1936 (0.1938) Prec@1 65.000 (64.536) Prec@5 99.000 (96.357) +2022-11-14 13:17:47,175 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1930) Prec@1 71.000 (64.759) Prec@5 95.000 (96.310) +2022-11-14 13:17:47,187 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1846 (0.1927) Prec@1 67.000 (64.833) Prec@5 97.000 (96.333) +2022-11-14 13:17:47,198 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2151 (0.1934) Prec@1 60.000 (64.677) Prec@5 98.000 (96.387) +2022-11-14 13:17:47,207 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1853 (0.1932) Prec@1 63.000 (64.625) Prec@5 98.000 (96.438) +2022-11-14 13:17:47,218 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1798 (0.1928) Prec@1 66.000 (64.667) Prec@5 97.000 (96.455) +2022-11-14 13:17:47,232 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2364 (0.1941) Prec@1 54.000 (64.353) Prec@5 94.000 (96.382) +2022-11-14 13:17:47,243 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2019 (0.1943) Prec@1 61.000 (64.257) Prec@5 96.000 (96.371) +2022-11-14 13:17:47,254 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2147 (0.1949) Prec@1 57.000 (64.056) Prec@5 96.000 (96.361) +2022-11-14 13:17:47,264 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1969 (0.1949) Prec@1 64.000 (64.054) Prec@5 97.000 (96.378) +2022-11-14 13:17:47,275 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.1954) Prec@1 59.000 (63.921) Prec@5 95.000 (96.342) +2022-11-14 13:17:47,286 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1844 (0.1951) Prec@1 67.000 (64.000) Prec@5 98.000 (96.385) +2022-11-14 13:17:47,298 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2264 (0.1959) Prec@1 59.000 (63.875) Prec@5 97.000 (96.400) +2022-11-14 13:17:47,308 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2087 (0.1962) Prec@1 62.000 (63.829) Prec@5 96.000 (96.390) +2022-11-14 13:17:47,319 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1749 (0.1957) Prec@1 67.000 (63.905) Prec@5 96.000 (96.381) +2022-11-14 13:17:47,331 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1704 (0.1951) Prec@1 69.000 (64.023) Prec@5 97.000 (96.395) +2022-11-14 13:17:47,342 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1926 (0.1950) Prec@1 66.000 (64.068) Prec@5 95.000 (96.364) +2022-11-14 13:17:47,353 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1941 (0.1950) Prec@1 63.000 (64.044) Prec@5 99.000 (96.422) +2022-11-14 13:17:47,364 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2089 (0.1953) Prec@1 58.000 (63.913) Prec@5 94.000 (96.370) +2022-11-14 13:17:47,375 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2037 (0.1955) Prec@1 66.000 (63.957) Prec@5 99.000 (96.426) +2022-11-14 13:17:47,387 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1611 (0.1948) Prec@1 70.000 (64.083) Prec@5 95.000 (96.396) +2022-11-14 13:17:47,397 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1704 (0.1943) Prec@1 68.000 (64.163) Prec@5 94.000 (96.347) +2022-11-14 13:17:47,408 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2239 (0.1949) Prec@1 61.000 (64.100) Prec@5 95.000 (96.320) +2022-11-14 13:17:47,420 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1929 (0.1948) Prec@1 66.000 (64.137) Prec@5 98.000 (96.353) +2022-11-14 13:17:47,431 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2102 (0.1951) Prec@1 61.000 (64.077) Prec@5 93.000 (96.288) +2022-11-14 13:17:47,442 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2009 (0.1952) Prec@1 66.000 (64.113) Prec@5 97.000 (96.302) +2022-11-14 13:17:47,454 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2129 (0.1956) Prec@1 60.000 (64.037) Prec@5 96.000 (96.296) +2022-11-14 13:17:47,465 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1867 (0.1954) Prec@1 64.000 (64.036) Prec@5 98.000 (96.327) +2022-11-14 13:17:47,477 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2136 (0.1957) Prec@1 62.000 (64.000) Prec@5 96.000 (96.321) +2022-11-14 13:17:47,487 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2130 (0.1960) Prec@1 60.000 (63.930) Prec@5 99.000 (96.368) +2022-11-14 13:17:47,499 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1685 (0.1956) Prec@1 70.000 (64.034) Prec@5 97.000 (96.379) +2022-11-14 13:17:47,510 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2378 (0.1963) Prec@1 53.000 (63.847) Prec@5 96.000 (96.373) +2022-11-14 13:17:47,521 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2261 (0.1968) Prec@1 62.000 (63.817) Prec@5 91.000 (96.283) +2022-11-14 13:17:47,533 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1963) Prec@1 71.000 (63.934) Prec@5 99.000 (96.328) +2022-11-14 13:17:47,544 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2022 (0.1964) Prec@1 67.000 (63.984) Prec@5 96.000 (96.323) +2022-11-14 13:17:47,556 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1608 (0.1958) Prec@1 72.000 (64.111) Prec@5 97.000 (96.333) +2022-11-14 13:17:47,567 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1895 (0.1957) Prec@1 67.000 (64.156) Prec@5 96.000 (96.328) +2022-11-14 13:17:47,578 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2257 (0.1962) Prec@1 60.000 (64.092) Prec@5 94.000 (96.292) +2022-11-14 13:17:47,589 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1748 (0.1958) Prec@1 70.000 (64.182) Prec@5 95.000 (96.273) +2022-11-14 13:17:47,600 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2166 (0.1962) Prec@1 63.000 (64.164) Prec@5 96.000 (96.269) +2022-11-14 13:17:47,612 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1516 (0.1955) Prec@1 72.000 (64.279) Prec@5 97.000 (96.279) +2022-11-14 13:17:47,624 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1911 (0.1954) Prec@1 66.000 (64.304) Prec@5 97.000 (96.290) +2022-11-14 13:17:47,635 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2314 (0.1960) Prec@1 59.000 (64.229) Prec@5 97.000 (96.300) +2022-11-14 13:17:47,650 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.1962) Prec@1 58.000 (64.141) Prec@5 98.000 (96.324) +2022-11-14 13:17:47,662 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2028 (0.1963) Prec@1 64.000 (64.139) Prec@5 98.000 (96.347) +2022-11-14 13:17:47,674 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1957) Prec@1 73.000 (64.260) Prec@5 95.000 (96.329) +2022-11-14 13:17:47,685 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1909 (0.1957) Prec@1 69.000 (64.324) Prec@5 98.000 (96.351) +2022-11-14 13:17:47,697 Test: [74/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1819 (0.1955) Prec@1 69.000 (64.387) Prec@5 96.000 (96.347) +2022-11-14 13:17:47,708 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1843 (0.1953) Prec@1 66.000 (64.408) Prec@5 100.000 (96.395) +2022-11-14 13:17:47,719 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.1954) Prec@1 60.000 (64.351) Prec@5 92.000 (96.338) +2022-11-14 13:17:47,729 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1764 (0.1951) Prec@1 70.000 (64.423) Prec@5 100.000 (96.385) +2022-11-14 13:17:47,741 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1876 (0.1950) Prec@1 68.000 (64.468) Prec@5 98.000 (96.405) +2022-11-14 13:17:47,753 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1783 (0.1948) Prec@1 69.000 (64.525) Prec@5 90.000 (96.325) +2022-11-14 13:17:47,764 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2165 (0.1951) Prec@1 57.000 (64.432) Prec@5 96.000 (96.321) +2022-11-14 13:17:47,775 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1765 (0.1948) Prec@1 65.000 (64.439) Prec@5 95.000 (96.305) +2022-11-14 13:17:47,787 Test: [82/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1632 (0.1945) Prec@1 71.000 (64.518) Prec@5 99.000 (96.337) +2022-11-14 13:17:47,800 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2341 (0.1949) Prec@1 57.000 (64.429) Prec@5 94.000 (96.310) +2022-11-14 13:17:47,813 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1849 (0.1948) Prec@1 64.000 (64.424) Prec@5 99.000 (96.341) +2022-11-14 13:17:47,826 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1940 (0.1948) Prec@1 62.000 (64.395) Prec@5 96.000 (96.337) +2022-11-14 13:17:47,836 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1986 (0.1949) Prec@1 62.000 (64.368) Prec@5 99.000 (96.368) +2022-11-14 13:17:47,845 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2068 (0.1950) Prec@1 59.000 (64.307) Prec@5 97.000 (96.375) +2022-11-14 13:17:47,855 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1804 (0.1948) Prec@1 67.000 (64.337) Prec@5 96.000 (96.371) +2022-11-14 13:17:47,866 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2024 (0.1949) Prec@1 61.000 (64.300) Prec@5 97.000 (96.378) +2022-11-14 13:17:47,876 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1764 (0.1947) Prec@1 68.000 (64.341) Prec@5 97.000 (96.385) +2022-11-14 13:17:47,888 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1648 (0.1944) Prec@1 71.000 (64.413) Prec@5 96.000 (96.380) +2022-11-14 13:17:47,898 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2050 (0.1945) Prec@1 58.000 (64.344) Prec@5 97.000 (96.387) +2022-11-14 13:17:47,910 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1972 (0.1945) Prec@1 66.000 (64.362) Prec@5 97.000 (96.394) +2022-11-14 13:17:47,921 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1775 (0.1943) Prec@1 66.000 (64.379) Prec@5 97.000 (96.400) +2022-11-14 13:17:47,932 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1786 (0.1942) Prec@1 65.000 (64.385) Prec@5 97.000 (96.406) +2022-11-14 13:17:47,944 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1768 (0.1940) Prec@1 67.000 (64.412) Prec@5 96.000 (96.402) +2022-11-14 13:17:47,953 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2115 (0.1942) Prec@1 61.000 (64.378) Prec@5 95.000 (96.388) +2022-11-14 13:17:47,964 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1975 (0.1942) Prec@1 61.000 (64.343) Prec@5 95.000 (96.374) +2022-11-14 13:17:47,975 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1986 (0.1943) Prec@1 63.000 (64.330) Prec@5 97.000 (96.380) +2022-11-14 13:17:48,030 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:17:48,342 Epoch: [17][0/500] Time 0.030 (0.030) Data 0.212 (0.212) Loss 0.1311 (0.1311) Prec@1 75.000 (75.000) Prec@5 99.000 (99.000) +2022-11-14 13:17:48,565 Epoch: [17][10/500] Time 0.018 (0.020) Data 0.002 (0.021) Loss 0.1093 (0.1202) Prec@1 81.000 (78.000) Prec@5 97.000 (98.000) +2022-11-14 13:17:48,784 Epoch: [17][20/500] Time 0.024 (0.020) Data 0.002 (0.012) Loss 0.1522 (0.1308) Prec@1 73.000 (76.333) Prec@5 100.000 (98.667) +2022-11-14 13:17:49,077 Epoch: [17][30/500] Time 0.031 (0.022) Data 0.002 (0.009) Loss 0.1122 (0.1262) Prec@1 85.000 (78.500) Prec@5 96.000 (98.000) +2022-11-14 13:17:49,374 Epoch: [17][40/500] Time 0.031 (0.023) Data 0.002 (0.007) Loss 0.1356 (0.1281) Prec@1 74.000 (77.600) Prec@5 99.000 (98.200) +2022-11-14 13:17:49,692 Epoch: [17][50/500] Time 0.030 (0.024) Data 0.002 (0.006) Loss 0.1472 (0.1313) Prec@1 76.000 (77.333) Prec@5 98.000 (98.167) +2022-11-14 13:17:50,004 Epoch: [17][60/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.1421 (0.1328) Prec@1 78.000 (77.429) Prec@5 95.000 (97.714) +2022-11-14 13:17:50,312 Epoch: [17][70/500] Time 0.028 (0.025) Data 0.002 (0.005) Loss 0.1725 (0.1378) Prec@1 66.000 (76.000) Prec@5 96.000 (97.500) +2022-11-14 13:17:50,627 Epoch: [17][80/500] Time 0.037 (0.025) Data 0.002 (0.004) Loss 0.1503 (0.1392) Prec@1 72.000 (75.556) Prec@5 95.000 (97.222) +2022-11-14 13:17:50,939 Epoch: [17][90/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.1444 (0.1397) Prec@1 75.000 (75.500) Prec@5 99.000 (97.400) +2022-11-14 13:17:51,248 Epoch: [17][100/500] Time 0.033 (0.026) Data 0.002 (0.004) Loss 0.1290 (0.1387) Prec@1 79.000 (75.818) Prec@5 97.000 (97.364) +2022-11-14 13:17:51,556 Epoch: [17][110/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.1072 (0.1361) Prec@1 82.000 (76.333) Prec@5 96.000 (97.250) +2022-11-14 13:17:51,864 Epoch: [17][120/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.1212 (0.1349) Prec@1 80.000 (76.615) Prec@5 98.000 (97.308) +2022-11-14 13:17:52,183 Epoch: [17][130/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1147 (0.1335) Prec@1 78.000 (76.714) Prec@5 96.000 (97.214) +2022-11-14 13:17:52,498 Epoch: [17][140/500] Time 0.036 (0.026) Data 0.002 (0.003) Loss 0.1273 (0.1331) Prec@1 78.000 (76.800) Prec@5 99.000 (97.333) +2022-11-14 13:17:52,815 Epoch: [17][150/500] Time 0.025 (0.026) Data 0.002 (0.003) Loss 0.1563 (0.1345) Prec@1 74.000 (76.625) Prec@5 92.000 (97.000) +2022-11-14 13:17:53,139 Epoch: [17][160/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1645 (0.1363) Prec@1 72.000 (76.353) Prec@5 97.000 (97.000) +2022-11-14 13:17:53,456 Epoch: [17][170/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.1113 (0.1349) Prec@1 80.000 (76.556) Prec@5 100.000 (97.167) +2022-11-14 13:17:53,761 Epoch: [17][180/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.1612 (0.1363) Prec@1 75.000 (76.474) Prec@5 98.000 (97.211) +2022-11-14 13:17:54,088 Epoch: [17][190/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1440 (0.1367) Prec@1 76.000 (76.450) Prec@5 95.000 (97.100) +2022-11-14 13:17:54,396 Epoch: [17][200/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1659 (0.1381) Prec@1 70.000 (76.143) Prec@5 95.000 (97.000) +2022-11-14 13:17:54,710 Epoch: [17][210/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1888 (0.1404) Prec@1 66.000 (75.682) Prec@5 96.000 (96.955) +2022-11-14 13:17:55,031 Epoch: [17][220/500] Time 0.032 (0.027) Data 0.001 (0.003) Loss 0.1329 (0.1401) Prec@1 79.000 (75.826) Prec@5 100.000 (97.087) +2022-11-14 13:17:55,344 Epoch: [17][230/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1456 (0.1403) Prec@1 74.000 (75.750) Prec@5 95.000 (97.000) +2022-11-14 13:17:55,659 Epoch: [17][240/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1729 (0.1416) Prec@1 71.000 (75.560) Prec@5 99.000 (97.080) +2022-11-14 13:17:55,960 Epoch: [17][250/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1449 (0.1417) Prec@1 70.000 (75.346) Prec@5 98.000 (97.115) +2022-11-14 13:17:56,274 Epoch: [17][260/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.1607 (0.1424) Prec@1 71.000 (75.185) Prec@5 96.000 (97.074) +2022-11-14 13:17:56,578 Epoch: [17][270/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1145 (0.1414) Prec@1 78.000 (75.286) Prec@5 98.000 (97.107) +2022-11-14 13:17:56,892 Epoch: [17][280/500] Time 0.025 (0.027) Data 0.002 (0.003) Loss 0.1656 (0.1423) Prec@1 71.000 (75.138) Prec@5 94.000 (97.000) +2022-11-14 13:17:57,206 Epoch: [17][290/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0904 (0.1405) Prec@1 86.000 (75.500) Prec@5 99.000 (97.067) +2022-11-14 13:17:57,521 Epoch: [17][300/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.1098 (0.1395) Prec@1 81.000 (75.677) Prec@5 96.000 (97.032) +2022-11-14 13:17:57,840 Epoch: [17][310/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1704 (0.1405) Prec@1 69.000 (75.469) Prec@5 98.000 (97.062) +2022-11-14 13:17:58,149 Epoch: [17][320/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.1109 (0.1396) Prec@1 82.000 (75.667) Prec@5 97.000 (97.061) +2022-11-14 13:17:58,463 Epoch: [17][330/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1579 (0.1401) Prec@1 71.000 (75.529) Prec@5 97.000 (97.059) +2022-11-14 13:17:58,777 Epoch: [17][340/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1492 (0.1404) Prec@1 77.000 (75.571) Prec@5 96.000 (97.029) +2022-11-14 13:17:59,111 Epoch: [17][350/500] Time 0.036 (0.027) Data 0.002 (0.002) Loss 0.1170 (0.1397) Prec@1 80.000 (75.694) Prec@5 95.000 (96.972) +2022-11-14 13:17:59,597 Epoch: [17][360/500] Time 0.044 (0.028) Data 0.002 (0.002) Loss 0.1137 (0.1390) Prec@1 83.000 (75.892) Prec@5 97.000 (96.973) +2022-11-14 13:18:00,113 Epoch: [17][370/500] Time 0.055 (0.028) Data 0.002 (0.002) Loss 0.1227 (0.1386) Prec@1 78.000 (75.947) Prec@5 99.000 (97.026) +2022-11-14 13:18:00,628 Epoch: [17][380/500] Time 0.058 (0.029) Data 0.002 (0.002) Loss 0.1721 (0.1395) Prec@1 69.000 (75.769) Prec@5 94.000 (96.949) +2022-11-14 13:18:01,108 Epoch: [17][390/500] Time 0.044 (0.029) Data 0.002 (0.002) Loss 0.1824 (0.1405) Prec@1 66.000 (75.525) Prec@5 98.000 (96.975) +2022-11-14 13:18:01,599 Epoch: [17][400/500] Time 0.044 (0.029) Data 0.002 (0.002) Loss 0.1296 (0.1403) Prec@1 79.000 (75.610) Prec@5 98.000 (97.000) +2022-11-14 13:18:02,074 Epoch: [17][410/500] Time 0.050 (0.030) Data 0.002 (0.002) Loss 0.1259 (0.1399) Prec@1 75.000 (75.595) Prec@5 98.000 (97.024) +2022-11-14 13:18:02,562 Epoch: [17][420/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.1562 (0.1403) Prec@1 70.000 (75.465) Prec@5 96.000 (97.000) +2022-11-14 13:18:03,048 Epoch: [17][430/500] Time 0.044 (0.030) Data 0.001 (0.002) Loss 0.1619 (0.1408) Prec@1 73.000 (75.409) Prec@5 96.000 (96.977) +2022-11-14 13:18:03,532 Epoch: [17][440/500] Time 0.050 (0.031) Data 0.002 (0.002) Loss 0.1325 (0.1406) Prec@1 76.000 (75.422) Prec@5 97.000 (96.978) +2022-11-14 13:18:04,033 Epoch: [17][450/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.1029 (0.1398) Prec@1 82.000 (75.565) Prec@5 100.000 (97.043) +2022-11-14 13:18:04,522 Epoch: [17][460/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.1342 (0.1397) Prec@1 78.000 (75.617) Prec@5 97.000 (97.043) +2022-11-14 13:18:05,032 Epoch: [17][470/500] Time 0.051 (0.031) Data 0.002 (0.002) Loss 0.1525 (0.1399) Prec@1 70.000 (75.500) Prec@5 98.000 (97.062) +2022-11-14 13:18:05,506 Epoch: [17][480/500] Time 0.046 (0.032) Data 0.001 (0.002) Loss 0.1324 (0.1398) Prec@1 76.000 (75.510) Prec@5 98.000 (97.082) +2022-11-14 13:18:06,008 Epoch: [17][490/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.1434 (0.1399) Prec@1 73.000 (75.460) Prec@5 100.000 (97.140) +2022-11-14 13:18:06,440 Epoch: [17][499/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.1229 (0.1395) Prec@1 81.000 (75.569) Prec@5 99.000 (97.176) +2022-11-14 13:18:06,719 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.1747 (0.1747) Prec@1 68.000 (68.000) Prec@5 96.000 (96.000) +2022-11-14 13:18:06,729 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1721 (0.1734) Prec@1 70.000 (69.000) Prec@5 98.000 (97.000) +2022-11-14 13:18:06,739 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1514 (0.1661) Prec@1 75.000 (71.000) Prec@5 96.000 (96.667) +2022-11-14 13:18:06,751 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1473 (0.1614) Prec@1 75.000 (72.000) Prec@5 100.000 (97.500) +2022-11-14 13:18:06,760 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1885 (0.1668) Prec@1 67.000 (71.000) Prec@5 98.000 (97.600) +2022-11-14 13:18:06,769 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1685 (0.1671) Prec@1 66.000 (70.167) Prec@5 97.000 (97.500) +2022-11-14 13:18:06,780 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1947 (0.1710) Prec@1 64.000 (69.286) Prec@5 95.000 (97.143) +2022-11-14 13:18:06,791 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1672 (0.1705) Prec@1 67.000 (69.000) Prec@5 97.000 (97.125) +2022-11-14 13:18:06,798 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1733 (0.1709) Prec@1 70.000 (69.111) Prec@5 97.000 (97.111) +2022-11-14 13:18:06,806 Test: [9/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.1777 (0.1715) Prec@1 67.000 (68.900) Prec@5 93.000 (96.700) +2022-11-14 13:18:06,816 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1603 (0.1705) Prec@1 69.000 (68.909) Prec@5 100.000 (97.000) +2022-11-14 13:18:06,826 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1750 (0.1709) Prec@1 69.000 (68.917) Prec@5 95.000 (96.833) +2022-11-14 13:18:06,836 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1733 (0.1711) Prec@1 69.000 (68.923) Prec@5 99.000 (97.000) +2022-11-14 13:18:06,846 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1400 (0.1689) Prec@1 75.000 (69.357) Prec@5 98.000 (97.071) +2022-11-14 13:18:06,857 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1639 (0.1685) Prec@1 68.000 (69.267) Prec@5 95.000 (96.933) +2022-11-14 13:18:06,868 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1911 (0.1699) Prec@1 69.000 (69.250) Prec@5 93.000 (96.688) +2022-11-14 13:18:06,878 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1572 (0.1692) Prec@1 72.000 (69.412) Prec@5 97.000 (96.706) +2022-11-14 13:18:06,888 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1732 (0.1694) Prec@1 69.000 (69.389) Prec@5 99.000 (96.833) +2022-11-14 13:18:06,901 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1464 (0.1682) Prec@1 70.000 (69.421) Prec@5 94.000 (96.684) +2022-11-14 13:18:06,911 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1741 (0.1685) Prec@1 65.000 (69.200) Prec@5 93.000 (96.500) +2022-11-14 13:18:06,921 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1870 (0.1694) Prec@1 65.000 (69.000) Prec@5 96.000 (96.476) +2022-11-14 13:18:06,930 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1573 (0.1688) Prec@1 68.000 (68.955) Prec@5 96.000 (96.455) +2022-11-14 13:18:06,940 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1562 (0.1683) Prec@1 75.000 (69.217) Prec@5 98.000 (96.522) +2022-11-14 13:18:06,950 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1757 (0.1686) Prec@1 68.000 (69.167) Prec@5 98.000 (96.583) +2022-11-14 13:18:06,959 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1775 (0.1689) Prec@1 65.000 (69.000) Prec@5 95.000 (96.520) +2022-11-14 13:18:06,968 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1885 (0.1697) Prec@1 66.000 (68.885) Prec@5 95.000 (96.462) +2022-11-14 13:18:06,978 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1558 (0.1692) Prec@1 71.000 (68.963) Prec@5 96.000 (96.444) +2022-11-14 13:18:06,987 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.1698) Prec@1 70.000 (69.000) Prec@5 94.000 (96.357) +2022-11-14 13:18:06,996 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1627 (0.1696) Prec@1 72.000 (69.103) Prec@5 94.000 (96.276) +2022-11-14 13:18:07,005 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1375 (0.1685) Prec@1 77.000 (69.367) Prec@5 97.000 (96.300) +2022-11-14 13:18:07,014 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1404 (0.1676) Prec@1 76.000 (69.581) Prec@5 95.000 (96.258) +2022-11-14 13:18:07,025 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1593 (0.1674) Prec@1 68.000 (69.531) Prec@5 99.000 (96.344) +2022-11-14 13:18:07,035 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1812 (0.1678) Prec@1 64.000 (69.364) Prec@5 94.000 (96.273) +2022-11-14 13:18:07,044 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1672 (0.1678) Prec@1 68.000 (69.324) Prec@5 98.000 (96.324) +2022-11-14 13:18:07,053 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1880 (0.1683) Prec@1 65.000 (69.200) Prec@5 94.000 (96.257) +2022-11-14 13:18:07,064 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1565 (0.1680) Prec@1 72.000 (69.278) Prec@5 95.000 (96.222) +2022-11-14 13:18:07,074 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2066 (0.1691) Prec@1 58.000 (68.973) Prec@5 97.000 (96.243) +2022-11-14 13:18:07,083 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1476 (0.1685) Prec@1 73.000 (69.079) Prec@5 99.000 (96.316) +2022-11-14 13:18:07,093 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1428 (0.1678) Prec@1 76.000 (69.256) Prec@5 99.000 (96.385) +2022-11-14 13:18:07,102 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1629 (0.1677) Prec@1 69.000 (69.250) Prec@5 95.000 (96.350) +2022-11-14 13:18:07,113 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1580 (0.1675) Prec@1 73.000 (69.341) Prec@5 93.000 (96.268) +2022-11-14 13:18:07,123 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1809 (0.1678) Prec@1 67.000 (69.286) Prec@5 95.000 (96.238) +2022-11-14 13:18:07,131 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1672) Prec@1 78.000 (69.488) Prec@5 96.000 (96.233) +2022-11-14 13:18:07,139 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.1669) Prec@1 74.000 (69.591) Prec@5 96.000 (96.227) +2022-11-14 13:18:07,149 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.1658) Prec@1 80.000 (69.822) Prec@5 97.000 (96.244) +2022-11-14 13:18:07,159 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1807 (0.1661) Prec@1 68.000 (69.783) Prec@5 96.000 (96.239) +2022-11-14 13:18:07,169 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1426 (0.1656) Prec@1 75.000 (69.894) Prec@5 97.000 (96.255) +2022-11-14 13:18:07,178 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1699 (0.1657) Prec@1 66.000 (69.812) Prec@5 98.000 (96.292) +2022-11-14 13:18:07,190 Test: [48/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1578 (0.1655) Prec@1 71.000 (69.837) Prec@5 99.000 (96.347) +2022-11-14 13:18:07,200 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1678 (0.1656) Prec@1 65.000 (69.740) Prec@5 95.000 (96.320) +2022-11-14 13:18:07,209 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1610 (0.1655) Prec@1 74.000 (69.824) Prec@5 95.000 (96.294) +2022-11-14 13:18:07,218 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1681 (0.1655) Prec@1 67.000 (69.769) Prec@5 97.000 (96.308) +2022-11-14 13:18:07,229 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.1650) Prec@1 75.000 (69.868) Prec@5 97.000 (96.321) +2022-11-14 13:18:07,240 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1541 (0.1648) Prec@1 75.000 (69.963) Prec@5 94.000 (96.278) +2022-11-14 13:18:07,248 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1874 (0.1652) Prec@1 63.000 (69.836) Prec@5 95.000 (96.255) +2022-11-14 13:18:07,257 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1822 (0.1655) Prec@1 65.000 (69.750) Prec@5 96.000 (96.250) +2022-11-14 13:18:07,268 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1791 (0.1657) Prec@1 65.000 (69.667) Prec@5 98.000 (96.281) +2022-11-14 13:18:07,279 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1924 (0.1662) Prec@1 63.000 (69.552) Prec@5 100.000 (96.345) +2022-11-14 13:18:07,289 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1855 (0.1665) Prec@1 65.000 (69.475) Prec@5 97.000 (96.356) +2022-11-14 13:18:07,299 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1787 (0.1667) Prec@1 68.000 (69.450) Prec@5 99.000 (96.400) +2022-11-14 13:18:07,310 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1466 (0.1664) Prec@1 74.000 (69.525) Prec@5 98.000 (96.426) +2022-11-14 13:18:07,320 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1620 (0.1663) Prec@1 68.000 (69.500) Prec@5 95.000 (96.403) +2022-11-14 13:18:07,330 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1429 (0.1659) Prec@1 74.000 (69.571) Prec@5 98.000 (96.429) +2022-11-14 13:18:07,338 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1589 (0.1658) Prec@1 69.000 (69.562) Prec@5 96.000 (96.422) +2022-11-14 13:18:07,350 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1828 (0.1661) Prec@1 67.000 (69.523) Prec@5 94.000 (96.385) +2022-11-14 13:18:07,360 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2068 (0.1667) Prec@1 62.000 (69.409) Prec@5 95.000 (96.364) +2022-11-14 13:18:07,369 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1903 (0.1670) Prec@1 66.000 (69.358) Prec@5 97.000 (96.373) +2022-11-14 13:18:07,378 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1671) Prec@1 68.000 (69.338) Prec@5 99.000 (96.412) +2022-11-14 13:18:07,389 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1884 (0.1674) Prec@1 59.000 (69.188) Prec@5 99.000 (96.449) +2022-11-14 13:18:07,400 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1922 (0.1678) Prec@1 62.000 (69.086) Prec@5 96.000 (96.443) +2022-11-14 13:18:07,408 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1496 (0.1675) Prec@1 71.000 (69.113) Prec@5 99.000 (96.479) +2022-11-14 13:18:07,417 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.1678) Prec@1 64.000 (69.042) Prec@5 92.000 (96.417) +2022-11-14 13:18:07,428 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1679) Prec@1 72.000 (69.082) Prec@5 97.000 (96.425) +2022-11-14 13:18:07,438 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1652 (0.1678) Prec@1 71.000 (69.108) Prec@5 97.000 (96.432) +2022-11-14 13:18:07,447 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1761 (0.1679) Prec@1 66.000 (69.067) Prec@5 96.000 (96.427) +2022-11-14 13:18:07,455 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1598 (0.1678) Prec@1 68.000 (69.053) Prec@5 98.000 (96.447) +2022-11-14 13:18:07,467 Test: [76/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1677 (0.1678) Prec@1 68.000 (69.039) Prec@5 97.000 (96.455) +2022-11-14 13:18:07,478 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1655 (0.1678) Prec@1 66.000 (69.000) Prec@5 98.000 (96.474) +2022-11-14 13:18:07,486 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1676 (0.1678) Prec@1 70.000 (69.013) Prec@5 97.000 (96.481) +2022-11-14 13:18:07,497 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.1679) Prec@1 68.000 (69.000) Prec@5 97.000 (96.487) +2022-11-14 13:18:07,508 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1515 (0.1677) Prec@1 71.000 (69.025) Prec@5 97.000 (96.494) +2022-11-14 13:18:07,518 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1676) Prec@1 74.000 (69.085) Prec@5 97.000 (96.500) +2022-11-14 13:18:07,527 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1712 (0.1676) Prec@1 70.000 (69.096) Prec@5 94.000 (96.470) +2022-11-14 13:18:07,537 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1922 (0.1679) Prec@1 67.000 (69.071) Prec@5 96.000 (96.464) +2022-11-14 13:18:07,548 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2070 (0.1684) Prec@1 60.000 (68.965) Prec@5 95.000 (96.447) +2022-11-14 13:18:07,558 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1948 (0.1687) Prec@1 63.000 (68.895) Prec@5 92.000 (96.395) +2022-11-14 13:18:07,568 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1739 (0.1688) Prec@1 71.000 (68.920) Prec@5 96.000 (96.391) +2022-11-14 13:18:07,577 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1689) Prec@1 70.000 (68.932) Prec@5 92.000 (96.341) +2022-11-14 13:18:07,588 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1643 (0.1688) Prec@1 73.000 (68.978) Prec@5 95.000 (96.326) +2022-11-14 13:18:07,599 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1955 (0.1691) Prec@1 66.000 (68.944) Prec@5 94.000 (96.300) +2022-11-14 13:18:07,608 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1496 (0.1689) Prec@1 72.000 (68.978) Prec@5 99.000 (96.330) +2022-11-14 13:18:07,617 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1685) Prec@1 75.000 (69.043) Prec@5 96.000 (96.326) +2022-11-14 13:18:07,626 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1733 (0.1685) Prec@1 70.000 (69.054) Prec@5 97.000 (96.333) +2022-11-14 13:18:07,635 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1670 (0.1685) Prec@1 67.000 (69.032) Prec@5 97.000 (96.340) +2022-11-14 13:18:07,644 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1661 (0.1685) Prec@1 72.000 (69.063) Prec@5 99.000 (96.368) +2022-11-14 13:18:07,652 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1603 (0.1684) Prec@1 71.000 (69.083) Prec@5 96.000 (96.365) +2022-11-14 13:18:07,662 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1682 (0.1684) Prec@1 68.000 (69.072) Prec@5 96.000 (96.361) +2022-11-14 13:18:07,671 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1896 (0.1686) Prec@1 64.000 (69.020) Prec@5 99.000 (96.388) +2022-11-14 13:18:07,679 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1709 (0.1686) Prec@1 67.000 (69.000) Prec@5 98.000 (96.404) +2022-11-14 13:18:07,688 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1723 (0.1687) Prec@1 68.000 (68.990) Prec@5 97.000 (96.410) +2022-11-14 13:18:07,743 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:18:08,044 Epoch: [18][0/500] Time 0.030 (0.030) Data 0.214 (0.214) Loss 0.0968 (0.0968) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:18:08,275 Epoch: [18][10/500] Time 0.020 (0.021) Data 0.002 (0.021) Loss 0.1264 (0.1116) Prec@1 75.000 (80.500) Prec@5 99.000 (99.000) +2022-11-14 13:18:08,481 Epoch: [18][20/500] Time 0.019 (0.020) Data 0.002 (0.012) Loss 0.1365 (0.1199) Prec@1 74.000 (78.333) Prec@5 97.000 (98.333) +2022-11-14 13:18:08,684 Epoch: [18][30/500] Time 0.020 (0.019) Data 0.002 (0.009) Loss 0.1185 (0.1195) Prec@1 78.000 (78.250) Prec@5 99.000 (98.500) +2022-11-14 13:18:08,886 Epoch: [18][40/500] Time 0.020 (0.019) Data 0.001 (0.007) Loss 0.1317 (0.1220) Prec@1 79.000 (78.400) Prec@5 98.000 (98.400) +2022-11-14 13:18:09,134 Epoch: [18][50/500] Time 0.022 (0.019) Data 0.002 (0.006) Loss 0.1273 (0.1229) Prec@1 79.000 (78.500) Prec@5 98.000 (98.333) +2022-11-14 13:18:09,408 Epoch: [18][60/500] Time 0.024 (0.020) Data 0.001 (0.005) Loss 0.1072 (0.1206) Prec@1 83.000 (79.143) Prec@5 99.000 (98.429) +2022-11-14 13:18:09,677 Epoch: [18][70/500] Time 0.025 (0.021) Data 0.001 (0.005) Loss 0.1580 (0.1253) Prec@1 68.000 (77.750) Prec@5 97.000 (98.250) +2022-11-14 13:18:09,940 Epoch: [18][80/500] Time 0.022 (0.021) Data 0.001 (0.004) Loss 0.1334 (0.1262) Prec@1 78.000 (77.778) Prec@5 98.000 (98.222) +2022-11-14 13:18:10,201 Epoch: [18][90/500] Time 0.027 (0.021) Data 0.001 (0.004) Loss 0.1228 (0.1258) Prec@1 81.000 (78.100) Prec@5 99.000 (98.300) +2022-11-14 13:18:10,469 Epoch: [18][100/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.1391 (0.1270) Prec@1 76.000 (77.909) Prec@5 97.000 (98.182) +2022-11-14 13:18:10,736 Epoch: [18][110/500] Time 0.022 (0.022) Data 0.001 (0.004) Loss 0.1874 (0.1321) Prec@1 68.000 (77.083) Prec@5 95.000 (97.917) +2022-11-14 13:18:11,005 Epoch: [18][120/500] Time 0.022 (0.022) Data 0.002 (0.003) Loss 0.1604 (0.1343) Prec@1 73.000 (76.769) Prec@5 96.000 (97.769) +2022-11-14 13:18:11,269 Epoch: [18][130/500] Time 0.022 (0.022) Data 0.002 (0.003) Loss 0.1356 (0.1344) Prec@1 75.000 (76.643) Prec@5 96.000 (97.643) +2022-11-14 13:18:11,529 Epoch: [18][140/500] Time 0.022 (0.022) Data 0.002 (0.003) Loss 0.1302 (0.1341) Prec@1 78.000 (76.733) Prec@5 100.000 (97.800) +2022-11-14 13:18:11,816 Epoch: [18][150/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.1401 (0.1345) Prec@1 74.000 (76.562) Prec@5 95.000 (97.625) +2022-11-14 13:18:12,252 Epoch: [18][160/500] Time 0.040 (0.023) Data 0.002 (0.003) Loss 0.1128 (0.1332) Prec@1 81.000 (76.824) Prec@5 100.000 (97.765) +2022-11-14 13:18:12,676 Epoch: [18][170/500] Time 0.039 (0.024) Data 0.002 (0.003) Loss 0.1413 (0.1336) Prec@1 72.000 (76.556) Prec@5 99.000 (97.833) +2022-11-14 13:18:13,111 Epoch: [18][180/500] Time 0.039 (0.025) Data 0.002 (0.003) Loss 0.1783 (0.1360) Prec@1 66.000 (76.000) Prec@5 95.000 (97.684) +2022-11-14 13:18:13,546 Epoch: [18][190/500] Time 0.040 (0.026) Data 0.002 (0.003) Loss 0.1187 (0.1351) Prec@1 76.000 (76.000) Prec@5 99.000 (97.750) +2022-11-14 13:18:13,983 Epoch: [18][200/500] Time 0.046 (0.026) Data 0.002 (0.003) Loss 0.1283 (0.1348) Prec@1 74.000 (75.905) Prec@5 99.000 (97.810) +2022-11-14 13:18:14,412 Epoch: [18][210/500] Time 0.045 (0.027) Data 0.002 (0.003) Loss 0.1179 (0.1340) Prec@1 82.000 (76.182) Prec@5 99.000 (97.864) +2022-11-14 13:18:14,855 Epoch: [18][220/500] Time 0.046 (0.027) Data 0.002 (0.003) Loss 0.1547 (0.1349) Prec@1 73.000 (76.043) Prec@5 96.000 (97.783) +2022-11-14 13:18:15,286 Epoch: [18][230/500] Time 0.051 (0.028) Data 0.003 (0.003) Loss 0.1421 (0.1352) Prec@1 74.000 (75.958) Prec@5 95.000 (97.667) +2022-11-14 13:18:15,702 Epoch: [18][240/500] Time 0.038 (0.028) Data 0.002 (0.003) Loss 0.1482 (0.1357) Prec@1 75.000 (75.920) Prec@5 97.000 (97.640) +2022-11-14 13:18:16,127 Epoch: [18][250/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.1592 (0.1366) Prec@1 70.000 (75.692) Prec@5 99.000 (97.692) +2022-11-14 13:18:16,565 Epoch: [18][260/500] Time 0.045 (0.029) Data 0.002 (0.003) Loss 0.1432 (0.1369) Prec@1 74.000 (75.630) Prec@5 99.000 (97.741) +2022-11-14 13:18:16,984 Epoch: [18][270/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.1228 (0.1364) Prec@1 78.000 (75.714) Prec@5 97.000 (97.714) +2022-11-14 13:18:17,413 Epoch: [18][280/500] Time 0.039 (0.030) Data 0.002 (0.003) Loss 0.1400 (0.1365) Prec@1 70.000 (75.517) Prec@5 98.000 (97.724) +2022-11-14 13:18:17,850 Epoch: [18][290/500] Time 0.046 (0.030) Data 0.002 (0.003) Loss 0.1670 (0.1375) Prec@1 69.000 (75.300) Prec@5 99.000 (97.767) +2022-11-14 13:18:18,267 Epoch: [18][300/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.1836 (0.1390) Prec@1 64.000 (74.935) Prec@5 98.000 (97.774) +2022-11-14 13:18:18,687 Epoch: [18][310/500] Time 0.050 (0.031) Data 0.002 (0.003) Loss 0.1593 (0.1396) Prec@1 68.000 (74.719) Prec@5 97.000 (97.750) +2022-11-14 13:18:19,103 Epoch: [18][320/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.1642 (0.1404) Prec@1 68.000 (74.515) Prec@5 99.000 (97.788) +2022-11-14 13:18:19,509 Epoch: [18][330/500] Time 0.037 (0.031) Data 0.002 (0.002) Loss 0.1203 (0.1398) Prec@1 80.000 (74.676) Prec@5 96.000 (97.735) +2022-11-14 13:18:19,933 Epoch: [18][340/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.1430 (0.1399) Prec@1 74.000 (74.657) Prec@5 98.000 (97.743) +2022-11-14 13:18:20,342 Epoch: [18][350/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.1566 (0.1404) Prec@1 73.000 (74.611) Prec@5 99.000 (97.778) +2022-11-14 13:18:20,762 Epoch: [18][360/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.1503 (0.1406) Prec@1 73.000 (74.568) Prec@5 95.000 (97.703) +2022-11-14 13:18:21,196 Epoch: [18][370/500] Time 0.049 (0.032) Data 0.002 (0.002) Loss 0.1636 (0.1412) Prec@1 71.000 (74.474) Prec@5 95.000 (97.632) +2022-11-14 13:18:21,627 Epoch: [18][380/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.1150 (0.1406) Prec@1 82.000 (74.667) Prec@5 97.000 (97.615) +2022-11-14 13:18:22,074 Epoch: [18][390/500] Time 0.047 (0.032) Data 0.003 (0.002) Loss 0.1320 (0.1403) Prec@1 76.000 (74.700) Prec@5 97.000 (97.600) +2022-11-14 13:18:22,496 Epoch: [18][400/500] Time 0.049 (0.032) Data 0.002 (0.002) Loss 0.1684 (0.1410) Prec@1 69.000 (74.561) Prec@5 97.000 (97.585) +2022-11-14 13:18:22,900 Epoch: [18][410/500] Time 0.045 (0.032) Data 0.002 (0.002) Loss 0.1773 (0.1419) Prec@1 67.000 (74.381) Prec@5 100.000 (97.643) +2022-11-14 13:18:23,328 Epoch: [18][420/500] Time 0.047 (0.032) Data 0.002 (0.002) Loss 0.1241 (0.1415) Prec@1 75.000 (74.395) Prec@5 99.000 (97.674) +2022-11-14 13:18:23,729 Epoch: [18][430/500] Time 0.039 (0.032) Data 0.002 (0.002) Loss 0.1359 (0.1414) Prec@1 76.000 (74.432) Prec@5 98.000 (97.682) +2022-11-14 13:18:24,158 Epoch: [18][440/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.1378 (0.1413) Prec@1 77.000 (74.489) Prec@5 99.000 (97.711) +2022-11-14 13:18:24,628 Epoch: [18][450/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.1160 (0.1407) Prec@1 78.000 (74.565) Prec@5 96.000 (97.674) +2022-11-14 13:18:25,066 Epoch: [18][460/500] Time 0.038 (0.033) Data 0.002 (0.002) Loss 0.1309 (0.1405) Prec@1 76.000 (74.596) Prec@5 98.000 (97.681) +2022-11-14 13:18:25,482 Epoch: [18][470/500] Time 0.046 (0.033) Data 0.001 (0.002) Loss 0.1346 (0.1404) Prec@1 76.000 (74.625) Prec@5 98.000 (97.688) +2022-11-14 13:18:25,975 Epoch: [18][480/500] Time 0.054 (0.033) Data 0.002 (0.002) Loss 0.1554 (0.1407) Prec@1 75.000 (74.633) Prec@5 97.000 (97.673) +2022-11-14 13:18:26,524 Epoch: [18][490/500] Time 0.056 (0.034) Data 0.002 (0.002) Loss 0.1749 (0.1414) Prec@1 63.000 (74.400) Prec@5 96.000 (97.640) +2022-11-14 13:18:26,974 Epoch: [18][499/500] Time 0.048 (0.034) Data 0.003 (0.002) Loss 0.1318 (0.1412) Prec@1 75.000 (74.412) Prec@5 99.000 (97.667) +2022-11-14 13:18:27,279 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1446 (0.1446) Prec@1 78.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:18:27,290 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1787 (0.1616) Prec@1 66.000 (72.000) Prec@5 98.000 (98.000) +2022-11-14 13:18:27,303 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1421 (0.1551) Prec@1 78.000 (74.000) Prec@5 97.000 (97.667) +2022-11-14 13:18:27,319 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1369 (0.1506) Prec@1 76.000 (74.500) Prec@5 100.000 (98.250) +2022-11-14 13:18:27,331 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1809 (0.1566) Prec@1 67.000 (73.000) Prec@5 95.000 (97.600) +2022-11-14 13:18:27,340 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1196 (0.1505) Prec@1 76.000 (73.500) Prec@5 99.000 (97.833) +2022-11-14 13:18:27,348 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1330 (0.1480) Prec@1 77.000 (74.000) Prec@5 99.000 (98.000) +2022-11-14 13:18:27,361 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1656 (0.1502) Prec@1 72.000 (73.750) Prec@5 96.000 (97.750) +2022-11-14 13:18:27,371 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1717 (0.1526) Prec@1 66.000 (72.889) Prec@5 99.000 (97.889) +2022-11-14 13:18:27,379 Test: [9/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1032 (0.1476) Prec@1 81.000 (73.700) Prec@5 99.000 (98.000) +2022-11-14 13:18:27,387 Test: [10/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1380 (0.1468) Prec@1 78.000 (74.091) Prec@5 99.000 (98.091) +2022-11-14 13:18:27,399 Test: [11/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1451 (0.1466) Prec@1 73.000 (74.000) Prec@5 96.000 (97.917) +2022-11-14 13:18:27,409 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1641 (0.1480) Prec@1 70.000 (73.692) Prec@5 99.000 (98.000) +2022-11-14 13:18:27,419 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1251 (0.1463) Prec@1 78.000 (74.000) Prec@5 99.000 (98.071) +2022-11-14 13:18:27,428 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1409 (0.1460) Prec@1 75.000 (74.067) Prec@5 97.000 (98.000) +2022-11-14 13:18:27,438 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1969 (0.1492) Prec@1 63.000 (73.375) Prec@5 97.000 (97.938) +2022-11-14 13:18:27,448 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1347 (0.1483) Prec@1 77.000 (73.588) Prec@5 98.000 (97.941) +2022-11-14 13:18:27,456 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1672 (0.1494) Prec@1 71.000 (73.444) Prec@5 97.000 (97.889) +2022-11-14 13:18:27,464 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1644 (0.1501) Prec@1 68.000 (73.158) Prec@5 95.000 (97.737) +2022-11-14 13:18:27,472 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1401 (0.1496) Prec@1 77.000 (73.350) Prec@5 95.000 (97.600) +2022-11-14 13:18:27,480 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1687 (0.1506) Prec@1 70.000 (73.190) Prec@5 98.000 (97.619) +2022-11-14 13:18:27,489 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1585 (0.1509) Prec@1 75.000 (73.273) Prec@5 96.000 (97.545) +2022-11-14 13:18:27,498 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1856 (0.1524) Prec@1 64.000 (72.870) Prec@5 100.000 (97.652) +2022-11-14 13:18:27,507 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1477 (0.1522) Prec@1 77.000 (73.042) Prec@5 98.000 (97.667) +2022-11-14 13:18:27,517 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1580 (0.1525) Prec@1 73.000 (73.040) Prec@5 97.000 (97.640) +2022-11-14 13:18:27,526 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2095 (0.1546) Prec@1 66.000 (72.769) Prec@5 93.000 (97.462) +2022-11-14 13:18:27,535 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1588 (0.1548) Prec@1 74.000 (72.815) Prec@5 99.000 (97.519) +2022-11-14 13:18:27,544 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1483 (0.1546) Prec@1 72.000 (72.786) Prec@5 95.000 (97.429) +2022-11-14 13:18:27,553 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1554 (0.1546) Prec@1 73.000 (72.793) Prec@5 93.000 (97.276) +2022-11-14 13:18:27,561 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1382 (0.1541) Prec@1 79.000 (73.000) Prec@5 98.000 (97.300) +2022-11-14 13:18:27,570 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1771 (0.1548) Prec@1 68.000 (72.839) Prec@5 100.000 (97.387) +2022-11-14 13:18:27,580 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1473 (0.1546) Prec@1 72.000 (72.812) Prec@5 97.000 (97.375) +2022-11-14 13:18:27,589 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1492 (0.1544) Prec@1 73.000 (72.818) Prec@5 95.000 (97.303) +2022-11-14 13:18:27,600 Test: 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0.1276 (0.1541) Prec@1 78.000 (72.700) Prec@5 99.000 (97.375) +2022-11-14 13:18:27,672 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1590 (0.1543) Prec@1 72.000 (72.683) Prec@5 99.000 (97.415) +2022-11-14 13:18:27,681 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1358 (0.1538) Prec@1 77.000 (72.786) Prec@5 98.000 (97.429) +2022-11-14 13:18:27,691 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1313 (0.1533) Prec@1 79.000 (72.930) Prec@5 98.000 (97.442) +2022-11-14 13:18:27,700 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1418 (0.1530) Prec@1 73.000 (72.932) Prec@5 98.000 (97.455) +2022-11-14 13:18:27,710 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1818 (0.1537) Prec@1 69.000 (72.844) Prec@5 98.000 (97.467) +2022-11-14 13:18:27,722 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.1531) Prec@1 80.000 (73.000) Prec@5 97.000 (97.457) +2022-11-14 13:18:27,732 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1597 (0.1532) Prec@1 76.000 (73.064) Prec@5 95.000 (97.404) +2022-11-14 13:18:27,742 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1312 (0.1527) Prec@1 76.000 (73.125) Prec@5 98.000 (97.417) +2022-11-14 13:18:27,751 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.1517) Prec@1 81.000 (73.286) Prec@5 98.000 (97.429) +2022-11-14 13:18:27,761 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1809 (0.1523) Prec@1 67.000 (73.160) Prec@5 98.000 (97.440) +2022-11-14 13:18:27,770 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1384 (0.1520) Prec@1 76.000 (73.216) Prec@5 98.000 (97.451) +2022-11-14 13:18:27,779 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1482 (0.1519) Prec@1 75.000 (73.250) Prec@5 96.000 (97.423) +2022-11-14 13:18:27,788 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1339 (0.1516) Prec@1 78.000 (73.340) Prec@5 98.000 (97.434) +2022-11-14 13:18:27,798 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1564 (0.1517) Prec@1 77.000 (73.407) Prec@5 96.000 (97.407) +2022-11-14 13:18:27,808 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1677 (0.1520) Prec@1 68.000 (73.309) Prec@5 97.000 (97.400) +2022-11-14 13:18:27,819 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1464 (0.1519) Prec@1 75.000 (73.339) Prec@5 98.000 (97.411) +2022-11-14 13:18:27,829 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1380 (0.1516) Prec@1 75.000 (73.368) Prec@5 99.000 (97.439) +2022-11-14 13:18:27,840 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1280 (0.1512) Prec@1 78.000 (73.448) Prec@5 99.000 (97.466) +2022-11-14 13:18:27,850 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1977 (0.1520) Prec@1 67.000 (73.339) Prec@5 98.000 (97.475) +2022-11-14 13:18:27,859 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1581 (0.1521) Prec@1 72.000 (73.317) Prec@5 96.000 (97.450) +2022-11-14 13:18:27,869 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1687 (0.1524) Prec@1 69.000 (73.246) Prec@5 97.000 (97.443) +2022-11-14 13:18:27,878 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1510 (0.1524) Prec@1 72.000 (73.226) Prec@5 98.000 (97.452) +2022-11-14 13:18:27,887 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1474 (0.1523) Prec@1 72.000 (73.206) Prec@5 98.000 (97.460) +2022-11-14 13:18:27,896 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1516) Prec@1 82.000 (73.344) Prec@5 100.000 (97.500) +2022-11-14 13:18:27,906 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1791 (0.1520) Prec@1 66.000 (73.231) Prec@5 96.000 (97.477) +2022-11-14 13:18:27,915 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1408 (0.1518) Prec@1 76.000 (73.273) Prec@5 98.000 (97.485) +2022-11-14 13:18:27,926 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1361 (0.1516) Prec@1 78.000 (73.343) Prec@5 99.000 (97.507) +2022-11-14 13:18:27,937 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1491 (0.1516) Prec@1 76.000 (73.382) Prec@5 95.000 (97.471) +2022-11-14 13:18:27,946 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1528 (0.1516) Prec@1 74.000 (73.391) Prec@5 96.000 (97.449) +2022-11-14 13:18:27,956 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1657 (0.1518) Prec@1 70.000 (73.343) Prec@5 97.000 (97.443) +2022-11-14 13:18:27,966 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1736 (0.1521) Prec@1 73.000 (73.338) Prec@5 98.000 (97.451) +2022-11-14 13:18:27,975 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1597 (0.1522) Prec@1 73.000 (73.333) Prec@5 98.000 (97.458) +2022-11-14 13:18:27,988 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1458 (0.1521) Prec@1 75.000 (73.356) Prec@5 99.000 (97.479) +2022-11-14 13:18:28,000 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1516) Prec@1 79.000 (73.432) Prec@5 99.000 (97.500) +2022-11-14 13:18:28,011 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1600 (0.1518) Prec@1 73.000 (73.427) Prec@5 96.000 (97.480) +2022-11-14 13:18:28,023 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1516) Prec@1 75.000 (73.447) Prec@5 98.000 (97.487) +2022-11-14 13:18:28,034 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1519) Prec@1 72.000 (73.429) Prec@5 94.000 (97.442) +2022-11-14 13:18:28,044 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1518) Prec@1 75.000 (73.449) Prec@5 97.000 (97.436) +2022-11-14 13:18:28,056 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1558 (0.1518) Prec@1 75.000 (73.468) Prec@5 100.000 (97.468) +2022-11-14 13:18:28,069 Test: [79/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1643 (0.1520) Prec@1 73.000 (73.463) Prec@5 98.000 (97.475) +2022-11-14 13:18:28,081 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1606 (0.1521) Prec@1 69.000 (73.407) Prec@5 97.000 (97.469) +2022-11-14 13:18:28,091 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1706 (0.1523) Prec@1 72.000 (73.390) Prec@5 96.000 (97.451) +2022-11-14 13:18:28,102 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1522) Prec@1 74.000 (73.398) Prec@5 100.000 (97.482) +2022-11-14 13:18:28,111 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1660 (0.1524) Prec@1 67.000 (73.321) Prec@5 98.000 (97.488) +2022-11-14 13:18:28,120 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1951 (0.1529) Prec@1 66.000 (73.235) Prec@5 94.000 (97.447) +2022-11-14 13:18:28,130 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1527) Prec@1 73.000 (73.233) Prec@5 100.000 (97.477) +2022-11-14 13:18:28,138 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1524 (0.1527) Prec@1 73.000 (73.230) Prec@5 98.000 (97.483) +2022-11-14 13:18:28,148 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1560 (0.1527) Prec@1 74.000 (73.239) Prec@5 98.000 (97.489) +2022-11-14 13:18:28,159 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1367 (0.1526) Prec@1 75.000 (73.258) Prec@5 99.000 (97.506) +2022-11-14 13:18:28,172 Test: [89/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1524) Prec@1 75.000 (73.278) Prec@5 98.000 (97.511) +2022-11-14 13:18:28,186 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1684 (0.1526) Prec@1 65.000 (73.187) Prec@5 100.000 (97.538) +2022-11-14 13:18:28,196 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.1519) Prec@1 86.000 (73.326) Prec@5 97.000 (97.533) +2022-11-14 13:18:28,206 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1739 (0.1522) Prec@1 67.000 (73.258) Prec@5 97.000 (97.527) +2022-11-14 13:18:28,216 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1518) Prec@1 80.000 (73.330) Prec@5 95.000 (97.500) +2022-11-14 13:18:28,226 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1518) Prec@1 77.000 (73.368) Prec@5 97.000 (97.495) +2022-11-14 13:18:28,236 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1518) Prec@1 71.000 (73.344) Prec@5 97.000 (97.490) +2022-11-14 13:18:28,246 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.1512) Prec@1 82.000 (73.433) Prec@5 100.000 (97.515) +2022-11-14 13:18:28,255 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1946 (0.1517) Prec@1 60.000 (73.296) Prec@5 96.000 (97.500) +2022-11-14 13:18:28,264 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1758 (0.1519) Prec@1 70.000 (73.263) Prec@5 98.000 (97.505) +2022-11-14 13:18:28,273 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1521) Prec@1 67.000 (73.200) Prec@5 97.000 (97.500) +2022-11-14 13:18:28,328 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:18:28,643 Epoch: [19][0/500] Time 0.030 (0.030) Data 0.222 (0.222) Loss 0.1821 (0.1821) Prec@1 70.000 (70.000) Prec@5 97.000 (97.000) +2022-11-14 13:18:28,874 Epoch: [19][10/500] Time 0.018 (0.021) Data 0.001 (0.022) Loss 0.1410 (0.1616) Prec@1 77.000 (73.500) Prec@5 98.000 (97.500) +2022-11-14 13:18:29,095 Epoch: [19][20/500] Time 0.018 (0.021) Data 0.002 (0.012) Loss 0.1484 (0.1572) Prec@1 74.000 (73.667) Prec@5 99.000 (98.000) +2022-11-14 13:18:29,312 Epoch: [19][30/500] Time 0.020 (0.020) Data 0.002 (0.009) Loss 0.1398 (0.1528) Prec@1 77.000 (74.500) Prec@5 97.000 (97.750) +2022-11-14 13:18:29,535 Epoch: [19][40/500] Time 0.016 (0.020) Data 0.002 (0.007) Loss 0.1232 (0.1469) Prec@1 75.000 (74.600) Prec@5 99.000 (98.000) +2022-11-14 13:18:29,750 Epoch: [19][50/500] Time 0.018 (0.020) Data 0.001 (0.006) Loss 0.1590 (0.1489) Prec@1 73.000 (74.333) Prec@5 98.000 (98.000) +2022-11-14 13:18:30,004 Epoch: [19][60/500] Time 0.023 (0.020) Data 0.002 (0.005) Loss 0.1366 (0.1472) Prec@1 77.000 (74.714) Prec@5 100.000 (98.286) +2022-11-14 13:18:30,274 Epoch: [19][70/500] Time 0.025 (0.021) Data 0.002 (0.005) Loss 0.1470 (0.1471) Prec@1 73.000 (74.500) Prec@5 99.000 (98.375) +2022-11-14 13:18:30,544 Epoch: [19][80/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.1676 (0.1494) Prec@1 68.000 (73.778) Prec@5 95.000 (98.000) +2022-11-14 13:18:30,817 Epoch: [19][90/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.1272 (0.1472) Prec@1 76.000 (74.000) Prec@5 96.000 (97.800) +2022-11-14 13:18:31,094 Epoch: [19][100/500] Time 0.023 (0.022) Data 0.001 (0.004) Loss 0.1539 (0.1478) Prec@1 71.000 (73.727) Prec@5 98.000 (97.818) +2022-11-14 13:18:31,412 Epoch: [19][110/500] Time 0.038 (0.022) Data 0.002 (0.004) Loss 0.1639 (0.1491) Prec@1 68.000 (73.250) Prec@5 97.000 (97.750) +2022-11-14 13:18:31,694 Epoch: [19][120/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.1418 (0.1486) Prec@1 74.000 (73.308) Prec@5 98.000 (97.769) +2022-11-14 13:18:31,970 Epoch: [19][130/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.1259 (0.1470) Prec@1 77.000 (73.571) Prec@5 100.000 (97.929) +2022-11-14 13:18:32,301 Epoch: [19][140/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.1182 (0.1450) Prec@1 81.000 (74.067) Prec@5 99.000 (98.000) +2022-11-14 13:18:32,627 Epoch: [19][150/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.1528 (0.1455) Prec@1 71.000 (73.875) Prec@5 95.000 (97.812) +2022-11-14 13:18:32,915 Epoch: [19][160/500] Time 0.022 (0.024) Data 0.002 (0.003) Loss 0.1228 (0.1442) Prec@1 80.000 (74.235) Prec@5 97.000 (97.765) +2022-11-14 13:18:33,230 Epoch: [19][170/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.1666 (0.1454) Prec@1 70.000 (74.000) Prec@5 93.000 (97.500) +2022-11-14 13:18:33,551 Epoch: [19][180/500] Time 0.035 (0.024) Data 0.002 (0.003) Loss 0.1697 (0.1467) Prec@1 69.000 (73.737) Prec@5 93.000 (97.263) +2022-11-14 13:18:33,834 Epoch: [19][190/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.1293 (0.1458) Prec@1 78.000 (73.950) Prec@5 98.000 (97.300) +2022-11-14 13:18:34,152 Epoch: [19][200/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.1542 (0.1462) Prec@1 72.000 (73.857) Prec@5 97.000 (97.286) +2022-11-14 13:18:34,494 Epoch: [19][210/500] Time 0.026 (0.025) Data 0.002 (0.003) Loss 0.1377 (0.1458) Prec@1 77.000 (74.000) Prec@5 99.000 (97.364) +2022-11-14 13:18:34,845 Epoch: [19][220/500] Time 0.034 (0.025) Data 0.002 (0.003) Loss 0.1404 (0.1456) Prec@1 76.000 (74.087) Prec@5 98.000 (97.391) +2022-11-14 13:18:35,152 Epoch: [19][230/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.1267 (0.1448) Prec@1 77.000 (74.208) Prec@5 99.000 (97.458) +2022-11-14 13:18:35,538 Epoch: [19][240/500] Time 0.042 (0.026) Data 0.002 (0.003) Loss 0.1710 (0.1459) Prec@1 68.000 (73.960) Prec@5 96.000 (97.400) +2022-11-14 13:18:35,846 Epoch: [19][250/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1636 (0.1466) Prec@1 66.000 (73.654) Prec@5 99.000 (97.462) +2022-11-14 13:18:36,180 Epoch: [19][260/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.1684 (0.1474) Prec@1 70.000 (73.519) Prec@5 97.000 (97.444) +2022-11-14 13:18:36,616 Epoch: [19][270/500] Time 0.037 (0.026) Data 0.002 (0.003) Loss 0.1292 (0.1467) Prec@1 76.000 (73.607) Prec@5 96.000 (97.393) +2022-11-14 13:18:36,940 Epoch: [19][280/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.1566 (0.1471) Prec@1 73.000 (73.586) Prec@5 97.000 (97.379) +2022-11-14 13:18:37,276 Epoch: [19][290/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.1437 (0.1469) Prec@1 76.000 (73.667) Prec@5 98.000 (97.400) +2022-11-14 13:18:37,604 Epoch: [19][300/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.1597 (0.1474) Prec@1 71.000 (73.581) Prec@5 97.000 (97.387) +2022-11-14 13:18:37,955 Epoch: [19][310/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1546 (0.1476) Prec@1 70.000 (73.469) Prec@5 96.000 (97.344) +2022-11-14 13:18:38,270 Epoch: [19][320/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1236 (0.1468) Prec@1 80.000 (73.667) Prec@5 100.000 (97.424) +2022-11-14 13:18:38,593 Epoch: [19][330/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1437 (0.1468) Prec@1 72.000 (73.618) Prec@5 97.000 (97.412) +2022-11-14 13:18:38,920 Epoch: [19][340/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.1355 (0.1464) Prec@1 72.000 (73.571) Prec@5 98.000 (97.429) +2022-11-14 13:18:39,247 Epoch: [19][350/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1199 (0.1457) Prec@1 75.000 (73.611) Prec@5 97.000 (97.417) +2022-11-14 13:18:39,575 Epoch: [19][360/500] Time 0.032 (0.027) Data 0.001 (0.002) Loss 0.1380 (0.1455) Prec@1 78.000 (73.730) Prec@5 98.000 (97.432) +2022-11-14 13:18:39,901 Epoch: [19][370/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1452 (0.1455) Prec@1 74.000 (73.737) Prec@5 100.000 (97.500) +2022-11-14 13:18:40,224 Epoch: [19][380/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.1819 (0.1464) Prec@1 62.000 (73.436) Prec@5 96.000 (97.462) +2022-11-14 13:18:40,549 Epoch: [19][390/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1426 (0.1463) Prec@1 76.000 (73.500) Prec@5 99.000 (97.500) +2022-11-14 13:18:40,880 Epoch: [19][400/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1321 (0.1460) Prec@1 75.000 (73.537) Prec@5 100.000 (97.561) +2022-11-14 13:18:41,227 Epoch: [19][410/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1482 (0.1460) Prec@1 72.000 (73.500) Prec@5 96.000 (97.524) +2022-11-14 13:18:41,556 Epoch: [19][420/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.1427 (0.1459) Prec@1 76.000 (73.558) Prec@5 97.000 (97.512) +2022-11-14 13:18:41,904 Epoch: [19][430/500] Time 0.045 (0.027) Data 0.002 (0.002) Loss 0.1170 (0.1453) Prec@1 78.000 (73.659) Prec@5 99.000 (97.545) +2022-11-14 13:18:42,216 Epoch: [19][440/500] Time 0.032 (0.027) Data 0.001 (0.002) Loss 0.1573 (0.1456) Prec@1 74.000 (73.667) Prec@5 96.000 (97.511) +2022-11-14 13:18:42,550 Epoch: [19][450/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1510 (0.1457) Prec@1 74.000 (73.674) Prec@5 98.000 (97.522) +2022-11-14 13:18:42,883 Epoch: [19][460/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.1698 (0.1462) Prec@1 69.000 (73.574) Prec@5 98.000 (97.532) +2022-11-14 13:18:43,352 Epoch: [19][470/500] Time 0.044 (0.028) Data 0.001 (0.002) Loss 0.1413 (0.1461) Prec@1 74.000 (73.583) Prec@5 95.000 (97.479) +2022-11-14 13:18:43,824 Epoch: [19][480/500] Time 0.042 (0.028) Data 0.002 (0.002) Loss 0.1359 (0.1459) Prec@1 74.000 (73.592) Prec@5 99.000 (97.510) +2022-11-14 13:18:44,295 Epoch: [19][490/500] Time 0.052 (0.028) Data 0.002 (0.002) Loss 0.1554 (0.1461) Prec@1 74.000 (73.600) Prec@5 94.000 (97.440) +2022-11-14 13:18:44,724 Epoch: [19][499/500] Time 0.044 (0.029) Data 0.001 (0.002) Loss 0.1324 (0.1458) Prec@1 74.000 (73.608) Prec@5 99.000 (97.471) +2022-11-14 13:18:44,994 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1133 (0.1133) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:18:45,003 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1520 (0.1327) Prec@1 72.000 (77.500) Prec@5 98.000 (98.500) +2022-11-14 13:18:45,012 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1330 (0.1328) Prec@1 75.000 (76.667) Prec@5 100.000 (99.000) +2022-11-14 13:18:45,025 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1408 (0.1348) Prec@1 76.000 (76.500) Prec@5 100.000 (99.250) +2022-11-14 13:18:45,033 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1645 (0.1407) Prec@1 70.000 (75.200) Prec@5 98.000 (99.000) +2022-11-14 13:18:45,042 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.1335) Prec@1 82.000 (76.333) Prec@5 98.000 (98.833) +2022-11-14 13:18:45,051 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1300 (0.1330) Prec@1 76.000 (76.286) Prec@5 98.000 (98.714) +2022-11-14 13:18:45,064 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1492 (0.1350) Prec@1 75.000 (76.125) Prec@5 97.000 (98.500) +2022-11-14 13:18:45,074 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1345 (0.1349) Prec@1 78.000 (76.333) Prec@5 99.000 (98.556) +2022-11-14 13:18:45,083 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1202 (0.1335) Prec@1 80.000 (76.700) Prec@5 98.000 (98.500) +2022-11-14 13:18:45,093 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1309) Prec@1 81.000 (77.091) Prec@5 100.000 (98.636) +2022-11-14 13:18:45,104 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.1301) Prec@1 78.000 (77.167) Prec@5 97.000 (98.500) +2022-11-14 13:18:45,114 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1292) Prec@1 75.000 (77.000) Prec@5 99.000 (98.538) +2022-11-14 13:18:45,124 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1294) Prec@1 74.000 (76.786) Prec@5 97.000 (98.429) +2022-11-14 13:18:45,136 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.1284) Prec@1 82.000 (77.133) Prec@5 98.000 (98.400) +2022-11-14 13:18:45,145 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1854 (0.1320) Prec@1 63.000 (76.250) Prec@5 99.000 (98.438) +2022-11-14 13:18:45,156 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1309) Prec@1 84.000 (76.706) Prec@5 98.000 (98.412) +2022-11-14 13:18:45,166 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1505 (0.1320) Prec@1 79.000 (76.833) Prec@5 95.000 (98.222) +2022-11-14 13:18:45,177 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1553 (0.1332) Prec@1 74.000 (76.684) Prec@5 94.000 (98.000) +2022-11-14 13:18:45,187 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1407 (0.1336) Prec@1 76.000 (76.650) Prec@5 97.000 (97.950) +2022-11-14 13:18:45,197 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1623 (0.1349) Prec@1 70.000 (76.333) Prec@5 97.000 (97.905) +2022-11-14 13:18:45,207 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1457 (0.1354) Prec@1 72.000 (76.136) Prec@5 99.000 (97.955) +2022-11-14 13:18:45,217 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1455 (0.1359) Prec@1 76.000 (76.130) Prec@5 98.000 (97.957) +2022-11-14 13:18:45,228 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1210 (0.1352) Prec@1 77.000 (76.167) Prec@5 99.000 (98.000) +2022-11-14 13:18:45,240 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1353) Prec@1 78.000 (76.240) Prec@5 96.000 (97.920) +2022-11-14 13:18:45,251 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1800 (0.1370) Prec@1 69.000 (75.962) Prec@5 97.000 (97.885) +2022-11-14 13:18:45,263 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1537 (0.1376) Prec@1 75.000 (75.926) Prec@5 100.000 (97.963) +2022-11-14 13:18:45,274 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1369) Prec@1 80.000 (76.071) Prec@5 99.000 (98.000) +2022-11-14 13:18:45,283 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1394 (0.1370) Prec@1 74.000 (76.000) Prec@5 96.000 (97.931) +2022-11-14 13:18:45,294 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1518 (0.1375) Prec@1 74.000 (75.933) Prec@5 97.000 (97.900) +2022-11-14 13:18:45,305 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.1367) Prec@1 79.000 (76.032) Prec@5 99.000 (97.935) +2022-11-14 13:18:45,316 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1367) Prec@1 79.000 (76.125) Prec@5 100.000 (98.000) +2022-11-14 13:18:45,327 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1369) Prec@1 74.000 (76.061) Prec@5 95.000 (97.909) +2022-11-14 13:18:45,338 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1611 (0.1376) Prec@1 73.000 (75.971) Prec@5 96.000 (97.853) +2022-11-14 13:18:45,348 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1378) Prec@1 76.000 (75.971) Prec@5 96.000 (97.800) +2022-11-14 13:18:45,359 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1377 (0.1378) Prec@1 77.000 (76.000) Prec@5 99.000 (97.833) +2022-11-14 13:18:45,371 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.1376) Prec@1 77.000 (76.027) Prec@5 97.000 (97.811) +2022-11-14 13:18:45,382 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1467 (0.1378) Prec@1 77.000 (76.053) Prec@5 97.000 (97.789) +2022-11-14 13:18:45,394 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.1372) Prec@1 84.000 (76.256) Prec@5 99.000 (97.821) +2022-11-14 13:18:45,405 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.1368) Prec@1 78.000 (76.300) Prec@5 97.000 (97.800) +2022-11-14 13:18:45,417 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1475 (0.1371) Prec@1 78.000 (76.341) Prec@5 96.000 (97.756) +2022-11-14 13:18:45,430 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.1368) Prec@1 82.000 (76.476) Prec@5 97.000 (97.738) +2022-11-14 13:18:45,443 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.1361) Prec@1 82.000 (76.605) Prec@5 98.000 (97.744) +2022-11-14 13:18:45,458 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1280 (0.1360) Prec@1 79.000 (76.659) Prec@5 98.000 (97.750) +2022-11-14 13:18:45,473 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1277 (0.1358) Prec@1 76.000 (76.644) Prec@5 96.000 (97.711) +2022-11-14 13:18:45,488 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1359) Prec@1 75.000 (76.609) Prec@5 93.000 (97.609) +2022-11-14 13:18:45,503 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.1357) Prec@1 76.000 (76.596) Prec@5 97.000 (97.596) +2022-11-14 13:18:45,517 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1358 (0.1357) Prec@1 76.000 (76.583) Prec@5 98.000 (97.604) +2022-11-14 13:18:45,530 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.1352) Prec@1 80.000 (76.653) Prec@5 97.000 (97.592) +2022-11-14 13:18:45,543 Test: [49/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1650 (0.1358) Prec@1 68.000 (76.480) Prec@5 98.000 (97.600) +2022-11-14 13:18:45,557 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.1350) Prec@1 84.000 (76.627) Prec@5 99.000 (97.627) +2022-11-14 13:18:45,568 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1653 (0.1356) Prec@1 72.000 (76.538) Prec@5 95.000 (97.577) +2022-11-14 13:18:45,577 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1292 (0.1355) Prec@1 80.000 (76.604) Prec@5 99.000 (97.604) +2022-11-14 13:18:45,590 Test: [53/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1489 (0.1357) Prec@1 74.000 (76.556) Prec@5 95.000 (97.556) +2022-11-14 13:18:45,601 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1673 (0.1363) Prec@1 66.000 (76.364) Prec@5 98.000 (97.564) +2022-11-14 13:18:45,611 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1409 (0.1364) Prec@1 74.000 (76.321) Prec@5 96.000 (97.536) +2022-11-14 13:18:45,621 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1610 (0.1368) Prec@1 70.000 (76.211) Prec@5 99.000 (97.561) +2022-11-14 13:18:45,630 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1330 (0.1367) Prec@1 75.000 (76.190) Prec@5 99.000 (97.586) +2022-11-14 13:18:45,640 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1676 (0.1373) Prec@1 74.000 (76.153) Prec@5 96.000 (97.559) +2022-11-14 13:18:45,652 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1446 (0.1374) Prec@1 76.000 (76.150) Prec@5 97.000 (97.550) +2022-11-14 13:18:45,661 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1376) Prec@1 71.000 (76.066) Prec@5 98.000 (97.557) +2022-11-14 13:18:45,670 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1376) Prec@1 77.000 (76.081) Prec@5 99.000 (97.581) +2022-11-14 13:18:45,681 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1420 (0.1376) Prec@1 75.000 (76.063) Prec@5 98.000 (97.587) +2022-11-14 13:18:45,693 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.1373) Prec@1 78.000 (76.094) Prec@5 100.000 (97.625) +2022-11-14 13:18:45,704 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1757 (0.1378) Prec@1 69.000 (75.985) Prec@5 97.000 (97.615) +2022-11-14 13:18:45,714 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1288 (0.1377) Prec@1 76.000 (75.985) Prec@5 97.000 (97.606) +2022-11-14 13:18:45,725 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1315 (0.1376) Prec@1 78.000 (76.015) Prec@5 99.000 (97.627) +2022-11-14 13:18:45,735 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1477 (0.1378) Prec@1 73.000 (75.971) Prec@5 98.000 (97.632) +2022-11-14 13:18:45,747 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1316 (0.1377) Prec@1 74.000 (75.942) Prec@5 97.000 (97.623) +2022-11-14 13:18:45,760 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1665 (0.1381) Prec@1 66.000 (75.800) Prec@5 98.000 (97.629) +2022-11-14 13:18:45,771 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1381) Prec@1 79.000 (75.845) Prec@5 98.000 (97.634) +2022-11-14 13:18:45,784 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1550 (0.1383) Prec@1 70.000 (75.764) Prec@5 100.000 (97.667) +2022-11-14 13:18:45,796 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1612 (0.1386) Prec@1 71.000 (75.699) Prec@5 99.000 (97.685) +2022-11-14 13:18:45,807 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1198 (0.1384) Prec@1 78.000 (75.730) Prec@5 98.000 (97.689) +2022-11-14 13:18:45,818 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1654 (0.1388) Prec@1 66.000 (75.600) Prec@5 95.000 (97.653) +2022-11-14 13:18:45,830 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.1383) Prec@1 83.000 (75.697) Prec@5 100.000 (97.684) +2022-11-14 13:18:45,840 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1521 (0.1385) Prec@1 73.000 (75.662) Prec@5 97.000 (97.675) +2022-11-14 13:18:45,851 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1385) Prec@1 79.000 (75.705) Prec@5 96.000 (97.654) +2022-11-14 13:18:45,862 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1417 (0.1385) Prec@1 74.000 (75.684) Prec@5 99.000 (97.671) +2022-11-14 13:18:45,874 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1385) Prec@1 76.000 (75.688) Prec@5 95.000 (97.638) +2022-11-14 13:18:45,886 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1384) Prec@1 78.000 (75.716) Prec@5 97.000 (97.630) +2022-11-14 13:18:45,896 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1365 (0.1384) Prec@1 76.000 (75.720) Prec@5 100.000 (97.659) +2022-11-14 13:18:45,907 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.1383) Prec@1 75.000 (75.711) Prec@5 99.000 (97.675) +2022-11-14 13:18:45,917 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1384) Prec@1 72.000 (75.667) Prec@5 98.000 (97.679) +2022-11-14 13:18:45,928 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1418 (0.1384) Prec@1 71.000 (75.612) Prec@5 95.000 (97.647) +2022-11-14 13:18:45,938 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.1383) Prec@1 76.000 (75.616) Prec@5 99.000 (97.663) +2022-11-14 13:18:45,950 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1557 (0.1385) Prec@1 73.000 (75.586) Prec@5 98.000 (97.667) +2022-11-14 13:18:45,960 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1213 (0.1383) Prec@1 76.000 (75.591) Prec@5 98.000 (97.670) +2022-11-14 13:18:45,971 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.1381) Prec@1 76.000 (75.596) Prec@5 98.000 (97.674) +2022-11-14 13:18:45,983 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1465 (0.1382) Prec@1 74.000 (75.578) Prec@5 96.000 (97.656) +2022-11-14 13:18:45,994 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1384) Prec@1 74.000 (75.560) Prec@5 96.000 (97.637) +2022-11-14 13:18:46,005 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.1377) Prec@1 85.000 (75.663) Prec@5 100.000 (97.663) +2022-11-14 13:18:46,017 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1382 (0.1377) Prec@1 69.000 (75.591) Prec@5 97.000 (97.656) +2022-11-14 13:18:46,026 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1378) Prec@1 74.000 (75.574) Prec@5 98.000 (97.660) +2022-11-14 13:18:46,036 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1219 (0.1376) Prec@1 78.000 (75.600) Prec@5 98.000 (97.663) +2022-11-14 13:18:46,047 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1374) Prec@1 79.000 (75.635) Prec@5 99.000 (97.677) +2022-11-14 13:18:46,059 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.1371) Prec@1 82.000 (75.701) Prec@5 98.000 (97.680) +2022-11-14 13:18:46,070 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1692 (0.1375) Prec@1 70.000 (75.643) Prec@5 99.000 (97.694) +2022-11-14 13:18:46,082 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1411 (0.1375) Prec@1 78.000 (75.667) Prec@5 100.000 (97.717) +2022-11-14 13:18:46,093 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1509 (0.1376) Prec@1 75.000 (75.660) Prec@5 99.000 (97.730) +2022-11-14 13:18:46,147 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:18:46,463 Epoch: [20][0/500] Time 0.028 (0.028) Data 0.227 (0.227) Loss 0.1113 (0.1113) Prec@1 81.000 (81.000) Prec@5 97.000 (97.000) +2022-11-14 13:18:46,674 Epoch: [20][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.1217 (0.1165) Prec@1 80.000 (80.500) Prec@5 100.000 (98.500) +2022-11-14 13:18:46,887 Epoch: [20][20/500] Time 0.017 (0.019) Data 0.001 (0.012) Loss 0.1132 (0.1154) Prec@1 78.000 (79.667) Prec@5 97.000 (98.000) +2022-11-14 13:18:47,167 Epoch: [20][30/500] Time 0.026 (0.021) Data 0.001 (0.009) Loss 0.1889 (0.1338) Prec@1 67.000 (76.500) Prec@5 96.000 (97.500) +2022-11-14 13:18:47,494 Epoch: [20][40/500] Time 0.032 (0.023) Data 0.001 (0.007) Loss 0.1152 (0.1300) Prec@1 83.000 (77.800) Prec@5 99.000 (97.800) +2022-11-14 13:18:47,823 Epoch: [20][50/500] Time 0.032 (0.024) Data 0.003 (0.006) Loss 0.1432 (0.1322) Prec@1 74.000 (77.167) Prec@5 96.000 (97.500) +2022-11-14 13:18:48,143 Epoch: [20][60/500] Time 0.031 (0.025) Data 0.001 (0.005) Loss 0.1270 (0.1315) Prec@1 83.000 (78.000) Prec@5 97.000 (97.429) +2022-11-14 13:18:48,479 Epoch: [20][70/500] Time 0.039 (0.026) Data 0.002 (0.005) Loss 0.1598 (0.1350) Prec@1 68.000 (76.750) Prec@5 93.000 (96.875) +2022-11-14 13:18:48,803 Epoch: [20][80/500] Time 0.030 (0.026) Data 0.002 (0.005) Loss 0.1331 (0.1348) Prec@1 77.000 (76.778) Prec@5 97.000 (96.889) +2022-11-14 13:18:49,128 Epoch: [20][90/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.1328 (0.1346) Prec@1 77.000 (76.800) Prec@5 99.000 (97.100) +2022-11-14 13:18:49,453 Epoch: [20][100/500] Time 0.032 (0.027) Data 0.001 (0.004) Loss 0.1610 (0.1370) Prec@1 69.000 (76.091) Prec@5 97.000 (97.091) +2022-11-14 13:18:49,789 Epoch: [20][110/500] Time 0.028 (0.027) Data 0.002 (0.004) Loss 0.1180 (0.1354) Prec@1 79.000 (76.333) Prec@5 99.000 (97.250) +2022-11-14 13:18:50,108 Epoch: [20][120/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.1196 (0.1342) Prec@1 78.000 (76.462) Prec@5 97.000 (97.231) +2022-11-14 13:18:50,438 Epoch: [20][130/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1425 (0.1348) Prec@1 72.000 (76.143) Prec@5 97.000 (97.214) +2022-11-14 13:18:50,761 Epoch: [20][140/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1571 (0.1363) Prec@1 74.000 (76.000) Prec@5 97.000 (97.200) +2022-11-14 13:18:51,092 Epoch: [20][150/500] Time 0.031 (0.027) Data 0.001 (0.003) Loss 0.1233 (0.1355) Prec@1 80.000 (76.250) Prec@5 100.000 (97.375) +2022-11-14 13:18:51,428 Epoch: [20][160/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1175 (0.1344) Prec@1 77.000 (76.294) Prec@5 99.000 (97.471) +2022-11-14 13:18:51,755 Epoch: [20][170/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.1827 (0.1371) Prec@1 70.000 (75.944) Prec@5 96.000 (97.389) +2022-11-14 13:18:52,084 Epoch: [20][180/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.1447 (0.1375) Prec@1 71.000 (75.684) Prec@5 97.000 (97.368) +2022-11-14 13:18:52,452 Epoch: [20][190/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.1210 (0.1367) Prec@1 76.000 (75.700) Prec@5 98.000 (97.400) +2022-11-14 13:18:52,767 Epoch: [20][200/500] Time 0.028 (0.028) Data 0.002 (0.003) Loss 0.1201 (0.1359) Prec@1 79.000 (75.857) Prec@5 100.000 (97.524) +2022-11-14 13:18:53,124 Epoch: [20][210/500] Time 0.024 (0.028) Data 0.002 (0.003) Loss 0.1689 (0.1374) Prec@1 71.000 (75.636) Prec@5 95.000 (97.409) +2022-11-14 13:18:53,501 Epoch: [20][220/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.1616 (0.1384) Prec@1 71.000 (75.435) Prec@5 94.000 (97.261) +2022-11-14 13:18:53,977 Epoch: [20][230/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.1321 (0.1382) Prec@1 80.000 (75.625) Prec@5 98.000 (97.292) +2022-11-14 13:18:54,450 Epoch: [20][240/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1175 (0.1373) Prec@1 78.000 (75.720) Prec@5 99.000 (97.360) +2022-11-14 13:18:54,915 Epoch: [20][250/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1406 (0.1375) Prec@1 73.000 (75.615) Prec@5 95.000 (97.269) +2022-11-14 13:18:55,388 Epoch: [20][260/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.1276 (0.1371) Prec@1 74.000 (75.556) Prec@5 99.000 (97.333) +2022-11-14 13:18:55,862 Epoch: [20][270/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1589 (0.1379) Prec@1 68.000 (75.286) Prec@5 99.000 (97.393) +2022-11-14 13:18:56,334 Epoch: [20][280/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.1440 (0.1381) Prec@1 75.000 (75.276) Prec@5 96.000 (97.345) +2022-11-14 13:18:56,899 Epoch: [20][290/500] Time 0.060 (0.032) Data 0.002 (0.003) Loss 0.1635 (0.1389) Prec@1 69.000 (75.067) Prec@5 97.000 (97.333) +2022-11-14 13:18:57,612 Epoch: [20][300/500] Time 0.059 (0.033) Data 0.002 (0.003) Loss 0.1352 (0.1388) Prec@1 75.000 (75.065) Prec@5 97.000 (97.323) +2022-11-14 13:18:58,321 Epoch: [20][310/500] Time 0.066 (0.034) Data 0.002 (0.003) Loss 0.1236 (0.1383) Prec@1 78.000 (75.156) Prec@5 98.000 (97.344) +2022-11-14 13:18:58,930 Epoch: [20][320/500] Time 0.063 (0.035) Data 0.002 (0.003) Loss 0.1232 (0.1379) Prec@1 79.000 (75.273) Prec@5 100.000 (97.424) +2022-11-14 13:18:59,408 Epoch: [20][330/500] Time 0.042 (0.035) Data 0.001 (0.003) Loss 0.1372 (0.1379) Prec@1 75.000 (75.265) Prec@5 99.000 (97.471) +2022-11-14 13:18:59,882 Epoch: [20][340/500] Time 0.054 (0.035) Data 0.002 (0.002) Loss 0.1174 (0.1373) Prec@1 78.000 (75.343) Prec@5 98.000 (97.486) +2022-11-14 13:19:00,353 Epoch: [20][350/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.1402 (0.1374) Prec@1 73.000 (75.278) Prec@5 98.000 (97.500) +2022-11-14 13:19:00,852 Epoch: [20][360/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.1508 (0.1377) Prec@1 73.000 (75.216) Prec@5 96.000 (97.459) +2022-11-14 13:19:01,330 Epoch: [20][370/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1175 (0.1372) Prec@1 81.000 (75.368) Prec@5 99.000 (97.500) +2022-11-14 13:19:01,769 Epoch: [20][380/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.1714 (0.1381) Prec@1 71.000 (75.256) Prec@5 97.000 (97.487) +2022-11-14 13:19:02,097 Epoch: [20][390/500] Time 0.029 (0.036) Data 0.001 (0.002) Loss 0.1381 (0.1381) Prec@1 74.000 (75.225) Prec@5 100.000 (97.550) +2022-11-14 13:19:02,435 Epoch: [20][400/500] Time 0.031 (0.036) Data 0.002 (0.002) Loss 0.1278 (0.1378) Prec@1 77.000 (75.268) Prec@5 97.000 (97.537) +2022-11-14 13:19:02,775 Epoch: [20][410/500] Time 0.033 (0.035) Data 0.001 (0.002) Loss 0.1612 (0.1384) Prec@1 71.000 (75.167) Prec@5 95.000 (97.476) +2022-11-14 13:19:03,119 Epoch: [20][420/500] Time 0.031 (0.035) Data 0.002 (0.002) Loss 0.1611 (0.1389) Prec@1 68.000 (75.000) Prec@5 97.000 (97.465) +2022-11-14 13:19:03,456 Epoch: [20][430/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.1684 (0.1396) Prec@1 69.000 (74.864) Prec@5 100.000 (97.523) +2022-11-14 13:19:03,788 Epoch: [20][440/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.1543 (0.1399) Prec@1 73.000 (74.822) Prec@5 97.000 (97.511) +2022-11-14 13:19:04,122 Epoch: [20][450/500] Time 0.031 (0.035) Data 0.002 (0.002) Loss 0.1497 (0.1401) Prec@1 76.000 (74.848) Prec@5 99.000 (97.543) +2022-11-14 13:19:04,459 Epoch: [20][460/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.1200 (0.1397) Prec@1 77.000 (74.894) Prec@5 99.000 (97.574) +2022-11-14 13:19:04,794 Epoch: [20][470/500] Time 0.030 (0.035) Data 0.002 (0.002) Loss 0.1505 (0.1399) Prec@1 72.000 (74.833) Prec@5 94.000 (97.500) +2022-11-14 13:19:05,132 Epoch: [20][480/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.1386 (0.1399) Prec@1 74.000 (74.816) Prec@5 99.000 (97.531) +2022-11-14 13:19:05,512 Epoch: [20][490/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.1853 (0.1408) Prec@1 67.000 (74.660) Prec@5 97.000 (97.520) +2022-11-14 13:19:05,865 Epoch: [20][499/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.1198 (0.1404) Prec@1 82.000 (74.804) Prec@5 99.000 (97.549) +2022-11-14 13:19:06,158 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.1806 (0.1806) Prec@1 71.000 (71.000) Prec@5 95.000 (95.000) +2022-11-14 13:19:06,170 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1894 (0.1850) Prec@1 66.000 (68.500) Prec@5 96.000 (95.500) +2022-11-14 13:19:06,181 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1630 (0.1777) Prec@1 69.000 (68.667) Prec@5 99.000 (96.667) +2022-11-14 13:19:06,193 Test: [3/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1714 (0.1761) Prec@1 72.000 (69.500) Prec@5 99.000 (97.250) +2022-11-14 13:19:06,200 Test: [4/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.2180 (0.1845) Prec@1 58.000 (67.200) Prec@5 97.000 (97.200) +2022-11-14 13:19:06,207 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1324 (0.1758) Prec@1 78.000 (69.000) Prec@5 99.000 (97.500) +2022-11-14 13:19:06,214 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1743 (0.1756) Prec@1 67.000 (68.714) Prec@5 97.000 (97.429) +2022-11-14 13:19:06,225 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1710 (0.1750) Prec@1 67.000 (68.500) Prec@5 98.000 (97.500) +2022-11-14 13:19:06,233 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2134 (0.1793) Prec@1 60.000 (67.556) Prec@5 92.000 (96.889) +2022-11-14 13:19:06,240 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.1737) Prec@1 78.000 (68.600) Prec@5 98.000 (97.000) +2022-11-14 13:19:06,249 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1375 (0.1704) Prec@1 76.000 (69.273) Prec@5 97.000 (97.000) +2022-11-14 13:19:06,259 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1485 (0.1685) Prec@1 74.000 (69.667) Prec@5 97.000 (97.000) +2022-11-14 13:19:06,269 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1559 (0.1676) Prec@1 73.000 (69.923) Prec@5 95.000 (96.846) +2022-11-14 13:19:06,279 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1787 (0.1684) Prec@1 68.000 (69.786) Prec@5 96.000 (96.786) +2022-11-14 13:19:06,289 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1516 (0.1672) Prec@1 71.000 (69.867) Prec@5 98.000 (96.867) +2022-11-14 13:19:06,298 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2360 (0.1715) Prec@1 58.000 (69.125) Prec@5 95.000 (96.750) +2022-11-14 13:19:06,308 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1382 (0.1696) Prec@1 77.000 (69.588) Prec@5 97.000 (96.765) +2022-11-14 13:19:06,317 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1644 (0.1693) Prec@1 74.000 (69.833) Prec@5 99.000 (96.889) +2022-11-14 13:19:06,326 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1537 (0.1685) Prec@1 72.000 (69.947) Prec@5 94.000 (96.737) +2022-11-14 13:19:06,336 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2003 (0.1701) Prec@1 65.000 (69.700) Prec@5 97.000 (96.750) +2022-11-14 13:19:06,345 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2077 (0.1719) Prec@1 60.000 (69.238) Prec@5 97.000 (96.762) +2022-11-14 13:19:06,354 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2044 (0.1733) Prec@1 63.000 (68.955) Prec@5 95.000 (96.682) +2022-11-14 13:19:06,364 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1977 (0.1744) Prec@1 67.000 (68.870) Prec@5 97.000 (96.696) +2022-11-14 13:19:06,373 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1494 (0.1734) Prec@1 73.000 (69.042) Prec@5 97.000 (96.708) +2022-11-14 13:19:06,382 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1624 (0.1729) Prec@1 74.000 (69.240) Prec@5 99.000 (96.800) +2022-11-14 13:19:06,391 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2290 (0.1751) Prec@1 56.000 (68.731) Prec@5 97.000 (96.808) +2022-11-14 13:19:06,400 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1830 (0.1754) Prec@1 70.000 (68.778) Prec@5 98.000 (96.852) +2022-11-14 13:19:06,408 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1933 (0.1760) Prec@1 63.000 (68.571) Prec@5 97.000 (96.857) +2022-11-14 13:19:06,417 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1888 (0.1764) Prec@1 65.000 (68.448) Prec@5 94.000 (96.759) +2022-11-14 13:19:06,427 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1776 (0.1765) Prec@1 69.000 (68.467) Prec@5 94.000 (96.667) +2022-11-14 13:19:06,435 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1677 (0.1762) Prec@1 72.000 (68.581) Prec@5 97.000 (96.677) +2022-11-14 13:19:06,444 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1614 (0.1757) Prec@1 70.000 (68.625) Prec@5 100.000 (96.781) +2022-11-14 13:19:06,454 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1747) Prec@1 78.000 (68.909) Prec@5 95.000 (96.727) +2022-11-14 13:19:06,463 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1810 (0.1749) Prec@1 68.000 (68.882) Prec@5 97.000 (96.735) +2022-11-14 13:19:06,471 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2126 (0.1760) Prec@1 62.000 (68.686) Prec@5 94.000 (96.657) +2022-11-14 13:19:06,481 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2055 (0.1768) Prec@1 69.000 (68.694) Prec@5 93.000 (96.556) +2022-11-14 13:19:06,490 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1696 (0.1766) Prec@1 66.000 (68.622) Prec@5 97.000 (96.568) +2022-11-14 13:19:06,498 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1615 (0.1762) Prec@1 72.000 (68.711) Prec@5 97.000 (96.579) +2022-11-14 13:19:06,507 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1518 (0.1756) Prec@1 71.000 (68.769) Prec@5 100.000 (96.667) +2022-11-14 13:19:06,517 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1792 (0.1757) Prec@1 68.000 (68.750) Prec@5 97.000 (96.675) +2022-11-14 13:19:06,525 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1960 (0.1762) Prec@1 66.000 (68.683) Prec@5 94.000 (96.610) +2022-11-14 13:19:06,534 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1761) Prec@1 66.000 (68.619) Prec@5 96.000 (96.595) +2022-11-14 13:19:06,543 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1757) Prec@1 73.000 (68.721) Prec@5 94.000 (96.535) +2022-11-14 13:19:06,552 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1511 (0.1751) Prec@1 75.000 (68.864) Prec@5 96.000 (96.523) +2022-11-14 13:19:06,561 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1818 (0.1753) Prec@1 69.000 (68.867) Prec@5 96.000 (96.511) +2022-11-14 13:19:06,571 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2003 (0.1758) Prec@1 61.000 (68.696) Prec@5 96.000 (96.500) +2022-11-14 13:19:06,580 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1825 (0.1760) Prec@1 69.000 (68.702) Prec@5 100.000 (96.574) +2022-11-14 13:19:06,589 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1454 (0.1753) Prec@1 73.000 (68.792) Prec@5 98.000 (96.604) +2022-11-14 13:19:06,599 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1747) Prec@1 73.000 (68.878) Prec@5 99.000 (96.653) +2022-11-14 13:19:06,608 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2104 (0.1754) Prec@1 65.000 (68.800) Prec@5 96.000 (96.640) +2022-11-14 13:19:06,617 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1600 (0.1751) Prec@1 73.000 (68.882) Prec@5 96.000 (96.627) +2022-11-14 13:19:06,626 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2077 (0.1758) Prec@1 65.000 (68.808) Prec@5 96.000 (96.615) +2022-11-14 13:19:06,636 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1456 (0.1752) Prec@1 76.000 (68.943) Prec@5 98.000 (96.642) +2022-11-14 13:19:06,645 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1699 (0.1751) Prec@1 70.000 (68.963) Prec@5 97.000 (96.648) +2022-11-14 13:19:06,654 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1806 (0.1752) Prec@1 69.000 (68.964) Prec@5 99.000 (96.691) +2022-11-14 13:19:06,663 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1521 (0.1748) Prec@1 72.000 (69.018) Prec@5 98.000 (96.714) +2022-11-14 13:19:06,672 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1770 (0.1748) Prec@1 69.000 (69.018) Prec@5 98.000 (96.737) +2022-11-14 13:19:06,682 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1747) Prec@1 75.000 (69.121) Prec@5 96.000 (96.724) +2022-11-14 13:19:06,691 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2157 (0.1754) Prec@1 61.000 (68.983) Prec@5 97.000 (96.729) +2022-11-14 13:19:06,700 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1569 (0.1751) Prec@1 74.000 (69.067) Prec@5 94.000 (96.683) +2022-11-14 13:19:06,709 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2213 (0.1758) Prec@1 61.000 (68.934) Prec@5 97.000 (96.689) +2022-11-14 13:19:06,718 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1700 (0.1757) Prec@1 70.000 (68.952) Prec@5 98.000 (96.710) +2022-11-14 13:19:06,727 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1743 (0.1757) Prec@1 68.000 (68.937) Prec@5 99.000 (96.746) +2022-11-14 13:19:06,736 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1654 (0.1756) Prec@1 70.000 (68.953) Prec@5 97.000 (96.750) +2022-11-14 13:19:06,745 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1990 (0.1759) Prec@1 66.000 (68.908) Prec@5 95.000 (96.723) +2022-11-14 13:19:06,754 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1727 (0.1759) Prec@1 66.000 (68.864) Prec@5 99.000 (96.758) +2022-11-14 13:19:06,763 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1718 (0.1758) Prec@1 67.000 (68.836) Prec@5 99.000 (96.791) +2022-11-14 13:19:06,773 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2141 (0.1764) Prec@1 60.000 (68.706) Prec@5 96.000 (96.779) +2022-11-14 13:19:06,781 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2060 (0.1768) Prec@1 64.000 (68.638) Prec@5 96.000 (96.768) +2022-11-14 13:19:06,789 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1911 (0.1770) Prec@1 67.000 (68.614) Prec@5 95.000 (96.743) +2022-11-14 13:19:06,797 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1983 (0.1773) Prec@1 63.000 (68.535) Prec@5 98.000 (96.761) +2022-11-14 13:19:06,804 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1753 (0.1773) Prec@1 71.000 (68.569) Prec@5 100.000 (96.806) +2022-11-14 13:19:06,814 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1826 (0.1774) Prec@1 71.000 (68.603) Prec@5 99.000 (96.836) +2022-11-14 13:19:06,823 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1786 (0.1774) Prec@1 71.000 (68.635) Prec@5 96.000 (96.824) +2022-11-14 13:19:06,832 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1971 (0.1776) Prec@1 63.000 (68.560) Prec@5 96.000 (96.813) +2022-11-14 13:19:06,842 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1651 (0.1775) Prec@1 73.000 (68.618) Prec@5 93.000 (96.763) +2022-11-14 13:19:06,851 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1926 (0.1777) Prec@1 69.000 (68.623) Prec@5 96.000 (96.753) +2022-11-14 13:19:06,860 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1498 (0.1773) Prec@1 76.000 (68.718) Prec@5 95.000 (96.731) +2022-11-14 13:19:06,872 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2001 (0.1776) Prec@1 69.000 (68.722) Prec@5 97.000 (96.734) +2022-11-14 13:19:06,883 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1470 (0.1772) Prec@1 74.000 (68.787) Prec@5 96.000 (96.725) +2022-11-14 13:19:06,893 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1821 (0.1773) Prec@1 69.000 (68.790) Prec@5 93.000 (96.679) +2022-11-14 13:19:06,901 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1786 (0.1773) Prec@1 72.000 (68.829) Prec@5 97.000 (96.683) +2022-11-14 13:19:06,914 Test: [82/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1729 (0.1772) Prec@1 67.000 (68.807) Prec@5 98.000 (96.699) +2022-11-14 13:19:06,925 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2133 (0.1777) Prec@1 60.000 (68.702) Prec@5 98.000 (96.714) +2022-11-14 13:19:06,934 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1712 (0.1776) Prec@1 73.000 (68.753) Prec@5 94.000 (96.682) +2022-11-14 13:19:06,943 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1523 (0.1773) Prec@1 73.000 (68.802) Prec@5 96.000 (96.674) +2022-11-14 13:19:06,955 Test: [86/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.1774) Prec@1 70.000 (68.816) Prec@5 98.000 (96.690) +2022-11-14 13:19:06,966 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1601 (0.1772) Prec@1 71.000 (68.841) Prec@5 96.000 (96.682) +2022-11-14 13:19:06,976 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1774 (0.1772) Prec@1 65.000 (68.798) Prec@5 95.000 (96.663) +2022-11-14 13:19:06,985 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1772) Prec@1 71.000 (68.822) Prec@5 96.000 (96.656) +2022-11-14 13:19:06,997 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1752 (0.1772) Prec@1 70.000 (68.835) Prec@5 97.000 (96.659) +2022-11-14 13:19:07,009 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.1765) Prec@1 81.000 (68.967) Prec@5 98.000 (96.674) +2022-11-14 13:19:07,018 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1735 (0.1765) Prec@1 66.000 (68.935) Prec@5 94.000 (96.645) +2022-11-14 13:19:07,026 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.1765) Prec@1 69.000 (68.936) Prec@5 95.000 (96.628) +2022-11-14 13:19:07,036 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1687 (0.1764) Prec@1 70.000 (68.947) Prec@5 98.000 (96.642) +2022-11-14 13:19:07,046 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1351 (0.1759) Prec@1 77.000 (69.031) Prec@5 98.000 (96.656) +2022-11-14 13:19:07,054 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1287 (0.1755) Prec@1 72.000 (69.062) Prec@5 100.000 (96.691) +2022-11-14 13:19:07,065 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2136 (0.1758) Prec@1 63.000 (69.000) Prec@5 96.000 (96.684) +2022-11-14 13:19:07,073 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1894 (0.1760) Prec@1 64.000 (68.949) Prec@5 97.000 (96.687) +2022-11-14 13:19:07,082 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1989 (0.1762) Prec@1 68.000 (68.940) Prec@5 95.000 (96.670) +2022-11-14 13:19:07,134 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:19:07,424 Epoch: [21][0/500] Time 0.022 (0.022) Data 0.211 (0.211) Loss 0.1379 (0.1379) Prec@1 74.000 (74.000) Prec@5 98.000 (98.000) +2022-11-14 13:19:07,630 Epoch: [21][10/500] Time 0.018 (0.018) Data 0.001 (0.021) Loss 0.1192 (0.1286) Prec@1 80.000 (77.000) Prec@5 98.000 (98.000) +2022-11-14 13:19:07,824 Epoch: [21][20/500] Time 0.018 (0.018) Data 0.002 (0.012) Loss 0.1670 (0.1414) Prec@1 70.000 (74.667) Prec@5 98.000 (98.000) +2022-11-14 13:19:08,077 Epoch: [21][30/500] Time 0.025 (0.019) Data 0.002 (0.008) Loss 0.1157 (0.1350) Prec@1 80.000 (76.000) Prec@5 97.000 (97.750) +2022-11-14 13:19:08,361 Epoch: [21][40/500] Time 0.025 (0.021) Data 0.001 (0.007) Loss 0.1252 (0.1330) Prec@1 76.000 (76.000) Prec@5 99.000 (98.000) +2022-11-14 13:19:08,683 Epoch: [21][50/500] Time 0.022 (0.022) Data 0.002 (0.006) Loss 0.1277 (0.1321) Prec@1 77.000 (76.167) Prec@5 98.000 (98.000) +2022-11-14 13:19:08,956 Epoch: [21][60/500] Time 0.026 (0.023) Data 0.002 (0.005) Loss 0.1015 (0.1278) Prec@1 83.000 (77.143) Prec@5 99.000 (98.143) +2022-11-14 13:19:09,239 Epoch: [21][70/500] Time 0.026 (0.023) Data 0.002 (0.005) Loss 0.1141 (0.1261) Prec@1 81.000 (77.625) Prec@5 98.000 (98.125) +2022-11-14 13:19:09,526 Epoch: [21][80/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.1187 (0.1252) Prec@1 78.000 (77.667) Prec@5 95.000 (97.778) +2022-11-14 13:19:09,806 Epoch: [21][90/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.1652 (0.1292) Prec@1 75.000 (77.400) Prec@5 96.000 (97.600) +2022-11-14 13:19:10,091 Epoch: [21][100/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.1877 (0.1346) Prec@1 67.000 (76.455) Prec@5 96.000 (97.455) +2022-11-14 13:19:10,373 Epoch: [21][110/500] Time 0.026 (0.024) Data 0.001 (0.004) Loss 0.1254 (0.1338) Prec@1 77.000 (76.500) Prec@5 100.000 (97.667) +2022-11-14 13:19:10,662 Epoch: [21][120/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.1282 (0.1334) Prec@1 76.000 (76.462) Prec@5 99.000 (97.769) +2022-11-14 13:19:10,948 Epoch: [21][130/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0776 (0.1294) Prec@1 86.000 (77.143) Prec@5 98.000 (97.786) +2022-11-14 13:19:11,236 Epoch: [21][140/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.1507 (0.1308) Prec@1 71.000 (76.733) Prec@5 97.000 (97.733) +2022-11-14 13:19:11,560 Epoch: [21][150/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.1426 (0.1315) Prec@1 73.000 (76.500) Prec@5 98.000 (97.750) +2022-11-14 13:19:12,042 Epoch: [21][160/500] Time 0.044 (0.025) Data 0.002 (0.003) Loss 0.1315 (0.1315) Prec@1 76.000 (76.471) Prec@5 100.000 (97.882) +2022-11-14 13:19:12,511 Epoch: [21][170/500] Time 0.044 (0.026) Data 0.002 (0.003) Loss 0.1420 (0.1321) Prec@1 72.000 (76.222) Prec@5 96.000 (97.778) +2022-11-14 13:19:12,997 Epoch: [21][180/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.1242 (0.1317) Prec@1 78.000 (76.316) Prec@5 97.000 (97.737) +2022-11-14 13:19:13,471 Epoch: [21][190/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.1721 (0.1337) Prec@1 70.000 (76.000) Prec@5 97.000 (97.700) +2022-11-14 13:19:13,941 Epoch: [21][200/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1779 (0.1358) Prec@1 69.000 (75.667) Prec@5 98.000 (97.714) +2022-11-14 13:19:14,411 Epoch: [21][210/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1275 (0.1354) Prec@1 77.000 (75.727) Prec@5 96.000 (97.636) +2022-11-14 13:19:14,903 Epoch: [21][220/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1117 (0.1344) Prec@1 82.000 (76.000) Prec@5 97.000 (97.609) +2022-11-14 13:19:15,384 Epoch: [21][230/500] Time 0.054 (0.031) Data 0.002 (0.003) Loss 0.1656 (0.1357) Prec@1 67.000 (75.625) Prec@5 97.000 (97.583) +2022-11-14 13:19:15,858 Epoch: [21][240/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.1326 (0.1356) Prec@1 76.000 (75.640) Prec@5 97.000 (97.560) +2022-11-14 13:19:16,377 Epoch: [21][250/500] Time 0.064 (0.032) Data 0.002 (0.003) Loss 0.1449 (0.1359) Prec@1 74.000 (75.577) Prec@5 96.000 (97.500) +2022-11-14 13:19:17,060 Epoch: [21][260/500] Time 0.080 (0.033) Data 0.002 (0.003) Loss 0.1371 (0.1360) Prec@1 74.000 (75.519) Prec@5 99.000 (97.556) +2022-11-14 13:19:17,585 Epoch: [21][270/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.1439 (0.1363) Prec@1 77.000 (75.571) Prec@5 99.000 (97.607) +2022-11-14 13:19:17,958 Epoch: [21][280/500] Time 0.022 (0.033) Data 0.002 (0.003) Loss 0.1388 (0.1364) Prec@1 77.000 (75.621) Prec@5 97.000 (97.586) +2022-11-14 13:19:18,288 Epoch: [21][290/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.1420 (0.1365) Prec@1 74.000 (75.567) Prec@5 98.000 (97.600) +2022-11-14 13:19:18,605 Epoch: [21][300/500] Time 0.031 (0.033) Data 0.002 (0.003) Loss 0.1039 (0.1355) Prec@1 82.000 (75.774) Prec@5 98.000 (97.613) +2022-11-14 13:19:18,966 Epoch: [21][310/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1709 (0.1366) Prec@1 73.000 (75.688) Prec@5 95.000 (97.531) +2022-11-14 13:19:19,293 Epoch: [21][320/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.1145 (0.1359) Prec@1 80.000 (75.818) Prec@5 98.000 (97.545) +2022-11-14 13:19:19,665 Epoch: [21][330/500] Time 0.023 (0.033) Data 0.002 (0.003) Loss 0.1275 (0.1357) Prec@1 76.000 (75.824) Prec@5 97.000 (97.529) +2022-11-14 13:19:20,027 Epoch: [21][340/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.1175 (0.1352) Prec@1 79.000 (75.914) Prec@5 98.000 (97.543) +2022-11-14 13:19:20,345 Epoch: [21][350/500] Time 0.030 (0.033) Data 0.001 (0.002) Loss 0.1563 (0.1357) Prec@1 73.000 (75.833) Prec@5 99.000 (97.583) +2022-11-14 13:19:20,746 Epoch: [21][360/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.1447 (0.1360) Prec@1 71.000 (75.703) Prec@5 98.000 (97.595) +2022-11-14 13:19:21,114 Epoch: [21][370/500] Time 0.022 (0.033) Data 0.002 (0.002) Loss 0.1519 (0.1364) Prec@1 71.000 (75.579) Prec@5 96.000 (97.553) +2022-11-14 13:19:21,437 Epoch: [21][380/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.1434 (0.1366) Prec@1 75.000 (75.564) Prec@5 98.000 (97.564) +2022-11-14 13:19:21,762 Epoch: [21][390/500] Time 0.033 (0.033) Data 0.002 (0.002) Loss 0.1104 (0.1359) Prec@1 78.000 (75.625) Prec@5 98.000 (97.575) +2022-11-14 13:19:22,092 Epoch: [21][400/500] Time 0.029 (0.033) Data 0.002 (0.002) Loss 0.1378 (0.1360) Prec@1 78.000 (75.683) Prec@5 100.000 (97.634) +2022-11-14 13:19:22,425 Epoch: [21][410/500] Time 0.031 (0.033) Data 0.002 (0.002) Loss 0.1242 (0.1357) Prec@1 79.000 (75.762) Prec@5 99.000 (97.667) +2022-11-14 13:19:22,760 Epoch: [21][420/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.1147 (0.1352) Prec@1 81.000 (75.884) Prec@5 98.000 (97.674) +2022-11-14 13:19:23,084 Epoch: [21][430/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.1604 (0.1358) Prec@1 68.000 (75.705) Prec@5 98.000 (97.682) +2022-11-14 13:19:23,410 Epoch: [21][440/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.1329 (0.1357) Prec@1 76.000 (75.711) Prec@5 99.000 (97.711) +2022-11-14 13:19:23,737 Epoch: [21][450/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.1606 (0.1363) Prec@1 76.000 (75.717) Prec@5 97.000 (97.696) +2022-11-14 13:19:24,068 Epoch: [21][460/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.1604 (0.1368) Prec@1 74.000 (75.681) Prec@5 98.000 (97.702) +2022-11-14 13:19:24,396 Epoch: [21][470/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.1484 (0.1370) Prec@1 74.000 (75.646) Prec@5 95.000 (97.646) +2022-11-14 13:19:24,728 Epoch: [21][480/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.1157 (0.1366) Prec@1 83.000 (75.796) Prec@5 97.000 (97.633) +2022-11-14 13:19:25,081 Epoch: [21][490/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.1513 (0.1369) Prec@1 71.000 (75.700) Prec@5 98.000 (97.640) +2022-11-14 13:19:25,371 Epoch: [21][499/500] Time 0.031 (0.032) Data 0.001 (0.002) Loss 0.1487 (0.1371) Prec@1 74.000 (75.667) Prec@5 98.000 (97.647) +2022-11-14 13:19:25,665 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.1238 (0.1238) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:19:25,677 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1524 (0.1381) Prec@1 70.000 (74.500) Prec@5 99.000 (98.500) +2022-11-14 13:19:25,687 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1703 (0.1488) Prec@1 74.000 (74.333) Prec@5 96.000 (97.667) +2022-11-14 13:19:25,703 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1450 (0.1479) Prec@1 73.000 (74.000) Prec@5 99.000 (98.000) +2022-11-14 13:19:25,714 Test: [4/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1697 (0.1523) Prec@1 67.000 (72.600) Prec@5 98.000 (98.000) +2022-11-14 13:19:25,723 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0993 (0.1434) Prec@1 85.000 (74.667) Prec@5 98.000 (98.000) +2022-11-14 13:19:25,732 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1107 (0.1387) Prec@1 83.000 (75.857) Prec@5 99.000 (98.143) +2022-11-14 13:19:25,746 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1668 (0.1422) Prec@1 70.000 (75.125) Prec@5 97.000 (98.000) +2022-11-14 13:19:25,755 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1623 (0.1445) Prec@1 69.000 (74.444) Prec@5 98.000 (98.000) +2022-11-14 13:19:25,764 Test: [9/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1158 (0.1416) Prec@1 78.000 (74.800) Prec@5 96.000 (97.800) +2022-11-14 13:19:25,772 Test: [10/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1288 (0.1404) Prec@1 76.000 (74.909) Prec@5 97.000 (97.727) +2022-11-14 13:19:25,783 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1591 (0.1420) Prec@1 71.000 (74.583) Prec@5 96.000 (97.583) +2022-11-14 13:19:25,795 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1402 (0.1419) Prec@1 73.000 (74.462) Prec@5 99.000 (97.692) +2022-11-14 13:19:25,803 Test: [13/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1240 (0.1406) Prec@1 76.000 (74.571) Prec@5 99.000 (97.786) +2022-11-14 13:19:25,812 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1332 (0.1401) Prec@1 74.000 (74.533) Prec@5 99.000 (97.867) +2022-11-14 13:19:25,823 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1909 (0.1433) Prec@1 63.000 (73.812) Prec@5 96.000 (97.750) +2022-11-14 13:19:25,834 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.1413) Prec@1 81.000 (74.235) Prec@5 98.000 (97.765) +2022-11-14 13:19:25,846 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1403 (0.1413) Prec@1 73.000 (74.167) Prec@5 98.000 (97.778) +2022-11-14 13:19:25,858 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1227 (0.1403) Prec@1 77.000 (74.316) Prec@5 95.000 (97.632) +2022-11-14 13:19:25,867 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1853 (0.1425) Prec@1 65.000 (73.850) Prec@5 94.000 (97.450) +2022-11-14 13:19:25,879 Test: [20/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1600 (0.1434) Prec@1 69.000 (73.619) Prec@5 97.000 (97.429) +2022-11-14 13:19:25,891 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1440 (0.1434) Prec@1 75.000 (73.682) Prec@5 98.000 (97.455) +2022-11-14 13:19:25,902 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1571 (0.1440) Prec@1 70.000 (73.522) Prec@5 95.000 (97.348) +2022-11-14 13:19:25,912 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1359 (0.1436) Prec@1 78.000 (73.708) Prec@5 96.000 (97.292) +2022-11-14 13:19:25,925 Test: [24/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1555 (0.1441) Prec@1 74.000 (73.720) Prec@5 97.000 (97.280) +2022-11-14 13:19:25,936 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1659 (0.1450) Prec@1 71.000 (73.615) Prec@5 97.000 (97.269) +2022-11-14 13:19:25,947 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1504 (0.1452) Prec@1 73.000 (73.593) Prec@5 100.000 (97.370) +2022-11-14 13:19:25,958 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1479 (0.1453) Prec@1 72.000 (73.536) Prec@5 96.000 (97.321) +2022-11-14 13:19:25,970 Test: [28/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1389 (0.1450) Prec@1 76.000 (73.621) Prec@5 95.000 (97.241) +2022-11-14 13:19:25,982 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1262 (0.1444) Prec@1 79.000 (73.800) Prec@5 97.000 (97.233) +2022-11-14 13:19:25,991 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1490 (0.1446) Prec@1 72.000 (73.742) Prec@5 96.000 (97.194) +2022-11-14 13:19:26,002 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1382 (0.1444) Prec@1 77.000 (73.844) Prec@5 98.000 (97.219) +2022-11-14 13:19:26,014 Test: [32/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1497 (0.1445) Prec@1 71.000 (73.758) Prec@5 95.000 (97.152) +2022-11-14 13:19:26,025 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1700 (0.1453) Prec@1 66.000 (73.529) Prec@5 92.000 (97.000) +2022-11-14 13:19:26,033 Test: [34/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1556 (0.1456) Prec@1 72.000 (73.486) Prec@5 97.000 (97.000) +2022-11-14 13:19:26,042 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1624 (0.1460) Prec@1 73.000 (73.472) Prec@5 97.000 (97.000) +2022-11-14 13:19:26,054 Test: [36/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1443 (0.1460) Prec@1 72.000 (73.432) Prec@5 98.000 (97.027) +2022-11-14 13:19:26,065 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1458 (0.1460) Prec@1 72.000 (73.395) Prec@5 98.000 (97.053) +2022-11-14 13:19:26,075 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.1450) Prec@1 80.000 (73.564) Prec@5 100.000 (97.128) +2022-11-14 13:19:26,085 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1163 (0.1443) Prec@1 80.000 (73.725) Prec@5 98.000 (97.150) +2022-11-14 13:19:26,097 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1468 (0.1443) Prec@1 72.000 (73.683) Prec@5 96.000 (97.122) +2022-11-14 13:19:26,107 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1519 (0.1445) Prec@1 72.000 (73.643) Prec@5 95.000 (97.071) +2022-11-14 13:19:26,117 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.1438) Prec@1 85.000 (73.907) Prec@5 95.000 (97.023) +2022-11-14 13:19:26,128 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1492 (0.1439) Prec@1 75.000 (73.932) Prec@5 96.000 (97.000) +2022-11-14 13:19:26,139 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1413 (0.1438) Prec@1 78.000 (74.022) Prec@5 96.000 (96.978) +2022-11-14 13:19:26,149 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1407 (0.1438) Prec@1 75.000 (74.043) Prec@5 97.000 (96.978) +2022-11-14 13:19:26,158 Test: [46/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1466 (0.1438) Prec@1 74.000 (74.043) Prec@5 99.000 (97.021) +2022-11-14 13:19:26,166 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1366 (0.1437) Prec@1 75.000 (74.062) Prec@5 96.000 (97.000) +2022-11-14 13:19:26,176 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1187 (0.1432) Prec@1 80.000 (74.184) Prec@5 98.000 (97.020) +2022-11-14 13:19:26,185 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1645 (0.1436) Prec@1 71.000 (74.120) Prec@5 98.000 (97.040) +2022-11-14 13:19:26,195 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1164 (0.1430) Prec@1 80.000 (74.235) Prec@5 98.000 (97.059) +2022-11-14 13:19:26,206 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1616 (0.1434) Prec@1 69.000 (74.135) Prec@5 96.000 (97.038) +2022-11-14 13:19:26,217 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1296 (0.1431) Prec@1 79.000 (74.226) Prec@5 99.000 (97.075) +2022-11-14 13:19:26,228 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1543 (0.1433) Prec@1 72.000 (74.185) Prec@5 98.000 (97.093) +2022-11-14 13:19:26,239 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1627 (0.1437) Prec@1 67.000 (74.055) Prec@5 97.000 (97.091) +2022-11-14 13:19:26,249 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1452 (0.1437) Prec@1 75.000 (74.071) Prec@5 97.000 (97.089) +2022-11-14 13:19:26,260 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1257 (0.1434) Prec@1 78.000 (74.140) Prec@5 99.000 (97.123) +2022-11-14 13:19:26,271 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1487 (0.1435) Prec@1 76.000 (74.172) Prec@5 98.000 (97.138) +2022-11-14 13:19:26,283 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1889 (0.1443) Prec@1 66.000 (74.034) Prec@5 97.000 (97.136) +2022-11-14 13:19:26,293 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1412 (0.1442) Prec@1 74.000 (74.033) Prec@5 96.000 (97.117) +2022-11-14 13:19:26,304 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1735 (0.1447) Prec@1 68.000 (73.934) Prec@5 99.000 (97.148) +2022-11-14 13:19:26,316 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1459 (0.1447) Prec@1 76.000 (73.968) Prec@5 95.000 (97.113) +2022-11-14 13:19:26,326 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1198 (0.1443) Prec@1 77.000 (74.016) Prec@5 99.000 (97.143) +2022-11-14 13:19:26,339 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1477 (0.1444) Prec@1 74.000 (74.016) Prec@5 98.000 (97.156) +2022-11-14 13:19:26,350 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1877 (0.1450) Prec@1 67.000 (73.908) Prec@5 97.000 (97.154) +2022-11-14 13:19:26,360 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1532 (0.1452) Prec@1 69.000 (73.833) Prec@5 99.000 (97.182) +2022-11-14 13:19:26,371 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1426 (0.1451) Prec@1 73.000 (73.821) Prec@5 99.000 (97.209) +2022-11-14 13:19:26,381 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1528 (0.1452) Prec@1 75.000 (73.838) Prec@5 96.000 (97.191) +2022-11-14 13:19:26,392 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1339 (0.1451) Prec@1 74.000 (73.841) Prec@5 97.000 (97.188) +2022-11-14 13:19:26,402 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1625 (0.1453) Prec@1 70.000 (73.786) Prec@5 97.000 (97.186) +2022-11-14 13:19:26,413 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1595 (0.1455) Prec@1 69.000 (73.718) Prec@5 98.000 (97.197) +2022-11-14 13:19:26,423 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1294 (0.1453) Prec@1 80.000 (73.806) Prec@5 98.000 (97.208) +2022-11-14 13:19:26,434 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.1449) Prec@1 81.000 (73.904) Prec@5 98.000 (97.219) +2022-11-14 13:19:26,444 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.1445) Prec@1 81.000 (74.000) Prec@5 98.000 (97.230) +2022-11-14 13:19:26,455 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1657 (0.1447) Prec@1 71.000 (73.960) Prec@5 96.000 (97.213) +2022-11-14 13:19:26,465 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1470 (0.1448) Prec@1 71.000 (73.921) Prec@5 99.000 (97.237) +2022-11-14 13:19:26,476 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1575 (0.1449) Prec@1 70.000 (73.870) Prec@5 97.000 (97.234) +2022-11-14 13:19:26,485 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.1445) Prec@1 83.000 (73.987) Prec@5 97.000 (97.231) +2022-11-14 13:19:26,496 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1402 (0.1444) Prec@1 80.000 (74.063) Prec@5 98.000 (97.241) +2022-11-14 13:19:26,506 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1236 (0.1441) Prec@1 76.000 (74.088) Prec@5 99.000 (97.263) +2022-11-14 13:19:26,517 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1334 (0.1440) Prec@1 77.000 (74.123) Prec@5 99.000 (97.284) +2022-11-14 13:19:26,527 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1439 (0.1440) Prec@1 76.000 (74.146) Prec@5 97.000 (97.280) +2022-11-14 13:19:26,539 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1409 (0.1440) Prec@1 73.000 (74.133) Prec@5 99.000 (97.301) +2022-11-14 13:19:26,550 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1807 (0.1444) Prec@1 67.000 (74.048) Prec@5 97.000 (97.298) +2022-11-14 13:19:26,562 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1567 (0.1445) Prec@1 73.000 (74.035) Prec@5 98.000 (97.306) +2022-11-14 13:19:26,573 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1438 (0.1445) Prec@1 75.000 (74.047) Prec@5 98.000 (97.314) +2022-11-14 13:19:26,583 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1307 (0.1444) Prec@1 79.000 (74.103) Prec@5 97.000 (97.310) +2022-11-14 13:19:26,594 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1484 (0.1444) Prec@1 72.000 (74.080) Prec@5 100.000 (97.341) +2022-11-14 13:19:26,603 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1582 (0.1446) Prec@1 73.000 (74.067) Prec@5 95.000 (97.315) +2022-11-14 13:19:26,615 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1496 (0.1446) Prec@1 75.000 (74.078) Prec@5 98.000 (97.322) +2022-11-14 13:19:26,624 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1500 (0.1447) Prec@1 72.000 (74.055) Prec@5 99.000 (97.341) +2022-11-14 13:19:26,635 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.1441) Prec@1 86.000 (74.185) Prec@5 100.000 (97.370) +2022-11-14 13:19:26,644 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1468 (0.1442) Prec@1 76.000 (74.204) Prec@5 97.000 (97.366) +2022-11-14 13:19:26,654 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1441 (0.1442) Prec@1 73.000 (74.191) Prec@5 98.000 (97.372) +2022-11-14 13:19:26,666 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1478 (0.1442) Prec@1 72.000 (74.168) Prec@5 98.000 (97.379) +2022-11-14 13:19:26,676 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1238 (0.1440) Prec@1 77.000 (74.198) Prec@5 96.000 (97.365) +2022-11-14 13:19:26,684 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1437) Prec@1 80.000 (74.258) Prec@5 99.000 (97.381) +2022-11-14 13:19:26,694 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1643 (0.1439) Prec@1 71.000 (74.224) Prec@5 99.000 (97.398) +2022-11-14 13:19:26,704 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1534 (0.1440) Prec@1 72.000 (74.202) Prec@5 98.000 (97.404) +2022-11-14 13:19:26,713 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1310 (0.1439) Prec@1 80.000 (74.260) Prec@5 95.000 (97.380) +2022-11-14 13:19:26,772 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:19:27,069 Epoch: [22][0/500] Time 0.023 (0.023) Data 0.213 (0.213) Loss 0.1421 (0.1421) Prec@1 73.000 (73.000) Prec@5 97.000 (97.000) +2022-11-14 13:19:27,285 Epoch: [22][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.1272 (0.1347) Prec@1 76.000 (74.500) Prec@5 99.000 (98.000) +2022-11-14 13:19:27,508 Epoch: [22][20/500] Time 0.020 (0.020) Data 0.001 (0.012) Loss 0.1635 (0.1443) Prec@1 72.000 (73.667) Prec@5 93.000 (96.333) +2022-11-14 13:19:27,800 Epoch: [22][30/500] Time 0.028 (0.022) Data 0.001 (0.009) Loss 0.1369 (0.1424) Prec@1 74.000 (73.750) Prec@5 97.000 (96.500) +2022-11-14 13:19:28,108 Epoch: [22][40/500] Time 0.029 (0.023) Data 0.002 (0.007) Loss 0.1093 (0.1358) Prec@1 81.000 (75.200) Prec@5 98.000 (96.800) +2022-11-14 13:19:28,418 Epoch: [22][50/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.1454 (0.1374) Prec@1 71.000 (74.500) Prec@5 97.000 (96.833) +2022-11-14 13:19:28,730 Epoch: [22][60/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.1237 (0.1354) Prec@1 77.000 (74.857) Prec@5 98.000 (97.000) +2022-11-14 13:19:29,039 Epoch: [22][70/500] Time 0.029 (0.025) Data 0.001 (0.005) Loss 0.1604 (0.1386) Prec@1 72.000 (74.500) Prec@5 96.000 (96.875) +2022-11-14 13:19:29,349 Epoch: [22][80/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.1446 (0.1392) Prec@1 75.000 (74.556) Prec@5 97.000 (96.889) +2022-11-14 13:19:29,664 Epoch: [22][90/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.1119 (0.1365) Prec@1 82.000 (75.300) Prec@5 97.000 (96.900) +2022-11-14 13:19:29,972 Epoch: [22][100/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.0904 (0.1323) Prec@1 84.000 (76.091) Prec@5 100.000 (97.182) +2022-11-14 13:19:30,281 Epoch: [22][110/500] Time 0.028 (0.026) Data 0.001 (0.004) Loss 0.1092 (0.1304) Prec@1 83.000 (76.667) Prec@5 97.000 (97.167) +2022-11-14 13:19:30,595 Epoch: [22][120/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1518 (0.1320) Prec@1 73.000 (76.385) Prec@5 97.000 (97.154) +2022-11-14 13:19:30,912 Epoch: [22][130/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1321 (0.1320) Prec@1 81.000 (76.714) Prec@5 94.000 (96.929) +2022-11-14 13:19:31,228 Epoch: [22][140/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1189 (0.1312) Prec@1 80.000 (76.933) Prec@5 99.000 (97.067) +2022-11-14 13:19:31,541 Epoch: [22][150/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.1069 (0.1296) Prec@1 83.000 (77.312) Prec@5 100.000 (97.250) +2022-11-14 13:19:31,857 Epoch: [22][160/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.1746 (0.1323) Prec@1 70.000 (76.882) Prec@5 96.000 (97.176) +2022-11-14 13:19:32,169 Epoch: [22][170/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1531 (0.1335) Prec@1 71.000 (76.556) Prec@5 97.000 (97.167) +2022-11-14 13:19:32,502 Epoch: [22][180/500] Time 0.038 (0.027) Data 0.001 (0.003) Loss 0.0980 (0.1316) Prec@1 83.000 (76.895) Prec@5 99.000 (97.263) +2022-11-14 13:19:32,827 Epoch: [22][190/500] Time 0.028 (0.027) Data 0.001 (0.003) Loss 0.0902 (0.1295) Prec@1 84.000 (77.250) Prec@5 97.000 (97.250) +2022-11-14 13:19:33,311 Epoch: [22][200/500] Time 0.040 (0.028) Data 0.002 (0.003) Loss 0.1806 (0.1319) Prec@1 66.000 (76.714) Prec@5 98.000 (97.286) +2022-11-14 13:19:33,896 Epoch: [22][210/500] Time 0.055 (0.029) Data 0.002 (0.003) Loss 0.1335 (0.1320) Prec@1 77.000 (76.727) Prec@5 98.000 (97.318) +2022-11-14 13:19:34,448 Epoch: [22][220/500] Time 0.046 (0.030) Data 0.002 (0.003) Loss 0.1576 (0.1331) Prec@1 70.000 (76.435) Prec@5 98.000 (97.348) +2022-11-14 13:19:34,996 Epoch: [22][230/500] Time 0.058 (0.031) Data 0.002 (0.003) Loss 0.1443 (0.1336) Prec@1 75.000 (76.375) Prec@5 96.000 (97.292) +2022-11-14 13:19:35,592 Epoch: [22][240/500] Time 0.061 (0.032) Data 0.003 (0.003) Loss 0.1461 (0.1341) Prec@1 79.000 (76.480) Prec@5 95.000 (97.200) +2022-11-14 13:19:36,101 Epoch: [22][250/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.1017 (0.1329) Prec@1 86.000 (76.846) Prec@5 98.000 (97.231) +2022-11-14 13:19:36,552 Epoch: [22][260/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.1715 (0.1343) Prec@1 70.000 (76.593) Prec@5 97.000 (97.222) +2022-11-14 13:19:37,033 Epoch: [22][270/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.1411 (0.1345) Prec@1 73.000 (76.464) Prec@5 100.000 (97.321) +2022-11-14 13:19:37,497 Epoch: [22][280/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.1548 (0.1352) Prec@1 73.000 (76.345) Prec@5 99.000 (97.379) +2022-11-14 13:19:37,948 Epoch: [22][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1459 (0.1356) Prec@1 70.000 (76.133) Prec@5 95.000 (97.300) +2022-11-14 13:19:38,406 Epoch: [22][300/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.1379 (0.1357) Prec@1 79.000 (76.226) Prec@5 97.000 (97.290) +2022-11-14 13:19:38,847 Epoch: [22][310/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.1270 (0.1354) Prec@1 78.000 (76.281) Prec@5 98.000 (97.312) +2022-11-14 13:19:39,300 Epoch: [22][320/500] Time 0.044 (0.034) Data 0.001 (0.002) Loss 0.1641 (0.1363) Prec@1 68.000 (76.030) Prec@5 95.000 (97.242) +2022-11-14 13:19:39,758 Epoch: [22][330/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.1453 (0.1365) Prec@1 71.000 (75.882) Prec@5 97.000 (97.235) +2022-11-14 13:19:40,215 Epoch: [22][340/500] Time 0.043 (0.034) Data 0.003 (0.002) Loss 0.1526 (0.1370) Prec@1 71.000 (75.743) Prec@5 99.000 (97.286) +2022-11-14 13:19:40,667 Epoch: [22][350/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.1481 (0.1373) Prec@1 70.000 (75.583) Prec@5 98.000 (97.306) +2022-11-14 13:19:41,123 Epoch: [22][360/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.1363 (0.1373) Prec@1 75.000 (75.568) Prec@5 98.000 (97.324) +2022-11-14 13:19:41,574 Epoch: [22][370/500] Time 0.043 (0.035) Data 0.001 (0.002) Loss 0.1304 (0.1371) Prec@1 76.000 (75.579) Prec@5 98.000 (97.342) +2022-11-14 13:19:42,028 Epoch: [22][380/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.1268 (0.1368) Prec@1 79.000 (75.667) Prec@5 96.000 (97.308) +2022-11-14 13:19:42,482 Epoch: [22][390/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.1454 (0.1370) Prec@1 74.000 (75.625) Prec@5 95.000 (97.250) +2022-11-14 13:19:42,937 Epoch: [22][400/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.1109 (0.1364) Prec@1 79.000 (75.707) Prec@5 100.000 (97.317) +2022-11-14 13:19:43,388 Epoch: [22][410/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1461 (0.1366) Prec@1 77.000 (75.738) Prec@5 97.000 (97.310) +2022-11-14 13:19:43,833 Epoch: [22][420/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.1641 (0.1373) Prec@1 68.000 (75.558) Prec@5 95.000 (97.256) +2022-11-14 13:19:44,291 Epoch: [22][430/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.1088 (0.1366) Prec@1 81.000 (75.682) Prec@5 100.000 (97.318) +2022-11-14 13:19:44,758 Epoch: [22][440/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1324 (0.1365) Prec@1 78.000 (75.733) Prec@5 97.000 (97.311) +2022-11-14 13:19:45,209 Epoch: [22][450/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.1445 (0.1367) Prec@1 74.000 (75.696) Prec@5 98.000 (97.326) +2022-11-14 13:19:45,722 Epoch: [22][460/500] Time 0.052 (0.036) Data 0.002 (0.002) Loss 0.1446 (0.1369) Prec@1 72.000 (75.617) Prec@5 96.000 (97.298) +2022-11-14 13:19:46,156 Epoch: [22][470/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.1458 (0.1371) Prec@1 75.000 (75.604) Prec@5 99.000 (97.333) +2022-11-14 13:19:46,676 Epoch: [22][480/500] Time 0.056 (0.036) Data 0.002 (0.002) Loss 0.1378 (0.1371) Prec@1 77.000 (75.633) Prec@5 95.000 (97.286) +2022-11-14 13:19:47,122 Epoch: [22][490/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.1393 (0.1371) Prec@1 77.000 (75.660) Prec@5 98.000 (97.300) +2022-11-14 13:19:47,556 Epoch: [22][499/500] Time 0.041 (0.037) Data 0.001 (0.002) Loss 0.1462 (0.1373) Prec@1 79.000 (75.725) Prec@5 98.000 (97.314) +2022-11-14 13:19:47,820 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1291 (0.1291) Prec@1 71.000 (71.000) Prec@5 99.000 (99.000) +2022-11-14 13:19:47,833 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1713 (0.1502) Prec@1 71.000 (71.000) Prec@5 99.000 (99.000) +2022-11-14 13:19:47,845 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1866 (0.1624) Prec@1 66.000 (69.333) Prec@5 97.000 (98.333) +2022-11-14 13:19:47,859 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1577 (0.1612) Prec@1 70.000 (69.500) Prec@5 97.000 (98.000) +2022-11-14 13:19:47,868 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1860 (0.1662) Prec@1 65.000 (68.600) Prec@5 97.000 (97.800) +2022-11-14 13:19:47,879 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1386 (0.1616) Prec@1 74.000 (69.500) Prec@5 98.000 (97.833) +2022-11-14 13:19:47,890 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1612 (0.1615) Prec@1 71.000 (69.714) Prec@5 98.000 (97.857) +2022-11-14 13:19:47,904 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1658 (0.1621) Prec@1 69.000 (69.625) Prec@5 98.000 (97.875) +2022-11-14 13:19:47,915 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2004 (0.1663) Prec@1 66.000 (69.222) Prec@5 95.000 (97.556) +2022-11-14 13:19:47,926 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1218 (0.1619) Prec@1 80.000 (70.300) Prec@5 97.000 (97.500) +2022-11-14 13:19:47,938 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1311 (0.1591) Prec@1 78.000 (71.000) Prec@5 99.000 (97.636) +2022-11-14 13:19:47,952 Test: [11/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1411 (0.1576) Prec@1 77.000 (71.500) Prec@5 97.000 (97.583) +2022-11-14 13:19:47,966 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1507 (0.1570) Prec@1 75.000 (71.769) Prec@5 97.000 (97.538) +2022-11-14 13:19:47,981 Test: [13/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1473 (0.1563) Prec@1 73.000 (71.857) Prec@5 98.000 (97.571) +2022-11-14 13:19:47,995 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1194 (0.1539) Prec@1 78.000 (72.267) Prec@5 98.000 (97.600) +2022-11-14 13:19:48,010 Test: [15/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1791 (0.1555) Prec@1 65.000 (71.812) Prec@5 94.000 (97.375) +2022-11-14 13:19:48,021 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1524 (0.1553) Prec@1 73.000 (71.882) Prec@5 98.000 (97.412) +2022-11-14 13:19:48,036 Test: [17/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1681 (0.1560) Prec@1 71.000 (71.833) Prec@5 97.000 (97.389) +2022-11-14 13:19:48,050 Test: [18/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1743 (0.1570) Prec@1 66.000 (71.526) Prec@5 97.000 (97.368) +2022-11-14 13:19:48,062 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1836 (0.1583) Prec@1 66.000 (71.250) Prec@5 97.000 (97.350) +2022-11-14 13:19:48,073 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1994 (0.1602) Prec@1 70.000 (71.190) Prec@5 95.000 (97.238) +2022-11-14 13:19:48,086 Test: [21/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1664 (0.1605) Prec@1 68.000 (71.045) Prec@5 97.000 (97.227) +2022-11-14 13:19:48,097 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1644 (0.1607) Prec@1 74.000 (71.174) Prec@5 99.000 (97.304) +2022-11-14 13:19:48,106 Test: [23/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1321 (0.1595) Prec@1 74.000 (71.292) Prec@5 95.000 (97.208) +2022-11-14 13:19:48,115 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1870 (0.1606) Prec@1 69.000 (71.200) Prec@5 95.000 (97.120) +2022-11-14 13:19:48,128 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1841 (0.1615) Prec@1 66.000 (71.000) Prec@5 94.000 (97.000) +2022-11-14 13:19:48,137 Test: [26/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1453 (0.1609) Prec@1 77.000 (71.222) Prec@5 99.000 (97.074) +2022-11-14 13:19:48,145 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1651 (0.1610) Prec@1 69.000 (71.143) Prec@5 98.000 (97.107) +2022-11-14 13:19:48,154 Test: [28/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1383 (0.1603) Prec@1 73.000 (71.207) Prec@5 97.000 (97.103) +2022-11-14 13:19:48,163 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1679 (0.1605) Prec@1 72.000 (71.233) Prec@5 96.000 (97.067) +2022-11-14 13:19:48,172 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1324 (0.1596) Prec@1 76.000 (71.387) Prec@5 96.000 (97.032) +2022-11-14 13:19:48,180 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1612 (0.1597) Prec@1 73.000 (71.438) Prec@5 97.000 (97.031) +2022-11-14 13:19:48,188 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1587 (0.1596) Prec@1 73.000 (71.485) Prec@5 97.000 (97.030) +2022-11-14 13:19:48,198 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2036 (0.1609) Prec@1 66.000 (71.324) Prec@5 95.000 (96.971) +2022-11-14 13:19:48,207 Test: [34/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1756 (0.1613) Prec@1 63.000 (71.086) Prec@5 94.000 (96.886) +2022-11-14 13:19:48,217 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1316 (0.1605) Prec@1 81.000 (71.361) Prec@5 95.000 (96.833) +2022-11-14 13:19:48,225 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1608 (0.1605) Prec@1 70.000 (71.324) Prec@5 97.000 (96.838) +2022-11-14 13:19:48,234 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1664 (0.1607) Prec@1 72.000 (71.342) Prec@5 98.000 (96.868) +2022-11-14 13:19:48,242 Test: [38/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1362 (0.1600) Prec@1 74.000 (71.410) Prec@5 98.000 (96.897) +2022-11-14 13:19:48,252 Test: [39/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1531 (0.1599) Prec@1 73.000 (71.450) Prec@5 97.000 (96.900) +2022-11-14 13:19:48,261 Test: [40/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1922 (0.1607) Prec@1 65.000 (71.293) Prec@5 94.000 (96.829) +2022-11-14 13:19:48,271 Test: [41/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1432 (0.1602) Prec@1 72.000 (71.310) Prec@5 96.000 (96.810) +2022-11-14 13:19:48,279 Test: [42/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1375 (0.1597) Prec@1 77.000 (71.442) Prec@5 99.000 (96.860) +2022-11-14 13:19:48,288 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1536 (0.1596) Prec@1 71.000 (71.432) Prec@5 96.000 (96.841) +2022-11-14 13:19:48,298 Test: [44/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1357 (0.1590) Prec@1 77.000 (71.556) Prec@5 98.000 (96.867) +2022-11-14 13:19:48,308 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1788 (0.1595) Prec@1 70.000 (71.522) Prec@5 96.000 (96.848) +2022-11-14 13:19:48,318 Test: [46/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1601 (0.1595) Prec@1 72.000 (71.532) Prec@5 98.000 (96.872) +2022-11-14 13:19:48,329 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1410 (0.1591) Prec@1 75.000 (71.604) Prec@5 96.000 (96.854) +2022-11-14 13:19:48,338 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1402 (0.1587) Prec@1 73.000 (71.633) Prec@5 99.000 (96.898) +2022-11-14 13:19:48,348 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2231 (0.1600) Prec@1 60.000 (71.400) Prec@5 94.000 (96.840) +2022-11-14 13:19:48,359 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1593 (0.1600) Prec@1 70.000 (71.373) Prec@5 95.000 (96.804) +2022-11-14 13:19:48,371 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1905 (0.1606) Prec@1 65.000 (71.250) Prec@5 95.000 (96.769) +2022-11-14 13:19:48,382 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1366 (0.1601) Prec@1 75.000 (71.321) Prec@5 96.000 (96.755) +2022-11-14 13:19:48,394 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1397 (0.1598) Prec@1 75.000 (71.389) Prec@5 97.000 (96.759) +2022-11-14 13:19:48,406 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1780 (0.1601) Prec@1 66.000 (71.291) Prec@5 96.000 (96.745) +2022-11-14 13:19:48,415 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1607 (0.1601) Prec@1 73.000 (71.321) Prec@5 97.000 (96.750) +2022-11-14 13:19:48,425 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1631 (0.1601) Prec@1 73.000 (71.351) Prec@5 95.000 (96.719) +2022-11-14 13:19:48,434 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1597) Prec@1 73.000 (71.379) Prec@5 98.000 (96.741) +2022-11-14 13:19:48,444 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1847 (0.1601) Prec@1 66.000 (71.288) Prec@5 98.000 (96.763) +2022-11-14 13:19:48,454 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1603) Prec@1 72.000 (71.300) Prec@5 97.000 (96.767) +2022-11-14 13:19:48,463 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1566 (0.1602) Prec@1 72.000 (71.311) Prec@5 98.000 (96.787) +2022-11-14 13:19:48,473 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1792 (0.1605) Prec@1 65.000 (71.210) Prec@5 95.000 (96.758) +2022-11-14 13:19:48,483 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1489 (0.1603) Prec@1 74.000 (71.254) Prec@5 98.000 (96.778) +2022-11-14 13:19:48,493 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1517 (0.1602) Prec@1 71.000 (71.250) Prec@5 98.000 (96.797) +2022-11-14 13:19:48,503 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1670 (0.1603) Prec@1 74.000 (71.292) Prec@5 96.000 (96.785) +2022-11-14 13:19:48,513 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1791 (0.1606) Prec@1 65.000 (71.197) Prec@5 98.000 (96.803) +2022-11-14 13:19:48,523 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1657 (0.1606) Prec@1 68.000 (71.149) Prec@5 97.000 (96.806) +2022-11-14 13:19:48,532 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1723 (0.1608) Prec@1 69.000 (71.118) Prec@5 98.000 (96.824) +2022-11-14 13:19:48,542 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1805 (0.1611) Prec@1 69.000 (71.087) Prec@5 98.000 (96.841) +2022-11-14 13:19:48,552 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1832 (0.1614) Prec@1 67.000 (71.029) Prec@5 96.000 (96.829) +2022-11-14 13:19:48,562 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1592 (0.1614) Prec@1 72.000 (71.042) Prec@5 97.000 (96.831) +2022-11-14 13:19:48,573 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1693 (0.1615) Prec@1 69.000 (71.014) Prec@5 100.000 (96.875) +2022-11-14 13:19:48,582 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1616) Prec@1 71.000 (71.014) Prec@5 98.000 (96.890) +2022-11-14 13:19:48,592 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1410 (0.1613) Prec@1 76.000 (71.081) Prec@5 97.000 (96.892) +2022-11-14 13:19:48,601 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1834 (0.1616) Prec@1 66.000 (71.013) Prec@5 96.000 (96.880) +2022-11-14 13:19:48,611 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.1608) Prec@1 82.000 (71.158) Prec@5 99.000 (96.908) +2022-11-14 13:19:48,622 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1741 (0.1610) Prec@1 72.000 (71.169) Prec@5 95.000 (96.883) +2022-11-14 13:19:48,632 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1734 (0.1612) Prec@1 66.000 (71.103) Prec@5 98.000 (96.897) +2022-11-14 13:19:48,644 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1565 (0.1611) Prec@1 74.000 (71.139) Prec@5 97.000 (96.899) +2022-11-14 13:19:48,655 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1791 (0.1613) Prec@1 68.000 (71.100) Prec@5 97.000 (96.900) +2022-11-14 13:19:48,665 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.1609) Prec@1 75.000 (71.148) Prec@5 98.000 (96.914) +2022-11-14 13:19:48,674 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1666 (0.1610) Prec@1 70.000 (71.134) Prec@5 97.000 (96.915) +2022-11-14 13:19:48,684 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1609) Prec@1 74.000 (71.169) Prec@5 99.000 (96.940) +2022-11-14 13:19:48,693 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1849 (0.1612) Prec@1 65.000 (71.095) Prec@5 97.000 (96.940) +2022-11-14 13:19:48,703 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1665 (0.1613) Prec@1 71.000 (71.094) Prec@5 98.000 (96.953) +2022-11-14 13:19:48,714 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1613 (0.1613) Prec@1 70.000 (71.081) Prec@5 99.000 (96.977) +2022-11-14 13:19:48,725 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1709 (0.1614) Prec@1 70.000 (71.069) Prec@5 99.000 (97.000) +2022-11-14 13:19:48,739 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1337 (0.1611) Prec@1 76.000 (71.125) Prec@5 97.000 (97.000) +2022-11-14 13:19:48,752 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1332 (0.1608) Prec@1 72.000 (71.135) Prec@5 99.000 (97.022) +2022-11-14 13:19:48,766 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.1607) Prec@1 73.000 (71.156) Prec@5 96.000 (97.011) +2022-11-14 13:19:48,779 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1449 (0.1605) Prec@1 73.000 (71.176) Prec@5 99.000 (97.033) +2022-11-14 13:19:48,794 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.1600) Prec@1 80.000 (71.272) Prec@5 98.000 (97.043) +2022-11-14 13:19:48,807 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1575 (0.1600) Prec@1 70.000 (71.258) Prec@5 96.000 (97.032) +2022-11-14 13:19:48,819 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1600) Prec@1 71.000 (71.255) Prec@5 93.000 (96.989) +2022-11-14 13:19:48,832 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1616 (0.1601) Prec@1 70.000 (71.242) Prec@5 98.000 (97.000) +2022-11-14 13:19:48,847 Test: [95/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1514 (0.1600) Prec@1 71.000 (71.240) Prec@5 96.000 (96.990) +2022-11-14 13:19:48,861 Test: [96/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1434 (0.1598) Prec@1 75.000 (71.278) Prec@5 95.000 (96.969) +2022-11-14 13:19:48,876 Test: [97/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1852 (0.1601) Prec@1 69.000 (71.255) Prec@5 93.000 (96.929) +2022-11-14 13:19:48,887 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1966 (0.1604) Prec@1 64.000 (71.182) Prec@5 95.000 (96.909) +2022-11-14 13:19:48,899 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.1605) Prec@1 73.000 (71.200) Prec@5 96.000 (96.900) +2022-11-14 13:19:48,970 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:19:49,280 Epoch: [23][0/500] Time 0.030 (0.030) Data 0.219 (0.219) Loss 0.1661 (0.1661) Prec@1 71.000 (71.000) Prec@5 94.000 (94.000) +2022-11-14 13:19:49,532 Epoch: [23][10/500] Time 0.023 (0.023) Data 0.002 (0.022) Loss 0.1561 (0.1611) Prec@1 75.000 (73.000) Prec@5 98.000 (96.000) +2022-11-14 13:19:49,794 Epoch: [23][20/500] Time 0.019 (0.023) Data 0.002 (0.012) Loss 0.1417 (0.1546) Prec@1 78.000 (74.667) Prec@5 100.000 (97.333) +2022-11-14 13:19:49,995 Epoch: [23][30/500] Time 0.018 (0.021) Data 0.002 (0.009) Loss 0.1235 (0.1469) Prec@1 80.000 (76.000) Prec@5 98.000 (97.500) +2022-11-14 13:19:50,280 Epoch: [23][40/500] Time 0.031 (0.022) Data 0.002 (0.007) Loss 0.1230 (0.1421) Prec@1 79.000 (76.600) Prec@5 98.000 (97.600) +2022-11-14 13:19:50,641 Epoch: [23][50/500] Time 0.033 (0.024) Data 0.002 (0.006) Loss 0.1486 (0.1432) Prec@1 72.000 (75.833) Prec@5 97.000 (97.500) +2022-11-14 13:19:50,965 Epoch: [23][60/500] Time 0.037 (0.025) Data 0.001 (0.005) Loss 0.1207 (0.1400) Prec@1 81.000 (76.571) Prec@5 99.000 (97.714) +2022-11-14 13:19:51,318 Epoch: [23][70/500] Time 0.028 (0.026) Data 0.001 (0.005) Loss 0.1108 (0.1363) Prec@1 83.000 (77.375) Prec@5 97.000 (97.625) +2022-11-14 13:19:51,638 Epoch: [23][80/500] Time 0.029 (0.026) Data 0.002 (0.005) Loss 0.1267 (0.1353) Prec@1 78.000 (77.444) Prec@5 97.000 (97.556) +2022-11-14 13:19:51,964 Epoch: [23][90/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.1658 (0.1383) Prec@1 72.000 (76.900) Prec@5 96.000 (97.400) +2022-11-14 13:19:52,339 Epoch: [23][100/500] Time 0.024 (0.027) Data 0.002 (0.004) Loss 0.1521 (0.1396) Prec@1 75.000 (76.727) Prec@5 99.000 (97.545) +2022-11-14 13:19:52,662 Epoch: [23][110/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.1339 (0.1391) Prec@1 74.000 (76.500) Prec@5 98.000 (97.583) +2022-11-14 13:19:52,991 Epoch: [23][120/500] Time 0.031 (0.027) Data 0.002 (0.004) Loss 0.1202 (0.1376) Prec@1 83.000 (77.000) Prec@5 100.000 (97.769) +2022-11-14 13:19:53,314 Epoch: [23][130/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.1506 (0.1386) Prec@1 71.000 (76.571) Prec@5 96.000 (97.643) +2022-11-14 13:19:53,722 Epoch: [23][140/500] Time 0.041 (0.028) Data 0.002 (0.003) Loss 0.1278 (0.1378) Prec@1 80.000 (76.800) Prec@5 98.000 (97.667) +2022-11-14 13:19:54,019 Epoch: [23][150/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.1245 (0.1370) Prec@1 77.000 (76.812) Prec@5 98.000 (97.688) +2022-11-14 13:19:54,352 Epoch: [23][160/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.1143 (0.1357) Prec@1 82.000 (77.118) Prec@5 99.000 (97.765) +2022-11-14 13:19:54,772 Epoch: [23][170/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.1473 (0.1363) Prec@1 71.000 (76.778) Prec@5 100.000 (97.889) +2022-11-14 13:19:55,074 Epoch: [23][180/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.1449 (0.1368) Prec@1 80.000 (76.947) Prec@5 96.000 (97.789) +2022-11-14 13:19:55,397 Epoch: [23][190/500] Time 0.031 (0.029) Data 0.001 (0.003) Loss 0.1441 (0.1371) Prec@1 75.000 (76.850) Prec@5 98.000 (97.800) +2022-11-14 13:19:55,809 Epoch: [23][200/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.1255 (0.1366) Prec@1 76.000 (76.810) Prec@5 98.000 (97.810) +2022-11-14 13:19:56,110 Epoch: [23][210/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.1363 (0.1366) Prec@1 75.000 (76.727) Prec@5 97.000 (97.773) +2022-11-14 13:19:56,438 Epoch: [23][220/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.1560 (0.1374) Prec@1 73.000 (76.565) Prec@5 98.000 (97.783) +2022-11-14 13:19:56,847 Epoch: [23][230/500] Time 0.045 (0.029) Data 0.002 (0.003) Loss 0.1183 (0.1366) Prec@1 79.000 (76.667) Prec@5 98.000 (97.792) +2022-11-14 13:19:57,149 Epoch: [23][240/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.1672 (0.1378) Prec@1 70.000 (76.400) Prec@5 96.000 (97.720) +2022-11-14 13:19:57,479 Epoch: [23][250/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.1443 (0.1381) Prec@1 74.000 (76.308) Prec@5 97.000 (97.692) +2022-11-14 13:19:57,862 Epoch: [23][260/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.1470 (0.1384) Prec@1 77.000 (76.333) Prec@5 99.000 (97.741) +2022-11-14 13:19:58,202 Epoch: [23][270/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.1087 (0.1374) Prec@1 83.000 (76.571) Prec@5 99.000 (97.786) +2022-11-14 13:19:58,535 Epoch: [23][280/500] Time 0.031 (0.029) Data 0.001 (0.003) Loss 0.1311 (0.1371) Prec@1 74.000 (76.483) Prec@5 97.000 (97.759) +2022-11-14 13:19:58,870 Epoch: [23][290/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.1322 (0.1370) Prec@1 78.000 (76.533) Prec@5 99.000 (97.800) +2022-11-14 13:19:59,200 Epoch: [23][300/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.1137 (0.1362) Prec@1 80.000 (76.645) Prec@5 98.000 (97.806) +2022-11-14 13:19:59,666 Epoch: [23][310/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1193 (0.1357) Prec@1 80.000 (76.750) Prec@5 98.000 (97.812) +2022-11-14 13:20:00,094 Epoch: [23][320/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.1448 (0.1360) Prec@1 75.000 (76.697) Prec@5 100.000 (97.879) +2022-11-14 13:20:00,538 Epoch: [23][330/500] Time 0.040 (0.030) Data 0.002 (0.003) Loss 0.1620 (0.1367) Prec@1 72.000 (76.559) Prec@5 96.000 (97.824) +2022-11-14 13:20:01,025 Epoch: [23][340/500] Time 0.063 (0.031) Data 0.002 (0.003) Loss 0.1616 (0.1375) Prec@1 73.000 (76.457) Prec@5 99.000 (97.857) +2022-11-14 13:20:01,782 Epoch: [23][350/500] Time 0.050 (0.032) Data 0.002 (0.002) Loss 0.1121 (0.1367) Prec@1 80.000 (76.556) Prec@5 98.000 (97.861) +2022-11-14 13:20:02,306 Epoch: [23][360/500] Time 0.041 (0.032) Data 0.002 (0.002) Loss 0.1478 (0.1370) Prec@1 76.000 (76.541) Prec@5 99.000 (97.892) +2022-11-14 13:20:02,822 Epoch: [23][370/500] Time 0.064 (0.033) Data 0.002 (0.002) Loss 0.1228 (0.1367) Prec@1 80.000 (76.632) Prec@5 100.000 (97.947) +2022-11-14 13:20:03,286 Epoch: [23][380/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.1416 (0.1368) Prec@1 73.000 (76.538) Prec@5 97.000 (97.923) +2022-11-14 13:20:03,749 Epoch: [23][390/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.1378 (0.1368) Prec@1 78.000 (76.575) Prec@5 98.000 (97.925) +2022-11-14 13:20:04,286 Epoch: [23][400/500] Time 0.090 (0.033) Data 0.002 (0.002) Loss 0.1348 (0.1368) Prec@1 78.000 (76.610) Prec@5 97.000 (97.902) +2022-11-14 13:20:04,779 Epoch: [23][410/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.1255 (0.1365) Prec@1 79.000 (76.667) Prec@5 97.000 (97.881) +2022-11-14 13:20:05,245 Epoch: [23][420/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.1653 (0.1372) Prec@1 73.000 (76.581) Prec@5 97.000 (97.860) +2022-11-14 13:20:05,709 Epoch: [23][430/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.1418 (0.1373) Prec@1 76.000 (76.568) Prec@5 96.000 (97.818) +2022-11-14 13:20:06,324 Epoch: [23][440/500] Time 0.058 (0.034) Data 0.002 (0.002) Loss 0.1262 (0.1370) Prec@1 80.000 (76.644) Prec@5 96.000 (97.778) +2022-11-14 13:20:06,919 Epoch: [23][450/500] Time 0.049 (0.035) Data 0.002 (0.002) Loss 0.1542 (0.1374) Prec@1 73.000 (76.565) Prec@5 97.000 (97.761) +2022-11-14 13:20:07,383 Epoch: [23][460/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.1200 (0.1370) Prec@1 81.000 (76.660) Prec@5 99.000 (97.787) +2022-11-14 13:20:08,046 Epoch: [23][470/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.1199 (0.1367) Prec@1 80.000 (76.729) Prec@5 100.000 (97.833) +2022-11-14 13:20:08,516 Epoch: [23][480/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1281 (0.1365) Prec@1 78.000 (76.755) Prec@5 95.000 (97.776) +2022-11-14 13:20:08,981 Epoch: [23][490/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1326 (0.1364) Prec@1 75.000 (76.720) Prec@5 97.000 (97.760) +2022-11-14 13:20:09,399 Epoch: [23][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1405 (0.1365) Prec@1 75.000 (76.686) Prec@5 98.000 (97.765) +2022-11-14 13:20:09,687 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1512 (0.1512) Prec@1 75.000 (75.000) Prec@5 98.000 (98.000) +2022-11-14 13:20:09,699 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1783 (0.1647) Prec@1 67.000 (71.000) Prec@5 96.000 (97.000) +2022-11-14 13:20:09,709 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2004 (0.1766) Prec@1 65.000 (69.000) Prec@5 94.000 (96.000) +2022-11-14 13:20:09,721 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1711 (0.1752) Prec@1 68.000 (68.750) Prec@5 94.000 (95.500) +2022-11-14 13:20:09,730 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1983 (0.1799) Prec@1 64.000 (67.800) Prec@5 93.000 (95.000) +2022-11-14 13:20:09,740 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1448 (0.1740) Prec@1 72.000 (68.500) Prec@5 100.000 (95.833) +2022-11-14 13:20:09,750 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2136 (0.1797) Prec@1 62.000 (67.571) Prec@5 95.000 (95.714) +2022-11-14 13:20:09,760 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2040 (0.1827) Prec@1 62.000 (66.875) Prec@5 96.000 (95.750) +2022-11-14 13:20:09,767 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1988 (0.1845) Prec@1 68.000 (67.000) Prec@5 92.000 (95.333) +2022-11-14 13:20:09,779 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1692 (0.1830) Prec@1 71.000 (67.400) Prec@5 94.000 (95.200) +2022-11-14 13:20:09,789 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1927 (0.1839) Prec@1 64.000 (67.091) Prec@5 94.000 (95.091) +2022-11-14 13:20:09,798 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1821 (0.1837) Prec@1 67.000 (67.083) Prec@5 97.000 (95.250) +2022-11-14 13:20:09,807 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1325 (0.1798) Prec@1 77.000 (67.846) Prec@5 100.000 (95.615) +2022-11-14 13:20:09,818 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1695 (0.1790) Prec@1 70.000 (68.000) Prec@5 93.000 (95.429) +2022-11-14 13:20:09,828 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1631 (0.1780) Prec@1 67.000 (67.933) Prec@5 95.000 (95.400) +2022-11-14 13:20:09,836 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1852 (0.1784) Prec@1 70.000 (68.062) Prec@5 96.000 (95.438) +2022-11-14 13:20:09,845 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1628 (0.1775) Prec@1 72.000 (68.294) Prec@5 98.000 (95.588) +2022-11-14 13:20:09,854 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2102 (0.1793) Prec@1 64.000 (68.056) Prec@5 97.000 (95.667) +2022-11-14 13:20:09,863 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1747 (0.1791) Prec@1 71.000 (68.211) Prec@5 94.000 (95.579) +2022-11-14 13:20:09,872 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1950 (0.1799) Prec@1 66.000 (68.100) Prec@5 95.000 (95.550) +2022-11-14 13:20:09,881 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2074 (0.1812) Prec@1 64.000 (67.905) Prec@5 95.000 (95.524) +2022-11-14 13:20:09,891 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1835 (0.1813) Prec@1 71.000 (68.045) Prec@5 95.000 (95.500) +2022-11-14 13:20:09,899 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1707 (0.1808) Prec@1 68.000 (68.043) Prec@5 95.000 (95.478) +2022-11-14 13:20:09,908 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1698 (0.1804) Prec@1 69.000 (68.083) Prec@5 97.000 (95.542) +2022-11-14 13:20:09,918 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1942 (0.1809) Prec@1 68.000 (68.080) Prec@5 96.000 (95.560) +2022-11-14 13:20:09,927 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1937 (0.1814) Prec@1 66.000 (68.000) Prec@5 91.000 (95.385) +2022-11-14 13:20:09,936 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1640 (0.1808) Prec@1 74.000 (68.222) Prec@5 96.000 (95.407) +2022-11-14 13:20:09,945 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1901 (0.1811) Prec@1 66.000 (68.143) Prec@5 97.000 (95.464) +2022-11-14 13:20:09,955 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1764 (0.1809) Prec@1 68.000 (68.138) Prec@5 97.000 (95.517) +2022-11-14 13:20:09,964 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1722 (0.1807) Prec@1 68.000 (68.133) Prec@5 98.000 (95.600) +2022-11-14 13:20:09,973 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1659 (0.1802) Prec@1 68.000 (68.129) Prec@5 95.000 (95.581) +2022-11-14 13:20:09,983 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1745 (0.1800) Prec@1 73.000 (68.281) Prec@5 94.000 (95.531) +2022-11-14 13:20:09,992 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1964 (0.1805) Prec@1 67.000 (68.242) Prec@5 95.000 (95.515) +2022-11-14 13:20:10,005 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1922 (0.1808) Prec@1 63.000 (68.088) Prec@5 94.000 (95.471) +2022-11-14 13:20:10,019 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1711 (0.1806) Prec@1 68.000 (68.086) Prec@5 94.000 (95.429) +2022-11-14 13:20:10,033 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1426 (0.1795) Prec@1 78.000 (68.361) Prec@5 96.000 (95.444) +2022-11-14 13:20:10,048 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2089 (0.1803) Prec@1 65.000 (68.270) Prec@5 94.000 (95.405) +2022-11-14 13:20:10,062 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1838 (0.1804) Prec@1 70.000 (68.316) Prec@5 94.000 (95.368) +2022-11-14 13:20:10,076 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1413 (0.1794) Prec@1 72.000 (68.410) Prec@5 99.000 (95.462) +2022-11-14 13:20:10,092 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1744 (0.1793) Prec@1 68.000 (68.400) Prec@5 97.000 (95.500) +2022-11-14 13:20:10,109 Test: [40/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.1837 (0.1794) Prec@1 68.000 (68.390) Prec@5 94.000 (95.463) +2022-11-14 13:20:10,125 Test: [41/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.2032 (0.1799) Prec@1 64.000 (68.286) Prec@5 95.000 (95.452) +2022-11-14 13:20:10,141 Test: [42/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.1428 (0.1791) Prec@1 78.000 (68.512) Prec@5 96.000 (95.465) +2022-11-14 13:20:10,157 Test: [43/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1616 (0.1787) Prec@1 70.000 (68.545) Prec@5 97.000 (95.500) +2022-11-14 13:20:10,171 Test: [44/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1726 (0.1785) Prec@1 71.000 (68.600) Prec@5 95.000 (95.489) +2022-11-14 13:20:10,183 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1910 (0.1788) Prec@1 64.000 (68.500) Prec@5 95.000 (95.478) +2022-11-14 13:20:10,194 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1527 (0.1783) Prec@1 75.000 (68.638) Prec@5 98.000 (95.532) +2022-11-14 13:20:10,203 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1522 (0.1777) Prec@1 72.000 (68.708) Prec@5 98.000 (95.583) +2022-11-14 13:20:10,213 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1513 (0.1772) Prec@1 70.000 (68.735) Prec@5 97.000 (95.612) +2022-11-14 13:20:10,223 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1983 (0.1776) Prec@1 61.000 (68.580) Prec@5 93.000 (95.560) +2022-11-14 13:20:10,233 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1585 (0.1772) Prec@1 74.000 (68.686) Prec@5 98.000 (95.608) +2022-11-14 13:20:10,242 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1975 (0.1776) Prec@1 64.000 (68.596) Prec@5 95.000 (95.596) +2022-11-14 13:20:10,252 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1717 (0.1775) Prec@1 66.000 (68.547) Prec@5 99.000 (95.660) +2022-11-14 13:20:10,261 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1997 (0.1779) Prec@1 66.000 (68.500) Prec@5 97.000 (95.685) +2022-11-14 13:20:10,273 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1978 (0.1783) Prec@1 67.000 (68.473) Prec@5 97.000 (95.709) +2022-11-14 13:20:10,285 Test: [55/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1910 (0.1785) Prec@1 69.000 (68.482) Prec@5 97.000 (95.732) +2022-11-14 13:20:10,296 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1796 (0.1785) Prec@1 66.000 (68.439) Prec@5 95.000 (95.719) +2022-11-14 13:20:10,307 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1777 (0.1785) Prec@1 69.000 (68.448) Prec@5 98.000 (95.759) +2022-11-14 13:20:10,317 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2048 (0.1790) Prec@1 61.000 (68.322) Prec@5 94.000 (95.729) +2022-11-14 13:20:10,326 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1459 (0.1784) Prec@1 75.000 (68.433) Prec@5 93.000 (95.683) +2022-11-14 13:20:10,335 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1894 (0.1786) Prec@1 69.000 (68.443) Prec@5 94.000 (95.656) +2022-11-14 13:20:10,345 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1700 (0.1784) Prec@1 69.000 (68.452) Prec@5 92.000 (95.597) +2022-11-14 13:20:10,355 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1762 (0.1784) Prec@1 68.000 (68.444) Prec@5 97.000 (95.619) +2022-11-14 13:20:10,364 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1853 (0.1785) Prec@1 67.000 (68.422) Prec@5 96.000 (95.625) +2022-11-14 13:20:10,373 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2051 (0.1789) Prec@1 68.000 (68.415) Prec@5 95.000 (95.615) +2022-11-14 13:20:10,381 Test: [65/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2313 (0.1797) Prec@1 59.000 (68.273) Prec@5 92.000 (95.561) +2022-11-14 13:20:10,391 Test: [66/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2068 (0.1801) Prec@1 63.000 (68.194) Prec@5 94.000 (95.537) +2022-11-14 13:20:10,400 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2004 (0.1804) Prec@1 66.000 (68.162) Prec@5 96.000 (95.544) +2022-11-14 13:20:10,410 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2008 (0.1807) Prec@1 64.000 (68.101) Prec@5 92.000 (95.493) +2022-11-14 13:20:10,420 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2000 (0.1810) Prec@1 64.000 (68.043) Prec@5 94.000 (95.471) +2022-11-14 13:20:10,428 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1429 (0.1805) Prec@1 76.000 (68.155) Prec@5 99.000 (95.521) +2022-11-14 13:20:10,438 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1739 (0.1804) Prec@1 69.000 (68.167) Prec@5 95.000 (95.514) +2022-11-14 13:20:10,447 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1775 (0.1803) Prec@1 69.000 (68.178) Prec@5 98.000 (95.548) +2022-11-14 13:20:10,456 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1419 (0.1798) Prec@1 74.000 (68.257) Prec@5 98.000 (95.581) +2022-11-14 13:20:10,466 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1700 (0.1797) Prec@1 73.000 (68.320) Prec@5 94.000 (95.560) +2022-11-14 13:20:10,476 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1665 (0.1795) Prec@1 75.000 (68.408) Prec@5 97.000 (95.579) +2022-11-14 13:20:10,485 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1638 (0.1793) Prec@1 73.000 (68.468) Prec@5 96.000 (95.584) +2022-11-14 13:20:10,495 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1662 (0.1791) Prec@1 69.000 (68.474) Prec@5 98.000 (95.615) +2022-11-14 13:20:10,504 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2121 (0.1796) Prec@1 59.000 (68.354) Prec@5 95.000 (95.608) +2022-11-14 13:20:10,513 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1800 (0.1796) Prec@1 69.000 (68.362) Prec@5 97.000 (95.625) +2022-11-14 13:20:10,523 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1605 (0.1793) Prec@1 72.000 (68.407) Prec@5 96.000 (95.630) +2022-11-14 13:20:10,532 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1698 (0.1792) Prec@1 68.000 (68.402) Prec@5 95.000 (95.622) +2022-11-14 13:20:10,541 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1618 (0.1790) Prec@1 72.000 (68.446) Prec@5 98.000 (95.651) +2022-11-14 13:20:10,551 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1876 (0.1791) Prec@1 63.000 (68.381) Prec@5 97.000 (95.667) +2022-11-14 13:20:10,560 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2341 (0.1797) Prec@1 57.000 (68.247) Prec@5 93.000 (95.635) +2022-11-14 13:20:10,569 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1796) Prec@1 67.000 (68.233) Prec@5 96.000 (95.640) +2022-11-14 13:20:10,578 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.1796) Prec@1 66.000 (68.207) Prec@5 97.000 (95.655) +2022-11-14 13:20:10,587 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2020 (0.1799) Prec@1 65.000 (68.170) Prec@5 96.000 (95.659) +2022-11-14 13:20:10,596 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1865 (0.1799) Prec@1 68.000 (68.169) Prec@5 94.000 (95.640) +2022-11-14 13:20:10,605 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1976 (0.1801) Prec@1 68.000 (68.167) Prec@5 90.000 (95.578) +2022-11-14 13:20:10,615 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.1800) Prec@1 66.000 (68.143) Prec@5 96.000 (95.582) +2022-11-14 13:20:10,624 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1255 (0.1795) Prec@1 78.000 (68.250) Prec@5 97.000 (95.598) +2022-11-14 13:20:10,633 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1868 (0.1795) Prec@1 68.000 (68.247) Prec@5 95.000 (95.591) +2022-11-14 13:20:10,643 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1881 (0.1796) Prec@1 66.000 (68.223) Prec@5 94.000 (95.574) +2022-11-14 13:20:10,652 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1982 (0.1798) Prec@1 65.000 (68.189) Prec@5 92.000 (95.537) +2022-11-14 13:20:10,662 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1805 (0.1798) Prec@1 68.000 (68.188) Prec@5 97.000 (95.552) +2022-11-14 13:20:10,670 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1739 (0.1798) Prec@1 67.000 (68.175) Prec@5 94.000 (95.536) +2022-11-14 13:20:10,678 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1793 (0.1798) Prec@1 68.000 (68.173) Prec@5 96.000 (95.541) +2022-11-14 13:20:10,688 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2061 (0.1800) Prec@1 61.000 (68.101) Prec@5 94.000 (95.525) +2022-11-14 13:20:10,698 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2092 (0.1803) Prec@1 63.000 (68.050) Prec@5 96.000 (95.530) +2022-11-14 13:20:10,755 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:20:11,054 Epoch: [24][0/500] Time 0.023 (0.023) Data 0.217 (0.217) Loss 0.1186 (0.1186) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:20:11,260 Epoch: [24][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.1446 (0.1316) Prec@1 73.000 (78.000) Prec@5 99.000 (99.500) +2022-11-14 13:20:11,455 Epoch: [24][20/500] Time 0.017 (0.018) Data 0.002 (0.012) Loss 0.1085 (0.1239) Prec@1 84.000 (80.000) Prec@5 99.000 (99.333) +2022-11-14 13:20:11,676 Epoch: [24][30/500] Time 0.022 (0.018) Data 0.002 (0.009) Loss 0.1401 (0.1280) Prec@1 74.000 (78.500) Prec@5 99.000 (99.250) +2022-11-14 13:20:11,987 Epoch: [24][40/500] Time 0.022 (0.021) Data 0.002 (0.007) Loss 0.1421 (0.1308) Prec@1 74.000 (77.600) Prec@5 98.000 (99.000) +2022-11-14 13:20:12,250 Epoch: [24][50/500] Time 0.032 (0.021) Data 0.002 (0.006) Loss 0.1441 (0.1330) Prec@1 77.000 (77.500) Prec@5 96.000 (98.500) +2022-11-14 13:20:12,648 Epoch: [24][60/500] Time 0.038 (0.023) Data 0.002 (0.005) Loss 0.1265 (0.1321) Prec@1 78.000 (77.571) Prec@5 97.000 (98.286) +2022-11-14 13:20:13,049 Epoch: [24][70/500] Time 0.038 (0.025) Data 0.001 (0.005) Loss 0.1737 (0.1373) Prec@1 68.000 (76.375) Prec@5 96.000 (98.000) +2022-11-14 13:20:13,556 Epoch: [24][80/500] Time 0.056 (0.028) Data 0.002 (0.004) Loss 0.1654 (0.1404) Prec@1 71.000 (75.778) Prec@5 98.000 (98.000) +2022-11-14 13:20:13,922 Epoch: [24][90/500] Time 0.041 (0.028) Data 0.002 (0.004) Loss 0.1347 (0.1398) Prec@1 76.000 (75.800) Prec@5 98.000 (98.000) +2022-11-14 13:20:14,330 Epoch: [24][100/500] Time 0.040 (0.029) Data 0.002 (0.004) Loss 0.1299 (0.1389) Prec@1 79.000 (76.091) Prec@5 97.000 (97.909) +2022-11-14 13:20:14,753 Epoch: [24][110/500] Time 0.039 (0.030) Data 0.002 (0.004) Loss 0.1688 (0.1414) Prec@1 71.000 (75.667) Prec@5 95.000 (97.667) +2022-11-14 13:20:15,173 Epoch: [24][120/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.1804 (0.1444) Prec@1 67.000 (75.000) Prec@5 96.000 (97.538) +2022-11-14 13:20:15,647 Epoch: [24][130/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.1540 (0.1451) Prec@1 73.000 (74.857) Prec@5 98.000 (97.571) +2022-11-14 13:20:16,049 Epoch: [24][140/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.1705 (0.1468) Prec@1 68.000 (74.400) Prec@5 98.000 (97.600) +2022-11-14 13:20:16,465 Epoch: [24][150/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.1563 (0.1474) Prec@1 69.000 (74.062) Prec@5 98.000 (97.625) +2022-11-14 13:20:16,910 Epoch: [24][160/500] Time 0.078 (0.032) Data 0.002 (0.003) Loss 0.1290 (0.1463) Prec@1 75.000 (74.118) Prec@5 98.000 (97.647) +2022-11-14 13:20:17,300 Epoch: [24][170/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.1240 (0.1451) Prec@1 78.000 (74.333) Prec@5 99.000 (97.722) +2022-11-14 13:20:17,705 Epoch: [24][180/500] Time 0.038 (0.033) Data 0.001 (0.003) Loss 0.1408 (0.1448) Prec@1 74.000 (74.316) Prec@5 100.000 (97.842) +2022-11-14 13:20:18,165 Epoch: [24][190/500] Time 0.080 (0.033) Data 0.002 (0.003) Loss 0.1076 (0.1430) Prec@1 78.000 (74.500) Prec@5 98.000 (97.850) +2022-11-14 13:20:18,539 Epoch: [24][200/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1528 (0.1434) Prec@1 70.000 (74.286) Prec@5 99.000 (97.905) +2022-11-14 13:20:18,947 Epoch: [24][210/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1547 (0.1440) Prec@1 71.000 (74.136) Prec@5 97.000 (97.864) +2022-11-14 13:20:19,376 Epoch: [24][220/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.1314 (0.1434) Prec@1 79.000 (74.348) Prec@5 99.000 (97.913) +2022-11-14 13:20:19,802 Epoch: [24][230/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.1453 (0.1435) Prec@1 75.000 (74.375) Prec@5 97.000 (97.875) +2022-11-14 13:20:20,222 Epoch: [24][240/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.1613 (0.1442) Prec@1 70.000 (74.200) Prec@5 99.000 (97.920) +2022-11-14 13:20:20,627 Epoch: [24][250/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1335 (0.1438) Prec@1 77.000 (74.308) Prec@5 95.000 (97.808) +2022-11-14 13:20:21,046 Epoch: [24][260/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0920 (0.1419) Prec@1 85.000 (74.704) Prec@5 100.000 (97.889) +2022-11-14 13:20:21,464 Epoch: [24][270/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1437 (0.1419) Prec@1 74.000 (74.679) Prec@5 94.000 (97.750) +2022-11-14 13:20:21,864 Epoch: [24][280/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1133 (0.1410) Prec@1 78.000 (74.793) Prec@5 99.000 (97.793) +2022-11-14 13:20:22,275 Epoch: [24][290/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.1348 (0.1407) Prec@1 77.000 (74.867) Prec@5 97.000 (97.767) +2022-11-14 13:20:22,685 Epoch: [24][300/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1203 (0.1401) Prec@1 81.000 (75.065) Prec@5 97.000 (97.742) +2022-11-14 13:20:23,094 Epoch: [24][310/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1495 (0.1404) Prec@1 73.000 (75.000) Prec@5 97.000 (97.719) +2022-11-14 13:20:23,498 Epoch: [24][320/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.1425 (0.1404) Prec@1 72.000 (74.909) Prec@5 99.000 (97.758) +2022-11-14 13:20:23,906 Epoch: [24][330/500] Time 0.041 (0.035) Data 0.001 (0.003) Loss 0.1570 (0.1409) Prec@1 74.000 (74.882) Prec@5 100.000 (97.824) +2022-11-14 13:20:24,363 Epoch: [24][340/500] Time 0.036 (0.035) Data 0.003 (0.003) Loss 0.1455 (0.1411) Prec@1 78.000 (74.971) Prec@5 98.000 (97.829) +2022-11-14 13:20:24,766 Epoch: [24][350/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.1800 (0.1421) Prec@1 71.000 (74.861) Prec@5 97.000 (97.806) +2022-11-14 13:20:25,180 Epoch: [24][360/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1092 (0.1413) Prec@1 81.000 (75.027) Prec@5 99.000 (97.838) +2022-11-14 13:20:25,579 Epoch: [24][370/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1368 (0.1411) Prec@1 76.000 (75.053) Prec@5 99.000 (97.868) +2022-11-14 13:20:25,998 Epoch: [24][380/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.1294 (0.1408) Prec@1 80.000 (75.179) Prec@5 99.000 (97.897) +2022-11-14 13:20:26,401 Epoch: [24][390/500] Time 0.038 (0.035) Data 0.003 (0.002) Loss 0.1249 (0.1404) Prec@1 80.000 (75.300) Prec@5 98.000 (97.900) +2022-11-14 13:20:26,821 Epoch: [24][400/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1446 (0.1405) Prec@1 72.000 (75.220) Prec@5 98.000 (97.902) +2022-11-14 13:20:27,220 Epoch: [24][410/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1453 (0.1407) Prec@1 72.000 (75.143) Prec@5 96.000 (97.857) +2022-11-14 13:20:27,635 Epoch: [24][420/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.1361 (0.1405) Prec@1 80.000 (75.256) Prec@5 99.000 (97.884) +2022-11-14 13:20:28,041 Epoch: [24][430/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1435 (0.1406) Prec@1 73.000 (75.205) Prec@5 98.000 (97.886) +2022-11-14 13:20:28,448 Epoch: [24][440/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.1179 (0.1401) Prec@1 82.000 (75.356) Prec@5 99.000 (97.911) +2022-11-14 13:20:28,842 Epoch: [24][450/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.1609 (0.1406) Prec@1 70.000 (75.239) Prec@5 97.000 (97.891) +2022-11-14 13:20:29,238 Epoch: [24][460/500] Time 0.033 (0.035) Data 0.003 (0.002) Loss 0.1319 (0.1404) Prec@1 76.000 (75.255) Prec@5 99.000 (97.915) +2022-11-14 13:20:29,640 Epoch: [24][470/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1279 (0.1401) Prec@1 78.000 (75.312) Prec@5 97.000 (97.896) +2022-11-14 13:20:30,058 Epoch: [24][480/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.1287 (0.1399) Prec@1 76.000 (75.327) Prec@5 100.000 (97.939) +2022-11-14 13:20:30,454 Epoch: [24][490/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.1385 (0.1399) Prec@1 72.000 (75.260) Prec@5 98.000 (97.940) +2022-11-14 13:20:30,818 Epoch: [24][499/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1887 (0.1408) Prec@1 65.000 (75.059) Prec@5 95.000 (97.882) +2022-11-14 13:20:31,098 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1356 (0.1356) Prec@1 79.000 (79.000) Prec@5 95.000 (95.000) +2022-11-14 13:20:31,109 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1532 (0.1444) Prec@1 69.000 (74.000) Prec@5 99.000 (97.000) +2022-11-14 13:20:31,122 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1479 (0.1455) Prec@1 72.000 (73.333) Prec@5 96.000 (96.667) +2022-11-14 13:20:31,133 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1342 (0.1427) Prec@1 80.000 (75.000) Prec@5 100.000 (97.500) +2022-11-14 13:20:31,142 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1413 (0.1424) Prec@1 75.000 (75.000) Prec@5 98.000 (97.600) +2022-11-14 13:20:31,152 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.1362) Prec@1 80.000 (75.833) Prec@5 100.000 (98.000) +2022-11-14 13:20:31,163 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1503 (0.1382) Prec@1 73.000 (75.429) Prec@5 100.000 (98.286) +2022-11-14 13:20:31,173 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1729 (0.1426) Prec@1 70.000 (74.750) Prec@5 97.000 (98.125) +2022-11-14 13:20:31,182 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1759 (0.1463) Prec@1 70.000 (74.222) Prec@5 96.000 (97.889) +2022-11-14 13:20:31,192 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1174 (0.1434) Prec@1 77.000 (74.500) Prec@5 96.000 (97.700) +2022-11-14 13:20:31,202 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1223 (0.1415) Prec@1 79.000 (74.909) Prec@5 99.000 (97.818) +2022-11-14 13:20:31,212 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1629 (0.1432) Prec@1 71.000 (74.583) Prec@5 98.000 (97.833) +2022-11-14 13:20:31,221 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1289 (0.1421) Prec@1 76.000 (74.692) Prec@5 98.000 (97.846) +2022-11-14 13:20:31,233 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1209 (0.1406) Prec@1 77.000 (74.857) Prec@5 100.000 (98.000) +2022-11-14 13:20:31,243 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1394 (0.1405) Prec@1 75.000 (74.867) Prec@5 100.000 (98.133) +2022-11-14 13:20:31,253 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1629 (0.1419) Prec@1 70.000 (74.562) Prec@5 97.000 (98.062) +2022-11-14 13:20:31,262 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.1396) Prec@1 83.000 (75.059) Prec@5 97.000 (98.000) +2022-11-14 13:20:31,273 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1398 (0.1396) Prec@1 78.000 (75.222) Prec@5 98.000 (98.000) +2022-11-14 13:20:31,284 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1294 (0.1391) Prec@1 77.000 (75.316) Prec@5 97.000 (97.947) +2022-11-14 13:20:31,293 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1589 (0.1401) Prec@1 73.000 (75.200) Prec@5 98.000 (97.950) +2022-11-14 13:20:31,302 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1623 (0.1411) Prec@1 71.000 (75.000) Prec@5 97.000 (97.905) +2022-11-14 13:20:31,313 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1355 (0.1409) Prec@1 75.000 (75.000) Prec@5 98.000 (97.909) +2022-11-14 13:20:31,323 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1284 (0.1403) Prec@1 78.000 (75.130) Prec@5 98.000 (97.913) +2022-11-14 13:20:31,334 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1233 (0.1396) Prec@1 78.000 (75.250) Prec@5 98.000 (97.917) +2022-11-14 13:20:31,343 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1618 (0.1405) Prec@1 70.000 (75.040) Prec@5 96.000 (97.840) +2022-11-14 13:20:31,355 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1805 (0.1421) Prec@1 69.000 (74.808) Prec@5 93.000 (97.654) +2022-11-14 13:20:31,366 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1574 (0.1426) Prec@1 72.000 (74.704) Prec@5 99.000 (97.704) +2022-11-14 13:20:31,376 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1397 (0.1425) Prec@1 74.000 (74.679) Prec@5 98.000 (97.714) +2022-11-14 13:20:31,385 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1276 (0.1420) Prec@1 80.000 (74.862) Prec@5 95.000 (97.621) +2022-11-14 13:20:31,396 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1506 (0.1423) Prec@1 69.000 (74.667) Prec@5 96.000 (97.567) +2022-11-14 13:20:31,408 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1338 (0.1420) Prec@1 75.000 (74.677) Prec@5 97.000 (97.548) +2022-11-14 13:20:31,417 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1284 (0.1416) Prec@1 81.000 (74.875) Prec@5 97.000 (97.531) +2022-11-14 13:20:31,427 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1597 (0.1421) Prec@1 72.000 (74.788) Prec@5 91.000 (97.333) +2022-11-14 13:20:31,438 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1621 (0.1427) Prec@1 72.000 (74.706) Prec@5 95.000 (97.265) +2022-11-14 13:20:31,449 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1531 (0.1430) Prec@1 71.000 (74.600) Prec@5 96.000 (97.229) +2022-11-14 13:20:31,459 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1219 (0.1424) Prec@1 76.000 (74.639) Prec@5 97.000 (97.222) +2022-11-14 13:20:31,468 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1653 (0.1431) Prec@1 71.000 (74.541) Prec@5 93.000 (97.108) +2022-11-14 13:20:31,480 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1604 (0.1435) Prec@1 72.000 (74.474) Prec@5 96.000 (97.079) +2022-11-14 13:20:31,491 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1413 (0.1435) Prec@1 74.000 (74.462) Prec@5 99.000 (97.128) +2022-11-14 13:20:31,500 Test: [39/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.1425) Prec@1 80.000 (74.600) Prec@5 100.000 (97.200) +2022-11-14 13:20:31,509 Test: [40/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1322 (0.1423) Prec@1 78.000 (74.683) Prec@5 97.000 (97.195) +2022-11-14 13:20:31,520 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1460 (0.1424) Prec@1 76.000 (74.714) Prec@5 96.000 (97.167) +2022-11-14 13:20:31,531 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.1418) Prec@1 78.000 (74.791) Prec@5 99.000 (97.209) +2022-11-14 13:20:31,540 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1290 (0.1415) Prec@1 75.000 (74.795) Prec@5 97.000 (97.205) +2022-11-14 13:20:31,549 Test: [44/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1356 (0.1414) Prec@1 73.000 (74.756) Prec@5 98.000 (97.222) +2022-11-14 13:20:31,561 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1575 (0.1417) Prec@1 70.000 (74.652) Prec@5 98.000 (97.239) +2022-11-14 13:20:31,571 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1357 (0.1416) Prec@1 79.000 (74.745) Prec@5 96.000 (97.213) +2022-11-14 13:20:31,580 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1103 (0.1410) Prec@1 78.000 (74.812) Prec@5 99.000 (97.250) +2022-11-14 13:20:31,588 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1103 (0.1403) Prec@1 84.000 (75.000) Prec@5 99.000 (97.286) +2022-11-14 13:20:31,600 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1421 (0.1404) Prec@1 77.000 (75.040) Prec@5 98.000 (97.300) +2022-11-14 13:20:31,610 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1399) Prec@1 78.000 (75.098) Prec@5 98.000 (97.314) +2022-11-14 13:20:31,619 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1390 (0.1399) Prec@1 77.000 (75.135) Prec@5 95.000 (97.269) +2022-11-14 13:20:31,628 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.1394) Prec@1 82.000 (75.264) Prec@5 99.000 (97.302) +2022-11-14 13:20:31,639 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1302 (0.1392) Prec@1 77.000 (75.296) Prec@5 97.000 (97.296) +2022-11-14 13:20:31,650 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1480 (0.1394) Prec@1 71.000 (75.218) Prec@5 99.000 (97.327) +2022-11-14 13:20:31,659 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1301 (0.1392) Prec@1 77.000 (75.250) Prec@5 96.000 (97.304) +2022-11-14 13:20:31,668 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1346 (0.1391) Prec@1 77.000 (75.281) Prec@5 97.000 (97.298) +2022-11-14 13:20:31,680 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1437 (0.1392) Prec@1 75.000 (75.276) Prec@5 99.000 (97.328) +2022-11-14 13:20:31,691 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2019 (0.1403) Prec@1 62.000 (75.051) Prec@5 97.000 (97.322) +2022-11-14 13:20:31,700 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1309 (0.1401) Prec@1 75.000 (75.050) Prec@5 96.000 (97.300) +2022-11-14 13:20:31,709 Test: [60/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1591 (0.1404) Prec@1 71.000 (74.984) Prec@5 97.000 (97.295) +2022-11-14 13:20:31,721 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1348 (0.1403) Prec@1 81.000 (75.081) Prec@5 97.000 (97.290) +2022-11-14 13:20:31,731 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1371 (0.1403) Prec@1 75.000 (75.079) Prec@5 99.000 (97.317) +2022-11-14 13:20:31,740 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1358 (0.1402) Prec@1 78.000 (75.125) Prec@5 99.000 (97.344) +2022-11-14 13:20:31,748 Test: [64/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1667 (0.1406) Prec@1 70.000 (75.046) Prec@5 99.000 (97.369) +2022-11-14 13:20:31,760 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1637 (0.1410) Prec@1 72.000 (75.000) Prec@5 100.000 (97.409) +2022-11-14 13:20:31,771 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1270 (0.1408) Prec@1 81.000 (75.090) Prec@5 99.000 (97.433) +2022-11-14 13:20:31,781 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1985 (0.1416) Prec@1 65.000 (74.941) Prec@5 97.000 (97.426) +2022-11-14 13:20:31,789 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.1412) Prec@1 80.000 (75.014) Prec@5 97.000 (97.420) +2022-11-14 13:20:31,801 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1537 (0.1413) Prec@1 70.000 (74.943) Prec@5 98.000 (97.429) +2022-11-14 13:20:31,812 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1263 (0.1411) Prec@1 79.000 (75.000) Prec@5 99.000 (97.451) +2022-11-14 13:20:31,820 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.1408) Prec@1 84.000 (75.125) Prec@5 98.000 (97.458) +2022-11-14 13:20:31,828 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1404 (0.1408) Prec@1 75.000 (75.123) Prec@5 98.000 (97.466) +2022-11-14 13:20:31,839 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1172 (0.1404) Prec@1 80.000 (75.189) Prec@5 98.000 (97.473) +2022-11-14 13:20:31,849 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1696 (0.1408) Prec@1 71.000 (75.133) Prec@5 95.000 (97.440) +2022-11-14 13:20:31,857 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1465 (0.1409) Prec@1 74.000 (75.118) Prec@5 98.000 (97.447) +2022-11-14 13:20:31,865 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1665 (0.1412) Prec@1 70.000 (75.052) Prec@5 94.000 (97.403) +2022-11-14 13:20:31,877 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1138 (0.1409) Prec@1 84.000 (75.167) Prec@5 97.000 (97.397) +2022-11-14 13:20:31,887 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1471 (0.1410) Prec@1 69.000 (75.089) Prec@5 98.000 (97.405) +2022-11-14 13:20:31,897 Test: [79/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1287 (0.1408) Prec@1 76.000 (75.100) Prec@5 99.000 (97.425) +2022-11-14 13:20:31,905 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1222 (0.1406) Prec@1 80.000 (75.160) Prec@5 97.000 (97.420) +2022-11-14 13:20:31,916 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1431 (0.1406) Prec@1 77.000 (75.183) Prec@5 97.000 (97.415) +2022-11-14 13:20:31,927 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1242 (0.1404) Prec@1 75.000 (75.181) Prec@5 98.000 (97.422) +2022-11-14 13:20:31,936 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1612 (0.1407) Prec@1 68.000 (75.095) Prec@5 98.000 (97.429) +2022-11-14 13:20:31,945 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1408) Prec@1 73.000 (75.071) Prec@5 98.000 (97.435) +2022-11-14 13:20:31,957 Test: [85/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1357 (0.1407) Prec@1 77.000 (75.093) Prec@5 95.000 (97.407) +2022-11-14 13:20:31,968 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1744 (0.1411) Prec@1 67.000 (75.000) Prec@5 96.000 (97.391) +2022-11-14 13:20:31,976 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1234 (0.1409) Prec@1 80.000 (75.057) Prec@5 98.000 (97.398) +2022-11-14 13:20:31,984 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1528 (0.1410) Prec@1 71.000 (75.011) Prec@5 93.000 (97.348) +2022-11-14 13:20:31,996 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1582 (0.1412) Prec@1 76.000 (75.022) Prec@5 98.000 (97.356) +2022-11-14 13:20:32,007 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1434 (0.1412) Prec@1 78.000 (75.055) Prec@5 98.000 (97.363) +2022-11-14 13:20:32,017 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1262 (0.1411) Prec@1 80.000 (75.109) Prec@5 95.000 (97.337) +2022-11-14 13:20:32,025 Test: [92/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1773 (0.1415) Prec@1 69.000 (75.043) Prec@5 96.000 (97.323) +2022-11-14 13:20:32,035 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1276 (0.1413) Prec@1 77.000 (75.064) Prec@5 98.000 (97.330) +2022-11-14 13:20:32,045 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1349 (0.1412) Prec@1 77.000 (75.084) Prec@5 99.000 (97.347) +2022-11-14 13:20:32,054 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.1410) Prec@1 79.000 (75.125) Prec@5 97.000 (97.344) +2022-11-14 13:20:32,063 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.1407) Prec@1 84.000 (75.216) Prec@5 99.000 (97.361) +2022-11-14 13:20:32,072 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1743 (0.1410) Prec@1 71.000 (75.173) Prec@5 96.000 (97.347) +2022-11-14 13:20:32,081 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1371 (0.1410) Prec@1 80.000 (75.222) Prec@5 98.000 (97.354) +2022-11-14 13:20:32,090 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1411) Prec@1 70.000 (75.170) Prec@5 98.000 (97.360) +2022-11-14 13:20:32,143 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:20:32,447 Epoch: [25][0/500] Time 0.024 (0.024) Data 0.224 (0.224) Loss 0.1302 (0.1302) Prec@1 77.000 (77.000) Prec@5 97.000 (97.000) +2022-11-14 13:20:32,648 Epoch: [25][10/500] Time 0.017 (0.018) Data 0.001 (0.022) Loss 0.1591 (0.1446) Prec@1 71.000 (74.000) Prec@5 94.000 (95.500) +2022-11-14 13:20:32,855 Epoch: [25][20/500] Time 0.016 (0.018) Data 0.002 (0.012) Loss 0.1451 (0.1448) Prec@1 74.000 (74.000) Prec@5 96.000 (95.667) +2022-11-14 13:20:33,063 Epoch: [25][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.1488 (0.1458) Prec@1 70.000 (73.000) Prec@5 98.000 (96.250) +2022-11-14 13:20:33,288 Epoch: [25][40/500] Time 0.017 (0.019) Data 0.002 (0.007) Loss 0.1168 (0.1400) Prec@1 79.000 (74.200) Prec@5 100.000 (97.000) +2022-11-14 13:20:33,589 Epoch: [25][50/500] Time 0.026 (0.020) Data 0.002 (0.006) Loss 0.1595 (0.1433) Prec@1 70.000 (73.500) Prec@5 99.000 (97.333) +2022-11-14 13:20:33,913 Epoch: [25][60/500] Time 0.037 (0.022) Data 0.002 (0.005) Loss 0.1133 (0.1390) Prec@1 81.000 (74.571) Prec@5 98.000 (97.429) +2022-11-14 13:20:34,228 Epoch: [25][70/500] Time 0.029 (0.022) Data 0.001 (0.005) Loss 0.1532 (0.1408) Prec@1 72.000 (74.250) Prec@5 100.000 (97.750) +2022-11-14 13:20:34,548 Epoch: [25][80/500] Time 0.029 (0.023) Data 0.002 (0.005) Loss 0.1479 (0.1416) Prec@1 77.000 (74.556) Prec@5 99.000 (97.889) +2022-11-14 13:20:34,868 Epoch: [25][90/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.1179 (0.1392) Prec@1 79.000 (75.000) Prec@5 98.000 (97.900) +2022-11-14 13:20:35,190 Epoch: [25][100/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.1432 (0.1396) Prec@1 72.000 (74.727) Prec@5 99.000 (98.000) +2022-11-14 13:20:35,510 Epoch: [25][110/500] Time 0.024 (0.025) Data 0.003 (0.004) Loss 0.1430 (0.1398) Prec@1 73.000 (74.583) Prec@5 93.000 (97.583) +2022-11-14 13:20:35,826 Epoch: [25][120/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.1109 (0.1376) Prec@1 78.000 (74.846) Prec@5 99.000 (97.692) +2022-11-14 13:20:36,142 Epoch: [25][130/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.1568 (0.1390) Prec@1 76.000 (74.929) Prec@5 98.000 (97.714) +2022-11-14 13:20:36,458 Epoch: [25][140/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.1322 (0.1385) Prec@1 77.000 (75.067) Prec@5 94.000 (97.467) +2022-11-14 13:20:36,778 Epoch: [25][150/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.1197 (0.1374) Prec@1 78.000 (75.250) Prec@5 99.000 (97.562) +2022-11-14 13:20:37,099 Epoch: [25][160/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1321 (0.1370) Prec@1 78.000 (75.412) Prec@5 99.000 (97.647) +2022-11-14 13:20:37,420 Epoch: [25][170/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.1258 (0.1364) Prec@1 80.000 (75.667) Prec@5 98.000 (97.667) +2022-11-14 13:20:37,735 Epoch: [25][180/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1375 (0.1365) Prec@1 78.000 (75.789) Prec@5 95.000 (97.526) +2022-11-14 13:20:38,051 Epoch: [25][190/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1280 (0.1361) Prec@1 77.000 (75.850) Prec@5 96.000 (97.450) +2022-11-14 13:20:38,367 Epoch: [25][200/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.1241 (0.1355) Prec@1 77.000 (75.905) Prec@5 99.000 (97.524) +2022-11-14 13:20:38,684 Epoch: [25][210/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1438 (0.1359) Prec@1 78.000 (76.000) Prec@5 94.000 (97.364) +2022-11-14 13:20:38,994 Epoch: [25][220/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1192 (0.1351) Prec@1 79.000 (76.130) Prec@5 98.000 (97.391) +2022-11-14 13:20:39,309 Epoch: [25][230/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0994 (0.1336) Prec@1 84.000 (76.458) Prec@5 99.000 (97.458) +2022-11-14 13:20:39,627 Epoch: [25][240/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0947 (0.1321) Prec@1 85.000 (76.800) Prec@5 100.000 (97.560) +2022-11-14 13:20:39,948 Epoch: [25][250/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.1295 (0.1320) Prec@1 78.000 (76.846) Prec@5 98.000 (97.577) +2022-11-14 13:20:40,268 Epoch: [25][260/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.1747 (0.1336) Prec@1 71.000 (76.630) Prec@5 94.000 (97.444) +2022-11-14 13:20:40,587 Epoch: [25][270/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1282 (0.1334) Prec@1 77.000 (76.643) Prec@5 98.000 (97.464) +2022-11-14 13:20:40,907 Epoch: [25][280/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1198 (0.1329) Prec@1 75.000 (76.586) Prec@5 99.000 (97.517) +2022-11-14 13:20:41,231 Epoch: [25][290/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1224 (0.1326) Prec@1 77.000 (76.600) Prec@5 98.000 (97.533) +2022-11-14 13:20:41,551 Epoch: [25][300/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.1245 (0.1323) Prec@1 79.000 (76.677) Prec@5 98.000 (97.548) +2022-11-14 13:20:41,871 Epoch: [25][310/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.1180 (0.1319) Prec@1 77.000 (76.688) Prec@5 99.000 (97.594) +2022-11-14 13:20:42,199 Epoch: [25][320/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1314 (0.1318) Prec@1 75.000 (76.636) Prec@5 99.000 (97.636) +2022-11-14 13:20:42,522 Epoch: [25][330/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1444 (0.1322) Prec@1 75.000 (76.588) Prec@5 97.000 (97.618) +2022-11-14 13:20:42,843 Epoch: [25][340/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.1362 (0.1323) Prec@1 77.000 (76.600) Prec@5 97.000 (97.600) +2022-11-14 13:20:43,162 Epoch: [25][350/500] Time 0.036 (0.027) Data 0.002 (0.002) Loss 0.1482 (0.1328) Prec@1 75.000 (76.556) Prec@5 98.000 (97.611) +2022-11-14 13:20:43,476 Epoch: [25][360/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1361 (0.1329) Prec@1 78.000 (76.595) Prec@5 99.000 (97.649) +2022-11-14 13:20:43,793 Epoch: [25][370/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1261 (0.1327) Prec@1 78.000 (76.632) Prec@5 99.000 (97.684) +2022-11-14 13:20:44,110 Epoch: [25][380/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.1341 (0.1327) Prec@1 76.000 (76.615) Prec@5 96.000 (97.641) +2022-11-14 13:20:44,441 Epoch: [25][390/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1286 (0.1326) Prec@1 76.000 (76.600) Prec@5 98.000 (97.650) +2022-11-14 13:20:44,761 Epoch: [25][400/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1291 (0.1325) Prec@1 79.000 (76.659) Prec@5 98.000 (97.659) +2022-11-14 13:20:45,080 Epoch: [25][410/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1471 (0.1329) Prec@1 73.000 (76.571) Prec@5 97.000 (97.643) +2022-11-14 13:20:45,398 Epoch: [25][420/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1333 (0.1329) Prec@1 78.000 (76.605) Prec@5 97.000 (97.628) +2022-11-14 13:20:45,717 Epoch: [25][430/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.1804 (0.1340) Prec@1 69.000 (76.432) Prec@5 97.000 (97.614) +2022-11-14 13:20:46,035 Epoch: [25][440/500] Time 0.030 (0.027) Data 0.001 (0.002) Loss 0.1345 (0.1340) Prec@1 80.000 (76.511) Prec@5 100.000 (97.667) +2022-11-14 13:20:46,357 Epoch: [25][450/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1391 (0.1341) Prec@1 75.000 (76.478) Prec@5 98.000 (97.674) +2022-11-14 13:20:46,674 Epoch: [25][460/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1604 (0.1346) Prec@1 71.000 (76.362) Prec@5 98.000 (97.681) +2022-11-14 13:20:46,996 Epoch: [25][470/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1238 (0.1344) Prec@1 81.000 (76.458) Prec@5 98.000 (97.688) +2022-11-14 13:20:47,321 Epoch: [25][480/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.1399 (0.1345) Prec@1 74.000 (76.408) Prec@5 98.000 (97.694) +2022-11-14 13:20:47,640 Epoch: [25][490/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1658 (0.1352) Prec@1 73.000 (76.340) Prec@5 94.000 (97.620) +2022-11-14 13:20:47,929 Epoch: [25][499/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.1221 (0.1349) Prec@1 79.000 (76.392) Prec@5 99.000 (97.647) +2022-11-14 13:20:48,211 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1803 (0.1803) Prec@1 67.000 (67.000) Prec@5 97.000 (97.000) +2022-11-14 13:20:48,222 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1914 (0.1858) Prec@1 63.000 (65.000) Prec@5 96.000 (96.500) +2022-11-14 13:20:48,231 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1833 (0.1850) Prec@1 63.000 (64.333) Prec@5 96.000 (96.333) +2022-11-14 13:20:48,241 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1710 (0.1815) Prec@1 69.000 (65.500) Prec@5 96.000 (96.250) +2022-11-14 13:20:48,250 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1592 (0.1770) Prec@1 75.000 (67.400) Prec@5 97.000 (96.400) +2022-11-14 13:20:48,259 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1449 (0.1717) Prec@1 74.000 (68.500) Prec@5 98.000 (96.667) +2022-11-14 13:20:48,267 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1722) Prec@1 70.000 (68.714) Prec@5 95.000 (96.429) +2022-11-14 13:20:48,276 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1829 (0.1735) Prec@1 68.000 (68.625) Prec@5 93.000 (96.000) +2022-11-14 13:20:48,284 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1886 (0.1752) Prec@1 65.000 (68.222) Prec@5 96.000 (96.000) +2022-11-14 13:20:48,292 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1584 (0.1735) Prec@1 69.000 (68.300) Prec@5 96.000 (96.000) +2022-11-14 13:20:48,301 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1477 (0.1711) Prec@1 73.000 (68.727) Prec@5 97.000 (96.091) +2022-11-14 13:20:48,310 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1621 (0.1704) Prec@1 73.000 (69.083) Prec@5 96.000 (96.083) +2022-11-14 13:20:48,320 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1710 (0.1704) Prec@1 63.000 (68.615) Prec@5 98.000 (96.231) +2022-11-14 13:20:48,329 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1801 (0.1711) Prec@1 64.000 (68.286) Prec@5 95.000 (96.143) +2022-11-14 13:20:48,338 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1559 (0.1701) Prec@1 68.000 (68.267) Prec@5 99.000 (96.333) +2022-11-14 13:20:48,348 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2311 (0.1739) Prec@1 59.000 (67.688) Prec@5 92.000 (96.062) +2022-11-14 13:20:48,356 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1372 (0.1718) Prec@1 74.000 (68.059) Prec@5 97.000 (96.118) +2022-11-14 13:20:48,364 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1708) Prec@1 70.000 (68.167) Prec@5 97.000 (96.167) +2022-11-14 13:20:48,372 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1718 (0.1708) Prec@1 72.000 (68.368) Prec@5 93.000 (96.000) +2022-11-14 13:20:48,379 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1863 (0.1716) Prec@1 65.000 (68.200) Prec@5 96.000 (96.000) +2022-11-14 13:20:48,387 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1488 (0.1705) Prec@1 73.000 (68.429) Prec@5 98.000 (96.095) +2022-11-14 13:20:48,395 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1557 (0.1698) Prec@1 71.000 (68.545) Prec@5 94.000 (96.000) +2022-11-14 13:20:48,405 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1712 (0.1699) Prec@1 71.000 (68.652) Prec@5 93.000 (95.870) +2022-11-14 13:20:48,413 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1836 (0.1705) Prec@1 66.000 (68.542) Prec@5 93.000 (95.750) +2022-11-14 13:20:48,422 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1695 (0.1704) Prec@1 73.000 (68.720) Prec@5 98.000 (95.840) +2022-11-14 13:20:48,431 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2095 (0.1719) Prec@1 61.000 (68.423) Prec@5 96.000 (95.846) +2022-11-14 13:20:48,439 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1646 (0.1717) Prec@1 72.000 (68.556) Prec@5 95.000 (95.815) +2022-11-14 13:20:48,447 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1617 (0.1713) Prec@1 72.000 (68.679) Prec@5 98.000 (95.893) +2022-11-14 13:20:48,457 Test: [28/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1847 (0.1718) Prec@1 63.000 (68.483) Prec@5 92.000 (95.759) +2022-11-14 13:20:48,467 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1887 (0.1723) Prec@1 65.000 (68.367) Prec@5 93.000 (95.667) +2022-11-14 13:20:48,476 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1832 (0.1727) Prec@1 63.000 (68.194) Prec@5 94.000 (95.613) +2022-11-14 13:20:48,485 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1581 (0.1722) Prec@1 70.000 (68.250) Prec@5 99.000 (95.719) +2022-11-14 13:20:48,495 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1568 (0.1718) Prec@1 71.000 (68.333) Prec@5 96.000 (95.727) +2022-11-14 13:20:48,504 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2119 (0.1729) Prec@1 59.000 (68.059) Prec@5 96.000 (95.735) +2022-11-14 13:20:48,514 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1649 (0.1727) Prec@1 68.000 (68.057) Prec@5 93.000 (95.657) +2022-11-14 13:20:48,524 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1929 (0.1733) Prec@1 67.000 (68.028) Prec@5 98.000 (95.722) +2022-11-14 13:20:48,533 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1831 (0.1735) Prec@1 67.000 (68.000) Prec@5 97.000 (95.757) +2022-11-14 13:20:48,543 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1886 (0.1739) Prec@1 66.000 (67.947) Prec@5 94.000 (95.711) +2022-11-14 13:20:48,552 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1462 (0.1732) Prec@1 71.000 (68.026) Prec@5 97.000 (95.744) +2022-11-14 13:20:48,561 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1701 (0.1731) Prec@1 63.000 (67.900) Prec@5 98.000 (95.800) +2022-11-14 13:20:48,571 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1960 (0.1737) Prec@1 64.000 (67.805) Prec@5 96.000 (95.805) +2022-11-14 13:20:48,580 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1535 (0.1732) Prec@1 73.000 (67.929) Prec@5 98.000 (95.857) +2022-11-14 13:20:48,589 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1422 (0.1725) Prec@1 77.000 (68.140) Prec@5 97.000 (95.884) +2022-11-14 13:20:48,599 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1421 (0.1718) Prec@1 74.000 (68.273) Prec@5 94.000 (95.841) +2022-11-14 13:20:48,609 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1715) Prec@1 74.000 (68.400) Prec@5 96.000 (95.844) +2022-11-14 13:20:48,620 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1745 (0.1716) Prec@1 66.000 (68.348) Prec@5 97.000 (95.870) +2022-11-14 13:20:48,631 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1553 (0.1712) Prec@1 71.000 (68.404) Prec@5 100.000 (95.957) +2022-11-14 13:20:48,645 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1710) Prec@1 70.000 (68.438) Prec@5 95.000 (95.938) +2022-11-14 13:20:48,655 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1672 (0.1709) Prec@1 69.000 (68.449) Prec@5 99.000 (96.000) +2022-11-14 13:20:48,664 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1794 (0.1711) Prec@1 68.000 (68.440) Prec@5 92.000 (95.920) +2022-11-14 13:20:48,674 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1633 (0.1709) Prec@1 68.000 (68.431) Prec@5 97.000 (95.941) +2022-11-14 13:20:48,688 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1795 (0.1711) Prec@1 68.000 (68.423) Prec@5 94.000 (95.904) +2022-11-14 13:20:48,699 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1659 (0.1710) Prec@1 69.000 (68.434) Prec@5 97.000 (95.925) +2022-11-14 13:20:48,712 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1568 (0.1707) Prec@1 68.000 (68.426) Prec@5 95.000 (95.907) +2022-11-14 13:20:48,726 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1754 (0.1708) Prec@1 70.000 (68.455) Prec@5 97.000 (95.927) +2022-11-14 13:20:48,738 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1745 (0.1709) Prec@1 69.000 (68.464) Prec@5 97.000 (95.946) +2022-11-14 13:20:48,754 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1822 (0.1711) Prec@1 64.000 (68.386) Prec@5 99.000 (96.000) +2022-11-14 13:20:48,770 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1965 (0.1715) Prec@1 60.000 (68.241) Prec@5 98.000 (96.034) +2022-11-14 13:20:48,785 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1916 (0.1719) Prec@1 68.000 (68.237) Prec@5 94.000 (96.000) +2022-11-14 13:20:48,800 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1778 (0.1720) Prec@1 67.000 (68.217) Prec@5 97.000 (96.017) +2022-11-14 13:20:48,815 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1811 (0.1721) Prec@1 70.000 (68.246) Prec@5 97.000 (96.033) +2022-11-14 13:20:48,829 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1582 (0.1719) Prec@1 71.000 (68.290) Prec@5 98.000 (96.065) +2022-11-14 13:20:48,844 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1630 (0.1718) Prec@1 72.000 (68.349) Prec@5 93.000 (96.016) +2022-11-14 13:20:48,859 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1620 (0.1716) Prec@1 72.000 (68.406) Prec@5 97.000 (96.031) +2022-11-14 13:20:48,875 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1963 (0.1720) Prec@1 66.000 (68.369) Prec@5 93.000 (95.985) +2022-11-14 13:20:48,890 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1995 (0.1724) Prec@1 62.000 (68.273) Prec@5 95.000 (95.970) +2022-11-14 13:20:48,904 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1680 (0.1723) Prec@1 70.000 (68.299) Prec@5 96.000 (95.970) +2022-11-14 13:20:48,919 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2088 (0.1729) Prec@1 61.000 (68.191) Prec@5 99.000 (96.015) +2022-11-14 13:20:48,935 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1497 (0.1725) Prec@1 72.000 (68.246) Prec@5 96.000 (96.014) +2022-11-14 13:20:48,950 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1871 (0.1727) Prec@1 64.000 (68.186) Prec@5 93.000 (95.971) +2022-11-14 13:20:48,965 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2022 (0.1732) Prec@1 65.000 (68.141) Prec@5 98.000 (96.000) +2022-11-14 13:20:48,980 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1442 (0.1728) Prec@1 75.000 (68.236) Prec@5 98.000 (96.028) +2022-11-14 13:20:48,995 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1594 (0.1726) Prec@1 77.000 (68.356) Prec@5 95.000 (96.014) +2022-11-14 13:20:49,009 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1733 (0.1726) Prec@1 67.000 (68.338) Prec@5 97.000 (96.027) +2022-11-14 13:20:49,024 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1686 (0.1725) Prec@1 71.000 (68.373) Prec@5 95.000 (96.013) +2022-11-14 13:20:49,040 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2030 (0.1729) Prec@1 62.000 (68.289) Prec@5 99.000 (96.053) +2022-11-14 13:20:49,056 Test: [76/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1649 (0.1728) Prec@1 67.000 (68.273) Prec@5 96.000 (96.052) +2022-11-14 13:20:49,071 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1395 (0.1724) Prec@1 74.000 (68.346) Prec@5 96.000 (96.051) +2022-11-14 13:20:49,086 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1668 (0.1723) Prec@1 68.000 (68.342) Prec@5 96.000 (96.051) +2022-11-14 13:20:49,098 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1591 (0.1722) Prec@1 69.000 (68.350) Prec@5 98.000 (96.075) +2022-11-14 13:20:49,110 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1750 (0.1722) Prec@1 68.000 (68.346) Prec@5 92.000 (96.025) +2022-11-14 13:20:49,126 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1862 (0.1724) Prec@1 65.000 (68.305) Prec@5 96.000 (96.024) +2022-11-14 13:20:49,142 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1700 (0.1723) Prec@1 70.000 (68.325) Prec@5 95.000 (96.012) +2022-11-14 13:20:49,157 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1721) Prec@1 71.000 (68.357) Prec@5 97.000 (96.024) +2022-11-14 13:20:49,173 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1527 (0.1719) Prec@1 72.000 (68.400) Prec@5 97.000 (96.035) +2022-11-14 13:20:49,189 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1815 (0.1720) Prec@1 64.000 (68.349) Prec@5 94.000 (96.012) +2022-11-14 13:20:49,203 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2070 (0.1724) Prec@1 58.000 (68.230) Prec@5 96.000 (96.011) +2022-11-14 13:20:49,216 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1887 (0.1726) Prec@1 67.000 (68.216) Prec@5 93.000 (95.977) +2022-11-14 13:20:49,232 Test: [88/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1780 (0.1726) Prec@1 66.000 (68.191) Prec@5 95.000 (95.966) +2022-11-14 13:20:49,245 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1921 (0.1729) Prec@1 62.000 (68.122) Prec@5 95.000 (95.956) +2022-11-14 13:20:49,259 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1833 (0.1730) Prec@1 67.000 (68.110) Prec@5 95.000 (95.945) +2022-11-14 13:20:49,274 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1456 (0.1727) Prec@1 72.000 (68.152) Prec@5 98.000 (95.967) +2022-11-14 13:20:49,287 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1875 (0.1728) Prec@1 68.000 (68.151) Prec@5 93.000 (95.935) +2022-11-14 13:20:49,299 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1693 (0.1728) Prec@1 69.000 (68.160) Prec@5 97.000 (95.947) +2022-11-14 13:20:49,315 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1874 (0.1730) Prec@1 65.000 (68.126) Prec@5 98.000 (95.968) +2022-11-14 13:20:49,328 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1681 (0.1729) Prec@1 67.000 (68.115) Prec@5 98.000 (95.990) +2022-11-14 13:20:49,341 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1647 (0.1728) Prec@1 69.000 (68.124) Prec@5 97.000 (96.000) +2022-11-14 13:20:49,356 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2170 (0.1733) Prec@1 59.000 (68.031) Prec@5 94.000 (95.980) +2022-11-14 13:20:49,370 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1612 (0.1731) Prec@1 68.000 (68.030) Prec@5 95.000 (95.970) +2022-11-14 13:20:49,383 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1737 (0.1732) Prec@1 69.000 (68.040) Prec@5 95.000 (95.960) +2022-11-14 13:20:49,439 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:20:49,748 Epoch: [26][0/500] Time 0.030 (0.030) Data 0.225 (0.225) Loss 0.1101 (0.1101) Prec@1 82.000 (82.000) Prec@5 98.000 (98.000) +2022-11-14 13:20:49,980 Epoch: [26][10/500] Time 0.023 (0.021) Data 0.001 (0.022) Loss 0.1308 (0.1204) Prec@1 74.000 (78.000) Prec@5 100.000 (99.000) +2022-11-14 13:20:50,237 Epoch: [26][20/500] Time 0.023 (0.022) Data 0.002 (0.012) Loss 0.1448 (0.1286) Prec@1 71.000 (75.667) Prec@5 97.000 (98.333) +2022-11-14 13:20:50,498 Epoch: [26][30/500] Time 0.023 (0.022) Data 0.002 (0.009) Loss 0.1269 (0.1282) Prec@1 79.000 (76.500) Prec@5 99.000 (98.500) +2022-11-14 13:20:50,805 Epoch: [26][40/500] Time 0.038 (0.023) Data 0.002 (0.007) Loss 0.1594 (0.1344) Prec@1 75.000 (76.200) Prec@5 99.000 (98.600) +2022-11-14 13:20:51,222 Epoch: [26][50/500] Time 0.038 (0.026) Data 0.002 (0.006) Loss 0.1681 (0.1400) Prec@1 75.000 (76.000) Prec@5 94.000 (97.833) +2022-11-14 13:20:51,662 Epoch: [26][60/500] Time 0.038 (0.028) Data 0.002 (0.005) Loss 0.1287 (0.1384) Prec@1 80.000 (76.571) Prec@5 97.000 (97.714) +2022-11-14 13:20:52,088 Epoch: [26][70/500] Time 0.041 (0.029) Data 0.001 (0.005) Loss 0.1247 (0.1367) Prec@1 76.000 (76.500) Prec@5 99.000 (97.875) +2022-11-14 13:20:52,504 Epoch: [26][80/500] Time 0.046 (0.030) Data 0.002 (0.005) Loss 0.1134 (0.1341) Prec@1 84.000 (77.333) Prec@5 97.000 (97.778) +2022-11-14 13:20:52,927 Epoch: [26][90/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.1172 (0.1324) Prec@1 81.000 (77.700) Prec@5 98.000 (97.800) +2022-11-14 13:20:53,350 Epoch: [26][100/500] Time 0.039 (0.032) Data 0.001 (0.004) Loss 0.1314 (0.1323) Prec@1 76.000 (77.545) Prec@5 98.000 (97.818) +2022-11-14 13:20:53,762 Epoch: [26][110/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.1667 (0.1352) Prec@1 68.000 (76.750) Prec@5 99.000 (97.917) +2022-11-14 13:20:54,180 Epoch: [26][120/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.1325 (0.1350) Prec@1 83.000 (77.231) Prec@5 96.000 (97.769) +2022-11-14 13:20:54,598 Epoch: [26][130/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.1457 (0.1357) Prec@1 75.000 (77.071) Prec@5 97.000 (97.714) +2022-11-14 13:20:55,028 Epoch: [26][140/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.1060 (0.1337) Prec@1 84.000 (77.533) Prec@5 99.000 (97.800) +2022-11-14 13:20:55,450 Epoch: [26][150/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1557 (0.1351) Prec@1 72.000 (77.188) Prec@5 96.000 (97.688) +2022-11-14 13:20:55,867 Epoch: [26][160/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1603 (0.1366) Prec@1 70.000 (76.765) Prec@5 97.000 (97.647) +2022-11-14 13:20:56,274 Epoch: [26][170/500] Time 0.041 (0.034) Data 0.001 (0.003) Loss 0.1380 (0.1367) Prec@1 74.000 (76.611) Prec@5 99.000 (97.722) +2022-11-14 13:20:56,693 Epoch: [26][180/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1408 (0.1369) Prec@1 75.000 (76.526) Prec@5 98.000 (97.737) +2022-11-14 13:20:57,114 Epoch: [26][190/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.1383 (0.1370) Prec@1 72.000 (76.300) Prec@5 97.000 (97.700) +2022-11-14 13:20:57,533 Epoch: [26][200/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1750 (0.1388) Prec@1 68.000 (75.905) Prec@5 93.000 (97.476) +2022-11-14 13:20:57,949 Epoch: [26][210/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1047 (0.1372) Prec@1 83.000 (76.227) Prec@5 96.000 (97.409) +2022-11-14 13:20:58,374 Epoch: [26][220/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.1437 (0.1375) Prec@1 78.000 (76.304) Prec@5 98.000 (97.435) +2022-11-14 13:20:58,791 Epoch: [26][230/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.1371 (0.1375) Prec@1 74.000 (76.208) Prec@5 98.000 (97.458) +2022-11-14 13:20:59,199 Epoch: [26][240/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1357 (0.1374) Prec@1 74.000 (76.120) Prec@5 100.000 (97.560) +2022-11-14 13:20:59,613 Epoch: [26][250/500] Time 0.039 (0.035) Data 0.001 (0.003) Loss 0.1250 (0.1369) Prec@1 77.000 (76.154) Prec@5 100.000 (97.654) +2022-11-14 13:21:00,030 Epoch: [26][260/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1203 (0.1363) Prec@1 79.000 (76.259) Prec@5 100.000 (97.741) +2022-11-14 13:21:00,437 Epoch: [26][270/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.1157 (0.1356) Prec@1 77.000 (76.286) Prec@5 100.000 (97.821) +2022-11-14 13:21:00,851 Epoch: [26][280/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.1261 (0.1353) Prec@1 72.000 (76.138) Prec@5 97.000 (97.793) +2022-11-14 13:21:01,264 Epoch: [26][290/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.1358 (0.1353) Prec@1 75.000 (76.100) Prec@5 99.000 (97.833) +2022-11-14 13:21:01,692 Epoch: [26][300/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.1233 (0.1349) Prec@1 81.000 (76.258) Prec@5 98.000 (97.839) +2022-11-14 13:21:02,103 Epoch: [26][310/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1321 (0.1348) Prec@1 80.000 (76.375) Prec@5 97.000 (97.812) +2022-11-14 13:21:02,521 Epoch: [26][320/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1468 (0.1352) Prec@1 73.000 (76.273) Prec@5 97.000 (97.788) +2022-11-14 13:21:02,945 Epoch: [26][330/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1128 (0.1345) Prec@1 80.000 (76.382) Prec@5 96.000 (97.735) +2022-11-14 13:21:03,362 Epoch: [26][340/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.1451 (0.1348) Prec@1 75.000 (76.343) Prec@5 97.000 (97.714) +2022-11-14 13:21:03,778 Epoch: [26][350/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1313 (0.1347) Prec@1 78.000 (76.389) Prec@5 97.000 (97.694) +2022-11-14 13:21:04,198 Epoch: [26][360/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.1087 (0.1340) Prec@1 81.000 (76.514) Prec@5 97.000 (97.676) +2022-11-14 13:21:04,615 Epoch: [26][370/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1030 (0.1332) Prec@1 81.000 (76.632) Prec@5 98.000 (97.684) +2022-11-14 13:21:05,029 Epoch: [26][380/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.1443 (0.1335) Prec@1 71.000 (76.487) Prec@5 98.000 (97.692) +2022-11-14 13:21:05,505 Epoch: [26][390/500] Time 0.053 (0.036) Data 0.002 (0.002) Loss 0.1277 (0.1333) Prec@1 77.000 (76.500) Prec@5 99.000 (97.725) +2022-11-14 13:21:05,932 Epoch: [26][400/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.1108 (0.1328) Prec@1 82.000 (76.634) Prec@5 98.000 (97.732) +2022-11-14 13:21:06,341 Epoch: [26][410/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.1163 (0.1324) Prec@1 81.000 (76.738) Prec@5 97.000 (97.714) +2022-11-14 13:21:06,811 Epoch: [26][420/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1582 (0.1330) Prec@1 72.000 (76.628) Prec@5 97.000 (97.698) +2022-11-14 13:21:07,214 Epoch: [26][430/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.1227 (0.1328) Prec@1 84.000 (76.795) Prec@5 99.000 (97.727) +2022-11-14 13:21:07,650 Epoch: [26][440/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.1594 (0.1333) Prec@1 70.000 (76.644) Prec@5 97.000 (97.711) +2022-11-14 13:21:08,194 Epoch: [26][450/500] Time 0.051 (0.036) Data 0.002 (0.002) Loss 0.1469 (0.1336) Prec@1 73.000 (76.565) Prec@5 97.000 (97.696) +2022-11-14 13:21:08,625 Epoch: [26][460/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.1441 (0.1339) Prec@1 73.000 (76.489) Prec@5 97.000 (97.681) +2022-11-14 13:21:09,075 Epoch: [26][470/500] Time 0.053 (0.036) Data 0.002 (0.002) Loss 0.1045 (0.1333) Prec@1 84.000 (76.646) Prec@5 99.000 (97.708) +2022-11-14 13:21:09,515 Epoch: [26][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1246 (0.1331) Prec@1 76.000 (76.633) Prec@5 98.000 (97.714) +2022-11-14 13:21:09,970 Epoch: [26][490/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1702 (0.1338) Prec@1 71.000 (76.520) Prec@5 98.000 (97.720) +2022-11-14 13:21:10,339 Epoch: [26][499/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1384 (0.1339) Prec@1 76.000 (76.510) Prec@5 94.000 (97.647) +2022-11-14 13:21:10,628 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1752 (0.1752) Prec@1 67.000 (67.000) Prec@5 91.000 (91.000) +2022-11-14 13:21:10,636 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1958 (0.1855) Prec@1 66.000 (66.500) Prec@5 91.000 (91.000) +2022-11-14 13:21:10,644 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2367 (0.2026) Prec@1 56.000 (63.000) Prec@5 96.000 (92.667) +2022-11-14 13:21:10,655 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1823 (0.1975) Prec@1 65.000 (63.500) Prec@5 96.000 (93.500) +2022-11-14 13:21:10,663 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2152 (0.2011) Prec@1 60.000 (62.800) Prec@5 91.000 (93.000) +2022-11-14 13:21:10,670 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2048 (0.2017) Prec@1 66.000 (63.333) Prec@5 95.000 (93.333) +2022-11-14 13:21:10,678 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2172 (0.2039) Prec@1 59.000 (62.714) Prec@5 91.000 (93.000) +2022-11-14 13:21:10,688 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1955 (0.2028) Prec@1 66.000 (63.125) Prec@5 96.000 (93.375) +2022-11-14 13:21:10,697 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2234 (0.2051) Prec@1 58.000 (62.556) Prec@5 93.000 (93.333) +2022-11-14 13:21:10,707 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1462 (0.1992) Prec@1 73.000 (63.600) Prec@5 94.000 (93.400) +2022-11-14 13:21:10,717 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1744 (0.1970) Prec@1 71.000 (64.273) Prec@5 96.000 (93.636) +2022-11-14 13:21:10,726 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1758 (0.1952) Prec@1 69.000 (64.667) Prec@5 90.000 (93.333) +2022-11-14 13:21:10,736 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2102 (0.1964) Prec@1 57.000 (64.077) Prec@5 92.000 (93.231) +2022-11-14 13:21:10,745 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2495 (0.2002) Prec@1 56.000 (63.500) Prec@5 91.000 (93.071) +2022-11-14 13:21:10,754 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1997 (0.2001) Prec@1 64.000 (63.533) Prec@5 95.000 (93.200) +2022-11-14 13:21:10,764 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2508 (0.2033) Prec@1 54.000 (62.938) Prec@5 95.000 (93.312) +2022-11-14 13:21:10,773 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1853 (0.2022) Prec@1 69.000 (63.294) Prec@5 91.000 (93.176) +2022-11-14 13:21:10,785 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2490 (0.2048) Prec@1 57.000 (62.944) Prec@5 92.000 (93.111) +2022-11-14 13:21:10,794 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1895 (0.2040) Prec@1 67.000 (63.158) Prec@5 89.000 (92.895) +2022-11-14 13:21:10,803 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2361 (0.2056) Prec@1 58.000 (62.900) Prec@5 95.000 (93.000) +2022-11-14 13:21:10,813 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2142 (0.2060) Prec@1 64.000 (62.952) Prec@5 93.000 (93.000) +2022-11-14 13:21:10,822 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2139 (0.2064) Prec@1 59.000 (62.773) Prec@5 93.000 (93.000) +2022-11-14 13:21:10,831 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2220 (0.2071) Prec@1 59.000 (62.609) Prec@5 95.000 (93.087) +2022-11-14 13:21:10,841 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2013 (0.2068) Prec@1 66.000 (62.750) Prec@5 90.000 (92.958) +2022-11-14 13:21:10,850 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2118 (0.2070) Prec@1 65.000 (62.840) Prec@5 90.000 (92.840) +2022-11-14 13:21:10,858 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2316 (0.2080) Prec@1 55.000 (62.538) Prec@5 93.000 (92.846) +2022-11-14 13:21:10,867 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2097 (0.2080) Prec@1 66.000 (62.667) Prec@5 95.000 (92.926) +2022-11-14 13:21:10,876 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1993 (0.2077) Prec@1 64.000 (62.714) Prec@5 92.000 (92.893) +2022-11-14 13:21:10,884 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1949 (0.2073) Prec@1 64.000 (62.759) Prec@5 91.000 (92.828) +2022-11-14 13:21:10,893 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2238 (0.2078) Prec@1 62.000 (62.733) Prec@5 94.000 (92.867) +2022-11-14 13:21:10,903 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1977 (0.2075) Prec@1 62.000 (62.710) Prec@5 90.000 (92.774) +2022-11-14 13:21:10,912 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1862 (0.2068) Prec@1 65.000 (62.781) Prec@5 97.000 (92.906) +2022-11-14 13:21:10,921 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2096 (0.2069) Prec@1 61.000 (62.727) Prec@5 89.000 (92.788) +2022-11-14 13:21:10,931 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2362 (0.2078) Prec@1 58.000 (62.588) Prec@5 88.000 (92.647) +2022-11-14 13:21:10,940 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2255 (0.2083) Prec@1 60.000 (62.514) Prec@5 88.000 (92.514) +2022-11-14 13:21:10,950 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1830 (0.2076) Prec@1 67.000 (62.639) Prec@5 97.000 (92.639) +2022-11-14 13:21:10,959 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2213 (0.2080) Prec@1 62.000 (62.622) Prec@5 92.000 (92.622) +2022-11-14 13:21:10,968 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2031 (0.2078) Prec@1 64.000 (62.658) Prec@5 95.000 (92.684) +2022-11-14 13:21:10,977 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1956 (0.2075) Prec@1 61.000 (62.615) Prec@5 94.000 (92.718) +2022-11-14 13:21:10,986 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1785 (0.2068) Prec@1 67.000 (62.725) Prec@5 95.000 (92.775) +2022-11-14 13:21:10,995 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2145 (0.2070) Prec@1 62.000 (62.707) Prec@5 90.000 (92.707) +2022-11-14 13:21:11,004 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1756 (0.2062) Prec@1 69.000 (62.857) Prec@5 93.000 (92.714) +2022-11-14 13:21:11,014 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1981 (0.2060) Prec@1 65.000 (62.907) Prec@5 96.000 (92.791) +2022-11-14 13:21:11,023 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1848 (0.2056) Prec@1 70.000 (63.068) Prec@5 94.000 (92.818) +2022-11-14 13:21:11,032 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1825 (0.2051) Prec@1 65.000 (63.111) Prec@5 98.000 (92.933) +2022-11-14 13:21:11,042 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1957 (0.2048) Prec@1 61.000 (63.065) Prec@5 93.000 (92.935) +2022-11-14 13:21:11,051 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2236 (0.2052) Prec@1 58.000 (62.957) Prec@5 89.000 (92.851) +2022-11-14 13:21:11,060 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1879 (0.2049) Prec@1 65.000 (63.000) Prec@5 93.000 (92.854) +2022-11-14 13:21:11,070 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1899 (0.2046) Prec@1 65.000 (63.041) Prec@5 94.000 (92.878) +2022-11-14 13:21:11,079 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2465 (0.2054) Prec@1 56.000 (62.900) Prec@5 90.000 (92.820) +2022-11-14 13:21:11,089 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2303 (0.2059) Prec@1 58.000 (62.804) Prec@5 93.000 (92.824) +2022-11-14 13:21:11,099 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2009 (0.2058) Prec@1 61.000 (62.769) Prec@5 86.000 (92.692) +2022-11-14 13:21:11,108 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2303 (0.2063) Prec@1 59.000 (62.698) Prec@5 93.000 (92.698) +2022-11-14 13:21:11,116 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2262 (0.2066) Prec@1 61.000 (62.667) Prec@5 93.000 (92.704) +2022-11-14 13:21:11,126 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2037 (0.2066) Prec@1 60.000 (62.618) Prec@5 95.000 (92.745) +2022-11-14 13:21:11,136 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2293 (0.2070) Prec@1 61.000 (62.589) Prec@5 91.000 (92.714) +2022-11-14 13:21:11,145 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2493 (0.2077) Prec@1 53.000 (62.421) Prec@5 91.000 (92.684) +2022-11-14 13:21:11,155 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1808 (0.2073) Prec@1 70.000 (62.552) Prec@5 95.000 (92.724) +2022-11-14 13:21:11,164 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2451 (0.2079) Prec@1 58.000 (62.475) Prec@5 93.000 (92.729) +2022-11-14 13:21:11,172 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2011 (0.2078) Prec@1 66.000 (62.533) Prec@5 91.000 (92.700) +2022-11-14 13:21:11,180 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2176 (0.2080) Prec@1 58.000 (62.459) Prec@5 92.000 (92.689) +2022-11-14 13:21:11,190 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2092 (0.2080) Prec@1 67.000 (62.532) Prec@5 92.000 (92.677) +2022-11-14 13:21:11,198 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1992 (0.2078) Prec@1 65.000 (62.571) Prec@5 94.000 (92.698) +2022-11-14 13:21:11,208 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2167 (0.2080) Prec@1 56.000 (62.469) Prec@5 96.000 (92.750) +2022-11-14 13:21:11,217 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2091 (0.2080) Prec@1 63.000 (62.477) Prec@5 89.000 (92.692) +2022-11-14 13:21:11,225 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2188 (0.2082) Prec@1 60.000 (62.439) Prec@5 96.000 (92.742) +2022-11-14 13:21:11,234 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2362 (0.2086) Prec@1 54.000 (62.313) Prec@5 93.000 (92.746) +2022-11-14 13:21:11,244 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1781 (0.2081) Prec@1 69.000 (62.412) Prec@5 99.000 (92.838) +2022-11-14 13:21:11,252 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2183 (0.2083) Prec@1 61.000 (62.391) Prec@5 94.000 (92.855) +2022-11-14 13:21:11,261 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2349 (0.2087) Prec@1 59.000 (62.343) Prec@5 91.000 (92.829) +2022-11-14 13:21:11,271 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2016 (0.2086) Prec@1 66.000 (62.394) Prec@5 92.000 (92.817) +2022-11-14 13:21:11,280 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2327 (0.2089) Prec@1 60.000 (62.361) Prec@5 94.000 (92.833) +2022-11-14 13:21:11,289 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2312 (0.2092) Prec@1 56.000 (62.274) Prec@5 98.000 (92.904) +2022-11-14 13:21:11,299 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2057 (0.2092) Prec@1 57.000 (62.203) Prec@5 96.000 (92.946) +2022-11-14 13:21:11,308 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2061 (0.2091) Prec@1 62.000 (62.200) Prec@5 91.000 (92.920) +2022-11-14 13:21:11,317 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1610 (0.2085) Prec@1 71.000 (62.316) Prec@5 97.000 (92.974) +2022-11-14 13:21:11,325 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2014 (0.2084) Prec@1 65.000 (62.351) Prec@5 93.000 (92.974) +2022-11-14 13:21:11,335 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2281 (0.2086) Prec@1 62.000 (62.346) Prec@5 89.000 (92.923) +2022-11-14 13:21:11,344 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1814 (0.2083) Prec@1 63.000 (62.354) Prec@5 95.000 (92.949) +2022-11-14 13:21:11,355 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1829 (0.2080) Prec@1 65.000 (62.388) Prec@5 95.000 (92.975) +2022-11-14 13:21:11,364 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1827 (0.2077) Prec@1 64.000 (62.407) Prec@5 88.000 (92.914) +2022-11-14 13:21:11,372 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1956 (0.2075) Prec@1 67.000 (62.463) Prec@5 91.000 (92.890) +2022-11-14 13:21:11,382 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1682 (0.2070) Prec@1 72.000 (62.578) Prec@5 95.000 (92.916) +2022-11-14 13:21:11,391 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2191 (0.2072) Prec@1 60.000 (62.548) Prec@5 90.000 (92.881) +2022-11-14 13:21:11,400 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2157 (0.2073) Prec@1 60.000 (62.518) Prec@5 96.000 (92.918) +2022-11-14 13:21:11,410 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1797 (0.2070) Prec@1 67.000 (62.570) Prec@5 95.000 (92.942) +2022-11-14 13:21:11,419 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1983 (0.2069) Prec@1 64.000 (62.586) Prec@5 95.000 (92.966) +2022-11-14 13:21:11,428 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1945 (0.2067) Prec@1 66.000 (62.625) Prec@5 96.000 (93.000) +2022-11-14 13:21:11,437 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2060 (0.2067) Prec@1 62.000 (62.618) Prec@5 90.000 (92.966) +2022-11-14 13:21:11,447 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2134 (0.2068) Prec@1 59.000 (62.578) Prec@5 93.000 (92.967) +2022-11-14 13:21:11,455 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2090 (0.2068) Prec@1 63.000 (62.582) Prec@5 95.000 (92.989) +2022-11-14 13:21:11,463 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1757 (0.2065) Prec@1 64.000 (62.598) Prec@5 97.000 (93.033) +2022-11-14 13:21:11,471 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2061 (0.2065) Prec@1 63.000 (62.602) Prec@5 92.000 (93.022) +2022-11-14 13:21:11,480 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2139 (0.2066) Prec@1 62.000 (62.596) Prec@5 94.000 (93.032) +2022-11-14 13:21:11,488 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1905 (0.2064) Prec@1 64.000 (62.611) Prec@5 93.000 (93.032) +2022-11-14 13:21:11,497 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1899 (0.2062) Prec@1 61.000 (62.594) Prec@5 96.000 (93.062) +2022-11-14 13:21:11,506 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.2058) Prec@1 69.000 (62.660) Prec@5 94.000 (93.072) +2022-11-14 13:21:11,515 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2328 (0.2061) Prec@1 56.000 (62.592) Prec@5 89.000 (93.031) +2022-11-14 13:21:11,524 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2240 (0.2062) Prec@1 57.000 (62.535) Prec@5 91.000 (93.010) +2022-11-14 13:21:11,532 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2055 (0.2062) Prec@1 64.000 (62.550) Prec@5 90.000 (92.980) +2022-11-14 13:21:11,587 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:21:11,903 Epoch: [27][0/500] Time 0.032 (0.032) Data 0.226 (0.226) Loss 0.1132 (0.1132) Prec@1 82.000 (82.000) Prec@5 98.000 (98.000) +2022-11-14 13:21:12,178 Epoch: [27][10/500] Time 0.026 (0.025) Data 0.002 (0.022) Loss 0.1574 (0.1353) Prec@1 73.000 (77.500) Prec@5 97.000 (97.500) +2022-11-14 13:21:12,439 Epoch: [27][20/500] Time 0.020 (0.024) Data 0.002 (0.013) Loss 0.1256 (0.1321) Prec@1 79.000 (78.000) Prec@5 98.000 (97.667) +2022-11-14 13:21:12,671 Epoch: [27][30/500] Time 0.019 (0.023) Data 0.002 (0.009) Loss 0.1229 (0.1298) Prec@1 79.000 (78.250) Prec@5 96.000 (97.250) +2022-11-14 13:21:12,890 Epoch: [27][40/500] Time 0.019 (0.022) Data 0.002 (0.007) Loss 0.1193 (0.1277) Prec@1 77.000 (78.000) Prec@5 99.000 (97.600) +2022-11-14 13:21:13,111 Epoch: [27][50/500] Time 0.020 (0.022) Data 0.002 (0.006) Loss 0.1105 (0.1248) Prec@1 80.000 (78.333) Prec@5 99.000 (97.833) +2022-11-14 13:21:13,395 Epoch: [27][60/500] Time 0.033 (0.022) Data 0.002 (0.006) Loss 0.1544 (0.1290) Prec@1 70.000 (77.143) Prec@5 95.000 (97.429) +2022-11-14 13:21:13,718 Epoch: [27][70/500] Time 0.027 (0.023) Data 0.002 (0.005) Loss 0.1285 (0.1290) Prec@1 79.000 (77.375) Prec@5 98.000 (97.500) +2022-11-14 13:21:14,104 Epoch: [27][80/500] Time 0.035 (0.024) Data 0.002 (0.005) Loss 0.1312 (0.1292) Prec@1 76.000 (77.222) Prec@5 98.000 (97.556) +2022-11-14 13:21:14,474 Epoch: [27][90/500] Time 0.035 (0.025) Data 0.002 (0.004) Loss 0.1192 (0.1282) Prec@1 81.000 (77.600) Prec@5 97.000 (97.500) +2022-11-14 13:21:14,783 Epoch: [27][100/500] Time 0.025 (0.026) Data 0.002 (0.004) Loss 0.1121 (0.1267) Prec@1 80.000 (77.818) Prec@5 99.000 (97.636) +2022-11-14 13:21:15,084 Epoch: [27][110/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.1229 (0.1264) Prec@1 76.000 (77.667) Prec@5 97.000 (97.583) +2022-11-14 13:21:15,386 Epoch: [27][120/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.1129 (0.1254) Prec@1 84.000 (78.154) Prec@5 98.000 (97.615) +2022-11-14 13:21:15,691 Epoch: [27][130/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.1131 (0.1245) Prec@1 80.000 (78.286) Prec@5 100.000 (97.786) +2022-11-14 13:21:15,995 Epoch: [27][140/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1056 (0.1232) Prec@1 83.000 (78.600) Prec@5 96.000 (97.667) +2022-11-14 13:21:16,302 Epoch: [27][150/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1355 (0.1240) Prec@1 77.000 (78.500) Prec@5 98.000 (97.688) +2022-11-14 13:21:16,605 Epoch: [27][160/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.1450 (0.1252) Prec@1 73.000 (78.176) Prec@5 97.000 (97.647) +2022-11-14 13:21:16,912 Epoch: [27][170/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.1415 (0.1261) Prec@1 74.000 (77.944) Prec@5 98.000 (97.667) +2022-11-14 13:21:17,208 Epoch: [27][180/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.1033 (0.1249) Prec@1 80.000 (78.053) Prec@5 97.000 (97.632) +2022-11-14 13:21:17,512 Epoch: [27][190/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1348 (0.1254) Prec@1 75.000 (77.900) Prec@5 99.000 (97.700) +2022-11-14 13:21:17,818 Epoch: [27][200/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1025 (0.1243) Prec@1 86.000 (78.286) Prec@5 100.000 (97.810) +2022-11-14 13:21:18,117 Epoch: [27][210/500] Time 0.029 (0.026) Data 0.003 (0.003) Loss 0.1249 (0.1244) Prec@1 80.000 (78.364) Prec@5 97.000 (97.773) +2022-11-14 13:21:18,421 Epoch: [27][220/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.1587 (0.1259) Prec@1 69.000 (77.957) Prec@5 96.000 (97.696) +2022-11-14 13:21:18,721 Epoch: [27][230/500] Time 0.024 (0.026) Data 0.003 (0.003) Loss 0.1393 (0.1264) Prec@1 76.000 (77.875) Prec@5 95.000 (97.583) +2022-11-14 13:21:19,024 Epoch: [27][240/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1014 (0.1254) Prec@1 83.000 (78.080) Prec@5 99.000 (97.640) +2022-11-14 13:21:19,327 Epoch: [27][250/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1393 (0.1260) Prec@1 74.000 (77.923) Prec@5 97.000 (97.615) +2022-11-14 13:21:19,635 Epoch: [27][260/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1411 (0.1265) Prec@1 73.000 (77.741) Prec@5 96.000 (97.556) +2022-11-14 13:21:19,994 Epoch: [27][270/500] Time 0.040 (0.027) Data 0.002 (0.003) Loss 0.1203 (0.1263) Prec@1 78.000 (77.750) Prec@5 99.000 (97.607) +2022-11-14 13:21:20,331 Epoch: [27][280/500] Time 0.023 (0.027) Data 0.002 (0.003) Loss 0.1859 (0.1283) Prec@1 66.000 (77.345) Prec@5 97.000 (97.586) +2022-11-14 13:21:20,634 Epoch: [27][290/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.1511 (0.1291) Prec@1 73.000 (77.200) Prec@5 96.000 (97.533) +2022-11-14 13:21:20,939 Epoch: [27][300/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1574 (0.1300) Prec@1 72.000 (77.032) Prec@5 97.000 (97.516) +2022-11-14 13:21:21,281 Epoch: [27][310/500] Time 0.044 (0.027) Data 0.002 (0.003) Loss 0.1585 (0.1309) Prec@1 72.000 (76.875) Prec@5 99.000 (97.562) +2022-11-14 13:21:21,747 Epoch: [27][320/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.1204 (0.1306) Prec@1 80.000 (76.970) Prec@5 100.000 (97.636) +2022-11-14 13:21:22,300 Epoch: [27][330/500] Time 0.050 (0.028) Data 0.002 (0.003) Loss 0.1318 (0.1306) Prec@1 76.000 (76.941) Prec@5 96.000 (97.588) +2022-11-14 13:21:22,927 Epoch: [27][340/500] Time 0.050 (0.029) Data 0.002 (0.003) Loss 0.1483 (0.1311) Prec@1 81.000 (77.057) Prec@5 98.000 (97.600) +2022-11-14 13:21:23,419 Epoch: [27][350/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.1364 (0.1313) Prec@1 76.000 (77.028) Prec@5 99.000 (97.639) +2022-11-14 13:21:24,143 Epoch: [27][360/500] Time 0.117 (0.030) Data 0.002 (0.003) Loss 0.1425 (0.1316) Prec@1 74.000 (76.946) Prec@5 97.000 (97.622) +2022-11-14 13:21:24,701 Epoch: [27][370/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.1347 (0.1317) Prec@1 78.000 (76.974) Prec@5 99.000 (97.658) +2022-11-14 13:21:25,181 Epoch: [27][380/500] Time 0.047 (0.031) Data 0.002 (0.002) Loss 0.1486 (0.1321) Prec@1 75.000 (76.923) Prec@5 95.000 (97.590) +2022-11-14 13:21:25,667 Epoch: [27][390/500] Time 0.048 (0.031) Data 0.002 (0.002) Loss 0.1167 (0.1317) Prec@1 78.000 (76.950) Prec@5 99.000 (97.625) +2022-11-14 13:21:26,139 Epoch: [27][400/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.1317 (0.1317) Prec@1 77.000 (76.951) Prec@5 100.000 (97.683) +2022-11-14 13:21:26,612 Epoch: [27][410/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.1300 (0.1317) Prec@1 78.000 (76.976) Prec@5 96.000 (97.643) +2022-11-14 13:21:27,099 Epoch: [27][420/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.1622 (0.1324) Prec@1 69.000 (76.791) Prec@5 97.000 (97.628) +2022-11-14 13:21:27,694 Epoch: [27][430/500] Time 0.068 (0.032) Data 0.002 (0.002) Loss 0.1008 (0.1317) Prec@1 82.000 (76.909) Prec@5 99.000 (97.659) +2022-11-14 13:21:28,201 Epoch: [27][440/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.1048 (0.1311) Prec@1 83.000 (77.044) Prec@5 98.000 (97.667) +2022-11-14 13:21:28,639 Epoch: [27][450/500] Time 0.046 (0.033) Data 0.001 (0.002) Loss 0.1329 (0.1311) Prec@1 74.000 (76.978) Prec@5 97.000 (97.652) +2022-11-14 13:21:29,076 Epoch: [27][460/500] Time 0.040 (0.033) Data 0.001 (0.002) Loss 0.1631 (0.1318) Prec@1 71.000 (76.851) Prec@5 96.000 (97.617) +2022-11-14 13:21:29,528 Epoch: [27][470/500] Time 0.048 (0.033) Data 0.002 (0.002) Loss 0.1367 (0.1319) Prec@1 78.000 (76.875) Prec@5 99.000 (97.646) +2022-11-14 13:21:29,958 Epoch: [27][480/500] Time 0.038 (0.033) Data 0.002 (0.002) Loss 0.1744 (0.1328) Prec@1 67.000 (76.673) Prec@5 94.000 (97.571) +2022-11-14 13:21:30,389 Epoch: [27][490/500] Time 0.050 (0.033) Data 0.001 (0.002) Loss 0.2043 (0.1342) Prec@1 61.000 (76.360) Prec@5 96.000 (97.540) +2022-11-14 13:21:30,770 Epoch: [27][499/500] Time 0.038 (0.033) Data 0.002 (0.002) Loss 0.1207 (0.1339) Prec@1 80.000 (76.431) Prec@5 98.000 (97.549) +2022-11-14 13:21:31,030 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1809 (0.1809) Prec@1 68.000 (68.000) Prec@5 92.000 (92.000) +2022-11-14 13:21:31,041 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1805 (0.1807) Prec@1 66.000 (67.000) Prec@5 98.000 (95.000) +2022-11-14 13:21:31,050 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1679 (0.1764) Prec@1 71.000 (68.333) Prec@5 92.000 (94.000) +2022-11-14 13:21:31,064 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1900 (0.1798) Prec@1 71.000 (69.000) Prec@5 94.000 (94.000) +2022-11-14 13:21:31,072 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2143 (0.1867) Prec@1 61.000 (67.400) Prec@5 92.000 (93.600) +2022-11-14 13:21:31,080 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1364 (0.1783) Prec@1 75.000 (68.667) Prec@5 96.000 (94.000) +2022-11-14 13:21:31,088 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1742 (0.1777) Prec@1 72.000 (69.143) Prec@5 98.000 (94.571) +2022-11-14 13:21:31,100 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1712 (0.1769) Prec@1 68.000 (69.000) Prec@5 99.000 (95.125) +2022-11-14 13:21:31,107 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2129 (0.1809) Prec@1 60.000 (68.000) Prec@5 98.000 (95.444) +2022-11-14 13:21:31,115 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1318 (0.1760) Prec@1 76.000 (68.800) Prec@5 96.000 (95.500) +2022-11-14 13:21:31,124 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1509 (0.1737) Prec@1 72.000 (69.091) Prec@5 97.000 (95.636) +2022-11-14 13:21:31,134 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1755 (0.1739) Prec@1 74.000 (69.500) Prec@5 94.000 (95.500) +2022-11-14 13:21:31,142 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1622 (0.1730) Prec@1 72.000 (69.692) Prec@5 99.000 (95.769) +2022-11-14 13:21:31,152 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1811 (0.1736) Prec@1 66.000 (69.429) Prec@5 94.000 (95.643) +2022-11-14 13:21:31,162 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1625 (0.1728) Prec@1 72.000 (69.600) Prec@5 96.000 (95.667) +2022-11-14 13:21:31,172 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2109 (0.1752) Prec@1 69.000 (69.562) Prec@5 95.000 (95.625) +2022-11-14 13:21:31,182 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1590 (0.1742) Prec@1 74.000 (69.824) Prec@5 97.000 (95.706) +2022-11-14 13:21:31,190 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2091 (0.1762) Prec@1 63.000 (69.444) Prec@5 95.000 (95.667) +2022-11-14 13:21:31,199 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1698 (0.1758) Prec@1 74.000 (69.684) Prec@5 97.000 (95.737) +2022-11-14 13:21:31,210 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1915 (0.1766) Prec@1 67.000 (69.550) Prec@5 99.000 (95.900) +2022-11-14 13:21:31,218 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1636 (0.1760) Prec@1 75.000 (69.810) Prec@5 95.000 (95.857) +2022-11-14 13:21:31,228 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1756) Prec@1 71.000 (69.864) Prec@5 93.000 (95.727) +2022-11-14 13:21:31,237 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1756) Prec@1 68.000 (69.783) Prec@5 97.000 (95.783) +2022-11-14 13:21:31,247 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1805 (0.1758) Prec@1 70.000 (69.792) Prec@5 97.000 (95.833) +2022-11-14 13:21:31,257 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1659 (0.1754) Prec@1 69.000 (69.760) Prec@5 97.000 (95.880) +2022-11-14 13:21:31,267 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2315 (0.1776) Prec@1 55.000 (69.192) Prec@5 98.000 (95.962) +2022-11-14 13:21:31,276 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1757 (0.1775) Prec@1 69.000 (69.185) Prec@5 96.000 (95.963) +2022-11-14 13:21:31,286 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1874 (0.1779) Prec@1 67.000 (69.107) Prec@5 96.000 (95.964) +2022-11-14 13:21:31,295 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1608 (0.1773) Prec@1 73.000 (69.241) Prec@5 96.000 (95.966) +2022-11-14 13:21:31,304 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1758 (0.1772) Prec@1 70.000 (69.267) Prec@5 97.000 (96.000) +2022-11-14 13:21:31,315 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1701 (0.1770) Prec@1 71.000 (69.323) Prec@5 95.000 (95.968) +2022-11-14 13:21:31,325 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1708 (0.1768) Prec@1 71.000 (69.375) Prec@5 95.000 (95.938) +2022-11-14 13:21:31,335 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1619 (0.1763) Prec@1 73.000 (69.485) Prec@5 98.000 (96.000) +2022-11-14 13:21:31,345 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2142 (0.1775) Prec@1 63.000 (69.294) Prec@5 91.000 (95.853) +2022-11-14 13:21:31,355 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1963 (0.1780) Prec@1 69.000 (69.286) Prec@5 94.000 (95.800) +2022-11-14 13:21:31,364 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1866 (0.1782) Prec@1 69.000 (69.278) Prec@5 92.000 (95.694) +2022-11-14 13:21:31,373 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1836 (0.1784) Prec@1 68.000 (69.243) Prec@5 94.000 (95.649) +2022-11-14 13:21:31,382 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2021 (0.1790) Prec@1 63.000 (69.079) Prec@5 96.000 (95.658) +2022-11-14 13:21:31,391 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1717 (0.1788) Prec@1 70.000 (69.103) Prec@5 96.000 (95.667) +2022-11-14 13:21:31,400 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1674 (0.1785) Prec@1 66.000 (69.025) Prec@5 98.000 (95.725) +2022-11-14 13:21:31,410 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1811 (0.1786) Prec@1 69.000 (69.024) Prec@5 94.000 (95.683) +2022-11-14 13:21:31,419 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1587 (0.1781) Prec@1 72.000 (69.095) Prec@5 98.000 (95.738) +2022-11-14 13:21:31,429 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1421 (0.1773) Prec@1 80.000 (69.349) Prec@5 93.000 (95.674) +2022-11-14 13:21:31,439 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1592 (0.1769) Prec@1 75.000 (69.477) Prec@5 92.000 (95.591) +2022-11-14 13:21:31,449 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1842 (0.1770) Prec@1 67.000 (69.422) Prec@5 97.000 (95.622) +2022-11-14 13:21:31,460 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1571 (0.1766) Prec@1 71.000 (69.457) Prec@5 97.000 (95.652) +2022-11-14 13:21:31,470 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1656 (0.1764) Prec@1 73.000 (69.532) Prec@5 96.000 (95.660) +2022-11-14 13:21:31,480 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1528 (0.1759) Prec@1 74.000 (69.625) Prec@5 98.000 (95.708) +2022-11-14 13:21:31,488 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1589 (0.1755) Prec@1 74.000 (69.714) Prec@5 99.000 (95.776) +2022-11-14 13:21:31,498 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2096 (0.1762) Prec@1 66.000 (69.640) Prec@5 93.000 (95.720) +2022-11-14 13:21:31,508 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1688 (0.1761) Prec@1 70.000 (69.647) Prec@5 90.000 (95.608) +2022-11-14 13:21:31,519 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1820 (0.1762) Prec@1 70.000 (69.654) Prec@5 94.000 (95.577) +2022-11-14 13:21:31,530 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1969 (0.1766) Prec@1 68.000 (69.623) Prec@5 96.000 (95.585) +2022-11-14 13:21:31,541 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2035 (0.1771) Prec@1 67.000 (69.574) Prec@5 95.000 (95.574) +2022-11-14 13:21:31,551 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2055 (0.1776) Prec@1 64.000 (69.473) Prec@5 96.000 (95.582) +2022-11-14 13:21:31,560 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1954 (0.1779) Prec@1 64.000 (69.375) Prec@5 94.000 (95.554) +2022-11-14 13:21:31,570 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1733 (0.1778) Prec@1 69.000 (69.368) Prec@5 97.000 (95.579) +2022-11-14 13:21:31,580 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1777) Prec@1 76.000 (69.483) Prec@5 98.000 (95.621) +2022-11-14 13:21:31,590 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2366 (0.1787) Prec@1 57.000 (69.271) Prec@5 90.000 (95.525) +2022-11-14 13:21:31,600 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1789 (0.1787) Prec@1 69.000 (69.267) Prec@5 95.000 (95.517) +2022-11-14 13:21:31,609 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1855 (0.1788) Prec@1 67.000 (69.230) Prec@5 99.000 (95.574) +2022-11-14 13:21:31,620 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1821 (0.1788) Prec@1 67.000 (69.194) Prec@5 91.000 (95.500) +2022-11-14 13:21:31,629 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1784) Prec@1 76.000 (69.302) Prec@5 99.000 (95.556) +2022-11-14 13:21:31,639 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1847 (0.1785) Prec@1 66.000 (69.250) Prec@5 94.000 (95.531) +2022-11-14 13:21:31,648 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1767 (0.1784) Prec@1 67.000 (69.215) Prec@5 99.000 (95.585) +2022-11-14 13:21:31,658 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2176 (0.1790) Prec@1 61.000 (69.091) Prec@5 94.000 (95.561) +2022-11-14 13:21:31,668 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1827 (0.1791) Prec@1 68.000 (69.075) Prec@5 97.000 (95.582) +2022-11-14 13:21:31,677 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2073 (0.1795) Prec@1 61.000 (68.956) Prec@5 98.000 (95.618) +2022-11-14 13:21:31,685 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1590 (0.1792) Prec@1 74.000 (69.029) Prec@5 95.000 (95.609) +2022-11-14 13:21:31,694 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2125 (0.1797) Prec@1 61.000 (68.914) Prec@5 95.000 (95.600) +2022-11-14 13:21:31,704 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1733 (0.1796) Prec@1 69.000 (68.915) Prec@5 96.000 (95.606) +2022-11-14 13:21:31,714 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1672 (0.1794) Prec@1 70.000 (68.931) Prec@5 96.000 (95.611) +2022-11-14 13:21:31,724 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1689 (0.1793) Prec@1 69.000 (68.932) Prec@5 98.000 (95.644) +2022-11-14 13:21:31,734 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1387 (0.1787) Prec@1 74.000 (69.000) Prec@5 97.000 (95.662) +2022-11-14 13:21:31,744 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2054 (0.1791) Prec@1 62.000 (68.907) Prec@5 95.000 (95.653) +2022-11-14 13:21:31,753 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1955 (0.1793) Prec@1 66.000 (68.868) Prec@5 96.000 (95.658) +2022-11-14 13:21:31,763 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2151 (0.1798) Prec@1 62.000 (68.779) Prec@5 92.000 (95.610) +2022-11-14 13:21:31,774 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1323 (0.1792) Prec@1 76.000 (68.872) Prec@5 96.000 (95.615) +2022-11-14 13:21:31,783 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1844 (0.1792) Prec@1 72.000 (68.911) Prec@5 96.000 (95.620) +2022-11-14 13:21:31,793 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1791) Prec@1 72.000 (68.950) Prec@5 98.000 (95.650) +2022-11-14 13:21:31,802 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1791 (0.1791) Prec@1 69.000 (68.951) Prec@5 96.000 (95.654) +2022-11-14 13:21:31,812 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1854 (0.1791) Prec@1 66.000 (68.915) Prec@5 94.000 (95.634) +2022-11-14 13:21:31,822 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1839 (0.1792) Prec@1 66.000 (68.880) Prec@5 98.000 (95.663) +2022-11-14 13:21:31,832 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1740 (0.1791) Prec@1 72.000 (68.917) Prec@5 93.000 (95.631) +2022-11-14 13:21:31,843 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1647 (0.1790) Prec@1 74.000 (68.976) Prec@5 93.000 (95.600) +2022-11-14 13:21:31,854 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1503 (0.1786) Prec@1 77.000 (69.070) Prec@5 94.000 (95.581) +2022-11-14 13:21:31,864 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1961 (0.1788) Prec@1 65.000 (69.023) Prec@5 93.000 (95.552) +2022-11-14 13:21:31,875 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1788) Prec@1 74.000 (69.080) Prec@5 97.000 (95.568) +2022-11-14 13:21:31,885 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1681 (0.1787) Prec@1 71.000 (69.101) Prec@5 98.000 (95.596) +2022-11-14 13:21:31,895 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2028 (0.1789) Prec@1 64.000 (69.044) Prec@5 95.000 (95.589) +2022-11-14 13:21:31,906 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1794 (0.1789) Prec@1 70.000 (69.055) Prec@5 95.000 (95.582) +2022-11-14 13:21:31,918 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.1784) Prec@1 79.000 (69.163) Prec@5 97.000 (95.598) +2022-11-14 13:21:31,928 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1916 (0.1785) Prec@1 64.000 (69.108) Prec@5 93.000 (95.570) +2022-11-14 13:21:31,938 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1790 (0.1785) Prec@1 69.000 (69.106) Prec@5 95.000 (95.564) +2022-11-14 13:21:31,947 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1861 (0.1786) Prec@1 68.000 (69.095) Prec@5 96.000 (95.568) +2022-11-14 13:21:31,956 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1403 (0.1782) Prec@1 78.000 (69.188) Prec@5 98.000 (95.594) +2022-11-14 13:21:31,966 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1778) Prec@1 78.000 (69.278) Prec@5 98.000 (95.619) +2022-11-14 13:21:31,975 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1864 (0.1779) Prec@1 64.000 (69.224) Prec@5 92.000 (95.582) +2022-11-14 13:21:31,984 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2040 (0.1782) Prec@1 63.000 (69.162) Prec@5 93.000 (95.556) +2022-11-14 13:21:31,994 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1810 (0.1782) Prec@1 67.000 (69.140) Prec@5 96.000 (95.560) +2022-11-14 13:21:32,048 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:21:32,363 Epoch: [28][0/500] Time 0.030 (0.030) Data 0.226 (0.226) Loss 0.1390 (0.1390) Prec@1 76.000 (76.000) Prec@5 97.000 (97.000) +2022-11-14 13:21:32,573 Epoch: [28][10/500] Time 0.018 (0.020) Data 0.001 (0.022) Loss 0.1325 (0.1357) Prec@1 77.000 (76.500) Prec@5 97.000 (97.000) +2022-11-14 13:21:32,787 Epoch: [28][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.1250 (0.1321) Prec@1 79.000 (77.333) Prec@5 98.000 (97.333) +2022-11-14 13:21:32,999 Epoch: [28][30/500] Time 0.019 (0.019) Data 0.002 (0.009) Loss 0.1058 (0.1256) Prec@1 82.000 (78.500) Prec@5 98.000 (97.500) +2022-11-14 13:21:33,395 Epoch: [28][40/500] Time 0.039 (0.023) Data 0.002 (0.007) Loss 0.1346 (0.1274) Prec@1 78.000 (78.400) Prec@5 96.000 (97.200) +2022-11-14 13:21:33,729 Epoch: [28][50/500] Time 0.036 (0.024) Data 0.002 (0.006) Loss 0.1483 (0.1309) Prec@1 70.000 (77.000) Prec@5 98.000 (97.333) +2022-11-14 13:21:34,084 Epoch: [28][60/500] Time 0.032 (0.025) Data 0.002 (0.006) Loss 0.1445 (0.1328) Prec@1 75.000 (76.714) Prec@5 97.000 (97.286) +2022-11-14 13:21:34,445 Epoch: [28][70/500] Time 0.033 (0.026) Data 0.003 (0.005) Loss 0.1302 (0.1325) Prec@1 77.000 (76.750) Prec@5 97.000 (97.250) +2022-11-14 13:21:34,792 Epoch: [28][80/500] Time 0.032 (0.027) Data 0.002 (0.005) Loss 0.1266 (0.1318) Prec@1 78.000 (76.889) Prec@5 99.000 (97.444) +2022-11-14 13:21:35,193 Epoch: [28][90/500] Time 0.052 (0.028) Data 0.002 (0.004) Loss 0.1311 (0.1318) Prec@1 76.000 (76.800) Prec@5 99.000 (97.600) +2022-11-14 13:21:35,561 Epoch: [28][100/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.1400 (0.1325) Prec@1 73.000 (76.455) Prec@5 95.000 (97.364) +2022-11-14 13:21:35,918 Epoch: [28][110/500] Time 0.034 (0.029) Data 0.002 (0.004) Loss 0.1320 (0.1325) Prec@1 77.000 (76.500) Prec@5 96.000 (97.250) +2022-11-14 13:21:36,264 Epoch: [28][120/500] Time 0.033 (0.029) Data 0.002 (0.004) Loss 0.1426 (0.1332) Prec@1 71.000 (76.077) Prec@5 98.000 (97.308) +2022-11-14 13:21:36,639 Epoch: [28][130/500] Time 0.030 (0.029) Data 0.002 (0.004) Loss 0.1459 (0.1342) Prec@1 73.000 (75.857) Prec@5 97.000 (97.286) +2022-11-14 13:21:36,985 Epoch: [28][140/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0944 (0.1315) Prec@1 86.000 (76.533) Prec@5 99.000 (97.400) +2022-11-14 13:21:37,407 Epoch: [28][150/500] Time 0.056 (0.030) Data 0.002 (0.003) Loss 0.1316 (0.1315) Prec@1 79.000 (76.688) Prec@5 100.000 (97.562) +2022-11-14 13:21:37,778 Epoch: [28][160/500] Time 0.028 (0.030) Data 0.002 (0.003) Loss 0.1402 (0.1320) Prec@1 75.000 (76.588) Prec@5 97.000 (97.529) +2022-11-14 13:21:38,138 Epoch: [28][170/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.1256 (0.1317) Prec@1 78.000 (76.667) Prec@5 95.000 (97.389) +2022-11-14 13:21:38,491 Epoch: [28][180/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.1413 (0.1322) Prec@1 78.000 (76.737) Prec@5 98.000 (97.421) +2022-11-14 13:21:38,848 Epoch: [28][190/500] Time 0.027 (0.030) Data 0.002 (0.003) Loss 0.1397 (0.1325) Prec@1 76.000 (76.700) Prec@5 96.000 (97.350) +2022-11-14 13:21:39,212 Epoch: [28][200/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.1167 (0.1318) Prec@1 79.000 (76.810) Prec@5 98.000 (97.381) +2022-11-14 13:21:39,639 Epoch: [28][210/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0853 (0.1297) Prec@1 87.000 (77.273) Prec@5 99.000 (97.455) +2022-11-14 13:21:39,974 Epoch: [28][220/500] Time 0.036 (0.031) Data 0.003 (0.003) Loss 0.1237 (0.1294) Prec@1 80.000 (77.391) Prec@5 97.000 (97.435) +2022-11-14 13:21:40,326 Epoch: [28][230/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.1257 (0.1293) Prec@1 79.000 (77.458) Prec@5 98.000 (97.458) +2022-11-14 13:21:40,690 Epoch: [28][240/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.1671 (0.1308) Prec@1 70.000 (77.160) Prec@5 96.000 (97.400) +2022-11-14 13:21:41,104 Epoch: [28][250/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.1363 (0.1310) Prec@1 74.000 (77.038) Prec@5 96.000 (97.346) +2022-11-14 13:21:41,468 Epoch: [28][260/500] Time 0.048 (0.031) Data 0.002 (0.003) Loss 0.0908 (0.1295) Prec@1 86.000 (77.370) Prec@5 98.000 (97.370) +2022-11-14 13:21:41,812 Epoch: [28][270/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.1510 (0.1303) Prec@1 78.000 (77.393) Prec@5 96.000 (97.321) +2022-11-14 13:21:42,180 Epoch: [28][280/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.1459 (0.1308) Prec@1 77.000 (77.379) Prec@5 96.000 (97.276) +2022-11-14 13:21:42,658 Epoch: [28][290/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.1429 (0.1312) Prec@1 75.000 (77.300) Prec@5 97.000 (97.267) +2022-11-14 13:21:43,001 Epoch: [28][300/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.1379 (0.1314) Prec@1 71.000 (77.097) Prec@5 97.000 (97.258) +2022-11-14 13:21:43,355 Epoch: [28][310/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.1119 (0.1308) Prec@1 80.000 (77.188) Prec@5 100.000 (97.344) +2022-11-14 13:21:43,715 Epoch: [28][320/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.1396 (0.1311) Prec@1 78.000 (77.212) Prec@5 98.000 (97.364) +2022-11-14 13:21:44,072 Epoch: [28][330/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.1314 (0.1311) Prec@1 80.000 (77.294) Prec@5 97.000 (97.353) +2022-11-14 13:21:44,432 Epoch: [28][340/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.1304 (0.1311) Prec@1 79.000 (77.343) Prec@5 98.000 (97.371) +2022-11-14 13:21:44,795 Epoch: [28][350/500] Time 0.038 (0.031) Data 0.002 (0.002) Loss 0.1337 (0.1311) Prec@1 75.000 (77.278) Prec@5 99.000 (97.417) +2022-11-14 13:21:45,149 Epoch: [28][360/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.1398 (0.1314) Prec@1 73.000 (77.162) Prec@5 98.000 (97.432) +2022-11-14 13:21:45,523 Epoch: [28][370/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.1436 (0.1317) Prec@1 76.000 (77.132) Prec@5 97.000 (97.421) +2022-11-14 13:21:45,880 Epoch: [28][380/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.1287 (0.1316) Prec@1 74.000 (77.051) Prec@5 98.000 (97.436) +2022-11-14 13:21:46,244 Epoch: [28][390/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.1256 (0.1315) Prec@1 78.000 (77.075) Prec@5 98.000 (97.450) +2022-11-14 13:21:46,604 Epoch: [28][400/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.1718 (0.1325) Prec@1 70.000 (76.902) Prec@5 94.000 (97.366) +2022-11-14 13:21:46,967 Epoch: [28][410/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.1271 (0.1323) Prec@1 82.000 (77.024) Prec@5 98.000 (97.381) +2022-11-14 13:21:47,321 Epoch: [28][420/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.1527 (0.1328) Prec@1 74.000 (76.953) Prec@5 98.000 (97.395) +2022-11-14 13:21:47,676 Epoch: [28][430/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.1961 (0.1342) Prec@1 66.000 (76.705) Prec@5 95.000 (97.341) +2022-11-14 13:21:48,035 Epoch: [28][440/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.1740 (0.1351) Prec@1 67.000 (76.489) Prec@5 95.000 (97.289) +2022-11-14 13:21:48,388 Epoch: [28][450/500] Time 0.032 (0.032) Data 0.002 (0.002) Loss 0.1491 (0.1354) Prec@1 73.000 (76.413) Prec@5 95.000 (97.239) +2022-11-14 13:21:48,780 Epoch: [28][460/500] Time 0.056 (0.032) Data 0.002 (0.002) Loss 0.1104 (0.1349) Prec@1 80.000 (76.489) Prec@5 97.000 (97.234) +2022-11-14 13:21:49,124 Epoch: [28][470/500] Time 0.037 (0.032) Data 0.002 (0.002) Loss 0.1348 (0.1349) Prec@1 77.000 (76.500) Prec@5 96.000 (97.208) +2022-11-14 13:21:49,490 Epoch: [28][480/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.1589 (0.1354) Prec@1 70.000 (76.367) Prec@5 98.000 (97.224) +2022-11-14 13:21:49,856 Epoch: [28][490/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.1317 (0.1353) Prec@1 76.000 (76.360) Prec@5 99.000 (97.260) +2022-11-14 13:21:50,182 Epoch: [28][499/500] Time 0.032 (0.032) Data 0.002 (0.002) Loss 0.1587 (0.1358) Prec@1 71.000 (76.255) Prec@5 99.000 (97.294) +2022-11-14 13:21:50,456 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.2099 (0.2099) Prec@1 63.000 (63.000) Prec@5 96.000 (96.000) +2022-11-14 13:21:50,466 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2065 (0.2082) Prec@1 67.000 (65.000) Prec@5 94.000 (95.000) +2022-11-14 13:21:50,476 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2170 (0.2111) Prec@1 60.000 (63.333) Prec@5 97.000 (95.667) +2022-11-14 13:21:50,489 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2149 (0.2121) Prec@1 63.000 (63.250) Prec@5 96.000 (95.750) +2022-11-14 13:21:50,497 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2546 (0.2206) Prec@1 55.000 (61.600) Prec@5 91.000 (94.800) +2022-11-14 13:21:50,506 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2112 (0.2190) Prec@1 62.000 (61.667) Prec@5 93.000 (94.500) +2022-11-14 13:21:50,514 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2481 (0.2232) Prec@1 56.000 (60.857) Prec@5 94.000 (94.429) +2022-11-14 13:21:50,523 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2118 (0.2218) Prec@1 65.000 (61.375) Prec@5 96.000 (94.625) +2022-11-14 13:21:50,531 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2147 (0.2210) Prec@1 66.000 (61.889) Prec@5 92.000 (94.333) +2022-11-14 13:21:50,541 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1919 (0.2181) Prec@1 69.000 (62.600) Prec@5 96.000 (94.500) +2022-11-14 13:21:50,551 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2025 (0.2166) Prec@1 63.000 (62.636) Prec@5 93.000 (94.364) +2022-11-14 13:21:50,561 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2015 (0.2154) Prec@1 67.000 (63.000) Prec@5 95.000 (94.417) +2022-11-14 13:21:50,569 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2405 (0.2173) Prec@1 57.000 (62.538) Prec@5 92.000 (94.231) +2022-11-14 13:21:50,576 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.2405 (0.2190) Prec@1 63.000 (62.571) Prec@5 92.000 (94.071) +2022-11-14 13:21:50,585 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1956 (0.2174) Prec@1 69.000 (63.000) Prec@5 94.000 (94.067) +2022-11-14 13:21:50,596 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2078 (0.2168) Prec@1 64.000 (63.062) Prec@5 96.000 (94.188) +2022-11-14 13:21:50,606 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2159 (0.2168) Prec@1 66.000 (63.235) Prec@5 91.000 (94.000) +2022-11-14 13:21:50,615 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2140 (0.2166) Prec@1 60.000 (63.056) Prec@5 97.000 (94.167) +2022-11-14 13:21:50,625 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2243 (0.2170) Prec@1 63.000 (63.053) Prec@5 95.000 (94.211) +2022-11-14 13:21:50,635 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2255 (0.2174) Prec@1 59.000 (62.850) Prec@5 96.000 (94.300) +2022-11-14 13:21:50,645 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2305 (0.2181) Prec@1 60.000 (62.714) Prec@5 94.000 (94.286) +2022-11-14 13:21:50,655 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2417 (0.2191) Prec@1 58.000 (62.500) Prec@5 94.000 (94.273) +2022-11-14 13:21:50,664 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2321 (0.2197) Prec@1 63.000 (62.522) Prec@5 94.000 (94.261) +2022-11-14 13:21:50,675 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1888 (0.2184) Prec@1 68.000 (62.750) Prec@5 90.000 (94.083) +2022-11-14 13:21:50,684 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2036 (0.2178) Prec@1 66.000 (62.880) Prec@5 91.000 (93.960) +2022-11-14 13:21:50,694 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2394 (0.2186) Prec@1 60.000 (62.769) Prec@5 95.000 (94.000) +2022-11-14 13:21:50,703 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1986 (0.2179) Prec@1 66.000 (62.889) Prec@5 97.000 (94.111) +2022-11-14 13:21:50,712 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2440 (0.2188) Prec@1 61.000 (62.821) Prec@5 95.000 (94.143) +2022-11-14 13:21:50,722 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2104 (0.2185) Prec@1 66.000 (62.931) Prec@5 93.000 (94.103) +2022-11-14 13:21:50,731 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1954 (0.2178) Prec@1 68.000 (63.100) Prec@5 93.000 (94.067) +2022-11-14 13:21:50,741 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2074 (0.2174) Prec@1 64.000 (63.129) Prec@5 94.000 (94.065) +2022-11-14 13:21:50,752 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2079 (0.2171) Prec@1 66.000 (63.219) Prec@5 89.000 (93.906) +2022-11-14 13:21:50,763 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2496 (0.2181) Prec@1 58.000 (63.061) Prec@5 91.000 (93.818) +2022-11-14 13:21:50,774 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2347 (0.2186) Prec@1 59.000 (62.941) Prec@5 92.000 (93.765) +2022-11-14 13:21:50,784 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2377 (0.2192) Prec@1 61.000 (62.886) Prec@5 93.000 (93.743) +2022-11-14 13:21:50,794 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.2173) Prec@1 75.000 (63.222) Prec@5 94.000 (93.750) +2022-11-14 13:21:50,803 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2222 (0.2175) Prec@1 64.000 (63.243) Prec@5 96.000 (93.811) +2022-11-14 13:21:50,812 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2015 (0.2170) Prec@1 69.000 (63.395) Prec@5 96.000 (93.868) +2022-11-14 13:21:50,821 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2027 (0.2167) Prec@1 66.000 (63.462) Prec@5 93.000 (93.846) +2022-11-14 13:21:50,830 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1975 (0.2162) Prec@1 67.000 (63.550) Prec@5 95.000 (93.875) +2022-11-14 13:21:50,840 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2247 (0.2164) Prec@1 64.000 (63.561) Prec@5 93.000 (93.854) +2022-11-14 13:21:50,849 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1773 (0.2155) Prec@1 70.000 (63.714) Prec@5 95.000 (93.881) +2022-11-14 13:21:50,858 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1891 (0.2149) Prec@1 67.000 (63.791) Prec@5 96.000 (93.930) +2022-11-14 13:21:50,869 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2170 (0.2149) Prec@1 63.000 (63.773) Prec@5 96.000 (93.977) +2022-11-14 13:21:50,877 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2139 (0.2149) Prec@1 65.000 (63.800) Prec@5 94.000 (93.978) +2022-11-14 13:21:50,886 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2481 (0.2156) Prec@1 56.000 (63.630) Prec@5 92.000 (93.935) +2022-11-14 13:21:50,894 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2358 (0.2160) Prec@1 58.000 (63.511) Prec@5 94.000 (93.936) +2022-11-14 13:21:50,902 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1979 (0.2157) Prec@1 67.000 (63.583) Prec@5 93.000 (93.917) +2022-11-14 13:21:50,912 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1860 (0.2151) Prec@1 67.000 (63.653) Prec@5 96.000 (93.959) +2022-11-14 13:21:50,921 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2513 (0.2158) Prec@1 60.000 (63.580) Prec@5 93.000 (93.940) +2022-11-14 13:21:50,930 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2576 (0.2166) Prec@1 54.000 (63.392) Prec@5 93.000 (93.922) +2022-11-14 13:21:50,940 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2608 (0.2174) Prec@1 56.000 (63.250) Prec@5 90.000 (93.846) +2022-11-14 13:21:50,949 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1985 (0.2171) Prec@1 64.000 (63.264) Prec@5 98.000 (93.925) +2022-11-14 13:21:50,960 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2045 (0.2169) Prec@1 68.000 (63.352) Prec@5 95.000 (93.944) +2022-11-14 13:21:50,969 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2098 (0.2167) Prec@1 64.000 (63.364) Prec@5 96.000 (93.982) +2022-11-14 13:21:50,977 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2490 (0.2173) Prec@1 54.000 (63.196) Prec@5 91.000 (93.929) +2022-11-14 13:21:50,987 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2417 (0.2177) Prec@1 58.000 (63.105) Prec@5 94.000 (93.930) +2022-11-14 13:21:50,996 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1728 (0.2170) Prec@1 70.000 (63.224) Prec@5 93.000 (93.914) +2022-11-14 13:21:51,005 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2704 (0.2179) Prec@1 55.000 (63.085) Prec@5 92.000 (93.881) +2022-11-14 13:21:51,014 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2310 (0.2181) Prec@1 61.000 (63.050) Prec@5 93.000 (93.867) +2022-11-14 13:21:51,023 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2401 (0.2184) Prec@1 61.000 (63.016) Prec@5 93.000 (93.852) +2022-11-14 13:21:51,032 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2524 (0.2190) Prec@1 55.000 (62.887) Prec@5 93.000 (93.839) +2022-11-14 13:21:51,042 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2199 (0.2190) Prec@1 61.000 (62.857) Prec@5 94.000 (93.841) +2022-11-14 13:21:51,051 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1929 (0.2186) Prec@1 67.000 (62.922) Prec@5 96.000 (93.875) +2022-11-14 13:21:51,060 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2240 (0.2187) Prec@1 61.000 (62.892) Prec@5 95.000 (93.892) +2022-11-14 13:21:51,069 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2172 (0.2187) Prec@1 61.000 (62.864) Prec@5 96.000 (93.924) +2022-11-14 13:21:51,078 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2215 (0.2187) Prec@1 63.000 (62.866) Prec@5 92.000 (93.896) +2022-11-14 13:21:51,087 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2169 (0.2187) Prec@1 61.000 (62.838) Prec@5 94.000 (93.897) +2022-11-14 13:21:51,097 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2039 (0.2185) Prec@1 64.000 (62.855) Prec@5 96.000 (93.928) +2022-11-14 13:21:51,106 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2794 (0.2193) Prec@1 55.000 (62.743) Prec@5 88.000 (93.843) +2022-11-14 13:21:51,115 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2043 (0.2191) Prec@1 64.000 (62.761) Prec@5 95.000 (93.859) +2022-11-14 13:21:51,124 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2395 (0.2194) Prec@1 57.000 (62.681) Prec@5 90.000 (93.806) +2022-11-14 13:21:51,134 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2482 (0.2198) Prec@1 57.000 (62.603) Prec@5 93.000 (93.795) +2022-11-14 13:21:51,143 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2058 (0.2196) Prec@1 62.000 (62.595) Prec@5 97.000 (93.838) +2022-11-14 13:21:51,153 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2391 (0.2199) Prec@1 59.000 (62.547) Prec@5 94.000 (93.840) +2022-11-14 13:21:51,162 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1666 (0.2192) Prec@1 70.000 (62.645) Prec@5 95.000 (93.855) +2022-11-14 13:21:51,171 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2111 (0.2191) Prec@1 63.000 (62.649) Prec@5 96.000 (93.883) +2022-11-14 13:21:51,180 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2464 (0.2194) Prec@1 57.000 (62.577) Prec@5 93.000 (93.872) +2022-11-14 13:21:51,188 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2088 (0.2193) Prec@1 65.000 (62.608) Prec@5 97.000 (93.911) +2022-11-14 13:21:51,198 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2265 (0.2194) Prec@1 62.000 (62.600) Prec@5 90.000 (93.862) +2022-11-14 13:21:51,206 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.2190) Prec@1 65.000 (62.630) Prec@5 96.000 (93.889) +2022-11-14 13:21:51,218 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.2159 (0.2189) Prec@1 63.000 (62.634) Prec@5 95.000 (93.902) +2022-11-14 13:21:51,228 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2376 (0.2192) Prec@1 61.000 (62.614) Prec@5 88.000 (93.831) +2022-11-14 13:21:51,237 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2108 (0.2191) Prec@1 64.000 (62.631) Prec@5 96.000 (93.857) +2022-11-14 13:21:51,247 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2252 (0.2191) Prec@1 64.000 (62.647) Prec@5 91.000 (93.824) +2022-11-14 13:21:51,257 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2277 (0.2192) Prec@1 62.000 (62.640) Prec@5 96.000 (93.849) +2022-11-14 13:21:51,267 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2345 (0.2194) Prec@1 64.000 (62.655) Prec@5 94.000 (93.851) +2022-11-14 13:21:51,276 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2184 (0.2194) Prec@1 59.000 (62.614) Prec@5 91.000 (93.818) +2022-11-14 13:21:51,285 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2117 (0.2193) Prec@1 65.000 (62.640) Prec@5 93.000 (93.809) +2022-11-14 13:21:51,294 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2503 (0.2197) Prec@1 58.000 (62.589) Prec@5 91.000 (93.778) +2022-11-14 13:21:51,303 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1802 (0.2192) Prec@1 69.000 (62.659) Prec@5 97.000 (93.813) +2022-11-14 13:21:51,313 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1820 (0.2188) Prec@1 70.000 (62.739) Prec@5 96.000 (93.837) +2022-11-14 13:21:51,322 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2323 (0.2190) Prec@1 58.000 (62.688) Prec@5 94.000 (93.839) +2022-11-14 13:21:51,331 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2472 (0.2193) Prec@1 63.000 (62.691) Prec@5 88.000 (93.777) +2022-11-14 13:21:51,340 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1976 (0.2190) Prec@1 62.000 (62.684) Prec@5 94.000 (93.779) +2022-11-14 13:21:51,350 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2053 (0.2189) Prec@1 65.000 (62.708) Prec@5 96.000 (93.802) +2022-11-14 13:21:51,358 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1911 (0.2186) Prec@1 67.000 (62.753) Prec@5 94.000 (93.804) +2022-11-14 13:21:51,367 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2520 (0.2189) Prec@1 59.000 (62.714) Prec@5 92.000 (93.786) +2022-11-14 13:21:51,377 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2369 (0.2191) Prec@1 62.000 (62.707) Prec@5 90.000 (93.747) +2022-11-14 13:21:51,386 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2170 (0.2191) Prec@1 64.000 (62.720) Prec@5 95.000 (93.760) +2022-11-14 13:21:51,439 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:21:51,758 Epoch: [29][0/500] Time 0.035 (0.035) Data 0.229 (0.229) Loss 0.1176 (0.1176) Prec@1 79.000 (79.000) Prec@5 100.000 (100.000) +2022-11-14 13:21:51,979 Epoch: [29][10/500] Time 0.026 (0.021) Data 0.002 (0.022) Loss 0.1133 (0.1154) Prec@1 82.000 (80.500) Prec@5 97.000 (98.500) +2022-11-14 13:21:52,185 Epoch: [29][20/500] Time 0.015 (0.020) Data 0.002 (0.013) Loss 0.1150 (0.1153) Prec@1 80.000 (80.333) Prec@5 99.000 (98.667) +2022-11-14 13:21:52,407 Epoch: [29][30/500] Time 0.026 (0.020) Data 0.002 (0.009) Loss 0.1468 (0.1232) Prec@1 75.000 (79.000) Prec@5 96.000 (98.000) +2022-11-14 13:21:52,660 Epoch: [29][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.1650 (0.1315) Prec@1 70.000 (77.200) Prec@5 98.000 (98.000) +2022-11-14 13:21:52,920 Epoch: [29][50/500] Time 0.026 (0.021) Data 0.002 (0.006) Loss 0.1021 (0.1266) Prec@1 79.000 (77.500) Prec@5 98.000 (98.000) +2022-11-14 13:21:53,182 Epoch: [29][60/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.1068 (0.1238) Prec@1 83.000 (78.286) Prec@5 100.000 (98.286) +2022-11-14 13:21:53,444 Epoch: [29][70/500] Time 0.024 (0.022) Data 0.001 (0.005) Loss 0.1507 (0.1272) Prec@1 71.000 (77.375) Prec@5 100.000 (98.500) +2022-11-14 13:21:53,704 Epoch: [29][80/500] Time 0.023 (0.022) Data 0.002 (0.005) Loss 0.1354 (0.1281) Prec@1 75.000 (77.111) Prec@5 99.000 (98.556) +2022-11-14 13:21:53,968 Epoch: [29][90/500] Time 0.026 (0.022) Data 0.001 (0.004) Loss 0.1497 (0.1302) Prec@1 74.000 (76.800) Prec@5 98.000 (98.500) +2022-11-14 13:21:54,229 Epoch: [29][100/500] Time 0.029 (0.022) Data 0.002 (0.004) Loss 0.1230 (0.1296) Prec@1 78.000 (76.909) Prec@5 100.000 (98.636) +2022-11-14 13:21:54,527 Epoch: [29][110/500] Time 0.031 (0.022) Data 0.002 (0.004) Loss 0.1426 (0.1307) Prec@1 76.000 (76.833) Prec@5 97.000 (98.500) +2022-11-14 13:21:54,884 Epoch: [29][120/500] Time 0.036 (0.023) Data 0.002 (0.004) Loss 0.1166 (0.1296) Prec@1 80.000 (77.077) Prec@5 97.000 (98.385) +2022-11-14 13:21:55,244 Epoch: [29][130/500] Time 0.035 (0.024) Data 0.001 (0.004) Loss 0.1410 (0.1304) Prec@1 77.000 (77.071) Prec@5 98.000 (98.357) +2022-11-14 13:21:55,602 Epoch: [29][140/500] Time 0.032 (0.024) Data 0.002 (0.003) Loss 0.1324 (0.1305) Prec@1 77.000 (77.067) Prec@5 99.000 (98.400) +2022-11-14 13:21:55,963 Epoch: [29][150/500] Time 0.035 (0.025) Data 0.002 (0.003) Loss 0.1442 (0.1314) Prec@1 73.000 (76.812) Prec@5 100.000 (98.500) +2022-11-14 13:21:56,318 Epoch: [29][160/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.1369 (0.1317) Prec@1 77.000 (76.824) Prec@5 98.000 (98.471) +2022-11-14 13:21:56,677 Epoch: [29][170/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.1276 (0.1315) Prec@1 77.000 (76.833) Prec@5 96.000 (98.333) +2022-11-14 13:21:57,038 Epoch: [29][180/500] Time 0.036 (0.026) Data 0.002 (0.003) Loss 0.1362 (0.1317) Prec@1 77.000 (76.842) Prec@5 97.000 (98.263) +2022-11-14 13:21:57,393 Epoch: [29][190/500] Time 0.036 (0.026) Data 0.001 (0.003) Loss 0.1569 (0.1330) Prec@1 70.000 (76.500) Prec@5 97.000 (98.200) +2022-11-14 13:21:57,747 Epoch: [29][200/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.1049 (0.1316) Prec@1 82.000 (76.762) Prec@5 100.000 (98.286) +2022-11-14 13:21:58,111 Epoch: [29][210/500] Time 0.036 (0.027) Data 0.001 (0.003) Loss 0.1526 (0.1326) Prec@1 70.000 (76.455) Prec@5 98.000 (98.273) +2022-11-14 13:21:58,463 Epoch: [29][220/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1777 (0.1346) Prec@1 69.000 (76.130) Prec@5 96.000 (98.174) +2022-11-14 13:21:58,821 Epoch: [29][230/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1375 (0.1347) Prec@1 74.000 (76.042) Prec@5 99.000 (98.208) +2022-11-14 13:21:59,188 Epoch: [29][240/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1262 (0.1343) Prec@1 77.000 (76.080) Prec@5 97.000 (98.160) +2022-11-14 13:21:59,552 Epoch: [29][250/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.1652 (0.1355) Prec@1 69.000 (75.808) Prec@5 96.000 (98.077) +2022-11-14 13:21:59,901 Epoch: [29][260/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.1193 (0.1349) Prec@1 79.000 (75.926) Prec@5 97.000 (98.037) +2022-11-14 13:22:00,264 Epoch: [29][270/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.1357 (0.1350) Prec@1 79.000 (76.036) Prec@5 98.000 (98.036) +2022-11-14 13:22:00,621 Epoch: [29][280/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.0994 (0.1337) Prec@1 86.000 (76.379) Prec@5 99.000 (98.069) +2022-11-14 13:22:00,975 Epoch: [29][290/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.1250 (0.1334) Prec@1 78.000 (76.433) Prec@5 97.000 (98.033) +2022-11-14 13:22:01,340 Epoch: [29][300/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.1457 (0.1338) Prec@1 74.000 (76.355) Prec@5 99.000 (98.065) +2022-11-14 13:22:01,699 Epoch: [29][310/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.1482 (0.1343) Prec@1 72.000 (76.219) Prec@5 99.000 (98.094) +2022-11-14 13:22:02,058 Epoch: [29][320/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.1015 (0.1333) Prec@1 82.000 (76.394) Prec@5 99.000 (98.121) +2022-11-14 13:22:02,412 Epoch: [29][330/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.1109 (0.1326) Prec@1 79.000 (76.471) Prec@5 99.000 (98.147) +2022-11-14 13:22:02,767 Epoch: [29][340/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.1297 (0.1325) Prec@1 80.000 (76.571) Prec@5 96.000 (98.086) +2022-11-14 13:22:03,123 Epoch: [29][350/500] Time 0.031 (0.029) Data 0.003 (0.002) Loss 0.1477 (0.1330) Prec@1 72.000 (76.444) Prec@5 98.000 (98.083) +2022-11-14 13:22:03,478 Epoch: [29][360/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.1596 (0.1337) Prec@1 74.000 (76.378) Prec@5 98.000 (98.081) +2022-11-14 13:22:03,841 Epoch: [29][370/500] Time 0.041 (0.029) Data 0.002 (0.002) Loss 0.1448 (0.1340) Prec@1 72.000 (76.263) Prec@5 100.000 (98.132) +2022-11-14 13:22:04,196 Epoch: [29][380/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.1684 (0.1349) Prec@1 72.000 (76.154) Prec@5 92.000 (97.974) +2022-11-14 13:22:04,561 Epoch: [29][390/500] Time 0.035 (0.029) Data 0.002 (0.002) Loss 0.1244 (0.1346) Prec@1 78.000 (76.200) Prec@5 97.000 (97.950) +2022-11-14 13:22:04,918 Epoch: [29][400/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.1289 (0.1345) Prec@1 80.000 (76.293) Prec@5 97.000 (97.927) +2022-11-14 13:22:05,332 Epoch: [29][410/500] Time 0.057 (0.029) Data 0.002 (0.002) Loss 0.1551 (0.1350) Prec@1 72.000 (76.190) Prec@5 98.000 (97.929) +2022-11-14 13:22:05,664 Epoch: [29][420/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.1405 (0.1351) Prec@1 76.000 (76.186) Prec@5 94.000 (97.837) +2022-11-14 13:22:06,020 Epoch: [29][430/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0994 (0.1343) Prec@1 84.000 (76.364) Prec@5 99.000 (97.864) +2022-11-14 13:22:06,379 Epoch: [29][440/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.1123 (0.1338) Prec@1 82.000 (76.489) Prec@5 99.000 (97.889) +2022-11-14 13:22:06,724 Epoch: [29][450/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0978 (0.1330) Prec@1 84.000 (76.652) Prec@5 99.000 (97.913) +2022-11-14 13:22:07,106 Epoch: [29][460/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.1645 (0.1337) Prec@1 71.000 (76.532) Prec@5 97.000 (97.894) +2022-11-14 13:22:07,490 Epoch: [29][470/500] Time 0.038 (0.030) Data 0.002 (0.002) Loss 0.1519 (0.1341) Prec@1 73.000 (76.458) Prec@5 98.000 (97.896) +2022-11-14 13:22:07,818 Epoch: [29][480/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.1035 (0.1334) Prec@1 82.000 (76.571) Prec@5 97.000 (97.878) +2022-11-14 13:22:08,178 Epoch: [29][490/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.1587 (0.1339) Prec@1 73.000 (76.500) Prec@5 96.000 (97.840) +2022-11-14 13:22:08,502 Epoch: [29][499/500] Time 0.034 (0.030) Data 0.001 (0.002) Loss 0.1465 (0.1342) Prec@1 73.000 (76.431) Prec@5 98.000 (97.843) +2022-11-14 13:22:08,780 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1526 (0.1526) Prec@1 73.000 (73.000) Prec@5 97.000 (97.000) +2022-11-14 13:22:08,787 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1809 (0.1668) Prec@1 68.000 (70.500) Prec@5 95.000 (96.000) +2022-11-14 13:22:08,798 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1938 (0.1758) Prec@1 64.000 (68.333) Prec@5 92.000 (94.667) +2022-11-14 13:22:08,809 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1649 (0.1731) Prec@1 68.000 (68.250) Prec@5 98.000 (95.500) +2022-11-14 13:22:08,817 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1890 (0.1762) Prec@1 65.000 (67.600) Prec@5 96.000 (95.600) +2022-11-14 13:22:08,826 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1681) Prec@1 76.000 (69.000) Prec@5 98.000 (96.000) +2022-11-14 13:22:08,835 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1963 (0.1721) Prec@1 66.000 (68.571) Prec@5 98.000 (96.286) +2022-11-14 13:22:08,845 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1776 (0.1728) Prec@1 69.000 (68.625) Prec@5 95.000 (96.125) +2022-11-14 13:22:08,854 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1718 (0.1727) Prec@1 72.000 (69.000) Prec@5 95.000 (96.000) +2022-11-14 13:22:08,863 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1725) Prec@1 66.000 (68.700) Prec@5 95.000 (95.900) +2022-11-14 13:22:08,871 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1399 (0.1695) Prec@1 74.000 (69.182) Prec@5 97.000 (96.000) +2022-11-14 13:22:08,880 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1684 (0.1694) Prec@1 69.000 (69.167) Prec@5 98.000 (96.167) +2022-11-14 13:22:08,890 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1502 (0.1679) Prec@1 71.000 (69.308) Prec@5 97.000 (96.231) +2022-11-14 13:22:08,898 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1664 (0.1678) Prec@1 70.000 (69.357) Prec@5 98.000 (96.357) +2022-11-14 13:22:08,906 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1538 (0.1669) Prec@1 73.000 (69.600) Prec@5 97.000 (96.400) +2022-11-14 13:22:08,916 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1953 (0.1687) Prec@1 67.000 (69.438) Prec@5 93.000 (96.188) +2022-11-14 13:22:08,926 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1565 (0.1679) Prec@1 73.000 (69.647) Prec@5 95.000 (96.118) +2022-11-14 13:22:08,936 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2020 (0.1698) Prec@1 63.000 (69.278) Prec@5 96.000 (96.111) +2022-11-14 13:22:08,946 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1544 (0.1690) Prec@1 71.000 (69.368) Prec@5 96.000 (96.105) +2022-11-14 13:22:08,955 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2050 (0.1708) Prec@1 64.000 (69.100) Prec@5 91.000 (95.850) +2022-11-14 13:22:08,964 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1924 (0.1718) Prec@1 67.000 (69.000) Prec@5 97.000 (95.905) +2022-11-14 13:22:08,974 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1539 (0.1710) Prec@1 72.000 (69.136) Prec@5 97.000 (95.955) +2022-11-14 13:22:08,983 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1940 (0.1720) Prec@1 66.000 (69.000) Prec@5 97.000 (96.000) +2022-11-14 13:22:08,992 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1446 (0.1709) Prec@1 76.000 (69.292) Prec@5 98.000 (96.083) +2022-11-14 13:22:09,001 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1577 (0.1704) Prec@1 74.000 (69.480) Prec@5 94.000 (96.000) +2022-11-14 13:22:09,010 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2001 (0.1715) Prec@1 61.000 (69.154) Prec@5 94.000 (95.923) +2022-11-14 13:22:09,021 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1421 (0.1704) Prec@1 77.000 (69.444) Prec@5 98.000 (96.000) +2022-11-14 13:22:09,030 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2040 (0.1716) Prec@1 62.000 (69.179) Prec@5 94.000 (95.929) +2022-11-14 13:22:09,039 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1898 (0.1722) Prec@1 62.000 (68.931) Prec@5 93.000 (95.828) +2022-11-14 13:22:09,049 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1541 (0.1716) Prec@1 72.000 (69.033) Prec@5 93.000 (95.733) +2022-11-14 13:22:09,058 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1482 (0.1709) Prec@1 76.000 (69.258) Prec@5 97.000 (95.774) +2022-11-14 13:22:09,067 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1456 (0.1701) Prec@1 72.000 (69.344) Prec@5 97.000 (95.812) +2022-11-14 13:22:09,076 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1811 (0.1704) Prec@1 65.000 (69.212) Prec@5 93.000 (95.727) +2022-11-14 13:22:09,086 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1760 (0.1706) Prec@1 71.000 (69.265) Prec@5 95.000 (95.706) +2022-11-14 13:22:09,095 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1807 (0.1709) Prec@1 65.000 (69.143) Prec@5 94.000 (95.657) +2022-11-14 13:22:09,104 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1596 (0.1706) Prec@1 68.000 (69.111) Prec@5 96.000 (95.667) +2022-11-14 13:22:09,113 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1975 (0.1713) Prec@1 63.000 (68.946) Prec@5 95.000 (95.649) +2022-11-14 13:22:09,122 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1648 (0.1711) Prec@1 71.000 (69.000) Prec@5 92.000 (95.553) +2022-11-14 13:22:09,131 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1362 (0.1702) Prec@1 76.000 (69.179) Prec@5 94.000 (95.513) +2022-11-14 13:22:09,145 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1648 (0.1701) Prec@1 70.000 (69.200) Prec@5 97.000 (95.550) +2022-11-14 13:22:09,155 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1803 (0.1703) Prec@1 66.000 (69.122) Prec@5 93.000 (95.488) +2022-11-14 13:22:09,164 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.1693) Prec@1 78.000 (69.333) Prec@5 96.000 (95.500) +2022-11-14 13:22:09,173 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1684) Prec@1 76.000 (69.488) Prec@5 98.000 (95.558) +2022-11-14 13:22:09,182 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1463 (0.1679) Prec@1 77.000 (69.659) Prec@5 95.000 (95.545) +2022-11-14 13:22:09,191 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1675) Prec@1 73.000 (69.733) Prec@5 96.000 (95.556) +2022-11-14 13:22:09,200 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1734 (0.1676) Prec@1 67.000 (69.674) Prec@5 94.000 (95.522) +2022-11-14 13:22:09,209 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1587 (0.1674) Prec@1 72.000 (69.723) Prec@5 96.000 (95.532) +2022-11-14 13:22:09,218 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1454 (0.1670) Prec@1 74.000 (69.812) Prec@5 94.000 (95.500) +2022-11-14 13:22:09,227 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1500 (0.1666) Prec@1 74.000 (69.898) Prec@5 96.000 (95.510) +2022-11-14 13:22:09,237 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1829 (0.1669) Prec@1 69.000 (69.880) Prec@5 97.000 (95.540) +2022-11-14 13:22:09,245 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1763 (0.1671) Prec@1 66.000 (69.804) Prec@5 95.000 (95.529) +2022-11-14 13:22:09,254 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1666 (0.1671) Prec@1 68.000 (69.769) Prec@5 98.000 (95.577) +2022-11-14 13:22:09,263 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1734 (0.1672) Prec@1 68.000 (69.736) Prec@5 91.000 (95.491) +2022-11-14 13:22:09,272 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1751 (0.1674) Prec@1 69.000 (69.722) Prec@5 93.000 (95.444) +2022-11-14 13:22:09,280 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1622 (0.1673) Prec@1 71.000 (69.745) Prec@5 97.000 (95.473) +2022-11-14 13:22:09,288 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1851 (0.1676) Prec@1 68.000 (69.714) Prec@5 93.000 (95.429) +2022-11-14 13:22:09,296 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2026 (0.1682) Prec@1 64.000 (69.614) Prec@5 90.000 (95.333) +2022-11-14 13:22:09,306 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1386 (0.1677) Prec@1 77.000 (69.741) Prec@5 98.000 (95.379) +2022-11-14 13:22:09,316 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1888 (0.1681) Prec@1 62.000 (69.610) Prec@5 97.000 (95.407) +2022-11-14 13:22:09,326 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1806 (0.1683) Prec@1 68.000 (69.583) Prec@5 96.000 (95.417) +2022-11-14 13:22:09,335 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1975 (0.1688) Prec@1 63.000 (69.475) Prec@5 95.000 (95.410) +2022-11-14 13:22:09,344 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1794 (0.1689) Prec@1 68.000 (69.452) Prec@5 95.000 (95.403) +2022-11-14 13:22:09,354 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1536 (0.1687) Prec@1 71.000 (69.476) Prec@5 96.000 (95.413) +2022-11-14 13:22:09,363 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1368 (0.1682) Prec@1 78.000 (69.609) Prec@5 98.000 (95.453) +2022-11-14 13:22:09,372 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1776 (0.1683) Prec@1 65.000 (69.538) Prec@5 98.000 (95.492) +2022-11-14 13:22:09,381 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2122 (0.1690) Prec@1 62.000 (69.424) Prec@5 93.000 (95.455) +2022-11-14 13:22:09,391 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1694 (0.1690) Prec@1 73.000 (69.478) Prec@5 97.000 (95.478) +2022-11-14 13:22:09,400 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1797 (0.1692) Prec@1 71.000 (69.500) Prec@5 93.000 (95.441) +2022-11-14 13:22:09,409 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1495 (0.1689) Prec@1 72.000 (69.536) Prec@5 97.000 (95.464) +2022-11-14 13:22:09,419 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1942 (0.1692) Prec@1 66.000 (69.486) Prec@5 94.000 (95.443) +2022-11-14 13:22:09,427 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1347 (0.1687) Prec@1 76.000 (69.577) Prec@5 97.000 (95.465) +2022-11-14 13:22:09,437 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1797 (0.1689) Prec@1 68.000 (69.556) Prec@5 96.000 (95.472) +2022-11-14 13:22:09,447 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1804 (0.1691) Prec@1 70.000 (69.562) Prec@5 96.000 (95.479) +2022-11-14 13:22:09,456 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1727 (0.1691) Prec@1 67.000 (69.527) Prec@5 98.000 (95.514) +2022-11-14 13:22:09,465 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1807 (0.1693) Prec@1 68.000 (69.507) Prec@5 97.000 (95.533) +2022-11-14 13:22:09,475 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1541 (0.1691) Prec@1 70.000 (69.513) Prec@5 99.000 (95.579) +2022-11-14 13:22:09,484 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1447 (0.1687) Prec@1 77.000 (69.610) Prec@5 97.000 (95.597) +2022-11-14 13:22:09,493 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1924 (0.1691) Prec@1 66.000 (69.564) Prec@5 96.000 (95.603) +2022-11-14 13:22:09,502 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1582 (0.1689) Prec@1 74.000 (69.620) Prec@5 95.000 (95.595) +2022-11-14 13:22:09,511 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1977 (0.1693) Prec@1 63.000 (69.537) Prec@5 98.000 (95.625) +2022-11-14 13:22:09,520 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1465 (0.1690) Prec@1 72.000 (69.568) Prec@5 95.000 (95.617) +2022-11-14 13:22:09,530 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1763 (0.1691) Prec@1 69.000 (69.561) Prec@5 97.000 (95.634) +2022-11-14 13:22:09,539 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2013 (0.1695) Prec@1 62.000 (69.470) Prec@5 98.000 (95.663) +2022-11-14 13:22:09,548 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1946 (0.1698) Prec@1 61.000 (69.369) Prec@5 96.000 (95.667) +2022-11-14 13:22:09,557 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1762 (0.1698) Prec@1 66.000 (69.329) Prec@5 91.000 (95.612) +2022-11-14 13:22:09,566 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1733 (0.1699) Prec@1 67.000 (69.302) Prec@5 95.000 (95.605) +2022-11-14 13:22:09,576 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1720 (0.1699) Prec@1 69.000 (69.299) Prec@5 96.000 (95.609) +2022-11-14 13:22:09,584 Test: 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0.1753 (0.1691) Prec@1 69.000 (69.394) Prec@5 90.000 (95.574) +2022-11-14 13:22:09,648 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1810 (0.1692) Prec@1 67.000 (69.368) Prec@5 96.000 (95.579) +2022-11-14 13:22:09,657 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1614 (0.1691) Prec@1 72.000 (69.396) Prec@5 96.000 (95.583) +2022-11-14 13:22:09,666 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1290 (0.1687) Prec@1 77.000 (69.474) Prec@5 95.000 (95.577) +2022-11-14 13:22:09,675 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1815 (0.1689) Prec@1 70.000 (69.480) Prec@5 96.000 (95.582) +2022-11-14 13:22:09,684 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1759 (0.1689) Prec@1 68.000 (69.465) Prec@5 96.000 (95.586) +2022-11-14 13:22:09,693 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1841 (0.1691) Prec@1 68.000 (69.450) Prec@5 92.000 (95.550) +2022-11-14 13:22:09,767 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:22:10,100 Epoch: [30][0/500] Time 0.026 (0.026) Data 0.247 (0.247) Loss 0.1294 (0.1294) Prec@1 79.000 (79.000) Prec@5 97.000 (97.000) +2022-11-14 13:22:10,324 Epoch: [30][10/500] Time 0.018 (0.020) Data 0.002 (0.024) Loss 0.1188 (0.1241) Prec@1 78.000 (78.500) Prec@5 99.000 (98.000) +2022-11-14 13:22:10,540 Epoch: [30][20/500] Time 0.021 (0.020) Data 0.001 (0.013) Loss 0.1419 (0.1300) Prec@1 74.000 (77.000) Prec@5 97.000 (97.667) +2022-11-14 13:22:10,779 Epoch: [30][30/500] Time 0.025 (0.020) Data 0.002 (0.010) Loss 0.1197 (0.1274) Prec@1 79.000 (77.500) Prec@5 96.000 (97.250) +2022-11-14 13:22:11,238 Epoch: [30][40/500] Time 0.043 (0.024) Data 0.002 (0.008) Loss 0.1381 (0.1296) Prec@1 76.000 (77.200) Prec@5 97.000 (97.200) +2022-11-14 13:22:11,630 Epoch: [30][50/500] Time 0.040 (0.026) Data 0.001 (0.007) Loss 0.1549 (0.1338) Prec@1 74.000 (76.667) Prec@5 97.000 (97.167) +2022-11-14 13:22:12,049 Epoch: [30][60/500] Time 0.044 (0.028) Data 0.002 (0.006) Loss 0.1462 (0.1356) Prec@1 74.000 (76.286) Prec@5 98.000 (97.286) +2022-11-14 13:22:12,472 Epoch: [30][70/500] Time 0.038 (0.029) Data 0.002 (0.005) Loss 0.1735 (0.1403) Prec@1 70.000 (75.500) Prec@5 97.000 (97.250) +2022-11-14 13:22:12,877 Epoch: [30][80/500] Time 0.038 (0.030) Data 0.002 (0.005) Loss 0.1126 (0.1372) Prec@1 81.000 (76.111) Prec@5 99.000 (97.444) +2022-11-14 13:22:13,289 Epoch: [30][90/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.1491 (0.1384) Prec@1 75.000 (76.000) Prec@5 96.000 (97.300) +2022-11-14 13:22:13,754 Epoch: [30][100/500] Time 0.039 (0.032) Data 0.002 (0.004) Loss 0.1629 (0.1406) Prec@1 72.000 (75.636) Prec@5 98.000 (97.364) +2022-11-14 13:22:14,225 Epoch: [30][110/500] Time 0.034 (0.033) Data 0.001 (0.004) Loss 0.1348 (0.1402) Prec@1 72.000 (75.333) Prec@5 97.000 (97.333) +2022-11-14 13:22:14,677 Epoch: [30][120/500] Time 0.037 (0.034) Data 0.002 (0.004) Loss 0.1419 (0.1403) Prec@1 78.000 (75.538) Prec@5 98.000 (97.385) +2022-11-14 13:22:15,133 Epoch: [30][130/500] Time 0.039 (0.034) Data 0.002 (0.004) Loss 0.0952 (0.1371) Prec@1 83.000 (76.071) Prec@5 98.000 (97.429) +2022-11-14 13:22:15,620 Epoch: [30][140/500] Time 0.057 (0.035) Data 0.002 (0.004) Loss 0.1140 (0.1355) Prec@1 80.000 (76.333) Prec@5 99.000 (97.533) +2022-11-14 13:22:16,142 Epoch: [30][150/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.1412 (0.1359) Prec@1 77.000 (76.375) Prec@5 94.000 (97.312) +2022-11-14 13:22:16,663 Epoch: [30][160/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.1433 (0.1363) Prec@1 76.000 (76.353) Prec@5 97.000 (97.294) +2022-11-14 13:22:17,187 Epoch: [30][170/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.1040 (0.1345) Prec@1 84.000 (76.778) Prec@5 98.000 (97.333) +2022-11-14 13:22:17,592 Epoch: [30][180/500] Time 0.031 (0.037) Data 0.002 (0.003) Loss 0.1265 (0.1341) Prec@1 78.000 (76.842) Prec@5 97.000 (97.316) +2022-11-14 13:22:18,079 Epoch: [30][190/500] Time 0.039 (0.037) Data 0.003 (0.003) Loss 0.1255 (0.1337) Prec@1 79.000 (76.950) Prec@5 99.000 (97.400) +2022-11-14 13:22:18,525 Epoch: [30][200/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.1147 (0.1328) Prec@1 75.000 (76.857) Prec@5 99.000 (97.476) +2022-11-14 13:22:18,943 Epoch: [30][210/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.1216 (0.1323) Prec@1 81.000 (77.045) Prec@5 99.000 (97.545) +2022-11-14 13:22:19,356 Epoch: [30][220/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.1583 (0.1334) Prec@1 68.000 (76.652) Prec@5 97.000 (97.522) +2022-11-14 13:22:19,785 Epoch: [30][230/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.1330 (0.1334) Prec@1 78.000 (76.708) Prec@5 99.000 (97.583) +2022-11-14 13:22:20,255 Epoch: [30][240/500] Time 0.031 (0.037) Data 0.002 (0.003) Loss 0.1489 (0.1340) Prec@1 71.000 (76.480) Prec@5 100.000 (97.680) +2022-11-14 13:22:20,666 Epoch: [30][250/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.1754 (0.1356) Prec@1 71.000 (76.269) Prec@5 98.000 (97.692) +2022-11-14 13:22:21,079 Epoch: [30][260/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1328 (0.1355) Prec@1 78.000 (76.333) Prec@5 94.000 (97.556) +2022-11-14 13:22:21,486 Epoch: [30][270/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1275 (0.1352) Prec@1 74.000 (76.250) Prec@5 99.000 (97.607) +2022-11-14 13:22:21,892 Epoch: [30][280/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1510 (0.1358) Prec@1 72.000 (76.103) Prec@5 97.000 (97.586) +2022-11-14 13:22:22,303 Epoch: [30][290/500] Time 0.038 (0.037) Data 0.001 (0.003) Loss 0.1101 (0.1349) Prec@1 81.000 (76.267) Prec@5 98.000 (97.600) +2022-11-14 13:22:22,706 Epoch: [30][300/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1288 (0.1347) Prec@1 78.000 (76.323) Prec@5 97.000 (97.581) +2022-11-14 13:22:23,112 Epoch: [30][310/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1418 (0.1349) Prec@1 74.000 (76.250) Prec@5 98.000 (97.594) +2022-11-14 13:22:23,625 Epoch: [30][320/500] Time 0.030 (0.038) Data 0.002 (0.003) Loss 0.1296 (0.1348) Prec@1 77.000 (76.273) Prec@5 99.000 (97.636) +2022-11-14 13:22:24,026 Epoch: [30][330/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1203 (0.1343) Prec@1 80.000 (76.382) Prec@5 96.000 (97.588) +2022-11-14 13:22:24,432 Epoch: [30][340/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.1523 (0.1349) Prec@1 74.000 (76.314) Prec@5 95.000 (97.514) +2022-11-14 13:22:24,843 Epoch: [30][350/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.1397 (0.1350) Prec@1 74.000 (76.250) Prec@5 97.000 (97.500) +2022-11-14 13:22:25,251 Epoch: [30][360/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1307 (0.1349) Prec@1 77.000 (76.270) Prec@5 96.000 (97.459) +2022-11-14 13:22:25,719 Epoch: [30][370/500] Time 0.033 (0.037) Data 0.002 (0.003) Loss 0.1362 (0.1349) Prec@1 77.000 (76.289) Prec@5 97.000 (97.447) +2022-11-14 13:22:26,141 Epoch: [30][380/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.1179 (0.1345) Prec@1 78.000 (76.333) Prec@5 99.000 (97.487) +2022-11-14 13:22:26,575 Epoch: [30][390/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.1145 (0.1340) Prec@1 78.000 (76.375) Prec@5 95.000 (97.425) +2022-11-14 13:22:26,980 Epoch: [30][400/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1045 (0.1332) Prec@1 79.000 (76.439) Prec@5 100.000 (97.488) +2022-11-14 13:22:27,384 Epoch: [30][410/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1277 (0.1331) Prec@1 77.000 (76.452) Prec@5 98.000 (97.500) +2022-11-14 13:22:27,784 Epoch: [30][420/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.1318 (0.1331) Prec@1 77.000 (76.465) Prec@5 99.000 (97.535) +2022-11-14 13:22:28,184 Epoch: [30][430/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1514 (0.1335) Prec@1 73.000 (76.386) Prec@5 95.000 (97.477) +2022-11-14 13:22:28,620 Epoch: [30][440/500] Time 0.065 (0.037) Data 0.002 (0.002) Loss 0.1421 (0.1337) Prec@1 73.000 (76.311) Prec@5 99.000 (97.511) +2022-11-14 13:22:29,016 Epoch: [30][450/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1075 (0.1331) Prec@1 80.000 (76.391) Prec@5 100.000 (97.565) +2022-11-14 13:22:29,462 Epoch: [30][460/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.1088 (0.1326) Prec@1 81.000 (76.489) Prec@5 98.000 (97.574) +2022-11-14 13:22:29,863 Epoch: [30][470/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.1185 (0.1323) Prec@1 80.000 (76.562) Prec@5 99.000 (97.604) +2022-11-14 13:22:30,263 Epoch: [30][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1069 (0.1318) Prec@1 82.000 (76.673) Prec@5 99.000 (97.633) +2022-11-14 13:22:30,663 Epoch: [30][490/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1376 (0.1319) Prec@1 74.000 (76.620) Prec@5 96.000 (97.600) +2022-11-14 13:22:31,129 Epoch: [30][499/500] Time 0.053 (0.037) Data 0.002 (0.002) Loss 0.1078 (0.1314) Prec@1 82.000 (76.725) Prec@5 98.000 (97.608) +2022-11-14 13:22:31,420 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1894 (0.1894) Prec@1 65.000 (65.000) Prec@5 99.000 (99.000) +2022-11-14 13:22:31,428 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1772 (0.1833) Prec@1 70.000 (67.500) Prec@5 95.000 (97.000) +2022-11-14 13:22:31,437 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1954 (0.1873) Prec@1 65.000 (66.667) Prec@5 95.000 (96.333) +2022-11-14 13:22:31,449 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1452 (0.1768) Prec@1 72.000 (68.000) Prec@5 98.000 (96.750) +2022-11-14 13:22:31,458 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2148 (0.1844) Prec@1 61.000 (66.600) Prec@5 96.000 (96.600) +2022-11-14 13:22:31,467 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1512 (0.1789) Prec@1 72.000 (67.500) Prec@5 98.000 (96.833) +2022-11-14 13:22:31,476 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1680 (0.1773) Prec@1 71.000 (68.000) Prec@5 95.000 (96.571) +2022-11-14 13:22:31,486 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1875 (0.1786) Prec@1 65.000 (67.625) Prec@5 94.000 (96.250) +2022-11-14 13:22:31,495 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1826 (0.1790) Prec@1 66.000 (67.444) Prec@5 97.000 (96.333) +2022-11-14 13:22:31,503 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.1749) Prec@1 73.000 (68.000) Prec@5 97.000 (96.400) +2022-11-14 13:22:31,513 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1766 (0.1751) Prec@1 65.000 (67.727) Prec@5 97.000 (96.455) +2022-11-14 13:22:31,522 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2018 (0.1773) Prec@1 64.000 (67.417) Prec@5 93.000 (96.167) +2022-11-14 13:22:31,531 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1463 (0.1749) Prec@1 72.000 (67.769) Prec@5 100.000 (96.462) +2022-11-14 13:22:31,541 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.1752) Prec@1 63.000 (67.429) Prec@5 98.000 (96.571) +2022-11-14 13:22:31,550 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1710 (0.1749) Prec@1 70.000 (67.600) Prec@5 97.000 (96.600) +2022-11-14 13:22:31,559 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2341 (0.1786) Prec@1 57.000 (66.938) Prec@5 95.000 (96.500) +2022-11-14 13:22:31,569 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1771) Prec@1 70.000 (67.118) Prec@5 97.000 (96.529) +2022-11-14 13:22:31,579 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1765 (0.1771) Prec@1 65.000 (67.000) Prec@5 93.000 (96.333) +2022-11-14 13:22:31,588 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1634 (0.1764) Prec@1 67.000 (67.000) Prec@5 95.000 (96.263) +2022-11-14 13:22:31,598 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1568 (0.1754) Prec@1 75.000 (67.400) Prec@5 97.000 (96.300) +2022-11-14 13:22:31,608 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1859 (0.1759) Prec@1 68.000 (67.429) Prec@5 97.000 (96.333) +2022-11-14 13:22:31,617 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1855 (0.1763) Prec@1 67.000 (67.409) Prec@5 94.000 (96.227) +2022-11-14 13:22:31,627 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1797 (0.1765) Prec@1 68.000 (67.435) Prec@5 94.000 (96.130) +2022-11-14 13:22:31,636 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1965 (0.1773) Prec@1 63.000 (67.250) Prec@5 99.000 (96.250) +2022-11-14 13:22:31,645 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1779 (0.1773) Prec@1 64.000 (67.120) Prec@5 97.000 (96.280) +2022-11-14 13:22:31,655 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2211 (0.1790) Prec@1 57.000 (66.731) Prec@5 91.000 (96.077) +2022-11-14 13:22:31,664 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.1781) Prec@1 73.000 (66.963) Prec@5 98.000 (96.148) +2022-11-14 13:22:31,673 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1796 (0.1782) Prec@1 65.000 (66.893) Prec@5 94.000 (96.071) +2022-11-14 13:22:31,682 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1629 (0.1776) Prec@1 69.000 (66.966) Prec@5 97.000 (96.103) +2022-11-14 13:22:31,691 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1651 (0.1772) Prec@1 72.000 (67.133) Prec@5 100.000 (96.233) +2022-11-14 13:22:31,701 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1794 (0.1773) Prec@1 65.000 (67.065) Prec@5 97.000 (96.258) +2022-11-14 13:22:31,710 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1767) Prec@1 72.000 (67.219) Prec@5 97.000 (96.281) +2022-11-14 13:22:31,718 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1787 (0.1768) Prec@1 70.000 (67.303) Prec@5 93.000 (96.182) +2022-11-14 13:22:31,728 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1891 (0.1771) Prec@1 64.000 (67.206) Prec@5 94.000 (96.118) +2022-11-14 13:22:31,738 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1944 (0.1776) Prec@1 60.000 (67.000) Prec@5 93.000 (96.029) +2022-11-14 13:22:31,747 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1627 (0.1772) Prec@1 74.000 (67.194) Prec@5 96.000 (96.028) +2022-11-14 13:22:31,757 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2007 (0.1778) Prec@1 64.000 (67.108) Prec@5 97.000 (96.054) +2022-11-14 13:22:31,767 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1577 (0.1773) Prec@1 71.000 (67.211) Prec@5 97.000 (96.079) +2022-11-14 13:22:31,778 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1555 (0.1767) Prec@1 73.000 (67.359) Prec@5 98.000 (96.128) +2022-11-14 13:22:31,788 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1515 (0.1761) Prec@1 71.000 (67.450) Prec@5 97.000 (96.150) +2022-11-14 13:22:31,798 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1832 (0.1763) Prec@1 67.000 (67.439) Prec@5 92.000 (96.049) +2022-11-14 13:22:31,808 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1853 (0.1765) Prec@1 67.000 (67.429) Prec@5 97.000 (96.071) +2022-11-14 13:22:31,816 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1510 (0.1759) Prec@1 71.000 (67.512) Prec@5 99.000 (96.140) +2022-11-14 13:22:31,826 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1642 (0.1756) Prec@1 72.000 (67.614) Prec@5 96.000 (96.136) +2022-11-14 13:22:31,835 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1664 (0.1754) Prec@1 72.000 (67.711) Prec@5 98.000 (96.178) +2022-11-14 13:22:31,844 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1535 (0.1750) Prec@1 71.000 (67.783) Prec@5 98.000 (96.217) +2022-11-14 13:22:31,853 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1567 (0.1746) Prec@1 72.000 (67.872) Prec@5 99.000 (96.277) +2022-11-14 13:22:31,863 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1732 (0.1745) Prec@1 71.000 (67.938) Prec@5 94.000 (96.229) +2022-11-14 13:22:31,872 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1739) Prec@1 74.000 (68.061) Prec@5 99.000 (96.286) +2022-11-14 13:22:31,881 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2170 (0.1748) Prec@1 58.000 (67.860) Prec@5 96.000 (96.280) +2022-11-14 13:22:31,891 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2115 (0.1755) Prec@1 62.000 (67.745) Prec@5 95.000 (96.255) +2022-11-14 13:22:31,900 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2283 (0.1765) Prec@1 59.000 (67.577) Prec@5 95.000 (96.231) +2022-11-14 13:22:31,909 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1975 (0.1769) Prec@1 65.000 (67.528) Prec@5 96.000 (96.226) +2022-11-14 13:22:31,919 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1787 (0.1770) Prec@1 64.000 (67.463) Prec@5 97.000 (96.241) +2022-11-14 13:22:31,927 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1877 (0.1772) Prec@1 67.000 (67.455) Prec@5 96.000 (96.236) +2022-11-14 13:22:31,937 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1814 (0.1772) Prec@1 66.000 (67.429) Prec@5 96.000 (96.232) +2022-11-14 13:22:31,946 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1961 (0.1776) Prec@1 62.000 (67.333) Prec@5 98.000 (96.263) +2022-11-14 13:22:31,955 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1688 (0.1774) Prec@1 66.000 (67.310) Prec@5 97.000 (96.276) +2022-11-14 13:22:31,964 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2005 (0.1778) Prec@1 60.000 (67.186) Prec@5 97.000 (96.288) +2022-11-14 13:22:31,974 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1669 (0.1776) Prec@1 73.000 (67.283) Prec@5 95.000 (96.267) +2022-11-14 13:22:31,983 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1911 (0.1778) Prec@1 67.000 (67.279) Prec@5 99.000 (96.311) +2022-11-14 13:22:31,992 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1811 (0.1779) Prec@1 64.000 (67.226) Prec@5 98.000 (96.339) +2022-11-14 13:22:32,001 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1832 (0.1780) Prec@1 66.000 (67.206) Prec@5 99.000 (96.381) +2022-11-14 13:22:32,010 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1767 (0.1780) Prec@1 71.000 (67.266) Prec@5 92.000 (96.312) +2022-11-14 13:22:32,019 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1734 (0.1779) Prec@1 68.000 (67.277) Prec@5 98.000 (96.338) +2022-11-14 13:22:32,029 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2014 (0.1782) Prec@1 64.000 (67.227) Prec@5 94.000 (96.303) +2022-11-14 13:22:32,038 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2148 (0.1788) Prec@1 61.000 (67.134) Prec@5 99.000 (96.343) +2022-11-14 13:22:32,048 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1786) Prec@1 73.000 (67.221) Prec@5 98.000 (96.368) +2022-11-14 13:22:32,058 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1927 (0.1788) Prec@1 67.000 (67.217) Prec@5 100.000 (96.420) +2022-11-14 13:22:32,067 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1909 (0.1790) Prec@1 64.000 (67.171) Prec@5 90.000 (96.329) +2022-11-14 13:22:32,077 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1757 (0.1789) Prec@1 66.000 (67.155) Prec@5 96.000 (96.324) +2022-11-14 13:22:32,085 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1982 (0.1792) Prec@1 59.000 (67.042) Prec@5 97.000 (96.333) +2022-11-14 13:22:32,094 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1711 (0.1791) Prec@1 67.000 (67.041) Prec@5 99.000 (96.370) +2022-11-14 13:22:32,103 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1626 (0.1789) Prec@1 64.000 (67.000) Prec@5 99.000 (96.405) +2022-11-14 13:22:32,113 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1912 (0.1790) Prec@1 69.000 (67.027) Prec@5 96.000 (96.400) +2022-11-14 13:22:32,122 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1461 (0.1786) Prec@1 75.000 (67.132) Prec@5 100.000 (96.447) +2022-11-14 13:22:32,132 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2032 (0.1789) Prec@1 66.000 (67.117) Prec@5 96.000 (96.442) +2022-11-14 13:22:32,140 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1598 (0.1787) Prec@1 68.000 (67.128) Prec@5 96.000 (96.436) +2022-11-14 13:22:32,149 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1997 (0.1789) Prec@1 63.000 (67.076) Prec@5 97.000 (96.443) +2022-11-14 13:22:32,159 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1786) Prec@1 76.000 (67.188) Prec@5 96.000 (96.438) +2022-11-14 13:22:32,168 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1872 (0.1787) Prec@1 66.000 (67.173) Prec@5 96.000 (96.432) +2022-11-14 13:22:32,177 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1784) Prec@1 72.000 (67.232) Prec@5 98.000 (96.451) +2022-11-14 13:22:32,187 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1552 (0.1781) Prec@1 70.000 (67.265) Prec@5 97.000 (96.458) +2022-11-14 13:22:32,196 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1756 (0.1781) Prec@1 69.000 (67.286) Prec@5 98.000 (96.476) +2022-11-14 13:22:32,205 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1794 (0.1781) Prec@1 66.000 (67.271) Prec@5 96.000 (96.471) +2022-11-14 13:22:32,215 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1835 (0.1782) Prec@1 63.000 (67.221) Prec@5 94.000 (96.442) +2022-11-14 13:22:32,224 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1508 (0.1779) Prec@1 73.000 (67.287) Prec@5 97.000 (96.448) +2022-11-14 13:22:32,233 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1799 (0.1779) Prec@1 66.000 (67.273) Prec@5 97.000 (96.455) +2022-11-14 13:22:32,243 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1900 (0.1780) Prec@1 65.000 (67.247) Prec@5 92.000 (96.404) +2022-11-14 13:22:32,252 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1747 (0.1780) Prec@1 71.000 (67.289) Prec@5 96.000 (96.400) +2022-11-14 13:22:32,261 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1657 (0.1779) Prec@1 71.000 (67.330) Prec@5 97.000 (96.407) +2022-11-14 13:22:32,271 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1363 (0.1774) Prec@1 76.000 (67.424) Prec@5 97.000 (96.413) +2022-11-14 13:22:32,280 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1723 (0.1774) Prec@1 70.000 (67.452) Prec@5 95.000 (96.398) +2022-11-14 13:22:32,289 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1782 (0.1774) Prec@1 68.000 (67.457) Prec@5 94.000 (96.372) +2022-11-14 13:22:32,298 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1687 (0.1773) Prec@1 70.000 (67.484) Prec@5 98.000 (96.389) +2022-11-14 13:22:32,306 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1777 (0.1773) Prec@1 69.000 (67.500) Prec@5 97.000 (96.396) +2022-11-14 13:22:32,314 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1676 (0.1772) Prec@1 68.000 (67.505) Prec@5 99.000 (96.423) +2022-11-14 13:22:32,322 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1772) Prec@1 69.000 (67.520) Prec@5 97.000 (96.429) +2022-11-14 13:22:32,330 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2017 (0.1774) Prec@1 65.000 (67.495) Prec@5 97.000 (96.434) +2022-11-14 13:22:32,339 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2091 (0.1777) Prec@1 61.000 (67.430) Prec@5 98.000 (96.450) +2022-11-14 13:22:32,395 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:22:32,718 Epoch: [31][0/500] Time 0.032 (0.032) Data 0.233 (0.233) Loss 0.1197 (0.1197) Prec@1 80.000 (80.000) Prec@5 97.000 (97.000) +2022-11-14 13:22:32,925 Epoch: [31][10/500] Time 0.017 (0.020) Data 0.002 (0.023) Loss 0.1548 (0.1373) Prec@1 72.000 (76.000) Prec@5 99.000 (98.000) +2022-11-14 13:22:33,129 Epoch: [31][20/500] Time 0.019 (0.019) Data 0.002 (0.013) Loss 0.0993 (0.1246) Prec@1 84.000 (78.667) Prec@5 99.000 (98.333) +2022-11-14 13:22:33,334 Epoch: [31][30/500] Time 0.018 (0.019) Data 0.002 (0.009) Loss 0.1082 (0.1205) Prec@1 84.000 (80.000) Prec@5 96.000 (97.750) +2022-11-14 13:22:33,552 Epoch: [31][40/500] Time 0.019 (0.019) Data 0.002 (0.007) Loss 0.1230 (0.1210) Prec@1 78.000 (79.600) Prec@5 98.000 (97.800) +2022-11-14 13:22:33,784 Epoch: [31][50/500] Time 0.017 (0.019) Data 0.002 (0.006) Loss 0.1382 (0.1239) Prec@1 78.000 (79.333) Prec@5 97.000 (97.667) +2022-11-14 13:22:34,013 Epoch: [31][60/500] Time 0.017 (0.019) Data 0.002 (0.006) Loss 0.1526 (0.1280) Prec@1 70.000 (78.000) Prec@5 96.000 (97.429) +2022-11-14 13:22:34,251 Epoch: [31][70/500] Time 0.023 (0.019) Data 0.002 (0.005) Loss 0.1486 (0.1306) Prec@1 73.000 (77.375) Prec@5 96.000 (97.250) +2022-11-14 13:22:34,726 Epoch: [31][80/500] Time 0.036 (0.022) Data 0.002 (0.005) Loss 0.1626 (0.1341) Prec@1 71.000 (76.667) Prec@5 94.000 (96.889) +2022-11-14 13:22:35,340 Epoch: [31][90/500] Time 0.037 (0.026) Data 0.003 (0.004) Loss 0.1457 (0.1353) Prec@1 73.000 (76.300) Prec@5 93.000 (96.500) +2022-11-14 13:22:35,835 Epoch: [31][100/500] Time 0.055 (0.028) Data 0.002 (0.004) Loss 0.1420 (0.1359) Prec@1 76.000 (76.273) Prec@5 97.000 (96.545) +2022-11-14 13:22:36,314 Epoch: [31][110/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.1293 (0.1353) Prec@1 76.000 (76.250) Prec@5 99.000 (96.750) +2022-11-14 13:22:36,899 Epoch: [31][120/500] Time 0.051 (0.031) Data 0.002 (0.004) Loss 0.1164 (0.1339) Prec@1 82.000 (76.692) Prec@5 99.000 (96.923) +2022-11-14 13:22:37,449 Epoch: [31][130/500] Time 0.052 (0.033) Data 0.002 (0.004) Loss 0.1404 (0.1344) Prec@1 73.000 (76.429) Prec@5 97.000 (96.929) +2022-11-14 13:22:38,007 Epoch: [31][140/500] Time 0.047 (0.034) Data 0.002 (0.003) Loss 0.1244 (0.1337) Prec@1 78.000 (76.533) Prec@5 99.000 (97.067) +2022-11-14 13:22:38,484 Epoch: [31][150/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.1361 (0.1338) Prec@1 76.000 (76.500) Prec@5 98.000 (97.125) +2022-11-14 13:22:38,779 Epoch: [31][160/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.1045 (0.1321) Prec@1 84.000 (76.941) Prec@5 100.000 (97.294) +2022-11-14 13:22:39,076 Epoch: [31][170/500] Time 0.026 (0.034) Data 0.003 (0.003) Loss 0.1445 (0.1328) Prec@1 74.000 (76.778) Prec@5 98.000 (97.333) +2022-11-14 13:22:39,418 Epoch: [31][180/500] Time 0.023 (0.033) Data 0.002 (0.003) Loss 0.1339 (0.1329) Prec@1 75.000 (76.684) Prec@5 98.000 (97.368) +2022-11-14 13:22:39,764 Epoch: [31][190/500] Time 0.022 (0.033) Data 0.002 (0.003) Loss 0.1470 (0.1336) Prec@1 70.000 (76.350) Prec@5 100.000 (97.500) +2022-11-14 13:22:40,135 Epoch: [31][200/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.1359 (0.1337) Prec@1 73.000 (76.190) Prec@5 99.000 (97.571) +2022-11-14 13:22:40,498 Epoch: [31][210/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.1413 (0.1340) Prec@1 75.000 (76.136) Prec@5 99.000 (97.636) +2022-11-14 13:22:40,810 Epoch: [31][220/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.1330 (0.1340) Prec@1 77.000 (76.174) Prec@5 98.000 (97.652) +2022-11-14 13:22:41,187 Epoch: [31][230/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.1083 (0.1329) Prec@1 80.000 (76.333) Prec@5 99.000 (97.708) +2022-11-14 13:22:41,485 Epoch: [31][240/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.1887 (0.1351) Prec@1 66.000 (75.920) Prec@5 95.000 (97.600) +2022-11-14 13:22:41,831 Epoch: [31][250/500] Time 0.052 (0.033) Data 0.002 (0.003) Loss 0.1666 (0.1364) Prec@1 71.000 (75.731) Prec@5 94.000 (97.462) +2022-11-14 13:22:42,111 Epoch: [31][260/500] Time 0.027 (0.032) Data 0.001 (0.003) Loss 0.1267 (0.1360) Prec@1 79.000 (75.852) Prec@5 100.000 (97.556) +2022-11-14 13:22:42,416 Epoch: [31][270/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.1475 (0.1364) Prec@1 76.000 (75.857) Prec@5 96.000 (97.500) +2022-11-14 13:22:42,716 Epoch: [31][280/500] Time 0.030 (0.032) Data 0.001 (0.003) Loss 0.1059 (0.1354) Prec@1 85.000 (76.172) Prec@5 98.000 (97.517) +2022-11-14 13:22:43,017 Epoch: [31][290/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.1477 (0.1358) Prec@1 69.000 (75.933) Prec@5 98.000 (97.533) +2022-11-14 13:22:43,317 Epoch: [31][300/500] Time 0.029 (0.032) Data 0.002 (0.003) Loss 0.1643 (0.1367) Prec@1 68.000 (75.677) Prec@5 96.000 (97.484) +2022-11-14 13:22:43,628 Epoch: [31][310/500] Time 0.027 (0.031) Data 0.002 (0.003) Loss 0.1188 (0.1361) Prec@1 83.000 (75.906) Prec@5 99.000 (97.531) +2022-11-14 13:22:43,957 Epoch: [31][320/500] Time 0.026 (0.031) Data 0.002 (0.003) Loss 0.1512 (0.1366) Prec@1 74.000 (75.848) Prec@5 98.000 (97.545) +2022-11-14 13:22:44,262 Epoch: [31][330/500] Time 0.026 (0.031) Data 0.002 (0.003) Loss 0.1241 (0.1362) Prec@1 77.000 (75.882) Prec@5 97.000 (97.529) +2022-11-14 13:22:44,600 Epoch: [31][340/500] Time 0.025 (0.031) Data 0.002 (0.003) Loss 0.1436 (0.1364) Prec@1 78.000 (75.943) Prec@5 96.000 (97.486) +2022-11-14 13:22:44,953 Epoch: [31][350/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.1347 (0.1364) Prec@1 79.000 (76.028) Prec@5 99.000 (97.528) +2022-11-14 13:22:45,227 Epoch: [31][360/500] Time 0.026 (0.031) Data 0.002 (0.003) Loss 0.1138 (0.1358) Prec@1 81.000 (76.162) Prec@5 98.000 (97.541) +2022-11-14 13:22:45,589 Epoch: [31][370/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.1143 (0.1352) Prec@1 81.000 (76.289) Prec@5 98.000 (97.553) +2022-11-14 13:22:45,970 Epoch: [31][380/500] Time 0.070 (0.031) Data 0.002 (0.002) Loss 0.1260 (0.1350) Prec@1 80.000 (76.385) Prec@5 100.000 (97.615) +2022-11-14 13:22:46,481 Epoch: [31][390/500] Time 0.044 (0.031) Data 0.001 (0.002) Loss 0.1181 (0.1346) Prec@1 78.000 (76.425) Prec@5 99.000 (97.650) +2022-11-14 13:22:46,996 Epoch: [31][400/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.1833 (0.1357) Prec@1 66.000 (76.171) Prec@5 98.000 (97.659) +2022-11-14 13:22:47,469 Epoch: [31][410/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.1522 (0.1361) Prec@1 70.000 (76.024) Prec@5 95.000 (97.595) +2022-11-14 13:22:47,946 Epoch: [31][420/500] Time 0.051 (0.032) Data 0.001 (0.002) Loss 0.1259 (0.1359) Prec@1 75.000 (76.000) Prec@5 94.000 (97.512) +2022-11-14 13:22:48,411 Epoch: [31][430/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.1282 (0.1357) Prec@1 77.000 (76.023) Prec@5 97.000 (97.500) +2022-11-14 13:22:48,932 Epoch: [31][440/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.1148 (0.1353) Prec@1 77.000 (76.044) Prec@5 100.000 (97.556) +2022-11-14 13:22:49,388 Epoch: [31][450/500] Time 0.052 (0.033) Data 0.002 (0.002) Loss 0.1226 (0.1350) Prec@1 77.000 (76.065) Prec@5 100.000 (97.609) +2022-11-14 13:22:49,856 Epoch: [31][460/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.1259 (0.1348) Prec@1 78.000 (76.106) Prec@5 98.000 (97.617) +2022-11-14 13:22:50,328 Epoch: [31][470/500] Time 0.044 (0.033) Data 0.001 (0.002) Loss 0.1233 (0.1345) Prec@1 79.000 (76.167) Prec@5 99.000 (97.646) +2022-11-14 13:22:50,797 Epoch: [31][480/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.1201 (0.1343) Prec@1 77.000 (76.184) Prec@5 96.000 (97.612) +2022-11-14 13:22:51,393 Epoch: [31][490/500] Time 0.064 (0.034) Data 0.002 (0.002) Loss 0.1456 (0.1345) Prec@1 74.000 (76.140) Prec@5 98.000 (97.620) +2022-11-14 13:22:51,787 Epoch: [31][499/500] Time 0.051 (0.034) Data 0.001 (0.002) Loss 0.1161 (0.1341) Prec@1 77.000 (76.157) Prec@5 98.000 (97.627) +2022-11-14 13:22:52,090 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1409 (0.1409) Prec@1 76.000 (76.000) Prec@5 99.000 (99.000) +2022-11-14 13:22:52,098 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1852 (0.1631) Prec@1 66.000 (71.000) Prec@5 95.000 (97.000) +2022-11-14 13:22:52,106 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1827 (0.1696) Prec@1 68.000 (70.000) Prec@5 98.000 (97.333) +2022-11-14 13:22:52,117 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1649 (0.1684) Prec@1 70.000 (70.000) Prec@5 96.000 (97.000) +2022-11-14 13:22:52,126 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1917 (0.1731) Prec@1 63.000 (68.600) Prec@5 94.000 (96.400) +2022-11-14 13:22:52,134 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1699) Prec@1 71.000 (69.000) Prec@5 99.000 (96.833) +2022-11-14 13:22:52,142 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1624 (0.1688) Prec@1 74.000 (69.714) Prec@5 98.000 (97.000) +2022-11-14 13:22:52,153 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1763 (0.1698) Prec@1 67.000 (69.375) Prec@5 96.000 (96.875) +2022-11-14 13:22:52,160 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1930 (0.1723) Prec@1 67.000 (69.111) Prec@5 98.000 (97.000) +2022-11-14 13:22:52,168 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1402 (0.1691) Prec@1 75.000 (69.700) Prec@5 97.000 (97.000) +2022-11-14 13:22:52,177 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.1659) Prec@1 78.000 (70.455) Prec@5 99.000 (97.182) +2022-11-14 13:22:52,187 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1547 (0.1650) Prec@1 74.000 (70.750) Prec@5 98.000 (97.250) +2022-11-14 13:22:52,196 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1660) Prec@1 68.000 (70.538) Prec@5 98.000 (97.308) +2022-11-14 13:22:52,206 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1598 (0.1655) Prec@1 68.000 (70.357) Prec@5 99.000 (97.429) +2022-11-14 13:22:52,217 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1622 (0.1653) Prec@1 70.000 (70.333) Prec@5 98.000 (97.467) +2022-11-14 13:22:52,227 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.1659) Prec@1 62.000 (69.812) Prec@5 99.000 (97.562) +2022-11-14 13:22:52,237 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1641) Prec@1 77.000 (70.235) Prec@5 96.000 (97.471) +2022-11-14 13:22:52,247 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1991 (0.1660) Prec@1 68.000 (70.111) Prec@5 99.000 (97.556) +2022-11-14 13:22:52,257 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1465 (0.1650) Prec@1 77.000 (70.474) Prec@5 94.000 (97.368) +2022-11-14 13:22:52,267 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1938 (0.1664) Prec@1 67.000 (70.300) Prec@5 94.000 (97.200) +2022-11-14 13:22:52,276 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1880 (0.1674) Prec@1 66.000 (70.095) Prec@5 98.000 (97.238) +2022-11-14 13:22:52,287 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1678) Prec@1 71.000 (70.136) Prec@5 96.000 (97.182) +2022-11-14 13:22:52,297 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1840 (0.1685) Prec@1 69.000 (70.087) Prec@5 97.000 (97.174) +2022-11-14 13:22:52,308 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1613 (0.1682) Prec@1 70.000 (70.083) Prec@5 97.000 (97.167) +2022-11-14 13:22:52,318 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1807 (0.1687) Prec@1 66.000 (69.920) Prec@5 98.000 (97.200) +2022-11-14 13:22:52,329 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2450 (0.1716) Prec@1 59.000 (69.500) Prec@5 94.000 (97.077) +2022-11-14 13:22:52,340 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1706 (0.1716) Prec@1 71.000 (69.556) Prec@5 100.000 (97.185) +2022-11-14 13:22:52,349 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1718 (0.1716) Prec@1 69.000 (69.536) Prec@5 95.000 (97.107) +2022-11-14 13:22:52,359 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1746 (0.1717) Prec@1 70.000 (69.552) Prec@5 94.000 (97.000) +2022-11-14 13:22:52,370 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1845 (0.1721) Prec@1 66.000 (69.433) Prec@5 97.000 (97.000) +2022-11-14 13:22:52,380 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1627 (0.1718) Prec@1 73.000 (69.548) Prec@5 97.000 (97.000) +2022-11-14 13:22:52,392 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1496 (0.1711) Prec@1 72.000 (69.625) Prec@5 100.000 (97.094) +2022-11-14 13:22:52,401 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1656 (0.1710) Prec@1 69.000 (69.606) Prec@5 97.000 (97.091) +2022-11-14 13:22:52,413 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2006 (0.1718) Prec@1 63.000 (69.412) Prec@5 91.000 (96.912) +2022-11-14 13:22:52,423 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2122 (0.1730) Prec@1 60.000 (69.143) Prec@5 95.000 (96.857) +2022-11-14 13:22:52,433 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1715 (0.1729) Prec@1 70.000 (69.167) Prec@5 96.000 (96.833) +2022-11-14 13:22:52,442 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1824 (0.1732) Prec@1 65.000 (69.054) Prec@5 99.000 (96.892) +2022-11-14 13:22:52,453 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1779 (0.1733) Prec@1 66.000 (68.974) Prec@5 97.000 (96.895) +2022-11-14 13:22:52,463 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1512 (0.1728) Prec@1 74.000 (69.103) Prec@5 98.000 (96.923) +2022-11-14 13:22:52,473 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1452 (0.1721) Prec@1 74.000 (69.225) Prec@5 97.000 (96.925) +2022-11-14 13:22:52,482 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1542 (0.1716) Prec@1 71.000 (69.268) Prec@5 98.000 (96.951) +2022-11-14 13:22:52,491 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1789 (0.1718) Prec@1 69.000 (69.262) Prec@5 94.000 (96.881) +2022-11-14 13:22:52,503 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1254 (0.1707) Prec@1 78.000 (69.465) Prec@5 96.000 (96.860) +2022-11-14 13:22:52,514 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1430 (0.1701) Prec@1 78.000 (69.659) Prec@5 94.000 (96.795) +2022-11-14 13:22:52,524 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1471 (0.1696) Prec@1 75.000 (69.778) Prec@5 98.000 (96.822) +2022-11-14 13:22:52,533 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1741 (0.1697) Prec@1 70.000 (69.783) Prec@5 93.000 (96.739) +2022-11-14 13:22:52,545 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1602 (0.1695) Prec@1 70.000 (69.787) Prec@5 98.000 (96.766) +2022-11-14 13:22:52,556 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1396 (0.1689) Prec@1 78.000 (69.958) Prec@5 97.000 (96.771) +2022-11-14 13:22:52,569 Test: [48/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1332 (0.1681) Prec@1 76.000 (70.082) Prec@5 97.000 (96.776) +2022-11-14 13:22:52,580 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1864 (0.1685) Prec@1 67.000 (70.020) Prec@5 96.000 (96.760) +2022-11-14 13:22:52,591 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1691 (0.1685) Prec@1 69.000 (70.000) Prec@5 97.000 (96.765) +2022-11-14 13:22:52,602 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.1687) Prec@1 68.000 (69.962) Prec@5 96.000 (96.750) +2022-11-14 13:22:52,614 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1815 (0.1689) Prec@1 69.000 (69.943) Prec@5 99.000 (96.792) +2022-11-14 13:22:52,626 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1500 (0.1686) Prec@1 73.000 (70.000) Prec@5 95.000 (96.759) +2022-11-14 13:22:52,636 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1781 (0.1688) Prec@1 68.000 (69.964) Prec@5 98.000 (96.782) +2022-11-14 13:22:52,647 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1555 (0.1685) Prec@1 75.000 (70.054) Prec@5 99.000 (96.821) +2022-11-14 13:22:52,658 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1764 (0.1687) Prec@1 68.000 (70.018) Prec@5 97.000 (96.825) +2022-11-14 13:22:52,670 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1639 (0.1686) Prec@1 69.000 (70.000) Prec@5 97.000 (96.828) +2022-11-14 13:22:52,681 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1887 (0.1689) Prec@1 63.000 (69.881) Prec@5 96.000 (96.814) +2022-11-14 13:22:52,694 Test: [59/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1560 (0.1687) Prec@1 73.000 (69.933) Prec@5 95.000 (96.783) +2022-11-14 13:22:52,706 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1875 (0.1690) Prec@1 66.000 (69.869) Prec@5 97.000 (96.787) +2022-11-14 13:22:52,717 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1828 (0.1692) Prec@1 68.000 (69.839) Prec@5 97.000 (96.790) +2022-11-14 13:22:52,728 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1588 (0.1691) Prec@1 76.000 (69.937) Prec@5 98.000 (96.810) +2022-11-14 13:22:52,738 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.1685) Prec@1 77.000 (70.047) Prec@5 99.000 (96.844) +2022-11-14 13:22:52,749 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1876 (0.1688) Prec@1 67.000 (70.000) Prec@5 97.000 (96.846) +2022-11-14 13:22:52,759 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1565 (0.1686) Prec@1 74.000 (70.061) Prec@5 97.000 (96.848) +2022-11-14 13:22:52,770 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1318 (0.1681) Prec@1 78.000 (70.179) Prec@5 98.000 (96.866) +2022-11-14 13:22:52,781 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1904 (0.1684) Prec@1 61.000 (70.044) Prec@5 96.000 (96.853) +2022-11-14 13:22:52,791 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1556 (0.1682) Prec@1 70.000 (70.043) Prec@5 98.000 (96.870) +2022-11-14 13:22:52,802 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1944 (0.1686) Prec@1 64.000 (69.957) Prec@5 95.000 (96.843) +2022-11-14 13:22:52,813 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1459 (0.1683) Prec@1 75.000 (70.028) Prec@5 99.000 (96.873) +2022-11-14 13:22:52,823 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1658 (0.1682) Prec@1 69.000 (70.014) Prec@5 96.000 (96.861) +2022-11-14 13:22:52,834 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1642 (0.1682) Prec@1 67.000 (69.973) Prec@5 98.000 (96.877) +2022-11-14 13:22:52,844 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1352 (0.1677) Prec@1 77.000 (70.068) Prec@5 99.000 (96.905) +2022-11-14 13:22:52,855 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1896 (0.1680) Prec@1 68.000 (70.040) Prec@5 98.000 (96.920) +2022-11-14 13:22:52,865 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1490 (0.1678) Prec@1 69.000 (70.026) Prec@5 98.000 (96.934) +2022-11-14 13:22:52,875 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1760 (0.1679) Prec@1 67.000 (69.987) Prec@5 97.000 (96.935) +2022-11-14 13:22:52,886 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1506 (0.1677) Prec@1 75.000 (70.051) Prec@5 96.000 (96.923) +2022-11-14 13:22:52,899 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1462 (0.1674) Prec@1 74.000 (70.101) Prec@5 98.000 (96.937) +2022-11-14 13:22:52,910 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1437 (0.1671) Prec@1 74.000 (70.150) Prec@5 96.000 (96.925) +2022-11-14 13:22:52,920 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1372 (0.1667) Prec@1 76.000 (70.222) Prec@5 99.000 (96.951) +2022-11-14 13:22:52,930 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1634 (0.1667) Prec@1 73.000 (70.256) Prec@5 98.000 (96.963) +2022-11-14 13:22:52,940 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1597 (0.1666) Prec@1 71.000 (70.265) Prec@5 100.000 (97.000) +2022-11-14 13:22:52,951 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1848 (0.1668) Prec@1 70.000 (70.262) Prec@5 98.000 (97.012) +2022-11-14 13:22:52,960 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2189 (0.1674) Prec@1 58.000 (70.118) Prec@5 98.000 (97.024) +2022-11-14 13:22:52,970 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1679 (0.1674) Prec@1 68.000 (70.093) Prec@5 97.000 (97.023) +2022-11-14 13:22:52,981 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1519 (0.1673) Prec@1 74.000 (70.138) Prec@5 96.000 (97.011) +2022-11-14 13:22:52,991 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1430 (0.1670) Prec@1 79.000 (70.239) Prec@5 100.000 (97.045) +2022-11-14 13:22:53,001 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1693 (0.1670) Prec@1 69.000 (70.225) Prec@5 97.000 (97.045) +2022-11-14 13:22:53,011 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1473 (0.1668) Prec@1 72.000 (70.244) Prec@5 98.000 (97.056) +2022-11-14 13:22:53,022 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2002 (0.1672) Prec@1 68.000 (70.220) Prec@5 99.000 (97.077) +2022-11-14 13:22:53,030 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1229 (0.1667) Prec@1 80.000 (70.326) Prec@5 100.000 (97.109) +2022-11-14 13:22:53,040 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1836 (0.1669) Prec@1 67.000 (70.290) Prec@5 97.000 (97.108) +2022-11-14 13:22:53,052 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1635 (0.1668) Prec@1 70.000 (70.287) Prec@5 97.000 (97.106) +2022-11-14 13:22:53,063 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1737 (0.1669) Prec@1 69.000 (70.274) Prec@5 97.000 (97.105) +2022-11-14 13:22:53,073 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1676 (0.1669) Prec@1 68.000 (70.250) Prec@5 98.000 (97.115) +2022-11-14 13:22:53,083 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.1665) Prec@1 79.000 (70.340) Prec@5 99.000 (97.134) +2022-11-14 13:22:53,094 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2432 (0.1672) Prec@1 57.000 (70.204) Prec@5 89.000 (97.051) +2022-11-14 13:22:53,105 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1649 (0.1672) Prec@1 73.000 (70.232) Prec@5 98.000 (97.061) +2022-11-14 13:22:53,114 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1683 (0.1672) Prec@1 72.000 (70.250) Prec@5 97.000 (97.060) +2022-11-14 13:22:53,192 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:22:53,509 Epoch: [32][0/500] Time 0.027 (0.027) Data 0.227 (0.227) Loss 0.0970 (0.0970) Prec@1 81.000 (81.000) Prec@5 99.000 (99.000) +2022-11-14 13:22:53,749 Epoch: [32][10/500] Time 0.020 (0.022) Data 0.002 (0.023) Loss 0.1209 (0.1090) Prec@1 74.000 (77.500) Prec@5 99.000 (99.000) +2022-11-14 13:22:54,016 Epoch: [32][20/500] Time 0.025 (0.023) Data 0.002 (0.013) Loss 0.1566 (0.1249) Prec@1 74.000 (76.333) Prec@5 95.000 (97.667) +2022-11-14 13:22:54,242 Epoch: [32][30/500] Time 0.024 (0.022) Data 0.001 (0.009) Loss 0.1521 (0.1317) Prec@1 71.000 (75.000) Prec@5 97.000 (97.500) +2022-11-14 13:22:54,555 Epoch: [32][40/500] Time 0.037 (0.023) Data 0.003 (0.008) Loss 0.1196 (0.1292) Prec@1 76.000 (75.200) Prec@5 98.000 (97.600) +2022-11-14 13:22:54,864 Epoch: [32][50/500] Time 0.031 (0.024) Data 0.002 (0.006) Loss 0.1441 (0.1317) Prec@1 78.000 (75.667) Prec@5 97.000 (97.500) +2022-11-14 13:22:55,148 Epoch: [32][60/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.1368 (0.1324) Prec@1 74.000 (75.429) Prec@5 99.000 (97.714) +2022-11-14 13:22:55,565 Epoch: [32][70/500] Time 0.044 (0.026) Data 0.002 (0.005) Loss 0.1546 (0.1352) Prec@1 74.000 (75.250) Prec@5 96.000 (97.500) +2022-11-14 13:22:56,054 Epoch: [32][80/500] Time 0.048 (0.028) Data 0.002 (0.005) Loss 0.1471 (0.1365) Prec@1 77.000 (75.444) Prec@5 98.000 (97.556) +2022-11-14 13:22:56,585 Epoch: [32][90/500] Time 0.048 (0.030) Data 0.002 (0.004) Loss 0.1514 (0.1380) Prec@1 72.000 (75.100) Prec@5 95.000 (97.300) +2022-11-14 13:22:57,138 Epoch: [32][100/500] Time 0.052 (0.032) Data 0.002 (0.004) Loss 0.1348 (0.1377) Prec@1 74.000 (75.000) Prec@5 98.000 (97.364) +2022-11-14 13:22:57,680 Epoch: [32][110/500] Time 0.068 (0.033) Data 0.002 (0.004) Loss 0.1394 (0.1379) Prec@1 76.000 (75.083) Prec@5 98.000 (97.417) +2022-11-14 13:22:58,240 Epoch: [32][120/500] Time 0.081 (0.035) Data 0.002 (0.004) Loss 0.1259 (0.1369) Prec@1 74.000 (75.000) Prec@5 98.000 (97.462) +2022-11-14 13:22:58,851 Epoch: [32][130/500] Time 0.065 (0.036) Data 0.002 (0.004) Loss 0.1388 (0.1371) Prec@1 78.000 (75.214) Prec@5 98.000 (97.500) +2022-11-14 13:22:59,320 Epoch: [32][140/500] Time 0.052 (0.036) Data 0.002 (0.004) Loss 0.1411 (0.1373) Prec@1 75.000 (75.200) Prec@5 97.000 (97.467) +2022-11-14 13:22:59,876 Epoch: [32][150/500] Time 0.051 (0.037) Data 0.002 (0.003) Loss 0.1562 (0.1385) Prec@1 71.000 (74.938) Prec@5 96.000 (97.375) +2022-11-14 13:23:00,488 Epoch: [32][160/500] Time 0.078 (0.038) Data 0.002 (0.003) Loss 0.1681 (0.1403) Prec@1 68.000 (74.529) Prec@5 99.000 (97.471) +2022-11-14 13:23:01,009 Epoch: [32][170/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.1632 (0.1415) Prec@1 71.000 (74.333) Prec@5 92.000 (97.167) +2022-11-14 13:23:01,557 Epoch: [32][180/500] Time 0.044 (0.039) Data 0.003 (0.003) Loss 0.1337 (0.1411) Prec@1 74.000 (74.316) Prec@5 96.000 (97.105) +2022-11-14 13:23:02,146 Epoch: [32][190/500] Time 0.097 (0.040) Data 0.002 (0.003) Loss 0.1226 (0.1402) Prec@1 78.000 (74.500) Prec@5 95.000 (97.000) +2022-11-14 13:23:02,618 Epoch: [32][200/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.1167 (0.1391) Prec@1 82.000 (74.857) Prec@5 96.000 (96.952) +2022-11-14 13:23:03,096 Epoch: [32][210/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.1262 (0.1385) Prec@1 77.000 (74.955) Prec@5 98.000 (97.000) +2022-11-14 13:23:03,829 Epoch: [32][220/500] Time 0.066 (0.041) Data 0.002 (0.003) Loss 0.1658 (0.1397) Prec@1 72.000 (74.826) Prec@5 97.000 (97.000) +2022-11-14 13:23:04,520 Epoch: [32][230/500] Time 0.069 (0.042) Data 0.002 (0.003) Loss 0.1094 (0.1384) Prec@1 84.000 (75.208) Prec@5 99.000 (97.083) +2022-11-14 13:23:05,013 Epoch: [32][240/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1588 (0.1392) Prec@1 72.000 (75.080) Prec@5 95.000 (97.000) +2022-11-14 13:23:05,498 Epoch: [32][250/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0821 (0.1370) Prec@1 86.000 (75.500) Prec@5 100.000 (97.115) +2022-11-14 13:23:05,960 Epoch: [32][260/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1320 (0.1368) Prec@1 76.000 (75.519) Prec@5 97.000 (97.111) +2022-11-14 13:23:06,436 Epoch: [32][270/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1174 (0.1362) Prec@1 76.000 (75.536) Prec@5 97.000 (97.107) +2022-11-14 13:23:06,910 Epoch: [32][280/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1255 (0.1358) Prec@1 81.000 (75.724) Prec@5 98.000 (97.138) +2022-11-14 13:23:07,481 Epoch: [32][290/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.1351 (0.1358) Prec@1 76.000 (75.733) Prec@5 99.000 (97.200) +2022-11-14 13:23:07,981 Epoch: [32][300/500] Time 0.043 (0.043) Data 0.001 (0.003) Loss 0.1165 (0.1351) Prec@1 77.000 (75.774) Prec@5 98.000 (97.226) +2022-11-14 13:23:08,492 Epoch: [32][310/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.1343 (0.1351) Prec@1 76.000 (75.781) Prec@5 96.000 (97.188) +2022-11-14 13:23:08,965 Epoch: [32][320/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0888 (0.1337) Prec@1 84.000 (76.030) Prec@5 99.000 (97.242) +2022-11-14 13:23:09,268 Epoch: [32][330/500] Time 0.028 (0.042) Data 0.002 (0.003) Loss 0.1245 (0.1334) Prec@1 80.000 (76.147) Prec@5 97.000 (97.235) +2022-11-14 13:23:09,562 Epoch: [32][340/500] Time 0.027 (0.042) Data 0.001 (0.003) Loss 0.1343 (0.1335) Prec@1 75.000 (76.114) Prec@5 97.000 (97.229) +2022-11-14 13:23:09,851 Epoch: [32][350/500] Time 0.027 (0.041) Data 0.002 (0.003) Loss 0.1445 (0.1338) Prec@1 73.000 (76.028) Prec@5 99.000 (97.278) +2022-11-14 13:23:10,145 Epoch: [32][360/500] Time 0.027 (0.041) Data 0.002 (0.003) Loss 0.1089 (0.1331) Prec@1 80.000 (76.135) Prec@5 99.000 (97.324) +2022-11-14 13:23:10,434 Epoch: [32][370/500] Time 0.027 (0.041) Data 0.003 (0.003) Loss 0.1326 (0.1331) Prec@1 80.000 (76.237) Prec@5 95.000 (97.263) +2022-11-14 13:23:10,771 Epoch: [32][380/500] Time 0.025 (0.040) Data 0.002 (0.003) Loss 0.1842 (0.1344) Prec@1 68.000 (76.026) Prec@5 95.000 (97.205) +2022-11-14 13:23:11,053 Epoch: [32][390/500] Time 0.026 (0.040) Data 0.002 (0.003) Loss 0.1474 (0.1347) Prec@1 69.000 (75.850) Prec@5 100.000 (97.275) +2022-11-14 13:23:11,345 Epoch: [32][400/500] Time 0.027 (0.039) Data 0.002 (0.003) Loss 0.1385 (0.1348) Prec@1 76.000 (75.854) Prec@5 100.000 (97.341) +2022-11-14 13:23:11,680 Epoch: [32][410/500] Time 0.021 (0.039) Data 0.002 (0.002) Loss 0.0967 (0.1339) Prec@1 83.000 (76.024) Prec@5 98.000 (97.357) +2022-11-14 13:23:11,970 Epoch: [32][420/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.1061 (0.1333) Prec@1 82.000 (76.163) Prec@5 98.000 (97.372) +2022-11-14 13:23:12,268 Epoch: [32][430/500] Time 0.025 (0.039) Data 0.002 (0.002) Loss 0.1622 (0.1339) Prec@1 70.000 (76.023) Prec@5 95.000 (97.318) +2022-11-14 13:23:12,563 Epoch: [32][440/500] Time 0.026 (0.038) Data 0.002 (0.002) Loss 0.1316 (0.1339) Prec@1 79.000 (76.089) Prec@5 99.000 (97.356) +2022-11-14 13:23:12,856 Epoch: [32][450/500] Time 0.025 (0.038) Data 0.002 (0.002) Loss 0.1379 (0.1340) Prec@1 74.000 (76.043) Prec@5 96.000 (97.326) +2022-11-14 13:23:13,233 Epoch: [32][460/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.1322 (0.1339) Prec@1 79.000 (76.106) Prec@5 96.000 (97.298) +2022-11-14 13:23:13,584 Epoch: [32][470/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.1318 (0.1339) Prec@1 78.000 (76.146) Prec@5 97.000 (97.292) +2022-11-14 13:23:13,853 Epoch: [32][480/500] Time 0.026 (0.038) Data 0.002 (0.002) Loss 0.1211 (0.1336) Prec@1 78.000 (76.184) Prec@5 99.000 (97.327) +2022-11-14 13:23:14,150 Epoch: [32][490/500] Time 0.027 (0.037) Data 0.002 (0.002) Loss 0.1373 (0.1337) Prec@1 75.000 (76.160) Prec@5 99.000 (97.360) +2022-11-14 13:23:14,467 Epoch: [32][499/500] Time 0.022 (0.037) Data 0.001 (0.002) Loss 0.1300 (0.1336) Prec@1 74.000 (76.118) Prec@5 98.000 (97.373) +2022-11-14 13:23:14,759 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1397 (0.1397) Prec@1 76.000 (76.000) Prec@5 98.000 (98.000) +2022-11-14 13:23:14,770 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1473 (0.1435) Prec@1 72.000 (74.000) Prec@5 98.000 (98.000) +2022-11-14 13:23:14,782 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1404 (0.1424) Prec@1 75.000 (74.333) Prec@5 95.000 (97.000) +2022-11-14 13:23:14,793 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1475 (0.1437) Prec@1 75.000 (74.500) Prec@5 99.000 (97.500) +2022-11-14 13:23:14,801 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1637 (0.1477) Prec@1 74.000 (74.400) Prec@5 95.000 (97.000) +2022-11-14 13:23:14,809 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1246 (0.1439) Prec@1 77.000 (74.833) Prec@5 97.000 (97.000) +2022-11-14 13:23:14,821 Test: [6/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1576 (0.1458) Prec@1 72.000 (74.429) Prec@5 96.000 (96.857) +2022-11-14 13:23:14,833 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1561 (0.1471) Prec@1 73.000 (74.250) Prec@5 98.000 (97.000) +2022-11-14 13:23:14,842 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1473) Prec@1 76.000 (74.444) Prec@5 93.000 (96.556) +2022-11-14 13:23:14,851 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1212 (0.1447) Prec@1 79.000 (74.900) Prec@5 97.000 (96.600) +2022-11-14 13:23:14,863 Test: [10/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1386 (0.1441) Prec@1 75.000 (74.909) Prec@5 98.000 (96.727) +2022-11-14 13:23:14,875 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1551 (0.1451) Prec@1 71.000 (74.583) Prec@5 98.000 (96.833) +2022-11-14 13:23:14,884 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1388 (0.1446) Prec@1 74.000 (74.538) Prec@5 97.000 (96.846) +2022-11-14 13:23:14,894 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1604 (0.1457) Prec@1 70.000 (74.214) Prec@5 92.000 (96.500) +2022-11-14 13:23:14,904 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1277 (0.1445) Prec@1 77.000 (74.400) Prec@5 96.000 (96.467) +2022-11-14 13:23:14,914 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1633 (0.1457) Prec@1 72.000 (74.250) Prec@5 93.000 (96.250) +2022-11-14 13:23:14,922 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.1442) Prec@1 79.000 (74.529) Prec@5 96.000 (96.235) +2022-11-14 13:23:14,931 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1407 (0.1440) Prec@1 75.000 (74.556) Prec@5 99.000 (96.389) +2022-11-14 13:23:14,940 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1588 (0.1448) Prec@1 69.000 (74.263) Prec@5 96.000 (96.368) +2022-11-14 13:23:14,949 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1691 (0.1460) Prec@1 72.000 (74.150) Prec@5 93.000 (96.200) +2022-11-14 13:23:14,961 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1682 (0.1470) Prec@1 71.000 (74.000) Prec@5 100.000 (96.381) +2022-11-14 13:23:14,972 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1301 (0.1463) Prec@1 76.000 (74.091) Prec@5 96.000 (96.364) +2022-11-14 13:23:14,981 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1489 (0.1464) Prec@1 76.000 (74.174) Prec@5 93.000 (96.217) +2022-11-14 13:23:14,991 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1451 (0.1463) Prec@1 73.000 (74.125) Prec@5 99.000 (96.333) +2022-11-14 13:23:15,002 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1577 (0.1468) Prec@1 72.000 (74.040) Prec@5 99.000 (96.440) +2022-11-14 13:23:15,012 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1661 (0.1475) Prec@1 73.000 (74.000) Prec@5 94.000 (96.346) +2022-11-14 13:23:15,023 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1320 (0.1469) Prec@1 77.000 (74.111) Prec@5 98.000 (96.407) +2022-11-14 13:23:15,033 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1570 (0.1473) Prec@1 71.000 (74.000) Prec@5 99.000 (96.500) +2022-11-14 13:23:15,044 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1675 (0.1480) Prec@1 70.000 (73.862) Prec@5 92.000 (96.345) +2022-11-14 13:23:15,056 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1344 (0.1475) Prec@1 74.000 (73.867) Prec@5 96.000 (96.333) +2022-11-14 13:23:15,065 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1391 (0.1473) Prec@1 76.000 (73.935) Prec@5 95.000 (96.290) +2022-11-14 13:23:15,074 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1327 (0.1468) Prec@1 81.000 (74.156) Prec@5 99.000 (96.375) +2022-11-14 13:23:15,085 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1614 (0.1473) Prec@1 73.000 (74.121) Prec@5 94.000 (96.303) +2022-11-14 13:23:15,095 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1509 (0.1474) Prec@1 72.000 (74.059) Prec@5 97.000 (96.324) +2022-11-14 13:23:15,107 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1425 (0.1472) Prec@1 75.000 (74.086) Prec@5 96.000 (96.314) +2022-11-14 13:23:15,118 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.1466) Prec@1 77.000 (74.167) Prec@5 98.000 (96.361) +2022-11-14 13:23:15,127 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1607 (0.1469) Prec@1 69.000 (74.027) Prec@5 94.000 (96.297) +2022-11-14 13:23:15,137 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1522 (0.1471) Prec@1 72.000 (73.974) Prec@5 97.000 (96.316) +2022-11-14 13:23:15,149 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1460) Prec@1 81.000 (74.154) Prec@5 98.000 (96.359) +2022-11-14 13:23:15,160 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1320 (0.1457) Prec@1 77.000 (74.225) Prec@5 97.000 (96.375) +2022-11-14 13:23:15,169 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1578 (0.1459) Prec@1 75.000 (74.244) Prec@5 98.000 (96.415) +2022-11-14 13:23:15,179 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.1455) Prec@1 82.000 (74.429) Prec@5 96.000 (96.405) +2022-11-14 13:23:15,190 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.1447) Prec@1 81.000 (74.581) Prec@5 98.000 (96.442) +2022-11-14 13:23:15,202 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1511 (0.1449) Prec@1 71.000 (74.500) Prec@5 94.000 (96.386) +2022-11-14 13:23:15,213 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1376 (0.1447) Prec@1 78.000 (74.578) Prec@5 94.000 (96.333) +2022-11-14 13:23:15,224 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1589 (0.1450) Prec@1 73.000 (74.543) Prec@5 98.000 (96.370) +2022-11-14 13:23:15,233 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1396 (0.1449) Prec@1 74.000 (74.532) Prec@5 96.000 (96.362) +2022-11-14 13:23:15,245 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1256 (0.1445) Prec@1 79.000 (74.625) Prec@5 98.000 (96.396) +2022-11-14 13:23:15,255 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1304 (0.1442) Prec@1 78.000 (74.694) Prec@5 98.000 (96.429) +2022-11-14 13:23:15,267 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1645 (0.1446) Prec@1 74.000 (74.680) Prec@5 95.000 (96.400) +2022-11-14 13:23:15,277 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1464 (0.1447) Prec@1 75.000 (74.686) Prec@5 96.000 (96.392) +2022-11-14 13:23:15,287 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1616 (0.1450) Prec@1 69.000 (74.577) Prec@5 92.000 (96.308) +2022-11-14 13:23:15,297 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1351 (0.1448) Prec@1 78.000 (74.642) Prec@5 96.000 (96.302) +2022-11-14 13:23:15,308 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.1443) Prec@1 79.000 (74.722) Prec@5 98.000 (96.333) +2022-11-14 13:23:15,319 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1710 (0.1448) Prec@1 69.000 (74.618) Prec@5 97.000 (96.345) +2022-11-14 13:23:15,328 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1297 (0.1446) Prec@1 80.000 (74.714) Prec@5 97.000 (96.357) +2022-11-14 13:23:15,338 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1538 (0.1447) Prec@1 72.000 (74.667) Prec@5 97.000 (96.368) +2022-11-14 13:23:15,350 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.1446) Prec@1 77.000 (74.707) Prec@5 99.000 (96.414) +2022-11-14 13:23:15,361 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1804 (0.1452) Prec@1 66.000 (74.559) Prec@5 97.000 (96.424) +2022-11-14 13:23:15,372 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1718 (0.1456) Prec@1 69.000 (74.467) Prec@5 95.000 (96.400) +2022-11-14 13:23:15,387 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1552 (0.1458) Prec@1 72.000 (74.426) Prec@5 99.000 (96.443) +2022-11-14 13:23:15,402 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1456) Prec@1 74.000 (74.419) Prec@5 98.000 (96.468) +2022-11-14 13:23:15,415 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1452) Prec@1 81.000 (74.524) Prec@5 95.000 (96.444) +2022-11-14 13:23:15,427 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.1450) Prec@1 76.000 (74.547) Prec@5 97.000 (96.453) +2022-11-14 13:23:15,439 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1450) Prec@1 75.000 (74.554) Prec@5 96.000 (96.446) +2022-11-14 13:23:15,452 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1680 (0.1454) Prec@1 71.000 (74.500) Prec@5 93.000 (96.394) +2022-11-14 13:23:15,464 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1500 (0.1454) Prec@1 71.000 (74.448) Prec@5 98.000 (96.418) +2022-11-14 13:23:15,477 Test: [67/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1678 (0.1458) Prec@1 72.000 (74.412) Prec@5 98.000 (96.441) +2022-11-14 13:23:15,488 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.1456) Prec@1 75.000 (74.420) Prec@5 95.000 (96.420) +2022-11-14 13:23:15,500 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1870 (0.1462) Prec@1 66.000 (74.300) Prec@5 95.000 (96.400) +2022-11-14 13:23:15,510 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1458 (0.1462) Prec@1 76.000 (74.324) Prec@5 99.000 (96.437) +2022-11-14 13:23:15,523 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1481 (0.1463) Prec@1 71.000 (74.278) Prec@5 98.000 (96.458) +2022-11-14 13:23:15,536 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1300 (0.1460) Prec@1 73.000 (74.260) Prec@5 99.000 (96.493) +2022-11-14 13:23:15,550 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1455) Prec@1 83.000 (74.378) Prec@5 98.000 (96.514) +2022-11-14 13:23:15,563 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1681 (0.1458) Prec@1 72.000 (74.347) Prec@5 96.000 (96.507) +2022-11-14 13:23:15,576 Test: [75/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1430 (0.1458) Prec@1 74.000 (74.342) Prec@5 98.000 (96.526) +2022-11-14 13:23:15,592 Test: [76/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1458) Prec@1 72.000 (74.312) Prec@5 98.000 (96.545) +2022-11-14 13:23:15,608 Test: [77/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.1607 (0.1460) Prec@1 70.000 (74.256) Prec@5 94.000 (96.513) +2022-11-14 13:23:15,624 Test: [78/100] Model Time 0.013 (0.007) Loss Time 0.000 (0.000) Loss 0.1340 (0.1458) Prec@1 78.000 (74.304) Prec@5 97.000 (96.519) +2022-11-14 13:23:15,639 Test: [79/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1399 (0.1457) Prec@1 78.000 (74.350) Prec@5 92.000 (96.463) +2022-11-14 13:23:15,656 Test: [80/100] Model Time 0.014 (0.008) Loss Time 0.000 (0.000) Loss 0.1105 (0.1453) Prec@1 79.000 (74.407) Prec@5 96.000 (96.457) +2022-11-14 13:23:15,670 Test: [81/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1386 (0.1452) Prec@1 71.000 (74.366) Prec@5 95.000 (96.439) +2022-11-14 13:23:15,681 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1441 (0.1452) Prec@1 73.000 (74.349) Prec@5 96.000 (96.434) +2022-11-14 13:23:15,692 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1664 (0.1455) Prec@1 69.000 (74.286) Prec@5 95.000 (96.417) +2022-11-14 13:23:15,705 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1741 (0.1458) Prec@1 65.000 (74.176) Prec@5 96.000 (96.412) +2022-11-14 13:23:15,716 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1553 (0.1459) Prec@1 70.000 (74.128) Prec@5 98.000 (96.430) +2022-11-14 13:23:15,727 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1542 (0.1460) Prec@1 72.000 (74.103) Prec@5 94.000 (96.402) +2022-11-14 13:23:15,738 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1407 (0.1459) Prec@1 74.000 (74.102) Prec@5 97.000 (96.409) +2022-11-14 13:23:15,749 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1247 (0.1457) Prec@1 76.000 (74.124) Prec@5 99.000 (96.438) +2022-11-14 13:23:15,762 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1412 (0.1456) Prec@1 75.000 (74.133) Prec@5 96.000 (96.433) +2022-11-14 13:23:15,774 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1237 (0.1454) Prec@1 75.000 (74.143) Prec@5 100.000 (96.473) +2022-11-14 13:23:15,785 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.1449) Prec@1 85.000 (74.261) Prec@5 97.000 (96.478) +2022-11-14 13:23:15,795 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1604 (0.1450) Prec@1 73.000 (74.247) Prec@5 96.000 (96.473) +2022-11-14 13:23:15,805 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1600 (0.1452) Prec@1 73.000 (74.234) Prec@5 94.000 (96.447) +2022-11-14 13:23:15,814 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1325 (0.1450) Prec@1 77.000 (74.263) Prec@5 100.000 (96.484) +2022-11-14 13:23:15,823 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1227 (0.1448) Prec@1 76.000 (74.281) Prec@5 98.000 (96.500) +2022-11-14 13:23:15,833 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1350 (0.1447) Prec@1 73.000 (74.268) Prec@5 96.000 (96.495) +2022-11-14 13:23:15,842 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1831 (0.1451) Prec@1 71.000 (74.235) Prec@5 98.000 (96.510) +2022-11-14 13:23:15,852 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1622 (0.1453) Prec@1 73.000 (74.222) Prec@5 95.000 (96.495) +2022-11-14 13:23:15,862 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1388 (0.1452) Prec@1 78.000 (74.260) Prec@5 97.000 (96.500) +2022-11-14 13:23:15,920 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:23:16,229 Epoch: [33][0/500] Time 0.029 (0.029) Data 0.221 (0.221) Loss 0.1204 (0.1204) Prec@1 78.000 (78.000) Prec@5 97.000 (97.000) +2022-11-14 13:23:16,545 Epoch: [33][10/500] Time 0.028 (0.029) Data 0.002 (0.022) Loss 0.1184 (0.1194) Prec@1 80.000 (79.000) Prec@5 99.000 (98.000) +2022-11-14 13:23:16,749 Epoch: [33][20/500] Time 0.016 (0.024) Data 0.002 (0.012) Loss 0.1284 (0.1224) Prec@1 80.000 (79.333) Prec@5 96.000 (97.333) +2022-11-14 13:23:16,957 Epoch: [33][30/500] Time 0.022 (0.022) Data 0.001 (0.009) Loss 0.1316 (0.1247) Prec@1 78.000 (79.000) Prec@5 97.000 (97.250) +2022-11-14 13:23:17,304 Epoch: [33][40/500] Time 0.045 (0.024) Data 0.002 (0.007) Loss 0.0990 (0.1196) Prec@1 85.000 (80.200) Prec@5 98.000 (97.400) +2022-11-14 13:23:17,873 Epoch: [33][50/500] Time 0.055 (0.029) Data 0.002 (0.006) Loss 0.1638 (0.1269) Prec@1 69.000 (78.333) Prec@5 96.000 (97.167) +2022-11-14 13:23:18,319 Epoch: [33][60/500] Time 0.044 (0.031) Data 0.002 (0.006) Loss 0.1716 (0.1333) Prec@1 69.000 (77.000) Prec@5 97.000 (97.143) +2022-11-14 13:23:18,778 Epoch: [33][70/500] Time 0.043 (0.032) Data 0.002 (0.005) Loss 0.1453 (0.1348) Prec@1 75.000 (76.750) Prec@5 96.000 (97.000) +2022-11-14 13:23:19,229 Epoch: [33][80/500] Time 0.045 (0.033) Data 0.002 (0.005) Loss 0.1398 (0.1354) Prec@1 74.000 (76.444) Prec@5 97.000 (97.000) +2022-11-14 13:23:19,725 Epoch: [33][90/500] Time 0.042 (0.034) Data 0.002 (0.004) Loss 0.1247 (0.1343) Prec@1 78.000 (76.600) Prec@5 97.000 (97.000) +2022-11-14 13:23:20,182 Epoch: [33][100/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.1529 (0.1360) Prec@1 71.000 (76.091) Prec@5 98.000 (97.091) +2022-11-14 13:23:20,707 Epoch: [33][110/500] Time 0.064 (0.036) Data 0.002 (0.004) Loss 0.0969 (0.1327) Prec@1 84.000 (76.750) Prec@5 98.000 (97.167) +2022-11-14 13:23:21,183 Epoch: [33][120/500] Time 0.037 (0.037) Data 0.002 (0.004) Loss 0.1196 (0.1317) Prec@1 81.000 (77.077) Prec@5 98.000 (97.231) +2022-11-14 13:23:21,632 Epoch: [33][130/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.1420 (0.1325) Prec@1 77.000 (77.071) Prec@5 97.000 (97.214) +2022-11-14 13:23:22,164 Epoch: [33][140/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.1405 (0.1330) Prec@1 76.000 (77.000) Prec@5 98.000 (97.267) +2022-11-14 13:23:22,603 Epoch: [33][150/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1412 (0.1335) Prec@1 76.000 (76.938) Prec@5 95.000 (97.125) +2022-11-14 13:23:23,051 Epoch: [33][160/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1706 (0.1357) Prec@1 68.000 (76.412) Prec@5 96.000 (97.059) +2022-11-14 13:23:23,506 Epoch: [33][170/500] Time 0.045 (0.038) Data 0.001 (0.003) Loss 0.1405 (0.1360) Prec@1 74.000 (76.278) Prec@5 98.000 (97.111) +2022-11-14 13:23:23,961 Epoch: [33][180/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1209 (0.1352) Prec@1 78.000 (76.368) Prec@5 98.000 (97.158) +2022-11-14 13:23:24,511 Epoch: [33][190/500] Time 0.058 (0.039) Data 0.003 (0.003) Loss 0.1092 (0.1339) Prec@1 80.000 (76.550) Prec@5 98.000 (97.200) +2022-11-14 13:23:24,944 Epoch: [33][200/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0960 (0.1321) Prec@1 85.000 (76.952) Prec@5 99.000 (97.286) +2022-11-14 13:23:25,393 Epoch: [33][210/500] Time 0.042 (0.039) Data 0.003 (0.003) Loss 0.1087 (0.1310) Prec@1 82.000 (77.182) Prec@5 99.000 (97.364) +2022-11-14 13:23:25,832 Epoch: [33][220/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1215 (0.1306) Prec@1 77.000 (77.174) Prec@5 97.000 (97.348) +2022-11-14 13:23:26,282 Epoch: [33][230/500] Time 0.043 (0.039) Data 0.001 (0.003) Loss 0.1298 (0.1306) Prec@1 77.000 (77.167) Prec@5 98.000 (97.375) +2022-11-14 13:23:26,727 Epoch: [33][240/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1699 (0.1321) Prec@1 66.000 (76.720) Prec@5 98.000 (97.400) +2022-11-14 13:23:27,175 Epoch: [33][250/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1094 (0.1313) Prec@1 80.000 (76.846) Prec@5 98.000 (97.423) +2022-11-14 13:23:27,628 Epoch: [33][260/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.1215 (0.1309) Prec@1 80.000 (76.963) Prec@5 95.000 (97.333) +2022-11-14 13:23:28,070 Epoch: [33][270/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1321 (0.1309) Prec@1 76.000 (76.929) Prec@5 99.000 (97.393) +2022-11-14 13:23:28,521 Epoch: [33][280/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.1446 (0.1314) Prec@1 77.000 (76.931) Prec@5 100.000 (97.483) +2022-11-14 13:23:29,002 Epoch: [33][290/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.1619 (0.1324) Prec@1 71.000 (76.733) Prec@5 97.000 (97.467) +2022-11-14 13:23:29,483 Epoch: [33][300/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1161 (0.1319) Prec@1 80.000 (76.839) Prec@5 97.000 (97.452) +2022-11-14 13:23:29,976 Epoch: [33][310/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.1114 (0.1313) Prec@1 79.000 (76.906) Prec@5 98.000 (97.469) +2022-11-14 13:23:30,451 Epoch: [33][320/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.1598 (0.1321) Prec@1 74.000 (76.818) Prec@5 97.000 (97.455) +2022-11-14 13:23:30,880 Epoch: [33][330/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.1178 (0.1317) Prec@1 77.000 (76.824) Prec@5 98.000 (97.471) +2022-11-14 13:23:31,320 Epoch: [33][340/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.1495 (0.1322) Prec@1 75.000 (76.771) Prec@5 100.000 (97.543) +2022-11-14 13:23:31,769 Epoch: [33][350/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1058 (0.1315) Prec@1 85.000 (77.000) Prec@5 96.000 (97.500) +2022-11-14 13:23:32,295 Epoch: [33][360/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.1311 (0.1315) Prec@1 78.000 (77.027) Prec@5 98.000 (97.514) +2022-11-14 13:23:32,765 Epoch: [33][370/500] Time 0.056 (0.040) Data 0.002 (0.002) Loss 0.1405 (0.1317) Prec@1 73.000 (76.921) Prec@5 97.000 (97.500) +2022-11-14 13:23:33,297 Epoch: [33][380/500] Time 0.076 (0.040) Data 0.002 (0.002) Loss 0.1430 (0.1320) Prec@1 76.000 (76.897) Prec@5 95.000 (97.436) +2022-11-14 13:23:33,850 Epoch: [33][390/500] Time 0.054 (0.040) Data 0.002 (0.002) Loss 0.1346 (0.1321) Prec@1 77.000 (76.900) Prec@5 97.000 (97.425) +2022-11-14 13:23:34,322 Epoch: [33][400/500] Time 0.035 (0.040) Data 0.002 (0.002) Loss 0.1317 (0.1320) Prec@1 83.000 (77.049) Prec@5 96.000 (97.390) +2022-11-14 13:23:34,776 Epoch: [33][410/500] Time 0.038 (0.040) Data 0.002 (0.002) Loss 0.1502 (0.1325) Prec@1 75.000 (77.000) Prec@5 97.000 (97.381) +2022-11-14 13:23:35,226 Epoch: [33][420/500] Time 0.034 (0.040) Data 0.002 (0.002) Loss 0.1638 (0.1332) Prec@1 66.000 (76.744) Prec@5 98.000 (97.395) +2022-11-14 13:23:35,701 Epoch: [33][430/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.1442 (0.1335) Prec@1 73.000 (76.659) Prec@5 98.000 (97.409) +2022-11-14 13:23:36,143 Epoch: [33][440/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.1795 (0.1345) Prec@1 67.000 (76.444) Prec@5 95.000 (97.356) +2022-11-14 13:23:36,586 Epoch: [33][450/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.1361 (0.1345) Prec@1 78.000 (76.478) Prec@5 96.000 (97.326) +2022-11-14 13:23:37,032 Epoch: [33][460/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.1195 (0.1342) Prec@1 79.000 (76.532) Prec@5 97.000 (97.319) +2022-11-14 13:23:37,480 Epoch: [33][470/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.1133 (0.1338) Prec@1 77.000 (76.542) Prec@5 98.000 (97.333) +2022-11-14 13:23:37,927 Epoch: [33][480/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.1618 (0.1343) Prec@1 71.000 (76.429) Prec@5 98.000 (97.347) +2022-11-14 13:23:38,375 Epoch: [33][490/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.1502 (0.1346) Prec@1 72.000 (76.340) Prec@5 100.000 (97.400) +2022-11-14 13:23:38,835 Epoch: [33][499/500] Time 0.079 (0.040) Data 0.002 (0.002) Loss 0.1276 (0.1345) Prec@1 78.000 (76.373) Prec@5 99.000 (97.431) +2022-11-14 13:23:39,144 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1837 (0.1837) Prec@1 66.000 (66.000) Prec@5 96.000 (96.000) +2022-11-14 13:23:39,154 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2037 (0.1937) Prec@1 61.000 (63.500) Prec@5 94.000 (95.000) +2022-11-14 13:23:39,163 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2105 (0.1993) Prec@1 63.000 (63.333) Prec@5 96.000 (95.333) +2022-11-14 13:23:39,174 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1902 (0.1970) Prec@1 66.000 (64.000) Prec@5 95.000 (95.250) +2022-11-14 13:23:39,182 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1927 (0.1962) Prec@1 69.000 (65.000) Prec@5 95.000 (95.200) +2022-11-14 13:23:39,190 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1873) Prec@1 73.000 (66.333) Prec@5 95.000 (95.167) +2022-11-14 13:23:39,198 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1361 (0.1800) Prec@1 78.000 (68.000) Prec@5 94.000 (95.000) +2022-11-14 13:23:39,209 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1745 (0.1793) Prec@1 70.000 (68.250) Prec@5 93.000 (94.750) +2022-11-14 13:23:39,216 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1911 (0.1806) Prec@1 62.000 (67.556) Prec@5 97.000 (95.000) +2022-11-14 13:23:39,225 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1685 (0.1794) Prec@1 67.000 (67.500) Prec@5 94.000 (94.900) +2022-11-14 13:23:39,234 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1584 (0.1775) Prec@1 73.000 (68.000) Prec@5 95.000 (94.909) +2022-11-14 13:23:39,244 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1567 (0.1758) Prec@1 73.000 (68.417) Prec@5 97.000 (95.083) +2022-11-14 13:23:39,253 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1625 (0.1747) Prec@1 69.000 (68.462) Prec@5 94.000 (95.000) +2022-11-14 13:23:39,263 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1358 (0.1720) Prec@1 76.000 (69.000) Prec@5 96.000 (95.071) +2022-11-14 13:23:39,272 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1908 (0.1732) Prec@1 62.000 (68.533) Prec@5 95.000 (95.067) +2022-11-14 13:23:39,281 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1880 (0.1741) Prec@1 67.000 (68.438) Prec@5 96.000 (95.125) +2022-11-14 13:23:39,290 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1721) Prec@1 77.000 (68.941) Prec@5 97.000 (95.235) +2022-11-14 13:23:39,299 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1779 (0.1724) Prec@1 66.000 (68.778) Prec@5 98.000 (95.389) +2022-11-14 13:23:39,308 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1815 (0.1729) Prec@1 71.000 (68.895) Prec@5 92.000 (95.211) +2022-11-14 13:23:39,319 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1920 (0.1738) Prec@1 63.000 (68.600) Prec@5 95.000 (95.200) +2022-11-14 13:23:39,331 Test: [20/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1921 (0.1747) Prec@1 67.000 (68.524) Prec@5 94.000 (95.143) +2022-11-14 13:23:39,342 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1633 (0.1742) Prec@1 73.000 (68.727) Prec@5 98.000 (95.273) +2022-11-14 13:23:39,353 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1894 (0.1748) Prec@1 69.000 (68.739) Prec@5 96.000 (95.304) +2022-11-14 13:23:39,363 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1746) Prec@1 68.000 (68.708) Prec@5 94.000 (95.250) +2022-11-14 13:23:39,372 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1999 (0.1756) Prec@1 65.000 (68.560) Prec@5 96.000 (95.280) +2022-11-14 13:23:39,381 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2140 (0.1771) Prec@1 60.000 (68.231) Prec@5 93.000 (95.192) +2022-11-14 13:23:39,388 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1859 (0.1774) Prec@1 70.000 (68.296) Prec@5 97.000 (95.259) +2022-11-14 13:23:39,396 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1576 (0.1767) Prec@1 70.000 (68.357) Prec@5 95.000 (95.250) +2022-11-14 13:23:39,405 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1892 (0.1772) Prec@1 69.000 (68.379) Prec@5 93.000 (95.172) +2022-11-14 13:23:39,414 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1874 (0.1775) Prec@1 68.000 (68.367) Prec@5 94.000 (95.133) +2022-11-14 13:23:39,424 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1807 (0.1776) Prec@1 64.000 (68.226) Prec@5 96.000 (95.161) +2022-11-14 13:23:39,433 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2009 (0.1783) Prec@1 67.000 (68.188) Prec@5 97.000 (95.219) +2022-11-14 13:23:39,443 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1708 (0.1781) Prec@1 68.000 (68.182) Prec@5 91.000 (95.091) +2022-11-14 13:23:39,452 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1886 (0.1784) Prec@1 66.000 (68.118) Prec@5 91.000 (94.971) +2022-11-14 13:23:39,461 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1963 (0.1789) Prec@1 66.000 (68.057) Prec@5 92.000 (94.886) +2022-11-14 13:23:39,471 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2002 (0.1795) Prec@1 65.000 (67.972) Prec@5 92.000 (94.806) +2022-11-14 13:23:39,480 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1955 (0.1799) Prec@1 60.000 (67.757) Prec@5 94.000 (94.784) +2022-11-14 13:23:39,489 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1902 (0.1802) Prec@1 65.000 (67.684) Prec@5 94.000 (94.763) +2022-11-14 13:23:39,498 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1688 (0.1799) Prec@1 70.000 (67.744) Prec@5 98.000 (94.846) +2022-11-14 13:23:39,508 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1501 (0.1792) Prec@1 74.000 (67.900) Prec@5 95.000 (94.850) +2022-11-14 13:23:39,517 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1577 (0.1786) Prec@1 74.000 (68.049) Prec@5 94.000 (94.829) +2022-11-14 13:23:39,526 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2021 (0.1792) Prec@1 61.000 (67.881) Prec@5 94.000 (94.810) +2022-11-14 13:23:39,535 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1529 (0.1786) Prec@1 73.000 (68.000) Prec@5 97.000 (94.860) +2022-11-14 13:23:39,544 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1783) Prec@1 70.000 (68.045) Prec@5 95.000 (94.864) +2022-11-14 13:23:39,554 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1988 (0.1788) Prec@1 66.000 (68.000) Prec@5 93.000 (94.822) +2022-11-14 13:23:39,563 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1819 (0.1788) Prec@1 69.000 (68.022) Prec@5 93.000 (94.783) +2022-11-14 13:23:39,572 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1607 (0.1785) Prec@1 73.000 (68.128) Prec@5 98.000 (94.851) +2022-11-14 13:23:39,582 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1667 (0.1782) Prec@1 73.000 (68.229) Prec@5 93.000 (94.812) +2022-11-14 13:23:39,591 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1409 (0.1774) Prec@1 77.000 (68.408) Prec@5 95.000 (94.816) +2022-11-14 13:23:39,599 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1994 (0.1779) Prec@1 64.000 (68.320) Prec@5 91.000 (94.740) +2022-11-14 13:23:39,608 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1604 (0.1775) Prec@1 75.000 (68.451) Prec@5 95.000 (94.745) +2022-11-14 13:23:39,618 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1775) Prec@1 66.000 (68.404) Prec@5 93.000 (94.712) +2022-11-14 13:23:39,627 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1888 (0.1777) Prec@1 65.000 (68.340) Prec@5 95.000 (94.717) +2022-11-14 13:23:39,635 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1779 (0.1777) Prec@1 71.000 (68.389) Prec@5 93.000 (94.685) +2022-11-14 13:23:39,645 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1876 (0.1779) Prec@1 68.000 (68.382) Prec@5 97.000 (94.727) +2022-11-14 13:23:39,654 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1525 (0.1774) Prec@1 77.000 (68.536) Prec@5 95.000 (94.732) +2022-11-14 13:23:39,663 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1421 (0.1768) Prec@1 73.000 (68.614) Prec@5 99.000 (94.807) +2022-11-14 13:23:39,672 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1715 (0.1767) Prec@1 71.000 (68.655) Prec@5 96.000 (94.828) +2022-11-14 13:23:39,680 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2006 (0.1771) Prec@1 67.000 (68.627) Prec@5 96.000 (94.847) +2022-11-14 13:23:39,688 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1358 (0.1764) Prec@1 76.000 (68.750) Prec@5 99.000 (94.917) +2022-11-14 13:23:39,697 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1774 (0.1765) Prec@1 69.000 (68.754) Prec@5 97.000 (94.951) +2022-11-14 13:23:39,705 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1785 (0.1765) Prec@1 68.000 (68.742) Prec@5 98.000 (95.000) +2022-11-14 13:23:39,715 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1763) Prec@1 68.000 (68.730) Prec@5 98.000 (95.048) +2022-11-14 13:23:39,723 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1758) Prec@1 75.000 (68.828) Prec@5 97.000 (95.078) +2022-11-14 13:23:39,732 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2151 (0.1764) Prec@1 59.000 (68.677) Prec@5 94.000 (95.062) +2022-11-14 13:23:39,741 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1712 (0.1763) Prec@1 70.000 (68.697) Prec@5 98.000 (95.106) +2022-11-14 13:23:39,751 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1819 (0.1764) Prec@1 70.000 (68.716) Prec@5 97.000 (95.134) +2022-11-14 13:23:39,760 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1964 (0.1767) Prec@1 62.000 (68.618) Prec@5 95.000 (95.132) +2022-11-14 13:23:39,769 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1757 (0.1767) Prec@1 67.000 (68.594) Prec@5 93.000 (95.101) +2022-11-14 13:23:39,778 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2230 (0.1774) Prec@1 56.000 (68.414) Prec@5 91.000 (95.043) +2022-11-14 13:23:39,787 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1822 (0.1774) Prec@1 65.000 (68.366) Prec@5 95.000 (95.042) +2022-11-14 13:23:39,797 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1720 (0.1774) Prec@1 72.000 (68.417) Prec@5 95.000 (95.042) +2022-11-14 13:23:39,806 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1752 (0.1773) Prec@1 67.000 (68.397) Prec@5 96.000 (95.055) +2022-11-14 13:23:39,815 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1435 (0.1769) Prec@1 76.000 (68.500) Prec@5 96.000 (95.068) +2022-11-14 13:23:39,825 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2091 (0.1773) Prec@1 66.000 (68.467) Prec@5 91.000 (95.013) +2022-11-14 13:23:39,834 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1672 (0.1772) Prec@1 70.000 (68.487) Prec@5 95.000 (95.013) +2022-11-14 13:23:39,843 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1718 (0.1771) Prec@1 68.000 (68.481) Prec@5 95.000 (95.013) +2022-11-14 13:23:39,853 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1467 (0.1767) Prec@1 73.000 (68.538) Prec@5 96.000 (95.026) +2022-11-14 13:23:39,862 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1767 (0.1767) Prec@1 68.000 (68.532) Prec@5 96.000 (95.038) +2022-11-14 13:23:39,871 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2058 (0.1771) Prec@1 62.000 (68.450) Prec@5 92.000 (95.000) +2022-11-14 13:23:39,880 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1878 (0.1772) Prec@1 66.000 (68.420) Prec@5 96.000 (95.012) +2022-11-14 13:23:39,889 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1629 (0.1770) Prec@1 70.000 (68.439) Prec@5 96.000 (95.024) +2022-11-14 13:23:39,899 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1684 (0.1769) Prec@1 67.000 (68.422) Prec@5 93.000 (95.000) +2022-11-14 13:23:39,908 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2146 (0.1774) Prec@1 61.000 (68.333) Prec@5 92.000 (94.964) +2022-11-14 13:23:39,917 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1890 (0.1775) Prec@1 62.000 (68.259) Prec@5 94.000 (94.953) +2022-11-14 13:23:39,926 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1688 (0.1774) Prec@1 71.000 (68.291) Prec@5 95.000 (94.953) +2022-11-14 13:23:39,936 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1814 (0.1775) Prec@1 67.000 (68.276) Prec@5 97.000 (94.977) +2022-11-14 13:23:39,946 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1702 (0.1774) Prec@1 71.000 (68.307) Prec@5 94.000 (94.966) +2022-11-14 13:23:39,955 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1938 (0.1776) Prec@1 64.000 (68.258) Prec@5 90.000 (94.910) +2022-11-14 13:23:39,962 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1901 (0.1777) Prec@1 72.000 (68.300) Prec@5 93.000 (94.889) +2022-11-14 13:23:39,970 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1938 (0.1779) Prec@1 67.000 (68.286) Prec@5 91.000 (94.846) +2022-11-14 13:23:39,979 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1566 (0.1776) Prec@1 70.000 (68.304) Prec@5 95.000 (94.848) +2022-11-14 13:23:39,988 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.2022 (0.1779) Prec@1 62.000 (68.237) Prec@5 93.000 (94.828) +2022-11-14 13:23:39,998 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1918 (0.1781) Prec@1 66.000 (68.213) Prec@5 95.000 (94.830) +2022-11-14 13:23:40,008 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1798 (0.1781) Prec@1 68.000 (68.211) Prec@5 93.000 (94.811) +2022-11-14 13:23:40,016 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1687 (0.1780) Prec@1 70.000 (68.229) Prec@5 93.000 (94.792) +2022-11-14 13:23:40,025 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1304 (0.1775) Prec@1 76.000 (68.309) Prec@5 97.000 (94.814) +2022-11-14 13:23:40,034 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1797 (0.1775) Prec@1 69.000 (68.316) Prec@5 93.000 (94.796) +2022-11-14 13:23:40,042 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2260 (0.1780) Prec@1 64.000 (68.273) Prec@5 95.000 (94.798) +2022-11-14 13:23:40,051 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1587 (0.1778) Prec@1 74.000 (68.330) Prec@5 95.000 (94.800) +2022-11-14 13:23:40,120 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:23:40,410 Epoch: [34][0/500] Time 0.022 (0.022) Data 0.209 (0.209) Loss 0.0967 (0.0967) Prec@1 81.000 (81.000) Prec@5 98.000 (98.000) +2022-11-14 13:23:40,624 Epoch: [34][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.1293 (0.1130) Prec@1 79.000 (80.000) Prec@5 100.000 (99.000) +2022-11-14 13:23:40,829 Epoch: [34][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.1317 (0.1192) Prec@1 83.000 (81.000) Prec@5 95.000 (97.667) +2022-11-14 13:23:41,030 Epoch: [34][30/500] Time 0.017 (0.018) Data 0.002 (0.008) Loss 0.1281 (0.1214) Prec@1 77.000 (80.000) Prec@5 98.000 (97.750) +2022-11-14 13:23:41,272 Epoch: [34][40/500] Time 0.024 (0.019) Data 0.001 (0.007) Loss 0.1145 (0.1200) Prec@1 80.000 (80.000) Prec@5 98.000 (97.800) +2022-11-14 13:23:41,544 Epoch: [34][50/500] Time 0.024 (0.020) Data 0.001 (0.006) Loss 0.1268 (0.1212) Prec@1 78.000 (79.667) Prec@5 97.000 (97.667) +2022-11-14 13:23:41,833 Epoch: [34][60/500] Time 0.041 (0.021) Data 0.002 (0.005) Loss 0.1484 (0.1251) Prec@1 73.000 (78.714) Prec@5 98.000 (97.714) +2022-11-14 13:23:42,159 Epoch: [34][70/500] Time 0.031 (0.022) Data 0.002 (0.005) Loss 0.1122 (0.1234) Prec@1 81.000 (79.000) Prec@5 98.000 (97.750) +2022-11-14 13:23:42,483 Epoch: [34][80/500] Time 0.028 (0.023) Data 0.002 (0.004) Loss 0.1519 (0.1266) Prec@1 70.000 (78.000) Prec@5 98.000 (97.778) +2022-11-14 13:23:42,807 Epoch: [34][90/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.1192 (0.1259) Prec@1 79.000 (78.100) Prec@5 98.000 (97.800) +2022-11-14 13:23:43,122 Epoch: [34][100/500] Time 0.032 (0.024) Data 0.002 (0.004) Loss 0.1511 (0.1282) Prec@1 73.000 (77.636) Prec@5 98.000 (97.818) +2022-11-14 13:23:43,449 Epoch: [34][110/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.1297 (0.1283) Prec@1 78.000 (77.667) Prec@5 98.000 (97.833) +2022-11-14 13:23:43,991 Epoch: [34][120/500] Time 0.071 (0.026) Data 0.002 (0.004) Loss 0.1225 (0.1278) Prec@1 78.000 (77.692) Prec@5 97.000 (97.769) +2022-11-14 13:23:44,443 Epoch: [34][130/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.1732 (0.1311) Prec@1 68.000 (77.000) Prec@5 96.000 (97.643) +2022-11-14 13:23:44,909 Epoch: [34][140/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.1310 (0.1311) Prec@1 79.000 (77.133) Prec@5 98.000 (97.667) +2022-11-14 13:23:45,373 Epoch: [34][150/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1584 (0.1328) Prec@1 67.000 (76.500) Prec@5 99.000 (97.750) +2022-11-14 13:23:45,880 Epoch: [34][160/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.1391 (0.1332) Prec@1 74.000 (76.353) Prec@5 96.000 (97.647) +2022-11-14 13:23:46,417 Epoch: [34][170/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1430 (0.1337) Prec@1 73.000 (76.167) Prec@5 98.000 (97.667) +2022-11-14 13:23:46,890 Epoch: [34][180/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.1178 (0.1329) Prec@1 82.000 (76.474) Prec@5 97.000 (97.632) +2022-11-14 13:23:47,435 Epoch: [34][190/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.1501 (0.1337) Prec@1 75.000 (76.400) Prec@5 94.000 (97.450) +2022-11-14 13:23:47,892 Epoch: [34][200/500] Time 0.044 (0.033) Data 0.001 (0.003) Loss 0.1104 (0.1326) Prec@1 82.000 (76.667) Prec@5 95.000 (97.333) +2022-11-14 13:23:48,453 Epoch: [34][210/500] Time 0.029 (0.034) Data 0.002 (0.003) Loss 0.1105 (0.1316) Prec@1 82.000 (76.909) Prec@5 99.000 (97.409) +2022-11-14 13:23:48,912 Epoch: [34][220/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.1152 (0.1309) Prec@1 80.000 (77.043) Prec@5 98.000 (97.435) +2022-11-14 13:23:49,373 Epoch: [34][230/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.1349 (0.1311) Prec@1 80.000 (77.167) Prec@5 99.000 (97.500) +2022-11-14 13:23:49,904 Epoch: [34][240/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.0995 (0.1298) Prec@1 86.000 (77.520) Prec@5 100.000 (97.600) +2022-11-14 13:23:50,359 Epoch: [34][250/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.1731 (0.1315) Prec@1 70.000 (77.231) Prec@5 99.000 (97.654) +2022-11-14 13:23:50,844 Epoch: [34][260/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.1502 (0.1322) Prec@1 74.000 (77.111) Prec@5 97.000 (97.630) +2022-11-14 13:23:51,395 Epoch: [34][270/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.1445 (0.1326) Prec@1 76.000 (77.071) Prec@5 95.000 (97.536) +2022-11-14 13:23:51,870 Epoch: [34][280/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1448 (0.1330) Prec@1 75.000 (77.000) Prec@5 97.000 (97.517) +2022-11-14 13:23:52,315 Epoch: [34][290/500] Time 0.022 (0.037) Data 0.002 (0.003) Loss 0.1428 (0.1333) Prec@1 76.000 (76.967) Prec@5 97.000 (97.500) +2022-11-14 13:23:52,618 Epoch: [34][300/500] Time 0.026 (0.036) Data 0.001 (0.003) Loss 0.1439 (0.1337) Prec@1 73.000 (76.839) Prec@5 97.000 (97.484) +2022-11-14 13:23:52,906 Epoch: [34][310/500] Time 0.027 (0.036) Data 0.001 (0.003) Loss 0.1036 (0.1327) Prec@1 83.000 (77.031) Prec@5 98.000 (97.500) +2022-11-14 13:23:53,249 Epoch: [34][320/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.1381 (0.1329) Prec@1 78.000 (77.061) Prec@5 97.000 (97.485) +2022-11-14 13:23:53,530 Epoch: [34][330/500] Time 0.024 (0.035) Data 0.002 (0.002) Loss 0.1355 (0.1330) Prec@1 76.000 (77.029) Prec@5 99.000 (97.529) +2022-11-14 13:23:53,866 Epoch: [34][340/500] Time 0.024 (0.035) Data 0.002 (0.002) Loss 0.1014 (0.1321) Prec@1 82.000 (77.171) Prec@5 99.000 (97.571) +2022-11-14 13:23:54,181 Epoch: [34][350/500] Time 0.034 (0.035) Data 0.003 (0.002) Loss 0.1568 (0.1328) Prec@1 75.000 (77.111) Prec@5 96.000 (97.528) +2022-11-14 13:23:54,510 Epoch: [34][360/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.1282 (0.1326) Prec@1 80.000 (77.189) Prec@5 99.000 (97.568) +2022-11-14 13:23:54,793 Epoch: [34][370/500] Time 0.028 (0.034) Data 0.002 (0.002) Loss 0.1484 (0.1331) Prec@1 74.000 (77.105) Prec@5 99.000 (97.605) +2022-11-14 13:23:55,084 Epoch: [34][380/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.1275 (0.1329) Prec@1 78.000 (77.128) Prec@5 99.000 (97.641) +2022-11-14 13:23:55,379 Epoch: [34][390/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.1320 (0.1329) Prec@1 77.000 (77.125) Prec@5 99.000 (97.675) +2022-11-14 13:23:55,735 Epoch: [34][400/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.1336 (0.1329) Prec@1 78.000 (77.146) Prec@5 99.000 (97.707) +2022-11-14 13:23:56,101 Epoch: [34][410/500] Time 0.031 (0.034) Data 0.002 (0.002) Loss 0.1270 (0.1328) Prec@1 77.000 (77.143) Prec@5 96.000 (97.667) +2022-11-14 13:23:56,465 Epoch: [34][420/500] Time 0.032 (0.034) Data 0.002 (0.002) Loss 0.1631 (0.1335) Prec@1 70.000 (76.977) Prec@5 98.000 (97.674) +2022-11-14 13:23:56,810 Epoch: [34][430/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.1596 (0.1341) Prec@1 71.000 (76.841) Prec@5 98.000 (97.682) +2022-11-14 13:23:57,164 Epoch: [34][440/500] Time 0.032 (0.034) Data 0.002 (0.002) Loss 0.1577 (0.1346) Prec@1 72.000 (76.733) Prec@5 98.000 (97.689) +2022-11-14 13:23:57,564 Epoch: [34][450/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.1376 (0.1347) Prec@1 80.000 (76.804) Prec@5 96.000 (97.652) +2022-11-14 13:23:58,166 Epoch: [34][460/500] Time 0.047 (0.034) Data 0.002 (0.002) Loss 0.1279 (0.1345) Prec@1 79.000 (76.851) Prec@5 100.000 (97.702) +2022-11-14 13:23:58,631 Epoch: [34][470/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.1135 (0.1341) Prec@1 81.000 (76.938) Prec@5 97.000 (97.688) +2022-11-14 13:23:59,103 Epoch: [34][480/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1155 (0.1337) Prec@1 80.000 (77.000) Prec@5 96.000 (97.653) +2022-11-14 13:23:59,568 Epoch: [34][490/500] Time 0.042 (0.035) Data 0.003 (0.002) Loss 0.1343 (0.1337) Prec@1 78.000 (77.020) Prec@5 99.000 (97.680) +2022-11-14 13:23:59,987 Epoch: [34][499/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1509 (0.1340) Prec@1 70.000 (76.882) Prec@5 98.000 (97.686) +2022-11-14 13:24:00,267 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.1397 (0.1397) Prec@1 76.000 (76.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:00,279 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1369 (0.1383) Prec@1 77.000 (76.500) Prec@5 99.000 (99.000) +2022-11-14 13:24:00,291 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1582 (0.1449) Prec@1 75.000 (76.000) Prec@5 95.000 (97.667) +2022-11-14 13:24:00,303 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1496 (0.1461) Prec@1 76.000 (76.000) Prec@5 100.000 (98.250) +2022-11-14 13:24:00,314 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1552 (0.1479) Prec@1 70.000 (74.800) Prec@5 97.000 (98.000) +2022-11-14 13:24:00,322 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.1429) Prec@1 80.000 (75.667) Prec@5 99.000 (98.167) +2022-11-14 13:24:00,331 Test: [6/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.1502 (0.1440) Prec@1 72.000 (75.143) Prec@5 96.000 (97.857) +2022-11-14 13:24:00,343 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1508 (0.1448) Prec@1 72.000 (74.750) Prec@5 97.000 (97.750) +2022-11-14 13:24:00,355 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1468 (0.1450) Prec@1 73.000 (74.556) Prec@5 99.000 (97.889) +2022-11-14 13:24:00,364 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.1420) Prec@1 82.000 (75.300) Prec@5 98.000 (97.900) +2022-11-14 13:24:00,376 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.1382) Prec@1 85.000 (76.182) Prec@5 98.000 (97.909) +2022-11-14 13:24:00,387 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1720 (0.1410) Prec@1 69.000 (75.583) Prec@5 99.000 (98.000) +2022-11-14 13:24:00,399 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1645 (0.1428) Prec@1 70.000 (75.154) Prec@5 100.000 (98.154) +2022-11-14 13:24:00,411 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1415 (0.1427) Prec@1 79.000 (75.429) Prec@5 95.000 (97.929) +2022-11-14 13:24:00,423 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1309 (0.1419) Prec@1 82.000 (75.867) Prec@5 98.000 (97.933) +2022-11-14 13:24:00,434 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1415) Prec@1 74.000 (75.750) Prec@5 99.000 (98.000) +2022-11-14 13:24:00,446 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1391) Prec@1 82.000 (76.118) Prec@5 97.000 (97.941) +2022-11-14 13:24:00,458 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1636 (0.1405) Prec@1 69.000 (75.722) Prec@5 98.000 (97.944) +2022-11-14 13:24:00,469 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1412) Prec@1 74.000 (75.632) Prec@5 97.000 (97.895) +2022-11-14 13:24:00,481 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1494 (0.1416) Prec@1 70.000 (75.350) Prec@5 97.000 (97.850) +2022-11-14 13:24:00,492 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1282 (0.1409) Prec@1 78.000 (75.476) Prec@5 98.000 (97.857) +2022-11-14 13:24:00,503 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1568 (0.1417) Prec@1 70.000 (75.227) Prec@5 97.000 (97.818) +2022-11-14 13:24:00,515 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1587 (0.1424) Prec@1 74.000 (75.174) Prec@5 98.000 (97.826) +2022-11-14 13:24:00,528 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1413) Prec@1 77.000 (75.250) Prec@5 99.000 (97.875) +2022-11-14 13:24:00,540 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1413) Prec@1 77.000 (75.320) Prec@5 99.000 (97.920) +2022-11-14 13:24:00,553 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1759 (0.1426) Prec@1 70.000 (75.115) Prec@5 94.000 (97.769) +2022-11-14 13:24:00,566 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.1416) Prec@1 83.000 (75.407) Prec@5 99.000 (97.815) +2022-11-14 13:24:00,579 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1422) Prec@1 73.000 (75.321) Prec@5 99.000 (97.857) +2022-11-14 13:24:00,591 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1421) Prec@1 74.000 (75.276) Prec@5 99.000 (97.897) +2022-11-14 13:24:00,605 Test: [29/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.1411) Prec@1 81.000 (75.467) Prec@5 98.000 (97.900) +2022-11-14 13:24:00,618 Test: [30/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1531 (0.1415) Prec@1 69.000 (75.258) Prec@5 97.000 (97.871) +2022-11-14 13:24:00,632 Test: [31/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.1407) Prec@1 80.000 (75.406) Prec@5 98.000 (97.875) +2022-11-14 13:24:00,644 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1493 (0.1409) Prec@1 74.000 (75.364) Prec@5 94.000 (97.758) +2022-11-14 13:24:00,656 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1501 (0.1412) Prec@1 75.000 (75.353) Prec@5 97.000 (97.735) +2022-11-14 13:24:00,669 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.1418) Prec@1 69.000 (75.171) Prec@5 93.000 (97.600) +2022-11-14 13:24:00,680 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1121 (0.1410) Prec@1 81.000 (75.333) Prec@5 99.000 (97.639) +2022-11-14 13:24:00,691 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1415) Prec@1 71.000 (75.216) Prec@5 93.000 (97.514) +2022-11-14 13:24:00,703 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1413 (0.1415) Prec@1 74.000 (75.184) Prec@5 98.000 (97.526) +2022-11-14 13:24:00,715 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1410) Prec@1 78.000 (75.256) Prec@5 96.000 (97.487) +2022-11-14 13:24:00,725 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.1400) Prec@1 87.000 (75.550) Prec@5 97.000 (97.475) +2022-11-14 13:24:00,738 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1432 (0.1401) Prec@1 78.000 (75.610) Prec@5 97.000 (97.463) +2022-11-14 13:24:00,750 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1399) Prec@1 76.000 (75.619) Prec@5 97.000 (97.452) +2022-11-14 13:24:00,760 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1391) Prec@1 82.000 (75.767) Prec@5 97.000 (97.442) +2022-11-14 13:24:00,773 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1430 (0.1392) Prec@1 77.000 (75.795) Prec@5 96.000 (97.409) +2022-11-14 13:24:00,786 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1282 (0.1389) Prec@1 79.000 (75.867) Prec@5 100.000 (97.467) +2022-11-14 13:24:00,798 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1389) Prec@1 74.000 (75.826) Prec@5 96.000 (97.435) +2022-11-14 13:24:00,809 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1388) Prec@1 77.000 (75.851) Prec@5 98.000 (97.447) +2022-11-14 13:24:00,826 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1313 (0.1387) Prec@1 74.000 (75.812) Prec@5 98.000 (97.458) +2022-11-14 13:24:00,845 Test: [48/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.1383) Prec@1 81.000 (75.918) Prec@5 100.000 (97.510) +2022-11-14 13:24:00,861 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.1390) Prec@1 69.000 (75.780) Prec@5 96.000 (97.480) +2022-11-14 13:24:00,877 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1521 (0.1393) Prec@1 73.000 (75.725) Prec@5 95.000 (97.431) +2022-11-14 13:24:00,894 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1728 (0.1399) Prec@1 72.000 (75.654) Prec@5 96.000 (97.404) +2022-11-14 13:24:00,910 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1399) Prec@1 77.000 (75.679) Prec@5 99.000 (97.434) +2022-11-14 13:24:00,927 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1302 (0.1397) Prec@1 78.000 (75.722) Prec@5 98.000 (97.444) +2022-11-14 13:24:00,943 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1690 (0.1402) Prec@1 73.000 (75.673) Prec@5 98.000 (97.455) +2022-11-14 13:24:00,959 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1400) Prec@1 75.000 (75.661) Prec@5 98.000 (97.464) +2022-11-14 13:24:00,976 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1642 (0.1404) Prec@1 69.000 (75.544) Prec@5 97.000 (97.456) +2022-11-14 13:24:00,991 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1340 (0.1403) Prec@1 76.000 (75.552) Prec@5 99.000 (97.483) +2022-11-14 13:24:01,006 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1968 (0.1412) Prec@1 65.000 (75.373) Prec@5 98.000 (97.492) +2022-11-14 13:24:01,022 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1528 (0.1414) Prec@1 73.000 (75.333) Prec@5 98.000 (97.500) +2022-11-14 13:24:01,036 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1416) Prec@1 71.000 (75.262) Prec@5 98.000 (97.508) +2022-11-14 13:24:01,052 Test: [61/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1484 (0.1417) Prec@1 74.000 (75.242) Prec@5 94.000 (97.452) +2022-11-14 13:24:01,069 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1232 (0.1414) Prec@1 80.000 (75.317) Prec@5 99.000 (97.476) +2022-11-14 13:24:01,085 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.1411) Prec@1 81.000 (75.406) Prec@5 99.000 (97.500) +2022-11-14 13:24:01,101 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1415) Prec@1 68.000 (75.292) Prec@5 97.000 (97.492) +2022-11-14 13:24:01,117 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1449 (0.1415) Prec@1 76.000 (75.303) Prec@5 97.000 (97.485) +2022-11-14 13:24:01,132 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1282 (0.1413) Prec@1 79.000 (75.358) Prec@5 100.000 (97.522) +2022-11-14 13:24:01,146 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1621 (0.1416) Prec@1 72.000 (75.309) Prec@5 98.000 (97.529) +2022-11-14 13:24:01,158 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.1414) Prec@1 75.000 (75.304) Prec@5 97.000 (97.522) +2022-11-14 13:24:01,174 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1846 (0.1421) Prec@1 69.000 (75.214) Prec@5 98.000 (97.529) +2022-11-14 13:24:01,189 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1446 (0.1421) Prec@1 73.000 (75.183) Prec@5 98.000 (97.535) +2022-11-14 13:24:01,205 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.1418) Prec@1 80.000 (75.250) Prec@5 98.000 (97.542) +2022-11-14 13:24:01,220 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.1415) Prec@1 78.000 (75.288) Prec@5 99.000 (97.562) +2022-11-14 13:24:01,235 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.1411) Prec@1 79.000 (75.338) Prec@5 99.000 (97.581) +2022-11-14 13:24:01,246 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1573 (0.1413) Prec@1 75.000 (75.333) Prec@5 96.000 (97.560) +2022-11-14 13:24:01,257 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1305 (0.1412) Prec@1 76.000 (75.342) Prec@5 98.000 (97.566) +2022-11-14 13:24:01,268 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1411) Prec@1 75.000 (75.338) Prec@5 97.000 (97.558) +2022-11-14 13:24:01,281 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1486 (0.1412) Prec@1 74.000 (75.321) Prec@5 97.000 (97.551) +2022-11-14 13:24:01,293 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1288 (0.1411) Prec@1 79.000 (75.367) Prec@5 98.000 (97.557) +2022-11-14 13:24:01,304 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1341 (0.1410) Prec@1 73.000 (75.338) Prec@5 97.000 (97.550) +2022-11-14 13:24:01,315 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1212 (0.1408) Prec@1 74.000 (75.321) Prec@5 98.000 (97.556) +2022-11-14 13:24:01,328 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.1406) Prec@1 82.000 (75.402) Prec@5 98.000 (97.561) +2022-11-14 13:24:01,339 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1406) Prec@1 77.000 (75.422) Prec@5 98.000 (97.566) +2022-11-14 13:24:01,351 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1422 (0.1406) Prec@1 73.000 (75.393) Prec@5 98.000 (97.571) +2022-11-14 13:24:01,363 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1535 (0.1407) Prec@1 74.000 (75.376) Prec@5 97.000 (97.565) +2022-11-14 13:24:01,376 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1349 (0.1407) Prec@1 74.000 (75.360) Prec@5 98.000 (97.570) +2022-11-14 13:24:01,388 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1520 (0.1408) Prec@1 70.000 (75.299) Prec@5 96.000 (97.552) +2022-11-14 13:24:01,399 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1350 (0.1407) Prec@1 77.000 (75.318) Prec@5 98.000 (97.557) +2022-11-14 13:24:01,411 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1407) Prec@1 77.000 (75.337) Prec@5 97.000 (97.551) +2022-11-14 13:24:01,423 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1406) Prec@1 76.000 (75.344) Prec@5 98.000 (97.556) +2022-11-14 13:24:01,433 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1405) Prec@1 78.000 (75.374) Prec@5 97.000 (97.549) +2022-11-14 13:24:01,446 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.1399) Prec@1 85.000 (75.478) Prec@5 99.000 (97.565) +2022-11-14 13:24:01,459 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.1399) Prec@1 77.000 (75.495) Prec@5 98.000 (97.570) +2022-11-14 13:24:01,471 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1574 (0.1401) Prec@1 72.000 (75.457) Prec@5 98.000 (97.574) +2022-11-14 13:24:01,483 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1467 (0.1401) Prec@1 73.000 (75.432) Prec@5 98.000 (97.579) +2022-11-14 13:24:01,495 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.1398) Prec@1 81.000 (75.490) Prec@5 99.000 (97.594) +2022-11-14 13:24:01,507 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.1395) Prec@1 81.000 (75.546) Prec@5 98.000 (97.598) +2022-11-14 13:24:01,518 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1693 (0.1398) Prec@1 70.000 (75.490) Prec@5 97.000 (97.592) +2022-11-14 13:24:01,529 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1399) Prec@1 72.000 (75.455) Prec@5 98.000 (97.596) +2022-11-14 13:24:01,542 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1492 (0.1400) Prec@1 74.000 (75.440) Prec@5 94.000 (97.560) +2022-11-14 13:24:01,598 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:24:01,919 Epoch: [35][0/500] Time 0.031 (0.031) Data 0.227 (0.227) Loss 0.1300 (0.1300) Prec@1 79.000 (79.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:02,135 Epoch: [35][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.1187 (0.1243) Prec@1 79.000 (79.000) Prec@5 97.000 (98.000) +2022-11-14 13:24:02,364 Epoch: [35][20/500] Time 0.028 (0.020) Data 0.002 (0.013) Loss 0.0931 (0.1139) Prec@1 84.000 (80.667) Prec@5 99.000 (98.333) +2022-11-14 13:24:02,770 Epoch: [35][30/500] Time 0.024 (0.025) Data 0.002 (0.009) Loss 0.1261 (0.1170) Prec@1 80.000 (80.500) Prec@5 99.000 (98.500) +2022-11-14 13:24:03,184 Epoch: [35][40/500] Time 0.028 (0.028) Data 0.002 (0.007) Loss 0.1557 (0.1247) Prec@1 71.000 (78.600) Prec@5 95.000 (97.800) +2022-11-14 13:24:03,671 Epoch: [35][50/500] Time 0.043 (0.032) Data 0.002 (0.006) Loss 0.1229 (0.1244) Prec@1 76.000 (78.167) Prec@5 99.000 (98.000) +2022-11-14 13:24:04,122 Epoch: [35][60/500] Time 0.044 (0.033) Data 0.002 (0.006) Loss 0.1095 (0.1223) Prec@1 80.000 (78.429) Prec@5 99.000 (98.143) +2022-11-14 13:24:04,510 Epoch: [35][70/500] Time 0.039 (0.033) Data 0.002 (0.005) Loss 0.1323 (0.1235) Prec@1 75.000 (78.000) Prec@5 99.000 (98.250) +2022-11-14 13:24:04,894 Epoch: [35][80/500] Time 0.031 (0.034) Data 0.002 (0.005) Loss 0.1179 (0.1229) Prec@1 79.000 (78.111) Prec@5 98.000 (98.222) +2022-11-14 13:24:05,356 Epoch: [35][90/500] Time 0.046 (0.034) Data 0.002 (0.004) Loss 0.1773 (0.1284) Prec@1 71.000 (77.400) Prec@5 95.000 (97.900) +2022-11-14 13:24:05,722 Epoch: [35][100/500] Time 0.035 (0.034) Data 0.002 (0.004) Loss 0.1880 (0.1338) Prec@1 67.000 (76.455) Prec@5 96.000 (97.727) +2022-11-14 13:24:06,098 Epoch: [35][110/500] Time 0.034 (0.034) Data 0.002 (0.004) Loss 0.1200 (0.1326) Prec@1 81.000 (76.833) Prec@5 98.000 (97.750) +2022-11-14 13:24:06,481 Epoch: [35][120/500] Time 0.036 (0.034) Data 0.002 (0.004) Loss 0.1184 (0.1315) Prec@1 78.000 (76.923) Prec@5 96.000 (97.615) +2022-11-14 13:24:06,863 Epoch: [35][130/500] Time 0.033 (0.034) Data 0.002 (0.004) Loss 0.1344 (0.1317) Prec@1 77.000 (76.929) Prec@5 98.000 (97.643) +2022-11-14 13:24:07,242 Epoch: [35][140/500] Time 0.037 (0.034) Data 0.001 (0.004) Loss 0.1025 (0.1298) Prec@1 79.000 (77.067) Prec@5 99.000 (97.733) +2022-11-14 13:24:07,623 Epoch: [35][150/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.1387 (0.1303) Prec@1 76.000 (77.000) Prec@5 98.000 (97.750) +2022-11-14 13:24:08,010 Epoch: [35][160/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0995 (0.1285) Prec@1 84.000 (77.412) Prec@5 99.000 (97.824) +2022-11-14 13:24:08,390 Epoch: [35][170/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.1674 (0.1307) Prec@1 69.000 (76.944) Prec@5 95.000 (97.667) +2022-11-14 13:24:08,770 Epoch: [35][180/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.1594 (0.1322) Prec@1 70.000 (76.579) Prec@5 99.000 (97.737) +2022-11-14 13:24:09,153 Epoch: [35][190/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1181 (0.1315) Prec@1 81.000 (76.800) Prec@5 96.000 (97.650) +2022-11-14 13:24:09,590 Epoch: [35][200/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.1335 (0.1316) Prec@1 76.000 (76.762) Prec@5 98.000 (97.667) +2022-11-14 13:24:10,070 Epoch: [35][210/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.1044 (0.1304) Prec@1 80.000 (76.909) Prec@5 100.000 (97.773) +2022-11-14 13:24:10,498 Epoch: [35][220/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.1489 (0.1312) Prec@1 73.000 (76.739) Prec@5 98.000 (97.783) +2022-11-14 13:24:10,986 Epoch: [35][230/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.1118 (0.1304) Prec@1 80.000 (76.875) Prec@5 99.000 (97.833) +2022-11-14 13:24:11,446 Epoch: [35][240/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.1262 (0.1302) Prec@1 77.000 (76.880) Prec@5 98.000 (97.840) +2022-11-14 13:24:11,826 Epoch: [35][250/500] Time 0.051 (0.035) Data 0.002 (0.003) Loss 0.0954 (0.1289) Prec@1 82.000 (77.077) Prec@5 99.000 (97.885) +2022-11-14 13:24:12,289 Epoch: [35][260/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.1134 (0.1283) Prec@1 79.000 (77.148) Prec@5 100.000 (97.963) +2022-11-14 13:24:12,740 Epoch: [35][270/500] Time 0.041 (0.036) Data 0.003 (0.003) Loss 0.1219 (0.1281) Prec@1 77.000 (77.143) Prec@5 98.000 (97.964) +2022-11-14 13:24:13,174 Epoch: [35][280/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0960 (0.1269) Prec@1 80.000 (77.241) Prec@5 97.000 (97.931) +2022-11-14 13:24:13,542 Epoch: [35][290/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.1146 (0.1265) Prec@1 82.000 (77.400) Prec@5 98.000 (97.933) +2022-11-14 13:24:13,999 Epoch: [35][300/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1389 (0.1269) Prec@1 76.000 (77.355) Prec@5 95.000 (97.839) +2022-11-14 13:24:14,492 Epoch: [35][310/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.1451 (0.1275) Prec@1 77.000 (77.344) Prec@5 98.000 (97.844) +2022-11-14 13:24:14,938 Epoch: [35][320/500] Time 0.037 (0.036) Data 0.003 (0.003) Loss 0.1053 (0.1268) Prec@1 83.000 (77.515) Prec@5 99.000 (97.879) +2022-11-14 13:24:15,329 Epoch: [35][330/500] Time 0.048 (0.036) Data 0.003 (0.003) Loss 0.1392 (0.1272) Prec@1 78.000 (77.529) Prec@5 98.000 (97.882) +2022-11-14 13:24:15,752 Epoch: [35][340/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.1235 (0.1271) Prec@1 80.000 (77.600) Prec@5 98.000 (97.886) +2022-11-14 13:24:16,145 Epoch: [35][350/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.1260 (0.1271) Prec@1 79.000 (77.639) Prec@5 95.000 (97.806) +2022-11-14 13:24:16,569 Epoch: [35][360/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.1381 (0.1274) Prec@1 75.000 (77.568) Prec@5 97.000 (97.784) +2022-11-14 13:24:16,950 Epoch: [35][370/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.1385 (0.1276) Prec@1 74.000 (77.474) Prec@5 97.000 (97.763) +2022-11-14 13:24:17,372 Epoch: [35][380/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1296 (0.1277) Prec@1 76.000 (77.436) Prec@5 95.000 (97.692) +2022-11-14 13:24:17,738 Epoch: [35][390/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.1217 (0.1275) Prec@1 77.000 (77.425) Prec@5 99.000 (97.725) +2022-11-14 13:24:18,123 Epoch: [35][400/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.1211 (0.1274) Prec@1 81.000 (77.512) Prec@5 98.000 (97.732) +2022-11-14 13:24:18,513 Epoch: [35][410/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.1572 (0.1281) Prec@1 72.000 (77.381) Prec@5 98.000 (97.738) +2022-11-14 13:24:18,895 Epoch: [35][420/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.1088 (0.1276) Prec@1 83.000 (77.512) Prec@5 98.000 (97.744) +2022-11-14 13:24:19,289 Epoch: [35][430/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1370 (0.1279) Prec@1 76.000 (77.477) Prec@5 95.000 (97.682) +2022-11-14 13:24:19,673 Epoch: [35][440/500] Time 0.040 (0.036) Data 0.001 (0.002) Loss 0.1251 (0.1278) Prec@1 77.000 (77.467) Prec@5 97.000 (97.667) +2022-11-14 13:24:20,105 Epoch: [35][450/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.1304 (0.1279) Prec@1 75.000 (77.413) Prec@5 100.000 (97.717) +2022-11-14 13:24:20,522 Epoch: [35][460/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1343 (0.1280) Prec@1 74.000 (77.340) Prec@5 98.000 (97.723) +2022-11-14 13:24:20,954 Epoch: [35][470/500] Time 0.048 (0.036) Data 0.002 (0.002) Loss 0.1138 (0.1277) Prec@1 79.000 (77.375) Prec@5 98.000 (97.729) +2022-11-14 13:24:21,321 Epoch: [35][480/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.1036 (0.1272) Prec@1 82.000 (77.469) Prec@5 99.000 (97.755) +2022-11-14 13:24:21,726 Epoch: [35][490/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.1449 (0.1276) Prec@1 76.000 (77.440) Prec@5 97.000 (97.740) +2022-11-14 13:24:22,083 Epoch: [35][499/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.1632 (0.1283) Prec@1 74.000 (77.373) Prec@5 95.000 (97.686) +2022-11-14 13:24:22,376 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1556 (0.1556) Prec@1 72.000 (72.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:22,384 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1531 (0.1543) Prec@1 72.000 (72.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:22,392 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1675 (0.1587) Prec@1 65.000 (69.667) Prec@5 97.000 (98.333) +2022-11-14 13:24:22,405 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1521 (0.1571) Prec@1 75.000 (71.000) Prec@5 99.000 (98.500) +2022-11-14 13:24:22,414 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1974 (0.1651) Prec@1 63.000 (69.400) Prec@5 98.000 (98.400) +2022-11-14 13:24:22,422 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1285 (0.1590) Prec@1 80.000 (71.167) Prec@5 98.000 (98.333) +2022-11-14 13:24:22,431 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1494 (0.1577) Prec@1 74.000 (71.571) Prec@5 98.000 (98.286) +2022-11-14 13:24:22,441 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1812 (0.1606) Prec@1 67.000 (71.000) Prec@5 95.000 (97.875) +2022-11-14 13:24:22,449 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1735 (0.1620) Prec@1 66.000 (70.444) Prec@5 96.000 (97.667) +2022-11-14 13:24:22,458 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1577) Prec@1 79.000 (71.300) Prec@5 97.000 (97.600) +2022-11-14 13:24:22,466 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.1543) Prec@1 75.000 (71.636) Prec@5 99.000 (97.727) +2022-11-14 13:24:22,474 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1547) Prec@1 69.000 (71.417) Prec@5 99.000 (97.833) +2022-11-14 13:24:22,482 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1591 (0.1550) Prec@1 71.000 (71.385) Prec@5 99.000 (97.923) +2022-11-14 13:24:22,490 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1812 (0.1569) Prec@1 67.000 (71.071) Prec@5 98.000 (97.929) +2022-11-14 13:24:22,498 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1673 (0.1576) Prec@1 71.000 (71.067) Prec@5 98.000 (97.933) +2022-11-14 13:24:22,506 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.2130 (0.1610) Prec@1 61.000 (70.438) Prec@5 97.000 (97.875) +2022-11-14 13:24:22,515 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1315 (0.1593) Prec@1 77.000 (70.824) Prec@5 97.000 (97.824) +2022-11-14 13:24:22,524 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1728 (0.1601) Prec@1 67.000 (70.611) Prec@5 95.000 (97.667) +2022-11-14 13:24:22,532 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1760 (0.1609) Prec@1 68.000 (70.474) Prec@5 93.000 (97.421) +2022-11-14 13:24:22,543 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1730 (0.1615) Prec@1 67.000 (70.300) Prec@5 95.000 (97.300) +2022-11-14 13:24:22,552 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1827 (0.1625) Prec@1 65.000 (70.048) Prec@5 97.000 (97.286) +2022-11-14 13:24:22,561 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1634 (0.1626) Prec@1 67.000 (69.909) Prec@5 96.000 (97.227) +2022-11-14 13:24:22,570 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1884 (0.1637) Prec@1 69.000 (69.870) Prec@5 97.000 (97.217) +2022-11-14 13:24:22,581 Test: [23/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1452 (0.1629) Prec@1 72.000 (69.958) Prec@5 97.000 (97.208) +2022-11-14 13:24:22,590 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1652 (0.1630) Prec@1 70.000 (69.960) Prec@5 98.000 (97.240) +2022-11-14 13:24:22,600 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1917 (0.1641) Prec@1 64.000 (69.731) Prec@5 94.000 (97.115) +2022-11-14 13:24:22,608 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1624 (0.1640) Prec@1 68.000 (69.667) Prec@5 99.000 (97.185) +2022-11-14 13:24:22,617 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1776 (0.1645) Prec@1 70.000 (69.679) Prec@5 95.000 (97.107) +2022-11-14 13:24:22,627 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1460 (0.1639) Prec@1 75.000 (69.862) Prec@5 98.000 (97.138) +2022-11-14 13:24:22,637 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1483 (0.1634) Prec@1 71.000 (69.900) Prec@5 97.000 (97.133) +2022-11-14 13:24:22,647 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1667 (0.1635) Prec@1 69.000 (69.871) Prec@5 99.000 (97.194) +2022-11-14 13:24:22,655 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1622 (0.1634) Prec@1 72.000 (69.938) Prec@5 97.000 (97.188) +2022-11-14 13:24:22,664 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1684 (0.1636) Prec@1 67.000 (69.848) Prec@5 96.000 (97.152) +2022-11-14 13:24:22,673 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1902 (0.1644) Prec@1 64.000 (69.676) Prec@5 96.000 (97.118) +2022-11-14 13:24:22,682 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1757 (0.1647) Prec@1 70.000 (69.686) Prec@5 98.000 (97.143) +2022-11-14 13:24:22,691 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1555 (0.1644) Prec@1 73.000 (69.778) Prec@5 98.000 (97.167) +2022-11-14 13:24:22,699 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1642 (0.1644) Prec@1 72.000 (69.838) Prec@5 95.000 (97.108) +2022-11-14 13:24:22,708 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1806 (0.1648) Prec@1 69.000 (69.816) Prec@5 98.000 (97.132) +2022-11-14 13:24:22,717 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1563 (0.1646) Prec@1 74.000 (69.923) Prec@5 98.000 (97.154) +2022-11-14 13:24:22,727 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1344 (0.1639) Prec@1 78.000 (70.125) Prec@5 99.000 (97.200) +2022-11-14 13:24:22,737 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1837 (0.1644) Prec@1 66.000 (70.024) Prec@5 97.000 (97.195) +2022-11-14 13:24:22,746 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1573 (0.1642) Prec@1 74.000 (70.119) Prec@5 94.000 (97.119) +2022-11-14 13:24:22,755 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1727 (0.1644) Prec@1 68.000 (70.070) Prec@5 97.000 (97.116) +2022-11-14 13:24:22,764 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1496 (0.1641) Prec@1 74.000 (70.159) Prec@5 100.000 (97.182) +2022-11-14 13:24:22,772 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1446 (0.1636) Prec@1 76.000 (70.289) Prec@5 96.000 (97.156) +2022-11-14 13:24:22,780 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1554 (0.1634) Prec@1 71.000 (70.304) Prec@5 98.000 (97.174) +2022-11-14 13:24:22,788 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1330 (0.1628) Prec@1 75.000 (70.404) Prec@5 97.000 (97.170) +2022-11-14 13:24:22,798 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1589 (0.1627) Prec@1 69.000 (70.375) Prec@5 98.000 (97.188) +2022-11-14 13:24:22,806 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1420 (0.1623) Prec@1 73.000 (70.429) Prec@5 98.000 (97.204) +2022-11-14 13:24:22,815 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1902 (0.1628) Prec@1 67.000 (70.360) Prec@5 97.000 (97.200) +2022-11-14 13:24:22,825 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1342 (0.1623) Prec@1 72.000 (70.392) Prec@5 96.000 (97.176) +2022-11-14 13:24:22,834 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1808 (0.1626) Prec@1 65.000 (70.288) Prec@5 92.000 (97.077) +2022-11-14 13:24:22,843 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1688 (0.1628) Prec@1 66.000 (70.208) Prec@5 99.000 (97.113) +2022-11-14 13:24:22,853 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1596 (0.1627) Prec@1 69.000 (70.185) Prec@5 95.000 (97.074) +2022-11-14 13:24:22,862 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1747 (0.1629) Prec@1 65.000 (70.091) Prec@5 100.000 (97.127) +2022-11-14 13:24:22,872 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1571 (0.1628) Prec@1 69.000 (70.071) Prec@5 96.000 (97.107) +2022-11-14 13:24:22,882 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1836 (0.1632) Prec@1 64.000 (69.965) Prec@5 97.000 (97.105) +2022-11-14 13:24:22,891 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1509 (0.1630) Prec@1 74.000 (70.034) Prec@5 96.000 (97.086) +2022-11-14 13:24:22,901 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1777 (0.1632) Prec@1 70.000 (70.034) Prec@5 100.000 (97.136) +2022-11-14 13:24:22,910 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1628 (0.1632) Prec@1 70.000 (70.033) Prec@5 96.000 (97.117) +2022-11-14 13:24:22,919 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1626 (0.1632) Prec@1 69.000 (70.016) Prec@5 97.000 (97.115) +2022-11-14 13:24:22,928 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1815 (0.1635) Prec@1 67.000 (69.968) Prec@5 94.000 (97.065) +2022-11-14 13:24:22,938 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1372 (0.1631) Prec@1 77.000 (70.079) Prec@5 96.000 (97.048) +2022-11-14 13:24:22,947 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1541 (0.1629) Prec@1 68.000 (70.047) Prec@5 100.000 (97.094) +2022-11-14 13:24:22,956 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1717 (0.1631) Prec@1 73.000 (70.092) Prec@5 94.000 (97.046) +2022-11-14 13:24:22,965 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1778 (0.1633) Prec@1 69.000 (70.076) Prec@5 99.000 (97.076) +2022-11-14 13:24:22,974 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1439 (0.1630) Prec@1 75.000 (70.149) Prec@5 96.000 (97.060) +2022-11-14 13:24:22,983 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1831 (0.1633) Prec@1 71.000 (70.162) Prec@5 96.000 (97.044) +2022-11-14 13:24:22,993 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1489 (0.1631) Prec@1 73.000 (70.203) Prec@5 97.000 (97.043) +2022-11-14 13:24:23,002 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1814 (0.1634) Prec@1 66.000 (70.143) Prec@5 95.000 (97.014) +2022-11-14 13:24:23,011 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1494 (0.1632) Prec@1 72.000 (70.169) Prec@5 96.000 (97.000) +2022-11-14 13:24:23,021 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1634 (0.1632) Prec@1 68.000 (70.139) Prec@5 96.000 (96.986) +2022-11-14 13:24:23,030 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1350 (0.1628) Prec@1 77.000 (70.233) Prec@5 97.000 (96.986) +2022-11-14 13:24:23,039 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1387 (0.1625) Prec@1 77.000 (70.324) Prec@5 97.000 (96.986) +2022-11-14 13:24:23,049 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1748 (0.1626) Prec@1 69.000 (70.307) Prec@5 96.000 (96.973) +2022-11-14 13:24:23,057 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1614 (0.1626) Prec@1 72.000 (70.329) Prec@5 98.000 (96.987) +2022-11-14 13:24:23,066 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1719 (0.1627) Prec@1 72.000 (70.351) Prec@5 97.000 (96.987) +2022-11-14 13:24:23,076 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.1627) Prec@1 69.000 (70.333) Prec@5 95.000 (96.962) +2022-11-14 13:24:23,085 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1422 (0.1625) Prec@1 71.000 (70.342) Prec@5 100.000 (97.000) +2022-11-14 13:24:23,095 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1622) Prec@1 76.000 (70.412) Prec@5 94.000 (96.963) +2022-11-14 13:24:23,105 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1619) Prec@1 76.000 (70.481) Prec@5 92.000 (96.901) +2022-11-14 13:24:23,116 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1912 (0.1622) Prec@1 70.000 (70.476) Prec@5 96.000 (96.890) +2022-11-14 13:24:23,126 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1621) Prec@1 74.000 (70.518) Prec@5 97.000 (96.892) +2022-11-14 13:24:23,135 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1717 (0.1622) Prec@1 70.000 (70.512) Prec@5 95.000 (96.869) +2022-11-14 13:24:23,145 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1641 (0.1623) Prec@1 70.000 (70.506) Prec@5 96.000 (96.859) +2022-11-14 13:24:23,155 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1555 (0.1622) Prec@1 74.000 (70.547) Prec@5 98.000 (96.872) +2022-11-14 13:24:23,164 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1756 (0.1623) Prec@1 68.000 (70.517) Prec@5 98.000 (96.885) +2022-11-14 13:24:23,174 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1476 (0.1622) Prec@1 76.000 (70.580) Prec@5 95.000 (96.864) +2022-11-14 13:24:23,184 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1724 (0.1623) Prec@1 71.000 (70.584) Prec@5 94.000 (96.831) +2022-11-14 13:24:23,193 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1623) Prec@1 69.000 (70.567) Prec@5 95.000 (96.811) +2022-11-14 13:24:23,203 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1704 (0.1624) Prec@1 69.000 (70.549) Prec@5 96.000 (96.802) +2022-11-14 13:24:23,212 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.1618) Prec@1 81.000 (70.663) Prec@5 96.000 (96.793) +2022-11-14 13:24:23,223 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1695 (0.1619) Prec@1 69.000 (70.645) Prec@5 96.000 (96.785) +2022-11-14 13:24:23,232 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1730 (0.1620) Prec@1 66.000 (70.596) Prec@5 94.000 (96.755) +2022-11-14 13:24:23,243 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1619) Prec@1 73.000 (70.621) Prec@5 97.000 (96.758) +2022-11-14 13:24:23,253 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1514 (0.1618) Prec@1 72.000 (70.635) Prec@5 99.000 (96.781) +2022-11-14 13:24:23,264 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1295 (0.1615) Prec@1 80.000 (70.732) Prec@5 98.000 (96.794) +2022-11-14 13:24:23,275 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1616) Prec@1 67.000 (70.694) Prec@5 96.000 (96.786) +2022-11-14 13:24:23,287 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1805 (0.1618) Prec@1 66.000 (70.646) Prec@5 95.000 (96.768) +2022-11-14 13:24:23,299 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1655 (0.1619) Prec@1 69.000 (70.630) Prec@5 97.000 (96.770) +2022-11-14 13:24:23,368 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:24:23,667 Epoch: [36][0/500] Time 0.023 (0.023) Data 0.218 (0.218) Loss 0.1357 (0.1357) Prec@1 74.000 (74.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:23,897 Epoch: [36][10/500] Time 0.022 (0.020) Data 0.002 (0.021) Loss 0.1188 (0.1273) Prec@1 78.000 (76.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:24,155 Epoch: [36][20/500] Time 0.022 (0.022) Data 0.002 (0.012) Loss 0.1262 (0.1269) Prec@1 79.000 (77.000) Prec@5 97.000 (98.333) +2022-11-14 13:24:24,411 Epoch: [36][30/500] Time 0.024 (0.022) Data 0.002 (0.009) Loss 0.1316 (0.1281) Prec@1 77.000 (77.000) Prec@5 100.000 (98.750) +2022-11-14 13:24:24,669 Epoch: [36][40/500] Time 0.023 (0.022) Data 0.001 (0.007) Loss 0.1332 (0.1291) Prec@1 74.000 (76.400) Prec@5 97.000 (98.400) +2022-11-14 13:24:24,943 Epoch: [36][50/500] Time 0.030 (0.022) Data 0.002 (0.006) Loss 0.1246 (0.1284) Prec@1 78.000 (76.667) Prec@5 98.000 (98.333) +2022-11-14 13:24:25,354 Epoch: [36][60/500] Time 0.041 (0.025) Data 0.002 (0.005) Loss 0.1289 (0.1284) Prec@1 79.000 (77.000) Prec@5 99.000 (98.429) +2022-11-14 13:24:25,775 Epoch: [36][70/500] Time 0.040 (0.026) Data 0.002 (0.005) Loss 0.1211 (0.1275) Prec@1 79.000 (77.250) Prec@5 99.000 (98.500) +2022-11-14 13:24:26,237 Epoch: [36][80/500] Time 0.047 (0.028) Data 0.002 (0.005) Loss 0.1104 (0.1256) Prec@1 83.000 (77.889) Prec@5 97.000 (98.333) +2022-11-14 13:24:26,670 Epoch: [36][90/500] Time 0.037 (0.029) Data 0.002 (0.004) Loss 0.1409 (0.1271) Prec@1 73.000 (77.400) Prec@5 99.000 (98.400) +2022-11-14 13:24:27,150 Epoch: [36][100/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.1229 (0.1268) Prec@1 74.000 (77.091) Prec@5 100.000 (98.545) +2022-11-14 13:24:27,574 Epoch: [36][110/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.1372 (0.1276) Prec@1 73.000 (76.750) Prec@5 99.000 (98.583) +2022-11-14 13:24:27,999 Epoch: [36][120/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.1462 (0.1291) Prec@1 72.000 (76.385) Prec@5 99.000 (98.615) +2022-11-14 13:24:28,408 Epoch: [36][130/500] Time 0.034 (0.032) Data 0.002 (0.004) Loss 0.1439 (0.1301) Prec@1 74.000 (76.214) Prec@5 99.000 (98.643) +2022-11-14 13:24:28,820 Epoch: [36][140/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.1328 (0.1303) Prec@1 73.000 (76.000) Prec@5 99.000 (98.667) +2022-11-14 13:24:29,239 Epoch: [36][150/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1096 (0.1290) Prec@1 83.000 (76.438) Prec@5 98.000 (98.625) +2022-11-14 13:24:29,655 Epoch: [36][160/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.1634 (0.1310) Prec@1 72.000 (76.176) Prec@5 100.000 (98.706) +2022-11-14 13:24:30,063 Epoch: [36][170/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.1156 (0.1302) Prec@1 77.000 (76.222) Prec@5 99.000 (98.722) +2022-11-14 13:24:30,478 Epoch: [36][180/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.1353 (0.1304) Prec@1 78.000 (76.316) Prec@5 99.000 (98.737) +2022-11-14 13:24:30,889 Epoch: [36][190/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0946 (0.1286) Prec@1 85.000 (76.750) Prec@5 100.000 (98.800) +2022-11-14 13:24:31,303 Epoch: [36][200/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1553 (0.1299) Prec@1 71.000 (76.476) Prec@5 99.000 (98.810) +2022-11-14 13:24:31,709 Epoch: [36][210/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1018 (0.1286) Prec@1 83.000 (76.773) Prec@5 98.000 (98.773) +2022-11-14 13:24:32,122 Epoch: [36][220/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.1117 (0.1279) Prec@1 82.000 (77.000) Prec@5 97.000 (98.696) +2022-11-14 13:24:32,529 Epoch: [36][230/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0998 (0.1267) Prec@1 82.000 (77.208) Prec@5 99.000 (98.708) +2022-11-14 13:24:32,941 Epoch: [36][240/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.1187 (0.1264) Prec@1 78.000 (77.240) Prec@5 94.000 (98.520) +2022-11-14 13:24:33,359 Epoch: [36][250/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1554 (0.1275) Prec@1 74.000 (77.115) Prec@5 100.000 (98.577) +2022-11-14 13:24:33,796 Epoch: [36][260/500] Time 0.042 (0.034) Data 0.001 (0.003) Loss 0.1415 (0.1280) Prec@1 76.000 (77.074) Prec@5 99.000 (98.593) +2022-11-14 13:24:34,236 Epoch: [36][270/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1597 (0.1292) Prec@1 67.000 (76.714) Prec@5 98.000 (98.571) +2022-11-14 13:24:34,653 Epoch: [36][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1155 (0.1287) Prec@1 79.000 (76.793) Prec@5 99.000 (98.586) +2022-11-14 13:24:35,073 Epoch: [36][290/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1692 (0.1301) Prec@1 71.000 (76.600) Prec@5 97.000 (98.533) +2022-11-14 13:24:35,488 Epoch: [36][300/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.1337 (0.1302) Prec@1 77.000 (76.613) Prec@5 98.000 (98.516) +2022-11-14 13:24:35,903 Epoch: [36][310/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.1288 (0.1301) Prec@1 77.000 (76.625) Prec@5 97.000 (98.469) +2022-11-14 13:24:36,328 Epoch: [36][320/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.1048 (0.1294) Prec@1 81.000 (76.758) Prec@5 99.000 (98.485) +2022-11-14 13:24:36,741 Epoch: [36][330/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1291 (0.1294) Prec@1 77.000 (76.765) Prec@5 99.000 (98.500) +2022-11-14 13:24:37,186 Epoch: [36][340/500] Time 0.066 (0.035) Data 0.002 (0.003) Loss 0.1341 (0.1295) Prec@1 79.000 (76.829) Prec@5 98.000 (98.486) +2022-11-14 13:24:37,591 Epoch: [36][350/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.1296 (0.1295) Prec@1 76.000 (76.806) Prec@5 98.000 (98.472) +2022-11-14 13:24:38,012 Epoch: [36][360/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1086 (0.1289) Prec@1 83.000 (76.973) Prec@5 100.000 (98.514) +2022-11-14 13:24:38,428 Epoch: [36][370/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.1274 (0.1289) Prec@1 77.000 (76.974) Prec@5 98.000 (98.500) +2022-11-14 13:24:38,896 Epoch: [36][380/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.1331 (0.1290) Prec@1 76.000 (76.949) Prec@5 96.000 (98.436) +2022-11-14 13:24:39,296 Epoch: [36][390/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.1223 (0.1288) Prec@1 78.000 (76.975) Prec@5 99.000 (98.450) +2022-11-14 13:24:39,710 Epoch: [36][400/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.1369 (0.1290) Prec@1 74.000 (76.902) Prec@5 97.000 (98.415) +2022-11-14 13:24:40,122 Epoch: [36][410/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.1788 (0.1302) Prec@1 69.000 (76.714) Prec@5 94.000 (98.310) +2022-11-14 13:24:40,583 Epoch: [36][420/500] Time 0.051 (0.036) Data 0.002 (0.002) Loss 0.1719 (0.1312) Prec@1 70.000 (76.558) Prec@5 99.000 (98.326) +2022-11-14 13:24:41,035 Epoch: [36][430/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1539 (0.1317) Prec@1 75.000 (76.523) Prec@5 99.000 (98.341) +2022-11-14 13:24:41,423 Epoch: [36][440/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.1540 (0.1322) Prec@1 75.000 (76.489) Prec@5 96.000 (98.289) +2022-11-14 13:24:41,820 Epoch: [36][450/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.1563 (0.1327) Prec@1 72.000 (76.391) Prec@5 96.000 (98.239) +2022-11-14 13:24:42,227 Epoch: [36][460/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1373 (0.1328) Prec@1 74.000 (76.340) Prec@5 98.000 (98.234) +2022-11-14 13:24:42,640 Epoch: [36][470/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.1328 (0.1328) Prec@1 76.000 (76.333) Prec@5 95.000 (98.167) +2022-11-14 13:24:43,048 Epoch: [36][480/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1269 (0.1327) Prec@1 76.000 (76.327) Prec@5 97.000 (98.143) +2022-11-14 13:24:43,484 Epoch: [36][490/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.1158 (0.1324) Prec@1 79.000 (76.380) Prec@5 99.000 (98.160) +2022-11-14 13:24:43,930 Epoch: [36][499/500] Time 0.060 (0.036) Data 0.002 (0.002) Loss 0.1429 (0.1326) Prec@1 74.000 (76.333) Prec@5 100.000 (98.196) +2022-11-14 13:24:44,221 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1368 (0.1368) Prec@1 76.000 (76.000) Prec@5 99.000 (99.000) +2022-11-14 13:24:44,234 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1654 (0.1511) Prec@1 73.000 (74.500) Prec@5 99.000 (99.000) +2022-11-14 13:24:44,248 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1495 (0.1505) Prec@1 73.000 (74.000) Prec@5 98.000 (98.667) +2022-11-14 13:24:44,259 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1436 (0.1488) Prec@1 74.000 (74.000) Prec@5 97.000 (98.250) +2022-11-14 13:24:44,272 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1783 (0.1547) Prec@1 70.000 (73.200) Prec@5 97.000 (98.000) +2022-11-14 13:24:44,283 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1289 (0.1504) Prec@1 77.000 (73.833) Prec@5 97.000 (97.833) +2022-11-14 13:24:44,294 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1503 (0.1504) Prec@1 69.000 (73.143) Prec@5 98.000 (97.857) +2022-11-14 13:24:44,306 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1687 (0.1527) Prec@1 70.000 (72.750) Prec@5 95.000 (97.500) +2022-11-14 13:24:44,317 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1861 (0.1564) Prec@1 67.000 (72.111) Prec@5 96.000 (97.333) +2022-11-14 13:24:44,328 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1357 (0.1543) Prec@1 75.000 (72.400) Prec@5 98.000 (97.400) +2022-11-14 13:24:44,339 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1148 (0.1507) Prec@1 78.000 (72.909) Prec@5 99.000 (97.545) +2022-11-14 13:24:44,350 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1425 (0.1500) Prec@1 78.000 (73.333) Prec@5 94.000 (97.250) +2022-11-14 13:24:44,360 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1749 (0.1519) Prec@1 67.000 (72.846) Prec@5 96.000 (97.154) +2022-11-14 13:24:44,371 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1458 (0.1515) Prec@1 71.000 (72.714) Prec@5 97.000 (97.143) +2022-11-14 13:24:44,381 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1610 (0.1521) Prec@1 74.000 (72.800) Prec@5 95.000 (97.000) +2022-11-14 13:24:44,392 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1608 (0.1527) Prec@1 71.000 (72.688) Prec@5 97.000 (97.000) +2022-11-14 13:24:44,402 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1588 (0.1530) Prec@1 74.000 (72.765) Prec@5 98.000 (97.059) +2022-11-14 13:24:44,413 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1362 (0.1521) Prec@1 76.000 (72.944) Prec@5 96.000 (97.000) +2022-11-14 13:24:44,423 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1624 (0.1526) Prec@1 69.000 (72.737) Prec@5 95.000 (96.895) +2022-11-14 13:24:44,434 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1655 (0.1533) Prec@1 68.000 (72.500) Prec@5 95.000 (96.800) +2022-11-14 13:24:44,443 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1629 (0.1538) Prec@1 71.000 (72.429) Prec@5 97.000 (96.810) +2022-11-14 13:24:44,451 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1451 (0.1534) Prec@1 73.000 (72.455) Prec@5 100.000 (96.955) +2022-11-14 13:24:44,459 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1756 (0.1543) Prec@1 69.000 (72.304) Prec@5 98.000 (97.000) +2022-11-14 13:24:44,467 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1466 (0.1540) Prec@1 70.000 (72.208) Prec@5 97.000 (97.000) +2022-11-14 13:24:44,478 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1653 (0.1545) Prec@1 73.000 (72.240) Prec@5 98.000 (97.040) +2022-11-14 13:24:44,489 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1983 (0.1561) Prec@1 66.000 (72.000) Prec@5 94.000 (96.923) +2022-11-14 13:24:44,501 Test: [26/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1795 (0.1570) Prec@1 66.000 (71.778) Prec@5 97.000 (96.926) +2022-11-14 13:24:44,512 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1541 (0.1569) Prec@1 70.000 (71.714) Prec@5 95.000 (96.857) +2022-11-14 13:24:44,524 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1579 (0.1569) Prec@1 70.000 (71.655) Prec@5 95.000 (96.793) +2022-11-14 13:24:44,534 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1666 (0.1573) Prec@1 71.000 (71.633) Prec@5 97.000 (96.800) +2022-11-14 13:24:44,544 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1653 (0.1575) Prec@1 73.000 (71.677) Prec@5 95.000 (96.742) +2022-11-14 13:24:44,553 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1507 (0.1573) Prec@1 70.000 (71.625) Prec@5 97.000 (96.750) +2022-11-14 13:24:44,563 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1568) Prec@1 77.000 (71.788) Prec@5 93.000 (96.636) +2022-11-14 13:24:44,574 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1799 (0.1575) Prec@1 66.000 (71.618) Prec@5 98.000 (96.676) +2022-11-14 13:24:44,584 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1707 (0.1579) Prec@1 69.000 (71.543) Prec@5 96.000 (96.657) +2022-11-14 13:24:44,594 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1650 (0.1581) Prec@1 73.000 (71.583) Prec@5 98.000 (96.694) +2022-11-14 13:24:44,606 Test: [36/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1482 (0.1578) Prec@1 76.000 (71.703) Prec@5 95.000 (96.649) +2022-11-14 13:24:44,617 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1623 (0.1579) Prec@1 75.000 (71.789) Prec@5 93.000 (96.553) +2022-11-14 13:24:44,627 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1385 (0.1574) Prec@1 74.000 (71.846) Prec@5 98.000 (96.590) +2022-11-14 13:24:44,637 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1733 (0.1578) Prec@1 64.000 (71.650) Prec@5 97.000 (96.600) +2022-11-14 13:24:44,648 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1734 (0.1582) Prec@1 69.000 (71.585) Prec@5 96.000 (96.585) +2022-11-14 13:24:44,658 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1543 (0.1581) Prec@1 75.000 (71.667) Prec@5 91.000 (96.452) +2022-11-14 13:24:44,667 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.1576) Prec@1 76.000 (71.767) Prec@5 98.000 (96.488) +2022-11-14 13:24:44,678 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1572) Prec@1 76.000 (71.864) Prec@5 95.000 (96.455) +2022-11-14 13:24:44,689 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1337 (0.1567) Prec@1 76.000 (71.956) Prec@5 98.000 (96.489) +2022-11-14 13:24:44,699 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1789 (0.1572) Prec@1 63.000 (71.761) Prec@5 97.000 (96.500) +2022-11-14 13:24:44,711 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1660 (0.1573) Prec@1 70.000 (71.723) Prec@5 98.000 (96.532) +2022-11-14 13:24:44,722 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1536 (0.1573) Prec@1 70.000 (71.688) Prec@5 97.000 (96.542) +2022-11-14 13:24:44,731 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1570) Prec@1 73.000 (71.714) Prec@5 97.000 (96.551) +2022-11-14 13:24:44,740 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1900 (0.1576) Prec@1 63.000 (71.540) Prec@5 98.000 (96.580) +2022-11-14 13:24:44,751 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1573) Prec@1 73.000 (71.569) Prec@5 99.000 (96.627) +2022-11-14 13:24:44,761 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1838 (0.1578) Prec@1 69.000 (71.519) Prec@5 92.000 (96.538) +2022-11-14 13:24:44,769 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1520 (0.1577) Prec@1 71.000 (71.509) Prec@5 96.000 (96.528) +2022-11-14 13:24:44,777 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1349 (0.1573) Prec@1 80.000 (71.667) Prec@5 96.000 (96.519) +2022-11-14 13:24:44,785 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1788 (0.1577) Prec@1 71.000 (71.655) Prec@5 98.000 (96.545) +2022-11-14 13:24:44,794 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1574 (0.1577) Prec@1 70.000 (71.625) Prec@5 97.000 (96.554) +2022-11-14 13:24:44,804 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1585 (0.1577) Prec@1 72.000 (71.632) Prec@5 95.000 (96.526) +2022-11-14 13:24:44,815 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1429 (0.1574) Prec@1 77.000 (71.724) Prec@5 97.000 (96.534) +2022-11-14 13:24:44,826 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1952 (0.1581) Prec@1 65.000 (71.610) Prec@5 98.000 (96.559) +2022-11-14 13:24:44,836 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1582) Prec@1 73.000 (71.633) Prec@5 96.000 (96.550) +2022-11-14 13:24:44,847 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1725 (0.1584) Prec@1 71.000 (71.623) Prec@5 96.000 (96.541) +2022-11-14 13:24:44,858 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1621 (0.1585) Prec@1 71.000 (71.613) Prec@5 97.000 (96.548) +2022-11-14 13:24:44,869 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1350 (0.1581) Prec@1 78.000 (71.714) Prec@5 99.000 (96.587) +2022-11-14 13:24:44,879 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1415 (0.1579) Prec@1 77.000 (71.797) Prec@5 96.000 (96.578) +2022-11-14 13:24:44,890 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1849 (0.1583) Prec@1 65.000 (71.692) Prec@5 94.000 (96.538) +2022-11-14 13:24:44,900 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1527 (0.1582) Prec@1 70.000 (71.667) Prec@5 97.000 (96.545) +2022-11-14 13:24:44,912 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1579) Prec@1 74.000 (71.701) Prec@5 97.000 (96.552) +2022-11-14 13:24:44,923 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1412 (0.1577) Prec@1 73.000 (71.721) Prec@5 99.000 (96.588) +2022-11-14 13:24:44,933 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1424 (0.1575) Prec@1 74.000 (71.754) Prec@5 99.000 (96.623) +2022-11-14 13:24:44,944 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1699 (0.1577) Prec@1 70.000 (71.729) Prec@5 96.000 (96.614) +2022-11-14 13:24:44,955 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1736 (0.1579) Prec@1 69.000 (71.690) Prec@5 95.000 (96.592) +2022-11-14 13:24:44,965 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1797 (0.1582) Prec@1 66.000 (71.611) Prec@5 98.000 (96.611) +2022-11-14 13:24:44,976 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1451 (0.1580) Prec@1 73.000 (71.630) Prec@5 98.000 (96.630) +2022-11-14 13:24:44,987 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1512 (0.1579) Prec@1 71.000 (71.622) Prec@5 98.000 (96.649) +2022-11-14 13:24:44,998 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1919 (0.1584) Prec@1 65.000 (71.533) Prec@5 95.000 (96.627) +2022-11-14 13:24:45,009 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1400 (0.1581) Prec@1 74.000 (71.566) Prec@5 98.000 (96.645) +2022-11-14 13:24:45,019 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1700 (0.1583) Prec@1 68.000 (71.519) Prec@5 97.000 (96.649) +2022-11-14 13:24:45,031 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1462 (0.1581) Prec@1 73.000 (71.538) Prec@5 97.000 (96.654) +2022-11-14 13:24:45,042 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1468 (0.1580) Prec@1 73.000 (71.557) Prec@5 97.000 (96.658) +2022-11-14 13:24:45,052 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1648 (0.1581) Prec@1 74.000 (71.588) Prec@5 93.000 (96.612) +2022-11-14 13:24:45,063 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1913 (0.1585) Prec@1 61.000 (71.457) Prec@5 93.000 (96.568) +2022-11-14 13:24:45,073 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1371 (0.1582) Prec@1 76.000 (71.512) Prec@5 97.000 (96.573) +2022-11-14 13:24:45,083 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1580) Prec@1 74.000 (71.542) Prec@5 98.000 (96.590) +2022-11-14 13:24:45,092 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1748 (0.1582) Prec@1 68.000 (71.500) Prec@5 98.000 (96.607) +2022-11-14 13:24:45,100 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1664 (0.1583) Prec@1 68.000 (71.459) Prec@5 96.000 (96.600) +2022-11-14 13:24:45,108 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1581) Prec@1 77.000 (71.523) Prec@5 99.000 (96.628) +2022-11-14 13:24:45,119 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1667 (0.1582) Prec@1 69.000 (71.494) Prec@5 98.000 (96.644) +2022-11-14 13:24:45,129 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1544 (0.1582) Prec@1 73.000 (71.511) Prec@5 97.000 (96.648) +2022-11-14 13:24:45,140 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1483 (0.1581) Prec@1 71.000 (71.506) Prec@5 96.000 (96.640) +2022-11-14 13:24:45,151 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.1580) Prec@1 78.000 (71.578) Prec@5 97.000 (96.644) +2022-11-14 13:24:45,163 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1933 (0.1584) Prec@1 66.000 (71.516) Prec@5 97.000 (96.648) +2022-11-14 13:24:45,173 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.1578) Prec@1 80.000 (71.609) Prec@5 98.000 (96.663) +2022-11-14 13:24:45,183 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1591 (0.1579) Prec@1 69.000 (71.581) Prec@5 97.000 (96.667) +2022-11-14 13:24:45,194 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1618 (0.1579) Prec@1 72.000 (71.585) Prec@5 96.000 (96.660) +2022-11-14 13:24:45,204 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1603 (0.1579) Prec@1 73.000 (71.600) Prec@5 98.000 (96.674) +2022-11-14 13:24:45,215 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1577) Prec@1 75.000 (71.635) Prec@5 95.000 (96.656) +2022-11-14 13:24:45,226 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1574) Prec@1 77.000 (71.691) Prec@5 98.000 (96.670) +2022-11-14 13:24:45,237 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1882 (0.1577) Prec@1 66.000 (71.633) Prec@5 96.000 (96.663) +2022-11-14 13:24:45,247 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1559 (0.1577) Prec@1 72.000 (71.636) Prec@5 97.000 (96.667) +2022-11-14 13:24:45,258 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1520 (0.1576) Prec@1 72.000 (71.640) Prec@5 97.000 (96.670) +2022-11-14 13:24:45,314 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:24:45,642 Epoch: [37][0/500] Time 0.031 (0.031) Data 0.230 (0.230) Loss 0.1264 (0.1264) Prec@1 78.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:24:45,965 Epoch: [37][10/500] Time 0.033 (0.029) Data 0.002 (0.023) Loss 0.0913 (0.1089) Prec@1 89.000 (83.500) Prec@5 99.000 (98.500) +2022-11-14 13:24:46,232 Epoch: [37][20/500] Time 0.025 (0.027) Data 0.002 (0.013) Loss 0.1071 (0.1083) Prec@1 80.000 (82.333) Prec@5 97.000 (98.000) +2022-11-14 13:24:46,481 Epoch: [37][30/500] Time 0.021 (0.025) Data 0.002 (0.009) Loss 0.1505 (0.1188) Prec@1 73.000 (80.000) Prec@5 99.000 (98.250) +2022-11-14 13:24:46,728 Epoch: [37][40/500] Time 0.022 (0.024) Data 0.002 (0.008) Loss 0.1059 (0.1162) Prec@1 82.000 (80.400) Prec@5 97.000 (98.000) +2022-11-14 13:24:47,026 Epoch: [37][50/500] Time 0.026 (0.025) Data 0.002 (0.007) Loss 0.1174 (0.1164) Prec@1 80.000 (80.333) Prec@5 99.000 (98.167) +2022-11-14 13:24:47,328 Epoch: [37][60/500] Time 0.031 (0.025) Data 0.002 (0.006) Loss 0.1361 (0.1192) Prec@1 78.000 (80.000) Prec@5 100.000 (98.429) +2022-11-14 13:24:47,621 Epoch: [37][70/500] Time 0.027 (0.025) Data 0.002 (0.005) Loss 0.1213 (0.1195) Prec@1 77.000 (79.625) Prec@5 96.000 (98.125) +2022-11-14 13:24:47,969 Epoch: [37][80/500] Time 0.042 (0.026) Data 0.002 (0.005) Loss 0.1168 (0.1192) Prec@1 80.000 (79.667) Prec@5 98.000 (98.111) +2022-11-14 13:24:48,336 Epoch: [37][90/500] Time 0.032 (0.027) Data 0.003 (0.005) Loss 0.1211 (0.1194) Prec@1 81.000 (79.800) Prec@5 100.000 (98.300) +2022-11-14 13:24:48,708 Epoch: [37][100/500] Time 0.040 (0.027) Data 0.002 (0.004) Loss 0.1230 (0.1197) Prec@1 80.000 (79.818) Prec@5 99.000 (98.364) +2022-11-14 13:24:49,087 Epoch: [37][110/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.1137 (0.1192) Prec@1 79.000 (79.750) Prec@5 96.000 (98.167) +2022-11-14 13:24:49,468 Epoch: [37][120/500] Time 0.032 (0.028) Data 0.002 (0.004) Loss 0.1131 (0.1187) Prec@1 80.000 (79.769) Prec@5 97.000 (98.077) +2022-11-14 13:24:49,907 Epoch: [37][130/500] Time 0.050 (0.029) Data 0.002 (0.004) Loss 0.1064 (0.1179) Prec@1 82.000 (79.929) Prec@5 98.000 (98.071) +2022-11-14 13:24:50,467 Epoch: [37][140/500] Time 0.071 (0.031) Data 0.002 (0.004) Loss 0.1434 (0.1196) Prec@1 75.000 (79.600) Prec@5 98.000 (98.067) +2022-11-14 13:24:51,053 Epoch: [37][150/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.1552 (0.1218) Prec@1 70.000 (79.000) Prec@5 96.000 (97.938) +2022-11-14 13:24:51,527 Epoch: [37][160/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1150 (0.1214) Prec@1 79.000 (79.000) Prec@5 99.000 (98.000) +2022-11-14 13:24:51,987 Epoch: [37][170/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1292 (0.1218) Prec@1 75.000 (78.778) Prec@5 99.000 (98.056) +2022-11-14 13:24:52,479 Epoch: [37][180/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.1317 (0.1223) Prec@1 75.000 (78.579) Prec@5 99.000 (98.105) +2022-11-14 13:24:52,949 Epoch: [37][190/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.1369 (0.1231) Prec@1 75.000 (78.400) Prec@5 94.000 (97.900) +2022-11-14 13:24:53,419 Epoch: [37][200/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.1319 (0.1235) Prec@1 77.000 (78.333) Prec@5 99.000 (97.952) +2022-11-14 13:24:53,889 Epoch: [37][210/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.1504 (0.1247) Prec@1 75.000 (78.182) Prec@5 94.000 (97.773) +2022-11-14 13:24:54,350 Epoch: [37][220/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.1466 (0.1257) Prec@1 75.000 (78.043) Prec@5 98.000 (97.783) +2022-11-14 13:24:54,811 Epoch: [37][230/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.1586 (0.1270) Prec@1 71.000 (77.750) Prec@5 94.000 (97.625) +2022-11-14 13:24:55,322 Epoch: [37][240/500] Time 0.042 (0.036) Data 0.003 (0.003) Loss 0.1565 (0.1282) Prec@1 70.000 (77.440) Prec@5 96.000 (97.560) +2022-11-14 13:24:55,853 Epoch: [37][250/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.1288 (0.1282) Prec@1 77.000 (77.423) Prec@5 97.000 (97.538) +2022-11-14 13:24:56,464 Epoch: [37][260/500] Time 0.074 (0.037) Data 0.002 (0.003) Loss 0.1592 (0.1294) Prec@1 74.000 (77.296) Prec@5 96.000 (97.481) +2022-11-14 13:24:57,001 Epoch: [37][270/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.1285 (0.1294) Prec@1 79.000 (77.357) Prec@5 98.000 (97.500) +2022-11-14 13:24:57,465 Epoch: [37][280/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1167 (0.1289) Prec@1 79.000 (77.414) Prec@5 98.000 (97.517) +2022-11-14 13:24:58,035 Epoch: [37][290/500] Time 0.069 (0.038) Data 0.002 (0.003) Loss 0.1345 (0.1291) Prec@1 78.000 (77.433) Prec@5 95.000 (97.433) +2022-11-14 13:24:58,624 Epoch: [37][300/500] Time 0.101 (0.039) Data 0.002 (0.003) Loss 0.1198 (0.1288) Prec@1 78.000 (77.452) Prec@5 99.000 (97.484) +2022-11-14 13:24:59,103 Epoch: [37][310/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.1131 (0.1283) Prec@1 78.000 (77.469) Prec@5 98.000 (97.500) +2022-11-14 13:24:59,571 Epoch: [37][320/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.1441 (0.1288) Prec@1 74.000 (77.364) Prec@5 100.000 (97.576) +2022-11-14 13:25:00,099 Epoch: [37][330/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.1115 (0.1283) Prec@1 80.000 (77.441) Prec@5 99.000 (97.618) +2022-11-14 13:25:00,376 Epoch: [37][340/500] Time 0.027 (0.039) Data 0.002 (0.003) Loss 0.1070 (0.1277) Prec@1 79.000 (77.486) Prec@5 98.000 (97.629) +2022-11-14 13:25:00,678 Epoch: [37][350/500] Time 0.024 (0.038) Data 0.002 (0.003) Loss 0.1528 (0.1284) Prec@1 72.000 (77.333) Prec@5 97.000 (97.611) +2022-11-14 13:25:00,972 Epoch: [37][360/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.1386 (0.1287) Prec@1 75.000 (77.270) Prec@5 97.000 (97.595) +2022-11-14 13:25:01,266 Epoch: [37][370/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.1440 (0.1291) Prec@1 74.000 (77.184) Prec@5 99.000 (97.632) +2022-11-14 13:25:01,562 Epoch: [37][380/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.1388 (0.1293) Prec@1 73.000 (77.077) Prec@5 98.000 (97.641) +2022-11-14 13:25:01,862 Epoch: [37][390/500] Time 0.028 (0.037) Data 0.002 (0.003) Loss 0.1483 (0.1298) Prec@1 70.000 (76.900) Prec@5 96.000 (97.600) +2022-11-14 13:25:02,163 Epoch: [37][400/500] Time 0.028 (0.037) Data 0.002 (0.003) Loss 0.1690 (0.1307) Prec@1 68.000 (76.683) Prec@5 95.000 (97.537) +2022-11-14 13:25:02,464 Epoch: [37][410/500] Time 0.028 (0.037) Data 0.002 (0.003) Loss 0.1354 (0.1308) Prec@1 75.000 (76.643) Prec@5 100.000 (97.595) +2022-11-14 13:25:02,762 Epoch: [37][420/500] Time 0.029 (0.036) Data 0.002 (0.003) Loss 0.1511 (0.1313) Prec@1 76.000 (76.628) Prec@5 99.000 (97.628) +2022-11-14 13:25:03,062 Epoch: [37][430/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.1237 (0.1311) Prec@1 76.000 (76.614) Prec@5 100.000 (97.682) +2022-11-14 13:25:03,358 Epoch: [37][440/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.1399 (0.1313) Prec@1 75.000 (76.578) Prec@5 99.000 (97.711) +2022-11-14 13:25:03,660 Epoch: [37][450/500] Time 0.028 (0.036) Data 0.003 (0.002) Loss 0.1442 (0.1316) Prec@1 72.000 (76.478) Prec@5 98.000 (97.717) +2022-11-14 13:25:03,961 Epoch: [37][460/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.1442 (0.1319) Prec@1 78.000 (76.511) Prec@5 97.000 (97.702) +2022-11-14 13:25:04,260 Epoch: [37][470/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.1123 (0.1315) Prec@1 82.000 (76.625) Prec@5 97.000 (97.688) +2022-11-14 13:25:04,566 Epoch: [37][480/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.1228 (0.1313) Prec@1 74.000 (76.571) Prec@5 99.000 (97.714) +2022-11-14 13:25:04,865 Epoch: [37][490/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.1079 (0.1308) Prec@1 80.000 (76.640) Prec@5 97.000 (97.700) +2022-11-14 13:25:05,135 Epoch: [37][499/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.1554 (0.1313) Prec@1 68.000 (76.471) Prec@5 100.000 (97.745) +2022-11-14 13:25:05,439 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1844 (0.1844) Prec@1 72.000 (72.000) Prec@5 97.000 (97.000) +2022-11-14 13:25:05,450 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2436 (0.2140) Prec@1 58.000 (65.000) Prec@5 94.000 (95.500) +2022-11-14 13:25:05,461 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2088 (0.2123) Prec@1 61.000 (63.667) Prec@5 92.000 (94.333) +2022-11-14 13:25:05,473 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1887 (0.2064) Prec@1 65.000 (64.000) Prec@5 96.000 (94.750) +2022-11-14 13:25:05,482 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2733 (0.2198) Prec@1 50.000 (61.200) Prec@5 95.000 (94.800) +2022-11-14 13:25:05,491 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1817 (0.2134) Prec@1 65.000 (61.833) Prec@5 97.000 (95.167) +2022-11-14 13:25:05,502 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2203 (0.2144) Prec@1 61.000 (61.714) Prec@5 96.000 (95.286) +2022-11-14 13:25:05,514 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1988 (0.2124) Prec@1 64.000 (62.000) Prec@5 96.000 (95.375) +2022-11-14 13:25:05,522 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2423 (0.2158) Prec@1 55.000 (61.222) Prec@5 91.000 (94.889) +2022-11-14 13:25:05,530 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1747 (0.2116) Prec@1 70.000 (62.100) Prec@5 95.000 (94.900) +2022-11-14 13:25:05,542 Test: [10/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1636 (0.2073) Prec@1 71.000 (62.909) Prec@5 94.000 (94.818) +2022-11-14 13:25:05,553 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2069 (0.2072) Prec@1 62.000 (62.833) Prec@5 95.000 (94.833) +2022-11-14 13:25:05,562 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1980 (0.2065) Prec@1 65.000 (63.000) Prec@5 94.000 (94.769) +2022-11-14 13:25:05,572 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1903 (0.2054) Prec@1 68.000 (63.357) Prec@5 95.000 (94.786) +2022-11-14 13:25:05,585 Test: [14/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.2097 (0.2057) Prec@1 63.000 (63.333) Prec@5 96.000 (94.867) +2022-11-14 13:25:05,596 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2227 (0.2067) Prec@1 65.000 (63.438) Prec@5 98.000 (95.062) +2022-11-14 13:25:05,607 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1503 (0.2034) Prec@1 75.000 (64.118) Prec@5 96.000 (95.118) +2022-11-14 13:25:05,621 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1936 (0.2029) Prec@1 69.000 (64.389) Prec@5 93.000 (95.000) +2022-11-14 13:25:05,636 Test: [18/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1776 (0.2015) Prec@1 70.000 (64.684) Prec@5 93.000 (94.895) +2022-11-14 13:25:05,652 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2018 (0.2015) Prec@1 64.000 (64.650) Prec@5 90.000 (94.650) +2022-11-14 13:25:05,664 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2089 (0.2019) Prec@1 64.000 (64.619) Prec@5 97.000 (94.762) +2022-11-14 13:25:05,677 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2151 (0.2025) Prec@1 66.000 (64.682) Prec@5 94.000 (94.727) +2022-11-14 13:25:05,691 Test: [22/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.2339 (0.2039) Prec@1 62.000 (64.565) Prec@5 96.000 (94.783) +2022-11-14 13:25:05,705 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1677 (0.2024) Prec@1 70.000 (64.792) Prec@5 96.000 (94.833) +2022-11-14 13:25:05,718 Test: [24/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1929 (0.2020) Prec@1 72.000 (65.080) Prec@5 95.000 (94.840) +2022-11-14 13:25:05,731 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2793 (0.2050) Prec@1 47.000 (64.385) Prec@5 92.000 (94.731) +2022-11-14 13:25:05,745 Test: [26/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.2122 (0.2052) Prec@1 62.000 (64.296) Prec@5 98.000 (94.852) +2022-11-14 13:25:05,760 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2461 (0.2067) Prec@1 57.000 (64.036) Prec@5 95.000 (94.857) +2022-11-14 13:25:05,773 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2069 (0.2067) Prec@1 64.000 (64.034) Prec@5 95.000 (94.862) +2022-11-14 13:25:05,787 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1931 (0.2062) Prec@1 66.000 (64.100) Prec@5 94.000 (94.833) +2022-11-14 13:25:05,800 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2275 (0.2069) Prec@1 60.000 (63.968) Prec@5 97.000 (94.903) +2022-11-14 13:25:05,812 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1864 (0.2063) Prec@1 65.000 (64.000) Prec@5 95.000 (94.906) +2022-11-14 13:25:05,823 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2141 (0.2065) Prec@1 63.000 (63.970) Prec@5 90.000 (94.758) +2022-11-14 13:25:05,835 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2320 (0.2073) Prec@1 58.000 (63.794) Prec@5 90.000 (94.618) +2022-11-14 13:25:05,848 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2359 (0.2081) Prec@1 61.000 (63.714) Prec@5 94.000 (94.600) +2022-11-14 13:25:05,860 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2064 (0.2080) Prec@1 66.000 (63.778) Prec@5 95.000 (94.611) +2022-11-14 13:25:05,872 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1908 (0.2076) Prec@1 66.000 (63.838) Prec@5 97.000 (94.676) +2022-11-14 13:25:05,884 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1850 (0.2070) Prec@1 66.000 (63.895) Prec@5 97.000 (94.737) +2022-11-14 13:25:05,896 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2121 (0.2071) Prec@1 61.000 (63.821) Prec@5 94.000 (94.718) +2022-11-14 13:25:05,908 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2140 (0.2073) Prec@1 63.000 (63.800) Prec@5 97.000 (94.775) +2022-11-14 13:25:05,920 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2121 (0.2074) Prec@1 66.000 (63.854) Prec@5 95.000 (94.780) +2022-11-14 13:25:05,932 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2041 (0.2073) Prec@1 66.000 (63.905) Prec@5 95.000 (94.786) +2022-11-14 13:25:05,944 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1541 (0.2061) Prec@1 73.000 (64.116) Prec@5 98.000 (94.860) +2022-11-14 13:25:05,955 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1878 (0.2057) Prec@1 70.000 (64.250) Prec@5 92.000 (94.795) +2022-11-14 13:25:05,968 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2074 (0.2057) Prec@1 63.000 (64.222) Prec@5 96.000 (94.822) +2022-11-14 13:25:05,982 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2250 (0.2061) Prec@1 60.000 (64.130) Prec@5 94.000 (94.804) +2022-11-14 13:25:05,994 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1908 (0.2058) Prec@1 63.000 (64.106) Prec@5 95.000 (94.809) +2022-11-14 13:25:06,007 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1648 (0.2049) Prec@1 71.000 (64.250) Prec@5 97.000 (94.854) +2022-11-14 13:25:06,017 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1883 (0.2046) Prec@1 65.000 (64.265) Prec@5 96.000 (94.878) +2022-11-14 13:25:06,028 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2490 (0.2055) Prec@1 56.000 (64.100) Prec@5 94.000 (94.860) +2022-11-14 13:25:06,037 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1912 (0.2052) Prec@1 66.000 (64.137) Prec@5 92.000 (94.804) +2022-11-14 13:25:06,047 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2215 (0.2055) Prec@1 57.000 (64.000) Prec@5 94.000 (94.788) +2022-11-14 13:25:06,057 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1940 (0.2053) Prec@1 66.000 (64.038) Prec@5 92.000 (94.736) +2022-11-14 13:25:06,066 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1959 (0.2051) Prec@1 65.000 (64.056) Prec@5 92.000 (94.685) +2022-11-14 13:25:06,075 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1892 (0.2048) Prec@1 64.000 (64.055) Prec@5 96.000 (94.709) +2022-11-14 13:25:06,085 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1948 (0.2047) Prec@1 68.000 (64.125) Prec@5 94.000 (94.696) +2022-11-14 13:25:06,094 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2108 (0.2048) Prec@1 64.000 (64.123) Prec@5 93.000 (94.667) +2022-11-14 13:25:06,104 Test: [57/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1755 (0.2043) Prec@1 69.000 (64.207) Prec@5 99.000 (94.741) +2022-11-14 13:25:06,113 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2172 (0.2045) Prec@1 63.000 (64.186) Prec@5 95.000 (94.746) +2022-11-14 13:25:06,122 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2233 (0.2048) Prec@1 63.000 (64.167) Prec@5 94.000 (94.733) +2022-11-14 13:25:06,132 Test: [60/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2327 (0.2053) Prec@1 59.000 (64.082) Prec@5 95.000 (94.738) +2022-11-14 13:25:06,140 Test: [61/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2480 (0.2060) Prec@1 53.000 (63.903) Prec@5 94.000 (94.726) +2022-11-14 13:25:06,149 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1986 (0.2058) Prec@1 65.000 (63.921) Prec@5 98.000 (94.778) +2022-11-14 13:25:06,157 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2137 (0.2060) Prec@1 61.000 (63.875) Prec@5 96.000 (94.797) +2022-11-14 13:25:06,166 Test: [64/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2523 (0.2067) Prec@1 51.000 (63.677) Prec@5 94.000 (94.785) +2022-11-14 13:25:06,175 Test: [65/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1794 (0.2063) Prec@1 69.000 (63.758) Prec@5 98.000 (94.833) +2022-11-14 13:25:06,183 Test: [66/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1822 (0.2059) Prec@1 65.000 (63.776) Prec@5 95.000 (94.836) +2022-11-14 13:25:06,193 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2129 (0.2060) Prec@1 68.000 (63.838) Prec@5 95.000 (94.838) +2022-11-14 13:25:06,201 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1784 (0.2056) Prec@1 69.000 (63.913) Prec@5 97.000 (94.870) +2022-11-14 13:25:06,210 Test: [69/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2376 (0.2061) Prec@1 55.000 (63.786) Prec@5 89.000 (94.786) +2022-11-14 13:25:06,220 Test: [70/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1850 (0.2058) Prec@1 68.000 (63.845) Prec@5 95.000 (94.789) +2022-11-14 13:25:06,229 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1557 (0.2051) Prec@1 74.000 (63.986) Prec@5 97.000 (94.819) +2022-11-14 13:25:06,237 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1788 (0.2047) Prec@1 68.000 (64.041) Prec@5 95.000 (94.822) +2022-11-14 13:25:06,249 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2014 (0.2047) Prec@1 62.000 (64.014) Prec@5 97.000 (94.851) +2022-11-14 13:25:06,258 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2416 (0.2052) Prec@1 60.000 (63.960) Prec@5 93.000 (94.827) +2022-11-14 13:25:06,271 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1890 (0.2049) Prec@1 69.000 (64.026) Prec@5 98.000 (94.868) +2022-11-14 13:25:06,283 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2319 (0.2053) Prec@1 57.000 (63.935) Prec@5 93.000 (94.844) +2022-11-14 13:25:06,294 Test: [77/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2171 (0.2054) Prec@1 63.000 (63.923) Prec@5 94.000 (94.833) +2022-11-14 13:25:06,310 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1850 (0.2052) Prec@1 69.000 (63.987) Prec@5 98.000 (94.873) +2022-11-14 13:25:06,326 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1944 (0.2050) Prec@1 69.000 (64.050) Prec@5 93.000 (94.850) +2022-11-14 13:25:06,340 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2077 (0.2051) Prec@1 65.000 (64.062) Prec@5 94.000 (94.840) +2022-11-14 13:25:06,355 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1797 (0.2048) Prec@1 74.000 (64.183) Prec@5 92.000 (94.805) +2022-11-14 13:25:06,370 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2119 (0.2049) Prec@1 59.000 (64.120) Prec@5 95.000 (94.807) +2022-11-14 13:25:06,387 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2287 (0.2051) Prec@1 61.000 (64.083) Prec@5 95.000 (94.810) +2022-11-14 13:25:06,405 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2290 (0.2054) Prec@1 63.000 (64.071) Prec@5 91.000 (94.765) +2022-11-14 13:25:06,420 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2007 (0.2054) Prec@1 64.000 (64.070) Prec@5 94.000 (94.756) +2022-11-14 13:25:06,436 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2159 (0.2055) Prec@1 62.000 (64.046) Prec@5 95.000 (94.759) +2022-11-14 13:25:06,451 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1791 (0.2052) Prec@1 68.000 (64.091) Prec@5 95.000 (94.761) +2022-11-14 13:25:06,466 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2129 (0.2053) Prec@1 61.000 (64.056) Prec@5 92.000 (94.730) +2022-11-14 13:25:06,483 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1862 (0.2051) Prec@1 67.000 (64.089) Prec@5 94.000 (94.722) +2022-11-14 13:25:06,500 Test: [90/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2010 (0.2050) Prec@1 65.000 (64.099) Prec@5 98.000 (94.758) +2022-11-14 13:25:06,515 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1725 (0.2047) Prec@1 66.000 (64.120) Prec@5 94.000 (94.750) +2022-11-14 13:25:06,529 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2234 (0.2049) Prec@1 56.000 (64.032) Prec@5 96.000 (94.763) +2022-11-14 13:25:06,544 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2024 (0.2048) Prec@1 66.000 (64.053) Prec@5 94.000 (94.755) +2022-11-14 13:25:06,559 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2010 (0.2048) Prec@1 68.000 (64.095) Prec@5 95.000 (94.758) +2022-11-14 13:25:06,576 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1869 (0.2046) Prec@1 66.000 (64.115) Prec@5 97.000 (94.781) +2022-11-14 13:25:06,592 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1487 (0.2040) Prec@1 73.000 (64.206) Prec@5 97.000 (94.804) +2022-11-14 13:25:06,608 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2666 (0.2047) Prec@1 55.000 (64.112) Prec@5 91.000 (94.765) +2022-11-14 13:25:06,625 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2064 (0.2047) Prec@1 61.000 (64.081) Prec@5 95.000 (94.768) +2022-11-14 13:25:06,640 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1920 (0.2046) Prec@1 66.000 (64.100) Prec@5 92.000 (94.740) +2022-11-14 13:25:06,696 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:25:07,009 Epoch: [38][0/500] Time 0.023 (0.023) Data 0.230 (0.230) Loss 0.1448 (0.1448) Prec@1 77.000 (77.000) Prec@5 98.000 (98.000) +2022-11-14 13:25:07,259 Epoch: [38][10/500] Time 0.032 (0.022) Data 0.002 (0.022) Loss 0.1568 (0.1508) Prec@1 75.000 (76.000) Prec@5 95.000 (96.500) +2022-11-14 13:25:07,526 Epoch: [38][20/500] Time 0.025 (0.023) Data 0.002 (0.013) Loss 0.1113 (0.1376) Prec@1 81.000 (77.667) Prec@5 96.000 (96.333) +2022-11-14 13:25:07,800 Epoch: [38][30/500] Time 0.024 (0.023) Data 0.001 (0.009) Loss 0.1286 (0.1354) Prec@1 77.000 (77.500) Prec@5 99.000 (97.000) +2022-11-14 13:25:08,074 Epoch: [38][40/500] Time 0.026 (0.023) Data 0.002 (0.007) Loss 0.1450 (0.1373) Prec@1 76.000 (77.200) Prec@5 99.000 (97.400) +2022-11-14 13:25:08,387 Epoch: [38][50/500] Time 0.031 (0.024) Data 0.001 (0.006) Loss 0.1157 (0.1337) Prec@1 82.000 (78.000) Prec@5 98.000 (97.500) +2022-11-14 13:25:08,798 Epoch: [38][60/500] Time 0.036 (0.026) Data 0.002 (0.006) Loss 0.1161 (0.1312) Prec@1 80.000 (78.286) Prec@5 95.000 (97.143) +2022-11-14 13:25:09,313 Epoch: [38][70/500] Time 0.054 (0.029) Data 0.002 (0.005) Loss 0.1329 (0.1314) Prec@1 79.000 (78.375) Prec@5 99.000 (97.375) +2022-11-14 13:25:09,792 Epoch: [38][80/500] Time 0.055 (0.031) Data 0.002 (0.005) Loss 0.1428 (0.1327) Prec@1 75.000 (78.000) Prec@5 98.000 (97.444) +2022-11-14 13:25:10,181 Epoch: [38][90/500] Time 0.045 (0.031) Data 0.002 (0.004) Loss 0.1282 (0.1322) Prec@1 79.000 (78.100) Prec@5 100.000 (97.700) +2022-11-14 13:25:10,580 Epoch: [38][100/500] Time 0.035 (0.032) Data 0.003 (0.004) Loss 0.1214 (0.1312) Prec@1 78.000 (78.091) Prec@5 99.000 (97.818) +2022-11-14 13:25:11,007 Epoch: [38][110/500] Time 0.034 (0.032) Data 0.002 (0.004) Loss 0.1753 (0.1349) Prec@1 69.000 (77.333) Prec@5 100.000 (98.000) +2022-11-14 13:25:11,408 Epoch: [38][120/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.1225 (0.1340) Prec@1 78.000 (77.385) Prec@5 96.000 (97.846) +2022-11-14 13:25:11,810 Epoch: [38][130/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.1409 (0.1345) Prec@1 76.000 (77.286) Prec@5 96.000 (97.714) +2022-11-14 13:25:12,223 Epoch: [38][140/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1233 (0.1337) Prec@1 79.000 (77.400) Prec@5 98.000 (97.733) +2022-11-14 13:25:12,688 Epoch: [38][150/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.1028 (0.1318) Prec@1 82.000 (77.688) Prec@5 100.000 (97.875) +2022-11-14 13:25:13,156 Epoch: [38][160/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1198 (0.1311) Prec@1 80.000 (77.824) Prec@5 98.000 (97.882) +2022-11-14 13:25:13,565 Epoch: [38][170/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1161 (0.1302) Prec@1 81.000 (78.000) Prec@5 96.000 (97.778) +2022-11-14 13:25:13,990 Epoch: [38][180/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.1181 (0.1296) Prec@1 80.000 (78.105) Prec@5 97.000 (97.737) +2022-11-14 13:25:14,407 Epoch: [38][190/500] Time 0.029 (0.034) Data 0.002 (0.003) Loss 0.1245 (0.1294) Prec@1 76.000 (78.000) Prec@5 99.000 (97.800) +2022-11-14 13:25:14,800 Epoch: [38][200/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.1267 (0.1292) Prec@1 80.000 (78.095) Prec@5 99.000 (97.857) +2022-11-14 13:25:15,200 Epoch: [38][210/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1453 (0.1300) Prec@1 74.000 (77.909) Prec@5 96.000 (97.773) +2022-11-14 13:25:15,606 Epoch: [38][220/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1220 (0.1296) Prec@1 81.000 (78.043) Prec@5 98.000 (97.783) +2022-11-14 13:25:16,008 Epoch: [38][230/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1078 (0.1287) Prec@1 83.000 (78.250) Prec@5 99.000 (97.833) +2022-11-14 13:25:16,420 Epoch: [38][240/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1114 (0.1280) Prec@1 82.000 (78.400) Prec@5 98.000 (97.840) +2022-11-14 13:25:16,934 Epoch: [38][250/500] Time 0.061 (0.035) Data 0.002 (0.003) Loss 0.1098 (0.1273) Prec@1 77.000 (78.346) Prec@5 100.000 (97.923) +2022-11-14 13:25:17,309 Epoch: [38][260/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1282 (0.1273) Prec@1 76.000 (78.259) Prec@5 97.000 (97.889) +2022-11-14 13:25:17,708 Epoch: [38][270/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1536 (0.1283) Prec@1 75.000 (78.143) Prec@5 95.000 (97.786) +2022-11-14 13:25:18,130 Epoch: [38][280/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.1362 (0.1286) Prec@1 74.000 (78.000) Prec@5 97.000 (97.759) +2022-11-14 13:25:18,621 Epoch: [38][290/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.1310 (0.1286) Prec@1 78.000 (78.000) Prec@5 96.000 (97.700) +2022-11-14 13:25:19,035 Epoch: [38][300/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1397 (0.1290) Prec@1 72.000 (77.806) Prec@5 99.000 (97.742) +2022-11-14 13:25:19,514 Epoch: [38][310/500] Time 0.066 (0.036) Data 0.002 (0.003) Loss 0.1421 (0.1294) Prec@1 74.000 (77.688) Prec@5 98.000 (97.750) +2022-11-14 13:25:19,957 Epoch: [38][320/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.1235 (0.1292) Prec@1 78.000 (77.697) Prec@5 95.000 (97.667) +2022-11-14 13:25:20,446 Epoch: [38][330/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.1214 (0.1290) Prec@1 78.000 (77.706) Prec@5 94.000 (97.559) +2022-11-14 13:25:20,965 Epoch: [38][340/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.1300 (0.1290) Prec@1 77.000 (77.686) Prec@5 98.000 (97.571) +2022-11-14 13:25:21,490 Epoch: [38][350/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.1141 (0.1286) Prec@1 81.000 (77.778) Prec@5 98.000 (97.583) +2022-11-14 13:25:22,000 Epoch: [38][360/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.1201 (0.1284) Prec@1 78.000 (77.784) Prec@5 95.000 (97.514) +2022-11-14 13:25:22,454 Epoch: [38][370/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.1577 (0.1291) Prec@1 68.000 (77.526) Prec@5 99.000 (97.553) +2022-11-14 13:25:22,901 Epoch: [38][380/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.1093 (0.1286) Prec@1 83.000 (77.667) Prec@5 98.000 (97.564) +2022-11-14 13:25:23,372 Epoch: [38][390/500] Time 0.056 (0.037) Data 0.002 (0.003) Loss 0.0970 (0.1278) Prec@1 83.000 (77.800) Prec@5 98.000 (97.575) +2022-11-14 13:25:23,798 Epoch: [38][400/500] Time 0.031 (0.037) Data 0.002 (0.003) Loss 0.1270 (0.1278) Prec@1 78.000 (77.805) Prec@5 98.000 (97.585) +2022-11-14 13:25:24,194 Epoch: [38][410/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1321 (0.1279) Prec@1 80.000 (77.857) Prec@5 96.000 (97.548) +2022-11-14 13:25:24,639 Epoch: [38][420/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1039 (0.1274) Prec@1 81.000 (77.930) Prec@5 99.000 (97.581) +2022-11-14 13:25:25,039 Epoch: [38][430/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.1403 (0.1277) Prec@1 73.000 (77.818) Prec@5 94.000 (97.500) +2022-11-14 13:25:25,467 Epoch: [38][440/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.1158 (0.1274) Prec@1 78.000 (77.822) Prec@5 100.000 (97.556) +2022-11-14 13:25:25,884 Epoch: [38][450/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1731 (0.1284) Prec@1 70.000 (77.652) Prec@5 94.000 (97.478) +2022-11-14 13:25:26,277 Epoch: [38][460/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1200 (0.1282) Prec@1 79.000 (77.681) Prec@5 98.000 (97.489) +2022-11-14 13:25:26,702 Epoch: [38][470/500] Time 0.046 (0.037) Data 0.002 (0.002) Loss 0.1207 (0.1281) Prec@1 78.000 (77.688) Prec@5 98.000 (97.500) +2022-11-14 13:25:27,096 Epoch: [38][480/500] Time 0.038 (0.037) Data 0.001 (0.002) Loss 0.1446 (0.1284) Prec@1 75.000 (77.633) Prec@5 96.000 (97.469) +2022-11-14 13:25:27,531 Epoch: [38][490/500] Time 0.052 (0.037) Data 0.002 (0.002) Loss 0.1639 (0.1291) Prec@1 68.000 (77.440) Prec@5 96.000 (97.440) +2022-11-14 13:25:27,922 Epoch: [38][499/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.1364 (0.1293) Prec@1 79.000 (77.471) Prec@5 97.000 (97.431) +2022-11-14 13:25:28,251 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1393 (0.1393) Prec@1 76.000 (76.000) Prec@5 98.000 (98.000) +2022-11-14 13:25:28,262 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1329 (0.1361) Prec@1 76.000 (76.000) Prec@5 99.000 (98.500) +2022-11-14 13:25:28,274 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1724 (0.1482) Prec@1 69.000 (73.667) Prec@5 99.000 (98.667) +2022-11-14 13:25:28,288 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1736 (0.1546) Prec@1 69.000 (72.500) Prec@5 98.000 (98.500) +2022-11-14 13:25:28,300 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1815 (0.1599) Prec@1 68.000 (71.600) Prec@5 96.000 (98.000) +2022-11-14 13:25:28,310 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1286 (0.1547) Prec@1 78.000 (72.667) Prec@5 98.000 (98.000) +2022-11-14 13:25:28,320 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1473 (0.1537) Prec@1 75.000 (73.000) Prec@5 100.000 (98.286) +2022-11-14 13:25:28,334 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1648 (0.1551) Prec@1 70.000 (72.625) Prec@5 95.000 (97.875) +2022-11-14 13:25:28,347 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1836 (0.1582) Prec@1 64.000 (71.667) Prec@5 94.000 (97.444) +2022-11-14 13:25:28,360 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1429 (0.1567) Prec@1 75.000 (72.000) Prec@5 98.000 (97.500) +2022-11-14 13:25:28,372 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1566 (0.1567) Prec@1 72.000 (72.000) Prec@5 99.000 (97.636) +2022-11-14 13:25:28,386 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1680 (0.1576) Prec@1 71.000 (71.917) Prec@5 93.000 (97.250) +2022-11-14 13:25:28,399 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1795 (0.1593) Prec@1 66.000 (71.462) Prec@5 98.000 (97.308) +2022-11-14 13:25:28,411 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1559 (0.1591) Prec@1 74.000 (71.643) Prec@5 97.000 (97.286) +2022-11-14 13:25:28,424 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1608 (0.1592) Prec@1 73.000 (71.733) Prec@5 98.000 (97.333) +2022-11-14 13:25:28,438 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1767 (0.1603) Prec@1 66.000 (71.375) Prec@5 98.000 (97.375) +2022-11-14 13:25:28,450 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1331 (0.1587) Prec@1 75.000 (71.588) Prec@5 98.000 (97.412) +2022-11-14 13:25:28,463 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1365 (0.1574) Prec@1 73.000 (71.667) Prec@5 98.000 (97.444) +2022-11-14 13:25:28,476 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1664 (0.1579) Prec@1 70.000 (71.579) Prec@5 95.000 (97.316) +2022-11-14 13:25:28,490 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1735 (0.1587) Prec@1 68.000 (71.400) Prec@5 93.000 (97.100) +2022-11-14 13:25:28,503 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1739 (0.1594) Prec@1 69.000 (71.286) Prec@5 97.000 (97.095) +2022-11-14 13:25:28,517 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1723 (0.1600) Prec@1 73.000 (71.364) Prec@5 98.000 (97.136) +2022-11-14 13:25:28,529 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1491 (0.1595) Prec@1 75.000 (71.522) Prec@5 96.000 (97.087) +2022-11-14 13:25:28,542 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1249 (0.1581) Prec@1 78.000 (71.792) Prec@5 99.000 (97.167) +2022-11-14 13:25:28,554 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1728 (0.1587) Prec@1 70.000 (71.720) Prec@5 98.000 (97.200) +2022-11-14 13:25:28,566 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2023 (0.1604) Prec@1 64.000 (71.423) Prec@5 96.000 (97.154) +2022-11-14 13:25:28,580 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1355 (0.1594) Prec@1 78.000 (71.667) Prec@5 100.000 (97.259) +2022-11-14 13:25:28,593 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1717 (0.1599) Prec@1 72.000 (71.679) Prec@5 97.000 (97.250) +2022-11-14 13:25:28,606 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1595 (0.1599) Prec@1 71.000 (71.655) Prec@5 96.000 (97.207) +2022-11-14 13:25:28,618 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1536 (0.1596) Prec@1 71.000 (71.633) Prec@5 97.000 (97.200) +2022-11-14 13:25:28,631 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1572 (0.1596) Prec@1 73.000 (71.677) Prec@5 95.000 (97.129) +2022-11-14 13:25:28,645 Test: [31/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1432 (0.1591) Prec@1 76.000 (71.812) Prec@5 97.000 (97.125) +2022-11-14 13:25:28,661 Test: [32/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1839 (0.1598) Prec@1 67.000 (71.667) Prec@5 93.000 (97.000) +2022-11-14 13:25:28,675 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1766 (0.1603) Prec@1 69.000 (71.588) Prec@5 95.000 (96.941) +2022-11-14 13:25:28,687 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1550 (0.1602) Prec@1 79.000 (71.800) Prec@5 95.000 (96.886) +2022-11-14 13:25:28,701 Test: [35/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1439 (0.1597) Prec@1 75.000 (71.889) Prec@5 96.000 (96.861) +2022-11-14 13:25:28,716 Test: [36/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1504 (0.1595) Prec@1 75.000 (71.973) Prec@5 97.000 (96.865) +2022-11-14 13:25:28,731 Test: [37/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1804 (0.1600) Prec@1 68.000 (71.868) Prec@5 96.000 (96.842) +2022-11-14 13:25:28,745 Test: [38/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1573 (0.1599) Prec@1 72.000 (71.872) Prec@5 99.000 (96.897) +2022-11-14 13:25:28,760 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1329 (0.1593) Prec@1 74.000 (71.925) Prec@5 97.000 (96.900) +2022-11-14 13:25:28,774 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1505 (0.1590) Prec@1 76.000 (72.024) Prec@5 97.000 (96.902) +2022-11-14 13:25:28,788 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1388 (0.1586) Prec@1 76.000 (72.119) Prec@5 96.000 (96.881) +2022-11-14 13:25:28,802 Test: [42/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1557 (0.1585) Prec@1 72.000 (72.116) Prec@5 99.000 (96.930) +2022-11-14 13:25:28,816 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1397 (0.1581) Prec@1 74.000 (72.159) Prec@5 98.000 (96.955) +2022-11-14 13:25:28,830 Test: [44/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1471 (0.1578) Prec@1 75.000 (72.222) Prec@5 97.000 (96.956) +2022-11-14 13:25:28,848 Test: [45/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1869 (0.1585) Prec@1 64.000 (72.043) Prec@5 94.000 (96.891) +2022-11-14 13:25:28,864 Test: [46/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1673 (0.1586) Prec@1 70.000 (72.000) Prec@5 100.000 (96.957) +2022-11-14 13:25:28,881 Test: [47/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1508 (0.1585) Prec@1 71.000 (71.979) Prec@5 96.000 (96.938) +2022-11-14 13:25:28,897 Test: [48/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1440 (0.1582) Prec@1 75.000 (72.041) Prec@5 98.000 (96.959) +2022-11-14 13:25:28,914 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1980 (0.1590) Prec@1 63.000 (71.860) Prec@5 92.000 (96.860) +2022-11-14 13:25:28,928 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1237 (0.1583) Prec@1 78.000 (71.980) Prec@5 100.000 (96.922) +2022-11-14 13:25:28,943 Test: [51/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1763 (0.1586) Prec@1 65.000 (71.846) Prec@5 92.000 (96.827) +2022-11-14 13:25:28,956 Test: [52/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1547 (0.1586) Prec@1 71.000 (71.830) Prec@5 98.000 (96.849) +2022-11-14 13:25:28,969 Test: [53/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1541 (0.1585) Prec@1 74.000 (71.870) Prec@5 94.000 (96.796) +2022-11-14 13:25:28,984 Test: [54/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1754 (0.1588) Prec@1 66.000 (71.764) Prec@5 100.000 (96.855) +2022-11-14 13:25:28,998 Test: [55/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1664 (0.1589) Prec@1 70.000 (71.732) Prec@5 96.000 (96.839) +2022-11-14 13:25:29,013 Test: [56/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1893 (0.1595) Prec@1 67.000 (71.649) Prec@5 95.000 (96.807) +2022-11-14 13:25:29,025 Test: [57/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1300 (0.1589) Prec@1 74.000 (71.690) Prec@5 99.000 (96.845) +2022-11-14 13:25:29,041 Test: [58/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1945 (0.1596) Prec@1 62.000 (71.525) Prec@5 98.000 (96.864) +2022-11-14 13:25:29,055 Test: [59/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1657 (0.1597) Prec@1 69.000 (71.483) Prec@5 99.000 (96.900) +2022-11-14 13:25:29,067 Test: [60/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1614 (0.1597) Prec@1 72.000 (71.492) Prec@5 97.000 (96.902) +2022-11-14 13:25:29,080 Test: [61/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1743 (0.1599) Prec@1 67.000 (71.419) Prec@5 98.000 (96.919) +2022-11-14 13:25:29,093 Test: [62/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1322 (0.1595) Prec@1 75.000 (71.476) Prec@5 97.000 (96.921) +2022-11-14 13:25:29,105 Test: [63/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1349 (0.1591) Prec@1 75.000 (71.531) Prec@5 99.000 (96.953) +2022-11-14 13:25:29,120 Test: [64/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1728 (0.1593) Prec@1 70.000 (71.508) Prec@5 97.000 (96.954) +2022-11-14 13:25:29,133 Test: [65/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1627 (0.1594) Prec@1 74.000 (71.545) Prec@5 97.000 (96.955) +2022-11-14 13:25:29,147 Test: [66/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1599 (0.1594) Prec@1 72.000 (71.552) Prec@5 100.000 (97.000) +2022-11-14 13:25:29,160 Test: [67/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1518 (0.1593) Prec@1 71.000 (71.544) Prec@5 97.000 (97.000) +2022-11-14 13:25:29,172 Test: [68/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1546 (0.1592) Prec@1 71.000 (71.536) Prec@5 100.000 (97.043) +2022-11-14 13:25:29,184 Test: [69/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1891 (0.1596) Prec@1 65.000 (71.443) Prec@5 96.000 (97.029) +2022-11-14 13:25:29,196 Test: [70/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1342 (0.1593) Prec@1 78.000 (71.535) Prec@5 96.000 (97.014) +2022-11-14 13:25:29,209 Test: [71/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1508 (0.1591) Prec@1 74.000 (71.569) Prec@5 96.000 (97.000) +2022-11-14 13:25:29,222 Test: [72/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1241 (0.1587) Prec@1 79.000 (71.671) Prec@5 99.000 (97.027) +2022-11-14 13:25:29,235 Test: [73/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1282 (0.1582) Prec@1 78.000 (71.757) Prec@5 98.000 (97.041) +2022-11-14 13:25:29,248 Test: [74/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1805 (0.1585) Prec@1 66.000 (71.680) Prec@5 96.000 (97.027) +2022-11-14 13:25:29,260 Test: [75/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1360 (0.1582) Prec@1 76.000 (71.737) Prec@5 96.000 (97.013) +2022-11-14 13:25:29,272 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1543 (0.1582) Prec@1 78.000 (71.818) Prec@5 97.000 (97.013) +2022-11-14 13:25:29,284 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1638 (0.1583) Prec@1 69.000 (71.782) Prec@5 95.000 (96.987) +2022-11-14 13:25:29,296 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1615 (0.1583) Prec@1 69.000 (71.747) Prec@5 96.000 (96.975) +2022-11-14 13:25:29,310 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1506 (0.1582) Prec@1 70.000 (71.725) Prec@5 96.000 (96.963) +2022-11-14 13:25:29,322 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1457 (0.1581) Prec@1 73.000 (71.741) Prec@5 96.000 (96.951) +2022-11-14 13:25:29,336 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1724 (0.1582) Prec@1 73.000 (71.756) Prec@5 96.000 (96.939) +2022-11-14 13:25:29,350 Test: [82/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1801 (0.1585) Prec@1 66.000 (71.687) Prec@5 98.000 (96.952) +2022-11-14 13:25:29,363 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2023 (0.1590) Prec@1 67.000 (71.631) Prec@5 97.000 (96.952) +2022-11-14 13:25:29,376 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1776 (0.1592) Prec@1 66.000 (71.565) Prec@5 95.000 (96.929) +2022-11-14 13:25:29,387 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1417 (0.1590) Prec@1 77.000 (71.628) Prec@5 98.000 (96.942) +2022-11-14 13:25:29,398 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1641 (0.1591) Prec@1 66.000 (71.563) Prec@5 98.000 (96.954) +2022-11-14 13:25:29,412 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1584 (0.1591) Prec@1 75.000 (71.602) Prec@5 96.000 (96.943) +2022-11-14 13:25:29,426 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1396 (0.1589) Prec@1 73.000 (71.618) Prec@5 98.000 (96.955) +2022-11-14 13:25:29,439 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1466 (0.1587) Prec@1 79.000 (71.700) Prec@5 95.000 (96.933) +2022-11-14 13:25:29,452 Test: [90/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1159 (0.1583) Prec@1 78.000 (71.769) Prec@5 98.000 (96.945) +2022-11-14 13:25:29,464 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1194 (0.1578) Prec@1 75.000 (71.804) Prec@5 98.000 (96.957) +2022-11-14 13:25:29,476 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1614 (0.1579) Prec@1 73.000 (71.817) Prec@5 96.000 (96.946) +2022-11-14 13:25:29,488 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1733 (0.1580) Prec@1 67.000 (71.766) Prec@5 95.000 (96.926) +2022-11-14 13:25:29,502 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1734 (0.1582) Prec@1 69.000 (71.737) Prec@5 98.000 (96.937) +2022-11-14 13:25:29,516 Test: [95/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1089 (0.1577) Prec@1 82.000 (71.844) Prec@5 97.000 (96.938) +2022-11-14 13:25:29,532 Test: [96/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1304 (0.1574) Prec@1 76.000 (71.887) Prec@5 97.000 (96.938) +2022-11-14 13:25:29,548 Test: [97/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.2022 (0.1579) Prec@1 61.000 (71.776) Prec@5 98.000 (96.949) +2022-11-14 13:25:29,561 Test: [98/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1681 (0.1580) Prec@1 70.000 (71.758) Prec@5 99.000 (96.970) +2022-11-14 13:25:29,575 Test: [99/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1839 (0.1582) Prec@1 63.000 (71.670) Prec@5 97.000 (96.970) +2022-11-14 13:25:29,639 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:25:29,994 Epoch: [39][0/500] Time 0.030 (0.030) Data 0.257 (0.257) Loss 0.1525 (0.1525) Prec@1 73.000 (73.000) Prec@5 96.000 (96.000) +2022-11-14 13:25:30,286 Epoch: [39][10/500] Time 0.026 (0.026) Data 0.002 (0.025) Loss 0.1152 (0.1338) Prec@1 82.000 (77.500) Prec@5 99.000 (97.500) +2022-11-14 13:25:30,623 Epoch: [39][20/500] Time 0.030 (0.028) Data 0.002 (0.014) Loss 0.1493 (0.1390) Prec@1 77.000 (77.333) Prec@5 96.000 (97.000) +2022-11-14 13:25:31,026 Epoch: [39][30/500] Time 0.037 (0.030) Data 0.002 (0.010) Loss 0.1223 (0.1348) Prec@1 78.000 (77.500) Prec@5 99.000 (97.500) +2022-11-14 13:25:31,428 Epoch: [39][40/500] Time 0.038 (0.032) Data 0.002 (0.008) Loss 0.1422 (0.1363) Prec@1 76.000 (77.200) Prec@5 97.000 (97.400) +2022-11-14 13:25:31,744 Epoch: [39][50/500] Time 0.025 (0.031) Data 0.002 (0.007) Loss 0.1378 (0.1365) Prec@1 77.000 (77.167) Prec@5 100.000 (97.833) +2022-11-14 13:25:32,091 Epoch: [39][60/500] Time 0.026 (0.031) Data 0.002 (0.006) Loss 0.1478 (0.1381) Prec@1 75.000 (76.857) Prec@5 99.000 (98.000) +2022-11-14 13:25:32,435 Epoch: [39][70/500] Time 0.051 (0.031) Data 0.002 (0.006) Loss 0.1279 (0.1369) Prec@1 77.000 (76.875) Prec@5 99.000 (98.125) +2022-11-14 13:25:32,741 Epoch: [39][80/500] Time 0.027 (0.030) Data 0.002 (0.005) Loss 0.1129 (0.1342) Prec@1 78.000 (77.000) Prec@5 99.000 (98.222) +2022-11-14 13:25:33,060 Epoch: [39][90/500] Time 0.031 (0.030) Data 0.002 (0.005) Loss 0.1309 (0.1339) Prec@1 75.000 (76.800) Prec@5 97.000 (98.100) +2022-11-14 13:25:33,381 Epoch: [39][100/500] Time 0.027 (0.030) Data 0.002 (0.005) Loss 0.1746 (0.1376) Prec@1 69.000 (76.091) Prec@5 98.000 (98.091) +2022-11-14 13:25:33,698 Epoch: [39][110/500] Time 0.026 (0.030) Data 0.002 (0.004) Loss 0.1641 (0.1398) Prec@1 72.000 (75.750) Prec@5 97.000 (98.000) +2022-11-14 13:25:34,087 Epoch: [39][120/500] Time 0.054 (0.030) Data 0.002 (0.004) Loss 0.0959 (0.1364) Prec@1 82.000 (76.231) Prec@5 100.000 (98.154) +2022-11-14 13:25:34,499 Epoch: [39][130/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.1432 (0.1369) Prec@1 72.000 (75.929) Prec@5 94.000 (97.857) +2022-11-14 13:25:35,378 Epoch: [39][140/500] Time 0.084 (0.034) Data 0.002 (0.004) Loss 0.1409 (0.1372) Prec@1 73.000 (75.733) Prec@5 98.000 (97.867) +2022-11-14 13:25:36,216 Epoch: [39][150/500] Time 0.079 (0.037) Data 0.002 (0.004) Loss 0.1348 (0.1370) Prec@1 79.000 (75.938) Prec@5 95.000 (97.688) +2022-11-14 13:25:36,888 Epoch: [39][160/500] Time 0.041 (0.038) Data 0.002 (0.004) Loss 0.1642 (0.1386) Prec@1 73.000 (75.765) Prec@5 95.000 (97.529) +2022-11-14 13:25:37,461 Epoch: [39][170/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1180 (0.1375) Prec@1 80.000 (76.000) Prec@5 99.000 (97.611) +2022-11-14 13:25:38,049 Epoch: [39][180/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.1212 (0.1366) Prec@1 82.000 (76.316) Prec@5 99.000 (97.684) +2022-11-14 13:25:38,598 Epoch: [39][190/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0943 (0.1345) Prec@1 84.000 (76.700) Prec@5 99.000 (97.750) +2022-11-14 13:25:39,065 Epoch: [39][200/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.1266 (0.1341) Prec@1 78.000 (76.762) Prec@5 98.000 (97.762) +2022-11-14 13:25:39,544 Epoch: [39][210/500] Time 0.048 (0.041) Data 0.002 (0.003) Loss 0.1136 (0.1332) Prec@1 79.000 (76.864) Prec@5 99.000 (97.818) +2022-11-14 13:25:40,165 Epoch: [39][220/500] Time 0.083 (0.041) Data 0.002 (0.003) Loss 0.1255 (0.1329) Prec@1 77.000 (76.870) Prec@5 99.000 (97.870) +2022-11-14 13:25:40,962 Epoch: [39][230/500] Time 0.082 (0.042) Data 0.002 (0.003) Loss 0.1505 (0.1336) Prec@1 74.000 (76.750) Prec@5 94.000 (97.708) +2022-11-14 13:25:41,760 Epoch: [39][240/500] Time 0.080 (0.044) Data 0.002 (0.003) Loss 0.1293 (0.1334) Prec@1 76.000 (76.720) Prec@5 100.000 (97.800) +2022-11-14 13:25:42,564 Epoch: [39][250/500] Time 0.077 (0.045) Data 0.002 (0.003) Loss 0.1068 (0.1324) Prec@1 82.000 (76.923) Prec@5 99.000 (97.846) +2022-11-14 13:25:43,211 Epoch: [39][260/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.1212 (0.1320) Prec@1 81.000 (77.074) Prec@5 97.000 (97.815) +2022-11-14 13:25:43,805 Epoch: [39][270/500] Time 0.069 (0.046) Data 0.002 (0.003) Loss 0.1607 (0.1330) Prec@1 75.000 (77.000) Prec@5 96.000 (97.750) +2022-11-14 13:25:44,302 Epoch: [39][280/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.1314 (0.1330) Prec@1 78.000 (77.034) Prec@5 98.000 (97.759) +2022-11-14 13:25:44,935 Epoch: [39][290/500] Time 0.087 (0.046) Data 0.002 (0.003) Loss 0.1309 (0.1329) Prec@1 74.000 (76.933) Prec@5 98.000 (97.767) +2022-11-14 13:25:45,731 Epoch: [39][300/500] Time 0.081 (0.047) Data 0.002 (0.003) Loss 0.1245 (0.1326) Prec@1 82.000 (77.097) Prec@5 99.000 (97.806) +2022-11-14 13:25:46,319 Epoch: [39][310/500] Time 0.043 (0.047) Data 0.002 (0.003) Loss 0.1300 (0.1325) Prec@1 76.000 (77.062) Prec@5 99.000 (97.844) +2022-11-14 13:25:46,788 Epoch: [39][320/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.1464 (0.1330) Prec@1 70.000 (76.848) Prec@5 98.000 (97.848) +2022-11-14 13:25:47,254 Epoch: [39][330/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.1413 (0.1332) Prec@1 74.000 (76.765) Prec@5 97.000 (97.824) +2022-11-14 13:25:47,729 Epoch: [39][340/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.1356 (0.1333) Prec@1 78.000 (76.800) Prec@5 98.000 (97.829) +2022-11-14 13:25:48,201 Epoch: [39][350/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.1368 (0.1334) Prec@1 72.000 (76.667) Prec@5 98.000 (97.833) +2022-11-14 13:25:48,674 Epoch: [39][360/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.1271 (0.1332) Prec@1 80.000 (76.757) Prec@5 97.000 (97.811) +2022-11-14 13:25:49,143 Epoch: [39][370/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.1246 (0.1330) Prec@1 79.000 (76.816) Prec@5 99.000 (97.842) +2022-11-14 13:25:49,715 Epoch: [39][380/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.1423 (0.1332) Prec@1 73.000 (76.718) Prec@5 96.000 (97.795) +2022-11-14 13:25:50,367 Epoch: [39][390/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.1266 (0.1330) Prec@1 79.000 (76.775) Prec@5 95.000 (97.725) +2022-11-14 13:25:50,764 Epoch: [39][400/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.1133 (0.1326) Prec@1 80.000 (76.854) Prec@5 100.000 (97.780) +2022-11-14 13:25:51,163 Epoch: [39][410/500] Time 0.036 (0.046) Data 0.002 (0.003) Loss 0.1385 (0.1327) Prec@1 75.000 (76.810) Prec@5 97.000 (97.762) +2022-11-14 13:25:51,562 Epoch: [39][420/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.1628 (0.1334) Prec@1 73.000 (76.721) Prec@5 97.000 (97.744) +2022-11-14 13:25:51,965 Epoch: [39][430/500] Time 0.034 (0.046) Data 0.002 (0.003) Loss 0.1417 (0.1336) Prec@1 74.000 (76.659) Prec@5 97.000 (97.727) +2022-11-14 13:25:52,365 Epoch: [39][440/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.1322 (0.1336) Prec@1 75.000 (76.622) Prec@5 95.000 (97.667) +2022-11-14 13:25:52,765 Epoch: [39][450/500] Time 0.037 (0.045) Data 0.003 (0.003) Loss 0.1355 (0.1336) Prec@1 75.000 (76.587) Prec@5 99.000 (97.696) +2022-11-14 13:25:53,162 Epoch: [39][460/500] Time 0.037 (0.045) Data 0.002 (0.003) Loss 0.1177 (0.1333) Prec@1 82.000 (76.702) Prec@5 97.000 (97.681) +2022-11-14 13:25:53,562 Epoch: [39][470/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.1524 (0.1337) Prec@1 75.000 (76.667) Prec@5 97.000 (97.667) +2022-11-14 13:25:53,960 Epoch: [39][480/500] Time 0.036 (0.045) Data 0.002 (0.003) Loss 0.1325 (0.1336) Prec@1 77.000 (76.673) Prec@5 97.000 (97.653) +2022-11-14 13:25:54,354 Epoch: [39][490/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.1158 (0.1333) Prec@1 80.000 (76.740) Prec@5 98.000 (97.660) +2022-11-14 13:25:54,719 Epoch: [39][499/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.1462 (0.1335) Prec@1 73.000 (76.667) Prec@5 97.000 (97.647) +2022-11-14 13:25:55,033 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1731 (0.1731) Prec@1 69.000 (69.000) Prec@5 96.000 (96.000) +2022-11-14 13:25:55,044 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1760 (0.1745) Prec@1 64.000 (66.500) Prec@5 97.000 (96.500) +2022-11-14 13:25:55,055 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2141 (0.1877) Prec@1 60.000 (64.333) Prec@5 96.000 (96.333) +2022-11-14 13:25:55,070 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1822 (0.1863) Prec@1 68.000 (65.250) Prec@5 97.000 (96.500) +2022-11-14 13:25:55,083 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2036 (0.1898) Prec@1 66.000 (65.400) Prec@5 98.000 (96.800) +2022-11-14 13:25:55,094 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1647 (0.1856) Prec@1 71.000 (66.333) Prec@5 93.000 (96.167) +2022-11-14 13:25:55,107 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1856 (0.1856) Prec@1 67.000 (66.429) Prec@5 95.000 (96.000) +2022-11-14 13:25:55,123 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2097 (0.1886) Prec@1 61.000 (65.750) Prec@5 95.000 (95.875) +2022-11-14 13:25:55,136 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.2200 (0.1921) Prec@1 63.000 (65.444) Prec@5 96.000 (95.889) +2022-11-14 13:25:55,149 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1562 (0.1885) Prec@1 73.000 (66.200) Prec@5 98.000 (96.100) +2022-11-14 13:25:55,162 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2087 (0.1903) Prec@1 63.000 (65.909) Prec@5 95.000 (96.000) +2022-11-14 13:25:55,175 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1610 (0.1879) Prec@1 69.000 (66.167) Prec@5 98.000 (96.167) +2022-11-14 13:25:55,191 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1650 (0.1861) Prec@1 71.000 (66.538) Prec@5 96.000 (96.154) +2022-11-14 13:25:55,204 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1746 (0.1853) Prec@1 66.000 (66.500) Prec@5 96.000 (96.143) +2022-11-14 13:25:55,216 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1866 (0.1854) Prec@1 66.000 (66.467) Prec@5 97.000 (96.200) +2022-11-14 13:25:55,228 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1501 (0.1832) Prec@1 75.000 (67.000) Prec@5 96.000 (96.188) +2022-11-14 13:25:55,244 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1383 (0.1806) Prec@1 74.000 (67.412) Prec@5 98.000 (96.294) +2022-11-14 13:25:55,259 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1991 (0.1816) Prec@1 70.000 (67.556) Prec@5 96.000 (96.278) +2022-11-14 13:25:55,272 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1617 (0.1805) Prec@1 75.000 (67.947) Prec@5 96.000 (96.263) +2022-11-14 13:25:55,285 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2140 (0.1822) Prec@1 62.000 (67.650) Prec@5 95.000 (96.200) +2022-11-14 13:25:55,298 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1827 (0.1822) Prec@1 69.000 (67.714) Prec@5 95.000 (96.143) +2022-11-14 13:25:55,312 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1929 (0.1827) Prec@1 68.000 (67.727) Prec@5 97.000 (96.182) +2022-11-14 13:25:55,326 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2090 (0.1839) Prec@1 61.000 (67.435) Prec@5 96.000 (96.174) +2022-11-14 13:25:55,340 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1919 (0.1842) Prec@1 64.000 (67.292) Prec@5 98.000 (96.250) +2022-11-14 13:25:55,356 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2008 (0.1849) Prec@1 64.000 (67.160) Prec@5 97.000 (96.280) +2022-11-14 13:25:55,371 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.2030 (0.1856) Prec@1 65.000 (67.077) Prec@5 91.000 (96.077) +2022-11-14 13:25:55,386 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1933 (0.1858) Prec@1 66.000 (67.037) Prec@5 98.000 (96.148) +2022-11-14 13:25:55,400 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1958 (0.1862) Prec@1 64.000 (66.929) Prec@5 95.000 (96.107) +2022-11-14 13:25:55,415 Test: [28/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1682 (0.1856) Prec@1 69.000 (67.000) Prec@5 96.000 (96.103) +2022-11-14 13:25:55,430 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.2304 (0.1871) Prec@1 61.000 (66.800) Prec@5 97.000 (96.133) +2022-11-14 13:25:55,444 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1928 (0.1873) Prec@1 66.000 (66.774) Prec@5 95.000 (96.097) +2022-11-14 13:25:55,458 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1914 (0.1874) Prec@1 66.000 (66.750) Prec@5 97.000 (96.125) +2022-11-14 13:25:55,474 Test: [32/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1769 (0.1871) Prec@1 66.000 (66.727) Prec@5 94.000 (96.061) +2022-11-14 13:25:55,489 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1861 (0.1870) Prec@1 65.000 (66.676) Prec@5 95.000 (96.029) +2022-11-14 13:25:55,505 Test: [34/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.2234 (0.1881) Prec@1 58.000 (66.429) Prec@5 88.000 (95.800) +2022-11-14 13:25:55,518 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1585 (0.1873) Prec@1 70.000 (66.528) Prec@5 96.000 (95.806) +2022-11-14 13:25:55,532 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1958 (0.1875) Prec@1 64.000 (66.459) Prec@5 97.000 (95.838) +2022-11-14 13:25:55,547 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1980 (0.1878) Prec@1 62.000 (66.342) Prec@5 96.000 (95.842) +2022-11-14 13:25:55,561 Test: [38/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1627 (0.1871) Prec@1 73.000 (66.513) Prec@5 96.000 (95.846) +2022-11-14 13:25:55,576 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1921 (0.1872) Prec@1 65.000 (66.475) Prec@5 98.000 (95.900) +2022-11-14 13:25:55,591 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1816 (0.1871) Prec@1 68.000 (66.512) Prec@5 97.000 (95.927) +2022-11-14 13:25:55,607 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1978 (0.1874) Prec@1 62.000 (66.405) Prec@5 95.000 (95.905) +2022-11-14 13:25:55,622 Test: [42/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1574 (0.1867) Prec@1 72.000 (66.535) Prec@5 97.000 (95.930) +2022-11-14 13:25:55,637 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1868 (0.1867) Prec@1 62.000 (66.432) Prec@5 95.000 (95.909) +2022-11-14 13:25:55,650 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1854 (0.1866) Prec@1 68.000 (66.467) Prec@5 97.000 (95.933) +2022-11-14 13:25:55,664 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.2045 (0.1870) Prec@1 64.000 (66.413) Prec@5 95.000 (95.913) +2022-11-14 13:25:55,680 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1937 (0.1872) Prec@1 67.000 (66.426) Prec@5 95.000 (95.894) +2022-11-14 13:25:55,694 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1880 (0.1872) Prec@1 64.000 (66.375) Prec@5 96.000 (95.896) +2022-11-14 13:25:55,711 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1377 (0.1862) Prec@1 79.000 (66.633) Prec@5 97.000 (95.918) +2022-11-14 13:25:55,724 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2199 (0.1869) Prec@1 63.000 (66.560) Prec@5 97.000 (95.940) +2022-11-14 13:25:55,738 Test: [50/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1619 (0.1864) Prec@1 74.000 (66.706) Prec@5 96.000 (95.941) +2022-11-14 13:25:55,750 Test: [51/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2044 (0.1867) Prec@1 64.000 (66.654) Prec@5 93.000 (95.885) +2022-11-14 13:25:55,760 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2119 (0.1872) Prec@1 60.000 (66.528) Prec@5 100.000 (95.962) +2022-11-14 13:25:55,772 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2240 (0.1879) Prec@1 60.000 (66.407) Prec@5 96.000 (95.963) +2022-11-14 13:25:55,783 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1819 (0.1878) Prec@1 69.000 (66.455) Prec@5 95.000 (95.945) +2022-11-14 13:25:55,792 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1791 (0.1876) Prec@1 67.000 (66.464) Prec@5 92.000 (95.875) +2022-11-14 13:25:55,803 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1944 (0.1877) Prec@1 65.000 (66.439) Prec@5 96.000 (95.877) +2022-11-14 13:25:55,814 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1747 (0.1875) Prec@1 71.000 (66.517) Prec@5 97.000 (95.897) +2022-11-14 13:25:55,825 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2012 (0.1877) Prec@1 63.000 (66.458) Prec@5 98.000 (95.932) +2022-11-14 13:25:55,837 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1866 (0.1877) Prec@1 68.000 (66.483) Prec@5 96.000 (95.933) +2022-11-14 13:25:55,849 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2136 (0.1881) Prec@1 63.000 (66.426) Prec@5 95.000 (95.918) +2022-11-14 13:25:55,861 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1543 (0.1876) Prec@1 76.000 (66.581) Prec@5 98.000 (95.952) +2022-11-14 13:25:55,873 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1483 (0.1870) Prec@1 74.000 (66.698) Prec@5 99.000 (96.000) +2022-11-14 13:25:55,883 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1999 (0.1872) Prec@1 61.000 (66.609) Prec@5 96.000 (96.000) +2022-11-14 13:25:55,896 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1994 (0.1874) Prec@1 67.000 (66.615) Prec@5 94.000 (95.969) +2022-11-14 13:25:55,908 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1931 (0.1874) Prec@1 67.000 (66.621) Prec@5 97.000 (95.985) +2022-11-14 13:25:55,920 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1791 (0.1873) Prec@1 71.000 (66.687) Prec@5 98.000 (96.015) +2022-11-14 13:25:55,933 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1522 (0.1868) Prec@1 70.000 (66.735) Prec@5 96.000 (96.015) +2022-11-14 13:25:55,945 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1883 (0.1868) Prec@1 66.000 (66.725) Prec@5 98.000 (96.043) +2022-11-14 13:25:55,957 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2314 (0.1875) Prec@1 58.000 (66.600) Prec@5 89.000 (95.943) +2022-11-14 13:25:55,968 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1807 (0.1874) Prec@1 65.000 (66.577) Prec@5 99.000 (95.986) +2022-11-14 13:25:55,982 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2254 (0.1879) Prec@1 60.000 (66.486) Prec@5 95.000 (95.972) +2022-11-14 13:25:55,995 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1469 (0.1873) Prec@1 77.000 (66.630) Prec@5 97.000 (95.986) +2022-11-14 13:25:56,006 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1842 (0.1873) Prec@1 65.000 (66.608) Prec@5 97.000 (96.000) +2022-11-14 13:25:56,017 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2024 (0.1875) Prec@1 65.000 (66.587) Prec@5 95.000 (95.987) +2022-11-14 13:25:56,029 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1854 (0.1875) Prec@1 63.000 (66.539) Prec@5 99.000 (96.026) +2022-11-14 13:25:56,041 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1894 (0.1875) Prec@1 63.000 (66.494) Prec@5 95.000 (96.013) +2022-11-14 13:25:56,052 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1592 (0.1871) Prec@1 77.000 (66.628) Prec@5 97.000 (96.026) +2022-11-14 13:25:56,064 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2220 (0.1876) Prec@1 61.000 (66.557) Prec@5 95.000 (96.013) +2022-11-14 13:25:56,073 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1936 (0.1876) Prec@1 64.000 (66.525) Prec@5 92.000 (95.963) +2022-11-14 13:25:56,084 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1774 (0.1875) Prec@1 70.000 (66.568) Prec@5 96.000 (95.963) +2022-11-14 13:25:56,096 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1661 (0.1873) Prec@1 70.000 (66.610) Prec@5 98.000 (95.988) +2022-11-14 13:25:56,106 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1680 (0.1870) Prec@1 66.000 (66.602) Prec@5 98.000 (96.012) +2022-11-14 13:25:56,118 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1895 (0.1871) Prec@1 66.000 (66.595) Prec@5 96.000 (96.012) +2022-11-14 13:25:56,129 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2003 (0.1872) Prec@1 64.000 (66.565) Prec@5 93.000 (95.976) +2022-11-14 13:25:56,141 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2062 (0.1874) Prec@1 64.000 (66.535) Prec@5 94.000 (95.953) +2022-11-14 13:25:56,153 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1934 (0.1875) Prec@1 62.000 (66.483) Prec@5 97.000 (95.966) +2022-11-14 13:25:56,164 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2274 (0.1880) Prec@1 57.000 (66.375) Prec@5 97.000 (95.977) +2022-11-14 13:25:56,175 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1767 (0.1878) Prec@1 70.000 (66.416) Prec@5 97.000 (95.989) +2022-11-14 13:25:56,187 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2083 (0.1881) Prec@1 64.000 (66.389) Prec@5 93.000 (95.956) +2022-11-14 13:25:56,198 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1713 (0.1879) Prec@1 69.000 (66.418) Prec@5 95.000 (95.945) +2022-11-14 13:25:56,210 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1500 (0.1875) Prec@1 75.000 (66.511) Prec@5 98.000 (95.967) +2022-11-14 13:25:56,223 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2325 (0.1879) Prec@1 59.000 (66.430) Prec@5 94.000 (95.946) +2022-11-14 13:25:56,234 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2076 (0.1882) Prec@1 63.000 (66.394) Prec@5 95.000 (95.936) +2022-11-14 13:25:56,244 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1745 (0.1880) Prec@1 67.000 (66.400) Prec@5 97.000 (95.947) +2022-11-14 13:25:56,256 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1778 (0.1879) Prec@1 67.000 (66.406) Prec@5 97.000 (95.958) +2022-11-14 13:25:56,268 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1593 (0.1876) Prec@1 71.000 (66.454) Prec@5 96.000 (95.959) +2022-11-14 13:25:56,280 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1976 (0.1877) Prec@1 63.000 (66.418) Prec@5 98.000 (95.980) +2022-11-14 13:25:56,292 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.2106 (0.1879) Prec@1 63.000 (66.384) Prec@5 98.000 (96.000) +2022-11-14 13:25:56,303 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1931 (0.1880) Prec@1 62.000 (66.340) Prec@5 98.000 (96.020) +2022-11-14 13:25:56,360 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:25:56,685 Epoch: [40][0/500] Time 0.027 (0.027) Data 0.237 (0.237) Loss 0.1063 (0.1063) Prec@1 83.000 (83.000) Prec@5 98.000 (98.000) +2022-11-14 13:25:56,934 Epoch: [40][10/500] Time 0.028 (0.022) Data 0.002 (0.023) Loss 0.1114 (0.1089) Prec@1 81.000 (82.000) Prec@5 98.000 (98.000) +2022-11-14 13:25:57,180 Epoch: [40][20/500] Time 0.019 (0.022) Data 0.002 (0.013) Loss 0.1505 (0.1227) Prec@1 77.000 (80.333) Prec@5 96.000 (97.333) +2022-11-14 13:25:57,587 Epoch: [40][30/500] Time 0.038 (0.026) Data 0.002 (0.010) Loss 0.1348 (0.1258) Prec@1 78.000 (79.750) Prec@5 97.000 (97.250) +2022-11-14 13:25:58,136 Epoch: [40][40/500] Time 0.047 (0.031) Data 0.002 (0.008) Loss 0.1013 (0.1209) Prec@1 81.000 (80.000) Prec@5 98.000 (97.400) +2022-11-14 13:25:58,863 Epoch: [40][50/500] Time 0.065 (0.038) Data 0.002 (0.007) Loss 0.1382 (0.1238) Prec@1 77.000 (79.500) Prec@5 94.000 (96.833) +2022-11-14 13:25:59,420 Epoch: [40][60/500] Time 0.044 (0.040) Data 0.002 (0.006) Loss 0.1651 (0.1297) Prec@1 70.000 (78.143) Prec@5 98.000 (97.000) +2022-11-14 13:25:59,986 Epoch: [40][70/500] Time 0.051 (0.041) Data 0.002 (0.005) Loss 0.1624 (0.1338) Prec@1 68.000 (76.875) Prec@5 95.000 (96.750) +2022-11-14 13:26:00,457 Epoch: [40][80/500] Time 0.043 (0.042) Data 0.002 (0.005) Loss 0.1375 (0.1342) Prec@1 75.000 (76.667) Prec@5 99.000 (97.000) +2022-11-14 13:26:00,920 Epoch: [40][90/500] Time 0.043 (0.042) Data 0.002 (0.005) Loss 0.1129 (0.1320) Prec@1 80.000 (77.000) Prec@5 99.000 (97.200) +2022-11-14 13:26:01,384 Epoch: [40][100/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.1196 (0.1309) Prec@1 79.000 (77.182) Prec@5 99.000 (97.364) +2022-11-14 13:26:01,849 Epoch: [40][110/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.1534 (0.1328) Prec@1 71.000 (76.667) Prec@5 96.000 (97.250) +2022-11-14 13:26:02,314 Epoch: [40][120/500] Time 0.044 (0.041) Data 0.001 (0.004) Loss 0.1297 (0.1326) Prec@1 78.000 (76.769) Prec@5 96.000 (97.154) +2022-11-14 13:26:02,776 Epoch: [40][130/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.1328 (0.1326) Prec@1 77.000 (76.786) Prec@5 95.000 (97.000) +2022-11-14 13:26:03,237 Epoch: [40][140/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.1297 (0.1324) Prec@1 78.000 (76.867) Prec@5 97.000 (97.000) +2022-11-14 13:26:03,768 Epoch: [40][150/500] Time 0.078 (0.042) Data 0.002 (0.003) Loss 0.1167 (0.1314) Prec@1 81.000 (77.125) Prec@5 99.000 (97.125) +2022-11-14 13:26:04,359 Epoch: [40][160/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.1458 (0.1322) Prec@1 76.000 (77.059) Prec@5 97.000 (97.118) +2022-11-14 13:26:05,020 Epoch: [40][170/500] Time 0.060 (0.043) Data 0.002 (0.003) Loss 0.1044 (0.1307) Prec@1 81.000 (77.278) Prec@5 99.000 (97.222) +2022-11-14 13:26:05,721 Epoch: [40][180/500] Time 0.066 (0.045) Data 0.002 (0.003) Loss 0.1004 (0.1291) Prec@1 81.000 (77.474) Prec@5 96.000 (97.158) +2022-11-14 13:26:06,408 Epoch: [40][190/500] Time 0.064 (0.045) Data 0.003 (0.003) Loss 0.1443 (0.1299) Prec@1 76.000 (77.400) Prec@5 98.000 (97.200) +2022-11-14 13:26:07,121 Epoch: [40][200/500] Time 0.067 (0.046) Data 0.002 (0.003) Loss 0.1178 (0.1293) Prec@1 80.000 (77.524) Prec@5 98.000 (97.238) +2022-11-14 13:26:07,793 Epoch: [40][210/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.1456 (0.1300) Prec@1 76.000 (77.455) Prec@5 96.000 (97.182) +2022-11-14 13:26:08,375 Epoch: [40][220/500] Time 0.047 (0.047) Data 0.003 (0.003) Loss 0.1490 (0.1309) Prec@1 73.000 (77.261) Prec@5 98.000 (97.217) +2022-11-14 13:26:08,774 Epoch: [40][230/500] Time 0.028 (0.047) Data 0.002 (0.003) Loss 0.1148 (0.1302) Prec@1 79.000 (77.333) Prec@5 96.000 (97.167) +2022-11-14 13:26:09,075 Epoch: [40][240/500] Time 0.032 (0.046) Data 0.002 (0.003) Loss 0.1096 (0.1294) Prec@1 83.000 (77.560) Prec@5 99.000 (97.240) +2022-11-14 13:26:09,375 Epoch: [40][250/500] Time 0.027 (0.045) Data 0.002 (0.003) Loss 0.1348 (0.1296) Prec@1 78.000 (77.577) Prec@5 98.000 (97.269) +2022-11-14 13:26:09,742 Epoch: [40][260/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.1256 (0.1294) Prec@1 78.000 (77.593) Prec@5 96.000 (97.222) +2022-11-14 13:26:10,084 Epoch: [40][270/500] Time 0.022 (0.044) Data 0.002 (0.003) Loss 0.1219 (0.1292) Prec@1 77.000 (77.571) Prec@5 99.000 (97.286) +2022-11-14 13:26:10,396 Epoch: [40][280/500] Time 0.026 (0.044) Data 0.002 (0.003) Loss 0.1230 (0.1289) Prec@1 77.000 (77.552) Prec@5 97.000 (97.276) +2022-11-14 13:26:10,701 Epoch: [40][290/500] Time 0.029 (0.043) Data 0.002 (0.003) Loss 0.1371 (0.1292) Prec@1 78.000 (77.567) Prec@5 98.000 (97.300) +2022-11-14 13:26:11,005 Epoch: [40][300/500] Time 0.027 (0.043) Data 0.002 (0.003) Loss 0.1333 (0.1294) Prec@1 75.000 (77.484) Prec@5 98.000 (97.323) +2022-11-14 13:26:11,313 Epoch: [40][310/500] Time 0.027 (0.042) Data 0.002 (0.003) Loss 0.1381 (0.1296) Prec@1 75.000 (77.406) Prec@5 100.000 (97.406) +2022-11-14 13:26:11,693 Epoch: [40][320/500] Time 0.028 (0.042) Data 0.002 (0.003) Loss 0.1282 (0.1296) Prec@1 77.000 (77.394) Prec@5 97.000 (97.394) +2022-11-14 13:26:12,092 Epoch: [40][330/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.1400 (0.1299) Prec@1 74.000 (77.294) Prec@5 97.000 (97.382) +2022-11-14 13:26:12,451 Epoch: [40][340/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.1512 (0.1305) Prec@1 76.000 (77.257) Prec@5 97.000 (97.371) +2022-11-14 13:26:12,859 Epoch: [40][350/500] Time 0.039 (0.041) Data 0.002 (0.003) Loss 0.1448 (0.1309) Prec@1 73.000 (77.139) Prec@5 98.000 (97.389) +2022-11-14 13:26:13,223 Epoch: [40][360/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.1339 (0.1310) Prec@1 78.000 (77.162) Prec@5 98.000 (97.405) +2022-11-14 13:26:13,533 Epoch: [40][370/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.1674 (0.1319) Prec@1 69.000 (76.947) Prec@5 98.000 (97.421) +2022-11-14 13:26:13,835 Epoch: [40][380/500] Time 0.026 (0.040) Data 0.002 (0.003) Loss 0.1487 (0.1324) Prec@1 74.000 (76.872) Prec@5 95.000 (97.359) +2022-11-14 13:26:14,147 Epoch: [40][390/500] Time 0.028 (0.040) Data 0.002 (0.003) Loss 0.1268 (0.1322) Prec@1 80.000 (76.950) Prec@5 97.000 (97.350) +2022-11-14 13:26:14,455 Epoch: [40][400/500] Time 0.029 (0.040) Data 0.002 (0.003) Loss 0.1212 (0.1320) Prec@1 78.000 (76.976) Prec@5 98.000 (97.366) +2022-11-14 13:26:14,849 Epoch: [40][410/500] Time 0.039 (0.039) Data 0.003 (0.003) Loss 0.1043 (0.1313) Prec@1 79.000 (77.024) Prec@5 100.000 (97.429) +2022-11-14 13:26:15,207 Epoch: [40][420/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.1034 (0.1306) Prec@1 84.000 (77.186) Prec@5 98.000 (97.442) +2022-11-14 13:26:15,549 Epoch: [40][430/500] Time 0.055 (0.039) Data 0.003 (0.002) Loss 0.1168 (0.1303) Prec@1 77.000 (77.182) Prec@5 97.000 (97.432) +2022-11-14 13:26:15,956 Epoch: [40][440/500] Time 0.039 (0.039) Data 0.002 (0.002) Loss 0.1183 (0.1301) Prec@1 77.000 (77.178) Prec@5 99.000 (97.467) +2022-11-14 13:26:16,343 Epoch: [40][450/500] Time 0.041 (0.039) Data 0.002 (0.002) Loss 0.1514 (0.1305) Prec@1 75.000 (77.130) Prec@5 93.000 (97.370) +2022-11-14 13:26:16,638 Epoch: [40][460/500] Time 0.026 (0.039) Data 0.002 (0.002) Loss 0.1450 (0.1308) Prec@1 70.000 (76.979) Prec@5 99.000 (97.404) +2022-11-14 13:26:16,978 Epoch: [40][470/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.1856 (0.1320) Prec@1 65.000 (76.729) Prec@5 97.000 (97.396) +2022-11-14 13:26:17,450 Epoch: [40][480/500] Time 0.041 (0.039) Data 0.002 (0.002) Loss 0.1287 (0.1319) Prec@1 77.000 (76.735) Prec@5 98.000 (97.408) +2022-11-14 13:26:17,996 Epoch: [40][490/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.1181 (0.1316) Prec@1 77.000 (76.740) Prec@5 94.000 (97.340) +2022-11-14 13:26:18,445 Epoch: [40][499/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0897 (0.1308) Prec@1 87.000 (76.941) Prec@5 98.000 (97.353) +2022-11-14 13:26:18,742 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.2203 (0.2203) Prec@1 60.000 (60.000) Prec@5 92.000 (92.000) +2022-11-14 13:26:18,750 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2095 (0.2149) Prec@1 61.000 (60.500) Prec@5 93.000 (92.500) +2022-11-14 13:26:18,760 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.2010 (0.2103) Prec@1 64.000 (61.667) Prec@5 94.000 (93.000) +2022-11-14 13:26:18,772 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2252 (0.2140) Prec@1 57.000 (60.500) Prec@5 91.000 (92.500) +2022-11-14 13:26:18,780 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1964 (0.2105) Prec@1 64.000 (61.200) Prec@5 94.000 (92.800) +2022-11-14 13:26:18,788 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1610 (0.2022) Prec@1 69.000 (62.500) Prec@5 98.000 (93.667) +2022-11-14 13:26:18,796 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.2144 (0.2040) Prec@1 63.000 (62.571) Prec@5 92.000 (93.429) +2022-11-14 13:26:18,807 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2256 (0.2067) Prec@1 56.000 (61.750) Prec@5 92.000 (93.250) +2022-11-14 13:26:18,816 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2434 (0.2107) Prec@1 54.000 (60.889) Prec@5 92.000 (93.111) +2022-11-14 13:26:18,826 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1770 (0.2074) Prec@1 68.000 (61.600) Prec@5 95.000 (93.300) +2022-11-14 13:26:18,837 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1548 (0.2026) Prec@1 71.000 (62.455) Prec@5 99.000 (93.818) +2022-11-14 13:26:18,848 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2385 (0.2056) Prec@1 59.000 (62.167) Prec@5 90.000 (93.500) +2022-11-14 13:26:18,858 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2407 (0.2083) Prec@1 55.000 (61.615) Prec@5 90.000 (93.231) +2022-11-14 13:26:18,870 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2101 (0.2084) Prec@1 61.000 (61.571) Prec@5 93.000 (93.214) +2022-11-14 13:26:18,882 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2009 (0.2079) Prec@1 62.000 (61.600) Prec@5 95.000 (93.333) +2022-11-14 13:26:18,893 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2421 (0.2101) Prec@1 57.000 (61.312) Prec@5 93.000 (93.312) +2022-11-14 13:26:18,905 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1817 (0.2084) Prec@1 67.000 (61.647) Prec@5 94.000 (93.353) +2022-11-14 13:26:18,918 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2184 (0.2089) Prec@1 60.000 (61.556) Prec@5 93.000 (93.333) +2022-11-14 13:26:18,928 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2098 (0.2090) Prec@1 59.000 (61.421) Prec@5 93.000 (93.316) +2022-11-14 13:26:18,941 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2271 (0.2099) Prec@1 58.000 (61.250) Prec@5 90.000 (93.150) +2022-11-14 13:26:18,953 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1678 (0.2079) Prec@1 68.000 (61.571) Prec@5 94.000 (93.190) +2022-11-14 13:26:18,966 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2252 (0.2087) Prec@1 54.000 (61.227) Prec@5 95.000 (93.273) +2022-11-14 13:26:18,976 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2181 (0.2091) Prec@1 63.000 (61.304) Prec@5 93.000 (93.261) +2022-11-14 13:26:18,986 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2050 (0.2089) Prec@1 61.000 (61.292) Prec@5 92.000 (93.208) +2022-11-14 13:26:18,995 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2235 (0.2095) Prec@1 59.000 (61.200) Prec@5 95.000 (93.280) +2022-11-14 13:26:19,005 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2550 (0.2113) Prec@1 55.000 (60.962) Prec@5 85.000 (92.962) +2022-11-14 13:26:19,015 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2024 (0.2109) Prec@1 61.000 (60.963) Prec@5 94.000 (93.000) +2022-11-14 13:26:19,028 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2204 (0.2113) Prec@1 60.000 (60.929) Prec@5 93.000 (93.000) +2022-11-14 13:26:19,040 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.2100) Prec@1 70.000 (61.241) Prec@5 91.000 (92.931) +2022-11-14 13:26:19,053 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1981 (0.2096) Prec@1 63.000 (61.300) Prec@5 90.000 (92.833) +2022-11-14 13:26:19,066 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2145 (0.2098) Prec@1 62.000 (61.323) Prec@5 90.000 (92.742) +2022-11-14 13:26:19,080 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1936 (0.2093) Prec@1 66.000 (61.469) Prec@5 95.000 (92.812) +2022-11-14 13:26:19,093 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1796 (0.2084) Prec@1 71.000 (61.758) Prec@5 94.000 (92.848) +2022-11-14 13:26:19,105 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2339 (0.2091) Prec@1 59.000 (61.676) Prec@5 87.000 (92.676) +2022-11-14 13:26:19,116 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1978 (0.2088) Prec@1 63.000 (61.714) Prec@5 90.000 (92.600) +2022-11-14 13:26:19,129 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1689 (0.2077) Prec@1 69.000 (61.917) Prec@5 94.000 (92.639) +2022-11-14 13:26:19,142 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1959 (0.2074) Prec@1 63.000 (61.946) Prec@5 92.000 (92.622) +2022-11-14 13:26:19,155 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2100 (0.2074) Prec@1 61.000 (61.921) Prec@5 94.000 (92.658) +2022-11-14 13:26:19,170 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1840 (0.2068) Prec@1 63.000 (61.949) Prec@5 96.000 (92.744) +2022-11-14 13:26:19,183 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2010 (0.2067) Prec@1 65.000 (62.025) Prec@5 89.000 (92.650) +2022-11-14 13:26:19,195 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2314 (0.2073) Prec@1 55.000 (61.854) Prec@5 90.000 (92.585) +2022-11-14 13:26:19,208 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1796 (0.2066) Prec@1 67.000 (61.976) Prec@5 92.000 (92.571) +2022-11-14 13:26:19,220 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1872 (0.2062) Prec@1 64.000 (62.023) Prec@5 90.000 (92.512) +2022-11-14 13:26:19,231 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1637 (0.2052) Prec@1 72.000 (62.250) Prec@5 92.000 (92.500) +2022-11-14 13:26:19,244 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1991 (0.2051) Prec@1 62.000 (62.244) Prec@5 94.000 (92.533) +2022-11-14 13:26:19,256 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2087 (0.2052) Prec@1 60.000 (62.196) Prec@5 90.000 (92.478) +2022-11-14 13:26:19,268 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2152 (0.2054) Prec@1 59.000 (62.128) Prec@5 93.000 (92.489) +2022-11-14 13:26:19,279 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2078 (0.2054) Prec@1 63.000 (62.146) Prec@5 91.000 (92.458) +2022-11-14 13:26:19,291 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1861 (0.2050) Prec@1 67.000 (62.245) Prec@5 92.000 (92.449) +2022-11-14 13:26:19,303 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2148 (0.2052) Prec@1 64.000 (62.280) Prec@5 87.000 (92.340) +2022-11-14 13:26:19,314 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1986 (0.2051) Prec@1 66.000 (62.353) Prec@5 88.000 (92.255) +2022-11-14 13:26:19,326 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2193 (0.2054) Prec@1 59.000 (62.288) Prec@5 87.000 (92.154) +2022-11-14 13:26:19,339 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.2405 (0.2060) Prec@1 51.000 (62.075) Prec@5 92.000 (92.151) +2022-11-14 13:26:19,351 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2099 (0.2061) Prec@1 61.000 (62.056) Prec@5 90.000 (92.111) +2022-11-14 13:26:19,364 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2041 (0.2061) Prec@1 63.000 (62.073) Prec@5 92.000 (92.109) +2022-11-14 13:26:19,375 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2022 (0.2060) Prec@1 65.000 (62.125) Prec@5 95.000 (92.161) +2022-11-14 13:26:19,385 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2334 (0.2065) Prec@1 56.000 (62.018) Prec@5 91.000 (92.140) +2022-11-14 13:26:19,397 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2007 (0.2064) Prec@1 61.000 (62.000) Prec@5 96.000 (92.207) +2022-11-14 13:26:19,409 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2335 (0.2068) Prec@1 57.000 (61.915) Prec@5 86.000 (92.102) +2022-11-14 13:26:19,421 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2174 (0.2070) Prec@1 61.000 (61.900) Prec@5 94.000 (92.133) +2022-11-14 13:26:19,432 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2127 (0.2071) Prec@1 63.000 (61.918) Prec@5 89.000 (92.082) +2022-11-14 13:26:19,444 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1959 (0.2069) Prec@1 63.000 (61.935) Prec@5 93.000 (92.097) +2022-11-14 13:26:19,456 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1860 (0.2066) Prec@1 64.000 (61.968) Prec@5 94.000 (92.127) +2022-11-14 13:26:19,466 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2016 (0.2065) Prec@1 63.000 (61.984) Prec@5 94.000 (92.156) +2022-11-14 13:26:19,479 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2410 (0.2071) Prec@1 59.000 (61.938) Prec@5 92.000 (92.154) +2022-11-14 13:26:19,490 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2040 (0.2070) Prec@1 64.000 (61.970) Prec@5 94.000 (92.182) +2022-11-14 13:26:19,501 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2071 (0.2070) Prec@1 61.000 (61.955) Prec@5 91.000 (92.164) +2022-11-14 13:26:19,514 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1957 (0.2068) Prec@1 68.000 (62.044) Prec@5 93.000 (92.176) +2022-11-14 13:26:19,526 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1741 (0.2064) Prec@1 68.000 (62.130) Prec@5 96.000 (92.232) +2022-11-14 13:26:19,537 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2254 (0.2066) Prec@1 65.000 (62.171) Prec@5 90.000 (92.200) +2022-11-14 13:26:19,549 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2173 (0.2068) Prec@1 64.000 (62.197) Prec@5 93.000 (92.211) +2022-11-14 13:26:19,562 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2030 (0.2067) Prec@1 62.000 (62.194) Prec@5 94.000 (92.236) +2022-11-14 13:26:19,574 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1717 (0.2063) Prec@1 69.000 (62.288) Prec@5 98.000 (92.315) +2022-11-14 13:26:19,585 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1816 (0.2059) Prec@1 68.000 (62.365) Prec@5 95.000 (92.351) +2022-11-14 13:26:19,597 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2246 (0.2062) Prec@1 58.000 (62.307) Prec@5 91.000 (92.333) +2022-11-14 13:26:19,609 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1869 (0.2059) Prec@1 68.000 (62.382) Prec@5 95.000 (92.368) +2022-11-14 13:26:19,621 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2272 (0.2062) Prec@1 59.000 (62.338) Prec@5 93.000 (92.377) +2022-11-14 13:26:19,634 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1917 (0.2060) Prec@1 64.000 (62.359) Prec@5 93.000 (92.385) +2022-11-14 13:26:19,647 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1878 (0.2058) Prec@1 62.000 (62.354) Prec@5 97.000 (92.443) +2022-11-14 13:26:19,658 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1899 (0.2056) Prec@1 69.000 (62.438) Prec@5 92.000 (92.438) +2022-11-14 13:26:19,668 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2109 (0.2056) Prec@1 62.000 (62.432) Prec@5 91.000 (92.420) +2022-11-14 13:26:19,681 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1986 (0.2056) Prec@1 58.000 (62.378) Prec@5 90.000 (92.390) +2022-11-14 13:26:19,693 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2144 (0.2057) Prec@1 61.000 (62.361) Prec@5 97.000 (92.446) +2022-11-14 13:26:19,705 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2211 (0.2059) Prec@1 60.000 (62.333) Prec@5 91.000 (92.429) +2022-11-14 13:26:19,717 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2131 (0.2059) Prec@1 57.000 (62.271) Prec@5 91.000 (92.412) +2022-11-14 13:26:19,729 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2020 (0.2059) Prec@1 62.000 (62.267) Prec@5 92.000 (92.407) +2022-11-14 13:26:19,741 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2381 (0.2063) Prec@1 59.000 (62.230) Prec@5 90.000 (92.379) +2022-11-14 13:26:19,752 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2078 (0.2063) Prec@1 60.000 (62.205) Prec@5 94.000 (92.398) +2022-11-14 13:26:19,764 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1950 (0.2062) Prec@1 68.000 (62.270) Prec@5 95.000 (92.427) +2022-11-14 13:26:19,776 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2106 (0.2062) Prec@1 58.000 (62.222) Prec@5 88.000 (92.378) +2022-11-14 13:26:19,788 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2100 (0.2062) Prec@1 61.000 (62.209) Prec@5 97.000 (92.429) +2022-11-14 13:26:19,800 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1719 (0.2059) Prec@1 73.000 (62.326) Prec@5 93.000 (92.435) +2022-11-14 13:26:19,813 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2172 (0.2060) Prec@1 65.000 (62.355) Prec@5 94.000 (92.452) +2022-11-14 13:26:19,825 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2170 (0.2061) Prec@1 59.000 (62.319) Prec@5 92.000 (92.447) +2022-11-14 13:26:19,837 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2118 (0.2062) Prec@1 61.000 (62.305) Prec@5 92.000 (92.442) +2022-11-14 13:26:19,848 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1798 (0.2059) Prec@1 65.000 (62.333) Prec@5 95.000 (92.469) +2022-11-14 13:26:19,861 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1679 (0.2055) Prec@1 71.000 (62.423) Prec@5 95.000 (92.495) +2022-11-14 13:26:19,873 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2406 (0.2059) Prec@1 55.000 (62.347) Prec@5 82.000 (92.388) +2022-11-14 13:26:19,885 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.2016 (0.2058) Prec@1 66.000 (62.384) Prec@5 91.000 (92.374) +2022-11-14 13:26:19,898 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.2291 (0.2060) Prec@1 54.000 (62.300) Prec@5 92.000 (92.370) +2022-11-14 13:26:19,966 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:26:20,285 Epoch: [41][0/500] Time 0.026 (0.026) Data 0.229 (0.229) Loss 0.1309 (0.1309) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:26:20,519 Epoch: [41][10/500] Time 0.018 (0.021) Data 0.002 (0.022) Loss 0.1015 (0.1162) Prec@1 79.000 (79.000) Prec@5 99.000 (98.500) +2022-11-14 13:26:20,762 Epoch: [41][20/500] Time 0.023 (0.022) Data 0.002 (0.013) Loss 0.1389 (0.1238) Prec@1 79.000 (79.000) Prec@5 98.000 (98.333) +2022-11-14 13:26:20,989 Epoch: [41][30/500] Time 0.018 (0.021) Data 0.002 (0.009) Loss 0.0937 (0.1162) Prec@1 81.000 (79.500) Prec@5 99.000 (98.500) +2022-11-14 13:26:21,357 Epoch: [41][40/500] Time 0.034 (0.024) Data 0.002 (0.007) Loss 0.1241 (0.1178) Prec@1 79.000 (79.400) Prec@5 96.000 (98.000) +2022-11-14 13:26:21,753 Epoch: [41][50/500] Time 0.030 (0.026) Data 0.001 (0.006) Loss 0.1320 (0.1202) Prec@1 79.000 (79.333) Prec@5 97.000 (97.833) +2022-11-14 13:26:22,143 Epoch: [41][60/500] Time 0.037 (0.028) Data 0.002 (0.006) Loss 0.1001 (0.1173) Prec@1 83.000 (79.857) Prec@5 99.000 (98.000) +2022-11-14 13:26:22,536 Epoch: [41][70/500] Time 0.036 (0.028) Data 0.002 (0.005) Loss 0.1096 (0.1163) Prec@1 83.000 (80.250) Prec@5 97.000 (97.875) +2022-11-14 13:26:22,976 Epoch: [41][80/500] Time 0.030 (0.030) Data 0.002 (0.005) Loss 0.0786 (0.1121) Prec@1 88.000 (81.111) Prec@5 100.000 (98.111) +2022-11-14 13:26:23,457 Epoch: [41][90/500] Time 0.028 (0.031) Data 0.002 (0.004) Loss 0.1628 (0.1172) Prec@1 73.000 (80.300) Prec@5 99.000 (98.200) +2022-11-14 13:26:23,834 Epoch: [41][100/500] Time 0.035 (0.032) Data 0.002 (0.004) Loss 0.1207 (0.1175) Prec@1 79.000 (80.182) Prec@5 99.000 (98.273) +2022-11-14 13:26:24,236 Epoch: [41][110/500] Time 0.033 (0.032) Data 0.002 (0.004) Loss 0.1139 (0.1172) Prec@1 79.000 (80.083) Prec@5 97.000 (98.167) +2022-11-14 13:26:24,660 Epoch: [41][120/500] Time 0.033 (0.033) Data 0.002 (0.004) Loss 0.1590 (0.1204) Prec@1 74.000 (79.615) Prec@5 97.000 (98.077) +2022-11-14 13:26:25,062 Epoch: [41][130/500] Time 0.030 (0.033) Data 0.002 (0.004) Loss 0.1265 (0.1209) Prec@1 79.000 (79.571) Prec@5 99.000 (98.143) +2022-11-14 13:26:25,531 Epoch: [41][140/500] Time 0.049 (0.033) Data 0.002 (0.004) Loss 0.0693 (0.1174) Prec@1 89.000 (80.200) Prec@5 100.000 (98.267) +2022-11-14 13:26:25,929 Epoch: [41][150/500] Time 0.030 (0.034) Data 0.002 (0.003) Loss 0.1262 (0.1180) Prec@1 75.000 (79.875) Prec@5 97.000 (98.188) +2022-11-14 13:26:26,347 Epoch: [41][160/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.1042 (0.1172) Prec@1 81.000 (79.941) Prec@5 100.000 (98.294) +2022-11-14 13:26:26,741 Epoch: [41][170/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1361 (0.1182) Prec@1 75.000 (79.667) Prec@5 96.000 (98.167) +2022-11-14 13:26:27,168 Epoch: [41][180/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.1050 (0.1175) Prec@1 83.000 (79.842) Prec@5 99.000 (98.211) +2022-11-14 13:26:27,596 Epoch: [41][190/500] Time 0.055 (0.034) Data 0.003 (0.003) Loss 0.0961 (0.1165) Prec@1 84.000 (80.050) Prec@5 96.000 (98.100) +2022-11-14 13:26:27,961 Epoch: [41][200/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0975 (0.1156) Prec@1 84.000 (80.238) Prec@5 97.000 (98.048) +2022-11-14 13:26:28,346 Epoch: [41][210/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1070 (0.1152) Prec@1 82.000 (80.318) Prec@5 100.000 (98.136) +2022-11-14 13:26:28,732 Epoch: [41][220/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0791 (0.1136) Prec@1 85.000 (80.522) Prec@5 100.000 (98.217) +2022-11-14 13:26:29,116 Epoch: [41][230/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.1080 (0.1134) Prec@1 82.000 (80.583) Prec@5 98.000 (98.208) +2022-11-14 13:26:29,498 Epoch: [41][240/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1519 (0.1149) Prec@1 73.000 (80.280) Prec@5 99.000 (98.240) +2022-11-14 13:26:29,891 Epoch: [41][250/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1089 (0.1147) Prec@1 78.000 (80.192) Prec@5 99.000 (98.269) +2022-11-14 13:26:30,282 Epoch: [41][260/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.1227 (0.1150) Prec@1 79.000 (80.148) Prec@5 99.000 (98.296) +2022-11-14 13:26:30,672 Epoch: [41][270/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1195 (0.1151) Prec@1 77.000 (80.036) Prec@5 97.000 (98.250) +2022-11-14 13:26:31,060 Epoch: [41][280/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0901 (0.1143) Prec@1 83.000 (80.138) Prec@5 99.000 (98.276) +2022-11-14 13:26:31,452 Epoch: [41][290/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.1066 (0.1140) Prec@1 82.000 (80.200) Prec@5 100.000 (98.333) +2022-11-14 13:26:31,966 Epoch: [41][300/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.1196 (0.1142) Prec@1 78.000 (80.129) Prec@5 98.000 (98.323) +2022-11-14 13:26:32,451 Epoch: [41][310/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.1005 (0.1138) Prec@1 82.000 (80.188) Prec@5 100.000 (98.375) +2022-11-14 13:26:32,910 Epoch: [41][320/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.1058 (0.1135) Prec@1 77.000 (80.091) Prec@5 99.000 (98.394) +2022-11-14 13:26:33,405 Epoch: [41][330/500] Time 0.049 (0.036) Data 0.002 (0.003) Loss 0.0963 (0.1130) Prec@1 82.000 (80.147) Prec@5 100.000 (98.441) +2022-11-14 13:26:33,878 Epoch: [41][340/500] Time 0.047 (0.036) Data 0.003 (0.003) Loss 0.0949 (0.1125) Prec@1 86.000 (80.314) Prec@5 99.000 (98.457) +2022-11-14 13:26:34,343 Epoch: [41][350/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.1129 (0.1125) Prec@1 82.000 (80.361) Prec@5 98.000 (98.444) +2022-11-14 13:26:34,719 Epoch: [41][360/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.1037 (0.1123) Prec@1 82.000 (80.405) Prec@5 96.000 (98.378) +2022-11-14 13:26:35,167 Epoch: [41][370/500] Time 0.056 (0.036) Data 0.003 (0.003) Loss 0.1122 (0.1123) Prec@1 80.000 (80.395) Prec@5 97.000 (98.342) +2022-11-14 13:26:35,641 Epoch: [41][380/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.1134 (0.1123) Prec@1 78.000 (80.333) Prec@5 97.000 (98.308) +2022-11-14 13:26:36,081 Epoch: [41][390/500] Time 0.048 (0.036) Data 0.003 (0.003) Loss 0.1073 (0.1122) Prec@1 81.000 (80.350) Prec@5 99.000 (98.325) +2022-11-14 13:26:36,529 Epoch: [41][400/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0910 (0.1117) Prec@1 83.000 (80.415) Prec@5 100.000 (98.366) +2022-11-14 13:26:37,019 Epoch: [41][410/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.1232 (0.1119) Prec@1 77.000 (80.333) Prec@5 98.000 (98.357) +2022-11-14 13:26:37,445 Epoch: [41][420/500] Time 0.030 (0.036) Data 0.002 (0.003) Loss 0.1252 (0.1122) Prec@1 75.000 (80.209) Prec@5 96.000 (98.302) +2022-11-14 13:26:37,859 Epoch: [41][430/500] Time 0.034 (0.036) Data 0.003 (0.003) Loss 0.1048 (0.1121) Prec@1 85.000 (80.318) Prec@5 100.000 (98.341) +2022-11-14 13:26:38,289 Epoch: [41][440/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.1346 (0.1126) Prec@1 73.000 (80.156) Prec@5 98.000 (98.333) +2022-11-14 13:26:38,775 Epoch: [41][450/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.1322 (0.1130) Prec@1 76.000 (80.065) Prec@5 98.000 (98.326) +2022-11-14 13:26:39,259 Epoch: [41][460/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0879 (0.1125) Prec@1 85.000 (80.170) Prec@5 99.000 (98.340) +2022-11-14 13:26:39,749 Epoch: [41][470/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.1440 (0.1131) Prec@1 74.000 (80.042) Prec@5 98.000 (98.333) +2022-11-14 13:26:40,245 Epoch: [41][480/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0988 (0.1128) Prec@1 82.000 (80.082) Prec@5 98.000 (98.327) +2022-11-14 13:26:40,678 Epoch: [41][490/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1011 (0.1126) Prec@1 84.000 (80.160) Prec@5 99.000 (98.340) +2022-11-14 13:26:41,141 Epoch: [41][499/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.0888 (0.1121) Prec@1 85.000 (80.255) Prec@5 95.000 (98.275) +2022-11-14 13:26:41,472 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1351 (0.1351) Prec@1 75.000 (75.000) Prec@5 99.000 (99.000) +2022-11-14 13:26:41,481 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1208 (0.1279) Prec@1 80.000 (77.500) Prec@5 98.000 (98.500) +2022-11-14 13:26:41,493 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1221 (0.1260) Prec@1 79.000 (78.000) Prec@5 99.000 (98.667) +2022-11-14 13:26:41,507 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1456 (0.1309) Prec@1 75.000 (77.250) Prec@5 98.000 (98.500) +2022-11-14 13:26:41,517 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1341 (0.1315) Prec@1 75.000 (76.800) Prec@5 100.000 (98.800) +2022-11-14 13:26:41,529 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.1214) Prec@1 88.000 (78.667) Prec@5 99.000 (98.833) +2022-11-14 13:26:41,540 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1134 (0.1203) Prec@1 83.000 (79.286) Prec@5 100.000 (99.000) +2022-11-14 13:26:41,555 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1621 (0.1255) Prec@1 73.000 (78.500) Prec@5 98.000 (98.875) +2022-11-14 13:26:41,567 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1563 (0.1289) Prec@1 73.000 (77.889) Prec@5 99.000 (98.889) +2022-11-14 13:26:41,579 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1274 (0.1288) Prec@1 75.000 (77.600) Prec@5 99.000 (98.900) +2022-11-14 13:26:41,592 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1147 (0.1275) Prec@1 78.000 (77.636) Prec@5 100.000 (99.000) +2022-11-14 13:26:41,606 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1420 (0.1287) Prec@1 74.000 (77.333) Prec@5 98.000 (98.917) +2022-11-14 13:26:41,623 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1448 (0.1299) Prec@1 72.000 (76.923) Prec@5 100.000 (99.000) +2022-11-14 13:26:41,638 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1216 (0.1294) Prec@1 78.000 (77.000) Prec@5 93.000 (98.571) +2022-11-14 13:26:41,652 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1232 (0.1289) Prec@1 81.000 (77.267) Prec@5 98.000 (98.533) +2022-11-14 13:26:41,665 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1809 (0.1322) Prec@1 64.000 (76.438) Prec@5 98.000 (98.500) +2022-11-14 13:26:41,679 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.1300) Prec@1 80.000 (76.647) Prec@5 97.000 (98.412) +2022-11-14 13:26:41,693 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1579 (0.1316) Prec@1 72.000 (76.389) Prec@5 98.000 (98.389) +2022-11-14 13:26:41,706 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1399 (0.1320) Prec@1 74.000 (76.263) Prec@5 98.000 (98.368) +2022-11-14 13:26:41,721 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1453 (0.1327) Prec@1 75.000 (76.200) Prec@5 99.000 (98.400) +2022-11-14 13:26:41,735 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1430 (0.1332) Prec@1 74.000 (76.095) Prec@5 100.000 (98.476) +2022-11-14 13:26:41,749 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1280 (0.1329) Prec@1 76.000 (76.091) Prec@5 97.000 (98.409) +2022-11-14 13:26:41,763 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1185 (0.1323) Prec@1 80.000 (76.261) Prec@5 96.000 (98.304) +2022-11-14 13:26:41,780 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1230 (0.1319) Prec@1 78.000 (76.333) Prec@5 99.000 (98.333) +2022-11-14 13:26:41,795 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1353 (0.1321) Prec@1 77.000 (76.360) Prec@5 99.000 (98.360) +2022-11-14 13:26:41,811 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1416 (0.1324) Prec@1 74.000 (76.269) Prec@5 97.000 (98.308) +2022-11-14 13:26:41,825 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.1319) Prec@1 80.000 (76.407) Prec@5 100.000 (98.370) +2022-11-14 13:26:41,840 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1366 (0.1321) Prec@1 76.000 (76.393) Prec@5 99.000 (98.393) +2022-11-14 13:26:41,853 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1340 (0.1321) Prec@1 76.000 (76.379) Prec@5 95.000 (98.276) +2022-11-14 13:26:41,868 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1105 (0.1314) Prec@1 81.000 (76.533) Prec@5 98.000 (98.267) +2022-11-14 13:26:41,884 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1320) Prec@1 73.000 (76.419) Prec@5 96.000 (98.194) +2022-11-14 13:26:41,898 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1349 (0.1321) Prec@1 76.000 (76.406) Prec@5 98.000 (98.188) +2022-11-14 13:26:41,912 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1335 (0.1321) Prec@1 74.000 (76.333) Prec@5 96.000 (98.121) +2022-11-14 13:26:41,928 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1538 (0.1327) Prec@1 75.000 (76.294) Prec@5 99.000 (98.147) +2022-11-14 13:26:41,944 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.1323) Prec@1 77.000 (76.314) Prec@5 97.000 (98.114) +2022-11-14 13:26:41,958 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1376 (0.1324) Prec@1 77.000 (76.333) Prec@5 98.000 (98.111) +2022-11-14 13:26:41,974 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1777 (0.1336) Prec@1 67.000 (76.081) Prec@5 98.000 (98.108) +2022-11-14 13:26:41,989 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1485 (0.1340) Prec@1 74.000 (76.026) Prec@5 100.000 (98.158) +2022-11-14 13:26:42,004 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.1331) Prec@1 82.000 (76.179) Prec@5 98.000 (98.154) +2022-11-14 13:26:42,020 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1394 (0.1333) Prec@1 77.000 (76.200) Prec@5 99.000 (98.175) +2022-11-14 13:26:42,036 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1350 (0.1333) Prec@1 75.000 (76.171) Prec@5 98.000 (98.171) +2022-11-14 13:26:42,051 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1329 (0.1333) Prec@1 76.000 (76.167) Prec@5 99.000 (98.190) +2022-11-14 13:26:42,066 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.1324) Prec@1 81.000 (76.279) Prec@5 99.000 (98.209) +2022-11-14 13:26:42,081 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.1319) Prec@1 84.000 (76.455) Prec@5 95.000 (98.136) +2022-11-14 13:26:42,093 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1352 (0.1320) Prec@1 76.000 (76.444) Prec@5 97.000 (98.111) +2022-11-14 13:26:42,108 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1668 (0.1327) Prec@1 69.000 (76.283) Prec@5 99.000 (98.130) +2022-11-14 13:26:42,122 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.1322) Prec@1 80.000 (76.362) Prec@5 100.000 (98.170) +2022-11-14 13:26:42,138 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1360 (0.1323) Prec@1 78.000 (76.396) Prec@5 96.000 (98.125) +2022-11-14 13:26:42,154 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.1322) Prec@1 79.000 (76.449) Prec@5 98.000 (98.122) +2022-11-14 13:26:42,169 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1516 (0.1326) Prec@1 73.000 (76.380) Prec@5 98.000 (98.120) +2022-11-14 13:26:42,184 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.1324) Prec@1 78.000 (76.412) Prec@5 98.000 (98.118) +2022-11-14 13:26:42,200 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.1322) Prec@1 76.000 (76.404) Prec@5 99.000 (98.135) +2022-11-14 13:26:42,214 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1252 (0.1321) Prec@1 78.000 (76.434) Prec@5 100.000 (98.170) +2022-11-14 13:26:42,227 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1330 (0.1321) Prec@1 75.000 (76.407) Prec@5 98.000 (98.167) +2022-11-14 13:26:42,242 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1317) Prec@1 79.000 (76.455) Prec@5 100.000 (98.200) +2022-11-14 13:26:42,256 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1507 (0.1320) Prec@1 75.000 (76.429) Prec@5 95.000 (98.143) +2022-11-14 13:26:42,271 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1396 (0.1322) Prec@1 73.000 (76.368) Prec@5 98.000 (98.140) +2022-11-14 13:26:42,287 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.1319) Prec@1 79.000 (76.414) Prec@5 100.000 (98.172) +2022-11-14 13:26:42,303 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1319) Prec@1 76.000 (76.407) Prec@5 100.000 (98.203) +2022-11-14 13:26:42,319 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1475 (0.1322) Prec@1 75.000 (76.383) Prec@5 96.000 (98.167) +2022-11-14 13:26:42,333 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1319) Prec@1 80.000 (76.443) Prec@5 98.000 (98.164) +2022-11-14 13:26:42,347 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1258 (0.1318) Prec@1 79.000 (76.484) Prec@5 98.000 (98.161) +2022-11-14 13:26:42,364 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1152 (0.1316) Prec@1 81.000 (76.556) Prec@5 96.000 (98.127) +2022-11-14 13:26:42,381 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.1316) Prec@1 78.000 (76.578) Prec@5 99.000 (98.141) +2022-11-14 13:26:42,395 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1321) Prec@1 69.000 (76.462) Prec@5 99.000 (98.154) +2022-11-14 13:26:42,407 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1476 (0.1324) Prec@1 73.000 (76.409) Prec@5 97.000 (98.136) +2022-11-14 13:26:42,422 Test: [66/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1205 (0.1322) Prec@1 80.000 (76.463) Prec@5 97.000 (98.119) +2022-11-14 13:26:42,437 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1459 (0.1324) Prec@1 74.000 (76.426) Prec@5 97.000 (98.103) +2022-11-14 13:26:42,452 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.1321) Prec@1 80.000 (76.478) Prec@5 97.000 (98.087) +2022-11-14 13:26:42,467 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1489 (0.1323) Prec@1 75.000 (76.457) Prec@5 100.000 (98.114) +2022-11-14 13:26:42,483 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.1322) Prec@1 79.000 (76.493) Prec@5 99.000 (98.127) +2022-11-14 13:26:42,500 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1426 (0.1323) Prec@1 74.000 (76.458) Prec@5 98.000 (98.125) +2022-11-14 13:26:42,514 Test: [72/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1215 (0.1322) Prec@1 81.000 (76.521) Prec@5 98.000 (98.123) +2022-11-14 13:26:42,528 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1277 (0.1321) Prec@1 80.000 (76.568) Prec@5 99.000 (98.135) +2022-11-14 13:26:42,543 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1392 (0.1322) Prec@1 77.000 (76.573) Prec@5 99.000 (98.147) +2022-11-14 13:26:42,557 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1212 (0.1321) Prec@1 82.000 (76.645) Prec@5 98.000 (98.145) +2022-11-14 13:26:42,572 Test: [76/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1277 (0.1320) Prec@1 77.000 (76.649) Prec@5 98.000 (98.143) +2022-11-14 13:26:42,589 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.1318) Prec@1 78.000 (76.667) Prec@5 99.000 (98.154) +2022-11-14 13:26:42,602 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.1316) Prec@1 80.000 (76.709) Prec@5 100.000 (98.177) +2022-11-14 13:26:42,616 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1266 (0.1315) Prec@1 76.000 (76.700) Prec@5 98.000 (98.175) +2022-11-14 13:26:42,630 Test: [80/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1262 (0.1314) Prec@1 78.000 (76.716) Prec@5 97.000 (98.160) +2022-11-14 13:26:42,644 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1277 (0.1314) Prec@1 78.000 (76.732) Prec@5 99.000 (98.171) +2022-11-14 13:26:42,660 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1473 (0.1316) Prec@1 71.000 (76.663) Prec@5 99.000 (98.181) +2022-11-14 13:26:42,675 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1442 (0.1317) Prec@1 75.000 (76.643) Prec@5 100.000 (98.202) +2022-11-14 13:26:42,690 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1452 (0.1319) Prec@1 75.000 (76.624) Prec@5 95.000 (98.165) +2022-11-14 13:26:42,706 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1715 (0.1324) Prec@1 72.000 (76.570) Prec@5 98.000 (98.163) +2022-11-14 13:26:42,721 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1471 (0.1325) Prec@1 72.000 (76.517) Prec@5 98.000 (98.161) +2022-11-14 13:26:42,738 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1362 (0.1326) Prec@1 80.000 (76.557) Prec@5 99.000 (98.170) +2022-11-14 13:26:42,755 Test: [88/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1196 (0.1324) Prec@1 80.000 (76.596) Prec@5 97.000 (98.157) +2022-11-14 13:26:42,772 Test: [89/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.1322) Prec@1 83.000 (76.667) Prec@5 100.000 (98.178) +2022-11-14 13:26:42,788 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1244 (0.1321) Prec@1 79.000 (76.692) Prec@5 99.000 (98.187) +2022-11-14 13:26:42,805 Test: [91/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.1319) Prec@1 82.000 (76.750) Prec@5 99.000 (98.196) +2022-11-14 13:26:42,819 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1824 (0.1324) Prec@1 68.000 (76.656) Prec@5 100.000 (98.215) +2022-11-14 13:26:42,835 Test: [93/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1376 (0.1325) Prec@1 74.000 (76.628) Prec@5 99.000 (98.223) +2022-11-14 13:26:42,851 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.1323) Prec@1 81.000 (76.674) Prec@5 99.000 (98.232) +2022-11-14 13:26:42,865 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.1320) Prec@1 82.000 (76.729) Prec@5 98.000 (98.229) +2022-11-14 13:26:42,879 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1186 (0.1319) Prec@1 81.000 (76.773) Prec@5 99.000 (98.237) +2022-11-14 13:26:42,894 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1616 (0.1322) Prec@1 71.000 (76.714) Prec@5 99.000 (98.245) +2022-11-14 13:26:42,908 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1574 (0.1324) Prec@1 74.000 (76.687) Prec@5 99.000 (98.253) +2022-11-14 13:26:42,922 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1452 (0.1326) Prec@1 73.000 (76.650) Prec@5 97.000 (98.240) +2022-11-14 13:26:42,997 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:26:43,332 Epoch: [42][0/500] Time 0.027 (0.027) Data 0.233 (0.233) Loss 0.1150 (0.1150) Prec@1 77.000 (77.000) Prec@5 97.000 (97.000) +2022-11-14 13:26:43,795 Epoch: [42][10/500] Time 0.049 (0.040) Data 0.002 (0.023) Loss 0.0932 (0.1041) Prec@1 81.000 (79.000) Prec@5 99.000 (98.000) +2022-11-14 13:26:44,298 Epoch: [42][20/500] Time 0.048 (0.042) Data 0.002 (0.013) Loss 0.1031 (0.1037) Prec@1 84.000 (80.667) Prec@5 98.000 (98.000) +2022-11-14 13:26:44,676 Epoch: [42][30/500] Time 0.033 (0.039) Data 0.002 (0.010) Loss 0.1051 (0.1041) Prec@1 81.000 (80.750) Prec@5 97.000 (97.750) +2022-11-14 13:26:45,064 Epoch: [42][40/500] Time 0.031 (0.038) Data 0.003 (0.008) Loss 0.1178 (0.1068) Prec@1 76.000 (79.800) Prec@5 99.000 (98.000) +2022-11-14 13:26:45,477 Epoch: [42][50/500] Time 0.033 (0.038) Data 0.002 (0.007) Loss 0.1023 (0.1061) Prec@1 80.000 (79.833) Prec@5 96.000 (97.667) +2022-11-14 13:26:45,874 Epoch: [42][60/500] Time 0.037 (0.037) Data 0.002 (0.006) Loss 0.1300 (0.1095) Prec@1 78.000 (79.571) Prec@5 98.000 (97.714) +2022-11-14 13:26:46,257 Epoch: [42][70/500] Time 0.035 (0.037) Data 0.002 (0.005) Loss 0.1231 (0.1112) Prec@1 81.000 (79.750) Prec@5 96.000 (97.500) +2022-11-14 13:26:46,651 Epoch: [42][80/500] Time 0.035 (0.037) Data 0.002 (0.005) Loss 0.0885 (0.1087) Prec@1 84.000 (80.222) Prec@5 99.000 (97.667) +2022-11-14 13:26:47,111 Epoch: [42][90/500] Time 0.047 (0.037) Data 0.002 (0.005) Loss 0.0929 (0.1071) Prec@1 82.000 (80.400) Prec@5 100.000 (97.900) +2022-11-14 13:26:47,611 Epoch: [42][100/500] Time 0.053 (0.038) Data 0.002 (0.004) Loss 0.1063 (0.1070) Prec@1 83.000 (80.636) Prec@5 96.000 (97.727) +2022-11-14 13:26:48,002 Epoch: [42][110/500] Time 0.041 (0.038) Data 0.002 (0.004) Loss 0.0913 (0.1057) Prec@1 84.000 (80.917) Prec@5 98.000 (97.750) +2022-11-14 13:26:48,400 Epoch: [42][120/500] Time 0.037 (0.037) Data 0.002 (0.004) Loss 0.0767 (0.1035) Prec@1 84.000 (81.154) Prec@5 100.000 (97.923) +2022-11-14 13:26:48,893 Epoch: [42][130/500] Time 0.042 (0.038) Data 0.002 (0.004) Loss 0.0838 (0.1021) Prec@1 88.000 (81.643) Prec@5 100.000 (98.071) +2022-11-14 13:26:49,380 Epoch: [42][140/500] Time 0.045 (0.038) Data 0.002 (0.004) Loss 0.1116 (0.1027) Prec@1 84.000 (81.800) Prec@5 98.000 (98.067) +2022-11-14 13:26:49,861 Epoch: [42][150/500] Time 0.050 (0.039) Data 0.002 (0.004) Loss 0.1224 (0.1039) Prec@1 76.000 (81.438) Prec@5 99.000 (98.125) +2022-11-14 13:26:50,285 Epoch: [42][160/500] Time 0.033 (0.039) Data 0.002 (0.004) Loss 0.1293 (0.1054) Prec@1 77.000 (81.176) Prec@5 100.000 (98.235) +2022-11-14 13:26:50,723 Epoch: [42][170/500] Time 0.064 (0.039) Data 0.002 (0.003) Loss 0.0947 (0.1048) Prec@1 83.000 (81.278) Prec@5 99.000 (98.278) +2022-11-14 13:26:51,115 Epoch: [42][180/500] Time 0.031 (0.038) Data 0.002 (0.003) Loss 0.0744 (0.1032) Prec@1 87.000 (81.579) Prec@5 99.000 (98.316) +2022-11-14 13:26:51,566 Epoch: [42][190/500] Time 0.054 (0.038) Data 0.002 (0.003) Loss 0.0905 (0.1026) Prec@1 84.000 (81.700) Prec@5 98.000 (98.300) +2022-11-14 13:26:51,964 Epoch: [42][200/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.1060 (0.1028) Prec@1 78.000 (81.524) Prec@5 98.000 (98.286) +2022-11-14 13:26:52,352 Epoch: [42][210/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.1151 (0.1033) Prec@1 82.000 (81.545) Prec@5 99.000 (98.318) +2022-11-14 13:26:52,783 Epoch: [42][220/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.1263 (0.1043) Prec@1 76.000 (81.304) Prec@5 97.000 (98.261) +2022-11-14 13:26:53,223 Epoch: [42][230/500] Time 0.061 (0.038) Data 0.002 (0.003) Loss 0.1026 (0.1042) Prec@1 82.000 (81.333) Prec@5 99.000 (98.292) +2022-11-14 13:26:53,682 Epoch: [42][240/500] Time 0.024 (0.038) Data 0.002 (0.003) Loss 0.1016 (0.1041) Prec@1 79.000 (81.240) Prec@5 99.000 (98.320) +2022-11-14 13:26:54,063 Epoch: [42][250/500] Time 0.039 (0.038) Data 0.001 (0.003) Loss 0.1087 (0.1043) Prec@1 79.000 (81.154) Prec@5 98.000 (98.308) +2022-11-14 13:26:54,496 Epoch: [42][260/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.1055 (0.1044) Prec@1 79.000 (81.074) Prec@5 97.000 (98.259) +2022-11-14 13:26:54,893 Epoch: [42][270/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0854 (0.1037) Prec@1 83.000 (81.143) Prec@5 98.000 (98.250) +2022-11-14 13:26:55,278 Epoch: [42][280/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.1139 (0.1040) Prec@1 75.000 (80.931) Prec@5 98.000 (98.241) +2022-11-14 13:26:55,736 Epoch: [42][290/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.1003 (0.1039) Prec@1 83.000 (81.000) Prec@5 99.000 (98.267) +2022-11-14 13:26:56,253 Epoch: [42][300/500] Time 0.054 (0.038) Data 0.002 (0.003) Loss 0.1268 (0.1046) Prec@1 78.000 (80.903) Prec@5 97.000 (98.226) +2022-11-14 13:26:56,674 Epoch: [42][310/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.1014 (0.1045) Prec@1 83.000 (80.969) Prec@5 99.000 (98.250) +2022-11-14 13:26:57,065 Epoch: [42][320/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.1067 (0.1046) Prec@1 84.000 (81.061) Prec@5 97.000 (98.212) +2022-11-14 13:26:57,469 Epoch: [42][330/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0999 (0.1045) Prec@1 84.000 (81.147) Prec@5 99.000 (98.235) +2022-11-14 13:26:57,874 Epoch: [42][340/500] Time 0.034 (0.038) Data 0.003 (0.003) Loss 0.1151 (0.1048) Prec@1 80.000 (81.114) Prec@5 99.000 (98.257) +2022-11-14 13:26:58,265 Epoch: [42][350/500] Time 0.028 (0.038) Data 0.003 (0.003) Loss 0.1207 (0.1052) Prec@1 78.000 (81.028) Prec@5 97.000 (98.222) +2022-11-14 13:26:58,655 Epoch: [42][360/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0972 (0.1050) Prec@1 83.000 (81.081) Prec@5 100.000 (98.270) +2022-11-14 13:26:59,052 Epoch: [42][370/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.1236 (0.1055) Prec@1 76.000 (80.947) Prec@5 100.000 (98.316) +2022-11-14 13:26:59,528 Epoch: [42][380/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1175 (0.1058) Prec@1 82.000 (80.974) Prec@5 99.000 (98.333) +2022-11-14 13:26:59,962 Epoch: [42][390/500] Time 0.029 (0.038) Data 0.003 (0.003) Loss 0.1173 (0.1061) Prec@1 81.000 (80.975) Prec@5 99.000 (98.350) +2022-11-14 13:27:00,465 Epoch: [42][400/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.1052 (0.1061) Prec@1 83.000 (81.024) Prec@5 98.000 (98.341) +2022-11-14 13:27:00,918 Epoch: [42][410/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.1497 (0.1071) Prec@1 76.000 (80.905) Prec@5 97.000 (98.310) +2022-11-14 13:27:01,360 Epoch: [42][420/500] Time 0.061 (0.038) Data 0.002 (0.003) Loss 0.0611 (0.1060) Prec@1 93.000 (81.186) Prec@5 100.000 (98.349) +2022-11-14 13:27:01,856 Epoch: [42][430/500] Time 0.048 (0.038) Data 0.002 (0.003) Loss 0.1097 (0.1061) Prec@1 81.000 (81.182) Prec@5 96.000 (98.295) +2022-11-14 13:27:02,260 Epoch: [42][440/500] Time 0.056 (0.038) Data 0.002 (0.003) Loss 0.1128 (0.1063) Prec@1 76.000 (81.067) Prec@5 99.000 (98.311) +2022-11-14 13:27:02,767 Epoch: [42][450/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0908 (0.1059) Prec@1 84.000 (81.130) Prec@5 99.000 (98.326) +2022-11-14 13:27:03,261 Epoch: [42][460/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0923 (0.1056) Prec@1 83.000 (81.170) Prec@5 100.000 (98.362) +2022-11-14 13:27:03,681 Epoch: [42][470/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0880 (0.1053) Prec@1 85.000 (81.250) Prec@5 97.000 (98.333) +2022-11-14 13:27:04,093 Epoch: [42][480/500] Time 0.053 (0.038) Data 0.002 (0.003) Loss 0.0926 (0.1050) Prec@1 80.000 (81.224) Prec@5 99.000 (98.347) +2022-11-14 13:27:04,492 Epoch: [42][490/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.1052 (0.1050) Prec@1 81.000 (81.220) Prec@5 100.000 (98.380) +2022-11-14 13:27:04,849 Epoch: [42][499/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0996 (0.1049) Prec@1 85.000 (81.294) Prec@5 100.000 (98.412) +2022-11-14 13:27:05,162 Test: [0/100] Model Time 0.018 (0.018) Loss Time 0.000 (0.000) Loss 0.0943 (0.0943) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:27:05,172 Test: [1/100] Model Time 0.008 (0.013) Loss Time 0.000 (0.000) Loss 0.1090 (0.1016) Prec@1 81.000 (82.500) Prec@5 98.000 (98.500) +2022-11-14 13:27:05,183 Test: [2/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1128 (0.1054) Prec@1 81.000 (82.000) Prec@5 97.000 (98.000) +2022-11-14 13:27:05,197 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1197 (0.1090) Prec@1 77.000 (80.750) Prec@5 100.000 (98.500) +2022-11-14 13:27:05,210 Test: [4/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1076 (0.1087) Prec@1 80.000 (80.600) Prec@5 100.000 (98.800) +2022-11-14 13:27:05,221 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0856 (0.1048) Prec@1 83.000 (81.000) Prec@5 99.000 (98.833) +2022-11-14 13:27:05,234 Test: [6/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1253 (0.1078) Prec@1 78.000 (80.571) Prec@5 99.000 (98.857) +2022-11-14 13:27:05,245 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1221 (0.1096) Prec@1 81.000 (80.625) Prec@5 97.000 (98.625) +2022-11-14 13:27:05,260 Test: [8/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1283 (0.1116) Prec@1 77.000 (80.222) Prec@5 98.000 (98.556) +2022-11-14 13:27:05,271 Test: [9/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1298 (0.1134) Prec@1 76.000 (79.800) Prec@5 99.000 (98.600) +2022-11-14 13:27:05,281 Test: [10/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0955 (0.1118) Prec@1 82.000 (80.000) Prec@5 99.000 (98.636) +2022-11-14 13:27:05,292 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1257 (0.1130) Prec@1 79.000 (79.917) Prec@5 97.000 (98.500) +2022-11-14 13:27:05,305 Test: [12/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0979 (0.1118) Prec@1 84.000 (80.231) Prec@5 100.000 (98.615) +2022-11-14 13:27:05,320 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1136 (0.1119) Prec@1 81.000 (80.286) Prec@5 99.000 (98.643) +2022-11-14 13:27:05,336 Test: [14/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1214 (0.1126) Prec@1 80.000 (80.267) Prec@5 99.000 (98.667) +2022-11-14 13:27:05,352 Test: [15/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1247 (0.1133) Prec@1 79.000 (80.188) Prec@5 98.000 (98.625) +2022-11-14 13:27:05,367 Test: [16/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0994 (0.1125) Prec@1 82.000 (80.294) Prec@5 98.000 (98.588) +2022-11-14 13:27:05,384 Test: [17/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1160 (0.1127) Prec@1 81.000 (80.333) Prec@5 100.000 (98.667) +2022-11-14 13:27:05,398 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1328 (0.1138) Prec@1 79.000 (80.263) Prec@5 94.000 (98.421) +2022-11-14 13:27:05,412 Test: [19/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1330 (0.1147) Prec@1 78.000 (80.150) Prec@5 97.000 (98.350) +2022-11-14 13:27:05,427 Test: [20/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1314 (0.1155) Prec@1 75.000 (79.905) Prec@5 97.000 (98.286) +2022-11-14 13:27:05,441 Test: [21/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1315 (0.1162) Prec@1 75.000 (79.682) Prec@5 100.000 (98.364) +2022-11-14 13:27:05,456 Test: [22/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1266 (0.1167) Prec@1 77.000 (79.565) Prec@5 98.000 (98.348) +2022-11-14 13:27:05,470 Test: [23/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1016 (0.1161) Prec@1 81.000 (79.625) Prec@5 100.000 (98.417) +2022-11-14 13:27:05,484 Test: [24/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1254 (0.1164) Prec@1 78.000 (79.560) Prec@5 98.000 (98.400) +2022-11-14 13:27:05,498 Test: [25/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1426 (0.1174) Prec@1 73.000 (79.308) Prec@5 96.000 (98.308) +2022-11-14 13:27:05,514 Test: [26/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1316 (0.1180) Prec@1 78.000 (79.259) Prec@5 99.000 (98.333) +2022-11-14 13:27:05,529 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1040 (0.1175) Prec@1 80.000 (79.286) Prec@5 99.000 (98.357) +2022-11-14 13:27:05,544 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1251 (0.1177) Prec@1 77.000 (79.207) Prec@5 98.000 (98.345) +2022-11-14 13:27:05,560 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1058 (0.1173) Prec@1 82.000 (79.300) Prec@5 98.000 (98.333) +2022-11-14 13:27:05,574 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1177 (0.1173) Prec@1 80.000 (79.323) Prec@5 98.000 (98.323) +2022-11-14 13:27:05,588 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1032 (0.1169) Prec@1 81.000 (79.375) Prec@5 100.000 (98.375) +2022-11-14 13:27:05,602 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1385 (0.1176) Prec@1 74.000 (79.212) Prec@5 97.000 (98.333) +2022-11-14 13:27:05,616 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1623 (0.1189) Prec@1 73.000 (79.029) Prec@5 98.000 (98.324) +2022-11-14 13:27:05,631 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1147 (0.1188) Prec@1 80.000 (79.057) Prec@5 97.000 (98.286) +2022-11-14 13:27:05,645 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.1183) Prec@1 86.000 (79.250) Prec@5 96.000 (98.222) +2022-11-14 13:27:05,659 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1325 (0.1187) Prec@1 77.000 (79.189) Prec@5 96.000 (98.162) +2022-11-14 13:27:05,673 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1273 (0.1189) Prec@1 77.000 (79.132) Prec@5 99.000 (98.184) +2022-11-14 13:27:05,688 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.1179) Prec@1 86.000 (79.308) Prec@5 98.000 (98.179) +2022-11-14 13:27:05,704 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1078 (0.1176) Prec@1 79.000 (79.300) Prec@5 96.000 (98.125) +2022-11-14 13:27:05,720 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1361 (0.1181) Prec@1 75.000 (79.195) Prec@5 99.000 (98.146) +2022-11-14 13:27:05,733 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1163 (0.1181) Prec@1 83.000 (79.286) Prec@5 97.000 (98.119) +2022-11-14 13:27:05,748 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.1173) Prec@1 84.000 (79.395) Prec@5 100.000 (98.163) +2022-11-14 13:27:05,762 Test: [43/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.1168) Prec@1 85.000 (79.523) Prec@5 98.000 (98.159) +2022-11-14 13:27:05,777 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.1163) Prec@1 83.000 (79.600) Prec@5 98.000 (98.156) +2022-11-14 13:27:05,791 Test: [45/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1171 (0.1163) Prec@1 77.000 (79.543) Prec@5 98.000 (98.152) +2022-11-14 13:27:05,807 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1272 (0.1166) Prec@1 78.000 (79.511) Prec@5 98.000 (98.149) +2022-11-14 13:27:05,824 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1371 (0.1170) Prec@1 73.000 (79.375) Prec@5 99.000 (98.167) +2022-11-14 13:27:05,837 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.1165) Prec@1 86.000 (79.510) Prec@5 99.000 (98.184) +2022-11-14 13:27:05,852 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1475 (0.1171) Prec@1 75.000 (79.420) Prec@5 97.000 (98.160) +2022-11-14 13:27:05,866 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0949 (0.1167) Prec@1 81.000 (79.451) Prec@5 99.000 (98.176) +2022-11-14 13:27:05,880 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1171 (0.1167) Prec@1 80.000 (79.462) Prec@5 98.000 (98.173) +2022-11-14 13:27:05,894 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0896 (0.1162) Prec@1 84.000 (79.547) Prec@5 100.000 (98.208) +2022-11-14 13:27:05,908 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1077 (0.1160) Prec@1 82.000 (79.593) Prec@5 99.000 (98.222) +2022-11-14 13:27:05,922 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1213 (0.1161) Prec@1 77.000 (79.545) Prec@5 99.000 (98.236) +2022-11-14 13:27:05,936 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.1161) Prec@1 79.000 (79.536) Prec@5 99.000 (98.250) +2022-11-14 13:27:05,950 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1377 (0.1165) Prec@1 77.000 (79.491) Prec@5 96.000 (98.211) +2022-11-14 13:27:05,964 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1393 (0.1169) Prec@1 77.000 (79.448) Prec@5 98.000 (98.207) +2022-11-14 13:27:05,978 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1410 (0.1173) Prec@1 76.000 (79.390) Prec@5 100.000 (98.237) +2022-11-14 13:27:05,994 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.1172) Prec@1 79.000 (79.383) Prec@5 99.000 (98.250) +2022-11-14 13:27:06,010 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.1172) Prec@1 81.000 (79.410) Prec@5 98.000 (98.246) +2022-11-14 13:27:06,026 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.1170) Prec@1 83.000 (79.468) Prec@5 98.000 (98.242) +2022-11-14 13:27:06,041 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.1165) Prec@1 87.000 (79.587) Prec@5 97.000 (98.222) +2022-11-14 13:27:06,054 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.1166) Prec@1 76.000 (79.531) Prec@5 100.000 (98.250) +2022-11-14 13:27:06,068 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1207 (0.1167) Prec@1 78.000 (79.508) Prec@5 96.000 (98.215) +2022-11-14 13:27:06,082 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1433 (0.1171) Prec@1 73.000 (79.409) Prec@5 100.000 (98.242) +2022-11-14 13:27:06,095 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.1170) Prec@1 84.000 (79.478) Prec@5 99.000 (98.254) +2022-11-14 13:27:06,110 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1385 (0.1173) Prec@1 73.000 (79.382) Prec@5 98.000 (98.250) +2022-11-14 13:27:06,124 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1187 (0.1173) Prec@1 78.000 (79.362) Prec@5 97.000 (98.232) +2022-11-14 13:27:06,138 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1396 (0.1176) Prec@1 73.000 (79.271) Prec@5 99.000 (98.243) +2022-11-14 13:27:06,153 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1175) Prec@1 81.000 (79.296) Prec@5 100.000 (98.268) +2022-11-14 13:27:06,168 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1129 (0.1175) Prec@1 81.000 (79.319) Prec@5 99.000 (98.278) +2022-11-14 13:27:06,185 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.1172) Prec@1 83.000 (79.370) Prec@5 100.000 (98.301) +2022-11-14 13:27:06,200 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.1169) Prec@1 86.000 (79.459) Prec@5 100.000 (98.324) +2022-11-14 13:27:06,215 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1276 (0.1171) Prec@1 79.000 (79.453) Prec@5 97.000 (98.307) +2022-11-14 13:27:06,232 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1169 (0.1171) Prec@1 78.000 (79.434) Prec@5 99.000 (98.316) +2022-11-14 13:27:06,251 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1302 (0.1172) Prec@1 77.000 (79.403) Prec@5 98.000 (98.312) +2022-11-14 13:27:06,268 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.1170) Prec@1 83.000 (79.449) Prec@5 99.000 (98.321) +2022-11-14 13:27:06,282 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.1168) Prec@1 82.000 (79.481) Prec@5 99.000 (98.329) +2022-11-14 13:27:06,298 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.1167) Prec@1 80.000 (79.487) Prec@5 97.000 (98.312) +2022-11-14 13:27:06,313 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1197 (0.1167) Prec@1 79.000 (79.481) Prec@5 97.000 (98.296) +2022-11-14 13:27:06,328 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1016 (0.1166) Prec@1 82.000 (79.512) Prec@5 100.000 (98.317) +2022-11-14 13:27:06,343 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1346 (0.1168) Prec@1 74.000 (79.446) Prec@5 98.000 (98.313) +2022-11-14 13:27:06,358 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1214 (0.1168) Prec@1 76.000 (79.405) Prec@5 98.000 (98.310) +2022-11-14 13:27:06,372 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1375 (0.1171) Prec@1 76.000 (79.365) Prec@5 97.000 (98.294) +2022-11-14 13:27:06,386 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1442 (0.1174) Prec@1 71.000 (79.267) Prec@5 97.000 (98.279) +2022-11-14 13:27:06,400 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1192 (0.1174) Prec@1 77.000 (79.241) Prec@5 99.000 (98.287) +2022-11-14 13:27:06,414 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1186 (0.1174) Prec@1 80.000 (79.250) Prec@5 96.000 (98.261) +2022-11-14 13:27:06,431 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1174) Prec@1 78.000 (79.236) Prec@5 98.000 (98.258) +2022-11-14 13:27:06,447 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1163 (0.1174) Prec@1 80.000 (79.244) Prec@5 99.000 (98.267) +2022-11-14 13:27:06,463 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1222 (0.1174) Prec@1 80.000 (79.253) Prec@5 100.000 (98.286) +2022-11-14 13:27:06,478 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.1169) Prec@1 90.000 (79.370) Prec@5 99.000 (98.293) +2022-11-14 13:27:06,492 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1379 (0.1171) Prec@1 76.000 (79.333) Prec@5 98.000 (98.290) +2022-11-14 13:27:06,506 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1309 (0.1172) Prec@1 78.000 (79.319) Prec@5 98.000 (98.287) +2022-11-14 13:27:06,520 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1124 (0.1172) Prec@1 79.000 (79.316) Prec@5 99.000 (98.295) +2022-11-14 13:27:06,534 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.1171) Prec@1 79.000 (79.312) Prec@5 97.000 (98.281) +2022-11-14 13:27:06,548 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.1168) Prec@1 83.000 (79.351) Prec@5 100.000 (98.299) +2022-11-14 13:27:06,562 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1761 (0.1174) Prec@1 69.000 (79.245) Prec@5 99.000 (98.306) +2022-11-14 13:27:06,576 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1335 (0.1176) Prec@1 79.000 (79.242) Prec@5 98.000 (98.303) +2022-11-14 13:27:06,593 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1242 (0.1177) Prec@1 80.000 (79.250) Prec@5 98.000 (98.300) +2022-11-14 13:27:06,654 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:27:06,975 Epoch: [43][0/500] Time 0.025 (0.025) Data 0.235 (0.235) Loss 0.1055 (0.1055) Prec@1 77.000 (77.000) Prec@5 99.000 (99.000) +2022-11-14 13:27:07,391 Epoch: [43][10/500] Time 0.052 (0.036) Data 0.002 (0.023) Loss 0.0942 (0.0999) Prec@1 84.000 (80.500) Prec@5 96.000 (97.500) +2022-11-14 13:27:07,876 Epoch: [43][20/500] Time 0.049 (0.040) Data 0.002 (0.013) Loss 0.0723 (0.0907) Prec@1 87.000 (82.667) Prec@5 100.000 (98.333) +2022-11-14 13:27:08,292 Epoch: [43][30/500] Time 0.033 (0.039) Data 0.002 (0.009) Loss 0.1306 (0.1006) Prec@1 79.000 (81.750) Prec@5 100.000 (98.750) +2022-11-14 13:27:08,691 Epoch: [43][40/500] Time 0.038 (0.038) Data 0.002 (0.008) Loss 0.0931 (0.0991) Prec@1 83.000 (82.000) Prec@5 99.000 (98.800) +2022-11-14 13:27:09,080 Epoch: [43][50/500] Time 0.035 (0.037) Data 0.003 (0.007) Loss 0.1136 (0.1015) Prec@1 80.000 (81.667) Prec@5 99.000 (98.833) +2022-11-14 13:27:09,489 Epoch: [43][60/500] Time 0.030 (0.037) Data 0.002 (0.006) Loss 0.1018 (0.1016) Prec@1 80.000 (81.429) Prec@5 100.000 (99.000) +2022-11-14 13:27:09,876 Epoch: [43][70/500] Time 0.036 (0.037) Data 0.002 (0.005) Loss 0.1259 (0.1046) Prec@1 77.000 (80.875) Prec@5 98.000 (98.875) +2022-11-14 13:27:10,277 Epoch: [43][80/500] Time 0.037 (0.037) Data 0.001 (0.005) Loss 0.1466 (0.1093) Prec@1 74.000 (80.111) Prec@5 97.000 (98.667) +2022-11-14 13:27:10,663 Epoch: [43][90/500] Time 0.035 (0.036) Data 0.002 (0.005) Loss 0.1007 (0.1084) Prec@1 83.000 (80.400) Prec@5 98.000 (98.600) +2022-11-14 13:27:11,062 Epoch: [43][100/500] Time 0.036 (0.036) Data 0.001 (0.004) Loss 0.0945 (0.1072) Prec@1 82.000 (80.545) Prec@5 98.000 (98.545) +2022-11-14 13:27:11,459 Epoch: [43][110/500] Time 0.045 (0.036) Data 0.002 (0.004) Loss 0.0972 (0.1063) Prec@1 83.000 (80.750) Prec@5 99.000 (98.583) +2022-11-14 13:27:11,951 Epoch: [43][120/500] Time 0.045 (0.037) Data 0.002 (0.004) Loss 0.1532 (0.1099) Prec@1 71.000 (80.000) Prec@5 99.000 (98.615) +2022-11-14 13:27:12,436 Epoch: [43][130/500] Time 0.048 (0.037) Data 0.002 (0.004) Loss 0.1153 (0.1103) Prec@1 79.000 (79.929) Prec@5 97.000 (98.500) +2022-11-14 13:27:12,932 Epoch: [43][140/500] Time 0.046 (0.038) Data 0.002 (0.004) Loss 0.0759 (0.1080) Prec@1 87.000 (80.400) Prec@5 99.000 (98.533) +2022-11-14 13:27:13,425 Epoch: [43][150/500] Time 0.052 (0.038) Data 0.002 (0.004) Loss 0.1061 (0.1079) Prec@1 79.000 (80.312) Prec@5 97.000 (98.438) +2022-11-14 13:27:13,879 Epoch: [43][160/500] Time 0.027 (0.038) Data 0.002 (0.003) Loss 0.1200 (0.1086) Prec@1 76.000 (80.059) Prec@5 99.000 (98.471) +2022-11-14 13:27:14,263 Epoch: [43][170/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0970 (0.1080) Prec@1 83.000 (80.222) Prec@5 99.000 (98.500) +2022-11-14 13:27:14,685 Epoch: [43][180/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0869 (0.1069) Prec@1 84.000 (80.421) Prec@5 99.000 (98.526) +2022-11-14 13:27:15,191 Epoch: [43][190/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.1309 (0.1081) Prec@1 78.000 (80.300) Prec@5 98.000 (98.500) +2022-11-14 13:27:15,685 Epoch: [43][200/500] Time 0.042 (0.039) Data 0.003 (0.003) Loss 0.1113 (0.1082) Prec@1 77.000 (80.143) Prec@5 98.000 (98.476) +2022-11-14 13:27:16,178 Epoch: [43][210/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.1318 (0.1093) Prec@1 75.000 (79.909) Prec@5 97.000 (98.409) +2022-11-14 13:27:16,607 Epoch: [43][220/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.1260 (0.1100) Prec@1 77.000 (79.783) Prec@5 100.000 (98.478) +2022-11-14 13:27:17,002 Epoch: [43][230/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.1074 (0.1099) Prec@1 80.000 (79.792) Prec@5 98.000 (98.458) +2022-11-14 13:27:17,387 Epoch: [43][240/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.1296 (0.1107) Prec@1 78.000 (79.720) Prec@5 99.000 (98.480) +2022-11-14 13:27:17,795 Epoch: [43][250/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.1140 (0.1108) Prec@1 79.000 (79.692) Prec@5 97.000 (98.423) +2022-11-14 13:27:18,194 Epoch: [43][260/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0761 (0.1095) Prec@1 87.000 (79.963) Prec@5 99.000 (98.444) +2022-11-14 13:27:18,587 Epoch: [43][270/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.1172 (0.1098) Prec@1 81.000 (80.000) Prec@5 99.000 (98.464) +2022-11-14 13:27:18,984 Epoch: [43][280/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0929 (0.1092) Prec@1 84.000 (80.138) Prec@5 100.000 (98.517) +2022-11-14 13:27:19,428 Epoch: [43][290/500] Time 0.031 (0.038) Data 0.002 (0.003) Loss 0.1347 (0.1101) Prec@1 76.000 (80.000) Prec@5 97.000 (98.467) +2022-11-14 13:27:19,836 Epoch: [43][300/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0952 (0.1096) Prec@1 86.000 (80.194) Prec@5 100.000 (98.516) +2022-11-14 13:27:20,269 Epoch: [43][310/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.1103 (0.1096) Prec@1 81.000 (80.219) Prec@5 98.000 (98.500) +2022-11-14 13:27:20,678 Epoch: [43][320/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.1186 (0.1099) Prec@1 82.000 (80.273) Prec@5 99.000 (98.515) +2022-11-14 13:27:21,086 Epoch: [43][330/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.1160 (0.1101) Prec@1 82.000 (80.324) Prec@5 99.000 (98.529) +2022-11-14 13:27:21,479 Epoch: [43][340/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.1007 (0.1098) Prec@1 85.000 (80.457) Prec@5 99.000 (98.543) +2022-11-14 13:27:21,915 Epoch: [43][350/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0909 (0.1093) Prec@1 82.000 (80.500) Prec@5 98.000 (98.528) +2022-11-14 13:27:22,302 Epoch: [43][360/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.1010 (0.1091) Prec@1 83.000 (80.568) Prec@5 98.000 (98.514) +2022-11-14 13:27:22,752 Epoch: [43][370/500] Time 0.057 (0.038) Data 0.002 (0.003) Loss 0.0881 (0.1085) Prec@1 86.000 (80.711) Prec@5 100.000 (98.553) +2022-11-14 13:27:23,185 Epoch: [43][380/500] Time 0.048 (0.038) Data 0.002 (0.003) Loss 0.1438 (0.1094) Prec@1 75.000 (80.564) Prec@5 96.000 (98.487) +2022-11-14 13:27:23,556 Epoch: [43][390/500] Time 0.037 (0.038) Data 0.001 (0.003) Loss 0.1099 (0.1094) Prec@1 80.000 (80.550) Prec@5 97.000 (98.450) +2022-11-14 13:27:23,948 Epoch: [43][400/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.1427 (0.1102) Prec@1 74.000 (80.390) Prec@5 95.000 (98.366) +2022-11-14 13:27:24,358 Epoch: [43][410/500] Time 0.031 (0.038) Data 0.002 (0.003) Loss 0.1062 (0.1101) Prec@1 82.000 (80.429) Prec@5 98.000 (98.357) +2022-11-14 13:27:24,750 Epoch: [43][420/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.1180 (0.1103) Prec@1 80.000 (80.419) Prec@5 95.000 (98.279) +2022-11-14 13:27:25,223 Epoch: [43][430/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0841 (0.1097) Prec@1 88.000 (80.591) Prec@5 99.000 (98.295) +2022-11-14 13:27:25,734 Epoch: [43][440/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.1324 (0.1102) Prec@1 80.000 (80.578) Prec@5 99.000 (98.311) +2022-11-14 13:27:26,121 Epoch: [43][450/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.1172 (0.1104) Prec@1 79.000 (80.543) Prec@5 100.000 (98.348) +2022-11-14 13:27:26,522 Epoch: [43][460/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.1172 (0.1105) Prec@1 78.000 (80.489) Prec@5 98.000 (98.340) +2022-11-14 13:27:26,916 Epoch: [43][470/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.1023 (0.1104) Prec@1 81.000 (80.500) Prec@5 99.000 (98.354) +2022-11-14 13:27:27,326 Epoch: [43][480/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.1614 (0.1114) Prec@1 73.000 (80.347) Prec@5 100.000 (98.388) +2022-11-14 13:27:27,769 Epoch: [43][490/500] Time 0.029 (0.038) Data 0.002 (0.002) Loss 0.1003 (0.1112) Prec@1 86.000 (80.460) Prec@5 99.000 (98.400) +2022-11-14 13:27:28,133 Epoch: [43][499/500] Time 0.037 (0.038) Data 0.001 (0.002) Loss 0.1012 (0.1110) Prec@1 84.000 (80.529) Prec@5 99.000 (98.412) +2022-11-14 13:27:28,412 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0790 (0.0790) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:27:28,420 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0907) Prec@1 81.000 (84.500) Prec@5 100.000 (99.500) +2022-11-14 13:27:28,429 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0931) Prec@1 83.000 (84.000) Prec@5 99.000 (99.333) +2022-11-14 13:27:28,442 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1013) Prec@1 77.000 (82.250) Prec@5 100.000 (99.500) +2022-11-14 13:27:28,453 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0989) Prec@1 86.000 (83.000) Prec@5 97.000 (99.000) +2022-11-14 13:27:28,463 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0944) Prec@1 88.000 (83.833) Prec@5 99.000 (99.000) +2022-11-14 13:27:28,473 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0947) Prec@1 84.000 (83.857) Prec@5 100.000 (99.143) +2022-11-14 13:27:28,490 Test: [7/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.0976) Prec@1 80.000 (83.375) Prec@5 100.000 (99.250) +2022-11-14 13:27:28,503 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1346 (0.1017) Prec@1 75.000 (82.444) Prec@5 98.000 (99.111) +2022-11-14 13:27:28,516 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.1010) Prec@1 84.000 (82.600) Prec@5 97.000 (98.900) +2022-11-14 13:27:28,530 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0997) Prec@1 85.000 (82.818) Prec@5 100.000 (99.000) +2022-11-14 13:27:28,545 Test: [11/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0999) Prec@1 85.000 (83.000) Prec@5 96.000 (98.750) +2022-11-14 13:27:28,559 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1139 (0.1010) Prec@1 81.000 (82.846) Prec@5 100.000 (98.846) +2022-11-14 13:27:28,572 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.1003) Prec@1 85.000 (83.000) Prec@5 99.000 (98.857) +2022-11-14 13:27:28,587 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.1002) Prec@1 83.000 (83.000) Prec@5 98.000 (98.800) +2022-11-14 13:27:28,603 Test: [15/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1356 (0.1024) Prec@1 75.000 (82.500) Prec@5 96.000 (98.625) +2022-11-14 13:27:28,618 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.1020) Prec@1 83.000 (82.529) Prec@5 100.000 (98.706) +2022-11-14 13:27:28,632 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.1027) Prec@1 78.000 (82.278) Prec@5 99.000 (98.722) +2022-11-14 13:27:28,647 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.1035) Prec@1 78.000 (82.053) Prec@5 97.000 (98.632) +2022-11-14 13:27:28,662 Test: [19/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1420 (0.1054) Prec@1 71.000 (81.500) Prec@5 98.000 (98.600) +2022-11-14 13:27:28,675 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1210 (0.1062) Prec@1 81.000 (81.476) Prec@5 98.000 (98.571) +2022-11-14 13:27:28,689 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.1065) Prec@1 83.000 (81.545) Prec@5 99.000 (98.591) +2022-11-14 13:27:28,704 Test: [22/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1180 (0.1070) Prec@1 79.000 (81.435) Prec@5 97.000 (98.522) +2022-11-14 13:27:28,718 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.1064) Prec@1 80.000 (81.375) Prec@5 100.000 (98.583) +2022-11-14 13:27:28,732 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.1064) Prec@1 81.000 (81.360) Prec@5 99.000 (98.600) +2022-11-14 13:27:28,747 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1343 (0.1074) Prec@1 77.000 (81.192) Prec@5 97.000 (98.538) +2022-11-14 13:27:28,761 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1076) Prec@1 84.000 (81.296) Prec@5 100.000 (98.593) +2022-11-14 13:27:28,775 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1166 (0.1079) Prec@1 81.000 (81.286) Prec@5 96.000 (98.500) +2022-11-14 13:27:28,790 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.1072) Prec@1 84.000 (81.379) Prec@5 99.000 (98.517) +2022-11-14 13:27:28,808 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.1076) Prec@1 79.000 (81.300) Prec@5 99.000 (98.533) +2022-11-14 13:27:28,825 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.1074) Prec@1 82.000 (81.323) Prec@5 99.000 (98.548) +2022-11-14 13:27:28,839 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.1075) Prec@1 81.000 (81.312) Prec@5 98.000 (98.531) +2022-11-14 13:27:28,854 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.1071) Prec@1 86.000 (81.455) Prec@5 96.000 (98.455) +2022-11-14 13:27:28,870 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1457 (0.1082) Prec@1 72.000 (81.176) Prec@5 98.000 (98.441) +2022-11-14 13:27:28,886 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1153 (0.1084) Prec@1 80.000 (81.143) Prec@5 96.000 (98.371) +2022-11-14 13:27:28,903 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.1082) Prec@1 84.000 (81.222) Prec@5 99.000 (98.389) +2022-11-14 13:27:28,919 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1094 (0.1082) Prec@1 81.000 (81.216) Prec@5 97.000 (98.351) +2022-11-14 13:27:28,934 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1093 (0.1083) Prec@1 81.000 (81.211) Prec@5 98.000 (98.342) +2022-11-14 13:27:28,948 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.1074) Prec@1 87.000 (81.359) Prec@5 100.000 (98.385) +2022-11-14 13:27:28,962 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.1071) Prec@1 87.000 (81.500) Prec@5 99.000 (98.400) +2022-11-14 13:27:28,979 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.1071) Prec@1 84.000 (81.561) Prec@5 98.000 (98.390) +2022-11-14 13:27:28,996 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.1066) Prec@1 86.000 (81.667) Prec@5 99.000 (98.405) +2022-11-14 13:27:29,013 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.1060) Prec@1 87.000 (81.791) Prec@5 99.000 (98.419) +2022-11-14 13:27:29,029 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.1055) Prec@1 85.000 (81.864) Prec@5 98.000 (98.409) +2022-11-14 13:27:29,045 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.1055) Prec@1 83.000 (81.889) Prec@5 99.000 (98.422) +2022-11-14 13:27:29,061 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1183 (0.1058) Prec@1 80.000 (81.848) Prec@5 100.000 (98.457) +2022-11-14 13:27:29,077 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1105 (0.1059) Prec@1 79.000 (81.787) Prec@5 99.000 (98.468) +2022-11-14 13:27:29,092 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1186 (0.1062) Prec@1 78.000 (81.708) Prec@5 98.000 (98.458) +2022-11-14 13:27:29,108 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.1056) Prec@1 86.000 (81.796) Prec@5 99.000 (98.469) +2022-11-14 13:27:29,124 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1415 (0.1063) Prec@1 75.000 (81.660) Prec@5 99.000 (98.480) +2022-11-14 13:27:29,139 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.1063) Prec@1 81.000 (81.647) Prec@5 97.000 (98.451) +2022-11-14 13:27:29,156 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1287 (0.1067) Prec@1 76.000 (81.538) Prec@5 99.000 (98.462) +2022-11-14 13:27:29,171 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1154 (0.1069) Prec@1 78.000 (81.472) Prec@5 99.000 (98.472) +2022-11-14 13:27:29,187 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.1069) Prec@1 82.000 (81.481) Prec@5 97.000 (98.444) +2022-11-14 13:27:29,204 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.1070) Prec@1 80.000 (81.455) Prec@5 100.000 (98.473) +2022-11-14 13:27:29,221 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.1068) Prec@1 82.000 (81.464) Prec@5 100.000 (98.500) +2022-11-14 13:27:29,238 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1311 (0.1072) Prec@1 77.000 (81.386) Prec@5 98.000 (98.491) +2022-11-14 13:27:29,256 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.1071) Prec@1 83.000 (81.414) Prec@5 99.000 (98.500) +2022-11-14 13:27:29,273 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1175 (0.1073) Prec@1 80.000 (81.390) Prec@5 100.000 (98.525) +2022-11-14 13:27:29,290 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1248 (0.1076) Prec@1 77.000 (81.317) Prec@5 99.000 (98.533) +2022-11-14 13:27:29,305 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1270 (0.1079) Prec@1 76.000 (81.230) Prec@5 100.000 (98.557) +2022-11-14 13:27:29,320 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1319 (0.1083) Prec@1 79.000 (81.194) Prec@5 99.000 (98.565) +2022-11-14 13:27:29,335 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.1079) Prec@1 85.000 (81.254) Prec@5 100.000 (98.587) +2022-11-14 13:27:29,351 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.1075) Prec@1 85.000 (81.312) Prec@5 100.000 (98.609) +2022-11-14 13:27:29,368 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.1077) Prec@1 79.000 (81.277) Prec@5 98.000 (98.600) +2022-11-14 13:27:29,385 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1216 (0.1079) Prec@1 78.000 (81.227) Prec@5 98.000 (98.591) +2022-11-14 13:27:29,401 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.1075) Prec@1 88.000 (81.328) Prec@5 99.000 (98.597) +2022-11-14 13:27:29,416 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1141 (0.1076) Prec@1 79.000 (81.294) Prec@5 100.000 (98.618) +2022-11-14 13:27:29,433 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.1074) Prec@1 85.000 (81.348) Prec@5 97.000 (98.594) +2022-11-14 13:27:29,447 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.1075) Prec@1 82.000 (81.357) Prec@5 97.000 (98.571) +2022-11-14 13:27:29,462 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1136 (0.1076) Prec@1 80.000 (81.338) Prec@5 99.000 (98.577) +2022-11-14 13:27:29,478 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.1076) Prec@1 80.000 (81.319) Prec@5 99.000 (98.583) +2022-11-14 13:27:29,495 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.1075) Prec@1 83.000 (81.342) Prec@5 99.000 (98.589) +2022-11-14 13:27:29,510 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.1073) Prec@1 84.000 (81.378) Prec@5 100.000 (98.608) +2022-11-14 13:27:29,529 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1202 (0.1074) Prec@1 80.000 (81.360) Prec@5 98.000 (98.600) +2022-11-14 13:27:29,545 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.1074) Prec@1 83.000 (81.382) Prec@5 98.000 (98.592) +2022-11-14 13:27:29,561 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.1074) Prec@1 80.000 (81.364) Prec@5 98.000 (98.584) +2022-11-14 13:27:29,578 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1208 (0.1076) Prec@1 77.000 (81.308) Prec@5 97.000 (98.564) +2022-11-14 13:27:29,594 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.1076) Prec@1 80.000 (81.291) Prec@5 100.000 (98.582) +2022-11-14 13:27:29,610 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.1076) Prec@1 77.000 (81.237) Prec@5 98.000 (98.575) +2022-11-14 13:27:29,626 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1213 (0.1078) Prec@1 77.000 (81.185) Prec@5 98.000 (98.568) +2022-11-14 13:27:29,639 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.1078) Prec@1 80.000 (81.171) Prec@5 98.000 (98.561) +2022-11-14 13:27:29,650 Test: [82/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.1078) Prec@1 79.000 (81.145) Prec@5 100.000 (98.578) +2022-11-14 13:27:29,664 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.1079) Prec@1 83.000 (81.167) Prec@5 97.000 (98.560) +2022-11-14 13:27:29,681 Test: [84/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1369 (0.1082) Prec@1 77.000 (81.118) Prec@5 97.000 (98.541) +2022-11-14 13:27:29,697 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1087) Prec@1 74.000 (81.035) Prec@5 96.000 (98.512) +2022-11-14 13:27:29,713 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.1086) Prec@1 83.000 (81.057) Prec@5 98.000 (98.506) +2022-11-14 13:27:29,728 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.1084) Prec@1 85.000 (81.102) Prec@5 98.000 (98.500) +2022-11-14 13:27:29,743 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.1084) Prec@1 78.000 (81.067) Prec@5 99.000 (98.506) +2022-11-14 13:27:29,759 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1093 (0.1085) Prec@1 82.000 (81.078) Prec@5 97.000 (98.489) +2022-11-14 13:27:29,773 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.1085) Prec@1 81.000 (81.077) Prec@5 99.000 (98.495) +2022-11-14 13:27:29,789 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.1082) Prec@1 85.000 (81.120) Prec@5 99.000 (98.500) +2022-11-14 13:27:29,805 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1227 (0.1084) Prec@1 76.000 (81.065) Prec@5 99.000 (98.505) +2022-11-14 13:27:29,820 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.1083) Prec@1 82.000 (81.074) Prec@5 96.000 (98.479) +2022-11-14 13:27:29,835 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.1081) Prec@1 84.000 (81.105) Prec@5 97.000 (98.463) +2022-11-14 13:27:29,850 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.1079) Prec@1 86.000 (81.156) Prec@5 99.000 (98.469) +2022-11-14 13:27:29,865 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.1077) Prec@1 83.000 (81.175) Prec@5 99.000 (98.474) +2022-11-14 13:27:29,883 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1413 (0.1080) Prec@1 74.000 (81.102) Prec@5 99.000 (98.480) +2022-11-14 13:27:29,899 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1306 (0.1083) Prec@1 78.000 (81.071) Prec@5 100.000 (98.495) +2022-11-14 13:27:29,913 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1320 (0.1085) Prec@1 75.000 (81.010) Prec@5 98.000 (98.490) +2022-11-14 13:27:29,968 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:27:30,303 Epoch: [44][0/500] Time 0.035 (0.035) Data 0.236 (0.236) Loss 0.0848 (0.0848) Prec@1 86.000 (86.000) Prec@5 95.000 (95.000) +2022-11-14 13:27:30,658 Epoch: [44][10/500] Time 0.039 (0.031) Data 0.002 (0.023) Loss 0.1089 (0.0968) Prec@1 78.000 (82.000) Prec@5 98.000 (96.500) +2022-11-14 13:27:31,155 Epoch: [44][20/500] Time 0.053 (0.037) Data 0.002 (0.013) Loss 0.0870 (0.0936) Prec@1 86.000 (83.333) Prec@5 98.000 (97.000) +2022-11-14 13:27:31,651 Epoch: [44][30/500] Time 0.049 (0.040) Data 0.002 (0.010) Loss 0.1110 (0.0979) Prec@1 84.000 (83.500) Prec@5 99.000 (97.500) +2022-11-14 13:27:32,050 Epoch: [44][40/500] Time 0.036 (0.038) Data 0.002 (0.008) Loss 0.1038 (0.0991) Prec@1 82.000 (83.200) Prec@5 99.000 (97.800) +2022-11-14 13:27:32,517 Epoch: [44][50/500] Time 0.058 (0.039) Data 0.002 (0.007) Loss 0.0966 (0.0987) Prec@1 82.000 (83.000) Prec@5 98.000 (97.833) +2022-11-14 13:27:33,011 Epoch: [44][60/500] Time 0.046 (0.040) Data 0.002 (0.006) Loss 0.1246 (0.1024) Prec@1 79.000 (82.429) Prec@5 98.000 (97.857) +2022-11-14 13:27:33,379 Epoch: [44][70/500] Time 0.035 (0.039) Data 0.002 (0.005) Loss 0.0979 (0.1018) Prec@1 85.000 (82.750) Prec@5 100.000 (98.125) +2022-11-14 13:27:33,799 Epoch: [44][80/500] Time 0.044 (0.038) Data 0.002 (0.005) Loss 0.1089 (0.1026) Prec@1 83.000 (82.778) Prec@5 96.000 (97.889) +2022-11-14 13:27:34,304 Epoch: [44][90/500] Time 0.047 (0.039) Data 0.002 (0.005) Loss 0.1264 (0.1050) Prec@1 78.000 (82.300) Prec@5 100.000 (98.100) +2022-11-14 13:27:34,757 Epoch: [44][100/500] Time 0.031 (0.039) Data 0.002 (0.004) Loss 0.1079 (0.1053) Prec@1 82.000 (82.273) Prec@5 99.000 (98.182) +2022-11-14 13:27:35,139 Epoch: [44][110/500] Time 0.036 (0.039) Data 0.002 (0.004) Loss 0.0935 (0.1043) Prec@1 86.000 (82.583) Prec@5 100.000 (98.333) +2022-11-14 13:27:35,548 Epoch: [44][120/500] Time 0.032 (0.039) Data 0.002 (0.004) Loss 0.1148 (0.1051) Prec@1 81.000 (82.462) Prec@5 97.000 (98.231) +2022-11-14 13:27:35,984 Epoch: [44][130/500] Time 0.033 (0.039) Data 0.002 (0.004) Loss 0.0867 (0.1038) Prec@1 87.000 (82.786) Prec@5 99.000 (98.286) +2022-11-14 13:27:36,372 Epoch: [44][140/500] Time 0.036 (0.038) Data 0.002 (0.004) Loss 0.0794 (0.1022) Prec@1 87.000 (83.067) Prec@5 99.000 (98.333) +2022-11-14 13:27:36,861 Epoch: [44][150/500] Time 0.063 (0.039) Data 0.002 (0.004) Loss 0.1266 (0.1037) Prec@1 78.000 (82.750) Prec@5 99.000 (98.375) +2022-11-14 13:27:37,344 Epoch: [44][160/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0877 (0.1027) Prec@1 83.000 (82.765) Prec@5 98.000 (98.353) +2022-11-14 13:27:37,798 Epoch: [44][170/500] Time 0.056 (0.039) Data 0.002 (0.003) Loss 0.1332 (0.1044) Prec@1 74.000 (82.278) Prec@5 97.000 (98.278) +2022-11-14 13:27:38,298 Epoch: [44][180/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.1072 (0.1046) Prec@1 83.000 (82.316) Prec@5 99.000 (98.316) +2022-11-14 13:27:38,794 Epoch: [44][190/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.1443 (0.1066) Prec@1 74.000 (81.900) Prec@5 97.000 (98.250) +2022-11-14 13:27:39,294 Epoch: [44][200/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0880 (0.1057) Prec@1 81.000 (81.857) Prec@5 99.000 (98.286) +2022-11-14 13:27:39,720 Epoch: [44][210/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.1099 (0.1059) Prec@1 82.000 (81.864) Prec@5 99.000 (98.318) +2022-11-14 13:27:40,124 Epoch: [44][220/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0843 (0.1049) Prec@1 87.000 (82.087) Prec@5 99.000 (98.348) +2022-11-14 13:27:40,533 Epoch: [44][230/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0818 (0.1040) Prec@1 88.000 (82.333) Prec@5 98.000 (98.333) +2022-11-14 13:27:40,931 Epoch: [44][240/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.1104 (0.1042) Prec@1 77.000 (82.120) Prec@5 99.000 (98.360) +2022-11-14 13:27:41,334 Epoch: [44][250/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.1011 (0.1041) Prec@1 85.000 (82.231) Prec@5 97.000 (98.308) +2022-11-14 13:27:41,730 Epoch: [44][260/500] Time 0.034 (0.039) Data 0.002 (0.003) Loss 0.1342 (0.1052) Prec@1 73.000 (81.889) Prec@5 100.000 (98.370) +2022-11-14 13:27:42,144 Epoch: [44][270/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0965 (0.1049) Prec@1 84.000 (81.964) Prec@5 98.000 (98.357) +2022-11-14 13:27:42,540 Epoch: [44][280/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0599 (0.1034) Prec@1 91.000 (82.276) Prec@5 98.000 (98.345) +2022-11-14 13:27:43,036 Epoch: [44][290/500] Time 0.045 (0.039) Data 0.003 (0.003) Loss 0.1096 (0.1036) Prec@1 80.000 (82.200) Prec@5 98.000 (98.333) +2022-11-14 13:27:43,443 Epoch: [44][300/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.1276 (0.1043) Prec@1 78.000 (82.065) Prec@5 99.000 (98.355) +2022-11-14 13:27:43,915 Epoch: [44][310/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.1255 (0.1050) Prec@1 77.000 (81.906) Prec@5 99.000 (98.375) +2022-11-14 13:27:44,402 Epoch: [44][320/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.1103 (0.1052) Prec@1 81.000 (81.879) Prec@5 96.000 (98.303) +2022-11-14 13:27:44,892 Epoch: [44][330/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0958 (0.1049) Prec@1 84.000 (81.941) Prec@5 98.000 (98.294) +2022-11-14 13:27:45,327 Epoch: [44][340/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.1024 (0.1048) Prec@1 84.000 (82.000) Prec@5 99.000 (98.314) +2022-11-14 13:27:45,695 Epoch: [44][350/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0874 (0.1043) Prec@1 85.000 (82.083) Prec@5 100.000 (98.361) +2022-11-14 13:27:46,088 Epoch: [44][360/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.1199 (0.1048) Prec@1 82.000 (82.081) Prec@5 96.000 (98.297) +2022-11-14 13:27:46,481 Epoch: [44][370/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.1102 (0.1049) Prec@1 82.000 (82.079) Prec@5 98.000 (98.289) +2022-11-14 13:27:46,874 Epoch: [44][380/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.1236 (0.1054) Prec@1 78.000 (81.974) Prec@5 96.000 (98.231) +2022-11-14 13:27:47,280 Epoch: [44][390/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.1110 (0.1055) Prec@1 81.000 (81.950) Prec@5 99.000 (98.250) +2022-11-14 13:27:47,676 Epoch: [44][400/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0985 (0.1054) Prec@1 80.000 (81.902) Prec@5 98.000 (98.244) +2022-11-14 13:27:48,098 Epoch: [44][410/500] Time 0.029 (0.039) Data 0.002 (0.003) Loss 0.1145 (0.1056) Prec@1 80.000 (81.857) Prec@5 100.000 (98.286) +2022-11-14 13:27:48,497 Epoch: [44][420/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.1087 (0.1056) Prec@1 81.000 (81.837) Prec@5 97.000 (98.256) +2022-11-14 13:27:48,908 Epoch: [44][430/500] Time 0.031 (0.038) Data 0.002 (0.003) Loss 0.0953 (0.1054) Prec@1 86.000 (81.932) Prec@5 99.000 (98.273) +2022-11-14 13:27:49,308 Epoch: [44][440/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.1021 (0.1053) Prec@1 82.000 (81.933) Prec@5 96.000 (98.222) +2022-11-14 13:27:49,708 Epoch: [44][450/500] Time 0.036 (0.038) Data 0.002 (0.002) Loss 0.0784 (0.1047) Prec@1 88.000 (82.065) Prec@5 100.000 (98.261) +2022-11-14 13:27:50,117 Epoch: [44][460/500] Time 0.034 (0.038) Data 0.002 (0.002) Loss 0.1204 (0.1051) Prec@1 78.000 (81.979) Prec@5 100.000 (98.298) +2022-11-14 13:27:50,522 Epoch: [44][470/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.1172 (0.1053) Prec@1 78.000 (81.896) Prec@5 97.000 (98.271) +2022-11-14 13:27:50,907 Epoch: [44][480/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0958 (0.1051) Prec@1 83.000 (81.918) Prec@5 99.000 (98.286) +2022-11-14 13:27:51,322 Epoch: [44][490/500] Time 0.035 (0.038) Data 0.002 (0.002) Loss 0.0931 (0.1049) Prec@1 84.000 (81.960) Prec@5 98.000 (98.280) +2022-11-14 13:27:51,674 Epoch: [44][499/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.1209 (0.1052) Prec@1 80.000 (81.922) Prec@5 99.000 (98.294) +2022-11-14 13:27:51,960 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0834 (0.0834) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:27:51,969 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1165 (0.1000) Prec@1 79.000 (81.500) Prec@5 99.000 (99.000) +2022-11-14 13:27:51,983 Test: [2/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1218 (0.1072) Prec@1 80.000 (81.000) Prec@5 96.000 (98.000) +2022-11-14 13:27:51,996 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.1075) Prec@1 82.000 (81.250) Prec@5 98.000 (98.000) +2022-11-14 13:27:52,006 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1226 (0.1105) Prec@1 80.000 (81.000) Prec@5 97.000 (97.800) +2022-11-14 13:27:52,016 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.1068) Prec@1 85.000 (81.667) Prec@5 98.000 (97.833) +2022-11-14 13:27:52,027 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1316 (0.1104) Prec@1 80.000 (81.429) Prec@5 99.000 (98.000) +2022-11-14 13:27:52,039 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1381 (0.1138) Prec@1 75.000 (80.625) Prec@5 99.000 (98.125) +2022-11-14 13:27:52,049 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1374 (0.1165) Prec@1 75.000 (80.000) Prec@5 99.000 (98.222) +2022-11-14 13:27:52,062 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.1146) Prec@1 84.000 (80.400) Prec@5 98.000 (98.200) +2022-11-14 13:27:52,076 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.1131) Prec@1 83.000 (80.636) Prec@5 99.000 (98.273) +2022-11-14 13:27:52,089 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1234 (0.1140) Prec@1 77.000 (80.333) Prec@5 98.000 (98.250) +2022-11-14 13:27:52,102 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1351 (0.1156) Prec@1 77.000 (80.077) Prec@5 99.000 (98.308) +2022-11-14 13:27:52,115 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.1142) Prec@1 86.000 (80.500) Prec@5 98.000 (98.286) +2022-11-14 13:27:52,126 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.1128) Prec@1 84.000 (80.733) Prec@5 99.000 (98.333) +2022-11-14 13:27:52,142 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1616 (0.1159) Prec@1 72.000 (80.188) Prec@5 96.000 (98.188) +2022-11-14 13:27:52,157 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1161) Prec@1 78.000 (80.059) Prec@5 96.000 (98.059) +2022-11-14 13:27:52,170 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.1161) Prec@1 79.000 (80.000) Prec@5 100.000 (98.167) +2022-11-14 13:27:52,184 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1355 (0.1172) Prec@1 78.000 (79.895) Prec@5 95.000 (98.000) +2022-11-14 13:27:52,196 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1441 (0.1185) Prec@1 73.000 (79.550) Prec@5 97.000 (97.950) +2022-11-14 13:27:52,212 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1685 (0.1209) Prec@1 72.000 (79.190) Prec@5 99.000 (98.000) +2022-11-14 13:27:52,226 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.1200) Prec@1 84.000 (79.409) Prec@5 96.000 (97.909) +2022-11-14 13:27:52,238 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1226 (0.1201) Prec@1 78.000 (79.348) Prec@5 97.000 (97.870) +2022-11-14 13:27:52,252 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1193) Prec@1 81.000 (79.417) Prec@5 99.000 (97.917) +2022-11-14 13:27:52,267 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1192) Prec@1 79.000 (79.400) Prec@5 99.000 (97.960) +2022-11-14 13:27:52,282 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1199) Prec@1 80.000 (79.423) Prec@5 97.000 (97.923) +2022-11-14 13:27:52,298 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1195) Prec@1 79.000 (79.407) Prec@5 100.000 (98.000) +2022-11-14 13:27:52,314 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1374 (0.1202) Prec@1 76.000 (79.286) Prec@5 98.000 (98.000) +2022-11-14 13:27:52,330 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1267 (0.1204) Prec@1 76.000 (79.172) Prec@5 98.000 (98.000) +2022-11-14 13:27:52,345 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.1200) Prec@1 85.000 (79.367) Prec@5 95.000 (97.900) +2022-11-14 13:27:52,359 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.1200) Prec@1 78.000 (79.323) Prec@5 97.000 (97.871) +2022-11-14 13:27:52,373 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.1195) Prec@1 82.000 (79.406) Prec@5 100.000 (97.938) +2022-11-14 13:27:52,388 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.1195) Prec@1 80.000 (79.424) Prec@5 95.000 (97.848) +2022-11-14 13:27:52,401 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1364 (0.1200) Prec@1 76.000 (79.324) Prec@5 98.000 (97.853) +2022-11-14 13:27:52,416 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.1191) Prec@1 86.000 (79.514) Prec@5 97.000 (97.829) +2022-11-14 13:27:52,430 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.1187) Prec@1 84.000 (79.639) Prec@5 98.000 (97.833) +2022-11-14 13:27:52,446 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1268 (0.1190) Prec@1 78.000 (79.595) Prec@5 97.000 (97.811) +2022-11-14 13:27:52,462 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1284 (0.1192) Prec@1 79.000 (79.579) Prec@5 98.000 (97.816) +2022-11-14 13:27:52,479 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.1193) Prec@1 78.000 (79.538) Prec@5 100.000 (97.872) +2022-11-14 13:27:52,496 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.1186) Prec@1 83.000 (79.625) Prec@5 97.000 (97.850) +2022-11-14 13:27:52,512 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1281 (0.1188) Prec@1 76.000 (79.537) Prec@5 97.000 (97.829) +2022-11-14 13:27:52,526 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1262 (0.1190) Prec@1 75.000 (79.429) Prec@5 100.000 (97.881) +2022-11-14 13:27:52,539 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.1182) Prec@1 86.000 (79.581) Prec@5 98.000 (97.884) +2022-11-14 13:27:52,553 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1179) Prec@1 85.000 (79.705) Prec@5 95.000 (97.818) +2022-11-14 13:27:52,566 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.1178) Prec@1 80.000 (79.711) Prec@5 98.000 (97.822) +2022-11-14 13:27:52,579 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1422 (0.1183) Prec@1 76.000 (79.630) Prec@5 99.000 (97.848) +2022-11-14 13:27:52,592 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1187) Prec@1 76.000 (79.553) Prec@5 97.000 (97.830) +2022-11-14 13:27:52,606 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1186) Prec@1 78.000 (79.521) Prec@5 96.000 (97.792) +2022-11-14 13:27:52,620 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.1182) Prec@1 82.000 (79.571) Prec@5 98.000 (97.796) +2022-11-14 13:27:52,636 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1428 (0.1187) Prec@1 71.000 (79.400) Prec@5 98.000 (97.800) +2022-11-14 13:27:52,654 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1179 (0.1187) Prec@1 80.000 (79.412) Prec@5 98.000 (97.804) +2022-11-14 13:27:52,670 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1331 (0.1189) Prec@1 75.000 (79.327) Prec@5 99.000 (97.827) +2022-11-14 13:27:52,686 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1189) Prec@1 77.000 (79.283) Prec@5 99.000 (97.849) +2022-11-14 13:27:52,700 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.1186) Prec@1 85.000 (79.389) Prec@5 99.000 (97.870) +2022-11-14 13:27:52,717 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.1188) Prec@1 77.000 (79.345) Prec@5 100.000 (97.909) +2022-11-14 13:27:52,732 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1186) Prec@1 81.000 (79.375) Prec@5 98.000 (97.911) +2022-11-14 13:27:52,747 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1185) Prec@1 83.000 (79.439) Prec@5 98.000 (97.912) +2022-11-14 13:27:52,762 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1230 (0.1186) Prec@1 78.000 (79.414) Prec@5 97.000 (97.897) +2022-11-14 13:27:52,777 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1412 (0.1190) Prec@1 76.000 (79.356) Prec@5 99.000 (97.915) +2022-11-14 13:27:52,792 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1283 (0.1191) Prec@1 76.000 (79.300) Prec@5 99.000 (97.933) +2022-11-14 13:27:52,808 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.1191) Prec@1 81.000 (79.328) Prec@5 98.000 (97.934) +2022-11-14 13:27:52,823 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1193) Prec@1 76.000 (79.274) Prec@5 97.000 (97.919) +2022-11-14 13:27:52,837 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1192) Prec@1 83.000 (79.333) Prec@5 100.000 (97.952) +2022-11-14 13:27:52,849 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.1188) Prec@1 85.000 (79.422) Prec@5 100.000 (97.984) +2022-11-14 13:27:52,864 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1262 (0.1189) Prec@1 80.000 (79.431) Prec@5 97.000 (97.969) +2022-11-14 13:27:52,878 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1767 (0.1198) Prec@1 69.000 (79.273) Prec@5 99.000 (97.985) +2022-11-14 13:27:52,896 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.1191) Prec@1 88.000 (79.403) Prec@5 98.000 (97.985) +2022-11-14 13:27:52,912 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1364 (0.1194) Prec@1 75.000 (79.338) Prec@5 98.000 (97.985) +2022-11-14 13:27:52,929 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1284 (0.1195) Prec@1 77.000 (79.304) Prec@5 96.000 (97.957) +2022-11-14 13:27:52,943 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1493 (0.1199) Prec@1 76.000 (79.257) Prec@5 98.000 (97.957) +2022-11-14 13:27:52,957 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1192 (0.1199) Prec@1 79.000 (79.254) Prec@5 98.000 (97.958) +2022-11-14 13:27:52,971 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1199) Prec@1 81.000 (79.278) Prec@5 96.000 (97.931) +2022-11-14 13:27:52,986 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1211 (0.1199) Prec@1 79.000 (79.274) Prec@5 99.000 (97.945) +2022-11-14 13:27:52,999 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.1196) Prec@1 83.000 (79.324) Prec@5 99.000 (97.959) +2022-11-14 13:27:53,013 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1520 (0.1200) Prec@1 70.000 (79.200) Prec@5 98.000 (97.960) +2022-11-14 13:27:53,026 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.1197) Prec@1 83.000 (79.250) Prec@5 98.000 (97.961) +2022-11-14 13:27:53,041 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1199) Prec@1 77.000 (79.221) Prec@5 98.000 (97.961) +2022-11-14 13:27:53,055 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1285 (0.1200) Prec@1 73.000 (79.141) Prec@5 97.000 (97.949) +2022-11-14 13:27:53,070 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1303 (0.1202) Prec@1 79.000 (79.139) Prec@5 100.000 (97.975) +2022-11-14 13:27:53,086 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1384 (0.1204) Prec@1 77.000 (79.112) Prec@5 98.000 (97.975) +2022-11-14 13:27:53,103 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.1201) Prec@1 86.000 (79.198) Prec@5 99.000 (97.988) +2022-11-14 13:27:53,121 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.1199) Prec@1 81.000 (79.220) Prec@5 99.000 (98.000) +2022-11-14 13:27:53,137 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1410 (0.1201) Prec@1 77.000 (79.193) Prec@5 95.000 (97.964) +2022-11-14 13:27:53,154 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.1200) Prec@1 83.000 (79.238) Prec@5 97.000 (97.952) +2022-11-14 13:27:53,171 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1202) Prec@1 76.000 (79.200) Prec@5 97.000 (97.941) +2022-11-14 13:27:53,187 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.1202) Prec@1 82.000 (79.233) Prec@5 97.000 (97.930) +2022-11-14 13:27:53,201 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1361 (0.1204) Prec@1 77.000 (79.207) Prec@5 98.000 (97.931) +2022-11-14 13:27:53,217 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1202) Prec@1 82.000 (79.239) Prec@5 99.000 (97.943) +2022-11-14 13:27:53,232 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.1202) Prec@1 77.000 (79.213) Prec@5 100.000 (97.966) +2022-11-14 13:27:53,248 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.1202) Prec@1 82.000 (79.244) Prec@5 98.000 (97.967) +2022-11-14 13:27:53,264 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1201) Prec@1 79.000 (79.242) Prec@5 97.000 (97.956) +2022-11-14 13:27:53,280 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.1197) Prec@1 89.000 (79.348) Prec@5 98.000 (97.957) +2022-11-14 13:27:53,296 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1349 (0.1198) Prec@1 76.000 (79.312) Prec@5 97.000 (97.946) +2022-11-14 13:27:53,311 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1200) Prec@1 75.000 (79.266) Prec@5 96.000 (97.926) +2022-11-14 13:27:53,328 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1202) Prec@1 75.000 (79.221) Prec@5 98.000 (97.926) +2022-11-14 13:27:53,345 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1202) Prec@1 82.000 (79.250) Prec@5 98.000 (97.927) +2022-11-14 13:27:53,362 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.1200) Prec@1 84.000 (79.299) Prec@5 95.000 (97.897) +2022-11-14 13:27:53,379 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1202) Prec@1 76.000 (79.265) Prec@5 98.000 (97.898) +2022-11-14 13:27:53,395 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1205) Prec@1 75.000 (79.222) Prec@5 98.000 (97.899) +2022-11-14 13:27:53,413 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1205) Prec@1 80.000 (79.230) Prec@5 99.000 (97.910) +2022-11-14 13:27:53,482 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:27:53,837 Epoch: [45][0/500] Time 0.027 (0.027) Data 0.255 (0.255) Loss 0.1208 (0.1208) Prec@1 80.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:27:54,176 Epoch: [45][10/500] Time 0.036 (0.029) Data 0.002 (0.025) Loss 0.1146 (0.1177) Prec@1 77.000 (78.500) Prec@5 98.000 (98.500) +2022-11-14 13:27:54,599 Epoch: [45][20/500] Time 0.035 (0.033) Data 0.002 (0.014) Loss 0.0632 (0.0995) Prec@1 88.000 (81.667) Prec@5 100.000 (99.000) +2022-11-14 13:27:55,023 Epoch: [45][30/500] Time 0.038 (0.035) Data 0.002 (0.010) Loss 0.0721 (0.0927) Prec@1 90.000 (83.750) Prec@5 99.000 (99.000) +2022-11-14 13:27:55,398 Epoch: [45][40/500] Time 0.036 (0.034) Data 0.002 (0.008) Loss 0.0957 (0.0933) Prec@1 83.000 (83.600) Prec@5 97.000 (98.600) +2022-11-14 13:27:55,918 Epoch: [45][50/500] Time 0.051 (0.037) Data 0.002 (0.007) Loss 0.1129 (0.0966) Prec@1 81.000 (83.167) Prec@5 98.000 (98.500) +2022-11-14 13:27:56,407 Epoch: [45][60/500] Time 0.041 (0.038) Data 0.002 (0.006) Loss 0.1182 (0.0996) Prec@1 79.000 (82.571) Prec@5 97.000 (98.286) +2022-11-14 13:27:56,847 Epoch: [45][70/500] Time 0.042 (0.038) Data 0.002 (0.006) Loss 0.0879 (0.0982) Prec@1 84.000 (82.750) Prec@5 99.000 (98.375) +2022-11-14 13:27:57,292 Epoch: [45][80/500] Time 0.046 (0.038) Data 0.004 (0.005) Loss 0.1136 (0.0999) Prec@1 80.000 (82.444) Prec@5 98.000 (98.333) +2022-11-14 13:27:57,751 Epoch: [45][90/500] Time 0.054 (0.039) Data 0.003 (0.005) Loss 0.0791 (0.0978) Prec@1 86.000 (82.800) Prec@5 99.000 (98.400) +2022-11-14 13:27:58,230 Epoch: [45][100/500] Time 0.045 (0.039) Data 0.003 (0.005) Loss 0.1395 (0.1016) Prec@1 75.000 (82.091) Prec@5 98.000 (98.364) +2022-11-14 13:27:58,720 Epoch: [45][110/500] Time 0.048 (0.039) Data 0.004 (0.005) Loss 0.1099 (0.1023) Prec@1 82.000 (82.083) Prec@5 98.000 (98.333) +2022-11-14 13:27:59,163 Epoch: [45][120/500] Time 0.028 (0.039) Data 0.002 (0.004) Loss 0.1108 (0.1029) Prec@1 82.000 (82.077) Prec@5 97.000 (98.231) +2022-11-14 13:27:59,620 Epoch: [45][130/500] Time 0.055 (0.039) Data 0.003 (0.004) Loss 0.0767 (0.1011) Prec@1 87.000 (82.429) Prec@5 99.000 (98.286) +2022-11-14 13:28:00,106 Epoch: [45][140/500] Time 0.038 (0.040) Data 0.002 (0.004) Loss 0.1074 (0.1015) Prec@1 81.000 (82.333) Prec@5 100.000 (98.400) +2022-11-14 13:28:00,590 Epoch: [45][150/500] Time 0.045 (0.040) Data 0.003 (0.004) Loss 0.0862 (0.1005) Prec@1 87.000 (82.625) Prec@5 100.000 (98.500) +2022-11-14 13:28:01,095 Epoch: [45][160/500] Time 0.041 (0.040) Data 0.003 (0.004) Loss 0.1323 (0.1024) Prec@1 75.000 (82.176) Prec@5 98.000 (98.471) +2022-11-14 13:28:01,801 Epoch: [45][170/500] Time 0.094 (0.042) Data 0.002 (0.004) Loss 0.1009 (0.1023) Prec@1 83.000 (82.222) Prec@5 98.000 (98.444) +2022-11-14 13:28:02,433 Epoch: [45][180/500] Time 0.044 (0.042) Data 0.002 (0.004) Loss 0.1109 (0.1028) Prec@1 81.000 (82.158) Prec@5 100.000 (98.526) +2022-11-14 13:28:03,020 Epoch: [45][190/500] Time 0.094 (0.043) Data 0.002 (0.004) Loss 0.1145 (0.1034) Prec@1 78.000 (81.950) Prec@5 99.000 (98.550) +2022-11-14 13:28:03,557 Epoch: [45][200/500] Time 0.044 (0.043) Data 0.002 (0.004) Loss 0.1121 (0.1038) Prec@1 80.000 (81.857) Prec@5 97.000 (98.476) +2022-11-14 13:28:04,495 Epoch: [45][210/500] Time 0.091 (0.045) Data 0.004 (0.004) Loss 0.0970 (0.1035) Prec@1 82.000 (81.864) Prec@5 100.000 (98.545) +2022-11-14 13:28:05,489 Epoch: [45][220/500] Time 0.089 (0.047) Data 0.002 (0.004) Loss 0.1293 (0.1046) Prec@1 76.000 (81.609) Prec@5 99.000 (98.565) +2022-11-14 13:28:06,324 Epoch: [45][230/500] Time 0.096 (0.048) Data 0.002 (0.003) Loss 0.0972 (0.1043) Prec@1 82.000 (81.625) Prec@5 100.000 (98.625) +2022-11-14 13:28:07,228 Epoch: [45][240/500] Time 0.079 (0.050) Data 0.002 (0.003) Loss 0.0919 (0.1038) Prec@1 84.000 (81.720) Prec@5 100.000 (98.680) +2022-11-14 13:28:07,740 Epoch: [45][250/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0961 (0.1035) Prec@1 81.000 (81.692) Prec@5 100.000 (98.731) +2022-11-14 13:28:08,224 Epoch: [45][260/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.1086 (0.1037) Prec@1 82.000 (81.704) Prec@5 99.000 (98.741) +2022-11-14 13:28:08,778 Epoch: [45][270/500] Time 0.079 (0.049) Data 0.002 (0.003) Loss 0.1128 (0.1040) Prec@1 82.000 (81.714) Prec@5 97.000 (98.679) +2022-11-14 13:28:09,663 Epoch: [45][280/500] Time 0.088 (0.050) Data 0.002 (0.003) Loss 0.1368 (0.1051) Prec@1 77.000 (81.552) Prec@5 99.000 (98.690) +2022-11-14 13:28:10,163 Epoch: [45][290/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0963 (0.1049) Prec@1 83.000 (81.600) Prec@5 99.000 (98.700) +2022-11-14 13:28:10,660 Epoch: [45][300/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.1163 (0.1052) Prec@1 79.000 (81.516) Prec@5 98.000 (98.677) +2022-11-14 13:28:11,167 Epoch: [45][310/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.1049 (0.1052) Prec@1 82.000 (81.531) Prec@5 99.000 (98.688) +2022-11-14 13:28:11,677 Epoch: [45][320/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.1067 (0.1053) Prec@1 82.000 (81.545) Prec@5 97.000 (98.636) +2022-11-14 13:28:12,262 Epoch: [45][330/500] Time 0.068 (0.050) Data 0.002 (0.003) Loss 0.0816 (0.1046) Prec@1 83.000 (81.588) Prec@5 99.000 (98.647) +2022-11-14 13:28:13,187 Epoch: [45][340/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.1234 (0.1051) Prec@1 76.000 (81.429) Prec@5 98.000 (98.629) +2022-11-14 13:28:13,803 Epoch: [45][350/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0867 (0.1046) Prec@1 84.000 (81.500) Prec@5 99.000 (98.639) +2022-11-14 13:28:14,354 Epoch: [45][360/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0979 (0.1044) Prec@1 84.000 (81.568) Prec@5 98.000 (98.622) +2022-11-14 13:28:14,818 Epoch: [45][370/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.1147 (0.1047) Prec@1 80.000 (81.526) Prec@5 99.000 (98.632) +2022-11-14 13:28:15,261 Epoch: [45][380/500] Time 0.037 (0.050) Data 0.002 (0.003) Loss 0.1161 (0.1050) Prec@1 80.000 (81.487) Prec@5 99.000 (98.641) +2022-11-14 13:28:15,759 Epoch: [45][390/500] Time 0.075 (0.050) Data 0.003 (0.003) Loss 0.1117 (0.1051) Prec@1 79.000 (81.425) Prec@5 100.000 (98.675) +2022-11-14 13:28:16,178 Epoch: [45][400/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0777 (0.1045) Prec@1 88.000 (81.585) Prec@5 100.000 (98.707) +2022-11-14 13:28:16,632 Epoch: [45][410/500] Time 0.040 (0.050) Data 0.002 (0.003) Loss 0.1194 (0.1048) Prec@1 78.000 (81.500) Prec@5 98.000 (98.690) +2022-11-14 13:28:17,210 Epoch: [45][420/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0865 (0.1044) Prec@1 88.000 (81.651) Prec@5 99.000 (98.698) +2022-11-14 13:28:17,734 Epoch: [45][430/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0628 (0.1035) Prec@1 88.000 (81.795) Prec@5 100.000 (98.727) +2022-11-14 13:28:18,227 Epoch: [45][440/500] Time 0.031 (0.049) Data 0.002 (0.003) Loss 0.1052 (0.1035) Prec@1 83.000 (81.822) Prec@5 97.000 (98.689) +2022-11-14 13:28:18,759 Epoch: [45][450/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.1220 (0.1039) Prec@1 78.000 (81.739) Prec@5 99.000 (98.696) +2022-11-14 13:28:19,308 Epoch: [45][460/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.1168 (0.1042) Prec@1 77.000 (81.638) Prec@5 99.000 (98.702) +2022-11-14 13:28:19,739 Epoch: [45][470/500] Time 0.037 (0.049) Data 0.002 (0.003) Loss 0.1013 (0.1041) Prec@1 81.000 (81.625) Prec@5 98.000 (98.688) +2022-11-14 13:28:20,201 Epoch: [45][480/500] Time 0.040 (0.049) Data 0.002 (0.003) Loss 0.1045 (0.1041) Prec@1 82.000 (81.633) Prec@5 99.000 (98.694) +2022-11-14 13:28:20,776 Epoch: [45][490/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0992 (0.1040) Prec@1 83.000 (81.660) Prec@5 98.000 (98.680) +2022-11-14 13:28:21,238 Epoch: [45][499/500] Time 0.038 (0.049) Data 0.002 (0.003) Loss 0.1282 (0.1045) Prec@1 80.000 (81.627) Prec@5 97.000 (98.647) +2022-11-14 13:28:21,598 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.1213 (0.1213) Prec@1 80.000 (80.000) Prec@5 98.000 (98.000) +2022-11-14 13:28:21,610 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1355 (0.1284) Prec@1 77.000 (78.500) Prec@5 100.000 (99.000) +2022-11-14 13:28:21,620 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1315 (0.1294) Prec@1 76.000 (77.667) Prec@5 97.000 (98.333) +2022-11-14 13:28:21,635 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1213 (0.1274) Prec@1 77.000 (77.500) Prec@5 98.000 (98.250) +2022-11-14 13:28:21,645 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1159 (0.1251) Prec@1 81.000 (78.200) Prec@5 99.000 (98.400) +2022-11-14 13:28:21,654 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0916 (0.1195) Prec@1 83.000 (79.000) Prec@5 98.000 (98.333) +2022-11-14 13:28:21,664 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1304 (0.1211) Prec@1 79.000 (79.000) Prec@5 95.000 (97.857) +2022-11-14 13:28:21,675 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1354 (0.1228) Prec@1 74.000 (78.375) Prec@5 94.000 (97.375) +2022-11-14 13:28:21,685 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1343 (0.1241) Prec@1 75.000 (78.000) Prec@5 100.000 (97.667) +2022-11-14 13:28:21,695 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0987 (0.1216) Prec@1 82.000 (78.400) Prec@5 97.000 (97.600) +2022-11-14 13:28:21,707 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1229 (0.1217) Prec@1 81.000 (78.636) Prec@5 97.000 (97.545) +2022-11-14 13:28:21,718 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.1208) Prec@1 78.000 (78.583) Prec@5 98.000 (97.583) +2022-11-14 13:28:21,730 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.1193) Prec@1 81.000 (78.769) Prec@5 100.000 (97.769) +2022-11-14 13:28:21,740 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.1189) Prec@1 79.000 (78.786) Prec@5 98.000 (97.786) +2022-11-14 13:28:21,750 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.1188) Prec@1 83.000 (79.067) Prec@5 100.000 (97.933) +2022-11-14 13:28:21,761 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1248 (0.1192) Prec@1 80.000 (79.125) Prec@5 99.000 (98.000) +2022-11-14 13:28:21,771 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.1183) Prec@1 83.000 (79.353) Prec@5 98.000 (98.000) +2022-11-14 13:28:21,781 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1261 (0.1187) Prec@1 78.000 (79.278) Prec@5 100.000 (98.111) +2022-11-14 13:28:21,791 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1284 (0.1192) Prec@1 77.000 (79.158) Prec@5 98.000 (98.105) +2022-11-14 13:28:21,803 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1304 (0.1198) Prec@1 77.000 (79.050) Prec@5 97.000 (98.050) +2022-11-14 13:28:21,813 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.1194) Prec@1 80.000 (79.095) Prec@5 99.000 (98.095) +2022-11-14 13:28:21,823 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1245 (0.1196) Prec@1 78.000 (79.045) Prec@5 99.000 (98.136) +2022-11-14 13:28:21,834 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1166 (0.1195) Prec@1 78.000 (79.000) Prec@5 98.000 (98.130) +2022-11-14 13:28:21,845 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.1184) Prec@1 82.000 (79.125) Prec@5 99.000 (98.167) +2022-11-14 13:28:21,855 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1202 (0.1185) Prec@1 79.000 (79.120) Prec@5 97.000 (98.120) +2022-11-14 13:28:21,867 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1631 (0.1202) Prec@1 67.000 (78.654) Prec@5 93.000 (97.923) +2022-11-14 13:28:21,878 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.1195) Prec@1 80.000 (78.704) Prec@5 100.000 (98.000) +2022-11-14 13:28:21,889 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1251 (0.1197) Prec@1 77.000 (78.643) Prec@5 97.000 (97.964) +2022-11-14 13:28:21,900 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.1188) Prec@1 86.000 (78.897) Prec@5 98.000 (97.966) +2022-11-14 13:28:21,909 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1234 (0.1190) Prec@1 76.000 (78.800) Prec@5 97.000 (97.933) +2022-11-14 13:28:21,920 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.1184) Prec@1 85.000 (79.000) Prec@5 99.000 (97.968) +2022-11-14 13:28:21,931 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.1178) Prec@1 85.000 (79.188) Prec@5 100.000 (98.031) +2022-11-14 13:28:21,941 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1161 (0.1178) Prec@1 76.000 (79.091) Prec@5 98.000 (98.030) +2022-11-14 13:28:21,951 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.1182) Prec@1 75.000 (78.971) Prec@5 99.000 (98.059) +2022-11-14 13:28:21,962 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.1180) Prec@1 82.000 (79.057) Prec@5 96.000 (98.000) +2022-11-14 13:28:21,972 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1274 (0.1183) Prec@1 78.000 (79.028) Prec@5 100.000 (98.056) +2022-11-14 13:28:21,982 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.1186) Prec@1 71.000 (78.811) Prec@5 96.000 (98.000) +2022-11-14 13:28:21,993 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1261 (0.1188) Prec@1 80.000 (78.842) Prec@5 98.000 (98.000) +2022-11-14 13:28:22,003 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.1183) Prec@1 86.000 (79.026) Prec@5 97.000 (97.974) +2022-11-14 13:28:22,013 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1203 (0.1183) Prec@1 78.000 (79.000) Prec@5 98.000 (97.975) +2022-11-14 13:28:22,023 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1166 (0.1183) Prec@1 81.000 (79.049) Prec@5 98.000 (97.976) +2022-11-14 13:28:22,035 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.1179) Prec@1 81.000 (79.095) Prec@5 99.000 (98.000) +2022-11-14 13:28:22,046 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.1172) Prec@1 84.000 (79.209) Prec@5 96.000 (97.953) +2022-11-14 13:28:22,056 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1222 (0.1173) Prec@1 80.000 (79.227) Prec@5 96.000 (97.909) +2022-11-14 13:28:22,068 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1193 (0.1173) Prec@1 81.000 (79.267) Prec@5 96.000 (97.867) +2022-11-14 13:28:22,079 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1267 (0.1175) Prec@1 79.000 (79.261) Prec@5 99.000 (97.891) +2022-11-14 13:28:22,090 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1079 (0.1173) Prec@1 82.000 (79.319) Prec@5 99.000 (97.915) +2022-11-14 13:28:22,101 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1204 (0.1174) Prec@1 77.000 (79.271) Prec@5 99.000 (97.938) +2022-11-14 13:28:22,111 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.1171) Prec@1 83.000 (79.347) Prec@5 99.000 (97.959) +2022-11-14 13:28:22,121 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1462 (0.1177) Prec@1 71.000 (79.180) Prec@5 97.000 (97.940) +2022-11-14 13:28:22,133 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.1177) Prec@1 78.000 (79.157) Prec@5 100.000 (97.980) +2022-11-14 13:28:22,146 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1391 (0.1181) Prec@1 73.000 (79.038) Prec@5 98.000 (97.981) +2022-11-14 13:28:22,157 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.1181) Prec@1 79.000 (79.038) Prec@5 98.000 (97.981) +2022-11-14 13:28:22,167 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.1180) Prec@1 79.000 (79.037) Prec@5 98.000 (97.981) +2022-11-14 13:28:22,178 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.1177) Prec@1 81.000 (79.073) Prec@5 100.000 (98.018) +2022-11-14 13:28:22,188 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.1175) Prec@1 86.000 (79.196) Prec@5 98.000 (98.018) +2022-11-14 13:28:22,199 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1270 (0.1176) Prec@1 79.000 (79.193) Prec@5 100.000 (98.053) +2022-11-14 13:28:22,209 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.1174) Prec@1 83.000 (79.259) Prec@5 99.000 (98.069) +2022-11-14 13:28:22,221 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1763 (0.1184) Prec@1 70.000 (79.102) Prec@5 100.000 (98.102) +2022-11-14 13:28:22,232 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1054 (0.1182) Prec@1 83.000 (79.167) Prec@5 96.000 (98.067) +2022-11-14 13:28:22,243 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.1179) Prec@1 83.000 (79.230) Prec@5 99.000 (98.082) +2022-11-14 13:28:22,254 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.1176) Prec@1 82.000 (79.274) Prec@5 99.000 (98.097) +2022-11-14 13:28:22,265 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.1176) Prec@1 81.000 (79.302) Prec@5 100.000 (98.127) +2022-11-14 13:28:22,276 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.1171) Prec@1 86.000 (79.406) Prec@5 99.000 (98.141) +2022-11-14 13:28:22,287 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1398 (0.1175) Prec@1 76.000 (79.354) Prec@5 97.000 (98.123) +2022-11-14 13:28:22,298 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1518 (0.1180) Prec@1 71.000 (79.227) Prec@5 99.000 (98.136) +2022-11-14 13:28:22,308 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.1177) Prec@1 85.000 (79.313) Prec@5 98.000 (98.134) +2022-11-14 13:28:22,318 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1262 (0.1178) Prec@1 76.000 (79.265) Prec@5 98.000 (98.132) +2022-11-14 13:28:22,330 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1378 (0.1181) Prec@1 78.000 (79.246) Prec@5 99.000 (98.145) +2022-11-14 13:28:22,340 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1477 (0.1185) Prec@1 72.000 (79.143) Prec@5 98.000 (98.143) +2022-11-14 13:28:22,352 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.1183) Prec@1 81.000 (79.169) Prec@5 99.000 (98.155) +2022-11-14 13:28:22,384 Test: [71/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.1182) Prec@1 80.000 (79.181) Prec@5 99.000 (98.167) +2022-11-14 13:28:22,402 Test: [72/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.1179) Prec@1 83.000 (79.233) Prec@5 100.000 (98.192) +2022-11-14 13:28:22,440 Test: [73/100] Model Time 0.014 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.1177) Prec@1 83.000 (79.284) Prec@5 100.000 (98.216) +2022-11-14 13:28:22,459 Test: [74/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.1219 (0.1178) Prec@1 78.000 (79.267) Prec@5 97.000 (98.200) +2022-11-14 13:28:22,479 Test: [75/100] Model Time 0.015 (0.008) Loss Time 0.000 (0.000) Loss 0.1243 (0.1179) Prec@1 78.000 (79.250) Prec@5 98.000 (98.197) +2022-11-14 13:28:22,494 Test: [76/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1203 (0.1179) Prec@1 79.000 (79.247) Prec@5 97.000 (98.182) +2022-11-14 13:28:22,505 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.1176) Prec@1 85.000 (79.321) Prec@5 97.000 (98.167) +2022-11-14 13:28:22,517 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1356 (0.1178) Prec@1 78.000 (79.304) Prec@5 100.000 (98.190) +2022-11-14 13:28:22,528 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.1180) Prec@1 76.000 (79.263) Prec@5 98.000 (98.188) +2022-11-14 13:28:22,539 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1093 (0.1179) Prec@1 79.000 (79.259) Prec@5 98.000 (98.185) +2022-11-14 13:28:22,550 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.1176) Prec@1 84.000 (79.317) Prec@5 98.000 (98.183) +2022-11-14 13:28:22,561 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1089 (0.1175) Prec@1 79.000 (79.313) Prec@5 99.000 (98.193) +2022-11-14 13:28:22,572 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1344 (0.1177) Prec@1 75.000 (79.262) Prec@5 97.000 (98.179) +2022-11-14 13:28:22,584 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1291 (0.1178) Prec@1 79.000 (79.259) Prec@5 97.000 (98.165) +2022-11-14 13:28:22,596 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1388 (0.1181) Prec@1 75.000 (79.209) Prec@5 98.000 (98.163) +2022-11-14 13:28:22,606 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1180) Prec@1 79.000 (79.207) Prec@5 99.000 (98.172) +2022-11-14 13:28:22,616 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1561 (0.1185) Prec@1 73.000 (79.136) Prec@5 96.000 (98.148) +2022-11-14 13:28:22,626 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.1184) Prec@1 82.000 (79.169) Prec@5 97.000 (98.135) +2022-11-14 13:28:22,637 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1237 (0.1184) Prec@1 81.000 (79.189) Prec@5 99.000 (98.144) +2022-11-14 13:28:22,649 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1234 (0.1185) Prec@1 79.000 (79.187) Prec@5 99.000 (98.154) +2022-11-14 13:28:22,659 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.1181) Prec@1 83.000 (79.228) Prec@5 99.000 (98.163) +2022-11-14 13:28:22,669 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1187 (0.1181) Prec@1 80.000 (79.237) Prec@5 98.000 (98.161) +2022-11-14 13:28:22,681 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1170 (0.1181) Prec@1 80.000 (79.245) Prec@5 100.000 (98.181) +2022-11-14 13:28:22,692 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.1180) Prec@1 80.000 (79.253) Prec@5 97.000 (98.168) +2022-11-14 13:28:22,703 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1191 (0.1180) Prec@1 78.000 (79.240) Prec@5 99.000 (98.177) +2022-11-14 13:28:22,714 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.1178) Prec@1 84.000 (79.289) Prec@5 98.000 (98.175) +2022-11-14 13:28:22,725 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.1178) Prec@1 78.000 (79.276) Prec@5 100.000 (98.194) +2022-11-14 13:28:22,737 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1249 (0.1178) Prec@1 77.000 (79.253) Prec@5 98.000 (98.192) +2022-11-14 13:28:22,747 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.1177) Prec@1 85.000 (79.310) Prec@5 99.000 (98.200) +2022-11-14 13:28:22,811 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:28:23,194 Epoch: [46][0/500] Time 0.036 (0.036) Data 0.265 (0.265) Loss 0.1147 (0.1147) Prec@1 78.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:28:23,500 Epoch: [46][10/500] Time 0.027 (0.028) Data 0.002 (0.026) Loss 0.1085 (0.1116) Prec@1 78.000 (78.000) Prec@5 99.000 (98.500) +2022-11-14 13:28:23,802 Epoch: [46][20/500] Time 0.026 (0.027) Data 0.002 (0.015) Loss 0.1148 (0.1127) Prec@1 77.000 (77.667) Prec@5 99.000 (98.667) +2022-11-14 13:28:24,207 Epoch: [46][30/500] Time 0.049 (0.030) Data 0.002 (0.011) Loss 0.1248 (0.1157) Prec@1 79.000 (78.000) Prec@5 95.000 (97.750) +2022-11-14 13:28:24,690 Epoch: [46][40/500] Time 0.047 (0.033) Data 0.002 (0.009) Loss 0.0893 (0.1104) Prec@1 87.000 (79.800) Prec@5 100.000 (98.200) +2022-11-14 13:28:25,157 Epoch: [46][50/500] Time 0.043 (0.035) Data 0.002 (0.007) Loss 0.1206 (0.1121) Prec@1 81.000 (80.000) Prec@5 95.000 (97.667) +2022-11-14 13:28:25,523 Epoch: [46][60/500] Time 0.034 (0.034) Data 0.002 (0.007) Loss 0.0852 (0.1083) Prec@1 85.000 (80.714) Prec@5 99.000 (97.857) +2022-11-14 13:28:25,961 Epoch: [46][70/500] Time 0.047 (0.035) Data 0.002 (0.006) Loss 0.0715 (0.1037) Prec@1 89.000 (81.750) Prec@5 100.000 (98.125) +2022-11-14 13:28:26,432 Epoch: [46][80/500] Time 0.046 (0.036) Data 0.002 (0.005) Loss 0.1103 (0.1044) Prec@1 81.000 (81.667) Prec@5 100.000 (98.333) +2022-11-14 13:28:26,838 Epoch: [46][90/500] Time 0.028 (0.036) Data 0.002 (0.005) Loss 0.0952 (0.1035) Prec@1 81.000 (81.600) Prec@5 100.000 (98.500) +2022-11-14 13:28:27,221 Epoch: [46][100/500] Time 0.036 (0.036) Data 0.002 (0.005) Loss 0.0970 (0.1029) Prec@1 82.000 (81.636) Prec@5 98.000 (98.455) +2022-11-14 13:28:27,696 Epoch: [46][110/500] Time 0.047 (0.036) Data 0.002 (0.004) Loss 0.1011 (0.1028) Prec@1 84.000 (81.833) Prec@5 98.000 (98.417) +2022-11-14 13:28:28,173 Epoch: [46][120/500] Time 0.046 (0.037) Data 0.002 (0.004) Loss 0.0720 (0.1004) Prec@1 91.000 (82.538) Prec@5 100.000 (98.538) +2022-11-14 13:28:28,645 Epoch: [46][130/500] Time 0.048 (0.037) Data 0.002 (0.004) Loss 0.1320 (0.1027) Prec@1 75.000 (82.000) Prec@5 98.000 (98.500) +2022-11-14 13:28:29,033 Epoch: [46][140/500] Time 0.049 (0.037) Data 0.002 (0.004) Loss 0.1139 (0.1034) Prec@1 78.000 (81.733) Prec@5 99.000 (98.533) +2022-11-14 13:28:29,501 Epoch: [46][150/500] Time 0.033 (0.037) Data 0.002 (0.004) Loss 0.1490 (0.1063) Prec@1 71.000 (81.062) Prec@5 97.000 (98.438) +2022-11-14 13:28:29,932 Epoch: [46][160/500] Time 0.055 (0.037) Data 0.003 (0.004) Loss 0.0910 (0.1054) Prec@1 84.000 (81.235) Prec@5 100.000 (98.529) +2022-11-14 13:28:30,341 Epoch: [46][170/500] Time 0.038 (0.037) Data 0.002 (0.004) Loss 0.1005 (0.1051) Prec@1 83.000 (81.333) Prec@5 94.000 (98.278) +2022-11-14 13:28:30,733 Epoch: [46][180/500] Time 0.031 (0.037) Data 0.002 (0.004) Loss 0.0694 (0.1032) Prec@1 90.000 (81.789) Prec@5 100.000 (98.368) +2022-11-14 13:28:31,113 Epoch: [46][190/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.1300 (0.1045) Prec@1 77.000 (81.550) Prec@5 98.000 (98.350) +2022-11-14 13:28:31,602 Epoch: [46][200/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.1091 (0.1048) Prec@1 78.000 (81.381) Prec@5 99.000 (98.381) +2022-11-14 13:28:32,091 Epoch: [46][210/500] Time 0.047 (0.038) Data 0.003 (0.003) Loss 0.1114 (0.1051) Prec@1 78.000 (81.227) Prec@5 100.000 (98.455) +2022-11-14 13:28:32,571 Epoch: [46][220/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.1006 (0.1049) Prec@1 80.000 (81.174) Prec@5 99.000 (98.478) +2022-11-14 13:28:32,933 Epoch: [46][230/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0892 (0.1042) Prec@1 84.000 (81.292) Prec@5 100.000 (98.542) +2022-11-14 13:28:33,309 Epoch: [46][240/500] Time 0.033 (0.038) Data 0.003 (0.003) Loss 0.0600 (0.1024) Prec@1 90.000 (81.640) Prec@5 99.000 (98.560) +2022-11-14 13:28:33,694 Epoch: [46][250/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1197 (0.1031) Prec@1 78.000 (81.500) Prec@5 98.000 (98.538) +2022-11-14 13:28:34,144 Epoch: [46][260/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.1008 (0.1030) Prec@1 81.000 (81.481) Prec@5 100.000 (98.593) +2022-11-14 13:28:34,568 Epoch: [46][270/500] Time 0.033 (0.037) Data 0.002 (0.003) Loss 0.0793 (0.1022) Prec@1 85.000 (81.607) Prec@5 98.000 (98.571) +2022-11-14 13:28:34,945 Epoch: [46][280/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1257 (0.1030) Prec@1 78.000 (81.483) Prec@5 98.000 (98.552) +2022-11-14 13:28:35,331 Epoch: [46][290/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0957 (0.1027) Prec@1 84.000 (81.567) Prec@5 98.000 (98.533) +2022-11-14 13:28:35,717 Epoch: [46][300/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1032 (0.1028) Prec@1 82.000 (81.581) Prec@5 97.000 (98.484) +2022-11-14 13:28:36,097 Epoch: [46][310/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.1100 (0.1030) Prec@1 84.000 (81.656) Prec@5 98.000 (98.469) +2022-11-14 13:28:36,481 Epoch: [46][320/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.1253 (0.1037) Prec@1 78.000 (81.545) Prec@5 98.000 (98.455) +2022-11-14 13:28:36,861 Epoch: [46][330/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.1111 (0.1039) Prec@1 82.000 (81.559) Prec@5 99.000 (98.471) +2022-11-14 13:28:37,267 Epoch: [46][340/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.1048 (0.1039) Prec@1 84.000 (81.629) Prec@5 99.000 (98.486) +2022-11-14 13:28:37,659 Epoch: [46][350/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0979 (0.1037) Prec@1 81.000 (81.611) Prec@5 100.000 (98.528) +2022-11-14 13:28:38,049 Epoch: [46][360/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.1125 (0.1040) Prec@1 79.000 (81.541) Prec@5 99.000 (98.541) +2022-11-14 13:28:38,471 Epoch: [46][370/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.1088 (0.1041) Prec@1 80.000 (81.500) Prec@5 100.000 (98.579) +2022-11-14 13:28:38,978 Epoch: [46][380/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.1197 (0.1045) Prec@1 80.000 (81.462) Prec@5 98.000 (98.564) +2022-11-14 13:28:39,394 Epoch: [46][390/500] Time 0.033 (0.037) Data 0.001 (0.003) Loss 0.1102 (0.1046) Prec@1 80.000 (81.425) Prec@5 98.000 (98.550) +2022-11-14 13:28:39,838 Epoch: [46][400/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.1148 (0.1049) Prec@1 80.000 (81.390) Prec@5 97.000 (98.512) +2022-11-14 13:28:40,322 Epoch: [46][410/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.1334 (0.1056) Prec@1 79.000 (81.333) Prec@5 99.000 (98.524) +2022-11-14 13:28:40,738 Epoch: [46][420/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.1042 (0.1055) Prec@1 80.000 (81.302) Prec@5 99.000 (98.535) +2022-11-14 13:28:41,155 Epoch: [46][430/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0878 (0.1051) Prec@1 84.000 (81.364) Prec@5 99.000 (98.545) +2022-11-14 13:28:41,637 Epoch: [46][440/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0868 (0.1047) Prec@1 84.000 (81.422) Prec@5 98.000 (98.533) +2022-11-14 13:28:42,095 Epoch: [46][450/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.1038 (0.1047) Prec@1 81.000 (81.413) Prec@5 100.000 (98.565) +2022-11-14 13:28:42,526 Epoch: [46][460/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.1065 (0.1048) Prec@1 84.000 (81.468) Prec@5 99.000 (98.574) +2022-11-14 13:28:42,912 Epoch: [46][470/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1024 (0.1047) Prec@1 80.000 (81.438) Prec@5 98.000 (98.562) +2022-11-14 13:28:43,312 Epoch: [46][480/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.1084 (0.1048) Prec@1 81.000 (81.429) Prec@5 97.000 (98.531) +2022-11-14 13:28:43,695 Epoch: [46][490/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.1548 (0.1058) Prec@1 72.000 (81.240) Prec@5 97.000 (98.500) +2022-11-14 13:28:44,032 Epoch: [46][499/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.1226 (0.1061) Prec@1 78.000 (81.176) Prec@5 97.000 (98.471) +2022-11-14 13:28:44,319 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0831 (0.0831) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:28:44,327 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.1030) Prec@1 77.000 (80.500) Prec@5 100.000 (100.000) +2022-11-14 13:28:44,336 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1426 (0.1162) Prec@1 76.000 (79.000) Prec@5 100.000 (100.000) +2022-11-14 13:28:44,348 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.1142) Prec@1 80.000 (79.250) Prec@5 99.000 (99.750) +2022-11-14 13:28:44,359 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1457 (0.1205) Prec@1 76.000 (78.600) Prec@5 98.000 (99.400) +2022-11-14 13:28:44,368 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.1165) Prec@1 82.000 (79.167) Prec@5 98.000 (99.167) +2022-11-14 13:28:44,378 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.1158) Prec@1 80.000 (79.286) Prec@5 98.000 (99.000) +2022-11-14 13:28:44,393 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1140 (0.1155) Prec@1 81.000 (79.500) Prec@5 100.000 (99.125) +2022-11-14 13:28:44,405 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.1171) Prec@1 77.000 (79.222) Prec@5 100.000 (99.222) +2022-11-14 13:28:44,420 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.1158) Prec@1 80.000 (79.300) Prec@5 98.000 (99.100) +2022-11-14 13:28:44,435 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.1152) Prec@1 80.000 (79.364) Prec@5 99.000 (99.091) +2022-11-14 13:28:44,447 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.1150) Prec@1 81.000 (79.500) Prec@5 98.000 (99.000) +2022-11-14 13:28:44,462 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.1147) Prec@1 77.000 (79.308) Prec@5 98.000 (98.923) +2022-11-14 13:28:44,476 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.1150) Prec@1 78.000 (79.214) Prec@5 99.000 (98.929) +2022-11-14 13:28:44,490 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.1153) Prec@1 79.000 (79.200) Prec@5 100.000 (99.000) +2022-11-14 13:28:44,503 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1316 (0.1163) Prec@1 78.000 (79.125) Prec@5 97.000 (98.875) +2022-11-14 13:28:44,519 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.1159) Prec@1 81.000 (79.235) Prec@5 97.000 (98.765) +2022-11-14 13:28:44,536 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1306 (0.1168) Prec@1 76.000 (79.056) Prec@5 98.000 (98.722) +2022-11-14 13:28:44,551 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1510 (0.1186) Prec@1 73.000 (78.737) Prec@5 96.000 (98.579) +2022-11-14 13:28:44,565 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1185) Prec@1 79.000 (78.750) Prec@5 99.000 (98.600) +2022-11-14 13:28:44,582 Test: [20/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1200) Prec@1 73.000 (78.476) Prec@5 98.000 (98.571) +2022-11-14 13:28:44,596 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.1200) Prec@1 80.000 (78.545) Prec@5 96.000 (98.455) +2022-11-14 13:28:44,612 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1205) Prec@1 79.000 (78.565) Prec@5 97.000 (98.391) +2022-11-14 13:28:44,627 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.1198) Prec@1 80.000 (78.625) Prec@5 100.000 (98.458) +2022-11-14 13:28:44,644 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1458 (0.1208) Prec@1 74.000 (78.440) Prec@5 99.000 (98.480) +2022-11-14 13:28:44,658 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1527 (0.1220) Prec@1 74.000 (78.269) Prec@5 95.000 (98.346) +2022-11-14 13:28:44,671 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.1218) Prec@1 79.000 (78.296) Prec@5 99.000 (98.370) +2022-11-14 13:28:44,684 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1382 (0.1224) Prec@1 74.000 (78.143) Prec@5 96.000 (98.286) +2022-11-14 13:28:44,700 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1305 (0.1227) Prec@1 76.000 (78.069) Prec@5 95.000 (98.172) +2022-11-14 13:28:44,714 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1338 (0.1231) Prec@1 76.000 (78.000) Prec@5 95.000 (98.067) +2022-11-14 13:28:44,730 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1280 (0.1232) Prec@1 79.000 (78.032) Prec@5 98.000 (98.065) +2022-11-14 13:28:44,745 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1425 (0.1238) Prec@1 75.000 (77.938) Prec@5 100.000 (98.125) +2022-11-14 13:28:44,760 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.1236) Prec@1 82.000 (78.061) Prec@5 94.000 (98.000) +2022-11-14 13:28:44,775 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1513 (0.1244) Prec@1 73.000 (77.912) Prec@5 96.000 (97.941) +2022-11-14 13:28:44,790 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1223 (0.1244) Prec@1 80.000 (77.971) Prec@5 98.000 (97.943) +2022-11-14 13:28:44,805 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.1240) Prec@1 82.000 (78.083) Prec@5 96.000 (97.889) +2022-11-14 13:28:44,820 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1236 (0.1240) Prec@1 77.000 (78.054) Prec@5 100.000 (97.946) +2022-11-14 13:28:44,835 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1225 (0.1240) Prec@1 80.000 (78.105) Prec@5 98.000 (97.947) +2022-11-14 13:28:44,849 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1235) Prec@1 83.000 (78.231) Prec@5 97.000 (97.923) +2022-11-14 13:28:44,864 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.1230) Prec@1 79.000 (78.250) Prec@5 99.000 (97.950) +2022-11-14 13:28:44,880 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.1228) Prec@1 78.000 (78.244) Prec@5 98.000 (97.951) +2022-11-14 13:28:44,894 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1230) Prec@1 79.000 (78.262) Prec@5 97.000 (97.929) +2022-11-14 13:28:44,907 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.1219) Prec@1 83.000 (78.372) Prec@5 98.000 (97.930) +2022-11-14 13:28:44,920 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.1215) Prec@1 82.000 (78.455) Prec@5 96.000 (97.886) +2022-11-14 13:28:44,935 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1513 (0.1222) Prec@1 70.000 (78.267) Prec@5 98.000 (97.889) +2022-11-14 13:28:44,948 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1289 (0.1223) Prec@1 75.000 (78.196) Prec@5 96.000 (97.848) +2022-11-14 13:28:44,961 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1448 (0.1228) Prec@1 75.000 (78.128) Prec@5 98.000 (97.851) +2022-11-14 13:28:44,974 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.1227) Prec@1 81.000 (78.188) Prec@5 96.000 (97.812) +2022-11-14 13:28:44,990 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1222) Prec@1 82.000 (78.265) Prec@5 98.000 (97.816) +2022-11-14 13:28:45,003 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1581 (0.1229) Prec@1 75.000 (78.200) Prec@5 97.000 (97.800) +2022-11-14 13:28:45,017 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1227) Prec@1 80.000 (78.235) Prec@5 98.000 (97.804) +2022-11-14 13:28:45,034 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1284 (0.1229) Prec@1 76.000 (78.192) Prec@5 99.000 (97.827) +2022-11-14 13:28:45,050 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.1225) Prec@1 81.000 (78.245) Prec@5 100.000 (97.868) +2022-11-14 13:28:45,066 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1233 (0.1225) Prec@1 79.000 (78.259) Prec@5 97.000 (97.852) +2022-11-14 13:28:45,082 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1240 (0.1225) Prec@1 78.000 (78.255) Prec@5 99.000 (97.873) +2022-11-14 13:28:45,097 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.1222) Prec@1 82.000 (78.321) Prec@5 99.000 (97.893) +2022-11-14 13:28:45,113 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1553 (0.1228) Prec@1 73.000 (78.228) Prec@5 99.000 (97.912) +2022-11-14 13:28:45,130 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1166 (0.1227) Prec@1 79.000 (78.241) Prec@5 98.000 (97.914) +2022-11-14 13:28:45,143 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1651 (0.1234) Prec@1 69.000 (78.085) Prec@5 100.000 (97.949) +2022-11-14 13:28:45,158 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.1235) Prec@1 79.000 (78.100) Prec@5 99.000 (97.967) +2022-11-14 13:28:45,174 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1405 (0.1238) Prec@1 79.000 (78.115) Prec@5 97.000 (97.951) +2022-11-14 13:28:45,189 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1297 (0.1239) Prec@1 75.000 (78.065) Prec@5 96.000 (97.919) +2022-11-14 13:28:45,204 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.1236) Prec@1 81.000 (78.111) Prec@5 100.000 (97.952) +2022-11-14 13:28:45,218 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.1229) Prec@1 84.000 (78.203) Prec@5 99.000 (97.969) +2022-11-14 13:28:45,234 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1394 (0.1232) Prec@1 77.000 (78.185) Prec@5 97.000 (97.954) +2022-11-14 13:28:45,247 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1465 (0.1236) Prec@1 73.000 (78.106) Prec@5 98.000 (97.955) +2022-11-14 13:28:45,261 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.1234) Prec@1 78.000 (78.104) Prec@5 99.000 (97.970) +2022-11-14 13:28:45,275 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.1233) Prec@1 81.000 (78.147) Prec@5 98.000 (97.971) +2022-11-14 13:28:45,288 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.1230) Prec@1 80.000 (78.174) Prec@5 99.000 (97.986) +2022-11-14 13:28:45,302 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1581 (0.1235) Prec@1 72.000 (78.086) Prec@5 96.000 (97.957) +2022-11-14 13:28:45,316 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.1230) Prec@1 85.000 (78.183) Prec@5 99.000 (97.972) +2022-11-14 13:28:45,329 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1308 (0.1231) Prec@1 77.000 (78.167) Prec@5 98.000 (97.972) +2022-11-14 13:28:45,343 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1228) Prec@1 81.000 (78.205) Prec@5 100.000 (98.000) +2022-11-14 13:28:45,358 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.1223) Prec@1 86.000 (78.311) Prec@5 99.000 (98.014) +2022-11-14 13:28:45,372 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1477 (0.1226) Prec@1 78.000 (78.307) Prec@5 94.000 (97.960) +2022-11-14 13:28:45,387 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.1222) Prec@1 80.000 (78.329) Prec@5 100.000 (97.987) +2022-11-14 13:28:45,400 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1223) Prec@1 77.000 (78.312) Prec@5 99.000 (98.000) +2022-11-14 13:28:45,414 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1311 (0.1224) Prec@1 75.000 (78.269) Prec@5 97.000 (97.987) +2022-11-14 13:28:45,430 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.1222) Prec@1 83.000 (78.329) Prec@5 98.000 (97.987) +2022-11-14 13:28:45,447 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.1223) Prec@1 77.000 (78.312) Prec@5 98.000 (97.987) +2022-11-14 13:28:45,463 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.1221) Prec@1 84.000 (78.383) Prec@5 95.000 (97.951) +2022-11-14 13:28:45,478 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.1217) Prec@1 85.000 (78.463) Prec@5 97.000 (97.939) +2022-11-14 13:28:45,492 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1217) Prec@1 78.000 (78.458) Prec@5 95.000 (97.904) +2022-11-14 13:28:45,507 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1600 (0.1222) Prec@1 72.000 (78.381) Prec@5 98.000 (97.905) +2022-11-14 13:28:45,522 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1568 (0.1226) Prec@1 75.000 (78.341) Prec@5 93.000 (97.847) +2022-11-14 13:28:45,538 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1383 (0.1228) Prec@1 74.000 (78.291) Prec@5 99.000 (97.860) +2022-11-14 13:28:45,553 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.1227) Prec@1 79.000 (78.299) Prec@5 100.000 (97.885) +2022-11-14 13:28:45,566 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1226) Prec@1 80.000 (78.318) Prec@5 99.000 (97.898) +2022-11-14 13:28:45,581 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1408 (0.1228) Prec@1 73.000 (78.258) Prec@5 96.000 (97.876) +2022-11-14 13:28:45,598 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.1226) Prec@1 85.000 (78.333) Prec@5 99.000 (97.889) +2022-11-14 13:28:45,613 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.1225) Prec@1 83.000 (78.385) Prec@5 97.000 (97.879) +2022-11-14 13:28:45,629 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.1219) Prec@1 88.000 (78.489) Prec@5 99.000 (97.891) +2022-11-14 13:28:45,642 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1219) Prec@1 77.000 (78.473) Prec@5 98.000 (97.892) +2022-11-14 13:28:45,656 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1535 (0.1223) Prec@1 74.000 (78.426) Prec@5 98.000 (97.894) +2022-11-14 13:28:45,670 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.1222) Prec@1 77.000 (78.411) Prec@5 99.000 (97.905) +2022-11-14 13:28:45,686 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.1219) Prec@1 83.000 (78.458) Prec@5 96.000 (97.885) +2022-11-14 13:28:45,700 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.1216) Prec@1 80.000 (78.474) Prec@5 96.000 (97.866) +2022-11-14 13:28:45,716 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1218) Prec@1 75.000 (78.439) Prec@5 99.000 (97.878) +2022-11-14 13:28:45,730 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1407 (0.1220) Prec@1 76.000 (78.414) Prec@5 98.000 (97.879) +2022-11-14 13:28:45,745 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.1218) Prec@1 85.000 (78.480) Prec@5 100.000 (97.900) +2022-11-14 13:28:45,803 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:28:46,102 Epoch: [47][0/500] Time 0.024 (0.024) Data 0.216 (0.216) Loss 0.1000 (0.1000) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:28:46,422 Epoch: [47][10/500] Time 0.042 (0.028) Data 0.002 (0.021) Loss 0.1133 (0.1066) Prec@1 84.000 (83.500) Prec@5 96.000 (97.500) +2022-11-14 13:28:46,805 Epoch: [47][20/500] Time 0.036 (0.031) Data 0.002 (0.012) Loss 0.0896 (0.1010) Prec@1 83.000 (83.333) Prec@5 97.000 (97.333) +2022-11-14 13:28:47,190 Epoch: [47][30/500] Time 0.038 (0.032) Data 0.002 (0.009) Loss 0.1228 (0.1064) Prec@1 81.000 (82.750) Prec@5 97.000 (97.250) +2022-11-14 13:28:47,576 Epoch: [47][40/500] Time 0.037 (0.032) Data 0.002 (0.007) Loss 0.0882 (0.1028) Prec@1 85.000 (83.200) Prec@5 97.000 (97.200) +2022-11-14 13:28:48,067 Epoch: [47][50/500] Time 0.049 (0.035) Data 0.002 (0.006) Loss 0.1118 (0.1043) Prec@1 80.000 (82.667) Prec@5 98.000 (97.333) +2022-11-14 13:28:48,560 Epoch: [47][60/500] Time 0.049 (0.036) Data 0.002 (0.005) Loss 0.0741 (0.1000) Prec@1 87.000 (83.286) Prec@5 99.000 (97.571) +2022-11-14 13:28:48,936 Epoch: [47][70/500] Time 0.033 (0.036) Data 0.002 (0.005) Loss 0.0973 (0.0997) Prec@1 84.000 (83.375) Prec@5 99.000 (97.750) +2022-11-14 13:28:49,316 Epoch: [47][80/500] Time 0.033 (0.036) Data 0.002 (0.005) Loss 0.0954 (0.0992) Prec@1 83.000 (83.333) Prec@5 100.000 (98.000) +2022-11-14 13:28:49,710 Epoch: [47][90/500] Time 0.034 (0.036) Data 0.002 (0.004) Loss 0.0740 (0.0967) Prec@1 88.000 (83.800) Prec@5 100.000 (98.200) +2022-11-14 13:28:50,110 Epoch: [47][100/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.1102 (0.0979) Prec@1 81.000 (83.545) Prec@5 100.000 (98.364) +2022-11-14 13:28:50,490 Epoch: [47][110/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.1085 (0.0988) Prec@1 81.000 (83.333) Prec@5 97.000 (98.250) +2022-11-14 13:28:50,879 Epoch: [47][120/500] Time 0.036 (0.035) Data 0.002 (0.004) Loss 0.1317 (0.1013) Prec@1 76.000 (82.769) Prec@5 98.000 (98.231) +2022-11-14 13:28:51,272 Epoch: [47][130/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0845 (0.1001) Prec@1 85.000 (82.929) Prec@5 99.000 (98.286) +2022-11-14 13:28:51,648 Epoch: [47][140/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1094 (0.1007) Prec@1 80.000 (82.733) Prec@5 99.000 (98.333) +2022-11-14 13:28:52,043 Epoch: [47][150/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1116 (0.1014) Prec@1 80.000 (82.562) Prec@5 99.000 (98.375) +2022-11-14 13:28:52,479 Epoch: [47][160/500] Time 0.051 (0.035) Data 0.002 (0.003) Loss 0.1202 (0.1025) Prec@1 81.000 (82.471) Prec@5 99.000 (98.412) +2022-11-14 13:28:52,848 Epoch: [47][170/500] Time 0.035 (0.035) Data 0.001 (0.003) Loss 0.1024 (0.1025) Prec@1 84.000 (82.556) Prec@5 99.000 (98.444) +2022-11-14 13:28:53,244 Epoch: [47][180/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.1008 (0.1024) Prec@1 83.000 (82.579) Prec@5 97.000 (98.368) +2022-11-14 13:28:53,621 Epoch: [47][190/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.1208 (0.1033) Prec@1 80.000 (82.450) Prec@5 98.000 (98.350) +2022-11-14 13:28:54,025 Epoch: [47][200/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0926 (0.1028) Prec@1 83.000 (82.476) Prec@5 98.000 (98.333) +2022-11-14 13:28:54,490 Epoch: [47][210/500] Time 0.036 (0.035) Data 0.003 (0.003) Loss 0.1272 (0.1039) Prec@1 79.000 (82.318) Prec@5 98.000 (98.318) +2022-11-14 13:28:54,976 Epoch: [47][220/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.1143 (0.1044) Prec@1 78.000 (82.130) Prec@5 98.000 (98.304) +2022-11-14 13:28:55,440 Epoch: [47][230/500] Time 0.041 (0.036) Data 0.003 (0.003) Loss 0.1112 (0.1047) Prec@1 80.000 (82.042) Prec@5 100.000 (98.375) +2022-11-14 13:28:55,904 Epoch: [47][240/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.1090 (0.1048) Prec@1 79.000 (81.920) Prec@5 100.000 (98.440) +2022-11-14 13:28:56,351 Epoch: [47][250/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.0916 (0.1043) Prec@1 86.000 (82.077) Prec@5 100.000 (98.500) +2022-11-14 13:28:56,834 Epoch: [47][260/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.1136 (0.1047) Prec@1 80.000 (82.000) Prec@5 96.000 (98.407) +2022-11-14 13:28:57,249 Epoch: [47][270/500] Time 0.033 (0.037) Data 0.001 (0.003) Loss 0.1038 (0.1046) Prec@1 86.000 (82.143) Prec@5 98.000 (98.393) +2022-11-14 13:28:57,653 Epoch: [47][280/500] Time 0.058 (0.037) Data 0.002 (0.003) Loss 0.1288 (0.1055) Prec@1 77.000 (81.966) Prec@5 96.000 (98.310) +2022-11-14 13:28:58,054 Epoch: [47][290/500] Time 0.043 (0.037) Data 0.003 (0.003) Loss 0.1105 (0.1056) Prec@1 83.000 (82.000) Prec@5 99.000 (98.333) +2022-11-14 13:28:58,450 Epoch: [47][300/500] Time 0.037 (0.037) Data 0.004 (0.003) Loss 0.0790 (0.1048) Prec@1 88.000 (82.194) Prec@5 98.000 (98.323) +2022-11-14 13:28:58,817 Epoch: [47][310/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.1676 (0.1067) Prec@1 73.000 (81.906) Prec@5 96.000 (98.250) +2022-11-14 13:28:59,210 Epoch: [47][320/500] Time 0.035 (0.036) Data 0.003 (0.003) Loss 0.1349 (0.1076) Prec@1 77.000 (81.758) Prec@5 98.000 (98.242) +2022-11-14 13:28:59,614 Epoch: [47][330/500] Time 0.031 (0.036) Data 0.003 (0.003) Loss 0.0824 (0.1069) Prec@1 86.000 (81.882) Prec@5 99.000 (98.265) +2022-11-14 13:29:00,003 Epoch: [47][340/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0875 (0.1063) Prec@1 85.000 (81.971) Prec@5 99.000 (98.286) +2022-11-14 13:29:00,396 Epoch: [47][350/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.0954 (0.1060) Prec@1 82.000 (81.972) Prec@5 100.000 (98.333) +2022-11-14 13:29:00,790 Epoch: [47][360/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0897 (0.1056) Prec@1 83.000 (82.000) Prec@5 99.000 (98.351) +2022-11-14 13:29:01,224 Epoch: [47][370/500] Time 0.038 (0.036) Data 0.003 (0.003) Loss 0.0872 (0.1051) Prec@1 84.000 (82.053) Prec@5 99.000 (98.368) +2022-11-14 13:29:01,601 Epoch: [47][380/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0815 (0.1045) Prec@1 85.000 (82.128) Prec@5 97.000 (98.333) +2022-11-14 13:29:02,054 Epoch: [47][390/500] Time 0.054 (0.036) Data 0.003 (0.003) Loss 0.0794 (0.1038) Prec@1 86.000 (82.225) Prec@5 100.000 (98.375) +2022-11-14 13:29:02,449 Epoch: [47][400/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.1129 (0.1041) Prec@1 80.000 (82.171) Prec@5 100.000 (98.415) +2022-11-14 13:29:02,848 Epoch: [47][410/500] Time 0.030 (0.036) Data 0.002 (0.003) Loss 0.0758 (0.1034) Prec@1 86.000 (82.262) Prec@5 99.000 (98.429) +2022-11-14 13:29:03,249 Epoch: [47][420/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.1054 (0.1034) Prec@1 80.000 (82.209) Prec@5 100.000 (98.465) +2022-11-14 13:29:03,645 Epoch: [47][430/500] Time 0.038 (0.036) Data 0.001 (0.003) Loss 0.1284 (0.1040) Prec@1 77.000 (82.091) Prec@5 95.000 (98.386) +2022-11-14 13:29:04,057 Epoch: [47][440/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1077 (0.1041) Prec@1 79.000 (82.022) Prec@5 97.000 (98.356) +2022-11-14 13:29:04,433 Epoch: [47][450/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0929 (0.1038) Prec@1 85.000 (82.087) Prec@5 99.000 (98.370) +2022-11-14 13:29:04,826 Epoch: [47][460/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0915 (0.1036) Prec@1 83.000 (82.106) Prec@5 100.000 (98.404) +2022-11-14 13:29:05,223 Epoch: [47][470/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.1024 (0.1036) Prec@1 83.000 (82.125) Prec@5 98.000 (98.396) +2022-11-14 13:29:05,629 Epoch: [47][480/500] Time 0.042 (0.036) Data 0.003 (0.002) Loss 0.0832 (0.1031) Prec@1 85.000 (82.184) Prec@5 99.000 (98.408) +2022-11-14 13:29:06,030 Epoch: [47][490/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1137 (0.1034) Prec@1 81.000 (82.160) Prec@5 99.000 (98.420) +2022-11-14 13:29:06,411 Epoch: [47][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1129 (0.1035) Prec@1 82.000 (82.157) Prec@5 99.000 (98.431) +2022-11-14 13:29:06,809 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0965 (0.0965) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:29:06,821 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0988 (0.0976) Prec@1 85.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:29:06,838 Test: [2/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1102 (0.1018) Prec@1 82.000 (83.333) Prec@5 99.000 (99.667) +2022-11-14 13:29:06,850 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1256 (0.1078) Prec@1 79.000 (82.250) Prec@5 99.000 (99.500) +2022-11-14 13:29:06,861 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1251 (0.1112) Prec@1 80.000 (81.800) Prec@5 99.000 (99.400) +2022-11-14 13:29:06,873 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0662 (0.1037) Prec@1 87.000 (82.667) Prec@5 100.000 (99.500) +2022-11-14 13:29:06,889 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0836 (0.1009) Prec@1 87.000 (83.286) Prec@5 99.000 (99.429) +2022-11-14 13:29:06,900 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1137 (0.1025) Prec@1 79.000 (82.750) Prec@5 97.000 (99.125) +2022-11-14 13:29:06,910 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1342 (0.1060) Prec@1 82.000 (82.667) Prec@5 100.000 (99.222) +2022-11-14 13:29:06,923 Test: [9/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.1038) Prec@1 85.000 (82.900) Prec@5 96.000 (98.900) +2022-11-14 13:29:06,938 Test: [10/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.1029) Prec@1 86.000 (83.182) Prec@5 98.000 (98.818) +2022-11-14 13:29:06,954 Test: [11/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1228 (0.1045) Prec@1 74.000 (82.417) Prec@5 98.000 (98.750) +2022-11-14 13:29:06,969 Test: [12/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1122 (0.1051) Prec@1 78.000 (82.077) Prec@5 100.000 (98.846) +2022-11-14 13:29:06,983 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1067 (0.1052) Prec@1 83.000 (82.143) Prec@5 100.000 (98.929) +2022-11-14 13:29:06,996 Test: [14/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1107 (0.1056) Prec@1 80.000 (82.000) Prec@5 98.000 (98.867) +2022-11-14 13:29:07,010 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1322 (0.1073) Prec@1 76.000 (81.625) Prec@5 97.000 (98.750) +2022-11-14 13:29:07,024 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.1070) Prec@1 83.000 (81.706) Prec@5 98.000 (98.706) +2022-11-14 13:29:07,039 Test: [17/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1201 (0.1078) Prec@1 82.000 (81.722) Prec@5 100.000 (98.778) +2022-11-14 13:29:07,053 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1047 (0.1076) Prec@1 82.000 (81.737) Prec@5 98.000 (98.737) +2022-11-14 13:29:07,067 Test: [19/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1430 (0.1094) Prec@1 74.000 (81.350) Prec@5 96.000 (98.600) +2022-11-14 13:29:07,083 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1192 (0.1098) Prec@1 79.000 (81.238) Prec@5 98.000 (98.571) +2022-11-14 13:29:07,096 Test: [21/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0974 (0.1093) Prec@1 82.000 (81.273) Prec@5 100.000 (98.636) +2022-11-14 13:29:07,111 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1067 (0.1092) Prec@1 81.000 (81.261) Prec@5 100.000 (98.696) +2022-11-14 13:29:07,126 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.1080) Prec@1 85.000 (81.417) Prec@5 99.000 (98.708) +2022-11-14 13:29:07,140 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1328 (0.1090) Prec@1 79.000 (81.320) Prec@5 99.000 (98.720) +2022-11-14 13:29:07,154 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1367 (0.1101) Prec@1 75.000 (81.077) Prec@5 96.000 (98.615) +2022-11-14 13:29:07,169 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1229 (0.1106) Prec@1 77.000 (80.926) Prec@5 100.000 (98.667) +2022-11-14 13:29:07,184 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1363 (0.1115) Prec@1 76.000 (80.750) Prec@5 98.000 (98.643) +2022-11-14 13:29:07,197 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1066 (0.1113) Prec@1 83.000 (80.828) Prec@5 97.000 (98.586) +2022-11-14 13:29:07,212 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1142 (0.1114) Prec@1 81.000 (80.833) Prec@5 98.000 (98.567) +2022-11-14 13:29:07,226 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1180 (0.1116) Prec@1 82.000 (80.871) Prec@5 100.000 (98.613) +2022-11-14 13:29:07,239 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1099 (0.1116) Prec@1 80.000 (80.844) Prec@5 100.000 (98.656) +2022-11-14 13:29:07,254 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1210 (0.1119) Prec@1 78.000 (80.758) Prec@5 97.000 (98.606) +2022-11-14 13:29:07,268 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1407 (0.1127) Prec@1 79.000 (80.706) Prec@5 97.000 (98.559) +2022-11-14 13:29:07,282 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1182 (0.1129) Prec@1 78.000 (80.629) Prec@5 97.000 (98.514) +2022-11-14 13:29:07,298 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.1126) Prec@1 81.000 (80.639) Prec@5 99.000 (98.528) +2022-11-14 13:29:07,313 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1122 (0.1126) Prec@1 78.000 (80.568) Prec@5 97.000 (98.486) +2022-11-14 13:29:07,329 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1032 (0.1124) Prec@1 84.000 (80.658) Prec@5 97.000 (98.447) +2022-11-14 13:29:07,344 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0971 (0.1120) Prec@1 85.000 (80.769) Prec@5 98.000 (98.436) +2022-11-14 13:29:07,358 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1041 (0.1118) Prec@1 84.000 (80.850) Prec@5 99.000 (98.450) +2022-11-14 13:29:07,372 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1046 (0.1116) Prec@1 84.000 (80.927) Prec@5 98.000 (98.439) +2022-11-14 13:29:07,386 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.1111) Prec@1 85.000 (81.024) Prec@5 97.000 (98.405) +2022-11-14 13:29:07,403 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.1103) Prec@1 86.000 (81.140) Prec@5 100.000 (98.442) +2022-11-14 13:29:07,419 Test: [43/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0839 (0.1097) Prec@1 86.000 (81.250) Prec@5 97.000 (98.409) +2022-11-14 13:29:07,435 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1178 (0.1099) Prec@1 77.000 (81.156) Prec@5 98.000 (98.400) +2022-11-14 13:29:07,451 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1215 (0.1102) Prec@1 80.000 (81.130) Prec@5 97.000 (98.370) +2022-11-14 13:29:07,467 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1136 (0.1102) Prec@1 80.000 (81.106) Prec@5 98.000 (98.362) +2022-11-14 13:29:07,483 Test: [47/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.1099) Prec@1 85.000 (81.188) Prec@5 98.000 (98.354) +2022-11-14 13:29:07,498 Test: [48/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.1095) Prec@1 83.000 (81.224) Prec@5 99.000 (98.367) +2022-11-14 13:29:07,513 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1437 (0.1102) Prec@1 74.000 (81.080) Prec@5 99.000 (98.380) +2022-11-14 13:29:07,531 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1287 (0.1106) Prec@1 78.000 (81.020) Prec@5 97.000 (98.353) +2022-11-14 13:29:07,547 Test: [51/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1460 (0.1113) Prec@1 70.000 (80.808) Prec@5 97.000 (98.327) +2022-11-14 13:29:07,562 Test: [52/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1098 (0.1112) Prec@1 83.000 (80.849) Prec@5 99.000 (98.340) +2022-11-14 13:29:07,575 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1281 (0.1116) Prec@1 80.000 (80.833) Prec@5 99.000 (98.352) +2022-11-14 13:29:07,590 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1154 (0.1116) Prec@1 77.000 (80.764) Prec@5 100.000 (98.382) +2022-11-14 13:29:07,605 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.1116) Prec@1 81.000 (80.768) Prec@5 98.000 (98.375) +2022-11-14 13:29:07,621 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1189 (0.1118) Prec@1 79.000 (80.737) Prec@5 99.000 (98.386) +2022-11-14 13:29:07,635 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1184 (0.1119) Prec@1 81.000 (80.741) Prec@5 98.000 (98.379) +2022-11-14 13:29:07,650 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1408 (0.1124) Prec@1 75.000 (80.644) Prec@5 99.000 (98.390) +2022-11-14 13:29:07,663 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1319 (0.1127) Prec@1 77.000 (80.583) Prec@5 95.000 (98.333) +2022-11-14 13:29:07,677 Test: [60/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1259 (0.1129) Prec@1 79.000 (80.557) Prec@5 100.000 (98.361) +2022-11-14 13:29:07,691 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1188 (0.1130) Prec@1 76.000 (80.484) Prec@5 98.000 (98.355) +2022-11-14 13:29:07,705 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.1126) Prec@1 86.000 (80.571) Prec@5 98.000 (98.349) +2022-11-14 13:29:07,718 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0895 (0.1122) Prec@1 86.000 (80.656) Prec@5 100.000 (98.375) +2022-11-14 13:29:07,733 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1525 (0.1129) Prec@1 75.000 (80.569) Prec@5 95.000 (98.323) +2022-11-14 13:29:07,747 Test: [65/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1070 (0.1128) Prec@1 84.000 (80.621) Prec@5 99.000 (98.333) +2022-11-14 13:29:07,761 Test: [66/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0983 (0.1126) Prec@1 83.000 (80.657) Prec@5 100.000 (98.358) +2022-11-14 13:29:07,774 Test: [67/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1143 (0.1126) Prec@1 81.000 (80.662) Prec@5 98.000 (98.353) +2022-11-14 13:29:07,788 Test: [68/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1030 (0.1124) Prec@1 80.000 (80.652) Prec@5 100.000 (98.377) +2022-11-14 13:29:07,802 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1318 (0.1127) Prec@1 79.000 (80.629) Prec@5 96.000 (98.343) +2022-11-14 13:29:07,816 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1153 (0.1128) Prec@1 78.000 (80.592) Prec@5 98.000 (98.338) +2022-11-14 13:29:07,830 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1323 (0.1130) Prec@1 79.000 (80.569) Prec@5 99.000 (98.347) +2022-11-14 13:29:07,847 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.1129) Prec@1 83.000 (80.603) Prec@5 99.000 (98.356) +2022-11-14 13:29:07,863 Test: [73/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1098 (0.1128) Prec@1 83.000 (80.635) Prec@5 99.000 (98.365) +2022-11-14 13:29:07,880 Test: [74/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1468 (0.1133) Prec@1 73.000 (80.533) Prec@5 99.000 (98.373) +2022-11-14 13:29:07,897 Test: [75/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.1130) Prec@1 86.000 (80.605) Prec@5 99.000 (98.382) +2022-11-14 13:29:07,911 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1143 (0.1130) Prec@1 81.000 (80.610) Prec@5 98.000 (98.377) +2022-11-14 13:29:07,925 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1221 (0.1131) Prec@1 81.000 (80.615) Prec@5 97.000 (98.359) +2022-11-14 13:29:07,940 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0958 (0.1129) Prec@1 83.000 (80.646) Prec@5 98.000 (98.354) +2022-11-14 13:29:07,957 Test: [79/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1016 (0.1127) Prec@1 85.000 (80.700) Prec@5 99.000 (98.362) +2022-11-14 13:29:07,973 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.1125) Prec@1 85.000 (80.753) Prec@5 98.000 (98.358) +2022-11-14 13:29:07,990 Test: [81/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.1123) Prec@1 83.000 (80.780) Prec@5 100.000 (98.378) +2022-11-14 13:29:08,008 Test: [82/100] Model Time 0.015 (0.009) Loss Time 0.000 (0.000) Loss 0.0986 (0.1121) Prec@1 82.000 (80.795) Prec@5 97.000 (98.361) +2022-11-14 13:29:08,024 Test: [83/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1371 (0.1124) Prec@1 77.000 (80.750) Prec@5 99.000 (98.369) +2022-11-14 13:29:08,038 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1319 (0.1126) Prec@1 79.000 (80.729) Prec@5 97.000 (98.353) +2022-11-14 13:29:08,055 Test: [85/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.1350 (0.1129) Prec@1 75.000 (80.663) Prec@5 99.000 (98.360) +2022-11-14 13:29:08,071 Test: [86/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.1126) Prec@1 87.000 (80.736) Prec@5 99.000 (98.368) +2022-11-14 13:29:08,084 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1082 (0.1125) Prec@1 80.000 (80.727) Prec@5 100.000 (98.386) +2022-11-14 13:29:08,097 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1297 (0.1127) Prec@1 72.000 (80.629) Prec@5 99.000 (98.393) +2022-11-14 13:29:08,114 Test: [89/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.1127) Prec@1 81.000 (80.633) Prec@5 99.000 (98.400) +2022-11-14 13:29:08,132 Test: [90/100] Model Time 0.015 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.1125) Prec@1 83.000 (80.659) Prec@5 99.000 (98.407) +2022-11-14 13:29:08,150 Test: [91/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.1122) Prec@1 85.000 (80.707) Prec@5 99.000 (98.413) +2022-11-14 13:29:08,165 Test: [92/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1285 (0.1124) Prec@1 78.000 (80.677) Prec@5 98.000 (98.409) +2022-11-14 13:29:08,179 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1213 (0.1125) Prec@1 79.000 (80.660) Prec@5 97.000 (98.394) +2022-11-14 13:29:08,194 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1123 (0.1125) Prec@1 78.000 (80.632) Prec@5 99.000 (98.400) +2022-11-14 13:29:08,210 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0969 (0.1123) Prec@1 85.000 (80.677) Prec@5 98.000 (98.396) +2022-11-14 13:29:08,225 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.1120) Prec@1 88.000 (80.753) Prec@5 99.000 (98.402) +2022-11-14 13:29:08,239 Test: [97/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1118 (0.1120) Prec@1 82.000 (80.765) Prec@5 98.000 (98.398) +2022-11-14 13:29:08,253 Test: [98/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1070 (0.1119) Prec@1 80.000 (80.758) Prec@5 98.000 (98.394) +2022-11-14 13:29:08,266 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1397 (0.1122) Prec@1 76.000 (80.710) Prec@5 99.000 (98.400) +2022-11-14 13:29:08,336 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:29:08,693 Epoch: [48][0/500] Time 0.027 (0.027) Data 0.252 (0.252) Loss 0.1062 (0.1062) Prec@1 80.000 (80.000) Prec@5 100.000 (100.000) +2022-11-14 13:29:09,127 Epoch: [48][10/500] Time 0.045 (0.037) Data 0.002 (0.025) Loss 0.0773 (0.0918) Prec@1 89.000 (84.500) Prec@5 100.000 (100.000) +2022-11-14 13:29:09,545 Epoch: [48][20/500] Time 0.032 (0.037) Data 0.002 (0.014) Loss 0.0807 (0.0881) Prec@1 85.000 (84.667) Prec@5 99.000 (99.667) +2022-11-14 13:29:10,012 Epoch: [48][30/500] Time 0.049 (0.039) Data 0.003 (0.010) Loss 0.0992 (0.0909) Prec@1 82.000 (84.000) Prec@5 99.000 (99.500) +2022-11-14 13:29:10,417 Epoch: [48][40/500] Time 0.033 (0.038) Data 0.002 (0.008) Loss 0.0873 (0.0902) Prec@1 87.000 (84.600) Prec@5 100.000 (99.600) +2022-11-14 13:29:10,811 Epoch: [48][50/500] Time 0.038 (0.037) Data 0.002 (0.007) Loss 0.1207 (0.0953) Prec@1 81.000 (84.000) Prec@5 98.000 (99.333) +2022-11-14 13:29:11,243 Epoch: [48][60/500] Time 0.053 (0.037) Data 0.002 (0.006) Loss 0.1249 (0.0995) Prec@1 79.000 (83.286) Prec@5 100.000 (99.429) +2022-11-14 13:29:11,649 Epoch: [48][70/500] Time 0.031 (0.037) Data 0.003 (0.006) Loss 0.0625 (0.0949) Prec@1 90.000 (84.125) Prec@5 100.000 (99.500) +2022-11-14 13:29:12,133 Epoch: [48][80/500] Time 0.052 (0.038) Data 0.002 (0.005) Loss 0.0893 (0.0942) Prec@1 84.000 (84.111) Prec@5 100.000 (99.556) +2022-11-14 13:29:12,553 Epoch: [48][90/500] Time 0.052 (0.038) Data 0.002 (0.005) Loss 0.1154 (0.0964) Prec@1 80.000 (83.700) Prec@5 98.000 (99.400) +2022-11-14 13:29:12,963 Epoch: [48][100/500] Time 0.055 (0.038) Data 0.002 (0.005) Loss 0.1289 (0.0993) Prec@1 78.000 (83.182) Prec@5 99.000 (99.364) +2022-11-14 13:29:13,408 Epoch: [48][110/500] Time 0.038 (0.038) Data 0.002 (0.004) Loss 0.0996 (0.0993) Prec@1 83.000 (83.167) Prec@5 100.000 (99.417) +2022-11-14 13:29:13,890 Epoch: [48][120/500] Time 0.044 (0.038) Data 0.003 (0.004) Loss 0.0874 (0.0984) Prec@1 85.000 (83.308) Prec@5 99.000 (99.385) +2022-11-14 13:29:14,300 Epoch: [48][130/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0796 (0.0971) Prec@1 86.000 (83.500) Prec@5 100.000 (99.429) +2022-11-14 13:29:14,919 Epoch: [48][140/500] Time 0.064 (0.039) Data 0.002 (0.004) Loss 0.1067 (0.0977) Prec@1 81.000 (83.333) Prec@5 98.000 (99.333) +2022-11-14 13:29:15,509 Epoch: [48][150/500] Time 0.036 (0.040) Data 0.002 (0.004) Loss 0.1340 (0.1000) Prec@1 74.000 (82.750) Prec@5 98.000 (99.250) +2022-11-14 13:29:16,072 Epoch: [48][160/500] Time 0.044 (0.041) Data 0.002 (0.004) Loss 0.1053 (0.1003) Prec@1 83.000 (82.765) Prec@5 98.000 (99.176) +2022-11-14 13:29:16,565 Epoch: [48][170/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.1096 (0.1008) Prec@1 80.000 (82.611) Prec@5 99.000 (99.167) +2022-11-14 13:29:17,100 Epoch: [48][180/500] Time 0.064 (0.041) Data 0.002 (0.004) Loss 0.1064 (0.1011) Prec@1 81.000 (82.526) Prec@5 98.000 (99.105) +2022-11-14 13:29:17,793 Epoch: [48][190/500] Time 0.069 (0.043) Data 0.002 (0.003) Loss 0.0961 (0.1009) Prec@1 86.000 (82.700) Prec@5 96.000 (98.950) +2022-11-14 13:29:18,305 Epoch: [48][200/500] Time 0.063 (0.043) Data 0.002 (0.003) Loss 0.1294 (0.1022) Prec@1 76.000 (82.381) Prec@5 99.000 (98.952) +2022-11-14 13:29:18,989 Epoch: [48][210/500] Time 0.071 (0.044) Data 0.002 (0.003) Loss 0.0928 (0.1018) Prec@1 82.000 (82.364) Prec@5 100.000 (99.000) +2022-11-14 13:29:19,653 Epoch: [48][220/500] Time 0.062 (0.044) Data 0.002 (0.003) Loss 0.1193 (0.1025) Prec@1 78.000 (82.174) Prec@5 96.000 (98.870) +2022-11-14 13:29:20,306 Epoch: [48][230/500] Time 0.068 (0.045) Data 0.002 (0.003) Loss 0.1181 (0.1032) Prec@1 79.000 (82.042) Prec@5 100.000 (98.917) +2022-11-14 13:29:20,961 Epoch: [48][240/500] Time 0.065 (0.045) Data 0.002 (0.003) Loss 0.0744 (0.1020) Prec@1 86.000 (82.200) Prec@5 100.000 (98.960) +2022-11-14 13:29:21,592 Epoch: [48][250/500] Time 0.066 (0.046) Data 0.002 (0.003) Loss 0.1248 (0.1029) Prec@1 79.000 (82.077) Prec@5 99.000 (98.962) +2022-11-14 13:29:22,246 Epoch: [48][260/500] Time 0.068 (0.046) Data 0.002 (0.003) Loss 0.1488 (0.1046) Prec@1 75.000 (81.815) Prec@5 98.000 (98.926) +2022-11-14 13:29:22,896 Epoch: [48][270/500] Time 0.069 (0.047) Data 0.002 (0.003) Loss 0.0925 (0.1042) Prec@1 85.000 (81.929) Prec@5 98.000 (98.893) +2022-11-14 13:29:23,564 Epoch: [48][280/500] Time 0.069 (0.047) Data 0.002 (0.003) Loss 0.0599 (0.1027) Prec@1 90.000 (82.207) Prec@5 100.000 (98.931) +2022-11-14 13:29:24,069 Epoch: [48][290/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.1145 (0.1031) Prec@1 81.000 (82.167) Prec@5 99.000 (98.933) +2022-11-14 13:29:24,540 Epoch: [48][300/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0600 (0.1017) Prec@1 91.000 (82.452) Prec@5 100.000 (98.968) +2022-11-14 13:29:25,136 Epoch: [48][310/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.1014 (0.1017) Prec@1 83.000 (82.469) Prec@5 100.000 (99.000) +2022-11-14 13:29:25,658 Epoch: [48][320/500] Time 0.063 (0.047) Data 0.002 (0.003) Loss 0.1144 (0.1020) Prec@1 77.000 (82.303) Prec@5 98.000 (98.970) +2022-11-14 13:29:26,197 Epoch: [48][330/500] Time 0.035 (0.047) Data 0.002 (0.003) Loss 0.1202 (0.1026) Prec@1 83.000 (82.324) Prec@5 98.000 (98.941) +2022-11-14 13:29:26,705 Epoch: [48][340/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0930 (0.1023) Prec@1 84.000 (82.371) Prec@5 100.000 (98.971) +2022-11-14 13:29:27,195 Epoch: [48][350/500] Time 0.043 (0.047) Data 0.002 (0.003) Loss 0.1046 (0.1024) Prec@1 83.000 (82.389) Prec@5 99.000 (98.972) +2022-11-14 13:29:27,753 Epoch: [48][360/500] Time 0.090 (0.047) Data 0.002 (0.003) Loss 0.1081 (0.1025) Prec@1 82.000 (82.378) Prec@5 100.000 (99.000) +2022-11-14 13:29:28,273 Epoch: [48][370/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0948 (0.1023) Prec@1 82.000 (82.368) Prec@5 99.000 (99.000) +2022-11-14 13:29:28,804 Epoch: [48][380/500] Time 0.077 (0.047) Data 0.002 (0.003) Loss 0.1043 (0.1024) Prec@1 84.000 (82.410) Prec@5 100.000 (99.026) +2022-11-14 13:29:29,449 Epoch: [48][390/500] Time 0.071 (0.047) Data 0.002 (0.003) Loss 0.1276 (0.1030) Prec@1 75.000 (82.225) Prec@5 95.000 (98.925) +2022-11-14 13:29:30,094 Epoch: [48][400/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0982 (0.1029) Prec@1 81.000 (82.195) Prec@5 100.000 (98.951) +2022-11-14 13:29:30,579 Epoch: [48][410/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.1136 (0.1031) Prec@1 79.000 (82.119) Prec@5 96.000 (98.881) +2022-11-14 13:29:31,142 Epoch: [48][420/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0868 (0.1028) Prec@1 87.000 (82.233) Prec@5 99.000 (98.884) +2022-11-14 13:29:31,770 Epoch: [48][430/500] Time 0.060 (0.048) Data 0.002 (0.003) Loss 0.0898 (0.1025) Prec@1 84.000 (82.273) Prec@5 99.000 (98.886) +2022-11-14 13:29:32,345 Epoch: [48][440/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.1084 (0.1026) Prec@1 82.000 (82.267) Prec@5 100.000 (98.911) +2022-11-14 13:29:33,015 Epoch: [48][450/500] Time 0.067 (0.048) Data 0.002 (0.003) Loss 0.0700 (0.1019) Prec@1 87.000 (82.370) Prec@5 97.000 (98.870) +2022-11-14 13:29:33,669 Epoch: [48][460/500] Time 0.065 (0.048) Data 0.002 (0.003) Loss 0.0766 (0.1013) Prec@1 88.000 (82.489) Prec@5 99.000 (98.872) +2022-11-14 13:29:34,166 Epoch: [48][470/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0793 (0.1009) Prec@1 89.000 (82.625) Prec@5 100.000 (98.896) +2022-11-14 13:29:34,640 Epoch: [48][480/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0861 (0.1006) Prec@1 84.000 (82.653) Prec@5 99.000 (98.898) +2022-11-14 13:29:35,107 Epoch: [48][490/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0842 (0.1003) Prec@1 90.000 (82.800) Prec@5 99.000 (98.900) +2022-11-14 13:29:35,520 Epoch: [48][499/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0896 (0.1001) Prec@1 85.000 (82.843) Prec@5 100.000 (98.922) +2022-11-14 13:29:35,807 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1263 (0.1263) Prec@1 78.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:29:35,814 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1278 (0.1271) Prec@1 77.000 (77.500) Prec@5 99.000 (98.500) +2022-11-14 13:29:35,823 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1315 (0.1285) Prec@1 77.000 (77.333) Prec@5 98.000 (98.333) +2022-11-14 13:29:35,833 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1208 (0.1266) Prec@1 77.000 (77.250) Prec@5 100.000 (98.750) +2022-11-14 13:29:35,842 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1292) Prec@1 73.000 (76.400) Prec@5 99.000 (98.800) +2022-11-14 13:29:35,851 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.1199) Prec@1 89.000 (78.500) Prec@5 98.000 (98.667) +2022-11-14 13:29:35,859 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1410 (0.1229) Prec@1 74.000 (77.857) Prec@5 98.000 (98.571) +2022-11-14 13:29:35,869 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1368 (0.1246) Prec@1 77.000 (77.750) Prec@5 100.000 (98.750) +2022-11-14 13:29:35,879 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1456 (0.1270) Prec@1 76.000 (77.556) Prec@5 96.000 (98.444) +2022-11-14 13:29:35,887 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.1242) Prec@1 86.000 (78.400) Prec@5 97.000 (98.300) +2022-11-14 13:29:35,896 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.1226) Prec@1 80.000 (78.545) Prec@5 100.000 (98.455) +2022-11-14 13:29:35,907 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1283 (0.1230) Prec@1 78.000 (78.500) Prec@5 98.000 (98.417) +2022-11-14 13:29:35,917 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1439 (0.1246) Prec@1 75.000 (78.231) Prec@5 99.000 (98.462) +2022-11-14 13:29:35,928 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1549 (0.1268) Prec@1 68.000 (77.500) Prec@5 94.000 (98.143) +2022-11-14 13:29:35,937 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.1260) Prec@1 80.000 (77.667) Prec@5 98.000 (98.133) +2022-11-14 13:29:35,947 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1498 (0.1275) Prec@1 74.000 (77.438) Prec@5 98.000 (98.125) +2022-11-14 13:29:35,957 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1387 (0.1281) Prec@1 75.000 (77.294) Prec@5 98.000 (98.118) +2022-11-14 13:29:35,968 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1381 (0.1287) Prec@1 74.000 (77.111) Prec@5 99.000 (98.167) +2022-11-14 13:29:35,980 Test: [18/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1406 (0.1293) Prec@1 75.000 (77.000) Prec@5 98.000 (98.158) +2022-11-14 13:29:35,992 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1518 (0.1304) Prec@1 71.000 (76.700) Prec@5 96.000 (98.050) +2022-11-14 13:29:36,004 Test: [20/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1513 (0.1314) Prec@1 73.000 (76.524) Prec@5 96.000 (97.952) +2022-11-14 13:29:36,015 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.1309) Prec@1 80.000 (76.682) Prec@5 97.000 (97.909) +2022-11-14 13:29:36,026 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1426 (0.1314) Prec@1 75.000 (76.609) Prec@5 96.000 (97.826) +2022-11-14 13:29:36,037 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.1313) Prec@1 76.000 (76.583) Prec@5 98.000 (97.833) +2022-11-14 13:29:36,047 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1337 (0.1314) Prec@1 78.000 (76.640) Prec@5 98.000 (97.840) +2022-11-14 13:29:36,057 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1316 (0.1314) Prec@1 78.000 (76.692) Prec@5 96.000 (97.769) +2022-11-14 13:29:36,068 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1317) Prec@1 73.000 (76.556) Prec@5 99.000 (97.815) +2022-11-14 13:29:36,078 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1373 (0.1319) Prec@1 80.000 (76.679) Prec@5 99.000 (97.857) +2022-11-14 13:29:36,088 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1317) Prec@1 80.000 (76.793) Prec@5 97.000 (97.828) +2022-11-14 13:29:36,099 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1602 (0.1327) Prec@1 72.000 (76.633) Prec@5 96.000 (97.767) +2022-11-14 13:29:36,108 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1324) Prec@1 79.000 (76.710) Prec@5 98.000 (97.774) +2022-11-14 13:29:36,117 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1315) Prec@1 83.000 (76.906) Prec@5 99.000 (97.812) +2022-11-14 13:29:36,127 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1155 (0.1310) Prec@1 79.000 (76.970) Prec@5 96.000 (97.758) +2022-11-14 13:29:36,137 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1410 (0.1313) Prec@1 72.000 (76.824) Prec@5 95.000 (97.676) +2022-11-14 13:29:36,146 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.1306) Prec@1 80.000 (76.914) Prec@5 96.000 (97.629) +2022-11-14 13:29:36,157 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.1301) Prec@1 83.000 (77.083) Prec@5 99.000 (97.667) +2022-11-14 13:29:36,169 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.1298) Prec@1 80.000 (77.162) Prec@5 96.000 (97.622) +2022-11-14 13:29:36,181 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1506 (0.1303) Prec@1 77.000 (77.158) Prec@5 97.000 (97.605) +2022-11-14 13:29:36,193 Test: [38/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.1296) Prec@1 82.000 (77.282) Prec@5 99.000 (97.641) +2022-11-14 13:29:36,204 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.1292) Prec@1 79.000 (77.325) Prec@5 98.000 (97.650) +2022-11-14 13:29:36,214 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1234 (0.1291) Prec@1 80.000 (77.390) Prec@5 97.000 (97.634) +2022-11-14 13:29:36,225 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.1293) Prec@1 74.000 (77.310) Prec@5 97.000 (97.619) +2022-11-14 13:29:36,234 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.1283) Prec@1 86.000 (77.512) Prec@5 98.000 (97.628) +2022-11-14 13:29:36,243 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.1280) Prec@1 79.000 (77.545) Prec@5 99.000 (97.659) +2022-11-14 13:29:36,255 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1276) Prec@1 81.000 (77.622) Prec@5 98.000 (97.667) +2022-11-14 13:29:36,266 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1275 (0.1275) Prec@1 78.000 (77.630) Prec@5 99.000 (97.696) +2022-11-14 13:29:36,275 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1272 (0.1275) Prec@1 79.000 (77.660) Prec@5 99.000 (97.723) +2022-11-14 13:29:36,285 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1271) Prec@1 81.000 (77.729) Prec@5 96.000 (97.688) +2022-11-14 13:29:36,297 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.1269) Prec@1 78.000 (77.735) Prec@5 100.000 (97.735) +2022-11-14 13:29:36,307 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1729 (0.1278) Prec@1 68.000 (77.540) Prec@5 94.000 (97.660) +2022-11-14 13:29:36,317 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.1277) Prec@1 78.000 (77.549) Prec@5 98.000 (97.667) +2022-11-14 13:29:36,329 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.1276) Prec@1 76.000 (77.519) Prec@5 95.000 (97.615) +2022-11-14 13:29:36,340 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.1278) Prec@1 74.000 (77.453) Prec@5 99.000 (97.642) +2022-11-14 13:29:36,353 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.1272) Prec@1 82.000 (77.537) Prec@5 98.000 (97.648) +2022-11-14 13:29:36,364 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1532 (0.1277) Prec@1 73.000 (77.455) Prec@5 97.000 (97.636) +2022-11-14 13:29:36,374 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1275) Prec@1 81.000 (77.518) Prec@5 98.000 (97.643) +2022-11-14 13:29:36,385 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1316 (0.1276) Prec@1 75.000 (77.474) Prec@5 99.000 (97.667) +2022-11-14 13:29:36,395 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1274) Prec@1 82.000 (77.552) Prec@5 96.000 (97.638) +2022-11-14 13:29:36,407 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1294 (0.1274) Prec@1 74.000 (77.492) Prec@5 98.000 (97.644) +2022-11-14 13:29:36,419 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1264 (0.1274) Prec@1 77.000 (77.483) Prec@5 98.000 (97.650) +2022-11-14 13:29:36,431 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1274) Prec@1 82.000 (77.557) Prec@5 99.000 (97.672) +2022-11-14 13:29:36,442 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1361 (0.1275) Prec@1 76.000 (77.532) Prec@5 97.000 (97.661) +2022-11-14 13:29:36,452 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.1273) Prec@1 81.000 (77.587) Prec@5 97.000 (97.651) +2022-11-14 13:29:36,463 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.1266) Prec@1 83.000 (77.672) Prec@5 98.000 (97.656) +2022-11-14 13:29:36,475 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.1266) Prec@1 77.000 (77.662) Prec@5 97.000 (97.646) +2022-11-14 13:29:36,487 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1754 (0.1274) Prec@1 66.000 (77.485) Prec@5 97.000 (97.636) +2022-11-14 13:29:36,498 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.1269) Prec@1 84.000 (77.582) Prec@5 98.000 (97.642) +2022-11-14 13:29:36,510 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1231 (0.1268) Prec@1 81.000 (77.632) Prec@5 94.000 (97.588) +2022-11-14 13:29:36,521 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.1265) Prec@1 82.000 (77.696) Prec@5 97.000 (97.580) +2022-11-14 13:29:36,532 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1268) Prec@1 75.000 (77.657) Prec@5 96.000 (97.557) +2022-11-14 13:29:36,542 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1268) Prec@1 78.000 (77.662) Prec@5 98.000 (97.563) +2022-11-14 13:29:36,553 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1276 (0.1268) Prec@1 78.000 (77.667) Prec@5 99.000 (97.583) +2022-11-14 13:29:36,565 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1472 (0.1271) Prec@1 72.000 (77.589) Prec@5 99.000 (97.603) +2022-11-14 13:29:36,577 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1269) Prec@1 82.000 (77.649) Prec@5 98.000 (97.608) +2022-11-14 13:29:36,588 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1321 (0.1270) Prec@1 77.000 (77.640) Prec@5 98.000 (97.613) +2022-11-14 13:29:36,599 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.1269) Prec@1 78.000 (77.645) Prec@5 98.000 (97.618) +2022-11-14 13:29:36,611 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1268) Prec@1 79.000 (77.662) Prec@5 98.000 (97.623) +2022-11-14 13:29:36,622 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1338 (0.1269) Prec@1 74.000 (77.615) Prec@5 97.000 (97.615) +2022-11-14 13:29:36,632 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.1269) Prec@1 82.000 (77.671) Prec@5 98.000 (97.620) +2022-11-14 13:29:36,642 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1231 (0.1269) Prec@1 77.000 (77.662) Prec@5 99.000 (97.638) +2022-11-14 13:29:36,652 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.1265) Prec@1 83.000 (77.728) Prec@5 100.000 (97.667) +2022-11-14 13:29:36,662 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.1265) Prec@1 79.000 (77.744) Prec@5 95.000 (97.634) +2022-11-14 13:29:36,671 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1152 (0.1263) Prec@1 80.000 (77.771) Prec@5 96.000 (97.614) +2022-11-14 13:29:36,681 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1471 (0.1266) Prec@1 72.000 (77.702) Prec@5 98.000 (97.619) +2022-11-14 13:29:36,693 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1402 (0.1267) Prec@1 76.000 (77.682) Prec@5 96.000 (97.600) +2022-11-14 13:29:36,703 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1269) Prec@1 75.000 (77.651) Prec@5 97.000 (97.593) +2022-11-14 13:29:36,714 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1363 (0.1270) Prec@1 76.000 (77.632) Prec@5 97.000 (97.586) +2022-11-14 13:29:36,724 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1211 (0.1269) Prec@1 81.000 (77.670) Prec@5 99.000 (97.602) +2022-11-14 13:29:36,734 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.1268) Prec@1 78.000 (77.674) Prec@5 99.000 (97.618) +2022-11-14 13:29:36,744 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1268) Prec@1 79.000 (77.689) Prec@5 96.000 (97.600) +2022-11-14 13:29:36,755 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1344 (0.1269) Prec@1 75.000 (77.659) Prec@5 99.000 (97.615) +2022-11-14 13:29:36,766 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.1264) Prec@1 83.000 (77.717) Prec@5 98.000 (97.620) +2022-11-14 13:29:36,776 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1265) Prec@1 80.000 (77.742) Prec@5 98.000 (97.624) +2022-11-14 13:29:36,785 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1341 (0.1266) Prec@1 77.000 (77.734) Prec@5 95.000 (97.596) +2022-11-14 13:29:36,796 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.1263) Prec@1 82.000 (77.779) Prec@5 99.000 (97.611) +2022-11-14 13:29:36,805 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1261) Prec@1 79.000 (77.792) Prec@5 95.000 (97.583) +2022-11-14 13:29:36,814 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.1258) Prec@1 83.000 (77.845) Prec@5 98.000 (97.588) +2022-11-14 13:29:36,823 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.1257) Prec@1 81.000 (77.878) Prec@5 98.000 (97.592) +2022-11-14 13:29:36,833 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1479 (0.1259) Prec@1 76.000 (77.859) Prec@5 98.000 (97.596) +2022-11-14 13:29:36,844 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1503 (0.1262) Prec@1 73.000 (77.810) Prec@5 94.000 (97.560) +2022-11-14 13:29:36,902 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:29:37,227 Epoch: [49][0/500] Time 0.025 (0.025) Data 0.242 (0.242) Loss 0.0899 (0.0899) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:29:37,436 Epoch: [49][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.1266 (0.1083) Prec@1 76.000 (80.500) Prec@5 99.000 (99.500) +2022-11-14 13:29:37,643 Epoch: [49][20/500] Time 0.020 (0.019) Data 0.002 (0.013) Loss 0.1229 (0.1131) Prec@1 80.000 (80.333) Prec@5 97.000 (98.667) +2022-11-14 13:29:37,963 Epoch: [49][30/500] Time 0.039 (0.021) Data 0.002 (0.009) Loss 0.0749 (0.1036) Prec@1 89.000 (82.500) Prec@5 99.000 (98.750) +2022-11-14 13:29:38,412 Epoch: [49][40/500] Time 0.043 (0.026) Data 0.002 (0.008) Loss 0.1178 (0.1064) Prec@1 81.000 (82.200) Prec@5 95.000 (98.000) +2022-11-14 13:29:38,864 Epoch: [49][50/500] Time 0.041 (0.029) Data 0.002 (0.006) Loss 0.0805 (0.1021) Prec@1 88.000 (83.167) Prec@5 98.000 (98.000) +2022-11-14 13:29:39,324 Epoch: [49][60/500] Time 0.043 (0.031) Data 0.002 (0.006) Loss 0.1166 (0.1042) Prec@1 80.000 (82.714) Prec@5 98.000 (98.000) +2022-11-14 13:29:39,780 Epoch: [49][70/500] Time 0.040 (0.032) Data 0.002 (0.005) Loss 0.0962 (0.1032) Prec@1 85.000 (83.000) Prec@5 97.000 (97.875) +2022-11-14 13:29:40,273 Epoch: [49][80/500] Time 0.039 (0.034) Data 0.002 (0.005) Loss 0.0660 (0.0990) Prec@1 90.000 (83.778) Prec@5 100.000 (98.111) +2022-11-14 13:29:40,760 Epoch: [49][90/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0818 (0.0973) Prec@1 87.000 (84.100) Prec@5 100.000 (98.300) +2022-11-14 13:29:41,233 Epoch: [49][100/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.0973 (0.0973) Prec@1 82.000 (83.909) Prec@5 100.000 (98.455) +2022-11-14 13:29:41,652 Epoch: [49][110/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.1260 (0.0997) Prec@1 76.000 (83.250) Prec@5 98.000 (98.417) +2022-11-14 13:29:42,140 Epoch: [49][120/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.1118 (0.1006) Prec@1 79.000 (82.923) Prec@5 98.000 (98.385) +2022-11-14 13:29:42,567 Epoch: [49][130/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.1200 (0.1020) Prec@1 79.000 (82.643) Prec@5 100.000 (98.500) +2022-11-14 13:29:43,098 Epoch: [49][140/500] Time 0.082 (0.037) Data 0.002 (0.004) Loss 0.0827 (0.1007) Prec@1 86.000 (82.867) Prec@5 98.000 (98.467) +2022-11-14 13:29:43,521 Epoch: [49][150/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0814 (0.0995) Prec@1 88.000 (83.188) Prec@5 99.000 (98.500) +2022-11-14 13:29:43,969 Epoch: [49][160/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0668 (0.0976) Prec@1 87.000 (83.412) Prec@5 100.000 (98.588) +2022-11-14 13:29:44,451 Epoch: [49][170/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0993 (0.0977) Prec@1 81.000 (83.278) Prec@5 99.000 (98.611) +2022-11-14 13:29:44,895 Epoch: [49][180/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0971 (0.0977) Prec@1 82.000 (83.211) Prec@5 97.000 (98.526) +2022-11-14 13:29:45,406 Epoch: [49][190/500] Time 0.080 (0.038) Data 0.002 (0.003) Loss 0.0893 (0.0972) Prec@1 85.000 (83.300) Prec@5 100.000 (98.600) +2022-11-14 13:29:45,898 Epoch: [49][200/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0963 (0.0972) Prec@1 83.000 (83.286) Prec@5 100.000 (98.667) +2022-11-14 13:29:46,395 Epoch: [49][210/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0810 (0.0965) Prec@1 88.000 (83.500) Prec@5 99.000 (98.682) +2022-11-14 13:29:46,868 Epoch: [49][220/500] Time 0.030 (0.039) Data 0.002 (0.003) Loss 0.0853 (0.0960) Prec@1 84.000 (83.522) Prec@5 100.000 (98.739) +2022-11-14 13:29:47,374 Epoch: [49][230/500] Time 0.048 (0.039) Data 0.003 (0.003) Loss 0.1194 (0.0970) Prec@1 76.000 (83.208) Prec@5 99.000 (98.750) +2022-11-14 13:29:47,889 Epoch: [49][240/500] Time 0.063 (0.039) Data 0.002 (0.003) Loss 0.1261 (0.0981) Prec@1 76.000 (82.920) Prec@5 100.000 (98.800) +2022-11-14 13:29:48,363 Epoch: [49][250/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0868 (0.0977) Prec@1 83.000 (82.923) Prec@5 98.000 (98.769) +2022-11-14 13:29:48,860 Epoch: [49][260/500] Time 0.058 (0.040) Data 0.002 (0.003) Loss 0.0960 (0.0976) Prec@1 84.000 (82.963) Prec@5 99.000 (98.778) +2022-11-14 13:29:49,284 Epoch: [49][270/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.1121 (0.0981) Prec@1 79.000 (82.821) Prec@5 99.000 (98.786) +2022-11-14 13:29:49,756 Epoch: [49][280/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0966 (0.0981) Prec@1 83.000 (82.828) Prec@5 100.000 (98.828) +2022-11-14 13:29:50,307 Epoch: [49][290/500] Time 0.062 (0.040) Data 0.002 (0.003) Loss 0.1100 (0.0985) Prec@1 78.000 (82.667) Prec@5 98.000 (98.800) +2022-11-14 13:29:50,815 Epoch: [49][300/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.1131 (0.0990) Prec@1 78.000 (82.516) Prec@5 99.000 (98.806) +2022-11-14 13:29:51,248 Epoch: [49][310/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.1026 (0.0991) Prec@1 81.000 (82.469) Prec@5 98.000 (98.781) +2022-11-14 13:29:51,701 Epoch: [49][320/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.1177 (0.0996) Prec@1 78.000 (82.333) Prec@5 99.000 (98.788) +2022-11-14 13:29:52,151 Epoch: [49][330/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.1083 (0.0999) Prec@1 81.000 (82.294) Prec@5 99.000 (98.794) +2022-11-14 13:29:52,595 Epoch: [49][340/500] Time 0.042 (0.040) Data 0.001 (0.003) Loss 0.0831 (0.0994) Prec@1 86.000 (82.400) Prec@5 99.000 (98.800) +2022-11-14 13:29:53,039 Epoch: [49][350/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.1380 (0.1005) Prec@1 75.000 (82.194) Prec@5 100.000 (98.833) +2022-11-14 13:29:53,479 Epoch: [49][360/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0796 (0.0999) Prec@1 84.000 (82.243) Prec@5 100.000 (98.865) +2022-11-14 13:29:53,930 Epoch: [49][370/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.1136 (0.1003) Prec@1 80.000 (82.184) Prec@5 98.000 (98.842) +2022-11-14 13:29:54,375 Epoch: [49][380/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.1088 (0.1005) Prec@1 79.000 (82.103) Prec@5 97.000 (98.795) +2022-11-14 13:29:54,817 Epoch: [49][390/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.1054 (0.1006) Prec@1 83.000 (82.125) Prec@5 99.000 (98.800) +2022-11-14 13:29:55,262 Epoch: [49][400/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.1212 (0.1011) Prec@1 77.000 (82.000) Prec@5 98.000 (98.780) +2022-11-14 13:29:55,702 Epoch: [49][410/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.1341 (0.1019) Prec@1 77.000 (81.881) Prec@5 97.000 (98.738) +2022-11-14 13:29:56,149 Epoch: [49][420/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.1008 (0.1019) Prec@1 82.000 (81.884) Prec@5 98.000 (98.721) +2022-11-14 13:29:56,607 Epoch: [49][430/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.1492 (0.1030) Prec@1 74.000 (81.705) Prec@5 99.000 (98.727) +2022-11-14 13:29:57,109 Epoch: [49][440/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.1053 (0.1030) Prec@1 81.000 (81.689) Prec@5 100.000 (98.756) +2022-11-14 13:29:57,665 Epoch: [49][450/500] Time 0.059 (0.040) Data 0.002 (0.002) Loss 0.0823 (0.1026) Prec@1 85.000 (81.761) Prec@5 100.000 (98.783) +2022-11-14 13:29:58,227 Epoch: [49][460/500] Time 0.054 (0.041) Data 0.002 (0.002) Loss 0.1140 (0.1028) Prec@1 81.000 (81.745) Prec@5 98.000 (98.766) +2022-11-14 13:29:58,660 Epoch: [49][470/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.1430 (0.1036) Prec@1 74.000 (81.583) Prec@5 98.000 (98.750) +2022-11-14 13:29:59,101 Epoch: [49][480/500] Time 0.045 (0.040) Data 0.002 (0.002) Loss 0.1070 (0.1037) Prec@1 82.000 (81.592) Prec@5 98.000 (98.735) +2022-11-14 13:29:59,553 Epoch: [49][490/500] Time 0.043 (0.040) Data 0.001 (0.002) Loss 0.1003 (0.1036) Prec@1 84.000 (81.640) Prec@5 97.000 (98.700) +2022-11-14 13:29:59,949 Epoch: [49][499/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.1018 (0.1036) Prec@1 83.000 (81.667) Prec@5 100.000 (98.725) +2022-11-14 13:30:00,221 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.1064 (0.1064) Prec@1 82.000 (82.000) Prec@5 99.000 (99.000) +2022-11-14 13:30:00,233 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1148 (0.1106) Prec@1 81.000 (81.500) Prec@5 100.000 (99.500) +2022-11-14 13:30:00,242 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1209 (0.1140) Prec@1 78.000 (80.333) Prec@5 100.000 (99.667) +2022-11-14 13:30:00,255 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1164 (0.1146) Prec@1 74.000 (78.750) Prec@5 99.000 (99.500) +2022-11-14 13:30:00,266 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1281 (0.1173) Prec@1 74.000 (77.800) Prec@5 100.000 (99.600) +2022-11-14 13:30:00,275 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0842 (0.1118) Prec@1 83.000 (78.667) Prec@5 98.000 (99.333) +2022-11-14 13:30:00,285 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.1120) Prec@1 80.000 (78.857) Prec@5 98.000 (99.143) +2022-11-14 13:30:00,295 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1160 (0.1125) Prec@1 79.000 (78.875) Prec@5 99.000 (99.125) +2022-11-14 13:30:00,306 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1174 (0.1130) Prec@1 81.000 (79.111) Prec@5 98.000 (99.000) +2022-11-14 13:30:00,313 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.1104) Prec@1 85.000 (79.700) Prec@5 98.000 (98.900) +2022-11-14 13:30:00,323 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.1096) Prec@1 85.000 (80.182) Prec@5 99.000 (98.909) +2022-11-14 13:30:00,333 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.1097) Prec@1 78.000 (80.000) Prec@5 97.000 (98.750) +2022-11-14 13:30:00,343 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.1081) Prec@1 84.000 (80.308) Prec@5 100.000 (98.846) +2022-11-14 13:30:00,353 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.1070) Prec@1 86.000 (80.714) Prec@5 98.000 (98.786) +2022-11-14 13:30:00,366 Test: [14/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.1073) Prec@1 79.000 (80.600) Prec@5 99.000 (98.800) +2022-11-14 13:30:00,376 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1413 (0.1094) Prec@1 74.000 (80.188) Prec@5 98.000 (98.750) +2022-11-14 13:30:00,386 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.1089) Prec@1 83.000 (80.353) Prec@5 99.000 (98.765) +2022-11-14 13:30:00,396 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.1090) Prec@1 81.000 (80.389) Prec@5 98.000 (98.722) +2022-11-14 13:30:00,407 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1103 (0.1091) Prec@1 80.000 (80.368) Prec@5 98.000 (98.684) +2022-11-14 13:30:00,419 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1292 (0.1101) Prec@1 76.000 (80.150) Prec@5 96.000 (98.550) +2022-11-14 13:30:00,429 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.1100) Prec@1 79.000 (80.095) Prec@5 97.000 (98.476) +2022-11-14 13:30:00,440 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.1089) Prec@1 85.000 (80.318) Prec@5 99.000 (98.500) +2022-11-14 13:30:00,453 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1201 (0.1094) Prec@1 80.000 (80.304) Prec@5 95.000 (98.348) +2022-11-14 13:30:00,464 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1209 (0.1099) Prec@1 74.000 (80.042) Prec@5 98.000 (98.333) +2022-11-14 13:30:00,475 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1334 (0.1108) Prec@1 77.000 (79.920) Prec@5 99.000 (98.360) +2022-11-14 13:30:00,485 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1329 (0.1117) Prec@1 75.000 (79.731) Prec@5 97.000 (98.308) +2022-11-14 13:30:00,497 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1040 (0.1114) Prec@1 80.000 (79.741) Prec@5 100.000 (98.370) +2022-11-14 13:30:00,509 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.1112) Prec@1 82.000 (79.821) Prec@5 99.000 (98.393) +2022-11-14 13:30:00,517 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.1110) Prec@1 79.000 (79.793) Prec@5 97.000 (98.345) +2022-11-14 13:30:00,527 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1140 (0.1111) Prec@1 79.000 (79.767) Prec@5 98.000 (98.333) +2022-11-14 13:30:00,539 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1050 (0.1109) Prec@1 83.000 (79.871) Prec@5 96.000 (98.258) +2022-11-14 13:30:00,550 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.1107) Prec@1 80.000 (79.875) Prec@5 98.000 (98.250) +2022-11-14 13:30:00,560 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1148 (0.1108) Prec@1 78.000 (79.818) Prec@5 98.000 (98.242) +2022-11-14 13:30:00,572 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1185 (0.1110) Prec@1 77.000 (79.735) Prec@5 98.000 (98.235) +2022-11-14 13:30:00,583 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.1106) Prec@1 85.000 (79.886) Prec@5 97.000 (98.200) +2022-11-14 13:30:00,594 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.1107) Prec@1 84.000 (80.000) Prec@5 99.000 (98.222) +2022-11-14 13:30:00,606 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.1113) Prec@1 75.000 (79.865) Prec@5 96.000 (98.162) +2022-11-14 13:30:00,617 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1227 (0.1116) Prec@1 78.000 (79.816) Prec@5 98.000 (98.158) +2022-11-14 13:30:00,628 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.1112) Prec@1 84.000 (79.923) Prec@5 98.000 (98.154) +2022-11-14 13:30:00,641 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.1110) Prec@1 84.000 (80.025) Prec@5 99.000 (98.175) +2022-11-14 13:30:00,653 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1110) Prec@1 80.000 (80.024) Prec@5 98.000 (98.171) +2022-11-14 13:30:00,666 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.1107) Prec@1 80.000 (80.024) Prec@5 97.000 (98.143) +2022-11-14 13:30:00,676 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.1097) Prec@1 91.000 (80.279) Prec@5 97.000 (98.116) +2022-11-14 13:30:00,686 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.1098) Prec@1 79.000 (80.250) Prec@5 96.000 (98.068) +2022-11-14 13:30:00,700 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.1094) Prec@1 84.000 (80.333) Prec@5 97.000 (98.044) +2022-11-14 13:30:00,713 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1291 (0.1099) Prec@1 75.000 (80.217) Prec@5 98.000 (98.043) +2022-11-14 13:30:00,724 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1258 (0.1102) Prec@1 77.000 (80.149) Prec@5 98.000 (98.043) +2022-11-14 13:30:00,734 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.1103) Prec@1 81.000 (80.167) Prec@5 99.000 (98.062) +2022-11-14 13:30:00,747 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.1099) Prec@1 86.000 (80.286) Prec@5 100.000 (98.102) +2022-11-14 13:30:00,759 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1152 (0.1100) Prec@1 80.000 (80.280) Prec@5 98.000 (98.100) +2022-11-14 13:30:00,770 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.1097) Prec@1 86.000 (80.392) Prec@5 99.000 (98.118) +2022-11-14 13:30:00,780 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.1097) Prec@1 77.000 (80.327) Prec@5 99.000 (98.135) +2022-11-14 13:30:00,793 Test: [52/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.1094) Prec@1 81.000 (80.340) Prec@5 100.000 (98.170) +2022-11-14 13:30:00,805 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.1093) Prec@1 81.000 (80.352) Prec@5 98.000 (98.167) +2022-11-14 13:30:00,815 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1204 (0.1095) Prec@1 81.000 (80.364) Prec@5 97.000 (98.145) +2022-11-14 13:30:00,825 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.1096) Prec@1 82.000 (80.393) Prec@5 98.000 (98.143) +2022-11-14 13:30:00,839 Test: [56/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1263 (0.1099) Prec@1 76.000 (80.316) Prec@5 98.000 (98.140) +2022-11-14 13:30:00,850 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.1097) Prec@1 84.000 (80.379) Prec@5 98.000 (98.138) +2022-11-14 13:30:00,861 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1349 (0.1101) Prec@1 75.000 (80.288) Prec@5 100.000 (98.169) +2022-11-14 13:30:00,872 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.1100) Prec@1 82.000 (80.317) Prec@5 98.000 (98.167) +2022-11-14 13:30:00,884 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.1100) Prec@1 82.000 (80.344) Prec@5 99.000 (98.180) +2022-11-14 13:30:00,896 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.1098) Prec@1 85.000 (80.419) Prec@5 98.000 (98.177) +2022-11-14 13:30:00,907 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.1095) Prec@1 86.000 (80.508) Prec@5 98.000 (98.175) +2022-11-14 13:30:00,916 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.1094) Prec@1 81.000 (80.516) Prec@5 100.000 (98.203) +2022-11-14 13:30:00,929 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1264 (0.1097) Prec@1 77.000 (80.462) Prec@5 99.000 (98.215) +2022-11-14 13:30:00,941 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1346 (0.1101) Prec@1 80.000 (80.455) Prec@5 99.000 (98.227) +2022-11-14 13:30:00,952 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.1099) Prec@1 83.000 (80.493) Prec@5 99.000 (98.239) +2022-11-14 13:30:00,963 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1319 (0.1102) Prec@1 79.000 (80.471) Prec@5 98.000 (98.235) +2022-11-14 13:30:00,975 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1172 (0.1103) Prec@1 78.000 (80.435) Prec@5 100.000 (98.261) +2022-11-14 13:30:00,987 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1559 (0.1110) Prec@1 72.000 (80.314) Prec@5 96.000 (98.229) +2022-11-14 13:30:00,998 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.1107) Prec@1 85.000 (80.380) Prec@5 100.000 (98.254) +2022-11-14 13:30:01,009 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.1107) Prec@1 82.000 (80.403) Prec@5 96.000 (98.222) +2022-11-14 13:30:01,021 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.1104) Prec@1 85.000 (80.466) Prec@5 99.000 (98.233) +2022-11-14 13:30:01,034 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.1101) Prec@1 86.000 (80.541) Prec@5 99.000 (98.243) +2022-11-14 13:30:01,045 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1102) Prec@1 77.000 (80.493) Prec@5 99.000 (98.253) +2022-11-14 13:30:01,055 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.1101) Prec@1 82.000 (80.513) Prec@5 100.000 (98.276) +2022-11-14 13:30:01,066 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.1099) Prec@1 81.000 (80.519) Prec@5 99.000 (98.286) +2022-11-14 13:30:01,078 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.1098) Prec@1 84.000 (80.564) Prec@5 98.000 (98.282) +2022-11-14 13:30:01,091 Test: [78/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1236 (0.1099) Prec@1 80.000 (80.557) Prec@5 99.000 (98.291) +2022-11-14 13:30:01,103 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1302 (0.1102) Prec@1 77.000 (80.513) Prec@5 99.000 (98.300) +2022-11-14 13:30:01,113 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.1100) Prec@1 83.000 (80.543) Prec@5 100.000 (98.321) +2022-11-14 13:30:01,123 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.1100) Prec@1 80.000 (80.537) Prec@5 98.000 (98.317) +2022-11-14 13:30:01,135 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.1101) Prec@1 78.000 (80.506) Prec@5 100.000 (98.337) +2022-11-14 13:30:01,146 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.1100) Prec@1 79.000 (80.488) Prec@5 98.000 (98.333) +2022-11-14 13:30:01,157 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.1099) Prec@1 82.000 (80.506) Prec@5 99.000 (98.341) +2022-11-14 13:30:01,167 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1468 (0.1103) Prec@1 70.000 (80.384) Prec@5 98.000 (98.337) +2022-11-14 13:30:01,180 Test: [86/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.1104) Prec@1 83.000 (80.414) Prec@5 98.000 (98.333) +2022-11-14 13:30:01,192 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.1104) Prec@1 81.000 (80.420) Prec@5 98.000 (98.330) +2022-11-14 13:30:01,204 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.1105) Prec@1 78.000 (80.393) Prec@5 96.000 (98.303) +2022-11-14 13:30:01,214 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1209 (0.1106) Prec@1 82.000 (80.411) Prec@5 97.000 (98.289) +2022-11-14 13:30:01,224 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.1104) Prec@1 83.000 (80.440) Prec@5 100.000 (98.308) +2022-11-14 13:30:01,236 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.1099) Prec@1 90.000 (80.543) Prec@5 100.000 (98.326) +2022-11-14 13:30:01,246 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1330 (0.1102) Prec@1 77.000 (80.505) Prec@5 99.000 (98.333) +2022-11-14 13:30:01,257 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.1100) Prec@1 83.000 (80.532) Prec@5 100.000 (98.351) +2022-11-14 13:30:01,268 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1211 (0.1101) Prec@1 80.000 (80.526) Prec@5 98.000 (98.347) +2022-11-14 13:30:01,278 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.1100) Prec@1 82.000 (80.542) Prec@5 99.000 (98.354) +2022-11-14 13:30:01,289 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.1100) Prec@1 82.000 (80.557) Prec@5 98.000 (98.351) +2022-11-14 13:30:01,301 Test: [97/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.1100) Prec@1 81.000 (80.561) Prec@5 98.000 (98.347) +2022-11-14 13:30:01,314 Test: [98/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1470 (0.1104) Prec@1 74.000 (80.495) Prec@5 99.000 (98.354) +2022-11-14 13:30:01,326 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.1104) Prec@1 81.000 (80.500) Prec@5 99.000 (98.360) +2022-11-14 13:30:01,381 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:30:01,682 Epoch: [50][0/500] Time 0.026 (0.026) Data 0.214 (0.214) Loss 0.0833 (0.0833) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 13:30:01,897 Epoch: [50][10/500] Time 0.018 (0.019) Data 0.002 (0.021) Loss 0.1071 (0.0952) Prec@1 82.000 (84.000) Prec@5 97.000 (98.500) +2022-11-14 13:30:02,106 Epoch: [50][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.1159 (0.1021) Prec@1 74.000 (80.667) Prec@5 99.000 (98.667) +2022-11-14 13:30:02,453 Epoch: [50][30/500] Time 0.041 (0.023) Data 0.002 (0.009) Loss 0.1135 (0.1049) Prec@1 82.000 (81.000) Prec@5 100.000 (99.000) +2022-11-14 13:30:02,835 Epoch: [50][40/500] Time 0.040 (0.025) Data 0.002 (0.007) Loss 0.0928 (0.1025) Prec@1 83.000 (81.400) Prec@5 98.000 (98.800) +2022-11-14 13:30:03,218 Epoch: [50][50/500] Time 0.042 (0.027) Data 0.002 (0.006) Loss 0.1145 (0.1045) Prec@1 81.000 (81.333) Prec@5 97.000 (98.500) +2022-11-14 13:30:03,613 Epoch: [50][60/500] Time 0.039 (0.028) Data 0.002 (0.005) Loss 0.0772 (0.1006) Prec@1 86.000 (82.000) Prec@5 99.000 (98.571) +2022-11-14 13:30:04,004 Epoch: [50][70/500] Time 0.041 (0.029) Data 0.002 (0.005) Loss 0.1152 (0.1024) Prec@1 78.000 (81.500) Prec@5 98.000 (98.500) +2022-11-14 13:30:04,403 Epoch: [50][80/500] Time 0.039 (0.030) Data 0.002 (0.005) Loss 0.1219 (0.1046) Prec@1 75.000 (80.778) Prec@5 98.000 (98.444) +2022-11-14 13:30:04,726 Epoch: [50][90/500] Time 0.028 (0.030) Data 0.002 (0.004) Loss 0.0942 (0.1036) Prec@1 81.000 (80.800) Prec@5 99.000 (98.500) +2022-11-14 13:30:05,112 Epoch: [50][100/500] Time 0.021 (0.030) Data 0.002 (0.004) Loss 0.1176 (0.1048) Prec@1 81.000 (80.818) Prec@5 96.000 (98.273) +2022-11-14 13:30:05,436 Epoch: [50][110/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.1088 (0.1052) Prec@1 82.000 (80.917) Prec@5 98.000 (98.250) +2022-11-14 13:30:05,745 Epoch: [50][120/500] Time 0.029 (0.030) Data 0.002 (0.004) Loss 0.1167 (0.1060) Prec@1 82.000 (81.000) Prec@5 100.000 (98.385) +2022-11-14 13:30:06,064 Epoch: [50][130/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0980 (0.1055) Prec@1 83.000 (81.143) Prec@5 98.000 (98.357) +2022-11-14 13:30:06,386 Epoch: [50][140/500] Time 0.028 (0.030) Data 0.002 (0.003) Loss 0.1038 (0.1054) Prec@1 81.000 (81.133) Prec@5 99.000 (98.400) +2022-11-14 13:30:06,700 Epoch: [50][150/500] Time 0.028 (0.030) Data 0.002 (0.003) Loss 0.1115 (0.1057) Prec@1 81.000 (81.125) Prec@5 97.000 (98.312) +2022-11-14 13:30:07,032 Epoch: [50][160/500] Time 0.029 (0.030) Data 0.002 (0.003) Loss 0.1214 (0.1067) Prec@1 80.000 (81.059) Prec@5 99.000 (98.353) +2022-11-14 13:30:07,356 Epoch: [50][170/500] Time 0.030 (0.030) Data 0.001 (0.003) Loss 0.1150 (0.1071) Prec@1 79.000 (80.944) Prec@5 98.000 (98.333) +2022-11-14 13:30:07,669 Epoch: [50][180/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.1017 (0.1068) Prec@1 81.000 (80.947) Prec@5 98.000 (98.316) +2022-11-14 13:30:07,994 Epoch: [50][190/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.1121 (0.1071) Prec@1 78.000 (80.800) Prec@5 100.000 (98.400) +2022-11-14 13:30:08,318 Epoch: [50][200/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0831 (0.1060) Prec@1 86.000 (81.048) Prec@5 100.000 (98.476) +2022-11-14 13:30:08,644 Epoch: [50][210/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.1150 (0.1064) Prec@1 82.000 (81.091) Prec@5 100.000 (98.545) +2022-11-14 13:30:08,973 Epoch: [50][220/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0973 (0.1060) Prec@1 81.000 (81.087) Prec@5 98.000 (98.522) +2022-11-14 13:30:09,295 Epoch: [50][230/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0948 (0.1055) Prec@1 81.000 (81.083) Prec@5 100.000 (98.583) +2022-11-14 13:30:09,625 Epoch: [50][240/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.1219 (0.1062) Prec@1 76.000 (80.880) Prec@5 96.000 (98.480) +2022-11-14 13:30:09,947 Epoch: [50][250/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.0838 (0.1053) Prec@1 84.000 (81.000) Prec@5 98.000 (98.462) +2022-11-14 13:30:10,275 Epoch: [50][260/500] Time 0.029 (0.029) Data 0.001 (0.003) Loss 0.1036 (0.1052) Prec@1 80.000 (80.963) Prec@5 96.000 (98.370) +2022-11-14 13:30:10,628 Epoch: [50][270/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.0874 (0.1046) Prec@1 85.000 (81.107) Prec@5 99.000 (98.393) +2022-11-14 13:30:11,130 Epoch: [50][280/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.1058 (0.1047) Prec@1 85.000 (81.241) Prec@5 99.000 (98.414) +2022-11-14 13:30:11,612 Epoch: [50][290/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0943 (0.1043) Prec@1 81.000 (81.233) Prec@5 97.000 (98.367) +2022-11-14 13:30:12,093 Epoch: [50][300/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.1126 (0.1046) Prec@1 78.000 (81.129) Prec@5 99.000 (98.387) +2022-11-14 13:30:12,577 Epoch: [50][310/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1164 (0.1049) Prec@1 82.000 (81.156) Prec@5 100.000 (98.438) +2022-11-14 13:30:13,188 Epoch: [50][320/500] Time 0.093 (0.032) Data 0.002 (0.003) Loss 0.1072 (0.1050) Prec@1 80.000 (81.121) Prec@5 96.000 (98.364) +2022-11-14 13:30:14,097 Epoch: [50][330/500] Time 0.082 (0.033) Data 0.002 (0.003) Loss 0.0841 (0.1044) Prec@1 86.000 (81.265) Prec@5 99.000 (98.382) +2022-11-14 13:30:14,961 Epoch: [50][340/500] Time 0.078 (0.035) Data 0.002 (0.003) Loss 0.0985 (0.1042) Prec@1 84.000 (81.343) Prec@5 99.000 (98.400) +2022-11-14 13:30:15,849 Epoch: [50][350/500] Time 0.083 (0.036) Data 0.002 (0.003) Loss 0.1077 (0.1043) Prec@1 77.000 (81.222) Prec@5 98.000 (98.389) +2022-11-14 13:30:16,731 Epoch: [50][360/500] Time 0.096 (0.037) Data 0.003 (0.003) Loss 0.1195 (0.1047) Prec@1 78.000 (81.135) Prec@5 99.000 (98.405) +2022-11-14 13:30:17,231 Epoch: [50][370/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.1210 (0.1052) Prec@1 78.000 (81.053) Prec@5 98.000 (98.395) +2022-11-14 13:30:17,708 Epoch: [50][380/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0886 (0.1047) Prec@1 82.000 (81.077) Prec@5 99.000 (98.410) +2022-11-14 13:30:18,184 Epoch: [50][390/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.1084 (0.1048) Prec@1 83.000 (81.125) Prec@5 99.000 (98.425) +2022-11-14 13:30:18,655 Epoch: [50][400/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0925 (0.1045) Prec@1 85.000 (81.220) Prec@5 100.000 (98.463) +2022-11-14 13:30:19,145 Epoch: [50][410/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0872 (0.1041) Prec@1 86.000 (81.333) Prec@5 99.000 (98.476) +2022-11-14 13:30:19,666 Epoch: [50][420/500] Time 0.072 (0.038) Data 0.005 (0.003) Loss 0.1121 (0.1043) Prec@1 78.000 (81.256) Prec@5 98.000 (98.465) +2022-11-14 13:30:20,123 Epoch: [50][430/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0870 (0.1039) Prec@1 88.000 (81.409) Prec@5 99.000 (98.477) +2022-11-14 13:30:20,606 Epoch: [50][440/500] Time 0.048 (0.038) Data 0.003 (0.003) Loss 0.1293 (0.1045) Prec@1 78.000 (81.333) Prec@5 99.000 (98.489) +2022-11-14 13:30:21,087 Epoch: [50][450/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0826 (0.1040) Prec@1 85.000 (81.413) Prec@5 99.000 (98.500) +2022-11-14 13:30:21,571 Epoch: [50][460/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0753 (0.1034) Prec@1 85.000 (81.489) Prec@5 97.000 (98.468) +2022-11-14 13:30:22,057 Epoch: [50][470/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.1047 (0.1034) Prec@1 82.000 (81.500) Prec@5 97.000 (98.438) +2022-11-14 13:30:22,546 Epoch: [50][480/500] Time 0.046 (0.039) Data 0.003 (0.003) Loss 0.1019 (0.1034) Prec@1 80.000 (81.469) Prec@5 99.000 (98.449) +2022-11-14 13:30:23,039 Epoch: [50][490/500] Time 0.048 (0.039) Data 0.003 (0.003) Loss 0.1114 (0.1035) Prec@1 81.000 (81.460) Prec@5 98.000 (98.440) +2022-11-14 13:30:23,460 Epoch: [50][499/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.1307 (0.1041) Prec@1 77.000 (81.373) Prec@5 99.000 (98.451) +2022-11-14 13:30:23,872 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.1240 (0.1240) Prec@1 77.000 (77.000) Prec@5 99.000 (99.000) +2022-11-14 13:30:23,883 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0982 (0.1111) Prec@1 83.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:30:23,901 Test: [2/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1453 (0.1225) Prec@1 72.000 (77.333) Prec@5 98.000 (98.667) +2022-11-14 13:30:23,921 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1143 (0.1205) Prec@1 81.000 (78.250) Prec@5 99.000 (98.750) +2022-11-14 13:30:23,931 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1219 (0.1208) Prec@1 78.000 (78.200) Prec@5 98.000 (98.600) +2022-11-14 13:30:23,943 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.1147) Prec@1 85.000 (79.333) Prec@5 98.000 (98.500) +2022-11-14 13:30:23,954 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1125 (0.1144) Prec@1 79.000 (79.286) Prec@5 97.000 (98.286) +2022-11-14 13:30:23,972 Test: [7/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1342 (0.1169) Prec@1 74.000 (78.625) Prec@5 98.000 (98.250) +2022-11-14 13:30:23,986 Test: [8/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1035 (0.1154) Prec@1 83.000 (79.111) Prec@5 100.000 (98.444) +2022-11-14 13:30:23,999 Test: [9/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0962 (0.1135) Prec@1 83.000 (79.500) Prec@5 98.000 (98.400) +2022-11-14 13:30:24,013 Test: [10/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1195 (0.1140) Prec@1 81.000 (79.636) Prec@5 99.000 (98.455) +2022-11-14 13:30:24,026 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1410 (0.1163) Prec@1 76.000 (79.333) Prec@5 97.000 (98.333) +2022-11-14 13:30:24,038 Test: [12/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1158 (0.1162) Prec@1 78.000 (79.231) Prec@5 99.000 (98.385) +2022-11-14 13:30:24,050 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1073 (0.1156) Prec@1 82.000 (79.429) Prec@5 98.000 (98.357) +2022-11-14 13:30:24,063 Test: [14/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1131 (0.1154) Prec@1 81.000 (79.533) Prec@5 97.000 (98.267) +2022-11-14 13:30:24,077 Test: [15/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1581 (0.1181) Prec@1 71.000 (79.000) Prec@5 97.000 (98.188) +2022-11-14 13:30:24,091 Test: [16/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0972 (0.1169) Prec@1 84.000 (79.294) Prec@5 98.000 (98.176) +2022-11-14 13:30:24,106 Test: [17/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1232 (0.1172) Prec@1 80.000 (79.333) Prec@5 98.000 (98.167) +2022-11-14 13:30:24,120 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1214 (0.1174) Prec@1 80.000 (79.368) Prec@5 96.000 (98.053) +2022-11-14 13:30:24,135 Test: [19/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1387 (0.1185) Prec@1 76.000 (79.200) Prec@5 95.000 (97.900) +2022-11-14 13:30:24,150 Test: [20/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1395 (0.1195) Prec@1 73.000 (78.905) Prec@5 99.000 (97.952) +2022-11-14 13:30:24,164 Test: [21/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0978 (0.1185) Prec@1 79.000 (78.909) Prec@5 99.000 (98.000) +2022-11-14 13:30:24,179 Test: [22/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1284 (0.1189) Prec@1 80.000 (78.957) Prec@5 98.000 (98.000) +2022-11-14 13:30:24,193 Test: [23/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0941 (0.1179) Prec@1 86.000 (79.250) Prec@5 100.000 (98.083) +2022-11-14 13:30:24,208 Test: [24/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1391 (0.1188) Prec@1 74.000 (79.040) Prec@5 99.000 (98.120) +2022-11-14 13:30:24,222 Test: [25/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1505 (0.1200) Prec@1 73.000 (78.808) Prec@5 97.000 (98.077) +2022-11-14 13:30:24,236 Test: [26/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0960 (0.1191) Prec@1 85.000 (79.037) Prec@5 100.000 (98.148) +2022-11-14 13:30:24,249 Test: [27/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1071 (0.1187) Prec@1 81.000 (79.107) Prec@5 97.000 (98.107) +2022-11-14 13:30:24,264 Test: [28/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1144 (0.1185) Prec@1 78.000 (79.069) Prec@5 98.000 (98.103) +2022-11-14 13:30:24,277 Test: [29/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0954 (0.1177) Prec@1 82.000 (79.167) Prec@5 96.000 (98.033) +2022-11-14 13:30:24,289 Test: [30/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1335 (0.1183) Prec@1 75.000 (79.032) Prec@5 100.000 (98.097) +2022-11-14 13:30:24,303 Test: [31/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1114 (0.1180) Prec@1 79.000 (79.031) Prec@5 100.000 (98.156) +2022-11-14 13:30:24,346 Test: [32/100] Model Time 0.023 (0.010) Loss Time 0.000 (0.000) Loss 0.1129 (0.1179) Prec@1 80.000 (79.061) Prec@5 95.000 (98.061) +2022-11-14 13:30:24,358 Test: [33/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1365 (0.1184) Prec@1 73.000 (78.882) Prec@5 97.000 (98.029) +2022-11-14 13:30:24,372 Test: [34/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0928 (0.1177) Prec@1 88.000 (79.143) Prec@5 98.000 (98.029) +2022-11-14 13:30:24,393 Test: [35/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1250 (0.1179) Prec@1 79.000 (79.139) Prec@5 98.000 (98.028) +2022-11-14 13:30:24,408 Test: [36/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1522 (0.1188) Prec@1 73.000 (78.973) Prec@5 96.000 (97.973) +2022-11-14 13:30:24,422 Test: [37/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1472 (0.1196) Prec@1 76.000 (78.895) Prec@5 96.000 (97.921) +2022-11-14 13:30:24,436 Test: [38/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0945 (0.1189) Prec@1 83.000 (79.000) Prec@5 100.000 (97.974) +2022-11-14 13:30:24,453 Test: [39/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0976 (0.1184) Prec@1 84.000 (79.125) Prec@5 98.000 (97.975) +2022-11-14 13:30:24,468 Test: [40/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1192 (0.1184) Prec@1 80.000 (79.146) Prec@5 99.000 (98.000) +2022-11-14 13:30:24,483 Test: [41/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1184 (0.1184) Prec@1 79.000 (79.143) Prec@5 96.000 (97.952) +2022-11-14 13:30:24,499 Test: [42/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0853 (0.1176) Prec@1 86.000 (79.302) Prec@5 99.000 (97.977) +2022-11-14 13:30:24,513 Test: [43/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1180 (0.1177) Prec@1 79.000 (79.295) Prec@5 97.000 (97.955) +2022-11-14 13:30:24,530 Test: [44/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1104 (0.1175) Prec@1 82.000 (79.356) Prec@5 97.000 (97.933) +2022-11-14 13:30:24,544 Test: [45/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1289 (0.1177) Prec@1 75.000 (79.261) Prec@5 97.000 (97.913) +2022-11-14 13:30:24,557 Test: [46/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0906 (0.1172) Prec@1 83.000 (79.340) Prec@5 98.000 (97.915) +2022-11-14 13:30:24,574 Test: [47/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1103 (0.1170) Prec@1 81.000 (79.375) Prec@5 99.000 (97.938) +2022-11-14 13:30:24,589 Test: [48/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0768 (0.1162) Prec@1 86.000 (79.510) Prec@5 99.000 (97.959) +2022-11-14 13:30:24,607 Test: [49/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1340 (0.1166) Prec@1 77.000 (79.460) Prec@5 98.000 (97.960) +2022-11-14 13:30:24,624 Test: [50/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1165 (0.1166) Prec@1 79.000 (79.451) Prec@5 98.000 (97.961) +2022-11-14 13:30:24,644 Test: [51/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1209 (0.1166) Prec@1 78.000 (79.423) Prec@5 98.000 (97.962) +2022-11-14 13:30:24,664 Test: [52/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1189 (0.1167) Prec@1 75.000 (79.340) Prec@5 100.000 (98.000) +2022-11-14 13:30:24,682 Test: [53/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1210 (0.1168) Prec@1 79.000 (79.333) Prec@5 97.000 (97.981) +2022-11-14 13:30:24,698 Test: [54/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1278 (0.1170) Prec@1 78.000 (79.309) Prec@5 98.000 (97.982) +2022-11-14 13:30:24,711 Test: [55/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1198 (0.1170) Prec@1 80.000 (79.321) Prec@5 99.000 (98.000) +2022-11-14 13:30:24,724 Test: [56/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1416 (0.1174) Prec@1 74.000 (79.228) Prec@5 96.000 (97.965) +2022-11-14 13:30:24,739 Test: [57/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1107 (0.1173) Prec@1 82.000 (79.276) Prec@5 100.000 (98.000) +2022-11-14 13:30:24,753 Test: [58/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1796 (0.1184) Prec@1 71.000 (79.136) Prec@5 98.000 (98.000) +2022-11-14 13:30:24,769 Test: [59/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1042 (0.1181) Prec@1 80.000 (79.150) Prec@5 100.000 (98.033) +2022-11-14 13:30:24,784 Test: [60/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1355 (0.1184) Prec@1 75.000 (79.082) Prec@5 98.000 (98.033) +2022-11-14 13:30:24,801 Test: [61/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1031 (0.1182) Prec@1 82.000 (79.129) Prec@5 96.000 (98.000) +2022-11-14 13:30:24,827 Test: [62/100] Model Time 0.018 (0.011) Loss Time 0.000 (0.000) Loss 0.0932 (0.1178) Prec@1 82.000 (79.175) Prec@5 100.000 (98.032) +2022-11-14 13:30:24,845 Test: [63/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0915 (0.1174) Prec@1 83.000 (79.234) Prec@5 99.000 (98.047) +2022-11-14 13:30:24,858 Test: [64/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1323 (0.1176) Prec@1 78.000 (79.215) Prec@5 97.000 (98.031) +2022-11-14 13:30:24,874 Test: [65/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1208 (0.1177) Prec@1 77.000 (79.182) Prec@5 98.000 (98.030) +2022-11-14 13:30:24,887 Test: [66/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0994 (0.1174) Prec@1 84.000 (79.254) Prec@5 100.000 (98.060) +2022-11-14 13:30:24,900 Test: [67/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1399 (0.1177) Prec@1 72.000 (79.147) Prec@5 99.000 (98.074) +2022-11-14 13:30:24,916 Test: [68/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1010 (0.1175) Prec@1 83.000 (79.203) Prec@5 99.000 (98.087) +2022-11-14 13:30:24,932 Test: [69/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1228 (0.1175) Prec@1 81.000 (79.229) Prec@5 98.000 (98.086) +2022-11-14 13:30:24,946 Test: [70/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1145 (0.1175) Prec@1 81.000 (79.254) Prec@5 100.000 (98.113) +2022-11-14 13:30:24,959 Test: [71/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1233 (0.1176) Prec@1 78.000 (79.236) Prec@5 100.000 (98.139) +2022-11-14 13:30:24,973 Test: [72/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1072 (0.1174) Prec@1 82.000 (79.274) Prec@5 99.000 (98.151) +2022-11-14 13:30:24,987 Test: [73/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1033 (0.1173) Prec@1 83.000 (79.324) Prec@5 100.000 (98.176) +2022-11-14 13:30:24,999 Test: [74/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1320 (0.1174) Prec@1 78.000 (79.307) Prec@5 96.000 (98.147) +2022-11-14 13:30:25,014 Test: [75/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1097 (0.1173) Prec@1 82.000 (79.342) Prec@5 100.000 (98.171) +2022-11-14 13:30:25,028 Test: [76/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1306 (0.1175) Prec@1 79.000 (79.338) Prec@5 97.000 (98.156) +2022-11-14 13:30:25,044 Test: [77/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0963 (0.1172) Prec@1 81.000 (79.359) Prec@5 98.000 (98.154) +2022-11-14 13:30:25,057 Test: [78/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1274 (0.1174) Prec@1 80.000 (79.367) Prec@5 98.000 (98.152) +2022-11-14 13:30:25,070 Test: [79/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1001 (0.1172) Prec@1 83.000 (79.412) Prec@5 98.000 (98.150) +2022-11-14 13:30:25,085 Test: [80/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1262 (0.1173) Prec@1 75.000 (79.358) Prec@5 97.000 (98.136) +2022-11-14 13:30:25,100 Test: [81/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1120 (0.1172) Prec@1 83.000 (79.402) Prec@5 98.000 (98.134) +2022-11-14 13:30:25,116 Test: [82/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1106 (0.1171) Prec@1 77.000 (79.373) Prec@5 99.000 (98.145) +2022-11-14 13:30:25,131 Test: [83/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1126 (0.1171) Prec@1 79.000 (79.369) Prec@5 100.000 (98.167) +2022-11-14 13:30:25,146 Test: [84/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1347 (0.1173) Prec@1 77.000 (79.341) Prec@5 97.000 (98.153) +2022-11-14 13:30:25,161 Test: [85/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1162 (0.1173) Prec@1 77.000 (79.314) Prec@5 98.000 (98.151) +2022-11-14 13:30:25,175 Test: [86/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0972 (0.1170) Prec@1 82.000 (79.345) Prec@5 99.000 (98.161) +2022-11-14 13:30:25,189 Test: [87/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1299 (0.1172) Prec@1 78.000 (79.330) Prec@5 99.000 (98.170) +2022-11-14 13:30:25,204 Test: [88/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1350 (0.1174) Prec@1 76.000 (79.292) Prec@5 96.000 (98.146) +2022-11-14 13:30:25,217 Test: [89/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1318 (0.1175) Prec@1 80.000 (79.300) Prec@5 98.000 (98.144) +2022-11-14 13:30:25,231 Test: [90/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0899 (0.1172) Prec@1 83.000 (79.341) Prec@5 100.000 (98.165) +2022-11-14 13:30:25,247 Test: [91/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0808 (0.1168) Prec@1 86.000 (79.413) Prec@5 99.000 (98.174) +2022-11-14 13:30:25,261 Test: [92/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1100 (0.1168) Prec@1 79.000 (79.409) Prec@5 97.000 (98.161) +2022-11-14 13:30:25,276 Test: [93/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1023 (0.1166) Prec@1 80.000 (79.415) Prec@5 99.000 (98.170) +2022-11-14 13:30:25,291 Test: [94/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1176 (0.1166) Prec@1 77.000 (79.389) Prec@5 100.000 (98.189) +2022-11-14 13:30:25,306 Test: [95/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1097 (0.1166) Prec@1 86.000 (79.458) Prec@5 97.000 (98.177) +2022-11-14 13:30:25,321 Test: [96/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0969 (0.1164) Prec@1 84.000 (79.505) Prec@5 98.000 (98.175) +2022-11-14 13:30:25,335 Test: [97/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1193 (0.1164) Prec@1 80.000 (79.510) Prec@5 98.000 (98.173) +2022-11-14 13:30:25,349 Test: [98/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1576 (0.1168) Prec@1 69.000 (79.404) Prec@5 100.000 (98.192) +2022-11-14 13:30:25,364 Test: [99/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1094 (0.1167) Prec@1 82.000 (79.430) Prec@5 99.000 (98.200) +2022-11-14 13:30:25,463 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:30:25,847 Epoch: [51][0/500] Time 0.034 (0.034) Data 0.273 (0.273) Loss 0.1007 (0.1007) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:30:26,177 Epoch: [51][10/500] Time 0.035 (0.029) Data 0.002 (0.027) Loss 0.1118 (0.1062) Prec@1 80.000 (82.000) Prec@5 99.000 (99.500) +2022-11-14 13:30:26,566 Epoch: [51][20/500] Time 0.032 (0.032) Data 0.002 (0.015) Loss 0.1160 (0.1095) Prec@1 78.000 (80.667) Prec@5 97.000 (98.667) +2022-11-14 13:30:26,948 Epoch: [51][30/500] Time 0.036 (0.032) Data 0.002 (0.011) Loss 0.0754 (0.1010) Prec@1 89.000 (82.750) Prec@5 100.000 (99.000) +2022-11-14 13:30:27,464 Epoch: [51][40/500] Time 0.049 (0.036) Data 0.002 (0.009) Loss 0.0968 (0.1001) Prec@1 85.000 (83.200) Prec@5 100.000 (99.200) +2022-11-14 13:30:27,912 Epoch: [51][50/500] Time 0.040 (0.037) Data 0.002 (0.007) Loss 0.0836 (0.0974) Prec@1 83.000 (83.167) Prec@5 100.000 (99.333) +2022-11-14 13:30:28,286 Epoch: [51][60/500] Time 0.032 (0.036) Data 0.002 (0.006) Loss 0.1338 (0.1026) Prec@1 77.000 (82.286) Prec@5 98.000 (99.143) +2022-11-14 13:30:28,659 Epoch: [51][70/500] Time 0.034 (0.036) Data 0.002 (0.006) Loss 0.0971 (0.1019) Prec@1 85.000 (82.625) Prec@5 100.000 (99.250) +2022-11-14 13:30:29,056 Epoch: [51][80/500] Time 0.035 (0.036) Data 0.002 (0.005) Loss 0.1154 (0.1034) Prec@1 78.000 (82.111) Prec@5 98.000 (99.111) +2022-11-14 13:30:29,445 Epoch: [51][90/500] Time 0.041 (0.036) Data 0.003 (0.005) Loss 0.0903 (0.1021) Prec@1 84.000 (82.300) Prec@5 98.000 (99.000) +2022-11-14 13:30:29,827 Epoch: [51][100/500] Time 0.034 (0.036) Data 0.002 (0.005) Loss 0.0720 (0.0994) Prec@1 92.000 (83.182) Prec@5 100.000 (99.091) +2022-11-14 13:30:30,287 Epoch: [51][110/500] Time 0.050 (0.036) Data 0.002 (0.004) Loss 0.0758 (0.0974) Prec@1 87.000 (83.500) Prec@5 100.000 (99.167) +2022-11-14 13:30:30,761 Epoch: [51][120/500] Time 0.048 (0.037) Data 0.002 (0.004) Loss 0.1265 (0.0996) Prec@1 80.000 (83.231) Prec@5 99.000 (99.154) +2022-11-14 13:30:31,142 Epoch: [51][130/500] Time 0.034 (0.036) Data 0.002 (0.004) Loss 0.0715 (0.0976) Prec@1 86.000 (83.429) Prec@5 99.000 (99.143) +2022-11-14 13:30:31,539 Epoch: [51][140/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.0964 (0.0975) Prec@1 81.000 (83.267) Prec@5 99.000 (99.133) +2022-11-14 13:30:31,928 Epoch: [51][150/500] Time 0.031 (0.036) Data 0.002 (0.004) Loss 0.1123 (0.0985) Prec@1 79.000 (83.000) Prec@5 99.000 (99.125) +2022-11-14 13:30:32,329 Epoch: [51][160/500] Time 0.031 (0.036) Data 0.002 (0.004) Loss 0.0800 (0.0974) Prec@1 87.000 (83.235) Prec@5 99.000 (99.118) +2022-11-14 13:30:32,711 Epoch: [51][170/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.0884 (0.0969) Prec@1 85.000 (83.333) Prec@5 99.000 (99.111) +2022-11-14 13:30:33,103 Epoch: [51][180/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0855 (0.0963) Prec@1 83.000 (83.316) Prec@5 99.000 (99.105) +2022-11-14 13:30:33,493 Epoch: [51][190/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.1067 (0.0968) Prec@1 83.000 (83.300) Prec@5 100.000 (99.150) +2022-11-14 13:30:33,980 Epoch: [51][200/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.1121 (0.0975) Prec@1 77.000 (83.000) Prec@5 98.000 (99.095) +2022-11-14 13:30:34,454 Epoch: [51][210/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0853 (0.0970) Prec@1 86.000 (83.136) Prec@5 99.000 (99.091) +2022-11-14 13:30:34,852 Epoch: [51][220/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0849 (0.0964) Prec@1 86.000 (83.261) Prec@5 98.000 (99.043) +2022-11-14 13:30:35,261 Epoch: [51][230/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.0854 (0.0960) Prec@1 82.000 (83.208) Prec@5 99.000 (99.042) +2022-11-14 13:30:35,653 Epoch: [51][240/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.1021 (0.0962) Prec@1 82.000 (83.160) Prec@5 99.000 (99.040) +2022-11-14 13:30:36,124 Epoch: [51][250/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0982 (0.0963) Prec@1 84.000 (83.192) Prec@5 98.000 (99.000) +2022-11-14 13:30:36,490 Epoch: [51][260/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0801 (0.0957) Prec@1 88.000 (83.370) Prec@5 100.000 (99.037) +2022-11-14 13:30:36,876 Epoch: [51][270/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0718 (0.0949) Prec@1 88.000 (83.536) Prec@5 100.000 (99.071) +2022-11-14 13:30:37,265 Epoch: [51][280/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.1128 (0.0955) Prec@1 82.000 (83.483) Prec@5 96.000 (98.966) +2022-11-14 13:30:37,648 Epoch: [51][290/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.1136 (0.0961) Prec@1 80.000 (83.367) Prec@5 96.000 (98.867) +2022-11-14 13:30:38,055 Epoch: [51][300/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.1266 (0.0971) Prec@1 76.000 (83.129) Prec@5 96.000 (98.774) +2022-11-14 13:30:38,437 Epoch: [51][310/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0946 (0.0970) Prec@1 85.000 (83.188) Prec@5 99.000 (98.781) +2022-11-14 13:30:38,822 Epoch: [51][320/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0817 (0.0965) Prec@1 86.000 (83.273) Prec@5 98.000 (98.758) +2022-11-14 13:30:39,210 Epoch: [51][330/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0872 (0.0962) Prec@1 83.000 (83.265) Prec@5 99.000 (98.765) +2022-11-14 13:30:39,591 Epoch: [51][340/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0855 (0.0959) Prec@1 82.000 (83.229) Prec@5 100.000 (98.800) +2022-11-14 13:30:39,981 Epoch: [51][350/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0756 (0.0954) Prec@1 87.000 (83.333) Prec@5 99.000 (98.806) +2022-11-14 13:30:40,378 Epoch: [51][360/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0864 (0.0951) Prec@1 86.000 (83.405) Prec@5 99.000 (98.811) +2022-11-14 13:30:40,758 Epoch: [51][370/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.1219 (0.0958) Prec@1 77.000 (83.237) Prec@5 99.000 (98.816) +2022-11-14 13:30:41,134 Epoch: [51][380/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.1069 (0.0961) Prec@1 82.000 (83.205) Prec@5 100.000 (98.846) +2022-11-14 13:30:41,519 Epoch: [51][390/500] Time 0.033 (0.036) Data 0.003 (0.003) Loss 0.0853 (0.0959) Prec@1 85.000 (83.250) Prec@5 100.000 (98.875) +2022-11-14 13:30:41,902 Epoch: [51][400/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0845 (0.0956) Prec@1 84.000 (83.268) Prec@5 100.000 (98.902) +2022-11-14 13:30:42,291 Epoch: [51][410/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.1077 (0.0959) Prec@1 83.000 (83.262) Prec@5 98.000 (98.881) +2022-11-14 13:30:42,724 Epoch: [51][420/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.1187 (0.0964) Prec@1 78.000 (83.140) Prec@5 97.000 (98.837) +2022-11-14 13:30:43,221 Epoch: [51][430/500] Time 0.054 (0.036) Data 0.002 (0.003) Loss 0.0785 (0.0960) Prec@1 86.000 (83.205) Prec@5 100.000 (98.864) +2022-11-14 13:30:43,709 Epoch: [51][440/500] Time 0.038 (0.036) Data 0.003 (0.003) Loss 0.0546 (0.0951) Prec@1 92.000 (83.400) Prec@5 100.000 (98.889) +2022-11-14 13:30:44,222 Epoch: [51][450/500] Time 0.059 (0.036) Data 0.004 (0.003) Loss 0.1417 (0.0961) Prec@1 75.000 (83.217) Prec@5 97.000 (98.848) +2022-11-14 13:30:44,745 Epoch: [51][460/500] Time 0.038 (0.037) Data 0.004 (0.003) Loss 0.0956 (0.0961) Prec@1 85.000 (83.255) Prec@5 98.000 (98.830) +2022-11-14 13:30:45,226 Epoch: [51][470/500] Time 0.042 (0.037) Data 0.004 (0.003) Loss 0.1225 (0.0966) Prec@1 80.000 (83.188) Prec@5 99.000 (98.833) +2022-11-14 13:30:45,718 Epoch: [51][480/500] Time 0.046 (0.037) Data 0.003 (0.003) Loss 0.0933 (0.0966) Prec@1 83.000 (83.184) Prec@5 99.000 (98.837) +2022-11-14 13:30:46,221 Epoch: [51][490/500] Time 0.044 (0.037) Data 0.004 (0.003) Loss 0.1280 (0.0972) Prec@1 78.000 (83.080) Prec@5 96.000 (98.780) +2022-11-14 13:30:46,697 Epoch: [51][499/500] Time 0.050 (0.037) Data 0.004 (0.003) Loss 0.1120 (0.0975) Prec@1 77.000 (82.961) Prec@5 100.000 (98.804) +2022-11-14 13:30:47,142 Test: [0/100] Model Time 0.023 (0.023) Loss Time 0.000 (0.000) Loss 0.0897 (0.0897) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:30:47,160 Test: [1/100] Model Time 0.013 (0.018) Loss Time 0.000 (0.000) Loss 0.0907 (0.0902) Prec@1 84.000 (84.500) Prec@5 99.000 (99.500) +2022-11-14 13:30:47,171 Test: [2/100] Model Time 0.010 (0.015) Loss Time 0.000 (0.000) Loss 0.1199 (0.1001) Prec@1 77.000 (82.000) Prec@5 100.000 (99.667) +2022-11-14 13:30:47,187 Test: [3/100] Model Time 0.010 (0.014) Loss Time 0.000 (0.000) Loss 0.1079 (0.1021) Prec@1 83.000 (82.250) Prec@5 99.000 (99.500) +2022-11-14 13:30:47,197 Test: [4/100] Model Time 0.009 (0.013) Loss Time 0.000 (0.000) Loss 0.1045 (0.1026) Prec@1 82.000 (82.200) Prec@5 100.000 (99.600) +2022-11-14 13:30:47,211 Test: [5/100] Model Time 0.012 (0.013) Loss Time 0.000 (0.000) Loss 0.0812 (0.0990) Prec@1 82.000 (82.167) Prec@5 99.000 (99.500) +2022-11-14 13:30:47,225 Test: [6/100] Model Time 0.012 (0.013) Loss Time 0.000 (0.000) Loss 0.0977 (0.0988) Prec@1 84.000 (82.429) Prec@5 98.000 (99.286) +2022-11-14 13:30:47,238 Test: [7/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1299 (0.1027) Prec@1 75.000 (81.500) Prec@5 99.000 (99.250) +2022-11-14 13:30:47,248 Test: [8/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1126 (0.1038) Prec@1 83.000 (81.667) Prec@5 98.000 (99.111) +2022-11-14 13:30:47,265 Test: [9/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0736 (0.1008) Prec@1 86.000 (82.100) Prec@5 99.000 (99.100) +2022-11-14 13:30:47,282 Test: [10/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0822 (0.0991) Prec@1 84.000 (82.273) Prec@5 99.000 (99.091) +2022-11-14 13:30:47,299 Test: [11/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.1147 (0.1004) Prec@1 81.000 (82.167) Prec@5 100.000 (99.167) +2022-11-14 13:30:47,313 Test: [12/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1117 (0.1013) Prec@1 81.000 (82.077) Prec@5 97.000 (99.000) +2022-11-14 13:30:47,328 Test: [13/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.1097 (0.1019) Prec@1 80.000 (81.929) Prec@5 98.000 (98.929) +2022-11-14 13:30:47,338 Test: [14/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1184 (0.1030) Prec@1 80.000 (81.800) Prec@5 99.000 (98.933) +2022-11-14 13:30:47,353 Test: [15/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1457 (0.1056) Prec@1 74.000 (81.312) Prec@5 99.000 (98.938) +2022-11-14 13:30:47,366 Test: [16/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0885 (0.1046) Prec@1 86.000 (81.588) Prec@5 99.000 (98.941) +2022-11-14 13:30:47,379 Test: [17/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1196 (0.1055) Prec@1 78.000 (81.389) Prec@5 98.000 (98.889) +2022-11-14 13:30:47,392 Test: [18/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0922 (0.1048) Prec@1 83.000 (81.474) Prec@5 99.000 (98.895) +2022-11-14 13:30:47,405 Test: [19/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1490 (0.1070) Prec@1 75.000 (81.150) Prec@5 97.000 (98.800) +2022-11-14 13:30:47,418 Test: [20/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1278 (0.1080) Prec@1 79.000 (81.048) Prec@5 97.000 (98.714) +2022-11-14 13:30:47,430 Test: [21/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1164 (0.1083) Prec@1 79.000 (80.955) Prec@5 98.000 (98.682) +2022-11-14 13:30:47,443 Test: [22/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1302 (0.1093) Prec@1 76.000 (80.739) Prec@5 99.000 (98.696) +2022-11-14 13:30:47,459 Test: [23/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1037 (0.1091) Prec@1 84.000 (80.875) Prec@5 98.000 (98.667) +2022-11-14 13:30:47,474 Test: [24/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1234 (0.1096) Prec@1 76.000 (80.680) Prec@5 99.000 (98.680) +2022-11-14 13:30:47,487 Test: [25/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1318 (0.1105) Prec@1 79.000 (80.615) Prec@5 98.000 (98.654) +2022-11-14 13:30:47,501 Test: [26/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1028 (0.1102) Prec@1 84.000 (80.741) Prec@5 100.000 (98.704) +2022-11-14 13:30:47,517 Test: [27/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1126 (0.1103) Prec@1 82.000 (80.786) Prec@5 97.000 (98.643) +2022-11-14 13:30:47,531 Test: [28/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0997 (0.1099) Prec@1 83.000 (80.862) Prec@5 97.000 (98.586) +2022-11-14 13:30:47,544 Test: [29/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1064 (0.1098) Prec@1 82.000 (80.900) Prec@5 96.000 (98.500) +2022-11-14 13:30:47,555 Test: [30/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1241 (0.1103) Prec@1 77.000 (80.774) Prec@5 98.000 (98.484) +2022-11-14 13:30:47,572 Test: [31/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0938 (0.1098) Prec@1 85.000 (80.906) Prec@5 99.000 (98.500) +2022-11-14 13:30:47,588 Test: [32/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1132 (0.1099) Prec@1 79.000 (80.848) Prec@5 99.000 (98.515) +2022-11-14 13:30:47,600 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1487 (0.1110) Prec@1 74.000 (80.647) Prec@5 98.000 (98.500) +2022-11-14 13:30:47,616 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1099 (0.1110) Prec@1 83.000 (80.714) Prec@5 98.000 (98.486) +2022-11-14 13:30:47,631 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1133 (0.1110) Prec@1 81.000 (80.722) Prec@5 98.000 (98.472) +2022-11-14 13:30:47,646 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1060 (0.1109) Prec@1 83.000 (80.784) Prec@5 98.000 (98.459) +2022-11-14 13:30:47,662 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1268 (0.1113) Prec@1 78.000 (80.711) Prec@5 98.000 (98.447) +2022-11-14 13:30:47,677 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1234 (0.1116) Prec@1 76.000 (80.590) Prec@5 99.000 (98.462) +2022-11-14 13:30:47,691 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.1110) Prec@1 86.000 (80.725) Prec@5 98.000 (98.450) +2022-11-14 13:30:47,705 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1119 (0.1110) Prec@1 83.000 (80.780) Prec@5 99.000 (98.463) +2022-11-14 13:30:47,719 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.1103) Prec@1 87.000 (80.929) Prec@5 98.000 (98.452) +2022-11-14 13:30:47,732 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.1097) Prec@1 89.000 (81.116) Prec@5 99.000 (98.465) +2022-11-14 13:30:47,746 Test: [43/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1080 (0.1096) Prec@1 80.000 (81.091) Prec@5 96.000 (98.409) +2022-11-14 13:30:47,760 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.1094) Prec@1 82.000 (81.111) Prec@5 98.000 (98.400) +2022-11-14 13:30:47,776 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1101 (0.1094) Prec@1 78.000 (81.043) Prec@5 98.000 (98.391) +2022-11-14 13:30:47,791 Test: [46/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1181 (0.1096) Prec@1 76.000 (80.936) Prec@5 96.000 (98.340) +2022-11-14 13:30:47,807 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1265 (0.1099) Prec@1 74.000 (80.792) Prec@5 98.000 (98.333) +2022-11-14 13:30:47,821 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.1097) Prec@1 84.000 (80.857) Prec@5 99.000 (98.347) +2022-11-14 13:30:47,837 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1443 (0.1104) Prec@1 76.000 (80.760) Prec@5 99.000 (98.360) +2022-11-14 13:30:47,854 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0983 (0.1101) Prec@1 84.000 (80.824) Prec@5 99.000 (98.373) +2022-11-14 13:30:47,869 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1133 (0.1102) Prec@1 77.000 (80.750) Prec@5 98.000 (98.365) +2022-11-14 13:30:47,885 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0990 (0.1100) Prec@1 84.000 (80.811) Prec@5 98.000 (98.358) +2022-11-14 13:30:47,898 Test: [53/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1096 (0.1100) Prec@1 82.000 (80.833) Prec@5 98.000 (98.352) +2022-11-14 13:30:47,911 Test: [54/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1212 (0.1102) Prec@1 78.000 (80.782) Prec@5 100.000 (98.382) +2022-11-14 13:30:47,927 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1039 (0.1101) Prec@1 81.000 (80.786) Prec@5 99.000 (98.393) +2022-11-14 13:30:47,942 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1254 (0.1103) Prec@1 80.000 (80.772) Prec@5 99.000 (98.404) +2022-11-14 13:30:47,957 Test: [57/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.1100) Prec@1 86.000 (80.862) Prec@5 98.000 (98.397) +2022-11-14 13:30:47,973 Test: [58/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1448 (0.1105) Prec@1 68.000 (80.644) Prec@5 100.000 (98.424) +2022-11-14 13:30:47,990 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1029 (0.1104) Prec@1 85.000 (80.717) Prec@5 96.000 (98.383) +2022-11-14 13:30:48,003 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1113 (0.1104) Prec@1 82.000 (80.738) Prec@5 99.000 (98.393) +2022-11-14 13:30:48,017 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1140 (0.1105) Prec@1 79.000 (80.710) Prec@5 99.000 (98.403) +2022-11-14 13:30:48,032 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.1102) Prec@1 85.000 (80.778) Prec@5 99.000 (98.413) +2022-11-14 13:30:48,047 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0906 (0.1099) Prec@1 83.000 (80.812) Prec@5 99.000 (98.422) +2022-11-14 13:30:48,062 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1291 (0.1102) Prec@1 77.000 (80.754) Prec@5 97.000 (98.400) +2022-11-14 13:30:48,077 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1070 (0.1102) Prec@1 81.000 (80.758) Prec@5 98.000 (98.394) +2022-11-14 13:30:48,093 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1009 (0.1100) Prec@1 84.000 (80.806) Prec@5 100.000 (98.418) +2022-11-14 13:30:48,108 Test: [67/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0945 (0.1098) Prec@1 85.000 (80.868) Prec@5 99.000 (98.426) +2022-11-14 13:30:48,122 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1191 (0.1099) Prec@1 78.000 (80.826) Prec@5 96.000 (98.391) +2022-11-14 13:30:48,135 Test: [69/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1244 (0.1101) Prec@1 76.000 (80.757) Prec@5 97.000 (98.371) +2022-11-14 13:30:48,148 Test: [70/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1187 (0.1103) Prec@1 79.000 (80.732) Prec@5 99.000 (98.380) +2022-11-14 13:30:48,161 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.1102) Prec@1 81.000 (80.736) Prec@5 99.000 (98.389) +2022-11-14 13:30:48,175 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1010 (0.1100) Prec@1 80.000 (80.726) Prec@5 100.000 (98.411) +2022-11-14 13:30:48,189 Test: [73/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.1098) Prec@1 86.000 (80.797) Prec@5 100.000 (98.432) +2022-11-14 13:30:48,201 Test: [74/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1152 (0.1099) Prec@1 78.000 (80.760) Prec@5 99.000 (98.440) +2022-11-14 13:30:48,217 Test: [75/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1006 (0.1098) Prec@1 84.000 (80.803) Prec@5 99.000 (98.447) +2022-11-14 13:30:48,233 Test: [76/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1121 (0.1098) Prec@1 83.000 (80.831) Prec@5 99.000 (98.455) +2022-11-14 13:30:48,249 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1069 (0.1098) Prec@1 83.000 (80.859) Prec@5 98.000 (98.449) +2022-11-14 13:30:48,264 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.1098) Prec@1 78.000 (80.823) Prec@5 99.000 (98.456) +2022-11-14 13:30:48,280 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.1096) Prec@1 84.000 (80.862) Prec@5 95.000 (98.412) +2022-11-14 13:30:48,295 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1171 (0.1097) Prec@1 81.000 (80.864) Prec@5 98.000 (98.407) +2022-11-14 13:30:48,309 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.1097) Prec@1 82.000 (80.878) Prec@5 98.000 (98.402) +2022-11-14 13:30:48,323 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.1095) Prec@1 84.000 (80.916) Prec@5 100.000 (98.422) +2022-11-14 13:30:48,338 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.1094) Prec@1 84.000 (80.952) Prec@5 98.000 (98.417) +2022-11-14 13:30:48,352 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1365 (0.1097) Prec@1 75.000 (80.882) Prec@5 97.000 (98.400) +2022-11-14 13:30:48,367 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1387 (0.1101) Prec@1 77.000 (80.837) Prec@5 99.000 (98.407) +2022-11-14 13:30:48,382 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.1102) Prec@1 79.000 (80.816) Prec@5 96.000 (98.379) +2022-11-14 13:30:48,399 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.1100) Prec@1 83.000 (80.841) Prec@5 99.000 (98.386) +2022-11-14 13:30:48,414 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.1099) Prec@1 80.000 (80.831) Prec@5 100.000 (98.404) +2022-11-14 13:30:48,428 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.1100) Prec@1 83.000 (80.856) Prec@5 99.000 (98.411) +2022-11-14 13:30:48,443 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.1099) Prec@1 81.000 (80.857) Prec@5 100.000 (98.429) +2022-11-14 13:30:48,458 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.1095) Prec@1 86.000 (80.913) Prec@5 99.000 (98.435) +2022-11-14 13:30:48,473 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1364 (0.1098) Prec@1 75.000 (80.849) Prec@5 98.000 (98.430) +2022-11-14 13:30:48,488 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.1098) Prec@1 83.000 (80.872) Prec@5 98.000 (98.426) +2022-11-14 13:30:48,501 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.1097) Prec@1 82.000 (80.884) Prec@5 98.000 (98.421) +2022-11-14 13:30:48,514 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.1094) Prec@1 86.000 (80.938) Prec@5 99.000 (98.427) +2022-11-14 13:30:48,529 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.1091) Prec@1 86.000 (80.990) Prec@5 99.000 (98.433) +2022-11-14 13:30:48,544 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1307 (0.1093) Prec@1 78.000 (80.959) Prec@5 98.000 (98.429) +2022-11-14 13:30:48,557 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1330 (0.1095) Prec@1 75.000 (80.899) Prec@5 100.000 (98.444) +2022-11-14 13:30:48,570 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.1095) Prec@1 83.000 (80.920) Prec@5 97.000 (98.430) +2022-11-14 13:30:48,644 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:30:49,008 Epoch: [52][0/500] Time 0.034 (0.034) Data 0.260 (0.260) Loss 0.1092 (0.1092) Prec@1 76.000 (76.000) Prec@5 98.000 (98.000) +2022-11-14 13:30:49,448 Epoch: [52][10/500] Time 0.048 (0.039) Data 0.002 (0.025) Loss 0.1185 (0.1138) Prec@1 80.000 (78.000) Prec@5 99.000 (98.500) +2022-11-14 13:30:49,931 Epoch: [52][20/500] Time 0.045 (0.041) Data 0.002 (0.014) Loss 0.0959 (0.1079) Prec@1 84.000 (80.000) Prec@5 97.000 (98.000) +2022-11-14 13:30:50,412 Epoch: [52][30/500] Time 0.043 (0.042) Data 0.002 (0.010) Loss 0.0947 (0.1046) Prec@1 82.000 (80.500) Prec@5 98.000 (98.000) +2022-11-14 13:30:50,895 Epoch: [52][40/500] Time 0.047 (0.042) Data 0.002 (0.008) Loss 0.0815 (0.1000) Prec@1 86.000 (81.600) Prec@5 99.000 (98.200) +2022-11-14 13:30:51,377 Epoch: [52][50/500] Time 0.048 (0.042) Data 0.002 (0.007) Loss 0.0869 (0.0978) Prec@1 84.000 (82.000) Prec@5 99.000 (98.333) +2022-11-14 13:30:51,861 Epoch: [52][60/500] Time 0.044 (0.042) Data 0.002 (0.006) Loss 0.0984 (0.0979) Prec@1 81.000 (81.857) Prec@5 98.000 (98.286) +2022-11-14 13:30:52,350 Epoch: [52][70/500] Time 0.049 (0.043) Data 0.002 (0.006) Loss 0.0825 (0.0960) Prec@1 86.000 (82.375) Prec@5 100.000 (98.500) +2022-11-14 13:30:52,836 Epoch: [52][80/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.1151 (0.0981) Prec@1 81.000 (82.222) Prec@5 97.000 (98.333) +2022-11-14 13:30:53,315 Epoch: [52][90/500] Time 0.049 (0.043) Data 0.002 (0.005) Loss 0.0875 (0.0970) Prec@1 86.000 (82.600) Prec@5 99.000 (98.400) +2022-11-14 13:30:53,799 Epoch: [52][100/500] Time 0.049 (0.043) Data 0.002 (0.005) Loss 0.1103 (0.0982) Prec@1 77.000 (82.091) Prec@5 98.000 (98.364) +2022-11-14 13:30:54,292 Epoch: [52][110/500] Time 0.046 (0.043) Data 0.002 (0.004) Loss 0.1102 (0.0992) Prec@1 81.000 (82.000) Prec@5 98.000 (98.333) +2022-11-14 13:30:54,760 Epoch: [52][120/500] Time 0.052 (0.043) Data 0.003 (0.004) Loss 0.1387 (0.1023) Prec@1 75.000 (81.462) Prec@5 97.000 (98.231) +2022-11-14 13:30:55,244 Epoch: [52][130/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.1020 (0.1023) Prec@1 79.000 (81.286) Prec@5 100.000 (98.357) +2022-11-14 13:30:55,708 Epoch: [52][140/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0884 (0.1013) Prec@1 86.000 (81.600) Prec@5 98.000 (98.333) +2022-11-14 13:30:56,507 Epoch: [52][150/500] Time 0.090 (0.045) Data 0.002 (0.004) Loss 0.1000 (0.1012) Prec@1 85.000 (81.812) Prec@5 96.000 (98.188) +2022-11-14 13:30:57,464 Epoch: [52][160/500] Time 0.099 (0.047) Data 0.002 (0.004) Loss 0.0828 (0.1002) Prec@1 84.000 (81.941) Prec@5 98.000 (98.176) +2022-11-14 13:30:58,446 Epoch: [52][170/500] Time 0.095 (0.050) Data 0.002 (0.004) Loss 0.1094 (0.1007) Prec@1 81.000 (81.889) Prec@5 98.000 (98.167) +2022-11-14 13:30:59,423 Epoch: [52][180/500] Time 0.093 (0.052) Data 0.002 (0.003) Loss 0.0917 (0.1002) Prec@1 87.000 (82.158) Prec@5 100.000 (98.263) +2022-11-14 13:31:00,390 Epoch: [52][190/500] Time 0.099 (0.053) Data 0.002 (0.003) Loss 0.0961 (0.1000) Prec@1 84.000 (82.250) Prec@5 98.000 (98.250) +2022-11-14 13:31:01,312 Epoch: [52][200/500] Time 0.097 (0.055) Data 0.002 (0.003) Loss 0.0940 (0.0997) Prec@1 83.000 (82.286) Prec@5 98.000 (98.238) +2022-11-14 13:31:02,104 Epoch: [52][210/500] Time 0.072 (0.056) Data 0.003 (0.003) Loss 0.0880 (0.0992) Prec@1 85.000 (82.409) Prec@5 100.000 (98.318) +2022-11-14 13:31:02,978 Epoch: [52][220/500] Time 0.052 (0.057) Data 0.003 (0.003) Loss 0.0947 (0.0990) Prec@1 86.000 (82.565) Prec@5 98.000 (98.304) +2022-11-14 13:31:03,541 Epoch: [52][230/500] Time 0.044 (0.056) Data 0.002 (0.003) Loss 0.1022 (0.0991) Prec@1 80.000 (82.458) Prec@5 99.000 (98.333) +2022-11-14 13:31:04,186 Epoch: [52][240/500] Time 0.068 (0.057) Data 0.002 (0.003) Loss 0.1049 (0.0994) Prec@1 81.000 (82.400) Prec@5 99.000 (98.360) +2022-11-14 13:31:04,649 Epoch: [52][250/500] Time 0.043 (0.056) Data 0.002 (0.003) Loss 0.0818 (0.0987) Prec@1 85.000 (82.500) Prec@5 100.000 (98.423) +2022-11-14 13:31:05,123 Epoch: [52][260/500] Time 0.042 (0.055) Data 0.002 (0.003) Loss 0.1416 (0.1003) Prec@1 76.000 (82.259) Prec@5 99.000 (98.444) +2022-11-14 13:31:05,598 Epoch: [52][270/500] Time 0.043 (0.055) Data 0.002 (0.003) Loss 0.1030 (0.1004) Prec@1 83.000 (82.286) Prec@5 99.000 (98.464) +2022-11-14 13:31:06,110 Epoch: [52][280/500] Time 0.042 (0.055) Data 0.002 (0.003) Loss 0.0920 (0.1001) Prec@1 84.000 (82.345) Prec@5 97.000 (98.414) +2022-11-14 13:31:06,624 Epoch: [52][290/500] Time 0.050 (0.054) Data 0.002 (0.003) Loss 0.0819 (0.0995) Prec@1 86.000 (82.467) Prec@5 99.000 (98.433) +2022-11-14 13:31:07,090 Epoch: [52][300/500] Time 0.044 (0.054) Data 0.002 (0.003) Loss 0.1297 (0.1004) Prec@1 75.000 (82.226) Prec@5 98.000 (98.419) +2022-11-14 13:31:07,562 Epoch: [52][310/500] Time 0.043 (0.053) Data 0.002 (0.003) Loss 0.0949 (0.1003) Prec@1 85.000 (82.312) Prec@5 100.000 (98.469) +2022-11-14 13:31:08,033 Epoch: [52][320/500] Time 0.044 (0.053) Data 0.002 (0.003) Loss 0.0797 (0.0996) Prec@1 85.000 (82.394) Prec@5 99.000 (98.485) +2022-11-14 13:31:08,506 Epoch: [52][330/500] Time 0.042 (0.053) Data 0.002 (0.003) Loss 0.0862 (0.0992) Prec@1 83.000 (82.412) Prec@5 97.000 (98.441) +2022-11-14 13:31:08,977 Epoch: [52][340/500] Time 0.043 (0.052) Data 0.002 (0.003) Loss 0.0975 (0.0992) Prec@1 85.000 (82.486) Prec@5 98.000 (98.429) +2022-11-14 13:31:09,441 Epoch: [52][350/500] Time 0.045 (0.052) Data 0.002 (0.003) Loss 0.1074 (0.0994) Prec@1 79.000 (82.389) Prec@5 97.000 (98.389) +2022-11-14 13:31:09,913 Epoch: [52][360/500] Time 0.044 (0.052) Data 0.002 (0.003) Loss 0.1144 (0.0998) Prec@1 79.000 (82.297) Prec@5 97.000 (98.351) +2022-11-14 13:31:10,387 Epoch: [52][370/500] Time 0.042 (0.052) Data 0.002 (0.003) Loss 0.1243 (0.1005) Prec@1 75.000 (82.105) Prec@5 99.000 (98.368) +2022-11-14 13:31:10,860 Epoch: [52][380/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0657 (0.0996) Prec@1 91.000 (82.333) Prec@5 100.000 (98.410) +2022-11-14 13:31:11,325 Epoch: [52][390/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.1212 (0.1001) Prec@1 78.000 (82.225) Prec@5 100.000 (98.450) +2022-11-14 13:31:11,821 Epoch: [52][400/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0963 (0.1000) Prec@1 86.000 (82.317) Prec@5 99.000 (98.463) +2022-11-14 13:31:12,308 Epoch: [52][410/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0838 (0.0996) Prec@1 84.000 (82.357) Prec@5 100.000 (98.500) +2022-11-14 13:31:12,781 Epoch: [52][420/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0968 (0.0996) Prec@1 83.000 (82.372) Prec@5 98.000 (98.488) +2022-11-14 13:31:13,253 Epoch: [52][430/500] Time 0.042 (0.050) Data 0.002 (0.003) Loss 0.0979 (0.0995) Prec@1 80.000 (82.318) Prec@5 97.000 (98.455) +2022-11-14 13:31:13,716 Epoch: [52][440/500] Time 0.044 (0.050) Data 0.001 (0.003) Loss 0.0820 (0.0991) Prec@1 87.000 (82.422) Prec@5 98.000 (98.444) +2022-11-14 13:31:14,188 Epoch: [52][450/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.1143 (0.0995) Prec@1 80.000 (82.370) Prec@5 100.000 (98.478) +2022-11-14 13:31:14,660 Epoch: [52][460/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0952 (0.0994) Prec@1 84.000 (82.404) Prec@5 97.000 (98.447) +2022-11-14 13:31:15,134 Epoch: [52][470/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0950 (0.0993) Prec@1 85.000 (82.458) Prec@5 97.000 (98.417) +2022-11-14 13:31:15,618 Epoch: [52][480/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0860 (0.0990) Prec@1 84.000 (82.490) Prec@5 100.000 (98.449) +2022-11-14 13:31:16,206 Epoch: [52][490/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0997 (0.0990) Prec@1 82.000 (82.480) Prec@5 99.000 (98.460) +2022-11-14 13:31:16,572 Epoch: [52][499/500] Time 0.037 (0.049) Data 0.002 (0.003) Loss 0.1031 (0.0991) Prec@1 83.000 (82.490) Prec@5 99.000 (98.471) +2022-11-14 13:31:16,870 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1121 (0.1121) Prec@1 79.000 (79.000) Prec@5 100.000 (100.000) +2022-11-14 13:31:16,878 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.1093) Prec@1 81.000 (80.000) Prec@5 98.000 (99.000) +2022-11-14 13:31:16,886 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1091 (0.1093) Prec@1 81.000 (80.333) Prec@5 99.000 (99.000) +2022-11-14 13:31:16,898 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1104) Prec@1 81.000 (80.500) Prec@5 98.000 (98.750) +2022-11-14 13:31:16,905 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.1085) Prec@1 84.000 (81.200) Prec@5 98.000 (98.600) +2022-11-14 13:31:16,914 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1068) Prec@1 81.000 (81.167) Prec@5 97.000 (98.333) +2022-11-14 13:31:16,922 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.1063) Prec@1 82.000 (81.286) Prec@5 97.000 (98.143) +2022-11-14 13:31:16,932 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1257 (0.1087) Prec@1 78.000 (80.875) Prec@5 98.000 (98.125) +2022-11-14 13:31:16,941 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1582 (0.1142) Prec@1 73.000 (80.000) Prec@5 99.000 (98.222) +2022-11-14 13:31:16,950 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.1128) Prec@1 83.000 (80.300) Prec@5 98.000 (98.200) +2022-11-14 13:31:16,960 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.1124) Prec@1 81.000 (80.364) Prec@5 99.000 (98.273) +2022-11-14 13:31:16,969 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1231 (0.1133) Prec@1 76.000 (80.000) Prec@5 99.000 (98.333) +2022-11-14 13:31:16,977 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.1126) Prec@1 82.000 (80.154) Prec@5 100.000 (98.462) +2022-11-14 13:31:16,987 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.1116) Prec@1 83.000 (80.357) Prec@5 100.000 (98.571) +2022-11-14 13:31:16,996 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1216 (0.1122) Prec@1 77.000 (80.133) Prec@5 99.000 (98.600) +2022-11-14 13:31:17,005 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1139) Prec@1 77.000 (79.938) Prec@5 98.000 (98.562) +2022-11-14 13:31:17,014 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.1137) Prec@1 80.000 (79.941) Prec@5 97.000 (98.471) +2022-11-14 13:31:17,024 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1132) Prec@1 81.000 (80.000) Prec@5 99.000 (98.500) +2022-11-14 13:31:17,033 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1549 (0.1154) Prec@1 74.000 (79.684) Prec@5 97.000 (98.421) +2022-11-14 13:31:17,042 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1594 (0.1176) Prec@1 72.000 (79.300) Prec@5 97.000 (98.350) +2022-11-14 13:31:17,052 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1618 (0.1197) Prec@1 74.000 (79.048) Prec@5 97.000 (98.286) +2022-11-14 13:31:17,061 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1190) Prec@1 83.000 (79.227) Prec@5 96.000 (98.182) +2022-11-14 13:31:17,071 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.1186) Prec@1 82.000 (79.348) Prec@5 98.000 (98.174) +2022-11-14 13:31:17,082 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1279 (0.1190) Prec@1 76.000 (79.208) Prec@5 100.000 (98.250) +2022-11-14 13:31:17,092 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1325 (0.1195) Prec@1 76.000 (79.080) Prec@5 98.000 (98.240) +2022-11-14 13:31:17,101 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1541 (0.1209) Prec@1 74.000 (78.885) Prec@5 96.000 (98.154) +2022-11-14 13:31:17,110 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1208) Prec@1 80.000 (78.926) Prec@5 99.000 (98.185) +2022-11-14 13:31:17,120 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.1214) Prec@1 76.000 (78.821) Prec@5 99.000 (98.214) +2022-11-14 13:31:17,129 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1351 (0.1218) Prec@1 78.000 (78.793) Prec@5 95.000 (98.103) +2022-11-14 13:31:17,138 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.1223) Prec@1 72.000 (78.567) Prec@5 100.000 (98.167) +2022-11-14 13:31:17,147 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.1222) Prec@1 78.000 (78.548) Prec@5 98.000 (98.161) +2022-11-14 13:31:17,156 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1220) Prec@1 83.000 (78.688) Prec@5 98.000 (98.156) +2022-11-14 13:31:17,164 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.1215) Prec@1 82.000 (78.788) Prec@5 100.000 (98.212) +2022-11-14 13:31:17,174 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1492 (0.1224) Prec@1 71.000 (78.559) Prec@5 99.000 (98.235) +2022-11-14 13:31:17,185 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1358 (0.1227) Prec@1 78.000 (78.543) Prec@5 96.000 (98.171) +2022-11-14 13:31:17,195 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.1223) Prec@1 83.000 (78.667) Prec@5 98.000 (98.167) +2022-11-14 13:31:17,203 Test: 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0.0767 (0.1210) Prec@1 87.000 (78.907) Prec@5 99.000 (98.163) +2022-11-14 13:31:17,266 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.1210) Prec@1 82.000 (78.977) Prec@5 99.000 (98.182) +2022-11-14 13:31:17,275 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1290 (0.1211) Prec@1 77.000 (78.933) Prec@5 98.000 (98.178) +2022-11-14 13:31:17,285 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1643 (0.1221) Prec@1 67.000 (78.674) Prec@5 99.000 (98.196) +2022-11-14 13:31:17,294 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1223) Prec@1 77.000 (78.638) Prec@5 98.000 (98.191) +2022-11-14 13:31:17,303 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1222) Prec@1 83.000 (78.729) Prec@5 99.000 (98.208) +2022-11-14 13:31:17,312 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1220) Prec@1 81.000 (78.776) Prec@5 100.000 (98.245) +2022-11-14 13:31:17,322 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1306 (0.1222) Prec@1 79.000 (78.780) Prec@5 97.000 (98.220) +2022-11-14 13:31:17,331 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.1215) Prec@1 85.000 (78.902) Prec@5 98.000 (98.216) +2022-11-14 13:31:17,341 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1281 (0.1216) Prec@1 80.000 (78.923) Prec@5 99.000 (98.231) +2022-11-14 13:31:17,350 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.1215) Prec@1 81.000 (78.962) Prec@5 100.000 (98.264) +2022-11-14 13:31:17,359 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.1213) Prec@1 82.000 (79.019) Prec@5 99.000 (98.278) +2022-11-14 13:31:17,368 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1212) Prec@1 82.000 (79.073) Prec@5 100.000 (98.309) +2022-11-14 13:31:17,377 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.1211) Prec@1 77.000 (79.036) Prec@5 97.000 (98.286) +2022-11-14 13:31:17,386 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1320 (0.1213) Prec@1 76.000 (78.982) Prec@5 99.000 (98.298) +2022-11-14 13:31:17,396 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1224 (0.1213) Prec@1 77.000 (78.948) Prec@5 98.000 (98.293) +2022-11-14 13:31:17,405 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1434 (0.1217) Prec@1 74.000 (78.864) Prec@5 99.000 (98.305) +2022-11-14 13:31:17,415 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.1215) Prec@1 82.000 (78.917) Prec@5 99.000 (98.317) +2022-11-14 13:31:17,425 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1282 (0.1216) Prec@1 79.000 (78.918) Prec@5 98.000 (98.311) +2022-11-14 13:31:17,433 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1428 (0.1220) Prec@1 74.000 (78.839) Prec@5 100.000 (98.339) +2022-11-14 13:31:17,442 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.1218) Prec@1 82.000 (78.889) Prec@5 97.000 (98.317) +2022-11-14 13:31:17,452 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.1211) Prec@1 88.000 (79.031) Prec@5 100.000 (98.344) +2022-11-14 13:31:17,461 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1348 (0.1213) Prec@1 78.000 (79.015) Prec@5 98.000 (98.338) +2022-11-14 13:31:17,469 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1394 (0.1216) Prec@1 75.000 (78.955) Prec@5 98.000 (98.333) +2022-11-14 13:31:17,477 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.1212) Prec@1 86.000 (79.060) Prec@5 100.000 (98.358) +2022-11-14 13:31:17,485 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1649 (0.1218) Prec@1 69.000 (78.912) Prec@5 99.000 (98.368) +2022-11-14 13:31:17,493 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.1216) Prec@1 82.000 (78.957) Prec@5 98.000 (98.362) +2022-11-14 13:31:17,502 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1678 (0.1222) Prec@1 69.000 (78.814) Prec@5 97.000 (98.343) +2022-11-14 13:31:17,510 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.1221) Prec@1 79.000 (78.817) Prec@5 99.000 (98.352) +2022-11-14 13:31:17,519 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.1220) Prec@1 82.000 (78.861) Prec@5 96.000 (98.319) +2022-11-14 13:31:17,528 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.1217) Prec@1 83.000 (78.918) Prec@5 99.000 (98.329) +2022-11-14 13:31:17,537 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1214) Prec@1 82.000 (78.959) Prec@5 99.000 (98.338) +2022-11-14 13:31:17,546 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1243 (0.1215) Prec@1 82.000 (79.000) Prec@5 99.000 (98.347) +2022-11-14 13:31:17,556 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1317 (0.1216) Prec@1 72.000 (78.908) Prec@5 98.000 (98.342) +2022-11-14 13:31:17,565 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1251 (0.1217) Prec@1 77.000 (78.883) Prec@5 99.000 (98.351) +2022-11-14 13:31:17,574 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1124 (0.1215) Prec@1 81.000 (78.910) Prec@5 97.000 (98.333) +2022-11-14 13:31:17,583 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1299 (0.1217) Prec@1 77.000 (78.886) Prec@5 99.000 (98.342) +2022-11-14 13:31:17,593 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.1215) Prec@1 79.000 (78.888) Prec@5 99.000 (98.350) +2022-11-14 13:31:17,601 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.1214) Prec@1 81.000 (78.914) Prec@5 98.000 (98.346) +2022-11-14 13:31:17,610 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1351 (0.1215) Prec@1 77.000 (78.890) Prec@5 98.000 (98.341) +2022-11-14 13:31:17,619 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.1215) Prec@1 79.000 (78.892) Prec@5 100.000 (98.361) +2022-11-14 13:31:17,628 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.1213) Prec@1 78.000 (78.881) Prec@5 99.000 (98.369) +2022-11-14 13:31:17,636 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1562 (0.1217) Prec@1 73.000 (78.812) Prec@5 97.000 (98.353) +2022-11-14 13:31:17,646 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1255 (0.1217) Prec@1 80.000 (78.826) Prec@5 99.000 (98.360) +2022-11-14 13:31:17,656 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1203 (0.1217) Prec@1 78.000 (78.816) Prec@5 99.000 (98.368) +2022-11-14 13:31:17,664 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.1214) Prec@1 84.000 (78.875) Prec@5 99.000 (98.375) +2022-11-14 13:31:17,674 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1359 (0.1216) Prec@1 77.000 (78.854) Prec@5 95.000 (98.337) +2022-11-14 13:31:17,683 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1376 (0.1218) Prec@1 77.000 (78.833) Prec@5 96.000 (98.311) +2022-11-14 13:31:17,691 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1173 (0.1217) Prec@1 82.000 (78.868) Prec@5 99.000 (98.319) +2022-11-14 13:31:17,700 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.1213) Prec@1 88.000 (78.967) Prec@5 99.000 (98.326) +2022-11-14 13:31:17,709 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1548 (0.1216) Prec@1 74.000 (78.914) Prec@5 96.000 (98.301) +2022-11-14 13:31:17,717 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1346 (0.1218) Prec@1 76.000 (78.883) Prec@5 98.000 (98.298) +2022-11-14 13:31:17,726 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.1216) Prec@1 82.000 (78.916) Prec@5 98.000 (98.295) +2022-11-14 13:31:17,734 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.1213) Prec@1 82.000 (78.948) Prec@5 99.000 (98.302) +2022-11-14 13:31:17,743 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.1210) Prec@1 84.000 (79.000) Prec@5 99.000 (98.309) +2022-11-14 13:31:17,751 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1242 (0.1210) Prec@1 77.000 (78.980) Prec@5 98.000 (98.306) +2022-11-14 13:31:17,759 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1332 (0.1211) Prec@1 74.000 (78.929) Prec@5 98.000 (98.303) +2022-11-14 13:31:17,767 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1091 (0.1210) Prec@1 81.000 (78.950) Prec@5 100.000 (98.320) +2022-11-14 13:31:17,821 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:31:18,123 Epoch: [53][0/500] Time 0.022 (0.022) Data 0.221 (0.221) Loss 0.1132 (0.1132) Prec@1 81.000 (81.000) Prec@5 99.000 (99.000) +2022-11-14 13:31:18,319 Epoch: [53][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0959 (0.1045) Prec@1 85.000 (83.000) Prec@5 97.000 (98.000) +2022-11-14 13:31:18,514 Epoch: [53][20/500] Time 0.017 (0.017) Data 0.002 (0.012) Loss 0.1039 (0.1043) Prec@1 80.000 (82.000) Prec@5 100.000 (98.667) +2022-11-14 13:31:18,799 Epoch: [53][30/500] Time 0.035 (0.020) Data 0.002 (0.009) Loss 0.0677 (0.0952) Prec@1 89.000 (83.750) Prec@5 100.000 (99.000) +2022-11-14 13:31:19,138 Epoch: [53][40/500] Time 0.031 (0.022) Data 0.001 (0.007) Loss 0.1146 (0.0991) Prec@1 82.000 (83.400) Prec@5 99.000 (99.000) +2022-11-14 13:31:19,474 Epoch: [53][50/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.1213 (0.1028) Prec@1 75.000 (82.000) Prec@5 98.000 (98.833) +2022-11-14 13:31:19,872 Epoch: [53][60/500] Time 0.040 (0.026) Data 0.002 (0.005) Loss 0.0867 (0.1005) Prec@1 84.000 (82.286) Prec@5 100.000 (99.000) +2022-11-14 13:31:20,224 Epoch: [53][70/500] Time 0.028 (0.027) Data 0.002 (0.005) Loss 0.0839 (0.0984) Prec@1 85.000 (82.625) Prec@5 99.000 (99.000) +2022-11-14 13:31:20,608 Epoch: [53][80/500] Time 0.045 (0.028) Data 0.002 (0.004) Loss 0.1175 (0.1005) Prec@1 80.000 (82.333) Prec@5 99.000 (99.000) +2022-11-14 13:31:20,927 Epoch: [53][90/500] Time 0.033 (0.028) Data 0.002 (0.004) Loss 0.0946 (0.0999) Prec@1 84.000 (82.500) Prec@5 100.000 (99.100) +2022-11-14 13:31:21,259 Epoch: [53][100/500] Time 0.032 (0.028) Data 0.003 (0.004) Loss 0.1142 (0.1012) Prec@1 76.000 (81.909) Prec@5 99.000 (99.091) +2022-11-14 13:31:21,632 Epoch: [53][110/500] Time 0.034 (0.028) Data 0.002 (0.004) Loss 0.0815 (0.0996) Prec@1 85.000 (82.167) Prec@5 99.000 (99.083) +2022-11-14 13:31:21,990 Epoch: [53][120/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0846 (0.0984) Prec@1 84.000 (82.308) Prec@5 98.000 (99.000) +2022-11-14 13:31:22,332 Epoch: [53][130/500] Time 0.038 (0.029) Data 0.002 (0.003) Loss 0.0901 (0.0978) Prec@1 85.000 (82.500) Prec@5 100.000 (99.071) +2022-11-14 13:31:22,678 Epoch: [53][140/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0843 (0.0969) Prec@1 87.000 (82.800) Prec@5 100.000 (99.133) +2022-11-14 13:31:23,052 Epoch: [53][150/500] Time 0.025 (0.029) Data 0.002 (0.003) Loss 0.0913 (0.0966) Prec@1 86.000 (83.000) Prec@5 97.000 (99.000) +2022-11-14 13:31:23,403 Epoch: [53][160/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0899 (0.0962) Prec@1 84.000 (83.059) Prec@5 99.000 (99.000) +2022-11-14 13:31:23,766 Epoch: [53][170/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0798 (0.0953) Prec@1 86.000 (83.222) Prec@5 99.000 (99.000) +2022-11-14 13:31:24,118 Epoch: [53][180/500] Time 0.027 (0.030) Data 0.002 (0.003) Loss 0.1353 (0.0974) Prec@1 76.000 (82.842) Prec@5 100.000 (99.053) +2022-11-14 13:31:24,453 Epoch: [53][190/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.1319 (0.0991) Prec@1 76.000 (82.500) Prec@5 99.000 (99.050) +2022-11-14 13:31:24,785 Epoch: [53][200/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0899 (0.0987) Prec@1 84.000 (82.571) Prec@5 98.000 (99.000) +2022-11-14 13:31:25,120 Epoch: [53][210/500] Time 0.031 (0.030) Data 0.003 (0.003) Loss 0.0858 (0.0981) Prec@1 87.000 (82.773) Prec@5 98.000 (98.955) +2022-11-14 13:31:25,462 Epoch: [53][220/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0647 (0.0966) Prec@1 91.000 (83.130) Prec@5 100.000 (99.000) +2022-11-14 13:31:25,801 Epoch: [53][230/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0824 (0.0961) Prec@1 85.000 (83.208) Prec@5 98.000 (98.958) +2022-11-14 13:31:26,147 Epoch: [53][240/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.1006 (0.0962) Prec@1 82.000 (83.160) Prec@5 99.000 (98.960) +2022-11-14 13:31:26,490 Epoch: [53][250/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0929 (0.0961) Prec@1 86.000 (83.269) Prec@5 99.000 (98.962) +2022-11-14 13:31:26,841 Epoch: [53][260/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0950 (0.0961) Prec@1 82.000 (83.222) Prec@5 99.000 (98.963) +2022-11-14 13:31:27,222 Epoch: [53][270/500] Time 0.054 (0.030) Data 0.002 (0.003) Loss 0.0654 (0.0950) Prec@1 89.000 (83.429) Prec@5 99.000 (98.964) +2022-11-14 13:31:27,552 Epoch: [53][280/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0989 (0.0951) Prec@1 82.000 (83.379) Prec@5 99.000 (98.966) +2022-11-14 13:31:27,903 Epoch: [53][290/500] Time 0.029 (0.030) Data 0.002 (0.003) Loss 0.0849 (0.0948) Prec@1 83.000 (83.367) Prec@5 97.000 (98.900) +2022-11-14 13:31:28,233 Epoch: [53][300/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0819 (0.0943) Prec@1 84.000 (83.387) Prec@5 100.000 (98.935) +2022-11-14 13:31:28,577 Epoch: [53][310/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0881 (0.0942) Prec@1 86.000 (83.469) Prec@5 99.000 (98.938) +2022-11-14 13:31:28,954 Epoch: [53][320/500] Time 0.043 (0.030) Data 0.001 (0.003) Loss 0.0962 (0.0942) Prec@1 85.000 (83.515) Prec@5 99.000 (98.939) +2022-11-14 13:31:29,472 Epoch: [53][330/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.1027 (0.0945) Prec@1 83.000 (83.500) Prec@5 100.000 (98.971) +2022-11-14 13:31:29,948 Epoch: [53][340/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.1136 (0.0950) Prec@1 80.000 (83.400) Prec@5 95.000 (98.857) +2022-11-14 13:31:30,430 Epoch: [53][350/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1230 (0.0958) Prec@1 79.000 (83.278) Prec@5 99.000 (98.861) +2022-11-14 13:31:31,036 Epoch: [53][360/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.1136 (0.0963) Prec@1 79.000 (83.162) Prec@5 97.000 (98.811) +2022-11-14 13:31:31,573 Epoch: [53][370/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0968 (0.0963) Prec@1 82.000 (83.132) Prec@5 99.000 (98.816) +2022-11-14 13:31:32,072 Epoch: [53][380/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.1098 (0.0966) Prec@1 82.000 (83.103) Prec@5 97.000 (98.769) +2022-11-14 13:31:32,538 Epoch: [53][390/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.1016 (0.0968) Prec@1 80.000 (83.025) Prec@5 99.000 (98.775) +2022-11-14 13:31:33,002 Epoch: [53][400/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0891 (0.0966) Prec@1 84.000 (83.049) Prec@5 99.000 (98.780) +2022-11-14 13:31:33,691 Epoch: [53][410/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0935 (0.0965) Prec@1 84.000 (83.071) Prec@5 99.000 (98.786) +2022-11-14 13:31:34,188 Epoch: [53][420/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.0743 (0.0960) Prec@1 86.000 (83.140) Prec@5 100.000 (98.814) +2022-11-14 13:31:34,772 Epoch: [53][430/500] Time 0.087 (0.034) Data 0.002 (0.002) Loss 0.0768 (0.0955) Prec@1 87.000 (83.227) Prec@5 100.000 (98.841) +2022-11-14 13:31:35,348 Epoch: [53][440/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0649 (0.0949) Prec@1 89.000 (83.356) Prec@5 98.000 (98.822) +2022-11-14 13:31:35,843 Epoch: [53][450/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0989 (0.0950) Prec@1 80.000 (83.283) Prec@5 99.000 (98.826) +2022-11-14 13:31:36,352 Epoch: [53][460/500] Time 0.046 (0.035) Data 0.002 (0.002) Loss 0.1196 (0.0955) Prec@1 78.000 (83.170) Prec@5 98.000 (98.809) +2022-11-14 13:31:36,816 Epoch: [53][470/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.1366 (0.0963) Prec@1 75.000 (83.000) Prec@5 92.000 (98.667) +2022-11-14 13:31:37,279 Epoch: [53][480/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0896 (0.0962) Prec@1 84.000 (83.020) Prec@5 98.000 (98.653) +2022-11-14 13:31:37,750 Epoch: [53][490/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0733 (0.0957) Prec@1 89.000 (83.140) Prec@5 100.000 (98.680) +2022-11-14 13:31:38,168 Epoch: [53][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0800 (0.0954) Prec@1 88.000 (83.235) Prec@5 99.000 (98.686) +2022-11-14 13:31:38,447 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1089 (0.1089) Prec@1 81.000 (81.000) Prec@5 99.000 (99.000) +2022-11-14 13:31:38,455 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1315 (0.1202) Prec@1 77.000 (79.000) Prec@5 98.000 (98.500) +2022-11-14 13:31:38,463 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1333 (0.1245) Prec@1 77.000 (78.333) Prec@5 98.000 (98.333) +2022-11-14 13:31:38,475 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1263) Prec@1 77.000 (78.000) Prec@5 100.000 (98.750) +2022-11-14 13:31:38,484 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.1270) Prec@1 77.000 (77.800) Prec@5 100.000 (99.000) +2022-11-14 13:31:38,493 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.1144) Prec@1 93.000 (80.333) Prec@5 99.000 (99.000) +2022-11-14 13:31:38,504 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1124) Prec@1 82.000 (80.571) Prec@5 97.000 (98.714) +2022-11-14 13:31:38,516 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1483 (0.1169) Prec@1 72.000 (79.500) Prec@5 99.000 (98.750) +2022-11-14 13:31:38,527 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.1187) Prec@1 78.000 (79.333) Prec@5 99.000 (98.778) +2022-11-14 13:31:38,539 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.1174) Prec@1 81.000 (79.500) Prec@5 99.000 (98.800) +2022-11-14 13:31:38,549 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.1161) Prec@1 84.000 (79.909) Prec@5 100.000 (98.909) +2022-11-14 13:31:38,558 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.1149) Prec@1 83.000 (80.167) Prec@5 98.000 (98.833) +2022-11-14 13:31:38,567 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.1128) Prec@1 83.000 (80.385) Prec@5 100.000 (98.923) +2022-11-14 13:31:38,577 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.1117) Prec@1 84.000 (80.643) Prec@5 95.000 (98.643) +2022-11-14 13:31:38,588 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1242 (0.1126) Prec@1 77.000 (80.400) Prec@5 96.000 (98.467) +2022-11-14 13:31:38,602 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1398 (0.1143) Prec@1 74.000 (80.000) Prec@5 98.000 (98.438) +2022-11-14 13:31:38,616 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.1142) Prec@1 79.000 (79.941) Prec@5 96.000 (98.294) +2022-11-14 13:31:38,630 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.1131) Prec@1 83.000 (80.111) Prec@5 99.000 (98.333) +2022-11-14 13:31:38,643 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1215 (0.1135) Prec@1 80.000 (80.105) Prec@5 98.000 (98.316) +2022-11-14 13:31:38,657 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1489 (0.1153) Prec@1 75.000 (79.850) Prec@5 97.000 (98.250) +2022-11-14 13:31:38,671 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1251 (0.1158) Prec@1 79.000 (79.810) Prec@5 98.000 (98.238) +2022-11-14 13:31:38,684 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.1151) Prec@1 82.000 (79.909) Prec@5 99.000 (98.273) +2022-11-14 13:31:38,698 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1144) Prec@1 83.000 (80.043) Prec@5 98.000 (98.261) +2022-11-14 13:31:38,712 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1109 (0.1143) Prec@1 81.000 (80.083) Prec@5 100.000 (98.333) +2022-11-14 13:31:38,725 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1398 (0.1153) Prec@1 77.000 (79.960) Prec@5 96.000 (98.240) +2022-11-14 13:31:38,740 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1408 (0.1163) Prec@1 77.000 (79.846) Prec@5 97.000 (98.192) +2022-11-14 13:31:38,754 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1310 (0.1168) Prec@1 79.000 (79.815) Prec@5 100.000 (98.259) +2022-11-14 13:31:38,768 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1320 (0.1174) Prec@1 76.000 (79.679) Prec@5 99.000 (98.286) +2022-11-14 13:31:38,781 Test: [28/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.1173) Prec@1 81.000 (79.724) Prec@5 97.000 (98.241) +2022-11-14 13:31:38,794 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1167) Prec@1 86.000 (79.933) Prec@5 95.000 (98.133) +2022-11-14 13:31:38,807 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.1162) Prec@1 85.000 (80.097) Prec@5 96.000 (98.065) +2022-11-14 13:31:38,821 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.1159) Prec@1 80.000 (80.094) Prec@5 100.000 (98.125) +2022-11-14 13:31:38,834 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.1148) Prec@1 84.000 (80.212) Prec@5 100.000 (98.182) +2022-11-14 13:31:38,846 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1362 (0.1154) Prec@1 74.000 (80.029) Prec@5 99.000 (98.206) +2022-11-14 13:31:38,862 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.1151) Prec@1 85.000 (80.171) Prec@5 98.000 (98.200) +2022-11-14 13:31:38,877 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.1148) Prec@1 85.000 (80.306) Prec@5 97.000 (98.167) +2022-11-14 13:31:38,890 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.1147) Prec@1 81.000 (80.324) Prec@5 97.000 (98.135) +2022-11-14 13:31:38,902 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1360 (0.1153) Prec@1 75.000 (80.184) Prec@5 99.000 (98.158) +2022-11-14 13:31:38,918 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1152) Prec@1 81.000 (80.205) Prec@5 98.000 (98.154) +2022-11-14 13:31:38,930 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.1146) Prec@1 84.000 (80.300) Prec@5 96.000 (98.100) +2022-11-14 13:31:38,945 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1394 (0.1152) Prec@1 79.000 (80.268) Prec@5 95.000 (98.024) +2022-11-14 13:31:38,959 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1093 (0.1151) Prec@1 82.000 (80.310) Prec@5 98.000 (98.024) +2022-11-14 13:31:38,972 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.1145) Prec@1 84.000 (80.395) Prec@5 98.000 (98.023) +2022-11-14 13:31:38,983 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1082 (0.1144) Prec@1 82.000 (80.432) Prec@5 97.000 (98.000) +2022-11-14 13:31:38,998 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.1141) Prec@1 87.000 (80.578) Prec@5 97.000 (97.978) +2022-11-14 13:31:39,013 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1330 (0.1145) Prec@1 74.000 (80.435) Prec@5 98.000 (97.978) +2022-11-14 13:31:39,029 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1216 (0.1147) Prec@1 80.000 (80.426) Prec@5 100.000 (98.021) +2022-11-14 13:31:39,044 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1274 (0.1149) Prec@1 78.000 (80.375) Prec@5 96.000 (97.979) +2022-11-14 13:31:39,058 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.1142) Prec@1 85.000 (80.469) Prec@5 100.000 (98.020) +2022-11-14 13:31:39,072 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1162 (0.1143) Prec@1 81.000 (80.480) Prec@5 98.000 (98.020) +2022-11-14 13:31:39,086 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.1138) Prec@1 83.000 (80.529) Prec@5 99.000 (98.039) +2022-11-14 13:31:39,101 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1359 (0.1143) Prec@1 75.000 (80.423) Prec@5 98.000 (98.038) +2022-11-14 13:31:39,115 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1190 (0.1144) Prec@1 80.000 (80.415) Prec@5 98.000 (98.038) +2022-11-14 13:31:39,128 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.1138) Prec@1 84.000 (80.481) Prec@5 98.000 (98.037) +2022-11-14 13:31:39,142 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.1137) Prec@1 82.000 (80.509) Prec@5 100.000 (98.073) +2022-11-14 13:31:39,156 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1296 (0.1139) Prec@1 78.000 (80.464) Prec@5 98.000 (98.071) +2022-11-14 13:31:39,171 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.1139) Prec@1 80.000 (80.456) Prec@5 97.000 (98.053) +2022-11-14 13:31:39,185 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.1137) Prec@1 84.000 (80.517) Prec@5 98.000 (98.052) +2022-11-14 13:31:39,200 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1536 (0.1143) Prec@1 74.000 (80.407) Prec@5 99.000 (98.068) +2022-11-14 13:31:39,213 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.1141) Prec@1 83.000 (80.450) Prec@5 98.000 (98.067) +2022-11-14 13:31:39,226 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1374 (0.1145) Prec@1 78.000 (80.410) Prec@5 99.000 (98.082) +2022-11-14 13:31:39,238 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.1143) Prec@1 81.000 (80.419) Prec@5 98.000 (98.081) +2022-11-14 13:31:39,251 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.1138) Prec@1 85.000 (80.492) Prec@5 99.000 (98.095) +2022-11-14 13:31:39,263 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.1135) Prec@1 82.000 (80.516) Prec@5 100.000 (98.125) +2022-11-14 13:31:39,277 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.1136) Prec@1 78.000 (80.477) Prec@5 98.000 (98.123) +2022-11-14 13:31:39,292 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.1135) Prec@1 82.000 (80.500) Prec@5 97.000 (98.106) +2022-11-14 13:31:39,306 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.1131) Prec@1 86.000 (80.582) Prec@5 99.000 (98.119) +2022-11-14 13:31:39,320 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1393 (0.1135) Prec@1 76.000 (80.515) Prec@5 96.000 (98.088) +2022-11-14 13:31:39,333 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.1129) Prec@1 88.000 (80.623) Prec@5 98.000 (98.087) +2022-11-14 13:31:39,346 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1640 (0.1136) Prec@1 72.000 (80.500) Prec@5 98.000 (98.086) +2022-11-14 13:31:39,361 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1197 (0.1137) Prec@1 80.000 (80.493) Prec@5 99.000 (98.099) +2022-11-14 13:31:39,375 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.1136) Prec@1 80.000 (80.486) Prec@5 100.000 (98.125) +2022-11-14 13:31:39,389 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.1135) Prec@1 80.000 (80.479) Prec@5 99.000 (98.137) +2022-11-14 13:31:39,403 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.1131) Prec@1 87.000 (80.568) Prec@5 100.000 (98.162) +2022-11-14 13:31:39,417 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.1130) Prec@1 81.000 (80.573) Prec@5 97.000 (98.147) +2022-11-14 13:31:39,431 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.1130) Prec@1 83.000 (80.605) Prec@5 99.000 (98.158) +2022-11-14 13:31:39,443 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1153 (0.1130) Prec@1 82.000 (80.623) Prec@5 98.000 (98.156) +2022-11-14 13:31:39,459 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.1128) Prec@1 83.000 (80.654) Prec@5 100.000 (98.179) +2022-11-14 13:31:39,472 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1417 (0.1131) Prec@1 77.000 (80.608) Prec@5 100.000 (98.203) +2022-11-14 13:31:39,487 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.1130) Prec@1 81.000 (80.612) Prec@5 99.000 (98.213) +2022-11-14 13:31:39,500 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.1127) Prec@1 84.000 (80.654) Prec@5 97.000 (98.198) +2022-11-14 13:31:39,514 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1236 (0.1128) Prec@1 77.000 (80.610) Prec@5 98.000 (98.195) +2022-11-14 13:31:39,527 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.1128) Prec@1 78.000 (80.578) Prec@5 99.000 (98.205) +2022-11-14 13:31:39,542 Test: [83/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1272 (0.1130) Prec@1 80.000 (80.571) Prec@5 99.000 (98.214) +2022-11-14 13:31:39,557 Test: [84/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1412 (0.1133) Prec@1 74.000 (80.494) Prec@5 98.000 (98.212) +2022-11-14 13:31:39,571 Test: [85/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1545 (0.1138) Prec@1 72.000 (80.395) Prec@5 99.000 (98.221) +2022-11-14 13:31:39,584 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1444 (0.1142) Prec@1 72.000 (80.299) Prec@5 97.000 (98.207) +2022-11-14 13:31:39,602 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1316 (0.1144) Prec@1 78.000 (80.273) Prec@5 100.000 (98.227) +2022-11-14 13:31:39,615 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1144) Prec@1 79.000 (80.258) Prec@5 100.000 (98.247) +2022-11-14 13:31:39,629 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.1144) Prec@1 79.000 (80.244) Prec@5 97.000 (98.233) +2022-11-14 13:31:39,643 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.1144) Prec@1 78.000 (80.220) Prec@5 99.000 (98.242) +2022-11-14 13:31:39,656 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.1140) Prec@1 85.000 (80.272) Prec@5 100.000 (98.261) +2022-11-14 13:31:39,671 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1143) Prec@1 76.000 (80.226) Prec@5 97.000 (98.247) +2022-11-14 13:31:39,684 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.1142) Prec@1 82.000 (80.245) Prec@5 99.000 (98.255) +2022-11-14 13:31:39,697 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.1140) Prec@1 81.000 (80.253) Prec@5 98.000 (98.253) +2022-11-14 13:31:39,710 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.1137) Prec@1 82.000 (80.271) Prec@5 98.000 (98.250) +2022-11-14 13:31:39,723 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1136) Prec@1 84.000 (80.309) Prec@5 99.000 (98.258) +2022-11-14 13:31:39,735 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.1138) Prec@1 78.000 (80.286) Prec@5 97.000 (98.245) +2022-11-14 13:31:39,749 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1462 (0.1141) Prec@1 76.000 (80.242) Prec@5 99.000 (98.253) +2022-11-14 13:31:39,763 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.1139) Prec@1 85.000 (80.290) Prec@5 99.000 (98.260) +2022-11-14 13:31:39,819 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:31:40,117 Epoch: [54][0/500] Time 0.026 (0.026) Data 0.212 (0.212) Loss 0.0801 (0.0801) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 13:31:40,330 Epoch: [54][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.1083 (0.0942) Prec@1 83.000 (84.500) Prec@5 99.000 (99.500) +2022-11-14 13:31:40,540 Epoch: [54][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0747 (0.0877) Prec@1 88.000 (85.667) Prec@5 99.000 (99.333) +2022-11-14 13:31:40,749 Epoch: [54][30/500] Time 0.021 (0.019) Data 0.002 (0.008) Loss 0.1074 (0.0926) Prec@1 79.000 (84.000) Prec@5 97.000 (98.750) +2022-11-14 13:31:41,012 Epoch: [54][40/500] Time 0.025 (0.020) Data 0.002 (0.007) Loss 0.1233 (0.0988) Prec@1 77.000 (82.600) Prec@5 97.000 (98.400) +2022-11-14 13:31:41,291 Epoch: [54][50/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.0864 (0.0967) Prec@1 86.000 (83.167) Prec@5 98.000 (98.333) +2022-11-14 13:31:41,576 Epoch: [54][60/500] Time 0.029 (0.022) Data 0.002 (0.005) Loss 0.0792 (0.0942) Prec@1 86.000 (83.571) Prec@5 99.000 (98.429) +2022-11-14 13:31:41,876 Epoch: [54][70/500] Time 0.035 (0.022) Data 0.002 (0.005) Loss 0.0929 (0.0940) Prec@1 85.000 (83.750) Prec@5 99.000 (98.500) +2022-11-14 13:31:42,131 Epoch: [54][80/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0855 (0.0931) Prec@1 83.000 (83.667) Prec@5 97.000 (98.333) +2022-11-14 13:31:42,406 Epoch: [54][90/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0747 (0.0913) Prec@1 87.000 (84.000) Prec@5 100.000 (98.500) +2022-11-14 13:31:42,761 Epoch: [54][100/500] Time 0.044 (0.023) Data 0.002 (0.004) Loss 0.1171 (0.0936) Prec@1 79.000 (83.545) Prec@5 98.000 (98.455) +2022-11-14 13:31:43,221 Epoch: [54][110/500] Time 0.043 (0.025) Data 0.002 (0.004) Loss 0.1045 (0.0945) Prec@1 82.000 (83.417) Prec@5 99.000 (98.500) +2022-11-14 13:31:43,680 Epoch: [54][120/500] Time 0.041 (0.026) Data 0.002 (0.004) Loss 0.0972 (0.0947) Prec@1 81.000 (83.231) Prec@5 100.000 (98.615) +2022-11-14 13:31:44,140 Epoch: [54][130/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0826 (0.0939) Prec@1 83.000 (83.214) Prec@5 100.000 (98.714) +2022-11-14 13:31:44,609 Epoch: [54][140/500] Time 0.039 (0.028) Data 0.002 (0.003) Loss 0.1091 (0.0949) Prec@1 80.000 (83.000) Prec@5 100.000 (98.800) +2022-11-14 13:31:45,098 Epoch: [54][150/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1118 (0.0959) Prec@1 79.000 (82.750) Prec@5 99.000 (98.812) +2022-11-14 13:31:45,556 Epoch: [54][160/500] Time 0.047 (0.030) Data 0.003 (0.003) Loss 0.1184 (0.0973) Prec@1 82.000 (82.706) Prec@5 97.000 (98.706) +2022-11-14 13:31:46,019 Epoch: [54][170/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.1098 (0.0980) Prec@1 77.000 (82.389) Prec@5 98.000 (98.667) +2022-11-14 13:31:46,556 Epoch: [54][180/500] Time 0.053 (0.032) Data 0.002 (0.003) Loss 0.0959 (0.0978) Prec@1 84.000 (82.474) Prec@5 100.000 (98.737) +2022-11-14 13:31:47,056 Epoch: [54][190/500] Time 0.049 (0.032) Data 0.002 (0.003) Loss 0.0807 (0.0970) Prec@1 87.000 (82.700) Prec@5 99.000 (98.750) +2022-11-14 13:31:47,575 Epoch: [54][200/500] Time 0.059 (0.033) Data 0.002 (0.003) Loss 0.1302 (0.0986) Prec@1 77.000 (82.429) Prec@5 96.000 (98.619) +2022-11-14 13:31:48,126 Epoch: [54][210/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.1381 (0.1004) Prec@1 76.000 (82.136) Prec@5 97.000 (98.545) +2022-11-14 13:31:48,640 Epoch: [54][220/500] Time 0.053 (0.034) Data 0.002 (0.003) Loss 0.0718 (0.0991) Prec@1 90.000 (82.478) Prec@5 100.000 (98.609) +2022-11-14 13:31:49,192 Epoch: [54][230/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.1133 (0.0997) Prec@1 80.000 (82.375) Prec@5 100.000 (98.667) +2022-11-14 13:31:49,689 Epoch: [54][240/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0890 (0.0993) Prec@1 84.000 (82.440) Prec@5 99.000 (98.680) +2022-11-14 13:31:50,250 Epoch: [54][250/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.1047 (0.0995) Prec@1 81.000 (82.385) Prec@5 98.000 (98.654) +2022-11-14 13:31:50,844 Epoch: [54][260/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.0938 (0.0993) Prec@1 84.000 (82.444) Prec@5 99.000 (98.667) +2022-11-14 13:31:51,315 Epoch: [54][270/500] Time 0.056 (0.037) Data 0.002 (0.003) Loss 0.1220 (0.1001) Prec@1 77.000 (82.250) Prec@5 95.000 (98.536) +2022-11-14 13:31:51,820 Epoch: [54][280/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0928 (0.0998) Prec@1 84.000 (82.310) Prec@5 98.000 (98.517) +2022-11-14 13:31:52,458 Epoch: [54][290/500] Time 0.056 (0.038) Data 0.003 (0.003) Loss 0.0954 (0.0997) Prec@1 85.000 (82.400) Prec@5 100.000 (98.567) +2022-11-14 13:31:53,089 Epoch: [54][300/500] Time 0.060 (0.039) Data 0.002 (0.003) Loss 0.1555 (0.1015) Prec@1 73.000 (82.097) Prec@5 98.000 (98.548) +2022-11-14 13:31:53,702 Epoch: [54][310/500] Time 0.067 (0.039) Data 0.002 (0.003) Loss 0.1117 (0.1018) Prec@1 80.000 (82.031) Prec@5 98.000 (98.531) +2022-11-14 13:31:54,235 Epoch: [54][320/500] Time 0.063 (0.039) Data 0.003 (0.003) Loss 0.0957 (0.1016) Prec@1 83.000 (82.061) Prec@5 100.000 (98.576) +2022-11-14 13:31:54,845 Epoch: [54][330/500] Time 0.037 (0.040) Data 0.003 (0.003) Loss 0.1077 (0.1018) Prec@1 80.000 (82.000) Prec@5 97.000 (98.529) +2022-11-14 13:31:55,417 Epoch: [54][340/500] Time 0.061 (0.040) Data 0.002 (0.003) Loss 0.1130 (0.1021) Prec@1 80.000 (81.943) Prec@5 99.000 (98.543) +2022-11-14 13:31:55,902 Epoch: [54][350/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.1067 (0.1023) Prec@1 79.000 (81.861) Prec@5 99.000 (98.556) +2022-11-14 13:31:56,464 Epoch: [54][360/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0995 (0.1022) Prec@1 83.000 (81.892) Prec@5 98.000 (98.541) +2022-11-14 13:31:57,047 Epoch: [54][370/500] Time 0.065 (0.041) Data 0.002 (0.003) Loss 0.1060 (0.1023) Prec@1 84.000 (81.947) Prec@5 99.000 (98.553) +2022-11-14 13:31:57,596 Epoch: [54][380/500] Time 0.043 (0.041) Data 0.003 (0.003) Loss 0.0902 (0.1020) Prec@1 87.000 (82.077) Prec@5 98.000 (98.538) +2022-11-14 13:31:58,111 Epoch: [54][390/500] Time 0.046 (0.041) Data 0.003 (0.003) Loss 0.1190 (0.1024) Prec@1 81.000 (82.050) Prec@5 97.000 (98.500) +2022-11-14 13:31:58,629 Epoch: [54][400/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.1499 (0.1036) Prec@1 72.000 (81.805) Prec@5 99.000 (98.512) +2022-11-14 13:31:59,202 Epoch: [54][410/500] Time 0.044 (0.042) Data 0.003 (0.003) Loss 0.0927 (0.1033) Prec@1 82.000 (81.810) Prec@5 100.000 (98.548) +2022-11-14 13:31:59,680 Epoch: [54][420/500] Time 0.035 (0.042) Data 0.002 (0.003) Loss 0.0695 (0.1025) Prec@1 89.000 (81.977) Prec@5 99.000 (98.558) +2022-11-14 13:32:00,183 Epoch: [54][430/500] Time 0.038 (0.042) Data 0.002 (0.003) Loss 0.0865 (0.1021) Prec@1 85.000 (82.045) Prec@5 99.000 (98.568) +2022-11-14 13:32:00,755 Epoch: [54][440/500] Time 0.052 (0.042) Data 0.002 (0.003) Loss 0.1026 (0.1022) Prec@1 81.000 (82.022) Prec@5 100.000 (98.600) +2022-11-14 13:32:01,339 Epoch: [54][450/500] Time 0.057 (0.042) Data 0.002 (0.003) Loss 0.1175 (0.1025) Prec@1 78.000 (81.935) Prec@5 99.000 (98.609) +2022-11-14 13:32:01,859 Epoch: [54][460/500] Time 0.036 (0.042) Data 0.002 (0.003) Loss 0.1155 (0.1028) Prec@1 79.000 (81.872) Prec@5 98.000 (98.596) +2022-11-14 13:32:02,314 Epoch: [54][470/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0623 (0.1019) Prec@1 88.000 (82.000) Prec@5 99.000 (98.604) +2022-11-14 13:32:02,776 Epoch: [54][480/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0946 (0.1018) Prec@1 82.000 (82.000) Prec@5 97.000 (98.571) +2022-11-14 13:32:03,234 Epoch: [54][490/500] Time 0.043 (0.042) Data 0.003 (0.003) Loss 0.1363 (0.1025) Prec@1 75.000 (81.860) Prec@5 98.000 (98.560) +2022-11-14 13:32:03,647 Epoch: [54][499/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1196 (0.1028) Prec@1 78.000 (81.784) Prec@5 99.000 (98.569) +2022-11-14 13:32:03,929 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1186 (0.1186) Prec@1 81.000 (81.000) Prec@5 97.000 (97.000) +2022-11-14 13:32:03,939 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1199 (0.1193) Prec@1 80.000 (80.500) Prec@5 100.000 (98.500) +2022-11-14 13:32:03,947 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1310 (0.1232) Prec@1 74.000 (78.333) Prec@5 99.000 (98.667) +2022-11-14 13:32:03,959 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1426 (0.1281) Prec@1 75.000 (77.500) Prec@5 100.000 (99.000) +2022-11-14 13:32:03,968 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.1262) Prec@1 78.000 (77.600) Prec@5 99.000 (99.000) +2022-11-14 13:32:03,976 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.1199) Prec@1 84.000 (78.667) Prec@5 99.000 (99.000) +2022-11-14 13:32:03,984 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1245 (0.1205) Prec@1 79.000 (78.714) Prec@5 99.000 (99.000) +2022-11-14 13:32:03,995 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1323 (0.1220) Prec@1 74.000 (78.125) Prec@5 100.000 (99.125) +2022-11-14 13:32:04,004 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1561 (0.1258) Prec@1 69.000 (77.111) Prec@5 100.000 (99.222) +2022-11-14 13:32:04,013 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.1242) Prec@1 82.000 (77.600) Prec@5 98.000 (99.100) +2022-11-14 13:32:04,023 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.1219) Prec@1 85.000 (78.273) Prec@5 99.000 (99.091) +2022-11-14 13:32:04,033 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1339 (0.1229) Prec@1 75.000 (78.000) Prec@5 99.000 (99.083) +2022-11-14 13:32:04,043 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.1201) Prec@1 82.000 (78.308) Prec@5 98.000 (99.000) +2022-11-14 13:32:04,052 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1187) Prec@1 81.000 (78.500) Prec@5 98.000 (98.929) +2022-11-14 13:32:04,061 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.1182) Prec@1 79.000 (78.533) Prec@5 100.000 (99.000) +2022-11-14 13:32:04,072 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1251 (0.1186) Prec@1 77.000 (78.438) Prec@5 97.000 (98.875) +2022-11-14 13:32:04,082 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.1172) Prec@1 86.000 (78.882) Prec@5 99.000 (98.882) +2022-11-14 13:32:04,093 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1334 (0.1181) Prec@1 75.000 (78.667) Prec@5 99.000 (98.889) +2022-11-14 13:32:04,102 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.1183) Prec@1 78.000 (78.632) Prec@5 98.000 (98.842) +2022-11-14 13:32:04,112 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1533 (0.1200) Prec@1 75.000 (78.450) Prec@5 94.000 (98.600) +2022-11-14 13:32:04,121 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1199) Prec@1 78.000 (78.429) Prec@5 100.000 (98.667) +2022-11-14 13:32:04,129 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.1195) Prec@1 81.000 (78.545) Prec@5 97.000 (98.591) +2022-11-14 13:32:04,139 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1198) Prec@1 78.000 (78.522) Prec@5 98.000 (98.565) +2022-11-14 13:32:04,149 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.1195) Prec@1 80.000 (78.583) Prec@5 98.000 (98.542) +2022-11-14 13:32:04,158 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.1198) Prec@1 78.000 (78.560) Prec@5 98.000 (98.520) +2022-11-14 13:32:04,169 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1202) Prec@1 79.000 (78.577) Prec@5 97.000 (98.462) +2022-11-14 13:32:04,179 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.1198) Prec@1 82.000 (78.704) Prec@5 100.000 (98.519) +2022-11-14 13:32:04,190 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.1197) Prec@1 81.000 (78.786) Prec@5 99.000 (98.536) +2022-11-14 13:32:04,200 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.1197) Prec@1 77.000 (78.724) Prec@5 96.000 (98.448) +2022-11-14 13:32:04,211 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1197) Prec@1 75.000 (78.600) Prec@5 99.000 (98.467) +2022-11-14 13:32:04,221 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.1193) Prec@1 80.000 (78.645) Prec@5 97.000 (98.419) +2022-11-14 13:32:04,232 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.1194) Prec@1 81.000 (78.719) Prec@5 99.000 (98.438) +2022-11-14 13:32:04,241 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.1188) Prec@1 84.000 (78.879) Prec@5 98.000 (98.424) +2022-11-14 13:32:04,253 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1409 (0.1194) Prec@1 75.000 (78.765) Prec@5 98.000 (98.412) +2022-11-14 13:32:04,262 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.1192) Prec@1 80.000 (78.800) Prec@5 99.000 (98.429) +2022-11-14 13:32:04,273 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.1196) Prec@1 73.000 (78.639) Prec@5 96.000 (98.361) +2022-11-14 13:32:04,283 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.1196) Prec@1 81.000 (78.703) Prec@5 98.000 (98.351) +2022-11-14 13:32:04,294 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1283 (0.1198) Prec@1 77.000 (78.658) Prec@5 98.000 (98.342) +2022-11-14 13:32:04,307 Test: [38/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.1197) Prec@1 82.000 (78.744) Prec@5 100.000 (98.385) +2022-11-14 13:32:04,317 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1192) Prec@1 83.000 (78.850) Prec@5 98.000 (98.375) +2022-11-14 13:32:04,327 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1428 (0.1197) Prec@1 72.000 (78.683) Prec@5 98.000 (98.366) +2022-11-14 13:32:04,336 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.1195) Prec@1 80.000 (78.714) Prec@5 99.000 (98.381) +2022-11-14 13:32:04,346 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.1189) Prec@1 84.000 (78.837) Prec@5 99.000 (98.395) +2022-11-14 13:32:04,356 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.1187) Prec@1 83.000 (78.932) Prec@5 96.000 (98.341) +2022-11-14 13:32:04,365 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.1185) Prec@1 83.000 (79.022) Prec@5 97.000 (98.311) +2022-11-14 13:32:04,376 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1554 (0.1193) Prec@1 68.000 (78.783) Prec@5 99.000 (98.326) +2022-11-14 13:32:04,385 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.1193) Prec@1 80.000 (78.809) Prec@5 99.000 (98.340) +2022-11-14 13:32:04,394 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1295 (0.1195) Prec@1 77.000 (78.771) Prec@5 98.000 (98.333) +2022-11-14 13:32:04,405 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.1189) Prec@1 84.000 (78.878) Prec@5 100.000 (98.367) +2022-11-14 13:32:04,415 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1349 (0.1192) Prec@1 77.000 (78.840) Prec@5 99.000 (98.380) +2022-11-14 13:32:04,426 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1234 (0.1193) Prec@1 74.000 (78.745) Prec@5 97.000 (98.353) +2022-11-14 13:32:04,437 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1355 (0.1196) Prec@1 78.000 (78.731) Prec@5 100.000 (98.385) +2022-11-14 13:32:04,446 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.1196) Prec@1 80.000 (78.755) Prec@5 100.000 (98.415) +2022-11-14 13:32:04,458 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.1195) Prec@1 77.000 (78.722) Prec@5 98.000 (98.407) +2022-11-14 13:32:04,468 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1192) Prec@1 83.000 (78.800) Prec@5 100.000 (98.436) +2022-11-14 13:32:04,478 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1383 (0.1195) Prec@1 76.000 (78.750) Prec@5 99.000 (98.446) +2022-11-14 13:32:04,489 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.1194) Prec@1 83.000 (78.825) Prec@5 100.000 (98.474) +2022-11-14 13:32:04,498 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.1190) Prec@1 81.000 (78.862) Prec@5 96.000 (98.431) +2022-11-14 13:32:04,509 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1604 (0.1197) Prec@1 73.000 (78.763) Prec@5 99.000 (98.441) +2022-11-14 13:32:04,519 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1195) Prec@1 81.000 (78.800) Prec@5 95.000 (98.383) +2022-11-14 13:32:04,530 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1241 (0.1196) Prec@1 80.000 (78.820) Prec@5 99.000 (98.393) +2022-11-14 13:32:04,540 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.1194) Prec@1 78.000 (78.806) Prec@5 98.000 (98.387) +2022-11-14 13:32:04,550 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1121 (0.1193) Prec@1 80.000 (78.825) Prec@5 96.000 (98.349) +2022-11-14 13:32:04,560 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1192) Prec@1 76.000 (78.781) Prec@5 99.000 (98.359) +2022-11-14 13:32:04,571 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1192) Prec@1 81.000 (78.815) Prec@5 99.000 (98.369) +2022-11-14 13:32:04,580 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1301 (0.1193) Prec@1 77.000 (78.788) Prec@5 99.000 (98.379) +2022-11-14 13:32:04,591 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.1188) Prec@1 87.000 (78.910) Prec@5 99.000 (98.388) +2022-11-14 13:32:04,600 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1404 (0.1191) Prec@1 77.000 (78.882) Prec@5 97.000 (98.368) +2022-11-14 13:32:04,610 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1191) Prec@1 79.000 (78.884) Prec@5 98.000 (98.362) +2022-11-14 13:32:04,621 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1524 (0.1196) Prec@1 73.000 (78.800) Prec@5 95.000 (98.314) +2022-11-14 13:32:04,630 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.1194) Prec@1 82.000 (78.845) Prec@5 98.000 (98.310) +2022-11-14 13:32:04,641 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.1192) Prec@1 80.000 (78.861) Prec@5 100.000 (98.333) +2022-11-14 13:32:04,653 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.1190) Prec@1 81.000 (78.890) Prec@5 99.000 (98.342) +2022-11-14 13:32:04,664 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.1187) Prec@1 81.000 (78.919) Prec@5 100.000 (98.365) +2022-11-14 13:32:04,677 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1645 (0.1194) Prec@1 70.000 (78.800) Prec@5 97.000 (98.347) +2022-11-14 13:32:04,689 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.1191) Prec@1 84.000 (78.868) Prec@5 99.000 (98.355) +2022-11-14 13:32:04,701 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.1191) Prec@1 81.000 (78.896) Prec@5 98.000 (98.351) +2022-11-14 13:32:04,714 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.1189) Prec@1 83.000 (78.949) Prec@5 98.000 (98.346) +2022-11-14 13:32:04,728 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1434 (0.1192) Prec@1 76.000 (78.911) Prec@5 99.000 (98.354) +2022-11-14 13:32:04,742 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1303 (0.1193) Prec@1 78.000 (78.900) Prec@5 99.000 (98.362) +2022-11-14 13:32:04,753 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.1193) Prec@1 82.000 (78.938) Prec@5 100.000 (98.383) +2022-11-14 13:32:04,764 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.1190) Prec@1 82.000 (78.976) Prec@5 100.000 (98.402) +2022-11-14 13:32:04,774 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1190) Prec@1 77.000 (78.952) Prec@5 100.000 (98.422) +2022-11-14 13:32:04,783 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1322 (0.1191) Prec@1 78.000 (78.940) Prec@5 99.000 (98.429) +2022-11-14 13:32:04,792 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1304 (0.1193) Prec@1 76.000 (78.906) Prec@5 95.000 (98.388) +2022-11-14 13:32:04,801 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1400 (0.1195) Prec@1 75.000 (78.860) Prec@5 97.000 (98.372) +2022-11-14 13:32:04,813 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1198) Prec@1 76.000 (78.828) Prec@5 99.000 (98.379) +2022-11-14 13:32:04,823 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.1198) Prec@1 77.000 (78.807) Prec@5 100.000 (98.398) +2022-11-14 13:32:04,834 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1166 (0.1197) Prec@1 76.000 (78.775) Prec@5 97.000 (98.382) +2022-11-14 13:32:04,845 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.1197) Prec@1 82.000 (78.811) Prec@5 100.000 (98.400) +2022-11-14 13:32:04,856 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.1195) Prec@1 79.000 (78.813) Prec@5 98.000 (98.396) +2022-11-14 13:32:04,867 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.1193) Prec@1 84.000 (78.870) Prec@5 100.000 (98.413) +2022-11-14 13:32:04,877 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1321 (0.1194) Prec@1 78.000 (78.860) Prec@5 97.000 (98.398) +2022-11-14 13:32:04,887 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.1193) Prec@1 81.000 (78.883) Prec@5 99.000 (98.404) +2022-11-14 13:32:04,897 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1193) Prec@1 77.000 (78.863) Prec@5 98.000 (98.400) +2022-11-14 13:32:04,906 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1193) Prec@1 81.000 (78.885) Prec@5 97.000 (98.385) +2022-11-14 13:32:04,915 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.1191) Prec@1 82.000 (78.918) Prec@5 98.000 (98.381) +2022-11-14 13:32:04,925 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1507 (0.1194) Prec@1 75.000 (78.878) Prec@5 98.000 (98.378) +2022-11-14 13:32:04,935 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1332 (0.1195) Prec@1 78.000 (78.869) Prec@5 100.000 (98.394) +2022-11-14 13:32:04,945 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1195) Prec@1 79.000 (78.870) Prec@5 100.000 (98.410) +2022-11-14 13:32:05,015 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:32:05,340 Epoch: [55][0/500] Time 0.025 (0.025) Data 0.233 (0.233) Loss 0.0750 (0.0750) Prec@1 85.000 (85.000) Prec@5 97.000 (97.000) +2022-11-14 13:32:05,593 Epoch: [55][10/500] Time 0.018 (0.023) Data 0.002 (0.023) Loss 0.0841 (0.0795) Prec@1 87.000 (86.000) Prec@5 99.000 (98.000) +2022-11-14 13:32:05,840 Epoch: [55][20/500] Time 0.018 (0.023) Data 0.002 (0.013) Loss 0.0669 (0.0753) Prec@1 88.000 (86.667) Prec@5 99.000 (98.333) +2022-11-14 13:32:06,105 Epoch: [55][30/500] Time 0.024 (0.023) Data 0.002 (0.009) Loss 0.1056 (0.0829) Prec@1 81.000 (85.250) Prec@5 97.000 (98.000) +2022-11-14 13:32:06,545 Epoch: [55][40/500] Time 0.043 (0.027) Data 0.002 (0.008) Loss 0.0929 (0.0849) Prec@1 86.000 (85.400) Prec@5 100.000 (98.400) +2022-11-14 13:32:07,005 Epoch: [55][50/500] Time 0.042 (0.029) Data 0.002 (0.006) Loss 0.1068 (0.0885) Prec@1 82.000 (84.833) Prec@5 99.000 (98.500) +2022-11-14 13:32:07,457 Epoch: [55][60/500] Time 0.037 (0.031) Data 0.003 (0.006) Loss 0.1250 (0.0938) Prec@1 78.000 (83.857) Prec@5 98.000 (98.429) +2022-11-14 13:32:07,963 Epoch: [55][70/500] Time 0.039 (0.033) Data 0.002 (0.005) Loss 0.1162 (0.0966) Prec@1 77.000 (83.000) Prec@5 98.000 (98.375) +2022-11-14 13:32:08,443 Epoch: [55][80/500] Time 0.064 (0.034) Data 0.002 (0.005) Loss 0.1112 (0.0982) Prec@1 82.000 (82.889) Prec@5 99.000 (98.444) +2022-11-14 13:32:08,903 Epoch: [55][90/500] Time 0.043 (0.035) Data 0.002 (0.005) Loss 0.0882 (0.0972) Prec@1 82.000 (82.800) Prec@5 99.000 (98.500) +2022-11-14 13:32:09,355 Epoch: [55][100/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0934 (0.0969) Prec@1 83.000 (82.818) Prec@5 99.000 (98.545) +2022-11-14 13:32:09,810 Epoch: [55][110/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0833 (0.0957) Prec@1 87.000 (83.167) Prec@5 100.000 (98.667) +2022-11-14 13:32:10,268 Epoch: [55][120/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.0666 (0.0935) Prec@1 88.000 (83.538) Prec@5 100.000 (98.769) +2022-11-14 13:32:10,728 Epoch: [55][130/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.1121 (0.0948) Prec@1 78.000 (83.143) Prec@5 96.000 (98.571) +2022-11-14 13:32:11,183 Epoch: [55][140/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0961 (0.0949) Prec@1 81.000 (83.000) Prec@5 97.000 (98.467) +2022-11-14 13:32:11,643 Epoch: [55][150/500] Time 0.041 (0.037) Data 0.002 (0.004) Loss 0.1041 (0.0955) Prec@1 78.000 (82.688) Prec@5 99.000 (98.500) +2022-11-14 13:32:12,106 Epoch: [55][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0856 (0.0949) Prec@1 86.000 (82.882) Prec@5 100.000 (98.588) +2022-11-14 13:32:12,569 Epoch: [55][170/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0918 (0.0947) Prec@1 84.000 (82.944) Prec@5 98.000 (98.556) +2022-11-14 13:32:13,034 Epoch: [55][180/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.1017 (0.0951) Prec@1 81.000 (82.842) Prec@5 99.000 (98.579) +2022-11-14 13:32:13,492 Epoch: [55][190/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0899 (0.0948) Prec@1 85.000 (82.950) Prec@5 100.000 (98.650) +2022-11-14 13:32:13,952 Epoch: [55][200/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0827 (0.0942) Prec@1 87.000 (83.143) Prec@5 99.000 (98.667) +2022-11-14 13:32:14,411 Epoch: [55][210/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0714 (0.0932) Prec@1 87.000 (83.318) Prec@5 100.000 (98.727) +2022-11-14 13:32:14,879 Epoch: [55][220/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.1215 (0.0944) Prec@1 77.000 (83.043) Prec@5 98.000 (98.696) +2022-11-14 13:32:15,336 Epoch: [55][230/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0986 (0.0946) Prec@1 84.000 (83.083) Prec@5 100.000 (98.750) +2022-11-14 13:32:15,805 Epoch: [55][240/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1031 (0.0950) Prec@1 82.000 (83.040) Prec@5 97.000 (98.680) +2022-11-14 13:32:16,276 Epoch: [55][250/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.1049 (0.0953) Prec@1 80.000 (82.923) Prec@5 98.000 (98.654) +2022-11-14 13:32:16,743 Epoch: [55][260/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0991 (0.0955) Prec@1 80.000 (82.815) Prec@5 99.000 (98.667) +2022-11-14 13:32:17,186 Epoch: [55][270/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1394 (0.0970) Prec@1 75.000 (82.536) Prec@5 99.000 (98.679) +2022-11-14 13:32:17,635 Epoch: [55][280/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1092 (0.0975) Prec@1 81.000 (82.483) Prec@5 98.000 (98.655) +2022-11-14 13:32:18,090 Epoch: [55][290/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0608 (0.0962) Prec@1 89.000 (82.700) Prec@5 99.000 (98.667) +2022-11-14 13:32:18,542 Epoch: [55][300/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0816 (0.0958) Prec@1 86.000 (82.806) Prec@5 98.000 (98.645) +2022-11-14 13:32:18,995 Epoch: [55][310/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.1263 (0.0967) Prec@1 81.000 (82.750) Prec@5 99.000 (98.656) +2022-11-14 13:32:19,441 Epoch: [55][320/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0991 (0.0968) Prec@1 84.000 (82.788) Prec@5 99.000 (98.667) +2022-11-14 13:32:19,885 Epoch: [55][330/500] Time 0.042 (0.039) Data 0.003 (0.003) Loss 0.0841 (0.0964) Prec@1 84.000 (82.824) Prec@5 100.000 (98.706) +2022-11-14 13:32:20,339 Epoch: [55][340/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1262 (0.0973) Prec@1 74.000 (82.571) Prec@5 99.000 (98.714) +2022-11-14 13:32:20,803 Epoch: [55][350/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.1111 (0.0977) Prec@1 80.000 (82.500) Prec@5 100.000 (98.750) +2022-11-14 13:32:21,257 Epoch: [55][360/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1037 (0.0978) Prec@1 85.000 (82.568) Prec@5 98.000 (98.730) +2022-11-14 13:32:21,700 Epoch: [55][370/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0853 (0.0975) Prec@1 85.000 (82.632) Prec@5 99.000 (98.737) +2022-11-14 13:32:22,165 Epoch: [55][380/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.1002 (0.0976) Prec@1 83.000 (82.641) Prec@5 100.000 (98.769) +2022-11-14 13:32:22,626 Epoch: [55][390/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.0932 (0.0975) Prec@1 85.000 (82.700) Prec@5 99.000 (98.775) +2022-11-14 13:32:23,074 Epoch: [55][400/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0890 (0.0972) Prec@1 85.000 (82.756) Prec@5 98.000 (98.756) +2022-11-14 13:32:23,521 Epoch: [55][410/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1103 (0.0976) Prec@1 83.000 (82.762) Prec@5 99.000 (98.762) +2022-11-14 13:32:23,957 Epoch: [55][420/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.1040 (0.0977) Prec@1 81.000 (82.721) Prec@5 99.000 (98.767) +2022-11-14 13:32:24,403 Epoch: [55][430/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.1054 (0.0979) Prec@1 82.000 (82.705) Prec@5 99.000 (98.773) +2022-11-14 13:32:24,855 Epoch: [55][440/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0885 (0.0977) Prec@1 85.000 (82.756) Prec@5 97.000 (98.733) +2022-11-14 13:32:25,302 Epoch: [55][450/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0933 (0.0976) Prec@1 80.000 (82.696) Prec@5 99.000 (98.739) +2022-11-14 13:32:25,758 Epoch: [55][460/500] Time 0.040 (0.039) Data 0.002 (0.002) Loss 0.0776 (0.0972) Prec@1 89.000 (82.830) Prec@5 100.000 (98.766) +2022-11-14 13:32:26,214 Epoch: [55][470/500] Time 0.047 (0.039) Data 0.002 (0.002) Loss 0.1015 (0.0972) Prec@1 79.000 (82.750) Prec@5 99.000 (98.771) +2022-11-14 13:32:26,657 Epoch: [55][480/500] Time 0.038 (0.039) Data 0.002 (0.002) Loss 0.0948 (0.0972) Prec@1 85.000 (82.796) Prec@5 99.000 (98.776) +2022-11-14 13:32:27,126 Epoch: [55][490/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.1543 (0.0983) Prec@1 75.000 (82.640) Prec@5 98.000 (98.760) +2022-11-14 13:32:27,537 Epoch: [55][499/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.1094 (0.0986) Prec@1 82.000 (82.627) Prec@5 97.000 (98.725) +2022-11-14 13:32:27,832 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.1069 (0.1069) Prec@1 81.000 (81.000) Prec@5 99.000 (99.000) +2022-11-14 13:32:27,843 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0923 (0.0996) Prec@1 88.000 (84.500) Prec@5 99.000 (99.000) +2022-11-14 13:32:27,855 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1063 (0.1018) Prec@1 81.000 (83.333) Prec@5 98.000 (98.667) +2022-11-14 13:32:27,867 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1149 (0.1051) Prec@1 80.000 (82.500) Prec@5 99.000 (98.750) +2022-11-14 13:32:27,875 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1150 (0.1071) Prec@1 81.000 (82.200) Prec@5 98.000 (98.600) +2022-11-14 13:32:27,886 Test: [5/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0624 (0.0996) Prec@1 89.000 (83.333) Prec@5 99.000 (98.667) +2022-11-14 13:32:27,897 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1124 (0.1014) Prec@1 80.000 (82.857) Prec@5 100.000 (98.857) +2022-11-14 13:32:27,906 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1083 (0.1023) Prec@1 81.000 (82.625) Prec@5 98.000 (98.750) +2022-11-14 13:32:27,915 Test: [8/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1380 (0.1063) Prec@1 77.000 (82.000) Prec@5 96.000 (98.444) +2022-11-14 13:32:27,927 Test: [9/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.1026) Prec@1 87.000 (82.500) Prec@5 99.000 (98.500) +2022-11-14 13:32:27,939 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0849 (0.1009) Prec@1 82.000 (82.455) Prec@5 99.000 (98.545) +2022-11-14 13:32:27,950 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1219 (0.1027) Prec@1 79.000 (82.167) Prec@5 99.000 (98.583) +2022-11-14 13:32:27,959 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.1012) Prec@1 86.000 (82.462) Prec@5 99.000 (98.615) +2022-11-14 13:32:27,971 Test: [13/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0864 (0.1002) Prec@1 84.000 (82.571) Prec@5 99.000 (98.643) +2022-11-14 13:32:27,983 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0996 (0.1001) Prec@1 81.000 (82.467) Prec@5 98.000 (98.600) +2022-11-14 13:32:27,993 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.1006) Prec@1 82.000 (82.438) Prec@5 96.000 (98.438) +2022-11-14 13:32:28,001 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.1005) Prec@1 82.000 (82.412) Prec@5 97.000 (98.353) +2022-11-14 13:32:28,013 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.1007) Prec@1 83.000 (82.444) Prec@5 100.000 (98.444) +2022-11-14 13:32:28,026 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1243 (0.1019) Prec@1 78.000 (82.211) Prec@5 98.000 (98.421) +2022-11-14 13:32:28,038 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1382 (0.1037) Prec@1 78.000 (82.000) Prec@5 99.000 (98.450) +2022-11-14 13:32:28,047 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.1037) Prec@1 81.000 (81.952) Prec@5 99.000 (98.476) +2022-11-14 13:32:28,059 Test: [21/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1237 (0.1046) Prec@1 79.000 (81.818) Prec@5 100.000 (98.545) +2022-11-14 13:32:28,071 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.1053) Prec@1 76.000 (81.565) Prec@5 100.000 (98.609) +2022-11-14 13:32:28,080 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.1049) Prec@1 82.000 (81.583) Prec@5 99.000 (98.625) +2022-11-14 13:32:28,090 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.1049) Prec@1 83.000 (81.640) Prec@5 100.000 (98.680) +2022-11-14 13:32:28,100 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1244 (0.1056) Prec@1 78.000 (81.500) Prec@5 96.000 (98.577) +2022-11-14 13:32:28,109 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.1046) Prec@1 88.000 (81.741) Prec@5 99.000 (98.593) +2022-11-14 13:32:28,119 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.1046) Prec@1 81.000 (81.714) Prec@5 99.000 (98.607) +2022-11-14 13:32:28,128 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.1046) Prec@1 82.000 (81.724) Prec@5 97.000 (98.552) +2022-11-14 13:32:28,137 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1170 (0.1050) Prec@1 78.000 (81.600) Prec@5 97.000 (98.500) +2022-11-14 13:32:28,146 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.1050) Prec@1 80.000 (81.548) Prec@5 98.000 (98.484) +2022-11-14 13:32:28,155 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.1044) Prec@1 84.000 (81.625) Prec@5 98.000 (98.469) +2022-11-14 13:32:28,164 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.1048) Prec@1 78.000 (81.515) Prec@5 96.000 (98.394) +2022-11-14 13:32:28,174 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1380 (0.1058) Prec@1 78.000 (81.412) Prec@5 97.000 (98.353) +2022-11-14 13:32:28,183 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.1054) Prec@1 85.000 (81.514) Prec@5 98.000 (98.343) +2022-11-14 13:32:28,193 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.1054) Prec@1 81.000 (81.500) Prec@5 99.000 (98.361) +2022-11-14 13:32:28,204 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1160 (0.1056) Prec@1 81.000 (81.486) Prec@5 96.000 (98.297) +2022-11-14 13:32:28,214 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.1058) Prec@1 83.000 (81.526) Prec@5 99.000 (98.316) +2022-11-14 13:32:28,224 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.1053) Prec@1 87.000 (81.667) Prec@5 99.000 (98.333) +2022-11-14 13:32:28,234 Test: [39/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.1053) Prec@1 82.000 (81.675) Prec@5 99.000 (98.350) +2022-11-14 13:32:28,244 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1081 (0.1053) Prec@1 83.000 (81.707) Prec@5 99.000 (98.366) +2022-11-14 13:32:28,253 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.1052) Prec@1 85.000 (81.786) Prec@5 98.000 (98.357) +2022-11-14 13:32:28,264 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.1045) Prec@1 89.000 (81.953) Prec@5 98.000 (98.349) +2022-11-14 13:32:28,275 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.1045) Prec@1 80.000 (81.909) Prec@5 97.000 (98.318) +2022-11-14 13:32:28,286 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.1042) Prec@1 85.000 (81.978) Prec@5 100.000 (98.356) +2022-11-14 13:32:28,296 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.1042) Prec@1 79.000 (81.913) Prec@5 97.000 (98.326) +2022-11-14 13:32:28,306 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.1040) Prec@1 83.000 (81.936) Prec@5 100.000 (98.362) +2022-11-14 13:32:28,315 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.1039) Prec@1 83.000 (81.958) Prec@5 98.000 (98.354) +2022-11-14 13:32:28,324 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.1035) Prec@1 85.000 (82.020) Prec@5 100.000 (98.388) +2022-11-14 13:32:28,334 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1044) Prec@1 75.000 (81.880) Prec@5 99.000 (98.400) +2022-11-14 13:32:28,344 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.1040) Prec@1 83.000 (81.902) Prec@5 99.000 (98.412) +2022-11-14 13:32:28,354 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1249 (0.1044) Prec@1 79.000 (81.846) Prec@5 94.000 (98.327) +2022-11-14 13:32:28,364 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1046) Prec@1 78.000 (81.774) Prec@5 99.000 (98.340) +2022-11-14 13:32:28,373 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.1041) Prec@1 88.000 (81.889) Prec@5 97.000 (98.315) +2022-11-14 13:32:28,384 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.1042) Prec@1 82.000 (81.891) Prec@5 100.000 (98.345) +2022-11-14 13:32:28,394 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1043) Prec@1 82.000 (81.893) Prec@5 97.000 (98.321) +2022-11-14 13:32:28,405 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.1042) Prec@1 83.000 (81.912) Prec@5 98.000 (98.316) +2022-11-14 13:32:28,416 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.1043) Prec@1 79.000 (81.862) Prec@5 98.000 (98.310) +2022-11-14 13:32:28,426 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1048) Prec@1 75.000 (81.746) Prec@5 99.000 (98.322) +2022-11-14 13:32:28,435 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.1048) Prec@1 84.000 (81.783) Prec@5 98.000 (98.317) +2022-11-14 13:32:28,445 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.1049) Prec@1 78.000 (81.721) Prec@5 99.000 (98.328) +2022-11-14 13:32:28,455 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.1048) Prec@1 87.000 (81.806) Prec@5 98.000 (98.323) +2022-11-14 13:32:28,467 Test: [62/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.1045) Prec@1 86.000 (81.873) Prec@5 99.000 (98.333) +2022-11-14 13:32:28,478 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.1042) Prec@1 85.000 (81.922) Prec@5 100.000 (98.359) +2022-11-14 13:32:28,488 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1043) Prec@1 81.000 (81.908) Prec@5 97.000 (98.338) +2022-11-14 13:32:28,497 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.1044) Prec@1 81.000 (81.894) Prec@5 97.000 (98.318) +2022-11-14 13:32:28,509 Test: [66/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.1039) Prec@1 90.000 (82.015) Prec@5 100.000 (98.343) +2022-11-14 13:32:28,520 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.1039) Prec@1 81.000 (82.000) Prec@5 98.000 (98.338) +2022-11-14 13:32:28,530 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1038) Prec@1 84.000 (82.029) Prec@5 100.000 (98.362) +2022-11-14 13:32:28,539 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.1039) Prec@1 81.000 (82.014) Prec@5 97.000 (98.343) +2022-11-14 13:32:28,550 Test: [70/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.1040) Prec@1 82.000 (82.014) Prec@5 98.000 (98.338) +2022-11-14 13:32:28,561 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.1038) Prec@1 80.000 (81.986) Prec@5 100.000 (98.361) +2022-11-14 13:32:28,571 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.1035) Prec@1 87.000 (82.055) Prec@5 100.000 (98.384) +2022-11-14 13:32:28,580 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.1032) Prec@1 87.000 (82.122) Prec@5 100.000 (98.405) +2022-11-14 13:32:28,591 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1245 (0.1034) Prec@1 78.000 (82.067) Prec@5 98.000 (98.400) +2022-11-14 13:32:28,602 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1034) Prec@1 84.000 (82.092) Prec@5 98.000 (98.395) +2022-11-14 13:32:28,613 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.1034) Prec@1 80.000 (82.065) Prec@5 99.000 (98.403) +2022-11-14 13:32:28,624 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.1030) Prec@1 89.000 (82.154) Prec@5 99.000 (98.410) +2022-11-14 13:32:28,636 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.1031) Prec@1 80.000 (82.127) Prec@5 99.000 (98.418) +2022-11-14 13:32:28,646 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1032) Prec@1 75.000 (82.037) Prec@5 99.000 (98.425) +2022-11-14 13:32:28,655 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.1032) Prec@1 86.000 (82.086) Prec@5 97.000 (98.407) +2022-11-14 13:32:28,665 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.1032) Prec@1 82.000 (82.085) Prec@5 98.000 (98.402) +2022-11-14 13:32:28,676 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.1032) Prec@1 82.000 (82.084) Prec@5 96.000 (98.373) +2022-11-14 13:32:28,687 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.1032) Prec@1 80.000 (82.060) Prec@5 99.000 (98.381) +2022-11-14 13:32:28,696 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.1034) Prec@1 81.000 (82.047) Prec@5 98.000 (98.376) +2022-11-14 13:32:28,705 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1267 (0.1037) Prec@1 78.000 (82.000) Prec@5 99.000 (98.384) +2022-11-14 13:32:28,717 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.1034) Prec@1 86.000 (82.046) Prec@5 99.000 (98.391) +2022-11-14 13:32:28,726 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.1033) Prec@1 85.000 (82.080) Prec@5 98.000 (98.386) +2022-11-14 13:32:28,737 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.1032) Prec@1 84.000 (82.101) Prec@5 96.000 (98.360) +2022-11-14 13:32:28,748 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.1032) Prec@1 85.000 (82.133) Prec@5 100.000 (98.378) +2022-11-14 13:32:28,758 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.1029) Prec@1 88.000 (82.198) Prec@5 100.000 (98.396) +2022-11-14 13:32:28,767 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.1026) Prec@1 89.000 (82.272) Prec@5 99.000 (98.402) +2022-11-14 13:32:28,776 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.1027) Prec@1 81.000 (82.258) Prec@5 99.000 (98.409) +2022-11-14 13:32:28,785 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.1028) Prec@1 80.000 (82.234) Prec@5 98.000 (98.404) +2022-11-14 13:32:28,794 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.1029) Prec@1 81.000 (82.221) Prec@5 99.000 (98.411) +2022-11-14 13:32:28,803 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.1027) Prec@1 84.000 (82.240) Prec@5 99.000 (98.417) +2022-11-14 13:32:28,812 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.1026) Prec@1 84.000 (82.258) Prec@5 100.000 (98.433) +2022-11-14 13:32:28,821 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1155 (0.1027) Prec@1 82.000 (82.255) Prec@5 99.000 (98.439) +2022-11-14 13:32:28,830 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1168 (0.1028) Prec@1 82.000 (82.253) Prec@5 96.000 (98.414) +2022-11-14 13:32:28,840 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.1028) Prec@1 78.000 (82.210) Prec@5 99.000 (98.420) +2022-11-14 13:32:28,894 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:32:29,192 Epoch: [56][0/500] Time 0.022 (0.022) Data 0.220 (0.220) Loss 0.0776 (0.0776) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:32:29,404 Epoch: [56][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0955 (0.0866) Prec@1 82.000 (85.500) Prec@5 100.000 (99.500) +2022-11-14 13:32:29,610 Epoch: [56][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0850 (0.0860) Prec@1 89.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 13:32:29,830 Epoch: [56][30/500] Time 0.016 (0.019) Data 0.002 (0.009) Loss 0.1059 (0.0910) Prec@1 81.000 (85.250) Prec@5 99.000 (99.500) +2022-11-14 13:32:30,207 Epoch: [56][40/500] Time 0.041 (0.022) Data 0.002 (0.007) Loss 0.1361 (0.1000) Prec@1 72.000 (82.600) Prec@5 98.000 (99.200) +2022-11-14 13:32:30,644 Epoch: [56][50/500] Time 0.034 (0.026) Data 0.002 (0.006) Loss 0.1056 (0.1010) Prec@1 81.000 (82.333) Prec@5 97.000 (98.833) +2022-11-14 13:32:31,067 Epoch: [56][60/500] Time 0.039 (0.028) Data 0.002 (0.005) Loss 0.1143 (0.1029) Prec@1 79.000 (81.857) Prec@5 98.000 (98.714) +2022-11-14 13:32:31,478 Epoch: [56][70/500] Time 0.038 (0.029) Data 0.002 (0.005) Loss 0.0916 (0.1014) Prec@1 88.000 (82.625) Prec@5 99.000 (98.750) +2022-11-14 13:32:31,889 Epoch: [56][80/500] Time 0.037 (0.030) Data 0.002 (0.005) Loss 0.0945 (0.1007) Prec@1 83.000 (82.667) Prec@5 98.000 (98.667) +2022-11-14 13:32:32,306 Epoch: [56][90/500] Time 0.046 (0.031) Data 0.002 (0.004) Loss 0.1177 (0.1024) Prec@1 80.000 (82.400) Prec@5 100.000 (98.800) +2022-11-14 13:32:32,718 Epoch: [56][100/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.1185 (0.1038) Prec@1 84.000 (82.545) Prec@5 98.000 (98.727) +2022-11-14 13:32:33,156 Epoch: [56][110/500] Time 0.038 (0.032) Data 0.003 (0.004) Loss 0.0709 (0.1011) Prec@1 90.000 (83.167) Prec@5 99.000 (98.750) +2022-11-14 13:32:33,571 Epoch: [56][120/500] Time 0.036 (0.032) Data 0.002 (0.004) Loss 0.1021 (0.1012) Prec@1 84.000 (83.231) Prec@5 98.000 (98.692) +2022-11-14 13:32:33,977 Epoch: [56][130/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.1017 (0.1012) Prec@1 82.000 (83.143) Prec@5 100.000 (98.786) +2022-11-14 13:32:34,390 Epoch: [56][140/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0944 (0.1008) Prec@1 84.000 (83.200) Prec@5 98.000 (98.733) +2022-11-14 13:32:34,798 Epoch: [56][150/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1039 (0.1009) Prec@1 82.000 (83.125) Prec@5 98.000 (98.688) +2022-11-14 13:32:35,205 Epoch: [56][160/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0947 (0.1006) Prec@1 83.000 (83.118) Prec@5 99.000 (98.706) +2022-11-14 13:32:35,617 Epoch: [56][170/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1067 (0.1009) Prec@1 83.000 (83.111) Prec@5 98.000 (98.667) +2022-11-14 13:32:36,022 Epoch: [56][180/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1089 (0.1013) Prec@1 82.000 (83.053) Prec@5 98.000 (98.632) +2022-11-14 13:32:36,430 Epoch: [56][190/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0887 (0.1007) Prec@1 82.000 (83.000) Prec@5 100.000 (98.700) +2022-11-14 13:32:36,834 Epoch: [56][200/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0875 (0.1001) Prec@1 85.000 (83.095) Prec@5 99.000 (98.714) +2022-11-14 13:32:37,242 Epoch: [56][210/500] Time 0.039 (0.034) Data 0.001 (0.003) Loss 0.1197 (0.1010) Prec@1 77.000 (82.818) Prec@5 99.000 (98.727) +2022-11-14 13:32:37,658 Epoch: [56][220/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0797 (0.1000) Prec@1 88.000 (83.043) Prec@5 99.000 (98.739) +2022-11-14 13:32:38,060 Epoch: [56][230/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.1013 (0.1001) Prec@1 83.000 (83.042) Prec@5 98.000 (98.708) +2022-11-14 13:32:38,471 Epoch: [56][240/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.1141 (0.1007) Prec@1 81.000 (82.960) Prec@5 95.000 (98.560) +2022-11-14 13:32:38,890 Epoch: [56][250/500] Time 0.047 (0.034) Data 0.002 (0.003) Loss 0.0950 (0.1004) Prec@1 84.000 (83.000) Prec@5 98.000 (98.538) +2022-11-14 13:32:39,319 Epoch: [56][260/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1037 (0.1006) Prec@1 81.000 (82.926) Prec@5 100.000 (98.593) +2022-11-14 13:32:39,729 Epoch: [56][270/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1172 (0.1012) Prec@1 78.000 (82.750) Prec@5 99.000 (98.607) +2022-11-14 13:32:40,146 Epoch: [56][280/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1042 (0.1013) Prec@1 82.000 (82.724) Prec@5 99.000 (98.621) +2022-11-14 13:32:40,556 Epoch: [56][290/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0957 (0.1011) Prec@1 82.000 (82.700) Prec@5 99.000 (98.633) +2022-11-14 13:32:40,976 Epoch: [56][300/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.1120 (0.1014) Prec@1 79.000 (82.581) Prec@5 98.000 (98.613) +2022-11-14 13:32:41,388 Epoch: [56][310/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0969 (0.1013) Prec@1 84.000 (82.625) Prec@5 97.000 (98.562) +2022-11-14 13:32:41,797 Epoch: [56][320/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0765 (0.1005) Prec@1 87.000 (82.758) Prec@5 100.000 (98.606) +2022-11-14 13:32:42,218 Epoch: [56][330/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0788 (0.0999) Prec@1 86.000 (82.853) Prec@5 99.000 (98.618) +2022-11-14 13:32:42,625 Epoch: [56][340/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0953 (0.0998) Prec@1 84.000 (82.886) Prec@5 99.000 (98.629) +2022-11-14 13:32:43,030 Epoch: [56][350/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0970 (0.0997) Prec@1 82.000 (82.861) Prec@5 100.000 (98.667) +2022-11-14 13:32:43,435 Epoch: [56][360/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1008 (0.0997) Prec@1 81.000 (82.811) Prec@5 98.000 (98.649) +2022-11-14 13:32:43,844 Epoch: [56][370/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0914 (0.0995) Prec@1 84.000 (82.842) Prec@5 97.000 (98.605) +2022-11-14 13:32:44,254 Epoch: [56][380/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0803 (0.0990) Prec@1 88.000 (82.974) Prec@5 100.000 (98.641) +2022-11-14 13:32:44,659 Epoch: [56][390/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1008 (0.0991) Prec@1 84.000 (83.000) Prec@5 98.000 (98.625) +2022-11-14 13:32:45,075 Epoch: [56][400/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0996 (0.0991) Prec@1 82.000 (82.976) Prec@5 98.000 (98.610) +2022-11-14 13:32:45,494 Epoch: [56][410/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.0850 (0.0987) Prec@1 85.000 (83.024) Prec@5 99.000 (98.619) +2022-11-14 13:32:45,906 Epoch: [56][420/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0966 (0.0987) Prec@1 84.000 (83.047) Prec@5 97.000 (98.581) +2022-11-14 13:32:46,300 Epoch: [56][430/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.1061 (0.0989) Prec@1 82.000 (83.023) Prec@5 98.000 (98.568) +2022-11-14 13:32:46,713 Epoch: [56][440/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0909 (0.0987) Prec@1 83.000 (83.022) Prec@5 100.000 (98.600) +2022-11-14 13:32:47,136 Epoch: [56][450/500] Time 0.047 (0.035) Data 0.002 (0.002) Loss 0.1136 (0.0990) Prec@1 80.000 (82.957) Prec@5 96.000 (98.543) +2022-11-14 13:32:47,538 Epoch: [56][460/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0999 (0.0990) Prec@1 82.000 (82.936) Prec@5 99.000 (98.553) +2022-11-14 13:32:47,948 Epoch: [56][470/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1048 (0.0991) Prec@1 83.000 (82.938) Prec@5 99.000 (98.562) +2022-11-14 13:32:48,358 Epoch: [56][480/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0988 (0.0991) Prec@1 84.000 (82.959) Prec@5 98.000 (98.551) +2022-11-14 13:32:48,764 Epoch: [56][490/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.1268 (0.0997) Prec@1 79.000 (82.880) Prec@5 97.000 (98.520) +2022-11-14 13:32:49,132 Epoch: [56][499/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0986 (0.0997) Prec@1 82.000 (82.863) Prec@5 97.000 (98.490) +2022-11-14 13:32:49,409 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1046 (0.1046) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:32:49,420 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0957 (0.1002) Prec@1 80.000 (81.500) Prec@5 98.000 (98.500) +2022-11-14 13:32:49,428 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.1037) Prec@1 81.000 (81.333) Prec@5 99.000 (98.667) +2022-11-14 13:32:49,441 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.1075) Prec@1 81.000 (81.250) Prec@5 100.000 (99.000) +2022-11-14 13:32:49,448 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1387 (0.1137) Prec@1 78.000 (80.600) Prec@5 98.000 (98.800) +2022-11-14 13:32:49,456 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.1029) Prec@1 92.000 (82.500) Prec@5 100.000 (99.000) +2022-11-14 13:32:49,463 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.1001) Prec@1 85.000 (82.857) Prec@5 100.000 (99.143) +2022-11-14 13:32:49,472 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.1028) Prec@1 79.000 (82.375) Prec@5 98.000 (99.000) +2022-11-14 13:32:49,480 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.1043) Prec@1 82.000 (82.333) Prec@5 97.000 (98.778) +2022-11-14 13:32:49,489 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.1021) Prec@1 86.000 (82.700) Prec@5 100.000 (98.900) +2022-11-14 13:32:49,499 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.1006) Prec@1 84.000 (82.818) Prec@5 100.000 (99.000) +2022-11-14 13:32:49,508 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.1007) Prec@1 85.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:32:49,517 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1182 (0.1021) Prec@1 81.000 (82.846) Prec@5 99.000 (99.000) +2022-11-14 13:32:49,527 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.1011) Prec@1 84.000 (82.929) Prec@5 98.000 (98.929) +2022-11-14 13:32:49,536 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.1010) Prec@1 81.000 (82.800) Prec@5 99.000 (98.933) +2022-11-14 13:32:49,545 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1361 (0.1032) Prec@1 75.000 (82.312) Prec@5 97.000 (98.812) +2022-11-14 13:32:49,553 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.1021) Prec@1 88.000 (82.647) Prec@5 99.000 (98.824) +2022-11-14 13:32:49,563 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1144 (0.1028) Prec@1 80.000 (82.500) Prec@5 98.000 (98.778) +2022-11-14 13:32:49,571 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1025) Prec@1 83.000 (82.526) Prec@5 99.000 (98.789) +2022-11-14 13:32:49,580 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1249 (0.1037) Prec@1 78.000 (82.300) Prec@5 98.000 (98.750) +2022-11-14 13:32:49,590 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.1039) Prec@1 81.000 (82.238) Prec@5 98.000 (98.714) +2022-11-14 13:32:49,601 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.1039) Prec@1 83.000 (82.273) Prec@5 98.000 (98.682) +2022-11-14 13:32:49,611 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1289 (0.1050) Prec@1 76.000 (82.000) Prec@5 99.000 (98.696) +2022-11-14 13:32:49,621 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.1049) Prec@1 80.000 (81.917) Prec@5 99.000 (98.708) +2022-11-14 13:32:49,631 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1205 (0.1055) Prec@1 82.000 (81.920) Prec@5 99.000 (98.720) +2022-11-14 13:32:49,642 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1380 (0.1068) Prec@1 77.000 (81.731) Prec@5 98.000 (98.692) +2022-11-14 13:32:49,652 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.1060) Prec@1 86.000 (81.889) Prec@5 100.000 (98.741) +2022-11-14 13:32:49,661 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1057) Prec@1 80.000 (81.821) Prec@5 98.000 (98.714) +2022-11-14 13:32:49,671 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.1060) Prec@1 79.000 (81.724) Prec@5 95.000 (98.586) +2022-11-14 13:32:49,680 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1064) Prec@1 84.000 (81.800) Prec@5 97.000 (98.533) +2022-11-14 13:32:49,690 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1066) Prec@1 81.000 (81.774) Prec@5 99.000 (98.548) +2022-11-14 13:32:49,699 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.1064) Prec@1 82.000 (81.781) Prec@5 100.000 (98.594) +2022-11-14 13:32:49,709 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1063) Prec@1 79.000 (81.697) Prec@5 97.000 (98.545) +2022-11-14 13:32:49,718 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1446 (0.1075) Prec@1 76.000 (81.529) Prec@5 98.000 (98.529) +2022-11-14 13:32:49,726 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.1067) Prec@1 88.000 (81.714) Prec@5 100.000 (98.571) +2022-11-14 13:32:49,736 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.1067) Prec@1 81.000 (81.694) Prec@5 99.000 (98.583) +2022-11-14 13:32:49,744 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1068) Prec@1 79.000 (81.622) Prec@5 98.000 (98.568) +2022-11-14 13:32:49,753 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1072) Prec@1 79.000 (81.553) Prec@5 97.000 (98.526) +2022-11-14 13:32:49,761 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.1073) Prec@1 83.000 (81.590) Prec@5 97.000 (98.487) +2022-11-14 13:32:49,769 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.1070) Prec@1 83.000 (81.625) Prec@5 99.000 (98.500) +2022-11-14 13:32:49,778 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1280 (0.1075) Prec@1 78.000 (81.537) Prec@5 97.000 (98.463) +2022-11-14 13:32:49,787 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.1073) Prec@1 84.000 (81.595) Prec@5 96.000 (98.405) +2022-11-14 13:32:49,796 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.1069) Prec@1 85.000 (81.674) Prec@5 98.000 (98.395) +2022-11-14 13:32:49,806 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.1062) Prec@1 84.000 (81.727) Prec@5 100.000 (98.432) +2022-11-14 13:32:49,814 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.1062) Prec@1 83.000 (81.756) Prec@5 100.000 (98.467) +2022-11-14 13:32:49,822 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.1062) Prec@1 83.000 (81.783) Prec@5 99.000 (98.478) +2022-11-14 13:32:49,831 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.1067) Prec@1 79.000 (81.723) Prec@5 99.000 (98.489) +2022-11-14 13:32:49,842 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.1065) Prec@1 88.000 (81.854) Prec@5 100.000 (98.521) +2022-11-14 13:32:49,851 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.1063) Prec@1 83.000 (81.878) Prec@5 100.000 (98.551) +2022-11-14 13:32:49,861 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1069) Prec@1 69.000 (81.620) Prec@5 99.000 (98.560) +2022-11-14 13:32:49,869 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.1067) Prec@1 83.000 (81.647) Prec@5 100.000 (98.588) +2022-11-14 13:32:49,878 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1270 (0.1071) Prec@1 75.000 (81.519) Prec@5 95.000 (98.519) +2022-11-14 13:32:49,887 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1251 (0.1074) Prec@1 80.000 (81.491) Prec@5 99.000 (98.528) +2022-11-14 13:32:49,896 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.1072) Prec@1 83.000 (81.519) Prec@5 99.000 (98.537) +2022-11-14 13:32:49,904 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.1073) Prec@1 80.000 (81.491) Prec@5 100.000 (98.564) +2022-11-14 13:32:49,913 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.1073) Prec@1 81.000 (81.482) Prec@5 97.000 (98.536) +2022-11-14 13:32:49,922 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.1074) Prec@1 81.000 (81.474) Prec@5 100.000 (98.561) +2022-11-14 13:32:49,932 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.1070) Prec@1 85.000 (81.534) Prec@5 99.000 (98.569) +2022-11-14 13:32:49,941 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1475 (0.1077) Prec@1 73.000 (81.390) Prec@5 98.000 (98.559) +2022-11-14 13:32:49,950 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.1076) Prec@1 79.000 (81.350) Prec@5 99.000 (98.567) +2022-11-14 13:32:49,960 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.1073) Prec@1 86.000 (81.426) Prec@5 99.000 (98.574) +2022-11-14 13:32:49,968 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.1072) Prec@1 82.000 (81.435) Prec@5 99.000 (98.581) +2022-11-14 13:32:49,977 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.1070) Prec@1 85.000 (81.492) Prec@5 98.000 (98.571) +2022-11-14 13:32:49,987 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.1069) Prec@1 80.000 (81.469) Prec@5 99.000 (98.578) +2022-11-14 13:32:49,996 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1072) Prec@1 77.000 (81.400) Prec@5 99.000 (98.585) +2022-11-14 13:32:50,006 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1075 (0.1072) Prec@1 82.000 (81.409) Prec@5 98.000 (98.576) +2022-11-14 13:32:50,015 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.1070) Prec@1 83.000 (81.433) Prec@5 100.000 (98.597) +2022-11-14 13:32:50,024 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1158 (0.1071) Prec@1 82.000 (81.441) Prec@5 96.000 (98.559) +2022-11-14 13:32:50,033 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.1068) Prec@1 84.000 (81.478) Prec@5 98.000 (98.551) +2022-11-14 13:32:50,042 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1239 (0.1071) Prec@1 80.000 (81.457) Prec@5 98.000 (98.543) +2022-11-14 13:32:50,050 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1262 (0.1074) Prec@1 79.000 (81.423) Prec@5 99.000 (98.549) +2022-11-14 13:32:50,058 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.1074) Prec@1 82.000 (81.431) Prec@5 98.000 (98.542) +2022-11-14 13:32:50,067 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.1070) Prec@1 88.000 (81.521) Prec@5 100.000 (98.562) +2022-11-14 13:32:50,076 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.1065) Prec@1 89.000 (81.622) Prec@5 99.000 (98.568) +2022-11-14 13:32:50,085 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1219 (0.1067) Prec@1 77.000 (81.560) Prec@5 99.000 (98.573) +2022-11-14 13:32:50,095 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.1066) Prec@1 85.000 (81.605) Prec@5 98.000 (98.566) +2022-11-14 13:32:50,105 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.1067) Prec@1 79.000 (81.571) Prec@5 98.000 (98.558) +2022-11-14 13:32:50,114 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.1066) Prec@1 83.000 (81.590) Prec@5 96.000 (98.526) +2022-11-14 13:32:50,124 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1085 (0.1066) Prec@1 82.000 (81.595) Prec@5 99.000 (98.532) +2022-11-14 13:32:50,133 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.1066) Prec@1 82.000 (81.600) Prec@5 97.000 (98.513) +2022-11-14 13:32:50,142 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.1066) Prec@1 84.000 (81.630) Prec@5 97.000 (98.494) +2022-11-14 13:32:50,152 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.1064) Prec@1 82.000 (81.634) Prec@5 99.000 (98.500) +2022-11-14 13:32:50,161 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.1065) Prec@1 77.000 (81.578) Prec@5 100.000 (98.518) +2022-11-14 13:32:50,170 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1134 (0.1065) Prec@1 82.000 (81.583) Prec@5 98.000 (98.512) +2022-11-14 13:32:50,180 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1297 (0.1068) Prec@1 77.000 (81.529) Prec@5 96.000 (98.482) +2022-11-14 13:32:50,189 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1294 (0.1071) Prec@1 75.000 (81.453) Prec@5 99.000 (98.488) +2022-11-14 13:32:50,197 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.1070) Prec@1 85.000 (81.494) Prec@5 97.000 (98.471) +2022-11-14 13:32:50,207 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.1069) Prec@1 81.000 (81.489) Prec@5 99.000 (98.477) +2022-11-14 13:32:50,217 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.1070) Prec@1 80.000 (81.472) Prec@5 96.000 (98.449) +2022-11-14 13:32:50,225 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.1068) Prec@1 82.000 (81.478) Prec@5 100.000 (98.467) +2022-11-14 13:32:50,235 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.1066) Prec@1 88.000 (81.549) Prec@5 100.000 (98.484) +2022-11-14 13:32:50,244 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.1062) Prec@1 88.000 (81.620) Prec@5 100.000 (98.500) +2022-11-14 13:32:50,253 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.1065) Prec@1 77.000 (81.570) Prec@5 100.000 (98.516) +2022-11-14 13:32:50,263 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.1064) Prec@1 83.000 (81.585) Prec@5 98.000 (98.511) +2022-11-14 13:32:50,272 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.1065) Prec@1 81.000 (81.579) Prec@5 99.000 (98.516) +2022-11-14 13:32:50,281 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.1061) Prec@1 88.000 (81.646) Prec@5 100.000 (98.531) +2022-11-14 13:32:50,290 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.1058) Prec@1 86.000 (81.691) Prec@5 99.000 (98.536) +2022-11-14 13:32:50,300 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1355 (0.1061) Prec@1 79.000 (81.663) Prec@5 98.000 (98.531) +2022-11-14 13:32:50,309 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1205 (0.1062) Prec@1 81.000 (81.657) Prec@5 100.000 (98.545) +2022-11-14 13:32:50,318 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.1062) Prec@1 80.000 (81.640) Prec@5 98.000 (98.540) +2022-11-14 13:32:50,372 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:32:50,695 Epoch: [57][0/500] Time 0.034 (0.034) Data 0.233 (0.233) Loss 0.1292 (0.1292) Prec@1 77.000 (77.000) Prec@5 97.000 (97.000) +2022-11-14 13:32:50,920 Epoch: [57][10/500] Time 0.022 (0.021) Data 0.002 (0.023) Loss 0.0836 (0.1064) Prec@1 85.000 (81.000) Prec@5 100.000 (98.500) +2022-11-14 13:32:51,130 Epoch: [57][20/500] Time 0.015 (0.020) Data 0.001 (0.013) Loss 0.1192 (0.1107) Prec@1 79.000 (80.333) Prec@5 98.000 (98.333) +2022-11-14 13:32:51,334 Epoch: [57][30/500] Time 0.018 (0.019) Data 0.001 (0.009) Loss 0.0878 (0.1050) Prec@1 84.000 (81.250) Prec@5 100.000 (98.750) +2022-11-14 13:32:51,581 Epoch: [57][40/500] Time 0.028 (0.020) Data 0.002 (0.007) Loss 0.0883 (0.1016) Prec@1 84.000 (81.800) Prec@5 100.000 (99.000) +2022-11-14 13:32:51,858 Epoch: [57][50/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.1106 (0.1031) Prec@1 82.000 (81.833) Prec@5 98.000 (98.833) +2022-11-14 13:32:52,112 Epoch: [57][60/500] Time 0.027 (0.021) Data 0.002 (0.006) Loss 0.1045 (0.1033) Prec@1 82.000 (81.857) Prec@5 98.000 (98.714) +2022-11-14 13:32:52,370 Epoch: [57][70/500] Time 0.024 (0.021) Data 0.001 (0.005) Loss 0.1071 (0.1038) Prec@1 82.000 (81.875) Prec@5 100.000 (98.875) +2022-11-14 13:32:52,625 Epoch: [57][80/500] Time 0.024 (0.022) Data 0.002 (0.005) Loss 0.1100 (0.1045) Prec@1 80.000 (81.667) Prec@5 98.000 (98.778) +2022-11-14 13:32:52,910 Epoch: [57][90/500] Time 0.031 (0.022) Data 0.002 (0.004) Loss 0.0758 (0.1016) Prec@1 88.000 (82.300) Prec@5 100.000 (98.900) +2022-11-14 13:32:53,159 Epoch: [57][100/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0870 (0.1003) Prec@1 84.000 (82.455) Prec@5 99.000 (98.909) +2022-11-14 13:32:53,431 Epoch: [57][110/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.1019 (0.1004) Prec@1 84.000 (82.583) Prec@5 96.000 (98.667) +2022-11-14 13:32:53,785 Epoch: [57][120/500] Time 0.031 (0.023) Data 0.002 (0.004) Loss 0.0907 (0.0997) Prec@1 86.000 (82.846) Prec@5 96.000 (98.462) +2022-11-14 13:32:54,149 Epoch: [57][130/500] Time 0.031 (0.024) Data 0.002 (0.004) Loss 0.1080 (0.1003) Prec@1 80.000 (82.643) Prec@5 98.000 (98.429) +2022-11-14 13:32:54,504 Epoch: [57][140/500] Time 0.038 (0.024) Data 0.002 (0.003) Loss 0.1140 (0.1012) Prec@1 79.000 (82.400) Prec@5 98.000 (98.400) +2022-11-14 13:32:54,848 Epoch: [57][150/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0974 (0.1009) Prec@1 83.000 (82.438) Prec@5 99.000 (98.438) +2022-11-14 13:32:55,193 Epoch: [57][160/500] Time 0.032 (0.025) Data 0.002 (0.003) Loss 0.0835 (0.0999) Prec@1 84.000 (82.529) Prec@5 97.000 (98.353) +2022-11-14 13:32:55,537 Epoch: [57][170/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0956 (0.0997) Prec@1 84.000 (82.611) Prec@5 98.000 (98.333) +2022-11-14 13:32:55,886 Epoch: [57][180/500] Time 0.032 (0.026) Data 0.002 (0.003) Loss 0.1498 (0.1023) Prec@1 75.000 (82.211) Prec@5 97.000 (98.263) +2022-11-14 13:32:56,231 Epoch: [57][190/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0969 (0.1020) Prec@1 82.000 (82.200) Prec@5 97.000 (98.200) +2022-11-14 13:32:56,583 Epoch: [57][200/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.0951 (0.1017) Prec@1 86.000 (82.381) Prec@5 99.000 (98.238) +2022-11-14 13:32:56,937 Epoch: [57][210/500] Time 0.037 (0.026) Data 0.002 (0.003) Loss 0.1100 (0.1021) Prec@1 80.000 (82.273) Prec@5 99.000 (98.273) +2022-11-14 13:32:57,283 Epoch: [57][220/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.1029 (0.1021) Prec@1 80.000 (82.174) Prec@5 98.000 (98.261) +2022-11-14 13:32:57,634 Epoch: [57][230/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.1270 (0.1032) Prec@1 77.000 (81.958) Prec@5 97.000 (98.208) +2022-11-14 13:32:57,977 Epoch: [57][240/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.1164 (0.1037) Prec@1 79.000 (81.840) Prec@5 99.000 (98.240) +2022-11-14 13:32:58,334 Epoch: [57][250/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0886 (0.1031) Prec@1 83.000 (81.885) Prec@5 100.000 (98.308) +2022-11-14 13:32:58,682 Epoch: [57][260/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0656 (0.1017) Prec@1 92.000 (82.259) Prec@5 99.000 (98.333) +2022-11-14 13:32:59,032 Epoch: [57][270/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0870 (0.1012) Prec@1 85.000 (82.357) Prec@5 100.000 (98.393) +2022-11-14 13:32:59,390 Epoch: [57][280/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.1077 (0.1014) Prec@1 84.000 (82.414) Prec@5 98.000 (98.379) +2022-11-14 13:32:59,731 Epoch: [57][290/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.1077 (0.1016) Prec@1 84.000 (82.467) Prec@5 97.000 (98.333) +2022-11-14 13:33:00,080 Epoch: [57][300/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.1086 (0.1019) Prec@1 81.000 (82.419) Prec@5 98.000 (98.323) +2022-11-14 13:33:00,424 Epoch: [57][310/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.1096 (0.1021) Prec@1 80.000 (82.344) Prec@5 97.000 (98.281) +2022-11-14 13:33:00,780 Epoch: [57][320/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0829 (0.1015) Prec@1 84.000 (82.394) Prec@5 100.000 (98.333) +2022-11-14 13:33:01,141 Epoch: [57][330/500] Time 0.039 (0.028) Data 0.002 (0.003) Loss 0.0964 (0.1014) Prec@1 83.000 (82.412) Prec@5 99.000 (98.353) +2022-11-14 13:33:01,494 Epoch: [57][340/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.1499 (0.1027) Prec@1 74.000 (82.171) Prec@5 95.000 (98.257) +2022-11-14 13:33:01,843 Epoch: [57][350/500] Time 0.033 (0.028) Data 0.001 (0.003) Loss 0.0766 (0.1020) Prec@1 89.000 (82.361) Prec@5 98.000 (98.250) +2022-11-14 13:33:02,196 Epoch: [57][360/500] Time 0.032 (0.028) Data 0.002 (0.002) Loss 0.1062 (0.1021) Prec@1 81.000 (82.324) Prec@5 98.000 (98.243) +2022-11-14 13:33:02,543 Epoch: [57][370/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.0981 (0.1020) Prec@1 85.000 (82.395) Prec@5 100.000 (98.289) +2022-11-14 13:33:02,897 Epoch: [57][380/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.0938 (0.1018) Prec@1 78.000 (82.282) Prec@5 99.000 (98.308) +2022-11-14 13:33:03,242 Epoch: [57][390/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0880 (0.1015) Prec@1 84.000 (82.325) Prec@5 100.000 (98.350) +2022-11-14 13:33:03,594 Epoch: [57][400/500] Time 0.032 (0.029) Data 0.001 (0.002) Loss 0.0883 (0.1011) Prec@1 82.000 (82.317) Prec@5 100.000 (98.390) +2022-11-14 13:33:03,948 Epoch: [57][410/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0755 (0.1005) Prec@1 87.000 (82.429) Prec@5 100.000 (98.429) +2022-11-14 13:33:04,304 Epoch: [57][420/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0598 (0.0996) Prec@1 90.000 (82.605) Prec@5 100.000 (98.465) +2022-11-14 13:33:04,658 Epoch: [57][430/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0616 (0.0987) Prec@1 89.000 (82.750) Prec@5 97.000 (98.432) +2022-11-14 13:33:05,013 Epoch: [57][440/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0636 (0.0979) Prec@1 89.000 (82.889) Prec@5 100.000 (98.467) +2022-11-14 13:33:05,368 Epoch: [57][450/500] Time 0.029 (0.029) Data 0.003 (0.002) Loss 0.0957 (0.0979) Prec@1 84.000 (82.913) Prec@5 99.000 (98.478) +2022-11-14 13:33:05,710 Epoch: [57][460/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.1089 (0.0981) Prec@1 80.000 (82.851) Prec@5 99.000 (98.489) +2022-11-14 13:33:06,063 Epoch: [57][470/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.1260 (0.0987) Prec@1 81.000 (82.812) Prec@5 99.000 (98.500) +2022-11-14 13:33:06,417 Epoch: [57][480/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.1031 (0.0988) Prec@1 83.000 (82.816) Prec@5 98.000 (98.490) +2022-11-14 13:33:06,770 Epoch: [57][490/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.1065 (0.0990) Prec@1 85.000 (82.860) Prec@5 100.000 (98.520) +2022-11-14 13:33:07,089 Epoch: [57][499/500] Time 0.035 (0.029) Data 0.002 (0.002) Loss 0.0784 (0.0986) Prec@1 87.000 (82.941) Prec@5 99.000 (98.529) +2022-11-14 13:33:07,380 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1076 (0.1076) Prec@1 83.000 (83.000) Prec@5 98.000 (98.000) +2022-11-14 13:33:07,388 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0925 (0.1001) Prec@1 84.000 (83.500) Prec@5 99.000 (98.500) +2022-11-14 13:33:07,397 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0986) Prec@1 85.000 (84.000) Prec@5 100.000 (99.000) +2022-11-14 13:33:07,409 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.1032) Prec@1 76.000 (82.000) Prec@5 99.000 (99.000) +2022-11-14 13:33:07,418 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1218 (0.1069) Prec@1 80.000 (81.600) Prec@5 99.000 (99.000) +2022-11-14 13:33:07,426 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.1011) Prec@1 86.000 (82.333) Prec@5 99.000 (99.000) +2022-11-14 13:33:07,435 Test: [6/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1046) Prec@1 80.000 (82.000) Prec@5 100.000 (99.143) +2022-11-14 13:33:07,448 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.1049) Prec@1 80.000 (81.750) Prec@5 99.000 (99.125) +2022-11-14 13:33:07,459 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1321 (0.1080) Prec@1 79.000 (81.444) Prec@5 99.000 (99.111) +2022-11-14 13:33:07,467 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.1068) Prec@1 84.000 (81.700) Prec@5 96.000 (98.800) +2022-11-14 13:33:07,479 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1060) Prec@1 84.000 (81.909) Prec@5 100.000 (98.909) +2022-11-14 13:33:07,490 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.1067) Prec@1 81.000 (81.833) Prec@5 98.000 (98.833) +2022-11-14 13:33:07,502 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1061) Prec@1 84.000 (82.000) Prec@5 99.000 (98.846) +2022-11-14 13:33:07,515 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.1047) Prec@1 85.000 (82.214) Prec@5 97.000 (98.714) +2022-11-14 13:33:07,526 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.1036) Prec@1 86.000 (82.467) Prec@5 99.000 (98.733) +2022-11-14 13:33:07,537 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.1044) Prec@1 79.000 (82.250) Prec@5 97.000 (98.625) +2022-11-14 13:33:07,548 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.1014) Prec@1 92.000 (82.824) Prec@5 98.000 (98.588) +2022-11-14 13:33:07,559 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1240 (0.1026) Prec@1 78.000 (82.556) Prec@5 99.000 (98.611) +2022-11-14 13:33:07,571 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1042) Prec@1 80.000 (82.421) Prec@5 99.000 (98.632) +2022-11-14 13:33:07,583 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1338 (0.1056) Prec@1 77.000 (82.150) Prec@5 96.000 (98.500) +2022-11-14 13:33:07,596 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1061) Prec@1 78.000 (81.952) Prec@5 100.000 (98.571) +2022-11-14 13:33:07,608 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.1061) Prec@1 83.000 (82.000) Prec@5 98.000 (98.545) +2022-11-14 13:33:07,620 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.1066) Prec@1 79.000 (81.870) Prec@5 98.000 (98.522) +2022-11-14 13:33:07,631 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.1057) Prec@1 85.000 (82.000) Prec@5 99.000 (98.542) +2022-11-14 13:33:07,642 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1318 (0.1068) Prec@1 78.000 (81.840) Prec@5 100.000 (98.600) +2022-11-14 13:33:07,654 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.1077) Prec@1 79.000 (81.731) Prec@5 95.000 (98.462) +2022-11-14 13:33:07,666 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.1068) Prec@1 86.000 (81.889) Prec@5 100.000 (98.519) +2022-11-14 13:33:07,678 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1074) Prec@1 80.000 (81.821) Prec@5 99.000 (98.536) +2022-11-14 13:33:07,691 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.1073) Prec@1 81.000 (81.793) Prec@5 100.000 (98.586) +2022-11-14 13:33:07,704 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.1070) Prec@1 83.000 (81.833) Prec@5 98.000 (98.567) +2022-11-14 13:33:07,717 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1069) Prec@1 85.000 (81.935) Prec@5 97.000 (98.516) +2022-11-14 13:33:07,729 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1071) Prec@1 79.000 (81.844) Prec@5 99.000 (98.531) +2022-11-14 13:33:07,741 Test: [32/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.1069) Prec@1 82.000 (81.848) Prec@5 96.000 (98.455) +2022-11-14 13:33:07,754 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1077) Prec@1 76.000 (81.676) Prec@5 98.000 (98.441) +2022-11-14 13:33:07,766 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.1073) Prec@1 83.000 (81.714) Prec@5 98.000 (98.429) +2022-11-14 13:33:07,778 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.1063) Prec@1 87.000 (81.861) Prec@5 100.000 (98.472) +2022-11-14 13:33:07,790 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.1064) Prec@1 82.000 (81.865) Prec@5 99.000 (98.486) +2022-11-14 13:33:07,803 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1311 (0.1070) Prec@1 78.000 (81.763) Prec@5 99.000 (98.500) +2022-11-14 13:33:07,815 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.1070) Prec@1 82.000 (81.769) Prec@5 99.000 (98.513) +2022-11-14 13:33:07,828 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.1066) Prec@1 82.000 (81.775) Prec@5 97.000 (98.475) +2022-11-14 13:33:07,840 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.1065) Prec@1 81.000 (81.756) Prec@5 96.000 (98.415) +2022-11-14 13:33:07,851 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.1061) Prec@1 83.000 (81.786) Prec@5 97.000 (98.381) +2022-11-14 13:33:07,863 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.1053) Prec@1 89.000 (81.953) Prec@5 98.000 (98.372) +2022-11-14 13:33:07,874 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.1054) Prec@1 82.000 (81.955) Prec@5 97.000 (98.341) +2022-11-14 13:33:07,886 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.1053) Prec@1 83.000 (81.978) Prec@5 98.000 (98.333) +2022-11-14 13:33:07,898 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1330 (0.1059) Prec@1 75.000 (81.826) Prec@5 100.000 (98.370) +2022-11-14 13:33:07,910 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1062) Prec@1 80.000 (81.787) Prec@5 99.000 (98.383) +2022-11-14 13:33:07,921 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1302 (0.1067) Prec@1 80.000 (81.750) Prec@5 99.000 (98.396) +2022-11-14 13:33:07,933 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.1061) Prec@1 86.000 (81.837) Prec@5 100.000 (98.429) +2022-11-14 13:33:07,946 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1235 (0.1064) Prec@1 80.000 (81.800) Prec@5 97.000 (98.400) +2022-11-14 13:33:07,958 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.1060) Prec@1 84.000 (81.843) Prec@5 99.000 (98.412) +2022-11-14 13:33:07,970 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1062) Prec@1 81.000 (81.827) Prec@5 100.000 (98.442) +2022-11-14 13:33:07,982 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.1062) Prec@1 81.000 (81.811) Prec@5 100.000 (98.472) +2022-11-14 13:33:07,994 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.1059) Prec@1 85.000 (81.870) Prec@5 100.000 (98.500) +2022-11-14 13:33:08,006 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.1060) Prec@1 79.000 (81.818) Prec@5 98.000 (98.491) +2022-11-14 13:33:08,018 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.1056) Prec@1 84.000 (81.857) Prec@5 99.000 (98.500) +2022-11-14 13:33:08,030 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1058) Prec@1 80.000 (81.825) Prec@5 99.000 (98.509) +2022-11-14 13:33:08,042 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.1054) Prec@1 85.000 (81.879) Prec@5 98.000 (98.500) +2022-11-14 13:33:08,053 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1345 (0.1059) Prec@1 71.000 (81.695) Prec@5 100.000 (98.525) +2022-11-14 13:33:08,066 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.1058) Prec@1 82.000 (81.700) Prec@5 99.000 (98.533) +2022-11-14 13:33:08,078 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.1058) Prec@1 83.000 (81.721) Prec@5 98.000 (98.525) +2022-11-14 13:33:08,090 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1060) Prec@1 79.000 (81.677) Prec@5 98.000 (98.516) +2022-11-14 13:33:08,101 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.1057) Prec@1 87.000 (81.762) Prec@5 98.000 (98.508) +2022-11-14 13:33:08,114 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.1055) Prec@1 83.000 (81.781) Prec@5 100.000 (98.531) +2022-11-14 13:33:08,127 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.1058) Prec@1 79.000 (81.738) Prec@5 98.000 (98.523) +2022-11-14 13:33:08,139 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1335 (0.1062) Prec@1 77.000 (81.667) Prec@5 99.000 (98.530) +2022-11-14 13:33:08,150 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.1058) Prec@1 88.000 (81.761) Prec@5 100.000 (98.552) +2022-11-14 13:33:08,163 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.1058) Prec@1 81.000 (81.750) Prec@5 97.000 (98.529) +2022-11-14 13:33:08,176 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.1057) Prec@1 84.000 (81.783) Prec@5 100.000 (98.551) +2022-11-14 13:33:08,188 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1436 (0.1062) Prec@1 77.000 (81.714) Prec@5 98.000 (98.543) +2022-11-14 13:33:08,199 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.1061) Prec@1 81.000 (81.704) Prec@5 98.000 (98.535) +2022-11-14 13:33:08,211 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.1059) Prec@1 86.000 (81.764) Prec@5 98.000 (98.528) +2022-11-14 13:33:08,224 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.1056) Prec@1 84.000 (81.795) Prec@5 100.000 (98.548) +2022-11-14 13:33:08,236 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.1052) Prec@1 86.000 (81.851) Prec@5 99.000 (98.554) +2022-11-14 13:33:08,247 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1426 (0.1057) Prec@1 74.000 (81.747) Prec@5 98.000 (98.547) +2022-11-14 13:33:08,261 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.1057) Prec@1 82.000 (81.750) Prec@5 98.000 (98.539) +2022-11-14 13:33:08,274 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.1056) Prec@1 83.000 (81.766) Prec@5 97.000 (98.519) +2022-11-14 13:33:08,286 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.1056) Prec@1 82.000 (81.769) Prec@5 97.000 (98.500) +2022-11-14 13:33:08,300 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1056) Prec@1 86.000 (81.823) Prec@5 99.000 (98.506) +2022-11-14 13:33:08,312 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1057) Prec@1 78.000 (81.775) Prec@5 100.000 (98.525) +2022-11-14 13:33:08,324 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.1053) Prec@1 86.000 (81.827) Prec@5 99.000 (98.531) +2022-11-14 13:33:08,336 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.1052) Prec@1 82.000 (81.829) Prec@5 99.000 (98.537) +2022-11-14 13:33:08,348 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1179 (0.1054) Prec@1 78.000 (81.783) Prec@5 100.000 (98.554) +2022-11-14 13:33:08,360 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.1054) Prec@1 83.000 (81.798) Prec@5 99.000 (98.560) +2022-11-14 13:33:08,372 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1333 (0.1058) Prec@1 76.000 (81.729) Prec@5 100.000 (98.576) +2022-11-14 13:33:08,385 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1202 (0.1059) Prec@1 77.000 (81.674) Prec@5 99.000 (98.581) +2022-11-14 13:33:08,397 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.1058) Prec@1 86.000 (81.724) Prec@5 99.000 (98.586) +2022-11-14 13:33:08,409 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.1055) Prec@1 84.000 (81.750) Prec@5 99.000 (98.591) +2022-11-14 13:33:08,421 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1057) Prec@1 80.000 (81.730) Prec@5 100.000 (98.607) +2022-11-14 13:33:08,433 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1058) Prec@1 82.000 (81.733) Prec@5 97.000 (98.589) +2022-11-14 13:33:08,445 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1057) Prec@1 83.000 (81.747) Prec@5 99.000 (98.593) +2022-11-14 13:33:08,457 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.1053) Prec@1 89.000 (81.826) Prec@5 99.000 (98.598) +2022-11-14 13:33:08,470 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1225 (0.1055) Prec@1 80.000 (81.806) Prec@5 98.000 (98.591) +2022-11-14 13:33:08,483 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.1054) Prec@1 85.000 (81.840) Prec@5 98.000 (98.585) +2022-11-14 13:33:08,495 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.1053) Prec@1 81.000 (81.832) Prec@5 99.000 (98.589) +2022-11-14 13:33:08,507 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.1051) Prec@1 83.000 (81.844) Prec@5 99.000 (98.594) +2022-11-14 13:33:08,518 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.1049) Prec@1 80.000 (81.825) Prec@5 100.000 (98.608) +2022-11-14 13:33:08,530 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.1050) Prec@1 80.000 (81.806) Prec@5 97.000 (98.592) +2022-11-14 13:33:08,542 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1297 (0.1053) Prec@1 78.000 (81.768) Prec@5 100.000 (98.606) +2022-11-14 13:33:08,553 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1054) Prec@1 78.000 (81.730) Prec@5 99.000 (98.610) +2022-11-14 13:33:08,610 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:33:08,909 Epoch: [58][0/500] Time 0.025 (0.025) Data 0.216 (0.216) Loss 0.1067 (0.1067) Prec@1 82.000 (82.000) Prec@5 100.000 (100.000) +2022-11-14 13:33:09,198 Epoch: [58][10/500] Time 0.032 (0.025) Data 0.002 (0.022) Loss 0.0926 (0.0997) Prec@1 82.000 (82.000) Prec@5 99.000 (99.500) +2022-11-14 13:33:09,545 Epoch: [58][20/500] Time 0.039 (0.028) Data 0.002 (0.012) Loss 0.1199 (0.1064) Prec@1 78.000 (80.667) Prec@5 100.000 (99.667) +2022-11-14 13:33:09,900 Epoch: [58][30/500] Time 0.036 (0.029) Data 0.002 (0.009) Loss 0.0784 (0.0994) Prec@1 88.000 (82.500) Prec@5 99.000 (99.500) +2022-11-14 13:33:10,268 Epoch: [58][40/500] Time 0.033 (0.030) Data 0.002 (0.007) Loss 0.0817 (0.0959) Prec@1 87.000 (83.400) Prec@5 100.000 (99.600) +2022-11-14 13:33:10,619 Epoch: [58][50/500] Time 0.033 (0.030) Data 0.002 (0.006) Loss 0.1074 (0.0978) Prec@1 80.000 (82.833) Prec@5 98.000 (99.333) +2022-11-14 13:33:10,975 Epoch: [58][60/500] Time 0.031 (0.030) Data 0.002 (0.005) Loss 0.0790 (0.0951) Prec@1 85.000 (83.143) Prec@5 99.000 (99.286) +2022-11-14 13:33:11,335 Epoch: [58][70/500] Time 0.035 (0.031) Data 0.002 (0.005) Loss 0.0966 (0.0953) Prec@1 84.000 (83.250) Prec@5 99.000 (99.250) +2022-11-14 13:33:11,689 Epoch: [58][80/500] Time 0.031 (0.031) Data 0.001 (0.005) Loss 0.1106 (0.0970) Prec@1 81.000 (83.000) Prec@5 100.000 (99.333) +2022-11-14 13:33:12,051 Epoch: [58][90/500] Time 0.032 (0.031) Data 0.001 (0.004) Loss 0.1357 (0.1009) Prec@1 78.000 (82.500) Prec@5 100.000 (99.400) +2022-11-14 13:33:12,406 Epoch: [58][100/500] Time 0.032 (0.031) Data 0.002 (0.004) Loss 0.1216 (0.1027) Prec@1 82.000 (82.455) Prec@5 97.000 (99.182) +2022-11-14 13:33:12,756 Epoch: [58][110/500] Time 0.037 (0.031) Data 0.002 (0.004) Loss 0.1058 (0.1030) Prec@1 82.000 (82.417) Prec@5 98.000 (99.083) +2022-11-14 13:33:13,112 Epoch: [58][120/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.1015 (0.1029) Prec@1 84.000 (82.538) Prec@5 99.000 (99.077) +2022-11-14 13:33:13,468 Epoch: [58][130/500] Time 0.034 (0.031) Data 0.002 (0.004) Loss 0.0730 (0.1008) Prec@1 89.000 (83.000) Prec@5 99.000 (99.071) +2022-11-14 13:33:13,833 Epoch: [58][140/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.1011 (0.1008) Prec@1 82.000 (82.933) Prec@5 98.000 (99.000) +2022-11-14 13:33:14,181 Epoch: [58][150/500] Time 0.031 (0.031) Data 0.001 (0.003) Loss 0.0850 (0.0998) Prec@1 85.000 (83.062) Prec@5 99.000 (99.000) +2022-11-14 13:33:14,543 Epoch: [58][160/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0912 (0.0993) Prec@1 85.000 (83.176) Prec@5 98.000 (98.941) +2022-11-14 13:33:14,898 Epoch: [58][170/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.1220 (0.1006) Prec@1 78.000 (82.889) Prec@5 99.000 (98.944) +2022-11-14 13:33:15,250 Epoch: [58][180/500] Time 0.029 (0.031) Data 0.002 (0.003) Loss 0.0912 (0.1001) Prec@1 85.000 (83.000) Prec@5 99.000 (98.947) +2022-11-14 13:33:15,607 Epoch: [58][190/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.1086 (0.1005) Prec@1 81.000 (82.900) Prec@5 100.000 (99.000) +2022-11-14 13:33:15,961 Epoch: [58][200/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.1140 (0.1011) Prec@1 81.000 (82.810) Prec@5 100.000 (99.048) +2022-11-14 13:33:16,320 Epoch: [58][210/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.1219 (0.1021) Prec@1 77.000 (82.545) Prec@5 99.000 (99.045) +2022-11-14 13:33:16,682 Epoch: [58][220/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0817 (0.1012) Prec@1 85.000 (82.652) Prec@5 98.000 (99.000) +2022-11-14 13:33:17,027 Epoch: [58][230/500] Time 0.028 (0.031) Data 0.002 (0.003) Loss 0.0966 (0.1010) Prec@1 83.000 (82.667) Prec@5 97.000 (98.917) +2022-11-14 13:33:17,378 Epoch: [58][240/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.1082 (0.1013) Prec@1 80.000 (82.560) Prec@5 99.000 (98.920) +2022-11-14 13:33:17,739 Epoch: [58][250/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.1164 (0.1019) Prec@1 80.000 (82.462) Prec@5 99.000 (98.923) +2022-11-14 13:33:18,132 Epoch: [58][260/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0749 (0.1009) Prec@1 86.000 (82.593) Prec@5 100.000 (98.963) +2022-11-14 13:33:18,629 Epoch: [58][270/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0943 (0.1006) Prec@1 81.000 (82.536) Prec@5 98.000 (98.929) +2022-11-14 13:33:19,130 Epoch: [58][280/500] Time 0.047 (0.032) Data 0.002 (0.003) Loss 0.0916 (0.1003) Prec@1 83.000 (82.552) Prec@5 98.000 (98.897) +2022-11-14 13:33:19,621 Epoch: [58][290/500] Time 0.052 (0.033) Data 0.002 (0.003) Loss 0.0912 (0.1000) Prec@1 83.000 (82.567) Prec@5 100.000 (98.933) +2022-11-14 13:33:20,111 Epoch: [58][300/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1252 (0.1008) Prec@1 75.000 (82.323) Prec@5 98.000 (98.903) +2022-11-14 13:33:20,588 Epoch: [58][310/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0959 (0.1007) Prec@1 82.000 (82.312) Prec@5 98.000 (98.875) +2022-11-14 13:33:21,060 Epoch: [58][320/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.1081 (0.1009) Prec@1 82.000 (82.303) Prec@5 100.000 (98.909) +2022-11-14 13:33:21,549 Epoch: [58][330/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0855 (0.1004) Prec@1 86.000 (82.412) Prec@5 100.000 (98.941) +2022-11-14 13:33:22,021 Epoch: [58][340/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0730 (0.0997) Prec@1 90.000 (82.629) Prec@5 100.000 (98.971) +2022-11-14 13:33:22,483 Epoch: [58][350/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.1129 (0.1000) Prec@1 80.000 (82.556) Prec@5 98.000 (98.944) +2022-11-14 13:33:22,965 Epoch: [58][360/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0957 (0.0999) Prec@1 83.000 (82.568) Prec@5 100.000 (98.973) +2022-11-14 13:33:23,466 Epoch: [58][370/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.1002 (0.0999) Prec@1 85.000 (82.632) Prec@5 99.000 (98.974) +2022-11-14 13:33:23,971 Epoch: [58][380/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0890 (0.0996) Prec@1 84.000 (82.667) Prec@5 99.000 (98.974) +2022-11-14 13:33:24,472 Epoch: [58][390/500] Time 0.051 (0.035) Data 0.002 (0.002) Loss 0.0937 (0.0995) Prec@1 85.000 (82.725) Prec@5 98.000 (98.950) +2022-11-14 13:33:24,963 Epoch: [58][400/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1400 (0.1005) Prec@1 75.000 (82.537) Prec@5 99.000 (98.951) +2022-11-14 13:33:25,465 Epoch: [58][410/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0851 (0.1001) Prec@1 86.000 (82.619) Prec@5 100.000 (98.976) +2022-11-14 13:33:25,938 Epoch: [58][420/500] Time 0.051 (0.036) Data 0.002 (0.002) Loss 0.0878 (0.0998) Prec@1 84.000 (82.651) Prec@5 99.000 (98.977) +2022-11-14 13:33:26,401 Epoch: [58][430/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0908 (0.0996) Prec@1 87.000 (82.750) Prec@5 100.000 (99.000) +2022-11-14 13:33:26,871 Epoch: [58][440/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0984 (0.0996) Prec@1 82.000 (82.733) Prec@5 98.000 (98.978) +2022-11-14 13:33:27,384 Epoch: [58][450/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1029 (0.0997) Prec@1 83.000 (82.739) Prec@5 100.000 (99.000) +2022-11-14 13:33:27,855 Epoch: [58][460/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0764 (0.0992) Prec@1 89.000 (82.872) Prec@5 99.000 (99.000) +2022-11-14 13:33:28,325 Epoch: [58][470/500] Time 0.053 (0.037) Data 0.002 (0.002) Loss 0.0700 (0.0986) Prec@1 89.000 (83.000) Prec@5 98.000 (98.979) +2022-11-14 13:33:28,836 Epoch: [58][480/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0946 (0.0985) Prec@1 84.000 (83.020) Prec@5 100.000 (99.000) +2022-11-14 13:33:29,338 Epoch: [58][490/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.1029 (0.0986) Prec@1 84.000 (83.040) Prec@5 95.000 (98.920) +2022-11-14 13:33:29,784 Epoch: [58][499/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0697 (0.0980) Prec@1 90.000 (83.176) Prec@5 100.000 (98.941) +2022-11-14 13:33:30,059 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0874 (0.0874) Prec@1 84.000 (84.000) Prec@5 98.000 (98.000) +2022-11-14 13:33:30,069 Test: [1/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0923 (0.0899) Prec@1 87.000 (85.500) Prec@5 100.000 (99.000) +2022-11-14 13:33:30,079 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1008 (0.0935) Prec@1 83.000 (84.667) Prec@5 98.000 (98.667) +2022-11-14 13:33:30,093 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1376 (0.1045) Prec@1 77.000 (82.750) Prec@5 99.000 (98.750) +2022-11-14 13:33:30,102 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1230 (0.1082) Prec@1 77.000 (81.600) Prec@5 97.000 (98.400) +2022-11-14 13:33:30,110 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.1044) Prec@1 83.000 (81.833) Prec@5 100.000 (98.667) +2022-11-14 13:33:30,119 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1069 (0.1047) Prec@1 83.000 (82.000) Prec@5 96.000 (98.286) +2022-11-14 13:33:30,130 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1233 (0.1070) Prec@1 80.000 (81.750) Prec@5 99.000 (98.375) +2022-11-14 13:33:30,141 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1260 (0.1091) Prec@1 81.000 (81.667) Prec@5 99.000 (98.444) +2022-11-14 13:33:30,150 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.1090) Prec@1 82.000 (81.700) Prec@5 99.000 (98.500) +2022-11-14 13:33:30,161 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.1086) Prec@1 83.000 (81.818) Prec@5 99.000 (98.545) +2022-11-14 13:33:30,172 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1130 (0.1090) Prec@1 81.000 (81.750) Prec@5 100.000 (98.667) +2022-11-14 13:33:30,184 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.1083) Prec@1 83.000 (81.846) Prec@5 100.000 (98.769) +2022-11-14 13:33:30,198 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.1077) Prec@1 84.000 (82.000) Prec@5 99.000 (98.786) +2022-11-14 13:33:30,210 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1205 (0.1086) Prec@1 76.000 (81.600) Prec@5 100.000 (98.867) +2022-11-14 13:33:30,221 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1195 (0.1093) Prec@1 78.000 (81.375) Prec@5 100.000 (98.938) +2022-11-14 13:33:30,234 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.1074) Prec@1 88.000 (81.765) Prec@5 99.000 (98.941) +2022-11-14 13:33:30,247 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1213 (0.1082) Prec@1 79.000 (81.611) Prec@5 99.000 (98.944) +2022-11-14 13:33:30,260 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1171 (0.1087) Prec@1 80.000 (81.526) Prec@5 97.000 (98.842) +2022-11-14 13:33:30,273 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1531 (0.1109) Prec@1 75.000 (81.200) Prec@5 96.000 (98.700) +2022-11-14 13:33:30,285 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.1105) Prec@1 83.000 (81.286) Prec@5 99.000 (98.714) +2022-11-14 13:33:30,296 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.1102) Prec@1 82.000 (81.318) Prec@5 97.000 (98.636) +2022-11-14 13:33:30,309 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.1113) Prec@1 77.000 (81.130) Prec@5 95.000 (98.478) +2022-11-14 13:33:30,320 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1115) Prec@1 78.000 (81.000) Prec@5 100.000 (98.542) +2022-11-14 13:33:30,333 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.1119) Prec@1 78.000 (80.880) Prec@5 100.000 (98.600) +2022-11-14 13:33:30,347 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1127) Prec@1 75.000 (80.654) Prec@5 95.000 (98.462) +2022-11-14 13:33:30,357 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.1119) Prec@1 83.000 (80.741) Prec@5 100.000 (98.519) +2022-11-14 13:33:30,369 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.1122) Prec@1 78.000 (80.643) Prec@5 98.000 (98.500) +2022-11-14 13:33:30,381 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1119) Prec@1 81.000 (80.655) Prec@5 96.000 (98.414) +2022-11-14 13:33:30,392 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.1115) Prec@1 82.000 (80.700) Prec@5 98.000 (98.400) +2022-11-14 13:33:30,404 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.1116) Prec@1 81.000 (80.710) Prec@5 97.000 (98.355) +2022-11-14 13:33:30,417 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.1118) Prec@1 78.000 (80.625) Prec@5 100.000 (98.406) +2022-11-14 13:33:30,429 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1282 (0.1123) Prec@1 77.000 (80.515) Prec@5 97.000 (98.364) +2022-11-14 13:33:30,443 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1353 (0.1130) Prec@1 79.000 (80.471) Prec@5 97.000 (98.324) +2022-11-14 13:33:30,455 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1249 (0.1133) Prec@1 78.000 (80.400) Prec@5 97.000 (98.286) +2022-11-14 13:33:30,468 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1134) Prec@1 80.000 (80.389) Prec@5 97.000 (98.250) +2022-11-14 13:33:30,479 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1141) Prec@1 75.000 (80.243) Prec@5 98.000 (98.243) +2022-11-14 13:33:30,492 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1141) Prec@1 82.000 (80.289) Prec@5 99.000 (98.263) +2022-11-14 13:33:30,504 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.1133) Prec@1 87.000 (80.462) Prec@5 99.000 (98.282) +2022-11-14 13:33:30,517 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.1127) Prec@1 84.000 (80.550) Prec@5 98.000 (98.275) +2022-11-14 13:33:30,529 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1225 (0.1129) Prec@1 78.000 (80.488) Prec@5 99.000 (98.293) +2022-11-14 13:33:30,543 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.1126) Prec@1 83.000 (80.548) Prec@5 98.000 (98.286) +2022-11-14 13:33:30,554 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.1121) Prec@1 84.000 (80.628) Prec@5 99.000 (98.302) +2022-11-14 13:33:30,566 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.1116) Prec@1 86.000 (80.750) Prec@5 98.000 (98.295) +2022-11-14 13:33:30,579 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1117) Prec@1 81.000 (80.756) Prec@5 99.000 (98.311) +2022-11-14 13:33:30,592 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1117) Prec@1 81.000 (80.761) Prec@5 99.000 (98.326) +2022-11-14 13:33:30,604 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.1112) Prec@1 85.000 (80.851) Prec@5 100.000 (98.362) +2022-11-14 13:33:30,615 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.1113) Prec@1 79.000 (80.812) Prec@5 98.000 (98.354) +2022-11-14 13:33:30,629 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.1108) Prec@1 86.000 (80.918) Prec@5 97.000 (98.327) +2022-11-14 13:33:30,644 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.1110) Prec@1 80.000 (80.900) Prec@5 97.000 (98.300) +2022-11-14 13:33:30,657 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.1106) Prec@1 87.000 (81.020) Prec@5 99.000 (98.314) +2022-11-14 13:33:30,670 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1396 (0.1111) Prec@1 74.000 (80.885) Prec@5 98.000 (98.308) +2022-11-14 13:33:30,682 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.1108) Prec@1 83.000 (80.925) Prec@5 100.000 (98.340) +2022-11-14 13:33:30,694 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.1107) Prec@1 82.000 (80.944) Prec@5 99.000 (98.352) +2022-11-14 13:33:30,705 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.1107) Prec@1 81.000 (80.945) Prec@5 98.000 (98.345) +2022-11-14 13:33:30,716 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.1106) Prec@1 81.000 (80.946) Prec@5 98.000 (98.339) +2022-11-14 13:33:30,729 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1305 (0.1110) Prec@1 76.000 (80.860) Prec@5 98.000 (98.333) +2022-11-14 13:33:30,740 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.1109) Prec@1 84.000 (80.914) Prec@5 100.000 (98.362) +2022-11-14 13:33:30,753 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.1110) Prec@1 80.000 (80.898) Prec@5 99.000 (98.373) +2022-11-14 13:33:30,767 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.1106) Prec@1 86.000 (80.983) Prec@5 99.000 (98.383) +2022-11-14 13:33:30,779 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.1107) Prec@1 77.000 (80.918) Prec@5 99.000 (98.393) +2022-11-14 13:33:30,791 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.1104) Prec@1 84.000 (80.968) Prec@5 99.000 (98.403) +2022-11-14 13:33:30,802 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.1101) Prec@1 81.000 (80.968) Prec@5 99.000 (98.413) +2022-11-14 13:33:30,815 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.1098) Prec@1 84.000 (81.016) Prec@5 100.000 (98.438) +2022-11-14 13:33:30,827 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1241 (0.1100) Prec@1 80.000 (81.000) Prec@5 97.000 (98.415) +2022-11-14 13:33:30,841 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.1098) Prec@1 84.000 (81.045) Prec@5 100.000 (98.439) +2022-11-14 13:33:30,853 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.1096) Prec@1 84.000 (81.090) Prec@5 100.000 (98.463) +2022-11-14 13:33:30,864 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1239 (0.1098) Prec@1 79.000 (81.059) Prec@5 99.000 (98.471) +2022-11-14 13:33:30,877 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.1098) Prec@1 78.000 (81.014) Prec@5 99.000 (98.478) +2022-11-14 13:33:30,889 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1204 (0.1099) Prec@1 79.000 (80.986) Prec@5 98.000 (98.471) +2022-11-14 13:33:30,900 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1100) Prec@1 75.000 (80.901) Prec@5 100.000 (98.493) +2022-11-14 13:33:30,914 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.1100) Prec@1 84.000 (80.944) Prec@5 100.000 (98.514) +2022-11-14 13:33:30,927 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.1095) Prec@1 87.000 (81.027) Prec@5 100.000 (98.534) +2022-11-14 13:33:30,940 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.1094) Prec@1 82.000 (81.041) Prec@5 100.000 (98.554) +2022-11-14 13:33:30,952 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1480 (0.1099) Prec@1 73.000 (80.933) Prec@5 96.000 (98.520) +2022-11-14 13:33:30,964 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.1096) Prec@1 85.000 (80.987) Prec@5 100.000 (98.539) +2022-11-14 13:33:30,976 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1242 (0.1098) Prec@1 78.000 (80.948) Prec@5 99.000 (98.545) +2022-11-14 13:33:30,991 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1099) Prec@1 78.000 (80.910) Prec@5 96.000 (98.513) +2022-11-14 13:33:31,004 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1283 (0.1101) Prec@1 75.000 (80.835) Prec@5 100.000 (98.532) +2022-11-14 13:33:31,018 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.1100) Prec@1 83.000 (80.862) Prec@5 100.000 (98.550) +2022-11-14 13:33:31,030 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1101) Prec@1 79.000 (80.840) Prec@5 96.000 (98.519) +2022-11-14 13:33:31,043 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1100) Prec@1 83.000 (80.866) Prec@5 97.000 (98.500) +2022-11-14 13:33:31,055 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1100) Prec@1 81.000 (80.867) Prec@5 99.000 (98.506) +2022-11-14 13:33:31,067 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1367 (0.1103) Prec@1 75.000 (80.798) Prec@5 98.000 (98.500) +2022-11-14 13:33:31,082 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1411 (0.1106) Prec@1 76.000 (80.741) Prec@5 99.000 (98.506) +2022-11-14 13:33:31,094 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1372 (0.1109) Prec@1 78.000 (80.709) Prec@5 97.000 (98.488) +2022-11-14 13:33:31,106 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.1110) Prec@1 78.000 (80.678) Prec@5 99.000 (98.494) +2022-11-14 13:33:31,117 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.1110) Prec@1 82.000 (80.693) Prec@5 99.000 (98.500) +2022-11-14 13:33:31,129 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.1109) Prec@1 83.000 (80.719) Prec@5 97.000 (98.483) +2022-11-14 13:33:31,141 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1420 (0.1112) Prec@1 77.000 (80.678) Prec@5 99.000 (98.489) +2022-11-14 13:33:31,154 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.1111) Prec@1 82.000 (80.692) Prec@5 99.000 (98.495) +2022-11-14 13:33:31,166 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.1107) Prec@1 87.000 (80.761) Prec@5 99.000 (98.500) +2022-11-14 13:33:31,181 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1338 (0.1110) Prec@1 78.000 (80.731) Prec@5 100.000 (98.516) +2022-11-14 13:33:31,194 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1109) Prec@1 81.000 (80.734) Prec@5 99.000 (98.521) +2022-11-14 13:33:31,205 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.1108) Prec@1 81.000 (80.737) Prec@5 99.000 (98.526) +2022-11-14 13:33:31,218 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.1107) Prec@1 82.000 (80.750) Prec@5 98.000 (98.521) +2022-11-14 13:33:31,231 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.1106) Prec@1 82.000 (80.763) Prec@5 98.000 (98.515) +2022-11-14 13:33:31,243 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1108) Prec@1 79.000 (80.745) Prec@5 100.000 (98.531) +2022-11-14 13:33:31,254 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.1107) Prec@1 81.000 (80.747) Prec@5 100.000 (98.545) +2022-11-14 13:33:31,267 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.1105) Prec@1 81.000 (80.750) Prec@5 99.000 (98.550) +2022-11-14 13:33:31,324 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:33:31,637 Epoch: [59][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.1159 (0.1159) Prec@1 80.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:33:31,854 Epoch: [59][10/500] Time 0.019 (0.020) Data 0.002 (0.023) Loss 0.0839 (0.0999) Prec@1 86.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:33:32,086 Epoch: [59][20/500] Time 0.022 (0.020) Data 0.001 (0.013) Loss 0.0822 (0.0940) Prec@1 88.000 (84.667) Prec@5 100.000 (99.333) +2022-11-14 13:33:32,434 Epoch: [59][30/500] Time 0.032 (0.024) Data 0.002 (0.009) Loss 0.1020 (0.0960) Prec@1 81.000 (83.750) Prec@5 99.000 (99.250) +2022-11-14 13:33:32,803 Epoch: [59][40/500] Time 0.036 (0.026) Data 0.002 (0.007) Loss 0.0730 (0.0914) Prec@1 85.000 (84.000) Prec@5 100.000 (99.400) +2022-11-14 13:33:33,181 Epoch: [59][50/500] Time 0.035 (0.027) Data 0.002 (0.006) Loss 0.1346 (0.0986) Prec@1 75.000 (82.500) Prec@5 97.000 (99.000) +2022-11-14 13:33:33,549 Epoch: [59][60/500] Time 0.038 (0.028) Data 0.002 (0.006) Loss 0.0840 (0.0965) Prec@1 84.000 (82.714) Prec@5 99.000 (99.000) +2022-11-14 13:33:33,925 Epoch: [59][70/500] Time 0.033 (0.029) Data 0.002 (0.005) Loss 0.1151 (0.0988) Prec@1 82.000 (82.625) Prec@5 99.000 (99.000) +2022-11-14 13:33:34,295 Epoch: [59][80/500] Time 0.038 (0.029) Data 0.002 (0.005) Loss 0.0887 (0.0977) Prec@1 81.000 (82.444) Prec@5 100.000 (99.111) +2022-11-14 13:33:34,666 Epoch: [59][90/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.1220 (0.1001) Prec@1 72.000 (81.400) Prec@5 100.000 (99.200) +2022-11-14 13:33:35,041 Epoch: [59][100/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0819 (0.0985) Prec@1 86.000 (81.818) Prec@5 100.000 (99.273) +2022-11-14 13:33:35,422 Epoch: [59][110/500] Time 0.039 (0.030) Data 0.002 (0.004) Loss 0.1010 (0.0987) Prec@1 83.000 (81.917) Prec@5 99.000 (99.250) +2022-11-14 13:33:35,792 Epoch: [59][120/500] Time 0.032 (0.031) Data 0.002 (0.004) Loss 0.1118 (0.0997) Prec@1 82.000 (81.923) Prec@5 97.000 (99.077) +2022-11-14 13:33:36,177 Epoch: [59][130/500] Time 0.031 (0.031) Data 0.002 (0.004) Loss 0.0984 (0.0996) Prec@1 81.000 (81.857) Prec@5 100.000 (99.143) +2022-11-14 13:33:36,541 Epoch: [59][140/500] Time 0.033 (0.031) Data 0.002 (0.004) Loss 0.0644 (0.0973) Prec@1 88.000 (82.267) Prec@5 100.000 (99.200) +2022-11-14 13:33:36,915 Epoch: [59][150/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0944 (0.0971) Prec@1 87.000 (82.562) Prec@5 97.000 (99.062) +2022-11-14 13:33:37,284 Epoch: [59][160/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.1261 (0.0988) Prec@1 80.000 (82.412) Prec@5 100.000 (99.118) +2022-11-14 13:33:37,653 Epoch: [59][170/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.1118 (0.0995) Prec@1 82.000 (82.389) Prec@5 99.000 (99.111) +2022-11-14 13:33:38,025 Epoch: [59][180/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0749 (0.0982) Prec@1 86.000 (82.579) Prec@5 99.000 (99.105) +2022-11-14 13:33:38,391 Epoch: [59][190/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0920 (0.0979) Prec@1 84.000 (82.650) Prec@5 99.000 (99.100) +2022-11-14 13:33:38,762 Epoch: [59][200/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0809 (0.0971) Prec@1 89.000 (82.952) Prec@5 98.000 (99.048) +2022-11-14 13:33:39,134 Epoch: [59][210/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0902 (0.0968) Prec@1 85.000 (83.045) Prec@5 99.000 (99.045) +2022-11-14 13:33:39,505 Epoch: [59][220/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.1378 (0.0986) Prec@1 75.000 (82.696) Prec@5 99.000 (99.043) +2022-11-14 13:33:39,876 Epoch: [59][230/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.1217 (0.0995) Prec@1 77.000 (82.458) Prec@5 100.000 (99.083) +2022-11-14 13:33:40,254 Epoch: [59][240/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.1218 (0.1004) Prec@1 79.000 (82.320) Prec@5 97.000 (99.000) +2022-11-14 13:33:40,630 Epoch: [59][250/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0899 (0.1000) Prec@1 86.000 (82.462) Prec@5 99.000 (99.000) +2022-11-14 13:33:41,009 Epoch: [59][260/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0615 (0.0986) Prec@1 90.000 (82.741) Prec@5 99.000 (99.000) +2022-11-14 13:33:41,376 Epoch: [59][270/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0609 (0.0972) Prec@1 89.000 (82.964) Prec@5 99.000 (99.000) +2022-11-14 13:33:41,759 Epoch: [59][280/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.1073 (0.0976) Prec@1 81.000 (82.897) Prec@5 99.000 (99.000) +2022-11-14 13:33:42,134 Epoch: [59][290/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.1545 (0.0995) Prec@1 75.000 (82.633) Prec@5 97.000 (98.933) +2022-11-14 13:33:42,504 Epoch: [59][300/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0882 (0.0991) Prec@1 87.000 (82.774) Prec@5 100.000 (98.968) +2022-11-14 13:33:42,889 Epoch: [59][310/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0949 (0.0990) Prec@1 85.000 (82.844) Prec@5 99.000 (98.969) +2022-11-14 13:33:43,266 Epoch: [59][320/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.1042 (0.0991) Prec@1 82.000 (82.818) Prec@5 99.000 (98.970) +2022-11-14 13:33:43,654 Epoch: [59][330/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0820 (0.0986) Prec@1 87.000 (82.941) Prec@5 96.000 (98.882) +2022-11-14 13:33:44,057 Epoch: [59][340/500] Time 0.051 (0.032) Data 0.002 (0.003) Loss 0.1084 (0.0989) Prec@1 79.000 (82.829) Prec@5 98.000 (98.857) +2022-11-14 13:33:44,407 Epoch: [59][350/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.1290 (0.0998) Prec@1 79.000 (82.722) Prec@5 98.000 (98.833) +2022-11-14 13:33:44,775 Epoch: [59][360/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.1373 (0.1008) Prec@1 74.000 (82.486) Prec@5 98.000 (98.811) +2022-11-14 13:33:45,151 Epoch: [59][370/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.1184 (0.1012) Prec@1 78.000 (82.368) Prec@5 100.000 (98.842) +2022-11-14 13:33:45,520 Epoch: [59][380/500] Time 0.037 (0.032) Data 0.001 (0.003) Loss 0.0595 (0.1002) Prec@1 91.000 (82.590) Prec@5 98.000 (98.821) +2022-11-14 13:33:45,903 Epoch: [59][390/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.1003 (0.1002) Prec@1 84.000 (82.625) Prec@5 99.000 (98.825) +2022-11-14 13:33:46,285 Epoch: [59][400/500] Time 0.036 (0.032) Data 0.001 (0.002) Loss 0.1043 (0.1003) Prec@1 80.000 (82.561) Prec@5 97.000 (98.780) +2022-11-14 13:33:46,669 Epoch: [59][410/500] Time 0.037 (0.032) Data 0.002 (0.002) Loss 0.1106 (0.1005) Prec@1 79.000 (82.476) Prec@5 98.000 (98.762) +2022-11-14 13:33:47,051 Epoch: [59][420/500] Time 0.034 (0.032) Data 0.001 (0.002) Loss 0.0839 (0.1001) Prec@1 83.000 (82.488) Prec@5 96.000 (98.698) +2022-11-14 13:33:47,428 Epoch: [59][430/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.1020 (0.1002) Prec@1 82.000 (82.477) Prec@5 100.000 (98.727) +2022-11-14 13:33:47,799 Epoch: [59][440/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0791 (0.0997) Prec@1 86.000 (82.556) Prec@5 98.000 (98.711) +2022-11-14 13:33:48,178 Epoch: [59][450/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0919 (0.0995) Prec@1 83.000 (82.565) Prec@5 99.000 (98.717) +2022-11-14 13:33:48,552 Epoch: [59][460/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0730 (0.0990) Prec@1 86.000 (82.638) Prec@5 98.000 (98.702) +2022-11-14 13:33:48,930 Epoch: [59][470/500] Time 0.031 (0.033) Data 0.002 (0.002) Loss 0.1189 (0.0994) Prec@1 79.000 (82.562) Prec@5 100.000 (98.729) +2022-11-14 13:33:49,307 Epoch: [59][480/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.1379 (0.1002) Prec@1 76.000 (82.429) Prec@5 100.000 (98.755) +2022-11-14 13:33:49,690 Epoch: [59][490/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.1232 (0.1006) Prec@1 79.000 (82.360) Prec@5 95.000 (98.680) +2022-11-14 13:33:50,035 Epoch: [59][499/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.1038 (0.1007) Prec@1 84.000 (82.392) Prec@5 98.000 (98.667) +2022-11-14 13:33:50,324 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1202 (0.1202) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:33:50,331 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1224 (0.1213) Prec@1 77.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:33:50,341 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1345 (0.1257) Prec@1 72.000 (76.000) Prec@5 98.000 (98.000) +2022-11-14 13:33:50,351 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1459 (0.1307) Prec@1 74.000 (75.500) Prec@5 97.000 (97.750) +2022-11-14 13:33:50,361 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1499 (0.1346) Prec@1 70.000 (74.400) Prec@5 100.000 (98.200) +2022-11-14 13:33:50,369 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.1226) Prec@1 88.000 (76.667) Prec@5 100.000 (98.500) +2022-11-14 13:33:50,377 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.1222) Prec@1 77.000 (76.714) Prec@5 97.000 (98.286) +2022-11-14 13:33:50,390 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1588 (0.1268) Prec@1 74.000 (76.375) Prec@5 95.000 (97.875) +2022-11-14 13:33:50,397 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1576 (0.1302) Prec@1 74.000 (76.111) Prec@5 98.000 (97.889) +2022-11-14 13:33:50,405 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.1300) Prec@1 73.000 (75.800) Prec@5 99.000 (98.000) +2022-11-14 13:33:50,415 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.1280) Prec@1 83.000 (76.455) Prec@5 100.000 (98.182) +2022-11-14 13:33:50,424 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.1260) Prec@1 86.000 (77.250) Prec@5 99.000 (98.250) +2022-11-14 13:33:50,433 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1246) Prec@1 81.000 (77.538) Prec@5 99.000 (98.308) +2022-11-14 13:33:50,443 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1236) Prec@1 83.000 (77.929) Prec@5 95.000 (98.071) +2022-11-14 13:33:50,452 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1332 (0.1242) Prec@1 75.000 (77.733) Prec@5 100.000 (98.200) +2022-11-14 13:33:50,461 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1490 (0.1257) Prec@1 75.000 (77.562) Prec@5 96.000 (98.062) +2022-11-14 13:33:50,471 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.1237) Prec@1 84.000 (77.941) Prec@5 97.000 (98.000) +2022-11-14 13:33:50,480 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1327 (0.1242) Prec@1 76.000 (77.833) Prec@5 98.000 (98.000) +2022-11-14 13:33:50,488 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1382 (0.1249) Prec@1 76.000 (77.737) Prec@5 96.000 (97.895) +2022-11-14 13:33:50,497 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1787 (0.1276) Prec@1 73.000 (77.500) Prec@5 95.000 (97.750) +2022-11-14 13:33:50,506 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1535 (0.1289) Prec@1 71.000 (77.190) Prec@5 99.000 (97.810) +2022-11-14 13:33:50,515 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1284) Prec@1 78.000 (77.227) Prec@5 97.000 (97.773) +2022-11-14 13:33:50,523 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1252 (0.1283) Prec@1 83.000 (77.478) Prec@5 99.000 (97.826) +2022-11-14 13:33:50,533 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1287) Prec@1 76.000 (77.417) Prec@5 100.000 (97.917) +2022-11-14 13:33:50,542 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1396 (0.1291) Prec@1 76.000 (77.360) Prec@5 98.000 (97.920) +2022-11-14 13:33:50,551 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1705 (0.1307) Prec@1 70.000 (77.077) Prec@5 94.000 (97.769) +2022-11-14 13:33:50,561 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1302) Prec@1 82.000 (77.259) Prec@5 99.000 (97.815) +2022-11-14 13:33:50,571 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.1297) Prec@1 78.000 (77.286) Prec@5 100.000 (97.893) +2022-11-14 13:33:50,580 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1292) Prec@1 79.000 (77.345) Prec@5 97.000 (97.862) +2022-11-14 13:33:50,590 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1295) Prec@1 75.000 (77.267) Prec@5 98.000 (97.867) +2022-11-14 13:33:50,598 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1527 (0.1303) Prec@1 74.000 (77.161) Prec@5 99.000 (97.903) +2022-11-14 13:33:50,606 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1332 (0.1304) Prec@1 76.000 (77.125) Prec@5 98.000 (97.906) +2022-11-14 13:33:50,614 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1297 (0.1303) Prec@1 78.000 (77.152) Prec@5 96.000 (97.848) +2022-11-14 13:33:50,622 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1613 (0.1313) Prec@1 71.000 (76.971) Prec@5 97.000 (97.824) +2022-11-14 13:33:50,630 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1344 (0.1313) Prec@1 76.000 (76.943) Prec@5 97.000 (97.800) +2022-11-14 13:33:50,640 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1298 (0.1313) Prec@1 79.000 (77.000) Prec@5 99.000 (97.833) +2022-11-14 13:33:50,648 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1354 (0.1314) Prec@1 80.000 (77.081) Prec@5 97.000 (97.811) +2022-11-14 13:33:50,658 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1567 (0.1321) Prec@1 73.000 (76.974) Prec@5 99.000 (97.842) +2022-11-14 13:33:50,667 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1142 (0.1316) Prec@1 82.000 (77.103) Prec@5 98.000 (97.846) +2022-11-14 13:33:50,676 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.1311) Prec@1 83.000 (77.250) Prec@5 99.000 (97.875) +2022-11-14 13:33:50,686 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1207 (0.1308) Prec@1 80.000 (77.317) Prec@5 98.000 (97.878) +2022-11-14 13:33:50,695 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.1299) Prec@1 84.000 (77.476) Prec@5 99.000 (97.905) +2022-11-14 13:33:50,704 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1184 (0.1297) Prec@1 78.000 (77.488) Prec@5 99.000 (97.930) +2022-11-14 13:33:50,714 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1313 (0.1297) Prec@1 76.000 (77.455) Prec@5 97.000 (97.909) +2022-11-14 13:33:50,723 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1407 (0.1300) Prec@1 75.000 (77.400) Prec@5 98.000 (97.911) +2022-11-14 13:33:50,732 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1554 (0.1305) Prec@1 74.000 (77.326) Prec@5 99.000 (97.935) +2022-11-14 13:33:50,741 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1250 (0.1304) Prec@1 81.000 (77.404) Prec@5 99.000 (97.957) +2022-11-14 13:33:50,751 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1332 (0.1304) Prec@1 73.000 (77.312) Prec@5 98.000 (97.958) +2022-11-14 13:33:50,760 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.1301) Prec@1 79.000 (77.347) Prec@5 98.000 (97.959) +2022-11-14 13:33:50,769 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1453 (0.1304) Prec@1 77.000 (77.340) Prec@5 99.000 (97.980) +2022-11-14 13:33:50,778 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.1300) Prec@1 80.000 (77.392) Prec@5 97.000 (97.961) +2022-11-14 13:33:50,787 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1098 (0.1296) Prec@1 83.000 (77.500) Prec@5 99.000 (97.981) +2022-11-14 13:33:50,796 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1192 (0.1294) Prec@1 77.000 (77.491) Prec@5 100.000 (98.019) +2022-11-14 13:33:50,806 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1355 (0.1295) Prec@1 79.000 (77.519) Prec@5 97.000 (98.000) +2022-11-14 13:33:50,815 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1356 (0.1297) Prec@1 77.000 (77.509) Prec@5 99.000 (98.018) +2022-11-14 13:33:50,825 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1400 (0.1298) Prec@1 76.000 (77.482) Prec@5 97.000 (98.000) +2022-11-14 13:33:50,834 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1523 (0.1302) Prec@1 72.000 (77.386) Prec@5 99.000 (98.018) +2022-11-14 13:33:50,842 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.1301) Prec@1 78.000 (77.397) Prec@5 98.000 (98.017) +2022-11-14 13:33:50,852 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1708 (0.1307) Prec@1 71.000 (77.288) Prec@5 99.000 (98.034) +2022-11-14 13:33:50,862 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.1304) Prec@1 81.000 (77.350) Prec@5 99.000 (98.050) +2022-11-14 13:33:50,871 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1237 (0.1303) Prec@1 81.000 (77.410) Prec@5 100.000 (98.082) +2022-11-14 13:33:50,880 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1542 (0.1307) Prec@1 74.000 (77.355) Prec@5 98.000 (98.081) +2022-11-14 13:33:50,889 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1152 (0.1304) Prec@1 81.000 (77.413) Prec@5 99.000 (98.095) +2022-11-14 13:33:50,897 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1122 (0.1301) Prec@1 79.000 (77.438) Prec@5 98.000 (98.094) +2022-11-14 13:33:50,905 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1364 (0.1302) Prec@1 75.000 (77.400) Prec@5 96.000 (98.062) +2022-11-14 13:33:50,912 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1463 (0.1305) Prec@1 71.000 (77.303) Prec@5 98.000 (98.061) +2022-11-14 13:33:50,921 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.1301) Prec@1 80.000 (77.343) Prec@5 99.000 (98.075) +2022-11-14 13:33:50,933 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1288 (0.1301) Prec@1 77.000 (77.338) Prec@5 99.000 (98.088) +2022-11-14 13:33:50,944 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.1299) Prec@1 81.000 (77.391) Prec@5 98.000 (98.087) +2022-11-14 13:33:50,957 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1566 (0.1302) Prec@1 71.000 (77.300) Prec@5 95.000 (98.043) +2022-11-14 13:33:50,969 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1329 (0.1303) Prec@1 79.000 (77.324) Prec@5 99.000 (98.056) +2022-11-14 13:33:50,982 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1301 (0.1303) Prec@1 79.000 (77.347) Prec@5 98.000 (98.056) +2022-11-14 13:33:50,995 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1095 (0.1300) Prec@1 79.000 (77.370) Prec@5 100.000 (98.082) +2022-11-14 13:33:51,008 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1162 (0.1298) Prec@1 82.000 (77.432) Prec@5 99.000 (98.095) +2022-11-14 13:33:51,021 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1474 (0.1300) Prec@1 74.000 (77.387) Prec@5 97.000 (98.080) +2022-11-14 13:33:51,035 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1320 (0.1301) Prec@1 77.000 (77.382) Prec@5 97.000 (98.066) +2022-11-14 13:33:51,049 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1574 (0.1304) Prec@1 72.000 (77.312) Prec@5 97.000 (98.052) +2022-11-14 13:33:51,064 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1174 (0.1302) Prec@1 80.000 (77.346) Prec@5 97.000 (98.038) +2022-11-14 13:33:51,079 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1271 (0.1302) Prec@1 75.000 (77.316) Prec@5 99.000 (98.051) +2022-11-14 13:33:51,094 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1386 (0.1303) Prec@1 77.000 (77.312) Prec@5 97.000 (98.037) +2022-11-14 13:33:51,110 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1302 (0.1303) Prec@1 78.000 (77.321) Prec@5 99.000 (98.049) +2022-11-14 13:33:51,124 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1306 (0.1303) Prec@1 78.000 (77.329) Prec@5 99.000 (98.061) +2022-11-14 13:33:51,138 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1192 (0.1302) Prec@1 75.000 (77.301) Prec@5 99.000 (98.072) +2022-11-14 13:33:51,153 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1592 (0.1305) Prec@1 74.000 (77.262) Prec@5 96.000 (98.048) +2022-11-14 13:33:51,170 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1119 (0.1303) Prec@1 83.000 (77.329) Prec@5 97.000 (98.035) +2022-11-14 13:33:51,186 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1652 (0.1307) Prec@1 69.000 (77.233) Prec@5 97.000 (98.023) +2022-11-14 13:33:51,202 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1571 (0.1310) Prec@1 72.000 (77.172) Prec@5 99.000 (98.034) +2022-11-14 13:33:51,217 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.1311) Prec@1 71.000 (77.102) Prec@5 98.000 (98.034) +2022-11-14 13:33:51,233 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1312) Prec@1 77.000 (77.101) Prec@5 99.000 (98.045) +2022-11-14 13:33:51,248 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1324 (0.1312) Prec@1 77.000 (77.100) Prec@5 98.000 (98.044) +2022-11-14 13:33:51,264 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1311) Prec@1 80.000 (77.132) Prec@5 99.000 (98.055) +2022-11-14 13:33:51,280 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.1309) Prec@1 85.000 (77.217) Prec@5 98.000 (98.054) +2022-11-14 13:33:51,295 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1312) Prec@1 69.000 (77.129) Prec@5 97.000 (98.043) +2022-11-14 13:33:51,311 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1310) Prec@1 79.000 (77.149) Prec@5 100.000 (98.064) +2022-11-14 13:33:51,327 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.1310) Prec@1 76.000 (77.137) Prec@5 98.000 (98.063) +2022-11-14 13:33:51,341 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1309) Prec@1 79.000 (77.156) Prec@5 98.000 (98.062) +2022-11-14 13:33:51,356 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.1304) Prec@1 85.000 (77.237) Prec@5 99.000 (98.072) +2022-11-14 13:33:51,371 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1588 (0.1307) Prec@1 71.000 (77.173) Prec@5 97.000 (98.061) +2022-11-14 13:33:51,386 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1474 (0.1309) Prec@1 74.000 (77.141) Prec@5 100.000 (98.081) +2022-11-14 13:33:51,403 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1327 (0.1309) Prec@1 78.000 (77.150) Prec@5 99.000 (98.090) +2022-11-14 13:33:51,460 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:33:51,769 Epoch: [60][0/500] Time 0.024 (0.024) Data 0.225 (0.225) Loss 0.1190 (0.1190) Prec@1 78.000 (78.000) Prec@5 99.000 (99.000) +2022-11-14 13:33:52,010 Epoch: [60][10/500] Time 0.023 (0.021) Data 0.002 (0.022) Loss 0.0927 (0.1058) Prec@1 83.000 (80.500) Prec@5 99.000 (99.000) +2022-11-14 13:33:52,276 Epoch: [60][20/500] Time 0.024 (0.022) Data 0.002 (0.012) Loss 0.1079 (0.1065) Prec@1 78.000 (79.667) Prec@5 99.000 (99.000) +2022-11-14 13:33:52,550 Epoch: [60][30/500] Time 0.024 (0.023) Data 0.002 (0.009) Loss 0.0918 (0.1028) Prec@1 82.000 (80.250) Prec@5 99.000 (99.000) +2022-11-14 13:33:53,051 Epoch: [60][40/500] Time 0.049 (0.028) Data 0.002 (0.007) Loss 0.0956 (0.1014) Prec@1 84.000 (81.000) Prec@5 100.000 (99.200) +2022-11-14 13:33:53,513 Epoch: [60][50/500] Time 0.044 (0.031) Data 0.002 (0.006) Loss 0.0819 (0.0981) Prec@1 85.000 (81.667) Prec@5 99.000 (99.167) +2022-11-14 13:33:53,985 Epoch: [60][60/500] Time 0.046 (0.033) Data 0.002 (0.005) Loss 0.1003 (0.0985) Prec@1 83.000 (81.857) Prec@5 99.000 (99.143) +2022-11-14 13:33:54,481 Epoch: [60][70/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0887 (0.0972) Prec@1 87.000 (82.500) Prec@5 98.000 (99.000) +2022-11-14 13:33:54,978 Epoch: [60][80/500] Time 0.051 (0.036) Data 0.002 (0.005) Loss 0.0913 (0.0966) Prec@1 88.000 (83.111) Prec@5 99.000 (99.000) +2022-11-14 13:33:55,449 Epoch: [60][90/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.1018 (0.0971) Prec@1 83.000 (83.100) Prec@5 100.000 (99.100) +2022-11-14 13:33:55,920 Epoch: [60][100/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0897 (0.0964) Prec@1 83.000 (83.091) Prec@5 98.000 (99.000) +2022-11-14 13:33:56,388 Epoch: [60][110/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.1055 (0.0972) Prec@1 81.000 (82.917) Prec@5 100.000 (99.083) +2022-11-14 13:33:56,869 Epoch: [60][120/500] Time 0.054 (0.038) Data 0.002 (0.004) Loss 0.0895 (0.0966) Prec@1 84.000 (83.000) Prec@5 99.000 (99.077) +2022-11-14 13:33:57,350 Epoch: [60][130/500] Time 0.051 (0.038) Data 0.002 (0.004) Loss 0.1179 (0.0981) Prec@1 82.000 (82.929) Prec@5 97.000 (98.929) +2022-11-14 13:33:57,842 Epoch: [60][140/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0716 (0.0963) Prec@1 87.000 (83.200) Prec@5 99.000 (98.933) +2022-11-14 13:33:58,312 Epoch: [60][150/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0709 (0.0948) Prec@1 89.000 (83.562) Prec@5 99.000 (98.938) +2022-11-14 13:33:58,794 Epoch: [60][160/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0800 (0.0939) Prec@1 88.000 (83.824) Prec@5 98.000 (98.882) +2022-11-14 13:33:59,281 Epoch: [60][170/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0845 (0.0934) Prec@1 84.000 (83.833) Prec@5 98.000 (98.833) +2022-11-14 13:33:59,794 Epoch: [60][180/500] Time 0.054 (0.040) Data 0.002 (0.003) Loss 0.0840 (0.0929) Prec@1 86.000 (83.947) Prec@5 99.000 (98.842) +2022-11-14 13:34:00,307 Epoch: [60][190/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.1035 (0.0934) Prec@1 83.000 (83.900) Prec@5 100.000 (98.900) +2022-11-14 13:34:00,795 Epoch: [60][200/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.1112 (0.0943) Prec@1 78.000 (83.619) Prec@5 97.000 (98.810) +2022-11-14 13:34:01,266 Epoch: [60][210/500] Time 0.045 (0.040) Data 0.001 (0.003) Loss 0.1084 (0.0949) Prec@1 80.000 (83.455) Prec@5 99.000 (98.818) +2022-11-14 13:34:01,753 Epoch: [60][220/500] Time 0.042 (0.040) Data 0.003 (0.003) Loss 0.0951 (0.0949) Prec@1 83.000 (83.435) Prec@5 99.000 (98.826) +2022-11-14 13:34:02,234 Epoch: [60][230/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0813 (0.0943) Prec@1 86.000 (83.542) Prec@5 98.000 (98.792) +2022-11-14 13:34:02,721 Epoch: [60][240/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.1081 (0.0949) Prec@1 81.000 (83.440) Prec@5 100.000 (98.840) +2022-11-14 13:34:03,208 Epoch: [60][250/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.1038 (0.0952) Prec@1 81.000 (83.346) Prec@5 99.000 (98.846) +2022-11-14 13:34:03,691 Epoch: [60][260/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.1128 (0.0959) Prec@1 81.000 (83.259) Prec@5 97.000 (98.778) +2022-11-14 13:34:04,170 Epoch: [60][270/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0926 (0.0958) Prec@1 84.000 (83.286) Prec@5 96.000 (98.679) +2022-11-14 13:34:04,652 Epoch: [60][280/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0719 (0.0949) Prec@1 89.000 (83.483) Prec@5 100.000 (98.724) +2022-11-14 13:34:05,158 Epoch: [60][290/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.1112 (0.0955) Prec@1 80.000 (83.367) Prec@5 99.000 (98.733) +2022-11-14 13:34:05,633 Epoch: [60][300/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0975 (0.0956) Prec@1 83.000 (83.355) Prec@5 99.000 (98.742) +2022-11-14 13:34:06,121 Epoch: [60][310/500] Time 0.044 (0.041) Data 0.001 (0.003) Loss 0.0793 (0.0950) Prec@1 86.000 (83.438) Prec@5 99.000 (98.750) +2022-11-14 13:34:06,599 Epoch: [60][320/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0921 (0.0950) Prec@1 86.000 (83.515) Prec@5 99.000 (98.758) +2022-11-14 13:34:07,097 Epoch: [60][330/500] Time 0.063 (0.041) Data 0.002 (0.003) Loss 0.1267 (0.0959) Prec@1 76.000 (83.294) Prec@5 98.000 (98.735) +2022-11-14 13:34:07,592 Epoch: [60][340/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.1122 (0.0964) Prec@1 81.000 (83.229) Prec@5 100.000 (98.771) +2022-11-14 13:34:08,095 Epoch: [60][350/500] Time 0.046 (0.042) Data 0.002 (0.002) Loss 0.1146 (0.0969) Prec@1 82.000 (83.194) Prec@5 98.000 (98.750) +2022-11-14 13:34:08,554 Epoch: [60][360/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0933 (0.0968) Prec@1 85.000 (83.243) Prec@5 100.000 (98.784) +2022-11-14 13:34:09,028 Epoch: [60][370/500] Time 0.041 (0.042) Data 0.002 (0.002) Loss 0.1019 (0.0969) Prec@1 84.000 (83.263) Prec@5 98.000 (98.763) +2022-11-14 13:34:09,503 Epoch: [60][380/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0866 (0.0966) Prec@1 85.000 (83.308) Prec@5 100.000 (98.795) +2022-11-14 13:34:10,045 Epoch: [60][390/500] Time 0.060 (0.042) Data 0.003 (0.002) Loss 0.1048 (0.0968) Prec@1 81.000 (83.250) Prec@5 99.000 (98.800) +2022-11-14 13:34:10,533 Epoch: [60][400/500] Time 0.050 (0.042) Data 0.002 (0.002) Loss 0.0963 (0.0968) Prec@1 85.000 (83.293) Prec@5 100.000 (98.829) +2022-11-14 13:34:10,888 Epoch: [60][410/500] Time 0.031 (0.042) Data 0.002 (0.002) Loss 0.0872 (0.0966) Prec@1 86.000 (83.357) Prec@5 100.000 (98.857) +2022-11-14 13:34:11,199 Epoch: [60][420/500] Time 0.030 (0.041) Data 0.002 (0.002) Loss 0.0908 (0.0965) Prec@1 86.000 (83.419) Prec@5 97.000 (98.814) +2022-11-14 13:34:11,536 Epoch: [60][430/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0751 (0.0960) Prec@1 87.000 (83.500) Prec@5 99.000 (98.818) +2022-11-14 13:34:11,828 Epoch: [60][440/500] Time 0.028 (0.041) Data 0.002 (0.002) Loss 0.0933 (0.0959) Prec@1 86.000 (83.556) Prec@5 98.000 (98.800) +2022-11-14 13:34:12,125 Epoch: [60][450/500] Time 0.034 (0.040) Data 0.002 (0.002) Loss 0.0866 (0.0957) Prec@1 87.000 (83.630) Prec@5 99.000 (98.804) +2022-11-14 13:34:12,428 Epoch: [60][460/500] Time 0.027 (0.040) Data 0.002 (0.002) Loss 0.1159 (0.0961) Prec@1 78.000 (83.511) Prec@5 98.000 (98.787) +2022-11-14 13:34:12,732 Epoch: [60][470/500] Time 0.028 (0.040) Data 0.002 (0.002) Loss 0.0808 (0.0958) Prec@1 85.000 (83.542) Prec@5 98.000 (98.771) +2022-11-14 13:34:13,034 Epoch: [60][480/500] Time 0.025 (0.039) Data 0.002 (0.002) Loss 0.0976 (0.0959) Prec@1 84.000 (83.551) Prec@5 99.000 (98.776) +2022-11-14 13:34:13,352 Epoch: [60][490/500] Time 0.026 (0.039) Data 0.002 (0.002) Loss 0.1061 (0.0961) Prec@1 81.000 (83.500) Prec@5 99.000 (98.780) +2022-11-14 13:34:13,625 Epoch: [60][499/500] Time 0.028 (0.039) Data 0.002 (0.002) Loss 0.0770 (0.0957) Prec@1 86.000 (83.549) Prec@5 99.000 (98.784) +2022-11-14 13:34:13,924 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0893 (0.0893) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:34:13,937 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1017 (0.0955) Prec@1 82.000 (82.500) Prec@5 99.000 (99.500) +2022-11-14 13:34:13,946 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1386 (0.1099) Prec@1 74.000 (79.667) Prec@5 100.000 (99.667) +2022-11-14 13:34:13,961 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1171 (0.1117) Prec@1 81.000 (80.000) Prec@5 99.000 (99.500) +2022-11-14 13:34:13,971 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1196 (0.1133) Prec@1 80.000 (80.000) Prec@5 100.000 (99.600) +2022-11-14 13:34:13,980 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0764 (0.1071) Prec@1 85.000 (80.833) Prec@5 100.000 (99.667) +2022-11-14 13:34:13,988 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1040 (0.1067) Prec@1 81.000 (80.857) Prec@5 99.000 (99.571) +2022-11-14 13:34:14,002 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1222 (0.1086) Prec@1 79.000 (80.625) Prec@5 98.000 (99.375) +2022-11-14 13:34:14,012 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1198 (0.1099) Prec@1 81.000 (80.667) Prec@5 100.000 (99.444) +2022-11-14 13:34:14,020 Test: [9/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.1091) Prec@1 82.000 (80.800) Prec@5 99.000 (99.400) +2022-11-14 13:34:14,028 Test: [10/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1139 (0.1095) Prec@1 81.000 (80.818) Prec@5 99.000 (99.364) +2022-11-14 13:34:14,040 Test: [11/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1262 (0.1109) Prec@1 77.000 (80.500) Prec@5 97.000 (99.167) +2022-11-14 13:34:14,052 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1214 (0.1117) Prec@1 77.000 (80.231) Prec@5 97.000 (99.000) +2022-11-14 13:34:14,062 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.1109) Prec@1 84.000 (80.500) Prec@5 98.000 (98.929) +2022-11-14 13:34:14,070 Test: [14/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1115 (0.1110) Prec@1 81.000 (80.533) Prec@5 99.000 (98.933) +2022-11-14 13:34:14,083 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1405 (0.1128) Prec@1 74.000 (80.125) Prec@5 100.000 (99.000) +2022-11-14 13:34:14,094 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.1107) Prec@1 88.000 (80.588) Prec@5 98.000 (98.941) +2022-11-14 13:34:14,104 Test: [17/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.1108) Prec@1 82.000 (80.667) Prec@5 99.000 (98.944) +2022-11-14 13:34:14,113 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1147 (0.1110) Prec@1 78.000 (80.526) Prec@5 97.000 (98.842) +2022-11-14 13:34:14,125 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1369 (0.1123) Prec@1 76.000 (80.300) Prec@5 99.000 (98.850) +2022-11-14 13:34:14,136 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1147 (0.1124) Prec@1 82.000 (80.381) Prec@5 99.000 (98.857) +2022-11-14 13:34:14,149 Test: [21/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1186 (0.1127) Prec@1 78.000 (80.273) Prec@5 97.000 (98.773) +2022-11-14 13:34:14,160 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1172 (0.1129) Prec@1 82.000 (80.348) Prec@5 98.000 (98.739) +2022-11-14 13:34:14,169 Test: [23/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1155 (0.1130) Prec@1 80.000 (80.333) Prec@5 99.000 (98.750) +2022-11-14 13:34:14,179 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1217 (0.1134) Prec@1 80.000 (80.320) Prec@5 100.000 (98.800) +2022-11-14 13:34:14,190 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1437 (0.1145) Prec@1 76.000 (80.154) Prec@5 97.000 (98.731) +2022-11-14 13:34:14,201 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.1140) Prec@1 80.000 (80.148) Prec@5 98.000 (98.704) +2022-11-14 13:34:14,209 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.1132) Prec@1 83.000 (80.250) Prec@5 100.000 (98.750) +2022-11-14 13:34:14,218 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.1125) Prec@1 86.000 (80.448) Prec@5 99.000 (98.759) +2022-11-14 13:34:14,230 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1222 (0.1129) Prec@1 80.000 (80.433) Prec@5 98.000 (98.733) +2022-11-14 13:34:14,240 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1360 (0.1136) Prec@1 76.000 (80.290) Prec@5 99.000 (98.742) +2022-11-14 13:34:14,250 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.1133) Prec@1 83.000 (80.375) Prec@5 100.000 (98.781) +2022-11-14 13:34:14,259 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1223 (0.1135) Prec@1 77.000 (80.273) Prec@5 100.000 (98.818) +2022-11-14 13:34:14,271 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1674 (0.1151) Prec@1 71.000 (80.000) Prec@5 97.000 (98.765) +2022-11-14 13:34:14,281 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1266 (0.1154) Prec@1 79.000 (79.971) Prec@5 97.000 (98.714) +2022-11-14 13:34:14,292 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1245 (0.1157) Prec@1 76.000 (79.861) Prec@5 98.000 (98.694) +2022-11-14 13:34:14,300 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.1156) Prec@1 79.000 (79.838) Prec@5 97.000 (98.649) +2022-11-14 13:34:14,312 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1370 (0.1162) Prec@1 77.000 (79.763) Prec@5 98.000 (98.632) +2022-11-14 13:34:14,323 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.1152) Prec@1 89.000 (80.000) Prec@5 98.000 (98.615) +2022-11-14 13:34:14,333 Test: [39/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.1152) Prec@1 81.000 (80.025) Prec@5 96.000 (98.550) +2022-11-14 13:34:14,341 Test: [40/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1201 (0.1153) Prec@1 82.000 (80.073) Prec@5 98.000 (98.537) +2022-11-14 13:34:14,352 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.1147) Prec@1 87.000 (80.238) Prec@5 98.000 (98.524) +2022-11-14 13:34:14,363 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.1141) Prec@1 82.000 (80.279) Prec@5 99.000 (98.535) +2022-11-14 13:34:14,371 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.1134) Prec@1 86.000 (80.409) Prec@5 99.000 (98.545) +2022-11-14 13:34:14,380 Test: [44/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.1134) Prec@1 81.000 (80.422) Prec@5 100.000 (98.578) +2022-11-14 13:34:14,392 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.1134) Prec@1 81.000 (80.435) Prec@5 99.000 (98.587) +2022-11-14 13:34:14,403 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.1134) Prec@1 82.000 (80.468) Prec@5 98.000 (98.574) +2022-11-14 13:34:14,411 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1252 (0.1136) Prec@1 80.000 (80.458) Prec@5 100.000 (98.604) +2022-11-14 13:34:14,420 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.1128) Prec@1 84.000 (80.531) Prec@5 100.000 (98.633) +2022-11-14 13:34:14,432 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1255 (0.1131) Prec@1 78.000 (80.480) Prec@5 99.000 (98.640) +2022-11-14 13:34:14,443 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.1131) Prec@1 82.000 (80.510) Prec@5 99.000 (98.647) +2022-11-14 13:34:14,453 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1473 (0.1137) Prec@1 73.000 (80.365) Prec@5 98.000 (98.635) +2022-11-14 13:34:14,463 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1095 (0.1136) Prec@1 81.000 (80.377) Prec@5 99.000 (98.642) +2022-11-14 13:34:14,474 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.1133) Prec@1 82.000 (80.407) Prec@5 98.000 (98.630) +2022-11-14 13:34:14,485 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1251 (0.1135) Prec@1 78.000 (80.364) Prec@5 97.000 (98.600) +2022-11-14 13:34:14,496 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.1131) Prec@1 86.000 (80.464) Prec@5 99.000 (98.607) +2022-11-14 13:34:14,508 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1278 (0.1134) Prec@1 77.000 (80.404) Prec@5 98.000 (98.596) +2022-11-14 13:34:14,519 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.1133) Prec@1 84.000 (80.466) Prec@5 98.000 (98.586) +2022-11-14 13:34:14,532 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1468 (0.1139) Prec@1 75.000 (80.373) Prec@5 100.000 (98.610) +2022-11-14 13:34:14,545 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.1137) Prec@1 85.000 (80.450) Prec@5 99.000 (98.617) +2022-11-14 13:34:14,555 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.1135) Prec@1 79.000 (80.426) Prec@5 100.000 (98.639) +2022-11-14 13:34:14,565 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.1134) Prec@1 82.000 (80.452) Prec@5 99.000 (98.645) +2022-11-14 13:34:14,575 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.1132) Prec@1 81.000 (80.460) Prec@5 99.000 (98.651) +2022-11-14 13:34:14,585 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.1127) Prec@1 84.000 (80.516) Prec@5 100.000 (98.672) +2022-11-14 13:34:14,596 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1320 (0.1130) Prec@1 80.000 (80.508) Prec@5 99.000 (98.677) +2022-11-14 13:34:14,605 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1298 (0.1133) Prec@1 79.000 (80.485) Prec@5 99.000 (98.682) +2022-11-14 13:34:14,615 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.1127) Prec@1 87.000 (80.582) Prec@5 99.000 (98.687) +2022-11-14 13:34:14,624 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.1125) Prec@1 83.000 (80.618) Prec@5 97.000 (98.662) +2022-11-14 13:34:14,633 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.1121) Prec@1 86.000 (80.696) Prec@5 100.000 (98.681) +2022-11-14 13:34:14,642 Test: [69/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.1121) Prec@1 82.000 (80.714) Prec@5 98.000 (98.671) +2022-11-14 13:34:14,651 Test: [70/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1377 (0.1124) Prec@1 75.000 (80.634) Prec@5 99.000 (98.676) +2022-11-14 13:34:14,660 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1208 (0.1125) Prec@1 78.000 (80.597) Prec@5 100.000 (98.694) +2022-11-14 13:34:14,669 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.1121) Prec@1 86.000 (80.671) Prec@5 99.000 (98.699) +2022-11-14 13:34:14,678 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1120 (0.1121) Prec@1 81.000 (80.676) Prec@5 100.000 (98.716) +2022-11-14 13:34:14,686 Test: [74/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1324 (0.1124) Prec@1 76.000 (80.613) Prec@5 99.000 (98.720) +2022-11-14 13:34:14,695 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1167 (0.1124) Prec@1 80.000 (80.605) Prec@5 99.000 (98.724) +2022-11-14 13:34:14,704 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1148 (0.1125) Prec@1 81.000 (80.610) Prec@5 99.000 (98.727) +2022-11-14 13:34:14,714 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.1121) Prec@1 86.000 (80.679) Prec@5 99.000 (98.731) +2022-11-14 13:34:14,723 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1207 (0.1122) Prec@1 79.000 (80.658) Prec@5 99.000 (98.734) +2022-11-14 13:34:14,732 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.1121) Prec@1 81.000 (80.662) Prec@5 99.000 (98.737) +2022-11-14 13:34:14,742 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1121) Prec@1 83.000 (80.691) Prec@5 98.000 (98.728) +2022-11-14 13:34:14,751 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.1119) Prec@1 85.000 (80.744) Prec@5 99.000 (98.732) +2022-11-14 13:34:14,761 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.1117) Prec@1 85.000 (80.795) Prec@5 99.000 (98.735) +2022-11-14 13:34:14,771 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1371 (0.1120) Prec@1 77.000 (80.750) Prec@5 97.000 (98.714) +2022-11-14 13:34:14,781 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.1119) Prec@1 82.000 (80.765) Prec@5 100.000 (98.729) +2022-11-14 13:34:14,790 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1253 (0.1121) Prec@1 79.000 (80.744) Prec@5 97.000 (98.709) +2022-11-14 13:34:14,800 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.1120) Prec@1 80.000 (80.736) Prec@5 98.000 (98.701) +2022-11-14 13:34:14,809 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.1119) Prec@1 81.000 (80.739) Prec@5 100.000 (98.716) +2022-11-14 13:34:14,820 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1136 (0.1119) Prec@1 77.000 (80.697) Prec@5 99.000 (98.719) +2022-11-14 13:34:14,830 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1100 (0.1119) Prec@1 81.000 (80.700) Prec@5 100.000 (98.733) +2022-11-14 13:34:14,840 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.1119) Prec@1 81.000 (80.703) Prec@5 100.000 (98.747) +2022-11-14 13:34:14,849 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.1115) Prec@1 86.000 (80.761) Prec@5 100.000 (98.761) +2022-11-14 13:34:14,858 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.1115) Prec@1 82.000 (80.774) Prec@5 97.000 (98.742) +2022-11-14 13:34:14,867 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.1115) Prec@1 81.000 (80.777) Prec@5 100.000 (98.755) +2022-11-14 13:34:14,876 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.1114) Prec@1 82.000 (80.789) Prec@5 99.000 (98.758) +2022-11-14 13:34:14,885 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1120 (0.1114) Prec@1 80.000 (80.781) Prec@5 98.000 (98.750) +2022-11-14 13:34:14,894 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.1111) Prec@1 88.000 (80.856) Prec@5 99.000 (98.753) +2022-11-14 13:34:14,904 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1311 (0.1113) Prec@1 77.000 (80.816) Prec@5 96.000 (98.724) +2022-11-14 13:34:14,912 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1295 (0.1115) Prec@1 77.000 (80.778) Prec@5 99.000 (98.727) +2022-11-14 13:34:14,922 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.1113) Prec@1 82.000 (80.790) Prec@5 99.000 (98.730) +2022-11-14 13:34:14,977 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:34:15,297 Epoch: [61][0/500] Time 0.037 (0.037) Data 0.226 (0.226) Loss 0.1111 (0.1111) Prec@1 78.000 (78.000) Prec@5 98.000 (98.000) +2022-11-14 13:34:15,514 Epoch: [61][10/500] Time 0.015 (0.021) Data 0.002 (0.022) Loss 0.0789 (0.0950) Prec@1 90.000 (84.000) Prec@5 99.000 (98.500) +2022-11-14 13:34:15,713 Epoch: [61][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0889 (0.0930) Prec@1 87.000 (85.000) Prec@5 99.000 (98.667) +2022-11-14 13:34:15,975 Epoch: [61][30/500] Time 0.029 (0.020) Data 0.002 (0.009) Loss 0.1145 (0.0984) Prec@1 79.000 (83.500) Prec@5 97.000 (98.250) +2022-11-14 13:34:16,388 Epoch: [61][40/500] Time 0.036 (0.024) Data 0.002 (0.007) Loss 0.1197 (0.1026) Prec@1 78.000 (82.400) Prec@5 96.000 (97.800) +2022-11-14 13:34:16,821 Epoch: [61][50/500] Time 0.047 (0.027) Data 0.002 (0.006) Loss 0.1061 (0.1032) Prec@1 83.000 (82.500) Prec@5 100.000 (98.167) +2022-11-14 13:34:17,249 Epoch: [61][60/500] Time 0.040 (0.029) Data 0.002 (0.006) Loss 0.0868 (0.1009) Prec@1 87.000 (83.143) Prec@5 99.000 (98.286) +2022-11-14 13:34:17,690 Epoch: [61][70/500] Time 0.045 (0.030) Data 0.002 (0.005) Loss 0.0592 (0.0956) Prec@1 90.000 (84.000) Prec@5 99.000 (98.375) +2022-11-14 13:34:18,118 Epoch: [61][80/500] Time 0.040 (0.031) Data 0.002 (0.005) Loss 0.1176 (0.0981) Prec@1 83.000 (83.889) Prec@5 97.000 (98.222) +2022-11-14 13:34:18,543 Epoch: [61][90/500] Time 0.038 (0.032) Data 0.003 (0.004) Loss 0.1092 (0.0992) Prec@1 82.000 (83.700) Prec@5 97.000 (98.100) +2022-11-14 13:34:18,978 Epoch: [61][100/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.1335 (0.1023) Prec@1 78.000 (83.182) Prec@5 97.000 (98.000) +2022-11-14 13:34:19,417 Epoch: [61][110/500] Time 0.045 (0.033) Data 0.002 (0.004) Loss 0.0940 (0.1016) Prec@1 85.000 (83.333) Prec@5 98.000 (98.000) +2022-11-14 13:34:19,842 Epoch: [61][120/500] Time 0.039 (0.034) Data 0.002 (0.004) Loss 0.1165 (0.1028) Prec@1 73.000 (82.538) Prec@5 98.000 (98.000) +2022-11-14 13:34:20,271 Epoch: [61][130/500] Time 0.039 (0.034) Data 0.002 (0.004) Loss 0.0666 (0.1002) Prec@1 91.000 (83.143) Prec@5 99.000 (98.071) +2022-11-14 13:34:20,698 Epoch: [61][140/500] Time 0.041 (0.034) Data 0.001 (0.004) Loss 0.0642 (0.0978) Prec@1 91.000 (83.667) Prec@5 99.000 (98.133) +2022-11-14 13:34:21,116 Epoch: [61][150/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.1298 (0.0998) Prec@1 77.000 (83.250) Prec@5 98.000 (98.125) +2022-11-14 13:34:21,545 Epoch: [61][160/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0837 (0.0988) Prec@1 87.000 (83.471) Prec@5 98.000 (98.118) +2022-11-14 13:34:21,974 Epoch: [61][170/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0651 (0.0970) Prec@1 91.000 (83.889) Prec@5 100.000 (98.222) +2022-11-14 13:34:22,408 Epoch: [61][180/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.1031 (0.0973) Prec@1 84.000 (83.895) Prec@5 100.000 (98.316) +2022-11-14 13:34:22,829 Epoch: [61][190/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0880 (0.0968) Prec@1 82.000 (83.800) Prec@5 100.000 (98.400) +2022-11-14 13:34:23,253 Epoch: [61][200/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0874 (0.0964) Prec@1 85.000 (83.857) Prec@5 99.000 (98.429) +2022-11-14 13:34:23,701 Epoch: [61][210/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0829 (0.0958) Prec@1 85.000 (83.909) Prec@5 99.000 (98.455) +2022-11-14 13:34:24,110 Epoch: [61][220/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.1083 (0.0963) Prec@1 80.000 (83.739) Prec@5 99.000 (98.478) +2022-11-14 13:34:24,543 Epoch: [61][230/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.1184 (0.0972) Prec@1 78.000 (83.500) Prec@5 99.000 (98.500) +2022-11-14 13:34:24,962 Epoch: [61][240/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.1030 (0.0975) Prec@1 81.000 (83.400) Prec@5 100.000 (98.560) +2022-11-14 13:34:25,386 Epoch: [61][250/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.1056 (0.0978) Prec@1 80.000 (83.269) Prec@5 98.000 (98.538) +2022-11-14 13:34:25,802 Epoch: [61][260/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.1302 (0.0990) Prec@1 79.000 (83.111) Prec@5 97.000 (98.481) +2022-11-14 13:34:26,220 Epoch: [61][270/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0558 (0.0974) Prec@1 91.000 (83.393) Prec@5 100.000 (98.536) +2022-11-14 13:34:26,639 Epoch: [61][280/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0980 (0.0975) Prec@1 82.000 (83.345) Prec@5 98.000 (98.517) +2022-11-14 13:34:27,044 Epoch: [61][290/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.1194 (0.0982) Prec@1 79.000 (83.200) Prec@5 97.000 (98.467) +2022-11-14 13:34:27,453 Epoch: [61][300/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0741 (0.0974) Prec@1 90.000 (83.419) Prec@5 99.000 (98.484) +2022-11-14 13:34:27,900 Epoch: [61][310/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0908 (0.0972) Prec@1 88.000 (83.562) Prec@5 98.000 (98.469) +2022-11-14 13:34:28,315 Epoch: [61][320/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0810 (0.0967) Prec@1 86.000 (83.636) Prec@5 99.000 (98.485) +2022-11-14 13:34:28,730 Epoch: [61][330/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0631 (0.0957) Prec@1 89.000 (83.794) Prec@5 100.000 (98.529) +2022-11-14 13:34:29,175 Epoch: [61][340/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0935 (0.0957) Prec@1 80.000 (83.686) Prec@5 99.000 (98.543) +2022-11-14 13:34:29,605 Epoch: [61][350/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.1180 (0.0963) Prec@1 79.000 (83.556) Prec@5 100.000 (98.583) +2022-11-14 13:34:30,020 Epoch: [61][360/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0936 (0.0962) Prec@1 83.000 (83.541) Prec@5 100.000 (98.622) +2022-11-14 13:34:30,455 Epoch: [61][370/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.1167 (0.0968) Prec@1 83.000 (83.526) Prec@5 100.000 (98.658) +2022-11-14 13:34:30,888 Epoch: [61][380/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.1036 (0.0969) Prec@1 81.000 (83.462) Prec@5 100.000 (98.692) +2022-11-14 13:34:31,308 Epoch: [61][390/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0853 (0.0966) Prec@1 85.000 (83.500) Prec@5 99.000 (98.700) +2022-11-14 13:34:31,738 Epoch: [61][400/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0959 (0.0966) Prec@1 81.000 (83.439) Prec@5 100.000 (98.732) +2022-11-14 13:34:32,182 Epoch: [61][410/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.1007 (0.0967) Prec@1 81.000 (83.381) Prec@5 100.000 (98.762) +2022-11-14 13:34:32,593 Epoch: [61][420/500] Time 0.050 (0.036) Data 0.002 (0.002) Loss 0.1040 (0.0969) Prec@1 80.000 (83.302) Prec@5 95.000 (98.674) +2022-11-14 13:34:33,014 Epoch: [61][430/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0937 (0.0968) Prec@1 85.000 (83.341) Prec@5 99.000 (98.682) +2022-11-14 13:34:33,436 Epoch: [61][440/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0885 (0.0966) Prec@1 85.000 (83.378) Prec@5 98.000 (98.667) +2022-11-14 13:34:33,851 Epoch: [61][450/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0870 (0.0964) Prec@1 82.000 (83.348) Prec@5 99.000 (98.674) +2022-11-14 13:34:34,283 Epoch: [61][460/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0835 (0.0961) Prec@1 86.000 (83.404) Prec@5 99.000 (98.681) +2022-11-14 13:34:34,703 Epoch: [61][470/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0893 (0.0960) Prec@1 84.000 (83.417) Prec@5 99.000 (98.688) +2022-11-14 13:34:35,122 Epoch: [61][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1306 (0.0967) Prec@1 76.000 (83.265) Prec@5 99.000 (98.694) +2022-11-14 13:34:35,551 Epoch: [61][490/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.1049 (0.0969) Prec@1 79.000 (83.180) Prec@5 99.000 (98.700) +2022-11-14 13:34:35,933 Epoch: [61][499/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.0903 (0.0967) Prec@1 85.000 (83.216) Prec@5 98.000 (98.686) +2022-11-14 13:34:36,217 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0924) Prec@1 82.000 (82.000) Prec@5 99.000 (99.000) +2022-11-14 13:34:36,225 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0992) Prec@1 83.000 (82.500) Prec@5 98.000 (98.500) +2022-11-14 13:34:36,234 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.1033) Prec@1 82.000 (82.333) Prec@5 100.000 (99.000) +2022-11-14 13:34:36,246 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1226 (0.1082) Prec@1 78.000 (81.250) Prec@5 98.000 (98.750) +2022-11-14 13:34:36,255 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.1108) Prec@1 80.000 (81.000) Prec@5 100.000 (99.000) +2022-11-14 13:34:36,264 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.1034) Prec@1 87.000 (82.000) Prec@5 100.000 (99.167) +2022-11-14 13:34:36,271 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.1015) Prec@1 86.000 (82.571) Prec@5 100.000 (99.286) +2022-11-14 13:34:36,281 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1363 (0.1058) Prec@1 76.000 (81.750) Prec@5 99.000 (99.250) +2022-11-14 13:34:36,290 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1215 (0.1076) Prec@1 81.000 (81.667) Prec@5 100.000 (99.333) +2022-11-14 13:34:36,299 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.1070) Prec@1 82.000 (81.700) Prec@5 98.000 (99.200) +2022-11-14 13:34:36,308 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.1048) Prec@1 86.000 (82.091) Prec@5 99.000 (99.182) +2022-11-14 13:34:36,318 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.1042) Prec@1 82.000 (82.083) Prec@5 99.000 (99.167) +2022-11-14 13:34:36,327 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1235 (0.1056) Prec@1 80.000 (81.923) Prec@5 99.000 (99.154) +2022-11-14 13:34:36,337 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.1061) Prec@1 81.000 (81.857) Prec@5 99.000 (99.143) +2022-11-14 13:34:36,347 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.1057) Prec@1 83.000 (81.933) Prec@5 99.000 (99.133) +2022-11-14 13:34:36,355 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.1061) Prec@1 84.000 (82.062) Prec@5 99.000 (99.125) +2022-11-14 13:34:36,364 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.1055) Prec@1 85.000 (82.235) Prec@5 99.000 (99.118) +2022-11-14 13:34:36,373 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.1058) Prec@1 79.000 (82.056) Prec@5 99.000 (99.111) +2022-11-14 13:34:36,381 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.1059) Prec@1 83.000 (82.105) Prec@5 96.000 (98.947) +2022-11-14 13:34:36,390 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1059) Prec@1 84.000 (82.200) Prec@5 99.000 (98.950) +2022-11-14 13:34:36,400 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1505 (0.1080) Prec@1 76.000 (81.905) Prec@5 98.000 (98.905) +2022-11-14 13:34:36,410 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.1075) Prec@1 84.000 (82.000) Prec@5 98.000 (98.864) +2022-11-14 13:34:36,419 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.1088) Prec@1 78.000 (81.826) Prec@5 98.000 (98.826) +2022-11-14 13:34:36,430 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.1089) Prec@1 81.000 (81.792) Prec@5 99.000 (98.833) +2022-11-14 13:34:36,440 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1268 (0.1096) Prec@1 80.000 (81.720) Prec@5 99.000 (98.840) +2022-11-14 13:34:36,450 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1719 (0.1120) Prec@1 70.000 (81.269) Prec@5 98.000 (98.808) +2022-11-14 13:34:36,460 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.1115) Prec@1 85.000 (81.407) Prec@5 100.000 (98.852) +2022-11-14 13:34:36,470 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1118) Prec@1 80.000 (81.357) Prec@5 97.000 (98.786) +2022-11-14 13:34:36,480 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1309 (0.1124) Prec@1 78.000 (81.241) Prec@5 97.000 (98.724) +2022-11-14 13:34:36,489 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1326 (0.1131) Prec@1 80.000 (81.200) Prec@5 97.000 (98.667) +2022-11-14 13:34:36,499 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1133) Prec@1 77.000 (81.065) Prec@5 98.000 (98.645) +2022-11-14 13:34:36,509 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.1132) Prec@1 82.000 (81.094) Prec@5 98.000 (98.625) +2022-11-14 13:34:36,519 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.1133) Prec@1 79.000 (81.030) Prec@5 98.000 (98.606) +2022-11-14 13:34:36,529 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1141) Prec@1 77.000 (80.912) Prec@5 97.000 (98.559) +2022-11-14 13:34:36,539 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1141) Prec@1 79.000 (80.857) Prec@5 97.000 (98.514) +2022-11-14 13:34:36,549 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.1135) Prec@1 85.000 (80.972) Prec@5 98.000 (98.500) +2022-11-14 13:34:36,557 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.1137) Prec@1 78.000 (80.892) Prec@5 95.000 (98.405) +2022-11-14 13:34:36,567 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1138) Prec@1 78.000 (80.816) Prec@5 98.000 (98.395) +2022-11-14 13:34:36,577 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.1131) Prec@1 87.000 (80.974) Prec@5 100.000 (98.436) +2022-11-14 13:34:36,586 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1135) Prec@1 78.000 (80.900) Prec@5 100.000 (98.475) +2022-11-14 13:34:36,595 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.1135) Prec@1 83.000 (80.951) Prec@5 98.000 (98.463) +2022-11-14 13:34:36,604 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.1131) Prec@1 84.000 (81.024) Prec@5 98.000 (98.452) +2022-11-14 13:34:36,613 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.1123) Prec@1 87.000 (81.163) Prec@5 100.000 (98.488) +2022-11-14 13:34:36,623 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1122) Prec@1 86.000 (81.273) Prec@5 94.000 (98.386) +2022-11-14 13:34:36,632 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1123) Prec@1 80.000 (81.244) Prec@5 99.000 (98.400) +2022-11-14 13:34:36,641 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1123) Prec@1 79.000 (81.196) Prec@5 99.000 (98.413) +2022-11-14 13:34:36,651 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.1121) Prec@1 83.000 (81.234) Prec@5 100.000 (98.447) +2022-11-14 13:34:36,660 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.1121) Prec@1 84.000 (81.292) Prec@5 100.000 (98.479) +2022-11-14 13:34:36,669 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.1112) Prec@1 90.000 (81.469) Prec@5 100.000 (98.510) +2022-11-14 13:34:36,678 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1117) Prec@1 78.000 (81.400) Prec@5 100.000 (98.540) +2022-11-14 13:34:36,687 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1119) Prec@1 78.000 (81.333) Prec@5 100.000 (98.569) +2022-11-14 13:34:36,695 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1300 (0.1122) Prec@1 73.000 (81.173) Prec@5 98.000 (98.558) +2022-11-14 13:34:36,705 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.1119) Prec@1 81.000 (81.170) Prec@5 99.000 (98.566) +2022-11-14 13:34:36,715 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.1116) Prec@1 81.000 (81.167) Prec@5 99.000 (98.574) +2022-11-14 13:34:36,725 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1117) Prec@1 78.000 (81.109) Prec@5 98.000 (98.564) +2022-11-14 13:34:36,735 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.1112) Prec@1 88.000 (81.232) Prec@5 99.000 (98.571) +2022-11-14 13:34:36,744 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.1112) Prec@1 82.000 (81.246) Prec@5 98.000 (98.561) +2022-11-14 13:34:36,754 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.1111) Prec@1 85.000 (81.310) Prec@5 98.000 (98.552) +2022-11-14 13:34:36,764 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1268 (0.1114) Prec@1 80.000 (81.288) Prec@5 99.000 (98.559) +2022-11-14 13:34:36,773 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.1114) Prec@1 82.000 (81.300) Prec@5 100.000 (98.583) +2022-11-14 13:34:36,784 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.1113) Prec@1 81.000 (81.295) Prec@5 100.000 (98.607) +2022-11-14 13:34:36,792 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1116) Prec@1 77.000 (81.226) Prec@5 98.000 (98.597) +2022-11-14 13:34:36,801 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.1115) Prec@1 82.000 (81.238) Prec@5 100.000 (98.619) +2022-11-14 13:34:36,813 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.1112) Prec@1 83.000 (81.266) Prec@5 100.000 (98.641) +2022-11-14 13:34:36,822 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1416 (0.1117) Prec@1 75.000 (81.169) Prec@5 97.000 (98.615) +2022-11-14 13:34:36,832 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1118) Prec@1 78.000 (81.121) Prec@5 99.000 (98.621) +2022-11-14 13:34:36,841 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.1113) Prec@1 85.000 (81.179) Prec@5 100.000 (98.642) +2022-11-14 13:34:36,851 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1113) Prec@1 80.000 (81.162) Prec@5 100.000 (98.662) +2022-11-14 13:34:36,861 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.1107) Prec@1 88.000 (81.261) Prec@5 100.000 (98.681) +2022-11-14 13:34:36,871 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1112) Prec@1 74.000 (81.157) Prec@5 96.000 (98.643) +2022-11-14 13:34:36,881 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.1110) Prec@1 84.000 (81.197) Prec@5 99.000 (98.648) +2022-11-14 13:34:36,890 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.1109) Prec@1 81.000 (81.194) Prec@5 100.000 (98.667) +2022-11-14 13:34:36,899 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.1103) Prec@1 90.000 (81.315) Prec@5 98.000 (98.658) +2022-11-14 13:34:36,910 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.1098) Prec@1 89.000 (81.419) Prec@5 100.000 (98.676) +2022-11-14 13:34:36,920 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1451 (0.1103) Prec@1 77.000 (81.360) Prec@5 99.000 (98.680) +2022-11-14 13:34:36,929 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.1100) Prec@1 86.000 (81.421) Prec@5 99.000 (98.684) +2022-11-14 13:34:36,939 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.1101) Prec@1 79.000 (81.390) Prec@5 99.000 (98.688) +2022-11-14 13:34:36,950 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.1099) Prec@1 85.000 (81.436) Prec@5 99.000 (98.692) +2022-11-14 13:34:36,960 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.1097) Prec@1 82.000 (81.443) Prec@5 100.000 (98.709) +2022-11-14 13:34:36,969 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1097) Prec@1 79.000 (81.412) Prec@5 99.000 (98.713) +2022-11-14 13:34:36,978 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.1097) Prec@1 81.000 (81.407) Prec@5 98.000 (98.704) +2022-11-14 13:34:36,987 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.1095) Prec@1 86.000 (81.463) Prec@5 99.000 (98.707) +2022-11-14 13:34:36,995 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1384 (0.1098) Prec@1 74.000 (81.373) Prec@5 99.000 (98.711) +2022-11-14 13:34:37,003 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1101) Prec@1 74.000 (81.286) Prec@5 98.000 (98.702) +2022-11-14 13:34:37,014 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1325 (0.1104) Prec@1 76.000 (81.224) Prec@5 97.000 (98.682) +2022-11-14 13:34:37,024 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1268 (0.1106) Prec@1 79.000 (81.198) Prec@5 99.000 (98.686) +2022-11-14 13:34:37,035 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.1105) Prec@1 82.000 (81.207) Prec@5 99.000 (98.690) +2022-11-14 13:34:37,045 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.1104) Prec@1 80.000 (81.193) Prec@5 99.000 (98.693) +2022-11-14 13:34:37,055 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.1103) Prec@1 81.000 (81.191) Prec@5 98.000 (98.685) +2022-11-14 13:34:37,065 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.1101) Prec@1 86.000 (81.244) Prec@5 98.000 (98.678) +2022-11-14 13:34:37,075 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.1100) Prec@1 82.000 (81.253) Prec@5 99.000 (98.681) +2022-11-14 13:34:37,084 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.1096) Prec@1 88.000 (81.326) Prec@5 100.000 (98.696) +2022-11-14 13:34:37,094 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.1097) Prec@1 80.000 (81.312) Prec@5 100.000 (98.710) +2022-11-14 13:34:37,104 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.1096) Prec@1 80.000 (81.298) Prec@5 99.000 (98.713) +2022-11-14 13:34:37,114 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1095) Prec@1 81.000 (81.295) Prec@5 99.000 (98.716) +2022-11-14 13:34:37,125 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.1093) Prec@1 85.000 (81.333) Prec@5 99.000 (98.719) +2022-11-14 13:34:37,135 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.1090) Prec@1 86.000 (81.381) Prec@5 99.000 (98.722) +2022-11-14 13:34:37,145 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1751 (0.1097) Prec@1 71.000 (81.276) Prec@5 97.000 (98.704) +2022-11-14 13:34:37,153 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1272 (0.1099) Prec@1 77.000 (81.232) Prec@5 99.000 (98.707) +2022-11-14 13:34:37,162 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.1099) Prec@1 80.000 (81.220) Prec@5 97.000 (98.690) +2022-11-14 13:34:37,215 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:34:37,533 Epoch: [62][0/500] Time 0.024 (0.024) Data 0.236 (0.236) Loss 0.0714 (0.0714) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:34:37,739 Epoch: [62][10/500] Time 0.021 (0.019) Data 0.001 (0.023) Loss 0.1051 (0.0882) Prec@1 80.000 (83.500) Prec@5 99.000 (99.500) +2022-11-14 13:34:37,935 Epoch: [62][20/500] Time 0.018 (0.018) Data 0.001 (0.013) Loss 0.0784 (0.0850) Prec@1 88.000 (85.000) Prec@5 100.000 (99.667) +2022-11-14 13:34:38,169 Epoch: [62][30/500] Time 0.026 (0.019) Data 0.002 (0.009) Loss 0.0956 (0.0876) Prec@1 84.000 (84.750) Prec@5 99.000 (99.500) +2022-11-14 13:34:38,476 Epoch: [62][40/500] Time 0.028 (0.021) Data 0.002 (0.007) Loss 0.0665 (0.0834) Prec@1 89.000 (85.600) Prec@5 100.000 (99.600) +2022-11-14 13:34:38,774 Epoch: [62][50/500] Time 0.026 (0.022) Data 0.002 (0.006) Loss 0.0916 (0.0848) Prec@1 86.000 (85.667) Prec@5 99.000 (99.500) +2022-11-14 13:34:39,079 Epoch: [62][60/500] Time 0.029 (0.023) Data 0.001 (0.006) Loss 0.0898 (0.0855) Prec@1 87.000 (85.857) Prec@5 98.000 (99.286) +2022-11-14 13:34:39,378 Epoch: [62][70/500] Time 0.028 (0.023) Data 0.002 (0.005) Loss 0.0653 (0.0830) Prec@1 90.000 (86.375) Prec@5 100.000 (99.375) +2022-11-14 13:34:39,683 Epoch: [62][80/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0950 (0.0843) Prec@1 80.000 (85.667) Prec@5 99.000 (99.333) +2022-11-14 13:34:39,984 Epoch: [62][90/500] Time 0.028 (0.024) Data 0.001 (0.004) Loss 0.0877 (0.0846) Prec@1 83.000 (85.400) Prec@5 98.000 (99.200) +2022-11-14 13:34:40,289 Epoch: [62][100/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.1128 (0.0872) Prec@1 79.000 (84.818) Prec@5 99.000 (99.182) +2022-11-14 13:34:40,589 Epoch: [62][110/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0769 (0.0863) Prec@1 89.000 (85.167) Prec@5 100.000 (99.250) +2022-11-14 13:34:40,897 Epoch: [62][120/500] Time 0.029 (0.025) Data 0.001 (0.004) Loss 0.0750 (0.0855) Prec@1 88.000 (85.385) Prec@5 96.000 (99.000) +2022-11-14 13:34:41,199 Epoch: [62][130/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.1303 (0.0887) Prec@1 76.000 (84.714) Prec@5 98.000 (98.929) +2022-11-14 13:34:41,511 Epoch: [62][140/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0999 (0.0894) Prec@1 81.000 (84.467) Prec@5 100.000 (99.000) +2022-11-14 13:34:41,812 Epoch: [62][150/500] Time 0.029 (0.025) Data 0.001 (0.003) Loss 0.0927 (0.0896) Prec@1 85.000 (84.500) Prec@5 97.000 (98.875) +2022-11-14 13:34:42,129 Epoch: [62][160/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.1240 (0.0916) Prec@1 80.000 (84.235) Prec@5 96.000 (98.706) +2022-11-14 13:34:42,443 Epoch: [62][170/500] Time 0.032 (0.026) Data 0.001 (0.003) Loss 0.0967 (0.0919) Prec@1 84.000 (84.222) Prec@5 96.000 (98.556) +2022-11-14 13:34:42,752 Epoch: [62][180/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.1242 (0.0936) Prec@1 78.000 (83.895) Prec@5 99.000 (98.579) +2022-11-14 13:34:43,107 Epoch: [62][190/500] Time 0.044 (0.026) Data 0.002 (0.003) Loss 0.1020 (0.0940) Prec@1 80.000 (83.700) Prec@5 99.000 (98.600) +2022-11-14 13:34:43,581 Epoch: [62][200/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.1251 (0.0955) Prec@1 75.000 (83.286) Prec@5 99.000 (98.619) +2022-11-14 13:34:44,055 Epoch: [62][210/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.1143 (0.0964) Prec@1 79.000 (83.091) Prec@5 99.000 (98.636) +2022-11-14 13:34:44,550 Epoch: [62][220/500] Time 0.048 (0.028) Data 0.002 (0.003) Loss 0.1262 (0.0977) Prec@1 79.000 (82.913) Prec@5 97.000 (98.565) +2022-11-14 13:34:45,048 Epoch: [62][230/500] Time 0.045 (0.029) Data 0.002 (0.003) Loss 0.0778 (0.0968) Prec@1 88.000 (83.125) Prec@5 98.000 (98.542) +2022-11-14 13:34:45,557 Epoch: [62][240/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0961 (0.0968) Prec@1 83.000 (83.120) Prec@5 100.000 (98.600) +2022-11-14 13:34:46,056 Epoch: [62][250/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.1052 (0.0971) Prec@1 81.000 (83.038) Prec@5 98.000 (98.577) +2022-11-14 13:34:46,521 Epoch: [62][260/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1154 (0.0978) Prec@1 80.000 (82.926) Prec@5 98.000 (98.556) +2022-11-14 13:34:47,002 Epoch: [62][270/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0770 (0.0971) Prec@1 87.000 (83.071) Prec@5 99.000 (98.571) +2022-11-14 13:34:47,475 Epoch: [62][280/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1113 (0.0976) Prec@1 78.000 (82.897) Prec@5 100.000 (98.621) +2022-11-14 13:34:47,957 Epoch: [62][290/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0888 (0.0973) Prec@1 87.000 (83.033) Prec@5 99.000 (98.633) +2022-11-14 13:34:48,446 Epoch: [62][300/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0964 (0.0972) Prec@1 84.000 (83.065) Prec@5 98.000 (98.613) +2022-11-14 13:34:48,939 Epoch: [62][310/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.1003 (0.0973) Prec@1 83.000 (83.062) Prec@5 97.000 (98.562) +2022-11-14 13:34:49,423 Epoch: [62][320/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0852 (0.0970) Prec@1 86.000 (83.152) Prec@5 100.000 (98.606) +2022-11-14 13:34:49,932 Epoch: [62][330/500] Time 0.055 (0.033) Data 0.002 (0.003) Loss 0.1098 (0.0973) Prec@1 82.000 (83.118) Prec@5 97.000 (98.559) +2022-11-14 13:34:50,416 Epoch: [62][340/500] Time 0.042 (0.034) Data 0.003 (0.003) Loss 0.1250 (0.0981) Prec@1 77.000 (82.943) Prec@5 100.000 (98.600) +2022-11-14 13:34:50,902 Epoch: [62][350/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.1063 (0.0984) Prec@1 83.000 (82.944) Prec@5 98.000 (98.583) +2022-11-14 13:34:51,589 Epoch: [62][360/500] Time 0.075 (0.035) Data 0.002 (0.003) Loss 0.0604 (0.0973) Prec@1 92.000 (83.189) Prec@5 100.000 (98.622) +2022-11-14 13:34:51,963 Epoch: [62][370/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0891 (0.0971) Prec@1 84.000 (83.211) Prec@5 100.000 (98.658) +2022-11-14 13:34:52,334 Epoch: [62][380/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0867 (0.0968) Prec@1 86.000 (83.282) Prec@5 100.000 (98.692) +2022-11-14 13:34:52,713 Epoch: [62][390/500] Time 0.035 (0.035) Data 0.001 (0.002) Loss 0.0984 (0.0969) Prec@1 82.000 (83.250) Prec@5 100.000 (98.725) +2022-11-14 13:34:53,097 Epoch: [62][400/500] Time 0.034 (0.035) Data 0.001 (0.002) Loss 0.0870 (0.0966) Prec@1 83.000 (83.244) Prec@5 100.000 (98.756) +2022-11-14 13:34:53,465 Epoch: [62][410/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.0605 (0.0958) Prec@1 91.000 (83.429) Prec@5 100.000 (98.786) +2022-11-14 13:34:53,839 Epoch: [62][420/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.1116 (0.0962) Prec@1 76.000 (83.256) Prec@5 100.000 (98.814) +2022-11-14 13:34:54,245 Epoch: [62][430/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.1142 (0.0966) Prec@1 83.000 (83.250) Prec@5 98.000 (98.795) +2022-11-14 13:34:54,657 Epoch: [62][440/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0990 (0.0966) Prec@1 83.000 (83.244) Prec@5 98.000 (98.778) +2022-11-14 13:34:55,029 Epoch: [62][450/500] Time 0.036 (0.035) Data 0.001 (0.002) Loss 0.0937 (0.0966) Prec@1 80.000 (83.174) Prec@5 100.000 (98.804) +2022-11-14 13:34:55,410 Epoch: [62][460/500] Time 0.036 (0.035) Data 0.001 (0.002) Loss 0.0713 (0.0960) Prec@1 89.000 (83.298) Prec@5 100.000 (98.830) +2022-11-14 13:34:55,783 Epoch: [62][470/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0841 (0.0958) Prec@1 85.000 (83.333) Prec@5 100.000 (98.854) +2022-11-14 13:34:56,164 Epoch: [62][480/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.1052 (0.0960) Prec@1 81.000 (83.286) Prec@5 99.000 (98.857) +2022-11-14 13:34:56,540 Epoch: [62][490/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0945 (0.0959) Prec@1 84.000 (83.300) Prec@5 99.000 (98.860) +2022-11-14 13:34:56,872 Epoch: [62][499/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.1083 (0.0962) Prec@1 82.000 (83.275) Prec@5 96.000 (98.804) +2022-11-14 13:34:57,146 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0842 (0.0842) Prec@1 84.000 (84.000) Prec@5 98.000 (98.000) +2022-11-14 13:34:57,155 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0904) Prec@1 83.000 (83.500) Prec@5 100.000 (99.000) +2022-11-14 13:34:57,164 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1227 (0.1012) Prec@1 80.000 (82.333) Prec@5 98.000 (98.667) +2022-11-14 13:34:57,177 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1184 (0.1055) Prec@1 79.000 (81.500) Prec@5 100.000 (99.000) +2022-11-14 13:34:57,186 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1081) Prec@1 82.000 (81.600) Prec@5 97.000 (98.600) +2022-11-14 13:34:57,196 Test: [5/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.1031) Prec@1 86.000 (82.333) Prec@5 98.000 (98.500) +2022-11-14 13:34:57,204 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.1050) Prec@1 81.000 (82.143) Prec@5 99.000 (98.571) +2022-11-14 13:34:57,214 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1313 (0.1083) Prec@1 76.000 (81.375) Prec@5 97.000 (98.375) +2022-11-14 13:34:57,222 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1311 (0.1108) Prec@1 82.000 (81.444) Prec@5 100.000 (98.556) +2022-11-14 13:34:57,231 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.1094) Prec@1 79.000 (81.200) Prec@5 97.000 (98.400) +2022-11-14 13:34:57,242 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.1066) Prec@1 86.000 (81.636) Prec@5 99.000 (98.455) +2022-11-14 13:34:57,253 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.1071) Prec@1 80.000 (81.500) Prec@5 100.000 (98.583) +2022-11-14 13:34:57,264 Test: [12/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1408 (0.1097) Prec@1 76.000 (81.077) Prec@5 99.000 (98.615) +2022-11-14 13:34:57,274 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.1082) Prec@1 86.000 (81.429) Prec@5 98.000 (98.571) +2022-11-14 13:34:57,284 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.1092) Prec@1 77.000 (81.133) Prec@5 99.000 (98.600) +2022-11-14 13:34:57,294 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.1103) Prec@1 77.000 (80.875) Prec@5 96.000 (98.438) +2022-11-14 13:34:57,304 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.1102) Prec@1 84.000 (81.059) Prec@5 97.000 (98.353) +2022-11-14 13:34:57,313 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.1103) Prec@1 80.000 (81.000) Prec@5 99.000 (98.389) +2022-11-14 13:34:57,322 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1107) Prec@1 80.000 (80.947) Prec@5 98.000 (98.368) +2022-11-14 13:34:57,331 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1421 (0.1123) Prec@1 78.000 (80.800) Prec@5 98.000 (98.350) +2022-11-14 13:34:57,340 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.1127) Prec@1 75.000 (80.524) Prec@5 99.000 (98.381) +2022-11-14 13:34:57,350 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.1131) Prec@1 80.000 (80.500) Prec@5 98.000 (98.364) +2022-11-14 13:34:57,359 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.1135) Prec@1 80.000 (80.478) Prec@5 98.000 (98.348) +2022-11-14 13:34:57,368 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.1131) Prec@1 83.000 (80.583) Prec@5 99.000 (98.375) +2022-11-14 13:34:57,377 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1132) Prec@1 80.000 (80.560) Prec@5 97.000 (98.320) +2022-11-14 13:34:57,386 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1539 (0.1148) Prec@1 76.000 (80.385) Prec@5 96.000 (98.231) +2022-11-14 13:34:57,394 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.1134) Prec@1 90.000 (80.741) Prec@5 100.000 (98.296) +2022-11-14 13:34:57,402 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1152 (0.1135) Prec@1 78.000 (80.643) Prec@5 100.000 (98.357) +2022-11-14 13:34:57,409 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1132) Prec@1 81.000 (80.655) Prec@5 97.000 (98.310) +2022-11-14 13:34:57,420 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.1126) Prec@1 84.000 (80.767) Prec@5 99.000 (98.333) +2022-11-14 13:34:57,429 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.1129) Prec@1 77.000 (80.645) Prec@5 99.000 (98.355) +2022-11-14 13:34:57,438 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.1128) Prec@1 82.000 (80.688) Prec@5 99.000 (98.375) +2022-11-14 13:34:57,447 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1179 (0.1129) Prec@1 76.000 (80.545) Prec@5 96.000 (98.303) +2022-11-14 13:34:57,455 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1493 (0.1140) Prec@1 76.000 (80.412) Prec@5 97.000 (98.265) +2022-11-14 13:34:57,465 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.1137) Prec@1 84.000 (80.514) Prec@5 98.000 (98.257) +2022-11-14 13:34:57,474 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.1137) Prec@1 80.000 (80.500) Prec@5 99.000 (98.278) +2022-11-14 13:34:57,483 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1350 (0.1143) Prec@1 75.000 (80.351) Prec@5 97.000 (98.243) +2022-11-14 13:34:57,492 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.1147) Prec@1 77.000 (80.263) Prec@5 97.000 (98.211) +2022-11-14 13:34:57,501 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.1145) Prec@1 80.000 (80.256) Prec@5 100.000 (98.256) +2022-11-14 13:34:57,510 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.1141) Prec@1 84.000 (80.350) Prec@5 99.000 (98.275) +2022-11-14 13:34:57,519 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.1140) Prec@1 78.000 (80.293) Prec@5 98.000 (98.268) +2022-11-14 13:34:57,528 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.1139) Prec@1 83.000 (80.357) Prec@5 98.000 (98.262) +2022-11-14 13:34:57,536 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.1133) Prec@1 86.000 (80.488) Prec@5 97.000 (98.233) +2022-11-14 13:34:57,546 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1134) Prec@1 82.000 (80.523) Prec@5 98.000 (98.227) +2022-11-14 13:34:57,555 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1135) Prec@1 78.000 (80.467) Prec@5 98.000 (98.222) +2022-11-14 13:34:57,564 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1404 (0.1141) Prec@1 74.000 (80.326) Prec@5 95.000 (98.152) +2022-11-14 13:34:57,575 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.1136) Prec@1 87.000 (80.468) Prec@5 99.000 (98.170) +2022-11-14 13:34:57,583 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.1137) Prec@1 81.000 (80.479) Prec@5 99.000 (98.188) +2022-11-14 13:34:57,591 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.1130) Prec@1 87.000 (80.612) Prec@5 99.000 (98.204) +2022-11-14 13:34:57,600 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1439 (0.1137) Prec@1 73.000 (80.460) Prec@5 96.000 (98.160) +2022-11-14 13:34:57,610 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1135) Prec@1 82.000 (80.490) Prec@5 98.000 (98.157) +2022-11-14 13:34:57,619 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1242 (0.1137) Prec@1 79.000 (80.462) Prec@5 98.000 (98.154) +2022-11-14 13:34:57,628 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.1137) Prec@1 79.000 (80.434) Prec@5 100.000 (98.189) +2022-11-14 13:34:57,639 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.1134) Prec@1 83.000 (80.481) Prec@5 100.000 (98.222) +2022-11-14 13:34:57,648 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.1135) Prec@1 77.000 (80.418) Prec@5 98.000 (98.218) +2022-11-14 13:34:57,658 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1135) Prec@1 78.000 (80.375) Prec@5 99.000 (98.232) +2022-11-14 13:34:57,667 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1356 (0.1138) Prec@1 72.000 (80.228) Prec@5 98.000 (98.228) +2022-11-14 13:34:57,676 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.1137) Prec@1 82.000 (80.259) Prec@5 100.000 (98.259) +2022-11-14 13:34:57,685 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1399 (0.1142) Prec@1 74.000 (80.153) Prec@5 100.000 (98.288) +2022-11-14 13:34:57,693 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1225 (0.1143) Prec@1 79.000 (80.133) Prec@5 98.000 (98.283) +2022-11-14 13:34:57,702 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1140) Prec@1 84.000 (80.197) Prec@5 99.000 (98.295) +2022-11-14 13:34:57,712 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1326 (0.1143) Prec@1 77.000 (80.145) Prec@5 99.000 (98.306) +2022-11-14 13:34:57,722 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.1143) Prec@1 82.000 (80.175) Prec@5 98.000 (98.302) +2022-11-14 13:34:57,730 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.1136) Prec@1 87.000 (80.281) Prec@5 100.000 (98.328) +2022-11-14 13:34:57,739 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1476 (0.1142) Prec@1 74.000 (80.185) Prec@5 99.000 (98.338) +2022-11-14 13:34:57,749 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.1138) Prec@1 84.000 (80.242) Prec@5 99.000 (98.348) +2022-11-14 13:34:57,758 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.1134) Prec@1 84.000 (80.299) Prec@5 99.000 (98.358) +2022-11-14 13:34:57,768 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1134) Prec@1 78.000 (80.265) Prec@5 96.000 (98.324) +2022-11-14 13:34:57,778 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1132) Prec@1 83.000 (80.304) Prec@5 98.000 (98.319) +2022-11-14 13:34:57,788 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.1132) Prec@1 77.000 (80.257) Prec@5 97.000 (98.300) +2022-11-14 13:34:57,798 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1131) Prec@1 79.000 (80.239) Prec@5 99.000 (98.310) +2022-11-14 13:34:57,807 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.1132) Prec@1 80.000 (80.236) Prec@5 100.000 (98.333) +2022-11-14 13:34:57,817 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.1129) Prec@1 83.000 (80.274) Prec@5 100.000 (98.356) +2022-11-14 13:34:57,826 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.1125) Prec@1 87.000 (80.365) Prec@5 99.000 (98.365) +2022-11-14 13:34:57,835 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.1126) Prec@1 78.000 (80.333) Prec@5 97.000 (98.347) +2022-11-14 13:34:57,845 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.1126) Prec@1 81.000 (80.342) Prec@5 99.000 (98.355) +2022-11-14 13:34:57,855 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1126) Prec@1 80.000 (80.338) Prec@5 97.000 (98.338) +2022-11-14 13:34:57,864 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.1125) Prec@1 81.000 (80.346) Prec@5 99.000 (98.346) +2022-11-14 13:34:57,873 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.1125) Prec@1 79.000 (80.329) Prec@5 99.000 (98.354) +2022-11-14 13:34:57,882 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1126) Prec@1 79.000 (80.312) Prec@5 98.000 (98.350) +2022-11-14 13:34:57,891 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.1125) Prec@1 83.000 (80.346) Prec@5 97.000 (98.333) +2022-11-14 13:34:57,901 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.1122) Prec@1 86.000 (80.415) Prec@5 98.000 (98.329) +2022-11-14 13:34:57,910 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1643 (0.1128) Prec@1 67.000 (80.253) Prec@5 100.000 (98.349) +2022-11-14 13:34:57,919 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.1127) Prec@1 85.000 (80.310) Prec@5 98.000 (98.345) +2022-11-14 13:34:57,929 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1168 (0.1127) Prec@1 80.000 (80.306) Prec@5 98.000 (98.341) +2022-11-14 13:34:57,938 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1386 (0.1130) Prec@1 78.000 (80.279) Prec@5 99.000 (98.349) +2022-11-14 13:34:57,947 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.1129) Prec@1 82.000 (80.299) Prec@5 98.000 (98.345) +2022-11-14 13:34:57,957 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1129) Prec@1 81.000 (80.307) Prec@5 99.000 (98.352) +2022-11-14 13:34:57,965 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1128) Prec@1 85.000 (80.360) Prec@5 99.000 (98.360) +2022-11-14 13:34:57,974 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1128) Prec@1 79.000 (80.344) Prec@5 98.000 (98.356) +2022-11-14 13:34:57,982 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.1125) Prec@1 84.000 (80.385) Prec@5 99.000 (98.363) +2022-11-14 13:34:57,991 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.1125) Prec@1 83.000 (80.413) Prec@5 98.000 (98.359) +2022-11-14 13:34:58,000 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1510 (0.1129) Prec@1 71.000 (80.312) Prec@5 98.000 (98.355) +2022-11-14 13:34:58,009 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.1128) Prec@1 77.000 (80.277) Prec@5 100.000 (98.372) +2022-11-14 13:34:58,019 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.1126) Prec@1 83.000 (80.305) Prec@5 99.000 (98.379) +2022-11-14 13:34:58,027 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.1125) Prec@1 78.000 (80.281) Prec@5 98.000 (98.375) +2022-11-14 13:34:58,036 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.1122) Prec@1 87.000 (80.351) Prec@5 99.000 (98.381) +2022-11-14 13:34:58,045 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1540 (0.1126) Prec@1 76.000 (80.306) Prec@5 98.000 (98.378) +2022-11-14 13:34:58,054 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1290 (0.1128) Prec@1 79.000 (80.293) Prec@5 99.000 (98.384) +2022-11-14 13:34:58,062 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1213 (0.1129) Prec@1 80.000 (80.290) Prec@5 98.000 (98.380) +2022-11-14 13:34:58,116 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:34:58,428 Epoch: [63][0/500] Time 0.030 (0.030) Data 0.226 (0.226) Loss 0.0969 (0.0969) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:34:58,644 Epoch: [63][10/500] Time 0.016 (0.020) Data 0.002 (0.022) Loss 0.0813 (0.0891) Prec@1 88.000 (86.500) Prec@5 98.000 (98.000) +2022-11-14 13:34:58,856 Epoch: [63][20/500] Time 0.016 (0.019) Data 0.002 (0.013) Loss 0.0924 (0.0902) Prec@1 82.000 (85.000) Prec@5 99.000 (98.333) +2022-11-14 13:34:59,108 Epoch: [63][30/500] Time 0.024 (0.020) Data 0.002 (0.009) Loss 0.1029 (0.0934) Prec@1 83.000 (84.500) Prec@5 99.000 (98.500) +2022-11-14 13:34:59,402 Epoch: [63][40/500] Time 0.029 (0.022) Data 0.002 (0.007) Loss 0.1220 (0.0991) Prec@1 78.000 (83.200) Prec@5 99.000 (98.600) +2022-11-14 13:34:59,698 Epoch: [63][50/500] Time 0.027 (0.023) Data 0.002 (0.006) Loss 0.0915 (0.0978) Prec@1 84.000 (83.333) Prec@5 98.000 (98.500) +2022-11-14 13:34:59,993 Epoch: [63][60/500] Time 0.027 (0.023) Data 0.002 (0.005) Loss 0.1285 (0.1022) Prec@1 75.000 (82.143) Prec@5 99.000 (98.571) +2022-11-14 13:35:00,288 Epoch: [63][70/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0941 (0.1012) Prec@1 84.000 (82.375) Prec@5 99.000 (98.625) +2022-11-14 13:35:00,582 Epoch: [63][80/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0999 (0.1011) Prec@1 80.000 (82.111) Prec@5 99.000 (98.667) +2022-11-14 13:35:00,881 Epoch: [63][90/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.0828 (0.0992) Prec@1 86.000 (82.500) Prec@5 100.000 (98.800) +2022-11-14 13:35:01,197 Epoch: [63][100/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0686 (0.0964) Prec@1 88.000 (83.000) Prec@5 100.000 (98.909) +2022-11-14 13:35:01,492 Epoch: [63][110/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0780 (0.0949) Prec@1 84.000 (83.083) Prec@5 100.000 (99.000) +2022-11-14 13:35:01,815 Epoch: [63][120/500] Time 0.024 (0.025) Data 0.002 (0.004) Loss 0.0993 (0.0952) Prec@1 82.000 (83.000) Prec@5 98.000 (98.923) +2022-11-14 13:35:02,175 Epoch: [63][130/500] Time 0.054 (0.026) Data 0.002 (0.004) Loss 0.0959 (0.0953) Prec@1 85.000 (83.143) Prec@5 100.000 (99.000) +2022-11-14 13:35:02,724 Epoch: [63][140/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0913 (0.0950) Prec@1 85.000 (83.267) Prec@5 98.000 (98.933) +2022-11-14 13:35:03,454 Epoch: [63][150/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0891 (0.0946) Prec@1 86.000 (83.438) Prec@5 100.000 (99.000) +2022-11-14 13:35:03,943 Epoch: [63][160/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1202 (0.0962) Prec@1 81.000 (83.294) Prec@5 98.000 (98.941) +2022-11-14 13:35:04,415 Epoch: [63][170/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0959 (0.0961) Prec@1 86.000 (83.444) Prec@5 98.000 (98.889) +2022-11-14 13:35:04,878 Epoch: [63][180/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0963 (0.0961) Prec@1 83.000 (83.421) Prec@5 96.000 (98.737) +2022-11-14 13:35:05,340 Epoch: [63][190/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.1190 (0.0973) Prec@1 81.000 (83.300) Prec@5 98.000 (98.700) +2022-11-14 13:35:05,803 Epoch: [63][200/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0581 (0.0954) Prec@1 92.000 (83.714) Prec@5 100.000 (98.762) +2022-11-14 13:35:06,266 Epoch: [63][210/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1143 (0.0963) Prec@1 80.000 (83.545) Prec@5 98.000 (98.727) +2022-11-14 13:35:06,727 Epoch: [63][220/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0774 (0.0955) Prec@1 87.000 (83.696) Prec@5 100.000 (98.783) +2022-11-14 13:35:07,188 Epoch: [63][230/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0777 (0.0947) Prec@1 88.000 (83.875) Prec@5 99.000 (98.792) +2022-11-14 13:35:07,650 Epoch: [63][240/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0923 (0.0946) Prec@1 87.000 (84.000) Prec@5 97.000 (98.720) +2022-11-14 13:35:08,112 Epoch: [63][250/500] Time 0.043 (0.034) Data 0.001 (0.003) Loss 0.0973 (0.0947) Prec@1 82.000 (83.923) Prec@5 99.000 (98.731) +2022-11-14 13:35:08,573 Epoch: [63][260/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0944 (0.0947) Prec@1 85.000 (83.963) Prec@5 98.000 (98.704) +2022-11-14 13:35:09,034 Epoch: [63][270/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0920 (0.0946) Prec@1 82.000 (83.893) Prec@5 100.000 (98.750) +2022-11-14 13:35:09,496 Epoch: [63][280/500] Time 0.044 (0.035) Data 0.001 (0.003) Loss 0.1161 (0.0954) Prec@1 80.000 (83.759) Prec@5 100.000 (98.793) +2022-11-14 13:35:09,957 Epoch: [63][290/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0978 (0.0954) Prec@1 82.000 (83.700) Prec@5 98.000 (98.767) +2022-11-14 13:35:10,420 Epoch: [63][300/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0702 (0.0946) Prec@1 90.000 (83.903) Prec@5 99.000 (98.774) +2022-11-14 13:35:10,881 Epoch: [63][310/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.1292 (0.0957) Prec@1 80.000 (83.781) Prec@5 96.000 (98.688) +2022-11-14 13:35:11,345 Epoch: [63][320/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0780 (0.0952) Prec@1 87.000 (83.879) Prec@5 100.000 (98.727) +2022-11-14 13:35:11,806 Epoch: [63][330/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0887 (0.0950) Prec@1 84.000 (83.882) Prec@5 99.000 (98.735) +2022-11-14 13:35:12,274 Epoch: [63][340/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0904 (0.0948) Prec@1 82.000 (83.829) Prec@5 99.000 (98.743) +2022-11-14 13:35:12,737 Epoch: [63][350/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0942 (0.0948) Prec@1 84.000 (83.833) Prec@5 99.000 (98.750) +2022-11-14 13:35:13,202 Epoch: [63][360/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0993 (0.0950) Prec@1 83.000 (83.811) Prec@5 98.000 (98.730) +2022-11-14 13:35:13,665 Epoch: [63][370/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0844 (0.0947) Prec@1 85.000 (83.842) Prec@5 99.000 (98.737) +2022-11-14 13:35:14,131 Epoch: [63][380/500] Time 0.045 (0.037) Data 0.001 (0.002) Loss 0.0954 (0.0947) Prec@1 86.000 (83.897) Prec@5 98.000 (98.718) +2022-11-14 13:35:14,595 Epoch: [63][390/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0840 (0.0944) Prec@1 85.000 (83.925) Prec@5 99.000 (98.725) +2022-11-14 13:35:15,058 Epoch: [63][400/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.1357 (0.0954) Prec@1 77.000 (83.756) Prec@5 98.000 (98.707) +2022-11-14 13:35:15,585 Epoch: [63][410/500] Time 0.049 (0.037) Data 0.002 (0.002) Loss 0.0864 (0.0952) Prec@1 87.000 (83.833) Prec@5 100.000 (98.738) +2022-11-14 13:35:15,970 Epoch: [63][420/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1059 (0.0955) Prec@1 82.000 (83.791) Prec@5 97.000 (98.698) +2022-11-14 13:35:16,357 Epoch: [63][430/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0649 (0.0948) Prec@1 90.000 (83.932) Prec@5 99.000 (98.705) +2022-11-14 13:35:16,768 Epoch: [63][440/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0757 (0.0943) Prec@1 87.000 (84.000) Prec@5 99.000 (98.711) +2022-11-14 13:35:17,157 Epoch: [63][450/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0851 (0.0941) Prec@1 84.000 (84.000) Prec@5 99.000 (98.717) +2022-11-14 13:35:17,557 Epoch: [63][460/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0902 (0.0941) Prec@1 83.000 (83.979) Prec@5 98.000 (98.702) +2022-11-14 13:35:17,959 Epoch: [63][470/500] Time 0.046 (0.037) Data 0.001 (0.002) Loss 0.0945 (0.0941) Prec@1 83.000 (83.958) Prec@5 99.000 (98.708) +2022-11-14 13:35:18,355 Epoch: [63][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.1164 (0.0945) Prec@1 83.000 (83.939) Prec@5 97.000 (98.673) +2022-11-14 13:35:18,760 Epoch: [63][490/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.1021 (0.0947) Prec@1 79.000 (83.840) Prec@5 100.000 (98.700) +2022-11-14 13:35:19,111 Epoch: [63][499/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1009 (0.0948) Prec@1 84.000 (83.843) Prec@5 100.000 (98.725) +2022-11-14 13:35:19,378 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0937 (0.0937) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:35:19,388 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.1030) Prec@1 82.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:35:19,396 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1173 (0.1077) Prec@1 80.000 (82.000) Prec@5 98.000 (99.333) +2022-11-14 13:35:19,406 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.1088) Prec@1 80.000 (81.500) Prec@5 100.000 (99.500) +2022-11-14 13:35:19,414 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.1081) Prec@1 82.000 (81.600) Prec@5 100.000 (99.600) +2022-11-14 13:35:19,423 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.1018) Prec@1 88.000 (82.667) Prec@5 98.000 (99.333) +2022-11-14 13:35:19,431 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0987) Prec@1 88.000 (83.429) Prec@5 100.000 (99.429) +2022-11-14 13:35:19,439 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1028) Prec@1 79.000 (82.875) Prec@5 99.000 (99.375) +2022-11-14 13:35:19,448 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1033) Prec@1 82.000 (82.778) Prec@5 98.000 (99.222) +2022-11-14 13:35:19,456 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.1025) Prec@1 86.000 (83.100) Prec@5 99.000 (99.200) +2022-11-14 13:35:19,465 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.1004) Prec@1 87.000 (83.455) Prec@5 100.000 (99.273) +2022-11-14 13:35:19,474 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.1002) Prec@1 86.000 (83.667) Prec@5 99.000 (99.250) +2022-11-14 13:35:19,482 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0982) Prec@1 90.000 (84.154) Prec@5 100.000 (99.308) +2022-11-14 13:35:19,491 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0981) Prec@1 81.000 (83.929) Prec@5 100.000 (99.357) +2022-11-14 13:35:19,501 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1041 (0.0985) Prec@1 80.000 (83.667) Prec@5 99.000 (99.333) +2022-11-14 13:35:19,509 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1001) Prec@1 78.000 (83.312) Prec@5 98.000 (99.250) +2022-11-14 13:35:19,518 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0998) Prec@1 83.000 (83.294) Prec@5 98.000 (99.176) +2022-11-14 13:35:19,527 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1192 (0.1009) Prec@1 77.000 (82.944) Prec@5 100.000 (99.222) +2022-11-14 13:35:19,536 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.1007) Prec@1 81.000 (82.842) Prec@5 98.000 (99.158) +2022-11-14 13:35:19,544 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1174 (0.1015) Prec@1 81.000 (82.750) Prec@5 98.000 (99.100) +2022-11-14 13:35:19,553 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1020) Prec@1 80.000 (82.619) Prec@5 100.000 (99.143) +2022-11-14 13:35:19,562 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.1016) Prec@1 85.000 (82.727) Prec@5 98.000 (99.091) +2022-11-14 13:35:19,571 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1265 (0.1026) Prec@1 78.000 (82.522) Prec@5 98.000 (99.043) +2022-11-14 13:35:19,579 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.1020) Prec@1 86.000 (82.667) Prec@5 100.000 (99.083) +2022-11-14 13:35:19,587 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.1019) Prec@1 84.000 (82.720) Prec@5 100.000 (99.120) +2022-11-14 13:35:19,596 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1193 (0.1026) Prec@1 81.000 (82.654) Prec@5 96.000 (99.000) +2022-11-14 13:35:19,606 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.1015) Prec@1 90.000 (82.926) Prec@5 99.000 (99.000) +2022-11-14 13:35:19,614 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.1018) Prec@1 83.000 (82.929) Prec@5 99.000 (99.000) +2022-11-14 13:35:19,623 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.1021) Prec@1 80.000 (82.828) Prec@5 99.000 (99.000) +2022-11-14 13:35:19,632 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1169 (0.1026) Prec@1 81.000 (82.767) Prec@5 97.000 (98.933) +2022-11-14 13:35:19,641 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1178 (0.1031) Prec@1 79.000 (82.645) Prec@5 99.000 (98.935) +2022-11-14 13:35:19,650 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.1028) Prec@1 85.000 (82.719) Prec@5 99.000 (98.938) +2022-11-14 13:35:19,659 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.1025) Prec@1 84.000 (82.758) Prec@5 98.000 (98.909) +2022-11-14 13:35:19,666 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1476 (0.1038) Prec@1 72.000 (82.441) Prec@5 97.000 (98.853) +2022-11-14 13:35:19,674 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.1036) Prec@1 81.000 (82.400) Prec@5 99.000 (98.857) +2022-11-14 13:35:19,682 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.1031) Prec@1 88.000 (82.556) Prec@5 100.000 (98.889) +2022-11-14 13:35:19,690 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1268 (0.1037) Prec@1 79.000 (82.459) Prec@5 98.000 (98.865) +2022-11-14 13:35:19,698 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.1040) Prec@1 81.000 (82.421) Prec@5 97.000 (98.816) +2022-11-14 13:35:19,706 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.1033) Prec@1 85.000 (82.487) Prec@5 100.000 (98.846) +2022-11-14 13:35:19,715 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.1029) Prec@1 86.000 (82.575) Prec@5 100.000 (98.875) +2022-11-14 13:35:19,724 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1193 (0.1033) Prec@1 79.000 (82.488) Prec@5 99.000 (98.878) +2022-11-14 13:35:19,733 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.1031) Prec@1 86.000 (82.571) Prec@5 99.000 (98.881) +2022-11-14 13:35:19,742 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.1019) Prec@1 94.000 (82.837) Prec@5 99.000 (98.884) +2022-11-14 13:35:19,751 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.1017) Prec@1 84.000 (82.864) Prec@5 98.000 (98.864) +2022-11-14 13:35:19,760 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1257 (0.1023) Prec@1 78.000 (82.756) Prec@5 99.000 (98.867) +2022-11-14 13:35:19,768 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1297 (0.1029) Prec@1 77.000 (82.630) Prec@5 99.000 (98.870) +2022-11-14 13:35:19,777 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.1027) Prec@1 85.000 (82.681) Prec@5 100.000 (98.894) +2022-11-14 13:35:19,786 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1193 (0.1030) Prec@1 82.000 (82.667) Prec@5 98.000 (98.875) +2022-11-14 13:35:19,795 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.1027) Prec@1 83.000 (82.673) Prec@5 100.000 (98.898) +2022-11-14 13:35:19,803 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1546 (0.1038) Prec@1 72.000 (82.460) Prec@5 96.000 (98.840) +2022-11-14 13:35:19,812 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1118 (0.1039) Prec@1 83.000 (82.471) Prec@5 98.000 (98.824) +2022-11-14 13:35:19,821 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1464 (0.1047) Prec@1 73.000 (82.288) Prec@5 98.000 (98.808) +2022-11-14 13:35:19,829 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.1046) Prec@1 83.000 (82.302) Prec@5 100.000 (98.830) +2022-11-14 13:35:19,839 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.1045) Prec@1 80.000 (82.259) Prec@5 99.000 (98.833) +2022-11-14 13:35:19,847 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.1048) Prec@1 76.000 (82.145) Prec@5 100.000 (98.855) +2022-11-14 13:35:19,855 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.1043) Prec@1 88.000 (82.250) Prec@5 99.000 (98.857) +2022-11-14 13:35:19,864 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1157 (0.1045) Prec@1 80.000 (82.211) Prec@5 100.000 (98.877) +2022-11-14 13:35:19,875 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.1042) Prec@1 87.000 (82.293) Prec@5 100.000 (98.897) +2022-11-14 13:35:19,883 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1029 (0.1042) Prec@1 80.000 (82.254) Prec@5 100.000 (98.915) +2022-11-14 13:35:19,892 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.1042) Prec@1 84.000 (82.283) Prec@5 99.000 (98.917) +2022-11-14 13:35:19,901 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.1043) Prec@1 80.000 (82.246) Prec@5 99.000 (98.918) +2022-11-14 13:35:19,910 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.1045) Prec@1 81.000 (82.226) Prec@5 98.000 (98.903) +2022-11-14 13:35:19,919 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.1042) Prec@1 86.000 (82.286) Prec@5 99.000 (98.905) +2022-11-14 13:35:19,929 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.1039) Prec@1 84.000 (82.312) Prec@5 99.000 (98.906) +2022-11-14 13:35:19,937 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1181 (0.1041) Prec@1 79.000 (82.262) Prec@5 99.000 (98.908) +2022-11-14 13:35:19,946 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1040) Prec@1 83.000 (82.273) Prec@5 99.000 (98.909) +2022-11-14 13:35:19,956 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.1035) Prec@1 91.000 (82.403) Prec@5 100.000 (98.925) +2022-11-14 13:35:19,964 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1151 (0.1036) Prec@1 81.000 (82.382) Prec@5 97.000 (98.897) +2022-11-14 13:35:19,972 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.1036) Prec@1 83.000 (82.391) Prec@5 99.000 (98.899) +2022-11-14 13:35:19,981 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1262 (0.1039) Prec@1 75.000 (82.286) Prec@5 99.000 (98.900) +2022-11-14 13:35:19,991 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.1039) Prec@1 81.000 (82.268) Prec@5 99.000 (98.901) +2022-11-14 13:35:20,000 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1190 (0.1041) Prec@1 79.000 (82.222) Prec@5 99.000 (98.903) +2022-11-14 13:35:20,009 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.1043) Prec@1 82.000 (82.219) Prec@5 99.000 (98.904) +2022-11-14 13:35:20,018 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.1039) Prec@1 90.000 (82.324) Prec@5 99.000 (98.905) +2022-11-14 13:35:20,027 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1189 (0.1041) Prec@1 79.000 (82.280) Prec@5 100.000 (98.920) +2022-11-14 13:35:20,036 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.1039) Prec@1 85.000 (82.316) Prec@5 98.000 (98.908) +2022-11-14 13:35:20,046 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1200 (0.1041) Prec@1 78.000 (82.260) Prec@5 98.000 (98.896) +2022-11-14 13:35:20,055 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.1042) Prec@1 81.000 (82.244) Prec@5 99.000 (98.897) +2022-11-14 13:35:20,064 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1169 (0.1043) Prec@1 82.000 (82.241) Prec@5 100.000 (98.911) +2022-11-14 13:35:20,074 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1438 (0.1048) Prec@1 72.000 (82.112) Prec@5 98.000 (98.900) +2022-11-14 13:35:20,083 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.1047) Prec@1 81.000 (82.099) Prec@5 99.000 (98.901) +2022-11-14 13:35:20,092 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.1047) Prec@1 79.000 (82.061) Prec@5 98.000 (98.890) +2022-11-14 13:35:20,102 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.1047) Prec@1 81.000 (82.048) Prec@5 99.000 (98.892) +2022-11-14 13:35:20,111 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.1046) Prec@1 82.000 (82.048) Prec@5 99.000 (98.893) +2022-11-14 13:35:20,122 Test: [84/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1309 (0.1049) Prec@1 74.000 (81.953) Prec@5 97.000 (98.871) +2022-11-14 13:35:20,132 Test: [85/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1269 (0.1052) Prec@1 76.000 (81.884) Prec@5 99.000 (98.872) +2022-11-14 13:35:20,142 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.1051) Prec@1 81.000 (81.874) Prec@5 97.000 (98.851) +2022-11-14 13:35:20,152 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.1050) Prec@1 83.000 (81.886) Prec@5 98.000 (98.841) +2022-11-14 13:35:20,162 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.1050) Prec@1 83.000 (81.899) Prec@5 100.000 (98.854) +2022-11-14 13:35:20,173 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.1049) Prec@1 84.000 (81.922) Prec@5 98.000 (98.844) +2022-11-14 13:35:20,183 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.1048) Prec@1 82.000 (81.923) Prec@5 100.000 (98.857) +2022-11-14 13:35:20,193 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.1044) Prec@1 88.000 (81.989) Prec@5 98.000 (98.848) +2022-11-14 13:35:20,202 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1403 (0.1048) Prec@1 75.000 (81.914) Prec@5 97.000 (98.828) +2022-11-14 13:35:20,211 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.1047) Prec@1 83.000 (81.926) Prec@5 100.000 (98.840) +2022-11-14 13:35:20,220 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.1045) Prec@1 86.000 (81.968) Prec@5 98.000 (98.832) +2022-11-14 13:35:20,230 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.1045) Prec@1 82.000 (81.969) Prec@5 100.000 (98.844) +2022-11-14 13:35:20,239 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.1045) Prec@1 82.000 (81.969) Prec@5 97.000 (98.825) +2022-11-14 13:35:20,248 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.1045) Prec@1 84.000 (81.990) Prec@5 99.000 (98.827) +2022-11-14 13:35:20,256 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1176 (0.1047) Prec@1 78.000 (81.949) Prec@5 100.000 (98.838) +2022-11-14 13:35:20,265 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.1047) Prec@1 81.000 (81.940) Prec@5 99.000 (98.840) +2022-11-14 13:35:20,332 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:35:20,635 Epoch: [64][0/500] Time 0.031 (0.031) Data 0.215 (0.215) Loss 0.0906 (0.0906) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:35:20,852 Epoch: [64][10/500] Time 0.017 (0.020) Data 0.002 (0.021) Loss 0.0850 (0.0878) Prec@1 84.000 (84.500) Prec@5 98.000 (99.000) +2022-11-14 13:35:21,062 Epoch: [64][20/500] Time 0.023 (0.019) Data 0.001 (0.012) Loss 0.1252 (0.1003) Prec@1 79.000 (82.667) Prec@5 96.000 (98.000) +2022-11-14 13:35:21,270 Epoch: [64][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.1226 (0.1059) Prec@1 79.000 (81.750) Prec@5 98.000 (98.000) +2022-11-14 13:35:21,492 Epoch: [64][40/500] Time 0.024 (0.019) Data 0.002 (0.007) Loss 0.0959 (0.1039) Prec@1 82.000 (81.800) Prec@5 99.000 (98.200) +2022-11-14 13:35:21,704 Epoch: [64][50/500] Time 0.019 (0.019) Data 0.001 (0.006) Loss 0.0860 (0.1009) Prec@1 89.000 (83.000) Prec@5 100.000 (98.500) +2022-11-14 13:35:21,969 Epoch: [64][60/500] Time 0.031 (0.020) Data 0.002 (0.005) Loss 0.0936 (0.0999) Prec@1 83.000 (83.000) Prec@5 100.000 (98.714) +2022-11-14 13:35:22,248 Epoch: [64][70/500] Time 0.025 (0.021) Data 0.002 (0.005) Loss 0.0746 (0.0967) Prec@1 88.000 (83.625) Prec@5 100.000 (98.875) +2022-11-14 13:35:22,513 Epoch: [64][80/500] Time 0.025 (0.021) Data 0.002 (0.004) Loss 0.1135 (0.0986) Prec@1 84.000 (83.667) Prec@5 98.000 (98.778) +2022-11-14 13:35:22,782 Epoch: [64][90/500] Time 0.024 (0.021) Data 0.003 (0.004) Loss 0.0621 (0.0949) Prec@1 88.000 (84.100) Prec@5 100.000 (98.900) +2022-11-14 13:35:23,076 Epoch: [64][100/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0936 (0.0948) Prec@1 85.000 (84.182) Prec@5 98.000 (98.818) +2022-11-14 13:35:23,364 Epoch: [64][110/500] Time 0.020 (0.022) Data 0.002 (0.004) Loss 0.0849 (0.0940) Prec@1 84.000 (84.167) Prec@5 99.000 (98.833) +2022-11-14 13:35:23,643 Epoch: [64][120/500] Time 0.028 (0.022) Data 0.002 (0.004) Loss 0.0787 (0.0928) Prec@1 83.000 (84.077) Prec@5 98.000 (98.769) +2022-11-14 13:35:23,920 Epoch: [64][130/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0808 (0.0919) Prec@1 85.000 (84.143) Prec@5 99.000 (98.786) +2022-11-14 13:35:24,191 Epoch: [64][140/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.1073 (0.0930) Prec@1 80.000 (83.867) Prec@5 99.000 (98.800) +2022-11-14 13:35:24,464 Epoch: [64][150/500] Time 0.022 (0.023) Data 0.001 (0.003) Loss 0.0779 (0.0920) Prec@1 88.000 (84.125) Prec@5 98.000 (98.750) +2022-11-14 13:35:24,748 Epoch: [64][160/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.1019 (0.0926) Prec@1 81.000 (83.941) Prec@5 98.000 (98.706) +2022-11-14 13:35:25,190 Epoch: [64][170/500] Time 0.043 (0.024) Data 0.002 (0.003) Loss 0.0788 (0.0918) Prec@1 86.000 (84.056) Prec@5 99.000 (98.722) +2022-11-14 13:35:25,773 Epoch: [64][180/500] Time 0.042 (0.025) Data 0.002 (0.003) Loss 0.1057 (0.0926) Prec@1 84.000 (84.053) Prec@5 100.000 (98.789) +2022-11-14 13:35:26,339 Epoch: [64][190/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.1205 (0.0940) Prec@1 75.000 (83.600) Prec@5 99.000 (98.800) +2022-11-14 13:35:26,802 Epoch: [64][200/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0872 (0.0936) Prec@1 85.000 (83.667) Prec@5 99.000 (98.810) +2022-11-14 13:35:27,263 Epoch: [64][210/500] Time 0.046 (0.028) Data 0.002 (0.003) Loss 0.1130 (0.0945) Prec@1 82.000 (83.591) Prec@5 98.000 (98.773) +2022-11-14 13:35:27,725 Epoch: [64][220/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0735 (0.0936) Prec@1 88.000 (83.783) Prec@5 100.000 (98.826) +2022-11-14 13:35:28,183 Epoch: [64][230/500] Time 0.042 (0.029) Data 0.002 (0.003) Loss 0.0883 (0.0934) Prec@1 85.000 (83.833) Prec@5 100.000 (98.875) +2022-11-14 13:35:28,645 Epoch: [64][240/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0943 (0.0934) Prec@1 87.000 (83.960) Prec@5 99.000 (98.880) +2022-11-14 13:35:29,101 Epoch: [64][250/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.1204 (0.0945) Prec@1 79.000 (83.769) Prec@5 99.000 (98.885) +2022-11-14 13:35:29,561 Epoch: [64][260/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1027 (0.0948) Prec@1 82.000 (83.704) Prec@5 100.000 (98.926) +2022-11-14 13:35:30,032 Epoch: [64][270/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0816 (0.0943) Prec@1 84.000 (83.714) Prec@5 99.000 (98.929) +2022-11-14 13:35:30,488 Epoch: [64][280/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0742 (0.0936) Prec@1 86.000 (83.793) Prec@5 100.000 (98.966) +2022-11-14 13:35:30,944 Epoch: [64][290/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0958 (0.0937) Prec@1 83.000 (83.767) Prec@5 98.000 (98.933) +2022-11-14 13:35:31,401 Epoch: [64][300/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0803 (0.0932) Prec@1 85.000 (83.806) Prec@5 99.000 (98.935) +2022-11-14 13:35:31,871 Epoch: [64][310/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0846 (0.0930) Prec@1 85.000 (83.844) Prec@5 99.000 (98.938) +2022-11-14 13:35:32,450 Epoch: [64][320/500] Time 0.051 (0.033) Data 0.002 (0.003) Loss 0.0979 (0.0931) Prec@1 79.000 (83.697) Prec@5 98.000 (98.909) +2022-11-14 13:35:32,951 Epoch: [64][330/500] Time 0.045 (0.033) Data 0.002 (0.003) Loss 0.1055 (0.0935) Prec@1 81.000 (83.618) Prec@5 99.000 (98.912) +2022-11-14 13:35:33,412 Epoch: [64][340/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1042 (0.0938) Prec@1 84.000 (83.629) Prec@5 98.000 (98.886) +2022-11-14 13:35:33,877 Epoch: [64][350/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.1051 (0.0941) Prec@1 81.000 (83.556) Prec@5 100.000 (98.917) +2022-11-14 13:35:34,346 Epoch: [64][360/500] Time 0.052 (0.034) Data 0.002 (0.002) Loss 0.0894 (0.0940) Prec@1 85.000 (83.595) Prec@5 100.000 (98.946) +2022-11-14 13:35:34,804 Epoch: [64][370/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0881 (0.0938) Prec@1 83.000 (83.579) Prec@5 99.000 (98.947) +2022-11-14 13:35:35,261 Epoch: [64][380/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0982 (0.0939) Prec@1 85.000 (83.615) Prec@5 100.000 (98.974) +2022-11-14 13:35:35,721 Epoch: [64][390/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.0931 (0.0939) Prec@1 84.000 (83.625) Prec@5 99.000 (98.975) +2022-11-14 13:35:36,061 Epoch: [64][400/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.1081 (0.0943) Prec@1 80.000 (83.537) Prec@5 98.000 (98.951) +2022-11-14 13:35:36,345 Epoch: [64][410/500] Time 0.031 (0.034) Data 0.002 (0.002) Loss 0.0840 (0.0940) Prec@1 86.000 (83.595) Prec@5 99.000 (98.952) +2022-11-14 13:35:36,630 Epoch: [64][420/500] Time 0.025 (0.034) Data 0.002 (0.002) Loss 0.0789 (0.0937) Prec@1 86.000 (83.651) Prec@5 98.000 (98.930) +2022-11-14 13:35:36,916 Epoch: [64][430/500] Time 0.031 (0.034) Data 0.002 (0.002) Loss 0.0772 (0.0933) Prec@1 87.000 (83.727) Prec@5 100.000 (98.955) +2022-11-14 13:35:37,200 Epoch: [64][440/500] Time 0.024 (0.033) Data 0.002 (0.002) Loss 0.1080 (0.0936) Prec@1 82.000 (83.689) Prec@5 100.000 (98.978) +2022-11-14 13:35:37,480 Epoch: [64][450/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0873 (0.0935) Prec@1 85.000 (83.717) Prec@5 98.000 (98.957) +2022-11-14 13:35:37,764 Epoch: [64][460/500] Time 0.025 (0.033) Data 0.003 (0.002) Loss 0.1121 (0.0939) Prec@1 81.000 (83.660) Prec@5 99.000 (98.957) +2022-11-14 13:35:38,047 Epoch: [64][470/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.1123 (0.0943) Prec@1 78.000 (83.542) Prec@5 99.000 (98.958) +2022-11-14 13:35:38,331 Epoch: [64][480/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0773 (0.0939) Prec@1 89.000 (83.653) Prec@5 100.000 (98.980) +2022-11-14 13:35:38,619 Epoch: [64][490/500] Time 0.028 (0.033) Data 0.001 (0.002) Loss 0.0843 (0.0937) Prec@1 86.000 (83.700) Prec@5 99.000 (98.980) +2022-11-14 13:35:38,878 Epoch: [64][499/500] Time 0.027 (0.032) Data 0.001 (0.002) Loss 0.1123 (0.0941) Prec@1 82.000 (83.667) Prec@5 100.000 (99.000) +2022-11-14 13:35:39,164 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1102 (0.1102) Prec@1 80.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:35:39,175 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1162 (0.1132) Prec@1 78.000 (79.000) Prec@5 98.000 (98.500) +2022-11-14 13:35:39,183 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1392 (0.1219) Prec@1 77.000 (78.333) Prec@5 97.000 (98.000) +2022-11-14 13:35:39,194 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1463 (0.1280) Prec@1 74.000 (77.250) Prec@5 97.000 (97.750) +2022-11-14 13:35:39,202 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1362 (0.1296) Prec@1 78.000 (77.400) Prec@5 99.000 (98.000) +2022-11-14 13:35:39,210 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1243) Prec@1 82.000 (78.167) Prec@5 100.000 (98.333) +2022-11-14 13:35:39,219 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1168 (0.1232) Prec@1 75.000 (77.714) Prec@5 99.000 (98.429) +2022-11-14 13:35:39,229 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.1231) Prec@1 80.000 (78.000) Prec@5 97.000 (98.250) +2022-11-14 13:35:39,237 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1255) Prec@1 77.000 (77.889) Prec@5 96.000 (98.000) +2022-11-14 13:35:39,245 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.1230) Prec@1 82.000 (78.300) Prec@5 98.000 (98.000) +2022-11-14 13:35:39,254 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.1230) Prec@1 76.000 (78.091) Prec@5 99.000 (98.091) +2022-11-14 13:35:39,262 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1280 (0.1234) Prec@1 78.000 (78.083) Prec@5 96.000 (97.917) +2022-11-14 13:35:39,270 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1235 (0.1234) Prec@1 78.000 (78.077) Prec@5 98.000 (97.923) +2022-11-14 13:35:39,278 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1166 (0.1229) Prec@1 78.000 (78.071) Prec@5 97.000 (97.857) +2022-11-14 13:35:39,286 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1181 (0.1226) Prec@1 80.000 (78.200) Prec@5 98.000 (97.867) +2022-11-14 13:35:39,295 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1285 (0.1230) Prec@1 75.000 (78.000) Prec@5 100.000 (98.000) +2022-11-14 13:35:39,305 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1088 (0.1221) Prec@1 81.000 (78.176) Prec@5 98.000 (98.000) +2022-11-14 13:35:39,314 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1167 (0.1218) Prec@1 83.000 (78.444) Prec@5 98.000 (98.000) +2022-11-14 13:35:39,323 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1315 (0.1223) Prec@1 74.000 (78.211) Prec@5 98.000 (98.000) +2022-11-14 13:35:39,333 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1476 (0.1236) Prec@1 70.000 (77.800) Prec@5 98.000 (98.000) +2022-11-14 13:35:39,342 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1492 (0.1248) Prec@1 74.000 (77.619) Prec@5 97.000 (97.952) +2022-11-14 13:35:39,351 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1311 (0.1251) Prec@1 77.000 (77.591) Prec@5 98.000 (97.955) +2022-11-14 13:35:39,360 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1468 (0.1260) Prec@1 73.000 (77.391) Prec@5 96.000 (97.870) +2022-11-14 13:35:39,370 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.1252) Prec@1 79.000 (77.458) Prec@5 99.000 (97.917) +2022-11-14 13:35:39,380 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1350 (0.1256) Prec@1 78.000 (77.480) Prec@5 97.000 (97.880) +2022-11-14 13:35:39,388 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1518 (0.1266) Prec@1 74.000 (77.346) Prec@5 95.000 (97.769) +2022-11-14 13:35:39,398 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1265) Prec@1 78.000 (77.370) Prec@5 100.000 (97.852) +2022-11-14 13:35:39,407 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1364 (0.1268) Prec@1 78.000 (77.393) Prec@5 96.000 (97.786) +2022-11-14 13:35:39,416 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1350 (0.1271) Prec@1 76.000 (77.345) Prec@5 96.000 (97.724) +2022-11-14 13:35:39,424 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1214 (0.1269) Prec@1 75.000 (77.267) Prec@5 98.000 (97.733) +2022-11-14 13:35:39,433 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1204 (0.1267) Prec@1 80.000 (77.355) Prec@5 99.000 (97.774) +2022-11-14 13:35:39,443 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1298 (0.1268) Prec@1 79.000 (77.406) Prec@5 99.000 (97.812) +2022-11-14 13:35:39,451 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1387 (0.1272) Prec@1 73.000 (77.273) Prec@5 97.000 (97.788) +2022-11-14 13:35:39,460 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1622 (0.1282) Prec@1 68.000 (77.000) Prec@5 97.000 (97.765) +2022-11-14 13:35:39,469 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1253 (0.1281) Prec@1 77.000 (77.000) Prec@5 99.000 (97.800) +2022-11-14 13:35:39,479 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.1277) Prec@1 84.000 (77.194) Prec@5 98.000 (97.806) +2022-11-14 13:35:39,487 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1419 (0.1281) Prec@1 77.000 (77.189) Prec@5 96.000 (97.757) +2022-11-14 13:35:39,497 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1285 (0.1281) Prec@1 77.000 (77.184) Prec@5 99.000 (97.789) +2022-11-14 13:35:39,506 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1277) Prec@1 82.000 (77.308) Prec@5 100.000 (97.846) +2022-11-14 13:35:39,516 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1219 (0.1275) Prec@1 79.000 (77.350) Prec@5 97.000 (97.825) +2022-11-14 13:35:39,525 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.1270) Prec@1 82.000 (77.463) Prec@5 98.000 (97.829) +2022-11-14 13:35:39,534 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.1266) Prec@1 82.000 (77.571) Prec@5 98.000 (97.833) +2022-11-14 13:35:39,542 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.1254) Prec@1 89.000 (77.837) Prec@5 99.000 (97.860) +2022-11-14 13:35:39,551 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.1250) Prec@1 80.000 (77.886) Prec@5 96.000 (97.818) +2022-11-14 13:35:39,560 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1368 (0.1253) Prec@1 74.000 (77.800) Prec@5 99.000 (97.844) +2022-11-14 13:35:39,570 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1660 (0.1262) Prec@1 70.000 (77.630) Prec@5 99.000 (97.870) +2022-11-14 13:35:39,579 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.1258) Prec@1 83.000 (77.745) Prec@5 97.000 (97.851) +2022-11-14 13:35:39,589 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1428 (0.1261) Prec@1 74.000 (77.667) Prec@5 97.000 (97.833) +2022-11-14 13:35:39,598 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.1257) Prec@1 80.000 (77.714) Prec@5 98.000 (97.837) +2022-11-14 13:35:39,607 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1985 (0.1272) Prec@1 65.000 (77.460) Prec@5 97.000 (97.820) +2022-11-14 13:35:39,619 Test: [50/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.1268) Prec@1 85.000 (77.608) Prec@5 99.000 (97.843) +2022-11-14 13:35:39,630 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1364 (0.1270) Prec@1 77.000 (77.596) Prec@5 96.000 (97.808) +2022-11-14 13:35:39,641 Test: [52/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1484 (0.1274) Prec@1 71.000 (77.472) Prec@5 98.000 (97.811) +2022-11-14 13:35:39,655 Test: [53/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1276) Prec@1 75.000 (77.426) Prec@5 95.000 (97.759) +2022-11-14 13:35:39,668 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1357 (0.1277) Prec@1 77.000 (77.418) Prec@5 96.000 (97.727) +2022-11-14 13:35:39,678 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.1276) Prec@1 77.000 (77.411) Prec@5 99.000 (97.750) +2022-11-14 13:35:39,687 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1464 (0.1279) Prec@1 75.000 (77.368) Prec@5 97.000 (97.737) +2022-11-14 13:35:39,696 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.1274) Prec@1 83.000 (77.466) Prec@5 99.000 (97.759) +2022-11-14 13:35:39,706 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1511 (0.1278) Prec@1 73.000 (77.390) Prec@5 98.000 (97.763) +2022-11-14 13:35:39,715 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1229 (0.1278) Prec@1 77.000 (77.383) Prec@5 97.000 (97.750) +2022-11-14 13:35:39,724 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.1277) Prec@1 77.000 (77.377) Prec@5 100.000 (97.787) +2022-11-14 13:35:39,734 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1469 (0.1281) Prec@1 73.000 (77.306) Prec@5 98.000 (97.790) +2022-11-14 13:35:39,744 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.1277) Prec@1 83.000 (77.397) Prec@5 100.000 (97.825) +2022-11-14 13:35:39,754 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1274) Prec@1 82.000 (77.469) Prec@5 99.000 (97.844) +2022-11-14 13:35:39,763 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1273) Prec@1 81.000 (77.523) Prec@5 98.000 (97.846) +2022-11-14 13:35:39,775 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1271) Prec@1 81.000 (77.576) Prec@5 98.000 (97.848) +2022-11-14 13:35:39,784 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1269) Prec@1 78.000 (77.582) Prec@5 100.000 (97.881) +2022-11-14 13:35:39,793 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1271) Prec@1 75.000 (77.544) Prec@5 97.000 (97.868) +2022-11-14 13:35:39,802 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1371 (0.1273) Prec@1 74.000 (77.493) Prec@5 99.000 (97.884) +2022-11-14 13:35:39,811 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1572 (0.1277) Prec@1 72.000 (77.414) Prec@5 94.000 (97.829) +2022-11-14 13:35:39,820 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1532 (0.1281) Prec@1 76.000 (77.394) Prec@5 99.000 (97.845) +2022-11-14 13:35:39,829 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1362 (0.1282) Prec@1 76.000 (77.375) Prec@5 98.000 (97.847) +2022-11-14 13:35:39,838 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1278) Prec@1 83.000 (77.452) Prec@5 100.000 (97.877) +2022-11-14 13:35:39,846 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.1273) Prec@1 85.000 (77.554) Prec@5 97.000 (97.865) +2022-11-14 13:35:39,855 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1657 (0.1278) Prec@1 73.000 (77.493) Prec@5 97.000 (97.853) +2022-11-14 13:35:39,865 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.1276) Prec@1 79.000 (77.513) Prec@5 99.000 (97.868) +2022-11-14 13:35:39,874 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.1276) Prec@1 76.000 (77.494) Prec@5 99.000 (97.883) +2022-11-14 13:35:39,882 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1191 (0.1275) Prec@1 81.000 (77.538) Prec@5 97.000 (97.872) +2022-11-14 13:35:39,890 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1230 (0.1275) Prec@1 78.000 (77.544) Prec@5 99.000 (97.886) +2022-11-14 13:35:39,899 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.1273) Prec@1 81.000 (77.588) Prec@5 97.000 (97.875) +2022-11-14 13:35:39,908 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1429 (0.1275) Prec@1 74.000 (77.543) Prec@5 98.000 (97.877) +2022-11-14 13:35:39,917 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.1273) Prec@1 82.000 (77.598) Prec@5 100.000 (97.902) +2022-11-14 13:35:39,925 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.1273) Prec@1 75.000 (77.566) Prec@5 98.000 (97.904) +2022-11-14 13:35:39,935 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1364 (0.1274) Prec@1 76.000 (77.548) Prec@5 98.000 (97.905) +2022-11-14 13:35:39,944 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1276) Prec@1 73.000 (77.494) Prec@5 98.000 (97.906) +2022-11-14 13:35:39,954 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.1274) Prec@1 83.000 (77.558) Prec@5 99.000 (97.919) +2022-11-14 13:35:39,963 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1235 (0.1274) Prec@1 76.000 (77.540) Prec@5 99.000 (97.931) +2022-11-14 13:35:39,973 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.1271) Prec@1 80.000 (77.568) Prec@5 100.000 (97.955) +2022-11-14 13:35:39,981 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1452 (0.1273) Prec@1 77.000 (77.562) Prec@5 97.000 (97.944) +2022-11-14 13:35:39,991 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1513 (0.1275) Prec@1 76.000 (77.544) Prec@5 98.000 (97.944) +2022-11-14 13:35:39,999 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.1272) Prec@1 82.000 (77.593) Prec@5 99.000 (97.956) +2022-11-14 13:35:40,008 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.1267) Prec@1 86.000 (77.685) Prec@5 99.000 (97.967) +2022-11-14 13:35:40,016 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.1266) Prec@1 79.000 (77.699) Prec@5 99.000 (97.978) +2022-11-14 13:35:40,025 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1269) Prec@1 74.000 (77.660) Prec@5 97.000 (97.968) +2022-11-14 13:35:40,034 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.1268) Prec@1 81.000 (77.695) Prec@5 96.000 (97.947) +2022-11-14 13:35:40,041 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.1265) Prec@1 81.000 (77.729) Prec@5 100.000 (97.969) +2022-11-14 13:35:40,050 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.1262) Prec@1 83.000 (77.784) Prec@5 100.000 (97.990) +2022-11-14 13:35:40,059 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1417 (0.1264) Prec@1 79.000 (77.796) Prec@5 96.000 (97.969) +2022-11-14 13:35:40,069 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1309 (0.1264) Prec@1 80.000 (77.818) Prec@5 98.000 (97.970) +2022-11-14 13:35:40,077 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1264) Prec@1 79.000 (77.830) Prec@5 96.000 (97.950) +2022-11-14 13:35:40,146 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:35:40,450 Epoch: [65][0/500] Time 0.024 (0.024) Data 0.222 (0.222) Loss 0.0772 (0.0772) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:35:40,651 Epoch: [65][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0887 (0.0830) Prec@1 84.000 (85.500) Prec@5 98.000 (98.500) +2022-11-14 13:35:40,856 Epoch: [65][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.1002 (0.0887) Prec@1 80.000 (83.667) Prec@5 98.000 (98.333) +2022-11-14 13:35:41,116 Epoch: [65][30/500] Time 0.029 (0.019) Data 0.002 (0.009) Loss 0.0736 (0.0849) Prec@1 90.000 (85.250) Prec@5 100.000 (98.750) +2022-11-14 13:35:41,430 Epoch: [65][40/500] Time 0.029 (0.021) Data 0.002 (0.007) Loss 0.1028 (0.0885) Prec@1 81.000 (84.400) Prec@5 99.000 (98.800) +2022-11-14 13:35:41,737 Epoch: [65][50/500] Time 0.028 (0.023) Data 0.002 (0.006) Loss 0.0901 (0.0888) Prec@1 86.000 (84.667) Prec@5 100.000 (99.000) +2022-11-14 13:35:42,052 Epoch: [65][60/500] Time 0.027 (0.023) Data 0.002 (0.005) Loss 0.0845 (0.0882) Prec@1 86.000 (84.857) Prec@5 100.000 (99.143) +2022-11-14 13:35:42,356 Epoch: [65][70/500] Time 0.028 (0.024) Data 0.001 (0.005) Loss 0.1187 (0.0920) Prec@1 77.000 (83.875) Prec@5 98.000 (99.000) +2022-11-14 13:35:42,668 Epoch: [65][80/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0778 (0.0904) Prec@1 87.000 (84.222) Prec@5 100.000 (99.111) +2022-11-14 13:35:42,977 Epoch: [65][90/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0838 (0.0897) Prec@1 84.000 (84.200) Prec@5 99.000 (99.100) +2022-11-14 13:35:43,290 Epoch: [65][100/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0871 (0.0895) Prec@1 86.000 (84.364) Prec@5 100.000 (99.182) +2022-11-14 13:35:43,603 Epoch: [65][110/500] Time 0.028 (0.025) Data 0.003 (0.004) Loss 0.0896 (0.0895) Prec@1 87.000 (84.583) Prec@5 100.000 (99.250) +2022-11-14 13:35:43,917 Epoch: [65][120/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0875 (0.0894) Prec@1 85.000 (84.615) Prec@5 99.000 (99.231) +2022-11-14 13:35:44,235 Epoch: [65][130/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.1047 (0.0905) Prec@1 83.000 (84.500) Prec@5 98.000 (99.143) +2022-11-14 13:35:44,548 Epoch: [65][140/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0767 (0.0895) Prec@1 86.000 (84.600) Prec@5 99.000 (99.133) +2022-11-14 13:35:44,862 Epoch: [65][150/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0690 (0.0883) Prec@1 90.000 (84.938) Prec@5 99.000 (99.125) +2022-11-14 13:35:45,169 Epoch: [65][160/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0608 (0.0866) Prec@1 91.000 (85.294) Prec@5 99.000 (99.118) +2022-11-14 13:35:45,481 Epoch: [65][170/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.1228 (0.0886) Prec@1 77.000 (84.833) Prec@5 99.000 (99.111) +2022-11-14 13:35:45,789 Epoch: [65][180/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.1135 (0.0900) Prec@1 80.000 (84.579) Prec@5 98.000 (99.053) +2022-11-14 13:35:46,102 Epoch: [65][190/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.0840 (0.0897) Prec@1 86.000 (84.650) Prec@5 100.000 (99.100) +2022-11-14 13:35:46,416 Epoch: [65][200/500] Time 0.024 (0.026) Data 0.002 (0.003) Loss 0.1196 (0.0911) Prec@1 79.000 (84.381) Prec@5 98.000 (99.048) +2022-11-14 13:35:46,734 Epoch: [65][210/500] Time 0.032 (0.026) Data 0.002 (0.003) Loss 0.1112 (0.0920) Prec@1 83.000 (84.318) Prec@5 97.000 (98.955) +2022-11-14 13:35:47,051 Epoch: [65][220/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.1058 (0.0926) Prec@1 81.000 (84.174) Prec@5 99.000 (98.957) +2022-11-14 13:35:47,367 Epoch: [65][230/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.1029 (0.0930) Prec@1 82.000 (84.083) Prec@5 100.000 (99.000) +2022-11-14 13:35:47,682 Epoch: [65][240/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0791 (0.0925) Prec@1 84.000 (84.080) Prec@5 97.000 (98.920) +2022-11-14 13:35:47,993 Epoch: [65][250/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0885 (0.0923) Prec@1 82.000 (84.000) Prec@5 98.000 (98.885) +2022-11-14 13:35:48,303 Epoch: [65][260/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0644 (0.0913) Prec@1 88.000 (84.148) Prec@5 100.000 (98.926) +2022-11-14 13:35:48,616 Epoch: [65][270/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.1064 (0.0918) Prec@1 83.000 (84.107) Prec@5 99.000 (98.929) +2022-11-14 13:35:48,933 Epoch: [65][280/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0973 (0.0920) Prec@1 81.000 (84.000) Prec@5 99.000 (98.931) +2022-11-14 13:35:49,242 Epoch: [65][290/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.1058 (0.0925) Prec@1 81.000 (83.900) Prec@5 99.000 (98.933) +2022-11-14 13:35:49,548 Epoch: [65][300/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.1152 (0.0932) Prec@1 80.000 (83.774) Prec@5 97.000 (98.871) +2022-11-14 13:35:49,861 Epoch: [65][310/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.1148 (0.0939) Prec@1 81.000 (83.688) Prec@5 96.000 (98.781) +2022-11-14 13:35:50,168 Epoch: [65][320/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.1109 (0.0944) Prec@1 80.000 (83.576) Prec@5 99.000 (98.788) +2022-11-14 13:35:50,478 Epoch: [65][330/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0932 (0.0944) Prec@1 82.000 (83.529) Prec@5 100.000 (98.824) +2022-11-14 13:35:50,786 Epoch: [65][340/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.1069 (0.0947) Prec@1 83.000 (83.514) Prec@5 98.000 (98.800) +2022-11-14 13:35:51,103 Epoch: [65][350/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0697 (0.0940) Prec@1 86.000 (83.583) Prec@5 98.000 (98.778) +2022-11-14 13:35:51,423 Epoch: [65][360/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0931 (0.0940) Prec@1 87.000 (83.676) Prec@5 99.000 (98.784) +2022-11-14 13:35:51,827 Epoch: [65][370/500] Time 0.042 (0.027) Data 0.002 (0.002) Loss 0.0990 (0.0941) Prec@1 83.000 (83.658) Prec@5 98.000 (98.763) +2022-11-14 13:35:52,288 Epoch: [65][380/500] Time 0.043 (0.027) Data 0.002 (0.002) Loss 0.0908 (0.0940) Prec@1 84.000 (83.667) Prec@5 99.000 (98.769) +2022-11-14 13:35:52,749 Epoch: [65][390/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0755 (0.0936) Prec@1 87.000 (83.750) Prec@5 99.000 (98.775) +2022-11-14 13:35:53,209 Epoch: [65][400/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0999 (0.0937) Prec@1 84.000 (83.756) Prec@5 97.000 (98.732) +2022-11-14 13:35:53,672 Epoch: [65][410/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.1045 (0.0940) Prec@1 80.000 (83.667) Prec@5 98.000 (98.714) +2022-11-14 13:35:54,133 Epoch: [65][420/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.0861 (0.0938) Prec@1 86.000 (83.721) Prec@5 99.000 (98.721) +2022-11-14 13:35:54,593 Epoch: [65][430/500] Time 0.044 (0.029) Data 0.002 (0.002) Loss 0.0636 (0.0931) Prec@1 90.000 (83.864) Prec@5 100.000 (98.750) +2022-11-14 13:35:55,054 Epoch: [65][440/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.1197 (0.0937) Prec@1 80.000 (83.778) Prec@5 98.000 (98.733) +2022-11-14 13:35:55,517 Epoch: [65][450/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0695 (0.0932) Prec@1 88.000 (83.870) Prec@5 99.000 (98.739) +2022-11-14 13:35:55,977 Epoch: [65][460/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.0977 (0.0933) Prec@1 84.000 (83.872) Prec@5 98.000 (98.723) +2022-11-14 13:35:56,438 Epoch: [65][470/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.1172 (0.0938) Prec@1 83.000 (83.854) Prec@5 97.000 (98.688) +2022-11-14 13:35:56,900 Epoch: [65][480/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.1013 (0.0939) Prec@1 83.000 (83.837) Prec@5 99.000 (98.694) +2022-11-14 13:35:57,360 Epoch: [65][490/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0908 (0.0939) Prec@1 85.000 (83.860) Prec@5 100.000 (98.720) +2022-11-14 13:35:57,777 Epoch: [65][499/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0827 (0.0937) Prec@1 84.000 (83.863) Prec@5 99.000 (98.725) +2022-11-14 13:35:58,050 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0729 (0.0729) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 13:35:58,061 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0883) Prec@1 82.000 (85.500) Prec@5 99.000 (98.500) +2022-11-14 13:35:58,068 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.0970) Prec@1 76.000 (82.333) Prec@5 99.000 (98.667) +2022-11-14 13:35:58,078 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0999) Prec@1 85.000 (83.000) Prec@5 99.000 (98.750) +2022-11-14 13:35:58,087 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1054) Prec@1 77.000 (81.800) Prec@5 98.000 (98.600) +2022-11-14 13:35:58,097 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0984) Prec@1 90.000 (83.167) Prec@5 99.000 (98.667) +2022-11-14 13:35:58,107 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0998) Prec@1 83.000 (83.143) Prec@5 100.000 (98.857) +2022-11-14 13:35:58,118 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1198 (0.1023) Prec@1 81.000 (82.875) Prec@5 99.000 (98.875) +2022-11-14 13:35:58,128 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1407 (0.1066) Prec@1 77.000 (82.222) Prec@5 99.000 (98.889) +2022-11-14 13:35:58,138 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.1053) Prec@1 86.000 (82.600) Prec@5 99.000 (98.900) +2022-11-14 13:35:58,149 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.1038) Prec@1 85.000 (82.818) Prec@5 100.000 (99.000) +2022-11-14 13:35:58,162 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.1026) Prec@1 84.000 (82.917) Prec@5 99.000 (99.000) +2022-11-14 13:35:58,173 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.1039) Prec@1 78.000 (82.538) Prec@5 100.000 (99.077) +2022-11-14 13:35:58,185 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.1043) Prec@1 82.000 (82.500) Prec@5 97.000 (98.929) +2022-11-14 13:35:58,196 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.1044) Prec@1 81.000 (82.400) Prec@5 99.000 (98.933) +2022-11-14 13:35:58,209 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1219 (0.1055) Prec@1 76.000 (82.000) Prec@5 98.000 (98.875) +2022-11-14 13:35:58,221 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.1045) Prec@1 84.000 (82.118) Prec@5 98.000 (98.824) +2022-11-14 13:35:58,232 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1144 (0.1051) Prec@1 78.000 (81.889) Prec@5 98.000 (98.778) +2022-11-14 13:35:58,244 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1452 (0.1072) Prec@1 74.000 (81.474) Prec@5 98.000 (98.737) +2022-11-14 13:35:58,257 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.1075) Prec@1 83.000 (81.550) Prec@5 98.000 (98.700) +2022-11-14 13:35:58,268 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.1076) Prec@1 80.000 (81.476) Prec@5 98.000 (98.667) +2022-11-14 13:35:58,279 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.1074) Prec@1 82.000 (81.500) Prec@5 98.000 (98.636) +2022-11-14 13:35:58,291 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1333 (0.1085) Prec@1 77.000 (81.304) Prec@5 96.000 (98.522) +2022-11-14 13:35:58,303 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.1070) Prec@1 88.000 (81.583) Prec@5 100.000 (98.583) +2022-11-14 13:35:58,315 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1072) Prec@1 82.000 (81.600) Prec@5 99.000 (98.600) +2022-11-14 13:35:58,328 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1438 (0.1086) Prec@1 75.000 (81.346) Prec@5 96.000 (98.500) +2022-11-14 13:35:58,340 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.1082) Prec@1 82.000 (81.370) Prec@5 99.000 (98.519) +2022-11-14 13:35:58,352 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.1084) Prec@1 81.000 (81.357) Prec@5 100.000 (98.571) +2022-11-14 13:35:58,363 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1325 (0.1092) Prec@1 79.000 (81.276) Prec@5 96.000 (98.483) +2022-11-14 13:35:58,376 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.1090) Prec@1 83.000 (81.333) Prec@5 100.000 (98.533) +2022-11-14 13:35:58,388 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1273 (0.1096) Prec@1 74.000 (81.097) Prec@5 98.000 (98.516) +2022-11-14 13:35:58,401 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.1093) Prec@1 83.000 (81.156) Prec@5 99.000 (98.531) +2022-11-14 13:35:58,412 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.1095) Prec@1 77.000 (81.030) Prec@5 98.000 (98.515) +2022-11-14 13:35:58,425 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1397 (0.1104) Prec@1 76.000 (80.882) Prec@5 97.000 (98.471) +2022-11-14 13:35:58,437 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.1099) Prec@1 87.000 (81.057) Prec@5 98.000 (98.457) +2022-11-14 13:35:58,448 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.1096) Prec@1 82.000 (81.083) Prec@5 98.000 (98.444) +2022-11-14 13:35:58,460 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1203 (0.1099) Prec@1 83.000 (81.135) Prec@5 98.000 (98.432) +2022-11-14 13:35:58,473 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1245 (0.1103) Prec@1 78.000 (81.053) Prec@5 98.000 (98.421) +2022-11-14 13:35:58,486 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1129 (0.1104) Prec@1 80.000 (81.026) Prec@5 100.000 (98.462) +2022-11-14 13:35:58,497 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.1106) Prec@1 82.000 (81.050) Prec@5 96.000 (98.400) +2022-11-14 13:35:58,508 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1326 (0.1111) Prec@1 76.000 (80.927) Prec@5 98.000 (98.390) +2022-11-14 13:35:58,521 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.1111) Prec@1 81.000 (80.929) Prec@5 99.000 (98.405) +2022-11-14 13:35:58,533 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.1107) Prec@1 84.000 (81.000) Prec@5 100.000 (98.442) +2022-11-14 13:35:58,544 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.1104) Prec@1 86.000 (81.114) Prec@5 99.000 (98.455) +2022-11-14 13:35:58,556 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.1102) Prec@1 82.000 (81.133) Prec@5 99.000 (98.467) +2022-11-14 13:35:58,569 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1586 (0.1113) Prec@1 69.000 (80.870) Prec@5 100.000 (98.500) +2022-11-14 13:35:58,581 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.1107) Prec@1 85.000 (80.957) Prec@5 100.000 (98.532) +2022-11-14 13:35:58,592 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.1103) Prec@1 88.000 (81.104) Prec@5 100.000 (98.562) +2022-11-14 13:35:58,605 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.1100) Prec@1 85.000 (81.184) Prec@5 100.000 (98.592) +2022-11-14 13:35:58,617 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1375 (0.1105) Prec@1 75.000 (81.060) Prec@5 97.000 (98.560) +2022-11-14 13:35:58,629 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.1109) Prec@1 76.000 (80.961) Prec@5 99.000 (98.569) +2022-11-14 13:35:58,641 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1226 (0.1112) Prec@1 77.000 (80.885) Prec@5 97.000 (98.538) +2022-11-14 13:35:58,654 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1184 (0.1113) Prec@1 80.000 (80.868) Prec@5 99.000 (98.547) +2022-11-14 13:35:58,666 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.1111) Prec@1 85.000 (80.944) Prec@5 99.000 (98.556) +2022-11-14 13:35:58,679 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1290 (0.1114) Prec@1 78.000 (80.891) Prec@5 99.000 (98.564) +2022-11-14 13:35:58,690 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.1113) Prec@1 81.000 (80.893) Prec@5 99.000 (98.571) +2022-11-14 13:35:58,704 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1206 (0.1114) Prec@1 81.000 (80.895) Prec@5 97.000 (98.544) +2022-11-14 13:35:58,718 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.1110) Prec@1 85.000 (80.966) Prec@5 99.000 (98.552) +2022-11-14 13:35:58,731 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1389 (0.1115) Prec@1 76.000 (80.881) Prec@5 100.000 (98.576) +2022-11-14 13:35:58,745 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1496 (0.1121) Prec@1 77.000 (80.817) Prec@5 96.000 (98.533) +2022-11-14 13:35:58,757 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1171 (0.1122) Prec@1 80.000 (80.803) Prec@5 100.000 (98.557) +2022-11-14 13:35:58,769 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1271 (0.1124) Prec@1 79.000 (80.774) Prec@5 97.000 (98.532) +2022-11-14 13:35:58,780 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.1122) Prec@1 83.000 (80.810) Prec@5 99.000 (98.540) +2022-11-14 13:35:58,792 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.1117) Prec@1 86.000 (80.891) Prec@5 100.000 (98.562) +2022-11-14 13:35:58,804 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1392 (0.1121) Prec@1 75.000 (80.800) Prec@5 96.000 (98.523) +2022-11-14 13:35:58,814 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.1122) Prec@1 81.000 (80.803) Prec@5 99.000 (98.530) +2022-11-14 13:35:58,826 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.1118) Prec@1 85.000 (80.866) Prec@5 100.000 (98.552) +2022-11-14 13:35:58,838 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1034 (0.1117) Prec@1 82.000 (80.882) Prec@5 99.000 (98.559) +2022-11-14 13:35:58,849 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.1115) Prec@1 84.000 (80.928) Prec@5 99.000 (98.565) +2022-11-14 13:35:58,862 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1473 (0.1120) Prec@1 74.000 (80.829) Prec@5 99.000 (98.571) +2022-11-14 13:35:58,874 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.1120) Prec@1 78.000 (80.789) Prec@5 98.000 (98.563) +2022-11-14 13:35:58,886 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1167 (0.1121) Prec@1 78.000 (80.750) Prec@5 99.000 (98.569) +2022-11-14 13:35:58,898 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.1119) Prec@1 82.000 (80.767) Prec@5 99.000 (98.575) +2022-11-14 13:35:58,911 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1117) Prec@1 81.000 (80.770) Prec@5 100.000 (98.595) +2022-11-14 13:35:58,923 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1282 (0.1120) Prec@1 78.000 (80.733) Prec@5 99.000 (98.600) +2022-11-14 13:35:58,935 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1201 (0.1121) Prec@1 78.000 (80.697) Prec@5 98.000 (98.592) +2022-11-14 13:35:58,947 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.1118) Prec@1 84.000 (80.740) Prec@5 99.000 (98.597) +2022-11-14 13:35:58,959 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.1117) Prec@1 79.000 (80.718) Prec@5 97.000 (98.577) +2022-11-14 13:35:58,972 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1239 (0.1118) Prec@1 80.000 (80.709) Prec@5 99.000 (98.582) +2022-11-14 13:35:58,984 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.1117) Prec@1 80.000 (80.700) Prec@5 98.000 (98.575) +2022-11-14 13:35:58,995 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.1116) Prec@1 82.000 (80.716) Prec@5 97.000 (98.556) +2022-11-14 13:35:59,007 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1284 (0.1118) Prec@1 78.000 (80.683) Prec@5 96.000 (98.524) +2022-11-14 13:35:59,019 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.1117) Prec@1 84.000 (80.723) Prec@5 99.000 (98.530) +2022-11-14 13:35:59,030 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1338 (0.1120) Prec@1 78.000 (80.690) Prec@5 100.000 (98.548) +2022-11-14 13:35:59,042 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1323 (0.1122) Prec@1 78.000 (80.659) Prec@5 99.000 (98.553) +2022-11-14 13:35:59,054 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.1123) Prec@1 80.000 (80.651) Prec@5 100.000 (98.570) +2022-11-14 13:35:59,065 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.1125) Prec@1 75.000 (80.586) Prec@5 99.000 (98.575) +2022-11-14 13:35:59,078 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1179 (0.1126) Prec@1 80.000 (80.580) Prec@5 98.000 (98.568) +2022-11-14 13:35:59,090 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.1126) Prec@1 82.000 (80.596) Prec@5 97.000 (98.551) +2022-11-14 13:35:59,103 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1294 (0.1128) Prec@1 80.000 (80.589) Prec@5 99.000 (98.556) +2022-11-14 13:35:59,114 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.1125) Prec@1 84.000 (80.626) Prec@5 100.000 (98.571) +2022-11-14 13:35:59,128 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.1122) Prec@1 87.000 (80.696) Prec@5 99.000 (98.576) +2022-11-14 13:35:59,141 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1216 (0.1123) Prec@1 78.000 (80.667) Prec@5 99.000 (98.581) +2022-11-14 13:35:59,153 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1234 (0.1124) Prec@1 78.000 (80.638) Prec@5 95.000 (98.543) +2022-11-14 13:35:59,165 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.1123) Prec@1 83.000 (80.663) Prec@5 99.000 (98.547) +2022-11-14 13:35:59,176 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.1121) Prec@1 86.000 (80.719) Prec@5 98.000 (98.542) +2022-11-14 13:35:59,189 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.1119) Prec@1 82.000 (80.732) Prec@5 100.000 (98.557) +2022-11-14 13:35:59,202 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1499 (0.1123) Prec@1 73.000 (80.653) Prec@5 99.000 (98.561) +2022-11-14 13:35:59,214 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1206 (0.1124) Prec@1 82.000 (80.667) Prec@5 100.000 (98.576) +2022-11-14 13:35:59,225 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.1124) Prec@1 80.000 (80.660) Prec@5 99.000 (98.580) +2022-11-14 13:35:59,280 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:35:59,581 Epoch: [66][0/500] Time 0.023 (0.023) Data 0.218 (0.218) Loss 0.1128 (0.1128) Prec@1 83.000 (83.000) Prec@5 98.000 (98.000) +2022-11-14 13:35:59,788 Epoch: [66][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.1150 (0.1139) Prec@1 79.000 (81.000) Prec@5 98.000 (98.000) +2022-11-14 13:35:59,987 Epoch: [66][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0912 (0.1064) Prec@1 85.000 (82.333) Prec@5 100.000 (98.667) +2022-11-14 13:36:00,255 Epoch: [66][30/500] Time 0.025 (0.020) Data 0.002 (0.009) Loss 0.1042 (0.1058) Prec@1 83.000 (82.500) Prec@5 99.000 (98.750) +2022-11-14 13:36:00,529 Epoch: [66][40/500] Time 0.027 (0.021) Data 0.002 (0.007) Loss 0.1031 (0.1053) Prec@1 81.000 (82.200) Prec@5 100.000 (99.000) +2022-11-14 13:36:00,803 Epoch: [66][50/500] Time 0.025 (0.022) Data 0.002 (0.006) Loss 0.0710 (0.0996) Prec@1 87.000 (83.000) Prec@5 98.000 (98.833) +2022-11-14 13:36:01,148 Epoch: [66][60/500] Time 0.031 (0.023) Data 0.002 (0.005) Loss 0.0950 (0.0989) Prec@1 82.000 (82.857) Prec@5 99.000 (98.857) +2022-11-14 13:36:01,406 Epoch: [66][70/500] Time 0.024 (0.023) Data 0.002 (0.005) Loss 0.0956 (0.0985) Prec@1 80.000 (82.500) Prec@5 97.000 (98.625) +2022-11-14 13:36:01,683 Epoch: [66][80/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0825 (0.0967) Prec@1 84.000 (82.667) Prec@5 100.000 (98.778) +2022-11-14 13:36:01,958 Epoch: [66][90/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.1072 (0.0978) Prec@1 79.000 (82.300) Prec@5 97.000 (98.600) +2022-11-14 13:36:02,231 Epoch: [66][100/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.1166 (0.0995) Prec@1 81.000 (82.182) Prec@5 96.000 (98.364) +2022-11-14 13:36:02,553 Epoch: [66][110/500] Time 0.041 (0.024) Data 0.002 (0.004) Loss 0.0817 (0.0980) Prec@1 86.000 (82.500) Prec@5 100.000 (98.500) +2022-11-14 13:36:03,044 Epoch: [66][120/500] Time 0.036 (0.025) Data 0.002 (0.004) Loss 0.0797 (0.0966) Prec@1 88.000 (82.923) Prec@5 99.000 (98.538) +2022-11-14 13:36:03,486 Epoch: [66][130/500] Time 0.044 (0.026) Data 0.002 (0.003) Loss 0.0476 (0.0931) Prec@1 93.000 (83.643) Prec@5 100.000 (98.643) +2022-11-14 13:36:03,947 Epoch: [66][140/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.1044 (0.0938) Prec@1 82.000 (83.533) Prec@5 98.000 (98.600) +2022-11-14 13:36:04,404 Epoch: [66][150/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0762 (0.0927) Prec@1 88.000 (83.812) Prec@5 99.000 (98.625) +2022-11-14 13:36:04,862 Epoch: [66][160/500] Time 0.042 (0.029) Data 0.002 (0.003) Loss 0.0906 (0.0926) Prec@1 85.000 (83.882) Prec@5 99.000 (98.647) +2022-11-14 13:36:05,307 Epoch: [66][170/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0917 (0.0926) Prec@1 85.000 (83.944) Prec@5 99.000 (98.667) +2022-11-14 13:36:05,755 Epoch: [66][180/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.1062 (0.0933) Prec@1 84.000 (83.947) Prec@5 99.000 (98.684) +2022-11-14 13:36:06,207 Epoch: [66][190/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0889 (0.0931) Prec@1 85.000 (84.000) Prec@5 98.000 (98.650) +2022-11-14 13:36:06,661 Epoch: [66][200/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0846 (0.0927) Prec@1 88.000 (84.190) Prec@5 100.000 (98.714) +2022-11-14 13:36:07,148 Epoch: [66][210/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0954 (0.0928) Prec@1 84.000 (84.182) Prec@5 99.000 (98.727) +2022-11-14 13:36:07,609 Epoch: [66][220/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0781 (0.0921) Prec@1 87.000 (84.304) Prec@5 98.000 (98.696) +2022-11-14 13:36:08,067 Epoch: [66][230/500] Time 0.045 (0.033) Data 0.002 (0.003) Loss 0.1339 (0.0939) Prec@1 75.000 (83.917) Prec@5 97.000 (98.625) +2022-11-14 13:36:08,529 Epoch: [66][240/500] Time 0.047 (0.033) Data 0.002 (0.003) Loss 0.0805 (0.0934) Prec@1 84.000 (83.920) Prec@5 98.000 (98.600) +2022-11-14 13:36:08,992 Epoch: [66][250/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0969 (0.0935) Prec@1 84.000 (83.923) Prec@5 100.000 (98.654) +2022-11-14 13:36:09,452 Epoch: [66][260/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0813 (0.0930) Prec@1 87.000 (84.037) Prec@5 98.000 (98.630) +2022-11-14 13:36:09,908 Epoch: [66][270/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0844 (0.0927) Prec@1 84.000 (84.036) Prec@5 99.000 (98.643) +2022-11-14 13:36:10,373 Epoch: [66][280/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.1222 (0.0937) Prec@1 72.000 (83.621) Prec@5 99.000 (98.655) +2022-11-14 13:36:10,817 Epoch: [66][290/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0758 (0.0931) Prec@1 89.000 (83.800) Prec@5 99.000 (98.667) +2022-11-14 13:36:11,259 Epoch: [66][300/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0917 (0.0931) Prec@1 84.000 (83.806) Prec@5 97.000 (98.613) +2022-11-14 13:36:11,718 Epoch: [66][310/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.1120 (0.0937) Prec@1 80.000 (83.688) Prec@5 100.000 (98.656) +2022-11-14 13:36:12,183 Epoch: [66][320/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0977 (0.0938) Prec@1 82.000 (83.636) Prec@5 97.000 (98.606) +2022-11-14 13:36:12,649 Epoch: [66][330/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0928 (0.0938) Prec@1 84.000 (83.647) Prec@5 98.000 (98.588) +2022-11-14 13:36:13,105 Epoch: [66][340/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0974 (0.0939) Prec@1 84.000 (83.657) Prec@5 99.000 (98.600) +2022-11-14 13:36:13,539 Epoch: [66][350/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0717 (0.0933) Prec@1 90.000 (83.833) Prec@5 100.000 (98.639) +2022-11-14 13:36:13,990 Epoch: [66][360/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.1134 (0.0938) Prec@1 79.000 (83.703) Prec@5 99.000 (98.649) +2022-11-14 13:36:14,442 Epoch: [66][370/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0984 (0.0939) Prec@1 85.000 (83.737) Prec@5 99.000 (98.658) +2022-11-14 13:36:14,892 Epoch: [66][380/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0861 (0.0937) Prec@1 88.000 (83.846) Prec@5 99.000 (98.667) +2022-11-14 13:36:15,330 Epoch: [66][390/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.1327 (0.0947) Prec@1 77.000 (83.675) Prec@5 99.000 (98.675) +2022-11-14 13:36:15,783 Epoch: [66][400/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1207 (0.0953) Prec@1 80.000 (83.585) Prec@5 98.000 (98.659) +2022-11-14 13:36:16,233 Epoch: [66][410/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0993 (0.0954) Prec@1 82.000 (83.548) Prec@5 98.000 (98.643) +2022-11-14 13:36:16,678 Epoch: [66][420/500] Time 0.049 (0.036) Data 0.002 (0.002) Loss 0.1048 (0.0957) Prec@1 82.000 (83.512) Prec@5 96.000 (98.581) +2022-11-14 13:36:17,115 Epoch: [66][430/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1022 (0.0958) Prec@1 82.000 (83.477) Prec@5 97.000 (98.545) +2022-11-14 13:36:17,559 Epoch: [66][440/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0958 (0.0958) Prec@1 83.000 (83.467) Prec@5 98.000 (98.533) +2022-11-14 13:36:18,016 Epoch: [66][450/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0861 (0.0956) Prec@1 85.000 (83.500) Prec@5 98.000 (98.522) +2022-11-14 13:36:18,449 Epoch: [66][460/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0753 (0.0952) Prec@1 85.000 (83.532) Prec@5 100.000 (98.553) +2022-11-14 13:36:18,891 Epoch: [66][470/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0902 (0.0951) Prec@1 85.000 (83.562) Prec@5 98.000 (98.542) +2022-11-14 13:36:19,163 Epoch: [66][480/500] Time 0.026 (0.036) Data 0.002 (0.002) Loss 0.0856 (0.0949) Prec@1 86.000 (83.612) Prec@5 99.000 (98.551) +2022-11-14 13:36:19,439 Epoch: [66][490/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.1120 (0.0952) Prec@1 80.000 (83.540) Prec@5 98.000 (98.540) +2022-11-14 13:36:19,687 Epoch: [66][499/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.1176 (0.0956) Prec@1 79.000 (83.451) Prec@5 98.000 (98.529) +2022-11-14 13:36:19,965 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1169 (0.1169) Prec@1 77.000 (77.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:19,975 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1095 (0.1132) Prec@1 83.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:19,984 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.1087) Prec@1 82.000 (80.667) Prec@5 98.000 (98.667) +2022-11-14 13:36:19,995 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1092) Prec@1 79.000 (80.250) Prec@5 100.000 (99.000) +2022-11-14 13:36:20,003 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1191 (0.1112) Prec@1 79.000 (80.000) Prec@5 98.000 (98.800) +2022-11-14 13:36:20,011 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1100) Prec@1 82.000 (80.333) Prec@5 99.000 (98.833) +2022-11-14 13:36:20,018 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.1089) Prec@1 83.000 (80.714) Prec@5 99.000 (98.857) +2022-11-14 13:36:20,028 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.1093) Prec@1 79.000 (80.500) Prec@5 99.000 (98.875) +2022-11-14 13:36:20,036 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.1098) Prec@1 79.000 (80.333) Prec@5 100.000 (99.000) +2022-11-14 13:36:20,044 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1090) Prec@1 80.000 (80.300) Prec@5 99.000 (99.000) +2022-11-14 13:36:20,054 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.1083) Prec@1 85.000 (80.727) Prec@5 100.000 (99.091) +2022-11-14 13:36:20,063 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1041 (0.1080) Prec@1 82.000 (80.833) Prec@5 98.000 (99.000) +2022-11-14 13:36:20,073 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1041 (0.1077) Prec@1 79.000 (80.692) Prec@5 99.000 (99.000) +2022-11-14 13:36:20,083 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.1072) Prec@1 82.000 (80.786) Prec@5 98.000 (98.929) +2022-11-14 13:36:20,092 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1074) Prec@1 82.000 (80.867) Prec@5 99.000 (98.933) +2022-11-14 13:36:20,101 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.1079) Prec@1 80.000 (80.812) Prec@5 98.000 (98.875) +2022-11-14 13:36:20,110 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.1062) Prec@1 87.000 (81.176) Prec@5 98.000 (98.824) +2022-11-14 13:36:20,120 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.1068) Prec@1 78.000 (81.000) Prec@5 99.000 (98.833) +2022-11-14 13:36:20,129 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1250 (0.1077) Prec@1 76.000 (80.737) Prec@5 97.000 (98.737) +2022-11-14 13:36:20,138 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1204 (0.1084) Prec@1 78.000 (80.600) Prec@5 96.000 (98.600) +2022-11-14 13:36:20,147 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.1087) Prec@1 81.000 (80.619) Prec@5 99.000 (98.619) +2022-11-14 13:36:20,156 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1109 (0.1088) Prec@1 81.000 (80.636) Prec@5 98.000 (98.591) +2022-11-14 13:36:20,166 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1429 (0.1103) Prec@1 74.000 (80.348) Prec@5 98.000 (98.565) +2022-11-14 13:36:20,175 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1188 (0.1107) Prec@1 74.000 (80.083) Prec@5 99.000 (98.583) +2022-11-14 13:36:20,185 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1252 (0.1113) Prec@1 80.000 (80.080) Prec@5 99.000 (98.600) +2022-11-14 13:36:20,194 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.1121) Prec@1 75.000 (79.885) Prec@5 98.000 (98.577) +2022-11-14 13:36:20,203 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.1106) Prec@1 87.000 (80.148) Prec@5 99.000 (98.593) +2022-11-14 13:36:20,213 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1157 (0.1108) Prec@1 80.000 (80.143) Prec@5 99.000 (98.607) +2022-11-14 13:36:20,221 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.1107) Prec@1 82.000 (80.207) Prec@5 97.000 (98.552) +2022-11-14 13:36:20,229 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.1106) Prec@1 80.000 (80.200) Prec@5 98.000 (98.533) +2022-11-14 13:36:20,237 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1110) Prec@1 81.000 (80.226) Prec@5 99.000 (98.548) +2022-11-14 13:36:20,247 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1199 (0.1113) Prec@1 81.000 (80.250) Prec@5 99.000 (98.562) +2022-11-14 13:36:20,256 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.1111) Prec@1 83.000 (80.333) Prec@5 95.000 (98.455) +2022-11-14 13:36:20,266 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1454 (0.1121) Prec@1 70.000 (80.029) Prec@5 100.000 (98.500) +2022-11-14 13:36:20,274 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1194 (0.1123) Prec@1 81.000 (80.057) Prec@5 95.000 (98.400) +2022-11-14 13:36:20,283 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.1121) Prec@1 86.000 (80.222) Prec@5 97.000 (98.361) +2022-11-14 13:36:20,292 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1212 (0.1123) Prec@1 78.000 (80.162) Prec@5 97.000 (98.324) +2022-11-14 13:36:20,301 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1269 (0.1127) Prec@1 76.000 (80.053) Prec@5 98.000 (98.316) +2022-11-14 13:36:20,310 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.1124) Prec@1 83.000 (80.128) Prec@5 99.000 (98.333) +2022-11-14 13:36:20,319 Test: 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0.1215 (0.1119) Prec@1 75.000 (80.283) Prec@5 99.000 (98.391) +2022-11-14 13:36:20,384 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.1117) Prec@1 82.000 (80.319) Prec@5 99.000 (98.404) +2022-11-14 13:36:20,394 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.1119) Prec@1 77.000 (80.250) Prec@5 99.000 (98.417) +2022-11-14 13:36:20,403 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.1113) Prec@1 87.000 (80.388) Prec@5 99.000 (98.429) +2022-11-14 13:36:20,411 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1546 (0.1122) Prec@1 70.000 (80.180) Prec@5 99.000 (98.440) +2022-11-14 13:36:20,421 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.1121) Prec@1 81.000 (80.196) Prec@5 98.000 (98.431) +2022-11-14 13:36:20,430 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1640 (0.1131) Prec@1 71.000 (80.019) Prec@5 95.000 (98.365) +2022-11-14 13:36:20,439 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.1127) Prec@1 84.000 (80.094) Prec@5 99.000 (98.377) +2022-11-14 13:36:20,448 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1136 (0.1128) Prec@1 80.000 (80.093) Prec@5 99.000 (98.389) +2022-11-14 13:36:20,457 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1260 (0.1130) Prec@1 76.000 (80.018) Prec@5 100.000 (98.418) +2022-11-14 13:36:20,466 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.1128) Prec@1 85.000 (80.107) Prec@5 99.000 (98.429) +2022-11-14 13:36:20,476 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1247 (0.1130) Prec@1 80.000 (80.105) Prec@5 99.000 (98.439) +2022-11-14 13:36:20,486 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.1128) Prec@1 87.000 (80.224) Prec@5 99.000 (98.448) +2022-11-14 13:36:20,496 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1468 (0.1134) Prec@1 74.000 (80.119) Prec@5 98.000 (98.441) +2022-11-14 13:36:20,506 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.1133) Prec@1 81.000 (80.133) Prec@5 98.000 (98.433) +2022-11-14 13:36:20,515 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.1133) Prec@1 82.000 (80.164) Prec@5 98.000 (98.426) +2022-11-14 13:36:20,524 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.1131) Prec@1 78.000 (80.129) Prec@5 99.000 (98.435) +2022-11-14 13:36:20,533 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.1129) Prec@1 80.000 (80.127) Prec@5 100.000 (98.460) +2022-11-14 13:36:20,541 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.1124) Prec@1 87.000 (80.234) Prec@5 100.000 (98.484) +2022-11-14 13:36:20,549 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1258 (0.1126) Prec@1 78.000 (80.200) Prec@5 99.000 (98.492) +2022-11-14 13:36:20,559 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1518 (0.1132) Prec@1 77.000 (80.152) Prec@5 97.000 (98.470) +2022-11-14 13:36:20,569 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.1132) Prec@1 80.000 (80.149) Prec@5 97.000 (98.448) +2022-11-14 13:36:20,578 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1112 (0.1132) Prec@1 77.000 (80.103) Prec@5 99.000 (98.456) +2022-11-14 13:36:20,588 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1114 (0.1132) Prec@1 82.000 (80.130) Prec@5 97.000 (98.435) +2022-11-14 13:36:20,597 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1448 (0.1136) Prec@1 73.000 (80.029) Prec@5 98.000 (98.429) +2022-11-14 13:36:20,606 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.1133) Prec@1 86.000 (80.113) Prec@5 100.000 (98.451) +2022-11-14 13:36:20,617 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1274 (0.1135) Prec@1 75.000 (80.042) Prec@5 99.000 (98.458) +2022-11-14 13:36:20,626 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.1133) Prec@1 82.000 (80.068) Prec@5 100.000 (98.479) +2022-11-14 13:36:20,635 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.1129) Prec@1 86.000 (80.149) Prec@5 100.000 (98.500) +2022-11-14 13:36:20,645 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1284 (0.1131) Prec@1 76.000 (80.093) Prec@5 98.000 (98.493) +2022-11-14 13:36:20,654 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.1128) Prec@1 87.000 (80.184) Prec@5 100.000 (98.513) +2022-11-14 13:36:20,663 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.1127) Prec@1 81.000 (80.195) Prec@5 99.000 (98.519) +2022-11-14 13:36:20,672 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.1126) Prec@1 83.000 (80.231) Prec@5 99.000 (98.526) +2022-11-14 13:36:20,681 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1226 (0.1127) Prec@1 81.000 (80.241) Prec@5 97.000 (98.506) +2022-11-14 13:36:20,692 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.1126) Prec@1 80.000 (80.237) Prec@5 99.000 (98.513) +2022-11-14 13:36:20,700 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1105 (0.1126) Prec@1 80.000 (80.235) Prec@5 98.000 (98.506) +2022-11-14 13:36:20,709 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.1124) Prec@1 82.000 (80.256) Prec@5 98.000 (98.500) +2022-11-14 13:36:20,718 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1284 (0.1126) Prec@1 75.000 (80.193) Prec@5 99.000 (98.506) +2022-11-14 13:36:20,729 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1231 (0.1127) Prec@1 79.000 (80.179) Prec@5 99.000 (98.512) +2022-11-14 13:36:20,739 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1302 (0.1130) Prec@1 78.000 (80.153) Prec@5 97.000 (98.494) +2022-11-14 13:36:20,749 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1172 (0.1130) Prec@1 79.000 (80.140) Prec@5 100.000 (98.512) +2022-11-14 13:36:20,758 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.1130) Prec@1 80.000 (80.138) Prec@5 99.000 (98.517) +2022-11-14 13:36:20,768 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1229 (0.1131) Prec@1 79.000 (80.125) Prec@5 99.000 (98.523) +2022-11-14 13:36:20,777 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.1130) Prec@1 79.000 (80.112) Prec@5 100.000 (98.539) +2022-11-14 13:36:20,786 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1258 (0.1131) Prec@1 80.000 (80.111) Prec@5 97.000 (98.522) +2022-11-14 13:36:20,796 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.1130) Prec@1 84.000 (80.154) Prec@5 100.000 (98.538) +2022-11-14 13:36:20,804 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.1125) Prec@1 88.000 (80.239) Prec@5 99.000 (98.543) +2022-11-14 13:36:20,813 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1352 (0.1128) Prec@1 76.000 (80.194) Prec@5 100.000 (98.559) +2022-11-14 13:36:20,823 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.1127) Prec@1 82.000 (80.213) Prec@5 99.000 (98.564) +2022-11-14 13:36:20,831 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.1125) Prec@1 86.000 (80.274) Prec@5 98.000 (98.558) +2022-11-14 13:36:20,839 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.1123) Prec@1 84.000 (80.312) Prec@5 98.000 (98.552) +2022-11-14 13:36:20,848 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.1122) Prec@1 82.000 (80.330) Prec@5 98.000 (98.546) +2022-11-14 13:36:20,858 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1335 (0.1124) Prec@1 78.000 (80.306) Prec@5 99.000 (98.551) +2022-11-14 13:36:20,867 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1438 (0.1128) Prec@1 73.000 (80.232) Prec@5 100.000 (98.566) +2022-11-14 13:36:20,876 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.1126) Prec@1 82.000 (80.250) Prec@5 100.000 (98.580) +2022-11-14 13:36:20,931 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:36:21,238 Epoch: [67][0/500] Time 0.023 (0.023) Data 0.225 (0.225) Loss 0.0861 (0.0861) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:36:21,445 Epoch: [67][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0959 (0.0910) Prec@1 81.000 (83.000) Prec@5 99.000 (98.500) +2022-11-14 13:36:21,655 Epoch: [67][20/500] Time 0.020 (0.019) Data 0.002 (0.012) Loss 0.0760 (0.0860) Prec@1 85.000 (83.667) Prec@5 99.000 (98.667) +2022-11-14 13:36:21,863 Epoch: [67][30/500] Time 0.019 (0.019) Data 0.002 (0.009) Loss 0.1296 (0.0969) Prec@1 77.000 (82.000) Prec@5 99.000 (98.750) +2022-11-14 13:36:22,122 Epoch: [67][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.1041 (0.0983) Prec@1 83.000 (82.200) Prec@5 96.000 (98.200) +2022-11-14 13:36:22,397 Epoch: [67][50/500] Time 0.026 (0.020) Data 0.002 (0.006) Loss 0.0711 (0.0938) Prec@1 88.000 (83.167) Prec@5 99.000 (98.333) +2022-11-14 13:36:22,681 Epoch: [67][60/500] Time 0.028 (0.021) Data 0.001 (0.005) Loss 0.0765 (0.0913) Prec@1 87.000 (83.714) Prec@5 100.000 (98.571) +2022-11-14 13:36:22,962 Epoch: [67][70/500] Time 0.028 (0.022) Data 0.002 (0.005) Loss 0.0955 (0.0918) Prec@1 84.000 (83.750) Prec@5 98.000 (98.500) +2022-11-14 13:36:23,240 Epoch: [67][80/500] Time 0.026 (0.022) Data 0.002 (0.005) Loss 0.1088 (0.0937) Prec@1 81.000 (83.444) Prec@5 100.000 (98.667) +2022-11-14 13:36:23,516 Epoch: [67][90/500] Time 0.025 (0.022) Data 0.001 (0.004) Loss 0.0984 (0.0942) Prec@1 82.000 (83.300) Prec@5 99.000 (98.700) +2022-11-14 13:36:23,795 Epoch: [67][100/500] Time 0.025 (0.022) Data 0.001 (0.004) Loss 0.0810 (0.0930) Prec@1 87.000 (83.636) Prec@5 97.000 (98.545) +2022-11-14 13:36:24,078 Epoch: [67][110/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.1107 (0.0945) Prec@1 83.000 (83.583) Prec@5 100.000 (98.667) +2022-11-14 13:36:24,366 Epoch: [67][120/500] Time 0.022 (0.023) Data 0.002 (0.004) Loss 0.1286 (0.0971) Prec@1 77.000 (83.077) Prec@5 98.000 (98.615) +2022-11-14 13:36:24,646 Epoch: [67][130/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.1176 (0.0986) Prec@1 81.000 (82.929) Prec@5 98.000 (98.571) +2022-11-14 13:36:24,931 Epoch: [67][140/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0903 (0.0980) Prec@1 82.000 (82.867) Prec@5 99.000 (98.600) +2022-11-14 13:36:25,210 Epoch: [67][150/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0731 (0.0965) Prec@1 86.000 (83.062) Prec@5 99.000 (98.625) +2022-11-14 13:36:25,502 Epoch: [67][160/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.1133 (0.0974) Prec@1 83.000 (83.059) Prec@5 98.000 (98.588) +2022-11-14 13:36:25,790 Epoch: [67][170/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.1082 (0.0980) Prec@1 82.000 (83.000) Prec@5 97.000 (98.500) +2022-11-14 13:36:26,075 Epoch: [67][180/500] Time 0.023 (0.024) Data 0.002 (0.003) Loss 0.0710 (0.0966) Prec@1 90.000 (83.368) Prec@5 100.000 (98.579) +2022-11-14 13:36:26,364 Epoch: [67][190/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0769 (0.0956) Prec@1 85.000 (83.450) Prec@5 100.000 (98.650) +2022-11-14 13:36:26,672 Epoch: [67][200/500] Time 0.036 (0.024) Data 0.002 (0.003) Loss 0.0834 (0.0951) Prec@1 86.000 (83.571) Prec@5 97.000 (98.571) +2022-11-14 13:36:27,112 Epoch: [67][210/500] Time 0.045 (0.025) Data 0.002 (0.003) Loss 0.0871 (0.0947) Prec@1 82.000 (83.500) Prec@5 98.000 (98.545) +2022-11-14 13:36:27,559 Epoch: [67][220/500] Time 0.037 (0.025) Data 0.002 (0.003) Loss 0.0784 (0.0940) Prec@1 86.000 (83.609) Prec@5 99.000 (98.565) +2022-11-14 13:36:28,011 Epoch: [67][230/500] Time 0.049 (0.026) Data 0.003 (0.003) Loss 0.0918 (0.0939) Prec@1 83.000 (83.583) Prec@5 99.000 (98.583) +2022-11-14 13:36:28,446 Epoch: [67][240/500] Time 0.041 (0.026) Data 0.002 (0.003) Loss 0.0759 (0.0932) Prec@1 86.000 (83.680) Prec@5 100.000 (98.640) +2022-11-14 13:36:28,891 Epoch: [67][250/500] Time 0.037 (0.027) Data 0.002 (0.003) Loss 0.0523 (0.0916) Prec@1 93.000 (84.038) Prec@5 100.000 (98.692) +2022-11-14 13:36:29,325 Epoch: [67][260/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0851 (0.0914) Prec@1 85.000 (84.074) Prec@5 99.000 (98.704) +2022-11-14 13:36:29,773 Epoch: [67][270/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.1191 (0.0923) Prec@1 78.000 (83.857) Prec@5 100.000 (98.750) +2022-11-14 13:36:30,206 Epoch: [67][280/500] Time 0.044 (0.028) Data 0.001 (0.003) Loss 0.1179 (0.0932) Prec@1 81.000 (83.759) Prec@5 99.000 (98.759) +2022-11-14 13:36:30,673 Epoch: [67][290/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.1026 (0.0935) Prec@1 82.000 (83.700) Prec@5 99.000 (98.767) +2022-11-14 13:36:31,115 Epoch: [67][300/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.0939 (0.0935) Prec@1 85.000 (83.742) Prec@5 96.000 (98.677) +2022-11-14 13:36:31,558 Epoch: [67][310/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.1111 (0.0941) Prec@1 82.000 (83.688) Prec@5 100.000 (98.719) +2022-11-14 13:36:31,975 Epoch: [67][320/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.1079 (0.0945) Prec@1 81.000 (83.606) Prec@5 100.000 (98.758) +2022-11-14 13:36:32,435 Epoch: [67][330/500] Time 0.039 (0.030) Data 0.002 (0.002) Loss 0.0799 (0.0941) Prec@1 88.000 (83.735) Prec@5 99.000 (98.765) +2022-11-14 13:36:32,869 Epoch: [67][340/500] Time 0.039 (0.030) Data 0.002 (0.002) Loss 0.1128 (0.0946) Prec@1 84.000 (83.743) Prec@5 99.000 (98.771) +2022-11-14 13:36:33,313 Epoch: [67][350/500] Time 0.041 (0.030) Data 0.002 (0.002) Loss 0.0923 (0.0946) Prec@1 84.000 (83.750) Prec@5 97.000 (98.722) +2022-11-14 13:36:33,737 Epoch: [67][360/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.0970 (0.0946) Prec@1 83.000 (83.730) Prec@5 100.000 (98.757) +2022-11-14 13:36:34,180 Epoch: [67][370/500] Time 0.041 (0.031) Data 0.002 (0.002) Loss 0.0985 (0.0947) Prec@1 84.000 (83.737) Prec@5 99.000 (98.763) +2022-11-14 13:36:34,623 Epoch: [67][380/500] Time 0.049 (0.031) Data 0.002 (0.002) Loss 0.1090 (0.0951) Prec@1 83.000 (83.718) Prec@5 98.000 (98.744) +2022-11-14 13:36:35,064 Epoch: [67][390/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.0866 (0.0949) Prec@1 84.000 (83.725) Prec@5 98.000 (98.725) +2022-11-14 13:36:35,503 Epoch: [67][400/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.0838 (0.0946) Prec@1 85.000 (83.756) Prec@5 100.000 (98.756) +2022-11-14 13:36:35,945 Epoch: [67][410/500] Time 0.040 (0.032) Data 0.002 (0.002) Loss 0.1041 (0.0948) Prec@1 82.000 (83.714) Prec@5 99.000 (98.762) +2022-11-14 13:36:36,376 Epoch: [67][420/500] Time 0.040 (0.032) Data 0.002 (0.002) Loss 0.0934 (0.0948) Prec@1 86.000 (83.767) Prec@5 99.000 (98.767) +2022-11-14 13:36:36,818 Epoch: [67][430/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0846 (0.0946) Prec@1 85.000 (83.795) Prec@5 99.000 (98.773) +2022-11-14 13:36:37,269 Epoch: [67][440/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0901 (0.0945) Prec@1 85.000 (83.822) Prec@5 99.000 (98.778) +2022-11-14 13:36:37,699 Epoch: [67][450/500] Time 0.040 (0.032) Data 0.002 (0.002) Loss 0.0921 (0.0944) Prec@1 83.000 (83.804) Prec@5 99.000 (98.783) +2022-11-14 13:36:38,145 Epoch: [67][460/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.0821 (0.0942) Prec@1 86.000 (83.851) Prec@5 98.000 (98.766) +2022-11-14 13:36:38,602 Epoch: [67][470/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0835 (0.0939) Prec@1 89.000 (83.958) Prec@5 99.000 (98.771) +2022-11-14 13:36:39,055 Epoch: [67][480/500] Time 0.049 (0.033) Data 0.002 (0.002) Loss 0.0826 (0.0937) Prec@1 85.000 (83.980) Prec@5 98.000 (98.755) +2022-11-14 13:36:39,484 Epoch: [67][490/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0910 (0.0936) Prec@1 85.000 (84.000) Prec@5 98.000 (98.740) +2022-11-14 13:36:39,884 Epoch: [67][499/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.1468 (0.0947) Prec@1 76.000 (83.843) Prec@5 99.000 (98.745) +2022-11-14 13:36:40,154 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0963 (0.0963) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,163 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1197 (0.1080) Prec@1 77.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,173 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1225 (0.1129) Prec@1 77.000 (79.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,184 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1313 (0.1175) Prec@1 79.000 (79.000) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,193 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1184) Prec@1 80.000 (79.200) Prec@5 100.000 (99.200) +2022-11-14 13:36:40,200 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.1093) Prec@1 89.000 (80.833) Prec@5 99.000 (99.167) +2022-11-14 13:36:40,209 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.1075) Prec@1 85.000 (81.429) Prec@5 98.000 (99.000) +2022-11-14 13:36:40,219 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.1101) Prec@1 75.000 (80.625) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,227 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1451 (0.1140) Prec@1 71.000 (79.556) Prec@5 98.000 (98.889) +2022-11-14 13:36:40,236 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1241 (0.1150) Prec@1 79.000 (79.500) Prec@5 99.000 (98.900) +2022-11-14 13:36:40,244 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.1156) Prec@1 79.000 (79.455) Prec@5 100.000 (99.000) +2022-11-14 13:36:40,254 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1291 (0.1168) Prec@1 79.000 (79.417) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,264 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.1131) Prec@1 89.000 (80.154) Prec@5 99.000 (99.000) +2022-11-14 13:36:40,273 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.1124) Prec@1 81.000 (80.214) Prec@5 97.000 (98.857) +2022-11-14 13:36:40,283 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.1124) Prec@1 81.000 (80.267) Prec@5 100.000 (98.933) +2022-11-14 13:36:40,291 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1202 (0.1129) Prec@1 79.000 (80.188) Prec@5 99.000 (98.938) +2022-11-14 13:36:40,300 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.1101) Prec@1 91.000 (80.824) Prec@5 98.000 (98.882) +2022-11-14 13:36:40,310 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.1107) Prec@1 81.000 (80.833) Prec@5 97.000 (98.778) +2022-11-14 13:36:40,318 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.1104) Prec@1 81.000 (80.842) Prec@5 98.000 (98.737) +2022-11-14 13:36:40,328 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1239 (0.1110) Prec@1 81.000 (80.850) Prec@5 98.000 (98.700) +2022-11-14 13:36:40,338 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1211 (0.1115) Prec@1 81.000 (80.857) Prec@5 99.000 (98.714) +2022-11-14 13:36:40,346 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.1111) Prec@1 81.000 (80.864) Prec@5 99.000 (98.727) +2022-11-14 13:36:40,355 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1240 (0.1116) Prec@1 75.000 (80.609) Prec@5 97.000 (98.652) +2022-11-14 13:36:40,365 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.1114) Prec@1 81.000 (80.625) Prec@5 98.000 (98.625) +2022-11-14 13:36:40,375 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.1107) Prec@1 86.000 (80.840) Prec@5 100.000 (98.680) +2022-11-14 13:36:40,386 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1446 (0.1120) Prec@1 76.000 (80.654) Prec@5 96.000 (98.577) +2022-11-14 13:36:40,395 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.1113) Prec@1 83.000 (80.741) Prec@5 100.000 (98.630) +2022-11-14 13:36:40,405 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1171 (0.1115) Prec@1 81.000 (80.750) Prec@5 99.000 (98.643) +2022-11-14 13:36:40,415 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.1116) Prec@1 79.000 (80.690) Prec@5 96.000 (98.552) +2022-11-14 13:36:40,424 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.1113) Prec@1 82.000 (80.733) Prec@5 100.000 (98.600) +2022-11-14 13:36:40,434 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1294 (0.1119) Prec@1 78.000 (80.645) Prec@5 96.000 (98.516) +2022-11-14 13:36:40,443 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.1114) Prec@1 87.000 (80.844) Prec@5 100.000 (98.562) +2022-11-14 13:36:40,452 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.1109) Prec@1 84.000 (80.939) Prec@5 98.000 (98.545) +2022-11-14 13:36:40,463 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1433 (0.1119) Prec@1 74.000 (80.735) Prec@5 100.000 (98.588) +2022-11-14 13:36:40,473 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1182 (0.1121) Prec@1 79.000 (80.686) Prec@5 98.000 (98.571) +2022-11-14 13:36:40,484 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.1121) Prec@1 81.000 (80.694) Prec@5 98.000 (98.556) +2022-11-14 13:36:40,492 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.1123) Prec@1 77.000 (80.595) Prec@5 97.000 (98.514) +2022-11-14 13:36:40,501 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1391 (0.1130) Prec@1 75.000 (80.447) Prec@5 97.000 (98.474) +2022-11-14 13:36:40,511 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.1125) Prec@1 84.000 (80.538) Prec@5 98.000 (98.462) +2022-11-14 13:36:40,520 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.1123) Prec@1 83.000 (80.600) Prec@5 98.000 (98.450) +2022-11-14 13:36:40,528 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1243 (0.1126) Prec@1 78.000 (80.537) Prec@5 100.000 (98.488) +2022-11-14 13:36:40,538 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.1126) Prec@1 82.000 (80.571) Prec@5 98.000 (98.476) +2022-11-14 13:36:40,548 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.1117) Prec@1 83.000 (80.628) Prec@5 99.000 (98.488) +2022-11-14 13:36:40,558 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.1113) Prec@1 86.000 (80.750) Prec@5 97.000 (98.455) +2022-11-14 13:36:40,569 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.1112) Prec@1 83.000 (80.800) Prec@5 99.000 (98.467) +2022-11-14 13:36:40,580 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1526 (0.1121) Prec@1 75.000 (80.674) Prec@5 98.000 (98.457) +2022-11-14 13:36:40,589 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.1120) Prec@1 78.000 (80.617) Prec@5 99.000 (98.468) +2022-11-14 13:36:40,598 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.1119) Prec@1 81.000 (80.625) Prec@5 99.000 (98.479) +2022-11-14 13:36:40,608 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.1114) Prec@1 86.000 (80.735) Prec@5 100.000 (98.510) +2022-11-14 13:36:40,617 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1201 (0.1116) Prec@1 81.000 (80.740) Prec@5 100.000 (98.540) +2022-11-14 13:36:40,627 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1150 (0.1116) Prec@1 79.000 (80.706) Prec@5 97.000 (98.510) +2022-11-14 13:36:40,638 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1555 (0.1125) Prec@1 71.000 (80.519) Prec@5 97.000 (98.481) +2022-11-14 13:36:40,648 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.1123) Prec@1 84.000 (80.585) Prec@5 100.000 (98.509) +2022-11-14 13:36:40,658 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.1124) Prec@1 78.000 (80.537) Prec@5 99.000 (98.519) +2022-11-14 13:36:40,667 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1239 (0.1126) Prec@1 78.000 (80.491) Prec@5 100.000 (98.545) +2022-11-14 13:36:40,678 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.1125) Prec@1 80.000 (80.482) Prec@5 99.000 (98.554) +2022-11-14 13:36:40,688 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1307 (0.1128) Prec@1 76.000 (80.404) Prec@5 99.000 (98.561) +2022-11-14 13:36:40,698 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.1125) Prec@1 85.000 (80.483) Prec@5 99.000 (98.569) +2022-11-14 13:36:40,708 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1274 (0.1127) Prec@1 77.000 (80.424) Prec@5 100.000 (98.593) +2022-11-14 13:36:40,717 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1127) Prec@1 83.000 (80.467) Prec@5 99.000 (98.600) +2022-11-14 13:36:40,729 Test: [60/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.1126) Prec@1 84.000 (80.525) Prec@5 100.000 (98.623) +2022-11-14 13:36:40,740 Test: [61/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.1124) Prec@1 83.000 (80.565) Prec@5 98.000 (98.613) +2022-11-14 13:36:40,752 Test: [62/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.1123) Prec@1 82.000 (80.587) Prec@5 100.000 (98.635) +2022-11-14 13:36:40,763 Test: [63/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.1118) Prec@1 84.000 (80.641) Prec@5 99.000 (98.641) +2022-11-14 13:36:40,775 Test: [64/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1150 (0.1119) Prec@1 77.000 (80.585) Prec@5 99.000 (98.646) +2022-11-14 13:36:40,786 Test: [65/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1305 (0.1122) Prec@1 80.000 (80.576) Prec@5 99.000 (98.652) +2022-11-14 13:36:40,797 Test: [66/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.1121) Prec@1 78.000 (80.537) Prec@5 99.000 (98.657) +2022-11-14 13:36:40,807 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.1119) Prec@1 85.000 (80.603) Prec@5 99.000 (98.662) +2022-11-14 13:36:40,820 Test: [68/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.1118) Prec@1 80.000 (80.594) Prec@5 98.000 (98.652) +2022-11-14 13:36:40,832 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.1119) Prec@1 80.000 (80.586) Prec@5 98.000 (98.643) +2022-11-14 13:36:40,840 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1252 (0.1120) Prec@1 78.000 (80.549) Prec@5 99.000 (98.648) +2022-11-14 13:36:40,850 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1121) Prec@1 80.000 (80.542) Prec@5 100.000 (98.667) +2022-11-14 13:36:40,863 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.1117) Prec@1 85.000 (80.603) Prec@5 99.000 (98.671) +2022-11-14 13:36:40,875 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.1114) Prec@1 85.000 (80.662) Prec@5 100.000 (98.689) +2022-11-14 13:36:40,884 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1215 (0.1115) Prec@1 79.000 (80.640) Prec@5 96.000 (98.653) +2022-11-14 13:36:40,893 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1114) Prec@1 84.000 (80.684) Prec@5 99.000 (98.658) +2022-11-14 13:36:40,906 Test: [76/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.1113) Prec@1 84.000 (80.727) Prec@5 100.000 (98.675) +2022-11-14 13:36:40,918 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.1113) Prec@1 82.000 (80.744) Prec@5 97.000 (98.654) +2022-11-14 13:36:40,928 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.1114) Prec@1 83.000 (80.772) Prec@5 98.000 (98.646) +2022-11-14 13:36:40,937 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1204 (0.1115) Prec@1 77.000 (80.725) Prec@5 100.000 (98.662) +2022-11-14 13:36:40,950 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.1112) Prec@1 86.000 (80.790) Prec@5 99.000 (98.667) +2022-11-14 13:36:40,962 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.1108) Prec@1 85.000 (80.841) Prec@5 99.000 (98.671) +2022-11-14 13:36:40,973 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.1108) Prec@1 79.000 (80.819) Prec@5 100.000 (98.687) +2022-11-14 13:36:40,983 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1468 (0.1113) Prec@1 70.000 (80.690) Prec@5 99.000 (98.690) +2022-11-14 13:36:40,997 Test: [84/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.1114) Prec@1 80.000 (80.682) Prec@5 97.000 (98.671) +2022-11-14 13:36:41,009 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.1116) Prec@1 77.000 (80.640) Prec@5 98.000 (98.663) +2022-11-14 13:36:41,018 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1370 (0.1119) Prec@1 76.000 (80.586) Prec@5 97.000 (98.644) +2022-11-14 13:36:41,027 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.1118) Prec@1 82.000 (80.602) Prec@5 99.000 (98.648) +2022-11-14 13:36:41,037 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.1119) Prec@1 80.000 (80.596) Prec@5 98.000 (98.640) +2022-11-14 13:36:41,047 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1119) Prec@1 83.000 (80.622) Prec@5 99.000 (98.644) +2022-11-14 13:36:41,056 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.1118) Prec@1 82.000 (80.637) Prec@5 97.000 (98.626) +2022-11-14 13:36:41,065 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.1114) Prec@1 86.000 (80.696) Prec@5 100.000 (98.641) +2022-11-14 13:36:41,075 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1114) Prec@1 78.000 (80.667) Prec@5 100.000 (98.656) +2022-11-14 13:36:41,084 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.1113) Prec@1 83.000 (80.691) Prec@5 99.000 (98.660) +2022-11-14 13:36:41,093 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.1112) Prec@1 83.000 (80.716) Prec@5 98.000 (98.653) +2022-11-14 13:36:41,103 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.1110) Prec@1 82.000 (80.729) Prec@5 98.000 (98.646) +2022-11-14 13:36:41,113 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.1109) Prec@1 83.000 (80.753) Prec@5 97.000 (98.629) +2022-11-14 13:36:41,123 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.1111) Prec@1 79.000 (80.735) Prec@5 98.000 (98.622) +2022-11-14 13:36:41,131 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.1109) Prec@1 81.000 (80.737) Prec@5 100.000 (98.636) +2022-11-14 13:36:41,141 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1258 (0.1110) Prec@1 75.000 (80.680) Prec@5 97.000 (98.620) +2022-11-14 13:36:41,197 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:36:41,501 Epoch: [68][0/500] Time 0.023 (0.023) Data 0.219 (0.219) Loss 0.0785 (0.0785) Prec@1 88.000 (88.000) Prec@5 98.000 (98.000) +2022-11-14 13:36:41,701 Epoch: [68][10/500] Time 0.017 (0.018) Data 0.001 (0.022) Loss 0.0965 (0.0875) Prec@1 83.000 (85.500) Prec@5 98.000 (98.000) +2022-11-14 13:36:41,897 Epoch: [68][20/500] Time 0.017 (0.018) Data 0.001 (0.012) Loss 0.0907 (0.0886) Prec@1 86.000 (85.667) Prec@5 98.000 (98.000) +2022-11-14 13:36:42,094 Epoch: [68][30/500] Time 0.016 (0.018) Data 0.002 (0.009) Loss 0.0915 (0.0893) Prec@1 83.000 (85.000) Prec@5 99.000 (98.250) +2022-11-14 13:36:42,348 Epoch: [68][40/500] Time 0.028 (0.019) Data 0.002 (0.007) Loss 0.0787 (0.0872) Prec@1 87.000 (85.400) Prec@5 100.000 (98.600) +2022-11-14 13:36:42,651 Epoch: [68][50/500] Time 0.024 (0.020) Data 0.002 (0.006) Loss 0.1018 (0.0896) Prec@1 82.000 (84.833) Prec@5 97.000 (98.333) +2022-11-14 13:36:42,944 Epoch: [68][60/500] Time 0.032 (0.021) Data 0.002 (0.005) Loss 0.1019 (0.0914) Prec@1 83.000 (84.571) Prec@5 99.000 (98.429) +2022-11-14 13:36:43,232 Epoch: [68][70/500] Time 0.028 (0.022) Data 0.001 (0.005) Loss 0.1029 (0.0928) Prec@1 83.000 (84.375) Prec@5 100.000 (98.625) +2022-11-14 13:36:43,532 Epoch: [68][80/500] Time 0.034 (0.022) Data 0.002 (0.004) Loss 0.0884 (0.0923) Prec@1 83.000 (84.222) Prec@5 97.000 (98.444) +2022-11-14 13:36:43,817 Epoch: [68][90/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0899 (0.0921) Prec@1 79.000 (83.700) Prec@5 98.000 (98.400) +2022-11-14 13:36:44,111 Epoch: [68][100/500] Time 0.027 (0.023) Data 0.002 (0.004) Loss 0.1183 (0.0945) Prec@1 81.000 (83.455) Prec@5 100.000 (98.545) +2022-11-14 13:36:44,413 Epoch: [68][110/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0643 (0.0919) Prec@1 89.000 (83.917) Prec@5 100.000 (98.667) +2022-11-14 13:36:44,705 Epoch: [68][120/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0761 (0.0907) Prec@1 86.000 (84.077) Prec@5 98.000 (98.615) +2022-11-14 13:36:45,003 Epoch: [68][130/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.1058 (0.0918) Prec@1 82.000 (83.929) Prec@5 98.000 (98.571) +2022-11-14 13:36:45,292 Epoch: [68][140/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.1139 (0.0933) Prec@1 83.000 (83.867) Prec@5 95.000 (98.333) +2022-11-14 13:36:45,589 Epoch: [68][150/500] Time 0.028 (0.024) Data 0.001 (0.003) Loss 0.1252 (0.0953) Prec@1 80.000 (83.625) Prec@5 99.000 (98.375) +2022-11-14 13:36:45,902 Epoch: [68][160/500] Time 0.034 (0.024) Data 0.002 (0.003) Loss 0.1051 (0.0959) Prec@1 84.000 (83.647) Prec@5 98.000 (98.353) +2022-11-14 13:36:46,191 Epoch: [68][170/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0864 (0.0953) Prec@1 84.000 (83.667) Prec@5 97.000 (98.278) +2022-11-14 13:36:46,487 Epoch: [68][180/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0821 (0.0946) Prec@1 85.000 (83.737) Prec@5 100.000 (98.368) +2022-11-14 13:36:46,784 Epoch: [68][190/500] Time 0.026 (0.025) Data 0.001 (0.003) Loss 0.1022 (0.0950) Prec@1 82.000 (83.650) Prec@5 99.000 (98.400) +2022-11-14 13:36:47,092 Epoch: [68][200/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0843 (0.0945) Prec@1 87.000 (83.810) Prec@5 100.000 (98.476) +2022-11-14 13:36:47,384 Epoch: [68][210/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.0915 (0.0944) Prec@1 85.000 (83.864) Prec@5 100.000 (98.545) +2022-11-14 13:36:47,680 Epoch: [68][220/500] Time 0.032 (0.025) Data 0.002 (0.003) Loss 0.0900 (0.0942) Prec@1 85.000 (83.913) Prec@5 99.000 (98.565) +2022-11-14 13:36:48,031 Epoch: [68][230/500] Time 0.043 (0.025) Data 0.002 (0.003) Loss 0.1208 (0.0953) Prec@1 81.000 (83.792) Prec@5 98.000 (98.542) +2022-11-14 13:36:48,528 Epoch: [68][240/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.1127 (0.0960) Prec@1 82.000 (83.720) Prec@5 100.000 (98.600) +2022-11-14 13:36:49,023 Epoch: [68][250/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.1010 (0.0962) Prec@1 84.000 (83.731) Prec@5 99.000 (98.615) +2022-11-14 13:36:49,512 Epoch: [68][260/500] Time 0.052 (0.027) Data 0.002 (0.003) Loss 0.0830 (0.0957) Prec@1 83.000 (83.704) Prec@5 100.000 (98.667) +2022-11-14 13:36:50,002 Epoch: [68][270/500] Time 0.051 (0.028) Data 0.002 (0.003) Loss 0.1070 (0.0961) Prec@1 81.000 (83.607) Prec@5 99.000 (98.679) +2022-11-14 13:36:50,467 Epoch: [68][280/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.1003 (0.0962) Prec@1 80.000 (83.483) Prec@5 99.000 (98.690) +2022-11-14 13:36:50,949 Epoch: [68][290/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.1219 (0.0971) Prec@1 79.000 (83.333) Prec@5 100.000 (98.733) +2022-11-14 13:36:51,455 Epoch: [68][300/500] Time 0.047 (0.029) Data 0.002 (0.003) Loss 0.0899 (0.0969) Prec@1 85.000 (83.387) Prec@5 98.000 (98.710) +2022-11-14 13:36:51,934 Epoch: [68][310/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0933 (0.0967) Prec@1 81.000 (83.312) Prec@5 98.000 (98.688) +2022-11-14 13:36:52,454 Epoch: [68][320/500] Time 0.042 (0.030) Data 0.003 (0.003) Loss 0.0914 (0.0966) Prec@1 83.000 (83.303) Prec@5 100.000 (98.727) +2022-11-14 13:36:52,950 Epoch: [68][330/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0734 (0.0959) Prec@1 89.000 (83.471) Prec@5 100.000 (98.765) +2022-11-14 13:36:53,417 Epoch: [68][340/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.1253 (0.0967) Prec@1 76.000 (83.257) Prec@5 95.000 (98.657) +2022-11-14 13:36:53,875 Epoch: [68][350/500] Time 0.044 (0.031) Data 0.002 (0.002) Loss 0.0699 (0.0960) Prec@1 88.000 (83.389) Prec@5 99.000 (98.667) +2022-11-14 13:36:54,355 Epoch: [68][360/500] Time 0.052 (0.032) Data 0.002 (0.002) Loss 0.0660 (0.0952) Prec@1 87.000 (83.486) Prec@5 99.000 (98.676) +2022-11-14 13:36:54,854 Epoch: [68][370/500] Time 0.059 (0.032) Data 0.002 (0.002) Loss 0.0912 (0.0951) Prec@1 82.000 (83.447) Prec@5 99.000 (98.684) +2022-11-14 13:36:55,345 Epoch: [68][380/500] Time 0.050 (0.032) Data 0.002 (0.002) Loss 0.0986 (0.0952) Prec@1 82.000 (83.410) Prec@5 100.000 (98.718) +2022-11-14 13:36:55,821 Epoch: [68][390/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.1181 (0.0957) Prec@1 81.000 (83.350) Prec@5 99.000 (98.725) +2022-11-14 13:36:56,299 Epoch: [68][400/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0866 (0.0955) Prec@1 85.000 (83.390) Prec@5 98.000 (98.707) +2022-11-14 13:36:56,775 Epoch: [68][410/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0489 (0.0944) Prec@1 92.000 (83.595) Prec@5 99.000 (98.714) +2022-11-14 13:36:57,273 Epoch: [68][420/500] Time 0.051 (0.033) Data 0.002 (0.002) Loss 0.0774 (0.0940) Prec@1 87.000 (83.674) Prec@5 100.000 (98.744) +2022-11-14 13:36:57,741 Epoch: [68][430/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.1157 (0.0945) Prec@1 79.000 (83.568) Prec@5 99.000 (98.750) +2022-11-14 13:36:58,214 Epoch: [68][440/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.1092 (0.0948) Prec@1 82.000 (83.533) Prec@5 96.000 (98.689) +2022-11-14 13:36:58,581 Epoch: [68][450/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0856 (0.0946) Prec@1 83.000 (83.522) Prec@5 99.000 (98.696) +2022-11-14 13:36:58,873 Epoch: [68][460/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0984 (0.0947) Prec@1 82.000 (83.489) Prec@5 96.000 (98.638) +2022-11-14 13:36:59,172 Epoch: [68][470/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0933 (0.0947) Prec@1 84.000 (83.500) Prec@5 100.000 (98.667) +2022-11-14 13:36:59,459 Epoch: [68][480/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.1135 (0.0951) Prec@1 78.000 (83.388) Prec@5 97.000 (98.633) +2022-11-14 13:36:59,762 Epoch: [68][490/500] Time 0.031 (0.033) Data 0.002 (0.002) Loss 0.0952 (0.0951) Prec@1 84.000 (83.400) Prec@5 97.000 (98.600) +2022-11-14 13:37:00,031 Epoch: [68][499/500] Time 0.025 (0.033) Data 0.001 (0.002) Loss 0.0853 (0.0949) Prec@1 85.000 (83.431) Prec@5 98.000 (98.588) +2022-11-14 13:37:00,323 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0946 (0.0946) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:37:00,336 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1098 (0.1022) Prec@1 81.000 (83.000) Prec@5 100.000 (99.000) +2022-11-14 13:37:00,346 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0976) Prec@1 87.000 (84.333) Prec@5 98.000 (98.667) +2022-11-14 13:37:00,356 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0966) Prec@1 85.000 (84.500) Prec@5 98.000 (98.500) +2022-11-14 13:37:00,367 Test: [4/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0978) Prec@1 82.000 (84.000) Prec@5 100.000 (98.800) +2022-11-14 13:37:00,378 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0970) Prec@1 82.000 (83.667) Prec@5 100.000 (99.000) +2022-11-14 13:37:00,386 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0932) Prec@1 88.000 (84.286) Prec@5 99.000 (99.000) +2022-11-14 13:37:00,394 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1377 (0.0988) Prec@1 76.000 (83.250) Prec@5 98.000 (98.875) +2022-11-14 13:37:00,405 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.1010) Prec@1 82.000 (83.111) Prec@5 99.000 (98.889) +2022-11-14 13:37:00,415 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0995) Prec@1 85.000 (83.300) Prec@5 98.000 (98.800) +2022-11-14 13:37:00,423 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.1010) Prec@1 82.000 (83.182) Prec@5 98.000 (98.727) +2022-11-14 13:37:00,432 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.1020) Prec@1 82.000 (83.083) Prec@5 99.000 (98.750) +2022-11-14 13:37:00,442 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.1010) Prec@1 84.000 (83.154) Prec@5 99.000 (98.769) +2022-11-14 13:37:00,451 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.1018) Prec@1 83.000 (83.143) Prec@5 98.000 (98.714) +2022-11-14 13:37:00,461 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1213 (0.1031) Prec@1 80.000 (82.933) Prec@5 100.000 (98.800) +2022-11-14 13:37:00,470 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1040) Prec@1 76.000 (82.500) Prec@5 97.000 (98.688) +2022-11-14 13:37:00,478 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.1037) Prec@1 82.000 (82.471) Prec@5 99.000 (98.706) +2022-11-14 13:37:00,486 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1048) Prec@1 80.000 (82.333) Prec@5 99.000 (98.722) +2022-11-14 13:37:00,494 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1054) Prec@1 78.000 (82.105) Prec@5 99.000 (98.737) +2022-11-14 13:37:00,504 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1059) Prec@1 79.000 (81.950) Prec@5 99.000 (98.750) +2022-11-14 13:37:00,512 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.1060) Prec@1 81.000 (81.905) Prec@5 99.000 (98.762) +2022-11-14 13:37:00,520 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1062) Prec@1 81.000 (81.864) Prec@5 99.000 (98.773) +2022-11-14 13:37:00,529 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.1071) Prec@1 80.000 (81.783) Prec@5 98.000 (98.739) +2022-11-14 13:37:00,539 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.1064) Prec@1 84.000 (81.875) Prec@5 99.000 (98.750) +2022-11-14 13:37:00,548 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1564 (0.1084) Prec@1 74.000 (81.560) Prec@5 100.000 (98.800) +2022-11-14 13:37:00,558 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1483 (0.1099) Prec@1 75.000 (81.308) Prec@5 98.000 (98.769) +2022-11-14 13:37:00,568 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.1099) Prec@1 77.000 (81.148) Prec@5 100.000 (98.815) +2022-11-14 13:37:00,579 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.1096) Prec@1 81.000 (81.143) Prec@5 99.000 (98.821) +2022-11-14 13:37:00,589 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.1088) Prec@1 87.000 (81.345) Prec@5 99.000 (98.828) +2022-11-14 13:37:00,600 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.1084) Prec@1 86.000 (81.500) Prec@5 100.000 (98.867) +2022-11-14 13:37:00,610 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.1081) Prec@1 83.000 (81.548) Prec@5 99.000 (98.871) +2022-11-14 13:37:00,620 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1084) Prec@1 81.000 (81.531) Prec@5 100.000 (98.906) +2022-11-14 13:37:00,630 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.1085) Prec@1 81.000 (81.515) Prec@5 96.000 (98.818) +2022-11-14 13:37:00,639 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1311 (0.1091) Prec@1 74.000 (81.294) Prec@5 98.000 (98.794) +2022-11-14 13:37:00,649 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1094) Prec@1 78.000 (81.200) Prec@5 97.000 (98.743) +2022-11-14 13:37:00,658 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.1090) Prec@1 84.000 (81.278) Prec@5 99.000 (98.750) +2022-11-14 13:37:00,667 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1094) Prec@1 75.000 (81.108) Prec@5 98.000 (98.730) +2022-11-14 13:37:00,676 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.1098) Prec@1 79.000 (81.053) Prec@5 97.000 (98.684) +2022-11-14 13:37:00,687 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1095) Prec@1 82.000 (81.077) Prec@5 100.000 (98.718) +2022-11-14 13:37:00,697 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.1090) Prec@1 82.000 (81.100) Prec@5 99.000 (98.725) +2022-11-14 13:37:00,707 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.1090) Prec@1 81.000 (81.098) Prec@5 99.000 (98.732) +2022-11-14 13:37:00,716 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.1089) Prec@1 80.000 (81.071) Prec@5 99.000 (98.738) +2022-11-14 13:37:00,726 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.1088) Prec@1 83.000 (81.116) Prec@5 99.000 (98.744) +2022-11-14 13:37:00,735 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.1088) Prec@1 80.000 (81.091) Prec@5 98.000 (98.727) +2022-11-14 13:37:00,744 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.1085) Prec@1 83.000 (81.133) Prec@5 99.000 (98.733) +2022-11-14 13:37:00,753 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1292 (0.1090) Prec@1 78.000 (81.065) Prec@5 100.000 (98.761) +2022-11-14 13:37:00,763 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.1084) Prec@1 88.000 (81.213) Prec@5 100.000 (98.787) +2022-11-14 13:37:00,772 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.1084) Prec@1 83.000 (81.250) Prec@5 100.000 (98.812) +2022-11-14 13:37:00,780 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.1079) Prec@1 81.000 (81.245) Prec@5 100.000 (98.837) +2022-11-14 13:37:00,790 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1404 (0.1086) Prec@1 77.000 (81.160) Prec@5 99.000 (98.840) +2022-11-14 13:37:00,799 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.1083) Prec@1 81.000 (81.157) Prec@5 99.000 (98.843) +2022-11-14 13:37:00,809 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1089) Prec@1 76.000 (81.058) Prec@5 97.000 (98.808) +2022-11-14 13:37:00,817 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.1090) Prec@1 79.000 (81.019) Prec@5 99.000 (98.811) +2022-11-14 13:37:00,826 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1092) Prec@1 80.000 (81.000) Prec@5 98.000 (98.796) +2022-11-14 13:37:00,835 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.1095) Prec@1 81.000 (81.000) Prec@5 100.000 (98.818) +2022-11-14 13:37:00,844 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1095) Prec@1 81.000 (81.000) Prec@5 98.000 (98.804) +2022-11-14 13:37:00,853 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1096) Prec@1 84.000 (81.053) Prec@5 98.000 (98.789) +2022-11-14 13:37:00,862 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.1096) Prec@1 80.000 (81.034) Prec@5 98.000 (98.776) +2022-11-14 13:37:00,871 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1501 (0.1103) Prec@1 72.000 (80.881) Prec@5 97.000 (98.746) +2022-11-14 13:37:00,880 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.1100) Prec@1 82.000 (80.900) Prec@5 100.000 (98.767) +2022-11-14 13:37:00,889 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.1099) Prec@1 82.000 (80.918) Prec@5 99.000 (98.770) +2022-11-14 13:37:00,900 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.1096) Prec@1 85.000 (80.984) Prec@5 100.000 (98.790) +2022-11-14 13:37:00,909 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1096) Prec@1 80.000 (80.968) Prec@5 99.000 (98.794) +2022-11-14 13:37:00,918 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.1092) Prec@1 87.000 (81.062) Prec@5 100.000 (98.812) +2022-11-14 13:37:00,928 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1179 (0.1093) Prec@1 81.000 (81.062) Prec@5 99.000 (98.815) +2022-11-14 13:37:00,938 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1095) Prec@1 81.000 (81.061) Prec@5 99.000 (98.818) +2022-11-14 13:37:00,949 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1096) Prec@1 79.000 (81.030) Prec@5 100.000 (98.836) +2022-11-14 13:37:00,957 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.1095) Prec@1 82.000 (81.044) Prec@5 97.000 (98.809) +2022-11-14 13:37:00,967 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.1094) Prec@1 81.000 (81.043) Prec@5 98.000 (98.797) +2022-11-14 13:37:00,976 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1326 (0.1098) Prec@1 76.000 (80.971) Prec@5 98.000 (98.786) +2022-11-14 13:37:00,985 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.1098) Prec@1 81.000 (80.972) Prec@5 100.000 (98.803) +2022-11-14 13:37:00,996 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1096) Prec@1 81.000 (80.972) Prec@5 99.000 (98.806) +2022-11-14 13:37:01,005 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.1090) Prec@1 90.000 (81.096) Prec@5 100.000 (98.822) +2022-11-14 13:37:01,014 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.1087) Prec@1 83.000 (81.122) Prec@5 100.000 (98.838) +2022-11-14 13:37:01,023 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1318 (0.1090) Prec@1 77.000 (81.067) Prec@5 98.000 (98.827) +2022-11-14 13:37:01,035 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.1087) Prec@1 86.000 (81.132) Prec@5 100.000 (98.842) +2022-11-14 13:37:01,047 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1088) Prec@1 81.000 (81.130) Prec@5 99.000 (98.844) +2022-11-14 13:37:01,056 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1087) Prec@1 79.000 (81.103) Prec@5 98.000 (98.833) +2022-11-14 13:37:01,065 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1304 (0.1090) Prec@1 79.000 (81.076) Prec@5 99.000 (98.835) +2022-11-14 13:37:01,078 Test: [79/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.1090) Prec@1 81.000 (81.075) Prec@5 99.000 (98.838) +2022-11-14 13:37:01,090 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.1089) Prec@1 80.000 (81.062) Prec@5 98.000 (98.827) +2022-11-14 13:37:01,099 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.1089) Prec@1 82.000 (81.073) Prec@5 97.000 (98.805) +2022-11-14 13:37:01,109 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.1088) Prec@1 83.000 (81.096) Prec@5 100.000 (98.819) +2022-11-14 13:37:01,121 Test: [83/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.1088) Prec@1 79.000 (81.071) Prec@5 99.000 (98.821) +2022-11-14 13:37:01,133 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1212 (0.1090) Prec@1 82.000 (81.082) Prec@5 100.000 (98.835) +2022-11-14 13:37:01,143 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1417 (0.1093) Prec@1 74.000 (81.000) Prec@5 97.000 (98.814) +2022-11-14 13:37:01,152 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1306 (0.1096) Prec@1 78.000 (80.966) Prec@5 97.000 (98.793) +2022-11-14 13:37:01,164 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.1098) Prec@1 80.000 (80.955) Prec@5 100.000 (98.807) +2022-11-14 13:37:01,177 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.1097) Prec@1 78.000 (80.921) Prec@5 98.000 (98.798) +2022-11-14 13:37:01,190 Test: [89/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1257 (0.1099) Prec@1 80.000 (80.911) Prec@5 99.000 (98.800) +2022-11-14 13:37:01,204 Test: [90/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.1098) Prec@1 84.000 (80.945) Prec@5 98.000 (98.791) +2022-11-14 13:37:01,219 Test: [91/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.1094) Prec@1 88.000 (81.022) Prec@5 100.000 (98.804) +2022-11-14 13:37:01,231 Test: [92/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.1093) Prec@1 80.000 (81.011) Prec@5 98.000 (98.796) +2022-11-14 13:37:01,242 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.1093) Prec@1 81.000 (81.011) Prec@5 98.000 (98.787) +2022-11-14 13:37:01,253 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1093) Prec@1 80.000 (81.000) Prec@5 98.000 (98.779) +2022-11-14 13:37:01,263 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.1091) Prec@1 81.000 (81.000) Prec@5 100.000 (98.792) +2022-11-14 13:37:01,273 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.1090) Prec@1 85.000 (81.041) Prec@5 99.000 (98.794) +2022-11-14 13:37:01,283 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.1089) Prec@1 81.000 (81.041) Prec@5 99.000 (98.796) +2022-11-14 13:37:01,293 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1383 (0.1092) Prec@1 78.000 (81.010) Prec@5 97.000 (98.778) +2022-11-14 13:37:01,302 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.1090) Prec@1 85.000 (81.050) Prec@5 97.000 (98.760) +2022-11-14 13:37:01,357 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:37:01,672 Epoch: [69][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.1126 (0.1126) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:37:01,877 Epoch: [69][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0934 (0.1030) Prec@1 86.000 (82.500) Prec@5 99.000 (98.500) +2022-11-14 13:37:02,074 Epoch: [69][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0811 (0.0957) Prec@1 87.000 (84.000) Prec@5 98.000 (98.333) +2022-11-14 13:37:02,274 Epoch: [69][30/500] Time 0.020 (0.018) Data 0.002 (0.009) Loss 0.0883 (0.0938) Prec@1 86.000 (84.500) Prec@5 98.000 (98.250) +2022-11-14 13:37:02,577 Epoch: [69][40/500] Time 0.035 (0.020) Data 0.002 (0.007) Loss 0.1006 (0.0952) Prec@1 83.000 (84.200) Prec@5 99.000 (98.400) +2022-11-14 13:37:02,995 Epoch: [69][50/500] Time 0.038 (0.023) Data 0.002 (0.006) Loss 0.0750 (0.0918) Prec@1 87.000 (84.667) Prec@5 99.000 (98.500) +2022-11-14 13:37:03,418 Epoch: [69][60/500] Time 0.038 (0.025) Data 0.002 (0.006) Loss 0.0663 (0.0882) Prec@1 87.000 (85.000) Prec@5 100.000 (98.714) +2022-11-14 13:37:03,846 Epoch: [69][70/500] Time 0.034 (0.027) Data 0.002 (0.005) Loss 0.0875 (0.0881) Prec@1 85.000 (85.000) Prec@5 99.000 (98.750) +2022-11-14 13:37:04,272 Epoch: [69][80/500] Time 0.042 (0.029) Data 0.002 (0.005) Loss 0.0790 (0.0871) Prec@1 86.000 (85.111) Prec@5 100.000 (98.889) +2022-11-14 13:37:04,694 Epoch: [69][90/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0945 (0.0878) Prec@1 84.000 (85.000) Prec@5 99.000 (98.900) +2022-11-14 13:37:05,122 Epoch: [69][100/500] Time 0.042 (0.030) Data 0.002 (0.004) Loss 0.0760 (0.0867) Prec@1 87.000 (85.182) Prec@5 98.000 (98.818) +2022-11-14 13:37:05,540 Epoch: [69][110/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.1019 (0.0880) Prec@1 81.000 (84.833) Prec@5 99.000 (98.833) +2022-11-14 13:37:05,955 Epoch: [69][120/500] Time 0.037 (0.031) Data 0.002 (0.004) Loss 0.1175 (0.0903) Prec@1 78.000 (84.308) Prec@5 100.000 (98.923) +2022-11-14 13:37:06,383 Epoch: [69][130/500] Time 0.041 (0.032) Data 0.002 (0.004) Loss 0.0793 (0.0895) Prec@1 90.000 (84.714) Prec@5 100.000 (99.000) +2022-11-14 13:37:06,810 Epoch: [69][140/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0973 (0.0900) Prec@1 81.000 (84.467) Prec@5 98.000 (98.933) +2022-11-14 13:37:07,218 Epoch: [69][150/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1070 (0.0911) Prec@1 81.000 (84.250) Prec@5 98.000 (98.875) +2022-11-14 13:37:07,634 Epoch: [69][160/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.1193 (0.0927) Prec@1 79.000 (83.941) Prec@5 99.000 (98.882) +2022-11-14 13:37:08,057 Epoch: [69][170/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0773 (0.0919) Prec@1 87.000 (84.111) Prec@5 100.000 (98.944) +2022-11-14 13:37:08,471 Epoch: [69][180/500] Time 0.042 (0.033) Data 0.001 (0.003) Loss 0.1008 (0.0923) Prec@1 81.000 (83.947) Prec@5 99.000 (98.947) +2022-11-14 13:37:08,895 Epoch: [69][190/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.1296 (0.0942) Prec@1 78.000 (83.650) Prec@5 97.000 (98.850) +2022-11-14 13:37:09,325 Epoch: [69][200/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.1008 (0.0945) Prec@1 84.000 (83.667) Prec@5 97.000 (98.762) +2022-11-14 13:37:09,740 Epoch: [69][210/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0862 (0.0941) Prec@1 86.000 (83.773) Prec@5 98.000 (98.727) +2022-11-14 13:37:10,156 Epoch: [69][220/500] Time 0.040 (0.034) Data 0.001 (0.003) Loss 0.1064 (0.0947) Prec@1 81.000 (83.652) Prec@5 100.000 (98.783) +2022-11-14 13:37:10,571 Epoch: [69][230/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.1223 (0.0958) Prec@1 78.000 (83.417) Prec@5 98.000 (98.750) +2022-11-14 13:37:10,989 Epoch: [69][240/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.1159 (0.0966) Prec@1 80.000 (83.280) Prec@5 97.000 (98.680) +2022-11-14 13:37:11,399 Epoch: [69][250/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0964 (0.0966) Prec@1 82.000 (83.231) Prec@5 99.000 (98.692) +2022-11-14 13:37:11,874 Epoch: [69][260/500] Time 0.082 (0.035) Data 0.002 (0.003) Loss 0.1054 (0.0969) Prec@1 79.000 (83.074) Prec@5 98.000 (98.667) +2022-11-14 13:37:12,267 Epoch: [69][270/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0877 (0.0966) Prec@1 86.000 (83.179) Prec@5 100.000 (98.714) +2022-11-14 13:37:12,682 Epoch: [69][280/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0963 (0.0966) Prec@1 86.000 (83.276) Prec@5 100.000 (98.759) +2022-11-14 13:37:13,169 Epoch: [69][290/500] Time 0.067 (0.035) Data 0.002 (0.003) Loss 0.0736 (0.0958) Prec@1 87.000 (83.400) Prec@5 100.000 (98.800) +2022-11-14 13:37:13,584 Epoch: [69][300/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1280 (0.0969) Prec@1 74.000 (83.097) Prec@5 98.000 (98.774) +2022-11-14 13:37:14,001 Epoch: [69][310/500] Time 0.039 (0.035) Data 0.001 (0.003) Loss 0.0781 (0.0963) Prec@1 88.000 (83.250) Prec@5 99.000 (98.781) +2022-11-14 13:37:14,419 Epoch: [69][320/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0917 (0.0961) Prec@1 86.000 (83.333) Prec@5 97.000 (98.727) +2022-11-14 13:37:14,841 Epoch: [69][330/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0856 (0.0958) Prec@1 85.000 (83.382) Prec@5 99.000 (98.735) +2022-11-14 13:37:15,277 Epoch: [69][340/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1080 (0.0962) Prec@1 79.000 (83.257) Prec@5 99.000 (98.743) +2022-11-14 13:37:15,706 Epoch: [69][350/500] Time 0.046 (0.035) Data 0.002 (0.002) Loss 0.1139 (0.0967) Prec@1 78.000 (83.111) Prec@5 97.000 (98.694) +2022-11-14 13:37:16,135 Epoch: [69][360/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0981 (0.0967) Prec@1 82.000 (83.081) Prec@5 100.000 (98.730) +2022-11-14 13:37:16,554 Epoch: [69][370/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0888 (0.0965) Prec@1 82.000 (83.053) Prec@5 99.000 (98.737) +2022-11-14 13:37:16,987 Epoch: [69][380/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.1162 (0.0970) Prec@1 82.000 (83.026) Prec@5 98.000 (98.718) +2022-11-14 13:37:17,407 Epoch: [69][390/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0906 (0.0968) Prec@1 87.000 (83.125) Prec@5 98.000 (98.700) +2022-11-14 13:37:17,830 Epoch: [69][400/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.1135 (0.0973) Prec@1 79.000 (83.024) Prec@5 97.000 (98.659) +2022-11-14 13:37:18,248 Epoch: [69][410/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0987 (0.0973) Prec@1 83.000 (83.024) Prec@5 98.000 (98.643) +2022-11-14 13:37:18,654 Epoch: [69][420/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1058 (0.0975) Prec@1 80.000 (82.953) Prec@5 98.000 (98.628) +2022-11-14 13:37:19,073 Epoch: [69][430/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0753 (0.0970) Prec@1 87.000 (83.045) Prec@5 100.000 (98.659) +2022-11-14 13:37:19,499 Epoch: [69][440/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0848 (0.0967) Prec@1 87.000 (83.133) Prec@5 99.000 (98.667) +2022-11-14 13:37:19,926 Epoch: [69][450/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0679 (0.0961) Prec@1 88.000 (83.239) Prec@5 100.000 (98.696) +2022-11-14 13:37:20,334 Epoch: [69][460/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0738 (0.0956) Prec@1 87.000 (83.319) Prec@5 98.000 (98.681) +2022-11-14 13:37:20,770 Epoch: [69][470/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.1204 (0.0961) Prec@1 81.000 (83.271) Prec@5 97.000 (98.646) +2022-11-14 13:37:21,198 Epoch: [69][480/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0966 (0.0961) Prec@1 82.000 (83.245) Prec@5 99.000 (98.653) +2022-11-14 13:37:21,619 Epoch: [69][490/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0948 (0.0961) Prec@1 83.000 (83.240) Prec@5 98.000 (98.640) +2022-11-14 13:37:21,997 Epoch: [69][499/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0882 (0.0960) Prec@1 88.000 (83.333) Prec@5 100.000 (98.667) +2022-11-14 13:37:22,271 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1318 (0.1318) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:37:22,283 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1241 (0.1279) Prec@1 77.000 (78.000) Prec@5 99.000 (98.500) +2022-11-14 13:37:22,294 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1164 (0.1241) Prec@1 80.000 (78.667) Prec@5 98.000 (98.333) +2022-11-14 13:37:22,306 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1568 (0.1323) Prec@1 72.000 (77.000) Prec@5 99.000 (98.500) +2022-11-14 13:37:22,314 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1546 (0.1367) Prec@1 72.000 (76.000) Prec@5 100.000 (98.800) +2022-11-14 13:37:22,323 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.1307) Prec@1 82.000 (77.000) Prec@5 99.000 (98.833) +2022-11-14 13:37:22,331 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1255 (0.1300) Prec@1 81.000 (77.571) Prec@5 99.000 (98.857) +2022-11-14 13:37:22,341 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1560 (0.1332) Prec@1 74.000 (77.125) Prec@5 96.000 (98.500) +2022-11-14 13:37:22,349 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1663 (0.1369) Prec@1 73.000 (76.667) Prec@5 97.000 (98.333) +2022-11-14 13:37:22,358 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1357) Prec@1 76.000 (76.600) Prec@5 99.000 (98.400) +2022-11-14 13:37:22,368 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1322 (0.1354) Prec@1 77.000 (76.636) Prec@5 100.000 (98.545) +2022-11-14 13:37:22,377 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1321 (0.1352) Prec@1 78.000 (76.750) Prec@5 99.000 (98.583) +2022-11-14 13:37:22,387 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1323) Prec@1 83.000 (77.231) Prec@5 99.000 (98.615) +2022-11-14 13:37:22,397 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1121 (0.1309) Prec@1 80.000 (77.429) Prec@5 99.000 (98.643) +2022-11-14 13:37:22,407 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1205 (0.1302) Prec@1 81.000 (77.667) Prec@5 99.000 (98.667) +2022-11-14 13:37:22,416 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1624 (0.1322) Prec@1 73.000 (77.375) Prec@5 98.000 (98.625) +2022-11-14 13:37:22,425 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.1313) Prec@1 81.000 (77.588) Prec@5 96.000 (98.471) +2022-11-14 13:37:22,435 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1511 (0.1324) Prec@1 72.000 (77.278) Prec@5 99.000 (98.500) +2022-11-14 13:37:22,443 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.1314) Prec@1 80.000 (77.421) Prec@5 97.000 (98.421) +2022-11-14 13:37:22,452 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1616 (0.1329) Prec@1 71.000 (77.100) Prec@5 96.000 (98.300) +2022-11-14 13:37:22,462 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.1327) Prec@1 77.000 (77.095) Prec@5 99.000 (98.333) +2022-11-14 13:37:22,471 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1321) Prec@1 81.000 (77.273) Prec@5 95.000 (98.182) +2022-11-14 13:37:22,480 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1402 (0.1325) Prec@1 77.000 (77.261) Prec@5 98.000 (98.174) +2022-11-14 13:37:22,489 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1317) Prec@1 81.000 (77.417) Prec@5 98.000 (98.167) +2022-11-14 13:37:22,497 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1345 (0.1318) Prec@1 77.000 (77.400) Prec@5 99.000 (98.200) +2022-11-14 13:37:22,506 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1759 (0.1335) Prec@1 70.000 (77.115) Prec@5 95.000 (98.077) +2022-11-14 13:37:22,516 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.1329) Prec@1 79.000 (77.185) Prec@5 99.000 (98.111) +2022-11-14 13:37:22,526 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.1321) Prec@1 83.000 (77.393) Prec@5 99.000 (98.143) +2022-11-14 13:37:22,535 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1450 (0.1325) Prec@1 73.000 (77.241) Prec@5 100.000 (98.207) +2022-11-14 13:37:22,545 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1447 (0.1329) Prec@1 73.000 (77.100) Prec@5 98.000 (98.200) +2022-11-14 13:37:22,554 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.1326) Prec@1 77.000 (77.097) Prec@5 97.000 (98.161) +2022-11-14 13:37:22,563 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.1319) Prec@1 82.000 (77.250) Prec@5 100.000 (98.219) +2022-11-14 13:37:22,573 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1490 (0.1325) Prec@1 75.000 (77.182) Prec@5 99.000 (98.242) +2022-11-14 13:37:22,582 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1597 (0.1333) Prec@1 72.000 (77.029) Prec@5 98.000 (98.235) +2022-11-14 13:37:22,590 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1327) Prec@1 82.000 (77.171) Prec@5 97.000 (98.200) +2022-11-14 13:37:22,600 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.1320) Prec@1 84.000 (77.361) Prec@5 98.000 (98.194) +2022-11-14 13:37:22,610 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1512 (0.1326) Prec@1 73.000 (77.243) Prec@5 96.000 (98.135) +2022-11-14 13:37:22,621 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1441 (0.1329) Prec@1 73.000 (77.132) Prec@5 97.000 (98.105) +2022-11-14 13:37:22,631 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1368 (0.1330) Prec@1 76.000 (77.103) Prec@5 98.000 (98.103) +2022-11-14 13:37:22,641 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.1323) Prec@1 83.000 (77.250) Prec@5 99.000 (98.125) +2022-11-14 13:37:22,651 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1475 (0.1326) Prec@1 75.000 (77.195) Prec@5 96.000 (98.073) +2022-11-14 13:37:22,660 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.1323) Prec@1 81.000 (77.286) Prec@5 98.000 (98.071) +2022-11-14 13:37:22,671 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.1312) Prec@1 84.000 (77.442) Prec@5 98.000 (98.070) +2022-11-14 13:37:22,679 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.1308) Prec@1 81.000 (77.523) Prec@5 98.000 (98.068) +2022-11-14 13:37:22,688 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1302 (0.1308) Prec@1 75.000 (77.467) Prec@5 95.000 (98.000) +2022-11-14 13:37:22,698 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1664 (0.1316) Prec@1 72.000 (77.348) Prec@5 99.000 (98.022) +2022-11-14 13:37:22,707 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1443 (0.1318) Prec@1 73.000 (77.255) Prec@5 98.000 (98.021) +2022-11-14 13:37:22,716 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.1318) Prec@1 81.000 (77.333) Prec@5 94.000 (97.938) +2022-11-14 13:37:22,725 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1337 (0.1318) Prec@1 78.000 (77.347) Prec@5 98.000 (97.939) +2022-11-14 13:37:22,734 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1448 (0.1321) Prec@1 75.000 (77.300) Prec@5 97.000 (97.920) +2022-11-14 13:37:22,742 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.1317) Prec@1 80.000 (77.353) Prec@5 97.000 (97.902) +2022-11-14 13:37:22,751 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1498 (0.1320) Prec@1 74.000 (77.288) Prec@5 97.000 (97.885) +2022-11-14 13:37:22,760 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1321) Prec@1 76.000 (77.264) Prec@5 100.000 (97.925) +2022-11-14 13:37:22,769 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.1316) Prec@1 83.000 (77.370) Prec@5 98.000 (97.926) +2022-11-14 13:37:22,779 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1496 (0.1320) Prec@1 77.000 (77.364) Prec@5 99.000 (97.945) +2022-11-14 13:37:22,790 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.1317) Prec@1 82.000 (77.446) Prec@5 100.000 (97.982) +2022-11-14 13:37:22,799 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1704 (0.1324) Prec@1 69.000 (77.298) Prec@5 96.000 (97.947) +2022-11-14 13:37:22,807 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.1320) Prec@1 83.000 (77.397) Prec@5 97.000 (97.931) +2022-11-14 13:37:22,817 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1703 (0.1326) Prec@1 67.000 (77.220) Prec@5 100.000 (97.966) +2022-11-14 13:37:22,827 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1323 (0.1326) Prec@1 77.000 (77.217) Prec@5 97.000 (97.950) +2022-11-14 13:37:22,837 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1327) Prec@1 77.000 (77.213) Prec@5 100.000 (97.984) +2022-11-14 13:37:22,846 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1404 (0.1328) Prec@1 77.000 (77.210) Prec@5 98.000 (97.984) +2022-11-14 13:37:22,855 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1384 (0.1329) Prec@1 74.000 (77.159) Prec@5 97.000 (97.968) +2022-11-14 13:37:22,865 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.1328) Prec@1 79.000 (77.188) Prec@5 97.000 (97.953) +2022-11-14 13:37:22,875 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.1328) Prec@1 79.000 (77.215) Prec@5 98.000 (97.954) +2022-11-14 13:37:22,885 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1385 (0.1329) Prec@1 80.000 (77.258) Prec@5 100.000 (97.985) +2022-11-14 13:37:22,894 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.1325) Prec@1 83.000 (77.343) Prec@5 98.000 (97.985) +2022-11-14 13:37:22,902 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1606 (0.1329) Prec@1 71.000 (77.250) Prec@5 98.000 (97.985) +2022-11-14 13:37:22,912 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1292 (0.1328) Prec@1 79.000 (77.275) Prec@5 98.000 (97.986) +2022-11-14 13:37:22,922 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1586 (0.1332) Prec@1 70.000 (77.171) Prec@5 97.000 (97.971) +2022-11-14 13:37:22,931 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1192 (0.1330) Prec@1 82.000 (77.239) Prec@5 97.000 (97.958) +2022-11-14 13:37:22,941 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.1327) Prec@1 86.000 (77.361) Prec@5 100.000 (97.986) +2022-11-14 13:37:22,950 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.1322) Prec@1 85.000 (77.466) Prec@5 99.000 (98.000) +2022-11-14 13:37:22,959 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1289 (0.1322) Prec@1 77.000 (77.459) Prec@5 99.000 (98.014) +2022-11-14 13:37:22,968 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1365 (0.1322) Prec@1 76.000 (77.440) Prec@5 98.000 (98.013) +2022-11-14 13:37:22,977 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1381 (0.1323) Prec@1 76.000 (77.421) Prec@5 98.000 (98.013) +2022-11-14 13:37:22,986 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.1323) Prec@1 80.000 (77.455) Prec@5 99.000 (98.026) +2022-11-14 13:37:22,996 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1324) Prec@1 78.000 (77.462) Prec@5 97.000 (98.013) +2022-11-14 13:37:23,005 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1331 (0.1324) Prec@1 78.000 (77.468) Prec@5 98.000 (98.013) +2022-11-14 13:37:23,015 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1469 (0.1326) Prec@1 77.000 (77.463) Prec@5 99.000 (98.025) +2022-11-14 13:37:23,025 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.1325) Prec@1 77.000 (77.457) Prec@5 99.000 (98.037) +2022-11-14 13:37:23,034 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1325) Prec@1 74.000 (77.415) Prec@5 96.000 (98.012) +2022-11-14 13:37:23,043 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1325) Prec@1 75.000 (77.386) Prec@5 99.000 (98.024) +2022-11-14 13:37:23,052 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.1323) Prec@1 82.000 (77.440) Prec@5 100.000 (98.048) +2022-11-14 13:37:23,061 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1419 (0.1325) Prec@1 76.000 (77.424) Prec@5 100.000 (98.071) +2022-11-14 13:37:23,070 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1369 (0.1325) Prec@1 78.000 (77.430) Prec@5 95.000 (98.035) +2022-11-14 13:37:23,079 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.1323) Prec@1 81.000 (77.471) Prec@5 98.000 (98.034) +2022-11-14 13:37:23,088 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1321) Prec@1 82.000 (77.523) Prec@5 98.000 (98.034) +2022-11-14 13:37:23,097 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1522 (0.1323) Prec@1 74.000 (77.483) Prec@5 98.000 (98.034) +2022-11-14 13:37:23,105 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1262 (0.1323) Prec@1 79.000 (77.500) Prec@5 100.000 (98.056) +2022-11-14 13:37:23,114 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1516 (0.1325) Prec@1 73.000 (77.451) Prec@5 97.000 (98.044) +2022-11-14 13:37:23,123 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.1321) Prec@1 82.000 (77.500) Prec@5 100.000 (98.065) +2022-11-14 13:37:23,133 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1368 (0.1321) Prec@1 76.000 (77.484) Prec@5 97.000 (98.054) +2022-11-14 13:37:23,143 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1414 (0.1322) Prec@1 73.000 (77.436) Prec@5 99.000 (98.064) +2022-11-14 13:37:23,153 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1651 (0.1326) Prec@1 75.000 (77.411) Prec@5 97.000 (98.053) +2022-11-14 13:37:23,163 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.1321) Prec@1 85.000 (77.490) Prec@5 98.000 (98.052) +2022-11-14 13:37:23,174 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.1318) Prec@1 82.000 (77.536) Prec@5 100.000 (98.072) +2022-11-14 13:37:23,184 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1406 (0.1319) Prec@1 76.000 (77.520) Prec@5 97.000 (98.061) +2022-11-14 13:37:23,192 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1317 (0.1318) Prec@1 77.000 (77.515) Prec@5 97.000 (98.051) +2022-11-14 13:37:23,202 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1324 (0.1319) Prec@1 76.000 (77.500) Prec@5 97.000 (98.040) +2022-11-14 13:37:23,257 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:37:23,560 Epoch: [70][0/500] Time 0.022 (0.022) Data 0.220 (0.220) Loss 0.0967 (0.0967) Prec@1 82.000 (82.000) Prec@5 97.000 (97.000) +2022-11-14 13:37:23,767 Epoch: [70][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0756 (0.0862) Prec@1 89.000 (85.500) Prec@5 100.000 (98.500) +2022-11-14 13:37:23,977 Epoch: [70][20/500] Time 0.020 (0.018) Data 0.002 (0.012) Loss 0.1144 (0.0956) Prec@1 80.000 (83.667) Prec@5 97.000 (98.000) +2022-11-14 13:37:24,177 Epoch: [70][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.1038 (0.0976) Prec@1 80.000 (82.750) Prec@5 99.000 (98.250) +2022-11-14 13:37:24,382 Epoch: [70][40/500] Time 0.019 (0.018) Data 0.002 (0.007) Loss 0.0551 (0.0891) Prec@1 90.000 (84.200) Prec@5 100.000 (98.600) +2022-11-14 13:37:24,659 Epoch: [70][50/500] Time 0.023 (0.019) Data 0.002 (0.006) Loss 0.0646 (0.0850) Prec@1 92.000 (85.500) Prec@5 100.000 (98.833) +2022-11-14 13:37:24,937 Epoch: [70][60/500] Time 0.026 (0.020) Data 0.002 (0.005) Loss 0.1088 (0.0884) Prec@1 85.000 (85.429) Prec@5 100.000 (99.000) +2022-11-14 13:37:25,226 Epoch: [70][70/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0956 (0.0893) Prec@1 83.000 (85.125) Prec@5 100.000 (99.125) +2022-11-14 13:37:25,517 Epoch: [70][80/500] Time 0.031 (0.021) Data 0.003 (0.005) Loss 0.0823 (0.0885) Prec@1 89.000 (85.556) Prec@5 99.000 (99.111) +2022-11-14 13:37:25,803 Epoch: [70][90/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0608 (0.0858) Prec@1 89.000 (85.900) Prec@5 99.000 (99.100) +2022-11-14 13:37:26,082 Epoch: [70][100/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0893 (0.0861) Prec@1 84.000 (85.727) Prec@5 99.000 (99.091) +2022-11-14 13:37:26,375 Epoch: [70][110/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0987 (0.0871) Prec@1 82.000 (85.417) Prec@5 100.000 (99.167) +2022-11-14 13:37:26,651 Epoch: [70][120/500] Time 0.029 (0.023) Data 0.002 (0.004) Loss 0.1046 (0.0885) Prec@1 83.000 (85.231) Prec@5 98.000 (99.077) +2022-11-14 13:37:26,931 Epoch: [70][130/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0999 (0.0893) Prec@1 84.000 (85.143) Prec@5 99.000 (99.071) +2022-11-14 13:37:27,222 Epoch: [70][140/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0830 (0.0889) Prec@1 84.000 (85.067) Prec@5 100.000 (99.133) +2022-11-14 13:37:27,511 Epoch: [70][150/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0796 (0.0883) Prec@1 84.000 (85.000) Prec@5 99.000 (99.125) +2022-11-14 13:37:27,796 Epoch: [70][160/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.1091 (0.0895) Prec@1 82.000 (84.824) Prec@5 95.000 (98.882) +2022-11-14 13:37:28,084 Epoch: [70][170/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.0803 (0.0890) Prec@1 83.000 (84.722) Prec@5 98.000 (98.833) +2022-11-14 13:37:28,471 Epoch: [70][180/500] Time 0.053 (0.024) Data 0.002 (0.003) Loss 0.0814 (0.0886) Prec@1 85.000 (84.737) Prec@5 100.000 (98.895) +2022-11-14 13:37:28,946 Epoch: [70][190/500] Time 0.043 (0.025) Data 0.002 (0.003) Loss 0.0720 (0.0878) Prec@1 88.000 (84.900) Prec@5 100.000 (98.950) +2022-11-14 13:37:29,453 Epoch: [70][200/500] Time 0.051 (0.026) Data 0.002 (0.003) Loss 0.0773 (0.0873) Prec@1 84.000 (84.857) Prec@5 99.000 (98.952) +2022-11-14 13:37:29,918 Epoch: [70][210/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.1118 (0.0884) Prec@1 81.000 (84.682) Prec@5 99.000 (98.955) +2022-11-14 13:37:30,387 Epoch: [70][220/500] Time 0.044 (0.027) Data 0.001 (0.003) Loss 0.0889 (0.0884) Prec@1 85.000 (84.696) Prec@5 98.000 (98.913) +2022-11-14 13:37:30,856 Epoch: [70][230/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.1027 (0.0890) Prec@1 77.000 (84.375) Prec@5 100.000 (98.958) +2022-11-14 13:37:31,356 Epoch: [70][240/500] Time 0.052 (0.029) Data 0.002 (0.003) Loss 0.0987 (0.0894) Prec@1 82.000 (84.280) Prec@5 99.000 (98.960) +2022-11-14 13:37:31,827 Epoch: [70][250/500] Time 0.042 (0.029) Data 0.003 (0.003) Loss 0.1356 (0.0912) Prec@1 74.000 (83.885) Prec@5 95.000 (98.808) +2022-11-14 13:37:32,299 Epoch: [70][260/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.1020 (0.0916) Prec@1 81.000 (83.778) Prec@5 99.000 (98.815) +2022-11-14 13:37:32,767 Epoch: [70][270/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0706 (0.0908) Prec@1 85.000 (83.821) Prec@5 99.000 (98.821) +2022-11-14 13:37:33,272 Epoch: [70][280/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.1051 (0.0913) Prec@1 83.000 (83.793) Prec@5 98.000 (98.793) +2022-11-14 13:37:33,752 Epoch: [70][290/500] Time 0.052 (0.031) Data 0.002 (0.003) Loss 0.0774 (0.0909) Prec@1 86.000 (83.867) Prec@5 100.000 (98.833) +2022-11-14 13:37:34,253 Epoch: [70][300/500] Time 0.053 (0.032) Data 0.002 (0.003) Loss 0.1099 (0.0915) Prec@1 81.000 (83.774) Prec@5 99.000 (98.839) +2022-11-14 13:37:34,737 Epoch: [70][310/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.1208 (0.0924) Prec@1 78.000 (83.594) Prec@5 98.000 (98.812) +2022-11-14 13:37:35,211 Epoch: [70][320/500] Time 0.060 (0.032) Data 0.002 (0.003) Loss 0.1004 (0.0926) Prec@1 82.000 (83.545) Prec@5 98.000 (98.788) +2022-11-14 13:37:35,711 Epoch: [70][330/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0954 (0.0927) Prec@1 83.000 (83.529) Prec@5 97.000 (98.735) +2022-11-14 13:37:36,188 Epoch: [70][340/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0732 (0.0922) Prec@1 86.000 (83.600) Prec@5 100.000 (98.771) +2022-11-14 13:37:36,657 Epoch: [70][350/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0918 (0.0921) Prec@1 82.000 (83.556) Prec@5 100.000 (98.806) +2022-11-14 13:37:37,134 Epoch: [70][360/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0982 (0.0923) Prec@1 82.000 (83.514) Prec@5 99.000 (98.811) +2022-11-14 13:37:37,600 Epoch: [70][370/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0782 (0.0919) Prec@1 87.000 (83.605) Prec@5 100.000 (98.842) +2022-11-14 13:37:38,064 Epoch: [70][380/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0866 (0.0918) Prec@1 84.000 (83.615) Prec@5 98.000 (98.821) +2022-11-14 13:37:38,519 Epoch: [70][390/500] Time 0.039 (0.034) Data 0.001 (0.002) Loss 0.1110 (0.0923) Prec@1 80.000 (83.525) Prec@5 98.000 (98.800) +2022-11-14 13:37:38,830 Epoch: [70][400/500] Time 0.032 (0.034) Data 0.002 (0.002) Loss 0.0759 (0.0919) Prec@1 89.000 (83.659) Prec@5 100.000 (98.829) +2022-11-14 13:37:39,129 Epoch: [70][410/500] Time 0.027 (0.034) Data 0.001 (0.002) Loss 0.1481 (0.0932) Prec@1 75.000 (83.452) Prec@5 100.000 (98.857) +2022-11-14 13:37:39,442 Epoch: [70][420/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0834 (0.0930) Prec@1 88.000 (83.558) Prec@5 100.000 (98.884) +2022-11-14 13:37:39,740 Epoch: [70][430/500] Time 0.027 (0.033) Data 0.001 (0.002) Loss 0.1173 (0.0935) Prec@1 77.000 (83.409) Prec@5 96.000 (98.818) +2022-11-14 13:37:40,048 Epoch: [70][440/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0943 (0.0936) Prec@1 85.000 (83.444) Prec@5 100.000 (98.844) +2022-11-14 13:37:40,349 Epoch: [70][450/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0697 (0.0930) Prec@1 89.000 (83.565) Prec@5 99.000 (98.848) +2022-11-14 13:37:40,658 Epoch: [70][460/500] Time 0.031 (0.033) Data 0.002 (0.002) Loss 0.0778 (0.0927) Prec@1 88.000 (83.660) Prec@5 99.000 (98.851) +2022-11-14 13:37:40,967 Epoch: [70][470/500] Time 0.032 (0.033) Data 0.002 (0.002) Loss 0.0953 (0.0928) Prec@1 86.000 (83.708) Prec@5 99.000 (98.854) +2022-11-14 13:37:41,272 Epoch: [70][480/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.1119 (0.0932) Prec@1 78.000 (83.592) Prec@5 96.000 (98.796) +2022-11-14 13:37:41,569 Epoch: [70][490/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.1091 (0.0935) Prec@1 84.000 (83.600) Prec@5 98.000 (98.780) +2022-11-14 13:37:41,848 Epoch: [70][499/500] Time 0.036 (0.032) Data 0.001 (0.002) Loss 0.1017 (0.0936) Prec@1 79.000 (83.510) Prec@5 100.000 (98.804) +2022-11-14 13:37:42,131 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0691 (0.0691) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 13:37:42,139 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0861) Prec@1 78.000 (83.500) Prec@5 100.000 (99.000) +2022-11-14 13:37:42,150 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0906) Prec@1 84.000 (83.667) Prec@5 99.000 (99.000) +2022-11-14 13:37:42,162 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1269 (0.0997) Prec@1 79.000 (82.500) Prec@5 100.000 (99.250) +2022-11-14 13:37:42,172 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0986) Prec@1 85.000 (83.000) Prec@5 100.000 (99.400) +2022-11-14 13:37:42,181 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0921) Prec@1 88.000 (83.833) Prec@5 98.000 (99.167) +2022-11-14 13:37:42,190 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0903) Prec@1 86.000 (84.143) Prec@5 100.000 (99.286) +2022-11-14 13:37:42,200 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.0930) Prec@1 80.000 (83.625) Prec@5 98.000 (99.125) +2022-11-14 13:37:42,208 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0937) Prec@1 84.000 (83.667) Prec@5 97.000 (98.889) +2022-11-14 13:37:42,218 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0910) Prec@1 87.000 (84.000) Prec@5 98.000 (98.800) +2022-11-14 13:37:42,227 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0917) Prec@1 82.000 (83.818) Prec@5 99.000 (98.818) +2022-11-14 13:37:42,236 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0927) Prec@1 83.000 (83.750) Prec@5 99.000 (98.833) +2022-11-14 13:37:42,246 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0934) Prec@1 80.000 (83.462) Prec@5 99.000 (98.846) +2022-11-14 13:37:42,255 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0944) Prec@1 78.000 (83.071) Prec@5 99.000 (98.857) +2022-11-14 13:37:42,264 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0941) Prec@1 84.000 (83.133) Prec@5 99.000 (98.867) +2022-11-14 13:37:42,273 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0949) Prec@1 80.000 (82.938) Prec@5 98.000 (98.812) +2022-11-14 13:37:42,283 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0949) Prec@1 85.000 (83.059) Prec@5 98.000 (98.765) +2022-11-14 13:37:42,292 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0947) Prec@1 86.000 (83.222) Prec@5 99.000 (98.778) +2022-11-14 13:37:42,302 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1229 (0.0962) Prec@1 78.000 (82.947) Prec@5 96.000 (98.632) +2022-11-14 13:37:42,311 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1388 (0.0984) Prec@1 77.000 (82.650) Prec@5 97.000 (98.550) +2022-11-14 13:37:42,320 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0985) Prec@1 84.000 (82.714) Prec@5 100.000 (98.619) +2022-11-14 13:37:42,329 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0995) Prec@1 80.000 (82.591) Prec@5 97.000 (98.545) +2022-11-14 13:37:42,339 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1303 (0.1008) Prec@1 79.000 (82.435) Prec@5 99.000 (98.565) +2022-11-14 13:37:42,348 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0996) Prec@1 86.000 (82.583) Prec@5 100.000 (98.625) +2022-11-14 13:37:42,357 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1003) Prec@1 84.000 (82.640) Prec@5 99.000 (98.640) +2022-11-14 13:37:42,366 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1206 (0.1011) Prec@1 78.000 (82.462) Prec@5 97.000 (98.577) +2022-11-14 13:37:42,375 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.1009) Prec@1 81.000 (82.407) Prec@5 100.000 (98.630) +2022-11-14 13:37:42,384 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.1006) Prec@1 84.000 (82.464) Prec@5 99.000 (98.643) +2022-11-14 13:37:42,393 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.1007) Prec@1 82.000 (82.448) Prec@5 99.000 (98.655) +2022-11-14 13:37:42,404 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.1003) Prec@1 87.000 (82.600) Prec@5 99.000 (98.667) +2022-11-14 13:37:42,415 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.1001) Prec@1 85.000 (82.677) Prec@5 97.000 (98.613) +2022-11-14 13:37:42,425 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.1003) Prec@1 83.000 (82.688) Prec@5 100.000 (98.656) +2022-11-14 13:37:42,434 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.1000) Prec@1 83.000 (82.697) Prec@5 100.000 (98.697) +2022-11-14 13:37:42,443 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.1003) Prec@1 81.000 (82.647) Prec@5 98.000 (98.676) +2022-11-14 13:37:42,451 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.1001) Prec@1 84.000 (82.686) Prec@5 97.000 (98.629) +2022-11-14 13:37:42,461 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0995) Prec@1 87.000 (82.806) Prec@5 99.000 (98.639) +2022-11-14 13:37:42,470 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1277 (0.1003) Prec@1 75.000 (82.595) Prec@5 98.000 (98.622) +2022-11-14 13:37:42,479 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1290 (0.1011) Prec@1 79.000 (82.500) Prec@5 94.000 (98.500) +2022-11-14 13:37:42,489 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.1007) Prec@1 86.000 (82.590) Prec@5 99.000 (98.513) +2022-11-14 13:37:42,498 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.1003) Prec@1 83.000 (82.600) Prec@5 99.000 (98.525) +2022-11-14 13:37:42,507 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.1004) Prec@1 83.000 (82.610) Prec@5 99.000 (98.537) +2022-11-14 13:37:42,516 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.1000) Prec@1 87.000 (82.714) Prec@5 98.000 (98.524) +2022-11-14 13:37:42,525 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0996) Prec@1 88.000 (82.837) Prec@5 98.000 (98.512) +2022-11-14 13:37:42,533 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1075 (0.0997) Prec@1 81.000 (82.795) Prec@5 98.000 (98.500) +2022-11-14 13:37:42,542 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0993) Prec@1 90.000 (82.956) Prec@5 99.000 (98.511) +2022-11-14 13:37:42,552 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0995) Prec@1 81.000 (82.913) Prec@5 100.000 (98.543) +2022-11-14 13:37:42,562 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0998) Prec@1 82.000 (82.894) Prec@5 98.000 (98.532) +2022-11-14 13:37:42,571 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1249 (0.1003) Prec@1 77.000 (82.771) Prec@5 98.000 (98.521) +2022-11-14 13:37:42,581 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0999) Prec@1 86.000 (82.837) Prec@5 100.000 (98.551) +2022-11-14 13:37:42,590 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1257 (0.1004) Prec@1 80.000 (82.780) Prec@5 100.000 (98.580) +2022-11-14 13:37:42,599 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.1005) Prec@1 80.000 (82.725) Prec@5 98.000 (98.569) +2022-11-14 13:37:42,609 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1217 (0.1009) Prec@1 77.000 (82.615) Prec@5 99.000 (98.577) +2022-11-14 13:37:42,617 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.1008) Prec@1 84.000 (82.642) Prec@5 100.000 (98.604) +2022-11-14 13:37:42,627 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.1010) Prec@1 80.000 (82.593) Prec@5 95.000 (98.537) +2022-11-14 13:37:42,637 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.1011) Prec@1 83.000 (82.600) Prec@5 100.000 (98.564) +2022-11-14 13:37:42,647 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.1010) Prec@1 83.000 (82.607) Prec@5 97.000 (98.536) +2022-11-14 13:37:42,657 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1136 (0.1013) Prec@1 79.000 (82.544) Prec@5 98.000 (98.526) +2022-11-14 13:37:42,666 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.1012) Prec@1 83.000 (82.552) Prec@5 99.000 (98.534) +2022-11-14 13:37:42,676 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.1014) Prec@1 78.000 (82.475) Prec@5 99.000 (98.542) +2022-11-14 13:37:42,685 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.1013) Prec@1 84.000 (82.500) Prec@5 98.000 (98.533) +2022-11-14 13:37:42,694 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.1015) Prec@1 80.000 (82.459) Prec@5 100.000 (98.557) +2022-11-14 13:37:42,702 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.1014) Prec@1 87.000 (82.532) Prec@5 99.000 (98.565) +2022-11-14 13:37:42,712 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.1012) Prec@1 85.000 (82.571) Prec@5 98.000 (98.556) +2022-11-14 13:37:42,720 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.1013) Prec@1 81.000 (82.547) Prec@5 100.000 (98.578) +2022-11-14 13:37:42,729 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1189 (0.1015) Prec@1 79.000 (82.492) Prec@5 97.000 (98.554) +2022-11-14 13:37:42,739 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.1016) Prec@1 82.000 (82.485) Prec@5 99.000 (98.561) +2022-11-14 13:37:42,749 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.1012) Prec@1 87.000 (82.552) Prec@5 99.000 (98.567) +2022-11-14 13:37:42,759 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.1014) Prec@1 81.000 (82.529) Prec@5 99.000 (98.574) +2022-11-14 13:37:42,768 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.1012) Prec@1 83.000 (82.536) Prec@5 97.000 (98.551) +2022-11-14 13:37:42,777 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.1014) Prec@1 83.000 (82.543) Prec@5 99.000 (98.557) +2022-11-14 13:37:42,787 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.1014) Prec@1 83.000 (82.549) Prec@5 100.000 (98.577) +2022-11-14 13:37:42,797 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.1014) Prec@1 85.000 (82.583) Prec@5 99.000 (98.583) +2022-11-14 13:37:42,806 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.1012) Prec@1 83.000 (82.589) Prec@5 99.000 (98.589) +2022-11-14 13:37:42,815 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.1010) Prec@1 88.000 (82.662) Prec@5 100.000 (98.608) +2022-11-14 13:37:42,824 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.1009) Prec@1 83.000 (82.667) Prec@5 97.000 (98.587) +2022-11-14 13:37:42,832 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.1007) Prec@1 89.000 (82.750) Prec@5 100.000 (98.605) +2022-11-14 13:37:42,841 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.1006) Prec@1 85.000 (82.779) Prec@5 98.000 (98.597) +2022-11-14 13:37:42,851 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1005) Prec@1 83.000 (82.782) Prec@5 99.000 (98.603) +2022-11-14 13:37:42,859 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.1004) Prec@1 86.000 (82.823) Prec@5 100.000 (98.620) +2022-11-14 13:37:42,867 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.1005) Prec@1 78.000 (82.763) Prec@5 98.000 (98.612) +2022-11-14 13:37:42,877 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.1001) Prec@1 88.000 (82.827) Prec@5 99.000 (98.617) +2022-11-14 13:37:42,886 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.1002) Prec@1 82.000 (82.817) Prec@5 99.000 (98.622) +2022-11-14 13:37:42,896 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1301 (0.1006) Prec@1 78.000 (82.759) Prec@5 98.000 (98.614) +2022-11-14 13:37:42,905 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.1003) Prec@1 87.000 (82.810) Prec@5 99.000 (98.619) +2022-11-14 13:37:42,916 Test: [84/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.1005) Prec@1 81.000 (82.788) Prec@5 98.000 (98.612) +2022-11-14 13:37:42,928 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1150 (0.1006) Prec@1 80.000 (82.756) Prec@5 97.000 (98.593) +2022-11-14 13:37:42,937 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.1007) Prec@1 81.000 (82.736) Prec@5 100.000 (98.609) +2022-11-14 13:37:42,946 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.1007) Prec@1 84.000 (82.750) Prec@5 99.000 (98.614) +2022-11-14 13:37:42,956 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.1006) Prec@1 84.000 (82.764) Prec@5 99.000 (98.618) +2022-11-14 13:37:42,965 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.1005) Prec@1 85.000 (82.789) Prec@5 97.000 (98.600) +2022-11-14 13:37:42,973 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.1005) Prec@1 80.000 (82.758) Prec@5 99.000 (98.604) +2022-11-14 13:37:42,983 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.1001) Prec@1 88.000 (82.815) Prec@5 99.000 (98.609) +2022-11-14 13:37:42,991 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.1003) Prec@1 78.000 (82.763) Prec@5 99.000 (98.613) +2022-11-14 13:37:43,000 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.1003) Prec@1 83.000 (82.766) Prec@5 98.000 (98.606) +2022-11-14 13:37:43,009 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.1004) Prec@1 80.000 (82.737) Prec@5 99.000 (98.611) +2022-11-14 13:37:43,019 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.1002) Prec@1 83.000 (82.740) Prec@5 99.000 (98.615) +2022-11-14 13:37:43,027 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.1000) Prec@1 86.000 (82.773) Prec@5 99.000 (98.619) +2022-11-14 13:37:43,035 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1249 (0.1003) Prec@1 79.000 (82.735) Prec@5 98.000 (98.612) +2022-11-14 13:37:43,043 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1347 (0.1006) Prec@1 78.000 (82.687) Prec@5 97.000 (98.596) +2022-11-14 13:37:43,051 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.1007) Prec@1 81.000 (82.670) Prec@5 98.000 (98.590) +2022-11-14 13:37:43,104 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:37:43,396 Epoch: [71][0/500] Time 0.022 (0.022) Data 0.211 (0.211) Loss 0.1049 (0.1049) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:37:43,605 Epoch: [71][10/500] Time 0.015 (0.019) Data 0.002 (0.021) Loss 0.0973 (0.1011) Prec@1 82.000 (83.000) Prec@5 100.000 (99.500) +2022-11-14 13:37:43,797 Epoch: [71][20/500] Time 0.017 (0.018) Data 0.002 (0.012) Loss 0.0787 (0.0936) Prec@1 85.000 (83.667) Prec@5 100.000 (99.667) +2022-11-14 13:37:44,037 Epoch: [71][30/500] Time 0.023 (0.019) Data 0.002 (0.008) Loss 0.0747 (0.0889) Prec@1 89.000 (85.000) Prec@5 100.000 (99.750) +2022-11-14 13:37:44,298 Epoch: [71][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.0986 (0.0908) Prec@1 81.000 (84.200) Prec@5 99.000 (99.600) +2022-11-14 13:37:44,567 Epoch: [71][50/500] Time 0.030 (0.021) Data 0.002 (0.006) Loss 0.0968 (0.0918) Prec@1 85.000 (84.333) Prec@5 99.000 (99.500) +2022-11-14 13:37:44,824 Epoch: [71][60/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0830 (0.0906) Prec@1 84.000 (84.286) Prec@5 100.000 (99.571) +2022-11-14 13:37:45,152 Epoch: [71][70/500] Time 0.043 (0.022) Data 0.002 (0.005) Loss 0.0868 (0.0901) Prec@1 84.000 (84.250) Prec@5 100.000 (99.625) +2022-11-14 13:37:45,671 Epoch: [71][80/500] Time 0.048 (0.025) Data 0.002 (0.004) Loss 0.0895 (0.0900) Prec@1 85.000 (84.333) Prec@5 97.000 (99.333) +2022-11-14 13:37:46,150 Epoch: [71][90/500] Time 0.056 (0.027) Data 0.002 (0.004) Loss 0.0794 (0.0890) Prec@1 84.000 (84.300) Prec@5 98.000 (99.200) +2022-11-14 13:37:46,613 Epoch: [71][100/500] Time 0.043 (0.028) Data 0.002 (0.004) Loss 0.1098 (0.0909) Prec@1 79.000 (83.818) Prec@5 100.000 (99.273) +2022-11-14 13:37:47,103 Epoch: [71][110/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0789 (0.0899) Prec@1 86.000 (84.000) Prec@5 100.000 (99.333) +2022-11-14 13:37:47,592 Epoch: [71][120/500] Time 0.054 (0.031) Data 0.002 (0.004) Loss 0.0992 (0.0906) Prec@1 80.000 (83.692) Prec@5 98.000 (99.231) +2022-11-14 13:37:48,079 Epoch: [71][130/500] Time 0.053 (0.032) Data 0.002 (0.003) Loss 0.0859 (0.0902) Prec@1 85.000 (83.786) Prec@5 99.000 (99.214) +2022-11-14 13:37:48,558 Epoch: [71][140/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0834 (0.0898) Prec@1 88.000 (84.067) Prec@5 98.000 (99.133) +2022-11-14 13:37:49,031 Epoch: [71][150/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0987 (0.0903) Prec@1 84.000 (84.062) Prec@5 97.000 (99.000) +2022-11-14 13:37:49,496 Epoch: [71][160/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0794 (0.0897) Prec@1 84.000 (84.059) Prec@5 100.000 (99.059) +2022-11-14 13:37:49,969 Epoch: [71][170/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0960 (0.0901) Prec@1 82.000 (83.944) Prec@5 99.000 (99.056) +2022-11-14 13:37:50,477 Epoch: [71][180/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0828 (0.0897) Prec@1 87.000 (84.105) Prec@5 99.000 (99.053) +2022-11-14 13:37:50,969 Epoch: [71][190/500] Time 0.055 (0.035) Data 0.002 (0.003) Loss 0.0671 (0.0885) Prec@1 91.000 (84.450) Prec@5 100.000 (99.100) +2022-11-14 13:37:51,444 Epoch: [71][200/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0939 (0.0888) Prec@1 83.000 (84.381) Prec@5 99.000 (99.095) +2022-11-14 13:37:51,967 Epoch: [71][210/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0805 (0.0884) Prec@1 86.000 (84.455) Prec@5 100.000 (99.136) +2022-11-14 13:37:52,430 Epoch: [71][220/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.1153 (0.0896) Prec@1 79.000 (84.217) Prec@5 99.000 (99.130) +2022-11-14 13:37:52,908 Epoch: [71][230/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0991 (0.0900) Prec@1 81.000 (84.083) Prec@5 99.000 (99.125) +2022-11-14 13:37:53,256 Epoch: [71][240/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0850 (0.0898) Prec@1 85.000 (84.120) Prec@5 98.000 (99.080) +2022-11-14 13:37:53,537 Epoch: [71][250/500] Time 0.026 (0.036) Data 0.002 (0.003) Loss 0.0964 (0.0900) Prec@1 82.000 (84.038) Prec@5 99.000 (99.077) +2022-11-14 13:37:53,822 Epoch: [71][260/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.1264 (0.0914) Prec@1 77.000 (83.778) Prec@5 96.000 (98.963) +2022-11-14 13:37:54,119 Epoch: [71][270/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.1161 (0.0923) Prec@1 83.000 (83.750) Prec@5 96.000 (98.857) +2022-11-14 13:37:54,408 Epoch: [71][280/500] Time 0.025 (0.035) Data 0.002 (0.003) Loss 0.0888 (0.0922) Prec@1 85.000 (83.793) Prec@5 100.000 (98.897) +2022-11-14 13:37:54,694 Epoch: [71][290/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0854 (0.0919) Prec@1 83.000 (83.767) Prec@5 99.000 (98.900) +2022-11-14 13:37:54,981 Epoch: [71][300/500] Time 0.027 (0.034) Data 0.002 (0.003) Loss 0.1220 (0.0929) Prec@1 78.000 (83.581) Prec@5 98.000 (98.871) +2022-11-14 13:37:55,287 Epoch: [71][310/500] Time 0.034 (0.034) Data 0.001 (0.003) Loss 0.0892 (0.0928) Prec@1 85.000 (83.625) Prec@5 97.000 (98.812) +2022-11-14 13:37:55,636 Epoch: [71][320/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0811 (0.0924) Prec@1 86.000 (83.697) Prec@5 100.000 (98.848) +2022-11-14 13:37:55,959 Epoch: [71][330/500] Time 0.023 (0.034) Data 0.002 (0.002) Loss 0.0935 (0.0925) Prec@1 83.000 (83.676) Prec@5 98.000 (98.824) +2022-11-14 13:37:56,237 Epoch: [71][340/500] Time 0.024 (0.033) Data 0.002 (0.002) Loss 0.1057 (0.0928) Prec@1 79.000 (83.543) Prec@5 98.000 (98.800) +2022-11-14 13:37:56,521 Epoch: [71][350/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0969 (0.0930) Prec@1 84.000 (83.556) Prec@5 100.000 (98.833) +2022-11-14 13:37:56,810 Epoch: [71][360/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.1019 (0.0932) Prec@1 82.000 (83.514) Prec@5 98.000 (98.811) +2022-11-14 13:37:57,096 Epoch: [71][370/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0882 (0.0931) Prec@1 84.000 (83.526) Prec@5 99.000 (98.816) +2022-11-14 13:37:57,387 Epoch: [71][380/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.1156 (0.0936) Prec@1 81.000 (83.462) Prec@5 99.000 (98.821) +2022-11-14 13:37:57,721 Epoch: [71][390/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0825 (0.0934) Prec@1 86.000 (83.525) Prec@5 100.000 (98.850) +2022-11-14 13:37:58,044 Epoch: [71][400/500] Time 0.039 (0.032) Data 0.002 (0.002) Loss 0.0818 (0.0931) Prec@1 85.000 (83.561) Prec@5 100.000 (98.878) +2022-11-14 13:37:58,385 Epoch: [71][410/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.1273 (0.0939) Prec@1 77.000 (83.405) Prec@5 99.000 (98.881) +2022-11-14 13:37:58,673 Epoch: [71][420/500] Time 0.023 (0.032) Data 0.002 (0.002) Loss 0.0714 (0.0934) Prec@1 88.000 (83.512) Prec@5 99.000 (98.884) +2022-11-14 13:37:58,971 Epoch: [71][430/500] Time 0.025 (0.032) Data 0.002 (0.002) Loss 0.0947 (0.0934) Prec@1 84.000 (83.523) Prec@5 97.000 (98.841) +2022-11-14 13:37:59,323 Epoch: [71][440/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0869 (0.0933) Prec@1 85.000 (83.556) Prec@5 98.000 (98.822) +2022-11-14 13:37:59,802 Epoch: [71][450/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.1008 (0.0934) Prec@1 85.000 (83.587) Prec@5 98.000 (98.804) +2022-11-14 13:38:00,295 Epoch: [71][460/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0998 (0.0936) Prec@1 82.000 (83.553) Prec@5 99.000 (98.809) +2022-11-14 13:38:00,765 Epoch: [71][470/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.1168 (0.0940) Prec@1 80.000 (83.479) Prec@5 96.000 (98.750) +2022-11-14 13:38:01,237 Epoch: [71][480/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0906 (0.0940) Prec@1 83.000 (83.469) Prec@5 99.000 (98.755) +2022-11-14 13:38:01,703 Epoch: [71][490/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0945 (0.0940) Prec@1 85.000 (83.500) Prec@5 99.000 (98.760) +2022-11-14 13:38:02,124 Epoch: [71][499/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0922 (0.0939) Prec@1 84.000 (83.510) Prec@5 99.000 (98.765) +2022-11-14 13:38:02,408 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1045 (0.1045) Prec@1 79.000 (79.000) Prec@5 98.000 (98.000) +2022-11-14 13:38:02,417 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.1015) Prec@1 82.000 (80.500) Prec@5 99.000 (98.500) +2022-11-14 13:38:02,429 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1234 (0.1088) Prec@1 78.000 (79.667) Prec@5 99.000 (98.667) +2022-11-14 13:38:02,442 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.1088) Prec@1 82.000 (80.250) Prec@5 100.000 (99.000) +2022-11-14 13:38:02,452 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1255 (0.1122) Prec@1 78.000 (79.800) Prec@5 99.000 (99.000) +2022-11-14 13:38:02,461 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.1047) Prec@1 88.000 (81.167) Prec@5 99.000 (99.000) +2022-11-14 13:38:02,472 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.1044) Prec@1 85.000 (81.714) Prec@5 99.000 (99.000) +2022-11-14 13:38:02,483 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.1049) Prec@1 82.000 (81.750) Prec@5 98.000 (98.875) +2022-11-14 13:38:02,492 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.1060) Prec@1 78.000 (81.333) Prec@5 98.000 (98.778) +2022-11-14 13:38:02,499 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.1044) Prec@1 86.000 (81.800) Prec@5 99.000 (98.800) +2022-11-14 13:38:02,507 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1231 (0.1061) Prec@1 81.000 (81.727) Prec@5 98.000 (98.727) +2022-11-14 13:38:02,515 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.1056) Prec@1 82.000 (81.750) Prec@5 98.000 (98.667) +2022-11-14 13:38:02,525 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.1058) Prec@1 78.000 (81.462) Prec@5 99.000 (98.692) +2022-11-14 13:38:02,535 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.1044) Prec@1 86.000 (81.786) Prec@5 99.000 (98.714) +2022-11-14 13:38:02,546 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.1041) Prec@1 82.000 (81.800) Prec@5 100.000 (98.800) +2022-11-14 13:38:02,555 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.1054) Prec@1 79.000 (81.625) Prec@5 96.000 (98.625) +2022-11-14 13:38:02,565 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.1043) Prec@1 85.000 (81.824) Prec@5 99.000 (98.647) +2022-11-14 13:38:02,576 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1048) Prec@1 81.000 (81.778) Prec@5 99.000 (98.667) +2022-11-14 13:38:02,586 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1053) Prec@1 81.000 (81.737) Prec@5 99.000 (98.684) +2022-11-14 13:38:02,597 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.1059) Prec@1 80.000 (81.650) Prec@5 96.000 (98.550) +2022-11-14 13:38:02,608 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1391 (0.1074) Prec@1 72.000 (81.190) Prec@5 99.000 (98.571) +2022-11-14 13:38:02,617 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1240 (0.1082) Prec@1 82.000 (81.227) Prec@5 98.000 (98.545) +2022-11-14 13:38:02,627 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1378 (0.1095) Prec@1 77.000 (81.043) Prec@5 99.000 (98.565) +2022-11-14 13:38:02,639 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.1086) Prec@1 84.000 (81.167) Prec@5 99.000 (98.583) +2022-11-14 13:38:02,649 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.1085) Prec@1 84.000 (81.280) Prec@5 100.000 (98.640) +2022-11-14 13:38:02,660 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1166 (0.1089) Prec@1 80.000 (81.231) Prec@5 98.000 (98.615) +2022-11-14 13:38:02,669 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.1085) Prec@1 83.000 (81.296) Prec@5 100.000 (98.667) +2022-11-14 13:38:02,679 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.1090) Prec@1 76.000 (81.107) Prec@5 99.000 (98.679) +2022-11-14 13:38:02,689 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.1089) Prec@1 83.000 (81.172) Prec@5 97.000 (98.621) +2022-11-14 13:38:02,699 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.1091) Prec@1 78.000 (81.067) Prec@5 97.000 (98.567) +2022-11-14 13:38:02,711 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.1090) Prec@1 79.000 (81.000) Prec@5 99.000 (98.581) +2022-11-14 13:38:02,722 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.1086) Prec@1 85.000 (81.125) Prec@5 99.000 (98.594) +2022-11-14 13:38:02,733 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.1091) Prec@1 77.000 (81.000) Prec@5 94.000 (98.455) +2022-11-14 13:38:02,743 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1468 (0.1103) Prec@1 74.000 (80.794) Prec@5 97.000 (98.412) +2022-11-14 13:38:02,754 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.1102) Prec@1 81.000 (80.800) Prec@5 96.000 (98.343) +2022-11-14 13:38:02,764 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.1103) Prec@1 81.000 (80.806) Prec@5 98.000 (98.333) +2022-11-14 13:38:02,774 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.1103) Prec@1 81.000 (80.811) Prec@5 96.000 (98.270) +2022-11-14 13:38:02,785 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.1106) Prec@1 77.000 (80.711) Prec@5 99.000 (98.289) +2022-11-14 13:38:02,796 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.1105) Prec@1 82.000 (80.744) Prec@5 100.000 (98.333) +2022-11-14 13:38:02,806 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.1102) Prec@1 83.000 (80.800) Prec@5 98.000 (98.325) +2022-11-14 13:38:02,816 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1106) Prec@1 80.000 (80.780) Prec@5 94.000 (98.220) +2022-11-14 13:38:02,826 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.1098) Prec@1 86.000 (80.905) Prec@5 99.000 (98.238) +2022-11-14 13:38:02,837 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.1093) Prec@1 84.000 (80.977) Prec@5 99.000 (98.256) +2022-11-14 13:38:02,846 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.1090) Prec@1 83.000 (81.023) Prec@5 99.000 (98.273) +2022-11-14 13:38:02,855 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1301 (0.1095) Prec@1 77.000 (80.933) Prec@5 99.000 (98.289) +2022-11-14 13:38:02,865 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1288 (0.1099) Prec@1 77.000 (80.848) Prec@5 99.000 (98.304) +2022-11-14 13:38:02,875 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.1100) Prec@1 78.000 (80.787) Prec@5 100.000 (98.340) +2022-11-14 13:38:02,885 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.1104) Prec@1 79.000 (80.750) Prec@5 98.000 (98.333) +2022-11-14 13:38:02,896 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.1099) Prec@1 84.000 (80.816) Prec@5 99.000 (98.347) +2022-11-14 13:38:02,906 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1452 (0.1106) Prec@1 75.000 (80.700) Prec@5 98.000 (98.340) +2022-11-14 13:38:02,916 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.1104) Prec@1 82.000 (80.725) Prec@5 100.000 (98.373) +2022-11-14 13:38:02,927 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.1107) Prec@1 77.000 (80.654) Prec@5 99.000 (98.385) +2022-11-14 13:38:02,938 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.1103) Prec@1 90.000 (80.830) Prec@5 100.000 (98.415) +2022-11-14 13:38:02,948 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.1101) Prec@1 84.000 (80.889) Prec@5 99.000 (98.426) +2022-11-14 13:38:02,958 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.1100) Prec@1 82.000 (80.909) Prec@5 100.000 (98.455) +2022-11-14 13:38:02,968 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.1100) Prec@1 80.000 (80.893) Prec@5 100.000 (98.482) +2022-11-14 13:38:02,979 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.1102) Prec@1 77.000 (80.825) Prec@5 99.000 (98.491) +2022-11-14 13:38:02,989 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.1095) Prec@1 90.000 (80.983) Prec@5 99.000 (98.500) +2022-11-14 13:38:03,000 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1140 (0.1096) Prec@1 82.000 (81.000) Prec@5 100.000 (98.525) +2022-11-14 13:38:03,010 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.1096) Prec@1 81.000 (81.000) Prec@5 98.000 (98.517) +2022-11-14 13:38:03,021 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.1095) Prec@1 81.000 (81.000) Prec@5 100.000 (98.541) +2022-11-14 13:38:03,031 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.1098) Prec@1 79.000 (80.968) Prec@5 100.000 (98.565) +2022-11-14 13:38:03,042 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.1096) Prec@1 85.000 (81.032) Prec@5 99.000 (98.571) +2022-11-14 13:38:03,052 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.1094) Prec@1 84.000 (81.078) Prec@5 100.000 (98.594) +2022-11-14 13:38:03,063 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1213 (0.1096) Prec@1 78.000 (81.031) Prec@5 98.000 (98.585) +2022-11-14 13:38:03,073 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.1097) Prec@1 79.000 (81.000) Prec@5 99.000 (98.591) +2022-11-14 13:38:03,083 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1098) Prec@1 81.000 (81.000) Prec@5 98.000 (98.582) +2022-11-14 13:38:03,094 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.1099) Prec@1 80.000 (80.985) Prec@5 97.000 (98.559) +2022-11-14 13:38:03,104 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1100) Prec@1 77.000 (80.928) Prec@5 97.000 (98.536) +2022-11-14 13:38:03,114 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.1104) Prec@1 76.000 (80.857) Prec@5 98.000 (98.529) +2022-11-14 13:38:03,125 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.1104) Prec@1 81.000 (80.859) Prec@5 99.000 (98.535) +2022-11-14 13:38:03,135 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1269 (0.1106) Prec@1 78.000 (80.819) Prec@5 99.000 (98.542) +2022-11-14 13:38:03,144 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.1104) Prec@1 84.000 (80.863) Prec@5 99.000 (98.548) +2022-11-14 13:38:03,152 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.1100) Prec@1 83.000 (80.892) Prec@5 100.000 (98.568) +2022-11-14 13:38:03,160 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1311 (0.1103) Prec@1 76.000 (80.827) Prec@5 98.000 (98.560) +2022-11-14 13:38:03,169 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.1100) Prec@1 87.000 (80.908) Prec@5 100.000 (98.579) +2022-11-14 13:38:03,179 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1257 (0.1102) Prec@1 80.000 (80.896) Prec@5 99.000 (98.584) +2022-11-14 13:38:03,188 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1102) Prec@1 80.000 (80.885) Prec@5 98.000 (98.577) +2022-11-14 13:38:03,199 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.1101) Prec@1 83.000 (80.911) Prec@5 99.000 (98.582) +2022-11-14 13:38:03,209 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.1103) Prec@1 80.000 (80.900) Prec@5 100.000 (98.600) +2022-11-14 13:38:03,219 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1102) Prec@1 82.000 (80.914) Prec@5 99.000 (98.605) +2022-11-14 13:38:03,230 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.1102) Prec@1 79.000 (80.890) Prec@5 99.000 (98.610) +2022-11-14 13:38:03,241 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1211 (0.1104) Prec@1 78.000 (80.855) Prec@5 99.000 (98.614) +2022-11-14 13:38:03,250 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.1103) Prec@1 81.000 (80.857) Prec@5 99.000 (98.619) +2022-11-14 13:38:03,261 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1452 (0.1107) Prec@1 76.000 (80.800) Prec@5 95.000 (98.576) +2022-11-14 13:38:03,271 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.1107) Prec@1 81.000 (80.802) Prec@5 99.000 (98.581) +2022-11-14 13:38:03,281 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1106) Prec@1 85.000 (80.851) Prec@5 97.000 (98.563) +2022-11-14 13:38:03,290 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.1106) Prec@1 78.000 (80.818) Prec@5 100.000 (98.580) +2022-11-14 13:38:03,300 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.1106) Prec@1 82.000 (80.831) Prec@5 96.000 (98.551) +2022-11-14 13:38:03,310 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1107) Prec@1 80.000 (80.822) Prec@5 99.000 (98.556) +2022-11-14 13:38:03,320 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.1106) Prec@1 81.000 (80.824) Prec@5 99.000 (98.560) +2022-11-14 13:38:03,331 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.1100) Prec@1 91.000 (80.935) Prec@5 100.000 (98.576) +2022-11-14 13:38:03,343 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.1100) Prec@1 79.000 (80.914) Prec@5 97.000 (98.559) +2022-11-14 13:38:03,354 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.1099) Prec@1 81.000 (80.915) Prec@5 100.000 (98.574) +2022-11-14 13:38:03,365 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1098) Prec@1 80.000 (80.905) Prec@5 98.000 (98.568) +2022-11-14 13:38:03,376 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.1098) Prec@1 81.000 (80.906) Prec@5 99.000 (98.573) +2022-11-14 13:38:03,387 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.1095) Prec@1 86.000 (80.959) Prec@5 99.000 (98.577) +2022-11-14 13:38:03,396 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1455 (0.1099) Prec@1 73.000 (80.878) Prec@5 99.000 (98.582) +2022-11-14 13:38:03,406 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.1102) Prec@1 78.000 (80.848) Prec@5 98.000 (98.576) +2022-11-14 13:38:03,414 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.1102) Prec@1 79.000 (80.830) Prec@5 100.000 (98.590) +2022-11-14 13:38:03,470 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:38:03,770 Epoch: [72][0/500] Time 0.022 (0.022) Data 0.218 (0.218) Loss 0.0859 (0.0859) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:38:03,988 Epoch: [72][10/500] Time 0.020 (0.019) Data 0.002 (0.021) Loss 0.0792 (0.0825) Prec@1 87.000 (85.000) Prec@5 100.000 (99.500) +2022-11-14 13:38:04,225 Epoch: [72][20/500] Time 0.029 (0.020) Data 0.002 (0.012) Loss 0.1020 (0.0890) Prec@1 83.000 (84.333) Prec@5 98.000 (99.000) +2022-11-14 13:38:04,454 Epoch: [72][30/500] Time 0.020 (0.020) Data 0.002 (0.009) Loss 0.0852 (0.0881) Prec@1 83.000 (84.000) Prec@5 100.000 (99.250) +2022-11-14 13:38:04,761 Epoch: [72][40/500] Time 0.031 (0.022) Data 0.002 (0.007) Loss 0.0865 (0.0878) Prec@1 85.000 (84.200) Prec@5 100.000 (99.400) +2022-11-14 13:38:05,160 Epoch: [72][50/500] Time 0.040 (0.024) Data 0.002 (0.006) Loss 0.0647 (0.0839) Prec@1 88.000 (84.833) Prec@5 100.000 (99.500) +2022-11-14 13:38:05,566 Epoch: [72][60/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.1037 (0.0867) Prec@1 84.000 (84.714) Prec@5 98.000 (99.286) +2022-11-14 13:38:05,939 Epoch: [72][70/500] Time 0.022 (0.027) Data 0.002 (0.005) Loss 0.0967 (0.0880) Prec@1 82.000 (84.375) Prec@5 99.000 (99.250) +2022-11-14 13:38:06,276 Epoch: [72][80/500] Time 0.037 (0.028) Data 0.002 (0.005) Loss 0.0797 (0.0871) Prec@1 86.000 (84.556) Prec@5 98.000 (99.111) +2022-11-14 13:38:06,608 Epoch: [72][90/500] Time 0.024 (0.028) Data 0.002 (0.004) Loss 0.0770 (0.0861) Prec@1 88.000 (84.900) Prec@5 97.000 (98.900) +2022-11-14 13:38:06,963 Epoch: [72][100/500] Time 0.025 (0.028) Data 0.002 (0.004) Loss 0.0891 (0.0863) Prec@1 85.000 (84.909) Prec@5 100.000 (99.000) +2022-11-14 13:38:07,319 Epoch: [72][110/500] Time 0.025 (0.029) Data 0.002 (0.004) Loss 0.1167 (0.0889) Prec@1 81.000 (84.583) Prec@5 100.000 (99.083) +2022-11-14 13:38:07,672 Epoch: [72][120/500] Time 0.039 (0.029) Data 0.002 (0.004) Loss 0.1026 (0.0899) Prec@1 82.000 (84.385) Prec@5 99.000 (99.077) +2022-11-14 13:38:08,001 Epoch: [72][130/500] Time 0.030 (0.029) Data 0.001 (0.004) Loss 0.1047 (0.0910) Prec@1 83.000 (84.286) Prec@5 100.000 (99.143) +2022-11-14 13:38:08,384 Epoch: [72][140/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.1176 (0.0928) Prec@1 81.000 (84.067) Prec@5 97.000 (99.000) +2022-11-14 13:38:08,752 Epoch: [72][150/500] Time 0.046 (0.030) Data 0.002 (0.003) Loss 0.1377 (0.0956) Prec@1 74.000 (83.438) Prec@5 98.000 (98.938) +2022-11-14 13:38:09,133 Epoch: [72][160/500] Time 0.022 (0.030) Data 0.002 (0.003) Loss 0.0903 (0.0953) Prec@1 84.000 (83.471) Prec@5 99.000 (98.941) +2022-11-14 13:38:09,496 Epoch: [72][170/500] Time 0.025 (0.030) Data 0.002 (0.003) Loss 0.0478 (0.0926) Prec@1 93.000 (84.000) Prec@5 98.000 (98.889) +2022-11-14 13:38:09,899 Epoch: [72][180/500] Time 0.037 (0.030) Data 0.003 (0.003) Loss 0.0984 (0.0929) Prec@1 84.000 (84.000) Prec@5 98.000 (98.842) +2022-11-14 13:38:10,284 Epoch: [72][190/500] Time 0.029 (0.031) Data 0.003 (0.003) Loss 0.1000 (0.0933) Prec@1 85.000 (84.050) Prec@5 100.000 (98.900) +2022-11-14 13:38:10,677 Epoch: [72][200/500] Time 0.033 (0.031) Data 0.003 (0.003) Loss 0.0948 (0.0934) Prec@1 85.000 (84.095) Prec@5 100.000 (98.952) +2022-11-14 13:38:11,096 Epoch: [72][210/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.1070 (0.0940) Prec@1 80.000 (83.909) Prec@5 100.000 (99.000) +2022-11-14 13:38:11,631 Epoch: [72][220/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0757 (0.0932) Prec@1 88.000 (84.087) Prec@5 99.000 (99.000) +2022-11-14 13:38:12,227 Epoch: [72][230/500] Time 0.092 (0.033) Data 0.003 (0.003) Loss 0.1190 (0.0942) Prec@1 77.000 (83.792) Prec@5 96.000 (98.875) +2022-11-14 13:38:12,918 Epoch: [72][240/500] Time 0.069 (0.034) Data 0.002 (0.003) Loss 0.0806 (0.0937) Prec@1 88.000 (83.960) Prec@5 99.000 (98.880) +2022-11-14 13:38:13,622 Epoch: [72][250/500] Time 0.068 (0.035) Data 0.002 (0.003) Loss 0.0775 (0.0931) Prec@1 85.000 (84.000) Prec@5 99.000 (98.885) +2022-11-14 13:38:14,301 Epoch: [72][260/500] Time 0.074 (0.036) Data 0.002 (0.003) Loss 0.1158 (0.0939) Prec@1 80.000 (83.852) Prec@5 99.000 (98.889) +2022-11-14 13:38:14,956 Epoch: [72][270/500] Time 0.066 (0.037) Data 0.002 (0.003) Loss 0.0720 (0.0931) Prec@1 86.000 (83.929) Prec@5 99.000 (98.893) +2022-11-14 13:38:15,645 Epoch: [72][280/500] Time 0.062 (0.038) Data 0.002 (0.003) Loss 0.1238 (0.0942) Prec@1 79.000 (83.759) Prec@5 98.000 (98.862) +2022-11-14 13:38:16,302 Epoch: [72][290/500] Time 0.063 (0.038) Data 0.002 (0.003) Loss 0.0905 (0.0941) Prec@1 86.000 (83.833) Prec@5 96.000 (98.767) +2022-11-14 13:38:16,959 Epoch: [72][300/500] Time 0.067 (0.039) Data 0.002 (0.003) Loss 0.1074 (0.0945) Prec@1 79.000 (83.677) Prec@5 99.000 (98.774) +2022-11-14 13:38:17,635 Epoch: [72][310/500] Time 0.061 (0.040) Data 0.003 (0.003) Loss 0.0704 (0.0937) Prec@1 89.000 (83.844) Prec@5 100.000 (98.812) +2022-11-14 13:38:18,282 Epoch: [72][320/500] Time 0.067 (0.040) Data 0.002 (0.003) Loss 0.0862 (0.0935) Prec@1 86.000 (83.909) Prec@5 98.000 (98.788) +2022-11-14 13:38:18,971 Epoch: [72][330/500] Time 0.068 (0.041) Data 0.002 (0.003) Loss 0.0994 (0.0937) Prec@1 83.000 (83.882) Prec@5 97.000 (98.735) +2022-11-14 13:38:19,633 Epoch: [72][340/500] Time 0.068 (0.041) Data 0.002 (0.003) Loss 0.0795 (0.0933) Prec@1 87.000 (83.971) Prec@5 97.000 (98.686) +2022-11-14 13:38:20,306 Epoch: [72][350/500] Time 0.060 (0.042) Data 0.003 (0.003) Loss 0.0494 (0.0921) Prec@1 94.000 (84.250) Prec@5 100.000 (98.722) +2022-11-14 13:38:20,988 Epoch: [72][360/500] Time 0.066 (0.042) Data 0.003 (0.003) Loss 0.0911 (0.0920) Prec@1 86.000 (84.297) Prec@5 99.000 (98.730) +2022-11-14 13:38:21,649 Epoch: [72][370/500] Time 0.066 (0.043) Data 0.002 (0.003) Loss 0.0839 (0.0918) Prec@1 87.000 (84.368) Prec@5 100.000 (98.763) +2022-11-14 13:38:22,322 Epoch: [72][380/500] Time 0.073 (0.043) Data 0.002 (0.003) Loss 0.0859 (0.0917) Prec@1 84.000 (84.359) Prec@5 100.000 (98.795) +2022-11-14 13:38:22,982 Epoch: [72][390/500] Time 0.060 (0.044) Data 0.002 (0.003) Loss 0.0978 (0.0918) Prec@1 80.000 (84.250) Prec@5 100.000 (98.825) +2022-11-14 13:38:23,649 Epoch: [72][400/500] Time 0.075 (0.044) Data 0.002 (0.003) Loss 0.1043 (0.0921) Prec@1 81.000 (84.171) Prec@5 97.000 (98.780) +2022-11-14 13:38:24,314 Epoch: [72][410/500] Time 0.068 (0.045) Data 0.002 (0.003) Loss 0.0636 (0.0915) Prec@1 89.000 (84.286) Prec@5 98.000 (98.762) +2022-11-14 13:38:24,959 Epoch: [72][420/500] Time 0.062 (0.045) Data 0.003 (0.003) Loss 0.0821 (0.0912) Prec@1 85.000 (84.302) Prec@5 100.000 (98.791) +2022-11-14 13:38:25,596 Epoch: [72][430/500] Time 0.064 (0.045) Data 0.003 (0.003) Loss 0.1093 (0.0916) Prec@1 80.000 (84.205) Prec@5 97.000 (98.750) +2022-11-14 13:38:26,251 Epoch: [72][440/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0950 (0.0917) Prec@1 83.000 (84.178) Prec@5 99.000 (98.756) +2022-11-14 13:38:26,911 Epoch: [72][450/500] Time 0.067 (0.046) Data 0.003 (0.003) Loss 0.0976 (0.0918) Prec@1 84.000 (84.174) Prec@5 99.000 (98.761) +2022-11-14 13:38:27,541 Epoch: [72][460/500] Time 0.065 (0.046) Data 0.003 (0.003) Loss 0.1064 (0.0922) Prec@1 81.000 (84.106) Prec@5 100.000 (98.787) +2022-11-14 13:38:28,220 Epoch: [72][470/500] Time 0.060 (0.046) Data 0.003 (0.003) Loss 0.0876 (0.0921) Prec@1 85.000 (84.125) Prec@5 99.000 (98.792) +2022-11-14 13:38:28,881 Epoch: [72][480/500] Time 0.058 (0.046) Data 0.001 (0.003) Loss 0.0994 (0.0922) Prec@1 82.000 (84.082) Prec@5 97.000 (98.755) +2022-11-14 13:38:29,539 Epoch: [72][490/500] Time 0.061 (0.047) Data 0.003 (0.003) Loss 0.1156 (0.0927) Prec@1 78.000 (83.960) Prec@5 99.000 (98.760) +2022-11-14 13:38:30,115 Epoch: [72][499/500] Time 0.063 (0.047) Data 0.002 (0.003) Loss 0.1077 (0.0930) Prec@1 81.000 (83.902) Prec@5 95.000 (98.686) +2022-11-14 13:38:30,540 Test: [0/100] Model Time 0.018 (0.018) Loss Time 0.000 (0.000) Loss 0.0672 (0.0672) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 13:38:30,552 Test: [1/100] Model Time 0.009 (0.013) Loss Time 0.000 (0.000) Loss 0.0927 (0.0800) Prec@1 84.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:38:30,564 Test: [2/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.1119 (0.0906) Prec@1 80.000 (84.667) Prec@5 99.000 (99.000) +2022-11-14 13:38:30,582 Test: [3/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1057 (0.0944) Prec@1 81.000 (83.750) Prec@5 100.000 (99.250) +2022-11-14 13:38:30,593 Test: [4/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.1312 (0.1017) Prec@1 78.000 (82.600) Prec@5 98.000 (99.000) +2022-11-14 13:38:30,604 Test: [5/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0674 (0.0960) Prec@1 88.000 (83.500) Prec@5 100.000 (99.167) +2022-11-14 13:38:30,615 Test: [6/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1047 (0.0973) Prec@1 79.000 (82.857) Prec@5 100.000 (99.286) +2022-11-14 13:38:30,626 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1231 (0.1005) Prec@1 79.000 (82.375) Prec@5 98.000 (99.125) +2022-11-14 13:38:30,638 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1180 (0.1024) Prec@1 81.000 (82.222) Prec@5 99.000 (99.111) +2022-11-14 13:38:30,649 Test: [9/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0829 (0.1005) Prec@1 91.000 (83.100) Prec@5 98.000 (99.000) +2022-11-14 13:38:30,661 Test: [10/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1015 (0.1006) Prec@1 83.000 (83.091) Prec@5 99.000 (99.000) +2022-11-14 13:38:30,673 Test: [11/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0995 (0.1005) Prec@1 82.000 (83.000) Prec@5 98.000 (98.917) +2022-11-14 13:38:30,684 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0987) Prec@1 86.000 (83.231) Prec@5 100.000 (99.000) +2022-11-14 13:38:30,694 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0915 (0.0982) Prec@1 81.000 (83.071) Prec@5 100.000 (99.071) +2022-11-14 13:38:30,706 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0974) Prec@1 87.000 (83.333) Prec@5 99.000 (99.067) +2022-11-14 13:38:30,716 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.0979) Prec@1 84.000 (83.375) Prec@5 100.000 (99.125) +2022-11-14 13:38:30,727 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0967) Prec@1 85.000 (83.471) Prec@5 99.000 (99.118) +2022-11-14 13:38:30,739 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1205 (0.0981) Prec@1 80.000 (83.278) Prec@5 99.000 (99.111) +2022-11-14 13:38:30,751 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1118 (0.0988) Prec@1 81.000 (83.158) Prec@5 97.000 (99.000) +2022-11-14 13:38:30,764 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1159 (0.0996) Prec@1 75.000 (82.750) Prec@5 99.000 (99.000) +2022-11-14 13:38:30,776 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1237 (0.1008) Prec@1 78.000 (82.524) Prec@5 98.000 (98.952) +2022-11-14 13:38:30,788 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1343 (0.1023) Prec@1 78.000 (82.318) Prec@5 97.000 (98.864) +2022-11-14 13:38:30,799 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1222 (0.1032) Prec@1 78.000 (82.130) Prec@5 98.000 (98.826) +2022-11-14 13:38:30,810 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1011 (0.1031) Prec@1 82.000 (82.125) Prec@5 99.000 (98.833) +2022-11-14 13:38:30,822 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0987 (0.1029) Prec@1 85.000 (82.240) Prec@5 100.000 (98.880) +2022-11-14 13:38:30,833 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1149 (0.1034) Prec@1 83.000 (82.269) Prec@5 98.000 (98.846) +2022-11-14 13:38:30,845 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.1035) Prec@1 82.000 (82.259) Prec@5 99.000 (98.852) +2022-11-14 13:38:30,857 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0904 (0.1030) Prec@1 83.000 (82.286) Prec@5 99.000 (98.857) +2022-11-14 13:38:30,867 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1037 (0.1030) Prec@1 82.000 (82.276) Prec@5 99.000 (98.862) +2022-11-14 13:38:30,879 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1145 (0.1034) Prec@1 80.000 (82.200) Prec@5 97.000 (98.800) +2022-11-14 13:38:30,891 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1109 (0.1036) Prec@1 82.000 (82.194) Prec@5 100.000 (98.839) +2022-11-14 13:38:30,902 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1087 (0.1038) Prec@1 81.000 (82.156) Prec@5 99.000 (98.844) +2022-11-14 13:38:30,913 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1080 (0.1039) Prec@1 82.000 (82.152) Prec@5 98.000 (98.818) +2022-11-14 13:38:30,924 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1266 (0.1046) Prec@1 77.000 (82.000) Prec@5 98.000 (98.794) +2022-11-14 13:38:30,936 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1315 (0.1054) Prec@1 77.000 (81.857) Prec@5 100.000 (98.829) +2022-11-14 13:38:30,948 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.1051) Prec@1 85.000 (81.944) Prec@5 98.000 (98.806) +2022-11-14 13:38:30,959 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.1049) Prec@1 82.000 (81.946) Prec@5 98.000 (98.784) +2022-11-14 13:38:30,970 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.1053) Prec@1 77.000 (81.816) Prec@5 98.000 (98.763) +2022-11-14 13:38:30,983 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.1051) Prec@1 83.000 (81.846) Prec@5 98.000 (98.744) +2022-11-14 13:38:30,994 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.1048) Prec@1 84.000 (81.900) Prec@5 99.000 (98.750) +2022-11-14 13:38:31,006 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1257 (0.1053) Prec@1 78.000 (81.805) Prec@5 98.000 (98.732) +2022-11-14 13:38:31,019 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.1053) Prec@1 83.000 (81.833) Prec@5 99.000 (98.738) +2022-11-14 13:38:31,031 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.1048) Prec@1 87.000 (81.953) Prec@5 99.000 (98.744) +2022-11-14 13:38:31,044 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.1045) Prec@1 86.000 (82.045) Prec@5 97.000 (98.705) +2022-11-14 13:38:31,056 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.1045) Prec@1 81.000 (82.022) Prec@5 100.000 (98.733) +2022-11-14 13:38:31,069 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1371 (0.1052) Prec@1 75.000 (81.870) Prec@5 100.000 (98.761) +2022-11-14 13:38:31,081 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.1050) Prec@1 83.000 (81.894) Prec@5 99.000 (98.766) +2022-11-14 13:38:31,093 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.1046) Prec@1 84.000 (81.938) Prec@5 99.000 (98.771) +2022-11-14 13:38:31,105 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1040 (0.1046) Prec@1 80.000 (81.898) Prec@5 100.000 (98.796) +2022-11-14 13:38:31,118 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1493 (0.1055) Prec@1 78.000 (81.820) Prec@5 98.000 (98.780) +2022-11-14 13:38:31,131 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.1053) Prec@1 84.000 (81.863) Prec@5 100.000 (98.804) +2022-11-14 13:38:31,142 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.1052) Prec@1 80.000 (81.827) Prec@5 98.000 (98.788) +2022-11-14 13:38:31,155 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1069 (0.1052) Prec@1 82.000 (81.830) Prec@5 100.000 (98.811) +2022-11-14 13:38:31,167 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1116 (0.1054) Prec@1 80.000 (81.796) Prec@5 96.000 (98.759) +2022-11-14 13:38:31,179 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1165 (0.1056) Prec@1 82.000 (81.800) Prec@5 100.000 (98.782) +2022-11-14 13:38:31,190 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1111 (0.1057) Prec@1 81.000 (81.786) Prec@5 98.000 (98.768) +2022-11-14 13:38:31,203 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.1057) Prec@1 81.000 (81.772) Prec@5 98.000 (98.754) +2022-11-14 13:38:31,218 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.1054) Prec@1 86.000 (81.845) Prec@5 99.000 (98.759) +2022-11-14 13:38:31,233 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1204 (0.1057) Prec@1 77.000 (81.763) Prec@5 99.000 (98.763) +2022-11-14 13:38:31,245 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0962 (0.1055) Prec@1 82.000 (81.767) Prec@5 98.000 (98.750) +2022-11-14 13:38:31,258 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.1054) Prec@1 86.000 (81.836) Prec@5 99.000 (98.754) +2022-11-14 13:38:31,270 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0971 (0.1052) Prec@1 84.000 (81.871) Prec@5 98.000 (98.742) +2022-11-14 13:38:31,283 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.1049) Prec@1 84.000 (81.905) Prec@5 100.000 (98.762) +2022-11-14 13:38:31,295 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0877 (0.1046) Prec@1 85.000 (81.953) Prec@5 100.000 (98.781) +2022-11-14 13:38:31,306 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1173 (0.1048) Prec@1 82.000 (81.954) Prec@5 99.000 (98.785) +2022-11-14 13:38:31,317 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1355 (0.1053) Prec@1 74.000 (81.833) Prec@5 100.000 (98.803) +2022-11-14 13:38:31,329 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.1051) Prec@1 85.000 (81.881) Prec@5 99.000 (98.806) +2022-11-14 13:38:31,340 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1140 (0.1052) Prec@1 81.000 (81.868) Prec@5 99.000 (98.809) +2022-11-14 13:38:31,353 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1166 (0.1054) Prec@1 80.000 (81.841) Prec@5 98.000 (98.797) +2022-11-14 13:38:31,367 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1135 (0.1055) Prec@1 79.000 (81.800) Prec@5 97.000 (98.771) +2022-11-14 13:38:31,379 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0917 (0.1053) Prec@1 86.000 (81.859) Prec@5 98.000 (98.761) +2022-11-14 13:38:31,391 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1055 (0.1053) Prec@1 79.000 (81.819) Prec@5 98.000 (98.750) +2022-11-14 13:38:31,403 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0899 (0.1051) Prec@1 86.000 (81.877) Prec@5 99.000 (98.753) +2022-11-14 13:38:31,417 Test: [73/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.1050) Prec@1 84.000 (81.905) Prec@5 99.000 (98.757) +2022-11-14 13:38:31,430 Test: [74/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1469 (0.1056) Prec@1 74.000 (81.800) Prec@5 99.000 (98.760) +2022-11-14 13:38:31,441 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1017 (0.1055) Prec@1 85.000 (81.842) Prec@5 98.000 (98.750) +2022-11-14 13:38:31,453 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1202 (0.1057) Prec@1 79.000 (81.805) Prec@5 98.000 (98.740) +2022-11-14 13:38:31,467 Test: [77/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1031 (0.1057) Prec@1 84.000 (81.833) Prec@5 100.000 (98.756) +2022-11-14 13:38:31,480 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1129 (0.1058) Prec@1 84.000 (81.861) Prec@5 99.000 (98.759) +2022-11-14 13:38:31,491 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1085 (0.1058) Prec@1 82.000 (81.862) Prec@5 99.000 (98.763) +2022-11-14 13:38:31,502 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1030 (0.1058) Prec@1 83.000 (81.877) Prec@5 98.000 (98.753) +2022-11-14 13:38:31,516 Test: [81/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.1057) Prec@1 83.000 (81.890) Prec@5 99.000 (98.756) +2022-11-14 13:38:31,528 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.1056) Prec@1 88.000 (81.964) Prec@5 100.000 (98.771) +2022-11-14 13:38:31,540 Test: [83/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1197 (0.1057) Prec@1 79.000 (81.929) Prec@5 99.000 (98.774) +2022-11-14 13:38:31,551 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1302 (0.1060) Prec@1 74.000 (81.835) Prec@5 99.000 (98.776) +2022-11-14 13:38:31,565 Test: [85/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1152 (0.1061) Prec@1 81.000 (81.826) Prec@5 98.000 (98.767) +2022-11-14 13:38:31,578 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1073 (0.1062) Prec@1 77.000 (81.770) Prec@5 99.000 (98.770) +2022-11-14 13:38:31,590 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.1061) Prec@1 83.000 (81.784) Prec@5 99.000 (98.773) +2022-11-14 13:38:31,603 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.1061) Prec@1 81.000 (81.775) Prec@5 100.000 (98.787) +2022-11-14 13:38:31,616 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1147 (0.1062) Prec@1 81.000 (81.767) Prec@5 99.000 (98.789) +2022-11-14 13:38:31,628 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0967 (0.1061) Prec@1 83.000 (81.780) Prec@5 100.000 (98.802) +2022-11-14 13:38:31,641 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0631 (0.1056) Prec@1 89.000 (81.859) Prec@5 100.000 (98.815) +2022-11-14 13:38:31,651 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1097 (0.1057) Prec@1 80.000 (81.839) Prec@5 98.000 (98.806) +2022-11-14 13:38:31,663 Test: [93/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1204 (0.1058) Prec@1 81.000 (81.830) Prec@5 99.000 (98.809) +2022-11-14 13:38:31,675 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1240 (0.1060) Prec@1 81.000 (81.821) Prec@5 100.000 (98.821) +2022-11-14 13:38:31,687 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0936 (0.1059) Prec@1 82.000 (81.823) Prec@5 99.000 (98.823) +2022-11-14 13:38:31,698 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.1056) Prec@1 89.000 (81.897) Prec@5 100.000 (98.835) +2022-11-14 13:38:31,709 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1269 (0.1058) Prec@1 79.000 (81.867) Prec@5 97.000 (98.816) +2022-11-14 13:38:31,721 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1145 (0.1059) Prec@1 78.000 (81.828) Prec@5 100.000 (98.828) +2022-11-14 13:38:31,732 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.1057) Prec@1 86.000 (81.870) Prec@5 100.000 (98.840) +2022-11-14 13:38:31,816 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:38:32,183 Epoch: [73][0/500] Time 0.034 (0.034) Data 0.262 (0.262) Loss 0.1032 (0.1032) Prec@1 85.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:38:32,466 Epoch: [73][10/500] Time 0.025 (0.026) Data 0.002 (0.026) Loss 0.0912 (0.0972) Prec@1 83.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:38:32,852 Epoch: [73][20/500] Time 0.038 (0.030) Data 0.003 (0.014) Loss 0.1099 (0.1014) Prec@1 85.000 (84.333) Prec@5 100.000 (99.333) +2022-11-14 13:38:33,217 Epoch: [73][30/500] Time 0.030 (0.031) Data 0.002 (0.010) Loss 0.0778 (0.0955) Prec@1 87.000 (85.000) Prec@5 98.000 (99.000) +2022-11-14 13:38:33,583 Epoch: [73][40/500] Time 0.031 (0.031) Data 0.002 (0.008) Loss 0.0955 (0.0955) Prec@1 83.000 (84.600) Prec@5 100.000 (99.200) +2022-11-14 13:38:34,015 Epoch: [73][50/500] Time 0.046 (0.032) Data 0.002 (0.007) Loss 0.0927 (0.0950) Prec@1 85.000 (84.667) Prec@5 100.000 (99.333) +2022-11-14 13:38:34,453 Epoch: [73][60/500] Time 0.039 (0.033) Data 0.002 (0.006) Loss 0.0802 (0.0929) Prec@1 87.000 (85.000) Prec@5 99.000 (99.286) +2022-11-14 13:38:34,815 Epoch: [73][70/500] Time 0.029 (0.033) Data 0.002 (0.006) Loss 0.1137 (0.0955) Prec@1 83.000 (84.750) Prec@5 98.000 (99.125) +2022-11-14 13:38:35,224 Epoch: [73][80/500] Time 0.050 (0.034) Data 0.002 (0.005) Loss 0.0715 (0.0928) Prec@1 88.000 (85.111) Prec@5 99.000 (99.111) +2022-11-14 13:38:35,668 Epoch: [73][90/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0896 (0.0925) Prec@1 85.000 (85.100) Prec@5 100.000 (99.200) +2022-11-14 13:38:36,106 Epoch: [73][100/500] Time 0.045 (0.035) Data 0.002 (0.005) Loss 0.0905 (0.0923) Prec@1 84.000 (85.000) Prec@5 99.000 (99.182) +2022-11-14 13:38:36,555 Epoch: [73][110/500] Time 0.046 (0.035) Data 0.002 (0.004) Loss 0.0767 (0.0910) Prec@1 89.000 (85.333) Prec@5 100.000 (99.250) +2022-11-14 13:38:36,998 Epoch: [73][120/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0917 (0.0911) Prec@1 85.000 (85.308) Prec@5 100.000 (99.308) +2022-11-14 13:38:37,434 Epoch: [73][130/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.1134 (0.0927) Prec@1 81.000 (85.000) Prec@5 99.000 (99.286) +2022-11-14 13:38:37,891 Epoch: [73][140/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.0659 (0.0909) Prec@1 91.000 (85.400) Prec@5 99.000 (99.267) +2022-11-14 13:38:38,332 Epoch: [73][150/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0942 (0.0911) Prec@1 86.000 (85.438) Prec@5 99.000 (99.250) +2022-11-14 13:38:38,775 Epoch: [73][160/500] Time 0.049 (0.037) Data 0.002 (0.004) Loss 0.1017 (0.0917) Prec@1 82.000 (85.235) Prec@5 98.000 (99.176) +2022-11-14 13:38:39,202 Epoch: [73][170/500] Time 0.038 (0.037) Data 0.002 (0.004) Loss 0.1065 (0.0925) Prec@1 85.000 (85.222) Prec@5 100.000 (99.222) +2022-11-14 13:38:40,088 Epoch: [73][180/500] Time 0.098 (0.039) Data 0.003 (0.003) Loss 0.0767 (0.0917) Prec@1 86.000 (85.263) Prec@5 100.000 (99.263) +2022-11-14 13:38:41,023 Epoch: [73][190/500] Time 0.086 (0.041) Data 0.002 (0.003) Loss 0.1049 (0.0924) Prec@1 82.000 (85.100) Prec@5 99.000 (99.250) +2022-11-14 13:38:41,859 Epoch: [73][200/500] Time 0.077 (0.043) Data 0.002 (0.003) Loss 0.0863 (0.0921) Prec@1 84.000 (85.048) Prec@5 99.000 (99.238) +2022-11-14 13:38:42,689 Epoch: [73][210/500] Time 0.083 (0.044) Data 0.002 (0.003) Loss 0.1110 (0.0929) Prec@1 83.000 (84.955) Prec@5 99.000 (99.227) +2022-11-14 13:38:43,612 Epoch: [73][220/500] Time 0.078 (0.046) Data 0.002 (0.003) Loss 0.0800 (0.0924) Prec@1 86.000 (85.000) Prec@5 100.000 (99.261) +2022-11-14 13:38:44,558 Epoch: [73][230/500] Time 0.105 (0.048) Data 0.002 (0.003) Loss 0.0829 (0.0920) Prec@1 88.000 (85.125) Prec@5 97.000 (99.167) +2022-11-14 13:38:45,527 Epoch: [73][240/500] Time 0.085 (0.049) Data 0.003 (0.003) Loss 0.0862 (0.0918) Prec@1 85.000 (85.120) Prec@5 100.000 (99.200) +2022-11-14 13:38:46,301 Epoch: [73][250/500] Time 0.069 (0.050) Data 0.003 (0.003) Loss 0.0714 (0.0910) Prec@1 88.000 (85.231) Prec@5 99.000 (99.192) +2022-11-14 13:38:47,174 Epoch: [73][260/500] Time 0.061 (0.051) Data 0.003 (0.003) Loss 0.0663 (0.0901) Prec@1 88.000 (85.333) Prec@5 100.000 (99.222) +2022-11-14 13:38:47,565 Epoch: [73][270/500] Time 0.041 (0.051) Data 0.002 (0.003) Loss 0.1035 (0.0905) Prec@1 83.000 (85.250) Prec@5 99.000 (99.214) +2022-11-14 13:38:47,964 Epoch: [73][280/500] Time 0.040 (0.050) Data 0.003 (0.003) Loss 0.1003 (0.0909) Prec@1 83.000 (85.172) Prec@5 100.000 (99.241) +2022-11-14 13:38:48,391 Epoch: [73][290/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0779 (0.0904) Prec@1 86.000 (85.200) Prec@5 99.000 (99.233) +2022-11-14 13:38:48,779 Epoch: [73][300/500] Time 0.039 (0.049) Data 0.003 (0.003) Loss 0.0815 (0.0901) Prec@1 84.000 (85.161) Prec@5 100.000 (99.258) +2022-11-14 13:38:49,166 Epoch: [73][310/500] Time 0.036 (0.049) Data 0.002 (0.003) Loss 0.0884 (0.0901) Prec@1 85.000 (85.156) Prec@5 99.000 (99.250) +2022-11-14 13:38:49,564 Epoch: [73][320/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.1015 (0.0904) Prec@1 82.000 (85.061) Prec@5 98.000 (99.212) +2022-11-14 13:38:49,994 Epoch: [73][330/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0976 (0.0907) Prec@1 82.000 (84.971) Prec@5 99.000 (99.206) +2022-11-14 13:38:50,390 Epoch: [73][340/500] Time 0.039 (0.048) Data 0.002 (0.003) Loss 0.0831 (0.0904) Prec@1 85.000 (84.971) Prec@5 99.000 (99.200) +2022-11-14 13:38:50,788 Epoch: [73][350/500] Time 0.041 (0.047) Data 0.003 (0.003) Loss 0.0969 (0.0906) Prec@1 82.000 (84.889) Prec@5 98.000 (99.167) +2022-11-14 13:38:51,236 Epoch: [73][360/500] Time 0.033 (0.047) Data 0.002 (0.003) Loss 0.0779 (0.0903) Prec@1 88.000 (84.973) Prec@5 98.000 (99.135) +2022-11-14 13:38:51,634 Epoch: [73][370/500] Time 0.033 (0.047) Data 0.002 (0.003) Loss 0.1312 (0.0914) Prec@1 77.000 (84.763) Prec@5 100.000 (99.158) +2022-11-14 13:38:52,102 Epoch: [73][380/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.1122 (0.0919) Prec@1 80.000 (84.641) Prec@5 100.000 (99.179) +2022-11-14 13:38:52,511 Epoch: [73][390/500] Time 0.038 (0.046) Data 0.002 (0.003) Loss 0.0708 (0.0914) Prec@1 90.000 (84.775) Prec@5 100.000 (99.200) +2022-11-14 13:38:52,933 Epoch: [73][400/500] Time 0.036 (0.046) Data 0.003 (0.003) Loss 0.1033 (0.0917) Prec@1 84.000 (84.756) Prec@5 98.000 (99.171) +2022-11-14 13:38:53,341 Epoch: [73][410/500] Time 0.032 (0.046) Data 0.002 (0.003) Loss 0.0526 (0.0907) Prec@1 93.000 (84.952) Prec@5 99.000 (99.167) +2022-11-14 13:38:53,778 Epoch: [73][420/500] Time 0.030 (0.046) Data 0.002 (0.003) Loss 0.0936 (0.0908) Prec@1 81.000 (84.860) Prec@5 100.000 (99.186) +2022-11-14 13:38:54,197 Epoch: [73][430/500] Time 0.051 (0.046) Data 0.004 (0.003) Loss 0.0974 (0.0909) Prec@1 82.000 (84.795) Prec@5 99.000 (99.182) +2022-11-14 13:38:54,593 Epoch: [73][440/500] Time 0.036 (0.045) Data 0.002 (0.003) Loss 0.1103 (0.0914) Prec@1 80.000 (84.689) Prec@5 97.000 (99.133) +2022-11-14 13:38:55,000 Epoch: [73][450/500] Time 0.035 (0.045) Data 0.002 (0.003) Loss 0.0726 (0.0910) Prec@1 87.000 (84.739) Prec@5 99.000 (99.130) +2022-11-14 13:38:55,399 Epoch: [73][460/500] Time 0.040 (0.045) Data 0.003 (0.003) Loss 0.0871 (0.0909) Prec@1 87.000 (84.787) Prec@5 99.000 (99.128) +2022-11-14 13:38:55,840 Epoch: [73][470/500] Time 0.034 (0.045) Data 0.002 (0.003) Loss 0.1121 (0.0913) Prec@1 80.000 (84.688) Prec@5 99.000 (99.125) +2022-11-14 13:38:56,245 Epoch: [73][480/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0933 (0.0914) Prec@1 84.000 (84.673) Prec@5 97.000 (99.082) +2022-11-14 13:38:56,649 Epoch: [73][490/500] Time 0.034 (0.045) Data 0.002 (0.003) Loss 0.0907 (0.0913) Prec@1 84.000 (84.660) Prec@5 99.000 (99.080) +2022-11-14 13:38:57,024 Epoch: [73][499/500] Time 0.035 (0.044) Data 0.002 (0.003) Loss 0.0940 (0.0914) Prec@1 83.000 (84.627) Prec@5 100.000 (99.098) +2022-11-14 13:38:57,427 Test: [0/100] Model Time 0.022 (0.022) Loss Time 0.000 (0.000) Loss 0.1101 (0.1101) Prec@1 79.000 (79.000) Prec@5 100.000 (100.000) +2022-11-14 13:38:57,449 Test: [1/100] Model Time 0.017 (0.019) Loss Time 0.000 (0.000) Loss 0.0980 (0.1041) Prec@1 85.000 (82.000) Prec@5 98.000 (99.000) +2022-11-14 13:38:57,471 Test: [2/100] Model Time 0.019 (0.019) Loss Time 0.000 (0.000) Loss 0.1172 (0.1085) Prec@1 80.000 (81.333) Prec@5 99.000 (99.000) +2022-11-14 13:38:57,494 Test: [3/100] Model Time 0.015 (0.018) Loss Time 0.000 (0.000) Loss 0.1055 (0.1077) Prec@1 82.000 (81.500) Prec@5 98.000 (98.750) +2022-11-14 13:38:57,510 Test: [4/100] Model Time 0.014 (0.018) Loss Time 0.000 (0.000) Loss 0.1199 (0.1101) Prec@1 78.000 (80.800) Prec@5 96.000 (98.200) +2022-11-14 13:38:57,527 Test: [5/100] Model Time 0.015 (0.017) Loss Time 0.000 (0.000) Loss 0.0841 (0.1058) Prec@1 84.000 (81.333) Prec@5 99.000 (98.333) +2022-11-14 13:38:57,543 Test: [6/100] Model Time 0.014 (0.017) Loss Time 0.001 (0.000) Loss 0.1107 (0.1065) Prec@1 82.000 (81.429) Prec@5 99.000 (98.429) +2022-11-14 13:38:57,562 Test: [7/100] Model Time 0.013 (0.016) Loss Time 0.000 (0.000) Loss 0.1277 (0.1092) Prec@1 79.000 (81.125) Prec@5 97.000 (98.250) +2022-11-14 13:38:57,576 Test: [8/100] Model Time 0.011 (0.016) Loss Time 0.000 (0.000) Loss 0.1352 (0.1120) Prec@1 75.000 (80.444) Prec@5 99.000 (98.333) +2022-11-14 13:38:57,589 Test: [9/100] Model Time 0.011 (0.015) Loss Time 0.000 (0.000) Loss 0.0971 (0.1106) Prec@1 84.000 (80.800) Prec@5 99.000 (98.400) +2022-11-14 13:38:57,608 Test: [10/100] Model Time 0.016 (0.015) Loss Time 0.000 (0.000) Loss 0.1052 (0.1101) Prec@1 81.000 (80.818) Prec@5 96.000 (98.182) +2022-11-14 13:38:57,633 Test: [11/100] Model Time 0.021 (0.016) Loss Time 0.000 (0.000) Loss 0.1043 (0.1096) Prec@1 81.000 (80.833) Prec@5 97.000 (98.083) +2022-11-14 13:38:57,648 Test: [12/100] Model Time 0.011 (0.015) Loss Time 0.000 (0.000) Loss 0.1251 (0.1108) Prec@1 76.000 (80.462) Prec@5 98.000 (98.077) +2022-11-14 13:38:57,661 Test: [13/100] Model Time 0.010 (0.015) Loss Time 0.000 (0.000) Loss 0.1160 (0.1111) Prec@1 78.000 (80.286) Prec@5 98.000 (98.071) +2022-11-14 13:38:57,673 Test: [14/100] Model Time 0.010 (0.015) Loss Time 0.000 (0.000) Loss 0.1181 (0.1116) Prec@1 80.000 (80.267) Prec@5 99.000 (98.133) +2022-11-14 13:38:57,684 Test: [15/100] Model Time 0.008 (0.014) Loss Time 0.000 (0.000) Loss 0.1431 (0.1136) Prec@1 72.000 (79.750) Prec@5 99.000 (98.188) +2022-11-14 13:38:57,695 Test: [16/100] Model Time 0.008 (0.014) Loss Time 0.000 (0.000) Loss 0.0963 (0.1126) Prec@1 85.000 (80.059) Prec@5 98.000 (98.176) +2022-11-14 13:38:57,706 Test: [17/100] Model Time 0.009 (0.014) Loss Time 0.000 (0.000) Loss 0.1106 (0.1125) Prec@1 81.000 (80.111) Prec@5 99.000 (98.222) +2022-11-14 13:38:57,718 Test: [18/100] Model Time 0.008 (0.013) Loss Time 0.000 (0.000) Loss 0.1169 (0.1127) Prec@1 78.000 (80.000) Prec@5 99.000 (98.263) +2022-11-14 13:38:57,729 Test: [19/100] Model Time 0.009 (0.013) Loss Time 0.000 (0.000) Loss 0.1404 (0.1141) Prec@1 73.000 (79.650) Prec@5 98.000 (98.250) +2022-11-14 13:38:57,741 Test: [20/100] Model Time 0.008 (0.013) Loss Time 0.000 (0.000) Loss 0.1030 (0.1135) Prec@1 79.000 (79.619) Prec@5 99.000 (98.286) +2022-11-14 13:38:57,751 Test: [21/100] Model Time 0.008 (0.013) Loss Time 0.000 (0.000) Loss 0.1229 (0.1140) Prec@1 79.000 (79.591) Prec@5 97.000 (98.227) +2022-11-14 13:38:57,762 Test: [22/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.1396 (0.1151) Prec@1 76.000 (79.435) Prec@5 97.000 (98.174) +2022-11-14 13:38:57,775 Test: [23/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.1052 (0.1147) Prec@1 80.000 (79.458) Prec@5 99.000 (98.208) +2022-11-14 13:38:57,789 Test: [24/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.1321 (0.1154) Prec@1 77.000 (79.360) Prec@5 99.000 (98.240) +2022-11-14 13:38:57,801 Test: [25/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.1468 (0.1166) Prec@1 73.000 (79.115) Prec@5 96.000 (98.154) +2022-11-14 13:38:57,812 Test: [26/100] Model Time 0.007 (0.012) Loss Time 0.000 (0.000) Loss 0.1211 (0.1168) Prec@1 80.000 (79.148) Prec@5 99.000 (98.185) +2022-11-14 13:38:57,824 Test: [27/100] Model Time 0.007 (0.012) Loss Time 0.000 (0.000) Loss 0.1224 (0.1170) Prec@1 76.000 (79.036) Prec@5 98.000 (98.179) +2022-11-14 13:38:57,836 Test: [28/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.1180 (0.1170) Prec@1 78.000 (79.000) Prec@5 98.000 (98.172) +2022-11-14 13:38:57,848 Test: [29/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.1170 (0.1170) Prec@1 79.000 (79.000) Prec@5 97.000 (98.133) +2022-11-14 13:38:57,862 Test: [30/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.1341 (0.1175) Prec@1 77.000 (78.935) Prec@5 99.000 (98.161) +2022-11-14 13:38:57,876 Test: [31/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1199 (0.1176) Prec@1 78.000 (78.906) Prec@5 100.000 (98.219) +2022-11-14 13:38:57,892 Test: [32/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1293 (0.1180) Prec@1 78.000 (78.879) Prec@5 94.000 (98.091) +2022-11-14 13:38:57,905 Test: [33/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1516 (0.1190) Prec@1 77.000 (78.824) Prec@5 95.000 (98.000) +2022-11-14 13:38:57,916 Test: [34/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1202 (0.1190) Prec@1 80.000 (78.857) Prec@5 98.000 (98.000) +2022-11-14 13:38:57,929 Test: [35/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1352 (0.1194) Prec@1 77.000 (78.806) Prec@5 99.000 (98.028) +2022-11-14 13:38:57,943 Test: [36/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1469 (0.1202) Prec@1 76.000 (78.730) Prec@5 97.000 (98.000) +2022-11-14 13:38:57,956 Test: [37/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1266 (0.1204) Prec@1 78.000 (78.711) Prec@5 97.000 (97.974) +2022-11-14 13:38:57,968 Test: [38/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1000 (0.1198) Prec@1 83.000 (78.821) Prec@5 99.000 (98.000) +2022-11-14 13:38:57,981 Test: [39/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0898 (0.1191) Prec@1 86.000 (79.000) Prec@5 100.000 (98.050) +2022-11-14 13:38:57,993 Test: [40/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1168 (0.1190) Prec@1 78.000 (78.976) Prec@5 97.000 (98.024) +2022-11-14 13:38:58,007 Test: [41/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1063 (0.1187) Prec@1 82.000 (79.048) Prec@5 96.000 (97.976) +2022-11-14 13:38:58,021 Test: [42/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0952 (0.1182) Prec@1 84.000 (79.163) Prec@5 100.000 (98.023) +2022-11-14 13:38:58,035 Test: [43/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1112 (0.1180) Prec@1 80.000 (79.182) Prec@5 99.000 (98.045) +2022-11-14 13:38:58,049 Test: [44/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1270 (0.1182) Prec@1 77.000 (79.133) Prec@5 98.000 (98.044) +2022-11-14 13:38:58,063 Test: [45/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1364 (0.1186) Prec@1 78.000 (79.109) Prec@5 98.000 (98.043) +2022-11-14 13:38:58,076 Test: [46/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1052 (0.1183) Prec@1 82.000 (79.170) Prec@5 100.000 (98.085) +2022-11-14 13:38:58,094 Test: [47/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1150 (0.1183) Prec@1 81.000 (79.208) Prec@5 98.000 (98.083) +2022-11-14 13:38:58,110 Test: [48/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1206 (0.1183) Prec@1 78.000 (79.184) Prec@5 100.000 (98.122) +2022-11-14 13:38:58,128 Test: [49/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1392 (0.1187) Prec@1 78.000 (79.160) Prec@5 96.000 (98.080) +2022-11-14 13:38:58,145 Test: [50/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1132 (0.1186) Prec@1 77.000 (79.118) Prec@5 98.000 (98.078) +2022-11-14 13:38:58,161 Test: [51/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1325 (0.1189) Prec@1 75.000 (79.038) Prec@5 96.000 (98.038) +2022-11-14 13:38:58,179 Test: [52/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1109 (0.1187) Prec@1 81.000 (79.075) Prec@5 99.000 (98.057) +2022-11-14 13:38:58,195 Test: [53/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1101 (0.1186) Prec@1 79.000 (79.074) Prec@5 98.000 (98.056) +2022-11-14 13:38:58,210 Test: [54/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1093 (0.1184) Prec@1 77.000 (79.036) Prec@5 100.000 (98.091) +2022-11-14 13:38:58,225 Test: [55/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1256 (0.1185) Prec@1 78.000 (79.018) Prec@5 97.000 (98.071) +2022-11-14 13:38:58,241 Test: [56/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1375 (0.1189) Prec@1 77.000 (78.982) Prec@5 99.000 (98.088) +2022-11-14 13:38:58,255 Test: [57/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0920 (0.1184) Prec@1 80.000 (79.000) Prec@5 99.000 (98.103) +2022-11-14 13:38:58,268 Test: [58/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1596 (0.1191) Prec@1 70.000 (78.847) Prec@5 99.000 (98.119) +2022-11-14 13:38:58,280 Test: [59/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1233 (0.1192) Prec@1 77.000 (78.817) Prec@5 97.000 (98.100) +2022-11-14 13:38:58,291 Test: [60/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1191 (0.1192) Prec@1 78.000 (78.803) Prec@5 99.000 (98.115) +2022-11-14 13:38:58,305 Test: [61/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0961 (0.1188) Prec@1 83.000 (78.871) Prec@5 99.000 (98.129) +2022-11-14 13:38:58,316 Test: [62/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1192 (0.1188) Prec@1 78.000 (78.857) Prec@5 99.000 (98.143) +2022-11-14 13:38:58,328 Test: [63/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0971 (0.1185) Prec@1 84.000 (78.938) Prec@5 98.000 (98.141) +2022-11-14 13:38:58,340 Test: [64/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1408 (0.1188) Prec@1 76.000 (78.892) Prec@5 94.000 (98.077) +2022-11-14 13:38:58,352 Test: [65/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1006 (0.1185) Prec@1 80.000 (78.909) Prec@5 98.000 (98.076) +2022-11-14 13:38:58,364 Test: [66/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1245 (0.1186) Prec@1 78.000 (78.896) Prec@5 98.000 (98.075) +2022-11-14 13:38:58,377 Test: [67/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1119 (0.1185) Prec@1 81.000 (78.926) Prec@5 98.000 (98.074) +2022-11-14 13:38:58,389 Test: [68/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1391 (0.1188) Prec@1 75.000 (78.870) Prec@5 97.000 (98.058) +2022-11-14 13:38:58,402 Test: [69/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1488 (0.1193) Prec@1 74.000 (78.800) Prec@5 97.000 (98.043) +2022-11-14 13:38:58,415 Test: [70/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1194 (0.1193) Prec@1 79.000 (78.803) Prec@5 98.000 (98.042) +2022-11-14 13:38:58,428 Test: [71/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1110 (0.1191) Prec@1 78.000 (78.792) Prec@5 99.000 (98.056) +2022-11-14 13:38:58,441 Test: [72/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1153 (0.1191) Prec@1 81.000 (78.822) Prec@5 99.000 (98.068) +2022-11-14 13:38:58,455 Test: [73/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1090 (0.1189) Prec@1 82.000 (78.865) Prec@5 99.000 (98.081) +2022-11-14 13:38:58,471 Test: [74/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1276 (0.1191) Prec@1 79.000 (78.867) Prec@5 95.000 (98.040) +2022-11-14 13:38:58,485 Test: [75/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1000 (0.1188) Prec@1 83.000 (78.921) Prec@5 98.000 (98.039) +2022-11-14 13:38:58,496 Test: [76/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1071 (0.1187) Prec@1 82.000 (78.961) Prec@5 98.000 (98.039) +2022-11-14 13:38:58,508 Test: [77/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1244 (0.1187) Prec@1 79.000 (78.962) Prec@5 98.000 (98.038) +2022-11-14 13:38:58,520 Test: [78/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1132 (0.1187) Prec@1 82.000 (79.000) Prec@5 100.000 (98.063) +2022-11-14 13:38:58,534 Test: [79/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1077 (0.1185) Prec@1 79.000 (79.000) Prec@5 96.000 (98.037) +2022-11-14 13:38:58,546 Test: [80/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0958 (0.1182) Prec@1 84.000 (79.062) Prec@5 98.000 (98.037) +2022-11-14 13:38:58,559 Test: [81/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1186 (0.1183) Prec@1 75.000 (79.012) Prec@5 98.000 (98.037) +2022-11-14 13:38:58,571 Test: [82/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0942 (0.1180) Prec@1 84.000 (79.072) Prec@5 100.000 (98.060) +2022-11-14 13:38:58,583 Test: [83/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1254 (0.1181) Prec@1 80.000 (79.083) Prec@5 98.000 (98.060) +2022-11-14 13:38:58,597 Test: [84/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1024 (0.1179) Prec@1 79.000 (79.082) Prec@5 99.000 (98.071) +2022-11-14 13:38:58,611 Test: [85/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1229 (0.1179) Prec@1 75.000 (79.035) Prec@5 98.000 (98.070) +2022-11-14 13:38:58,625 Test: [86/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1312 (0.1181) Prec@1 78.000 (79.023) Prec@5 97.000 (98.057) +2022-11-14 13:38:58,638 Test: [87/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0986 (0.1179) Prec@1 85.000 (79.091) Prec@5 97.000 (98.045) +2022-11-14 13:38:58,653 Test: [88/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1474 (0.1182) Prec@1 77.000 (79.067) Prec@5 95.000 (98.011) +2022-11-14 13:38:58,666 Test: [89/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1246 (0.1183) Prec@1 75.000 (79.022) Prec@5 98.000 (98.011) +2022-11-14 13:38:58,680 Test: [90/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1109 (0.1182) Prec@1 84.000 (79.077) Prec@5 99.000 (98.022) +2022-11-14 13:38:58,694 Test: [91/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0708 (0.1177) Prec@1 86.000 (79.152) Prec@5 100.000 (98.043) +2022-11-14 13:38:58,707 Test: [92/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1146 (0.1176) Prec@1 80.000 (79.161) Prec@5 100.000 (98.065) +2022-11-14 13:38:58,723 Test: [93/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1109 (0.1176) Prec@1 82.000 (79.191) Prec@5 99.000 (98.074) +2022-11-14 13:38:58,738 Test: [94/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1276 (0.1177) Prec@1 78.000 (79.179) Prec@5 97.000 (98.063) +2022-11-14 13:38:58,755 Test: [95/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1077 (0.1176) Prec@1 82.000 (79.208) Prec@5 97.000 (98.052) +2022-11-14 13:38:58,770 Test: [96/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1060 (0.1174) Prec@1 82.000 (79.237) Prec@5 100.000 (98.072) +2022-11-14 13:38:58,784 Test: [97/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1365 (0.1176) Prec@1 77.000 (79.214) Prec@5 99.000 (98.082) +2022-11-14 13:38:58,796 Test: [98/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1106 (0.1176) Prec@1 82.000 (79.242) Prec@5 97.000 (98.071) +2022-11-14 13:38:58,810 Test: [99/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1441 (0.1178) Prec@1 74.000 (79.190) Prec@5 96.000 (98.050) +2022-11-14 13:38:58,872 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:38:59,298 Epoch: [74][0/500] Time 0.045 (0.045) Data 0.308 (0.308) Loss 0.0654 (0.0654) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:38:59,607 Epoch: [74][10/500] Time 0.024 (0.029) Data 0.002 (0.030) Loss 0.0974 (0.0814) Prec@1 81.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 13:38:59,934 Epoch: [74][20/500] Time 0.033 (0.029) Data 0.003 (0.017) Loss 0.0802 (0.0810) Prec@1 87.000 (86.000) Prec@5 99.000 (99.667) +2022-11-14 13:39:00,339 Epoch: [74][30/500] Time 0.043 (0.031) Data 0.003 (0.012) Loss 0.0933 (0.0841) Prec@1 84.000 (85.500) Prec@5 100.000 (99.750) +2022-11-14 13:39:00,768 Epoch: [74][40/500] Time 0.037 (0.033) Data 0.002 (0.010) Loss 0.0983 (0.0869) Prec@1 82.000 (84.800) Prec@5 97.000 (99.200) +2022-11-14 13:39:01,176 Epoch: [74][50/500] Time 0.040 (0.033) Data 0.003 (0.008) Loss 0.0820 (0.0861) Prec@1 87.000 (85.167) Prec@5 99.000 (99.167) +2022-11-14 13:39:01,587 Epoch: [74][60/500] Time 0.036 (0.034) Data 0.002 (0.007) Loss 0.0899 (0.0867) Prec@1 85.000 (85.143) Prec@5 99.000 (99.143) +2022-11-14 13:39:02,002 Epoch: [74][70/500] Time 0.036 (0.035) Data 0.002 (0.007) Loss 0.0969 (0.0879) Prec@1 85.000 (85.125) Prec@5 99.000 (99.125) +2022-11-14 13:39:02,440 Epoch: [74][80/500] Time 0.033 (0.035) Data 0.002 (0.006) Loss 0.0925 (0.0884) Prec@1 83.000 (84.889) Prec@5 96.000 (98.778) +2022-11-14 13:39:02,847 Epoch: [74][90/500] Time 0.036 (0.035) Data 0.003 (0.006) Loss 0.1199 (0.0916) Prec@1 77.000 (84.100) Prec@5 99.000 (98.800) +2022-11-14 13:39:03,256 Epoch: [74][100/500] Time 0.044 (0.035) Data 0.003 (0.005) Loss 0.1151 (0.0937) Prec@1 81.000 (83.818) Prec@5 97.000 (98.636) +2022-11-14 13:39:03,667 Epoch: [74][110/500] Time 0.039 (0.035) Data 0.002 (0.005) Loss 0.0733 (0.0920) Prec@1 87.000 (84.083) Prec@5 100.000 (98.750) +2022-11-14 13:39:04,098 Epoch: [74][120/500] Time 0.037 (0.036) Data 0.002 (0.005) Loss 0.1041 (0.0930) Prec@1 85.000 (84.154) Prec@5 97.000 (98.615) +2022-11-14 13:39:04,510 Epoch: [74][130/500] Time 0.038 (0.036) Data 0.002 (0.005) Loss 0.1070 (0.0940) Prec@1 83.000 (84.071) Prec@5 99.000 (98.643) +2022-11-14 13:39:04,903 Epoch: [74][140/500] Time 0.033 (0.036) Data 0.003 (0.005) Loss 0.0913 (0.0938) Prec@1 82.000 (83.933) Prec@5 99.000 (98.667) +2022-11-14 13:39:05,310 Epoch: [74][150/500] Time 0.033 (0.036) Data 0.002 (0.004) Loss 0.1047 (0.0945) Prec@1 82.000 (83.812) Prec@5 97.000 (98.562) +2022-11-14 13:39:05,749 Epoch: [74][160/500] Time 0.036 (0.036) Data 0.002 (0.004) Loss 0.1046 (0.0951) Prec@1 81.000 (83.647) Prec@5 99.000 (98.588) +2022-11-14 13:39:06,157 Epoch: [74][170/500] Time 0.033 (0.036) Data 0.002 (0.004) Loss 0.1074 (0.0957) Prec@1 81.000 (83.500) Prec@5 99.000 (98.611) +2022-11-14 13:39:06,565 Epoch: [74][180/500] Time 0.039 (0.036) Data 0.002 (0.004) Loss 0.0855 (0.0952) Prec@1 82.000 (83.421) Prec@5 100.000 (98.684) +2022-11-14 13:39:06,969 Epoch: [74][190/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0790 (0.0944) Prec@1 86.000 (83.550) Prec@5 98.000 (98.650) +2022-11-14 13:39:07,396 Epoch: [74][200/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0791 (0.0937) Prec@1 89.000 (83.810) Prec@5 99.000 (98.667) +2022-11-14 13:39:07,801 Epoch: [74][210/500] Time 0.034 (0.036) Data 0.002 (0.004) Loss 0.0705 (0.0926) Prec@1 85.000 (83.864) Prec@5 100.000 (98.727) +2022-11-14 13:39:08,207 Epoch: [74][220/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0718 (0.0917) Prec@1 88.000 (84.043) Prec@5 99.000 (98.739) +2022-11-14 13:39:08,622 Epoch: [74][230/500] Time 0.038 (0.036) Data 0.002 (0.004) Loss 0.0837 (0.0914) Prec@1 87.000 (84.167) Prec@5 99.000 (98.750) +2022-11-14 13:39:09,060 Epoch: [74][240/500] Time 0.038 (0.036) Data 0.002 (0.004) Loss 0.1133 (0.0923) Prec@1 81.000 (84.040) Prec@5 99.000 (98.760) +2022-11-14 13:39:09,478 Epoch: [74][250/500] Time 0.041 (0.036) Data 0.003 (0.004) Loss 0.0987 (0.0925) Prec@1 81.000 (83.923) Prec@5 100.000 (98.808) +2022-11-14 13:39:09,890 Epoch: [74][260/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.1153 (0.0933) Prec@1 79.000 (83.741) Prec@5 98.000 (98.778) +2022-11-14 13:39:10,302 Epoch: [74][270/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.1164 (0.0942) Prec@1 81.000 (83.643) Prec@5 99.000 (98.786) +2022-11-14 13:39:10,737 Epoch: [74][280/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0935 (0.0941) Prec@1 84.000 (83.655) Prec@5 98.000 (98.759) +2022-11-14 13:39:11,148 Epoch: [74][290/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.1157 (0.0949) Prec@1 78.000 (83.467) Prec@5 100.000 (98.800) +2022-11-14 13:39:11,557 Epoch: [74][300/500] Time 0.035 (0.036) Data 0.003 (0.003) Loss 0.0742 (0.0942) Prec@1 87.000 (83.581) Prec@5 98.000 (98.774) +2022-11-14 13:39:12,000 Epoch: [74][310/500] Time 0.045 (0.036) Data 0.003 (0.003) Loss 0.1113 (0.0947) Prec@1 78.000 (83.406) Prec@5 98.000 (98.750) +2022-11-14 13:39:12,424 Epoch: [74][320/500] Time 0.037 (0.036) Data 0.003 (0.003) Loss 0.1113 (0.0952) Prec@1 81.000 (83.333) Prec@5 97.000 (98.697) +2022-11-14 13:39:12,830 Epoch: [74][330/500] Time 0.033 (0.036) Data 0.003 (0.003) Loss 0.1092 (0.0956) Prec@1 80.000 (83.235) Prec@5 99.000 (98.706) +2022-11-14 13:39:13,250 Epoch: [74][340/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0848 (0.0953) Prec@1 86.000 (83.314) Prec@5 98.000 (98.686) +2022-11-14 13:39:13,688 Epoch: [74][350/500] Time 0.051 (0.037) Data 0.002 (0.003) Loss 0.1091 (0.0957) Prec@1 82.000 (83.278) Prec@5 97.000 (98.639) +2022-11-14 13:39:14,098 Epoch: [74][360/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.1445 (0.0970) Prec@1 75.000 (83.054) Prec@5 99.000 (98.649) +2022-11-14 13:39:14,505 Epoch: [74][370/500] Time 0.043 (0.037) Data 0.003 (0.003) Loss 0.0882 (0.0968) Prec@1 86.000 (83.132) Prec@5 100.000 (98.684) +2022-11-14 13:39:15,042 Epoch: [74][380/500] Time 0.062 (0.037) Data 0.002 (0.003) Loss 0.1268 (0.0976) Prec@1 78.000 (83.000) Prec@5 97.000 (98.641) +2022-11-14 13:39:15,788 Epoch: [74][390/500] Time 0.087 (0.038) Data 0.002 (0.003) Loss 0.0975 (0.0976) Prec@1 84.000 (83.025) Prec@5 96.000 (98.575) +2022-11-14 13:39:16,436 Epoch: [74][400/500] Time 0.066 (0.038) Data 0.003 (0.003) Loss 0.1026 (0.0977) Prec@1 83.000 (83.024) Prec@5 99.000 (98.585) +2022-11-14 13:39:17,104 Epoch: [74][410/500] Time 0.064 (0.039) Data 0.002 (0.003) Loss 0.0736 (0.0971) Prec@1 89.000 (83.167) Prec@5 99.000 (98.595) +2022-11-14 13:39:17,853 Epoch: [74][420/500] Time 0.058 (0.039) Data 0.002 (0.003) Loss 0.1207 (0.0977) Prec@1 81.000 (83.116) Prec@5 97.000 (98.558) +2022-11-14 13:39:18,540 Epoch: [74][430/500] Time 0.069 (0.040) Data 0.002 (0.003) Loss 0.0856 (0.0974) Prec@1 85.000 (83.159) Prec@5 98.000 (98.545) +2022-11-14 13:39:19,305 Epoch: [74][440/500] Time 0.088 (0.041) Data 0.002 (0.003) Loss 0.1173 (0.0978) Prec@1 77.000 (83.022) Prec@5 96.000 (98.489) +2022-11-14 13:39:19,984 Epoch: [74][450/500] Time 0.070 (0.041) Data 0.002 (0.003) Loss 0.0934 (0.0977) Prec@1 84.000 (83.043) Prec@5 100.000 (98.522) +2022-11-14 13:39:20,659 Epoch: [74][460/500] Time 0.060 (0.041) Data 0.003 (0.003) Loss 0.1073 (0.0979) Prec@1 80.000 (82.979) Prec@5 96.000 (98.468) +2022-11-14 13:39:21,527 Epoch: [74][470/500] Time 0.071 (0.042) Data 0.002 (0.003) Loss 0.0894 (0.0978) Prec@1 82.000 (82.958) Prec@5 100.000 (98.500) +2022-11-14 13:39:22,367 Epoch: [74][480/500] Time 0.060 (0.043) Data 0.002 (0.003) Loss 0.1062 (0.0979) Prec@1 78.000 (82.857) Prec@5 99.000 (98.510) +2022-11-14 13:39:23,206 Epoch: [74][490/500] Time 0.119 (0.043) Data 0.002 (0.003) Loss 0.1050 (0.0981) Prec@1 85.000 (82.900) Prec@5 98.000 (98.500) +2022-11-14 13:39:23,726 Epoch: [74][499/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.1176 (0.0985) Prec@1 80.000 (82.843) Prec@5 98.000 (98.490) +2022-11-14 13:39:24,102 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0876 (0.0876) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:39:24,112 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0961 (0.0918) Prec@1 84.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 13:39:24,123 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1241 (0.1026) Prec@1 77.000 (82.667) Prec@5 100.000 (100.000) +2022-11-14 13:39:24,140 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1378 (0.1114) Prec@1 76.000 (81.000) Prec@5 100.000 (100.000) +2022-11-14 13:39:24,149 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1283 (0.1148) Prec@1 78.000 (80.400) Prec@5 97.000 (99.400) +2022-11-14 13:39:24,161 Test: [5/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0893 (0.1105) Prec@1 84.000 (81.000) Prec@5 99.000 (99.333) +2022-11-14 13:39:24,171 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1039 (0.1096) Prec@1 82.000 (81.143) Prec@5 99.000 (99.286) +2022-11-14 13:39:24,181 Test: [7/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1482 (0.1144) Prec@1 72.000 (80.000) Prec@5 99.000 (99.250) +2022-11-14 13:39:24,192 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1350 (0.1167) Prec@1 79.000 (79.889) Prec@5 99.000 (99.222) +2022-11-14 13:39:24,203 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0999 (0.1150) Prec@1 80.000 (79.900) Prec@5 98.000 (99.100) +2022-11-14 13:39:24,215 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.1139) Prec@1 83.000 (80.182) Prec@5 100.000 (99.182) +2022-11-14 13:39:24,226 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1203 (0.1144) Prec@1 81.000 (80.250) Prec@5 97.000 (99.000) +2022-11-14 13:39:24,238 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1084 (0.1139) Prec@1 78.000 (80.077) Prec@5 100.000 (99.077) +2022-11-14 13:39:24,251 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.1128) Prec@1 84.000 (80.357) Prec@5 97.000 (98.929) +2022-11-14 13:39:24,264 Test: [14/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1264 (0.1137) Prec@1 74.000 (79.933) Prec@5 99.000 (98.933) +2022-11-14 13:39:24,276 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1018 (0.1130) Prec@1 83.000 (80.125) Prec@5 98.000 (98.875) +2022-11-14 13:39:24,288 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0836 (0.1112) Prec@1 86.000 (80.471) Prec@5 98.000 (98.824) +2022-11-14 13:39:24,298 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1316 (0.1124) Prec@1 79.000 (80.389) Prec@5 98.000 (98.778) +2022-11-14 13:39:24,309 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1197 (0.1128) Prec@1 80.000 (80.368) Prec@5 98.000 (98.737) +2022-11-14 13:39:24,319 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1410 (0.1142) Prec@1 77.000 (80.200) Prec@5 95.000 (98.550) +2022-11-14 13:39:24,329 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1008 (0.1135) Prec@1 81.000 (80.238) Prec@5 98.000 (98.524) +2022-11-14 13:39:24,340 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1387 (0.1147) Prec@1 75.000 (80.000) Prec@5 98.000 (98.500) +2022-11-14 13:39:24,351 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1367 (0.1156) Prec@1 76.000 (79.826) Prec@5 97.000 (98.435) +2022-11-14 13:39:24,360 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1320 (0.1163) Prec@1 76.000 (79.667) Prec@5 99.000 (98.458) +2022-11-14 13:39:24,370 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1444 (0.1174) Prec@1 75.000 (79.480) Prec@5 99.000 (98.480) +2022-11-14 13:39:24,382 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1420 (0.1184) Prec@1 77.000 (79.385) Prec@5 97.000 (98.423) +2022-11-14 13:39:24,397 Test: [26/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1129 (0.1182) Prec@1 82.000 (79.481) Prec@5 100.000 (98.481) +2022-11-14 13:39:24,412 Test: [27/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1163 (0.1181) Prec@1 80.000 (79.500) Prec@5 99.000 (98.500) +2022-11-14 13:39:24,426 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1159 (0.1180) Prec@1 79.000 (79.483) Prec@5 97.000 (98.448) +2022-11-14 13:39:24,435 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1122 (0.1178) Prec@1 80.000 (79.500) Prec@5 99.000 (98.467) +2022-11-14 13:39:24,445 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1168 (0.1178) Prec@1 79.000 (79.484) Prec@5 97.000 (98.419) +2022-11-14 13:39:24,455 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.1173) Prec@1 83.000 (79.594) Prec@5 98.000 (98.406) +2022-11-14 13:39:24,469 Test: [32/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1232 (0.1175) Prec@1 80.000 (79.606) Prec@5 99.000 (98.424) +2022-11-14 13:39:24,481 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1444 (0.1183) Prec@1 74.000 (79.441) Prec@5 96.000 (98.353) +2022-11-14 13:39:24,491 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1296 (0.1186) Prec@1 75.000 (79.314) Prec@5 97.000 (98.314) +2022-11-14 13:39:24,501 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1150 (0.1185) Prec@1 80.000 (79.333) Prec@5 98.000 (98.306) +2022-11-14 13:39:24,512 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1160 (0.1185) Prec@1 78.000 (79.297) Prec@5 100.000 (98.351) +2022-11-14 13:39:24,522 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1334 (0.1189) Prec@1 76.000 (79.211) Prec@5 96.000 (98.289) +2022-11-14 13:39:24,533 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.1185) Prec@1 82.000 (79.282) Prec@5 98.000 (98.282) +2022-11-14 13:39:24,547 Test: [39/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.1178) Prec@1 88.000 (79.500) Prec@5 99.000 (98.300) +2022-11-14 13:39:24,559 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1295 (0.1181) Prec@1 77.000 (79.439) Prec@5 96.000 (98.244) +2022-11-14 13:39:24,570 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1030 (0.1177) Prec@1 81.000 (79.476) Prec@5 97.000 (98.214) +2022-11-14 13:39:24,581 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.1168) Prec@1 87.000 (79.651) Prec@5 98.000 (98.209) +2022-11-14 13:39:24,592 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.1161) Prec@1 83.000 (79.727) Prec@5 97.000 (98.182) +2022-11-14 13:39:24,602 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1185 (0.1162) Prec@1 80.000 (79.733) Prec@5 99.000 (98.200) +2022-11-14 13:39:24,613 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1427 (0.1168) Prec@1 74.000 (79.609) Prec@5 98.000 (98.196) +2022-11-14 13:39:24,623 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1072 (0.1166) Prec@1 79.000 (79.596) Prec@5 99.000 (98.213) +2022-11-14 13:39:24,634 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1223 (0.1167) Prec@1 81.000 (79.625) Prec@5 99.000 (98.229) +2022-11-14 13:39:24,643 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.1164) Prec@1 83.000 (79.694) Prec@5 98.000 (98.224) +2022-11-14 13:39:24,653 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1215 (0.1165) Prec@1 81.000 (79.720) Prec@5 100.000 (98.260) +2022-11-14 13:39:24,663 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1104 (0.1164) Prec@1 79.000 (79.706) Prec@5 98.000 (98.255) +2022-11-14 13:39:24,674 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1335 (0.1167) Prec@1 76.000 (79.635) Prec@5 96.000 (98.212) +2022-11-14 13:39:24,685 Test: [52/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.1164) Prec@1 85.000 (79.736) Prec@5 99.000 (98.226) +2022-11-14 13:39:24,695 Test: [53/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1119 (0.1164) Prec@1 84.000 (79.815) Prec@5 97.000 (98.204) +2022-11-14 13:39:24,705 Test: [54/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.1161) Prec@1 84.000 (79.891) Prec@5 100.000 (98.236) +2022-11-14 13:39:24,714 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1175 (0.1161) Prec@1 82.000 (79.929) Prec@5 98.000 (98.232) +2022-11-14 13:39:24,724 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1049 (0.1159) Prec@1 82.000 (79.965) Prec@5 99.000 (98.246) +2022-11-14 13:39:24,735 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0919 (0.1155) Prec@1 82.000 (80.000) Prec@5 100.000 (98.276) +2022-11-14 13:39:24,745 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1455 (0.1160) Prec@1 73.000 (79.881) Prec@5 99.000 (98.288) +2022-11-14 13:39:24,757 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1019 (0.1158) Prec@1 80.000 (79.883) Prec@5 99.000 (98.300) +2022-11-14 13:39:24,772 Test: [60/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.1155) Prec@1 81.000 (79.902) Prec@5 100.000 (98.328) +2022-11-14 13:39:24,786 Test: [61/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1087 (0.1154) Prec@1 80.000 (79.903) Prec@5 100.000 (98.355) +2022-11-14 13:39:24,798 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1364 (0.1158) Prec@1 75.000 (79.825) Prec@5 98.000 (98.349) +2022-11-14 13:39:24,810 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1033 (0.1156) Prec@1 80.000 (79.828) Prec@5 99.000 (98.359) +2022-11-14 13:39:24,821 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1259 (0.1157) Prec@1 75.000 (79.754) Prec@5 99.000 (98.369) +2022-11-14 13:39:24,833 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1368 (0.1160) Prec@1 75.000 (79.682) Prec@5 98.000 (98.364) +2022-11-14 13:39:24,847 Test: [66/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.1156) Prec@1 85.000 (79.761) Prec@5 100.000 (98.388) +2022-11-14 13:39:24,859 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1329 (0.1159) Prec@1 77.000 (79.721) Prec@5 98.000 (98.382) +2022-11-14 13:39:24,870 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1121 (0.1158) Prec@1 81.000 (79.739) Prec@5 100.000 (98.406) +2022-11-14 13:39:24,881 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.1155) Prec@1 84.000 (79.800) Prec@5 100.000 (98.429) +2022-11-14 13:39:24,894 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1145 (0.1155) Prec@1 77.000 (79.761) Prec@5 99.000 (98.437) +2022-11-14 13:39:24,907 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.1150) Prec@1 87.000 (79.861) Prec@5 100.000 (98.458) +2022-11-14 13:39:24,922 Test: [72/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.1144) Prec@1 89.000 (79.986) Prec@5 98.000 (98.452) +2022-11-14 13:39:24,937 Test: [73/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.1140) Prec@1 87.000 (80.081) Prec@5 99.000 (98.459) +2022-11-14 13:39:24,951 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1432 (0.1144) Prec@1 75.000 (80.013) Prec@5 97.000 (98.440) +2022-11-14 13:39:24,965 Test: [75/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1104 (0.1143) Prec@1 82.000 (80.039) Prec@5 96.000 (98.408) +2022-11-14 13:39:24,977 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1046 (0.1142) Prec@1 84.000 (80.091) Prec@5 98.000 (98.403) +2022-11-14 13:39:24,992 Test: [77/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.1140) Prec@1 84.000 (80.141) Prec@5 99.000 (98.410) +2022-11-14 13:39:25,004 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1269 (0.1142) Prec@1 76.000 (80.089) Prec@5 96.000 (98.380) +2022-11-14 13:39:25,018 Test: [79/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1340 (0.1144) Prec@1 75.000 (80.025) Prec@5 98.000 (98.375) +2022-11-14 13:39:25,032 Test: [80/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1221 (0.1145) Prec@1 77.000 (79.988) Prec@5 95.000 (98.333) +2022-11-14 13:39:25,044 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1056 (0.1144) Prec@1 81.000 (80.000) Prec@5 98.000 (98.329) +2022-11-14 13:39:25,056 Test: [82/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1123 (0.1144) Prec@1 79.000 (79.988) Prec@5 99.000 (98.337) +2022-11-14 13:39:25,068 Test: [83/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1053 (0.1143) Prec@1 83.000 (80.024) Prec@5 99.000 (98.345) +2022-11-14 13:39:25,081 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1292 (0.1144) Prec@1 78.000 (80.000) Prec@5 99.000 (98.353) +2022-11-14 13:39:25,094 Test: [85/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1500 (0.1149) Prec@1 77.000 (79.965) Prec@5 97.000 (98.337) +2022-11-14 13:39:25,108 Test: [86/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1336 (0.1151) Prec@1 77.000 (79.931) Prec@5 98.000 (98.333) +2022-11-14 13:39:25,120 Test: [87/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1073 (0.1150) Prec@1 82.000 (79.955) Prec@5 98.000 (98.330) +2022-11-14 13:39:25,131 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.1148) Prec@1 82.000 (79.978) Prec@5 97.000 (98.315) +2022-11-14 13:39:25,142 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1182 (0.1149) Prec@1 82.000 (80.000) Prec@5 97.000 (98.300) +2022-11-14 13:39:25,153 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1303 (0.1150) Prec@1 75.000 (79.945) Prec@5 99.000 (98.308) +2022-11-14 13:39:25,165 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0593 (0.1144) Prec@1 91.000 (80.065) Prec@5 98.000 (98.304) +2022-11-14 13:39:25,177 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1326 (0.1146) Prec@1 79.000 (80.054) Prec@5 97.000 (98.290) +2022-11-14 13:39:25,190 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0880 (0.1144) Prec@1 86.000 (80.117) Prec@5 100.000 (98.309) +2022-11-14 13:39:25,200 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1378 (0.1146) Prec@1 77.000 (80.084) Prec@5 97.000 (98.295) +2022-11-14 13:39:25,211 Test: [95/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1286 (0.1147) Prec@1 76.000 (80.042) Prec@5 99.000 (98.302) +2022-11-14 13:39:25,221 Test: [96/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1058 (0.1147) Prec@1 83.000 (80.072) Prec@5 99.000 (98.309) +2022-11-14 13:39:25,231 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1387 (0.1149) Prec@1 78.000 (80.051) Prec@5 97.000 (98.296) +2022-11-14 13:39:25,240 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1183 (0.1149) Prec@1 81.000 (80.061) Prec@5 98.000 (98.293) +2022-11-14 13:39:25,250 Test: [99/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1159 (0.1149) Prec@1 81.000 (80.070) Prec@5 97.000 (98.280) +2022-11-14 13:39:25,332 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:39:25,704 Epoch: [75][0/500] Time 0.028 (0.028) Data 0.283 (0.283) Loss 0.0819 (0.0819) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:39:26,019 Epoch: [75][10/500] Time 0.019 (0.027) Data 0.002 (0.029) Loss 0.0606 (0.0712) Prec@1 90.000 (88.500) Prec@5 99.000 (98.500) +2022-11-14 13:39:26,257 Epoch: [75][20/500] Time 0.019 (0.024) Data 0.002 (0.016) Loss 0.0677 (0.0700) Prec@1 90.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 13:39:26,519 Epoch: [75][30/500] Time 0.027 (0.024) Data 0.002 (0.012) Loss 0.0929 (0.0758) Prec@1 84.000 (87.750) Prec@5 100.000 (99.250) +2022-11-14 13:39:26,853 Epoch: [75][40/500] Time 0.031 (0.025) Data 0.003 (0.009) Loss 0.0906 (0.0787) Prec@1 85.000 (87.200) Prec@5 100.000 (99.400) +2022-11-14 13:39:27,216 Epoch: [75][50/500] Time 0.035 (0.027) Data 0.002 (0.008) Loss 0.0702 (0.0773) Prec@1 86.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 13:39:27,546 Epoch: [75][60/500] Time 0.030 (0.027) Data 0.002 (0.007) Loss 0.0765 (0.0772) Prec@1 85.000 (86.714) Prec@5 98.000 (99.286) +2022-11-14 13:39:27,885 Epoch: [75][70/500] Time 0.035 (0.027) Data 0.002 (0.006) Loss 0.1010 (0.0802) Prec@1 82.000 (86.125) Prec@5 98.000 (99.125) +2022-11-14 13:39:28,223 Epoch: [75][80/500] Time 0.031 (0.028) Data 0.003 (0.006) Loss 0.1059 (0.0830) Prec@1 77.000 (85.111) Prec@5 99.000 (99.111) +2022-11-14 13:39:28,566 Epoch: [75][90/500] Time 0.034 (0.028) Data 0.002 (0.006) Loss 0.0954 (0.0843) Prec@1 83.000 (84.900) Prec@5 98.000 (99.000) +2022-11-14 13:39:28,926 Epoch: [75][100/500] Time 0.027 (0.028) Data 0.002 (0.005) Loss 0.0989 (0.0856) Prec@1 83.000 (84.727) Prec@5 98.000 (98.909) +2022-11-14 13:39:29,279 Epoch: [75][110/500] Time 0.028 (0.029) Data 0.003 (0.005) Loss 0.0800 (0.0851) Prec@1 84.000 (84.667) Prec@5 100.000 (99.000) +2022-11-14 13:39:29,639 Epoch: [75][120/500] Time 0.028 (0.029) Data 0.003 (0.005) Loss 0.0649 (0.0836) Prec@1 91.000 (85.154) Prec@5 100.000 (99.077) +2022-11-14 13:39:29,990 Epoch: [75][130/500] Time 0.027 (0.029) Data 0.002 (0.005) Loss 0.1070 (0.0852) Prec@1 82.000 (84.929) Prec@5 99.000 (99.071) +2022-11-14 13:39:30,341 Epoch: [75][140/500] Time 0.025 (0.029) Data 0.003 (0.004) Loss 0.0962 (0.0860) Prec@1 84.000 (84.867) Prec@5 99.000 (99.067) +2022-11-14 13:39:30,709 Epoch: [75][150/500] Time 0.025 (0.030) Data 0.002 (0.004) Loss 0.1100 (0.0875) Prec@1 79.000 (84.500) Prec@5 98.000 (99.000) +2022-11-14 13:39:31,195 Epoch: [75][160/500] Time 0.055 (0.030) Data 0.002 (0.004) Loss 0.1093 (0.0888) Prec@1 81.000 (84.294) Prec@5 97.000 (98.882) +2022-11-14 13:39:31,854 Epoch: [75][170/500] Time 0.080 (0.032) Data 0.002 (0.004) Loss 0.1071 (0.0898) Prec@1 82.000 (84.167) Prec@5 95.000 (98.667) +2022-11-14 13:39:32,477 Epoch: [75][180/500] Time 0.052 (0.033) Data 0.002 (0.004) Loss 0.0822 (0.0894) Prec@1 87.000 (84.316) Prec@5 99.000 (98.684) +2022-11-14 13:39:33,076 Epoch: [75][190/500] Time 0.054 (0.034) Data 0.002 (0.004) Loss 0.1130 (0.0906) Prec@1 76.000 (83.900) Prec@5 99.000 (98.700) +2022-11-14 13:39:33,682 Epoch: [75][200/500] Time 0.058 (0.035) Data 0.002 (0.004) Loss 0.1118 (0.0916) Prec@1 83.000 (83.857) Prec@5 99.000 (98.714) +2022-11-14 13:39:34,300 Epoch: [75][210/500] Time 0.055 (0.036) Data 0.002 (0.004) Loss 0.0797 (0.0910) Prec@1 87.000 (84.000) Prec@5 99.000 (98.727) +2022-11-14 13:39:34,920 Epoch: [75][220/500] Time 0.059 (0.037) Data 0.002 (0.004) Loss 0.0855 (0.0908) Prec@1 86.000 (84.087) Prec@5 99.000 (98.739) +2022-11-14 13:39:35,570 Epoch: [75][230/500] Time 0.061 (0.038) Data 0.002 (0.004) Loss 0.0796 (0.0903) Prec@1 85.000 (84.125) Prec@5 100.000 (98.792) +2022-11-14 13:39:36,184 Epoch: [75][240/500] Time 0.074 (0.039) Data 0.003 (0.004) Loss 0.1028 (0.0908) Prec@1 84.000 (84.120) Prec@5 100.000 (98.840) +2022-11-14 13:39:36,797 Epoch: [75][250/500] Time 0.049 (0.039) Data 0.002 (0.004) Loss 0.0982 (0.0911) Prec@1 79.000 (83.923) Prec@5 99.000 (98.846) +2022-11-14 13:39:37,399 Epoch: [75][260/500] Time 0.058 (0.040) Data 0.002 (0.004) Loss 0.0749 (0.0905) Prec@1 88.000 (84.074) Prec@5 99.000 (98.852) +2022-11-14 13:39:37,999 Epoch: [75][270/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0954 (0.0907) Prec@1 87.000 (84.179) Prec@5 98.000 (98.821) +2022-11-14 13:39:38,678 Epoch: [75][280/500] Time 0.075 (0.041) Data 0.003 (0.003) Loss 0.0720 (0.0900) Prec@1 87.000 (84.276) Prec@5 100.000 (98.862) +2022-11-14 13:39:39,315 Epoch: [75][290/500] Time 0.061 (0.042) Data 0.003 (0.003) Loss 0.0993 (0.0903) Prec@1 87.000 (84.367) Prec@5 98.000 (98.833) +2022-11-14 13:39:39,916 Epoch: [75][300/500] Time 0.066 (0.042) Data 0.003 (0.003) Loss 0.1232 (0.0914) Prec@1 77.000 (84.129) Prec@5 98.000 (98.806) +2022-11-14 13:39:40,547 Epoch: [75][310/500] Time 0.065 (0.043) Data 0.003 (0.003) Loss 0.0802 (0.0911) Prec@1 85.000 (84.156) Prec@5 99.000 (98.812) +2022-11-14 13:39:41,275 Epoch: [75][320/500] Time 0.059 (0.043) Data 0.003 (0.003) Loss 0.0504 (0.0898) Prec@1 91.000 (84.364) Prec@5 100.000 (98.848) +2022-11-14 13:39:41,948 Epoch: [75][330/500] Time 0.069 (0.044) Data 0.002 (0.003) Loss 0.1262 (0.0909) Prec@1 78.000 (84.176) Prec@5 96.000 (98.765) +2022-11-14 13:39:42,610 Epoch: [75][340/500] Time 0.065 (0.044) Data 0.003 (0.003) Loss 0.1076 (0.0914) Prec@1 78.000 (84.000) Prec@5 99.000 (98.771) +2022-11-14 13:39:43,297 Epoch: [75][350/500] Time 0.077 (0.045) Data 0.002 (0.003) Loss 0.0934 (0.0914) Prec@1 84.000 (84.000) Prec@5 100.000 (98.806) +2022-11-14 13:39:43,959 Epoch: [75][360/500] Time 0.069 (0.045) Data 0.003 (0.003) Loss 0.1108 (0.0920) Prec@1 81.000 (83.919) Prec@5 99.000 (98.811) +2022-11-14 13:39:44,678 Epoch: [75][370/500] Time 0.070 (0.046) Data 0.002 (0.003) Loss 0.1141 (0.0925) Prec@1 80.000 (83.816) Prec@5 96.000 (98.737) +2022-11-14 13:39:45,347 Epoch: [75][380/500] Time 0.067 (0.046) Data 0.002 (0.003) Loss 0.1048 (0.0929) Prec@1 83.000 (83.795) Prec@5 99.000 (98.744) +2022-11-14 13:39:46,045 Epoch: [75][390/500] Time 0.064 (0.046) Data 0.003 (0.003) Loss 0.1170 (0.0935) Prec@1 82.000 (83.750) Prec@5 99.000 (98.750) +2022-11-14 13:39:46,750 Epoch: [75][400/500] Time 0.070 (0.047) Data 0.002 (0.003) Loss 0.1099 (0.0939) Prec@1 82.000 (83.707) Prec@5 100.000 (98.780) +2022-11-14 13:39:47,417 Epoch: [75][410/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0785 (0.0935) Prec@1 89.000 (83.833) Prec@5 100.000 (98.810) +2022-11-14 13:39:48,106 Epoch: [75][420/500] Time 0.066 (0.048) Data 0.003 (0.003) Loss 0.1252 (0.0942) Prec@1 79.000 (83.721) Prec@5 100.000 (98.837) +2022-11-14 13:39:48,799 Epoch: [75][430/500] Time 0.064 (0.048) Data 0.002 (0.003) Loss 0.0931 (0.0942) Prec@1 84.000 (83.727) Prec@5 100.000 (98.864) +2022-11-14 13:39:49,483 Epoch: [75][440/500] Time 0.072 (0.048) Data 0.002 (0.003) Loss 0.1254 (0.0949) Prec@1 78.000 (83.600) Prec@5 99.000 (98.867) +2022-11-14 13:39:50,174 Epoch: [75][450/500] Time 0.071 (0.048) Data 0.002 (0.003) Loss 0.1054 (0.0951) Prec@1 82.000 (83.565) Prec@5 97.000 (98.826) +2022-11-14 13:39:50,830 Epoch: [75][460/500] Time 0.066 (0.049) Data 0.002 (0.003) Loss 0.1076 (0.0954) Prec@1 82.000 (83.532) Prec@5 97.000 (98.787) +2022-11-14 13:39:51,484 Epoch: [75][470/500] Time 0.068 (0.049) Data 0.002 (0.003) Loss 0.1246 (0.0960) Prec@1 79.000 (83.438) Prec@5 98.000 (98.771) +2022-11-14 13:39:52,170 Epoch: [75][480/500] Time 0.065 (0.049) Data 0.003 (0.003) Loss 0.1280 (0.0967) Prec@1 77.000 (83.306) Prec@5 99.000 (98.776) +2022-11-14 13:39:52,832 Epoch: [75][490/500] Time 0.075 (0.049) Data 0.003 (0.003) Loss 0.1260 (0.0972) Prec@1 80.000 (83.240) Prec@5 97.000 (98.740) +2022-11-14 13:39:53,418 Epoch: [75][499/500] Time 0.071 (0.049) Data 0.002 (0.003) Loss 0.1334 (0.0979) Prec@1 76.000 (83.098) Prec@5 97.000 (98.706) +2022-11-14 13:39:53,803 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.1261 (0.1261) Prec@1 80.000 (80.000) Prec@5 100.000 (100.000) +2022-11-14 13:39:53,814 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0954 (0.1107) Prec@1 81.000 (80.500) Prec@5 100.000 (100.000) +2022-11-14 13:39:53,823 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0999 (0.1071) Prec@1 82.000 (81.000) Prec@5 98.000 (99.333) +2022-11-14 13:39:53,838 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1206 (0.1105) Prec@1 81.000 (81.000) Prec@5 100.000 (99.500) +2022-11-14 13:39:53,849 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1011 (0.1086) Prec@1 82.000 (81.200) Prec@5 100.000 (99.600) +2022-11-14 13:39:53,860 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1035 (0.1078) Prec@1 80.000 (81.000) Prec@5 98.000 (99.333) +2022-11-14 13:39:53,870 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0892 (0.1051) Prec@1 84.000 (81.429) Prec@5 99.000 (99.286) +2022-11-14 13:39:53,881 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1356 (0.1089) Prec@1 79.000 (81.125) Prec@5 98.000 (99.125) +2022-11-14 13:39:53,893 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1252 (0.1107) Prec@1 75.000 (80.444) Prec@5 98.000 (99.000) +2022-11-14 13:39:53,906 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.1081) Prec@1 87.000 (81.100) Prec@5 100.000 (99.100) +2022-11-14 13:39:53,918 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.1077) Prec@1 82.000 (81.182) Prec@5 97.000 (98.909) +2022-11-14 13:39:53,934 Test: [11/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1449 (0.1108) Prec@1 74.000 (80.583) Prec@5 98.000 (98.833) +2022-11-14 13:39:53,947 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.1099) Prec@1 81.000 (80.615) Prec@5 100.000 (98.923) +2022-11-14 13:39:53,958 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1211 (0.1107) Prec@1 83.000 (80.786) Prec@5 97.000 (98.786) +2022-11-14 13:39:53,969 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1184 (0.1112) Prec@1 81.000 (80.800) Prec@5 99.000 (98.800) +2022-11-14 13:39:53,984 Test: [15/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1386 (0.1129) Prec@1 76.000 (80.500) Prec@5 96.000 (98.625) +2022-11-14 13:39:53,997 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0921 (0.1117) Prec@1 86.000 (80.824) Prec@5 98.000 (98.588) +2022-11-14 13:39:54,008 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1424 (0.1134) Prec@1 73.000 (80.389) Prec@5 99.000 (98.611) +2022-11-14 13:39:54,021 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0972 (0.1125) Prec@1 85.000 (80.632) Prec@5 98.000 (98.579) +2022-11-14 13:39:54,037 Test: [19/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1258 (0.1132) Prec@1 78.000 (80.500) Prec@5 98.000 (98.550) +2022-11-14 13:39:54,049 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.1119) Prec@1 85.000 (80.714) Prec@5 98.000 (98.524) +2022-11-14 13:39:54,061 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1066 (0.1116) Prec@1 82.000 (80.773) Prec@5 99.000 (98.545) +2022-11-14 13:39:54,074 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1129 (0.1117) Prec@1 77.000 (80.609) Prec@5 99.000 (98.565) +2022-11-14 13:39:54,084 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1040 (0.1114) Prec@1 79.000 (80.542) Prec@5 99.000 (98.583) +2022-11-14 13:39:54,096 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1066 (0.1112) Prec@1 86.000 (80.760) Prec@5 98.000 (98.560) +2022-11-14 13:39:54,109 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1466 (0.1125) Prec@1 75.000 (80.538) Prec@5 96.000 (98.462) +2022-11-14 13:39:54,120 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1039 (0.1122) Prec@1 80.000 (80.519) Prec@5 98.000 (98.444) +2022-11-14 13:39:54,136 Test: [27/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1149 (0.1123) Prec@1 76.000 (80.357) Prec@5 98.000 (98.429) +2022-11-14 13:39:54,150 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1139 (0.1124) Prec@1 78.000 (80.276) Prec@5 97.000 (98.379) +2022-11-14 13:39:54,160 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1132 (0.1124) Prec@1 83.000 (80.367) Prec@5 99.000 (98.400) +2022-11-14 13:39:54,171 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1197 (0.1126) Prec@1 78.000 (80.290) Prec@5 97.000 (98.355) +2022-11-14 13:39:54,185 Test: [31/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0904 (0.1119) Prec@1 86.000 (80.469) Prec@5 99.000 (98.375) +2022-11-14 13:39:54,199 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.1117) Prec@1 78.000 (80.394) Prec@5 98.000 (98.364) +2022-11-14 13:39:54,209 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1091 (0.1117) Prec@1 79.000 (80.353) Prec@5 99.000 (98.382) +2022-11-14 13:39:54,221 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1273 (0.1121) Prec@1 76.000 (80.229) Prec@5 98.000 (98.371) +2022-11-14 13:39:54,236 Test: [35/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.1118) Prec@1 80.000 (80.222) Prec@5 100.000 (98.417) +2022-11-14 13:39:54,249 Test: [36/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1296 (0.1123) Prec@1 75.000 (80.081) Prec@5 95.000 (98.324) +2022-11-14 13:39:54,261 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1273 (0.1127) Prec@1 76.000 (79.974) Prec@5 98.000 (98.316) +2022-11-14 13:39:54,273 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.1120) Prec@1 85.000 (80.103) Prec@5 99.000 (98.333) +2022-11-14 13:39:54,289 Test: [39/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1053 (0.1118) Prec@1 82.000 (80.150) Prec@5 97.000 (98.300) +2022-11-14 13:39:54,302 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1263 (0.1122) Prec@1 81.000 (80.171) Prec@5 97.000 (98.268) +2022-11-14 13:39:54,313 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0951 (0.1118) Prec@1 88.000 (80.357) Prec@5 99.000 (98.286) +2022-11-14 13:39:54,325 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.1113) Prec@1 84.000 (80.442) Prec@5 99.000 (98.302) +2022-11-14 13:39:54,339 Test: [43/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0973 (0.1109) Prec@1 83.000 (80.500) Prec@5 97.000 (98.273) +2022-11-14 13:39:54,351 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1034 (0.1108) Prec@1 82.000 (80.533) Prec@5 98.000 (98.267) +2022-11-14 13:39:54,363 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1137 (0.1108) Prec@1 77.000 (80.457) Prec@5 99.000 (98.283) +2022-11-14 13:39:54,375 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1067 (0.1107) Prec@1 80.000 (80.447) Prec@5 100.000 (98.319) +2022-11-14 13:39:54,388 Test: [47/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1402 (0.1114) Prec@1 73.000 (80.292) Prec@5 98.000 (98.312) +2022-11-14 13:39:54,400 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1065 (0.1113) Prec@1 78.000 (80.245) Prec@5 98.000 (98.306) +2022-11-14 13:39:54,412 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1547 (0.1121) Prec@1 77.000 (80.180) Prec@5 96.000 (98.260) +2022-11-14 13:39:54,423 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1121 (0.1121) Prec@1 81.000 (80.196) Prec@5 97.000 (98.235) +2022-11-14 13:39:54,435 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1308 (0.1125) Prec@1 77.000 (80.135) Prec@5 96.000 (98.192) +2022-11-14 13:39:54,445 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1192 (0.1126) Prec@1 79.000 (80.113) Prec@5 99.000 (98.208) +2022-11-14 13:39:54,458 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.1124) Prec@1 82.000 (80.148) Prec@5 96.000 (98.167) +2022-11-14 13:39:54,470 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1224 (0.1126) Prec@1 76.000 (80.073) Prec@5 99.000 (98.182) +2022-11-14 13:39:54,482 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1046 (0.1125) Prec@1 82.000 (80.107) Prec@5 99.000 (98.196) +2022-11-14 13:39:54,494 Test: [56/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1201 (0.1126) Prec@1 80.000 (80.105) Prec@5 99.000 (98.211) +2022-11-14 13:39:54,505 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.1120) Prec@1 87.000 (80.224) Prec@5 99.000 (98.224) +2022-11-14 13:39:54,516 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1550 (0.1127) Prec@1 73.000 (80.102) Prec@5 98.000 (98.220) +2022-11-14 13:39:54,528 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1167 (0.1128) Prec@1 79.000 (80.083) Prec@5 96.000 (98.183) +2022-11-14 13:39:54,544 Test: [60/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1435 (0.1133) Prec@1 73.000 (79.967) Prec@5 98.000 (98.180) +2022-11-14 13:39:54,560 Test: [61/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.1129) Prec@1 86.000 (80.065) Prec@5 99.000 (98.194) +2022-11-14 13:39:54,576 Test: [62/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1018 (0.1127) Prec@1 81.000 (80.079) Prec@5 98.000 (98.190) +2022-11-14 13:39:54,593 Test: [63/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.1125) Prec@1 87.000 (80.188) Prec@5 99.000 (98.203) +2022-11-14 13:39:54,620 Test: [64/100] Model Time 0.021 (0.010) Loss Time 0.000 (0.000) Loss 0.1303 (0.1128) Prec@1 75.000 (80.108) Prec@5 97.000 (98.185) +2022-11-14 13:39:54,636 Test: [65/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1140 (0.1128) Prec@1 81.000 (80.121) Prec@5 98.000 (98.182) +2022-11-14 13:39:54,654 Test: [66/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1180 (0.1129) Prec@1 79.000 (80.104) Prec@5 99.000 (98.194) +2022-11-14 13:39:54,671 Test: [67/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0843 (0.1124) Prec@1 85.000 (80.176) Prec@5 98.000 (98.191) +2022-11-14 13:39:54,685 Test: [68/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1260 (0.1126) Prec@1 77.000 (80.130) Prec@5 98.000 (98.188) +2022-11-14 13:39:54,698 Test: [69/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1333 (0.1129) Prec@1 76.000 (80.071) Prec@5 97.000 (98.171) +2022-11-14 13:39:54,715 Test: [70/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1269 (0.1131) Prec@1 75.000 (80.000) Prec@5 98.000 (98.169) +2022-11-14 13:39:54,731 Test: [71/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1151 (0.1131) Prec@1 79.000 (79.986) Prec@5 98.000 (98.167) +2022-11-14 13:39:54,743 Test: [72/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0820 (0.1127) Prec@1 87.000 (80.082) Prec@5 98.000 (98.164) +2022-11-14 13:39:54,758 Test: [73/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0828 (0.1123) Prec@1 89.000 (80.203) Prec@5 100.000 (98.189) +2022-11-14 13:39:54,772 Test: [74/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1285 (0.1125) Prec@1 77.000 (80.160) Prec@5 99.000 (98.200) +2022-11-14 13:39:54,785 Test: [75/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0984 (0.1123) Prec@1 85.000 (80.224) Prec@5 98.000 (98.197) +2022-11-14 13:39:54,799 Test: [76/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1226 (0.1125) Prec@1 79.000 (80.208) Prec@5 99.000 (98.208) +2022-11-14 13:39:54,814 Test: [77/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1162 (0.1125) Prec@1 79.000 (80.192) Prec@5 96.000 (98.179) +2022-11-14 13:39:54,827 Test: [78/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1337 (0.1128) Prec@1 78.000 (80.165) Prec@5 99.000 (98.190) +2022-11-14 13:39:54,842 Test: [79/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1280 (0.1130) Prec@1 77.000 (80.125) Prec@5 98.000 (98.188) +2022-11-14 13:39:54,858 Test: [80/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1199 (0.1131) Prec@1 82.000 (80.148) Prec@5 99.000 (98.198) +2022-11-14 13:39:54,871 Test: [81/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1289 (0.1133) Prec@1 75.000 (80.085) Prec@5 99.000 (98.207) +2022-11-14 13:39:54,886 Test: [82/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1241 (0.1134) Prec@1 75.000 (80.024) Prec@5 98.000 (98.205) +2022-11-14 13:39:54,901 Test: [83/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1098 (0.1134) Prec@1 83.000 (80.060) Prec@5 99.000 (98.214) +2022-11-14 13:39:54,917 Test: [84/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1391 (0.1137) Prec@1 74.000 (79.988) Prec@5 100.000 (98.235) +2022-11-14 13:39:54,934 Test: [85/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1527 (0.1141) Prec@1 73.000 (79.907) Prec@5 98.000 (98.233) +2022-11-14 13:39:54,949 Test: [86/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0944 (0.1139) Prec@1 82.000 (79.931) Prec@5 98.000 (98.230) +2022-11-14 13:39:54,966 Test: [87/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1487 (0.1143) Prec@1 74.000 (79.864) Prec@5 97.000 (98.216) +2022-11-14 13:39:54,983 Test: [88/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1072 (0.1142) Prec@1 81.000 (79.876) Prec@5 96.000 (98.191) +2022-11-14 13:39:55,000 Test: [89/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1406 (0.1145) Prec@1 78.000 (79.856) Prec@5 97.000 (98.178) +2022-11-14 13:39:55,015 Test: [90/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.1142) Prec@1 85.000 (79.912) Prec@5 100.000 (98.198) +2022-11-14 13:39:55,034 Test: [91/100] Model Time 0.016 (0.010) Loss Time 0.000 (0.000) Loss 0.0789 (0.1138) Prec@1 87.000 (79.989) Prec@5 99.000 (98.207) +2022-11-14 13:39:55,053 Test: [92/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.1229 (0.1139) Prec@1 78.000 (79.968) Prec@5 97.000 (98.194) +2022-11-14 13:39:55,066 Test: [93/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1140 (0.1139) Prec@1 79.000 (79.957) Prec@5 99.000 (98.202) +2022-11-14 13:39:55,081 Test: [94/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1015 (0.1137) Prec@1 83.000 (79.989) Prec@5 98.000 (98.200) +2022-11-14 13:39:55,094 Test: [95/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1007 (0.1136) Prec@1 83.000 (80.021) Prec@5 98.000 (98.198) +2022-11-14 13:39:55,108 Test: [96/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0990 (0.1135) Prec@1 81.000 (80.031) Prec@5 98.000 (98.196) +2022-11-14 13:39:55,122 Test: [97/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1416 (0.1137) Prec@1 78.000 (80.010) Prec@5 97.000 (98.184) +2022-11-14 13:39:55,136 Test: [98/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1282 (0.1139) Prec@1 77.000 (79.980) Prec@5 97.000 (98.172) +2022-11-14 13:39:55,151 Test: [99/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0959 (0.1137) Prec@1 84.000 (80.020) Prec@5 99.000 (98.180) +2022-11-14 13:39:55,241 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:39:55,659 Epoch: [76][0/500] Time 0.028 (0.028) Data 0.303 (0.303) Loss 0.0754 (0.0754) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 13:39:55,949 Epoch: [76][10/500] Time 0.026 (0.026) Data 0.002 (0.030) Loss 0.1116 (0.0935) Prec@1 82.000 (87.000) Prec@5 97.000 (98.000) +2022-11-14 13:39:56,234 Epoch: [76][20/500] Time 0.025 (0.026) Data 0.002 (0.016) Loss 0.0870 (0.0914) Prec@1 83.000 (85.667) Prec@5 98.000 (98.000) +2022-11-14 13:39:56,525 Epoch: [76][30/500] Time 0.031 (0.026) Data 0.002 (0.012) Loss 0.1184 (0.0981) Prec@1 81.000 (84.500) Prec@5 97.000 (97.750) +2022-11-14 13:39:56,925 Epoch: [76][40/500] Time 0.035 (0.028) Data 0.002 (0.010) Loss 0.0870 (0.0959) Prec@1 81.000 (83.800) Prec@5 100.000 (98.200) +2022-11-14 13:39:57,337 Epoch: [76][50/500] Time 0.044 (0.030) Data 0.003 (0.008) Loss 0.0879 (0.0946) Prec@1 87.000 (84.333) Prec@5 97.000 (98.000) +2022-11-14 13:39:57,763 Epoch: [76][60/500] Time 0.043 (0.031) Data 0.003 (0.007) Loss 0.0966 (0.0949) Prec@1 83.000 (84.143) Prec@5 97.000 (97.857) +2022-11-14 13:39:58,177 Epoch: [76][70/500] Time 0.040 (0.032) Data 0.002 (0.007) Loss 0.0854 (0.0937) Prec@1 83.000 (84.000) Prec@5 100.000 (98.125) +2022-11-14 13:39:58,587 Epoch: [76][80/500] Time 0.033 (0.032) Data 0.002 (0.006) Loss 0.0834 (0.0925) Prec@1 88.000 (84.444) Prec@5 98.000 (98.111) +2022-11-14 13:39:58,988 Epoch: [76][90/500] Time 0.036 (0.033) Data 0.002 (0.006) Loss 0.0786 (0.0911) Prec@1 86.000 (84.600) Prec@5 99.000 (98.200) +2022-11-14 13:39:59,399 Epoch: [76][100/500] Time 0.038 (0.033) Data 0.002 (0.005) Loss 0.0749 (0.0897) Prec@1 87.000 (84.818) Prec@5 98.000 (98.182) +2022-11-14 13:39:59,833 Epoch: [76][110/500] Time 0.045 (0.034) Data 0.002 (0.005) Loss 0.0882 (0.0895) Prec@1 86.000 (84.917) Prec@5 99.000 (98.250) +2022-11-14 13:40:00,273 Epoch: [76][120/500] Time 0.048 (0.034) Data 0.002 (0.005) Loss 0.1176 (0.0917) Prec@1 79.000 (84.462) Prec@5 99.000 (98.308) +2022-11-14 13:40:00,690 Epoch: [76][130/500] Time 0.039 (0.034) Data 0.002 (0.005) Loss 0.1250 (0.0941) Prec@1 78.000 (84.000) Prec@5 100.000 (98.429) +2022-11-14 13:40:01,090 Epoch: [76][140/500] Time 0.037 (0.034) Data 0.003 (0.004) Loss 0.0984 (0.0944) Prec@1 85.000 (84.067) Prec@5 99.000 (98.467) +2022-11-14 13:40:01,531 Epoch: [76][150/500] Time 0.052 (0.035) Data 0.003 (0.004) Loss 0.0807 (0.0935) Prec@1 87.000 (84.250) Prec@5 97.000 (98.375) +2022-11-14 13:40:01,950 Epoch: [76][160/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.0932 (0.0935) Prec@1 84.000 (84.235) Prec@5 100.000 (98.471) +2022-11-14 13:40:02,373 Epoch: [76][170/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.1061 (0.0942) Prec@1 80.000 (84.000) Prec@5 100.000 (98.556) +2022-11-14 13:40:02,791 Epoch: [76][180/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.1157 (0.0953) Prec@1 81.000 (83.842) Prec@5 99.000 (98.579) +2022-11-14 13:40:03,243 Epoch: [76][190/500] Time 0.046 (0.035) Data 0.002 (0.004) Loss 0.0875 (0.0949) Prec@1 85.000 (83.900) Prec@5 99.000 (98.600) +2022-11-14 13:40:03,671 Epoch: [76][200/500] Time 0.042 (0.035) Data 0.003 (0.004) Loss 0.1053 (0.0954) Prec@1 84.000 (83.905) Prec@5 98.000 (98.571) +2022-11-14 13:40:04,137 Epoch: [76][210/500] Time 0.042 (0.036) Data 0.003 (0.004) Loss 0.0872 (0.0951) Prec@1 85.000 (83.955) Prec@5 98.000 (98.545) +2022-11-14 13:40:04,945 Epoch: [76][220/500] Time 0.096 (0.037) Data 0.003 (0.004) Loss 0.1032 (0.0954) Prec@1 83.000 (83.913) Prec@5 99.000 (98.565) +2022-11-14 13:40:05,987 Epoch: [76][230/500] Time 0.100 (0.040) Data 0.003 (0.004) Loss 0.0821 (0.0949) Prec@1 85.000 (83.958) Prec@5 98.000 (98.542) +2022-11-14 13:40:06,993 Epoch: [76][240/500] Time 0.096 (0.042) Data 0.003 (0.004) Loss 0.0795 (0.0942) Prec@1 87.000 (84.080) Prec@5 100.000 (98.600) +2022-11-14 13:40:08,048 Epoch: [76][250/500] Time 0.094 (0.044) Data 0.003 (0.004) Loss 0.0976 (0.0944) Prec@1 81.000 (83.962) Prec@5 100.000 (98.654) +2022-11-14 13:40:09,044 Epoch: [76][260/500] Time 0.082 (0.046) Data 0.002 (0.004) Loss 0.0823 (0.0939) Prec@1 86.000 (84.037) Prec@5 99.000 (98.667) +2022-11-14 13:40:09,986 Epoch: [76][270/500] Time 0.060 (0.047) Data 0.002 (0.004) Loss 0.0849 (0.0936) Prec@1 85.000 (84.071) Prec@5 98.000 (98.643) +2022-11-14 13:40:10,461 Epoch: [76][280/500] Time 0.040 (0.047) Data 0.002 (0.004) Loss 0.1036 (0.0940) Prec@1 82.000 (84.000) Prec@5 100.000 (98.690) +2022-11-14 13:40:10,947 Epoch: [76][290/500] Time 0.044 (0.047) Data 0.003 (0.004) Loss 0.0737 (0.0933) Prec@1 86.000 (84.067) Prec@5 100.000 (98.733) +2022-11-14 13:40:11,459 Epoch: [76][300/500] Time 0.040 (0.047) Data 0.003 (0.004) Loss 0.0752 (0.0927) Prec@1 87.000 (84.161) Prec@5 100.000 (98.774) +2022-11-14 13:40:11,957 Epoch: [76][310/500] Time 0.044 (0.047) Data 0.003 (0.003) Loss 0.0854 (0.0925) Prec@1 86.000 (84.219) Prec@5 100.000 (98.812) +2022-11-14 13:40:12,439 Epoch: [76][320/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.1144 (0.0931) Prec@1 82.000 (84.152) Prec@5 99.000 (98.818) +2022-11-14 13:40:12,959 Epoch: [76][330/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.1179 (0.0939) Prec@1 79.000 (84.000) Prec@5 97.000 (98.765) +2022-11-14 13:40:13,455 Epoch: [76][340/500] Time 0.052 (0.047) Data 0.003 (0.003) Loss 0.0899 (0.0937) Prec@1 81.000 (83.914) Prec@5 98.000 (98.743) +2022-11-14 13:40:13,948 Epoch: [76][350/500] Time 0.041 (0.047) Data 0.003 (0.003) Loss 0.1050 (0.0941) Prec@1 82.000 (83.861) Prec@5 99.000 (98.750) +2022-11-14 13:40:14,440 Epoch: [76][360/500] Time 0.042 (0.046) Data 0.003 (0.003) Loss 0.1047 (0.0943) Prec@1 83.000 (83.838) Prec@5 100.000 (98.784) +2022-11-14 13:40:14,934 Epoch: [76][370/500] Time 0.037 (0.046) Data 0.003 (0.003) Loss 0.0699 (0.0937) Prec@1 88.000 (83.947) Prec@5 100.000 (98.816) +2022-11-14 13:40:15,432 Epoch: [76][380/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0963 (0.0938) Prec@1 84.000 (83.949) Prec@5 99.000 (98.821) +2022-11-14 13:40:15,922 Epoch: [76][390/500] Time 0.039 (0.046) Data 0.002 (0.003) Loss 0.0998 (0.0939) Prec@1 85.000 (83.975) Prec@5 99.000 (98.825) +2022-11-14 13:40:16,439 Epoch: [76][400/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.1072 (0.0942) Prec@1 80.000 (83.878) Prec@5 96.000 (98.756) +2022-11-14 13:40:16,933 Epoch: [76][410/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.1181 (0.0948) Prec@1 79.000 (83.762) Prec@5 98.000 (98.738) +2022-11-14 13:40:17,425 Epoch: [76][420/500] Time 0.044 (0.046) Data 0.003 (0.003) Loss 0.1009 (0.0950) Prec@1 85.000 (83.791) Prec@5 97.000 (98.698) +2022-11-14 13:40:17,939 Epoch: [76][430/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0760 (0.0945) Prec@1 87.000 (83.864) Prec@5 100.000 (98.727) +2022-11-14 13:40:18,435 Epoch: [76][440/500] Time 0.046 (0.046) Data 0.003 (0.003) Loss 0.1399 (0.0955) Prec@1 76.000 (83.689) Prec@5 97.000 (98.689) +2022-11-14 13:40:18,932 Epoch: [76][450/500] Time 0.041 (0.046) Data 0.003 (0.003) Loss 0.1022 (0.0957) Prec@1 82.000 (83.652) Prec@5 99.000 (98.696) +2022-11-14 13:40:19,452 Epoch: [76][460/500] Time 0.032 (0.046) Data 0.006 (0.003) Loss 0.1105 (0.0960) Prec@1 80.000 (83.574) Prec@5 99.000 (98.702) +2022-11-14 13:40:19,953 Epoch: [76][470/500] Time 0.038 (0.046) Data 0.002 (0.003) Loss 0.0760 (0.0956) Prec@1 87.000 (83.646) Prec@5 100.000 (98.729) +2022-11-14 13:40:20,445 Epoch: [76][480/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0803 (0.0953) Prec@1 87.000 (83.714) Prec@5 100.000 (98.755) +2022-11-14 13:40:20,972 Epoch: [76][490/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0813 (0.0950) Prec@1 85.000 (83.740) Prec@5 98.000 (98.740) +2022-11-14 13:40:21,409 Epoch: [76][499/500] Time 0.064 (0.046) Data 0.003 (0.003) Loss 0.0892 (0.0949) Prec@1 86.000 (83.784) Prec@5 100.000 (98.765) +2022-11-14 13:40:21,781 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0929 (0.0929) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:40:21,790 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0927) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:40:21,803 Test: [2/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1070 (0.0974) Prec@1 83.000 (83.667) Prec@5 100.000 (99.333) +2022-11-14 13:40:21,821 Test: [3/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1201 (0.1031) Prec@1 81.000 (83.000) Prec@5 100.000 (99.500) +2022-11-14 13:40:21,831 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1077 (0.1040) Prec@1 83.000 (83.000) Prec@5 100.000 (99.600) +2022-11-14 13:40:21,843 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0714 (0.0986) Prec@1 88.000 (83.833) Prec@5 99.000 (99.500) +2022-11-14 13:40:21,853 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0977) Prec@1 86.000 (84.143) Prec@5 99.000 (99.429) +2022-11-14 13:40:21,869 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1212 (0.1006) Prec@1 78.000 (83.375) Prec@5 98.000 (99.250) +2022-11-14 13:40:21,883 Test: [8/100] Model Time 0.011 (0.009) Loss Time 0.001 (0.000) Loss 0.1255 (0.1034) Prec@1 80.000 (83.000) Prec@5 99.000 (99.222) +2022-11-14 13:40:21,899 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.1021) Prec@1 81.000 (82.800) Prec@5 98.000 (99.100) +2022-11-14 13:40:21,913 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0999) Prec@1 88.000 (83.273) Prec@5 100.000 (99.182) +2022-11-14 13:40:21,928 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1162 (0.1012) Prec@1 80.000 (83.000) Prec@5 98.000 (99.083) +2022-11-14 13:40:21,941 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0945 (0.1007) Prec@1 85.000 (83.154) Prec@5 99.000 (99.077) +2022-11-14 13:40:21,956 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0994) Prec@1 85.000 (83.286) Prec@5 98.000 (99.000) +2022-11-14 13:40:21,969 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1216 (0.1009) Prec@1 78.000 (82.933) Prec@5 98.000 (98.933) +2022-11-14 13:40:21,984 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1288 (0.1027) Prec@1 78.000 (82.625) Prec@5 96.000 (98.750) +2022-11-14 13:40:22,001 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.1018) Prec@1 83.000 (82.647) Prec@5 99.000 (98.765) +2022-11-14 13:40:22,016 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1077 (0.1022) Prec@1 80.000 (82.500) Prec@5 100.000 (98.833) +2022-11-14 13:40:22,030 Test: [18/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1126 (0.1027) Prec@1 83.000 (82.526) Prec@5 97.000 (98.737) +2022-11-14 13:40:22,045 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1356 (0.1043) Prec@1 76.000 (82.200) Prec@5 96.000 (98.600) +2022-11-14 13:40:22,061 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1336 (0.1057) Prec@1 73.000 (81.762) Prec@5 96.000 (98.476) +2022-11-14 13:40:22,077 Test: [21/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1088 (0.1059) Prec@1 77.000 (81.545) Prec@5 99.000 (98.500) +2022-11-14 13:40:22,096 Test: [22/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1151 (0.1063) Prec@1 78.000 (81.391) Prec@5 99.000 (98.522) +2022-11-14 13:40:22,111 Test: [23/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0906 (0.1056) Prec@1 83.000 (81.458) Prec@5 99.000 (98.542) +2022-11-14 13:40:22,127 Test: [24/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1204 (0.1062) Prec@1 75.000 (81.200) Prec@5 100.000 (98.600) +2022-11-14 13:40:22,142 Test: [25/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1321 (0.1072) Prec@1 79.000 (81.115) Prec@5 97.000 (98.538) +2022-11-14 13:40:22,156 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.1068) Prec@1 83.000 (81.185) Prec@5 99.000 (98.556) +2022-11-14 13:40:22,170 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1075 (0.1068) Prec@1 84.000 (81.286) Prec@5 99.000 (98.571) +2022-11-14 13:40:22,185 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.1069) Prec@1 81.000 (81.276) Prec@5 99.000 (98.586) +2022-11-14 13:40:22,201 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.1062) Prec@1 85.000 (81.400) Prec@5 100.000 (98.633) +2022-11-14 13:40:22,216 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1136 (0.1064) Prec@1 79.000 (81.323) Prec@5 99.000 (98.645) +2022-11-14 13:40:22,232 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1014 (0.1063) Prec@1 82.000 (81.344) Prec@5 100.000 (98.688) +2022-11-14 13:40:22,249 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1068 (0.1063) Prec@1 80.000 (81.303) Prec@5 98.000 (98.667) +2022-11-14 13:40:22,265 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1205 (0.1067) Prec@1 79.000 (81.235) Prec@5 97.000 (98.618) +2022-11-14 13:40:22,281 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1296 (0.1073) Prec@1 79.000 (81.171) Prec@5 98.000 (98.600) +2022-11-14 13:40:22,297 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1116 (0.1075) Prec@1 82.000 (81.194) Prec@5 98.000 (98.583) +2022-11-14 13:40:22,313 Test: [36/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1054 (0.1074) Prec@1 82.000 (81.216) Prec@5 99.000 (98.595) +2022-11-14 13:40:22,328 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1126 (0.1075) Prec@1 78.000 (81.132) Prec@5 99.000 (98.605) +2022-11-14 13:40:22,343 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.1070) Prec@1 83.000 (81.179) Prec@5 100.000 (98.641) +2022-11-14 13:40:22,358 Test: [39/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.1064) Prec@1 88.000 (81.350) Prec@5 100.000 (98.675) +2022-11-14 13:40:22,374 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.1059) Prec@1 86.000 (81.463) Prec@5 98.000 (98.659) +2022-11-14 13:40:22,391 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1175 (0.1061) Prec@1 79.000 (81.405) Prec@5 99.000 (98.667) +2022-11-14 13:40:22,409 Test: [42/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.1056) Prec@1 87.000 (81.535) Prec@5 98.000 (98.651) +2022-11-14 13:40:22,427 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.1051) Prec@1 87.000 (81.659) Prec@5 96.000 (98.591) +2022-11-14 13:40:22,448 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0983 (0.1050) Prec@1 85.000 (81.733) Prec@5 99.000 (98.600) +2022-11-14 13:40:22,468 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1244 (0.1054) Prec@1 77.000 (81.630) Prec@5 98.000 (98.587) +2022-11-14 13:40:22,492 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.1051) Prec@1 86.000 (81.723) Prec@5 100.000 (98.617) +2022-11-14 13:40:22,510 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1182 (0.1053) Prec@1 80.000 (81.688) Prec@5 98.000 (98.604) +2022-11-14 13:40:22,529 Test: [48/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.1045) Prec@1 91.000 (81.878) Prec@5 100.000 (98.633) +2022-11-14 13:40:22,546 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1405 (0.1052) Prec@1 74.000 (81.720) Prec@5 98.000 (98.620) +2022-11-14 13:40:22,561 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.1050) Prec@1 79.000 (81.667) Prec@5 99.000 (98.627) +2022-11-14 13:40:22,576 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1151 (0.1052) Prec@1 80.000 (81.635) Prec@5 99.000 (98.635) +2022-11-14 13:40:22,591 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0915 (0.1050) Prec@1 83.000 (81.660) Prec@5 100.000 (98.660) +2022-11-14 13:40:22,609 Test: [53/100] Model Time 0.015 (0.009) Loss Time 0.000 (0.000) Loss 0.1006 (0.1049) Prec@1 83.000 (81.685) Prec@5 96.000 (98.611) +2022-11-14 13:40:22,626 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1082 (0.1049) Prec@1 83.000 (81.709) Prec@5 99.000 (98.618) +2022-11-14 13:40:22,642 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.1045) Prec@1 87.000 (81.804) Prec@5 99.000 (98.625) +2022-11-14 13:40:22,657 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1345 (0.1051) Prec@1 75.000 (81.684) Prec@5 97.000 (98.596) +2022-11-14 13:40:22,673 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.1049) Prec@1 84.000 (81.724) Prec@5 99.000 (98.603) +2022-11-14 13:40:22,691 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.1049) Prec@1 84.000 (81.763) Prec@5 99.000 (98.610) +2022-11-14 13:40:22,710 Test: [59/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.1045) Prec@1 87.000 (81.850) Prec@5 100.000 (98.633) +2022-11-14 13:40:22,727 Test: [60/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1045 (0.1045) Prec@1 81.000 (81.836) Prec@5 100.000 (98.656) +2022-11-14 13:40:22,743 Test: [61/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1272 (0.1049) Prec@1 78.000 (81.774) Prec@5 99.000 (98.661) +2022-11-14 13:40:22,760 Test: [62/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1007 (0.1048) Prec@1 80.000 (81.746) Prec@5 100.000 (98.683) +2022-11-14 13:40:22,779 Test: [63/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0818 (0.1045) Prec@1 86.000 (81.812) Prec@5 99.000 (98.688) +2022-11-14 13:40:22,795 Test: [64/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1168 (0.1047) Prec@1 82.000 (81.815) Prec@5 97.000 (98.662) +2022-11-14 13:40:22,811 Test: [65/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1291 (0.1050) Prec@1 77.000 (81.742) Prec@5 98.000 (98.652) +2022-11-14 13:40:22,829 Test: [66/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.1047) Prec@1 88.000 (81.836) Prec@5 100.000 (98.672) +2022-11-14 13:40:22,844 Test: [67/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1222 (0.1049) Prec@1 79.000 (81.794) Prec@5 99.000 (98.676) +2022-11-14 13:40:22,861 Test: [68/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1088 (0.1050) Prec@1 82.000 (81.797) Prec@5 97.000 (98.652) +2022-11-14 13:40:22,878 Test: [69/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1416 (0.1055) Prec@1 74.000 (81.686) Prec@5 96.000 (98.614) +2022-11-14 13:40:22,895 Test: [70/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1079 (0.1056) Prec@1 82.000 (81.690) Prec@5 100.000 (98.634) +2022-11-14 13:40:22,912 Test: [71/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0949 (0.1054) Prec@1 85.000 (81.736) Prec@5 98.000 (98.625) +2022-11-14 13:40:22,932 Test: [72/100] Model Time 0.016 (0.010) Loss Time 0.000 (0.000) Loss 0.0943 (0.1053) Prec@1 86.000 (81.795) Prec@5 99.000 (98.630) +2022-11-14 13:40:22,949 Test: [73/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0741 (0.1048) Prec@1 86.000 (81.851) Prec@5 99.000 (98.635) +2022-11-14 13:40:22,968 Test: [74/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.1037 (0.1048) Prec@1 80.000 (81.827) Prec@5 99.000 (98.640) +2022-11-14 13:40:22,985 Test: [75/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1047 (0.1048) Prec@1 82.000 (81.829) Prec@5 99.000 (98.645) +2022-11-14 13:40:23,003 Test: [76/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.0847 (0.1046) Prec@1 86.000 (81.883) Prec@5 99.000 (98.649) +2022-11-14 13:40:23,020 Test: [77/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1083 (0.1046) Prec@1 81.000 (81.872) Prec@5 98.000 (98.641) +2022-11-14 13:40:23,041 Test: [78/100] Model Time 0.017 (0.010) Loss Time 0.000 (0.000) Loss 0.1286 (0.1049) Prec@1 82.000 (81.873) Prec@5 99.000 (98.646) +2022-11-14 13:40:23,058 Test: [79/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1018 (0.1049) Prec@1 80.000 (81.850) Prec@5 99.000 (98.650) +2022-11-14 13:40:23,074 Test: [80/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0806 (0.1046) Prec@1 87.000 (81.914) Prec@5 98.000 (98.642) +2022-11-14 13:40:23,094 Test: [81/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.1089 (0.1046) Prec@1 86.000 (81.963) Prec@5 97.000 (98.622) +2022-11-14 13:40:23,118 Test: [82/100] Model Time 0.019 (0.011) Loss Time 0.000 (0.000) Loss 0.1159 (0.1048) Prec@1 79.000 (81.928) Prec@5 100.000 (98.639) +2022-11-14 13:40:23,134 Test: [83/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0912 (0.1046) Prec@1 84.000 (81.952) Prec@5 99.000 (98.643) +2022-11-14 13:40:23,150 Test: [84/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1090 (0.1047) Prec@1 82.000 (81.953) Prec@5 100.000 (98.659) +2022-11-14 13:40:23,168 Test: [85/100] Model Time 0.016 (0.011) Loss Time 0.000 (0.000) Loss 0.1043 (0.1046) Prec@1 83.000 (81.965) Prec@5 98.000 (98.651) +2022-11-14 13:40:23,183 Test: [86/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1030 (0.1046) Prec@1 82.000 (81.966) Prec@5 98.000 (98.644) +2022-11-14 13:40:23,195 Test: [87/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1082 (0.1047) Prec@1 83.000 (81.977) Prec@5 98.000 (98.636) +2022-11-14 13:40:23,208 Test: [88/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1189 (0.1048) Prec@1 78.000 (81.933) Prec@5 99.000 (98.640) +2022-11-14 13:40:23,223 Test: [89/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1033 (0.1048) Prec@1 81.000 (81.922) Prec@5 98.000 (98.633) +2022-11-14 13:40:23,238 Test: [90/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1007 (0.1048) Prec@1 79.000 (81.890) Prec@5 100.000 (98.648) +2022-11-14 13:40:23,252 Test: [91/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0605 (0.1043) Prec@1 90.000 (81.978) Prec@5 99.000 (98.652) +2022-11-14 13:40:23,266 Test: [92/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1024 (0.1043) Prec@1 84.000 (82.000) Prec@5 100.000 (98.667) +2022-11-14 13:40:23,280 Test: [93/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1070 (0.1043) Prec@1 83.000 (82.011) Prec@5 98.000 (98.660) +2022-11-14 13:40:23,294 Test: [94/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0939 (0.1042) Prec@1 85.000 (82.042) Prec@5 98.000 (98.653) +2022-11-14 13:40:23,308 Test: [95/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0781 (0.1039) Prec@1 88.000 (82.104) Prec@5 99.000 (98.656) +2022-11-14 13:40:23,322 Test: [96/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0916 (0.1038) Prec@1 83.000 (82.113) Prec@5 99.000 (98.660) +2022-11-14 13:40:23,336 Test: [97/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1329 (0.1041) Prec@1 77.000 (82.061) Prec@5 98.000 (98.653) +2022-11-14 13:40:23,350 Test: [98/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1210 (0.1043) Prec@1 77.000 (82.010) Prec@5 100.000 (98.667) +2022-11-14 13:40:23,365 Test: [99/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1095 (0.1043) Prec@1 83.000 (82.020) Prec@5 99.000 (98.670) +2022-11-14 13:40:23,443 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:40:23,864 Epoch: [77][0/500] Time 0.038 (0.038) Data 0.302 (0.302) Loss 0.0881 (0.0881) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:40:24,180 Epoch: [77][10/500] Time 0.027 (0.029) Data 0.003 (0.030) Loss 0.0691 (0.0786) Prec@1 90.000 (88.500) Prec@5 98.000 (98.000) +2022-11-14 13:40:24,499 Epoch: [77][20/500] Time 0.027 (0.028) Data 0.003 (0.017) Loss 0.0828 (0.0800) Prec@1 83.000 (86.667) Prec@5 100.000 (98.667) +2022-11-14 13:40:24,835 Epoch: [77][30/500] Time 0.040 (0.028) Data 0.002 (0.012) Loss 0.1096 (0.0874) Prec@1 81.000 (85.250) Prec@5 100.000 (99.000) +2022-11-14 13:40:25,461 Epoch: [77][40/500] Time 0.047 (0.035) Data 0.003 (0.010) Loss 0.0815 (0.0862) Prec@1 86.000 (85.400) Prec@5 98.000 (98.800) +2022-11-14 13:40:26,107 Epoch: [77][50/500] Time 0.070 (0.039) Data 0.002 (0.009) Loss 0.0928 (0.0873) Prec@1 79.000 (84.333) Prec@5 97.000 (98.500) +2022-11-14 13:40:26,719 Epoch: [77][60/500] Time 0.058 (0.042) Data 0.002 (0.008) Loss 0.0861 (0.0872) Prec@1 84.000 (84.286) Prec@5 100.000 (98.714) +2022-11-14 13:40:27,359 Epoch: [77][70/500] Time 0.059 (0.044) Data 0.003 (0.007) Loss 0.1218 (0.0915) Prec@1 79.000 (83.625) Prec@5 96.000 (98.375) +2022-11-14 13:40:28,038 Epoch: [77][80/500] Time 0.062 (0.046) Data 0.003 (0.006) Loss 0.0887 (0.0912) Prec@1 81.000 (83.333) Prec@5 98.000 (98.333) +2022-11-14 13:40:28,687 Epoch: [77][90/500] Time 0.067 (0.047) Data 0.002 (0.006) Loss 0.0742 (0.0895) Prec@1 89.000 (83.900) Prec@5 100.000 (98.500) +2022-11-14 13:40:29,336 Epoch: [77][100/500] Time 0.066 (0.049) Data 0.002 (0.006) Loss 0.0821 (0.0888) Prec@1 86.000 (84.091) Prec@5 99.000 (98.545) +2022-11-14 13:40:29,983 Epoch: [77][110/500] Time 0.059 (0.049) Data 0.003 (0.005) Loss 0.1073 (0.0904) Prec@1 81.000 (83.833) Prec@5 96.000 (98.333) +2022-11-14 13:40:30,647 Epoch: [77][120/500] Time 0.063 (0.050) Data 0.002 (0.005) Loss 0.0587 (0.0879) Prec@1 91.000 (84.385) Prec@5 100.000 (98.462) +2022-11-14 13:40:31,292 Epoch: [77][130/500] Time 0.052 (0.051) Data 0.002 (0.005) Loss 0.0898 (0.0881) Prec@1 84.000 (84.357) Prec@5 98.000 (98.429) +2022-11-14 13:40:31,927 Epoch: [77][140/500] Time 0.053 (0.051) Data 0.003 (0.005) Loss 0.1164 (0.0900) Prec@1 80.000 (84.067) Prec@5 100.000 (98.533) +2022-11-14 13:40:32,592 Epoch: [77][150/500] Time 0.066 (0.052) Data 0.002 (0.005) Loss 0.0999 (0.0906) Prec@1 81.000 (83.875) Prec@5 99.000 (98.562) +2022-11-14 13:40:33,235 Epoch: [77][160/500] Time 0.059 (0.052) Data 0.002 (0.004) Loss 0.0864 (0.0903) Prec@1 85.000 (83.941) Prec@5 99.000 (98.588) +2022-11-14 13:40:33,867 Epoch: [77][170/500] Time 0.060 (0.052) Data 0.003 (0.004) Loss 0.0976 (0.0907) Prec@1 84.000 (83.944) Prec@5 99.000 (98.611) +2022-11-14 13:40:34,524 Epoch: [77][180/500] Time 0.065 (0.053) Data 0.002 (0.004) Loss 0.0784 (0.0901) Prec@1 88.000 (84.158) Prec@5 99.000 (98.632) +2022-11-14 13:40:35,159 Epoch: [77][190/500] Time 0.065 (0.053) Data 0.002 (0.004) Loss 0.0903 (0.0901) Prec@1 87.000 (84.300) Prec@5 99.000 (98.650) +2022-11-14 13:40:35,780 Epoch: [77][200/500] Time 0.063 (0.053) Data 0.002 (0.004) Loss 0.1079 (0.0909) Prec@1 81.000 (84.143) Prec@5 98.000 (98.619) +2022-11-14 13:40:36,349 Epoch: [77][210/500] Time 0.048 (0.053) Data 0.003 (0.004) Loss 0.0704 (0.0900) Prec@1 88.000 (84.318) Prec@5 99.000 (98.636) +2022-11-14 13:40:36,930 Epoch: [77][220/500] Time 0.052 (0.053) Data 0.002 (0.004) Loss 0.0857 (0.0898) Prec@1 83.000 (84.261) Prec@5 99.000 (98.652) +2022-11-14 13:40:37,600 Epoch: [77][230/500] Time 0.065 (0.053) Data 0.002 (0.004) Loss 0.0903 (0.0898) Prec@1 82.000 (84.167) Prec@5 99.000 (98.667) +2022-11-14 13:40:38,250 Epoch: [77][240/500] Time 0.067 (0.053) Data 0.003 (0.004) Loss 0.1142 (0.0908) Prec@1 80.000 (84.000) Prec@5 99.000 (98.680) +2022-11-14 13:40:38,875 Epoch: [77][250/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0745 (0.0902) Prec@1 88.000 (84.154) Prec@5 100.000 (98.731) +2022-11-14 13:40:39,451 Epoch: [77][260/500] Time 0.045 (0.053) Data 0.003 (0.004) Loss 0.0779 (0.0897) Prec@1 83.000 (84.111) Prec@5 100.000 (98.778) +2022-11-14 13:40:40,027 Epoch: [77][270/500] Time 0.055 (0.053) Data 0.003 (0.004) Loss 0.0767 (0.0893) Prec@1 88.000 (84.250) Prec@5 99.000 (98.786) +2022-11-14 13:40:40,745 Epoch: [77][280/500] Time 0.066 (0.053) Data 0.002 (0.004) Loss 0.0907 (0.0893) Prec@1 87.000 (84.345) Prec@5 99.000 (98.793) +2022-11-14 13:40:41,481 Epoch: [77][290/500] Time 0.066 (0.054) Data 0.005 (0.004) Loss 0.1205 (0.0904) Prec@1 78.000 (84.133) Prec@5 98.000 (98.767) +2022-11-14 13:40:42,500 Epoch: [77][300/500] Time 0.094 (0.055) Data 0.010 (0.004) Loss 0.1162 (0.0912) Prec@1 80.000 (84.000) Prec@5 98.000 (98.742) +2022-11-14 13:40:43,177 Epoch: [77][310/500] Time 0.069 (0.055) Data 0.004 (0.004) Loss 0.0902 (0.0912) Prec@1 87.000 (84.094) Prec@5 97.000 (98.688) +2022-11-14 13:40:43,934 Epoch: [77][320/500] Time 0.056 (0.056) Data 0.004 (0.004) Loss 0.0883 (0.0911) Prec@1 86.000 (84.152) Prec@5 98.000 (98.667) +2022-11-14 13:40:44,572 Epoch: [77][330/500] Time 0.063 (0.056) Data 0.002 (0.004) Loss 0.0735 (0.0906) Prec@1 90.000 (84.324) Prec@5 99.000 (98.676) +2022-11-14 13:40:45,138 Epoch: [77][340/500] Time 0.049 (0.056) Data 0.003 (0.004) Loss 0.0657 (0.0898) Prec@1 90.000 (84.486) Prec@5 100.000 (98.714) +2022-11-14 13:40:45,759 Epoch: [77][350/500] Time 0.053 (0.056) Data 0.002 (0.004) Loss 0.1013 (0.0902) Prec@1 84.000 (84.472) Prec@5 98.000 (98.694) +2022-11-14 13:40:46,315 Epoch: [77][360/500] Time 0.047 (0.055) Data 0.005 (0.004) Loss 0.1302 (0.0912) Prec@1 78.000 (84.297) Prec@5 100.000 (98.730) +2022-11-14 13:40:46,927 Epoch: [77][370/500] Time 0.061 (0.056) Data 0.004 (0.004) Loss 0.1068 (0.0917) Prec@1 84.000 (84.289) Prec@5 98.000 (98.711) +2022-11-14 13:40:47,474 Epoch: [77][380/500] Time 0.045 (0.055) Data 0.005 (0.004) Loss 0.1169 (0.0923) Prec@1 81.000 (84.205) Prec@5 98.000 (98.692) +2022-11-14 13:40:48,075 Epoch: [77][390/500] Time 0.051 (0.055) Data 0.003 (0.004) Loss 0.0854 (0.0921) Prec@1 86.000 (84.250) Prec@5 99.000 (98.700) +2022-11-14 13:40:48,718 Epoch: [77][400/500] Time 0.049 (0.055) Data 0.003 (0.004) Loss 0.0892 (0.0921) Prec@1 86.000 (84.293) Prec@5 100.000 (98.732) +2022-11-14 13:40:49,321 Epoch: [77][410/500] Time 0.035 (0.055) Data 0.008 (0.004) Loss 0.1081 (0.0924) Prec@1 84.000 (84.286) Prec@5 99.000 (98.738) +2022-11-14 13:40:49,912 Epoch: [77][420/500] Time 0.048 (0.055) Data 0.003 (0.004) Loss 0.0856 (0.0923) Prec@1 86.000 (84.326) Prec@5 99.000 (98.744) +2022-11-14 13:40:50,545 Epoch: [77][430/500] Time 0.057 (0.055) Data 0.002 (0.004) Loss 0.1260 (0.0930) Prec@1 77.000 (84.159) Prec@5 95.000 (98.659) +2022-11-14 13:40:51,142 Epoch: [77][440/500] Time 0.055 (0.055) Data 0.003 (0.004) Loss 0.1092 (0.0934) Prec@1 81.000 (84.089) Prec@5 99.000 (98.667) +2022-11-14 13:40:51,749 Epoch: [77][450/500] Time 0.059 (0.055) Data 0.004 (0.004) Loss 0.1002 (0.0935) Prec@1 82.000 (84.043) Prec@5 98.000 (98.652) +2022-11-14 13:40:52,372 Epoch: [77][460/500] Time 0.065 (0.055) Data 0.002 (0.004) Loss 0.0989 (0.0937) Prec@1 82.000 (84.000) Prec@5 100.000 (98.681) +2022-11-14 13:40:53,012 Epoch: [77][470/500] Time 0.044 (0.055) Data 0.003 (0.004) Loss 0.0989 (0.0938) Prec@1 83.000 (83.979) Prec@5 99.000 (98.688) +2022-11-14 13:40:53,573 Epoch: [77][480/500] Time 0.046 (0.055) Data 0.003 (0.004) Loss 0.1125 (0.0942) Prec@1 79.000 (83.878) Prec@5 99.000 (98.694) +2022-11-14 13:40:54,199 Epoch: [77][490/500] Time 0.070 (0.055) Data 0.003 (0.004) Loss 0.0759 (0.0938) Prec@1 88.000 (83.960) Prec@5 100.000 (98.720) +2022-11-14 13:40:54,885 Epoch: [77][499/500] Time 0.066 (0.055) Data 0.002 (0.004) Loss 0.1261 (0.0944) Prec@1 79.000 (83.863) Prec@5 99.000 (98.725) +2022-11-14 13:40:55,306 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0880 (0.0880) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:40:55,320 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0999 (0.0939) Prec@1 84.000 (83.500) Prec@5 100.000 (100.000) +2022-11-14 13:40:55,336 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1052 (0.0977) Prec@1 83.000 (83.333) Prec@5 97.000 (99.000) +2022-11-14 13:40:55,359 Test: [3/100] Model Time 0.015 (0.012) Loss Time 0.000 (0.000) Loss 0.1103 (0.1008) Prec@1 77.000 (81.750) Prec@5 98.000 (98.750) +2022-11-14 13:40:55,374 Test: [4/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.1401 (0.1087) Prec@1 77.000 (80.800) Prec@5 98.000 (98.600) +2022-11-14 13:40:55,383 Test: [5/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0889 (0.1054) Prec@1 84.000 (81.333) Prec@5 98.000 (98.500) +2022-11-14 13:40:55,392 Test: [6/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0953 (0.1040) Prec@1 83.000 (81.571) Prec@5 99.000 (98.571) +2022-11-14 13:40:55,404 Test: [7/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1563 (0.1105) Prec@1 71.000 (80.250) Prec@5 96.000 (98.250) +2022-11-14 13:40:55,416 Test: [8/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1159 (0.1111) Prec@1 80.000 (80.222) Prec@5 99.000 (98.333) +2022-11-14 13:40:55,428 Test: [9/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1047 (0.1105) Prec@1 81.000 (80.300) Prec@5 97.000 (98.200) +2022-11-14 13:40:55,441 Test: [10/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0981 (0.1093) Prec@1 84.000 (80.636) Prec@5 100.000 (98.364) +2022-11-14 13:40:55,453 Test: [11/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0907 (0.1078) Prec@1 84.000 (80.917) Prec@5 99.000 (98.417) +2022-11-14 13:40:55,463 Test: [12/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0741 (0.1052) Prec@1 85.000 (81.231) Prec@5 99.000 (98.462) +2022-11-14 13:40:55,474 Test: [13/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0691 (0.1026) Prec@1 90.000 (81.857) Prec@5 100.000 (98.571) +2022-11-14 13:40:55,484 Test: [14/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0953 (0.1021) Prec@1 83.000 (81.933) Prec@5 99.000 (98.600) +2022-11-14 13:40:55,494 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1157 (0.1030) Prec@1 78.000 (81.688) Prec@5 100.000 (98.688) +2022-11-14 13:40:55,506 Test: [16/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0789 (0.1016) Prec@1 88.000 (82.059) Prec@5 99.000 (98.706) +2022-11-14 13:40:55,517 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1117 (0.1021) Prec@1 80.000 (81.944) Prec@5 99.000 (98.722) +2022-11-14 13:40:55,529 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1017 (0.1021) Prec@1 82.000 (81.947) Prec@5 98.000 (98.684) +2022-11-14 13:40:55,540 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1054 (0.1023) Prec@1 84.000 (82.050) Prec@5 98.000 (98.650) +2022-11-14 13:40:55,553 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1346 (0.1038) Prec@1 76.000 (81.762) Prec@5 99.000 (98.667) +2022-11-14 13:40:55,565 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1084 (0.1040) Prec@1 83.000 (81.818) Prec@5 98.000 (98.636) +2022-11-14 13:40:55,576 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1346 (0.1053) Prec@1 77.000 (81.609) Prec@5 98.000 (98.609) +2022-11-14 13:40:55,589 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.1051) Prec@1 79.000 (81.500) Prec@5 99.000 (98.625) +2022-11-14 13:40:55,599 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1333 (0.1063) Prec@1 79.000 (81.400) Prec@5 98.000 (98.600) +2022-11-14 13:40:55,609 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1533 (0.1081) Prec@1 73.000 (81.077) Prec@5 95.000 (98.462) +2022-11-14 13:40:55,623 Test: [26/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.1072) Prec@1 85.000 (81.222) Prec@5 99.000 (98.481) +2022-11-14 13:40:55,635 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.1066) Prec@1 87.000 (81.429) Prec@5 100.000 (98.536) +2022-11-14 13:40:55,645 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1111 (0.1068) Prec@1 81.000 (81.414) Prec@5 96.000 (98.448) +2022-11-14 13:40:55,658 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1141 (0.1070) Prec@1 81.000 (81.400) Prec@5 98.000 (98.433) +2022-11-14 13:40:55,673 Test: [30/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.1068) Prec@1 82.000 (81.419) Prec@5 100.000 (98.484) +2022-11-14 13:40:55,687 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1192 (0.1072) Prec@1 79.000 (81.344) Prec@5 100.000 (98.531) +2022-11-14 13:40:55,699 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1065 (0.1072) Prec@1 83.000 (81.394) Prec@5 98.000 (98.515) +2022-11-14 13:40:55,710 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1222 (0.1076) Prec@1 77.000 (81.265) Prec@5 97.000 (98.471) +2022-11-14 13:40:55,722 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1353 (0.1084) Prec@1 76.000 (81.114) Prec@5 95.000 (98.371) +2022-11-14 13:40:55,734 Test: [35/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1092 (0.1084) Prec@1 82.000 (81.139) Prec@5 100.000 (98.417) +2022-11-14 13:40:55,747 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1246 (0.1089) Prec@1 77.000 (81.027) Prec@5 98.000 (98.405) +2022-11-14 13:40:55,759 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.1088) Prec@1 83.000 (81.079) Prec@5 99.000 (98.421) +2022-11-14 13:40:55,771 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1024 (0.1087) Prec@1 80.000 (81.051) Prec@5 99.000 (98.436) +2022-11-14 13:40:55,783 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0919 (0.1082) Prec@1 84.000 (81.125) Prec@5 100.000 (98.475) +2022-11-14 13:40:55,798 Test: [40/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1000 (0.1080) Prec@1 83.000 (81.171) Prec@5 97.000 (98.439) +2022-11-14 13:40:55,813 Test: [41/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.1079) Prec@1 83.000 (81.214) Prec@5 99.000 (98.452) +2022-11-14 13:40:55,826 Test: [42/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0849 (0.1073) Prec@1 87.000 (81.349) Prec@5 98.000 (98.442) +2022-11-14 13:40:55,841 Test: [43/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.1070) Prec@1 83.000 (81.386) Prec@5 99.000 (98.455) +2022-11-14 13:40:55,855 Test: [44/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1147 (0.1071) Prec@1 77.000 (81.289) Prec@5 98.000 (98.444) +2022-11-14 13:40:55,866 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1145 (0.1073) Prec@1 79.000 (81.239) Prec@5 97.000 (98.413) +2022-11-14 13:40:55,877 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0970 (0.1071) Prec@1 83.000 (81.277) Prec@5 99.000 (98.426) +2022-11-14 13:40:55,887 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1065 (0.1071) Prec@1 82.000 (81.292) Prec@5 98.000 (98.417) +2022-11-14 13:40:55,904 Test: [48/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.1063) Prec@1 88.000 (81.429) Prec@5 98.000 (98.408) +2022-11-14 13:40:55,916 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1184 (0.1065) Prec@1 79.000 (81.380) Prec@5 97.000 (98.380) +2022-11-14 13:40:55,927 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.1062) Prec@1 83.000 (81.412) Prec@5 98.000 (98.373) +2022-11-14 13:40:55,938 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1166 (0.1064) Prec@1 77.000 (81.327) Prec@5 99.000 (98.385) +2022-11-14 13:40:55,949 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1221 (0.1067) Prec@1 80.000 (81.302) Prec@5 100.000 (98.415) +2022-11-14 13:40:55,961 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.1066) Prec@1 78.000 (81.241) Prec@5 98.000 (98.407) +2022-11-14 13:40:55,974 Test: [54/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1183 (0.1069) Prec@1 79.000 (81.200) Prec@5 99.000 (98.418) +2022-11-14 13:40:55,991 Test: [55/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.1067) Prec@1 82.000 (81.214) Prec@5 99.000 (98.429) +2022-11-14 13:40:56,005 Test: [56/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1000 (0.1066) Prec@1 80.000 (81.193) Prec@5 100.000 (98.456) +2022-11-14 13:40:56,018 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1115 (0.1067) Prec@1 83.000 (81.224) Prec@5 99.000 (98.466) +2022-11-14 13:40:56,032 Test: [58/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1424 (0.1073) Prec@1 71.000 (81.051) Prec@5 99.000 (98.475) +2022-11-14 13:40:56,044 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.1070) Prec@1 82.000 (81.067) Prec@5 99.000 (98.483) +2022-11-14 13:40:56,058 Test: [60/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1022 (0.1069) Prec@1 85.000 (81.131) Prec@5 99.000 (98.492) +2022-11-14 13:40:56,072 Test: [61/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1193 (0.1071) Prec@1 81.000 (81.129) Prec@5 98.000 (98.484) +2022-11-14 13:40:56,087 Test: [62/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0826 (0.1067) Prec@1 86.000 (81.206) Prec@5 99.000 (98.492) +2022-11-14 13:40:56,105 Test: [63/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0651 (0.1061) Prec@1 91.000 (81.359) Prec@5 100.000 (98.516) +2022-11-14 13:40:56,122 Test: [64/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1075 (0.1061) Prec@1 82.000 (81.369) Prec@5 96.000 (98.477) +2022-11-14 13:40:56,141 Test: [65/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.1205 (0.1063) Prec@1 77.000 (81.303) Prec@5 97.000 (98.455) +2022-11-14 13:40:56,159 Test: [66/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.1058) Prec@1 87.000 (81.388) Prec@5 100.000 (98.478) +2022-11-14 13:40:56,179 Test: [67/100] Model Time 0.016 (0.010) Loss Time 0.000 (0.000) Loss 0.1233 (0.1060) Prec@1 76.000 (81.309) Prec@5 97.000 (98.456) +2022-11-14 13:40:56,198 Test: [68/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.1168 (0.1062) Prec@1 77.000 (81.246) Prec@5 99.000 (98.464) +2022-11-14 13:40:56,213 Test: [69/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1428 (0.1067) Prec@1 73.000 (81.129) Prec@5 98.000 (98.457) +2022-11-14 13:40:56,231 Test: [70/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.1064) Prec@1 86.000 (81.197) Prec@5 99.000 (98.465) +2022-11-14 13:40:56,249 Test: [71/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.1060) Prec@1 87.000 (81.278) Prec@5 99.000 (98.472) +2022-11-14 13:40:56,269 Test: [72/100] Model Time 0.016 (0.010) Loss Time 0.000 (0.000) Loss 0.0884 (0.1058) Prec@1 83.000 (81.301) Prec@5 100.000 (98.493) +2022-11-14 13:40:56,290 Test: [73/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.0820 (0.1055) Prec@1 87.000 (81.378) Prec@5 100.000 (98.514) +2022-11-14 13:40:56,307 Test: [74/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1234 (0.1057) Prec@1 77.000 (81.320) Prec@5 100.000 (98.533) +2022-11-14 13:40:56,324 Test: [75/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0947 (0.1056) Prec@1 82.000 (81.329) Prec@5 99.000 (98.539) +2022-11-14 13:40:56,340 Test: [76/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1103 (0.1056) Prec@1 81.000 (81.325) Prec@5 98.000 (98.532) +2022-11-14 13:40:56,357 Test: [77/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0950 (0.1055) Prec@1 82.000 (81.333) Prec@5 99.000 (98.538) +2022-11-14 13:40:56,374 Test: [78/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1265 (0.1058) Prec@1 79.000 (81.304) Prec@5 99.000 (98.544) +2022-11-14 13:40:56,391 Test: [79/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1010 (0.1057) Prec@1 80.000 (81.287) Prec@5 99.000 (98.550) +2022-11-14 13:40:56,407 Test: [80/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1065 (0.1057) Prec@1 81.000 (81.284) Prec@5 100.000 (98.568) +2022-11-14 13:40:56,425 Test: [81/100] Model Time 0.015 (0.011) Loss Time 0.000 (0.000) Loss 0.0828 (0.1054) Prec@1 87.000 (81.354) Prec@5 99.000 (98.573) +2022-11-14 13:40:56,442 Test: [82/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0981 (0.1053) Prec@1 84.000 (81.386) Prec@5 98.000 (98.566) +2022-11-14 13:40:56,458 Test: [83/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1074 (0.1054) Prec@1 83.000 (81.405) Prec@5 99.000 (98.571) +2022-11-14 13:40:56,478 Test: [84/100] Model Time 0.015 (0.011) Loss Time 0.000 (0.000) Loss 0.1303 (0.1057) Prec@1 76.000 (81.341) Prec@5 97.000 (98.553) +2022-11-14 13:40:56,496 Test: [85/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1090 (0.1057) Prec@1 78.000 (81.302) Prec@5 98.000 (98.547) +2022-11-14 13:40:56,511 Test: [86/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0954 (0.1056) Prec@1 82.000 (81.310) Prec@5 99.000 (98.552) +2022-11-14 13:40:56,527 Test: [87/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1126 (0.1057) Prec@1 80.000 (81.295) Prec@5 98.000 (98.545) +2022-11-14 13:40:56,545 Test: [88/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1289 (0.1059) Prec@1 76.000 (81.236) Prec@5 99.000 (98.551) +2022-11-14 13:40:56,564 Test: [89/100] Model Time 0.015 (0.011) Loss Time 0.000 (0.000) Loss 0.1233 (0.1061) Prec@1 80.000 (81.222) Prec@5 98.000 (98.544) +2022-11-14 13:40:56,581 Test: [90/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1298 (0.1064) Prec@1 78.000 (81.187) Prec@5 98.000 (98.538) +2022-11-14 13:40:56,597 Test: [91/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0739 (0.1060) Prec@1 86.000 (81.239) Prec@5 96.000 (98.511) +2022-11-14 13:40:56,614 Test: [92/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1268 (0.1062) Prec@1 75.000 (81.172) Prec@5 99.000 (98.516) +2022-11-14 13:40:56,627 Test: [93/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0969 (0.1061) Prec@1 83.000 (81.191) Prec@5 99.000 (98.521) +2022-11-14 13:40:56,642 Test: [94/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1130 (0.1062) Prec@1 81.000 (81.189) Prec@5 100.000 (98.537) +2022-11-14 13:40:56,660 Test: [95/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.1178 (0.1063) Prec@1 77.000 (81.146) Prec@5 98.000 (98.531) +2022-11-14 13:40:56,677 Test: [96/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0847 (0.1061) Prec@1 86.000 (81.196) Prec@5 99.000 (98.536) +2022-11-14 13:40:56,691 Test: [97/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1190 (0.1062) Prec@1 82.000 (81.204) Prec@5 99.000 (98.541) +2022-11-14 13:40:56,707 Test: [98/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.1151 (0.1063) Prec@1 82.000 (81.212) Prec@5 98.000 (98.535) +2022-11-14 13:40:56,722 Test: [99/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0924 (0.1062) Prec@1 85.000 (81.250) Prec@5 100.000 (98.550) +2022-11-14 13:40:56,811 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:40:57,213 Epoch: [78][0/500] Time 0.030 (0.030) Data 0.302 (0.302) Loss 0.0976 (0.0976) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:40:57,515 Epoch: [78][10/500] Time 0.024 (0.027) Data 0.003 (0.030) Loss 0.0769 (0.0873) Prec@1 86.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:40:57,837 Epoch: [78][20/500] Time 0.035 (0.028) Data 0.003 (0.017) Loss 0.1333 (0.1026) Prec@1 76.000 (82.000) Prec@5 98.000 (98.667) +2022-11-14 13:40:58,173 Epoch: [78][30/500] Time 0.033 (0.029) Data 0.003 (0.012) Loss 0.0832 (0.0978) Prec@1 87.000 (83.250) Prec@5 98.000 (98.500) +2022-11-14 13:40:58,523 Epoch: [78][40/500] Time 0.028 (0.029) Data 0.003 (0.010) Loss 0.0683 (0.0919) Prec@1 88.000 (84.200) Prec@5 97.000 (98.200) +2022-11-14 13:40:58,877 Epoch: [78][50/500] Time 0.028 (0.030) Data 0.003 (0.009) Loss 0.0831 (0.0904) Prec@1 87.000 (84.667) Prec@5 98.000 (98.167) +2022-11-14 13:40:59,218 Epoch: [78][60/500] Time 0.025 (0.030) Data 0.003 (0.008) Loss 0.1016 (0.0920) Prec@1 82.000 (84.286) Prec@5 98.000 (98.143) +2022-11-14 13:40:59,583 Epoch: [78][70/500] Time 0.033 (0.030) Data 0.005 (0.007) Loss 0.0788 (0.0904) Prec@1 87.000 (84.625) Prec@5 100.000 (98.375) +2022-11-14 13:40:59,936 Epoch: [78][80/500] Time 0.031 (0.030) Data 0.005 (0.007) Loss 0.1045 (0.0919) Prec@1 80.000 (84.111) Prec@5 98.000 (98.333) +2022-11-14 13:41:00,262 Epoch: [78][90/500] Time 0.031 (0.030) Data 0.003 (0.006) Loss 0.0587 (0.0886) Prec@1 90.000 (84.700) Prec@5 98.000 (98.300) +2022-11-14 13:41:00,618 Epoch: [78][100/500] Time 0.027 (0.030) Data 0.003 (0.006) Loss 0.0997 (0.0896) Prec@1 84.000 (84.636) Prec@5 97.000 (98.182) +2022-11-14 13:41:00,952 Epoch: [78][110/500] Time 0.031 (0.030) Data 0.002 (0.006) Loss 0.1064 (0.0910) Prec@1 82.000 (84.417) Prec@5 100.000 (98.333) +2022-11-14 13:41:01,400 Epoch: [78][120/500] Time 0.042 (0.031) Data 0.003 (0.006) Loss 0.0760 (0.0899) Prec@1 90.000 (84.846) Prec@5 98.000 (98.308) +2022-11-14 13:41:01,849 Epoch: [78][130/500] Time 0.048 (0.032) Data 0.003 (0.005) Loss 0.0661 (0.0882) Prec@1 89.000 (85.143) Prec@5 100.000 (98.429) +2022-11-14 13:41:02,293 Epoch: [78][140/500] Time 0.043 (0.032) Data 0.003 (0.005) Loss 0.0860 (0.0880) Prec@1 83.000 (85.000) Prec@5 100.000 (98.533) +2022-11-14 13:41:02,764 Epoch: [78][150/500] Time 0.040 (0.033) Data 0.002 (0.005) Loss 0.0886 (0.0881) Prec@1 87.000 (85.125) Prec@5 99.000 (98.562) +2022-11-14 13:41:03,227 Epoch: [78][160/500] Time 0.043 (0.034) Data 0.003 (0.005) Loss 0.1118 (0.0895) Prec@1 81.000 (84.882) Prec@5 97.000 (98.471) +2022-11-14 13:41:03,674 Epoch: [78][170/500] Time 0.044 (0.034) Data 0.003 (0.005) Loss 0.0626 (0.0880) Prec@1 90.000 (85.167) Prec@5 100.000 (98.556) +2022-11-14 13:41:04,116 Epoch: [78][180/500] Time 0.043 (0.034) Data 0.002 (0.005) Loss 0.1442 (0.0909) Prec@1 76.000 (84.684) Prec@5 97.000 (98.474) +2022-11-14 13:41:04,568 Epoch: [78][190/500] Time 0.043 (0.034) Data 0.003 (0.005) Loss 0.0965 (0.0912) Prec@1 80.000 (84.450) Prec@5 99.000 (98.500) +2022-11-14 13:41:05,019 Epoch: [78][200/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0882 (0.0911) Prec@1 85.000 (84.476) Prec@5 100.000 (98.571) +2022-11-14 13:41:05,442 Epoch: [78][210/500] Time 0.031 (0.035) Data 0.002 (0.004) Loss 0.0929 (0.0911) Prec@1 86.000 (84.545) Prec@5 98.000 (98.545) +2022-11-14 13:41:05,834 Epoch: [78][220/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0677 (0.0901) Prec@1 87.000 (84.652) Prec@5 99.000 (98.565) +2022-11-14 13:41:06,240 Epoch: [78][230/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.1032 (0.0907) Prec@1 81.000 (84.500) Prec@5 98.000 (98.542) +2022-11-14 13:41:06,650 Epoch: [78][240/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.1122 (0.0915) Prec@1 82.000 (84.400) Prec@5 97.000 (98.480) +2022-11-14 13:41:07,073 Epoch: [78][250/500] Time 0.029 (0.035) Data 0.002 (0.004) Loss 0.1149 (0.0924) Prec@1 76.000 (84.077) Prec@5 99.000 (98.500) +2022-11-14 13:41:07,473 Epoch: [78][260/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0773 (0.0919) Prec@1 90.000 (84.296) Prec@5 98.000 (98.481) +2022-11-14 13:41:07,915 Epoch: [78][270/500] Time 0.028 (0.035) Data 0.002 (0.004) Loss 0.0911 (0.0918) Prec@1 84.000 (84.286) Prec@5 100.000 (98.536) +2022-11-14 13:41:08,384 Epoch: [78][280/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.1041 (0.0923) Prec@1 79.000 (84.103) Prec@5 100.000 (98.586) +2022-11-14 13:41:08,823 Epoch: [78][290/500] Time 0.045 (0.036) Data 0.002 (0.004) Loss 0.1169 (0.0931) Prec@1 77.000 (83.867) Prec@5 97.000 (98.533) +2022-11-14 13:41:09,272 Epoch: [78][300/500] Time 0.082 (0.036) Data 0.002 (0.004) Loss 0.1484 (0.0949) Prec@1 75.000 (83.581) Prec@5 95.000 (98.419) +2022-11-14 13:41:09,669 Epoch: [78][310/500] Time 0.040 (0.036) Data 0.002 (0.004) Loss 0.0722 (0.0942) Prec@1 86.000 (83.656) Prec@5 99.000 (98.438) +2022-11-14 13:41:10,154 Epoch: [78][320/500] Time 0.068 (0.036) Data 0.002 (0.004) Loss 0.0943 (0.0942) Prec@1 83.000 (83.636) Prec@5 98.000 (98.424) +2022-11-14 13:41:10,583 Epoch: [78][330/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.1168 (0.0948) Prec@1 78.000 (83.471) Prec@5 99.000 (98.441) +2022-11-14 13:41:11,019 Epoch: [78][340/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.1028 (0.0951) Prec@1 84.000 (83.486) Prec@5 97.000 (98.400) +2022-11-14 13:41:11,460 Epoch: [78][350/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0947 (0.0950) Prec@1 85.000 (83.528) Prec@5 99.000 (98.417) +2022-11-14 13:41:11,900 Epoch: [78][360/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.1152 (0.0956) Prec@1 82.000 (83.486) Prec@5 98.000 (98.405) +2022-11-14 13:41:12,345 Epoch: [78][370/500] Time 0.030 (0.036) Data 0.002 (0.003) Loss 0.0542 (0.0945) Prec@1 90.000 (83.658) Prec@5 100.000 (98.447) +2022-11-14 13:41:12,798 Epoch: [78][380/500] Time 0.066 (0.037) Data 0.002 (0.003) Loss 0.1215 (0.0952) Prec@1 78.000 (83.513) Prec@5 98.000 (98.436) +2022-11-14 13:41:13,226 Epoch: [78][390/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0921 (0.0951) Prec@1 84.000 (83.525) Prec@5 100.000 (98.475) +2022-11-14 13:41:13,622 Epoch: [78][400/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0821 (0.0948) Prec@1 87.000 (83.610) Prec@5 100.000 (98.512) +2022-11-14 13:41:14,065 Epoch: [78][410/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0820 (0.0945) Prec@1 87.000 (83.690) Prec@5 99.000 (98.524) +2022-11-14 13:41:14,514 Epoch: [78][420/500] Time 0.036 (0.037) Data 0.001 (0.003) Loss 0.1115 (0.0949) Prec@1 83.000 (83.674) Prec@5 100.000 (98.558) +2022-11-14 13:41:14,968 Epoch: [78][430/500] Time 0.029 (0.037) Data 0.002 (0.003) Loss 0.1081 (0.0952) Prec@1 80.000 (83.591) Prec@5 100.000 (98.591) +2022-11-14 13:41:15,393 Epoch: [78][440/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1230 (0.0958) Prec@1 79.000 (83.489) Prec@5 100.000 (98.622) +2022-11-14 13:41:15,922 Epoch: [78][450/500] Time 0.064 (0.037) Data 0.002 (0.003) Loss 0.1190 (0.0963) Prec@1 80.000 (83.413) Prec@5 100.000 (98.652) +2022-11-14 13:41:16,410 Epoch: [78][460/500] Time 0.056 (0.037) Data 0.002 (0.003) Loss 0.0988 (0.0964) Prec@1 80.000 (83.340) Prec@5 100.000 (98.681) +2022-11-14 13:41:16,804 Epoch: [78][470/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0766 (0.0960) Prec@1 84.000 (83.354) Prec@5 100.000 (98.708) +2022-11-14 13:41:17,358 Epoch: [78][480/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0774 (0.0956) Prec@1 86.000 (83.408) Prec@5 100.000 (98.735) +2022-11-14 13:41:17,806 Epoch: [78][490/500] Time 0.029 (0.037) Data 0.002 (0.003) Loss 0.0842 (0.0953) Prec@1 83.000 (83.400) Prec@5 100.000 (98.760) +2022-11-14 13:41:18,166 Epoch: [78][499/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.1272 (0.0960) Prec@1 75.000 (83.235) Prec@5 98.000 (98.745) +2022-11-14 13:41:18,475 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0935 (0.0935) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:41:18,487 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1089 (0.1012) Prec@1 80.000 (83.000) Prec@5 98.000 (98.000) +2022-11-14 13:41:18,499 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1216 (0.1080) Prec@1 80.000 (82.000) Prec@5 97.000 (97.667) +2022-11-14 13:41:18,511 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1255 (0.1124) Prec@1 79.000 (81.250) Prec@5 100.000 (98.250) +2022-11-14 13:41:18,519 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1084 (0.1116) Prec@1 81.000 (81.200) Prec@5 98.000 (98.200) +2022-11-14 13:41:18,527 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.1092) Prec@1 83.000 (81.500) Prec@5 99.000 (98.333) +2022-11-14 13:41:18,534 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1260 (0.1116) Prec@1 79.000 (81.143) Prec@5 95.000 (97.857) +2022-11-14 13:41:18,544 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1374 (0.1148) Prec@1 78.000 (80.750) Prec@5 95.000 (97.500) +2022-11-14 13:41:18,551 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1444 (0.1181) Prec@1 77.000 (80.333) Prec@5 98.000 (97.556) +2022-11-14 13:41:18,560 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.1166) Prec@1 82.000 (80.500) Prec@5 98.000 (97.600) +2022-11-14 13:41:18,569 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.1160) Prec@1 81.000 (80.545) Prec@5 96.000 (97.455) +2022-11-14 13:41:18,578 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1235 (0.1166) Prec@1 78.000 (80.333) Prec@5 99.000 (97.583) +2022-11-14 13:41:18,588 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.1160) Prec@1 77.000 (80.077) Prec@5 99.000 (97.692) +2022-11-14 13:41:18,597 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1284 (0.1169) Prec@1 77.000 (79.857) Prec@5 97.000 (97.643) +2022-11-14 13:41:18,606 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.1176) Prec@1 78.000 (79.733) Prec@5 99.000 (97.733) +2022-11-14 13:41:18,615 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1283 (0.1183) Prec@1 78.000 (79.625) Prec@5 96.000 (97.625) +2022-11-14 13:41:18,625 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.1181) Prec@1 85.000 (79.941) Prec@5 97.000 (97.588) +2022-11-14 13:41:18,634 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1440 (0.1196) Prec@1 74.000 (79.611) Prec@5 98.000 (97.611) +2022-11-14 13:41:18,644 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.1195) Prec@1 80.000 (79.632) Prec@5 98.000 (97.632) +2022-11-14 13:41:18,654 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1862 (0.1229) Prec@1 68.000 (79.050) Prec@5 95.000 (97.500) +2022-11-14 13:41:18,663 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.1225) Prec@1 83.000 (79.238) Prec@5 97.000 (97.476) +2022-11-14 13:41:18,675 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1400 (0.1233) Prec@1 79.000 (79.227) Prec@5 97.000 (97.455) +2022-11-14 13:41:18,686 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1305 (0.1236) Prec@1 74.000 (79.000) Prec@5 100.000 (97.565) +2022-11-14 13:41:18,698 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.1237) Prec@1 76.000 (78.875) Prec@5 100.000 (97.667) +2022-11-14 13:41:18,710 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1372 (0.1243) Prec@1 77.000 (78.800) Prec@5 97.000 (97.640) +2022-11-14 13:41:18,723 Test: [25/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1448 (0.1251) Prec@1 74.000 (78.615) Prec@5 97.000 (97.615) +2022-11-14 13:41:18,736 Test: [26/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.1238) Prec@1 83.000 (78.778) Prec@5 99.000 (97.667) +2022-11-14 13:41:18,749 Test: [27/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1334 (0.1241) Prec@1 76.000 (78.679) Prec@5 100.000 (97.750) +2022-11-14 13:41:18,763 Test: [28/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.1235) Prec@1 81.000 (78.759) Prec@5 97.000 (97.724) +2022-11-14 13:41:18,777 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.1231) Prec@1 81.000 (78.833) Prec@5 99.000 (97.767) +2022-11-14 13:41:18,788 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.1222) Prec@1 83.000 (78.968) Prec@5 99.000 (97.806) +2022-11-14 13:41:18,800 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.1214) Prec@1 82.000 (79.062) Prec@5 99.000 (97.844) +2022-11-14 13:41:18,810 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1206 (0.1214) Prec@1 80.000 (79.091) Prec@5 98.000 (97.848) +2022-11-14 13:41:18,820 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1524 (0.1223) Prec@1 73.000 (78.912) Prec@5 95.000 (97.765) +2022-11-14 13:41:18,830 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.1222) Prec@1 80.000 (78.943) Prec@5 97.000 (97.743) +2022-11-14 13:41:18,841 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.1215) Prec@1 83.000 (79.056) Prec@5 97.000 (97.722) +2022-11-14 13:41:18,851 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1251 (0.1216) Prec@1 82.000 (79.135) Prec@5 97.000 (97.703) +2022-11-14 13:41:18,861 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1582 (0.1226) Prec@1 69.000 (78.868) Prec@5 98.000 (97.711) +2022-11-14 13:41:18,871 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.1221) Prec@1 84.000 (79.000) Prec@5 99.000 (97.744) +2022-11-14 13:41:18,882 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.1215) Prec@1 84.000 (79.125) Prec@5 98.000 (97.750) +2022-11-14 13:41:18,891 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1383 (0.1219) Prec@1 78.000 (79.098) Prec@5 97.000 (97.732) +2022-11-14 13:41:18,901 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1236 (0.1220) Prec@1 78.000 (79.071) Prec@5 97.000 (97.714) +2022-11-14 13:41:18,911 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.1217) Prec@1 81.000 (79.116) Prec@5 97.000 (97.698) +2022-11-14 13:41:18,920 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.1212) Prec@1 81.000 (79.159) Prec@5 96.000 (97.659) +2022-11-14 13:41:18,930 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.1201) Prec@1 89.000 (79.378) Prec@5 99.000 (97.689) +2022-11-14 13:41:18,939 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1285 (0.1203) Prec@1 78.000 (79.348) Prec@5 99.000 (97.717) +2022-11-14 13:41:18,949 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.1200) Prec@1 80.000 (79.362) Prec@5 100.000 (97.766) +2022-11-14 13:41:18,958 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1623 (0.1209) Prec@1 71.000 (79.188) Prec@5 98.000 (97.771) +2022-11-14 13:41:18,967 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.1209) Prec@1 78.000 (79.163) Prec@5 99.000 (97.796) +2022-11-14 13:41:18,976 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1504 (0.1215) Prec@1 70.000 (78.980) Prec@5 99.000 (97.820) +2022-11-14 13:41:18,986 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1211) Prec@1 80.000 (79.000) Prec@5 97.000 (97.804) +2022-11-14 13:41:18,996 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1248 (0.1212) Prec@1 79.000 (79.000) Prec@5 96.000 (97.769) +2022-11-14 13:41:19,008 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.1209) Prec@1 80.000 (79.019) Prec@5 100.000 (97.811) +2022-11-14 13:41:19,020 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.1203) Prec@1 85.000 (79.130) Prec@5 99.000 (97.833) +2022-11-14 13:41:19,031 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1580 (0.1210) Prec@1 74.000 (79.036) Prec@5 99.000 (97.855) +2022-11-14 13:41:19,044 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.1206) Prec@1 86.000 (79.161) Prec@5 99.000 (97.875) +2022-11-14 13:41:19,058 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1415 (0.1209) Prec@1 77.000 (79.123) Prec@5 99.000 (97.895) +2022-11-14 13:41:19,071 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.1206) Prec@1 82.000 (79.172) Prec@5 98.000 (97.897) +2022-11-14 13:41:19,084 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1418 (0.1210) Prec@1 76.000 (79.119) Prec@5 100.000 (97.932) +2022-11-14 13:41:19,096 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1501 (0.1215) Prec@1 76.000 (79.067) Prec@5 97.000 (97.917) +2022-11-14 13:41:19,110 Test: [60/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1349 (0.1217) Prec@1 76.000 (79.016) Prec@5 99.000 (97.934) +2022-11-14 13:41:19,124 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.1213) Prec@1 84.000 (79.097) Prec@5 100.000 (97.968) +2022-11-14 13:41:19,136 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1244 (0.1214) Prec@1 80.000 (79.111) Prec@5 100.000 (98.000) +2022-11-14 13:41:19,148 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.1211) Prec@1 83.000 (79.172) Prec@5 99.000 (98.016) +2022-11-14 13:41:19,162 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1209) Prec@1 80.000 (79.185) Prec@5 98.000 (98.015) +2022-11-14 13:41:19,175 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1372 (0.1212) Prec@1 76.000 (79.136) Prec@5 97.000 (98.000) +2022-11-14 13:41:19,188 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.1209) Prec@1 79.000 (79.134) Prec@5 100.000 (98.030) +2022-11-14 13:41:19,200 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.1207) Prec@1 83.000 (79.191) Prec@5 98.000 (98.029) +2022-11-14 13:41:19,214 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1091 (0.1206) Prec@1 79.000 (79.188) Prec@5 98.000 (98.029) +2022-11-14 13:41:19,227 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1346 (0.1208) Prec@1 77.000 (79.157) Prec@5 98.000 (98.029) +2022-11-14 13:41:19,239 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1314 (0.1209) Prec@1 80.000 (79.169) Prec@5 96.000 (98.000) +2022-11-14 13:41:19,252 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1368 (0.1211) Prec@1 76.000 (79.125) Prec@5 99.000 (98.014) +2022-11-14 13:41:19,263 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.1208) Prec@1 84.000 (79.192) Prec@5 99.000 (98.027) +2022-11-14 13:41:19,278 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1147 (0.1208) Prec@1 79.000 (79.189) Prec@5 97.000 (98.014) +2022-11-14 13:41:19,295 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1383 (0.1210) Prec@1 78.000 (79.173) Prec@5 99.000 (98.027) +2022-11-14 13:41:19,316 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.1207) Prec@1 82.000 (79.211) Prec@5 97.000 (98.013) +2022-11-14 13:41:19,334 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.1206) Prec@1 77.000 (79.182) Prec@5 98.000 (98.013) +2022-11-14 13:41:19,354 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1266 (0.1207) Prec@1 75.000 (79.128) Prec@5 98.000 (98.013) +2022-11-14 13:41:19,374 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1432 (0.1210) Prec@1 73.000 (79.051) Prec@5 97.000 (98.000) +2022-11-14 13:41:19,390 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1225 (0.1210) Prec@1 77.000 (79.025) Prec@5 98.000 (98.000) +2022-11-14 13:41:19,407 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1245 (0.1210) Prec@1 78.000 (79.012) Prec@5 97.000 (97.988) +2022-11-14 13:41:19,420 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1391 (0.1213) Prec@1 78.000 (79.000) Prec@5 96.000 (97.963) +2022-11-14 13:41:19,435 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1288 (0.1214) Prec@1 77.000 (78.976) Prec@5 98.000 (97.964) +2022-11-14 13:41:19,450 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1183 (0.1213) Prec@1 78.000 (78.964) Prec@5 99.000 (97.976) +2022-11-14 13:41:19,465 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1318 (0.1214) Prec@1 77.000 (78.941) Prec@5 98.000 (97.976) +2022-11-14 13:41:19,481 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1488 (0.1218) Prec@1 77.000 (78.919) Prec@5 98.000 (97.977) +2022-11-14 13:41:19,496 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1285 (0.1218) Prec@1 76.000 (78.885) Prec@5 99.000 (97.989) +2022-11-14 13:41:19,514 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1225 (0.1218) Prec@1 79.000 (78.886) Prec@5 99.000 (98.000) +2022-11-14 13:41:19,532 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1379 (0.1220) Prec@1 75.000 (78.843) Prec@5 98.000 (98.000) +2022-11-14 13:41:19,548 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1417 (0.1222) Prec@1 75.000 (78.800) Prec@5 99.000 (98.011) +2022-11-14 13:41:19,564 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.1220) Prec@1 84.000 (78.857) Prec@5 100.000 (98.033) +2022-11-14 13:41:19,580 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.1217) Prec@1 85.000 (78.924) Prec@5 99.000 (98.043) +2022-11-14 13:41:19,596 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1415 (0.1219) Prec@1 76.000 (78.892) Prec@5 98.000 (98.043) +2022-11-14 13:41:19,613 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1287 (0.1220) Prec@1 77.000 (78.872) Prec@5 96.000 (98.021) +2022-11-14 13:41:19,630 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1312 (0.1221) Prec@1 78.000 (78.863) Prec@5 96.000 (98.000) +2022-11-14 13:41:19,646 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.1218) Prec@1 82.000 (78.896) Prec@5 98.000 (98.000) +2022-11-14 13:41:19,661 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.1216) Prec@1 80.000 (78.907) Prec@5 98.000 (98.000) +2022-11-14 13:41:19,675 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1501 (0.1219) Prec@1 74.000 (78.857) Prec@5 99.000 (98.010) +2022-11-14 13:41:19,689 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1341 (0.1220) Prec@1 73.000 (78.798) Prec@5 97.000 (98.000) +2022-11-14 13:41:19,703 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1321 (0.1221) Prec@1 77.000 (78.780) Prec@5 97.000 (97.990) +2022-11-14 13:41:19,761 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:41:20,092 Epoch: [79][0/500] Time 0.032 (0.032) Data 0.239 (0.239) Loss 0.0824 (0.0824) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:41:20,340 Epoch: [79][10/500] Time 0.022 (0.022) Data 0.002 (0.024) Loss 0.0615 (0.0720) Prec@1 92.000 (89.500) Prec@5 99.000 (98.500) +2022-11-14 13:41:20,611 Epoch: [79][20/500] Time 0.028 (0.023) Data 0.002 (0.013) Loss 0.1022 (0.0820) Prec@1 82.000 (87.000) Prec@5 99.000 (98.667) +2022-11-14 13:41:20,891 Epoch: [79][30/500] Time 0.029 (0.024) Data 0.002 (0.010) Loss 0.0999 (0.0865) Prec@1 81.000 (85.500) Prec@5 99.000 (98.750) +2022-11-14 13:41:21,173 Epoch: [79][40/500] Time 0.028 (0.024) Data 0.002 (0.008) Loss 0.0909 (0.0874) Prec@1 83.000 (85.000) Prec@5 98.000 (98.600) +2022-11-14 13:41:21,442 Epoch: [79][50/500] Time 0.024 (0.024) Data 0.002 (0.007) Loss 0.1203 (0.0929) Prec@1 79.000 (84.000) Prec@5 98.000 (98.500) +2022-11-14 13:41:21,873 Epoch: [79][60/500] Time 0.040 (0.026) Data 0.002 (0.006) Loss 0.0904 (0.0925) Prec@1 85.000 (84.143) Prec@5 100.000 (98.714) +2022-11-14 13:41:22,360 Epoch: [79][70/500] Time 0.043 (0.029) Data 0.002 (0.005) Loss 0.0727 (0.0900) Prec@1 88.000 (84.625) Prec@5 100.000 (98.875) +2022-11-14 13:41:22,823 Epoch: [79][80/500] Time 0.043 (0.030) Data 0.002 (0.005) Loss 0.0915 (0.0902) Prec@1 84.000 (84.556) Prec@5 100.000 (99.000) +2022-11-14 13:41:23,349 Epoch: [79][90/500] Time 0.061 (0.032) Data 0.002 (0.005) Loss 0.0696 (0.0881) Prec@1 90.000 (85.100) Prec@5 99.000 (99.000) +2022-11-14 13:41:23,833 Epoch: [79][100/500] Time 0.049 (0.033) Data 0.002 (0.004) Loss 0.1190 (0.0910) Prec@1 78.000 (84.455) Prec@5 98.000 (98.909) +2022-11-14 13:41:24,313 Epoch: [79][110/500] Time 0.049 (0.034) Data 0.002 (0.004) Loss 0.0917 (0.0910) Prec@1 83.000 (84.333) Prec@5 99.000 (98.917) +2022-11-14 13:41:24,809 Epoch: [79][120/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0972 (0.0915) Prec@1 80.000 (84.000) Prec@5 97.000 (98.769) +2022-11-14 13:41:25,269 Epoch: [79][130/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0793 (0.0906) Prec@1 87.000 (84.214) Prec@5 100.000 (98.857) +2022-11-14 13:41:25,740 Epoch: [79][140/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0808 (0.0900) Prec@1 86.000 (84.333) Prec@5 98.000 (98.800) +2022-11-14 13:41:26,274 Epoch: [79][150/500] Time 0.054 (0.037) Data 0.002 (0.004) Loss 0.1093 (0.0912) Prec@1 80.000 (84.062) Prec@5 98.000 (98.750) +2022-11-14 13:41:26,772 Epoch: [79][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.1113 (0.0924) Prec@1 81.000 (83.882) Prec@5 99.000 (98.765) +2022-11-14 13:41:27,300 Epoch: [79][170/500] Time 0.041 (0.038) Data 0.003 (0.003) Loss 0.1062 (0.0931) Prec@1 78.000 (83.556) Prec@5 96.000 (98.611) +2022-11-14 13:41:27,858 Epoch: [79][180/500] Time 0.076 (0.038) Data 0.002 (0.003) Loss 0.0912 (0.0930) Prec@1 84.000 (83.579) Prec@5 99.000 (98.632) +2022-11-14 13:41:28,325 Epoch: [79][190/500] Time 0.041 (0.038) Data 0.003 (0.003) Loss 0.1095 (0.0939) Prec@1 82.000 (83.500) Prec@5 99.000 (98.650) +2022-11-14 13:41:28,788 Epoch: [79][200/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0674 (0.0926) Prec@1 88.000 (83.714) Prec@5 97.000 (98.571) +2022-11-14 13:41:29,338 Epoch: [79][210/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.1003 (0.0929) Prec@1 81.000 (83.591) Prec@5 99.000 (98.591) +2022-11-14 13:41:29,953 Epoch: [79][220/500] Time 0.062 (0.040) Data 0.002 (0.003) Loss 0.0624 (0.0916) Prec@1 92.000 (83.957) Prec@5 100.000 (98.652) +2022-11-14 13:41:30,394 Epoch: [79][230/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0945 (0.0917) Prec@1 85.000 (84.000) Prec@5 99.000 (98.667) +2022-11-14 13:41:30,924 Epoch: [79][240/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0940 (0.0918) Prec@1 83.000 (83.960) Prec@5 99.000 (98.680) +2022-11-14 13:41:31,451 Epoch: [79][250/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0866 (0.0916) Prec@1 83.000 (83.923) Prec@5 100.000 (98.731) +2022-11-14 13:41:32,037 Epoch: [79][260/500] Time 0.034 (0.041) Data 0.003 (0.003) Loss 0.1097 (0.0923) Prec@1 79.000 (83.741) Prec@5 98.000 (98.704) +2022-11-14 13:41:32,630 Epoch: [79][270/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0815 (0.0919) Prec@1 87.000 (83.857) Prec@5 99.000 (98.714) +2022-11-14 13:41:33,097 Epoch: [79][280/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.1029 (0.0923) Prec@1 84.000 (83.862) Prec@5 96.000 (98.621) +2022-11-14 13:41:33,579 Epoch: [79][290/500] Time 0.062 (0.042) Data 0.002 (0.003) Loss 0.1050 (0.0927) Prec@1 81.000 (83.767) Prec@5 100.000 (98.667) +2022-11-14 13:41:34,099 Epoch: [79][300/500] Time 0.070 (0.042) Data 0.002 (0.003) Loss 0.0819 (0.0924) Prec@1 87.000 (83.871) Prec@5 99.000 (98.677) +2022-11-14 13:41:34,612 Epoch: [79][310/500] Time 0.082 (0.042) Data 0.002 (0.003) Loss 0.1378 (0.0938) Prec@1 76.000 (83.625) Prec@5 99.000 (98.688) +2022-11-14 13:41:35,208 Epoch: [79][320/500] Time 0.061 (0.042) Data 0.002 (0.003) Loss 0.1247 (0.0947) Prec@1 78.000 (83.455) Prec@5 97.000 (98.636) +2022-11-14 13:41:35,695 Epoch: [79][330/500] Time 0.034 (0.042) Data 0.002 (0.003) Loss 0.0767 (0.0942) Prec@1 88.000 (83.588) Prec@5 99.000 (98.647) +2022-11-14 13:41:36,208 Epoch: [79][340/500] Time 0.036 (0.042) Data 0.003 (0.003) Loss 0.0960 (0.0942) Prec@1 84.000 (83.600) Prec@5 98.000 (98.629) +2022-11-14 13:41:36,724 Epoch: [79][350/500] Time 0.034 (0.042) Data 0.002 (0.003) Loss 0.0916 (0.0942) Prec@1 85.000 (83.639) Prec@5 98.000 (98.611) +2022-11-14 13:41:37,244 Epoch: [79][360/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0864 (0.0940) Prec@1 86.000 (83.703) Prec@5 100.000 (98.649) +2022-11-14 13:41:37,754 Epoch: [79][370/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0755 (0.0935) Prec@1 85.000 (83.737) Prec@5 100.000 (98.684) +2022-11-14 13:41:38,272 Epoch: [79][380/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.1108 (0.0939) Prec@1 81.000 (83.667) Prec@5 98.000 (98.667) +2022-11-14 13:41:38,796 Epoch: [79][390/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0801 (0.0936) Prec@1 87.000 (83.750) Prec@5 98.000 (98.650) +2022-11-14 13:41:39,307 Epoch: [79][400/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.1348 (0.0946) Prec@1 75.000 (83.537) Prec@5 99.000 (98.659) +2022-11-14 13:41:39,821 Epoch: [79][410/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0866 (0.0944) Prec@1 85.000 (83.571) Prec@5 99.000 (98.667) +2022-11-14 13:41:40,331 Epoch: [79][420/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0849 (0.0942) Prec@1 85.000 (83.605) Prec@5 99.000 (98.674) +2022-11-14 13:41:40,847 Epoch: [79][430/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.1162 (0.0947) Prec@1 80.000 (83.523) Prec@5 100.000 (98.705) +2022-11-14 13:41:41,349 Epoch: [79][440/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0775 (0.0943) Prec@1 87.000 (83.600) Prec@5 99.000 (98.711) +2022-11-14 13:41:41,863 Epoch: [79][450/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.1092 (0.0946) Prec@1 80.000 (83.522) Prec@5 100.000 (98.739) +2022-11-14 13:41:42,313 Epoch: [79][460/500] Time 0.031 (0.043) Data 0.002 (0.003) Loss 0.0983 (0.0947) Prec@1 85.000 (83.553) Prec@5 98.000 (98.723) +2022-11-14 13:41:42,602 Epoch: [79][470/500] Time 0.025 (0.043) Data 0.002 (0.003) Loss 0.1209 (0.0952) Prec@1 80.000 (83.479) Prec@5 98.000 (98.708) +2022-11-14 13:41:42,896 Epoch: [79][480/500] Time 0.031 (0.042) Data 0.002 (0.002) Loss 0.0987 (0.0953) Prec@1 80.000 (83.408) Prec@5 100.000 (98.735) +2022-11-14 13:41:43,185 Epoch: [79][490/500] Time 0.030 (0.042) Data 0.002 (0.002) Loss 0.0925 (0.0953) Prec@1 85.000 (83.440) Prec@5 98.000 (98.720) +2022-11-14 13:41:43,446 Epoch: [79][499/500] Time 0.023 (0.042) Data 0.002 (0.002) Loss 0.0994 (0.0953) Prec@1 83.000 (83.431) Prec@5 98.000 (98.706) +2022-11-14 13:41:43,747 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1146 (0.1146) Prec@1 77.000 (77.000) Prec@5 100.000 (100.000) +2022-11-14 13:41:43,754 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.1111) Prec@1 83.000 (80.000) Prec@5 100.000 (100.000) +2022-11-14 13:41:43,763 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1493 (0.1238) Prec@1 74.000 (78.000) Prec@5 100.000 (100.000) +2022-11-14 13:41:43,776 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1319 (0.1259) Prec@1 79.000 (78.250) Prec@5 99.000 (99.750) +2022-11-14 13:41:43,784 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1234 (0.1254) Prec@1 77.000 (78.000) Prec@5 99.000 (99.600) +2022-11-14 13:41:43,793 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1209) Prec@1 85.000 (79.167) Prec@5 100.000 (99.667) +2022-11-14 13:41:43,800 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.1160) Prec@1 84.000 (79.857) Prec@5 100.000 (99.714) +2022-11-14 13:41:43,810 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1287 (0.1176) Prec@1 77.000 (79.500) Prec@5 98.000 (99.500) +2022-11-14 13:41:43,818 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1397 (0.1201) Prec@1 79.000 (79.444) Prec@5 99.000 (99.444) +2022-11-14 13:41:43,826 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.1180) Prec@1 83.000 (79.800) Prec@5 97.000 (99.200) +2022-11-14 13:41:43,835 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.1182) Prec@1 80.000 (79.818) Prec@5 100.000 (99.273) +2022-11-14 13:41:43,844 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.1178) Prec@1 81.000 (79.917) Prec@5 99.000 (99.250) +2022-11-14 13:41:43,852 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.1153) Prec@1 82.000 (80.077) Prec@5 100.000 (99.308) +2022-11-14 13:41:43,862 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.1155) Prec@1 79.000 (80.000) Prec@5 99.000 (99.286) +2022-11-14 13:41:43,870 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.1138) Prec@1 86.000 (80.400) Prec@5 98.000 (99.200) +2022-11-14 13:41:43,879 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1257 (0.1145) Prec@1 79.000 (80.312) Prec@5 99.000 (99.188) +2022-11-14 13:41:43,888 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.1130) Prec@1 86.000 (80.647) Prec@5 98.000 (99.118) +2022-11-14 13:41:43,896 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1427 (0.1147) Prec@1 77.000 (80.444) Prec@5 97.000 (99.000) +2022-11-14 13:41:43,905 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1218 (0.1151) Prec@1 78.000 (80.316) Prec@5 100.000 (99.053) +2022-11-14 13:41:43,913 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1193 (0.1153) Prec@1 83.000 (80.450) Prec@5 97.000 (98.950) +2022-11-14 13:41:43,923 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1136 (0.1152) Prec@1 78.000 (80.333) Prec@5 98.000 (98.905) +2022-11-14 13:41:43,932 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1454 (0.1166) Prec@1 75.000 (80.091) Prec@5 99.000 (98.909) +2022-11-14 13:41:43,941 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1472 (0.1179) Prec@1 74.000 (79.826) Prec@5 96.000 (98.783) +2022-11-14 13:41:43,951 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1142 (0.1177) Prec@1 76.000 (79.667) Prec@5 99.000 (98.792) +2022-11-14 13:41:43,960 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1389 (0.1186) Prec@1 78.000 (79.600) Prec@5 100.000 (98.840) +2022-11-14 13:41:43,969 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1611 (0.1202) Prec@1 71.000 (79.269) Prec@5 97.000 (98.769) +2022-11-14 13:41:43,978 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1201 (0.1202) Prec@1 77.000 (79.185) Prec@5 99.000 (98.778) +2022-11-14 13:41:43,988 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1316 (0.1206) Prec@1 77.000 (79.107) Prec@5 100.000 (98.821) +2022-11-14 13:41:43,996 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.1201) Prec@1 85.000 (79.310) Prec@5 97.000 (98.759) +2022-11-14 13:41:44,006 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1178 (0.1200) Prec@1 77.000 (79.233) Prec@5 100.000 (98.800) +2022-11-14 13:41:44,016 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1227 (0.1201) Prec@1 76.000 (79.129) Prec@5 100.000 (98.839) +2022-11-14 13:41:44,024 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1204 (0.1201) Prec@1 80.000 (79.156) Prec@5 98.000 (98.812) +2022-11-14 13:41:44,033 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1249 (0.1202) Prec@1 76.000 (79.061) Prec@5 97.000 (98.758) +2022-11-14 13:41:44,042 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1430 (0.1209) Prec@1 75.000 (78.941) Prec@5 98.000 (98.735) +2022-11-14 13:41:44,050 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.1205) Prec@1 80.000 (78.971) Prec@5 96.000 (98.657) +2022-11-14 13:41:44,059 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.1200) Prec@1 84.000 (79.111) Prec@5 98.000 (98.639) +2022-11-14 13:41:44,069 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.1200) Prec@1 77.000 (79.054) Prec@5 95.000 (98.541) +2022-11-14 13:41:44,078 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1131 (0.1198) Prec@1 81.000 (79.105) Prec@5 98.000 (98.526) +2022-11-14 13:41:44,087 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.1191) Prec@1 83.000 (79.205) Prec@5 100.000 (98.564) +2022-11-14 13:41:44,096 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1345 (0.1195) Prec@1 72.000 (79.025) Prec@5 99.000 (98.575) +2022-11-14 13:41:44,106 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.1188) Prec@1 83.000 (79.122) Prec@5 99.000 (98.585) +2022-11-14 13:41:44,115 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1160 (0.1187) Prec@1 80.000 (79.143) Prec@5 99.000 (98.595) +2022-11-14 13:41:44,124 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.1181) Prec@1 85.000 (79.279) Prec@5 99.000 (98.605) +2022-11-14 13:41:44,133 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.1178) Prec@1 83.000 (79.364) Prec@5 99.000 (98.614) +2022-11-14 13:41:44,142 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1273 (0.1180) Prec@1 79.000 (79.356) Prec@5 99.000 (98.622) +2022-11-14 13:41:44,151 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1306 (0.1183) Prec@1 76.000 (79.283) Prec@5 98.000 (98.609) +2022-11-14 13:41:44,160 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.1181) Prec@1 80.000 (79.298) Prec@5 99.000 (98.617) +2022-11-14 13:41:44,169 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1270 (0.1183) Prec@1 78.000 (79.271) Prec@5 98.000 (98.604) +2022-11-14 13:41:44,178 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.1175) Prec@1 86.000 (79.408) Prec@5 100.000 (98.633) +2022-11-14 13:41:44,186 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1438 (0.1180) Prec@1 72.000 (79.260) Prec@5 97.000 (98.600) +2022-11-14 13:41:44,194 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.1177) Prec@1 81.000 (79.294) Prec@5 99.000 (98.608) +2022-11-14 13:41:44,203 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1469 (0.1183) Prec@1 73.000 (79.173) Prec@5 99.000 (98.615) +2022-11-14 13:41:44,212 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.1177) Prec@1 85.000 (79.283) Prec@5 100.000 (98.642) +2022-11-14 13:41:44,220 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.1175) Prec@1 82.000 (79.333) Prec@5 98.000 (98.630) +2022-11-14 13:41:44,228 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.1173) Prec@1 82.000 (79.382) Prec@5 98.000 (98.618) +2022-11-14 13:41:44,236 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.1168) Prec@1 87.000 (79.518) Prec@5 99.000 (98.625) +2022-11-14 13:41:44,244 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1411 (0.1173) Prec@1 75.000 (79.439) Prec@5 97.000 (98.596) +2022-11-14 13:41:44,254 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.1170) Prec@1 83.000 (79.500) Prec@5 98.000 (98.586) +2022-11-14 13:41:44,263 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1285 (0.1172) Prec@1 75.000 (79.424) Prec@5 100.000 (98.610) +2022-11-14 13:41:44,275 Test: [59/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1158 (0.1172) Prec@1 78.000 (79.400) Prec@5 99.000 (98.617) +2022-11-14 13:41:44,285 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1085 (0.1171) Prec@1 80.000 (79.410) Prec@5 99.000 (98.623) +2022-11-14 13:41:44,295 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1211 (0.1171) Prec@1 78.000 (79.387) Prec@5 99.000 (98.629) +2022-11-14 13:41:44,304 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.1168) Prec@1 84.000 (79.460) Prec@5 99.000 (98.635) +2022-11-14 13:41:44,314 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.1164) Prec@1 83.000 (79.516) Prec@5 100.000 (98.656) +2022-11-14 13:41:44,324 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1211 (0.1165) Prec@1 78.000 (79.492) Prec@5 98.000 (98.646) +2022-11-14 13:41:44,336 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1458 (0.1169) Prec@1 75.000 (79.424) Prec@5 99.000 (98.652) +2022-11-14 13:41:44,345 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.1165) Prec@1 85.000 (79.507) Prec@5 100.000 (98.672) +2022-11-14 13:41:44,354 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1273 (0.1166) Prec@1 76.000 (79.456) Prec@5 98.000 (98.662) +2022-11-14 13:41:44,363 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.1165) Prec@1 77.000 (79.420) Prec@5 97.000 (98.638) +2022-11-14 13:41:44,372 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.1164) Prec@1 79.000 (79.414) Prec@5 98.000 (98.629) +2022-11-14 13:41:44,382 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.1163) Prec@1 81.000 (79.437) Prec@5 99.000 (98.634) +2022-11-14 13:41:44,391 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.1161) Prec@1 82.000 (79.472) Prec@5 100.000 (98.653) +2022-11-14 13:41:44,400 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.1156) Prec@1 89.000 (79.603) Prec@5 100.000 (98.671) +2022-11-14 13:41:44,410 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.1150) Prec@1 89.000 (79.730) Prec@5 100.000 (98.689) +2022-11-14 13:41:44,420 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.1151) Prec@1 78.000 (79.707) Prec@5 98.000 (98.680) +2022-11-14 13:41:44,429 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.1149) Prec@1 82.000 (79.737) Prec@5 99.000 (98.684) +2022-11-14 13:41:44,439 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1150) Prec@1 82.000 (79.766) Prec@5 98.000 (98.675) +2022-11-14 13:41:44,448 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.1148) Prec@1 83.000 (79.808) Prec@5 97.000 (98.654) +2022-11-14 13:41:44,458 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.1148) Prec@1 80.000 (79.810) Prec@5 100.000 (98.671) +2022-11-14 13:41:44,467 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.1148) Prec@1 79.000 (79.800) Prec@5 97.000 (98.650) +2022-11-14 13:41:44,475 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.1148) Prec@1 78.000 (79.778) Prec@5 97.000 (98.630) +2022-11-14 13:41:44,488 Test: [81/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.1147) Prec@1 82.000 (79.805) Prec@5 99.000 (98.634) +2022-11-14 13:41:44,500 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.1147) Prec@1 80.000 (79.807) Prec@5 98.000 (98.627) +2022-11-14 13:41:44,510 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1318 (0.1149) Prec@1 76.000 (79.762) Prec@5 99.000 (98.631) +2022-11-14 13:41:44,521 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1535 (0.1153) Prec@1 69.000 (79.635) Prec@5 99.000 (98.635) +2022-11-14 13:41:44,530 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.1154) Prec@1 76.000 (79.593) Prec@5 99.000 (98.640) +2022-11-14 13:41:44,539 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.1152) Prec@1 86.000 (79.667) Prec@5 97.000 (98.621) +2022-11-14 13:41:44,548 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1292 (0.1153) Prec@1 75.000 (79.614) Prec@5 99.000 (98.625) +2022-11-14 13:41:44,557 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.1152) Prec@1 85.000 (79.674) Prec@5 97.000 (98.607) +2022-11-14 13:41:44,566 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1179 (0.1152) Prec@1 80.000 (79.678) Prec@5 97.000 (98.589) +2022-11-14 13:41:44,576 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.1150) Prec@1 85.000 (79.736) Prec@5 98.000 (98.582) +2022-11-14 13:41:44,585 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.1145) Prec@1 86.000 (79.804) Prec@5 100.000 (98.598) +2022-11-14 13:41:44,594 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.1147) Prec@1 75.000 (79.753) Prec@5 100.000 (98.613) +2022-11-14 13:41:44,603 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.1146) Prec@1 81.000 (79.766) Prec@5 99.000 (98.617) +2022-11-14 13:41:44,616 Test: [94/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.1146) Prec@1 82.000 (79.789) Prec@5 96.000 (98.589) +2022-11-14 13:41:44,627 Test: [95/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1146) Prec@1 82.000 (79.812) Prec@5 100.000 (98.604) +2022-11-14 13:41:44,638 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.1143) Prec@1 89.000 (79.907) Prec@5 97.000 (98.588) +2022-11-14 13:41:44,649 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1377 (0.1145) Prec@1 75.000 (79.857) Prec@5 99.000 (98.592) +2022-11-14 13:41:44,659 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1421 (0.1148) Prec@1 72.000 (79.778) Prec@5 100.000 (98.606) +2022-11-14 13:41:44,668 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.1148) Prec@1 80.000 (79.780) Prec@5 100.000 (98.620) +2022-11-14 13:41:44,737 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:41:45,063 Epoch: [80][0/500] Time 0.025 (0.025) Data 0.240 (0.240) Loss 0.0892 (0.0892) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:41:45,296 Epoch: [80][10/500] Time 0.017 (0.021) Data 0.003 (0.024) Loss 0.1004 (0.0948) Prec@1 82.000 (84.000) Prec@5 100.000 (99.000) +2022-11-14 13:41:45,513 Epoch: [80][20/500] Time 0.018 (0.020) Data 0.002 (0.013) Loss 0.0948 (0.0948) Prec@1 81.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:41:45,790 Epoch: [80][30/500] Time 0.032 (0.021) Data 0.002 (0.010) Loss 0.0778 (0.0905) Prec@1 88.000 (84.250) Prec@5 100.000 (99.250) +2022-11-14 13:41:46,246 Epoch: [80][40/500] Time 0.038 (0.026) Data 0.002 (0.008) Loss 0.1069 (0.0938) Prec@1 80.000 (83.400) Prec@5 97.000 (98.800) +2022-11-14 13:41:46,793 Epoch: [80][50/500] Time 0.029 (0.030) Data 0.002 (0.007) Loss 0.1032 (0.0954) Prec@1 80.000 (82.833) Prec@5 99.000 (98.833) +2022-11-14 13:41:47,251 Epoch: [80][60/500] Time 0.044 (0.032) Data 0.002 (0.006) Loss 0.0764 (0.0927) Prec@1 87.000 (83.429) Prec@5 99.000 (98.857) +2022-11-14 13:41:47,724 Epoch: [80][70/500] Time 0.039 (0.034) Data 0.002 (0.005) Loss 0.0815 (0.0913) Prec@1 86.000 (83.750) Prec@5 97.000 (98.625) +2022-11-14 13:41:48,191 Epoch: [80][80/500] Time 0.042 (0.035) Data 0.002 (0.005) Loss 0.0721 (0.0891) Prec@1 88.000 (84.222) Prec@5 100.000 (98.778) +2022-11-14 13:41:48,712 Epoch: [80][90/500] Time 0.044 (0.036) Data 0.003 (0.005) Loss 0.1537 (0.0956) Prec@1 76.000 (83.400) Prec@5 99.000 (98.800) +2022-11-14 13:41:49,209 Epoch: [80][100/500] Time 0.039 (0.037) Data 0.003 (0.004) Loss 0.0959 (0.0956) Prec@1 83.000 (83.364) Prec@5 99.000 (98.818) +2022-11-14 13:41:49,760 Epoch: [80][110/500] Time 0.068 (0.038) Data 0.002 (0.004) Loss 0.1287 (0.0984) Prec@1 77.000 (82.833) Prec@5 96.000 (98.583) +2022-11-14 13:41:50,382 Epoch: [80][120/500] Time 0.060 (0.039) Data 0.002 (0.004) Loss 0.0844 (0.0973) Prec@1 89.000 (83.308) Prec@5 97.000 (98.462) +2022-11-14 13:41:50,833 Epoch: [80][130/500] Time 0.053 (0.039) Data 0.002 (0.004) Loss 0.0782 (0.0960) Prec@1 87.000 (83.571) Prec@5 100.000 (98.571) +2022-11-14 13:41:51,279 Epoch: [80][140/500] Time 0.040 (0.039) Data 0.002 (0.004) Loss 0.1200 (0.0976) Prec@1 79.000 (83.267) Prec@5 98.000 (98.533) +2022-11-14 13:41:51,775 Epoch: [80][150/500] Time 0.045 (0.040) Data 0.002 (0.004) Loss 0.0774 (0.0963) Prec@1 89.000 (83.625) Prec@5 100.000 (98.625) +2022-11-14 13:41:52,282 Epoch: [80][160/500] Time 0.042 (0.040) Data 0.002 (0.004) Loss 0.0729 (0.0949) Prec@1 88.000 (83.882) Prec@5 99.000 (98.647) +2022-11-14 13:41:52,924 Epoch: [80][170/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0884 (0.0946) Prec@1 86.000 (84.000) Prec@5 100.000 (98.722) +2022-11-14 13:41:53,414 Epoch: [80][180/500] Time 0.069 (0.041) Data 0.002 (0.003) Loss 0.0824 (0.0939) Prec@1 87.000 (84.158) Prec@5 100.000 (98.789) +2022-11-14 13:41:53,912 Epoch: [80][190/500] Time 0.072 (0.041) Data 0.002 (0.003) Loss 0.1040 (0.0944) Prec@1 81.000 (84.000) Prec@5 99.000 (98.800) +2022-11-14 13:41:54,390 Epoch: [80][200/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.1092 (0.0951) Prec@1 80.000 (83.810) Prec@5 99.000 (98.810) +2022-11-14 13:41:54,881 Epoch: [80][210/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.1144 (0.0960) Prec@1 82.000 (83.727) Prec@5 97.000 (98.727) +2022-11-14 13:41:55,357 Epoch: [80][220/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0664 (0.0947) Prec@1 87.000 (83.870) Prec@5 99.000 (98.739) +2022-11-14 13:41:55,813 Epoch: [80][230/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.1024 (0.0950) Prec@1 83.000 (83.833) Prec@5 100.000 (98.792) +2022-11-14 13:41:56,287 Epoch: [80][240/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.1266 (0.0963) Prec@1 77.000 (83.560) Prec@5 99.000 (98.800) +2022-11-14 13:41:56,767 Epoch: [80][250/500] Time 0.043 (0.041) Data 0.001 (0.003) Loss 0.0806 (0.0957) Prec@1 84.000 (83.577) Prec@5 99.000 (98.808) +2022-11-14 13:41:57,258 Epoch: [80][260/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0713 (0.0948) Prec@1 87.000 (83.704) Prec@5 99.000 (98.815) +2022-11-14 13:41:57,754 Epoch: [80][270/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0843 (0.0944) Prec@1 81.000 (83.607) Prec@5 100.000 (98.857) +2022-11-14 13:41:58,252 Epoch: [80][280/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0849 (0.0941) Prec@1 85.000 (83.655) Prec@5 98.000 (98.828) +2022-11-14 13:41:58,714 Epoch: [80][290/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.1348 (0.0954) Prec@1 78.000 (83.467) Prec@5 98.000 (98.800) +2022-11-14 13:41:59,032 Epoch: [80][300/500] Time 0.025 (0.041) Data 0.002 (0.003) Loss 0.0952 (0.0954) Prec@1 85.000 (83.516) Prec@5 100.000 (98.839) +2022-11-14 13:41:59,308 Epoch: [80][310/500] Time 0.027 (0.040) Data 0.002 (0.003) Loss 0.1173 (0.0961) Prec@1 77.000 (83.312) Prec@5 99.000 (98.844) +2022-11-14 13:41:59,586 Epoch: [80][320/500] Time 0.025 (0.040) Data 0.002 (0.003) Loss 0.1073 (0.0965) Prec@1 81.000 (83.242) Prec@5 97.000 (98.788) +2022-11-14 13:41:59,864 Epoch: [80][330/500] Time 0.027 (0.039) Data 0.001 (0.003) Loss 0.1083 (0.0968) Prec@1 80.000 (83.147) Prec@5 97.000 (98.735) +2022-11-14 13:42:00,185 Epoch: [80][340/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0701 (0.0960) Prec@1 87.000 (83.257) Prec@5 99.000 (98.743) +2022-11-14 13:42:00,456 Epoch: [80][350/500] Time 0.024 (0.039) Data 0.002 (0.003) Loss 0.0887 (0.0958) Prec@1 86.000 (83.333) Prec@5 98.000 (98.722) +2022-11-14 13:42:00,778 Epoch: [80][360/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.0987 (0.0959) Prec@1 83.000 (83.324) Prec@5 98.000 (98.703) +2022-11-14 13:42:01,045 Epoch: [80][370/500] Time 0.025 (0.038) Data 0.001 (0.003) Loss 0.0760 (0.0954) Prec@1 85.000 (83.368) Prec@5 98.000 (98.684) +2022-11-14 13:42:01,359 Epoch: [80][380/500] Time 0.023 (0.038) Data 0.002 (0.003) Loss 0.0711 (0.0948) Prec@1 88.000 (83.487) Prec@5 97.000 (98.641) +2022-11-14 13:42:01,674 Epoch: [80][390/500] Time 0.044 (0.037) Data 0.001 (0.003) Loss 0.0966 (0.0948) Prec@1 85.000 (83.525) Prec@5 100.000 (98.675) +2022-11-14 13:42:01,956 Epoch: [80][400/500] Time 0.027 (0.037) Data 0.002 (0.002) Loss 0.1186 (0.0954) Prec@1 80.000 (83.439) Prec@5 97.000 (98.634) +2022-11-14 13:42:02,279 Epoch: [80][410/500] Time 0.024 (0.037) Data 0.002 (0.002) Loss 0.0871 (0.0952) Prec@1 86.000 (83.500) Prec@5 100.000 (98.667) +2022-11-14 13:42:02,628 Epoch: [80][420/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0966 (0.0952) Prec@1 81.000 (83.442) Prec@5 98.000 (98.651) +2022-11-14 13:42:03,146 Epoch: [80][430/500] Time 0.049 (0.037) Data 0.002 (0.002) Loss 0.1122 (0.0956) Prec@1 80.000 (83.364) Prec@5 100.000 (98.682) +2022-11-14 13:42:03,640 Epoch: [80][440/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.0938 (0.0956) Prec@1 85.000 (83.400) Prec@5 100.000 (98.711) +2022-11-14 13:42:04,130 Epoch: [80][450/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0971 (0.0956) Prec@1 81.000 (83.348) Prec@5 98.000 (98.696) +2022-11-14 13:42:04,713 Epoch: [80][460/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1023 (0.0958) Prec@1 82.000 (83.319) Prec@5 98.000 (98.681) +2022-11-14 13:42:05,252 Epoch: [80][470/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0864 (0.0956) Prec@1 83.000 (83.312) Prec@5 99.000 (98.688) +2022-11-14 13:42:05,779 Epoch: [80][480/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.1063 (0.0958) Prec@1 82.000 (83.286) Prec@5 99.000 (98.694) +2022-11-14 13:42:06,402 Epoch: [80][490/500] Time 0.060 (0.038) Data 0.002 (0.002) Loss 0.0919 (0.0957) Prec@1 84.000 (83.300) Prec@5 98.000 (98.680) +2022-11-14 13:42:07,019 Epoch: [80][499/500] Time 0.075 (0.039) Data 0.002 (0.002) Loss 0.0637 (0.0951) Prec@1 91.000 (83.451) Prec@5 98.000 (98.667) +2022-11-14 13:42:07,356 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0982 (0.0982) Prec@1 80.000 (80.000) Prec@5 99.000 (99.000) +2022-11-14 13:42:07,365 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1124 (0.1053) Prec@1 79.000 (79.500) Prec@5 98.000 (98.500) +2022-11-14 13:42:07,376 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1366 (0.1157) Prec@1 78.000 (79.000) Prec@5 99.000 (98.667) +2022-11-14 13:42:07,388 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1162 (0.1158) Prec@1 82.000 (79.750) Prec@5 99.000 (98.750) +2022-11-14 13:42:07,397 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1153 (0.1157) Prec@1 82.000 (80.200) Prec@5 100.000 (99.000) +2022-11-14 13:42:07,407 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.1096) Prec@1 86.000 (81.167) Prec@5 100.000 (99.167) +2022-11-14 13:42:07,416 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.1050) Prec@1 88.000 (82.143) Prec@5 98.000 (99.000) +2022-11-14 13:42:07,427 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1383 (0.1092) Prec@1 77.000 (81.500) Prec@5 98.000 (98.875) +2022-11-14 13:42:07,436 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1280 (0.1113) Prec@1 76.000 (80.889) Prec@5 99.000 (98.889) +2022-11-14 13:42:07,446 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.1101) Prec@1 83.000 (81.100) Prec@5 97.000 (98.700) +2022-11-14 13:42:07,458 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.1072) Prec@1 86.000 (81.545) Prec@5 98.000 (98.636) +2022-11-14 13:42:07,470 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1093 (0.1074) Prec@1 83.000 (81.667) Prec@5 99.000 (98.667) +2022-11-14 13:42:07,481 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1187 (0.1083) Prec@1 79.000 (81.462) Prec@5 99.000 (98.692) +2022-11-14 13:42:07,492 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.1064) Prec@1 87.000 (81.857) Prec@5 99.000 (98.714) +2022-11-14 13:42:07,504 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.1060) Prec@1 82.000 (81.867) Prec@5 99.000 (98.733) +2022-11-14 13:42:07,515 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.1064) Prec@1 80.000 (81.750) Prec@5 99.000 (98.750) +2022-11-14 13:42:07,525 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.1060) Prec@1 80.000 (81.647) Prec@5 99.000 (98.765) +2022-11-14 13:42:07,535 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.1059) Prec@1 78.000 (81.444) Prec@5 99.000 (98.778) +2022-11-14 13:42:07,545 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.1062) Prec@1 80.000 (81.368) Prec@5 98.000 (98.737) +2022-11-14 13:42:07,555 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1340 (0.1076) Prec@1 78.000 (81.200) Prec@5 98.000 (98.700) +2022-11-14 13:42:07,565 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1222 (0.1083) Prec@1 79.000 (81.095) Prec@5 99.000 (98.714) +2022-11-14 13:42:07,574 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.1080) Prec@1 85.000 (81.273) Prec@5 98.000 (98.682) +2022-11-14 13:42:07,586 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1308 (0.1090) Prec@1 78.000 (81.130) Prec@5 99.000 (98.696) +2022-11-14 13:42:07,596 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.1089) Prec@1 82.000 (81.167) Prec@5 99.000 (98.708) +2022-11-14 13:42:07,607 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1356 (0.1099) Prec@1 75.000 (80.920) Prec@5 98.000 (98.680) +2022-11-14 13:42:07,616 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1334 (0.1108) Prec@1 76.000 (80.731) Prec@5 98.000 (98.654) +2022-11-14 13:42:07,625 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.1098) Prec@1 86.000 (80.926) Prec@5 100.000 (98.704) +2022-11-14 13:42:07,634 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.1093) Prec@1 86.000 (81.107) Prec@5 99.000 (98.714) +2022-11-14 13:42:07,644 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.1087) Prec@1 83.000 (81.172) Prec@5 97.000 (98.655) +2022-11-14 13:42:07,655 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.1087) Prec@1 82.000 (81.200) Prec@5 98.000 (98.633) +2022-11-14 13:42:07,665 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.1088) Prec@1 81.000 (81.194) Prec@5 99.000 (98.645) +2022-11-14 13:42:07,676 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.1087) Prec@1 81.000 (81.188) Prec@5 100.000 (98.688) +2022-11-14 13:42:07,688 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.1081) Prec@1 81.000 (81.182) Prec@5 96.000 (98.606) +2022-11-14 13:42:07,697 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1360 (0.1090) Prec@1 75.000 (81.000) Prec@5 99.000 (98.618) +2022-11-14 13:42:07,707 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1361 (0.1097) Prec@1 76.000 (80.857) Prec@5 98.000 (98.600) +2022-11-14 13:42:07,718 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.1090) Prec@1 87.000 (81.028) Prec@5 98.000 (98.583) +2022-11-14 13:42:07,729 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1507 (0.1101) Prec@1 74.000 (80.838) Prec@5 98.000 (98.568) +2022-11-14 13:42:07,741 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1320 (0.1107) Prec@1 79.000 (80.789) Prec@5 99.000 (98.579) +2022-11-14 13:42:07,753 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.1102) Prec@1 86.000 (80.923) Prec@5 98.000 (98.564) +2022-11-14 13:42:07,765 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.1098) Prec@1 83.000 (80.975) Prec@5 98.000 (98.550) +2022-11-14 13:42:07,776 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1236 (0.1102) Prec@1 80.000 (80.951) Prec@5 98.000 (98.537) +2022-11-14 13:42:07,787 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.1098) Prec@1 86.000 (81.071) Prec@5 98.000 (98.524) +2022-11-14 13:42:07,798 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.1090) Prec@1 89.000 (81.256) Prec@5 100.000 (98.558) +2022-11-14 13:42:07,809 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.1091) Prec@1 80.000 (81.227) Prec@5 98.000 (98.545) +2022-11-14 13:42:07,820 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.1088) Prec@1 82.000 (81.244) Prec@5 98.000 (98.533) +2022-11-14 13:42:07,829 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.1091) Prec@1 77.000 (81.152) Prec@5 98.000 (98.522) +2022-11-14 13:42:07,839 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.1088) Prec@1 83.000 (81.191) Prec@5 100.000 (98.553) +2022-11-14 13:42:07,852 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1292 (0.1092) Prec@1 76.000 (81.083) Prec@5 99.000 (98.562) +2022-11-14 13:42:07,868 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.1087) Prec@1 85.000 (81.163) Prec@5 98.000 (98.551) +2022-11-14 13:42:07,884 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1295 (0.1091) Prec@1 76.000 (81.060) Prec@5 98.000 (98.540) +2022-11-14 13:42:07,900 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.1089) Prec@1 82.000 (81.078) Prec@5 99.000 (98.549) +2022-11-14 13:42:07,915 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1303 (0.1093) Prec@1 77.000 (81.000) Prec@5 99.000 (98.558) +2022-11-14 13:42:07,930 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.1090) Prec@1 86.000 (81.094) Prec@5 99.000 (98.566) +2022-11-14 13:42:07,945 Test: [53/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.1085) Prec@1 86.000 (81.185) Prec@5 98.000 (98.556) +2022-11-14 13:42:07,958 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.1085) Prec@1 81.000 (81.182) Prec@5 98.000 (98.545) +2022-11-14 13:42:07,970 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.1084) Prec@1 86.000 (81.268) Prec@5 100.000 (98.571) +2022-11-14 13:42:07,982 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1196 (0.1086) Prec@1 83.000 (81.298) Prec@5 99.000 (98.579) +2022-11-14 13:42:07,991 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.1084) Prec@1 82.000 (81.310) Prec@5 99.000 (98.586) +2022-11-14 13:42:08,003 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.1084) Prec@1 84.000 (81.356) Prec@5 97.000 (98.559) +2022-11-14 13:42:08,012 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.1082) Prec@1 80.000 (81.333) Prec@5 97.000 (98.533) +2022-11-14 13:42:08,024 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.1080) Prec@1 84.000 (81.377) Prec@5 99.000 (98.541) +2022-11-14 13:42:08,034 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.1080) Prec@1 81.000 (81.371) Prec@5 99.000 (98.548) +2022-11-14 13:42:08,044 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.1075) Prec@1 88.000 (81.476) Prec@5 97.000 (98.524) +2022-11-14 13:42:08,054 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.1071) Prec@1 84.000 (81.516) Prec@5 99.000 (98.531) +2022-11-14 13:42:08,065 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1144 (0.1072) Prec@1 79.000 (81.477) Prec@5 98.000 (98.523) +2022-11-14 13:42:08,077 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.1076) Prec@1 77.000 (81.409) Prec@5 99.000 (98.530) +2022-11-14 13:42:08,086 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.1071) Prec@1 84.000 (81.448) Prec@5 100.000 (98.552) +2022-11-14 13:42:08,096 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.1072) Prec@1 81.000 (81.441) Prec@5 98.000 (98.544) +2022-11-14 13:42:08,107 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.1068) Prec@1 86.000 (81.507) Prec@5 99.000 (98.551) +2022-11-14 13:42:08,119 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.1070) Prec@1 80.000 (81.486) Prec@5 99.000 (98.557) +2022-11-14 13:42:08,129 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1069) Prec@1 81.000 (81.479) Prec@5 99.000 (98.563) +2022-11-14 13:42:08,143 Test: [71/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.1069) Prec@1 79.000 (81.444) Prec@5 99.000 (98.569) +2022-11-14 13:42:08,156 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.1064) Prec@1 88.000 (81.534) Prec@5 100.000 (98.589) +2022-11-14 13:42:08,166 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.1062) Prec@1 84.000 (81.568) Prec@5 100.000 (98.608) +2022-11-14 13:42:08,176 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.1064) Prec@1 82.000 (81.573) Prec@5 98.000 (98.600) +2022-11-14 13:42:08,188 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.1060) Prec@1 88.000 (81.658) Prec@5 100.000 (98.618) +2022-11-14 13:42:08,199 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.1060) Prec@1 80.000 (81.636) Prec@5 98.000 (98.610) +2022-11-14 13:42:08,210 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.1057) Prec@1 84.000 (81.667) Prec@5 99.000 (98.615) +2022-11-14 13:42:08,219 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.1058) Prec@1 83.000 (81.684) Prec@5 100.000 (98.633) +2022-11-14 13:42:08,232 Test: [79/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.1057) Prec@1 80.000 (81.662) Prec@5 97.000 (98.612) +2022-11-14 13:42:08,244 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1056) Prec@1 85.000 (81.704) Prec@5 97.000 (98.593) +2022-11-14 13:42:08,254 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1056) Prec@1 79.000 (81.671) Prec@5 100.000 (98.610) +2022-11-14 13:42:08,265 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1232 (0.1058) Prec@1 77.000 (81.614) Prec@5 99.000 (98.614) +2022-11-14 13:42:08,278 Test: [83/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.1059) Prec@1 82.000 (81.619) Prec@5 99.000 (98.619) +2022-11-14 13:42:08,290 Test: [84/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1436 (0.1063) Prec@1 74.000 (81.529) Prec@5 99.000 (98.624) +2022-11-14 13:42:08,301 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.1063) Prec@1 84.000 (81.558) Prec@5 98.000 (98.616) +2022-11-14 13:42:08,311 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.1062) Prec@1 82.000 (81.563) Prec@5 98.000 (98.609) +2022-11-14 13:42:08,323 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1200 (0.1064) Prec@1 81.000 (81.557) Prec@5 99.000 (98.614) +2022-11-14 13:42:08,335 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.1063) Prec@1 82.000 (81.562) Prec@5 98.000 (98.607) +2022-11-14 13:42:08,345 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.1061) Prec@1 86.000 (81.611) Prec@5 98.000 (98.600) +2022-11-14 13:42:08,355 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.1059) Prec@1 89.000 (81.692) Prec@5 100.000 (98.615) +2022-11-14 13:42:08,367 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.1054) Prec@1 88.000 (81.761) Prec@5 99.000 (98.620) +2022-11-14 13:42:08,380 Test: [92/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1390 (0.1058) Prec@1 76.000 (81.699) Prec@5 97.000 (98.602) +2022-11-14 13:42:08,391 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.1057) Prec@1 85.000 (81.734) Prec@5 97.000 (98.585) +2022-11-14 13:42:08,401 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.1056) Prec@1 87.000 (81.789) Prec@5 99.000 (98.589) +2022-11-14 13:42:08,412 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.1054) Prec@1 83.000 (81.802) Prec@5 98.000 (98.583) +2022-11-14 13:42:08,423 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.1051) Prec@1 88.000 (81.866) Prec@5 99.000 (98.588) +2022-11-14 13:42:08,432 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.1052) Prec@1 83.000 (81.878) Prec@5 98.000 (98.582) +2022-11-14 13:42:08,440 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.1054) Prec@1 77.000 (81.828) Prec@5 100.000 (98.596) +2022-11-14 13:42:08,450 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.1053) Prec@1 80.000 (81.810) Prec@5 100.000 (98.610) +2022-11-14 13:42:08,510 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:42:08,854 Epoch: [81][0/500] Time 0.029 (0.029) Data 0.253 (0.253) Loss 0.0884 (0.0884) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:42:09,104 Epoch: [81][10/500] Time 0.020 (0.023) Data 0.002 (0.025) Loss 0.0987 (0.0935) Prec@1 83.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:42:09,318 Epoch: [81][20/500] Time 0.019 (0.021) Data 0.002 (0.014) Loss 0.1087 (0.0986) Prec@1 83.000 (83.667) Prec@5 98.000 (99.333) +2022-11-14 13:42:09,570 Epoch: [81][30/500] Time 0.025 (0.021) Data 0.002 (0.010) Loss 0.0739 (0.0924) Prec@1 85.000 (84.000) Prec@5 100.000 (99.500) +2022-11-14 13:42:09,864 Epoch: [81][40/500] Time 0.024 (0.022) Data 0.002 (0.008) Loss 0.0697 (0.0879) Prec@1 89.000 (85.000) Prec@5 100.000 (99.600) +2022-11-14 13:42:10,165 Epoch: [81][50/500] Time 0.028 (0.023) Data 0.002 (0.007) Loss 0.0626 (0.0837) Prec@1 91.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 13:42:10,454 Epoch: [81][60/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.0820 (0.0834) Prec@1 85.000 (85.857) Prec@5 100.000 (99.714) +2022-11-14 13:42:10,766 Epoch: [81][70/500] Time 0.025 (0.024) Data 0.002 (0.005) Loss 0.0843 (0.0835) Prec@1 84.000 (85.625) Prec@5 99.000 (99.625) +2022-11-14 13:42:11,052 Epoch: [81][80/500] Time 0.025 (0.024) Data 0.002 (0.005) Loss 0.0891 (0.0842) Prec@1 86.000 (85.667) Prec@5 100.000 (99.667) +2022-11-14 13:42:11,350 Epoch: [81][90/500] Time 0.032 (0.025) Data 0.002 (0.005) Loss 0.1013 (0.0859) Prec@1 80.000 (85.100) Prec@5 99.000 (99.600) +2022-11-14 13:42:11,650 Epoch: [81][100/500] Time 0.026 (0.025) Data 0.002 (0.004) Loss 0.0836 (0.0857) Prec@1 86.000 (85.182) Prec@5 99.000 (99.545) +2022-11-14 13:42:12,099 Epoch: [81][110/500] Time 0.044 (0.026) Data 0.002 (0.004) Loss 0.0838 (0.0855) Prec@1 84.000 (85.083) Prec@5 98.000 (99.417) +2022-11-14 13:42:12,562 Epoch: [81][120/500] Time 0.042 (0.027) Data 0.002 (0.004) Loss 0.0593 (0.0835) Prec@1 89.000 (85.385) Prec@5 100.000 (99.462) +2022-11-14 13:42:13,031 Epoch: [81][130/500] Time 0.044 (0.028) Data 0.002 (0.004) Loss 0.0829 (0.0834) Prec@1 87.000 (85.500) Prec@5 99.000 (99.429) +2022-11-14 13:42:13,590 Epoch: [81][140/500] Time 0.053 (0.030) Data 0.002 (0.004) Loss 0.0640 (0.0822) Prec@1 90.000 (85.800) Prec@5 100.000 (99.467) +2022-11-14 13:42:14,116 Epoch: [81][150/500] Time 0.059 (0.031) Data 0.002 (0.004) Loss 0.0617 (0.0809) Prec@1 91.000 (86.125) Prec@5 100.000 (99.500) +2022-11-14 13:42:14,624 Epoch: [81][160/500] Time 0.052 (0.032) Data 0.002 (0.003) Loss 0.0973 (0.0818) Prec@1 85.000 (86.059) Prec@5 96.000 (99.294) +2022-11-14 13:42:15,138 Epoch: [81][170/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0793 (0.0817) Prec@1 83.000 (85.889) Prec@5 100.000 (99.333) +2022-11-14 13:42:15,626 Epoch: [81][180/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0721 (0.0812) Prec@1 88.000 (86.000) Prec@5 100.000 (99.368) +2022-11-14 13:42:16,182 Epoch: [81][190/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.1069 (0.0825) Prec@1 81.000 (85.750) Prec@5 99.000 (99.350) +2022-11-14 13:42:16,737 Epoch: [81][200/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.1039 (0.0835) Prec@1 83.000 (85.619) Prec@5 97.000 (99.238) +2022-11-14 13:42:17,290 Epoch: [81][210/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.1101 (0.0847) Prec@1 81.000 (85.409) Prec@5 95.000 (99.045) +2022-11-14 13:42:17,903 Epoch: [81][220/500] Time 0.051 (0.036) Data 0.001 (0.003) Loss 0.0995 (0.0854) Prec@1 81.000 (85.217) Prec@5 98.000 (99.000) +2022-11-14 13:42:18,469 Epoch: [81][230/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0867 (0.0854) Prec@1 85.000 (85.208) Prec@5 100.000 (99.042) +2022-11-14 13:42:18,955 Epoch: [81][240/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0936 (0.0857) Prec@1 84.000 (85.160) Prec@5 100.000 (99.080) +2022-11-14 13:42:19,707 Epoch: [81][250/500] Time 0.078 (0.038) Data 0.002 (0.003) Loss 0.0839 (0.0857) Prec@1 86.000 (85.192) Prec@5 100.000 (99.115) +2022-11-14 13:42:20,219 Epoch: [81][260/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0747 (0.0853) Prec@1 86.000 (85.222) Prec@5 99.000 (99.111) +2022-11-14 13:42:20,684 Epoch: [81][270/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0708 (0.0847) Prec@1 88.000 (85.321) Prec@5 98.000 (99.071) +2022-11-14 13:42:21,161 Epoch: [81][280/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0937 (0.0851) Prec@1 83.000 (85.241) Prec@5 100.000 (99.103) +2022-11-14 13:42:21,679 Epoch: [81][290/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.1032 (0.0857) Prec@1 80.000 (85.067) Prec@5 100.000 (99.133) +2022-11-14 13:42:22,198 Epoch: [81][300/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0766 (0.0854) Prec@1 86.000 (85.097) Prec@5 99.000 (99.129) +2022-11-14 13:42:22,686 Epoch: [81][310/500] Time 0.057 (0.040) Data 0.002 (0.003) Loss 0.0885 (0.0855) Prec@1 85.000 (85.094) Prec@5 100.000 (99.156) +2022-11-14 13:42:23,148 Epoch: [81][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0839 (0.0854) Prec@1 83.000 (85.030) Prec@5 100.000 (99.182) +2022-11-14 13:42:23,611 Epoch: [81][330/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0786 (0.0852) Prec@1 87.000 (85.088) Prec@5 99.000 (99.176) +2022-11-14 13:42:24,135 Epoch: [81][340/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0910 (0.0854) Prec@1 84.000 (85.057) Prec@5 99.000 (99.171) +2022-11-14 13:42:24,682 Epoch: [81][350/500] Time 0.081 (0.040) Data 0.002 (0.003) Loss 0.1039 (0.0859) Prec@1 83.000 (85.000) Prec@5 100.000 (99.194) +2022-11-14 13:42:25,219 Epoch: [81][360/500] Time 0.088 (0.040) Data 0.002 (0.003) Loss 0.0982 (0.0862) Prec@1 83.000 (84.946) Prec@5 97.000 (99.135) +2022-11-14 13:42:25,751 Epoch: [81][370/500] Time 0.037 (0.040) Data 0.003 (0.003) Loss 0.0883 (0.0863) Prec@1 84.000 (84.921) Prec@5 98.000 (99.105) +2022-11-14 13:42:26,299 Epoch: [81][380/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0536 (0.0854) Prec@1 91.000 (85.077) Prec@5 99.000 (99.103) +2022-11-14 13:42:26,838 Epoch: [81][390/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0921 (0.0856) Prec@1 84.000 (85.050) Prec@5 99.000 (99.100) +2022-11-14 13:42:27,347 Epoch: [81][400/500] Time 0.029 (0.041) Data 0.002 (0.003) Loss 0.0655 (0.0851) Prec@1 89.000 (85.146) Prec@5 100.000 (99.122) +2022-11-14 13:42:27,711 Epoch: [81][410/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0785 (0.0850) Prec@1 84.000 (85.119) Prec@5 100.000 (99.143) +2022-11-14 13:42:28,097 Epoch: [81][420/500] Time 0.028 (0.041) Data 0.002 (0.002) Loss 0.0664 (0.0845) Prec@1 90.000 (85.233) Prec@5 100.000 (99.163) +2022-11-14 13:42:28,479 Epoch: [81][430/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0841 (0.0845) Prec@1 81.000 (85.136) Prec@5 99.000 (99.159) +2022-11-14 13:42:28,822 Epoch: [81][440/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.0896 (0.0846) Prec@1 82.000 (85.067) Prec@5 100.000 (99.178) +2022-11-14 13:42:29,131 Epoch: [81][450/500] Time 0.029 (0.040) Data 0.002 (0.002) Loss 0.0801 (0.0845) Prec@1 84.000 (85.043) Prec@5 100.000 (99.196) +2022-11-14 13:42:29,482 Epoch: [81][460/500] Time 0.030 (0.040) Data 0.002 (0.002) Loss 0.0935 (0.0847) Prec@1 82.000 (84.979) Prec@5 99.000 (99.191) +2022-11-14 13:42:29,849 Epoch: [81][470/500] Time 0.046 (0.040) Data 0.002 (0.002) Loss 0.0852 (0.0847) Prec@1 82.000 (84.917) Prec@5 100.000 (99.208) +2022-11-14 13:42:30,156 Epoch: [81][480/500] Time 0.033 (0.039) Data 0.002 (0.002) Loss 0.0678 (0.0844) Prec@1 89.000 (85.000) Prec@5 99.000 (99.204) +2022-11-14 13:42:30,523 Epoch: [81][490/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0751 (0.0842) Prec@1 88.000 (85.060) Prec@5 99.000 (99.200) +2022-11-14 13:42:30,805 Epoch: [81][499/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0620 (0.0838) Prec@1 90.000 (85.157) Prec@5 100.000 (99.216) +2022-11-14 13:42:31,102 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0705 (0.0705) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:42:31,112 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0776) Prec@1 83.000 (86.000) Prec@5 100.000 (99.500) +2022-11-14 13:42:31,126 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1001 (0.0851) Prec@1 85.000 (85.667) Prec@5 99.000 (99.333) +2022-11-14 13:42:31,138 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1193 (0.0936) Prec@1 80.000 (84.250) Prec@5 100.000 (99.500) +2022-11-14 13:42:31,147 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0896) Prec@1 89.000 (85.200) Prec@5 100.000 (99.600) +2022-11-14 13:42:31,155 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0848) Prec@1 90.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 13:42:31,163 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0829) Prec@1 87.000 (86.143) Prec@5 100.000 (99.714) +2022-11-14 13:42:31,173 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1210 (0.0877) Prec@1 80.000 (85.375) Prec@5 98.000 (99.500) +2022-11-14 13:42:31,181 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0884) Prec@1 84.000 (85.222) Prec@5 100.000 (99.556) +2022-11-14 13:42:31,189 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0894) Prec@1 81.000 (84.800) Prec@5 95.000 (99.100) +2022-11-14 13:42:31,198 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0883) Prec@1 86.000 (84.909) Prec@5 100.000 (99.182) +2022-11-14 13:42:31,207 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0890) Prec@1 83.000 (84.750) Prec@5 100.000 (99.250) +2022-11-14 13:42:31,217 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0888) Prec@1 86.000 (84.846) Prec@5 98.000 (99.154) +2022-11-14 13:42:31,227 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0893) Prec@1 82.000 (84.643) Prec@5 98.000 (99.071) +2022-11-14 13:42:31,238 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0899) Prec@1 83.000 (84.533) Prec@5 99.000 (99.067) +2022-11-14 13:42:31,247 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0912) Prec@1 79.000 (84.188) Prec@5 99.000 (99.062) +2022-11-14 13:42:31,257 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0901) Prec@1 89.000 (84.471) Prec@5 99.000 (99.059) +2022-11-14 13:42:31,266 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0909) Prec@1 81.000 (84.278) Prec@5 100.000 (99.111) +2022-11-14 13:42:31,275 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0917) Prec@1 78.000 (83.947) Prec@5 98.000 (99.053) +2022-11-14 13:42:31,284 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1223 (0.0932) Prec@1 81.000 (83.800) Prec@5 98.000 (99.000) +2022-11-14 13:42:31,293 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1349 (0.0952) Prec@1 78.000 (83.524) Prec@5 98.000 (98.952) +2022-11-14 13:42:31,302 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0956) Prec@1 82.000 (83.455) Prec@5 95.000 (98.773) +2022-11-14 13:42:31,311 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1215 (0.0968) Prec@1 81.000 (83.348) Prec@5 99.000 (98.783) +2022-11-14 13:42:31,321 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0964) Prec@1 84.000 (83.375) Prec@5 99.000 (98.792) +2022-11-14 13:42:31,330 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0969) Prec@1 85.000 (83.440) Prec@5 99.000 (98.800) +2022-11-14 13:42:31,340 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.0975) Prec@1 79.000 (83.269) Prec@5 98.000 (98.769) +2022-11-14 13:42:31,349 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0974) Prec@1 83.000 (83.259) Prec@5 100.000 (98.815) +2022-11-14 13:42:31,359 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0969) Prec@1 86.000 (83.357) Prec@5 100.000 (98.857) +2022-11-14 13:42:31,369 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0964) Prec@1 85.000 (83.414) Prec@5 99.000 (98.862) +2022-11-14 13:42:31,379 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0961) Prec@1 87.000 (83.533) Prec@5 100.000 (98.900) +2022-11-14 13:42:31,388 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0962) Prec@1 81.000 (83.452) Prec@5 98.000 (98.871) +2022-11-14 13:42:31,398 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0957) Prec@1 89.000 (83.625) Prec@5 98.000 (98.844) +2022-11-14 13:42:31,406 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0954) Prec@1 86.000 (83.697) Prec@5 99.000 (98.848) +2022-11-14 13:42:31,416 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0954) Prec@1 84.000 (83.706) Prec@5 99.000 (98.853) +2022-11-14 13:42:31,424 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0956) Prec@1 82.000 (83.657) Prec@5 97.000 (98.800) +2022-11-14 13:42:31,432 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0959) Prec@1 79.000 (83.528) Prec@5 99.000 (98.806) +2022-11-14 13:42:31,441 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.0964) Prec@1 82.000 (83.486) Prec@5 97.000 (98.757) +2022-11-14 13:42:31,450 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1353 (0.0974) Prec@1 77.000 (83.316) Prec@5 98.000 (98.737) +2022-11-14 13:42:31,459 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0967) Prec@1 89.000 (83.462) Prec@5 100.000 (98.769) +2022-11-14 13:42:31,468 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0959) Prec@1 89.000 (83.600) Prec@5 100.000 (98.800) +2022-11-14 13:42:31,477 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0961) Prec@1 84.000 (83.610) Prec@5 98.000 (98.780) +2022-11-14 13:42:31,486 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0955) Prec@1 87.000 (83.690) Prec@5 97.000 (98.738) +2022-11-14 13:42:31,497 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0948) Prec@1 87.000 (83.767) Prec@5 100.000 (98.767) +2022-11-14 13:42:31,509 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0947) Prec@1 86.000 (83.818) Prec@5 98.000 (98.750) +2022-11-14 13:42:31,521 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0947) Prec@1 83.000 (83.800) Prec@5 99.000 (98.756) +2022-11-14 13:42:31,534 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0950) Prec@1 83.000 (83.783) Prec@5 100.000 (98.783) +2022-11-14 13:42:31,545 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0947) Prec@1 86.000 (83.830) Prec@5 99.000 (98.787) +2022-11-14 13:42:31,557 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.0954) Prec@1 78.000 (83.708) Prec@5 100.000 (98.812) +2022-11-14 13:42:31,570 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0947) Prec@1 90.000 (83.837) Prec@5 100.000 (98.837) +2022-11-14 13:42:31,582 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.0952) Prec@1 79.000 (83.740) Prec@5 99.000 (98.840) +2022-11-14 13:42:31,595 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0952) Prec@1 84.000 (83.745) Prec@5 97.000 (98.804) +2022-11-14 13:42:31,608 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0953) Prec@1 82.000 (83.712) Prec@5 98.000 (98.788) +2022-11-14 13:42:31,620 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0952) Prec@1 81.000 (83.660) Prec@5 99.000 (98.792) +2022-11-14 13:42:31,631 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0949) Prec@1 83.000 (83.648) Prec@5 99.000 (98.796) +2022-11-14 13:42:31,640 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0951) Prec@1 83.000 (83.636) Prec@5 100.000 (98.818) +2022-11-14 13:42:31,649 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0948) Prec@1 86.000 (83.679) Prec@5 99.000 (98.821) +2022-11-14 13:42:31,659 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0950) Prec@1 82.000 (83.649) Prec@5 99.000 (98.825) +2022-11-14 13:42:31,668 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0945) Prec@1 88.000 (83.724) Prec@5 99.000 (98.828) +2022-11-14 13:42:31,677 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0947) Prec@1 84.000 (83.729) Prec@5 99.000 (98.831) +2022-11-14 13:42:31,688 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0948) Prec@1 83.000 (83.717) Prec@5 100.000 (98.850) +2022-11-14 13:42:31,697 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0948) Prec@1 83.000 (83.705) Prec@5 100.000 (98.869) +2022-11-14 13:42:31,705 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0949) Prec@1 85.000 (83.726) Prec@5 99.000 (98.871) +2022-11-14 13:42:31,715 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0945) Prec@1 91.000 (83.841) Prec@5 99.000 (98.873) +2022-11-14 13:42:31,724 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0940) Prec@1 91.000 (83.953) Prec@5 100.000 (98.891) +2022-11-14 13:42:31,733 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0940) Prec@1 82.000 (83.923) Prec@5 99.000 (98.892) +2022-11-14 13:42:31,745 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0941) Prec@1 82.000 (83.894) Prec@5 98.000 (98.879) +2022-11-14 13:42:31,757 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0938) Prec@1 84.000 (83.896) Prec@5 100.000 (98.896) +2022-11-14 13:42:31,770 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0938) Prec@1 85.000 (83.912) Prec@5 99.000 (98.897) +2022-11-14 13:42:31,783 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0936) Prec@1 89.000 (83.986) Prec@5 99.000 (98.899) +2022-11-14 13:42:31,795 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0937) Prec@1 80.000 (83.929) Prec@5 98.000 (98.886) +2022-11-14 13:42:31,807 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0939) Prec@1 83.000 (83.915) Prec@5 100.000 (98.901) +2022-11-14 13:42:31,819 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0939) Prec@1 85.000 (83.931) Prec@5 97.000 (98.875) +2022-11-14 13:42:31,831 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0937) Prec@1 85.000 (83.945) Prec@5 100.000 (98.890) +2022-11-14 13:42:31,842 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0933) Prec@1 89.000 (84.014) Prec@5 100.000 (98.905) +2022-11-14 13:42:31,853 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.0935) Prec@1 80.000 (83.960) Prec@5 98.000 (98.893) +2022-11-14 13:42:31,866 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0935) Prec@1 83.000 (83.947) Prec@5 98.000 (98.882) +2022-11-14 13:42:31,877 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0934) Prec@1 85.000 (83.961) Prec@5 100.000 (98.896) +2022-11-14 13:42:31,890 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0933) Prec@1 87.000 (84.000) Prec@5 98.000 (98.885) +2022-11-14 13:42:31,902 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0934) Prec@1 82.000 (83.975) Prec@5 100.000 (98.899) +2022-11-14 13:42:31,913 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0933) Prec@1 82.000 (83.950) Prec@5 99.000 (98.900) +2022-11-14 13:42:31,925 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0932) Prec@1 88.000 (84.000) Prec@5 98.000 (98.889) +2022-11-14 13:42:31,937 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0934) Prec@1 82.000 (83.976) Prec@5 98.000 (98.878) +2022-11-14 13:42:31,949 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0933) Prec@1 82.000 (83.952) Prec@5 98.000 (98.867) +2022-11-14 13:42:31,960 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0932) Prec@1 88.000 (84.000) Prec@5 99.000 (98.869) +2022-11-14 13:42:31,971 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1379 (0.0937) Prec@1 76.000 (83.906) Prec@5 97.000 (98.847) +2022-11-14 13:42:31,980 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0936) Prec@1 83.000 (83.895) Prec@5 98.000 (98.837) +2022-11-14 13:42:31,991 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0935) Prec@1 86.000 (83.920) Prec@5 99.000 (98.839) +2022-11-14 13:42:32,003 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0934) Prec@1 85.000 (83.932) Prec@5 100.000 (98.852) +2022-11-14 13:42:32,016 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0933) Prec@1 84.000 (83.933) Prec@5 98.000 (98.843) +2022-11-14 13:42:32,029 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0934) Prec@1 86.000 (83.956) Prec@5 99.000 (98.844) +2022-11-14 13:42:32,042 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0931) Prec@1 90.000 (84.022) Prec@5 100.000 (98.857) +2022-11-14 13:42:32,054 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0927) Prec@1 91.000 (84.098) Prec@5 99.000 (98.859) +2022-11-14 13:42:32,066 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0929) Prec@1 80.000 (84.054) Prec@5 99.000 (98.860) +2022-11-14 13:42:32,079 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0929) Prec@1 82.000 (84.032) Prec@5 97.000 (98.840) +2022-11-14 13:42:32,091 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0928) Prec@1 86.000 (84.053) Prec@5 99.000 (98.842) +2022-11-14 13:42:32,103 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0927) Prec@1 85.000 (84.062) Prec@5 100.000 (98.854) +2022-11-14 13:42:32,115 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0925) Prec@1 86.000 (84.082) Prec@5 100.000 (98.866) +2022-11-14 13:42:32,126 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0926) Prec@1 83.000 (84.071) Prec@5 97.000 (98.847) +2022-11-14 13:42:32,135 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1229 (0.0929) Prec@1 77.000 (84.000) Prec@5 100.000 (98.859) +2022-11-14 13:42:32,144 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0930) Prec@1 81.000 (83.970) Prec@5 100.000 (98.870) +2022-11-14 13:42:32,200 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:42:32,557 Epoch: [82][0/500] Time 0.036 (0.036) Data 0.260 (0.260) Loss 0.0982 (0.0982) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 13:42:32,806 Epoch: [82][10/500] Time 0.016 (0.024) Data 0.002 (0.025) Loss 0.0718 (0.0850) Prec@1 89.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 13:42:33,089 Epoch: [82][20/500] Time 0.028 (0.024) Data 0.002 (0.014) Loss 0.0808 (0.0836) Prec@1 88.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 13:42:33,376 Epoch: [82][30/500] Time 0.030 (0.025) Data 0.002 (0.010) Loss 0.0709 (0.0804) Prec@1 89.000 (87.250) Prec@5 100.000 (99.750) +2022-11-14 13:42:33,763 Epoch: [82][40/500] Time 0.040 (0.027) Data 0.003 (0.008) Loss 0.0621 (0.0768) Prec@1 89.000 (87.600) Prec@5 97.000 (99.200) +2022-11-14 13:42:34,087 Epoch: [82][50/500] Time 0.030 (0.027) Data 0.003 (0.007) Loss 0.0546 (0.0731) Prec@1 93.000 (88.500) Prec@5 97.000 (98.833) +2022-11-14 13:42:34,422 Epoch: [82][60/500] Time 0.038 (0.028) Data 0.002 (0.006) Loss 0.0777 (0.0737) Prec@1 86.000 (88.143) Prec@5 100.000 (99.000) +2022-11-14 13:42:34,743 Epoch: [82][70/500] Time 0.030 (0.028) Data 0.002 (0.006) Loss 0.0803 (0.0745) Prec@1 84.000 (87.625) Prec@5 100.000 (99.125) +2022-11-14 13:42:35,073 Epoch: [82][80/500] Time 0.025 (0.028) Data 0.002 (0.005) Loss 0.0881 (0.0760) Prec@1 82.000 (87.000) Prec@5 100.000 (99.222) +2022-11-14 13:42:35,403 Epoch: [82][90/500] Time 0.029 (0.028) Data 0.002 (0.005) Loss 0.1026 (0.0787) Prec@1 84.000 (86.700) Prec@5 99.000 (99.200) +2022-11-14 13:42:35,721 Epoch: [82][100/500] Time 0.026 (0.028) Data 0.002 (0.005) Loss 0.0796 (0.0788) Prec@1 89.000 (86.909) Prec@5 100.000 (99.273) +2022-11-14 13:42:36,045 Epoch: [82][110/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.1068 (0.0811) Prec@1 83.000 (86.583) Prec@5 98.000 (99.167) +2022-11-14 13:42:36,367 Epoch: [82][120/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0786 (0.0809) Prec@1 87.000 (86.615) Prec@5 100.000 (99.231) +2022-11-14 13:42:36,689 Epoch: [82][130/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0536 (0.0790) Prec@1 90.000 (86.857) Prec@5 99.000 (99.214) +2022-11-14 13:42:37,011 Epoch: [82][140/500] Time 0.028 (0.028) Data 0.002 (0.004) Loss 0.0718 (0.0785) Prec@1 87.000 (86.867) Prec@5 99.000 (99.200) +2022-11-14 13:42:37,333 Epoch: [82][150/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0614 (0.0774) Prec@1 91.000 (87.125) Prec@5 98.000 (99.125) +2022-11-14 13:42:37,659 Epoch: [82][160/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.1092 (0.0793) Prec@1 80.000 (86.706) Prec@5 100.000 (99.176) +2022-11-14 13:42:37,985 Epoch: [82][170/500] Time 0.027 (0.028) Data 0.002 (0.004) Loss 0.1097 (0.0810) Prec@1 80.000 (86.333) Prec@5 99.000 (99.167) +2022-11-14 13:42:38,311 Epoch: [82][180/500] Time 0.027 (0.028) Data 0.002 (0.003) Loss 0.1024 (0.0821) Prec@1 83.000 (86.158) Prec@5 98.000 (99.105) +2022-11-14 13:42:38,637 Epoch: [82][190/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0476 (0.0804) Prec@1 91.000 (86.400) Prec@5 100.000 (99.150) +2022-11-14 13:42:38,968 Epoch: [82][200/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0523 (0.0790) Prec@1 92.000 (86.667) Prec@5 100.000 (99.190) +2022-11-14 13:42:39,295 Epoch: [82][210/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0884 (0.0795) Prec@1 83.000 (86.500) Prec@5 100.000 (99.227) +2022-11-14 13:42:39,621 Epoch: [82][220/500] Time 0.030 (0.028) Data 0.001 (0.003) Loss 0.0648 (0.0788) Prec@1 89.000 (86.609) Prec@5 98.000 (99.174) +2022-11-14 13:42:39,953 Epoch: [82][230/500] Time 0.037 (0.028) Data 0.002 (0.003) Loss 0.1002 (0.0797) Prec@1 81.000 (86.375) Prec@5 100.000 (99.208) +2022-11-14 13:42:40,277 Epoch: [82][240/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.1040 (0.0807) Prec@1 84.000 (86.280) Prec@5 97.000 (99.120) +2022-11-14 13:42:40,738 Epoch: [82][250/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0815 (0.0807) Prec@1 82.000 (86.115) Prec@5 100.000 (99.154) +2022-11-14 13:42:41,220 Epoch: [82][260/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0819 (0.0808) Prec@1 88.000 (86.185) Prec@5 99.000 (99.148) +2022-11-14 13:42:41,702 Epoch: [82][270/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0682 (0.0803) Prec@1 88.000 (86.250) Prec@5 100.000 (99.179) +2022-11-14 13:42:42,183 Epoch: [82][280/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0778 (0.0802) Prec@1 88.000 (86.310) Prec@5 99.000 (99.172) +2022-11-14 13:42:42,665 Epoch: [82][290/500] Time 0.048 (0.031) Data 0.002 (0.003) Loss 0.0682 (0.0798) Prec@1 88.000 (86.367) Prec@5 100.000 (99.200) +2022-11-14 13:42:43,282 Epoch: [82][300/500] Time 0.100 (0.032) Data 0.002 (0.003) Loss 0.1290 (0.0814) Prec@1 75.000 (86.000) Prec@5 99.000 (99.194) +2022-11-14 13:42:44,220 Epoch: [82][310/500] Time 0.096 (0.033) Data 0.002 (0.003) Loss 0.1312 (0.0830) Prec@1 77.000 (85.719) Prec@5 99.000 (99.188) +2022-11-14 13:42:45,052 Epoch: [82][320/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0782 (0.0828) Prec@1 86.000 (85.727) Prec@5 99.000 (99.182) +2022-11-14 13:42:45,531 Epoch: [82][330/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0770 (0.0827) Prec@1 87.000 (85.765) Prec@5 98.000 (99.147) +2022-11-14 13:42:46,005 Epoch: [82][340/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0694 (0.0823) Prec@1 88.000 (85.829) Prec@5 99.000 (99.143) +2022-11-14 13:42:46,479 Epoch: [82][350/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0887 (0.0825) Prec@1 87.000 (85.861) Prec@5 99.000 (99.139) +2022-11-14 13:42:46,953 Epoch: [82][360/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0613 (0.0819) Prec@1 90.000 (85.973) Prec@5 98.000 (99.108) +2022-11-14 13:42:47,424 Epoch: [82][370/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0980 (0.0823) Prec@1 85.000 (85.947) Prec@5 98.000 (99.079) +2022-11-14 13:42:47,896 Epoch: [82][380/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0691 (0.0820) Prec@1 89.000 (86.026) Prec@5 99.000 (99.077) +2022-11-14 13:42:48,367 Epoch: [82][390/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0977 (0.0824) Prec@1 80.000 (85.875) Prec@5 99.000 (99.075) +2022-11-14 13:42:48,845 Epoch: [82][400/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0718 (0.0821) Prec@1 87.000 (85.902) Prec@5 97.000 (99.024) +2022-11-14 13:42:49,325 Epoch: [82][410/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0656 (0.0817) Prec@1 89.000 (85.976) Prec@5 100.000 (99.048) +2022-11-14 13:42:49,795 Epoch: [82][420/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0766 (0.0816) Prec@1 85.000 (85.953) Prec@5 98.000 (99.023) +2022-11-14 13:42:50,264 Epoch: [82][430/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0629 (0.0812) Prec@1 90.000 (86.045) Prec@5 100.000 (99.045) +2022-11-14 13:42:50,734 Epoch: [82][440/500] Time 0.044 (0.037) Data 0.001 (0.003) Loss 0.1080 (0.0818) Prec@1 82.000 (85.956) Prec@5 98.000 (99.022) +2022-11-14 13:42:51,201 Epoch: [82][450/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0566 (0.0812) Prec@1 91.000 (86.065) Prec@5 99.000 (99.022) +2022-11-14 13:42:51,670 Epoch: [82][460/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0510 (0.0806) Prec@1 93.000 (86.213) Prec@5 100.000 (99.043) +2022-11-14 13:42:52,141 Epoch: [82][470/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.1058 (0.0811) Prec@1 82.000 (86.125) Prec@5 99.000 (99.042) +2022-11-14 13:42:52,611 Epoch: [82][480/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.0822 (0.0811) Prec@1 86.000 (86.122) Prec@5 99.000 (99.041) +2022-11-14 13:42:53,081 Epoch: [82][490/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0868 (0.0812) Prec@1 86.000 (86.120) Prec@5 99.000 (99.040) +2022-11-14 13:42:53,504 Epoch: [82][499/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.1234 (0.0821) Prec@1 78.000 (85.961) Prec@5 99.000 (99.039) +2022-11-14 13:42:53,788 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0650 (0.0650) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 13:42:53,801 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0802 (0.0726) Prec@1 86.000 (89.500) Prec@5 98.000 (99.000) +2022-11-14 13:42:53,811 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0694 (0.0716) Prec@1 89.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 13:42:53,825 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0885 (0.0758) Prec@1 84.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 13:42:53,835 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1100 (0.0826) Prec@1 79.000 (86.200) Prec@5 100.000 (99.400) +2022-11-14 13:42:53,847 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0489 (0.0770) Prec@1 92.000 (87.167) Prec@5 99.000 (99.333) +2022-11-14 13:42:53,858 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0766) Prec@1 88.000 (87.286) Prec@5 100.000 (99.429) +2022-11-14 13:42:53,872 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1185 (0.0819) Prec@1 77.000 (86.000) Prec@5 97.000 (99.125) +2022-11-14 13:42:53,881 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0834) Prec@1 83.000 (85.667) Prec@5 99.000 (99.111) +2022-11-14 13:42:53,892 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0830) Prec@1 87.000 (85.800) Prec@5 98.000 (99.000) +2022-11-14 13:42:53,901 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0816) Prec@1 88.000 (86.000) Prec@5 100.000 (99.091) +2022-11-14 13:42:53,910 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0814) Prec@1 89.000 (86.250) Prec@5 99.000 (99.083) +2022-11-14 13:42:53,919 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0818) Prec@1 86.000 (86.231) Prec@5 99.000 (99.077) +2022-11-14 13:42:53,931 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0829) Prec@1 83.000 (86.000) Prec@5 99.000 (99.071) +2022-11-14 13:42:53,944 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0840) Prec@1 81.000 (85.667) Prec@5 98.000 (99.000) +2022-11-14 13:42:53,955 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0846) Prec@1 86.000 (85.688) Prec@5 99.000 (99.000) +2022-11-14 13:42:53,968 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0842) Prec@1 86.000 (85.706) Prec@5 98.000 (98.941) +2022-11-14 13:42:53,980 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0853) Prec@1 81.000 (85.444) Prec@5 100.000 (99.000) +2022-11-14 13:42:53,993 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0867) Prec@1 78.000 (85.053) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,004 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0882) Prec@1 82.000 (84.900) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,017 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0886) Prec@1 83.000 (84.810) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,029 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0893) Prec@1 82.000 (84.682) Prec@5 97.000 (98.909) +2022-11-14 13:42:54,042 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0896) Prec@1 83.000 (84.609) Prec@5 99.000 (98.913) +2022-11-14 13:42:54,053 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0894) Prec@1 85.000 (84.625) Prec@5 100.000 (98.958) +2022-11-14 13:42:54,066 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0889) Prec@1 89.000 (84.800) Prec@5 100.000 (99.000) +2022-11-14 13:42:54,081 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.0901) Prec@1 77.000 (84.500) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,092 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0897) Prec@1 88.000 (84.630) Prec@5 100.000 (99.037) +2022-11-14 13:42:54,102 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0899) Prec@1 84.000 (84.607) Prec@5 99.000 (99.036) +2022-11-14 13:42:54,114 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0896) Prec@1 87.000 (84.690) Prec@5 98.000 (99.000) +2022-11-14 13:42:54,125 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0893) Prec@1 85.000 (84.700) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,136 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0890) Prec@1 84.000 (84.677) Prec@5 98.000 (98.968) +2022-11-14 13:42:54,147 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0889) Prec@1 85.000 (84.688) Prec@5 100.000 (99.000) +2022-11-14 13:42:54,158 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0884) Prec@1 88.000 (84.788) Prec@5 98.000 (98.970) +2022-11-14 13:42:54,169 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.0891) Prec@1 78.000 (84.588) Prec@5 99.000 (98.971) +2022-11-14 13:42:54,181 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0892) Prec@1 83.000 (84.543) Prec@5 96.000 (98.886) +2022-11-14 13:42:54,192 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0892) Prec@1 86.000 (84.583) Prec@5 98.000 (98.861) +2022-11-14 13:42:54,205 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.0901) Prec@1 79.000 (84.432) Prec@5 97.000 (98.811) +2022-11-14 13:42:54,219 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.0910) Prec@1 74.000 (84.158) Prec@5 99.000 (98.816) +2022-11-14 13:42:54,231 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0907) Prec@1 90.000 (84.308) Prec@5 100.000 (98.846) +2022-11-14 13:42:54,241 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0904) Prec@1 85.000 (84.325) Prec@5 100.000 (98.875) +2022-11-14 13:42:54,254 Test: [40/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0907) Prec@1 82.000 (84.268) Prec@5 98.000 (98.854) +2022-11-14 13:42:54,268 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0903) Prec@1 89.000 (84.381) Prec@5 98.000 (98.833) +2022-11-14 13:42:54,279 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0898) Prec@1 88.000 (84.465) Prec@5 100.000 (98.860) +2022-11-14 13:42:54,289 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0897) Prec@1 86.000 (84.500) Prec@5 98.000 (98.841) +2022-11-14 13:42:54,302 Test: [44/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0898) Prec@1 85.000 (84.511) Prec@5 100.000 (98.867) +2022-11-14 13:42:54,314 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0901) Prec@1 82.000 (84.457) Prec@5 100.000 (98.891) +2022-11-14 13:42:54,325 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0894) Prec@1 87.000 (84.511) Prec@5 100.000 (98.915) +2022-11-14 13:42:54,335 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0898) Prec@1 83.000 (84.479) Prec@5 100.000 (98.938) +2022-11-14 13:42:54,348 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0894) Prec@1 88.000 (84.551) Prec@5 100.000 (98.959) +2022-11-14 13:42:54,359 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1438 (0.0905) Prec@1 74.000 (84.340) Prec@5 99.000 (98.960) +2022-11-14 13:42:54,372 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0901) Prec@1 90.000 (84.451) Prec@5 99.000 (98.961) +2022-11-14 13:42:54,385 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0902) Prec@1 82.000 (84.404) Prec@5 100.000 (98.981) +2022-11-14 13:42:54,396 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0903) Prec@1 81.000 (84.340) Prec@5 99.000 (98.981) +2022-11-14 13:42:54,407 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0900) Prec@1 87.000 (84.389) Prec@5 99.000 (98.981) +2022-11-14 13:42:54,418 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0901) Prec@1 83.000 (84.364) Prec@5 100.000 (99.000) +2022-11-14 13:42:54,429 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0898) Prec@1 87.000 (84.411) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,441 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0898) Prec@1 87.000 (84.456) Prec@5 100.000 (99.018) +2022-11-14 13:42:54,453 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0895) Prec@1 91.000 (84.569) Prec@5 99.000 (99.017) +2022-11-14 13:42:54,464 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.0900) Prec@1 80.000 (84.492) Prec@5 100.000 (99.034) +2022-11-14 13:42:54,476 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0898) Prec@1 85.000 (84.500) Prec@5 98.000 (99.017) +2022-11-14 13:42:54,490 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0900) Prec@1 80.000 (84.426) Prec@5 100.000 (99.033) +2022-11-14 13:42:54,501 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0897) Prec@1 89.000 (84.500) Prec@5 100.000 (99.048) +2022-11-14 13:42:54,512 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0894) Prec@1 88.000 (84.556) Prec@5 100.000 (99.063) +2022-11-14 13:42:54,523 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0891) Prec@1 87.000 (84.594) Prec@5 100.000 (99.078) +2022-11-14 13:42:54,535 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0891) Prec@1 84.000 (84.585) Prec@5 100.000 (99.092) +2022-11-14 13:42:54,546 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0892) Prec@1 85.000 (84.591) Prec@5 99.000 (99.091) +2022-11-14 13:42:54,557 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0890) Prec@1 87.000 (84.627) Prec@5 99.000 (99.090) +2022-11-14 13:42:54,568 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0891) Prec@1 82.000 (84.588) Prec@5 98.000 (99.074) +2022-11-14 13:42:54,580 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0888) Prec@1 90.000 (84.667) Prec@5 98.000 (99.058) +2022-11-14 13:42:54,593 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.0892) Prec@1 78.000 (84.571) Prec@5 99.000 (99.057) +2022-11-14 13:42:54,605 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0893) Prec@1 85.000 (84.577) Prec@5 98.000 (99.042) +2022-11-14 13:42:54,616 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0890) Prec@1 88.000 (84.625) Prec@5 100.000 (99.056) +2022-11-14 13:42:54,629 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0892) Prec@1 81.000 (84.575) Prec@5 100.000 (99.068) +2022-11-14 13:42:54,642 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0891) Prec@1 88.000 (84.622) Prec@5 100.000 (99.081) +2022-11-14 13:42:54,654 Test: [74/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0892) Prec@1 80.000 (84.560) Prec@5 100.000 (99.093) +2022-11-14 13:42:54,667 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0891) Prec@1 86.000 (84.579) Prec@5 98.000 (99.079) +2022-11-14 13:42:54,679 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0891) Prec@1 84.000 (84.571) Prec@5 100.000 (99.091) +2022-11-14 13:42:54,691 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.0896) Prec@1 79.000 (84.500) Prec@5 95.000 (99.038) +2022-11-14 13:42:54,702 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0897) Prec@1 84.000 (84.494) Prec@5 100.000 (99.051) +2022-11-14 13:42:54,712 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0897) Prec@1 83.000 (84.475) Prec@5 99.000 (99.050) +2022-11-14 13:42:54,722 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0895) Prec@1 88.000 (84.519) Prec@5 100.000 (99.062) +2022-11-14 13:42:54,733 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0897) Prec@1 83.000 (84.500) Prec@5 96.000 (99.024) +2022-11-14 13:42:54,742 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0899) Prec@1 81.000 (84.458) Prec@5 100.000 (99.036) +2022-11-14 13:42:54,752 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0898) Prec@1 85.000 (84.464) Prec@5 98.000 (99.024) +2022-11-14 13:42:54,762 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1172 (0.0902) Prec@1 79.000 (84.400) Prec@5 97.000 (99.000) +2022-11-14 13:42:54,773 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0900) Prec@1 88.000 (84.442) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,783 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0899) Prec@1 85.000 (84.448) Prec@5 100.000 (99.011) +2022-11-14 13:42:54,795 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0899) Prec@1 87.000 (84.477) Prec@5 98.000 (99.000) +2022-11-14 13:42:54,805 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0897) Prec@1 87.000 (84.506) Prec@5 98.000 (98.989) +2022-11-14 13:42:54,815 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0897) Prec@1 83.000 (84.489) Prec@5 99.000 (98.989) +2022-11-14 13:42:54,827 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0896) Prec@1 88.000 (84.527) Prec@5 99.000 (98.989) +2022-11-14 13:42:54,837 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0891) Prec@1 90.000 (84.587) Prec@5 99.000 (98.989) +2022-11-14 13:42:54,849 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0892) Prec@1 83.000 (84.570) Prec@5 99.000 (98.989) +2022-11-14 13:42:54,861 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0892) Prec@1 87.000 (84.596) Prec@5 100.000 (99.000) +2022-11-14 13:42:54,870 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0892) Prec@1 84.000 (84.589) Prec@5 99.000 (99.000) +2022-11-14 13:42:54,883 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0890) Prec@1 87.000 (84.615) Prec@5 100.000 (99.010) +2022-11-14 13:42:54,894 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0888) Prec@1 90.000 (84.670) Prec@5 100.000 (99.021) +2022-11-14 13:42:54,907 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0890) Prec@1 82.000 (84.643) Prec@5 100.000 (99.031) +2022-11-14 13:42:54,918 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0893) Prec@1 78.000 (84.576) Prec@5 99.000 (99.030) +2022-11-14 13:42:54,929 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0892) Prec@1 87.000 (84.600) Prec@5 99.000 (99.030) +2022-11-14 13:42:54,986 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:42:55,306 Epoch: [83][0/500] Time 0.035 (0.035) Data 0.227 (0.227) Loss 0.0851 (0.0851) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:42:55,515 Epoch: [83][10/500] Time 0.016 (0.020) Data 0.002 (0.022) Loss 0.0946 (0.0898) Prec@1 85.000 (85.000) Prec@5 99.000 (98.500) +2022-11-14 13:42:55,714 Epoch: [83][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0734 (0.0843) Prec@1 88.000 (86.000) Prec@5 99.000 (98.667) +2022-11-14 13:42:55,917 Epoch: [83][30/500] Time 0.015 (0.018) Data 0.002 (0.009) Loss 0.0599 (0.0782) Prec@1 90.000 (87.000) Prec@5 100.000 (99.000) +2022-11-14 13:42:56,171 Epoch: [83][40/500] Time 0.028 (0.019) Data 0.002 (0.007) Loss 0.0782 (0.0782) Prec@1 85.000 (86.600) Prec@5 100.000 (99.200) +2022-11-14 13:42:56,540 Epoch: [83][50/500] Time 0.035 (0.022) Data 0.002 (0.006) Loss 0.0650 (0.0760) Prec@1 89.000 (87.000) Prec@5 99.000 (99.167) +2022-11-14 13:42:56,914 Epoch: [83][60/500] Time 0.034 (0.024) Data 0.002 (0.005) Loss 0.0643 (0.0743) Prec@1 90.000 (87.429) Prec@5 100.000 (99.286) +2022-11-14 13:42:57,290 Epoch: [83][70/500] Time 0.034 (0.025) Data 0.001 (0.005) Loss 0.1187 (0.0799) Prec@1 79.000 (86.375) Prec@5 97.000 (99.000) +2022-11-14 13:42:57,668 Epoch: [83][80/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.0733 (0.0792) Prec@1 87.000 (86.444) Prec@5 99.000 (99.000) +2022-11-14 13:42:58,040 Epoch: [83][90/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0770 (0.0789) Prec@1 87.000 (86.500) Prec@5 99.000 (99.000) +2022-11-14 13:42:58,421 Epoch: [83][100/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.0730 (0.0784) Prec@1 88.000 (86.636) Prec@5 100.000 (99.091) +2022-11-14 13:42:58,797 Epoch: [83][110/500] Time 0.037 (0.028) Data 0.002 (0.004) Loss 0.0905 (0.0794) Prec@1 85.000 (86.500) Prec@5 99.000 (99.083) +2022-11-14 13:42:59,171 Epoch: [83][120/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0816 (0.0796) Prec@1 84.000 (86.308) Prec@5 100.000 (99.154) +2022-11-14 13:42:59,552 Epoch: [83][130/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0650 (0.0785) Prec@1 87.000 (86.357) Prec@5 100.000 (99.214) +2022-11-14 13:42:59,937 Epoch: [83][140/500] Time 0.033 (0.029) Data 0.001 (0.003) Loss 0.0901 (0.0793) Prec@1 85.000 (86.267) Prec@5 99.000 (99.200) +2022-11-14 13:43:00,388 Epoch: [83][150/500] Time 0.023 (0.030) Data 0.002 (0.003) Loss 0.0643 (0.0784) Prec@1 87.000 (86.312) Prec@5 99.000 (99.188) +2022-11-14 13:43:00,755 Epoch: [83][160/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0632 (0.0775) Prec@1 89.000 (86.471) Prec@5 100.000 (99.235) +2022-11-14 13:43:01,221 Epoch: [83][170/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0982 (0.0786) Prec@1 84.000 (86.333) Prec@5 97.000 (99.111) +2022-11-14 13:43:01,575 Epoch: [83][180/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0652 (0.0779) Prec@1 89.000 (86.474) Prec@5 99.000 (99.105) +2022-11-14 13:43:01,951 Epoch: [83][190/500] Time 0.036 (0.031) Data 0.003 (0.003) Loss 0.0980 (0.0789) Prec@1 84.000 (86.350) Prec@5 97.000 (99.000) +2022-11-14 13:43:02,337 Epoch: [83][200/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0776 (0.0789) Prec@1 87.000 (86.381) Prec@5 99.000 (99.000) +2022-11-14 13:43:02,708 Epoch: [83][210/500] Time 0.032 (0.031) Data 0.003 (0.003) Loss 0.0696 (0.0784) Prec@1 85.000 (86.318) Prec@5 100.000 (99.045) +2022-11-14 13:43:03,082 Epoch: [83][220/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0903 (0.0790) Prec@1 84.000 (86.217) Prec@5 99.000 (99.043) +2022-11-14 13:43:03,457 Epoch: [83][230/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0857 (0.0792) Prec@1 87.000 (86.250) Prec@5 99.000 (99.042) +2022-11-14 13:43:03,872 Epoch: [83][240/500] Time 0.049 (0.032) Data 0.002 (0.003) Loss 0.0742 (0.0790) Prec@1 88.000 (86.320) Prec@5 100.000 (99.080) +2022-11-14 13:43:04,225 Epoch: [83][250/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0965 (0.0797) Prec@1 84.000 (86.231) Prec@5 99.000 (99.077) +2022-11-14 13:43:04,619 Epoch: [83][260/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0630 (0.0791) Prec@1 89.000 (86.333) Prec@5 99.000 (99.074) +2022-11-14 13:43:05,097 Epoch: [83][270/500] Time 0.048 (0.032) Data 0.002 (0.003) Loss 0.0665 (0.0786) Prec@1 89.000 (86.429) Prec@5 99.000 (99.071) +2022-11-14 13:43:05,573 Epoch: [83][280/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0812 (0.0787) Prec@1 85.000 (86.379) Prec@5 100.000 (99.103) +2022-11-14 13:43:05,926 Epoch: [83][290/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0847 (0.0789) Prec@1 86.000 (86.367) Prec@5 99.000 (99.100) +2022-11-14 13:43:06,308 Epoch: [83][300/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0498 (0.0780) Prec@1 92.000 (86.548) Prec@5 100.000 (99.129) +2022-11-14 13:43:06,687 Epoch: [83][310/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0735 (0.0778) Prec@1 88.000 (86.594) Prec@5 99.000 (99.125) +2022-11-14 13:43:07,065 Epoch: [83][320/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0701 (0.0776) Prec@1 86.000 (86.576) Prec@5 100.000 (99.152) +2022-11-14 13:43:07,478 Epoch: [83][330/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.0906 (0.0780) Prec@1 84.000 (86.500) Prec@5 100.000 (99.176) +2022-11-14 13:43:07,857 Epoch: [83][340/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0748 (0.0779) Prec@1 89.000 (86.571) Prec@5 99.000 (99.171) +2022-11-14 13:43:08,226 Epoch: [83][350/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0497 (0.0771) Prec@1 91.000 (86.694) Prec@5 100.000 (99.194) +2022-11-14 13:43:08,713 Epoch: [83][360/500] Time 0.045 (0.033) Data 0.002 (0.003) Loss 0.0714 (0.0770) Prec@1 84.000 (86.622) Prec@5 99.000 (99.189) +2022-11-14 13:43:09,163 Epoch: [83][370/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0655 (0.0767) Prec@1 89.000 (86.684) Prec@5 100.000 (99.211) +2022-11-14 13:43:09,525 Epoch: [83][380/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0819 (0.0768) Prec@1 83.000 (86.590) Prec@5 98.000 (99.179) +2022-11-14 13:43:09,908 Epoch: [83][390/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0787 (0.0768) Prec@1 85.000 (86.550) Prec@5 98.000 (99.150) +2022-11-14 13:43:10,285 Epoch: [83][400/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0662 (0.0766) Prec@1 90.000 (86.634) Prec@5 100.000 (99.171) +2022-11-14 13:43:10,662 Epoch: [83][410/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0924 (0.0770) Prec@1 84.000 (86.571) Prec@5 98.000 (99.143) +2022-11-14 13:43:11,039 Epoch: [83][420/500] Time 0.033 (0.033) Data 0.002 (0.002) Loss 0.0786 (0.0770) Prec@1 87.000 (86.581) Prec@5 100.000 (99.163) +2022-11-14 13:43:11,424 Epoch: [83][430/500] Time 0.033 (0.033) Data 0.002 (0.002) Loss 0.0914 (0.0773) Prec@1 83.000 (86.500) Prec@5 100.000 (99.182) +2022-11-14 13:43:11,811 Epoch: [83][440/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0948 (0.0777) Prec@1 82.000 (86.400) Prec@5 99.000 (99.178) +2022-11-14 13:43:12,185 Epoch: [83][450/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0770 (0.0777) Prec@1 88.000 (86.435) Prec@5 99.000 (99.174) +2022-11-14 13:43:12,565 Epoch: [83][460/500] Time 0.032 (0.033) Data 0.002 (0.002) Loss 0.0792 (0.0777) Prec@1 86.000 (86.426) Prec@5 98.000 (99.149) +2022-11-14 13:43:12,940 Epoch: [83][470/500] Time 0.033 (0.033) Data 0.001 (0.002) Loss 0.0920 (0.0780) Prec@1 84.000 (86.375) Prec@5 97.000 (99.104) +2022-11-14 13:43:13,322 Epoch: [83][480/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0573 (0.0776) Prec@1 91.000 (86.469) Prec@5 100.000 (99.122) +2022-11-14 13:43:13,697 Epoch: [83][490/500] Time 0.036 (0.033) Data 0.003 (0.002) Loss 0.0591 (0.0772) Prec@1 90.000 (86.540) Prec@5 100.000 (99.140) +2022-11-14 13:43:14,034 Epoch: [83][499/500] Time 0.036 (0.033) Data 0.001 (0.002) Loss 0.0980 (0.0776) Prec@1 86.000 (86.529) Prec@5 100.000 (99.157) +2022-11-14 13:43:14,341 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0542 (0.0542) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,350 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0675) Prec@1 85.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,362 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0725) Prec@1 86.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,378 Test: [3/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0732) Prec@1 85.000 (86.750) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,388 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.0790) Prec@1 83.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,396 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0764) Prec@1 87.000 (86.167) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,406 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0739) Prec@1 91.000 (86.857) Prec@5 100.000 (100.000) +2022-11-14 13:43:14,420 Test: [7/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1123 (0.0787) Prec@1 81.000 (86.125) Prec@5 96.000 (99.500) +2022-11-14 13:43:14,431 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1124 (0.0824) Prec@1 81.000 (85.556) Prec@5 98.000 (99.333) +2022-11-14 13:43:14,440 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0822) Prec@1 86.000 (85.600) Prec@5 99.000 (99.300) +2022-11-14 13:43:14,451 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0818) Prec@1 88.000 (85.818) Prec@5 100.000 (99.364) +2022-11-14 13:43:14,462 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0821) Prec@1 87.000 (85.917) Prec@5 98.000 (99.250) +2022-11-14 13:43:14,473 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0831) Prec@1 82.000 (85.615) Prec@5 100.000 (99.308) +2022-11-14 13:43:14,482 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.0849) Prec@1 80.000 (85.214) Prec@5 99.000 (99.286) +2022-11-14 13:43:14,493 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0859) Prec@1 82.000 (85.000) Prec@5 98.000 (99.200) +2022-11-14 13:43:14,502 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1208 (0.0881) Prec@1 76.000 (84.438) Prec@5 99.000 (99.188) +2022-11-14 13:43:14,513 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0873) Prec@1 87.000 (84.588) Prec@5 99.000 (99.176) +2022-11-14 13:43:14,524 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0877) Prec@1 82.000 (84.444) Prec@5 100.000 (99.222) +2022-11-14 13:43:14,534 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0885) Prec@1 82.000 (84.316) Prec@5 98.000 (99.158) +2022-11-14 13:43:14,543 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0890) Prec@1 83.000 (84.250) Prec@5 98.000 (99.100) +2022-11-14 13:43:14,553 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1200 (0.0905) Prec@1 78.000 (83.952) Prec@5 99.000 (99.095) +2022-11-14 13:43:14,562 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0909) Prec@1 82.000 (83.864) Prec@5 100.000 (99.136) +2022-11-14 13:43:14,571 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0918) Prec@1 81.000 (83.739) Prec@5 98.000 (99.087) +2022-11-14 13:43:14,581 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0918) Prec@1 85.000 (83.792) Prec@5 99.000 (99.083) +2022-11-14 13:43:14,592 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1249 (0.0931) Prec@1 80.000 (83.640) Prec@5 99.000 (99.080) +2022-11-14 13:43:14,603 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1194 (0.0941) Prec@1 78.000 (83.423) Prec@5 98.000 (99.038) +2022-11-14 13:43:14,614 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0933) Prec@1 87.000 (83.556) Prec@5 100.000 (99.074) +2022-11-14 13:43:14,624 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0932) Prec@1 86.000 (83.643) Prec@5 100.000 (99.107) +2022-11-14 13:43:14,635 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.0934) Prec@1 84.000 (83.655) Prec@5 97.000 (99.034) +2022-11-14 13:43:14,646 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0934) Prec@1 85.000 (83.700) Prec@5 99.000 (99.033) +2022-11-14 13:43:14,655 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0932) Prec@1 83.000 (83.677) Prec@5 99.000 (99.032) +2022-11-14 13:43:14,665 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0928) Prec@1 87.000 (83.781) Prec@5 99.000 (99.031) +2022-11-14 13:43:14,677 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0918) Prec@1 88.000 (83.909) Prec@5 99.000 (99.030) +2022-11-14 13:43:14,687 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0927) Prec@1 77.000 (83.706) Prec@5 98.000 (99.000) +2022-11-14 13:43:14,697 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0925) Prec@1 86.000 (83.771) Prec@5 99.000 (99.000) +2022-11-14 13:43:14,707 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0920) Prec@1 87.000 (83.861) Prec@5 99.000 (99.000) +2022-11-14 13:43:14,718 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0925) Prec@1 81.000 (83.784) Prec@5 98.000 (98.973) +2022-11-14 13:43:14,729 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0927) Prec@1 81.000 (83.711) Prec@5 97.000 (98.921) +2022-11-14 13:43:14,739 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0928) Prec@1 81.000 (83.641) Prec@5 100.000 (98.949) +2022-11-14 13:43:14,750 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0923) Prec@1 85.000 (83.675) Prec@5 100.000 (98.975) +2022-11-14 13:43:14,760 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.0929) Prec@1 80.000 (83.585) Prec@5 96.000 (98.902) +2022-11-14 13:43:14,771 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0927) Prec@1 87.000 (83.667) Prec@5 99.000 (98.905) +2022-11-14 13:43:14,781 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0920) Prec@1 91.000 (83.837) Prec@5 100.000 (98.930) +2022-11-14 13:43:14,792 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0918) Prec@1 88.000 (83.932) Prec@5 99.000 (98.932) +2022-11-14 13:43:14,801 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0921) Prec@1 84.000 (83.933) Prec@5 98.000 (98.911) +2022-11-14 13:43:14,812 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0926) Prec@1 81.000 (83.870) Prec@5 99.000 (98.913) +2022-11-14 13:43:14,823 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0924) Prec@1 85.000 (83.894) Prec@5 100.000 (98.936) +2022-11-14 13:43:14,834 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0926) Prec@1 83.000 (83.875) Prec@5 99.000 (98.938) +2022-11-14 13:43:14,843 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0921) Prec@1 89.000 (83.980) Prec@5 100.000 (98.959) +2022-11-14 13:43:14,854 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1392 (0.0931) Prec@1 72.000 (83.740) Prec@5 95.000 (98.880) +2022-11-14 13:43:14,864 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0930) Prec@1 85.000 (83.765) Prec@5 99.000 (98.882) +2022-11-14 13:43:14,874 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0932) Prec@1 82.000 (83.731) Prec@5 100.000 (98.904) +2022-11-14 13:43:14,885 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0931) Prec@1 85.000 (83.755) Prec@5 99.000 (98.906) +2022-11-14 13:43:14,896 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0927) Prec@1 88.000 (83.833) Prec@5 98.000 (98.889) +2022-11-14 13:43:14,906 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0928) Prec@1 84.000 (83.836) Prec@5 100.000 (98.909) +2022-11-14 13:43:14,917 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0929) Prec@1 83.000 (83.821) Prec@5 97.000 (98.875) +2022-11-14 13:43:14,927 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0930) Prec@1 80.000 (83.754) Prec@5 100.000 (98.895) +2022-11-14 13:43:14,938 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0928) Prec@1 86.000 (83.793) Prec@5 99.000 (98.897) +2022-11-14 13:43:14,948 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0932) Prec@1 80.000 (83.729) Prec@5 99.000 (98.898) +2022-11-14 13:43:14,958 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0929) Prec@1 89.000 (83.817) Prec@5 99.000 (98.900) +2022-11-14 13:43:14,968 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0930) Prec@1 82.000 (83.787) Prec@5 100.000 (98.918) +2022-11-14 13:43:14,979 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0932) Prec@1 82.000 (83.758) Prec@5 98.000 (98.903) +2022-11-14 13:43:14,989 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0931) Prec@1 85.000 (83.778) Prec@5 99.000 (98.905) +2022-11-14 13:43:15,000 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0929) Prec@1 85.000 (83.797) Prec@5 100.000 (98.922) +2022-11-14 13:43:15,010 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.0933) Prec@1 80.000 (83.738) Prec@5 99.000 (98.923) +2022-11-14 13:43:15,020 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0935) Prec@1 80.000 (83.682) Prec@5 98.000 (98.909) +2022-11-14 13:43:15,031 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0930) Prec@1 89.000 (83.761) Prec@5 100.000 (98.925) +2022-11-14 13:43:15,042 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0930) Prec@1 83.000 (83.750) Prec@5 99.000 (98.926) +2022-11-14 13:43:15,052 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0927) Prec@1 88.000 (83.812) Prec@5 99.000 (98.928) +2022-11-14 13:43:15,062 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1140 (0.0930) Prec@1 77.000 (83.714) Prec@5 98.000 (98.914) +2022-11-14 13:43:15,072 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0930) Prec@1 85.000 (83.732) Prec@5 100.000 (98.930) +2022-11-14 13:43:15,082 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0931) Prec@1 84.000 (83.736) Prec@5 100.000 (98.944) +2022-11-14 13:43:15,093 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0929) Prec@1 92.000 (83.849) Prec@5 99.000 (98.945) +2022-11-14 13:43:15,104 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0925) Prec@1 90.000 (83.932) Prec@5 100.000 (98.959) +2022-11-14 13:43:15,114 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0927) Prec@1 79.000 (83.867) Prec@5 98.000 (98.947) +2022-11-14 13:43:15,125 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0923) Prec@1 89.000 (83.934) Prec@5 98.000 (98.934) +2022-11-14 13:43:15,135 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0923) Prec@1 83.000 (83.922) Prec@5 98.000 (98.922) +2022-11-14 13:43:15,146 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0925) Prec@1 83.000 (83.910) Prec@5 99.000 (98.923) +2022-11-14 13:43:15,156 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0927) Prec@1 82.000 (83.886) Prec@5 100.000 (98.937) +2022-11-14 13:43:15,167 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0925) Prec@1 83.000 (83.875) Prec@5 100.000 (98.950) +2022-11-14 13:43:15,177 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0923) Prec@1 87.000 (83.914) Prec@5 100.000 (98.963) +2022-11-14 13:43:15,187 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0924) Prec@1 85.000 (83.927) Prec@5 99.000 (98.963) +2022-11-14 13:43:15,199 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0924) Prec@1 83.000 (83.916) Prec@5 99.000 (98.964) +2022-11-14 13:43:15,212 Test: [83/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0924) Prec@1 85.000 (83.929) Prec@5 98.000 (98.952) +2022-11-14 13:43:15,224 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0926) Prec@1 77.000 (83.847) Prec@5 100.000 (98.965) +2022-11-14 13:43:15,234 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.0929) Prec@1 81.000 (83.814) Prec@5 99.000 (98.965) +2022-11-14 13:43:15,244 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0929) Prec@1 85.000 (83.828) Prec@5 100.000 (98.977) +2022-11-14 13:43:15,253 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0928) Prec@1 84.000 (83.830) Prec@5 99.000 (98.977) +2022-11-14 13:43:15,261 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0927) Prec@1 84.000 (83.831) Prec@5 99.000 (98.978) +2022-11-14 13:43:15,271 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0926) Prec@1 86.000 (83.856) Prec@5 100.000 (98.989) +2022-11-14 13:43:15,282 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0923) Prec@1 89.000 (83.912) Prec@5 100.000 (99.000) +2022-11-14 13:43:15,292 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0921) Prec@1 84.000 (83.913) Prec@5 99.000 (99.000) +2022-11-14 13:43:15,301 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0921) Prec@1 83.000 (83.903) Prec@5 100.000 (99.011) +2022-11-14 13:43:15,309 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0921) Prec@1 82.000 (83.883) Prec@5 98.000 (99.000) +2022-11-14 13:43:15,319 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0920) Prec@1 87.000 (83.916) Prec@5 100.000 (99.011) +2022-11-14 13:43:15,328 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0920) Prec@1 83.000 (83.906) Prec@5 100.000 (99.021) +2022-11-14 13:43:15,337 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0917) Prec@1 89.000 (83.959) Prec@5 99.000 (99.021) +2022-11-14 13:43:15,347 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0919) Prec@1 83.000 (83.949) Prec@5 99.000 (99.020) +2022-11-14 13:43:15,356 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.0922) Prec@1 78.000 (83.889) Prec@5 100.000 (99.030) +2022-11-14 13:43:15,366 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0922) Prec@1 83.000 (83.880) Prec@5 99.000 (99.030) +2022-11-14 13:43:15,421 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:43:15,746 Epoch: [84][0/500] Time 0.033 (0.033) Data 0.227 (0.227) Loss 0.0806 (0.0806) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:16,113 Epoch: [84][10/500] Time 0.041 (0.032) Data 0.002 (0.022) Loss 0.0929 (0.0867) Prec@1 83.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:16,555 Epoch: [84][20/500] Time 0.041 (0.035) Data 0.002 (0.013) Loss 0.0394 (0.0709) Prec@1 93.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 13:43:16,998 Epoch: [84][30/500] Time 0.043 (0.037) Data 0.002 (0.009) Loss 0.0878 (0.0752) Prec@1 84.000 (86.750) Prec@5 99.000 (99.250) +2022-11-14 13:43:17,434 Epoch: [84][40/500] Time 0.040 (0.037) Data 0.002 (0.007) Loss 0.0906 (0.0783) Prec@1 85.000 (86.400) Prec@5 99.000 (99.200) +2022-11-14 13:43:17,870 Epoch: [84][50/500] Time 0.035 (0.038) Data 0.002 (0.006) Loss 0.0766 (0.0780) Prec@1 86.000 (86.333) Prec@5 98.000 (99.000) +2022-11-14 13:43:18,308 Epoch: [84][60/500] Time 0.040 (0.038) Data 0.002 (0.006) Loss 0.0652 (0.0762) Prec@1 90.000 (86.857) Prec@5 98.000 (98.857) +2022-11-14 13:43:18,748 Epoch: [84][70/500] Time 0.041 (0.038) Data 0.002 (0.005) Loss 0.0430 (0.0720) Prec@1 93.000 (87.625) Prec@5 100.000 (99.000) +2022-11-14 13:43:19,187 Epoch: [84][80/500] Time 0.042 (0.038) Data 0.002 (0.005) Loss 0.0558 (0.0702) Prec@1 91.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:19,634 Epoch: [84][90/500] Time 0.041 (0.038) Data 0.002 (0.004) Loss 0.1031 (0.0735) Prec@1 82.000 (87.400) Prec@5 100.000 (99.100) +2022-11-14 13:43:20,069 Epoch: [84][100/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0695 (0.0731) Prec@1 89.000 (87.545) Prec@5 99.000 (99.091) +2022-11-14 13:43:20,507 Epoch: [84][110/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0589 (0.0719) Prec@1 91.000 (87.833) Prec@5 100.000 (99.167) +2022-11-14 13:43:20,943 Epoch: [84][120/500] Time 0.039 (0.038) Data 0.002 (0.004) Loss 0.0605 (0.0711) Prec@1 91.000 (88.077) Prec@5 98.000 (99.077) +2022-11-14 13:43:21,396 Epoch: [84][130/500] Time 0.036 (0.038) Data 0.003 (0.004) Loss 0.0963 (0.0729) Prec@1 82.000 (87.643) Prec@5 98.000 (99.000) +2022-11-14 13:43:21,854 Epoch: [84][140/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0682 (0.0726) Prec@1 89.000 (87.733) Prec@5 97.000 (98.867) +2022-11-14 13:43:22,289 Epoch: [84][150/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0581 (0.0717) Prec@1 91.000 (87.938) Prec@5 99.000 (98.875) +2022-11-14 13:43:22,732 Epoch: [84][160/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.1063 (0.0737) Prec@1 85.000 (87.765) Prec@5 98.000 (98.824) +2022-11-14 13:43:23,193 Epoch: [84][170/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0566 (0.0727) Prec@1 91.000 (87.944) Prec@5 100.000 (98.889) +2022-11-14 13:43:23,629 Epoch: [84][180/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0892 (0.0736) Prec@1 83.000 (87.684) Prec@5 100.000 (98.947) +2022-11-14 13:43:24,067 Epoch: [84][190/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.1068 (0.0753) Prec@1 84.000 (87.500) Prec@5 97.000 (98.850) +2022-11-14 13:43:24,506 Epoch: [84][200/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0539 (0.0743) Prec@1 93.000 (87.762) Prec@5 99.000 (98.857) +2022-11-14 13:43:24,935 Epoch: [84][210/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0634 (0.0738) Prec@1 90.000 (87.864) Prec@5 99.000 (98.864) +2022-11-14 13:43:25,352 Epoch: [84][220/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.1028 (0.0750) Prec@1 79.000 (87.478) Prec@5 99.000 (98.870) +2022-11-14 13:43:25,778 Epoch: [84][230/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0474 (0.0739) Prec@1 91.000 (87.625) Prec@5 100.000 (98.917) +2022-11-14 13:43:26,223 Epoch: [84][240/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0695 (0.0737) Prec@1 90.000 (87.720) Prec@5 99.000 (98.920) +2022-11-14 13:43:26,651 Epoch: [84][250/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0836 (0.0741) Prec@1 86.000 (87.654) Prec@5 99.000 (98.923) +2022-11-14 13:43:27,085 Epoch: [84][260/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0585 (0.0735) Prec@1 90.000 (87.741) Prec@5 100.000 (98.963) +2022-11-14 13:43:27,552 Epoch: [84][270/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0743 (0.0735) Prec@1 86.000 (87.679) Prec@5 99.000 (98.964) +2022-11-14 13:43:28,036 Epoch: [84][280/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0792 (0.0737) Prec@1 86.000 (87.621) Prec@5 99.000 (98.966) +2022-11-14 13:43:28,530 Epoch: [84][290/500] Time 0.058 (0.039) Data 0.002 (0.003) Loss 0.0683 (0.0735) Prec@1 88.000 (87.633) Prec@5 100.000 (99.000) +2022-11-14 13:43:28,985 Epoch: [84][300/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0727 (0.0735) Prec@1 89.000 (87.677) Prec@5 100.000 (99.032) +2022-11-14 13:43:29,429 Epoch: [84][310/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0712 (0.0734) Prec@1 88.000 (87.688) Prec@5 99.000 (99.031) +2022-11-14 13:43:30,021 Epoch: [84][320/500] Time 0.057 (0.040) Data 0.002 (0.003) Loss 0.0606 (0.0731) Prec@1 88.000 (87.697) Prec@5 100.000 (99.061) +2022-11-14 13:43:30,559 Epoch: [84][330/500] Time 0.053 (0.040) Data 0.003 (0.003) Loss 0.0899 (0.0735) Prec@1 85.000 (87.618) Prec@5 98.000 (99.029) +2022-11-14 13:43:31,090 Epoch: [84][340/500] Time 0.055 (0.040) Data 0.002 (0.003) Loss 0.0552 (0.0730) Prec@1 92.000 (87.743) Prec@5 100.000 (99.057) +2022-11-14 13:43:31,533 Epoch: [84][350/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0649 (0.0728) Prec@1 89.000 (87.778) Prec@5 100.000 (99.083) +2022-11-14 13:43:32,001 Epoch: [84][360/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0898 (0.0733) Prec@1 85.000 (87.703) Prec@5 99.000 (99.081) +2022-11-14 13:43:32,543 Epoch: [84][370/500] Time 0.055 (0.040) Data 0.002 (0.002) Loss 0.0921 (0.0738) Prec@1 81.000 (87.526) Prec@5 99.000 (99.079) +2022-11-14 13:43:33,064 Epoch: [84][380/500] Time 0.051 (0.041) Data 0.002 (0.002) Loss 0.0560 (0.0733) Prec@1 91.000 (87.615) Prec@5 100.000 (99.103) +2022-11-14 13:43:33,486 Epoch: [84][390/500] Time 0.040 (0.041) Data 0.002 (0.002) Loss 0.0581 (0.0729) Prec@1 92.000 (87.725) Prec@5 99.000 (99.100) +2022-11-14 13:43:34,031 Epoch: [84][400/500] Time 0.050 (0.041) Data 0.002 (0.002) Loss 0.0604 (0.0726) Prec@1 88.000 (87.732) Prec@5 99.000 (99.098) +2022-11-14 13:43:34,442 Epoch: [84][410/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0678 (0.0725) Prec@1 92.000 (87.833) Prec@5 99.000 (99.095) +2022-11-14 13:43:34,997 Epoch: [84][420/500] Time 0.055 (0.041) Data 0.002 (0.002) Loss 0.0852 (0.0728) Prec@1 85.000 (87.767) Prec@5 98.000 (99.070) +2022-11-14 13:43:35,547 Epoch: [84][430/500] Time 0.058 (0.041) Data 0.002 (0.002) Loss 0.0833 (0.0730) Prec@1 87.000 (87.750) Prec@5 99.000 (99.068) +2022-11-14 13:43:36,094 Epoch: [84][440/500] Time 0.046 (0.041) Data 0.002 (0.002) Loss 0.0888 (0.0734) Prec@1 83.000 (87.644) Prec@5 100.000 (99.089) +2022-11-14 13:43:36,532 Epoch: [84][450/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0935 (0.0738) Prec@1 82.000 (87.522) Prec@5 100.000 (99.109) +2022-11-14 13:43:37,098 Epoch: [84][460/500] Time 0.054 (0.041) Data 0.002 (0.002) Loss 0.1054 (0.0745) Prec@1 84.000 (87.447) Prec@5 100.000 (99.128) +2022-11-14 13:43:37,562 Epoch: [84][470/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0710 (0.0744) Prec@1 86.000 (87.417) Prec@5 98.000 (99.104) +2022-11-14 13:43:37,999 Epoch: [84][480/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0630 (0.0742) Prec@1 90.000 (87.469) Prec@5 99.000 (99.102) +2022-11-14 13:43:38,435 Epoch: [84][490/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0558 (0.0738) Prec@1 92.000 (87.560) Prec@5 99.000 (99.100) +2022-11-14 13:43:38,822 Epoch: [84][499/500] Time 0.040 (0.041) Data 0.002 (0.002) Loss 0.0684 (0.0737) Prec@1 89.000 (87.588) Prec@5 99.000 (99.098) +2022-11-14 13:43:39,106 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0694 (0.0694) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,118 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0915 (0.0805) Prec@1 83.000 (86.500) Prec@5 97.000 (98.000) +2022-11-14 13:43:39,128 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0829) Prec@1 82.000 (85.000) Prec@5 100.000 (98.667) +2022-11-14 13:43:39,142 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0973 (0.0865) Prec@1 84.000 (84.750) Prec@5 99.000 (98.750) +2022-11-14 13:43:39,152 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0888) Prec@1 81.000 (84.000) Prec@5 99.000 (98.800) +2022-11-14 13:43:39,161 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0822) Prec@1 92.000 (85.333) Prec@5 99.000 (98.833) +2022-11-14 13:43:39,171 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0808) Prec@1 89.000 (85.857) Prec@5 100.000 (99.000) +2022-11-14 13:43:39,181 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0834) Prec@1 78.000 (84.875) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,191 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0828) Prec@1 89.000 (85.333) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,200 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0831) Prec@1 87.000 (85.500) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,213 Test: [10/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0810) Prec@1 91.000 (86.000) Prec@5 100.000 (99.091) +2022-11-14 13:43:39,227 Test: [11/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0816) Prec@1 84.000 (85.833) Prec@5 99.000 (99.083) +2022-11-14 13:43:39,239 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0821) Prec@1 84.000 (85.692) Prec@5 100.000 (99.154) +2022-11-14 13:43:39,250 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0813) Prec@1 88.000 (85.857) Prec@5 99.000 (99.143) +2022-11-14 13:43:39,260 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0823) Prec@1 85.000 (85.800) Prec@5 99.000 (99.133) +2022-11-14 13:43:39,271 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0821) Prec@1 89.000 (86.000) Prec@5 100.000 (99.188) +2022-11-14 13:43:39,281 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0814) Prec@1 88.000 (86.118) Prec@5 99.000 (99.176) +2022-11-14 13:43:39,292 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0821) Prec@1 82.000 (85.889) Prec@5 100.000 (99.222) +2022-11-14 13:43:39,302 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0827) Prec@1 82.000 (85.684) Prec@5 98.000 (99.158) +2022-11-14 13:43:39,314 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0839) Prec@1 85.000 (85.650) Prec@5 98.000 (99.100) +2022-11-14 13:43:39,324 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0848) Prec@1 83.000 (85.524) Prec@5 98.000 (99.048) +2022-11-14 13:43:39,334 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0845) Prec@1 86.000 (85.545) Prec@5 98.000 (99.000) +2022-11-14 13:43:39,344 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.0856) Prec@1 80.000 (85.304) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,356 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0853) Prec@1 87.000 (85.375) Prec@5 100.000 (99.042) +2022-11-14 13:43:39,367 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0862) Prec@1 81.000 (85.200) Prec@5 99.000 (99.040) +2022-11-14 13:43:39,378 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.0873) Prec@1 80.000 (85.000) Prec@5 97.000 (98.962) +2022-11-14 13:43:39,389 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0861) Prec@1 92.000 (85.259) Prec@5 100.000 (99.000) +2022-11-14 13:43:39,399 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0865) Prec@1 84.000 (85.214) Prec@5 100.000 (99.036) +2022-11-14 13:43:39,410 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0864) Prec@1 87.000 (85.276) Prec@5 98.000 (99.000) +2022-11-14 13:43:39,423 Test: [29/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0863) Prec@1 86.000 (85.300) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,435 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0864) Prec@1 84.000 (85.258) Prec@5 99.000 (99.000) +2022-11-14 13:43:39,446 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0864) Prec@1 86.000 (85.281) Prec@5 100.000 (99.031) +2022-11-14 13:43:39,457 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0866) Prec@1 85.000 (85.273) Prec@5 99.000 (99.030) +2022-11-14 13:43:39,468 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1151 (0.0875) Prec@1 77.000 (85.029) Prec@5 99.000 (99.029) +2022-11-14 13:43:39,479 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0878) Prec@1 81.000 (84.914) Prec@5 99.000 (99.029) +2022-11-14 13:43:39,489 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0880) Prec@1 83.000 (84.861) Prec@5 98.000 (99.000) +2022-11-14 13:43:39,500 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0884) Prec@1 82.000 (84.784) Prec@5 97.000 (98.946) +2022-11-14 13:43:39,511 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1219 (0.0893) Prec@1 77.000 (84.579) Prec@5 99.000 (98.947) +2022-11-14 13:43:39,522 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0887) Prec@1 88.000 (84.667) Prec@5 99.000 (98.949) +2022-11-14 13:43:39,532 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0883) Prec@1 86.000 (84.700) Prec@5 100.000 (98.975) +2022-11-14 13:43:39,543 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0889) Prec@1 82.000 (84.634) Prec@5 98.000 (98.951) +2022-11-14 13:43:39,553 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0886) Prec@1 88.000 (84.714) Prec@5 98.000 (98.929) +2022-11-14 13:43:39,563 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0881) Prec@1 88.000 (84.791) Prec@5 100.000 (98.953) +2022-11-14 13:43:39,575 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0879) Prec@1 88.000 (84.864) Prec@5 98.000 (98.932) +2022-11-14 13:43:39,586 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0882) Prec@1 84.000 (84.844) Prec@5 97.000 (98.889) +2022-11-14 13:43:39,599 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0885) Prec@1 80.000 (84.739) Prec@5 99.000 (98.891) +2022-11-14 13:43:39,612 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0883) Prec@1 86.000 (84.766) Prec@5 100.000 (98.915) +2022-11-14 13:43:39,625 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0884) Prec@1 86.000 (84.792) Prec@5 98.000 (98.896) +2022-11-14 13:43:39,636 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0881) Prec@1 87.000 (84.837) Prec@5 99.000 (98.898) +2022-11-14 13:43:39,647 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1262 (0.0888) Prec@1 77.000 (84.680) Prec@5 99.000 (98.900) +2022-11-14 13:43:39,657 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0887) Prec@1 84.000 (84.667) Prec@5 99.000 (98.902) +2022-11-14 13:43:39,668 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0890) Prec@1 80.000 (84.577) Prec@5 98.000 (98.885) +2022-11-14 13:43:39,680 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0889) Prec@1 83.000 (84.547) Prec@5 99.000 (98.887) +2022-11-14 13:43:39,691 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0888) Prec@1 86.000 (84.574) Prec@5 98.000 (98.870) +2022-11-14 13:43:39,702 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1173 (0.0893) Prec@1 81.000 (84.509) Prec@5 99.000 (98.873) +2022-11-14 13:43:39,713 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0890) Prec@1 87.000 (84.554) Prec@5 99.000 (98.875) +2022-11-14 13:43:39,723 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0890) Prec@1 84.000 (84.544) Prec@5 99.000 (98.877) +2022-11-14 13:43:39,735 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0886) Prec@1 91.000 (84.655) Prec@5 99.000 (98.879) +2022-11-14 13:43:39,747 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1139 (0.0890) Prec@1 81.000 (84.593) Prec@5 100.000 (98.898) +2022-11-14 13:43:39,758 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0892) Prec@1 83.000 (84.567) Prec@5 98.000 (98.883) +2022-11-14 13:43:39,768 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0893) Prec@1 82.000 (84.525) Prec@5 99.000 (98.885) +2022-11-14 13:43:39,778 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0893) Prec@1 81.000 (84.468) Prec@5 100.000 (98.903) +2022-11-14 13:43:39,789 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0893) Prec@1 84.000 (84.460) Prec@5 99.000 (98.905) +2022-11-14 13:43:39,799 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0887) Prec@1 91.000 (84.562) Prec@5 99.000 (98.906) +2022-11-14 13:43:39,810 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0889) Prec@1 79.000 (84.477) Prec@5 100.000 (98.923) +2022-11-14 13:43:39,821 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0891) Prec@1 82.000 (84.439) Prec@5 99.000 (98.924) +2022-11-14 13:43:39,832 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0886) Prec@1 91.000 (84.537) Prec@5 100.000 (98.940) +2022-11-14 13:43:39,843 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0886) Prec@1 85.000 (84.544) Prec@5 99.000 (98.941) +2022-11-14 13:43:39,854 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0884) Prec@1 89.000 (84.609) Prec@5 98.000 (98.928) +2022-11-14 13:43:39,865 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0886) Prec@1 81.000 (84.557) Prec@5 97.000 (98.900) +2022-11-14 13:43:39,877 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0887) Prec@1 84.000 (84.549) Prec@5 100.000 (98.915) +2022-11-14 13:43:39,888 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0887) Prec@1 83.000 (84.528) Prec@5 100.000 (98.931) +2022-11-14 13:43:39,899 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0885) Prec@1 89.000 (84.589) Prec@5 100.000 (98.945) +2022-11-14 13:43:39,909 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0884) Prec@1 87.000 (84.622) Prec@5 100.000 (98.959) +2022-11-14 13:43:39,920 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0886) Prec@1 84.000 (84.613) Prec@5 98.000 (98.947) +2022-11-14 13:43:39,931 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0885) Prec@1 87.000 (84.645) Prec@5 98.000 (98.934) +2022-11-14 13:43:39,942 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0884) Prec@1 84.000 (84.636) Prec@5 99.000 (98.935) +2022-11-14 13:43:39,955 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0883) Prec@1 84.000 (84.628) Prec@5 97.000 (98.910) +2022-11-14 13:43:39,967 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0883) Prec@1 85.000 (84.633) Prec@5 100.000 (98.924) +2022-11-14 13:43:39,976 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0884) Prec@1 83.000 (84.612) Prec@5 98.000 (98.912) +2022-11-14 13:43:39,986 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0884) Prec@1 84.000 (84.605) Prec@5 98.000 (98.901) +2022-11-14 13:43:39,998 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0884) Prec@1 87.000 (84.634) Prec@5 98.000 (98.890) +2022-11-14 13:43:40,008 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0883) Prec@1 84.000 (84.627) Prec@5 100.000 (98.904) +2022-11-14 13:43:40,018 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0885) Prec@1 80.000 (84.571) Prec@5 99.000 (98.905) +2022-11-14 13:43:40,029 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.0888) Prec@1 83.000 (84.553) Prec@5 99.000 (98.906) +2022-11-14 13:43:40,040 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1243 (0.0892) Prec@1 79.000 (84.488) Prec@5 98.000 (98.895) +2022-11-14 13:43:40,051 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0891) Prec@1 88.000 (84.529) Prec@5 99.000 (98.897) +2022-11-14 13:43:40,061 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0891) Prec@1 85.000 (84.534) Prec@5 99.000 (98.898) +2022-11-14 13:43:40,072 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0890) Prec@1 87.000 (84.562) Prec@5 98.000 (98.888) +2022-11-14 13:43:40,083 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0891) Prec@1 85.000 (84.567) Prec@5 100.000 (98.900) +2022-11-14 13:43:40,093 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0888) Prec@1 91.000 (84.637) Prec@5 100.000 (98.912) +2022-11-14 13:43:40,104 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0885) Prec@1 89.000 (84.685) Prec@5 98.000 (98.902) +2022-11-14 13:43:40,115 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0887) Prec@1 83.000 (84.667) Prec@5 99.000 (98.903) +2022-11-14 13:43:40,126 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0886) Prec@1 87.000 (84.691) Prec@5 100.000 (98.915) +2022-11-14 13:43:40,137 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0886) Prec@1 86.000 (84.705) Prec@5 99.000 (98.916) +2022-11-14 13:43:40,147 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0884) Prec@1 88.000 (84.740) Prec@5 99.000 (98.917) +2022-11-14 13:43:40,159 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0885) Prec@1 86.000 (84.753) Prec@5 97.000 (98.897) +2022-11-14 13:43:40,170 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1251 (0.0888) Prec@1 79.000 (84.694) Prec@5 98.000 (98.888) +2022-11-14 13:43:40,182 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0889) Prec@1 84.000 (84.687) Prec@5 100.000 (98.899) +2022-11-14 13:43:40,193 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0889) Prec@1 87.000 (84.710) Prec@5 100.000 (98.910) +2022-11-14 13:43:40,251 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:43:40,640 Epoch: [85][0/500] Time 0.033 (0.033) Data 0.280 (0.280) Loss 0.0835 (0.0835) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:40,898 Epoch: [85][10/500] Time 0.018 (0.024) Data 0.002 (0.027) Loss 0.0691 (0.0763) Prec@1 88.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 13:43:41,128 Epoch: [85][20/500] Time 0.026 (0.022) Data 0.002 (0.015) Loss 0.0790 (0.0772) Prec@1 87.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 13:43:41,537 Epoch: [85][30/500] Time 0.042 (0.027) Data 0.002 (0.011) Loss 0.0522 (0.0710) Prec@1 93.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 13:43:41,934 Epoch: [85][40/500] Time 0.029 (0.029) Data 0.002 (0.009) Loss 0.0656 (0.0699) Prec@1 89.000 (88.800) Prec@5 100.000 (99.600) +2022-11-14 13:43:42,292 Epoch: [85][50/500] Time 0.034 (0.029) Data 0.002 (0.007) Loss 0.0652 (0.0691) Prec@1 89.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 13:43:42,669 Epoch: [85][60/500] Time 0.037 (0.030) Data 0.002 (0.006) Loss 0.0578 (0.0675) Prec@1 91.000 (89.143) Prec@5 99.000 (99.571) +2022-11-14 13:43:43,064 Epoch: [85][70/500] Time 0.035 (0.031) Data 0.002 (0.006) Loss 0.0717 (0.0680) Prec@1 89.000 (89.125) Prec@5 99.000 (99.500) +2022-11-14 13:43:43,428 Epoch: [85][80/500] Time 0.034 (0.031) Data 0.002 (0.005) Loss 0.0895 (0.0704) Prec@1 82.000 (88.333) Prec@5 99.000 (99.444) +2022-11-14 13:43:43,803 Epoch: [85][90/500] Time 0.032 (0.031) Data 0.001 (0.005) Loss 0.0777 (0.0711) Prec@1 85.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 13:43:44,274 Epoch: [85][100/500] Time 0.046 (0.032) Data 0.002 (0.005) Loss 0.0614 (0.0702) Prec@1 89.000 (88.091) Prec@5 99.000 (99.455) +2022-11-14 13:43:44,733 Epoch: [85][110/500] Time 0.042 (0.033) Data 0.002 (0.004) Loss 0.0751 (0.0707) Prec@1 89.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 13:43:45,162 Epoch: [85][120/500] Time 0.040 (0.034) Data 0.002 (0.004) Loss 0.0664 (0.0703) Prec@1 88.000 (88.154) Prec@5 98.000 (99.385) +2022-11-14 13:43:45,517 Epoch: [85][130/500] Time 0.036 (0.033) Data 0.001 (0.004) Loss 0.0824 (0.0712) Prec@1 86.000 (88.000) Prec@5 100.000 (99.429) +2022-11-14 13:43:45,922 Epoch: [85][140/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0923 (0.0726) Prec@1 82.000 (87.600) Prec@5 98.000 (99.333) +2022-11-14 13:43:46,311 Epoch: [85][150/500] Time 0.032 (0.034) Data 0.002 (0.004) Loss 0.0539 (0.0714) Prec@1 92.000 (87.875) Prec@5 100.000 (99.375) +2022-11-14 13:43:46,670 Epoch: [85][160/500] Time 0.036 (0.034) Data 0.002 (0.004) Loss 0.0888 (0.0724) Prec@1 86.000 (87.765) Prec@5 100.000 (99.412) +2022-11-14 13:43:47,101 Epoch: [85][170/500] Time 0.035 (0.034) Data 0.002 (0.004) Loss 0.0851 (0.0732) Prec@1 86.000 (87.667) Prec@5 100.000 (99.444) +2022-11-14 13:43:47,487 Epoch: [85][180/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.0682 (0.0729) Prec@1 89.000 (87.737) Prec@5 100.000 (99.474) +2022-11-14 13:43:47,852 Epoch: [85][190/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0642 (0.0725) Prec@1 88.000 (87.750) Prec@5 99.000 (99.450) +2022-11-14 13:43:48,217 Epoch: [85][200/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0612 (0.0719) Prec@1 90.000 (87.857) Prec@5 99.000 (99.429) +2022-11-14 13:43:48,579 Epoch: [85][210/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0833 (0.0724) Prec@1 84.000 (87.682) Prec@5 100.000 (99.455) +2022-11-14 13:43:48,948 Epoch: [85][220/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0656 (0.0721) Prec@1 88.000 (87.696) Prec@5 99.000 (99.435) +2022-11-14 13:43:49,321 Epoch: [85][230/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0522 (0.0713) Prec@1 93.000 (87.917) Prec@5 99.000 (99.417) +2022-11-14 13:43:49,688 Epoch: [85][240/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0859 (0.0719) Prec@1 86.000 (87.840) Prec@5 100.000 (99.440) +2022-11-14 13:43:50,064 Epoch: [85][250/500] Time 0.030 (0.034) Data 0.002 (0.003) Loss 0.0603 (0.0714) Prec@1 90.000 (87.923) Prec@5 98.000 (99.385) +2022-11-14 13:43:50,427 Epoch: [85][260/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0768 (0.0716) Prec@1 87.000 (87.889) Prec@5 99.000 (99.370) +2022-11-14 13:43:50,797 Epoch: [85][270/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0710 (0.0716) Prec@1 86.000 (87.821) Prec@5 100.000 (99.393) +2022-11-14 13:43:51,246 Epoch: [85][280/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0780 (0.0718) Prec@1 85.000 (87.724) Prec@5 98.000 (99.345) +2022-11-14 13:43:51,662 Epoch: [85][290/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0671 (0.0717) Prec@1 89.000 (87.767) Prec@5 98.000 (99.300) +2022-11-14 13:43:52,085 Epoch: [85][300/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0592 (0.0713) Prec@1 91.000 (87.871) Prec@5 100.000 (99.323) +2022-11-14 13:43:52,433 Epoch: [85][310/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0571 (0.0708) Prec@1 88.000 (87.875) Prec@5 100.000 (99.344) +2022-11-14 13:43:52,804 Epoch: [85][320/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0729 (0.0709) Prec@1 90.000 (87.939) Prec@5 99.000 (99.333) +2022-11-14 13:43:53,177 Epoch: [85][330/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0505 (0.0703) Prec@1 93.000 (88.088) Prec@5 100.000 (99.353) +2022-11-14 13:43:53,537 Epoch: [85][340/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0701 (0.0703) Prec@1 88.000 (88.086) Prec@5 100.000 (99.371) +2022-11-14 13:43:53,924 Epoch: [85][350/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0769 (0.0705) Prec@1 85.000 (88.000) Prec@5 100.000 (99.389) +2022-11-14 13:43:54,276 Epoch: [85][360/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0557 (0.0701) Prec@1 92.000 (88.108) Prec@5 99.000 (99.378) +2022-11-14 13:43:54,641 Epoch: [85][370/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0726 (0.0701) Prec@1 87.000 (88.079) Prec@5 98.000 (99.342) +2022-11-14 13:43:55,011 Epoch: [85][380/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0825 (0.0705) Prec@1 87.000 (88.051) Prec@5 100.000 (99.359) +2022-11-14 13:43:55,390 Epoch: [85][390/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0846 (0.0708) Prec@1 86.000 (88.000) Prec@5 98.000 (99.325) +2022-11-14 13:43:55,760 Epoch: [85][400/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0578 (0.0705) Prec@1 91.000 (88.073) Prec@5 99.000 (99.317) +2022-11-14 13:43:56,127 Epoch: [85][410/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0577 (0.0702) Prec@1 90.000 (88.119) Prec@5 100.000 (99.333) +2022-11-14 13:43:56,502 Epoch: [85][420/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0720 (0.0702) Prec@1 87.000 (88.093) Prec@5 98.000 (99.302) +2022-11-14 13:43:56,867 Epoch: [85][430/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0634 (0.0701) Prec@1 90.000 (88.136) Prec@5 100.000 (99.318) +2022-11-14 13:43:57,238 Epoch: [85][440/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0795 (0.0703) Prec@1 84.000 (88.044) Prec@5 100.000 (99.333) +2022-11-14 13:43:57,626 Epoch: [85][450/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0583 (0.0700) Prec@1 90.000 (88.087) Prec@5 100.000 (99.348) +2022-11-14 13:43:57,993 Epoch: [85][460/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0577 (0.0698) Prec@1 91.000 (88.149) Prec@5 100.000 (99.362) +2022-11-14 13:43:58,366 Epoch: [85][470/500] Time 0.034 (0.034) Data 0.003 (0.003) Loss 0.0775 (0.0699) Prec@1 87.000 (88.125) Prec@5 100.000 (99.375) +2022-11-14 13:43:58,733 Epoch: [85][480/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0936 (0.0704) Prec@1 82.000 (88.000) Prec@5 99.000 (99.367) +2022-11-14 13:43:59,096 Epoch: [85][490/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0663 (0.0703) Prec@1 91.000 (88.060) Prec@5 98.000 (99.340) +2022-11-14 13:43:59,431 Epoch: [85][499/500] Time 0.032 (0.034) Data 0.001 (0.003) Loss 0.0449 (0.0698) Prec@1 93.000 (88.157) Prec@5 99.000 (99.333) +2022-11-14 13:43:59,713 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0791 (0.0791) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:43:59,734 Test: [1/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0659 (0.0725) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 13:43:59,745 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0752 (0.0734) Prec@1 88.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 13:43:59,760 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1137 (0.0835) Prec@1 79.000 (86.250) Prec@5 99.000 (99.250) +2022-11-14 13:43:59,770 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1195 (0.0907) Prec@1 78.000 (84.600) Prec@5 99.000 (99.200) +2022-11-14 13:43:59,780 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0658 (0.0865) Prec@1 87.000 (85.000) Prec@5 100.000 (99.333) +2022-11-14 13:43:59,789 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0850) Prec@1 88.000 (85.429) Prec@5 100.000 (99.429) +2022-11-14 13:43:59,803 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1136 (0.0886) Prec@1 82.000 (85.000) Prec@5 97.000 (99.125) +2022-11-14 13:43:59,814 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1378 (0.0941) Prec@1 76.000 (84.000) Prec@5 98.000 (99.000) +2022-11-14 13:43:59,823 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0918) Prec@1 87.000 (84.300) Prec@5 98.000 (98.900) +2022-11-14 13:43:59,835 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0905) Prec@1 90.000 (84.818) Prec@5 98.000 (98.818) +2022-11-14 13:43:59,850 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0954 (0.0909) Prec@1 86.000 (84.917) Prec@5 99.000 (98.833) +2022-11-14 13:43:59,862 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0906) Prec@1 84.000 (84.846) Prec@5 100.000 (98.923) +2022-11-14 13:43:59,875 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0888) Prec@1 89.000 (85.143) Prec@5 98.000 (98.857) +2022-11-14 13:43:59,889 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.0898) Prec@1 86.000 (85.200) Prec@5 97.000 (98.733) +2022-11-14 13:43:59,901 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1049 (0.0907) Prec@1 83.000 (85.062) Prec@5 99.000 (98.750) +2022-11-14 13:43:59,916 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0900) Prec@1 87.000 (85.176) Prec@5 98.000 (98.706) +2022-11-14 13:43:59,930 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1242 (0.0919) Prec@1 77.000 (84.722) Prec@5 99.000 (98.722) +2022-11-14 13:43:59,943 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1052 (0.0926) Prec@1 80.000 (84.474) Prec@5 99.000 (98.737) +2022-11-14 13:43:59,957 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1239 (0.0941) Prec@1 80.000 (84.250) Prec@5 96.000 (98.600) +2022-11-14 13:43:59,972 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1170 (0.0952) Prec@1 80.000 (84.048) Prec@5 99.000 (98.619) +2022-11-14 13:43:59,987 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1013 (0.0955) Prec@1 81.000 (83.909) Prec@5 98.000 (98.591) +2022-11-14 13:44:00,000 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0970 (0.0956) Prec@1 83.000 (83.870) Prec@5 99.000 (98.609) +2022-11-14 13:44:00,014 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0945) Prec@1 87.000 (84.000) Prec@5 100.000 (98.667) +2022-11-14 13:44:00,027 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1128 (0.0952) Prec@1 81.000 (83.880) Prec@5 100.000 (98.720) +2022-11-14 13:44:00,040 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1083 (0.0957) Prec@1 84.000 (83.885) Prec@5 96.000 (98.615) +2022-11-14 13:44:00,053 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0950) Prec@1 86.000 (83.963) Prec@5 100.000 (98.667) +2022-11-14 13:44:00,070 Test: [27/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0950) Prec@1 84.000 (83.964) Prec@5 98.000 (98.643) +2022-11-14 13:44:00,084 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0944) Prec@1 89.000 (84.138) Prec@5 98.000 (98.621) +2022-11-14 13:44:00,097 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0971 (0.0945) Prec@1 85.000 (84.167) Prec@5 94.000 (98.467) +2022-11-14 13:44:00,110 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0948) Prec@1 84.000 (84.161) Prec@5 99.000 (98.484) +2022-11-14 13:44:00,124 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0839 (0.0945) Prec@1 86.000 (84.219) Prec@5 99.000 (98.500) +2022-11-14 13:44:00,138 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0982 (0.0946) Prec@1 86.000 (84.273) Prec@5 97.000 (98.455) +2022-11-14 13:44:00,152 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1150 (0.0952) Prec@1 80.000 (84.147) Prec@5 97.000 (98.412) +2022-11-14 13:44:00,166 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0951) Prec@1 83.000 (84.114) Prec@5 99.000 (98.429) +2022-11-14 13:44:00,178 Test: [35/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0947) Prec@1 87.000 (84.194) Prec@5 99.000 (98.444) +2022-11-14 13:44:00,195 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1097 (0.0951) Prec@1 80.000 (84.081) Prec@5 97.000 (98.405) +2022-11-14 13:44:00,208 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.0954) Prec@1 80.000 (83.974) Prec@5 99.000 (98.421) +2022-11-14 13:44:00,222 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0943) Prec@1 92.000 (84.179) Prec@5 99.000 (98.436) +2022-11-14 13:44:00,236 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0937) Prec@1 90.000 (84.325) Prec@5 99.000 (98.450) +2022-11-14 13:44:00,250 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0939) Prec@1 84.000 (84.317) Prec@5 98.000 (98.439) +2022-11-14 13:44:00,263 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0937) Prec@1 85.000 (84.333) Prec@5 98.000 (98.429) +2022-11-14 13:44:00,275 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0931) Prec@1 87.000 (84.395) Prec@5 100.000 (98.465) +2022-11-14 13:44:00,291 Test: [43/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0927) Prec@1 86.000 (84.432) Prec@5 97.000 (98.432) +2022-11-14 13:44:00,307 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0926) Prec@1 87.000 (84.489) Prec@5 98.000 (98.422) +2022-11-14 13:44:00,321 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1197 (0.0932) Prec@1 77.000 (84.326) Prec@5 99.000 (98.435) +2022-11-14 13:44:00,337 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0927) Prec@1 90.000 (84.447) Prec@5 99.000 (98.447) +2022-11-14 13:44:00,353 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0929) Prec@1 81.000 (84.375) Prec@5 100.000 (98.479) +2022-11-14 13:44:00,366 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0927) Prec@1 86.000 (84.408) Prec@5 99.000 (98.490) +2022-11-14 13:44:00,378 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1332 (0.0935) Prec@1 76.000 (84.240) Prec@5 98.000 (98.480) +2022-11-14 13:44:00,393 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0932) Prec@1 89.000 (84.333) Prec@5 98.000 (98.471) +2022-11-14 13:44:00,407 Test: [51/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0932) Prec@1 81.000 (84.269) Prec@5 100.000 (98.500) +2022-11-14 13:44:00,422 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0934) Prec@1 81.000 (84.208) Prec@5 98.000 (98.491) +2022-11-14 13:44:00,436 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0932) Prec@1 87.000 (84.259) Prec@5 99.000 (98.500) +2022-11-14 13:44:00,451 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0934) Prec@1 81.000 (84.200) Prec@5 100.000 (98.527) +2022-11-14 13:44:00,466 Test: [55/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0933) Prec@1 85.000 (84.214) Prec@5 99.000 (98.536) +2022-11-14 13:44:00,480 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0935) Prec@1 80.000 (84.140) Prec@5 100.000 (98.561) +2022-11-14 13:44:00,494 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0935) Prec@1 85.000 (84.155) Prec@5 99.000 (98.569) +2022-11-14 13:44:00,507 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1261 (0.0941) Prec@1 77.000 (84.034) Prec@5 100.000 (98.593) +2022-11-14 13:44:00,522 Test: [59/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0941) Prec@1 85.000 (84.050) Prec@5 98.000 (98.583) +2022-11-14 13:44:00,537 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0941) Prec@1 83.000 (84.033) Prec@5 99.000 (98.590) +2022-11-14 13:44:00,553 Test: [61/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0941) Prec@1 84.000 (84.032) Prec@5 99.000 (98.597) +2022-11-14 13:44:00,567 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0936) Prec@1 89.000 (84.111) Prec@5 100.000 (98.619) +2022-11-14 13:44:00,581 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0933) Prec@1 87.000 (84.156) Prec@5 100.000 (98.641) +2022-11-14 13:44:00,594 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0934) Prec@1 85.000 (84.169) Prec@5 99.000 (98.646) +2022-11-14 13:44:00,608 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0935) Prec@1 84.000 (84.167) Prec@5 100.000 (98.667) +2022-11-14 13:44:00,622 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0931) Prec@1 88.000 (84.224) Prec@5 100.000 (98.687) +2022-11-14 13:44:00,635 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1103 (0.0934) Prec@1 82.000 (84.191) Prec@5 99.000 (98.691) +2022-11-14 13:44:00,650 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0931) Prec@1 90.000 (84.275) Prec@5 97.000 (98.667) +2022-11-14 13:44:00,664 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.0934) Prec@1 81.000 (84.229) Prec@5 98.000 (98.657) +2022-11-14 13:44:00,678 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0935) Prec@1 81.000 (84.183) Prec@5 100.000 (98.676) +2022-11-14 13:44:00,693 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0935) Prec@1 87.000 (84.222) Prec@5 100.000 (98.694) +2022-11-14 13:44:00,707 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0933) Prec@1 86.000 (84.247) Prec@5 100.000 (98.712) +2022-11-14 13:44:00,720 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0931) Prec@1 86.000 (84.270) Prec@5 100.000 (98.730) +2022-11-14 13:44:00,736 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0933) Prec@1 85.000 (84.280) Prec@5 98.000 (98.720) +2022-11-14 13:44:00,749 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0931) Prec@1 83.000 (84.263) Prec@5 100.000 (98.737) +2022-11-14 13:44:00,762 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0929) Prec@1 87.000 (84.299) Prec@5 100.000 (98.753) +2022-11-14 13:44:00,778 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0930) Prec@1 85.000 (84.308) Prec@5 96.000 (98.718) +2022-11-14 13:44:00,791 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0929) Prec@1 85.000 (84.316) Prec@5 100.000 (98.734) +2022-11-14 13:44:00,804 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0929) Prec@1 85.000 (84.325) Prec@5 99.000 (98.737) +2022-11-14 13:44:00,819 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0929) Prec@1 84.000 (84.321) Prec@5 99.000 (98.741) +2022-11-14 13:44:00,834 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0930) Prec@1 83.000 (84.305) Prec@5 100.000 (98.756) +2022-11-14 13:44:00,847 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0931) Prec@1 81.000 (84.265) Prec@5 100.000 (98.771) +2022-11-14 13:44:00,861 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0930) Prec@1 86.000 (84.286) Prec@5 99.000 (98.774) +2022-11-14 13:44:00,875 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0931) Prec@1 83.000 (84.271) Prec@5 98.000 (98.765) +2022-11-14 13:44:00,888 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1095 (0.0933) Prec@1 81.000 (84.233) Prec@5 100.000 (98.779) +2022-11-14 13:44:00,902 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0931) Prec@1 89.000 (84.287) Prec@5 99.000 (98.782) +2022-11-14 13:44:00,915 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0931) Prec@1 85.000 (84.295) Prec@5 98.000 (98.773) +2022-11-14 13:44:00,931 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0930) Prec@1 83.000 (84.281) Prec@5 99.000 (98.775) +2022-11-14 13:44:00,946 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0930) Prec@1 86.000 (84.300) Prec@5 99.000 (98.778) +2022-11-14 13:44:00,959 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0926) Prec@1 86.000 (84.319) Prec@5 100.000 (98.791) +2022-11-14 13:44:00,972 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0923) Prec@1 90.000 (84.380) Prec@5 99.000 (98.793) +2022-11-14 13:44:00,986 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1202 (0.0926) Prec@1 78.000 (84.312) Prec@5 100.000 (98.806) +2022-11-14 13:44:00,999 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0927) Prec@1 79.000 (84.255) Prec@5 98.000 (98.798) +2022-11-14 13:44:01,013 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0926) Prec@1 87.000 (84.284) Prec@5 99.000 (98.800) +2022-11-14 13:44:01,025 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0924) Prec@1 87.000 (84.312) Prec@5 99.000 (98.802) +2022-11-14 13:44:01,040 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0921) Prec@1 94.000 (84.412) Prec@5 99.000 (98.804) +2022-11-14 13:44:01,056 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1149 (0.0923) Prec@1 81.000 (84.378) Prec@5 100.000 (98.816) +2022-11-14 13:44:01,070 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1350 (0.0927) Prec@1 78.000 (84.313) Prec@5 98.000 (98.808) +2022-11-14 13:44:01,083 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0927) Prec@1 82.000 (84.290) Prec@5 99.000 (98.810) +2022-11-14 13:44:01,141 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:44:01,445 Epoch: [86][0/500] Time 0.024 (0.024) Data 0.223 (0.223) Loss 0.0719 (0.0719) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 13:44:01,671 Epoch: [86][10/500] Time 0.021 (0.020) Data 0.002 (0.022) Loss 0.0959 (0.0839) Prec@1 83.000 (86.500) Prec@5 97.000 (98.000) +2022-11-14 13:44:01,941 Epoch: [86][20/500] Time 0.031 (0.022) Data 0.002 (0.012) Loss 0.0730 (0.0803) Prec@1 86.000 (86.333) Prec@5 100.000 (98.667) +2022-11-14 13:44:02,332 Epoch: [86][30/500] Time 0.036 (0.026) Data 0.002 (0.009) Loss 0.0927 (0.0834) Prec@1 82.000 (85.250) Prec@5 99.000 (98.750) +2022-11-14 13:44:02,730 Epoch: [86][40/500] Time 0.036 (0.028) Data 0.002 (0.007) Loss 0.1085 (0.0884) Prec@1 78.000 (83.800) Prec@5 99.000 (98.800) +2022-11-14 13:44:03,122 Epoch: [86][50/500] Time 0.036 (0.029) Data 0.002 (0.006) Loss 0.0576 (0.0833) Prec@1 91.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:44:03,513 Epoch: [86][60/500] Time 0.037 (0.030) Data 0.002 (0.006) Loss 0.0629 (0.0804) Prec@1 92.000 (86.000) Prec@5 100.000 (99.143) +2022-11-14 13:44:03,912 Epoch: [86][70/500] Time 0.037 (0.031) Data 0.002 (0.005) Loss 0.0748 (0.0797) Prec@1 86.000 (86.000) Prec@5 100.000 (99.250) +2022-11-14 13:44:04,307 Epoch: [86][80/500] Time 0.037 (0.032) Data 0.002 (0.005) Loss 0.0854 (0.0803) Prec@1 87.000 (86.111) Prec@5 98.000 (99.111) +2022-11-14 13:44:04,702 Epoch: [86][90/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0816 (0.0804) Prec@1 84.000 (85.900) Prec@5 99.000 (99.100) +2022-11-14 13:44:05,100 Epoch: [86][100/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0688 (0.0794) Prec@1 87.000 (86.000) Prec@5 100.000 (99.182) +2022-11-14 13:44:05,499 Epoch: [86][110/500] Time 0.036 (0.032) Data 0.002 (0.004) Loss 0.0872 (0.0800) Prec@1 85.000 (85.917) Prec@5 99.000 (99.167) +2022-11-14 13:44:05,886 Epoch: [86][120/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0665 (0.0790) Prec@1 88.000 (86.077) Prec@5 98.000 (99.077) +2022-11-14 13:44:06,364 Epoch: [86][130/500] Time 0.026 (0.033) Data 0.002 (0.004) Loss 0.1307 (0.0827) Prec@1 80.000 (85.643) Prec@5 98.000 (99.000) +2022-11-14 13:44:06,803 Epoch: [86][140/500] Time 0.048 (0.034) Data 0.002 (0.004) Loss 0.1011 (0.0839) Prec@1 83.000 (85.467) Prec@5 100.000 (99.067) +2022-11-14 13:44:07,259 Epoch: [86][150/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0605 (0.0825) Prec@1 91.000 (85.812) Prec@5 99.000 (99.062) +2022-11-14 13:44:07,677 Epoch: [86][160/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0828 (0.0825) Prec@1 88.000 (85.941) Prec@5 99.000 (99.059) +2022-11-14 13:44:08,060 Epoch: [86][170/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0699 (0.0818) Prec@1 89.000 (86.111) Prec@5 99.000 (99.056) +2022-11-14 13:44:08,448 Epoch: [86][180/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0682 (0.0811) Prec@1 89.000 (86.263) Prec@5 98.000 (99.000) +2022-11-14 13:44:08,842 Epoch: [86][190/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0781 (0.0809) Prec@1 87.000 (86.300) Prec@5 100.000 (99.050) +2022-11-14 13:44:09,235 Epoch: [86][200/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0668 (0.0802) Prec@1 88.000 (86.381) Prec@5 100.000 (99.095) +2022-11-14 13:44:09,623 Epoch: [86][210/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0994 (0.0811) Prec@1 85.000 (86.318) Prec@5 98.000 (99.045) +2022-11-14 13:44:10,018 Epoch: [86][220/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0725 (0.0807) Prec@1 88.000 (86.391) Prec@5 99.000 (99.043) +2022-11-14 13:44:10,404 Epoch: [86][230/500] Time 0.035 (0.035) Data 0.001 (0.003) Loss 0.0574 (0.0798) Prec@1 90.000 (86.542) Prec@5 100.000 (99.083) +2022-11-14 13:44:10,798 Epoch: [86][240/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0722 (0.0795) Prec@1 87.000 (86.560) Prec@5 99.000 (99.080) +2022-11-14 13:44:11,192 Epoch: [86][250/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0728 (0.0792) Prec@1 88.000 (86.615) Prec@5 100.000 (99.115) +2022-11-14 13:44:11,585 Epoch: [86][260/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.1028 (0.0801) Prec@1 84.000 (86.519) Prec@5 99.000 (99.111) +2022-11-14 13:44:11,978 Epoch: [86][270/500] Time 0.035 (0.035) Data 0.003 (0.003) Loss 0.0792 (0.0801) Prec@1 85.000 (86.464) Prec@5 98.000 (99.071) +2022-11-14 13:44:12,373 Epoch: [86][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0729 (0.0798) Prec@1 87.000 (86.483) Prec@5 99.000 (99.069) +2022-11-14 13:44:12,762 Epoch: [86][290/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0864 (0.0800) Prec@1 86.000 (86.467) Prec@5 99.000 (99.067) +2022-11-14 13:44:13,151 Epoch: [86][300/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0732 (0.0798) Prec@1 88.000 (86.516) Prec@5 99.000 (99.065) +2022-11-14 13:44:13,539 Epoch: [86][310/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0588 (0.0791) Prec@1 89.000 (86.594) Prec@5 99.000 (99.062) +2022-11-14 13:44:13,930 Epoch: [86][320/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0674 (0.0788) Prec@1 89.000 (86.667) Prec@5 98.000 (99.030) +2022-11-14 13:44:14,331 Epoch: [86][330/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0686 (0.0785) Prec@1 88.000 (86.706) Prec@5 99.000 (99.029) +2022-11-14 13:44:14,721 Epoch: [86][340/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0836 (0.0786) Prec@1 86.000 (86.686) Prec@5 100.000 (99.057) +2022-11-14 13:44:15,111 Epoch: [86][350/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0695 (0.0784) Prec@1 88.000 (86.722) Prec@5 99.000 (99.056) +2022-11-14 13:44:15,507 Epoch: [86][360/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0752 (0.0783) Prec@1 84.000 (86.649) Prec@5 100.000 (99.081) +2022-11-14 13:44:15,904 Epoch: [86][370/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0722 (0.0781) Prec@1 88.000 (86.684) Prec@5 100.000 (99.105) +2022-11-14 13:44:16,293 Epoch: [86][380/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0662 (0.0778) Prec@1 90.000 (86.769) Prec@5 100.000 (99.128) +2022-11-14 13:44:16,680 Epoch: [86][390/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0523 (0.0772) Prec@1 93.000 (86.925) Prec@5 100.000 (99.150) +2022-11-14 13:44:17,071 Epoch: [86][400/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0846 (0.0774) Prec@1 84.000 (86.854) Prec@5 99.000 (99.146) +2022-11-14 13:44:17,464 Epoch: [86][410/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0805 (0.0774) Prec@1 86.000 (86.833) Prec@5 98.000 (99.119) +2022-11-14 13:44:17,864 Epoch: [86][420/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.1250 (0.0786) Prec@1 77.000 (86.605) Prec@5 100.000 (99.140) +2022-11-14 13:44:18,259 Epoch: [86][430/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0863 (0.0787) Prec@1 85.000 (86.568) Prec@5 99.000 (99.136) +2022-11-14 13:44:18,651 Epoch: [86][440/500] Time 0.038 (0.035) Data 0.001 (0.002) Loss 0.0770 (0.0787) Prec@1 85.000 (86.533) Prec@5 100.000 (99.156) +2022-11-14 13:44:19,039 Epoch: [86][450/500] Time 0.036 (0.035) Data 0.003 (0.002) Loss 0.0830 (0.0788) Prec@1 85.000 (86.500) Prec@5 99.000 (99.152) +2022-11-14 13:44:19,432 Epoch: [86][460/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0745 (0.0787) Prec@1 88.000 (86.532) Prec@5 98.000 (99.128) +2022-11-14 13:44:19,818 Epoch: [86][470/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.1060 (0.0793) Prec@1 84.000 (86.479) Prec@5 100.000 (99.146) +2022-11-14 13:44:20,213 Epoch: [86][480/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0797 (0.0793) Prec@1 88.000 (86.510) Prec@5 98.000 (99.122) +2022-11-14 13:44:20,596 Epoch: [86][490/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.1194 (0.0801) Prec@1 80.000 (86.380) Prec@5 99.000 (99.120) +2022-11-14 13:44:20,956 Epoch: [86][499/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0608 (0.0797) Prec@1 89.000 (86.431) Prec@5 99.000 (99.118) +2022-11-14 13:44:21,238 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0785 (0.0785) Prec@1 83.000 (83.000) Prec@5 99.000 (99.000) +2022-11-14 13:44:21,245 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0833) Prec@1 85.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:44:21,256 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1138 (0.0935) Prec@1 79.000 (82.333) Prec@5 100.000 (99.333) +2022-11-14 13:44:21,268 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0960) Prec@1 82.000 (82.250) Prec@5 100.000 (99.500) +2022-11-14 13:44:21,280 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0983) Prec@1 82.000 (82.200) Prec@5 99.000 (99.400) +2022-11-14 13:44:21,292 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0928) Prec@1 90.000 (83.500) Prec@5 100.000 (99.500) +2022-11-14 13:44:21,303 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0940) Prec@1 84.000 (83.571) Prec@5 100.000 (99.571) +2022-11-14 13:44:21,318 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0966) Prec@1 78.000 (82.875) Prec@5 97.000 (99.250) +2022-11-14 13:44:21,331 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0972) Prec@1 85.000 (83.111) Prec@5 100.000 (99.333) +2022-11-14 13:44:21,344 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0951) Prec@1 85.000 (83.300) Prec@5 98.000 (99.200) +2022-11-14 13:44:21,358 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0933) Prec@1 88.000 (83.727) Prec@5 99.000 (99.182) +2022-11-14 13:44:21,371 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0931) Prec@1 83.000 (83.667) Prec@5 100.000 (99.250) +2022-11-14 13:44:21,386 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0928) Prec@1 83.000 (83.615) Prec@5 100.000 (99.308) +2022-11-14 13:44:21,401 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0909) Prec@1 89.000 (84.000) Prec@5 99.000 (99.286) +2022-11-14 13:44:21,415 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0914) Prec@1 83.000 (83.933) Prec@5 98.000 (99.200) +2022-11-14 13:44:21,428 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0922) Prec@1 84.000 (83.938) Prec@5 99.000 (99.188) +2022-11-14 13:44:21,443 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0914) Prec@1 87.000 (84.118) Prec@5 98.000 (99.118) +2022-11-14 13:44:21,457 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0924) Prec@1 82.000 (84.000) Prec@5 97.000 (99.000) +2022-11-14 13:44:21,472 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1249 (0.0941) Prec@1 79.000 (83.737) Prec@5 96.000 (98.842) +2022-11-14 13:44:21,484 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0946) Prec@1 82.000 (83.650) Prec@5 97.000 (98.750) +2022-11-14 13:44:21,499 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1246 (0.0960) Prec@1 79.000 (83.429) Prec@5 98.000 (98.714) +2022-11-14 13:44:21,515 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.0971) Prec@1 80.000 (83.273) Prec@5 99.000 (98.727) +2022-11-14 13:44:21,528 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0971) Prec@1 85.000 (83.348) Prec@5 99.000 (98.739) +2022-11-14 13:44:21,541 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0967) Prec@1 86.000 (83.458) Prec@5 99.000 (98.750) +2022-11-14 13:44:21,554 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.0979) Prec@1 79.000 (83.280) Prec@5 99.000 (98.760) +2022-11-14 13:44:21,566 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0983) Prec@1 84.000 (83.308) Prec@5 97.000 (98.692) +2022-11-14 13:44:21,581 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0972) Prec@1 89.000 (83.519) Prec@5 100.000 (98.741) +2022-11-14 13:44:21,597 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0974) Prec@1 80.000 (83.393) Prec@5 99.000 (98.750) +2022-11-14 13:44:21,611 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0969) Prec@1 89.000 (83.586) Prec@5 99.000 (98.759) +2022-11-14 13:44:21,625 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0971) Prec@1 82.000 (83.533) Prec@5 98.000 (98.733) +2022-11-14 13:44:21,638 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0968) Prec@1 82.000 (83.484) Prec@5 100.000 (98.774) +2022-11-14 13:44:21,652 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0970) Prec@1 85.000 (83.531) Prec@5 100.000 (98.812) +2022-11-14 13:44:21,667 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0971) Prec@1 85.000 (83.576) Prec@5 97.000 (98.758) +2022-11-14 13:44:21,681 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0975) Prec@1 78.000 (83.412) Prec@5 99.000 (98.765) +2022-11-14 13:44:21,694 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0969) Prec@1 86.000 (83.486) Prec@5 98.000 (98.743) +2022-11-14 13:44:21,708 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0969) Prec@1 85.000 (83.528) Prec@5 98.000 (98.722) +2022-11-14 13:44:21,722 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0970) Prec@1 81.000 (83.459) Prec@5 99.000 (98.730) +2022-11-14 13:44:21,735 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.0979) Prec@1 76.000 (83.263) Prec@5 98.000 (98.711) +2022-11-14 13:44:21,750 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0974) Prec@1 89.000 (83.410) Prec@5 98.000 (98.692) +2022-11-14 13:44:21,763 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0971) Prec@1 82.000 (83.375) Prec@5 99.000 (98.700) +2022-11-14 13:44:21,777 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0974) Prec@1 82.000 (83.341) Prec@5 97.000 (98.659) +2022-11-14 13:44:21,791 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0968) Prec@1 88.000 (83.452) Prec@5 100.000 (98.690) +2022-11-14 13:44:21,806 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0966) Prec@1 85.000 (83.488) Prec@5 98.000 (98.674) +2022-11-14 13:44:21,820 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0963) Prec@1 86.000 (83.545) Prec@5 99.000 (98.682) +2022-11-14 13:44:21,836 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0964) Prec@1 83.000 (83.533) Prec@5 99.000 (98.689) +2022-11-14 13:44:21,852 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.0971) Prec@1 77.000 (83.391) Prec@5 99.000 (98.696) +2022-11-14 13:44:21,869 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0970) Prec@1 82.000 (83.362) Prec@5 97.000 (98.660) +2022-11-14 13:44:21,885 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0972) Prec@1 80.000 (83.292) Prec@5 99.000 (98.667) +2022-11-14 13:44:21,901 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0963) Prec@1 90.000 (83.429) Prec@5 100.000 (98.694) +2022-11-14 13:44:21,918 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.0969) Prec@1 80.000 (83.360) Prec@5 98.000 (98.680) +2022-11-14 13:44:21,933 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0966) Prec@1 86.000 (83.412) Prec@5 100.000 (98.706) +2022-11-14 13:44:21,949 Test: [51/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0970) Prec@1 77.000 (83.288) Prec@5 99.000 (98.712) +2022-11-14 13:44:21,966 Test: 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Loss 0.1045 (0.0965) Prec@1 82.000 (83.356) Prec@5 99.000 (98.797) +2022-11-14 13:44:22,069 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0963) Prec@1 85.000 (83.383) Prec@5 99.000 (98.800) +2022-11-14 13:44:22,084 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1190 (0.0967) Prec@1 81.000 (83.344) Prec@5 99.000 (98.803) +2022-11-14 13:44:22,099 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.0969) Prec@1 81.000 (83.306) Prec@5 99.000 (98.806) +2022-11-14 13:44:22,113 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0967) Prec@1 84.000 (83.317) Prec@5 99.000 (98.810) +2022-11-14 13:44:22,129 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0962) Prec@1 89.000 (83.406) Prec@5 99.000 (98.812) +2022-11-14 13:44:22,144 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1172 (0.0965) Prec@1 78.000 (83.323) Prec@5 99.000 (98.815) +2022-11-14 13:44:22,160 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0966) Prec@1 79.000 (83.258) Prec@5 99.000 (98.818) +2022-11-14 13:44:22,173 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0963) Prec@1 87.000 (83.313) Prec@5 98.000 (98.806) +2022-11-14 13:44:22,187 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0962) Prec@1 85.000 (83.338) Prec@5 100.000 (98.824) +2022-11-14 13:44:22,200 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0963) Prec@1 84.000 (83.348) Prec@5 100.000 (98.841) +2022-11-14 13:44:22,213 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1302 (0.0967) Prec@1 78.000 (83.271) Prec@5 99.000 (98.843) +2022-11-14 13:44:22,230 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0966) Prec@1 85.000 (83.296) Prec@5 99.000 (98.845) +2022-11-14 13:44:22,243 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0966) Prec@1 83.000 (83.292) Prec@5 100.000 (98.861) +2022-11-14 13:44:22,259 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0965) Prec@1 87.000 (83.342) Prec@5 98.000 (98.849) +2022-11-14 13:44:22,274 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0961) Prec@1 89.000 (83.419) Prec@5 100.000 (98.865) +2022-11-14 13:44:22,290 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0962) Prec@1 84.000 (83.427) Prec@5 98.000 (98.853) +2022-11-14 13:44:22,306 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0960) Prec@1 88.000 (83.487) Prec@5 99.000 (98.855) +2022-11-14 13:44:22,320 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0957) Prec@1 88.000 (83.545) Prec@5 100.000 (98.870) +2022-11-14 13:44:22,334 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0958) Prec@1 84.000 (83.551) Prec@5 98.000 (98.859) +2022-11-14 13:44:22,348 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0959) Prec@1 84.000 (83.557) Prec@5 100.000 (98.873) +2022-11-14 13:44:22,362 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0956) Prec@1 88.000 (83.612) Prec@5 99.000 (98.875) +2022-11-14 13:44:22,379 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0956) Prec@1 85.000 (83.630) Prec@5 99.000 (98.877) +2022-11-14 13:44:22,393 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0956) Prec@1 81.000 (83.598) Prec@5 100.000 (98.890) +2022-11-14 13:44:22,409 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0956) Prec@1 84.000 (83.602) Prec@5 99.000 (98.892) +2022-11-14 13:44:22,426 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0956) Prec@1 82.000 (83.583) Prec@5 99.000 (98.893) +2022-11-14 13:44:22,442 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0957) Prec@1 83.000 (83.576) Prec@5 99.000 (98.894) +2022-11-14 13:44:22,458 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0959) Prec@1 81.000 (83.547) Prec@5 100.000 (98.907) +2022-11-14 13:44:22,471 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0960) Prec@1 82.000 (83.529) Prec@5 98.000 (98.897) +2022-11-14 13:44:22,485 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0960) Prec@1 83.000 (83.523) Prec@5 100.000 (98.909) +2022-11-14 13:44:22,499 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0959) Prec@1 84.000 (83.528) Prec@5 99.000 (98.910) +2022-11-14 13:44:22,512 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0959) Prec@1 84.000 (83.533) Prec@5 99.000 (98.911) +2022-11-14 13:44:22,529 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0958) Prec@1 85.000 (83.549) Prec@5 100.000 (98.923) +2022-11-14 13:44:22,545 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0954) Prec@1 89.000 (83.609) Prec@5 98.000 (98.913) +2022-11-14 13:44:22,560 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0955) Prec@1 80.000 (83.570) Prec@5 99.000 (98.914) +2022-11-14 13:44:22,576 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0956) Prec@1 82.000 (83.553) Prec@5 99.000 (98.915) +2022-11-14 13:44:22,589 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0957) Prec@1 79.000 (83.505) Prec@5 99.000 (98.916) +2022-11-14 13:44:22,604 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0955) Prec@1 89.000 (83.562) Prec@5 98.000 (98.906) +2022-11-14 13:44:22,618 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0952) Prec@1 90.000 (83.629) Prec@5 98.000 (98.897) +2022-11-14 13:44:22,632 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0952) Prec@1 84.000 (83.633) Prec@5 99.000 (98.898) +2022-11-14 13:44:22,648 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.0954) Prec@1 82.000 (83.616) Prec@5 99.000 (98.899) +2022-11-14 13:44:22,663 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0954) Prec@1 85.000 (83.630) Prec@5 100.000 (98.910) +2022-11-14 13:44:22,725 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:44:23,025 Epoch: [87][0/500] Time 0.021 (0.021) Data 0.218 (0.218) Loss 0.1196 (0.1196) Prec@1 77.000 (77.000) Prec@5 99.000 (99.000) +2022-11-14 13:44:23,255 Epoch: [87][10/500] Time 0.023 (0.020) Data 0.002 (0.021) Loss 0.0722 (0.0959) Prec@1 86.000 (81.500) Prec@5 100.000 (99.500) +2022-11-14 13:44:23,506 Epoch: [87][20/500] Time 0.022 (0.021) Data 0.002 (0.012) Loss 0.0699 (0.0872) Prec@1 89.000 (84.000) Prec@5 100.000 (99.667) +2022-11-14 13:44:23,940 Epoch: [87][30/500] Time 0.046 (0.027) Data 0.002 (0.009) Loss 0.0492 (0.0777) Prec@1 96.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 13:44:24,410 Epoch: [87][40/500] Time 0.044 (0.030) Data 0.002 (0.007) Loss 0.0646 (0.0751) Prec@1 90.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 13:44:24,883 Epoch: [87][50/500] Time 0.044 (0.033) Data 0.002 (0.006) Loss 0.0704 (0.0743) Prec@1 87.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 13:44:25,357 Epoch: [87][60/500] Time 0.042 (0.034) Data 0.003 (0.005) Loss 0.0725 (0.0740) Prec@1 88.000 (87.571) Prec@5 100.000 (99.571) +2022-11-14 13:44:25,877 Epoch: [87][70/500] Time 0.045 (0.036) Data 0.002 (0.005) Loss 0.0837 (0.0753) Prec@1 87.000 (87.500) Prec@5 100.000 (99.625) +2022-11-14 13:44:26,349 Epoch: [87][80/500] Time 0.036 (0.037) Data 0.002 (0.005) Loss 0.0743 (0.0752) Prec@1 87.000 (87.444) Prec@5 100.000 (99.667) +2022-11-14 13:44:26,819 Epoch: [87][90/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0699 (0.0746) Prec@1 89.000 (87.600) Prec@5 100.000 (99.700) +2022-11-14 13:44:27,297 Epoch: [87][100/500] Time 0.042 (0.038) Data 0.003 (0.004) Loss 0.0633 (0.0736) Prec@1 90.000 (87.818) Prec@5 99.000 (99.636) +2022-11-14 13:44:27,779 Epoch: [87][110/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0514 (0.0717) Prec@1 90.000 (88.000) Prec@5 99.000 (99.583) +2022-11-14 13:44:28,250 Epoch: [87][120/500] Time 0.042 (0.039) Data 0.002 (0.004) Loss 0.0680 (0.0715) Prec@1 89.000 (88.077) Prec@5 100.000 (99.615) +2022-11-14 13:44:28,723 Epoch: [87][130/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0936 (0.0730) Prec@1 83.000 (87.714) Prec@5 99.000 (99.571) +2022-11-14 13:44:29,194 Epoch: [87][140/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0995 (0.0748) Prec@1 81.000 (87.267) Prec@5 99.000 (99.533) +2022-11-14 13:44:29,665 Epoch: [87][150/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0721 (0.0746) Prec@1 86.000 (87.188) Prec@5 99.000 (99.500) +2022-11-14 13:44:30,196 Epoch: [87][160/500] Time 0.055 (0.040) Data 0.002 (0.003) Loss 0.0727 (0.0745) Prec@1 86.000 (87.118) Prec@5 98.000 (99.412) +2022-11-14 13:44:30,688 Epoch: [87][170/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0835 (0.0750) Prec@1 83.000 (86.889) Prec@5 100.000 (99.444) +2022-11-14 13:44:31,173 Epoch: [87][180/500] Time 0.043 (0.040) Data 0.001 (0.003) Loss 0.0689 (0.0747) Prec@1 88.000 (86.947) Prec@5 100.000 (99.474) +2022-11-14 13:44:31,678 Epoch: [87][190/500] Time 0.057 (0.040) Data 0.003 (0.003) Loss 0.0720 (0.0746) Prec@1 88.000 (87.000) Prec@5 98.000 (99.400) +2022-11-14 13:44:32,170 Epoch: [87][200/500] Time 0.063 (0.041) Data 0.002 (0.003) Loss 0.0893 (0.0753) Prec@1 86.000 (86.952) Prec@5 99.000 (99.381) +2022-11-14 13:44:32,643 Epoch: [87][210/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0979 (0.0763) Prec@1 83.000 (86.773) Prec@5 100.000 (99.409) +2022-11-14 13:44:33,146 Epoch: [87][220/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0936 (0.0770) Prec@1 82.000 (86.565) Prec@5 98.000 (99.348) +2022-11-14 13:44:33,627 Epoch: [87][230/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0590 (0.0763) Prec@1 92.000 (86.792) Prec@5 100.000 (99.375) +2022-11-14 13:44:34,099 Epoch: [87][240/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0906 (0.0769) Prec@1 85.000 (86.720) Prec@5 99.000 (99.360) +2022-11-14 13:44:34,574 Epoch: [87][250/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0780 (0.0769) Prec@1 84.000 (86.615) Prec@5 100.000 (99.385) +2022-11-14 13:44:35,046 Epoch: [87][260/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0697 (0.0766) Prec@1 89.000 (86.704) Prec@5 100.000 (99.407) +2022-11-14 13:44:35,858 Epoch: [87][270/500] Time 0.090 (0.042) Data 0.002 (0.003) Loss 0.0796 (0.0767) Prec@1 86.000 (86.679) Prec@5 99.000 (99.393) +2022-11-14 13:44:36,281 Epoch: [87][280/500] Time 0.050 (0.042) Data 0.002 (0.003) Loss 0.0874 (0.0771) Prec@1 86.000 (86.655) Prec@5 99.000 (99.379) +2022-11-14 13:44:36,668 Epoch: [87][290/500] Time 0.033 (0.042) Data 0.002 (0.003) Loss 0.0639 (0.0767) Prec@1 89.000 (86.733) Prec@5 99.000 (99.367) +2022-11-14 13:44:37,071 Epoch: [87][300/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0790 (0.0767) Prec@1 86.000 (86.710) Prec@5 98.000 (99.323) +2022-11-14 13:44:37,453 Epoch: [87][310/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0686 (0.0765) Prec@1 87.000 (86.719) Prec@5 100.000 (99.344) +2022-11-14 13:44:37,849 Epoch: [87][320/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0543 (0.0758) Prec@1 92.000 (86.879) Prec@5 99.000 (99.333) +2022-11-14 13:44:38,230 Epoch: [87][330/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.1045 (0.0767) Prec@1 84.000 (86.794) Prec@5 98.000 (99.294) +2022-11-14 13:44:38,620 Epoch: [87][340/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0658 (0.0764) Prec@1 86.000 (86.771) Prec@5 100.000 (99.314) +2022-11-14 13:44:39,002 Epoch: [87][350/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0747 (0.0763) Prec@1 88.000 (86.806) Prec@5 99.000 (99.306) +2022-11-14 13:44:39,382 Epoch: [87][360/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.0914 (0.0767) Prec@1 86.000 (86.784) Prec@5 99.000 (99.297) +2022-11-14 13:44:39,764 Epoch: [87][370/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0596 (0.0763) Prec@1 90.000 (86.868) Prec@5 98.000 (99.263) +2022-11-14 13:44:40,150 Epoch: [87][380/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0837 (0.0765) Prec@1 86.000 (86.846) Prec@5 99.000 (99.256) +2022-11-14 13:44:40,540 Epoch: [87][390/500] Time 0.038 (0.040) Data 0.002 (0.002) Loss 0.0666 (0.0762) Prec@1 86.000 (86.825) Prec@5 100.000 (99.275) +2022-11-14 13:44:41,010 Epoch: [87][400/500] Time 0.049 (0.040) Data 0.002 (0.002) Loss 0.0564 (0.0757) Prec@1 91.000 (86.927) Prec@5 99.000 (99.268) +2022-11-14 13:44:41,478 Epoch: [87][410/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.0627 (0.0754) Prec@1 88.000 (86.952) Prec@5 99.000 (99.262) +2022-11-14 13:44:41,955 Epoch: [87][420/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0968 (0.0759) Prec@1 84.000 (86.884) Prec@5 99.000 (99.256) +2022-11-14 13:44:42,439 Epoch: [87][430/500] Time 0.046 (0.040) Data 0.002 (0.002) Loss 0.0731 (0.0758) Prec@1 86.000 (86.864) Prec@5 100.000 (99.273) +2022-11-14 13:44:42,825 Epoch: [87][440/500] Time 0.039 (0.040) Data 0.002 (0.002) Loss 0.0795 (0.0759) Prec@1 86.000 (86.844) Prec@5 97.000 (99.222) +2022-11-14 13:44:43,204 Epoch: [87][450/500] Time 0.035 (0.040) Data 0.002 (0.002) Loss 0.1142 (0.0768) Prec@1 79.000 (86.674) Prec@5 100.000 (99.239) +2022-11-14 13:44:43,643 Epoch: [87][460/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.0579 (0.0764) Prec@1 90.000 (86.745) Prec@5 100.000 (99.255) +2022-11-14 13:44:44,115 Epoch: [87][470/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0563 (0.0759) Prec@1 90.000 (86.812) Prec@5 99.000 (99.250) +2022-11-14 13:44:44,580 Epoch: [87][480/500] Time 0.045 (0.040) Data 0.002 (0.002) Loss 0.0980 (0.0764) Prec@1 82.000 (86.714) Prec@5 99.000 (99.245) +2022-11-14 13:44:45,021 Epoch: [87][490/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0763 (0.0764) Prec@1 85.000 (86.680) Prec@5 100.000 (99.260) +2022-11-14 13:44:45,454 Epoch: [87][499/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0659 (0.0762) Prec@1 90.000 (86.745) Prec@5 98.000 (99.235) +2022-11-14 13:44:45,763 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0866 (0.0866) Prec@1 85.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:44:45,778 Test: [1/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.1042 (0.0954) Prec@1 83.000 (84.000) Prec@5 98.000 (98.500) +2022-11-14 13:44:45,792 Test: [2/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0772 (0.0893) Prec@1 85.000 (84.333) Prec@5 100.000 (99.000) +2022-11-14 13:44:45,805 Test: [3/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.1092 (0.0943) Prec@1 79.000 (83.000) Prec@5 98.000 (98.750) +2022-11-14 13:44:45,814 Test: [4/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.1043 (0.0963) Prec@1 82.000 (82.800) Prec@5 97.000 (98.400) +2022-11-14 13:44:45,822 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0476 (0.0882) Prec@1 92.000 (84.333) Prec@5 100.000 (98.667) +2022-11-14 13:44:45,833 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0895 (0.0884) Prec@1 85.000 (84.429) Prec@5 100.000 (98.857) +2022-11-14 13:44:45,844 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1182 (0.0921) Prec@1 79.000 (83.750) Prec@5 99.000 (98.875) +2022-11-14 13:44:45,856 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1105 (0.0941) Prec@1 81.000 (83.444) Prec@5 99.000 (98.889) +2022-11-14 13:44:45,868 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0928) Prec@1 85.000 (83.600) Prec@5 97.000 (98.700) +2022-11-14 13:44:45,881 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0908) Prec@1 90.000 (84.182) Prec@5 99.000 (98.727) +2022-11-14 13:44:45,895 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1108 (0.0924) Prec@1 80.000 (83.833) Prec@5 99.000 (98.750) +2022-11-14 13:44:45,908 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0920) Prec@1 87.000 (84.077) Prec@5 100.000 (98.846) +2022-11-14 13:44:45,922 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0922) Prec@1 83.000 (84.000) Prec@5 99.000 (98.857) +2022-11-14 13:44:45,936 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0933) Prec@1 82.000 (83.867) Prec@5 98.000 (98.800) +2022-11-14 13:44:45,948 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.0946) Prec@1 79.000 (83.562) Prec@5 99.000 (98.812) +2022-11-14 13:44:45,961 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0932) Prec@1 87.000 (83.765) Prec@5 98.000 (98.765) +2022-11-14 13:44:45,976 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1337 (0.0954) Prec@1 77.000 (83.389) Prec@5 100.000 (98.833) +2022-11-14 13:44:45,992 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0955) Prec@1 83.000 (83.368) Prec@5 100.000 (98.895) +2022-11-14 13:44:46,006 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1307 (0.0973) Prec@1 77.000 (83.050) Prec@5 97.000 (98.800) +2022-11-14 13:44:46,019 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0977) Prec@1 82.000 (83.000) Prec@5 97.000 (98.714) +2022-11-14 13:44:46,033 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0982) Prec@1 79.000 (82.818) Prec@5 97.000 (98.636) +2022-11-14 13:44:46,048 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1150 (0.0989) Prec@1 81.000 (82.739) Prec@5 99.000 (98.652) +2022-11-14 13:44:46,061 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0988) Prec@1 83.000 (82.750) Prec@5 99.000 (98.667) +2022-11-14 13:44:46,076 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0988) Prec@1 84.000 (82.800) Prec@5 100.000 (98.720) +2022-11-14 13:44:46,089 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1145 (0.0994) Prec@1 81.000 (82.731) Prec@5 96.000 (98.615) +2022-11-14 13:44:46,103 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.1000) Prec@1 83.000 (82.741) Prec@5 100.000 (98.667) +2022-11-14 13:44:46,118 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.1002) Prec@1 83.000 (82.750) Prec@5 98.000 (98.643) +2022-11-14 13:44:46,134 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0995) Prec@1 88.000 (82.931) Prec@5 98.000 (98.621) +2022-11-14 13:44:46,149 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0996) Prec@1 81.000 (82.867) Prec@5 98.000 (98.600) +2022-11-14 13:44:46,164 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0995) Prec@1 81.000 (82.806) Prec@5 100.000 (98.645) +2022-11-14 13:44:46,180 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0991) Prec@1 88.000 (82.969) Prec@5 100.000 (98.688) +2022-11-14 13:44:46,193 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0992) Prec@1 84.000 (83.000) Prec@5 99.000 (98.697) +2022-11-14 13:44:46,208 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1226 (0.0999) Prec@1 80.000 (82.912) Prec@5 98.000 (98.676) +2022-11-14 13:44:46,222 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0999) Prec@1 82.000 (82.886) Prec@5 98.000 (98.657) +2022-11-14 13:44:46,236 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1105 (0.1002) Prec@1 81.000 (82.833) Prec@5 100.000 (98.694) +2022-11-14 13:44:46,252 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.1002) Prec@1 81.000 (82.784) Prec@5 98.000 (98.676) +2022-11-14 13:44:46,268 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.1002) Prec@1 81.000 (82.737) Prec@5 100.000 (98.711) +2022-11-14 13:44:46,284 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0996) Prec@1 90.000 (82.923) Prec@5 100.000 (98.744) +2022-11-14 13:44:46,298 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0992) Prec@1 84.000 (82.950) Prec@5 98.000 (98.725) +2022-11-14 13:44:46,312 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0993) Prec@1 83.000 (82.951) Prec@5 97.000 (98.683) +2022-11-14 13:44:46,329 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0992) Prec@1 86.000 (83.024) Prec@5 98.000 (98.667) +2022-11-14 13:44:46,344 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0985) Prec@1 88.000 (83.140) Prec@5 98.000 (98.651) +2022-11-14 13:44:46,359 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0985) Prec@1 85.000 (83.182) Prec@5 98.000 (98.636) +2022-11-14 13:44:46,373 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1080 (0.0987) Prec@1 82.000 (83.156) Prec@5 100.000 (98.667) +2022-11-14 13:44:46,388 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0988) Prec@1 81.000 (83.109) Prec@5 98.000 (98.652) +2022-11-14 13:44:46,402 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0987) Prec@1 83.000 (83.106) Prec@5 99.000 (98.660) +2022-11-14 13:44:46,416 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0985) Prec@1 85.000 (83.146) Prec@5 98.000 (98.646) +2022-11-14 13:44:46,432 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0982) Prec@1 85.000 (83.184) Prec@5 100.000 (98.673) +2022-11-14 13:44:46,446 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1443 (0.0991) Prec@1 77.000 (83.060) Prec@5 98.000 (98.660) +2022-11-14 13:44:46,459 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0986) Prec@1 87.000 (83.137) Prec@5 100.000 (98.686) +2022-11-14 13:44:46,475 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1127 (0.0989) Prec@1 78.000 (83.038) Prec@5 100.000 (98.712) +2022-11-14 13:44:46,490 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0987) Prec@1 84.000 (83.057) Prec@5 99.000 (98.717) +2022-11-14 13:44:46,506 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0984) Prec@1 85.000 (83.093) Prec@5 100.000 (98.741) +2022-11-14 13:44:46,519 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0984) Prec@1 85.000 (83.127) Prec@5 100.000 (98.764) +2022-11-14 13:44:46,533 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0983) Prec@1 84.000 (83.143) Prec@5 100.000 (98.786) +2022-11-14 13:44:46,548 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0982) Prec@1 84.000 (83.158) Prec@5 99.000 (98.789) +2022-11-14 13:44:46,561 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0978) Prec@1 88.000 (83.241) Prec@5 99.000 (98.793) +2022-11-14 13:44:46,576 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1371 (0.0984) Prec@1 75.000 (83.102) Prec@5 98.000 (98.780) +2022-11-14 13:44:46,590 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0981) Prec@1 86.000 (83.150) Prec@5 98.000 (98.767) +2022-11-14 13:44:46,606 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0983) Prec@1 83.000 (83.148) Prec@5 99.000 (98.770) +2022-11-14 13:44:46,620 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0983) Prec@1 83.000 (83.145) Prec@5 99.000 (98.774) +2022-11-14 13:44:46,633 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0982) Prec@1 85.000 (83.175) Prec@5 100.000 (98.794) +2022-11-14 13:44:46,648 Test: [63/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0978) Prec@1 88.000 (83.250) Prec@5 99.000 (98.797) +2022-11-14 13:44:46,663 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1225 (0.0982) Prec@1 77.000 (83.154) Prec@5 99.000 (98.800) +2022-11-14 13:44:46,678 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1285 (0.0987) Prec@1 75.000 (83.030) Prec@5 99.000 (98.803) +2022-11-14 13:44:46,693 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0980) Prec@1 91.000 (83.149) Prec@5 99.000 (98.806) +2022-11-14 13:44:46,707 Test: [67/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1095 (0.0982) Prec@1 83.000 (83.147) Prec@5 99.000 (98.809) +2022-11-14 13:44:46,720 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0979) Prec@1 89.000 (83.232) Prec@5 98.000 (98.797) +2022-11-14 13:44:46,735 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0980) Prec@1 79.000 (83.171) Prec@5 97.000 (98.771) +2022-11-14 13:44:46,749 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.0983) Prec@1 82.000 (83.155) Prec@5 98.000 (98.761) +2022-11-14 13:44:46,763 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0981) Prec@1 85.000 (83.181) Prec@5 100.000 (98.778) +2022-11-14 13:44:46,777 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0979) Prec@1 86.000 (83.219) Prec@5 99.000 (98.781) +2022-11-14 13:44:46,792 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0976) Prec@1 86.000 (83.257) Prec@5 100.000 (98.797) +2022-11-14 13:44:46,806 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1294 (0.0980) Prec@1 76.000 (83.160) Prec@5 98.000 (98.787) +2022-11-14 13:44:46,821 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0979) Prec@1 86.000 (83.197) Prec@5 98.000 (98.776) +2022-11-14 13:44:46,836 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0978) Prec@1 83.000 (83.195) Prec@5 100.000 (98.792) +2022-11-14 13:44:46,852 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0979) Prec@1 82.000 (83.179) Prec@5 97.000 (98.769) +2022-11-14 13:44:46,867 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0980) Prec@1 84.000 (83.190) Prec@5 100.000 (98.785) +2022-11-14 13:44:46,880 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0981) Prec@1 79.000 (83.138) Prec@5 98.000 (98.775) +2022-11-14 13:44:46,894 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0980) Prec@1 83.000 (83.136) Prec@5 99.000 (98.778) +2022-11-14 13:44:46,908 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0981) Prec@1 82.000 (83.122) Prec@5 99.000 (98.780) +2022-11-14 13:44:46,921 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0981) Prec@1 83.000 (83.120) Prec@5 100.000 (98.795) +2022-11-14 13:44:46,937 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0981) Prec@1 83.000 (83.119) Prec@5 99.000 (98.798) +2022-11-14 13:44:46,951 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0982) Prec@1 83.000 (83.118) Prec@5 98.000 (98.788) +2022-11-14 13:44:46,966 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1212 (0.0984) Prec@1 82.000 (83.105) Prec@5 96.000 (98.756) +2022-11-14 13:44:46,983 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.0986) Prec@1 82.000 (83.092) Prec@5 99.000 (98.759) +2022-11-14 13:44:46,998 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0984) Prec@1 85.000 (83.114) Prec@5 99.000 (98.761) +2022-11-14 13:44:47,012 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0984) Prec@1 84.000 (83.124) Prec@5 97.000 (98.742) +2022-11-14 13:44:47,027 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0982) Prec@1 86.000 (83.156) Prec@5 99.000 (98.744) +2022-11-14 13:44:47,041 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0982) Prec@1 81.000 (83.132) Prec@5 100.000 (98.758) +2022-11-14 13:44:47,055 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0979) Prec@1 89.000 (83.196) Prec@5 99.000 (98.761) +2022-11-14 13:44:47,069 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0980) Prec@1 82.000 (83.183) Prec@5 97.000 (98.742) +2022-11-14 13:44:47,082 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0980) Prec@1 85.000 (83.202) Prec@5 98.000 (98.734) +2022-11-14 13:44:47,097 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0981) Prec@1 82.000 (83.189) Prec@5 99.000 (98.737) +2022-11-14 13:44:47,113 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0979) Prec@1 86.000 (83.219) Prec@5 100.000 (98.750) +2022-11-14 13:44:47,127 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0977) Prec@1 88.000 (83.268) Prec@5 100.000 (98.763) +2022-11-14 13:44:47,141 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1212 (0.0979) Prec@1 79.000 (83.224) Prec@5 97.000 (98.745) +2022-11-14 13:44:47,157 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0979) Prec@1 84.000 (83.232) Prec@5 100.000 (98.758) +2022-11-14 13:44:47,169 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0978) Prec@1 87.000 (83.270) Prec@5 100.000 (98.770) +2022-11-14 13:44:47,242 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:44:47,650 Epoch: [88][0/500] Time 0.037 (0.037) Data 0.306 (0.306) Loss 0.0636 (0.0636) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:44:47,979 Epoch: [88][10/500] Time 0.033 (0.030) Data 0.003 (0.030) Loss 0.0697 (0.0666) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:44:48,320 Epoch: [88][20/500] Time 0.032 (0.030) Data 0.002 (0.017) Loss 0.0947 (0.0760) Prec@1 81.000 (85.667) Prec@5 99.000 (99.667) +2022-11-14 13:44:48,669 Epoch: [88][30/500] Time 0.029 (0.031) Data 0.002 (0.013) Loss 0.0680 (0.0740) Prec@1 90.000 (86.750) Prec@5 98.000 (99.250) +2022-11-14 13:44:49,008 Epoch: [88][40/500] Time 0.037 (0.030) Data 0.003 (0.010) Loss 0.0519 (0.0696) Prec@1 92.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 13:44:49,301 Epoch: [88][50/500] Time 0.021 (0.030) Data 0.002 (0.009) Loss 0.0983 (0.0744) Prec@1 81.000 (86.667) Prec@5 100.000 (99.500) +2022-11-14 13:44:49,522 Epoch: [88][60/500] Time 0.017 (0.028) Data 0.002 (0.008) Loss 0.0423 (0.0698) Prec@1 91.000 (87.286) Prec@5 100.000 (99.571) +2022-11-14 13:44:49,837 Epoch: [88][70/500] Time 0.030 (0.028) Data 0.002 (0.007) Loss 0.0798 (0.0710) Prec@1 83.000 (86.750) Prec@5 100.000 (99.625) +2022-11-14 13:44:50,208 Epoch: [88][80/500] Time 0.036 (0.029) Data 0.002 (0.006) Loss 0.0797 (0.0720) Prec@1 87.000 (86.778) Prec@5 99.000 (99.556) +2022-11-14 13:44:50,587 Epoch: [88][90/500] Time 0.036 (0.029) Data 0.002 (0.006) Loss 0.0812 (0.0729) Prec@1 88.000 (86.900) Prec@5 98.000 (99.400) +2022-11-14 13:44:50,964 Epoch: [88][100/500] Time 0.030 (0.030) Data 0.002 (0.005) Loss 0.1015 (0.0755) Prec@1 82.000 (86.455) Prec@5 100.000 (99.455) +2022-11-14 13:44:51,335 Epoch: [88][110/500] Time 0.036 (0.030) Data 0.002 (0.005) Loss 0.0729 (0.0753) Prec@1 88.000 (86.583) Prec@5 97.000 (99.250) +2022-11-14 13:44:51,705 Epoch: [88][120/500] Time 0.034 (0.030) Data 0.002 (0.005) Loss 0.0714 (0.0750) Prec@1 88.000 (86.692) Prec@5 100.000 (99.308) +2022-11-14 13:44:52,076 Epoch: [88][130/500] Time 0.040 (0.030) Data 0.003 (0.005) Loss 0.1261 (0.0787) Prec@1 76.000 (85.929) Prec@5 100.000 (99.357) +2022-11-14 13:44:52,493 Epoch: [88][140/500] Time 0.041 (0.031) Data 0.003 (0.004) Loss 0.0799 (0.0787) Prec@1 86.000 (85.933) Prec@5 100.000 (99.400) +2022-11-14 13:44:52,843 Epoch: [88][150/500] Time 0.032 (0.031) Data 0.002 (0.004) Loss 0.0904 (0.0795) Prec@1 86.000 (85.938) Prec@5 100.000 (99.438) +2022-11-14 13:44:53,224 Epoch: [88][160/500] Time 0.030 (0.031) Data 0.002 (0.004) Loss 0.1039 (0.0809) Prec@1 83.000 (85.765) Prec@5 99.000 (99.412) +2022-11-14 13:44:53,601 Epoch: [88][170/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0487 (0.0791) Prec@1 91.000 (86.056) Prec@5 98.000 (99.333) +2022-11-14 13:44:54,002 Epoch: [88][180/500] Time 0.060 (0.031) Data 0.002 (0.004) Loss 0.0878 (0.0796) Prec@1 82.000 (85.842) Prec@5 100.000 (99.368) +2022-11-14 13:44:54,384 Epoch: [88][190/500] Time 0.055 (0.032) Data 0.002 (0.004) Loss 0.1005 (0.0806) Prec@1 82.000 (85.650) Prec@5 98.000 (99.300) +2022-11-14 13:44:54,739 Epoch: [88][200/500] Time 0.036 (0.032) Data 0.002 (0.004) Loss 0.0851 (0.0808) Prec@1 85.000 (85.619) Prec@5 99.000 (99.286) +2022-11-14 13:44:55,110 Epoch: [88][210/500] Time 0.033 (0.032) Data 0.002 (0.004) Loss 0.0687 (0.0803) Prec@1 88.000 (85.727) Prec@5 99.000 (99.273) +2022-11-14 13:44:55,483 Epoch: [88][220/500] Time 0.036 (0.032) Data 0.002 (0.004) Loss 0.0642 (0.0796) Prec@1 89.000 (85.870) Prec@5 100.000 (99.304) +2022-11-14 13:44:55,858 Epoch: [88][230/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0834 (0.0797) Prec@1 87.000 (85.917) Prec@5 99.000 (99.292) +2022-11-14 13:44:56,231 Epoch: [88][240/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0923 (0.0802) Prec@1 86.000 (85.920) Prec@5 100.000 (99.320) +2022-11-14 13:44:56,603 Epoch: [88][250/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0549 (0.0793) Prec@1 91.000 (86.115) Prec@5 99.000 (99.308) +2022-11-14 13:44:56,990 Epoch: [88][260/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0888 (0.0796) Prec@1 84.000 (86.037) Prec@5 98.000 (99.259) +2022-11-14 13:44:57,353 Epoch: [88][270/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0888 (0.0799) Prec@1 84.000 (85.964) Prec@5 100.000 (99.286) +2022-11-14 13:44:57,749 Epoch: [88][280/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.0788 (0.0799) Prec@1 88.000 (86.034) Prec@5 99.000 (99.276) +2022-11-14 13:44:58,131 Epoch: [88][290/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0578 (0.0792) Prec@1 91.000 (86.200) Prec@5 99.000 (99.267) +2022-11-14 13:44:58,523 Epoch: [88][300/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0767 (0.0791) Prec@1 84.000 (86.129) Prec@5 99.000 (99.258) +2022-11-14 13:44:58,901 Epoch: [88][310/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.1252 (0.0805) Prec@1 78.000 (85.875) Prec@5 100.000 (99.281) +2022-11-14 13:44:59,271 Epoch: [88][320/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0883 (0.0808) Prec@1 84.000 (85.818) Prec@5 98.000 (99.242) +2022-11-14 13:44:59,649 Epoch: [88][330/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0938 (0.0811) Prec@1 85.000 (85.794) Prec@5 99.000 (99.235) +2022-11-14 13:45:00,032 Epoch: [88][340/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0837 (0.0812) Prec@1 86.000 (85.800) Prec@5 99.000 (99.229) +2022-11-14 13:45:00,406 Epoch: [88][350/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0714 (0.0809) Prec@1 87.000 (85.833) Prec@5 100.000 (99.250) +2022-11-14 13:45:00,782 Epoch: [88][360/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0831 (0.0810) Prec@1 85.000 (85.811) Prec@5 100.000 (99.270) +2022-11-14 13:45:01,152 Epoch: [88][370/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0833 (0.0811) Prec@1 88.000 (85.868) Prec@5 100.000 (99.289) +2022-11-14 13:45:01,522 Epoch: [88][380/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0661 (0.0807) Prec@1 89.000 (85.949) Prec@5 98.000 (99.256) +2022-11-14 13:45:01,888 Epoch: [88][390/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0663 (0.0803) Prec@1 88.000 (86.000) Prec@5 98.000 (99.225) +2022-11-14 13:45:02,262 Epoch: [88][400/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0668 (0.0800) Prec@1 87.000 (86.024) Prec@5 100.000 (99.244) +2022-11-14 13:45:02,660 Epoch: [88][410/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.0311 (0.0788) Prec@1 94.000 (86.214) Prec@5 100.000 (99.262) +2022-11-14 13:45:03,036 Epoch: [88][420/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0453 (0.0781) Prec@1 91.000 (86.326) Prec@5 100.000 (99.279) +2022-11-14 13:45:03,418 Epoch: [88][430/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0793 (0.0781) Prec@1 85.000 (86.295) Prec@5 98.000 (99.250) +2022-11-14 13:45:03,790 Epoch: [88][440/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0950 (0.0785) Prec@1 83.000 (86.222) Prec@5 99.000 (99.244) +2022-11-14 13:45:04,166 Epoch: [88][450/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0489 (0.0778) Prec@1 91.000 (86.326) Prec@5 100.000 (99.261) +2022-11-14 13:45:04,538 Epoch: [88][460/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0748 (0.0777) Prec@1 86.000 (86.319) Prec@5 100.000 (99.277) +2022-11-14 13:45:04,917 Epoch: [88][470/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0465 (0.0771) Prec@1 93.000 (86.458) Prec@5 100.000 (99.292) +2022-11-14 13:45:05,292 Epoch: [88][480/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0902 (0.0774) Prec@1 84.000 (86.408) Prec@5 100.000 (99.306) +2022-11-14 13:45:05,667 Epoch: [88][490/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.1074 (0.0780) Prec@1 83.000 (86.340) Prec@5 98.000 (99.280) +2022-11-14 13:45:06,009 Epoch: [88][499/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0845 (0.0781) Prec@1 85.000 (86.314) Prec@5 100.000 (99.294) +2022-11-14 13:45:06,293 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0703 (0.0703) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:45:06,301 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0727) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 13:45:06,311 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0805) Prec@1 85.000 (86.667) Prec@5 99.000 (99.667) +2022-11-14 13:45:06,326 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0871) Prec@1 81.000 (85.250) Prec@5 98.000 (99.250) +2022-11-14 13:45:06,335 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0846) Prec@1 87.000 (85.600) Prec@5 100.000 (99.400) +2022-11-14 13:45:06,346 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0799) Prec@1 89.000 (86.167) Prec@5 100.000 (99.500) +2022-11-14 13:45:06,356 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0792) Prec@1 88.000 (86.429) Prec@5 100.000 (99.571) +2022-11-14 13:45:06,370 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0819) Prec@1 80.000 (85.625) Prec@5 100.000 (99.625) +2022-11-14 13:45:06,381 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0857) Prec@1 80.000 (85.000) Prec@5 100.000 (99.667) +2022-11-14 13:45:06,392 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0861) Prec@1 81.000 (84.600) Prec@5 99.000 (99.600) +2022-11-14 13:45:06,407 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0844) Prec@1 89.000 (85.000) Prec@5 99.000 (99.545) +2022-11-14 13:45:06,421 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0862) Prec@1 81.000 (84.667) Prec@5 100.000 (99.583) +2022-11-14 13:45:06,433 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0875) Prec@1 82.000 (84.462) Prec@5 100.000 (99.615) +2022-11-14 13:45:06,447 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0866) Prec@1 87.000 (84.643) Prec@5 98.000 (99.500) +2022-11-14 13:45:06,461 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0866) Prec@1 85.000 (84.667) Prec@5 100.000 (99.533) +2022-11-14 13:45:06,475 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0875) Prec@1 84.000 (84.625) Prec@5 99.000 (99.500) +2022-11-14 13:45:06,489 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0874) Prec@1 88.000 (84.824) Prec@5 99.000 (99.471) +2022-11-14 13:45:06,504 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0884) Prec@1 82.000 (84.667) Prec@5 100.000 (99.500) +2022-11-14 13:45:06,517 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0888) Prec@1 84.000 (84.632) Prec@5 100.000 (99.526) +2022-11-14 13:45:06,533 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0902) Prec@1 82.000 (84.500) Prec@5 96.000 (99.350) +2022-11-14 13:45:06,546 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.0911) Prec@1 78.000 (84.190) Prec@5 97.000 (99.238) +2022-11-14 13:45:06,560 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0911) Prec@1 84.000 (84.182) Prec@5 99.000 (99.227) +2022-11-14 13:45:06,574 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.0922) Prec@1 79.000 (83.957) Prec@5 99.000 (99.217) +2022-11-14 13:45:06,588 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0920) Prec@1 84.000 (83.958) Prec@5 99.000 (99.208) +2022-11-14 13:45:06,602 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1182 (0.0930) Prec@1 76.000 (83.640) Prec@5 100.000 (99.240) +2022-11-14 13:45:06,615 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1315 (0.0945) Prec@1 81.000 (83.538) Prec@5 96.000 (99.115) +2022-11-14 13:45:06,629 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0935) Prec@1 86.000 (83.630) Prec@5 100.000 (99.148) +2022-11-14 13:45:06,643 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0933) Prec@1 84.000 (83.643) Prec@5 100.000 (99.179) +2022-11-14 13:45:06,658 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0930) Prec@1 84.000 (83.655) Prec@5 98.000 (99.138) +2022-11-14 13:45:06,671 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0926) Prec@1 88.000 (83.800) Prec@5 100.000 (99.167) +2022-11-14 13:45:06,685 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0919) Prec@1 87.000 (83.903) Prec@5 100.000 (99.194) +2022-11-14 13:45:06,699 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0920) Prec@1 84.000 (83.906) Prec@5 100.000 (99.219) +2022-11-14 13:45:06,712 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0917) Prec@1 85.000 (83.939) Prec@5 99.000 (99.212) +2022-11-14 13:45:06,728 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0922) Prec@1 78.000 (83.765) Prec@5 100.000 (99.235) +2022-11-14 13:45:06,741 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0920) Prec@1 86.000 (83.829) Prec@5 98.000 (99.200) +2022-11-14 13:45:06,754 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0916) Prec@1 87.000 (83.917) Prec@5 99.000 (99.194) +2022-11-14 13:45:06,769 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0917) Prec@1 82.000 (83.865) Prec@5 100.000 (99.216) +2022-11-14 13:45:06,783 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0922) Prec@1 78.000 (83.711) Prec@5 98.000 (99.184) +2022-11-14 13:45:06,796 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0919) Prec@1 87.000 (83.795) Prec@5 99.000 (99.179) +2022-11-14 13:45:06,810 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0914) Prec@1 88.000 (83.900) Prec@5 98.000 (99.150) +2022-11-14 13:45:06,825 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.0920) Prec@1 83.000 (83.878) Prec@5 96.000 (99.073) +2022-11-14 13:45:06,838 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0917) Prec@1 88.000 (83.976) Prec@5 99.000 (99.071) +2022-11-14 13:45:06,852 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0912) Prec@1 87.000 (84.047) Prec@5 100.000 (99.093) +2022-11-14 13:45:06,865 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0909) Prec@1 87.000 (84.114) Prec@5 99.000 (99.091) +2022-11-14 13:45:06,880 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0913) Prec@1 80.000 (84.022) Prec@5 98.000 (99.067) +2022-11-14 13:45:06,894 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0916) Prec@1 80.000 (83.935) Prec@5 100.000 (99.087) +2022-11-14 13:45:06,908 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0915) Prec@1 85.000 (83.957) Prec@5 100.000 (99.106) +2022-11-14 13:45:06,921 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0914) Prec@1 85.000 (83.979) Prec@5 98.000 (99.083) +2022-11-14 13:45:06,935 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0910) Prec@1 86.000 (84.020) Prec@5 100.000 (99.102) +2022-11-14 13:45:06,951 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0915) Prec@1 79.000 (83.920) Prec@5 99.000 (99.100) +2022-11-14 13:45:06,964 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0915) Prec@1 82.000 (83.882) Prec@5 100.000 (99.118) +2022-11-14 13:45:06,978 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.0920) Prec@1 80.000 (83.808) Prec@5 100.000 (99.135) +2022-11-14 13:45:06,992 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0922) Prec@1 81.000 (83.755) Prec@5 98.000 (99.113) +2022-11-14 13:45:07,005 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0919) Prec@1 87.000 (83.815) Prec@5 99.000 (99.111) +2022-11-14 13:45:07,019 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0919) Prec@1 83.000 (83.800) Prec@5 100.000 (99.127) +2022-11-14 13:45:07,033 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0921) Prec@1 84.000 (83.804) Prec@5 100.000 (99.143) +2022-11-14 13:45:07,048 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0923) Prec@1 84.000 (83.807) Prec@5 99.000 (99.140) +2022-11-14 13:45:07,061 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0920) Prec@1 88.000 (83.879) Prec@5 99.000 (99.138) +2022-11-14 13:45:07,075 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0923) Prec@1 81.000 (83.831) Prec@5 100.000 (99.153) +2022-11-14 13:45:07,089 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1239 (0.0928) Prec@1 75.000 (83.683) Prec@5 99.000 (99.150) +2022-11-14 13:45:07,103 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0929) Prec@1 85.000 (83.705) Prec@5 100.000 (99.164) +2022-11-14 13:45:07,117 Test: [61/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0930) Prec@1 84.000 (83.710) Prec@5 99.000 (99.161) +2022-11-14 13:45:07,131 Test: [62/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0926) Prec@1 87.000 (83.762) Prec@5 100.000 (99.175) +2022-11-14 13:45:07,146 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0921) Prec@1 89.000 (83.844) Prec@5 100.000 (99.188) +2022-11-14 13:45:07,161 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.0926) Prec@1 78.000 (83.754) Prec@5 98.000 (99.169) +2022-11-14 13:45:07,179 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0926) Prec@1 83.000 (83.742) Prec@5 98.000 (99.152) +2022-11-14 13:45:07,192 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0922) Prec@1 91.000 (83.851) Prec@5 100.000 (99.164) +2022-11-14 13:45:07,206 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0923) Prec@1 82.000 (83.824) Prec@5 98.000 (99.147) +2022-11-14 13:45:07,220 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0921) Prec@1 88.000 (83.884) Prec@5 99.000 (99.145) +2022-11-14 13:45:07,234 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1242 (0.0925) Prec@1 78.000 (83.800) Prec@5 97.000 (99.114) +2022-11-14 13:45:07,248 Test: [70/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0928) Prec@1 83.000 (83.789) Prec@5 99.000 (99.113) +2022-11-14 13:45:07,262 Test: [71/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0927) Prec@1 83.000 (83.778) Prec@5 99.000 (99.111) +2022-11-14 13:45:07,276 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0927) Prec@1 84.000 (83.781) Prec@5 100.000 (99.123) +2022-11-14 13:45:07,290 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0923) Prec@1 87.000 (83.824) Prec@5 100.000 (99.135) +2022-11-14 13:45:07,303 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.0927) Prec@1 81.000 (83.787) Prec@5 99.000 (99.133) +2022-11-14 13:45:07,317 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0924) Prec@1 89.000 (83.855) Prec@5 97.000 (99.105) +2022-11-14 13:45:07,331 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0922) Prec@1 89.000 (83.922) Prec@5 97.000 (99.078) +2022-11-14 13:45:07,344 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0923) Prec@1 83.000 (83.910) Prec@5 99.000 (99.077) +2022-11-14 13:45:07,358 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0921) Prec@1 86.000 (83.937) Prec@5 100.000 (99.089) +2022-11-14 13:45:07,374 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0919) Prec@1 86.000 (83.963) Prec@5 100.000 (99.100) +2022-11-14 13:45:07,388 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0918) Prec@1 85.000 (83.975) Prec@5 100.000 (99.111) +2022-11-14 13:45:07,401 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.0920) Prec@1 80.000 (83.927) Prec@5 98.000 (99.098) +2022-11-14 13:45:07,415 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0919) Prec@1 84.000 (83.928) Prec@5 100.000 (99.108) +2022-11-14 13:45:07,428 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0919) Prec@1 84.000 (83.929) Prec@5 99.000 (99.107) +2022-11-14 13:45:07,442 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1202 (0.0922) Prec@1 79.000 (83.871) Prec@5 100.000 (99.118) +2022-11-14 13:45:07,456 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1267 (0.0926) Prec@1 79.000 (83.814) Prec@5 100.000 (99.128) +2022-11-14 13:45:07,469 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0926) Prec@1 83.000 (83.805) Prec@5 100.000 (99.138) +2022-11-14 13:45:07,483 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0926) Prec@1 83.000 (83.795) Prec@5 98.000 (99.125) +2022-11-14 13:45:07,497 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0925) Prec@1 83.000 (83.787) Prec@5 96.000 (99.090) +2022-11-14 13:45:07,513 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0924) Prec@1 85.000 (83.800) Prec@5 98.000 (99.078) +2022-11-14 13:45:07,526 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0923) Prec@1 87.000 (83.835) Prec@5 100.000 (99.088) +2022-11-14 13:45:07,540 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0917) Prec@1 93.000 (83.935) Prec@5 99.000 (99.087) +2022-11-14 13:45:07,553 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0918) Prec@1 84.000 (83.935) Prec@5 99.000 (99.086) +2022-11-14 13:45:07,566 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0918) Prec@1 84.000 (83.936) Prec@5 98.000 (99.074) +2022-11-14 13:45:07,581 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0916) Prec@1 86.000 (83.958) Prec@5 100.000 (99.084) +2022-11-14 13:45:07,594 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0915) Prec@1 86.000 (83.979) Prec@5 100.000 (99.094) +2022-11-14 13:45:07,607 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0913) Prec@1 85.000 (83.990) Prec@5 100.000 (99.103) +2022-11-14 13:45:07,621 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0915) Prec@1 84.000 (83.990) Prec@5 98.000 (99.092) +2022-11-14 13:45:07,635 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.0918) Prec@1 79.000 (83.939) Prec@5 100.000 (99.101) +2022-11-14 13:45:07,649 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0917) Prec@1 84.000 (83.940) Prec@5 99.000 (99.100) +2022-11-14 13:45:07,705 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:45:08,017 Epoch: [89][0/500] Time 0.026 (0.026) Data 0.226 (0.226) Loss 0.0555 (0.0555) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:45:08,254 Epoch: [89][10/500] Time 0.019 (0.021) Data 0.002 (0.022) Loss 0.0655 (0.0605) Prec@1 89.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:45:08,526 Epoch: [89][20/500] Time 0.025 (0.022) Data 0.002 (0.013) Loss 0.1145 (0.0785) Prec@1 77.000 (86.333) Prec@5 96.000 (98.000) +2022-11-14 13:45:08,829 Epoch: [89][30/500] Time 0.034 (0.024) Data 0.002 (0.009) Loss 0.0910 (0.0816) Prec@1 83.000 (85.500) Prec@5 98.000 (98.000) +2022-11-14 13:45:09,134 Epoch: [89][40/500] Time 0.025 (0.025) Data 0.002 (0.007) Loss 0.0567 (0.0766) Prec@1 92.000 (86.800) Prec@5 100.000 (98.400) +2022-11-14 13:45:09,590 Epoch: [89][50/500] Time 0.047 (0.028) Data 0.002 (0.006) Loss 0.0660 (0.0749) Prec@1 90.000 (87.333) Prec@5 99.000 (98.500) +2022-11-14 13:45:10,084 Epoch: [89][60/500] Time 0.042 (0.031) Data 0.002 (0.006) Loss 0.0725 (0.0745) Prec@1 88.000 (87.429) Prec@5 98.000 (98.429) +2022-11-14 13:45:10,621 Epoch: [89][70/500] Time 0.050 (0.033) Data 0.002 (0.005) Loss 0.0566 (0.0723) Prec@1 88.000 (87.500) Prec@5 98.000 (98.375) +2022-11-14 13:45:11,299 Epoch: [89][80/500] Time 0.072 (0.036) Data 0.002 (0.005) Loss 0.0646 (0.0714) Prec@1 88.000 (87.556) Prec@5 100.000 (98.556) +2022-11-14 13:45:11,802 Epoch: [89][90/500] Time 0.042 (0.037) Data 0.003 (0.004) Loss 0.0707 (0.0713) Prec@1 89.000 (87.700) Prec@5 100.000 (98.700) +2022-11-14 13:45:12,326 Epoch: [89][100/500] Time 0.050 (0.038) Data 0.002 (0.004) Loss 0.0538 (0.0697) Prec@1 92.000 (88.091) Prec@5 100.000 (98.818) +2022-11-14 13:45:12,822 Epoch: [89][110/500] Time 0.042 (0.039) Data 0.002 (0.004) Loss 0.0690 (0.0697) Prec@1 89.000 (88.167) Prec@5 98.000 (98.750) +2022-11-14 13:45:13,603 Epoch: [89][120/500] Time 0.078 (0.042) Data 0.002 (0.004) Loss 0.0585 (0.0688) Prec@1 92.000 (88.462) Prec@5 100.000 (98.846) +2022-11-14 13:45:14,082 Epoch: [89][130/500] Time 0.047 (0.042) Data 0.002 (0.004) Loss 0.0724 (0.0691) Prec@1 87.000 (88.357) Prec@5 99.000 (98.857) +2022-11-14 13:45:14,586 Epoch: [89][140/500] Time 0.042 (0.042) Data 0.002 (0.004) Loss 0.0458 (0.0675) Prec@1 91.000 (88.533) Prec@5 100.000 (98.933) +2022-11-14 13:45:15,091 Epoch: [89][150/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0869 (0.0687) Prec@1 86.000 (88.375) Prec@5 99.000 (98.938) +2022-11-14 13:45:15,593 Epoch: [89][160/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0552 (0.0679) Prec@1 90.000 (88.471) Prec@5 100.000 (99.000) +2022-11-14 13:45:16,077 Epoch: [89][170/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0741 (0.0683) Prec@1 88.000 (88.444) Prec@5 100.000 (99.056) +2022-11-14 13:45:16,556 Epoch: [89][180/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.1009 (0.0700) Prec@1 86.000 (88.316) Prec@5 98.000 (99.000) +2022-11-14 13:45:17,036 Epoch: [89][190/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0958 (0.0713) Prec@1 81.000 (87.950) Prec@5 99.000 (99.000) +2022-11-14 13:45:17,540 Epoch: [89][200/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0736 (0.0714) Prec@1 89.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:45:18,089 Epoch: [89][210/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0560 (0.0707) Prec@1 92.000 (88.182) Prec@5 99.000 (99.000) +2022-11-14 13:45:18,807 Epoch: [89][220/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0625 (0.0703) Prec@1 91.000 (88.304) Prec@5 99.000 (99.000) +2022-11-14 13:45:19,355 Epoch: [89][230/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0735 (0.0705) Prec@1 89.000 (88.333) Prec@5 100.000 (99.042) +2022-11-14 13:45:20,102 Epoch: [89][240/500] Time 0.089 (0.045) Data 0.002 (0.003) Loss 0.0692 (0.0704) Prec@1 87.000 (88.280) Prec@5 100.000 (99.080) +2022-11-14 13:45:20,562 Epoch: [89][250/500] Time 0.029 (0.045) Data 0.001 (0.003) Loss 0.0917 (0.0712) Prec@1 83.000 (88.077) Prec@5 99.000 (99.077) +2022-11-14 13:45:20,962 Epoch: [89][260/500] Time 0.038 (0.045) Data 0.002 (0.003) Loss 0.0611 (0.0709) Prec@1 90.000 (88.148) Prec@5 98.000 (99.037) +2022-11-14 13:45:21,390 Epoch: [89][270/500] Time 0.037 (0.044) Data 0.002 (0.003) Loss 0.0415 (0.0698) Prec@1 93.000 (88.321) Prec@5 100.000 (99.071) +2022-11-14 13:45:21,782 Epoch: [89][280/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.1006 (0.0709) Prec@1 82.000 (88.103) Prec@5 99.000 (99.069) +2022-11-14 13:45:22,196 Epoch: [89][290/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0298 (0.0695) Prec@1 96.000 (88.367) Prec@5 100.000 (99.100) +2022-11-14 13:45:22,605 Epoch: [89][300/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0911 (0.0702) Prec@1 84.000 (88.226) Prec@5 100.000 (99.129) +2022-11-14 13:45:23,065 Epoch: [89][310/500] Time 0.034 (0.043) Data 0.002 (0.003) Loss 0.0637 (0.0700) Prec@1 91.000 (88.312) Prec@5 99.000 (99.125) +2022-11-14 13:45:23,461 Epoch: [89][320/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0702 (0.0700) Prec@1 90.000 (88.364) Prec@5 100.000 (99.152) +2022-11-14 13:45:23,881 Epoch: [89][330/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0860 (0.0705) Prec@1 83.000 (88.206) Prec@5 100.000 (99.176) +2022-11-14 13:45:24,389 Epoch: [89][340/500] Time 0.047 (0.043) Data 0.003 (0.003) Loss 0.0784 (0.0707) Prec@1 84.000 (88.086) Prec@5 100.000 (99.200) +2022-11-14 13:45:24,872 Epoch: [89][350/500] Time 0.042 (0.043) Data 0.003 (0.003) Loss 0.0548 (0.0703) Prec@1 91.000 (88.167) Prec@5 100.000 (99.222) +2022-11-14 13:45:25,392 Epoch: [89][360/500] Time 0.045 (0.043) Data 0.003 (0.003) Loss 0.0706 (0.0703) Prec@1 86.000 (88.108) Prec@5 100.000 (99.243) +2022-11-14 13:45:25,892 Epoch: [89][370/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0636 (0.0701) Prec@1 89.000 (88.132) Prec@5 99.000 (99.237) +2022-11-14 13:45:26,286 Epoch: [89][380/500] Time 0.045 (0.043) Data 0.003 (0.003) Loss 0.0516 (0.0696) Prec@1 90.000 (88.179) Prec@5 99.000 (99.231) +2022-11-14 13:45:26,685 Epoch: [89][390/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0969 (0.0703) Prec@1 84.000 (88.075) Prec@5 98.000 (99.200) +2022-11-14 13:45:27,084 Epoch: [89][400/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0989 (0.0710) Prec@1 83.000 (87.951) Prec@5 99.000 (99.195) +2022-11-14 13:45:27,490 Epoch: [89][410/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0921 (0.0715) Prec@1 81.000 (87.786) Prec@5 100.000 (99.214) +2022-11-14 13:45:27,902 Epoch: [89][420/500] Time 0.036 (0.042) Data 0.002 (0.003) Loss 0.0659 (0.0714) Prec@1 90.000 (87.837) Prec@5 100.000 (99.233) +2022-11-14 13:45:28,321 Epoch: [89][430/500] Time 0.035 (0.042) Data 0.002 (0.003) Loss 0.1029 (0.0721) Prec@1 83.000 (87.727) Prec@5 97.000 (99.182) +2022-11-14 13:45:28,732 Epoch: [89][440/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0744 (0.0721) Prec@1 87.000 (87.711) Prec@5 100.000 (99.200) +2022-11-14 13:45:29,144 Epoch: [89][450/500] Time 0.037 (0.042) Data 0.002 (0.002) Loss 0.0624 (0.0719) Prec@1 91.000 (87.783) Prec@5 100.000 (99.217) +2022-11-14 13:45:29,542 Epoch: [89][460/500] Time 0.036 (0.042) Data 0.002 (0.002) Loss 0.0607 (0.0717) Prec@1 89.000 (87.809) Prec@5 99.000 (99.213) +2022-11-14 13:45:29,951 Epoch: [89][470/500] Time 0.038 (0.042) Data 0.002 (0.002) Loss 0.0514 (0.0713) Prec@1 93.000 (87.917) Prec@5 99.000 (99.208) +2022-11-14 13:45:30,360 Epoch: [89][480/500] Time 0.030 (0.042) Data 0.002 (0.002) Loss 0.0642 (0.0711) Prec@1 89.000 (87.939) Prec@5 98.000 (99.184) +2022-11-14 13:45:30,762 Epoch: [89][490/500] Time 0.036 (0.042) Data 0.002 (0.002) Loss 0.0631 (0.0710) Prec@1 89.000 (87.960) Prec@5 99.000 (99.180) +2022-11-14 13:45:31,130 Epoch: [89][499/500] Time 0.039 (0.041) Data 0.001 (0.002) Loss 0.0669 (0.0709) Prec@1 85.000 (87.902) Prec@5 100.000 (99.196) +2022-11-14 13:45:31,418 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0654 (0.0654) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:45:31,428 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0748) Prec@1 87.000 (86.500) Prec@5 100.000 (99.000) +2022-11-14 13:45:31,440 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0781) Prec@1 87.000 (86.667) Prec@5 100.000 (99.333) +2022-11-14 13:45:31,452 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1006 (0.0838) Prec@1 82.000 (85.500) Prec@5 99.000 (99.250) +2022-11-14 13:45:31,462 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0842) Prec@1 84.000 (85.200) Prec@5 100.000 (99.400) +2022-11-14 13:45:31,473 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0432 (0.0774) Prec@1 92.000 (86.333) Prec@5 100.000 (99.500) +2022-11-14 13:45:31,482 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0785) Prec@1 86.000 (86.286) Prec@5 99.000 (99.429) +2022-11-14 13:45:31,491 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.0832) Prec@1 81.000 (85.625) Prec@5 98.000 (99.250) +2022-11-14 13:45:31,498 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0858) Prec@1 81.000 (85.111) Prec@5 98.000 (99.111) +2022-11-14 13:45:31,506 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0846) Prec@1 87.000 (85.300) Prec@5 99.000 (99.100) +2022-11-14 13:45:31,517 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0837) Prec@1 87.000 (85.455) Prec@5 99.000 (99.091) +2022-11-14 13:45:31,529 Test: [11/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0843) Prec@1 84.000 (85.333) Prec@5 100.000 (99.167) +2022-11-14 13:45:31,539 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0847) Prec@1 85.000 (85.308) Prec@5 100.000 (99.231) +2022-11-14 13:45:31,550 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0855) Prec@1 84.000 (85.214) Prec@5 99.000 (99.214) +2022-11-14 13:45:31,560 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0868) Prec@1 81.000 (84.933) Prec@5 100.000 (99.267) +2022-11-14 13:45:31,571 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1204 (0.0889) Prec@1 78.000 (84.500) Prec@5 98.000 (99.188) +2022-11-14 13:45:31,581 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0888) Prec@1 85.000 (84.529) Prec@5 98.000 (99.118) +2022-11-14 13:45:31,590 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1200 (0.0905) Prec@1 81.000 (84.333) Prec@5 100.000 (99.167) +2022-11-14 13:45:31,601 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0918) Prec@1 79.000 (84.053) Prec@5 99.000 (99.158) +2022-11-14 13:45:31,609 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0924) Prec@1 82.000 (83.950) Prec@5 98.000 (99.100) +2022-11-14 13:45:31,619 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1151 (0.0935) Prec@1 80.000 (83.762) Prec@5 99.000 (99.095) +2022-11-14 13:45:31,631 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0937) Prec@1 84.000 (83.773) Prec@5 100.000 (99.136) +2022-11-14 13:45:31,643 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0937) Prec@1 84.000 (83.783) Prec@5 97.000 (99.043) +2022-11-14 13:45:31,655 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0936) Prec@1 85.000 (83.833) Prec@5 99.000 (99.042) +2022-11-14 13:45:31,665 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0937) Prec@1 86.000 (83.920) Prec@5 100.000 (99.080) +2022-11-14 13:45:31,678 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1136 (0.0945) Prec@1 81.000 (83.808) Prec@5 98.000 (99.038) +2022-11-14 13:45:31,688 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0933) Prec@1 89.000 (84.000) Prec@5 100.000 (99.074) +2022-11-14 13:45:31,698 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0928) Prec@1 87.000 (84.107) Prec@5 100.000 (99.107) +2022-11-14 13:45:31,709 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0932) Prec@1 83.000 (84.069) Prec@5 96.000 (99.000) +2022-11-14 13:45:31,720 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0936) Prec@1 80.000 (83.933) Prec@5 97.000 (98.933) +2022-11-14 13:45:31,729 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0938) Prec@1 83.000 (83.903) Prec@5 100.000 (98.968) +2022-11-14 13:45:31,740 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0935) Prec@1 85.000 (83.938) Prec@5 99.000 (98.969) +2022-11-14 13:45:31,750 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0933) Prec@1 85.000 (83.970) Prec@5 99.000 (98.970) +2022-11-14 13:45:31,760 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0940) Prec@1 78.000 (83.794) Prec@5 96.000 (98.882) +2022-11-14 13:45:31,769 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0936) Prec@1 86.000 (83.857) Prec@5 99.000 (98.886) +2022-11-14 13:45:31,780 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0937) Prec@1 83.000 (83.833) Prec@5 99.000 (98.889) +2022-11-14 13:45:31,790 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0940) Prec@1 83.000 (83.811) Prec@5 97.000 (98.838) +2022-11-14 13:45:31,800 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0939) Prec@1 84.000 (83.816) Prec@5 99.000 (98.842) +2022-11-14 13:45:31,811 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0932) Prec@1 91.000 (84.000) Prec@5 98.000 (98.821) +2022-11-14 13:45:31,820 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0930) Prec@1 85.000 (84.025) Prec@5 99.000 (98.825) +2022-11-14 13:45:31,830 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0933) Prec@1 80.000 (83.927) Prec@5 99.000 (98.829) +2022-11-14 13:45:31,839 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0930) Prec@1 86.000 (83.976) Prec@5 99.000 (98.833) +2022-11-14 13:45:31,849 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0927) Prec@1 84.000 (83.977) Prec@5 100.000 (98.860) +2022-11-14 13:45:31,859 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0923) Prec@1 90.000 (84.114) Prec@5 98.000 (98.841) +2022-11-14 13:45:31,869 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0922) Prec@1 88.000 (84.200) Prec@5 99.000 (98.844) +2022-11-14 13:45:31,880 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.0925) Prec@1 78.000 (84.065) Prec@5 99.000 (98.848) +2022-11-14 13:45:31,890 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0924) Prec@1 86.000 (84.106) Prec@5 99.000 (98.851) +2022-11-14 13:45:31,900 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1168 (0.0929) Prec@1 77.000 (83.958) Prec@5 100.000 (98.875) +2022-11-14 13:45:31,910 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0924) Prec@1 87.000 (84.020) Prec@5 100.000 (98.898) +2022-11-14 13:45:31,920 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0926) Prec@1 85.000 (84.040) Prec@5 100.000 (98.920) +2022-11-14 13:45:31,931 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0922) Prec@1 87.000 (84.098) Prec@5 100.000 (98.941) +2022-11-14 13:45:31,942 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0924) Prec@1 83.000 (84.077) Prec@5 97.000 (98.904) +2022-11-14 13:45:31,952 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0920) Prec@1 87.000 (84.132) Prec@5 99.000 (98.906) +2022-11-14 13:45:31,962 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0916) Prec@1 88.000 (84.204) Prec@5 100.000 (98.926) +2022-11-14 13:45:31,974 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0914) Prec@1 88.000 (84.273) Prec@5 99.000 (98.927) +2022-11-14 13:45:31,985 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0917) Prec@1 79.000 (84.179) Prec@5 98.000 (98.911) +2022-11-14 13:45:31,995 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0919) Prec@1 83.000 (84.158) Prec@5 100.000 (98.930) +2022-11-14 13:45:32,005 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0919) Prec@1 85.000 (84.172) Prec@5 98.000 (98.914) +2022-11-14 13:45:32,015 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.0923) Prec@1 79.000 (84.085) Prec@5 99.000 (98.915) +2022-11-14 13:45:32,025 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0924) Prec@1 82.000 (84.050) Prec@5 99.000 (98.917) +2022-11-14 13:45:32,035 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0925) Prec@1 84.000 (84.049) Prec@5 100.000 (98.934) +2022-11-14 13:45:32,046 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0924) Prec@1 84.000 (84.048) Prec@5 98.000 (98.919) +2022-11-14 13:45:32,056 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0922) Prec@1 84.000 (84.048) Prec@5 99.000 (98.921) +2022-11-14 13:45:32,066 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0920) Prec@1 88.000 (84.109) Prec@5 99.000 (98.922) +2022-11-14 13:45:32,076 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0923) Prec@1 80.000 (84.046) Prec@5 99.000 (98.923) +2022-11-14 13:45:32,086 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0923) Prec@1 83.000 (84.030) Prec@5 100.000 (98.939) +2022-11-14 13:45:32,098 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0920) Prec@1 89.000 (84.104) Prec@5 99.000 (98.940) +2022-11-14 13:45:32,108 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0920) Prec@1 85.000 (84.118) Prec@5 98.000 (98.926) +2022-11-14 13:45:32,119 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0918) Prec@1 85.000 (84.130) Prec@5 100.000 (98.942) +2022-11-14 13:45:32,129 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1306 (0.0924) Prec@1 78.000 (84.043) Prec@5 98.000 (98.929) +2022-11-14 13:45:32,139 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0924) Prec@1 83.000 (84.028) Prec@5 99.000 (98.930) +2022-11-14 13:45:32,149 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0921) Prec@1 89.000 (84.097) Prec@5 100.000 (98.944) +2022-11-14 13:45:32,159 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0922) Prec@1 82.000 (84.068) Prec@5 99.000 (98.945) +2022-11-14 13:45:32,168 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0918) Prec@1 89.000 (84.135) Prec@5 100.000 (98.959) +2022-11-14 13:45:32,178 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1224 (0.0922) Prec@1 81.000 (84.093) Prec@5 99.000 (98.960) +2022-11-14 13:45:32,188 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0920) Prec@1 88.000 (84.145) Prec@5 98.000 (98.947) +2022-11-14 13:45:32,199 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0919) Prec@1 87.000 (84.182) Prec@5 100.000 (98.961) +2022-11-14 13:45:32,209 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0919) Prec@1 84.000 (84.179) Prec@5 98.000 (98.949) +2022-11-14 13:45:32,219 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0921) Prec@1 81.000 (84.139) Prec@5 99.000 (98.949) +2022-11-14 13:45:32,230 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0921) Prec@1 86.000 (84.162) Prec@5 98.000 (98.938) +2022-11-14 13:45:32,241 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0922) Prec@1 82.000 (84.136) Prec@5 97.000 (98.914) +2022-11-14 13:45:32,252 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0920) Prec@1 87.000 (84.171) Prec@5 99.000 (98.915) +2022-11-14 13:45:32,262 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1296 (0.0925) Prec@1 76.000 (84.072) Prec@5 100.000 (98.928) +2022-11-14 13:45:32,272 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0924) Prec@1 87.000 (84.107) Prec@5 99.000 (98.929) +2022-11-14 13:45:32,283 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0926) Prec@1 80.000 (84.059) Prec@5 99.000 (98.929) +2022-11-14 13:45:32,293 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.0930) Prec@1 80.000 (84.012) Prec@5 100.000 (98.942) +2022-11-14 13:45:32,303 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0929) Prec@1 86.000 (84.034) Prec@5 99.000 (98.943) +2022-11-14 13:45:32,313 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0928) Prec@1 82.000 (84.011) Prec@5 98.000 (98.932) +2022-11-14 13:45:32,323 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0927) Prec@1 82.000 (83.989) Prec@5 99.000 (98.933) +2022-11-14 13:45:32,332 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0929) Prec@1 85.000 (84.000) Prec@5 99.000 (98.933) +2022-11-14 13:45:32,341 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0928) Prec@1 83.000 (83.989) Prec@5 100.000 (98.945) +2022-11-14 13:45:32,353 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0924) Prec@1 89.000 (84.043) Prec@5 100.000 (98.957) +2022-11-14 13:45:32,363 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0925) Prec@1 84.000 (84.043) Prec@5 100.000 (98.968) +2022-11-14 13:45:32,374 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0925) Prec@1 82.000 (84.021) Prec@5 99.000 (98.968) +2022-11-14 13:45:32,384 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.0928) Prec@1 78.000 (83.958) Prec@5 98.000 (98.958) +2022-11-14 13:45:32,395 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0928) Prec@1 85.000 (83.969) Prec@5 98.000 (98.948) +2022-11-14 13:45:32,406 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0926) Prec@1 90.000 (84.031) Prec@5 97.000 (98.928) +2022-11-14 13:45:32,414 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0928) Prec@1 82.000 (84.010) Prec@5 99.000 (98.929) +2022-11-14 13:45:32,424 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0929) Prec@1 80.000 (83.970) Prec@5 100.000 (98.939) +2022-11-14 13:45:32,434 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0928) Prec@1 87.000 (84.000) Prec@5 100.000 (98.950) +2022-11-14 13:45:32,492 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:45:32,794 Epoch: [90][0/500] Time 0.029 (0.029) Data 0.214 (0.214) Loss 0.0648 (0.0648) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:45:33,012 Epoch: [90][10/500] Time 0.018 (0.020) Data 0.001 (0.021) Loss 0.0858 (0.0753) Prec@1 85.000 (85.500) Prec@5 100.000 (99.500) +2022-11-14 13:45:33,212 Epoch: [90][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0849 (0.0785) Prec@1 85.000 (85.333) Prec@5 99.000 (99.333) +2022-11-14 13:45:33,485 Epoch: [90][30/500] Time 0.032 (0.020) Data 0.001 (0.008) Loss 0.0643 (0.0749) Prec@1 89.000 (86.250) Prec@5 98.000 (99.000) +2022-11-14 13:45:33,907 Epoch: [90][40/500] Time 0.039 (0.025) Data 0.002 (0.007) Loss 0.0802 (0.0760) Prec@1 86.000 (86.200) Prec@5 100.000 (99.200) +2022-11-14 13:45:34,334 Epoch: [90][50/500] Time 0.037 (0.027) Data 0.002 (0.006) Loss 0.0646 (0.0741) Prec@1 89.000 (86.667) Prec@5 98.000 (99.000) +2022-11-14 13:45:34,756 Epoch: [90][60/500] Time 0.036 (0.029) Data 0.002 (0.005) Loss 0.0658 (0.0729) Prec@1 87.000 (86.714) Prec@5 100.000 (99.143) +2022-11-14 13:45:35,194 Epoch: [90][70/500] Time 0.041 (0.030) Data 0.002 (0.005) Loss 0.0584 (0.0711) Prec@1 91.000 (87.250) Prec@5 99.000 (99.125) +2022-11-14 13:45:35,601 Epoch: [90][80/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.0770 (0.0718) Prec@1 83.000 (86.778) Prec@5 99.000 (99.111) +2022-11-14 13:45:36,028 Epoch: [90][90/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.1051 (0.0751) Prec@1 80.000 (86.100) Prec@5 98.000 (99.000) +2022-11-14 13:45:36,455 Epoch: [90][100/500] Time 0.039 (0.032) Data 0.002 (0.004) Loss 0.0997 (0.0773) Prec@1 81.000 (85.636) Prec@5 98.000 (98.909) +2022-11-14 13:45:36,874 Epoch: [90][110/500] Time 0.039 (0.033) Data 0.002 (0.004) Loss 0.0721 (0.0769) Prec@1 90.000 (86.000) Prec@5 99.000 (98.917) +2022-11-14 13:45:37,294 Epoch: [90][120/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.0729 (0.0766) Prec@1 88.000 (86.154) Prec@5 99.000 (98.923) +2022-11-14 13:45:37,716 Epoch: [90][130/500] Time 0.040 (0.034) Data 0.002 (0.004) Loss 0.0725 (0.0763) Prec@1 88.000 (86.286) Prec@5 100.000 (99.000) +2022-11-14 13:45:38,138 Epoch: [90][140/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0909 (0.0773) Prec@1 83.000 (86.067) Prec@5 99.000 (99.000) +2022-11-14 13:45:38,552 Epoch: [90][150/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0671 (0.0766) Prec@1 87.000 (86.125) Prec@5 99.000 (99.000) +2022-11-14 13:45:38,982 Epoch: [90][160/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0573 (0.0755) Prec@1 90.000 (86.353) Prec@5 98.000 (98.941) +2022-11-14 13:45:39,394 Epoch: [90][170/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0816 (0.0758) Prec@1 88.000 (86.444) Prec@5 100.000 (99.000) +2022-11-14 13:45:39,813 Epoch: [90][180/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0934 (0.0768) Prec@1 84.000 (86.316) Prec@5 99.000 (99.000) +2022-11-14 13:45:40,225 Epoch: [90][190/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0603 (0.0759) Prec@1 88.000 (86.400) Prec@5 100.000 (99.050) +2022-11-14 13:45:40,657 Epoch: [90][200/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0537 (0.0749) Prec@1 90.000 (86.571) Prec@5 100.000 (99.095) +2022-11-14 13:45:41,073 Epoch: [90][210/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0622 (0.0743) Prec@1 89.000 (86.682) Prec@5 100.000 (99.136) +2022-11-14 13:45:41,496 Epoch: [90][220/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0733 (0.0743) Prec@1 86.000 (86.652) Prec@5 99.000 (99.130) +2022-11-14 13:45:41,904 Epoch: [90][230/500] Time 0.038 (0.035) Data 0.001 (0.003) Loss 0.0705 (0.0741) Prec@1 89.000 (86.750) Prec@5 100.000 (99.167) +2022-11-14 13:45:42,323 Epoch: [90][240/500] Time 0.039 (0.035) Data 0.001 (0.003) Loss 0.0821 (0.0744) Prec@1 84.000 (86.640) Prec@5 100.000 (99.200) +2022-11-14 13:45:42,743 Epoch: [90][250/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0799 (0.0746) Prec@1 86.000 (86.615) Prec@5 99.000 (99.192) +2022-11-14 13:45:43,171 Epoch: [90][260/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0730 (0.0746) Prec@1 87.000 (86.630) Prec@5 99.000 (99.185) +2022-11-14 13:45:43,598 Epoch: [90][270/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0950 (0.0753) Prec@1 83.000 (86.500) Prec@5 99.000 (99.179) +2022-11-14 13:45:44,020 Epoch: [90][280/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0493 (0.0744) Prec@1 92.000 (86.690) Prec@5 100.000 (99.207) +2022-11-14 13:45:44,440 Epoch: [90][290/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0451 (0.0734) Prec@1 95.000 (86.967) Prec@5 99.000 (99.200) +2022-11-14 13:45:44,871 Epoch: [90][300/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0802 (0.0736) Prec@1 83.000 (86.839) Prec@5 98.000 (99.161) +2022-11-14 13:45:45,297 Epoch: [90][310/500] Time 0.044 (0.036) Data 0.003 (0.003) Loss 0.1124 (0.0749) Prec@1 82.000 (86.688) Prec@5 100.000 (99.188) +2022-11-14 13:45:45,716 Epoch: [90][320/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0935 (0.0754) Prec@1 83.000 (86.576) Prec@5 100.000 (99.212) +2022-11-14 13:45:46,135 Epoch: [90][330/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0607 (0.0750) Prec@1 91.000 (86.706) Prec@5 99.000 (99.206) +2022-11-14 13:45:46,560 Epoch: [90][340/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0766 (0.0750) Prec@1 88.000 (86.743) Prec@5 99.000 (99.200) +2022-11-14 13:45:46,979 Epoch: [90][350/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0984 (0.0757) Prec@1 83.000 (86.639) Prec@5 99.000 (99.194) +2022-11-14 13:45:47,397 Epoch: [90][360/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0568 (0.0752) Prec@1 91.000 (86.757) Prec@5 98.000 (99.162) +2022-11-14 13:45:47,817 Epoch: [90][370/500] Time 0.037 (0.036) Data 0.003 (0.002) Loss 0.1051 (0.0760) Prec@1 83.000 (86.658) Prec@5 100.000 (99.184) +2022-11-14 13:45:48,244 Epoch: [90][380/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.0850 (0.0762) Prec@1 88.000 (86.692) Prec@5 98.000 (99.154) +2022-11-14 13:45:48,676 Epoch: [90][390/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0486 (0.0755) Prec@1 90.000 (86.775) Prec@5 100.000 (99.175) +2022-11-14 13:45:49,096 Epoch: [90][400/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0568 (0.0750) Prec@1 91.000 (86.878) Prec@5 99.000 (99.171) +2022-11-14 13:45:49,514 Epoch: [90][410/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0870 (0.0753) Prec@1 87.000 (86.881) Prec@5 98.000 (99.143) +2022-11-14 13:45:49,933 Epoch: [90][420/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0894 (0.0757) Prec@1 86.000 (86.860) Prec@5 100.000 (99.163) +2022-11-14 13:45:50,369 Epoch: [90][430/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0879 (0.0759) Prec@1 85.000 (86.818) Prec@5 99.000 (99.159) +2022-11-14 13:45:50,775 Epoch: [90][440/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0941 (0.0763) Prec@1 86.000 (86.800) Prec@5 98.000 (99.133) +2022-11-14 13:45:51,196 Epoch: [90][450/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0626 (0.0760) Prec@1 90.000 (86.870) Prec@5 99.000 (99.130) +2022-11-14 13:45:51,741 Epoch: [90][460/500] Time 0.048 (0.037) Data 0.002 (0.002) Loss 0.0668 (0.0758) Prec@1 88.000 (86.894) Prec@5 100.000 (99.149) +2022-11-14 13:45:52,247 Epoch: [90][470/500] Time 0.057 (0.037) Data 0.002 (0.002) Loss 0.0781 (0.0759) Prec@1 87.000 (86.896) Prec@5 100.000 (99.167) +2022-11-14 13:45:52,716 Epoch: [90][480/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.1076 (0.0765) Prec@1 82.000 (86.796) Prec@5 98.000 (99.143) +2022-11-14 13:45:53,199 Epoch: [90][490/500] Time 0.046 (0.037) Data 0.002 (0.002) Loss 0.0999 (0.0770) Prec@1 83.000 (86.720) Prec@5 98.000 (99.120) +2022-11-14 13:45:53,568 Epoch: [90][499/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0439 (0.0764) Prec@1 93.000 (86.843) Prec@5 100.000 (99.137) +2022-11-14 13:45:53,870 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0590 (0.0590) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:45:53,881 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0905 (0.0748) Prec@1 83.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 13:45:53,891 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0805 (0.0767) Prec@1 87.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 13:45:53,904 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0984 (0.0821) Prec@1 86.000 (86.500) Prec@5 99.000 (99.750) +2022-11-14 13:45:53,915 Test: [4/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0839 (0.0825) Prec@1 86.000 (86.400) Prec@5 99.000 (99.600) +2022-11-14 13:45:53,925 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0489 (0.0769) Prec@1 91.000 (87.167) Prec@5 100.000 (99.667) +2022-11-14 13:45:53,934 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0993 (0.0801) Prec@1 85.000 (86.857) Prec@5 97.000 (99.286) +2022-11-14 13:45:53,945 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0826) Prec@1 85.000 (86.625) Prec@5 100.000 (99.375) +2022-11-14 13:45:53,956 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1074 (0.0853) Prec@1 82.000 (86.111) Prec@5 100.000 (99.444) +2022-11-14 13:45:53,968 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0937 (0.0862) Prec@1 82.000 (85.700) Prec@5 99.000 (99.400) +2022-11-14 13:45:53,979 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0837) Prec@1 89.000 (86.000) Prec@5 100.000 (99.455) +2022-11-14 13:45:53,991 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1110 (0.0860) Prec@1 82.000 (85.667) Prec@5 100.000 (99.500) +2022-11-14 13:45:54,006 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0854) Prec@1 87.000 (85.769) Prec@5 99.000 (99.462) +2022-11-14 13:45:54,018 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1106 (0.0872) Prec@1 81.000 (85.429) Prec@5 98.000 (99.357) +2022-11-14 13:45:54,029 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1048 (0.0884) Prec@1 83.000 (85.267) Prec@5 99.000 (99.333) +2022-11-14 13:45:54,039 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0886) Prec@1 84.000 (85.188) Prec@5 100.000 (99.375) +2022-11-14 13:45:54,051 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0878) Prec@1 88.000 (85.353) Prec@5 99.000 (99.353) +2022-11-14 13:45:54,062 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1157 (0.0893) Prec@1 79.000 (85.000) Prec@5 100.000 (99.389) +2022-11-14 13:45:54,073 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1075 (0.0903) Prec@1 82.000 (84.842) Prec@5 99.000 (99.368) +2022-11-14 13:45:54,082 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.0915) Prec@1 81.000 (84.650) Prec@5 98.000 (99.300) +2022-11-14 13:45:54,091 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0918) Prec@1 83.000 (84.571) Prec@5 98.000 (99.238) +2022-11-14 13:45:54,100 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0916) Prec@1 84.000 (84.545) Prec@5 100.000 (99.273) +2022-11-14 13:45:54,109 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0919) Prec@1 82.000 (84.435) Prec@5 98.000 (99.217) +2022-11-14 13:45:54,118 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0916) Prec@1 85.000 (84.458) Prec@5 100.000 (99.250) +2022-11-14 13:45:54,128 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0916) Prec@1 87.000 (84.560) Prec@5 100.000 (99.280) +2022-11-14 13:45:54,136 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1307 (0.0931) Prec@1 80.000 (84.385) Prec@5 96.000 (99.154) +2022-11-14 13:45:54,146 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0923) Prec@1 90.000 (84.593) Prec@5 100.000 (99.185) +2022-11-14 13:45:54,157 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0917) Prec@1 86.000 (84.643) Prec@5 99.000 (99.179) +2022-11-14 13:45:54,166 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0916) Prec@1 82.000 (84.552) Prec@5 98.000 (99.138) +2022-11-14 13:45:54,177 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0915) Prec@1 84.000 (84.533) Prec@5 99.000 (99.133) +2022-11-14 13:45:54,187 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0916) Prec@1 84.000 (84.516) Prec@5 100.000 (99.161) +2022-11-14 13:45:54,199 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0915) Prec@1 86.000 (84.562) Prec@5 99.000 (99.156) +2022-11-14 13:45:54,210 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0913) Prec@1 83.000 (84.515) Prec@5 99.000 (99.152) +2022-11-14 13:45:54,222 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1277 (0.0924) Prec@1 75.000 (84.235) Prec@5 98.000 (99.118) +2022-11-14 13:45:54,234 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0919) Prec@1 89.000 (84.371) Prec@5 99.000 (99.114) +2022-11-14 13:45:54,246 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.0924) Prec@1 81.000 (84.278) Prec@5 99.000 (99.111) +2022-11-14 13:45:54,256 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.0930) Prec@1 79.000 (84.135) Prec@5 96.000 (99.027) +2022-11-14 13:45:54,267 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0928) Prec@1 87.000 (84.211) Prec@5 99.000 (99.026) +2022-11-14 13:45:54,277 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0923) Prec@1 87.000 (84.282) Prec@5 99.000 (99.026) +2022-11-14 13:45:54,288 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0920) Prec@1 84.000 (84.275) Prec@5 99.000 (99.025) +2022-11-14 13:45:54,298 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.0925) Prec@1 83.000 (84.244) Prec@5 99.000 (99.024) +2022-11-14 13:45:54,309 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0923) Prec@1 85.000 (84.262) Prec@5 99.000 (99.024) +2022-11-14 13:45:54,318 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0917) Prec@1 90.000 (84.395) Prec@5 99.000 (99.023) +2022-11-14 13:45:54,329 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0915) Prec@1 88.000 (84.477) Prec@5 99.000 (99.023) +2022-11-14 13:45:54,338 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0915) Prec@1 83.000 (84.444) Prec@5 100.000 (99.044) +2022-11-14 13:45:54,348 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0917) Prec@1 82.000 (84.391) Prec@5 100.000 (99.065) +2022-11-14 13:45:54,357 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0915) Prec@1 85.000 (84.404) Prec@5 99.000 (99.064) +2022-11-14 13:45:54,366 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0915) Prec@1 84.000 (84.396) Prec@5 100.000 (99.083) +2022-11-14 13:45:54,375 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0911) Prec@1 86.000 (84.429) Prec@5 99.000 (99.082) +2022-11-14 13:45:54,384 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0914) Prec@1 84.000 (84.420) Prec@5 99.000 (99.080) +2022-11-14 13:45:54,393 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0912) Prec@1 86.000 (84.451) Prec@5 98.000 (99.059) +2022-11-14 13:45:54,402 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0912) Prec@1 85.000 (84.462) Prec@5 99.000 (99.058) +2022-11-14 13:45:54,412 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0914) Prec@1 82.000 (84.415) Prec@5 99.000 (99.057) +2022-11-14 13:45:54,421 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0914) Prec@1 83.000 (84.389) Prec@5 99.000 (99.056) +2022-11-14 13:45:54,430 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0913) Prec@1 84.000 (84.382) Prec@5 100.000 (99.073) +2022-11-14 13:45:54,440 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0916) Prec@1 83.000 (84.357) Prec@5 97.000 (99.036) +2022-11-14 13:45:54,449 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0917) Prec@1 80.000 (84.281) Prec@5 100.000 (99.053) +2022-11-14 13:45:54,458 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0915) Prec@1 87.000 (84.328) Prec@5 100.000 (99.069) +2022-11-14 13:45:54,469 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0918) Prec@1 82.000 (84.288) Prec@5 100.000 (99.085) +2022-11-14 13:45:54,480 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0920) Prec@1 81.000 (84.233) Prec@5 100.000 (99.100) +2022-11-14 13:45:54,491 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0922) Prec@1 82.000 (84.197) Prec@5 100.000 (99.115) +2022-11-14 13:45:54,502 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0922) Prec@1 85.000 (84.210) Prec@5 98.000 (99.097) +2022-11-14 13:45:54,512 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0921) Prec@1 85.000 (84.222) Prec@5 100.000 (99.111) +2022-11-14 13:45:54,521 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0918) Prec@1 87.000 (84.266) Prec@5 100.000 (99.125) +2022-11-14 13:45:54,531 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.0922) Prec@1 78.000 (84.169) Prec@5 99.000 (99.123) +2022-11-14 13:45:54,540 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0923) Prec@1 83.000 (84.152) Prec@5 100.000 (99.136) +2022-11-14 13:45:54,551 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0919) Prec@1 90.000 (84.239) Prec@5 100.000 (99.149) +2022-11-14 13:45:54,560 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0920) Prec@1 83.000 (84.221) Prec@5 99.000 (99.147) +2022-11-14 13:45:54,570 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0917) Prec@1 87.000 (84.261) Prec@5 100.000 (99.159) +2022-11-14 13:45:54,580 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0918) Prec@1 83.000 (84.243) Prec@5 99.000 (99.157) +2022-11-14 13:45:54,590 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0919) Prec@1 81.000 (84.197) Prec@5 99.000 (99.155) +2022-11-14 13:45:54,600 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0918) Prec@1 85.000 (84.208) Prec@5 100.000 (99.167) +2022-11-14 13:45:54,609 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0918) Prec@1 85.000 (84.219) Prec@5 99.000 (99.164) +2022-11-14 13:45:54,618 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0916) Prec@1 88.000 (84.270) Prec@5 100.000 (99.176) +2022-11-14 13:45:54,628 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0919) Prec@1 76.000 (84.160) Prec@5 99.000 (99.173) +2022-11-14 13:45:54,636 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0918) Prec@1 86.000 (84.184) Prec@5 99.000 (99.171) +2022-11-14 13:45:54,645 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0917) Prec@1 80.000 (84.130) Prec@5 98.000 (99.156) +2022-11-14 13:45:54,655 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0918) Prec@1 84.000 (84.128) Prec@5 99.000 (99.154) +2022-11-14 13:45:54,664 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0918) Prec@1 83.000 (84.114) Prec@5 99.000 (99.152) +2022-11-14 13:45:54,672 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0917) Prec@1 88.000 (84.162) Prec@5 99.000 (99.150) +2022-11-14 13:45:54,682 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0919) Prec@1 81.000 (84.123) Prec@5 97.000 (99.123) +2022-11-14 13:45:54,692 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0918) Prec@1 85.000 (84.134) Prec@5 99.000 (99.122) +2022-11-14 13:45:54,701 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0919) Prec@1 81.000 (84.096) Prec@5 99.000 (99.120) +2022-11-14 13:45:54,711 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0920) Prec@1 81.000 (84.060) Prec@5 99.000 (99.119) +2022-11-14 13:45:54,722 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.0923) Prec@1 78.000 (83.988) Prec@5 99.000 (99.118) +2022-11-14 13:45:54,734 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0923) Prec@1 84.000 (83.988) Prec@5 97.000 (99.093) +2022-11-14 13:45:54,746 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0923) Prec@1 84.000 (83.989) Prec@5 98.000 (99.080) +2022-11-14 13:45:54,759 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0924) Prec@1 81.000 (83.955) Prec@5 99.000 (99.080) +2022-11-14 13:45:54,769 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0925) Prec@1 78.000 (83.888) Prec@5 99.000 (99.079) +2022-11-14 13:45:54,780 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0926) Prec@1 82.000 (83.867) Prec@5 100.000 (99.089) +2022-11-14 13:45:54,791 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0923) Prec@1 88.000 (83.912) Prec@5 100.000 (99.099) +2022-11-14 13:45:54,803 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0921) Prec@1 85.000 (83.924) Prec@5 100.000 (99.109) +2022-11-14 13:45:54,813 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0923) Prec@1 80.000 (83.882) Prec@5 99.000 (99.108) +2022-11-14 13:45:54,823 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0924) Prec@1 85.000 (83.894) Prec@5 98.000 (99.096) +2022-11-14 13:45:54,835 Test: [94/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0923) Prec@1 83.000 (83.884) Prec@5 99.000 (99.095) +2022-11-14 13:45:54,846 Test: [95/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0920) Prec@1 88.000 (83.927) Prec@5 99.000 (99.094) +2022-11-14 13:45:54,857 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0919) Prec@1 85.000 (83.938) Prec@5 99.000 (99.093) +2022-11-14 13:45:54,867 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0921) Prec@1 82.000 (83.918) Prec@5 99.000 (99.092) +2022-11-14 13:45:54,877 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0921) Prec@1 82.000 (83.899) Prec@5 99.000 (99.091) +2022-11-14 13:45:54,887 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0921) Prec@1 84.000 (83.900) Prec@5 99.000 (99.090) +2022-11-14 13:45:54,949 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:45:55,275 Epoch: [91][0/500] Time 0.027 (0.027) Data 0.243 (0.243) Loss 0.0695 (0.0695) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:45:55,482 Epoch: [91][10/500] Time 0.017 (0.019) Data 0.001 (0.023) Loss 0.0846 (0.0770) Prec@1 86.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 13:45:55,676 Epoch: [91][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0948 (0.0830) Prec@1 81.000 (85.000) Prec@5 98.000 (99.000) +2022-11-14 13:45:55,903 Epoch: [91][30/500] Time 0.023 (0.019) Data 0.002 (0.009) Loss 0.0762 (0.0813) Prec@1 88.000 (85.750) Prec@5 98.000 (98.750) +2022-11-14 13:45:56,263 Epoch: [91][40/500] Time 0.035 (0.022) Data 0.002 (0.008) Loss 0.0883 (0.0827) Prec@1 86.000 (85.800) Prec@5 100.000 (99.000) +2022-11-14 13:45:56,682 Epoch: [91][50/500] Time 0.052 (0.025) Data 0.002 (0.006) Loss 0.0647 (0.0797) Prec@1 89.000 (86.333) Prec@5 98.000 (98.833) +2022-11-14 13:45:57,030 Epoch: [91][60/500] Time 0.035 (0.026) Data 0.002 (0.006) Loss 0.0697 (0.0783) Prec@1 89.000 (86.714) Prec@5 100.000 (99.000) +2022-11-14 13:45:57,406 Epoch: [91][70/500] Time 0.035 (0.027) Data 0.002 (0.005) Loss 0.0674 (0.0769) Prec@1 87.000 (86.750) Prec@5 99.000 (99.000) +2022-11-14 13:45:57,779 Epoch: [91][80/500] Time 0.034 (0.028) Data 0.002 (0.005) Loss 0.0888 (0.0782) Prec@1 85.000 (86.556) Prec@5 100.000 (99.111) +2022-11-14 13:45:58,154 Epoch: [91][90/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.0735 (0.0777) Prec@1 85.000 (86.400) Prec@5 99.000 (99.100) +2022-11-14 13:45:58,535 Epoch: [91][100/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0567 (0.0758) Prec@1 89.000 (86.636) Prec@5 99.000 (99.091) +2022-11-14 13:45:58,909 Epoch: [91][110/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0607 (0.0746) Prec@1 87.000 (86.667) Prec@5 100.000 (99.167) +2022-11-14 13:45:59,293 Epoch: [91][120/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0578 (0.0733) Prec@1 92.000 (87.077) Prec@5 99.000 (99.154) +2022-11-14 13:45:59,660 Epoch: [91][130/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.1009 (0.0753) Prec@1 82.000 (86.714) Prec@5 98.000 (99.071) +2022-11-14 13:46:00,038 Epoch: [91][140/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.1292 (0.0789) Prec@1 75.000 (85.933) Prec@5 98.000 (99.000) +2022-11-14 13:46:00,403 Epoch: [91][150/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0953 (0.0799) Prec@1 84.000 (85.812) Prec@5 99.000 (99.000) +2022-11-14 13:46:00,776 Epoch: [91][160/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0522 (0.0783) Prec@1 91.000 (86.118) Prec@5 100.000 (99.059) +2022-11-14 13:46:01,144 Epoch: [91][170/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0841 (0.0786) Prec@1 86.000 (86.111) Prec@5 98.000 (99.000) +2022-11-14 13:46:01,518 Epoch: [91][180/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0683 (0.0780) Prec@1 89.000 (86.263) Prec@5 100.000 (99.053) +2022-11-14 13:46:01,890 Epoch: [91][190/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.1096 (0.0796) Prec@1 80.000 (85.950) Prec@5 98.000 (99.000) +2022-11-14 13:46:02,264 Epoch: [91][200/500] Time 0.034 (0.031) Data 0.001 (0.003) Loss 0.0757 (0.0794) Prec@1 87.000 (86.000) Prec@5 100.000 (99.048) +2022-11-14 13:46:02,664 Epoch: [91][210/500] Time 0.024 (0.031) Data 0.003 (0.003) Loss 0.0862 (0.0797) Prec@1 85.000 (85.955) Prec@5 100.000 (99.091) +2022-11-14 13:46:03,089 Epoch: [91][220/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0794 (0.0797) Prec@1 83.000 (85.826) Prec@5 100.000 (99.130) +2022-11-14 13:46:03,452 Epoch: [91][230/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0706 (0.0793) Prec@1 86.000 (85.833) Prec@5 99.000 (99.125) +2022-11-14 13:46:03,897 Epoch: [91][240/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0549 (0.0784) Prec@1 92.000 (86.080) Prec@5 99.000 (99.120) +2022-11-14 13:46:04,300 Epoch: [91][250/500] Time 0.029 (0.032) Data 0.002 (0.003) Loss 0.0671 (0.0779) Prec@1 89.000 (86.192) Prec@5 97.000 (99.038) +2022-11-14 13:46:04,733 Epoch: [91][260/500] Time 0.030 (0.032) Data 0.002 (0.003) Loss 0.0668 (0.0775) Prec@1 88.000 (86.259) Prec@5 100.000 (99.074) +2022-11-14 13:46:05,141 Epoch: [91][270/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0585 (0.0768) Prec@1 89.000 (86.357) Prec@5 100.000 (99.107) +2022-11-14 13:46:05,509 Epoch: [91][280/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.1011 (0.0777) Prec@1 81.000 (86.172) Prec@5 99.000 (99.103) +2022-11-14 13:46:05,883 Epoch: [91][290/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0883 (0.0780) Prec@1 83.000 (86.067) Prec@5 100.000 (99.133) +2022-11-14 13:46:06,334 Epoch: [91][300/500] Time 0.048 (0.033) Data 0.002 (0.003) Loss 0.0496 (0.0771) Prec@1 92.000 (86.258) Prec@5 98.000 (99.097) +2022-11-14 13:46:06,685 Epoch: [91][310/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0922 (0.0776) Prec@1 86.000 (86.250) Prec@5 100.000 (99.125) +2022-11-14 13:46:07,066 Epoch: [91][320/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.1004 (0.0783) Prec@1 81.000 (86.091) Prec@5 98.000 (99.091) +2022-11-14 13:46:07,504 Epoch: [91][330/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0652 (0.0779) Prec@1 89.000 (86.176) Prec@5 100.000 (99.118) +2022-11-14 13:46:07,873 Epoch: [91][340/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0633 (0.0775) Prec@1 91.000 (86.314) Prec@5 99.000 (99.114) +2022-11-14 13:46:08,244 Epoch: [91][350/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0628 (0.0771) Prec@1 87.000 (86.333) Prec@5 100.000 (99.139) +2022-11-14 13:46:08,630 Epoch: [91][360/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0909 (0.0774) Prec@1 84.000 (86.270) Prec@5 97.000 (99.081) +2022-11-14 13:46:09,001 Epoch: [91][370/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.1132 (0.0784) Prec@1 80.000 (86.105) Prec@5 100.000 (99.105) +2022-11-14 13:46:09,441 Epoch: [91][380/500] Time 0.050 (0.033) Data 0.002 (0.003) Loss 0.0953 (0.0788) Prec@1 83.000 (86.026) Prec@5 99.000 (99.103) +2022-11-14 13:46:09,796 Epoch: [91][390/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0550 (0.0782) Prec@1 90.000 (86.125) Prec@5 100.000 (99.125) +2022-11-14 13:46:10,179 Epoch: [91][400/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0942 (0.0786) Prec@1 83.000 (86.049) Prec@5 99.000 (99.122) +2022-11-14 13:46:10,559 Epoch: [91][410/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0761 (0.0785) Prec@1 86.000 (86.048) Prec@5 100.000 (99.143) +2022-11-14 13:46:10,982 Epoch: [91][420/500] Time 0.052 (0.033) Data 0.002 (0.002) Loss 0.0621 (0.0782) Prec@1 92.000 (86.186) Prec@5 100.000 (99.163) +2022-11-14 13:46:11,358 Epoch: [91][430/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0570 (0.0777) Prec@1 93.000 (86.341) Prec@5 99.000 (99.159) +2022-11-14 13:46:11,741 Epoch: [91][440/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0965 (0.0781) Prec@1 82.000 (86.244) Prec@5 99.000 (99.156) +2022-11-14 13:46:12,115 Epoch: [91][450/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0599 (0.0777) Prec@1 92.000 (86.370) Prec@5 99.000 (99.152) +2022-11-14 13:46:12,486 Epoch: [91][460/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0830 (0.0778) Prec@1 87.000 (86.383) Prec@5 98.000 (99.128) +2022-11-14 13:46:12,864 Epoch: [91][470/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.1014 (0.0783) Prec@1 82.000 (86.292) Prec@5 100.000 (99.146) +2022-11-14 13:46:13,235 Epoch: [91][480/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0329 (0.0774) Prec@1 96.000 (86.490) Prec@5 100.000 (99.163) +2022-11-14 13:46:13,614 Epoch: [91][490/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0682 (0.0772) Prec@1 89.000 (86.540) Prec@5 100.000 (99.180) +2022-11-14 13:46:13,947 Epoch: [91][499/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0707 (0.0771) Prec@1 89.000 (86.588) Prec@5 99.000 (99.176) +2022-11-14 13:46:14,233 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0629 (0.0629) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:46:14,243 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0693) Prec@1 90.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 13:46:14,253 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0729) Prec@1 86.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 13:46:14,265 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0779) Prec@1 84.000 (87.500) Prec@5 99.000 (99.250) +2022-11-14 13:46:14,274 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0785) Prec@1 86.000 (87.200) Prec@5 100.000 (99.400) +2022-11-14 13:46:14,281 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0773) Prec@1 88.000 (87.333) Prec@5 100.000 (99.500) +2022-11-14 13:46:14,289 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0772) Prec@1 87.000 (87.286) Prec@5 100.000 (99.571) +2022-11-14 13:46:14,299 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0785) Prec@1 85.000 (87.000) Prec@5 98.000 (99.375) +2022-11-14 13:46:14,308 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0804) Prec@1 87.000 (87.000) Prec@5 98.000 (99.222) +2022-11-14 13:46:14,317 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0805) Prec@1 86.000 (86.900) Prec@5 99.000 (99.200) +2022-11-14 13:46:14,327 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0796) Prec@1 90.000 (87.182) Prec@5 99.000 (99.182) +2022-11-14 13:46:14,337 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0793) Prec@1 86.000 (87.083) Prec@5 100.000 (99.250) +2022-11-14 13:46:14,349 Test: [12/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0792) Prec@1 88.000 (87.154) Prec@5 99.000 (99.231) +2022-11-14 13:46:14,358 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0803) Prec@1 82.000 (86.786) Prec@5 100.000 (99.286) +2022-11-14 13:46:14,367 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0802) Prec@1 88.000 (86.867) Prec@5 100.000 (99.333) +2022-11-14 13:46:14,376 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1190 (0.0827) Prec@1 76.000 (86.188) Prec@5 100.000 (99.375) +2022-11-14 13:46:14,386 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0823) Prec@1 89.000 (86.353) Prec@5 97.000 (99.235) +2022-11-14 13:46:14,394 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1230 (0.0845) Prec@1 80.000 (86.000) Prec@5 99.000 (99.222) +2022-11-14 13:46:14,404 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0848) Prec@1 84.000 (85.895) Prec@5 98.000 (99.158) +2022-11-14 13:46:14,413 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1182 (0.0865) Prec@1 80.000 (85.600) Prec@5 97.000 (99.050) +2022-11-14 13:46:14,422 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0875) Prec@1 82.000 (85.429) Prec@5 99.000 (99.048) +2022-11-14 13:46:14,432 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0874) Prec@1 84.000 (85.364) Prec@5 99.000 (99.045) +2022-11-14 13:46:14,441 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0887) Prec@1 80.000 (85.130) Prec@5 99.000 (99.043) +2022-11-14 13:46:14,450 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0885) Prec@1 83.000 (85.042) Prec@5 99.000 (99.042) +2022-11-14 13:46:14,459 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0889) Prec@1 85.000 (85.040) Prec@5 100.000 (99.080) +2022-11-14 13:46:14,468 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1240 (0.0903) Prec@1 79.000 (84.808) Prec@5 98.000 (99.038) +2022-11-14 13:46:14,477 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0896) Prec@1 88.000 (84.926) Prec@5 100.000 (99.074) +2022-11-14 13:46:14,485 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0892) Prec@1 86.000 (84.964) Prec@5 99.000 (99.071) +2022-11-14 13:46:14,495 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0893) Prec@1 84.000 (84.931) Prec@5 98.000 (99.034) +2022-11-14 13:46:14,504 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0894) Prec@1 82.000 (84.833) Prec@5 97.000 (98.967) +2022-11-14 13:46:14,512 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0896) Prec@1 84.000 (84.806) Prec@5 99.000 (98.968) +2022-11-14 13:46:14,522 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0892) Prec@1 87.000 (84.875) Prec@5 100.000 (99.000) +2022-11-14 13:46:14,531 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0895) Prec@1 84.000 (84.848) Prec@5 98.000 (98.970) +2022-11-14 13:46:14,540 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.0904) Prec@1 78.000 (84.647) Prec@5 98.000 (98.941) +2022-11-14 13:46:14,550 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0901) Prec@1 88.000 (84.743) Prec@5 99.000 (98.943) +2022-11-14 13:46:14,559 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0901) Prec@1 85.000 (84.750) Prec@5 99.000 (98.944) +2022-11-14 13:46:14,568 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0903) Prec@1 84.000 (84.730) Prec@5 96.000 (98.865) +2022-11-14 13:46:14,576 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0902) Prec@1 87.000 (84.789) Prec@5 99.000 (98.868) +2022-11-14 13:46:14,586 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0898) Prec@1 89.000 (84.897) Prec@5 98.000 (98.846) +2022-11-14 13:46:14,594 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0896) Prec@1 85.000 (84.900) Prec@5 100.000 (98.875) +2022-11-14 13:46:14,603 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0898) Prec@1 83.000 (84.854) Prec@5 98.000 (98.854) +2022-11-14 13:46:14,612 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0898) Prec@1 87.000 (84.905) Prec@5 98.000 (98.833) +2022-11-14 13:46:14,622 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0894) Prec@1 87.000 (84.953) Prec@5 100.000 (98.860) +2022-11-14 13:46:14,631 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0893) Prec@1 86.000 (84.977) Prec@5 98.000 (98.841) +2022-11-14 13:46:14,640 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0896) Prec@1 83.000 (84.933) Prec@5 100.000 (98.867) +2022-11-14 13:46:14,650 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0895) Prec@1 86.000 (84.957) Prec@5 100.000 (98.891) +2022-11-14 13:46:14,659 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0893) Prec@1 87.000 (85.000) Prec@5 100.000 (98.915) +2022-11-14 13:46:14,669 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0894) Prec@1 83.000 (84.958) Prec@5 99.000 (98.917) +2022-11-14 13:46:14,678 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0886) Prec@1 92.000 (85.102) Prec@5 100.000 (98.939) +2022-11-14 13:46:14,687 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1225 (0.0893) Prec@1 78.000 (84.960) Prec@5 100.000 (98.960) +2022-11-14 13:46:14,696 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0892) Prec@1 85.000 (84.961) Prec@5 99.000 (98.961) +2022-11-14 13:46:14,705 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0893) Prec@1 84.000 (84.942) Prec@5 98.000 (98.942) +2022-11-14 13:46:14,714 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0894) Prec@1 82.000 (84.887) Prec@5 99.000 (98.943) +2022-11-14 13:46:14,722 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0894) Prec@1 85.000 (84.889) Prec@5 98.000 (98.926) +2022-11-14 13:46:14,732 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1210 (0.0900) Prec@1 80.000 (84.800) Prec@5 100.000 (98.945) +2022-11-14 13:46:14,740 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0901) Prec@1 83.000 (84.768) Prec@5 99.000 (98.946) +2022-11-14 13:46:14,748 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0901) Prec@1 83.000 (84.737) Prec@5 99.000 (98.947) +2022-11-14 13:46:14,757 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0898) Prec@1 91.000 (84.845) Prec@5 100.000 (98.966) +2022-11-14 13:46:14,765 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0902) Prec@1 82.000 (84.797) Prec@5 100.000 (98.983) +2022-11-14 13:46:14,777 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0900) Prec@1 87.000 (84.833) Prec@5 99.000 (98.983) +2022-11-14 13:46:14,788 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0903) Prec@1 80.000 (84.754) Prec@5 98.000 (98.967) +2022-11-14 13:46:14,801 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0902) Prec@1 88.000 (84.806) Prec@5 99.000 (98.968) +2022-11-14 13:46:14,812 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0900) Prec@1 87.000 (84.841) Prec@5 99.000 (98.968) +2022-11-14 13:46:14,825 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0894) Prec@1 89.000 (84.906) Prec@5 100.000 (98.984) +2022-11-14 13:46:14,840 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1277 (0.0900) Prec@1 81.000 (84.846) Prec@5 98.000 (98.969) +2022-11-14 13:46:14,856 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.0904) Prec@1 80.000 (84.773) Prec@5 98.000 (98.955) +2022-11-14 13:46:14,871 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0899) Prec@1 91.000 (84.866) Prec@5 100.000 (98.970) +2022-11-14 13:46:14,885 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0898) Prec@1 86.000 (84.882) Prec@5 100.000 (98.985) +2022-11-14 13:46:14,899 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0895) Prec@1 89.000 (84.942) Prec@5 99.000 (98.986) +2022-11-14 13:46:14,913 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0899) Prec@1 80.000 (84.871) Prec@5 100.000 (99.000) +2022-11-14 13:46:14,928 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0900) Prec@1 85.000 (84.873) Prec@5 100.000 (99.014) +2022-11-14 13:46:14,943 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0900) Prec@1 85.000 (84.875) Prec@5 98.000 (99.000) +2022-11-14 13:46:14,956 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0896) Prec@1 90.000 (84.945) Prec@5 100.000 (99.014) +2022-11-14 13:46:14,969 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0893) Prec@1 86.000 (84.959) Prec@5 100.000 (99.027) +2022-11-14 13:46:14,982 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0896) Prec@1 79.000 (84.880) Prec@5 98.000 (99.013) +2022-11-14 13:46:14,995 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0894) Prec@1 83.000 (84.855) Prec@5 99.000 (99.013) +2022-11-14 13:46:15,009 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0895) Prec@1 83.000 (84.831) Prec@5 99.000 (99.013) +2022-11-14 13:46:15,021 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0896) Prec@1 83.000 (84.808) Prec@5 97.000 (98.987) +2022-11-14 13:46:15,034 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0895) Prec@1 85.000 (84.810) Prec@5 100.000 (99.000) +2022-11-14 13:46:15,048 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0894) Prec@1 83.000 (84.787) Prec@5 98.000 (98.987) +2022-11-14 13:46:15,061 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0895) Prec@1 84.000 (84.778) Prec@5 98.000 (98.975) +2022-11-14 13:46:15,075 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0896) Prec@1 83.000 (84.756) Prec@5 99.000 (98.976) +2022-11-14 13:46:15,087 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0897) Prec@1 82.000 (84.723) Prec@5 100.000 (98.988) +2022-11-14 13:46:15,100 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0897) Prec@1 83.000 (84.702) Prec@5 99.000 (98.988) +2022-11-14 13:46:15,112 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.0900) Prec@1 79.000 (84.635) Prec@5 98.000 (98.976) +2022-11-14 13:46:15,127 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0901) Prec@1 84.000 (84.628) Prec@5 99.000 (98.977) +2022-11-14 13:46:15,140 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0898) Prec@1 89.000 (84.678) Prec@5 99.000 (98.977) +2022-11-14 13:46:15,152 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0896) Prec@1 90.000 (84.739) Prec@5 99.000 (98.977) +2022-11-14 13:46:15,167 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0895) Prec@1 86.000 (84.753) Prec@5 100.000 (98.989) +2022-11-14 13:46:15,182 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0897) Prec@1 83.000 (84.733) Prec@5 98.000 (98.978) +2022-11-14 13:46:15,197 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0896) Prec@1 86.000 (84.747) Prec@5 100.000 (98.989) +2022-11-14 13:46:15,209 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0891) Prec@1 91.000 (84.815) Prec@5 100.000 (99.000) +2022-11-14 13:46:15,225 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0891) Prec@1 86.000 (84.828) Prec@5 100.000 (99.011) +2022-11-14 13:46:15,237 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0890) Prec@1 86.000 (84.840) Prec@5 97.000 (98.989) +2022-11-14 13:46:15,253 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0891) Prec@1 84.000 (84.832) Prec@5 99.000 (98.989) +2022-11-14 13:46:15,267 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0888) Prec@1 90.000 (84.885) Prec@5 100.000 (99.000) +2022-11-14 13:46:15,281 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0886) Prec@1 89.000 (84.928) Prec@5 100.000 (99.010) +2022-11-14 13:46:15,293 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0886) Prec@1 83.000 (84.908) Prec@5 98.000 (99.000) +2022-11-14 13:46:15,308 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0888) Prec@1 79.000 (84.848) Prec@5 100.000 (99.010) +2022-11-14 13:46:15,320 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0888) Prec@1 84.000 (84.840) Prec@5 100.000 (99.020) +2022-11-14 13:46:15,380 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:46:15,715 Epoch: [92][0/500] Time 0.033 (0.033) Data 0.239 (0.239) Loss 0.0641 (0.0641) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:46:15,983 Epoch: [92][10/500] Time 0.021 (0.025) Data 0.002 (0.024) Loss 0.0744 (0.0693) Prec@1 86.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 13:46:16,419 Epoch: [92][20/500] Time 0.042 (0.031) Data 0.002 (0.013) Loss 0.0749 (0.0712) Prec@1 85.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 13:46:16,878 Epoch: [92][30/500] Time 0.043 (0.034) Data 0.002 (0.010) Loss 0.0649 (0.0696) Prec@1 89.000 (87.250) Prec@5 100.000 (99.750) +2022-11-14 13:46:17,338 Epoch: [92][40/500] Time 0.043 (0.036) Data 0.002 (0.008) Loss 0.0813 (0.0719) Prec@1 86.000 (87.000) Prec@5 100.000 (99.800) +2022-11-14 13:46:17,795 Epoch: [92][50/500] Time 0.044 (0.037) Data 0.002 (0.007) Loss 0.0756 (0.0725) Prec@1 87.000 (87.000) Prec@5 99.000 (99.667) +2022-11-14 13:46:18,250 Epoch: [92][60/500] Time 0.042 (0.038) Data 0.002 (0.006) Loss 0.0631 (0.0712) Prec@1 90.000 (87.429) Prec@5 99.000 (99.571) +2022-11-14 13:46:18,708 Epoch: [92][70/500] Time 0.042 (0.038) Data 0.002 (0.005) Loss 0.0755 (0.0717) Prec@1 85.000 (87.125) Prec@5 98.000 (99.375) +2022-11-14 13:46:19,163 Epoch: [92][80/500] Time 0.043 (0.038) Data 0.002 (0.005) Loss 0.0823 (0.0729) Prec@1 88.000 (87.222) Prec@5 100.000 (99.444) +2022-11-14 13:46:19,622 Epoch: [92][90/500] Time 0.044 (0.039) Data 0.002 (0.004) Loss 0.0656 (0.0722) Prec@1 90.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 13:46:20,078 Epoch: [92][100/500] Time 0.045 (0.039) Data 0.002 (0.004) Loss 0.0724 (0.0722) Prec@1 86.000 (87.364) Prec@5 98.000 (99.364) +2022-11-14 13:46:20,539 Epoch: [92][110/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0854 (0.0733) Prec@1 85.000 (87.167) Prec@5 98.000 (99.250) +2022-11-14 13:46:20,992 Epoch: [92][120/500] Time 0.042 (0.039) Data 0.002 (0.004) Loss 0.0875 (0.0744) Prec@1 86.000 (87.077) Prec@5 100.000 (99.308) +2022-11-14 13:46:21,445 Epoch: [92][130/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0537 (0.0729) Prec@1 92.000 (87.429) Prec@5 100.000 (99.357) +2022-11-14 13:46:21,898 Epoch: [92][140/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0408 (0.0708) Prec@1 94.000 (87.867) Prec@5 99.000 (99.333) +2022-11-14 13:46:22,419 Epoch: [92][150/500] Time 0.068 (0.040) Data 0.002 (0.003) Loss 0.0800 (0.0714) Prec@1 84.000 (87.625) Prec@5 99.000 (99.312) +2022-11-14 13:46:22,878 Epoch: [92][160/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0642 (0.0709) Prec@1 90.000 (87.765) Prec@5 100.000 (99.353) +2022-11-14 13:46:23,361 Epoch: [92][170/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0421 (0.0693) Prec@1 94.000 (88.111) Prec@5 100.000 (99.389) +2022-11-14 13:46:23,905 Epoch: [92][180/500] Time 0.061 (0.040) Data 0.002 (0.003) Loss 0.0519 (0.0684) Prec@1 94.000 (88.421) Prec@5 99.000 (99.368) +2022-11-14 13:46:24,340 Epoch: [92][190/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0929 (0.0696) Prec@1 85.000 (88.250) Prec@5 98.000 (99.300) +2022-11-14 13:46:24,784 Epoch: [92][200/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0967 (0.0709) Prec@1 84.000 (88.048) Prec@5 100.000 (99.333) +2022-11-14 13:46:25,242 Epoch: [92][210/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0984 (0.0722) Prec@1 85.000 (87.909) Prec@5 97.000 (99.227) +2022-11-14 13:46:25,700 Epoch: [92][220/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0679 (0.0720) Prec@1 90.000 (88.000) Prec@5 98.000 (99.174) +2022-11-14 13:46:26,155 Epoch: [92][230/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0628 (0.0716) Prec@1 88.000 (88.000) Prec@5 100.000 (99.208) +2022-11-14 13:46:26,603 Epoch: [92][240/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0629 (0.0713) Prec@1 90.000 (88.080) Prec@5 100.000 (99.240) +2022-11-14 13:46:27,064 Epoch: [92][250/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.1226 (0.0732) Prec@1 78.000 (87.692) Prec@5 99.000 (99.231) +2022-11-14 13:46:27,518 Epoch: [92][260/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0706 (0.0731) Prec@1 88.000 (87.704) Prec@5 100.000 (99.259) +2022-11-14 13:46:27,967 Epoch: [92][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0786 (0.0733) Prec@1 87.000 (87.679) Prec@5 99.000 (99.250) +2022-11-14 13:46:28,420 Epoch: [92][280/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0936 (0.0740) Prec@1 82.000 (87.483) Prec@5 98.000 (99.207) +2022-11-14 13:46:28,889 Epoch: [92][290/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.1010 (0.0749) Prec@1 82.000 (87.300) Prec@5 100.000 (99.233) +2022-11-14 13:46:29,340 Epoch: [92][300/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0802 (0.0751) Prec@1 86.000 (87.258) Prec@5 99.000 (99.226) +2022-11-14 13:46:29,828 Epoch: [92][310/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0573 (0.0745) Prec@1 90.000 (87.344) Prec@5 100.000 (99.250) +2022-11-14 13:46:30,289 Epoch: [92][320/500] Time 0.045 (0.041) Data 0.003 (0.003) Loss 0.0763 (0.0746) Prec@1 88.000 (87.364) Prec@5 99.000 (99.242) +2022-11-14 13:46:30,734 Epoch: [92][330/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0661 (0.0743) Prec@1 88.000 (87.382) Prec@5 100.000 (99.265) +2022-11-14 13:46:31,193 Epoch: [92][340/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0729 (0.0743) Prec@1 87.000 (87.371) Prec@5 99.000 (99.257) +2022-11-14 13:46:31,650 Epoch: [92][350/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0492 (0.0736) Prec@1 93.000 (87.528) Prec@5 100.000 (99.278) +2022-11-14 13:46:32,103 Epoch: [92][360/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0726 (0.0736) Prec@1 83.000 (87.405) Prec@5 99.000 (99.270) +2022-11-14 13:46:32,566 Epoch: [92][370/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0907 (0.0740) Prec@1 85.000 (87.342) Prec@5 100.000 (99.289) +2022-11-14 13:46:33,046 Epoch: [92][380/500] Time 0.056 (0.041) Data 0.002 (0.003) Loss 0.0834 (0.0743) Prec@1 85.000 (87.282) Prec@5 99.000 (99.282) +2022-11-14 13:46:33,482 Epoch: [92][390/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0944 (0.0748) Prec@1 85.000 (87.225) Prec@5 98.000 (99.250) +2022-11-14 13:46:33,932 Epoch: [92][400/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0457 (0.0741) Prec@1 93.000 (87.366) Prec@5 100.000 (99.268) +2022-11-14 13:46:34,384 Epoch: [92][410/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0832 (0.0743) Prec@1 86.000 (87.333) Prec@5 99.000 (99.262) +2022-11-14 13:46:34,829 Epoch: [92][420/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0760 (0.0743) Prec@1 86.000 (87.302) Prec@5 100.000 (99.279) +2022-11-14 13:46:35,279 Epoch: [92][430/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0761 (0.0744) Prec@1 86.000 (87.273) Prec@5 99.000 (99.273) +2022-11-14 13:46:35,728 Epoch: [92][440/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0695 (0.0742) Prec@1 86.000 (87.244) Prec@5 100.000 (99.289) +2022-11-14 13:46:36,179 Epoch: [92][450/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0716 (0.0742) Prec@1 89.000 (87.283) Prec@5 100.000 (99.304) +2022-11-14 13:46:36,623 Epoch: [92][460/500] Time 0.039 (0.040) Data 0.002 (0.002) Loss 0.0674 (0.0740) Prec@1 89.000 (87.319) Prec@5 99.000 (99.298) +2022-11-14 13:46:37,108 Epoch: [92][470/500] Time 0.029 (0.040) Data 0.002 (0.002) Loss 0.0741 (0.0740) Prec@1 85.000 (87.271) Prec@5 99.000 (99.292) +2022-11-14 13:46:37,584 Epoch: [92][480/500] Time 0.063 (0.041) Data 0.002 (0.002) Loss 0.0948 (0.0745) Prec@1 84.000 (87.204) Prec@5 98.000 (99.265) +2022-11-14 13:46:37,919 Epoch: [92][490/500] Time 0.024 (0.040) Data 0.003 (0.002) Loss 0.0506 (0.0740) Prec@1 92.000 (87.300) Prec@5 100.000 (99.280) +2022-11-14 13:46:38,201 Epoch: [92][499/500] Time 0.020 (0.040) Data 0.002 (0.002) Loss 0.0630 (0.0738) Prec@1 90.000 (87.353) Prec@5 100.000 (99.294) +2022-11-14 13:46:38,490 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0686 (0.0686) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:46:38,498 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0839) Prec@1 84.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 13:46:38,505 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0918) Prec@1 83.000 (86.000) Prec@5 99.000 (99.333) +2022-11-14 13:46:38,516 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0926) Prec@1 82.000 (85.000) Prec@5 100.000 (99.500) +2022-11-14 13:46:38,524 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0952) Prec@1 80.000 (84.000) Prec@5 99.000 (99.400) +2022-11-14 13:46:38,531 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0894) Prec@1 91.000 (85.167) Prec@5 100.000 (99.500) +2022-11-14 13:46:38,538 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0902) Prec@1 81.000 (84.571) Prec@5 100.000 (99.571) +2022-11-14 13:46:38,548 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0927) Prec@1 82.000 (84.250) Prec@5 98.000 (99.375) +2022-11-14 13:46:38,556 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0911) Prec@1 88.000 (84.667) Prec@5 99.000 (99.333) +2022-11-14 13:46:38,565 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0898) Prec@1 87.000 (84.900) Prec@5 99.000 (99.300) +2022-11-14 13:46:38,573 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0880) Prec@1 91.000 (85.455) Prec@5 99.000 (99.273) +2022-11-14 13:46:38,582 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0895) Prec@1 82.000 (85.167) Prec@5 99.000 (99.250) +2022-11-14 13:46:38,591 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0901) Prec@1 83.000 (85.000) Prec@5 99.000 (99.231) +2022-11-14 13:46:38,601 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0896) Prec@1 82.000 (84.786) Prec@5 99.000 (99.214) +2022-11-14 13:46:38,609 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0902) Prec@1 84.000 (84.733) Prec@5 100.000 (99.267) +2022-11-14 13:46:38,619 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0902) Prec@1 83.000 (84.625) Prec@5 98.000 (99.188) +2022-11-14 13:46:38,628 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0892) Prec@1 85.000 (84.647) Prec@5 98.000 (99.118) +2022-11-14 13:46:38,637 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0900) Prec@1 83.000 (84.556) Prec@5 100.000 (99.167) +2022-11-14 13:46:38,645 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0910) Prec@1 78.000 (84.211) Prec@5 99.000 (99.158) +2022-11-14 13:46:38,655 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0912) Prec@1 84.000 (84.200) Prec@5 97.000 (99.050) +2022-11-14 13:46:38,663 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0912) Prec@1 83.000 (84.143) Prec@5 100.000 (99.095) +2022-11-14 13:46:38,672 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0914) Prec@1 86.000 (84.227) Prec@5 98.000 (99.045) +2022-11-14 13:46:38,682 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1271 (0.0929) Prec@1 76.000 (83.870) Prec@5 100.000 (99.087) +2022-11-14 13:46:38,691 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0928) Prec@1 82.000 (83.792) Prec@5 100.000 (99.125) +2022-11-14 13:46:38,700 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1155 (0.0937) Prec@1 79.000 (83.600) Prec@5 98.000 (99.080) +2022-11-14 13:46:38,709 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1381 (0.0954) Prec@1 78.000 (83.385) Prec@5 96.000 (98.962) +2022-11-14 13:46:38,718 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0952) Prec@1 84.000 (83.407) Prec@5 100.000 (99.000) +2022-11-14 13:46:38,727 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0954) Prec@1 85.000 (83.464) Prec@5 100.000 (99.036) +2022-11-14 13:46:38,736 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1085 (0.0958) Prec@1 83.000 (83.448) Prec@5 95.000 (98.897) +2022-11-14 13:46:38,747 Test: [29/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1188 (0.0966) Prec@1 79.000 (83.300) Prec@5 97.000 (98.833) +2022-11-14 13:46:38,759 Test: [30/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0962) Prec@1 85.000 (83.355) Prec@5 99.000 (98.839) +2022-11-14 13:46:38,770 Test: [31/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0959) Prec@1 85.000 (83.406) Prec@5 99.000 (98.844) +2022-11-14 13:46:38,781 Test: [32/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0958) Prec@1 84.000 (83.424) Prec@5 97.000 (98.788) +2022-11-14 13:46:38,792 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0957) Prec@1 82.000 (83.382) Prec@5 100.000 (98.824) +2022-11-14 13:46:38,801 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0957) Prec@1 82.000 (83.343) Prec@5 98.000 (98.800) +2022-11-14 13:46:38,811 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0958) Prec@1 83.000 (83.333) Prec@5 100.000 (98.833) +2022-11-14 13:46:38,821 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0956) Prec@1 86.000 (83.405) Prec@5 98.000 (98.811) +2022-11-14 13:46:38,830 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0959) Prec@1 81.000 (83.342) Prec@5 100.000 (98.842) +2022-11-14 13:46:38,839 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0950) Prec@1 90.000 (83.513) Prec@5 100.000 (98.872) +2022-11-14 13:46:38,849 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0948) Prec@1 86.000 (83.575) Prec@5 99.000 (98.875) +2022-11-14 13:46:38,858 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0953) Prec@1 82.000 (83.537) Prec@5 98.000 (98.854) +2022-11-14 13:46:38,867 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0948) Prec@1 90.000 (83.690) Prec@5 100.000 (98.881) +2022-11-14 13:46:38,877 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0942) Prec@1 87.000 (83.767) Prec@5 100.000 (98.907) +2022-11-14 13:46:38,885 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0942) Prec@1 86.000 (83.818) Prec@5 97.000 (98.864) +2022-11-14 13:46:38,894 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0942) Prec@1 82.000 (83.778) Prec@5 100.000 (98.889) +2022-11-14 13:46:38,904 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0946) Prec@1 79.000 (83.674) Prec@5 97.000 (98.848) +2022-11-14 13:46:38,913 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0946) Prec@1 84.000 (83.681) Prec@5 100.000 (98.872) +2022-11-14 13:46:38,922 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0949) Prec@1 82.000 (83.646) Prec@5 98.000 (98.854) +2022-11-14 13:46:38,932 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0942) Prec@1 87.000 (83.714) Prec@5 100.000 (98.878) +2022-11-14 13:46:38,942 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1224 (0.0948) Prec@1 82.000 (83.680) Prec@5 96.000 (98.820) +2022-11-14 13:46:38,952 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0946) Prec@1 88.000 (83.765) Prec@5 100.000 (98.843) +2022-11-14 13:46:38,962 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0947) Prec@1 84.000 (83.769) Prec@5 99.000 (98.846) +2022-11-14 13:46:38,971 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0947) Prec@1 87.000 (83.830) Prec@5 99.000 (98.849) +2022-11-14 13:46:38,981 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0946) Prec@1 84.000 (83.833) Prec@5 100.000 (98.870) +2022-11-14 13:46:38,990 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.0949) Prec@1 79.000 (83.745) Prec@5 100.000 (98.891) +2022-11-14 13:46:38,999 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0946) Prec@1 87.000 (83.804) Prec@5 99.000 (98.893) +2022-11-14 13:46:39,008 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0946) Prec@1 83.000 (83.789) Prec@5 100.000 (98.912) +2022-11-14 13:46:39,017 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0941) Prec@1 88.000 (83.862) Prec@5 100.000 (98.931) +2022-11-14 13:46:39,026 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1258 (0.0947) Prec@1 76.000 (83.729) Prec@5 99.000 (98.932) +2022-11-14 13:46:39,035 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0947) Prec@1 85.000 (83.750) Prec@5 98.000 (98.917) +2022-11-14 13:46:39,045 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0946) Prec@1 84.000 (83.754) Prec@5 100.000 (98.934) +2022-11-14 13:46:39,052 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0945) Prec@1 85.000 (83.774) Prec@5 99.000 (98.935) +2022-11-14 13:46:39,061 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0945) Prec@1 83.000 (83.762) Prec@5 99.000 (98.937) +2022-11-14 13:46:39,071 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0940) Prec@1 89.000 (83.844) Prec@5 100.000 (98.953) +2022-11-14 13:46:39,079 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.0943) Prec@1 82.000 (83.815) Prec@5 97.000 (98.923) +2022-11-14 13:46:39,087 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0943) Prec@1 81.000 (83.773) Prec@5 100.000 (98.939) +2022-11-14 13:46:39,095 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0943) Prec@1 81.000 (83.731) Prec@5 100.000 (98.955) +2022-11-14 13:46:39,104 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0941) Prec@1 85.000 (83.750) Prec@5 99.000 (98.956) +2022-11-14 13:46:39,114 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0939) Prec@1 86.000 (83.783) Prec@5 99.000 (98.957) +2022-11-14 13:46:39,122 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1180 (0.0943) Prec@1 79.000 (83.714) Prec@5 98.000 (98.943) +2022-11-14 13:46:39,130 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0944) Prec@1 84.000 (83.718) Prec@5 99.000 (98.944) +2022-11-14 13:46:39,140 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0943) Prec@1 86.000 (83.750) Prec@5 100.000 (98.958) +2022-11-14 13:46:39,150 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0941) Prec@1 88.000 (83.808) Prec@5 99.000 (98.959) +2022-11-14 13:46:39,159 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0937) Prec@1 90.000 (83.892) Prec@5 100.000 (98.973) +2022-11-14 13:46:39,168 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1297 (0.0942) Prec@1 79.000 (83.827) Prec@5 97.000 (98.947) +2022-11-14 13:46:39,177 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0938) Prec@1 90.000 (83.908) Prec@5 99.000 (98.947) +2022-11-14 13:46:39,184 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0938) Prec@1 84.000 (83.909) Prec@5 99.000 (98.948) +2022-11-14 13:46:39,193 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0938) Prec@1 81.000 (83.872) Prec@5 96.000 (98.910) +2022-11-14 13:46:39,202 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0938) Prec@1 81.000 (83.835) Prec@5 100.000 (98.924) +2022-11-14 13:46:39,212 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0940) Prec@1 83.000 (83.825) Prec@5 98.000 (98.912) +2022-11-14 13:46:39,220 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0940) Prec@1 86.000 (83.852) Prec@5 98.000 (98.901) +2022-11-14 13:46:39,229 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0940) Prec@1 86.000 (83.878) Prec@5 98.000 (98.890) +2022-11-14 13:46:39,238 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0940) Prec@1 85.000 (83.892) Prec@5 100.000 (98.904) +2022-11-14 13:46:39,246 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0939) Prec@1 86.000 (83.917) Prec@5 99.000 (98.905) +2022-11-14 13:46:39,255 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1105 (0.0941) Prec@1 81.000 (83.882) Prec@5 99.000 (98.906) +2022-11-14 13:46:39,266 Test: [85/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1294 (0.0945) Prec@1 75.000 (83.779) Prec@5 99.000 (98.907) +2022-11-14 13:46:39,276 Test: [86/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0944) Prec@1 87.000 (83.816) Prec@5 99.000 (98.908) +2022-11-14 13:46:39,286 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0943) Prec@1 85.000 (83.830) Prec@5 98.000 (98.898) +2022-11-14 13:46:39,295 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0942) Prec@1 85.000 (83.843) Prec@5 99.000 (98.899) +2022-11-14 13:46:39,306 Test: [89/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0938) Prec@1 89.000 (83.900) Prec@5 100.000 (98.911) +2022-11-14 13:46:39,317 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0938) Prec@1 84.000 (83.901) Prec@5 100.000 (98.923) +2022-11-14 13:46:39,325 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0935) Prec@1 89.000 (83.957) Prec@5 99.000 (98.924) +2022-11-14 13:46:39,334 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0935) Prec@1 86.000 (83.978) Prec@5 97.000 (98.903) +2022-11-14 13:46:39,343 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0938) Prec@1 80.000 (83.936) Prec@5 99.000 (98.904) +2022-11-14 13:46:39,351 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0938) Prec@1 83.000 (83.926) Prec@5 100.000 (98.916) +2022-11-14 13:46:39,359 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0937) Prec@1 87.000 (83.958) Prec@5 99.000 (98.917) +2022-11-14 13:46:39,368 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0936) Prec@1 86.000 (83.979) Prec@5 99.000 (98.918) +2022-11-14 13:46:39,376 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.0938) Prec@1 82.000 (83.959) Prec@5 99.000 (98.918) +2022-11-14 13:46:39,384 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0938) Prec@1 86.000 (83.980) Prec@5 99.000 (98.919) +2022-11-14 13:46:39,392 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0938) Prec@1 83.000 (83.970) Prec@5 100.000 (98.930) +2022-11-14 13:46:39,452 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:46:39,752 Epoch: [93][0/500] Time 0.030 (0.030) Data 0.215 (0.215) Loss 0.0716 (0.0716) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 13:46:39,953 Epoch: [93][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.0717 (0.0717) Prec@1 87.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 13:46:40,145 Epoch: [93][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.0436 (0.0623) Prec@1 93.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 13:46:40,340 Epoch: [93][30/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0620 (0.0622) Prec@1 90.000 (89.750) Prec@5 99.000 (99.250) +2022-11-14 13:46:40,573 Epoch: [93][40/500] Time 0.023 (0.018) Data 0.002 (0.007) Loss 0.0422 (0.0582) Prec@1 93.000 (90.400) Prec@5 99.000 (99.200) +2022-11-14 13:46:40,825 Epoch: [93][50/500] Time 0.024 (0.019) Data 0.001 (0.006) Loss 0.0625 (0.0589) Prec@1 87.000 (89.833) Prec@5 100.000 (99.333) +2022-11-14 13:46:41,092 Epoch: [93][60/500] Time 0.021 (0.020) Data 0.002 (0.005) Loss 0.0793 (0.0618) Prec@1 89.000 (89.714) Prec@5 100.000 (99.429) +2022-11-14 13:46:41,354 Epoch: [93][70/500] Time 0.030 (0.020) Data 0.002 (0.005) Loss 0.0685 (0.0627) Prec@1 87.000 (89.375) Prec@5 99.000 (99.375) +2022-11-14 13:46:41,615 Epoch: [93][80/500] Time 0.030 (0.021) Data 0.002 (0.004) Loss 0.0482 (0.0611) Prec@1 91.000 (89.556) Prec@5 100.000 (99.444) +2022-11-14 13:46:42,023 Epoch: [93][90/500] Time 0.027 (0.022) Data 0.002 (0.004) Loss 0.0634 (0.0613) Prec@1 87.000 (89.300) Prec@5 100.000 (99.500) +2022-11-14 13:46:42,387 Epoch: [93][100/500] Time 0.036 (0.023) Data 0.002 (0.004) Loss 0.0631 (0.0615) Prec@1 92.000 (89.545) Prec@5 100.000 (99.545) +2022-11-14 13:46:42,784 Epoch: [93][110/500] Time 0.045 (0.024) Data 0.003 (0.004) Loss 0.0573 (0.0611) Prec@1 89.000 (89.500) Prec@5 100.000 (99.583) +2022-11-14 13:46:43,188 Epoch: [93][120/500] Time 0.044 (0.025) Data 0.002 (0.004) Loss 0.0720 (0.0620) Prec@1 87.000 (89.308) Prec@5 99.000 (99.538) +2022-11-14 13:46:43,617 Epoch: [93][130/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0760 (0.0630) Prec@1 88.000 (89.214) Prec@5 98.000 (99.429) +2022-11-14 13:46:44,049 Epoch: [93][140/500] Time 0.049 (0.027) Data 0.002 (0.003) Loss 0.0628 (0.0629) Prec@1 88.000 (89.133) Prec@5 100.000 (99.467) +2022-11-14 13:46:44,402 Epoch: [93][150/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0899 (0.0646) Prec@1 84.000 (88.812) Prec@5 98.000 (99.375) +2022-11-14 13:46:44,771 Epoch: [93][160/500] Time 0.034 (0.028) Data 0.003 (0.003) Loss 0.0579 (0.0642) Prec@1 91.000 (88.941) Prec@5 99.000 (99.353) +2022-11-14 13:46:45,154 Epoch: [93][170/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0813 (0.0652) Prec@1 85.000 (88.722) Prec@5 100.000 (99.389) +2022-11-14 13:46:45,526 Epoch: [93][180/500] Time 0.035 (0.028) Data 0.002 (0.003) Loss 0.0675 (0.0653) Prec@1 89.000 (88.737) Prec@5 100.000 (99.421) +2022-11-14 13:46:45,898 Epoch: [93][190/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0687 (0.0655) Prec@1 90.000 (88.800) Prec@5 100.000 (99.450) +2022-11-14 13:46:46,271 Epoch: [93][200/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0642 (0.0654) Prec@1 89.000 (88.810) Prec@5 100.000 (99.476) +2022-11-14 13:46:46,651 Epoch: [93][210/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0680 (0.0655) Prec@1 90.000 (88.864) Prec@5 99.000 (99.455) +2022-11-14 13:46:47,022 Epoch: [93][220/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0553 (0.0651) Prec@1 90.000 (88.913) Prec@5 100.000 (99.478) +2022-11-14 13:46:47,391 Epoch: [93][230/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0676 (0.0652) Prec@1 90.000 (88.958) Prec@5 100.000 (99.500) +2022-11-14 13:46:47,760 Epoch: [93][240/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0665 (0.0652) Prec@1 88.000 (88.920) Prec@5 100.000 (99.520) +2022-11-14 13:46:48,126 Epoch: [93][250/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0772 (0.0657) Prec@1 88.000 (88.885) Prec@5 100.000 (99.538) +2022-11-14 13:46:48,509 Epoch: [93][260/500] Time 0.038 (0.030) Data 0.002 (0.003) Loss 0.0870 (0.0665) Prec@1 84.000 (88.704) Prec@5 100.000 (99.556) +2022-11-14 13:46:48,886 Epoch: [93][270/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0508 (0.0659) Prec@1 92.000 (88.821) Prec@5 99.000 (99.536) +2022-11-14 13:46:49,261 Epoch: [93][280/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0758 (0.0663) Prec@1 88.000 (88.793) Prec@5 98.000 (99.483) +2022-11-14 13:46:49,631 Epoch: [93][290/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0585 (0.0660) Prec@1 91.000 (88.867) Prec@5 100.000 (99.500) +2022-11-14 13:46:50,002 Epoch: [93][300/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0742 (0.0663) Prec@1 86.000 (88.774) Prec@5 99.000 (99.484) +2022-11-14 13:46:50,381 Epoch: [93][310/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0791 (0.0667) Prec@1 86.000 (88.688) Prec@5 99.000 (99.469) +2022-11-14 13:46:50,759 Epoch: [93][320/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0843 (0.0672) Prec@1 85.000 (88.576) Prec@5 98.000 (99.424) +2022-11-14 13:46:51,131 Epoch: [93][330/500] Time 0.035 (0.031) Data 0.003 (0.003) Loss 0.0671 (0.0672) Prec@1 89.000 (88.588) Prec@5 99.000 (99.412) +2022-11-14 13:46:51,506 Epoch: [93][340/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0899 (0.0679) Prec@1 83.000 (88.429) Prec@5 99.000 (99.400) +2022-11-14 13:46:51,875 Epoch: [93][350/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0976 (0.0687) Prec@1 81.000 (88.222) Prec@5 98.000 (99.361) +2022-11-14 13:46:52,365 Epoch: [93][360/500] Time 0.046 (0.031) Data 0.002 (0.002) Loss 0.0825 (0.0691) Prec@1 85.000 (88.135) Prec@5 99.000 (99.351) +2022-11-14 13:46:52,814 Epoch: [93][370/500] Time 0.041 (0.031) Data 0.002 (0.002) Loss 0.0650 (0.0689) Prec@1 93.000 (88.263) Prec@5 99.000 (99.342) +2022-11-14 13:46:53,274 Epoch: [93][380/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0429 (0.0683) Prec@1 94.000 (88.410) Prec@5 100.000 (99.359) +2022-11-14 13:46:53,634 Epoch: [93][390/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.0665 (0.0682) Prec@1 89.000 (88.425) Prec@5 99.000 (99.350) +2022-11-14 13:46:54,010 Epoch: [93][400/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.0699 (0.0683) Prec@1 87.000 (88.390) Prec@5 99.000 (99.341) +2022-11-14 13:46:54,447 Epoch: [93][410/500] Time 0.046 (0.032) Data 0.002 (0.002) Loss 0.0772 (0.0685) Prec@1 85.000 (88.310) Prec@5 100.000 (99.357) +2022-11-14 13:46:54,886 Epoch: [93][420/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0504 (0.0681) Prec@1 92.000 (88.395) Prec@5 99.000 (99.349) +2022-11-14 13:46:55,352 Epoch: [93][430/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0776 (0.0683) Prec@1 88.000 (88.386) Prec@5 99.000 (99.341) +2022-11-14 13:46:55,772 Epoch: [93][440/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0806 (0.0686) Prec@1 85.000 (88.311) Prec@5 98.000 (99.311) +2022-11-14 13:46:56,143 Epoch: [93][450/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0816 (0.0688) Prec@1 86.000 (88.261) Prec@5 98.000 (99.283) +2022-11-14 13:46:56,520 Epoch: [93][460/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.1079 (0.0697) Prec@1 78.000 (88.043) Prec@5 99.000 (99.277) +2022-11-14 13:46:56,891 Epoch: [93][470/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0768 (0.0698) Prec@1 87.000 (88.021) Prec@5 98.000 (99.250) +2022-11-14 13:46:57,269 Epoch: [93][480/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0640 (0.0697) Prec@1 89.000 (88.041) Prec@5 100.000 (99.265) +2022-11-14 13:46:57,650 Epoch: [93][490/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.0671 (0.0697) Prec@1 89.000 (88.060) Prec@5 99.000 (99.260) +2022-11-14 13:46:57,983 Epoch: [93][499/500] Time 0.037 (0.032) Data 0.002 (0.002) Loss 0.0759 (0.0698) Prec@1 87.000 (88.039) Prec@5 99.000 (99.255) +2022-11-14 13:46:58,265 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0849 (0.0849) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:46:58,275 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0799) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:46:58,284 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0858) Prec@1 81.000 (83.000) Prec@5 100.000 (99.333) +2022-11-14 13:46:58,297 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0910) Prec@1 84.000 (83.250) Prec@5 100.000 (99.500) +2022-11-14 13:46:58,307 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0873) Prec@1 87.000 (84.000) Prec@5 100.000 (99.600) +2022-11-14 13:46:58,316 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0817) Prec@1 91.000 (85.167) Prec@5 100.000 (99.667) +2022-11-14 13:46:58,325 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0811) Prec@1 85.000 (85.143) Prec@5 100.000 (99.714) +2022-11-14 13:46:58,338 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1161 (0.0854) Prec@1 78.000 (84.250) Prec@5 98.000 (99.500) +2022-11-14 13:46:58,349 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0866) Prec@1 83.000 (84.111) Prec@5 100.000 (99.556) +2022-11-14 13:46:58,358 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0853) Prec@1 88.000 (84.500) Prec@5 99.000 (99.500) +2022-11-14 13:46:58,366 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0847) Prec@1 82.000 (84.273) Prec@5 100.000 (99.545) +2022-11-14 13:46:58,375 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0845) Prec@1 86.000 (84.417) Prec@5 99.000 (99.500) +2022-11-14 13:46:58,385 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0860) Prec@1 80.000 (84.077) Prec@5 99.000 (99.462) +2022-11-14 13:46:58,395 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0859) Prec@1 86.000 (84.214) Prec@5 97.000 (99.286) +2022-11-14 13:46:58,406 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0855) Prec@1 87.000 (84.400) Prec@5 97.000 (99.133) +2022-11-14 13:46:58,416 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.0871) Prec@1 82.000 (84.250) Prec@5 99.000 (99.125) +2022-11-14 13:46:58,426 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0860) Prec@1 90.000 (84.588) Prec@5 99.000 (99.118) +2022-11-14 13:46:58,435 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0861) Prec@1 84.000 (84.556) Prec@5 100.000 (99.167) +2022-11-14 13:46:58,444 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0867) Prec@1 83.000 (84.474) Prec@5 98.000 (99.105) +2022-11-14 13:46:58,456 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1185 (0.0883) Prec@1 80.000 (84.250) Prec@5 98.000 (99.050) +2022-11-14 13:46:58,467 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0888) Prec@1 80.000 (84.048) Prec@5 99.000 (99.048) +2022-11-14 13:46:58,478 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0895) Prec@1 84.000 (84.045) Prec@5 100.000 (99.091) +2022-11-14 13:46:58,489 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0899) Prec@1 85.000 (84.087) Prec@5 99.000 (99.087) +2022-11-14 13:46:58,499 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0893) Prec@1 85.000 (84.125) Prec@5 99.000 (99.083) +2022-11-14 13:46:58,509 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0892) Prec@1 87.000 (84.240) Prec@5 100.000 (99.120) +2022-11-14 13:46:58,517 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.0904) Prec@1 80.000 (84.077) Prec@5 99.000 (99.115) +2022-11-14 13:46:58,528 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0897) Prec@1 85.000 (84.111) Prec@5 100.000 (99.148) +2022-11-14 13:46:58,538 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0895) Prec@1 86.000 (84.179) Prec@5 100.000 (99.179) +2022-11-14 13:46:58,548 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0898) Prec@1 85.000 (84.207) Prec@5 98.000 (99.138) +2022-11-14 13:46:58,559 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0897) Prec@1 85.000 (84.233) Prec@5 99.000 (99.133) +2022-11-14 13:46:58,568 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0898) Prec@1 85.000 (84.258) Prec@5 99.000 (99.129) +2022-11-14 13:46:58,578 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0893) Prec@1 89.000 (84.406) Prec@5 99.000 (99.125) +2022-11-14 13:46:58,587 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0889) Prec@1 88.000 (84.515) Prec@5 98.000 (99.091) +2022-11-14 13:46:58,597 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0896) Prec@1 78.000 (84.324) Prec@5 100.000 (99.118) +2022-11-14 13:46:58,608 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0898) Prec@1 83.000 (84.286) Prec@5 99.000 (99.114) +2022-11-14 13:46:58,617 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0902) Prec@1 84.000 (84.278) Prec@5 99.000 (99.111) +2022-11-14 13:46:58,628 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0902) Prec@1 83.000 (84.243) Prec@5 98.000 (99.081) +2022-11-14 13:46:58,637 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1248 (0.0911) Prec@1 82.000 (84.184) Prec@5 98.000 (99.053) +2022-11-14 13:46:58,648 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0907) Prec@1 88.000 (84.282) Prec@5 100.000 (99.077) +2022-11-14 13:46:58,657 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0903) Prec@1 87.000 (84.350) Prec@5 99.000 (99.075) +2022-11-14 13:46:58,667 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0908) Prec@1 82.000 (84.293) Prec@5 98.000 (99.049) +2022-11-14 13:46:58,677 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0908) Prec@1 85.000 (84.310) Prec@5 99.000 (99.048) +2022-11-14 13:46:58,687 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0899) Prec@1 91.000 (84.465) Prec@5 99.000 (99.047) +2022-11-14 13:46:58,697 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0897) Prec@1 87.000 (84.523) Prec@5 97.000 (99.000) +2022-11-14 13:46:58,707 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0893) Prec@1 87.000 (84.578) Prec@5 99.000 (99.000) +2022-11-14 13:46:58,718 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0894) Prec@1 83.000 (84.543) Prec@5 98.000 (98.978) +2022-11-14 13:46:58,727 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0894) Prec@1 83.000 (84.511) Prec@5 98.000 (98.957) +2022-11-14 13:46:58,738 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0894) Prec@1 84.000 (84.500) Prec@5 100.000 (98.979) +2022-11-14 13:46:58,747 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0887) Prec@1 91.000 (84.633) Prec@5 100.000 (99.000) +2022-11-14 13:46:58,757 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1259 (0.0895) Prec@1 79.000 (84.520) Prec@5 98.000 (98.980) +2022-11-14 13:46:58,768 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0895) Prec@1 83.000 (84.490) Prec@5 100.000 (99.000) +2022-11-14 13:46:58,778 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0897) Prec@1 85.000 (84.500) Prec@5 98.000 (98.981) +2022-11-14 13:46:58,788 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0896) Prec@1 85.000 (84.509) Prec@5 100.000 (99.000) +2022-11-14 13:46:58,797 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0894) Prec@1 89.000 (84.593) Prec@5 100.000 (99.019) +2022-11-14 13:46:58,807 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1121 (0.0898) Prec@1 80.000 (84.509) Prec@5 100.000 (99.036) +2022-11-14 13:46:58,817 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0896) Prec@1 87.000 (84.554) Prec@5 100.000 (99.054) +2022-11-14 13:46:58,828 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0898) Prec@1 83.000 (84.526) Prec@5 99.000 (99.053) +2022-11-14 13:46:58,836 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0899) Prec@1 83.000 (84.500) Prec@5 98.000 (99.034) +2022-11-14 13:46:58,847 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0902) Prec@1 82.000 (84.458) Prec@5 99.000 (99.034) +2022-11-14 13:46:58,858 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.0905) Prec@1 81.000 (84.400) Prec@5 98.000 (99.017) +2022-11-14 13:46:58,867 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0904) Prec@1 85.000 (84.410) Prec@5 100.000 (99.033) +2022-11-14 13:46:58,877 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0903) Prec@1 83.000 (84.387) Prec@5 99.000 (99.032) +2022-11-14 13:46:58,887 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0901) Prec@1 86.000 (84.413) Prec@5 100.000 (99.048) +2022-11-14 13:46:58,898 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0897) Prec@1 89.000 (84.484) Prec@5 99.000 (99.047) +2022-11-14 13:46:58,908 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0897) Prec@1 87.000 (84.523) Prec@5 100.000 (99.062) +2022-11-14 13:46:58,919 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0899) Prec@1 84.000 (84.515) Prec@5 100.000 (99.076) +2022-11-14 13:46:58,928 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0375 (0.0891) Prec@1 93.000 (84.642) Prec@5 100.000 (99.090) +2022-11-14 13:46:58,938 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0894) Prec@1 79.000 (84.559) Prec@5 99.000 (99.088) +2022-11-14 13:46:58,950 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0891) Prec@1 86.000 (84.580) Prec@5 98.000 (99.072) +2022-11-14 13:46:58,962 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0894) Prec@1 80.000 (84.514) Prec@5 98.000 (99.057) +2022-11-14 13:46:58,971 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.0900) Prec@1 78.000 (84.423) Prec@5 97.000 (99.028) +2022-11-14 13:46:58,983 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0899) Prec@1 86.000 (84.444) Prec@5 98.000 (99.014) +2022-11-14 13:46:58,993 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0897) Prec@1 89.000 (84.507) Prec@5 99.000 (99.014) +2022-11-14 13:46:59,002 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0895) Prec@1 86.000 (84.527) Prec@5 100.000 (99.027) +2022-11-14 13:46:59,012 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1251 (0.0900) Prec@1 80.000 (84.467) Prec@5 99.000 (99.027) +2022-11-14 13:46:59,022 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0899) Prec@1 85.000 (84.474) Prec@5 98.000 (99.013) +2022-11-14 13:46:59,034 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0898) Prec@1 85.000 (84.481) Prec@5 99.000 (99.013) +2022-11-14 13:46:59,045 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0898) Prec@1 82.000 (84.449) Prec@5 99.000 (99.013) +2022-11-14 13:46:59,057 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0898) Prec@1 86.000 (84.468) Prec@5 99.000 (99.013) +2022-11-14 13:46:59,069 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0899) Prec@1 84.000 (84.463) Prec@5 98.000 (99.000) +2022-11-14 13:46:59,080 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0899) Prec@1 85.000 (84.469) Prec@5 98.000 (98.988) +2022-11-14 13:46:59,094 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0900) Prec@1 85.000 (84.476) Prec@5 99.000 (98.988) +2022-11-14 13:46:59,105 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0900) Prec@1 85.000 (84.482) Prec@5 100.000 (99.000) +2022-11-14 13:46:59,117 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0899) Prec@1 89.000 (84.536) Prec@5 99.000 (99.000) +2022-11-14 13:46:59,130 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0900) Prec@1 82.000 (84.506) Prec@5 100.000 (99.012) +2022-11-14 13:46:59,140 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0902) Prec@1 84.000 (84.500) Prec@5 99.000 (99.012) +2022-11-14 13:46:59,149 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0901) Prec@1 84.000 (84.494) Prec@5 99.000 (99.011) +2022-11-14 13:46:59,159 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0899) Prec@1 86.000 (84.511) Prec@5 99.000 (99.011) +2022-11-14 13:46:59,170 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0895) Prec@1 89.000 (84.562) Prec@5 100.000 (99.022) +2022-11-14 13:46:59,180 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0894) Prec@1 87.000 (84.589) Prec@5 100.000 (99.033) +2022-11-14 13:46:59,191 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0893) Prec@1 88.000 (84.626) Prec@5 100.000 (99.044) +2022-11-14 13:46:59,202 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0889) Prec@1 92.000 (84.707) Prec@5 99.000 (99.043) +2022-11-14 13:46:59,214 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0890) Prec@1 84.000 (84.699) Prec@5 100.000 (99.054) +2022-11-14 13:46:59,225 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0892) Prec@1 83.000 (84.681) Prec@5 95.000 (99.011) +2022-11-14 13:46:59,236 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0892) Prec@1 83.000 (84.663) Prec@5 99.000 (99.011) +2022-11-14 13:46:59,247 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0891) Prec@1 87.000 (84.688) Prec@5 100.000 (99.021) +2022-11-14 13:46:59,255 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0888) Prec@1 89.000 (84.732) Prec@5 99.000 (99.021) +2022-11-14 13:46:59,266 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0890) Prec@1 81.000 (84.694) Prec@5 99.000 (99.020) +2022-11-14 13:46:59,274 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.0893) Prec@1 78.000 (84.626) Prec@5 100.000 (99.030) +2022-11-14 13:46:59,284 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.0896) Prec@1 82.000 (84.600) Prec@5 97.000 (99.010) +2022-11-14 13:46:59,342 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:46:59,639 Epoch: [94][0/500] Time 0.023 (0.023) Data 0.217 (0.217) Loss 0.0757 (0.0757) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:46:59,854 Epoch: [94][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.0363 (0.0560) Prec@1 94.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 13:47:00,071 Epoch: [94][20/500] Time 0.020 (0.019) Data 0.001 (0.012) Loss 0.0857 (0.0659) Prec@1 87.000 (88.667) Prec@5 98.000 (99.333) +2022-11-14 13:47:00,415 Epoch: [94][30/500] Time 0.043 (0.022) Data 0.002 (0.009) Loss 0.0637 (0.0653) Prec@1 89.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 13:47:00,884 Epoch: [94][40/500] Time 0.042 (0.027) Data 0.002 (0.007) Loss 0.0521 (0.0627) Prec@1 88.000 (88.600) Prec@5 100.000 (99.400) +2022-11-14 13:47:01,347 Epoch: [94][50/500] Time 0.042 (0.030) Data 0.002 (0.006) Loss 0.0772 (0.0651) Prec@1 87.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 13:47:01,815 Epoch: [94][60/500] Time 0.043 (0.032) Data 0.002 (0.005) Loss 0.0736 (0.0663) Prec@1 89.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 13:47:02,283 Epoch: [94][70/500] Time 0.043 (0.033) Data 0.002 (0.005) Loss 0.0729 (0.0671) Prec@1 89.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 13:47:02,752 Epoch: [94][80/500] Time 0.043 (0.034) Data 0.002 (0.005) Loss 0.0747 (0.0680) Prec@1 89.000 (88.556) Prec@5 100.000 (99.444) +2022-11-14 13:47:03,222 Epoch: [94][90/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0659 (0.0678) Prec@1 90.000 (88.700) Prec@5 97.000 (99.200) +2022-11-14 13:47:03,695 Epoch: [94][100/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.0834 (0.0692) Prec@1 87.000 (88.545) Prec@5 100.000 (99.273) +2022-11-14 13:47:04,160 Epoch: [94][110/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0614 (0.0685) Prec@1 89.000 (88.583) Prec@5 100.000 (99.333) +2022-11-14 13:47:04,665 Epoch: [94][120/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0740 (0.0690) Prec@1 86.000 (88.385) Prec@5 100.000 (99.385) +2022-11-14 13:47:05,132 Epoch: [94][130/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0751 (0.0694) Prec@1 87.000 (88.286) Prec@5 100.000 (99.429) +2022-11-14 13:47:05,613 Epoch: [94][140/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0601 (0.0688) Prec@1 90.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 13:47:06,136 Epoch: [94][150/500] Time 0.070 (0.038) Data 0.002 (0.003) Loss 0.0489 (0.0675) Prec@1 92.000 (88.625) Prec@5 100.000 (99.438) +2022-11-14 13:47:06,740 Epoch: [94][160/500] Time 0.065 (0.039) Data 0.002 (0.003) Loss 0.0706 (0.0677) Prec@1 90.000 (88.706) Prec@5 100.000 (99.471) +2022-11-14 13:47:07,223 Epoch: [94][170/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0523 (0.0669) Prec@1 92.000 (88.889) Prec@5 100.000 (99.500) +2022-11-14 13:47:07,691 Epoch: [94][180/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0599 (0.0665) Prec@1 88.000 (88.842) Prec@5 100.000 (99.526) +2022-11-14 13:47:08,154 Epoch: [94][190/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0585 (0.0661) Prec@1 88.000 (88.800) Prec@5 100.000 (99.550) +2022-11-14 13:47:08,668 Epoch: [94][200/500] Time 0.060 (0.040) Data 0.002 (0.003) Loss 0.0713 (0.0663) Prec@1 89.000 (88.810) Prec@5 100.000 (99.571) +2022-11-14 13:47:09,173 Epoch: [94][210/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0857 (0.0672) Prec@1 85.000 (88.636) Prec@5 96.000 (99.409) +2022-11-14 13:47:09,666 Epoch: [94][220/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0743 (0.0675) Prec@1 87.000 (88.565) Prec@5 99.000 (99.391) +2022-11-14 13:47:10,130 Epoch: [94][230/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0577 (0.0671) Prec@1 91.000 (88.667) Prec@5 100.000 (99.417) +2022-11-14 13:47:10,596 Epoch: [94][240/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0630 (0.0670) Prec@1 90.000 (88.720) Prec@5 100.000 (99.440) +2022-11-14 13:47:11,065 Epoch: [94][250/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0902 (0.0678) Prec@1 88.000 (88.692) Prec@5 100.000 (99.462) +2022-11-14 13:47:11,593 Epoch: [94][260/500] Time 0.040 (0.041) Data 0.001 (0.003) Loss 0.0758 (0.0681) Prec@1 86.000 (88.593) Prec@5 97.000 (99.370) +2022-11-14 13:47:12,113 Epoch: [94][270/500] Time 0.038 (0.041) Data 0.001 (0.003) Loss 0.0735 (0.0683) Prec@1 87.000 (88.536) Prec@5 100.000 (99.393) +2022-11-14 13:47:12,643 Epoch: [94][280/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0722 (0.0685) Prec@1 87.000 (88.483) Prec@5 99.000 (99.379) +2022-11-14 13:47:13,099 Epoch: [94][290/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0763 (0.0687) Prec@1 85.000 (88.367) Prec@5 100.000 (99.400) +2022-11-14 13:47:13,560 Epoch: [94][300/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0869 (0.0693) Prec@1 86.000 (88.290) Prec@5 99.000 (99.387) +2022-11-14 13:47:14,020 Epoch: [94][310/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0665 (0.0692) Prec@1 90.000 (88.344) Prec@5 99.000 (99.375) +2022-11-14 13:47:14,531 Epoch: [94][320/500] Time 0.039 (0.041) Data 0.002 (0.003) Loss 0.0723 (0.0693) Prec@1 86.000 (88.273) Prec@5 100.000 (99.394) +2022-11-14 13:47:15,060 Epoch: [94][330/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0708 (0.0694) Prec@1 88.000 (88.265) Prec@5 100.000 (99.412) +2022-11-14 13:47:15,585 Epoch: [94][340/500] Time 0.032 (0.042) Data 0.002 (0.003) Loss 0.0585 (0.0691) Prec@1 89.000 (88.286) Prec@5 100.000 (99.429) +2022-11-14 13:47:16,078 Epoch: [94][350/500] Time 0.044 (0.042) Data 0.001 (0.003) Loss 0.0868 (0.0695) Prec@1 85.000 (88.194) Prec@5 97.000 (99.361) +2022-11-14 13:47:16,555 Epoch: [94][360/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0713 (0.0696) Prec@1 89.000 (88.216) Prec@5 99.000 (99.351) +2022-11-14 13:47:17,063 Epoch: [94][370/500] Time 0.064 (0.042) Data 0.002 (0.003) Loss 0.0734 (0.0697) Prec@1 88.000 (88.211) Prec@5 100.000 (99.368) +2022-11-14 13:47:17,560 Epoch: [94][380/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0506 (0.0692) Prec@1 94.000 (88.359) Prec@5 100.000 (99.385) +2022-11-14 13:47:17,927 Epoch: [94][390/500] Time 0.042 (0.042) Data 0.002 (0.002) Loss 0.0601 (0.0690) Prec@1 92.000 (88.450) Prec@5 99.000 (99.375) +2022-11-14 13:47:18,208 Epoch: [94][400/500] Time 0.027 (0.041) Data 0.002 (0.002) Loss 0.0411 (0.0683) Prec@1 94.000 (88.585) Prec@5 100.000 (99.390) +2022-11-14 13:47:18,529 Epoch: [94][410/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0680 (0.0683) Prec@1 87.000 (88.548) Prec@5 99.000 (99.381) +2022-11-14 13:47:18,801 Epoch: [94][420/500] Time 0.023 (0.041) Data 0.002 (0.002) Loss 0.0705 (0.0683) Prec@1 88.000 (88.535) Prec@5 100.000 (99.395) +2022-11-14 13:47:19,084 Epoch: [94][430/500] Time 0.027 (0.040) Data 0.002 (0.002) Loss 0.0842 (0.0687) Prec@1 87.000 (88.500) Prec@5 98.000 (99.364) +2022-11-14 13:47:19,373 Epoch: [94][440/500] Time 0.024 (0.040) Data 0.002 (0.002) Loss 0.0914 (0.0692) Prec@1 83.000 (88.378) Prec@5 100.000 (99.378) +2022-11-14 13:47:19,652 Epoch: [94][450/500] Time 0.026 (0.040) Data 0.002 (0.002) Loss 0.0927 (0.0697) Prec@1 84.000 (88.283) Prec@5 98.000 (99.348) +2022-11-14 13:47:19,968 Epoch: [94][460/500] Time 0.023 (0.039) Data 0.002 (0.002) Loss 0.0871 (0.0701) Prec@1 85.000 (88.213) Prec@5 99.000 (99.340) +2022-11-14 13:47:20,298 Epoch: [94][470/500] Time 0.037 (0.039) Data 0.003 (0.002) Loss 0.1023 (0.0708) Prec@1 84.000 (88.125) Prec@5 98.000 (99.312) +2022-11-14 13:47:20,561 Epoch: [94][480/500] Time 0.026 (0.039) Data 0.002 (0.002) Loss 0.0833 (0.0710) Prec@1 86.000 (88.082) Prec@5 99.000 (99.306) +2022-11-14 13:47:20,885 Epoch: [94][490/500] Time 0.021 (0.039) Data 0.002 (0.002) Loss 0.0501 (0.0706) Prec@1 92.000 (88.160) Prec@5 100.000 (99.320) +2022-11-14 13:47:21,131 Epoch: [94][499/500] Time 0.027 (0.038) Data 0.001 (0.002) Loss 0.0619 (0.0704) Prec@1 90.000 (88.196) Prec@5 100.000 (99.333) +2022-11-14 13:47:21,429 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0777 (0.0777) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:47:21,441 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0834) Prec@1 86.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 13:47:21,449 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0910) Prec@1 83.000 (86.000) Prec@5 99.000 (99.667) +2022-11-14 13:47:21,461 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0907) Prec@1 86.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 13:47:21,469 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0927) Prec@1 82.000 (85.200) Prec@5 100.000 (99.600) +2022-11-14 13:47:21,477 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0885) Prec@1 88.000 (85.667) Prec@5 100.000 (99.667) +2022-11-14 13:47:21,486 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0871) Prec@1 86.000 (85.714) Prec@5 99.000 (99.571) +2022-11-14 13:47:21,497 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.0896) Prec@1 80.000 (85.000) Prec@5 99.000 (99.500) +2022-11-14 13:47:21,506 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0916) Prec@1 83.000 (84.778) Prec@5 100.000 (99.556) +2022-11-14 13:47:21,517 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0915) Prec@1 85.000 (84.800) Prec@5 99.000 (99.500) +2022-11-14 13:47:21,527 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0906) Prec@1 88.000 (85.091) Prec@5 100.000 (99.545) +2022-11-14 13:47:21,538 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0912) Prec@1 83.000 (84.917) Prec@5 99.000 (99.500) +2022-11-14 13:47:21,547 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0905) Prec@1 84.000 (84.846) Prec@5 100.000 (99.538) +2022-11-14 13:47:21,558 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0911) Prec@1 83.000 (84.714) Prec@5 98.000 (99.429) +2022-11-14 13:47:21,567 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0915) Prec@1 84.000 (84.667) Prec@5 99.000 (99.400) +2022-11-14 13:47:21,577 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1272 (0.0937) Prec@1 78.000 (84.250) Prec@5 100.000 (99.438) +2022-11-14 13:47:21,586 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0916) Prec@1 91.000 (84.647) Prec@5 99.000 (99.412) +2022-11-14 13:47:21,596 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1248 (0.0934) Prec@1 80.000 (84.389) Prec@5 99.000 (99.389) +2022-11-14 13:47:21,605 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0939) Prec@1 82.000 (84.263) Prec@5 96.000 (99.211) +2022-11-14 13:47:21,617 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0941) Prec@1 84.000 (84.250) Prec@5 98.000 (99.150) +2022-11-14 13:47:21,628 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.0951) Prec@1 80.000 (84.048) Prec@5 100.000 (99.190) +2022-11-14 13:47:21,637 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0957) Prec@1 78.000 (83.773) Prec@5 99.000 (99.182) +2022-11-14 13:47:21,645 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0962) Prec@1 81.000 (83.652) Prec@5 98.000 (99.130) +2022-11-14 13:47:21,653 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0959) Prec@1 83.000 (83.625) Prec@5 100.000 (99.167) +2022-11-14 13:47:21,662 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0957) Prec@1 86.000 (83.720) Prec@5 100.000 (99.200) +2022-11-14 13:47:21,672 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.0967) Prec@1 77.000 (83.462) Prec@5 99.000 (99.192) +2022-11-14 13:47:21,685 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0963) Prec@1 85.000 (83.519) Prec@5 99.000 (99.185) +2022-11-14 13:47:21,698 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0964) Prec@1 82.000 (83.464) Prec@5 99.000 (99.179) +2022-11-14 13:47:21,711 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0960) Prec@1 85.000 (83.517) Prec@5 95.000 (99.034) +2022-11-14 13:47:21,725 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0953) Prec@1 88.000 (83.667) Prec@5 98.000 (99.000) +2022-11-14 13:47:21,738 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0950) Prec@1 86.000 (83.742) Prec@5 99.000 (99.000) +2022-11-14 13:47:21,750 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0946) Prec@1 86.000 (83.812) Prec@5 100.000 (99.031) +2022-11-14 13:47:21,764 Test: [32/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0945) Prec@1 84.000 (83.818) Prec@5 98.000 (99.000) +2022-11-14 13:47:21,776 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0950) Prec@1 80.000 (83.706) Prec@5 100.000 (99.029) +2022-11-14 13:47:21,789 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0947) Prec@1 86.000 (83.771) Prec@5 99.000 (99.029) +2022-11-14 13:47:21,802 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0942) Prec@1 87.000 (83.861) Prec@5 100.000 (99.056) +2022-11-14 13:47:21,815 Test: [36/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0945) Prec@1 82.000 (83.811) Prec@5 98.000 (99.027) +2022-11-14 13:47:21,827 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0945) Prec@1 83.000 (83.789) Prec@5 100.000 (99.053) +2022-11-14 13:47:21,836 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0936) Prec@1 91.000 (83.974) Prec@5 99.000 (99.051) +2022-11-14 13:47:21,846 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0937) Prec@1 82.000 (83.925) Prec@5 99.000 (99.050) +2022-11-14 13:47:21,858 Test: [40/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0938) Prec@1 84.000 (83.927) Prec@5 95.000 (98.951) +2022-11-14 13:47:21,870 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1016 (0.0939) Prec@1 83.000 (83.905) Prec@5 99.000 (98.952) +2022-11-14 13:47:21,879 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0927) Prec@1 94.000 (84.140) Prec@5 99.000 (98.953) +2022-11-14 13:47:21,889 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0929) Prec@1 84.000 (84.136) Prec@5 98.000 (98.932) +2022-11-14 13:47:21,902 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0931) Prec@1 83.000 (84.111) Prec@5 98.000 (98.911) +2022-11-14 13:47:21,913 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0931) Prec@1 83.000 (84.087) Prec@5 99.000 (98.913) +2022-11-14 13:47:21,921 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0933) Prec@1 81.000 (84.021) Prec@5 100.000 (98.936) +2022-11-14 13:47:21,933 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0932) Prec@1 85.000 (84.042) Prec@5 99.000 (98.938) +2022-11-14 13:47:21,945 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0926) Prec@1 90.000 (84.163) Prec@5 99.000 (98.939) +2022-11-14 13:47:21,956 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1233 (0.0932) Prec@1 77.000 (84.020) Prec@5 100.000 (98.960) +2022-11-14 13:47:21,964 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0927) Prec@1 89.000 (84.118) Prec@5 99.000 (98.961) +2022-11-14 13:47:21,973 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0930) Prec@1 83.000 (84.096) Prec@5 99.000 (98.962) +2022-11-14 13:47:21,986 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0932) Prec@1 85.000 (84.113) Prec@5 99.000 (98.962) +2022-11-14 13:47:21,997 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0930) Prec@1 85.000 (84.130) Prec@5 100.000 (98.981) +2022-11-14 13:47:22,006 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0932) Prec@1 82.000 (84.091) Prec@5 99.000 (98.982) +2022-11-14 13:47:22,015 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0933) Prec@1 84.000 (84.089) Prec@5 100.000 (99.000) +2022-11-14 13:47:22,024 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.0938) Prec@1 77.000 (83.965) Prec@5 100.000 (99.018) +2022-11-14 13:47:22,035 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0935) Prec@1 87.000 (84.017) Prec@5 99.000 (99.017) +2022-11-14 13:47:22,045 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0937) Prec@1 82.000 (83.983) Prec@5 99.000 (99.017) +2022-11-14 13:47:22,056 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0935) Prec@1 87.000 (84.033) Prec@5 99.000 (99.017) +2022-11-14 13:47:22,067 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0936) Prec@1 83.000 (84.016) Prec@5 99.000 (99.016) +2022-11-14 13:47:22,076 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0937) Prec@1 84.000 (84.016) Prec@5 98.000 (99.000) +2022-11-14 13:47:22,086 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0934) Prec@1 85.000 (84.032) Prec@5 100.000 (99.016) +2022-11-14 13:47:22,095 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0931) Prec@1 87.000 (84.078) Prec@5 100.000 (99.031) +2022-11-14 13:47:22,105 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0934) Prec@1 80.000 (84.015) Prec@5 99.000 (99.031) +2022-11-14 13:47:22,114 Test: [65/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1334 (0.0940) Prec@1 77.000 (83.909) Prec@5 99.000 (99.030) +2022-11-14 13:47:22,124 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0935) Prec@1 87.000 (83.955) Prec@5 100.000 (99.045) +2022-11-14 13:47:22,134 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0934) Prec@1 84.000 (83.956) Prec@5 99.000 (99.044) +2022-11-14 13:47:22,144 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0933) Prec@1 85.000 (83.971) Prec@5 100.000 (99.058) +2022-11-14 13:47:22,154 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0933) Prec@1 84.000 (83.971) Prec@5 99.000 (99.057) +2022-11-14 13:47:22,166 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.0937) Prec@1 80.000 (83.915) Prec@5 99.000 (99.056) +2022-11-14 13:47:22,179 Test: [71/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0940) Prec@1 80.000 (83.861) Prec@5 100.000 (99.069) +2022-11-14 13:47:22,193 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0939) Prec@1 86.000 (83.890) Prec@5 99.000 (99.068) +2022-11-14 13:47:22,207 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0937) Prec@1 85.000 (83.905) Prec@5 100.000 (99.081) +2022-11-14 13:47:22,220 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0938) Prec@1 81.000 (83.867) Prec@5 97.000 (99.053) +2022-11-14 13:47:22,232 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0934) Prec@1 91.000 (83.961) Prec@5 99.000 (99.053) +2022-11-14 13:47:22,246 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0931) Prec@1 88.000 (84.013) Prec@5 100.000 (99.065) +2022-11-14 13:47:22,258 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0932) Prec@1 83.000 (84.000) Prec@5 97.000 (99.038) +2022-11-14 13:47:22,271 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1126 (0.0935) Prec@1 83.000 (83.987) Prec@5 99.000 (99.038) +2022-11-14 13:47:22,284 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0935) Prec@1 81.000 (83.950) Prec@5 99.000 (99.037) +2022-11-14 13:47:22,296 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0935) Prec@1 85.000 (83.963) Prec@5 100.000 (99.049) +2022-11-14 13:47:22,308 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0936) Prec@1 87.000 (84.000) Prec@5 98.000 (99.037) +2022-11-14 13:47:22,319 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0935) Prec@1 84.000 (84.000) Prec@5 99.000 (99.036) +2022-11-14 13:47:22,330 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0933) Prec@1 84.000 (84.000) Prec@5 97.000 (99.012) +2022-11-14 13:47:22,339 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0935) Prec@1 77.000 (83.918) Prec@5 99.000 (99.012) +2022-11-14 13:47:22,350 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1100 (0.0937) Prec@1 83.000 (83.907) Prec@5 98.000 (99.000) +2022-11-14 13:47:22,360 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0936) Prec@1 86.000 (83.931) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,370 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0935) Prec@1 88.000 (83.977) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,380 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0934) Prec@1 85.000 (83.989) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,390 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0934) Prec@1 84.000 (83.989) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,399 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0931) Prec@1 88.000 (84.033) Prec@5 100.000 (99.011) +2022-11-14 13:47:22,408 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0928) Prec@1 88.000 (84.076) Prec@5 100.000 (99.022) +2022-11-14 13:47:22,418 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.0931) Prec@1 79.000 (84.022) Prec@5 98.000 (99.011) +2022-11-14 13:47:22,427 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0930) Prec@1 87.000 (84.053) Prec@5 99.000 (99.011) +2022-11-14 13:47:22,436 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0929) Prec@1 84.000 (84.053) Prec@5 99.000 (99.011) +2022-11-14 13:47:22,447 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0926) Prec@1 90.000 (84.115) Prec@5 98.000 (99.000) +2022-11-14 13:47:22,456 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0922) Prec@1 91.000 (84.186) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,466 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0922) Prec@1 85.000 (84.194) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,475 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0924) Prec@1 80.000 (84.152) Prec@5 99.000 (99.000) +2022-11-14 13:47:22,486 Test: [99/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0924) Prec@1 86.000 (84.170) Prec@5 100.000 (99.010) +2022-11-14 13:47:22,552 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:47:22,863 Epoch: [95][0/500] Time 0.030 (0.030) Data 0.221 (0.221) Loss 0.0859 (0.0859) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:47:23,127 Epoch: [95][10/500] Time 0.028 (0.024) Data 0.002 (0.022) Loss 0.0813 (0.0836) Prec@1 85.000 (86.000) Prec@5 99.000 (98.500) +2022-11-14 13:47:23,342 Epoch: [95][20/500] Time 0.017 (0.021) Data 0.002 (0.012) Loss 0.0648 (0.0773) Prec@1 89.000 (87.000) Prec@5 100.000 (99.000) +2022-11-14 13:47:23,644 Epoch: [95][30/500] Time 0.027 (0.023) Data 0.002 (0.009) Loss 0.0929 (0.0812) Prec@1 86.000 (86.750) Prec@5 98.000 (98.750) +2022-11-14 13:47:24,034 Epoch: [95][40/500] Time 0.045 (0.026) Data 0.002 (0.007) Loss 0.0710 (0.0792) Prec@1 91.000 (87.600) Prec@5 99.000 (98.800) +2022-11-14 13:47:24,359 Epoch: [95][50/500] Time 0.028 (0.026) Data 0.002 (0.006) Loss 0.0704 (0.0777) Prec@1 87.000 (87.500) Prec@5 100.000 (99.000) +2022-11-14 13:47:24,721 Epoch: [95][60/500] Time 0.022 (0.028) Data 0.002 (0.005) Loss 0.0538 (0.0743) Prec@1 91.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:47:25,071 Epoch: [95][70/500] Time 0.039 (0.028) Data 0.002 (0.005) Loss 0.0552 (0.0719) Prec@1 91.000 (88.375) Prec@5 99.000 (99.000) +2022-11-14 13:47:25,401 Epoch: [95][80/500] Time 0.030 (0.028) Data 0.002 (0.005) Loss 0.0478 (0.0692) Prec@1 93.000 (88.889) Prec@5 100.000 (99.111) +2022-11-14 13:47:25,732 Epoch: [95][90/500] Time 0.028 (0.028) Data 0.002 (0.004) Loss 0.0893 (0.0713) Prec@1 85.000 (88.500) Prec@5 97.000 (98.900) +2022-11-14 13:47:26,050 Epoch: [95][100/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.1124 (0.0750) Prec@1 81.000 (87.818) Prec@5 100.000 (99.000) +2022-11-14 13:47:26,392 Epoch: [95][110/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.0766 (0.0751) Prec@1 85.000 (87.583) Prec@5 97.000 (98.833) +2022-11-14 13:47:26,727 Epoch: [95][120/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.0393 (0.0724) Prec@1 95.000 (88.154) Prec@5 100.000 (98.923) +2022-11-14 13:47:27,065 Epoch: [95][130/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0627 (0.0717) Prec@1 88.000 (88.143) Prec@5 99.000 (98.929) +2022-11-14 13:47:27,510 Epoch: [95][140/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.0571 (0.0707) Prec@1 89.000 (88.200) Prec@5 100.000 (99.000) +2022-11-14 13:47:27,829 Epoch: [95][150/500] Time 0.030 (0.029) Data 0.001 (0.003) Loss 0.0686 (0.0706) Prec@1 88.000 (88.188) Prec@5 100.000 (99.062) +2022-11-14 13:47:28,159 Epoch: [95][160/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0816 (0.0712) Prec@1 84.000 (87.941) Prec@5 100.000 (99.118) +2022-11-14 13:47:28,516 Epoch: [95][170/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0866 (0.0721) Prec@1 82.000 (87.611) Prec@5 99.000 (99.111) +2022-11-14 13:47:28,903 Epoch: [95][180/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0847 (0.0727) Prec@1 83.000 (87.368) Prec@5 99.000 (99.105) +2022-11-14 13:47:29,381 Epoch: [95][190/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0948 (0.0738) Prec@1 80.000 (87.000) Prec@5 100.000 (99.150) +2022-11-14 13:47:29,846 Epoch: [95][200/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0601 (0.0732) Prec@1 91.000 (87.190) Prec@5 100.000 (99.190) +2022-11-14 13:47:30,337 Epoch: [95][210/500] Time 0.052 (0.032) Data 0.002 (0.003) Loss 0.0601 (0.0726) Prec@1 90.000 (87.318) Prec@5 100.000 (99.227) +2022-11-14 13:47:30,966 Epoch: [95][220/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0560 (0.0719) Prec@1 93.000 (87.565) Prec@5 99.000 (99.217) +2022-11-14 13:47:31,485 Epoch: [95][230/500] Time 0.048 (0.033) Data 0.002 (0.003) Loss 0.0577 (0.0713) Prec@1 91.000 (87.708) Prec@5 100.000 (99.250) +2022-11-14 13:47:32,084 Epoch: [95][240/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0904 (0.0720) Prec@1 86.000 (87.640) Prec@5 100.000 (99.280) +2022-11-14 13:47:32,669 Epoch: [95][250/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0659 (0.0718) Prec@1 89.000 (87.692) Prec@5 99.000 (99.269) +2022-11-14 13:47:33,259 Epoch: [95][260/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0718 (0.0718) Prec@1 87.000 (87.667) Prec@5 100.000 (99.296) +2022-11-14 13:47:33,771 Epoch: [95][270/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0634 (0.0715) Prec@1 90.000 (87.750) Prec@5 99.000 (99.286) +2022-11-14 13:47:34,325 Epoch: [95][280/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0537 (0.0709) Prec@1 88.000 (87.759) Prec@5 100.000 (99.310) +2022-11-14 13:47:34,971 Epoch: [95][290/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0649 (0.0707) Prec@1 91.000 (87.867) Prec@5 100.000 (99.333) +2022-11-14 13:47:35,751 Epoch: [95][300/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0656 (0.0705) Prec@1 86.000 (87.806) Prec@5 100.000 (99.355) +2022-11-14 13:47:36,473 Epoch: [95][310/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0723 (0.0706) Prec@1 89.000 (87.844) Prec@5 100.000 (99.375) +2022-11-14 13:47:37,048 Epoch: [95][320/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0608 (0.0703) Prec@1 90.000 (87.909) Prec@5 100.000 (99.394) +2022-11-14 13:47:37,628 Epoch: [95][330/500] Time 0.119 (0.040) Data 0.002 (0.003) Loss 0.0783 (0.0705) Prec@1 84.000 (87.794) Prec@5 100.000 (99.412) +2022-11-14 13:47:38,204 Epoch: [95][340/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0839 (0.0709) Prec@1 84.000 (87.686) Prec@5 100.000 (99.429) +2022-11-14 13:47:38,763 Epoch: [95][350/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0807 (0.0712) Prec@1 86.000 (87.639) Prec@5 99.000 (99.417) +2022-11-14 13:47:39,320 Epoch: [95][360/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0878 (0.0716) Prec@1 85.000 (87.568) Prec@5 98.000 (99.378) +2022-11-14 13:47:39,752 Epoch: [95][370/500] Time 0.034 (0.041) Data 0.002 (0.002) Loss 0.0788 (0.0718) Prec@1 87.000 (87.553) Prec@5 99.000 (99.368) +2022-11-14 13:47:40,243 Epoch: [95][380/500] Time 0.050 (0.041) Data 0.002 (0.002) Loss 0.0586 (0.0715) Prec@1 89.000 (87.590) Prec@5 100.000 (99.385) +2022-11-14 13:47:40,632 Epoch: [95][390/500] Time 0.047 (0.041) Data 0.002 (0.002) Loss 0.0725 (0.0715) Prec@1 87.000 (87.575) Prec@5 100.000 (99.400) +2022-11-14 13:47:41,041 Epoch: [95][400/500] Time 0.035 (0.041) Data 0.002 (0.002) Loss 0.0598 (0.0712) Prec@1 90.000 (87.634) Prec@5 100.000 (99.415) +2022-11-14 13:47:41,453 Epoch: [95][410/500] Time 0.033 (0.040) Data 0.002 (0.002) Loss 0.0744 (0.0713) Prec@1 87.000 (87.619) Prec@5 98.000 (99.381) +2022-11-14 13:47:42,019 Epoch: [95][420/500] Time 0.049 (0.041) Data 0.002 (0.002) Loss 0.0690 (0.0712) Prec@1 89.000 (87.651) Prec@5 100.000 (99.395) +2022-11-14 13:47:42,439 Epoch: [95][430/500] Time 0.032 (0.041) Data 0.002 (0.002) Loss 0.0958 (0.0718) Prec@1 81.000 (87.500) Prec@5 98.000 (99.364) +2022-11-14 13:47:42,837 Epoch: [95][440/500] Time 0.037 (0.041) Data 0.002 (0.002) Loss 0.0574 (0.0715) Prec@1 93.000 (87.622) Prec@5 99.000 (99.356) +2022-11-14 13:47:43,236 Epoch: [95][450/500] Time 0.038 (0.040) Data 0.002 (0.002) Loss 0.0721 (0.0715) Prec@1 88.000 (87.630) Prec@5 99.000 (99.348) +2022-11-14 13:47:43,757 Epoch: [95][460/500] Time 0.055 (0.041) Data 0.002 (0.002) Loss 0.0617 (0.0713) Prec@1 90.000 (87.681) Prec@5 100.000 (99.362) +2022-11-14 13:47:44,178 Epoch: [95][470/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0665 (0.0712) Prec@1 90.000 (87.729) Prec@5 100.000 (99.375) +2022-11-14 13:47:44,632 Epoch: [95][480/500] Time 0.085 (0.040) Data 0.002 (0.002) Loss 0.0772 (0.0713) Prec@1 84.000 (87.653) Prec@5 99.000 (99.367) +2022-11-14 13:47:45,040 Epoch: [95][490/500] Time 0.038 (0.040) Data 0.002 (0.002) Loss 0.0687 (0.0713) Prec@1 87.000 (87.640) Prec@5 100.000 (99.380) +2022-11-14 13:47:45,414 Epoch: [95][499/500] Time 0.038 (0.040) Data 0.002 (0.002) Loss 0.0582 (0.0710) Prec@1 90.000 (87.686) Prec@5 99.000 (99.373) +2022-11-14 13:47:45,713 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0821 (0.0821) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:47:45,724 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0906 (0.0864) Prec@1 83.000 (83.500) Prec@5 99.000 (99.000) +2022-11-14 13:47:45,734 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0749 (0.0826) Prec@1 85.000 (84.000) Prec@5 100.000 (99.333) +2022-11-14 13:47:45,744 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1045 (0.0881) Prec@1 81.000 (83.250) Prec@5 99.000 (99.250) +2022-11-14 13:47:45,755 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.0900) Prec@1 81.000 (82.800) Prec@5 100.000 (99.400) +2022-11-14 13:47:45,763 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0604 (0.0851) Prec@1 87.000 (83.500) Prec@5 100.000 (99.500) +2022-11-14 13:47:45,772 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0805) Prec@1 93.000 (84.857) Prec@5 100.000 (99.571) +2022-11-14 13:47:45,781 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0828) Prec@1 79.000 (84.125) Prec@5 98.000 (99.375) +2022-11-14 13:47:45,791 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0826) Prec@1 89.000 (84.667) Prec@5 99.000 (99.333) +2022-11-14 13:47:45,800 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0805) Prec@1 90.000 (85.200) Prec@5 99.000 (99.300) +2022-11-14 13:47:45,809 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0806) Prec@1 86.000 (85.273) Prec@5 100.000 (99.364) +2022-11-14 13:47:45,820 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0828) Prec@1 80.000 (84.833) Prec@5 97.000 (99.167) +2022-11-14 13:47:45,829 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0836) Prec@1 84.000 (84.769) Prec@5 100.000 (99.231) +2022-11-14 13:47:45,837 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0836) Prec@1 84.000 (84.714) Prec@5 99.000 (99.214) +2022-11-14 13:47:45,847 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0826) Prec@1 88.000 (84.933) Prec@5 99.000 (99.200) +2022-11-14 13:47:45,856 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0834) Prec@1 84.000 (84.875) Prec@5 99.000 (99.188) +2022-11-14 13:47:45,867 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0822) Prec@1 89.000 (85.118) Prec@5 99.000 (99.176) +2022-11-14 13:47:45,879 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0822) Prec@1 87.000 (85.222) Prec@5 100.000 (99.222) +2022-11-14 13:47:45,890 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0831) Prec@1 85.000 (85.211) Prec@5 99.000 (99.211) +2022-11-14 13:47:45,899 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0837) Prec@1 83.000 (85.100) Prec@5 100.000 (99.250) +2022-11-14 13:47:45,909 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.0853) Prec@1 82.000 (84.952) Prec@5 97.000 (99.143) +2022-11-14 13:47:45,918 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1172 (0.0868) Prec@1 80.000 (84.727) Prec@5 98.000 (99.091) +2022-11-14 13:47:45,931 Test: [22/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0870) Prec@1 84.000 (84.696) Prec@5 99.000 (99.087) +2022-11-14 13:47:45,942 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0867) Prec@1 87.000 (84.792) Prec@5 100.000 (99.125) +2022-11-14 13:47:45,952 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0871) Prec@1 86.000 (84.840) Prec@5 99.000 (99.120) +2022-11-14 13:47:45,961 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.0882) Prec@1 82.000 (84.731) Prec@5 96.000 (99.000) +2022-11-14 13:47:45,970 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0875) Prec@1 86.000 (84.778) Prec@5 100.000 (99.037) +2022-11-14 13:47:45,978 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0871) Prec@1 88.000 (84.893) Prec@5 100.000 (99.071) +2022-11-14 13:47:45,987 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0866) Prec@1 89.000 (85.034) Prec@5 99.000 (99.069) +2022-11-14 13:47:45,999 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0866) Prec@1 84.000 (85.000) Prec@5 100.000 (99.100) +2022-11-14 13:47:46,012 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0870) Prec@1 81.000 (84.871) Prec@5 100.000 (99.129) +2022-11-14 13:47:46,023 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0875) Prec@1 84.000 (84.844) Prec@5 99.000 (99.125) +2022-11-14 13:47:46,036 Test: [32/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0877) Prec@1 84.000 (84.818) Prec@5 98.000 (99.091) +2022-11-14 13:47:46,048 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0874) Prec@1 83.000 (84.765) Prec@5 100.000 (99.118) +2022-11-14 13:47:46,061 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0873) Prec@1 86.000 (84.800) Prec@5 98.000 (99.086) +2022-11-14 13:47:46,073 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0872) Prec@1 87.000 (84.861) Prec@5 99.000 (99.083) +2022-11-14 13:47:46,085 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0872) Prec@1 82.000 (84.784) Prec@5 98.000 (99.054) +2022-11-14 13:47:46,097 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0876) Prec@1 84.000 (84.763) Prec@5 99.000 (99.053) +2022-11-14 13:47:46,109 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0871) Prec@1 88.000 (84.846) Prec@5 98.000 (99.026) +2022-11-14 13:47:46,121 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0867) Prec@1 87.000 (84.900) Prec@5 99.000 (99.025) +2022-11-14 13:47:46,132 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0871) Prec@1 82.000 (84.829) Prec@5 96.000 (98.951) +2022-11-14 13:47:46,143 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0868) Prec@1 87.000 (84.881) Prec@5 98.000 (98.929) +2022-11-14 13:47:46,154 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0861) Prec@1 91.000 (85.023) Prec@5 99.000 (98.930) +2022-11-14 13:47:46,165 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0862) Prec@1 85.000 (85.023) Prec@5 98.000 (98.909) +2022-11-14 13:47:46,175 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0863) Prec@1 86.000 (85.044) Prec@5 100.000 (98.933) +2022-11-14 13:47:46,184 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0865) Prec@1 81.000 (84.957) Prec@5 99.000 (98.935) +2022-11-14 13:47:46,196 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0867) Prec@1 83.000 (84.915) Prec@5 100.000 (98.957) +2022-11-14 13:47:46,207 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0873) Prec@1 82.000 (84.854) Prec@5 99.000 (98.958) +2022-11-14 13:47:46,217 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0867) Prec@1 92.000 (85.000) Prec@5 100.000 (98.980) +2022-11-14 13:47:46,226 Test: [49/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0871) Prec@1 81.000 (84.920) Prec@5 100.000 (99.000) +2022-11-14 13:47:46,238 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0868) Prec@1 88.000 (84.980) Prec@5 100.000 (99.020) +2022-11-14 13:47:46,249 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1302 (0.0876) Prec@1 77.000 (84.827) Prec@5 99.000 (99.019) +2022-11-14 13:47:46,259 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0877) Prec@1 83.000 (84.792) Prec@5 100.000 (99.038) +2022-11-14 13:47:46,267 Test: [53/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0873) Prec@1 87.000 (84.833) Prec@5 100.000 (99.056) +2022-11-14 13:47:46,280 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0875) Prec@1 79.000 (84.727) Prec@5 100.000 (99.073) +2022-11-14 13:47:46,291 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0874) Prec@1 86.000 (84.750) Prec@5 98.000 (99.054) +2022-11-14 13:47:46,300 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0875) Prec@1 85.000 (84.754) Prec@5 100.000 (99.070) +2022-11-14 13:47:46,309 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0874) Prec@1 88.000 (84.810) Prec@5 97.000 (99.034) +2022-11-14 13:47:46,321 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1150 (0.0879) Prec@1 77.000 (84.678) Prec@5 100.000 (99.051) +2022-11-14 13:47:46,332 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0878) Prec@1 84.000 (84.667) Prec@5 99.000 (99.050) +2022-11-14 13:47:46,342 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0880) Prec@1 82.000 (84.623) Prec@5 99.000 (99.049) +2022-11-14 13:47:46,351 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0880) Prec@1 86.000 (84.645) Prec@5 97.000 (99.016) +2022-11-14 13:47:46,364 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0879) Prec@1 85.000 (84.651) Prec@5 100.000 (99.032) +2022-11-14 13:47:46,376 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0875) Prec@1 88.000 (84.703) Prec@5 99.000 (99.031) +2022-11-14 13:47:46,384 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0875) Prec@1 87.000 (84.738) Prec@5 99.000 (99.031) +2022-11-14 13:47:46,393 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1287 (0.0882) Prec@1 80.000 (84.667) Prec@5 98.000 (99.015) +2022-11-14 13:47:46,406 Test: [66/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0880) Prec@1 88.000 (84.716) Prec@5 99.000 (99.015) +2022-11-14 13:47:46,417 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0879) Prec@1 85.000 (84.721) Prec@5 99.000 (99.015) +2022-11-14 13:47:46,426 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0879) Prec@1 85.000 (84.725) Prec@5 99.000 (99.014) +2022-11-14 13:47:46,435 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0878) Prec@1 86.000 (84.743) Prec@5 99.000 (99.014) +2022-11-14 13:47:46,448 Test: [70/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0879) Prec@1 84.000 (84.732) Prec@5 99.000 (99.014) +2022-11-14 13:47:46,460 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0876) Prec@1 89.000 (84.792) Prec@5 99.000 (99.014) +2022-11-14 13:47:46,469 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0876) Prec@1 88.000 (84.836) Prec@5 98.000 (99.000) +2022-11-14 13:47:46,480 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0872) Prec@1 91.000 (84.919) Prec@5 100.000 (99.014) +2022-11-14 13:47:46,494 Test: [74/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1150 (0.0875) Prec@1 82.000 (84.880) Prec@5 99.000 (99.013) +2022-11-14 13:47:46,506 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0873) Prec@1 88.000 (84.921) Prec@5 98.000 (99.000) +2022-11-14 13:47:46,518 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0874) Prec@1 84.000 (84.909) Prec@5 98.000 (98.987) +2022-11-14 13:47:46,531 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0873) Prec@1 87.000 (84.936) Prec@5 98.000 (98.974) +2022-11-14 13:47:46,545 Test: [78/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0874) Prec@1 84.000 (84.924) Prec@5 100.000 (98.987) +2022-11-14 13:47:46,556 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0871) Prec@1 91.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:47:46,566 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.0874) Prec@1 81.000 (84.951) Prec@5 99.000 (99.000) +2022-11-14 13:47:46,575 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0874) Prec@1 87.000 (84.976) Prec@5 98.000 (98.988) +2022-11-14 13:47:46,587 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0872) Prec@1 87.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:47:46,597 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0873) Prec@1 85.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:47:46,607 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.0877) Prec@1 78.000 (84.918) Prec@5 99.000 (99.000) +2022-11-14 13:47:46,618 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0878) Prec@1 83.000 (84.895) Prec@5 99.000 (99.000) +2022-11-14 13:47:46,629 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0878) Prec@1 86.000 (84.908) Prec@5 100.000 (99.011) +2022-11-14 13:47:46,640 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0877) Prec@1 88.000 (84.943) Prec@5 97.000 (98.989) +2022-11-14 13:47:46,649 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0876) Prec@1 89.000 (84.989) Prec@5 100.000 (99.000) +2022-11-14 13:47:46,657 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0876) Prec@1 85.000 (84.989) Prec@5 100.000 (99.011) +2022-11-14 13:47:46,666 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0874) Prec@1 89.000 (85.033) Prec@5 100.000 (99.022) +2022-11-14 13:47:46,678 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0870) Prec@1 95.000 (85.141) Prec@5 99.000 (99.022) +2022-11-14 13:47:46,688 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0870) Prec@1 86.000 (85.151) Prec@5 99.000 (99.022) +2022-11-14 13:47:46,698 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0871) Prec@1 84.000 (85.138) Prec@5 97.000 (99.000) +2022-11-14 13:47:46,708 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0871) Prec@1 83.000 (85.116) Prec@5 99.000 (99.000) +2022-11-14 13:47:46,719 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0871) Prec@1 86.000 (85.125) Prec@5 100.000 (99.010) +2022-11-14 13:47:46,729 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0868) Prec@1 91.000 (85.186) Prec@5 99.000 (99.010) +2022-11-14 13:47:46,739 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1202 (0.0871) Prec@1 82.000 (85.153) Prec@5 98.000 (99.000) +2022-11-14 13:47:46,749 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.0874) Prec@1 81.000 (85.111) Prec@5 100.000 (99.010) +2022-11-14 13:47:46,760 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0875) Prec@1 83.000 (85.090) Prec@5 100.000 (99.020) +2022-11-14 13:47:46,818 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:47:47,152 Epoch: [96][0/500] Time 0.028 (0.028) Data 0.238 (0.238) Loss 0.0662 (0.0662) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:47:47,378 Epoch: [96][10/500] Time 0.017 (0.021) Data 0.001 (0.023) Loss 0.0752 (0.0707) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:47:47,585 Epoch: [96][20/500] Time 0.023 (0.020) Data 0.002 (0.013) Loss 0.0639 (0.0684) Prec@1 89.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 13:47:47,828 Epoch: [96][30/500] Time 0.021 (0.020) Data 0.001 (0.009) Loss 0.0499 (0.0638) Prec@1 92.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 13:47:48,140 Epoch: [96][40/500] Time 0.035 (0.022) Data 0.002 (0.007) Loss 0.0530 (0.0616) Prec@1 91.000 (89.200) Prec@5 100.000 (99.400) +2022-11-14 13:47:48,559 Epoch: [96][50/500] Time 0.035 (0.025) Data 0.002 (0.006) Loss 0.0831 (0.0652) Prec@1 84.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 13:47:48,983 Epoch: [96][60/500] Time 0.032 (0.027) Data 0.002 (0.006) Loss 0.0756 (0.0667) Prec@1 88.000 (88.286) Prec@5 98.000 (99.143) +2022-11-14 13:47:49,412 Epoch: [96][70/500] Time 0.026 (0.029) Data 0.002 (0.005) Loss 0.0602 (0.0659) Prec@1 89.000 (88.375) Prec@5 99.000 (99.125) +2022-11-14 13:47:49,837 Epoch: [96][80/500] Time 0.065 (0.030) Data 0.002 (0.005) Loss 0.0790 (0.0673) Prec@1 86.000 (88.111) Prec@5 100.000 (99.222) +2022-11-14 13:47:50,332 Epoch: [96][90/500] Time 0.048 (0.031) Data 0.002 (0.004) Loss 0.0609 (0.0667) Prec@1 90.000 (88.300) Prec@5 100.000 (99.300) +2022-11-14 13:47:50,684 Epoch: [96][100/500] Time 0.034 (0.031) Data 0.002 (0.004) Loss 0.0777 (0.0677) Prec@1 87.000 (88.182) Prec@5 99.000 (99.273) +2022-11-14 13:47:51,097 Epoch: [96][110/500] Time 0.036 (0.032) Data 0.002 (0.004) Loss 0.0690 (0.0678) Prec@1 88.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 13:47:51,513 Epoch: [96][120/500] Time 0.035 (0.032) Data 0.001 (0.004) Loss 0.0675 (0.0678) Prec@1 88.000 (88.154) Prec@5 100.000 (99.385) +2022-11-14 13:47:51,933 Epoch: [96][130/500] Time 0.029 (0.033) Data 0.002 (0.004) Loss 0.0567 (0.0670) Prec@1 91.000 (88.357) Prec@5 100.000 (99.429) +2022-11-14 13:47:52,347 Epoch: [96][140/500] Time 0.032 (0.033) Data 0.002 (0.004) Loss 0.0463 (0.0656) Prec@1 91.000 (88.533) Prec@5 100.000 (99.467) +2022-11-14 13:47:52,731 Epoch: [96][150/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0856 (0.0669) Prec@1 84.000 (88.250) Prec@5 98.000 (99.375) +2022-11-14 13:47:53,149 Epoch: [96][160/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0713 (0.0671) Prec@1 89.000 (88.294) Prec@5 99.000 (99.353) +2022-11-14 13:47:53,620 Epoch: [96][170/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0737 (0.0675) Prec@1 88.000 (88.278) Prec@5 99.000 (99.333) +2022-11-14 13:47:54,034 Epoch: [96][180/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0778 (0.0680) Prec@1 85.000 (88.105) Prec@5 99.000 (99.316) +2022-11-14 13:47:54,426 Epoch: [96][190/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0672 (0.0680) Prec@1 90.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 13:47:54,856 Epoch: [96][200/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0726 (0.0682) Prec@1 88.000 (88.190) Prec@5 100.000 (99.333) +2022-11-14 13:47:55,246 Epoch: [96][210/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0962 (0.0695) Prec@1 86.000 (88.091) Prec@5 99.000 (99.318) +2022-11-14 13:47:55,707 Epoch: [96][220/500] Time 0.058 (0.035) Data 0.002 (0.003) Loss 0.0727 (0.0696) Prec@1 87.000 (88.043) Prec@5 100.000 (99.348) +2022-11-14 13:47:56,165 Epoch: [96][230/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0709 (0.0697) Prec@1 87.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 13:47:56,584 Epoch: [96][240/500] Time 0.029 (0.035) Data 0.002 (0.003) Loss 0.0833 (0.0702) Prec@1 84.000 (87.840) Prec@5 99.000 (99.360) +2022-11-14 13:47:57,048 Epoch: [96][250/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0603 (0.0698) Prec@1 88.000 (87.846) Prec@5 100.000 (99.385) +2022-11-14 13:47:57,438 Epoch: [96][260/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0610 (0.0695) Prec@1 90.000 (87.926) Prec@5 99.000 (99.370) +2022-11-14 13:47:57,875 Epoch: [96][270/500] Time 0.029 (0.036) Data 0.002 (0.003) Loss 0.0841 (0.0700) Prec@1 84.000 (87.786) Prec@5 100.000 (99.393) +2022-11-14 13:47:58,259 Epoch: [96][280/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0348 (0.0688) Prec@1 94.000 (88.000) Prec@5 100.000 (99.414) +2022-11-14 13:47:58,717 Epoch: [96][290/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0849 (0.0694) Prec@1 86.000 (87.933) Prec@5 97.000 (99.333) +2022-11-14 13:47:59,127 Epoch: [96][300/500] Time 0.032 (0.036) Data 0.001 (0.003) Loss 0.0889 (0.0700) Prec@1 86.000 (87.871) Prec@5 97.000 (99.258) +2022-11-14 13:47:59,520 Epoch: [96][310/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0944 (0.0707) Prec@1 85.000 (87.781) Prec@5 99.000 (99.250) +2022-11-14 13:47:59,911 Epoch: [96][320/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0777 (0.0710) Prec@1 87.000 (87.758) Prec@5 100.000 (99.273) +2022-11-14 13:48:00,329 Epoch: [96][330/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0953 (0.0717) Prec@1 83.000 (87.618) Prec@5 99.000 (99.265) +2022-11-14 13:48:00,726 Epoch: [96][340/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.0628 (0.0714) Prec@1 88.000 (87.629) Prec@5 100.000 (99.286) +2022-11-14 13:48:01,101 Epoch: [96][350/500] Time 0.036 (0.036) Data 0.003 (0.003) Loss 0.0887 (0.0719) Prec@1 86.000 (87.583) Prec@5 99.000 (99.278) +2022-11-14 13:48:01,546 Epoch: [96][360/500] Time 0.041 (0.036) Data 0.003 (0.003) Loss 0.0723 (0.0719) Prec@1 89.000 (87.622) Prec@5 100.000 (99.297) +2022-11-14 13:48:01,978 Epoch: [96][370/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.0868 (0.0723) Prec@1 88.000 (87.632) Prec@5 99.000 (99.289) +2022-11-14 13:48:02,405 Epoch: [96][380/500] Time 0.034 (0.036) Data 0.001 (0.003) Loss 0.0341 (0.0713) Prec@1 94.000 (87.795) Prec@5 100.000 (99.308) +2022-11-14 13:48:02,828 Epoch: [96][390/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0723 (0.0714) Prec@1 88.000 (87.800) Prec@5 99.000 (99.300) +2022-11-14 13:48:03,223 Epoch: [96][400/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0652 (0.0712) Prec@1 89.000 (87.829) Prec@5 100.000 (99.317) +2022-11-14 13:48:03,607 Epoch: [96][410/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0816 (0.0714) Prec@1 87.000 (87.810) Prec@5 99.000 (99.310) +2022-11-14 13:48:04,002 Epoch: [96][420/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0543 (0.0711) Prec@1 92.000 (87.907) Prec@5 100.000 (99.326) +2022-11-14 13:48:04,397 Epoch: [96][430/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.1056 (0.0718) Prec@1 81.000 (87.750) Prec@5 98.000 (99.295) +2022-11-14 13:48:04,835 Epoch: [96][440/500] Time 0.055 (0.036) Data 0.002 (0.002) Loss 0.0704 (0.0718) Prec@1 89.000 (87.778) Prec@5 100.000 (99.311) +2022-11-14 13:48:05,242 Epoch: [96][450/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0837 (0.0721) Prec@1 86.000 (87.739) Prec@5 100.000 (99.326) +2022-11-14 13:48:05,668 Epoch: [96][460/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.0717 (0.0721) Prec@1 88.000 (87.745) Prec@5 97.000 (99.277) +2022-11-14 13:48:06,084 Epoch: [96][470/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0701 (0.0720) Prec@1 86.000 (87.708) Prec@5 99.000 (99.271) +2022-11-14 13:48:06,455 Epoch: [96][480/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0965 (0.0725) Prec@1 83.000 (87.612) Prec@5 100.000 (99.286) +2022-11-14 13:48:06,869 Epoch: [96][490/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0828 (0.0727) Prec@1 85.000 (87.560) Prec@5 99.000 (99.280) +2022-11-14 13:48:07,208 Epoch: [96][499/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0698 (0.0727) Prec@1 89.000 (87.588) Prec@5 100.000 (99.294) +2022-11-14 13:48:07,517 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0572 (0.0572) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:48:07,526 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1074 (0.0823) Prec@1 81.000 (86.000) Prec@5 97.000 (98.500) +2022-11-14 13:48:07,535 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0892) Prec@1 83.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:48:07,548 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0872) Prec@1 86.000 (85.250) Prec@5 100.000 (99.250) +2022-11-14 13:48:07,557 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0900) Prec@1 85.000 (85.200) Prec@5 99.000 (99.200) +2022-11-14 13:48:07,569 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0876) Prec@1 86.000 (85.333) Prec@5 98.000 (99.000) +2022-11-14 13:48:07,580 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0879) Prec@1 84.000 (85.143) Prec@5 97.000 (98.714) +2022-11-14 13:48:07,596 Test: [7/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1175 (0.0916) Prec@1 82.000 (84.750) Prec@5 98.000 (98.625) +2022-11-14 13:48:07,608 Test: [8/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0937) Prec@1 81.000 (84.333) Prec@5 100.000 (98.778) +2022-11-14 13:48:07,622 Test: [9/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0916) Prec@1 89.000 (84.800) Prec@5 99.000 (98.800) +2022-11-14 13:48:07,636 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0907) Prec@1 83.000 (84.636) Prec@5 98.000 (98.727) +2022-11-14 13:48:07,648 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0894) Prec@1 88.000 (84.917) Prec@5 99.000 (98.750) +2022-11-14 13:48:07,660 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0893) Prec@1 85.000 (84.923) Prec@5 100.000 (98.846) +2022-11-14 13:48:07,670 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0905) Prec@1 82.000 (84.714) Prec@5 98.000 (98.786) +2022-11-14 13:48:07,680 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0899) Prec@1 87.000 (84.867) Prec@5 99.000 (98.800) +2022-11-14 13:48:07,692 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0900) Prec@1 82.000 (84.688) Prec@5 100.000 (98.875) +2022-11-14 13:48:07,705 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0891) Prec@1 87.000 (84.824) Prec@5 100.000 (98.941) +2022-11-14 13:48:07,718 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.0907) Prec@1 80.000 (84.556) Prec@5 100.000 (99.000) +2022-11-14 13:48:07,731 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0910) Prec@1 82.000 (84.421) Prec@5 100.000 (99.053) +2022-11-14 13:48:07,744 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1338 (0.0932) Prec@1 75.000 (83.950) Prec@5 99.000 (99.050) +2022-11-14 13:48:07,756 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1210 (0.0945) Prec@1 78.000 (83.667) Prec@5 98.000 (99.000) +2022-11-14 13:48:07,769 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0943) Prec@1 83.000 (83.636) Prec@5 98.000 (98.955) +2022-11-14 13:48:07,783 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1185 (0.0954) Prec@1 80.000 (83.478) Prec@5 99.000 (98.957) +2022-11-14 13:48:07,798 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0959) Prec@1 82.000 (83.417) Prec@5 99.000 (98.958) +2022-11-14 13:48:07,813 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0959) Prec@1 86.000 (83.520) Prec@5 99.000 (98.960) +2022-11-14 13:48:07,827 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1275 (0.0972) Prec@1 77.000 (83.269) Prec@5 97.000 (98.885) +2022-11-14 13:48:07,840 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0959) Prec@1 88.000 (83.444) Prec@5 100.000 (98.926) +2022-11-14 13:48:07,856 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0958) Prec@1 84.000 (83.464) Prec@5 98.000 (98.893) +2022-11-14 13:48:07,870 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0956) Prec@1 84.000 (83.483) Prec@5 99.000 (98.897) +2022-11-14 13:48:07,884 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0959) Prec@1 83.000 (83.467) Prec@5 98.000 (98.867) +2022-11-14 13:48:07,897 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0954) Prec@1 86.000 (83.548) Prec@5 97.000 (98.806) +2022-11-14 13:48:07,912 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0949) Prec@1 87.000 (83.656) Prec@5 100.000 (98.844) +2022-11-14 13:48:07,928 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0946) Prec@1 86.000 (83.727) Prec@5 100.000 (98.879) +2022-11-14 13:48:07,944 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1294 (0.0956) Prec@1 76.000 (83.500) Prec@5 98.000 (98.853) +2022-11-14 13:48:07,959 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1215 (0.0963) Prec@1 77.000 (83.314) Prec@5 98.000 (98.829) +2022-11-14 13:48:07,974 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0958) Prec@1 87.000 (83.417) Prec@5 99.000 (98.833) +2022-11-14 13:48:07,988 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0959) Prec@1 82.000 (83.378) Prec@5 99.000 (98.838) +2022-11-14 13:48:08,001 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1259 (0.0967) Prec@1 80.000 (83.289) Prec@5 98.000 (98.816) +2022-11-14 13:48:08,016 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0959) Prec@1 88.000 (83.410) Prec@5 99.000 (98.821) +2022-11-14 13:48:08,035 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0954) Prec@1 87.000 (83.500) Prec@5 98.000 (98.800) +2022-11-14 13:48:08,051 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0954) Prec@1 84.000 (83.512) Prec@5 97.000 (98.756) +2022-11-14 13:48:08,070 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0954) Prec@1 84.000 (83.524) Prec@5 99.000 (98.762) +2022-11-14 13:48:08,086 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0948) Prec@1 85.000 (83.558) Prec@5 98.000 (98.744) +2022-11-14 13:48:08,103 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0945) Prec@1 87.000 (83.636) Prec@5 97.000 (98.705) +2022-11-14 13:48:08,123 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0942) Prec@1 86.000 (83.689) Prec@5 99.000 (98.711) +2022-11-14 13:48:08,140 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1210 (0.0948) Prec@1 76.000 (83.522) Prec@5 99.000 (98.717) +2022-11-14 13:48:08,160 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0944) Prec@1 88.000 (83.617) Prec@5 100.000 (98.745) +2022-11-14 13:48:08,178 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1338 (0.0952) Prec@1 78.000 (83.500) Prec@5 97.000 (98.708) +2022-11-14 13:48:08,197 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0950) Prec@1 85.000 (83.531) Prec@5 99.000 (98.714) +2022-11-14 13:48:08,215 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.0955) Prec@1 80.000 (83.460) Prec@5 100.000 (98.740) +2022-11-14 13:48:08,232 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0952) Prec@1 83.000 (83.451) Prec@5 100.000 (98.765) +2022-11-14 13:48:08,248 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.0955) Prec@1 81.000 (83.404) Prec@5 99.000 (98.769) +2022-11-14 13:48:08,266 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0957) Prec@1 81.000 (83.358) Prec@5 99.000 (98.774) +2022-11-14 13:48:08,284 Test: [53/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0955) Prec@1 87.000 (83.426) Prec@5 98.000 (98.759) +2022-11-14 13:48:08,301 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0957) Prec@1 81.000 (83.382) Prec@5 99.000 (98.764) +2022-11-14 13:48:08,317 Test: [55/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0958) Prec@1 81.000 (83.339) Prec@5 97.000 (98.732) +2022-11-14 13:48:08,336 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0957) Prec@1 83.000 (83.333) Prec@5 100.000 (98.754) +2022-11-14 13:48:08,352 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0956) Prec@1 86.000 (83.379) Prec@5 99.000 (98.759) +2022-11-14 13:48:08,369 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1196 (0.0960) Prec@1 78.000 (83.288) Prec@5 98.000 (98.746) +2022-11-14 13:48:08,385 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.0962) Prec@1 78.000 (83.200) Prec@5 99.000 (98.750) +2022-11-14 13:48:08,404 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0961) Prec@1 86.000 (83.246) Prec@5 99.000 (98.754) +2022-11-14 13:48:08,420 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0963) Prec@1 79.000 (83.177) Prec@5 99.000 (98.758) +2022-11-14 13:48:08,436 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0961) Prec@1 86.000 (83.222) Prec@5 99.000 (98.762) +2022-11-14 13:48:08,453 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0956) Prec@1 88.000 (83.297) Prec@5 100.000 (98.781) +2022-11-14 13:48:08,471 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0957) Prec@1 83.000 (83.292) Prec@5 100.000 (98.800) +2022-11-14 13:48:08,488 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0956) Prec@1 85.000 (83.318) Prec@5 99.000 (98.803) +2022-11-14 13:48:08,502 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0951) Prec@1 90.000 (83.418) Prec@5 99.000 (98.806) +2022-11-14 13:48:08,518 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.0953) Prec@1 80.000 (83.368) Prec@5 98.000 (98.794) +2022-11-14 13:48:08,536 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0953) Prec@1 81.000 (83.333) Prec@5 97.000 (98.768) +2022-11-14 13:48:08,553 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.0955) Prec@1 83.000 (83.329) Prec@5 96.000 (98.729) +2022-11-14 13:48:08,567 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0954) Prec@1 86.000 (83.366) Prec@5 98.000 (98.718) +2022-11-14 13:48:08,579 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0953) Prec@1 88.000 (83.431) Prec@5 98.000 (98.708) +2022-11-14 13:48:08,592 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0948) Prec@1 93.000 (83.562) Prec@5 100.000 (98.726) +2022-11-14 13:48:08,604 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0945) Prec@1 86.000 (83.595) Prec@5 100.000 (98.743) +2022-11-14 13:48:08,615 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0946) Prec@1 83.000 (83.587) Prec@5 99.000 (98.747) +2022-11-14 13:48:08,628 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0944) Prec@1 86.000 (83.618) Prec@5 97.000 (98.724) +2022-11-14 13:48:08,641 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0942) Prec@1 88.000 (83.675) Prec@5 98.000 (98.714) +2022-11-14 13:48:08,653 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0942) Prec@1 83.000 (83.667) Prec@5 99.000 (98.718) +2022-11-14 13:48:08,665 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.0945) Prec@1 79.000 (83.608) Prec@5 99.000 (98.722) +2022-11-14 13:48:08,678 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0945) Prec@1 81.000 (83.575) Prec@5 98.000 (98.713) +2022-11-14 13:48:08,692 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0942) Prec@1 87.000 (83.617) Prec@5 99.000 (98.716) +2022-11-14 13:48:08,705 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0943) Prec@1 80.000 (83.573) Prec@5 98.000 (98.707) +2022-11-14 13:48:08,718 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.0945) Prec@1 80.000 (83.530) Prec@5 99.000 (98.711) +2022-11-14 13:48:08,732 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0944) Prec@1 89.000 (83.595) Prec@5 100.000 (98.726) +2022-11-14 13:48:08,745 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1231 (0.0947) Prec@1 75.000 (83.494) Prec@5 98.000 (98.718) +2022-11-14 13:48:08,759 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0947) Prec@1 82.000 (83.477) Prec@5 98.000 (98.709) +2022-11-14 13:48:08,772 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0947) Prec@1 89.000 (83.540) Prec@5 98.000 (98.701) +2022-11-14 13:48:08,785 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0948) Prec@1 84.000 (83.545) Prec@5 98.000 (98.693) +2022-11-14 13:48:08,797 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0945) Prec@1 89.000 (83.607) Prec@5 100.000 (98.708) +2022-11-14 13:48:08,811 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1152 (0.0947) Prec@1 80.000 (83.567) Prec@5 100.000 (98.722) +2022-11-14 13:48:08,827 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0949) Prec@1 80.000 (83.527) Prec@5 100.000 (98.736) +2022-11-14 13:48:08,840 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0943) Prec@1 93.000 (83.630) Prec@5 97.000 (98.717) +2022-11-14 13:48:08,853 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0944) Prec@1 83.000 (83.624) Prec@5 99.000 (98.720) +2022-11-14 13:48:08,868 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0945) Prec@1 82.000 (83.606) Prec@5 99.000 (98.723) +2022-11-14 13:48:08,884 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0943) Prec@1 88.000 (83.653) Prec@5 98.000 (98.716) +2022-11-14 13:48:08,897 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0942) Prec@1 85.000 (83.667) Prec@5 100.000 (98.729) +2022-11-14 13:48:08,910 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0941) Prec@1 85.000 (83.680) Prec@5 100.000 (98.742) +2022-11-14 13:48:08,922 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0941) Prec@1 85.000 (83.694) Prec@5 97.000 (98.724) +2022-11-14 13:48:08,938 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1157 (0.0944) Prec@1 81.000 (83.667) Prec@5 99.000 (98.727) +2022-11-14 13:48:08,952 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0943) Prec@1 84.000 (83.670) Prec@5 97.000 (98.710) +2022-11-14 13:48:09,009 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:48:09,336 Epoch: [97][0/500] Time 0.031 (0.031) Data 0.234 (0.234) Loss 0.0500 (0.0500) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:48:09,570 Epoch: [97][10/500] Time 0.019 (0.021) Data 0.002 (0.023) Loss 0.0711 (0.0605) Prec@1 88.000 (90.500) Prec@5 99.000 (99.000) +2022-11-14 13:48:09,859 Epoch: [97][20/500] Time 0.031 (0.023) Data 0.002 (0.013) Loss 0.0696 (0.0635) Prec@1 87.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 13:48:10,117 Epoch: [97][30/500] Time 0.021 (0.023) Data 0.002 (0.009) Loss 0.0826 (0.0683) Prec@1 86.000 (88.500) Prec@5 98.000 (99.000) +2022-11-14 13:48:10,446 Epoch: [97][40/500] Time 0.025 (0.025) Data 0.002 (0.008) Loss 0.0429 (0.0632) Prec@1 93.000 (89.400) Prec@5 100.000 (99.200) +2022-11-14 13:48:10,969 Epoch: [97][50/500] Time 0.066 (0.029) Data 0.002 (0.006) Loss 0.0365 (0.0588) Prec@1 97.000 (90.667) Prec@5 99.000 (99.167) +2022-11-14 13:48:11,559 Epoch: [97][60/500] Time 0.044 (0.033) Data 0.002 (0.006) Loss 0.0842 (0.0624) Prec@1 87.000 (90.143) Prec@5 96.000 (98.714) +2022-11-14 13:48:12,204 Epoch: [97][70/500] Time 0.067 (0.037) Data 0.002 (0.005) Loss 0.0794 (0.0645) Prec@1 85.000 (89.500) Prec@5 99.000 (98.750) +2022-11-14 13:48:12,751 Epoch: [97][80/500] Time 0.041 (0.038) Data 0.002 (0.005) Loss 0.0447 (0.0623) Prec@1 91.000 (89.667) Prec@5 99.000 (98.778) +2022-11-14 13:48:13,291 Epoch: [97][90/500] Time 0.073 (0.039) Data 0.002 (0.005) Loss 0.0545 (0.0615) Prec@1 92.000 (89.900) Prec@5 99.000 (98.800) +2022-11-14 13:48:13,925 Epoch: [97][100/500] Time 0.067 (0.041) Data 0.002 (0.004) Loss 0.0746 (0.0627) Prec@1 88.000 (89.727) Prec@5 100.000 (98.909) +2022-11-14 13:48:14,389 Epoch: [97][110/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0667 (0.0631) Prec@1 85.000 (89.333) Prec@5 100.000 (99.000) +2022-11-14 13:48:14,866 Epoch: [97][120/500] Time 0.044 (0.041) Data 0.002 (0.004) Loss 0.0827 (0.0646) Prec@1 82.000 (88.769) Prec@5 99.000 (99.000) +2022-11-14 13:48:15,346 Epoch: [97][130/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0850 (0.0660) Prec@1 86.000 (88.571) Prec@5 100.000 (99.071) +2022-11-14 13:48:15,825 Epoch: [97][140/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0749 (0.0666) Prec@1 87.000 (88.467) Prec@5 100.000 (99.133) +2022-11-14 13:48:16,305 Epoch: [97][150/500] Time 0.040 (0.041) Data 0.002 (0.004) Loss 0.0690 (0.0668) Prec@1 88.000 (88.438) Prec@5 99.000 (99.125) +2022-11-14 13:48:16,797 Epoch: [97][160/500] Time 0.044 (0.042) Data 0.001 (0.003) Loss 0.0869 (0.0679) Prec@1 87.000 (88.353) Prec@5 99.000 (99.118) +2022-11-14 13:48:17,279 Epoch: [97][170/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0668 (0.0679) Prec@1 90.000 (88.444) Prec@5 100.000 (99.167) +2022-11-14 13:48:17,752 Epoch: [97][180/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0510 (0.0670) Prec@1 92.000 (88.632) Prec@5 97.000 (99.053) +2022-11-14 13:48:18,237 Epoch: [97][190/500] Time 0.041 (0.042) Data 0.003 (0.003) Loss 0.0609 (0.0667) Prec@1 92.000 (88.800) Prec@5 99.000 (99.050) +2022-11-14 13:48:18,712 Epoch: [97][200/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0618 (0.0665) Prec@1 91.000 (88.905) Prec@5 99.000 (99.048) +2022-11-14 13:48:19,189 Epoch: [97][210/500] Time 0.053 (0.042) Data 0.002 (0.003) Loss 0.0767 (0.0669) Prec@1 87.000 (88.818) Prec@5 99.000 (99.045) +2022-11-14 13:48:19,661 Epoch: [97][220/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0601 (0.0666) Prec@1 89.000 (88.826) Prec@5 99.000 (99.043) +2022-11-14 13:48:20,131 Epoch: [97][230/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0716 (0.0668) Prec@1 88.000 (88.792) Prec@5 100.000 (99.083) +2022-11-14 13:48:20,606 Epoch: [97][240/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0679 (0.0669) Prec@1 88.000 (88.760) Prec@5 100.000 (99.120) +2022-11-14 13:48:21,075 Epoch: [97][250/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0885 (0.0677) Prec@1 84.000 (88.577) Prec@5 99.000 (99.115) +2022-11-14 13:48:21,549 Epoch: [97][260/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0930 (0.0686) Prec@1 83.000 (88.370) Prec@5 99.000 (99.111) +2022-11-14 13:48:22,030 Epoch: [97][270/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0511 (0.0680) Prec@1 92.000 (88.500) Prec@5 99.000 (99.107) +2022-11-14 13:48:22,502 Epoch: [97][280/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0668 (0.0680) Prec@1 87.000 (88.448) Prec@5 100.000 (99.138) +2022-11-14 13:48:22,983 Epoch: [97][290/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0819 (0.0684) Prec@1 88.000 (88.433) Prec@5 99.000 (99.133) +2022-11-14 13:48:23,565 Epoch: [97][300/500] Time 0.068 (0.042) Data 0.002 (0.003) Loss 0.0865 (0.0690) Prec@1 87.000 (88.387) Prec@5 100.000 (99.161) +2022-11-14 13:48:24,126 Epoch: [97][310/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0822 (0.0694) Prec@1 88.000 (88.375) Prec@5 99.000 (99.156) +2022-11-14 13:48:24,654 Epoch: [97][320/500] Time 0.058 (0.043) Data 0.002 (0.003) Loss 0.0747 (0.0696) Prec@1 89.000 (88.394) Prec@5 98.000 (99.121) +2022-11-14 13:48:25,217 Epoch: [97][330/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.1065 (0.0707) Prec@1 85.000 (88.294) Prec@5 98.000 (99.088) +2022-11-14 13:48:25,681 Epoch: [97][340/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0684 (0.0706) Prec@1 87.000 (88.257) Prec@5 100.000 (99.114) +2022-11-14 13:48:26,248 Epoch: [97][350/500] Time 0.065 (0.043) Data 0.002 (0.003) Loss 0.0850 (0.0710) Prec@1 86.000 (88.194) Prec@5 99.000 (99.111) +2022-11-14 13:48:26,736 Epoch: [97][360/500] Time 0.036 (0.043) Data 0.002 (0.003) Loss 0.0889 (0.0715) Prec@1 82.000 (88.027) Prec@5 100.000 (99.135) +2022-11-14 13:48:27,272 Epoch: [97][370/500] Time 0.034 (0.043) Data 0.002 (0.003) Loss 0.0859 (0.0719) Prec@1 89.000 (88.053) Prec@5 99.000 (99.132) +2022-11-14 13:48:27,772 Epoch: [97][380/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0721 (0.0719) Prec@1 89.000 (88.077) Prec@5 99.000 (99.128) +2022-11-14 13:48:28,235 Epoch: [97][390/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.1082 (0.0728) Prec@1 79.000 (87.850) Prec@5 98.000 (99.100) +2022-11-14 13:48:28,695 Epoch: [97][400/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0752 (0.0729) Prec@1 87.000 (87.829) Prec@5 97.000 (99.049) +2022-11-14 13:48:29,157 Epoch: [97][410/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0425 (0.0721) Prec@1 94.000 (87.976) Prec@5 100.000 (99.071) +2022-11-14 13:48:29,618 Epoch: [97][420/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0902 (0.0725) Prec@1 83.000 (87.860) Prec@5 98.000 (99.047) +2022-11-14 13:48:30,082 Epoch: [97][430/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.1002 (0.0732) Prec@1 84.000 (87.773) Prec@5 97.000 (99.000) +2022-11-14 13:48:30,538 Epoch: [97][440/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0712 (0.0731) Prec@1 88.000 (87.778) Prec@5 99.000 (99.000) +2022-11-14 13:48:30,991 Epoch: [97][450/500] Time 0.039 (0.043) Data 0.002 (0.002) Loss 0.0614 (0.0729) Prec@1 90.000 (87.826) Prec@5 98.000 (98.978) +2022-11-14 13:48:31,293 Epoch: [97][460/500] Time 0.027 (0.043) Data 0.002 (0.002) Loss 0.0534 (0.0725) Prec@1 91.000 (87.894) Prec@5 100.000 (99.000) +2022-11-14 13:48:31,588 Epoch: [97][470/500] Time 0.028 (0.042) Data 0.002 (0.002) Loss 0.0839 (0.0727) Prec@1 87.000 (87.875) Prec@5 99.000 (99.000) +2022-11-14 13:48:31,881 Epoch: [97][480/500] Time 0.028 (0.042) Data 0.001 (0.002) Loss 0.0560 (0.0724) Prec@1 90.000 (87.918) Prec@5 100.000 (99.020) +2022-11-14 13:48:32,173 Epoch: [97][490/500] Time 0.026 (0.041) Data 0.002 (0.002) Loss 0.0820 (0.0726) Prec@1 87.000 (87.900) Prec@5 99.000 (99.020) +2022-11-14 13:48:32,440 Epoch: [97][499/500] Time 0.026 (0.041) Data 0.001 (0.002) Loss 0.0982 (0.0731) Prec@1 82.000 (87.784) Prec@5 100.000 (99.039) +2022-11-14 13:48:32,717 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0803 (0.0803) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:48:32,729 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0723 (0.0763) Prec@1 87.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 13:48:32,740 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0964 (0.0830) Prec@1 81.000 (85.000) Prec@5 98.000 (99.000) +2022-11-14 13:48:32,754 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0855) Prec@1 82.000 (84.250) Prec@5 100.000 (99.250) +2022-11-14 13:48:32,763 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0859) Prec@1 84.000 (84.200) Prec@5 100.000 (99.400) +2022-11-14 13:48:32,771 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0806) Prec@1 91.000 (85.333) Prec@5 100.000 (99.500) +2022-11-14 13:48:32,780 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0823) Prec@1 84.000 (85.143) Prec@5 100.000 (99.571) +2022-11-14 13:48:32,789 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1141 (0.0863) Prec@1 77.000 (84.125) Prec@5 99.000 (99.500) +2022-11-14 13:48:32,798 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0862) Prec@1 86.000 (84.333) Prec@5 100.000 (99.556) +2022-11-14 13:48:32,809 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0846) Prec@1 88.000 (84.700) Prec@5 98.000 (99.400) +2022-11-14 13:48:32,819 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0841) Prec@1 86.000 (84.818) Prec@5 100.000 (99.455) +2022-11-14 13:48:32,827 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0836) Prec@1 88.000 (85.083) Prec@5 100.000 (99.500) +2022-11-14 13:48:32,835 Test: [12/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0836) Prec@1 85.000 (85.077) Prec@5 100.000 (99.538) +2022-11-14 13:48:32,845 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0833) Prec@1 88.000 (85.286) Prec@5 100.000 (99.571) +2022-11-14 13:48:32,854 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0838) Prec@1 83.000 (85.133) Prec@5 99.000 (99.533) +2022-11-14 13:48:32,862 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0850) Prec@1 85.000 (85.125) Prec@5 99.000 (99.500) +2022-11-14 13:48:32,871 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0842) Prec@1 88.000 (85.294) Prec@5 99.000 (99.471) +2022-11-14 13:48:32,880 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0853) Prec@1 81.000 (85.056) Prec@5 99.000 (99.444) +2022-11-14 13:48:32,890 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0858) Prec@1 83.000 (84.947) Prec@5 96.000 (99.263) +2022-11-14 13:48:32,898 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.0870) Prec@1 82.000 (84.800) Prec@5 96.000 (99.100) +2022-11-14 13:48:32,907 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0871) Prec@1 87.000 (84.905) Prec@5 99.000 (99.095) +2022-11-14 13:48:32,916 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0869) Prec@1 85.000 (84.909) Prec@5 100.000 (99.136) +2022-11-14 13:48:32,924 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1260 (0.0886) Prec@1 78.000 (84.609) Prec@5 97.000 (99.043) +2022-11-14 13:48:32,932 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0888) Prec@1 82.000 (84.500) Prec@5 99.000 (99.042) +2022-11-14 13:48:32,941 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0883) Prec@1 86.000 (84.560) Prec@5 99.000 (99.040) +2022-11-14 13:48:32,950 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0894) Prec@1 80.000 (84.385) Prec@5 98.000 (99.000) +2022-11-14 13:48:32,959 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0889) Prec@1 88.000 (84.519) Prec@5 100.000 (99.037) +2022-11-14 13:48:32,967 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0886) Prec@1 86.000 (84.571) Prec@5 100.000 (99.071) +2022-11-14 13:48:32,975 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0885) Prec@1 84.000 (84.552) Prec@5 98.000 (99.034) +2022-11-14 13:48:32,985 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0885) Prec@1 85.000 (84.567) Prec@5 98.000 (99.000) +2022-11-14 13:48:32,993 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0885) Prec@1 85.000 (84.581) Prec@5 99.000 (99.000) +2022-11-14 13:48:33,002 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0878) Prec@1 90.000 (84.750) Prec@5 99.000 (99.000) +2022-11-14 13:48:33,011 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0878) Prec@1 87.000 (84.818) Prec@5 99.000 (99.000) +2022-11-14 13:48:33,020 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.0889) Prec@1 77.000 (84.588) Prec@5 98.000 (98.971) +2022-11-14 13:48:33,029 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0888) Prec@1 86.000 (84.629) Prec@5 98.000 (98.943) +2022-11-14 13:48:33,038 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0884) Prec@1 88.000 (84.722) Prec@5 99.000 (98.944) +2022-11-14 13:48:33,047 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0883) Prec@1 85.000 (84.730) Prec@5 98.000 (98.919) +2022-11-14 13:48:33,056 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0888) Prec@1 80.000 (84.605) Prec@5 98.000 (98.895) +2022-11-14 13:48:33,064 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0881) Prec@1 91.000 (84.769) Prec@5 99.000 (98.897) +2022-11-14 13:48:33,073 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0879) Prec@1 86.000 (84.800) Prec@5 100.000 (98.925) +2022-11-14 13:48:33,082 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0885) Prec@1 80.000 (84.683) Prec@5 96.000 (98.854) +2022-11-14 13:48:33,091 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0883) Prec@1 89.000 (84.786) Prec@5 98.000 (98.833) +2022-11-14 13:48:33,100 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0876) Prec@1 89.000 (84.884) Prec@5 99.000 (98.837) +2022-11-14 13:48:33,109 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0878) Prec@1 85.000 (84.886) Prec@5 99.000 (98.841) +2022-11-14 13:48:33,117 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0873) Prec@1 88.000 (84.956) Prec@5 99.000 (98.844) +2022-11-14 13:48:33,125 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0874) Prec@1 83.000 (84.913) Prec@5 99.000 (98.848) +2022-11-14 13:48:33,134 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0869) Prec@1 90.000 (85.021) Prec@5 100.000 (98.872) +2022-11-14 13:48:33,144 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.0876) Prec@1 82.000 (84.958) Prec@5 99.000 (98.875) +2022-11-14 13:48:33,153 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0870) Prec@1 89.000 (85.041) Prec@5 100.000 (98.898) +2022-11-14 13:48:33,162 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0876) Prec@1 79.000 (84.920) Prec@5 99.000 (98.900) +2022-11-14 13:48:33,171 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0875) Prec@1 86.000 (84.941) Prec@5 99.000 (98.902) +2022-11-14 13:48:33,181 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0877) Prec@1 83.000 (84.904) Prec@5 98.000 (98.885) +2022-11-14 13:48:33,190 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0880) Prec@1 82.000 (84.849) Prec@5 99.000 (98.887) +2022-11-14 13:48:33,202 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0879) Prec@1 86.000 (84.870) Prec@5 98.000 (98.870) +2022-11-14 13:48:33,213 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0881) Prec@1 82.000 (84.818) Prec@5 100.000 (98.891) +2022-11-14 13:48:33,222 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0880) Prec@1 85.000 (84.821) Prec@5 99.000 (98.893) +2022-11-14 13:48:33,231 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0880) Prec@1 86.000 (84.842) Prec@5 99.000 (98.895) +2022-11-14 13:48:33,244 Test: [57/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0878) Prec@1 88.000 (84.897) Prec@5 100.000 (98.914) +2022-11-14 13:48:33,255 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0882) Prec@1 85.000 (84.898) Prec@5 98.000 (98.898) +2022-11-14 13:48:33,264 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0880) Prec@1 88.000 (84.950) Prec@5 100.000 (98.917) +2022-11-14 13:48:33,274 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0884) Prec@1 81.000 (84.885) Prec@5 97.000 (98.885) +2022-11-14 13:48:33,286 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0885) Prec@1 82.000 (84.839) Prec@5 99.000 (98.887) +2022-11-14 13:48:33,297 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0887) Prec@1 85.000 (84.841) Prec@5 100.000 (98.905) +2022-11-14 13:48:33,306 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0885) Prec@1 85.000 (84.844) Prec@5 99.000 (98.906) +2022-11-14 13:48:33,315 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1239 (0.0891) Prec@1 78.000 (84.738) Prec@5 97.000 (98.877) +2022-11-14 13:48:33,328 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0891) Prec@1 83.000 (84.712) Prec@5 100.000 (98.894) +2022-11-14 13:48:33,339 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0887) Prec@1 87.000 (84.746) Prec@5 100.000 (98.910) +2022-11-14 13:48:33,348 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0888) Prec@1 84.000 (84.735) Prec@5 100.000 (98.926) +2022-11-14 13:48:33,357 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0888) Prec@1 84.000 (84.725) Prec@5 99.000 (98.928) +2022-11-14 13:48:33,369 Test: [69/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0889) Prec@1 82.000 (84.686) Prec@5 98.000 (98.914) +2022-11-14 13:48:33,379 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0890) Prec@1 83.000 (84.662) Prec@5 98.000 (98.901) +2022-11-14 13:48:33,390 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0892) Prec@1 83.000 (84.639) Prec@5 100.000 (98.917) +2022-11-14 13:48:33,398 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0893) Prec@1 85.000 (84.644) Prec@5 99.000 (98.918) +2022-11-14 13:48:33,408 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0890) Prec@1 89.000 (84.703) Prec@5 100.000 (98.932) +2022-11-14 13:48:33,418 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0891) Prec@1 86.000 (84.720) Prec@5 98.000 (98.920) +2022-11-14 13:48:33,427 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0888) Prec@1 89.000 (84.776) Prec@5 97.000 (98.895) +2022-11-14 13:48:33,436 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0888) Prec@1 85.000 (84.779) Prec@5 100.000 (98.909) +2022-11-14 13:48:33,445 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0889) Prec@1 82.000 (84.744) Prec@5 99.000 (98.910) +2022-11-14 13:48:33,453 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0887) Prec@1 88.000 (84.785) Prec@5 100.000 (98.924) +2022-11-14 13:48:33,462 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0887) Prec@1 84.000 (84.775) Prec@5 98.000 (98.912) +2022-11-14 13:48:33,471 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0886) Prec@1 86.000 (84.790) Prec@5 97.000 (98.889) +2022-11-14 13:48:33,480 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0887) Prec@1 78.000 (84.707) Prec@5 100.000 (98.902) +2022-11-14 13:48:33,487 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0889) Prec@1 84.000 (84.699) Prec@5 100.000 (98.916) +2022-11-14 13:48:33,496 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0886) Prec@1 90.000 (84.762) Prec@5 99.000 (98.917) +2022-11-14 13:48:33,506 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0886) Prec@1 84.000 (84.753) Prec@5 97.000 (98.894) +2022-11-14 13:48:33,514 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1359 (0.0892) Prec@1 79.000 (84.686) Prec@5 99.000 (98.895) +2022-11-14 13:48:33,523 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0894) Prec@1 82.000 (84.655) Prec@5 97.000 (98.874) +2022-11-14 13:48:33,532 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0896) Prec@1 83.000 (84.636) Prec@5 100.000 (98.886) +2022-11-14 13:48:33,541 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0893) Prec@1 90.000 (84.697) Prec@5 98.000 (98.876) +2022-11-14 13:48:33,550 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0894) Prec@1 82.000 (84.667) Prec@5 98.000 (98.867) +2022-11-14 13:48:33,559 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0891) Prec@1 88.000 (84.703) Prec@5 100.000 (98.879) +2022-11-14 13:48:33,569 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0886) Prec@1 92.000 (84.783) Prec@5 100.000 (98.891) +2022-11-14 13:48:33,577 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0890) Prec@1 79.000 (84.720) Prec@5 100.000 (98.903) +2022-11-14 13:48:33,585 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0890) Prec@1 84.000 (84.713) Prec@5 100.000 (98.915) +2022-11-14 13:48:33,594 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0890) Prec@1 84.000 (84.705) Prec@5 99.000 (98.916) +2022-11-14 13:48:33,603 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0890) Prec@1 87.000 (84.729) Prec@5 98.000 (98.906) +2022-11-14 13:48:33,611 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0891) Prec@1 79.000 (84.670) Prec@5 98.000 (98.897) +2022-11-14 13:48:33,619 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0894) Prec@1 82.000 (84.643) Prec@5 98.000 (98.888) +2022-11-14 13:48:33,627 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0895) Prec@1 84.000 (84.636) Prec@5 99.000 (98.889) +2022-11-14 13:48:33,636 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0896) Prec@1 85.000 (84.640) Prec@5 97.000 (98.870) +2022-11-14 13:48:33,691 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:48:33,991 Epoch: [98][0/500] Time 0.029 (0.029) Data 0.217 (0.217) Loss 0.0880 (0.0880) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 13:48:34,191 Epoch: [98][10/500] Time 0.017 (0.018) Data 0.001 (0.021) Loss 0.0642 (0.0761) Prec@1 88.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 13:48:34,382 Epoch: [98][20/500] Time 0.017 (0.018) Data 0.001 (0.012) Loss 0.0712 (0.0745) Prec@1 88.000 (86.667) Prec@5 99.000 (99.667) +2022-11-14 13:48:34,669 Epoch: [98][30/500] Time 0.034 (0.020) Data 0.002 (0.009) Loss 0.0857 (0.0773) Prec@1 85.000 (86.250) Prec@5 100.000 (99.750) +2022-11-14 13:48:35,017 Epoch: [98][40/500] Time 0.032 (0.023) Data 0.002 (0.007) Loss 0.0847 (0.0788) Prec@1 87.000 (86.400) Prec@5 100.000 (99.800) +2022-11-14 13:48:35,357 Epoch: [98][50/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.0653 (0.0765) Prec@1 89.000 (86.833) Prec@5 99.000 (99.667) +2022-11-14 13:48:35,707 Epoch: [98][60/500] Time 0.033 (0.025) Data 0.002 (0.005) Loss 0.0709 (0.0757) Prec@1 86.000 (86.714) Prec@5 100.000 (99.714) +2022-11-14 13:48:36,056 Epoch: [98][70/500] Time 0.035 (0.026) Data 0.002 (0.005) Loss 0.0692 (0.0749) Prec@1 87.000 (86.750) Prec@5 98.000 (99.500) +2022-11-14 13:48:36,408 Epoch: [98][80/500] Time 0.035 (0.027) Data 0.001 (0.004) Loss 0.0785 (0.0753) Prec@1 85.000 (86.556) Prec@5 100.000 (99.556) +2022-11-14 13:48:36,759 Epoch: [98][90/500] Time 0.033 (0.027) Data 0.003 (0.004) Loss 0.0585 (0.0736) Prec@1 89.000 (86.800) Prec@5 99.000 (99.500) +2022-11-14 13:48:37,105 Epoch: [98][100/500] Time 0.032 (0.027) Data 0.002 (0.004) Loss 0.0742 (0.0737) Prec@1 88.000 (86.909) Prec@5 98.000 (99.364) +2022-11-14 13:48:37,448 Epoch: [98][110/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0838 (0.0745) Prec@1 86.000 (86.833) Prec@5 100.000 (99.417) +2022-11-14 13:48:37,804 Epoch: [98][120/500] Time 0.034 (0.028) Data 0.002 (0.004) Loss 0.0569 (0.0732) Prec@1 90.000 (87.077) Prec@5 99.000 (99.385) +2022-11-14 13:48:38,161 Epoch: [98][130/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0672 (0.0727) Prec@1 91.000 (87.357) Prec@5 99.000 (99.357) +2022-11-14 13:48:38,508 Epoch: [98][140/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0526 (0.0714) Prec@1 91.000 (87.600) Prec@5 100.000 (99.400) +2022-11-14 13:48:38,850 Epoch: [98][150/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0520 (0.0702) Prec@1 92.000 (87.875) Prec@5 100.000 (99.438) +2022-11-14 13:48:39,199 Epoch: [98][160/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.1236 (0.0733) Prec@1 78.000 (87.294) Prec@5 97.000 (99.294) +2022-11-14 13:48:39,549 Epoch: [98][170/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0605 (0.0726) Prec@1 91.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 13:48:39,944 Epoch: [98][180/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0741 (0.0727) Prec@1 89.000 (87.579) Prec@5 99.000 (99.316) +2022-11-14 13:48:40,288 Epoch: [98][190/500] Time 0.031 (0.029) Data 0.001 (0.003) Loss 0.0558 (0.0718) Prec@1 90.000 (87.700) Prec@5 100.000 (99.350) +2022-11-14 13:48:40,687 Epoch: [98][200/500] Time 0.024 (0.030) Data 0.002 (0.003) Loss 0.0528 (0.0709) Prec@1 89.000 (87.762) Prec@5 99.000 (99.333) +2022-11-14 13:48:41,026 Epoch: [98][210/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0562 (0.0703) Prec@1 90.000 (87.864) Prec@5 100.000 (99.364) +2022-11-14 13:48:41,381 Epoch: [98][220/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.1062 (0.0718) Prec@1 83.000 (87.652) Prec@5 99.000 (99.348) +2022-11-14 13:48:41,729 Epoch: [98][230/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0747 (0.0720) Prec@1 86.000 (87.583) Prec@5 100.000 (99.375) +2022-11-14 13:48:42,134 Epoch: [98][240/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0705 (0.0719) Prec@1 88.000 (87.600) Prec@5 100.000 (99.400) +2022-11-14 13:48:42,555 Epoch: [98][250/500] Time 0.047 (0.030) Data 0.002 (0.003) Loss 0.0569 (0.0713) Prec@1 90.000 (87.692) Prec@5 100.000 (99.423) +2022-11-14 13:48:42,928 Epoch: [98][260/500] Time 0.028 (0.030) Data 0.002 (0.003) Loss 0.0683 (0.0712) Prec@1 87.000 (87.667) Prec@5 100.000 (99.444) +2022-11-14 13:48:43,278 Epoch: [98][270/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0731 (0.0713) Prec@1 88.000 (87.679) Prec@5 100.000 (99.464) +2022-11-14 13:48:43,636 Epoch: [98][280/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0716 (0.0713) Prec@1 89.000 (87.724) Prec@5 99.000 (99.448) +2022-11-14 13:48:43,999 Epoch: [98][290/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0462 (0.0704) Prec@1 94.000 (87.933) Prec@5 100.000 (99.467) +2022-11-14 13:48:44,348 Epoch: [98][300/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0637 (0.0702) Prec@1 89.000 (87.968) Prec@5 100.000 (99.484) +2022-11-14 13:48:44,699 Epoch: [98][310/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0623 (0.0700) Prec@1 89.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 13:48:45,046 Epoch: [98][320/500] Time 0.030 (0.030) Data 0.002 (0.002) Loss 0.0601 (0.0697) Prec@1 90.000 (88.061) Prec@5 100.000 (99.515) +2022-11-14 13:48:45,436 Epoch: [98][330/500] Time 0.041 (0.031) Data 0.002 (0.002) Loss 0.0814 (0.0700) Prec@1 88.000 (88.059) Prec@5 100.000 (99.529) +2022-11-14 13:48:45,863 Epoch: [98][340/500] Time 0.046 (0.031) Data 0.003 (0.002) Loss 0.0654 (0.0699) Prec@1 90.000 (88.114) Prec@5 99.000 (99.514) +2022-11-14 13:48:46,218 Epoch: [98][350/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0611 (0.0697) Prec@1 92.000 (88.222) Prec@5 99.000 (99.500) +2022-11-14 13:48:46,598 Epoch: [98][360/500] Time 0.026 (0.031) Data 0.002 (0.002) Loss 0.0648 (0.0695) Prec@1 87.000 (88.189) Prec@5 99.000 (99.486) +2022-11-14 13:48:46,939 Epoch: [98][370/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0668 (0.0694) Prec@1 90.000 (88.237) Prec@5 100.000 (99.500) +2022-11-14 13:48:47,385 Epoch: [98][380/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.0760 (0.0696) Prec@1 86.000 (88.179) Prec@5 100.000 (99.513) +2022-11-14 13:48:47,779 Epoch: [98][390/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0615 (0.0694) Prec@1 90.000 (88.225) Prec@5 100.000 (99.525) +2022-11-14 13:48:48,144 Epoch: [98][400/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.0783 (0.0696) Prec@1 87.000 (88.195) Prec@5 99.000 (99.512) +2022-11-14 13:48:48,520 Epoch: [98][410/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.1230 (0.0709) Prec@1 77.000 (87.929) Prec@5 99.000 (99.500) +2022-11-14 13:48:48,935 Epoch: [98][420/500] Time 0.038 (0.031) Data 0.002 (0.002) Loss 0.0583 (0.0706) Prec@1 91.000 (88.000) Prec@5 99.000 (99.488) +2022-11-14 13:48:49,310 Epoch: [98][430/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.0673 (0.0705) Prec@1 88.000 (88.000) Prec@5 98.000 (99.455) +2022-11-14 13:48:49,662 Epoch: [98][440/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0831 (0.0708) Prec@1 86.000 (87.956) Prec@5 98.000 (99.422) +2022-11-14 13:48:50,098 Epoch: [98][450/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.0693 (0.0708) Prec@1 89.000 (87.978) Prec@5 100.000 (99.435) +2022-11-14 13:48:50,474 Epoch: [98][460/500] Time 0.048 (0.032) Data 0.002 (0.002) Loss 0.0796 (0.0710) Prec@1 86.000 (87.936) Prec@5 100.000 (99.447) +2022-11-14 13:48:50,839 Epoch: [98][470/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.0358 (0.0702) Prec@1 94.000 (88.062) Prec@5 100.000 (99.458) +2022-11-14 13:48:51,199 Epoch: [98][480/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0851 (0.0705) Prec@1 82.000 (87.939) Prec@5 100.000 (99.469) +2022-11-14 13:48:51,550 Epoch: [98][490/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0808 (0.0707) Prec@1 87.000 (87.920) Prec@5 99.000 (99.460) +2022-11-14 13:48:51,938 Epoch: [98][499/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0901 (0.0711) Prec@1 83.000 (87.824) Prec@5 98.000 (99.431) +2022-11-14 13:48:52,267 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0705 (0.0705) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:48:52,279 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0926 (0.0815) Prec@1 85.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:48:52,291 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0917 (0.0849) Prec@1 83.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 13:48:52,302 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0887) Prec@1 82.000 (84.250) Prec@5 99.000 (99.000) +2022-11-14 13:48:52,311 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1129 (0.0936) Prec@1 81.000 (83.600) Prec@5 99.000 (99.000) +2022-11-14 13:48:52,323 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0350 (0.0838) Prec@1 94.000 (85.333) Prec@5 100.000 (99.167) +2022-11-14 13:48:52,332 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0829) Prec@1 88.000 (85.714) Prec@5 100.000 (99.286) +2022-11-14 13:48:52,342 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.0860) Prec@1 82.000 (85.250) Prec@5 98.000 (99.125) +2022-11-14 13:48:52,351 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1138 (0.0891) Prec@1 81.000 (84.778) Prec@5 97.000 (98.889) +2022-11-14 13:48:52,360 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0875) Prec@1 83.000 (84.600) Prec@5 96.000 (98.600) +2022-11-14 13:48:52,369 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0846) Prec@1 89.000 (85.000) Prec@5 100.000 (98.727) +2022-11-14 13:48:52,378 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0858) Prec@1 82.000 (84.750) Prec@5 98.000 (98.667) +2022-11-14 13:48:52,388 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0850) Prec@1 86.000 (84.846) Prec@5 100.000 (98.769) +2022-11-14 13:48:52,397 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0851) Prec@1 87.000 (85.000) Prec@5 99.000 (98.786) +2022-11-14 13:48:52,406 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0848) Prec@1 85.000 (85.000) Prec@5 98.000 (98.733) +2022-11-14 13:48:52,416 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0852) Prec@1 85.000 (85.000) Prec@5 99.000 (98.750) +2022-11-14 13:48:52,424 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0849) Prec@1 88.000 (85.176) Prec@5 98.000 (98.706) +2022-11-14 13:48:52,433 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0855) Prec@1 86.000 (85.222) Prec@5 100.000 (98.778) +2022-11-14 13:48:52,443 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0857) Prec@1 83.000 (85.105) Prec@5 98.000 (98.737) +2022-11-14 13:48:52,451 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0871) Prec@1 81.000 (84.900) Prec@5 96.000 (98.600) +2022-11-14 13:48:52,459 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0870) Prec@1 85.000 (84.905) Prec@5 100.000 (98.667) +2022-11-14 13:48:52,467 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0873) Prec@1 85.000 (84.909) Prec@5 99.000 (98.682) +2022-11-14 13:48:52,475 Test: [22/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0885) Prec@1 80.000 (84.696) Prec@5 98.000 (98.652) +2022-11-14 13:48:52,483 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0885) Prec@1 82.000 (84.583) Prec@5 100.000 (98.708) +2022-11-14 13:48:52,492 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0891) Prec@1 84.000 (84.560) Prec@5 100.000 (98.760) +2022-11-14 13:48:52,500 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.0902) Prec@1 81.000 (84.423) Prec@5 97.000 (98.692) +2022-11-14 13:48:52,507 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0899) Prec@1 85.000 (84.444) Prec@5 99.000 (98.704) +2022-11-14 13:48:52,515 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0900) Prec@1 82.000 (84.357) Prec@5 100.000 (98.750) +2022-11-14 13:48:52,523 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0903) Prec@1 83.000 (84.310) Prec@5 98.000 (98.724) +2022-11-14 13:48:52,532 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0907) Prec@1 83.000 (84.267) Prec@5 98.000 (98.700) +2022-11-14 13:48:52,541 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0908) Prec@1 80.000 (84.129) Prec@5 97.000 (98.645) +2022-11-14 13:48:52,550 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0910) Prec@1 83.000 (84.094) Prec@5 99.000 (98.656) +2022-11-14 13:48:52,558 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0909) Prec@1 85.000 (84.121) Prec@5 100.000 (98.697) +2022-11-14 13:48:52,565 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0914) Prec@1 81.000 (84.029) Prec@5 99.000 (98.706) +2022-11-14 13:48:52,573 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0915) Prec@1 86.000 (84.086) Prec@5 97.000 (98.657) +2022-11-14 13:48:52,583 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0909) Prec@1 91.000 (84.278) Prec@5 100.000 (98.694) +2022-11-14 13:48:52,593 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0908) Prec@1 85.000 (84.297) Prec@5 97.000 (98.649) +2022-11-14 13:48:52,602 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0911) Prec@1 83.000 (84.263) Prec@5 99.000 (98.658) +2022-11-14 13:48:52,610 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0904) Prec@1 90.000 (84.410) Prec@5 100.000 (98.692) +2022-11-14 13:48:52,620 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0901) Prec@1 87.000 (84.475) Prec@5 100.000 (98.725) +2022-11-14 13:48:52,629 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0905) Prec@1 82.000 (84.415) Prec@5 96.000 (98.659) +2022-11-14 13:48:52,637 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0902) Prec@1 87.000 (84.476) Prec@5 97.000 (98.619) +2022-11-14 13:48:52,645 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0899) Prec@1 87.000 (84.535) Prec@5 99.000 (98.628) +2022-11-14 13:48:52,654 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0897) Prec@1 88.000 (84.614) Prec@5 98.000 (98.614) +2022-11-14 13:48:52,663 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0893) Prec@1 89.000 (84.711) Prec@5 100.000 (98.644) +2022-11-14 13:48:52,672 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1117 (0.0898) Prec@1 78.000 (84.565) Prec@5 100.000 (98.674) +2022-11-14 13:48:52,680 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0892) Prec@1 88.000 (84.638) Prec@5 100.000 (98.702) +2022-11-14 13:48:52,688 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0896) Prec@1 82.000 (84.583) Prec@5 97.000 (98.667) +2022-11-14 13:48:52,697 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0892) Prec@1 88.000 (84.653) Prec@5 99.000 (98.673) +2022-11-14 13:48:52,706 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1248 (0.0899) Prec@1 81.000 (84.580) Prec@5 97.000 (98.640) +2022-11-14 13:48:52,716 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0896) Prec@1 86.000 (84.608) Prec@5 99.000 (98.647) +2022-11-14 13:48:52,725 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0901) Prec@1 79.000 (84.500) Prec@5 98.000 (98.635) +2022-11-14 13:48:52,734 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0901) Prec@1 82.000 (84.453) Prec@5 99.000 (98.642) +2022-11-14 13:48:52,743 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0899) Prec@1 86.000 (84.481) Prec@5 99.000 (98.648) +2022-11-14 13:48:52,751 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1222 (0.0905) Prec@1 79.000 (84.382) Prec@5 99.000 (98.655) +2022-11-14 13:48:52,761 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0905) Prec@1 86.000 (84.411) Prec@5 100.000 (98.679) +2022-11-14 13:48:52,771 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0906) Prec@1 88.000 (84.474) Prec@5 99.000 (98.684) +2022-11-14 13:48:52,780 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0905) Prec@1 86.000 (84.500) Prec@5 98.000 (98.672) +2022-11-14 13:48:52,789 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1155 (0.0909) Prec@1 81.000 (84.441) Prec@5 100.000 (98.695) +2022-11-14 13:48:52,799 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0911) Prec@1 80.000 (84.367) Prec@5 99.000 (98.700) +2022-11-14 13:48:52,807 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0913) Prec@1 83.000 (84.344) Prec@5 98.000 (98.689) +2022-11-14 13:48:52,816 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0915) Prec@1 85.000 (84.355) Prec@5 100.000 (98.710) +2022-11-14 13:48:52,826 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0914) Prec@1 85.000 (84.365) Prec@5 100.000 (98.730) +2022-11-14 13:48:52,834 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0910) Prec@1 90.000 (84.453) Prec@5 100.000 (98.750) +2022-11-14 13:48:52,843 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.0913) Prec@1 81.000 (84.400) Prec@5 98.000 (98.738) +2022-11-14 13:48:52,853 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0916) Prec@1 81.000 (84.348) Prec@5 99.000 (98.742) +2022-11-14 13:48:52,862 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0912) Prec@1 87.000 (84.388) Prec@5 100.000 (98.761) +2022-11-14 13:48:52,872 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0915) Prec@1 80.000 (84.324) Prec@5 98.000 (98.750) +2022-11-14 13:48:52,884 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1034 (0.0917) Prec@1 82.000 (84.290) Prec@5 98.000 (98.739) +2022-11-14 13:48:52,895 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.0919) Prec@1 80.000 (84.229) Prec@5 98.000 (98.729) +2022-11-14 13:48:52,906 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.0921) Prec@1 82.000 (84.197) Prec@5 100.000 (98.746) +2022-11-14 13:48:52,918 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1011 (0.0922) Prec@1 83.000 (84.181) Prec@5 99.000 (98.750) +2022-11-14 13:48:52,929 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0918) Prec@1 91.000 (84.274) Prec@5 99.000 (98.753) +2022-11-14 13:48:52,940 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0915) Prec@1 85.000 (84.284) Prec@5 100.000 (98.770) +2022-11-14 13:48:52,952 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1167 (0.0919) Prec@1 79.000 (84.213) Prec@5 99.000 (98.773) +2022-11-14 13:48:52,964 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0916) Prec@1 88.000 (84.263) Prec@5 97.000 (98.750) +2022-11-14 13:48:52,975 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0912) Prec@1 92.000 (84.364) Prec@5 100.000 (98.766) +2022-11-14 13:48:52,989 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1118 (0.0915) Prec@1 82.000 (84.333) Prec@5 97.000 (98.744) +2022-11-14 13:48:53,004 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0915) Prec@1 86.000 (84.354) Prec@5 100.000 (98.759) +2022-11-14 13:48:53,018 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0913) Prec@1 86.000 (84.375) Prec@5 99.000 (98.763) +2022-11-14 13:48:53,032 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0913) Prec@1 83.000 (84.358) Prec@5 99.000 (98.765) +2022-11-14 13:48:53,046 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0914) Prec@1 83.000 (84.341) Prec@5 99.000 (98.768) +2022-11-14 13:48:53,058 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0913) Prec@1 85.000 (84.349) Prec@5 99.000 (98.771) +2022-11-14 13:48:53,068 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0912) Prec@1 85.000 (84.357) Prec@5 99.000 (98.774) +2022-11-14 13:48:53,082 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1049 (0.0914) Prec@1 81.000 (84.318) Prec@5 100.000 (98.788) +2022-11-14 13:48:53,096 Test: [85/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0913) Prec@1 85.000 (84.326) Prec@5 98.000 (98.779) +2022-11-14 13:48:53,111 Test: [86/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0912) Prec@1 83.000 (84.310) Prec@5 98.000 (98.770) +2022-11-14 13:48:53,125 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0909) Prec@1 86.000 (84.330) Prec@5 99.000 (98.773) +2022-11-14 13:48:53,138 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0910) Prec@1 84.000 (84.326) Prec@5 97.000 (98.753) +2022-11-14 13:48:53,150 Test: [89/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0908) Prec@1 91.000 (84.400) Prec@5 98.000 (98.744) +2022-11-14 13:48:53,164 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0906) Prec@1 88.000 (84.440) Prec@5 100.000 (98.758) +2022-11-14 13:48:53,178 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0902) Prec@1 90.000 (84.500) Prec@5 99.000 (98.761) +2022-11-14 13:48:53,192 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.0905) Prec@1 83.000 (84.484) Prec@5 99.000 (98.763) +2022-11-14 13:48:53,206 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0904) Prec@1 86.000 (84.500) Prec@5 98.000 (98.755) +2022-11-14 13:48:53,219 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0903) Prec@1 85.000 (84.505) Prec@5 98.000 (98.747) +2022-11-14 13:48:53,233 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0899) Prec@1 91.000 (84.573) Prec@5 100.000 (98.760) +2022-11-14 13:48:53,247 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0896) Prec@1 91.000 (84.639) Prec@5 99.000 (98.763) +2022-11-14 13:48:53,261 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0897) Prec@1 83.000 (84.622) Prec@5 97.000 (98.745) +2022-11-14 13:48:53,275 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1220 (0.0901) Prec@1 79.000 (84.566) Prec@5 99.000 (98.747) +2022-11-14 13:48:53,291 Test: [99/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0900) Prec@1 85.000 (84.570) Prec@5 100.000 (98.760) +2022-11-14 13:48:53,349 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:48:53,660 Epoch: [99][0/500] Time 0.022 (0.022) Data 0.229 (0.229) Loss 0.0953 (0.0953) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:48:54,052 Epoch: [99][10/500] Time 0.045 (0.034) Data 0.002 (0.022) Loss 0.0651 (0.0802) Prec@1 88.000 (86.500) Prec@5 100.000 (99.000) +2022-11-14 13:48:54,422 Epoch: [99][20/500] Time 0.037 (0.034) Data 0.002 (0.013) Loss 0.0731 (0.0778) Prec@1 86.000 (86.333) Prec@5 100.000 (99.333) +2022-11-14 13:48:54,859 Epoch: [99][30/500] Time 0.040 (0.035) Data 0.002 (0.009) Loss 0.0441 (0.0694) Prec@1 93.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 13:48:55,218 Epoch: [99][40/500] Time 0.036 (0.035) Data 0.002 (0.007) Loss 0.0594 (0.0674) Prec@1 90.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 13:48:55,619 Epoch: [99][50/500] Time 0.032 (0.035) Data 0.002 (0.006) Loss 0.0628 (0.0666) Prec@1 89.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 13:48:55,993 Epoch: [99][60/500] Time 0.033 (0.035) Data 0.002 (0.006) Loss 0.0740 (0.0677) Prec@1 86.000 (88.143) Prec@5 100.000 (99.286) +2022-11-14 13:48:56,373 Epoch: [99][70/500] Time 0.037 (0.034) Data 0.002 (0.005) Loss 0.0657 (0.0674) Prec@1 89.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 13:48:56,806 Epoch: [99][80/500] Time 0.047 (0.035) Data 0.002 (0.005) Loss 0.0785 (0.0687) Prec@1 85.000 (87.889) Prec@5 100.000 (99.333) +2022-11-14 13:48:57,170 Epoch: [99][90/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0762 (0.0694) Prec@1 87.000 (87.800) Prec@5 99.000 (99.300) +2022-11-14 13:48:57,568 Epoch: [99][100/500] Time 0.032 (0.035) Data 0.002 (0.004) Loss 0.0636 (0.0689) Prec@1 90.000 (88.000) Prec@5 100.000 (99.364) +2022-11-14 13:48:58,005 Epoch: [99][110/500] Time 0.061 (0.035) Data 0.002 (0.004) Loss 0.0874 (0.0704) Prec@1 86.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 13:48:58,382 Epoch: [99][120/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0579 (0.0695) Prec@1 92.000 (88.154) Prec@5 99.000 (99.308) +2022-11-14 13:48:58,763 Epoch: [99][130/500] Time 0.029 (0.035) Data 0.002 (0.004) Loss 0.0555 (0.0685) Prec@1 89.000 (88.214) Prec@5 100.000 (99.357) +2022-11-14 13:48:59,153 Epoch: [99][140/500] Time 0.036 (0.035) Data 0.002 (0.004) Loss 0.0411 (0.0666) Prec@1 92.000 (88.467) Prec@5 100.000 (99.400) +2022-11-14 13:48:59,650 Epoch: [99][150/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0534 (0.0658) Prec@1 94.000 (88.812) Prec@5 100.000 (99.438) +2022-11-14 13:49:00,049 Epoch: [99][160/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.1120 (0.0685) Prec@1 82.000 (88.412) Prec@5 100.000 (99.471) +2022-11-14 13:49:00,422 Epoch: [99][170/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0755 (0.0689) Prec@1 84.000 (88.167) Prec@5 99.000 (99.444) +2022-11-14 13:49:00,833 Epoch: [99][180/500] Time 0.031 (0.035) Data 0.002 (0.003) Loss 0.0684 (0.0689) Prec@1 88.000 (88.158) Prec@5 99.000 (99.421) +2022-11-14 13:49:01,223 Epoch: [99][190/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0921 (0.0701) Prec@1 85.000 (88.000) Prec@5 100.000 (99.450) +2022-11-14 13:49:01,667 Epoch: [99][200/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0649 (0.0698) Prec@1 90.000 (88.095) Prec@5 99.000 (99.429) +2022-11-14 13:49:02,035 Epoch: [99][210/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.0580 (0.0693) Prec@1 91.000 (88.227) Prec@5 99.000 (99.409) +2022-11-14 13:49:02,410 Epoch: [99][220/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0499 (0.0684) Prec@1 93.000 (88.435) Prec@5 100.000 (99.435) +2022-11-14 13:49:02,790 Epoch: [99][230/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0860 (0.0692) Prec@1 84.000 (88.250) Prec@5 99.000 (99.417) +2022-11-14 13:49:03,172 Epoch: [99][240/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0668 (0.0691) Prec@1 88.000 (88.240) Prec@5 100.000 (99.440) +2022-11-14 13:49:03,546 Epoch: [99][250/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0760 (0.0693) Prec@1 86.000 (88.154) Prec@5 99.000 (99.423) +2022-11-14 13:49:03,971 Epoch: [99][260/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0598 (0.0690) Prec@1 91.000 (88.259) Prec@5 100.000 (99.444) +2022-11-14 13:49:04,408 Epoch: [99][270/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0757 (0.0692) Prec@1 83.000 (88.071) Prec@5 100.000 (99.464) +2022-11-14 13:49:04,797 Epoch: [99][280/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.0726 (0.0693) Prec@1 88.000 (88.069) Prec@5 100.000 (99.483) +2022-11-14 13:49:05,185 Epoch: [99][290/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0584 (0.0690) Prec@1 92.000 (88.200) Prec@5 98.000 (99.433) +2022-11-14 13:49:05,579 Epoch: [99][300/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.1096 (0.0703) Prec@1 82.000 (88.000) Prec@5 97.000 (99.355) +2022-11-14 13:49:05,975 Epoch: [99][310/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0510 (0.0697) Prec@1 94.000 (88.188) Prec@5 99.000 (99.344) +2022-11-14 13:49:06,465 Epoch: [99][320/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0595 (0.0694) Prec@1 91.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 13:49:06,824 Epoch: [99][330/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0489 (0.0688) Prec@1 92.000 (88.382) Prec@5 99.000 (99.353) +2022-11-14 13:49:07,286 Epoch: [99][340/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0773 (0.0690) Prec@1 90.000 (88.429) Prec@5 99.000 (99.343) +2022-11-14 13:49:07,758 Epoch: [99][350/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0806 (0.0693) Prec@1 86.000 (88.361) Prec@5 98.000 (99.306) +2022-11-14 13:49:08,132 Epoch: [99][360/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0996 (0.0702) Prec@1 80.000 (88.135) Prec@5 100.000 (99.324) +2022-11-14 13:49:08,515 Epoch: [99][370/500] Time 0.035 (0.036) Data 0.003 (0.003) Loss 0.0651 (0.0700) Prec@1 88.000 (88.132) Prec@5 98.000 (99.289) +2022-11-14 13:49:08,954 Epoch: [99][380/500] Time 0.050 (0.036) Data 0.002 (0.003) Loss 0.0628 (0.0698) Prec@1 89.000 (88.154) Prec@5 100.000 (99.308) +2022-11-14 13:49:09,444 Epoch: [99][390/500] Time 0.045 (0.036) Data 0.003 (0.003) Loss 0.0692 (0.0698) Prec@1 87.000 (88.125) Prec@5 100.000 (99.325) +2022-11-14 13:49:09,858 Epoch: [99][400/500] Time 0.026 (0.036) Data 0.002 (0.003) Loss 0.0648 (0.0697) Prec@1 91.000 (88.195) Prec@5 100.000 (99.341) +2022-11-14 13:49:10,256 Epoch: [99][410/500] Time 0.031 (0.036) Data 0.002 (0.002) Loss 0.0907 (0.0702) Prec@1 87.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 13:49:10,680 Epoch: [99][420/500] Time 0.048 (0.036) Data 0.002 (0.002) Loss 0.0857 (0.0706) Prec@1 84.000 (88.070) Prec@5 100.000 (99.349) +2022-11-14 13:49:11,096 Epoch: [99][430/500] Time 0.031 (0.036) Data 0.002 (0.002) Loss 0.0899 (0.0710) Prec@1 81.000 (87.909) Prec@5 100.000 (99.364) +2022-11-14 13:49:11,490 Epoch: [99][440/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0729 (0.0710) Prec@1 87.000 (87.889) Prec@5 99.000 (99.356) +2022-11-14 13:49:11,900 Epoch: [99][450/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0693 (0.0710) Prec@1 89.000 (87.913) Prec@5 100.000 (99.370) +2022-11-14 13:49:12,276 Epoch: [99][460/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0765 (0.0711) Prec@1 84.000 (87.830) Prec@5 100.000 (99.383) +2022-11-14 13:49:12,654 Epoch: [99][470/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0517 (0.0707) Prec@1 93.000 (87.938) Prec@5 98.000 (99.354) +2022-11-14 13:49:13,033 Epoch: [99][480/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0927 (0.0712) Prec@1 84.000 (87.857) Prec@5 98.000 (99.327) +2022-11-14 13:49:13,455 Epoch: [99][490/500] Time 0.055 (0.036) Data 0.003 (0.002) Loss 0.0588 (0.0709) Prec@1 88.000 (87.860) Prec@5 100.000 (99.340) +2022-11-14 13:49:13,819 Epoch: [99][499/500] Time 0.034 (0.036) Data 0.001 (0.002) Loss 0.0600 (0.0707) Prec@1 89.000 (87.882) Prec@5 100.000 (99.353) +2022-11-14 13:49:14,122 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0861 (0.0861) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:49:14,130 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0825) Prec@1 88.000 (87.000) Prec@5 99.000 (98.500) +2022-11-14 13:49:14,138 Test: [2/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0833) Prec@1 84.000 (86.000) Prec@5 99.000 (98.667) +2022-11-14 13:49:14,151 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0889) Prec@1 83.000 (85.250) Prec@5 100.000 (99.000) +2022-11-14 13:49:14,160 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0915) Prec@1 84.000 (85.000) Prec@5 100.000 (99.200) +2022-11-14 13:49:14,167 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0845) Prec@1 92.000 (86.167) Prec@5 100.000 (99.333) +2022-11-14 13:49:14,177 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0827) Prec@1 89.000 (86.571) Prec@5 100.000 (99.429) +2022-11-14 13:49:14,189 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0874) Prec@1 79.000 (85.625) Prec@5 96.000 (99.000) +2022-11-14 13:49:14,200 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0880) Prec@1 85.000 (85.556) Prec@5 99.000 (99.000) +2022-11-14 13:49:14,210 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0855) Prec@1 90.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:49:14,223 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0848) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:49:14,235 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0856) Prec@1 86.000 (86.000) Prec@5 98.000 (98.917) +2022-11-14 13:49:14,246 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0854) Prec@1 84.000 (85.846) Prec@5 100.000 (99.000) +2022-11-14 13:49:14,258 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0849) Prec@1 87.000 (85.929) Prec@5 100.000 (99.071) +2022-11-14 13:49:14,271 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0857) Prec@1 83.000 (85.733) Prec@5 100.000 (99.133) +2022-11-14 13:49:14,284 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1285 (0.0884) Prec@1 74.000 (85.000) Prec@5 100.000 (99.188) +2022-11-14 13:49:14,295 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0867) Prec@1 88.000 (85.176) Prec@5 99.000 (99.176) +2022-11-14 13:49:14,309 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0869) Prec@1 81.000 (84.944) Prec@5 100.000 (99.222) +2022-11-14 13:49:14,322 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0874) Prec@1 83.000 (84.842) Prec@5 98.000 (99.158) +2022-11-14 13:49:14,336 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.0887) Prec@1 81.000 (84.650) Prec@5 98.000 (99.100) +2022-11-14 13:49:14,349 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0888) Prec@1 84.000 (84.619) Prec@5 99.000 (99.095) +2022-11-14 13:49:14,362 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0895) Prec@1 81.000 (84.455) Prec@5 99.000 (99.091) +2022-11-14 13:49:14,375 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0896) Prec@1 85.000 (84.478) Prec@5 100.000 (99.130) +2022-11-14 13:49:14,387 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0899) Prec@1 86.000 (84.542) Prec@5 100.000 (99.167) +2022-11-14 13:49:14,399 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1029 (0.0904) Prec@1 83.000 (84.480) Prec@5 98.000 (99.120) +2022-11-14 13:49:14,413 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0914) Prec@1 79.000 (84.269) Prec@5 99.000 (99.115) +2022-11-14 13:49:14,426 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0907) Prec@1 89.000 (84.444) Prec@5 100.000 (99.148) +2022-11-14 13:49:14,440 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0906) Prec@1 85.000 (84.464) Prec@5 99.000 (99.143) +2022-11-14 13:49:14,453 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0906) Prec@1 84.000 (84.448) Prec@5 99.000 (99.138) +2022-11-14 13:49:14,466 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0911) Prec@1 81.000 (84.333) Prec@5 98.000 (99.100) +2022-11-14 13:49:14,479 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0909) Prec@1 86.000 (84.387) Prec@5 100.000 (99.129) +2022-11-14 13:49:14,492 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0908) Prec@1 83.000 (84.344) Prec@5 100.000 (99.156) +2022-11-14 13:49:14,503 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0904) Prec@1 83.000 (84.303) Prec@5 100.000 (99.182) +2022-11-14 13:49:14,517 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0906) Prec@1 83.000 (84.265) Prec@5 99.000 (99.176) +2022-11-14 13:49:14,532 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0900) Prec@1 91.000 (84.457) Prec@5 98.000 (99.143) +2022-11-14 13:49:14,545 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0900) Prec@1 85.000 (84.472) Prec@5 100.000 (99.167) +2022-11-14 13:49:14,560 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0900) Prec@1 85.000 (84.486) Prec@5 96.000 (99.081) +2022-11-14 13:49:14,574 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0904) Prec@1 79.000 (84.342) Prec@5 99.000 (99.079) +2022-11-14 13:49:14,589 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0900) Prec@1 90.000 (84.487) Prec@5 99.000 (99.077) +2022-11-14 13:49:14,604 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0895) Prec@1 87.000 (84.550) Prec@5 100.000 (99.100) +2022-11-14 13:49:14,617 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0898) Prec@1 85.000 (84.561) Prec@5 97.000 (99.049) +2022-11-14 13:49:14,628 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0899) Prec@1 85.000 (84.571) Prec@5 98.000 (99.024) +2022-11-14 13:49:14,645 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0891) Prec@1 90.000 (84.698) Prec@5 97.000 (98.977) +2022-11-14 13:49:14,658 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0892) Prec@1 88.000 (84.773) Prec@5 98.000 (98.955) +2022-11-14 13:49:14,670 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0891) Prec@1 83.000 (84.733) Prec@5 100.000 (98.978) +2022-11-14 13:49:14,686 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0892) Prec@1 83.000 (84.696) Prec@5 98.000 (98.957) +2022-11-14 13:49:14,698 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0892) Prec@1 87.000 (84.745) Prec@5 99.000 (98.957) +2022-11-14 13:49:14,711 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0897) Prec@1 79.000 (84.625) Prec@5 99.000 (98.958) +2022-11-14 13:49:14,725 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0898) Prec@1 83.000 (84.592) Prec@5 100.000 (98.980) +2022-11-14 13:49:14,738 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1410 (0.0908) Prec@1 76.000 (84.420) Prec@5 99.000 (98.980) +2022-11-14 13:49:14,752 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0907) Prec@1 85.000 (84.431) Prec@5 100.000 (99.000) +2022-11-14 13:49:14,764 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0910) Prec@1 80.000 (84.346) Prec@5 99.000 (99.000) +2022-11-14 13:49:14,777 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0908) Prec@1 85.000 (84.358) Prec@5 99.000 (99.000) +2022-11-14 13:49:14,788 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0903) Prec@1 87.000 (84.407) Prec@5 100.000 (99.019) +2022-11-14 13:49:14,802 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0903) Prec@1 85.000 (84.418) Prec@5 100.000 (99.036) +2022-11-14 13:49:14,816 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0904) Prec@1 84.000 (84.411) Prec@5 99.000 (99.036) +2022-11-14 13:49:14,830 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0902) Prec@1 84.000 (84.404) Prec@5 100.000 (99.053) +2022-11-14 13:49:14,844 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0899) Prec@1 89.000 (84.483) Prec@5 98.000 (99.034) +2022-11-14 13:49:14,858 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0903) Prec@1 81.000 (84.424) Prec@5 100.000 (99.051) +2022-11-14 13:49:14,872 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0906) Prec@1 81.000 (84.367) Prec@5 99.000 (99.050) +2022-11-14 13:49:14,882 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0906) Prec@1 85.000 (84.377) Prec@5 98.000 (99.033) +2022-11-14 13:49:14,895 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0904) Prec@1 87.000 (84.419) Prec@5 99.000 (99.032) +2022-11-14 13:49:14,907 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0900) Prec@1 89.000 (84.492) Prec@5 99.000 (99.032) +2022-11-14 13:49:14,920 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0898) Prec@1 89.000 (84.562) Prec@5 99.000 (99.031) +2022-11-14 13:49:14,934 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.0901) Prec@1 80.000 (84.492) Prec@5 97.000 (99.000) +2022-11-14 13:49:14,948 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0904) Prec@1 84.000 (84.485) Prec@5 98.000 (98.985) +2022-11-14 13:49:14,961 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0898) Prec@1 92.000 (84.597) Prec@5 100.000 (99.000) +2022-11-14 13:49:14,975 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0900) Prec@1 81.000 (84.544) Prec@5 97.000 (98.971) +2022-11-14 13:49:14,988 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0898) Prec@1 89.000 (84.609) Prec@5 98.000 (98.957) +2022-11-14 13:49:15,002 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0899) Prec@1 82.000 (84.571) Prec@5 99.000 (98.957) +2022-11-14 13:49:15,015 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0902) Prec@1 82.000 (84.535) Prec@5 99.000 (98.958) +2022-11-14 13:49:15,029 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0902) Prec@1 82.000 (84.500) Prec@5 99.000 (98.958) +2022-11-14 13:49:15,042 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0898) Prec@1 91.000 (84.589) Prec@5 100.000 (98.973) +2022-11-14 13:49:15,054 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0897) Prec@1 87.000 (84.622) Prec@5 100.000 (98.986) +2022-11-14 13:49:15,066 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0896) Prec@1 84.000 (84.613) Prec@5 98.000 (98.973) +2022-11-14 13:49:15,079 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0895) Prec@1 86.000 (84.632) Prec@5 99.000 (98.974) +2022-11-14 13:49:15,092 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0895) Prec@1 85.000 (84.636) Prec@5 98.000 (98.961) +2022-11-14 13:49:15,106 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0897) Prec@1 82.000 (84.603) Prec@5 96.000 (98.923) +2022-11-14 13:49:15,120 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0899) Prec@1 81.000 (84.557) Prec@5 100.000 (98.937) +2022-11-14 13:49:15,133 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0899) Prec@1 86.000 (84.575) Prec@5 99.000 (98.938) +2022-11-14 13:49:15,147 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0899) Prec@1 82.000 (84.543) Prec@5 98.000 (98.926) +2022-11-14 13:49:15,159 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0898) Prec@1 87.000 (84.573) Prec@5 98.000 (98.915) +2022-11-14 13:49:15,173 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0898) Prec@1 85.000 (84.578) Prec@5 100.000 (98.928) +2022-11-14 13:49:15,187 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0899) Prec@1 84.000 (84.571) Prec@5 100.000 (98.940) +2022-11-14 13:49:15,201 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0899) Prec@1 83.000 (84.553) Prec@5 100.000 (98.953) +2022-11-14 13:49:15,213 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0901) Prec@1 82.000 (84.523) Prec@5 100.000 (98.965) +2022-11-14 13:49:15,225 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0900) Prec@1 86.000 (84.540) Prec@5 98.000 (98.954) +2022-11-14 13:49:15,240 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0899) Prec@1 88.000 (84.580) Prec@5 99.000 (98.955) +2022-11-14 13:49:15,254 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0898) Prec@1 84.000 (84.573) Prec@5 100.000 (98.966) +2022-11-14 13:49:15,267 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0900) Prec@1 83.000 (84.556) Prec@5 97.000 (98.944) +2022-11-14 13:49:15,283 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0900) Prec@1 85.000 (84.560) Prec@5 100.000 (98.956) +2022-11-14 13:49:15,295 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0897) Prec@1 89.000 (84.609) Prec@5 99.000 (98.957) +2022-11-14 13:49:15,307 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0898) Prec@1 86.000 (84.624) Prec@5 100.000 (98.968) +2022-11-14 13:49:15,320 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0898) Prec@1 84.000 (84.617) Prec@5 100.000 (98.979) +2022-11-14 13:49:15,334 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0898) Prec@1 84.000 (84.611) Prec@5 99.000 (98.979) +2022-11-14 13:49:15,348 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0896) Prec@1 86.000 (84.625) Prec@5 100.000 (98.990) +2022-11-14 13:49:15,362 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0894) Prec@1 87.000 (84.649) Prec@5 100.000 (99.000) +2022-11-14 13:49:15,376 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0894) Prec@1 86.000 (84.663) Prec@5 99.000 (99.000) +2022-11-14 13:49:15,388 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0897) Prec@1 80.000 (84.616) Prec@5 98.000 (98.990) +2022-11-14 13:49:15,402 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0898) Prec@1 82.000 (84.590) Prec@5 99.000 (98.990) +2022-11-14 13:49:15,461 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:49:15,802 Epoch: [100][0/500] Time 0.036 (0.036) Data 0.243 (0.243) Loss 0.0493 (0.0493) Prec@1 92.000 (92.000) Prec@5 98.000 (98.000) +2022-11-14 13:49:16,038 Epoch: [100][10/500] Time 0.020 (0.022) Data 0.002 (0.024) Loss 0.0754 (0.0623) Prec@1 85.000 (88.500) Prec@5 99.000 (98.500) +2022-11-14 13:49:16,347 Epoch: [100][20/500] Time 0.041 (0.024) Data 0.002 (0.013) Loss 0.0542 (0.0596) Prec@1 92.000 (89.667) Prec@5 99.000 (98.667) +2022-11-14 13:49:16,814 Epoch: [100][30/500] Time 0.044 (0.030) Data 0.002 (0.010) Loss 0.0844 (0.0658) Prec@1 85.000 (88.500) Prec@5 97.000 (98.250) +2022-11-14 13:49:17,282 Epoch: [100][40/500] Time 0.043 (0.033) Data 0.002 (0.008) Loss 0.0741 (0.0675) Prec@1 87.000 (88.200) Prec@5 99.000 (98.400) +2022-11-14 13:49:17,753 Epoch: [100][50/500] Time 0.044 (0.034) Data 0.002 (0.007) Loss 0.0834 (0.0701) Prec@1 88.000 (88.167) Prec@5 98.000 (98.333) +2022-11-14 13:49:18,278 Epoch: [100][60/500] Time 0.042 (0.036) Data 0.002 (0.006) Loss 0.0467 (0.0668) Prec@1 93.000 (88.857) Prec@5 99.000 (98.429) +2022-11-14 13:49:18,784 Epoch: [100][70/500] Time 0.043 (0.038) Data 0.003 (0.005) Loss 0.0717 (0.0674) Prec@1 88.000 (88.750) Prec@5 99.000 (98.500) +2022-11-14 13:49:19,294 Epoch: [100][80/500] Time 0.056 (0.039) Data 0.002 (0.005) Loss 0.0526 (0.0658) Prec@1 92.000 (89.111) Prec@5 100.000 (98.667) +2022-11-14 13:49:19,801 Epoch: [100][90/500] Time 0.044 (0.039) Data 0.002 (0.005) Loss 0.0708 (0.0663) Prec@1 88.000 (89.000) Prec@5 100.000 (98.800) +2022-11-14 13:49:20,301 Epoch: [100][100/500] Time 0.051 (0.040) Data 0.002 (0.004) Loss 0.0551 (0.0652) Prec@1 90.000 (89.091) Prec@5 99.000 (98.818) +2022-11-14 13:49:20,810 Epoch: [100][110/500] Time 0.053 (0.040) Data 0.002 (0.004) Loss 0.0839 (0.0668) Prec@1 86.000 (88.833) Prec@5 99.000 (98.833) +2022-11-14 13:49:21,297 Epoch: [100][120/500] Time 0.042 (0.041) Data 0.002 (0.004) Loss 0.0683 (0.0669) Prec@1 87.000 (88.692) Prec@5 100.000 (98.923) +2022-11-14 13:49:21,787 Epoch: [100][130/500] Time 0.044 (0.041) Data 0.002 (0.004) Loss 0.0658 (0.0668) Prec@1 89.000 (88.714) Prec@5 100.000 (99.000) +2022-11-14 13:49:22,269 Epoch: [100][140/500] Time 0.042 (0.041) Data 0.002 (0.004) Loss 0.0945 (0.0687) Prec@1 84.000 (88.400) Prec@5 100.000 (99.067) +2022-11-14 13:49:22,738 Epoch: [100][150/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0788 (0.0693) Prec@1 83.000 (88.062) Prec@5 100.000 (99.125) +2022-11-14 13:49:23,200 Epoch: [100][160/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0584 (0.0687) Prec@1 91.000 (88.235) Prec@5 100.000 (99.176) +2022-11-14 13:49:23,678 Epoch: [100][170/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.1051 (0.0707) Prec@1 85.000 (88.056) Prec@5 98.000 (99.111) +2022-11-14 13:49:24,188 Epoch: [100][180/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0727 (0.0708) Prec@1 86.000 (87.947) Prec@5 99.000 (99.105) +2022-11-14 13:49:24,657 Epoch: [100][190/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0506 (0.0698) Prec@1 92.000 (88.150) Prec@5 100.000 (99.150) +2022-11-14 13:49:25,275 Epoch: [100][200/500] Time 0.069 (0.042) Data 0.002 (0.003) Loss 0.0810 (0.0703) Prec@1 89.000 (88.190) Prec@5 99.000 (99.143) +2022-11-14 13:49:25,915 Epoch: [100][210/500] Time 0.059 (0.043) Data 0.004 (0.003) Loss 0.0731 (0.0704) Prec@1 88.000 (88.182) Prec@5 100.000 (99.182) +2022-11-14 13:49:26,555 Epoch: [100][220/500] Time 0.063 (0.043) Data 0.002 (0.003) Loss 0.0810 (0.0709) Prec@1 89.000 (88.217) Prec@5 99.000 (99.174) +2022-11-14 13:49:27,092 Epoch: [100][230/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0926 (0.0718) Prec@1 84.000 (88.042) Prec@5 100.000 (99.208) +2022-11-14 13:49:27,629 Epoch: [100][240/500] Time 0.075 (0.044) Data 0.002 (0.003) Loss 0.0647 (0.0715) Prec@1 88.000 (88.040) Prec@5 99.000 (99.200) +2022-11-14 13:49:28,099 Epoch: [100][250/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0842 (0.0720) Prec@1 87.000 (88.000) Prec@5 99.000 (99.192) +2022-11-14 13:49:28,565 Epoch: [100][260/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0767 (0.0722) Prec@1 86.000 (87.926) Prec@5 100.000 (99.222) +2022-11-14 13:49:29,040 Epoch: [100][270/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0761 (0.0723) Prec@1 89.000 (87.964) Prec@5 99.000 (99.214) +2022-11-14 13:49:29,503 Epoch: [100][280/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0954 (0.0731) Prec@1 83.000 (87.793) Prec@5 100.000 (99.241) +2022-11-14 13:49:30,114 Epoch: [100][290/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0796 (0.0733) Prec@1 86.000 (87.733) Prec@5 97.000 (99.167) +2022-11-14 13:49:30,610 Epoch: [100][300/500] Time 0.042 (0.044) Data 0.001 (0.003) Loss 0.0810 (0.0736) Prec@1 86.000 (87.677) Prec@5 100.000 (99.194) +2022-11-14 13:49:31,095 Epoch: [100][310/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0665 (0.0734) Prec@1 87.000 (87.656) Prec@5 100.000 (99.219) +2022-11-14 13:49:31,563 Epoch: [100][320/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0794 (0.0736) Prec@1 89.000 (87.697) Prec@5 99.000 (99.212) +2022-11-14 13:49:32,125 Epoch: [100][330/500] Time 0.042 (0.044) Data 0.003 (0.003) Loss 0.0668 (0.0734) Prec@1 89.000 (87.735) Prec@5 99.000 (99.206) +2022-11-14 13:49:32,589 Epoch: [100][340/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0526 (0.0728) Prec@1 91.000 (87.829) Prec@5 99.000 (99.200) +2022-11-14 13:49:33,134 Epoch: [100][350/500] Time 0.036 (0.044) Data 0.002 (0.003) Loss 0.0802 (0.0730) Prec@1 88.000 (87.833) Prec@5 99.000 (99.194) +2022-11-14 13:49:33,671 Epoch: [100][360/500] Time 0.072 (0.044) Data 0.002 (0.003) Loss 0.0497 (0.0723) Prec@1 90.000 (87.892) Prec@5 100.000 (99.216) +2022-11-14 13:49:34,171 Epoch: [100][370/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0863 (0.0727) Prec@1 85.000 (87.816) Prec@5 98.000 (99.184) +2022-11-14 13:49:34,705 Epoch: [100][380/500] Time 0.035 (0.044) Data 0.002 (0.003) Loss 0.0822 (0.0730) Prec@1 86.000 (87.769) Prec@5 98.000 (99.154) +2022-11-14 13:49:35,241 Epoch: [100][390/500] Time 0.068 (0.044) Data 0.002 (0.003) Loss 0.0797 (0.0731) Prec@1 86.000 (87.725) Prec@5 99.000 (99.150) +2022-11-14 13:49:35,715 Epoch: [100][400/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.1036 (0.0739) Prec@1 81.000 (87.561) Prec@5 97.000 (99.098) +2022-11-14 13:49:36,275 Epoch: [100][410/500] Time 0.034 (0.044) Data 0.002 (0.003) Loss 0.0886 (0.0742) Prec@1 85.000 (87.500) Prec@5 99.000 (99.095) +2022-11-14 13:49:36,773 Epoch: [100][420/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0808 (0.0744) Prec@1 89.000 (87.535) Prec@5 100.000 (99.116) +2022-11-14 13:49:37,287 Epoch: [100][430/500] Time 0.052 (0.044) Data 0.002 (0.002) Loss 0.0602 (0.0740) Prec@1 91.000 (87.614) Prec@5 100.000 (99.136) +2022-11-14 13:49:37,600 Epoch: [100][440/500] Time 0.026 (0.044) Data 0.002 (0.002) Loss 0.0757 (0.0741) Prec@1 89.000 (87.644) Prec@5 99.000 (99.133) +2022-11-14 13:49:37,902 Epoch: [100][450/500] Time 0.027 (0.044) Data 0.002 (0.002) Loss 0.0661 (0.0739) Prec@1 89.000 (87.674) Prec@5 98.000 (99.109) +2022-11-14 13:49:38,198 Epoch: [100][460/500] Time 0.024 (0.043) Data 0.002 (0.002) Loss 0.0552 (0.0735) Prec@1 90.000 (87.723) Prec@5 99.000 (99.106) +2022-11-14 13:49:38,491 Epoch: [100][470/500] Time 0.027 (0.043) Data 0.002 (0.002) Loss 0.0647 (0.0733) Prec@1 88.000 (87.729) Prec@5 100.000 (99.125) +2022-11-14 13:49:38,784 Epoch: [100][480/500] Time 0.027 (0.042) Data 0.002 (0.002) Loss 0.0516 (0.0729) Prec@1 94.000 (87.857) Prec@5 99.000 (99.122) +2022-11-14 13:49:39,082 Epoch: [100][490/500] Time 0.028 (0.042) Data 0.002 (0.002) Loss 0.0873 (0.0732) Prec@1 87.000 (87.840) Prec@5 100.000 (99.140) +2022-11-14 13:49:39,355 Epoch: [100][499/500] Time 0.029 (0.042) Data 0.002 (0.002) Loss 0.0942 (0.0736) Prec@1 85.000 (87.784) Prec@5 99.000 (99.137) +2022-11-14 13:49:39,636 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0839 (0.0839) Prec@1 82.000 (82.000) Prec@5 100.000 (100.000) +2022-11-14 13:49:39,645 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.0912) Prec@1 84.000 (83.000) Prec@5 98.000 (99.000) +2022-11-14 13:49:39,653 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0963) Prec@1 79.000 (81.667) Prec@5 100.000 (99.333) +2022-11-14 13:49:39,664 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1226 (0.1029) Prec@1 79.000 (81.000) Prec@5 99.000 (99.250) +2022-11-14 13:49:39,673 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.1046) Prec@1 81.000 (81.000) Prec@5 99.000 (99.200) +2022-11-14 13:49:39,681 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0945) Prec@1 93.000 (83.000) Prec@5 99.000 (99.167) +2022-11-14 13:49:39,688 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0933) Prec@1 85.000 (83.286) Prec@5 100.000 (99.286) +2022-11-14 13:49:39,696 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0950) Prec@1 82.000 (83.125) Prec@5 97.000 (99.000) +2022-11-14 13:49:39,705 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.0968) Prec@1 79.000 (82.667) Prec@5 99.000 (99.000) +2022-11-14 13:49:39,715 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0949) Prec@1 87.000 (83.100) Prec@5 97.000 (98.800) +2022-11-14 13:49:39,722 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0940) Prec@1 87.000 (83.455) Prec@5 100.000 (98.909) +2022-11-14 13:49:39,731 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0947) Prec@1 84.000 (83.500) Prec@5 99.000 (98.917) +2022-11-14 13:49:39,742 Test: [12/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0949) Prec@1 80.000 (83.231) Prec@5 100.000 (99.000) +2022-11-14 13:49:39,752 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0946) Prec@1 85.000 (83.357) Prec@5 99.000 (99.000) +2022-11-14 13:49:39,762 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0938) Prec@1 86.000 (83.533) Prec@5 99.000 (99.000) +2022-11-14 13:49:39,770 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0948) Prec@1 79.000 (83.250) Prec@5 98.000 (98.938) +2022-11-14 13:49:39,781 Test: [16/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0939) Prec@1 87.000 (83.471) Prec@5 99.000 (98.941) +2022-11-14 13:49:39,791 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0934) Prec@1 86.000 (83.611) Prec@5 100.000 (99.000) +2022-11-14 13:49:39,800 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0944) Prec@1 77.000 (83.263) Prec@5 99.000 (99.000) +2022-11-14 13:49:39,810 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1272 (0.0960) Prec@1 79.000 (83.050) Prec@5 97.000 (98.900) +2022-11-14 13:49:39,819 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0964) Prec@1 79.000 (82.857) Prec@5 98.000 (98.857) +2022-11-14 13:49:39,828 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0970) Prec@1 79.000 (82.682) Prec@5 99.000 (98.864) +2022-11-14 13:49:39,838 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0976) Prec@1 80.000 (82.565) Prec@5 98.000 (98.826) +2022-11-14 13:49:39,847 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0974) Prec@1 82.000 (82.542) Prec@5 100.000 (98.875) +2022-11-14 13:49:39,857 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1216 (0.0984) Prec@1 81.000 (82.480) Prec@5 99.000 (98.880) +2022-11-14 13:49:39,867 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1215 (0.0993) Prec@1 80.000 (82.385) Prec@5 95.000 (98.731) +2022-11-14 13:49:39,876 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0979) Prec@1 87.000 (82.556) Prec@5 100.000 (98.778) +2022-11-14 13:49:39,886 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0982) Prec@1 84.000 (82.607) Prec@5 99.000 (98.786) +2022-11-14 13:49:39,895 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0977) Prec@1 86.000 (82.724) Prec@5 98.000 (98.759) +2022-11-14 13:49:39,904 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.0985) Prec@1 80.000 (82.633) Prec@5 99.000 (98.767) +2022-11-14 13:49:39,913 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0981) Prec@1 84.000 (82.677) Prec@5 100.000 (98.806) +2022-11-14 13:49:39,923 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0983) Prec@1 82.000 (82.656) Prec@5 99.000 (98.812) +2022-11-14 13:49:39,931 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0986) Prec@1 83.000 (82.667) Prec@5 98.000 (98.788) +2022-11-14 13:49:39,940 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.0994) Prec@1 76.000 (82.471) Prec@5 100.000 (98.824) +2022-11-14 13:49:39,950 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0991) Prec@1 82.000 (82.457) Prec@5 98.000 (98.800) +2022-11-14 13:49:39,958 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0991) Prec@1 85.000 (82.528) Prec@5 98.000 (98.778) +2022-11-14 13:49:39,966 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0994) Prec@1 76.000 (82.351) Prec@5 96.000 (98.703) +2022-11-14 13:49:39,975 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1406 (0.1005) Prec@1 77.000 (82.211) Prec@5 97.000 (98.658) +2022-11-14 13:49:39,984 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0999) Prec@1 86.000 (82.308) Prec@5 99.000 (98.667) +2022-11-14 13:49:39,992 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.1003) Prec@1 81.000 (82.275) Prec@5 97.000 (98.625) +2022-11-14 13:49:40,000 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.1007) Prec@1 79.000 (82.195) Prec@5 98.000 (98.610) +2022-11-14 13:49:40,009 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.1007) Prec@1 86.000 (82.286) Prec@5 97.000 (98.571) +2022-11-14 13:49:40,019 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.1001) Prec@1 88.000 (82.419) Prec@5 99.000 (98.581) +2022-11-14 13:49:40,028 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0996) Prec@1 86.000 (82.500) Prec@5 98.000 (98.568) +2022-11-14 13:49:40,037 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0996) Prec@1 82.000 (82.489) Prec@5 99.000 (98.578) +2022-11-14 13:49:40,047 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.1000) Prec@1 82.000 (82.478) Prec@5 99.000 (98.587) +2022-11-14 13:49:40,056 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.1004) Prec@1 80.000 (82.426) Prec@5 100.000 (98.617) +2022-11-14 13:49:40,066 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1264 (0.1009) Prec@1 78.000 (82.333) Prec@5 98.000 (98.604) +2022-11-14 13:49:40,076 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.1004) Prec@1 85.000 (82.388) Prec@5 100.000 (98.633) +2022-11-14 13:49:40,085 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1007) Prec@1 81.000 (82.360) Prec@5 98.000 (98.620) +2022-11-14 13:49:40,095 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.1007) Prec@1 83.000 (82.373) Prec@5 97.000 (98.588) +2022-11-14 13:49:40,105 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1252 (0.1011) Prec@1 76.000 (82.250) Prec@5 98.000 (98.577) +2022-11-14 13:49:40,116 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.1011) Prec@1 85.000 (82.302) Prec@5 99.000 (98.585) +2022-11-14 13:49:40,126 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.1005) Prec@1 90.000 (82.444) Prec@5 99.000 (98.593) +2022-11-14 13:49:40,138 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.1007) Prec@1 81.000 (82.418) Prec@5 100.000 (98.618) +2022-11-14 13:49:40,148 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.1006) Prec@1 85.000 (82.464) Prec@5 99.000 (98.625) +2022-11-14 13:49:40,160 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.1005) Prec@1 84.000 (82.491) Prec@5 99.000 (98.632) +2022-11-14 13:49:40,170 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.1001) Prec@1 85.000 (82.534) Prec@5 98.000 (98.621) +2022-11-14 13:49:40,181 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1248 (0.1005) Prec@1 76.000 (82.424) Prec@5 98.000 (98.610) +2022-11-14 13:49:40,191 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.1005) Prec@1 83.000 (82.433) Prec@5 98.000 (98.600) +2022-11-14 13:49:40,202 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.1005) Prec@1 83.000 (82.443) Prec@5 99.000 (98.607) +2022-11-14 13:49:40,211 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.1002) Prec@1 85.000 (82.484) Prec@5 100.000 (98.629) +2022-11-14 13:49:40,221 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0999) Prec@1 87.000 (82.556) Prec@5 99.000 (98.635) +2022-11-14 13:49:40,229 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0995) Prec@1 87.000 (82.625) Prec@5 99.000 (98.641) +2022-11-14 13:49:40,238 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0996) Prec@1 81.000 (82.600) Prec@5 99.000 (98.646) +2022-11-14 13:49:40,247 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1331 (0.1001) Prec@1 76.000 (82.500) Prec@5 100.000 (98.667) +2022-11-14 13:49:40,257 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0996) Prec@1 89.000 (82.597) Prec@5 99.000 (98.672) +2022-11-14 13:49:40,266 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0995) Prec@1 85.000 (82.632) Prec@5 100.000 (98.691) +2022-11-14 13:49:40,275 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0995) Prec@1 86.000 (82.681) Prec@5 97.000 (98.667) +2022-11-14 13:49:40,284 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1239 (0.0998) Prec@1 79.000 (82.629) Prec@5 94.000 (98.600) +2022-11-14 13:49:40,291 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.1000) Prec@1 82.000 (82.620) Prec@5 98.000 (98.592) +2022-11-14 13:49:40,299 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.1001) Prec@1 81.000 (82.597) Prec@5 99.000 (98.597) +2022-11-14 13:49:40,308 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0999) Prec@1 86.000 (82.644) Prec@5 100.000 (98.616) +2022-11-14 13:49:40,318 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0996) Prec@1 88.000 (82.716) Prec@5 99.000 (98.622) +2022-11-14 13:49:40,328 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.1000) Prec@1 82.000 (82.707) Prec@5 99.000 (98.627) +2022-11-14 13:49:40,337 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0996) Prec@1 89.000 (82.789) Prec@5 99.000 (98.632) +2022-11-14 13:49:40,347 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0994) Prec@1 83.000 (82.792) Prec@5 100.000 (98.649) +2022-11-14 13:49:40,356 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.0998) Prec@1 78.000 (82.731) Prec@5 97.000 (98.628) +2022-11-14 13:49:40,365 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0999) Prec@1 85.000 (82.759) Prec@5 99.000 (98.633) +2022-11-14 13:49:40,374 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0998) Prec@1 83.000 (82.763) Prec@5 96.000 (98.600) +2022-11-14 13:49:40,383 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0997) Prec@1 86.000 (82.802) Prec@5 98.000 (98.593) +2022-11-14 13:49:40,393 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0999) Prec@1 80.000 (82.768) Prec@5 99.000 (98.598) +2022-11-14 13:49:40,402 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.1001) Prec@1 79.000 (82.723) Prec@5 99.000 (98.602) +2022-11-14 13:49:40,411 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.1001) Prec@1 82.000 (82.714) Prec@5 99.000 (98.607) +2022-11-14 13:49:40,422 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.1002) Prec@1 82.000 (82.706) Prec@5 98.000 (98.600) +2022-11-14 13:49:40,430 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.1004) Prec@1 78.000 (82.651) Prec@5 100.000 (98.616) +2022-11-14 13:49:40,439 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.1003) Prec@1 83.000 (82.655) Prec@5 98.000 (98.609) +2022-11-14 13:49:40,451 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.1000) Prec@1 88.000 (82.716) Prec@5 98.000 (98.602) +2022-11-14 13:49:40,461 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0998) Prec@1 88.000 (82.775) Prec@5 100.000 (98.618) +2022-11-14 13:49:40,471 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0997) Prec@1 85.000 (82.800) Prec@5 99.000 (98.622) +2022-11-14 13:49:40,481 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0996) Prec@1 85.000 (82.824) Prec@5 100.000 (98.637) +2022-11-14 13:49:40,490 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0989) Prec@1 95.000 (82.957) Prec@5 99.000 (98.641) +2022-11-14 13:49:40,499 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.0991) Prec@1 78.000 (82.903) Prec@5 100.000 (98.656) +2022-11-14 13:49:40,508 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1276 (0.0994) Prec@1 78.000 (82.851) Prec@5 96.000 (98.628) +2022-11-14 13:49:40,517 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0994) Prec@1 83.000 (82.853) Prec@5 99.000 (98.632) +2022-11-14 13:49:40,527 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0991) Prec@1 89.000 (82.917) Prec@5 100.000 (98.646) +2022-11-14 13:49:40,535 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0988) Prec@1 87.000 (82.959) Prec@5 99.000 (98.649) +2022-11-14 13:49:40,543 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1307 (0.0991) Prec@1 80.000 (82.929) Prec@5 100.000 (98.663) +2022-11-14 13:49:40,552 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0993) Prec@1 78.000 (82.879) Prec@5 100.000 (98.677) +2022-11-14 13:49:40,561 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0993) Prec@1 83.000 (82.880) Prec@5 99.000 (98.680) +2022-11-14 13:49:40,619 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:49:40,910 Epoch: [101][0/500] Time 0.022 (0.022) Data 0.212 (0.212) Loss 0.0632 (0.0632) Prec@1 90.000 (90.000) Prec@5 98.000 (98.000) +2022-11-14 13:49:41,116 Epoch: [101][10/500] Time 0.016 (0.019) Data 0.001 (0.021) Loss 0.0924 (0.0778) Prec@1 83.000 (86.500) Prec@5 100.000 (99.000) +2022-11-14 13:49:41,345 Epoch: [101][20/500] Time 0.024 (0.019) Data 0.002 (0.012) Loss 0.0837 (0.0798) Prec@1 84.000 (85.667) Prec@5 100.000 (99.333) +2022-11-14 13:49:41,701 Epoch: [101][30/500] Time 0.032 (0.023) Data 0.002 (0.009) Loss 0.0794 (0.0797) Prec@1 86.000 (85.750) Prec@5 100.000 (99.500) +2022-11-14 13:49:41,975 Epoch: [101][40/500] Time 0.022 (0.023) Data 0.002 (0.007) Loss 0.0964 (0.0830) Prec@1 83.000 (85.200) Prec@5 98.000 (99.200) +2022-11-14 13:49:42,294 Epoch: [101][50/500] Time 0.037 (0.024) Data 0.002 (0.006) Loss 0.0864 (0.0836) Prec@1 84.000 (85.000) Prec@5 100.000 (99.333) +2022-11-14 13:49:42,570 Epoch: [101][60/500] Time 0.023 (0.024) Data 0.001 (0.005) Loss 0.0496 (0.0787) Prec@1 92.000 (86.000) Prec@5 99.000 (99.286) +2022-11-14 13:49:42,853 Epoch: [101][70/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0519 (0.0754) Prec@1 90.000 (86.500) Prec@5 100.000 (99.375) +2022-11-14 13:49:43,292 Epoch: [101][80/500] Time 0.040 (0.026) Data 0.002 (0.004) Loss 0.0767 (0.0755) Prec@1 86.000 (86.444) Prec@5 98.000 (99.222) +2022-11-14 13:49:43,733 Epoch: [101][90/500] Time 0.040 (0.028) Data 0.002 (0.004) Loss 0.0430 (0.0723) Prec@1 91.000 (86.900) Prec@5 100.000 (99.300) +2022-11-14 13:49:44,174 Epoch: [101][100/500] Time 0.046 (0.029) Data 0.002 (0.004) Loss 0.0698 (0.0720) Prec@1 89.000 (87.091) Prec@5 100.000 (99.364) +2022-11-14 13:49:44,611 Epoch: [101][110/500] Time 0.041 (0.030) Data 0.002 (0.004) Loss 0.0550 (0.0706) Prec@1 90.000 (87.333) Prec@5 100.000 (99.417) +2022-11-14 13:49:45,060 Epoch: [101][120/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0661 (0.0703) Prec@1 89.000 (87.462) Prec@5 100.000 (99.462) +2022-11-14 13:49:45,501 Epoch: [101][130/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0617 (0.0697) Prec@1 90.000 (87.643) Prec@5 100.000 (99.500) +2022-11-14 13:49:45,930 Epoch: [101][140/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0503 (0.0684) Prec@1 94.000 (88.067) Prec@5 100.000 (99.533) +2022-11-14 13:49:46,375 Epoch: [101][150/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0773 (0.0689) Prec@1 85.000 (87.875) Prec@5 99.000 (99.500) +2022-11-14 13:49:46,810 Epoch: [101][160/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0730 (0.0692) Prec@1 86.000 (87.765) Prec@5 100.000 (99.529) +2022-11-14 13:49:47,254 Epoch: [101][170/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0813 (0.0698) Prec@1 85.000 (87.611) Prec@5 97.000 (99.389) +2022-11-14 13:49:47,703 Epoch: [101][180/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0592 (0.0693) Prec@1 91.000 (87.789) Prec@5 100.000 (99.421) +2022-11-14 13:49:48,134 Epoch: [101][190/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0500 (0.0683) Prec@1 91.000 (87.950) Prec@5 100.000 (99.450) +2022-11-14 13:49:48,567 Epoch: [101][200/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0714 (0.0685) Prec@1 88.000 (87.952) Prec@5 98.000 (99.381) +2022-11-14 13:49:49,007 Epoch: [101][210/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0729 (0.0687) Prec@1 88.000 (87.955) Prec@5 100.000 (99.409) +2022-11-14 13:49:49,452 Epoch: [101][220/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0829 (0.0693) Prec@1 86.000 (87.870) Prec@5 99.000 (99.391) +2022-11-14 13:49:49,897 Epoch: [101][230/500] Time 0.054 (0.035) Data 0.002 (0.003) Loss 0.0555 (0.0687) Prec@1 91.000 (88.000) Prec@5 99.000 (99.375) +2022-11-14 13:49:50,328 Epoch: [101][240/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0690 (0.0687) Prec@1 89.000 (88.040) Prec@5 98.000 (99.320) +2022-11-14 13:49:50,754 Epoch: [101][250/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0685 (0.0687) Prec@1 90.000 (88.115) Prec@5 99.000 (99.308) +2022-11-14 13:49:51,189 Epoch: [101][260/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0829 (0.0692) Prec@1 86.000 (88.037) Prec@5 100.000 (99.333) +2022-11-14 13:49:51,618 Epoch: [101][270/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0555 (0.0687) Prec@1 90.000 (88.107) Prec@5 100.000 (99.357) +2022-11-14 13:49:52,058 Epoch: [101][280/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0592 (0.0684) Prec@1 88.000 (88.103) Prec@5 99.000 (99.345) +2022-11-14 13:49:52,503 Epoch: [101][290/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0711 (0.0685) Prec@1 88.000 (88.100) Prec@5 99.000 (99.333) +2022-11-14 13:49:52,953 Epoch: [101][300/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0847 (0.0690) Prec@1 86.000 (88.032) Prec@5 100.000 (99.355) +2022-11-14 13:49:53,395 Epoch: [101][310/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0711 (0.0691) Prec@1 88.000 (88.031) Prec@5 99.000 (99.344) +2022-11-14 13:49:53,821 Epoch: [101][320/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0704 (0.0691) Prec@1 88.000 (88.030) Prec@5 99.000 (99.333) +2022-11-14 13:49:54,254 Epoch: [101][330/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0632 (0.0690) Prec@1 90.000 (88.088) Prec@5 99.000 (99.324) +2022-11-14 13:49:54,690 Epoch: [101][340/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0667 (0.0689) Prec@1 90.000 (88.143) Prec@5 100.000 (99.343) +2022-11-14 13:49:55,112 Epoch: [101][350/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0604 (0.0687) Prec@1 89.000 (88.167) Prec@5 100.000 (99.361) +2022-11-14 13:49:55,537 Epoch: [101][360/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0516 (0.0682) Prec@1 92.000 (88.270) Prec@5 100.000 (99.378) +2022-11-14 13:49:55,969 Epoch: [101][370/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0941 (0.0689) Prec@1 87.000 (88.237) Prec@5 100.000 (99.395) +2022-11-14 13:49:56,402 Epoch: [101][380/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0857 (0.0693) Prec@1 87.000 (88.205) Prec@5 96.000 (99.308) +2022-11-14 13:49:56,841 Epoch: [101][390/500] Time 0.042 (0.036) Data 0.001 (0.002) Loss 0.0526 (0.0689) Prec@1 92.000 (88.300) Prec@5 100.000 (99.325) +2022-11-14 13:49:57,274 Epoch: [101][400/500] Time 0.041 (0.036) Data 0.001 (0.002) Loss 0.0621 (0.0687) Prec@1 89.000 (88.317) Prec@5 99.000 (99.317) +2022-11-14 13:49:57,709 Epoch: [101][410/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.0699 (0.0688) Prec@1 87.000 (88.286) Prec@5 100.000 (99.333) +2022-11-14 13:49:58,136 Epoch: [101][420/500] Time 0.039 (0.036) Data 0.001 (0.002) Loss 0.0801 (0.0690) Prec@1 83.000 (88.163) Prec@5 98.000 (99.302) +2022-11-14 13:49:58,563 Epoch: [101][430/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0528 (0.0686) Prec@1 92.000 (88.250) Prec@5 100.000 (99.318) +2022-11-14 13:49:59,004 Epoch: [101][440/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0630 (0.0685) Prec@1 90.000 (88.289) Prec@5 99.000 (99.311) +2022-11-14 13:49:59,434 Epoch: [101][450/500] Time 0.048 (0.036) Data 0.002 (0.002) Loss 0.0634 (0.0684) Prec@1 87.000 (88.261) Prec@5 100.000 (99.326) +2022-11-14 13:49:59,867 Epoch: [101][460/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.0474 (0.0680) Prec@1 92.000 (88.340) Prec@5 100.000 (99.340) +2022-11-14 13:50:00,307 Epoch: [101][470/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0571 (0.0677) Prec@1 91.000 (88.396) Prec@5 100.000 (99.354) +2022-11-14 13:50:00,744 Epoch: [101][480/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0702 (0.0678) Prec@1 88.000 (88.388) Prec@5 99.000 (99.347) +2022-11-14 13:50:01,176 Epoch: [101][490/500] Time 0.046 (0.037) Data 0.003 (0.002) Loss 0.0766 (0.0680) Prec@1 86.000 (88.340) Prec@5 100.000 (99.360) +2022-11-14 13:50:01,570 Epoch: [101][499/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0881 (0.0684) Prec@1 85.000 (88.275) Prec@5 99.000 (99.353) +2022-11-14 13:50:01,881 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0608) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 13:50:01,889 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0735) Prec@1 85.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:50:01,900 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.0882) Prec@1 79.000 (83.667) Prec@5 100.000 (99.333) +2022-11-14 13:50:01,912 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0941) Prec@1 80.000 (82.750) Prec@5 97.000 (98.750) +2022-11-14 13:50:01,922 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0920) Prec@1 83.000 (82.800) Prec@5 100.000 (99.000) +2022-11-14 13:50:01,930 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0855) Prec@1 91.000 (84.167) Prec@5 98.000 (98.833) +2022-11-14 13:50:01,938 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0824) Prec@1 90.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:50:01,947 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.0863) Prec@1 82.000 (84.625) Prec@5 98.000 (98.875) +2022-11-14 13:50:01,956 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0876) Prec@1 85.000 (84.667) Prec@5 99.000 (98.889) +2022-11-14 13:50:01,965 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0867) Prec@1 84.000 (84.600) Prec@5 98.000 (98.800) +2022-11-14 13:50:01,974 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0870) Prec@1 83.000 (84.455) Prec@5 97.000 (98.636) +2022-11-14 13:50:01,984 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0880) Prec@1 83.000 (84.333) Prec@5 100.000 (98.750) +2022-11-14 13:50:01,992 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0871) Prec@1 88.000 (84.615) Prec@5 100.000 (98.846) +2022-11-14 13:50:02,002 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0853) Prec@1 90.000 (85.000) Prec@5 100.000 (98.929) +2022-11-14 13:50:02,012 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0865) Prec@1 82.000 (84.800) Prec@5 99.000 (98.933) +2022-11-14 13:50:02,021 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0864) Prec@1 85.000 (84.812) Prec@5 98.000 (98.875) +2022-11-14 13:50:02,031 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0852) Prec@1 87.000 (84.941) Prec@5 99.000 (98.882) +2022-11-14 13:50:02,040 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0865) Prec@1 81.000 (84.722) Prec@5 100.000 (98.944) +2022-11-14 13:50:02,049 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0878) Prec@1 79.000 (84.421) Prec@5 96.000 (98.789) +2022-11-14 13:50:02,058 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0893) Prec@1 80.000 (84.200) Prec@5 98.000 (98.750) +2022-11-14 13:50:02,068 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0903) Prec@1 81.000 (84.048) Prec@5 100.000 (98.810) +2022-11-14 13:50:02,077 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0901) Prec@1 86.000 (84.136) Prec@5 98.000 (98.773) +2022-11-14 13:50:02,085 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.0912) Prec@1 84.000 (84.130) Prec@5 99.000 (98.783) +2022-11-14 13:50:02,095 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0910) Prec@1 86.000 (84.208) Prec@5 100.000 (98.833) +2022-11-14 13:50:02,103 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0910) Prec@1 85.000 (84.240) Prec@5 99.000 (98.840) +2022-11-14 13:50:02,113 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1161 (0.0919) Prec@1 78.000 (84.000) Prec@5 97.000 (98.769) +2022-11-14 13:50:02,123 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0909) Prec@1 92.000 (84.296) Prec@5 100.000 (98.815) +2022-11-14 13:50:02,131 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0909) Prec@1 85.000 (84.321) Prec@5 100.000 (98.857) +2022-11-14 13:50:02,140 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0910) Prec@1 83.000 (84.276) Prec@5 98.000 (98.828) +2022-11-14 13:50:02,150 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1149 (0.0918) Prec@1 78.000 (84.067) Prec@5 97.000 (98.767) +2022-11-14 13:50:02,159 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0920) Prec@1 81.000 (83.968) Prec@5 100.000 (98.806) +2022-11-14 13:50:02,167 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1279 (0.0931) Prec@1 78.000 (83.781) Prec@5 100.000 (98.844) +2022-11-14 13:50:02,177 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0929) Prec@1 85.000 (83.818) Prec@5 98.000 (98.818) +2022-11-14 13:50:02,186 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0932) Prec@1 83.000 (83.794) Prec@5 100.000 (98.853) +2022-11-14 13:50:02,195 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0935) Prec@1 83.000 (83.771) Prec@5 98.000 (98.829) +2022-11-14 13:50:02,205 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0937) Prec@1 84.000 (83.778) Prec@5 97.000 (98.778) +2022-11-14 13:50:02,216 Test: [36/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0939) Prec@1 80.000 (83.676) Prec@5 98.000 (98.757) +2022-11-14 13:50:02,226 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0939) Prec@1 81.000 (83.605) Prec@5 98.000 (98.737) +2022-11-14 13:50:02,235 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0937) Prec@1 84.000 (83.615) Prec@5 98.000 (98.718) +2022-11-14 13:50:02,245 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0933) Prec@1 88.000 (83.725) Prec@5 99.000 (98.725) +2022-11-14 13:50:02,255 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1268 (0.0941) Prec@1 77.000 (83.561) Prec@5 99.000 (98.732) +2022-11-14 13:50:02,264 Test: [41/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0938) Prec@1 85.000 (83.595) Prec@5 98.000 (98.714) +2022-11-14 13:50:02,274 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0930) Prec@1 88.000 (83.698) Prec@5 100.000 (98.744) +2022-11-14 13:50:02,283 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0925) Prec@1 88.000 (83.795) Prec@5 98.000 (98.727) +2022-11-14 13:50:02,292 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0927) Prec@1 80.000 (83.711) Prec@5 99.000 (98.733) +2022-11-14 13:50:02,302 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.0932) Prec@1 78.000 (83.587) Prec@5 99.000 (98.739) +2022-11-14 13:50:02,310 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0930) Prec@1 84.000 (83.596) Prec@5 100.000 (98.766) +2022-11-14 13:50:02,320 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.0934) Prec@1 81.000 (83.542) Prec@5 97.000 (98.729) +2022-11-14 13:50:02,331 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0927) Prec@1 90.000 (83.673) Prec@5 99.000 (98.735) +2022-11-14 13:50:02,340 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1323 (0.0935) Prec@1 78.000 (83.560) Prec@5 98.000 (98.720) +2022-11-14 13:50:02,349 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0930) Prec@1 88.000 (83.647) Prec@5 100.000 (98.745) +2022-11-14 13:50:02,359 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0932) Prec@1 83.000 (83.635) Prec@5 98.000 (98.731) +2022-11-14 13:50:02,367 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0934) Prec@1 81.000 (83.585) Prec@5 100.000 (98.755) +2022-11-14 13:50:02,377 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0934) Prec@1 84.000 (83.593) Prec@5 99.000 (98.759) +2022-11-14 13:50:02,387 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0935) Prec@1 81.000 (83.545) Prec@5 100.000 (98.782) +2022-11-14 13:50:02,396 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0934) Prec@1 84.000 (83.554) Prec@5 99.000 (98.786) +2022-11-14 13:50:02,406 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0936) Prec@1 82.000 (83.526) Prec@5 100.000 (98.807) +2022-11-14 13:50:02,416 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0936) Prec@1 83.000 (83.517) Prec@5 99.000 (98.810) +2022-11-14 13:50:02,425 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1313 (0.0942) Prec@1 75.000 (83.373) Prec@5 97.000 (98.780) +2022-11-14 13:50:02,435 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0941) Prec@1 83.000 (83.367) Prec@5 99.000 (98.783) +2022-11-14 13:50:02,446 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1172 (0.0945) Prec@1 81.000 (83.328) Prec@5 98.000 (98.770) +2022-11-14 13:50:02,456 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0941) Prec@1 87.000 (83.387) Prec@5 98.000 (98.758) +2022-11-14 13:50:02,467 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0938) Prec@1 89.000 (83.476) Prec@5 100.000 (98.778) +2022-11-14 13:50:02,477 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0933) Prec@1 91.000 (83.594) Prec@5 100.000 (98.797) +2022-11-14 13:50:02,486 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.0936) Prec@1 78.000 (83.508) Prec@5 98.000 (98.785) +2022-11-14 13:50:02,495 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0935) Prec@1 84.000 (83.515) Prec@5 100.000 (98.803) +2022-11-14 13:50:02,505 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0932) Prec@1 87.000 (83.567) Prec@5 100.000 (98.821) +2022-11-14 13:50:02,514 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1152 (0.0935) Prec@1 82.000 (83.544) Prec@5 99.000 (98.824) +2022-11-14 13:50:02,525 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0937) Prec@1 79.000 (83.478) Prec@5 99.000 (98.826) +2022-11-14 13:50:02,535 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0937) Prec@1 83.000 (83.471) Prec@5 98.000 (98.814) +2022-11-14 13:50:02,545 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0935) Prec@1 84.000 (83.479) Prec@5 97.000 (98.789) +2022-11-14 13:50:02,555 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0933) Prec@1 86.000 (83.514) Prec@5 100.000 (98.806) +2022-11-14 13:50:02,564 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0931) Prec@1 91.000 (83.616) Prec@5 99.000 (98.808) +2022-11-14 13:50:02,573 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0931) Prec@1 83.000 (83.608) Prec@5 100.000 (98.824) +2022-11-14 13:50:02,582 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1489 (0.0938) Prec@1 71.000 (83.440) Prec@5 97.000 (98.800) +2022-11-14 13:50:02,591 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0936) Prec@1 89.000 (83.513) Prec@5 98.000 (98.789) +2022-11-14 13:50:02,600 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0936) Prec@1 83.000 (83.506) Prec@5 97.000 (98.766) +2022-11-14 13:50:02,612 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0935) Prec@1 86.000 (83.538) Prec@5 98.000 (98.756) +2022-11-14 13:50:02,620 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0935) Prec@1 84.000 (83.544) Prec@5 99.000 (98.759) +2022-11-14 13:50:02,630 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0936) Prec@1 83.000 (83.537) Prec@5 98.000 (98.750) +2022-11-14 13:50:02,640 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0935) Prec@1 84.000 (83.543) Prec@5 97.000 (98.728) +2022-11-14 13:50:02,649 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0935) Prec@1 83.000 (83.537) Prec@5 99.000 (98.732) +2022-11-14 13:50:02,658 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0938) Prec@1 82.000 (83.518) Prec@5 99.000 (98.735) +2022-11-14 13:50:02,668 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0938) Prec@1 82.000 (83.500) Prec@5 99.000 (98.738) +2022-11-14 13:50:02,677 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0938) Prec@1 86.000 (83.529) Prec@5 99.000 (98.741) +2022-11-14 13:50:02,686 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1182 (0.0941) Prec@1 80.000 (83.488) Prec@5 98.000 (98.733) +2022-11-14 13:50:02,695 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0941) Prec@1 87.000 (83.529) Prec@5 98.000 (98.724) +2022-11-14 13:50:02,705 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0938) Prec@1 88.000 (83.580) Prec@5 98.000 (98.716) +2022-11-14 13:50:02,716 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0938) Prec@1 82.000 (83.562) Prec@5 99.000 (98.719) +2022-11-14 13:50:02,726 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0939) Prec@1 86.000 (83.589) Prec@5 100.000 (98.733) +2022-11-14 13:50:02,735 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0937) Prec@1 85.000 (83.604) Prec@5 100.000 (98.747) +2022-11-14 13:50:02,744 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0937) Prec@1 84.000 (83.609) Prec@5 100.000 (98.761) +2022-11-14 13:50:02,754 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.0938) Prec@1 82.000 (83.591) Prec@5 98.000 (98.753) +2022-11-14 13:50:02,763 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0938) Prec@1 86.000 (83.617) Prec@5 99.000 (98.755) +2022-11-14 13:50:02,772 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0938) Prec@1 86.000 (83.642) Prec@5 97.000 (98.737) +2022-11-14 13:50:02,781 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0938) Prec@1 84.000 (83.646) Prec@5 100.000 (98.750) +2022-11-14 13:50:02,791 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0935) Prec@1 92.000 (83.732) Prec@5 99.000 (98.753) +2022-11-14 13:50:02,799 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0936) Prec@1 80.000 (83.694) Prec@5 98.000 (98.745) +2022-11-14 13:50:02,808 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0938) Prec@1 77.000 (83.626) Prec@5 99.000 (98.747) +2022-11-14 13:50:02,818 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0937) Prec@1 86.000 (83.650) Prec@5 99.000 (98.750) +2022-11-14 13:50:02,875 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:50:03,182 Epoch: [102][0/500] Time 0.022 (0.022) Data 0.225 (0.225) Loss 0.0682 (0.0682) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:03,403 Epoch: [102][10/500] Time 0.020 (0.020) Data 0.002 (0.022) Loss 0.0720 (0.0701) Prec@1 86.000 (85.500) Prec@5 98.000 (99.000) +2022-11-14 13:50:03,601 Epoch: [102][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0960 (0.0788) Prec@1 86.000 (85.667) Prec@5 98.000 (98.667) +2022-11-14 13:50:03,820 Epoch: [102][30/500] Time 0.025 (0.019) Data 0.002 (0.009) Loss 0.0871 (0.0809) Prec@1 87.000 (86.000) Prec@5 97.000 (98.250) +2022-11-14 13:50:04,106 Epoch: [102][40/500] Time 0.028 (0.020) Data 0.002 (0.007) Loss 0.0561 (0.0759) Prec@1 90.000 (86.800) Prec@5 98.000 (98.200) +2022-11-14 13:50:04,396 Epoch: [102][50/500] Time 0.027 (0.021) Data 0.002 (0.006) Loss 0.0895 (0.0782) Prec@1 83.000 (86.167) Prec@5 99.000 (98.333) +2022-11-14 13:50:04,682 Epoch: [102][60/500] Time 0.032 (0.022) Data 0.002 (0.005) Loss 0.0590 (0.0754) Prec@1 89.000 (86.571) Prec@5 99.000 (98.429) +2022-11-14 13:50:04,967 Epoch: [102][70/500] Time 0.028 (0.022) Data 0.002 (0.005) Loss 0.0553 (0.0729) Prec@1 92.000 (87.250) Prec@5 100.000 (98.625) +2022-11-14 13:50:05,249 Epoch: [102][80/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.0888 (0.0747) Prec@1 83.000 (86.778) Prec@5 100.000 (98.778) +2022-11-14 13:50:05,535 Epoch: [102][90/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0544 (0.0726) Prec@1 88.000 (86.900) Prec@5 100.000 (98.900) +2022-11-14 13:50:05,815 Epoch: [102][100/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0671 (0.0721) Prec@1 89.000 (87.091) Prec@5 100.000 (99.000) +2022-11-14 13:50:06,098 Epoch: [102][110/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0659 (0.0716) Prec@1 87.000 (87.083) Prec@5 100.000 (99.083) +2022-11-14 13:50:06,383 Epoch: [102][120/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0704 (0.0715) Prec@1 89.000 (87.231) Prec@5 100.000 (99.154) +2022-11-14 13:50:06,670 Epoch: [102][130/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0543 (0.0703) Prec@1 91.000 (87.500) Prec@5 100.000 (99.214) +2022-11-14 13:50:06,958 Epoch: [102][140/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0685 (0.0702) Prec@1 89.000 (87.600) Prec@5 100.000 (99.267) +2022-11-14 13:50:07,248 Epoch: [102][150/500] Time 0.023 (0.024) Data 0.002 (0.003) Loss 0.0572 (0.0694) Prec@1 88.000 (87.625) Prec@5 100.000 (99.312) +2022-11-14 13:50:07,537 Epoch: [102][160/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0722 (0.0695) Prec@1 87.000 (87.588) Prec@5 99.000 (99.294) +2022-11-14 13:50:07,831 Epoch: [102][170/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0751 (0.0698) Prec@1 86.000 (87.500) Prec@5 99.000 (99.278) +2022-11-14 13:50:08,112 Epoch: [102][180/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0696 (0.0698) Prec@1 88.000 (87.526) Prec@5 99.000 (99.263) +2022-11-14 13:50:08,400 Epoch: [102][190/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0697 (0.0698) Prec@1 88.000 (87.550) Prec@5 99.000 (99.250) +2022-11-14 13:50:08,881 Epoch: [102][200/500] Time 0.042 (0.025) Data 0.002 (0.003) Loss 0.0626 (0.0695) Prec@1 90.000 (87.667) Prec@5 99.000 (99.238) +2022-11-14 13:50:09,396 Epoch: [102][210/500] Time 0.045 (0.026) Data 0.002 (0.003) Loss 0.0744 (0.0697) Prec@1 89.000 (87.727) Prec@5 99.000 (99.227) +2022-11-14 13:50:09,876 Epoch: [102][220/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0582 (0.0692) Prec@1 90.000 (87.826) Prec@5 100.000 (99.261) +2022-11-14 13:50:10,345 Epoch: [102][230/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0635 (0.0690) Prec@1 90.000 (87.917) Prec@5 98.000 (99.208) +2022-11-14 13:50:10,817 Epoch: [102][240/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0669 (0.0689) Prec@1 89.000 (87.960) Prec@5 100.000 (99.240) +2022-11-14 13:50:11,308 Epoch: [102][250/500] Time 0.049 (0.029) Data 0.002 (0.003) Loss 0.0585 (0.0685) Prec@1 92.000 (88.115) Prec@5 99.000 (99.231) +2022-11-14 13:50:11,804 Epoch: [102][260/500] Time 0.051 (0.029) Data 0.002 (0.003) Loss 0.0894 (0.0693) Prec@1 85.000 (88.000) Prec@5 99.000 (99.222) +2022-11-14 13:50:12,310 Epoch: [102][270/500] Time 0.048 (0.030) Data 0.002 (0.003) Loss 0.0784 (0.0696) Prec@1 87.000 (87.964) Prec@5 100.000 (99.250) +2022-11-14 13:50:12,815 Epoch: [102][280/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0747 (0.0698) Prec@1 87.000 (87.931) Prec@5 99.000 (99.241) +2022-11-14 13:50:13,286 Epoch: [102][290/500] Time 0.054 (0.031) Data 0.002 (0.003) Loss 0.0702 (0.0698) Prec@1 87.000 (87.900) Prec@5 99.000 (99.233) +2022-11-14 13:50:13,751 Epoch: [102][300/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.0640 (0.0696) Prec@1 91.000 (88.000) Prec@5 99.000 (99.226) +2022-11-14 13:50:14,231 Epoch: [102][310/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.1032 (0.0706) Prec@1 83.000 (87.844) Prec@5 100.000 (99.250) +2022-11-14 13:50:14,748 Epoch: [102][320/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0713 (0.0707) Prec@1 87.000 (87.818) Prec@5 99.000 (99.242) +2022-11-14 13:50:15,275 Epoch: [102][330/500] Time 0.052 (0.032) Data 0.003 (0.003) Loss 0.0705 (0.0707) Prec@1 88.000 (87.824) Prec@5 98.000 (99.206) +2022-11-14 13:50:15,750 Epoch: [102][340/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0822 (0.0710) Prec@1 87.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 13:50:16,241 Epoch: [102][350/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0575 (0.0706) Prec@1 93.000 (87.944) Prec@5 99.000 (99.194) +2022-11-14 13:50:16,714 Epoch: [102][360/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0799 (0.0709) Prec@1 89.000 (87.973) Prec@5 98.000 (99.162) +2022-11-14 13:50:17,186 Epoch: [102][370/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.0697 (0.0708) Prec@1 89.000 (88.000) Prec@5 99.000 (99.158) +2022-11-14 13:50:17,650 Epoch: [102][380/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0688 (0.0708) Prec@1 87.000 (87.974) Prec@5 100.000 (99.179) +2022-11-14 13:50:18,324 Epoch: [102][390/500] Time 0.047 (0.034) Data 0.002 (0.002) Loss 0.0741 (0.0709) Prec@1 87.000 (87.950) Prec@5 100.000 (99.200) +2022-11-14 13:50:18,807 Epoch: [102][400/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0432 (0.0702) Prec@1 95.000 (88.122) Prec@5 99.000 (99.195) +2022-11-14 13:50:19,316 Epoch: [102][410/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0640 (0.0700) Prec@1 91.000 (88.190) Prec@5 99.000 (99.190) +2022-11-14 13:50:19,837 Epoch: [102][420/500] Time 0.043 (0.035) Data 0.003 (0.002) Loss 0.0669 (0.0700) Prec@1 88.000 (88.186) Prec@5 100.000 (99.209) +2022-11-14 13:50:20,252 Epoch: [102][430/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0844 (0.0703) Prec@1 85.000 (88.114) Prec@5 98.000 (99.182) +2022-11-14 13:50:20,645 Epoch: [102][440/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0969 (0.0709) Prec@1 83.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 13:50:21,033 Epoch: [102][450/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0678 (0.0708) Prec@1 89.000 (88.022) Prec@5 100.000 (99.217) +2022-11-14 13:50:21,433 Epoch: [102][460/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.0690 (0.0708) Prec@1 87.000 (88.000) Prec@5 99.000 (99.213) +2022-11-14 13:50:21,836 Epoch: [102][470/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0747 (0.0709) Prec@1 85.000 (87.938) Prec@5 100.000 (99.229) +2022-11-14 13:50:22,227 Epoch: [102][480/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.0517 (0.0705) Prec@1 89.000 (87.959) Prec@5 100.000 (99.245) +2022-11-14 13:50:22,614 Epoch: [102][490/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0564 (0.0702) Prec@1 90.000 (88.000) Prec@5 100.000 (99.260) +2022-11-14 13:50:22,992 Epoch: [102][499/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0684 (0.0702) Prec@1 88.000 (88.000) Prec@5 99.000 (99.255) +2022-11-14 13:50:23,292 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0626 (0.0626) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:23,300 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0643) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 13:50:23,308 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0760) Prec@1 81.000 (86.667) Prec@5 99.000 (99.667) +2022-11-14 13:50:23,320 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0811) Prec@1 82.000 (85.500) Prec@5 98.000 (99.250) +2022-11-14 13:50:23,328 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0866) Prec@1 80.000 (84.400) Prec@5 100.000 (99.400) +2022-11-14 13:50:23,336 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0812) Prec@1 89.000 (85.167) Prec@5 100.000 (99.500) +2022-11-14 13:50:23,344 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0806) Prec@1 89.000 (85.714) Prec@5 100.000 (99.571) +2022-11-14 13:50:23,354 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0836) Prec@1 83.000 (85.375) Prec@5 98.000 (99.375) +2022-11-14 13:50:23,363 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0868) Prec@1 84.000 (85.222) Prec@5 99.000 (99.333) +2022-11-14 13:50:23,371 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0840) Prec@1 91.000 (85.800) Prec@5 99.000 (99.300) +2022-11-14 13:50:23,381 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0836) Prec@1 84.000 (85.636) Prec@5 100.000 (99.364) +2022-11-14 13:50:23,390 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0847) Prec@1 85.000 (85.583) Prec@5 100.000 (99.417) +2022-11-14 13:50:23,399 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0833) Prec@1 88.000 (85.769) Prec@5 99.000 (99.385) +2022-11-14 13:50:23,408 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0821) Prec@1 89.000 (86.000) Prec@5 98.000 (99.286) +2022-11-14 13:50:23,417 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0823) Prec@1 86.000 (86.000) Prec@5 99.000 (99.267) +2022-11-14 13:50:23,425 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0822) Prec@1 90.000 (86.250) Prec@5 98.000 (99.188) +2022-11-14 13:50:23,433 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0802) Prec@1 94.000 (86.706) Prec@5 98.000 (99.118) +2022-11-14 13:50:23,441 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1153 (0.0821) Prec@1 78.000 (86.222) Prec@5 98.000 (99.056) +2022-11-14 13:50:23,451 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0833) Prec@1 81.000 (85.947) Prec@5 99.000 (99.053) +2022-11-14 13:50:23,461 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0847) Prec@1 81.000 (85.700) Prec@5 100.000 (99.100) +2022-11-14 13:50:23,470 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1502 (0.0878) Prec@1 75.000 (85.190) Prec@5 99.000 (99.095) +2022-11-14 13:50:23,479 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0879) Prec@1 83.000 (85.091) Prec@5 100.000 (99.136) +2022-11-14 13:50:23,487 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1158 (0.0891) Prec@1 83.000 (85.000) Prec@5 97.000 (99.043) +2022-11-14 13:50:23,495 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0896) Prec@1 82.000 (84.875) Prec@5 99.000 (99.042) +2022-11-14 13:50:23,502 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0897) Prec@1 86.000 (84.920) Prec@5 99.000 (99.040) +2022-11-14 13:50:23,512 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0901) Prec@1 82.000 (84.808) Prec@5 99.000 (99.038) +2022-11-14 13:50:23,521 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0890) Prec@1 90.000 (85.000) Prec@5 100.000 (99.074) +2022-11-14 13:50:23,531 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0889) Prec@1 84.000 (84.964) Prec@5 100.000 (99.107) +2022-11-14 13:50:23,540 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0882) Prec@1 90.000 (85.138) Prec@5 99.000 (99.103) +2022-11-14 13:50:23,548 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0882) Prec@1 84.000 (85.100) Prec@5 99.000 (99.100) +2022-11-14 13:50:23,557 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0883) Prec@1 85.000 (85.097) Prec@5 98.000 (99.065) +2022-11-14 13:50:23,566 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0880) Prec@1 88.000 (85.188) Prec@5 99.000 (99.062) +2022-11-14 13:50:23,575 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0879) Prec@1 84.000 (85.152) Prec@5 100.000 (99.091) +2022-11-14 13:50:23,584 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1105 (0.0886) Prec@1 80.000 (85.000) Prec@5 98.000 (99.059) +2022-11-14 13:50:23,594 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0883) Prec@1 86.000 (85.029) Prec@5 99.000 (99.057) +2022-11-14 13:50:23,603 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0882) Prec@1 89.000 (85.139) Prec@5 98.000 (99.028) +2022-11-14 13:50:23,611 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0882) Prec@1 84.000 (85.108) Prec@5 97.000 (98.973) +2022-11-14 13:50:23,621 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0883) Prec@1 84.000 (85.079) Prec@5 99.000 (98.974) +2022-11-14 13:50:23,631 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0876) Prec@1 87.000 (85.128) Prec@5 100.000 (99.000) +2022-11-14 13:50:23,640 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0875) Prec@1 87.000 (85.175) Prec@5 100.000 (99.025) +2022-11-14 13:50:23,649 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0876) Prec@1 83.000 (85.122) Prec@5 99.000 (99.024) +2022-11-14 13:50:23,658 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0876) Prec@1 85.000 (85.119) Prec@5 99.000 (99.024) +2022-11-14 13:50:23,669 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0871) Prec@1 88.000 (85.186) Prec@5 99.000 (99.023) +2022-11-14 13:50:23,680 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0866) Prec@1 91.000 (85.318) Prec@5 100.000 (99.045) +2022-11-14 13:50:23,689 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0867) Prec@1 84.000 (85.289) Prec@5 100.000 (99.067) +2022-11-14 13:50:23,699 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1265 (0.0875) Prec@1 76.000 (85.087) Prec@5 99.000 (99.065) +2022-11-14 13:50:23,707 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0873) Prec@1 88.000 (85.149) Prec@5 100.000 (99.085) +2022-11-14 13:50:23,716 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0877) Prec@1 81.000 (85.062) Prec@5 96.000 (99.021) +2022-11-14 13:50:23,726 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0876) Prec@1 86.000 (85.082) Prec@5 100.000 (99.041) +2022-11-14 13:50:23,735 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.0879) Prec@1 81.000 (85.000) Prec@5 98.000 (99.020) +2022-11-14 13:50:23,744 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0876) Prec@1 87.000 (85.039) Prec@5 98.000 (99.000) +2022-11-14 13:50:23,754 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0875) Prec@1 87.000 (85.077) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,763 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0874) Prec@1 85.000 (85.075) Prec@5 100.000 (99.019) +2022-11-14 13:50:23,772 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0875) Prec@1 86.000 (85.093) Prec@5 97.000 (98.981) +2022-11-14 13:50:23,781 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1287 (0.0883) Prec@1 77.000 (84.945) Prec@5 98.000 (98.964) +2022-11-14 13:50:23,790 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0882) Prec@1 85.000 (84.946) Prec@5 100.000 (98.982) +2022-11-14 13:50:23,799 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0881) Prec@1 88.000 (85.000) Prec@5 100.000 (99.000) +2022-11-14 13:50:23,809 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0876) Prec@1 90.000 (85.086) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,818 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1179 (0.0881) Prec@1 77.000 (84.949) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,827 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0880) Prec@1 85.000 (84.950) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,836 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0883) Prec@1 83.000 (84.918) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,846 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0883) Prec@1 84.000 (84.903) Prec@5 97.000 (98.968) +2022-11-14 13:50:23,855 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0879) Prec@1 89.000 (84.968) Prec@5 100.000 (98.984) +2022-11-14 13:50:23,865 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0873) Prec@1 92.000 (85.078) Prec@5 100.000 (99.000) +2022-11-14 13:50:23,873 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0874) Prec@1 85.000 (85.077) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,882 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0875) Prec@1 81.000 (85.015) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,892 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0869) Prec@1 92.000 (85.119) Prec@5 99.000 (99.000) +2022-11-14 13:50:23,901 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0873) Prec@1 81.000 (85.059) Prec@5 98.000 (98.985) +2022-11-14 13:50:23,910 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0872) Prec@1 87.000 (85.087) Prec@5 100.000 (99.000) +2022-11-14 13:50:23,920 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0873) Prec@1 86.000 (85.100) Prec@5 98.000 (98.986) +2022-11-14 13:50:23,929 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0873) Prec@1 87.000 (85.127) Prec@5 99.000 (98.986) +2022-11-14 13:50:23,938 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0874) Prec@1 84.000 (85.111) Prec@5 100.000 (99.000) +2022-11-14 13:50:23,948 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0871) Prec@1 89.000 (85.164) Prec@5 100.000 (99.014) +2022-11-14 13:50:23,957 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0869) Prec@1 88.000 (85.203) Prec@5 100.000 (99.027) +2022-11-14 13:50:23,967 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.0871) Prec@1 79.000 (85.120) Prec@5 100.000 (99.040) +2022-11-14 13:50:23,976 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0871) Prec@1 86.000 (85.132) Prec@5 100.000 (99.053) +2022-11-14 13:50:23,988 Test: [76/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0873) Prec@1 84.000 (85.117) Prec@5 99.000 (99.052) +2022-11-14 13:50:23,998 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0875) Prec@1 81.000 (85.064) Prec@5 100.000 (99.064) +2022-11-14 13:50:24,007 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0874) Prec@1 86.000 (85.076) Prec@5 100.000 (99.076) +2022-11-14 13:50:24,017 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0875) Prec@1 84.000 (85.062) Prec@5 100.000 (99.088) +2022-11-14 13:50:24,027 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0872) Prec@1 88.000 (85.099) Prec@5 100.000 (99.099) +2022-11-14 13:50:24,036 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0870) Prec@1 88.000 (85.134) Prec@5 100.000 (99.110) +2022-11-14 13:50:24,046 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0872) Prec@1 86.000 (85.145) Prec@5 99.000 (99.108) +2022-11-14 13:50:24,054 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0873) Prec@1 85.000 (85.143) Prec@5 99.000 (99.107) +2022-11-14 13:50:24,063 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0875) Prec@1 84.000 (85.129) Prec@5 99.000 (99.106) +2022-11-14 13:50:24,072 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0876) Prec@1 82.000 (85.093) Prec@5 98.000 (99.093) +2022-11-14 13:50:24,081 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0875) Prec@1 88.000 (85.126) Prec@5 99.000 (99.092) +2022-11-14 13:50:24,089 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0873) Prec@1 90.000 (85.182) Prec@5 98.000 (99.080) +2022-11-14 13:50:24,098 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0874) Prec@1 82.000 (85.146) Prec@5 98.000 (99.067) +2022-11-14 13:50:24,107 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0874) Prec@1 85.000 (85.144) Prec@5 100.000 (99.078) +2022-11-14 13:50:24,116 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0873) Prec@1 87.000 (85.165) Prec@5 100.000 (99.088) +2022-11-14 13:50:24,125 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0871) Prec@1 89.000 (85.207) Prec@5 99.000 (99.087) +2022-11-14 13:50:24,135 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0871) Prec@1 86.000 (85.215) Prec@5 100.000 (99.097) +2022-11-14 13:50:24,144 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0871) Prec@1 86.000 (85.223) Prec@5 100.000 (99.106) +2022-11-14 13:50:24,153 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0871) Prec@1 86.000 (85.232) Prec@5 99.000 (99.105) +2022-11-14 13:50:24,163 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0870) Prec@1 87.000 (85.250) Prec@5 100.000 (99.115) +2022-11-14 13:50:24,172 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0867) Prec@1 92.000 (85.320) Prec@5 98.000 (99.103) +2022-11-14 13:50:24,181 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0868) Prec@1 90.000 (85.367) Prec@5 100.000 (99.112) +2022-11-14 13:50:24,190 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1115 (0.0870) Prec@1 83.000 (85.343) Prec@5 100.000 (99.121) +2022-11-14 13:50:24,200 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0869) Prec@1 87.000 (85.360) Prec@5 100.000 (99.130) +2022-11-14 13:50:24,258 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:50:24,566 Epoch: [103][0/500] Time 0.028 (0.028) Data 0.219 (0.219) Loss 0.0656 (0.0656) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:24,770 Epoch: [103][10/500] Time 0.020 (0.019) Data 0.001 (0.021) Loss 0.0815 (0.0735) Prec@1 83.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 13:50:24,968 Epoch: [103][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.0578 (0.0683) Prec@1 90.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 13:50:25,230 Epoch: [103][30/500] Time 0.029 (0.020) Data 0.002 (0.009) Loss 0.0454 (0.0626) Prec@1 92.000 (88.750) Prec@5 100.000 (100.000) +2022-11-14 13:50:25,548 Epoch: [103][40/500] Time 0.030 (0.022) Data 0.002 (0.007) Loss 0.0559 (0.0612) Prec@1 88.000 (88.600) Prec@5 100.000 (100.000) +2022-11-14 13:50:25,858 Epoch: [103][50/500] Time 0.034 (0.023) Data 0.002 (0.006) Loss 0.0573 (0.0606) Prec@1 89.000 (88.667) Prec@5 99.000 (99.833) +2022-11-14 13:50:26,157 Epoch: [103][60/500] Time 0.028 (0.024) Data 0.001 (0.005) Loss 0.0638 (0.0610) Prec@1 90.000 (88.857) Prec@5 100.000 (99.857) +2022-11-14 13:50:26,467 Epoch: [103][70/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0702 (0.0622) Prec@1 89.000 (88.875) Prec@5 100.000 (99.875) +2022-11-14 13:50:26,776 Epoch: [103][80/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0654 (0.0625) Prec@1 87.000 (88.667) Prec@5 100.000 (99.889) +2022-11-14 13:50:27,083 Epoch: [103][90/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0920 (0.0655) Prec@1 85.000 (88.300) Prec@5 97.000 (99.600) +2022-11-14 13:50:27,388 Epoch: [103][100/500] Time 0.029 (0.025) Data 0.001 (0.004) Loss 0.0776 (0.0666) Prec@1 87.000 (88.182) Prec@5 99.000 (99.545) +2022-11-14 13:50:27,698 Epoch: [103][110/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0478 (0.0650) Prec@1 91.000 (88.417) Prec@5 100.000 (99.583) +2022-11-14 13:50:28,009 Epoch: [103][120/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0578 (0.0645) Prec@1 90.000 (88.538) Prec@5 99.000 (99.538) +2022-11-14 13:50:28,324 Epoch: [103][130/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0845 (0.0659) Prec@1 85.000 (88.286) Prec@5 98.000 (99.429) +2022-11-14 13:50:28,634 Epoch: [103][140/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0944 (0.0678) Prec@1 84.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 13:50:28,936 Epoch: [103][150/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0883 (0.0691) Prec@1 86.000 (87.875) Prec@5 100.000 (99.438) +2022-11-14 13:50:29,246 Epoch: [103][160/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0877 (0.0702) Prec@1 85.000 (87.706) Prec@5 99.000 (99.412) +2022-11-14 13:50:29,556 Epoch: [103][170/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0583 (0.0695) Prec@1 88.000 (87.722) Prec@5 99.000 (99.389) +2022-11-14 13:50:29,875 Epoch: [103][180/500] Time 0.037 (0.026) Data 0.002 (0.003) Loss 0.0663 (0.0693) Prec@1 90.000 (87.842) Prec@5 100.000 (99.421) +2022-11-14 13:50:30,174 Epoch: [103][190/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0530 (0.0685) Prec@1 91.000 (88.000) Prec@5 98.000 (99.350) +2022-11-14 13:50:30,485 Epoch: [103][200/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0526 (0.0678) Prec@1 92.000 (88.190) Prec@5 100.000 (99.381) +2022-11-14 13:50:30,801 Epoch: [103][210/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0599 (0.0674) Prec@1 90.000 (88.273) Prec@5 100.000 (99.409) +2022-11-14 13:50:31,189 Epoch: [103][220/500] Time 0.060 (0.027) Data 0.002 (0.003) Loss 0.1006 (0.0689) Prec@1 83.000 (88.043) Prec@5 97.000 (99.304) +2022-11-14 13:50:31,688 Epoch: [103][230/500] Time 0.049 (0.027) Data 0.002 (0.003) Loss 0.1514 (0.0723) Prec@1 78.000 (87.625) Prec@5 98.000 (99.250) +2022-11-14 13:50:32,169 Epoch: [103][240/500] Time 0.045 (0.028) Data 0.002 (0.003) Loss 0.0819 (0.0727) Prec@1 85.000 (87.520) Prec@5 98.000 (99.200) +2022-11-14 13:50:32,648 Epoch: [103][250/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0488 (0.0718) Prec@1 92.000 (87.692) Prec@5 99.000 (99.192) +2022-11-14 13:50:33,163 Epoch: [103][260/500] Time 0.053 (0.029) Data 0.002 (0.003) Loss 0.0730 (0.0718) Prec@1 86.000 (87.630) Prec@5 100.000 (99.222) +2022-11-14 13:50:33,635 Epoch: [103][270/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0935 (0.0726) Prec@1 85.000 (87.536) Prec@5 97.000 (99.143) +2022-11-14 13:50:34,096 Epoch: [103][280/500] Time 0.044 (0.030) Data 0.001 (0.003) Loss 0.0825 (0.0729) Prec@1 89.000 (87.586) Prec@5 99.000 (99.138) +2022-11-14 13:50:34,567 Epoch: [103][290/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0895 (0.0735) Prec@1 85.000 (87.500) Prec@5 98.000 (99.100) +2022-11-14 13:50:35,153 Epoch: [103][300/500] Time 0.058 (0.031) Data 0.002 (0.003) Loss 0.0631 (0.0731) Prec@1 89.000 (87.548) Prec@5 99.000 (99.097) +2022-11-14 13:50:35,647 Epoch: [103][310/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0498 (0.0724) Prec@1 91.000 (87.656) Prec@5 100.000 (99.125) +2022-11-14 13:50:36,113 Epoch: [103][320/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0926 (0.0730) Prec@1 83.000 (87.515) Prec@5 99.000 (99.121) +2022-11-14 13:50:36,586 Epoch: [103][330/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0561 (0.0725) Prec@1 92.000 (87.647) Prec@5 99.000 (99.118) +2022-11-14 13:50:37,065 Epoch: [103][340/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0714 (0.0725) Prec@1 90.000 (87.714) Prec@5 99.000 (99.114) +2022-11-14 13:50:37,536 Epoch: [103][350/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0954 (0.0731) Prec@1 86.000 (87.667) Prec@5 99.000 (99.111) +2022-11-14 13:50:38,019 Epoch: [103][360/500] Time 0.038 (0.033) Data 0.002 (0.002) Loss 0.0511 (0.0725) Prec@1 90.000 (87.730) Prec@5 100.000 (99.135) +2022-11-14 13:50:38,476 Epoch: [103][370/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0473 (0.0719) Prec@1 92.000 (87.842) Prec@5 100.000 (99.158) +2022-11-14 13:50:38,955 Epoch: [103][380/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.1157 (0.0730) Prec@1 75.000 (87.513) Prec@5 99.000 (99.154) +2022-11-14 13:50:39,524 Epoch: [103][390/500] Time 0.054 (0.034) Data 0.002 (0.002) Loss 0.0879 (0.0734) Prec@1 87.000 (87.500) Prec@5 99.000 (99.150) +2022-11-14 13:50:39,994 Epoch: [103][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0912 (0.0738) Prec@1 83.000 (87.390) Prec@5 99.000 (99.146) +2022-11-14 13:50:40,479 Epoch: [103][410/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0960 (0.0743) Prec@1 83.000 (87.286) Prec@5 100.000 (99.167) +2022-11-14 13:50:40,986 Epoch: [103][420/500] Time 0.055 (0.035) Data 0.002 (0.002) Loss 0.0727 (0.0743) Prec@1 87.000 (87.279) Prec@5 100.000 (99.186) +2022-11-14 13:50:41,484 Epoch: [103][430/500] Time 0.053 (0.035) Data 0.002 (0.002) Loss 0.0591 (0.0739) Prec@1 92.000 (87.386) Prec@5 100.000 (99.205) +2022-11-14 13:50:41,961 Epoch: [103][440/500] Time 0.051 (0.035) Data 0.002 (0.002) Loss 0.0712 (0.0739) Prec@1 87.000 (87.378) Prec@5 99.000 (99.200) +2022-11-14 13:50:42,456 Epoch: [103][450/500] Time 0.044 (0.035) Data 0.003 (0.002) Loss 0.0643 (0.0737) Prec@1 88.000 (87.391) Prec@5 100.000 (99.217) +2022-11-14 13:50:42,954 Epoch: [103][460/500] Time 0.058 (0.035) Data 0.002 (0.002) Loss 0.0569 (0.0733) Prec@1 91.000 (87.468) Prec@5 100.000 (99.234) +2022-11-14 13:50:43,432 Epoch: [103][470/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0340 (0.0725) Prec@1 93.000 (87.583) Prec@5 100.000 (99.250) +2022-11-14 13:50:43,926 Epoch: [103][480/500] Time 0.055 (0.036) Data 0.002 (0.002) Loss 0.0589 (0.0722) Prec@1 87.000 (87.571) Prec@5 100.000 (99.265) +2022-11-14 13:50:44,418 Epoch: [103][490/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0660 (0.0721) Prec@1 91.000 (87.640) Prec@5 99.000 (99.260) +2022-11-14 13:50:44,874 Epoch: [103][499/500] Time 0.056 (0.036) Data 0.002 (0.002) Loss 0.0489 (0.0716) Prec@1 94.000 (87.765) Prec@5 100.000 (99.275) +2022-11-14 13:50:45,175 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0815 (0.0815) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,184 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0735) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,193 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0796) Prec@1 83.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,206 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.0878) Prec@1 79.000 (84.750) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,213 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0913) Prec@1 83.000 (84.400) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,221 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0846) Prec@1 91.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 13:50:45,229 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0845) Prec@1 86.000 (85.571) Prec@5 99.000 (99.857) +2022-11-14 13:50:45,240 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0859) Prec@1 83.000 (85.250) Prec@5 98.000 (99.625) +2022-11-14 13:50:45,249 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0862) Prec@1 85.000 (85.222) Prec@5 100.000 (99.667) +2022-11-14 13:50:45,258 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0855) Prec@1 84.000 (85.100) Prec@5 100.000 (99.700) +2022-11-14 13:50:45,270 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0859) Prec@1 82.000 (84.818) Prec@5 100.000 (99.727) +2022-11-14 13:50:45,280 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.0886) Prec@1 80.000 (84.417) Prec@5 100.000 (99.750) +2022-11-14 13:50:45,290 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0882) Prec@1 86.000 (84.538) Prec@5 100.000 (99.769) +2022-11-14 13:50:45,299 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0886) Prec@1 83.000 (84.429) Prec@5 99.000 (99.714) +2022-11-14 13:50:45,310 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0881) Prec@1 85.000 (84.467) Prec@5 100.000 (99.733) +2022-11-14 13:50:45,320 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0885) Prec@1 83.000 (84.375) Prec@5 100.000 (99.750) +2022-11-14 13:50:45,330 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0871) Prec@1 89.000 (84.647) Prec@5 99.000 (99.706) +2022-11-14 13:50:45,340 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0872) Prec@1 85.000 (84.667) Prec@5 100.000 (99.722) +2022-11-14 13:50:45,351 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0873) Prec@1 84.000 (84.632) Prec@5 98.000 (99.632) +2022-11-14 13:50:45,363 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.0889) Prec@1 82.000 (84.500) Prec@5 98.000 (99.550) +2022-11-14 13:50:45,373 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0893) Prec@1 84.000 (84.476) Prec@5 99.000 (99.524) +2022-11-14 13:50:45,383 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0887) Prec@1 90.000 (84.727) Prec@5 98.000 (99.455) +2022-11-14 13:50:45,393 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0894) Prec@1 82.000 (84.609) Prec@5 98.000 (99.391) +2022-11-14 13:50:45,403 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0895) Prec@1 84.000 (84.583) Prec@5 98.000 (99.333) +2022-11-14 13:50:45,413 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0888) Prec@1 88.000 (84.720) Prec@5 100.000 (99.360) +2022-11-14 13:50:45,422 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.0901) Prec@1 80.000 (84.538) Prec@5 97.000 (99.269) +2022-11-14 13:50:45,431 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0900) Prec@1 86.000 (84.593) Prec@5 100.000 (99.296) +2022-11-14 13:50:45,441 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0900) Prec@1 85.000 (84.607) Prec@5 99.000 (99.286) +2022-11-14 13:50:45,450 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0897) Prec@1 85.000 (84.621) Prec@5 99.000 (99.276) +2022-11-14 13:50:45,459 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0893) Prec@1 86.000 (84.667) Prec@5 98.000 (99.233) +2022-11-14 13:50:45,470 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0896) Prec@1 81.000 (84.548) Prec@5 99.000 (99.226) +2022-11-14 13:50:45,478 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0894) Prec@1 85.000 (84.562) Prec@5 100.000 (99.250) +2022-11-14 13:50:45,488 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0890) Prec@1 86.000 (84.606) Prec@5 100.000 (99.273) +2022-11-14 13:50:45,500 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0893) Prec@1 81.000 (84.500) Prec@5 99.000 (99.265) +2022-11-14 13:50:45,509 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0892) Prec@1 88.000 (84.600) Prec@5 98.000 (99.229) +2022-11-14 13:50:45,521 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0895) Prec@1 83.000 (84.556) Prec@5 98.000 (99.194) +2022-11-14 13:50:45,531 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0895) Prec@1 83.000 (84.514) Prec@5 100.000 (99.216) +2022-11-14 13:50:45,542 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0898) Prec@1 83.000 (84.474) Prec@5 100.000 (99.237) +2022-11-14 13:50:45,554 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0897) Prec@1 87.000 (84.538) Prec@5 97.000 (99.179) +2022-11-14 13:50:45,564 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0894) Prec@1 89.000 (84.650) Prec@5 100.000 (99.200) +2022-11-14 13:50:45,575 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1244 (0.0903) Prec@1 78.000 (84.488) Prec@5 99.000 (99.195) +2022-11-14 13:50:45,585 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0901) Prec@1 87.000 (84.548) Prec@5 97.000 (99.143) +2022-11-14 13:50:45,597 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0897) Prec@1 87.000 (84.605) Prec@5 100.000 (99.163) +2022-11-14 13:50:45,607 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0894) Prec@1 88.000 (84.682) Prec@5 99.000 (99.159) +2022-11-14 13:50:45,618 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0891) Prec@1 88.000 (84.756) Prec@5 99.000 (99.156) +2022-11-14 13:50:45,628 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1109 (0.0896) Prec@1 79.000 (84.630) Prec@5 99.000 (99.152) +2022-11-14 13:50:45,638 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0895) Prec@1 85.000 (84.638) Prec@5 100.000 (99.170) +2022-11-14 13:50:45,649 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0897) Prec@1 80.000 (84.542) Prec@5 98.000 (99.146) +2022-11-14 13:50:45,661 Test: [48/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0892) Prec@1 90.000 (84.653) Prec@5 99.000 (99.143) +2022-11-14 13:50:45,672 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0896) Prec@1 81.000 (84.580) Prec@5 98.000 (99.120) +2022-11-14 13:50:45,682 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0896) Prec@1 90.000 (84.686) Prec@5 99.000 (99.118) +2022-11-14 13:50:45,693 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0901) Prec@1 82.000 (84.635) Prec@5 99.000 (99.115) +2022-11-14 13:50:45,704 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0903) Prec@1 82.000 (84.585) Prec@5 99.000 (99.113) +2022-11-14 13:50:45,716 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0901) Prec@1 86.000 (84.611) Prec@5 99.000 (99.111) +2022-11-14 13:50:45,727 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0902) Prec@1 83.000 (84.582) Prec@5 99.000 (99.109) +2022-11-14 13:50:45,736 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1163 (0.0907) Prec@1 83.000 (84.554) Prec@5 99.000 (99.107) +2022-11-14 13:50:45,746 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0910) Prec@1 80.000 (84.474) Prec@5 100.000 (99.123) +2022-11-14 13:50:45,756 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0910) Prec@1 87.000 (84.517) Prec@5 97.000 (99.086) +2022-11-14 13:50:45,766 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0911) Prec@1 82.000 (84.475) Prec@5 99.000 (99.085) +2022-11-14 13:50:45,777 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.0913) Prec@1 81.000 (84.417) Prec@5 100.000 (99.100) +2022-11-14 13:50:45,788 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0914) Prec@1 82.000 (84.377) Prec@5 99.000 (99.098) +2022-11-14 13:50:45,797 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0911) Prec@1 87.000 (84.419) Prec@5 99.000 (99.097) +2022-11-14 13:50:45,806 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0912) Prec@1 83.000 (84.397) Prec@5 100.000 (99.111) +2022-11-14 13:50:45,817 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0910) Prec@1 85.000 (84.406) Prec@5 100.000 (99.125) +2022-11-14 13:50:45,827 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0910) Prec@1 86.000 (84.431) Prec@5 98.000 (99.108) +2022-11-14 13:50:45,839 Test: [65/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0908) Prec@1 84.000 (84.424) Prec@5 100.000 (99.121) +2022-11-14 13:50:45,851 Test: [66/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0499 (0.0902) Prec@1 90.000 (84.507) Prec@5 100.000 (99.134) +2022-11-14 13:50:45,860 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0904) Prec@1 80.000 (84.441) Prec@5 99.000 (99.132) +2022-11-14 13:50:45,870 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0902) Prec@1 88.000 (84.493) Prec@5 100.000 (99.145) +2022-11-14 13:50:45,881 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0902) Prec@1 84.000 (84.486) Prec@5 98.000 (99.129) +2022-11-14 13:50:45,891 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0904) Prec@1 85.000 (84.493) Prec@5 97.000 (99.099) +2022-11-14 13:50:45,902 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0902) Prec@1 87.000 (84.528) Prec@5 98.000 (99.083) +2022-11-14 13:50:45,913 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0901) Prec@1 88.000 (84.575) Prec@5 99.000 (99.082) +2022-11-14 13:50:45,925 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0901) Prec@1 84.000 (84.568) Prec@5 100.000 (99.095) +2022-11-14 13:50:45,936 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0901) Prec@1 79.000 (84.493) Prec@5 99.000 (99.093) +2022-11-14 13:50:45,946 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0901) Prec@1 87.000 (84.526) Prec@5 99.000 (99.092) +2022-11-14 13:50:45,958 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0901) Prec@1 83.000 (84.506) Prec@5 99.000 (99.091) +2022-11-14 13:50:45,970 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0901) Prec@1 84.000 (84.500) Prec@5 97.000 (99.064) +2022-11-14 13:50:45,980 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0902) Prec@1 85.000 (84.506) Prec@5 100.000 (99.076) +2022-11-14 13:50:45,991 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0902) Prec@1 82.000 (84.475) Prec@5 100.000 (99.088) +2022-11-14 13:50:46,001 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0901) Prec@1 87.000 (84.506) Prec@5 99.000 (99.086) +2022-11-14 13:50:46,012 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0903) Prec@1 81.000 (84.463) Prec@5 99.000 (99.085) +2022-11-14 13:50:46,023 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0905) Prec@1 81.000 (84.422) Prec@5 100.000 (99.096) +2022-11-14 13:50:46,034 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0905) Prec@1 84.000 (84.417) Prec@5 100.000 (99.107) +2022-11-14 13:50:46,045 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0905) Prec@1 87.000 (84.447) Prec@5 99.000 (99.106) +2022-11-14 13:50:46,054 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1374 (0.0910) Prec@1 76.000 (84.349) Prec@5 99.000 (99.105) +2022-11-14 13:50:46,064 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0909) Prec@1 87.000 (84.379) Prec@5 100.000 (99.115) +2022-11-14 13:50:46,076 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0910) Prec@1 85.000 (84.386) Prec@5 99.000 (99.114) +2022-11-14 13:50:46,087 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0909) Prec@1 85.000 (84.393) Prec@5 99.000 (99.112) +2022-11-14 13:50:46,098 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0908) Prec@1 88.000 (84.433) Prec@5 99.000 (99.111) +2022-11-14 13:50:46,110 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0911) Prec@1 83.000 (84.418) Prec@5 100.000 (99.121) +2022-11-14 13:50:46,120 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0908) Prec@1 90.000 (84.478) Prec@5 100.000 (99.130) +2022-11-14 13:50:46,130 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0908) Prec@1 84.000 (84.473) Prec@5 100.000 (99.140) +2022-11-14 13:50:46,139 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0909) Prec@1 82.000 (84.447) Prec@5 97.000 (99.117) +2022-11-14 13:50:46,149 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0910) Prec@1 87.000 (84.474) Prec@5 98.000 (99.105) +2022-11-14 13:50:46,157 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0907) Prec@1 89.000 (84.521) Prec@5 100.000 (99.115) +2022-11-14 13:50:46,166 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0904) Prec@1 89.000 (84.567) Prec@5 99.000 (99.113) +2022-11-14 13:50:46,175 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0906) Prec@1 84.000 (84.561) Prec@5 99.000 (99.112) +2022-11-14 13:50:46,187 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0908) Prec@1 82.000 (84.535) Prec@5 100.000 (99.121) +2022-11-14 13:50:46,198 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0907) Prec@1 88.000 (84.570) Prec@5 99.000 (99.120) +2022-11-14 13:50:46,254 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:50:46,572 Epoch: [104][0/500] Time 0.024 (0.024) Data 0.232 (0.232) Loss 0.0500 (0.0500) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:46,789 Epoch: [104][10/500] Time 0.017 (0.020) Data 0.002 (0.023) Loss 0.0515 (0.0508) Prec@1 92.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:50:46,996 Epoch: [104][20/500] Time 0.018 (0.019) Data 0.001 (0.013) Loss 0.0941 (0.0652) Prec@1 84.000 (88.667) Prec@5 98.000 (99.333) +2022-11-14 13:50:47,211 Epoch: [104][30/500] Time 0.021 (0.019) Data 0.002 (0.009) Loss 0.0645 (0.0650) Prec@1 90.000 (89.000) Prec@5 99.000 (99.250) +2022-11-14 13:50:47,498 Epoch: [104][40/500] Time 0.026 (0.020) Data 0.002 (0.007) Loss 0.0639 (0.0648) Prec@1 91.000 (89.400) Prec@5 99.000 (99.200) +2022-11-14 13:50:47,784 Epoch: [104][50/500] Time 0.027 (0.021) Data 0.002 (0.006) Loss 0.0973 (0.0702) Prec@1 85.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 13:50:48,076 Epoch: [104][60/500] Time 0.026 (0.022) Data 0.002 (0.006) Loss 0.0582 (0.0685) Prec@1 87.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 13:50:48,365 Epoch: [104][70/500] Time 0.029 (0.023) Data 0.002 (0.005) Loss 0.0518 (0.0664) Prec@1 91.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 13:50:48,646 Epoch: [104][80/500] Time 0.029 (0.023) Data 0.002 (0.005) Loss 0.0603 (0.0657) Prec@1 88.000 (88.667) Prec@5 99.000 (99.444) +2022-11-14 13:50:48,922 Epoch: [104][90/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.0782 (0.0670) Prec@1 87.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 13:50:49,206 Epoch: [104][100/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0658 (0.0669) Prec@1 90.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 13:50:49,485 Epoch: [104][110/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0599 (0.0663) Prec@1 89.000 (88.667) Prec@5 100.000 (99.583) +2022-11-14 13:50:49,781 Epoch: [104][120/500] Time 0.030 (0.024) Data 0.001 (0.004) Loss 0.0950 (0.0685) Prec@1 84.000 (88.308) Prec@5 99.000 (99.538) +2022-11-14 13:50:50,066 Epoch: [104][130/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0764 (0.0691) Prec@1 89.000 (88.357) Prec@5 100.000 (99.571) +2022-11-14 13:50:50,354 Epoch: [104][140/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0480 (0.0677) Prec@1 92.000 (88.600) Prec@5 99.000 (99.533) +2022-11-14 13:50:50,646 Epoch: [104][150/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0685 (0.0677) Prec@1 85.000 (88.375) Prec@5 100.000 (99.562) +2022-11-14 13:50:50,920 Epoch: [104][160/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0665 (0.0677) Prec@1 90.000 (88.471) Prec@5 97.000 (99.412) +2022-11-14 13:50:51,205 Epoch: [104][170/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0762 (0.0681) Prec@1 89.000 (88.500) Prec@5 100.000 (99.444) +2022-11-14 13:50:51,485 Epoch: [104][180/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0548 (0.0674) Prec@1 92.000 (88.684) Prec@5 97.000 (99.316) +2022-11-14 13:50:51,875 Epoch: [104][190/500] Time 0.046 (0.025) Data 0.002 (0.003) Loss 0.0603 (0.0671) Prec@1 89.000 (88.700) Prec@5 100.000 (99.350) +2022-11-14 13:50:52,382 Epoch: [104][200/500] Time 0.050 (0.026) Data 0.002 (0.003) Loss 0.0636 (0.0669) Prec@1 90.000 (88.762) Prec@5 100.000 (99.381) +2022-11-14 13:50:52,885 Epoch: [104][210/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.0660 (0.0669) Prec@1 91.000 (88.864) Prec@5 97.000 (99.273) +2022-11-14 13:50:53,377 Epoch: [104][220/500] Time 0.055 (0.027) Data 0.002 (0.003) Loss 0.0504 (0.0661) Prec@1 93.000 (89.043) Prec@5 100.000 (99.304) +2022-11-14 13:50:53,875 Epoch: [104][230/500] Time 0.052 (0.028) Data 0.002 (0.003) Loss 0.0628 (0.0660) Prec@1 89.000 (89.042) Prec@5 99.000 (99.292) +2022-11-14 13:50:54,366 Epoch: [104][240/500] Time 0.054 (0.029) Data 0.002 (0.003) Loss 0.0766 (0.0664) Prec@1 89.000 (89.040) Prec@5 99.000 (99.280) +2022-11-14 13:50:54,845 Epoch: [104][250/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0700 (0.0666) Prec@1 89.000 (89.038) Prec@5 97.000 (99.192) +2022-11-14 13:50:55,380 Epoch: [104][260/500] Time 0.060 (0.030) Data 0.002 (0.003) Loss 0.0739 (0.0668) Prec@1 88.000 (89.000) Prec@5 100.000 (99.222) +2022-11-14 13:50:55,886 Epoch: [104][270/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0502 (0.0663) Prec@1 92.000 (89.107) Prec@5 100.000 (99.250) +2022-11-14 13:50:56,366 Epoch: [104][280/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0758 (0.0666) Prec@1 87.000 (89.034) Prec@5 100.000 (99.276) +2022-11-14 13:50:56,837 Epoch: [104][290/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0741 (0.0668) Prec@1 88.000 (89.000) Prec@5 98.000 (99.233) +2022-11-14 13:50:57,351 Epoch: [104][300/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0636 (0.0667) Prec@1 89.000 (89.000) Prec@5 100.000 (99.258) +2022-11-14 13:50:57,872 Epoch: [104][310/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0697 (0.0668) Prec@1 88.000 (88.969) Prec@5 100.000 (99.281) +2022-11-14 13:50:58,330 Epoch: [104][320/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0484 (0.0663) Prec@1 91.000 (89.030) Prec@5 100.000 (99.303) +2022-11-14 13:50:58,809 Epoch: [104][330/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0690 (0.0663) Prec@1 86.000 (88.941) Prec@5 99.000 (99.294) +2022-11-14 13:50:59,292 Epoch: [104][340/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0917 (0.0671) Prec@1 84.000 (88.800) Prec@5 98.000 (99.257) +2022-11-14 13:50:59,760 Epoch: [104][350/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0708 (0.0672) Prec@1 88.000 (88.778) Prec@5 100.000 (99.278) +2022-11-14 13:51:00,234 Epoch: [104][360/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0879 (0.0677) Prec@1 86.000 (88.703) Prec@5 100.000 (99.297) +2022-11-14 13:51:00,704 Epoch: [104][370/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.1220 (0.0692) Prec@1 76.000 (88.368) Prec@5 98.000 (99.263) +2022-11-14 13:51:01,184 Epoch: [104][380/500] Time 0.049 (0.034) Data 0.002 (0.002) Loss 0.0789 (0.0694) Prec@1 88.000 (88.359) Prec@5 99.000 (99.256) +2022-11-14 13:51:01,646 Epoch: [104][390/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0441 (0.0688) Prec@1 93.000 (88.475) Prec@5 100.000 (99.275) +2022-11-14 13:51:02,114 Epoch: [104][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0969 (0.0695) Prec@1 83.000 (88.341) Prec@5 100.000 (99.293) +2022-11-14 13:51:02,582 Epoch: [104][410/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0520 (0.0690) Prec@1 92.000 (88.429) Prec@5 100.000 (99.310) +2022-11-14 13:51:03,063 Epoch: [104][420/500] Time 0.053 (0.035) Data 0.002 (0.002) Loss 0.0772 (0.0692) Prec@1 86.000 (88.372) Prec@5 98.000 (99.279) +2022-11-14 13:51:03,559 Epoch: [104][430/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.1081 (0.0701) Prec@1 82.000 (88.227) Prec@5 98.000 (99.250) +2022-11-14 13:51:04,043 Epoch: [104][440/500] Time 0.048 (0.035) Data 0.002 (0.002) Loss 0.0413 (0.0695) Prec@1 94.000 (88.356) Prec@5 100.000 (99.267) +2022-11-14 13:51:04,544 Epoch: [104][450/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0776 (0.0697) Prec@1 85.000 (88.283) Prec@5 99.000 (99.261) +2022-11-14 13:51:04,952 Epoch: [104][460/500] Time 0.030 (0.035) Data 0.002 (0.002) Loss 0.0873 (0.0700) Prec@1 86.000 (88.234) Prec@5 97.000 (99.213) +2022-11-14 13:51:05,263 Epoch: [104][470/500] Time 0.031 (0.035) Data 0.002 (0.002) Loss 0.0528 (0.0697) Prec@1 90.000 (88.271) Prec@5 100.000 (99.229) +2022-11-14 13:51:05,570 Epoch: [104][480/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.1010 (0.0703) Prec@1 81.000 (88.122) Prec@5 99.000 (99.224) +2022-11-14 13:51:05,877 Epoch: [104][490/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0701 (0.0703) Prec@1 88.000 (88.120) Prec@5 100.000 (99.240) +2022-11-14 13:51:06,154 Epoch: [104][499/500] Time 0.028 (0.035) Data 0.001 (0.002) Loss 0.0688 (0.0703) Prec@1 89.000 (88.137) Prec@5 99.000 (99.235) +2022-11-14 13:51:06,437 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0582 (0.0582) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:06,446 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0657) Prec@1 88.000 (90.500) Prec@5 99.000 (99.000) +2022-11-14 13:51:06,457 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0770) Prec@1 82.000 (87.667) Prec@5 99.000 (99.000) +2022-11-14 13:51:06,468 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0827) Prec@1 81.000 (86.000) Prec@5 100.000 (99.250) +2022-11-14 13:51:06,477 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0863) Prec@1 83.000 (85.400) Prec@5 99.000 (99.200) +2022-11-14 13:51:06,484 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0821) Prec@1 90.000 (86.167) Prec@5 100.000 (99.333) +2022-11-14 13:51:06,492 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0792) Prec@1 90.000 (86.714) Prec@5 100.000 (99.429) +2022-11-14 13:51:06,501 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0829) Prec@1 81.000 (86.000) Prec@5 100.000 (99.500) +2022-11-14 13:51:06,508 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0833) Prec@1 84.000 (85.778) Prec@5 99.000 (99.444) +2022-11-14 13:51:06,517 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0825) Prec@1 88.000 (86.000) Prec@5 98.000 (99.300) +2022-11-14 13:51:06,526 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0823) Prec@1 87.000 (86.091) Prec@5 100.000 (99.364) +2022-11-14 13:51:06,535 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0833) Prec@1 84.000 (85.917) Prec@5 99.000 (99.333) +2022-11-14 13:51:06,544 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0836) Prec@1 87.000 (86.000) Prec@5 99.000 (99.308) +2022-11-14 13:51:06,554 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0827) Prec@1 90.000 (86.286) Prec@5 99.000 (99.286) +2022-11-14 13:51:06,563 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0839) Prec@1 81.000 (85.933) Prec@5 99.000 (99.267) +2022-11-14 13:51:06,573 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0845) Prec@1 82.000 (85.688) Prec@5 100.000 (99.312) +2022-11-14 13:51:06,582 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0834) Prec@1 91.000 (86.000) Prec@5 99.000 (99.294) +2022-11-14 13:51:06,592 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0843) Prec@1 84.000 (85.889) Prec@5 100.000 (99.333) +2022-11-14 13:51:06,601 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0835) Prec@1 88.000 (86.000) Prec@5 99.000 (99.316) +2022-11-14 13:51:06,609 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0835) Prec@1 87.000 (86.050) Prec@5 99.000 (99.300) +2022-11-14 13:51:06,618 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1210 (0.0852) Prec@1 79.000 (85.714) Prec@5 99.000 (99.286) +2022-11-14 13:51:06,627 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.0862) Prec@1 81.000 (85.500) Prec@5 99.000 (99.273) +2022-11-14 13:51:06,636 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0868) Prec@1 86.000 (85.522) Prec@5 98.000 (99.217) +2022-11-14 13:51:06,645 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0866) Prec@1 85.000 (85.500) Prec@5 99.000 (99.208) +2022-11-14 13:51:06,653 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0869) Prec@1 85.000 (85.480) Prec@5 99.000 (99.200) +2022-11-14 13:51:06,662 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1445 (0.0891) Prec@1 73.000 (85.000) Prec@5 97.000 (99.115) +2022-11-14 13:51:06,671 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0891) Prec@1 88.000 (85.111) Prec@5 100.000 (99.148) +2022-11-14 13:51:06,680 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0887) Prec@1 88.000 (85.214) Prec@5 100.000 (99.179) +2022-11-14 13:51:06,688 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0888) Prec@1 84.000 (85.172) Prec@5 100.000 (99.207) +2022-11-14 13:51:06,699 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0886) Prec@1 85.000 (85.167) Prec@5 99.000 (99.200) +2022-11-14 13:51:06,709 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0886) Prec@1 84.000 (85.129) Prec@5 100.000 (99.226) +2022-11-14 13:51:06,719 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0887) Prec@1 84.000 (85.094) Prec@5 100.000 (99.250) +2022-11-14 13:51:06,728 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0890) Prec@1 84.000 (85.061) Prec@5 97.000 (99.182) +2022-11-14 13:51:06,737 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1325 (0.0902) Prec@1 76.000 (84.794) Prec@5 99.000 (99.176) +2022-11-14 13:51:06,747 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0903) Prec@1 83.000 (84.743) Prec@5 98.000 (99.143) +2022-11-14 13:51:06,755 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0909) Prec@1 82.000 (84.667) Prec@5 99.000 (99.139) +2022-11-14 13:51:06,763 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0909) Prec@1 84.000 (84.649) Prec@5 99.000 (99.135) +2022-11-14 13:51:06,771 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0911) Prec@1 78.000 (84.474) Prec@5 100.000 (99.158) +2022-11-14 13:51:06,779 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0910) Prec@1 83.000 (84.436) Prec@5 99.000 (99.154) +2022-11-14 13:51:06,787 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0908) Prec@1 85.000 (84.450) Prec@5 100.000 (99.175) +2022-11-14 13:51:06,795 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0910) Prec@1 81.000 (84.366) Prec@5 98.000 (99.146) +2022-11-14 13:51:06,804 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0908) Prec@1 83.000 (84.333) Prec@5 100.000 (99.167) +2022-11-14 13:51:06,813 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0901) Prec@1 92.000 (84.512) Prec@5 99.000 (99.163) +2022-11-14 13:51:06,823 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0896) Prec@1 89.000 (84.614) Prec@5 98.000 (99.136) +2022-11-14 13:51:06,831 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1162 (0.0902) Prec@1 79.000 (84.489) Prec@5 100.000 (99.156) +2022-11-14 13:51:06,840 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0905) Prec@1 80.000 (84.391) Prec@5 100.000 (99.174) +2022-11-14 13:51:06,849 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0903) Prec@1 85.000 (84.404) Prec@5 100.000 (99.191) +2022-11-14 13:51:06,859 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1186 (0.0909) Prec@1 81.000 (84.333) Prec@5 99.000 (99.188) +2022-11-14 13:51:06,867 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0905) Prec@1 88.000 (84.408) Prec@5 100.000 (99.204) +2022-11-14 13:51:06,877 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1244 (0.0912) Prec@1 79.000 (84.300) Prec@5 100.000 (99.220) +2022-11-14 13:51:06,886 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0909) Prec@1 88.000 (84.373) Prec@5 100.000 (99.235) +2022-11-14 13:51:06,895 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1152 (0.0914) Prec@1 82.000 (84.327) Prec@5 97.000 (99.192) +2022-11-14 13:51:06,904 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0911) Prec@1 88.000 (84.396) Prec@5 99.000 (99.189) +2022-11-14 13:51:06,913 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0910) Prec@1 84.000 (84.389) Prec@5 98.000 (99.167) +2022-11-14 13:51:06,921 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0910) Prec@1 82.000 (84.345) Prec@5 100.000 (99.182) +2022-11-14 13:51:06,930 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0909) Prec@1 88.000 (84.411) Prec@5 99.000 (99.179) +2022-11-14 13:51:06,939 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0906) Prec@1 87.000 (84.456) Prec@5 99.000 (99.175) +2022-11-14 13:51:06,949 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0902) Prec@1 87.000 (84.500) Prec@5 99.000 (99.172) +2022-11-14 13:51:06,958 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0906) Prec@1 83.000 (84.475) Prec@5 100.000 (99.186) +2022-11-14 13:51:06,968 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0907) Prec@1 83.000 (84.450) Prec@5 100.000 (99.200) +2022-11-14 13:51:06,978 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0908) Prec@1 84.000 (84.443) Prec@5 100.000 (99.213) +2022-11-14 13:51:06,987 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0903) Prec@1 91.000 (84.548) Prec@5 98.000 (99.194) +2022-11-14 13:51:06,997 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0901) Prec@1 85.000 (84.556) Prec@5 100.000 (99.206) +2022-11-14 13:51:07,005 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0898) Prec@1 89.000 (84.625) Prec@5 100.000 (99.219) +2022-11-14 13:51:07,014 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1085 (0.0901) Prec@1 80.000 (84.554) Prec@5 98.000 (99.200) +2022-11-14 13:51:07,024 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0903) Prec@1 81.000 (84.500) Prec@5 99.000 (99.197) +2022-11-14 13:51:07,033 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0901) Prec@1 88.000 (84.552) Prec@5 98.000 (99.179) +2022-11-14 13:51:07,042 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0900) Prec@1 87.000 (84.588) Prec@5 99.000 (99.176) +2022-11-14 13:51:07,051 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0899) Prec@1 85.000 (84.594) Prec@5 100.000 (99.188) +2022-11-14 13:51:07,060 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0900) Prec@1 85.000 (84.600) Prec@5 98.000 (99.171) +2022-11-14 13:51:07,069 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0901) Prec@1 85.000 (84.606) Prec@5 99.000 (99.169) +2022-11-14 13:51:07,078 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0899) Prec@1 85.000 (84.611) Prec@5 100.000 (99.181) +2022-11-14 13:51:07,086 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0896) Prec@1 88.000 (84.658) Prec@5 98.000 (99.164) +2022-11-14 13:51:07,095 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0893) Prec@1 87.000 (84.689) Prec@5 100.000 (99.176) +2022-11-14 13:51:07,104 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0894) Prec@1 83.000 (84.667) Prec@5 100.000 (99.187) +2022-11-14 13:51:07,115 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0893) Prec@1 84.000 (84.658) Prec@5 100.000 (99.197) +2022-11-14 13:51:07,124 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0895) Prec@1 83.000 (84.636) Prec@5 98.000 (99.182) +2022-11-14 13:51:07,132 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0893) Prec@1 88.000 (84.679) Prec@5 100.000 (99.192) +2022-11-14 13:51:07,143 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.0895) Prec@1 81.000 (84.633) Prec@5 100.000 (99.203) +2022-11-14 13:51:07,152 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0898) Prec@1 79.000 (84.562) Prec@5 97.000 (99.175) +2022-11-14 13:51:07,163 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0901) Prec@1 82.000 (84.531) Prec@5 99.000 (99.173) +2022-11-14 13:51:07,173 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0902) Prec@1 84.000 (84.524) Prec@5 100.000 (99.183) +2022-11-14 13:51:07,183 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0902) Prec@1 85.000 (84.530) Prec@5 99.000 (99.181) +2022-11-14 13:51:07,193 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0899) Prec@1 88.000 (84.571) Prec@5 100.000 (99.190) +2022-11-14 13:51:07,202 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0902) Prec@1 80.000 (84.518) Prec@5 98.000 (99.176) +2022-11-14 13:51:07,212 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0903) Prec@1 85.000 (84.523) Prec@5 98.000 (99.163) +2022-11-14 13:51:07,221 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0901) Prec@1 88.000 (84.563) Prec@5 99.000 (99.161) +2022-11-14 13:51:07,231 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0901) Prec@1 86.000 (84.580) Prec@5 99.000 (99.159) +2022-11-14 13:51:07,240 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0899) Prec@1 88.000 (84.618) Prec@5 99.000 (99.157) +2022-11-14 13:51:07,250 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0898) Prec@1 84.000 (84.611) Prec@5 100.000 (99.167) +2022-11-14 13:51:07,259 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0897) Prec@1 85.000 (84.615) Prec@5 100.000 (99.176) +2022-11-14 13:51:07,268 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0893) Prec@1 90.000 (84.674) Prec@5 99.000 (99.174) +2022-11-14 13:51:07,277 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0895) Prec@1 81.000 (84.634) Prec@5 99.000 (99.172) +2022-11-14 13:51:07,287 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0894) Prec@1 88.000 (84.670) Prec@5 97.000 (99.149) +2022-11-14 13:51:07,298 Test: [94/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0894) Prec@1 81.000 (84.632) Prec@5 99.000 (99.147) +2022-11-14 13:51:07,308 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0893) Prec@1 87.000 (84.656) Prec@5 100.000 (99.156) +2022-11-14 13:51:07,318 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0890) Prec@1 90.000 (84.711) Prec@5 99.000 (99.155) +2022-11-14 13:51:07,327 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0891) Prec@1 84.000 (84.704) Prec@5 99.000 (99.153) +2022-11-14 13:51:07,338 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0892) Prec@1 82.000 (84.677) Prec@5 100.000 (99.162) +2022-11-14 13:51:07,347 Test: [99/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0891) Prec@1 89.000 (84.720) Prec@5 99.000 (99.160) +2022-11-14 13:51:07,409 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:51:07,716 Epoch: [105][0/500] Time 0.023 (0.023) Data 0.223 (0.223) Loss 0.0496 (0.0496) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:07,914 Epoch: [105][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0601 (0.0548) Prec@1 87.000 (88.500) Prec@5 97.000 (98.000) +2022-11-14 13:51:08,107 Epoch: [105][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0822 (0.0640) Prec@1 86.000 (87.667) Prec@5 98.000 (98.000) +2022-11-14 13:51:08,318 Epoch: [105][30/500] Time 0.021 (0.018) Data 0.002 (0.009) Loss 0.0557 (0.0619) Prec@1 91.000 (88.500) Prec@5 100.000 (98.500) +2022-11-14 13:51:08,609 Epoch: [105][40/500] Time 0.035 (0.020) Data 0.002 (0.007) Loss 0.0657 (0.0627) Prec@1 87.000 (88.200) Prec@5 100.000 (98.800) +2022-11-14 13:51:08,939 Epoch: [105][50/500] Time 0.032 (0.022) Data 0.002 (0.006) Loss 0.0496 (0.0605) Prec@1 95.000 (89.333) Prec@5 97.000 (98.500) +2022-11-14 13:51:09,272 Epoch: [105][60/500] Time 0.032 (0.023) Data 0.002 (0.005) Loss 0.0582 (0.0602) Prec@1 90.000 (89.429) Prec@5 100.000 (98.714) +2022-11-14 13:51:09,607 Epoch: [105][70/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0528 (0.0592) Prec@1 91.000 (89.625) Prec@5 100.000 (98.875) +2022-11-14 13:51:09,948 Epoch: [105][80/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0815 (0.0617) Prec@1 88.000 (89.444) Prec@5 100.000 (99.000) +2022-11-14 13:51:10,278 Epoch: [105][90/500] Time 0.031 (0.025) Data 0.001 (0.004) Loss 0.0856 (0.0641) Prec@1 83.000 (88.800) Prec@5 100.000 (99.100) +2022-11-14 13:51:10,616 Epoch: [105][100/500] Time 0.031 (0.026) Data 0.003 (0.004) Loss 0.0656 (0.0642) Prec@1 86.000 (88.545) Prec@5 99.000 (99.091) +2022-11-14 13:51:10,946 Epoch: [105][110/500] Time 0.032 (0.026) Data 0.002 (0.004) Loss 0.0577 (0.0637) Prec@1 89.000 (88.583) Prec@5 100.000 (99.167) +2022-11-14 13:51:11,284 Epoch: [105][120/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0946 (0.0661) Prec@1 81.000 (88.000) Prec@5 98.000 (99.077) +2022-11-14 13:51:11,618 Epoch: [105][130/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0776 (0.0669) Prec@1 88.000 (88.000) Prec@5 100.000 (99.143) +2022-11-14 13:51:11,958 Epoch: [105][140/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0498 (0.0657) Prec@1 92.000 (88.267) Prec@5 100.000 (99.200) +2022-11-14 13:51:12,290 Epoch: [105][150/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0626 (0.0655) Prec@1 91.000 (88.438) Prec@5 100.000 (99.250) +2022-11-14 13:51:12,633 Epoch: [105][160/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0563 (0.0650) Prec@1 91.000 (88.588) Prec@5 99.000 (99.235) +2022-11-14 13:51:12,971 Epoch: [105][170/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0821 (0.0659) Prec@1 85.000 (88.389) Prec@5 100.000 (99.278) +2022-11-14 13:51:13,305 Epoch: [105][180/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0650 (0.0659) Prec@1 90.000 (88.474) Prec@5 98.000 (99.211) +2022-11-14 13:51:13,644 Epoch: [105][190/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0715 (0.0662) Prec@1 90.000 (88.550) Prec@5 100.000 (99.250) +2022-11-14 13:51:13,980 Epoch: [105][200/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0460 (0.0652) Prec@1 94.000 (88.810) Prec@5 100.000 (99.286) +2022-11-14 13:51:14,321 Epoch: [105][210/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0698 (0.0654) Prec@1 89.000 (88.818) Prec@5 98.000 (99.227) +2022-11-14 13:51:14,651 Epoch: [105][220/500] Time 0.031 (0.028) Data 0.001 (0.003) Loss 0.0688 (0.0656) Prec@1 88.000 (88.783) Prec@5 100.000 (99.261) +2022-11-14 13:51:14,986 Epoch: [105][230/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0589 (0.0653) Prec@1 90.000 (88.833) Prec@5 99.000 (99.250) +2022-11-14 13:51:15,324 Epoch: [105][240/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0683 (0.0654) Prec@1 88.000 (88.800) Prec@5 98.000 (99.200) +2022-11-14 13:51:15,663 Epoch: [105][250/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0864 (0.0662) Prec@1 85.000 (88.654) Prec@5 98.000 (99.154) +2022-11-14 13:51:16,008 Epoch: [105][260/500] Time 0.037 (0.028) Data 0.002 (0.003) Loss 0.0646 (0.0662) Prec@1 89.000 (88.667) Prec@5 100.000 (99.185) +2022-11-14 13:51:16,345 Epoch: [105][270/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0700 (0.0663) Prec@1 89.000 (88.679) Prec@5 99.000 (99.179) +2022-11-14 13:51:16,682 Epoch: [105][280/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0603 (0.0661) Prec@1 90.000 (88.724) Prec@5 98.000 (99.138) +2022-11-14 13:51:17,012 Epoch: [105][290/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0512 (0.0656) Prec@1 91.000 (88.800) Prec@5 99.000 (99.133) +2022-11-14 13:51:17,350 Epoch: [105][300/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0796 (0.0661) Prec@1 88.000 (88.774) Prec@5 100.000 (99.161) +2022-11-14 13:51:17,679 Epoch: [105][310/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0712 (0.0662) Prec@1 88.000 (88.750) Prec@5 99.000 (99.156) +2022-11-14 13:51:18,016 Epoch: [105][320/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0536 (0.0658) Prec@1 92.000 (88.848) Prec@5 100.000 (99.182) +2022-11-14 13:51:18,354 Epoch: [105][330/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0533 (0.0655) Prec@1 93.000 (88.971) Prec@5 100.000 (99.206) +2022-11-14 13:51:18,703 Epoch: [105][340/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0862 (0.0661) Prec@1 86.000 (88.886) Prec@5 99.000 (99.200) +2022-11-14 13:51:19,039 Epoch: [105][350/500] Time 0.030 (0.029) Data 0.002 (0.002) Loss 0.1122 (0.0673) Prec@1 83.000 (88.722) Prec@5 98.000 (99.167) +2022-11-14 13:51:19,371 Epoch: [105][360/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.1019 (0.0683) Prec@1 83.000 (88.568) Prec@5 99.000 (99.162) +2022-11-14 13:51:19,710 Epoch: [105][370/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.1187 (0.0696) Prec@1 79.000 (88.316) Prec@5 99.000 (99.158) +2022-11-14 13:51:20,045 Epoch: [105][380/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0625 (0.0694) Prec@1 88.000 (88.308) Prec@5 100.000 (99.179) +2022-11-14 13:51:20,394 Epoch: [105][390/500] Time 0.036 (0.029) Data 0.003 (0.002) Loss 0.0470 (0.0689) Prec@1 94.000 (88.450) Prec@5 100.000 (99.200) +2022-11-14 13:51:20,728 Epoch: [105][400/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0689 (0.0689) Prec@1 88.000 (88.439) Prec@5 99.000 (99.195) +2022-11-14 13:51:21,081 Epoch: [105][410/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0823 (0.0692) Prec@1 89.000 (88.452) Prec@5 98.000 (99.167) +2022-11-14 13:51:21,426 Epoch: [105][420/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0689 (0.0692) Prec@1 85.000 (88.372) Prec@5 100.000 (99.186) +2022-11-14 13:51:21,773 Epoch: [105][430/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0695 (0.0692) Prec@1 89.000 (88.386) Prec@5 97.000 (99.136) +2022-11-14 13:51:22,125 Epoch: [105][440/500] Time 0.036 (0.029) Data 0.002 (0.002) Loss 0.0825 (0.0695) Prec@1 85.000 (88.311) Prec@5 100.000 (99.156) +2022-11-14 13:51:22,452 Epoch: [105][450/500] Time 0.028 (0.029) Data 0.002 (0.002) Loss 0.1004 (0.0701) Prec@1 85.000 (88.239) Prec@5 98.000 (99.130) +2022-11-14 13:51:22,791 Epoch: [105][460/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0538 (0.0698) Prec@1 92.000 (88.319) Prec@5 100.000 (99.149) +2022-11-14 13:51:23,133 Epoch: [105][470/500] Time 0.039 (0.029) Data 0.002 (0.002) Loss 0.0483 (0.0693) Prec@1 94.000 (88.438) Prec@5 99.000 (99.146) +2022-11-14 13:51:23,475 Epoch: [105][480/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0569 (0.0691) Prec@1 92.000 (88.510) Prec@5 100.000 (99.163) +2022-11-14 13:51:23,809 Epoch: [105][490/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0753 (0.0692) Prec@1 86.000 (88.460) Prec@5 99.000 (99.160) +2022-11-14 13:51:24,116 Epoch: [105][499/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0601 (0.0690) Prec@1 90.000 (88.490) Prec@5 100.000 (99.176) +2022-11-14 13:51:24,393 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0544 (0.0544) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:51:24,400 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0639) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 13:51:24,409 Test: [2/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0729) Prec@1 83.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 13:51:24,421 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0770) Prec@1 83.000 (86.250) Prec@5 98.000 (99.500) +2022-11-14 13:51:24,429 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0810) Prec@1 85.000 (86.000) Prec@5 99.000 (99.400) +2022-11-14 13:51:24,438 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0758) Prec@1 90.000 (86.667) Prec@5 99.000 (99.333) +2022-11-14 13:51:24,448 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0748) Prec@1 89.000 (87.000) Prec@5 100.000 (99.429) +2022-11-14 13:51:24,458 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1137 (0.0797) Prec@1 79.000 (86.000) Prec@5 99.000 (99.375) +2022-11-14 13:51:24,468 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.0839) Prec@1 77.000 (85.000) Prec@5 99.000 (99.333) +2022-11-14 13:51:24,478 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0827) Prec@1 85.000 (85.000) Prec@5 98.000 (99.200) +2022-11-14 13:51:24,489 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0815) Prec@1 89.000 (85.364) Prec@5 100.000 (99.273) +2022-11-14 13:51:24,500 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0812) Prec@1 87.000 (85.500) Prec@5 100.000 (99.333) +2022-11-14 13:51:24,512 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0800) Prec@1 89.000 (85.769) Prec@5 100.000 (99.385) +2022-11-14 13:51:24,521 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0806) Prec@1 84.000 (85.643) Prec@5 100.000 (99.429) +2022-11-14 13:51:24,530 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0806) Prec@1 84.000 (85.533) Prec@5 99.000 (99.400) +2022-11-14 13:51:24,539 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0816) Prec@1 82.000 (85.312) Prec@5 98.000 (99.312) +2022-11-14 13:51:24,550 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0802) Prec@1 90.000 (85.588) Prec@5 98.000 (99.235) +2022-11-14 13:51:24,561 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0820) Prec@1 82.000 (85.389) Prec@5 99.000 (99.222) +2022-11-14 13:51:24,574 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0821) Prec@1 86.000 (85.421) Prec@5 99.000 (99.211) +2022-11-14 13:51:24,587 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0836) Prec@1 82.000 (85.250) Prec@5 96.000 (99.050) +2022-11-14 13:51:24,600 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0840) Prec@1 84.000 (85.190) Prec@5 100.000 (99.095) +2022-11-14 13:51:24,611 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0847) Prec@1 83.000 (85.091) Prec@5 99.000 (99.091) +2022-11-14 13:51:24,622 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0854) Prec@1 83.000 (85.000) Prec@5 98.000 (99.043) +2022-11-14 13:51:24,635 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0849) Prec@1 86.000 (85.042) Prec@5 100.000 (99.083) +2022-11-14 13:51:24,646 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0858) Prec@1 84.000 (85.000) Prec@5 99.000 (99.080) +2022-11-14 13:51:24,659 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1236 (0.0873) Prec@1 78.000 (84.731) Prec@5 99.000 (99.077) +2022-11-14 13:51:24,672 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0868) Prec@1 87.000 (84.815) Prec@5 100.000 (99.111) +2022-11-14 13:51:24,684 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0866) Prec@1 85.000 (84.821) Prec@5 100.000 (99.143) +2022-11-14 13:51:24,696 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0866) Prec@1 86.000 (84.862) Prec@5 98.000 (99.103) +2022-11-14 13:51:24,709 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0860) Prec@1 88.000 (84.967) Prec@5 99.000 (99.100) +2022-11-14 13:51:24,723 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0862) Prec@1 83.000 (84.903) Prec@5 99.000 (99.097) +2022-11-14 13:51:24,736 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0862) Prec@1 84.000 (84.875) Prec@5 99.000 (99.094) +2022-11-14 13:51:24,749 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0870) Prec@1 80.000 (84.727) Prec@5 96.000 (99.000) +2022-11-14 13:51:24,762 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0868) Prec@1 84.000 (84.706) Prec@5 99.000 (99.000) +2022-11-14 13:51:24,774 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0863) Prec@1 87.000 (84.771) Prec@5 99.000 (99.000) +2022-11-14 13:51:24,784 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0865) Prec@1 87.000 (84.833) Prec@5 99.000 (99.000) +2022-11-14 13:51:24,797 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0867) Prec@1 84.000 (84.811) Prec@5 99.000 (99.000) +2022-11-14 13:51:24,810 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0864) Prec@1 88.000 (84.895) Prec@5 98.000 (98.974) +2022-11-14 13:51:24,822 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0862) Prec@1 88.000 (84.974) Prec@5 98.000 (98.949) +2022-11-14 13:51:24,833 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0859) Prec@1 86.000 (85.000) Prec@5 99.000 (98.950) +2022-11-14 13:51:24,847 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0861) Prec@1 85.000 (85.000) Prec@5 97.000 (98.902) +2022-11-14 13:51:24,862 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0861) Prec@1 84.000 (84.976) Prec@5 98.000 (98.881) +2022-11-14 13:51:24,874 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0855) Prec@1 90.000 (85.093) Prec@5 98.000 (98.860) +2022-11-14 13:51:24,887 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0852) Prec@1 88.000 (85.159) Prec@5 100.000 (98.886) +2022-11-14 13:51:24,898 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0855) Prec@1 83.000 (85.111) Prec@5 99.000 (98.889) +2022-11-14 13:51:24,909 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0854) Prec@1 87.000 (85.152) Prec@5 98.000 (98.870) +2022-11-14 13:51:24,920 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0854) Prec@1 85.000 (85.149) Prec@5 100.000 (98.894) +2022-11-14 13:51:24,929 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0857) Prec@1 81.000 (85.062) Prec@5 100.000 (98.917) +2022-11-14 13:51:24,940 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0850) Prec@1 91.000 (85.184) Prec@5 100.000 (98.939) +2022-11-14 13:51:24,951 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0856) Prec@1 80.000 (85.080) Prec@5 99.000 (98.940) +2022-11-14 13:51:24,963 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0854) Prec@1 86.000 (85.098) Prec@5 100.000 (98.961) +2022-11-14 13:51:24,975 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0860) Prec@1 81.000 (85.019) Prec@5 98.000 (98.942) +2022-11-14 13:51:24,986 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0859) Prec@1 85.000 (85.019) Prec@5 100.000 (98.962) +2022-11-14 13:51:24,999 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0859) Prec@1 85.000 (85.019) Prec@5 97.000 (98.926) +2022-11-14 13:51:25,012 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0857) Prec@1 86.000 (85.036) Prec@5 100.000 (98.945) +2022-11-14 13:51:25,025 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0857) Prec@1 87.000 (85.071) Prec@5 99.000 (98.946) +2022-11-14 13:51:25,037 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0858) Prec@1 85.000 (85.070) Prec@5 99.000 (98.947) +2022-11-14 13:51:25,048 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0854) Prec@1 90.000 (85.155) Prec@5 98.000 (98.931) +2022-11-14 13:51:25,061 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0858) Prec@1 84.000 (85.136) Prec@5 100.000 (98.949) +2022-11-14 13:51:25,072 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0859) Prec@1 84.000 (85.117) Prec@5 99.000 (98.950) +2022-11-14 13:51:25,083 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0856) Prec@1 89.000 (85.180) Prec@5 100.000 (98.967) +2022-11-14 13:51:25,096 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0858) Prec@1 83.000 (85.145) Prec@5 99.000 (98.968) +2022-11-14 13:51:25,108 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0855) Prec@1 85.000 (85.143) Prec@5 100.000 (98.984) +2022-11-14 13:51:25,119 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0852) Prec@1 87.000 (85.172) Prec@5 99.000 (98.984) +2022-11-14 13:51:25,132 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0855) Prec@1 81.000 (85.108) Prec@5 99.000 (98.985) +2022-11-14 13:51:25,144 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0856) Prec@1 85.000 (85.106) Prec@5 98.000 (98.970) +2022-11-14 13:51:25,156 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0854) Prec@1 87.000 (85.134) Prec@5 99.000 (98.970) +2022-11-14 13:51:25,168 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0856) Prec@1 80.000 (85.059) Prec@5 96.000 (98.926) +2022-11-14 13:51:25,181 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0856) Prec@1 87.000 (85.087) Prec@5 100.000 (98.942) +2022-11-14 13:51:25,193 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0858) Prec@1 83.000 (85.057) Prec@5 99.000 (98.943) +2022-11-14 13:51:25,205 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0856) Prec@1 88.000 (85.099) Prec@5 100.000 (98.958) +2022-11-14 13:51:25,217 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0854) Prec@1 89.000 (85.153) Prec@5 100.000 (98.972) +2022-11-14 13:51:25,229 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0851) Prec@1 91.000 (85.233) Prec@5 99.000 (98.973) +2022-11-14 13:51:25,241 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0849) Prec@1 88.000 (85.270) Prec@5 99.000 (98.973) +2022-11-14 13:51:25,252 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0850) Prec@1 85.000 (85.267) Prec@5 98.000 (98.960) +2022-11-14 13:51:25,264 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0847) Prec@1 88.000 (85.303) Prec@5 100.000 (98.974) +2022-11-14 13:51:25,276 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0849) Prec@1 82.000 (85.260) Prec@5 100.000 (98.987) +2022-11-14 13:51:25,288 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0848) Prec@1 84.000 (85.244) Prec@5 99.000 (98.987) +2022-11-14 13:51:25,298 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0850) Prec@1 83.000 (85.215) Prec@5 99.000 (98.987) +2022-11-14 13:51:25,309 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0850) Prec@1 85.000 (85.213) Prec@5 99.000 (98.987) +2022-11-14 13:51:25,320 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0852) Prec@1 84.000 (85.198) Prec@5 98.000 (98.975) +2022-11-14 13:51:25,334 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0853) Prec@1 82.000 (85.159) Prec@5 100.000 (98.988) +2022-11-14 13:51:25,347 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0857) Prec@1 77.000 (85.060) Prec@5 100.000 (99.000) +2022-11-14 13:51:25,360 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0856) Prec@1 86.000 (85.071) Prec@5 100.000 (99.012) +2022-11-14 13:51:25,373 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.0860) Prec@1 82.000 (85.035) Prec@5 99.000 (99.012) +2022-11-14 13:51:25,385 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0862) Prec@1 84.000 (85.023) Prec@5 99.000 (99.012) +2022-11-14 13:51:25,395 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0863) Prec@1 80.000 (84.966) Prec@5 99.000 (99.011) +2022-11-14 13:51:25,408 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0863) Prec@1 88.000 (85.000) Prec@5 100.000 (99.023) +2022-11-14 13:51:25,419 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0861) Prec@1 89.000 (85.045) Prec@5 99.000 (99.022) +2022-11-14 13:51:25,430 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0861) Prec@1 83.000 (85.022) Prec@5 98.000 (99.011) +2022-11-14 13:51:25,442 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0858) Prec@1 91.000 (85.088) Prec@5 100.000 (99.022) +2022-11-14 13:51:25,454 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0853) Prec@1 93.000 (85.174) Prec@5 100.000 (99.033) +2022-11-14 13:51:25,465 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0851) Prec@1 90.000 (85.226) Prec@5 100.000 (99.043) +2022-11-14 13:51:25,478 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0850) Prec@1 88.000 (85.255) Prec@5 100.000 (99.053) +2022-11-14 13:51:25,489 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0849) Prec@1 88.000 (85.284) Prec@5 100.000 (99.063) +2022-11-14 13:51:25,502 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0849) Prec@1 84.000 (85.271) Prec@5 99.000 (99.062) +2022-11-14 13:51:25,514 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0846) Prec@1 91.000 (85.330) Prec@5 100.000 (99.072) +2022-11-14 13:51:25,526 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0849) Prec@1 81.000 (85.286) Prec@5 100.000 (99.082) +2022-11-14 13:51:25,537 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0850) Prec@1 83.000 (85.263) Prec@5 99.000 (99.081) +2022-11-14 13:51:25,548 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0851) Prec@1 83.000 (85.240) Prec@5 99.000 (99.080) +2022-11-14 13:51:25,606 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:51:25,909 Epoch: [106][0/500] Time 0.023 (0.023) Data 0.219 (0.219) Loss 0.0507 (0.0507) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:26,130 Epoch: [106][10/500] Time 0.019 (0.020) Data 0.002 (0.022) Loss 0.0630 (0.0569) Prec@1 87.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 13:51:26,399 Epoch: [106][20/500] Time 0.031 (0.021) Data 0.002 (0.012) Loss 0.0543 (0.0560) Prec@1 91.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 13:51:26,759 Epoch: [106][30/500] Time 0.033 (0.025) Data 0.001 (0.009) Loss 0.0685 (0.0591) Prec@1 86.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 13:51:27,114 Epoch: [106][40/500] Time 0.031 (0.026) Data 0.002 (0.007) Loss 0.0406 (0.0554) Prec@1 92.000 (89.400) Prec@5 100.000 (99.600) +2022-11-14 13:51:27,470 Epoch: [106][50/500] Time 0.032 (0.027) Data 0.001 (0.006) Loss 0.0524 (0.0549) Prec@1 91.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 13:51:27,828 Epoch: [106][60/500] Time 0.033 (0.028) Data 0.001 (0.005) Loss 0.0568 (0.0552) Prec@1 91.000 (89.857) Prec@5 99.000 (99.571) +2022-11-14 13:51:28,177 Epoch: [106][70/500] Time 0.032 (0.028) Data 0.002 (0.005) Loss 0.1044 (0.0613) Prec@1 83.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 13:51:28,537 Epoch: [106][80/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.0544 (0.0606) Prec@1 91.000 (89.222) Prec@5 100.000 (99.556) +2022-11-14 13:51:28,881 Epoch: [106][90/500] Time 0.030 (0.029) Data 0.002 (0.004) Loss 0.0824 (0.0627) Prec@1 86.000 (88.900) Prec@5 100.000 (99.600) +2022-11-14 13:51:29,237 Epoch: [106][100/500] Time 0.033 (0.029) Data 0.002 (0.004) Loss 0.0585 (0.0624) Prec@1 91.000 (89.091) Prec@5 100.000 (99.636) +2022-11-14 13:51:29,591 Epoch: [106][110/500] Time 0.033 (0.030) Data 0.002 (0.004) Loss 0.0730 (0.0632) Prec@1 86.000 (88.833) Prec@5 99.000 (99.583) +2022-11-14 13:51:29,951 Epoch: [106][120/500] Time 0.041 (0.030) Data 0.002 (0.004) Loss 0.0514 (0.0623) Prec@1 92.000 (89.077) Prec@5 100.000 (99.615) +2022-11-14 13:51:30,306 Epoch: [106][130/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0539 (0.0617) Prec@1 94.000 (89.429) Prec@5 100.000 (99.643) +2022-11-14 13:51:30,663 Epoch: [106][140/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0297 (0.0596) Prec@1 97.000 (89.933) Prec@5 100.000 (99.667) +2022-11-14 13:51:31,023 Epoch: [106][150/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0806 (0.0609) Prec@1 88.000 (89.812) Prec@5 99.000 (99.625) +2022-11-14 13:51:31,375 Epoch: [106][160/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0956 (0.0630) Prec@1 84.000 (89.471) Prec@5 96.000 (99.412) +2022-11-14 13:51:31,740 Epoch: [106][170/500] Time 0.029 (0.030) Data 0.002 (0.003) Loss 0.0750 (0.0636) Prec@1 86.000 (89.278) Prec@5 100.000 (99.444) +2022-11-14 13:51:32,090 Epoch: [106][180/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0522 (0.0630) Prec@1 94.000 (89.526) Prec@5 98.000 (99.368) +2022-11-14 13:51:32,447 Epoch: [106][190/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0443 (0.0621) Prec@1 95.000 (89.800) Prec@5 100.000 (99.400) +2022-11-14 13:51:32,804 Epoch: [106][200/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0686 (0.0624) Prec@1 88.000 (89.714) Prec@5 99.000 (99.381) +2022-11-14 13:51:33,160 Epoch: [106][210/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0665 (0.0626) Prec@1 90.000 (89.727) Prec@5 100.000 (99.409) +2022-11-14 13:51:33,520 Epoch: [106][220/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0679 (0.0628) Prec@1 88.000 (89.652) Prec@5 97.000 (99.304) +2022-11-14 13:51:33,870 Epoch: [106][230/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0535 (0.0624) Prec@1 91.000 (89.708) Prec@5 100.000 (99.333) +2022-11-14 13:51:34,229 Epoch: [106][240/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0668 (0.0626) Prec@1 88.000 (89.640) Prec@5 100.000 (99.360) +2022-11-14 13:51:34,588 Epoch: [106][250/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0676 (0.0628) Prec@1 87.000 (89.538) Prec@5 99.000 (99.346) +2022-11-14 13:51:34,947 Epoch: [106][260/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0565 (0.0626) Prec@1 89.000 (89.519) Prec@5 99.000 (99.333) +2022-11-14 13:51:35,307 Epoch: [106][270/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0715 (0.0629) Prec@1 88.000 (89.464) Prec@5 99.000 (99.321) +2022-11-14 13:51:35,669 Epoch: [106][280/500] Time 0.034 (0.031) Data 0.001 (0.003) Loss 0.0717 (0.0632) Prec@1 86.000 (89.345) Prec@5 99.000 (99.310) +2022-11-14 13:51:36,025 Epoch: [106][290/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0621 (0.0632) Prec@1 90.000 (89.367) Prec@5 100.000 (99.333) +2022-11-14 13:51:36,386 Epoch: [106][300/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0839 (0.0638) Prec@1 83.000 (89.161) Prec@5 100.000 (99.355) +2022-11-14 13:51:36,744 Epoch: [106][310/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0513 (0.0634) Prec@1 93.000 (89.281) Prec@5 100.000 (99.375) +2022-11-14 13:51:37,105 Epoch: [106][320/500] Time 0.031 (0.031) Data 0.002 (0.002) Loss 0.1034 (0.0646) Prec@1 81.000 (89.030) Prec@5 99.000 (99.364) +2022-11-14 13:51:37,462 Epoch: [106][330/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0682 (0.0647) Prec@1 90.000 (89.059) Prec@5 99.000 (99.353) +2022-11-14 13:51:37,818 Epoch: [106][340/500] Time 0.035 (0.031) Data 0.001 (0.002) Loss 0.0586 (0.0646) Prec@1 88.000 (89.029) Prec@5 99.000 (99.343) +2022-11-14 13:51:38,177 Epoch: [106][350/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0505 (0.0642) Prec@1 91.000 (89.083) Prec@5 100.000 (99.361) +2022-11-14 13:51:38,536 Epoch: [106][360/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0457 (0.0637) Prec@1 91.000 (89.135) Prec@5 99.000 (99.351) +2022-11-14 13:51:38,897 Epoch: [106][370/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0629 (0.0637) Prec@1 89.000 (89.132) Prec@5 100.000 (99.368) +2022-11-14 13:51:39,253 Epoch: [106][380/500] Time 0.034 (0.031) Data 0.001 (0.002) Loss 0.0546 (0.0634) Prec@1 92.000 (89.205) Prec@5 100.000 (99.385) +2022-11-14 13:51:39,622 Epoch: [106][390/500] Time 0.032 (0.031) Data 0.002 (0.002) Loss 0.0779 (0.0638) Prec@1 89.000 (89.200) Prec@5 99.000 (99.375) +2022-11-14 13:51:39,973 Epoch: [106][400/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0842 (0.0643) Prec@1 85.000 (89.098) Prec@5 99.000 (99.366) +2022-11-14 13:51:40,331 Epoch: [106][410/500] Time 0.033 (0.031) Data 0.001 (0.002) Loss 0.0804 (0.0647) Prec@1 88.000 (89.071) Prec@5 98.000 (99.333) +2022-11-14 13:51:40,699 Epoch: [106][420/500] Time 0.032 (0.031) Data 0.002 (0.002) Loss 0.0600 (0.0646) Prec@1 88.000 (89.047) Prec@5 99.000 (99.326) +2022-11-14 13:51:41,061 Epoch: [106][430/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0896 (0.0651) Prec@1 86.000 (88.977) Prec@5 99.000 (99.318) +2022-11-14 13:51:41,430 Epoch: [106][440/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0689 (0.0652) Prec@1 88.000 (88.956) Prec@5 100.000 (99.333) +2022-11-14 13:51:41,793 Epoch: [106][450/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.0504 (0.0649) Prec@1 92.000 (89.022) Prec@5 99.000 (99.326) +2022-11-14 13:51:42,139 Epoch: [106][460/500] Time 0.032 (0.031) Data 0.002 (0.002) Loss 0.0603 (0.0648) Prec@1 89.000 (89.021) Prec@5 99.000 (99.319) +2022-11-14 13:51:42,503 Epoch: [106][470/500] Time 0.044 (0.031) Data 0.002 (0.002) Loss 0.0757 (0.0650) Prec@1 88.000 (89.000) Prec@5 99.000 (99.312) +2022-11-14 13:51:42,855 Epoch: [106][480/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.1024 (0.0658) Prec@1 83.000 (88.878) Prec@5 100.000 (99.327) +2022-11-14 13:51:43,222 Epoch: [106][490/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0427 (0.0653) Prec@1 93.000 (88.960) Prec@5 100.000 (99.340) +2022-11-14 13:51:43,546 Epoch: [106][499/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0945 (0.0659) Prec@1 83.000 (88.843) Prec@5 99.000 (99.333) +2022-11-14 13:51:43,862 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0555 (0.0555) Prec@1 91.000 (91.000) Prec@5 98.000 (98.000) +2022-11-14 13:51:43,875 Test: [1/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0702 (0.0629) Prec@1 87.000 (89.000) Prec@5 99.000 (98.500) +2022-11-14 13:51:43,885 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0800 (0.0686) Prec@1 84.000 (87.333) Prec@5 100.000 (99.000) +2022-11-14 13:51:43,897 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1121 (0.0795) Prec@1 82.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:43,907 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0833) Prec@1 84.000 (85.600) Prec@5 99.000 (99.000) +2022-11-14 13:51:43,915 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0793) Prec@1 92.000 (86.667) Prec@5 99.000 (99.000) +2022-11-14 13:51:43,924 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0992 (0.0822) Prec@1 84.000 (86.286) Prec@5 99.000 (99.000) +2022-11-14 13:51:43,937 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1188 (0.0867) Prec@1 80.000 (85.500) Prec@5 95.000 (98.500) +2022-11-14 13:51:43,947 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1271 (0.0912) Prec@1 78.000 (84.667) Prec@5 96.000 (98.222) +2022-11-14 13:51:43,956 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0903) Prec@1 86.000 (84.800) Prec@5 98.000 (98.200) +2022-11-14 13:51:43,967 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0903) Prec@1 84.000 (84.727) Prec@5 99.000 (98.273) +2022-11-14 13:51:43,978 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0898) Prec@1 88.000 (85.000) Prec@5 99.000 (98.333) +2022-11-14 13:51:43,992 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0874) Prec@1 89.000 (85.308) Prec@5 100.000 (98.462) +2022-11-14 13:51:44,006 Test: [13/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0882) Prec@1 82.000 (85.071) Prec@5 99.000 (98.500) +2022-11-14 13:51:44,017 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0884) Prec@1 86.000 (85.133) Prec@5 99.000 (98.533) +2022-11-14 13:51:44,028 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0895) Prec@1 83.000 (85.000) Prec@5 98.000 (98.500) +2022-11-14 13:51:44,040 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0890) Prec@1 86.000 (85.059) Prec@5 98.000 (98.471) +2022-11-14 13:51:44,052 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0900) Prec@1 83.000 (84.944) Prec@5 98.000 (98.444) +2022-11-14 13:51:44,064 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0899) Prec@1 84.000 (84.895) Prec@5 98.000 (98.421) +2022-11-14 13:51:44,077 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0897) Prec@1 85.000 (84.900) Prec@5 96.000 (98.300) +2022-11-14 13:51:44,090 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0902) Prec@1 86.000 (84.952) Prec@5 98.000 (98.286) +2022-11-14 13:51:44,104 Test: [21/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0902) Prec@1 84.000 (84.909) Prec@5 99.000 (98.318) +2022-11-14 13:51:44,116 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1157 (0.0913) Prec@1 81.000 (84.739) Prec@5 98.000 (98.304) +2022-11-14 13:51:44,127 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0910) Prec@1 86.000 (84.792) Prec@5 98.000 (98.292) +2022-11-14 13:51:44,139 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0910) Prec@1 86.000 (84.840) Prec@5 99.000 (98.320) +2022-11-14 13:51:44,153 Test: [25/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1238 (0.0922) Prec@1 80.000 (84.654) Prec@5 95.000 (98.192) +2022-11-14 13:51:44,167 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0918) Prec@1 87.000 (84.741) Prec@5 100.000 (98.259) +2022-11-14 13:51:44,178 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0919) Prec@1 84.000 (84.714) Prec@5 98.000 (98.250) +2022-11-14 13:51:44,189 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0919) Prec@1 85.000 (84.724) Prec@5 97.000 (98.207) +2022-11-14 13:51:44,202 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0924) Prec@1 83.000 (84.667) Prec@5 96.000 (98.133) +2022-11-14 13:51:44,215 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0923) Prec@1 84.000 (84.645) Prec@5 98.000 (98.129) +2022-11-14 13:51:44,227 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0921) Prec@1 87.000 (84.719) Prec@5 99.000 (98.156) +2022-11-14 13:51:44,239 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0920) Prec@1 85.000 (84.727) Prec@5 96.000 (98.091) +2022-11-14 13:51:44,251 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1263 (0.0930) Prec@1 77.000 (84.500) Prec@5 99.000 (98.118) +2022-11-14 13:51:44,264 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0933) Prec@1 82.000 (84.429) Prec@5 99.000 (98.143) +2022-11-14 13:51:44,278 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0934) Prec@1 84.000 (84.417) Prec@5 100.000 (98.194) +2022-11-14 13:51:44,292 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0932) Prec@1 83.000 (84.378) Prec@5 99.000 (98.216) +2022-11-14 13:51:44,305 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0934) Prec@1 82.000 (84.316) Prec@5 100.000 (98.263) +2022-11-14 13:51:44,319 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0936) Prec@1 83.000 (84.282) Prec@5 97.000 (98.231) +2022-11-14 13:51:44,333 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0931) Prec@1 88.000 (84.375) Prec@5 99.000 (98.250) +2022-11-14 13:51:44,345 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.0936) Prec@1 80.000 (84.268) Prec@5 98.000 (98.244) +2022-11-14 13:51:44,359 Test: [41/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0936) Prec@1 85.000 (84.286) Prec@5 97.000 (98.214) +2022-11-14 13:51:44,372 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0933) Prec@1 86.000 (84.326) Prec@5 100.000 (98.256) +2022-11-14 13:51:44,383 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0931) Prec@1 87.000 (84.386) Prec@5 98.000 (98.250) +2022-11-14 13:51:44,395 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0935) Prec@1 80.000 (84.289) Prec@5 99.000 (98.267) +2022-11-14 13:51:44,408 Test: [45/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1246 (0.0941) Prec@1 77.000 (84.130) Prec@5 98.000 (98.261) +2022-11-14 13:51:44,422 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0938) Prec@1 83.000 (84.106) Prec@5 100.000 (98.298) +2022-11-14 13:51:44,434 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1169 (0.0942) Prec@1 80.000 (84.021) Prec@5 98.000 (98.292) +2022-11-14 13:51:44,445 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0936) Prec@1 87.000 (84.082) Prec@5 100.000 (98.327) +2022-11-14 13:51:44,458 Test: [49/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1172 (0.0941) Prec@1 79.000 (83.980) Prec@5 100.000 (98.360) +2022-11-14 13:51:44,471 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0937) Prec@1 87.000 (84.039) Prec@5 99.000 (98.373) +2022-11-14 13:51:44,483 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0936) Prec@1 83.000 (84.019) Prec@5 99.000 (98.385) +2022-11-14 13:51:44,495 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0935) Prec@1 85.000 (84.038) Prec@5 100.000 (98.415) +2022-11-14 13:51:44,508 Test: [53/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0935) Prec@1 84.000 (84.037) Prec@5 97.000 (98.389) +2022-11-14 13:51:44,520 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0933) Prec@1 85.000 (84.055) Prec@5 100.000 (98.418) +2022-11-14 13:51:44,531 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0932) Prec@1 85.000 (84.071) Prec@5 98.000 (98.411) +2022-11-14 13:51:44,543 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0927) Prec@1 89.000 (84.158) Prec@5 100.000 (98.439) +2022-11-14 13:51:44,556 Test: [57/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0928) Prec@1 85.000 (84.172) Prec@5 99.000 (98.448) +2022-11-14 13:51:44,569 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1150 (0.0932) Prec@1 79.000 (84.085) Prec@5 100.000 (98.475) +2022-11-14 13:51:44,582 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0929) Prec@1 87.000 (84.133) Prec@5 100.000 (98.500) +2022-11-14 13:51:44,593 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0930) Prec@1 82.000 (84.098) Prec@5 99.000 (98.508) +2022-11-14 13:51:44,607 Test: [61/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0927) Prec@1 88.000 (84.161) Prec@5 99.000 (98.516) +2022-11-14 13:51:44,620 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0924) Prec@1 87.000 (84.206) Prec@5 100.000 (98.540) +2022-11-14 13:51:44,631 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0486 (0.0917) Prec@1 89.000 (84.281) Prec@5 100.000 (98.562) +2022-11-14 13:51:44,645 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0920) Prec@1 81.000 (84.231) Prec@5 99.000 (98.569) +2022-11-14 13:51:44,659 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0919) Prec@1 87.000 (84.273) Prec@5 99.000 (98.576) +2022-11-14 13:51:44,672 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0917) Prec@1 88.000 (84.328) Prec@5 99.000 (98.582) +2022-11-14 13:51:44,684 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1217 (0.0921) Prec@1 76.000 (84.206) Prec@5 99.000 (98.588) +2022-11-14 13:51:44,695 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0920) Prec@1 87.000 (84.246) Prec@5 99.000 (98.594) +2022-11-14 13:51:44,710 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0920) Prec@1 82.000 (84.214) Prec@5 98.000 (98.586) +2022-11-14 13:51:44,723 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0920) Prec@1 84.000 (84.211) Prec@5 98.000 (98.577) +2022-11-14 13:51:44,734 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0921) Prec@1 85.000 (84.222) Prec@5 99.000 (98.583) +2022-11-14 13:51:44,747 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0918) Prec@1 86.000 (84.247) Prec@5 100.000 (98.603) +2022-11-14 13:51:44,759 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0918) Prec@1 85.000 (84.257) Prec@5 100.000 (98.622) +2022-11-14 13:51:44,770 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1088 (0.0920) Prec@1 79.000 (84.187) Prec@5 97.000 (98.600) +2022-11-14 13:51:44,783 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0918) Prec@1 85.000 (84.197) Prec@5 99.000 (98.605) +2022-11-14 13:51:44,795 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0918) Prec@1 84.000 (84.195) Prec@5 99.000 (98.610) +2022-11-14 13:51:44,807 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0917) Prec@1 84.000 (84.192) Prec@5 98.000 (98.603) +2022-11-14 13:51:44,820 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0919) Prec@1 81.000 (84.152) Prec@5 99.000 (98.608) +2022-11-14 13:51:44,834 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0921) Prec@1 83.000 (84.138) Prec@5 100.000 (98.625) +2022-11-14 13:51:44,846 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0919) Prec@1 85.000 (84.148) Prec@5 97.000 (98.605) +2022-11-14 13:51:44,858 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0918) Prec@1 87.000 (84.183) Prec@5 99.000 (98.610) +2022-11-14 13:51:44,870 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1094 (0.0920) Prec@1 80.000 (84.133) Prec@5 99.000 (98.614) +2022-11-14 13:51:44,882 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0919) Prec@1 86.000 (84.155) Prec@5 98.000 (98.607) +2022-11-14 13:51:44,895 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0919) Prec@1 84.000 (84.153) Prec@5 99.000 (98.612) +2022-11-14 13:51:44,909 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0920) Prec@1 82.000 (84.128) Prec@5 100.000 (98.628) +2022-11-14 13:51:44,923 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0920) Prec@1 86.000 (84.149) Prec@5 100.000 (98.644) +2022-11-14 13:51:44,934 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0921) Prec@1 86.000 (84.170) Prec@5 98.000 (98.636) +2022-11-14 13:51:44,946 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0920) Prec@1 87.000 (84.202) Prec@5 99.000 (98.640) +2022-11-14 13:51:44,958 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0919) Prec@1 87.000 (84.233) Prec@5 99.000 (98.644) +2022-11-14 13:51:44,971 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0917) Prec@1 86.000 (84.253) Prec@5 100.000 (98.659) +2022-11-14 13:51:44,983 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0916) Prec@1 85.000 (84.261) Prec@5 100.000 (98.674) +2022-11-14 13:51:44,995 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0919) Prec@1 82.000 (84.237) Prec@5 100.000 (98.688) +2022-11-14 13:51:45,007 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0916) Prec@1 88.000 (84.277) Prec@5 100.000 (98.702) +2022-11-14 13:51:45,019 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0917) Prec@1 83.000 (84.263) Prec@5 100.000 (98.716) +2022-11-14 13:51:45,031 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0915) Prec@1 87.000 (84.292) Prec@5 99.000 (98.719) +2022-11-14 13:51:45,041 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0911) Prec@1 92.000 (84.371) Prec@5 99.000 (98.722) +2022-11-14 13:51:45,054 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0913) Prec@1 85.000 (84.378) Prec@5 98.000 (98.714) +2022-11-14 13:51:45,066 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.0915) Prec@1 83.000 (84.364) Prec@5 98.000 (98.707) +2022-11-14 13:51:45,076 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0913) Prec@1 86.000 (84.380) Prec@5 99.000 (98.710) +2022-11-14 13:51:45,144 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:51:45,468 Epoch: [107][0/500] Time 0.023 (0.023) Data 0.237 (0.237) Loss 0.0525 (0.0525) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:45,694 Epoch: [107][10/500] Time 0.019 (0.020) Data 0.002 (0.023) Loss 0.0634 (0.0580) Prec@1 92.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:51:46,058 Epoch: [107][20/500] Time 0.035 (0.026) Data 0.002 (0.013) Loss 0.0275 (0.0478) Prec@1 95.000 (93.667) Prec@5 100.000 (99.333) +2022-11-14 13:51:46,461 Epoch: [107][30/500] Time 0.035 (0.029) Data 0.002 (0.009) Loss 0.0635 (0.0517) Prec@1 90.000 (92.750) Prec@5 99.000 (99.250) +2022-11-14 13:51:46,855 Epoch: [107][40/500] Time 0.037 (0.030) Data 0.002 (0.008) Loss 0.0576 (0.0529) Prec@1 90.000 (92.200) Prec@5 100.000 (99.400) +2022-11-14 13:51:47,258 Epoch: [107][50/500] Time 0.044 (0.032) Data 0.002 (0.006) Loss 0.0445 (0.0515) Prec@1 93.000 (92.333) Prec@5 99.000 (99.333) +2022-11-14 13:51:47,642 Epoch: [107][60/500] Time 0.037 (0.032) Data 0.002 (0.006) Loss 0.0728 (0.0546) Prec@1 87.000 (91.571) Prec@5 98.000 (99.143) +2022-11-14 13:51:48,042 Epoch: [107][70/500] Time 0.031 (0.033) Data 0.002 (0.005) Loss 0.0512 (0.0541) Prec@1 91.000 (91.500) Prec@5 100.000 (99.250) +2022-11-14 13:51:48,440 Epoch: [107][80/500] Time 0.043 (0.033) Data 0.002 (0.005) Loss 0.0606 (0.0549) Prec@1 90.000 (91.333) Prec@5 100.000 (99.333) +2022-11-14 13:51:48,843 Epoch: [107][90/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.0833 (0.0577) Prec@1 88.000 (91.000) Prec@5 100.000 (99.400) +2022-11-14 13:51:49,236 Epoch: [107][100/500] Time 0.033 (0.033) Data 0.002 (0.004) Loss 0.0486 (0.0569) Prec@1 92.000 (91.091) Prec@5 100.000 (99.455) +2022-11-14 13:51:49,623 Epoch: [107][110/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0737 (0.0583) Prec@1 87.000 (90.750) Prec@5 100.000 (99.500) +2022-11-14 13:51:50,005 Epoch: [107][120/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0454 (0.0573) Prec@1 94.000 (91.000) Prec@5 99.000 (99.462) +2022-11-14 13:51:50,405 Epoch: [107][130/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0636 (0.0577) Prec@1 92.000 (91.071) Prec@5 100.000 (99.500) +2022-11-14 13:51:50,799 Epoch: [107][140/500] Time 0.037 (0.034) Data 0.002 (0.004) Loss 0.0698 (0.0585) Prec@1 86.000 (90.733) Prec@5 100.000 (99.533) +2022-11-14 13:51:51,187 Epoch: [107][150/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0594 (0.0586) Prec@1 90.000 (90.688) Prec@5 99.000 (99.500) +2022-11-14 13:51:51,591 Epoch: [107][160/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0533 (0.0583) Prec@1 90.000 (90.647) Prec@5 100.000 (99.529) +2022-11-14 13:51:51,993 Epoch: [107][170/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0466 (0.0576) Prec@1 93.000 (90.778) Prec@5 100.000 (99.556) +2022-11-14 13:51:52,387 Epoch: [107][180/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0716 (0.0584) Prec@1 87.000 (90.579) Prec@5 100.000 (99.579) +2022-11-14 13:51:52,780 Epoch: [107][190/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0685 (0.0589) Prec@1 89.000 (90.500) Prec@5 99.000 (99.550) +2022-11-14 13:51:53,168 Epoch: [107][200/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.1070 (0.0612) Prec@1 82.000 (90.095) Prec@5 99.000 (99.524) +2022-11-14 13:51:53,577 Epoch: [107][210/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0863 (0.0623) Prec@1 85.000 (89.864) Prec@5 99.000 (99.500) +2022-11-14 13:51:53,963 Epoch: [107][220/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0621 (0.0623) Prec@1 89.000 (89.826) Prec@5 100.000 (99.522) +2022-11-14 13:51:54,368 Epoch: [107][230/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0611 (0.0622) Prec@1 91.000 (89.875) Prec@5 100.000 (99.542) +2022-11-14 13:51:54,761 Epoch: [107][240/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.0704 (0.0626) Prec@1 86.000 (89.720) Prec@5 99.000 (99.520) +2022-11-14 13:51:55,171 Epoch: [107][250/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0635 (0.0626) Prec@1 90.000 (89.731) Prec@5 100.000 (99.538) +2022-11-14 13:51:55,569 Epoch: [107][260/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0701 (0.0629) Prec@1 87.000 (89.630) Prec@5 98.000 (99.481) +2022-11-14 13:51:55,968 Epoch: [107][270/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0541 (0.0626) Prec@1 92.000 (89.714) Prec@5 99.000 (99.464) +2022-11-14 13:51:56,362 Epoch: [107][280/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0573 (0.0624) Prec@1 91.000 (89.759) Prec@5 100.000 (99.483) +2022-11-14 13:51:56,767 Epoch: [107][290/500] Time 0.031 (0.035) Data 0.002 (0.003) Loss 0.0983 (0.0636) Prec@1 83.000 (89.533) Prec@5 99.000 (99.467) +2022-11-14 13:51:57,165 Epoch: [107][300/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0729 (0.0639) Prec@1 90.000 (89.548) Prec@5 99.000 (99.452) +2022-11-14 13:51:57,565 Epoch: [107][310/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0629 (0.0639) Prec@1 91.000 (89.594) Prec@5 100.000 (99.469) +2022-11-14 13:51:57,959 Epoch: [107][320/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0449 (0.0633) Prec@1 94.000 (89.727) Prec@5 100.000 (99.485) +2022-11-14 13:51:58,349 Epoch: [107][330/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0920 (0.0641) Prec@1 83.000 (89.529) Prec@5 99.000 (99.471) +2022-11-14 13:51:58,748 Epoch: [107][340/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0820 (0.0646) Prec@1 85.000 (89.400) Prec@5 99.000 (99.457) +2022-11-14 13:51:59,144 Epoch: [107][350/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0426 (0.0640) Prec@1 93.000 (89.500) Prec@5 100.000 (99.472) +2022-11-14 13:51:59,527 Epoch: [107][360/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0745 (0.0643) Prec@1 87.000 (89.432) Prec@5 99.000 (99.459) +2022-11-14 13:51:59,917 Epoch: [107][370/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0677 (0.0644) Prec@1 87.000 (89.368) Prec@5 99.000 (99.447) +2022-11-14 13:52:00,317 Epoch: [107][380/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0821 (0.0649) Prec@1 86.000 (89.282) Prec@5 99.000 (99.436) +2022-11-14 13:52:00,714 Epoch: [107][390/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0680 (0.0649) Prec@1 88.000 (89.250) Prec@5 99.000 (99.425) +2022-11-14 13:52:01,111 Epoch: [107][400/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0884 (0.0655) Prec@1 82.000 (89.073) Prec@5 99.000 (99.415) +2022-11-14 13:52:01,510 Epoch: [107][410/500] Time 0.037 (0.035) Data 0.001 (0.002) Loss 0.0802 (0.0659) Prec@1 86.000 (89.000) Prec@5 99.000 (99.405) +2022-11-14 13:52:01,905 Epoch: [107][420/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0601 (0.0657) Prec@1 92.000 (89.070) Prec@5 100.000 (99.419) +2022-11-14 13:52:02,307 Epoch: [107][430/500] Time 0.033 (0.035) Data 0.002 (0.002) Loss 0.0823 (0.0661) Prec@1 87.000 (89.023) Prec@5 97.000 (99.364) +2022-11-14 13:52:02,698 Epoch: [107][440/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0715 (0.0662) Prec@1 88.000 (89.000) Prec@5 100.000 (99.378) +2022-11-14 13:52:03,093 Epoch: [107][450/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0715 (0.0663) Prec@1 88.000 (88.978) Prec@5 100.000 (99.391) +2022-11-14 13:52:03,489 Epoch: [107][460/500] Time 0.046 (0.035) Data 0.002 (0.002) Loss 0.0878 (0.0668) Prec@1 86.000 (88.915) Prec@5 98.000 (99.362) +2022-11-14 13:52:03,877 Epoch: [107][470/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0613 (0.0667) Prec@1 91.000 (88.958) Prec@5 99.000 (99.354) +2022-11-14 13:52:04,268 Epoch: [107][480/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0526 (0.0664) Prec@1 93.000 (89.041) Prec@5 99.000 (99.347) +2022-11-14 13:52:04,660 Epoch: [107][490/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0609 (0.0663) Prec@1 89.000 (89.040) Prec@5 100.000 (99.360) +2022-11-14 13:52:04,999 Epoch: [107][499/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0601 (0.0662) Prec@1 89.000 (89.039) Prec@5 100.000 (99.373) +2022-11-14 13:52:05,282 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0758 (0.0758) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:52:05,290 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0858) Prec@1 84.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:52:05,303 Test: [2/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1225 (0.0981) Prec@1 76.000 (82.667) Prec@5 98.000 (98.667) +2022-11-14 13:52:05,317 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1216 (0.1040) Prec@1 79.000 (81.750) Prec@5 99.000 (98.750) +2022-11-14 13:52:05,325 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1323 (0.1096) Prec@1 76.000 (80.600) Prec@5 100.000 (99.000) +2022-11-14 13:52:05,334 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0451 (0.0989) Prec@1 91.000 (82.333) Prec@5 99.000 (99.000) +2022-11-14 13:52:05,346 Test: [6/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0967) Prec@1 86.000 (82.857) Prec@5 98.000 (98.857) +2022-11-14 13:52:05,359 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1184 (0.0994) Prec@1 80.000 (82.500) Prec@5 98.000 (98.750) +2022-11-14 13:52:05,368 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.1007) Prec@1 81.000 (82.333) Prec@5 100.000 (98.889) +2022-11-14 13:52:05,379 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0990) Prec@1 85.000 (82.600) Prec@5 95.000 (98.500) +2022-11-14 13:52:05,391 Test: [10/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0980) Prec@1 87.000 (83.000) Prec@5 100.000 (98.636) +2022-11-14 13:52:05,403 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0981) Prec@1 84.000 (83.083) Prec@5 99.000 (98.667) +2022-11-14 13:52:05,416 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0970) Prec@1 86.000 (83.308) Prec@5 100.000 (98.769) +2022-11-14 13:52:05,428 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0962) Prec@1 87.000 (83.571) Prec@5 100.000 (98.857) +2022-11-14 13:52:05,442 Test: [14/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1118 (0.0973) Prec@1 80.000 (83.333) Prec@5 99.000 (98.867) +2022-11-14 13:52:05,455 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0976) Prec@1 82.000 (83.250) Prec@5 99.000 (98.875) +2022-11-14 13:52:05,467 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0959) Prec@1 89.000 (83.588) Prec@5 98.000 (98.824) +2022-11-14 13:52:05,478 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1288 (0.0977) Prec@1 78.000 (83.278) Prec@5 100.000 (98.889) +2022-11-14 13:52:05,491 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0980) Prec@1 83.000 (83.263) Prec@5 98.000 (98.842) +2022-11-14 13:52:05,505 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1414 (0.1002) Prec@1 81.000 (83.150) Prec@5 97.000 (98.750) +2022-11-14 13:52:05,517 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.1007) Prec@1 80.000 (83.000) Prec@5 97.000 (98.667) +2022-11-14 13:52:05,528 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.1008) Prec@1 81.000 (82.909) Prec@5 98.000 (98.636) +2022-11-14 13:52:05,542 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.1013) Prec@1 81.000 (82.826) Prec@5 98.000 (98.609) +2022-11-14 13:52:05,556 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.1016) Prec@1 82.000 (82.792) Prec@5 100.000 (98.667) +2022-11-14 13:52:05,570 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.1019) Prec@1 80.000 (82.680) Prec@5 99.000 (98.680) +2022-11-14 13:52:05,585 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1297 (0.1030) Prec@1 78.000 (82.500) Prec@5 95.000 (98.538) +2022-11-14 13:52:05,598 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.1027) Prec@1 85.000 (82.593) Prec@5 100.000 (98.593) +2022-11-14 13:52:05,611 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.1017) Prec@1 87.000 (82.750) Prec@5 100.000 (98.643) +2022-11-14 13:52:05,627 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.1010) Prec@1 87.000 (82.897) Prec@5 100.000 (98.690) +2022-11-14 13:52:05,641 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.1012) Prec@1 83.000 (82.900) Prec@5 99.000 (98.700) +2022-11-14 13:52:05,653 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.1011) Prec@1 83.000 (82.903) Prec@5 99.000 (98.710) +2022-11-14 13:52:05,665 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.1011) Prec@1 86.000 (83.000) Prec@5 98.000 (98.688) +2022-11-14 13:52:05,679 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.1004) Prec@1 87.000 (83.121) Prec@5 96.000 (98.606) +2022-11-14 13:52:05,692 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1388 (0.1016) Prec@1 77.000 (82.941) Prec@5 99.000 (98.618) +2022-11-14 13:52:05,707 Test: [34/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.1019) Prec@1 79.000 (82.829) Prec@5 99.000 (98.629) +2022-11-14 13:52:05,724 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1229 (0.1025) Prec@1 81.000 (82.778) Prec@5 98.000 (98.611) +2022-11-14 13:52:05,738 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1258 (0.1031) Prec@1 79.000 (82.676) Prec@5 97.000 (98.568) +2022-11-14 13:52:05,750 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1352 (0.1040) Prec@1 77.000 (82.526) Prec@5 98.000 (98.553) +2022-11-14 13:52:05,766 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.1030) Prec@1 89.000 (82.692) Prec@5 97.000 (98.513) +2022-11-14 13:52:05,780 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.1025) Prec@1 86.000 (82.775) Prec@5 100.000 (98.550) +2022-11-14 13:52:05,795 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.1024) Prec@1 83.000 (82.780) Prec@5 97.000 (98.512) +2022-11-14 13:52:05,809 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.1023) Prec@1 84.000 (82.810) Prec@5 97.000 (98.476) +2022-11-14 13:52:05,822 Test: [42/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.1016) Prec@1 88.000 (82.930) Prec@5 98.000 (98.465) +2022-11-14 13:52:05,836 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.1013) Prec@1 85.000 (82.977) Prec@5 98.000 (98.455) +2022-11-14 13:52:05,848 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1250 (0.1018) Prec@1 77.000 (82.844) Prec@5 98.000 (98.444) +2022-11-14 13:52:05,863 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1330 (0.1025) Prec@1 76.000 (82.696) Prec@5 99.000 (98.457) +2022-11-14 13:52:05,877 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.1028) Prec@1 82.000 (82.681) Prec@5 97.000 (98.426) +2022-11-14 13:52:05,890 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.1028) Prec@1 83.000 (82.688) Prec@5 99.000 (98.438) +2022-11-14 13:52:05,904 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.1021) Prec@1 89.000 (82.816) Prec@5 100.000 (98.469) +2022-11-14 13:52:05,918 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1281 (0.1026) Prec@1 81.000 (82.780) Prec@5 100.000 (98.500) +2022-11-14 13:52:05,933 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.1021) Prec@1 88.000 (82.882) Prec@5 99.000 (98.510) +2022-11-14 13:52:05,948 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1089 (0.1022) Prec@1 83.000 (82.885) Prec@5 99.000 (98.519) +2022-11-14 13:52:05,962 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.1021) Prec@1 83.000 (82.887) Prec@5 99.000 (98.528) +2022-11-14 13:52:05,976 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.1018) Prec@1 87.000 (82.963) Prec@5 100.000 (98.556) +2022-11-14 13:52:05,990 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.1018) Prec@1 80.000 (82.909) Prec@5 100.000 (98.582) +2022-11-14 13:52:06,004 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1239 (0.1022) Prec@1 80.000 (82.857) Prec@5 99.000 (98.589) +2022-11-14 13:52:06,018 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.1019) Prec@1 86.000 (82.912) Prec@5 100.000 (98.614) +2022-11-14 13:52:06,031 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.1016) Prec@1 88.000 (83.000) Prec@5 98.000 (98.603) +2022-11-14 13:52:06,045 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1219 (0.1019) Prec@1 81.000 (82.966) Prec@5 100.000 (98.627) +2022-11-14 13:52:06,059 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.1018) Prec@1 81.000 (82.933) Prec@5 100.000 (98.650) +2022-11-14 13:52:06,074 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.1018) Prec@1 82.000 (82.918) Prec@5 99.000 (98.656) +2022-11-14 13:52:06,089 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.1018) Prec@1 81.000 (82.887) Prec@5 99.000 (98.661) +2022-11-14 13:52:06,104 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.1016) Prec@1 87.000 (82.952) Prec@5 99.000 (98.667) +2022-11-14 13:52:06,120 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.1010) Prec@1 91.000 (83.078) Prec@5 99.000 (98.672) +2022-11-14 13:52:06,132 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1347 (0.1015) Prec@1 77.000 (82.985) Prec@5 96.000 (98.631) +2022-11-14 13:52:06,146 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.1013) Prec@1 86.000 (83.030) Prec@5 100.000 (98.652) +2022-11-14 13:52:06,162 Test: [66/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.1010) Prec@1 87.000 (83.090) Prec@5 96.000 (98.612) +2022-11-14 13:52:06,176 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.1010) Prec@1 82.000 (83.074) Prec@5 99.000 (98.618) +2022-11-14 13:52:06,189 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.1010) Prec@1 85.000 (83.101) Prec@5 99.000 (98.623) +2022-11-14 13:52:06,203 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.1011) Prec@1 81.000 (83.071) Prec@5 99.000 (98.629) +2022-11-14 13:52:06,217 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.1012) Prec@1 83.000 (83.070) Prec@5 99.000 (98.634) +2022-11-14 13:52:06,231 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.1012) Prec@1 82.000 (83.056) Prec@5 99.000 (98.639) +2022-11-14 13:52:06,245 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.1006) Prec@1 92.000 (83.178) Prec@5 99.000 (98.644) +2022-11-14 13:52:06,259 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.1006) Prec@1 83.000 (83.176) Prec@5 99.000 (98.649) +2022-11-14 13:52:06,273 Test: [74/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1362 (0.1011) Prec@1 77.000 (83.093) Prec@5 99.000 (98.653) +2022-11-14 13:52:06,287 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.1009) Prec@1 87.000 (83.145) Prec@5 98.000 (98.645) +2022-11-14 13:52:06,299 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.1010) Prec@1 82.000 (83.130) Prec@5 99.000 (98.649) +2022-11-14 13:52:06,315 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.1010) Prec@1 83.000 (83.128) Prec@5 97.000 (98.628) +2022-11-14 13:52:06,329 Test: [78/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.1012) Prec@1 81.000 (83.101) Prec@5 98.000 (98.620) +2022-11-14 13:52:06,343 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.1012) Prec@1 84.000 (83.112) Prec@5 98.000 (98.612) +2022-11-14 13:52:06,357 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.1010) Prec@1 85.000 (83.136) Prec@5 99.000 (98.617) +2022-11-14 13:52:06,369 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.1007) Prec@1 86.000 (83.171) Prec@5 99.000 (98.622) +2022-11-14 13:52:06,385 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.1007) Prec@1 84.000 (83.181) Prec@5 99.000 (98.627) +2022-11-14 13:52:06,403 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1170 (0.1009) Prec@1 82.000 (83.167) Prec@5 100.000 (98.643) +2022-11-14 13:52:06,417 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1251 (0.1012) Prec@1 77.000 (83.094) Prec@5 97.000 (98.624) +2022-11-14 13:52:06,431 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.1012) Prec@1 85.000 (83.116) Prec@5 97.000 (98.605) +2022-11-14 13:52:06,445 Test: [86/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.1012) Prec@1 81.000 (83.092) Prec@5 98.000 (98.598) +2022-11-14 13:52:06,458 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.1011) Prec@1 85.000 (83.114) Prec@5 99.000 (98.602) +2022-11-14 13:52:06,472 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.1010) Prec@1 86.000 (83.146) Prec@5 98.000 (98.596) +2022-11-14 13:52:06,486 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.1010) Prec@1 82.000 (83.133) Prec@5 100.000 (98.611) +2022-11-14 13:52:06,501 Test: [90/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.1010) Prec@1 85.000 (83.154) Prec@5 100.000 (98.626) +2022-11-14 13:52:06,515 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.1004) Prec@1 93.000 (83.261) Prec@5 100.000 (98.641) +2022-11-14 13:52:06,528 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.1004) Prec@1 83.000 (83.258) Prec@5 99.000 (98.645) +2022-11-14 13:52:06,543 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.1001) Prec@1 86.000 (83.287) Prec@5 100.000 (98.660) +2022-11-14 13:52:06,553 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.1002) Prec@1 83.000 (83.284) Prec@5 99.000 (98.663) +2022-11-14 13:52:06,565 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.1000) Prec@1 87.000 (83.323) Prec@5 100.000 (98.677) +2022-11-14 13:52:06,579 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0999) Prec@1 86.000 (83.351) Prec@5 99.000 (98.680) +2022-11-14 13:52:06,594 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1224 (0.1001) Prec@1 81.000 (83.327) Prec@5 97.000 (98.663) +2022-11-14 13:52:06,608 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1174 (0.1003) Prec@1 80.000 (83.293) Prec@5 99.000 (98.667) +2022-11-14 13:52:06,622 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.1003) Prec@1 84.000 (83.300) Prec@5 100.000 (98.680) +2022-11-14 13:52:06,679 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:52:06,979 Epoch: [108][0/500] Time 0.022 (0.022) Data 0.217 (0.217) Loss 0.0564 (0.0564) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:52:07,180 Epoch: [108][10/500] Time 0.018 (0.018) Data 0.001 (0.021) Loss 0.0723 (0.0644) Prec@1 89.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 13:52:07,376 Epoch: [108][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0704 (0.0664) Prec@1 87.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 13:52:07,680 Epoch: [108][30/500] Time 0.031 (0.020) Data 0.002 (0.009) Loss 0.0951 (0.0736) Prec@1 84.000 (87.500) Prec@5 100.000 (99.750) +2022-11-14 13:52:08,143 Epoch: [108][40/500] Time 0.043 (0.025) Data 0.002 (0.007) Loss 0.0949 (0.0778) Prec@1 84.000 (86.800) Prec@5 97.000 (99.200) +2022-11-14 13:52:08,624 Epoch: [108][50/500] Time 0.053 (0.029) Data 0.002 (0.006) Loss 0.0729 (0.0770) Prec@1 88.000 (87.000) Prec@5 100.000 (99.333) +2022-11-14 13:52:09,096 Epoch: [108][60/500] Time 0.043 (0.031) Data 0.002 (0.005) Loss 0.0566 (0.0741) Prec@1 91.000 (87.571) Prec@5 99.000 (99.286) +2022-11-14 13:52:09,567 Epoch: [108][70/500] Time 0.043 (0.033) Data 0.002 (0.005) Loss 0.0880 (0.0758) Prec@1 88.000 (87.625) Prec@5 100.000 (99.375) +2022-11-14 13:52:10,048 Epoch: [108][80/500] Time 0.053 (0.034) Data 0.002 (0.004) Loss 0.0477 (0.0727) Prec@1 93.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 13:52:10,548 Epoch: [108][90/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0671 (0.0721) Prec@1 88.000 (88.200) Prec@5 98.000 (99.300) +2022-11-14 13:52:11,026 Epoch: [108][100/500] Time 0.045 (0.036) Data 0.002 (0.004) Loss 0.0387 (0.0691) Prec@1 96.000 (88.909) Prec@5 100.000 (99.364) +2022-11-14 13:52:11,526 Epoch: [108][110/500] Time 0.051 (0.037) Data 0.002 (0.004) Loss 0.0642 (0.0687) Prec@1 90.000 (89.000) Prec@5 97.000 (99.167) +2022-11-14 13:52:11,999 Epoch: [108][120/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0652 (0.0684) Prec@1 89.000 (89.000) Prec@5 98.000 (99.077) +2022-11-14 13:52:12,481 Epoch: [108][130/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.0881 (0.0698) Prec@1 84.000 (88.643) Prec@5 98.000 (99.000) +2022-11-14 13:52:12,953 Epoch: [108][140/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0809 (0.0706) Prec@1 84.000 (88.333) Prec@5 99.000 (99.000) +2022-11-14 13:52:13,420 Epoch: [108][150/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0799 (0.0712) Prec@1 87.000 (88.250) Prec@5 99.000 (99.000) +2022-11-14 13:52:13,900 Epoch: [108][160/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0972 (0.0727) Prec@1 83.000 (87.941) Prec@5 99.000 (99.000) +2022-11-14 13:52:14,373 Epoch: [108][170/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0626 (0.0721) Prec@1 91.000 (88.111) Prec@5 99.000 (99.000) +2022-11-14 13:52:14,880 Epoch: [108][180/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0755 (0.0723) Prec@1 86.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:52:15,369 Epoch: [108][190/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0521 (0.0713) Prec@1 91.000 (88.150) Prec@5 99.000 (99.000) +2022-11-14 13:52:15,839 Epoch: [108][200/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0743 (0.0714) Prec@1 90.000 (88.238) Prec@5 99.000 (99.000) +2022-11-14 13:52:16,313 Epoch: [108][210/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.1060 (0.0730) Prec@1 80.000 (87.864) Prec@5 99.000 (99.000) +2022-11-14 13:52:16,780 Epoch: [108][220/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0848 (0.0735) Prec@1 86.000 (87.783) Prec@5 100.000 (99.043) +2022-11-14 13:52:17,260 Epoch: [108][230/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0977 (0.0745) Prec@1 81.000 (87.500) Prec@5 99.000 (99.042) +2022-11-14 13:52:17,732 Epoch: [108][240/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0628 (0.0741) Prec@1 90.000 (87.600) Prec@5 98.000 (99.000) +2022-11-14 13:52:18,222 Epoch: [108][250/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0646 (0.0737) Prec@1 88.000 (87.615) Prec@5 100.000 (99.038) +2022-11-14 13:52:18,711 Epoch: [108][260/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0469 (0.0727) Prec@1 93.000 (87.815) Prec@5 100.000 (99.074) +2022-11-14 13:52:19,211 Epoch: [108][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0437 (0.0717) Prec@1 94.000 (88.036) Prec@5 98.000 (99.036) +2022-11-14 13:52:19,708 Epoch: [108][280/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0595 (0.0712) Prec@1 90.000 (88.103) Prec@5 99.000 (99.034) +2022-11-14 13:52:20,204 Epoch: [108][290/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0626 (0.0710) Prec@1 90.000 (88.167) Prec@5 99.000 (99.033) +2022-11-14 13:52:20,601 Epoch: [108][300/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0677 (0.0709) Prec@1 90.000 (88.226) Prec@5 100.000 (99.065) +2022-11-14 13:52:20,944 Epoch: [108][310/500] Time 0.032 (0.040) Data 0.002 (0.003) Loss 0.0656 (0.0707) Prec@1 89.000 (88.250) Prec@5 99.000 (99.062) +2022-11-14 13:52:21,288 Epoch: [108][320/500] Time 0.032 (0.040) Data 0.002 (0.003) Loss 0.0677 (0.0706) Prec@1 88.000 (88.242) Prec@5 100.000 (99.091) +2022-11-14 13:52:21,626 Epoch: [108][330/500] Time 0.032 (0.039) Data 0.002 (0.003) Loss 0.0695 (0.0706) Prec@1 89.000 (88.265) Prec@5 98.000 (99.059) +2022-11-14 13:52:21,972 Epoch: [108][340/500] Time 0.033 (0.039) Data 0.002 (0.002) Loss 0.0452 (0.0698) Prec@1 93.000 (88.400) Prec@5 100.000 (99.086) +2022-11-14 13:52:22,323 Epoch: [108][350/500] Time 0.034 (0.039) Data 0.002 (0.002) Loss 0.0730 (0.0699) Prec@1 87.000 (88.361) Prec@5 99.000 (99.083) +2022-11-14 13:52:22,674 Epoch: [108][360/500] Time 0.033 (0.039) Data 0.002 (0.002) Loss 0.0810 (0.0702) Prec@1 86.000 (88.297) Prec@5 99.000 (99.081) +2022-11-14 13:52:23,031 Epoch: [108][370/500] Time 0.031 (0.039) Data 0.002 (0.002) Loss 0.0774 (0.0704) Prec@1 88.000 (88.289) Prec@5 98.000 (99.053) +2022-11-14 13:52:23,381 Epoch: [108][380/500] Time 0.034 (0.038) Data 0.002 (0.002) Loss 0.0877 (0.0709) Prec@1 86.000 (88.231) Prec@5 100.000 (99.077) +2022-11-14 13:52:23,729 Epoch: [108][390/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0814 (0.0711) Prec@1 86.000 (88.175) Prec@5 99.000 (99.075) +2022-11-14 13:52:24,071 Epoch: [108][400/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0966 (0.0717) Prec@1 82.000 (88.024) Prec@5 99.000 (99.073) +2022-11-14 13:52:24,412 Epoch: [108][410/500] Time 0.030 (0.038) Data 0.002 (0.002) Loss 0.0874 (0.0721) Prec@1 84.000 (87.929) Prec@5 99.000 (99.071) +2022-11-14 13:52:24,771 Epoch: [108][420/500] Time 0.036 (0.038) Data 0.002 (0.002) Loss 0.0659 (0.0720) Prec@1 89.000 (87.953) Prec@5 100.000 (99.093) +2022-11-14 13:52:25,120 Epoch: [108][430/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0656 (0.0718) Prec@1 86.000 (87.909) Prec@5 98.000 (99.068) +2022-11-14 13:52:25,472 Epoch: [108][440/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0599 (0.0716) Prec@1 90.000 (87.956) Prec@5 99.000 (99.067) +2022-11-14 13:52:25,821 Epoch: [108][450/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0689 (0.0715) Prec@1 90.000 (88.000) Prec@5 99.000 (99.065) +2022-11-14 13:52:26,175 Epoch: [108][460/500] Time 0.033 (0.037) Data 0.001 (0.002) Loss 0.0761 (0.0716) Prec@1 85.000 (87.936) Prec@5 100.000 (99.085) +2022-11-14 13:52:26,534 Epoch: [108][470/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0656 (0.0715) Prec@1 89.000 (87.958) Prec@5 100.000 (99.104) +2022-11-14 13:52:26,886 Epoch: [108][480/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0686 (0.0714) Prec@1 88.000 (87.959) Prec@5 99.000 (99.102) +2022-11-14 13:52:27,239 Epoch: [108][490/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0725 (0.0714) Prec@1 87.000 (87.940) Prec@5 99.000 (99.100) +2022-11-14 13:52:27,546 Epoch: [108][499/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0557 (0.0711) Prec@1 92.000 (88.020) Prec@5 99.000 (99.098) +2022-11-14 13:52:27,824 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:52:27,831 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0723) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:52:27,841 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0782) Prec@1 84.000 (87.333) Prec@5 98.000 (99.333) +2022-11-14 13:52:27,851 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1204 (0.0888) Prec@1 80.000 (85.500) Prec@5 99.000 (99.250) +2022-11-14 13:52:27,859 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0860) Prec@1 86.000 (85.600) Prec@5 100.000 (99.400) +2022-11-14 13:52:27,867 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0808) Prec@1 90.000 (86.333) Prec@5 100.000 (99.500) +2022-11-14 13:52:27,874 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0794) Prec@1 89.000 (86.714) Prec@5 100.000 (99.571) +2022-11-14 13:52:27,883 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0830) Prec@1 82.000 (86.125) Prec@5 98.000 (99.375) +2022-11-14 13:52:27,890 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1175 (0.0868) Prec@1 80.000 (85.444) Prec@5 99.000 (99.333) +2022-11-14 13:52:27,898 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0868) Prec@1 85.000 (85.400) Prec@5 99.000 (99.300) +2022-11-14 13:52:27,906 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0838) Prec@1 92.000 (86.000) Prec@5 100.000 (99.364) +2022-11-14 13:52:27,914 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0840) Prec@1 86.000 (86.000) Prec@5 100.000 (99.417) +2022-11-14 13:52:27,923 Test: [12/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0840) Prec@1 84.000 (85.846) Prec@5 100.000 (99.462) +2022-11-14 13:52:27,932 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0838) Prec@1 86.000 (85.857) Prec@5 96.000 (99.214) +2022-11-14 13:52:27,941 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0849) Prec@1 84.000 (85.733) Prec@5 99.000 (99.200) +2022-11-14 13:52:27,949 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0855) Prec@1 85.000 (85.688) Prec@5 98.000 (99.125) +2022-11-14 13:52:27,959 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0846) Prec@1 87.000 (85.765) Prec@5 97.000 (99.000) +2022-11-14 13:52:27,968 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0850) Prec@1 85.000 (85.722) Prec@5 100.000 (99.056) +2022-11-14 13:52:27,977 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0850) Prec@1 88.000 (85.842) Prec@5 98.000 (99.000) +2022-11-14 13:52:27,987 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.0864) Prec@1 84.000 (85.750) Prec@5 97.000 (98.900) +2022-11-14 13:52:27,996 Test: [20/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0869) Prec@1 84.000 (85.667) Prec@5 98.000 (98.857) +2022-11-14 13:52:28,005 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0865) Prec@1 86.000 (85.682) Prec@5 99.000 (98.864) +2022-11-14 13:52:28,015 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0871) Prec@1 85.000 (85.652) Prec@5 97.000 (98.783) +2022-11-14 13:52:28,024 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0867) Prec@1 88.000 (85.750) Prec@5 99.000 (98.792) +2022-11-14 13:52:28,033 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0865) Prec@1 85.000 (85.720) Prec@5 100.000 (98.840) +2022-11-14 13:52:28,042 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1204 (0.0878) Prec@1 82.000 (85.577) Prec@5 97.000 (98.769) +2022-11-14 13:52:28,052 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0879) Prec@1 84.000 (85.519) Prec@5 98.000 (98.741) +2022-11-14 13:52:28,061 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.0886) Prec@1 84.000 (85.464) Prec@5 98.000 (98.714) +2022-11-14 13:52:28,070 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0882) Prec@1 89.000 (85.586) Prec@5 100.000 (98.759) +2022-11-14 13:52:28,079 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0878) Prec@1 86.000 (85.600) Prec@5 99.000 (98.767) +2022-11-14 13:52:28,087 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0876) Prec@1 83.000 (85.516) Prec@5 98.000 (98.742) +2022-11-14 13:52:28,095 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0873) Prec@1 86.000 (85.531) Prec@5 100.000 (98.781) +2022-11-14 13:52:28,105 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0871) Prec@1 86.000 (85.545) Prec@5 99.000 (98.788) +2022-11-14 13:52:28,114 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1251 (0.0883) Prec@1 77.000 (85.294) Prec@5 97.000 (98.735) +2022-11-14 13:52:28,123 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0887) Prec@1 83.000 (85.229) Prec@5 100.000 (98.771) +2022-11-14 13:52:28,132 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0886) Prec@1 85.000 (85.222) Prec@5 100.000 (98.806) +2022-11-14 13:52:28,142 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0887) Prec@1 85.000 (85.216) Prec@5 99.000 (98.811) +2022-11-14 13:52:28,150 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0887) Prec@1 84.000 (85.184) Prec@5 100.000 (98.842) +2022-11-14 13:52:28,159 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0878) Prec@1 93.000 (85.385) Prec@5 99.000 (98.846) +2022-11-14 13:52:28,168 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0879) Prec@1 84.000 (85.350) Prec@5 99.000 (98.850) +2022-11-14 13:52:28,176 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1171 (0.0886) Prec@1 79.000 (85.195) Prec@5 98.000 (98.829) +2022-11-14 13:52:28,184 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0883) Prec@1 89.000 (85.286) Prec@5 97.000 (98.786) +2022-11-14 13:52:28,192 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0878) Prec@1 90.000 (85.395) Prec@5 98.000 (98.767) +2022-11-14 13:52:28,200 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0877) Prec@1 87.000 (85.432) Prec@5 99.000 (98.773) +2022-11-14 13:52:28,210 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0876) Prec@1 87.000 (85.467) Prec@5 100.000 (98.800) +2022-11-14 13:52:28,219 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0879) Prec@1 82.000 (85.391) Prec@5 100.000 (98.826) +2022-11-14 13:52:28,228 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0878) Prec@1 84.000 (85.362) Prec@5 99.000 (98.830) +2022-11-14 13:52:28,237 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.0882) Prec@1 79.000 (85.229) Prec@5 99.000 (98.833) +2022-11-14 13:52:28,246 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0879) Prec@1 86.000 (85.245) Prec@5 100.000 (98.857) +2022-11-14 13:52:28,254 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1263 (0.0887) Prec@1 77.000 (85.080) Prec@5 98.000 (98.840) +2022-11-14 13:52:28,264 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0887) Prec@1 83.000 (85.039) Prec@5 98.000 (98.824) +2022-11-14 13:52:28,274 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0887) Prec@1 85.000 (85.038) Prec@5 100.000 (98.846) +2022-11-14 13:52:28,282 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0889) Prec@1 84.000 (85.019) Prec@5 99.000 (98.849) +2022-11-14 13:52:28,291 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0890) Prec@1 84.000 (85.000) Prec@5 99.000 (98.852) +2022-11-14 13:52:28,300 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0891) Prec@1 83.000 (84.964) Prec@5 99.000 (98.855) +2022-11-14 13:52:28,308 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1059 (0.0894) Prec@1 83.000 (84.929) Prec@5 98.000 (98.839) +2022-11-14 13:52:28,317 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0896) Prec@1 80.000 (84.842) Prec@5 100.000 (98.860) +2022-11-14 13:52:28,327 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0892) Prec@1 90.000 (84.931) Prec@5 98.000 (98.845) +2022-11-14 13:52:28,338 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0894) Prec@1 82.000 (84.881) Prec@5 99.000 (98.847) +2022-11-14 13:52:28,348 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0896) Prec@1 84.000 (84.867) Prec@5 98.000 (98.833) +2022-11-14 13:52:28,357 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0896) Prec@1 85.000 (84.869) Prec@5 100.000 (98.852) +2022-11-14 13:52:28,367 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0893) Prec@1 88.000 (84.919) Prec@5 99.000 (98.855) +2022-11-14 13:52:28,376 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0892) Prec@1 84.000 (84.905) Prec@5 100.000 (98.873) +2022-11-14 13:52:28,386 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0888) Prec@1 89.000 (84.969) Prec@5 100.000 (98.891) +2022-11-14 13:52:28,396 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0891) Prec@1 84.000 (84.954) Prec@5 99.000 (98.892) +2022-11-14 13:52:28,405 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1149 (0.0895) Prec@1 81.000 (84.894) Prec@5 99.000 (98.894) +2022-11-14 13:52:28,414 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0891) Prec@1 88.000 (84.940) Prec@5 100.000 (98.910) +2022-11-14 13:52:28,423 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1088 (0.0894) Prec@1 82.000 (84.897) Prec@5 97.000 (98.882) +2022-11-14 13:52:28,432 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0892) Prec@1 88.000 (84.942) Prec@5 99.000 (98.884) +2022-11-14 13:52:28,440 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1364 (0.0899) Prec@1 78.000 (84.843) Prec@5 96.000 (98.843) +2022-11-14 13:52:28,449 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0901) Prec@1 84.000 (84.831) Prec@5 98.000 (98.831) +2022-11-14 13:52:28,458 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0899) Prec@1 87.000 (84.861) Prec@5 100.000 (98.847) +2022-11-14 13:52:28,467 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0896) Prec@1 89.000 (84.918) Prec@5 99.000 (98.849) +2022-11-14 13:52:28,475 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0893) Prec@1 87.000 (84.946) Prec@5 99.000 (98.851) +2022-11-14 13:52:28,483 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0894) Prec@1 85.000 (84.947) Prec@5 100.000 (98.867) +2022-11-14 13:52:28,491 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0891) Prec@1 91.000 (85.026) Prec@5 99.000 (98.868) +2022-11-14 13:52:28,499 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0890) Prec@1 84.000 (85.013) Prec@5 99.000 (98.870) +2022-11-14 13:52:28,509 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1041 (0.0892) Prec@1 80.000 (84.949) Prec@5 99.000 (98.872) +2022-11-14 13:52:28,517 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0894) Prec@1 81.000 (84.899) Prec@5 100.000 (98.886) +2022-11-14 13:52:28,526 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0894) Prec@1 82.000 (84.862) Prec@5 100.000 (98.900) +2022-11-14 13:52:28,535 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0891) Prec@1 87.000 (84.889) Prec@5 99.000 (98.901) +2022-11-14 13:52:28,545 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0894) Prec@1 83.000 (84.866) Prec@5 98.000 (98.890) +2022-11-14 13:52:28,554 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0894) Prec@1 85.000 (84.867) Prec@5 99.000 (98.892) +2022-11-14 13:52:28,563 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0893) Prec@1 89.000 (84.917) Prec@5 100.000 (98.905) +2022-11-14 13:52:28,572 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0894) Prec@1 83.000 (84.894) Prec@5 98.000 (98.894) +2022-11-14 13:52:28,581 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0893) Prec@1 89.000 (84.942) Prec@5 97.000 (98.872) +2022-11-14 13:52:28,591 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0894) Prec@1 81.000 (84.897) Prec@5 99.000 (98.874) +2022-11-14 13:52:28,600 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0892) Prec@1 88.000 (84.932) Prec@5 98.000 (98.864) +2022-11-14 13:52:28,609 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0891) Prec@1 86.000 (84.944) Prec@5 100.000 (98.876) +2022-11-14 13:52:28,617 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0891) Prec@1 87.000 (84.967) Prec@5 98.000 (98.867) +2022-11-14 13:52:28,627 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0891) Prec@1 83.000 (84.945) Prec@5 100.000 (98.879) +2022-11-14 13:52:28,635 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0887) Prec@1 93.000 (85.033) Prec@5 100.000 (98.891) +2022-11-14 13:52:28,644 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0887) Prec@1 82.000 (85.000) Prec@5 99.000 (98.892) +2022-11-14 13:52:28,654 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0888) Prec@1 81.000 (84.957) Prec@5 97.000 (98.872) +2022-11-14 13:52:28,663 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0886) Prec@1 88.000 (84.989) Prec@5 99.000 (98.874) +2022-11-14 13:52:28,672 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0885) Prec@1 86.000 (85.000) Prec@5 100.000 (98.885) +2022-11-14 13:52:28,681 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0885) Prec@1 86.000 (85.010) Prec@5 98.000 (98.876) +2022-11-14 13:52:28,691 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1122 (0.0887) Prec@1 84.000 (85.000) Prec@5 97.000 (98.857) +2022-11-14 13:52:28,700 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1140 (0.0890) Prec@1 80.000 (84.949) Prec@5 99.000 (98.859) +2022-11-14 13:52:28,709 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0892) Prec@1 83.000 (84.930) Prec@5 99.000 (98.860) +2022-11-14 13:52:28,779 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:52:29,067 Epoch: [109][0/500] Time 0.025 (0.025) Data 0.209 (0.209) Loss 0.0590 (0.0590) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:52:29,270 Epoch: [109][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.0521 (0.0556) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:52:29,466 Epoch: [109][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0852 (0.0655) Prec@1 86.000 (89.333) Prec@5 99.000 (99.000) +2022-11-14 13:52:29,724 Epoch: [109][30/500] Time 0.027 (0.019) Data 0.002 (0.008) Loss 0.0667 (0.0658) Prec@1 89.000 (89.250) Prec@5 98.000 (98.750) +2022-11-14 13:52:30,034 Epoch: [109][40/500] Time 0.033 (0.021) Data 0.002 (0.007) Loss 0.0577 (0.0642) Prec@1 91.000 (89.600) Prec@5 100.000 (99.000) +2022-11-14 13:52:30,348 Epoch: [109][50/500] Time 0.028 (0.023) Data 0.001 (0.006) Loss 0.0756 (0.0661) Prec@1 87.000 (89.167) Prec@5 97.000 (98.667) +2022-11-14 13:52:30,662 Epoch: [109][60/500] Time 0.030 (0.023) Data 0.002 (0.005) Loss 0.0711 (0.0668) Prec@1 88.000 (89.000) Prec@5 98.000 (98.571) +2022-11-14 13:52:30,981 Epoch: [109][70/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0692 (0.0671) Prec@1 87.000 (88.750) Prec@5 100.000 (98.750) +2022-11-14 13:52:31,290 Epoch: [109][80/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0559 (0.0658) Prec@1 91.000 (89.000) Prec@5 99.000 (98.778) +2022-11-14 13:52:31,607 Epoch: [109][90/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0918 (0.0684) Prec@1 83.000 (88.400) Prec@5 99.000 (98.800) +2022-11-14 13:52:31,923 Epoch: [109][100/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0686 (0.0684) Prec@1 88.000 (88.364) Prec@5 100.000 (98.909) +2022-11-14 13:52:32,240 Epoch: [109][110/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0809 (0.0695) Prec@1 85.000 (88.083) Prec@5 98.000 (98.833) +2022-11-14 13:52:32,553 Epoch: [109][120/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0839 (0.0706) Prec@1 86.000 (87.923) Prec@5 100.000 (98.923) +2022-11-14 13:52:32,862 Epoch: [109][130/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0993 (0.0726) Prec@1 84.000 (87.643) Prec@5 98.000 (98.857) +2022-11-14 13:52:33,182 Epoch: [109][140/500] Time 0.036 (0.026) Data 0.001 (0.003) Loss 0.0762 (0.0729) Prec@1 90.000 (87.800) Prec@5 100.000 (98.933) +2022-11-14 13:52:33,498 Epoch: [109][150/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0827 (0.0735) Prec@1 88.000 (87.812) Prec@5 100.000 (99.000) +2022-11-14 13:52:33,813 Epoch: [109][160/500] Time 0.025 (0.026) Data 0.002 (0.003) Loss 0.0615 (0.0728) Prec@1 88.000 (87.824) Prec@5 98.000 (98.941) +2022-11-14 13:52:34,131 Epoch: [109][170/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0897 (0.0737) Prec@1 82.000 (87.500) Prec@5 99.000 (98.944) +2022-11-14 13:52:34,454 Epoch: [109][180/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0719 (0.0736) Prec@1 89.000 (87.579) Prec@5 98.000 (98.895) +2022-11-14 13:52:34,773 Epoch: [109][190/500] Time 0.031 (0.026) Data 0.001 (0.003) Loss 0.0596 (0.0729) Prec@1 90.000 (87.700) Prec@5 100.000 (98.950) +2022-11-14 13:52:35,094 Epoch: [109][200/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0569 (0.0722) Prec@1 92.000 (87.905) Prec@5 99.000 (98.952) +2022-11-14 13:52:35,428 Epoch: [109][210/500] Time 0.026 (0.027) Data 0.002 (0.003) Loss 0.0526 (0.0713) Prec@1 91.000 (88.045) Prec@5 99.000 (98.955) +2022-11-14 13:52:35,771 Epoch: [109][220/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0672 (0.0711) Prec@1 87.000 (88.000) Prec@5 99.000 (98.957) +2022-11-14 13:52:36,084 Epoch: [109][230/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.0945 (0.0721) Prec@1 82.000 (87.750) Prec@5 99.000 (98.958) +2022-11-14 13:52:36,405 Epoch: [109][240/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0790 (0.0723) Prec@1 87.000 (87.720) Prec@5 98.000 (98.920) +2022-11-14 13:52:36,724 Epoch: [109][250/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0819 (0.0727) Prec@1 87.000 (87.692) Prec@5 97.000 (98.846) +2022-11-14 13:52:37,047 Epoch: [109][260/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0928 (0.0735) Prec@1 83.000 (87.519) Prec@5 100.000 (98.889) +2022-11-14 13:52:37,365 Epoch: [109][270/500] Time 0.028 (0.027) Data 0.001 (0.003) Loss 0.0707 (0.0734) Prec@1 89.000 (87.571) Prec@5 100.000 (98.929) +2022-11-14 13:52:37,686 Epoch: [109][280/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0693 (0.0732) Prec@1 89.000 (87.621) Prec@5 99.000 (98.931) +2022-11-14 13:52:38,006 Epoch: [109][290/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0528 (0.0725) Prec@1 89.000 (87.667) Prec@5 100.000 (98.967) +2022-11-14 13:52:38,408 Epoch: [109][300/500] Time 0.044 (0.027) Data 0.002 (0.002) Loss 0.0794 (0.0728) Prec@1 85.000 (87.581) Prec@5 99.000 (98.968) +2022-11-14 13:52:38,873 Epoch: [109][310/500] Time 0.045 (0.028) Data 0.002 (0.002) Loss 0.0844 (0.0731) Prec@1 85.000 (87.500) Prec@5 99.000 (98.969) +2022-11-14 13:52:39,337 Epoch: [109][320/500] Time 0.042 (0.028) Data 0.002 (0.002) Loss 0.0928 (0.0737) Prec@1 83.000 (87.364) Prec@5 97.000 (98.909) +2022-11-14 13:52:39,799 Epoch: [109][330/500] Time 0.042 (0.029) Data 0.002 (0.002) Loss 0.0521 (0.0731) Prec@1 92.000 (87.500) Prec@5 100.000 (98.941) +2022-11-14 13:52:40,262 Epoch: [109][340/500] Time 0.043 (0.029) Data 0.003 (0.002) Loss 0.0523 (0.0725) Prec@1 92.000 (87.629) Prec@5 99.000 (98.943) +2022-11-14 13:52:40,755 Epoch: [109][350/500] Time 0.053 (0.030) Data 0.002 (0.002) Loss 0.0590 (0.0721) Prec@1 87.000 (87.611) Prec@5 99.000 (98.944) +2022-11-14 13:52:41,219 Epoch: [109][360/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0809 (0.0724) Prec@1 84.000 (87.514) Prec@5 99.000 (98.946) +2022-11-14 13:52:41,684 Epoch: [109][370/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0842 (0.0727) Prec@1 83.000 (87.395) Prec@5 97.000 (98.895) +2022-11-14 13:52:42,153 Epoch: [109][380/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0760 (0.0727) Prec@1 87.000 (87.385) Prec@5 100.000 (98.923) +2022-11-14 13:52:42,628 Epoch: [109][390/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0763 (0.0728) Prec@1 88.000 (87.400) Prec@5 99.000 (98.925) +2022-11-14 13:52:43,191 Epoch: [109][400/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0680 (0.0727) Prec@1 87.000 (87.390) Prec@5 99.000 (98.927) +2022-11-14 13:52:43,694 Epoch: [109][410/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0549 (0.0723) Prec@1 92.000 (87.500) Prec@5 100.000 (98.952) +2022-11-14 13:52:44,236 Epoch: [109][420/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0725 (0.0723) Prec@1 88.000 (87.512) Prec@5 100.000 (98.977) +2022-11-14 13:52:44,708 Epoch: [109][430/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0924 (0.0728) Prec@1 86.000 (87.477) Prec@5 99.000 (98.977) +2022-11-14 13:52:45,203 Epoch: [109][440/500] Time 0.053 (0.033) Data 0.002 (0.002) Loss 0.0865 (0.0731) Prec@1 87.000 (87.467) Prec@5 99.000 (98.978) +2022-11-14 13:52:45,675 Epoch: [109][450/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0515 (0.0726) Prec@1 92.000 (87.565) Prec@5 100.000 (99.000) +2022-11-14 13:52:46,152 Epoch: [109][460/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0649 (0.0724) Prec@1 87.000 (87.553) Prec@5 100.000 (99.021) +2022-11-14 13:52:46,631 Epoch: [109][470/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0773 (0.0725) Prec@1 87.000 (87.542) Prec@5 99.000 (99.021) +2022-11-14 13:52:47,105 Epoch: [109][480/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0888 (0.0729) Prec@1 86.000 (87.510) Prec@5 100.000 (99.041) +2022-11-14 13:52:47,615 Epoch: [109][490/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0609 (0.0726) Prec@1 88.000 (87.520) Prec@5 97.000 (99.000) +2022-11-14 13:52:48,060 Epoch: [109][499/500] Time 0.060 (0.034) Data 0.002 (0.002) Loss 0.0883 (0.0729) Prec@1 84.000 (87.451) Prec@5 97.000 (98.961) +2022-11-14 13:52:48,356 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0788 (0.0788) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:52:48,364 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0821) Prec@1 85.000 (86.000) Prec@5 100.000 (99.000) +2022-11-14 13:52:48,376 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.0919) Prec@1 80.000 (84.000) Prec@5 98.000 (98.667) +2022-11-14 13:52:48,386 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0909) Prec@1 85.000 (84.250) Prec@5 100.000 (99.000) +2022-11-14 13:52:48,394 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0916) Prec@1 80.000 (83.400) Prec@5 99.000 (99.000) +2022-11-14 13:52:48,403 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0848) Prec@1 89.000 (84.333) Prec@5 100.000 (99.167) +2022-11-14 13:52:48,413 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0804) Prec@1 89.000 (85.000) Prec@5 100.000 (99.286) +2022-11-14 13:52:48,422 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0834) Prec@1 80.000 (84.375) Prec@5 97.000 (99.000) +2022-11-14 13:52:48,431 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0856) Prec@1 83.000 (84.222) Prec@5 100.000 (99.111) +2022-11-14 13:52:48,439 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0871) Prec@1 83.000 (84.100) Prec@5 99.000 (99.100) +2022-11-14 13:52:48,449 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0873) Prec@1 83.000 (84.000) Prec@5 99.000 (99.091) +2022-11-14 13:52:48,458 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0869) Prec@1 84.000 (84.000) Prec@5 100.000 (99.167) +2022-11-14 13:52:48,468 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0869) Prec@1 86.000 (84.154) Prec@5 100.000 (99.231) +2022-11-14 13:52:48,478 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0863) Prec@1 90.000 (84.571) Prec@5 99.000 (99.214) +2022-11-14 13:52:48,488 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0868) Prec@1 83.000 (84.467) Prec@5 99.000 (99.200) +2022-11-14 13:52:48,495 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0864) Prec@1 85.000 (84.500) Prec@5 100.000 (99.250) +2022-11-14 13:52:48,504 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0845) Prec@1 90.000 (84.824) Prec@5 99.000 (99.235) +2022-11-14 13:52:48,512 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0858) Prec@1 79.000 (84.500) Prec@5 100.000 (99.278) +2022-11-14 13:52:48,520 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0866) Prec@1 84.000 (84.474) Prec@5 98.000 (99.211) +2022-11-14 13:52:48,529 Test: [19/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1160 (0.0881) Prec@1 80.000 (84.250) Prec@5 97.000 (99.100) +2022-11-14 13:52:48,539 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0880) Prec@1 85.000 (84.286) Prec@5 98.000 (99.048) +2022-11-14 13:52:48,550 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0883) Prec@1 80.000 (84.091) Prec@5 99.000 (99.045) +2022-11-14 13:52:48,558 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1186 (0.0896) Prec@1 79.000 (83.870) Prec@5 100.000 (99.087) +2022-11-14 13:52:48,569 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0890) Prec@1 86.000 (83.958) Prec@5 99.000 (99.083) +2022-11-14 13:52:48,580 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0893) Prec@1 85.000 (84.000) Prec@5 99.000 (99.080) +2022-11-14 13:52:48,588 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0899) Prec@1 81.000 (83.885) Prec@5 97.000 (99.000) +2022-11-14 13:52:48,598 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0888) Prec@1 92.000 (84.185) Prec@5 99.000 (99.000) +2022-11-14 13:52:48,609 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0888) Prec@1 84.000 (84.179) Prec@5 100.000 (99.036) +2022-11-14 13:52:48,619 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0882) Prec@1 87.000 (84.276) Prec@5 99.000 (99.034) +2022-11-14 13:52:48,629 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0880) Prec@1 87.000 (84.367) Prec@5 98.000 (99.000) +2022-11-14 13:52:48,639 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0879) Prec@1 83.000 (84.323) Prec@5 100.000 (99.032) +2022-11-14 13:52:48,651 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.0890) Prec@1 80.000 (84.188) Prec@5 99.000 (99.031) +2022-11-14 13:52:48,662 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0891) Prec@1 84.000 (84.182) Prec@5 100.000 (99.061) +2022-11-14 13:52:48,671 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1144 (0.0898) Prec@1 79.000 (84.029) Prec@5 100.000 (99.088) +2022-11-14 13:52:48,679 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0899) Prec@1 86.000 (84.086) Prec@5 98.000 (99.057) +2022-11-14 13:52:48,691 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0895) Prec@1 90.000 (84.250) Prec@5 99.000 (99.056) +2022-11-14 13:52:48,702 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0904) Prec@1 77.000 (84.054) Prec@5 97.000 (99.000) +2022-11-14 13:52:48,711 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0909) Prec@1 83.000 (84.026) Prec@5 98.000 (98.974) +2022-11-14 13:52:48,720 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0904) Prec@1 87.000 (84.103) Prec@5 99.000 (98.974) +2022-11-14 13:52:48,732 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0899) Prec@1 88.000 (84.200) Prec@5 99.000 (98.975) +2022-11-14 13:52:48,743 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0902) Prec@1 86.000 (84.244) Prec@5 99.000 (98.976) +2022-11-14 13:52:48,752 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0903) Prec@1 85.000 (84.262) Prec@5 97.000 (98.929) +2022-11-14 13:52:48,761 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0902) Prec@1 87.000 (84.326) Prec@5 99.000 (98.930) +2022-11-14 13:52:48,773 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0897) Prec@1 87.000 (84.386) Prec@5 98.000 (98.909) +2022-11-14 13:52:48,784 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0894) Prec@1 89.000 (84.489) Prec@5 99.000 (98.911) +2022-11-14 13:52:48,794 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0898) Prec@1 81.000 (84.413) Prec@5 100.000 (98.935) +2022-11-14 13:52:48,803 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0898) Prec@1 85.000 (84.426) Prec@5 100.000 (98.957) +2022-11-14 13:52:48,814 Test: [47/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0897) Prec@1 88.000 (84.500) Prec@5 99.000 (98.958) +2022-11-14 13:52:48,825 Test: [48/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0895) Prec@1 87.000 (84.551) Prec@5 100.000 (98.980) +2022-11-14 13:52:48,833 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0900) Prec@1 82.000 (84.500) Prec@5 98.000 (98.960) +2022-11-14 13:52:48,841 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0901) Prec@1 83.000 (84.471) Prec@5 99.000 (98.961) +2022-11-14 13:52:48,853 Test: [51/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1121 (0.0905) Prec@1 81.000 (84.404) Prec@5 99.000 (98.962) +2022-11-14 13:52:48,864 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0905) Prec@1 85.000 (84.415) Prec@5 98.000 (98.943) +2022-11-14 13:52:48,874 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0904) Prec@1 85.000 (84.426) Prec@5 99.000 (98.944) +2022-11-14 13:52:48,884 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0905) Prec@1 83.000 (84.400) Prec@5 100.000 (98.964) +2022-11-14 13:52:48,896 Test: [55/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0903) Prec@1 86.000 (84.429) Prec@5 99.000 (98.964) +2022-11-14 13:52:48,907 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0902) Prec@1 86.000 (84.456) Prec@5 100.000 (98.982) +2022-11-14 13:52:48,917 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0902) Prec@1 88.000 (84.517) Prec@5 99.000 (98.983) +2022-11-14 13:52:48,926 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.0907) Prec@1 79.000 (84.424) Prec@5 99.000 (98.983) +2022-11-14 13:52:48,938 Test: [59/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0908) Prec@1 81.000 (84.367) Prec@5 100.000 (99.000) +2022-11-14 13:52:48,949 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0908) Prec@1 87.000 (84.410) Prec@5 99.000 (99.000) +2022-11-14 13:52:48,958 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0909) Prec@1 86.000 (84.435) Prec@5 98.000 (98.984) +2022-11-14 13:52:48,967 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0906) Prec@1 86.000 (84.460) Prec@5 99.000 (98.984) +2022-11-14 13:52:48,979 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0902) Prec@1 89.000 (84.531) Prec@5 99.000 (98.984) +2022-11-14 13:52:48,990 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0901) Prec@1 84.000 (84.523) Prec@5 100.000 (99.000) +2022-11-14 13:52:49,001 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0902) Prec@1 82.000 (84.485) Prec@5 100.000 (99.015) +2022-11-14 13:52:49,011 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0898) Prec@1 89.000 (84.552) Prec@5 100.000 (99.030) +2022-11-14 13:52:49,023 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0898) Prec@1 84.000 (84.544) Prec@5 98.000 (99.015) +2022-11-14 13:52:49,034 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0899) Prec@1 82.000 (84.507) Prec@5 100.000 (99.029) +2022-11-14 13:52:49,045 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.0903) Prec@1 82.000 (84.471) Prec@5 100.000 (99.043) +2022-11-14 13:52:49,054 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0905) Prec@1 81.000 (84.423) Prec@5 99.000 (99.042) +2022-11-14 13:52:49,063 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0904) Prec@1 85.000 (84.431) Prec@5 98.000 (99.028) +2022-11-14 13:52:49,072 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0902) Prec@1 89.000 (84.493) Prec@5 99.000 (99.027) +2022-11-14 13:52:49,081 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0899) Prec@1 91.000 (84.581) Prec@5 100.000 (99.041) +2022-11-14 13:52:49,090 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1166 (0.0902) Prec@1 79.000 (84.507) Prec@5 99.000 (99.040) +2022-11-14 13:52:49,100 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0899) Prec@1 87.000 (84.539) Prec@5 100.000 (99.053) +2022-11-14 13:52:49,109 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0898) Prec@1 86.000 (84.558) Prec@5 98.000 (99.039) +2022-11-14 13:52:49,118 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0900) Prec@1 80.000 (84.500) Prec@5 98.000 (99.026) +2022-11-14 13:52:49,127 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0901) Prec@1 85.000 (84.506) Prec@5 99.000 (99.025) +2022-11-14 13:52:49,136 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0901) Prec@1 86.000 (84.525) Prec@5 98.000 (99.013) +2022-11-14 13:52:49,146 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0902) Prec@1 84.000 (84.519) Prec@5 98.000 (99.000) +2022-11-14 13:52:49,155 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0903) Prec@1 82.000 (84.488) Prec@5 98.000 (98.988) +2022-11-14 13:52:49,163 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0903) Prec@1 88.000 (84.530) Prec@5 99.000 (98.988) +2022-11-14 13:52:49,171 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0904) Prec@1 83.000 (84.512) Prec@5 99.000 (98.988) +2022-11-14 13:52:49,181 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0907) Prec@1 81.000 (84.471) Prec@5 98.000 (98.976) +2022-11-14 13:52:49,190 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0909) Prec@1 80.000 (84.419) Prec@5 100.000 (98.988) +2022-11-14 13:52:49,199 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0908) Prec@1 82.000 (84.391) Prec@5 99.000 (98.989) +2022-11-14 13:52:49,209 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0906) Prec@1 90.000 (84.455) Prec@5 99.000 (98.989) +2022-11-14 13:52:49,220 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0906) Prec@1 82.000 (84.427) Prec@5 100.000 (99.000) +2022-11-14 13:52:49,229 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0906) Prec@1 84.000 (84.422) Prec@5 98.000 (98.989) +2022-11-14 13:52:49,239 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0904) Prec@1 91.000 (84.495) Prec@5 100.000 (99.000) +2022-11-14 13:52:49,248 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0900) Prec@1 91.000 (84.565) Prec@5 100.000 (99.011) +2022-11-14 13:52:49,258 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0903) Prec@1 83.000 (84.548) Prec@5 99.000 (99.011) +2022-11-14 13:52:49,266 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0904) Prec@1 83.000 (84.532) Prec@5 99.000 (99.011) +2022-11-14 13:52:49,277 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0904) Prec@1 87.000 (84.558) Prec@5 100.000 (99.021) +2022-11-14 13:52:49,288 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0902) Prec@1 89.000 (84.604) Prec@5 100.000 (99.031) +2022-11-14 13:52:49,297 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0901) Prec@1 83.000 (84.588) Prec@5 99.000 (99.031) +2022-11-14 13:52:49,306 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0903) Prec@1 83.000 (84.571) Prec@5 99.000 (99.031) +2022-11-14 13:52:49,316 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.0906) Prec@1 79.000 (84.515) Prec@5 100.000 (99.040) +2022-11-14 13:52:49,324 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0905) Prec@1 82.000 (84.490) Prec@5 100.000 (99.050) +2022-11-14 13:52:49,378 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:52:49,679 Epoch: [110][0/500] Time 0.023 (0.023) Data 0.222 (0.222) Loss 0.0630 (0.0630) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:52:49,892 Epoch: [110][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0421 (0.0526) Prec@1 92.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 13:52:50,118 Epoch: [110][20/500] Time 0.025 (0.020) Data 0.002 (0.012) Loss 0.0677 (0.0576) Prec@1 88.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 13:52:50,386 Epoch: [110][30/500] Time 0.025 (0.021) Data 0.001 (0.009) Loss 0.0781 (0.0627) Prec@1 87.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 13:52:50,667 Epoch: [110][40/500] Time 0.022 (0.022) Data 0.002 (0.007) Loss 0.0765 (0.0655) Prec@1 88.000 (88.800) Prec@5 98.000 (99.400) +2022-11-14 13:52:50,946 Epoch: [110][50/500] Time 0.023 (0.022) Data 0.002 (0.006) Loss 0.0665 (0.0657) Prec@1 88.000 (88.667) Prec@5 100.000 (99.500) +2022-11-14 13:52:51,223 Epoch: [110][60/500] Time 0.026 (0.023) Data 0.002 (0.005) Loss 0.0493 (0.0633) Prec@1 92.000 (89.143) Prec@5 99.000 (99.429) +2022-11-14 13:52:51,493 Epoch: [110][70/500] Time 0.023 (0.023) Data 0.002 (0.005) Loss 0.0698 (0.0641) Prec@1 86.000 (88.750) Prec@5 98.000 (99.250) +2022-11-14 13:52:51,769 Epoch: [110][80/500] Time 0.025 (0.023) Data 0.001 (0.005) Loss 0.0480 (0.0623) Prec@1 92.000 (89.111) Prec@5 100.000 (99.333) +2022-11-14 13:52:52,038 Epoch: [110][90/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0735 (0.0635) Prec@1 88.000 (89.000) Prec@5 99.000 (99.300) +2022-11-14 13:52:52,475 Epoch: [110][100/500] Time 0.043 (0.025) Data 0.002 (0.004) Loss 0.0393 (0.0613) Prec@1 94.000 (89.455) Prec@5 99.000 (99.273) +2022-11-14 13:52:52,941 Epoch: [110][110/500] Time 0.043 (0.026) Data 0.002 (0.004) Loss 0.0465 (0.0600) Prec@1 96.000 (90.000) Prec@5 100.000 (99.333) +2022-11-14 13:52:53,428 Epoch: [110][120/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0452 (0.0589) Prec@1 92.000 (90.154) Prec@5 100.000 (99.385) +2022-11-14 13:52:53,890 Epoch: [110][130/500] Time 0.044 (0.029) Data 0.002 (0.004) Loss 0.0622 (0.0591) Prec@1 89.000 (90.071) Prec@5 98.000 (99.286) +2022-11-14 13:52:54,385 Epoch: [110][140/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0716 (0.0600) Prec@1 88.000 (89.933) Prec@5 100.000 (99.333) +2022-11-14 13:52:54,868 Epoch: [110][150/500] Time 0.054 (0.031) Data 0.002 (0.003) Loss 0.0903 (0.0619) Prec@1 85.000 (89.625) Prec@5 100.000 (99.375) +2022-11-14 13:52:55,329 Epoch: [110][160/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0635 (0.0620) Prec@1 87.000 (89.471) Prec@5 99.000 (99.353) +2022-11-14 13:52:55,801 Epoch: [110][170/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0668 (0.0622) Prec@1 89.000 (89.444) Prec@5 100.000 (99.389) +2022-11-14 13:52:56,277 Epoch: [110][180/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0697 (0.0626) Prec@1 86.000 (89.263) Prec@5 100.000 (99.421) +2022-11-14 13:52:56,742 Epoch: [110][190/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0502 (0.0620) Prec@1 92.000 (89.400) Prec@5 98.000 (99.350) +2022-11-14 13:52:57,263 Epoch: [110][200/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0690 (0.0623) Prec@1 90.000 (89.429) Prec@5 100.000 (99.381) +2022-11-14 13:52:57,750 Epoch: [110][210/500] Time 0.061 (0.034) Data 0.002 (0.003) Loss 0.0788 (0.0631) Prec@1 87.000 (89.318) Prec@5 99.000 (99.364) +2022-11-14 13:52:58,230 Epoch: [110][220/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0667 (0.0632) Prec@1 89.000 (89.304) Prec@5 99.000 (99.348) +2022-11-14 13:52:58,745 Epoch: [110][230/500] Time 0.067 (0.035) Data 0.002 (0.003) Loss 0.0894 (0.0643) Prec@1 86.000 (89.167) Prec@5 100.000 (99.375) +2022-11-14 13:52:59,312 Epoch: [110][240/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0996 (0.0657) Prec@1 83.000 (88.920) Prec@5 99.000 (99.360) +2022-11-14 13:52:59,813 Epoch: [110][250/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0495 (0.0651) Prec@1 91.000 (89.000) Prec@5 99.000 (99.346) +2022-11-14 13:53:00,302 Epoch: [110][260/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0783 (0.0656) Prec@1 85.000 (88.852) Prec@5 99.000 (99.333) +2022-11-14 13:53:00,796 Epoch: [110][270/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0850 (0.0663) Prec@1 83.000 (88.643) Prec@5 100.000 (99.357) +2022-11-14 13:53:01,272 Epoch: [110][280/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0643 (0.0662) Prec@1 89.000 (88.655) Prec@5 100.000 (99.379) +2022-11-14 13:53:01,731 Epoch: [110][290/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0578 (0.0659) Prec@1 90.000 (88.700) Prec@5 100.000 (99.400) +2022-11-14 13:53:02,197 Epoch: [110][300/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0712 (0.0661) Prec@1 87.000 (88.645) Prec@5 100.000 (99.419) +2022-11-14 13:53:02,668 Epoch: [110][310/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0854 (0.0667) Prec@1 86.000 (88.562) Prec@5 100.000 (99.438) +2022-11-14 13:53:03,133 Epoch: [110][320/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0636 (0.0666) Prec@1 89.000 (88.576) Prec@5 99.000 (99.424) +2022-11-14 13:53:03,649 Epoch: [110][330/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0729 (0.0668) Prec@1 88.000 (88.559) Prec@5 99.000 (99.412) +2022-11-14 13:53:04,154 Epoch: [110][340/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0640 (0.0667) Prec@1 88.000 (88.543) Prec@5 100.000 (99.429) +2022-11-14 13:53:04,665 Epoch: [110][350/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0875 (0.0673) Prec@1 83.000 (88.389) Prec@5 100.000 (99.444) +2022-11-14 13:53:05,199 Epoch: [110][360/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.1064 (0.0684) Prec@1 81.000 (88.189) Prec@5 100.000 (99.459) +2022-11-14 13:53:05,699 Epoch: [110][370/500] Time 0.062 (0.038) Data 0.002 (0.003) Loss 0.0673 (0.0683) Prec@1 87.000 (88.158) Prec@5 100.000 (99.474) +2022-11-14 13:53:06,255 Epoch: [110][380/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0722 (0.0684) Prec@1 87.000 (88.128) Prec@5 98.000 (99.436) +2022-11-14 13:53:06,797 Epoch: [110][390/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0655 (0.0684) Prec@1 90.000 (88.175) Prec@5 100.000 (99.450) +2022-11-14 13:53:07,356 Epoch: [110][400/500] Time 0.038 (0.039) Data 0.002 (0.002) Loss 0.0709 (0.0684) Prec@1 88.000 (88.171) Prec@5 100.000 (99.463) +2022-11-14 13:53:07,897 Epoch: [110][410/500] Time 0.049 (0.040) Data 0.002 (0.002) Loss 0.0390 (0.0677) Prec@1 96.000 (88.357) Prec@5 100.000 (99.476) +2022-11-14 13:53:08,395 Epoch: [110][420/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0943 (0.0683) Prec@1 82.000 (88.209) Prec@5 99.000 (99.465) +2022-11-14 13:53:08,873 Epoch: [110][430/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0838 (0.0687) Prec@1 89.000 (88.227) Prec@5 99.000 (99.455) +2022-11-14 13:53:09,347 Epoch: [110][440/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0708 (0.0687) Prec@1 89.000 (88.244) Prec@5 100.000 (99.467) +2022-11-14 13:53:09,818 Epoch: [110][450/500] Time 0.053 (0.040) Data 0.002 (0.002) Loss 0.0629 (0.0686) Prec@1 90.000 (88.283) Prec@5 100.000 (99.478) +2022-11-14 13:53:10,291 Epoch: [110][460/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0767 (0.0688) Prec@1 87.000 (88.255) Prec@5 100.000 (99.489) +2022-11-14 13:53:10,758 Epoch: [110][470/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0726 (0.0689) Prec@1 88.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 13:53:11,216 Epoch: [110][480/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0903 (0.0693) Prec@1 85.000 (88.184) Prec@5 99.000 (99.490) +2022-11-14 13:53:11,682 Epoch: [110][490/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0643 (0.0692) Prec@1 90.000 (88.220) Prec@5 100.000 (99.500) +2022-11-14 13:53:12,106 Epoch: [110][499/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.1145 (0.0701) Prec@1 81.000 (88.078) Prec@5 97.000 (99.451) +2022-11-14 13:53:12,391 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0765 (0.0765) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:53:12,399 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0816) Prec@1 85.000 (85.500) Prec@5 100.000 (99.000) +2022-11-14 13:53:12,411 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0826) Prec@1 86.000 (85.667) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,423 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0851) Prec@1 83.000 (85.000) Prec@5 100.000 (99.250) +2022-11-14 13:53:12,434 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0832) Prec@1 87.000 (85.400) Prec@5 98.000 (99.000) +2022-11-14 13:53:12,444 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0463 (0.0771) Prec@1 92.000 (86.500) Prec@5 100.000 (99.167) +2022-11-14 13:53:12,455 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0749) Prec@1 90.000 (87.000) Prec@5 100.000 (99.286) +2022-11-14 13:53:12,467 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1130 (0.0797) Prec@1 79.000 (86.000) Prec@5 97.000 (99.000) +2022-11-14 13:53:12,478 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.0841) Prec@1 79.000 (85.222) Prec@5 98.000 (98.889) +2022-11-14 13:53:12,488 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0842) Prec@1 85.000 (85.200) Prec@5 98.000 (98.800) +2022-11-14 13:53:12,500 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0846) Prec@1 85.000 (85.182) Prec@5 100.000 (98.909) +2022-11-14 13:53:12,512 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1269 (0.0881) Prec@1 77.000 (84.500) Prec@5 98.000 (98.833) +2022-11-14 13:53:12,523 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0871) Prec@1 84.000 (84.462) Prec@5 100.000 (98.923) +2022-11-14 13:53:12,534 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0859) Prec@1 89.000 (84.786) Prec@5 100.000 (99.000) +2022-11-14 13:53:12,545 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0856) Prec@1 86.000 (84.867) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,557 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0864) Prec@1 81.000 (84.625) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,568 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0851) Prec@1 90.000 (84.941) Prec@5 98.000 (98.941) +2022-11-14 13:53:12,580 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1245 (0.0873) Prec@1 82.000 (84.778) Prec@5 100.000 (99.000) +2022-11-14 13:53:12,592 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0878) Prec@1 84.000 (84.737) Prec@5 100.000 (99.053) +2022-11-14 13:53:12,603 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0887) Prec@1 80.000 (84.500) Prec@5 97.000 (98.950) +2022-11-14 13:53:12,614 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0888) Prec@1 84.000 (84.476) Prec@5 100.000 (99.000) +2022-11-14 13:53:12,624 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.0902) Prec@1 80.000 (84.273) Prec@5 100.000 (99.045) +2022-11-14 13:53:12,636 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0908) Prec@1 81.000 (84.130) Prec@5 99.000 (99.043) +2022-11-14 13:53:12,648 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0906) Prec@1 85.000 (84.167) Prec@5 100.000 (99.083) +2022-11-14 13:53:12,658 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0915) Prec@1 81.000 (84.040) Prec@5 99.000 (99.080) +2022-11-14 13:53:12,668 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.0924) Prec@1 78.000 (83.808) Prec@5 97.000 (99.000) +2022-11-14 13:53:12,680 Test: [26/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0919) Prec@1 86.000 (83.889) Prec@5 100.000 (99.037) +2022-11-14 13:53:12,693 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0917) Prec@1 84.000 (83.893) Prec@5 99.000 (99.036) +2022-11-14 13:53:12,703 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0917) Prec@1 85.000 (83.931) Prec@5 98.000 (99.000) +2022-11-14 13:53:12,713 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0917) Prec@1 84.000 (83.933) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,725 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0914) Prec@1 87.000 (84.032) Prec@5 100.000 (99.032) +2022-11-14 13:53:12,735 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0918) Prec@1 83.000 (84.000) Prec@5 100.000 (99.062) +2022-11-14 13:53:12,746 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0922) Prec@1 85.000 (84.030) Prec@5 99.000 (99.061) +2022-11-14 13:53:12,757 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0929) Prec@1 78.000 (83.853) Prec@5 99.000 (99.059) +2022-11-14 13:53:12,770 Test: [34/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0925) Prec@1 88.000 (83.971) Prec@5 98.000 (99.029) +2022-11-14 13:53:12,783 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0922) Prec@1 87.000 (84.056) Prec@5 100.000 (99.056) +2022-11-14 13:53:12,795 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0916) Prec@1 86.000 (84.108) Prec@5 97.000 (99.000) +2022-11-14 13:53:12,806 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0921) Prec@1 81.000 (84.026) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,819 Test: [38/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0916) Prec@1 90.000 (84.179) Prec@5 99.000 (99.000) +2022-11-14 13:53:12,831 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0913) Prec@1 86.000 (84.225) Prec@5 100.000 (99.025) +2022-11-14 13:53:12,842 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0916) Prec@1 83.000 (84.195) Prec@5 95.000 (98.927) +2022-11-14 13:53:12,851 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0911) Prec@1 88.000 (84.286) Prec@5 98.000 (98.905) +2022-11-14 13:53:12,863 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0904) Prec@1 92.000 (84.465) Prec@5 98.000 (98.884) +2022-11-14 13:53:12,874 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0907) Prec@1 84.000 (84.455) Prec@5 98.000 (98.864) +2022-11-14 13:53:12,885 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0911) Prec@1 82.000 (84.400) Prec@5 98.000 (98.844) +2022-11-14 13:53:12,896 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0910) Prec@1 85.000 (84.413) Prec@5 99.000 (98.848) +2022-11-14 13:53:12,910 Test: [46/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0913) Prec@1 83.000 (84.383) Prec@5 100.000 (98.872) +2022-11-14 13:53:12,923 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0913) Prec@1 83.000 (84.354) Prec@5 100.000 (98.896) +2022-11-14 13:53:12,934 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0910) Prec@1 86.000 (84.388) Prec@5 100.000 (98.918) +2022-11-14 13:53:12,946 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.0916) Prec@1 78.000 (84.260) Prec@5 98.000 (98.900) +2022-11-14 13:53:12,957 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0913) Prec@1 85.000 (84.275) Prec@5 99.000 (98.902) +2022-11-14 13:53:12,968 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0917) Prec@1 80.000 (84.192) Prec@5 99.000 (98.904) +2022-11-14 13:53:12,978 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0916) Prec@1 87.000 (84.245) Prec@5 99.000 (98.906) +2022-11-14 13:53:12,989 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0912) Prec@1 86.000 (84.278) Prec@5 98.000 (98.889) +2022-11-14 13:53:13,000 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1245 (0.0918) Prec@1 80.000 (84.200) Prec@5 100.000 (98.909) +2022-11-14 13:53:13,011 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0920) Prec@1 85.000 (84.214) Prec@5 99.000 (98.911) +2022-11-14 13:53:13,020 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0919) Prec@1 84.000 (84.211) Prec@5 100.000 (98.930) +2022-11-14 13:53:13,030 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0916) Prec@1 89.000 (84.293) Prec@5 97.000 (98.897) +2022-11-14 13:53:13,040 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1490 (0.0926) Prec@1 73.000 (84.102) Prec@5 100.000 (98.915) +2022-11-14 13:53:13,050 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0927) Prec@1 84.000 (84.100) Prec@5 100.000 (98.933) +2022-11-14 13:53:13,061 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0928) Prec@1 84.000 (84.098) Prec@5 99.000 (98.934) +2022-11-14 13:53:13,072 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0926) Prec@1 85.000 (84.113) Prec@5 99.000 (98.935) +2022-11-14 13:53:13,083 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0923) Prec@1 87.000 (84.159) Prec@5 100.000 (98.952) +2022-11-14 13:53:13,095 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0920) Prec@1 91.000 (84.266) Prec@5 99.000 (98.953) +2022-11-14 13:53:13,105 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.0924) Prec@1 79.000 (84.185) Prec@5 97.000 (98.923) +2022-11-14 13:53:13,116 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0926) Prec@1 81.000 (84.136) Prec@5 99.000 (98.924) +2022-11-14 13:53:13,127 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0921) Prec@1 93.000 (84.269) Prec@5 99.000 (98.925) +2022-11-14 13:53:13,138 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0919) Prec@1 88.000 (84.324) Prec@5 97.000 (98.897) +2022-11-14 13:53:13,150 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0919) Prec@1 84.000 (84.319) Prec@5 99.000 (98.899) +2022-11-14 13:53:13,161 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1333 (0.0925) Prec@1 78.000 (84.229) Prec@5 96.000 (98.857) +2022-11-14 13:53:13,172 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0927) Prec@1 81.000 (84.183) Prec@5 97.000 (98.831) +2022-11-14 13:53:13,183 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0925) Prec@1 87.000 (84.222) Prec@5 100.000 (98.847) +2022-11-14 13:53:13,193 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0923) Prec@1 86.000 (84.247) Prec@5 100.000 (98.863) +2022-11-14 13:53:13,205 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0919) Prec@1 90.000 (84.324) Prec@5 100.000 (98.878) +2022-11-14 13:53:13,218 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1366 (0.0925) Prec@1 79.000 (84.253) Prec@5 99.000 (98.880) +2022-11-14 13:53:13,228 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0923) Prec@1 89.000 (84.316) Prec@5 99.000 (98.882) +2022-11-14 13:53:13,241 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0922) Prec@1 87.000 (84.351) Prec@5 99.000 (98.883) +2022-11-14 13:53:13,252 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0922) Prec@1 84.000 (84.346) Prec@5 98.000 (98.872) +2022-11-14 13:53:13,263 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0922) Prec@1 83.000 (84.329) Prec@5 100.000 (98.886) +2022-11-14 13:53:13,274 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0922) Prec@1 82.000 (84.300) Prec@5 99.000 (98.888) +2022-11-14 13:53:13,284 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0922) Prec@1 87.000 (84.333) Prec@5 98.000 (98.877) +2022-11-14 13:53:13,296 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0921) Prec@1 88.000 (84.378) Prec@5 99.000 (98.878) +2022-11-14 13:53:13,307 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0922) Prec@1 85.000 (84.386) Prec@5 100.000 (98.892) +2022-11-14 13:53:13,319 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0918) Prec@1 88.000 (84.429) Prec@5 98.000 (98.881) +2022-11-14 13:53:13,331 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0919) Prec@1 84.000 (84.424) Prec@5 99.000 (98.882) +2022-11-14 13:53:13,342 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0921) Prec@1 83.000 (84.407) Prec@5 99.000 (98.884) +2022-11-14 13:53:13,351 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0921) Prec@1 84.000 (84.402) Prec@5 98.000 (98.874) +2022-11-14 13:53:13,362 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0923) Prec@1 82.000 (84.375) Prec@5 98.000 (98.864) +2022-11-14 13:53:13,371 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0919) Prec@1 89.000 (84.427) Prec@5 100.000 (98.876) +2022-11-14 13:53:13,381 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0920) Prec@1 86.000 (84.444) Prec@5 99.000 (98.878) +2022-11-14 13:53:13,394 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0916) Prec@1 91.000 (84.516) Prec@5 100.000 (98.890) +2022-11-14 13:53:13,406 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0912) Prec@1 91.000 (84.587) Prec@5 99.000 (98.891) +2022-11-14 13:53:13,418 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0913) Prec@1 81.000 (84.548) Prec@5 100.000 (98.903) +2022-11-14 13:53:13,427 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0912) Prec@1 87.000 (84.574) Prec@5 97.000 (98.883) +2022-11-14 13:53:13,438 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0913) Prec@1 83.000 (84.558) Prec@5 99.000 (98.884) +2022-11-14 13:53:13,451 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0912) Prec@1 88.000 (84.594) Prec@5 99.000 (98.885) +2022-11-14 13:53:13,463 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0908) Prec@1 91.000 (84.660) Prec@5 97.000 (98.866) +2022-11-14 13:53:13,473 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1168 (0.0911) Prec@1 80.000 (84.612) Prec@5 100.000 (98.878) +2022-11-14 13:53:13,484 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0911) Prec@1 82.000 (84.586) Prec@5 100.000 (98.889) +2022-11-14 13:53:13,498 Test: [99/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0912) Prec@1 83.000 (84.570) Prec@5 99.000 (98.890) +2022-11-14 13:53:13,576 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:53:13,892 Epoch: [111][0/500] Time 0.031 (0.031) Data 0.227 (0.227) Loss 0.0875 (0.0875) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:53:14,101 Epoch: [111][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0831 (0.0853) Prec@1 87.000 (86.500) Prec@5 99.000 (98.500) +2022-11-14 13:53:14,314 Epoch: [111][20/500] Time 0.017 (0.019) Data 0.001 (0.012) Loss 0.0820 (0.0842) Prec@1 86.000 (86.333) Prec@5 98.000 (98.333) +2022-11-14 13:53:14,524 Epoch: [111][30/500] Time 0.018 (0.019) Data 0.001 (0.009) Loss 0.0686 (0.0803) Prec@1 86.000 (86.250) Prec@5 100.000 (98.750) +2022-11-14 13:53:14,735 Epoch: [111][40/500] Time 0.022 (0.019) Data 0.001 (0.007) Loss 0.0534 (0.0749) Prec@1 91.000 (87.200) Prec@5 100.000 (99.000) +2022-11-14 13:53:15,130 Epoch: [111][50/500] Time 0.060 (0.022) Data 0.002 (0.006) Loss 0.0783 (0.0755) Prec@1 86.000 (87.000) Prec@5 100.000 (99.167) +2022-11-14 13:53:15,679 Epoch: [111][60/500] Time 0.053 (0.026) Data 0.002 (0.005) Loss 0.0478 (0.0715) Prec@1 92.000 (87.714) Prec@5 100.000 (99.286) +2022-11-14 13:53:16,135 Epoch: [111][70/500] Time 0.041 (0.028) Data 0.001 (0.005) Loss 0.0593 (0.0700) Prec@1 89.000 (87.875) Prec@5 100.000 (99.375) +2022-11-14 13:53:16,666 Epoch: [111][80/500] Time 0.051 (0.031) Data 0.002 (0.005) Loss 0.0468 (0.0674) Prec@1 92.000 (88.333) Prec@5 100.000 (99.444) +2022-11-14 13:53:17,148 Epoch: [111][90/500] Time 0.028 (0.032) Data 0.002 (0.004) Loss 0.0701 (0.0677) Prec@1 90.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 13:53:17,634 Epoch: [111][100/500] Time 0.069 (0.033) Data 0.002 (0.004) Loss 0.0446 (0.0656) Prec@1 93.000 (88.909) Prec@5 100.000 (99.545) +2022-11-14 13:53:18,045 Epoch: [111][110/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.1009 (0.0685) Prec@1 83.000 (88.417) Prec@5 99.000 (99.500) +2022-11-14 13:53:18,523 Epoch: [111][120/500] Time 0.039 (0.034) Data 0.002 (0.004) Loss 0.0598 (0.0679) Prec@1 88.000 (88.385) Prec@5 100.000 (99.538) +2022-11-14 13:53:18,942 Epoch: [111][130/500] Time 0.038 (0.034) Data 0.002 (0.004) Loss 0.0665 (0.0678) Prec@1 88.000 (88.357) Prec@5 99.000 (99.500) +2022-11-14 13:53:19,378 Epoch: [111][140/500] Time 0.050 (0.035) Data 0.002 (0.004) Loss 0.0652 (0.0676) Prec@1 90.000 (88.467) Prec@5 99.000 (99.467) +2022-11-14 13:53:19,788 Epoch: [111][150/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0548 (0.0668) Prec@1 92.000 (88.688) Prec@5 99.000 (99.438) +2022-11-14 13:53:20,213 Epoch: [111][160/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0885 (0.0681) Prec@1 85.000 (88.471) Prec@5 100.000 (99.471) +2022-11-14 13:53:20,652 Epoch: [111][170/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0859 (0.0691) Prec@1 85.000 (88.278) Prec@5 99.000 (99.444) +2022-11-14 13:53:21,077 Epoch: [111][180/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0501 (0.0681) Prec@1 92.000 (88.474) Prec@5 100.000 (99.474) +2022-11-14 13:53:21,506 Epoch: [111][190/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0704 (0.0682) Prec@1 88.000 (88.450) Prec@5 99.000 (99.450) +2022-11-14 13:53:21,942 Epoch: [111][200/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0547 (0.0675) Prec@1 93.000 (88.667) Prec@5 100.000 (99.476) +2022-11-14 13:53:22,395 Epoch: [111][210/500] Time 0.055 (0.036) Data 0.002 (0.003) Loss 0.0639 (0.0674) Prec@1 90.000 (88.727) Prec@5 97.000 (99.364) +2022-11-14 13:53:22,887 Epoch: [111][220/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0706 (0.0675) Prec@1 85.000 (88.565) Prec@5 99.000 (99.348) +2022-11-14 13:53:23,401 Epoch: [111][230/500] Time 0.054 (0.037) Data 0.002 (0.003) Loss 0.0799 (0.0680) Prec@1 88.000 (88.542) Prec@5 100.000 (99.375) +2022-11-14 13:53:23,929 Epoch: [111][240/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.0855 (0.0687) Prec@1 89.000 (88.560) Prec@5 98.000 (99.320) +2022-11-14 13:53:24,367 Epoch: [111][250/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0610 (0.0684) Prec@1 89.000 (88.577) Prec@5 99.000 (99.308) +2022-11-14 13:53:24,822 Epoch: [111][260/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0829 (0.0690) Prec@1 85.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 13:53:25,322 Epoch: [111][270/500] Time 0.069 (0.038) Data 0.002 (0.003) Loss 0.0727 (0.0691) Prec@1 87.000 (88.393) Prec@5 100.000 (99.357) +2022-11-14 13:53:25,762 Epoch: [111][280/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0652 (0.0690) Prec@1 86.000 (88.310) Prec@5 98.000 (99.310) +2022-11-14 13:53:26,184 Epoch: [111][290/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0803 (0.0693) Prec@1 88.000 (88.300) Prec@5 98.000 (99.267) +2022-11-14 13:53:26,609 Epoch: [111][300/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0741 (0.0695) Prec@1 87.000 (88.258) Prec@5 99.000 (99.258) +2022-11-14 13:53:27,058 Epoch: [111][310/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.1005 (0.0705) Prec@1 82.000 (88.062) Prec@5 99.000 (99.250) +2022-11-14 13:53:27,465 Epoch: [111][320/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0714 (0.0705) Prec@1 84.000 (87.939) Prec@5 99.000 (99.242) +2022-11-14 13:53:27,891 Epoch: [111][330/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0707 (0.0705) Prec@1 88.000 (87.941) Prec@5 99.000 (99.235) +2022-11-14 13:53:28,318 Epoch: [111][340/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0749 (0.0706) Prec@1 86.000 (87.886) Prec@5 99.000 (99.229) +2022-11-14 13:53:28,749 Epoch: [111][350/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0875 (0.0711) Prec@1 86.000 (87.833) Prec@5 100.000 (99.250) +2022-11-14 13:53:29,174 Epoch: [111][360/500] Time 0.042 (0.038) Data 0.001 (0.003) Loss 0.0590 (0.0708) Prec@1 89.000 (87.865) Prec@5 100.000 (99.270) +2022-11-14 13:53:29,647 Epoch: [111][370/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0743 (0.0709) Prec@1 88.000 (87.868) Prec@5 98.000 (99.237) +2022-11-14 13:53:30,179 Epoch: [111][380/500] Time 0.058 (0.038) Data 0.002 (0.003) Loss 0.0718 (0.0709) Prec@1 91.000 (87.949) Prec@5 98.000 (99.205) +2022-11-14 13:53:30,630 Epoch: [111][390/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0565 (0.0705) Prec@1 91.000 (88.025) Prec@5 99.000 (99.200) +2022-11-14 13:53:31,122 Epoch: [111][400/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0874 (0.0709) Prec@1 84.000 (87.927) Prec@5 100.000 (99.220) +2022-11-14 13:53:31,592 Epoch: [111][410/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0638 (0.0708) Prec@1 89.000 (87.952) Prec@5 100.000 (99.238) +2022-11-14 13:53:32,041 Epoch: [111][420/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0731 (0.0708) Prec@1 86.000 (87.907) Prec@5 100.000 (99.256) +2022-11-14 13:53:32,466 Epoch: [111][430/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0632 (0.0707) Prec@1 90.000 (87.955) Prec@5 100.000 (99.273) +2022-11-14 13:53:32,895 Epoch: [111][440/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0494 (0.0702) Prec@1 94.000 (88.089) Prec@5 100.000 (99.289) +2022-11-14 13:53:33,335 Epoch: [111][450/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0800 (0.0704) Prec@1 86.000 (88.043) Prec@5 99.000 (99.283) +2022-11-14 13:53:33,768 Epoch: [111][460/500] Time 0.050 (0.038) Data 0.003 (0.002) Loss 0.0667 (0.0703) Prec@1 90.000 (88.085) Prec@5 98.000 (99.255) +2022-11-14 13:53:34,198 Epoch: [111][470/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0618 (0.0701) Prec@1 90.000 (88.125) Prec@5 100.000 (99.271) +2022-11-14 13:53:34,634 Epoch: [111][480/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0816 (0.0704) Prec@1 87.000 (88.102) Prec@5 100.000 (99.286) +2022-11-14 13:53:35,059 Epoch: [111][490/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0630 (0.0702) Prec@1 92.000 (88.180) Prec@5 99.000 (99.280) +2022-11-14 13:53:35,450 Epoch: [111][499/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0743 (0.0703) Prec@1 87.000 (88.157) Prec@5 100.000 (99.294) +2022-11-14 13:53:35,743 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0720 (0.0720) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:53:35,753 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0620 (0.0670) Prec@1 91.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 13:53:35,763 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1058 (0.0799) Prec@1 83.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 13:53:35,775 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1011 (0.0852) Prec@1 84.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 13:53:35,784 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0577 (0.0797) Prec@1 90.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 13:53:35,793 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0738) Prec@1 92.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 13:53:35,804 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0724) Prec@1 89.000 (88.143) Prec@5 100.000 (99.714) +2022-11-14 13:53:35,814 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1309 (0.0797) Prec@1 78.000 (86.875) Prec@5 97.000 (99.375) +2022-11-14 13:53:35,821 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0819) Prec@1 80.000 (86.111) Prec@5 99.000 (99.333) +2022-11-14 13:53:35,830 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0826) Prec@1 82.000 (85.700) Prec@5 99.000 (99.300) +2022-11-14 13:53:35,842 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0829) Prec@1 86.000 (85.727) Prec@5 100.000 (99.364) +2022-11-14 13:53:35,852 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0842) Prec@1 86.000 (85.750) Prec@5 98.000 (99.250) +2022-11-14 13:53:35,862 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0843) Prec@1 84.000 (85.615) Prec@5 99.000 (99.231) +2022-11-14 13:53:35,870 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0840) Prec@1 87.000 (85.714) Prec@5 99.000 (99.214) +2022-11-14 13:53:35,880 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0842) Prec@1 84.000 (85.600) Prec@5 99.000 (99.200) +2022-11-14 13:53:35,891 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0846) Prec@1 86.000 (85.625) Prec@5 99.000 (99.188) +2022-11-14 13:53:35,900 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0831) Prec@1 92.000 (86.000) Prec@5 97.000 (99.059) +2022-11-14 13:53:35,910 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1206 (0.0852) Prec@1 82.000 (85.778) Prec@5 100.000 (99.111) +2022-11-14 13:53:35,921 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0855) Prec@1 85.000 (85.737) Prec@5 98.000 (99.053) +2022-11-14 13:53:35,931 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0863) Prec@1 81.000 (85.500) Prec@5 99.000 (99.050) +2022-11-14 13:53:35,939 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0866) Prec@1 82.000 (85.333) Prec@5 98.000 (99.000) +2022-11-14 13:53:35,948 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0875) Prec@1 83.000 (85.227) Prec@5 98.000 (98.955) +2022-11-14 13:53:35,958 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.0888) Prec@1 78.000 (84.913) Prec@5 98.000 (98.913) +2022-11-14 13:53:35,969 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0888) Prec@1 81.000 (84.750) Prec@5 100.000 (98.958) +2022-11-14 13:53:35,978 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0890) Prec@1 86.000 (84.800) Prec@5 98.000 (98.920) +2022-11-14 13:53:35,988 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0896) Prec@1 84.000 (84.769) Prec@5 99.000 (98.923) +2022-11-14 13:53:35,997 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0892) Prec@1 87.000 (84.852) Prec@5 100.000 (98.963) +2022-11-14 13:53:36,006 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0896) Prec@1 83.000 (84.786) Prec@5 99.000 (98.964) +2022-11-14 13:53:36,016 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0889) Prec@1 87.000 (84.862) Prec@5 98.000 (98.931) +2022-11-14 13:53:36,024 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0892) Prec@1 81.000 (84.733) Prec@5 99.000 (98.933) +2022-11-14 13:53:36,034 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0893) Prec@1 83.000 (84.677) Prec@5 99.000 (98.935) +2022-11-14 13:53:36,043 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0891) Prec@1 86.000 (84.719) Prec@5 100.000 (98.969) +2022-11-14 13:53:36,052 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0890) Prec@1 86.000 (84.758) Prec@5 98.000 (98.939) +2022-11-14 13:53:36,060 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.0901) Prec@1 80.000 (84.618) Prec@5 100.000 (98.971) +2022-11-14 13:53:36,069 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0901) Prec@1 84.000 (84.600) Prec@5 98.000 (98.943) +2022-11-14 13:53:36,078 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0896) Prec@1 89.000 (84.722) Prec@5 100.000 (98.972) +2022-11-14 13:53:36,088 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0897) Prec@1 83.000 (84.676) Prec@5 99.000 (98.973) +2022-11-14 13:53:36,098 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1329 (0.0908) Prec@1 77.000 (84.474) Prec@5 99.000 (98.974) +2022-11-14 13:53:36,109 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0905) Prec@1 88.000 (84.564) Prec@5 99.000 (98.974) +2022-11-14 13:53:36,119 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0901) Prec@1 89.000 (84.675) Prec@5 100.000 (99.000) +2022-11-14 13:53:36,127 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0903) Prec@1 84.000 (84.659) Prec@5 99.000 (99.000) +2022-11-14 13:53:36,136 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0904) Prec@1 84.000 (84.643) Prec@5 97.000 (98.952) +2022-11-14 13:53:36,147 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0895) Prec@1 92.000 (84.814) Prec@5 99.000 (98.953) +2022-11-14 13:53:36,155 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0892) Prec@1 89.000 (84.909) Prec@5 98.000 (98.932) +2022-11-14 13:53:36,164 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0896) Prec@1 81.000 (84.822) Prec@5 100.000 (98.956) +2022-11-14 13:53:36,175 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1233 (0.0904) Prec@1 77.000 (84.652) Prec@5 97.000 (98.913) +2022-11-14 13:53:36,184 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0900) Prec@1 87.000 (84.702) Prec@5 99.000 (98.915) +2022-11-14 13:53:36,194 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0903) Prec@1 82.000 (84.646) Prec@5 98.000 (98.896) +2022-11-14 13:53:36,203 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0901) Prec@1 86.000 (84.673) Prec@5 97.000 (98.857) +2022-11-14 13:53:36,213 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1395 (0.0911) Prec@1 74.000 (84.460) Prec@5 98.000 (98.840) +2022-11-14 13:53:36,223 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0912) Prec@1 83.000 (84.431) Prec@5 100.000 (98.863) +2022-11-14 13:53:36,231 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0914) Prec@1 82.000 (84.385) Prec@5 98.000 (98.846) +2022-11-14 13:53:36,241 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0914) Prec@1 85.000 (84.396) Prec@5 99.000 (98.849) +2022-11-14 13:53:36,251 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0917) Prec@1 82.000 (84.352) Prec@5 97.000 (98.815) +2022-11-14 13:53:36,260 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0918) Prec@1 84.000 (84.345) Prec@5 99.000 (98.818) +2022-11-14 13:53:36,269 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0919) Prec@1 84.000 (84.339) Prec@5 98.000 (98.804) +2022-11-14 13:53:36,279 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0918) Prec@1 88.000 (84.404) Prec@5 99.000 (98.807) +2022-11-14 13:53:36,289 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0913) Prec@1 90.000 (84.500) Prec@5 98.000 (98.793) +2022-11-14 13:53:36,299 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1546 (0.0924) Prec@1 72.000 (84.288) Prec@5 99.000 (98.797) +2022-11-14 13:53:36,308 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0924) Prec@1 81.000 (84.233) Prec@5 99.000 (98.800) +2022-11-14 13:53:36,317 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0924) Prec@1 86.000 (84.262) Prec@5 100.000 (98.820) +2022-11-14 13:53:36,327 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0923) Prec@1 84.000 (84.258) Prec@5 100.000 (98.839) +2022-11-14 13:53:36,336 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0920) Prec@1 88.000 (84.317) Prec@5 100.000 (98.857) +2022-11-14 13:53:36,345 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0918) Prec@1 88.000 (84.375) Prec@5 99.000 (98.859) +2022-11-14 13:53:36,356 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.0921) Prec@1 80.000 (84.308) Prec@5 100.000 (98.877) +2022-11-14 13:53:36,365 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0921) Prec@1 83.000 (84.288) Prec@5 100.000 (98.894) +2022-11-14 13:53:36,375 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0915) Prec@1 91.000 (84.388) Prec@5 100.000 (98.910) +2022-11-14 13:53:36,384 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0917) Prec@1 80.000 (84.324) Prec@5 99.000 (98.912) +2022-11-14 13:53:36,394 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0918) Prec@1 83.000 (84.304) Prec@5 100.000 (98.928) +2022-11-14 13:53:36,405 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0920) Prec@1 84.000 (84.300) Prec@5 99.000 (98.929) +2022-11-14 13:53:36,414 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0922) Prec@1 83.000 (84.282) Prec@5 98.000 (98.915) +2022-11-14 13:53:36,424 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0920) Prec@1 90.000 (84.361) Prec@5 99.000 (98.917) +2022-11-14 13:53:36,433 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0918) Prec@1 86.000 (84.384) Prec@5 100.000 (98.932) +2022-11-14 13:53:36,442 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0916) Prec@1 89.000 (84.446) Prec@5 100.000 (98.946) +2022-11-14 13:53:36,452 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0918) Prec@1 81.000 (84.400) Prec@5 99.000 (98.947) +2022-11-14 13:53:36,461 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0915) Prec@1 90.000 (84.474) Prec@5 100.000 (98.961) +2022-11-14 13:53:36,470 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0914) Prec@1 86.000 (84.494) Prec@5 99.000 (98.961) +2022-11-14 13:53:36,480 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0913) Prec@1 87.000 (84.526) Prec@5 98.000 (98.949) +2022-11-14 13:53:36,490 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0914) Prec@1 81.000 (84.481) Prec@5 99.000 (98.949) +2022-11-14 13:53:36,500 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0914) Prec@1 84.000 (84.475) Prec@5 100.000 (98.963) +2022-11-14 13:53:36,509 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0913) Prec@1 86.000 (84.494) Prec@5 99.000 (98.963) +2022-11-14 13:53:36,518 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0913) Prec@1 82.000 (84.463) Prec@5 100.000 (98.976) +2022-11-14 13:53:36,529 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0913) Prec@1 85.000 (84.470) Prec@5 99.000 (98.976) +2022-11-14 13:53:36,538 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0914) Prec@1 85.000 (84.476) Prec@5 100.000 (98.988) +2022-11-14 13:53:36,547 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0915) Prec@1 84.000 (84.471) Prec@5 98.000 (98.976) +2022-11-14 13:53:36,558 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0916) Prec@1 82.000 (84.442) Prec@5 98.000 (98.965) +2022-11-14 13:53:36,568 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0914) Prec@1 85.000 (84.448) Prec@5 99.000 (98.966) +2022-11-14 13:53:36,579 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0913) Prec@1 85.000 (84.455) Prec@5 97.000 (98.943) +2022-11-14 13:53:36,588 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0914) Prec@1 83.000 (84.438) Prec@5 98.000 (98.933) +2022-11-14 13:53:36,599 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0914) Prec@1 84.000 (84.433) Prec@5 98.000 (98.922) +2022-11-14 13:53:36,608 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0913) Prec@1 89.000 (84.484) Prec@5 100.000 (98.934) +2022-11-14 13:53:36,618 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0910) Prec@1 89.000 (84.533) Prec@5 100.000 (98.946) +2022-11-14 13:53:36,627 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0912) Prec@1 85.000 (84.538) Prec@5 96.000 (98.914) +2022-11-14 13:53:36,636 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0912) Prec@1 83.000 (84.521) Prec@5 97.000 (98.894) +2022-11-14 13:53:36,646 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0912) Prec@1 86.000 (84.537) Prec@5 100.000 (98.905) +2022-11-14 13:53:36,655 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0909) Prec@1 89.000 (84.583) Prec@5 100.000 (98.917) +2022-11-14 13:53:36,664 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0907) Prec@1 87.000 (84.608) Prec@5 99.000 (98.918) +2022-11-14 13:53:36,672 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0909) Prec@1 80.000 (84.561) Prec@5 98.000 (98.908) +2022-11-14 13:53:36,681 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0909) Prec@1 87.000 (84.586) Prec@5 99.000 (98.909) +2022-11-14 13:53:36,690 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0909) Prec@1 83.000 (84.570) Prec@5 100.000 (98.920) +2022-11-14 13:53:36,744 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:53:37,037 Epoch: [112][0/500] Time 0.025 (0.025) Data 0.211 (0.211) Loss 0.0902 (0.0902) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:53:37,239 Epoch: [112][10/500] Time 0.017 (0.018) Data 0.002 (0.021) Loss 0.0401 (0.0651) Prec@1 92.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 13:53:37,442 Epoch: [112][20/500] Time 0.018 (0.018) Data 0.002 (0.012) Loss 0.0908 (0.0737) Prec@1 82.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 13:53:37,657 Epoch: [112][30/500] Time 0.022 (0.018) Data 0.002 (0.008) Loss 0.0709 (0.0730) Prec@1 88.000 (86.500) Prec@5 100.000 (99.750) +2022-11-14 13:53:37,904 Epoch: [112][40/500] Time 0.023 (0.019) Data 0.001 (0.007) Loss 0.0684 (0.0721) Prec@1 88.000 (86.800) Prec@5 100.000 (99.800) +2022-11-14 13:53:38,144 Epoch: [112][50/500] Time 0.023 (0.019) Data 0.002 (0.006) Loss 0.0479 (0.0680) Prec@1 90.000 (87.333) Prec@5 100.000 (99.833) +2022-11-14 13:53:38,386 Epoch: [112][60/500] Time 0.023 (0.020) Data 0.001 (0.005) Loss 0.0777 (0.0694) Prec@1 88.000 (87.429) Prec@5 99.000 (99.714) +2022-11-14 13:53:38,630 Epoch: [112][70/500] Time 0.022 (0.020) Data 0.001 (0.005) Loss 0.0685 (0.0693) Prec@1 88.000 (87.500) Prec@5 98.000 (99.500) +2022-11-14 13:53:38,927 Epoch: [112][80/500] Time 0.035 (0.021) Data 0.002 (0.004) Loss 0.0646 (0.0688) Prec@1 89.000 (87.667) Prec@5 98.000 (99.333) +2022-11-14 13:53:39,311 Epoch: [112][90/500] Time 0.034 (0.022) Data 0.002 (0.004) Loss 0.0572 (0.0676) Prec@1 93.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 13:53:39,692 Epoch: [112][100/500] Time 0.035 (0.023) Data 0.002 (0.004) Loss 0.0804 (0.0688) Prec@1 87.000 (88.091) Prec@5 98.000 (99.182) +2022-11-14 13:53:40,074 Epoch: [112][110/500] Time 0.034 (0.024) Data 0.003 (0.004) Loss 0.0685 (0.0688) Prec@1 88.000 (88.083) Prec@5 99.000 (99.167) +2022-11-14 13:53:40,457 Epoch: [112][120/500] Time 0.035 (0.025) Data 0.002 (0.003) Loss 0.0729 (0.0691) Prec@1 86.000 (87.923) Prec@5 100.000 (99.231) +2022-11-14 13:53:40,833 Epoch: [112][130/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0678 (0.0690) Prec@1 89.000 (88.000) Prec@5 98.000 (99.143) +2022-11-14 13:53:41,218 Epoch: [112][140/500] Time 0.036 (0.026) Data 0.002 (0.003) Loss 0.0527 (0.0679) Prec@1 92.000 (88.267) Prec@5 100.000 (99.200) +2022-11-14 13:53:41,603 Epoch: [112][150/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0331 (0.0657) Prec@1 95.000 (88.688) Prec@5 100.000 (99.250) +2022-11-14 13:53:41,981 Epoch: [112][160/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0805 (0.0666) Prec@1 86.000 (88.529) Prec@5 99.000 (99.235) +2022-11-14 13:53:42,368 Epoch: [112][170/500] Time 0.035 (0.028) Data 0.002 (0.003) Loss 0.0630 (0.0664) Prec@1 89.000 (88.556) Prec@5 100.000 (99.278) +2022-11-14 13:53:42,760 Epoch: [112][180/500] Time 0.046 (0.028) Data 0.002 (0.003) Loss 0.0807 (0.0671) Prec@1 86.000 (88.421) Prec@5 98.000 (99.211) +2022-11-14 13:53:43,135 Epoch: [112][190/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.0958 (0.0686) Prec@1 81.000 (88.050) Prec@5 100.000 (99.250) +2022-11-14 13:53:43,524 Epoch: [112][200/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0739 (0.0688) Prec@1 85.000 (87.905) Prec@5 99.000 (99.238) +2022-11-14 13:53:43,905 Epoch: [112][210/500] Time 0.038 (0.029) Data 0.002 (0.003) Loss 0.0636 (0.0686) Prec@1 87.000 (87.864) Prec@5 100.000 (99.273) +2022-11-14 13:53:44,284 Epoch: [112][220/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0751 (0.0689) Prec@1 87.000 (87.826) Prec@5 99.000 (99.261) +2022-11-14 13:53:44,662 Epoch: [112][230/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0585 (0.0684) Prec@1 90.000 (87.917) Prec@5 100.000 (99.292) +2022-11-14 13:53:45,039 Epoch: [112][240/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0572 (0.0680) Prec@1 89.000 (87.960) Prec@5 100.000 (99.320) +2022-11-14 13:53:45,425 Epoch: [112][250/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0560 (0.0675) Prec@1 91.000 (88.077) Prec@5 100.000 (99.346) +2022-11-14 13:53:45,811 Epoch: [112][260/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0814 (0.0680) Prec@1 86.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 13:53:46,189 Epoch: [112][270/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0826 (0.0686) Prec@1 89.000 (88.036) Prec@5 99.000 (99.321) +2022-11-14 13:53:46,573 Epoch: [112][280/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0732 (0.0687) Prec@1 88.000 (88.034) Prec@5 100.000 (99.345) +2022-11-14 13:53:46,957 Epoch: [112][290/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0807 (0.0691) Prec@1 86.000 (87.967) Prec@5 100.000 (99.367) +2022-11-14 13:53:47,328 Epoch: [112][300/500] Time 0.035 (0.030) Data 0.002 (0.002) Loss 0.0633 (0.0689) Prec@1 90.000 (88.032) Prec@5 100.000 (99.387) +2022-11-14 13:53:47,713 Epoch: [112][310/500] Time 0.037 (0.030) Data 0.001 (0.002) Loss 0.0607 (0.0687) Prec@1 89.000 (88.062) Prec@5 100.000 (99.406) +2022-11-14 13:53:48,099 Epoch: [112][320/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0954 (0.0695) Prec@1 83.000 (87.909) Prec@5 100.000 (99.424) +2022-11-14 13:53:48,478 Epoch: [112][330/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0922 (0.0702) Prec@1 85.000 (87.824) Prec@5 99.000 (99.412) +2022-11-14 13:53:48,861 Epoch: [112][340/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0979 (0.0710) Prec@1 84.000 (87.714) Prec@5 98.000 (99.371) +2022-11-14 13:53:49,236 Epoch: [112][350/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0689 (0.0709) Prec@1 88.000 (87.722) Prec@5 100.000 (99.389) +2022-11-14 13:53:49,613 Epoch: [112][360/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0847 (0.0713) Prec@1 87.000 (87.703) Prec@5 99.000 (99.378) +2022-11-14 13:53:49,995 Epoch: [112][370/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0836 (0.0716) Prec@1 84.000 (87.605) Prec@5 98.000 (99.342) +2022-11-14 13:53:50,373 Epoch: [112][380/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0571 (0.0712) Prec@1 88.000 (87.615) Prec@5 99.000 (99.333) +2022-11-14 13:53:50,750 Epoch: [112][390/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0888 (0.0717) Prec@1 84.000 (87.525) Prec@5 99.000 (99.325) +2022-11-14 13:53:51,139 Epoch: [112][400/500] Time 0.041 (0.031) Data 0.002 (0.002) Loss 0.1085 (0.0726) Prec@1 83.000 (87.415) Prec@5 98.000 (99.293) +2022-11-14 13:53:51,519 Epoch: [112][410/500] Time 0.038 (0.031) Data 0.002 (0.002) Loss 0.0584 (0.0722) Prec@1 90.000 (87.476) Prec@5 99.000 (99.286) +2022-11-14 13:53:51,905 Epoch: [112][420/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0709 (0.0722) Prec@1 88.000 (87.488) Prec@5 100.000 (99.302) +2022-11-14 13:53:52,295 Epoch: [112][430/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0498 (0.0717) Prec@1 92.000 (87.591) Prec@5 99.000 (99.295) +2022-11-14 13:53:52,673 Epoch: [112][440/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0508 (0.0712) Prec@1 92.000 (87.689) Prec@5 100.000 (99.311) +2022-11-14 13:53:53,056 Epoch: [112][450/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0692 (0.0712) Prec@1 88.000 (87.696) Prec@5 100.000 (99.326) +2022-11-14 13:53:53,435 Epoch: [112][460/500] Time 0.037 (0.032) Data 0.002 (0.002) Loss 0.0558 (0.0708) Prec@1 92.000 (87.787) Prec@5 99.000 (99.319) +2022-11-14 13:53:53,811 Epoch: [112][470/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0797 (0.0710) Prec@1 87.000 (87.771) Prec@5 100.000 (99.333) +2022-11-14 13:53:54,196 Epoch: [112][480/500] Time 0.034 (0.032) Data 0.001 (0.002) Loss 0.0669 (0.0709) Prec@1 90.000 (87.816) Prec@5 99.000 (99.327) +2022-11-14 13:53:54,569 Epoch: [112][490/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0729 (0.0710) Prec@1 90.000 (87.860) Prec@5 98.000 (99.300) +2022-11-14 13:53:54,922 Epoch: [112][499/500] Time 0.036 (0.032) Data 0.001 (0.002) Loss 0.0491 (0.0706) Prec@1 90.000 (87.902) Prec@5 100.000 (99.314) +2022-11-14 13:53:55,200 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0732 (0.0732) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:53:55,208 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0752) Prec@1 87.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 13:53:55,218 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0827) Prec@1 83.000 (85.667) Prec@5 99.000 (99.333) +2022-11-14 13:53:55,229 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0871) Prec@1 85.000 (85.500) Prec@5 100.000 (99.500) +2022-11-14 13:53:55,237 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0896) Prec@1 83.000 (85.000) Prec@5 98.000 (99.200) +2022-11-14 13:53:55,245 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0851) Prec@1 88.000 (85.500) Prec@5 99.000 (99.167) +2022-11-14 13:53:55,253 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0834) Prec@1 88.000 (85.857) Prec@5 100.000 (99.286) +2022-11-14 13:53:55,264 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0857) Prec@1 81.000 (85.250) Prec@5 98.000 (99.125) +2022-11-14 13:53:55,271 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0873) Prec@1 85.000 (85.222) Prec@5 97.000 (98.889) +2022-11-14 13:53:55,280 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0857) Prec@1 87.000 (85.400) Prec@5 99.000 (98.900) +2022-11-14 13:53:55,289 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0844) Prec@1 88.000 (85.636) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,298 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0838) Prec@1 87.000 (85.750) Prec@5 100.000 (99.083) +2022-11-14 13:53:55,307 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0831) Prec@1 88.000 (85.923) Prec@5 99.000 (99.077) +2022-11-14 13:53:55,316 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0840) Prec@1 85.000 (85.857) Prec@5 100.000 (99.143) +2022-11-14 13:53:55,326 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0840) Prec@1 86.000 (85.867) Prec@5 99.000 (99.133) +2022-11-14 13:53:55,335 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1448 (0.0878) Prec@1 74.000 (85.125) Prec@5 97.000 (99.000) +2022-11-14 13:53:55,343 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0872) Prec@1 87.000 (85.235) Prec@5 98.000 (98.941) +2022-11-14 13:53:55,353 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0880) Prec@1 82.000 (85.056) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,362 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1250 (0.0899) Prec@1 79.000 (84.737) Prec@5 99.000 (99.000) +2022-11-14 13:53:55,371 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1144 (0.0911) Prec@1 78.000 (84.400) Prec@5 99.000 (99.000) +2022-11-14 13:53:55,381 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0913) Prec@1 85.000 (84.429) Prec@5 99.000 (99.000) +2022-11-14 13:53:55,390 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0914) Prec@1 83.000 (84.364) Prec@5 98.000 (98.955) +2022-11-14 13:53:55,399 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1261 (0.0929) Prec@1 78.000 (84.087) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,407 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0928) Prec@1 84.000 (84.083) Prec@5 100.000 (99.042) +2022-11-14 13:53:55,417 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0925) Prec@1 86.000 (84.160) Prec@5 100.000 (99.080) +2022-11-14 13:53:55,425 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0929) Prec@1 84.000 (84.154) Prec@5 98.000 (99.038) +2022-11-14 13:53:55,434 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0916) Prec@1 91.000 (84.407) Prec@5 99.000 (99.037) +2022-11-14 13:53:55,444 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0918) Prec@1 83.000 (84.357) Prec@5 98.000 (99.000) +2022-11-14 13:53:55,455 Test: [28/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0919) Prec@1 84.000 (84.345) Prec@5 97.000 (98.931) +2022-11-14 13:53:55,465 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0920) Prec@1 83.000 (84.300) Prec@5 99.000 (98.933) +2022-11-14 13:53:55,473 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0917) Prec@1 85.000 (84.323) Prec@5 100.000 (98.968) +2022-11-14 13:53:55,482 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0914) Prec@1 87.000 (84.406) Prec@5 99.000 (98.969) +2022-11-14 13:53:55,493 Test: [32/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0913) Prec@1 84.000 (84.394) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,503 Test: [33/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0916) Prec@1 84.000 (84.382) Prec@5 98.000 (98.971) +2022-11-14 13:53:55,512 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0917) Prec@1 83.000 (84.343) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,522 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0915) Prec@1 86.000 (84.389) Prec@5 99.000 (99.000) +2022-11-14 13:53:55,531 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0914) Prec@1 85.000 (84.405) Prec@5 97.000 (98.946) +2022-11-14 13:53:55,539 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1169 (0.0921) Prec@1 78.000 (84.237) Prec@5 99.000 (98.947) +2022-11-14 13:53:55,549 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0914) Prec@1 90.000 (84.385) Prec@5 100.000 (98.974) +2022-11-14 13:53:55,557 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0913) Prec@1 86.000 (84.425) Prec@5 100.000 (99.000) +2022-11-14 13:53:55,565 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0916) Prec@1 85.000 (84.439) Prec@5 97.000 (98.951) +2022-11-14 13:53:55,573 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0916) Prec@1 85.000 (84.452) Prec@5 98.000 (98.929) +2022-11-14 13:53:55,581 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0910) Prec@1 91.000 (84.605) Prec@5 100.000 (98.953) +2022-11-14 13:53:55,590 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0910) Prec@1 83.000 (84.568) Prec@5 96.000 (98.886) +2022-11-14 13:53:55,599 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0912) Prec@1 84.000 (84.556) Prec@5 98.000 (98.867) +2022-11-14 13:53:55,608 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0912) Prec@1 82.000 (84.500) Prec@5 100.000 (98.891) +2022-11-14 13:53:55,618 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0912) Prec@1 84.000 (84.489) Prec@5 99.000 (98.894) +2022-11-14 13:53:55,627 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0916) Prec@1 82.000 (84.438) Prec@5 99.000 (98.896) +2022-11-14 13:53:55,635 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0915) Prec@1 84.000 (84.429) Prec@5 99.000 (98.898) +2022-11-14 13:53:55,645 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1428 (0.0925) Prec@1 76.000 (84.260) Prec@5 98.000 (98.880) +2022-11-14 13:53:55,654 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0922) Prec@1 87.000 (84.314) Prec@5 100.000 (98.902) +2022-11-14 13:53:55,663 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0923) Prec@1 84.000 (84.308) Prec@5 98.000 (98.885) +2022-11-14 13:53:55,673 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0924) Prec@1 80.000 (84.226) Prec@5 100.000 (98.906) +2022-11-14 13:53:55,682 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0926) Prec@1 82.000 (84.185) Prec@5 98.000 (98.889) +2022-11-14 13:53:55,691 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0929) Prec@1 80.000 (84.109) Prec@5 99.000 (98.891) +2022-11-14 13:53:55,701 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0927) Prec@1 88.000 (84.179) Prec@5 99.000 (98.893) +2022-11-14 13:53:55,710 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.0930) Prec@1 79.000 (84.088) Prec@5 99.000 (98.895) +2022-11-14 13:53:55,719 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0931) Prec@1 85.000 (84.103) Prec@5 100.000 (98.914) +2022-11-14 13:53:55,729 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1265 (0.0936) Prec@1 74.000 (83.932) Prec@5 100.000 (98.932) +2022-11-14 13:53:55,738 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.0940) Prec@1 81.000 (83.883) Prec@5 97.000 (98.900) +2022-11-14 13:53:55,746 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0939) Prec@1 83.000 (83.869) Prec@5 98.000 (98.885) +2022-11-14 13:53:55,756 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0941) Prec@1 80.000 (83.806) Prec@5 99.000 (98.887) +2022-11-14 13:53:55,765 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0939) Prec@1 89.000 (83.889) Prec@5 99.000 (98.889) +2022-11-14 13:53:55,774 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0935) Prec@1 87.000 (83.938) Prec@5 100.000 (98.906) +2022-11-14 13:53:55,783 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1288 (0.0940) Prec@1 79.000 (83.862) Prec@5 99.000 (98.908) +2022-11-14 13:53:55,793 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0942) Prec@1 82.000 (83.833) Prec@5 99.000 (98.909) +2022-11-14 13:53:55,802 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0937) Prec@1 90.000 (83.925) Prec@5 99.000 (98.910) +2022-11-14 13:53:55,811 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0940) Prec@1 81.000 (83.882) Prec@5 99.000 (98.912) +2022-11-14 13:53:55,821 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0938) Prec@1 85.000 (83.899) Prec@5 100.000 (98.928) +2022-11-14 13:53:55,830 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0938) Prec@1 83.000 (83.886) Prec@5 99.000 (98.929) +2022-11-14 13:53:55,840 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0939) Prec@1 85.000 (83.901) Prec@5 99.000 (98.930) +2022-11-14 13:53:55,849 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0934) Prec@1 90.000 (83.986) Prec@5 100.000 (98.944) +2022-11-14 13:53:55,857 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0931) Prec@1 85.000 (84.000) Prec@5 99.000 (98.945) +2022-11-14 13:53:55,867 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0930) Prec@1 85.000 (84.014) Prec@5 100.000 (98.959) +2022-11-14 13:53:55,877 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1166 (0.0933) Prec@1 80.000 (83.960) Prec@5 98.000 (98.947) +2022-11-14 13:53:55,888 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0928) Prec@1 92.000 (84.066) Prec@5 98.000 (98.934) +2022-11-14 13:53:55,900 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0927) Prec@1 86.000 (84.091) Prec@5 100.000 (98.948) +2022-11-14 13:53:55,913 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0930) Prec@1 81.000 (84.051) Prec@5 97.000 (98.923) +2022-11-14 13:53:55,924 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0930) Prec@1 83.000 (84.038) Prec@5 100.000 (98.937) +2022-11-14 13:53:55,934 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0930) Prec@1 81.000 (84.000) Prec@5 100.000 (98.950) +2022-11-14 13:53:55,944 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0928) Prec@1 84.000 (84.000) Prec@5 98.000 (98.938) +2022-11-14 13:53:55,953 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0929) Prec@1 84.000 (84.000) Prec@5 98.000 (98.927) +2022-11-14 13:53:55,962 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1112 (0.0931) Prec@1 80.000 (83.952) Prec@5 100.000 (98.940) +2022-11-14 13:53:55,971 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0929) Prec@1 87.000 (83.988) Prec@5 99.000 (98.940) +2022-11-14 13:53:55,980 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1214 (0.0932) Prec@1 77.000 (83.906) Prec@5 98.000 (98.929) +2022-11-14 13:53:55,989 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0933) Prec@1 84.000 (83.907) Prec@5 100.000 (98.942) +2022-11-14 13:53:55,998 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0933) Prec@1 82.000 (83.885) Prec@5 99.000 (98.943) +2022-11-14 13:53:56,007 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0934) Prec@1 87.000 (83.920) Prec@5 98.000 (98.932) +2022-11-14 13:53:56,015 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0930) Prec@1 87.000 (83.955) Prec@5 98.000 (98.921) +2022-11-14 13:53:56,024 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0929) Prec@1 86.000 (83.978) Prec@5 97.000 (98.900) +2022-11-14 13:53:56,034 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0928) Prec@1 85.000 (83.989) Prec@5 100.000 (98.912) +2022-11-14 13:53:56,043 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0925) Prec@1 84.000 (83.989) Prec@5 99.000 (98.913) +2022-11-14 13:53:56,052 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1176 (0.0927) Prec@1 81.000 (83.957) Prec@5 98.000 (98.903) +2022-11-14 13:53:56,061 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0928) Prec@1 85.000 (83.968) Prec@5 99.000 (98.904) +2022-11-14 13:53:56,071 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0928) Prec@1 86.000 (83.989) Prec@5 99.000 (98.905) +2022-11-14 13:53:56,080 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0926) Prec@1 89.000 (84.042) Prec@5 98.000 (98.896) +2022-11-14 13:53:56,089 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0924) Prec@1 85.000 (84.052) Prec@5 100.000 (98.907) +2022-11-14 13:53:56,098 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1259 (0.0927) Prec@1 80.000 (84.010) Prec@5 99.000 (98.908) +2022-11-14 13:53:56,107 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0929) Prec@1 82.000 (83.990) Prec@5 98.000 (98.899) +2022-11-14 13:53:56,117 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0930) Prec@1 84.000 (83.990) Prec@5 98.000 (98.890) +2022-11-14 13:53:56,177 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:53:56,480 Epoch: [113][0/500] Time 0.023 (0.023) Data 0.219 (0.219) Loss 0.0720 (0.0720) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:53:56,681 Epoch: [113][10/500] Time 0.018 (0.018) Data 0.002 (0.021) Loss 0.0643 (0.0682) Prec@1 92.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 13:53:56,908 Epoch: [113][20/500] Time 0.027 (0.019) Data 0.002 (0.012) Loss 0.0741 (0.0701) Prec@1 87.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 13:53:57,186 Epoch: [113][30/500] Time 0.027 (0.021) Data 0.001 (0.009) Loss 0.0612 (0.0679) Prec@1 90.000 (89.000) Prec@5 100.000 (99.750) +2022-11-14 13:53:57,461 Epoch: [113][40/500] Time 0.023 (0.021) Data 0.002 (0.007) Loss 0.0458 (0.0635) Prec@1 94.000 (90.000) Prec@5 100.000 (99.800) +2022-11-14 13:53:57,732 Epoch: [113][50/500] Time 0.024 (0.022) Data 0.002 (0.006) Loss 0.0836 (0.0668) Prec@1 87.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 13:53:58,020 Epoch: [113][60/500] Time 0.028 (0.022) Data 0.001 (0.005) Loss 0.0576 (0.0655) Prec@1 91.000 (89.714) Prec@5 99.000 (99.429) +2022-11-14 13:53:58,509 Epoch: [113][70/500] Time 0.045 (0.025) Data 0.002 (0.005) Loss 0.0897 (0.0685) Prec@1 82.000 (88.750) Prec@5 99.000 (99.375) +2022-11-14 13:53:59,013 Epoch: [113][80/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.1206 (0.0743) Prec@1 77.000 (87.444) Prec@5 99.000 (99.333) +2022-11-14 13:53:59,497 Epoch: [113][90/500] Time 0.052 (0.029) Data 0.002 (0.004) Loss 0.0931 (0.0762) Prec@1 85.000 (87.200) Prec@5 98.000 (99.200) +2022-11-14 13:53:59,985 Epoch: [113][100/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0415 (0.0730) Prec@1 94.000 (87.818) Prec@5 99.000 (99.182) +2022-11-14 13:54:00,498 Epoch: [113][110/500] Time 0.057 (0.032) Data 0.002 (0.004) Loss 0.0752 (0.0732) Prec@1 87.000 (87.750) Prec@5 100.000 (99.250) +2022-11-14 13:54:00,992 Epoch: [113][120/500] Time 0.051 (0.033) Data 0.002 (0.004) Loss 0.0695 (0.0729) Prec@1 89.000 (87.846) Prec@5 98.000 (99.154) +2022-11-14 13:54:01,478 Epoch: [113][130/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0667 (0.0725) Prec@1 89.000 (87.929) Prec@5 99.000 (99.143) +2022-11-14 13:54:01,966 Epoch: [113][140/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.1112 (0.0751) Prec@1 81.000 (87.467) Prec@5 98.000 (99.067) +2022-11-14 13:54:02,437 Epoch: [113][150/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0458 (0.0732) Prec@1 92.000 (87.750) Prec@5 100.000 (99.125) +2022-11-14 13:54:02,919 Epoch: [113][160/500] Time 0.052 (0.036) Data 0.002 (0.003) Loss 0.0689 (0.0730) Prec@1 87.000 (87.706) Prec@5 99.000 (99.118) +2022-11-14 13:54:03,415 Epoch: [113][170/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0579 (0.0721) Prec@1 87.000 (87.667) Prec@5 99.000 (99.111) +2022-11-14 13:54:03,904 Epoch: [113][180/500] Time 0.053 (0.036) Data 0.001 (0.003) Loss 0.0608 (0.0716) Prec@1 90.000 (87.789) Prec@5 100.000 (99.158) +2022-11-14 13:54:04,416 Epoch: [113][190/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.1027 (0.0731) Prec@1 83.000 (87.550) Prec@5 100.000 (99.200) +2022-11-14 13:54:04,910 Epoch: [113][200/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0776 (0.0733) Prec@1 87.000 (87.524) Prec@5 99.000 (99.190) +2022-11-14 13:54:05,398 Epoch: [113][210/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0447 (0.0720) Prec@1 93.000 (87.773) Prec@5 100.000 (99.227) +2022-11-14 13:54:05,886 Epoch: [113][220/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0517 (0.0711) Prec@1 92.000 (87.957) Prec@5 100.000 (99.261) +2022-11-14 13:54:06,365 Epoch: [113][230/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0523 (0.0704) Prec@1 92.000 (88.125) Prec@5 100.000 (99.292) +2022-11-14 13:54:06,849 Epoch: [113][240/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0618 (0.0700) Prec@1 84.000 (87.960) Prec@5 100.000 (99.320) +2022-11-14 13:54:07,319 Epoch: [113][250/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0405 (0.0689) Prec@1 93.000 (88.154) Prec@5 100.000 (99.346) +2022-11-14 13:54:07,825 Epoch: [113][260/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0780 (0.0692) Prec@1 86.000 (88.074) Prec@5 99.000 (99.333) +2022-11-14 13:54:08,288 Epoch: [113][270/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0672 (0.0691) Prec@1 88.000 (88.071) Prec@5 100.000 (99.357) +2022-11-14 13:54:08,754 Epoch: [113][280/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0901 (0.0699) Prec@1 85.000 (87.966) Prec@5 98.000 (99.310) +2022-11-14 13:54:09,240 Epoch: [113][290/500] Time 0.044 (0.039) Data 0.001 (0.003) Loss 0.0681 (0.0698) Prec@1 87.000 (87.933) Prec@5 99.000 (99.300) +2022-11-14 13:54:09,706 Epoch: [113][300/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0759 (0.0700) Prec@1 86.000 (87.871) Prec@5 99.000 (99.290) +2022-11-14 13:54:10,176 Epoch: [113][310/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0727 (0.0701) Prec@1 87.000 (87.844) Prec@5 99.000 (99.281) +2022-11-14 13:54:10,673 Epoch: [113][320/500] Time 0.060 (0.039) Data 0.002 (0.003) Loss 0.0637 (0.0699) Prec@1 90.000 (87.909) Prec@5 100.000 (99.303) +2022-11-14 13:54:11,165 Epoch: [113][330/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0441 (0.0691) Prec@1 91.000 (88.000) Prec@5 100.000 (99.324) +2022-11-14 13:54:11,556 Epoch: [113][340/500] Time 0.027 (0.039) Data 0.001 (0.002) Loss 0.0523 (0.0687) Prec@1 91.000 (88.086) Prec@5 100.000 (99.343) +2022-11-14 13:54:11,865 Epoch: [113][350/500] Time 0.034 (0.039) Data 0.002 (0.002) Loss 0.0721 (0.0687) Prec@1 91.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 13:54:12,174 Epoch: [113][360/500] Time 0.032 (0.039) Data 0.002 (0.002) Loss 0.0438 (0.0681) Prec@1 95.000 (88.351) Prec@5 100.000 (99.351) +2022-11-14 13:54:12,476 Epoch: [113][370/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0937 (0.0687) Prec@1 86.000 (88.289) Prec@5 99.000 (99.342) +2022-11-14 13:54:12,780 Epoch: [113][380/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0848 (0.0692) Prec@1 86.000 (88.231) Prec@5 99.000 (99.333) +2022-11-14 13:54:13,089 Epoch: [113][390/500] Time 0.028 (0.038) Data 0.002 (0.002) Loss 0.0563 (0.0688) Prec@1 92.000 (88.325) Prec@5 99.000 (99.325) +2022-11-14 13:54:13,396 Epoch: [113][400/500] Time 0.029 (0.038) Data 0.001 (0.002) Loss 0.0552 (0.0685) Prec@1 91.000 (88.390) Prec@5 99.000 (99.317) +2022-11-14 13:54:13,709 Epoch: [113][410/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0651 (0.0684) Prec@1 90.000 (88.429) Prec@5 99.000 (99.310) +2022-11-14 13:54:14,018 Epoch: [113][420/500] Time 0.028 (0.037) Data 0.002 (0.002) Loss 0.0819 (0.0687) Prec@1 85.000 (88.349) Prec@5 100.000 (99.326) +2022-11-14 13:54:14,327 Epoch: [113][430/500] Time 0.029 (0.037) Data 0.002 (0.002) Loss 0.0757 (0.0689) Prec@1 86.000 (88.295) Prec@5 99.000 (99.318) +2022-11-14 13:54:14,632 Epoch: [113][440/500] Time 0.030 (0.037) Data 0.001 (0.002) Loss 0.0605 (0.0687) Prec@1 90.000 (88.333) Prec@5 99.000 (99.311) +2022-11-14 13:54:14,938 Epoch: [113][450/500] Time 0.030 (0.036) Data 0.001 (0.002) Loss 0.0637 (0.0686) Prec@1 90.000 (88.370) Prec@5 98.000 (99.283) +2022-11-14 13:54:15,253 Epoch: [113][460/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0572 (0.0684) Prec@1 90.000 (88.404) Prec@5 100.000 (99.298) +2022-11-14 13:54:15,576 Epoch: [113][470/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0850 (0.0687) Prec@1 86.000 (88.354) Prec@5 97.000 (99.250) +2022-11-14 13:54:15,883 Epoch: [113][480/500] Time 0.026 (0.036) Data 0.003 (0.002) Loss 0.0731 (0.0688) Prec@1 86.000 (88.306) Prec@5 100.000 (99.265) +2022-11-14 13:54:16,196 Epoch: [113][490/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0514 (0.0684) Prec@1 91.000 (88.360) Prec@5 100.000 (99.280) +2022-11-14 13:54:16,478 Epoch: [113][499/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0831 (0.0687) Prec@1 86.000 (88.314) Prec@5 100.000 (99.294) +2022-11-14 13:54:16,759 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0748 (0.0748) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 13:54:16,767 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0847) Prec@1 82.000 (84.000) Prec@5 99.000 (99.500) +2022-11-14 13:54:16,777 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0876) Prec@1 82.000 (83.333) Prec@5 99.000 (99.333) +2022-11-14 13:54:16,788 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0915) Prec@1 83.000 (83.250) Prec@5 100.000 (99.500) +2022-11-14 13:54:16,796 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0949) Prec@1 81.000 (82.800) Prec@5 99.000 (99.400) +2022-11-14 13:54:16,804 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0891) Prec@1 88.000 (83.667) Prec@5 100.000 (99.500) +2022-11-14 13:54:16,813 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0857) Prec@1 92.000 (84.857) Prec@5 100.000 (99.571) +2022-11-14 13:54:16,824 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0895) Prec@1 78.000 (84.000) Prec@5 99.000 (99.500) +2022-11-14 13:54:16,832 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0914) Prec@1 84.000 (84.000) Prec@5 99.000 (99.444) +2022-11-14 13:54:16,841 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0897) Prec@1 84.000 (84.000) Prec@5 99.000 (99.400) +2022-11-14 13:54:16,850 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0888) Prec@1 85.000 (84.091) Prec@5 100.000 (99.455) +2022-11-14 13:54:16,860 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0889) Prec@1 85.000 (84.167) Prec@5 100.000 (99.500) +2022-11-14 13:54:16,869 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0881) Prec@1 86.000 (84.308) Prec@5 100.000 (99.538) +2022-11-14 13:54:16,878 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0878) Prec@1 85.000 (84.357) Prec@5 98.000 (99.429) +2022-11-14 13:54:16,888 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0872) Prec@1 87.000 (84.533) Prec@5 98.000 (99.333) +2022-11-14 13:54:16,896 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0877) Prec@1 81.000 (84.312) Prec@5 99.000 (99.312) +2022-11-14 13:54:16,905 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0873) Prec@1 88.000 (84.529) Prec@5 98.000 (99.235) +2022-11-14 13:54:16,915 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.0891) Prec@1 80.000 (84.278) Prec@5 99.000 (99.222) +2022-11-14 13:54:16,923 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0894) Prec@1 83.000 (84.211) Prec@5 99.000 (99.211) +2022-11-14 13:54:16,931 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0901) Prec@1 83.000 (84.150) Prec@5 98.000 (99.150) +2022-11-14 13:54:16,940 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0904) Prec@1 82.000 (84.048) Prec@5 99.000 (99.143) +2022-11-14 13:54:16,950 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0908) Prec@1 83.000 (84.000) Prec@5 100.000 (99.182) +2022-11-14 13:54:16,959 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0907) Prec@1 85.000 (84.043) Prec@5 100.000 (99.217) +2022-11-14 13:54:16,969 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0896) Prec@1 88.000 (84.208) Prec@5 100.000 (99.250) +2022-11-14 13:54:16,979 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0903) Prec@1 84.000 (84.200) Prec@5 99.000 (99.240) +2022-11-14 13:54:16,987 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0912) Prec@1 82.000 (84.115) Prec@5 98.000 (99.192) +2022-11-14 13:54:16,997 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0902) Prec@1 89.000 (84.296) Prec@5 100.000 (99.222) +2022-11-14 13:54:17,007 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0898) Prec@1 87.000 (84.393) Prec@5 99.000 (99.214) +2022-11-14 13:54:17,015 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0892) Prec@1 89.000 (84.552) Prec@5 97.000 (99.138) +2022-11-14 13:54:17,024 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0896) Prec@1 84.000 (84.533) Prec@5 99.000 (99.133) +2022-11-14 13:54:17,033 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0896) Prec@1 82.000 (84.452) Prec@5 99.000 (99.129) +2022-11-14 13:54:17,043 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0896) Prec@1 83.000 (84.406) Prec@5 100.000 (99.156) +2022-11-14 13:54:17,052 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0900) Prec@1 84.000 (84.394) Prec@5 98.000 (99.121) +2022-11-14 13:54:17,062 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0907) Prec@1 80.000 (84.265) Prec@5 99.000 (99.118) +2022-11-14 13:54:17,071 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0909) Prec@1 85.000 (84.286) Prec@5 100.000 (99.143) +2022-11-14 13:54:17,081 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0911) Prec@1 87.000 (84.361) Prec@5 99.000 (99.139) +2022-11-14 13:54:17,091 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0913) Prec@1 84.000 (84.351) Prec@5 97.000 (99.081) +2022-11-14 13:54:17,101 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.0923) Prec@1 76.000 (84.132) Prec@5 100.000 (99.105) +2022-11-14 13:54:17,110 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0912) Prec@1 92.000 (84.333) Prec@5 99.000 (99.103) +2022-11-14 13:54:17,119 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0907) Prec@1 88.000 (84.425) Prec@5 100.000 (99.125) +2022-11-14 13:54:17,128 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0912) Prec@1 83.000 (84.390) Prec@5 96.000 (99.049) +2022-11-14 13:54:17,137 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0913) Prec@1 85.000 (84.405) Prec@5 98.000 (99.024) +2022-11-14 13:54:17,147 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0911) Prec@1 85.000 (84.419) Prec@5 100.000 (99.047) +2022-11-14 13:54:17,156 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0909) Prec@1 87.000 (84.477) Prec@5 100.000 (99.068) +2022-11-14 13:54:17,165 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0909) Prec@1 84.000 (84.467) Prec@5 99.000 (99.067) +2022-11-14 13:54:17,174 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0909) Prec@1 83.000 (84.435) Prec@5 100.000 (99.087) +2022-11-14 13:54:17,184 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0909) Prec@1 86.000 (84.468) Prec@5 100.000 (99.106) +2022-11-14 13:54:17,193 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.0914) Prec@1 79.000 (84.354) Prec@5 98.000 (99.083) +2022-11-14 13:54:17,203 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0910) Prec@1 89.000 (84.449) Prec@5 100.000 (99.102) +2022-11-14 13:54:17,214 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1234 (0.0916) Prec@1 76.000 (84.280) Prec@5 100.000 (99.120) +2022-11-14 13:54:17,223 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0913) Prec@1 86.000 (84.314) Prec@5 100.000 (99.137) +2022-11-14 13:54:17,232 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0915) Prec@1 83.000 (84.288) Prec@5 98.000 (99.115) +2022-11-14 13:54:17,242 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0917) Prec@1 82.000 (84.245) Prec@5 100.000 (99.132) +2022-11-14 13:54:17,251 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0914) Prec@1 89.000 (84.333) Prec@5 98.000 (99.111) +2022-11-14 13:54:17,259 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0917) Prec@1 83.000 (84.309) Prec@5 100.000 (99.127) +2022-11-14 13:54:17,270 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0920) Prec@1 82.000 (84.268) Prec@5 100.000 (99.143) +2022-11-14 13:54:17,280 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0920) Prec@1 84.000 (84.263) Prec@5 100.000 (99.158) +2022-11-14 13:54:17,290 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0917) Prec@1 87.000 (84.310) Prec@5 100.000 (99.172) +2022-11-14 13:54:17,300 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1246 (0.0922) Prec@1 77.000 (84.186) Prec@5 98.000 (99.153) +2022-11-14 13:54:17,309 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0921) Prec@1 86.000 (84.217) Prec@5 100.000 (99.167) +2022-11-14 13:54:17,319 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0921) Prec@1 84.000 (84.213) Prec@5 100.000 (99.180) +2022-11-14 13:54:17,328 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0922) Prec@1 84.000 (84.210) Prec@5 99.000 (99.177) +2022-11-14 13:54:17,336 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0921) Prec@1 83.000 (84.190) Prec@5 99.000 (99.175) +2022-11-14 13:54:17,346 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0917) Prec@1 90.000 (84.281) Prec@5 100.000 (99.188) +2022-11-14 13:54:17,355 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0920) Prec@1 80.000 (84.215) Prec@5 97.000 (99.154) +2022-11-14 13:54:17,364 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0921) Prec@1 81.000 (84.167) Prec@5 99.000 (99.152) +2022-11-14 13:54:17,374 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0916) Prec@1 90.000 (84.254) Prec@5 99.000 (99.149) +2022-11-14 13:54:17,384 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0919) Prec@1 81.000 (84.206) Prec@5 97.000 (99.118) +2022-11-14 13:54:17,395 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0916) Prec@1 86.000 (84.232) Prec@5 99.000 (99.116) +2022-11-14 13:54:17,403 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0917) Prec@1 81.000 (84.186) Prec@5 99.000 (99.114) +2022-11-14 13:54:17,412 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0921) Prec@1 82.000 (84.155) Prec@5 97.000 (99.085) +2022-11-14 13:54:17,422 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0918) Prec@1 89.000 (84.222) Prec@5 100.000 (99.097) +2022-11-14 13:54:17,431 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0918) Prec@1 84.000 (84.219) Prec@5 98.000 (99.082) +2022-11-14 13:54:17,440 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0917) Prec@1 84.000 (84.216) Prec@5 100.000 (99.095) +2022-11-14 13:54:17,448 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0918) Prec@1 83.000 (84.200) Prec@5 99.000 (99.093) +2022-11-14 13:54:17,458 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0916) Prec@1 87.000 (84.237) Prec@5 99.000 (99.092) +2022-11-14 13:54:17,466 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0915) Prec@1 86.000 (84.260) Prec@5 100.000 (99.104) +2022-11-14 13:54:17,475 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0915) Prec@1 82.000 (84.231) Prec@5 98.000 (99.090) +2022-11-14 13:54:17,483 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0916) Prec@1 84.000 (84.228) Prec@5 99.000 (99.089) +2022-11-14 13:54:17,494 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0917) Prec@1 81.000 (84.188) Prec@5 100.000 (99.100) +2022-11-14 13:54:17,503 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0916) Prec@1 87.000 (84.222) Prec@5 98.000 (99.086) +2022-11-14 13:54:17,512 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0914) Prec@1 90.000 (84.293) Prec@5 100.000 (99.098) +2022-11-14 13:54:17,520 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0915) Prec@1 84.000 (84.289) Prec@5 99.000 (99.096) +2022-11-14 13:54:17,529 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0916) Prec@1 86.000 (84.310) Prec@5 99.000 (99.095) +2022-11-14 13:54:17,538 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.0919) Prec@1 83.000 (84.294) Prec@5 99.000 (99.094) +2022-11-14 13:54:17,548 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.0921) Prec@1 85.000 (84.302) Prec@5 99.000 (99.093) +2022-11-14 13:54:17,557 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0921) Prec@1 85.000 (84.310) Prec@5 97.000 (99.069) +2022-11-14 13:54:17,566 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0920) Prec@1 87.000 (84.341) Prec@5 98.000 (99.057) +2022-11-14 13:54:17,576 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0918) Prec@1 88.000 (84.382) Prec@5 100.000 (99.067) +2022-11-14 13:54:17,585 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0917) Prec@1 86.000 (84.400) Prec@5 98.000 (99.056) +2022-11-14 13:54:17,595 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0916) Prec@1 86.000 (84.418) Prec@5 100.000 (99.066) +2022-11-14 13:54:17,605 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0913) Prec@1 91.000 (84.489) Prec@5 100.000 (99.076) +2022-11-14 13:54:17,614 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.0915) Prec@1 83.000 (84.473) Prec@5 98.000 (99.065) +2022-11-14 13:54:17,623 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0916) Prec@1 79.000 (84.415) Prec@5 99.000 (99.064) +2022-11-14 13:54:17,633 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0917) Prec@1 82.000 (84.389) Prec@5 98.000 (99.053) +2022-11-14 13:54:17,641 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0915) Prec@1 88.000 (84.427) Prec@5 99.000 (99.052) +2022-11-14 13:54:17,650 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0914) Prec@1 86.000 (84.443) Prec@5 100.000 (99.062) +2022-11-14 13:54:17,660 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1429 (0.0920) Prec@1 73.000 (84.327) Prec@5 96.000 (99.031) +2022-11-14 13:54:17,670 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0921) Prec@1 83.000 (84.313) Prec@5 100.000 (99.040) +2022-11-14 13:54:17,681 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0921) Prec@1 84.000 (84.310) Prec@5 98.000 (99.030) +2022-11-14 13:54:17,739 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:54:18,045 Epoch: [114][0/500] Time 0.024 (0.024) Data 0.221 (0.221) Loss 0.0434 (0.0434) Prec@1 93.000 (93.000) Prec@5 98.000 (98.000) +2022-11-14 13:54:18,273 Epoch: [114][10/500] Time 0.022 (0.020) Data 0.001 (0.022) Loss 0.0496 (0.0465) Prec@1 91.000 (92.000) Prec@5 100.000 (99.000) +2022-11-14 13:54:18,527 Epoch: [114][20/500] Time 0.024 (0.021) Data 0.001 (0.012) Loss 0.0704 (0.0545) Prec@1 87.000 (90.333) Prec@5 98.000 (98.667) +2022-11-14 13:54:18,772 Epoch: [114][30/500] Time 0.025 (0.022) Data 0.001 (0.009) Loss 0.0481 (0.0529) Prec@1 92.000 (90.750) Prec@5 100.000 (99.000) +2022-11-14 13:54:19,020 Epoch: [114][40/500] Time 0.023 (0.022) Data 0.002 (0.007) Loss 0.0377 (0.0499) Prec@1 94.000 (91.400) Prec@5 100.000 (99.200) +2022-11-14 13:54:19,277 Epoch: [114][50/500] Time 0.021 (0.022) Data 0.002 (0.006) Loss 0.0816 (0.0552) Prec@1 86.000 (90.500) Prec@5 100.000 (99.333) +2022-11-14 13:54:19,627 Epoch: [114][60/500] Time 0.036 (0.023) Data 0.002 (0.005) Loss 0.0769 (0.0583) Prec@1 87.000 (90.000) Prec@5 100.000 (99.429) +2022-11-14 13:54:19,992 Epoch: [114][70/500] Time 0.035 (0.025) Data 0.002 (0.005) Loss 0.0526 (0.0576) Prec@1 91.000 (90.125) Prec@5 100.000 (99.500) +2022-11-14 13:54:20,369 Epoch: [114][80/500] Time 0.034 (0.026) Data 0.002 (0.004) Loss 0.0787 (0.0599) Prec@1 86.000 (89.667) Prec@5 99.000 (99.444) +2022-11-14 13:54:20,738 Epoch: [114][90/500] Time 0.035 (0.026) Data 0.002 (0.004) Loss 0.0811 (0.0620) Prec@1 87.000 (89.400) Prec@5 97.000 (99.200) +2022-11-14 13:54:21,109 Epoch: [114][100/500] Time 0.035 (0.027) Data 0.002 (0.004) Loss 0.0453 (0.0605) Prec@1 93.000 (89.727) Prec@5 99.000 (99.182) +2022-11-14 13:54:21,479 Epoch: [114][110/500] Time 0.035 (0.028) Data 0.002 (0.004) Loss 0.0749 (0.0617) Prec@1 87.000 (89.500) Prec@5 100.000 (99.250) +2022-11-14 13:54:21,848 Epoch: [114][120/500] Time 0.036 (0.028) Data 0.001 (0.004) Loss 0.0738 (0.0626) Prec@1 91.000 (89.615) Prec@5 100.000 (99.308) +2022-11-14 13:54:22,210 Epoch: [114][130/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.0701 (0.0632) Prec@1 89.000 (89.571) Prec@5 100.000 (99.357) +2022-11-14 13:54:22,577 Epoch: [114][140/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.1122 (0.0664) Prec@1 81.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 13:54:22,949 Epoch: [114][150/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0720 (0.0668) Prec@1 86.000 (88.812) Prec@5 97.000 (99.250) +2022-11-14 13:54:23,316 Epoch: [114][160/500] Time 0.033 (0.029) Data 0.001 (0.003) Loss 0.0772 (0.0674) Prec@1 89.000 (88.824) Prec@5 99.000 (99.235) +2022-11-14 13:54:23,686 Epoch: [114][170/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0694 (0.0675) Prec@1 90.000 (88.889) Prec@5 99.000 (99.222) +2022-11-14 13:54:24,064 Epoch: [114][180/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0735 (0.0678) Prec@1 88.000 (88.842) Prec@5 100.000 (99.263) +2022-11-14 13:54:24,436 Epoch: [114][190/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0754 (0.0682) Prec@1 89.000 (88.850) Prec@5 98.000 (99.200) +2022-11-14 13:54:24,800 Epoch: [114][200/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0682 (0.0682) Prec@1 88.000 (88.810) Prec@5 99.000 (99.190) +2022-11-14 13:54:25,167 Epoch: [114][210/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0877 (0.0691) Prec@1 85.000 (88.636) Prec@5 99.000 (99.182) +2022-11-14 13:54:25,533 Epoch: [114][220/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0732 (0.0693) Prec@1 89.000 (88.652) Prec@5 100.000 (99.217) +2022-11-14 13:54:25,904 Epoch: [114][230/500] Time 0.034 (0.030) Data 0.003 (0.003) Loss 0.0800 (0.0697) Prec@1 84.000 (88.458) Prec@5 99.000 (99.208) +2022-11-14 13:54:26,273 Epoch: [114][240/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0414 (0.0686) Prec@1 95.000 (88.720) Prec@5 99.000 (99.200) +2022-11-14 13:54:26,633 Epoch: [114][250/500] Time 0.034 (0.030) Data 0.001 (0.003) Loss 0.0470 (0.0677) Prec@1 92.000 (88.846) Prec@5 99.000 (99.192) +2022-11-14 13:54:27,009 Epoch: [114][260/500] Time 0.036 (0.031) Data 0.001 (0.003) Loss 0.0710 (0.0679) Prec@1 88.000 (88.815) Prec@5 100.000 (99.222) +2022-11-14 13:54:27,376 Epoch: [114][270/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0588 (0.0675) Prec@1 93.000 (88.964) Prec@5 100.000 (99.250) +2022-11-14 13:54:27,745 Epoch: [114][280/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0779 (0.0679) Prec@1 86.000 (88.862) Prec@5 100.000 (99.276) +2022-11-14 13:54:28,119 Epoch: [114][290/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0598 (0.0676) Prec@1 90.000 (88.900) Prec@5 99.000 (99.267) +2022-11-14 13:54:28,489 Epoch: [114][300/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0828 (0.0681) Prec@1 84.000 (88.742) Prec@5 99.000 (99.258) +2022-11-14 13:54:28,858 Epoch: [114][310/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0748 (0.0683) Prec@1 88.000 (88.719) Prec@5 99.000 (99.250) +2022-11-14 13:54:29,237 Epoch: [114][320/500] Time 0.037 (0.031) Data 0.002 (0.002) Loss 0.0796 (0.0687) Prec@1 86.000 (88.636) Prec@5 100.000 (99.273) +2022-11-14 13:54:29,602 Epoch: [114][330/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0644 (0.0685) Prec@1 90.000 (88.676) Prec@5 99.000 (99.265) +2022-11-14 13:54:29,973 Epoch: [114][340/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0792 (0.0688) Prec@1 89.000 (88.686) Prec@5 100.000 (99.286) +2022-11-14 13:54:30,341 Epoch: [114][350/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0476 (0.0683) Prec@1 96.000 (88.889) Prec@5 100.000 (99.306) +2022-11-14 13:54:30,710 Epoch: [114][360/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0760 (0.0685) Prec@1 89.000 (88.892) Prec@5 100.000 (99.324) +2022-11-14 13:54:31,086 Epoch: [114][370/500] Time 0.032 (0.031) Data 0.002 (0.002) Loss 0.0875 (0.0690) Prec@1 84.000 (88.763) Prec@5 100.000 (99.342) +2022-11-14 13:54:31,453 Epoch: [114][380/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0817 (0.0693) Prec@1 87.000 (88.718) Prec@5 99.000 (99.333) +2022-11-14 13:54:31,829 Epoch: [114][390/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.1058 (0.0702) Prec@1 79.000 (88.475) Prec@5 100.000 (99.350) +2022-11-14 13:54:32,208 Epoch: [114][400/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0663 (0.0701) Prec@1 90.000 (88.512) Prec@5 99.000 (99.341) +2022-11-14 13:54:32,570 Epoch: [114][410/500] Time 0.034 (0.031) Data 0.001 (0.002) Loss 0.0554 (0.0698) Prec@1 89.000 (88.524) Prec@5 100.000 (99.357) +2022-11-14 13:54:32,941 Epoch: [114][420/500] Time 0.034 (0.031) Data 0.001 (0.002) Loss 0.0831 (0.0701) Prec@1 84.000 (88.419) Prec@5 99.000 (99.349) +2022-11-14 13:54:33,308 Epoch: [114][430/500] Time 0.037 (0.031) Data 0.002 (0.002) Loss 0.0582 (0.0698) Prec@1 92.000 (88.500) Prec@5 100.000 (99.364) +2022-11-14 13:54:33,681 Epoch: [114][440/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0776 (0.0700) Prec@1 86.000 (88.444) Prec@5 99.000 (99.356) +2022-11-14 13:54:34,103 Epoch: [114][450/500] Time 0.047 (0.032) Data 0.002 (0.002) Loss 0.0609 (0.0698) Prec@1 90.000 (88.478) Prec@5 100.000 (99.370) +2022-11-14 13:54:34,483 Epoch: [114][460/500] Time 0.034 (0.032) Data 0.001 (0.002) Loss 0.0601 (0.0696) Prec@1 90.000 (88.511) Prec@5 100.000 (99.383) +2022-11-14 13:54:34,932 Epoch: [114][470/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.1038 (0.0703) Prec@1 83.000 (88.396) Prec@5 99.000 (99.375) +2022-11-14 13:54:35,340 Epoch: [114][480/500] Time 0.041 (0.032) Data 0.002 (0.002) Loss 0.0830 (0.0705) Prec@1 85.000 (88.327) Prec@5 100.000 (99.388) +2022-11-14 13:54:35,691 Epoch: [114][490/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0906 (0.0709) Prec@1 83.000 (88.220) Prec@5 96.000 (99.320) +2022-11-14 13:54:36,031 Epoch: [114][499/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0480 (0.0705) Prec@1 91.000 (88.275) Prec@5 100.000 (99.333) +2022-11-14 13:54:36,338 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0925 (0.0925) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 13:54:36,348 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0915 (0.0920) Prec@1 85.000 (84.500) Prec@5 99.000 (99.000) +2022-11-14 13:54:36,360 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1034 (0.0958) Prec@1 80.000 (83.000) Prec@5 100.000 (99.333) +2022-11-14 13:54:36,374 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1079 (0.0988) Prec@1 81.000 (82.500) Prec@5 98.000 (99.000) +2022-11-14 13:54:36,385 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1009 (0.0993) Prec@1 85.000 (83.000) Prec@5 100.000 (99.200) +2022-11-14 13:54:36,396 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0932) Prec@1 88.000 (83.833) Prec@5 100.000 (99.333) +2022-11-14 13:54:36,407 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1107 (0.0957) Prec@1 84.000 (83.857) Prec@5 100.000 (99.429) +2022-11-14 13:54:36,417 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1248 (0.0994) Prec@1 78.000 (83.125) Prec@5 98.000 (99.250) +2022-11-14 13:54:36,424 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1308 (0.1029) Prec@1 79.000 (82.667) Prec@5 99.000 (99.222) +2022-11-14 13:54:36,433 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0990) Prec@1 89.000 (83.300) Prec@5 97.000 (99.000) +2022-11-14 13:54:36,443 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0976) Prec@1 85.000 (83.455) Prec@5 100.000 (99.091) +2022-11-14 13:54:36,452 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1130 (0.0989) Prec@1 78.000 (83.000) Prec@5 100.000 (99.167) +2022-11-14 13:54:36,460 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0974) Prec@1 85.000 (83.154) Prec@5 99.000 (99.154) +2022-11-14 13:54:36,469 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0960) Prec@1 86.000 (83.357) Prec@5 99.000 (99.143) +2022-11-14 13:54:36,479 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0958) Prec@1 83.000 (83.333) Prec@5 100.000 (99.200) +2022-11-14 13:54:36,487 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0958) Prec@1 83.000 (83.312) Prec@5 98.000 (99.125) +2022-11-14 13:54:36,496 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0947) Prec@1 90.000 (83.706) Prec@5 99.000 (99.118) +2022-11-14 13:54:36,506 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.0962) Prec@1 79.000 (83.444) Prec@5 100.000 (99.167) +2022-11-14 13:54:36,515 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0965) Prec@1 83.000 (83.421) Prec@5 99.000 (99.158) +2022-11-14 13:54:36,524 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1463 (0.0990) Prec@1 74.000 (82.950) Prec@5 98.000 (99.100) +2022-11-14 13:54:36,533 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0990) Prec@1 81.000 (82.857) Prec@5 99.000 (99.095) +2022-11-14 13:54:36,542 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0983) Prec@1 87.000 (83.045) Prec@5 98.000 (99.045) +2022-11-14 13:54:36,551 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1247 (0.0995) Prec@1 78.000 (82.826) Prec@5 100.000 (99.087) +2022-11-14 13:54:36,561 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0993) Prec@1 81.000 (82.750) Prec@5 100.000 (99.125) +2022-11-14 13:54:36,571 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0999) Prec@1 81.000 (82.680) Prec@5 100.000 (99.160) +2022-11-14 13:54:36,580 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.1005) Prec@1 82.000 (82.654) Prec@5 99.000 (99.154) +2022-11-14 13:54:36,588 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0997) Prec@1 87.000 (82.815) Prec@5 100.000 (99.185) +2022-11-14 13:54:36,596 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0992) Prec@1 82.000 (82.786) Prec@5 100.000 (99.214) +2022-11-14 13:54:36,605 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0991) Prec@1 85.000 (82.862) Prec@5 97.000 (99.138) +2022-11-14 13:54:36,614 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1333 (0.1002) Prec@1 79.000 (82.733) Prec@5 98.000 (99.100) +2022-11-14 13:54:36,623 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.1002) Prec@1 83.000 (82.742) Prec@5 97.000 (99.032) +2022-11-14 13:54:36,632 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.1000) Prec@1 84.000 (82.781) Prec@5 99.000 (99.031) +2022-11-14 13:54:36,641 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0995) Prec@1 86.000 (82.879) Prec@5 98.000 (99.000) +2022-11-14 13:54:36,651 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1384 (0.1007) Prec@1 78.000 (82.735) Prec@5 100.000 (99.029) +2022-11-14 13:54:36,660 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.1004) Prec@1 87.000 (82.857) Prec@5 99.000 (99.029) +2022-11-14 13:54:36,670 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.1006) Prec@1 82.000 (82.833) Prec@5 100.000 (99.056) +2022-11-14 13:54:36,679 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.1009) Prec@1 81.000 (82.784) Prec@5 96.000 (98.973) +2022-11-14 13:54:36,688 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.1012) Prec@1 79.000 (82.684) Prec@5 100.000 (99.000) +2022-11-14 13:54:36,697 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.1007) Prec@1 89.000 (82.846) Prec@5 100.000 (99.026) +2022-11-14 13:54:36,708 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.1002) Prec@1 86.000 (82.925) Prec@5 100.000 (99.050) +2022-11-14 13:54:36,720 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.1006) Prec@1 82.000 (82.902) Prec@5 98.000 (99.024) +2022-11-14 13:54:36,732 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.1003) Prec@1 84.000 (82.929) Prec@5 98.000 (99.000) +2022-11-14 13:54:36,743 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0995) Prec@1 87.000 (83.023) Prec@5 100.000 (99.023) +2022-11-14 13:54:36,754 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0996) Prec@1 84.000 (83.045) Prec@5 97.000 (98.977) +2022-11-14 13:54:36,767 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0997) Prec@1 81.000 (83.000) Prec@5 99.000 (98.978) +2022-11-14 13:54:36,780 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1497 (0.1008) Prec@1 75.000 (82.826) Prec@5 100.000 (99.000) +2022-11-14 13:54:36,790 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.1010) Prec@1 82.000 (82.809) Prec@5 100.000 (99.021) +2022-11-14 13:54:36,802 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.1010) Prec@1 84.000 (82.833) Prec@5 99.000 (99.021) +2022-11-14 13:54:36,812 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.1005) Prec@1 86.000 (82.898) Prec@5 100.000 (99.041) +2022-11-14 13:54:36,822 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.1007) Prec@1 81.000 (82.860) Prec@5 99.000 (99.040) +2022-11-14 13:54:36,833 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.1006) Prec@1 84.000 (82.882) Prec@5 100.000 (99.059) +2022-11-14 13:54:36,842 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.1005) Prec@1 85.000 (82.923) Prec@5 98.000 (99.038) +2022-11-14 13:54:36,852 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.1000) Prec@1 83.000 (82.925) Prec@5 100.000 (99.057) +2022-11-14 13:54:36,861 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0999) Prec@1 81.000 (82.889) Prec@5 99.000 (99.056) +2022-11-14 13:54:36,870 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.1003) Prec@1 83.000 (82.891) Prec@5 100.000 (99.073) +2022-11-14 13:54:36,880 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.1002) Prec@1 83.000 (82.893) Prec@5 99.000 (99.071) +2022-11-14 13:54:36,889 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1229 (0.1006) Prec@1 80.000 (82.842) Prec@5 99.000 (99.070) +2022-11-14 13:54:36,898 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.1002) Prec@1 84.000 (82.862) Prec@5 97.000 (99.034) +2022-11-14 13:54:36,907 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1224 (0.1006) Prec@1 78.000 (82.780) Prec@5 100.000 (99.051) +2022-11-14 13:54:36,916 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.1008) Prec@1 80.000 (82.733) Prec@5 99.000 (99.050) +2022-11-14 13:54:36,924 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1330 (0.1013) Prec@1 76.000 (82.623) Prec@5 99.000 (99.049) +2022-11-14 13:54:36,933 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.1013) Prec@1 81.000 (82.597) Prec@5 99.000 (99.048) +2022-11-14 13:54:36,943 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.1011) Prec@1 84.000 (82.619) Prec@5 99.000 (99.048) +2022-11-14 13:54:36,952 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.1006) Prec@1 87.000 (82.688) Prec@5 99.000 (99.047) +2022-11-14 13:54:36,961 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.1008) Prec@1 80.000 (82.646) Prec@5 99.000 (99.046) +2022-11-14 13:54:36,971 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.1009) Prec@1 78.000 (82.576) Prec@5 100.000 (99.061) +2022-11-14 13:54:36,979 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.1003) Prec@1 89.000 (82.672) Prec@5 100.000 (99.075) +2022-11-14 13:54:36,988 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.1005) Prec@1 80.000 (82.632) Prec@5 97.000 (99.044) +2022-11-14 13:54:36,998 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.1001) Prec@1 85.000 (82.667) Prec@5 99.000 (99.043) +2022-11-14 13:54:37,007 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.1003) Prec@1 85.000 (82.700) Prec@5 98.000 (99.029) +2022-11-14 13:54:37,017 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.1005) Prec@1 80.000 (82.662) Prec@5 99.000 (99.028) +2022-11-14 13:54:37,027 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.1004) Prec@1 85.000 (82.694) Prec@5 100.000 (99.042) +2022-11-14 13:54:37,037 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.1000) Prec@1 89.000 (82.781) Prec@5 99.000 (99.041) +2022-11-14 13:54:37,047 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0999) Prec@1 86.000 (82.824) Prec@5 100.000 (99.054) +2022-11-14 13:54:37,056 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.1001) Prec@1 79.000 (82.773) Prec@5 100.000 (99.067) +2022-11-14 13:54:37,065 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0999) Prec@1 86.000 (82.816) Prec@5 99.000 (99.066) +2022-11-14 13:54:37,074 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0996) Prec@1 88.000 (82.883) Prec@5 99.000 (99.065) +2022-11-14 13:54:37,084 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0998) Prec@1 82.000 (82.872) Prec@5 95.000 (99.013) +2022-11-14 13:54:37,093 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0997) Prec@1 84.000 (82.886) Prec@5 100.000 (99.025) +2022-11-14 13:54:37,102 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0998) Prec@1 84.000 (82.900) Prec@5 97.000 (99.000) +2022-11-14 13:54:37,111 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0997) Prec@1 84.000 (82.914) Prec@5 98.000 (98.988) +2022-11-14 13:54:37,120 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0994) Prec@1 87.000 (82.963) Prec@5 98.000 (98.976) +2022-11-14 13:54:37,130 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1186 (0.0996) Prec@1 80.000 (82.928) Prec@5 99.000 (98.976) +2022-11-14 13:54:37,140 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0995) Prec@1 85.000 (82.952) Prec@5 100.000 (98.988) +2022-11-14 13:54:37,148 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0997) Prec@1 79.000 (82.906) Prec@5 99.000 (98.988) +2022-11-14 13:54:37,158 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.0999) Prec@1 81.000 (82.884) Prec@5 99.000 (98.988) +2022-11-14 13:54:37,168 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0999) Prec@1 83.000 (82.885) Prec@5 99.000 (98.989) +2022-11-14 13:54:37,179 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0998) Prec@1 85.000 (82.909) Prec@5 98.000 (98.977) +2022-11-14 13:54:37,191 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.1000) Prec@1 76.000 (82.831) Prec@5 99.000 (98.978) +2022-11-14 13:54:37,200 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0999) Prec@1 86.000 (82.867) Prec@5 100.000 (98.989) +2022-11-14 13:54:37,208 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.1000) Prec@1 79.000 (82.824) Prec@5 100.000 (99.000) +2022-11-14 13:54:37,216 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0998) Prec@1 85.000 (82.848) Prec@5 99.000 (99.000) +2022-11-14 13:54:37,225 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0998) Prec@1 83.000 (82.849) Prec@5 99.000 (99.000) +2022-11-14 13:54:37,235 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0997) Prec@1 81.000 (82.830) Prec@5 98.000 (98.989) +2022-11-14 13:54:37,244 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0999) Prec@1 78.000 (82.779) Prec@5 98.000 (98.979) +2022-11-14 13:54:37,252 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0998) Prec@1 86.000 (82.812) Prec@5 100.000 (98.990) +2022-11-14 13:54:37,262 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0506 (0.0993) Prec@1 92.000 (82.907) Prec@5 100.000 (99.000) +2022-11-14 13:54:37,273 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1261 (0.0996) Prec@1 81.000 (82.888) Prec@5 98.000 (98.990) +2022-11-14 13:54:37,284 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0995) Prec@1 85.000 (82.909) Prec@5 100.000 (99.000) +2022-11-14 13:54:37,295 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0996) Prec@1 81.000 (82.890) Prec@5 97.000 (98.980) +2022-11-14 13:54:37,354 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:54:37,717 Epoch: [115][0/500] Time 0.031 (0.031) Data 0.271 (0.271) Loss 0.0896 (0.0896) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 13:54:37,959 Epoch: [115][10/500] Time 0.022 (0.022) Data 0.002 (0.026) Loss 0.0827 (0.0861) Prec@1 89.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 13:54:38,208 Epoch: [115][20/500] Time 0.023 (0.022) Data 0.002 (0.015) Loss 0.0507 (0.0743) Prec@1 91.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 13:54:38,529 Epoch: [115][30/500] Time 0.041 (0.024) Data 0.002 (0.010) Loss 0.0474 (0.0676) Prec@1 92.000 (89.250) Prec@5 98.000 (99.000) +2022-11-14 13:54:38,994 Epoch: [115][40/500] Time 0.061 (0.028) Data 0.002 (0.008) Loss 0.0808 (0.0702) Prec@1 87.000 (88.800) Prec@5 100.000 (99.200) +2022-11-14 13:54:39,407 Epoch: [115][50/500] Time 0.041 (0.030) Data 0.002 (0.007) Loss 0.0705 (0.0703) Prec@1 88.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 13:54:39,840 Epoch: [115][60/500] Time 0.040 (0.031) Data 0.002 (0.006) Loss 0.0789 (0.0715) Prec@1 87.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 13:54:40,269 Epoch: [115][70/500] Time 0.040 (0.032) Data 0.002 (0.006) Loss 0.0552 (0.0695) Prec@1 90.000 (88.625) Prec@5 99.000 (99.375) +2022-11-14 13:54:40,690 Epoch: [115][80/500] Time 0.040 (0.033) Data 0.002 (0.005) Loss 0.0606 (0.0685) Prec@1 91.000 (88.889) Prec@5 99.000 (99.333) +2022-11-14 13:54:41,120 Epoch: [115][90/500] Time 0.041 (0.033) Data 0.002 (0.005) Loss 0.0697 (0.0686) Prec@1 90.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 13:54:41,544 Epoch: [115][100/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0696 (0.0687) Prec@1 88.000 (88.909) Prec@5 99.000 (99.364) +2022-11-14 13:54:41,968 Epoch: [115][110/500] Time 0.039 (0.034) Data 0.002 (0.004) Loss 0.0563 (0.0677) Prec@1 91.000 (89.083) Prec@5 99.000 (99.333) +2022-11-14 13:54:42,388 Epoch: [115][120/500] Time 0.040 (0.034) Data 0.002 (0.004) Loss 0.0609 (0.0672) Prec@1 88.000 (89.000) Prec@5 99.000 (99.308) +2022-11-14 13:54:42,807 Epoch: [115][130/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0488 (0.0658) Prec@1 93.000 (89.286) Prec@5 99.000 (99.286) +2022-11-14 13:54:43,234 Epoch: [115][140/500] Time 0.041 (0.035) Data 0.002 (0.004) Loss 0.0474 (0.0646) Prec@1 93.000 (89.533) Prec@5 100.000 (99.333) +2022-11-14 13:54:43,671 Epoch: [115][150/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0560 (0.0641) Prec@1 91.000 (89.625) Prec@5 100.000 (99.375) +2022-11-14 13:54:44,098 Epoch: [115][160/500] Time 0.041 (0.035) Data 0.002 (0.004) Loss 0.0537 (0.0635) Prec@1 90.000 (89.647) Prec@5 100.000 (99.412) +2022-11-14 13:54:44,529 Epoch: [115][170/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0474 (0.0626) Prec@1 93.000 (89.833) Prec@5 100.000 (99.444) +2022-11-14 13:54:44,955 Epoch: [115][180/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0695 (0.0629) Prec@1 90.000 (89.842) Prec@5 100.000 (99.474) +2022-11-14 13:54:45,377 Epoch: [115][190/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0536 (0.0625) Prec@1 88.000 (89.750) Prec@5 100.000 (99.500) +2022-11-14 13:54:45,803 Epoch: [115][200/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0764 (0.0631) Prec@1 88.000 (89.667) Prec@5 100.000 (99.524) +2022-11-14 13:54:46,225 Epoch: [115][210/500] Time 0.040 (0.036) Data 0.001 (0.003) Loss 0.0636 (0.0632) Prec@1 92.000 (89.773) Prec@5 98.000 (99.455) +2022-11-14 13:54:46,647 Epoch: [115][220/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0883 (0.0642) Prec@1 85.000 (89.565) Prec@5 99.000 (99.435) +2022-11-14 13:54:47,059 Epoch: [115][230/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0721 (0.0646) Prec@1 91.000 (89.625) Prec@5 96.000 (99.292) +2022-11-14 13:54:47,474 Epoch: [115][240/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0734 (0.0649) Prec@1 87.000 (89.520) Prec@5 100.000 (99.320) +2022-11-14 13:54:47,891 Epoch: [115][250/500] Time 0.040 (0.036) Data 0.001 (0.003) Loss 0.0667 (0.0650) Prec@1 89.000 (89.500) Prec@5 99.000 (99.308) +2022-11-14 13:54:48,320 Epoch: [115][260/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0868 (0.0658) Prec@1 84.000 (89.296) Prec@5 100.000 (99.333) +2022-11-14 13:54:48,736 Epoch: [115][270/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0777 (0.0662) Prec@1 88.000 (89.250) Prec@5 100.000 (99.357) +2022-11-14 13:54:49,156 Epoch: [115][280/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0633 (0.0661) Prec@1 91.000 (89.310) Prec@5 100.000 (99.379) +2022-11-14 13:54:49,574 Epoch: [115][290/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0695 (0.0662) Prec@1 88.000 (89.267) Prec@5 100.000 (99.400) +2022-11-14 13:54:50,003 Epoch: [115][300/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0977 (0.0673) Prec@1 84.000 (89.097) Prec@5 98.000 (99.355) +2022-11-14 13:54:50,433 Epoch: [115][310/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0860 (0.0678) Prec@1 84.000 (88.938) Prec@5 100.000 (99.375) +2022-11-14 13:54:50,859 Epoch: [115][320/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0693 (0.0679) Prec@1 88.000 (88.909) Prec@5 99.000 (99.364) +2022-11-14 13:54:51,270 Epoch: [115][330/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0663 (0.0678) Prec@1 89.000 (88.912) Prec@5 99.000 (99.353) +2022-11-14 13:54:51,678 Epoch: [115][340/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0585 (0.0676) Prec@1 92.000 (89.000) Prec@5 99.000 (99.343) +2022-11-14 13:54:52,094 Epoch: [115][350/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0819 (0.0680) Prec@1 84.000 (88.861) Prec@5 99.000 (99.333) +2022-11-14 13:54:52,518 Epoch: [115][360/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0637 (0.0679) Prec@1 89.000 (88.865) Prec@5 98.000 (99.297) +2022-11-14 13:54:52,931 Epoch: [115][370/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0592 (0.0676) Prec@1 90.000 (88.895) Prec@5 98.000 (99.263) +2022-11-14 13:54:53,349 Epoch: [115][380/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0673 (0.0676) Prec@1 88.000 (88.872) Prec@5 100.000 (99.282) +2022-11-14 13:54:53,759 Epoch: [115][390/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0656 (0.0676) Prec@1 90.000 (88.900) Prec@5 99.000 (99.275) +2022-11-14 13:54:54,182 Epoch: [115][400/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0489 (0.0671) Prec@1 93.000 (89.000) Prec@5 100.000 (99.293) +2022-11-14 13:54:54,595 Epoch: [115][410/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0699 (0.0672) Prec@1 88.000 (88.976) Prec@5 100.000 (99.310) +2022-11-14 13:54:55,015 Epoch: [115][420/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0437 (0.0666) Prec@1 92.000 (89.047) Prec@5 99.000 (99.302) +2022-11-14 13:54:55,441 Epoch: [115][430/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0658 (0.0666) Prec@1 88.000 (89.023) Prec@5 100.000 (99.318) +2022-11-14 13:54:55,862 Epoch: [115][440/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0751 (0.0668) Prec@1 87.000 (88.978) Prec@5 98.000 (99.289) +2022-11-14 13:54:56,271 Epoch: [115][450/500] Time 0.041 (0.036) Data 0.001 (0.002) Loss 0.0758 (0.0670) Prec@1 88.000 (88.957) Prec@5 97.000 (99.239) +2022-11-14 13:54:56,690 Epoch: [115][460/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0601 (0.0669) Prec@1 92.000 (89.021) Prec@5 100.000 (99.255) +2022-11-14 13:54:57,119 Epoch: [115][470/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0699 (0.0669) Prec@1 89.000 (89.021) Prec@5 99.000 (99.250) +2022-11-14 13:54:57,544 Epoch: [115][480/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0786 (0.0672) Prec@1 86.000 (88.959) Prec@5 100.000 (99.265) +2022-11-14 13:54:57,960 Epoch: [115][490/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0647 (0.0671) Prec@1 91.000 (89.000) Prec@5 98.000 (99.240) +2022-11-14 13:54:58,333 Epoch: [115][499/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0693 (0.0671) Prec@1 89.000 (89.000) Prec@5 100.000 (99.255) +2022-11-14 13:54:58,604 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0707 (0.0707) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 13:54:58,613 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0782) Prec@1 82.000 (84.500) Prec@5 99.000 (98.500) +2022-11-14 13:54:58,622 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0833) Prec@1 84.000 (84.333) Prec@5 98.000 (98.333) +2022-11-14 13:54:58,634 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0875) Prec@1 80.000 (83.250) Prec@5 99.000 (98.500) +2022-11-14 13:54:58,641 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0883) Prec@1 81.000 (82.800) Prec@5 100.000 (98.800) +2022-11-14 13:54:58,648 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0850) Prec@1 86.000 (83.333) Prec@5 100.000 (99.000) +2022-11-14 13:54:58,656 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0844) Prec@1 89.000 (84.143) Prec@5 100.000 (99.143) +2022-11-14 13:54:58,666 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.0885) Prec@1 79.000 (83.500) Prec@5 98.000 (99.000) +2022-11-14 13:54:58,674 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0878) Prec@1 87.000 (83.889) Prec@5 100.000 (99.111) +2022-11-14 13:54:58,684 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0871) Prec@1 87.000 (84.200) Prec@5 97.000 (98.900) +2022-11-14 13:54:58,693 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0858) Prec@1 88.000 (84.545) Prec@5 100.000 (99.000) +2022-11-14 13:54:58,702 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0851) Prec@1 89.000 (84.917) Prec@5 99.000 (99.000) +2022-11-14 13:54:58,711 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0857) Prec@1 82.000 (84.692) Prec@5 100.000 (99.077) +2022-11-14 13:54:58,720 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0842) Prec@1 91.000 (85.143) Prec@5 98.000 (99.000) +2022-11-14 13:54:58,730 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0852) Prec@1 84.000 (85.067) Prec@5 100.000 (99.067) +2022-11-14 13:54:58,739 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0858) Prec@1 83.000 (84.938) Prec@5 98.000 (99.000) +2022-11-14 13:54:58,749 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0860) Prec@1 85.000 (84.941) Prec@5 98.000 (98.941) +2022-11-14 13:54:58,757 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.0877) Prec@1 80.000 (84.667) Prec@5 100.000 (99.000) +2022-11-14 13:54:58,766 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0886) Prec@1 80.000 (84.421) Prec@5 97.000 (98.895) +2022-11-14 13:54:58,775 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0892) Prec@1 84.000 (84.400) Prec@5 98.000 (98.850) +2022-11-14 13:54:58,785 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0893) Prec@1 85.000 (84.429) Prec@5 99.000 (98.857) +2022-11-14 13:54:58,794 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0891) Prec@1 84.000 (84.409) Prec@5 98.000 (98.818) +2022-11-14 13:54:58,803 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.0906) Prec@1 78.000 (84.130) Prec@5 98.000 (98.783) +2022-11-14 13:54:58,813 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0910) Prec@1 82.000 (84.042) Prec@5 100.000 (98.833) +2022-11-14 13:54:58,822 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0916) Prec@1 82.000 (83.960) Prec@5 100.000 (98.880) +2022-11-14 13:54:58,831 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1314 (0.0932) Prec@1 77.000 (83.692) Prec@5 97.000 (98.808) +2022-11-14 13:54:58,840 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0924) Prec@1 90.000 (83.926) Prec@5 99.000 (98.815) +2022-11-14 13:54:58,849 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0924) Prec@1 86.000 (84.000) Prec@5 99.000 (98.821) +2022-11-14 13:54:58,857 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0921) Prec@1 85.000 (84.034) Prec@5 99.000 (98.828) +2022-11-14 13:54:58,867 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0917) Prec@1 85.000 (84.067) Prec@5 99.000 (98.833) +2022-11-14 13:54:58,875 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0919) Prec@1 82.000 (84.000) Prec@5 100.000 (98.871) +2022-11-14 13:54:58,884 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0918) Prec@1 83.000 (83.969) Prec@5 99.000 (98.875) +2022-11-14 13:54:58,893 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0919) Prec@1 83.000 (83.939) Prec@5 99.000 (98.879) +2022-11-14 13:54:58,903 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1269 (0.0929) Prec@1 79.000 (83.794) Prec@5 95.000 (98.765) +2022-11-14 13:54:58,911 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0932) Prec@1 84.000 (83.800) Prec@5 99.000 (98.771) +2022-11-14 13:54:58,919 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0931) Prec@1 86.000 (83.861) Prec@5 99.000 (98.778) +2022-11-14 13:54:58,929 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0935) Prec@1 80.000 (83.757) Prec@5 99.000 (98.784) +2022-11-14 13:54:58,938 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0937) Prec@1 80.000 (83.658) Prec@5 100.000 (98.816) +2022-11-14 13:54:58,947 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0931) Prec@1 89.000 (83.795) Prec@5 100.000 (98.846) +2022-11-14 13:54:58,956 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0923) Prec@1 92.000 (84.000) Prec@5 99.000 (98.850) +2022-11-14 13:54:58,965 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.0928) Prec@1 80.000 (83.902) Prec@5 99.000 (98.854) +2022-11-14 13:54:58,974 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0926) Prec@1 87.000 (83.976) Prec@5 99.000 (98.857) +2022-11-14 13:54:58,984 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0920) Prec@1 89.000 (84.093) Prec@5 100.000 (98.884) +2022-11-14 13:54:58,994 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0919) Prec@1 84.000 (84.091) Prec@5 98.000 (98.864) +2022-11-14 13:54:59,003 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0919) Prec@1 82.000 (84.044) Prec@5 99.000 (98.867) +2022-11-14 13:54:59,012 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.0924) Prec@1 77.000 (83.891) Prec@5 100.000 (98.891) +2022-11-14 13:54:59,021 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0922) Prec@1 84.000 (83.894) Prec@5 100.000 (98.915) +2022-11-14 13:54:59,030 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0923) Prec@1 81.000 (83.833) Prec@5 99.000 (98.917) +2022-11-14 13:54:59,040 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0919) Prec@1 86.000 (83.878) Prec@5 100.000 (98.939) +2022-11-14 13:54:59,049 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0922) Prec@1 84.000 (83.880) Prec@5 97.000 (98.900) +2022-11-14 13:54:59,058 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0923) Prec@1 83.000 (83.863) Prec@5 99.000 (98.902) +2022-11-14 13:54:59,067 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1197 (0.0928) Prec@1 79.000 (83.769) Prec@5 98.000 (98.885) +2022-11-14 13:54:59,077 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0927) Prec@1 86.000 (83.811) Prec@5 99.000 (98.887) +2022-11-14 13:54:59,086 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0922) Prec@1 88.000 (83.889) Prec@5 99.000 (98.889) +2022-11-14 13:54:59,095 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0925) Prec@1 81.000 (83.836) Prec@5 100.000 (98.909) +2022-11-14 13:54:59,104 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0925) Prec@1 85.000 (83.857) Prec@5 98.000 (98.893) +2022-11-14 13:54:59,113 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0924) Prec@1 85.000 (83.877) Prec@5 99.000 (98.895) +2022-11-14 13:54:59,122 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0920) Prec@1 85.000 (83.897) Prec@5 98.000 (98.879) +2022-11-14 13:54:59,132 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1225 (0.0926) Prec@1 76.000 (83.763) Prec@5 99.000 (98.881) +2022-11-14 13:54:59,140 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0924) Prec@1 84.000 (83.767) Prec@5 99.000 (98.883) +2022-11-14 13:54:59,150 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0924) Prec@1 87.000 (83.820) Prec@5 100.000 (98.902) +2022-11-14 13:54:59,160 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0926) Prec@1 81.000 (83.774) Prec@5 100.000 (98.919) +2022-11-14 13:54:59,169 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0924) Prec@1 86.000 (83.810) Prec@5 100.000 (98.937) +2022-11-14 13:54:59,179 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0921) Prec@1 84.000 (83.812) Prec@5 100.000 (98.953) +2022-11-14 13:54:59,188 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0925) Prec@1 81.000 (83.769) Prec@5 100.000 (98.969) +2022-11-14 13:54:59,198 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0925) Prec@1 84.000 (83.773) Prec@5 100.000 (98.985) +2022-11-14 13:54:59,207 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0920) Prec@1 90.000 (83.866) Prec@5 100.000 (99.000) +2022-11-14 13:54:59,216 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0923) Prec@1 80.000 (83.809) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,226 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0919) Prec@1 88.000 (83.870) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,236 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.0922) Prec@1 79.000 (83.800) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,245 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0918) Prec@1 87.000 (83.845) Prec@5 98.000 (98.986) +2022-11-14 13:54:59,256 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0917) Prec@1 87.000 (83.889) Prec@5 100.000 (99.000) +2022-11-14 13:54:59,265 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0914) Prec@1 89.000 (83.959) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,274 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0913) Prec@1 87.000 (84.000) Prec@5 100.000 (99.014) +2022-11-14 13:54:59,283 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0915) Prec@1 83.000 (83.987) Prec@5 99.000 (99.013) +2022-11-14 13:54:59,292 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0915) Prec@1 86.000 (84.013) Prec@5 98.000 (99.000) +2022-11-14 13:54:59,301 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0915) Prec@1 81.000 (83.974) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,311 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0915) Prec@1 85.000 (83.987) Prec@5 97.000 (98.974) +2022-11-14 13:54:59,320 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0916) Prec@1 82.000 (83.962) Prec@5 100.000 (98.987) +2022-11-14 13:54:59,329 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0917) Prec@1 84.000 (83.963) Prec@5 99.000 (98.987) +2022-11-14 13:54:59,339 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0919) Prec@1 82.000 (83.938) Prec@5 97.000 (98.963) +2022-11-14 13:54:59,348 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0920) Prec@1 84.000 (83.939) Prec@5 99.000 (98.963) +2022-11-14 13:54:59,356 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0923) Prec@1 81.000 (83.904) Prec@5 100.000 (98.976) +2022-11-14 13:54:59,366 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0922) Prec@1 87.000 (83.940) Prec@5 100.000 (98.988) +2022-11-14 13:54:59,375 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0923) Prec@1 80.000 (83.894) Prec@5 98.000 (98.976) +2022-11-14 13:54:59,384 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1264 (0.0927) Prec@1 77.000 (83.814) Prec@5 100.000 (98.988) +2022-11-14 13:54:59,393 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0926) Prec@1 86.000 (83.839) Prec@5 99.000 (98.989) +2022-11-14 13:54:59,403 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0923) Prec@1 90.000 (83.909) Prec@5 99.000 (98.989) +2022-11-14 13:54:59,412 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0925) Prec@1 82.000 (83.888) Prec@5 99.000 (98.989) +2022-11-14 13:54:59,421 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0923) Prec@1 87.000 (83.922) Prec@5 99.000 (98.989) +2022-11-14 13:54:59,431 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0921) Prec@1 88.000 (83.967) Prec@5 100.000 (99.000) +2022-11-14 13:54:59,440 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0917) Prec@1 91.000 (84.043) Prec@5 100.000 (99.011) +2022-11-14 13:54:59,449 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0919) Prec@1 81.000 (84.011) Prec@5 99.000 (99.011) +2022-11-14 13:54:59,458 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0917) Prec@1 88.000 (84.053) Prec@5 98.000 (99.000) +2022-11-14 13:54:59,467 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0918) Prec@1 83.000 (84.042) Prec@5 99.000 (99.000) +2022-11-14 13:54:59,476 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0916) Prec@1 87.000 (84.073) Prec@5 100.000 (99.010) +2022-11-14 13:54:59,485 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0914) Prec@1 88.000 (84.113) Prec@5 100.000 (99.021) +2022-11-14 13:54:59,493 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1253 (0.0917) Prec@1 79.000 (84.061) Prec@5 99.000 (99.020) +2022-11-14 13:54:59,501 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0917) Prec@1 87.000 (84.091) Prec@5 98.000 (99.010) +2022-11-14 13:54:59,509 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0915) Prec@1 89.000 (84.140) Prec@5 98.000 (99.000) +2022-11-14 13:54:59,575 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:54:59,889 Epoch: [116][0/500] Time 0.025 (0.025) Data 0.233 (0.233) Loss 0.0679 (0.0679) Prec@1 88.000 (88.000) Prec@5 98.000 (98.000) +2022-11-14 13:55:00,093 Epoch: [116][10/500] Time 0.016 (0.019) Data 0.002 (0.023) Loss 0.0733 (0.0706) Prec@1 88.000 (88.000) Prec@5 99.000 (98.500) +2022-11-14 13:55:00,288 Epoch: [116][20/500] Time 0.019 (0.018) Data 0.001 (0.013) Loss 0.0597 (0.0670) Prec@1 88.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 13:55:00,530 Epoch: [116][30/500] Time 0.023 (0.019) Data 0.002 (0.009) Loss 0.0582 (0.0648) Prec@1 92.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:55:00,783 Epoch: [116][40/500] Time 0.022 (0.020) Data 0.002 (0.007) Loss 0.0667 (0.0651) Prec@1 89.000 (89.000) Prec@5 98.000 (98.800) +2022-11-14 13:55:01,038 Epoch: [116][50/500] Time 0.024 (0.020) Data 0.002 (0.006) Loss 0.0600 (0.0643) Prec@1 89.000 (89.000) Prec@5 99.000 (98.833) +2022-11-14 13:55:01,290 Epoch: [116][60/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0906 (0.0680) Prec@1 82.000 (88.000) Prec@5 99.000 (98.857) +2022-11-14 13:55:01,545 Epoch: [116][70/500] Time 0.023 (0.021) Data 0.002 (0.005) Loss 0.0730 (0.0687) Prec@1 90.000 (88.250) Prec@5 98.000 (98.750) +2022-11-14 13:55:01,801 Epoch: [116][80/500] Time 0.024 (0.021) Data 0.002 (0.004) Loss 0.0585 (0.0675) Prec@1 90.000 (88.444) Prec@5 100.000 (98.889) +2022-11-14 13:55:02,057 Epoch: [116][90/500] Time 0.021 (0.021) Data 0.002 (0.004) Loss 0.0371 (0.0645) Prec@1 95.000 (89.100) Prec@5 100.000 (99.000) +2022-11-14 13:55:02,312 Epoch: [116][100/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0464 (0.0628) Prec@1 92.000 (89.364) Prec@5 100.000 (99.091) +2022-11-14 13:55:02,654 Epoch: [116][110/500] Time 0.033 (0.022) Data 0.002 (0.004) Loss 0.0520 (0.0619) Prec@1 92.000 (89.583) Prec@5 99.000 (99.083) +2022-11-14 13:55:03,008 Epoch: [116][120/500] Time 0.033 (0.023) Data 0.002 (0.004) Loss 0.0713 (0.0627) Prec@1 87.000 (89.385) Prec@5 100.000 (99.154) +2022-11-14 13:55:03,363 Epoch: [116][130/500] Time 0.033 (0.024) Data 0.002 (0.003) Loss 0.0538 (0.0620) Prec@1 91.000 (89.500) Prec@5 99.000 (99.143) +2022-11-14 13:55:03,713 Epoch: [116][140/500] Time 0.034 (0.024) Data 0.002 (0.003) Loss 0.0777 (0.0631) Prec@1 85.000 (89.200) Prec@5 100.000 (99.200) +2022-11-14 13:55:04,063 Epoch: [116][150/500] Time 0.034 (0.025) Data 0.002 (0.003) Loss 0.0360 (0.0614) Prec@1 94.000 (89.500) Prec@5 100.000 (99.250) +2022-11-14 13:55:04,413 Epoch: [116][160/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0774 (0.0623) Prec@1 86.000 (89.294) Prec@5 100.000 (99.294) +2022-11-14 13:55:04,762 Epoch: [116][170/500] Time 0.033 (0.025) Data 0.001 (0.003) Loss 0.0705 (0.0628) Prec@1 87.000 (89.167) Prec@5 100.000 (99.333) +2022-11-14 13:55:05,115 Epoch: [116][180/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.0509 (0.0621) Prec@1 92.000 (89.316) Prec@5 100.000 (99.368) +2022-11-14 13:55:05,473 Epoch: [116][190/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0806 (0.0631) Prec@1 86.000 (89.150) Prec@5 98.000 (99.300) +2022-11-14 13:55:05,835 Epoch: [116][200/500] Time 0.032 (0.026) Data 0.002 (0.003) Loss 0.0578 (0.0628) Prec@1 89.000 (89.143) Prec@5 99.000 (99.286) +2022-11-14 13:55:06,188 Epoch: [116][210/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0672 (0.0630) Prec@1 89.000 (89.136) Prec@5 99.000 (99.273) +2022-11-14 13:55:06,540 Epoch: [116][220/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0816 (0.0638) Prec@1 87.000 (89.043) Prec@5 99.000 (99.261) +2022-11-14 13:55:06,893 Epoch: [116][230/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0477 (0.0632) Prec@1 92.000 (89.167) Prec@5 98.000 (99.208) +2022-11-14 13:55:07,248 Epoch: [116][240/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0550 (0.0628) Prec@1 94.000 (89.360) Prec@5 100.000 (99.240) +2022-11-14 13:55:07,606 Epoch: [116][250/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0735 (0.0632) Prec@1 89.000 (89.346) Prec@5 99.000 (99.231) +2022-11-14 13:55:07,959 Epoch: [116][260/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0887 (0.0642) Prec@1 87.000 (89.259) Prec@5 99.000 (99.222) +2022-11-14 13:55:08,311 Epoch: [116][270/500] Time 0.033 (0.028) Data 0.001 (0.003) Loss 0.0633 (0.0641) Prec@1 88.000 (89.214) Prec@5 100.000 (99.250) +2022-11-14 13:55:08,668 Epoch: [116][280/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0880 (0.0650) Prec@1 86.000 (89.103) Prec@5 99.000 (99.241) +2022-11-14 13:55:09,023 Epoch: [116][290/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.0430 (0.0642) Prec@1 94.000 (89.267) Prec@5 100.000 (99.267) +2022-11-14 13:55:09,376 Epoch: [116][300/500] Time 0.034 (0.028) Data 0.001 (0.003) Loss 0.0869 (0.0650) Prec@1 86.000 (89.161) Prec@5 100.000 (99.290) +2022-11-14 13:55:09,726 Epoch: [116][310/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0891 (0.0657) Prec@1 85.000 (89.031) Prec@5 100.000 (99.312) +2022-11-14 13:55:10,077 Epoch: [116][320/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.0747 (0.0660) Prec@1 89.000 (89.030) Prec@5 100.000 (99.333) +2022-11-14 13:55:10,430 Epoch: [116][330/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.0604 (0.0658) Prec@1 91.000 (89.088) Prec@5 100.000 (99.353) +2022-11-14 13:55:10,785 Epoch: [116][340/500] Time 0.033 (0.028) Data 0.002 (0.002) Loss 0.0746 (0.0661) Prec@1 88.000 (89.057) Prec@5 100.000 (99.371) +2022-11-14 13:55:11,146 Epoch: [116][350/500] Time 0.034 (0.028) Data 0.002 (0.002) Loss 0.0373 (0.0653) Prec@1 95.000 (89.222) Prec@5 100.000 (99.389) +2022-11-14 13:55:11,503 Epoch: [116][360/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0584 (0.0651) Prec@1 91.000 (89.270) Prec@5 100.000 (99.405) +2022-11-14 13:55:11,857 Epoch: [116][370/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0822 (0.0655) Prec@1 88.000 (89.237) Prec@5 100.000 (99.421) +2022-11-14 13:55:12,220 Epoch: [116][380/500] Time 0.037 (0.029) Data 0.002 (0.002) Loss 0.0803 (0.0659) Prec@1 86.000 (89.154) Prec@5 97.000 (99.359) +2022-11-14 13:55:12,567 Epoch: [116][390/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0437 (0.0654) Prec@1 93.000 (89.250) Prec@5 100.000 (99.375) +2022-11-14 13:55:12,922 Epoch: [116][400/500] Time 0.035 (0.029) Data 0.002 (0.002) Loss 0.0701 (0.0655) Prec@1 87.000 (89.195) Prec@5 99.000 (99.366) +2022-11-14 13:55:13,278 Epoch: [116][410/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0362 (0.0648) Prec@1 94.000 (89.310) Prec@5 100.000 (99.381) +2022-11-14 13:55:13,633 Epoch: [116][420/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0426 (0.0643) Prec@1 92.000 (89.372) Prec@5 100.000 (99.395) +2022-11-14 13:55:13,987 Epoch: [116][430/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0608 (0.0642) Prec@1 90.000 (89.386) Prec@5 100.000 (99.409) +2022-11-14 13:55:14,339 Epoch: [116][440/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0453 (0.0638) Prec@1 92.000 (89.444) Prec@5 100.000 (99.422) +2022-11-14 13:55:14,701 Epoch: [116][450/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0746 (0.0640) Prec@1 89.000 (89.435) Prec@5 100.000 (99.435) +2022-11-14 13:55:15,049 Epoch: [116][460/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0569 (0.0639) Prec@1 89.000 (89.426) Prec@5 99.000 (99.426) +2022-11-14 13:55:15,410 Epoch: [116][470/500] Time 0.036 (0.029) Data 0.002 (0.002) Loss 0.0759 (0.0641) Prec@1 87.000 (89.375) Prec@5 100.000 (99.438) +2022-11-14 13:55:15,767 Epoch: [116][480/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0623 (0.0641) Prec@1 90.000 (89.388) Prec@5 100.000 (99.449) +2022-11-14 13:55:16,121 Epoch: [116][490/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0793 (0.0644) Prec@1 85.000 (89.300) Prec@5 100.000 (99.460) +2022-11-14 13:55:16,438 Epoch: [116][499/500] Time 0.034 (0.029) Data 0.001 (0.002) Loss 0.0565 (0.0642) Prec@1 93.000 (89.373) Prec@5 98.000 (99.431) +2022-11-14 13:55:16,718 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0936 (0.0936) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 13:55:16,726 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1081 (0.1008) Prec@1 81.000 (83.000) Prec@5 97.000 (97.500) +2022-11-14 13:55:16,736 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.1017) Prec@1 84.000 (83.333) Prec@5 100.000 (98.333) +2022-11-14 13:55:16,747 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.1039) Prec@1 84.000 (83.500) Prec@5 98.000 (98.250) +2022-11-14 13:55:16,756 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.1049) Prec@1 80.000 (82.800) Prec@5 100.000 (98.600) +2022-11-14 13:55:16,764 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.1000) Prec@1 87.000 (83.500) Prec@5 100.000 (98.833) +2022-11-14 13:55:16,773 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0954) Prec@1 89.000 (84.286) Prec@5 100.000 (99.000) +2022-11-14 13:55:16,783 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1488 (0.1020) Prec@1 76.000 (83.250) Prec@5 98.000 (98.875) +2022-11-14 13:55:16,791 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.1025) Prec@1 86.000 (83.556) Prec@5 99.000 (98.889) +2022-11-14 13:55:16,799 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0995) Prec@1 87.000 (83.900) Prec@5 99.000 (98.900) +2022-11-14 13:55:16,808 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0973) Prec@1 87.000 (84.182) Prec@5 100.000 (99.000) +2022-11-14 13:55:16,817 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0984) Prec@1 82.000 (84.000) Prec@5 98.000 (98.917) +2022-11-14 13:55:16,825 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0988) Prec@1 81.000 (83.769) Prec@5 99.000 (98.923) +2022-11-14 13:55:16,833 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0991) Prec@1 81.000 (83.571) Prec@5 98.000 (98.857) +2022-11-14 13:55:16,842 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0991) Prec@1 83.000 (83.533) Prec@5 99.000 (98.867) +2022-11-14 13:55:16,852 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1719 (0.1037) Prec@1 75.000 (83.000) Prec@5 98.000 (98.812) +2022-11-14 13:55:16,861 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.1035) Prec@1 83.000 (83.000) Prec@5 96.000 (98.647) +2022-11-14 13:55:16,870 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.1041) Prec@1 83.000 (83.000) Prec@5 100.000 (98.722) +2022-11-14 13:55:16,879 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.1037) Prec@1 84.000 (83.053) Prec@5 98.000 (98.684) +2022-11-14 13:55:16,888 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.1037) Prec@1 83.000 (83.050) Prec@5 98.000 (98.650) +2022-11-14 13:55:16,897 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1318 (0.1050) Prec@1 80.000 (82.905) Prec@5 97.000 (98.571) +2022-11-14 13:55:16,907 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1176 (0.1056) Prec@1 82.000 (82.864) Prec@5 98.000 (98.545) +2022-11-14 13:55:16,916 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1154 (0.1060) Prec@1 81.000 (82.783) Prec@5 97.000 (98.478) +2022-11-14 13:55:16,925 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.1056) Prec@1 82.000 (82.750) Prec@5 99.000 (98.500) +2022-11-14 13:55:16,935 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.1056) Prec@1 80.000 (82.640) Prec@5 100.000 (98.560) +2022-11-14 13:55:16,944 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.1056) Prec@1 82.000 (82.615) Prec@5 97.000 (98.500) +2022-11-14 13:55:16,953 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1235 (0.1063) Prec@1 77.000 (82.407) Prec@5 98.000 (98.481) +2022-11-14 13:55:16,962 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.1063) Prec@1 81.000 (82.357) Prec@5 98.000 (98.464) +2022-11-14 13:55:16,972 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.1060) Prec@1 84.000 (82.414) Prec@5 97.000 (98.414) +2022-11-14 13:55:16,981 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1210 (0.1065) Prec@1 81.000 (82.367) Prec@5 97.000 (98.367) +2022-11-14 13:55:16,990 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.1062) Prec@1 82.000 (82.355) Prec@5 100.000 (98.419) +2022-11-14 13:55:17,000 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.1064) Prec@1 81.000 (82.312) Prec@5 97.000 (98.375) +2022-11-14 13:55:17,008 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.1066) Prec@1 80.000 (82.242) Prec@5 99.000 (98.394) +2022-11-14 13:55:17,018 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1213 (0.1071) Prec@1 74.000 (82.000) Prec@5 100.000 (98.441) +2022-11-14 13:55:17,027 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.1070) Prec@1 82.000 (82.000) Prec@5 97.000 (98.400) +2022-11-14 13:55:17,036 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.1068) Prec@1 84.000 (82.056) Prec@5 100.000 (98.444) +2022-11-14 13:55:17,045 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.1068) Prec@1 86.000 (82.162) Prec@5 97.000 (98.405) +2022-11-14 13:55:17,056 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1449 (0.1078) Prec@1 76.000 (82.000) Prec@5 99.000 (98.421) +2022-11-14 13:55:17,065 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.1074) Prec@1 86.000 (82.103) Prec@5 99.000 (98.436) +2022-11-14 13:55:17,074 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.1069) Prec@1 83.000 (82.125) Prec@5 100.000 (98.475) +2022-11-14 13:55:17,083 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.1068) Prec@1 85.000 (82.195) Prec@5 95.000 (98.390) +2022-11-14 13:55:17,092 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.1071) Prec@1 81.000 (82.167) Prec@5 98.000 (98.381) +2022-11-14 13:55:17,101 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1122 (0.1072) Prec@1 80.000 (82.116) Prec@5 97.000 (98.349) +2022-11-14 13:55:17,110 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.1068) Prec@1 87.000 (82.227) Prec@5 98.000 (98.341) +2022-11-14 13:55:17,118 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.1061) Prec@1 89.000 (82.378) Prec@5 99.000 (98.356) +2022-11-14 13:55:17,127 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1172 (0.1064) Prec@1 78.000 (82.283) Prec@5 99.000 (98.370) +2022-11-14 13:55:17,135 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.1065) Prec@1 81.000 (82.255) Prec@5 100.000 (98.404) +2022-11-14 13:55:17,144 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1262 (0.1069) Prec@1 77.000 (82.146) Prec@5 100.000 (98.438) +2022-11-14 13:55:17,152 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.1071) Prec@1 81.000 (82.122) Prec@5 100.000 (98.469) +2022-11-14 13:55:17,161 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1308 (0.1076) Prec@1 77.000 (82.020) Prec@5 99.000 (98.480) +2022-11-14 13:55:17,170 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.1074) Prec@1 83.000 (82.039) Prec@5 98.000 (98.471) +2022-11-14 13:55:17,179 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1248 (0.1077) Prec@1 77.000 (81.942) Prec@5 98.000 (98.462) +2022-11-14 13:55:17,187 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1163 (0.1079) Prec@1 78.000 (81.868) Prec@5 100.000 (98.491) +2022-11-14 13:55:17,196 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.1077) Prec@1 83.000 (81.889) Prec@5 100.000 (98.519) +2022-11-14 13:55:17,205 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.1072) Prec@1 85.000 (81.945) Prec@5 100.000 (98.545) +2022-11-14 13:55:17,215 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1290 (0.1076) Prec@1 77.000 (81.857) Prec@5 99.000 (98.554) +2022-11-14 13:55:17,224 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.1073) Prec@1 85.000 (81.912) Prec@5 98.000 (98.544) +2022-11-14 13:55:17,233 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.1072) Prec@1 83.000 (81.931) Prec@5 98.000 (98.534) +2022-11-14 13:55:17,243 Test: [58/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1315 (0.1076) Prec@1 79.000 (81.881) Prec@5 98.000 (98.525) +2022-11-14 13:55:17,254 Test: [59/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.1076) Prec@1 82.000 (81.883) Prec@5 98.000 (98.517) +2022-11-14 13:55:17,267 Test: [60/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.1074) Prec@1 83.000 (81.902) Prec@5 100.000 (98.541) +2022-11-14 13:55:17,279 Test: [61/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1243 (0.1077) Prec@1 79.000 (81.855) Prec@5 99.000 (98.548) +2022-11-14 13:55:17,290 Test: [62/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.1072) Prec@1 88.000 (81.952) Prec@5 100.000 (98.571) +2022-11-14 13:55:17,302 Test: [63/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.1070) Prec@1 85.000 (82.000) Prec@5 99.000 (98.578) +2022-11-14 13:55:17,314 Test: [64/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1258 (0.1072) Prec@1 81.000 (81.985) Prec@5 99.000 (98.585) +2022-11-14 13:55:17,325 Test: [65/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1334 (0.1076) Prec@1 78.000 (81.924) Prec@5 99.000 (98.591) +2022-11-14 13:55:17,335 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.1070) Prec@1 87.000 (82.000) Prec@5 99.000 (98.597) +2022-11-14 13:55:17,345 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.1068) Prec@1 82.000 (82.000) Prec@5 100.000 (98.618) +2022-11-14 13:55:17,354 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.1067) Prec@1 86.000 (82.058) Prec@5 98.000 (98.609) +2022-11-14 13:55:17,363 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.1066) Prec@1 84.000 (82.086) Prec@5 98.000 (98.600) +2022-11-14 13:55:17,373 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1431 (0.1072) Prec@1 77.000 (82.014) Prec@5 96.000 (98.563) +2022-11-14 13:55:17,382 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.1072) Prec@1 79.000 (81.972) Prec@5 100.000 (98.583) +2022-11-14 13:55:17,391 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.1066) Prec@1 85.000 (82.014) Prec@5 100.000 (98.603) +2022-11-14 13:55:17,400 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.1065) Prec@1 81.000 (82.000) Prec@5 99.000 (98.608) +2022-11-14 13:55:17,408 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1315 (0.1068) Prec@1 77.000 (81.933) Prec@5 99.000 (98.613) +2022-11-14 13:55:17,416 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.1064) Prec@1 87.000 (82.000) Prec@5 100.000 (98.632) +2022-11-14 13:55:17,425 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.1067) Prec@1 77.000 (81.935) Prec@5 100.000 (98.649) +2022-11-14 13:55:17,435 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1389 (0.1071) Prec@1 77.000 (81.872) Prec@5 98.000 (98.641) +2022-11-14 13:55:17,444 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.1069) Prec@1 85.000 (81.911) Prec@5 100.000 (98.658) +2022-11-14 13:55:17,453 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1236 (0.1071) Prec@1 78.000 (81.862) Prec@5 99.000 (98.662) +2022-11-14 13:55:17,463 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.1069) Prec@1 84.000 (81.889) Prec@5 98.000 (98.654) +2022-11-14 13:55:17,473 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.1069) Prec@1 81.000 (81.878) Prec@5 99.000 (98.659) +2022-11-14 13:55:17,482 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.1069) Prec@1 82.000 (81.880) Prec@5 98.000 (98.651) +2022-11-14 13:55:17,492 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.1068) Prec@1 84.000 (81.905) Prec@5 100.000 (98.667) +2022-11-14 13:55:17,502 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.1069) Prec@1 79.000 (81.871) Prec@5 98.000 (98.659) +2022-11-14 13:55:17,512 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1294 (0.1072) Prec@1 80.000 (81.849) Prec@5 96.000 (98.628) +2022-11-14 13:55:17,523 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.1070) Prec@1 85.000 (81.885) Prec@5 99.000 (98.632) +2022-11-14 13:55:17,533 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.1069) Prec@1 80.000 (81.864) Prec@5 99.000 (98.636) +2022-11-14 13:55:17,542 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.1069) Prec@1 81.000 (81.854) Prec@5 98.000 (98.629) +2022-11-14 13:55:17,552 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.1069) Prec@1 85.000 (81.889) Prec@5 99.000 (98.633) +2022-11-14 13:55:17,562 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1198 (0.1070) Prec@1 79.000 (81.857) Prec@5 100.000 (98.648) +2022-11-14 13:55:17,571 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.1068) Prec@1 86.000 (81.902) Prec@5 98.000 (98.641) +2022-11-14 13:55:17,580 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.1069) Prec@1 82.000 (81.903) Prec@5 98.000 (98.634) +2022-11-14 13:55:17,589 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.1068) Prec@1 82.000 (81.904) Prec@5 98.000 (98.628) +2022-11-14 13:55:17,598 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.1066) Prec@1 85.000 (81.937) Prec@5 98.000 (98.621) +2022-11-14 13:55:17,607 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.1066) Prec@1 82.000 (81.938) Prec@5 98.000 (98.615) +2022-11-14 13:55:17,617 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.1062) Prec@1 88.000 (82.000) Prec@5 98.000 (98.608) +2022-11-14 13:55:17,625 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1354 (0.1065) Prec@1 80.000 (81.980) Prec@5 97.000 (98.592) +2022-11-14 13:55:17,633 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1209 (0.1066) Prec@1 80.000 (81.960) Prec@5 97.000 (98.576) +2022-11-14 13:55:17,644 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.1067) Prec@1 80.000 (81.940) Prec@5 99.000 (98.580) +2022-11-14 13:55:17,703 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:55:18,001 Epoch: [117][0/500] Time 0.030 (0.030) Data 0.216 (0.216) Loss 0.0901 (0.0901) Prec@1 87.000 (87.000) Prec@5 97.000 (97.000) +2022-11-14 13:55:18,234 Epoch: [117][10/500] Time 0.020 (0.021) Data 0.002 (0.021) Loss 0.0839 (0.0870) Prec@1 86.000 (86.500) Prec@5 100.000 (98.500) +2022-11-14 13:55:18,484 Epoch: [117][20/500] Time 0.021 (0.022) Data 0.002 (0.012) Loss 0.0684 (0.0808) Prec@1 89.000 (87.333) Prec@5 100.000 (99.000) +2022-11-14 13:55:18,924 Epoch: [117][30/500] Time 0.043 (0.027) Data 0.002 (0.009) Loss 0.0657 (0.0770) Prec@1 89.000 (87.750) Prec@5 100.000 (99.250) +2022-11-14 13:55:19,384 Epoch: [117][40/500] Time 0.043 (0.030) Data 0.002 (0.007) Loss 0.0705 (0.0757) Prec@1 88.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 13:55:19,843 Epoch: [117][50/500] Time 0.042 (0.032) Data 0.002 (0.006) Loss 0.0682 (0.0745) Prec@1 90.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 13:55:20,303 Epoch: [117][60/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0602 (0.0724) Prec@1 90.000 (88.429) Prec@5 99.000 (99.286) +2022-11-14 13:55:20,764 Epoch: [117][70/500] Time 0.044 (0.035) Data 0.002 (0.005) Loss 0.0573 (0.0705) Prec@1 90.000 (88.625) Prec@5 100.000 (99.375) +2022-11-14 13:55:21,220 Epoch: [117][80/500] Time 0.043 (0.036) Data 0.002 (0.005) Loss 0.0661 (0.0700) Prec@1 89.000 (88.667) Prec@5 100.000 (99.444) +2022-11-14 13:55:21,681 Epoch: [117][90/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0609 (0.0691) Prec@1 89.000 (88.700) Prec@5 100.000 (99.500) +2022-11-14 13:55:22,148 Epoch: [117][100/500] Time 0.049 (0.037) Data 0.002 (0.004) Loss 0.0678 (0.0690) Prec@1 88.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 13:55:22,622 Epoch: [117][110/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0699 (0.0691) Prec@1 87.000 (88.500) Prec@5 98.000 (99.417) +2022-11-14 13:55:23,091 Epoch: [117][120/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0467 (0.0674) Prec@1 91.000 (88.692) Prec@5 100.000 (99.462) +2022-11-14 13:55:23,560 Epoch: [117][130/500] Time 0.049 (0.038) Data 0.002 (0.004) Loss 0.0680 (0.0674) Prec@1 89.000 (88.714) Prec@5 100.000 (99.500) +2022-11-14 13:55:24,020 Epoch: [117][140/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0704 (0.0676) Prec@1 88.000 (88.667) Prec@5 100.000 (99.533) +2022-11-14 13:55:24,510 Epoch: [117][150/500] Time 0.059 (0.038) Data 0.002 (0.003) Loss 0.0734 (0.0680) Prec@1 89.000 (88.688) Prec@5 100.000 (99.562) +2022-11-14 13:55:25,068 Epoch: [117][160/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0517 (0.0670) Prec@1 91.000 (88.824) Prec@5 100.000 (99.588) +2022-11-14 13:55:25,600 Epoch: [117][170/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0635 (0.0668) Prec@1 90.000 (88.889) Prec@5 100.000 (99.611) +2022-11-14 13:55:26,110 Epoch: [117][180/500] Time 0.066 (0.040) Data 0.002 (0.003) Loss 0.0669 (0.0668) Prec@1 88.000 (88.842) Prec@5 100.000 (99.632) +2022-11-14 13:55:26,604 Epoch: [117][190/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0779 (0.0674) Prec@1 86.000 (88.700) Prec@5 100.000 (99.650) +2022-11-14 13:55:27,151 Epoch: [117][200/500] Time 0.041 (0.040) Data 0.001 (0.003) Loss 0.0686 (0.0674) Prec@1 89.000 (88.714) Prec@5 100.000 (99.667) +2022-11-14 13:55:27,715 Epoch: [117][210/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0677 (0.0674) Prec@1 88.000 (88.682) Prec@5 99.000 (99.636) +2022-11-14 13:55:28,283 Epoch: [117][220/500] Time 0.091 (0.041) Data 0.002 (0.003) Loss 0.0792 (0.0679) Prec@1 88.000 (88.652) Prec@5 100.000 (99.652) +2022-11-14 13:55:28,884 Epoch: [117][230/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0611 (0.0677) Prec@1 87.000 (88.583) Prec@5 100.000 (99.667) +2022-11-14 13:55:29,458 Epoch: [117][240/500] Time 0.037 (0.042) Data 0.001 (0.003) Loss 0.0543 (0.0671) Prec@1 91.000 (88.680) Prec@5 99.000 (99.640) +2022-11-14 13:55:29,981 Epoch: [117][250/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0926 (0.0681) Prec@1 87.000 (88.615) Prec@5 98.000 (99.577) +2022-11-14 13:55:30,541 Epoch: [117][260/500] Time 0.092 (0.043) Data 0.002 (0.003) Loss 0.0519 (0.0675) Prec@1 91.000 (88.704) Prec@5 100.000 (99.593) +2022-11-14 13:55:31,031 Epoch: [117][270/500] Time 0.033 (0.043) Data 0.002 (0.003) Loss 0.0622 (0.0673) Prec@1 89.000 (88.714) Prec@5 100.000 (99.607) +2022-11-14 13:55:31,576 Epoch: [117][280/500] Time 0.056 (0.043) Data 0.002 (0.003) Loss 0.0821 (0.0678) Prec@1 88.000 (88.690) Prec@5 98.000 (99.552) +2022-11-14 13:55:31,895 Epoch: [117][290/500] Time 0.024 (0.042) Data 0.002 (0.003) Loss 0.0694 (0.0679) Prec@1 88.000 (88.667) Prec@5 98.000 (99.500) +2022-11-14 13:55:32,189 Epoch: [117][300/500] Time 0.024 (0.042) Data 0.002 (0.003) Loss 0.0602 (0.0676) Prec@1 88.000 (88.645) Prec@5 100.000 (99.516) +2022-11-14 13:55:32,493 Epoch: [117][310/500] Time 0.027 (0.041) Data 0.002 (0.003) Loss 0.1306 (0.0696) Prec@1 77.000 (88.281) Prec@5 99.000 (99.500) +2022-11-14 13:55:32,784 Epoch: [117][320/500] Time 0.026 (0.041) Data 0.002 (0.003) Loss 0.0579 (0.0692) Prec@1 91.000 (88.364) Prec@5 100.000 (99.515) +2022-11-14 13:55:33,077 Epoch: [117][330/500] Time 0.027 (0.040) Data 0.002 (0.003) Loss 0.0445 (0.0685) Prec@1 92.000 (88.471) Prec@5 100.000 (99.529) +2022-11-14 13:55:33,413 Epoch: [117][340/500] Time 0.025 (0.040) Data 0.002 (0.003) Loss 0.0774 (0.0688) Prec@1 85.000 (88.371) Prec@5 100.000 (99.543) +2022-11-14 13:55:33,785 Epoch: [117][350/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0508 (0.0683) Prec@1 91.000 (88.444) Prec@5 100.000 (99.556) +2022-11-14 13:55:34,073 Epoch: [117][360/500] Time 0.026 (0.040) Data 0.001 (0.003) Loss 0.1390 (0.0702) Prec@1 75.000 (88.081) Prec@5 98.000 (99.514) +2022-11-14 13:55:34,396 Epoch: [117][370/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.0720 (0.0702) Prec@1 91.000 (88.158) Prec@5 99.000 (99.500) +2022-11-14 13:55:34,681 Epoch: [117][380/500] Time 0.025 (0.039) Data 0.002 (0.002) Loss 0.0718 (0.0703) Prec@1 88.000 (88.154) Prec@5 100.000 (99.513) +2022-11-14 13:55:34,978 Epoch: [117][390/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.0660 (0.0702) Prec@1 90.000 (88.200) Prec@5 100.000 (99.525) +2022-11-14 13:55:35,272 Epoch: [117][400/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0927 (0.0707) Prec@1 82.000 (88.049) Prec@5 98.000 (99.488) +2022-11-14 13:55:35,611 Epoch: [117][410/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0697 (0.0707) Prec@1 90.000 (88.095) Prec@5 98.000 (99.452) +2022-11-14 13:55:35,911 Epoch: [117][420/500] Time 0.024 (0.038) Data 0.002 (0.002) Loss 0.0918 (0.0712) Prec@1 84.000 (88.000) Prec@5 98.000 (99.419) +2022-11-14 13:55:36,204 Epoch: [117][430/500] Time 0.027 (0.038) Data 0.001 (0.002) Loss 0.0982 (0.0718) Prec@1 84.000 (87.909) Prec@5 99.000 (99.409) +2022-11-14 13:55:36,501 Epoch: [117][440/500] Time 0.028 (0.037) Data 0.002 (0.002) Loss 0.0860 (0.0721) Prec@1 84.000 (87.822) Prec@5 100.000 (99.422) +2022-11-14 13:55:36,807 Epoch: [117][450/500] Time 0.025 (0.037) Data 0.002 (0.002) Loss 0.0663 (0.0720) Prec@1 88.000 (87.826) Prec@5 100.000 (99.435) +2022-11-14 13:55:37,098 Epoch: [117][460/500] Time 0.028 (0.037) Data 0.002 (0.002) Loss 0.0672 (0.0719) Prec@1 88.000 (87.830) Prec@5 99.000 (99.426) +2022-11-14 13:55:37,440 Epoch: [117][470/500] Time 0.056 (0.037) Data 0.002 (0.002) Loss 0.0712 (0.0719) Prec@1 91.000 (87.896) Prec@5 98.000 (99.396) +2022-11-14 13:55:37,905 Epoch: [117][480/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0523 (0.0715) Prec@1 94.000 (88.020) Prec@5 100.000 (99.408) +2022-11-14 13:55:38,369 Epoch: [117][490/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0841 (0.0717) Prec@1 86.000 (87.980) Prec@5 98.000 (99.380) +2022-11-14 13:55:38,788 Epoch: [117][499/500] Time 0.044 (0.037) Data 0.001 (0.002) Loss 0.0760 (0.0718) Prec@1 85.000 (87.922) Prec@5 100.000 (99.392) +2022-11-14 13:55:39,068 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0797 (0.0797) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:55:39,076 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0788) Prec@1 87.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 13:55:39,088 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1198 (0.0925) Prec@1 77.000 (83.333) Prec@5 100.000 (99.667) +2022-11-14 13:55:39,098 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0955) Prec@1 83.000 (83.250) Prec@5 98.000 (99.250) +2022-11-14 13:55:39,106 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0988) Prec@1 79.000 (82.400) Prec@5 99.000 (99.200) +2022-11-14 13:55:39,115 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0927) Prec@1 90.000 (83.667) Prec@5 99.000 (99.167) +2022-11-14 13:55:39,124 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0911) Prec@1 84.000 (83.714) Prec@5 100.000 (99.286) +2022-11-14 13:55:39,134 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.0945) Prec@1 78.000 (83.000) Prec@5 97.000 (99.000) +2022-11-14 13:55:39,143 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1266 (0.0981) Prec@1 78.000 (82.444) Prec@5 98.000 (98.889) +2022-11-14 13:55:39,154 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0958) Prec@1 86.000 (82.800) Prec@5 98.000 (98.800) +2022-11-14 13:55:39,164 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0954) Prec@1 83.000 (82.818) Prec@5 99.000 (98.818) +2022-11-14 13:55:39,175 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0951) Prec@1 84.000 (82.917) Prec@5 99.000 (98.833) +2022-11-14 13:55:39,187 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0951) Prec@1 83.000 (82.923) Prec@5 100.000 (98.923) +2022-11-14 13:55:39,198 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0935) Prec@1 88.000 (83.286) Prec@5 99.000 (98.929) +2022-11-14 13:55:39,210 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0930) Prec@1 86.000 (83.467) Prec@5 98.000 (98.867) +2022-11-14 13:55:39,222 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0926) Prec@1 83.000 (83.438) Prec@5 99.000 (98.875) +2022-11-14 13:55:39,233 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0910) Prec@1 90.000 (83.824) Prec@5 98.000 (98.824) +2022-11-14 13:55:39,244 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0916) Prec@1 84.000 (83.833) Prec@5 98.000 (98.778) +2022-11-14 13:55:39,256 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0917) Prec@1 84.000 (83.842) Prec@5 95.000 (98.579) +2022-11-14 13:55:39,266 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0928) Prec@1 80.000 (83.650) Prec@5 98.000 (98.550) +2022-11-14 13:55:39,278 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0935) Prec@1 84.000 (83.667) Prec@5 98.000 (98.524) +2022-11-14 13:55:39,290 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0929) Prec@1 88.000 (83.864) Prec@5 98.000 (98.500) +2022-11-14 13:55:39,300 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.0939) Prec@1 79.000 (83.652) Prec@5 97.000 (98.435) +2022-11-14 13:55:39,313 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0934) Prec@1 85.000 (83.708) Prec@5 100.000 (98.500) +2022-11-14 13:55:39,324 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0933) Prec@1 86.000 (83.800) Prec@5 100.000 (98.560) +2022-11-14 13:55:39,337 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.0943) Prec@1 80.000 (83.654) Prec@5 95.000 (98.423) +2022-11-14 13:55:39,350 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0938) Prec@1 83.000 (83.630) Prec@5 100.000 (98.481) +2022-11-14 13:55:39,362 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0934) Prec@1 87.000 (83.750) Prec@5 99.000 (98.500) +2022-11-14 13:55:39,375 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0932) Prec@1 83.000 (83.724) Prec@5 99.000 (98.517) +2022-11-14 13:55:39,387 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0930) Prec@1 86.000 (83.800) Prec@5 100.000 (98.567) +2022-11-14 13:55:39,397 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0925) Prec@1 87.000 (83.903) Prec@5 100.000 (98.613) +2022-11-14 13:55:39,410 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0929) Prec@1 85.000 (83.938) Prec@5 99.000 (98.625) +2022-11-14 13:55:39,421 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0932) Prec@1 83.000 (83.909) Prec@5 96.000 (98.545) +2022-11-14 13:55:39,432 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1198 (0.0940) Prec@1 77.000 (83.706) Prec@5 99.000 (98.559) +2022-11-14 13:55:39,444 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0941) Prec@1 81.000 (83.629) Prec@5 99.000 (98.571) +2022-11-14 13:55:39,456 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0935) Prec@1 88.000 (83.750) Prec@5 98.000 (98.556) +2022-11-14 13:55:39,467 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0932) Prec@1 83.000 (83.730) Prec@5 98.000 (98.541) +2022-11-14 13:55:39,480 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0934) Prec@1 81.000 (83.658) Prec@5 100.000 (98.579) +2022-11-14 13:55:39,492 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0929) Prec@1 88.000 (83.769) Prec@5 99.000 (98.590) +2022-11-14 13:55:39,504 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0926) Prec@1 85.000 (83.800) Prec@5 98.000 (98.575) +2022-11-14 13:55:39,516 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0929) Prec@1 83.000 (83.780) Prec@5 99.000 (98.585) +2022-11-14 13:55:39,528 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0926) Prec@1 85.000 (83.810) Prec@5 96.000 (98.524) +2022-11-14 13:55:39,540 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0923) Prec@1 85.000 (83.837) Prec@5 98.000 (98.512) +2022-11-14 13:55:39,552 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0917) Prec@1 89.000 (83.955) Prec@5 98.000 (98.500) +2022-11-14 13:55:39,565 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0920) Prec@1 82.000 (83.911) Prec@5 99.000 (98.511) +2022-11-14 13:55:39,577 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1223 (0.0926) Prec@1 78.000 (83.783) Prec@5 99.000 (98.522) +2022-11-14 13:55:39,590 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0929) Prec@1 82.000 (83.745) Prec@5 99.000 (98.532) +2022-11-14 13:55:39,601 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1232 (0.0935) Prec@1 78.000 (83.625) Prec@5 100.000 (98.562) +2022-11-14 13:55:39,613 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0933) Prec@1 87.000 (83.694) Prec@5 99.000 (98.571) +2022-11-14 13:55:39,625 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.0940) Prec@1 78.000 (83.580) Prec@5 98.000 (98.560) +2022-11-14 13:55:39,637 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0942) Prec@1 79.000 (83.490) Prec@5 100.000 (98.588) +2022-11-14 13:55:39,647 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0945) Prec@1 79.000 (83.404) Prec@5 99.000 (98.596) +2022-11-14 13:55:39,659 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1183 (0.0949) Prec@1 81.000 (83.358) Prec@5 99.000 (98.604) +2022-11-14 13:55:39,671 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0946) Prec@1 88.000 (83.444) Prec@5 98.000 (98.593) +2022-11-14 13:55:39,683 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0945) Prec@1 85.000 (83.473) Prec@5 100.000 (98.618) +2022-11-14 13:55:39,695 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0946) Prec@1 85.000 (83.500) Prec@5 99.000 (98.625) +2022-11-14 13:55:39,707 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0945) Prec@1 84.000 (83.509) Prec@5 100.000 (98.649) +2022-11-14 13:55:39,719 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0940) Prec@1 89.000 (83.603) Prec@5 99.000 (98.655) +2022-11-14 13:55:39,732 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0944) Prec@1 79.000 (83.525) Prec@5 100.000 (98.678) +2022-11-14 13:55:39,744 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0945) Prec@1 83.000 (83.517) Prec@5 100.000 (98.700) +2022-11-14 13:55:39,757 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0947) Prec@1 80.000 (83.459) Prec@5 99.000 (98.705) +2022-11-14 13:55:39,769 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0945) Prec@1 89.000 (83.548) Prec@5 99.000 (98.710) +2022-11-14 13:55:39,783 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0945) Prec@1 83.000 (83.540) Prec@5 100.000 (98.730) +2022-11-14 13:55:39,797 Test: [63/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0939) Prec@1 91.000 (83.656) Prec@5 100.000 (98.750) +2022-11-14 13:55:39,812 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1301 (0.0944) Prec@1 79.000 (83.585) Prec@5 98.000 (98.738) +2022-11-14 13:55:39,826 Test: [65/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0945) Prec@1 81.000 (83.545) Prec@5 99.000 (98.742) +2022-11-14 13:55:39,838 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0939) Prec@1 93.000 (83.687) Prec@5 100.000 (98.761) +2022-11-14 13:55:39,851 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0940) Prec@1 84.000 (83.691) Prec@5 97.000 (98.735) +2022-11-14 13:55:39,863 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0942) Prec@1 80.000 (83.638) Prec@5 98.000 (98.725) +2022-11-14 13:55:39,875 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0944) Prec@1 80.000 (83.586) Prec@5 99.000 (98.729) +2022-11-14 13:55:39,890 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0944) Prec@1 86.000 (83.620) Prec@5 99.000 (98.732) +2022-11-14 13:55:39,905 Test: [71/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0945) Prec@1 80.000 (83.569) Prec@5 99.000 (98.736) +2022-11-14 13:55:39,919 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0943) Prec@1 86.000 (83.603) Prec@5 99.000 (98.740) +2022-11-14 13:55:39,936 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0939) Prec@1 88.000 (83.662) Prec@5 100.000 (98.757) +2022-11-14 13:55:39,949 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0941) Prec@1 82.000 (83.640) Prec@5 99.000 (98.760) +2022-11-14 13:55:39,961 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0938) Prec@1 87.000 (83.684) Prec@5 99.000 (98.763) +2022-11-14 13:55:39,975 Test: [76/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0938) Prec@1 84.000 (83.688) Prec@5 98.000 (98.753) +2022-11-14 13:55:39,988 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0938) Prec@1 84.000 (83.692) Prec@5 98.000 (98.744) +2022-11-14 13:55:39,999 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0940) Prec@1 80.000 (83.646) Prec@5 99.000 (98.747) +2022-11-14 13:55:40,011 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0939) Prec@1 81.000 (83.612) Prec@5 100.000 (98.763) +2022-11-14 13:55:40,024 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0940) Prec@1 82.000 (83.593) Prec@5 97.000 (98.741) +2022-11-14 13:55:40,036 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0940) Prec@1 84.000 (83.598) Prec@5 100.000 (98.756) +2022-11-14 13:55:40,048 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0940) Prec@1 82.000 (83.578) Prec@5 100.000 (98.771) +2022-11-14 13:55:40,059 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0942) Prec@1 78.000 (83.512) Prec@5 100.000 (98.786) +2022-11-14 13:55:40,071 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1352 (0.0947) Prec@1 75.000 (83.412) Prec@5 97.000 (98.765) +2022-11-14 13:55:40,083 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0948) Prec@1 84.000 (83.419) Prec@5 99.000 (98.767) +2022-11-14 13:55:40,094 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0946) Prec@1 89.000 (83.483) Prec@5 98.000 (98.759) +2022-11-14 13:55:40,106 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0944) Prec@1 86.000 (83.511) Prec@5 99.000 (98.761) +2022-11-14 13:55:40,118 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0945) Prec@1 82.000 (83.494) Prec@5 99.000 (98.764) +2022-11-14 13:55:40,129 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0945) Prec@1 85.000 (83.511) Prec@5 100.000 (98.778) +2022-11-14 13:55:40,143 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0944) Prec@1 86.000 (83.538) Prec@5 99.000 (98.780) +2022-11-14 13:55:40,157 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0940) Prec@1 92.000 (83.630) Prec@5 100.000 (98.793) +2022-11-14 13:55:40,171 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0940) Prec@1 85.000 (83.645) Prec@5 100.000 (98.806) +2022-11-14 13:55:40,185 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0938) Prec@1 86.000 (83.670) Prec@5 98.000 (98.798) +2022-11-14 13:55:40,199 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0941) Prec@1 82.000 (83.653) Prec@5 98.000 (98.789) +2022-11-14 13:55:40,213 Test: [95/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0939) Prec@1 86.000 (83.677) Prec@5 100.000 (98.802) +2022-11-14 13:55:40,227 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0937) Prec@1 88.000 (83.722) Prec@5 98.000 (98.794) +2022-11-14 13:55:40,241 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1343 (0.0941) Prec@1 77.000 (83.653) Prec@5 99.000 (98.796) +2022-11-14 13:55:40,254 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.0945) Prec@1 76.000 (83.576) Prec@5 99.000 (98.798) +2022-11-14 13:55:40,268 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0945) Prec@1 82.000 (83.560) Prec@5 100.000 (98.810) +2022-11-14 13:55:40,328 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:55:40,642 Epoch: [118][0/500] Time 0.023 (0.023) Data 0.225 (0.225) Loss 0.0556 (0.0556) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:55:40,920 Epoch: [118][10/500] Time 0.026 (0.025) Data 0.002 (0.022) Loss 0.0777 (0.0666) Prec@1 88.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 13:55:41,186 Epoch: [118][20/500] Time 0.024 (0.024) Data 0.002 (0.013) Loss 0.0505 (0.0613) Prec@1 93.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 13:55:41,540 Epoch: [118][30/500] Time 0.037 (0.026) Data 0.002 (0.009) Loss 0.0711 (0.0637) Prec@1 88.000 (89.250) Prec@5 100.000 (99.750) +2022-11-14 13:55:41,871 Epoch: [118][40/500] Time 0.032 (0.027) Data 0.002 (0.007) Loss 0.0489 (0.0608) Prec@1 91.000 (89.600) Prec@5 100.000 (99.800) +2022-11-14 13:55:42,215 Epoch: [118][50/500] Time 0.033 (0.028) Data 0.002 (0.006) Loss 0.0746 (0.0631) Prec@1 91.000 (89.833) Prec@5 99.000 (99.667) +2022-11-14 13:55:42,613 Epoch: [118][60/500] Time 0.046 (0.029) Data 0.002 (0.006) Loss 0.0593 (0.0625) Prec@1 91.000 (90.000) Prec@5 98.000 (99.429) +2022-11-14 13:55:42,999 Epoch: [118][70/500] Time 0.053 (0.030) Data 0.002 (0.005) Loss 0.0603 (0.0623) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 13:55:43,367 Epoch: [118][80/500] Time 0.043 (0.030) Data 0.002 (0.005) Loss 0.0657 (0.0626) Prec@1 89.000 (89.889) Prec@5 99.000 (99.444) +2022-11-14 13:55:43,730 Epoch: [118][90/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0654 (0.0629) Prec@1 87.000 (89.600) Prec@5 99.000 (99.400) +2022-11-14 13:55:44,079 Epoch: [118][100/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0488 (0.0616) Prec@1 91.000 (89.727) Prec@5 99.000 (99.364) +2022-11-14 13:55:44,432 Epoch: [118][110/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0584 (0.0614) Prec@1 91.000 (89.833) Prec@5 99.000 (99.333) +2022-11-14 13:55:44,794 Epoch: [118][120/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0547 (0.0608) Prec@1 90.000 (89.846) Prec@5 100.000 (99.385) +2022-11-14 13:55:45,148 Epoch: [118][130/500] Time 0.034 (0.031) Data 0.002 (0.004) Loss 0.0649 (0.0611) Prec@1 90.000 (89.857) Prec@5 100.000 (99.429) +2022-11-14 13:55:45,503 Epoch: [118][140/500] Time 0.029 (0.031) Data 0.002 (0.003) Loss 0.0660 (0.0615) Prec@1 89.000 (89.800) Prec@5 98.000 (99.333) +2022-11-14 13:55:45,855 Epoch: [118][150/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0722 (0.0621) Prec@1 87.000 (89.625) Prec@5 99.000 (99.312) +2022-11-14 13:55:46,223 Epoch: [118][160/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0771 (0.0630) Prec@1 88.000 (89.529) Prec@5 99.000 (99.294) +2022-11-14 13:55:46,623 Epoch: [118][170/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0694 (0.0634) Prec@1 89.000 (89.500) Prec@5 100.000 (99.333) +2022-11-14 13:55:46,968 Epoch: [118][180/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0747 (0.0640) Prec@1 87.000 (89.368) Prec@5 99.000 (99.316) +2022-11-14 13:55:47,318 Epoch: [118][190/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0902 (0.0653) Prec@1 83.000 (89.050) Prec@5 99.000 (99.300) +2022-11-14 13:55:47,672 Epoch: [118][200/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0582 (0.0649) Prec@1 90.000 (89.095) Prec@5 99.000 (99.286) +2022-11-14 13:55:48,094 Epoch: [118][210/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0856 (0.0659) Prec@1 85.000 (88.909) Prec@5 100.000 (99.318) +2022-11-14 13:55:48,444 Epoch: [118][220/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0782 (0.0664) Prec@1 88.000 (88.870) Prec@5 99.000 (99.304) +2022-11-14 13:55:48,808 Epoch: [118][230/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0491 (0.0657) Prec@1 92.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 13:55:49,182 Epoch: [118][240/500] Time 0.033 (0.031) Data 0.003 (0.003) Loss 0.0859 (0.0665) Prec@1 87.000 (88.920) Prec@5 97.000 (99.240) +2022-11-14 13:55:49,551 Epoch: [118][250/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0720 (0.0667) Prec@1 88.000 (88.885) Prec@5 100.000 (99.269) +2022-11-14 13:55:49,916 Epoch: [118][260/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0873 (0.0675) Prec@1 85.000 (88.741) Prec@5 98.000 (99.222) +2022-11-14 13:55:50,283 Epoch: [118][270/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0539 (0.0670) Prec@1 90.000 (88.786) Prec@5 100.000 (99.250) +2022-11-14 13:55:50,639 Epoch: [118][280/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.0733 (0.0672) Prec@1 89.000 (88.793) Prec@5 100.000 (99.276) +2022-11-14 13:55:50,993 Epoch: [118][290/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0588 (0.0669) Prec@1 91.000 (88.867) Prec@5 100.000 (99.300) +2022-11-14 13:55:51,348 Epoch: [118][300/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0573 (0.0666) Prec@1 91.000 (88.935) Prec@5 100.000 (99.323) +2022-11-14 13:55:51,719 Epoch: [118][310/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0754 (0.0669) Prec@1 87.000 (88.875) Prec@5 99.000 (99.312) +2022-11-14 13:55:52,142 Epoch: [118][320/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0642 (0.0668) Prec@1 90.000 (88.909) Prec@5 98.000 (99.273) +2022-11-14 13:55:52,623 Epoch: [118][330/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0472 (0.0662) Prec@1 92.000 (89.000) Prec@5 100.000 (99.294) +2022-11-14 13:55:53,095 Epoch: [118][340/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0627 (0.0661) Prec@1 90.000 (89.029) Prec@5 98.000 (99.257) +2022-11-14 13:55:53,593 Epoch: [118][350/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0670 (0.0662) Prec@1 91.000 (89.083) Prec@5 99.000 (99.250) +2022-11-14 13:55:54,115 Epoch: [118][360/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0896 (0.0668) Prec@1 85.000 (88.973) Prec@5 97.000 (99.189) +2022-11-14 13:55:54,625 Epoch: [118][370/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0514 (0.0664) Prec@1 90.000 (89.000) Prec@5 100.000 (99.211) +2022-11-14 13:55:55,114 Epoch: [118][380/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0733 (0.0666) Prec@1 87.000 (88.949) Prec@5 99.000 (99.205) +2022-11-14 13:55:55,623 Epoch: [118][390/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0525 (0.0662) Prec@1 91.000 (89.000) Prec@5 100.000 (99.225) +2022-11-14 13:55:56,135 Epoch: [118][400/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.0406 (0.0656) Prec@1 95.000 (89.146) Prec@5 100.000 (99.244) +2022-11-14 13:55:56,637 Epoch: [118][410/500] Time 0.049 (0.035) Data 0.002 (0.002) Loss 0.0959 (0.0663) Prec@1 84.000 (89.024) Prec@5 98.000 (99.214) +2022-11-14 13:55:57,152 Epoch: [118][420/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0551 (0.0660) Prec@1 92.000 (89.093) Prec@5 100.000 (99.233) +2022-11-14 13:55:57,686 Epoch: [118][430/500] Time 0.054 (0.035) Data 0.002 (0.002) Loss 0.0855 (0.0665) Prec@1 86.000 (89.023) Prec@5 100.000 (99.250) +2022-11-14 13:55:58,207 Epoch: [118][440/500] Time 0.060 (0.035) Data 0.002 (0.002) Loss 0.0757 (0.0667) Prec@1 89.000 (89.022) Prec@5 99.000 (99.244) +2022-11-14 13:55:58,694 Epoch: [118][450/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0776 (0.0669) Prec@1 87.000 (88.978) Prec@5 99.000 (99.239) +2022-11-14 13:55:59,207 Epoch: [118][460/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0666 (0.0669) Prec@1 90.000 (89.000) Prec@5 100.000 (99.255) +2022-11-14 13:55:59,676 Epoch: [118][470/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0687 (0.0670) Prec@1 88.000 (88.979) Prec@5 99.000 (99.250) +2022-11-14 13:56:00,162 Epoch: [118][480/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0453 (0.0665) Prec@1 93.000 (89.061) Prec@5 99.000 (99.245) +2022-11-14 13:56:00,637 Epoch: [118][490/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0594 (0.0664) Prec@1 92.000 (89.120) Prec@5 99.000 (99.240) +2022-11-14 13:56:01,065 Epoch: [118][499/500] Time 0.049 (0.036) Data 0.002 (0.002) Loss 0.0696 (0.0664) Prec@1 88.000 (89.098) Prec@5 99.000 (99.235) +2022-11-14 13:56:01,354 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0690 (0.0690) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:56:01,365 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0590 (0.0640) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 13:56:01,375 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0750 (0.0676) Prec@1 89.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 13:56:01,387 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1198 (0.0807) Prec@1 82.000 (87.000) Prec@5 100.000 (99.750) +2022-11-14 13:56:01,397 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1042 (0.0854) Prec@1 85.000 (86.600) Prec@5 99.000 (99.600) +2022-11-14 13:56:01,406 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0429 (0.0783) Prec@1 94.000 (87.833) Prec@5 100.000 (99.667) +2022-11-14 13:56:01,416 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0839 (0.0791) Prec@1 86.000 (87.571) Prec@5 99.000 (99.571) +2022-11-14 13:56:01,427 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1191 (0.0841) Prec@1 78.000 (86.375) Prec@5 98.000 (99.375) +2022-11-14 13:56:01,439 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0858) Prec@1 85.000 (86.222) Prec@5 99.000 (99.333) +2022-11-14 13:56:01,450 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0838) Prec@1 86.000 (86.200) Prec@5 99.000 (99.300) +2022-11-14 13:56:01,462 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0822) Prec@1 89.000 (86.455) Prec@5 100.000 (99.364) +2022-11-14 13:56:01,475 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0833) Prec@1 84.000 (86.250) Prec@5 99.000 (99.333) +2022-11-14 13:56:01,488 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0824) Prec@1 88.000 (86.385) Prec@5 100.000 (99.385) +2022-11-14 13:56:01,500 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0824) Prec@1 86.000 (86.357) Prec@5 100.000 (99.429) +2022-11-14 13:56:01,512 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0838) Prec@1 80.000 (85.933) Prec@5 99.000 (99.400) +2022-11-14 13:56:01,525 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0852) Prec@1 79.000 (85.500) Prec@5 98.000 (99.312) +2022-11-14 13:56:01,537 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0841) Prec@1 88.000 (85.647) Prec@5 100.000 (99.353) +2022-11-14 13:56:01,549 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0860) Prec@1 81.000 (85.389) Prec@5 99.000 (99.333) +2022-11-14 13:56:01,562 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1129 (0.0874) Prec@1 80.000 (85.105) Prec@5 99.000 (99.316) +2022-11-14 13:56:01,574 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0883) Prec@1 81.000 (84.900) Prec@5 98.000 (99.250) +2022-11-14 13:56:01,585 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0888) Prec@1 83.000 (84.810) Prec@5 99.000 (99.238) +2022-11-14 13:56:01,597 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0887) Prec@1 86.000 (84.864) Prec@5 97.000 (99.136) +2022-11-14 13:56:01,610 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0892) Prec@1 82.000 (84.739) Prec@5 98.000 (99.087) +2022-11-14 13:56:01,623 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0897) Prec@1 85.000 (84.750) Prec@5 98.000 (99.042) +2022-11-14 13:56:01,634 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0898) Prec@1 84.000 (84.720) Prec@5 100.000 (99.080) +2022-11-14 13:56:01,645 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1342 (0.0915) Prec@1 76.000 (84.385) Prec@5 98.000 (99.038) +2022-11-14 13:56:01,656 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0911) Prec@1 85.000 (84.407) Prec@5 100.000 (99.074) +2022-11-14 13:56:01,667 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0916) Prec@1 82.000 (84.321) Prec@5 100.000 (99.107) +2022-11-14 13:56:01,678 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0915) Prec@1 83.000 (84.276) Prec@5 99.000 (99.103) +2022-11-14 13:56:01,691 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.0924) Prec@1 80.000 (84.133) Prec@5 99.000 (99.100) +2022-11-14 13:56:01,704 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0925) Prec@1 81.000 (84.032) Prec@5 100.000 (99.129) +2022-11-14 13:56:01,717 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0926) Prec@1 86.000 (84.094) Prec@5 100.000 (99.156) +2022-11-14 13:56:01,731 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0929) Prec@1 84.000 (84.091) Prec@5 98.000 (99.121) +2022-11-14 13:56:01,744 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1324 (0.0941) Prec@1 77.000 (83.882) Prec@5 98.000 (99.088) +2022-11-14 13:56:01,755 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0941) Prec@1 85.000 (83.914) Prec@5 98.000 (99.057) +2022-11-14 13:56:01,767 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0941) Prec@1 86.000 (83.972) Prec@5 98.000 (99.028) +2022-11-14 13:56:01,780 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0947) Prec@1 81.000 (83.892) Prec@5 97.000 (98.973) +2022-11-14 13:56:01,793 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1262 (0.0955) Prec@1 77.000 (83.711) Prec@5 98.000 (98.947) +2022-11-14 13:56:01,807 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0953) Prec@1 84.000 (83.718) Prec@5 98.000 (98.923) +2022-11-14 13:56:01,820 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0955) Prec@1 83.000 (83.700) Prec@5 99.000 (98.925) +2022-11-14 13:56:01,833 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0958) Prec@1 82.000 (83.659) Prec@5 99.000 (98.927) +2022-11-14 13:56:01,846 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0957) Prec@1 83.000 (83.643) Prec@5 98.000 (98.905) +2022-11-14 13:56:01,859 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0953) Prec@1 85.000 (83.674) Prec@5 98.000 (98.884) +2022-11-14 13:56:01,871 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0953) Prec@1 86.000 (83.727) Prec@5 98.000 (98.864) +2022-11-14 13:56:01,882 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0953) Prec@1 85.000 (83.756) Prec@5 98.000 (98.844) +2022-11-14 13:56:01,894 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1286 (0.0960) Prec@1 78.000 (83.630) Prec@5 100.000 (98.870) +2022-11-14 13:56:01,905 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0959) Prec@1 85.000 (83.660) Prec@5 99.000 (98.872) +2022-11-14 13:56:01,916 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0962) Prec@1 83.000 (83.646) Prec@5 98.000 (98.854) +2022-11-14 13:56:01,927 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0962) Prec@1 83.000 (83.633) Prec@5 100.000 (98.878) +2022-11-14 13:56:01,938 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.0969) Prec@1 80.000 (83.560) Prec@5 100.000 (98.900) +2022-11-14 13:56:01,951 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0965) Prec@1 86.000 (83.608) Prec@5 99.000 (98.902) +2022-11-14 13:56:01,963 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0965) Prec@1 83.000 (83.596) Prec@5 99.000 (98.904) +2022-11-14 13:56:01,974 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0966) Prec@1 83.000 (83.585) Prec@5 98.000 (98.887) +2022-11-14 13:56:01,986 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0965) Prec@1 85.000 (83.611) Prec@5 98.000 (98.870) +2022-11-14 13:56:01,999 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0965) Prec@1 85.000 (83.636) Prec@5 100.000 (98.891) +2022-11-14 13:56:02,011 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0969) Prec@1 83.000 (83.625) Prec@5 98.000 (98.875) +2022-11-14 13:56:02,022 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0968) Prec@1 83.000 (83.614) Prec@5 99.000 (98.877) +2022-11-14 13:56:02,032 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0963) Prec@1 89.000 (83.707) Prec@5 99.000 (98.879) +2022-11-14 13:56:02,041 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1402 (0.0971) Prec@1 77.000 (83.593) Prec@5 98.000 (98.864) +2022-11-14 13:56:02,051 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0971) Prec@1 84.000 (83.600) Prec@5 99.000 (98.867) +2022-11-14 13:56:02,061 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0972) Prec@1 79.000 (83.525) Prec@5 97.000 (98.836) +2022-11-14 13:56:02,074 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.0975) Prec@1 83.000 (83.516) Prec@5 99.000 (98.839) +2022-11-14 13:56:02,087 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0973) Prec@1 86.000 (83.556) Prec@5 100.000 (98.857) +2022-11-14 13:56:02,097 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0970) Prec@1 87.000 (83.609) Prec@5 100.000 (98.875) +2022-11-14 13:56:02,109 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0972) Prec@1 77.000 (83.508) Prec@5 100.000 (98.892) +2022-11-14 13:56:02,120 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.0977) Prec@1 79.000 (83.439) Prec@5 98.000 (98.879) +2022-11-14 13:56:02,133 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0970) Prec@1 93.000 (83.582) Prec@5 100.000 (98.896) +2022-11-14 13:56:02,145 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0972) Prec@1 83.000 (83.574) Prec@5 99.000 (98.897) +2022-11-14 13:56:02,157 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0970) Prec@1 85.000 (83.594) Prec@5 100.000 (98.913) +2022-11-14 13:56:02,167 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0970) Prec@1 81.000 (83.557) Prec@5 100.000 (98.929) +2022-11-14 13:56:02,179 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.0972) Prec@1 82.000 (83.535) Prec@5 98.000 (98.915) +2022-11-14 13:56:02,190 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0969) Prec@1 90.000 (83.625) Prec@5 98.000 (98.903) +2022-11-14 13:56:02,203 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0966) Prec@1 87.000 (83.671) Prec@5 99.000 (98.904) +2022-11-14 13:56:02,215 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0965) Prec@1 85.000 (83.689) Prec@5 100.000 (98.919) +2022-11-14 13:56:02,227 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.0968) Prec@1 85.000 (83.707) Prec@5 98.000 (98.907) +2022-11-14 13:56:02,238 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0968) Prec@1 84.000 (83.711) Prec@5 98.000 (98.895) +2022-11-14 13:56:02,251 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0967) Prec@1 84.000 (83.714) Prec@5 99.000 (98.896) +2022-11-14 13:56:02,263 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0967) Prec@1 84.000 (83.718) Prec@5 97.000 (98.872) +2022-11-14 13:56:02,274 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1264 (0.0971) Prec@1 76.000 (83.620) Prec@5 100.000 (98.886) +2022-11-14 13:56:02,285 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0968) Prec@1 87.000 (83.662) Prec@5 100.000 (98.900) +2022-11-14 13:56:02,297 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0968) Prec@1 80.000 (83.617) Prec@5 100.000 (98.914) +2022-11-14 13:56:02,308 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0967) Prec@1 84.000 (83.622) Prec@5 100.000 (98.927) +2022-11-14 13:56:02,320 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0966) Prec@1 85.000 (83.639) Prec@5 100.000 (98.940) +2022-11-14 13:56:02,332 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.0968) Prec@1 83.000 (83.631) Prec@5 99.000 (98.940) +2022-11-14 13:56:02,343 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0970) Prec@1 80.000 (83.588) Prec@5 100.000 (98.953) +2022-11-14 13:56:02,355 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.0973) Prec@1 83.000 (83.581) Prec@5 96.000 (98.919) +2022-11-14 13:56:02,367 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0973) Prec@1 81.000 (83.552) Prec@5 99.000 (98.920) +2022-11-14 13:56:02,379 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0973) Prec@1 83.000 (83.545) Prec@5 97.000 (98.898) +2022-11-14 13:56:02,389 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0969) Prec@1 92.000 (83.640) Prec@5 99.000 (98.899) +2022-11-14 13:56:02,399 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0969) Prec@1 85.000 (83.656) Prec@5 98.000 (98.889) +2022-11-14 13:56:02,409 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.0972) Prec@1 82.000 (83.637) Prec@5 100.000 (98.901) +2022-11-14 13:56:02,419 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0967) Prec@1 91.000 (83.717) Prec@5 99.000 (98.902) +2022-11-14 13:56:02,432 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0969) Prec@1 81.000 (83.688) Prec@5 100.000 (98.914) +2022-11-14 13:56:02,445 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0967) Prec@1 87.000 (83.723) Prec@5 100.000 (98.926) +2022-11-14 13:56:02,458 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.0970) Prec@1 79.000 (83.674) Prec@5 99.000 (98.926) +2022-11-14 13:56:02,470 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0969) Prec@1 86.000 (83.698) Prec@5 99.000 (98.927) +2022-11-14 13:56:02,480 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0965) Prec@1 91.000 (83.773) Prec@5 99.000 (98.928) +2022-11-14 13:56:02,492 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.0968) Prec@1 79.000 (83.724) Prec@5 97.000 (98.908) +2022-11-14 13:56:02,503 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.0969) Prec@1 81.000 (83.697) Prec@5 99.000 (98.909) +2022-11-14 13:56:02,515 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0970) Prec@1 79.000 (83.650) Prec@5 99.000 (98.910) +2022-11-14 13:56:02,574 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:56:02,883 Epoch: [119][0/500] Time 0.027 (0.027) Data 0.225 (0.225) Loss 0.1082 (0.1082) Prec@1 79.000 (79.000) Prec@5 99.000 (99.000) +2022-11-14 13:56:03,084 Epoch: [119][10/500] Time 0.017 (0.019) Data 0.001 (0.022) Loss 0.0815 (0.0948) Prec@1 87.000 (83.000) Prec@5 100.000 (99.500) +2022-11-14 13:56:03,299 Epoch: [119][20/500] Time 0.019 (0.019) Data 0.002 (0.012) Loss 0.0622 (0.0840) Prec@1 89.000 (85.000) Prec@5 100.000 (99.667) +2022-11-14 13:56:03,567 Epoch: [119][30/500] Time 0.028 (0.020) Data 0.002 (0.009) Loss 0.0675 (0.0798) Prec@1 88.000 (85.750) Prec@5 99.000 (99.500) +2022-11-14 13:56:03,881 Epoch: [119][40/500] Time 0.028 (0.022) Data 0.002 (0.007) Loss 0.0708 (0.0780) Prec@1 89.000 (86.400) Prec@5 99.000 (99.400) +2022-11-14 13:56:04,185 Epoch: [119][50/500] Time 0.029 (0.023) Data 0.002 (0.006) Loss 0.0381 (0.0714) Prec@1 96.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 13:56:04,504 Epoch: [119][60/500] Time 0.032 (0.024) Data 0.002 (0.005) Loss 0.0718 (0.0714) Prec@1 89.000 (88.143) Prec@5 100.000 (99.429) +2022-11-14 13:56:04,818 Epoch: [119][70/500] Time 0.030 (0.024) Data 0.002 (0.005) Loss 0.0630 (0.0704) Prec@1 89.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 13:56:05,134 Epoch: [119][80/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0740 (0.0708) Prec@1 88.000 (88.222) Prec@5 99.000 (99.444) +2022-11-14 13:56:05,442 Epoch: [119][90/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0597 (0.0697) Prec@1 89.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 13:56:05,756 Epoch: [119][100/500] Time 0.026 (0.025) Data 0.001 (0.004) Loss 0.0790 (0.0705) Prec@1 87.000 (88.182) Prec@5 97.000 (99.182) +2022-11-14 13:56:06,068 Epoch: [119][110/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.0673 (0.0702) Prec@1 88.000 (88.167) Prec@5 100.000 (99.250) +2022-11-14 13:56:06,380 Epoch: [119][120/500] Time 0.028 (0.026) Data 0.001 (0.004) Loss 0.0585 (0.0693) Prec@1 89.000 (88.231) Prec@5 99.000 (99.231) +2022-11-14 13:56:06,688 Epoch: [119][130/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0670 (0.0692) Prec@1 88.000 (88.214) Prec@5 100.000 (99.286) +2022-11-14 13:56:07,000 Epoch: [119][140/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0603 (0.0686) Prec@1 89.000 (88.267) Prec@5 99.000 (99.267) +2022-11-14 13:56:07,314 Epoch: [119][150/500] Time 0.030 (0.026) Data 0.001 (0.003) Loss 0.0807 (0.0693) Prec@1 85.000 (88.062) Prec@5 98.000 (99.188) +2022-11-14 13:56:07,641 Epoch: [119][160/500] Time 0.032 (0.026) Data 0.002 (0.003) Loss 0.0779 (0.0698) Prec@1 87.000 (88.000) Prec@5 100.000 (99.235) +2022-11-14 13:56:07,940 Epoch: [119][170/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0720 (0.0700) Prec@1 88.000 (88.000) Prec@5 99.000 (99.222) +2022-11-14 13:56:08,317 Epoch: [119][180/500] Time 0.027 (0.027) Data 0.003 (0.003) Loss 0.0914 (0.0711) Prec@1 83.000 (87.737) Prec@5 100.000 (99.263) +2022-11-14 13:56:08,821 Epoch: [119][190/500] Time 0.060 (0.028) Data 0.003 (0.003) Loss 0.0777 (0.0714) Prec@1 89.000 (87.800) Prec@5 100.000 (99.300) +2022-11-14 13:56:09,389 Epoch: [119][200/500] Time 0.066 (0.029) Data 0.002 (0.003) Loss 0.0702 (0.0714) Prec@1 87.000 (87.762) Prec@5 99.000 (99.286) +2022-11-14 13:56:09,871 Epoch: [119][210/500] Time 0.038 (0.029) Data 0.003 (0.003) Loss 0.0814 (0.0718) Prec@1 86.000 (87.682) Prec@5 100.000 (99.318) +2022-11-14 13:56:10,341 Epoch: [119][220/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0737 (0.0719) Prec@1 86.000 (87.609) Prec@5 100.000 (99.348) +2022-11-14 13:56:10,800 Epoch: [119][230/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0640 (0.0716) Prec@1 89.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 13:56:11,273 Epoch: [119][240/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0820 (0.0720) Prec@1 88.000 (87.680) Prec@5 100.000 (99.360) +2022-11-14 13:56:11,742 Epoch: [119][250/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0543 (0.0713) Prec@1 89.000 (87.731) Prec@5 100.000 (99.385) +2022-11-14 13:56:12,219 Epoch: [119][260/500] Time 0.061 (0.032) Data 0.002 (0.003) Loss 0.0540 (0.0707) Prec@1 89.000 (87.778) Prec@5 99.000 (99.370) +2022-11-14 13:56:12,703 Epoch: [119][270/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0653 (0.0705) Prec@1 88.000 (87.786) Prec@5 99.000 (99.357) +2022-11-14 13:56:13,169 Epoch: [119][280/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0686 (0.0704) Prec@1 89.000 (87.828) Prec@5 100.000 (99.379) +2022-11-14 13:56:13,639 Epoch: [119][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0768 (0.0706) Prec@1 88.000 (87.833) Prec@5 100.000 (99.400) +2022-11-14 13:56:14,113 Epoch: [119][300/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0686 (0.0706) Prec@1 87.000 (87.806) Prec@5 99.000 (99.387) +2022-11-14 13:56:14,583 Epoch: [119][310/500] Time 0.051 (0.033) Data 0.002 (0.003) Loss 0.0718 (0.0706) Prec@1 87.000 (87.781) Prec@5 99.000 (99.375) +2022-11-14 13:56:15,051 Epoch: [119][320/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0633 (0.0704) Prec@1 89.000 (87.818) Prec@5 99.000 (99.364) +2022-11-14 13:56:15,531 Epoch: [119][330/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0548 (0.0699) Prec@1 92.000 (87.941) Prec@5 100.000 (99.382) +2022-11-14 13:56:16,001 Epoch: [119][340/500] Time 0.043 (0.034) Data 0.003 (0.003) Loss 0.0645 (0.0698) Prec@1 90.000 (88.000) Prec@5 99.000 (99.371) +2022-11-14 13:56:16,472 Epoch: [119][350/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0705 (0.0698) Prec@1 90.000 (88.056) Prec@5 100.000 (99.389) +2022-11-14 13:56:16,941 Epoch: [119][360/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0650 (0.0697) Prec@1 90.000 (88.108) Prec@5 100.000 (99.405) +2022-11-14 13:56:17,400 Epoch: [119][370/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0520 (0.0692) Prec@1 90.000 (88.158) Prec@5 100.000 (99.421) +2022-11-14 13:56:17,870 Epoch: [119][380/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0713 (0.0692) Prec@1 88.000 (88.154) Prec@5 100.000 (99.436) +2022-11-14 13:56:18,340 Epoch: [119][390/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0713 (0.0693) Prec@1 87.000 (88.125) Prec@5 99.000 (99.425) +2022-11-14 13:56:18,814 Epoch: [119][400/500] Time 0.052 (0.035) Data 0.002 (0.002) Loss 0.0464 (0.0687) Prec@1 91.000 (88.195) Prec@5 100.000 (99.439) +2022-11-14 13:56:19,272 Epoch: [119][410/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0646 (0.0686) Prec@1 89.000 (88.214) Prec@5 99.000 (99.429) +2022-11-14 13:56:19,742 Epoch: [119][420/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0695 (0.0687) Prec@1 87.000 (88.186) Prec@5 100.000 (99.442) +2022-11-14 13:56:20,208 Epoch: [119][430/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0559 (0.0684) Prec@1 90.000 (88.227) Prec@5 100.000 (99.455) +2022-11-14 13:56:20,675 Epoch: [119][440/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0648 (0.0683) Prec@1 89.000 (88.244) Prec@5 100.000 (99.467) +2022-11-14 13:56:21,145 Epoch: [119][450/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0437 (0.0678) Prec@1 94.000 (88.370) Prec@5 100.000 (99.478) +2022-11-14 13:56:21,604 Epoch: [119][460/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0626 (0.0676) Prec@1 89.000 (88.383) Prec@5 100.000 (99.489) +2022-11-14 13:56:22,071 Epoch: [119][470/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.1202 (0.0687) Prec@1 81.000 (88.229) Prec@5 99.000 (99.479) +2022-11-14 13:56:22,547 Epoch: [119][480/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0550 (0.0685) Prec@1 89.000 (88.245) Prec@5 100.000 (99.490) +2022-11-14 13:56:23,016 Epoch: [119][490/500] Time 0.050 (0.036) Data 0.002 (0.002) Loss 0.0431 (0.0680) Prec@1 93.000 (88.340) Prec@5 100.000 (99.500) +2022-11-14 13:56:23,432 Epoch: [119][499/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0641 (0.0679) Prec@1 89.000 (88.353) Prec@5 100.000 (99.510) +2022-11-14 13:56:23,705 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0920) Prec@1 80.000 (80.000) Prec@5 100.000 (100.000) +2022-11-14 13:56:23,712 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0795) Prec@1 88.000 (84.000) Prec@5 99.000 (99.500) +2022-11-14 13:56:23,722 Test: [2/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0819) Prec@1 85.000 (84.333) Prec@5 100.000 (99.667) +2022-11-14 13:56:23,733 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0815) Prec@1 84.000 (84.250) Prec@5 100.000 (99.750) +2022-11-14 13:56:23,741 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0848) Prec@1 82.000 (83.800) Prec@5 100.000 (99.800) +2022-11-14 13:56:23,750 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0796) Prec@1 92.000 (85.167) Prec@5 100.000 (99.833) +2022-11-14 13:56:23,759 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0788) Prec@1 89.000 (85.714) Prec@5 99.000 (99.714) +2022-11-14 13:56:23,769 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0820) Prec@1 83.000 (85.375) Prec@5 99.000 (99.625) +2022-11-14 13:56:23,779 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0840) Prec@1 81.000 (84.889) Prec@5 100.000 (99.667) +2022-11-14 13:56:23,788 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0819) Prec@1 88.000 (85.200) Prec@5 99.000 (99.600) +2022-11-14 13:56:23,798 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0816) Prec@1 86.000 (85.273) Prec@5 100.000 (99.636) +2022-11-14 13:56:23,808 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0814) Prec@1 87.000 (85.417) Prec@5 99.000 (99.583) +2022-11-14 13:56:23,818 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0813) Prec@1 87.000 (85.538) Prec@5 100.000 (99.615) +2022-11-14 13:56:23,828 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0808) Prec@1 86.000 (85.571) Prec@5 100.000 (99.643) +2022-11-14 13:56:23,838 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0801) Prec@1 88.000 (85.733) Prec@5 100.000 (99.667) +2022-11-14 13:56:23,848 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1287 (0.0831) Prec@1 75.000 (85.062) Prec@5 100.000 (99.688) +2022-11-14 13:56:23,858 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0808) Prec@1 94.000 (85.588) Prec@5 99.000 (99.647) +2022-11-14 13:56:23,868 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0815) Prec@1 86.000 (85.611) Prec@5 100.000 (99.667) +2022-11-14 13:56:23,878 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0822) Prec@1 81.000 (85.368) Prec@5 100.000 (99.684) +2022-11-14 13:56:23,887 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0832) Prec@1 86.000 (85.400) Prec@5 98.000 (99.600) +2022-11-14 13:56:23,897 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0846) Prec@1 81.000 (85.190) Prec@5 98.000 (99.524) +2022-11-14 13:56:23,907 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0845) Prec@1 85.000 (85.182) Prec@5 99.000 (99.500) +2022-11-14 13:56:23,916 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0848) Prec@1 84.000 (85.130) Prec@5 99.000 (99.478) +2022-11-14 13:56:23,927 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0852) Prec@1 85.000 (85.125) Prec@5 99.000 (99.458) +2022-11-14 13:56:23,937 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0859) Prec@1 83.000 (85.040) Prec@5 100.000 (99.480) +2022-11-14 13:56:23,949 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0865) Prec@1 84.000 (85.000) Prec@5 97.000 (99.385) +2022-11-14 13:56:23,960 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0857) Prec@1 88.000 (85.111) Prec@5 100.000 (99.407) +2022-11-14 13:56:23,971 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0860) Prec@1 85.000 (85.107) Prec@5 99.000 (99.393) +2022-11-14 13:56:23,981 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0854) Prec@1 90.000 (85.276) Prec@5 99.000 (99.379) +2022-11-14 13:56:23,993 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0853) Prec@1 85.000 (85.267) Prec@5 99.000 (99.367) +2022-11-14 13:56:24,004 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0852) Prec@1 86.000 (85.290) Prec@5 99.000 (99.355) +2022-11-14 13:56:24,014 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0852) Prec@1 84.000 (85.250) Prec@5 100.000 (99.375) +2022-11-14 13:56:24,026 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0848) Prec@1 86.000 (85.273) Prec@5 100.000 (99.394) +2022-11-14 13:56:24,035 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0856) Prec@1 80.000 (85.118) Prec@5 98.000 (99.353) +2022-11-14 13:56:24,045 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0860) Prec@1 83.000 (85.057) Prec@5 99.000 (99.343) +2022-11-14 13:56:24,056 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0857) Prec@1 89.000 (85.167) Prec@5 100.000 (99.361) +2022-11-14 13:56:24,066 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0857) Prec@1 85.000 (85.162) Prec@5 98.000 (99.324) +2022-11-14 13:56:24,075 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0861) Prec@1 82.000 (85.079) Prec@5 100.000 (99.342) +2022-11-14 13:56:24,085 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0857) Prec@1 88.000 (85.154) Prec@5 98.000 (99.308) +2022-11-14 13:56:24,097 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0855) Prec@1 88.000 (85.225) Prec@5 100.000 (99.325) +2022-11-14 13:56:24,107 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0857) Prec@1 88.000 (85.293) Prec@5 97.000 (99.268) +2022-11-14 13:56:24,119 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0857) Prec@1 85.000 (85.286) Prec@5 99.000 (99.262) +2022-11-14 13:56:24,131 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0854) Prec@1 88.000 (85.349) Prec@5 100.000 (99.279) +2022-11-14 13:56:24,142 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0853) Prec@1 88.000 (85.409) Prec@5 98.000 (99.250) +2022-11-14 13:56:24,153 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0849) Prec@1 88.000 (85.467) Prec@5 99.000 (99.244) +2022-11-14 13:56:24,164 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1088 (0.0854) Prec@1 78.000 (85.304) Prec@5 100.000 (99.261) +2022-11-14 13:56:24,173 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0855) Prec@1 83.000 (85.255) Prec@5 100.000 (99.277) +2022-11-14 13:56:24,183 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0858) Prec@1 84.000 (85.229) Prec@5 97.000 (99.229) +2022-11-14 13:56:24,194 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0853) Prec@1 90.000 (85.327) Prec@5 100.000 (99.245) +2022-11-14 13:56:24,204 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1114 (0.0858) Prec@1 82.000 (85.260) Prec@5 100.000 (99.260) +2022-11-14 13:56:24,216 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0860) Prec@1 82.000 (85.196) Prec@5 100.000 (99.275) +2022-11-14 13:56:24,227 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0862) Prec@1 84.000 (85.173) Prec@5 98.000 (99.250) +2022-11-14 13:56:24,236 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0862) Prec@1 86.000 (85.189) Prec@5 98.000 (99.226) +2022-11-14 13:56:24,246 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0861) Prec@1 88.000 (85.241) Prec@5 98.000 (99.204) +2022-11-14 13:56:24,257 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0864) Prec@1 84.000 (85.218) Prec@5 99.000 (99.200) +2022-11-14 13:56:24,269 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0864) Prec@1 86.000 (85.232) Prec@5 100.000 (99.214) +2022-11-14 13:56:24,279 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0865) Prec@1 85.000 (85.228) Prec@5 100.000 (99.228) +2022-11-14 13:56:24,289 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0863) Prec@1 88.000 (85.276) Prec@5 98.000 (99.207) +2022-11-14 13:56:24,300 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1405 (0.0872) Prec@1 78.000 (85.153) Prec@5 100.000 (99.220) +2022-11-14 13:56:24,311 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0873) Prec@1 84.000 (85.133) Prec@5 99.000 (99.217) +2022-11-14 13:56:24,322 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0874) Prec@1 84.000 (85.115) Prec@5 99.000 (99.213) +2022-11-14 13:56:24,333 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0872) Prec@1 85.000 (85.113) Prec@5 99.000 (99.210) +2022-11-14 13:56:24,342 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0870) Prec@1 86.000 (85.127) Prec@5 100.000 (99.222) +2022-11-14 13:56:24,354 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0867) Prec@1 90.000 (85.203) Prec@5 100.000 (99.234) +2022-11-14 13:56:24,364 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0871) Prec@1 82.000 (85.154) Prec@5 99.000 (99.231) +2022-11-14 13:56:24,375 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0873) Prec@1 82.000 (85.106) Prec@5 98.000 (99.212) +2022-11-14 13:56:24,386 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0870) Prec@1 86.000 (85.119) Prec@5 99.000 (99.209) +2022-11-14 13:56:24,395 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0869) Prec@1 86.000 (85.132) Prec@5 99.000 (99.206) +2022-11-14 13:56:24,405 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0865) Prec@1 92.000 (85.232) Prec@5 98.000 (99.188) +2022-11-14 13:56:24,417 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.0869) Prec@1 81.000 (85.171) Prec@5 98.000 (99.171) +2022-11-14 13:56:24,428 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1242 (0.0875) Prec@1 77.000 (85.056) Prec@5 98.000 (99.155) +2022-11-14 13:56:24,437 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0873) Prec@1 85.000 (85.056) Prec@5 99.000 (99.153) +2022-11-14 13:56:24,447 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0872) Prec@1 89.000 (85.110) Prec@5 99.000 (99.151) +2022-11-14 13:56:24,459 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0869) Prec@1 88.000 (85.149) Prec@5 100.000 (99.162) +2022-11-14 13:56:24,470 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0869) Prec@1 85.000 (85.147) Prec@5 100.000 (99.173) +2022-11-14 13:56:24,480 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0867) Prec@1 88.000 (85.184) Prec@5 99.000 (99.171) +2022-11-14 13:56:24,491 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0866) Prec@1 87.000 (85.208) Prec@5 100.000 (99.182) +2022-11-14 13:56:24,502 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0866) Prec@1 86.000 (85.218) Prec@5 100.000 (99.192) +2022-11-14 13:56:24,514 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0869) Prec@1 81.000 (85.165) Prec@5 100.000 (99.203) +2022-11-14 13:56:24,524 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0866) Prec@1 89.000 (85.213) Prec@5 99.000 (99.200) +2022-11-14 13:56:24,535 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0867) Prec@1 85.000 (85.210) Prec@5 100.000 (99.210) +2022-11-14 13:56:24,546 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0865) Prec@1 88.000 (85.244) Prec@5 99.000 (99.207) +2022-11-14 13:56:24,555 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1124 (0.0868) Prec@1 78.000 (85.157) Prec@5 99.000 (99.205) +2022-11-14 13:56:24,566 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0867) Prec@1 87.000 (85.179) Prec@5 99.000 (99.202) +2022-11-14 13:56:24,577 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0868) Prec@1 83.000 (85.153) Prec@5 99.000 (99.200) +2022-11-14 13:56:24,588 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0870) Prec@1 82.000 (85.116) Prec@5 99.000 (99.198) +2022-11-14 13:56:24,598 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0869) Prec@1 83.000 (85.092) Prec@5 98.000 (99.184) +2022-11-14 13:56:24,609 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0868) Prec@1 87.000 (85.114) Prec@5 99.000 (99.182) +2022-11-14 13:56:24,619 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0866) Prec@1 89.000 (85.157) Prec@5 100.000 (99.191) +2022-11-14 13:56:24,630 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0868) Prec@1 83.000 (85.133) Prec@5 99.000 (99.189) +2022-11-14 13:56:24,641 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0865) Prec@1 88.000 (85.165) Prec@5 100.000 (99.198) +2022-11-14 13:56:24,652 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0862) Prec@1 91.000 (85.228) Prec@5 99.000 (99.196) +2022-11-14 13:56:24,663 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0863) Prec@1 84.000 (85.215) Prec@5 98.000 (99.183) +2022-11-14 13:56:24,674 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0865) Prec@1 80.000 (85.160) Prec@5 99.000 (99.181) +2022-11-14 13:56:24,684 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0864) Prec@1 87.000 (85.179) Prec@5 100.000 (99.189) +2022-11-14 13:56:24,695 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0864) Prec@1 83.000 (85.156) Prec@5 99.000 (99.188) +2022-11-14 13:56:24,707 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0860) Prec@1 94.000 (85.247) Prec@5 98.000 (99.175) +2022-11-14 13:56:24,717 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0862) Prec@1 82.000 (85.214) Prec@5 99.000 (99.173) +2022-11-14 13:56:24,728 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0864) Prec@1 81.000 (85.172) Prec@5 99.000 (99.172) +2022-11-14 13:56:24,737 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0865) Prec@1 83.000 (85.150) Prec@5 100.000 (99.180) +2022-11-14 13:56:24,791 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:56:25,106 Epoch: [120][0/500] Time 0.023 (0.023) Data 0.238 (0.238) Loss 0.0758 (0.0758) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:56:25,332 Epoch: [120][10/500] Time 0.017 (0.020) Data 0.002 (0.023) Loss 0.0486 (0.0622) Prec@1 91.000 (88.500) Prec@5 98.000 (98.500) +2022-11-14 13:56:25,549 Epoch: [120][20/500] Time 0.017 (0.020) Data 0.003 (0.013) Loss 0.0831 (0.0692) Prec@1 85.000 (87.333) Prec@5 99.000 (98.667) +2022-11-14 13:56:25,769 Epoch: [120][30/500] Time 0.017 (0.019) Data 0.002 (0.010) Loss 0.1208 (0.0821) Prec@1 79.000 (85.250) Prec@5 99.000 (98.750) +2022-11-14 13:56:25,990 Epoch: [120][40/500] Time 0.017 (0.020) Data 0.002 (0.008) Loss 0.0629 (0.0782) Prec@1 88.000 (85.800) Prec@5 99.000 (98.800) +2022-11-14 13:56:26,207 Epoch: [120][50/500] Time 0.017 (0.019) Data 0.002 (0.007) Loss 0.0761 (0.0779) Prec@1 87.000 (86.000) Prec@5 100.000 (99.000) +2022-11-14 13:56:26,474 Epoch: [120][60/500] Time 0.028 (0.020) Data 0.001 (0.006) Loss 0.0498 (0.0739) Prec@1 94.000 (87.143) Prec@5 98.000 (98.857) +2022-11-14 13:56:26,787 Epoch: [120][70/500] Time 0.029 (0.021) Data 0.002 (0.005) Loss 0.0549 (0.0715) Prec@1 92.000 (87.750) Prec@5 99.000 (98.875) +2022-11-14 13:56:27,099 Epoch: [120][80/500] Time 0.029 (0.022) Data 0.002 (0.005) Loss 0.0819 (0.0727) Prec@1 85.000 (87.444) Prec@5 98.000 (98.778) +2022-11-14 13:56:27,407 Epoch: [120][90/500] Time 0.028 (0.022) Data 0.002 (0.004) Loss 0.0648 (0.0719) Prec@1 87.000 (87.400) Prec@5 100.000 (98.900) +2022-11-14 13:56:27,718 Epoch: [120][100/500] Time 0.028 (0.023) Data 0.002 (0.004) Loss 0.0686 (0.0716) Prec@1 89.000 (87.545) Prec@5 98.000 (98.818) +2022-11-14 13:56:28,030 Epoch: [120][110/500] Time 0.029 (0.023) Data 0.002 (0.004) Loss 0.0579 (0.0704) Prec@1 92.000 (87.917) Prec@5 99.000 (98.833) +2022-11-14 13:56:28,350 Epoch: [120][120/500] Time 0.031 (0.024) Data 0.002 (0.004) Loss 0.0616 (0.0698) Prec@1 90.000 (88.077) Prec@5 99.000 (98.846) +2022-11-14 13:56:28,659 Epoch: [120][130/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0597 (0.0690) Prec@1 89.000 (88.143) Prec@5 100.000 (98.929) +2022-11-14 13:56:28,973 Epoch: [120][140/500] Time 0.036 (0.024) Data 0.001 (0.004) Loss 0.0480 (0.0676) Prec@1 92.000 (88.400) Prec@5 99.000 (98.933) +2022-11-14 13:56:29,288 Epoch: [120][150/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0562 (0.0669) Prec@1 90.000 (88.500) Prec@5 100.000 (99.000) +2022-11-14 13:56:29,605 Epoch: [120][160/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0526 (0.0661) Prec@1 90.000 (88.588) Prec@5 100.000 (99.059) +2022-11-14 13:56:29,917 Epoch: [120][170/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0948 (0.0677) Prec@1 86.000 (88.444) Prec@5 99.000 (99.056) +2022-11-14 13:56:30,233 Epoch: [120][180/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0669 (0.0676) Prec@1 90.000 (88.526) Prec@5 100.000 (99.105) +2022-11-14 13:56:30,546 Epoch: [120][190/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0519 (0.0668) Prec@1 91.000 (88.650) Prec@5 100.000 (99.150) +2022-11-14 13:56:30,862 Epoch: [120][200/500] Time 0.029 (0.025) Data 0.001 (0.003) Loss 0.0295 (0.0651) Prec@1 94.000 (88.905) Prec@5 100.000 (99.190) +2022-11-14 13:56:31,174 Epoch: [120][210/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0841 (0.0659) Prec@1 85.000 (88.727) Prec@5 99.000 (99.182) +2022-11-14 13:56:31,492 Epoch: [120][220/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0536 (0.0654) Prec@1 88.000 (88.696) Prec@5 100.000 (99.217) +2022-11-14 13:56:31,807 Epoch: [120][230/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0596 (0.0652) Prec@1 91.000 (88.792) Prec@5 100.000 (99.250) +2022-11-14 13:56:32,115 Epoch: [120][240/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0774 (0.0656) Prec@1 86.000 (88.680) Prec@5 100.000 (99.280) +2022-11-14 13:56:32,429 Epoch: [120][250/500] Time 0.032 (0.026) Data 0.002 (0.003) Loss 0.0439 (0.0648) Prec@1 95.000 (88.923) Prec@5 100.000 (99.308) +2022-11-14 13:56:32,760 Epoch: [120][260/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0669 (0.0649) Prec@1 86.000 (88.815) Prec@5 99.000 (99.296) +2022-11-14 13:56:33,090 Epoch: [120][270/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.0640 (0.0648) Prec@1 88.000 (88.786) Prec@5 98.000 (99.250) +2022-11-14 13:56:33,415 Epoch: [120][280/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0447 (0.0642) Prec@1 91.000 (88.862) Prec@5 100.000 (99.276) +2022-11-14 13:56:33,739 Epoch: [120][290/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0704 (0.0644) Prec@1 86.000 (88.767) Prec@5 98.000 (99.233) +2022-11-14 13:56:34,060 Epoch: [120][300/500] Time 0.026 (0.026) Data 0.002 (0.003) Loss 0.0798 (0.0649) Prec@1 87.000 (88.710) Prec@5 98.000 (99.194) +2022-11-14 13:56:34,384 Epoch: [120][310/500] Time 0.035 (0.026) Data 0.002 (0.003) Loss 0.0749 (0.0652) Prec@1 87.000 (88.656) Prec@5 100.000 (99.219) +2022-11-14 13:56:34,712 Epoch: [120][320/500] Time 0.035 (0.026) Data 0.002 (0.003) Loss 0.0567 (0.0649) Prec@1 91.000 (88.727) Prec@5 100.000 (99.242) +2022-11-14 13:56:35,030 Epoch: [120][330/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.0742 (0.0652) Prec@1 87.000 (88.676) Prec@5 99.000 (99.235) +2022-11-14 13:56:35,349 Epoch: [120][340/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0769 (0.0655) Prec@1 88.000 (88.657) Prec@5 99.000 (99.229) +2022-11-14 13:56:35,671 Epoch: [120][350/500] Time 0.026 (0.027) Data 0.002 (0.003) Loss 0.0501 (0.0651) Prec@1 93.000 (88.778) Prec@5 99.000 (99.222) +2022-11-14 13:56:35,989 Epoch: [120][360/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0735 (0.0653) Prec@1 85.000 (88.676) Prec@5 99.000 (99.216) +2022-11-14 13:56:36,311 Epoch: [120][370/500] Time 0.025 (0.027) Data 0.002 (0.002) Loss 0.0803 (0.0657) Prec@1 87.000 (88.632) Prec@5 99.000 (99.211) +2022-11-14 13:56:36,678 Epoch: [120][380/500] Time 0.043 (0.027) Data 0.002 (0.002) Loss 0.0837 (0.0662) Prec@1 87.000 (88.590) Prec@5 100.000 (99.231) +2022-11-14 13:56:37,146 Epoch: [120][390/500] Time 0.043 (0.027) Data 0.001 (0.002) Loss 0.0716 (0.0663) Prec@1 87.000 (88.550) Prec@5 98.000 (99.200) +2022-11-14 13:56:37,617 Epoch: [120][400/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0551 (0.0660) Prec@1 92.000 (88.634) Prec@5 100.000 (99.220) +2022-11-14 13:56:38,089 Epoch: [120][410/500] Time 0.043 (0.028) Data 0.001 (0.002) Loss 0.0711 (0.0662) Prec@1 89.000 (88.643) Prec@5 98.000 (99.190) +2022-11-14 13:56:38,557 Epoch: [120][420/500] Time 0.054 (0.028) Data 0.002 (0.002) Loss 0.0884 (0.0667) Prec@1 85.000 (88.558) Prec@5 99.000 (99.186) +2022-11-14 13:56:39,032 Epoch: [120][430/500] Time 0.044 (0.029) Data 0.001 (0.002) Loss 0.0365 (0.0660) Prec@1 95.000 (88.705) Prec@5 100.000 (99.205) +2022-11-14 13:56:39,499 Epoch: [120][440/500] Time 0.044 (0.029) Data 0.001 (0.002) Loss 0.0715 (0.0661) Prec@1 88.000 (88.689) Prec@5 100.000 (99.222) +2022-11-14 13:56:39,973 Epoch: [120][450/500] Time 0.044 (0.029) Data 0.002 (0.002) Loss 0.0596 (0.0660) Prec@1 91.000 (88.739) Prec@5 100.000 (99.239) +2022-11-14 13:56:40,444 Epoch: [120][460/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.0875 (0.0664) Prec@1 84.000 (88.638) Prec@5 100.000 (99.255) +2022-11-14 13:56:40,930 Epoch: [120][470/500] Time 0.062 (0.030) Data 0.002 (0.002) Loss 0.1003 (0.0671) Prec@1 81.000 (88.479) Prec@5 99.000 (99.250) +2022-11-14 13:56:41,398 Epoch: [120][480/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0634 (0.0671) Prec@1 90.000 (88.510) Prec@5 99.000 (99.245) +2022-11-14 13:56:41,872 Epoch: [120][490/500] Time 0.045 (0.030) Data 0.002 (0.002) Loss 0.0808 (0.0673) Prec@1 83.000 (88.400) Prec@5 100.000 (99.260) +2022-11-14 13:56:42,307 Epoch: [120][499/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0430 (0.0669) Prec@1 91.000 (88.451) Prec@5 100.000 (99.275) +2022-11-14 13:56:42,587 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0793 (0.0793) Prec@1 85.000 (85.000) Prec@5 97.000 (97.000) +2022-11-14 13:56:42,596 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0843) Prec@1 85.000 (85.000) Prec@5 99.000 (98.000) +2022-11-14 13:56:42,605 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0866) Prec@1 83.000 (84.333) Prec@5 100.000 (98.667) +2022-11-14 13:56:42,619 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0818) Prec@1 88.000 (85.250) Prec@5 99.000 (98.750) +2022-11-14 13:56:42,629 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0832) Prec@1 86.000 (85.400) Prec@5 99.000 (98.800) +2022-11-14 13:56:42,638 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0797) Prec@1 91.000 (86.333) Prec@5 100.000 (99.000) +2022-11-14 13:56:42,647 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0812) Prec@1 84.000 (86.000) Prec@5 100.000 (99.143) +2022-11-14 13:56:42,658 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0822) Prec@1 84.000 (85.750) Prec@5 98.000 (99.000) +2022-11-14 13:56:42,667 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0835) Prec@1 86.000 (85.778) Prec@5 100.000 (99.111) +2022-11-14 13:56:42,676 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0823) Prec@1 90.000 (86.200) Prec@5 98.000 (99.000) +2022-11-14 13:56:42,686 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0813) Prec@1 88.000 (86.364) Prec@5 100.000 (99.091) +2022-11-14 13:56:42,697 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0824) Prec@1 85.000 (86.250) Prec@5 99.000 (99.083) +2022-11-14 13:56:42,707 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0800) Prec@1 92.000 (86.692) Prec@5 100.000 (99.154) +2022-11-14 13:56:42,716 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0814) Prec@1 84.000 (86.500) Prec@5 100.000 (99.214) +2022-11-14 13:56:42,726 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0815) Prec@1 85.000 (86.400) Prec@5 98.000 (99.133) +2022-11-14 13:56:42,736 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0828) Prec@1 82.000 (86.125) Prec@5 100.000 (99.188) +2022-11-14 13:56:42,746 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0813) Prec@1 91.000 (86.412) Prec@5 98.000 (99.118) +2022-11-14 13:56:42,757 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0828) Prec@1 81.000 (86.111) Prec@5 99.000 (99.111) +2022-11-14 13:56:42,767 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0829) Prec@1 89.000 (86.263) Prec@5 99.000 (99.105) +2022-11-14 13:56:42,777 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0832) Prec@1 87.000 (86.300) Prec@5 99.000 (99.100) +2022-11-14 13:56:42,786 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0841) Prec@1 83.000 (86.143) Prec@5 99.000 (99.095) +2022-11-14 13:56:42,797 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0848) Prec@1 83.000 (86.000) Prec@5 97.000 (99.000) +2022-11-14 13:56:42,808 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1303 (0.0867) Prec@1 77.000 (85.609) Prec@5 98.000 (98.957) +2022-11-14 13:56:42,820 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0870) Prec@1 83.000 (85.500) Prec@5 98.000 (98.917) +2022-11-14 13:56:42,832 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0871) Prec@1 83.000 (85.400) Prec@5 100.000 (98.960) +2022-11-14 13:56:42,842 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0874) Prec@1 84.000 (85.346) Prec@5 99.000 (98.962) +2022-11-14 13:56:42,852 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0868) Prec@1 85.000 (85.333) Prec@5 100.000 (99.000) +2022-11-14 13:56:42,862 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0867) Prec@1 85.000 (85.321) Prec@5 99.000 (99.000) +2022-11-14 13:56:42,873 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0859) Prec@1 88.000 (85.414) Prec@5 99.000 (99.000) +2022-11-14 13:56:42,883 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0860) Prec@1 86.000 (85.433) Prec@5 99.000 (99.000) +2022-11-14 13:56:42,894 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0862) Prec@1 84.000 (85.387) Prec@5 99.000 (99.000) +2022-11-14 13:56:42,905 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0859) Prec@1 89.000 (85.500) Prec@5 100.000 (99.031) +2022-11-14 13:56:42,917 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0857) Prec@1 82.000 (85.394) Prec@5 99.000 (99.030) +2022-11-14 13:56:42,927 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.0864) Prec@1 84.000 (85.353) Prec@5 100.000 (99.059) +2022-11-14 13:56:42,936 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0870) Prec@1 82.000 (85.257) Prec@5 99.000 (99.057) +2022-11-14 13:56:42,946 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0869) Prec@1 88.000 (85.333) Prec@5 99.000 (99.056) +2022-11-14 13:56:42,958 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0872) Prec@1 81.000 (85.216) Prec@5 98.000 (99.027) +2022-11-14 13:56:42,969 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1323 (0.0884) Prec@1 78.000 (85.026) Prec@5 99.000 (99.026) +2022-11-14 13:56:42,979 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0878) Prec@1 90.000 (85.154) Prec@5 100.000 (99.051) +2022-11-14 13:56:42,988 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0877) Prec@1 88.000 (85.225) Prec@5 99.000 (99.050) +2022-11-14 13:56:43,000 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0880) Prec@1 82.000 (85.146) Prec@5 99.000 (99.049) +2022-11-14 13:56:43,011 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0880) Prec@1 84.000 (85.119) Prec@5 98.000 (99.024) +2022-11-14 13:56:43,020 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0871) Prec@1 91.000 (85.256) Prec@5 100.000 (99.047) +2022-11-14 13:56:43,030 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0870) Prec@1 87.000 (85.295) Prec@5 98.000 (99.023) +2022-11-14 13:56:43,039 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0868) Prec@1 86.000 (85.311) Prec@5 99.000 (99.022) +2022-11-14 13:56:43,050 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0869) Prec@1 85.000 (85.304) Prec@5 100.000 (99.043) +2022-11-14 13:56:43,063 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0866) Prec@1 86.000 (85.319) Prec@5 100.000 (99.064) +2022-11-14 13:56:43,075 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0867) Prec@1 83.000 (85.271) Prec@5 99.000 (99.062) +2022-11-14 13:56:43,086 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0861) Prec@1 88.000 (85.327) Prec@5 100.000 (99.082) +2022-11-14 13:56:43,098 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0863) Prec@1 84.000 (85.300) Prec@5 99.000 (99.080) +2022-11-14 13:56:43,109 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0863) Prec@1 87.000 (85.333) Prec@5 97.000 (99.039) +2022-11-14 13:56:43,119 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0866) Prec@1 81.000 (85.250) Prec@5 100.000 (99.058) +2022-11-14 13:56:43,130 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0863) Prec@1 85.000 (85.245) Prec@5 100.000 (99.075) +2022-11-14 13:56:43,139 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0865) Prec@1 85.000 (85.241) Prec@5 98.000 (99.056) +2022-11-14 13:56:43,150 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1306 (0.0873) Prec@1 76.000 (85.073) Prec@5 100.000 (99.073) +2022-11-14 13:56:43,159 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0871) Prec@1 86.000 (85.089) Prec@5 100.000 (99.089) +2022-11-14 13:56:43,170 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0872) Prec@1 83.000 (85.053) Prec@5 100.000 (99.105) +2022-11-14 13:56:43,180 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0873) Prec@1 87.000 (85.086) Prec@5 98.000 (99.086) +2022-11-14 13:56:43,189 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0875) Prec@1 84.000 (85.068) Prec@5 99.000 (99.085) +2022-11-14 13:56:43,201 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0878) Prec@1 83.000 (85.033) Prec@5 100.000 (99.100) +2022-11-14 13:56:43,211 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0879) Prec@1 83.000 (85.000) Prec@5 100.000 (99.115) +2022-11-14 13:56:43,223 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0880) Prec@1 82.000 (84.952) Prec@5 100.000 (99.129) +2022-11-14 13:56:43,234 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0879) Prec@1 87.000 (84.984) Prec@5 100.000 (99.143) +2022-11-14 13:56:43,245 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0873) Prec@1 91.000 (85.078) Prec@5 100.000 (99.156) +2022-11-14 13:56:43,256 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0876) Prec@1 84.000 (85.062) Prec@5 96.000 (99.108) +2022-11-14 13:56:43,267 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0876) Prec@1 85.000 (85.061) Prec@5 99.000 (99.106) +2022-11-14 13:56:43,278 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0869) Prec@1 92.000 (85.164) Prec@5 100.000 (99.119) +2022-11-14 13:56:43,291 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0868) Prec@1 87.000 (85.191) Prec@5 99.000 (99.118) +2022-11-14 13:56:43,302 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0867) Prec@1 88.000 (85.232) Prec@5 100.000 (99.130) +2022-11-14 13:56:43,311 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1277 (0.0872) Prec@1 80.000 (85.157) Prec@5 98.000 (99.114) +2022-11-14 13:56:43,320 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0872) Prec@1 86.000 (85.169) Prec@5 99.000 (99.113) +2022-11-14 13:56:43,332 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0873) Prec@1 84.000 (85.153) Prec@5 99.000 (99.111) +2022-11-14 13:56:43,342 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0868) Prec@1 90.000 (85.219) Prec@5 99.000 (99.110) +2022-11-14 13:56:43,353 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0864) Prec@1 91.000 (85.297) Prec@5 100.000 (99.122) +2022-11-14 13:56:43,364 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0868) Prec@1 79.000 (85.213) Prec@5 98.000 (99.107) +2022-11-14 13:56:43,375 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0867) Prec@1 87.000 (85.237) Prec@5 99.000 (99.105) +2022-11-14 13:56:43,386 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0867) Prec@1 86.000 (85.247) Prec@5 99.000 (99.104) +2022-11-14 13:56:43,397 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0870) Prec@1 81.000 (85.192) Prec@5 99.000 (99.103) +2022-11-14 13:56:43,408 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0871) Prec@1 82.000 (85.152) Prec@5 99.000 (99.101) +2022-11-14 13:56:43,418 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0868) Prec@1 90.000 (85.213) Prec@5 98.000 (99.088) +2022-11-14 13:56:43,430 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0868) Prec@1 87.000 (85.235) Prec@5 99.000 (99.086) +2022-11-14 13:56:43,439 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0871) Prec@1 81.000 (85.183) Prec@5 100.000 (99.098) +2022-11-14 13:56:43,447 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0872) Prec@1 84.000 (85.169) Prec@5 100.000 (99.108) +2022-11-14 13:56:43,457 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0870) Prec@1 90.000 (85.226) Prec@5 99.000 (99.107) +2022-11-14 13:56:43,467 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0872) Prec@1 83.000 (85.200) Prec@5 99.000 (99.106) +2022-11-14 13:56:43,480 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0872) Prec@1 87.000 (85.221) Prec@5 99.000 (99.105) +2022-11-14 13:56:43,492 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0872) Prec@1 85.000 (85.218) Prec@5 100.000 (99.115) +2022-11-14 13:56:43,502 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0871) Prec@1 88.000 (85.250) Prec@5 100.000 (99.125) +2022-11-14 13:56:43,514 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0873) Prec@1 81.000 (85.202) Prec@5 98.000 (99.112) +2022-11-14 13:56:43,525 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0873) Prec@1 86.000 (85.211) Prec@5 99.000 (99.111) +2022-11-14 13:56:43,535 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0871) Prec@1 89.000 (85.253) Prec@5 99.000 (99.110) +2022-11-14 13:56:43,547 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0422 (0.0866) Prec@1 92.000 (85.326) Prec@5 99.000 (99.109) +2022-11-14 13:56:43,557 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1266 (0.0870) Prec@1 79.000 (85.258) Prec@5 98.000 (99.097) +2022-11-14 13:56:43,568 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0870) Prec@1 86.000 (85.266) Prec@5 99.000 (99.096) +2022-11-14 13:56:43,578 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0871) Prec@1 85.000 (85.263) Prec@5 100.000 (99.105) +2022-11-14 13:56:43,589 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0871) Prec@1 85.000 (85.260) Prec@5 100.000 (99.115) +2022-11-14 13:56:43,599 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0870) Prec@1 86.000 (85.268) Prec@5 98.000 (99.103) +2022-11-14 13:56:43,610 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0872) Prec@1 85.000 (85.265) Prec@5 98.000 (99.092) +2022-11-14 13:56:43,619 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0874) Prec@1 79.000 (85.202) Prec@5 100.000 (99.101) +2022-11-14 13:56:43,631 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0873) Prec@1 87.000 (85.220) Prec@5 100.000 (99.110) +2022-11-14 13:56:43,687 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:56:44,004 Epoch: [121][0/500] Time 0.023 (0.023) Data 0.233 (0.233) Loss 0.0760 (0.0760) Prec@1 86.000 (86.000) Prec@5 98.000 (98.000) +2022-11-14 13:56:44,212 Epoch: [121][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0758 (0.0759) Prec@1 86.000 (86.000) Prec@5 99.000 (98.500) +2022-11-14 13:56:44,454 Epoch: [121][20/500] Time 0.027 (0.020) Data 0.001 (0.013) Loss 0.0620 (0.0713) Prec@1 89.000 (87.000) Prec@5 99.000 (98.667) +2022-11-14 13:56:44,738 Epoch: [121][30/500] Time 0.027 (0.022) Data 0.002 (0.009) Loss 0.0360 (0.0625) Prec@1 95.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 13:56:45,021 Epoch: [121][40/500] Time 0.027 (0.022) Data 0.001 (0.007) Loss 0.0599 (0.0619) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:56:45,307 Epoch: [121][50/500] Time 0.038 (0.023) Data 0.002 (0.006) Loss 0.0787 (0.0647) Prec@1 85.000 (88.333) Prec@5 99.000 (99.000) +2022-11-14 13:56:45,590 Epoch: [121][60/500] Time 0.027 (0.023) Data 0.002 (0.006) Loss 0.0702 (0.0655) Prec@1 86.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:56:45,876 Epoch: [121][70/500] Time 0.026 (0.024) Data 0.002 (0.005) Loss 0.0401 (0.0623) Prec@1 93.000 (88.625) Prec@5 100.000 (99.125) +2022-11-14 13:56:46,163 Epoch: [121][80/500] Time 0.027 (0.024) Data 0.001 (0.005) Loss 0.0864 (0.0650) Prec@1 83.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 13:56:46,618 Epoch: [121][90/500] Time 0.044 (0.026) Data 0.002 (0.004) Loss 0.0505 (0.0636) Prec@1 92.000 (88.400) Prec@5 100.000 (99.300) +2022-11-14 13:56:47,088 Epoch: [121][100/500] Time 0.043 (0.027) Data 0.001 (0.004) Loss 0.0759 (0.0647) Prec@1 90.000 (88.545) Prec@5 98.000 (99.182) +2022-11-14 13:56:47,558 Epoch: [121][110/500] Time 0.052 (0.029) Data 0.002 (0.004) Loss 0.0727 (0.0653) Prec@1 87.000 (88.417) Prec@5 100.000 (99.250) +2022-11-14 13:56:48,019 Epoch: [121][120/500] Time 0.044 (0.030) Data 0.002 (0.004) Loss 0.0462 (0.0639) Prec@1 92.000 (88.692) Prec@5 100.000 (99.308) +2022-11-14 13:56:48,487 Epoch: [121][130/500] Time 0.044 (0.031) Data 0.002 (0.004) Loss 0.0754 (0.0647) Prec@1 87.000 (88.571) Prec@5 98.000 (99.214) +2022-11-14 13:56:48,962 Epoch: [121][140/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0752 (0.0654) Prec@1 86.000 (88.400) Prec@5 100.000 (99.267) +2022-11-14 13:56:49,432 Epoch: [121][150/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0528 (0.0646) Prec@1 93.000 (88.688) Prec@5 100.000 (99.312) +2022-11-14 13:56:49,893 Epoch: [121][160/500] Time 0.044 (0.033) Data 0.001 (0.003) Loss 0.0569 (0.0642) Prec@1 90.000 (88.765) Prec@5 100.000 (99.353) +2022-11-14 13:56:50,354 Epoch: [121][170/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0523 (0.0635) Prec@1 90.000 (88.833) Prec@5 100.000 (99.389) +2022-11-14 13:56:50,819 Epoch: [121][180/500] Time 0.044 (0.034) Data 0.001 (0.003) Loss 0.0600 (0.0633) Prec@1 91.000 (88.947) Prec@5 100.000 (99.421) +2022-11-14 13:56:51,287 Epoch: [121][190/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0709 (0.0637) Prec@1 89.000 (88.950) Prec@5 99.000 (99.400) +2022-11-14 13:56:51,754 Epoch: [121][200/500] Time 0.053 (0.034) Data 0.001 (0.003) Loss 0.0751 (0.0642) Prec@1 87.000 (88.857) Prec@5 100.000 (99.429) +2022-11-14 13:56:52,209 Epoch: [121][210/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0592 (0.0640) Prec@1 89.000 (88.864) Prec@5 99.000 (99.409) +2022-11-14 13:56:52,677 Epoch: [121][220/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0896 (0.0651) Prec@1 82.000 (88.565) Prec@5 100.000 (99.435) +2022-11-14 13:56:53,142 Epoch: [121][230/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0498 (0.0645) Prec@1 94.000 (88.792) Prec@5 99.000 (99.417) +2022-11-14 13:56:53,610 Epoch: [121][240/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0759 (0.0649) Prec@1 87.000 (88.720) Prec@5 100.000 (99.440) +2022-11-14 13:56:54,068 Epoch: [121][250/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0715 (0.0652) Prec@1 87.000 (88.654) Prec@5 99.000 (99.423) +2022-11-14 13:56:54,528 Epoch: [121][260/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0520 (0.0647) Prec@1 93.000 (88.815) Prec@5 100.000 (99.444) +2022-11-14 13:56:54,997 Epoch: [121][270/500] Time 0.052 (0.036) Data 0.002 (0.003) Loss 0.0376 (0.0637) Prec@1 93.000 (88.964) Prec@5 100.000 (99.464) +2022-11-14 13:56:55,466 Epoch: [121][280/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0703 (0.0640) Prec@1 88.000 (88.931) Prec@5 99.000 (99.448) +2022-11-14 13:56:55,934 Epoch: [121][290/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0602 (0.0638) Prec@1 90.000 (88.967) Prec@5 100.000 (99.467) +2022-11-14 13:56:56,391 Epoch: [121][300/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0321 (0.0628) Prec@1 96.000 (89.194) Prec@5 100.000 (99.484) +2022-11-14 13:56:56,859 Epoch: [121][310/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0583 (0.0627) Prec@1 90.000 (89.219) Prec@5 100.000 (99.500) +2022-11-14 13:56:57,333 Epoch: [121][320/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0519 (0.0623) Prec@1 91.000 (89.273) Prec@5 99.000 (99.485) +2022-11-14 13:56:57,797 Epoch: [121][330/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0468 (0.0619) Prec@1 92.000 (89.353) Prec@5 100.000 (99.500) +2022-11-14 13:56:58,257 Epoch: [121][340/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0610 (0.0619) Prec@1 90.000 (89.371) Prec@5 100.000 (99.514) +2022-11-14 13:56:58,723 Epoch: [121][350/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0480 (0.0615) Prec@1 88.000 (89.333) Prec@5 100.000 (99.528) +2022-11-14 13:56:59,202 Epoch: [121][360/500] Time 0.045 (0.038) Data 0.002 (0.002) Loss 0.0440 (0.0610) Prec@1 92.000 (89.405) Prec@5 100.000 (99.541) +2022-11-14 13:56:59,668 Epoch: [121][370/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0623 (0.0610) Prec@1 90.000 (89.421) Prec@5 100.000 (99.553) +2022-11-14 13:57:00,140 Epoch: [121][380/500] Time 0.047 (0.038) Data 0.002 (0.002) Loss 0.0359 (0.0604) Prec@1 95.000 (89.564) Prec@5 100.000 (99.564) +2022-11-14 13:57:00,600 Epoch: [121][390/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0447 (0.0600) Prec@1 93.000 (89.650) Prec@5 99.000 (99.550) +2022-11-14 13:57:01,066 Epoch: [121][400/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0499 (0.0598) Prec@1 92.000 (89.707) Prec@5 100.000 (99.561) +2022-11-14 13:57:01,529 Epoch: [121][410/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0355 (0.0592) Prec@1 95.000 (89.833) Prec@5 100.000 (99.571) +2022-11-14 13:57:01,989 Epoch: [121][420/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0680 (0.0594) Prec@1 88.000 (89.791) Prec@5 100.000 (99.581) +2022-11-14 13:57:02,443 Epoch: [121][430/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0538 (0.0593) Prec@1 90.000 (89.795) Prec@5 100.000 (99.591) +2022-11-14 13:57:02,908 Epoch: [121][440/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0543 (0.0591) Prec@1 90.000 (89.800) Prec@5 99.000 (99.578) +2022-11-14 13:57:03,371 Epoch: [121][450/500] Time 0.044 (0.038) Data 0.001 (0.002) Loss 0.0675 (0.0593) Prec@1 91.000 (89.826) Prec@5 99.000 (99.565) +2022-11-14 13:57:03,837 Epoch: [121][460/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0648 (0.0594) Prec@1 89.000 (89.809) Prec@5 100.000 (99.574) +2022-11-14 13:57:04,310 Epoch: [121][470/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0616 (0.0595) Prec@1 89.000 (89.792) Prec@5 100.000 (99.583) +2022-11-14 13:57:04,759 Epoch: [121][480/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0510 (0.0593) Prec@1 93.000 (89.857) Prec@5 98.000 (99.551) +2022-11-14 13:57:05,230 Epoch: [121][490/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0648 (0.0594) Prec@1 88.000 (89.820) Prec@5 100.000 (99.560) +2022-11-14 13:57:05,682 Epoch: [121][499/500] Time 0.067 (0.039) Data 0.001 (0.002) Loss 0.0623 (0.0595) Prec@1 88.000 (89.784) Prec@5 98.000 (99.529) +2022-11-14 13:57:05,970 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0473 (0.0473) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 13:57:05,980 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0609) Prec@1 87.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 13:57:05,989 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0653) Prec@1 87.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,000 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0681) Prec@1 87.000 (88.250) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,008 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0699) Prec@1 89.000 (88.400) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,017 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0658) Prec@1 93.000 (89.167) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,026 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0656) Prec@1 89.000 (89.143) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,035 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0693) Prec@1 84.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 13:57:06,043 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0715) Prec@1 86.000 (88.222) Prec@5 99.000 (99.889) +2022-11-14 13:57:06,052 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0699) Prec@1 90.000 (88.400) Prec@5 100.000 (99.900) +2022-11-14 13:57:06,061 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0713) Prec@1 84.000 (88.000) Prec@5 99.000 (99.818) +2022-11-14 13:57:06,071 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0727) Prec@1 84.000 (87.667) Prec@5 100.000 (99.833) +2022-11-14 13:57:06,081 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0721) Prec@1 89.000 (87.769) Prec@5 100.000 (99.846) +2022-11-14 13:57:06,092 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0719) Prec@1 88.000 (87.786) Prec@5 100.000 (99.857) +2022-11-14 13:57:06,102 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0721) Prec@1 87.000 (87.733) Prec@5 98.000 (99.733) +2022-11-14 13:57:06,111 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0731) Prec@1 84.000 (87.500) Prec@5 99.000 (99.688) +2022-11-14 13:57:06,120 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0721) Prec@1 91.000 (87.706) Prec@5 98.000 (99.588) +2022-11-14 13:57:06,130 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0743) Prec@1 81.000 (87.333) Prec@5 100.000 (99.611) +2022-11-14 13:57:06,138 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0748) Prec@1 85.000 (87.211) Prec@5 99.000 (99.579) +2022-11-14 13:57:06,147 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0759) Prec@1 86.000 (87.150) Prec@5 99.000 (99.550) +2022-11-14 13:57:06,155 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0772) Prec@1 79.000 (86.762) Prec@5 99.000 (99.524) +2022-11-14 13:57:06,163 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0772) Prec@1 86.000 (86.727) Prec@5 100.000 (99.545) +2022-11-14 13:57:06,171 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0781) Prec@1 85.000 (86.652) Prec@5 99.000 (99.522) +2022-11-14 13:57:06,180 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0780) Prec@1 86.000 (86.625) Prec@5 100.000 (99.542) +2022-11-14 13:57:06,190 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0784) Prec@1 84.000 (86.520) Prec@5 100.000 (99.560) +2022-11-14 13:57:06,199 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0789) Prec@1 84.000 (86.423) Prec@5 96.000 (99.423) +2022-11-14 13:57:06,208 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0780) Prec@1 89.000 (86.519) Prec@5 100.000 (99.444) +2022-11-14 13:57:06,218 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0781) Prec@1 88.000 (86.571) Prec@5 100.000 (99.464) +2022-11-14 13:57:06,227 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0778) Prec@1 87.000 (86.586) Prec@5 99.000 (99.448) +2022-11-14 13:57:06,236 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0779) Prec@1 86.000 (86.567) Prec@5 99.000 (99.433) +2022-11-14 13:57:06,245 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0781) Prec@1 85.000 (86.516) Prec@5 98.000 (99.387) +2022-11-14 13:57:06,255 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0779) Prec@1 90.000 (86.625) Prec@5 100.000 (99.406) +2022-11-14 13:57:06,263 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0781) Prec@1 84.000 (86.545) Prec@5 98.000 (99.364) +2022-11-14 13:57:06,273 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0789) Prec@1 79.000 (86.324) Prec@5 99.000 (99.353) +2022-11-14 13:57:06,282 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0785) Prec@1 87.000 (86.343) Prec@5 99.000 (99.343) +2022-11-14 13:57:06,292 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0783) Prec@1 89.000 (86.417) Prec@5 99.000 (99.333) +2022-11-14 13:57:06,301 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0781) Prec@1 88.000 (86.459) Prec@5 99.000 (99.324) +2022-11-14 13:57:06,310 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0791) Prec@1 79.000 (86.263) Prec@5 99.000 (99.316) +2022-11-14 13:57:06,319 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0786) Prec@1 91.000 (86.385) Prec@5 100.000 (99.333) +2022-11-14 13:57:06,329 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0783) Prec@1 89.000 (86.450) Prec@5 99.000 (99.325) +2022-11-14 13:57:06,338 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0790) Prec@1 79.000 (86.268) Prec@5 99.000 (99.317) +2022-11-14 13:57:06,347 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0792) Prec@1 86.000 (86.262) Prec@5 97.000 (99.262) +2022-11-14 13:57:06,356 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0786) Prec@1 90.000 (86.349) Prec@5 100.000 (99.279) +2022-11-14 13:57:06,366 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0783) Prec@1 92.000 (86.477) Prec@5 99.000 (99.273) +2022-11-14 13:57:06,375 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0781) Prec@1 88.000 (86.511) Prec@5 100.000 (99.289) +2022-11-14 13:57:06,384 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0786) Prec@1 80.000 (86.370) Prec@5 99.000 (99.283) +2022-11-14 13:57:06,393 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0786) Prec@1 85.000 (86.340) Prec@5 100.000 (99.298) +2022-11-14 13:57:06,402 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0789) Prec@1 86.000 (86.333) Prec@5 100.000 (99.312) +2022-11-14 13:57:06,412 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0786) Prec@1 88.000 (86.367) Prec@5 100.000 (99.327) +2022-11-14 13:57:06,421 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1231 (0.0795) Prec@1 79.000 (86.220) Prec@5 99.000 (99.320) +2022-11-14 13:57:06,430 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0793) Prec@1 88.000 (86.255) Prec@5 99.000 (99.314) +2022-11-14 13:57:06,438 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0792) Prec@1 88.000 (86.288) Prec@5 98.000 (99.288) +2022-11-14 13:57:06,447 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0790) Prec@1 90.000 (86.358) Prec@5 99.000 (99.283) +2022-11-14 13:57:06,455 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0787) Prec@1 88.000 (86.389) Prec@5 100.000 (99.296) +2022-11-14 13:57:06,463 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0792) Prec@1 82.000 (86.309) Prec@5 100.000 (99.309) +2022-11-14 13:57:06,471 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0793) Prec@1 87.000 (86.321) Prec@5 99.000 (99.304) +2022-11-14 13:57:06,479 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0791) Prec@1 86.000 (86.316) Prec@5 100.000 (99.316) +2022-11-14 13:57:06,489 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0789) Prec@1 89.000 (86.362) Prec@5 98.000 (99.293) +2022-11-14 13:57:06,497 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1218 (0.0796) Prec@1 78.000 (86.220) Prec@5 100.000 (99.305) +2022-11-14 13:57:06,506 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0798) Prec@1 84.000 (86.183) Prec@5 99.000 (99.300) +2022-11-14 13:57:06,515 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0799) Prec@1 85.000 (86.164) Prec@5 100.000 (99.311) +2022-11-14 13:57:06,524 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0798) Prec@1 86.000 (86.161) Prec@5 99.000 (99.306) +2022-11-14 13:57:06,532 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0798) Prec@1 87.000 (86.175) Prec@5 99.000 (99.302) +2022-11-14 13:57:06,541 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0795) Prec@1 89.000 (86.219) Prec@5 100.000 (99.312) +2022-11-14 13:57:06,549 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0798) Prec@1 80.000 (86.123) Prec@5 100.000 (99.323) +2022-11-14 13:57:06,559 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0801) Prec@1 83.000 (86.076) Prec@5 99.000 (99.318) +2022-11-14 13:57:06,567 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0796) Prec@1 92.000 (86.164) Prec@5 100.000 (99.328) +2022-11-14 13:57:06,575 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0794) Prec@1 87.000 (86.176) Prec@5 99.000 (99.324) +2022-11-14 13:57:06,583 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0794) Prec@1 88.000 (86.203) Prec@5 99.000 (99.319) +2022-11-14 13:57:06,593 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0795) Prec@1 86.000 (86.200) Prec@5 98.000 (99.300) +2022-11-14 13:57:06,602 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0798) Prec@1 85.000 (86.183) Prec@5 99.000 (99.296) +2022-11-14 13:57:06,610 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0795) Prec@1 90.000 (86.236) Prec@5 100.000 (99.306) +2022-11-14 13:57:06,619 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0792) Prec@1 91.000 (86.301) Prec@5 100.000 (99.315) +2022-11-14 13:57:06,628 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0397 (0.0787) Prec@1 93.000 (86.392) Prec@5 100.000 (99.324) +2022-11-14 13:57:06,637 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0790) Prec@1 81.000 (86.320) Prec@5 100.000 (99.333) +2022-11-14 13:57:06,645 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0786) Prec@1 92.000 (86.395) Prec@5 100.000 (99.342) +2022-11-14 13:57:06,655 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0786) Prec@1 87.000 (86.403) Prec@5 99.000 (99.338) +2022-11-14 13:57:06,664 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0787) Prec@1 86.000 (86.397) Prec@5 99.000 (99.333) +2022-11-14 13:57:06,672 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0787) Prec@1 88.000 (86.418) Prec@5 100.000 (99.342) +2022-11-14 13:57:06,681 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0786) Prec@1 88.000 (86.438) Prec@5 99.000 (99.338) +2022-11-14 13:57:06,691 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0786) Prec@1 85.000 (86.420) Prec@5 100.000 (99.346) +2022-11-14 13:57:06,700 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0786) Prec@1 87.000 (86.427) Prec@5 100.000 (99.354) +2022-11-14 13:57:06,710 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0786) Prec@1 84.000 (86.398) Prec@5 100.000 (99.361) +2022-11-14 13:57:06,720 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0786) Prec@1 89.000 (86.429) Prec@5 100.000 (99.369) +2022-11-14 13:57:06,728 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0786) Prec@1 89.000 (86.459) Prec@5 100.000 (99.376) +2022-11-14 13:57:06,736 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0787) Prec@1 83.000 (86.419) Prec@5 99.000 (99.372) +2022-11-14 13:57:06,745 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0787) Prec@1 88.000 (86.437) Prec@5 99.000 (99.368) +2022-11-14 13:57:06,755 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0787) Prec@1 85.000 (86.420) Prec@5 99.000 (99.364) +2022-11-14 13:57:06,763 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0786) Prec@1 87.000 (86.427) Prec@5 100.000 (99.371) +2022-11-14 13:57:06,772 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0787) Prec@1 86.000 (86.422) Prec@5 99.000 (99.367) +2022-11-14 13:57:06,781 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0784) Prec@1 92.000 (86.484) Prec@5 100.000 (99.374) +2022-11-14 13:57:06,790 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0784) Prec@1 88.000 (86.500) Prec@5 99.000 (99.370) +2022-11-14 13:57:06,799 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0784) Prec@1 90.000 (86.538) Prec@5 99.000 (99.366) +2022-11-14 13:57:06,809 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0784) Prec@1 87.000 (86.543) Prec@5 98.000 (99.351) +2022-11-14 13:57:06,818 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0784) Prec@1 84.000 (86.516) Prec@5 100.000 (99.358) +2022-11-14 13:57:06,827 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0784) Prec@1 89.000 (86.542) Prec@5 100.000 (99.365) +2022-11-14 13:57:06,836 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0781) Prec@1 92.000 (86.598) Prec@5 99.000 (99.361) +2022-11-14 13:57:06,845 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.0785) Prec@1 81.000 (86.541) Prec@5 98.000 (99.347) +2022-11-14 13:57:06,854 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0787) Prec@1 82.000 (86.495) Prec@5 100.000 (99.354) +2022-11-14 13:57:06,863 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0785) Prec@1 89.000 (86.520) Prec@5 100.000 (99.360) +2022-11-14 13:57:06,923 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:57:07,263 Epoch: [122][0/500] Time 0.033 (0.033) Data 0.248 (0.248) Loss 0.0940 (0.0940) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 13:57:07,468 Epoch: [122][10/500] Time 0.019 (0.020) Data 0.002 (0.024) Loss 0.0501 (0.0721) Prec@1 92.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:57:07,712 Epoch: [122][20/500] Time 0.031 (0.020) Data 0.002 (0.014) Loss 0.0760 (0.0734) Prec@1 88.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 13:57:07,970 Epoch: [122][30/500] Time 0.025 (0.021) Data 0.002 (0.010) Loss 0.0705 (0.0726) Prec@1 90.000 (89.000) Prec@5 99.000 (99.250) +2022-11-14 13:57:08,252 Epoch: [122][40/500] Time 0.027 (0.022) Data 0.002 (0.008) Loss 0.0609 (0.0703) Prec@1 91.000 (89.400) Prec@5 99.000 (99.200) +2022-11-14 13:57:08,522 Epoch: [122][50/500] Time 0.024 (0.022) Data 0.002 (0.007) Loss 0.0793 (0.0718) Prec@1 85.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 13:57:08,797 Epoch: [122][60/500] Time 0.027 (0.023) Data 0.001 (0.006) Loss 0.0449 (0.0679) Prec@1 93.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 13:57:09,078 Epoch: [122][70/500] Time 0.024 (0.023) Data 0.001 (0.005) Loss 0.0507 (0.0658) Prec@1 91.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 13:57:09,374 Epoch: [122][80/500] Time 0.031 (0.023) Data 0.002 (0.005) Loss 0.0710 (0.0664) Prec@1 87.000 (89.222) Prec@5 100.000 (99.556) +2022-11-14 13:57:09,668 Epoch: [122][90/500] Time 0.024 (0.024) Data 0.002 (0.005) Loss 0.0555 (0.0653) Prec@1 89.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 13:57:09,956 Epoch: [122][100/500] Time 0.024 (0.024) Data 0.002 (0.004) Loss 0.0725 (0.0659) Prec@1 86.000 (88.909) Prec@5 100.000 (99.636) +2022-11-14 13:57:10,236 Epoch: [122][110/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0595 (0.0654) Prec@1 88.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 13:57:10,518 Epoch: [122][120/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0328 (0.0629) Prec@1 95.000 (89.308) Prec@5 100.000 (99.692) +2022-11-14 13:57:10,806 Epoch: [122][130/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0315 (0.0607) Prec@1 94.000 (89.643) Prec@5 100.000 (99.714) +2022-11-14 13:57:11,083 Epoch: [122][140/500] Time 0.024 (0.024) Data 0.002 (0.004) Loss 0.0801 (0.0619) Prec@1 86.000 (89.400) Prec@5 100.000 (99.733) +2022-11-14 13:57:11,364 Epoch: [122][150/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0545 (0.0615) Prec@1 90.000 (89.438) Prec@5 100.000 (99.750) +2022-11-14 13:57:11,642 Epoch: [122][160/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0568 (0.0612) Prec@1 88.000 (89.353) Prec@5 100.000 (99.765) +2022-11-14 13:57:12,088 Epoch: [122][170/500] Time 0.058 (0.025) Data 0.003 (0.003) Loss 0.0563 (0.0609) Prec@1 90.000 (89.389) Prec@5 100.000 (99.778) +2022-11-14 13:57:12,802 Epoch: [122][180/500] Time 0.071 (0.027) Data 0.002 (0.003) Loss 0.0756 (0.0617) Prec@1 88.000 (89.316) Prec@5 99.000 (99.737) +2022-11-14 13:57:13,378 Epoch: [122][190/500] Time 0.072 (0.029) Data 0.002 (0.003) Loss 0.0564 (0.0614) Prec@1 91.000 (89.400) Prec@5 99.000 (99.700) +2022-11-14 13:57:13,985 Epoch: [122][200/500] Time 0.078 (0.030) Data 0.002 (0.003) Loss 0.0657 (0.0616) Prec@1 90.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 13:57:14,455 Epoch: [122][210/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.0345 (0.0604) Prec@1 97.000 (89.773) Prec@5 99.000 (99.682) +2022-11-14 13:57:14,995 Epoch: [122][220/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0570 (0.0603) Prec@1 90.000 (89.783) Prec@5 100.000 (99.696) +2022-11-14 13:57:15,551 Epoch: [122][230/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0848 (0.0613) Prec@1 84.000 (89.542) Prec@5 98.000 (99.625) +2022-11-14 13:57:16,038 Epoch: [122][240/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0493 (0.0608) Prec@1 91.000 (89.600) Prec@5 100.000 (99.640) +2022-11-14 13:57:16,558 Epoch: [122][250/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0742 (0.0613) Prec@1 88.000 (89.538) Prec@5 100.000 (99.654) +2022-11-14 13:57:17,129 Epoch: [122][260/500] Time 0.079 (0.034) Data 0.002 (0.003) Loss 0.0631 (0.0614) Prec@1 88.000 (89.481) Prec@5 99.000 (99.630) +2022-11-14 13:57:17,727 Epoch: [122][270/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0552 (0.0612) Prec@1 91.000 (89.536) Prec@5 99.000 (99.607) +2022-11-14 13:57:18,205 Epoch: [122][280/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0416 (0.0605) Prec@1 93.000 (89.655) Prec@5 99.000 (99.586) +2022-11-14 13:57:18,750 Epoch: [122][290/500] Time 0.077 (0.035) Data 0.002 (0.003) Loss 0.0668 (0.0607) Prec@1 85.000 (89.500) Prec@5 100.000 (99.600) +2022-11-14 13:57:19,385 Epoch: [122][300/500] Time 0.050 (0.036) Data 0.002 (0.003) Loss 0.0497 (0.0603) Prec@1 93.000 (89.613) Prec@5 99.000 (99.581) +2022-11-14 13:57:20,044 Epoch: [122][310/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0474 (0.0599) Prec@1 93.000 (89.719) Prec@5 99.000 (99.562) +2022-11-14 13:57:20,654 Epoch: [122][320/500] Time 0.076 (0.037) Data 0.002 (0.003) Loss 0.0701 (0.0602) Prec@1 88.000 (89.667) Prec@5 99.000 (99.545) +2022-11-14 13:57:21,125 Epoch: [122][330/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0549 (0.0601) Prec@1 90.000 (89.676) Prec@5 100.000 (99.559) +2022-11-14 13:57:21,622 Epoch: [122][340/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0543 (0.0599) Prec@1 92.000 (89.743) Prec@5 98.000 (99.514) +2022-11-14 13:57:22,171 Epoch: [122][350/500] Time 0.071 (0.038) Data 0.002 (0.003) Loss 0.0425 (0.0594) Prec@1 92.000 (89.806) Prec@5 100.000 (99.528) +2022-11-14 13:57:22,686 Epoch: [122][360/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.0447 (0.0590) Prec@1 91.000 (89.838) Prec@5 100.000 (99.541) +2022-11-14 13:57:23,027 Epoch: [122][370/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.0612 (0.0591) Prec@1 90.000 (89.842) Prec@5 99.000 (99.526) +2022-11-14 13:57:23,321 Epoch: [122][380/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.0632 (0.0592) Prec@1 89.000 (89.821) Prec@5 100.000 (99.538) +2022-11-14 13:57:23,643 Epoch: [122][390/500] Time 0.024 (0.037) Data 0.002 (0.003) Loss 0.0455 (0.0589) Prec@1 91.000 (89.850) Prec@5 97.000 (99.475) +2022-11-14 13:57:23,963 Epoch: [122][400/500] Time 0.023 (0.037) Data 0.002 (0.003) Loss 0.0502 (0.0586) Prec@1 91.000 (89.878) Prec@5 99.000 (99.463) +2022-11-14 13:57:24,262 Epoch: [122][410/500] Time 0.028 (0.037) Data 0.002 (0.003) Loss 0.0726 (0.0590) Prec@1 86.000 (89.786) Prec@5 98.000 (99.429) +2022-11-14 13:57:24,581 Epoch: [122][420/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0548 (0.0589) Prec@1 89.000 (89.767) Prec@5 100.000 (99.442) +2022-11-14 13:57:24,904 Epoch: [122][430/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0693 (0.0591) Prec@1 88.000 (89.727) Prec@5 99.000 (99.432) +2022-11-14 13:57:25,251 Epoch: [122][440/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.0626 (0.0592) Prec@1 91.000 (89.756) Prec@5 99.000 (99.422) +2022-11-14 13:57:25,544 Epoch: [122][450/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0608 (0.0592) Prec@1 91.000 (89.783) Prec@5 97.000 (99.370) +2022-11-14 13:57:25,900 Epoch: [122][460/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0494 (0.0590) Prec@1 95.000 (89.894) Prec@5 99.000 (99.362) +2022-11-14 13:57:26,200 Epoch: [122][470/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0523 (0.0589) Prec@1 91.000 (89.917) Prec@5 100.000 (99.375) +2022-11-14 13:57:26,513 Epoch: [122][480/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0568 (0.0588) Prec@1 91.000 (89.939) Prec@5 99.000 (99.367) +2022-11-14 13:57:26,817 Epoch: [122][490/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0501 (0.0587) Prec@1 93.000 (90.000) Prec@5 100.000 (99.380) +2022-11-14 13:57:27,098 Epoch: [122][499/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0753 (0.0590) Prec@1 85.000 (89.902) Prec@5 100.000 (99.392) +2022-11-14 13:57:27,377 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0635 (0.0635) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:57:27,389 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0689) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 13:57:27,400 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0927 (0.0768) Prec@1 85.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 13:57:27,413 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0900 (0.0801) Prec@1 84.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 13:57:27,421 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0808) Prec@1 87.000 (86.600) Prec@5 100.000 (99.600) +2022-11-14 13:57:27,429 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0791) Prec@1 88.000 (86.833) Prec@5 100.000 (99.667) +2022-11-14 13:57:27,439 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0779) Prec@1 88.000 (87.000) Prec@5 100.000 (99.714) +2022-11-14 13:57:27,451 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0804) Prec@1 82.000 (86.375) Prec@5 98.000 (99.500) +2022-11-14 13:57:27,459 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0812) Prec@1 84.000 (86.111) Prec@5 99.000 (99.444) +2022-11-14 13:57:27,468 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0783) Prec@1 90.000 (86.500) Prec@5 99.000 (99.400) +2022-11-14 13:57:27,479 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0774) Prec@1 89.000 (86.727) Prec@5 100.000 (99.455) +2022-11-14 13:57:27,490 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0796) Prec@1 81.000 (86.250) Prec@5 100.000 (99.500) +2022-11-14 13:57:27,498 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0782) Prec@1 89.000 (86.462) Prec@5 100.000 (99.538) +2022-11-14 13:57:27,506 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0780) Prec@1 86.000 (86.429) Prec@5 98.000 (99.429) +2022-11-14 13:57:27,518 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0779) Prec@1 87.000 (86.467) Prec@5 100.000 (99.467) +2022-11-14 13:57:27,528 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0786) Prec@1 85.000 (86.375) Prec@5 99.000 (99.438) +2022-11-14 13:57:27,538 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0767) Prec@1 92.000 (86.706) Prec@5 99.000 (99.412) +2022-11-14 13:57:27,546 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.0786) Prec@1 78.000 (86.222) Prec@5 99.000 (99.389) +2022-11-14 13:57:27,559 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.0800) Prec@1 84.000 (86.105) Prec@5 98.000 (99.316) +2022-11-14 13:57:27,571 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1152 (0.0818) Prec@1 81.000 (85.850) Prec@5 99.000 (99.300) +2022-11-14 13:57:27,581 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0826) Prec@1 84.000 (85.762) Prec@5 100.000 (99.333) +2022-11-14 13:57:27,595 Test: [21/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0835) Prec@1 82.000 (85.591) Prec@5 99.000 (99.318) +2022-11-14 13:57:27,607 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0839) Prec@1 86.000 (85.609) Prec@5 99.000 (99.304) +2022-11-14 13:57:27,620 Test: [23/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.0851) Prec@1 81.000 (85.417) Prec@5 97.000 (99.208) +2022-11-14 13:57:27,632 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0851) Prec@1 86.000 (85.440) Prec@5 100.000 (99.240) +2022-11-14 13:57:27,642 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.0860) Prec@1 83.000 (85.346) Prec@5 96.000 (99.115) +2022-11-14 13:57:27,652 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0849) Prec@1 89.000 (85.481) Prec@5 100.000 (99.148) +2022-11-14 13:57:27,660 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0844) Prec@1 90.000 (85.643) Prec@5 100.000 (99.179) +2022-11-14 13:57:27,668 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0835) Prec@1 89.000 (85.759) Prec@5 98.000 (99.138) +2022-11-14 13:57:27,676 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0837) Prec@1 86.000 (85.767) Prec@5 99.000 (99.133) +2022-11-14 13:57:27,684 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0835) Prec@1 87.000 (85.806) Prec@5 99.000 (99.129) +2022-11-14 13:57:27,692 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0833) Prec@1 86.000 (85.812) Prec@5 100.000 (99.156) +2022-11-14 13:57:27,701 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0836) Prec@1 83.000 (85.727) Prec@5 100.000 (99.182) +2022-11-14 13:57:27,711 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1139 (0.0845) Prec@1 81.000 (85.588) Prec@5 100.000 (99.206) +2022-11-14 13:57:27,720 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0844) Prec@1 86.000 (85.600) Prec@5 99.000 (99.200) +2022-11-14 13:57:27,730 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0840) Prec@1 88.000 (85.667) Prec@5 100.000 (99.222) +2022-11-14 13:57:27,740 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0838) Prec@1 85.000 (85.649) Prec@5 99.000 (99.216) +2022-11-14 13:57:27,749 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.0844) Prec@1 81.000 (85.526) Prec@5 100.000 (99.237) +2022-11-14 13:57:27,759 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0839) Prec@1 90.000 (85.641) Prec@5 99.000 (99.231) +2022-11-14 13:57:27,768 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0837) Prec@1 87.000 (85.675) Prec@5 99.000 (99.225) +2022-11-14 13:57:27,777 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0838) Prec@1 88.000 (85.732) Prec@5 98.000 (99.195) +2022-11-14 13:57:27,787 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0833) Prec@1 90.000 (85.833) Prec@5 99.000 (99.190) +2022-11-14 13:57:27,796 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0827) Prec@1 88.000 (85.884) Prec@5 98.000 (99.163) +2022-11-14 13:57:27,805 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0823) Prec@1 90.000 (85.977) Prec@5 98.000 (99.136) +2022-11-14 13:57:27,814 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0823) Prec@1 86.000 (85.978) Prec@5 99.000 (99.133) +2022-11-14 13:57:27,824 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0825) Prec@1 83.000 (85.913) Prec@5 100.000 (99.152) +2022-11-14 13:57:27,833 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0823) Prec@1 86.000 (85.915) Prec@5 100.000 (99.170) +2022-11-14 13:57:27,843 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0826) Prec@1 85.000 (85.896) Prec@5 99.000 (99.167) +2022-11-14 13:57:27,853 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0340 (0.0816) Prec@1 95.000 (86.082) Prec@5 100.000 (99.184) +2022-11-14 13:57:27,862 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1120 (0.0822) Prec@1 80.000 (85.960) Prec@5 98.000 (99.160) +2022-11-14 13:57:27,872 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0821) Prec@1 88.000 (86.000) Prec@5 100.000 (99.176) +2022-11-14 13:57:27,882 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0825) Prec@1 80.000 (85.885) Prec@5 100.000 (99.192) +2022-11-14 13:57:27,891 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0823) Prec@1 87.000 (85.906) Prec@5 100.000 (99.208) +2022-11-14 13:57:27,900 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0822) Prec@1 84.000 (85.870) Prec@5 100.000 (99.222) +2022-11-14 13:57:27,909 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0822) Prec@1 83.000 (85.818) Prec@5 100.000 (99.236) +2022-11-14 13:57:27,919 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0821) Prec@1 88.000 (85.857) Prec@5 98.000 (99.214) +2022-11-14 13:57:27,928 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0820) Prec@1 87.000 (85.877) Prec@5 100.000 (99.228) +2022-11-14 13:57:27,937 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0816) Prec@1 91.000 (85.966) Prec@5 98.000 (99.207) +2022-11-14 13:57:27,947 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0820) Prec@1 83.000 (85.915) Prec@5 100.000 (99.220) +2022-11-14 13:57:27,955 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0817) Prec@1 90.000 (85.983) Prec@5 99.000 (99.217) +2022-11-14 13:57:27,964 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0821) Prec@1 85.000 (85.967) Prec@5 100.000 (99.230) +2022-11-14 13:57:27,973 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0822) Prec@1 85.000 (85.952) Prec@5 100.000 (99.242) +2022-11-14 13:57:27,982 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0819) Prec@1 88.000 (85.984) Prec@5 100.000 (99.254) +2022-11-14 13:57:27,990 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0816) Prec@1 91.000 (86.062) Prec@5 100.000 (99.266) +2022-11-14 13:57:27,999 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0816) Prec@1 85.000 (86.046) Prec@5 100.000 (99.277) +2022-11-14 13:57:28,009 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0818) Prec@1 82.000 (85.985) Prec@5 98.000 (99.258) +2022-11-14 13:57:28,018 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0813) Prec@1 95.000 (86.119) Prec@5 100.000 (99.269) +2022-11-14 13:57:28,027 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0812) Prec@1 87.000 (86.132) Prec@5 98.000 (99.250) +2022-11-14 13:57:28,037 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0808) Prec@1 90.000 (86.188) Prec@5 100.000 (99.261) +2022-11-14 13:57:28,046 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0809) Prec@1 88.000 (86.214) Prec@5 98.000 (99.243) +2022-11-14 13:57:28,055 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0811) Prec@1 84.000 (86.183) Prec@5 100.000 (99.254) +2022-11-14 13:57:28,065 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0812) Prec@1 87.000 (86.194) Prec@5 98.000 (99.236) +2022-11-14 13:57:28,074 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0809) Prec@1 90.000 (86.247) Prec@5 100.000 (99.247) +2022-11-14 13:57:28,083 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0807) Prec@1 91.000 (86.311) Prec@5 99.000 (99.243) +2022-11-14 13:57:28,093 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0810) Prec@1 84.000 (86.280) Prec@5 100.000 (99.253) +2022-11-14 13:57:28,101 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0808) Prec@1 88.000 (86.303) Prec@5 100.000 (99.263) +2022-11-14 13:57:28,111 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0808) Prec@1 86.000 (86.299) Prec@5 100.000 (99.273) +2022-11-14 13:57:28,120 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0807) Prec@1 90.000 (86.346) Prec@5 98.000 (99.256) +2022-11-14 13:57:28,130 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0809) Prec@1 85.000 (86.329) Prec@5 100.000 (99.266) +2022-11-14 13:57:28,140 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0809) Prec@1 86.000 (86.325) Prec@5 100.000 (99.275) +2022-11-14 13:57:28,150 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0809) Prec@1 84.000 (86.296) Prec@5 99.000 (99.272) +2022-11-14 13:57:28,159 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0809) Prec@1 88.000 (86.317) Prec@5 100.000 (99.280) +2022-11-14 13:57:28,169 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0807) Prec@1 87.000 (86.325) Prec@5 100.000 (99.289) +2022-11-14 13:57:28,178 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0807) Prec@1 84.000 (86.298) Prec@5 99.000 (99.286) +2022-11-14 13:57:28,188 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0809) Prec@1 83.000 (86.259) Prec@5 97.000 (99.259) +2022-11-14 13:57:28,198 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0809) Prec@1 86.000 (86.256) Prec@5 99.000 (99.256) +2022-11-14 13:57:28,206 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0808) Prec@1 87.000 (86.264) Prec@5 99.000 (99.253) +2022-11-14 13:57:28,215 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0809) Prec@1 81.000 (86.205) Prec@5 98.000 (99.239) +2022-11-14 13:57:28,225 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0808) Prec@1 87.000 (86.213) Prec@5 100.000 (99.247) +2022-11-14 13:57:28,234 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0810) Prec@1 85.000 (86.200) Prec@5 100.000 (99.256) +2022-11-14 13:57:28,243 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0807) Prec@1 91.000 (86.253) Prec@5 100.000 (99.264) +2022-11-14 13:57:28,252 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0806) Prec@1 88.000 (86.272) Prec@5 99.000 (99.261) +2022-11-14 13:57:28,260 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0805) Prec@1 89.000 (86.301) Prec@5 100.000 (99.269) +2022-11-14 13:57:28,268 Test: [93/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0807) Prec@1 81.000 (86.245) Prec@5 99.000 (99.266) +2022-11-14 13:57:28,277 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0809) Prec@1 85.000 (86.232) Prec@5 99.000 (99.263) +2022-11-14 13:57:28,285 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0809) Prec@1 86.000 (86.229) Prec@5 100.000 (99.271) +2022-11-14 13:57:28,295 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0806) Prec@1 91.000 (86.278) Prec@5 98.000 (99.258) +2022-11-14 13:57:28,303 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0808) Prec@1 85.000 (86.265) Prec@5 98.000 (99.245) +2022-11-14 13:57:28,311 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0806) Prec@1 90.000 (86.303) Prec@5 100.000 (99.253) +2022-11-14 13:57:28,319 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0803) Prec@1 91.000 (86.350) Prec@5 100.000 (99.260) +2022-11-14 13:57:28,373 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:57:28,674 Epoch: [123][0/500] Time 0.025 (0.025) Data 0.217 (0.217) Loss 0.0666 (0.0666) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 13:57:29,012 Epoch: [123][10/500] Time 0.038 (0.029) Data 0.002 (0.021) Loss 0.0451 (0.0559) Prec@1 92.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 13:57:29,418 Epoch: [123][20/500] Time 0.039 (0.032) Data 0.002 (0.012) Loss 0.0552 (0.0556) Prec@1 93.000 (91.000) Prec@5 99.000 (99.333) +2022-11-14 13:57:29,814 Epoch: [123][30/500] Time 0.036 (0.033) Data 0.002 (0.009) Loss 0.0555 (0.0556) Prec@1 91.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 13:57:30,225 Epoch: [123][40/500] Time 0.038 (0.034) Data 0.001 (0.007) Loss 0.0441 (0.0533) Prec@1 90.000 (90.800) Prec@5 99.000 (99.400) +2022-11-14 13:57:30,634 Epoch: [123][50/500] Time 0.038 (0.035) Data 0.001 (0.006) Loss 0.0427 (0.0515) Prec@1 92.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 13:57:31,035 Epoch: [123][60/500] Time 0.039 (0.035) Data 0.002 (0.005) Loss 0.0402 (0.0499) Prec@1 93.000 (91.286) Prec@5 100.000 (99.571) +2022-11-14 13:57:31,436 Epoch: [123][70/500] Time 0.038 (0.035) Data 0.001 (0.005) Loss 0.0302 (0.0475) Prec@1 95.000 (91.750) Prec@5 100.000 (99.625) +2022-11-14 13:57:31,828 Epoch: [123][80/500] Time 0.036 (0.035) Data 0.002 (0.004) Loss 0.0631 (0.0492) Prec@1 88.000 (91.333) Prec@5 98.000 (99.444) +2022-11-14 13:57:32,224 Epoch: [123][90/500] Time 0.045 (0.035) Data 0.002 (0.004) Loss 0.0677 (0.0510) Prec@1 90.000 (91.200) Prec@5 99.000 (99.400) +2022-11-14 13:57:32,623 Epoch: [123][100/500] Time 0.038 (0.035) Data 0.002 (0.004) Loss 0.0715 (0.0529) Prec@1 87.000 (90.818) Prec@5 100.000 (99.455) +2022-11-14 13:57:33,029 Epoch: [123][110/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.0597 (0.0535) Prec@1 87.000 (90.500) Prec@5 99.000 (99.417) +2022-11-14 13:57:33,427 Epoch: [123][120/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0533 (0.0535) Prec@1 91.000 (90.538) Prec@5 99.000 (99.385) +2022-11-14 13:57:33,831 Epoch: [123][130/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0388 (0.0524) Prec@1 94.000 (90.786) Prec@5 100.000 (99.429) +2022-11-14 13:57:34,270 Epoch: [123][140/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0736 (0.0538) Prec@1 87.000 (90.533) Prec@5 99.000 (99.400) +2022-11-14 13:57:34,653 Epoch: [123][150/500] Time 0.038 (0.035) Data 0.001 (0.003) Loss 0.0727 (0.0550) Prec@1 88.000 (90.375) Prec@5 99.000 (99.375) +2022-11-14 13:57:35,082 Epoch: [123][160/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0348 (0.0538) Prec@1 95.000 (90.647) Prec@5 100.000 (99.412) +2022-11-14 13:57:35,519 Epoch: [123][170/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0749 (0.0550) Prec@1 87.000 (90.444) Prec@5 99.000 (99.389) +2022-11-14 13:57:35,917 Epoch: [123][180/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0655 (0.0555) Prec@1 89.000 (90.368) Prec@5 99.000 (99.368) +2022-11-14 13:57:36,314 Epoch: [123][190/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0687 (0.0562) Prec@1 88.000 (90.250) Prec@5 99.000 (99.350) +2022-11-14 13:57:36,724 Epoch: [123][200/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0502 (0.0559) Prec@1 92.000 (90.333) Prec@5 100.000 (99.381) +2022-11-14 13:57:37,129 Epoch: [123][210/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0394 (0.0552) Prec@1 94.000 (90.500) Prec@5 99.000 (99.364) +2022-11-14 13:57:37,526 Epoch: [123][220/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0573 (0.0553) Prec@1 90.000 (90.478) Prec@5 100.000 (99.391) +2022-11-14 13:57:37,930 Epoch: [123][230/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0965 (0.0570) Prec@1 84.000 (90.208) Prec@5 100.000 (99.417) +2022-11-14 13:57:38,337 Epoch: [123][240/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0806 (0.0579) Prec@1 88.000 (90.120) Prec@5 98.000 (99.360) +2022-11-14 13:57:38,771 Epoch: [123][250/500] Time 0.061 (0.036) Data 0.002 (0.003) Loss 0.0678 (0.0583) Prec@1 88.000 (90.038) Prec@5 99.000 (99.346) +2022-11-14 13:57:39,167 Epoch: [123][260/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0403 (0.0576) Prec@1 94.000 (90.185) Prec@5 100.000 (99.370) +2022-11-14 13:57:39,567 Epoch: [123][270/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.0452 (0.0572) Prec@1 91.000 (90.214) Prec@5 100.000 (99.393) +2022-11-14 13:57:39,966 Epoch: [123][280/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0732 (0.0577) Prec@1 88.000 (90.138) Prec@5 97.000 (99.310) +2022-11-14 13:57:40,363 Epoch: [123][290/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0664 (0.0580) Prec@1 88.000 (90.067) Prec@5 100.000 (99.333) +2022-11-14 13:57:40,765 Epoch: [123][300/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0755 (0.0586) Prec@1 88.000 (90.000) Prec@5 100.000 (99.355) +2022-11-14 13:57:41,169 Epoch: [123][310/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0491 (0.0583) Prec@1 91.000 (90.031) Prec@5 100.000 (99.375) +2022-11-14 13:57:41,577 Epoch: [123][320/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0383 (0.0577) Prec@1 93.000 (90.121) Prec@5 100.000 (99.394) +2022-11-14 13:57:41,989 Epoch: [123][330/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0432 (0.0573) Prec@1 94.000 (90.235) Prec@5 99.000 (99.382) +2022-11-14 13:57:42,406 Epoch: [123][340/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0621 (0.0574) Prec@1 90.000 (90.229) Prec@5 100.000 (99.400) +2022-11-14 13:57:42,814 Epoch: [123][350/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0766 (0.0579) Prec@1 86.000 (90.111) Prec@5 100.000 (99.417) +2022-11-14 13:57:43,215 Epoch: [123][360/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0909 (0.0588) Prec@1 86.000 (90.000) Prec@5 98.000 (99.378) +2022-11-14 13:57:43,621 Epoch: [123][370/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0582 (0.0588) Prec@1 92.000 (90.053) Prec@5 99.000 (99.368) +2022-11-14 13:57:44,012 Epoch: [123][380/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0791 (0.0593) Prec@1 87.000 (89.974) Prec@5 100.000 (99.385) +2022-11-14 13:57:44,405 Epoch: [123][390/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0422 (0.0589) Prec@1 93.000 (90.050) Prec@5 99.000 (99.375) +2022-11-14 13:57:44,815 Epoch: [123][400/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0525 (0.0588) Prec@1 92.000 (90.098) Prec@5 100.000 (99.390) +2022-11-14 13:57:45,211 Epoch: [123][410/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0514 (0.0586) Prec@1 89.000 (90.071) Prec@5 99.000 (99.381) +2022-11-14 13:57:45,611 Epoch: [123][420/500] Time 0.037 (0.036) Data 0.003 (0.002) Loss 0.0473 (0.0583) Prec@1 91.000 (90.093) Prec@5 100.000 (99.395) +2022-11-14 13:57:46,015 Epoch: [123][430/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0568 (0.0583) Prec@1 91.000 (90.114) Prec@5 100.000 (99.409) +2022-11-14 13:57:46,423 Epoch: [123][440/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0441 (0.0580) Prec@1 91.000 (90.133) Prec@5 100.000 (99.422) +2022-11-14 13:57:46,827 Epoch: [123][450/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0636 (0.0581) Prec@1 90.000 (90.130) Prec@5 100.000 (99.435) +2022-11-14 13:57:47,227 Epoch: [123][460/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0489 (0.0579) Prec@1 92.000 (90.170) Prec@5 100.000 (99.447) +2022-11-14 13:57:47,640 Epoch: [123][470/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0776 (0.0583) Prec@1 87.000 (90.104) Prec@5 99.000 (99.438) +2022-11-14 13:57:48,039 Epoch: [123][480/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0463 (0.0581) Prec@1 93.000 (90.163) Prec@5 98.000 (99.408) +2022-11-14 13:57:48,444 Epoch: [123][490/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0709 (0.0583) Prec@1 88.000 (90.120) Prec@5 99.000 (99.400) +2022-11-14 13:57:48,824 Epoch: [123][499/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0400 (0.0580) Prec@1 96.000 (90.235) Prec@5 100.000 (99.412) +2022-11-14 13:57:49,101 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0645 (0.0645) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:57:49,111 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0683) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:57:49,121 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0744) Prec@1 86.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 13:57:49,132 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0733) Prec@1 89.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 13:57:49,139 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0780) Prec@1 85.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 13:57:49,146 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0773) Prec@1 88.000 (88.000) Prec@5 100.000 (99.833) +2022-11-14 13:57:49,154 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0766) Prec@1 87.000 (87.857) Prec@5 100.000 (99.857) +2022-11-14 13:57:49,164 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0791) Prec@1 84.000 (87.375) Prec@5 99.000 (99.750) +2022-11-14 13:57:49,173 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0813) Prec@1 83.000 (86.889) Prec@5 100.000 (99.778) +2022-11-14 13:57:49,183 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0804) Prec@1 85.000 (86.700) Prec@5 99.000 (99.700) +2022-11-14 13:57:49,192 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0823) Prec@1 82.000 (86.273) Prec@5 100.000 (99.727) +2022-11-14 13:57:49,201 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0833) Prec@1 87.000 (86.333) Prec@5 100.000 (99.750) +2022-11-14 13:57:49,210 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0829) Prec@1 84.000 (86.154) Prec@5 100.000 (99.769) +2022-11-14 13:57:49,219 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0816) Prec@1 88.000 (86.286) Prec@5 100.000 (99.786) +2022-11-14 13:57:49,228 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0817) Prec@1 85.000 (86.200) Prec@5 100.000 (99.800) +2022-11-14 13:57:49,237 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0830) Prec@1 81.000 (85.875) Prec@5 100.000 (99.812) +2022-11-14 13:57:49,246 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0818) Prec@1 90.000 (86.118) Prec@5 98.000 (99.706) +2022-11-14 13:57:49,255 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0832) Prec@1 84.000 (86.000) Prec@5 100.000 (99.722) +2022-11-14 13:57:49,264 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0828) Prec@1 87.000 (86.053) Prec@5 99.000 (99.684) +2022-11-14 13:57:49,274 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0833) Prec@1 85.000 (86.000) Prec@5 97.000 (99.550) +2022-11-14 13:57:49,283 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0843) Prec@1 83.000 (85.857) Prec@5 99.000 (99.524) +2022-11-14 13:57:49,291 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0846) Prec@1 87.000 (85.909) Prec@5 99.000 (99.500) +2022-11-14 13:57:49,301 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0855) Prec@1 82.000 (85.739) Prec@5 98.000 (99.435) +2022-11-14 13:57:49,312 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0856) Prec@1 84.000 (85.667) Prec@5 99.000 (99.417) +2022-11-14 13:57:49,322 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0856) Prec@1 87.000 (85.720) Prec@5 100.000 (99.440) +2022-11-14 13:57:49,331 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0862) Prec@1 83.000 (85.615) Prec@5 97.000 (99.346) +2022-11-14 13:57:49,339 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0858) Prec@1 85.000 (85.593) Prec@5 100.000 (99.370) +2022-11-14 13:57:49,349 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0848) Prec@1 92.000 (85.821) Prec@5 99.000 (99.357) +2022-11-14 13:57:49,359 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0852) Prec@1 85.000 (85.793) Prec@5 98.000 (99.310) +2022-11-14 13:57:49,369 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0853) Prec@1 87.000 (85.833) Prec@5 98.000 (99.267) +2022-11-14 13:57:49,379 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0853) Prec@1 83.000 (85.742) Prec@5 98.000 (99.226) +2022-11-14 13:57:49,387 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0851) Prec@1 89.000 (85.844) Prec@5 99.000 (99.219) +2022-11-14 13:57:49,397 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0850) Prec@1 88.000 (85.909) Prec@5 100.000 (99.242) +2022-11-14 13:57:49,407 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0859) Prec@1 79.000 (85.706) Prec@5 100.000 (99.265) +2022-11-14 13:57:49,415 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0852) Prec@1 90.000 (85.829) Prec@5 100.000 (99.286) +2022-11-14 13:57:49,424 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0848) Prec@1 89.000 (85.917) Prec@5 99.000 (99.278) +2022-11-14 13:57:49,434 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0848) Prec@1 84.000 (85.865) Prec@5 98.000 (99.243) +2022-11-14 13:57:49,442 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0856) Prec@1 80.000 (85.711) Prec@5 99.000 (99.237) +2022-11-14 13:57:49,452 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0852) Prec@1 89.000 (85.795) Prec@5 99.000 (99.231) +2022-11-14 13:57:49,461 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0847) Prec@1 89.000 (85.875) Prec@5 98.000 (99.200) +2022-11-14 13:57:49,471 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0850) Prec@1 84.000 (85.829) Prec@5 97.000 (99.146) +2022-11-14 13:57:49,479 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0849) Prec@1 85.000 (85.810) Prec@5 99.000 (99.143) +2022-11-14 13:57:49,487 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0840) Prec@1 91.000 (85.930) Prec@5 100.000 (99.163) +2022-11-14 13:57:49,496 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0835) Prec@1 90.000 (86.023) Prec@5 99.000 (99.159) +2022-11-14 13:57:49,505 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0835) Prec@1 85.000 (86.000) Prec@5 100.000 (99.178) +2022-11-14 13:57:49,514 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0838) Prec@1 83.000 (85.935) Prec@5 100.000 (99.196) +2022-11-14 13:57:49,524 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0840) Prec@1 81.000 (85.830) Prec@5 100.000 (99.213) +2022-11-14 13:57:49,535 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0845) Prec@1 82.000 (85.750) Prec@5 100.000 (99.229) +2022-11-14 13:57:49,544 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0843) Prec@1 89.000 (85.816) Prec@5 100.000 (99.245) +2022-11-14 13:57:49,554 Test: 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0.0924 (0.0844) Prec@1 85.000 (85.714) Prec@5 97.000 (99.161) +2022-11-14 13:57:49,620 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0846) Prec@1 84.000 (85.684) Prec@5 100.000 (99.175) +2022-11-14 13:57:49,630 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0843) Prec@1 89.000 (85.741) Prec@5 99.000 (99.172) +2022-11-14 13:57:49,639 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.0847) Prec@1 82.000 (85.678) Prec@5 99.000 (99.169) +2022-11-14 13:57:49,649 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0849) Prec@1 87.000 (85.700) Prec@5 99.000 (99.167) +2022-11-14 13:57:49,657 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0848) Prec@1 87.000 (85.721) Prec@5 100.000 (99.180) +2022-11-14 13:57:49,666 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0846) Prec@1 88.000 (85.758) Prec@5 97.000 (99.145) +2022-11-14 13:57:49,676 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0845) Prec@1 88.000 (85.794) Prec@5 100.000 (99.159) +2022-11-14 13:57:49,685 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0841) Prec@1 88.000 (85.828) Prec@5 100.000 (99.172) +2022-11-14 13:57:49,694 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0842) Prec@1 85.000 (85.815) Prec@5 100.000 (99.185) +2022-11-14 13:57:49,703 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0844) Prec@1 84.000 (85.788) Prec@5 97.000 (99.152) +2022-11-14 13:57:49,712 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0837) Prec@1 94.000 (85.910) Prec@5 100.000 (99.164) +2022-11-14 13:57:49,721 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.0841) Prec@1 82.000 (85.853) Prec@5 98.000 (99.147) +2022-11-14 13:57:49,729 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0841) Prec@1 86.000 (85.855) Prec@5 99.000 (99.145) +2022-11-14 13:57:49,737 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0842) Prec@1 88.000 (85.886) Prec@5 98.000 (99.129) +2022-11-14 13:57:49,748 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0843) Prec@1 87.000 (85.901) Prec@5 99.000 (99.127) +2022-11-14 13:57:49,758 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0843) Prec@1 86.000 (85.903) Prec@5 99.000 (99.125) +2022-11-14 13:57:49,767 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0841) Prec@1 88.000 (85.932) Prec@5 100.000 (99.137) +2022-11-14 13:57:49,777 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0837) Prec@1 91.000 (86.000) Prec@5 99.000 (99.135) +2022-11-14 13:57:49,786 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1250 (0.0843) Prec@1 79.000 (85.907) Prec@5 100.000 (99.147) +2022-11-14 13:57:49,796 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0841) Prec@1 87.000 (85.921) Prec@5 99.000 (99.145) +2022-11-14 13:57:49,805 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0842) Prec@1 85.000 (85.909) Prec@5 99.000 (99.143) +2022-11-14 13:57:49,815 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0844) Prec@1 86.000 (85.910) Prec@5 97.000 (99.115) +2022-11-14 13:57:49,824 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0846) Prec@1 83.000 (85.873) Prec@5 100.000 (99.127) +2022-11-14 13:57:49,834 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0847) Prec@1 85.000 (85.862) Prec@5 100.000 (99.138) +2022-11-14 13:57:49,844 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0848) Prec@1 86.000 (85.864) Prec@5 100.000 (99.148) +2022-11-14 13:57:49,854 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0848) Prec@1 85.000 (85.854) Prec@5 100.000 (99.159) +2022-11-14 13:57:49,864 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0847) Prec@1 88.000 (85.880) Prec@5 100.000 (99.169) +2022-11-14 13:57:49,873 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0848) Prec@1 86.000 (85.881) Prec@5 100.000 (99.179) +2022-11-14 13:57:49,884 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0847) Prec@1 86.000 (85.882) Prec@5 99.000 (99.176) +2022-11-14 13:57:49,894 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.0850) Prec@1 84.000 (85.860) Prec@5 99.000 (99.174) +2022-11-14 13:57:49,903 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0850) Prec@1 88.000 (85.885) Prec@5 99.000 (99.172) +2022-11-14 13:57:49,913 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0851) Prec@1 86.000 (85.886) Prec@5 99.000 (99.170) +2022-11-14 13:57:49,921 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0849) Prec@1 86.000 (85.888) Prec@5 100.000 (99.180) +2022-11-14 13:57:49,930 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0850) Prec@1 84.000 (85.867) Prec@5 97.000 (99.156) +2022-11-14 13:57:49,940 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0849) Prec@1 87.000 (85.879) Prec@5 100.000 (99.165) +2022-11-14 13:57:49,948 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0847) Prec@1 88.000 (85.902) Prec@5 99.000 (99.163) +2022-11-14 13:57:49,957 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0846) Prec@1 86.000 (85.903) Prec@5 100.000 (99.172) +2022-11-14 13:57:49,968 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0845) Prec@1 87.000 (85.915) Prec@5 99.000 (99.170) +2022-11-14 13:57:49,978 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0845) Prec@1 85.000 (85.905) Prec@5 100.000 (99.179) +2022-11-14 13:57:49,988 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0844) Prec@1 86.000 (85.906) Prec@5 98.000 (99.167) +2022-11-14 13:57:49,998 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0841) Prec@1 89.000 (85.938) Prec@5 99.000 (99.165) +2022-11-14 13:57:50,007 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1152 (0.0845) Prec@1 81.000 (85.888) Prec@5 98.000 (99.153) +2022-11-14 13:57:50,016 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0843) Prec@1 89.000 (85.919) Prec@5 99.000 (99.152) +2022-11-14 13:57:50,026 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0843) Prec@1 83.000 (85.890) Prec@5 100.000 (99.160) +2022-11-14 13:57:50,082 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:57:50,402 Epoch: [124][0/500] Time 0.025 (0.025) Data 0.236 (0.236) Loss 0.0704 (0.0704) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 13:57:50,721 Epoch: [124][10/500] Time 0.032 (0.027) Data 0.002 (0.023) Loss 0.0587 (0.0645) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 13:57:51,094 Epoch: [124][20/500] Time 0.032 (0.030) Data 0.002 (0.013) Loss 0.0337 (0.0542) Prec@1 96.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 13:57:51,457 Epoch: [124][30/500] Time 0.034 (0.031) Data 0.002 (0.009) Loss 0.0517 (0.0536) Prec@1 91.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 13:57:51,822 Epoch: [124][40/500] Time 0.032 (0.031) Data 0.002 (0.008) Loss 0.0805 (0.0590) Prec@1 83.000 (89.400) Prec@5 98.000 (99.200) +2022-11-14 13:57:52,191 Epoch: [124][50/500] Time 0.033 (0.031) Data 0.002 (0.007) Loss 0.0392 (0.0557) Prec@1 95.000 (90.333) Prec@5 100.000 (99.333) +2022-11-14 13:57:52,567 Epoch: [124][60/500] Time 0.031 (0.032) Data 0.002 (0.006) Loss 0.0415 (0.0537) Prec@1 93.000 (90.714) Prec@5 100.000 (99.429) +2022-11-14 13:57:52,940 Epoch: [124][70/500] Time 0.036 (0.032) Data 0.003 (0.005) Loss 0.0807 (0.0570) Prec@1 88.000 (90.375) Prec@5 99.000 (99.375) +2022-11-14 13:57:53,303 Epoch: [124][80/500] Time 0.029 (0.032) Data 0.003 (0.005) Loss 0.0470 (0.0559) Prec@1 94.000 (90.778) Prec@5 100.000 (99.444) +2022-11-14 13:57:53,685 Epoch: [124][90/500] Time 0.032 (0.032) Data 0.002 (0.005) Loss 0.0713 (0.0575) Prec@1 86.000 (90.300) Prec@5 99.000 (99.400) +2022-11-14 13:57:54,066 Epoch: [124][100/500] Time 0.035 (0.032) Data 0.002 (0.004) Loss 0.0565 (0.0574) Prec@1 89.000 (90.182) Prec@5 97.000 (99.182) +2022-11-14 13:57:54,436 Epoch: [124][110/500] Time 0.036 (0.032) Data 0.001 (0.004) Loss 0.0533 (0.0570) Prec@1 90.000 (90.167) Prec@5 100.000 (99.250) +2022-11-14 13:57:54,812 Epoch: [124][120/500] Time 0.035 (0.032) Data 0.002 (0.004) Loss 0.0526 (0.0567) Prec@1 90.000 (90.154) Prec@5 99.000 (99.231) +2022-11-14 13:57:55,185 Epoch: [124][130/500] Time 0.039 (0.032) Data 0.002 (0.004) Loss 0.0537 (0.0565) Prec@1 88.000 (90.000) Prec@5 100.000 (99.286) +2022-11-14 13:57:55,558 Epoch: [124][140/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0504 (0.0561) Prec@1 91.000 (90.067) Prec@5 100.000 (99.333) +2022-11-14 13:57:55,929 Epoch: [124][150/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0493 (0.0557) Prec@1 90.000 (90.062) Prec@5 100.000 (99.375) +2022-11-14 13:57:56,302 Epoch: [124][160/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0504 (0.0553) Prec@1 94.000 (90.294) Prec@5 99.000 (99.353) +2022-11-14 13:57:56,675 Epoch: [124][170/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0607 (0.0556) Prec@1 90.000 (90.278) Prec@5 100.000 (99.389) +2022-11-14 13:57:57,048 Epoch: [124][180/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0462 (0.0551) Prec@1 92.000 (90.368) Prec@5 100.000 (99.421) +2022-11-14 13:57:57,419 Epoch: [124][190/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0595 (0.0554) Prec@1 91.000 (90.400) Prec@5 100.000 (99.450) +2022-11-14 13:57:57,795 Epoch: [124][200/500] Time 0.037 (0.033) Data 0.001 (0.003) Loss 0.0450 (0.0549) Prec@1 93.000 (90.524) Prec@5 100.000 (99.476) +2022-11-14 13:57:58,176 Epoch: [124][210/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.1148 (0.0576) Prec@1 82.000 (90.136) Prec@5 99.000 (99.455) +2022-11-14 13:57:58,559 Epoch: [124][220/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0582 (0.0576) Prec@1 90.000 (90.130) Prec@5 100.000 (99.478) +2022-11-14 13:57:58,935 Epoch: [124][230/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0550 (0.0575) Prec@1 89.000 (90.083) Prec@5 100.000 (99.500) +2022-11-14 13:57:59,311 Epoch: [124][240/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0674 (0.0579) Prec@1 88.000 (90.000) Prec@5 100.000 (99.520) +2022-11-14 13:57:59,685 Epoch: [124][250/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0647 (0.0582) Prec@1 87.000 (89.885) Prec@5 100.000 (99.538) +2022-11-14 13:58:00,073 Epoch: [124][260/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0506 (0.0579) Prec@1 92.000 (89.963) Prec@5 99.000 (99.519) +2022-11-14 13:58:00,443 Epoch: [124][270/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0579 (0.0579) Prec@1 92.000 (90.036) Prec@5 99.000 (99.500) +2022-11-14 13:58:00,820 Epoch: [124][280/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0749 (0.0585) Prec@1 89.000 (90.000) Prec@5 99.000 (99.483) +2022-11-14 13:58:01,197 Epoch: [124][290/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0625 (0.0586) Prec@1 90.000 (90.000) Prec@5 99.000 (99.467) +2022-11-14 13:58:01,570 Epoch: [124][300/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0327 (0.0578) Prec@1 96.000 (90.194) Prec@5 100.000 (99.484) +2022-11-14 13:58:01,950 Epoch: [124][310/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0444 (0.0574) Prec@1 92.000 (90.250) Prec@5 100.000 (99.500) +2022-11-14 13:58:02,322 Epoch: [124][320/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0481 (0.0571) Prec@1 93.000 (90.333) Prec@5 100.000 (99.515) +2022-11-14 13:58:02,699 Epoch: [124][330/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0688 (0.0574) Prec@1 87.000 (90.235) Prec@5 100.000 (99.529) +2022-11-14 13:58:03,066 Epoch: [124][340/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0753 (0.0579) Prec@1 87.000 (90.143) Prec@5 100.000 (99.543) +2022-11-14 13:58:03,444 Epoch: [124][350/500] Time 0.036 (0.033) Data 0.001 (0.003) Loss 0.0823 (0.0586) Prec@1 86.000 (90.028) Prec@5 98.000 (99.500) +2022-11-14 13:58:03,822 Epoch: [124][360/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0577 (0.0586) Prec@1 89.000 (90.000) Prec@5 100.000 (99.514) +2022-11-14 13:58:04,200 Epoch: [124][370/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0298 (0.0578) Prec@1 95.000 (90.132) Prec@5 100.000 (99.526) +2022-11-14 13:58:04,580 Epoch: [124][380/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0760 (0.0583) Prec@1 89.000 (90.103) Prec@5 97.000 (99.462) +2022-11-14 13:58:04,962 Epoch: [124][390/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0698 (0.0586) Prec@1 86.000 (90.000) Prec@5 99.000 (99.450) +2022-11-14 13:58:05,337 Epoch: [124][400/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0496 (0.0584) Prec@1 91.000 (90.024) Prec@5 100.000 (99.463) +2022-11-14 13:58:05,709 Epoch: [124][410/500] Time 0.035 (0.033) Data 0.001 (0.002) Loss 0.0701 (0.0586) Prec@1 88.000 (89.976) Prec@5 98.000 (99.429) +2022-11-14 13:58:06,089 Epoch: [124][420/500] Time 0.035 (0.033) Data 0.001 (0.002) Loss 0.0376 (0.0581) Prec@1 94.000 (90.070) Prec@5 100.000 (99.442) +2022-11-14 13:58:06,491 Epoch: [124][430/500] Time 0.029 (0.033) Data 0.002 (0.002) Loss 0.0372 (0.0577) Prec@1 96.000 (90.205) Prec@5 100.000 (99.455) +2022-11-14 13:58:06,866 Epoch: [124][440/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0881 (0.0584) Prec@1 85.000 (90.089) Prec@5 100.000 (99.467) +2022-11-14 13:58:07,239 Epoch: [124][450/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0437 (0.0580) Prec@1 92.000 (90.130) Prec@5 100.000 (99.478) +2022-11-14 13:58:07,616 Epoch: [124][460/500] Time 0.032 (0.033) Data 0.002 (0.002) Loss 0.0576 (0.0580) Prec@1 92.000 (90.170) Prec@5 100.000 (99.489) +2022-11-14 13:58:07,994 Epoch: [124][470/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0494 (0.0578) Prec@1 93.000 (90.229) Prec@5 98.000 (99.458) +2022-11-14 13:58:08,369 Epoch: [124][480/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0720 (0.0581) Prec@1 88.000 (90.184) Prec@5 99.000 (99.449) +2022-11-14 13:58:08,745 Epoch: [124][490/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0437 (0.0578) Prec@1 92.000 (90.220) Prec@5 100.000 (99.460) +2022-11-14 13:58:09,082 Epoch: [124][499/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0640 (0.0580) Prec@1 89.000 (90.196) Prec@5 98.000 (99.431) +2022-11-14 13:58:09,362 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0597 (0.0597) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:58:09,373 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0703) Prec@1 87.000 (89.000) Prec@5 98.000 (98.500) +2022-11-14 13:58:09,382 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0996 (0.0801) Prec@1 83.000 (87.000) Prec@5 100.000 (99.000) +2022-11-14 13:58:09,395 Test: [3/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0804) Prec@1 89.000 (87.500) Prec@5 99.000 (99.000) +2022-11-14 13:58:09,404 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0788) Prec@1 87.000 (87.400) Prec@5 100.000 (99.200) +2022-11-14 13:58:09,414 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0764) Prec@1 90.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 13:58:09,424 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0737) Prec@1 92.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 13:58:09,437 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0748) Prec@1 87.000 (88.250) Prec@5 99.000 (99.375) +2022-11-14 13:58:09,447 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0759) Prec@1 88.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 13:58:09,458 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0748) Prec@1 88.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 13:58:09,470 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0746) Prec@1 86.000 (88.000) Prec@5 100.000 (99.455) +2022-11-14 13:58:09,483 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0750) Prec@1 88.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 13:58:09,494 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0733) Prec@1 89.000 (88.077) Prec@5 100.000 (99.538) +2022-11-14 13:58:09,505 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0739) Prec@1 87.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 13:58:09,516 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0744) Prec@1 85.000 (87.800) Prec@5 100.000 (99.533) +2022-11-14 13:58:09,528 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0762) Prec@1 82.000 (87.438) Prec@5 99.000 (99.500) +2022-11-14 13:58:09,542 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0753) Prec@1 91.000 (87.647) Prec@5 99.000 (99.471) +2022-11-14 13:58:09,555 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0768) Prec@1 84.000 (87.444) Prec@5 100.000 (99.500) +2022-11-14 13:58:09,567 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0777) Prec@1 83.000 (87.211) Prec@5 97.000 (99.368) +2022-11-14 13:58:09,580 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0784) Prec@1 85.000 (87.100) Prec@5 97.000 (99.250) +2022-11-14 13:58:09,593 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0787) Prec@1 84.000 (86.952) Prec@5 100.000 (99.286) +2022-11-14 13:58:09,604 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0794) Prec@1 85.000 (86.864) Prec@5 98.000 (99.227) +2022-11-14 13:58:09,618 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0804) Prec@1 84.000 (86.739) Prec@5 97.000 (99.130) +2022-11-14 13:58:09,633 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0802) Prec@1 83.000 (86.583) Prec@5 100.000 (99.167) +2022-11-14 13:58:09,646 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0812) Prec@1 85.000 (86.520) Prec@5 100.000 (99.200) +2022-11-14 13:58:09,660 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0821) Prec@1 83.000 (86.385) Prec@5 99.000 (99.192) +2022-11-14 13:58:09,674 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0814) Prec@1 89.000 (86.481) Prec@5 100.000 (99.222) +2022-11-14 13:58:09,688 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0820) Prec@1 82.000 (86.321) Prec@5 100.000 (99.250) +2022-11-14 13:58:09,702 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0813) Prec@1 90.000 (86.448) Prec@5 99.000 (99.241) +2022-11-14 13:58:09,716 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0819) Prec@1 82.000 (86.300) Prec@5 99.000 (99.233) +2022-11-14 13:58:09,729 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0824) Prec@1 82.000 (86.161) Prec@5 99.000 (99.226) +2022-11-14 13:58:09,745 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0822) Prec@1 88.000 (86.219) Prec@5 99.000 (99.219) +2022-11-14 13:58:09,760 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0829) Prec@1 83.000 (86.121) Prec@5 99.000 (99.212) +2022-11-14 13:58:09,771 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1195 (0.0840) Prec@1 79.000 (85.912) Prec@5 99.000 (99.206) +2022-11-14 13:58:09,784 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0841) Prec@1 86.000 (85.914) Prec@5 99.000 (99.200) +2022-11-14 13:58:09,798 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0837) Prec@1 90.000 (86.028) Prec@5 99.000 (99.194) +2022-11-14 13:58:09,812 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0838) Prec@1 84.000 (85.973) Prec@5 98.000 (99.162) +2022-11-14 13:58:09,825 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0845) Prec@1 82.000 (85.868) Prec@5 99.000 (99.158) +2022-11-14 13:58:09,838 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0839) Prec@1 90.000 (85.974) Prec@5 99.000 (99.154) +2022-11-14 13:58:09,850 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0834) Prec@1 92.000 (86.125) Prec@5 99.000 (99.150) +2022-11-14 13:58:09,863 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0838) Prec@1 84.000 (86.073) Prec@5 99.000 (99.146) +2022-11-14 13:58:09,876 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0839) Prec@1 85.000 (86.048) Prec@5 99.000 (99.143) +2022-11-14 13:58:09,889 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0833) Prec@1 91.000 (86.163) Prec@5 100.000 (99.163) +2022-11-14 13:58:09,903 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0831) Prec@1 88.000 (86.205) Prec@5 97.000 (99.114) +2022-11-14 13:58:09,914 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0829) Prec@1 89.000 (86.267) Prec@5 100.000 (99.133) +2022-11-14 13:58:09,926 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0833) Prec@1 81.000 (86.152) Prec@5 100.000 (99.152) +2022-11-14 13:58:09,940 Test: [46/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0828) Prec@1 91.000 (86.255) Prec@5 99.000 (99.149) +2022-11-14 13:58:09,953 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0835) Prec@1 81.000 (86.146) Prec@5 99.000 (99.146) +2022-11-14 13:58:09,965 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0828) Prec@1 89.000 (86.204) Prec@5 100.000 (99.163) +2022-11-14 13:58:09,979 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0831) Prec@1 84.000 (86.160) Prec@5 100.000 (99.180) +2022-11-14 13:58:09,994 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0826) Prec@1 89.000 (86.216) Prec@5 100.000 (99.196) +2022-11-14 13:58:10,008 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0828) Prec@1 84.000 (86.173) Prec@5 99.000 (99.192) +2022-11-14 13:58:10,021 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0825) Prec@1 90.000 (86.245) Prec@5 100.000 (99.208) +2022-11-14 13:58:10,034 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0824) Prec@1 89.000 (86.296) Prec@5 99.000 (99.204) +2022-11-14 13:58:10,047 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0827) Prec@1 83.000 (86.236) Prec@5 100.000 (99.218) +2022-11-14 13:58:10,061 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0825) Prec@1 88.000 (86.268) Prec@5 99.000 (99.214) +2022-11-14 13:58:10,074 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0824) Prec@1 88.000 (86.298) Prec@5 100.000 (99.228) +2022-11-14 13:58:10,087 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0822) Prec@1 89.000 (86.345) Prec@5 99.000 (99.224) +2022-11-14 13:58:10,101 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.0828) Prec@1 80.000 (86.237) Prec@5 100.000 (99.237) +2022-11-14 13:58:10,113 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0827) Prec@1 87.000 (86.250) Prec@5 99.000 (99.233) +2022-11-14 13:58:10,125 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0827) Prec@1 86.000 (86.246) Prec@5 99.000 (99.230) +2022-11-14 13:58:10,139 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0825) Prec@1 89.000 (86.290) Prec@5 98.000 (99.210) +2022-11-14 13:58:10,153 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0822) Prec@1 88.000 (86.317) Prec@5 100.000 (99.222) +2022-11-14 13:58:10,166 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0818) Prec@1 90.000 (86.375) Prec@5 100.000 (99.234) +2022-11-14 13:58:10,180 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0821) Prec@1 83.000 (86.323) Prec@5 100.000 (99.246) +2022-11-14 13:58:10,194 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0823) Prec@1 83.000 (86.273) Prec@5 97.000 (99.212) +2022-11-14 13:58:10,208 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0818) Prec@1 95.000 (86.403) Prec@5 99.000 (99.209) +2022-11-14 13:58:10,221 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0817) Prec@1 85.000 (86.382) Prec@5 99.000 (99.206) +2022-11-14 13:58:10,235 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0814) Prec@1 91.000 (86.449) Prec@5 99.000 (99.203) +2022-11-14 13:58:10,248 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0818) Prec@1 81.000 (86.371) Prec@5 97.000 (99.171) +2022-11-14 13:58:10,261 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0821) Prec@1 84.000 (86.338) Prec@5 100.000 (99.183) +2022-11-14 13:58:10,274 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0817) Prec@1 91.000 (86.403) Prec@5 99.000 (99.181) +2022-11-14 13:58:10,286 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0812) Prec@1 94.000 (86.507) Prec@5 100.000 (99.192) +2022-11-14 13:58:10,299 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0807) Prec@1 93.000 (86.595) Prec@5 100.000 (99.203) +2022-11-14 13:58:10,314 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0810) Prec@1 85.000 (86.573) Prec@5 100.000 (99.213) +2022-11-14 13:58:10,325 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0808) Prec@1 91.000 (86.632) Prec@5 98.000 (99.197) +2022-11-14 13:58:10,340 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0807) Prec@1 85.000 (86.610) Prec@5 99.000 (99.195) +2022-11-14 13:58:10,357 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0808) Prec@1 87.000 (86.615) Prec@5 99.000 (99.192) +2022-11-14 13:58:10,370 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0809) Prec@1 83.000 (86.570) Prec@5 99.000 (99.190) +2022-11-14 13:58:10,384 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0808) Prec@1 86.000 (86.562) Prec@5 99.000 (99.188) +2022-11-14 13:58:10,396 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0810) Prec@1 86.000 (86.556) Prec@5 97.000 (99.160) +2022-11-14 13:58:10,411 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0813) Prec@1 81.000 (86.488) Prec@5 99.000 (99.159) +2022-11-14 13:58:10,424 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0813) Prec@1 88.000 (86.506) Prec@5 100.000 (99.169) +2022-11-14 13:58:10,438 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0811) Prec@1 88.000 (86.524) Prec@5 99.000 (99.167) +2022-11-14 13:58:10,452 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0814) Prec@1 80.000 (86.447) Prec@5 99.000 (99.165) +2022-11-14 13:58:10,466 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0818) Prec@1 83.000 (86.407) Prec@5 99.000 (99.163) +2022-11-14 13:58:10,480 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0817) Prec@1 86.000 (86.402) Prec@5 99.000 (99.161) +2022-11-14 13:58:10,494 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0820) Prec@1 81.000 (86.341) Prec@5 99.000 (99.159) +2022-11-14 13:58:10,507 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0821) Prec@1 82.000 (86.292) Prec@5 99.000 (99.157) +2022-11-14 13:58:10,521 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0822) Prec@1 85.000 (86.278) Prec@5 99.000 (99.156) +2022-11-14 13:58:10,535 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0822) Prec@1 87.000 (86.286) Prec@5 100.000 (99.165) +2022-11-14 13:58:10,549 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0383 (0.0817) Prec@1 94.000 (86.370) Prec@5 100.000 (99.174) +2022-11-14 13:58:10,563 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0820) Prec@1 82.000 (86.323) Prec@5 99.000 (99.172) +2022-11-14 13:58:10,576 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0820) Prec@1 84.000 (86.298) Prec@5 99.000 (99.170) +2022-11-14 13:58:10,590 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0819) Prec@1 88.000 (86.316) Prec@5 99.000 (99.168) +2022-11-14 13:58:10,603 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0818) Prec@1 87.000 (86.323) Prec@5 99.000 (99.167) +2022-11-14 13:58:10,617 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0817) Prec@1 86.000 (86.320) Prec@5 98.000 (99.155) +2022-11-14 13:58:10,630 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0818) Prec@1 85.000 (86.306) Prec@5 98.000 (99.143) +2022-11-14 13:58:10,644 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0819) Prec@1 86.000 (86.303) Prec@5 99.000 (99.141) +2022-11-14 13:58:10,660 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0818) Prec@1 90.000 (86.340) Prec@5 98.000 (99.130) +2022-11-14 13:58:10,717 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:58:11,036 Epoch: [125][0/500] Time 0.028 (0.028) Data 0.230 (0.230) Loss 0.0503 (0.0503) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 13:58:11,258 Epoch: [125][10/500] Time 0.023 (0.020) Data 0.001 (0.022) Loss 0.0384 (0.0443) Prec@1 94.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:58:11,592 Epoch: [125][20/500] Time 0.037 (0.024) Data 0.002 (0.013) Loss 0.0857 (0.0581) Prec@1 87.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:58:11,992 Epoch: [125][30/500] Time 0.038 (0.028) Data 0.002 (0.009) Loss 0.0391 (0.0534) Prec@1 93.000 (91.500) Prec@5 100.000 (99.250) +2022-11-14 13:58:12,383 Epoch: [125][40/500] Time 0.037 (0.030) Data 0.002 (0.007) Loss 0.0437 (0.0515) Prec@1 93.000 (91.800) Prec@5 100.000 (99.400) +2022-11-14 13:58:12,792 Epoch: [125][50/500] Time 0.042 (0.031) Data 0.002 (0.006) Loss 0.0771 (0.0557) Prec@1 86.000 (90.833) Prec@5 100.000 (99.500) +2022-11-14 13:58:13,190 Epoch: [125][60/500] Time 0.037 (0.032) Data 0.002 (0.006) Loss 0.0497 (0.0549) Prec@1 91.000 (90.857) Prec@5 100.000 (99.571) +2022-11-14 13:58:13,584 Epoch: [125][70/500] Time 0.038 (0.032) Data 0.002 (0.005) Loss 0.0443 (0.0535) Prec@1 93.000 (91.125) Prec@5 99.000 (99.500) +2022-11-14 13:58:13,987 Epoch: [125][80/500] Time 0.042 (0.032) Data 0.002 (0.005) Loss 0.0500 (0.0532) Prec@1 91.000 (91.111) Prec@5 98.000 (99.333) +2022-11-14 13:58:14,381 Epoch: [125][90/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0564 (0.0535) Prec@1 90.000 (91.000) Prec@5 100.000 (99.400) +2022-11-14 13:58:14,778 Epoch: [125][100/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0610 (0.0542) Prec@1 89.000 (90.818) Prec@5 99.000 (99.364) +2022-11-14 13:58:15,186 Epoch: [125][110/500] Time 0.041 (0.033) Data 0.002 (0.004) Loss 0.0611 (0.0547) Prec@1 88.000 (90.583) Prec@5 100.000 (99.417) +2022-11-14 13:58:15,577 Epoch: [125][120/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0592 (0.0551) Prec@1 91.000 (90.615) Prec@5 99.000 (99.385) +2022-11-14 13:58:15,977 Epoch: [125][130/500] Time 0.038 (0.034) Data 0.002 (0.004) Loss 0.0505 (0.0548) Prec@1 92.000 (90.714) Prec@5 98.000 (99.286) +2022-11-14 13:58:16,384 Epoch: [125][140/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0635 (0.0553) Prec@1 91.000 (90.733) Prec@5 99.000 (99.267) +2022-11-14 13:58:16,780 Epoch: [125][150/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0630 (0.0558) Prec@1 87.000 (90.500) Prec@5 99.000 (99.250) +2022-11-14 13:58:17,188 Epoch: [125][160/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0391 (0.0548) Prec@1 94.000 (90.706) Prec@5 100.000 (99.294) +2022-11-14 13:58:17,587 Epoch: [125][170/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0361 (0.0538) Prec@1 95.000 (90.944) Prec@5 99.000 (99.278) +2022-11-14 13:58:17,979 Epoch: [125][180/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0685 (0.0546) Prec@1 87.000 (90.737) Prec@5 98.000 (99.211) +2022-11-14 13:58:18,389 Epoch: [125][190/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0560 (0.0546) Prec@1 91.000 (90.750) Prec@5 100.000 (99.250) +2022-11-14 13:58:18,795 Epoch: [125][200/500] Time 0.049 (0.034) Data 0.001 (0.003) Loss 0.0506 (0.0544) Prec@1 90.000 (90.714) Prec@5 100.000 (99.286) +2022-11-14 13:58:19,188 Epoch: [125][210/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0487 (0.0542) Prec@1 93.000 (90.818) Prec@5 100.000 (99.318) +2022-11-14 13:58:19,603 Epoch: [125][220/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0896 (0.0557) Prec@1 85.000 (90.565) Prec@5 99.000 (99.304) +2022-11-14 13:58:20,017 Epoch: [125][230/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0371 (0.0550) Prec@1 96.000 (90.792) Prec@5 99.000 (99.292) +2022-11-14 13:58:20,409 Epoch: [125][240/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0468 (0.0546) Prec@1 91.000 (90.800) Prec@5 100.000 (99.320) +2022-11-14 13:58:20,809 Epoch: [125][250/500] Time 0.038 (0.035) Data 0.001 (0.003) Loss 0.0392 (0.0540) Prec@1 95.000 (90.962) Prec@5 100.000 (99.346) +2022-11-14 13:58:21,212 Epoch: [125][260/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0559 (0.0541) Prec@1 89.000 (90.889) Prec@5 99.000 (99.333) +2022-11-14 13:58:21,615 Epoch: [125][270/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0567 (0.0542) Prec@1 88.000 (90.786) Prec@5 100.000 (99.357) +2022-11-14 13:58:22,015 Epoch: [125][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0612 (0.0544) Prec@1 90.000 (90.759) Prec@5 100.000 (99.379) +2022-11-14 13:58:22,422 Epoch: [125][290/500] Time 0.036 (0.035) Data 0.001 (0.003) Loss 0.0430 (0.0541) Prec@1 94.000 (90.867) Prec@5 99.000 (99.367) +2022-11-14 13:58:22,818 Epoch: [125][300/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0471 (0.0538) Prec@1 91.000 (90.871) Prec@5 99.000 (99.355) +2022-11-14 13:58:23,227 Epoch: [125][310/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0258 (0.0529) Prec@1 96.000 (91.031) Prec@5 100.000 (99.375) +2022-11-14 13:58:23,631 Epoch: [125][320/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0627 (0.0532) Prec@1 89.000 (90.970) Prec@5 100.000 (99.394) +2022-11-14 13:58:24,033 Epoch: [125][330/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0403 (0.0529) Prec@1 95.000 (91.088) Prec@5 100.000 (99.412) +2022-11-14 13:58:24,431 Epoch: [125][340/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0415 (0.0525) Prec@1 96.000 (91.229) Prec@5 99.000 (99.400) +2022-11-14 13:58:24,835 Epoch: [125][350/500] Time 0.037 (0.035) Data 0.003 (0.003) Loss 0.0749 (0.0532) Prec@1 86.000 (91.083) Prec@5 100.000 (99.417) +2022-11-14 13:58:25,224 Epoch: [125][360/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0336 (0.0526) Prec@1 95.000 (91.189) Prec@5 99.000 (99.405) +2022-11-14 13:58:25,626 Epoch: [125][370/500] Time 0.038 (0.035) Data 0.001 (0.002) Loss 0.0638 (0.0529) Prec@1 89.000 (91.132) Prec@5 99.000 (99.395) +2022-11-14 13:58:26,030 Epoch: [125][380/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0813 (0.0537) Prec@1 83.000 (90.923) Prec@5 99.000 (99.385) +2022-11-14 13:58:26,433 Epoch: [125][390/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0648 (0.0539) Prec@1 88.000 (90.850) Prec@5 98.000 (99.350) +2022-11-14 13:58:26,834 Epoch: [125][400/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0845 (0.0547) Prec@1 83.000 (90.659) Prec@5 99.000 (99.341) +2022-11-14 13:58:27,246 Epoch: [125][410/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0463 (0.0545) Prec@1 91.000 (90.667) Prec@5 100.000 (99.357) +2022-11-14 13:58:27,645 Epoch: [125][420/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0679 (0.0548) Prec@1 88.000 (90.605) Prec@5 100.000 (99.372) +2022-11-14 13:58:28,046 Epoch: [125][430/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0490 (0.0547) Prec@1 91.000 (90.614) Prec@5 100.000 (99.386) +2022-11-14 13:58:28,447 Epoch: [125][440/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0520 (0.0546) Prec@1 90.000 (90.600) Prec@5 100.000 (99.400) +2022-11-14 13:58:28,837 Epoch: [125][450/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0742 (0.0550) Prec@1 87.000 (90.522) Prec@5 99.000 (99.391) +2022-11-14 13:58:29,236 Epoch: [125][460/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0456 (0.0548) Prec@1 94.000 (90.596) Prec@5 100.000 (99.404) +2022-11-14 13:58:29,638 Epoch: [125][470/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0515 (0.0548) Prec@1 91.000 (90.604) Prec@5 100.000 (99.417) +2022-11-14 13:58:30,036 Epoch: [125][480/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0452 (0.0546) Prec@1 91.000 (90.612) Prec@5 99.000 (99.408) +2022-11-14 13:58:30,442 Epoch: [125][490/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0421 (0.0543) Prec@1 93.000 (90.660) Prec@5 100.000 (99.420) +2022-11-14 13:58:30,808 Epoch: [125][499/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0621 (0.0545) Prec@1 88.000 (90.608) Prec@5 99.000 (99.412) +2022-11-14 13:58:31,091 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0618 (0.0618) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:31,099 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0737) Prec@1 83.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:31,110 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0736) Prec@1 89.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 13:58:31,121 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0769) Prec@1 85.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 13:58:31,128 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0802) Prec@1 83.000 (86.200) Prec@5 100.000 (99.800) +2022-11-14 13:58:31,136 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0749) Prec@1 92.000 (87.167) Prec@5 99.000 (99.667) +2022-11-14 13:58:31,144 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0735) Prec@1 89.000 (87.429) Prec@5 100.000 (99.714) +2022-11-14 13:58:31,154 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0771) Prec@1 79.000 (86.375) Prec@5 99.000 (99.625) +2022-11-14 13:58:31,163 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0798) Prec@1 85.000 (86.222) Prec@5 99.000 (99.556) +2022-11-14 13:58:31,172 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0784) Prec@1 89.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 13:58:31,182 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0784) Prec@1 87.000 (86.545) Prec@5 100.000 (99.545) +2022-11-14 13:58:31,191 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0769) Prec@1 92.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 13:58:31,200 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0752) Prec@1 91.000 (87.308) Prec@5 99.000 (99.462) +2022-11-14 13:58:31,210 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0749) Prec@1 90.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 13:58:31,219 Test: [14/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0739) Prec@1 92.000 (87.800) Prec@5 99.000 (99.467) +2022-11-14 13:58:31,228 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0740) Prec@1 89.000 (87.875) Prec@5 98.000 (99.375) +2022-11-14 13:58:31,237 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0733) Prec@1 89.000 (87.941) Prec@5 98.000 (99.294) +2022-11-14 13:58:31,246 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1238 (0.0761) Prec@1 79.000 (87.444) Prec@5 99.000 (99.278) +2022-11-14 13:58:31,255 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0772) Prec@1 80.000 (87.053) Prec@5 100.000 (99.316) +2022-11-14 13:58:31,265 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0784) Prec@1 86.000 (87.000) Prec@5 98.000 (99.250) +2022-11-14 13:58:31,274 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0779) Prec@1 88.000 (87.048) Prec@5 100.000 (99.286) +2022-11-14 13:58:31,283 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0771) Prec@1 91.000 (87.227) Prec@5 100.000 (99.318) +2022-11-14 13:58:31,291 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0786) Prec@1 82.000 (87.000) Prec@5 96.000 (99.174) +2022-11-14 13:58:31,300 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0785) Prec@1 87.000 (87.000) Prec@5 99.000 (99.167) +2022-11-14 13:58:31,309 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0790) Prec@1 85.000 (86.920) Prec@5 99.000 (99.160) +2022-11-14 13:58:31,318 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0802) Prec@1 83.000 (86.769) Prec@5 97.000 (99.077) +2022-11-14 13:58:31,328 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0799) Prec@1 87.000 (86.778) Prec@5 100.000 (99.111) +2022-11-14 13:58:31,337 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0798) Prec@1 87.000 (86.786) Prec@5 100.000 (99.143) +2022-11-14 13:58:31,346 Test: 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0.0837 (0.0806) Prec@1 86.000 (86.514) Prec@5 99.000 (99.086) +2022-11-14 13:58:31,414 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0802) Prec@1 89.000 (86.583) Prec@5 99.000 (99.083) +2022-11-14 13:58:31,423 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0804) Prec@1 84.000 (86.514) Prec@5 99.000 (99.081) +2022-11-14 13:58:31,433 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0811) Prec@1 84.000 (86.447) Prec@5 98.000 (99.053) +2022-11-14 13:58:31,443 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0810) Prec@1 86.000 (86.436) Prec@5 98.000 (99.026) +2022-11-14 13:58:31,454 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0809) Prec@1 87.000 (86.450) Prec@5 99.000 (99.025) +2022-11-14 13:58:31,463 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0812) Prec@1 87.000 (86.463) Prec@5 97.000 (98.976) +2022-11-14 13:58:31,472 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0812) Prec@1 87.000 (86.476) Prec@5 98.000 (98.952) +2022-11-14 13:58:31,481 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0807) Prec@1 89.000 (86.535) Prec@5 99.000 (98.953) +2022-11-14 13:58:31,490 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0810) Prec@1 84.000 (86.477) Prec@5 99.000 (98.955) +2022-11-14 13:58:31,499 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0813) Prec@1 84.000 (86.422) Prec@5 99.000 (98.956) +2022-11-14 13:58:31,509 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1349 (0.0824) Prec@1 76.000 (86.196) Prec@5 98.000 (98.935) +2022-11-14 13:58:31,517 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0820) Prec@1 89.000 (86.255) Prec@5 100.000 (98.957) +2022-11-14 13:58:31,526 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0824) Prec@1 82.000 (86.167) Prec@5 98.000 (98.938) +2022-11-14 13:58:31,536 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0819) Prec@1 90.000 (86.245) Prec@5 99.000 (98.939) +2022-11-14 13:58:31,545 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.0825) Prec@1 79.000 (86.100) Prec@5 99.000 (98.940) +2022-11-14 13:58:31,554 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0823) Prec@1 87.000 (86.118) Prec@5 99.000 (98.941) +2022-11-14 13:58:31,563 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0825) Prec@1 84.000 (86.077) Prec@5 98.000 (98.923) +2022-11-14 13:58:31,573 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0820) Prec@1 89.000 (86.132) Prec@5 100.000 (98.943) +2022-11-14 13:58:31,581 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0818) Prec@1 88.000 (86.167) Prec@5 99.000 (98.944) +2022-11-14 13:58:31,589 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0819) Prec@1 85.000 (86.145) Prec@5 99.000 (98.945) +2022-11-14 13:58:31,598 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0821) Prec@1 87.000 (86.161) Prec@5 99.000 (98.946) +2022-11-14 13:58:31,608 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0820) Prec@1 87.000 (86.175) Prec@5 100.000 (98.965) +2022-11-14 13:58:31,617 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0818) Prec@1 90.000 (86.241) Prec@5 98.000 (98.948) +2022-11-14 13:58:31,627 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1237 (0.0825) Prec@1 81.000 (86.153) Prec@5 99.000 (98.949) +2022-11-14 13:58:31,635 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0828) Prec@1 83.000 (86.100) Prec@5 100.000 (98.967) +2022-11-14 13:58:31,644 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0830) Prec@1 83.000 (86.049) Prec@5 100.000 (98.984) +2022-11-14 13:58:31,654 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0830) Prec@1 87.000 (86.065) Prec@5 99.000 (98.984) +2022-11-14 13:58:31,663 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0829) Prec@1 86.000 (86.063) Prec@5 100.000 (99.000) +2022-11-14 13:58:31,672 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0825) Prec@1 92.000 (86.156) Prec@5 100.000 (99.016) +2022-11-14 13:58:31,682 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0826) Prec@1 87.000 (86.169) Prec@5 99.000 (99.015) +2022-11-14 13:58:31,692 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0828) Prec@1 84.000 (86.136) Prec@5 97.000 (98.985) +2022-11-14 13:58:31,701 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0823) Prec@1 94.000 (86.254) Prec@5 100.000 (99.000) +2022-11-14 13:58:31,711 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0823) Prec@1 85.000 (86.235) Prec@5 100.000 (99.015) +2022-11-14 13:58:31,719 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0823) Prec@1 85.000 (86.217) Prec@5 100.000 (99.029) +2022-11-14 13:58:31,728 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0821) Prec@1 87.000 (86.229) Prec@5 100.000 (99.043) +2022-11-14 13:58:31,738 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0822) Prec@1 86.000 (86.225) Prec@5 100.000 (99.056) +2022-11-14 13:58:31,747 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0821) Prec@1 87.000 (86.236) Prec@5 98.000 (99.042) +2022-11-14 13:58:31,756 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0818) Prec@1 92.000 (86.315) Prec@5 100.000 (99.055) +2022-11-14 13:58:31,766 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0815) Prec@1 90.000 (86.365) Prec@5 100.000 (99.068) +2022-11-14 13:58:31,775 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0815) Prec@1 86.000 (86.360) Prec@5 100.000 (99.080) +2022-11-14 13:58:31,784 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0814) Prec@1 88.000 (86.382) Prec@5 98.000 (99.066) +2022-11-14 13:58:31,795 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0812) Prec@1 89.000 (86.416) Prec@5 98.000 (99.052) +2022-11-14 13:58:31,804 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0814) Prec@1 87.000 (86.423) Prec@5 98.000 (99.038) +2022-11-14 13:58:31,814 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0816) Prec@1 83.000 (86.380) Prec@5 100.000 (99.051) +2022-11-14 13:58:31,823 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0819) Prec@1 81.000 (86.312) Prec@5 100.000 (99.062) +2022-11-14 13:58:31,832 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0819) Prec@1 87.000 (86.321) Prec@5 97.000 (99.037) +2022-11-14 13:58:31,842 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0818) Prec@1 89.000 (86.354) Prec@5 100.000 (99.049) +2022-11-14 13:58:31,851 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0819) Prec@1 85.000 (86.337) Prec@5 100.000 (99.060) +2022-11-14 13:58:31,861 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0819) Prec@1 83.000 (86.298) Prec@5 99.000 (99.060) +2022-11-14 13:58:31,871 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0819) Prec@1 85.000 (86.282) Prec@5 100.000 (99.071) +2022-11-14 13:58:31,881 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0823) Prec@1 81.000 (86.221) Prec@5 99.000 (99.070) +2022-11-14 13:58:31,890 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0822) Prec@1 86.000 (86.218) Prec@5 98.000 (99.057) +2022-11-14 13:58:31,899 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0819) Prec@1 92.000 (86.284) Prec@5 99.000 (99.057) +2022-11-14 13:58:31,908 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0820) Prec@1 84.000 (86.258) Prec@5 99.000 (99.056) +2022-11-14 13:58:31,918 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0819) Prec@1 90.000 (86.300) Prec@5 100.000 (99.067) +2022-11-14 13:58:31,930 Test: [90/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0818) Prec@1 89.000 (86.330) Prec@5 100.000 (99.077) +2022-11-14 13:58:31,940 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0815) Prec@1 91.000 (86.380) Prec@5 99.000 (99.076) +2022-11-14 13:58:31,950 Test: [92/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0816) Prec@1 83.000 (86.344) Prec@5 99.000 (99.075) +2022-11-14 13:58:31,960 Test: [93/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0814) Prec@1 91.000 (86.394) Prec@5 100.000 (99.085) +2022-11-14 13:58:31,970 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0814) Prec@1 83.000 (86.358) Prec@5 98.000 (99.074) +2022-11-14 13:58:31,979 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0815) Prec@1 84.000 (86.333) Prec@5 98.000 (99.062) +2022-11-14 13:58:31,988 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0812) Prec@1 92.000 (86.392) Prec@5 98.000 (99.052) +2022-11-14 13:58:31,996 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0815) Prec@1 84.000 (86.367) Prec@5 100.000 (99.061) +2022-11-14 13:58:32,005 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0816) Prec@1 84.000 (86.343) Prec@5 99.000 (99.061) +2022-11-14 13:58:32,014 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0817) Prec@1 87.000 (86.350) Prec@5 99.000 (99.060) +2022-11-14 13:58:32,082 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:58:32,384 Epoch: [126][0/500] Time 0.026 (0.026) Data 0.215 (0.215) Loss 0.0472 (0.0472) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:32,622 Epoch: [126][10/500] Time 0.025 (0.021) Data 0.002 (0.021) Loss 0.0572 (0.0522) Prec@1 91.000 (91.500) Prec@5 99.000 (99.500) +2022-11-14 13:58:32,879 Epoch: [126][20/500] Time 0.023 (0.022) Data 0.002 (0.012) Loss 0.0580 (0.0542) Prec@1 91.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 13:58:33,161 Epoch: [126][30/500] Time 0.030 (0.023) Data 0.002 (0.009) Loss 0.0641 (0.0566) Prec@1 89.000 (90.750) Prec@5 99.000 (99.500) +2022-11-14 13:58:33,548 Epoch: [126][40/500] Time 0.035 (0.025) Data 0.002 (0.007) Loss 0.0723 (0.0598) Prec@1 87.000 (90.000) Prec@5 99.000 (99.400) +2022-11-14 13:58:33,932 Epoch: [126][50/500] Time 0.033 (0.027) Data 0.002 (0.006) Loss 0.0483 (0.0579) Prec@1 92.000 (90.333) Prec@5 100.000 (99.500) +2022-11-14 13:58:34,315 Epoch: [126][60/500] Time 0.037 (0.028) Data 0.003 (0.005) Loss 0.0611 (0.0583) Prec@1 92.000 (90.571) Prec@5 100.000 (99.571) +2022-11-14 13:58:34,698 Epoch: [126][70/500] Time 0.042 (0.029) Data 0.002 (0.005) Loss 0.0475 (0.0570) Prec@1 92.000 (90.750) Prec@5 100.000 (99.625) +2022-11-14 13:58:35,086 Epoch: [126][80/500] Time 0.036 (0.030) Data 0.002 (0.005) Loss 0.0637 (0.0577) Prec@1 89.000 (90.556) Prec@5 100.000 (99.667) +2022-11-14 13:58:35,467 Epoch: [126][90/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0457 (0.0565) Prec@1 92.000 (90.700) Prec@5 100.000 (99.700) +2022-11-14 13:58:35,854 Epoch: [126][100/500] Time 0.033 (0.031) Data 0.002 (0.004) Loss 0.0456 (0.0555) Prec@1 92.000 (90.818) Prec@5 99.000 (99.636) +2022-11-14 13:58:36,233 Epoch: [126][110/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0544 (0.0554) Prec@1 90.000 (90.750) Prec@5 100.000 (99.667) +2022-11-14 13:58:36,622 Epoch: [126][120/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0582 (0.0556) Prec@1 89.000 (90.615) Prec@5 100.000 (99.692) +2022-11-14 13:58:37,003 Epoch: [126][130/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0710 (0.0567) Prec@1 87.000 (90.357) Prec@5 98.000 (99.571) +2022-11-14 13:58:37,386 Epoch: [126][140/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0705 (0.0577) Prec@1 86.000 (90.067) Prec@5 99.000 (99.533) +2022-11-14 13:58:37,765 Epoch: [126][150/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0465 (0.0570) Prec@1 92.000 (90.188) Prec@5 99.000 (99.500) +2022-11-14 13:58:38,159 Epoch: [126][160/500] Time 0.049 (0.032) Data 0.002 (0.003) Loss 0.0678 (0.0576) Prec@1 89.000 (90.118) Prec@5 99.000 (99.471) +2022-11-14 13:58:38,539 Epoch: [126][170/500] Time 0.036 (0.032) Data 0.001 (0.003) Loss 0.0523 (0.0573) Prec@1 91.000 (90.167) Prec@5 100.000 (99.500) +2022-11-14 13:58:38,926 Epoch: [126][180/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0736 (0.0582) Prec@1 86.000 (89.947) Prec@5 99.000 (99.474) +2022-11-14 13:58:39,314 Epoch: [126][190/500] Time 0.034 (0.032) Data 0.003 (0.003) Loss 0.0543 (0.0580) Prec@1 91.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 13:58:39,708 Epoch: [126][200/500] Time 0.038 (0.032) Data 0.001 (0.003) Loss 0.0515 (0.0577) Prec@1 90.000 (90.000) Prec@5 99.000 (99.476) +2022-11-14 13:58:40,096 Epoch: [126][210/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0472 (0.0572) Prec@1 92.000 (90.091) Prec@5 99.000 (99.455) +2022-11-14 13:58:40,489 Epoch: [126][220/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0624 (0.0574) Prec@1 92.000 (90.174) Prec@5 100.000 (99.478) +2022-11-14 13:58:40,886 Epoch: [126][230/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0366 (0.0565) Prec@1 94.000 (90.333) Prec@5 100.000 (99.500) +2022-11-14 13:58:41,263 Epoch: [126][240/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0479 (0.0562) Prec@1 92.000 (90.400) Prec@5 99.000 (99.480) +2022-11-14 13:58:41,643 Epoch: [126][250/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0666 (0.0566) Prec@1 90.000 (90.385) Prec@5 99.000 (99.462) +2022-11-14 13:58:42,029 Epoch: [126][260/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0422 (0.0561) Prec@1 91.000 (90.407) Prec@5 99.000 (99.444) +2022-11-14 13:58:42,420 Epoch: [126][270/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0670 (0.0565) Prec@1 88.000 (90.321) Prec@5 99.000 (99.429) +2022-11-14 13:58:42,818 Epoch: [126][280/500] Time 0.041 (0.033) Data 0.001 (0.003) Loss 0.0470 (0.0561) Prec@1 93.000 (90.414) Prec@5 99.000 (99.414) +2022-11-14 13:58:43,201 Epoch: [126][290/500] Time 0.036 (0.033) Data 0.001 (0.003) Loss 0.0455 (0.0558) Prec@1 90.000 (90.400) Prec@5 100.000 (99.433) +2022-11-14 13:58:43,595 Epoch: [126][300/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0957 (0.0571) Prec@1 83.000 (90.161) Prec@5 100.000 (99.452) +2022-11-14 13:58:43,967 Epoch: [126][310/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0707 (0.0575) Prec@1 86.000 (90.031) Prec@5 99.000 (99.438) +2022-11-14 13:58:44,355 Epoch: [126][320/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0388 (0.0569) Prec@1 93.000 (90.121) Prec@5 100.000 (99.455) +2022-11-14 13:58:44,741 Epoch: [126][330/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0317 (0.0562) Prec@1 95.000 (90.265) Prec@5 100.000 (99.471) +2022-11-14 13:58:45,120 Epoch: [126][340/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0642 (0.0564) Prec@1 91.000 (90.286) Prec@5 99.000 (99.457) +2022-11-14 13:58:45,505 Epoch: [126][350/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0554 (0.0564) Prec@1 91.000 (90.306) Prec@5 100.000 (99.472) +2022-11-14 13:58:45,881 Epoch: [126][360/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0517 (0.0563) Prec@1 92.000 (90.351) Prec@5 99.000 (99.459) +2022-11-14 13:58:46,268 Epoch: [126][370/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0604 (0.0564) Prec@1 91.000 (90.368) Prec@5 99.000 (99.447) +2022-11-14 13:58:46,650 Epoch: [126][380/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0430 (0.0560) Prec@1 94.000 (90.462) Prec@5 99.000 (99.436) +2022-11-14 13:58:47,042 Epoch: [126][390/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0720 (0.0564) Prec@1 87.000 (90.375) Prec@5 100.000 (99.450) +2022-11-14 13:58:47,426 Epoch: [126][400/500] Time 0.040 (0.033) Data 0.002 (0.002) Loss 0.0596 (0.0565) Prec@1 92.000 (90.415) Prec@5 100.000 (99.463) +2022-11-14 13:58:47,812 Epoch: [126][410/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0612 (0.0566) Prec@1 89.000 (90.381) Prec@5 99.000 (99.452) +2022-11-14 13:58:48,188 Epoch: [126][420/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0377 (0.0562) Prec@1 93.000 (90.442) Prec@5 100.000 (99.465) +2022-11-14 13:58:48,578 Epoch: [126][430/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0440 (0.0559) Prec@1 95.000 (90.545) Prec@5 100.000 (99.477) +2022-11-14 13:58:48,955 Epoch: [126][440/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0643 (0.0561) Prec@1 91.000 (90.556) Prec@5 100.000 (99.489) +2022-11-14 13:58:49,328 Epoch: [126][450/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0237 (0.0554) Prec@1 97.000 (90.696) Prec@5 100.000 (99.500) +2022-11-14 13:58:49,711 Epoch: [126][460/500] Time 0.036 (0.033) Data 0.001 (0.002) Loss 0.0630 (0.0555) Prec@1 90.000 (90.681) Prec@5 99.000 (99.489) +2022-11-14 13:58:50,099 Epoch: [126][470/500] Time 0.032 (0.033) Data 0.002 (0.002) Loss 0.0468 (0.0554) Prec@1 91.000 (90.688) Prec@5 99.000 (99.479) +2022-11-14 13:58:50,488 Epoch: [126][480/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0430 (0.0551) Prec@1 96.000 (90.796) Prec@5 100.000 (99.490) +2022-11-14 13:58:50,861 Epoch: [126][490/500] Time 0.036 (0.033) Data 0.001 (0.002) Loss 0.0660 (0.0553) Prec@1 91.000 (90.800) Prec@5 99.000 (99.480) +2022-11-14 13:58:51,231 Epoch: [126][499/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0781 (0.0558) Prec@1 87.000 (90.725) Prec@5 99.000 (99.471) +2022-11-14 13:58:51,521 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0464 (0.0464) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,536 Test: [1/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0791 (0.0628) Prec@1 88.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,547 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0709 (0.0655) Prec@1 88.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,560 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0769 (0.0683) Prec@1 86.000 (88.750) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,568 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0692) Prec@1 86.000 (88.200) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,579 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0484 (0.0658) Prec@1 92.000 (88.833) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,589 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0642 (0.0655) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:51,598 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0696) Prec@1 84.000 (88.375) Prec@5 99.000 (99.875) +2022-11-14 13:58:51,606 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0703) Prec@1 89.000 (88.444) Prec@5 99.000 (99.778) +2022-11-14 13:58:51,618 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0687) Prec@1 90.000 (88.600) Prec@5 99.000 (99.700) +2022-11-14 13:58:51,629 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0700) Prec@1 85.000 (88.273) Prec@5 100.000 (99.727) +2022-11-14 13:58:51,638 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0704) Prec@1 91.000 (88.500) Prec@5 99.000 (99.667) +2022-11-14 13:58:51,648 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0703) Prec@1 87.000 (88.385) Prec@5 99.000 (99.615) +2022-11-14 13:58:51,658 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0721) Prec@1 82.000 (87.929) Prec@5 97.000 (99.429) +2022-11-14 13:58:51,669 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0723) Prec@1 90.000 (88.067) Prec@5 99.000 (99.400) +2022-11-14 13:58:51,679 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0733) Prec@1 84.000 (87.812) Prec@5 100.000 (99.438) +2022-11-14 13:58:51,689 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0723) Prec@1 92.000 (88.059) Prec@5 99.000 (99.412) +2022-11-14 13:58:51,698 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.0745) Prec@1 83.000 (87.778) Prec@5 99.000 (99.389) +2022-11-14 13:58:51,706 Test: [18/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0754) Prec@1 82.000 (87.474) Prec@5 100.000 (99.421) +2022-11-14 13:58:51,716 Test: [19/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0761) Prec@1 86.000 (87.400) Prec@5 97.000 (99.300) +2022-11-14 13:58:51,723 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0759) Prec@1 87.000 (87.381) Prec@5 100.000 (99.333) +2022-11-14 13:58:51,735 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0760) Prec@1 88.000 (87.409) Prec@5 98.000 (99.273) +2022-11-14 13:58:51,745 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0769) Prec@1 85.000 (87.304) Prec@5 98.000 (99.217) +2022-11-14 13:58:51,754 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0771) Prec@1 85.000 (87.208) Prec@5 100.000 (99.250) +2022-11-14 13:58:51,763 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0775) Prec@1 84.000 (87.080) Prec@5 100.000 (99.280) +2022-11-14 13:58:51,772 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0782) Prec@1 87.000 (87.077) Prec@5 97.000 (99.192) +2022-11-14 13:58:51,781 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0775) Prec@1 88.000 (87.111) Prec@5 100.000 (99.222) +2022-11-14 13:58:51,789 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0771) Prec@1 89.000 (87.179) Prec@5 100.000 (99.250) +2022-11-14 13:58:51,797 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0773) Prec@1 84.000 (87.069) Prec@5 97.000 (99.172) +2022-11-14 13:58:51,805 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0779) Prec@1 83.000 (86.933) Prec@5 99.000 (99.167) +2022-11-14 13:58:51,813 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0784) Prec@1 84.000 (86.839) Prec@5 99.000 (99.161) +2022-11-14 13:58:51,821 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0788) Prec@1 84.000 (86.750) Prec@5 99.000 (99.156) +2022-11-14 13:58:51,830 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0788) Prec@1 83.000 (86.636) Prec@5 100.000 (99.182) +2022-11-14 13:58:51,839 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0792) Prec@1 81.000 (86.471) Prec@5 99.000 (99.176) +2022-11-14 13:58:51,848 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0792) Prec@1 86.000 (86.457) Prec@5 98.000 (99.143) +2022-11-14 13:58:51,857 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0795) Prec@1 85.000 (86.417) Prec@5 100.000 (99.167) +2022-11-14 13:58:51,866 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0794) Prec@1 88.000 (86.459) Prec@5 100.000 (99.189) +2022-11-14 13:58:51,875 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0802) Prec@1 79.000 (86.263) Prec@5 98.000 (99.158) +2022-11-14 13:58:51,885 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0800) Prec@1 89.000 (86.333) Prec@5 99.000 (99.154) +2022-11-14 13:58:51,894 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0506 (0.0792) Prec@1 92.000 (86.475) Prec@5 99.000 (99.150) +2022-11-14 13:58:51,903 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0801) Prec@1 83.000 (86.390) Prec@5 98.000 (99.122) +2022-11-14 13:58:51,913 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0800) Prec@1 87.000 (86.405) Prec@5 99.000 (99.119) +2022-11-14 13:58:51,922 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0799) Prec@1 89.000 (86.465) Prec@5 98.000 (99.093) +2022-11-14 13:58:51,931 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0797) Prec@1 90.000 (86.545) Prec@5 98.000 (99.068) +2022-11-14 13:58:51,940 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0794) Prec@1 88.000 (86.578) Prec@5 99.000 (99.067) +2022-11-14 13:58:51,949 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0793) Prec@1 87.000 (86.587) Prec@5 99.000 (99.065) +2022-11-14 13:58:51,959 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0788) Prec@1 91.000 (86.681) Prec@5 100.000 (99.085) +2022-11-14 13:58:51,968 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0792) Prec@1 85.000 (86.646) Prec@5 100.000 (99.104) +2022-11-14 13:58:51,977 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0785) Prec@1 93.000 (86.776) Prec@5 100.000 (99.122) +2022-11-14 13:58:51,987 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1198 (0.0793) Prec@1 79.000 (86.620) Prec@5 99.000 (99.120) +2022-11-14 13:58:51,996 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0790) Prec@1 89.000 (86.667) Prec@5 100.000 (99.137) +2022-11-14 13:58:52,005 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0790) Prec@1 87.000 (86.673) Prec@5 99.000 (99.135) +2022-11-14 13:58:52,015 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0785) Prec@1 92.000 (86.774) Prec@5 100.000 (99.151) +2022-11-14 13:58:52,024 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0783) Prec@1 88.000 (86.796) Prec@5 99.000 (99.148) +2022-11-14 13:58:52,033 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0786) Prec@1 84.000 (86.745) Prec@5 99.000 (99.145) +2022-11-14 13:58:52,043 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0787) Prec@1 87.000 (86.750) Prec@5 99.000 (99.143) +2022-11-14 13:58:52,051 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0788) Prec@1 86.000 (86.737) Prec@5 100.000 (99.158) +2022-11-14 13:58:52,060 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0787) Prec@1 89.000 (86.776) Prec@5 98.000 (99.138) +2022-11-14 13:58:52,070 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0790) Prec@1 82.000 (86.695) Prec@5 100.000 (99.153) +2022-11-14 13:58:52,079 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0791) Prec@1 85.000 (86.667) Prec@5 100.000 (99.167) +2022-11-14 13:58:52,087 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0791) Prec@1 89.000 (86.705) Prec@5 100.000 (99.180) +2022-11-14 13:58:52,094 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0790) Prec@1 89.000 (86.742) Prec@5 99.000 (99.177) +2022-11-14 13:58:52,102 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0787) Prec@1 90.000 (86.794) Prec@5 100.000 (99.190) +2022-11-14 13:58:52,110 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0782) Prec@1 91.000 (86.859) Prec@5 100.000 (99.203) +2022-11-14 13:58:52,120 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0783) Prec@1 83.000 (86.800) Prec@5 100.000 (99.215) +2022-11-14 13:58:52,131 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0784) Prec@1 84.000 (86.758) Prec@5 99.000 (99.212) +2022-11-14 13:58:52,140 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0779) Prec@1 92.000 (86.836) Prec@5 100.000 (99.224) +2022-11-14 13:58:52,150 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0782) Prec@1 87.000 (86.838) Prec@5 98.000 (99.206) +2022-11-14 13:58:52,159 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0779) Prec@1 92.000 (86.913) Prec@5 98.000 (99.188) +2022-11-14 13:58:52,169 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0780) Prec@1 85.000 (86.886) Prec@5 98.000 (99.171) +2022-11-14 13:58:52,178 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0779) Prec@1 89.000 (86.915) Prec@5 99.000 (99.169) +2022-11-14 13:58:52,187 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0779) Prec@1 87.000 (86.917) Prec@5 99.000 (99.167) +2022-11-14 13:58:52,197 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0779) Prec@1 86.000 (86.904) Prec@5 100.000 (99.178) +2022-11-14 13:58:52,206 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0776) Prec@1 90.000 (86.946) Prec@5 100.000 (99.189) +2022-11-14 13:58:52,215 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0777) Prec@1 86.000 (86.933) Prec@5 100.000 (99.200) +2022-11-14 13:58:52,224 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0775) Prec@1 90.000 (86.974) Prec@5 98.000 (99.184) +2022-11-14 13:58:52,232 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0776) Prec@1 83.000 (86.922) Prec@5 97.000 (99.156) +2022-11-14 13:58:52,241 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0777) Prec@1 85.000 (86.897) Prec@5 98.000 (99.141) +2022-11-14 13:58:52,251 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0777) Prec@1 87.000 (86.899) Prec@5 100.000 (99.152) +2022-11-14 13:58:52,260 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0777) Prec@1 86.000 (86.888) Prec@5 99.000 (99.150) +2022-11-14 13:58:52,269 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0777) Prec@1 88.000 (86.901) Prec@5 99.000 (99.148) +2022-11-14 13:58:52,279 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0776) Prec@1 86.000 (86.890) Prec@5 99.000 (99.146) +2022-11-14 13:58:52,289 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0778) Prec@1 87.000 (86.892) Prec@5 100.000 (99.157) +2022-11-14 13:58:52,299 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0777) Prec@1 90.000 (86.929) Prec@5 99.000 (99.155) +2022-11-14 13:58:52,311 Test: [84/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0779) Prec@1 82.000 (86.871) Prec@5 100.000 (99.165) +2022-11-14 13:58:52,324 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0780) Prec@1 84.000 (86.837) Prec@5 100.000 (99.174) +2022-11-14 13:58:52,335 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0779) Prec@1 90.000 (86.874) Prec@5 100.000 (99.184) +2022-11-14 13:58:52,345 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0779) Prec@1 88.000 (86.886) Prec@5 98.000 (99.170) +2022-11-14 13:58:52,357 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0779) Prec@1 84.000 (86.854) Prec@5 100.000 (99.180) +2022-11-14 13:58:52,369 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0780) Prec@1 88.000 (86.867) Prec@5 100.000 (99.189) +2022-11-14 13:58:52,382 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0777) Prec@1 92.000 (86.923) Prec@5 100.000 (99.198) +2022-11-14 13:58:52,396 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0775) Prec@1 92.000 (86.978) Prec@5 99.000 (99.196) +2022-11-14 13:58:52,407 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0777) Prec@1 83.000 (86.935) Prec@5 98.000 (99.183) +2022-11-14 13:58:52,419 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0778) Prec@1 86.000 (86.926) Prec@5 100.000 (99.191) +2022-11-14 13:58:52,431 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0779) Prec@1 83.000 (86.884) Prec@5 99.000 (99.189) +2022-11-14 13:58:52,448 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0777) Prec@1 90.000 (86.917) Prec@5 99.000 (99.188) +2022-11-14 13:58:52,463 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0774) Prec@1 92.000 (86.969) Prec@5 100.000 (99.196) +2022-11-14 13:58:52,477 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0777) Prec@1 83.000 (86.929) Prec@5 100.000 (99.204) +2022-11-14 13:58:52,493 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0778) Prec@1 83.000 (86.889) Prec@5 99.000 (99.202) +2022-11-14 13:58:52,508 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0780) Prec@1 84.000 (86.860) Prec@5 98.000 (99.190) +2022-11-14 13:58:52,563 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:58:52,868 Epoch: [127][0/500] Time 0.023 (0.023) Data 0.223 (0.223) Loss 0.0604 (0.0604) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 13:58:53,104 Epoch: [127][10/500] Time 0.025 (0.021) Data 0.001 (0.022) Loss 0.0455 (0.0530) Prec@1 94.000 (92.500) Prec@5 98.000 (99.000) +2022-11-14 13:58:53,370 Epoch: [127][20/500] Time 0.025 (0.022) Data 0.002 (0.012) Loss 0.0760 (0.0606) Prec@1 88.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 13:58:53,639 Epoch: [127][30/500] Time 0.024 (0.023) Data 0.002 (0.009) Loss 0.0552 (0.0593) Prec@1 90.000 (90.750) Prec@5 100.000 (99.250) +2022-11-14 13:58:54,039 Epoch: [127][40/500] Time 0.044 (0.026) Data 0.002 (0.007) Loss 0.0517 (0.0578) Prec@1 90.000 (90.600) Prec@5 100.000 (99.400) +2022-11-14 13:58:54,509 Epoch: [127][50/500] Time 0.043 (0.029) Data 0.002 (0.006) Loss 0.0667 (0.0593) Prec@1 89.000 (90.333) Prec@5 99.000 (99.333) +2022-11-14 13:58:54,984 Epoch: [127][60/500] Time 0.042 (0.031) Data 0.002 (0.005) Loss 0.0638 (0.0599) Prec@1 90.000 (90.286) Prec@5 99.000 (99.286) +2022-11-14 13:58:55,456 Epoch: [127][70/500] Time 0.042 (0.033) Data 0.002 (0.005) Loss 0.0736 (0.0616) Prec@1 86.000 (89.750) Prec@5 100.000 (99.375) +2022-11-14 13:58:55,927 Epoch: [127][80/500] Time 0.048 (0.034) Data 0.002 (0.005) Loss 0.0569 (0.0611) Prec@1 90.000 (89.778) Prec@5 99.000 (99.333) +2022-11-14 13:58:56,391 Epoch: [127][90/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0689 (0.0619) Prec@1 89.000 (89.700) Prec@5 99.000 (99.300) +2022-11-14 13:58:56,874 Epoch: [127][100/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0763 (0.0632) Prec@1 88.000 (89.545) Prec@5 100.000 (99.364) +2022-11-14 13:58:57,367 Epoch: [127][110/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0809 (0.0647) Prec@1 85.000 (89.167) Prec@5 96.000 (99.083) +2022-11-14 13:58:57,848 Epoch: [127][120/500] Time 0.044 (0.037) Data 0.002 (0.004) Loss 0.0620 (0.0645) Prec@1 89.000 (89.154) Prec@5 100.000 (99.154) +2022-11-14 13:58:58,320 Epoch: [127][130/500] Time 0.044 (0.037) Data 0.002 (0.004) Loss 0.0576 (0.0640) Prec@1 92.000 (89.357) Prec@5 100.000 (99.214) +2022-11-14 13:58:58,842 Epoch: [127][140/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0552 (0.0634) Prec@1 91.000 (89.467) Prec@5 100.000 (99.267) +2022-11-14 13:58:59,314 Epoch: [127][150/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0641 (0.0634) Prec@1 86.000 (89.250) Prec@5 98.000 (99.188) +2022-11-14 13:58:59,785 Epoch: [127][160/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0686 (0.0637) Prec@1 85.000 (89.000) Prec@5 99.000 (99.176) +2022-11-14 13:59:00,264 Epoch: [127][170/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0435 (0.0626) Prec@1 92.000 (89.167) Prec@5 99.000 (99.167) +2022-11-14 13:59:00,739 Epoch: [127][180/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0429 (0.0616) Prec@1 93.000 (89.368) Prec@5 100.000 (99.211) +2022-11-14 13:59:01,203 Epoch: [127][190/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0494 (0.0610) Prec@1 92.000 (89.500) Prec@5 99.000 (99.200) +2022-11-14 13:59:01,674 Epoch: [127][200/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0433 (0.0601) Prec@1 92.000 (89.619) Prec@5 99.000 (99.190) +2022-11-14 13:59:02,144 Epoch: [127][210/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0678 (0.0605) Prec@1 88.000 (89.545) Prec@5 99.000 (99.182) +2022-11-14 13:59:02,617 Epoch: [127][220/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0376 (0.0595) Prec@1 93.000 (89.696) Prec@5 100.000 (99.217) +2022-11-14 13:59:03,085 Epoch: [127][230/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0627 (0.0596) Prec@1 87.000 (89.583) Prec@5 100.000 (99.250) +2022-11-14 13:59:03,551 Epoch: [127][240/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0451 (0.0590) Prec@1 94.000 (89.760) Prec@5 100.000 (99.280) +2022-11-14 13:59:04,023 Epoch: [127][250/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0677 (0.0594) Prec@1 86.000 (89.615) Prec@5 99.000 (99.269) +2022-11-14 13:59:04,499 Epoch: [127][260/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0609 (0.0594) Prec@1 91.000 (89.667) Prec@5 99.000 (99.259) +2022-11-14 13:59:04,971 Epoch: [127][270/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0544 (0.0592) Prec@1 91.000 (89.714) Prec@5 100.000 (99.286) +2022-11-14 13:59:05,434 Epoch: [127][280/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0470 (0.0588) Prec@1 92.000 (89.793) Prec@5 100.000 (99.310) +2022-11-14 13:59:05,904 Epoch: [127][290/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0798 (0.0595) Prec@1 86.000 (89.667) Prec@5 99.000 (99.300) +2022-11-14 13:59:06,377 Epoch: [127][300/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0570 (0.0594) Prec@1 91.000 (89.710) Prec@5 99.000 (99.290) +2022-11-14 13:59:06,846 Epoch: [127][310/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0400 (0.0588) Prec@1 94.000 (89.844) Prec@5 98.000 (99.250) +2022-11-14 13:59:07,335 Epoch: [127][320/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0815 (0.0595) Prec@1 86.000 (89.727) Prec@5 97.000 (99.182) +2022-11-14 13:59:07,797 Epoch: [127][330/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0599 (0.0595) Prec@1 90.000 (89.735) Prec@5 99.000 (99.176) +2022-11-14 13:59:08,269 Epoch: [127][340/500] Time 0.044 (0.040) Data 0.001 (0.002) Loss 0.0533 (0.0593) Prec@1 92.000 (89.800) Prec@5 100.000 (99.200) +2022-11-14 13:59:08,740 Epoch: [127][350/500] Time 0.042 (0.040) Data 0.001 (0.002) Loss 0.0658 (0.0595) Prec@1 90.000 (89.806) Prec@5 99.000 (99.194) +2022-11-14 13:59:09,211 Epoch: [127][360/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0520 (0.0593) Prec@1 91.000 (89.838) Prec@5 100.000 (99.216) +2022-11-14 13:59:09,679 Epoch: [127][370/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0496 (0.0591) Prec@1 91.000 (89.868) Prec@5 100.000 (99.237) +2022-11-14 13:59:10,145 Epoch: [127][380/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0363 (0.0585) Prec@1 96.000 (90.026) Prec@5 99.000 (99.231) +2022-11-14 13:59:10,619 Epoch: [127][390/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0915 (0.0593) Prec@1 83.000 (89.850) Prec@5 100.000 (99.250) +2022-11-14 13:59:11,098 Epoch: [127][400/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0541 (0.0592) Prec@1 89.000 (89.829) Prec@5 100.000 (99.268) +2022-11-14 13:59:11,569 Epoch: [127][410/500] Time 0.050 (0.041) Data 0.002 (0.002) Loss 0.0409 (0.0587) Prec@1 92.000 (89.881) Prec@5 100.000 (99.286) +2022-11-14 13:59:11,899 Epoch: [127][420/500] Time 0.029 (0.040) Data 0.002 (0.002) Loss 0.0794 (0.0592) Prec@1 90.000 (89.884) Prec@5 99.000 (99.279) +2022-11-14 13:59:12,233 Epoch: [127][430/500] Time 0.030 (0.040) Data 0.001 (0.002) Loss 0.0503 (0.0590) Prec@1 90.000 (89.886) Prec@5 100.000 (99.295) +2022-11-14 13:59:12,559 Epoch: [127][440/500] Time 0.033 (0.040) Data 0.001 (0.002) Loss 0.0581 (0.0590) Prec@1 92.000 (89.933) Prec@5 100.000 (99.311) +2022-11-14 13:59:12,889 Epoch: [127][450/500] Time 0.031 (0.040) Data 0.002 (0.002) Loss 0.0564 (0.0589) Prec@1 92.000 (89.978) Prec@5 100.000 (99.326) +2022-11-14 13:59:13,212 Epoch: [127][460/500] Time 0.032 (0.039) Data 0.002 (0.002) Loss 0.0755 (0.0593) Prec@1 87.000 (89.915) Prec@5 99.000 (99.319) +2022-11-14 13:59:13,549 Epoch: [127][470/500] Time 0.028 (0.039) Data 0.002 (0.002) Loss 0.0574 (0.0593) Prec@1 89.000 (89.896) Prec@5 97.000 (99.271) +2022-11-14 13:59:13,883 Epoch: [127][480/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0664 (0.0594) Prec@1 87.000 (89.837) Prec@5 100.000 (99.286) +2022-11-14 13:59:14,208 Epoch: [127][490/500] Time 0.029 (0.039) Data 0.001 (0.002) Loss 0.0523 (0.0593) Prec@1 91.000 (89.860) Prec@5 100.000 (99.300) +2022-11-14 13:59:14,509 Epoch: [127][499/500] Time 0.034 (0.039) Data 0.002 (0.002) Loss 0.0545 (0.0592) Prec@1 90.000 (89.863) Prec@5 100.000 (99.314) +2022-11-14 13:59:14,806 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0669 (0.0669) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:59:14,818 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0672) Prec@1 90.000 (89.000) Prec@5 98.000 (99.000) +2022-11-14 13:59:14,827 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0713) Prec@1 88.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 13:59:14,838 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0745) Prec@1 85.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 13:59:14,846 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0727) Prec@1 89.000 (88.000) Prec@5 100.000 (99.400) +2022-11-14 13:59:14,854 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0341 (0.0663) Prec@1 95.000 (89.167) Prec@5 100.000 (99.500) +2022-11-14 13:59:14,861 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0659) Prec@1 91.000 (89.429) Prec@5 100.000 (99.571) +2022-11-14 13:59:14,869 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0692) Prec@1 85.000 (88.875) Prec@5 100.000 (99.625) +2022-11-14 13:59:14,877 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0714) Prec@1 86.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 13:59:14,885 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0725) Prec@1 87.000 (88.400) Prec@5 98.000 (99.500) +2022-11-14 13:59:14,894 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0713) Prec@1 87.000 (88.273) Prec@5 100.000 (99.545) +2022-11-14 13:59:14,903 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0738) Prec@1 83.000 (87.833) Prec@5 100.000 (99.583) +2022-11-14 13:59:14,913 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0732) Prec@1 87.000 (87.769) Prec@5 100.000 (99.615) +2022-11-14 13:59:14,922 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0742) Prec@1 87.000 (87.714) Prec@5 99.000 (99.571) +2022-11-14 13:59:14,933 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0746) Prec@1 86.000 (87.600) Prec@5 99.000 (99.533) +2022-11-14 13:59:14,942 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1301 (0.0781) Prec@1 77.000 (86.938) Prec@5 99.000 (99.500) +2022-11-14 13:59:14,952 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0776) Prec@1 89.000 (87.059) Prec@5 98.000 (99.412) +2022-11-14 13:59:14,961 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0789) Prec@1 82.000 (86.778) Prec@5 100.000 (99.444) +2022-11-14 13:59:14,970 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0788) Prec@1 87.000 (86.789) Prec@5 99.000 (99.421) +2022-11-14 13:59:14,979 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0793) Prec@1 88.000 (86.850) Prec@5 98.000 (99.350) +2022-11-14 13:59:14,989 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0807) Prec@1 84.000 (86.714) Prec@5 100.000 (99.381) +2022-11-14 13:59:14,997 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0805) Prec@1 87.000 (86.727) Prec@5 99.000 (99.364) +2022-11-14 13:59:15,007 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0805) Prec@1 90.000 (86.870) Prec@5 99.000 (99.348) +2022-11-14 13:59:15,016 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0795) Prec@1 90.000 (87.000) Prec@5 99.000 (99.333) +2022-11-14 13:59:15,025 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0794) Prec@1 88.000 (87.040) Prec@5 100.000 (99.360) +2022-11-14 13:59:15,035 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0802) Prec@1 83.000 (86.885) Prec@5 98.000 (99.308) +2022-11-14 13:59:15,044 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0793) Prec@1 90.000 (87.000) Prec@5 100.000 (99.333) +2022-11-14 13:59:15,053 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0793) Prec@1 87.000 (87.000) Prec@5 99.000 (99.321) +2022-11-14 13:59:15,063 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0790) Prec@1 88.000 (87.034) Prec@5 99.000 (99.310) +2022-11-14 13:59:15,072 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0791) Prec@1 83.000 (86.900) Prec@5 99.000 (99.300) +2022-11-14 13:59:15,081 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0797) Prec@1 84.000 (86.806) Prec@5 100.000 (99.323) +2022-11-14 13:59:15,091 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0797) Prec@1 89.000 (86.875) Prec@5 99.000 (99.312) +2022-11-14 13:59:15,100 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0800) Prec@1 85.000 (86.818) Prec@5 97.000 (99.242) +2022-11-14 13:59:15,109 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1157 (0.0811) Prec@1 79.000 (86.588) Prec@5 99.000 (99.235) +2022-11-14 13:59:15,119 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0809) Prec@1 88.000 (86.629) Prec@5 100.000 (99.257) +2022-11-14 13:59:15,128 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0807) Prec@1 88.000 (86.667) Prec@5 100.000 (99.278) +2022-11-14 13:59:15,136 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0810) Prec@1 84.000 (86.595) Prec@5 99.000 (99.270) +2022-11-14 13:59:15,144 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0814) Prec@1 82.000 (86.474) Prec@5 99.000 (99.263) +2022-11-14 13:59:15,152 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0807) Prec@1 92.000 (86.615) Prec@5 99.000 (99.256) +2022-11-14 13:59:15,161 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0803) Prec@1 88.000 (86.650) Prec@5 98.000 (99.225) +2022-11-14 13:59:15,170 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0803) Prec@1 89.000 (86.707) Prec@5 98.000 (99.195) +2022-11-14 13:59:15,179 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0800) Prec@1 87.000 (86.714) Prec@5 98.000 (99.167) +2022-11-14 13:59:15,188 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0792) Prec@1 91.000 (86.814) Prec@5 100.000 (99.186) +2022-11-14 13:59:15,197 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0792) Prec@1 87.000 (86.818) Prec@5 99.000 (99.182) +2022-11-14 13:59:15,206 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0791) Prec@1 87.000 (86.822) Prec@5 99.000 (99.178) +2022-11-14 13:59:15,216 Test: [45/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0794) Prec@1 83.000 (86.739) Prec@5 99.000 (99.174) +2022-11-14 13:59:15,225 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0794) Prec@1 89.000 (86.787) Prec@5 100.000 (99.191) +2022-11-14 13:59:15,235 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.0801) Prec@1 82.000 (86.688) Prec@5 99.000 (99.188) +2022-11-14 13:59:15,246 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0798) Prec@1 90.000 (86.755) Prec@5 99.000 (99.184) +2022-11-14 13:59:15,256 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.0804) Prec@1 80.000 (86.620) Prec@5 100.000 (99.200) +2022-11-14 13:59:15,266 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0804) Prec@1 84.000 (86.569) Prec@5 98.000 (99.176) +2022-11-14 13:59:15,276 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0805) Prec@1 83.000 (86.500) Prec@5 98.000 (99.154) +2022-11-14 13:59:15,286 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0808) Prec@1 84.000 (86.453) Prec@5 100.000 (99.170) +2022-11-14 13:59:15,297 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0811) Prec@1 82.000 (86.370) Prec@5 99.000 (99.167) +2022-11-14 13:59:15,306 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0810) Prec@1 88.000 (86.400) Prec@5 100.000 (99.182) +2022-11-14 13:59:15,316 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0809) Prec@1 88.000 (86.429) Prec@5 99.000 (99.179) +2022-11-14 13:59:15,325 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0808) Prec@1 89.000 (86.474) Prec@5 100.000 (99.193) +2022-11-14 13:59:15,337 Test: [57/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0806) Prec@1 91.000 (86.552) Prec@5 99.000 (99.190) +2022-11-14 13:59:15,348 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0807) Prec@1 85.000 (86.525) Prec@5 100.000 (99.203) +2022-11-14 13:59:15,357 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0806) Prec@1 86.000 (86.517) Prec@5 98.000 (99.183) +2022-11-14 13:59:15,366 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0804) Prec@1 89.000 (86.557) Prec@5 100.000 (99.197) +2022-11-14 13:59:15,378 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0806) Prec@1 84.000 (86.516) Prec@5 99.000 (99.194) +2022-11-14 13:59:15,390 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0805) Prec@1 87.000 (86.524) Prec@5 99.000 (99.190) +2022-11-14 13:59:15,400 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0356 (0.0798) Prec@1 94.000 (86.641) Prec@5 100.000 (99.203) +2022-11-14 13:59:15,410 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0800) Prec@1 85.000 (86.615) Prec@5 98.000 (99.185) +2022-11-14 13:59:15,420 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0800) Prec@1 87.000 (86.621) Prec@5 98.000 (99.167) +2022-11-14 13:59:15,429 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0460 (0.0795) Prec@1 92.000 (86.701) Prec@5 100.000 (99.179) +2022-11-14 13:59:15,438 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0793) Prec@1 88.000 (86.721) Prec@5 100.000 (99.191) +2022-11-14 13:59:15,446 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0794) Prec@1 84.000 (86.681) Prec@5 99.000 (99.188) +2022-11-14 13:59:15,454 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0793) Prec@1 88.000 (86.700) Prec@5 99.000 (99.186) +2022-11-14 13:59:15,462 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0796) Prec@1 84.000 (86.662) Prec@5 98.000 (99.169) +2022-11-14 13:59:15,471 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0793) Prec@1 90.000 (86.708) Prec@5 99.000 (99.167) +2022-11-14 13:59:15,481 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0790) Prec@1 90.000 (86.753) Prec@5 100.000 (99.178) +2022-11-14 13:59:15,489 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0786) Prec@1 93.000 (86.838) Prec@5 100.000 (99.189) +2022-11-14 13:59:15,498 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0790) Prec@1 83.000 (86.787) Prec@5 99.000 (99.187) +2022-11-14 13:59:15,507 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0789) Prec@1 87.000 (86.789) Prec@5 99.000 (99.184) +2022-11-14 13:59:15,517 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0789) Prec@1 83.000 (86.740) Prec@5 99.000 (99.182) +2022-11-14 13:59:15,526 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0790) Prec@1 85.000 (86.718) Prec@5 97.000 (99.154) +2022-11-14 13:59:15,536 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0792) Prec@1 86.000 (86.709) Prec@5 99.000 (99.152) +2022-11-14 13:59:15,546 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0792) Prec@1 89.000 (86.737) Prec@5 100.000 (99.162) +2022-11-14 13:59:15,556 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0791) Prec@1 87.000 (86.741) Prec@5 99.000 (99.160) +2022-11-14 13:59:15,565 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0790) Prec@1 87.000 (86.744) Prec@5 99.000 (99.159) +2022-11-14 13:59:15,574 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0792) Prec@1 83.000 (86.699) Prec@5 100.000 (99.169) +2022-11-14 13:59:15,583 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0791) Prec@1 88.000 (86.714) Prec@5 99.000 (99.167) +2022-11-14 13:59:15,593 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0792) Prec@1 85.000 (86.694) Prec@5 100.000 (99.176) +2022-11-14 13:59:15,602 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0794) Prec@1 87.000 (86.698) Prec@5 100.000 (99.186) +2022-11-14 13:59:15,611 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0792) Prec@1 91.000 (86.747) Prec@5 100.000 (99.195) +2022-11-14 13:59:15,621 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0791) Prec@1 88.000 (86.761) Prec@5 99.000 (99.193) +2022-11-14 13:59:15,630 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0790) Prec@1 86.000 (86.753) Prec@5 99.000 (99.191) +2022-11-14 13:59:15,639 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0790) Prec@1 86.000 (86.744) Prec@5 100.000 (99.200) +2022-11-14 13:59:15,648 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0787) Prec@1 90.000 (86.780) Prec@5 100.000 (99.209) +2022-11-14 13:59:15,657 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0784) Prec@1 91.000 (86.826) Prec@5 100.000 (99.217) +2022-11-14 13:59:15,667 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0787) Prec@1 80.000 (86.753) Prec@5 100.000 (99.226) +2022-11-14 13:59:15,676 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0787) Prec@1 84.000 (86.723) Prec@5 99.000 (99.223) +2022-11-14 13:59:15,685 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0787) Prec@1 89.000 (86.747) Prec@5 100.000 (99.232) +2022-11-14 13:59:15,694 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0786) Prec@1 86.000 (86.740) Prec@5 99.000 (99.229) +2022-11-14 13:59:15,704 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0785) Prec@1 86.000 (86.732) Prec@5 99.000 (99.227) +2022-11-14 13:59:15,712 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0787) Prec@1 84.000 (86.704) Prec@5 99.000 (99.224) +2022-11-14 13:59:15,721 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0788) Prec@1 87.000 (86.707) Prec@5 100.000 (99.232) +2022-11-14 13:59:15,730 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0788) Prec@1 89.000 (86.730) Prec@5 99.000 (99.230) +2022-11-14 13:59:15,782 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:59:16,096 Epoch: [128][0/500] Time 0.023 (0.023) Data 0.232 (0.232) Loss 0.0465 (0.0465) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 13:59:16,307 Epoch: [128][10/500] Time 0.018 (0.019) Data 0.002 (0.023) Loss 0.0375 (0.0420) Prec@1 95.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 13:59:16,522 Epoch: [128][20/500] Time 0.019 (0.019) Data 0.002 (0.013) Loss 0.0696 (0.0512) Prec@1 88.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 13:59:16,787 Epoch: [128][30/500] Time 0.024 (0.020) Data 0.002 (0.009) Loss 0.0543 (0.0520) Prec@1 93.000 (92.250) Prec@5 100.000 (99.750) +2022-11-14 13:59:17,050 Epoch: [128][40/500] Time 0.022 (0.021) Data 0.002 (0.007) Loss 0.0528 (0.0521) Prec@1 95.000 (92.800) Prec@5 99.000 (99.600) +2022-11-14 13:59:17,304 Epoch: [128][50/500] Time 0.025 (0.021) Data 0.001 (0.006) Loss 0.0573 (0.0530) Prec@1 91.000 (92.500) Prec@5 100.000 (99.667) +2022-11-14 13:59:17,610 Epoch: [128][60/500] Time 0.040 (0.022) Data 0.002 (0.006) Loss 0.0771 (0.0564) Prec@1 89.000 (92.000) Prec@5 99.000 (99.571) +2022-11-14 13:59:18,081 Epoch: [128][70/500] Time 0.043 (0.025) Data 0.002 (0.005) Loss 0.0617 (0.0571) Prec@1 90.000 (91.750) Prec@5 100.000 (99.625) +2022-11-14 13:59:18,555 Epoch: [128][80/500] Time 0.045 (0.027) Data 0.002 (0.005) Loss 0.0558 (0.0570) Prec@1 92.000 (91.778) Prec@5 99.000 (99.556) +2022-11-14 13:59:19,054 Epoch: [128][90/500] Time 0.050 (0.029) Data 0.002 (0.004) Loss 0.0572 (0.0570) Prec@1 89.000 (91.500) Prec@5 100.000 (99.600) +2022-11-14 13:59:19,543 Epoch: [128][100/500] Time 0.051 (0.030) Data 0.002 (0.004) Loss 0.0546 (0.0568) Prec@1 90.000 (91.364) Prec@5 100.000 (99.636) +2022-11-14 13:59:20,019 Epoch: [128][110/500] Time 0.042 (0.031) Data 0.002 (0.004) Loss 0.0534 (0.0565) Prec@1 91.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 13:59:20,484 Epoch: [128][120/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.0417 (0.0553) Prec@1 93.000 (91.462) Prec@5 100.000 (99.692) +2022-11-14 13:59:20,957 Epoch: [128][130/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0437 (0.0545) Prec@1 92.000 (91.500) Prec@5 100.000 (99.714) +2022-11-14 13:59:21,431 Epoch: [128][140/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0635 (0.0551) Prec@1 89.000 (91.333) Prec@5 100.000 (99.733) +2022-11-14 13:59:21,916 Epoch: [128][150/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0472 (0.0546) Prec@1 92.000 (91.375) Prec@5 98.000 (99.625) +2022-11-14 13:59:22,415 Epoch: [128][160/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0452 (0.0541) Prec@1 93.000 (91.471) Prec@5 98.000 (99.529) +2022-11-14 13:59:22,877 Epoch: [128][170/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0720 (0.0551) Prec@1 85.000 (91.111) Prec@5 100.000 (99.556) +2022-11-14 13:59:23,367 Epoch: [128][180/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0658 (0.0556) Prec@1 90.000 (91.053) Prec@5 99.000 (99.526) +2022-11-14 13:59:23,864 Epoch: [128][190/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0529 (0.0555) Prec@1 91.000 (91.050) Prec@5 100.000 (99.550) +2022-11-14 13:59:24,347 Epoch: [128][200/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0388 (0.0547) Prec@1 94.000 (91.190) Prec@5 99.000 (99.524) +2022-11-14 13:59:24,802 Epoch: [128][210/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0903 (0.0563) Prec@1 84.000 (90.864) Prec@5 98.000 (99.455) +2022-11-14 13:59:25,276 Epoch: [128][220/500] Time 0.049 (0.037) Data 0.001 (0.003) Loss 0.0436 (0.0558) Prec@1 94.000 (91.000) Prec@5 100.000 (99.478) +2022-11-14 13:59:25,750 Epoch: [128][230/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0402 (0.0551) Prec@1 94.000 (91.125) Prec@5 100.000 (99.500) +2022-11-14 13:59:26,233 Epoch: [128][240/500] Time 0.047 (0.037) Data 0.001 (0.003) Loss 0.0653 (0.0555) Prec@1 88.000 (91.000) Prec@5 99.000 (99.480) +2022-11-14 13:59:26,707 Epoch: [128][250/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0555 (0.0555) Prec@1 91.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 13:59:27,187 Epoch: [128][260/500] Time 0.056 (0.038) Data 0.002 (0.003) Loss 0.0543 (0.0555) Prec@1 92.000 (91.037) Prec@5 100.000 (99.519) +2022-11-14 13:59:27,670 Epoch: [128][270/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0584 (0.0556) Prec@1 90.000 (91.000) Prec@5 100.000 (99.536) +2022-11-14 13:59:28,143 Epoch: [128][280/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0770 (0.0563) Prec@1 85.000 (90.793) Prec@5 100.000 (99.552) +2022-11-14 13:59:28,622 Epoch: [128][290/500] Time 0.048 (0.038) Data 0.002 (0.003) Loss 0.0327 (0.0555) Prec@1 94.000 (90.900) Prec@5 100.000 (99.567) +2022-11-14 13:59:29,090 Epoch: [128][300/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0424 (0.0551) Prec@1 91.000 (90.903) Prec@5 100.000 (99.581) +2022-11-14 13:59:29,553 Epoch: [128][310/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0591 (0.0552) Prec@1 90.000 (90.875) Prec@5 100.000 (99.594) +2022-11-14 13:59:30,028 Epoch: [128][320/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0543 (0.0552) Prec@1 90.000 (90.848) Prec@5 98.000 (99.545) +2022-11-14 13:59:30,414 Epoch: [128][330/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.0697 (0.0556) Prec@1 88.000 (90.765) Prec@5 100.000 (99.559) +2022-11-14 13:59:30,701 Epoch: [128][340/500] Time 0.025 (0.038) Data 0.002 (0.003) Loss 0.0659 (0.0559) Prec@1 89.000 (90.714) Prec@5 100.000 (99.571) +2022-11-14 13:59:30,988 Epoch: [128][350/500] Time 0.027 (0.038) Data 0.001 (0.003) Loss 0.0404 (0.0555) Prec@1 94.000 (90.806) Prec@5 100.000 (99.583) +2022-11-14 13:59:31,275 Epoch: [128][360/500] Time 0.025 (0.037) Data 0.002 (0.003) Loss 0.0651 (0.0558) Prec@1 90.000 (90.784) Prec@5 100.000 (99.595) +2022-11-14 13:59:31,561 Epoch: [128][370/500] Time 0.026 (0.037) Data 0.003 (0.002) Loss 0.0603 (0.0559) Prec@1 91.000 (90.789) Prec@5 99.000 (99.579) +2022-11-14 13:59:31,853 Epoch: [128][380/500] Time 0.021 (0.037) Data 0.002 (0.002) Loss 0.0709 (0.0563) Prec@1 88.000 (90.718) Prec@5 98.000 (99.538) +2022-11-14 13:59:32,135 Epoch: [128][390/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.0804 (0.0569) Prec@1 88.000 (90.650) Prec@5 98.000 (99.500) +2022-11-14 13:59:32,423 Epoch: [128][400/500] Time 0.026 (0.036) Data 0.002 (0.002) Loss 0.0748 (0.0573) Prec@1 88.000 (90.585) Prec@5 100.000 (99.512) +2022-11-14 13:59:32,714 Epoch: [128][410/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0721 (0.0577) Prec@1 88.000 (90.524) Prec@5 100.000 (99.524) +2022-11-14 13:59:32,998 Epoch: [128][420/500] Time 0.023 (0.036) Data 0.002 (0.002) Loss 0.0501 (0.0575) Prec@1 90.000 (90.512) Prec@5 100.000 (99.535) +2022-11-14 13:59:33,292 Epoch: [128][430/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.0599 (0.0575) Prec@1 90.000 (90.500) Prec@5 100.000 (99.545) +2022-11-14 13:59:33,587 Epoch: [128][440/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0467 (0.0573) Prec@1 92.000 (90.533) Prec@5 99.000 (99.533) +2022-11-14 13:59:33,891 Epoch: [128][450/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0452 (0.0570) Prec@1 93.000 (90.587) Prec@5 100.000 (99.543) +2022-11-14 13:59:34,180 Epoch: [128][460/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0665 (0.0572) Prec@1 88.000 (90.532) Prec@5 100.000 (99.553) +2022-11-14 13:59:34,478 Epoch: [128][470/500] Time 0.026 (0.035) Data 0.001 (0.002) Loss 0.0385 (0.0568) Prec@1 94.000 (90.604) Prec@5 100.000 (99.562) +2022-11-14 13:59:34,771 Epoch: [128][480/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0724 (0.0572) Prec@1 87.000 (90.531) Prec@5 99.000 (99.551) +2022-11-14 13:59:35,055 Epoch: [128][490/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0734 (0.0575) Prec@1 85.000 (90.420) Prec@5 100.000 (99.560) +2022-11-14 13:59:35,325 Epoch: [128][499/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0843 (0.0580) Prec@1 84.000 (90.294) Prec@5 99.000 (99.549) +2022-11-14 13:59:35,625 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0650 (0.0650) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 13:59:35,634 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0843 (0.0746) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 13:59:35,642 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0867 (0.0786) Prec@1 87.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 13:59:35,654 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0804) Prec@1 84.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 13:59:35,662 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0797) Prec@1 84.000 (86.000) Prec@5 100.000 (99.600) +2022-11-14 13:59:35,669 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0747) Prec@1 94.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 13:59:35,676 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0765) Prec@1 85.000 (87.000) Prec@5 100.000 (99.714) +2022-11-14 13:59:35,686 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0787) Prec@1 84.000 (86.625) Prec@5 99.000 (99.625) +2022-11-14 13:59:35,696 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0801) Prec@1 84.000 (86.333) Prec@5 98.000 (99.444) +2022-11-14 13:59:35,705 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0791) Prec@1 86.000 (86.300) Prec@5 99.000 (99.400) +2022-11-14 13:59:35,714 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0785) Prec@1 88.000 (86.455) Prec@5 100.000 (99.455) +2022-11-14 13:59:35,725 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0802) Prec@1 85.000 (86.333) Prec@5 99.000 (99.417) +2022-11-14 13:59:35,735 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0788) Prec@1 89.000 (86.538) Prec@5 100.000 (99.462) +2022-11-14 13:59:35,744 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0803) Prec@1 81.000 (86.143) Prec@5 100.000 (99.500) +2022-11-14 13:59:35,753 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0800) Prec@1 89.000 (86.333) Prec@5 99.000 (99.467) +2022-11-14 13:59:35,762 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0807) Prec@1 84.000 (86.188) Prec@5 99.000 (99.438) +2022-11-14 13:59:35,772 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0793) Prec@1 92.000 (86.529) Prec@5 99.000 (99.412) +2022-11-14 13:59:35,780 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0798) Prec@1 88.000 (86.611) Prec@5 99.000 (99.389) +2022-11-14 13:59:35,790 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0800) Prec@1 83.000 (86.421) Prec@5 99.000 (99.368) +2022-11-14 13:59:35,800 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0811) Prec@1 83.000 (86.250) Prec@5 96.000 (99.200) +2022-11-14 13:59:35,809 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0810) Prec@1 86.000 (86.238) Prec@5 100.000 (99.238) +2022-11-14 13:59:35,819 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0809) Prec@1 83.000 (86.091) Prec@5 99.000 (99.227) +2022-11-14 13:59:35,830 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0823) Prec@1 84.000 (86.000) Prec@5 99.000 (99.217) +2022-11-14 13:59:35,842 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0823) Prec@1 86.000 (86.000) Prec@5 100.000 (99.250) +2022-11-14 13:59:35,851 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0836) Prec@1 80.000 (85.760) Prec@5 99.000 (99.240) +2022-11-14 13:59:35,860 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0846) Prec@1 82.000 (85.615) Prec@5 98.000 (99.192) +2022-11-14 13:59:35,871 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0849) Prec@1 87.000 (85.667) Prec@5 99.000 (99.185) +2022-11-14 13:59:35,880 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0839) Prec@1 90.000 (85.821) Prec@5 100.000 (99.214) +2022-11-14 13:59:35,891 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0839) Prec@1 85.000 (85.793) Prec@5 99.000 (99.207) +2022-11-14 13:59:35,901 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0838) Prec@1 86.000 (85.800) Prec@5 100.000 (99.233) +2022-11-14 13:59:35,911 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0835) Prec@1 88.000 (85.871) Prec@5 100.000 (99.258) +2022-11-14 13:59:35,920 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0837) Prec@1 85.000 (85.844) Prec@5 99.000 (99.250) +2022-11-14 13:59:35,930 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0837) Prec@1 87.000 (85.879) Prec@5 99.000 (99.242) +2022-11-14 13:59:35,941 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0841) Prec@1 85.000 (85.853) Prec@5 98.000 (99.206) +2022-11-14 13:59:35,953 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0841) Prec@1 84.000 (85.800) Prec@5 98.000 (99.171) +2022-11-14 13:59:35,964 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0837) Prec@1 88.000 (85.861) Prec@5 100.000 (99.194) +2022-11-14 13:59:35,975 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0838) Prec@1 85.000 (85.838) Prec@5 97.000 (99.135) +2022-11-14 13:59:35,985 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0841) Prec@1 82.000 (85.737) Prec@5 100.000 (99.158) +2022-11-14 13:59:35,996 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0838) Prec@1 88.000 (85.795) Prec@5 99.000 (99.154) +2022-11-14 13:59:36,005 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0837) Prec@1 85.000 (85.775) Prec@5 97.000 (99.100) +2022-11-14 13:59:36,016 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0842) Prec@1 86.000 (85.780) Prec@5 98.000 (99.073) +2022-11-14 13:59:36,026 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0841) Prec@1 85.000 (85.762) Prec@5 99.000 (99.071) +2022-11-14 13:59:36,037 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0835) Prec@1 91.000 (85.884) Prec@5 100.000 (99.093) +2022-11-14 13:59:36,047 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0837) Prec@1 84.000 (85.841) Prec@5 98.000 (99.068) +2022-11-14 13:59:36,057 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0839) Prec@1 86.000 (85.844) Prec@5 99.000 (99.067) +2022-11-14 13:59:36,068 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0840) Prec@1 83.000 (85.783) Prec@5 98.000 (99.043) +2022-11-14 13:59:36,079 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0843) Prec@1 83.000 (85.723) Prec@5 98.000 (99.021) +2022-11-14 13:59:36,090 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0841) Prec@1 87.000 (85.750) Prec@5 100.000 (99.042) +2022-11-14 13:59:36,100 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0836) Prec@1 90.000 (85.837) Prec@5 100.000 (99.061) +2022-11-14 13:59:36,110 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1308 (0.0845) Prec@1 80.000 (85.720) Prec@5 99.000 (99.060) +2022-11-14 13:59:36,121 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0846) Prec@1 85.000 (85.706) Prec@5 99.000 (99.059) +2022-11-14 13:59:36,131 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0846) Prec@1 84.000 (85.673) Prec@5 98.000 (99.038) +2022-11-14 13:59:36,143 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0844) Prec@1 86.000 (85.679) Prec@5 100.000 (99.057) +2022-11-14 13:59:36,154 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0846) Prec@1 83.000 (85.630) Prec@5 97.000 (99.019) +2022-11-14 13:59:36,165 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0849) Prec@1 83.000 (85.582) Prec@5 100.000 (99.036) +2022-11-14 13:59:36,177 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0847) Prec@1 87.000 (85.607) Prec@5 99.000 (99.036) +2022-11-14 13:59:36,188 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0849) Prec@1 85.000 (85.596) Prec@5 99.000 (99.035) +2022-11-14 13:59:36,197 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0847) Prec@1 89.000 (85.655) Prec@5 99.000 (99.034) +2022-11-14 13:59:36,207 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1352 (0.0856) Prec@1 78.000 (85.525) Prec@5 100.000 (99.051) +2022-11-14 13:59:36,218 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.0859) Prec@1 84.000 (85.500) Prec@5 99.000 (99.050) +2022-11-14 13:59:36,228 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0858) Prec@1 85.000 (85.492) Prec@5 100.000 (99.066) +2022-11-14 13:59:36,239 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0857) Prec@1 90.000 (85.565) Prec@5 96.000 (99.016) +2022-11-14 13:59:36,249 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0856) Prec@1 87.000 (85.587) Prec@5 99.000 (99.016) +2022-11-14 13:59:36,262 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0851) Prec@1 92.000 (85.688) Prec@5 100.000 (99.031) +2022-11-14 13:59:36,273 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1084 (0.0854) Prec@1 82.000 (85.631) Prec@5 98.000 (99.015) +2022-11-14 13:59:36,282 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0855) Prec@1 85.000 (85.621) Prec@5 99.000 (99.015) +2022-11-14 13:59:36,292 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0854) Prec@1 85.000 (85.612) Prec@5 100.000 (99.030) +2022-11-14 13:59:36,301 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0853) Prec@1 90.000 (85.676) Prec@5 98.000 (99.015) +2022-11-14 13:59:36,311 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0853) Prec@1 87.000 (85.696) Prec@5 100.000 (99.029) +2022-11-14 13:59:36,321 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0852) Prec@1 86.000 (85.700) Prec@5 98.000 (99.014) +2022-11-14 13:59:36,330 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0856) Prec@1 84.000 (85.676) Prec@5 99.000 (99.014) +2022-11-14 13:59:36,340 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0854) Prec@1 87.000 (85.694) Prec@5 98.000 (99.000) +2022-11-14 13:59:36,351 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0855) Prec@1 86.000 (85.699) Prec@5 99.000 (99.000) +2022-11-14 13:59:36,361 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0851) Prec@1 89.000 (85.743) Prec@5 100.000 (99.014) +2022-11-14 13:59:36,372 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1132 (0.0855) Prec@1 83.000 (85.707) Prec@5 98.000 (99.000) +2022-11-14 13:59:36,383 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0852) Prec@1 88.000 (85.737) Prec@5 99.000 (99.000) +2022-11-14 13:59:36,392 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0851) Prec@1 84.000 (85.714) Prec@5 100.000 (99.013) +2022-11-14 13:59:36,401 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0852) Prec@1 86.000 (85.718) Prec@5 97.000 (98.987) +2022-11-14 13:59:36,411 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0850) Prec@1 88.000 (85.747) Prec@5 100.000 (99.000) +2022-11-14 13:59:36,420 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0851) Prec@1 85.000 (85.737) Prec@5 98.000 (98.987) +2022-11-14 13:59:36,433 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0851) Prec@1 86.000 (85.741) Prec@5 98.000 (98.975) +2022-11-14 13:59:36,446 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0851) Prec@1 84.000 (85.720) Prec@5 98.000 (98.963) +2022-11-14 13:59:36,455 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0852) Prec@1 86.000 (85.723) Prec@5 100.000 (98.976) +2022-11-14 13:59:36,464 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0852) Prec@1 85.000 (85.714) Prec@5 99.000 (98.976) +2022-11-14 13:59:36,475 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0853) Prec@1 83.000 (85.682) Prec@5 99.000 (98.976) +2022-11-14 13:59:36,485 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0853) Prec@1 88.000 (85.709) Prec@5 100.000 (98.988) +2022-11-14 13:59:36,496 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0854) Prec@1 84.000 (85.690) Prec@5 100.000 (99.000) +2022-11-14 13:59:36,506 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0852) Prec@1 91.000 (85.750) Prec@5 99.000 (99.000) +2022-11-14 13:59:36,518 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0851) Prec@1 86.000 (85.753) Prec@5 98.000 (98.989) +2022-11-14 13:59:36,528 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0852) Prec@1 86.000 (85.756) Prec@5 100.000 (99.000) +2022-11-14 13:59:36,539 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0849) Prec@1 87.000 (85.769) Prec@5 100.000 (99.011) +2022-11-14 13:59:36,550 Test: [91/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0845) Prec@1 93.000 (85.848) Prec@5 100.000 (99.022) +2022-11-14 13:59:36,561 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0846) Prec@1 86.000 (85.849) Prec@5 100.000 (99.032) +2022-11-14 13:59:36,571 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0845) Prec@1 88.000 (85.872) Prec@5 98.000 (99.021) +2022-11-14 13:59:36,582 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0843) Prec@1 88.000 (85.895) Prec@5 99.000 (99.021) +2022-11-14 13:59:36,592 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0843) Prec@1 88.000 (85.917) Prec@5 100.000 (99.031) +2022-11-14 13:59:36,602 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0839) Prec@1 94.000 (86.000) Prec@5 99.000 (99.031) +2022-11-14 13:59:36,612 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0840) Prec@1 87.000 (86.010) Prec@5 99.000 (99.031) +2022-11-14 13:59:36,621 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0839) Prec@1 86.000 (86.010) Prec@5 100.000 (99.040) +2022-11-14 13:59:36,630 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0838) Prec@1 86.000 (86.010) Prec@5 99.000 (99.040) +2022-11-14 13:59:36,697 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 13:59:37,009 Epoch: [129][0/500] Time 0.026 (0.026) Data 0.226 (0.226) Loss 0.0548 (0.0548) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 13:59:37,219 Epoch: [129][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0525 (0.0537) Prec@1 93.000 (91.500) Prec@5 99.000 (99.500) +2022-11-14 13:59:37,447 Epoch: [129][20/500] Time 0.024 (0.019) Data 0.002 (0.012) Loss 0.0360 (0.0478) Prec@1 94.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 13:59:37,738 Epoch: [129][30/500] Time 0.033 (0.022) Data 0.003 (0.009) Loss 0.0463 (0.0474) Prec@1 91.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 13:59:38,017 Epoch: [129][40/500] Time 0.025 (0.022) Data 0.002 (0.007) Loss 0.0622 (0.0504) Prec@1 89.000 (91.400) Prec@5 100.000 (99.800) +2022-11-14 13:59:38,295 Epoch: [129][50/500] Time 0.025 (0.023) Data 0.002 (0.006) Loss 0.0643 (0.0527) Prec@1 90.000 (91.167) Prec@5 100.000 (99.833) +2022-11-14 13:59:38,587 Epoch: [129][60/500] Time 0.024 (0.023) Data 0.002 (0.005) Loss 0.0528 (0.0527) Prec@1 87.000 (90.571) Prec@5 100.000 (99.857) +2022-11-14 13:59:39,041 Epoch: [129][70/500] Time 0.044 (0.026) Data 0.002 (0.005) Loss 0.0652 (0.0543) Prec@1 89.000 (90.375) Prec@5 99.000 (99.750) +2022-11-14 13:59:39,536 Epoch: [129][80/500] Time 0.042 (0.028) Data 0.002 (0.005) Loss 0.0479 (0.0535) Prec@1 91.000 (90.444) Prec@5 100.000 (99.778) +2022-11-14 13:59:40,048 Epoch: [129][90/500] Time 0.053 (0.030) Data 0.002 (0.004) Loss 0.0427 (0.0525) Prec@1 94.000 (90.800) Prec@5 100.000 (99.800) +2022-11-14 13:59:40,523 Epoch: [129][100/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0645 (0.0536) Prec@1 88.000 (90.545) Prec@5 97.000 (99.545) +2022-11-14 13:59:41,000 Epoch: [129][110/500] Time 0.043 (0.032) Data 0.002 (0.004) Loss 0.0153 (0.0504) Prec@1 96.000 (91.000) Prec@5 100.000 (99.583) +2022-11-14 13:59:41,468 Epoch: [129][120/500] Time 0.046 (0.033) Data 0.001 (0.004) Loss 0.0428 (0.0498) Prec@1 94.000 (91.231) Prec@5 99.000 (99.538) +2022-11-14 13:59:41,938 Epoch: [129][130/500] Time 0.042 (0.034) Data 0.002 (0.004) Loss 0.0542 (0.0501) Prec@1 91.000 (91.214) Prec@5 100.000 (99.571) +2022-11-14 13:59:42,435 Epoch: [129][140/500] Time 0.057 (0.034) Data 0.001 (0.003) Loss 0.0571 (0.0506) Prec@1 91.000 (91.200) Prec@5 98.000 (99.467) +2022-11-14 13:59:42,944 Epoch: [129][150/500] Time 0.054 (0.035) Data 0.002 (0.003) Loss 0.0290 (0.0492) Prec@1 95.000 (91.438) Prec@5 100.000 (99.500) +2022-11-14 13:59:43,453 Epoch: [129][160/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0775 (0.0509) Prec@1 88.000 (91.235) Prec@5 99.000 (99.471) +2022-11-14 13:59:43,936 Epoch: [129][170/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0826 (0.0526) Prec@1 87.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 13:59:44,415 Epoch: [129][180/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0556 (0.0528) Prec@1 90.000 (90.947) Prec@5 100.000 (99.526) +2022-11-14 13:59:44,922 Epoch: [129][190/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0420 (0.0523) Prec@1 93.000 (91.050) Prec@5 100.000 (99.550) +2022-11-14 13:59:45,415 Epoch: [129][200/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0350 (0.0514) Prec@1 95.000 (91.238) Prec@5 100.000 (99.571) +2022-11-14 13:59:45,881 Epoch: [129][210/500] Time 0.051 (0.037) Data 0.002 (0.003) Loss 0.0508 (0.0514) Prec@1 91.000 (91.227) Prec@5 99.000 (99.545) +2022-11-14 13:59:46,367 Epoch: [129][220/500] Time 0.054 (0.038) Data 0.002 (0.003) Loss 0.0695 (0.0522) Prec@1 89.000 (91.130) Prec@5 99.000 (99.522) +2022-11-14 13:59:46,850 Epoch: [129][230/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0571 (0.0524) Prec@1 90.000 (91.083) Prec@5 99.000 (99.500) +2022-11-14 13:59:47,321 Epoch: [129][240/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0561 (0.0526) Prec@1 92.000 (91.120) Prec@5 100.000 (99.520) +2022-11-14 13:59:47,792 Epoch: [129][250/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0661 (0.0531) Prec@1 88.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 13:59:48,288 Epoch: [129][260/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0476 (0.0529) Prec@1 93.000 (91.074) Prec@5 100.000 (99.519) +2022-11-14 13:59:48,766 Epoch: [129][270/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0579 (0.0530) Prec@1 91.000 (91.071) Prec@5 100.000 (99.536) +2022-11-14 13:59:49,241 Epoch: [129][280/500] Time 0.053 (0.039) Data 0.002 (0.003) Loss 0.0430 (0.0527) Prec@1 93.000 (91.138) Prec@5 100.000 (99.552) +2022-11-14 13:59:49,712 Epoch: [129][290/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0642 (0.0531) Prec@1 90.000 (91.100) Prec@5 99.000 (99.533) +2022-11-14 13:59:50,174 Epoch: [129][300/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0697 (0.0536) Prec@1 89.000 (91.032) Prec@5 99.000 (99.516) +2022-11-14 13:59:50,675 Epoch: [129][310/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0634 (0.0539) Prec@1 88.000 (90.938) Prec@5 100.000 (99.531) +2022-11-14 13:59:51,145 Epoch: [129][320/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0589 (0.0541) Prec@1 90.000 (90.909) Prec@5 100.000 (99.545) +2022-11-14 13:59:51,627 Epoch: [129][330/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0631 (0.0543) Prec@1 89.000 (90.853) Prec@5 100.000 (99.559) +2022-11-14 13:59:51,967 Epoch: [129][340/500] Time 0.026 (0.039) Data 0.002 (0.003) Loss 0.0636 (0.0546) Prec@1 88.000 (90.771) Prec@5 99.000 (99.543) +2022-11-14 13:59:52,261 Epoch: [129][350/500] Time 0.023 (0.039) Data 0.002 (0.003) Loss 0.0599 (0.0548) Prec@1 90.000 (90.750) Prec@5 100.000 (99.556) +2022-11-14 13:59:52,567 Epoch: [129][360/500] Time 0.024 (0.038) Data 0.002 (0.003) Loss 0.0444 (0.0545) Prec@1 92.000 (90.784) Prec@5 100.000 (99.568) +2022-11-14 13:59:52,866 Epoch: [129][370/500] Time 0.022 (0.038) Data 0.002 (0.002) Loss 0.0603 (0.0546) Prec@1 89.000 (90.737) Prec@5 99.000 (99.553) +2022-11-14 13:59:53,163 Epoch: [129][380/500] Time 0.023 (0.038) Data 0.002 (0.002) Loss 0.0483 (0.0545) Prec@1 91.000 (90.744) Prec@5 100.000 (99.564) +2022-11-14 13:59:53,475 Epoch: [129][390/500] Time 0.027 (0.037) Data 0.002 (0.002) Loss 0.0730 (0.0549) Prec@1 87.000 (90.650) Prec@5 99.000 (99.550) +2022-11-14 13:59:53,777 Epoch: [129][400/500] Time 0.025 (0.037) Data 0.002 (0.002) Loss 0.0761 (0.0554) Prec@1 87.000 (90.561) Prec@5 100.000 (99.561) +2022-11-14 13:59:54,070 Epoch: [129][410/500] Time 0.028 (0.037) Data 0.001 (0.002) Loss 0.0616 (0.0556) Prec@1 90.000 (90.548) Prec@5 98.000 (99.524) +2022-11-14 13:59:54,378 Epoch: [129][420/500] Time 0.024 (0.037) Data 0.002 (0.002) Loss 0.0322 (0.0550) Prec@1 96.000 (90.674) Prec@5 100.000 (99.535) +2022-11-14 13:59:54,684 Epoch: [129][430/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0631 (0.0552) Prec@1 89.000 (90.636) Prec@5 100.000 (99.545) +2022-11-14 13:59:54,984 Epoch: [129][440/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0715 (0.0556) Prec@1 87.000 (90.556) Prec@5 99.000 (99.533) +2022-11-14 13:59:55,280 Epoch: [129][450/500] Time 0.026 (0.036) Data 0.002 (0.002) Loss 0.0463 (0.0554) Prec@1 93.000 (90.609) Prec@5 99.000 (99.522) +2022-11-14 13:59:55,578 Epoch: [129][460/500] Time 0.024 (0.036) Data 0.002 (0.002) Loss 0.0772 (0.0559) Prec@1 88.000 (90.553) Prec@5 99.000 (99.511) +2022-11-14 13:59:55,882 Epoch: [129][470/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0572 (0.0559) Prec@1 90.000 (90.542) Prec@5 100.000 (99.521) +2022-11-14 13:59:56,187 Epoch: [129][480/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0361 (0.0555) Prec@1 92.000 (90.571) Prec@5 100.000 (99.531) +2022-11-14 13:59:56,485 Epoch: [129][490/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0562 (0.0555) Prec@1 92.000 (90.600) Prec@5 100.000 (99.540) +2022-11-14 13:59:56,772 Epoch: [129][499/500] Time 0.035 (0.035) Data 0.002 (0.002) Loss 0.0564 (0.0555) Prec@1 90.000 (90.588) Prec@5 99.000 (99.529) +2022-11-14 13:59:57,049 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0546 (0.0546) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 13:59:57,057 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0593) Prec@1 88.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 13:59:57,066 Test: [2/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0703) Prec@1 83.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 13:59:57,078 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0700) Prec@1 89.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 13:59:57,086 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0695) Prec@1 89.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 13:59:57,095 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0670) Prec@1 92.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 13:59:57,103 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0652) Prec@1 92.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 13:59:57,113 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0693) Prec@1 83.000 (88.500) Prec@5 99.000 (99.625) +2022-11-14 13:59:57,121 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0732) Prec@1 85.000 (88.111) Prec@5 100.000 (99.667) +2022-11-14 13:59:57,129 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0737) Prec@1 84.000 (87.700) Prec@5 99.000 (99.600) +2022-11-14 13:59:57,138 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0715) Prec@1 91.000 (88.000) Prec@5 100.000 (99.636) +2022-11-14 13:59:57,146 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0726) Prec@1 88.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 13:59:57,154 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0719) Prec@1 89.000 (88.077) Prec@5 99.000 (99.615) +2022-11-14 13:59:57,162 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0726) Prec@1 89.000 (88.143) Prec@5 100.000 (99.643) +2022-11-14 13:59:57,171 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0736) Prec@1 84.000 (87.867) Prec@5 100.000 (99.667) +2022-11-14 13:59:57,181 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0741) Prec@1 84.000 (87.625) Prec@5 100.000 (99.688) +2022-11-14 13:59:57,190 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0732) Prec@1 91.000 (87.824) Prec@5 99.000 (99.647) +2022-11-14 13:59:57,199 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0745) Prec@1 85.000 (87.667) Prec@5 99.000 (99.611) +2022-11-14 13:59:57,208 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0754) Prec@1 83.000 (87.421) Prec@5 100.000 (99.632) +2022-11-14 13:59:57,218 Test: [19/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0752) Prec@1 87.000 (87.400) Prec@5 98.000 (99.550) +2022-11-14 13:59:57,227 Test: [20/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0763) Prec@1 81.000 (87.095) Prec@5 99.000 (99.524) +2022-11-14 13:59:57,236 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0767) Prec@1 87.000 (87.091) Prec@5 99.000 (99.500) +2022-11-14 13:59:57,244 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0777) Prec@1 84.000 (86.957) Prec@5 99.000 (99.478) +2022-11-14 13:59:57,252 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0775) Prec@1 88.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 13:59:57,261 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0783) Prec@1 84.000 (86.880) Prec@5 100.000 (99.520) +2022-11-14 13:59:57,271 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0793) Prec@1 83.000 (86.731) Prec@5 96.000 (99.385) +2022-11-14 13:59:57,280 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0785) Prec@1 88.000 (86.778) Prec@5 100.000 (99.407) +2022-11-14 13:59:57,289 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0781) Prec@1 90.000 (86.893) Prec@5 100.000 (99.429) +2022-11-14 13:59:57,298 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0783) Prec@1 86.000 (86.862) Prec@5 99.000 (99.414) +2022-11-14 13:59:57,308 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0784) Prec@1 84.000 (86.767) Prec@5 99.000 (99.400) +2022-11-14 13:59:57,317 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0784) Prec@1 85.000 (86.710) Prec@5 99.000 (99.387) +2022-11-14 13:59:57,326 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0778) Prec@1 89.000 (86.781) Prec@5 100.000 (99.406) +2022-11-14 13:59:57,335 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0778) Prec@1 87.000 (86.788) Prec@5 100.000 (99.424) +2022-11-14 13:59:57,344 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0782) Prec@1 86.000 (86.765) Prec@5 99.000 (99.412) +2022-11-14 13:59:57,352 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0787) Prec@1 81.000 (86.600) Prec@5 99.000 (99.400) +2022-11-14 13:59:57,362 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0781) Prec@1 90.000 (86.694) Prec@5 100.000 (99.417) +2022-11-14 13:59:57,371 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0783) Prec@1 83.000 (86.595) Prec@5 99.000 (99.405) +2022-11-14 13:59:57,379 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1093 (0.0791) Prec@1 80.000 (86.421) Prec@5 100.000 (99.421) +2022-11-14 13:59:57,388 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0788) Prec@1 89.000 (86.487) Prec@5 100.000 (99.436) +2022-11-14 13:59:57,398 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0786) Prec@1 87.000 (86.500) Prec@5 99.000 (99.425) +2022-11-14 13:59:57,407 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.0794) Prec@1 81.000 (86.366) Prec@5 99.000 (99.415) +2022-11-14 13:59:57,416 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0794) Prec@1 85.000 (86.333) Prec@5 98.000 (99.381) +2022-11-14 13:59:57,426 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0786) Prec@1 93.000 (86.488) Prec@5 100.000 (99.395) +2022-11-14 13:59:57,434 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0785) Prec@1 88.000 (86.523) Prec@5 99.000 (99.386) +2022-11-14 13:59:57,444 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0783) Prec@1 90.000 (86.600) Prec@5 100.000 (99.400) +2022-11-14 13:59:57,453 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1177 (0.0791) Prec@1 78.000 (86.413) Prec@5 99.000 (99.391) +2022-11-14 13:59:57,462 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0790) Prec@1 87.000 (86.426) Prec@5 100.000 (99.404) +2022-11-14 13:59:57,472 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0793) Prec@1 86.000 (86.417) Prec@5 97.000 (99.354) +2022-11-14 13:59:57,481 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0788) Prec@1 91.000 (86.510) Prec@5 99.000 (99.347) +2022-11-14 13:59:57,490 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0794) Prec@1 80.000 (86.380) Prec@5 97.000 (99.300) +2022-11-14 13:59:57,499 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0790) Prec@1 89.000 (86.431) Prec@5 98.000 (99.275) +2022-11-14 13:59:57,509 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0789) Prec@1 88.000 (86.462) Prec@5 99.000 (99.269) +2022-11-14 13:59:57,518 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0789) Prec@1 86.000 (86.453) Prec@5 99.000 (99.264) +2022-11-14 13:59:57,527 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0790) Prec@1 86.000 (86.444) Prec@5 98.000 (99.241) +2022-11-14 13:59:57,536 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0789) Prec@1 86.000 (86.436) Prec@5 100.000 (99.255) +2022-11-14 13:59:57,545 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0788) Prec@1 88.000 (86.464) Prec@5 100.000 (99.268) +2022-11-14 13:59:57,552 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0788) Prec@1 86.000 (86.456) Prec@5 100.000 (99.281) +2022-11-14 13:59:57,562 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0784) Prec@1 91.000 (86.534) Prec@5 98.000 (99.259) +2022-11-14 13:59:57,571 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1049 (0.0789) Prec@1 83.000 (86.475) Prec@5 100.000 (99.271) +2022-11-14 13:59:57,580 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0791) Prec@1 84.000 (86.433) Prec@5 100.000 (99.283) +2022-11-14 13:59:57,589 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0791) Prec@1 88.000 (86.459) Prec@5 100.000 (99.295) +2022-11-14 13:59:57,599 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0788) Prec@1 91.000 (86.532) Prec@5 100.000 (99.306) +2022-11-14 13:59:57,608 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0785) Prec@1 90.000 (86.587) Prec@5 100.000 (99.317) +2022-11-14 13:59:57,617 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0780) Prec@1 93.000 (86.688) Prec@5 100.000 (99.328) +2022-11-14 13:59:57,627 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0781) Prec@1 87.000 (86.692) Prec@5 99.000 (99.323) +2022-11-14 13:59:57,636 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0782) Prec@1 84.000 (86.652) Prec@5 98.000 (99.303) +2022-11-14 13:59:57,647 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0778) Prec@1 89.000 (86.687) Prec@5 100.000 (99.313) +2022-11-14 13:59:57,657 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0776) Prec@1 89.000 (86.721) Prec@5 97.000 (99.279) +2022-11-14 13:59:57,668 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0774) Prec@1 87.000 (86.725) Prec@5 99.000 (99.275) +2022-11-14 13:59:57,678 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0773) Prec@1 89.000 (86.757) Prec@5 99.000 (99.271) +2022-11-14 13:59:57,691 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0775) Prec@1 85.000 (86.732) Prec@5 99.000 (99.268) +2022-11-14 13:59:57,702 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0773) Prec@1 90.000 (86.778) Prec@5 99.000 (99.264) +2022-11-14 13:59:57,713 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0769) Prec@1 91.000 (86.836) Prec@5 99.000 (99.260) +2022-11-14 13:59:57,726 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0767) Prec@1 91.000 (86.892) Prec@5 100.000 (99.270) +2022-11-14 13:59:57,739 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0768) Prec@1 87.000 (86.893) Prec@5 98.000 (99.253) +2022-11-14 13:59:57,751 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0766) Prec@1 90.000 (86.934) Prec@5 100.000 (99.263) +2022-11-14 13:59:57,764 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0764) Prec@1 90.000 (86.974) Prec@5 99.000 (99.260) +2022-11-14 13:59:57,776 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0765) Prec@1 85.000 (86.949) Prec@5 98.000 (99.244) +2022-11-14 13:59:57,789 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0765) Prec@1 88.000 (86.962) Prec@5 99.000 (99.241) +2022-11-14 13:59:57,802 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0763) Prec@1 90.000 (87.000) Prec@5 100.000 (99.250) +2022-11-14 13:59:57,815 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0763) Prec@1 86.000 (86.988) Prec@5 99.000 (99.247) +2022-11-14 13:59:57,829 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0763) Prec@1 86.000 (86.976) Prec@5 99.000 (99.244) +2022-11-14 13:59:57,842 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0763) Prec@1 86.000 (86.964) Prec@5 100.000 (99.253) +2022-11-14 13:59:57,855 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0762) Prec@1 88.000 (86.976) Prec@5 100.000 (99.262) +2022-11-14 13:59:57,866 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0762) Prec@1 88.000 (86.988) Prec@5 99.000 (99.259) +2022-11-14 13:59:57,879 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0765) Prec@1 83.000 (86.942) Prec@5 98.000 (99.244) +2022-11-14 13:59:57,892 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0766) Prec@1 85.000 (86.920) Prec@5 99.000 (99.241) +2022-11-14 13:59:57,906 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0766) Prec@1 89.000 (86.943) Prec@5 99.000 (99.239) +2022-11-14 13:59:57,918 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0765) Prec@1 88.000 (86.955) Prec@5 100.000 (99.247) +2022-11-14 13:59:57,930 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0764) Prec@1 89.000 (86.978) Prec@5 99.000 (99.244) +2022-11-14 13:59:57,944 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0762) Prec@1 91.000 (87.022) Prec@5 99.000 (99.242) +2022-11-14 13:59:57,957 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0760) Prec@1 90.000 (87.054) Prec@5 99.000 (99.239) +2022-11-14 13:59:57,971 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 85.000 (87.032) Prec@5 99.000 (99.237) +2022-11-14 13:59:57,984 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0761) Prec@1 88.000 (87.043) Prec@5 99.000 (99.234) +2022-11-14 13:59:57,997 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0761) Prec@1 86.000 (87.032) Prec@5 99.000 (99.232) +2022-11-14 13:59:58,010 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0760) Prec@1 88.000 (87.042) Prec@5 98.000 (99.219) +2022-11-14 13:59:58,023 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0759) Prec@1 90.000 (87.072) Prec@5 99.000 (99.216) +2022-11-14 13:59:58,036 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0761) Prec@1 85.000 (87.051) Prec@5 100.000 (99.224) +2022-11-14 13:59:58,047 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0763) Prec@1 85.000 (87.030) Prec@5 98.000 (99.212) +2022-11-14 13:59:58,061 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0763) Prec@1 84.000 (87.000) Prec@5 100.000 (99.220) +2022-11-14 13:59:58,120 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 13:59:58,431 Epoch: [130][0/500] Time 0.034 (0.034) Data 0.217 (0.217) Loss 0.0723 (0.0723) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 13:59:58,660 Epoch: [130][10/500] Time 0.020 (0.021) Data 0.002 (0.021) Loss 0.0577 (0.0650) Prec@1 89.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 13:59:58,913 Epoch: [130][20/500] Time 0.024 (0.022) Data 0.002 (0.012) Loss 0.0549 (0.0617) Prec@1 94.000 (90.667) Prec@5 100.000 (99.333) +2022-11-14 13:59:59,160 Epoch: [130][30/500] Time 0.022 (0.022) Data 0.002 (0.009) Loss 0.0699 (0.0637) Prec@1 87.000 (89.750) Prec@5 99.000 (99.250) +2022-11-14 13:59:59,407 Epoch: [130][40/500] Time 0.022 (0.022) Data 0.002 (0.007) Loss 0.0467 (0.0603) Prec@1 92.000 (90.200) Prec@5 98.000 (99.000) +2022-11-14 13:59:59,892 Epoch: [130][50/500] Time 0.071 (0.026) Data 0.002 (0.006) Loss 0.0351 (0.0561) Prec@1 95.000 (91.000) Prec@5 100.000 (99.167) +2022-11-14 14:00:00,372 Epoch: [130][60/500] Time 0.042 (0.029) Data 0.002 (0.005) Loss 0.0161 (0.0504) Prec@1 98.000 (92.000) Prec@5 100.000 (99.286) +2022-11-14 14:00:00,846 Epoch: [130][70/500] Time 0.043 (0.031) Data 0.002 (0.005) Loss 0.0508 (0.0504) Prec@1 91.000 (91.875) Prec@5 98.000 (99.125) +2022-11-14 14:00:01,320 Epoch: [130][80/500] Time 0.044 (0.032) Data 0.002 (0.005) Loss 0.0700 (0.0526) Prec@1 89.000 (91.556) Prec@5 99.000 (99.111) +2022-11-14 14:00:01,782 Epoch: [130][90/500] Time 0.043 (0.033) Data 0.001 (0.004) Loss 0.0400 (0.0513) Prec@1 93.000 (91.700) Prec@5 100.000 (99.200) +2022-11-14 14:00:02,252 Epoch: [130][100/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0734 (0.0534) Prec@1 88.000 (91.364) Prec@5 100.000 (99.273) +2022-11-14 14:00:02,723 Epoch: [130][110/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0591 (0.0538) Prec@1 90.000 (91.250) Prec@5 99.000 (99.250) +2022-11-14 14:00:03,195 Epoch: [130][120/500] Time 0.044 (0.035) Data 0.001 (0.004) Loss 0.0532 (0.0538) Prec@1 91.000 (91.231) Prec@5 100.000 (99.308) +2022-11-14 14:00:03,668 Epoch: [130][130/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.0498 (0.0535) Prec@1 92.000 (91.286) Prec@5 99.000 (99.286) +2022-11-14 14:00:04,131 Epoch: [130][140/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0431 (0.0528) Prec@1 92.000 (91.333) Prec@5 99.000 (99.267) +2022-11-14 14:00:04,606 Epoch: [130][150/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0807 (0.0545) Prec@1 86.000 (91.000) Prec@5 100.000 (99.312) +2022-11-14 14:00:05,077 Epoch: [130][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0491 (0.0542) Prec@1 92.000 (91.059) Prec@5 100.000 (99.353) +2022-11-14 14:00:05,549 Epoch: [130][170/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0639 (0.0548) Prec@1 88.000 (90.889) Prec@5 99.000 (99.333) +2022-11-14 14:00:06,019 Epoch: [130][180/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0306 (0.0535) Prec@1 98.000 (91.263) Prec@5 100.000 (99.368) +2022-11-14 14:00:06,484 Epoch: [130][190/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0512 (0.0534) Prec@1 90.000 (91.200) Prec@5 100.000 (99.400) +2022-11-14 14:00:06,956 Epoch: [130][200/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0259 (0.0521) Prec@1 96.000 (91.429) Prec@5 100.000 (99.429) +2022-11-14 14:00:07,438 Epoch: [130][210/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0816 (0.0534) Prec@1 85.000 (91.136) Prec@5 100.000 (99.455) +2022-11-14 14:00:07,909 Epoch: [130][220/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0495 (0.0532) Prec@1 90.000 (91.087) Prec@5 100.000 (99.478) +2022-11-14 14:00:08,373 Epoch: [130][230/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0573 (0.0534) Prec@1 90.000 (91.042) Prec@5 100.000 (99.500) +2022-11-14 14:00:08,912 Epoch: [130][240/500] Time 0.061 (0.039) Data 0.002 (0.003) Loss 0.0455 (0.0531) Prec@1 92.000 (91.080) Prec@5 100.000 (99.520) +2022-11-14 14:00:09,286 Epoch: [130][250/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0442 (0.0528) Prec@1 93.000 (91.154) Prec@5 99.000 (99.500) +2022-11-14 14:00:09,682 Epoch: [130][260/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0735 (0.0535) Prec@1 88.000 (91.037) Prec@5 100.000 (99.519) +2022-11-14 14:00:10,024 Epoch: [130][270/500] Time 0.034 (0.038) Data 0.003 (0.003) Loss 0.0592 (0.0537) Prec@1 90.000 (91.000) Prec@5 100.000 (99.536) +2022-11-14 14:00:10,400 Epoch: [130][280/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0443 (0.0534) Prec@1 91.000 (91.000) Prec@5 100.000 (99.552) +2022-11-14 14:00:10,753 Epoch: [130][290/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0765 (0.0542) Prec@1 88.000 (90.900) Prec@5 100.000 (99.567) +2022-11-14 14:00:11,109 Epoch: [130][300/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0541 (0.0542) Prec@1 88.000 (90.806) Prec@5 100.000 (99.581) +2022-11-14 14:00:11,469 Epoch: [130][310/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0977 (0.0555) Prec@1 81.000 (90.500) Prec@5 98.000 (99.531) +2022-11-14 14:00:11,828 Epoch: [130][320/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.0499 (0.0554) Prec@1 92.000 (90.545) Prec@5 100.000 (99.545) +2022-11-14 14:00:12,183 Epoch: [130][330/500] Time 0.033 (0.037) Data 0.002 (0.003) Loss 0.0493 (0.0552) Prec@1 94.000 (90.647) Prec@5 99.000 (99.529) +2022-11-14 14:00:12,539 Epoch: [130][340/500] Time 0.033 (0.037) Data 0.001 (0.002) Loss 0.0352 (0.0546) Prec@1 94.000 (90.743) Prec@5 100.000 (99.543) +2022-11-14 14:00:12,893 Epoch: [130][350/500] Time 0.033 (0.037) Data 0.002 (0.002) Loss 0.0484 (0.0544) Prec@1 93.000 (90.806) Prec@5 100.000 (99.556) +2022-11-14 14:00:13,249 Epoch: [130][360/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0774 (0.0551) Prec@1 88.000 (90.730) Prec@5 100.000 (99.568) +2022-11-14 14:00:13,609 Epoch: [130][370/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0561 (0.0551) Prec@1 92.000 (90.763) Prec@5 99.000 (99.553) +2022-11-14 14:00:13,971 Epoch: [130][380/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0777 (0.0557) Prec@1 88.000 (90.692) Prec@5 99.000 (99.538) +2022-11-14 14:00:14,343 Epoch: [130][390/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0534 (0.0556) Prec@1 91.000 (90.700) Prec@5 100.000 (99.550) +2022-11-14 14:00:14,773 Epoch: [130][400/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0861 (0.0564) Prec@1 87.000 (90.610) Prec@5 99.000 (99.537) +2022-11-14 14:00:15,161 Epoch: [130][410/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0359 (0.0559) Prec@1 93.000 (90.667) Prec@5 100.000 (99.548) +2022-11-14 14:00:15,516 Epoch: [130][420/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.0568 (0.0559) Prec@1 92.000 (90.698) Prec@5 100.000 (99.558) +2022-11-14 14:00:15,885 Epoch: [130][430/500] Time 0.036 (0.036) Data 0.001 (0.002) Loss 0.0658 (0.0561) Prec@1 88.000 (90.636) Prec@5 99.000 (99.545) +2022-11-14 14:00:16,246 Epoch: [130][440/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0489 (0.0560) Prec@1 91.000 (90.644) Prec@5 100.000 (99.556) +2022-11-14 14:00:16,605 Epoch: [130][450/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0458 (0.0557) Prec@1 95.000 (90.739) Prec@5 100.000 (99.565) +2022-11-14 14:00:16,969 Epoch: [130][460/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0521 (0.0557) Prec@1 92.000 (90.766) Prec@5 98.000 (99.532) +2022-11-14 14:00:17,329 Epoch: [130][470/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0284 (0.0551) Prec@1 97.000 (90.896) Prec@5 100.000 (99.542) +2022-11-14 14:00:17,710 Epoch: [130][480/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0764 (0.0555) Prec@1 87.000 (90.816) Prec@5 99.000 (99.531) +2022-11-14 14:00:18,066 Epoch: [130][490/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0572 (0.0556) Prec@1 91.000 (90.820) Prec@5 100.000 (99.540) +2022-11-14 14:00:18,418 Epoch: [130][499/500] Time 0.031 (0.036) Data 0.002 (0.002) Loss 0.0430 (0.0553) Prec@1 91.000 (90.824) Prec@5 100.000 (99.549) +2022-11-14 14:00:18,701 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0673 (0.0673) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:00:18,711 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0632 (0.0652) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:00:18,721 Test: [2/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0899 (0.0734) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:00:18,733 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0654 (0.0714) Prec@1 89.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 14:00:18,743 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0815 (0.0734) Prec@1 87.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 14:00:18,754 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0684) Prec@1 92.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 14:00:18,764 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0843 (0.0707) Prec@1 85.000 (88.143) Prec@5 100.000 (99.857) +2022-11-14 14:00:18,780 Test: [7/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1062 (0.0751) Prec@1 83.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 14:00:18,792 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0774) Prec@1 83.000 (87.000) Prec@5 99.000 (99.667) +2022-11-14 14:00:18,805 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0510 (0.0748) Prec@1 90.000 (87.300) Prec@5 99.000 (99.600) +2022-11-14 14:00:18,818 Test: [10/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0646 (0.0739) Prec@1 89.000 (87.455) Prec@5 100.000 (99.636) +2022-11-14 14:00:18,828 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0739) Prec@1 89.000 (87.583) Prec@5 99.000 (99.583) +2022-11-14 14:00:18,838 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0591 (0.0728) Prec@1 90.000 (87.769) Prec@5 100.000 (99.615) +2022-11-14 14:00:18,851 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0727) Prec@1 89.000 (87.857) Prec@5 99.000 (99.571) +2022-11-14 14:00:18,862 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0730) Prec@1 88.000 (87.867) Prec@5 99.000 (99.533) +2022-11-14 14:00:18,872 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0734) Prec@1 87.000 (87.812) Prec@5 100.000 (99.562) +2022-11-14 14:00:18,882 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0728) Prec@1 90.000 (87.941) Prec@5 98.000 (99.471) +2022-11-14 14:00:18,891 Test: [17/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1096 (0.0749) Prec@1 82.000 (87.611) Prec@5 100.000 (99.500) +2022-11-14 14:00:18,900 Test: [18/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0800 (0.0751) Prec@1 86.000 (87.526) Prec@5 99.000 (99.474) +2022-11-14 14:00:18,910 Test: [19/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1030 (0.0765) Prec@1 82.000 (87.250) Prec@5 98.000 (99.400) +2022-11-14 14:00:18,918 Test: [20/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0772) Prec@1 86.000 (87.190) Prec@5 99.000 (99.381) +2022-11-14 14:00:18,927 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0773) Prec@1 87.000 (87.182) Prec@5 100.000 (99.409) +2022-11-14 14:00:18,937 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.0791) Prec@1 82.000 (86.957) Prec@5 99.000 (99.391) +2022-11-14 14:00:18,946 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0790) Prec@1 85.000 (86.875) Prec@5 100.000 (99.417) +2022-11-14 14:00:18,955 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0792) Prec@1 86.000 (86.840) Prec@5 100.000 (99.440) +2022-11-14 14:00:18,964 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0794) Prec@1 86.000 (86.808) Prec@5 99.000 (99.423) +2022-11-14 14:00:18,974 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0786) Prec@1 90.000 (86.926) Prec@5 100.000 (99.444) +2022-11-14 14:00:18,982 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0782) Prec@1 89.000 (87.000) Prec@5 100.000 (99.464) +2022-11-14 14:00:18,991 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0777) Prec@1 89.000 (87.069) Prec@5 100.000 (99.483) +2022-11-14 14:00:19,001 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0772) Prec@1 89.000 (87.133) Prec@5 99.000 (99.467) +2022-11-14 14:00:19,009 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0771) Prec@1 87.000 (87.129) Prec@5 98.000 (99.419) +2022-11-14 14:00:19,017 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0775) Prec@1 85.000 (87.062) Prec@5 99.000 (99.406) +2022-11-14 14:00:19,027 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0773) Prec@1 86.000 (87.030) Prec@5 98.000 (99.364) +2022-11-14 14:00:19,036 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0779) Prec@1 83.000 (86.912) Prec@5 99.000 (99.353) +2022-11-14 14:00:19,045 Test: [34/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0780) Prec@1 85.000 (86.857) Prec@5 100.000 (99.371) +2022-11-14 14:00:19,053 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0776) Prec@1 89.000 (86.917) Prec@5 100.000 (99.389) +2022-11-14 14:00:19,063 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0773) Prec@1 89.000 (86.973) Prec@5 99.000 (99.378) +2022-11-14 14:00:19,071 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0780) Prec@1 81.000 (86.816) Prec@5 100.000 (99.395) +2022-11-14 14:00:19,080 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0774) Prec@1 94.000 (87.000) Prec@5 100.000 (99.410) +2022-11-14 14:00:19,088 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0767) Prec@1 91.000 (87.100) Prec@5 100.000 (99.425) +2022-11-14 14:00:19,097 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0770) Prec@1 86.000 (87.073) Prec@5 99.000 (99.415) +2022-11-14 14:00:19,105 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0767) Prec@1 91.000 (87.167) Prec@5 100.000 (99.429) +2022-11-14 14:00:19,114 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0760) Prec@1 92.000 (87.279) Prec@5 99.000 (99.419) +2022-11-14 14:00:19,123 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0758) Prec@1 88.000 (87.295) Prec@5 100.000 (99.432) +2022-11-14 14:00:19,132 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0755) Prec@1 89.000 (87.333) Prec@5 98.000 (99.400) +2022-11-14 14:00:19,140 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0762) Prec@1 80.000 (87.174) Prec@5 100.000 (99.413) +2022-11-14 14:00:19,149 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0758) Prec@1 89.000 (87.213) Prec@5 100.000 (99.426) +2022-11-14 14:00:19,158 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0761) Prec@1 85.000 (87.167) Prec@5 100.000 (99.438) +2022-11-14 14:00:19,168 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0756) Prec@1 93.000 (87.286) Prec@5 100.000 (99.449) +2022-11-14 14:00:19,177 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0762) Prec@1 83.000 (87.200) Prec@5 99.000 (99.440) +2022-11-14 14:00:19,185 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0763) Prec@1 86.000 (87.176) Prec@5 100.000 (99.451) +2022-11-14 14:00:19,195 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0760) Prec@1 90.000 (87.231) Prec@5 99.000 (99.442) +2022-11-14 14:00:19,203 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0756) Prec@1 89.000 (87.264) Prec@5 99.000 (99.434) +2022-11-14 14:00:19,213 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0756) Prec@1 87.000 (87.259) Prec@5 100.000 (99.444) +2022-11-14 14:00:19,222 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0760) Prec@1 85.000 (87.218) Prec@5 98.000 (99.418) +2022-11-14 14:00:19,231 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0762) Prec@1 86.000 (87.196) Prec@5 100.000 (99.429) +2022-11-14 14:00:19,240 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0764) Prec@1 87.000 (87.193) Prec@5 100.000 (99.439) +2022-11-14 14:00:19,249 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0764) Prec@1 89.000 (87.224) Prec@5 99.000 (99.431) +2022-11-14 14:00:19,259 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0771) Prec@1 77.000 (87.051) Prec@5 100.000 (99.441) +2022-11-14 14:00:19,267 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0773) Prec@1 83.000 (86.983) Prec@5 100.000 (99.450) +2022-11-14 14:00:19,277 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0770) Prec@1 91.000 (87.049) Prec@5 100.000 (99.459) +2022-11-14 14:00:19,286 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0769) Prec@1 88.000 (87.065) Prec@5 100.000 (99.468) +2022-11-14 14:00:19,294 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0766) Prec@1 89.000 (87.095) Prec@5 100.000 (99.476) +2022-11-14 14:00:19,302 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0764) Prec@1 92.000 (87.172) Prec@5 100.000 (99.484) +2022-11-14 14:00:19,310 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0764) Prec@1 89.000 (87.200) Prec@5 98.000 (99.462) +2022-11-14 14:00:19,319 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0769) Prec@1 80.000 (87.091) Prec@5 99.000 (99.455) +2022-11-14 14:00:19,328 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0765) Prec@1 91.000 (87.149) Prec@5 100.000 (99.463) +2022-11-14 14:00:19,338 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0766) Prec@1 84.000 (87.103) Prec@5 98.000 (99.441) +2022-11-14 14:00:19,347 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0762) Prec@1 91.000 (87.159) Prec@5 99.000 (99.435) +2022-11-14 14:00:19,357 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0763) Prec@1 86.000 (87.143) Prec@5 98.000 (99.414) +2022-11-14 14:00:19,367 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0766) Prec@1 85.000 (87.113) Prec@5 100.000 (99.423) +2022-11-14 14:00:19,377 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0764) Prec@1 89.000 (87.139) Prec@5 100.000 (99.431) +2022-11-14 14:00:19,387 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0760) Prec@1 94.000 (87.233) Prec@5 99.000 (99.425) +2022-11-14 14:00:19,398 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0374 (0.0755) Prec@1 94.000 (87.324) Prec@5 100.000 (99.432) +2022-11-14 14:00:19,409 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0760) Prec@1 81.000 (87.240) Prec@5 100.000 (99.440) +2022-11-14 14:00:19,422 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0758) Prec@1 90.000 (87.276) Prec@5 99.000 (99.434) +2022-11-14 14:00:19,435 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0759) Prec@1 86.000 (87.260) Prec@5 100.000 (99.442) +2022-11-14 14:00:19,447 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0759) Prec@1 86.000 (87.244) Prec@5 100.000 (99.449) +2022-11-14 14:00:19,457 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0759) Prec@1 88.000 (87.253) Prec@5 99.000 (99.443) +2022-11-14 14:00:19,466 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0760) Prec@1 88.000 (87.263) Prec@5 100.000 (99.450) +2022-11-14 14:00:19,475 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0761) Prec@1 86.000 (87.247) Prec@5 98.000 (99.432) +2022-11-14 14:00:19,484 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0762) Prec@1 85.000 (87.220) Prec@5 99.000 (99.427) +2022-11-14 14:00:19,494 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0762) Prec@1 88.000 (87.229) Prec@5 100.000 (99.434) +2022-11-14 14:00:19,503 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0762) Prec@1 88.000 (87.238) Prec@5 100.000 (99.440) +2022-11-14 14:00:19,511 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0765) Prec@1 86.000 (87.224) Prec@5 98.000 (99.424) +2022-11-14 14:00:19,521 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1190 (0.0770) Prec@1 78.000 (87.116) Prec@5 99.000 (99.419) +2022-11-14 14:00:19,530 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0771) Prec@1 84.000 (87.080) Prec@5 98.000 (99.402) +2022-11-14 14:00:19,539 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0771) Prec@1 85.000 (87.057) Prec@5 99.000 (99.398) +2022-11-14 14:00:19,548 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0770) Prec@1 90.000 (87.090) Prec@5 100.000 (99.404) +2022-11-14 14:00:19,557 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0771) Prec@1 87.000 (87.089) Prec@5 98.000 (99.389) +2022-11-14 14:00:19,566 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0769) Prec@1 90.000 (87.121) Prec@5 100.000 (99.396) +2022-11-14 14:00:19,576 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0767) Prec@1 90.000 (87.152) Prec@5 100.000 (99.402) +2022-11-14 14:00:19,585 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0769) Prec@1 82.000 (87.097) Prec@5 100.000 (99.409) +2022-11-14 14:00:19,594 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0770) Prec@1 86.000 (87.085) Prec@5 98.000 (99.394) +2022-11-14 14:00:19,604 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0772) Prec@1 82.000 (87.032) Prec@5 100.000 (99.400) +2022-11-14 14:00:19,613 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0771) Prec@1 87.000 (87.031) Prec@5 99.000 (99.396) +2022-11-14 14:00:19,622 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0769) Prec@1 91.000 (87.072) Prec@5 99.000 (99.392) +2022-11-14 14:00:19,631 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0771) Prec@1 85.000 (87.051) Prec@5 100.000 (99.398) +2022-11-14 14:00:19,640 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0771) Prec@1 87.000 (87.051) Prec@5 100.000 (99.404) +2022-11-14 14:00:19,649 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0770) Prec@1 90.000 (87.080) Prec@5 100.000 (99.410) +2022-11-14 14:00:19,719 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:00:20,037 Epoch: [131][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.0528 (0.0528) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 14:00:20,257 Epoch: [131][10/500] Time 0.017 (0.020) Data 0.002 (0.023) Loss 0.0464 (0.0496) Prec@1 91.000 (90.000) Prec@5 99.000 (98.500) +2022-11-14 14:00:20,465 Epoch: [131][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0886 (0.0626) Prec@1 87.000 (89.000) Prec@5 99.000 (98.667) +2022-11-14 14:00:20,704 Epoch: [131][30/500] Time 0.030 (0.020) Data 0.002 (0.009) Loss 0.0473 (0.0588) Prec@1 92.000 (89.750) Prec@5 100.000 (99.000) +2022-11-14 14:00:20,997 Epoch: [131][40/500] Time 0.027 (0.021) Data 0.002 (0.007) Loss 0.0787 (0.0628) Prec@1 87.000 (89.200) Prec@5 100.000 (99.200) +2022-11-14 14:00:21,302 Epoch: [131][50/500] Time 0.033 (0.022) Data 0.002 (0.006) Loss 0.0448 (0.0598) Prec@1 93.000 (89.833) Prec@5 100.000 (99.333) +2022-11-14 14:00:21,607 Epoch: [131][60/500] Time 0.028 (0.023) Data 0.001 (0.006) Loss 0.0573 (0.0594) Prec@1 90.000 (89.857) Prec@5 100.000 (99.429) +2022-11-14 14:00:21,909 Epoch: [131][70/500] Time 0.030 (0.024) Data 0.002 (0.005) Loss 0.0510 (0.0584) Prec@1 90.000 (89.875) Prec@5 99.000 (99.375) +2022-11-14 14:00:22,215 Epoch: [131][80/500] Time 0.033 (0.024) Data 0.002 (0.005) Loss 0.0388 (0.0562) Prec@1 94.000 (90.333) Prec@5 100.000 (99.444) +2022-11-14 14:00:22,519 Epoch: [131][90/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0430 (0.0549) Prec@1 90.000 (90.300) Prec@5 100.000 (99.500) +2022-11-14 14:00:22,818 Epoch: [131][100/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0764 (0.0568) Prec@1 86.000 (89.909) Prec@5 100.000 (99.545) +2022-11-14 14:00:23,116 Epoch: [131][110/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0461 (0.0559) Prec@1 92.000 (90.083) Prec@5 100.000 (99.583) +2022-11-14 14:00:23,417 Epoch: [131][120/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0759 (0.0575) Prec@1 89.000 (90.000) Prec@5 99.000 (99.538) +2022-11-14 14:00:23,722 Epoch: [131][130/500] Time 0.028 (0.025) Data 0.001 (0.004) Loss 0.0777 (0.0589) Prec@1 87.000 (89.786) Prec@5 99.000 (99.500) +2022-11-14 14:00:24,026 Epoch: [131][140/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.0668 (0.0595) Prec@1 90.000 (89.800) Prec@5 100.000 (99.533) +2022-11-14 14:00:24,326 Epoch: [131][150/500] Time 0.027 (0.025) Data 0.001 (0.003) Loss 0.0636 (0.0597) Prec@1 90.000 (89.812) Prec@5 100.000 (99.562) +2022-11-14 14:00:24,627 Epoch: [131][160/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0634 (0.0599) Prec@1 89.000 (89.765) Prec@5 100.000 (99.588) +2022-11-14 14:00:24,933 Epoch: [131][170/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0589 (0.0599) Prec@1 90.000 (89.778) Prec@5 99.000 (99.556) +2022-11-14 14:00:25,233 Epoch: [131][180/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0646 (0.0601) Prec@1 89.000 (89.737) Prec@5 99.000 (99.526) +2022-11-14 14:00:25,556 Epoch: [131][190/500] Time 0.039 (0.026) Data 0.001 (0.003) Loss 0.0600 (0.0601) Prec@1 89.000 (89.700) Prec@5 99.000 (99.500) +2022-11-14 14:00:26,038 Epoch: [131][200/500] Time 0.053 (0.026) Data 0.002 (0.003) Loss 0.0399 (0.0592) Prec@1 94.000 (89.905) Prec@5 100.000 (99.524) +2022-11-14 14:00:26,539 Epoch: [131][210/500] Time 0.055 (0.027) Data 0.002 (0.003) Loss 0.0915 (0.0606) Prec@1 88.000 (89.818) Prec@5 98.000 (99.455) +2022-11-14 14:00:27,026 Epoch: [131][220/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0680 (0.0609) Prec@1 90.000 (89.826) Prec@5 98.000 (99.391) +2022-11-14 14:00:27,496 Epoch: [131][230/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0753 (0.0615) Prec@1 87.000 (89.708) Prec@5 98.000 (99.333) +2022-11-14 14:00:27,963 Epoch: [131][240/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0343 (0.0605) Prec@1 95.000 (89.920) Prec@5 100.000 (99.360) +2022-11-14 14:00:28,455 Epoch: [131][250/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0668 (0.0607) Prec@1 89.000 (89.885) Prec@5 100.000 (99.385) +2022-11-14 14:00:28,926 Epoch: [131][260/500] Time 0.051 (0.030) Data 0.002 (0.003) Loss 0.0610 (0.0607) Prec@1 90.000 (89.889) Prec@5 99.000 (99.370) +2022-11-14 14:00:29,398 Epoch: [131][270/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0529 (0.0604) Prec@1 93.000 (90.000) Prec@5 99.000 (99.357) +2022-11-14 14:00:29,897 Epoch: [131][280/500] Time 0.056 (0.031) Data 0.002 (0.003) Loss 0.0626 (0.0605) Prec@1 88.000 (89.931) Prec@5 100.000 (99.379) +2022-11-14 14:00:30,381 Epoch: [131][290/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0541 (0.0603) Prec@1 91.000 (89.967) Prec@5 100.000 (99.400) +2022-11-14 14:00:30,877 Epoch: [131][300/500] Time 0.052 (0.032) Data 0.002 (0.003) Loss 0.0507 (0.0600) Prec@1 90.000 (89.968) Prec@5 100.000 (99.419) +2022-11-14 14:00:31,377 Epoch: [131][310/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0498 (0.0597) Prec@1 93.000 (90.062) Prec@5 99.000 (99.406) +2022-11-14 14:00:31,905 Epoch: [131][320/500] Time 0.051 (0.033) Data 0.002 (0.003) Loss 0.0548 (0.0595) Prec@1 91.000 (90.091) Prec@5 100.000 (99.424) +2022-11-14 14:00:32,393 Epoch: [131][330/500] Time 0.043 (0.033) Data 0.003 (0.003) Loss 0.0403 (0.0589) Prec@1 94.000 (90.206) Prec@5 100.000 (99.441) +2022-11-14 14:00:32,885 Epoch: [131][340/500] Time 0.054 (0.033) Data 0.002 (0.003) Loss 0.0358 (0.0583) Prec@1 96.000 (90.371) Prec@5 100.000 (99.457) +2022-11-14 14:00:33,367 Epoch: [131][350/500] Time 0.052 (0.034) Data 0.002 (0.003) Loss 0.0660 (0.0585) Prec@1 89.000 (90.333) Prec@5 99.000 (99.444) +2022-11-14 14:00:33,852 Epoch: [131][360/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0760 (0.0590) Prec@1 88.000 (90.270) Prec@5 98.000 (99.405) +2022-11-14 14:00:34,325 Epoch: [131][370/500] Time 0.055 (0.034) Data 0.002 (0.003) Loss 0.0257 (0.0581) Prec@1 97.000 (90.447) Prec@5 100.000 (99.421) +2022-11-14 14:00:34,789 Epoch: [131][380/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0551 (0.0580) Prec@1 93.000 (90.513) Prec@5 99.000 (99.410) +2022-11-14 14:00:35,257 Epoch: [131][390/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0452 (0.0577) Prec@1 91.000 (90.525) Prec@5 100.000 (99.425) +2022-11-14 14:00:35,746 Epoch: [131][400/500] Time 0.051 (0.035) Data 0.002 (0.002) Loss 0.0229 (0.0569) Prec@1 98.000 (90.707) Prec@5 100.000 (99.439) +2022-11-14 14:00:36,230 Epoch: [131][410/500] Time 0.055 (0.035) Data 0.002 (0.002) Loss 0.0760 (0.0573) Prec@1 88.000 (90.643) Prec@5 100.000 (99.452) +2022-11-14 14:00:36,699 Epoch: [131][420/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0504 (0.0571) Prec@1 90.000 (90.628) Prec@5 100.000 (99.465) +2022-11-14 14:00:37,167 Epoch: [131][430/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0656 (0.0573) Prec@1 91.000 (90.636) Prec@5 98.000 (99.432) +2022-11-14 14:00:37,640 Epoch: [131][440/500] Time 0.043 (0.035) Data 0.003 (0.002) Loss 0.0464 (0.0571) Prec@1 90.000 (90.622) Prec@5 100.000 (99.444) +2022-11-14 14:00:38,116 Epoch: [131][450/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0578 (0.0571) Prec@1 89.000 (90.587) Prec@5 100.000 (99.457) +2022-11-14 14:00:38,632 Epoch: [131][460/500] Time 0.063 (0.036) Data 0.002 (0.002) Loss 0.0414 (0.0568) Prec@1 94.000 (90.660) Prec@5 100.000 (99.468) +2022-11-14 14:00:39,097 Epoch: [131][470/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0466 (0.0566) Prec@1 92.000 (90.688) Prec@5 100.000 (99.479) +2022-11-14 14:00:39,609 Epoch: [131][480/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0683 (0.0568) Prec@1 89.000 (90.653) Prec@5 99.000 (99.469) +2022-11-14 14:00:40,153 Epoch: [131][490/500] Time 0.053 (0.036) Data 0.002 (0.002) Loss 0.0551 (0.0568) Prec@1 90.000 (90.640) Prec@5 98.000 (99.440) +2022-11-14 14:00:40,595 Epoch: [131][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0657 (0.0569) Prec@1 88.000 (90.588) Prec@5 100.000 (99.451) +2022-11-14 14:00:40,903 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0668 (0.0668) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:00:40,914 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0644) Prec@1 89.000 (88.500) Prec@5 98.000 (99.000) +2022-11-14 14:00:40,923 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0680) Prec@1 88.000 (88.333) Prec@5 99.000 (99.000) +2022-11-14 14:00:40,935 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0646) Prec@1 92.000 (89.250) Prec@5 99.000 (99.000) +2022-11-14 14:00:40,943 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0650) Prec@1 88.000 (89.000) Prec@5 100.000 (99.200) +2022-11-14 14:00:40,950 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0269 (0.0587) Prec@1 96.000 (90.167) Prec@5 100.000 (99.333) +2022-11-14 14:00:40,958 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0593) Prec@1 91.000 (90.286) Prec@5 99.000 (99.286) +2022-11-14 14:00:40,967 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0657) Prec@1 80.000 (89.000) Prec@5 100.000 (99.375) +2022-11-14 14:00:40,976 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0692) Prec@1 84.000 (88.444) Prec@5 99.000 (99.333) +2022-11-14 14:00:40,985 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0690) Prec@1 89.000 (88.500) Prec@5 99.000 (99.300) +2022-11-14 14:00:40,995 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0686) Prec@1 88.000 (88.455) Prec@5 100.000 (99.364) +2022-11-14 14:00:41,004 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0692) Prec@1 88.000 (88.417) Prec@5 99.000 (99.333) +2022-11-14 14:00:41,015 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0680) Prec@1 89.000 (88.462) Prec@5 100.000 (99.385) +2022-11-14 14:00:41,026 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0687) Prec@1 84.000 (88.143) Prec@5 99.000 (99.357) +2022-11-14 14:00:41,040 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0687) Prec@1 88.000 (88.133) Prec@5 100.000 (99.400) +2022-11-14 14:00:41,054 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0689) Prec@1 90.000 (88.250) Prec@5 100.000 (99.438) +2022-11-14 14:00:41,069 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0684) Prec@1 90.000 (88.353) Prec@5 98.000 (99.353) +2022-11-14 14:00:41,083 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0694) Prec@1 84.000 (88.111) Prec@5 100.000 (99.389) +2022-11-14 14:00:41,095 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0704) Prec@1 84.000 (87.895) Prec@5 98.000 (99.316) +2022-11-14 14:00:41,109 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.0723) Prec@1 80.000 (87.500) Prec@5 99.000 (99.300) +2022-11-14 14:00:41,121 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0731) Prec@1 86.000 (87.429) Prec@5 99.000 (99.286) +2022-11-14 14:00:41,132 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0734) Prec@1 86.000 (87.364) Prec@5 100.000 (99.318) +2022-11-14 14:00:41,141 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0740) Prec@1 87.000 (87.348) Prec@5 99.000 (99.304) +2022-11-14 14:00:41,151 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0733) Prec@1 90.000 (87.458) Prec@5 100.000 (99.333) +2022-11-14 14:00:41,161 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0735) Prec@1 88.000 (87.480) Prec@5 100.000 (99.360) +2022-11-14 14:00:41,171 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0739) Prec@1 87.000 (87.462) Prec@5 98.000 (99.308) +2022-11-14 14:00:41,181 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0738) Prec@1 88.000 (87.481) Prec@5 100.000 (99.333) +2022-11-14 14:00:41,191 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0735) Prec@1 89.000 (87.536) Prec@5 100.000 (99.357) +2022-11-14 14:00:41,202 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0736) Prec@1 88.000 (87.552) Prec@5 97.000 (99.276) +2022-11-14 14:00:41,211 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0742) Prec@1 82.000 (87.367) Prec@5 100.000 (99.300) +2022-11-14 14:00:41,220 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0740) Prec@1 88.000 (87.387) Prec@5 99.000 (99.290) +2022-11-14 14:00:41,231 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0740) Prec@1 89.000 (87.438) Prec@5 100.000 (99.312) +2022-11-14 14:00:41,241 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0741) Prec@1 87.000 (87.424) Prec@5 100.000 (99.333) +2022-11-14 14:00:41,253 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0748) Prec@1 82.000 (87.265) Prec@5 99.000 (99.324) +2022-11-14 14:00:41,263 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0757) Prec@1 83.000 (87.143) Prec@5 98.000 (99.286) +2022-11-14 14:00:41,274 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0762) Prec@1 84.000 (87.056) Prec@5 99.000 (99.278) +2022-11-14 14:00:41,286 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0765) Prec@1 86.000 (87.027) Prec@5 98.000 (99.243) +2022-11-14 14:00:41,296 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.0777) Prec@1 80.000 (86.842) Prec@5 100.000 (99.263) +2022-11-14 14:00:41,305 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0770) Prec@1 93.000 (87.000) Prec@5 99.000 (99.256) +2022-11-14 14:00:41,313 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0766) Prec@1 89.000 (87.050) Prec@5 99.000 (99.250) +2022-11-14 14:00:41,324 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0772) Prec@1 83.000 (86.951) Prec@5 98.000 (99.220) +2022-11-14 14:00:41,335 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0771) Prec@1 90.000 (87.024) Prec@5 98.000 (99.190) +2022-11-14 14:00:41,346 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0763) Prec@1 92.000 (87.140) Prec@5 100.000 (99.209) +2022-11-14 14:00:41,357 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0764) Prec@1 87.000 (87.136) Prec@5 98.000 (99.182) +2022-11-14 14:00:41,369 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0762) Prec@1 90.000 (87.200) Prec@5 100.000 (99.200) +2022-11-14 14:00:41,380 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0769) Prec@1 79.000 (87.022) Prec@5 100.000 (99.217) +2022-11-14 14:00:41,391 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0768) Prec@1 87.000 (87.021) Prec@5 100.000 (99.234) +2022-11-14 14:00:41,401 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0775) Prec@1 84.000 (86.958) Prec@5 99.000 (99.229) +2022-11-14 14:00:41,412 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0773) Prec@1 89.000 (87.000) Prec@5 100.000 (99.245) +2022-11-14 14:00:41,423 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0778) Prec@1 81.000 (86.880) Prec@5 100.000 (99.260) +2022-11-14 14:00:41,433 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0780) Prec@1 84.000 (86.824) Prec@5 100.000 (99.275) +2022-11-14 14:00:41,443 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0784) Prec@1 81.000 (86.712) Prec@5 99.000 (99.269) +2022-11-14 14:00:41,455 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0786) Prec@1 84.000 (86.660) Prec@5 100.000 (99.283) +2022-11-14 14:00:41,467 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0783) Prec@1 90.000 (86.722) Prec@5 98.000 (99.259) +2022-11-14 14:00:41,478 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0781) Prec@1 88.000 (86.745) Prec@5 99.000 (99.255) +2022-11-14 14:00:41,489 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0782) Prec@1 88.000 (86.768) Prec@5 100.000 (99.268) +2022-11-14 14:00:41,500 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0784) Prec@1 85.000 (86.737) Prec@5 100.000 (99.281) +2022-11-14 14:00:41,510 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0783) Prec@1 89.000 (86.776) Prec@5 99.000 (99.276) +2022-11-14 14:00:41,521 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1237 (0.0791) Prec@1 81.000 (86.678) Prec@5 100.000 (99.288) +2022-11-14 14:00:41,530 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0793) Prec@1 84.000 (86.633) Prec@5 99.000 (99.283) +2022-11-14 14:00:41,540 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0795) Prec@1 86.000 (86.623) Prec@5 99.000 (99.279) +2022-11-14 14:00:41,551 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0795) Prec@1 89.000 (86.661) Prec@5 100.000 (99.290) +2022-11-14 14:00:41,563 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0795) Prec@1 86.000 (86.651) Prec@5 100.000 (99.302) +2022-11-14 14:00:41,573 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0792) Prec@1 91.000 (86.719) Prec@5 100.000 (99.312) +2022-11-14 14:00:41,584 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0795) Prec@1 86.000 (86.708) Prec@5 100.000 (99.323) +2022-11-14 14:00:41,594 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0797) Prec@1 82.000 (86.636) Prec@5 99.000 (99.318) +2022-11-14 14:00:41,606 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0458 (0.0792) Prec@1 93.000 (86.731) Prec@5 100.000 (99.328) +2022-11-14 14:00:41,617 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0794) Prec@1 86.000 (86.721) Prec@5 98.000 (99.309) +2022-11-14 14:00:41,628 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0793) Prec@1 89.000 (86.754) Prec@5 98.000 (99.290) +2022-11-14 14:00:41,639 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0796) Prec@1 85.000 (86.729) Prec@5 98.000 (99.271) +2022-11-14 14:00:41,651 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0797) Prec@1 85.000 (86.704) Prec@5 100.000 (99.282) +2022-11-14 14:00:41,661 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0796) Prec@1 88.000 (86.722) Prec@5 100.000 (99.292) +2022-11-14 14:00:41,671 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0795) Prec@1 87.000 (86.726) Prec@5 99.000 (99.288) +2022-11-14 14:00:41,682 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0792) Prec@1 91.000 (86.784) Prec@5 100.000 (99.297) +2022-11-14 14:00:41,692 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0791) Prec@1 87.000 (86.787) Prec@5 100.000 (99.307) +2022-11-14 14:00:41,702 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0792) Prec@1 88.000 (86.803) Prec@5 98.000 (99.289) +2022-11-14 14:00:41,712 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0792) Prec@1 87.000 (86.805) Prec@5 98.000 (99.273) +2022-11-14 14:00:41,723 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0793) Prec@1 84.000 (86.769) Prec@5 95.000 (99.218) +2022-11-14 14:00:41,733 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0793) Prec@1 87.000 (86.772) Prec@5 100.000 (99.228) +2022-11-14 14:00:41,744 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0793) Prec@1 89.000 (86.800) Prec@5 100.000 (99.237) +2022-11-14 14:00:41,754 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0793) Prec@1 87.000 (86.802) Prec@5 98.000 (99.222) +2022-11-14 14:00:41,766 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0795) Prec@1 84.000 (86.768) Prec@5 100.000 (99.232) +2022-11-14 14:00:41,776 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0796) Prec@1 84.000 (86.735) Prec@5 100.000 (99.241) +2022-11-14 14:00:41,785 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0794) Prec@1 90.000 (86.774) Prec@5 100.000 (99.250) +2022-11-14 14:00:41,795 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0795) Prec@1 88.000 (86.788) Prec@5 99.000 (99.247) +2022-11-14 14:00:41,806 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.0799) Prec@1 82.000 (86.733) Prec@5 99.000 (99.244) +2022-11-14 14:00:41,816 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0799) Prec@1 88.000 (86.747) Prec@5 98.000 (99.230) +2022-11-14 14:00:41,827 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0798) Prec@1 87.000 (86.750) Prec@5 99.000 (99.227) +2022-11-14 14:00:41,837 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0795) Prec@1 93.000 (86.820) Prec@5 100.000 (99.236) +2022-11-14 14:00:41,848 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0795) Prec@1 87.000 (86.822) Prec@5 99.000 (99.233) +2022-11-14 14:00:41,858 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0796) Prec@1 85.000 (86.802) Prec@5 100.000 (99.242) +2022-11-14 14:00:41,870 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0793) Prec@1 90.000 (86.837) Prec@5 99.000 (99.239) +2022-11-14 14:00:41,880 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0795) Prec@1 82.000 (86.785) Prec@5 100.000 (99.247) +2022-11-14 14:00:41,891 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0795) Prec@1 87.000 (86.787) Prec@5 98.000 (99.234) +2022-11-14 14:00:41,901 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0796) Prec@1 83.000 (86.747) Prec@5 99.000 (99.232) +2022-11-14 14:00:41,912 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0794) Prec@1 90.000 (86.781) Prec@5 100.000 (99.240) +2022-11-14 14:00:41,923 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0792) Prec@1 85.000 (86.763) Prec@5 99.000 (99.237) +2022-11-14 14:00:41,933 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0795) Prec@1 82.000 (86.714) Prec@5 98.000 (99.224) +2022-11-14 14:00:41,944 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0796) Prec@1 83.000 (86.677) Prec@5 99.000 (99.222) +2022-11-14 14:00:41,955 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0796) Prec@1 88.000 (86.690) Prec@5 100.000 (99.230) +2022-11-14 14:00:42,017 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:00:42,344 Epoch: [132][0/500] Time 0.029 (0.029) Data 0.237 (0.237) Loss 0.0459 (0.0459) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:00:42,559 Epoch: [132][10/500] Time 0.024 (0.020) Data 0.002 (0.023) Loss 0.0508 (0.0483) Prec@1 90.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 14:00:42,778 Epoch: [132][20/500] Time 0.018 (0.020) Data 0.002 (0.013) Loss 0.0368 (0.0445) Prec@1 93.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:00:42,972 Epoch: [132][30/500] Time 0.017 (0.019) Data 0.001 (0.009) Loss 0.0274 (0.0402) Prec@1 95.000 (92.250) Prec@5 100.000 (99.750) +2022-11-14 14:00:43,194 Epoch: [132][40/500] Time 0.023 (0.019) Data 0.002 (0.007) Loss 0.0830 (0.0488) Prec@1 87.000 (91.200) Prec@5 100.000 (99.800) +2022-11-14 14:00:43,476 Epoch: [132][50/500] Time 0.026 (0.020) Data 0.002 (0.006) Loss 0.0438 (0.0480) Prec@1 95.000 (91.833) Prec@5 100.000 (99.833) +2022-11-14 14:00:43,798 Epoch: [132][60/500] Time 0.036 (0.021) Data 0.002 (0.006) Loss 0.0853 (0.0533) Prec@1 87.000 (91.143) Prec@5 99.000 (99.714) +2022-11-14 14:00:44,070 Epoch: [132][70/500] Time 0.031 (0.022) Data 0.002 (0.005) Loss 0.0589 (0.0540) Prec@1 90.000 (91.000) Prec@5 99.000 (99.625) +2022-11-14 14:00:44,353 Epoch: [132][80/500] Time 0.022 (0.022) Data 0.002 (0.005) Loss 0.0472 (0.0532) Prec@1 93.000 (91.222) Prec@5 100.000 (99.667) +2022-11-14 14:00:44,636 Epoch: [132][90/500] Time 0.030 (0.023) Data 0.002 (0.004) Loss 0.0351 (0.0514) Prec@1 95.000 (91.600) Prec@5 100.000 (99.700) +2022-11-14 14:00:44,928 Epoch: [132][100/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.0683 (0.0530) Prec@1 87.000 (91.182) Prec@5 99.000 (99.636) +2022-11-14 14:00:45,211 Epoch: [132][110/500] Time 0.033 (0.023) Data 0.002 (0.004) Loss 0.0588 (0.0534) Prec@1 88.000 (90.917) Prec@5 100.000 (99.667) +2022-11-14 14:00:45,496 Epoch: [132][120/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0348 (0.0520) Prec@1 94.000 (91.154) Prec@5 100.000 (99.692) +2022-11-14 14:00:45,780 Epoch: [132][130/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.0558 (0.0523) Prec@1 93.000 (91.286) Prec@5 99.000 (99.643) +2022-11-14 14:00:46,063 Epoch: [132][140/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0764 (0.0539) Prec@1 88.000 (91.067) Prec@5 100.000 (99.667) +2022-11-14 14:00:46,350 Epoch: [132][150/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0409 (0.0531) Prec@1 94.000 (91.250) Prec@5 100.000 (99.688) +2022-11-14 14:00:46,669 Epoch: [132][160/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0585 (0.0534) Prec@1 90.000 (91.176) Prec@5 100.000 (99.706) +2022-11-14 14:00:46,941 Epoch: [132][170/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0342 (0.0523) Prec@1 95.000 (91.389) Prec@5 100.000 (99.722) +2022-11-14 14:00:47,227 Epoch: [132][180/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0686 (0.0532) Prec@1 88.000 (91.211) Prec@5 99.000 (99.684) +2022-11-14 14:00:47,576 Epoch: [132][190/500] Time 0.042 (0.024) Data 0.002 (0.003) Loss 0.0353 (0.0523) Prec@1 93.000 (91.300) Prec@5 100.000 (99.700) +2022-11-14 14:00:48,059 Epoch: [132][200/500] Time 0.039 (0.025) Data 0.002 (0.003) Loss 0.0715 (0.0532) Prec@1 88.000 (91.143) Prec@5 100.000 (99.714) +2022-11-14 14:00:48,513 Epoch: [132][210/500] Time 0.042 (0.026) Data 0.002 (0.003) Loss 0.0519 (0.0531) Prec@1 90.000 (91.091) Prec@5 99.000 (99.682) +2022-11-14 14:00:49,043 Epoch: [132][220/500] Time 0.049 (0.027) Data 0.002 (0.003) Loss 0.0867 (0.0546) Prec@1 85.000 (90.826) Prec@5 98.000 (99.609) +2022-11-14 14:00:49,490 Epoch: [132][230/500] Time 0.040 (0.028) Data 0.002 (0.003) Loss 0.0634 (0.0550) Prec@1 88.000 (90.708) Prec@5 99.000 (99.583) +2022-11-14 14:00:49,988 Epoch: [132][240/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0549 (0.0550) Prec@1 91.000 (90.720) Prec@5 100.000 (99.600) +2022-11-14 14:00:50,574 Epoch: [132][250/500] Time 0.063 (0.029) Data 0.002 (0.003) Loss 0.0472 (0.0547) Prec@1 91.000 (90.731) Prec@5 100.000 (99.615) +2022-11-14 14:00:51,023 Epoch: [132][260/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0537 (0.0546) Prec@1 91.000 (90.741) Prec@5 99.000 (99.593) +2022-11-14 14:00:51,479 Epoch: [132][270/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0605 (0.0548) Prec@1 89.000 (90.679) Prec@5 99.000 (99.571) +2022-11-14 14:00:51,929 Epoch: [132][280/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0474 (0.0546) Prec@1 90.000 (90.655) Prec@5 100.000 (99.586) +2022-11-14 14:00:52,384 Epoch: [132][290/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0533 (0.0545) Prec@1 92.000 (90.700) Prec@5 99.000 (99.567) +2022-11-14 14:00:52,834 Epoch: [132][300/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0682 (0.0550) Prec@1 87.000 (90.581) Prec@5 99.000 (99.548) +2022-11-14 14:00:53,286 Epoch: [132][310/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0663 (0.0553) Prec@1 88.000 (90.500) Prec@5 100.000 (99.562) +2022-11-14 14:00:53,735 Epoch: [132][320/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0523 (0.0552) Prec@1 92.000 (90.545) Prec@5 99.000 (99.545) +2022-11-14 14:00:54,190 Epoch: [132][330/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0392 (0.0548) Prec@1 93.000 (90.618) Prec@5 100.000 (99.559) +2022-11-14 14:00:54,666 Epoch: [132][340/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0572 (0.0548) Prec@1 89.000 (90.571) Prec@5 100.000 (99.571) +2022-11-14 14:00:55,205 Epoch: [132][350/500] Time 0.055 (0.033) Data 0.002 (0.003) Loss 0.0606 (0.0550) Prec@1 91.000 (90.583) Prec@5 100.000 (99.583) +2022-11-14 14:00:55,691 Epoch: [132][360/500] Time 0.065 (0.033) Data 0.002 (0.003) Loss 0.0612 (0.0552) Prec@1 93.000 (90.649) Prec@5 99.000 (99.568) +2022-11-14 14:00:56,175 Epoch: [132][370/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0490 (0.0550) Prec@1 93.000 (90.711) Prec@5 100.000 (99.579) +2022-11-14 14:00:56,674 Epoch: [132][380/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0350 (0.0545) Prec@1 94.000 (90.795) Prec@5 100.000 (99.590) +2022-11-14 14:00:57,122 Epoch: [132][390/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0350 (0.0540) Prec@1 94.000 (90.875) Prec@5 100.000 (99.600) +2022-11-14 14:00:57,584 Epoch: [132][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0324 (0.0535) Prec@1 96.000 (91.000) Prec@5 100.000 (99.610) +2022-11-14 14:00:58,112 Epoch: [132][410/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.0673 (0.0538) Prec@1 88.000 (90.929) Prec@5 100.000 (99.619) +2022-11-14 14:00:58,607 Epoch: [132][420/500] Time 0.060 (0.034) Data 0.002 (0.002) Loss 0.0600 (0.0540) Prec@1 90.000 (90.907) Prec@5 98.000 (99.581) +2022-11-14 14:00:59,107 Epoch: [132][430/500] Time 0.055 (0.035) Data 0.002 (0.002) Loss 0.0507 (0.0539) Prec@1 90.000 (90.886) Prec@5 100.000 (99.591) +2022-11-14 14:00:59,563 Epoch: [132][440/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0329 (0.0534) Prec@1 96.000 (91.000) Prec@5 100.000 (99.600) +2022-11-14 14:01:00,013 Epoch: [132][450/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0435 (0.0532) Prec@1 93.000 (91.043) Prec@5 100.000 (99.609) +2022-11-14 14:01:00,530 Epoch: [132][460/500] Time 0.081 (0.035) Data 0.002 (0.002) Loss 0.0881 (0.0539) Prec@1 87.000 (90.957) Prec@5 99.000 (99.596) +2022-11-14 14:01:01,018 Epoch: [132][470/500] Time 0.036 (0.035) Data 0.002 (0.002) Loss 0.0439 (0.0537) Prec@1 94.000 (91.021) Prec@5 99.000 (99.583) +2022-11-14 14:01:01,594 Epoch: [132][480/500] Time 0.070 (0.036) Data 0.002 (0.002) Loss 0.0497 (0.0536) Prec@1 92.000 (91.041) Prec@5 100.000 (99.592) +2022-11-14 14:01:02,006 Epoch: [132][490/500] Time 0.047 (0.036) Data 0.002 (0.002) Loss 0.0672 (0.0539) Prec@1 88.000 (90.980) Prec@5 99.000 (99.580) +2022-11-14 14:01:02,576 Epoch: [132][499/500] Time 0.061 (0.036) Data 0.002 (0.002) Loss 0.0552 (0.0539) Prec@1 91.000 (90.980) Prec@5 99.000 (99.569) +2022-11-14 14:01:02,882 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0420 (0.0420) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 14:01:02,891 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0550 (0.0485) Prec@1 91.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 14:01:02,903 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0613) Prec@1 84.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 14:01:02,918 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0648) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:01:02,929 Test: [4/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0688) Prec@1 85.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 14:01:02,942 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0482 (0.0654) Prec@1 92.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 14:01:02,953 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0688) Prec@1 85.000 (88.286) Prec@5 99.000 (99.429) +2022-11-14 14:01:02,966 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0971 (0.0723) Prec@1 83.000 (87.625) Prec@5 100.000 (99.500) +2022-11-14 14:01:02,978 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.0758) Prec@1 85.000 (87.333) Prec@5 99.000 (99.444) +2022-11-14 14:01:02,990 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0768) Prec@1 85.000 (87.100) Prec@5 99.000 (99.400) +2022-11-14 14:01:03,004 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0762) Prec@1 87.000 (87.091) Prec@5 100.000 (99.455) +2022-11-14 14:01:03,017 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1030 (0.0784) Prec@1 83.000 (86.750) Prec@5 99.000 (99.417) +2022-11-14 14:01:03,029 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0782) Prec@1 87.000 (86.769) Prec@5 100.000 (99.462) +2022-11-14 14:01:03,042 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0779) Prec@1 87.000 (86.786) Prec@5 100.000 (99.500) +2022-11-14 14:01:03,054 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.0789) Prec@1 82.000 (86.467) Prec@5 99.000 (99.467) +2022-11-14 14:01:03,067 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0949 (0.0799) Prec@1 82.000 (86.188) Prec@5 100.000 (99.500) +2022-11-14 14:01:03,081 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0595 (0.0787) Prec@1 91.000 (86.471) Prec@5 97.000 (99.353) +2022-11-14 14:01:03,094 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0949 (0.0796) Prec@1 84.000 (86.333) Prec@5 100.000 (99.389) +2022-11-14 14:01:03,107 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1055 (0.0809) Prec@1 82.000 (86.105) Prec@5 97.000 (99.263) +2022-11-14 14:01:03,120 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1019 (0.0820) Prec@1 80.000 (85.800) Prec@5 98.000 (99.200) +2022-11-14 14:01:03,134 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0820) Prec@1 84.000 (85.714) Prec@5 100.000 (99.238) +2022-11-14 14:01:03,147 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0933 (0.0826) Prec@1 83.000 (85.591) Prec@5 99.000 (99.227) +2022-11-14 14:01:03,158 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1072 (0.0836) Prec@1 83.000 (85.478) Prec@5 99.000 (99.217) +2022-11-14 14:01:03,172 Test: [23/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0832) Prec@1 85.000 (85.458) Prec@5 100.000 (99.250) +2022-11-14 14:01:03,186 Test: [24/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1027 (0.0839) Prec@1 85.000 (85.440) Prec@5 99.000 (99.240) +2022-11-14 14:01:03,197 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1108 (0.0850) Prec@1 81.000 (85.269) Prec@5 97.000 (99.154) +2022-11-14 14:01:03,208 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0482 (0.0836) Prec@1 92.000 (85.519) Prec@5 99.000 (99.148) +2022-11-14 14:01:03,218 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0836) Prec@1 86.000 (85.536) Prec@5 100.000 (99.179) +2022-11-14 14:01:03,228 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0835) Prec@1 87.000 (85.586) Prec@5 99.000 (99.172) +2022-11-14 14:01:03,239 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0864 (0.0836) Prec@1 86.000 (85.600) Prec@5 100.000 (99.200) +2022-11-14 14:01:03,249 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0842) Prec@1 83.000 (85.516) Prec@5 100.000 (99.226) +2022-11-14 14:01:03,260 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0836) Prec@1 89.000 (85.625) Prec@5 100.000 (99.250) +2022-11-14 14:01:03,271 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0837) Prec@1 84.000 (85.576) Prec@5 100.000 (99.273) +2022-11-14 14:01:03,281 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1240 (0.0849) Prec@1 79.000 (85.382) Prec@5 100.000 (99.294) +2022-11-14 14:01:03,291 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0842 (0.0848) Prec@1 87.000 (85.429) Prec@5 100.000 (99.314) +2022-11-14 14:01:03,301 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0848) Prec@1 87.000 (85.472) Prec@5 100.000 (99.333) +2022-11-14 14:01:03,311 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0846) Prec@1 89.000 (85.568) Prec@5 97.000 (99.270) +2022-11-14 14:01:03,321 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.0850) Prec@1 84.000 (85.526) Prec@5 100.000 (99.289) +2022-11-14 14:01:03,331 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0846) Prec@1 89.000 (85.615) Prec@5 99.000 (99.282) +2022-11-14 14:01:03,341 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0842) Prec@1 89.000 (85.700) Prec@5 98.000 (99.250) +2022-11-14 14:01:03,352 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0847) Prec@1 86.000 (85.707) Prec@5 99.000 (99.244) +2022-11-14 14:01:03,365 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0844) Prec@1 90.000 (85.810) Prec@5 98.000 (99.214) +2022-11-14 14:01:03,377 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0649 (0.0840) Prec@1 90.000 (85.907) Prec@5 99.000 (99.209) +2022-11-14 14:01:03,388 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0840) Prec@1 86.000 (85.909) Prec@5 99.000 (99.205) +2022-11-14 14:01:03,400 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0842) Prec@1 84.000 (85.867) Prec@5 99.000 (99.200) +2022-11-14 14:01:03,412 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0976 (0.0845) Prec@1 82.000 (85.783) Prec@5 100.000 (99.217) +2022-11-14 14:01:03,421 Test: [46/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0844) Prec@1 85.000 (85.766) Prec@5 100.000 (99.234) +2022-11-14 14:01:03,431 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1267 (0.0853) Prec@1 82.000 (85.688) Prec@5 98.000 (99.208) +2022-11-14 14:01:03,440 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0852) Prec@1 87.000 (85.714) Prec@5 100.000 (99.224) +2022-11-14 14:01:03,449 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1129 (0.0858) Prec@1 83.000 (85.660) Prec@5 99.000 (99.220) +2022-11-14 14:01:03,459 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0856) Prec@1 86.000 (85.667) Prec@5 100.000 (99.235) +2022-11-14 14:01:03,470 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0860) Prec@1 81.000 (85.577) Prec@5 98.000 (99.212) +2022-11-14 14:01:03,480 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1149 (0.0866) Prec@1 78.000 (85.434) Prec@5 100.000 (99.226) +2022-11-14 14:01:03,491 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0866) Prec@1 84.000 (85.407) Prec@5 96.000 (99.167) +2022-11-14 14:01:03,502 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0868) Prec@1 84.000 (85.382) Prec@5 100.000 (99.182) +2022-11-14 14:01:03,513 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0867) Prec@1 84.000 (85.357) Prec@5 99.000 (99.179) +2022-11-14 14:01:03,525 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0866) Prec@1 86.000 (85.368) Prec@5 99.000 (99.175) +2022-11-14 14:01:03,536 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0866) Prec@1 87.000 (85.397) Prec@5 99.000 (99.172) +2022-11-14 14:01:03,547 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0870) Prec@1 79.000 (85.288) Prec@5 99.000 (99.169) +2022-11-14 14:01:03,559 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1094 (0.0874) Prec@1 82.000 (85.233) Prec@5 100.000 (99.183) +2022-11-14 14:01:03,571 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0874) Prec@1 86.000 (85.246) Prec@5 99.000 (99.180) +2022-11-14 14:01:03,583 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0874) Prec@1 84.000 (85.226) Prec@5 99.000 (99.177) +2022-11-14 14:01:03,594 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0870) Prec@1 91.000 (85.317) Prec@5 100.000 (99.190) +2022-11-14 14:01:03,606 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0867) Prec@1 91.000 (85.406) Prec@5 99.000 (99.188) +2022-11-14 14:01:03,617 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0870) Prec@1 80.000 (85.323) Prec@5 97.000 (99.154) +2022-11-14 14:01:03,627 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0871) Prec@1 85.000 (85.318) Prec@5 99.000 (99.152) +2022-11-14 14:01:03,637 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0505 (0.0866) Prec@1 91.000 (85.403) Prec@5 100.000 (99.164) +2022-11-14 14:01:03,646 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0862) Prec@1 91.000 (85.485) Prec@5 99.000 (99.162) +2022-11-14 14:01:03,656 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0858) Prec@1 90.000 (85.551) Prec@5 99.000 (99.159) +2022-11-14 14:01:03,666 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0856) Prec@1 89.000 (85.600) Prec@5 100.000 (99.171) +2022-11-14 14:01:03,676 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0857) Prec@1 84.000 (85.577) Prec@5 99.000 (99.169) +2022-11-14 14:01:03,685 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0857) Prec@1 86.000 (85.583) Prec@5 100.000 (99.181) +2022-11-14 14:01:03,694 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0853) Prec@1 90.000 (85.644) Prec@5 99.000 (99.178) +2022-11-14 14:01:03,704 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0849) Prec@1 92.000 (85.730) Prec@5 100.000 (99.189) +2022-11-14 14:01:03,716 Test: [74/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0852) Prec@1 80.000 (85.653) Prec@5 99.000 (99.187) +2022-11-14 14:01:03,726 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0851) Prec@1 87.000 (85.671) Prec@5 99.000 (99.184) +2022-11-14 14:01:03,737 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0851) Prec@1 86.000 (85.675) Prec@5 99.000 (99.182) +2022-11-14 14:01:03,747 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.0853) Prec@1 82.000 (85.628) Prec@5 98.000 (99.167) +2022-11-14 14:01:03,759 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0852) Prec@1 86.000 (85.633) Prec@5 100.000 (99.177) +2022-11-14 14:01:03,773 Test: [79/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0852) Prec@1 85.000 (85.625) Prec@5 99.000 (99.175) +2022-11-14 14:01:03,785 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0851) Prec@1 87.000 (85.642) Prec@5 98.000 (99.160) +2022-11-14 14:01:03,797 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0852) Prec@1 83.000 (85.610) Prec@5 99.000 (99.159) +2022-11-14 14:01:03,811 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0855) Prec@1 82.000 (85.566) Prec@5 99.000 (99.157) +2022-11-14 14:01:03,824 Test: [83/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0857) Prec@1 83.000 (85.536) Prec@5 98.000 (99.143) +2022-11-14 14:01:03,835 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0858) Prec@1 83.000 (85.506) Prec@5 99.000 (99.141) +2022-11-14 14:01:03,846 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1210 (0.0862) Prec@1 79.000 (85.430) Prec@5 98.000 (99.128) +2022-11-14 14:01:03,858 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0860) Prec@1 89.000 (85.471) Prec@5 98.000 (99.115) +2022-11-14 14:01:03,869 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0859) Prec@1 87.000 (85.489) Prec@5 98.000 (99.102) +2022-11-14 14:01:03,879 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0859) Prec@1 88.000 (85.517) Prec@5 100.000 (99.112) +2022-11-14 14:01:03,890 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0856) Prec@1 90.000 (85.567) Prec@5 100.000 (99.122) +2022-11-14 14:01:03,901 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0855) Prec@1 89.000 (85.604) Prec@5 100.000 (99.132) +2022-11-14 14:01:03,912 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0851) Prec@1 91.000 (85.663) Prec@5 99.000 (99.130) +2022-11-14 14:01:03,924 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0852) Prec@1 84.000 (85.645) Prec@5 100.000 (99.140) +2022-11-14 14:01:03,935 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0852) Prec@1 86.000 (85.649) Prec@5 99.000 (99.138) +2022-11-14 14:01:03,947 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0854) Prec@1 81.000 (85.600) Prec@5 100.000 (99.147) +2022-11-14 14:01:03,959 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0853) Prec@1 88.000 (85.625) Prec@5 99.000 (99.146) +2022-11-14 14:01:03,972 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0851) Prec@1 89.000 (85.660) Prec@5 100.000 (99.155) +2022-11-14 14:01:03,984 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0851) Prec@1 86.000 (85.663) Prec@5 100.000 (99.163) +2022-11-14 14:01:03,997 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1091 (0.0854) Prec@1 82.000 (85.626) Prec@5 98.000 (99.152) +2022-11-14 14:01:04,009 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0851) Prec@1 89.000 (85.660) Prec@5 100.000 (99.160) +2022-11-14 14:01:04,072 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:01:04,395 Epoch: [133][0/500] Time 0.023 (0.023) Data 0.233 (0.233) Loss 0.0516 (0.0516) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:04,641 Epoch: [133][10/500] Time 0.027 (0.022) Data 0.002 (0.023) Loss 0.0404 (0.0460) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:04,884 Epoch: [133][20/500] Time 0.017 (0.022) Data 0.002 (0.013) Loss 0.0342 (0.0420) Prec@1 96.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:01:05,143 Epoch: [133][30/500] Time 0.029 (0.022) Data 0.002 (0.009) Loss 0.0517 (0.0444) Prec@1 92.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:01:05,549 Epoch: [133][40/500] Time 0.075 (0.025) Data 0.002 (0.008) Loss 0.0312 (0.0418) Prec@1 95.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:01:06,068 Epoch: [133][50/500] Time 0.029 (0.030) Data 0.002 (0.006) Loss 0.0561 (0.0442) Prec@1 91.000 (93.000) Prec@5 100.000 (99.833) +2022-11-14 14:01:06,546 Epoch: [133][60/500] Time 0.032 (0.032) Data 0.002 (0.006) Loss 0.0624 (0.0468) Prec@1 87.000 (92.143) Prec@5 98.000 (99.571) +2022-11-14 14:01:06,974 Epoch: [133][70/500] Time 0.040 (0.033) Data 0.002 (0.005) Loss 0.0670 (0.0493) Prec@1 87.000 (91.500) Prec@5 100.000 (99.625) +2022-11-14 14:01:07,395 Epoch: [133][80/500] Time 0.039 (0.033) Data 0.002 (0.005) Loss 0.0317 (0.0474) Prec@1 93.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:01:07,883 Epoch: [133][90/500] Time 0.027 (0.034) Data 0.002 (0.005) Loss 0.0621 (0.0488) Prec@1 90.000 (91.500) Prec@5 98.000 (99.500) +2022-11-14 14:01:08,305 Epoch: [133][100/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.0593 (0.0498) Prec@1 91.000 (91.455) Prec@5 100.000 (99.545) +2022-11-14 14:01:08,730 Epoch: [133][110/500] Time 0.037 (0.035) Data 0.002 (0.004) Loss 0.0539 (0.0501) Prec@1 89.000 (91.250) Prec@5 99.000 (99.500) +2022-11-14 14:01:09,258 Epoch: [133][120/500] Time 0.029 (0.036) Data 0.002 (0.004) Loss 0.0439 (0.0496) Prec@1 93.000 (91.385) Prec@5 100.000 (99.538) +2022-11-14 14:01:09,724 Epoch: [133][130/500] Time 0.032 (0.037) Data 0.002 (0.004) Loss 0.0313 (0.0483) Prec@1 96.000 (91.714) Prec@5 100.000 (99.571) +2022-11-14 14:01:10,146 Epoch: [133][140/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0951 (0.0514) Prec@1 85.000 (91.267) Prec@5 98.000 (99.467) +2022-11-14 14:01:10,632 Epoch: [133][150/500] Time 0.027 (0.037) Data 0.002 (0.004) Loss 0.0735 (0.0528) Prec@1 88.000 (91.062) Prec@5 100.000 (99.500) +2022-11-14 14:01:11,053 Epoch: [133][160/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0694 (0.0538) Prec@1 88.000 (90.882) Prec@5 99.000 (99.471) +2022-11-14 14:01:11,478 Epoch: [133][170/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0555 (0.0539) Prec@1 91.000 (90.889) Prec@5 100.000 (99.500) +2022-11-14 14:01:11,935 Epoch: [133][180/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0599 (0.0542) Prec@1 89.000 (90.789) Prec@5 99.000 (99.474) +2022-11-14 14:01:12,353 Epoch: [133][190/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0364 (0.0533) Prec@1 96.000 (91.050) Prec@5 99.000 (99.450) +2022-11-14 14:01:12,805 Epoch: [133][200/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0754 (0.0544) Prec@1 88.000 (90.905) Prec@5 98.000 (99.381) +2022-11-14 14:01:13,302 Epoch: [133][210/500] Time 0.034 (0.038) Data 0.001 (0.003) Loss 0.0394 (0.0537) Prec@1 93.000 (91.000) Prec@5 100.000 (99.409) +2022-11-14 14:01:13,709 Epoch: [133][220/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0511 (0.0536) Prec@1 93.000 (91.087) Prec@5 100.000 (99.435) +2022-11-14 14:01:14,133 Epoch: [133][230/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0491 (0.0534) Prec@1 90.000 (91.042) Prec@5 100.000 (99.458) +2022-11-14 14:01:14,555 Epoch: [133][240/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0758 (0.0543) Prec@1 85.000 (90.800) Prec@5 99.000 (99.440) +2022-11-14 14:01:14,975 Epoch: [133][250/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0321 (0.0534) Prec@1 93.000 (90.885) Prec@5 99.000 (99.423) +2022-11-14 14:01:15,442 Epoch: [133][260/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0618 (0.0537) Prec@1 90.000 (90.852) Prec@5 100.000 (99.444) +2022-11-14 14:01:15,873 Epoch: [133][270/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0367 (0.0531) Prec@1 94.000 (90.964) Prec@5 100.000 (99.464) +2022-11-14 14:01:16,294 Epoch: [133][280/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0376 (0.0526) Prec@1 95.000 (91.103) Prec@5 100.000 (99.483) +2022-11-14 14:01:16,713 Epoch: [133][290/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0547 (0.0527) Prec@1 90.000 (91.067) Prec@5 100.000 (99.500) +2022-11-14 14:01:17,142 Epoch: [133][300/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0735 (0.0533) Prec@1 87.000 (90.935) Prec@5 100.000 (99.516) +2022-11-14 14:01:17,569 Epoch: [133][310/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0640 (0.0537) Prec@1 90.000 (90.906) Prec@5 98.000 (99.469) +2022-11-14 14:01:17,994 Epoch: [133][320/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0532 (0.0537) Prec@1 92.000 (90.939) Prec@5 99.000 (99.455) +2022-11-14 14:01:18,404 Epoch: [133][330/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0604 (0.0539) Prec@1 92.000 (90.971) Prec@5 98.000 (99.412) +2022-11-14 14:01:18,828 Epoch: [133][340/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0607 (0.0541) Prec@1 88.000 (90.886) Prec@5 100.000 (99.429) +2022-11-14 14:01:19,252 Epoch: [133][350/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0816 (0.0548) Prec@1 85.000 (90.722) Prec@5 99.000 (99.417) +2022-11-14 14:01:19,670 Epoch: [133][360/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0489 (0.0547) Prec@1 92.000 (90.757) Prec@5 100.000 (99.432) +2022-11-14 14:01:20,091 Epoch: [133][370/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0416 (0.0543) Prec@1 95.000 (90.868) Prec@5 100.000 (99.447) +2022-11-14 14:01:20,509 Epoch: [133][380/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0657 (0.0546) Prec@1 89.000 (90.821) Prec@5 100.000 (99.462) +2022-11-14 14:01:20,929 Epoch: [133][390/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0791 (0.0552) Prec@1 85.000 (90.675) Prec@5 99.000 (99.450) +2022-11-14 14:01:21,346 Epoch: [133][400/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0369 (0.0548) Prec@1 95.000 (90.780) Prec@5 100.000 (99.463) +2022-11-14 14:01:21,772 Epoch: [133][410/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0724 (0.0552) Prec@1 88.000 (90.714) Prec@5 100.000 (99.476) +2022-11-14 14:01:22,276 Epoch: [133][420/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0388 (0.0548) Prec@1 95.000 (90.814) Prec@5 100.000 (99.488) +2022-11-14 14:01:22,785 Epoch: [133][430/500] Time 0.056 (0.038) Data 0.002 (0.002) Loss 0.0523 (0.0548) Prec@1 90.000 (90.795) Prec@5 100.000 (99.500) +2022-11-14 14:01:23,211 Epoch: [133][440/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0483 (0.0546) Prec@1 90.000 (90.778) Prec@5 100.000 (99.511) +2022-11-14 14:01:23,710 Epoch: [133][450/500] Time 0.059 (0.038) Data 0.003 (0.002) Loss 0.0359 (0.0542) Prec@1 93.000 (90.826) Prec@5 100.000 (99.522) +2022-11-14 14:01:24,149 Epoch: [133][460/500] Time 0.060 (0.038) Data 0.002 (0.002) Loss 0.0395 (0.0539) Prec@1 91.000 (90.830) Prec@5 100.000 (99.532) +2022-11-14 14:01:24,699 Epoch: [133][470/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0699 (0.0542) Prec@1 90.000 (90.812) Prec@5 100.000 (99.542) +2022-11-14 14:01:25,150 Epoch: [133][480/500] Time 0.057 (0.038) Data 0.002 (0.002) Loss 0.0400 (0.0539) Prec@1 94.000 (90.878) Prec@5 99.000 (99.531) +2022-11-14 14:01:25,681 Epoch: [133][490/500] Time 0.051 (0.039) Data 0.002 (0.002) Loss 0.0880 (0.0546) Prec@1 84.000 (90.740) Prec@5 100.000 (99.540) +2022-11-14 14:01:26,055 Epoch: [133][499/500] Time 0.039 (0.039) Data 0.002 (0.002) Loss 0.0330 (0.0542) Prec@1 93.000 (90.784) Prec@5 99.000 (99.529) +2022-11-14 14:01:26,359 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0616 (0.0616) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:26,369 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0672 (0.0644) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:26,383 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0975 (0.0755) Prec@1 83.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 14:01:26,398 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0755 (0.0755) Prec@1 89.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:01:26,410 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0854 (0.0775) Prec@1 87.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 14:01:26,422 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0390 (0.0711) Prec@1 93.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 14:01:26,434 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0755 (0.0717) Prec@1 89.000 (88.714) Prec@5 100.000 (99.857) +2022-11-14 14:01:26,447 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0778 (0.0725) Prec@1 88.000 (88.625) Prec@5 99.000 (99.750) +2022-11-14 14:01:26,458 Test: [8/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0852 (0.0739) Prec@1 88.000 (88.556) Prec@5 98.000 (99.556) +2022-11-14 14:01:26,470 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0704 (0.0735) Prec@1 85.000 (88.200) Prec@5 98.000 (99.400) +2022-11-14 14:01:26,483 Test: [10/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0605 (0.0723) Prec@1 92.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 14:01:26,495 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0831 (0.0732) Prec@1 86.000 (88.333) Prec@5 99.000 (99.417) +2022-11-14 14:01:26,510 Test: [12/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0566 (0.0720) Prec@1 91.000 (88.538) Prec@5 100.000 (99.462) +2022-11-14 14:01:26,525 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0607 (0.0712) Prec@1 89.000 (88.571) Prec@5 100.000 (99.500) +2022-11-14 14:01:26,538 Test: [14/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0931 (0.0726) Prec@1 87.000 (88.467) Prec@5 100.000 (99.533) +2022-11-14 14:01:26,550 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0937 (0.0739) Prec@1 86.000 (88.312) Prec@5 100.000 (99.562) +2022-11-14 14:01:26,561 Test: [16/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0546 (0.0728) Prec@1 92.000 (88.529) Prec@5 98.000 (99.471) +2022-11-14 14:01:26,573 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.0739) Prec@1 81.000 (88.111) Prec@5 99.000 (99.444) +2022-11-14 14:01:26,583 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0748) Prec@1 83.000 (87.842) Prec@5 99.000 (99.421) +2022-11-14 14:01:26,594 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0752) Prec@1 87.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 14:01:26,604 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0751) Prec@1 88.000 (87.810) Prec@5 99.000 (99.381) +2022-11-14 14:01:26,613 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0590 (0.0744) Prec@1 90.000 (87.909) Prec@5 100.000 (99.409) +2022-11-14 14:01:26,621 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0751) Prec@1 86.000 (87.826) Prec@5 97.000 (99.304) +2022-11-14 14:01:26,630 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0609 (0.0745) Prec@1 90.000 (87.917) Prec@5 100.000 (99.333) +2022-11-14 14:01:26,641 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0750) Prec@1 89.000 (87.960) Prec@5 99.000 (99.320) +2022-11-14 14:01:26,651 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0755) Prec@1 84.000 (87.808) Prec@5 97.000 (99.231) +2022-11-14 14:01:26,660 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0597 (0.0749) Prec@1 91.000 (87.926) Prec@5 100.000 (99.259) +2022-11-14 14:01:26,670 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.0750) Prec@1 84.000 (87.786) Prec@5 99.000 (99.250) +2022-11-14 14:01:26,679 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0752) Prec@1 87.000 (87.759) Prec@5 99.000 (99.241) +2022-11-14 14:01:26,689 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0539 (0.0745) Prec@1 90.000 (87.833) Prec@5 99.000 (99.233) +2022-11-14 14:01:26,698 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0745) Prec@1 87.000 (87.806) Prec@5 100.000 (99.258) +2022-11-14 14:01:26,708 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0744) Prec@1 87.000 (87.781) Prec@5 99.000 (99.250) +2022-11-14 14:01:26,718 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0745) Prec@1 87.000 (87.758) Prec@5 100.000 (99.273) +2022-11-14 14:01:26,728 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1103 (0.0755) Prec@1 79.000 (87.500) Prec@5 99.000 (99.265) +2022-11-14 14:01:26,738 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0755) Prec@1 87.000 (87.486) Prec@5 100.000 (99.286) +2022-11-14 14:01:26,749 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0753) Prec@1 90.000 (87.556) Prec@5 99.000 (99.278) +2022-11-14 14:01:26,762 Test: [36/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0753) Prec@1 88.000 (87.568) Prec@5 99.000 (99.270) +2022-11-14 14:01:26,774 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0758) Prec@1 84.000 (87.474) Prec@5 100.000 (99.289) +2022-11-14 14:01:26,784 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0754) Prec@1 89.000 (87.513) Prec@5 100.000 (99.308) +2022-11-14 14:01:26,793 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0754) Prec@1 90.000 (87.575) Prec@5 99.000 (99.300) +2022-11-14 14:01:26,806 Test: [40/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0951 (0.0759) Prec@1 87.000 (87.561) Prec@5 98.000 (99.268) +2022-11-14 14:01:26,819 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0758) Prec@1 88.000 (87.571) Prec@5 99.000 (99.262) +2022-11-14 14:01:26,828 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0753) Prec@1 91.000 (87.651) Prec@5 98.000 (99.233) +2022-11-14 14:01:26,838 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0752) Prec@1 88.000 (87.659) Prec@5 99.000 (99.227) +2022-11-14 14:01:26,851 Test: [44/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0754) Prec@1 86.000 (87.622) Prec@5 100.000 (99.244) +2022-11-14 14:01:26,864 Test: [45/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0955 (0.0759) Prec@1 84.000 (87.543) Prec@5 99.000 (99.239) +2022-11-14 14:01:26,874 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0758) Prec@1 87.000 (87.532) Prec@5 99.000 (99.234) +2022-11-14 14:01:26,885 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0758) Prec@1 88.000 (87.542) Prec@5 99.000 (99.229) +2022-11-14 14:01:26,898 Test: [48/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0496 (0.0753) Prec@1 91.000 (87.612) Prec@5 98.000 (99.204) +2022-11-14 14:01:26,911 Test: [49/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1109 (0.0760) Prec@1 83.000 (87.520) Prec@5 100.000 (99.220) +2022-11-14 14:01:26,921 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.0760) Prec@1 88.000 (87.529) Prec@5 99.000 (99.216) +2022-11-14 14:01:26,931 Test: [51/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0827 (0.0762) Prec@1 84.000 (87.462) Prec@5 100.000 (99.231) +2022-11-14 14:01:26,944 Test: [52/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0545 (0.0758) Prec@1 89.000 (87.491) Prec@5 100.000 (99.245) +2022-11-14 14:01:26,956 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0758) Prec@1 84.000 (87.426) Prec@5 100.000 (99.259) +2022-11-14 14:01:26,965 Test: [54/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0759) Prec@1 86.000 (87.400) Prec@5 100.000 (99.273) +2022-11-14 14:01:26,974 Test: [55/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0762) Prec@1 85.000 (87.357) Prec@5 100.000 (99.286) +2022-11-14 14:01:26,987 Test: [56/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0763) Prec@1 86.000 (87.333) Prec@5 100.000 (99.298) +2022-11-14 14:01:26,999 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0759) Prec@1 92.000 (87.414) Prec@5 100.000 (99.310) +2022-11-14 14:01:27,008 Test: [58/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0967 (0.0762) Prec@1 81.000 (87.305) Prec@5 98.000 (99.288) +2022-11-14 14:01:27,018 Test: [59/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0763) Prec@1 86.000 (87.283) Prec@5 100.000 (99.300) +2022-11-14 14:01:27,031 Test: [60/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0764) Prec@1 86.000 (87.262) Prec@5 99.000 (99.295) +2022-11-14 14:01:27,044 Test: [61/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0765) Prec@1 86.000 (87.242) Prec@5 99.000 (99.290) +2022-11-14 14:01:27,054 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0766) Prec@1 88.000 (87.254) Prec@5 100.000 (99.302) +2022-11-14 14:01:27,063 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0476 (0.0761) Prec@1 94.000 (87.359) Prec@5 100.000 (99.312) +2022-11-14 14:01:27,076 Test: [64/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0999 (0.0765) Prec@1 83.000 (87.292) Prec@5 99.000 (99.308) +2022-11-14 14:01:27,088 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0766) Prec@1 83.000 (87.227) Prec@5 99.000 (99.303) +2022-11-14 14:01:27,097 Test: [66/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0537 (0.0762) Prec@1 91.000 (87.284) Prec@5 99.000 (99.299) +2022-11-14 14:01:27,107 Test: [67/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0761) Prec@1 90.000 (87.324) Prec@5 98.000 (99.279) +2022-11-14 14:01:27,120 Test: [68/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0760) Prec@1 86.000 (87.304) Prec@5 99.000 (99.275) +2022-11-14 14:01:27,131 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0761) Prec@1 86.000 (87.286) Prec@5 99.000 (99.271) +2022-11-14 14:01:27,140 Test: [70/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0762) Prec@1 86.000 (87.268) Prec@5 100.000 (99.282) +2022-11-14 14:01:27,150 Test: [71/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0761) Prec@1 90.000 (87.306) Prec@5 100.000 (99.292) +2022-11-14 14:01:27,160 Test: [72/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0558 (0.0758) Prec@1 91.000 (87.356) Prec@5 99.000 (99.288) +2022-11-14 14:01:27,169 Test: [73/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0586 (0.0756) Prec@1 89.000 (87.378) Prec@5 100.000 (99.297) +2022-11-14 14:01:27,177 Test: [74/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1091 (0.0760) Prec@1 81.000 (87.293) Prec@5 98.000 (99.280) +2022-11-14 14:01:27,188 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0760) Prec@1 88.000 (87.303) Prec@5 99.000 (99.276) +2022-11-14 14:01:27,198 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0761) Prec@1 84.000 (87.260) Prec@5 99.000 (99.273) +2022-11-14 14:01:27,208 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0762) Prec@1 86.000 (87.244) Prec@5 98.000 (99.256) +2022-11-14 14:01:27,217 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0760) Prec@1 89.000 (87.266) Prec@5 99.000 (99.253) +2022-11-14 14:01:27,227 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0762) Prec@1 86.000 (87.250) Prec@5 99.000 (99.250) +2022-11-14 14:01:27,237 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0762) Prec@1 88.000 (87.259) Prec@5 100.000 (99.259) +2022-11-14 14:01:27,246 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0763) Prec@1 87.000 (87.256) Prec@5 100.000 (99.268) +2022-11-14 14:01:27,255 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0763) Prec@1 86.000 (87.241) Prec@5 99.000 (99.265) +2022-11-14 14:01:27,265 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0763) Prec@1 85.000 (87.214) Prec@5 100.000 (99.274) +2022-11-14 14:01:27,274 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0764) Prec@1 85.000 (87.188) Prec@5 99.000 (99.271) +2022-11-14 14:01:27,283 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0766) Prec@1 86.000 (87.174) Prec@5 100.000 (99.279) +2022-11-14 14:01:27,292 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0764) Prec@1 93.000 (87.241) Prec@5 99.000 (99.276) +2022-11-14 14:01:27,302 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0763) Prec@1 91.000 (87.284) Prec@5 99.000 (99.273) +2022-11-14 14:01:27,312 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0762) Prec@1 84.000 (87.247) Prec@5 100.000 (99.281) +2022-11-14 14:01:27,322 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0764) Prec@1 86.000 (87.233) Prec@5 99.000 (99.278) +2022-11-14 14:01:27,332 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0763) Prec@1 91.000 (87.275) Prec@5 100.000 (99.286) +2022-11-14 14:01:27,342 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0459 (0.0760) Prec@1 92.000 (87.326) Prec@5 100.000 (99.293) +2022-11-14 14:01:27,352 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0762) Prec@1 84.000 (87.290) Prec@5 100.000 (99.301) +2022-11-14 14:01:27,362 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0762) Prec@1 86.000 (87.277) Prec@5 100.000 (99.309) +2022-11-14 14:01:27,371 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0763) Prec@1 86.000 (87.263) Prec@5 100.000 (99.316) +2022-11-14 14:01:27,381 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0762) Prec@1 88.000 (87.271) Prec@5 99.000 (99.312) +2022-11-14 14:01:27,391 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0760) Prec@1 89.000 (87.289) Prec@5 97.000 (99.289) +2022-11-14 14:01:27,401 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0762) Prec@1 84.000 (87.255) Prec@5 100.000 (99.296) +2022-11-14 14:01:27,411 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0764) Prec@1 84.000 (87.222) Prec@5 99.000 (99.293) +2022-11-14 14:01:27,420 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0766) Prec@1 85.000 (87.200) Prec@5 99.000 (99.290) +2022-11-14 14:01:27,478 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:01:27,839 Epoch: [134][0/500] Time 0.029 (0.029) Data 0.256 (0.256) Loss 0.0251 (0.0251) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:28,081 Epoch: [134][10/500] Time 0.017 (0.022) Data 0.002 (0.025) Loss 0.0513 (0.0382) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:01:28,366 Epoch: [134][20/500] Time 0.034 (0.024) Data 0.002 (0.014) Loss 0.0508 (0.0424) Prec@1 92.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 14:01:28,781 Epoch: [134][30/500] Time 0.023 (0.028) Data 0.002 (0.010) Loss 0.0445 (0.0429) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:29,147 Epoch: [134][40/500] Time 0.030 (0.029) Data 0.002 (0.008) Loss 0.0600 (0.0464) Prec@1 91.000 (92.600) Prec@5 97.000 (99.400) +2022-11-14 14:01:29,496 Epoch: [134][50/500] Time 0.034 (0.030) Data 0.002 (0.007) Loss 0.0407 (0.0454) Prec@1 93.000 (92.667) Prec@5 99.000 (99.333) +2022-11-14 14:01:29,837 Epoch: [134][60/500] Time 0.033 (0.030) Data 0.001 (0.006) Loss 0.0568 (0.0470) Prec@1 88.000 (92.000) Prec@5 100.000 (99.429) +2022-11-14 14:01:30,228 Epoch: [134][70/500] Time 0.030 (0.031) Data 0.002 (0.006) Loss 0.0353 (0.0456) Prec@1 95.000 (92.375) Prec@5 100.000 (99.500) +2022-11-14 14:01:30,564 Epoch: [134][80/500] Time 0.029 (0.031) Data 0.002 (0.005) Loss 0.0826 (0.0497) Prec@1 84.000 (91.444) Prec@5 98.000 (99.333) +2022-11-14 14:01:30,929 Epoch: [134][90/500] Time 0.045 (0.031) Data 0.002 (0.005) Loss 0.1006 (0.0548) Prec@1 86.000 (90.900) Prec@5 100.000 (99.400) +2022-11-14 14:01:31,269 Epoch: [134][100/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0418 (0.0536) Prec@1 92.000 (91.000) Prec@5 100.000 (99.455) +2022-11-14 14:01:31,626 Epoch: [134][110/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0701 (0.0550) Prec@1 86.000 (90.583) Prec@5 99.000 (99.417) +2022-11-14 14:01:32,037 Epoch: [134][120/500] Time 0.059 (0.031) Data 0.002 (0.004) Loss 0.0655 (0.0558) Prec@1 88.000 (90.385) Prec@5 99.000 (99.385) +2022-11-14 14:01:32,471 Epoch: [134][130/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.0257 (0.0536) Prec@1 96.000 (90.786) Prec@5 100.000 (99.429) +2022-11-14 14:01:32,900 Epoch: [134][140/500] Time 0.046 (0.032) Data 0.002 (0.004) Loss 0.0561 (0.0538) Prec@1 92.000 (90.867) Prec@5 100.000 (99.467) +2022-11-14 14:01:33,242 Epoch: [134][150/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0649 (0.0545) Prec@1 89.000 (90.750) Prec@5 99.000 (99.438) +2022-11-14 14:01:33,648 Epoch: [134][160/500] Time 0.040 (0.032) Data 0.002 (0.004) Loss 0.0917 (0.0567) Prec@1 83.000 (90.294) Prec@5 100.000 (99.471) +2022-11-14 14:01:34,096 Epoch: [134][170/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0545 (0.0566) Prec@1 92.000 (90.389) Prec@5 97.000 (99.333) +2022-11-14 14:01:34,530 Epoch: [134][180/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0545 (0.0565) Prec@1 91.000 (90.421) Prec@5 99.000 (99.316) +2022-11-14 14:01:34,920 Epoch: [134][190/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0479 (0.0560) Prec@1 91.000 (90.450) Prec@5 100.000 (99.350) +2022-11-14 14:01:35,407 Epoch: [134][200/500] Time 0.052 (0.034) Data 0.002 (0.003) Loss 0.0685 (0.0566) Prec@1 91.000 (90.476) Prec@5 100.000 (99.381) +2022-11-14 14:01:36,217 Epoch: [134][210/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0540 (0.0565) Prec@1 92.000 (90.545) Prec@5 100.000 (99.409) +2022-11-14 14:01:37,067 Epoch: [134][220/500] Time 0.097 (0.037) Data 0.002 (0.003) Loss 0.0552 (0.0564) Prec@1 89.000 (90.478) Prec@5 100.000 (99.435) +2022-11-14 14:01:38,015 Epoch: [134][230/500] Time 0.090 (0.039) Data 0.002 (0.003) Loss 0.0613 (0.0566) Prec@1 90.000 (90.458) Prec@5 100.000 (99.458) +2022-11-14 14:01:38,788 Epoch: [134][240/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0730 (0.0573) Prec@1 89.000 (90.400) Prec@5 100.000 (99.480) +2022-11-14 14:01:39,635 Epoch: [134][250/500] Time 0.062 (0.042) Data 0.002 (0.003) Loss 0.0488 (0.0570) Prec@1 90.000 (90.385) Prec@5 100.000 (99.500) +2022-11-14 14:01:40,418 Epoch: [134][260/500] Time 0.031 (0.043) Data 0.002 (0.003) Loss 0.0400 (0.0563) Prec@1 95.000 (90.556) Prec@5 100.000 (99.519) +2022-11-14 14:01:40,790 Epoch: [134][270/500] Time 0.032 (0.043) Data 0.002 (0.003) Loss 0.0616 (0.0565) Prec@1 90.000 (90.536) Prec@5 100.000 (99.536) +2022-11-14 14:01:41,201 Epoch: [134][280/500] Time 0.032 (0.043) Data 0.002 (0.003) Loss 0.0579 (0.0566) Prec@1 90.000 (90.517) Prec@5 100.000 (99.552) +2022-11-14 14:01:41,602 Epoch: [134][290/500] Time 0.033 (0.042) Data 0.002 (0.003) Loss 0.0745 (0.0572) Prec@1 89.000 (90.467) Prec@5 99.000 (99.533) +2022-11-14 14:01:41,980 Epoch: [134][300/500] Time 0.034 (0.042) Data 0.002 (0.003) Loss 0.0478 (0.0569) Prec@1 94.000 (90.581) Prec@5 100.000 (99.548) +2022-11-14 14:01:42,372 Epoch: [134][310/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0274 (0.0560) Prec@1 95.000 (90.719) Prec@5 100.000 (99.562) +2022-11-14 14:01:42,742 Epoch: [134][320/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0476 (0.0557) Prec@1 90.000 (90.697) Prec@5 99.000 (99.545) +2022-11-14 14:01:43,153 Epoch: [134][330/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0749 (0.0563) Prec@1 86.000 (90.559) Prec@5 99.000 (99.529) +2022-11-14 14:01:43,631 Epoch: [134][340/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0410 (0.0558) Prec@1 94.000 (90.657) Prec@5 100.000 (99.543) +2022-11-14 14:01:44,014 Epoch: [134][350/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0572 (0.0559) Prec@1 92.000 (90.694) Prec@5 100.000 (99.556) +2022-11-14 14:01:44,452 Epoch: [134][360/500] Time 0.025 (0.041) Data 0.002 (0.003) Loss 0.0828 (0.0566) Prec@1 85.000 (90.541) Prec@5 98.000 (99.514) +2022-11-14 14:01:44,896 Epoch: [134][370/500] Time 0.059 (0.041) Data 0.002 (0.003) Loss 0.0338 (0.0560) Prec@1 96.000 (90.684) Prec@5 99.000 (99.500) +2022-11-14 14:01:45,258 Epoch: [134][380/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0486 (0.0558) Prec@1 92.000 (90.718) Prec@5 100.000 (99.513) +2022-11-14 14:01:45,637 Epoch: [134][390/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0418 (0.0555) Prec@1 94.000 (90.800) Prec@5 99.000 (99.500) +2022-11-14 14:01:46,062 Epoch: [134][400/500] Time 0.030 (0.041) Data 0.002 (0.003) Loss 0.0399 (0.0551) Prec@1 92.000 (90.829) Prec@5 100.000 (99.512) +2022-11-14 14:01:46,427 Epoch: [134][410/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0765 (0.0556) Prec@1 85.000 (90.690) Prec@5 100.000 (99.524) +2022-11-14 14:01:46,821 Epoch: [134][420/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.0484 (0.0554) Prec@1 94.000 (90.767) Prec@5 98.000 (99.488) +2022-11-14 14:01:47,240 Epoch: [134][430/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0424 (0.0551) Prec@1 94.000 (90.841) Prec@5 99.000 (99.477) +2022-11-14 14:01:47,626 Epoch: [134][440/500] Time 0.036 (0.040) Data 0.001 (0.003) Loss 0.0491 (0.0550) Prec@1 93.000 (90.889) Prec@5 100.000 (99.489) +2022-11-14 14:01:48,013 Epoch: [134][450/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0603 (0.0551) Prec@1 91.000 (90.891) Prec@5 98.000 (99.457) +2022-11-14 14:01:48,425 Epoch: [134][460/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0835 (0.0557) Prec@1 87.000 (90.809) Prec@5 100.000 (99.468) +2022-11-14 14:01:48,931 Epoch: [134][470/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0718 (0.0560) Prec@1 88.000 (90.750) Prec@5 100.000 (99.479) +2022-11-14 14:01:49,359 Epoch: [134][480/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0486 (0.0559) Prec@1 92.000 (90.776) Prec@5 100.000 (99.490) +2022-11-14 14:01:49,722 Epoch: [134][490/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0599 (0.0560) Prec@1 90.000 (90.760) Prec@5 99.000 (99.480) +2022-11-14 14:01:50,070 Epoch: [134][499/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.0751 (0.0563) Prec@1 86.000 (90.667) Prec@5 100.000 (99.490) +2022-11-14 14:01:50,383 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0632) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:50,394 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0665) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:01:50,404 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0717) Prec@1 85.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:01:50,418 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0715) Prec@1 89.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 14:01:50,432 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0731) Prec@1 88.000 (87.400) Prec@5 100.000 (99.800) +2022-11-14 14:01:50,447 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0343 (0.0666) Prec@1 94.000 (88.500) Prec@5 100.000 (99.833) +2022-11-14 14:01:50,463 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0661) Prec@1 90.000 (88.714) Prec@5 100.000 (99.857) +2022-11-14 14:01:50,480 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0670) Prec@1 90.000 (88.875) Prec@5 99.000 (99.750) +2022-11-14 14:01:50,496 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0685) Prec@1 87.000 (88.667) Prec@5 100.000 (99.778) +2022-11-14 14:01:50,513 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0699) Prec@1 87.000 (88.500) Prec@5 99.000 (99.700) +2022-11-14 14:01:50,530 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0699) Prec@1 87.000 (88.364) Prec@5 100.000 (99.727) +2022-11-14 14:01:50,546 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0726) Prec@1 83.000 (87.917) Prec@5 99.000 (99.667) +2022-11-14 14:01:50,563 Test: [12/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0731) Prec@1 86.000 (87.769) Prec@5 100.000 (99.692) +2022-11-14 14:01:50,580 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0732) Prec@1 87.000 (87.714) Prec@5 99.000 (99.643) +2022-11-14 14:01:50,596 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0733) Prec@1 89.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 14:01:50,609 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0735) Prec@1 88.000 (87.812) Prec@5 100.000 (99.625) +2022-11-14 14:01:50,621 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0732) Prec@1 89.000 (87.882) Prec@5 99.000 (99.588) +2022-11-14 14:01:50,632 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0749) Prec@1 83.000 (87.611) Prec@5 100.000 (99.611) +2022-11-14 14:01:50,645 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0750) Prec@1 87.000 (87.579) Prec@5 98.000 (99.526) +2022-11-14 14:01:50,657 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0762) Prec@1 82.000 (87.300) Prec@5 100.000 (99.550) +2022-11-14 14:01:50,668 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0758) Prec@1 90.000 (87.429) Prec@5 100.000 (99.571) +2022-11-14 14:01:50,680 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0762) Prec@1 86.000 (87.364) Prec@5 98.000 (99.500) +2022-11-14 14:01:50,693 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1157 (0.0779) Prec@1 82.000 (87.130) Prec@5 97.000 (99.391) +2022-11-14 14:01:50,705 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0784) Prec@1 85.000 (87.042) Prec@5 100.000 (99.417) +2022-11-14 14:01:50,718 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0783) Prec@1 89.000 (87.120) Prec@5 98.000 (99.360) +2022-11-14 14:01:50,730 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0786) Prec@1 85.000 (87.038) Prec@5 98.000 (99.308) +2022-11-14 14:01:50,744 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0782) Prec@1 89.000 (87.111) Prec@5 100.000 (99.333) +2022-11-14 14:01:50,760 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0777) Prec@1 90.000 (87.214) Prec@5 100.000 (99.357) +2022-11-14 14:01:50,771 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0776) Prec@1 87.000 (87.207) Prec@5 98.000 (99.310) +2022-11-14 14:01:50,782 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0774) Prec@1 89.000 (87.267) Prec@5 99.000 (99.300) +2022-11-14 14:01:50,792 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0776) Prec@1 84.000 (87.161) Prec@5 97.000 (99.226) +2022-11-14 14:01:50,806 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0772) Prec@1 89.000 (87.219) Prec@5 100.000 (99.250) +2022-11-14 14:01:50,819 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0773) Prec@1 86.000 (87.182) Prec@5 99.000 (99.242) +2022-11-14 14:01:50,833 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0775) Prec@1 83.000 (87.059) Prec@5 100.000 (99.265) +2022-11-14 14:01:50,846 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0772) Prec@1 90.000 (87.143) Prec@5 98.000 (99.229) +2022-11-14 14:01:50,859 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0769) Prec@1 89.000 (87.194) Prec@5 99.000 (99.222) +2022-11-14 14:01:50,874 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0769) Prec@1 88.000 (87.216) Prec@5 98.000 (99.189) +2022-11-14 14:01:50,888 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0776) Prec@1 82.000 (87.079) Prec@5 100.000 (99.211) +2022-11-14 14:01:50,901 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0768) Prec@1 94.000 (87.256) Prec@5 100.000 (99.231) +2022-11-14 14:01:50,915 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0767) Prec@1 86.000 (87.225) Prec@5 100.000 (99.250) +2022-11-14 14:01:50,929 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0776) Prec@1 82.000 (87.098) Prec@5 98.000 (99.220) +2022-11-14 14:01:50,947 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0776) Prec@1 87.000 (87.095) Prec@5 98.000 (99.190) +2022-11-14 14:01:50,961 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0775) Prec@1 88.000 (87.116) Prec@5 99.000 (99.186) +2022-11-14 14:01:50,975 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0774) Prec@1 87.000 (87.114) Prec@5 99.000 (99.182) +2022-11-14 14:01:50,992 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0775) Prec@1 86.000 (87.089) Prec@5 98.000 (99.156) +2022-11-14 14:01:51,010 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0781) Prec@1 81.000 (86.957) Prec@5 99.000 (99.152) +2022-11-14 14:01:51,028 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0780) Prec@1 88.000 (86.979) Prec@5 99.000 (99.149) +2022-11-14 14:01:51,048 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1166 (0.0788) Prec@1 79.000 (86.812) Prec@5 99.000 (99.146) +2022-11-14 14:01:51,066 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0342 (0.0779) Prec@1 93.000 (86.939) Prec@5 100.000 (99.163) +2022-11-14 14:01:51,087 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0784) Prec@1 85.000 (86.900) Prec@5 100.000 (99.180) +2022-11-14 14:01:51,106 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0780) Prec@1 91.000 (86.980) Prec@5 100.000 (99.196) +2022-11-14 14:01:51,123 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0783) Prec@1 85.000 (86.942) Prec@5 100.000 (99.212) +2022-11-14 14:01:51,140 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0780) Prec@1 89.000 (86.981) Prec@5 100.000 (99.226) +2022-11-14 14:01:51,157 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0779) Prec@1 87.000 (86.981) Prec@5 100.000 (99.241) +2022-11-14 14:01:51,174 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0779) Prec@1 88.000 (87.000) Prec@5 99.000 (99.236) +2022-11-14 14:01:51,193 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0778) Prec@1 90.000 (87.054) Prec@5 99.000 (99.232) +2022-11-14 14:01:51,212 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0776) Prec@1 91.000 (87.123) Prec@5 99.000 (99.228) +2022-11-14 14:01:51,229 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0777) Prec@1 85.000 (87.086) Prec@5 100.000 (99.241) +2022-11-14 14:01:51,242 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0781) Prec@1 81.000 (86.983) Prec@5 100.000 (99.254) +2022-11-14 14:01:51,252 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0783) Prec@1 84.000 (86.933) Prec@5 99.000 (99.250) +2022-11-14 14:01:51,265 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0784) Prec@1 85.000 (86.902) Prec@5 100.000 (99.262) +2022-11-14 14:01:51,276 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0781) Prec@1 91.000 (86.968) Prec@5 100.000 (99.274) +2022-11-14 14:01:51,287 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0781) Prec@1 85.000 (86.937) Prec@5 99.000 (99.270) +2022-11-14 14:01:51,299 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0777) Prec@1 92.000 (87.016) Prec@5 100.000 (99.281) +2022-11-14 14:01:51,311 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0779) Prec@1 83.000 (86.954) Prec@5 99.000 (99.277) +2022-11-14 14:01:51,323 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0780) Prec@1 86.000 (86.939) Prec@5 98.000 (99.258) +2022-11-14 14:01:51,337 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0775) Prec@1 93.000 (87.030) Prec@5 100.000 (99.269) +2022-11-14 14:01:51,351 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0775) Prec@1 88.000 (87.044) Prec@5 100.000 (99.279) +2022-11-14 14:01:51,365 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0774) Prec@1 88.000 (87.058) Prec@5 99.000 (99.275) +2022-11-14 14:01:51,379 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0776) Prec@1 88.000 (87.071) Prec@5 100.000 (99.286) +2022-11-14 14:01:51,393 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0776) Prec@1 87.000 (87.070) Prec@5 99.000 (99.282) +2022-11-14 14:01:51,407 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0773) Prec@1 91.000 (87.125) Prec@5 100.000 (99.292) +2022-11-14 14:01:51,420 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0770) Prec@1 92.000 (87.192) Prec@5 100.000 (99.301) +2022-11-14 14:01:51,434 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0767) Prec@1 90.000 (87.230) Prec@5 100.000 (99.311) +2022-11-14 14:01:51,449 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0770) Prec@1 79.000 (87.120) Prec@5 100.000 (99.320) +2022-11-14 14:01:51,463 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0768) Prec@1 90.000 (87.158) Prec@5 99.000 (99.316) +2022-11-14 14:01:51,476 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0770) Prec@1 84.000 (87.117) Prec@5 99.000 (99.312) +2022-11-14 14:01:51,490 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0773) Prec@1 86.000 (87.103) Prec@5 97.000 (99.282) +2022-11-14 14:01:51,505 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0771) Prec@1 88.000 (87.114) Prec@5 99.000 (99.278) +2022-11-14 14:01:51,517 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0773) Prec@1 83.000 (87.062) Prec@5 100.000 (99.287) +2022-11-14 14:01:51,532 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0774) Prec@1 87.000 (87.062) Prec@5 96.000 (99.247) +2022-11-14 14:01:51,548 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0775) Prec@1 86.000 (87.049) Prec@5 100.000 (99.256) +2022-11-14 14:01:51,563 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0777) Prec@1 81.000 (86.976) Prec@5 100.000 (99.265) +2022-11-14 14:01:51,576 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0776) Prec@1 87.000 (86.976) Prec@5 100.000 (99.274) +2022-11-14 14:01:51,589 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0778) Prec@1 81.000 (86.906) Prec@5 100.000 (99.282) +2022-11-14 14:01:51,601 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0780) Prec@1 84.000 (86.872) Prec@5 99.000 (99.279) +2022-11-14 14:01:51,617 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0781) Prec@1 86.000 (86.862) Prec@5 98.000 (99.264) +2022-11-14 14:01:51,632 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0780) Prec@1 89.000 (86.886) Prec@5 100.000 (99.273) +2022-11-14 14:01:51,645 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0778) Prec@1 88.000 (86.899) Prec@5 99.000 (99.270) +2022-11-14 14:01:51,657 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0778) Prec@1 90.000 (86.933) Prec@5 100.000 (99.278) +2022-11-14 14:01:51,672 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0776) Prec@1 89.000 (86.956) Prec@5 100.000 (99.286) +2022-11-14 14:01:51,686 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0773) Prec@1 92.000 (87.011) Prec@5 100.000 (99.293) +2022-11-14 14:01:51,697 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0774) Prec@1 87.000 (87.011) Prec@5 100.000 (99.301) +2022-11-14 14:01:51,708 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0774) Prec@1 87.000 (87.011) Prec@5 99.000 (99.298) +2022-11-14 14:01:51,721 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0772) Prec@1 89.000 (87.032) Prec@5 100.000 (99.305) +2022-11-14 14:01:51,735 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0771) Prec@1 90.000 (87.062) Prec@5 99.000 (99.302) +2022-11-14 14:01:51,748 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0770) Prec@1 90.000 (87.093) Prec@5 99.000 (99.299) +2022-11-14 14:01:51,762 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0771) Prec@1 84.000 (87.061) Prec@5 99.000 (99.296) +2022-11-14 14:01:51,776 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0773) Prec@1 85.000 (87.040) Prec@5 99.000 (99.293) +2022-11-14 14:01:51,790 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0774) Prec@1 87.000 (87.040) Prec@5 100.000 (99.300) +2022-11-14 14:01:51,861 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:01:52,166 Epoch: [135][0/500] Time 0.024 (0.024) Data 0.219 (0.219) Loss 0.0526 (0.0526) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:01:52,453 Epoch: [135][10/500] Time 0.028 (0.025) Data 0.002 (0.022) Loss 0.0467 (0.0496) Prec@1 90.000 (92.000) Prec@5 99.000 (99.500) +2022-11-14 14:01:52,723 Epoch: [135][20/500] Time 0.019 (0.025) Data 0.001 (0.012) Loss 0.0597 (0.0530) Prec@1 91.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:01:53,063 Epoch: [135][30/500] Time 0.049 (0.026) Data 0.001 (0.009) Loss 0.0306 (0.0474) Prec@1 96.000 (92.750) Prec@5 100.000 (99.750) +2022-11-14 14:01:53,529 Epoch: [135][40/500] Time 0.044 (0.030) Data 0.002 (0.007) Loss 0.0648 (0.0509) Prec@1 88.000 (91.800) Prec@5 99.000 (99.600) +2022-11-14 14:01:54,094 Epoch: [135][50/500] Time 0.094 (0.033) Data 0.002 (0.006) Loss 0.0506 (0.0508) Prec@1 91.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:01:54,548 Epoch: [135][60/500] Time 0.044 (0.034) Data 0.002 (0.005) Loss 0.0532 (0.0512) Prec@1 89.000 (91.286) Prec@5 99.000 (99.571) +2022-11-14 14:01:55,010 Epoch: [135][70/500] Time 0.043 (0.035) Data 0.002 (0.005) Loss 0.0685 (0.0533) Prec@1 89.000 (91.000) Prec@5 100.000 (99.625) +2022-11-14 14:01:55,566 Epoch: [135][80/500] Time 0.090 (0.037) Data 0.002 (0.005) Loss 0.0681 (0.0550) Prec@1 88.000 (90.667) Prec@5 100.000 (99.667) +2022-11-14 14:01:56,023 Epoch: [135][90/500] Time 0.045 (0.037) Data 0.002 (0.004) Loss 0.0519 (0.0547) Prec@1 91.000 (90.700) Prec@5 99.000 (99.600) +2022-11-14 14:01:56,488 Epoch: [135][100/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0693 (0.0560) Prec@1 89.000 (90.545) Prec@5 100.000 (99.636) +2022-11-14 14:01:57,138 Epoch: [135][110/500] Time 0.043 (0.040) Data 0.002 (0.004) Loss 0.0472 (0.0553) Prec@1 90.000 (90.500) Prec@5 100.000 (99.667) +2022-11-14 14:01:57,673 Epoch: [135][120/500] Time 0.043 (0.040) Data 0.002 (0.004) Loss 0.0835 (0.0574) Prec@1 87.000 (90.231) Prec@5 98.000 (99.538) +2022-11-14 14:01:58,207 Epoch: [135][130/500] Time 0.046 (0.041) Data 0.002 (0.004) Loss 0.0746 (0.0587) Prec@1 87.000 (90.000) Prec@5 98.000 (99.429) +2022-11-14 14:01:58,761 Epoch: [135][140/500] Time 0.061 (0.042) Data 0.001 (0.003) Loss 0.0701 (0.0594) Prec@1 88.000 (89.867) Prec@5 100.000 (99.467) +2022-11-14 14:01:59,412 Epoch: [135][150/500] Time 0.077 (0.043) Data 0.002 (0.003) Loss 0.0924 (0.0615) Prec@1 84.000 (89.500) Prec@5 99.000 (99.438) +2022-11-14 14:02:00,004 Epoch: [135][160/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0291 (0.0596) Prec@1 97.000 (89.941) Prec@5 100.000 (99.471) +2022-11-14 14:02:00,501 Epoch: [135][170/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0501 (0.0591) Prec@1 93.000 (90.111) Prec@5 100.000 (99.500) +2022-11-14 14:02:00,966 Epoch: [135][180/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0414 (0.0581) Prec@1 92.000 (90.211) Prec@5 100.000 (99.526) +2022-11-14 14:02:01,428 Epoch: [135][190/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0572 (0.0581) Prec@1 89.000 (90.150) Prec@5 100.000 (99.550) +2022-11-14 14:02:01,903 Epoch: [135][200/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0490 (0.0576) Prec@1 93.000 (90.286) Prec@5 100.000 (99.571) +2022-11-14 14:02:02,589 Epoch: [135][210/500] Time 0.054 (0.044) Data 0.003 (0.003) Loss 0.0705 (0.0582) Prec@1 90.000 (90.273) Prec@5 99.000 (99.545) +2022-11-14 14:02:03,197 Epoch: [135][220/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0366 (0.0573) Prec@1 93.000 (90.391) Prec@5 100.000 (99.565) +2022-11-14 14:02:03,783 Epoch: [135][230/500] Time 0.093 (0.045) Data 0.002 (0.003) Loss 0.0663 (0.0577) Prec@1 85.000 (90.167) Prec@5 99.000 (99.542) +2022-11-14 14:02:04,239 Epoch: [135][240/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0495 (0.0573) Prec@1 92.000 (90.240) Prec@5 100.000 (99.560) +2022-11-14 14:02:04,702 Epoch: [135][250/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0433 (0.0568) Prec@1 90.000 (90.231) Prec@5 100.000 (99.577) +2022-11-14 14:02:05,167 Epoch: [135][260/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0662 (0.0571) Prec@1 87.000 (90.111) Prec@5 100.000 (99.593) +2022-11-14 14:02:05,630 Epoch: [135][270/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0667 (0.0575) Prec@1 89.000 (90.071) Prec@5 100.000 (99.607) +2022-11-14 14:02:06,092 Epoch: [135][280/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0470 (0.0571) Prec@1 93.000 (90.172) Prec@5 100.000 (99.621) +2022-11-14 14:02:06,555 Epoch: [135][290/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0610 (0.0573) Prec@1 89.000 (90.133) Prec@5 99.000 (99.600) +2022-11-14 14:02:07,047 Epoch: [135][300/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0653 (0.0575) Prec@1 89.000 (90.097) Prec@5 99.000 (99.581) +2022-11-14 14:02:07,542 Epoch: [135][310/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0490 (0.0572) Prec@1 90.000 (90.094) Prec@5 100.000 (99.594) +2022-11-14 14:02:08,140 Epoch: [135][320/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0599 (0.0573) Prec@1 89.000 (90.061) Prec@5 98.000 (99.545) +2022-11-14 14:02:08,614 Epoch: [135][330/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0578 (0.0573) Prec@1 92.000 (90.118) Prec@5 100.000 (99.559) +2022-11-14 14:02:09,077 Epoch: [135][340/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0391 (0.0568) Prec@1 93.000 (90.200) Prec@5 100.000 (99.571) +2022-11-14 14:02:09,564 Epoch: [135][350/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0559 (0.0568) Prec@1 91.000 (90.222) Prec@5 100.000 (99.583) +2022-11-14 14:02:10,027 Epoch: [135][360/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0628 (0.0570) Prec@1 89.000 (90.189) Prec@5 98.000 (99.541) +2022-11-14 14:02:10,492 Epoch: [135][370/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0480 (0.0567) Prec@1 93.000 (90.263) Prec@5 100.000 (99.553) +2022-11-14 14:02:10,980 Epoch: [135][380/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0927 (0.0576) Prec@1 82.000 (90.051) Prec@5 99.000 (99.538) +2022-11-14 14:02:11,530 Epoch: [135][390/500] Time 0.044 (0.044) Data 0.002 (0.002) Loss 0.0740 (0.0581) Prec@1 87.000 (89.975) Prec@5 100.000 (99.550) +2022-11-14 14:02:12,002 Epoch: [135][400/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0637 (0.0582) Prec@1 89.000 (89.951) Prec@5 99.000 (99.537) +2022-11-14 14:02:12,465 Epoch: [135][410/500] Time 0.044 (0.044) Data 0.002 (0.002) Loss 0.0831 (0.0588) Prec@1 86.000 (89.857) Prec@5 100.000 (99.548) +2022-11-14 14:02:13,121 Epoch: [135][420/500] Time 0.072 (0.044) Data 0.002 (0.002) Loss 0.0597 (0.0588) Prec@1 90.000 (89.860) Prec@5 100.000 (99.558) +2022-11-14 14:02:13,586 Epoch: [135][430/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0410 (0.0584) Prec@1 95.000 (89.977) Prec@5 100.000 (99.568) +2022-11-14 14:02:14,049 Epoch: [135][440/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0536 (0.0583) Prec@1 90.000 (89.978) Prec@5 100.000 (99.578) +2022-11-14 14:02:14,512 Epoch: [135][450/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0417 (0.0579) Prec@1 93.000 (90.043) Prec@5 100.000 (99.587) +2022-11-14 14:02:14,990 Epoch: [135][460/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0644 (0.0581) Prec@1 88.000 (90.000) Prec@5 100.000 (99.596) +2022-11-14 14:02:15,558 Epoch: [135][470/500] Time 0.040 (0.044) Data 0.002 (0.002) Loss 0.0600 (0.0581) Prec@1 90.000 (90.000) Prec@5 100.000 (99.604) +2022-11-14 14:02:16,035 Epoch: [135][480/500] Time 0.044 (0.044) Data 0.001 (0.002) Loss 0.0604 (0.0582) Prec@1 91.000 (90.020) Prec@5 99.000 (99.592) +2022-11-14 14:02:16,517 Epoch: [135][490/500] Time 0.046 (0.044) Data 0.002 (0.002) Loss 0.0486 (0.0580) Prec@1 92.000 (90.060) Prec@5 100.000 (99.600) +2022-11-14 14:02:17,061 Epoch: [135][499/500] Time 0.075 (0.044) Data 0.002 (0.002) Loss 0.0446 (0.0577) Prec@1 93.000 (90.118) Prec@5 100.000 (99.608) +2022-11-14 14:02:17,357 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0710 (0.0710) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:02:17,366 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0705) Prec@1 91.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:02:17,377 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0806) Prec@1 84.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:02:17,390 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0795) Prec@1 90.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 14:02:17,398 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0812) Prec@1 84.000 (87.000) Prec@5 100.000 (99.600) +2022-11-14 14:02:17,406 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0756) Prec@1 91.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 14:02:17,413 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0737) Prec@1 88.000 (87.714) Prec@5 100.000 (99.714) +2022-11-14 14:02:17,422 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0757) Prec@1 85.000 (87.375) Prec@5 100.000 (99.750) +2022-11-14 14:02:17,430 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0769) Prec@1 86.000 (87.222) Prec@5 99.000 (99.667) +2022-11-14 14:02:17,439 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0764) Prec@1 87.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 14:02:17,449 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0755) Prec@1 87.000 (87.182) Prec@5 100.000 (99.636) +2022-11-14 14:02:17,458 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0764) Prec@1 85.000 (87.000) Prec@5 99.000 (99.583) +2022-11-14 14:02:17,468 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0754) Prec@1 88.000 (87.077) Prec@5 100.000 (99.615) +2022-11-14 14:02:17,480 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0756) Prec@1 87.000 (87.071) Prec@5 99.000 (99.571) +2022-11-14 14:02:17,490 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0766) Prec@1 87.000 (87.067) Prec@5 100.000 (99.600) +2022-11-14 14:02:17,501 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0765) Prec@1 89.000 (87.188) Prec@5 99.000 (99.562) +2022-11-14 14:02:17,512 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0753) Prec@1 90.000 (87.353) Prec@5 99.000 (99.529) +2022-11-14 14:02:17,522 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0774) Prec@1 83.000 (87.111) Prec@5 100.000 (99.556) +2022-11-14 14:02:17,532 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0780) Prec@1 83.000 (86.895) Prec@5 99.000 (99.526) +2022-11-14 14:02:17,543 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.0799) Prec@1 80.000 (86.550) Prec@5 97.000 (99.400) +2022-11-14 14:02:17,555 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0795) Prec@1 88.000 (86.619) Prec@5 99.000 (99.381) +2022-11-14 14:02:17,565 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0795) Prec@1 86.000 (86.591) Prec@5 97.000 (99.273) +2022-11-14 14:02:17,576 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0795) Prec@1 86.000 (86.565) Prec@5 99.000 (99.261) +2022-11-14 14:02:17,587 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0791) Prec@1 88.000 (86.625) Prec@5 100.000 (99.292) +2022-11-14 14:02:17,599 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0791) Prec@1 85.000 (86.560) Prec@5 99.000 (99.280) +2022-11-14 14:02:17,611 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.0809) Prec@1 80.000 (86.308) Prec@5 96.000 (99.154) +2022-11-14 14:02:17,622 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0803) Prec@1 89.000 (86.407) Prec@5 100.000 (99.185) +2022-11-14 14:02:17,634 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0799) Prec@1 89.000 (86.500) Prec@5 99.000 (99.179) +2022-11-14 14:02:17,645 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0793) Prec@1 89.000 (86.586) Prec@5 97.000 (99.103) +2022-11-14 14:02:17,656 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0791) Prec@1 84.000 (86.500) Prec@5 99.000 (99.100) +2022-11-14 14:02:17,668 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0794) Prec@1 85.000 (86.452) Prec@5 100.000 (99.129) +2022-11-14 14:02:17,678 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0789) Prec@1 90.000 (86.562) Prec@5 100.000 (99.156) +2022-11-14 14:02:17,688 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0786) Prec@1 90.000 (86.667) Prec@5 99.000 (99.152) +2022-11-14 14:02:17,699 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1216 (0.0799) Prec@1 78.000 (86.412) Prec@5 99.000 (99.147) +2022-11-14 14:02:17,710 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0801) Prec@1 85.000 (86.371) Prec@5 99.000 (99.143) +2022-11-14 14:02:17,722 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0801) Prec@1 87.000 (86.389) Prec@5 100.000 (99.167) +2022-11-14 14:02:17,733 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0802) Prec@1 85.000 (86.351) Prec@5 98.000 (99.135) +2022-11-14 14:02:17,746 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0802) Prec@1 88.000 (86.395) Prec@5 100.000 (99.158) +2022-11-14 14:02:17,758 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0801) Prec@1 89.000 (86.462) Prec@5 98.000 (99.128) +2022-11-14 14:02:17,769 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0799) Prec@1 88.000 (86.500) Prec@5 99.000 (99.125) +2022-11-14 14:02:17,779 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0800) Prec@1 88.000 (86.537) Prec@5 99.000 (99.122) +2022-11-14 14:02:17,791 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0802) Prec@1 88.000 (86.571) Prec@5 99.000 (99.119) +2022-11-14 14:02:17,801 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0797) Prec@1 92.000 (86.698) Prec@5 99.000 (99.116) +2022-11-14 14:02:17,813 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0800) Prec@1 85.000 (86.659) Prec@5 100.000 (99.136) +2022-11-14 14:02:17,824 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0798) Prec@1 89.000 (86.711) Prec@5 99.000 (99.133) +2022-11-14 14:02:17,836 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0804) Prec@1 82.000 (86.609) Prec@5 99.000 (99.130) +2022-11-14 14:02:17,847 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0804) Prec@1 85.000 (86.574) Prec@5 100.000 (99.149) +2022-11-14 14:02:17,858 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0809) Prec@1 80.000 (86.438) Prec@5 98.000 (99.125) +2022-11-14 14:02:17,870 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0803) Prec@1 91.000 (86.531) Prec@5 100.000 (99.143) +2022-11-14 14:02:17,881 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0808) Prec@1 82.000 (86.440) Prec@5 99.000 (99.140) +2022-11-14 14:02:17,892 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0804) Prec@1 87.000 (86.451) Prec@5 100.000 (99.157) +2022-11-14 14:02:17,905 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0809) Prec@1 82.000 (86.365) Prec@5 99.000 (99.154) +2022-11-14 14:02:17,916 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0809) Prec@1 86.000 (86.358) Prec@5 99.000 (99.151) +2022-11-14 14:02:17,927 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0806) Prec@1 89.000 (86.407) Prec@5 99.000 (99.148) +2022-11-14 14:02:17,938 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0808) Prec@1 83.000 (86.345) Prec@5 100.000 (99.164) +2022-11-14 14:02:17,949 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0808) Prec@1 89.000 (86.393) Prec@5 99.000 (99.161) +2022-11-14 14:02:17,960 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0807) Prec@1 86.000 (86.386) Prec@5 100.000 (99.175) +2022-11-14 14:02:17,971 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0804) Prec@1 91.000 (86.466) Prec@5 98.000 (99.155) +2022-11-14 14:02:17,981 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1151 (0.0810) Prec@1 83.000 (86.407) Prec@5 98.000 (99.136) +2022-11-14 14:02:17,992 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1211 (0.0817) Prec@1 78.000 (86.267) Prec@5 99.000 (99.133) +2022-11-14 14:02:18,003 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0819) Prec@1 81.000 (86.180) Prec@5 100.000 (99.148) +2022-11-14 14:02:18,014 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0817) Prec@1 88.000 (86.210) Prec@5 100.000 (99.161) +2022-11-14 14:02:18,025 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0815) Prec@1 90.000 (86.270) Prec@5 100.000 (99.175) +2022-11-14 14:02:18,037 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0808) Prec@1 94.000 (86.391) Prec@5 100.000 (99.188) +2022-11-14 14:02:18,048 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0812) Prec@1 81.000 (86.308) Prec@5 99.000 (99.185) +2022-11-14 14:02:18,060 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0811) Prec@1 89.000 (86.348) Prec@5 100.000 (99.197) +2022-11-14 14:02:18,071 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0393 (0.0805) Prec@1 91.000 (86.418) Prec@5 100.000 (99.209) +2022-11-14 14:02:18,082 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0805) Prec@1 89.000 (86.456) Prec@5 99.000 (99.206) +2022-11-14 14:02:18,092 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0803) Prec@1 89.000 (86.493) Prec@5 99.000 (99.203) +2022-11-14 14:02:18,103 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0804) Prec@1 87.000 (86.500) Prec@5 99.000 (99.200) +2022-11-14 14:02:18,114 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.0808) Prec@1 82.000 (86.437) Prec@5 99.000 (99.197) +2022-11-14 14:02:18,125 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0807) Prec@1 87.000 (86.444) Prec@5 100.000 (99.208) +2022-11-14 14:02:18,136 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0805) Prec@1 90.000 (86.493) Prec@5 100.000 (99.219) +2022-11-14 14:02:18,148 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0803) Prec@1 89.000 (86.527) Prec@5 100.000 (99.230) +2022-11-14 14:02:18,160 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0806) Prec@1 83.000 (86.480) Prec@5 98.000 (99.213) +2022-11-14 14:02:18,173 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0805) Prec@1 88.000 (86.500) Prec@5 98.000 (99.197) +2022-11-14 14:02:18,188 Test: [76/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0804) Prec@1 86.000 (86.494) Prec@5 98.000 (99.182) +2022-11-14 14:02:18,201 Test: [77/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0804) Prec@1 88.000 (86.513) Prec@5 98.000 (99.167) +2022-11-14 14:02:18,218 Test: [78/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0804) Prec@1 86.000 (86.506) Prec@5 100.000 (99.177) +2022-11-14 14:02:18,231 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0804) Prec@1 86.000 (86.500) Prec@5 100.000 (99.188) +2022-11-14 14:02:18,246 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0805) Prec@1 87.000 (86.506) Prec@5 99.000 (99.185) +2022-11-14 14:02:18,262 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0805) Prec@1 84.000 (86.476) Prec@5 100.000 (99.195) +2022-11-14 14:02:18,277 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0806) Prec@1 86.000 (86.470) Prec@5 99.000 (99.193) +2022-11-14 14:02:18,290 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0805) Prec@1 86.000 (86.464) Prec@5 100.000 (99.202) +2022-11-14 14:02:18,304 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0806) Prec@1 86.000 (86.459) Prec@5 100.000 (99.212) +2022-11-14 14:02:18,319 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0808) Prec@1 83.000 (86.419) Prec@5 100.000 (99.221) +2022-11-14 14:02:18,331 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0806) Prec@1 90.000 (86.460) Prec@5 100.000 (99.230) +2022-11-14 14:02:18,346 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0805) Prec@1 88.000 (86.477) Prec@5 99.000 (99.227) +2022-11-14 14:02:18,360 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0804) Prec@1 84.000 (86.449) Prec@5 98.000 (99.213) +2022-11-14 14:02:18,375 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0804) Prec@1 89.000 (86.478) Prec@5 100.000 (99.222) +2022-11-14 14:02:18,388 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0802) Prec@1 89.000 (86.505) Prec@5 100.000 (99.231) +2022-11-14 14:02:18,402 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0799) Prec@1 91.000 (86.554) Prec@5 100.000 (99.239) +2022-11-14 14:02:18,416 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0801) Prec@1 81.000 (86.495) Prec@5 99.000 (99.237) +2022-11-14 14:02:18,430 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0801) Prec@1 85.000 (86.479) Prec@5 100.000 (99.245) +2022-11-14 14:02:18,442 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0801) Prec@1 87.000 (86.484) Prec@5 99.000 (99.242) +2022-11-14 14:02:18,458 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0800) Prec@1 89.000 (86.510) Prec@5 99.000 (99.240) +2022-11-14 14:02:18,472 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0799) Prec@1 87.000 (86.515) Prec@5 100.000 (99.247) +2022-11-14 14:02:18,487 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0801) Prec@1 83.000 (86.480) Prec@5 99.000 (99.245) +2022-11-14 14:02:18,497 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0802) Prec@1 84.000 (86.455) Prec@5 98.000 (99.232) +2022-11-14 14:02:18,511 Test: [99/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0803) Prec@1 86.000 (86.450) Prec@5 99.000 (99.230) +2022-11-14 14:02:18,594 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:02:18,908 Epoch: [136][0/500] Time 0.035 (0.035) Data 0.225 (0.225) Loss 0.0399 (0.0399) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:02:19,127 Epoch: [136][10/500] Time 0.016 (0.021) Data 0.002 (0.022) Loss 0.0459 (0.0429) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:02:19,324 Epoch: [136][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0547 (0.0469) Prec@1 90.000 (92.000) Prec@5 99.000 (99.667) +2022-11-14 14:02:19,566 Epoch: [136][30/500] Time 0.020 (0.020) Data 0.002 (0.009) Loss 0.0565 (0.0493) Prec@1 90.000 (91.500) Prec@5 100.000 (99.750) +2022-11-14 14:02:20,022 Epoch: [136][40/500] Time 0.036 (0.025) Data 0.002 (0.007) Loss 0.0699 (0.0534) Prec@1 89.000 (91.000) Prec@5 100.000 (99.800) +2022-11-14 14:02:20,418 Epoch: [136][50/500] Time 0.042 (0.027) Data 0.002 (0.006) Loss 0.0483 (0.0526) Prec@1 94.000 (91.500) Prec@5 100.000 (99.833) +2022-11-14 14:02:20,834 Epoch: [136][60/500] Time 0.038 (0.029) Data 0.001 (0.005) Loss 0.0532 (0.0526) Prec@1 91.000 (91.429) Prec@5 100.000 (99.857) +2022-11-14 14:02:21,295 Epoch: [136][70/500] Time 0.078 (0.030) Data 0.002 (0.005) Loss 0.0438 (0.0515) Prec@1 93.000 (91.625) Prec@5 99.000 (99.750) +2022-11-14 14:02:21,784 Epoch: [136][80/500] Time 0.047 (0.032) Data 0.002 (0.005) Loss 0.0822 (0.0549) Prec@1 85.000 (90.889) Prec@5 99.000 (99.667) +2022-11-14 14:02:22,194 Epoch: [136][90/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0632 (0.0558) Prec@1 87.000 (90.500) Prec@5 100.000 (99.700) +2022-11-14 14:02:22,623 Epoch: [136][100/500] Time 0.039 (0.033) Data 0.002 (0.004) Loss 0.0639 (0.0565) Prec@1 89.000 (90.364) Prec@5 100.000 (99.727) +2022-11-14 14:02:23,046 Epoch: [136][110/500] Time 0.048 (0.034) Data 0.002 (0.004) Loss 0.0643 (0.0572) Prec@1 88.000 (90.167) Prec@5 100.000 (99.750) +2022-11-14 14:02:23,525 Epoch: [136][120/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0395 (0.0558) Prec@1 94.000 (90.462) Prec@5 100.000 (99.769) +2022-11-14 14:02:23,966 Epoch: [136][130/500] Time 0.032 (0.035) Data 0.002 (0.004) Loss 0.0407 (0.0547) Prec@1 95.000 (90.786) Prec@5 100.000 (99.786) +2022-11-14 14:02:24,391 Epoch: [136][140/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0286 (0.0530) Prec@1 95.000 (91.067) Prec@5 98.000 (99.667) +2022-11-14 14:02:24,809 Epoch: [136][150/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0437 (0.0524) Prec@1 92.000 (91.125) Prec@5 100.000 (99.688) +2022-11-14 14:02:25,220 Epoch: [136][160/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0453 (0.0520) Prec@1 93.000 (91.235) Prec@5 100.000 (99.706) +2022-11-14 14:02:25,636 Epoch: [136][170/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0451 (0.0516) Prec@1 93.000 (91.333) Prec@5 100.000 (99.722) +2022-11-14 14:02:26,036 Epoch: [136][180/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0547 (0.0518) Prec@1 91.000 (91.316) Prec@5 100.000 (99.737) +2022-11-14 14:02:26,436 Epoch: [136][190/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0574 (0.0520) Prec@1 87.000 (91.100) Prec@5 99.000 (99.700) +2022-11-14 14:02:26,836 Epoch: [136][200/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0680 (0.0528) Prec@1 87.000 (90.905) Prec@5 99.000 (99.667) +2022-11-14 14:02:27,240 Epoch: [136][210/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0835 (0.0542) Prec@1 87.000 (90.727) Prec@5 99.000 (99.636) +2022-11-14 14:02:27,735 Epoch: [136][220/500] Time 0.065 (0.036) Data 0.002 (0.003) Loss 0.0420 (0.0537) Prec@1 94.000 (90.870) Prec@5 100.000 (99.652) +2022-11-14 14:02:28,173 Epoch: [136][230/500] Time 0.037 (0.036) Data 0.001 (0.003) Loss 0.0361 (0.0529) Prec@1 94.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:02:28,589 Epoch: [136][240/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0436 (0.0526) Prec@1 94.000 (91.120) Prec@5 100.000 (99.680) +2022-11-14 14:02:29,002 Epoch: [136][250/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0673 (0.0531) Prec@1 89.000 (91.038) Prec@5 100.000 (99.692) +2022-11-14 14:02:29,404 Epoch: [136][260/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0851 (0.0543) Prec@1 85.000 (90.815) Prec@5 99.000 (99.667) +2022-11-14 14:02:29,816 Epoch: [136][270/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0622 (0.0546) Prec@1 90.000 (90.786) Prec@5 100.000 (99.679) +2022-11-14 14:02:30,230 Epoch: [136][280/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0459 (0.0543) Prec@1 94.000 (90.897) Prec@5 98.000 (99.621) +2022-11-14 14:02:30,645 Epoch: [136][290/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0808 (0.0552) Prec@1 87.000 (90.767) Prec@5 100.000 (99.633) +2022-11-14 14:02:31,061 Epoch: [136][300/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0698 (0.0557) Prec@1 88.000 (90.677) Prec@5 99.000 (99.613) +2022-11-14 14:02:31,473 Epoch: [136][310/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0429 (0.0553) Prec@1 94.000 (90.781) Prec@5 98.000 (99.562) +2022-11-14 14:02:31,882 Epoch: [136][320/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0835 (0.0561) Prec@1 86.000 (90.636) Prec@5 100.000 (99.576) +2022-11-14 14:02:32,299 Epoch: [136][330/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0486 (0.0559) Prec@1 93.000 (90.706) Prec@5 99.000 (99.559) +2022-11-14 14:02:32,717 Epoch: [136][340/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0463 (0.0556) Prec@1 91.000 (90.714) Prec@5 99.000 (99.543) +2022-11-14 14:02:33,123 Epoch: [136][350/500] Time 0.038 (0.036) Data 0.001 (0.002) Loss 0.0430 (0.0553) Prec@1 94.000 (90.806) Prec@5 100.000 (99.556) +2022-11-14 14:02:33,539 Epoch: [136][360/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0744 (0.0558) Prec@1 88.000 (90.730) Prec@5 99.000 (99.541) +2022-11-14 14:02:33,955 Epoch: [136][370/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0649 (0.0560) Prec@1 91.000 (90.737) Prec@5 99.000 (99.526) +2022-11-14 14:02:34,378 Epoch: [136][380/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0558 (0.0560) Prec@1 90.000 (90.718) Prec@5 100.000 (99.538) +2022-11-14 14:02:34,795 Epoch: [136][390/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0519 (0.0559) Prec@1 91.000 (90.725) Prec@5 100.000 (99.550) +2022-11-14 14:02:35,229 Epoch: [136][400/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0419 (0.0556) Prec@1 94.000 (90.805) Prec@5 100.000 (99.561) +2022-11-14 14:02:35,649 Epoch: [136][410/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0323 (0.0550) Prec@1 93.000 (90.857) Prec@5 100.000 (99.571) +2022-11-14 14:02:36,069 Epoch: [136][420/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0305 (0.0544) Prec@1 93.000 (90.907) Prec@5 100.000 (99.581) +2022-11-14 14:02:36,491 Epoch: [136][430/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0447 (0.0542) Prec@1 91.000 (90.909) Prec@5 99.000 (99.568) +2022-11-14 14:02:36,901 Epoch: [136][440/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0462 (0.0540) Prec@1 92.000 (90.933) Prec@5 100.000 (99.578) +2022-11-14 14:02:37,313 Epoch: [136][450/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0375 (0.0537) Prec@1 93.000 (90.978) Prec@5 100.000 (99.587) +2022-11-14 14:02:37,720 Epoch: [136][460/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0604 (0.0538) Prec@1 91.000 (90.979) Prec@5 99.000 (99.574) +2022-11-14 14:02:38,132 Epoch: [136][470/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0603 (0.0540) Prec@1 92.000 (91.000) Prec@5 99.000 (99.562) +2022-11-14 14:02:38,552 Epoch: [136][480/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0758 (0.0544) Prec@1 87.000 (90.918) Prec@5 99.000 (99.551) +2022-11-14 14:02:38,965 Epoch: [136][490/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0688 (0.0547) Prec@1 89.000 (90.880) Prec@5 100.000 (99.560) +2022-11-14 14:02:39,336 Epoch: [136][499/500] Time 0.039 (0.036) Data 0.001 (0.002) Loss 0.0747 (0.0551) Prec@1 86.000 (90.784) Prec@5 99.000 (99.549) +2022-11-14 14:02:39,612 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0697 (0.0697) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:02:39,620 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0767) Prec@1 87.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 14:02:39,629 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0799) Prec@1 81.000 (85.333) Prec@5 100.000 (99.667) +2022-11-14 14:02:39,640 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0804) Prec@1 88.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 14:02:39,648 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0817) Prec@1 85.000 (85.800) Prec@5 100.000 (99.600) +2022-11-14 14:02:39,657 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0394 (0.0746) Prec@1 93.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 14:02:39,666 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0729) Prec@1 91.000 (87.571) Prec@5 100.000 (99.571) +2022-11-14 14:02:39,675 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0747) Prec@1 86.000 (87.375) Prec@5 99.000 (99.500) +2022-11-14 14:02:39,684 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0772) Prec@1 82.000 (86.778) Prec@5 100.000 (99.556) +2022-11-14 14:02:39,694 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0763) Prec@1 87.000 (86.800) Prec@5 97.000 (99.300) +2022-11-14 14:02:39,703 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0750) Prec@1 87.000 (86.818) Prec@5 100.000 (99.364) +2022-11-14 14:02:39,712 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0768) Prec@1 85.000 (86.667) Prec@5 100.000 (99.417) +2022-11-14 14:02:39,722 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0767) Prec@1 88.000 (86.769) Prec@5 100.000 (99.462) +2022-11-14 14:02:39,730 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0770) Prec@1 87.000 (86.786) Prec@5 99.000 (99.429) +2022-11-14 14:02:39,740 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0773) Prec@1 83.000 (86.533) Prec@5 100.000 (99.467) +2022-11-14 14:02:39,748 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0780) Prec@1 85.000 (86.438) Prec@5 99.000 (99.438) +2022-11-14 14:02:39,757 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0775) Prec@1 89.000 (86.588) Prec@5 97.000 (99.294) +2022-11-14 14:02:39,767 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0784) Prec@1 85.000 (86.500) Prec@5 100.000 (99.333) +2022-11-14 14:02:39,777 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0793) Prec@1 83.000 (86.316) Prec@5 96.000 (99.158) +2022-11-14 14:02:39,786 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0804) Prec@1 84.000 (86.200) Prec@5 99.000 (99.150) +2022-11-14 14:02:39,795 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0817) Prec@1 80.000 (85.905) Prec@5 100.000 (99.190) +2022-11-14 14:02:39,805 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0821) Prec@1 87.000 (85.955) Prec@5 97.000 (99.091) +2022-11-14 14:02:39,814 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0828) Prec@1 88.000 (86.043) Prec@5 99.000 (99.087) +2022-11-14 14:02:39,823 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0824) Prec@1 85.000 (86.000) Prec@5 100.000 (99.125) +2022-11-14 14:02:39,833 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0826) Prec@1 87.000 (86.040) Prec@5 100.000 (99.160) +2022-11-14 14:02:39,842 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0835) Prec@1 81.000 (85.846) Prec@5 98.000 (99.115) +2022-11-14 14:02:39,851 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0829) Prec@1 90.000 (86.000) Prec@5 100.000 (99.148) +2022-11-14 14:02:39,860 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0826) Prec@1 90.000 (86.143) Prec@5 100.000 (99.179) +2022-11-14 14:02:39,869 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0821) Prec@1 89.000 (86.241) Prec@5 99.000 (99.172) +2022-11-14 14:02:39,879 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0813) Prec@1 90.000 (86.367) Prec@5 97.000 (99.100) +2022-11-14 14:02:39,888 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0812) Prec@1 85.000 (86.323) Prec@5 99.000 (99.097) +2022-11-14 14:02:39,898 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0808) Prec@1 88.000 (86.375) Prec@5 100.000 (99.125) +2022-11-14 14:02:39,908 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0810) Prec@1 85.000 (86.333) Prec@5 100.000 (99.152) +2022-11-14 14:02:39,916 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0811) Prec@1 86.000 (86.324) Prec@5 99.000 (99.147) +2022-11-14 14:02:39,925 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0809) Prec@1 89.000 (86.400) Prec@5 98.000 (99.114) +2022-11-14 14:02:39,933 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0802) Prec@1 90.000 (86.500) Prec@5 100.000 (99.139) +2022-11-14 14:02:39,943 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0804) Prec@1 86.000 (86.486) Prec@5 99.000 (99.135) +2022-11-14 14:02:39,951 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0811) Prec@1 81.000 (86.342) Prec@5 98.000 (99.105) +2022-11-14 14:02:39,960 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0807) Prec@1 88.000 (86.385) Prec@5 100.000 (99.128) +2022-11-14 14:02:39,969 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0807) Prec@1 86.000 (86.375) Prec@5 100.000 (99.150) +2022-11-14 14:02:39,979 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0813) Prec@1 85.000 (86.341) Prec@5 100.000 (99.171) +2022-11-14 14:02:39,988 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0812) Prec@1 87.000 (86.357) Prec@5 97.000 (99.119) +2022-11-14 14:02:39,998 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0805) Prec@1 92.000 (86.488) Prec@5 99.000 (99.116) +2022-11-14 14:02:40,006 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0805) Prec@1 88.000 (86.523) Prec@5 98.000 (99.091) +2022-11-14 14:02:40,015 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0803) Prec@1 87.000 (86.533) Prec@5 100.000 (99.111) +2022-11-14 14:02:40,024 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1185 (0.0811) Prec@1 81.000 (86.413) Prec@5 100.000 (99.130) +2022-11-14 14:02:40,034 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0812) Prec@1 82.000 (86.319) Prec@5 100.000 (99.149) +2022-11-14 14:02:40,043 Test: 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0.0781 (0.0813) Prec@1 87.000 (86.222) Prec@5 99.000 (99.111) +2022-11-14 14:02:40,109 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0814) Prec@1 85.000 (86.200) Prec@5 100.000 (99.127) +2022-11-14 14:02:40,117 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0811) Prec@1 92.000 (86.304) Prec@5 98.000 (99.107) +2022-11-14 14:02:40,126 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0811) Prec@1 88.000 (86.333) Prec@5 99.000 (99.105) +2022-11-14 14:02:40,135 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0810) Prec@1 87.000 (86.345) Prec@5 99.000 (99.103) +2022-11-14 14:02:40,145 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1210 (0.0817) Prec@1 78.000 (86.203) Prec@5 99.000 (99.102) +2022-11-14 14:02:40,154 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0820) Prec@1 83.000 (86.150) Prec@5 100.000 (99.117) +2022-11-14 14:02:40,163 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0822) Prec@1 88.000 (86.180) Prec@5 100.000 (99.131) +2022-11-14 14:02:40,173 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0824) Prec@1 85.000 (86.161) Prec@5 98.000 (99.113) +2022-11-14 14:02:40,183 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0821) Prec@1 90.000 (86.222) Prec@5 99.000 (99.111) +2022-11-14 14:02:40,193 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0817) Prec@1 92.000 (86.312) Prec@5 100.000 (99.125) +2022-11-14 14:02:40,201 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0816) Prec@1 89.000 (86.354) Prec@5 100.000 (99.138) +2022-11-14 14:02:40,210 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1134 (0.0821) Prec@1 81.000 (86.273) Prec@5 100.000 (99.152) +2022-11-14 14:02:40,219 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0816) Prec@1 93.000 (86.373) Prec@5 99.000 (99.149) +2022-11-14 14:02:40,229 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0819) Prec@1 83.000 (86.324) Prec@5 97.000 (99.118) +2022-11-14 14:02:40,237 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0818) Prec@1 87.000 (86.333) Prec@5 99.000 (99.116) +2022-11-14 14:02:40,247 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1152 (0.0823) Prec@1 81.000 (86.257) Prec@5 100.000 (99.129) +2022-11-14 14:02:40,256 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0825) Prec@1 86.000 (86.254) Prec@5 99.000 (99.127) +2022-11-14 14:02:40,265 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0825) Prec@1 85.000 (86.236) Prec@5 98.000 (99.111) +2022-11-14 14:02:40,275 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0821) Prec@1 92.000 (86.315) Prec@5 100.000 (99.123) +2022-11-14 14:02:40,285 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0818) Prec@1 89.000 (86.351) Prec@5 100.000 (99.135) +2022-11-14 14:02:40,296 Test: [74/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0819) Prec@1 83.000 (86.307) Prec@5 100.000 (99.147) +2022-11-14 14:02:40,306 Test: [75/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0815) Prec@1 92.000 (86.382) Prec@5 99.000 (99.145) +2022-11-14 14:02:40,315 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0814) Prec@1 87.000 (86.390) Prec@5 100.000 (99.156) +2022-11-14 14:02:40,324 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1289 (0.0820) Prec@1 77.000 (86.269) Prec@5 98.000 (99.141) +2022-11-14 14:02:40,335 Test: [78/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0820) Prec@1 86.000 (86.266) Prec@5 100.000 (99.152) +2022-11-14 14:02:40,345 Test: [79/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0820) Prec@1 87.000 (86.275) Prec@5 99.000 (99.150) +2022-11-14 14:02:40,354 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0819) Prec@1 87.000 (86.284) Prec@5 98.000 (99.136) +2022-11-14 14:02:40,362 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0821) Prec@1 87.000 (86.293) Prec@5 99.000 (99.134) +2022-11-14 14:02:40,374 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0821) Prec@1 85.000 (86.277) Prec@5 99.000 (99.133) +2022-11-14 14:02:40,384 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0821) Prec@1 88.000 (86.298) Prec@5 100.000 (99.143) +2022-11-14 14:02:40,393 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0823) Prec@1 83.000 (86.259) Prec@5 99.000 (99.141) +2022-11-14 14:02:40,402 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0824) Prec@1 82.000 (86.209) Prec@5 100.000 (99.151) +2022-11-14 14:02:40,414 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0825) Prec@1 84.000 (86.184) Prec@5 100.000 (99.161) +2022-11-14 14:02:40,425 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0823) Prec@1 89.000 (86.216) Prec@5 99.000 (99.159) +2022-11-14 14:02:40,434 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0825) Prec@1 84.000 (86.191) Prec@5 99.000 (99.157) +2022-11-14 14:02:40,444 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0824) Prec@1 87.000 (86.200) Prec@5 100.000 (99.167) +2022-11-14 14:02:40,456 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0821) Prec@1 92.000 (86.264) Prec@5 100.000 (99.176) +2022-11-14 14:02:40,467 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0819) Prec@1 91.000 (86.315) Prec@5 99.000 (99.174) +2022-11-14 14:02:40,476 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0822) Prec@1 84.000 (86.290) Prec@5 100.000 (99.183) +2022-11-14 14:02:40,486 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0822) Prec@1 86.000 (86.287) Prec@5 99.000 (99.181) +2022-11-14 14:02:40,495 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0822) Prec@1 87.000 (86.295) Prec@5 100.000 (99.189) +2022-11-14 14:02:40,504 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0819) Prec@1 91.000 (86.344) Prec@5 100.000 (99.198) +2022-11-14 14:02:40,513 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0818) Prec@1 84.000 (86.320) Prec@5 98.000 (99.186) +2022-11-14 14:02:40,522 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0819) Prec@1 87.000 (86.327) Prec@5 99.000 (99.184) +2022-11-14 14:02:40,531 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0821) Prec@1 82.000 (86.283) Prec@5 99.000 (99.182) +2022-11-14 14:02:40,541 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0822) Prec@1 85.000 (86.270) Prec@5 100.000 (99.190) +2022-11-14 14:02:40,595 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:02:40,911 Epoch: [137][0/500] Time 0.032 (0.032) Data 0.227 (0.227) Loss 0.0517 (0.0517) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:02:41,136 Epoch: [137][10/500] Time 0.016 (0.021) Data 0.002 (0.023) Loss 0.0467 (0.0492) Prec@1 93.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 14:02:41,349 Epoch: [137][20/500] Time 0.019 (0.020) Data 0.002 (0.013) Loss 0.0628 (0.0537) Prec@1 89.000 (91.333) Prec@5 99.000 (99.333) +2022-11-14 14:02:41,569 Epoch: [137][30/500] Time 0.019 (0.020) Data 0.002 (0.009) Loss 0.0471 (0.0521) Prec@1 93.000 (91.750) Prec@5 100.000 (99.500) +2022-11-14 14:02:41,828 Epoch: [137][40/500] Time 0.024 (0.020) Data 0.002 (0.007) Loss 0.0412 (0.0499) Prec@1 93.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:02:42,091 Epoch: [137][50/500] Time 0.022 (0.021) Data 0.002 (0.006) Loss 0.0623 (0.0520) Prec@1 87.000 (91.167) Prec@5 99.000 (99.500) +2022-11-14 14:02:42,351 Epoch: [137][60/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.0469 (0.0512) Prec@1 92.000 (91.286) Prec@5 100.000 (99.571) +2022-11-14 14:02:42,667 Epoch: [137][70/500] Time 0.040 (0.022) Data 0.002 (0.005) Loss 0.0552 (0.0517) Prec@1 85.000 (90.500) Prec@5 100.000 (99.625) +2022-11-14 14:02:43,186 Epoch: [137][80/500] Time 0.025 (0.025) Data 0.002 (0.005) Loss 0.0470 (0.0512) Prec@1 91.000 (90.556) Prec@5 100.000 (99.667) +2022-11-14 14:02:43,587 Epoch: [137][90/500] Time 0.038 (0.026) Data 0.002 (0.004) Loss 0.0377 (0.0499) Prec@1 94.000 (90.900) Prec@5 100.000 (99.700) +2022-11-14 14:02:44,024 Epoch: [137][100/500] Time 0.037 (0.028) Data 0.002 (0.004) Loss 0.0558 (0.0504) Prec@1 91.000 (90.909) Prec@5 100.000 (99.727) +2022-11-14 14:02:44,428 Epoch: [137][110/500] Time 0.037 (0.028) Data 0.002 (0.004) Loss 0.0524 (0.0506) Prec@1 91.000 (90.917) Prec@5 99.000 (99.667) +2022-11-14 14:02:44,886 Epoch: [137][120/500] Time 0.069 (0.029) Data 0.002 (0.004) Loss 0.0587 (0.0512) Prec@1 90.000 (90.846) Prec@5 100.000 (99.692) +2022-11-14 14:02:45,338 Epoch: [137][130/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0517 (0.0512) Prec@1 89.000 (90.714) Prec@5 99.000 (99.643) +2022-11-14 14:02:45,749 Epoch: [137][140/500] Time 0.039 (0.031) Data 0.002 (0.004) Loss 0.0539 (0.0514) Prec@1 92.000 (90.800) Prec@5 99.000 (99.600) +2022-11-14 14:02:46,170 Epoch: [137][150/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0435 (0.0509) Prec@1 92.000 (90.875) Prec@5 100.000 (99.625) +2022-11-14 14:02:46,570 Epoch: [137][160/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0616 (0.0515) Prec@1 91.000 (90.882) Prec@5 100.000 (99.647) +2022-11-14 14:02:47,030 Epoch: [137][170/500] Time 0.067 (0.032) Data 0.002 (0.003) Loss 0.0475 (0.0513) Prec@1 92.000 (90.944) Prec@5 99.000 (99.611) +2022-11-14 14:02:47,465 Epoch: [137][180/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0464 (0.0511) Prec@1 93.000 (91.053) Prec@5 99.000 (99.579) +2022-11-14 14:02:47,907 Epoch: [137][190/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0464 (0.0508) Prec@1 96.000 (91.300) Prec@5 100.000 (99.600) +2022-11-14 14:02:48,369 Epoch: [137][200/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.0691 (0.0517) Prec@1 88.000 (91.143) Prec@5 100.000 (99.619) +2022-11-14 14:02:48,866 Epoch: [137][210/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0401 (0.0512) Prec@1 94.000 (91.273) Prec@5 100.000 (99.636) +2022-11-14 14:02:49,268 Epoch: [137][220/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0474 (0.0510) Prec@1 92.000 (91.304) Prec@5 98.000 (99.565) +2022-11-14 14:02:49,742 Epoch: [137][230/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0386 (0.0505) Prec@1 93.000 (91.375) Prec@5 99.000 (99.542) +2022-11-14 14:02:50,126 Epoch: [137][240/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0463 (0.0503) Prec@1 93.000 (91.440) Prec@5 100.000 (99.560) +2022-11-14 14:02:50,619 Epoch: [137][250/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0573 (0.0506) Prec@1 90.000 (91.385) Prec@5 100.000 (99.577) +2022-11-14 14:02:51,135 Epoch: [137][260/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0603 (0.0509) Prec@1 90.000 (91.333) Prec@5 98.000 (99.519) +2022-11-14 14:02:51,627 Epoch: [137][270/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0588 (0.0512) Prec@1 91.000 (91.321) Prec@5 100.000 (99.536) +2022-11-14 14:02:52,013 Epoch: [137][280/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0565 (0.0514) Prec@1 91.000 (91.310) Prec@5 100.000 (99.552) +2022-11-14 14:02:52,434 Epoch: [137][290/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0404 (0.0510) Prec@1 93.000 (91.367) Prec@5 100.000 (99.567) +2022-11-14 14:02:52,876 Epoch: [137][300/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0659 (0.0515) Prec@1 89.000 (91.290) Prec@5 99.000 (99.548) +2022-11-14 14:02:53,328 Epoch: [137][310/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0646 (0.0519) Prec@1 88.000 (91.188) Prec@5 98.000 (99.500) +2022-11-14 14:02:53,848 Epoch: [137][320/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0652 (0.0523) Prec@1 89.000 (91.121) Prec@5 100.000 (99.515) +2022-11-14 14:02:54,309 Epoch: [137][330/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0378 (0.0519) Prec@1 94.000 (91.206) Prec@5 100.000 (99.529) +2022-11-14 14:02:54,786 Epoch: [137][340/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0562 (0.0520) Prec@1 90.000 (91.171) Prec@5 99.000 (99.514) +2022-11-14 14:02:55,199 Epoch: [137][350/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0487 (0.0519) Prec@1 91.000 (91.167) Prec@5 100.000 (99.528) +2022-11-14 14:02:55,615 Epoch: [137][360/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0650 (0.0523) Prec@1 90.000 (91.135) Prec@5 100.000 (99.541) +2022-11-14 14:02:56,044 Epoch: [137][370/500] Time 0.035 (0.036) Data 0.003 (0.003) Loss 0.0734 (0.0528) Prec@1 86.000 (91.000) Prec@5 100.000 (99.553) +2022-11-14 14:02:56,556 Epoch: [137][380/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.0576 (0.0530) Prec@1 91.000 (91.000) Prec@5 100.000 (99.564) +2022-11-14 14:02:57,062 Epoch: [137][390/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.0671 (0.0533) Prec@1 89.000 (90.950) Prec@5 99.000 (99.550) +2022-11-14 14:02:57,455 Epoch: [137][400/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0390 (0.0530) Prec@1 93.000 (91.000) Prec@5 100.000 (99.561) +2022-11-14 14:02:57,868 Epoch: [137][410/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0553 (0.0530) Prec@1 90.000 (90.976) Prec@5 99.000 (99.548) +2022-11-14 14:02:58,282 Epoch: [137][420/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0634 (0.0533) Prec@1 89.000 (90.930) Prec@5 99.000 (99.535) +2022-11-14 14:02:58,702 Epoch: [137][430/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0538 (0.0533) Prec@1 91.000 (90.932) Prec@5 100.000 (99.545) +2022-11-14 14:02:59,129 Epoch: [137][440/500] Time 0.049 (0.037) Data 0.002 (0.002) Loss 0.0477 (0.0532) Prec@1 92.000 (90.956) Prec@5 100.000 (99.556) +2022-11-14 14:02:59,545 Epoch: [137][450/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0805 (0.0538) Prec@1 85.000 (90.826) Prec@5 100.000 (99.565) +2022-11-14 14:02:59,967 Epoch: [137][460/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0792 (0.0543) Prec@1 86.000 (90.723) Prec@5 100.000 (99.574) +2022-11-14 14:03:00,385 Epoch: [137][470/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0352 (0.0539) Prec@1 95.000 (90.812) Prec@5 100.000 (99.583) +2022-11-14 14:03:00,795 Epoch: [137][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0509 (0.0538) Prec@1 92.000 (90.837) Prec@5 100.000 (99.592) +2022-11-14 14:03:01,202 Epoch: [137][490/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0567 (0.0539) Prec@1 91.000 (90.840) Prec@5 99.000 (99.580) +2022-11-14 14:03:01,579 Epoch: [137][499/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0593 (0.0540) Prec@1 92.000 (90.863) Prec@5 100.000 (99.588) +2022-11-14 14:03:01,853 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0770 (0.0770) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:03:01,862 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0751) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:03:01,872 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0787) Prec@1 87.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:03:01,884 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0766) Prec@1 90.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:03:01,893 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0802) Prec@1 82.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:03:01,903 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0738) Prec@1 94.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:03:01,912 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0708) Prec@1 92.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 14:03:01,923 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0741) Prec@1 83.000 (88.125) Prec@5 99.000 (99.625) +2022-11-14 14:03:01,932 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0777) Prec@1 81.000 (87.333) Prec@5 99.000 (99.556) +2022-11-14 14:03:01,942 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0774) Prec@1 89.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:03:01,953 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0763) Prec@1 89.000 (87.636) Prec@5 100.000 (99.545) +2022-11-14 14:03:01,964 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0766) Prec@1 87.000 (87.583) Prec@5 100.000 (99.583) +2022-11-14 14:03:01,974 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0743) Prec@1 92.000 (87.923) Prec@5 100.000 (99.615) +2022-11-14 14:03:01,985 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0738) Prec@1 90.000 (88.071) Prec@5 98.000 (99.500) +2022-11-14 14:03:01,995 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0739) Prec@1 88.000 (88.067) Prec@5 100.000 (99.533) +2022-11-14 14:03:02,006 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0745) Prec@1 85.000 (87.875) Prec@5 100.000 (99.562) +2022-11-14 14:03:02,016 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0732) Prec@1 93.000 (88.176) Prec@5 98.000 (99.471) +2022-11-14 14:03:02,026 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0748) Prec@1 83.000 (87.889) Prec@5 100.000 (99.500) +2022-11-14 14:03:02,037 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0759) Prec@1 81.000 (87.526) Prec@5 99.000 (99.474) +2022-11-14 14:03:02,047 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0771) Prec@1 85.000 (87.400) Prec@5 99.000 (99.450) +2022-11-14 14:03:02,057 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0783) Prec@1 83.000 (87.190) Prec@5 100.000 (99.476) +2022-11-14 14:03:02,068 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0785) Prec@1 86.000 (87.136) Prec@5 99.000 (99.455) +2022-11-14 14:03:02,078 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0794) Prec@1 82.000 (86.913) Prec@5 99.000 (99.435) +2022-11-14 14:03:02,088 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0794) Prec@1 86.000 (86.875) Prec@5 99.000 (99.417) +2022-11-14 14:03:02,098 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0797) Prec@1 86.000 (86.840) Prec@5 99.000 (99.400) +2022-11-14 14:03:02,108 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1276 (0.0815) Prec@1 78.000 (86.500) Prec@5 99.000 (99.385) +2022-11-14 14:03:02,117 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0804) Prec@1 93.000 (86.741) Prec@5 100.000 (99.407) +2022-11-14 14:03:02,126 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0799) Prec@1 89.000 (86.821) Prec@5 100.000 (99.429) +2022-11-14 14:03:02,134 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0796) Prec@1 88.000 (86.862) Prec@5 100.000 (99.448) +2022-11-14 14:03:02,142 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0802) Prec@1 80.000 (86.633) Prec@5 98.000 (99.400) +2022-11-14 14:03:02,152 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0808) Prec@1 83.000 (86.516) Prec@5 97.000 (99.323) +2022-11-14 14:03:02,162 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0808) Prec@1 85.000 (86.469) Prec@5 100.000 (99.344) +2022-11-14 14:03:02,172 Test: [32/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0811) Prec@1 84.000 (86.394) Prec@5 99.000 (99.333) +2022-11-14 14:03:02,183 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0817) Prec@1 84.000 (86.324) Prec@5 97.000 (99.265) +2022-11-14 14:03:02,192 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0814) Prec@1 87.000 (86.343) Prec@5 99.000 (99.257) +2022-11-14 14:03:02,201 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0812) Prec@1 88.000 (86.389) Prec@5 100.000 (99.278) +2022-11-14 14:03:02,211 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0812) Prec@1 85.000 (86.351) Prec@5 98.000 (99.243) +2022-11-14 14:03:02,220 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0816) Prec@1 81.000 (86.211) Prec@5 99.000 (99.237) +2022-11-14 14:03:02,228 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0816) Prec@1 89.000 (86.282) Prec@5 99.000 (99.231) +2022-11-14 14:03:02,237 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0813) Prec@1 88.000 (86.325) Prec@5 99.000 (99.225) +2022-11-14 14:03:02,247 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0817) Prec@1 85.000 (86.293) Prec@5 98.000 (99.195) +2022-11-14 14:03:02,259 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0815) Prec@1 86.000 (86.286) Prec@5 99.000 (99.190) +2022-11-14 14:03:02,270 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0811) Prec@1 90.000 (86.372) Prec@5 100.000 (99.209) +2022-11-14 14:03:02,280 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0810) Prec@1 88.000 (86.409) Prec@5 99.000 (99.205) +2022-11-14 14:03:02,290 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0808) Prec@1 88.000 (86.444) Prec@5 100.000 (99.222) +2022-11-14 14:03:02,301 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0812) Prec@1 83.000 (86.370) Prec@5 99.000 (99.217) +2022-11-14 14:03:02,311 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0811) Prec@1 86.000 (86.362) Prec@5 99.000 (99.213) +2022-11-14 14:03:02,321 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0815) Prec@1 81.000 (86.250) Prec@5 100.000 (99.229) +2022-11-14 14:03:02,332 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0811) Prec@1 91.000 (86.347) Prec@5 100.000 (99.245) +2022-11-14 14:03:02,343 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0813) Prec@1 83.000 (86.280) Prec@5 100.000 (99.260) +2022-11-14 14:03:02,353 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0808) Prec@1 91.000 (86.373) Prec@5 100.000 (99.275) +2022-11-14 14:03:02,364 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0811) Prec@1 85.000 (86.346) Prec@5 99.000 (99.269) +2022-11-14 14:03:02,374 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0806) Prec@1 93.000 (86.472) Prec@5 99.000 (99.264) +2022-11-14 14:03:02,385 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0803) Prec@1 88.000 (86.500) Prec@5 98.000 (99.241) +2022-11-14 14:03:02,397 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0803) Prec@1 88.000 (86.527) Prec@5 100.000 (99.255) +2022-11-14 14:03:02,408 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0804) Prec@1 86.000 (86.518) Prec@5 99.000 (99.250) +2022-11-14 14:03:02,418 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0805) Prec@1 85.000 (86.491) Prec@5 100.000 (99.263) +2022-11-14 14:03:02,428 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0803) Prec@1 89.000 (86.534) Prec@5 99.000 (99.259) +2022-11-14 14:03:02,439 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1299 (0.0811) Prec@1 82.000 (86.458) Prec@5 100.000 (99.271) +2022-11-14 14:03:02,451 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0814) Prec@1 82.000 (86.383) Prec@5 98.000 (99.250) +2022-11-14 14:03:02,462 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0815) Prec@1 82.000 (86.311) Prec@5 100.000 (99.262) +2022-11-14 14:03:02,474 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0814) Prec@1 86.000 (86.306) Prec@5 100.000 (99.274) +2022-11-14 14:03:02,484 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0815) Prec@1 85.000 (86.286) Prec@5 99.000 (99.270) +2022-11-14 14:03:02,494 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0811) Prec@1 90.000 (86.344) Prec@5 100.000 (99.281) +2022-11-14 14:03:02,505 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0811) Prec@1 86.000 (86.338) Prec@5 100.000 (99.292) +2022-11-14 14:03:02,515 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0812) Prec@1 87.000 (86.348) Prec@5 99.000 (99.288) +2022-11-14 14:03:02,526 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0810) Prec@1 90.000 (86.403) Prec@5 99.000 (99.284) +2022-11-14 14:03:02,536 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0811) Prec@1 85.000 (86.382) Prec@5 99.000 (99.279) +2022-11-14 14:03:02,546 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0810) Prec@1 87.000 (86.391) Prec@5 99.000 (99.275) +2022-11-14 14:03:02,558 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0811) Prec@1 85.000 (86.371) Prec@5 100.000 (99.286) +2022-11-14 14:03:02,570 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0813) Prec@1 83.000 (86.324) Prec@5 100.000 (99.296) +2022-11-14 14:03:02,582 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0813) Prec@1 84.000 (86.292) Prec@5 100.000 (99.306) +2022-11-14 14:03:02,595 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0810) Prec@1 92.000 (86.370) Prec@5 99.000 (99.301) +2022-11-14 14:03:02,608 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0807) Prec@1 89.000 (86.405) Prec@5 100.000 (99.311) +2022-11-14 14:03:02,623 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0810) Prec@1 81.000 (86.333) Prec@5 100.000 (99.320) +2022-11-14 14:03:02,637 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0809) Prec@1 88.000 (86.355) Prec@5 98.000 (99.303) +2022-11-14 14:03:02,651 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0809) Prec@1 88.000 (86.377) Prec@5 99.000 (99.299) +2022-11-14 14:03:02,666 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0809) Prec@1 88.000 (86.397) Prec@5 98.000 (99.282) +2022-11-14 14:03:02,682 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0809) Prec@1 87.000 (86.405) Prec@5 100.000 (99.291) +2022-11-14 14:03:02,699 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0809) Prec@1 85.000 (86.388) Prec@5 99.000 (99.287) +2022-11-14 14:03:02,717 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0809) Prec@1 88.000 (86.407) Prec@5 98.000 (99.272) +2022-11-14 14:03:02,734 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0808) Prec@1 87.000 (86.415) Prec@5 100.000 (99.280) +2022-11-14 14:03:02,752 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0807) Prec@1 88.000 (86.434) Prec@5 99.000 (99.277) +2022-11-14 14:03:02,769 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0808) Prec@1 89.000 (86.464) Prec@5 100.000 (99.286) +2022-11-14 14:03:02,788 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0810) Prec@1 83.000 (86.424) Prec@5 100.000 (99.294) +2022-11-14 14:03:02,803 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0813) Prec@1 80.000 (86.349) Prec@5 100.000 (99.302) +2022-11-14 14:03:02,820 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0812) Prec@1 88.000 (86.368) Prec@5 99.000 (99.299) +2022-11-14 14:03:02,837 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0812) Prec@1 87.000 (86.375) Prec@5 99.000 (99.295) +2022-11-14 14:03:02,855 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0812) Prec@1 85.000 (86.360) Prec@5 98.000 (99.281) +2022-11-14 14:03:02,870 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0813) Prec@1 86.000 (86.356) Prec@5 98.000 (99.267) +2022-11-14 14:03:02,887 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0810) Prec@1 91.000 (86.407) Prec@5 100.000 (99.275) +2022-11-14 14:03:02,902 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0807) Prec@1 92.000 (86.467) Prec@5 99.000 (99.272) +2022-11-14 14:03:02,917 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0810) Prec@1 82.000 (86.419) Prec@5 100.000 (99.280) +2022-11-14 14:03:02,934 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0809) Prec@1 90.000 (86.457) Prec@5 100.000 (99.287) +2022-11-14 14:03:02,950 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0807) Prec@1 88.000 (86.474) Prec@5 100.000 (99.295) +2022-11-14 14:03:02,966 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0806) Prec@1 90.000 (86.510) Prec@5 98.000 (99.281) +2022-11-14 14:03:02,982 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0802) Prec@1 93.000 (86.577) Prec@5 99.000 (99.278) +2022-11-14 14:03:02,998 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0803) Prec@1 85.000 (86.561) Prec@5 99.000 (99.276) +2022-11-14 14:03:03,015 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0807) Prec@1 83.000 (86.525) Prec@5 99.000 (99.273) +2022-11-14 14:03:03,031 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0805) Prec@1 88.000 (86.540) Prec@5 100.000 (99.280) +2022-11-14 14:03:03,087 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:03:03,405 Epoch: [138][0/500] Time 0.026 (0.026) Data 0.240 (0.240) Loss 0.0379 (0.0379) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:03,646 Epoch: [138][10/500] Time 0.023 (0.022) Data 0.002 (0.023) Loss 0.0752 (0.0566) Prec@1 87.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:03,917 Epoch: [138][20/500] Time 0.024 (0.023) Data 0.002 (0.013) Loss 0.0629 (0.0587) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:04,223 Epoch: [138][30/500] Time 0.035 (0.024) Data 0.002 (0.010) Loss 0.0452 (0.0553) Prec@1 94.000 (90.250) Prec@5 100.000 (100.000) +2022-11-14 14:03:04,645 Epoch: [138][40/500] Time 0.056 (0.027) Data 0.002 (0.008) Loss 0.0473 (0.0537) Prec@1 92.000 (90.600) Prec@5 99.000 (99.800) +2022-11-14 14:03:05,116 Epoch: [138][50/500] Time 0.039 (0.030) Data 0.002 (0.007) Loss 0.0400 (0.0514) Prec@1 93.000 (91.000) Prec@5 100.000 (99.833) +2022-11-14 14:03:05,632 Epoch: [138][60/500] Time 0.054 (0.032) Data 0.002 (0.006) Loss 0.0494 (0.0511) Prec@1 93.000 (91.286) Prec@5 100.000 (99.857) +2022-11-14 14:03:06,204 Epoch: [138][70/500] Time 0.046 (0.035) Data 0.002 (0.005) Loss 0.0624 (0.0525) Prec@1 91.000 (91.250) Prec@5 99.000 (99.750) +2022-11-14 14:03:06,707 Epoch: [138][80/500] Time 0.044 (0.036) Data 0.002 (0.005) Loss 0.0493 (0.0522) Prec@1 92.000 (91.333) Prec@5 99.000 (99.667) +2022-11-14 14:03:07,131 Epoch: [138][90/500] Time 0.047 (0.036) Data 0.002 (0.005) Loss 0.0677 (0.0537) Prec@1 87.000 (90.900) Prec@5 99.000 (99.600) +2022-11-14 14:03:07,563 Epoch: [138][100/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0400 (0.0525) Prec@1 94.000 (91.182) Prec@5 100.000 (99.636) +2022-11-14 14:03:07,996 Epoch: [138][110/500] Time 0.041 (0.037) Data 0.002 (0.004) Loss 0.0592 (0.0530) Prec@1 90.000 (91.083) Prec@5 100.000 (99.667) +2022-11-14 14:03:08,420 Epoch: [138][120/500] Time 0.038 (0.037) Data 0.002 (0.004) Loss 0.0323 (0.0515) Prec@1 97.000 (91.538) Prec@5 100.000 (99.692) +2022-11-14 14:03:08,848 Epoch: [138][130/500] Time 0.041 (0.037) Data 0.001 (0.004) Loss 0.0809 (0.0536) Prec@1 87.000 (91.214) Prec@5 99.000 (99.643) +2022-11-14 14:03:09,275 Epoch: [138][140/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0542 (0.0536) Prec@1 92.000 (91.267) Prec@5 99.000 (99.600) +2022-11-14 14:03:09,701 Epoch: [138][150/500] Time 0.041 (0.037) Data 0.002 (0.004) Loss 0.0662 (0.0544) Prec@1 91.000 (91.250) Prec@5 99.000 (99.562) +2022-11-14 14:03:10,137 Epoch: [138][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0566 (0.0545) Prec@1 90.000 (91.176) Prec@5 100.000 (99.588) +2022-11-14 14:03:10,573 Epoch: [138][170/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0348 (0.0534) Prec@1 95.000 (91.389) Prec@5 100.000 (99.611) +2022-11-14 14:03:11,001 Epoch: [138][180/500] Time 0.040 (0.037) Data 0.001 (0.003) Loss 0.0563 (0.0536) Prec@1 93.000 (91.474) Prec@5 100.000 (99.632) +2022-11-14 14:03:11,426 Epoch: [138][190/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0446 (0.0531) Prec@1 91.000 (91.450) Prec@5 100.000 (99.650) +2022-11-14 14:03:11,857 Epoch: [138][200/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0496 (0.0530) Prec@1 92.000 (91.476) Prec@5 99.000 (99.619) +2022-11-14 14:03:12,292 Epoch: [138][210/500] Time 0.041 (0.037) Data 0.003 (0.003) Loss 0.0569 (0.0531) Prec@1 90.000 (91.409) Prec@5 100.000 (99.636) +2022-11-14 14:03:12,726 Epoch: [138][220/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0719 (0.0539) Prec@1 86.000 (91.174) Prec@5 100.000 (99.652) +2022-11-14 14:03:13,150 Epoch: [138][230/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0396 (0.0533) Prec@1 94.000 (91.292) Prec@5 99.000 (99.625) +2022-11-14 14:03:13,570 Epoch: [138][240/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0459 (0.0531) Prec@1 93.000 (91.360) Prec@5 100.000 (99.640) +2022-11-14 14:03:13,991 Epoch: [138][250/500] Time 0.041 (0.037) Data 0.001 (0.003) Loss 0.0519 (0.0530) Prec@1 91.000 (91.346) Prec@5 100.000 (99.654) +2022-11-14 14:03:14,412 Epoch: [138][260/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0290 (0.0521) Prec@1 93.000 (91.407) Prec@5 100.000 (99.667) +2022-11-14 14:03:14,835 Epoch: [138][270/500] Time 0.041 (0.037) Data 0.001 (0.003) Loss 0.0623 (0.0525) Prec@1 88.000 (91.286) Prec@5 100.000 (99.679) +2022-11-14 14:03:15,258 Epoch: [138][280/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0561 (0.0526) Prec@1 92.000 (91.310) Prec@5 100.000 (99.690) +2022-11-14 14:03:15,685 Epoch: [138][290/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0503 (0.0525) Prec@1 93.000 (91.367) Prec@5 99.000 (99.667) +2022-11-14 14:03:16,114 Epoch: [138][300/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0722 (0.0532) Prec@1 85.000 (91.161) Prec@5 100.000 (99.677) +2022-11-14 14:03:16,531 Epoch: [138][310/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0520 (0.0531) Prec@1 92.000 (91.188) Prec@5 100.000 (99.688) +2022-11-14 14:03:16,955 Epoch: [138][320/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0531 (0.0531) Prec@1 92.000 (91.212) Prec@5 99.000 (99.667) +2022-11-14 14:03:17,375 Epoch: [138][330/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0636 (0.0534) Prec@1 88.000 (91.118) Prec@5 98.000 (99.618) +2022-11-14 14:03:17,799 Epoch: [138][340/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0472 (0.0533) Prec@1 91.000 (91.114) Prec@5 100.000 (99.629) +2022-11-14 14:03:18,228 Epoch: [138][350/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0305 (0.0526) Prec@1 94.000 (91.194) Prec@5 100.000 (99.639) +2022-11-14 14:03:18,654 Epoch: [138][360/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0415 (0.0523) Prec@1 94.000 (91.270) Prec@5 100.000 (99.649) +2022-11-14 14:03:19,079 Epoch: [138][370/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0502 (0.0523) Prec@1 92.000 (91.289) Prec@5 100.000 (99.658) +2022-11-14 14:03:19,513 Epoch: [138][380/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0838 (0.0531) Prec@1 87.000 (91.179) Prec@5 100.000 (99.667) +2022-11-14 14:03:19,937 Epoch: [138][390/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0340 (0.0526) Prec@1 95.000 (91.275) Prec@5 99.000 (99.650) +2022-11-14 14:03:20,361 Epoch: [138][400/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0489 (0.0525) Prec@1 92.000 (91.293) Prec@5 100.000 (99.659) +2022-11-14 14:03:20,783 Epoch: [138][410/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0589 (0.0527) Prec@1 91.000 (91.286) Prec@5 100.000 (99.667) +2022-11-14 14:03:21,212 Epoch: [138][420/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.1076 (0.0539) Prec@1 83.000 (91.093) Prec@5 97.000 (99.605) +2022-11-14 14:03:21,640 Epoch: [138][430/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0552 (0.0540) Prec@1 91.000 (91.091) Prec@5 100.000 (99.614) +2022-11-14 14:03:22,068 Epoch: [138][440/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0636 (0.0542) Prec@1 88.000 (91.022) Prec@5 99.000 (99.600) +2022-11-14 14:03:22,492 Epoch: [138][450/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0410 (0.0539) Prec@1 94.000 (91.087) Prec@5 99.000 (99.587) +2022-11-14 14:03:22,917 Epoch: [138][460/500] Time 0.039 (0.038) Data 0.001 (0.002) Loss 0.0555 (0.0539) Prec@1 90.000 (91.064) Prec@5 100.000 (99.596) +2022-11-14 14:03:23,339 Epoch: [138][470/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0725 (0.0543) Prec@1 90.000 (91.042) Prec@5 98.000 (99.562) +2022-11-14 14:03:23,767 Epoch: [138][480/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0878 (0.0550) Prec@1 86.000 (90.939) Prec@5 97.000 (99.510) +2022-11-14 14:03:24,191 Epoch: [138][490/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0594 (0.0551) Prec@1 92.000 (90.960) Prec@5 99.000 (99.500) +2022-11-14 14:03:24,569 Epoch: [138][499/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0413 (0.0548) Prec@1 93.000 (91.000) Prec@5 99.000 (99.490) +2022-11-14 14:03:24,845 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0339 (0.0339) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:24,853 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0670) Prec@1 83.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:03:24,861 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0717) Prec@1 89.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 14:03:24,874 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0769) Prec@1 85.000 (87.750) Prec@5 98.000 (99.250) +2022-11-14 14:03:24,883 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0772) Prec@1 87.000 (87.600) Prec@5 100.000 (99.400) +2022-11-14 14:03:24,891 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0418 (0.0713) Prec@1 91.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 14:03:24,900 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0696) Prec@1 91.000 (88.571) Prec@5 100.000 (99.571) +2022-11-14 14:03:24,910 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0712) Prec@1 85.000 (88.125) Prec@5 100.000 (99.625) +2022-11-14 14:03:24,919 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0723) Prec@1 85.000 (87.778) Prec@5 99.000 (99.556) +2022-11-14 14:03:24,928 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0715) Prec@1 89.000 (87.900) Prec@5 99.000 (99.500) +2022-11-14 14:03:24,938 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0704) Prec@1 92.000 (88.273) Prec@5 100.000 (99.545) +2022-11-14 14:03:24,947 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0713) Prec@1 86.000 (88.083) Prec@5 99.000 (99.500) +2022-11-14 14:03:24,956 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0721) Prec@1 85.000 (87.846) Prec@5 100.000 (99.538) +2022-11-14 14:03:24,965 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0725) Prec@1 87.000 (87.786) Prec@5 100.000 (99.571) +2022-11-14 14:03:24,974 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0741) Prec@1 84.000 (87.533) Prec@5 98.000 (99.467) +2022-11-14 14:03:24,983 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0761) Prec@1 82.000 (87.188) Prec@5 100.000 (99.500) +2022-11-14 14:03:24,993 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0745) Prec@1 91.000 (87.412) Prec@5 98.000 (99.412) +2022-11-14 14:03:25,002 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0764) Prec@1 83.000 (87.167) Prec@5 99.000 (99.389) +2022-11-14 14:03:25,011 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0764) Prec@1 86.000 (87.105) Prec@5 98.000 (99.316) +2022-11-14 14:03:25,021 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0760) Prec@1 89.000 (87.200) Prec@5 100.000 (99.350) +2022-11-14 14:03:25,030 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0773) Prec@1 83.000 (87.000) Prec@5 98.000 (99.286) +2022-11-14 14:03:25,039 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0773) Prec@1 87.000 (87.000) Prec@5 99.000 (99.273) +2022-11-14 14:03:25,048 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0782) Prec@1 86.000 (86.957) Prec@5 99.000 (99.261) +2022-11-14 14:03:25,058 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0779) Prec@1 87.000 (86.958) Prec@5 99.000 (99.250) +2022-11-14 14:03:25,067 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0788) Prec@1 84.000 (86.840) Prec@5 100.000 (99.280) +2022-11-14 14:03:25,078 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0801) Prec@1 83.000 (86.692) Prec@5 99.000 (99.269) +2022-11-14 14:03:25,087 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0379 (0.0785) Prec@1 94.000 (86.963) Prec@5 100.000 (99.296) +2022-11-14 14:03:25,096 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0777) Prec@1 90.000 (87.071) Prec@5 99.000 (99.286) +2022-11-14 14:03:25,105 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0773) Prec@1 91.000 (87.207) Prec@5 99.000 (99.276) +2022-11-14 14:03:25,115 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0769) Prec@1 89.000 (87.267) Prec@5 100.000 (99.300) +2022-11-14 14:03:25,123 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0764) Prec@1 89.000 (87.323) Prec@5 100.000 (99.323) +2022-11-14 14:03:25,131 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0759) Prec@1 90.000 (87.406) Prec@5 99.000 (99.312) +2022-11-14 14:03:25,139 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0763) Prec@1 84.000 (87.303) Prec@5 98.000 (99.273) +2022-11-14 14:03:25,147 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0766) Prec@1 85.000 (87.235) Prec@5 100.000 (99.294) +2022-11-14 14:03:25,155 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0765) Prec@1 87.000 (87.229) Prec@5 100.000 (99.314) +2022-11-14 14:03:25,165 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0760) Prec@1 91.000 (87.333) Prec@5 99.000 (99.306) +2022-11-14 14:03:25,173 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0765) Prec@1 84.000 (87.243) Prec@5 98.000 (99.270) +2022-11-14 14:03:25,181 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0768) Prec@1 85.000 (87.184) Prec@5 100.000 (99.289) +2022-11-14 14:03:25,189 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0766) Prec@1 90.000 (87.256) Prec@5 99.000 (99.282) +2022-11-14 14:03:25,197 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0768) Prec@1 89.000 (87.300) Prec@5 100.000 (99.300) +2022-11-14 14:03:25,207 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0773) Prec@1 84.000 (87.220) Prec@5 98.000 (99.268) +2022-11-14 14:03:25,215 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0773) Prec@1 87.000 (87.214) Prec@5 97.000 (99.214) +2022-11-14 14:03:25,223 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0504 (0.0767) Prec@1 93.000 (87.349) Prec@5 100.000 (99.233) +2022-11-14 14:03:25,231 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0771) Prec@1 84.000 (87.273) Prec@5 98.000 (99.205) +2022-11-14 14:03:25,238 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0769) Prec@1 89.000 (87.311) Prec@5 99.000 (99.200) +2022-11-14 14:03:25,247 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0771) Prec@1 86.000 (87.283) Prec@5 99.000 (99.196) +2022-11-14 14:03:25,256 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0771) Prec@1 88.000 (87.298) Prec@5 100.000 (99.213) +2022-11-14 14:03:25,264 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0775) Prec@1 84.000 (87.229) Prec@5 100.000 (99.229) +2022-11-14 14:03:25,274 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0770) Prec@1 89.000 (87.265) Prec@5 100.000 (99.245) +2022-11-14 14:03:25,283 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0776) Prec@1 83.000 (87.180) Prec@5 98.000 (99.220) +2022-11-14 14:03:25,292 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0774) Prec@1 87.000 (87.176) Prec@5 100.000 (99.235) +2022-11-14 14:03:25,301 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0777) Prec@1 85.000 (87.135) Prec@5 99.000 (99.231) +2022-11-14 14:03:25,310 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0777) Prec@1 87.000 (87.132) Prec@5 99.000 (99.226) +2022-11-14 14:03:25,318 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0774) Prec@1 90.000 (87.185) Prec@5 99.000 (99.222) +2022-11-14 14:03:25,327 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0772) Prec@1 88.000 (87.200) Prec@5 100.000 (99.236) +2022-11-14 14:03:25,337 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0772) Prec@1 88.000 (87.214) Prec@5 99.000 (99.232) +2022-11-14 14:03:25,346 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0775) Prec@1 85.000 (87.175) Prec@5 100.000 (99.246) +2022-11-14 14:03:25,354 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0777) Prec@1 88.000 (87.190) Prec@5 99.000 (99.241) +2022-11-14 14:03:25,364 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1094 (0.0782) Prec@1 82.000 (87.102) Prec@5 100.000 (99.254) +2022-11-14 14:03:25,373 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0782) Prec@1 85.000 (87.067) Prec@5 100.000 (99.267) +2022-11-14 14:03:25,382 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0784) Prec@1 82.000 (86.984) Prec@5 100.000 (99.279) +2022-11-14 14:03:25,391 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0784) Prec@1 88.000 (87.000) Prec@5 100.000 (99.290) +2022-11-14 14:03:25,399 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0780) Prec@1 92.000 (87.079) Prec@5 100.000 (99.302) +2022-11-14 14:03:25,407 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0778) Prec@1 88.000 (87.094) Prec@5 100.000 (99.312) +2022-11-14 14:03:25,415 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0780) Prec@1 85.000 (87.062) Prec@5 100.000 (99.323) +2022-11-14 14:03:25,423 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0779) Prec@1 91.000 (87.121) Prec@5 99.000 (99.318) +2022-11-14 14:03:25,432 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0775) Prec@1 93.000 (87.209) Prec@5 99.000 (99.313) +2022-11-14 14:03:25,441 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0779) Prec@1 81.000 (87.118) Prec@5 97.000 (99.279) +2022-11-14 14:03:25,453 Test: [68/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0776) Prec@1 91.000 (87.174) Prec@5 99.000 (99.275) +2022-11-14 14:03:25,467 Test: [69/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0777) Prec@1 87.000 (87.171) Prec@5 99.000 (99.271) +2022-11-14 14:03:25,479 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0776) Prec@1 88.000 (87.183) Prec@5 100.000 (99.282) +2022-11-14 14:03:25,491 Test: [71/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0774) Prec@1 91.000 (87.236) Prec@5 100.000 (99.292) +2022-11-14 14:03:25,504 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0464 (0.0770) Prec@1 91.000 (87.288) Prec@5 100.000 (99.301) +2022-11-14 14:03:25,515 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0766) Prec@1 94.000 (87.378) Prec@5 99.000 (99.297) +2022-11-14 14:03:25,525 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0767) Prec@1 85.000 (87.347) Prec@5 100.000 (99.307) +2022-11-14 14:03:25,535 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0764) Prec@1 91.000 (87.395) Prec@5 100.000 (99.316) +2022-11-14 14:03:25,545 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0763) Prec@1 90.000 (87.429) Prec@5 99.000 (99.312) +2022-11-14 14:03:25,554 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0765) Prec@1 85.000 (87.397) Prec@5 98.000 (99.295) +2022-11-14 14:03:25,563 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0765) Prec@1 85.000 (87.367) Prec@5 100.000 (99.304) +2022-11-14 14:03:25,573 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0763) Prec@1 91.000 (87.412) Prec@5 100.000 (99.312) +2022-11-14 14:03:25,582 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0762) Prec@1 89.000 (87.432) Prec@5 97.000 (99.284) +2022-11-14 14:03:25,591 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0761) Prec@1 89.000 (87.451) Prec@5 100.000 (99.293) +2022-11-14 14:03:25,601 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0762) Prec@1 87.000 (87.446) Prec@5 100.000 (99.301) +2022-11-14 14:03:25,610 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0762) Prec@1 87.000 (87.440) Prec@5 100.000 (99.310) +2022-11-14 14:03:25,619 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0763) Prec@1 84.000 (87.400) Prec@5 100.000 (99.318) +2022-11-14 14:03:25,628 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0765) Prec@1 84.000 (87.360) Prec@5 100.000 (99.326) +2022-11-14 14:03:25,637 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0766) Prec@1 86.000 (87.345) Prec@5 99.000 (99.322) +2022-11-14 14:03:25,647 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0765) Prec@1 91.000 (87.386) Prec@5 99.000 (99.318) +2022-11-14 14:03:25,656 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0764) Prec@1 89.000 (87.404) Prec@5 99.000 (99.315) +2022-11-14 14:03:25,665 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0764) Prec@1 88.000 (87.411) Prec@5 100.000 (99.322) +2022-11-14 14:03:25,674 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0763) Prec@1 88.000 (87.418) Prec@5 100.000 (99.330) +2022-11-14 14:03:25,683 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0761) Prec@1 89.000 (87.435) Prec@5 100.000 (99.337) +2022-11-14 14:03:25,693 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0762) Prec@1 86.000 (87.419) Prec@5 100.000 (99.344) +2022-11-14 14:03:25,701 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0761) Prec@1 90.000 (87.447) Prec@5 99.000 (99.340) +2022-11-14 14:03:25,708 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0760) Prec@1 87.000 (87.442) Prec@5 100.000 (99.347) +2022-11-14 14:03:25,716 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0759) Prec@1 88.000 (87.448) Prec@5 100.000 (99.354) +2022-11-14 14:03:25,724 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0758) Prec@1 90.000 (87.474) Prec@5 98.000 (99.340) +2022-11-14 14:03:25,732 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0761) Prec@1 84.000 (87.439) Prec@5 100.000 (99.347) +2022-11-14 14:03:25,741 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0761) Prec@1 89.000 (87.455) Prec@5 100.000 (99.354) +2022-11-14 14:03:25,749 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0760) Prec@1 87.000 (87.450) Prec@5 100.000 (99.360) +2022-11-14 14:03:25,803 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:03:26,102 Epoch: [139][0/500] Time 0.025 (0.025) Data 0.218 (0.218) Loss 0.0319 (0.0319) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:26,312 Epoch: [139][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.0510 (0.0414) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:03:26,519 Epoch: [139][20/500] Time 0.017 (0.019) Data 0.001 (0.012) Loss 0.0516 (0.0448) Prec@1 91.000 (92.667) Prec@5 99.000 (99.667) +2022-11-14 14:03:26,755 Epoch: [139][30/500] Time 0.023 (0.019) Data 0.002 (0.009) Loss 0.0391 (0.0434) Prec@1 93.000 (92.750) Prec@5 100.000 (99.750) +2022-11-14 14:03:27,016 Epoch: [139][40/500] Time 0.027 (0.020) Data 0.002 (0.007) Loss 0.0430 (0.0433) Prec@1 94.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:03:27,259 Epoch: [139][50/500] Time 0.023 (0.021) Data 0.001 (0.006) Loss 0.0513 (0.0447) Prec@1 91.000 (92.667) Prec@5 99.000 (99.667) +2022-11-14 14:03:27,508 Epoch: [139][60/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0384 (0.0438) Prec@1 94.000 (92.857) Prec@5 100.000 (99.714) +2022-11-14 14:03:27,908 Epoch: [139][70/500] Time 0.043 (0.023) Data 0.002 (0.005) Loss 0.0437 (0.0437) Prec@1 93.000 (92.875) Prec@5 100.000 (99.750) +2022-11-14 14:03:28,365 Epoch: [139][80/500] Time 0.042 (0.025) Data 0.002 (0.004) Loss 0.0471 (0.0441) Prec@1 91.000 (92.667) Prec@5 100.000 (99.778) +2022-11-14 14:03:28,816 Epoch: [139][90/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0799 (0.0477) Prec@1 87.000 (92.100) Prec@5 99.000 (99.700) +2022-11-14 14:03:29,272 Epoch: [139][100/500] Time 0.043 (0.028) Data 0.002 (0.004) Loss 0.0451 (0.0475) Prec@1 93.000 (92.182) Prec@5 99.000 (99.636) +2022-11-14 14:03:29,723 Epoch: [139][110/500] Time 0.043 (0.029) Data 0.002 (0.004) Loss 0.0418 (0.0470) Prec@1 93.000 (92.250) Prec@5 100.000 (99.667) +2022-11-14 14:03:30,177 Epoch: [139][120/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.0394 (0.0464) Prec@1 96.000 (92.538) Prec@5 100.000 (99.692) +2022-11-14 14:03:30,625 Epoch: [139][130/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0445 (0.0463) Prec@1 92.000 (92.500) Prec@5 99.000 (99.643) +2022-11-14 14:03:31,079 Epoch: [139][140/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0363 (0.0456) Prec@1 95.000 (92.667) Prec@5 99.000 (99.600) +2022-11-14 14:03:31,528 Epoch: [139][150/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0722 (0.0473) Prec@1 88.000 (92.375) Prec@5 100.000 (99.625) +2022-11-14 14:03:31,981 Epoch: [139][160/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0376 (0.0467) Prec@1 92.000 (92.353) Prec@5 100.000 (99.647) +2022-11-14 14:03:32,431 Epoch: [139][170/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0468 (0.0467) Prec@1 92.000 (92.333) Prec@5 99.000 (99.611) +2022-11-14 14:03:32,885 Epoch: [139][180/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0734 (0.0481) Prec@1 88.000 (92.105) Prec@5 99.000 (99.579) +2022-11-14 14:03:33,324 Epoch: [139][190/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0637 (0.0489) Prec@1 88.000 (91.900) Prec@5 100.000 (99.600) +2022-11-14 14:03:33,774 Epoch: [139][200/500] Time 0.045 (0.034) Data 0.001 (0.003) Loss 0.0501 (0.0489) Prec@1 92.000 (91.905) Prec@5 100.000 (99.619) +2022-11-14 14:03:34,223 Epoch: [139][210/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0597 (0.0494) Prec@1 90.000 (91.818) Prec@5 99.000 (99.591) +2022-11-14 14:03:34,675 Epoch: [139][220/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0442 (0.0492) Prec@1 91.000 (91.783) Prec@5 100.000 (99.609) +2022-11-14 14:03:35,127 Epoch: [139][230/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0611 (0.0497) Prec@1 88.000 (91.625) Prec@5 99.000 (99.583) +2022-11-14 14:03:35,583 Epoch: [139][240/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0630 (0.0502) Prec@1 89.000 (91.520) Prec@5 100.000 (99.600) +2022-11-14 14:03:36,040 Epoch: [139][250/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0702 (0.0510) Prec@1 89.000 (91.423) Prec@5 100.000 (99.615) +2022-11-14 14:03:36,500 Epoch: [139][260/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0496 (0.0509) Prec@1 92.000 (91.444) Prec@5 100.000 (99.630) +2022-11-14 14:03:36,945 Epoch: [139][270/500] Time 0.043 (0.036) Data 0.001 (0.003) Loss 0.0549 (0.0511) Prec@1 92.000 (91.464) Prec@5 99.000 (99.607) +2022-11-14 14:03:37,395 Epoch: [139][280/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0579 (0.0513) Prec@1 90.000 (91.414) Prec@5 98.000 (99.552) +2022-11-14 14:03:37,839 Epoch: [139][290/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0498 (0.0513) Prec@1 92.000 (91.433) Prec@5 100.000 (99.567) +2022-11-14 14:03:38,290 Epoch: [139][300/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0472 (0.0511) Prec@1 93.000 (91.484) Prec@5 100.000 (99.581) +2022-11-14 14:03:38,743 Epoch: [139][310/500] Time 0.042 (0.036) Data 0.001 (0.003) Loss 0.0354 (0.0506) Prec@1 93.000 (91.531) Prec@5 100.000 (99.594) +2022-11-14 14:03:39,199 Epoch: [139][320/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0377 (0.0503) Prec@1 95.000 (91.636) Prec@5 100.000 (99.606) +2022-11-14 14:03:39,636 Epoch: [139][330/500] Time 0.043 (0.036) Data 0.001 (0.002) Loss 0.0340 (0.0498) Prec@1 95.000 (91.735) Prec@5 100.000 (99.618) +2022-11-14 14:03:40,083 Epoch: [139][340/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0634 (0.0502) Prec@1 90.000 (91.686) Prec@5 100.000 (99.629) +2022-11-14 14:03:40,536 Epoch: [139][350/500] Time 0.042 (0.037) Data 0.001 (0.002) Loss 0.1209 (0.0521) Prec@1 80.000 (91.361) Prec@5 97.000 (99.556) +2022-11-14 14:03:40,993 Epoch: [139][360/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0644 (0.0525) Prec@1 90.000 (91.324) Prec@5 100.000 (99.568) +2022-11-14 14:03:41,441 Epoch: [139][370/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0466 (0.0523) Prec@1 92.000 (91.342) Prec@5 100.000 (99.579) +2022-11-14 14:03:41,890 Epoch: [139][380/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.0383 (0.0520) Prec@1 93.000 (91.385) Prec@5 100.000 (99.590) +2022-11-14 14:03:42,341 Epoch: [139][390/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0437 (0.0517) Prec@1 92.000 (91.400) Prec@5 100.000 (99.600) +2022-11-14 14:03:42,796 Epoch: [139][400/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0658 (0.0521) Prec@1 90.000 (91.366) Prec@5 100.000 (99.610) +2022-11-14 14:03:43,241 Epoch: [139][410/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0687 (0.0525) Prec@1 88.000 (91.286) Prec@5 100.000 (99.619) +2022-11-14 14:03:43,683 Epoch: [139][420/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0487 (0.0524) Prec@1 92.000 (91.302) Prec@5 100.000 (99.628) +2022-11-14 14:03:44,129 Epoch: [139][430/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0614 (0.0526) Prec@1 90.000 (91.273) Prec@5 100.000 (99.636) +2022-11-14 14:03:44,575 Epoch: [139][440/500] Time 0.040 (0.037) Data 0.001 (0.002) Loss 0.0703 (0.0530) Prec@1 87.000 (91.178) Prec@5 99.000 (99.622) +2022-11-14 14:03:45,025 Epoch: [139][450/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0670 (0.0533) Prec@1 88.000 (91.109) Prec@5 100.000 (99.630) +2022-11-14 14:03:45,467 Epoch: [139][460/500] Time 0.043 (0.037) Data 0.001 (0.002) Loss 0.0534 (0.0533) Prec@1 91.000 (91.106) Prec@5 99.000 (99.617) +2022-11-14 14:03:45,910 Epoch: [139][470/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0623 (0.0535) Prec@1 89.000 (91.062) Prec@5 100.000 (99.625) +2022-11-14 14:03:46,356 Epoch: [139][480/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0776 (0.0540) Prec@1 89.000 (91.020) Prec@5 100.000 (99.633) +2022-11-14 14:03:46,795 Epoch: [139][490/500] Time 0.038 (0.037) Data 0.003 (0.002) Loss 0.0450 (0.0538) Prec@1 95.000 (91.100) Prec@5 99.000 (99.620) +2022-11-14 14:03:47,199 Epoch: [139][499/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0923 (0.0546) Prec@1 83.000 (90.941) Prec@5 98.000 (99.588) +2022-11-14 14:03:47,509 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0576 (0.0576) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:03:47,520 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0801 (0.0688) Prec@1 85.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 14:03:47,530 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0766) Prec@1 84.000 (86.000) Prec@5 98.000 (98.667) +2022-11-14 14:03:47,540 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0809) Prec@1 86.000 (86.000) Prec@5 99.000 (98.750) +2022-11-14 14:03:47,548 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0830) Prec@1 85.000 (85.800) Prec@5 100.000 (99.000) +2022-11-14 14:03:47,556 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0786) Prec@1 91.000 (86.667) Prec@5 100.000 (99.167) +2022-11-14 14:03:47,565 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0768) Prec@1 87.000 (86.714) Prec@5 100.000 (99.286) +2022-11-14 14:03:47,574 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0788) Prec@1 85.000 (86.500) Prec@5 99.000 (99.250) +2022-11-14 14:03:47,581 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0791) Prec@1 89.000 (86.778) Prec@5 98.000 (99.111) +2022-11-14 14:03:47,589 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0796) Prec@1 87.000 (86.800) Prec@5 96.000 (98.800) +2022-11-14 14:03:47,598 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0799) Prec@1 87.000 (86.818) Prec@5 100.000 (98.909) +2022-11-14 14:03:47,608 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0801) Prec@1 85.000 (86.667) Prec@5 99.000 (98.917) +2022-11-14 14:03:47,617 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0797) Prec@1 86.000 (86.615) Prec@5 100.000 (99.000) +2022-11-14 14:03:47,626 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0796) Prec@1 87.000 (86.643) Prec@5 97.000 (98.857) +2022-11-14 14:03:47,636 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0802) Prec@1 84.000 (86.467) Prec@5 100.000 (98.933) +2022-11-14 14:03:47,645 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0797) Prec@1 89.000 (86.625) Prec@5 100.000 (99.000) +2022-11-14 14:03:47,654 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0788) Prec@1 90.000 (86.824) Prec@5 99.000 (99.000) +2022-11-14 14:03:47,663 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0795) Prec@1 87.000 (86.833) Prec@5 100.000 (99.056) +2022-11-14 14:03:47,672 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0803) Prec@1 85.000 (86.737) Prec@5 97.000 (98.947) +2022-11-14 14:03:47,681 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.0820) Prec@1 81.000 (86.450) Prec@5 98.000 (98.900) +2022-11-14 14:03:47,693 Test: [20/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0810) Prec@1 89.000 (86.571) Prec@5 99.000 (98.905) +2022-11-14 14:03:47,704 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0805) Prec@1 87.000 (86.591) Prec@5 100.000 (98.955) +2022-11-14 14:03:47,713 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1214 (0.0823) Prec@1 78.000 (86.217) Prec@5 100.000 (99.000) +2022-11-14 14:03:47,722 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0818) Prec@1 91.000 (86.417) Prec@5 100.000 (99.042) +2022-11-14 14:03:47,734 Test: [24/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0816) Prec@1 85.000 (86.360) Prec@5 100.000 (99.080) +2022-11-14 14:03:47,745 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1251 (0.0832) Prec@1 78.000 (86.038) Prec@5 98.000 (99.038) +2022-11-14 14:03:47,754 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0822) Prec@1 92.000 (86.259) Prec@5 100.000 (99.074) +2022-11-14 14:03:47,763 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0822) Prec@1 86.000 (86.250) Prec@5 100.000 (99.107) +2022-11-14 14:03:47,775 Test: [28/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0816) Prec@1 89.000 (86.345) Prec@5 100.000 (99.138) +2022-11-14 14:03:47,786 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0811) Prec@1 88.000 (86.400) Prec@5 100.000 (99.167) +2022-11-14 14:03:47,796 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0810) Prec@1 85.000 (86.355) Prec@5 99.000 (99.161) +2022-11-14 14:03:47,804 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0809) Prec@1 86.000 (86.344) Prec@5 100.000 (99.188) +2022-11-14 14:03:47,816 Test: [32/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0815) Prec@1 82.000 (86.212) Prec@5 100.000 (99.212) +2022-11-14 14:03:47,828 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0819) Prec@1 81.000 (86.059) Prec@5 100.000 (99.235) +2022-11-14 14:03:47,837 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0818) Prec@1 87.000 (86.086) Prec@5 99.000 (99.229) +2022-11-14 14:03:47,845 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0817) Prec@1 89.000 (86.167) Prec@5 99.000 (99.222) +2022-11-14 14:03:47,857 Test: [36/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0818) Prec@1 85.000 (86.135) Prec@5 98.000 (99.189) +2022-11-14 14:03:47,869 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0827) Prec@1 79.000 (85.947) Prec@5 99.000 (99.184) +2022-11-14 14:03:47,877 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0823) Prec@1 89.000 (86.026) Prec@5 98.000 (99.154) +2022-11-14 14:03:47,885 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0819) Prec@1 90.000 (86.125) Prec@5 99.000 (99.150) +2022-11-14 14:03:47,896 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0827) Prec@1 82.000 (86.024) Prec@5 97.000 (99.098) +2022-11-14 14:03:47,907 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0824) Prec@1 88.000 (86.071) Prec@5 99.000 (99.095) +2022-11-14 14:03:47,916 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0816) Prec@1 90.000 (86.163) Prec@5 99.000 (99.093) +2022-11-14 14:03:47,925 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0814) Prec@1 88.000 (86.205) Prec@5 97.000 (99.045) +2022-11-14 14:03:47,936 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0817) Prec@1 85.000 (86.178) Prec@5 98.000 (99.022) +2022-11-14 14:03:47,945 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1226 (0.0826) Prec@1 78.000 (86.000) Prec@5 99.000 (99.022) +2022-11-14 14:03:47,955 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0830) Prec@1 84.000 (85.957) Prec@5 100.000 (99.043) +2022-11-14 14:03:47,963 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0834) Prec@1 82.000 (85.875) Prec@5 99.000 (99.042) +2022-11-14 14:03:47,971 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0835) Prec@1 87.000 (85.898) Prec@5 99.000 (99.041) +2022-11-14 14:03:47,979 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0837) Prec@1 87.000 (85.920) Prec@5 99.000 (99.040) +2022-11-14 14:03:47,988 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0833) Prec@1 89.000 (85.980) Prec@5 100.000 (99.059) +2022-11-14 14:03:47,998 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.0840) Prec@1 81.000 (85.885) Prec@5 99.000 (99.058) +2022-11-14 14:03:48,006 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0839) Prec@1 86.000 (85.887) Prec@5 100.000 (99.075) +2022-11-14 14:03:48,017 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0835) Prec@1 88.000 (85.926) Prec@5 98.000 (99.056) +2022-11-14 14:03:48,026 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0838) Prec@1 86.000 (85.927) Prec@5 100.000 (99.073) +2022-11-14 14:03:48,035 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0833) Prec@1 90.000 (86.000) Prec@5 99.000 (99.071) +2022-11-14 14:03:48,044 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0835) Prec@1 85.000 (85.982) Prec@5 99.000 (99.070) +2022-11-14 14:03:48,053 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0833) Prec@1 87.000 (86.000) Prec@5 99.000 (99.069) +2022-11-14 14:03:48,062 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1355 (0.0842) Prec@1 75.000 (85.814) Prec@5 100.000 (99.085) +2022-11-14 14:03:48,070 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0845) Prec@1 85.000 (85.800) Prec@5 100.000 (99.100) +2022-11-14 14:03:48,080 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0849) Prec@1 84.000 (85.770) Prec@5 99.000 (99.098) +2022-11-14 14:03:48,089 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0850) Prec@1 84.000 (85.742) Prec@5 99.000 (99.097) +2022-11-14 14:03:48,098 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0846) Prec@1 89.000 (85.794) Prec@5 100.000 (99.111) +2022-11-14 14:03:48,107 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0841) Prec@1 90.000 (85.859) Prec@5 100.000 (99.125) +2022-11-14 14:03:48,116 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0844) Prec@1 83.000 (85.815) Prec@5 99.000 (99.123) +2022-11-14 14:03:48,125 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0847) Prec@1 82.000 (85.758) Prec@5 98.000 (99.106) +2022-11-14 14:03:48,135 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0840) Prec@1 93.000 (85.866) Prec@5 100.000 (99.119) +2022-11-14 14:03:48,144 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0839) Prec@1 87.000 (85.882) Prec@5 98.000 (99.103) +2022-11-14 14:03:48,152 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0837) Prec@1 86.000 (85.884) Prec@5 99.000 (99.101) +2022-11-14 14:03:48,161 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0837) Prec@1 86.000 (85.886) Prec@5 98.000 (99.086) +2022-11-14 14:03:48,169 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.0841) Prec@1 82.000 (85.831) Prec@5 98.000 (99.070) +2022-11-14 14:03:48,177 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0841) Prec@1 87.000 (85.847) Prec@5 99.000 (99.069) +2022-11-14 14:03:48,184 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0838) Prec@1 93.000 (85.945) Prec@5 99.000 (99.068) +2022-11-14 14:03:48,193 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0834) Prec@1 91.000 (86.014) Prec@5 100.000 (99.081) +2022-11-14 14:03:48,202 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0835) Prec@1 85.000 (86.000) Prec@5 100.000 (99.093) +2022-11-14 14:03:48,212 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0835) Prec@1 85.000 (85.987) Prec@5 99.000 (99.092) +2022-11-14 14:03:48,221 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0834) Prec@1 88.000 (86.013) Prec@5 98.000 (99.078) +2022-11-14 14:03:48,230 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0836) Prec@1 85.000 (86.000) Prec@5 99.000 (99.077) +2022-11-14 14:03:48,240 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0834) Prec@1 87.000 (86.013) Prec@5 100.000 (99.089) +2022-11-14 14:03:48,249 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0834) Prec@1 84.000 (85.987) Prec@5 100.000 (99.100) +2022-11-14 14:03:48,258 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0833) Prec@1 89.000 (86.025) Prec@5 99.000 (99.099) +2022-11-14 14:03:48,267 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0830) Prec@1 88.000 (86.049) Prec@5 100.000 (99.110) +2022-11-14 14:03:48,276 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0830) Prec@1 87.000 (86.060) Prec@5 99.000 (99.108) +2022-11-14 14:03:48,285 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0830) Prec@1 85.000 (86.048) Prec@5 100.000 (99.119) +2022-11-14 14:03:48,294 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0831) Prec@1 86.000 (86.047) Prec@5 100.000 (99.129) +2022-11-14 14:03:48,304 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0832) Prec@1 86.000 (86.047) Prec@5 100.000 (99.140) +2022-11-14 14:03:48,313 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0830) Prec@1 89.000 (86.080) Prec@5 100.000 (99.149) +2022-11-14 14:03:48,322 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0829) Prec@1 90.000 (86.125) Prec@5 98.000 (99.136) +2022-11-14 14:03:48,331 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0829) Prec@1 87.000 (86.135) Prec@5 100.000 (99.146) +2022-11-14 14:03:48,340 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0830) Prec@1 87.000 (86.144) Prec@5 100.000 (99.156) +2022-11-14 14:03:48,350 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0827) Prec@1 89.000 (86.176) Prec@5 100.000 (99.165) +2022-11-14 14:03:48,359 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0826) Prec@1 88.000 (86.196) Prec@5 99.000 (99.163) +2022-11-14 14:03:48,368 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0828) Prec@1 82.000 (86.151) Prec@5 100.000 (99.172) +2022-11-14 14:03:48,378 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0829) Prec@1 86.000 (86.149) Prec@5 100.000 (99.181) +2022-11-14 14:03:48,387 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0831) Prec@1 82.000 (86.105) Prec@5 100.000 (99.189) +2022-11-14 14:03:48,396 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0830) Prec@1 89.000 (86.135) Prec@5 99.000 (99.188) +2022-11-14 14:03:48,405 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0826) Prec@1 93.000 (86.206) Prec@5 100.000 (99.196) +2022-11-14 14:03:48,415 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0826) Prec@1 90.000 (86.245) Prec@5 98.000 (99.184) +2022-11-14 14:03:48,423 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0826) Prec@1 85.000 (86.232) Prec@5 99.000 (99.182) +2022-11-14 14:03:48,431 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0826) Prec@1 86.000 (86.230) Prec@5 98.000 (99.170) +2022-11-14 14:03:48,486 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:03:48,809 Epoch: [140][0/500] Time 0.025 (0.025) Data 0.238 (0.238) Loss 0.0578 (0.0578) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:03:49,014 Epoch: [140][10/500] Time 0.021 (0.019) Data 0.001 (0.023) Loss 0.0654 (0.0616) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:03:49,206 Epoch: [140][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0234 (0.0489) Prec@1 96.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:03:49,450 Epoch: [140][30/500] Time 0.025 (0.019) Data 0.002 (0.009) Loss 0.0636 (0.0526) Prec@1 91.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:03:49,726 Epoch: [140][40/500] Time 0.025 (0.020) Data 0.002 (0.007) Loss 0.0437 (0.0508) Prec@1 93.000 (91.400) Prec@5 100.000 (99.600) +2022-11-14 14:03:49,997 Epoch: [140][50/500] Time 0.025 (0.021) Data 0.002 (0.006) Loss 0.0506 (0.0508) Prec@1 92.000 (91.500) Prec@5 100.000 (99.667) +2022-11-14 14:03:50,270 Epoch: [140][60/500] Time 0.024 (0.021) Data 0.001 (0.006) Loss 0.0755 (0.0543) Prec@1 88.000 (91.000) Prec@5 100.000 (99.714) +2022-11-14 14:03:50,545 Epoch: [140][70/500] Time 0.027 (0.022) Data 0.002 (0.005) Loss 0.0560 (0.0545) Prec@1 92.000 (91.125) Prec@5 100.000 (99.750) +2022-11-14 14:03:50,822 Epoch: [140][80/500] Time 0.026 (0.022) Data 0.002 (0.005) Loss 0.0752 (0.0568) Prec@1 87.000 (90.667) Prec@5 100.000 (99.778) +2022-11-14 14:03:51,099 Epoch: [140][90/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0456 (0.0557) Prec@1 93.000 (90.900) Prec@5 100.000 (99.800) +2022-11-14 14:03:51,378 Epoch: [140][100/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0374 (0.0540) Prec@1 94.000 (91.182) Prec@5 100.000 (99.818) +2022-11-14 14:03:51,653 Epoch: [140][110/500] Time 0.026 (0.023) Data 0.001 (0.004) Loss 0.0530 (0.0539) Prec@1 90.000 (91.083) Prec@5 99.000 (99.750) +2022-11-14 14:03:51,927 Epoch: [140][120/500] Time 0.026 (0.023) Data 0.001 (0.004) Loss 0.0720 (0.0553) Prec@1 88.000 (90.846) Prec@5 98.000 (99.615) +2022-11-14 14:03:52,202 Epoch: [140][130/500] Time 0.026 (0.023) Data 0.001 (0.003) Loss 0.0671 (0.0562) Prec@1 89.000 (90.714) Prec@5 100.000 (99.643) +2022-11-14 14:03:52,480 Epoch: [140][140/500] Time 0.026 (0.023) Data 0.001 (0.003) Loss 0.0569 (0.0562) Prec@1 90.000 (90.667) Prec@5 99.000 (99.600) +2022-11-14 14:03:52,756 Epoch: [140][150/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0579 (0.0563) Prec@1 92.000 (90.750) Prec@5 100.000 (99.625) +2022-11-14 14:03:53,032 Epoch: [140][160/500] Time 0.025 (0.023) Data 0.001 (0.003) Loss 0.0446 (0.0556) Prec@1 92.000 (90.824) Prec@5 100.000 (99.647) +2022-11-14 14:03:53,305 Epoch: [140][170/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0569 (0.0557) Prec@1 90.000 (90.778) Prec@5 100.000 (99.667) +2022-11-14 14:03:53,585 Epoch: [140][180/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0569 (0.0558) Prec@1 90.000 (90.737) Prec@5 100.000 (99.684) +2022-11-14 14:03:53,859 Epoch: [140][190/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0530 (0.0556) Prec@1 90.000 (90.700) Prec@5 100.000 (99.700) +2022-11-14 14:03:54,218 Epoch: [140][200/500] Time 0.042 (0.024) Data 0.002 (0.003) Loss 0.0817 (0.0569) Prec@1 85.000 (90.429) Prec@5 99.000 (99.667) +2022-11-14 14:03:54,632 Epoch: [140][210/500] Time 0.040 (0.024) Data 0.001 (0.003) Loss 0.0410 (0.0562) Prec@1 91.000 (90.455) Prec@5 100.000 (99.682) +2022-11-14 14:03:55,050 Epoch: [140][220/500] Time 0.039 (0.025) Data 0.002 (0.003) Loss 0.0550 (0.0561) Prec@1 91.000 (90.478) Prec@5 100.000 (99.696) +2022-11-14 14:03:55,471 Epoch: [140][230/500] Time 0.039 (0.026) Data 0.001 (0.003) Loss 0.0453 (0.0557) Prec@1 94.000 (90.625) Prec@5 100.000 (99.708) +2022-11-14 14:03:55,901 Epoch: [140][240/500] Time 0.044 (0.026) Data 0.002 (0.003) Loss 0.0809 (0.0567) Prec@1 85.000 (90.400) Prec@5 100.000 (99.720) +2022-11-14 14:03:56,321 Epoch: [140][250/500] Time 0.039 (0.027) Data 0.001 (0.003) Loss 0.0618 (0.0569) Prec@1 89.000 (90.346) Prec@5 100.000 (99.731) +2022-11-14 14:03:56,741 Epoch: [140][260/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0696 (0.0573) Prec@1 88.000 (90.259) Prec@5 100.000 (99.741) +2022-11-14 14:03:57,168 Epoch: [140][270/500] Time 0.040 (0.027) Data 0.002 (0.003) Loss 0.0432 (0.0568) Prec@1 92.000 (90.321) Prec@5 100.000 (99.750) +2022-11-14 14:03:57,596 Epoch: [140][280/500] Time 0.041 (0.028) Data 0.002 (0.003) Loss 0.0446 (0.0564) Prec@1 94.000 (90.448) Prec@5 100.000 (99.759) +2022-11-14 14:03:58,018 Epoch: [140][290/500] Time 0.041 (0.028) Data 0.002 (0.003) Loss 0.0696 (0.0568) Prec@1 89.000 (90.400) Prec@5 100.000 (99.767) +2022-11-14 14:03:58,433 Epoch: [140][300/500] Time 0.041 (0.028) Data 0.002 (0.003) Loss 0.0532 (0.0567) Prec@1 89.000 (90.355) Prec@5 100.000 (99.774) +2022-11-14 14:03:58,857 Epoch: [140][310/500] Time 0.040 (0.029) Data 0.001 (0.002) Loss 0.0639 (0.0569) Prec@1 88.000 (90.281) Prec@5 99.000 (99.750) +2022-11-14 14:03:59,277 Epoch: [140][320/500] Time 0.036 (0.029) Data 0.002 (0.002) Loss 0.0393 (0.0564) Prec@1 91.000 (90.303) Prec@5 100.000 (99.758) +2022-11-14 14:03:59,694 Epoch: [140][330/500] Time 0.039 (0.029) Data 0.003 (0.002) Loss 0.0439 (0.0560) Prec@1 93.000 (90.382) Prec@5 100.000 (99.765) +2022-11-14 14:04:00,124 Epoch: [140][340/500] Time 0.038 (0.029) Data 0.002 (0.002) Loss 0.0709 (0.0565) Prec@1 87.000 (90.286) Prec@5 99.000 (99.743) +2022-11-14 14:04:00,540 Epoch: [140][350/500] Time 0.037 (0.030) Data 0.002 (0.002) Loss 0.0584 (0.0565) Prec@1 91.000 (90.306) Prec@5 100.000 (99.750) +2022-11-14 14:04:00,962 Epoch: [140][360/500] Time 0.041 (0.030) Data 0.002 (0.002) Loss 0.0518 (0.0564) Prec@1 91.000 (90.324) Prec@5 100.000 (99.757) +2022-11-14 14:04:01,364 Epoch: [140][370/500] Time 0.037 (0.030) Data 0.002 (0.002) Loss 0.0576 (0.0564) Prec@1 91.000 (90.342) Prec@5 100.000 (99.763) +2022-11-14 14:04:01,772 Epoch: [140][380/500] Time 0.039 (0.030) Data 0.002 (0.002) Loss 0.0777 (0.0570) Prec@1 88.000 (90.282) Prec@5 99.000 (99.744) +2022-11-14 14:04:02,198 Epoch: [140][390/500] Time 0.040 (0.030) Data 0.001 (0.002) Loss 0.0474 (0.0567) Prec@1 94.000 (90.375) Prec@5 99.000 (99.725) +2022-11-14 14:04:02,616 Epoch: [140][400/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.0558 (0.0567) Prec@1 91.000 (90.390) Prec@5 99.000 (99.707) +2022-11-14 14:04:03,039 Epoch: [140][410/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.0857 (0.0574) Prec@1 85.000 (90.262) Prec@5 99.000 (99.690) +2022-11-14 14:04:03,451 Epoch: [140][420/500] Time 0.039 (0.031) Data 0.002 (0.002) Loss 0.0511 (0.0573) Prec@1 91.000 (90.279) Prec@5 100.000 (99.698) +2022-11-14 14:04:03,868 Epoch: [140][430/500] Time 0.039 (0.031) Data 0.001 (0.002) Loss 0.0636 (0.0574) Prec@1 88.000 (90.227) Prec@5 100.000 (99.705) +2022-11-14 14:04:04,285 Epoch: [140][440/500] Time 0.037 (0.031) Data 0.002 (0.002) Loss 0.0798 (0.0579) Prec@1 86.000 (90.133) Prec@5 99.000 (99.689) +2022-11-14 14:04:04,703 Epoch: [140][450/500] Time 0.036 (0.031) Data 0.002 (0.002) Loss 0.0371 (0.0574) Prec@1 95.000 (90.239) Prec@5 100.000 (99.696) +2022-11-14 14:04:05,107 Epoch: [140][460/500] Time 0.038 (0.031) Data 0.002 (0.002) Loss 0.0569 (0.0574) Prec@1 91.000 (90.255) Prec@5 100.000 (99.702) +2022-11-14 14:04:05,523 Epoch: [140][470/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.0363 (0.0570) Prec@1 94.000 (90.333) Prec@5 100.000 (99.708) +2022-11-14 14:04:05,940 Epoch: [140][480/500] Time 0.039 (0.032) Data 0.002 (0.002) Loss 0.0359 (0.0566) Prec@1 94.000 (90.408) Prec@5 100.000 (99.714) +2022-11-14 14:04:06,361 Epoch: [140][490/500] Time 0.042 (0.032) Data 0.001 (0.002) Loss 0.0531 (0.0565) Prec@1 89.000 (90.380) Prec@5 99.000 (99.700) +2022-11-14 14:04:06,728 Epoch: [140][499/500] Time 0.038 (0.032) Data 0.002 (0.002) Loss 0.0510 (0.0564) Prec@1 91.000 (90.392) Prec@5 99.000 (99.686) +2022-11-14 14:04:07,013 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0700 (0.0700) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 14:04:07,025 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0718 (0.0709) Prec@1 88.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 14:04:07,039 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0790 (0.0736) Prec@1 87.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:04:07,054 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0821 (0.0757) Prec@1 88.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:04:07,061 Test: [4/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0817 (0.0769) Prec@1 87.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 14:04:07,069 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0507 (0.0725) Prec@1 91.000 (88.000) Prec@5 98.000 (99.333) +2022-11-14 14:04:07,079 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0702) Prec@1 91.000 (88.429) Prec@5 99.000 (99.286) +2022-11-14 14:04:07,091 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0726) Prec@1 86.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 14:04:07,098 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0733) Prec@1 88.000 (88.111) Prec@5 100.000 (99.333) +2022-11-14 14:04:07,107 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0730) Prec@1 89.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 14:04:07,116 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0720) Prec@1 88.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 14:04:07,125 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0724) Prec@1 87.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 14:04:07,136 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0722) Prec@1 89.000 (88.154) Prec@5 100.000 (99.462) +2022-11-14 14:04:07,144 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0735) Prec@1 85.000 (87.929) Prec@5 99.000 (99.429) +2022-11-14 14:04:07,153 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0751) Prec@1 84.000 (87.667) Prec@5 99.000 (99.400) +2022-11-14 14:04:07,161 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0769) Prec@1 81.000 (87.250) Prec@5 97.000 (99.250) +2022-11-14 14:04:07,169 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0756) Prec@1 91.000 (87.471) Prec@5 99.000 (99.235) +2022-11-14 14:04:07,177 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0761) Prec@1 86.000 (87.389) Prec@5 100.000 (99.278) +2022-11-14 14:04:07,186 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0776) Prec@1 81.000 (87.053) Prec@5 96.000 (99.105) +2022-11-14 14:04:07,195 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0789) Prec@1 86.000 (87.000) Prec@5 97.000 (99.000) +2022-11-14 14:04:07,205 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0796) Prec@1 83.000 (86.810) Prec@5 100.000 (99.048) +2022-11-14 14:04:07,214 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0800) Prec@1 87.000 (86.818) Prec@5 100.000 (99.091) +2022-11-14 14:04:07,222 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0804) Prec@1 84.000 (86.696) Prec@5 99.000 (99.087) +2022-11-14 14:04:07,232 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0799) Prec@1 91.000 (86.875) Prec@5 100.000 (99.125) +2022-11-14 14:04:07,241 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0801) Prec@1 85.000 (86.800) Prec@5 100.000 (99.160) +2022-11-14 14:04:07,250 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0813) Prec@1 81.000 (86.577) Prec@5 99.000 (99.154) +2022-11-14 14:04:07,259 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0349 (0.0796) Prec@1 93.000 (86.815) Prec@5 100.000 (99.185) +2022-11-14 14:04:07,269 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0794) Prec@1 88.000 (86.857) Prec@5 100.000 (99.214) +2022-11-14 14:04:07,278 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0799) Prec@1 85.000 (86.793) Prec@5 99.000 (99.207) +2022-11-14 14:04:07,287 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0795) Prec@1 87.000 (86.800) Prec@5 100.000 (99.233) +2022-11-14 14:04:07,296 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0802) Prec@1 83.000 (86.677) Prec@5 99.000 (99.226) +2022-11-14 14:04:07,305 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0797) Prec@1 89.000 (86.750) Prec@5 99.000 (99.219) +2022-11-14 14:04:07,315 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0798) Prec@1 86.000 (86.727) Prec@5 100.000 (99.242) +2022-11-14 14:04:07,324 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.0810) Prec@1 79.000 (86.500) Prec@5 99.000 (99.235) +2022-11-14 14:04:07,333 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0805) Prec@1 86.000 (86.486) Prec@5 100.000 (99.257) +2022-11-14 14:04:07,342 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0801) Prec@1 91.000 (86.611) Prec@5 99.000 (99.250) +2022-11-14 14:04:07,352 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0809) Prec@1 83.000 (86.514) Prec@5 97.000 (99.189) +2022-11-14 14:04:07,360 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0815) Prec@1 82.000 (86.395) Prec@5 99.000 (99.184) +2022-11-14 14:04:07,369 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0809) Prec@1 90.000 (86.487) Prec@5 100.000 (99.205) +2022-11-14 14:04:07,378 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0807) Prec@1 87.000 (86.500) Prec@5 99.000 (99.200) +2022-11-14 14:04:07,388 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0811) Prec@1 85.000 (86.463) Prec@5 98.000 (99.171) +2022-11-14 14:04:07,396 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0808) Prec@1 90.000 (86.548) Prec@5 100.000 (99.190) +2022-11-14 14:04:07,405 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0808) Prec@1 85.000 (86.512) Prec@5 99.000 (99.186) +2022-11-14 14:04:07,414 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0806) Prec@1 88.000 (86.545) Prec@5 100.000 (99.205) +2022-11-14 14:04:07,423 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0805) Prec@1 86.000 (86.533) Prec@5 100.000 (99.222) +2022-11-14 14:04:07,432 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0813) Prec@1 80.000 (86.391) Prec@5 98.000 (99.196) +2022-11-14 14:04:07,441 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0814) Prec@1 87.000 (86.404) Prec@5 99.000 (99.191) +2022-11-14 14:04:07,449 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1242 (0.0823) Prec@1 80.000 (86.271) Prec@5 99.000 (99.188) +2022-11-14 14:04:07,458 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0818) Prec@1 92.000 (86.388) Prec@5 99.000 (99.184) +2022-11-14 14:04:07,466 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0824) Prec@1 82.000 (86.300) Prec@5 99.000 (99.180) +2022-11-14 14:04:07,474 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0821) Prec@1 86.000 (86.294) Prec@5 99.000 (99.176) +2022-11-14 14:04:07,484 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0825) Prec@1 82.000 (86.212) Prec@5 100.000 (99.192) +2022-11-14 14:04:07,493 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0822) Prec@1 88.000 (86.245) Prec@5 100.000 (99.208) +2022-11-14 14:04:07,502 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0820) Prec@1 86.000 (86.241) Prec@5 99.000 (99.204) +2022-11-14 14:04:07,511 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0822) Prec@1 86.000 (86.236) Prec@5 100.000 (99.218) +2022-11-14 14:04:07,520 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0819) Prec@1 89.000 (86.286) Prec@5 99.000 (99.214) +2022-11-14 14:04:07,529 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0816) Prec@1 90.000 (86.351) Prec@5 98.000 (99.193) +2022-11-14 14:04:07,539 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0819) Prec@1 84.000 (86.310) Prec@5 99.000 (99.190) +2022-11-14 14:04:07,547 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1176 (0.0825) Prec@1 83.000 (86.254) Prec@5 99.000 (99.186) +2022-11-14 14:04:07,556 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0823) Prec@1 91.000 (86.333) Prec@5 100.000 (99.200) +2022-11-14 14:04:07,565 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0824) Prec@1 85.000 (86.311) Prec@5 100.000 (99.213) +2022-11-14 14:04:07,574 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0822) Prec@1 89.000 (86.355) Prec@5 100.000 (99.226) +2022-11-14 14:04:07,583 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0820) Prec@1 87.000 (86.365) Prec@5 100.000 (99.238) +2022-11-14 14:04:07,591 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0817) Prec@1 91.000 (86.438) Prec@5 100.000 (99.250) +2022-11-14 14:04:07,601 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0819) Prec@1 83.000 (86.385) Prec@5 99.000 (99.246) +2022-11-14 14:04:07,610 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0818) Prec@1 87.000 (86.394) Prec@5 99.000 (99.242) +2022-11-14 14:04:07,619 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0813) Prec@1 92.000 (86.478) Prec@5 99.000 (99.239) +2022-11-14 14:04:07,628 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0812) Prec@1 87.000 (86.485) Prec@5 100.000 (99.250) +2022-11-14 14:04:07,637 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0809) Prec@1 89.000 (86.522) Prec@5 99.000 (99.246) +2022-11-14 14:04:07,645 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0809) Prec@1 84.000 (86.486) Prec@5 98.000 (99.229) +2022-11-14 14:04:07,654 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0812) Prec@1 83.000 (86.437) Prec@5 99.000 (99.225) +2022-11-14 14:04:07,664 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0810) Prec@1 89.000 (86.472) Prec@5 100.000 (99.236) +2022-11-14 14:04:07,672 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0807) Prec@1 90.000 (86.521) Prec@5 100.000 (99.247) +2022-11-14 14:04:07,680 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0405 (0.0802) Prec@1 93.000 (86.608) Prec@5 100.000 (99.257) +2022-11-14 14:04:07,690 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.0807) Prec@1 81.000 (86.533) Prec@5 100.000 (99.267) +2022-11-14 14:04:07,699 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0804) Prec@1 89.000 (86.566) Prec@5 99.000 (99.263) +2022-11-14 14:04:07,708 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0803) Prec@1 88.000 (86.584) Prec@5 97.000 (99.234) +2022-11-14 14:04:07,716 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0803) Prec@1 89.000 (86.615) Prec@5 96.000 (99.192) +2022-11-14 14:04:07,726 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0804) Prec@1 85.000 (86.595) Prec@5 100.000 (99.203) +2022-11-14 14:04:07,734 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0804) Prec@1 88.000 (86.612) Prec@5 100.000 (99.213) +2022-11-14 14:04:07,742 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0804) Prec@1 87.000 (86.617) Prec@5 98.000 (99.198) +2022-11-14 14:04:07,751 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0805) Prec@1 83.000 (86.573) Prec@5 99.000 (99.195) +2022-11-14 14:04:07,759 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0806) Prec@1 84.000 (86.542) Prec@5 100.000 (99.205) +2022-11-14 14:04:07,768 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0804) Prec@1 89.000 (86.571) Prec@5 99.000 (99.202) +2022-11-14 14:04:07,776 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0807) Prec@1 85.000 (86.553) Prec@5 98.000 (99.188) +2022-11-14 14:04:07,784 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0809) Prec@1 81.000 (86.488) Prec@5 99.000 (99.186) +2022-11-14 14:04:07,794 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0811) Prec@1 79.000 (86.402) Prec@5 98.000 (99.172) +2022-11-14 14:04:07,804 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0809) Prec@1 90.000 (86.443) Prec@5 100.000 (99.182) +2022-11-14 14:04:07,812 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0806) Prec@1 89.000 (86.472) Prec@5 100.000 (99.191) +2022-11-14 14:04:07,821 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0807) Prec@1 87.000 (86.478) Prec@5 98.000 (99.178) +2022-11-14 14:04:07,830 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0807) Prec@1 86.000 (86.473) Prec@5 99.000 (99.176) +2022-11-14 14:04:07,838 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0804) Prec@1 92.000 (86.533) Prec@5 100.000 (99.185) +2022-11-14 14:04:07,847 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0804) Prec@1 86.000 (86.527) Prec@5 100.000 (99.194) +2022-11-14 14:04:07,855 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0804) Prec@1 88.000 (86.543) Prec@5 99.000 (99.191) +2022-11-14 14:04:07,865 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0803) Prec@1 89.000 (86.568) Prec@5 100.000 (99.200) +2022-11-14 14:04:07,872 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0801) Prec@1 88.000 (86.583) Prec@5 99.000 (99.198) +2022-11-14 14:04:07,880 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0798) Prec@1 92.000 (86.639) Prec@5 100.000 (99.206) +2022-11-14 14:04:07,889 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0800) Prec@1 82.000 (86.592) Prec@5 99.000 (99.204) +2022-11-14 14:04:07,898 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.0803) Prec@1 83.000 (86.556) Prec@5 100.000 (99.212) +2022-11-14 14:04:07,907 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0801) Prec@1 88.000 (86.570) Prec@5 100.000 (99.220) +2022-11-14 14:04:07,963 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:04:08,274 Epoch: [141][0/500] Time 0.025 (0.025) Data 0.225 (0.225) Loss 0.0428 (0.0428) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:04:08,473 Epoch: [141][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0360 (0.0394) Prec@1 94.000 (93.500) Prec@5 100.000 (99.500) +2022-11-14 14:04:08,663 Epoch: [141][20/500] Time 0.017 (0.018) Data 0.001 (0.012) Loss 0.0462 (0.0417) Prec@1 92.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:04:08,964 Epoch: [141][30/500] Time 0.036 (0.020) Data 0.002 (0.009) Loss 0.0309 (0.0390) Prec@1 96.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:04:09,338 Epoch: [141][40/500] Time 0.035 (0.023) Data 0.002 (0.007) Loss 0.0685 (0.0449) Prec@1 87.000 (92.400) Prec@5 99.000 (99.600) +2022-11-14 14:04:09,711 Epoch: [141][50/500] Time 0.036 (0.025) Data 0.002 (0.006) Loss 0.0478 (0.0454) Prec@1 93.000 (92.500) Prec@5 100.000 (99.667) +2022-11-14 14:04:10,082 Epoch: [141][60/500] Time 0.034 (0.027) Data 0.002 (0.005) Loss 0.0552 (0.0468) Prec@1 92.000 (92.429) Prec@5 99.000 (99.571) +2022-11-14 14:04:10,451 Epoch: [141][70/500] Time 0.034 (0.027) Data 0.002 (0.005) Loss 0.0635 (0.0489) Prec@1 90.000 (92.125) Prec@5 100.000 (99.625) +2022-11-14 14:04:10,825 Epoch: [141][80/500] Time 0.035 (0.028) Data 0.002 (0.004) Loss 0.0628 (0.0504) Prec@1 89.000 (91.778) Prec@5 100.000 (99.667) +2022-11-14 14:04:11,203 Epoch: [141][90/500] Time 0.034 (0.029) Data 0.002 (0.004) Loss 0.0481 (0.0502) Prec@1 94.000 (92.000) Prec@5 100.000 (99.700) +2022-11-14 14:04:11,571 Epoch: [141][100/500] Time 0.036 (0.029) Data 0.002 (0.004) Loss 0.0364 (0.0489) Prec@1 94.000 (92.182) Prec@5 100.000 (99.727) +2022-11-14 14:04:11,945 Epoch: [141][110/500] Time 0.035 (0.029) Data 0.001 (0.004) Loss 0.0605 (0.0499) Prec@1 89.000 (91.917) Prec@5 99.000 (99.667) +2022-11-14 14:04:12,324 Epoch: [141][120/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0407 (0.0492) Prec@1 94.000 (92.077) Prec@5 100.000 (99.692) +2022-11-14 14:04:12,707 Epoch: [141][130/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0591 (0.0499) Prec@1 88.000 (91.786) Prec@5 100.000 (99.714) +2022-11-14 14:04:13,076 Epoch: [141][140/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0522 (0.0501) Prec@1 89.000 (91.600) Prec@5 100.000 (99.733) +2022-11-14 14:04:13,454 Epoch: [141][150/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0695 (0.0513) Prec@1 88.000 (91.375) Prec@5 99.000 (99.688) +2022-11-14 14:04:13,821 Epoch: [141][160/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0687 (0.0523) Prec@1 90.000 (91.294) Prec@5 99.000 (99.647) +2022-11-14 14:04:14,188 Epoch: [141][170/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0557 (0.0525) Prec@1 90.000 (91.222) Prec@5 100.000 (99.667) +2022-11-14 14:04:14,553 Epoch: [141][180/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0593 (0.0528) Prec@1 90.000 (91.158) Prec@5 99.000 (99.632) +2022-11-14 14:04:14,922 Epoch: [141][190/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0761 (0.0540) Prec@1 87.000 (90.950) Prec@5 99.000 (99.600) +2022-11-14 14:04:15,293 Epoch: [141][200/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0439 (0.0535) Prec@1 93.000 (91.048) Prec@5 99.000 (99.571) +2022-11-14 14:04:15,670 Epoch: [141][210/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0362 (0.0527) Prec@1 93.000 (91.136) Prec@5 100.000 (99.591) +2022-11-14 14:04:16,046 Epoch: [141][220/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0513 (0.0527) Prec@1 91.000 (91.130) Prec@5 100.000 (99.609) +2022-11-14 14:04:16,412 Epoch: [141][230/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0452 (0.0524) Prec@1 91.000 (91.125) Prec@5 100.000 (99.625) +2022-11-14 14:04:16,780 Epoch: [141][240/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0503 (0.0523) Prec@1 89.000 (91.040) Prec@5 100.000 (99.640) +2022-11-14 14:04:17,152 Epoch: [141][250/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0778 (0.0533) Prec@1 85.000 (90.808) Prec@5 98.000 (99.577) +2022-11-14 14:04:17,523 Epoch: [141][260/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0438 (0.0529) Prec@1 93.000 (90.889) Prec@5 100.000 (99.593) +2022-11-14 14:04:17,902 Epoch: [141][270/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0299 (0.0521) Prec@1 95.000 (91.036) Prec@5 99.000 (99.571) +2022-11-14 14:04:18,283 Epoch: [141][280/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0783 (0.0530) Prec@1 88.000 (90.931) Prec@5 100.000 (99.586) +2022-11-14 14:04:18,663 Epoch: [141][290/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0519 (0.0530) Prec@1 91.000 (90.933) Prec@5 100.000 (99.600) +2022-11-14 14:04:19,046 Epoch: [141][300/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0485 (0.0528) Prec@1 91.000 (90.935) Prec@5 100.000 (99.613) +2022-11-14 14:04:19,420 Epoch: [141][310/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0724 (0.0534) Prec@1 85.000 (90.750) Prec@5 99.000 (99.594) +2022-11-14 14:04:19,795 Epoch: [141][320/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0660 (0.0538) Prec@1 89.000 (90.697) Prec@5 97.000 (99.515) +2022-11-14 14:04:20,176 Epoch: [141][330/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0516 (0.0537) Prec@1 92.000 (90.735) Prec@5 100.000 (99.529) +2022-11-14 14:04:20,550 Epoch: [141][340/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0557 (0.0538) Prec@1 91.000 (90.743) Prec@5 99.000 (99.514) +2022-11-14 14:04:20,928 Epoch: [141][350/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0474 (0.0536) Prec@1 92.000 (90.778) Prec@5 99.000 (99.500) +2022-11-14 14:04:21,306 Epoch: [141][360/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0540 (0.0536) Prec@1 92.000 (90.811) Prec@5 100.000 (99.514) +2022-11-14 14:04:21,685 Epoch: [141][370/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0599 (0.0538) Prec@1 89.000 (90.763) Prec@5 100.000 (99.526) +2022-11-14 14:04:22,053 Epoch: [141][380/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0569 (0.0539) Prec@1 90.000 (90.744) Prec@5 100.000 (99.538) +2022-11-14 14:04:22,422 Epoch: [141][390/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0340 (0.0534) Prec@1 94.000 (90.825) Prec@5 100.000 (99.550) +2022-11-14 14:04:22,794 Epoch: [141][400/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0633 (0.0536) Prec@1 90.000 (90.805) Prec@5 99.000 (99.537) +2022-11-14 14:04:23,171 Epoch: [141][410/500] Time 0.036 (0.032) Data 0.001 (0.002) Loss 0.0855 (0.0544) Prec@1 85.000 (90.667) Prec@5 98.000 (99.500) +2022-11-14 14:04:23,550 Epoch: [141][420/500] Time 0.039 (0.032) Data 0.002 (0.002) Loss 0.0677 (0.0547) Prec@1 89.000 (90.628) Prec@5 100.000 (99.512) +2022-11-14 14:04:23,927 Epoch: [141][430/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0672 (0.0550) Prec@1 89.000 (90.591) Prec@5 100.000 (99.523) +2022-11-14 14:04:24,304 Epoch: [141][440/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0459 (0.0548) Prec@1 92.000 (90.622) Prec@5 99.000 (99.511) +2022-11-14 14:04:24,683 Epoch: [141][450/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0359 (0.0544) Prec@1 94.000 (90.696) Prec@5 100.000 (99.522) +2022-11-14 14:04:25,062 Epoch: [141][460/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0461 (0.0542) Prec@1 89.000 (90.660) Prec@5 100.000 (99.532) +2022-11-14 14:04:25,441 Epoch: [141][470/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0530 (0.0542) Prec@1 90.000 (90.646) Prec@5 100.000 (99.542) +2022-11-14 14:04:25,815 Epoch: [141][480/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0454 (0.0540) Prec@1 95.000 (90.735) Prec@5 100.000 (99.551) +2022-11-14 14:04:26,185 Epoch: [141][490/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0619 (0.0541) Prec@1 86.000 (90.640) Prec@5 100.000 (99.560) +2022-11-14 14:04:26,526 Epoch: [141][499/500] Time 0.037 (0.032) Data 0.001 (0.002) Loss 0.0369 (0.0538) Prec@1 93.000 (90.686) Prec@5 100.000 (99.569) +2022-11-14 14:04:26,810 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0657 (0.0657) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:04:26,821 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0975 (0.0816) Prec@1 83.000 (85.500) Prec@5 100.000 (99.500) +2022-11-14 14:04:26,830 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1060 (0.0897) Prec@1 79.000 (83.333) Prec@5 100.000 (99.667) +2022-11-14 14:04:26,840 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0882) Prec@1 86.000 (84.000) Prec@5 98.000 (99.250) +2022-11-14 14:04:26,848 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0894) Prec@1 84.000 (84.000) Prec@5 100.000 (99.400) +2022-11-14 14:04:26,859 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0833) Prec@1 90.000 (85.000) Prec@5 100.000 (99.500) +2022-11-14 14:04:26,869 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0816) Prec@1 88.000 (85.429) Prec@5 100.000 (99.571) +2022-11-14 14:04:26,878 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0829) Prec@1 83.000 (85.125) Prec@5 100.000 (99.625) +2022-11-14 14:04:26,887 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0837) Prec@1 86.000 (85.222) Prec@5 99.000 (99.556) +2022-11-14 14:04:26,897 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0822) Prec@1 90.000 (85.700) Prec@5 98.000 (99.400) +2022-11-14 14:04:26,908 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0816) Prec@1 86.000 (85.727) Prec@5 99.000 (99.364) +2022-11-14 14:04:26,917 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0807) Prec@1 88.000 (85.917) Prec@5 99.000 (99.333) +2022-11-14 14:04:26,925 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0782) Prec@1 92.000 (86.385) Prec@5 100.000 (99.385) +2022-11-14 14:04:26,936 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0783) Prec@1 87.000 (86.429) Prec@5 100.000 (99.429) +2022-11-14 14:04:26,947 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0791) Prec@1 85.000 (86.333) Prec@5 99.000 (99.400) +2022-11-14 14:04:26,956 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0801) Prec@1 85.000 (86.250) Prec@5 99.000 (99.375) +2022-11-14 14:04:26,964 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0785) Prec@1 92.000 (86.588) Prec@5 98.000 (99.294) +2022-11-14 14:04:26,975 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0798) Prec@1 83.000 (86.389) Prec@5 100.000 (99.333) +2022-11-14 14:04:26,985 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0797) Prec@1 85.000 (86.316) Prec@5 100.000 (99.368) +2022-11-14 14:04:26,994 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0803) Prec@1 85.000 (86.250) Prec@5 97.000 (99.250) +2022-11-14 14:04:27,003 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0812) Prec@1 83.000 (86.095) Prec@5 98.000 (99.190) +2022-11-14 14:04:27,014 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0813) Prec@1 85.000 (86.045) Prec@5 99.000 (99.182) +2022-11-14 14:04:27,024 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0814) Prec@1 86.000 (86.043) Prec@5 100.000 (99.217) +2022-11-14 14:04:27,032 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0812) Prec@1 88.000 (86.125) Prec@5 100.000 (99.250) +2022-11-14 14:04:27,040 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0820) Prec@1 79.000 (85.840) Prec@5 99.000 (99.240) +2022-11-14 14:04:27,050 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1211 (0.0835) Prec@1 79.000 (85.577) Prec@5 99.000 (99.231) +2022-11-14 14:04:27,061 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0825) Prec@1 90.000 (85.741) Prec@5 100.000 (99.259) +2022-11-14 14:04:27,070 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0820) Prec@1 88.000 (85.821) Prec@5 100.000 (99.286) +2022-11-14 14:04:27,079 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0818) Prec@1 86.000 (85.828) Prec@5 98.000 (99.241) +2022-11-14 14:04:27,090 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0818) Prec@1 85.000 (85.800) Prec@5 99.000 (99.233) +2022-11-14 14:04:27,101 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0820) Prec@1 82.000 (85.677) Prec@5 99.000 (99.226) +2022-11-14 14:04:27,110 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0812) Prec@1 90.000 (85.812) Prec@5 99.000 (99.219) +2022-11-14 14:04:27,118 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0813) Prec@1 85.000 (85.788) Prec@5 97.000 (99.152) +2022-11-14 14:04:27,129 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1271 (0.0827) Prec@1 75.000 (85.471) Prec@5 98.000 (99.118) +2022-11-14 14:04:27,139 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0826) Prec@1 87.000 (85.514) Prec@5 99.000 (99.114) +2022-11-14 14:04:27,148 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0829) Prec@1 82.000 (85.417) Prec@5 98.000 (99.083) +2022-11-14 14:04:27,157 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0831) Prec@1 89.000 (85.514) Prec@5 98.000 (99.054) +2022-11-14 14:04:27,167 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0831) Prec@1 85.000 (85.500) Prec@5 100.000 (99.079) +2022-11-14 14:04:27,177 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0828) Prec@1 87.000 (85.538) Prec@5 99.000 (99.077) +2022-11-14 14:04:27,186 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0832) Prec@1 82.000 (85.450) Prec@5 99.000 (99.075) +2022-11-14 14:04:27,194 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0833) Prec@1 87.000 (85.488) Prec@5 99.000 (99.073) +2022-11-14 14:04:27,205 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0830) Prec@1 85.000 (85.476) Prec@5 98.000 (99.048) +2022-11-14 14:04:27,214 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0311 (0.0818) Prec@1 96.000 (85.721) Prec@5 100.000 (99.070) +2022-11-14 14:04:27,223 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0815) Prec@1 88.000 (85.773) Prec@5 99.000 (99.068) +2022-11-14 14:04:27,232 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0816) Prec@1 87.000 (85.800) Prec@5 99.000 (99.067) +2022-11-14 14:04:27,244 Test: [45/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0818) Prec@1 84.000 (85.761) Prec@5 99.000 (99.065) +2022-11-14 14:04:27,254 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0818) Prec@1 86.000 (85.766) Prec@5 99.000 (99.064) +2022-11-14 14:04:27,263 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0822) Prec@1 83.000 (85.708) Prec@5 100.000 (99.083) +2022-11-14 14:04:27,271 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0815) Prec@1 93.000 (85.857) Prec@5 99.000 (99.082) +2022-11-14 14:04:27,282 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0819) Prec@1 83.000 (85.800) Prec@5 100.000 (99.100) +2022-11-14 14:04:27,292 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0818) Prec@1 87.000 (85.824) Prec@5 99.000 (99.098) +2022-11-14 14:04:27,302 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0818) Prec@1 85.000 (85.808) Prec@5 99.000 (99.096) +2022-11-14 14:04:27,310 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0818) Prec@1 87.000 (85.830) Prec@5 99.000 (99.094) +2022-11-14 14:04:27,321 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0814) Prec@1 89.000 (85.889) Prec@5 99.000 (99.093) +2022-11-14 14:04:27,331 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0819) Prec@1 85.000 (85.873) Prec@5 99.000 (99.091) +2022-11-14 14:04:27,340 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0820) Prec@1 85.000 (85.857) Prec@5 98.000 (99.071) +2022-11-14 14:04:27,349 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0819) Prec@1 85.000 (85.842) Prec@5 100.000 (99.088) +2022-11-14 14:04:27,359 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0818) Prec@1 89.000 (85.897) Prec@5 99.000 (99.086) +2022-11-14 14:04:27,369 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0821) Prec@1 84.000 (85.864) Prec@5 100.000 (99.102) +2022-11-14 14:04:27,379 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0823) Prec@1 86.000 (85.867) Prec@5 100.000 (99.117) +2022-11-14 14:04:27,387 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0822) Prec@1 86.000 (85.869) Prec@5 100.000 (99.131) +2022-11-14 14:04:27,396 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0822) Prec@1 87.000 (85.887) Prec@5 99.000 (99.129) +2022-11-14 14:04:27,405 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0818) Prec@1 91.000 (85.968) Prec@5 99.000 (99.127) +2022-11-14 14:04:27,415 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0404 (0.0812) Prec@1 95.000 (86.109) Prec@5 100.000 (99.141) +2022-11-14 14:04:27,423 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0813) Prec@1 83.000 (86.062) Prec@5 99.000 (99.138) +2022-11-14 14:04:27,433 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0811) Prec@1 92.000 (86.152) Prec@5 99.000 (99.136) +2022-11-14 14:04:27,442 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0809) Prec@1 88.000 (86.179) Prec@5 100.000 (99.149) +2022-11-14 14:04:27,450 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0810) Prec@1 87.000 (86.191) Prec@5 98.000 (99.132) +2022-11-14 14:04:27,459 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0811) Prec@1 86.000 (86.188) Prec@5 99.000 (99.130) +2022-11-14 14:04:27,469 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0810) Prec@1 88.000 (86.214) Prec@5 100.000 (99.143) +2022-11-14 14:04:27,477 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0809) Prec@1 89.000 (86.254) Prec@5 100.000 (99.155) +2022-11-14 14:04:27,486 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0807) Prec@1 91.000 (86.319) Prec@5 100.000 (99.167) +2022-11-14 14:04:27,496 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0806) Prec@1 85.000 (86.301) Prec@5 100.000 (99.178) +2022-11-14 14:04:27,505 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0803) Prec@1 91.000 (86.365) Prec@5 99.000 (99.176) +2022-11-14 14:04:27,515 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0806) Prec@1 83.000 (86.320) Prec@5 100.000 (99.187) +2022-11-14 14:04:27,526 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0803) Prec@1 91.000 (86.382) Prec@5 99.000 (99.184) +2022-11-14 14:04:27,536 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0802) Prec@1 88.000 (86.403) Prec@5 100.000 (99.195) +2022-11-14 14:04:27,546 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0804) Prec@1 82.000 (86.346) Prec@5 99.000 (99.192) +2022-11-14 14:04:27,556 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0802) Prec@1 89.000 (86.380) Prec@5 100.000 (99.203) +2022-11-14 14:04:27,566 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.0807) Prec@1 81.000 (86.312) Prec@5 100.000 (99.213) +2022-11-14 14:04:27,574 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0806) Prec@1 88.000 (86.333) Prec@5 98.000 (99.198) +2022-11-14 14:04:27,583 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0807) Prec@1 86.000 (86.329) Prec@5 100.000 (99.207) +2022-11-14 14:04:27,594 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0808) Prec@1 85.000 (86.313) Prec@5 100.000 (99.217) +2022-11-14 14:04:27,603 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0809) Prec@1 85.000 (86.298) Prec@5 98.000 (99.202) +2022-11-14 14:04:27,611 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0811) Prec@1 83.000 (86.259) Prec@5 100.000 (99.212) +2022-11-14 14:04:27,621 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0815) Prec@1 81.000 (86.198) Prec@5 100.000 (99.221) +2022-11-14 14:04:27,629 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0816) Prec@1 86.000 (86.195) Prec@5 99.000 (99.218) +2022-11-14 14:04:27,637 Test: [87/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0816) Prec@1 83.000 (86.159) Prec@5 99.000 (99.216) +2022-11-14 14:04:27,646 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0817) Prec@1 85.000 (86.146) Prec@5 98.000 (99.202) +2022-11-14 14:04:27,654 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0817) Prec@1 88.000 (86.167) Prec@5 100.000 (99.211) +2022-11-14 14:04:27,662 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0816) Prec@1 88.000 (86.187) Prec@5 100.000 (99.220) +2022-11-14 14:04:27,671 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0815) Prec@1 90.000 (86.228) Prec@5 100.000 (99.228) +2022-11-14 14:04:27,680 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0818) Prec@1 80.000 (86.161) Prec@5 100.000 (99.237) +2022-11-14 14:04:27,690 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0816) Prec@1 90.000 (86.202) Prec@5 100.000 (99.245) +2022-11-14 14:04:27,699 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0815) Prec@1 88.000 (86.221) Prec@5 100.000 (99.253) +2022-11-14 14:04:27,707 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0816) Prec@1 84.000 (86.198) Prec@5 98.000 (99.240) +2022-11-14 14:04:27,716 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0814) Prec@1 88.000 (86.216) Prec@5 98.000 (99.227) +2022-11-14 14:04:27,726 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0815) Prec@1 87.000 (86.224) Prec@5 100.000 (99.235) +2022-11-14 14:04:27,733 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0815) Prec@1 87.000 (86.232) Prec@5 100.000 (99.242) +2022-11-14 14:04:27,741 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0814) Prec@1 90.000 (86.270) Prec@5 100.000 (99.250) +2022-11-14 14:04:27,795 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:04:28,088 Epoch: [142][0/500] Time 0.027 (0.027) Data 0.211 (0.211) Loss 0.0459 (0.0459) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:04:28,290 Epoch: [142][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.0508 (0.0484) Prec@1 94.000 (94.000) Prec@5 98.000 (99.000) +2022-11-14 14:04:28,483 Epoch: [142][20/500] Time 0.020 (0.018) Data 0.001 (0.012) Loss 0.0540 (0.0502) Prec@1 90.000 (92.667) Prec@5 100.000 (99.333) +2022-11-14 14:04:28,698 Epoch: [142][30/500] Time 0.022 (0.018) Data 0.001 (0.008) Loss 0.0473 (0.0495) Prec@1 95.000 (93.250) Prec@5 100.000 (99.500) +2022-11-14 14:04:29,021 Epoch: [142][40/500] Time 0.035 (0.021) Data 0.002 (0.007) Loss 0.0629 (0.0522) Prec@1 90.000 (92.600) Prec@5 99.000 (99.400) +2022-11-14 14:04:29,391 Epoch: [142][50/500] Time 0.036 (0.023) Data 0.002 (0.006) Loss 0.0483 (0.0515) Prec@1 92.000 (92.500) Prec@5 99.000 (99.333) +2022-11-14 14:04:29,768 Epoch: [142][60/500] Time 0.036 (0.025) Data 0.002 (0.005) Loss 0.0782 (0.0553) Prec@1 89.000 (92.000) Prec@5 99.000 (99.286) +2022-11-14 14:04:30,136 Epoch: [142][70/500] Time 0.036 (0.026) Data 0.002 (0.005) Loss 0.0523 (0.0550) Prec@1 91.000 (91.875) Prec@5 100.000 (99.375) +2022-11-14 14:04:30,506 Epoch: [142][80/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0478 (0.0542) Prec@1 89.000 (91.556) Prec@5 100.000 (99.444) +2022-11-14 14:04:30,881 Epoch: [142][90/500] Time 0.036 (0.027) Data 0.001 (0.004) Loss 0.0533 (0.0541) Prec@1 92.000 (91.600) Prec@5 100.000 (99.500) +2022-11-14 14:04:31,250 Epoch: [142][100/500] Time 0.035 (0.028) Data 0.002 (0.004) Loss 0.0498 (0.0537) Prec@1 92.000 (91.636) Prec@5 98.000 (99.364) +2022-11-14 14:04:31,619 Epoch: [142][110/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.0749 (0.0555) Prec@1 87.000 (91.250) Prec@5 99.000 (99.333) +2022-11-14 14:04:31,989 Epoch: [142][120/500] Time 0.038 (0.029) Data 0.001 (0.003) Loss 0.0511 (0.0551) Prec@1 93.000 (91.385) Prec@5 100.000 (99.385) +2022-11-14 14:04:32,366 Epoch: [142][130/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0541 (0.0550) Prec@1 91.000 (91.357) Prec@5 99.000 (99.357) +2022-11-14 14:04:32,738 Epoch: [142][140/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0259 (0.0531) Prec@1 96.000 (91.667) Prec@5 100.000 (99.400) +2022-11-14 14:04:33,114 Epoch: [142][150/500] Time 0.034 (0.030) Data 0.001 (0.003) Loss 0.0485 (0.0528) Prec@1 92.000 (91.688) Prec@5 100.000 (99.438) +2022-11-14 14:04:33,483 Epoch: [142][160/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0679 (0.0537) Prec@1 87.000 (91.412) Prec@5 99.000 (99.412) +2022-11-14 14:04:33,850 Epoch: [142][170/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0519 (0.0536) Prec@1 91.000 (91.389) Prec@5 99.000 (99.389) +2022-11-14 14:04:34,221 Epoch: [142][180/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0552 (0.0537) Prec@1 92.000 (91.421) Prec@5 99.000 (99.368) +2022-11-14 14:04:34,594 Epoch: [142][190/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0529 (0.0536) Prec@1 91.000 (91.400) Prec@5 100.000 (99.400) +2022-11-14 14:04:34,966 Epoch: [142][200/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0396 (0.0530) Prec@1 92.000 (91.429) Prec@5 100.000 (99.429) +2022-11-14 14:04:35,341 Epoch: [142][210/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0708 (0.0538) Prec@1 90.000 (91.364) Prec@5 99.000 (99.409) +2022-11-14 14:04:35,709 Epoch: [142][220/500] Time 0.036 (0.031) Data 0.001 (0.003) Loss 0.0592 (0.0540) Prec@1 90.000 (91.304) Prec@5 99.000 (99.391) +2022-11-14 14:04:36,083 Epoch: [142][230/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0467 (0.0537) Prec@1 93.000 (91.375) Prec@5 100.000 (99.417) +2022-11-14 14:04:36,454 Epoch: [142][240/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0504 (0.0536) Prec@1 92.000 (91.400) Prec@5 100.000 (99.440) +2022-11-14 14:04:36,822 Epoch: [142][250/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0374 (0.0530) Prec@1 94.000 (91.500) Prec@5 100.000 (99.462) +2022-11-14 14:04:37,190 Epoch: [142][260/500] Time 0.035 (0.031) Data 0.001 (0.003) Loss 0.0521 (0.0529) Prec@1 92.000 (91.519) Prec@5 100.000 (99.481) +2022-11-14 14:04:37,561 Epoch: [142][270/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0611 (0.0532) Prec@1 91.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:04:37,928 Epoch: [142][280/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0626 (0.0535) Prec@1 91.000 (91.483) Prec@5 100.000 (99.517) +2022-11-14 14:04:38,299 Epoch: [142][290/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0434 (0.0532) Prec@1 94.000 (91.567) Prec@5 100.000 (99.533) +2022-11-14 14:04:38,664 Epoch: [142][300/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0639 (0.0536) Prec@1 88.000 (91.452) Prec@5 99.000 (99.516) +2022-11-14 14:04:39,035 Epoch: [142][310/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0438 (0.0532) Prec@1 94.000 (91.531) Prec@5 98.000 (99.469) +2022-11-14 14:04:39,407 Epoch: [142][320/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0468 (0.0530) Prec@1 95.000 (91.636) Prec@5 100.000 (99.485) +2022-11-14 14:04:39,785 Epoch: [142][330/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0328 (0.0525) Prec@1 94.000 (91.706) Prec@5 99.000 (99.471) +2022-11-14 14:04:40,161 Epoch: [142][340/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0415 (0.0521) Prec@1 94.000 (91.771) Prec@5 99.000 (99.457) +2022-11-14 14:04:40,536 Epoch: [142][350/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0459 (0.0520) Prec@1 91.000 (91.750) Prec@5 100.000 (99.472) +2022-11-14 14:04:40,920 Epoch: [142][360/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.0683 (0.0524) Prec@1 87.000 (91.622) Prec@5 99.000 (99.459) +2022-11-14 14:04:41,282 Epoch: [142][370/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0668 (0.0528) Prec@1 88.000 (91.526) Prec@5 100.000 (99.474) +2022-11-14 14:04:41,658 Epoch: [142][380/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0755 (0.0534) Prec@1 86.000 (91.385) Prec@5 100.000 (99.487) +2022-11-14 14:04:42,030 Epoch: [142][390/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0454 (0.0532) Prec@1 93.000 (91.425) Prec@5 100.000 (99.500) +2022-11-14 14:04:42,406 Epoch: [142][400/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0593 (0.0533) Prec@1 92.000 (91.439) Prec@5 99.000 (99.488) +2022-11-14 14:04:42,787 Epoch: [142][410/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0603 (0.0535) Prec@1 91.000 (91.429) Prec@5 99.000 (99.476) +2022-11-14 14:04:43,159 Epoch: [142][420/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0551 (0.0535) Prec@1 91.000 (91.419) Prec@5 100.000 (99.488) +2022-11-14 14:04:43,525 Epoch: [142][430/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0744 (0.0540) Prec@1 89.000 (91.364) Prec@5 99.000 (99.477) +2022-11-14 14:04:43,893 Epoch: [142][440/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0428 (0.0538) Prec@1 94.000 (91.422) Prec@5 100.000 (99.489) +2022-11-14 14:04:44,264 Epoch: [142][450/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0670 (0.0540) Prec@1 90.000 (91.391) Prec@5 100.000 (99.500) +2022-11-14 14:04:44,641 Epoch: [142][460/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0433 (0.0538) Prec@1 94.000 (91.447) Prec@5 100.000 (99.511) +2022-11-14 14:04:45,014 Epoch: [142][470/500] Time 0.036 (0.032) Data 0.002 (0.002) Loss 0.0539 (0.0538) Prec@1 92.000 (91.458) Prec@5 100.000 (99.521) +2022-11-14 14:04:45,390 Epoch: [142][480/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0394 (0.0535) Prec@1 91.000 (91.449) Prec@5 100.000 (99.531) +2022-11-14 14:04:45,757 Epoch: [142][490/500] Time 0.033 (0.032) Data 0.002 (0.002) Loss 0.0464 (0.0534) Prec@1 93.000 (91.480) Prec@5 99.000 (99.520) +2022-11-14 14:04:46,090 Epoch: [142][499/500] Time 0.035 (0.032) Data 0.002 (0.002) Loss 0.0539 (0.0534) Prec@1 90.000 (91.451) Prec@5 99.000 (99.510) +2022-11-14 14:04:46,372 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0655 (0.0655) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:04:46,382 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0760) Prec@1 85.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:04:46,389 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0792) Prec@1 86.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:04:46,400 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0770) Prec@1 88.000 (87.000) Prec@5 98.000 (99.500) +2022-11-14 14:04:46,408 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0768) Prec@1 87.000 (87.000) Prec@5 100.000 (99.600) +2022-11-14 14:04:46,416 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0728) Prec@1 90.000 (87.500) Prec@5 100.000 (99.667) +2022-11-14 14:04:46,424 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0717) Prec@1 89.000 (87.714) Prec@5 99.000 (99.571) +2022-11-14 14:04:46,434 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0757) Prec@1 82.000 (87.000) Prec@5 100.000 (99.625) +2022-11-14 14:04:46,442 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0763) Prec@1 87.000 (87.000) Prec@5 99.000 (99.556) +2022-11-14 14:04:46,450 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0751) Prec@1 89.000 (87.200) Prec@5 99.000 (99.500) +2022-11-14 14:04:46,460 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0731) Prec@1 91.000 (87.545) Prec@5 100.000 (99.545) +2022-11-14 14:04:46,470 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0732) Prec@1 90.000 (87.750) Prec@5 100.000 (99.583) +2022-11-14 14:04:46,479 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0729) Prec@1 87.000 (87.692) Prec@5 100.000 (99.615) +2022-11-14 14:04:46,490 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0729) Prec@1 89.000 (87.786) Prec@5 99.000 (99.571) +2022-11-14 14:04:46,500 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0738) Prec@1 85.000 (87.600) Prec@5 99.000 (99.533) +2022-11-14 14:04:46,509 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0744) Prec@1 86.000 (87.500) Prec@5 100.000 (99.562) +2022-11-14 14:04:46,519 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0729) Prec@1 92.000 (87.765) Prec@5 99.000 (99.529) +2022-11-14 14:04:46,528 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0746) Prec@1 86.000 (87.667) Prec@5 100.000 (99.556) +2022-11-14 14:04:46,537 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0754) Prec@1 84.000 (87.474) Prec@5 100.000 (99.579) +2022-11-14 14:04:46,546 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0767) Prec@1 81.000 (87.150) Prec@5 98.000 (99.500) +2022-11-14 14:04:46,555 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0775) Prec@1 83.000 (86.952) Prec@5 100.000 (99.524) +2022-11-14 14:04:46,565 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0774) Prec@1 86.000 (86.909) Prec@5 100.000 (99.545) +2022-11-14 14:04:46,574 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0781) Prec@1 84.000 (86.783) Prec@5 99.000 (99.522) +2022-11-14 14:04:46,583 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0780) Prec@1 86.000 (86.750) Prec@5 100.000 (99.542) +2022-11-14 14:04:46,593 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0783) Prec@1 84.000 (86.640) Prec@5 100.000 (99.560) +2022-11-14 14:04:46,602 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.0798) Prec@1 81.000 (86.423) Prec@5 99.000 (99.538) +2022-11-14 14:04:46,611 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0421 (0.0784) Prec@1 95.000 (86.741) Prec@5 100.000 (99.556) +2022-11-14 14:04:46,620 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0779) Prec@1 92.000 (86.929) Prec@5 99.000 (99.536) +2022-11-14 14:04:46,629 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0777) Prec@1 86.000 (86.897) Prec@5 99.000 (99.517) +2022-11-14 14:04:46,637 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0776) Prec@1 86.000 (86.867) Prec@5 100.000 (99.533) +2022-11-14 14:04:46,646 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0780) Prec@1 83.000 (86.742) Prec@5 98.000 (99.484) +2022-11-14 14:04:46,655 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0776) Prec@1 88.000 (86.781) Prec@5 100.000 (99.500) +2022-11-14 14:04:46,663 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0774) Prec@1 88.000 (86.818) Prec@5 99.000 (99.485) +2022-11-14 14:04:46,671 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0775) Prec@1 85.000 (86.765) Prec@5 98.000 (99.441) +2022-11-14 14:04:46,680 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0770) Prec@1 89.000 (86.829) Prec@5 98.000 (99.400) +2022-11-14 14:04:46,690 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0767) Prec@1 89.000 (86.889) Prec@5 100.000 (99.417) +2022-11-14 14:04:46,699 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0773) Prec@1 83.000 (86.784) Prec@5 98.000 (99.378) +2022-11-14 14:04:46,708 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1144 (0.0783) Prec@1 81.000 (86.632) Prec@5 99.000 (99.368) +2022-11-14 14:04:46,718 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0778) Prec@1 93.000 (86.795) Prec@5 99.000 (99.359) +2022-11-14 14:04:46,727 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0774) Prec@1 91.000 (86.900) Prec@5 100.000 (99.375) +2022-11-14 14:04:46,736 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0781) Prec@1 82.000 (86.780) Prec@5 99.000 (99.366) +2022-11-14 14:04:46,745 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0781) Prec@1 87.000 (86.786) Prec@5 97.000 (99.310) +2022-11-14 14:04:46,754 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0357 (0.0771) Prec@1 94.000 (86.953) Prec@5 100.000 (99.326) +2022-11-14 14:04:46,763 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0769) Prec@1 87.000 (86.955) Prec@5 99.000 (99.318) +2022-11-14 14:04:46,773 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0769) Prec@1 85.000 (86.911) Prec@5 99.000 (99.311) +2022-11-14 14:04:46,782 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.0774) Prec@1 84.000 (86.848) Prec@5 98.000 (99.283) +2022-11-14 14:04:46,791 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0776) Prec@1 85.000 (86.809) Prec@5 100.000 (99.298) +2022-11-14 14:04:46,800 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0777) Prec@1 85.000 (86.771) Prec@5 100.000 (99.312) +2022-11-14 14:04:46,810 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0775) Prec@1 88.000 (86.796) Prec@5 100.000 (99.327) +2022-11-14 14:04:46,819 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.0781) Prec@1 83.000 (86.720) Prec@5 99.000 (99.320) +2022-11-14 14:04:46,828 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0781) Prec@1 86.000 (86.706) Prec@5 99.000 (99.314) +2022-11-14 14:04:46,837 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0784) Prec@1 82.000 (86.615) Prec@5 99.000 (99.308) +2022-11-14 14:04:46,846 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0782) Prec@1 87.000 (86.623) Prec@5 100.000 (99.321) +2022-11-14 14:04:46,855 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0782) Prec@1 87.000 (86.630) Prec@5 100.000 (99.333) +2022-11-14 14:04:46,865 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0782) Prec@1 86.000 (86.618) Prec@5 100.000 (99.345) +2022-11-14 14:04:46,874 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0785) Prec@1 87.000 (86.625) Prec@5 98.000 (99.321) +2022-11-14 14:04:46,882 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0788) Prec@1 82.000 (86.544) Prec@5 99.000 (99.316) +2022-11-14 14:04:46,892 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0790) Prec@1 86.000 (86.534) Prec@5 99.000 (99.310) +2022-11-14 14:04:46,901 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0796) Prec@1 82.000 (86.458) Prec@5 99.000 (99.305) +2022-11-14 14:04:46,910 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1061 (0.0800) Prec@1 83.000 (86.400) Prec@5 100.000 (99.317) +2022-11-14 14:04:46,920 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0798) Prec@1 88.000 (86.426) Prec@5 100.000 (99.328) +2022-11-14 14:04:46,928 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0798) Prec@1 85.000 (86.403) Prec@5 99.000 (99.323) +2022-11-14 14:04:46,937 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0797) Prec@1 87.000 (86.413) Prec@5 100.000 (99.333) +2022-11-14 14:04:46,947 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0792) Prec@1 91.000 (86.484) Prec@5 99.000 (99.328) +2022-11-14 14:04:46,955 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0797) Prec@1 84.000 (86.446) Prec@5 97.000 (99.292) +2022-11-14 14:04:46,963 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0797) Prec@1 87.000 (86.455) Prec@5 98.000 (99.273) +2022-11-14 14:04:46,972 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0794) Prec@1 91.000 (86.522) Prec@5 100.000 (99.284) +2022-11-14 14:04:46,982 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0795) Prec@1 84.000 (86.485) Prec@5 98.000 (99.265) +2022-11-14 14:04:46,992 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0798) Prec@1 84.000 (86.449) Prec@5 99.000 (99.261) +2022-11-14 14:04:47,002 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1049 (0.0802) Prec@1 86.000 (86.443) Prec@5 99.000 (99.257) +2022-11-14 14:04:47,011 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0803) Prec@1 85.000 (86.423) Prec@5 100.000 (99.268) +2022-11-14 14:04:47,020 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0803) Prec@1 85.000 (86.403) Prec@5 100.000 (99.278) +2022-11-14 14:04:47,030 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0802) Prec@1 89.000 (86.438) Prec@5 100.000 (99.288) +2022-11-14 14:04:47,039 Test: 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0.0726 (0.0797) Prec@1 86.000 (86.550) Prec@5 99.000 (99.250) +2022-11-14 14:04:47,103 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0797) Prec@1 86.000 (86.543) Prec@5 99.000 (99.247) +2022-11-14 14:04:47,113 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0798) Prec@1 85.000 (86.524) Prec@5 100.000 (99.256) +2022-11-14 14:04:47,122 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0800) Prec@1 83.000 (86.482) Prec@5 99.000 (99.253) +2022-11-14 14:04:47,131 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0800) Prec@1 88.000 (86.500) Prec@5 100.000 (99.262) +2022-11-14 14:04:47,141 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0801) Prec@1 81.000 (86.435) Prec@5 99.000 (99.259) +2022-11-14 14:04:47,150 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0802) Prec@1 80.000 (86.360) Prec@5 100.000 (99.267) +2022-11-14 14:04:47,159 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0801) Prec@1 90.000 (86.402) Prec@5 99.000 (99.264) +2022-11-14 14:04:47,168 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0801) Prec@1 86.000 (86.398) Prec@5 99.000 (99.261) +2022-11-14 14:04:47,178 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0801) Prec@1 86.000 (86.393) Prec@5 99.000 (99.258) +2022-11-14 14:04:47,186 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0799) Prec@1 89.000 (86.422) Prec@5 99.000 (99.256) +2022-11-14 14:04:47,196 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0797) Prec@1 89.000 (86.451) Prec@5 99.000 (99.253) +2022-11-14 14:04:47,205 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0795) Prec@1 92.000 (86.511) Prec@5 99.000 (99.250) +2022-11-14 14:04:47,214 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0795) Prec@1 87.000 (86.516) Prec@5 100.000 (99.258) +2022-11-14 14:04:47,223 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0797) Prec@1 85.000 (86.500) Prec@5 99.000 (99.255) +2022-11-14 14:04:47,232 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0796) Prec@1 87.000 (86.505) Prec@5 99.000 (99.253) +2022-11-14 14:04:47,240 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0795) Prec@1 89.000 (86.531) Prec@5 98.000 (99.240) +2022-11-14 14:04:47,249 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0792) Prec@1 93.000 (86.598) Prec@5 98.000 (99.227) +2022-11-14 14:04:47,257 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0792) Prec@1 89.000 (86.622) Prec@5 99.000 (99.224) +2022-11-14 14:04:47,264 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0791) Prec@1 87.000 (86.626) Prec@5 99.000 (99.222) +2022-11-14 14:04:47,273 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0792) Prec@1 85.000 (86.610) Prec@5 99.000 (99.220) +2022-11-14 14:04:47,328 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:04:47,645 Epoch: [143][0/500] Time 0.024 (0.024) Data 0.234 (0.234) Loss 0.0665 (0.0665) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:04:47,844 Epoch: [143][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0610 (0.0638) Prec@1 90.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:04:48,044 Epoch: [143][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0427 (0.0567) Prec@1 93.000 (90.667) Prec@5 100.000 (99.667) +2022-11-14 14:04:48,321 Epoch: [143][30/500] Time 0.034 (0.020) Data 0.002 (0.009) Loss 0.0504 (0.0552) Prec@1 91.000 (90.750) Prec@5 99.000 (99.500) +2022-11-14 14:04:48,755 Epoch: [143][40/500] Time 0.041 (0.024) Data 0.002 (0.007) Loss 0.0335 (0.0508) Prec@1 95.000 (91.600) Prec@5 99.000 (99.400) +2022-11-14 14:04:49,187 Epoch: [143][50/500] Time 0.043 (0.027) Data 0.002 (0.006) Loss 0.0504 (0.0508) Prec@1 90.000 (91.333) Prec@5 100.000 (99.500) +2022-11-14 14:04:49,623 Epoch: [143][60/500] Time 0.043 (0.029) Data 0.001 (0.006) Loss 0.0512 (0.0508) Prec@1 92.000 (91.429) Prec@5 100.000 (99.571) +2022-11-14 14:04:50,059 Epoch: [143][70/500] Time 0.041 (0.030) Data 0.002 (0.005) Loss 0.0802 (0.0545) Prec@1 86.000 (90.750) Prec@5 99.000 (99.500) +2022-11-14 14:04:50,484 Epoch: [143][80/500] Time 0.039 (0.031) Data 0.002 (0.005) Loss 0.0506 (0.0541) Prec@1 92.000 (90.889) Prec@5 100.000 (99.556) +2022-11-14 14:04:50,917 Epoch: [143][90/500] Time 0.040 (0.032) Data 0.002 (0.004) Loss 0.0818 (0.0568) Prec@1 85.000 (90.300) Prec@5 99.000 (99.500) +2022-11-14 14:04:51,354 Epoch: [143][100/500] Time 0.040 (0.033) Data 0.003 (0.004) Loss 0.0416 (0.0554) Prec@1 93.000 (90.545) Prec@5 99.000 (99.455) +2022-11-14 14:04:51,786 Epoch: [143][110/500] Time 0.042 (0.033) Data 0.002 (0.004) Loss 0.0556 (0.0555) Prec@1 92.000 (90.667) Prec@5 99.000 (99.417) +2022-11-14 14:04:52,216 Epoch: [143][120/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.0504 (0.0551) Prec@1 92.000 (90.769) Prec@5 100.000 (99.462) +2022-11-14 14:04:52,640 Epoch: [143][130/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0595 (0.0554) Prec@1 90.000 (90.714) Prec@5 100.000 (99.500) +2022-11-14 14:04:53,062 Epoch: [143][140/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0661 (0.0561) Prec@1 90.000 (90.667) Prec@5 99.000 (99.467) +2022-11-14 14:04:53,487 Epoch: [143][150/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0471 (0.0555) Prec@1 93.000 (90.812) Prec@5 99.000 (99.438) +2022-11-14 14:04:53,922 Epoch: [143][160/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0397 (0.0546) Prec@1 93.000 (90.941) Prec@5 100.000 (99.471) +2022-11-14 14:04:54,347 Epoch: [143][170/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0766 (0.0558) Prec@1 87.000 (90.722) Prec@5 99.000 (99.444) +2022-11-14 14:04:54,781 Epoch: [143][180/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0629 (0.0562) Prec@1 89.000 (90.632) Prec@5 99.000 (99.421) +2022-11-14 14:04:55,204 Epoch: [143][190/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0210 (0.0544) Prec@1 98.000 (91.000) Prec@5 100.000 (99.450) +2022-11-14 14:04:55,630 Epoch: [143][200/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0692 (0.0551) Prec@1 87.000 (90.810) Prec@5 99.000 (99.429) +2022-11-14 14:04:56,058 Epoch: [143][210/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0337 (0.0542) Prec@1 93.000 (90.909) Prec@5 100.000 (99.455) +2022-11-14 14:04:56,480 Epoch: [143][220/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0524 (0.0541) Prec@1 92.000 (90.957) Prec@5 99.000 (99.435) +2022-11-14 14:04:56,908 Epoch: [143][230/500] Time 0.041 (0.036) Data 0.001 (0.003) Loss 0.0749 (0.0550) Prec@1 86.000 (90.750) Prec@5 98.000 (99.375) +2022-11-14 14:04:57,336 Epoch: [143][240/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0716 (0.0556) Prec@1 89.000 (90.680) Prec@5 100.000 (99.400) +2022-11-14 14:04:57,767 Epoch: [143][250/500] Time 0.041 (0.036) Data 0.001 (0.003) Loss 0.0505 (0.0554) Prec@1 91.000 (90.692) Prec@5 100.000 (99.423) +2022-11-14 14:04:58,195 Epoch: [143][260/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0616 (0.0557) Prec@1 88.000 (90.593) Prec@5 100.000 (99.444) +2022-11-14 14:04:58,619 Epoch: [143][270/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0377 (0.0550) Prec@1 95.000 (90.750) Prec@5 99.000 (99.429) +2022-11-14 14:04:59,045 Epoch: [143][280/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0612 (0.0552) Prec@1 89.000 (90.690) Prec@5 98.000 (99.379) +2022-11-14 14:04:59,478 Epoch: [143][290/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0325 (0.0545) Prec@1 93.000 (90.767) Prec@5 100.000 (99.400) +2022-11-14 14:04:59,896 Epoch: [143][300/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0410 (0.0540) Prec@1 94.000 (90.871) Prec@5 99.000 (99.387) +2022-11-14 14:05:00,322 Epoch: [143][310/500] Time 0.039 (0.036) Data 0.001 (0.003) Loss 0.0588 (0.0542) Prec@1 91.000 (90.875) Prec@5 100.000 (99.406) +2022-11-14 14:05:00,747 Epoch: [143][320/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0477 (0.0540) Prec@1 89.000 (90.818) Prec@5 100.000 (99.424) +2022-11-14 14:05:01,169 Epoch: [143][330/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0794 (0.0547) Prec@1 86.000 (90.676) Prec@5 100.000 (99.441) +2022-11-14 14:05:01,595 Epoch: [143][340/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0278 (0.0540) Prec@1 97.000 (90.857) Prec@5 99.000 (99.429) +2022-11-14 14:05:02,017 Epoch: [143][350/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0333 (0.0534) Prec@1 94.000 (90.944) Prec@5 100.000 (99.444) +2022-11-14 14:05:02,450 Epoch: [143][360/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0349 (0.0529) Prec@1 95.000 (91.054) Prec@5 100.000 (99.459) +2022-11-14 14:05:02,872 Epoch: [143][370/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0433 (0.0526) Prec@1 95.000 (91.158) Prec@5 100.000 (99.474) +2022-11-14 14:05:03,290 Epoch: [143][380/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0452 (0.0524) Prec@1 93.000 (91.205) Prec@5 99.000 (99.462) +2022-11-14 14:05:03,710 Epoch: [143][390/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0550 (0.0525) Prec@1 90.000 (91.175) Prec@5 100.000 (99.475) +2022-11-14 14:05:04,141 Epoch: [143][400/500] Time 0.039 (0.036) Data 0.001 (0.002) Loss 0.0688 (0.0529) Prec@1 89.000 (91.122) Prec@5 99.000 (99.463) +2022-11-14 14:05:04,566 Epoch: [143][410/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0628 (0.0531) Prec@1 89.000 (91.071) Prec@5 100.000 (99.476) +2022-11-14 14:05:04,993 Epoch: [143][420/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0463 (0.0530) Prec@1 93.000 (91.116) Prec@5 99.000 (99.465) +2022-11-14 14:05:05,416 Epoch: [143][430/500] Time 0.040 (0.037) Data 0.001 (0.002) Loss 0.0496 (0.0529) Prec@1 89.000 (91.068) Prec@5 99.000 (99.455) +2022-11-14 14:05:05,829 Epoch: [143][440/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0651 (0.0532) Prec@1 89.000 (91.022) Prec@5 100.000 (99.467) +2022-11-14 14:05:06,247 Epoch: [143][450/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0312 (0.0527) Prec@1 94.000 (91.087) Prec@5 100.000 (99.478) +2022-11-14 14:05:06,683 Epoch: [143][460/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0562 (0.0528) Prec@1 91.000 (91.085) Prec@5 98.000 (99.447) +2022-11-14 14:05:07,106 Epoch: [143][470/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0572 (0.0529) Prec@1 92.000 (91.104) Prec@5 100.000 (99.458) +2022-11-14 14:05:07,542 Epoch: [143][480/500] Time 0.041 (0.037) Data 0.001 (0.002) Loss 0.0413 (0.0526) Prec@1 93.000 (91.143) Prec@5 100.000 (99.469) +2022-11-14 14:05:07,963 Epoch: [143][490/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0521 (0.0526) Prec@1 92.000 (91.160) Prec@5 100.000 (99.480) +2022-11-14 14:05:08,344 Epoch: [143][499/500] Time 0.039 (0.037) Data 0.001 (0.002) Loss 0.0465 (0.0525) Prec@1 92.000 (91.176) Prec@5 100.000 (99.490) +2022-11-14 14:05:08,619 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0722 (0.0722) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:05:08,631 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0733 (0.0727) Prec@1 87.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 14:05:08,642 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0820 (0.0758) Prec@1 86.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:05:08,654 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0715 (0.0748) Prec@1 89.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:05:08,662 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1130 (0.0824) Prec@1 81.000 (86.200) Prec@5 100.000 (99.600) +2022-11-14 14:05:08,671 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0455 (0.0763) Prec@1 92.000 (87.167) Prec@5 99.000 (99.500) +2022-11-14 14:05:08,679 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0761) Prec@1 89.000 (87.429) Prec@5 100.000 (99.571) +2022-11-14 14:05:08,689 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0795) Prec@1 82.000 (86.750) Prec@5 99.000 (99.500) +2022-11-14 14:05:08,698 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0819) Prec@1 83.000 (86.333) Prec@5 99.000 (99.444) +2022-11-14 14:05:08,706 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0805) Prec@1 87.000 (86.400) Prec@5 99.000 (99.400) +2022-11-14 14:05:08,715 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0798) Prec@1 89.000 (86.636) Prec@5 99.000 (99.364) +2022-11-14 14:05:08,724 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0806) Prec@1 86.000 (86.583) Prec@5 100.000 (99.417) +2022-11-14 14:05:08,733 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0806) Prec@1 86.000 (86.538) Prec@5 100.000 (99.462) +2022-11-14 14:05:08,742 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0814) Prec@1 84.000 (86.357) Prec@5 99.000 (99.429) +2022-11-14 14:05:08,752 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0817) Prec@1 83.000 (86.133) Prec@5 100.000 (99.467) +2022-11-14 14:05:08,761 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0824) Prec@1 85.000 (86.062) Prec@5 100.000 (99.500) +2022-11-14 14:05:08,770 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0814) Prec@1 89.000 (86.235) Prec@5 99.000 (99.471) +2022-11-14 14:05:08,779 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0820) Prec@1 86.000 (86.222) Prec@5 98.000 (99.389) +2022-11-14 14:05:08,788 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0822) Prec@1 83.000 (86.053) Prec@5 99.000 (99.368) +2022-11-14 14:05:08,797 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0836) Prec@1 81.000 (85.800) Prec@5 99.000 (99.350) +2022-11-14 14:05:08,807 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0841) Prec@1 82.000 (85.619) Prec@5 100.000 (99.381) +2022-11-14 14:05:08,816 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0839) Prec@1 88.000 (85.727) Prec@5 100.000 (99.409) +2022-11-14 14:05:08,825 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0847) Prec@1 84.000 (85.652) Prec@5 100.000 (99.435) +2022-11-14 14:05:08,834 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0851) Prec@1 82.000 (85.500) Prec@5 100.000 (99.458) +2022-11-14 14:05:08,844 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0852) Prec@1 87.000 (85.560) Prec@5 99.000 (99.440) +2022-11-14 14:05:08,852 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0863) Prec@1 81.000 (85.385) Prec@5 100.000 (99.462) +2022-11-14 14:05:08,860 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0852) Prec@1 92.000 (85.630) Prec@5 100.000 (99.481) +2022-11-14 14:05:08,870 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0848) Prec@1 87.000 (85.679) Prec@5 100.000 (99.500) +2022-11-14 14:05:08,879 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0849) Prec@1 84.000 (85.621) Prec@5 100.000 (99.517) +2022-11-14 14:05:08,888 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0844) Prec@1 86.000 (85.633) Prec@5 99.000 (99.500) +2022-11-14 14:05:08,897 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0844) Prec@1 82.000 (85.516) Prec@5 99.000 (99.484) +2022-11-14 14:05:08,907 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0839) Prec@1 88.000 (85.594) Prec@5 99.000 (99.469) +2022-11-14 14:05:08,915 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0837) Prec@1 85.000 (85.576) Prec@5 99.000 (99.455) +2022-11-14 14:05:08,925 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0839) Prec@1 83.000 (85.500) Prec@5 98.000 (99.412) +2022-11-14 14:05:08,934 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0839) Prec@1 85.000 (85.486) Prec@5 99.000 (99.400) +2022-11-14 14:05:08,943 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0838) Prec@1 85.000 (85.472) Prec@5 100.000 (99.417) +2022-11-14 14:05:08,952 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0834) Prec@1 88.000 (85.541) Prec@5 98.000 (99.378) +2022-11-14 14:05:08,961 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0843) Prec@1 80.000 (85.395) Prec@5 100.000 (99.395) +2022-11-14 14:05:08,969 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0837) Prec@1 92.000 (85.564) Prec@5 98.000 (99.359) +2022-11-14 14:05:08,978 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0834) Prec@1 88.000 (85.625) Prec@5 99.000 (99.350) +2022-11-14 14:05:08,986 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1022 (0.0839) Prec@1 85.000 (85.610) Prec@5 97.000 (99.293) +2022-11-14 14:05:08,994 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0839) Prec@1 85.000 (85.595) Prec@5 98.000 (99.262) +2022-11-14 14:05:09,003 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0831) Prec@1 93.000 (85.767) Prec@5 100.000 (99.279) +2022-11-14 14:05:09,011 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0830) Prec@1 86.000 (85.773) Prec@5 98.000 (99.250) +2022-11-14 14:05:09,020 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0830) Prec@1 86.000 (85.778) Prec@5 99.000 (99.244) +2022-11-14 14:05:09,029 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1162 (0.0837) Prec@1 80.000 (85.652) Prec@5 99.000 (99.239) +2022-11-14 14:05:09,039 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0841) Prec@1 81.000 (85.553) Prec@5 99.000 (99.234) +2022-11-14 14:05:09,047 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0844) Prec@1 83.000 (85.500) Prec@5 99.000 (99.229) +2022-11-14 14:05:09,056 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0843) Prec@1 87.000 (85.531) Prec@5 100.000 (99.245) +2022-11-14 14:05:09,066 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0846) Prec@1 85.000 (85.520) Prec@5 98.000 (99.220) +2022-11-14 14:05:09,074 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0846) Prec@1 88.000 (85.569) Prec@5 99.000 (99.216) +2022-11-14 14:05:09,082 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0849) Prec@1 83.000 (85.519) Prec@5 99.000 (99.212) +2022-11-14 14:05:09,091 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0849) Prec@1 85.000 (85.509) Prec@5 100.000 (99.226) +2022-11-14 14:05:09,101 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0846) Prec@1 89.000 (85.574) Prec@5 100.000 (99.241) +2022-11-14 14:05:09,110 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0849) Prec@1 82.000 (85.509) Prec@5 100.000 (99.255) +2022-11-14 14:05:09,118 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0848) Prec@1 86.000 (85.518) Prec@5 99.000 (99.250) +2022-11-14 14:05:09,128 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0850) Prec@1 81.000 (85.439) Prec@5 100.000 (99.263) +2022-11-14 14:05:09,136 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0847) Prec@1 88.000 (85.483) Prec@5 98.000 (99.241) +2022-11-14 14:05:09,145 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1150 (0.0852) Prec@1 80.000 (85.390) Prec@5 100.000 (99.254) +2022-11-14 14:05:09,154 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0855) Prec@1 81.000 (85.317) Prec@5 96.000 (99.200) +2022-11-14 14:05:09,163 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0856) Prec@1 86.000 (85.328) Prec@5 100.000 (99.213) +2022-11-14 14:05:09,172 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0855) Prec@1 86.000 (85.339) Prec@5 99.000 (99.210) +2022-11-14 14:05:09,181 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0854) Prec@1 85.000 (85.333) Prec@5 99.000 (99.206) +2022-11-14 14:05:09,190 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0440 (0.0848) Prec@1 93.000 (85.453) Prec@5 99.000 (99.203) +2022-11-14 14:05:09,198 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0847) Prec@1 87.000 (85.477) Prec@5 99.000 (99.200) +2022-11-14 14:05:09,207 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0850) Prec@1 81.000 (85.409) Prec@5 100.000 (99.212) +2022-11-14 14:05:09,216 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0411 (0.0843) Prec@1 94.000 (85.537) Prec@5 99.000 (99.209) +2022-11-14 14:05:09,226 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0840) Prec@1 91.000 (85.618) Prec@5 98.000 (99.191) +2022-11-14 14:05:09,234 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0837) Prec@1 89.000 (85.667) Prec@5 99.000 (99.188) +2022-11-14 14:05:09,242 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0836) Prec@1 86.000 (85.671) Prec@5 100.000 (99.200) +2022-11-14 14:05:09,252 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1130 (0.0841) Prec@1 80.000 (85.592) Prec@5 99.000 (99.197) +2022-11-14 14:05:09,261 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0840) Prec@1 85.000 (85.583) Prec@5 99.000 (99.194) +2022-11-14 14:05:09,269 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0837) Prec@1 90.000 (85.644) Prec@5 100.000 (99.205) +2022-11-14 14:05:09,277 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0835) Prec@1 89.000 (85.689) Prec@5 100.000 (99.216) +2022-11-14 14:05:09,286 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0838) Prec@1 82.000 (85.640) Prec@5 98.000 (99.200) +2022-11-14 14:05:09,295 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0835) Prec@1 88.000 (85.671) Prec@5 100.000 (99.211) +2022-11-14 14:05:09,303 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0835) Prec@1 85.000 (85.662) Prec@5 99.000 (99.208) +2022-11-14 14:05:09,311 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0837) Prec@1 84.000 (85.641) Prec@5 99.000 (99.205) +2022-11-14 14:05:09,319 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0835) Prec@1 90.000 (85.696) Prec@5 100.000 (99.215) +2022-11-14 14:05:09,327 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0836) Prec@1 86.000 (85.700) Prec@5 99.000 (99.213) +2022-11-14 14:05:09,338 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0836) Prec@1 84.000 (85.679) Prec@5 100.000 (99.222) +2022-11-14 14:05:09,349 Test: [81/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0835) Prec@1 84.000 (85.659) Prec@5 99.000 (99.220) +2022-11-14 14:05:09,361 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0837) Prec@1 86.000 (85.663) Prec@5 98.000 (99.205) +2022-11-14 14:05:09,373 Test: [83/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0838) Prec@1 83.000 (85.631) Prec@5 98.000 (99.190) +2022-11-14 14:05:09,383 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.0842) Prec@1 81.000 (85.576) Prec@5 99.000 (99.188) +2022-11-14 14:05:09,392 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1153 (0.0845) Prec@1 83.000 (85.547) Prec@5 99.000 (99.186) +2022-11-14 14:05:09,401 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0844) Prec@1 88.000 (85.575) Prec@5 99.000 (99.184) +2022-11-14 14:05:09,411 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0845) Prec@1 83.000 (85.545) Prec@5 99.000 (99.182) +2022-11-14 14:05:09,420 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0847) Prec@1 81.000 (85.494) Prec@5 97.000 (99.157) +2022-11-14 14:05:09,429 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0850) Prec@1 82.000 (85.456) Prec@5 100.000 (99.167) +2022-11-14 14:05:09,438 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0848) Prec@1 88.000 (85.484) Prec@5 100.000 (99.176) +2022-11-14 14:05:09,447 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0845) Prec@1 89.000 (85.522) Prec@5 100.000 (99.185) +2022-11-14 14:05:09,455 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0848) Prec@1 80.000 (85.462) Prec@5 99.000 (99.183) +2022-11-14 14:05:09,463 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0848) Prec@1 83.000 (85.436) Prec@5 97.000 (99.160) +2022-11-14 14:05:09,472 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0847) Prec@1 86.000 (85.442) Prec@5 100.000 (99.168) +2022-11-14 14:05:09,481 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0848) Prec@1 87.000 (85.458) Prec@5 98.000 (99.156) +2022-11-14 14:05:09,490 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0844) Prec@1 92.000 (85.526) Prec@5 100.000 (99.165) +2022-11-14 14:05:09,497 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1173 (0.0847) Prec@1 82.000 (85.490) Prec@5 99.000 (99.163) +2022-11-14 14:05:09,506 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1075 (0.0849) Prec@1 83.000 (85.465) Prec@5 100.000 (99.172) +2022-11-14 14:05:09,515 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0849) Prec@1 86.000 (85.470) Prec@5 99.000 (99.170) +2022-11-14 14:05:09,569 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:05:09,868 Epoch: [144][0/500] Time 0.027 (0.027) Data 0.220 (0.220) Loss 0.0453 (0.0453) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:10,072 Epoch: [144][10/500] Time 0.016 (0.019) Data 0.002 (0.022) Loss 0.0573 (0.0513) Prec@1 90.000 (92.000) Prec@5 99.000 (99.500) +2022-11-14 14:05:10,273 Epoch: [144][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.0524 (0.0517) Prec@1 90.000 (91.333) Prec@5 99.000 (99.333) +2022-11-14 14:05:10,492 Epoch: [144][30/500] Time 0.022 (0.018) Data 0.002 (0.009) Loss 0.0498 (0.0512) Prec@1 92.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:05:10,750 Epoch: [144][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.0441 (0.0498) Prec@1 94.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:05:11,006 Epoch: [144][50/500] Time 0.024 (0.020) Data 0.002 (0.006) Loss 0.0501 (0.0498) Prec@1 92.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:05:11,261 Epoch: [144][60/500] Time 0.023 (0.021) Data 0.002 (0.005) Loss 0.0532 (0.0503) Prec@1 90.000 (91.714) Prec@5 100.000 (99.714) +2022-11-14 14:05:11,512 Epoch: [144][70/500] Time 0.023 (0.021) Data 0.002 (0.005) Loss 0.0433 (0.0494) Prec@1 94.000 (92.000) Prec@5 99.000 (99.625) +2022-11-14 14:05:11,766 Epoch: [144][80/500] Time 0.024 (0.021) Data 0.002 (0.004) Loss 0.0632 (0.0510) Prec@1 87.000 (91.444) Prec@5 100.000 (99.667) +2022-11-14 14:05:12,202 Epoch: [144][90/500] Time 0.045 (0.023) Data 0.002 (0.004) Loss 0.0668 (0.0526) Prec@1 88.000 (91.100) Prec@5 100.000 (99.700) +2022-11-14 14:05:12,659 Epoch: [144][100/500] Time 0.044 (0.025) Data 0.002 (0.004) Loss 0.0398 (0.0514) Prec@1 94.000 (91.364) Prec@5 99.000 (99.636) +2022-11-14 14:05:13,124 Epoch: [144][110/500] Time 0.043 (0.026) Data 0.001 (0.004) Loss 0.0352 (0.0500) Prec@1 94.000 (91.583) Prec@5 100.000 (99.667) +2022-11-14 14:05:13,582 Epoch: [144][120/500] Time 0.044 (0.027) Data 0.002 (0.004) Loss 0.0480 (0.0499) Prec@1 94.000 (91.769) Prec@5 99.000 (99.615) +2022-11-14 14:05:14,038 Epoch: [144][130/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0524 (0.0501) Prec@1 91.000 (91.714) Prec@5 99.000 (99.571) +2022-11-14 14:05:14,500 Epoch: [144][140/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0643 (0.0510) Prec@1 90.000 (91.600) Prec@5 100.000 (99.600) +2022-11-14 14:05:14,957 Epoch: [144][150/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0410 (0.0504) Prec@1 93.000 (91.688) Prec@5 99.000 (99.562) +2022-11-14 14:05:15,415 Epoch: [144][160/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0627 (0.0511) Prec@1 88.000 (91.471) Prec@5 99.000 (99.529) +2022-11-14 14:05:15,868 Epoch: [144][170/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0425 (0.0506) Prec@1 92.000 (91.500) Prec@5 100.000 (99.556) +2022-11-14 14:05:16,327 Epoch: [144][180/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0405 (0.0501) Prec@1 91.000 (91.474) Prec@5 100.000 (99.579) +2022-11-14 14:05:16,783 Epoch: [144][190/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0381 (0.0495) Prec@1 94.000 (91.600) Prec@5 100.000 (99.600) +2022-11-14 14:05:17,240 Epoch: [144][200/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0541 (0.0497) Prec@1 89.000 (91.476) Prec@5 98.000 (99.524) +2022-11-14 14:05:17,697 Epoch: [144][210/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0414 (0.0494) Prec@1 94.000 (91.591) Prec@5 100.000 (99.545) +2022-11-14 14:05:18,156 Epoch: [144][220/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0359 (0.0488) Prec@1 92.000 (91.609) Prec@5 100.000 (99.565) +2022-11-14 14:05:18,612 Epoch: [144][230/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0462 (0.0487) Prec@1 91.000 (91.583) Prec@5 100.000 (99.583) +2022-11-14 14:05:19,074 Epoch: [144][240/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0869 (0.0502) Prec@1 84.000 (91.280) Prec@5 99.000 (99.560) +2022-11-14 14:05:19,531 Epoch: [144][250/500] Time 0.046 (0.034) Data 0.001 (0.003) Loss 0.0645 (0.0507) Prec@1 88.000 (91.154) Prec@5 100.000 (99.577) +2022-11-14 14:05:19,982 Epoch: [144][260/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0701 (0.0515) Prec@1 88.000 (91.037) Prec@5 100.000 (99.593) +2022-11-14 14:05:20,436 Epoch: [144][270/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0438 (0.0512) Prec@1 91.000 (91.036) Prec@5 100.000 (99.607) +2022-11-14 14:05:20,889 Epoch: [144][280/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0656 (0.0517) Prec@1 90.000 (91.000) Prec@5 100.000 (99.621) +2022-11-14 14:05:21,350 Epoch: [144][290/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0516 (0.0517) Prec@1 92.000 (91.033) Prec@5 100.000 (99.633) +2022-11-14 14:05:21,806 Epoch: [144][300/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0356 (0.0512) Prec@1 93.000 (91.097) Prec@5 100.000 (99.645) +2022-11-14 14:05:22,262 Epoch: [144][310/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0821 (0.0521) Prec@1 87.000 (90.969) Prec@5 99.000 (99.625) +2022-11-14 14:05:22,715 Epoch: [144][320/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0293 (0.0514) Prec@1 93.000 (91.030) Prec@5 100.000 (99.636) +2022-11-14 14:05:23,066 Epoch: [144][330/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.1055 (0.0530) Prec@1 84.000 (90.824) Prec@5 99.000 (99.618) +2022-11-14 14:05:23,344 Epoch: [144][340/500] Time 0.025 (0.035) Data 0.001 (0.002) Loss 0.0785 (0.0538) Prec@1 88.000 (90.743) Prec@5 100.000 (99.629) +2022-11-14 14:05:23,629 Epoch: [144][350/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0550 (0.0538) Prec@1 91.000 (90.750) Prec@5 99.000 (99.611) +2022-11-14 14:05:23,908 Epoch: [144][360/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0676 (0.0542) Prec@1 89.000 (90.703) Prec@5 100.000 (99.622) +2022-11-14 14:05:24,189 Epoch: [144][370/500] Time 0.026 (0.034) Data 0.001 (0.002) Loss 0.0472 (0.0540) Prec@1 92.000 (90.737) Prec@5 100.000 (99.632) +2022-11-14 14:05:24,473 Epoch: [144][380/500] Time 0.029 (0.034) Data 0.001 (0.002) Loss 0.0474 (0.0538) Prec@1 91.000 (90.744) Prec@5 100.000 (99.641) +2022-11-14 14:05:24,762 Epoch: [144][390/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0441 (0.0536) Prec@1 94.000 (90.825) Prec@5 100.000 (99.650) +2022-11-14 14:05:25,046 Epoch: [144][400/500] Time 0.025 (0.034) Data 0.002 (0.002) Loss 0.0715 (0.0540) Prec@1 87.000 (90.732) Prec@5 100.000 (99.659) +2022-11-14 14:05:25,329 Epoch: [144][410/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0509 (0.0539) Prec@1 90.000 (90.714) Prec@5 100.000 (99.667) +2022-11-14 14:05:25,614 Epoch: [144][420/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0781 (0.0545) Prec@1 87.000 (90.628) Prec@5 100.000 (99.674) +2022-11-14 14:05:25,899 Epoch: [144][430/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0536 (0.0545) Prec@1 90.000 (90.614) Prec@5 100.000 (99.682) +2022-11-14 14:05:26,179 Epoch: [144][440/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0418 (0.0542) Prec@1 92.000 (90.644) Prec@5 99.000 (99.667) +2022-11-14 14:05:26,459 Epoch: [144][450/500] Time 0.023 (0.033) Data 0.002 (0.002) Loss 0.0369 (0.0538) Prec@1 95.000 (90.739) Prec@5 100.000 (99.674) +2022-11-14 14:05:26,746 Epoch: [144][460/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0486 (0.0537) Prec@1 90.000 (90.723) Prec@5 98.000 (99.638) +2022-11-14 14:05:27,026 Epoch: [144][470/500] Time 0.023 (0.032) Data 0.002 (0.002) Loss 0.0572 (0.0538) Prec@1 90.000 (90.708) Prec@5 99.000 (99.625) +2022-11-14 14:05:27,307 Epoch: [144][480/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0369 (0.0534) Prec@1 92.000 (90.735) Prec@5 99.000 (99.612) +2022-11-14 14:05:27,592 Epoch: [144][490/500] Time 0.023 (0.032) Data 0.002 (0.002) Loss 0.0501 (0.0534) Prec@1 90.000 (90.720) Prec@5 100.000 (99.620) +2022-11-14 14:05:27,846 Epoch: [144][499/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0748 (0.0538) Prec@1 86.000 (90.627) Prec@5 100.000 (99.627) +2022-11-14 14:05:28,126 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0716 (0.0716) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:05:28,135 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.0819) Prec@1 83.000 (85.500) Prec@5 100.000 (99.500) +2022-11-14 14:05:28,143 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0817) Prec@1 84.000 (85.000) Prec@5 100.000 (99.667) +2022-11-14 14:05:28,155 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0752) Prec@1 93.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 14:05:28,163 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0728) Prec@1 90.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 14:05:28,172 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0378 (0.0670) Prec@1 92.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:05:28,180 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0659) Prec@1 90.000 (88.571) Prec@5 100.000 (99.714) +2022-11-14 14:05:28,192 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0703) Prec@1 81.000 (87.625) Prec@5 99.000 (99.625) +2022-11-14 14:05:28,200 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0729) Prec@1 85.000 (87.333) Prec@5 99.000 (99.556) +2022-11-14 14:05:28,210 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0719) Prec@1 90.000 (87.600) Prec@5 99.000 (99.500) +2022-11-14 14:05:28,220 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0714) Prec@1 89.000 (87.727) Prec@5 100.000 (99.545) +2022-11-14 14:05:28,229 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0733) Prec@1 83.000 (87.333) Prec@5 100.000 (99.583) +2022-11-14 14:05:28,239 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0735) Prec@1 88.000 (87.385) Prec@5 100.000 (99.615) +2022-11-14 14:05:28,247 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0722) Prec@1 89.000 (87.500) Prec@5 99.000 (99.571) +2022-11-14 14:05:28,257 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0714) Prec@1 89.000 (87.600) Prec@5 99.000 (99.533) +2022-11-14 14:05:28,267 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0728) Prec@1 85.000 (87.438) Prec@5 99.000 (99.500) +2022-11-14 14:05:28,275 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0722) Prec@1 91.000 (87.647) Prec@5 98.000 (99.412) +2022-11-14 14:05:28,285 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0737) Prec@1 85.000 (87.500) Prec@5 99.000 (99.389) +2022-11-14 14:05:28,295 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0741) Prec@1 87.000 (87.474) Prec@5 100.000 (99.421) +2022-11-14 14:05:28,303 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0743) Prec@1 85.000 (87.350) Prec@5 97.000 (99.300) +2022-11-14 14:05:28,313 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0750) Prec@1 84.000 (87.190) Prec@5 100.000 (99.333) +2022-11-14 14:05:28,323 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0751) Prec@1 84.000 (87.045) Prec@5 98.000 (99.273) +2022-11-14 14:05:28,332 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0750) Prec@1 90.000 (87.174) Prec@5 99.000 (99.261) +2022-11-14 14:05:28,343 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0751) Prec@1 86.000 (87.125) Prec@5 98.000 (99.208) +2022-11-14 14:05:28,351 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0747) Prec@1 90.000 (87.240) Prec@5 100.000 (99.240) +2022-11-14 14:05:28,360 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0754) Prec@1 84.000 (87.115) Prec@5 97.000 (99.154) +2022-11-14 14:05:28,371 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0744) Prec@1 93.000 (87.333) Prec@5 99.000 (99.148) +2022-11-14 14:05:28,381 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0743) Prec@1 86.000 (87.286) Prec@5 100.000 (99.179) +2022-11-14 14:05:28,391 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0744) Prec@1 87.000 (87.276) Prec@5 100.000 (99.207) +2022-11-14 14:05:28,400 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0745) Prec@1 84.000 (87.167) Prec@5 100.000 (99.233) +2022-11-14 14:05:28,410 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0746) Prec@1 87.000 (87.161) Prec@5 100.000 (99.258) +2022-11-14 14:05:28,422 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0742) Prec@1 88.000 (87.188) Prec@5 99.000 (99.250) +2022-11-14 14:05:28,431 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0742) Prec@1 84.000 (87.091) Prec@5 99.000 (99.242) +2022-11-14 14:05:28,440 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0750) Prec@1 83.000 (86.971) Prec@5 100.000 (99.265) +2022-11-14 14:05:28,450 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0750) Prec@1 86.000 (86.943) Prec@5 98.000 (99.229) +2022-11-14 14:05:28,461 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0746) Prec@1 92.000 (87.083) Prec@5 100.000 (99.250) +2022-11-14 14:05:28,470 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0743) Prec@1 90.000 (87.162) Prec@5 99.000 (99.243) +2022-11-14 14:05:28,479 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0748) Prec@1 84.000 (87.079) Prec@5 100.000 (99.263) +2022-11-14 14:05:28,490 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0743) Prec@1 92.000 (87.205) Prec@5 98.000 (99.231) +2022-11-14 14:05:28,501 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0743) Prec@1 85.000 (87.150) Prec@5 99.000 (99.225) +2022-11-14 14:05:28,512 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0749) Prec@1 86.000 (87.122) Prec@5 98.000 (99.195) +2022-11-14 14:05:28,522 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0752) Prec@1 84.000 (87.048) Prec@5 100.000 (99.214) +2022-11-14 14:05:28,533 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0748) Prec@1 91.000 (87.140) Prec@5 100.000 (99.233) +2022-11-14 14:05:28,544 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0749) Prec@1 88.000 (87.159) Prec@5 98.000 (99.205) +2022-11-14 14:05:28,553 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0749) Prec@1 89.000 (87.200) Prec@5 100.000 (99.222) +2022-11-14 14:05:28,563 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0752) Prec@1 87.000 (87.196) Prec@5 100.000 (99.239) +2022-11-14 14:05:28,575 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0747) Prec@1 90.000 (87.255) Prec@5 100.000 (99.255) +2022-11-14 14:05:28,586 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0753) Prec@1 82.000 (87.146) Prec@5 99.000 (99.250) +2022-11-14 14:05:28,597 Test: [48/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0364 (0.0745) Prec@1 93.000 (87.265) Prec@5 99.000 (99.245) +2022-11-14 14:05:28,608 Test: [49/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1269 (0.0756) Prec@1 78.000 (87.080) Prec@5 98.000 (99.220) +2022-11-14 14:05:28,620 Test: [50/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0753) Prec@1 87.000 (87.078) Prec@5 100.000 (99.235) +2022-11-14 14:05:28,631 Test: [51/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0757) Prec@1 84.000 (87.019) Prec@5 99.000 (99.231) +2022-11-14 14:05:28,642 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0755) Prec@1 90.000 (87.075) Prec@5 100.000 (99.245) +2022-11-14 14:05:28,653 Test: [53/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0751) Prec@1 90.000 (87.130) Prec@5 99.000 (99.241) +2022-11-14 14:05:28,663 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0750) Prec@1 92.000 (87.218) Prec@5 100.000 (99.255) +2022-11-14 14:05:28,673 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0748) Prec@1 88.000 (87.232) Prec@5 100.000 (99.268) +2022-11-14 14:05:28,684 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0749) Prec@1 87.000 (87.228) Prec@5 100.000 (99.281) +2022-11-14 14:05:28,693 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0748) Prec@1 89.000 (87.259) Prec@5 99.000 (99.276) +2022-11-14 14:05:28,703 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1094 (0.0754) Prec@1 84.000 (87.203) Prec@5 100.000 (99.288) +2022-11-14 14:05:28,712 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0755) Prec@1 86.000 (87.183) Prec@5 98.000 (99.267) +2022-11-14 14:05:28,722 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0760) Prec@1 80.000 (87.066) Prec@5 100.000 (99.279) +2022-11-14 14:05:28,732 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0761) Prec@1 86.000 (87.048) Prec@5 100.000 (99.290) +2022-11-14 14:05:28,742 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0757) Prec@1 90.000 (87.095) Prec@5 100.000 (99.302) +2022-11-14 14:05:28,752 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0752) Prec@1 94.000 (87.203) Prec@5 100.000 (99.312) +2022-11-14 14:05:28,761 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0755) Prec@1 86.000 (87.185) Prec@5 100.000 (99.323) +2022-11-14 14:05:28,771 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0754) Prec@1 89.000 (87.212) Prec@5 98.000 (99.303) +2022-11-14 14:05:28,781 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0751) Prec@1 93.000 (87.299) Prec@5 100.000 (99.313) +2022-11-14 14:05:28,791 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0751) Prec@1 89.000 (87.324) Prec@5 100.000 (99.324) +2022-11-14 14:05:28,801 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0749) Prec@1 90.000 (87.362) Prec@5 99.000 (99.319) +2022-11-14 14:05:28,812 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0749) Prec@1 89.000 (87.386) Prec@5 98.000 (99.300) +2022-11-14 14:05:28,823 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0749) Prec@1 88.000 (87.394) Prec@5 99.000 (99.296) +2022-11-14 14:05:28,833 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0748) Prec@1 89.000 (87.417) Prec@5 100.000 (99.306) +2022-11-14 14:05:28,843 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0746) Prec@1 89.000 (87.438) Prec@5 98.000 (99.288) +2022-11-14 14:05:28,853 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0746) Prec@1 87.000 (87.432) Prec@5 99.000 (99.284) +2022-11-14 14:05:28,863 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0748) Prec@1 85.000 (87.400) Prec@5 99.000 (99.280) +2022-11-14 14:05:28,873 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0746) Prec@1 89.000 (87.421) Prec@5 99.000 (99.276) +2022-11-14 14:05:28,882 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0744) Prec@1 89.000 (87.442) Prec@5 100.000 (99.286) +2022-11-14 14:05:28,892 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0745) Prec@1 84.000 (87.397) Prec@5 99.000 (99.282) +2022-11-14 14:05:28,902 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0748) Prec@1 85.000 (87.367) Prec@5 100.000 (99.291) +2022-11-14 14:05:28,912 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0748) Prec@1 87.000 (87.362) Prec@5 100.000 (99.300) +2022-11-14 14:05:28,920 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0748) Prec@1 86.000 (87.346) Prec@5 100.000 (99.309) +2022-11-14 14:05:28,929 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0749) Prec@1 86.000 (87.329) Prec@5 99.000 (99.305) +2022-11-14 14:05:28,939 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0748) Prec@1 86.000 (87.313) Prec@5 100.000 (99.313) +2022-11-14 14:05:28,950 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0749) Prec@1 87.000 (87.310) Prec@5 99.000 (99.310) +2022-11-14 14:05:28,961 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0751) Prec@1 84.000 (87.271) Prec@5 100.000 (99.318) +2022-11-14 14:05:28,970 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0753) Prec@1 86.000 (87.256) Prec@5 99.000 (99.314) +2022-11-14 14:05:28,980 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0754) Prec@1 86.000 (87.241) Prec@5 100.000 (99.322) +2022-11-14 14:05:28,991 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0754) Prec@1 87.000 (87.239) Prec@5 99.000 (99.318) +2022-11-14 14:05:29,002 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0753) Prec@1 89.000 (87.258) Prec@5 99.000 (99.315) +2022-11-14 14:05:29,011 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0754) Prec@1 86.000 (87.244) Prec@5 99.000 (99.311) +2022-11-14 14:05:29,021 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0752) Prec@1 91.000 (87.286) Prec@5 100.000 (99.319) +2022-11-14 14:05:29,033 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0749) Prec@1 93.000 (87.348) Prec@5 100.000 (99.326) +2022-11-14 14:05:29,043 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0752) Prec@1 82.000 (87.290) Prec@5 100.000 (99.333) +2022-11-14 14:05:29,053 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0749) Prec@1 93.000 (87.351) Prec@5 99.000 (99.330) +2022-11-14 14:05:29,062 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0750) Prec@1 86.000 (87.337) Prec@5 100.000 (99.337) +2022-11-14 14:05:29,073 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0749) Prec@1 91.000 (87.375) Prec@5 99.000 (99.333) +2022-11-14 14:05:29,083 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0748) Prec@1 89.000 (87.392) Prec@5 99.000 (99.330) +2022-11-14 14:05:29,093 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0750) Prec@1 85.000 (87.367) Prec@5 97.000 (99.306) +2022-11-14 14:05:29,101 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1202 (0.0755) Prec@1 79.000 (87.283) Prec@5 99.000 (99.303) +2022-11-14 14:05:29,112 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0755) Prec@1 86.000 (87.270) Prec@5 99.000 (99.300) +2022-11-14 14:05:29,167 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:05:29,467 Epoch: [145][0/500] Time 0.022 (0.022) Data 0.223 (0.223) Loss 0.0404 (0.0404) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:29,667 Epoch: [145][10/500] Time 0.020 (0.018) Data 0.002 (0.022) Loss 0.0413 (0.0409) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:29,874 Epoch: [145][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.0409 (0.0409) Prec@1 93.000 (92.333) Prec@5 99.000 (99.667) +2022-11-14 14:05:30,092 Epoch: [145][30/500] Time 0.023 (0.018) Data 0.002 (0.009) Loss 0.0407 (0.0408) Prec@1 93.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:05:30,426 Epoch: [145][40/500] Time 0.039 (0.021) Data 0.002 (0.007) Loss 0.0463 (0.0419) Prec@1 92.000 (92.400) Prec@5 99.000 (99.600) +2022-11-14 14:05:30,839 Epoch: [145][50/500] Time 0.039 (0.024) Data 0.002 (0.006) Loss 0.0479 (0.0429) Prec@1 91.000 (92.167) Prec@5 99.000 (99.500) +2022-11-14 14:05:31,254 Epoch: [145][60/500] Time 0.038 (0.026) Data 0.002 (0.005) Loss 0.0607 (0.0455) Prec@1 91.000 (92.000) Prec@5 98.000 (99.286) +2022-11-14 14:05:31,668 Epoch: [145][70/500] Time 0.039 (0.028) Data 0.002 (0.005) Loss 0.0369 (0.0444) Prec@1 94.000 (92.250) Prec@5 100.000 (99.375) +2022-11-14 14:05:32,075 Epoch: [145][80/500] Time 0.037 (0.029) Data 0.002 (0.005) Loss 0.0554 (0.0456) Prec@1 89.000 (91.889) Prec@5 100.000 (99.444) +2022-11-14 14:05:32,493 Epoch: [145][90/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0472 (0.0458) Prec@1 92.000 (91.900) Prec@5 99.000 (99.400) +2022-11-14 14:05:32,901 Epoch: [145][100/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0555 (0.0467) Prec@1 92.000 (91.909) Prec@5 100.000 (99.455) +2022-11-14 14:05:33,309 Epoch: [145][110/500] Time 0.039 (0.031) Data 0.002 (0.004) Loss 0.0656 (0.0482) Prec@1 89.000 (91.667) Prec@5 100.000 (99.500) +2022-11-14 14:05:33,717 Epoch: [145][120/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.0487 (0.0483) Prec@1 91.000 (91.615) Prec@5 100.000 (99.538) +2022-11-14 14:05:34,133 Epoch: [145][130/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0561 (0.0488) Prec@1 90.000 (91.500) Prec@5 100.000 (99.571) +2022-11-14 14:05:34,540 Epoch: [145][140/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0233 (0.0471) Prec@1 96.000 (91.800) Prec@5 100.000 (99.600) +2022-11-14 14:05:34,951 Epoch: [145][150/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0574 (0.0478) Prec@1 90.000 (91.688) Prec@5 99.000 (99.562) +2022-11-14 14:05:35,369 Epoch: [145][160/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0298 (0.0467) Prec@1 95.000 (91.882) Prec@5 100.000 (99.588) +2022-11-14 14:05:35,785 Epoch: [145][170/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0592 (0.0474) Prec@1 89.000 (91.722) Prec@5 100.000 (99.611) +2022-11-14 14:05:36,194 Epoch: [145][180/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0544 (0.0478) Prec@1 91.000 (91.684) Prec@5 99.000 (99.579) +2022-11-14 14:05:36,615 Epoch: [145][190/500] Time 0.040 (0.033) Data 0.001 (0.003) Loss 0.0616 (0.0485) Prec@1 89.000 (91.550) Prec@5 99.000 (99.550) +2022-11-14 14:05:37,026 Epoch: [145][200/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0412 (0.0481) Prec@1 93.000 (91.619) Prec@5 99.000 (99.524) +2022-11-14 14:05:37,431 Epoch: [145][210/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0513 (0.0483) Prec@1 92.000 (91.636) Prec@5 100.000 (99.545) +2022-11-14 14:05:37,832 Epoch: [145][220/500] Time 0.035 (0.034) Data 0.003 (0.003) Loss 0.0706 (0.0492) Prec@1 88.000 (91.478) Prec@5 100.000 (99.565) +2022-11-14 14:05:38,235 Epoch: [145][230/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0574 (0.0496) Prec@1 91.000 (91.458) Prec@5 100.000 (99.583) +2022-11-14 14:05:38,646 Epoch: [145][240/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0545 (0.0498) Prec@1 90.000 (91.400) Prec@5 100.000 (99.600) +2022-11-14 14:05:39,051 Epoch: [145][250/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0363 (0.0493) Prec@1 95.000 (91.538) Prec@5 100.000 (99.615) +2022-11-14 14:05:39,451 Epoch: [145][260/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0667 (0.0499) Prec@1 86.000 (91.333) Prec@5 100.000 (99.630) +2022-11-14 14:05:39,859 Epoch: [145][270/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0688 (0.0506) Prec@1 86.000 (91.143) Prec@5 100.000 (99.643) +2022-11-14 14:05:40,266 Epoch: [145][280/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0424 (0.0503) Prec@1 93.000 (91.207) Prec@5 99.000 (99.621) +2022-11-14 14:05:40,670 Epoch: [145][290/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0736 (0.0511) Prec@1 86.000 (91.033) Prec@5 98.000 (99.567) +2022-11-14 14:05:41,079 Epoch: [145][300/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0618 (0.0514) Prec@1 88.000 (90.935) Prec@5 99.000 (99.548) +2022-11-14 14:05:41,488 Epoch: [145][310/500] Time 0.038 (0.034) Data 0.001 (0.003) Loss 0.0620 (0.0518) Prec@1 90.000 (90.906) Prec@5 98.000 (99.500) +2022-11-14 14:05:41,904 Epoch: [145][320/500] Time 0.037 (0.034) Data 0.001 (0.003) Loss 0.0577 (0.0519) Prec@1 87.000 (90.788) Prec@5 100.000 (99.515) +2022-11-14 14:05:42,309 Epoch: [145][330/500] Time 0.038 (0.034) Data 0.001 (0.002) Loss 0.0350 (0.0514) Prec@1 94.000 (90.882) Prec@5 99.000 (99.500) +2022-11-14 14:05:42,714 Epoch: [145][340/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0837 (0.0524) Prec@1 87.000 (90.771) Prec@5 100.000 (99.514) +2022-11-14 14:05:43,117 Epoch: [145][350/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0552 (0.0524) Prec@1 91.000 (90.778) Prec@5 99.000 (99.500) +2022-11-14 14:05:43,519 Epoch: [145][360/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0418 (0.0522) Prec@1 94.000 (90.865) Prec@5 98.000 (99.459) +2022-11-14 14:05:43,922 Epoch: [145][370/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0552 (0.0522) Prec@1 90.000 (90.842) Prec@5 100.000 (99.474) +2022-11-14 14:05:44,325 Epoch: [145][380/500] Time 0.038 (0.035) Data 0.001 (0.002) Loss 0.0618 (0.0525) Prec@1 89.000 (90.795) Prec@5 99.000 (99.462) +2022-11-14 14:05:44,728 Epoch: [145][390/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0439 (0.0523) Prec@1 94.000 (90.875) Prec@5 100.000 (99.475) +2022-11-14 14:05:45,129 Epoch: [145][400/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0559 (0.0523) Prec@1 91.000 (90.878) Prec@5 99.000 (99.463) +2022-11-14 14:05:45,538 Epoch: [145][410/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0483 (0.0523) Prec@1 93.000 (90.929) Prec@5 100.000 (99.476) +2022-11-14 14:05:45,939 Epoch: [145][420/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0877 (0.0531) Prec@1 85.000 (90.791) Prec@5 98.000 (99.442) +2022-11-14 14:05:46,346 Epoch: [145][430/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0624 (0.0533) Prec@1 88.000 (90.727) Prec@5 100.000 (99.455) +2022-11-14 14:05:46,754 Epoch: [145][440/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0539 (0.0533) Prec@1 92.000 (90.756) Prec@5 99.000 (99.444) +2022-11-14 14:05:47,163 Epoch: [145][450/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0416 (0.0530) Prec@1 93.000 (90.804) Prec@5 100.000 (99.457) +2022-11-14 14:05:47,567 Epoch: [145][460/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0376 (0.0527) Prec@1 95.000 (90.894) Prec@5 100.000 (99.468) +2022-11-14 14:05:47,968 Epoch: [145][470/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0440 (0.0525) Prec@1 93.000 (90.938) Prec@5 99.000 (99.458) +2022-11-14 14:05:48,372 Epoch: [145][480/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.1053 (0.0536) Prec@1 82.000 (90.755) Prec@5 99.000 (99.449) +2022-11-14 14:05:48,780 Epoch: [145][490/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0499 (0.0535) Prec@1 93.000 (90.800) Prec@5 99.000 (99.440) +2022-11-14 14:05:49,147 Epoch: [145][499/500] Time 0.038 (0.035) Data 0.002 (0.002) Loss 0.0637 (0.0537) Prec@1 90.000 (90.784) Prec@5 100.000 (99.451) +2022-11-14 14:05:49,427 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0841 (0.0841) Prec@1 85.000 (85.000) Prec@5 99.000 (99.000) +2022-11-14 14:05:49,438 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0767 (0.0804) Prec@1 88.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 14:05:49,447 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.0881) Prec@1 81.000 (84.667) Prec@5 100.000 (99.667) +2022-11-14 14:05:49,459 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0757 (0.0850) Prec@1 89.000 (85.750) Prec@5 99.000 (99.500) +2022-11-14 14:05:49,470 Test: [4/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0849) Prec@1 87.000 (86.000) Prec@5 100.000 (99.600) +2022-11-14 14:05:49,481 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0801) Prec@1 93.000 (87.167) Prec@5 99.000 (99.500) +2022-11-14 14:05:49,489 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0785) Prec@1 88.000 (87.286) Prec@5 100.000 (99.571) +2022-11-14 14:05:49,499 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0817) Prec@1 81.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 14:05:49,510 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.0829) Prec@1 83.000 (86.111) Prec@5 99.000 (99.444) +2022-11-14 14:05:49,522 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0519 (0.0798) Prec@1 90.000 (86.500) Prec@5 99.000 (99.400) +2022-11-14 14:05:49,531 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0789) Prec@1 86.000 (86.455) Prec@5 100.000 (99.455) +2022-11-14 14:05:49,539 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0811) Prec@1 85.000 (86.333) Prec@5 98.000 (99.333) +2022-11-14 14:05:49,551 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0790) Prec@1 93.000 (86.846) Prec@5 100.000 (99.385) +2022-11-14 14:05:49,563 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0787) Prec@1 88.000 (86.929) Prec@5 99.000 (99.357) +2022-11-14 14:05:49,573 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0794) Prec@1 87.000 (86.933) Prec@5 100.000 (99.400) +2022-11-14 14:05:49,581 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0792) Prec@1 86.000 (86.875) Prec@5 100.000 (99.438) +2022-11-14 14:05:49,594 Test: [16/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0779) Prec@1 92.000 (87.176) Prec@5 98.000 (99.353) +2022-11-14 14:05:49,605 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0801) Prec@1 83.000 (86.944) Prec@5 100.000 (99.389) +2022-11-14 14:05:49,614 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.0818) Prec@1 81.000 (86.632) Prec@5 98.000 (99.316) +2022-11-14 14:05:49,622 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0824) Prec@1 84.000 (86.500) Prec@5 97.000 (99.200) +2022-11-14 14:05:49,634 Test: [20/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0830) Prec@1 84.000 (86.381) Prec@5 100.000 (99.238) +2022-11-14 14:05:49,645 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0828) Prec@1 86.000 (86.364) Prec@5 99.000 (99.227) +2022-11-14 14:05:49,654 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0833) Prec@1 84.000 (86.261) Prec@5 99.000 (99.217) +2022-11-14 14:05:49,662 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0838) Prec@1 84.000 (86.167) Prec@5 100.000 (99.250) +2022-11-14 14:05:49,673 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0842) Prec@1 86.000 (86.160) Prec@5 100.000 (99.280) +2022-11-14 14:05:49,684 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.0855) Prec@1 75.000 (85.731) Prec@5 99.000 (99.269) +2022-11-14 14:05:49,693 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0848) Prec@1 88.000 (85.815) Prec@5 100.000 (99.296) +2022-11-14 14:05:49,702 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0848) Prec@1 84.000 (85.750) Prec@5 99.000 (99.286) +2022-11-14 14:05:49,714 Test: [28/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0851) Prec@1 87.000 (85.793) Prec@5 99.000 (99.276) +2022-11-14 14:05:49,725 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0851) Prec@1 84.000 (85.733) Prec@5 100.000 (99.300) +2022-11-14 14:05:49,733 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0850) Prec@1 88.000 (85.806) Prec@5 100.000 (99.323) +2022-11-14 14:05:49,742 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0852) Prec@1 84.000 (85.750) Prec@5 99.000 (99.312) +2022-11-14 14:05:49,753 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0848) Prec@1 89.000 (85.848) Prec@5 100.000 (99.333) +2022-11-14 14:05:49,764 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0850) Prec@1 87.000 (85.882) Prec@5 100.000 (99.353) +2022-11-14 14:05:49,774 Test: [34/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0849) Prec@1 86.000 (85.886) Prec@5 99.000 (99.343) +2022-11-14 14:05:49,784 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0848) Prec@1 88.000 (85.944) Prec@5 100.000 (99.361) +2022-11-14 14:05:49,796 Test: [36/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0848) Prec@1 84.000 (85.892) Prec@5 99.000 (99.351) +2022-11-14 14:05:49,807 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0848) Prec@1 83.000 (85.816) Prec@5 99.000 (99.342) +2022-11-14 14:05:49,815 Test: [38/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0842) Prec@1 91.000 (85.949) Prec@5 99.000 (99.333) +2022-11-14 14:05:49,824 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0846) Prec@1 83.000 (85.875) Prec@5 97.000 (99.275) +2022-11-14 14:05:49,837 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0847) Prec@1 85.000 (85.854) Prec@5 99.000 (99.268) +2022-11-14 14:05:49,848 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0841) Prec@1 91.000 (85.976) Prec@5 99.000 (99.262) +2022-11-14 14:05:49,857 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0835) Prec@1 91.000 (86.093) Prec@5 100.000 (99.279) +2022-11-14 14:05:49,866 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0835) Prec@1 88.000 (86.136) Prec@5 96.000 (99.205) +2022-11-14 14:05:49,878 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0832) Prec@1 88.000 (86.178) Prec@5 100.000 (99.222) +2022-11-14 14:05:49,889 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1201 (0.0840) Prec@1 80.000 (86.043) Prec@5 100.000 (99.239) +2022-11-14 14:05:49,899 Test: [46/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0838) Prec@1 88.000 (86.085) Prec@5 99.000 (99.234) +2022-11-14 14:05:49,907 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1059 (0.0843) Prec@1 83.000 (86.021) Prec@5 100.000 (99.250) +2022-11-14 14:05:49,919 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0839) Prec@1 88.000 (86.061) Prec@5 100.000 (99.265) +2022-11-14 14:05:49,930 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1164 (0.0846) Prec@1 82.000 (85.980) Prec@5 99.000 (99.260) +2022-11-14 14:05:49,940 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0843) Prec@1 89.000 (86.039) Prec@5 100.000 (99.275) +2022-11-14 14:05:49,948 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0847) Prec@1 83.000 (85.981) Prec@5 100.000 (99.288) +2022-11-14 14:05:49,960 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0848) Prec@1 84.000 (85.943) Prec@5 99.000 (99.283) +2022-11-14 14:05:49,972 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0844) Prec@1 89.000 (86.000) Prec@5 100.000 (99.296) +2022-11-14 14:05:49,981 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0843) Prec@1 84.000 (85.964) Prec@5 99.000 (99.291) +2022-11-14 14:05:49,990 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0848) Prec@1 81.000 (85.875) Prec@5 99.000 (99.286) +2022-11-14 14:05:50,001 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0850) Prec@1 85.000 (85.860) Prec@5 100.000 (99.298) +2022-11-14 14:05:50,012 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0846) Prec@1 90.000 (85.931) Prec@5 100.000 (99.310) +2022-11-14 14:05:50,021 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0849) Prec@1 83.000 (85.881) Prec@5 100.000 (99.322) +2022-11-14 14:05:50,031 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0849) Prec@1 86.000 (85.883) Prec@5 100.000 (99.333) +2022-11-14 14:05:50,043 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.0853) Prec@1 80.000 (85.787) Prec@5 100.000 (99.344) +2022-11-14 14:05:50,053 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0853) Prec@1 85.000 (85.774) Prec@5 97.000 (99.306) +2022-11-14 14:05:50,062 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0849) Prec@1 88.000 (85.810) Prec@5 100.000 (99.317) +2022-11-14 14:05:50,071 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0846) Prec@1 91.000 (85.891) Prec@5 100.000 (99.328) +2022-11-14 14:05:50,083 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0850) Prec@1 83.000 (85.846) Prec@5 100.000 (99.338) +2022-11-14 14:05:50,092 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0850) Prec@1 84.000 (85.818) Prec@5 98.000 (99.318) +2022-11-14 14:05:50,101 Test: [66/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0847) Prec@1 90.000 (85.881) Prec@5 100.000 (99.328) +2022-11-14 14:05:50,110 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0844) Prec@1 88.000 (85.912) Prec@5 98.000 (99.309) +2022-11-14 14:05:50,119 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0848) Prec@1 81.000 (85.841) Prec@5 99.000 (99.304) +2022-11-14 14:05:50,128 Test: [69/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0848) Prec@1 86.000 (85.843) Prec@5 99.000 (99.300) +2022-11-14 14:05:50,137 Test: [70/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0849) Prec@1 84.000 (85.817) Prec@5 99.000 (99.296) +2022-11-14 14:05:50,146 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0848) Prec@1 89.000 (85.861) Prec@5 100.000 (99.306) +2022-11-14 14:05:50,156 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0848) Prec@1 89.000 (85.904) Prec@5 98.000 (99.288) +2022-11-14 14:05:50,164 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0845) Prec@1 89.000 (85.946) Prec@5 100.000 (99.297) +2022-11-14 14:05:50,173 Test: [74/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0848) Prec@1 83.000 (85.907) Prec@5 100.000 (99.307) +2022-11-14 14:05:50,183 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0845) Prec@1 90.000 (85.961) Prec@5 98.000 (99.289) +2022-11-14 14:05:50,192 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0843) Prec@1 88.000 (85.987) Prec@5 100.000 (99.299) +2022-11-14 14:05:50,201 Test: [77/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0843) Prec@1 87.000 (86.000) Prec@5 98.000 (99.282) +2022-11-14 14:05:50,211 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0843) Prec@1 87.000 (86.013) Prec@5 100.000 (99.291) +2022-11-14 14:05:50,221 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0841) Prec@1 89.000 (86.050) Prec@5 99.000 (99.287) +2022-11-14 14:05:50,231 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0838) Prec@1 89.000 (86.086) Prec@5 100.000 (99.296) +2022-11-14 14:05:50,240 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0838) Prec@1 85.000 (86.073) Prec@5 99.000 (99.293) +2022-11-14 14:05:50,249 Test: [82/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0838) Prec@1 87.000 (86.084) Prec@5 98.000 (99.277) +2022-11-14 14:05:50,258 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0838) Prec@1 86.000 (86.083) Prec@5 99.000 (99.274) +2022-11-14 14:05:50,267 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0838) Prec@1 86.000 (86.082) Prec@5 100.000 (99.282) +2022-11-14 14:05:50,276 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0842) Prec@1 80.000 (86.012) Prec@5 99.000 (99.279) +2022-11-14 14:05:50,284 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0840) Prec@1 86.000 (86.011) Prec@5 98.000 (99.264) +2022-11-14 14:05:50,292 Test: [87/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0841) Prec@1 87.000 (86.023) Prec@5 99.000 (99.261) +2022-11-14 14:05:50,300 Test: [88/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0839) Prec@1 86.000 (86.022) Prec@5 99.000 (99.258) +2022-11-14 14:05:50,307 Test: [89/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0841) Prec@1 86.000 (86.022) Prec@5 99.000 (99.256) +2022-11-14 14:05:50,317 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0839) Prec@1 91.000 (86.077) Prec@5 99.000 (99.253) +2022-11-14 14:05:50,325 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0837) Prec@1 89.000 (86.109) Prec@5 100.000 (99.261) +2022-11-14 14:05:50,335 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0839) Prec@1 84.000 (86.086) Prec@5 100.000 (99.269) +2022-11-14 14:05:50,344 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0840) Prec@1 85.000 (86.074) Prec@5 97.000 (99.245) +2022-11-14 14:05:50,353 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0839) Prec@1 87.000 (86.084) Prec@5 99.000 (99.242) +2022-11-14 14:05:50,362 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0836) Prec@1 91.000 (86.135) Prec@5 100.000 (99.250) +2022-11-14 14:05:50,371 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0832) Prec@1 91.000 (86.186) Prec@5 99.000 (99.247) +2022-11-14 14:05:50,380 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1206 (0.0835) Prec@1 78.000 (86.102) Prec@5 99.000 (99.245) +2022-11-14 14:05:50,390 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0837) Prec@1 84.000 (86.081) Prec@5 99.000 (99.242) +2022-11-14 14:05:50,399 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0837) Prec@1 88.000 (86.100) Prec@5 99.000 (99.240) +2022-11-14 14:05:50,454 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:05:50,776 Epoch: [146][0/500] Time 0.027 (0.027) Data 0.237 (0.237) Loss 0.0511 (0.0511) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:50,972 Epoch: [146][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0611 (0.0561) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:51,164 Epoch: [146][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0595 (0.0572) Prec@1 88.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:05:51,369 Epoch: [146][30/500] Time 0.020 (0.018) Data 0.002 (0.009) Loss 0.0641 (0.0589) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:05:51,625 Epoch: [146][40/500] Time 0.022 (0.019) Data 0.001 (0.007) Loss 0.0467 (0.0565) Prec@1 91.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:05:51,886 Epoch: [146][50/500] Time 0.023 (0.020) Data 0.002 (0.006) Loss 0.0470 (0.0549) Prec@1 91.000 (89.333) Prec@5 99.000 (99.833) +2022-11-14 14:05:52,145 Epoch: [146][60/500] Time 0.024 (0.020) Data 0.002 (0.005) Loss 0.0634 (0.0561) Prec@1 91.000 (89.571) Prec@5 99.000 (99.714) +2022-11-14 14:05:52,406 Epoch: [146][70/500] Time 0.024 (0.021) Data 0.001 (0.005) Loss 0.0639 (0.0571) Prec@1 89.000 (89.500) Prec@5 99.000 (99.625) +2022-11-14 14:05:52,670 Epoch: [146][80/500] Time 0.025 (0.021) Data 0.002 (0.005) Loss 0.0669 (0.0582) Prec@1 89.000 (89.444) Prec@5 100.000 (99.667) +2022-11-14 14:05:52,930 Epoch: [146][90/500] Time 0.027 (0.021) Data 0.002 (0.004) Loss 0.0579 (0.0582) Prec@1 91.000 (89.600) Prec@5 100.000 (99.700) +2022-11-14 14:05:53,189 Epoch: [146][100/500] Time 0.022 (0.021) Data 0.002 (0.004) Loss 0.0821 (0.0603) Prec@1 85.000 (89.182) Prec@5 99.000 (99.636) +2022-11-14 14:05:53,451 Epoch: [146][110/500] Time 0.029 (0.022) Data 0.002 (0.004) Loss 0.0605 (0.0603) Prec@1 90.000 (89.250) Prec@5 98.000 (99.500) +2022-11-14 14:05:53,709 Epoch: [146][120/500] Time 0.023 (0.022) Data 0.001 (0.004) Loss 0.0618 (0.0605) Prec@1 89.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 14:05:53,971 Epoch: [146][130/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0331 (0.0585) Prec@1 95.000 (89.643) Prec@5 100.000 (99.571) +2022-11-14 14:05:54,404 Epoch: [146][140/500] Time 0.042 (0.023) Data 0.002 (0.003) Loss 0.0345 (0.0569) Prec@1 95.000 (90.000) Prec@5 99.000 (99.533) +2022-11-14 14:05:54,863 Epoch: [146][150/500] Time 0.042 (0.024) Data 0.002 (0.003) Loss 0.0399 (0.0558) Prec@1 96.000 (90.375) Prec@5 100.000 (99.562) +2022-11-14 14:05:55,320 Epoch: [146][160/500] Time 0.042 (0.025) Data 0.002 (0.003) Loss 0.0499 (0.0555) Prec@1 91.000 (90.412) Prec@5 100.000 (99.588) +2022-11-14 14:05:55,770 Epoch: [146][170/500] Time 0.042 (0.026) Data 0.002 (0.003) Loss 0.0495 (0.0552) Prec@1 91.000 (90.444) Prec@5 99.000 (99.556) +2022-11-14 14:05:56,224 Epoch: [146][180/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0725 (0.0561) Prec@1 86.000 (90.211) Prec@5 99.000 (99.526) +2022-11-14 14:05:56,680 Epoch: [146][190/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0452 (0.0555) Prec@1 93.000 (90.350) Prec@5 100.000 (99.550) +2022-11-14 14:05:57,137 Epoch: [146][200/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0425 (0.0549) Prec@1 93.000 (90.476) Prec@5 100.000 (99.571) +2022-11-14 14:05:57,588 Epoch: [146][210/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0497 (0.0547) Prec@1 91.000 (90.500) Prec@5 99.000 (99.545) +2022-11-14 14:05:58,035 Epoch: [146][220/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0481 (0.0544) Prec@1 93.000 (90.609) Prec@5 99.000 (99.522) +2022-11-14 14:05:58,486 Epoch: [146][230/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0809 (0.0555) Prec@1 87.000 (90.458) Prec@5 99.000 (99.500) +2022-11-14 14:05:58,942 Epoch: [146][240/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0564 (0.0555) Prec@1 91.000 (90.480) Prec@5 99.000 (99.480) +2022-11-14 14:05:59,406 Epoch: [146][250/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0515 (0.0554) Prec@1 91.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 14:05:59,859 Epoch: [146][260/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0634 (0.0557) Prec@1 91.000 (90.519) Prec@5 97.000 (99.407) +2022-11-14 14:06:00,312 Epoch: [146][270/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0549 (0.0556) Prec@1 90.000 (90.500) Prec@5 99.000 (99.393) +2022-11-14 14:06:00,764 Epoch: [146][280/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0670 (0.0560) Prec@1 87.000 (90.379) Prec@5 99.000 (99.379) +2022-11-14 14:06:01,215 Epoch: [146][290/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0453 (0.0557) Prec@1 93.000 (90.467) Prec@5 99.000 (99.367) +2022-11-14 14:06:01,670 Epoch: [146][300/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0407 (0.0552) Prec@1 92.000 (90.516) Prec@5 100.000 (99.387) +2022-11-14 14:06:02,115 Epoch: [146][310/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0467 (0.0549) Prec@1 93.000 (90.594) Prec@5 100.000 (99.406) +2022-11-14 14:06:02,566 Epoch: [146][320/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0732 (0.0555) Prec@1 86.000 (90.455) Prec@5 100.000 (99.424) +2022-11-14 14:06:03,018 Epoch: [146][330/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0914 (0.0565) Prec@1 83.000 (90.235) Prec@5 100.000 (99.441) +2022-11-14 14:06:03,467 Epoch: [146][340/500] Time 0.043 (0.033) Data 0.001 (0.002) Loss 0.0438 (0.0562) Prec@1 93.000 (90.314) Prec@5 100.000 (99.457) +2022-11-14 14:06:03,915 Epoch: [146][350/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0694 (0.0565) Prec@1 86.000 (90.194) Prec@5 100.000 (99.472) +2022-11-14 14:06:04,368 Epoch: [146][360/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0516 (0.0564) Prec@1 91.000 (90.216) Prec@5 100.000 (99.486) +2022-11-14 14:06:04,817 Epoch: [146][370/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0608 (0.0565) Prec@1 89.000 (90.184) Prec@5 99.000 (99.474) +2022-11-14 14:06:05,265 Epoch: [146][380/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0544 (0.0565) Prec@1 91.000 (90.205) Prec@5 99.000 (99.462) +2022-11-14 14:06:05,717 Epoch: [146][390/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0745 (0.0569) Prec@1 88.000 (90.150) Prec@5 99.000 (99.450) +2022-11-14 14:06:06,169 Epoch: [146][400/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.0376 (0.0564) Prec@1 93.000 (90.220) Prec@5 100.000 (99.463) +2022-11-14 14:06:06,621 Epoch: [146][410/500] Time 0.043 (0.034) Data 0.001 (0.002) Loss 0.0398 (0.0561) Prec@1 94.000 (90.310) Prec@5 99.000 (99.452) +2022-11-14 14:06:07,077 Epoch: [146][420/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0573 (0.0561) Prec@1 93.000 (90.372) Prec@5 99.000 (99.442) +2022-11-14 14:06:07,517 Epoch: [146][430/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0399 (0.0557) Prec@1 94.000 (90.455) Prec@5 100.000 (99.455) +2022-11-14 14:06:07,811 Epoch: [146][440/500] Time 0.025 (0.034) Data 0.002 (0.002) Loss 0.0320 (0.0552) Prec@1 94.000 (90.533) Prec@5 100.000 (99.467) +2022-11-14 14:06:08,086 Epoch: [146][450/500] Time 0.025 (0.034) Data 0.002 (0.002) Loss 0.0584 (0.0553) Prec@1 92.000 (90.565) Prec@5 99.000 (99.457) +2022-11-14 14:06:08,361 Epoch: [146][460/500] Time 0.026 (0.034) Data 0.001 (0.002) Loss 0.0351 (0.0548) Prec@1 94.000 (90.638) Prec@5 99.000 (99.447) +2022-11-14 14:06:08,636 Epoch: [146][470/500] Time 0.025 (0.034) Data 0.002 (0.002) Loss 0.0464 (0.0546) Prec@1 92.000 (90.667) Prec@5 99.000 (99.438) +2022-11-14 14:06:08,915 Epoch: [146][480/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0347 (0.0542) Prec@1 94.000 (90.735) Prec@5 100.000 (99.449) +2022-11-14 14:06:09,192 Epoch: [146][490/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0463 (0.0541) Prec@1 93.000 (90.780) Prec@5 100.000 (99.460) +2022-11-14 14:06:09,442 Epoch: [146][499/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0476 (0.0540) Prec@1 92.000 (90.804) Prec@5 100.000 (99.471) +2022-11-14 14:06:09,730 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0433 (0.0433) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:06:09,740 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0579) Prec@1 90.000 (92.000) Prec@5 98.000 (99.000) +2022-11-14 14:06:09,748 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0621) Prec@1 90.000 (91.333) Prec@5 100.000 (99.333) +2022-11-14 14:06:09,760 Test: [3/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0668) Prec@1 83.000 (89.250) Prec@5 99.000 (99.250) +2022-11-14 14:06:09,768 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0668) Prec@1 87.000 (88.800) Prec@5 100.000 (99.400) +2022-11-14 14:06:09,776 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0315 (0.0609) Prec@1 95.000 (89.833) Prec@5 100.000 (99.500) +2022-11-14 14:06:09,785 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0612) Prec@1 89.000 (89.714) Prec@5 99.000 (99.429) +2022-11-14 14:06:09,794 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.0684) Prec@1 79.000 (88.375) Prec@5 100.000 (99.500) +2022-11-14 14:06:09,802 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0725) Prec@1 83.000 (87.778) Prec@5 99.000 (99.444) +2022-11-14 14:06:09,810 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0735) Prec@1 88.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 14:06:09,820 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0733) Prec@1 87.000 (87.727) Prec@5 99.000 (99.364) +2022-11-14 14:06:09,829 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0747) Prec@1 88.000 (87.750) Prec@5 100.000 (99.417) +2022-11-14 14:06:09,838 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0735) Prec@1 91.000 (88.000) Prec@5 99.000 (99.385) +2022-11-14 14:06:09,848 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0730) Prec@1 91.000 (88.214) Prec@5 99.000 (99.357) +2022-11-14 14:06:09,857 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0724) Prec@1 89.000 (88.267) Prec@5 100.000 (99.400) +2022-11-14 14:06:09,866 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1176 (0.0753) Prec@1 80.000 (87.750) Prec@5 99.000 (99.375) +2022-11-14 14:06:09,875 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0736) Prec@1 94.000 (88.118) Prec@5 98.000 (99.294) +2022-11-14 14:06:09,885 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0751) Prec@1 83.000 (87.833) Prec@5 98.000 (99.222) +2022-11-14 14:06:09,894 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0757) Prec@1 86.000 (87.737) Prec@5 99.000 (99.211) +2022-11-14 14:06:09,903 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0772) Prec@1 84.000 (87.550) Prec@5 98.000 (99.150) +2022-11-14 14:06:09,912 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.0785) Prec@1 84.000 (87.381) Prec@5 100.000 (99.190) +2022-11-14 14:06:09,921 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0783) Prec@1 86.000 (87.318) Prec@5 100.000 (99.227) +2022-11-14 14:06:09,931 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.0796) Prec@1 83.000 (87.130) Prec@5 98.000 (99.174) +2022-11-14 14:06:09,940 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0801) Prec@1 85.000 (87.042) Prec@5 100.000 (99.208) +2022-11-14 14:06:09,949 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0805) Prec@1 84.000 (86.920) Prec@5 99.000 (99.200) +2022-11-14 14:06:09,958 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0813) Prec@1 84.000 (86.808) Prec@5 98.000 (99.154) +2022-11-14 14:06:09,968 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0806) Prec@1 89.000 (86.889) Prec@5 100.000 (99.185) +2022-11-14 14:06:09,976 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0811) Prec@1 85.000 (86.821) Prec@5 100.000 (99.214) +2022-11-14 14:06:09,985 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0808) Prec@1 89.000 (86.897) Prec@5 99.000 (99.207) +2022-11-14 14:06:09,995 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0802) Prec@1 90.000 (87.000) Prec@5 100.000 (99.233) +2022-11-14 14:06:10,003 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0797) Prec@1 89.000 (87.065) Prec@5 99.000 (99.226) +2022-11-14 14:06:10,011 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0795) Prec@1 86.000 (87.031) Prec@5 100.000 (99.250) +2022-11-14 14:06:10,019 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0794) Prec@1 87.000 (87.030) Prec@5 100.000 (99.273) +2022-11-14 14:06:10,027 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1197 (0.0806) Prec@1 81.000 (86.853) Prec@5 99.000 (99.265) +2022-11-14 14:06:10,035 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0802) Prec@1 88.000 (86.886) Prec@5 99.000 (99.257) +2022-11-14 14:06:10,043 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0799) Prec@1 86.000 (86.861) Prec@5 100.000 (99.278) +2022-11-14 14:06:10,051 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0802) Prec@1 85.000 (86.811) Prec@5 99.000 (99.270) +2022-11-14 14:06:10,060 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0806) Prec@1 84.000 (86.737) Prec@5 98.000 (99.237) +2022-11-14 14:06:10,068 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0799) Prec@1 93.000 (86.897) Prec@5 99.000 (99.231) +2022-11-14 14:06:10,076 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0795) Prec@1 90.000 (86.975) Prec@5 98.000 (99.200) +2022-11-14 14:06:10,084 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0798) Prec@1 84.000 (86.902) Prec@5 98.000 (99.171) +2022-11-14 14:06:10,092 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0795) Prec@1 90.000 (86.976) Prec@5 98.000 (99.143) +2022-11-14 14:06:10,100 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0793) Prec@1 92.000 (87.093) Prec@5 98.000 (99.116) +2022-11-14 14:06:10,109 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0794) Prec@1 88.000 (87.114) Prec@5 96.000 (99.045) +2022-11-14 14:06:10,117 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0791) Prec@1 89.000 (87.156) Prec@5 100.000 (99.067) +2022-11-14 14:06:10,127 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1264 (0.0801) Prec@1 78.000 (86.957) Prec@5 100.000 (99.087) +2022-11-14 14:06:10,135 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0798) Prec@1 91.000 (87.043) Prec@5 100.000 (99.106) +2022-11-14 14:06:10,144 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0805) Prec@1 82.000 (86.938) Prec@5 99.000 (99.104) +2022-11-14 14:06:10,154 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0802) Prec@1 89.000 (86.980) Prec@5 99.000 (99.102) +2022-11-14 14:06:10,162 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1227 (0.0811) Prec@1 78.000 (86.800) Prec@5 100.000 (99.120) +2022-11-14 14:06:10,171 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0805) Prec@1 92.000 (86.902) Prec@5 100.000 (99.137) +2022-11-14 14:06:10,180 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0806) Prec@1 82.000 (86.808) Prec@5 100.000 (99.154) +2022-11-14 14:06:10,189 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0803) Prec@1 87.000 (86.811) Prec@5 99.000 (99.151) +2022-11-14 14:06:10,198 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0802) Prec@1 85.000 (86.778) Prec@5 100.000 (99.167) +2022-11-14 14:06:10,206 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0802) Prec@1 86.000 (86.764) Prec@5 100.000 (99.182) +2022-11-14 14:06:10,216 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0800) Prec@1 89.000 (86.804) Prec@5 99.000 (99.179) +2022-11-14 14:06:10,225 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0803) Prec@1 83.000 (86.737) Prec@5 100.000 (99.193) +2022-11-14 14:06:10,234 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0804) Prec@1 86.000 (86.724) Prec@5 99.000 (99.190) +2022-11-14 14:06:10,243 Test: [58/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0808) Prec@1 80.000 (86.610) Prec@5 98.000 (99.169) +2022-11-14 14:06:10,253 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0808) Prec@1 84.000 (86.567) Prec@5 100.000 (99.183) +2022-11-14 14:06:10,261 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0810) Prec@1 86.000 (86.557) Prec@5 98.000 (99.164) +2022-11-14 14:06:10,270 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0810) Prec@1 87.000 (86.565) Prec@5 99.000 (99.161) +2022-11-14 14:06:10,279 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0811) Prec@1 85.000 (86.540) Prec@5 100.000 (99.175) +2022-11-14 14:06:10,289 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0808) Prec@1 91.000 (86.609) Prec@5 100.000 (99.188) +2022-11-14 14:06:10,297 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0811) Prec@1 82.000 (86.538) Prec@5 99.000 (99.185) +2022-11-14 14:06:10,305 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0812) Prec@1 87.000 (86.545) Prec@5 99.000 (99.182) +2022-11-14 14:06:10,313 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0810) Prec@1 87.000 (86.552) Prec@5 100.000 (99.194) +2022-11-14 14:06:10,321 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0812) Prec@1 85.000 (86.529) Prec@5 99.000 (99.191) +2022-11-14 14:06:10,329 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0811) Prec@1 86.000 (86.522) Prec@5 100.000 (99.203) +2022-11-14 14:06:10,338 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0814) Prec@1 84.000 (86.486) Prec@5 98.000 (99.186) +2022-11-14 14:06:10,346 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0816) Prec@1 85.000 (86.465) Prec@5 99.000 (99.183) +2022-11-14 14:06:10,353 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0814) Prec@1 87.000 (86.472) Prec@5 100.000 (99.194) +2022-11-14 14:06:10,361 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0812) Prec@1 88.000 (86.493) Prec@5 100.000 (99.205) +2022-11-14 14:06:10,370 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0810) Prec@1 88.000 (86.514) Prec@5 100.000 (99.216) +2022-11-14 14:06:10,378 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0811) Prec@1 83.000 (86.467) Prec@5 100.000 (99.227) +2022-11-14 14:06:10,387 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0809) Prec@1 88.000 (86.487) Prec@5 98.000 (99.211) +2022-11-14 14:06:10,396 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0810) Prec@1 81.000 (86.416) Prec@5 100.000 (99.221) +2022-11-14 14:06:10,405 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0811) Prec@1 84.000 (86.385) Prec@5 98.000 (99.205) +2022-11-14 14:06:10,415 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0810) Prec@1 88.000 (86.405) Prec@5 100.000 (99.215) +2022-11-14 14:06:10,424 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0810) Prec@1 84.000 (86.375) Prec@5 100.000 (99.225) +2022-11-14 14:06:10,433 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0809) Prec@1 87.000 (86.383) Prec@5 100.000 (99.235) +2022-11-14 14:06:10,442 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0810) Prec@1 82.000 (86.329) Prec@5 100.000 (99.244) +2022-11-14 14:06:10,452 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0811) Prec@1 87.000 (86.337) Prec@5 98.000 (99.229) +2022-11-14 14:06:10,461 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0813) Prec@1 82.000 (86.286) Prec@5 100.000 (99.238) +2022-11-14 14:06:10,470 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0813) Prec@1 85.000 (86.271) Prec@5 100.000 (99.247) +2022-11-14 14:06:10,479 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0815) Prec@1 84.000 (86.244) Prec@5 99.000 (99.244) +2022-11-14 14:06:10,489 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0816) Prec@1 84.000 (86.218) Prec@5 100.000 (99.253) +2022-11-14 14:06:10,498 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0816) Prec@1 86.000 (86.216) Prec@5 99.000 (99.250) +2022-11-14 14:06:10,507 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0815) Prec@1 88.000 (86.236) Prec@5 99.000 (99.247) +2022-11-14 14:06:10,517 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0815) Prec@1 85.000 (86.222) Prec@5 100.000 (99.256) +2022-11-14 14:06:10,525 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0815) Prec@1 89.000 (86.253) Prec@5 100.000 (99.264) +2022-11-14 14:06:10,535 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0812) Prec@1 90.000 (86.293) Prec@5 100.000 (99.272) +2022-11-14 14:06:10,545 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0815) Prec@1 84.000 (86.269) Prec@5 98.000 (99.258) +2022-11-14 14:06:10,554 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0815) Prec@1 88.000 (86.287) Prec@5 99.000 (99.255) +2022-11-14 14:06:10,563 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0815) Prec@1 86.000 (86.284) Prec@5 99.000 (99.253) +2022-11-14 14:06:10,572 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0812) Prec@1 90.000 (86.323) Prec@5 97.000 (99.229) +2022-11-14 14:06:10,580 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0809) Prec@1 92.000 (86.381) Prec@5 100.000 (99.237) +2022-11-14 14:06:10,588 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0811) Prec@1 83.000 (86.347) Prec@5 99.000 (99.235) +2022-11-14 14:06:10,596 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0815) Prec@1 83.000 (86.313) Prec@5 100.000 (99.242) +2022-11-14 14:06:10,605 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0814) Prec@1 88.000 (86.330) Prec@5 99.000 (99.240) +2022-11-14 14:06:10,660 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:06:10,959 Epoch: [147][0/500] Time 0.023 (0.023) Data 0.219 (0.219) Loss 0.0778 (0.0778) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:06:11,163 Epoch: [147][10/500] Time 0.017 (0.018) Data 0.002 (0.021) Loss 0.0815 (0.0797) Prec@1 86.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 14:06:11,360 Epoch: [147][20/500] Time 0.017 (0.018) Data 0.002 (0.012) Loss 0.0412 (0.0668) Prec@1 92.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 14:06:11,610 Epoch: [147][30/500] Time 0.024 (0.019) Data 0.002 (0.009) Loss 0.0633 (0.0660) Prec@1 90.000 (88.250) Prec@5 98.000 (99.500) +2022-11-14 14:06:12,062 Epoch: [147][40/500] Time 0.043 (0.024) Data 0.002 (0.007) Loss 0.0760 (0.0680) Prec@1 88.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 14:06:12,523 Epoch: [147][50/500] Time 0.043 (0.027) Data 0.002 (0.006) Loss 0.0551 (0.0658) Prec@1 92.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 14:06:12,986 Epoch: [147][60/500] Time 0.043 (0.030) Data 0.002 (0.005) Loss 0.0576 (0.0646) Prec@1 91.000 (89.143) Prec@5 99.000 (99.429) +2022-11-14 14:06:13,448 Epoch: [147][70/500] Time 0.045 (0.031) Data 0.002 (0.005) Loss 0.0338 (0.0608) Prec@1 95.000 (89.875) Prec@5 100.000 (99.500) +2022-11-14 14:06:13,911 Epoch: [147][80/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.0346 (0.0579) Prec@1 94.000 (90.333) Prec@5 100.000 (99.556) +2022-11-14 14:06:14,374 Epoch: [147][90/500] Time 0.044 (0.033) Data 0.001 (0.004) Loss 0.0680 (0.0589) Prec@1 88.000 (90.100) Prec@5 100.000 (99.600) +2022-11-14 14:06:14,835 Epoch: [147][100/500] Time 0.046 (0.034) Data 0.002 (0.004) Loss 0.0497 (0.0580) Prec@1 93.000 (90.364) Prec@5 98.000 (99.455) +2022-11-14 14:06:15,296 Epoch: [147][110/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0642 (0.0586) Prec@1 90.000 (90.333) Prec@5 100.000 (99.500) +2022-11-14 14:06:15,759 Epoch: [147][120/500] Time 0.044 (0.035) Data 0.001 (0.004) Loss 0.0659 (0.0591) Prec@1 90.000 (90.308) Prec@5 100.000 (99.538) +2022-11-14 14:06:16,221 Epoch: [147][130/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0450 (0.0581) Prec@1 93.000 (90.500) Prec@5 100.000 (99.571) +2022-11-14 14:06:16,678 Epoch: [147][140/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0468 (0.0574) Prec@1 91.000 (90.533) Prec@5 100.000 (99.600) +2022-11-14 14:06:17,140 Epoch: [147][150/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0341 (0.0559) Prec@1 94.000 (90.750) Prec@5 100.000 (99.625) +2022-11-14 14:06:17,599 Epoch: [147][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0471 (0.0554) Prec@1 93.000 (90.882) Prec@5 100.000 (99.647) +2022-11-14 14:06:18,060 Epoch: [147][170/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0618 (0.0557) Prec@1 91.000 (90.889) Prec@5 100.000 (99.667) +2022-11-14 14:06:18,521 Epoch: [147][180/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0352 (0.0547) Prec@1 95.000 (91.105) Prec@5 100.000 (99.684) +2022-11-14 14:06:18,980 Epoch: [147][190/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0616 (0.0550) Prec@1 88.000 (90.950) Prec@5 100.000 (99.700) +2022-11-14 14:06:19,286 Epoch: [147][200/500] Time 0.031 (0.037) Data 0.002 (0.003) Loss 0.0501 (0.0548) Prec@1 95.000 (91.143) Prec@5 99.000 (99.667) +2022-11-14 14:06:19,574 Epoch: [147][210/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.0587 (0.0550) Prec@1 90.000 (91.091) Prec@5 100.000 (99.682) +2022-11-14 14:06:19,865 Epoch: [147][220/500] Time 0.028 (0.036) Data 0.001 (0.003) Loss 0.0433 (0.0544) Prec@1 92.000 (91.130) Prec@5 99.000 (99.652) +2022-11-14 14:06:20,158 Epoch: [147][230/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.0583 (0.0546) Prec@1 92.000 (91.167) Prec@5 99.000 (99.625) +2022-11-14 14:06:20,453 Epoch: [147][240/500] Time 0.028 (0.035) Data 0.001 (0.003) Loss 0.0610 (0.0549) Prec@1 89.000 (91.080) Prec@5 98.000 (99.560) +2022-11-14 14:06:20,746 Epoch: [147][250/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.0766 (0.0557) Prec@1 89.000 (91.000) Prec@5 100.000 (99.577) +2022-11-14 14:06:21,042 Epoch: [147][260/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0618 (0.0559) Prec@1 89.000 (90.926) Prec@5 100.000 (99.593) +2022-11-14 14:06:21,337 Epoch: [147][270/500] Time 0.027 (0.034) Data 0.001 (0.003) Loss 0.0438 (0.0555) Prec@1 91.000 (90.929) Prec@5 99.000 (99.571) +2022-11-14 14:06:21,630 Epoch: [147][280/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0656 (0.0558) Prec@1 90.000 (90.897) Prec@5 100.000 (99.586) +2022-11-14 14:06:21,922 Epoch: [147][290/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.0639 (0.0561) Prec@1 90.000 (90.867) Prec@5 100.000 (99.600) +2022-11-14 14:06:22,217 Epoch: [147][300/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.0565 (0.0561) Prec@1 91.000 (90.871) Prec@5 100.000 (99.613) +2022-11-14 14:06:22,511 Epoch: [147][310/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.0585 (0.0562) Prec@1 92.000 (90.906) Prec@5 99.000 (99.594) +2022-11-14 14:06:22,813 Epoch: [147][320/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.0313 (0.0554) Prec@1 95.000 (91.030) Prec@5 100.000 (99.606) +2022-11-14 14:06:23,109 Epoch: [147][330/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0440 (0.0551) Prec@1 93.000 (91.088) Prec@5 100.000 (99.618) +2022-11-14 14:06:23,405 Epoch: [147][340/500] Time 0.027 (0.032) Data 0.003 (0.002) Loss 0.0589 (0.0552) Prec@1 89.000 (91.029) Prec@5 100.000 (99.629) +2022-11-14 14:06:23,706 Epoch: [147][350/500] Time 0.027 (0.032) Data 0.001 (0.002) Loss 0.0561 (0.0552) Prec@1 90.000 (91.000) Prec@5 99.000 (99.611) +2022-11-14 14:06:24,003 Epoch: [147][360/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.0562 (0.0553) Prec@1 90.000 (90.973) Prec@5 100.000 (99.622) +2022-11-14 14:06:24,304 Epoch: [147][370/500] Time 0.028 (0.032) Data 0.002 (0.002) Loss 0.0685 (0.0556) Prec@1 86.000 (90.842) Prec@5 100.000 (99.632) +2022-11-14 14:06:24,602 Epoch: [147][380/500] Time 0.028 (0.032) Data 0.001 (0.002) Loss 0.0442 (0.0553) Prec@1 93.000 (90.897) Prec@5 100.000 (99.641) +2022-11-14 14:06:24,909 Epoch: [147][390/500] Time 0.034 (0.032) Data 0.002 (0.002) Loss 0.0656 (0.0556) Prec@1 90.000 (90.875) Prec@5 100.000 (99.650) +2022-11-14 14:06:25,204 Epoch: [147][400/500] Time 0.028 (0.032) Data 0.002 (0.002) Loss 0.0609 (0.0557) Prec@1 90.000 (90.854) Prec@5 100.000 (99.659) +2022-11-14 14:06:25,502 Epoch: [147][410/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0777 (0.0562) Prec@1 86.000 (90.738) Prec@5 98.000 (99.619) +2022-11-14 14:06:25,804 Epoch: [147][420/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0504 (0.0561) Prec@1 92.000 (90.767) Prec@5 100.000 (99.628) +2022-11-14 14:06:26,099 Epoch: [147][430/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0443 (0.0558) Prec@1 93.000 (90.818) Prec@5 100.000 (99.636) +2022-11-14 14:06:26,394 Epoch: [147][440/500] Time 0.029 (0.031) Data 0.001 (0.002) Loss 0.0596 (0.0559) Prec@1 87.000 (90.733) Prec@5 99.000 (99.622) +2022-11-14 14:06:26,689 Epoch: [147][450/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0675 (0.0562) Prec@1 89.000 (90.696) Prec@5 98.000 (99.587) +2022-11-14 14:06:26,988 Epoch: [147][460/500] Time 0.027 (0.031) Data 0.002 (0.002) Loss 0.0318 (0.0556) Prec@1 96.000 (90.809) Prec@5 100.000 (99.596) +2022-11-14 14:06:27,284 Epoch: [147][470/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0235 (0.0550) Prec@1 98.000 (90.958) Prec@5 100.000 (99.604) +2022-11-14 14:06:27,601 Epoch: [147][480/500] Time 0.031 (0.031) Data 0.002 (0.002) Loss 0.0615 (0.0551) Prec@1 88.000 (90.898) Prec@5 99.000 (99.592) +2022-11-14 14:06:28,066 Epoch: [147][490/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0485 (0.0550) Prec@1 91.000 (90.900) Prec@5 100.000 (99.600) +2022-11-14 14:06:28,485 Epoch: [147][499/500] Time 0.043 (0.031) Data 0.001 (0.002) Loss 0.0675 (0.0552) Prec@1 89.000 (90.863) Prec@5 99.000 (99.588) +2022-11-14 14:06:28,772 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0572 (0.0572) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:06:28,781 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0762) Prec@1 83.000 (85.500) Prec@5 98.000 (99.000) +2022-11-14 14:06:28,790 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0777) Prec@1 88.000 (86.333) Prec@5 100.000 (99.333) +2022-11-14 14:06:28,801 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0831) Prec@1 85.000 (86.000) Prec@5 99.000 (99.250) +2022-11-14 14:06:28,809 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0843) Prec@1 85.000 (85.800) Prec@5 99.000 (99.200) +2022-11-14 14:06:28,817 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0492 (0.0784) Prec@1 91.000 (86.667) Prec@5 100.000 (99.333) +2022-11-14 14:06:28,827 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0759) Prec@1 89.000 (87.000) Prec@5 100.000 (99.429) +2022-11-14 14:06:28,837 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0791) Prec@1 81.000 (86.250) Prec@5 99.000 (99.375) +2022-11-14 14:06:28,845 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0802) Prec@1 85.000 (86.111) Prec@5 99.000 (99.333) +2022-11-14 14:06:28,854 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0788) Prec@1 89.000 (86.400) Prec@5 99.000 (99.300) +2022-11-14 14:06:28,862 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0784) Prec@1 87.000 (86.455) Prec@5 100.000 (99.364) +2022-11-14 14:06:28,871 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0787) Prec@1 87.000 (86.500) Prec@5 98.000 (99.250) +2022-11-14 14:06:28,882 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0789) Prec@1 86.000 (86.462) Prec@5 100.000 (99.308) +2022-11-14 14:06:28,894 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0785) Prec@1 89.000 (86.643) Prec@5 98.000 (99.214) +2022-11-14 14:06:28,906 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0783) Prec@1 89.000 (86.800) Prec@5 97.000 (99.067) +2022-11-14 14:06:28,917 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0788) Prec@1 82.000 (86.500) Prec@5 98.000 (99.000) +2022-11-14 14:06:28,929 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0781) Prec@1 91.000 (86.765) Prec@5 97.000 (98.882) +2022-11-14 14:06:28,941 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.0798) Prec@1 83.000 (86.556) Prec@5 100.000 (98.944) +2022-11-14 14:06:28,951 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0808) Prec@1 83.000 (86.368) Prec@5 98.000 (98.895) +2022-11-14 14:06:28,963 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0818) Prec@1 84.000 (86.250) Prec@5 97.000 (98.800) +2022-11-14 14:06:28,975 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0829) Prec@1 84.000 (86.143) Prec@5 100.000 (98.857) +2022-11-14 14:06:28,986 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0839) Prec@1 82.000 (85.955) Prec@5 99.000 (98.864) +2022-11-14 14:06:28,998 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0842) Prec@1 87.000 (86.000) Prec@5 100.000 (98.913) +2022-11-14 14:06:29,010 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0838) Prec@1 87.000 (86.042) Prec@5 99.000 (98.917) +2022-11-14 14:06:29,021 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0843) Prec@1 83.000 (85.920) Prec@5 100.000 (98.960) +2022-11-14 14:06:29,033 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.0853) Prec@1 83.000 (85.808) Prec@5 97.000 (98.885) +2022-11-14 14:06:29,044 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0843) Prec@1 90.000 (85.963) Prec@5 100.000 (98.926) +2022-11-14 14:06:29,055 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0844) Prec@1 88.000 (86.036) Prec@5 100.000 (98.964) +2022-11-14 14:06:29,066 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0840) Prec@1 88.000 (86.103) Prec@5 99.000 (98.966) +2022-11-14 14:06:29,079 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0839) Prec@1 85.000 (86.067) Prec@5 100.000 (99.000) +2022-11-14 14:06:29,090 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0842) Prec@1 86.000 (86.065) Prec@5 99.000 (99.000) +2022-11-14 14:06:29,102 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0837) Prec@1 87.000 (86.094) Prec@5 100.000 (99.031) +2022-11-14 14:06:29,114 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0836) Prec@1 84.000 (86.030) Prec@5 99.000 (99.030) +2022-11-14 14:06:29,124 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0841) Prec@1 84.000 (85.971) Prec@5 100.000 (99.059) +2022-11-14 14:06:29,136 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0837) Prec@1 87.000 (86.000) Prec@5 99.000 (99.057) +2022-11-14 14:06:29,148 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0835) Prec@1 88.000 (86.056) Prec@5 100.000 (99.083) +2022-11-14 14:06:29,159 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0833) Prec@1 86.000 (86.054) Prec@5 99.000 (99.081) +2022-11-14 14:06:29,171 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0837) Prec@1 83.000 (85.974) Prec@5 99.000 (99.079) +2022-11-14 14:06:29,182 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0833) Prec@1 89.000 (86.051) Prec@5 99.000 (99.077) +2022-11-14 14:06:29,192 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0831) Prec@1 87.000 (86.075) Prec@5 99.000 (99.075) +2022-11-14 14:06:29,202 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1118 (0.0838) Prec@1 81.000 (85.951) Prec@5 97.000 (99.024) +2022-11-14 14:06:29,212 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0836) Prec@1 87.000 (85.976) Prec@5 99.000 (99.024) +2022-11-14 14:06:29,223 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0832) Prec@1 88.000 (86.023) Prec@5 100.000 (99.047) +2022-11-14 14:06:29,234 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0830) Prec@1 90.000 (86.114) Prec@5 99.000 (99.045) +2022-11-14 14:06:29,246 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0828) Prec@1 88.000 (86.156) Prec@5 99.000 (99.044) +2022-11-14 14:06:29,258 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.0833) Prec@1 81.000 (86.043) Prec@5 99.000 (99.043) +2022-11-14 14:06:29,269 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0829) Prec@1 90.000 (86.128) Prec@5 100.000 (99.064) +2022-11-14 14:06:29,280 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0832) Prec@1 82.000 (86.042) Prec@5 100.000 (99.083) +2022-11-14 14:06:29,292 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0829) Prec@1 87.000 (86.061) Prec@5 100.000 (99.102) +2022-11-14 14:06:29,304 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1462 (0.0842) Prec@1 76.000 (85.860) Prec@5 99.000 (99.100) +2022-11-14 14:06:29,316 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0839) Prec@1 87.000 (85.882) Prec@5 100.000 (99.118) +2022-11-14 14:06:29,328 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0841) Prec@1 84.000 (85.846) Prec@5 99.000 (99.115) +2022-11-14 14:06:29,338 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0844) Prec@1 83.000 (85.792) Prec@5 100.000 (99.132) +2022-11-14 14:06:29,350 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0843) Prec@1 86.000 (85.796) Prec@5 99.000 (99.130) +2022-11-14 14:06:29,362 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0842) Prec@1 89.000 (85.855) Prec@5 100.000 (99.145) +2022-11-14 14:06:29,373 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0846) Prec@1 82.000 (85.786) Prec@5 98.000 (99.125) +2022-11-14 14:06:29,386 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0843) Prec@1 87.000 (85.807) Prec@5 100.000 (99.140) +2022-11-14 14:06:29,397 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0840) Prec@1 91.000 (85.897) Prec@5 98.000 (99.121) +2022-11-14 14:06:29,408 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0842) Prec@1 86.000 (85.898) Prec@5 100.000 (99.136) +2022-11-14 14:06:29,420 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0842) Prec@1 86.000 (85.900) Prec@5 99.000 (99.133) +2022-11-14 14:06:29,432 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0843) Prec@1 85.000 (85.885) Prec@5 100.000 (99.148) +2022-11-14 14:06:29,443 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0844) Prec@1 85.000 (85.871) Prec@5 99.000 (99.145) +2022-11-14 14:06:29,455 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0843) Prec@1 87.000 (85.889) Prec@5 100.000 (99.159) +2022-11-14 14:06:29,466 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0839) Prec@1 90.000 (85.953) Prec@5 99.000 (99.156) +2022-11-14 14:06:29,477 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0840) Prec@1 83.000 (85.908) Prec@5 98.000 (99.138) +2022-11-14 14:06:29,490 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.0844) Prec@1 84.000 (85.879) Prec@5 98.000 (99.121) +2022-11-14 14:06:29,501 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0838) Prec@1 95.000 (86.015) Prec@5 99.000 (99.119) +2022-11-14 14:06:29,511 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0841) Prec@1 85.000 (86.000) Prec@5 98.000 (99.103) +2022-11-14 14:06:29,524 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0839) Prec@1 89.000 (86.043) Prec@5 100.000 (99.116) +2022-11-14 14:06:29,535 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0840) Prec@1 89.000 (86.086) Prec@5 99.000 (99.114) +2022-11-14 14:06:29,547 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0841) Prec@1 87.000 (86.099) Prec@5 99.000 (99.113) +2022-11-14 14:06:29,559 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0841) Prec@1 87.000 (86.111) Prec@5 98.000 (99.097) +2022-11-14 14:06:29,570 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0839) Prec@1 91.000 (86.178) Prec@5 100.000 (99.110) +2022-11-14 14:06:29,581 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0835) Prec@1 92.000 (86.257) Prec@5 100.000 (99.122) +2022-11-14 14:06:29,593 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0836) Prec@1 81.000 (86.187) Prec@5 100.000 (99.133) +2022-11-14 14:06:29,604 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0834) Prec@1 91.000 (86.250) Prec@5 100.000 (99.145) +2022-11-14 14:06:29,616 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0833) Prec@1 88.000 (86.273) Prec@5 98.000 (99.130) +2022-11-14 14:06:29,628 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0833) Prec@1 87.000 (86.282) Prec@5 96.000 (99.090) +2022-11-14 14:06:29,640 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0834) Prec@1 88.000 (86.304) Prec@5 100.000 (99.101) +2022-11-14 14:06:29,651 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0835) Prec@1 84.000 (86.275) Prec@5 100.000 (99.112) +2022-11-14 14:06:29,663 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0834) Prec@1 88.000 (86.296) Prec@5 100.000 (99.123) +2022-11-14 14:06:29,674 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0835) Prec@1 85.000 (86.280) Prec@5 100.000 (99.134) +2022-11-14 14:06:29,686 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0837) Prec@1 84.000 (86.253) Prec@5 99.000 (99.133) +2022-11-14 14:06:29,698 Test: [83/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0838) Prec@1 86.000 (86.250) Prec@5 99.000 (99.131) +2022-11-14 14:06:29,711 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0840) Prec@1 80.000 (86.176) Prec@5 97.000 (99.106) +2022-11-14 14:06:29,722 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0843) Prec@1 83.000 (86.140) Prec@5 98.000 (99.093) +2022-11-14 14:06:29,734 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0842) Prec@1 89.000 (86.172) Prec@5 97.000 (99.069) +2022-11-14 14:06:29,747 Test: [87/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0841) Prec@1 88.000 (86.193) Prec@5 99.000 (99.068) +2022-11-14 14:06:29,759 Test: [88/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0840) Prec@1 85.000 (86.180) Prec@5 99.000 (99.067) +2022-11-14 14:06:29,770 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1029 (0.0843) Prec@1 84.000 (86.156) Prec@5 99.000 (99.067) +2022-11-14 14:06:29,783 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0840) Prec@1 88.000 (86.176) Prec@5 100.000 (99.077) +2022-11-14 14:06:29,797 Test: [91/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0838) Prec@1 92.000 (86.239) Prec@5 99.000 (99.076) +2022-11-14 14:06:29,809 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0838) Prec@1 87.000 (86.247) Prec@5 100.000 (99.086) +2022-11-14 14:06:29,820 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0838) Prec@1 86.000 (86.245) Prec@5 99.000 (99.085) +2022-11-14 14:06:29,831 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0838) Prec@1 84.000 (86.221) Prec@5 99.000 (99.084) +2022-11-14 14:06:29,842 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0837) Prec@1 88.000 (86.240) Prec@5 98.000 (99.073) +2022-11-14 14:06:29,852 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0835) Prec@1 89.000 (86.268) Prec@5 99.000 (99.072) +2022-11-14 14:06:29,864 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0837) Prec@1 82.000 (86.224) Prec@5 98.000 (99.061) +2022-11-14 14:06:29,874 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1273 (0.0841) Prec@1 78.000 (86.141) Prec@5 99.000 (99.061) +2022-11-14 14:06:29,886 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0840) Prec@1 90.000 (86.180) Prec@5 99.000 (99.060) +2022-11-14 14:06:29,940 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:06:30,240 Epoch: [148][0/500] Time 0.024 (0.024) Data 0.219 (0.219) Loss 0.0670 (0.0670) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:06:30,449 Epoch: [148][10/500] Time 0.019 (0.019) Data 0.001 (0.021) Loss 0.0559 (0.0615) Prec@1 90.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:06:30,682 Epoch: [148][20/500] Time 0.030 (0.020) Data 0.002 (0.012) Loss 0.0517 (0.0582) Prec@1 92.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 14:06:30,996 Epoch: [148][30/500] Time 0.030 (0.022) Data 0.002 (0.009) Loss 0.0549 (0.0574) Prec@1 92.000 (90.750) Prec@5 100.000 (99.750) +2022-11-14 14:06:31,317 Epoch: [148][40/500] Time 0.030 (0.024) Data 0.002 (0.007) Loss 0.0594 (0.0578) Prec@1 91.000 (90.800) Prec@5 100.000 (99.800) +2022-11-14 14:06:31,643 Epoch: [148][50/500] Time 0.031 (0.025) Data 0.002 (0.006) Loss 0.0589 (0.0580) Prec@1 88.000 (90.333) Prec@5 99.000 (99.667) +2022-11-14 14:06:31,973 Epoch: [148][60/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0362 (0.0549) Prec@1 95.000 (91.000) Prec@5 100.000 (99.714) +2022-11-14 14:06:32,301 Epoch: [148][70/500] Time 0.030 (0.026) Data 0.002 (0.005) Loss 0.0799 (0.0580) Prec@1 85.000 (90.250) Prec@5 99.000 (99.625) +2022-11-14 14:06:32,629 Epoch: [148][80/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0430 (0.0563) Prec@1 94.000 (90.667) Prec@5 98.000 (99.444) +2022-11-14 14:06:32,956 Epoch: [148][90/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0497 (0.0557) Prec@1 91.000 (90.700) Prec@5 100.000 (99.500) +2022-11-14 14:06:33,285 Epoch: [148][100/500] Time 0.032 (0.027) Data 0.002 (0.004) Loss 0.0445 (0.0547) Prec@1 92.000 (90.818) Prec@5 100.000 (99.545) +2022-11-14 14:06:33,615 Epoch: [148][110/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0549 (0.0547) Prec@1 90.000 (90.750) Prec@5 100.000 (99.583) +2022-11-14 14:06:33,938 Epoch: [148][120/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0756 (0.0563) Prec@1 85.000 (90.308) Prec@5 100.000 (99.615) +2022-11-14 14:06:34,260 Epoch: [148][130/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0689 (0.0572) Prec@1 88.000 (90.143) Prec@5 98.000 (99.500) +2022-11-14 14:06:34,585 Epoch: [148][140/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0314 (0.0555) Prec@1 94.000 (90.400) Prec@5 100.000 (99.533) +2022-11-14 14:06:34,912 Epoch: [148][150/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0490 (0.0551) Prec@1 91.000 (90.438) Prec@5 100.000 (99.562) +2022-11-14 14:06:35,236 Epoch: [148][160/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0641 (0.0556) Prec@1 90.000 (90.412) Prec@5 98.000 (99.471) +2022-11-14 14:06:35,563 Epoch: [148][170/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0659 (0.0562) Prec@1 87.000 (90.222) Prec@5 100.000 (99.500) +2022-11-14 14:06:35,893 Epoch: [148][180/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0616 (0.0565) Prec@1 90.000 (90.211) Prec@5 98.000 (99.421) +2022-11-14 14:06:36,226 Epoch: [148][190/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0395 (0.0556) Prec@1 94.000 (90.400) Prec@5 99.000 (99.400) +2022-11-14 14:06:36,557 Epoch: [148][200/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0740 (0.0565) Prec@1 88.000 (90.286) Prec@5 100.000 (99.429) +2022-11-14 14:06:36,887 Epoch: [148][210/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0557 (0.0564) Prec@1 91.000 (90.318) Prec@5 99.000 (99.409) +2022-11-14 14:06:37,215 Epoch: [148][220/500] Time 0.031 (0.028) Data 0.001 (0.003) Loss 0.0545 (0.0564) Prec@1 92.000 (90.391) Prec@5 100.000 (99.435) +2022-11-14 14:06:37,550 Epoch: [148][230/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0976 (0.0581) Prec@1 84.000 (90.125) Prec@5 98.000 (99.375) +2022-11-14 14:06:37,878 Epoch: [148][240/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0376 (0.0573) Prec@1 93.000 (90.240) Prec@5 99.000 (99.360) +2022-11-14 14:06:38,210 Epoch: [148][250/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0584 (0.0573) Prec@1 89.000 (90.192) Prec@5 100.000 (99.385) +2022-11-14 14:06:38,539 Epoch: [148][260/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0388 (0.0566) Prec@1 92.000 (90.259) Prec@5 100.000 (99.407) +2022-11-14 14:06:38,868 Epoch: [148][270/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0937 (0.0579) Prec@1 84.000 (90.036) Prec@5 99.000 (99.393) +2022-11-14 14:06:39,194 Epoch: [148][280/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0560 (0.0579) Prec@1 89.000 (90.000) Prec@5 100.000 (99.414) +2022-11-14 14:06:39,525 Epoch: [148][290/500] Time 0.032 (0.028) Data 0.001 (0.002) Loss 0.0483 (0.0576) Prec@1 94.000 (90.133) Prec@5 99.000 (99.400) +2022-11-14 14:06:39,854 Epoch: [148][300/500] Time 0.031 (0.028) Data 0.002 (0.002) Loss 0.0669 (0.0579) Prec@1 90.000 (90.129) Prec@5 98.000 (99.355) +2022-11-14 14:06:40,186 Epoch: [148][310/500] Time 0.032 (0.028) Data 0.001 (0.002) Loss 0.0304 (0.0570) Prec@1 97.000 (90.344) Prec@5 100.000 (99.375) +2022-11-14 14:06:40,573 Epoch: [148][320/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0295 (0.0562) Prec@1 94.000 (90.455) Prec@5 100.000 (99.394) +2022-11-14 14:06:40,890 Epoch: [148][330/500] Time 0.037 (0.029) Data 0.002 (0.002) Loss 0.0337 (0.0555) Prec@1 94.000 (90.559) Prec@5 100.000 (99.412) +2022-11-14 14:06:41,213 Epoch: [148][340/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0503 (0.0554) Prec@1 92.000 (90.600) Prec@5 100.000 (99.429) +2022-11-14 14:06:41,543 Epoch: [148][350/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0464 (0.0551) Prec@1 94.000 (90.694) Prec@5 100.000 (99.444) +2022-11-14 14:06:41,877 Epoch: [148][360/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0229 (0.0542) Prec@1 96.000 (90.838) Prec@5 100.000 (99.459) +2022-11-14 14:06:42,206 Epoch: [148][370/500] Time 0.032 (0.029) Data 0.002 (0.002) Loss 0.0460 (0.0540) Prec@1 93.000 (90.895) Prec@5 98.000 (99.421) +2022-11-14 14:06:42,537 Epoch: [148][380/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0628 (0.0542) Prec@1 89.000 (90.846) Prec@5 98.000 (99.385) +2022-11-14 14:06:42,870 Epoch: [148][390/500] Time 0.029 (0.029) Data 0.002 (0.002) Loss 0.0531 (0.0542) Prec@1 89.000 (90.800) Prec@5 100.000 (99.400) +2022-11-14 14:06:43,200 Epoch: [148][400/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0311 (0.0537) Prec@1 97.000 (90.951) Prec@5 99.000 (99.390) +2022-11-14 14:06:43,526 Epoch: [148][410/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0503 (0.0536) Prec@1 89.000 (90.905) Prec@5 100.000 (99.405) +2022-11-14 14:06:43,858 Epoch: [148][420/500] Time 0.031 (0.029) Data 0.002 (0.002) Loss 0.0597 (0.0537) Prec@1 89.000 (90.860) Prec@5 100.000 (99.419) +2022-11-14 14:06:44,345 Epoch: [148][430/500] Time 0.079 (0.029) Data 0.002 (0.002) Loss 0.0741 (0.0542) Prec@1 87.000 (90.773) Prec@5 98.000 (99.386) +2022-11-14 14:06:44,898 Epoch: [148][440/500] Time 0.045 (0.029) Data 0.002 (0.002) Loss 0.0430 (0.0539) Prec@1 95.000 (90.867) Prec@5 100.000 (99.400) +2022-11-14 14:06:45,360 Epoch: [148][450/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0640 (0.0541) Prec@1 87.000 (90.783) Prec@5 100.000 (99.413) +2022-11-14 14:06:45,823 Epoch: [148][460/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0618 (0.0543) Prec@1 89.000 (90.745) Prec@5 99.000 (99.404) +2022-11-14 14:06:46,286 Epoch: [148][470/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0439 (0.0541) Prec@1 93.000 (90.792) Prec@5 100.000 (99.417) +2022-11-14 14:06:46,751 Epoch: [148][480/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0528 (0.0541) Prec@1 93.000 (90.837) Prec@5 98.000 (99.388) +2022-11-14 14:06:47,213 Epoch: [148][490/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0288 (0.0536) Prec@1 95.000 (90.920) Prec@5 100.000 (99.400) +2022-11-14 14:06:47,628 Epoch: [148][499/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0521 (0.0535) Prec@1 91.000 (90.922) Prec@5 100.000 (99.412) +2022-11-14 14:06:47,910 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0545 (0.0545) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:06:47,918 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0947 (0.0746) Prec@1 82.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 14:06:47,929 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0795) Prec@1 83.000 (85.667) Prec@5 100.000 (99.667) +2022-11-14 14:06:47,941 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0778) Prec@1 87.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 14:06:47,950 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0794) Prec@1 83.000 (85.400) Prec@5 100.000 (99.600) +2022-11-14 14:06:47,959 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0745) Prec@1 91.000 (86.333) Prec@5 99.000 (99.500) +2022-11-14 14:06:47,968 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0732) Prec@1 88.000 (86.571) Prec@5 100.000 (99.571) +2022-11-14 14:06:47,980 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0776) Prec@1 81.000 (85.875) Prec@5 98.000 (99.375) +2022-11-14 14:06:47,991 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0795) Prec@1 84.000 (85.667) Prec@5 99.000 (99.333) +2022-11-14 14:06:48,001 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0783) Prec@1 88.000 (85.900) Prec@5 98.000 (99.200) +2022-11-14 14:06:48,014 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0790) Prec@1 85.000 (85.818) Prec@5 100.000 (99.273) +2022-11-14 14:06:48,027 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0810) Prec@1 82.000 (85.500) Prec@5 99.000 (99.250) +2022-11-14 14:06:48,039 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0796) Prec@1 91.000 (85.923) Prec@5 100.000 (99.308) +2022-11-14 14:06:48,050 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0810) Prec@1 82.000 (85.643) Prec@5 100.000 (99.357) +2022-11-14 14:06:48,065 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0811) Prec@1 85.000 (85.600) Prec@5 100.000 (99.400) +2022-11-14 14:06:48,079 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0815) Prec@1 87.000 (85.688) Prec@5 100.000 (99.438) +2022-11-14 14:06:48,089 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0803) Prec@1 89.000 (85.882) Prec@5 98.000 (99.353) +2022-11-14 14:06:48,101 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0814) Prec@1 84.000 (85.778) Prec@5 100.000 (99.389) +2022-11-14 14:06:48,116 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0807) Prec@1 89.000 (85.947) Prec@5 98.000 (99.316) +2022-11-14 14:06:48,132 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0815) Prec@1 83.000 (85.800) Prec@5 99.000 (99.300) +2022-11-14 14:06:48,147 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0813) Prec@1 87.000 (85.857) Prec@5 99.000 (99.286) +2022-11-14 14:06:48,163 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0814) Prec@1 85.000 (85.818) Prec@5 98.000 (99.227) +2022-11-14 14:06:48,178 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0830) Prec@1 84.000 (85.739) Prec@5 100.000 (99.261) +2022-11-14 14:06:48,193 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0824) Prec@1 89.000 (85.875) Prec@5 100.000 (99.292) +2022-11-14 14:06:48,207 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0823) Prec@1 86.000 (85.880) Prec@5 100.000 (99.320) +2022-11-14 14:06:48,221 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0829) Prec@1 84.000 (85.808) Prec@5 98.000 (99.269) +2022-11-14 14:06:48,235 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0821) Prec@1 90.000 (85.963) Prec@5 100.000 (99.296) +2022-11-14 14:06:48,251 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0823) Prec@1 85.000 (85.929) Prec@5 100.000 (99.321) +2022-11-14 14:06:48,266 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0818) Prec@1 88.000 (86.000) Prec@5 99.000 (99.310) +2022-11-14 14:06:48,280 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0815) Prec@1 87.000 (86.033) Prec@5 99.000 (99.300) +2022-11-14 14:06:48,295 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0813) Prec@1 85.000 (86.000) Prec@5 100.000 (99.323) +2022-11-14 14:06:48,309 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0814) Prec@1 88.000 (86.062) Prec@5 100.000 (99.344) +2022-11-14 14:06:48,324 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0815) Prec@1 85.000 (86.030) Prec@5 97.000 (99.273) +2022-11-14 14:06:48,339 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0818) Prec@1 84.000 (85.971) Prec@5 100.000 (99.294) +2022-11-14 14:06:48,353 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0813) Prec@1 89.000 (86.057) Prec@5 99.000 (99.286) +2022-11-14 14:06:48,369 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0810) Prec@1 87.000 (86.083) Prec@5 100.000 (99.306) +2022-11-14 14:06:48,382 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0813) Prec@1 86.000 (86.081) Prec@5 99.000 (99.297) +2022-11-14 14:06:48,397 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0816) Prec@1 85.000 (86.053) Prec@5 99.000 (99.289) +2022-11-14 14:06:48,412 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0811) Prec@1 91.000 (86.179) Prec@5 100.000 (99.308) +2022-11-14 14:06:48,425 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0811) Prec@1 83.000 (86.100) Prec@5 100.000 (99.325) +2022-11-14 14:06:48,437 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0818) Prec@1 83.000 (86.024) Prec@5 98.000 (99.293) +2022-11-14 14:06:48,449 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0818) Prec@1 88.000 (86.071) Prec@5 98.000 (99.262) +2022-11-14 14:06:48,463 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0811) Prec@1 90.000 (86.163) Prec@5 100.000 (99.279) +2022-11-14 14:06:48,478 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0812) Prec@1 85.000 (86.136) Prec@5 99.000 (99.273) +2022-11-14 14:06:48,492 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0809) Prec@1 88.000 (86.178) Prec@5 100.000 (99.289) +2022-11-14 14:06:48,507 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0810) Prec@1 87.000 (86.196) Prec@5 98.000 (99.261) +2022-11-14 14:06:48,522 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0813) Prec@1 84.000 (86.149) Prec@5 100.000 (99.277) +2022-11-14 14:06:48,535 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0816) Prec@1 85.000 (86.125) Prec@5 99.000 (99.271) +2022-11-14 14:06:48,547 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0810) Prec@1 92.000 (86.245) Prec@5 100.000 (99.286) +2022-11-14 14:06:48,560 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1117 (0.0816) Prec@1 80.000 (86.120) Prec@5 99.000 (99.280) +2022-11-14 14:06:48,575 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0813) Prec@1 90.000 (86.196) Prec@5 100.000 (99.294) +2022-11-14 14:06:48,590 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0814) Prec@1 83.000 (86.135) Prec@5 99.000 (99.288) +2022-11-14 14:06:48,606 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0812) Prec@1 91.000 (86.226) Prec@5 100.000 (99.302) +2022-11-14 14:06:48,620 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0810) Prec@1 88.000 (86.259) Prec@5 100.000 (99.315) +2022-11-14 14:06:48,633 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0813) Prec@1 83.000 (86.200) Prec@5 100.000 (99.327) +2022-11-14 14:06:48,647 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0814) Prec@1 86.000 (86.196) Prec@5 99.000 (99.321) +2022-11-14 14:06:48,661 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0810) Prec@1 92.000 (86.298) Prec@5 100.000 (99.333) +2022-11-14 14:06:48,677 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0809) Prec@1 86.000 (86.293) Prec@5 99.000 (99.328) +2022-11-14 14:06:48,691 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0812) Prec@1 84.000 (86.254) Prec@5 100.000 (99.339) +2022-11-14 14:06:48,706 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0813) Prec@1 85.000 (86.233) Prec@5 100.000 (99.350) +2022-11-14 14:06:48,721 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0816) Prec@1 84.000 (86.197) Prec@5 99.000 (99.344) +2022-11-14 14:06:48,736 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0815) Prec@1 88.000 (86.226) Prec@5 100.000 (99.355) +2022-11-14 14:06:48,750 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0811) Prec@1 91.000 (86.302) Prec@5 100.000 (99.365) +2022-11-14 14:06:48,765 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0807) Prec@1 92.000 (86.391) Prec@5 100.000 (99.375) +2022-11-14 14:06:48,781 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1093 (0.0811) Prec@1 81.000 (86.308) Prec@5 99.000 (99.369) +2022-11-14 14:06:48,795 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0811) Prec@1 85.000 (86.288) Prec@5 99.000 (99.364) +2022-11-14 14:06:48,809 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0810) Prec@1 88.000 (86.313) Prec@5 99.000 (99.358) +2022-11-14 14:06:48,824 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0809) Prec@1 89.000 (86.353) Prec@5 99.000 (99.353) +2022-11-14 14:06:48,838 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0805) Prec@1 92.000 (86.435) Prec@5 100.000 (99.362) +2022-11-14 14:06:48,853 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0806) Prec@1 84.000 (86.400) Prec@5 99.000 (99.357) +2022-11-14 14:06:48,869 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0809) Prec@1 80.000 (86.310) Prec@5 99.000 (99.352) +2022-11-14 14:06:48,883 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0807) Prec@1 89.000 (86.347) Prec@5 100.000 (99.361) +2022-11-14 14:06:48,896 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0806) Prec@1 88.000 (86.370) Prec@5 100.000 (99.370) +2022-11-14 14:06:48,909 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0804) Prec@1 91.000 (86.432) Prec@5 100.000 (99.378) +2022-11-14 14:06:48,925 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0805) Prec@1 83.000 (86.387) Prec@5 100.000 (99.387) +2022-11-14 14:06:48,939 Test: [75/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0803) Prec@1 88.000 (86.408) Prec@5 98.000 (99.368) +2022-11-14 14:06:48,953 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0802) Prec@1 87.000 (86.416) Prec@5 99.000 (99.364) +2022-11-14 14:06:48,968 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0803) Prec@1 84.000 (86.385) Prec@5 99.000 (99.359) +2022-11-14 14:06:48,982 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0800) Prec@1 88.000 (86.405) Prec@5 100.000 (99.367) +2022-11-14 14:06:48,996 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0801) Prec@1 82.000 (86.350) Prec@5 99.000 (99.362) +2022-11-14 14:06:49,010 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0802) Prec@1 84.000 (86.321) Prec@5 99.000 (99.358) +2022-11-14 14:06:49,024 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0802) Prec@1 89.000 (86.354) Prec@5 100.000 (99.366) +2022-11-14 14:06:49,039 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0802) Prec@1 87.000 (86.361) Prec@5 100.000 (99.373) +2022-11-14 14:06:49,053 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0801) Prec@1 88.000 (86.381) Prec@5 100.000 (99.381) +2022-11-14 14:06:49,069 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0800) Prec@1 87.000 (86.388) Prec@5 100.000 (99.388) +2022-11-14 14:06:49,085 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0802) Prec@1 83.000 (86.349) Prec@5 100.000 (99.395) +2022-11-14 14:06:49,100 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0800) Prec@1 89.000 (86.379) Prec@5 100.000 (99.402) +2022-11-14 14:06:49,116 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0799) Prec@1 88.000 (86.398) Prec@5 99.000 (99.398) +2022-11-14 14:06:49,132 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0799) Prec@1 82.000 (86.348) Prec@5 100.000 (99.404) +2022-11-14 14:06:49,148 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0798) Prec@1 88.000 (86.367) Prec@5 100.000 (99.411) +2022-11-14 14:06:49,163 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0797) Prec@1 89.000 (86.396) Prec@5 100.000 (99.418) +2022-11-14 14:06:49,176 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0796) Prec@1 89.000 (86.424) Prec@5 99.000 (99.413) +2022-11-14 14:06:49,190 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0795) Prec@1 89.000 (86.452) Prec@5 100.000 (99.419) +2022-11-14 14:06:49,206 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0793) Prec@1 92.000 (86.511) Prec@5 99.000 (99.415) +2022-11-14 14:06:49,221 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0794) Prec@1 83.000 (86.474) Prec@5 100.000 (99.421) +2022-11-14 14:06:49,236 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0793) Prec@1 88.000 (86.490) Prec@5 99.000 (99.417) +2022-11-14 14:06:49,251 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0397 (0.0789) Prec@1 93.000 (86.557) Prec@5 100.000 (99.423) +2022-11-14 14:06:49,266 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.0793) Prec@1 80.000 (86.490) Prec@5 97.000 (99.398) +2022-11-14 14:06:49,281 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0794) Prec@1 86.000 (86.485) Prec@5 99.000 (99.394) +2022-11-14 14:06:49,295 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0793) Prec@1 89.000 (86.510) Prec@5 99.000 (99.390) +2022-11-14 14:06:49,348 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:06:49,655 Epoch: [149][0/500] Time 0.030 (0.030) Data 0.220 (0.220) Loss 0.0615 (0.0615) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:06:49,872 Epoch: [149][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.0349 (0.0482) Prec@1 94.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:06:50,071 Epoch: [149][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0312 (0.0425) Prec@1 95.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:06:50,303 Epoch: [149][30/500] Time 0.021 (0.019) Data 0.001 (0.009) Loss 0.0514 (0.0447) Prec@1 92.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:06:50,545 Epoch: [149][40/500] Time 0.023 (0.020) Data 0.001 (0.007) Loss 0.0664 (0.0490) Prec@1 89.000 (91.800) Prec@5 100.000 (99.600) +2022-11-14 14:06:50,809 Epoch: [149][50/500] Time 0.033 (0.020) Data 0.002 (0.006) Loss 0.0442 (0.0482) Prec@1 93.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:06:51,164 Epoch: [149][60/500] Time 0.035 (0.022) Data 0.002 (0.005) Loss 0.0429 (0.0475) Prec@1 93.000 (92.143) Prec@5 100.000 (99.714) +2022-11-14 14:06:51,527 Epoch: [149][70/500] Time 0.035 (0.024) Data 0.001 (0.005) Loss 0.0808 (0.0516) Prec@1 85.000 (91.250) Prec@5 99.000 (99.625) +2022-11-14 14:06:51,882 Epoch: [149][80/500] Time 0.034 (0.025) Data 0.002 (0.004) Loss 0.0333 (0.0496) Prec@1 96.000 (91.778) Prec@5 100.000 (99.667) +2022-11-14 14:06:52,241 Epoch: [149][90/500] Time 0.035 (0.025) Data 0.002 (0.004) Loss 0.0712 (0.0518) Prec@1 88.000 (91.400) Prec@5 100.000 (99.700) +2022-11-14 14:06:52,602 Epoch: [149][100/500] Time 0.033 (0.026) Data 0.002 (0.004) Loss 0.0414 (0.0508) Prec@1 92.000 (91.455) Prec@5 99.000 (99.636) +2022-11-14 14:06:52,964 Epoch: [149][110/500] Time 0.035 (0.027) Data 0.002 (0.004) Loss 0.0580 (0.0514) Prec@1 90.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:06:53,323 Epoch: [149][120/500] Time 0.032 (0.027) Data 0.002 (0.004) Loss 0.0384 (0.0504) Prec@1 95.000 (91.615) Prec@5 100.000 (99.692) +2022-11-14 14:06:53,679 Epoch: [149][130/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0604 (0.0511) Prec@1 91.000 (91.571) Prec@5 100.000 (99.714) +2022-11-14 14:06:54,038 Epoch: [149][140/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0420 (0.0505) Prec@1 94.000 (91.733) Prec@5 99.000 (99.667) +2022-11-14 14:06:54,404 Epoch: [149][150/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.0475 (0.0503) Prec@1 93.000 (91.812) Prec@5 100.000 (99.688) +2022-11-14 14:06:54,762 Epoch: [149][160/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0556 (0.0507) Prec@1 90.000 (91.706) Prec@5 100.000 (99.706) +2022-11-14 14:06:55,127 Epoch: [149][170/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0461 (0.0504) Prec@1 91.000 (91.667) Prec@5 100.000 (99.722) +2022-11-14 14:06:55,484 Epoch: [149][180/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0506 (0.0504) Prec@1 92.000 (91.684) Prec@5 99.000 (99.684) +2022-11-14 14:06:55,836 Epoch: [149][190/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0817 (0.0520) Prec@1 89.000 (91.550) Prec@5 100.000 (99.700) +2022-11-14 14:06:56,197 Epoch: [149][200/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0559 (0.0522) Prec@1 90.000 (91.476) Prec@5 99.000 (99.667) +2022-11-14 14:06:56,564 Epoch: [149][210/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0476 (0.0520) Prec@1 91.000 (91.455) Prec@5 99.000 (99.636) +2022-11-14 14:06:56,920 Epoch: [149][220/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0341 (0.0512) Prec@1 94.000 (91.565) Prec@5 100.000 (99.652) +2022-11-14 14:06:57,279 Epoch: [149][230/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0548 (0.0513) Prec@1 90.000 (91.500) Prec@5 100.000 (99.667) +2022-11-14 14:06:57,645 Epoch: [149][240/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0533 (0.0514) Prec@1 92.000 (91.520) Prec@5 100.000 (99.680) +2022-11-14 14:06:58,002 Epoch: [149][250/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0372 (0.0509) Prec@1 93.000 (91.577) Prec@5 100.000 (99.692) +2022-11-14 14:06:58,364 Epoch: [149][260/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0345 (0.0503) Prec@1 93.000 (91.630) Prec@5 100.000 (99.704) +2022-11-14 14:06:58,721 Epoch: [149][270/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0553 (0.0504) Prec@1 91.000 (91.607) Prec@5 100.000 (99.714) +2022-11-14 14:06:59,077 Epoch: [149][280/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0606 (0.0508) Prec@1 88.000 (91.483) Prec@5 100.000 (99.724) +2022-11-14 14:06:59,444 Epoch: [149][290/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0465 (0.0506) Prec@1 95.000 (91.600) Prec@5 100.000 (99.733) +2022-11-14 14:06:59,812 Epoch: [149][300/500] Time 0.035 (0.030) Data 0.003 (0.003) Loss 0.0501 (0.0506) Prec@1 91.000 (91.581) Prec@5 99.000 (99.710) +2022-11-14 14:07:00,177 Epoch: [149][310/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0404 (0.0503) Prec@1 95.000 (91.688) Prec@5 99.000 (99.688) +2022-11-14 14:07:00,540 Epoch: [149][320/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0692 (0.0509) Prec@1 89.000 (91.606) Prec@5 97.000 (99.606) +2022-11-14 14:07:00,905 Epoch: [149][330/500] Time 0.035 (0.030) Data 0.002 (0.002) Loss 0.0516 (0.0509) Prec@1 93.000 (91.647) Prec@5 100.000 (99.618) +2022-11-14 14:07:01,265 Epoch: [149][340/500] Time 0.035 (0.030) Data 0.001 (0.002) Loss 0.0594 (0.0511) Prec@1 91.000 (91.629) Prec@5 97.000 (99.543) +2022-11-14 14:07:01,629 Epoch: [149][350/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.0600 (0.0514) Prec@1 89.000 (91.556) Prec@5 99.000 (99.528) +2022-11-14 14:07:01,992 Epoch: [149][360/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0318 (0.0509) Prec@1 95.000 (91.649) Prec@5 100.000 (99.541) +2022-11-14 14:07:02,354 Epoch: [149][370/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.0449 (0.0507) Prec@1 92.000 (91.658) Prec@5 100.000 (99.553) +2022-11-14 14:07:02,714 Epoch: [149][380/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0438 (0.0505) Prec@1 93.000 (91.692) Prec@5 100.000 (99.564) +2022-11-14 14:07:03,075 Epoch: [149][390/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0659 (0.0509) Prec@1 89.000 (91.625) Prec@5 99.000 (99.550) +2022-11-14 14:07:03,437 Epoch: [149][400/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0471 (0.0508) Prec@1 91.000 (91.610) Prec@5 99.000 (99.537) +2022-11-14 14:07:03,803 Epoch: [149][410/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0678 (0.0512) Prec@1 88.000 (91.524) Prec@5 99.000 (99.524) +2022-11-14 14:07:04,168 Epoch: [149][420/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0634 (0.0515) Prec@1 91.000 (91.512) Prec@5 100.000 (99.535) +2022-11-14 14:07:04,530 Epoch: [149][430/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0559 (0.0516) Prec@1 91.000 (91.500) Prec@5 99.000 (99.523) +2022-11-14 14:07:04,891 Epoch: [149][440/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0509 (0.0516) Prec@1 92.000 (91.511) Prec@5 99.000 (99.511) +2022-11-14 14:07:05,249 Epoch: [149][450/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0636 (0.0519) Prec@1 89.000 (91.457) Prec@5 100.000 (99.522) +2022-11-14 14:07:05,611 Epoch: [149][460/500] Time 0.032 (0.031) Data 0.003 (0.002) Loss 0.0489 (0.0518) Prec@1 92.000 (91.468) Prec@5 100.000 (99.532) +2022-11-14 14:07:05,971 Epoch: [149][470/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0689 (0.0521) Prec@1 88.000 (91.396) Prec@5 100.000 (99.542) +2022-11-14 14:07:06,334 Epoch: [149][480/500] Time 0.031 (0.031) Data 0.002 (0.002) Loss 0.0730 (0.0526) Prec@1 87.000 (91.306) Prec@5 99.000 (99.531) +2022-11-14 14:07:06,693 Epoch: [149][490/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0491 (0.0525) Prec@1 92.000 (91.320) Prec@5 100.000 (99.540) +2022-11-14 14:07:07,017 Epoch: [149][499/500] Time 0.034 (0.031) Data 0.002 (0.002) Loss 0.0622 (0.0527) Prec@1 89.000 (91.275) Prec@5 99.000 (99.529) +2022-11-14 14:07:07,293 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0575) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:07,300 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0604) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:07,313 Test: [2/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0686) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:07,324 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0722) Prec@1 85.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 14:07:07,333 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0737) Prec@1 87.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 14:07:07,342 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0726) Prec@1 89.000 (87.500) Prec@5 98.000 (99.333) +2022-11-14 14:07:07,352 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0736) Prec@1 87.000 (87.429) Prec@5 100.000 (99.429) +2022-11-14 14:07:07,363 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.0774) Prec@1 81.000 (86.625) Prec@5 96.000 (99.000) +2022-11-14 14:07:07,370 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0759) Prec@1 89.000 (86.889) Prec@5 99.000 (99.000) +2022-11-14 14:07:07,379 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0747) Prec@1 89.000 (87.100) Prec@5 99.000 (99.000) +2022-11-14 14:07:07,390 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0745) Prec@1 87.000 (87.091) Prec@5 100.000 (99.091) +2022-11-14 14:07:07,400 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0757) Prec@1 84.000 (86.833) Prec@5 100.000 (99.167) +2022-11-14 14:07:07,410 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0746) Prec@1 86.000 (86.769) Prec@5 100.000 (99.231) +2022-11-14 14:07:07,419 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0739) Prec@1 89.000 (86.929) Prec@5 99.000 (99.214) +2022-11-14 14:07:07,430 Test: [14/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0741) Prec@1 87.000 (86.933) Prec@5 100.000 (99.267) +2022-11-14 14:07:07,441 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0746) Prec@1 87.000 (86.938) Prec@5 100.000 (99.312) +2022-11-14 14:07:07,450 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0731) Prec@1 93.000 (87.294) Prec@5 99.000 (99.294) +2022-11-14 14:07:07,460 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0745) Prec@1 84.000 (87.111) Prec@5 100.000 (99.333) +2022-11-14 14:07:07,469 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0752) Prec@1 85.000 (87.000) Prec@5 99.000 (99.316) +2022-11-14 14:07:07,477 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0758) Prec@1 83.000 (86.800) Prec@5 97.000 (99.200) +2022-11-14 14:07:07,487 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0769) Prec@1 83.000 (86.619) Prec@5 99.000 (99.190) +2022-11-14 14:07:07,495 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0777) Prec@1 81.000 (86.364) Prec@5 98.000 (99.136) +2022-11-14 14:07:07,504 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0784) Prec@1 85.000 (86.304) Prec@5 98.000 (99.087) +2022-11-14 14:07:07,514 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0778) Prec@1 89.000 (86.417) Prec@5 100.000 (99.125) +2022-11-14 14:07:07,523 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0780) Prec@1 89.000 (86.520) Prec@5 100.000 (99.160) +2022-11-14 14:07:07,531 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0790) Prec@1 80.000 (86.269) Prec@5 96.000 (99.038) +2022-11-14 14:07:07,541 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0779) Prec@1 93.000 (86.519) Prec@5 99.000 (99.037) +2022-11-14 14:07:07,549 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0777) Prec@1 87.000 (86.536) Prec@5 100.000 (99.071) +2022-11-14 14:07:07,557 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0781) Prec@1 84.000 (86.448) Prec@5 98.000 (99.034) +2022-11-14 14:07:07,566 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0779) Prec@1 87.000 (86.467) Prec@5 100.000 (99.067) +2022-11-14 14:07:07,576 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0776) Prec@1 90.000 (86.581) Prec@5 100.000 (99.097) +2022-11-14 14:07:07,585 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0773) Prec@1 89.000 (86.656) Prec@5 99.000 (99.094) +2022-11-14 14:07:07,594 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0770) Prec@1 89.000 (86.727) Prec@5 99.000 (99.091) +2022-11-14 14:07:07,604 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0770) Prec@1 85.000 (86.676) Prec@5 100.000 (99.118) +2022-11-14 14:07:07,613 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0775) Prec@1 84.000 (86.600) Prec@5 99.000 (99.114) +2022-11-14 14:07:07,622 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0774) Prec@1 88.000 (86.639) Prec@5 99.000 (99.111) +2022-11-14 14:07:07,632 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0776) Prec@1 87.000 (86.649) Prec@5 98.000 (99.081) +2022-11-14 14:07:07,641 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.0787) Prec@1 76.000 (86.368) Prec@5 99.000 (99.079) +2022-11-14 14:07:07,650 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0784) Prec@1 87.000 (86.385) Prec@5 100.000 (99.103) +2022-11-14 14:07:07,660 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0786) Prec@1 85.000 (86.350) Prec@5 100.000 (99.125) +2022-11-14 14:07:07,669 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0787) Prec@1 85.000 (86.317) Prec@5 99.000 (99.122) +2022-11-14 14:07:07,678 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0787) Prec@1 88.000 (86.357) Prec@5 98.000 (99.095) +2022-11-14 14:07:07,687 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0783) Prec@1 89.000 (86.419) Prec@5 100.000 (99.116) +2022-11-14 14:07:07,697 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0779) Prec@1 90.000 (86.500) Prec@5 99.000 (99.114) +2022-11-14 14:07:07,706 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0779) Prec@1 86.000 (86.489) Prec@5 99.000 (99.111) +2022-11-14 14:07:07,715 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0784) Prec@1 80.000 (86.348) Prec@5 99.000 (99.109) +2022-11-14 14:07:07,724 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0783) Prec@1 86.000 (86.340) Prec@5 100.000 (99.128) +2022-11-14 14:07:07,733 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0789) Prec@1 82.000 (86.250) Prec@5 99.000 (99.125) +2022-11-14 14:07:07,743 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0784) Prec@1 92.000 (86.367) Prec@5 100.000 (99.143) +2022-11-14 14:07:07,752 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.0791) Prec@1 81.000 (86.260) Prec@5 99.000 (99.140) +2022-11-14 14:07:07,761 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0788) Prec@1 89.000 (86.314) Prec@5 100.000 (99.157) +2022-11-14 14:07:07,770 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0789) Prec@1 85.000 (86.288) Prec@5 99.000 (99.154) +2022-11-14 14:07:07,780 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0788) Prec@1 88.000 (86.321) Prec@5 99.000 (99.151) +2022-11-14 14:07:07,788 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0788) Prec@1 86.000 (86.315) Prec@5 99.000 (99.148) +2022-11-14 14:07:07,798 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0791) Prec@1 84.000 (86.273) Prec@5 100.000 (99.164) +2022-11-14 14:07:07,807 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0792) Prec@1 86.000 (86.268) Prec@5 99.000 (99.161) +2022-11-14 14:07:07,816 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0791) Prec@1 88.000 (86.298) Prec@5 100.000 (99.175) +2022-11-14 14:07:07,824 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0787) Prec@1 92.000 (86.397) Prec@5 100.000 (99.190) +2022-11-14 14:07:07,833 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0788) Prec@1 85.000 (86.373) Prec@5 100.000 (99.203) +2022-11-14 14:07:07,842 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0790) Prec@1 83.000 (86.317) Prec@5 99.000 (99.200) +2022-11-14 14:07:07,851 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0790) Prec@1 89.000 (86.361) Prec@5 99.000 (99.197) +2022-11-14 14:07:07,860 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0788) Prec@1 88.000 (86.387) Prec@5 99.000 (99.194) +2022-11-14 14:07:07,870 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0786) Prec@1 90.000 (86.444) Prec@5 100.000 (99.206) +2022-11-14 14:07:07,879 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0312 (0.0778) Prec@1 95.000 (86.578) Prec@5 99.000 (99.203) +2022-11-14 14:07:07,888 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0780) Prec@1 86.000 (86.569) Prec@5 98.000 (99.185) +2022-11-14 14:07:07,898 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0781) Prec@1 87.000 (86.576) Prec@5 98.000 (99.167) +2022-11-14 14:07:07,907 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0778) Prec@1 91.000 (86.642) Prec@5 100.000 (99.179) +2022-11-14 14:07:07,916 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0779) Prec@1 87.000 (86.647) Prec@5 98.000 (99.162) +2022-11-14 14:07:07,926 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0780) Prec@1 83.000 (86.594) Prec@5 100.000 (99.174) +2022-11-14 14:07:07,935 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0781) Prec@1 87.000 (86.600) Prec@5 100.000 (99.186) +2022-11-14 14:07:07,944 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0783) Prec@1 86.000 (86.592) Prec@5 100.000 (99.197) +2022-11-14 14:07:07,953 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0781) Prec@1 91.000 (86.653) Prec@5 100.000 (99.208) +2022-11-14 14:07:07,962 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0778) Prec@1 92.000 (86.726) Prec@5 100.000 (99.219) +2022-11-14 14:07:07,970 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0774) Prec@1 92.000 (86.797) Prec@5 100.000 (99.230) +2022-11-14 14:07:07,980 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.0779) Prec@1 79.000 (86.693) Prec@5 98.000 (99.213) +2022-11-14 14:07:07,988 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0777) Prec@1 88.000 (86.711) Prec@5 100.000 (99.224) +2022-11-14 14:07:07,997 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0777) Prec@1 88.000 (86.727) Prec@5 98.000 (99.208) +2022-11-14 14:07:08,005 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0777) Prec@1 86.000 (86.718) Prec@5 99.000 (99.205) +2022-11-14 14:07:08,015 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0780) Prec@1 85.000 (86.696) Prec@5 100.000 (99.215) +2022-11-14 14:07:08,024 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0780) Prec@1 87.000 (86.700) Prec@5 99.000 (99.213) +2022-11-14 14:07:08,033 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0780) Prec@1 88.000 (86.716) Prec@5 100.000 (99.222) +2022-11-14 14:07:08,043 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0779) Prec@1 87.000 (86.720) Prec@5 100.000 (99.232) +2022-11-14 14:07:08,051 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0782) Prec@1 83.000 (86.675) Prec@5 100.000 (99.241) +2022-11-14 14:07:08,059 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0780) Prec@1 88.000 (86.690) Prec@5 100.000 (99.250) +2022-11-14 14:07:08,069 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0780) Prec@1 87.000 (86.694) Prec@5 100.000 (99.259) +2022-11-14 14:07:08,079 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0784) Prec@1 82.000 (86.640) Prec@5 100.000 (99.267) +2022-11-14 14:07:08,088 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0782) Prec@1 90.000 (86.678) Prec@5 100.000 (99.276) +2022-11-14 14:07:08,098 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0781) Prec@1 89.000 (86.705) Prec@5 100.000 (99.284) +2022-11-14 14:07:08,106 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0781) Prec@1 85.000 (86.685) Prec@5 98.000 (99.270) +2022-11-14 14:07:08,115 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0780) Prec@1 90.000 (86.722) Prec@5 100.000 (99.278) +2022-11-14 14:07:08,124 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0777) Prec@1 91.000 (86.769) Prec@5 100.000 (99.286) +2022-11-14 14:07:08,137 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0372 (0.0772) Prec@1 94.000 (86.848) Prec@5 100.000 (99.293) +2022-11-14 14:07:08,149 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0774) Prec@1 84.000 (86.817) Prec@5 99.000 (99.290) +2022-11-14 14:07:08,161 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0772) Prec@1 91.000 (86.862) Prec@5 99.000 (99.287) +2022-11-14 14:07:08,172 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0773) Prec@1 86.000 (86.853) Prec@5 99.000 (99.284) +2022-11-14 14:07:08,186 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0774) Prec@1 87.000 (86.854) Prec@5 98.000 (99.271) +2022-11-14 14:07:08,201 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0453 (0.0770) Prec@1 94.000 (86.928) Prec@5 98.000 (99.258) +2022-11-14 14:07:08,216 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0772) Prec@1 85.000 (86.908) Prec@5 99.000 (99.255) +2022-11-14 14:07:08,230 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0774) Prec@1 81.000 (86.848) Prec@5 99.000 (99.253) +2022-11-14 14:07:08,246 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0773) Prec@1 91.000 (86.890) Prec@5 100.000 (99.260) +2022-11-14 14:07:08,305 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:07:08,627 Epoch: [150][0/500] Time 0.032 (0.032) Data 0.234 (0.234) Loss 0.0451 (0.0451) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:08,867 Epoch: [150][10/500] Time 0.023 (0.022) Data 0.002 (0.023) Loss 0.0361 (0.0406) Prec@1 96.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 14:07:09,137 Epoch: [150][20/500] Time 0.026 (0.023) Data 0.001 (0.013) Loss 0.0438 (0.0417) Prec@1 91.000 (93.000) Prec@5 98.000 (99.000) +2022-11-14 14:07:09,411 Epoch: [150][30/500] Time 0.025 (0.023) Data 0.002 (0.009) Loss 0.0449 (0.0425) Prec@1 91.000 (92.500) Prec@5 100.000 (99.250) +2022-11-14 14:07:09,682 Epoch: [150][40/500] Time 0.026 (0.023) Data 0.002 (0.007) Loss 0.0441 (0.0428) Prec@1 94.000 (92.800) Prec@5 100.000 (99.400) +2022-11-14 14:07:09,952 Epoch: [150][50/500] Time 0.026 (0.024) Data 0.001 (0.006) Loss 0.0332 (0.0412) Prec@1 94.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 14:07:10,387 Epoch: [150][60/500] Time 0.043 (0.026) Data 0.002 (0.005) Loss 0.0739 (0.0459) Prec@1 88.000 (92.286) Prec@5 99.000 (99.429) +2022-11-14 14:07:10,855 Epoch: [150][70/500] Time 0.044 (0.028) Data 0.002 (0.005) Loss 0.0950 (0.0520) Prec@1 83.000 (91.125) Prec@5 98.000 (99.250) +2022-11-14 14:07:11,314 Epoch: [150][80/500] Time 0.044 (0.030) Data 0.002 (0.005) Loss 0.0498 (0.0518) Prec@1 92.000 (91.222) Prec@5 100.000 (99.333) +2022-11-14 14:07:11,774 Epoch: [150][90/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0497 (0.0516) Prec@1 91.000 (91.200) Prec@5 100.000 (99.400) +2022-11-14 14:07:12,233 Epoch: [150][100/500] Time 0.041 (0.032) Data 0.002 (0.004) Loss 0.0500 (0.0514) Prec@1 92.000 (91.273) Prec@5 100.000 (99.455) +2022-11-14 14:07:12,701 Epoch: [150][110/500] Time 0.045 (0.033) Data 0.002 (0.004) Loss 0.0650 (0.0526) Prec@1 89.000 (91.083) Prec@5 98.000 (99.333) +2022-11-14 14:07:13,155 Epoch: [150][120/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0500 (0.0524) Prec@1 93.000 (91.231) Prec@5 100.000 (99.385) +2022-11-14 14:07:13,615 Epoch: [150][130/500] Time 0.045 (0.034) Data 0.002 (0.004) Loss 0.0353 (0.0511) Prec@1 93.000 (91.357) Prec@5 100.000 (99.429) +2022-11-14 14:07:14,069 Epoch: [150][140/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0533 (0.0513) Prec@1 92.000 (91.400) Prec@5 100.000 (99.467) +2022-11-14 14:07:14,527 Epoch: [150][150/500] Time 0.044 (0.035) Data 0.001 (0.003) Loss 0.0392 (0.0505) Prec@1 93.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:07:14,984 Epoch: [150][160/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0783 (0.0522) Prec@1 88.000 (91.294) Prec@5 98.000 (99.412) +2022-11-14 14:07:15,443 Epoch: [150][170/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0302 (0.0509) Prec@1 95.000 (91.500) Prec@5 100.000 (99.444) +2022-11-14 14:07:15,899 Epoch: [150][180/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0613 (0.0515) Prec@1 91.000 (91.474) Prec@5 99.000 (99.421) +2022-11-14 14:07:16,356 Epoch: [150][190/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0675 (0.0523) Prec@1 88.000 (91.300) Prec@5 100.000 (99.450) +2022-11-14 14:07:16,810 Epoch: [150][200/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0544 (0.0524) Prec@1 89.000 (91.190) Prec@5 100.000 (99.476) +2022-11-14 14:07:17,270 Epoch: [150][210/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0537 (0.0524) Prec@1 92.000 (91.227) Prec@5 100.000 (99.500) +2022-11-14 14:07:17,730 Epoch: [150][220/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0792 (0.0536) Prec@1 85.000 (90.957) Prec@5 98.000 (99.435) +2022-11-14 14:07:18,188 Epoch: [150][230/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0617 (0.0539) Prec@1 88.000 (90.833) Prec@5 100.000 (99.458) +2022-11-14 14:07:18,645 Epoch: [150][240/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0428 (0.0535) Prec@1 95.000 (91.000) Prec@5 100.000 (99.480) +2022-11-14 14:07:19,104 Epoch: [150][250/500] Time 0.044 (0.037) Data 0.001 (0.003) Loss 0.0477 (0.0533) Prec@1 91.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 14:07:19,559 Epoch: [150][260/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0663 (0.0538) Prec@1 90.000 (90.963) Prec@5 100.000 (99.519) +2022-11-14 14:07:20,010 Epoch: [150][270/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0460 (0.0535) Prec@1 90.000 (90.929) Prec@5 100.000 (99.536) +2022-11-14 14:07:20,469 Epoch: [150][280/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0399 (0.0530) Prec@1 93.000 (91.000) Prec@5 100.000 (99.552) +2022-11-14 14:07:20,925 Epoch: [150][290/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0386 (0.0525) Prec@1 93.000 (91.067) Prec@5 100.000 (99.567) +2022-11-14 14:07:21,380 Epoch: [150][300/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0699 (0.0531) Prec@1 85.000 (90.871) Prec@5 99.000 (99.548) +2022-11-14 14:07:21,833 Epoch: [150][310/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0228 (0.0522) Prec@1 97.000 (91.062) Prec@5 100.000 (99.562) +2022-11-14 14:07:22,287 Epoch: [150][320/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0647 (0.0525) Prec@1 89.000 (91.000) Prec@5 99.000 (99.545) +2022-11-14 14:07:22,737 Epoch: [150][330/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0280 (0.0518) Prec@1 95.000 (91.118) Prec@5 100.000 (99.559) +2022-11-14 14:07:23,191 Epoch: [150][340/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0419 (0.0515) Prec@1 93.000 (91.171) Prec@5 100.000 (99.571) +2022-11-14 14:07:23,641 Epoch: [150][350/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0408 (0.0512) Prec@1 94.000 (91.250) Prec@5 100.000 (99.583) +2022-11-14 14:07:24,091 Epoch: [150][360/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0571 (0.0514) Prec@1 92.000 (91.270) Prec@5 99.000 (99.568) +2022-11-14 14:07:24,537 Epoch: [150][370/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0535 (0.0514) Prec@1 92.000 (91.289) Prec@5 100.000 (99.579) +2022-11-14 14:07:24,992 Epoch: [150][380/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0474 (0.0513) Prec@1 90.000 (91.256) Prec@5 100.000 (99.590) +2022-11-14 14:07:25,338 Epoch: [150][390/500] Time 0.026 (0.038) Data 0.002 (0.002) Loss 0.0704 (0.0518) Prec@1 89.000 (91.200) Prec@5 100.000 (99.600) +2022-11-14 14:07:25,618 Epoch: [150][400/500] Time 0.024 (0.038) Data 0.002 (0.002) Loss 0.0639 (0.0521) Prec@1 89.000 (91.146) Prec@5 99.000 (99.585) +2022-11-14 14:07:25,895 Epoch: [150][410/500] Time 0.026 (0.037) Data 0.001 (0.002) Loss 0.0557 (0.0522) Prec@1 91.000 (91.143) Prec@5 98.000 (99.548) +2022-11-14 14:07:26,176 Epoch: [150][420/500] Time 0.026 (0.037) Data 0.002 (0.002) Loss 0.0441 (0.0520) Prec@1 91.000 (91.140) Prec@5 98.000 (99.512) +2022-11-14 14:07:26,454 Epoch: [150][430/500] Time 0.026 (0.037) Data 0.002 (0.002) Loss 0.0763 (0.0526) Prec@1 87.000 (91.045) Prec@5 100.000 (99.523) +2022-11-14 14:07:26,735 Epoch: [150][440/500] Time 0.026 (0.036) Data 0.001 (0.002) Loss 0.0438 (0.0524) Prec@1 92.000 (91.067) Prec@5 100.000 (99.533) +2022-11-14 14:07:27,018 Epoch: [150][450/500] Time 0.027 (0.036) Data 0.001 (0.002) Loss 0.0499 (0.0523) Prec@1 92.000 (91.087) Prec@5 100.000 (99.543) +2022-11-14 14:07:27,298 Epoch: [150][460/500] Time 0.026 (0.036) Data 0.002 (0.002) Loss 0.0488 (0.0522) Prec@1 91.000 (91.085) Prec@5 100.000 (99.553) +2022-11-14 14:07:27,581 Epoch: [150][470/500] Time 0.028 (0.036) Data 0.001 (0.002) Loss 0.0413 (0.0520) Prec@1 95.000 (91.167) Prec@5 100.000 (99.562) +2022-11-14 14:07:27,862 Epoch: [150][480/500] Time 0.024 (0.035) Data 0.002 (0.002) Loss 0.0394 (0.0518) Prec@1 94.000 (91.224) Prec@5 100.000 (99.571) +2022-11-14 14:07:28,144 Epoch: [150][490/500] Time 0.027 (0.035) Data 0.001 (0.002) Loss 0.0274 (0.0513) Prec@1 98.000 (91.360) Prec@5 100.000 (99.580) +2022-11-14 14:07:28,401 Epoch: [150][499/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0362 (0.0510) Prec@1 95.000 (91.431) Prec@5 100.000 (99.588) +2022-11-14 14:07:28,691 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0525 (0.0525) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:28,699 Test: [1/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0633 (0.0579) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:28,711 Test: [2/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0721) Prec@1 82.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:07:28,720 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0780) Prec@1 85.000 (86.250) Prec@5 99.000 (99.750) +2022-11-14 14:07:28,729 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0841) Prec@1 82.000 (85.400) Prec@5 100.000 (99.800) +2022-11-14 14:07:28,739 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0798) Prec@1 89.000 (86.000) Prec@5 100.000 (99.833) +2022-11-14 14:07:28,747 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0777) Prec@1 91.000 (86.714) Prec@5 100.000 (99.857) +2022-11-14 14:07:28,757 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0779) Prec@1 87.000 (86.750) Prec@5 100.000 (99.875) +2022-11-14 14:07:28,765 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0784) Prec@1 88.000 (86.889) Prec@5 100.000 (99.889) +2022-11-14 14:07:28,774 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0776) Prec@1 89.000 (87.100) Prec@5 98.000 (99.700) +2022-11-14 14:07:28,782 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0768) Prec@1 85.000 (86.909) Prec@5 100.000 (99.727) +2022-11-14 14:07:28,791 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0766) Prec@1 89.000 (87.083) Prec@5 98.000 (99.583) +2022-11-14 14:07:28,800 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0750) Prec@1 90.000 (87.308) Prec@5 100.000 (99.615) +2022-11-14 14:07:28,809 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0750) Prec@1 87.000 (87.286) Prec@5 99.000 (99.571) +2022-11-14 14:07:28,817 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0746) Prec@1 87.000 (87.267) Prec@5 100.000 (99.600) +2022-11-14 14:07:28,827 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0750) Prec@1 86.000 (87.188) Prec@5 99.000 (99.562) +2022-11-14 14:07:28,835 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0739) Prec@1 92.000 (87.471) Prec@5 98.000 (99.471) +2022-11-14 14:07:28,843 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0748) Prec@1 87.000 (87.444) Prec@5 100.000 (99.500) +2022-11-14 14:07:28,852 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0762) Prec@1 82.000 (87.158) Prec@5 99.000 (99.474) +2022-11-14 14:07:28,861 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0766) Prec@1 87.000 (87.150) Prec@5 98.000 (99.400) +2022-11-14 14:07:28,869 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0770) Prec@1 86.000 (87.095) Prec@5 98.000 (99.333) +2022-11-14 14:07:28,878 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0774) Prec@1 87.000 (87.091) Prec@5 98.000 (99.273) +2022-11-14 14:07:28,888 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0782) Prec@1 84.000 (86.957) Prec@5 97.000 (99.174) +2022-11-14 14:07:28,897 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0771) Prec@1 91.000 (87.125) Prec@5 99.000 (99.167) +2022-11-14 14:07:28,906 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0775) Prec@1 86.000 (87.080) Prec@5 100.000 (99.200) +2022-11-14 14:07:28,916 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1204 (0.0791) Prec@1 81.000 (86.846) Prec@5 99.000 (99.192) +2022-11-14 14:07:28,925 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0788) Prec@1 89.000 (86.926) Prec@5 100.000 (99.222) +2022-11-14 14:07:28,934 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0789) Prec@1 86.000 (86.893) Prec@5 99.000 (99.214) +2022-11-14 14:07:28,944 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0792) Prec@1 84.000 (86.793) Prec@5 100.000 (99.241) +2022-11-14 14:07:28,953 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0789) Prec@1 88.000 (86.833) Prec@5 100.000 (99.267) +2022-11-14 14:07:28,962 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0519 (0.0780) Prec@1 92.000 (87.000) Prec@5 100.000 (99.290) +2022-11-14 14:07:28,972 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0779) Prec@1 89.000 (87.062) Prec@5 97.000 (99.219) +2022-11-14 14:07:28,981 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0776) Prec@1 89.000 (87.121) Prec@5 99.000 (99.212) +2022-11-14 14:07:28,990 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0774) Prec@1 91.000 (87.235) Prec@5 100.000 (99.235) +2022-11-14 14:07:28,999 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0772) Prec@1 87.000 (87.229) Prec@5 100.000 (99.257) +2022-11-14 14:07:29,008 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0776) Prec@1 84.000 (87.139) Prec@5 100.000 (99.278) +2022-11-14 14:07:29,017 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0777) Prec@1 85.000 (87.081) Prec@5 98.000 (99.243) +2022-11-14 14:07:29,025 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0783) Prec@1 82.000 (86.947) Prec@5 99.000 (99.237) +2022-11-14 14:07:29,035 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0781) Prec@1 88.000 (86.974) Prec@5 99.000 (99.231) +2022-11-14 14:07:29,043 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0782) Prec@1 87.000 (86.975) Prec@5 99.000 (99.225) +2022-11-14 14:07:29,052 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0781) Prec@1 89.000 (87.024) Prec@5 97.000 (99.171) +2022-11-14 14:07:29,061 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0783) Prec@1 86.000 (87.000) Prec@5 99.000 (99.167) +2022-11-14 14:07:29,071 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0778) Prec@1 90.000 (87.070) Prec@5 99.000 (99.163) +2022-11-14 14:07:29,080 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0777) Prec@1 87.000 (87.068) Prec@5 100.000 (99.182) +2022-11-14 14:07:29,090 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0777) Prec@1 84.000 (87.000) Prec@5 99.000 (99.178) +2022-11-14 14:07:29,099 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0779) Prec@1 87.000 (87.000) Prec@5 100.000 (99.196) +2022-11-14 14:07:29,108 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0782) Prec@1 85.000 (86.957) Prec@5 100.000 (99.213) +2022-11-14 14:07:29,117 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1059 (0.0788) Prec@1 81.000 (86.833) Prec@5 100.000 (99.229) +2022-11-14 14:07:29,127 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0454 (0.0781) Prec@1 92.000 (86.939) Prec@5 100.000 (99.245) +2022-11-14 14:07:29,136 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1082 (0.0787) Prec@1 82.000 (86.840) Prec@5 100.000 (99.260) +2022-11-14 14:07:29,145 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0786) Prec@1 87.000 (86.843) Prec@5 100.000 (99.275) +2022-11-14 14:07:29,155 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0790) Prec@1 82.000 (86.750) Prec@5 98.000 (99.250) +2022-11-14 14:07:29,164 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0521 (0.0785) Prec@1 91.000 (86.830) Prec@5 100.000 (99.264) +2022-11-14 14:07:29,173 Test: 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Loss 0.0793 (0.0790) Prec@1 85.000 (86.667) Prec@5 100.000 (99.283) +2022-11-14 14:07:29,238 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0792) Prec@1 86.000 (86.656) Prec@5 100.000 (99.295) +2022-11-14 14:07:29,247 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0796) Prec@1 84.000 (86.613) Prec@5 99.000 (99.290) +2022-11-14 14:07:29,256 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0790) Prec@1 92.000 (86.698) Prec@5 100.000 (99.302) +2022-11-14 14:07:29,265 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0380 (0.0784) Prec@1 92.000 (86.781) Prec@5 100.000 (99.312) +2022-11-14 14:07:29,274 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0786) Prec@1 85.000 (86.754) Prec@5 99.000 (99.308) +2022-11-14 14:07:29,284 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0786) Prec@1 90.000 (86.803) Prec@5 100.000 (99.318) +2022-11-14 14:07:29,292 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0782) Prec@1 91.000 (86.866) Prec@5 100.000 (99.328) +2022-11-14 14:07:29,300 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0782) Prec@1 86.000 (86.853) Prec@5 98.000 (99.309) +2022-11-14 14:07:29,308 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0781) Prec@1 88.000 (86.870) Prec@5 100.000 (99.319) +2022-11-14 14:07:29,317 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0783) Prec@1 85.000 (86.843) Prec@5 99.000 (99.314) +2022-11-14 14:07:29,326 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0784) Prec@1 85.000 (86.817) Prec@5 100.000 (99.324) +2022-11-14 14:07:29,335 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0782) Prec@1 87.000 (86.819) Prec@5 99.000 (99.319) +2022-11-14 14:07:29,344 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0779) Prec@1 89.000 (86.849) Prec@5 100.000 (99.329) +2022-11-14 14:07:29,354 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0776) Prec@1 92.000 (86.919) Prec@5 99.000 (99.324) +2022-11-14 14:07:29,363 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0778) Prec@1 81.000 (86.840) Prec@5 98.000 (99.307) +2022-11-14 14:07:29,371 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0776) Prec@1 90.000 (86.882) Prec@5 100.000 (99.316) +2022-11-14 14:07:29,381 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0776) Prec@1 86.000 (86.870) Prec@5 97.000 (99.286) +2022-11-14 14:07:29,391 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0778) Prec@1 83.000 (86.821) Prec@5 96.000 (99.244) +2022-11-14 14:07:29,399 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0780) Prec@1 84.000 (86.785) Prec@5 99.000 (99.241) +2022-11-14 14:07:29,408 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0780) Prec@1 85.000 (86.763) Prec@5 99.000 (99.237) +2022-11-14 14:07:29,418 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0780) Prec@1 83.000 (86.716) Prec@5 100.000 (99.247) +2022-11-14 14:07:29,427 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0781) Prec@1 86.000 (86.707) Prec@5 100.000 (99.256) +2022-11-14 14:07:29,436 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0783) Prec@1 84.000 (86.675) Prec@5 100.000 (99.265) +2022-11-14 14:07:29,446 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0785) Prec@1 80.000 (86.595) Prec@5 100.000 (99.274) +2022-11-14 14:07:29,455 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0787) Prec@1 84.000 (86.565) Prec@5 100.000 (99.282) +2022-11-14 14:07:29,463 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0787) Prec@1 88.000 (86.581) Prec@5 100.000 (99.291) +2022-11-14 14:07:29,475 Test: [86/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0787) Prec@1 82.000 (86.529) Prec@5 99.000 (99.287) +2022-11-14 14:07:29,486 Test: [87/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0789) Prec@1 83.000 (86.489) Prec@5 99.000 (99.284) +2022-11-14 14:07:29,495 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0790) Prec@1 87.000 (86.494) Prec@5 99.000 (99.281) +2022-11-14 14:07:29,504 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0788) Prec@1 89.000 (86.522) Prec@5 100.000 (99.289) +2022-11-14 14:07:29,514 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0785) Prec@1 92.000 (86.582) Prec@5 100.000 (99.297) +2022-11-14 14:07:29,523 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0783) Prec@1 90.000 (86.620) Prec@5 100.000 (99.304) +2022-11-14 14:07:29,531 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0785) Prec@1 85.000 (86.602) Prec@5 99.000 (99.301) +2022-11-14 14:07:29,541 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0785) Prec@1 87.000 (86.606) Prec@5 97.000 (99.277) +2022-11-14 14:07:29,550 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0787) Prec@1 82.000 (86.558) Prec@5 100.000 (99.284) +2022-11-14 14:07:29,559 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0786) Prec@1 88.000 (86.573) Prec@5 100.000 (99.292) +2022-11-14 14:07:29,567 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0783) Prec@1 94.000 (86.649) Prec@5 98.000 (99.278) +2022-11-14 14:07:29,576 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0785) Prec@1 83.000 (86.612) Prec@5 98.000 (99.265) +2022-11-14 14:07:29,584 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0788) Prec@1 84.000 (86.586) Prec@5 99.000 (99.263) +2022-11-14 14:07:29,592 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0787) Prec@1 89.000 (86.610) Prec@5 98.000 (99.250) +2022-11-14 14:07:29,648 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:07:29,946 Epoch: [151][0/500] Time 0.022 (0.022) Data 0.217 (0.217) Loss 0.0427 (0.0427) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:07:30,148 Epoch: [151][10/500] Time 0.018 (0.018) Data 0.002 (0.021) Loss 0.0646 (0.0536) Prec@1 91.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:07:30,355 Epoch: [151][20/500] Time 0.016 (0.018) Data 0.002 (0.012) Loss 0.0613 (0.0562) Prec@1 90.000 (92.000) Prec@5 97.000 (98.333) +2022-11-14 14:07:30,586 Epoch: [151][30/500] Time 0.023 (0.019) Data 0.002 (0.009) Loss 0.0438 (0.0531) Prec@1 92.000 (92.000) Prec@5 99.000 (98.500) +2022-11-14 14:07:30,866 Epoch: [151][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.0448 (0.0514) Prec@1 93.000 (92.200) Prec@5 99.000 (98.600) +2022-11-14 14:07:31,139 Epoch: [151][50/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.0306 (0.0480) Prec@1 96.000 (92.833) Prec@5 100.000 (98.833) +2022-11-14 14:07:31,413 Epoch: [151][60/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0742 (0.0517) Prec@1 88.000 (92.143) Prec@5 100.000 (99.000) +2022-11-14 14:07:31,691 Epoch: [151][70/500] Time 0.024 (0.022) Data 0.002 (0.005) Loss 0.0458 (0.0510) Prec@1 93.000 (92.250) Prec@5 100.000 (99.125) +2022-11-14 14:07:32,135 Epoch: [151][80/500] Time 0.044 (0.024) Data 0.002 (0.004) Loss 0.0567 (0.0516) Prec@1 90.000 (92.000) Prec@5 100.000 (99.222) +2022-11-14 14:07:32,592 Epoch: [151][90/500] Time 0.043 (0.026) Data 0.002 (0.004) Loss 0.0548 (0.0519) Prec@1 90.000 (91.800) Prec@5 100.000 (99.300) +2022-11-14 14:07:33,053 Epoch: [151][100/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0383 (0.0507) Prec@1 93.000 (91.909) Prec@5 100.000 (99.364) +2022-11-14 14:07:33,511 Epoch: [151][110/500] Time 0.043 (0.028) Data 0.002 (0.004) Loss 0.0757 (0.0528) Prec@1 89.000 (91.667) Prec@5 99.000 (99.333) +2022-11-14 14:07:33,970 Epoch: [151][120/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.0349 (0.0514) Prec@1 96.000 (92.000) Prec@5 100.000 (99.385) +2022-11-14 14:07:34,431 Epoch: [151][130/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0676 (0.0526) Prec@1 91.000 (91.929) Prec@5 98.000 (99.286) +2022-11-14 14:07:34,890 Epoch: [151][140/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0645 (0.0534) Prec@1 89.000 (91.733) Prec@5 99.000 (99.267) +2022-11-14 14:07:35,347 Epoch: [151][150/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0570 (0.0536) Prec@1 90.000 (91.625) Prec@5 98.000 (99.188) +2022-11-14 14:07:35,807 Epoch: [151][160/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0528 (0.0535) Prec@1 91.000 (91.588) Prec@5 99.000 (99.176) +2022-11-14 14:07:36,270 Epoch: [151][170/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0833 (0.0552) Prec@1 86.000 (91.278) Prec@5 100.000 (99.222) +2022-11-14 14:07:36,739 Epoch: [151][180/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0520 (0.0550) Prec@1 92.000 (91.316) Prec@5 100.000 (99.263) +2022-11-14 14:07:37,197 Epoch: [151][190/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0656 (0.0556) Prec@1 90.000 (91.250) Prec@5 100.000 (99.300) +2022-11-14 14:07:37,649 Epoch: [151][200/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0394 (0.0548) Prec@1 95.000 (91.429) Prec@5 100.000 (99.333) +2022-11-14 14:07:38,105 Epoch: [151][210/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0553 (0.0548) Prec@1 91.000 (91.409) Prec@5 98.000 (99.273) +2022-11-14 14:07:38,565 Epoch: [151][220/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0543 (0.0548) Prec@1 91.000 (91.391) Prec@5 99.000 (99.261) +2022-11-14 14:07:39,023 Epoch: [151][230/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0321 (0.0538) Prec@1 97.000 (91.625) Prec@5 98.000 (99.208) +2022-11-14 14:07:39,483 Epoch: [151][240/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0540 (0.0538) Prec@1 88.000 (91.480) Prec@5 100.000 (99.240) +2022-11-14 14:07:39,942 Epoch: [151][250/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0558 (0.0539) Prec@1 91.000 (91.462) Prec@5 100.000 (99.269) +2022-11-14 14:07:40,403 Epoch: [151][260/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0419 (0.0535) Prec@1 94.000 (91.556) Prec@5 100.000 (99.296) +2022-11-14 14:07:40,870 Epoch: [151][270/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0569 (0.0536) Prec@1 90.000 (91.500) Prec@5 100.000 (99.321) +2022-11-14 14:07:41,324 Epoch: [151][280/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0641 (0.0540) Prec@1 86.000 (91.310) Prec@5 99.000 (99.310) +2022-11-14 14:07:41,762 Epoch: [151][290/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0540 (0.0540) Prec@1 91.000 (91.300) Prec@5 100.000 (99.333) +2022-11-14 14:07:42,054 Epoch: [151][300/500] Time 0.026 (0.036) Data 0.002 (0.003) Loss 0.0441 (0.0536) Prec@1 92.000 (91.323) Prec@5 100.000 (99.355) +2022-11-14 14:07:42,341 Epoch: [151][310/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.0763 (0.0544) Prec@1 89.000 (91.250) Prec@5 100.000 (99.375) +2022-11-14 14:07:42,630 Epoch: [151][320/500] Time 0.028 (0.035) Data 0.001 (0.003) Loss 0.0284 (0.0536) Prec@1 96.000 (91.394) Prec@5 100.000 (99.394) +2022-11-14 14:07:42,908 Epoch: [151][330/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0370 (0.0531) Prec@1 91.000 (91.382) Prec@5 100.000 (99.412) +2022-11-14 14:07:43,191 Epoch: [151][340/500] Time 0.027 (0.034) Data 0.001 (0.002) Loss 0.0482 (0.0529) Prec@1 93.000 (91.429) Prec@5 100.000 (99.429) +2022-11-14 14:07:43,476 Epoch: [151][350/500] Time 0.026 (0.034) Data 0.001 (0.002) Loss 0.0644 (0.0533) Prec@1 90.000 (91.389) Prec@5 100.000 (99.444) +2022-11-14 14:07:43,759 Epoch: [151][360/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0374 (0.0528) Prec@1 91.000 (91.378) Prec@5 100.000 (99.459) +2022-11-14 14:07:44,046 Epoch: [151][370/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0484 (0.0527) Prec@1 93.000 (91.421) Prec@5 100.000 (99.474) +2022-11-14 14:07:44,331 Epoch: [151][380/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0660 (0.0531) Prec@1 89.000 (91.359) Prec@5 100.000 (99.487) +2022-11-14 14:07:44,617 Epoch: [151][390/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0520 (0.0530) Prec@1 90.000 (91.325) Prec@5 100.000 (99.500) +2022-11-14 14:07:44,903 Epoch: [151][400/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0609 (0.0532) Prec@1 91.000 (91.317) Prec@5 100.000 (99.512) +2022-11-14 14:07:45,194 Epoch: [151][410/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0475 (0.0531) Prec@1 94.000 (91.381) Prec@5 100.000 (99.524) +2022-11-14 14:07:45,481 Epoch: [151][420/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0420 (0.0528) Prec@1 94.000 (91.442) Prec@5 100.000 (99.535) +2022-11-14 14:07:45,766 Epoch: [151][430/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.0627 (0.0531) Prec@1 88.000 (91.364) Prec@5 100.000 (99.545) +2022-11-14 14:07:46,051 Epoch: [151][440/500] Time 0.027 (0.032) Data 0.001 (0.002) Loss 0.0705 (0.0534) Prec@1 87.000 (91.267) Prec@5 99.000 (99.533) +2022-11-14 14:07:46,340 Epoch: [151][450/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0600 (0.0536) Prec@1 90.000 (91.239) Prec@5 100.000 (99.543) +2022-11-14 14:07:46,625 Epoch: [151][460/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0491 (0.0535) Prec@1 93.000 (91.277) Prec@5 100.000 (99.553) +2022-11-14 14:07:46,907 Epoch: [151][470/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0741 (0.0539) Prec@1 87.000 (91.188) Prec@5 99.000 (99.542) +2022-11-14 14:07:47,191 Epoch: [151][480/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0431 (0.0537) Prec@1 92.000 (91.204) Prec@5 100.000 (99.551) +2022-11-14 14:07:47,474 Epoch: [151][490/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0884 (0.0544) Prec@1 86.000 (91.100) Prec@5 99.000 (99.540) +2022-11-14 14:07:47,734 Epoch: [151][499/500] Time 0.027 (0.031) Data 0.001 (0.002) Loss 0.0532 (0.0544) Prec@1 90.000 (91.078) Prec@5 100.000 (99.549) +2022-11-14 14:07:48,013 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0643 (0.0643) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:07:48,020 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0700) Prec@1 86.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 14:07:48,029 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0777) Prec@1 84.000 (85.667) Prec@5 99.000 (99.667) +2022-11-14 14:07:48,040 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0762) Prec@1 89.000 (86.500) Prec@5 98.000 (99.250) +2022-11-14 14:07:48,049 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0798) Prec@1 85.000 (86.200) Prec@5 100.000 (99.400) +2022-11-14 14:07:48,057 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0745) Prec@1 91.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 14:07:48,065 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0736) Prec@1 88.000 (87.143) Prec@5 100.000 (99.571) +2022-11-14 14:07:48,076 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0756) Prec@1 85.000 (86.875) Prec@5 99.000 (99.500) +2022-11-14 14:07:48,084 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0797) Prec@1 80.000 (86.111) Prec@5 98.000 (99.333) +2022-11-14 14:07:48,091 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0791) Prec@1 87.000 (86.200) Prec@5 99.000 (99.300) +2022-11-14 14:07:48,099 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0779) Prec@1 90.000 (86.545) Prec@5 100.000 (99.364) +2022-11-14 14:07:48,107 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0781) Prec@1 88.000 (86.667) Prec@5 100.000 (99.417) +2022-11-14 14:07:48,115 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0402 (0.0752) Prec@1 94.000 (87.231) Prec@5 100.000 (99.462) +2022-11-14 14:07:48,124 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0753) Prec@1 85.000 (87.071) Prec@5 100.000 (99.500) +2022-11-14 14:07:48,133 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0757) Prec@1 89.000 (87.200) Prec@5 100.000 (99.533) +2022-11-14 14:07:48,142 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0750) Prec@1 90.000 (87.375) Prec@5 99.000 (99.500) +2022-11-14 14:07:48,151 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0736) Prec@1 94.000 (87.765) Prec@5 97.000 (99.353) +2022-11-14 14:07:48,162 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1258 (0.0765) Prec@1 79.000 (87.278) Prec@5 100.000 (99.389) +2022-11-14 14:07:48,170 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0772) Prec@1 83.000 (87.053) Prec@5 100.000 (99.421) +2022-11-14 14:07:48,180 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0777) Prec@1 84.000 (86.900) Prec@5 97.000 (99.300) +2022-11-14 14:07:48,189 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0788) Prec@1 83.000 (86.714) Prec@5 100.000 (99.333) +2022-11-14 14:07:48,198 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0781) Prec@1 89.000 (86.818) Prec@5 100.000 (99.364) +2022-11-14 14:07:48,208 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0790) Prec@1 83.000 (86.652) Prec@5 98.000 (99.304) +2022-11-14 14:07:48,217 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0781) Prec@1 91.000 (86.833) Prec@5 99.000 (99.292) +2022-11-14 14:07:48,225 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0788) Prec@1 84.000 (86.720) Prec@5 100.000 (99.320) +2022-11-14 14:07:48,235 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1011 (0.0797) Prec@1 81.000 (86.500) Prec@5 99.000 (99.308) +2022-11-14 14:07:48,244 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0791) Prec@1 88.000 (86.556) Prec@5 100.000 (99.333) +2022-11-14 14:07:48,253 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0795) Prec@1 83.000 (86.429) Prec@5 99.000 (99.321) +2022-11-14 14:07:48,263 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0789) Prec@1 90.000 (86.552) Prec@5 99.000 (99.310) +2022-11-14 14:07:48,272 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0792) Prec@1 86.000 (86.533) Prec@5 99.000 (99.300) +2022-11-14 14:07:48,281 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0786) Prec@1 90.000 (86.645) Prec@5 99.000 (99.290) +2022-11-14 14:07:48,289 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0780) Prec@1 89.000 (86.719) Prec@5 100.000 (99.312) +2022-11-14 14:07:48,299 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0786) Prec@1 80.000 (86.515) Prec@5 98.000 (99.273) +2022-11-14 14:07:48,308 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0790) Prec@1 86.000 (86.500) Prec@5 100.000 (99.294) +2022-11-14 14:07:48,316 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0787) Prec@1 89.000 (86.571) Prec@5 99.000 (99.286) +2022-11-14 14:07:48,326 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0781) Prec@1 91.000 (86.694) Prec@5 100.000 (99.306) +2022-11-14 14:07:48,335 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0782) Prec@1 89.000 (86.757) Prec@5 99.000 (99.297) +2022-11-14 14:07:48,344 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1249 (0.0794) Prec@1 79.000 (86.553) Prec@5 100.000 (99.316) +2022-11-14 14:07:48,353 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0790) Prec@1 90.000 (86.641) Prec@5 100.000 (99.333) +2022-11-14 14:07:48,363 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0789) Prec@1 86.000 (86.625) Prec@5 98.000 (99.300) +2022-11-14 14:07:48,371 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0793) Prec@1 84.000 (86.561) Prec@5 99.000 (99.293) +2022-11-14 14:07:48,381 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0793) Prec@1 88.000 (86.595) Prec@5 99.000 (99.286) +2022-11-14 14:07:48,389 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0787) Prec@1 92.000 (86.721) Prec@5 99.000 (99.279) +2022-11-14 14:07:48,397 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0791) Prec@1 84.000 (86.659) Prec@5 99.000 (99.273) +2022-11-14 14:07:48,406 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0793) Prec@1 86.000 (86.644) Prec@5 100.000 (99.289) +2022-11-14 14:07:48,415 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0800) Prec@1 84.000 (86.587) Prec@5 98.000 (99.261) +2022-11-14 14:07:48,425 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0799) Prec@1 87.000 (86.596) Prec@5 100.000 (99.277) +2022-11-14 14:07:48,433 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1226 (0.0808) Prec@1 77.000 (86.396) Prec@5 99.000 (99.271) +2022-11-14 14:07:48,441 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0803) Prec@1 90.000 (86.469) Prec@5 99.000 (99.265) +2022-11-14 14:07:48,449 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1229 (0.0812) Prec@1 77.000 (86.280) Prec@5 100.000 (99.280) +2022-11-14 14:07:48,458 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0810) Prec@1 89.000 (86.333) Prec@5 99.000 (99.275) +2022-11-14 14:07:48,467 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0814) Prec@1 83.000 (86.269) Prec@5 99.000 (99.269) +2022-11-14 14:07:48,476 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0811) Prec@1 89.000 (86.321) Prec@5 100.000 (99.283) +2022-11-14 14:07:48,485 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0809) Prec@1 88.000 (86.352) Prec@5 98.000 (99.259) +2022-11-14 14:07:48,494 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0813) Prec@1 83.000 (86.291) Prec@5 100.000 (99.273) +2022-11-14 14:07:48,503 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0816) Prec@1 83.000 (86.232) Prec@5 99.000 (99.268) +2022-11-14 14:07:48,513 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0817) Prec@1 85.000 (86.211) Prec@5 98.000 (99.246) +2022-11-14 14:07:48,522 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0816) Prec@1 88.000 (86.241) Prec@5 100.000 (99.259) +2022-11-14 14:07:48,531 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0820) Prec@1 77.000 (86.085) Prec@5 100.000 (99.271) +2022-11-14 14:07:48,540 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0821) Prec@1 87.000 (86.100) Prec@5 100.000 (99.283) +2022-11-14 14:07:48,550 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0822) Prec@1 86.000 (86.098) Prec@5 99.000 (99.279) +2022-11-14 14:07:48,559 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0822) Prec@1 86.000 (86.097) Prec@5 98.000 (99.258) +2022-11-14 14:07:48,568 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0817) Prec@1 92.000 (86.190) Prec@5 100.000 (99.270) +2022-11-14 14:07:48,578 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0337 (0.0809) Prec@1 95.000 (86.328) Prec@5 100.000 (99.281) +2022-11-14 14:07:48,587 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0814) Prec@1 81.000 (86.246) Prec@5 99.000 (99.277) +2022-11-14 14:07:48,597 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0815) Prec@1 84.000 (86.212) Prec@5 100.000 (99.288) +2022-11-14 14:07:48,606 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0813) Prec@1 88.000 (86.239) Prec@5 100.000 (99.299) +2022-11-14 14:07:48,615 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0814) Prec@1 83.000 (86.191) Prec@5 99.000 (99.294) +2022-11-14 14:07:48,624 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0816) Prec@1 86.000 (86.188) Prec@5 99.000 (99.290) +2022-11-14 14:07:48,633 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0816) Prec@1 86.000 (86.186) Prec@5 99.000 (99.286) +2022-11-14 14:07:48,642 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0816) Prec@1 86.000 (86.183) Prec@5 100.000 (99.296) +2022-11-14 14:07:48,652 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0816) Prec@1 86.000 (86.181) Prec@5 98.000 (99.278) +2022-11-14 14:07:48,661 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0814) Prec@1 88.000 (86.205) Prec@5 99.000 (99.274) +2022-11-14 14:07:48,670 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0809) Prec@1 94.000 (86.311) Prec@5 100.000 (99.284) +2022-11-14 14:07:48,679 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0811) Prec@1 85.000 (86.293) Prec@5 99.000 (99.280) +2022-11-14 14:07:48,689 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0808) Prec@1 91.000 (86.355) Prec@5 100.000 (99.289) +2022-11-14 14:07:48,700 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0386 (0.0803) Prec@1 95.000 (86.468) Prec@5 98.000 (99.273) +2022-11-14 14:07:48,713 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.0807) Prec@1 78.000 (86.359) Prec@5 99.000 (99.269) +2022-11-14 14:07:48,726 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0805) Prec@1 89.000 (86.392) Prec@5 100.000 (99.278) +2022-11-14 14:07:48,739 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0804) Prec@1 87.000 (86.400) Prec@5 100.000 (99.287) +2022-11-14 14:07:48,752 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0803) Prec@1 90.000 (86.444) Prec@5 99.000 (99.284) +2022-11-14 14:07:48,764 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1168 (0.0808) Prec@1 82.000 (86.390) Prec@5 98.000 (99.268) +2022-11-14 14:07:48,776 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0809) Prec@1 84.000 (86.361) Prec@5 99.000 (99.265) +2022-11-14 14:07:48,790 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0810) Prec@1 85.000 (86.345) Prec@5 99.000 (99.262) +2022-11-14 14:07:48,805 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.0813) Prec@1 82.000 (86.294) Prec@5 99.000 (99.259) +2022-11-14 14:07:48,818 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0814) Prec@1 83.000 (86.256) Prec@5 100.000 (99.267) +2022-11-14 14:07:48,832 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0811) Prec@1 90.000 (86.299) Prec@5 100.000 (99.276) +2022-11-14 14:07:48,848 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0811) Prec@1 87.000 (86.307) Prec@5 99.000 (99.273) +2022-11-14 14:07:48,864 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0811) Prec@1 88.000 (86.326) Prec@5 98.000 (99.258) +2022-11-14 14:07:48,880 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0812) Prec@1 86.000 (86.322) Prec@5 99.000 (99.256) +2022-11-14 14:07:48,895 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0810) Prec@1 91.000 (86.374) Prec@5 100.000 (99.264) +2022-11-14 14:07:48,910 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0807) Prec@1 92.000 (86.435) Prec@5 100.000 (99.272) +2022-11-14 14:07:48,924 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0807) Prec@1 87.000 (86.441) Prec@5 100.000 (99.280) +2022-11-14 14:07:48,939 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0809) Prec@1 84.000 (86.415) Prec@5 98.000 (99.266) +2022-11-14 14:07:48,953 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0808) Prec@1 88.000 (86.432) Prec@5 100.000 (99.274) +2022-11-14 14:07:48,968 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0807) Prec@1 89.000 (86.458) Prec@5 99.000 (99.271) +2022-11-14 14:07:48,982 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0804) Prec@1 90.000 (86.495) Prec@5 98.000 (99.258) +2022-11-14 14:07:48,997 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1229 (0.0808) Prec@1 82.000 (86.449) Prec@5 98.000 (99.245) +2022-11-14 14:07:49,012 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0809) Prec@1 83.000 (86.414) Prec@5 100.000 (99.253) +2022-11-14 14:07:49,027 Test: [99/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0810) Prec@1 84.000 (86.390) Prec@5 99.000 (99.250) +2022-11-14 14:07:49,082 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:07:49,394 Epoch: [152][0/500] Time 0.026 (0.026) Data 0.229 (0.229) Loss 0.0458 (0.0458) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:07:49,621 Epoch: [152][10/500] Time 0.022 (0.020) Data 0.001 (0.022) Loss 0.0642 (0.0550) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 14:07:49,871 Epoch: [152][20/500] Time 0.024 (0.021) Data 0.001 (0.012) Loss 0.0387 (0.0496) Prec@1 93.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:07:50,124 Epoch: [152][30/500] Time 0.023 (0.022) Data 0.002 (0.009) Loss 0.0392 (0.0470) Prec@1 93.000 (91.500) Prec@5 100.000 (99.750) +2022-11-14 14:07:50,429 Epoch: [152][40/500] Time 0.042 (0.023) Data 0.002 (0.007) Loss 0.0510 (0.0478) Prec@1 92.000 (91.600) Prec@5 98.000 (99.400) +2022-11-14 14:07:50,889 Epoch: [152][50/500] Time 0.043 (0.026) Data 0.002 (0.006) Loss 0.0458 (0.0474) Prec@1 94.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:07:51,348 Epoch: [152][60/500] Time 0.042 (0.029) Data 0.002 (0.005) Loss 0.0411 (0.0465) Prec@1 94.000 (92.286) Prec@5 100.000 (99.571) +2022-11-14 14:07:51,808 Epoch: [152][70/500] Time 0.043 (0.030) Data 0.002 (0.005) Loss 0.0662 (0.0490) Prec@1 88.000 (91.750) Prec@5 99.000 (99.500) +2022-11-14 14:07:52,267 Epoch: [152][80/500] Time 0.043 (0.032) Data 0.002 (0.005) Loss 0.0547 (0.0496) Prec@1 92.000 (91.778) Prec@5 100.000 (99.556) +2022-11-14 14:07:52,726 Epoch: [152][90/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0360 (0.0483) Prec@1 94.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:07:53,187 Epoch: [152][100/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0510 (0.0485) Prec@1 92.000 (92.000) Prec@5 100.000 (99.636) +2022-11-14 14:07:53,650 Epoch: [152][110/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0806 (0.0512) Prec@1 88.000 (91.667) Prec@5 99.000 (99.583) +2022-11-14 14:07:54,109 Epoch: [152][120/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0621 (0.0520) Prec@1 90.000 (91.538) Prec@5 99.000 (99.538) +2022-11-14 14:07:54,569 Epoch: [152][130/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0326 (0.0506) Prec@1 95.000 (91.786) Prec@5 100.000 (99.571) +2022-11-14 14:07:55,027 Epoch: [152][140/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0642 (0.0515) Prec@1 89.000 (91.600) Prec@5 98.000 (99.467) +2022-11-14 14:07:55,488 Epoch: [152][150/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0519 (0.0516) Prec@1 92.000 (91.625) Prec@5 99.000 (99.438) +2022-11-14 14:07:55,945 Epoch: [152][160/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0441 (0.0511) Prec@1 93.000 (91.706) Prec@5 99.000 (99.412) +2022-11-14 14:07:56,409 Epoch: [152][170/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0274 (0.0498) Prec@1 94.000 (91.833) Prec@5 100.000 (99.444) +2022-11-14 14:07:56,869 Epoch: [152][180/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0377 (0.0492) Prec@1 93.000 (91.895) Prec@5 99.000 (99.421) +2022-11-14 14:07:57,326 Epoch: [152][190/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0532 (0.0494) Prec@1 89.000 (91.750) Prec@5 100.000 (99.450) +2022-11-14 14:07:57,789 Epoch: [152][200/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0597 (0.0499) Prec@1 91.000 (91.714) Prec@5 98.000 (99.381) +2022-11-14 14:07:58,250 Epoch: [152][210/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0427 (0.0495) Prec@1 94.000 (91.818) Prec@5 100.000 (99.409) +2022-11-14 14:07:58,566 Epoch: [152][220/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.0500 (0.0496) Prec@1 90.000 (91.739) Prec@5 100.000 (99.435) +2022-11-14 14:07:58,859 Epoch: [152][230/500] Time 0.025 (0.036) Data 0.003 (0.003) Loss 0.0468 (0.0494) Prec@1 92.000 (91.750) Prec@5 98.000 (99.375) +2022-11-14 14:07:59,153 Epoch: [152][240/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.0462 (0.0493) Prec@1 93.000 (91.800) Prec@5 98.000 (99.320) +2022-11-14 14:07:59,452 Epoch: [152][250/500] Time 0.027 (0.036) Data 0.001 (0.003) Loss 0.0598 (0.0497) Prec@1 90.000 (91.731) Prec@5 100.000 (99.346) +2022-11-14 14:07:59,744 Epoch: [152][260/500] Time 0.027 (0.035) Data 0.002 (0.003) Loss 0.0657 (0.0503) Prec@1 87.000 (91.556) Prec@5 100.000 (99.370) +2022-11-14 14:08:00,047 Epoch: [152][270/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0388 (0.0499) Prec@1 94.000 (91.643) Prec@5 100.000 (99.393) +2022-11-14 14:08:00,343 Epoch: [152][280/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.0244 (0.0490) Prec@1 96.000 (91.793) Prec@5 100.000 (99.414) +2022-11-14 14:08:00,642 Epoch: [152][290/500] Time 0.028 (0.034) Data 0.001 (0.003) Loss 0.0354 (0.0486) Prec@1 94.000 (91.867) Prec@5 100.000 (99.433) +2022-11-14 14:08:00,942 Epoch: [152][300/500] Time 0.028 (0.034) Data 0.001 (0.003) Loss 0.0781 (0.0495) Prec@1 88.000 (91.742) Prec@5 98.000 (99.387) +2022-11-14 14:08:01,241 Epoch: [152][310/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0259 (0.0488) Prec@1 96.000 (91.875) Prec@5 100.000 (99.406) +2022-11-14 14:08:01,541 Epoch: [152][320/500] Time 0.027 (0.034) Data 0.001 (0.003) Loss 0.0563 (0.0490) Prec@1 91.000 (91.848) Prec@5 99.000 (99.394) +2022-11-14 14:08:01,841 Epoch: [152][330/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.0424 (0.0488) Prec@1 93.000 (91.882) Prec@5 100.000 (99.412) +2022-11-14 14:08:02,135 Epoch: [152][340/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.0398 (0.0486) Prec@1 93.000 (91.914) Prec@5 100.000 (99.429) +2022-11-14 14:08:02,436 Epoch: [152][350/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.0339 (0.0481) Prec@1 95.000 (92.000) Prec@5 100.000 (99.444) +2022-11-14 14:08:02,732 Epoch: [152][360/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0714 (0.0488) Prec@1 89.000 (91.919) Prec@5 100.000 (99.459) +2022-11-14 14:08:03,033 Epoch: [152][370/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.0574 (0.0490) Prec@1 91.000 (91.895) Prec@5 100.000 (99.474) +2022-11-14 14:08:03,331 Epoch: [152][380/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0457 (0.0489) Prec@1 92.000 (91.897) Prec@5 100.000 (99.487) +2022-11-14 14:08:03,638 Epoch: [152][390/500] Time 0.028 (0.032) Data 0.002 (0.002) Loss 0.0254 (0.0483) Prec@1 96.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:08:03,940 Epoch: [152][400/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.0520 (0.0484) Prec@1 93.000 (92.024) Prec@5 100.000 (99.512) +2022-11-14 14:08:04,241 Epoch: [152][410/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.0694 (0.0489) Prec@1 85.000 (91.857) Prec@5 99.000 (99.500) +2022-11-14 14:08:04,547 Epoch: [152][420/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.0585 (0.0491) Prec@1 92.000 (91.860) Prec@5 99.000 (99.488) +2022-11-14 14:08:04,848 Epoch: [152][430/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0666 (0.0495) Prec@1 89.000 (91.795) Prec@5 100.000 (99.500) +2022-11-14 14:08:05,148 Epoch: [152][440/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.0410 (0.0494) Prec@1 94.000 (91.844) Prec@5 100.000 (99.511) +2022-11-14 14:08:05,448 Epoch: [152][450/500] Time 0.031 (0.032) Data 0.002 (0.002) Loss 0.0573 (0.0495) Prec@1 90.000 (91.804) Prec@5 100.000 (99.522) +2022-11-14 14:08:05,755 Epoch: [152][460/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0418 (0.0494) Prec@1 93.000 (91.830) Prec@5 99.000 (99.511) +2022-11-14 14:08:06,051 Epoch: [152][470/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0324 (0.0490) Prec@1 95.000 (91.896) Prec@5 100.000 (99.521) +2022-11-14 14:08:06,357 Epoch: [152][480/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0729 (0.0495) Prec@1 87.000 (91.796) Prec@5 97.000 (99.469) +2022-11-14 14:08:06,662 Epoch: [152][490/500] Time 0.027 (0.031) Data 0.002 (0.002) Loss 0.0604 (0.0497) Prec@1 87.000 (91.700) Prec@5 100.000 (99.480) +2022-11-14 14:08:06,936 Epoch: [152][499/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0482 (0.0497) Prec@1 91.000 (91.686) Prec@5 100.000 (99.490) +2022-11-14 14:08:07,207 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0842 (0.0842) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:07,215 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0843) Prec@1 86.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:07,222 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0859) Prec@1 82.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:07,235 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0814) Prec@1 90.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 14:08:07,244 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0832) Prec@1 85.000 (85.400) Prec@5 99.000 (99.800) +2022-11-14 14:08:07,251 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0782) Prec@1 90.000 (86.167) Prec@5 100.000 (99.833) +2022-11-14 14:08:07,260 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0776) Prec@1 87.000 (86.286) Prec@5 99.000 (99.714) +2022-11-14 14:08:07,268 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0812) Prec@1 81.000 (85.625) Prec@5 99.000 (99.625) +2022-11-14 14:08:07,278 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0809) Prec@1 86.000 (85.667) Prec@5 99.000 (99.556) +2022-11-14 14:08:07,287 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0803) Prec@1 87.000 (85.800) Prec@5 99.000 (99.500) +2022-11-14 14:08:07,296 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0797) Prec@1 86.000 (85.818) Prec@5 99.000 (99.455) +2022-11-14 14:08:07,306 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0812) Prec@1 86.000 (85.833) Prec@5 98.000 (99.333) +2022-11-14 14:08:07,316 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0412 (0.0781) Prec@1 92.000 (86.308) Prec@5 100.000 (99.385) +2022-11-14 14:08:07,327 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0778) Prec@1 84.000 (86.143) Prec@5 100.000 (99.429) +2022-11-14 14:08:07,337 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0788) Prec@1 85.000 (86.067) Prec@5 99.000 (99.400) +2022-11-14 14:08:07,348 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0790) Prec@1 85.000 (86.000) Prec@5 100.000 (99.438) +2022-11-14 14:08:07,358 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0780) Prec@1 90.000 (86.235) Prec@5 99.000 (99.412) +2022-11-14 14:08:07,369 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0792) Prec@1 82.000 (86.000) Prec@5 100.000 (99.444) +2022-11-14 14:08:07,379 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0794) Prec@1 85.000 (85.947) Prec@5 100.000 (99.474) +2022-11-14 14:08:07,389 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0793) Prec@1 86.000 (85.950) Prec@5 98.000 (99.400) +2022-11-14 14:08:07,398 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0797) Prec@1 86.000 (85.952) Prec@5 100.000 (99.429) +2022-11-14 14:08:07,408 Test: [21/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0797) Prec@1 87.000 (86.000) Prec@5 99.000 (99.409) +2022-11-14 14:08:07,419 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0802) Prec@1 85.000 (85.957) Prec@5 99.000 (99.391) +2022-11-14 14:08:07,429 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0796) Prec@1 89.000 (86.083) Prec@5 100.000 (99.417) +2022-11-14 14:08:07,440 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0793) Prec@1 89.000 (86.200) Prec@5 100.000 (99.440) +2022-11-14 14:08:07,452 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0799) Prec@1 85.000 (86.154) Prec@5 96.000 (99.308) +2022-11-14 14:08:07,463 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0789) Prec@1 95.000 (86.481) Prec@5 100.000 (99.333) +2022-11-14 14:08:07,474 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0789) Prec@1 85.000 (86.429) Prec@5 100.000 (99.357) +2022-11-14 14:08:07,485 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0784) Prec@1 90.000 (86.552) Prec@5 97.000 (99.276) +2022-11-14 14:08:07,496 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0783) Prec@1 87.000 (86.567) Prec@5 98.000 (99.233) +2022-11-14 14:08:07,508 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0783) Prec@1 87.000 (86.581) Prec@5 99.000 (99.226) +2022-11-14 14:08:07,518 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0781) Prec@1 89.000 (86.656) Prec@5 99.000 (99.219) +2022-11-14 14:08:07,529 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0784) Prec@1 84.000 (86.576) Prec@5 98.000 (99.182) +2022-11-14 14:08:07,540 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0790) Prec@1 83.000 (86.471) Prec@5 100.000 (99.206) +2022-11-14 14:08:07,552 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0793) Prec@1 86.000 (86.457) Prec@5 97.000 (99.143) +2022-11-14 14:08:07,562 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0789) Prec@1 91.000 (86.583) Prec@5 100.000 (99.167) +2022-11-14 14:08:07,571 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0788) Prec@1 88.000 (86.622) Prec@5 98.000 (99.135) +2022-11-14 14:08:07,582 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0791) Prec@1 85.000 (86.579) Prec@5 99.000 (99.132) +2022-11-14 14:08:07,593 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0790) Prec@1 87.000 (86.590) Prec@5 98.000 (99.103) +2022-11-14 14:08:07,604 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0791) Prec@1 89.000 (86.650) Prec@5 99.000 (99.100) +2022-11-14 14:08:07,614 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0790) Prec@1 87.000 (86.659) Prec@5 98.000 (99.073) +2022-11-14 14:08:07,626 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0786) Prec@1 89.000 (86.714) Prec@5 98.000 (99.048) +2022-11-14 14:08:07,636 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0778) Prec@1 91.000 (86.814) Prec@5 100.000 (99.070) +2022-11-14 14:08:07,648 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0779) Prec@1 86.000 (86.795) Prec@5 99.000 (99.068) +2022-11-14 14:08:07,657 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0784) Prec@1 84.000 (86.733) Prec@5 100.000 (99.089) +2022-11-14 14:08:07,669 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0792) Prec@1 80.000 (86.587) Prec@5 98.000 (99.065) +2022-11-14 14:08:07,680 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0792) Prec@1 84.000 (86.532) Prec@5 98.000 (99.043) +2022-11-14 14:08:07,689 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0799) Prec@1 82.000 (86.438) Prec@5 100.000 (99.062) +2022-11-14 14:08:07,699 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0796) Prec@1 89.000 (86.490) Prec@5 100.000 (99.082) +2022-11-14 14:08:07,710 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.0804) Prec@1 81.000 (86.380) Prec@5 99.000 (99.080) +2022-11-14 14:08:07,720 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0801) Prec@1 89.000 (86.431) Prec@5 100.000 (99.098) +2022-11-14 14:08:07,731 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0801) Prec@1 87.000 (86.442) Prec@5 98.000 (99.077) +2022-11-14 14:08:07,742 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0799) Prec@1 87.000 (86.453) Prec@5 100.000 (99.094) +2022-11-14 14:08:07,753 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0798) Prec@1 88.000 (86.481) Prec@5 99.000 (99.093) +2022-11-14 14:08:07,765 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0800) Prec@1 84.000 (86.436) Prec@5 100.000 (99.109) +2022-11-14 14:08:07,776 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0802) Prec@1 83.000 (86.375) Prec@5 99.000 (99.107) +2022-11-14 14:08:07,788 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0803) Prec@1 85.000 (86.351) Prec@5 100.000 (99.123) +2022-11-14 14:08:07,799 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0800) Prec@1 90.000 (86.414) Prec@5 99.000 (99.121) +2022-11-14 14:08:07,810 Test: [58/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0802) Prec@1 84.000 (86.373) Prec@5 100.000 (99.136) +2022-11-14 14:08:07,821 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0803) Prec@1 86.000 (86.367) Prec@5 100.000 (99.150) +2022-11-14 14:08:07,834 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0804) Prec@1 85.000 (86.344) Prec@5 99.000 (99.148) +2022-11-14 14:08:07,847 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0804) Prec@1 88.000 (86.371) Prec@5 100.000 (99.161) +2022-11-14 14:08:07,858 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0804) Prec@1 87.000 (86.381) Prec@5 100.000 (99.175) +2022-11-14 14:08:07,869 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0798) Prec@1 93.000 (86.484) Prec@5 98.000 (99.156) +2022-11-14 14:08:07,878 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0799) Prec@1 85.000 (86.462) Prec@5 100.000 (99.169) +2022-11-14 14:08:07,890 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0803) Prec@1 83.000 (86.409) Prec@5 99.000 (99.167) +2022-11-14 14:08:07,901 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0800) Prec@1 91.000 (86.478) Prec@5 100.000 (99.179) +2022-11-14 14:08:07,911 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0799) Prec@1 88.000 (86.500) Prec@5 98.000 (99.162) +2022-11-14 14:08:07,921 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0799) Prec@1 87.000 (86.507) Prec@5 99.000 (99.159) +2022-11-14 14:08:07,933 Test: [69/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0801) Prec@1 84.000 (86.471) Prec@5 98.000 (99.143) +2022-11-14 14:08:07,944 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0800) Prec@1 89.000 (86.507) Prec@5 100.000 (99.155) +2022-11-14 14:08:07,953 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0800) Prec@1 85.000 (86.486) Prec@5 99.000 (99.153) +2022-11-14 14:08:07,962 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0796) Prec@1 92.000 (86.562) Prec@5 100.000 (99.164) +2022-11-14 14:08:07,973 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0792) Prec@1 92.000 (86.635) Prec@5 100.000 (99.176) +2022-11-14 14:08:07,983 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0793) Prec@1 87.000 (86.640) Prec@5 100.000 (99.187) +2022-11-14 14:08:07,993 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0791) Prec@1 91.000 (86.697) Prec@5 100.000 (99.197) +2022-11-14 14:08:08,002 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0790) Prec@1 89.000 (86.727) Prec@5 99.000 (99.195) +2022-11-14 14:08:08,011 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0791) Prec@1 84.000 (86.692) Prec@5 96.000 (99.154) +2022-11-14 14:08:08,022 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0789) Prec@1 85.000 (86.671) Prec@5 100.000 (99.165) +2022-11-14 14:08:08,032 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0788) Prec@1 88.000 (86.688) Prec@5 99.000 (99.162) +2022-11-14 14:08:08,043 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0788) Prec@1 87.000 (86.691) Prec@5 98.000 (99.148) +2022-11-14 14:08:08,053 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0791) Prec@1 83.000 (86.646) Prec@5 99.000 (99.146) +2022-11-14 14:08:08,063 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0793) Prec@1 83.000 (86.602) Prec@5 99.000 (99.145) +2022-11-14 14:08:08,074 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0794) Prec@1 83.000 (86.560) Prec@5 99.000 (99.143) +2022-11-14 14:08:08,085 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0797) Prec@1 83.000 (86.518) Prec@5 99.000 (99.141) +2022-11-14 14:08:08,095 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.0800) Prec@1 83.000 (86.477) Prec@5 99.000 (99.140) +2022-11-14 14:08:08,105 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0802) Prec@1 83.000 (86.437) Prec@5 99.000 (99.138) +2022-11-14 14:08:08,118 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0803) Prec@1 83.000 (86.398) Prec@5 99.000 (99.136) +2022-11-14 14:08:08,130 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0802) Prec@1 84.000 (86.371) Prec@5 99.000 (99.135) +2022-11-14 14:08:08,144 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0802) Prec@1 90.000 (86.411) Prec@5 100.000 (99.144) +2022-11-14 14:08:08,159 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0801) Prec@1 87.000 (86.418) Prec@5 100.000 (99.154) +2022-11-14 14:08:08,172 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0797) Prec@1 93.000 (86.489) Prec@5 100.000 (99.163) +2022-11-14 14:08:08,183 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0798) Prec@1 87.000 (86.495) Prec@5 100.000 (99.172) +2022-11-14 14:08:08,192 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0799) Prec@1 88.000 (86.511) Prec@5 100.000 (99.181) +2022-11-14 14:08:08,204 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0798) Prec@1 88.000 (86.526) Prec@5 100.000 (99.189) +2022-11-14 14:08:08,213 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0797) Prec@1 90.000 (86.562) Prec@5 99.000 (99.188) +2022-11-14 14:08:08,225 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0795) Prec@1 92.000 (86.619) Prec@5 99.000 (99.186) +2022-11-14 14:08:08,234 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0796) Prec@1 84.000 (86.592) Prec@5 100.000 (99.194) +2022-11-14 14:08:08,246 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0798) Prec@1 86.000 (86.586) Prec@5 99.000 (99.192) +2022-11-14 14:08:08,255 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0796) Prec@1 91.000 (86.630) Prec@5 98.000 (99.180) +2022-11-14 14:08:08,322 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:08:08,637 Epoch: [153][0/500] Time 0.025 (0.025) Data 0.229 (0.229) Loss 0.0561 (0.0561) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:08,846 Epoch: [153][10/500] Time 0.019 (0.019) Data 0.001 (0.022) Loss 0.0576 (0.0569) Prec@1 89.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:08:09,079 Epoch: [153][20/500] Time 0.018 (0.020) Data 0.001 (0.013) Loss 0.0389 (0.0509) Prec@1 94.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:08:09,378 Epoch: [153][30/500] Time 0.029 (0.022) Data 0.002 (0.009) Loss 0.0372 (0.0474) Prec@1 95.000 (92.250) Prec@5 100.000 (99.750) +2022-11-14 14:08:09,732 Epoch: [153][40/500] Time 0.034 (0.024) Data 0.001 (0.007) Loss 0.0511 (0.0482) Prec@1 91.000 (92.000) Prec@5 100.000 (99.800) +2022-11-14 14:08:10,090 Epoch: [153][50/500] Time 0.029 (0.025) Data 0.002 (0.006) Loss 0.0415 (0.0471) Prec@1 93.000 (92.167) Prec@5 100.000 (99.833) +2022-11-14 14:08:10,420 Epoch: [153][60/500] Time 0.030 (0.026) Data 0.002 (0.006) Loss 0.0465 (0.0470) Prec@1 93.000 (92.286) Prec@5 99.000 (99.714) +2022-11-14 14:08:10,778 Epoch: [153][70/500] Time 0.029 (0.027) Data 0.002 (0.005) Loss 0.0484 (0.0472) Prec@1 90.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:08:11,107 Epoch: [153][80/500] Time 0.031 (0.027) Data 0.001 (0.005) Loss 0.0575 (0.0483) Prec@1 91.000 (91.889) Prec@5 100.000 (99.778) +2022-11-14 14:08:11,440 Epoch: [153][90/500] Time 0.032 (0.027) Data 0.002 (0.004) Loss 0.0812 (0.0516) Prec@1 87.000 (91.400) Prec@5 99.000 (99.700) +2022-11-14 14:08:11,772 Epoch: [153][100/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0601 (0.0524) Prec@1 89.000 (91.182) Prec@5 100.000 (99.727) +2022-11-14 14:08:12,137 Epoch: [153][110/500] Time 0.043 (0.028) Data 0.002 (0.004) Loss 0.0358 (0.0510) Prec@1 94.000 (91.417) Prec@5 100.000 (99.750) +2022-11-14 14:08:12,466 Epoch: [153][120/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0655 (0.0521) Prec@1 88.000 (91.154) Prec@5 99.000 (99.692) +2022-11-14 14:08:12,829 Epoch: [153][130/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0536 (0.0522) Prec@1 90.000 (91.071) Prec@5 99.000 (99.643) +2022-11-14 14:08:13,186 Epoch: [153][140/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0607 (0.0528) Prec@1 91.000 (91.067) Prec@5 100.000 (99.667) +2022-11-14 14:08:13,520 Epoch: [153][150/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0469 (0.0524) Prec@1 92.000 (91.125) Prec@5 100.000 (99.688) +2022-11-14 14:08:13,900 Epoch: [153][160/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0474 (0.0521) Prec@1 93.000 (91.235) Prec@5 100.000 (99.706) +2022-11-14 14:08:14,275 Epoch: [153][170/500] Time 0.026 (0.029) Data 0.002 (0.003) Loss 0.0372 (0.0513) Prec@1 92.000 (91.278) Prec@5 100.000 (99.722) +2022-11-14 14:08:14,670 Epoch: [153][180/500] Time 0.040 (0.030) Data 0.002 (0.003) Loss 0.0492 (0.0512) Prec@1 92.000 (91.316) Prec@5 100.000 (99.737) +2022-11-14 14:08:15,035 Epoch: [153][190/500] Time 0.038 (0.030) Data 0.002 (0.003) Loss 0.0764 (0.0524) Prec@1 88.000 (91.150) Prec@5 100.000 (99.750) +2022-11-14 14:08:15,411 Epoch: [153][200/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.0510 (0.0524) Prec@1 91.000 (91.143) Prec@5 98.000 (99.667) +2022-11-14 14:08:15,755 Epoch: [153][210/500] Time 0.025 (0.030) Data 0.002 (0.003) Loss 0.0512 (0.0523) Prec@1 90.000 (91.091) Prec@5 99.000 (99.636) +2022-11-14 14:08:16,133 Epoch: [153][220/500] Time 0.026 (0.030) Data 0.002 (0.003) Loss 0.0790 (0.0535) Prec@1 85.000 (90.826) Prec@5 99.000 (99.609) +2022-11-14 14:08:16,569 Epoch: [153][230/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0656 (0.0540) Prec@1 88.000 (90.708) Prec@5 98.000 (99.542) +2022-11-14 14:08:16,976 Epoch: [153][240/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0865 (0.0553) Prec@1 86.000 (90.520) Prec@5 98.000 (99.480) +2022-11-14 14:08:17,338 Epoch: [153][250/500] Time 0.029 (0.031) Data 0.002 (0.003) Loss 0.0579 (0.0554) Prec@1 88.000 (90.423) Prec@5 100.000 (99.500) +2022-11-14 14:08:17,725 Epoch: [153][260/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0381 (0.0547) Prec@1 91.000 (90.444) Prec@5 100.000 (99.519) +2022-11-14 14:08:18,183 Epoch: [153][270/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0271 (0.0538) Prec@1 95.000 (90.607) Prec@5 100.000 (99.536) +2022-11-14 14:08:18,935 Epoch: [153][280/500] Time 0.051 (0.033) Data 0.002 (0.003) Loss 0.0493 (0.0536) Prec@1 90.000 (90.586) Prec@5 100.000 (99.552) +2022-11-14 14:08:19,403 Epoch: [153][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0821 (0.0545) Prec@1 84.000 (90.367) Prec@5 100.000 (99.567) +2022-11-14 14:08:19,865 Epoch: [153][300/500] Time 0.045 (0.033) Data 0.001 (0.003) Loss 0.0661 (0.0549) Prec@1 89.000 (90.323) Prec@5 99.000 (99.548) +2022-11-14 14:08:20,483 Epoch: [153][310/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0529 (0.0549) Prec@1 91.000 (90.344) Prec@5 100.000 (99.562) +2022-11-14 14:08:21,076 Epoch: [153][320/500] Time 0.096 (0.035) Data 0.003 (0.003) Loss 0.0594 (0.0550) Prec@1 89.000 (90.303) Prec@5 98.000 (99.515) +2022-11-14 14:08:21,755 Epoch: [153][330/500] Time 0.068 (0.035) Data 0.002 (0.003) Loss 0.0429 (0.0546) Prec@1 91.000 (90.324) Prec@5 99.000 (99.500) +2022-11-14 14:08:22,369 Epoch: [153][340/500] Time 0.071 (0.036) Data 0.002 (0.003) Loss 0.0473 (0.0544) Prec@1 92.000 (90.371) Prec@5 100.000 (99.514) +2022-11-14 14:08:23,025 Epoch: [153][350/500] Time 0.072 (0.037) Data 0.002 (0.003) Loss 0.0617 (0.0546) Prec@1 90.000 (90.361) Prec@5 99.000 (99.500) +2022-11-14 14:08:23,678 Epoch: [153][360/500] Time 0.059 (0.037) Data 0.002 (0.003) Loss 0.0563 (0.0547) Prec@1 89.000 (90.324) Prec@5 99.000 (99.486) +2022-11-14 14:08:24,570 Epoch: [153][370/500] Time 0.101 (0.038) Data 0.002 (0.003) Loss 0.0485 (0.0545) Prec@1 92.000 (90.368) Prec@5 100.000 (99.500) +2022-11-14 14:08:25,293 Epoch: [153][380/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0657 (0.0548) Prec@1 87.000 (90.282) Prec@5 100.000 (99.513) +2022-11-14 14:08:25,779 Epoch: [153][390/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0658 (0.0551) Prec@1 88.000 (90.225) Prec@5 99.000 (99.500) +2022-11-14 14:08:26,326 Epoch: [153][400/500] Time 0.082 (0.039) Data 0.002 (0.003) Loss 0.0618 (0.0552) Prec@1 88.000 (90.171) Prec@5 100.000 (99.512) +2022-11-14 14:08:27,065 Epoch: [153][410/500] Time 0.088 (0.040) Data 0.002 (0.003) Loss 0.0482 (0.0551) Prec@1 92.000 (90.214) Prec@5 100.000 (99.524) +2022-11-14 14:08:27,670 Epoch: [153][420/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0472 (0.0549) Prec@1 92.000 (90.256) Prec@5 100.000 (99.535) +2022-11-14 14:08:28,153 Epoch: [153][430/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0357 (0.0545) Prec@1 93.000 (90.318) Prec@5 100.000 (99.545) +2022-11-14 14:08:28,638 Epoch: [153][440/500] Time 0.050 (0.041) Data 0.002 (0.002) Loss 0.0575 (0.0545) Prec@1 94.000 (90.400) Prec@5 100.000 (99.556) +2022-11-14 14:08:29,160 Epoch: [153][450/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0429 (0.0543) Prec@1 93.000 (90.457) Prec@5 100.000 (99.565) +2022-11-14 14:08:29,769 Epoch: [153][460/500] Time 0.070 (0.041) Data 0.002 (0.002) Loss 0.0403 (0.0540) Prec@1 95.000 (90.553) Prec@5 98.000 (99.532) +2022-11-14 14:08:30,391 Epoch: [153][470/500] Time 0.074 (0.041) Data 0.002 (0.002) Loss 0.0603 (0.0541) Prec@1 89.000 (90.521) Prec@5 100.000 (99.542) +2022-11-14 14:08:31,194 Epoch: [153][480/500] Time 0.089 (0.042) Data 0.002 (0.002) Loss 0.0439 (0.0539) Prec@1 93.000 (90.571) Prec@5 100.000 (99.551) +2022-11-14 14:08:31,794 Epoch: [153][490/500] Time 0.038 (0.042) Data 0.002 (0.002) Loss 0.0685 (0.0542) Prec@1 89.000 (90.540) Prec@5 100.000 (99.560) +2022-11-14 14:08:32,090 Epoch: [153][499/500] Time 0.030 (0.042) Data 0.002 (0.002) Loss 0.0482 (0.0541) Prec@1 91.000 (90.549) Prec@5 100.000 (99.569) +2022-11-14 14:08:32,414 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0800 (0.0800) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:08:32,426 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0732 (0.0766) Prec@1 86.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 14:08:32,438 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0879 (0.0804) Prec@1 85.000 (86.333) Prec@5 100.000 (99.667) +2022-11-14 14:08:32,461 Test: [3/100] Model Time 0.015 (0.012) Loss Time 0.000 (0.000) Loss 0.0914 (0.0831) Prec@1 84.000 (85.750) Prec@5 98.000 (99.250) +2022-11-14 14:08:32,476 Test: [4/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0892 (0.0844) Prec@1 85.000 (85.600) Prec@5 100.000 (99.400) +2022-11-14 14:08:32,489 Test: [5/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0470 (0.0781) Prec@1 90.000 (86.333) Prec@5 99.000 (99.333) +2022-11-14 14:08:32,502 Test: [6/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0650 (0.0763) Prec@1 90.000 (86.857) Prec@5 100.000 (99.429) +2022-11-14 14:08:32,519 Test: [7/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.1180 (0.0815) Prec@1 80.000 (86.000) Prec@5 98.000 (99.250) +2022-11-14 14:08:32,536 Test: [8/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0982 (0.0833) Prec@1 84.000 (85.778) Prec@5 99.000 (99.222) +2022-11-14 14:08:32,550 Test: [9/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0701 (0.0820) Prec@1 89.000 (86.100) Prec@5 98.000 (99.100) +2022-11-14 14:08:32,565 Test: [10/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0679 (0.0807) Prec@1 88.000 (86.273) Prec@5 100.000 (99.182) +2022-11-14 14:08:32,578 Test: [11/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0785 (0.0805) Prec@1 86.000 (86.250) Prec@5 100.000 (99.250) +2022-11-14 14:08:32,589 Test: [12/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0639 (0.0793) Prec@1 88.000 (86.385) Prec@5 100.000 (99.308) +2022-11-14 14:08:32,599 Test: [13/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0725 (0.0788) Prec@1 88.000 (86.500) Prec@5 100.000 (99.357) +2022-11-14 14:08:32,609 Test: [14/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0672 (0.0780) Prec@1 88.000 (86.600) Prec@5 99.000 (99.333) +2022-11-14 14:08:32,623 Test: [15/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0934 (0.0790) Prec@1 84.000 (86.438) Prec@5 100.000 (99.375) +2022-11-14 14:08:32,635 Test: [16/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0536 (0.0775) Prec@1 90.000 (86.647) Prec@5 98.000 (99.294) +2022-11-14 14:08:32,647 Test: [17/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0989 (0.0787) Prec@1 83.000 (86.444) Prec@5 98.000 (99.222) +2022-11-14 14:08:32,658 Test: [18/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1082 (0.0802) Prec@1 83.000 (86.263) Prec@5 98.000 (99.158) +2022-11-14 14:08:32,669 Test: [19/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0950 (0.0810) Prec@1 82.000 (86.050) Prec@5 97.000 (99.050) +2022-11-14 14:08:32,681 Test: [20/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0929 (0.0815) Prec@1 83.000 (85.905) Prec@5 98.000 (99.000) +2022-11-14 14:08:32,695 Test: [21/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1007 (0.0824) Prec@1 82.000 (85.727) Prec@5 100.000 (99.045) +2022-11-14 14:08:32,710 Test: [22/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0852 (0.0825) Prec@1 85.000 (85.696) Prec@5 98.000 (99.000) +2022-11-14 14:08:32,722 Test: [23/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0936 (0.0830) Prec@1 85.000 (85.667) Prec@5 99.000 (99.000) +2022-11-14 14:08:32,733 Test: [24/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0681 (0.0824) Prec@1 89.000 (85.800) Prec@5 100.000 (99.040) +2022-11-14 14:08:32,744 Test: [25/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1156 (0.0837) Prec@1 79.000 (85.538) Prec@5 97.000 (98.962) +2022-11-14 14:08:32,756 Test: [26/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0803 (0.0835) Prec@1 85.000 (85.519) Prec@5 100.000 (99.000) +2022-11-14 14:08:32,771 Test: [27/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0909 (0.0838) Prec@1 85.000 (85.500) Prec@5 100.000 (99.036) +2022-11-14 14:08:32,786 Test: [28/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0844 (0.0838) Prec@1 82.000 (85.379) Prec@5 100.000 (99.069) +2022-11-14 14:08:32,801 Test: [29/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0928 (0.0841) Prec@1 82.000 (85.267) Prec@5 100.000 (99.100) +2022-11-14 14:08:32,813 Test: [30/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0576 (0.0833) Prec@1 90.000 (85.419) Prec@5 100.000 (99.129) +2022-11-14 14:08:32,823 Test: [31/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0711 (0.0829) Prec@1 86.000 (85.438) Prec@5 100.000 (99.156) +2022-11-14 14:08:32,834 Test: [32/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0991 (0.0834) Prec@1 81.000 (85.303) Prec@5 99.000 (99.152) +2022-11-14 14:08:32,846 Test: [33/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0891 (0.0835) Prec@1 82.000 (85.206) Prec@5 99.000 (99.147) +2022-11-14 14:08:32,857 Test: [34/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0778 (0.0834) Prec@1 86.000 (85.229) Prec@5 100.000 (99.171) +2022-11-14 14:08:32,868 Test: [35/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0831 (0.0834) Prec@1 85.000 (85.222) Prec@5 98.000 (99.139) +2022-11-14 14:08:32,879 Test: [36/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0810 (0.0833) Prec@1 87.000 (85.270) Prec@5 100.000 (99.162) +2022-11-14 14:08:32,890 Test: [37/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0940 (0.0836) Prec@1 83.000 (85.211) Prec@5 100.000 (99.184) +2022-11-14 14:08:32,902 Test: [38/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0670 (0.0832) Prec@1 89.000 (85.308) Prec@5 99.000 (99.179) +2022-11-14 14:08:32,913 Test: [39/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0752 (0.0830) Prec@1 88.000 (85.375) Prec@5 99.000 (99.175) +2022-11-14 14:08:32,924 Test: [40/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0879 (0.0831) Prec@1 87.000 (85.415) Prec@5 98.000 (99.146) +2022-11-14 14:08:32,937 Test: [41/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0860 (0.0832) Prec@1 86.000 (85.429) Prec@5 100.000 (99.167) +2022-11-14 14:08:32,950 Test: [42/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0714 (0.0829) Prec@1 86.000 (85.442) Prec@5 100.000 (99.186) +2022-11-14 14:08:32,963 Test: [43/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0808 (0.0828) Prec@1 85.000 (85.432) Prec@5 98.000 (99.159) +2022-11-14 14:08:32,976 Test: [44/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0771 (0.0827) Prec@1 87.000 (85.467) Prec@5 100.000 (99.178) +2022-11-14 14:08:32,989 Test: [45/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1208 (0.0835) Prec@1 78.000 (85.304) Prec@5 99.000 (99.174) +2022-11-14 14:08:33,002 Test: [46/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0811 (0.0835) Prec@1 87.000 (85.340) Prec@5 100.000 (99.191) +2022-11-14 14:08:33,013 Test: [47/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0988 (0.0838) Prec@1 83.000 (85.292) Prec@5 98.000 (99.167) +2022-11-14 14:08:33,024 Test: [48/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0489 (0.0831) Prec@1 93.000 (85.449) Prec@5 100.000 (99.184) +2022-11-14 14:08:33,035 Test: [49/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1143 (0.0837) Prec@1 84.000 (85.420) Prec@5 100.000 (99.200) +2022-11-14 14:08:33,045 Test: [50/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0558 (0.0832) Prec@1 89.000 (85.490) Prec@5 100.000 (99.216) +2022-11-14 14:08:33,055 Test: [51/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.0832) Prec@1 88.000 (85.538) Prec@5 100.000 (99.231) +2022-11-14 14:08:33,066 Test: [52/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0894 (0.0833) Prec@1 85.000 (85.528) Prec@5 100.000 (99.245) +2022-11-14 14:08:33,077 Test: [53/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0817 (0.0832) Prec@1 88.000 (85.574) Prec@5 98.000 (99.222) +2022-11-14 14:08:33,087 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0926 (0.0834) Prec@1 84.000 (85.545) Prec@5 100.000 (99.236) +2022-11-14 14:08:33,098 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0832) Prec@1 90.000 (85.625) Prec@5 99.000 (99.232) +2022-11-14 14:08:33,109 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0831) Prec@1 87.000 (85.649) Prec@5 100.000 (99.246) +2022-11-14 14:08:33,119 Test: [57/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0826) Prec@1 90.000 (85.724) Prec@5 100.000 (99.259) +2022-11-14 14:08:33,128 Test: [58/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1155 (0.0832) Prec@1 82.000 (85.661) Prec@5 100.000 (99.271) +2022-11-14 14:08:33,138 Test: [59/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0828) Prec@1 87.000 (85.683) Prec@5 100.000 (99.283) +2022-11-14 14:08:33,147 Test: [60/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0921 (0.0830) Prec@1 86.000 (85.689) Prec@5 100.000 (99.295) +2022-11-14 14:08:33,158 Test: [61/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0830) Prec@1 86.000 (85.694) Prec@5 100.000 (99.306) +2022-11-14 14:08:33,168 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0625 (0.0826) Prec@1 89.000 (85.746) Prec@5 100.000 (99.317) +2022-11-14 14:08:33,180 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0531 (0.0822) Prec@1 91.000 (85.828) Prec@5 100.000 (99.328) +2022-11-14 14:08:33,191 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1028 (0.0825) Prec@1 87.000 (85.846) Prec@5 98.000 (99.308) +2022-11-14 14:08:33,203 Test: [65/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0916 (0.0826) Prec@1 81.000 (85.773) Prec@5 99.000 (99.303) +2022-11-14 14:08:33,214 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0634 (0.0823) Prec@1 89.000 (85.821) Prec@5 99.000 (99.299) +2022-11-14 14:08:33,225 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0823) Prec@1 88.000 (85.853) Prec@5 98.000 (99.279) +2022-11-14 14:08:33,237 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0824) Prec@1 85.000 (85.841) Prec@5 100.000 (99.290) +2022-11-14 14:08:33,248 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1059 (0.0827) Prec@1 80.000 (85.757) Prec@5 100.000 (99.300) +2022-11-14 14:08:33,259 Test: [70/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0974 (0.0829) Prec@1 85.000 (85.746) Prec@5 98.000 (99.282) +2022-11-14 14:08:33,269 Test: [71/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0829) Prec@1 83.000 (85.708) Prec@5 100.000 (99.292) +2022-11-14 14:08:33,279 Test: [72/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0582 (0.0826) Prec@1 90.000 (85.767) Prec@5 99.000 (99.288) +2022-11-14 14:08:33,288 Test: [73/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0842 (0.0826) Prec@1 83.000 (85.730) Prec@5 100.000 (99.297) +2022-11-14 14:08:33,298 Test: [74/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1216 (0.0831) Prec@1 79.000 (85.640) Prec@5 99.000 (99.293) +2022-11-14 14:08:33,308 Test: [75/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0830) Prec@1 86.000 (85.645) Prec@5 100.000 (99.303) +2022-11-14 14:08:33,318 Test: [76/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0828) Prec@1 88.000 (85.675) Prec@5 100.000 (99.312) +2022-11-14 14:08:33,329 Test: [77/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0829) Prec@1 86.000 (85.679) Prec@5 96.000 (99.269) +2022-11-14 14:08:33,339 Test: [78/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0831) Prec@1 84.000 (85.658) Prec@5 100.000 (99.278) +2022-11-14 14:08:33,349 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0831) Prec@1 86.000 (85.662) Prec@5 99.000 (99.275) +2022-11-14 14:08:33,358 Test: [80/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0831) Prec@1 85.000 (85.654) Prec@5 99.000 (99.272) +2022-11-14 14:08:33,367 Test: [81/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0642 (0.0829) Prec@1 87.000 (85.671) Prec@5 99.000 (99.268) +2022-11-14 14:08:33,377 Test: [82/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0828) Prec@1 84.000 (85.651) Prec@5 100.000 (99.277) +2022-11-14 14:08:33,385 Test: [83/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0829) Prec@1 83.000 (85.619) Prec@5 98.000 (99.262) +2022-11-14 14:08:33,394 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1210 (0.0834) Prec@1 82.000 (85.576) Prec@5 99.000 (99.259) +2022-11-14 14:08:33,403 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1028 (0.0836) Prec@1 85.000 (85.570) Prec@5 100.000 (99.267) +2022-11-14 14:08:33,413 Test: [86/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0835) Prec@1 87.000 (85.586) Prec@5 99.000 (99.264) +2022-11-14 14:08:33,423 Test: [87/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0834) Prec@1 88.000 (85.614) Prec@5 98.000 (99.250) +2022-11-14 14:08:33,433 Test: [88/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0836) Prec@1 84.000 (85.596) Prec@5 98.000 (99.236) +2022-11-14 14:08:33,441 Test: [89/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0834) Prec@1 91.000 (85.656) Prec@5 100.000 (99.244) +2022-11-14 14:08:33,449 Test: [90/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0832) Prec@1 89.000 (85.692) Prec@5 100.000 (99.253) +2022-11-14 14:08:33,458 Test: [91/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0829) Prec@1 88.000 (85.717) Prec@5 100.000 (99.261) +2022-11-14 14:08:33,467 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0831) Prec@1 83.000 (85.688) Prec@5 100.000 (99.269) +2022-11-14 14:08:33,477 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0833) Prec@1 82.000 (85.649) Prec@5 99.000 (99.266) +2022-11-14 14:08:33,486 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0832) Prec@1 87.000 (85.663) Prec@5 100.000 (99.274) +2022-11-14 14:08:33,495 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0830) Prec@1 92.000 (85.729) Prec@5 99.000 (99.271) +2022-11-14 14:08:33,502 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0410 (0.0826) Prec@1 93.000 (85.804) Prec@5 100.000 (99.278) +2022-11-14 14:08:33,511 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0826) Prec@1 86.000 (85.806) Prec@5 98.000 (99.265) +2022-11-14 14:08:33,520 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0829) Prec@1 83.000 (85.778) Prec@5 99.000 (99.263) +2022-11-14 14:08:33,528 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0828) Prec@1 85.000 (85.770) Prec@5 99.000 (99.260) +2022-11-14 14:08:33,585 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:08:33,900 Epoch: [154][0/500] Time 0.030 (0.030) Data 0.228 (0.228) Loss 0.0307 (0.0307) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:34,166 Epoch: [154][10/500] Time 0.033 (0.024) Data 0.003 (0.023) Loss 0.0784 (0.0546) Prec@1 85.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:34,547 Epoch: [154][20/500] Time 0.034 (0.029) Data 0.002 (0.013) Loss 0.0695 (0.0595) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:34,907 Epoch: [154][30/500] Time 0.032 (0.030) Data 0.002 (0.010) Loss 0.0472 (0.0565) Prec@1 93.000 (90.750) Prec@5 100.000 (100.000) +2022-11-14 14:08:35,215 Epoch: [154][40/500] Time 0.025 (0.029) Data 0.002 (0.008) Loss 0.0685 (0.0589) Prec@1 87.000 (90.000) Prec@5 99.000 (99.800) +2022-11-14 14:08:35,530 Epoch: [154][50/500] Time 0.032 (0.029) Data 0.003 (0.007) Loss 0.0640 (0.0597) Prec@1 90.000 (90.000) Prec@5 100.000 (99.833) +2022-11-14 14:08:35,860 Epoch: [154][60/500] Time 0.030 (0.029) Data 0.002 (0.006) Loss 0.0742 (0.0618) Prec@1 85.000 (89.286) Prec@5 99.000 (99.714) +2022-11-14 14:08:36,219 Epoch: [154][70/500] Time 0.036 (0.029) Data 0.002 (0.005) Loss 0.0588 (0.0614) Prec@1 91.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 14:08:36,562 Epoch: [154][80/500] Time 0.030 (0.029) Data 0.002 (0.005) Loss 0.0558 (0.0608) Prec@1 91.000 (89.667) Prec@5 99.000 (99.444) +2022-11-14 14:08:36,963 Epoch: [154][90/500] Time 0.039 (0.030) Data 0.002 (0.005) Loss 0.0982 (0.0645) Prec@1 85.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 14:08:37,335 Epoch: [154][100/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0396 (0.0623) Prec@1 93.000 (89.545) Prec@5 100.000 (99.455) +2022-11-14 14:08:37,740 Epoch: [154][110/500] Time 0.039 (0.031) Data 0.002 (0.004) Loss 0.0561 (0.0618) Prec@1 92.000 (89.750) Prec@5 99.000 (99.417) +2022-11-14 14:08:38,094 Epoch: [154][120/500] Time 0.028 (0.031) Data 0.002 (0.004) Loss 0.0627 (0.0618) Prec@1 90.000 (89.769) Prec@5 100.000 (99.462) +2022-11-14 14:08:38,463 Epoch: [154][130/500] Time 0.041 (0.031) Data 0.002 (0.004) Loss 0.0499 (0.0610) Prec@1 90.000 (89.786) Prec@5 100.000 (99.500) +2022-11-14 14:08:38,817 Epoch: [154][140/500] Time 0.031 (0.031) Data 0.002 (0.004) Loss 0.0638 (0.0612) Prec@1 90.000 (89.800) Prec@5 100.000 (99.533) +2022-11-14 14:08:39,202 Epoch: [154][150/500] Time 0.041 (0.031) Data 0.002 (0.004) Loss 0.0750 (0.0620) Prec@1 87.000 (89.625) Prec@5 97.000 (99.375) +2022-11-14 14:08:39,604 Epoch: [154][160/500] Time 0.036 (0.032) Data 0.003 (0.003) Loss 0.0469 (0.0611) Prec@1 93.000 (89.824) Prec@5 100.000 (99.412) +2022-11-14 14:08:40,015 Epoch: [154][170/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0720 (0.0617) Prec@1 88.000 (89.722) Prec@5 99.000 (99.389) +2022-11-14 14:08:40,522 Epoch: [154][180/500] Time 0.074 (0.033) Data 0.002 (0.003) Loss 0.0471 (0.0610) Prec@1 95.000 (90.000) Prec@5 100.000 (99.421) +2022-11-14 14:08:41,058 Epoch: [154][190/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0540 (0.0606) Prec@1 91.000 (90.050) Prec@5 98.000 (99.350) +2022-11-14 14:08:41,587 Epoch: [154][200/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0517 (0.0602) Prec@1 91.000 (90.095) Prec@5 99.000 (99.333) +2022-11-14 14:08:42,075 Epoch: [154][210/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0623 (0.0603) Prec@1 90.000 (90.091) Prec@5 100.000 (99.364) +2022-11-14 14:08:42,594 Epoch: [154][220/500] Time 0.060 (0.035) Data 0.002 (0.003) Loss 0.0463 (0.0597) Prec@1 93.000 (90.217) Prec@5 99.000 (99.348) +2022-11-14 14:08:43,109 Epoch: [154][230/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0705 (0.0601) Prec@1 89.000 (90.167) Prec@5 99.000 (99.333) +2022-11-14 14:08:43,644 Epoch: [154][240/500] Time 0.069 (0.036) Data 0.002 (0.003) Loss 0.0450 (0.0595) Prec@1 93.000 (90.280) Prec@5 100.000 (99.360) +2022-11-14 14:08:44,181 Epoch: [154][250/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0343 (0.0586) Prec@1 94.000 (90.423) Prec@5 99.000 (99.346) +2022-11-14 14:08:44,796 Epoch: [154][260/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0423 (0.0580) Prec@1 92.000 (90.481) Prec@5 100.000 (99.370) +2022-11-14 14:08:45,291 Epoch: [154][270/500] Time 0.057 (0.037) Data 0.002 (0.003) Loss 0.0606 (0.0581) Prec@1 91.000 (90.500) Prec@5 97.000 (99.286) +2022-11-14 14:08:45,769 Epoch: [154][280/500] Time 0.048 (0.038) Data 0.002 (0.003) Loss 0.0687 (0.0584) Prec@1 89.000 (90.448) Prec@5 100.000 (99.310) +2022-11-14 14:08:46,256 Epoch: [154][290/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0507 (0.0582) Prec@1 92.000 (90.500) Prec@5 100.000 (99.333) +2022-11-14 14:08:47,067 Epoch: [154][300/500] Time 0.069 (0.039) Data 0.002 (0.003) Loss 0.0408 (0.0576) Prec@1 94.000 (90.613) Prec@5 100.000 (99.355) +2022-11-14 14:08:47,685 Epoch: [154][310/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0835 (0.0584) Prec@1 88.000 (90.531) Prec@5 100.000 (99.375) +2022-11-14 14:08:48,176 Epoch: [154][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0612 (0.0585) Prec@1 88.000 (90.455) Prec@5 100.000 (99.394) +2022-11-14 14:08:48,653 Epoch: [154][330/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0527 (0.0583) Prec@1 92.000 (90.500) Prec@5 98.000 (99.353) +2022-11-14 14:08:49,236 Epoch: [154][340/500] Time 0.087 (0.040) Data 0.002 (0.003) Loss 0.0689 (0.0586) Prec@1 89.000 (90.457) Prec@5 100.000 (99.371) +2022-11-14 14:08:50,041 Epoch: [154][350/500] Time 0.077 (0.041) Data 0.002 (0.003) Loss 0.0388 (0.0581) Prec@1 94.000 (90.556) Prec@5 100.000 (99.389) +2022-11-14 14:08:50,843 Epoch: [154][360/500] Time 0.077 (0.042) Data 0.002 (0.003) Loss 0.0641 (0.0582) Prec@1 90.000 (90.541) Prec@5 99.000 (99.378) +2022-11-14 14:08:51,552 Epoch: [154][370/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0697 (0.0585) Prec@1 90.000 (90.526) Prec@5 100.000 (99.395) +2022-11-14 14:08:52,248 Epoch: [154][380/500] Time 0.074 (0.043) Data 0.002 (0.003) Loss 0.0384 (0.0580) Prec@1 95.000 (90.641) Prec@5 100.000 (99.410) +2022-11-14 14:08:52,803 Epoch: [154][390/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0659 (0.0582) Prec@1 90.000 (90.625) Prec@5 99.000 (99.400) +2022-11-14 14:08:53,292 Epoch: [154][400/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0392 (0.0578) Prec@1 94.000 (90.707) Prec@5 99.000 (99.390) +2022-11-14 14:08:53,772 Epoch: [154][410/500] Time 0.049 (0.043) Data 0.003 (0.003) Loss 0.0573 (0.0577) Prec@1 91.000 (90.714) Prec@5 100.000 (99.405) +2022-11-14 14:08:54,260 Epoch: [154][420/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0638 (0.0579) Prec@1 90.000 (90.698) Prec@5 100.000 (99.419) +2022-11-14 14:08:54,903 Epoch: [154][430/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0623 (0.0580) Prec@1 88.000 (90.636) Prec@5 100.000 (99.432) +2022-11-14 14:08:55,452 Epoch: [154][440/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0860 (0.0586) Prec@1 85.000 (90.511) Prec@5 99.000 (99.422) +2022-11-14 14:08:55,960 Epoch: [154][450/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0287 (0.0580) Prec@1 96.000 (90.630) Prec@5 100.000 (99.435) +2022-11-14 14:08:56,375 Epoch: [154][460/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0511 (0.0578) Prec@1 90.000 (90.617) Prec@5 100.000 (99.447) +2022-11-14 14:08:56,713 Epoch: [154][470/500] Time 0.029 (0.043) Data 0.002 (0.003) Loss 0.0556 (0.0578) Prec@1 90.000 (90.604) Prec@5 99.000 (99.438) +2022-11-14 14:08:57,053 Epoch: [154][480/500] Time 0.035 (0.043) Data 0.002 (0.003) Loss 0.0568 (0.0577) Prec@1 92.000 (90.633) Prec@5 100.000 (99.449) +2022-11-14 14:08:57,395 Epoch: [154][490/500] Time 0.041 (0.043) Data 0.002 (0.002) Loss 0.0635 (0.0579) Prec@1 89.000 (90.600) Prec@5 100.000 (99.460) +2022-11-14 14:08:57,696 Epoch: [154][499/500] Time 0.036 (0.043) Data 0.001 (0.002) Loss 0.0622 (0.0579) Prec@1 90.000 (90.588) Prec@5 99.000 (99.451) +2022-11-14 14:08:57,993 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0570 (0.0570) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:58,002 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0662) Prec@1 89.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:08:58,010 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0772) Prec@1 81.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:08:58,022 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0760) Prec@1 91.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:08:58,032 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0761) Prec@1 87.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 14:08:58,041 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0730) Prec@1 88.000 (87.833) Prec@5 100.000 (99.500) +2022-11-14 14:08:58,049 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0734) Prec@1 88.000 (87.857) Prec@5 99.000 (99.429) +2022-11-14 14:08:58,063 Test: [7/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0788) Prec@1 78.000 (86.625) Prec@5 99.000 (99.375) +2022-11-14 14:08:58,073 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0810) Prec@1 83.000 (86.222) Prec@5 99.000 (99.333) +2022-11-14 14:08:58,082 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0801) Prec@1 90.000 (86.600) Prec@5 97.000 (99.100) +2022-11-14 14:08:58,092 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0775) Prec@1 92.000 (87.091) Prec@5 100.000 (99.182) +2022-11-14 14:08:58,104 Test: [11/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0770) Prec@1 89.000 (87.250) Prec@5 98.000 (99.083) +2022-11-14 14:08:58,116 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0756) Prec@1 91.000 (87.538) Prec@5 100.000 (99.154) +2022-11-14 14:08:58,126 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0761) Prec@1 88.000 (87.571) Prec@5 99.000 (99.143) +2022-11-14 14:08:58,136 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0768) Prec@1 86.000 (87.467) Prec@5 99.000 (99.133) +2022-11-14 14:08:58,149 Test: [15/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0768) Prec@1 86.000 (87.375) Prec@5 99.000 (99.125) +2022-11-14 14:08:58,161 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0756) Prec@1 91.000 (87.588) Prec@5 96.000 (98.941) +2022-11-14 14:08:58,172 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0769) Prec@1 83.000 (87.333) Prec@5 100.000 (99.000) +2022-11-14 14:08:58,183 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0769) Prec@1 86.000 (87.263) Prec@5 99.000 (99.000) +2022-11-14 14:08:58,196 Test: [19/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0783) Prec@1 83.000 (87.050) Prec@5 97.000 (98.900) +2022-11-14 14:08:58,208 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0783) Prec@1 89.000 (87.143) Prec@5 98.000 (98.857) +2022-11-14 14:08:58,218 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0790) Prec@1 84.000 (87.000) Prec@5 99.000 (98.864) +2022-11-14 14:08:58,227 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1248 (0.0810) Prec@1 79.000 (86.652) Prec@5 98.000 (98.826) +2022-11-14 14:08:58,241 Test: [23/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0806) Prec@1 87.000 (86.667) Prec@5 99.000 (98.833) +2022-11-14 14:08:58,253 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0809) Prec@1 87.000 (86.680) Prec@5 100.000 (98.880) +2022-11-14 14:08:58,264 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0816) Prec@1 84.000 (86.577) Prec@5 99.000 (98.885) +2022-11-14 14:08:58,274 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0803) Prec@1 92.000 (86.778) Prec@5 100.000 (98.926) +2022-11-14 14:08:58,287 Test: [27/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0809) Prec@1 84.000 (86.679) Prec@5 100.000 (98.964) +2022-11-14 14:08:58,298 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0804) Prec@1 89.000 (86.759) Prec@5 100.000 (99.000) +2022-11-14 14:08:58,306 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0801) Prec@1 88.000 (86.800) Prec@5 98.000 (98.967) +2022-11-14 14:08:58,316 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0802) Prec@1 87.000 (86.806) Prec@5 100.000 (99.000) +2022-11-14 14:08:58,327 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0802) Prec@1 86.000 (86.781) Prec@5 99.000 (99.000) +2022-11-14 14:08:58,338 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0804) Prec@1 84.000 (86.697) Prec@5 99.000 (99.000) +2022-11-14 14:08:58,348 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0807) Prec@1 82.000 (86.559) Prec@5 98.000 (98.971) +2022-11-14 14:08:58,358 Test: [34/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0812) Prec@1 83.000 (86.457) Prec@5 96.000 (98.886) +2022-11-14 14:08:58,368 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0813) Prec@1 88.000 (86.500) Prec@5 99.000 (98.889) +2022-11-14 14:08:58,377 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0814) Prec@1 86.000 (86.486) Prec@5 98.000 (98.865) +2022-11-14 14:08:58,387 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0816) Prec@1 85.000 (86.447) Prec@5 100.000 (98.895) +2022-11-14 14:08:58,396 Test: [38/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0812) Prec@1 90.000 (86.538) Prec@5 99.000 (98.897) +2022-11-14 14:08:58,405 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0812) Prec@1 85.000 (86.500) Prec@5 98.000 (98.875) +2022-11-14 14:08:58,415 Test: [40/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0816) Prec@1 83.000 (86.415) Prec@5 98.000 (98.854) +2022-11-14 14:08:58,424 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0816) Prec@1 89.000 (86.476) Prec@5 98.000 (98.833) +2022-11-14 14:08:58,432 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0812) Prec@1 88.000 (86.512) Prec@5 100.000 (98.860) +2022-11-14 14:08:58,440 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0812) Prec@1 86.000 (86.500) Prec@5 98.000 (98.841) +2022-11-14 14:08:58,449 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0809) Prec@1 87.000 (86.511) Prec@5 99.000 (98.844) +2022-11-14 14:08:58,459 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1219 (0.0818) Prec@1 78.000 (86.326) Prec@5 99.000 (98.848) +2022-11-14 14:08:58,468 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0819) Prec@1 83.000 (86.255) Prec@5 100.000 (98.872) +2022-11-14 14:08:58,477 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0821) Prec@1 84.000 (86.208) Prec@5 98.000 (98.854) +2022-11-14 14:08:58,485 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0817) Prec@1 90.000 (86.286) Prec@5 100.000 (98.878) +2022-11-14 14:08:58,494 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1237 (0.0826) Prec@1 80.000 (86.160) Prec@5 99.000 (98.880) +2022-11-14 14:08:58,503 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0825) Prec@1 84.000 (86.118) Prec@5 100.000 (98.902) +2022-11-14 14:08:58,512 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0825) Prec@1 86.000 (86.115) Prec@5 99.000 (98.904) +2022-11-14 14:08:58,521 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0825) Prec@1 85.000 (86.094) Prec@5 100.000 (98.925) +2022-11-14 14:08:58,529 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0824) Prec@1 86.000 (86.093) Prec@5 99.000 (98.926) +2022-11-14 14:08:58,538 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0828) Prec@1 81.000 (86.000) Prec@5 100.000 (98.945) +2022-11-14 14:08:58,548 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0825) Prec@1 88.000 (86.036) Prec@5 99.000 (98.946) +2022-11-14 14:08:58,557 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0825) Prec@1 87.000 (86.053) Prec@5 100.000 (98.965) +2022-11-14 14:08:58,566 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0823) Prec@1 89.000 (86.103) Prec@5 99.000 (98.966) +2022-11-14 14:08:58,574 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0825) Prec@1 85.000 (86.085) Prec@5 100.000 (98.983) +2022-11-14 14:08:58,583 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0823) Prec@1 87.000 (86.100) Prec@5 100.000 (99.000) +2022-11-14 14:08:58,593 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0823) Prec@1 87.000 (86.115) Prec@5 99.000 (99.000) +2022-11-14 14:08:58,604 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0823) Prec@1 84.000 (86.081) Prec@5 99.000 (99.000) +2022-11-14 14:08:58,614 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0817) Prec@1 91.000 (86.159) Prec@5 100.000 (99.016) +2022-11-14 14:08:58,624 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0811) Prec@1 93.000 (86.266) Prec@5 100.000 (99.031) +2022-11-14 14:08:58,634 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0813) Prec@1 86.000 (86.262) Prec@5 98.000 (99.015) +2022-11-14 14:08:58,643 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0814) Prec@1 84.000 (86.227) Prec@5 99.000 (99.015) +2022-11-14 14:08:58,652 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0810) Prec@1 91.000 (86.299) Prec@5 100.000 (99.030) +2022-11-14 14:08:58,660 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0811) Prec@1 87.000 (86.309) Prec@5 98.000 (99.015) +2022-11-14 14:08:58,669 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0809) Prec@1 89.000 (86.348) Prec@5 99.000 (99.014) +2022-11-14 14:08:58,679 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0811) Prec@1 82.000 (86.286) Prec@5 100.000 (99.029) +2022-11-14 14:08:58,688 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0813) Prec@1 85.000 (86.268) Prec@5 98.000 (99.014) +2022-11-14 14:08:58,697 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0811) Prec@1 90.000 (86.319) Prec@5 100.000 (99.028) +2022-11-14 14:08:58,705 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0807) Prec@1 93.000 (86.411) Prec@5 99.000 (99.027) +2022-11-14 14:08:58,715 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0805) Prec@1 88.000 (86.432) Prec@5 100.000 (99.041) +2022-11-14 14:08:58,725 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0808) Prec@1 84.000 (86.400) Prec@5 98.000 (99.027) +2022-11-14 14:08:58,735 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0804) Prec@1 90.000 (86.447) Prec@5 100.000 (99.039) +2022-11-14 14:08:58,746 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0805) Prec@1 88.000 (86.468) Prec@5 99.000 (99.039) +2022-11-14 14:08:58,757 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0806) Prec@1 84.000 (86.436) Prec@5 98.000 (99.026) +2022-11-14 14:08:58,767 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0804) Prec@1 92.000 (86.506) Prec@5 100.000 (99.038) +2022-11-14 14:08:58,777 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0803) Prec@1 89.000 (86.537) Prec@5 98.000 (99.025) +2022-11-14 14:08:58,787 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0805) Prec@1 84.000 (86.506) Prec@5 98.000 (99.012) +2022-11-14 14:08:58,798 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0806) Prec@1 81.000 (86.439) Prec@5 99.000 (99.012) +2022-11-14 14:08:58,809 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.0811) Prec@1 79.000 (86.349) Prec@5 100.000 (99.024) +2022-11-14 14:08:58,821 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0811) Prec@1 86.000 (86.345) Prec@5 99.000 (99.024) +2022-11-14 14:08:58,832 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0813) Prec@1 79.000 (86.259) Prec@5 99.000 (99.024) +2022-11-14 14:08:58,843 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0817) Prec@1 81.000 (86.198) Prec@5 100.000 (99.035) +2022-11-14 14:08:58,854 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0817) Prec@1 86.000 (86.195) Prec@5 98.000 (99.023) +2022-11-14 14:08:58,864 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0816) Prec@1 88.000 (86.216) Prec@5 99.000 (99.023) +2022-11-14 14:08:58,876 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0818) Prec@1 81.000 (86.157) Prec@5 100.000 (99.034) +2022-11-14 14:08:58,886 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0818) Prec@1 86.000 (86.156) Prec@5 98.000 (99.022) +2022-11-14 14:08:58,898 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0817) Prec@1 89.000 (86.187) Prec@5 100.000 (99.033) +2022-11-14 14:08:58,908 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0814) Prec@1 91.000 (86.239) Prec@5 100.000 (99.043) +2022-11-14 14:08:58,919 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0815) Prec@1 84.000 (86.215) Prec@5 100.000 (99.054) +2022-11-14 14:08:58,930 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0814) Prec@1 90.000 (86.255) Prec@5 98.000 (99.043) +2022-11-14 14:08:58,940 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0815) Prec@1 86.000 (86.253) Prec@5 98.000 (99.032) +2022-11-14 14:08:58,951 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0814) Prec@1 84.000 (86.229) Prec@5 99.000 (99.031) +2022-11-14 14:08:58,961 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0813) Prec@1 90.000 (86.268) Prec@5 99.000 (99.031) +2022-11-14 14:08:58,971 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0813) Prec@1 88.000 (86.286) Prec@5 99.000 (99.031) +2022-11-14 14:08:58,982 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0814) Prec@1 83.000 (86.253) Prec@5 99.000 (99.030) +2022-11-14 14:08:58,991 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0812) Prec@1 90.000 (86.290) Prec@5 100.000 (99.040) +2022-11-14 14:08:59,067 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:08:59,437 Epoch: [155][0/500] Time 0.029 (0.029) Data 0.281 (0.281) Loss 0.0602 (0.0602) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:08:59,728 Epoch: [155][10/500] Time 0.026 (0.026) Data 0.002 (0.027) Loss 0.0369 (0.0485) Prec@1 94.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:09:00,012 Epoch: [155][20/500] Time 0.026 (0.026) Data 0.002 (0.015) Loss 0.0519 (0.0497) Prec@1 91.000 (91.333) Prec@5 99.000 (99.667) +2022-11-14 14:09:00,344 Epoch: [155][30/500] Time 0.031 (0.027) Data 0.002 (0.011) Loss 0.0427 (0.0479) Prec@1 94.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:09:00,710 Epoch: [155][40/500] Time 0.031 (0.028) Data 0.002 (0.009) Loss 0.0469 (0.0477) Prec@1 92.000 (92.000) Prec@5 100.000 (99.800) +2022-11-14 14:09:01,076 Epoch: [155][50/500] Time 0.032 (0.029) Data 0.002 (0.007) Loss 0.0626 (0.0502) Prec@1 91.000 (91.833) Prec@5 100.000 (99.833) +2022-11-14 14:09:01,464 Epoch: [155][60/500] Time 0.052 (0.030) Data 0.003 (0.007) Loss 0.0571 (0.0512) Prec@1 90.000 (91.571) Prec@5 100.000 (99.857) +2022-11-14 14:09:01,878 Epoch: [155][70/500] Time 0.043 (0.031) Data 0.002 (0.006) Loss 0.0408 (0.0499) Prec@1 92.000 (91.625) Prec@5 100.000 (99.875) +2022-11-14 14:09:02,294 Epoch: [155][80/500] Time 0.038 (0.032) Data 0.002 (0.005) Loss 0.0421 (0.0490) Prec@1 92.000 (91.667) Prec@5 100.000 (99.889) +2022-11-14 14:09:02,672 Epoch: [155][90/500] Time 0.026 (0.032) Data 0.002 (0.005) Loss 0.0298 (0.0471) Prec@1 94.000 (91.900) Prec@5 100.000 (99.900) +2022-11-14 14:09:03,052 Epoch: [155][100/500] Time 0.024 (0.032) Data 0.002 (0.005) Loss 0.0869 (0.0507) Prec@1 86.000 (91.364) Prec@5 98.000 (99.727) +2022-11-14 14:09:03,463 Epoch: [155][110/500] Time 0.026 (0.033) Data 0.002 (0.004) Loss 0.0296 (0.0489) Prec@1 96.000 (91.750) Prec@5 100.000 (99.750) +2022-11-14 14:09:03,813 Epoch: [155][120/500] Time 0.033 (0.033) Data 0.001 (0.004) Loss 0.0470 (0.0488) Prec@1 92.000 (91.769) Prec@5 100.000 (99.769) +2022-11-14 14:09:04,282 Epoch: [155][130/500] Time 0.045 (0.033) Data 0.002 (0.004) Loss 0.0750 (0.0507) Prec@1 87.000 (91.429) Prec@5 98.000 (99.643) +2022-11-14 14:09:04,645 Epoch: [155][140/500] Time 0.053 (0.033) Data 0.002 (0.004) Loss 0.0481 (0.0505) Prec@1 91.000 (91.400) Prec@5 99.000 (99.600) +2022-11-14 14:09:05,093 Epoch: [155][150/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0456 (0.0502) Prec@1 92.000 (91.438) Prec@5 100.000 (99.625) +2022-11-14 14:09:05,568 Epoch: [155][160/500] Time 0.047 (0.034) Data 0.002 (0.004) Loss 0.0514 (0.0503) Prec@1 92.000 (91.471) Prec@5 100.000 (99.647) +2022-11-14 14:09:05,939 Epoch: [155][170/500] Time 0.030 (0.034) Data 0.002 (0.004) Loss 0.0532 (0.0504) Prec@1 91.000 (91.444) Prec@5 100.000 (99.667) +2022-11-14 14:09:06,294 Epoch: [155][180/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0389 (0.0498) Prec@1 93.000 (91.526) Prec@5 100.000 (99.684) +2022-11-14 14:09:06,693 Epoch: [155][190/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0757 (0.0511) Prec@1 88.000 (91.350) Prec@5 100.000 (99.700) +2022-11-14 14:09:07,044 Epoch: [155][200/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0525 (0.0512) Prec@1 91.000 (91.333) Prec@5 100.000 (99.714) +2022-11-14 14:09:07,419 Epoch: [155][210/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.0371 (0.0505) Prec@1 92.000 (91.364) Prec@5 99.000 (99.682) +2022-11-14 14:09:07,769 Epoch: [155][220/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.0581 (0.0509) Prec@1 90.000 (91.304) Prec@5 100.000 (99.696) +2022-11-14 14:09:08,168 Epoch: [155][230/500] Time 0.024 (0.034) Data 0.002 (0.003) Loss 0.0384 (0.0503) Prec@1 94.000 (91.417) Prec@5 99.000 (99.667) +2022-11-14 14:09:08,530 Epoch: [155][240/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0311 (0.0496) Prec@1 94.000 (91.520) Prec@5 100.000 (99.680) +2022-11-14 14:09:08,953 Epoch: [155][250/500] Time 0.059 (0.034) Data 0.002 (0.003) Loss 0.0644 (0.0501) Prec@1 90.000 (91.462) Prec@5 100.000 (99.692) +2022-11-14 14:09:09,476 Epoch: [155][260/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0659 (0.0507) Prec@1 91.000 (91.444) Prec@5 99.000 (99.667) +2022-11-14 14:09:09,951 Epoch: [155][270/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0528 (0.0508) Prec@1 90.000 (91.393) Prec@5 100.000 (99.679) +2022-11-14 14:09:10,423 Epoch: [155][280/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0330 (0.0502) Prec@1 96.000 (91.552) Prec@5 100.000 (99.690) +2022-11-14 14:09:10,909 Epoch: [155][290/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.0501 (0.0502) Prec@1 91.000 (91.533) Prec@5 99.000 (99.667) +2022-11-14 14:09:11,392 Epoch: [155][300/500] Time 0.044 (0.036) Data 0.001 (0.003) Loss 0.0348 (0.0497) Prec@1 94.000 (91.613) Prec@5 100.000 (99.677) +2022-11-14 14:09:11,872 Epoch: [155][310/500] Time 0.044 (0.036) Data 0.001 (0.003) Loss 0.0494 (0.0497) Prec@1 92.000 (91.625) Prec@5 100.000 (99.688) +2022-11-14 14:09:12,338 Epoch: [155][320/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0549 (0.0498) Prec@1 89.000 (91.545) Prec@5 100.000 (99.697) +2022-11-14 14:09:13,063 Epoch: [155][330/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0714 (0.0505) Prec@1 89.000 (91.471) Prec@5 100.000 (99.706) +2022-11-14 14:09:13,658 Epoch: [155][340/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.0522 (0.0505) Prec@1 93.000 (91.514) Prec@5 100.000 (99.714) +2022-11-14 14:09:14,139 Epoch: [155][350/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0402 (0.0502) Prec@1 94.000 (91.583) Prec@5 99.000 (99.694) +2022-11-14 14:09:14,927 Epoch: [155][360/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0600 (0.0505) Prec@1 90.000 (91.541) Prec@5 100.000 (99.703) +2022-11-14 14:09:15,452 Epoch: [155][370/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0799 (0.0513) Prec@1 87.000 (91.421) Prec@5 100.000 (99.711) +2022-11-14 14:09:15,933 Epoch: [155][380/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0381 (0.0509) Prec@1 95.000 (91.513) Prec@5 100.000 (99.718) +2022-11-14 14:09:16,450 Epoch: [155][390/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0560 (0.0511) Prec@1 92.000 (91.525) Prec@5 100.000 (99.725) +2022-11-14 14:09:17,181 Epoch: [155][400/500] Time 0.107 (0.040) Data 0.002 (0.003) Loss 0.0549 (0.0512) Prec@1 91.000 (91.512) Prec@5 100.000 (99.732) +2022-11-14 14:09:17,872 Epoch: [155][410/500] Time 0.076 (0.040) Data 0.002 (0.003) Loss 0.0777 (0.0518) Prec@1 88.000 (91.429) Prec@5 98.000 (99.690) +2022-11-14 14:09:18,501 Epoch: [155][420/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0648 (0.0521) Prec@1 89.000 (91.372) Prec@5 99.000 (99.674) +2022-11-14 14:09:19,031 Epoch: [155][430/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0803 (0.0527) Prec@1 86.000 (91.250) Prec@5 99.000 (99.659) +2022-11-14 14:09:19,523 Epoch: [155][440/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0421 (0.0525) Prec@1 93.000 (91.289) Prec@5 99.000 (99.644) +2022-11-14 14:09:20,221 Epoch: [155][450/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0555 (0.0526) Prec@1 89.000 (91.239) Prec@5 100.000 (99.652) +2022-11-14 14:09:20,690 Epoch: [155][460/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0630 (0.0528) Prec@1 88.000 (91.170) Prec@5 100.000 (99.660) +2022-11-14 14:09:21,161 Epoch: [155][470/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0566 (0.0529) Prec@1 90.000 (91.146) Prec@5 100.000 (99.667) +2022-11-14 14:09:21,631 Epoch: [155][480/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0734 (0.0533) Prec@1 89.000 (91.102) Prec@5 99.000 (99.653) +2022-11-14 14:09:22,103 Epoch: [155][490/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0518 (0.0532) Prec@1 91.000 (91.100) Prec@5 100.000 (99.660) +2022-11-14 14:09:22,552 Epoch: [155][499/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0445 (0.0531) Prec@1 93.000 (91.137) Prec@5 99.000 (99.647) +2022-11-14 14:09:22,845 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0615 (0.0615) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:09:22,862 Test: [1/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0799 (0.0707) Prec@1 86.000 (88.500) Prec@5 97.000 (98.500) +2022-11-14 14:09:22,873 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0898 (0.0771) Prec@1 86.000 (87.667) Prec@5 98.000 (98.333) +2022-11-14 14:09:22,885 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0959 (0.0818) Prec@1 86.000 (87.250) Prec@5 98.000 (98.250) +2022-11-14 14:09:22,895 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0919 (0.0838) Prec@1 87.000 (87.200) Prec@5 100.000 (98.600) +2022-11-14 14:09:22,905 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0742 (0.0822) Prec@1 88.000 (87.333) Prec@5 99.000 (98.667) +2022-11-14 14:09:22,914 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0816) Prec@1 86.000 (87.143) Prec@5 100.000 (98.857) +2022-11-14 14:09:22,924 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0831) Prec@1 82.000 (86.500) Prec@5 97.000 (98.625) +2022-11-14 14:09:22,934 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0830) Prec@1 88.000 (86.667) Prec@5 99.000 (98.667) +2022-11-14 14:09:22,943 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0819) Prec@1 89.000 (86.900) Prec@5 97.000 (98.500) +2022-11-14 14:09:22,952 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0800) Prec@1 91.000 (87.273) Prec@5 100.000 (98.636) +2022-11-14 14:09:22,960 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0808) Prec@1 85.000 (87.083) Prec@5 99.000 (98.667) +2022-11-14 14:09:22,968 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0796) Prec@1 89.000 (87.231) Prec@5 100.000 (98.769) +2022-11-14 14:09:22,977 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0796) Prec@1 86.000 (87.143) Prec@5 100.000 (98.857) +2022-11-14 14:09:22,986 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0793) Prec@1 86.000 (87.067) Prec@5 99.000 (98.867) +2022-11-14 14:09:22,996 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0803) Prec@1 81.000 (86.688) Prec@5 99.000 (98.875) +2022-11-14 14:09:23,006 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0787) Prec@1 90.000 (86.882) Prec@5 99.000 (98.882) +2022-11-14 14:09:23,018 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0802) Prec@1 84.000 (86.722) Prec@5 100.000 (98.944) +2022-11-14 14:09:23,030 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0810) Prec@1 85.000 (86.632) Prec@5 96.000 (98.789) +2022-11-14 14:09:23,041 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0818) Prec@1 85.000 (86.550) Prec@5 98.000 (98.750) +2022-11-14 14:09:23,051 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0828) Prec@1 82.000 (86.333) Prec@5 100.000 (98.810) +2022-11-14 14:09:23,062 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0819) Prec@1 91.000 (86.545) Prec@5 100.000 (98.864) +2022-11-14 14:09:23,072 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0825) Prec@1 86.000 (86.522) Prec@5 97.000 (98.783) +2022-11-14 14:09:23,081 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0823) Prec@1 88.000 (86.583) Prec@5 99.000 (98.792) +2022-11-14 14:09:23,089 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0828) Prec@1 85.000 (86.520) Prec@5 100.000 (98.840) +2022-11-14 14:09:23,099 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0839) Prec@1 81.000 (86.308) Prec@5 97.000 (98.769) +2022-11-14 14:09:23,108 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0836) Prec@1 85.000 (86.259) Prec@5 99.000 (98.778) +2022-11-14 14:09:23,117 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0833) Prec@1 90.000 (86.393) Prec@5 100.000 (98.821) +2022-11-14 14:09:23,126 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0829) Prec@1 87.000 (86.414) Prec@5 100.000 (98.862) +2022-11-14 14:09:23,135 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0834) Prec@1 83.000 (86.300) Prec@5 99.000 (98.867) +2022-11-14 14:09:23,143 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0831) Prec@1 87.000 (86.323) Prec@5 98.000 (98.839) +2022-11-14 14:09:23,153 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0835) Prec@1 82.000 (86.188) Prec@5 100.000 (98.875) +2022-11-14 14:09:23,162 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0833) Prec@1 89.000 (86.273) Prec@5 100.000 (98.909) +2022-11-14 14:09:23,171 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0839) Prec@1 82.000 (86.147) Prec@5 98.000 (98.882) +2022-11-14 14:09:23,181 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0848) Prec@1 81.000 (86.000) Prec@5 97.000 (98.829) +2022-11-14 14:09:23,190 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0849) Prec@1 87.000 (86.028) Prec@5 99.000 (98.833) +2022-11-14 14:09:23,200 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0849) Prec@1 85.000 (86.000) Prec@5 99.000 (98.838) +2022-11-14 14:09:23,210 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.0855) Prec@1 80.000 (85.842) Prec@5 99.000 (98.842) +2022-11-14 14:09:23,220 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0850) Prec@1 89.000 (85.923) Prec@5 98.000 (98.821) +2022-11-14 14:09:23,229 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0849) Prec@1 85.000 (85.900) Prec@5 99.000 (98.825) +2022-11-14 14:09:23,239 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0852) Prec@1 83.000 (85.829) Prec@5 98.000 (98.805) +2022-11-14 14:09:23,249 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0849) Prec@1 88.000 (85.881) Prec@5 99.000 (98.810) +2022-11-14 14:09:23,259 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0843) Prec@1 90.000 (85.977) Prec@5 100.000 (98.837) +2022-11-14 14:09:23,269 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0845) Prec@1 84.000 (85.932) Prec@5 98.000 (98.818) +2022-11-14 14:09:23,278 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0843) Prec@1 89.000 (86.000) Prec@5 100.000 (98.844) +2022-11-14 14:09:23,287 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0848) Prec@1 80.000 (85.870) Prec@5 98.000 (98.826) +2022-11-14 14:09:23,298 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0847) Prec@1 87.000 (85.894) Prec@5 98.000 (98.809) +2022-11-14 14:09:23,307 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0851) Prec@1 83.000 (85.833) Prec@5 100.000 (98.833) +2022-11-14 14:09:23,317 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0844) Prec@1 92.000 (85.959) Prec@5 100.000 (98.857) +2022-11-14 14:09:23,326 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1332 (0.0854) Prec@1 79.000 (85.820) Prec@5 100.000 (98.880) +2022-11-14 14:09:23,335 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0853) Prec@1 84.000 (85.784) Prec@5 98.000 (98.863) +2022-11-14 14:09:23,346 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0853) Prec@1 86.000 (85.788) Prec@5 98.000 (98.846) +2022-11-14 14:09:23,356 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0855) Prec@1 84.000 (85.755) Prec@5 100.000 (98.868) +2022-11-14 14:09:23,367 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0855) Prec@1 87.000 (85.778) Prec@5 98.000 (98.852) +2022-11-14 14:09:23,376 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0857) Prec@1 83.000 (85.727) Prec@5 100.000 (98.873) +2022-11-14 14:09:23,385 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0857) Prec@1 88.000 (85.768) Prec@5 99.000 (98.875) +2022-11-14 14:09:23,396 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0856) Prec@1 87.000 (85.789) Prec@5 99.000 (98.877) +2022-11-14 14:09:23,406 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0854) Prec@1 86.000 (85.793) Prec@5 99.000 (98.879) +2022-11-14 14:09:23,416 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1244 (0.0861) Prec@1 77.000 (85.644) Prec@5 100.000 (98.898) +2022-11-14 14:09:23,425 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0858) Prec@1 89.000 (85.700) Prec@5 100.000 (98.917) +2022-11-14 14:09:23,435 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0860) Prec@1 84.000 (85.672) Prec@5 100.000 (98.934) +2022-11-14 14:09:23,445 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0859) Prec@1 86.000 (85.677) Prec@5 100.000 (98.952) +2022-11-14 14:09:23,455 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0856) Prec@1 87.000 (85.698) Prec@5 100.000 (98.968) +2022-11-14 14:09:23,465 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0852) Prec@1 90.000 (85.766) Prec@5 100.000 (98.984) +2022-11-14 14:09:23,476 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0855) Prec@1 82.000 (85.708) Prec@5 97.000 (98.954) +2022-11-14 14:09:23,486 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0857) Prec@1 83.000 (85.667) Prec@5 97.000 (98.924) +2022-11-14 14:09:23,496 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0856) Prec@1 86.000 (85.672) Prec@5 98.000 (98.910) +2022-11-14 14:09:23,506 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0856) Prec@1 84.000 (85.647) Prec@5 98.000 (98.897) +2022-11-14 14:09:23,515 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0855) Prec@1 88.000 (85.681) Prec@5 99.000 (98.899) +2022-11-14 14:09:23,526 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0857) Prec@1 85.000 (85.671) Prec@5 99.000 (98.900) +2022-11-14 14:09:23,534 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0857) Prec@1 88.000 (85.704) Prec@5 100.000 (98.915) +2022-11-14 14:09:23,544 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0856) Prec@1 86.000 (85.708) Prec@5 99.000 (98.917) +2022-11-14 14:09:23,554 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0853) Prec@1 90.000 (85.767) Prec@5 99.000 (98.918) +2022-11-14 14:09:23,563 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0852) Prec@1 84.000 (85.743) Prec@5 100.000 (98.932) +2022-11-14 14:09:23,571 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0855) Prec@1 82.000 (85.693) Prec@5 99.000 (98.933) +2022-11-14 14:09:23,579 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0855) Prec@1 86.000 (85.697) Prec@5 98.000 (98.921) +2022-11-14 14:09:23,588 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0856) Prec@1 85.000 (85.688) Prec@5 97.000 (98.896) +2022-11-14 14:09:23,599 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0856) Prec@1 83.000 (85.654) Prec@5 98.000 (98.885) +2022-11-14 14:09:23,611 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0857) Prec@1 82.000 (85.608) Prec@5 100.000 (98.899) +2022-11-14 14:09:23,620 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0856) Prec@1 86.000 (85.612) Prec@5 98.000 (98.888) +2022-11-14 14:09:23,629 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0856) Prec@1 86.000 (85.617) Prec@5 100.000 (98.901) +2022-11-14 14:09:23,639 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0856) Prec@1 86.000 (85.622) Prec@5 99.000 (98.902) +2022-11-14 14:09:23,648 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0856) Prec@1 83.000 (85.590) Prec@5 99.000 (98.904) +2022-11-14 14:09:23,658 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0855) Prec@1 86.000 (85.595) Prec@5 100.000 (98.917) +2022-11-14 14:09:23,667 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0856) Prec@1 84.000 (85.576) Prec@5 96.000 (98.882) +2022-11-14 14:09:23,677 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0857) Prec@1 85.000 (85.570) Prec@5 98.000 (98.872) +2022-11-14 14:09:23,688 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0859) Prec@1 83.000 (85.540) Prec@5 99.000 (98.874) +2022-11-14 14:09:23,698 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0861) Prec@1 86.000 (85.545) Prec@5 99.000 (98.875) +2022-11-14 14:09:23,710 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0860) Prec@1 86.000 (85.551) Prec@5 98.000 (98.865) +2022-11-14 14:09:23,719 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0860) Prec@1 86.000 (85.556) Prec@5 99.000 (98.867) +2022-11-14 14:09:23,729 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0860) Prec@1 85.000 (85.549) Prec@5 100.000 (98.879) +2022-11-14 14:09:23,737 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0856) Prec@1 92.000 (85.620) Prec@5 98.000 (98.870) +2022-11-14 14:09:23,746 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0858) Prec@1 83.000 (85.591) Prec@5 99.000 (98.871) +2022-11-14 14:09:23,756 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0856) Prec@1 91.000 (85.649) Prec@5 100.000 (98.883) +2022-11-14 14:09:23,764 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0856) Prec@1 84.000 (85.632) Prec@5 100.000 (98.895) +2022-11-14 14:09:23,773 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0854) Prec@1 86.000 (85.635) Prec@5 98.000 (98.885) +2022-11-14 14:09:23,783 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0851) Prec@1 94.000 (85.722) Prec@5 98.000 (98.876) +2022-11-14 14:09:23,792 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0852) Prec@1 86.000 (85.724) Prec@5 99.000 (98.878) +2022-11-14 14:09:23,801 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0851) Prec@1 89.000 (85.758) Prec@5 99.000 (98.879) +2022-11-14 14:09:23,811 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0849) Prec@1 92.000 (85.820) Prec@5 99.000 (98.880) +2022-11-14 14:09:23,867 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:09:24,192 Epoch: [156][0/500] Time 0.023 (0.023) Data 0.240 (0.240) Loss 0.0537 (0.0537) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:09:24,403 Epoch: [156][10/500] Time 0.021 (0.019) Data 0.002 (0.023) Loss 0.0465 (0.0501) Prec@1 94.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:09:24,632 Epoch: [156][20/500] Time 0.024 (0.020) Data 0.002 (0.013) Loss 0.0562 (0.0522) Prec@1 90.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:09:24,926 Epoch: [156][30/500] Time 0.022 (0.022) Data 0.002 (0.009) Loss 0.0476 (0.0510) Prec@1 92.000 (91.750) Prec@5 100.000 (99.750) +2022-11-14 14:09:25,207 Epoch: [156][40/500] Time 0.027 (0.022) Data 0.002 (0.008) Loss 0.0454 (0.0499) Prec@1 93.000 (92.000) Prec@5 100.000 (99.800) +2022-11-14 14:09:25,490 Epoch: [156][50/500] Time 0.026 (0.023) Data 0.002 (0.006) Loss 0.0476 (0.0495) Prec@1 92.000 (92.000) Prec@5 99.000 (99.667) +2022-11-14 14:09:25,770 Epoch: [156][60/500] Time 0.026 (0.023) Data 0.002 (0.006) Loss 0.0341 (0.0473) Prec@1 95.000 (92.429) Prec@5 100.000 (99.714) +2022-11-14 14:09:26,064 Epoch: [156][70/500] Time 0.026 (0.024) Data 0.002 (0.005) Loss 0.0593 (0.0488) Prec@1 90.000 (92.125) Prec@5 99.000 (99.625) +2022-11-14 14:09:26,351 Epoch: [156][80/500] Time 0.024 (0.024) Data 0.002 (0.005) Loss 0.0360 (0.0474) Prec@1 95.000 (92.444) Prec@5 100.000 (99.667) +2022-11-14 14:09:26,656 Epoch: [156][90/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0731 (0.0499) Prec@1 91.000 (92.300) Prec@5 100.000 (99.700) +2022-11-14 14:09:27,119 Epoch: [156][100/500] Time 0.060 (0.026) Data 0.002 (0.004) Loss 0.0687 (0.0516) Prec@1 87.000 (91.818) Prec@5 99.000 (99.636) +2022-11-14 14:09:27,671 Epoch: [156][110/500] Time 0.040 (0.028) Data 0.003 (0.004) Loss 0.0752 (0.0536) Prec@1 86.000 (91.333) Prec@5 99.000 (99.583) +2022-11-14 14:09:28,242 Epoch: [156][120/500] Time 0.051 (0.030) Data 0.002 (0.004) Loss 0.0646 (0.0545) Prec@1 91.000 (91.308) Prec@5 100.000 (99.615) +2022-11-14 14:09:28,747 Epoch: [156][130/500] Time 0.038 (0.031) Data 0.002 (0.004) Loss 0.0788 (0.0562) Prec@1 88.000 (91.071) Prec@5 97.000 (99.429) +2022-11-14 14:09:29,288 Epoch: [156][140/500] Time 0.058 (0.032) Data 0.003 (0.004) Loss 0.0574 (0.0563) Prec@1 91.000 (91.067) Prec@5 100.000 (99.467) +2022-11-14 14:09:29,856 Epoch: [156][150/500] Time 0.057 (0.034) Data 0.003 (0.004) Loss 0.0535 (0.0561) Prec@1 93.000 (91.188) Prec@5 100.000 (99.500) +2022-11-14 14:09:30,324 Epoch: [156][160/500] Time 0.047 (0.034) Data 0.002 (0.003) Loss 0.0687 (0.0568) Prec@1 86.000 (90.882) Prec@5 99.000 (99.471) +2022-11-14 14:09:30,893 Epoch: [156][170/500] Time 0.055 (0.035) Data 0.002 (0.003) Loss 0.0495 (0.0564) Prec@1 94.000 (91.056) Prec@5 100.000 (99.500) +2022-11-14 14:09:31,432 Epoch: [156][180/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0796 (0.0577) Prec@1 85.000 (90.737) Prec@5 100.000 (99.526) +2022-11-14 14:09:31,914 Epoch: [156][190/500] Time 0.060 (0.036) Data 0.002 (0.003) Loss 0.0536 (0.0575) Prec@1 92.000 (90.800) Prec@5 98.000 (99.450) +2022-11-14 14:09:32,455 Epoch: [156][200/500] Time 0.068 (0.037) Data 0.002 (0.003) Loss 0.0616 (0.0577) Prec@1 89.000 (90.714) Prec@5 99.000 (99.429) +2022-11-14 14:09:32,910 Epoch: [156][210/500] Time 0.060 (0.037) Data 0.002 (0.003) Loss 0.0448 (0.0571) Prec@1 94.000 (90.864) Prec@5 100.000 (99.455) +2022-11-14 14:09:33,389 Epoch: [156][220/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0496 (0.0567) Prec@1 91.000 (90.870) Prec@5 99.000 (99.435) +2022-11-14 14:09:33,983 Epoch: [156][230/500] Time 0.048 (0.038) Data 0.002 (0.003) Loss 0.0716 (0.0574) Prec@1 87.000 (90.708) Prec@5 100.000 (99.458) +2022-11-14 14:09:34,499 Epoch: [156][240/500] Time 0.055 (0.038) Data 0.002 (0.003) Loss 0.0338 (0.0564) Prec@1 95.000 (90.880) Prec@5 100.000 (99.480) +2022-11-14 14:09:35,087 Epoch: [156][250/500] Time 0.053 (0.039) Data 0.002 (0.003) Loss 0.0302 (0.0554) Prec@1 93.000 (90.962) Prec@5 100.000 (99.500) +2022-11-14 14:09:35,678 Epoch: [156][260/500] Time 0.058 (0.040) Data 0.002 (0.003) Loss 0.0641 (0.0557) Prec@1 90.000 (90.926) Prec@5 100.000 (99.519) +2022-11-14 14:09:36,243 Epoch: [156][270/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0576 (0.0558) Prec@1 90.000 (90.893) Prec@5 100.000 (99.536) +2022-11-14 14:09:36,828 Epoch: [156][280/500] Time 0.057 (0.040) Data 0.002 (0.003) Loss 0.0454 (0.0554) Prec@1 92.000 (90.931) Prec@5 98.000 (99.483) +2022-11-14 14:09:37,394 Epoch: [156][290/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0578 (0.0555) Prec@1 90.000 (90.900) Prec@5 100.000 (99.500) +2022-11-14 14:09:37,828 Epoch: [156][300/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0419 (0.0551) Prec@1 91.000 (90.903) Prec@5 100.000 (99.516) +2022-11-14 14:09:38,385 Epoch: [156][310/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0482 (0.0549) Prec@1 92.000 (90.938) Prec@5 99.000 (99.500) +2022-11-14 14:09:38,809 Epoch: [156][320/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0239 (0.0539) Prec@1 97.000 (91.121) Prec@5 100.000 (99.515) +2022-11-14 14:09:39,274 Epoch: [156][330/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0669 (0.0543) Prec@1 91.000 (91.118) Prec@5 100.000 (99.529) +2022-11-14 14:09:39,728 Epoch: [156][340/500] Time 0.041 (0.041) Data 0.003 (0.003) Loss 0.0652 (0.0546) Prec@1 90.000 (91.086) Prec@5 100.000 (99.543) +2022-11-14 14:09:40,200 Epoch: [156][350/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0452 (0.0544) Prec@1 92.000 (91.111) Prec@5 100.000 (99.556) +2022-11-14 14:09:40,750 Epoch: [156][360/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0476 (0.0542) Prec@1 92.000 (91.135) Prec@5 100.000 (99.568) +2022-11-14 14:09:41,246 Epoch: [156][370/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0444 (0.0539) Prec@1 91.000 (91.132) Prec@5 100.000 (99.579) +2022-11-14 14:09:41,822 Epoch: [156][380/500] Time 0.056 (0.042) Data 0.002 (0.003) Loss 0.0534 (0.0539) Prec@1 94.000 (91.205) Prec@5 98.000 (99.538) +2022-11-14 14:09:42,282 Epoch: [156][390/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0830 (0.0546) Prec@1 85.000 (91.050) Prec@5 99.000 (99.525) +2022-11-14 14:09:42,786 Epoch: [156][400/500] Time 0.088 (0.042) Data 0.002 (0.003) Loss 0.0573 (0.0547) Prec@1 91.000 (91.049) Prec@5 95.000 (99.415) +2022-11-14 14:09:43,215 Epoch: [156][410/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0584 (0.0548) Prec@1 91.000 (91.048) Prec@5 100.000 (99.429) +2022-11-14 14:09:43,666 Epoch: [156][420/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0741 (0.0552) Prec@1 90.000 (91.023) Prec@5 97.000 (99.372) +2022-11-14 14:09:44,123 Epoch: [156][430/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0602 (0.0554) Prec@1 90.000 (91.000) Prec@5 100.000 (99.386) +2022-11-14 14:09:44,573 Epoch: [156][440/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0427 (0.0551) Prec@1 93.000 (91.044) Prec@5 100.000 (99.400) +2022-11-14 14:09:45,085 Epoch: [156][450/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0560 (0.0551) Prec@1 90.000 (91.022) Prec@5 100.000 (99.413) +2022-11-14 14:09:45,579 Epoch: [156][460/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0637 (0.0553) Prec@1 90.000 (91.000) Prec@5 100.000 (99.426) +2022-11-14 14:09:46,045 Epoch: [156][470/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0714 (0.0556) Prec@1 87.000 (90.917) Prec@5 99.000 (99.417) +2022-11-14 14:09:46,552 Epoch: [156][480/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0482 (0.0555) Prec@1 92.000 (90.939) Prec@5 100.000 (99.429) +2022-11-14 14:09:47,007 Epoch: [156][490/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0932 (0.0562) Prec@1 83.000 (90.780) Prec@5 99.000 (99.420) +2022-11-14 14:09:47,447 Epoch: [156][499/500] Time 0.036 (0.042) Data 0.001 (0.003) Loss 0.0564 (0.0562) Prec@1 91.000 (90.784) Prec@5 99.000 (99.412) +2022-11-14 14:09:47,758 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0591 (0.0591) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:09:47,771 Test: [1/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0595 (0.0593) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 14:09:47,783 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0722 (0.0636) Prec@1 88.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 14:09:47,796 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1070 (0.0744) Prec@1 82.000 (87.500) Prec@5 98.000 (99.000) +2022-11-14 14:09:47,805 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0733) Prec@1 90.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 14:09:47,812 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0493 (0.0693) Prec@1 91.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 14:09:47,820 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0598 (0.0679) Prec@1 92.000 (89.000) Prec@5 100.000 (99.286) +2022-11-14 14:09:47,831 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0708) Prec@1 87.000 (88.750) Prec@5 98.000 (99.125) +2022-11-14 14:09:47,840 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0717) Prec@1 87.000 (88.556) Prec@5 99.000 (99.111) +2022-11-14 14:09:47,849 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0712) Prec@1 89.000 (88.600) Prec@5 99.000 (99.100) +2022-11-14 14:09:47,860 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0703) Prec@1 89.000 (88.636) Prec@5 100.000 (99.182) +2022-11-14 14:09:47,870 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0706) Prec@1 87.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 14:09:47,880 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0696) Prec@1 91.000 (88.692) Prec@5 100.000 (99.231) +2022-11-14 14:09:47,888 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0704) Prec@1 87.000 (88.571) Prec@5 98.000 (99.143) +2022-11-14 14:09:47,898 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0711) Prec@1 83.000 (88.200) Prec@5 99.000 (99.133) +2022-11-14 14:09:47,908 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0718) Prec@1 89.000 (88.250) Prec@5 99.000 (99.125) +2022-11-14 14:09:47,917 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0709) Prec@1 92.000 (88.471) Prec@5 98.000 (99.059) +2022-11-14 14:09:47,926 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0722) Prec@1 85.000 (88.278) Prec@5 100.000 (99.111) +2022-11-14 14:09:47,936 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0718) Prec@1 86.000 (88.158) Prec@5 100.000 (99.158) +2022-11-14 14:09:47,944 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0731) Prec@1 85.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 14:09:47,953 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0743) Prec@1 85.000 (87.857) Prec@5 100.000 (99.238) +2022-11-14 14:09:47,962 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0745) Prec@1 89.000 (87.909) Prec@5 99.000 (99.227) +2022-11-14 14:09:47,972 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0761) Prec@1 84.000 (87.739) Prec@5 99.000 (99.217) +2022-11-14 14:09:47,980 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0763) Prec@1 86.000 (87.667) Prec@5 99.000 (99.208) +2022-11-14 14:09:47,989 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0776) Prec@1 81.000 (87.400) Prec@5 100.000 (99.240) +2022-11-14 14:09:47,998 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0781) Prec@1 82.000 (87.192) Prec@5 99.000 (99.231) +2022-11-14 14:09:48,006 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0771) Prec@1 89.000 (87.259) Prec@5 100.000 (99.259) +2022-11-14 14:09:48,016 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0772) Prec@1 85.000 (87.179) Prec@5 100.000 (99.286) +2022-11-14 14:09:48,026 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0774) Prec@1 84.000 (87.069) Prec@5 99.000 (99.276) +2022-11-14 14:09:48,037 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0776) Prec@1 85.000 (87.000) Prec@5 100.000 (99.300) +2022-11-14 14:09:48,045 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0774) Prec@1 87.000 (87.000) Prec@5 100.000 (99.323) +2022-11-14 14:09:48,055 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0780) Prec@1 85.000 (86.938) Prec@5 100.000 (99.344) +2022-11-14 14:09:48,064 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0786) Prec@1 81.000 (86.758) Prec@5 99.000 (99.333) +2022-11-14 14:09:48,074 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0796) Prec@1 81.000 (86.588) Prec@5 99.000 (99.324) +2022-11-14 14:09:48,083 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0798) Prec@1 85.000 (86.543) Prec@5 99.000 (99.314) +2022-11-14 14:09:48,093 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0796) Prec@1 87.000 (86.556) Prec@5 99.000 (99.306) +2022-11-14 14:09:48,103 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0798) Prec@1 88.000 (86.595) Prec@5 99.000 (99.297) +2022-11-14 14:09:48,113 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0803) Prec@1 81.000 (86.447) Prec@5 99.000 (99.289) +2022-11-14 14:09:48,123 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0464 (0.0794) Prec@1 92.000 (86.590) Prec@5 100.000 (99.308) +2022-11-14 14:09:48,132 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0792) Prec@1 88.000 (86.625) Prec@5 99.000 (99.300) +2022-11-14 14:09:48,142 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0796) Prec@1 84.000 (86.561) Prec@5 100.000 (99.317) +2022-11-14 14:09:48,153 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0797) Prec@1 87.000 (86.571) Prec@5 99.000 (99.310) +2022-11-14 14:09:48,164 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0791) Prec@1 89.000 (86.628) Prec@5 99.000 (99.302) +2022-11-14 14:09:48,177 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0788) Prec@1 89.000 (86.682) Prec@5 99.000 (99.295) +2022-11-14 14:09:48,189 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0783) Prec@1 88.000 (86.711) Prec@5 100.000 (99.311) +2022-11-14 14:09:48,199 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0789) Prec@1 85.000 (86.674) Prec@5 99.000 (99.304) +2022-11-14 14:09:48,212 Test: [46/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0784) Prec@1 88.000 (86.702) Prec@5 100.000 (99.319) +2022-11-14 14:09:48,222 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0792) Prec@1 83.000 (86.625) Prec@5 98.000 (99.292) +2022-11-14 14:09:48,232 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0788) Prec@1 91.000 (86.714) Prec@5 100.000 (99.306) +2022-11-14 14:09:48,243 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0795) Prec@1 80.000 (86.580) Prec@5 99.000 (99.300) +2022-11-14 14:09:48,255 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0794) Prec@1 87.000 (86.588) Prec@5 99.000 (99.294) +2022-11-14 14:09:48,264 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0797) Prec@1 83.000 (86.519) Prec@5 98.000 (99.269) +2022-11-14 14:09:48,276 Test: [52/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0798) Prec@1 84.000 (86.472) Prec@5 100.000 (99.283) +2022-11-14 14:09:48,288 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0794) Prec@1 91.000 (86.556) Prec@5 99.000 (99.278) +2022-11-14 14:09:48,298 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0799) Prec@1 83.000 (86.491) Prec@5 99.000 (99.273) +2022-11-14 14:09:48,307 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0798) Prec@1 88.000 (86.518) Prec@5 99.000 (99.268) +2022-11-14 14:09:48,320 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0796) Prec@1 87.000 (86.526) Prec@5 100.000 (99.281) +2022-11-14 14:09:48,331 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0792) Prec@1 91.000 (86.603) Prec@5 99.000 (99.276) +2022-11-14 14:09:48,340 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0793) Prec@1 86.000 (86.593) Prec@5 100.000 (99.288) +2022-11-14 14:09:48,349 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0796) Prec@1 82.000 (86.517) Prec@5 100.000 (99.300) +2022-11-14 14:09:48,361 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0796) Prec@1 89.000 (86.557) Prec@5 100.000 (99.311) +2022-11-14 14:09:48,373 Test: [61/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0796) Prec@1 84.000 (86.516) Prec@5 100.000 (99.323) +2022-11-14 14:09:48,381 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0791) Prec@1 94.000 (86.635) Prec@5 100.000 (99.333) +2022-11-14 14:09:48,390 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0787) Prec@1 91.000 (86.703) Prec@5 100.000 (99.344) +2022-11-14 14:09:48,403 Test: [64/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0791) Prec@1 85.000 (86.677) Prec@5 100.000 (99.354) +2022-11-14 14:09:48,414 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0790) Prec@1 89.000 (86.712) Prec@5 99.000 (99.348) +2022-11-14 14:09:48,423 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0785) Prec@1 91.000 (86.776) Prec@5 100.000 (99.358) +2022-11-14 14:09:48,431 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0786) Prec@1 87.000 (86.779) Prec@5 98.000 (99.338) +2022-11-14 14:09:48,442 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0783) Prec@1 91.000 (86.841) Prec@5 100.000 (99.348) +2022-11-14 14:09:48,454 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0785) Prec@1 84.000 (86.800) Prec@5 99.000 (99.343) +2022-11-14 14:09:48,463 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0786) Prec@1 87.000 (86.803) Prec@5 99.000 (99.338) +2022-11-14 14:09:48,472 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0787) Prec@1 85.000 (86.778) Prec@5 99.000 (99.333) +2022-11-14 14:09:48,484 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0784) Prec@1 90.000 (86.822) Prec@5 99.000 (99.329) +2022-11-14 14:09:48,496 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0780) Prec@1 91.000 (86.878) Prec@5 100.000 (99.338) +2022-11-14 14:09:48,505 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.0786) Prec@1 81.000 (86.800) Prec@5 100.000 (99.347) +2022-11-14 14:09:48,514 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0783) Prec@1 91.000 (86.855) Prec@5 100.000 (99.355) +2022-11-14 14:09:48,527 Test: [76/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0783) Prec@1 88.000 (86.870) Prec@5 100.000 (99.364) +2022-11-14 14:09:48,539 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0784) Prec@1 86.000 (86.859) Prec@5 96.000 (99.321) +2022-11-14 14:09:48,548 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0783) Prec@1 87.000 (86.861) Prec@5 99.000 (99.316) +2022-11-14 14:09:48,557 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0783) Prec@1 88.000 (86.875) Prec@5 99.000 (99.312) +2022-11-14 14:09:48,569 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0783) Prec@1 86.000 (86.864) Prec@5 99.000 (99.309) +2022-11-14 14:09:48,580 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0785) Prec@1 86.000 (86.854) Prec@5 100.000 (99.317) +2022-11-14 14:09:48,588 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0783) Prec@1 89.000 (86.880) Prec@5 100.000 (99.325) +2022-11-14 14:09:48,597 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0781) Prec@1 89.000 (86.905) Prec@5 99.000 (99.321) +2022-11-14 14:09:48,609 Test: [84/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0785) Prec@1 81.000 (86.835) Prec@5 99.000 (99.318) +2022-11-14 14:09:48,620 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0788) Prec@1 86.000 (86.826) Prec@5 99.000 (99.314) +2022-11-14 14:09:48,630 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0788) Prec@1 86.000 (86.816) Prec@5 99.000 (99.310) +2022-11-14 14:09:48,639 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0786) Prec@1 90.000 (86.852) Prec@5 98.000 (99.295) +2022-11-14 14:09:48,652 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0784) Prec@1 90.000 (86.888) Prec@5 100.000 (99.303) +2022-11-14 14:09:48,663 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0782) Prec@1 90.000 (86.922) Prec@5 99.000 (99.300) +2022-11-14 14:09:48,673 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0780) Prec@1 91.000 (86.967) Prec@5 100.000 (99.308) +2022-11-14 14:09:48,683 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0777) Prec@1 91.000 (87.011) Prec@5 99.000 (99.304) +2022-11-14 14:09:48,693 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0780) Prec@1 83.000 (86.968) Prec@5 99.000 (99.301) +2022-11-14 14:09:48,702 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0780) Prec@1 86.000 (86.957) Prec@5 99.000 (99.298) +2022-11-14 14:09:48,710 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0782) Prec@1 85.000 (86.937) Prec@5 99.000 (99.295) +2022-11-14 14:09:48,720 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0783) Prec@1 84.000 (86.906) Prec@5 100.000 (99.302) +2022-11-14 14:09:48,729 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0780) Prec@1 91.000 (86.948) Prec@5 99.000 (99.299) +2022-11-14 14:09:48,738 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1114 (0.0783) Prec@1 83.000 (86.908) Prec@5 100.000 (99.306) +2022-11-14 14:09:48,748 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0786) Prec@1 81.000 (86.848) Prec@5 99.000 (99.303) +2022-11-14 14:09:48,756 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0785) Prec@1 90.000 (86.880) Prec@5 100.000 (99.310) +2022-11-14 14:09:48,823 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:09:49,138 Epoch: [157][0/500] Time 0.028 (0.028) Data 0.226 (0.226) Loss 0.0550 (0.0550) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:09:49,343 Epoch: [157][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0309 (0.0430) Prec@1 96.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:09:49,562 Epoch: [157][20/500] Time 0.023 (0.019) Data 0.002 (0.012) Loss 0.0413 (0.0424) Prec@1 92.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:09:49,937 Epoch: [157][30/500] Time 0.050 (0.023) Data 0.002 (0.009) Loss 0.0612 (0.0471) Prec@1 90.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:09:50,448 Epoch: [157][40/500] Time 0.042 (0.029) Data 0.002 (0.007) Loss 0.0567 (0.0490) Prec@1 91.000 (92.200) Prec@5 99.000 (99.800) +2022-11-14 14:09:51,036 Epoch: [157][50/500] Time 0.038 (0.034) Data 0.002 (0.006) Loss 0.0332 (0.0464) Prec@1 95.000 (92.667) Prec@5 100.000 (99.833) +2022-11-14 14:09:51,545 Epoch: [157][60/500] Time 0.043 (0.035) Data 0.002 (0.006) Loss 0.0591 (0.0482) Prec@1 90.000 (92.286) Prec@5 100.000 (99.857) +2022-11-14 14:09:52,163 Epoch: [157][70/500] Time 0.049 (0.038) Data 0.002 (0.005) Loss 0.0563 (0.0492) Prec@1 90.000 (92.000) Prec@5 99.000 (99.750) +2022-11-14 14:09:52,627 Epoch: [157][80/500] Time 0.043 (0.038) Data 0.002 (0.005) Loss 0.0603 (0.0504) Prec@1 90.000 (91.778) Prec@5 100.000 (99.778) +2022-11-14 14:09:53,123 Epoch: [157][90/500] Time 0.042 (0.039) Data 0.002 (0.004) Loss 0.0394 (0.0493) Prec@1 91.000 (91.700) Prec@5 100.000 (99.800) +2022-11-14 14:09:53,586 Epoch: [157][100/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0677 (0.0510) Prec@1 88.000 (91.364) Prec@5 98.000 (99.636) +2022-11-14 14:09:54,226 Epoch: [157][110/500] Time 0.085 (0.041) Data 0.002 (0.004) Loss 0.0691 (0.0525) Prec@1 88.000 (91.083) Prec@5 100.000 (99.667) +2022-11-14 14:09:54,713 Epoch: [157][120/500] Time 0.044 (0.041) Data 0.002 (0.004) Loss 0.0255 (0.0504) Prec@1 97.000 (91.538) Prec@5 100.000 (99.692) +2022-11-14 14:09:55,183 Epoch: [157][130/500] Time 0.043 (0.041) Data 0.001 (0.004) Loss 0.0573 (0.0509) Prec@1 89.000 (91.357) Prec@5 100.000 (99.714) +2022-11-14 14:09:55,646 Epoch: [157][140/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0565 (0.0513) Prec@1 91.000 (91.333) Prec@5 100.000 (99.733) +2022-11-14 14:09:56,116 Epoch: [157][150/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0463 (0.0510) Prec@1 92.000 (91.375) Prec@5 100.000 (99.750) +2022-11-14 14:09:56,581 Epoch: [157][160/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0865 (0.0531) Prec@1 83.000 (90.882) Prec@5 98.000 (99.647) +2022-11-14 14:09:57,056 Epoch: [157][170/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0486 (0.0528) Prec@1 92.000 (90.944) Prec@5 100.000 (99.667) +2022-11-14 14:09:57,519 Epoch: [157][180/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0450 (0.0524) Prec@1 93.000 (91.053) Prec@5 100.000 (99.684) +2022-11-14 14:09:57,991 Epoch: [157][190/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0451 (0.0520) Prec@1 92.000 (91.100) Prec@5 100.000 (99.700) +2022-11-14 14:09:58,493 Epoch: [157][200/500] Time 0.056 (0.041) Data 0.002 (0.003) Loss 0.0654 (0.0527) Prec@1 89.000 (91.000) Prec@5 100.000 (99.714) +2022-11-14 14:09:59,127 Epoch: [157][210/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0764 (0.0538) Prec@1 87.000 (90.818) Prec@5 98.000 (99.636) +2022-11-14 14:09:59,775 Epoch: [157][220/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0569 (0.0539) Prec@1 91.000 (90.826) Prec@5 100.000 (99.652) +2022-11-14 14:10:00,535 Epoch: [157][230/500] Time 0.094 (0.044) Data 0.002 (0.003) Loss 0.0590 (0.0541) Prec@1 91.000 (90.833) Prec@5 99.000 (99.625) +2022-11-14 14:10:01,085 Epoch: [157][240/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0295 (0.0531) Prec@1 96.000 (91.040) Prec@5 100.000 (99.640) +2022-11-14 14:10:01,669 Epoch: [157][250/500] Time 0.067 (0.045) Data 0.002 (0.003) Loss 0.0613 (0.0534) Prec@1 88.000 (90.923) Prec@5 99.000 (99.615) +2022-11-14 14:10:02,482 Epoch: [157][260/500] Time 0.079 (0.046) Data 0.002 (0.003) Loss 0.0860 (0.0546) Prec@1 87.000 (90.778) Prec@5 100.000 (99.630) +2022-11-14 14:10:03,266 Epoch: [157][270/500] Time 0.067 (0.047) Data 0.002 (0.003) Loss 0.0537 (0.0546) Prec@1 90.000 (90.750) Prec@5 99.000 (99.607) +2022-11-14 14:10:03,839 Epoch: [157][280/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0515 (0.0545) Prec@1 94.000 (90.862) Prec@5 100.000 (99.621) +2022-11-14 14:10:04,517 Epoch: [157][290/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0553 (0.0545) Prec@1 90.000 (90.833) Prec@5 99.000 (99.600) +2022-11-14 14:10:05,033 Epoch: [157][300/500] Time 0.043 (0.047) Data 0.002 (0.003) Loss 0.0707 (0.0551) Prec@1 87.000 (90.710) Prec@5 100.000 (99.613) +2022-11-14 14:10:05,594 Epoch: [157][310/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0336 (0.0544) Prec@1 96.000 (90.875) Prec@5 100.000 (99.625) +2022-11-14 14:10:06,247 Epoch: [157][320/500] Time 0.098 (0.048) Data 0.002 (0.003) Loss 0.0438 (0.0541) Prec@1 93.000 (90.939) Prec@5 99.000 (99.606) +2022-11-14 14:10:06,711 Epoch: [157][330/500] Time 0.042 (0.048) Data 0.002 (0.003) Loss 0.0459 (0.0538) Prec@1 92.000 (90.971) Prec@5 98.000 (99.559) +2022-11-14 14:10:07,228 Epoch: [157][340/500] Time 0.060 (0.047) Data 0.002 (0.003) Loss 0.0453 (0.0536) Prec@1 93.000 (91.029) Prec@5 100.000 (99.571) +2022-11-14 14:10:07,770 Epoch: [157][350/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0355 (0.0531) Prec@1 94.000 (91.111) Prec@5 100.000 (99.583) +2022-11-14 14:10:08,243 Epoch: [157][360/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0618 (0.0533) Prec@1 90.000 (91.081) Prec@5 99.000 (99.568) +2022-11-14 14:10:08,708 Epoch: [157][370/500] Time 0.043 (0.047) Data 0.002 (0.003) Loss 0.0447 (0.0531) Prec@1 95.000 (91.184) Prec@5 100.000 (99.579) +2022-11-14 14:10:09,289 Epoch: [157][380/500] Time 0.052 (0.047) Data 0.002 (0.002) Loss 0.0607 (0.0533) Prec@1 88.000 (91.103) Prec@5 100.000 (99.590) +2022-11-14 14:10:09,887 Epoch: [157][390/500] Time 0.051 (0.047) Data 0.002 (0.002) Loss 0.0613 (0.0535) Prec@1 90.000 (91.075) Prec@5 99.000 (99.575) +2022-11-14 14:10:10,519 Epoch: [157][400/500] Time 0.042 (0.048) Data 0.002 (0.002) Loss 0.0313 (0.0529) Prec@1 95.000 (91.171) Prec@5 100.000 (99.585) +2022-11-14 14:10:11,156 Epoch: [157][410/500] Time 0.106 (0.048) Data 0.002 (0.002) Loss 0.0433 (0.0527) Prec@1 93.000 (91.214) Prec@5 99.000 (99.571) +2022-11-14 14:10:11,860 Epoch: [157][420/500] Time 0.037 (0.048) Data 0.002 (0.002) Loss 0.0505 (0.0527) Prec@1 93.000 (91.256) Prec@5 100.000 (99.581) +2022-11-14 14:10:12,359 Epoch: [157][430/500] Time 0.047 (0.048) Data 0.002 (0.002) Loss 0.0790 (0.0533) Prec@1 89.000 (91.205) Prec@5 98.000 (99.545) +2022-11-14 14:10:12,845 Epoch: [157][440/500] Time 0.043 (0.048) Data 0.002 (0.002) Loss 0.0743 (0.0537) Prec@1 88.000 (91.133) Prec@5 100.000 (99.556) +2022-11-14 14:10:13,400 Epoch: [157][450/500] Time 0.045 (0.048) Data 0.002 (0.002) Loss 0.0439 (0.0535) Prec@1 94.000 (91.196) Prec@5 100.000 (99.565) +2022-11-14 14:10:13,798 Epoch: [157][460/500] Time 0.038 (0.048) Data 0.002 (0.002) Loss 0.0530 (0.0535) Prec@1 90.000 (91.170) Prec@5 100.000 (99.574) +2022-11-14 14:10:14,126 Epoch: [157][470/500] Time 0.028 (0.047) Data 0.002 (0.002) Loss 0.0535 (0.0535) Prec@1 91.000 (91.167) Prec@5 100.000 (99.583) +2022-11-14 14:10:14,504 Epoch: [157][480/500] Time 0.037 (0.047) Data 0.002 (0.002) Loss 0.0347 (0.0531) Prec@1 94.000 (91.224) Prec@5 99.000 (99.571) +2022-11-14 14:10:14,882 Epoch: [157][490/500] Time 0.035 (0.047) Data 0.002 (0.002) Loss 0.0548 (0.0531) Prec@1 89.000 (91.180) Prec@5 100.000 (99.580) +2022-11-14 14:10:15,158 Epoch: [157][499/500] Time 0.029 (0.047) Data 0.002 (0.002) Loss 0.0634 (0.0534) Prec@1 90.000 (91.157) Prec@5 99.000 (99.569) +2022-11-14 14:10:15,451 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0628 (0.0628) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:10:15,460 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0778 (0.0703) Prec@1 88.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:10:15,469 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0843 (0.0749) Prec@1 83.000 (86.333) Prec@5 100.000 (99.667) +2022-11-14 14:10:15,481 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0784) Prec@1 86.000 (86.250) Prec@5 100.000 (99.750) +2022-11-14 14:10:15,490 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0753) Prec@1 90.000 (87.000) Prec@5 99.000 (99.600) +2022-11-14 14:10:15,498 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0712) Prec@1 89.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:10:15,507 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0714) Prec@1 88.000 (87.429) Prec@5 98.000 (99.429) +2022-11-14 14:10:15,517 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0763) Prec@1 83.000 (86.875) Prec@5 99.000 (99.375) +2022-11-14 14:10:15,526 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0772) Prec@1 85.000 (86.667) Prec@5 99.000 (99.333) +2022-11-14 14:10:15,535 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0766) Prec@1 88.000 (86.800) Prec@5 99.000 (99.300) +2022-11-14 14:10:15,545 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0754) Prec@1 89.000 (87.000) Prec@5 99.000 (99.273) +2022-11-14 14:10:15,554 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0761) Prec@1 85.000 (86.833) Prec@5 99.000 (99.250) +2022-11-14 14:10:15,563 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0752) Prec@1 91.000 (87.154) Prec@5 100.000 (99.308) +2022-11-14 14:10:15,573 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0762) Prec@1 82.000 (86.786) Prec@5 100.000 (99.357) +2022-11-14 14:10:15,582 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0753) Prec@1 89.000 (86.933) Prec@5 99.000 (99.333) +2022-11-14 14:10:15,591 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0758) Prec@1 84.000 (86.750) Prec@5 98.000 (99.250) +2022-11-14 14:10:15,600 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0744) Prec@1 92.000 (87.059) Prec@5 98.000 (99.176) +2022-11-14 14:10:15,610 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1328 (0.0777) Prec@1 77.000 (86.500) Prec@5 100.000 (99.222) +2022-11-14 14:10:15,619 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0777) Prec@1 83.000 (86.316) Prec@5 100.000 (99.263) +2022-11-14 14:10:15,628 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0795) Prec@1 83.000 (86.150) Prec@5 99.000 (99.250) +2022-11-14 14:10:15,638 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0796) Prec@1 85.000 (86.095) Prec@5 100.000 (99.286) +2022-11-14 14:10:15,647 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0794) Prec@1 88.000 (86.182) Prec@5 99.000 (99.273) +2022-11-14 14:10:15,656 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0801) Prec@1 83.000 (86.043) Prec@5 99.000 (99.261) +2022-11-14 14:10:15,666 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0809) Prec@1 85.000 (86.000) Prec@5 100.000 (99.292) +2022-11-14 14:10:15,674 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0813) Prec@1 86.000 (86.000) Prec@5 100.000 (99.320) +2022-11-14 14:10:15,683 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0825) Prec@1 80.000 (85.769) Prec@5 99.000 (99.308) +2022-11-14 14:10:15,691 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0822) Prec@1 88.000 (85.852) Prec@5 100.000 (99.333) +2022-11-14 14:10:15,699 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0822) Prec@1 88.000 (85.929) Prec@5 100.000 (99.357) +2022-11-14 14:10:15,707 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0824) Prec@1 85.000 (85.897) Prec@5 99.000 (99.345) +2022-11-14 14:10:15,716 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0827) Prec@1 84.000 (85.833) Prec@5 99.000 (99.333) +2022-11-14 14:10:15,724 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0829) Prec@1 86.000 (85.839) Prec@5 99.000 (99.323) +2022-11-14 14:10:15,734 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0825) Prec@1 88.000 (85.906) Prec@5 99.000 (99.312) +2022-11-14 14:10:15,742 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0824) Prec@1 86.000 (85.909) Prec@5 99.000 (99.303) +2022-11-14 14:10:15,749 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0824) Prec@1 87.000 (85.941) Prec@5 99.000 (99.294) +2022-11-14 14:10:15,759 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0827) Prec@1 85.000 (85.914) Prec@5 98.000 (99.257) +2022-11-14 14:10:15,769 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0824) Prec@1 91.000 (86.056) Prec@5 100.000 (99.278) +2022-11-14 14:10:15,778 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0824) Prec@1 85.000 (86.027) Prec@5 99.000 (99.270) +2022-11-14 14:10:15,787 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0826) Prec@1 86.000 (86.026) Prec@5 99.000 (99.263) +2022-11-14 14:10:15,796 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0819) Prec@1 93.000 (86.205) Prec@5 99.000 (99.256) +2022-11-14 14:10:15,805 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0819) Prec@1 84.000 (86.150) Prec@5 99.000 (99.250) +2022-11-14 14:10:15,813 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0825) Prec@1 82.000 (86.049) Prec@5 99.000 (99.244) +2022-11-14 14:10:15,823 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0825) Prec@1 88.000 (86.095) Prec@5 99.000 (99.238) +2022-11-14 14:10:15,833 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0816) Prec@1 92.000 (86.233) Prec@5 100.000 (99.256) +2022-11-14 14:10:15,842 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0818) Prec@1 86.000 (86.227) Prec@5 99.000 (99.250) +2022-11-14 14:10:15,852 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0813) Prec@1 89.000 (86.289) Prec@5 100.000 (99.267) +2022-11-14 14:10:15,863 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0819) Prec@1 83.000 (86.217) Prec@5 99.000 (99.261) +2022-11-14 14:10:15,872 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0817) Prec@1 87.000 (86.234) Prec@5 100.000 (99.277) +2022-11-14 14:10:15,881 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.0823) Prec@1 81.000 (86.125) Prec@5 99.000 (99.271) +2022-11-14 14:10:15,890 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0818) Prec@1 90.000 (86.204) Prec@5 100.000 (99.286) +2022-11-14 14:10:15,900 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0825) Prec@1 78.000 (86.040) Prec@5 100.000 (99.300) +2022-11-14 14:10:15,909 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0823) Prec@1 88.000 (86.078) Prec@5 100.000 (99.314) +2022-11-14 14:10:15,918 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0822) Prec@1 88.000 (86.115) Prec@5 98.000 (99.288) +2022-11-14 14:10:15,928 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0823) Prec@1 85.000 (86.094) Prec@5 99.000 (99.283) +2022-11-14 14:10:15,936 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0823) Prec@1 87.000 (86.111) Prec@5 99.000 (99.278) +2022-11-14 14:10:15,945 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0823) Prec@1 85.000 (86.091) Prec@5 100.000 (99.291) +2022-11-14 14:10:15,954 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0821) Prec@1 89.000 (86.143) Prec@5 99.000 (99.286) +2022-11-14 14:10:15,963 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0822) Prec@1 84.000 (86.105) Prec@5 99.000 (99.281) +2022-11-14 14:10:15,973 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0822) Prec@1 88.000 (86.138) Prec@5 100.000 (99.293) +2022-11-14 14:10:15,981 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.0827) Prec@1 82.000 (86.068) Prec@5 99.000 (99.288) +2022-11-14 14:10:15,989 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0827) Prec@1 85.000 (86.050) Prec@5 100.000 (99.300) +2022-11-14 14:10:15,997 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0828) Prec@1 86.000 (86.049) Prec@5 99.000 (99.295) +2022-11-14 14:10:16,005 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0826) Prec@1 88.000 (86.081) Prec@5 99.000 (99.290) +2022-11-14 14:10:16,014 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0822) Prec@1 89.000 (86.127) Prec@5 100.000 (99.302) +2022-11-14 14:10:16,023 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0405 (0.0816) Prec@1 91.000 (86.203) Prec@5 100.000 (99.312) +2022-11-14 14:10:16,031 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0818) Prec@1 83.000 (86.154) Prec@5 99.000 (99.308) +2022-11-14 14:10:16,039 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0817) Prec@1 87.000 (86.167) Prec@5 99.000 (99.303) +2022-11-14 14:10:16,046 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0409 (0.0811) Prec@1 93.000 (86.269) Prec@5 100.000 (99.313) +2022-11-14 14:10:16,055 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0811) Prec@1 88.000 (86.294) Prec@5 99.000 (99.309) +2022-11-14 14:10:16,063 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0808) Prec@1 90.000 (86.348) Prec@5 99.000 (99.304) +2022-11-14 14:10:16,073 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0808) Prec@1 87.000 (86.357) Prec@5 97.000 (99.271) +2022-11-14 14:10:16,084 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0809) Prec@1 83.000 (86.310) Prec@5 98.000 (99.254) +2022-11-14 14:10:16,095 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0807) Prec@1 89.000 (86.347) Prec@5 100.000 (99.264) +2022-11-14 14:10:16,107 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0803) Prec@1 94.000 (86.452) Prec@5 99.000 (99.260) +2022-11-14 14:10:16,118 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0803) Prec@1 87.000 (86.459) Prec@5 100.000 (99.270) +2022-11-14 14:10:16,129 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0804) Prec@1 84.000 (86.427) Prec@5 100.000 (99.280) +2022-11-14 14:10:16,140 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0804) Prec@1 87.000 (86.434) Prec@5 100.000 (99.289) +2022-11-14 14:10:16,151 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0800) Prec@1 91.000 (86.494) Prec@5 100.000 (99.299) +2022-11-14 14:10:16,163 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0800) Prec@1 87.000 (86.500) Prec@5 98.000 (99.282) +2022-11-14 14:10:16,174 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0802) Prec@1 86.000 (86.494) Prec@5 99.000 (99.278) +2022-11-14 14:10:16,186 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0800) Prec@1 91.000 (86.550) Prec@5 100.000 (99.287) +2022-11-14 14:10:16,198 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0801) Prec@1 85.000 (86.531) Prec@5 99.000 (99.284) +2022-11-14 14:10:16,209 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0798) Prec@1 91.000 (86.585) Prec@5 100.000 (99.293) +2022-11-14 14:10:16,221 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0799) Prec@1 85.000 (86.566) Prec@5 98.000 (99.277) +2022-11-14 14:10:16,233 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0800) Prec@1 87.000 (86.571) Prec@5 100.000 (99.286) +2022-11-14 14:10:16,243 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0801) Prec@1 83.000 (86.529) Prec@5 99.000 (99.282) +2022-11-14 14:10:16,252 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0804) Prec@1 84.000 (86.500) Prec@5 100.000 (99.291) +2022-11-14 14:10:16,262 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0804) Prec@1 83.000 (86.460) Prec@5 100.000 (99.299) +2022-11-14 14:10:16,270 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0804) Prec@1 86.000 (86.455) Prec@5 98.000 (99.284) +2022-11-14 14:10:16,279 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0802) Prec@1 90.000 (86.494) Prec@5 99.000 (99.281) +2022-11-14 14:10:16,288 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0801) Prec@1 89.000 (86.522) Prec@5 100.000 (99.289) +2022-11-14 14:10:16,298 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0799) Prec@1 88.000 (86.538) Prec@5 100.000 (99.297) +2022-11-14 14:10:16,306 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0795) Prec@1 94.000 (86.620) Prec@5 100.000 (99.304) +2022-11-14 14:10:16,314 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0798) Prec@1 84.000 (86.591) Prec@5 97.000 (99.280) +2022-11-14 14:10:16,323 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0796) Prec@1 90.000 (86.628) Prec@5 99.000 (99.277) +2022-11-14 14:10:16,332 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0795) Prec@1 88.000 (86.642) Prec@5 99.000 (99.274) +2022-11-14 14:10:16,341 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0793) Prec@1 90.000 (86.677) Prec@5 99.000 (99.271) +2022-11-14 14:10:16,349 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0456 (0.0789) Prec@1 92.000 (86.732) Prec@5 99.000 (99.268) +2022-11-14 14:10:16,359 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0790) Prec@1 87.000 (86.735) Prec@5 99.000 (99.265) +2022-11-14 14:10:16,367 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0792) Prec@1 83.000 (86.697) Prec@5 100.000 (99.273) +2022-11-14 14:10:16,374 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0792) Prec@1 88.000 (86.710) Prec@5 99.000 (99.270) +2022-11-14 14:10:16,449 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:10:16,758 Epoch: [158][0/500] Time 0.028 (0.028) Data 0.225 (0.225) Loss 0.0360 (0.0360) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 14:10:16,965 Epoch: [158][10/500] Time 0.017 (0.019) Data 0.001 (0.022) Loss 0.0419 (0.0390) Prec@1 94.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:10:17,163 Epoch: [158][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0611 (0.0463) Prec@1 91.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:10:17,451 Epoch: [158][30/500] Time 0.037 (0.020) Data 0.001 (0.009) Loss 0.0351 (0.0435) Prec@1 95.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:10:17,904 Epoch: [158][40/500] Time 0.039 (0.025) Data 0.002 (0.007) Loss 0.0748 (0.0498) Prec@1 86.000 (92.000) Prec@5 100.000 (99.800) +2022-11-14 14:10:18,382 Epoch: [158][50/500] Time 0.067 (0.029) Data 0.002 (0.006) Loss 0.0496 (0.0498) Prec@1 92.000 (92.000) Prec@5 100.000 (99.833) +2022-11-14 14:10:18,800 Epoch: [158][60/500] Time 0.045 (0.030) Data 0.002 (0.005) Loss 0.0663 (0.0521) Prec@1 90.000 (91.714) Prec@5 100.000 (99.857) +2022-11-14 14:10:19,230 Epoch: [158][70/500] Time 0.040 (0.031) Data 0.001 (0.005) Loss 0.0443 (0.0511) Prec@1 91.000 (91.625) Prec@5 100.000 (99.875) +2022-11-14 14:10:19,659 Epoch: [158][80/500] Time 0.041 (0.032) Data 0.002 (0.005) Loss 0.0648 (0.0527) Prec@1 90.000 (91.444) Prec@5 100.000 (99.889) +2022-11-14 14:10:20,099 Epoch: [158][90/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0610 (0.0535) Prec@1 91.000 (91.400) Prec@5 100.000 (99.900) +2022-11-14 14:10:20,578 Epoch: [158][100/500] Time 0.050 (0.034) Data 0.002 (0.004) Loss 0.0523 (0.0534) Prec@1 91.000 (91.364) Prec@5 100.000 (99.909) +2022-11-14 14:10:21,026 Epoch: [158][110/500] Time 0.036 (0.035) Data 0.002 (0.004) Loss 0.0360 (0.0519) Prec@1 94.000 (91.583) Prec@5 100.000 (99.917) +2022-11-14 14:10:21,557 Epoch: [158][120/500] Time 0.052 (0.036) Data 0.002 (0.004) Loss 0.0581 (0.0524) Prec@1 91.000 (91.538) Prec@5 100.000 (99.923) +2022-11-14 14:10:21,998 Epoch: [158][130/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0530 (0.0524) Prec@1 90.000 (91.429) Prec@5 100.000 (99.929) +2022-11-14 14:10:22,455 Epoch: [158][140/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0504 (0.0523) Prec@1 91.000 (91.400) Prec@5 99.000 (99.867) +2022-11-14 14:10:22,926 Epoch: [158][150/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0513 (0.0522) Prec@1 92.000 (91.438) Prec@5 100.000 (99.875) +2022-11-14 14:10:23,381 Epoch: [158][160/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0482 (0.0520) Prec@1 94.000 (91.588) Prec@5 100.000 (99.882) +2022-11-14 14:10:23,860 Epoch: [158][170/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0368 (0.0512) Prec@1 95.000 (91.778) Prec@5 100.000 (99.889) +2022-11-14 14:10:24,366 Epoch: [158][180/500] Time 0.051 (0.037) Data 0.002 (0.003) Loss 0.0335 (0.0502) Prec@1 93.000 (91.842) Prec@5 100.000 (99.895) +2022-11-14 14:10:24,789 Epoch: [158][190/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.0452 (0.0500) Prec@1 94.000 (91.950) Prec@5 100.000 (99.900) +2022-11-14 14:10:25,353 Epoch: [158][200/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0698 (0.0509) Prec@1 88.000 (91.762) Prec@5 100.000 (99.905) +2022-11-14 14:10:25,807 Epoch: [158][210/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0278 (0.0499) Prec@1 97.000 (92.000) Prec@5 100.000 (99.909) +2022-11-14 14:10:26,318 Epoch: [158][220/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0647 (0.0505) Prec@1 87.000 (91.783) Prec@5 99.000 (99.870) +2022-11-14 14:10:26,739 Epoch: [158][230/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0159 (0.0491) Prec@1 98.000 (92.042) Prec@5 100.000 (99.875) +2022-11-14 14:10:27,185 Epoch: [158][240/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0607 (0.0495) Prec@1 90.000 (91.960) Prec@5 99.000 (99.840) +2022-11-14 14:10:27,610 Epoch: [158][250/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0650 (0.0501) Prec@1 90.000 (91.885) Prec@5 100.000 (99.846) +2022-11-14 14:10:28,056 Epoch: [158][260/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0464 (0.0500) Prec@1 92.000 (91.889) Prec@5 99.000 (99.815) +2022-11-14 14:10:28,498 Epoch: [158][270/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0367 (0.0495) Prec@1 94.000 (91.964) Prec@5 100.000 (99.821) +2022-11-14 14:10:28,927 Epoch: [158][280/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0543 (0.0497) Prec@1 92.000 (91.966) Prec@5 100.000 (99.828) +2022-11-14 14:10:29,348 Epoch: [158][290/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0484 (0.0497) Prec@1 91.000 (91.933) Prec@5 100.000 (99.833) +2022-11-14 14:10:29,783 Epoch: [158][300/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0338 (0.0491) Prec@1 95.000 (92.032) Prec@5 100.000 (99.839) +2022-11-14 14:10:30,228 Epoch: [158][310/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0417 (0.0489) Prec@1 93.000 (92.062) Prec@5 100.000 (99.844) +2022-11-14 14:10:30,666 Epoch: [158][320/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0677 (0.0495) Prec@1 88.000 (91.939) Prec@5 99.000 (99.818) +2022-11-14 14:10:31,103 Epoch: [158][330/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0383 (0.0491) Prec@1 96.000 (92.059) Prec@5 100.000 (99.824) +2022-11-14 14:10:31,538 Epoch: [158][340/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0535 (0.0493) Prec@1 91.000 (92.029) Prec@5 100.000 (99.829) +2022-11-14 14:10:31,984 Epoch: [158][350/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0812 (0.0502) Prec@1 85.000 (91.833) Prec@5 100.000 (99.833) +2022-11-14 14:10:32,545 Epoch: [158][360/500] Time 0.049 (0.039) Data 0.002 (0.002) Loss 0.0484 (0.0501) Prec@1 91.000 (91.811) Prec@5 99.000 (99.811) +2022-11-14 14:10:33,041 Epoch: [158][370/500] Time 0.033 (0.039) Data 0.002 (0.002) Loss 0.0537 (0.0502) Prec@1 93.000 (91.842) Prec@5 100.000 (99.816) +2022-11-14 14:10:33,493 Epoch: [158][380/500] Time 0.042 (0.039) Data 0.002 (0.002) Loss 0.0485 (0.0502) Prec@1 90.000 (91.795) Prec@5 100.000 (99.821) +2022-11-14 14:10:33,939 Epoch: [158][390/500] Time 0.048 (0.039) Data 0.002 (0.002) Loss 0.0812 (0.0509) Prec@1 86.000 (91.650) Prec@5 100.000 (99.825) +2022-11-14 14:10:34,373 Epoch: [158][400/500] Time 0.041 (0.039) Data 0.002 (0.002) Loss 0.0519 (0.0510) Prec@1 93.000 (91.683) Prec@5 99.000 (99.805) +2022-11-14 14:10:34,799 Epoch: [158][410/500] Time 0.038 (0.039) Data 0.002 (0.002) Loss 0.0806 (0.0517) Prec@1 85.000 (91.524) Prec@5 99.000 (99.786) +2022-11-14 14:10:35,247 Epoch: [158][420/500] Time 0.037 (0.039) Data 0.002 (0.002) Loss 0.0629 (0.0519) Prec@1 91.000 (91.512) Prec@5 99.000 (99.767) +2022-11-14 14:10:35,687 Epoch: [158][430/500] Time 0.052 (0.039) Data 0.002 (0.002) Loss 0.0665 (0.0523) Prec@1 90.000 (91.477) Prec@5 100.000 (99.773) +2022-11-14 14:10:36,140 Epoch: [158][440/500] Time 0.051 (0.039) Data 0.002 (0.002) Loss 0.0563 (0.0523) Prec@1 93.000 (91.511) Prec@5 100.000 (99.778) +2022-11-14 14:10:36,573 Epoch: [158][450/500] Time 0.038 (0.039) Data 0.002 (0.002) Loss 0.0504 (0.0523) Prec@1 92.000 (91.522) Prec@5 100.000 (99.783) +2022-11-14 14:10:37,025 Epoch: [158][460/500] Time 0.040 (0.039) Data 0.003 (0.002) Loss 0.0519 (0.0523) Prec@1 89.000 (91.468) Prec@5 100.000 (99.787) +2022-11-14 14:10:37,470 Epoch: [158][470/500] Time 0.038 (0.039) Data 0.002 (0.002) Loss 0.0414 (0.0521) Prec@1 94.000 (91.521) Prec@5 100.000 (99.792) +2022-11-14 14:10:37,957 Epoch: [158][480/500] Time 0.066 (0.039) Data 0.002 (0.002) Loss 0.0330 (0.0517) Prec@1 95.000 (91.592) Prec@5 100.000 (99.796) +2022-11-14 14:10:38,511 Epoch: [158][490/500] Time 0.054 (0.039) Data 0.002 (0.002) Loss 0.0722 (0.0521) Prec@1 86.000 (91.480) Prec@5 99.000 (99.780) +2022-11-14 14:10:38,943 Epoch: [158][499/500] Time 0.049 (0.040) Data 0.002 (0.002) Loss 0.0722 (0.0525) Prec@1 89.000 (91.431) Prec@5 99.000 (99.765) +2022-11-14 14:10:39,233 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0624 (0.0624) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:10:39,242 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0690) Prec@1 89.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 14:10:39,254 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0683) Prec@1 87.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 14:10:39,265 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0720) Prec@1 84.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:10:39,275 Test: [4/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0699) Prec@1 90.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 14:10:39,283 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0685) Prec@1 90.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 14:10:39,293 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0675) Prec@1 92.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 14:10:39,308 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0689) Prec@1 85.000 (88.625) Prec@5 100.000 (99.875) +2022-11-14 14:10:39,320 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0714) Prec@1 86.000 (88.333) Prec@5 99.000 (99.778) +2022-11-14 14:10:39,331 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0713) Prec@1 88.000 (88.300) Prec@5 99.000 (99.700) +2022-11-14 14:10:39,345 Test: [10/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0721) Prec@1 87.000 (88.182) Prec@5 100.000 (99.727) +2022-11-14 14:10:39,358 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0736) Prec@1 86.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 14:10:39,369 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0727) Prec@1 90.000 (88.154) Prec@5 100.000 (99.692) +2022-11-14 14:10:39,381 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0728) Prec@1 88.000 (88.143) Prec@5 100.000 (99.714) +2022-11-14 14:10:39,392 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0725) Prec@1 86.000 (88.000) Prec@5 100.000 (99.733) +2022-11-14 14:10:39,403 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0722) Prec@1 88.000 (88.000) Prec@5 99.000 (99.688) +2022-11-14 14:10:39,414 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0717) Prec@1 90.000 (88.118) Prec@5 99.000 (99.647) +2022-11-14 14:10:39,425 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0727) Prec@1 85.000 (87.944) Prec@5 100.000 (99.667) +2022-11-14 14:10:39,435 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0720) Prec@1 90.000 (88.053) Prec@5 99.000 (99.632) +2022-11-14 14:10:39,444 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0733) Prec@1 80.000 (87.650) Prec@5 100.000 (99.650) +2022-11-14 14:10:39,453 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0738) Prec@1 86.000 (87.571) Prec@5 99.000 (99.619) +2022-11-14 14:10:39,463 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0744) Prec@1 87.000 (87.545) Prec@5 100.000 (99.636) +2022-11-14 14:10:39,472 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1081 (0.0758) Prec@1 81.000 (87.261) Prec@5 98.000 (99.565) +2022-11-14 14:10:39,483 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0755) Prec@1 88.000 (87.292) Prec@5 100.000 (99.583) +2022-11-14 14:10:39,492 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1079 (0.0768) Prec@1 82.000 (87.080) Prec@5 99.000 (99.560) +2022-11-14 14:10:39,501 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1130 (0.0782) Prec@1 82.000 (86.885) Prec@5 98.000 (99.500) +2022-11-14 14:10:39,513 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0773) Prec@1 90.000 (87.000) Prec@5 100.000 (99.519) +2022-11-14 14:10:39,524 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0773) Prec@1 87.000 (87.000) Prec@5 100.000 (99.536) +2022-11-14 14:10:39,534 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0772) Prec@1 87.000 (87.000) Prec@5 100.000 (99.552) +2022-11-14 14:10:39,543 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0768) Prec@1 91.000 (87.133) Prec@5 100.000 (99.567) +2022-11-14 14:10:39,556 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0767) Prec@1 86.000 (87.097) Prec@5 98.000 (99.516) +2022-11-14 14:10:39,567 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0769) Prec@1 86.000 (87.062) Prec@5 99.000 (99.500) +2022-11-14 14:10:39,576 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0773) Prec@1 86.000 (87.030) Prec@5 99.000 (99.485) +2022-11-14 14:10:39,585 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0779) Prec@1 83.000 (86.912) Prec@5 98.000 (99.441) +2022-11-14 14:10:39,597 Test: [34/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0784) Prec@1 83.000 (86.800) Prec@5 99.000 (99.429) +2022-11-14 14:10:39,608 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0781) Prec@1 91.000 (86.917) Prec@5 100.000 (99.444) +2022-11-14 14:10:39,617 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0785) Prec@1 84.000 (86.838) Prec@5 98.000 (99.405) +2022-11-14 14:10:39,626 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0784) Prec@1 88.000 (86.868) Prec@5 100.000 (99.421) +2022-11-14 14:10:39,638 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0780) Prec@1 88.000 (86.897) Prec@5 99.000 (99.410) +2022-11-14 14:10:39,648 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0782) Prec@1 86.000 (86.875) Prec@5 99.000 (99.400) +2022-11-14 14:10:39,656 Test: [40/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.0791) Prec@1 83.000 (86.780) Prec@5 97.000 (99.341) +2022-11-14 14:10:39,667 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0787) Prec@1 90.000 (86.857) Prec@5 99.000 (99.333) +2022-11-14 14:10:39,678 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0782) Prec@1 93.000 (87.000) Prec@5 100.000 (99.349) +2022-11-14 14:10:39,686 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0783) Prec@1 85.000 (86.955) Prec@5 99.000 (99.341) +2022-11-14 14:10:39,696 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0783) Prec@1 88.000 (86.978) Prec@5 100.000 (99.356) +2022-11-14 14:10:39,709 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0786) Prec@1 84.000 (86.913) Prec@5 100.000 (99.370) +2022-11-14 14:10:39,720 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0783) Prec@1 87.000 (86.915) Prec@5 100.000 (99.383) +2022-11-14 14:10:39,729 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0789) Prec@1 81.000 (86.792) Prec@5 99.000 (99.375) +2022-11-14 14:10:39,738 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0437 (0.0782) Prec@1 94.000 (86.939) Prec@5 100.000 (99.388) +2022-11-14 14:10:39,751 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0787) Prec@1 83.000 (86.860) Prec@5 100.000 (99.400) +2022-11-14 14:10:39,761 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0789) Prec@1 85.000 (86.824) Prec@5 100.000 (99.412) +2022-11-14 14:10:39,770 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0791) Prec@1 84.000 (86.769) Prec@5 99.000 (99.404) +2022-11-14 14:10:39,779 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0790) Prec@1 86.000 (86.755) Prec@5 99.000 (99.396) +2022-11-14 14:10:39,791 Test: [53/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0788) Prec@1 90.000 (86.815) Prec@5 100.000 (99.407) +2022-11-14 14:10:39,803 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0790) Prec@1 87.000 (86.818) Prec@5 100.000 (99.418) +2022-11-14 14:10:39,812 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0789) Prec@1 88.000 (86.839) Prec@5 99.000 (99.411) +2022-11-14 14:10:39,821 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0787) Prec@1 90.000 (86.895) Prec@5 100.000 (99.421) +2022-11-14 14:10:39,833 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0786) Prec@1 89.000 (86.931) Prec@5 99.000 (99.414) +2022-11-14 14:10:39,845 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0790) Prec@1 82.000 (86.847) Prec@5 100.000 (99.424) +2022-11-14 14:10:39,855 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0791) Prec@1 86.000 (86.833) Prec@5 100.000 (99.433) +2022-11-14 14:10:39,865 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0793) Prec@1 86.000 (86.820) Prec@5 100.000 (99.443) +2022-11-14 14:10:39,879 Test: [61/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0791) Prec@1 88.000 (86.839) Prec@5 99.000 (99.435) +2022-11-14 14:10:39,890 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0791) Prec@1 89.000 (86.873) Prec@5 100.000 (99.444) +2022-11-14 14:10:39,899 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0416 (0.0785) Prec@1 94.000 (86.984) Prec@5 100.000 (99.453) +2022-11-14 14:10:39,908 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0787) Prec@1 84.000 (86.938) Prec@5 99.000 (99.446) +2022-11-14 14:10:39,920 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0786) Prec@1 89.000 (86.970) Prec@5 99.000 (99.439) +2022-11-14 14:10:39,932 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0787) Prec@1 86.000 (86.955) Prec@5 100.000 (99.448) +2022-11-14 14:10:39,940 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0786) Prec@1 88.000 (86.971) Prec@5 99.000 (99.441) +2022-11-14 14:10:39,948 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0787) Prec@1 85.000 (86.942) Prec@5 98.000 (99.420) +2022-11-14 14:10:39,960 Test: [69/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0790) Prec@1 84.000 (86.900) Prec@5 97.000 (99.386) +2022-11-14 14:10:39,972 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0793) Prec@1 83.000 (86.845) Prec@5 98.000 (99.366) +2022-11-14 14:10:39,980 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0792) Prec@1 88.000 (86.861) Prec@5 100.000 (99.375) +2022-11-14 14:10:39,987 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0793) Prec@1 87.000 (86.863) Prec@5 99.000 (99.370) +2022-11-14 14:10:40,000 Test: [73/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0791) Prec@1 88.000 (86.878) Prec@5 100.000 (99.378) +2022-11-14 14:10:40,011 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0793) Prec@1 83.000 (86.827) Prec@5 100.000 (99.387) +2022-11-14 14:10:40,020 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0791) Prec@1 89.000 (86.855) Prec@5 100.000 (99.395) +2022-11-14 14:10:40,029 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0790) Prec@1 90.000 (86.896) Prec@5 100.000 (99.403) +2022-11-14 14:10:40,041 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0791) Prec@1 85.000 (86.872) Prec@5 98.000 (99.385) +2022-11-14 14:10:40,050 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0791) Prec@1 86.000 (86.861) Prec@5 99.000 (99.380) +2022-11-14 14:10:40,063 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0791) Prec@1 87.000 (86.862) Prec@5 100.000 (99.388) +2022-11-14 14:10:40,074 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0790) Prec@1 87.000 (86.864) Prec@5 99.000 (99.383) +2022-11-14 14:10:40,083 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0791) Prec@1 86.000 (86.854) Prec@5 99.000 (99.378) +2022-11-14 14:10:40,093 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0793) Prec@1 84.000 (86.819) Prec@5 99.000 (99.373) +2022-11-14 14:10:40,104 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0791) Prec@1 90.000 (86.857) Prec@5 100.000 (99.381) +2022-11-14 14:10:40,115 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0793) Prec@1 86.000 (86.847) Prec@5 99.000 (99.376) +2022-11-14 14:10:40,125 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0796) Prec@1 83.000 (86.802) Prec@5 98.000 (99.360) +2022-11-14 14:10:40,134 Test: [86/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0794) Prec@1 89.000 (86.828) Prec@5 99.000 (99.356) +2022-11-14 14:10:40,145 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0795) Prec@1 85.000 (86.807) Prec@5 98.000 (99.341) +2022-11-14 14:10:40,156 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0794) Prec@1 87.000 (86.809) Prec@5 98.000 (99.326) +2022-11-14 14:10:40,165 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0794) Prec@1 89.000 (86.833) Prec@5 100.000 (99.333) +2022-11-14 14:10:40,175 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0791) Prec@1 89.000 (86.857) Prec@5 100.000 (99.341) +2022-11-14 14:10:40,184 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0788) Prec@1 92.000 (86.913) Prec@5 99.000 (99.337) +2022-11-14 14:10:40,193 Test: [92/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0788) Prec@1 85.000 (86.892) Prec@5 100.000 (99.344) +2022-11-14 14:10:40,202 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0789) Prec@1 86.000 (86.883) Prec@5 98.000 (99.330) +2022-11-14 14:10:40,211 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0789) Prec@1 86.000 (86.874) Prec@5 100.000 (99.337) +2022-11-14 14:10:40,221 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0787) Prec@1 89.000 (86.896) Prec@5 100.000 (99.344) +2022-11-14 14:10:40,230 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0512 (0.0785) Prec@1 92.000 (86.948) Prec@5 98.000 (99.330) +2022-11-14 14:10:40,239 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0787) Prec@1 86.000 (86.939) Prec@5 99.000 (99.327) +2022-11-14 14:10:40,247 Test: [98/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0789) Prec@1 82.000 (86.889) Prec@5 100.000 (99.333) +2022-11-14 14:10:40,255 Test: [99/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0789) Prec@1 89.000 (86.910) Prec@5 100.000 (99.340) +2022-11-14 14:10:40,320 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:10:40,655 Epoch: [159][0/500] Time 0.032 (0.032) Data 0.240 (0.240) Loss 0.0476 (0.0476) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:10:41,141 Epoch: [159][10/500] Time 0.053 (0.042) Data 0.002 (0.024) Loss 0.0514 (0.0495) Prec@1 91.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:10:41,674 Epoch: [159][20/500] Time 0.049 (0.045) Data 0.002 (0.013) Loss 0.0376 (0.0455) Prec@1 93.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:10:42,173 Epoch: [159][30/500] Time 0.039 (0.045) Data 0.002 (0.010) Loss 0.0619 (0.0496) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:10:42,584 Epoch: [159][40/500] Time 0.037 (0.043) Data 0.002 (0.008) Loss 0.0679 (0.0533) Prec@1 90.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:10:43,024 Epoch: [159][50/500] Time 0.033 (0.042) Data 0.002 (0.007) Loss 0.0423 (0.0514) Prec@1 93.000 (92.167) Prec@5 100.000 (100.000) +2022-11-14 14:10:43,482 Epoch: [159][60/500] Time 0.036 (0.042) Data 0.002 (0.006) Loss 0.0453 (0.0506) Prec@1 92.000 (92.143) Prec@5 100.000 (100.000) +2022-11-14 14:10:43,993 Epoch: [159][70/500] Time 0.031 (0.043) Data 0.002 (0.005) Loss 0.0642 (0.0523) Prec@1 86.000 (91.375) Prec@5 97.000 (99.625) +2022-11-14 14:10:44,501 Epoch: [159][80/500] Time 0.048 (0.043) Data 0.002 (0.005) Loss 0.0461 (0.0516) Prec@1 93.000 (91.556) Prec@5 100.000 (99.667) +2022-11-14 14:10:44,900 Epoch: [159][90/500] Time 0.035 (0.042) Data 0.002 (0.005) Loss 0.0389 (0.0503) Prec@1 93.000 (91.700) Prec@5 100.000 (99.700) +2022-11-14 14:10:45,412 Epoch: [159][100/500] Time 0.074 (0.043) Data 0.002 (0.004) Loss 0.0728 (0.0524) Prec@1 89.000 (91.455) Prec@5 100.000 (99.727) +2022-11-14 14:10:45,826 Epoch: [159][110/500] Time 0.037 (0.042) Data 0.003 (0.004) Loss 0.0542 (0.0525) Prec@1 90.000 (91.333) Prec@5 100.000 (99.750) +2022-11-14 14:10:46,250 Epoch: [159][120/500] Time 0.047 (0.042) Data 0.002 (0.004) Loss 0.0367 (0.0513) Prec@1 93.000 (91.462) Prec@5 99.000 (99.692) +2022-11-14 14:10:46,662 Epoch: [159][130/500] Time 0.038 (0.041) Data 0.002 (0.004) Loss 0.0491 (0.0511) Prec@1 92.000 (91.500) Prec@5 100.000 (99.714) +2022-11-14 14:10:47,085 Epoch: [159][140/500] Time 0.039 (0.041) Data 0.002 (0.004) Loss 0.0628 (0.0519) Prec@1 90.000 (91.400) Prec@5 100.000 (99.733) +2022-11-14 14:10:47,506 Epoch: [159][150/500] Time 0.039 (0.041) Data 0.002 (0.004) Loss 0.0423 (0.0513) Prec@1 93.000 (91.500) Prec@5 100.000 (99.750) +2022-11-14 14:10:47,971 Epoch: [159][160/500] Time 0.034 (0.041) Data 0.002 (0.003) Loss 0.0645 (0.0521) Prec@1 90.000 (91.412) Prec@5 98.000 (99.647) +2022-11-14 14:10:48,490 Epoch: [159][170/500] Time 0.061 (0.041) Data 0.003 (0.003) Loss 0.0538 (0.0522) Prec@1 91.000 (91.389) Prec@5 100.000 (99.667) +2022-11-14 14:10:49,085 Epoch: [159][180/500] Time 0.057 (0.042) Data 0.003 (0.003) Loss 0.0407 (0.0516) Prec@1 94.000 (91.526) Prec@5 99.000 (99.632) +2022-11-14 14:10:49,529 Epoch: [159][190/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0516 (0.0516) Prec@1 91.000 (91.500) Prec@5 100.000 (99.650) +2022-11-14 14:10:49,964 Epoch: [159][200/500] Time 0.033 (0.042) Data 0.002 (0.003) Loss 0.0509 (0.0516) Prec@1 91.000 (91.476) Prec@5 100.000 (99.667) +2022-11-14 14:10:50,399 Epoch: [159][210/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0476 (0.0514) Prec@1 91.000 (91.455) Prec@5 98.000 (99.591) +2022-11-14 14:10:50,799 Epoch: [159][220/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0611 (0.0518) Prec@1 89.000 (91.348) Prec@5 100.000 (99.609) +2022-11-14 14:10:51,285 Epoch: [159][230/500] Time 0.073 (0.041) Data 0.002 (0.003) Loss 0.0584 (0.0521) Prec@1 89.000 (91.250) Prec@5 100.000 (99.625) +2022-11-14 14:10:51,728 Epoch: [159][240/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0709 (0.0528) Prec@1 85.000 (91.000) Prec@5 100.000 (99.640) +2022-11-14 14:10:52,144 Epoch: [159][250/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0704 (0.0535) Prec@1 89.000 (90.923) Prec@5 99.000 (99.615) +2022-11-14 14:10:52,680 Epoch: [159][260/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0932 (0.0550) Prec@1 84.000 (90.667) Prec@5 99.000 (99.593) +2022-11-14 14:10:53,078 Epoch: [159][270/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0763 (0.0557) Prec@1 88.000 (90.571) Prec@5 99.000 (99.571) +2022-11-14 14:10:53,498 Epoch: [159][280/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0440 (0.0553) Prec@1 93.000 (90.655) Prec@5 99.000 (99.552) +2022-11-14 14:10:53,914 Epoch: [159][290/500] Time 0.051 (0.041) Data 0.002 (0.003) Loss 0.0411 (0.0549) Prec@1 94.000 (90.767) Prec@5 100.000 (99.567) +2022-11-14 14:10:54,367 Epoch: [159][300/500] Time 0.031 (0.041) Data 0.002 (0.003) Loss 0.0299 (0.0540) Prec@1 97.000 (90.968) Prec@5 100.000 (99.581) +2022-11-14 14:10:54,775 Epoch: [159][310/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0327 (0.0534) Prec@1 94.000 (91.062) Prec@5 100.000 (99.594) +2022-11-14 14:10:55,214 Epoch: [159][320/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0802 (0.0542) Prec@1 85.000 (90.879) Prec@5 98.000 (99.545) +2022-11-14 14:10:55,625 Epoch: [159][330/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0413 (0.0538) Prec@1 93.000 (90.941) Prec@5 100.000 (99.559) +2022-11-14 14:10:56,186 Epoch: [159][340/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0423 (0.0535) Prec@1 93.000 (91.000) Prec@5 100.000 (99.571) +2022-11-14 14:10:56,599 Epoch: [159][350/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0707 (0.0540) Prec@1 88.000 (90.917) Prec@5 100.000 (99.583) +2022-11-14 14:10:57,018 Epoch: [159][360/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0856 (0.0548) Prec@1 86.000 (90.784) Prec@5 99.000 (99.568) +2022-11-14 14:10:57,438 Epoch: [159][370/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0671 (0.0551) Prec@1 91.000 (90.789) Prec@5 100.000 (99.579) +2022-11-14 14:10:57,861 Epoch: [159][380/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0615 (0.0553) Prec@1 88.000 (90.718) Prec@5 100.000 (99.590) +2022-11-14 14:10:58,287 Epoch: [159][390/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0539 (0.0553) Prec@1 92.000 (90.750) Prec@5 100.000 (99.600) +2022-11-14 14:10:58,766 Epoch: [159][400/500] Time 0.072 (0.041) Data 0.002 (0.003) Loss 0.0462 (0.0551) Prec@1 92.000 (90.780) Prec@5 100.000 (99.610) +2022-11-14 14:10:59,206 Epoch: [159][410/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0450 (0.0548) Prec@1 92.000 (90.810) Prec@5 99.000 (99.595) +2022-11-14 14:10:59,615 Epoch: [159][420/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0457 (0.0546) Prec@1 92.000 (90.837) Prec@5 99.000 (99.581) +2022-11-14 14:11:00,132 Epoch: [159][430/500] Time 0.051 (0.041) Data 0.002 (0.003) Loss 0.0772 (0.0551) Prec@1 86.000 (90.727) Prec@5 100.000 (99.591) +2022-11-14 14:11:00,559 Epoch: [159][440/500] Time 0.034 (0.041) Data 0.002 (0.003) Loss 0.0285 (0.0545) Prec@1 93.000 (90.778) Prec@5 99.000 (99.578) +2022-11-14 14:11:00,974 Epoch: [159][450/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0497 (0.0544) Prec@1 93.000 (90.826) Prec@5 100.000 (99.587) +2022-11-14 14:11:01,406 Epoch: [159][460/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0613 (0.0546) Prec@1 92.000 (90.851) Prec@5 100.000 (99.596) +2022-11-14 14:11:01,845 Epoch: [159][470/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0534 (0.0545) Prec@1 91.000 (90.854) Prec@5 99.000 (99.583) +2022-11-14 14:11:02,262 Epoch: [159][480/500] Time 0.037 (0.040) Data 0.002 (0.002) Loss 0.0532 (0.0545) Prec@1 92.000 (90.878) Prec@5 99.000 (99.571) +2022-11-14 14:11:02,704 Epoch: [159][490/500] Time 0.039 (0.040) Data 0.002 (0.002) Loss 0.0678 (0.0548) Prec@1 89.000 (90.840) Prec@5 100.000 (99.580) +2022-11-14 14:11:03,206 Epoch: [159][499/500] Time 0.058 (0.040) Data 0.002 (0.002) Loss 0.0447 (0.0546) Prec@1 94.000 (90.902) Prec@5 98.000 (99.549) +2022-11-14 14:11:03,514 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0609 (0.0609) Prec@1 90.000 (90.000) Prec@5 98.000 (98.000) +2022-11-14 14:11:03,529 Test: [1/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0583 (0.0596) Prec@1 88.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 14:11:03,542 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0997 (0.0730) Prec@1 81.000 (86.333) Prec@5 98.000 (98.667) +2022-11-14 14:11:03,553 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0844 (0.0758) Prec@1 84.000 (85.750) Prec@5 98.000 (98.500) +2022-11-14 14:11:03,562 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0619 (0.0730) Prec@1 88.000 (86.200) Prec@5 100.000 (98.800) +2022-11-14 14:11:03,574 Test: [5/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0367 (0.0670) Prec@1 95.000 (87.667) Prec@5 100.000 (99.000) +2022-11-14 14:11:03,587 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0716 (0.0676) Prec@1 90.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:11:03,598 Test: [7/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0944 (0.0710) Prec@1 84.000 (87.500) Prec@5 98.000 (98.875) +2022-11-14 14:11:03,608 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1190 (0.0763) Prec@1 82.000 (86.889) Prec@5 99.000 (98.889) +2022-11-14 14:11:03,621 Test: [9/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0759) Prec@1 87.000 (86.900) Prec@5 99.000 (98.900) +2022-11-14 14:11:03,633 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0748) Prec@1 88.000 (87.000) Prec@5 100.000 (99.000) +2022-11-14 14:11:03,643 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0760) Prec@1 87.000 (87.000) Prec@5 100.000 (99.083) +2022-11-14 14:11:03,656 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0485 (0.0739) Prec@1 91.000 (87.308) Prec@5 98.000 (99.000) +2022-11-14 14:11:03,668 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0748) Prec@1 87.000 (87.286) Prec@5 99.000 (99.000) +2022-11-14 14:11:03,682 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1011 (0.0765) Prec@1 82.000 (86.933) Prec@5 99.000 (99.000) +2022-11-14 14:11:03,695 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0766) Prec@1 84.000 (86.750) Prec@5 99.000 (99.000) +2022-11-14 14:11:03,708 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0529 (0.0752) Prec@1 92.000 (87.059) Prec@5 98.000 (98.941) +2022-11-14 14:11:03,722 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1278 (0.0782) Prec@1 79.000 (86.611) Prec@5 100.000 (99.000) +2022-11-14 14:11:03,734 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0784) Prec@1 84.000 (86.474) Prec@5 99.000 (99.000) +2022-11-14 14:11:03,747 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1042 (0.0797) Prec@1 82.000 (86.250) Prec@5 97.000 (98.900) +2022-11-14 14:11:03,759 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0791) Prec@1 90.000 (86.429) Prec@5 98.000 (98.857) +2022-11-14 14:11:03,774 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0790) Prec@1 83.000 (86.273) Prec@5 99.000 (98.864) +2022-11-14 14:11:03,789 Test: [22/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0995 (0.0799) Prec@1 82.000 (86.087) Prec@5 99.000 (98.870) +2022-11-14 14:11:03,804 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0794) Prec@1 87.000 (86.125) Prec@5 99.000 (98.875) +2022-11-14 14:11:03,824 Test: [24/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0797) Prec@1 84.000 (86.040) Prec@5 99.000 (98.880) +2022-11-14 14:11:03,846 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1170 (0.0812) Prec@1 80.000 (85.808) Prec@5 98.000 (98.846) +2022-11-14 14:11:03,868 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0550 (0.0802) Prec@1 90.000 (85.963) Prec@5 100.000 (98.889) +2022-11-14 14:11:03,888 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0803) Prec@1 87.000 (86.000) Prec@5 99.000 (98.893) +2022-11-14 14:11:03,906 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0803) Prec@1 89.000 (86.103) Prec@5 97.000 (98.828) +2022-11-14 14:11:03,921 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0804) Prec@1 85.000 (86.067) Prec@5 99.000 (98.833) +2022-11-14 14:11:03,938 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0807) Prec@1 82.000 (85.935) Prec@5 99.000 (98.839) +2022-11-14 14:11:03,957 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.0813) Prec@1 84.000 (85.875) Prec@5 98.000 (98.812) +2022-11-14 14:11:03,971 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0814) Prec@1 86.000 (85.879) Prec@5 100.000 (98.848) +2022-11-14 14:11:03,984 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1190 (0.0825) Prec@1 80.000 (85.706) Prec@5 97.000 (98.794) +2022-11-14 14:11:03,997 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0826) Prec@1 86.000 (85.714) Prec@5 98.000 (98.771) +2022-11-14 14:11:04,015 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0824) Prec@1 85.000 (85.694) Prec@5 100.000 (98.806) +2022-11-14 14:11:04,033 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0828) Prec@1 84.000 (85.649) Prec@5 98.000 (98.784) +2022-11-14 14:11:04,049 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0829) Prec@1 85.000 (85.632) Prec@5 99.000 (98.789) +2022-11-14 14:11:04,068 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0827) Prec@1 88.000 (85.692) Prec@5 98.000 (98.769) +2022-11-14 14:11:04,082 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0825) Prec@1 89.000 (85.775) Prec@5 98.000 (98.750) +2022-11-14 14:11:04,095 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0830) Prec@1 82.000 (85.683) Prec@5 98.000 (98.732) +2022-11-14 14:11:04,108 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0829) Prec@1 88.000 (85.738) Prec@5 98.000 (98.714) +2022-11-14 14:11:04,120 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0824) Prec@1 90.000 (85.837) Prec@5 100.000 (98.744) +2022-11-14 14:11:04,137 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0824) Prec@1 87.000 (85.864) Prec@5 99.000 (98.750) +2022-11-14 14:11:04,158 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0823) Prec@1 89.000 (85.933) Prec@5 98.000 (98.733) +2022-11-14 14:11:04,173 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1140 (0.0830) Prec@1 81.000 (85.826) Prec@5 98.000 (98.717) +2022-11-14 14:11:04,187 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0512 (0.0823) Prec@1 92.000 (85.957) Prec@5 100.000 (98.745) +2022-11-14 14:11:04,201 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0825) Prec@1 86.000 (85.958) Prec@5 99.000 (98.750) +2022-11-14 14:11:04,215 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0822) Prec@1 88.000 (86.000) Prec@5 99.000 (98.755) +2022-11-14 14:11:04,229 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1172 (0.0829) Prec@1 80.000 (85.880) Prec@5 99.000 (98.760) +2022-11-14 14:11:04,248 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0830) Prec@1 85.000 (85.863) Prec@5 98.000 (98.745) +2022-11-14 14:11:04,269 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0831) Prec@1 87.000 (85.885) Prec@5 99.000 (98.750) +2022-11-14 14:11:04,284 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0833) Prec@1 84.000 (85.849) Prec@5 98.000 (98.736) +2022-11-14 14:11:04,299 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0831) Prec@1 85.000 (85.833) Prec@5 100.000 (98.759) +2022-11-14 14:11:04,313 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0832) Prec@1 84.000 (85.800) Prec@5 100.000 (98.782) +2022-11-14 14:11:04,327 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0831) Prec@1 89.000 (85.857) Prec@5 99.000 (98.786) +2022-11-14 14:11:04,344 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0832) Prec@1 83.000 (85.807) Prec@5 99.000 (98.789) +2022-11-14 14:11:04,359 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0829) Prec@1 91.000 (85.897) Prec@5 100.000 (98.810) +2022-11-14 14:11:04,373 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0832) Prec@1 82.000 (85.831) Prec@5 100.000 (98.831) +2022-11-14 14:11:04,386 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0833) Prec@1 85.000 (85.817) Prec@5 100.000 (98.850) +2022-11-14 14:11:04,401 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0833) Prec@1 87.000 (85.836) Prec@5 100.000 (98.869) +2022-11-14 14:11:04,415 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0836) Prec@1 84.000 (85.806) Prec@5 100.000 (98.887) +2022-11-14 14:11:04,429 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0834) Prec@1 88.000 (85.841) Prec@5 100.000 (98.905) +2022-11-14 14:11:04,444 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0830) Prec@1 90.000 (85.906) Prec@5 100.000 (98.922) +2022-11-14 14:11:04,459 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0830) Prec@1 87.000 (85.923) Prec@5 99.000 (98.923) +2022-11-14 14:11:04,473 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0830) Prec@1 83.000 (85.879) Prec@5 99.000 (98.924) +2022-11-14 14:11:04,488 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0415 (0.0824) Prec@1 93.000 (85.985) Prec@5 100.000 (98.940) +2022-11-14 14:11:04,505 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0821) Prec@1 88.000 (86.015) Prec@5 97.000 (98.912) +2022-11-14 14:11:04,519 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0820) Prec@1 91.000 (86.087) Prec@5 99.000 (98.913) +2022-11-14 14:11:04,533 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0822) Prec@1 84.000 (86.057) Prec@5 100.000 (98.929) +2022-11-14 14:11:04,546 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0824) Prec@1 85.000 (86.042) Prec@5 98.000 (98.915) +2022-11-14 14:11:04,560 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0821) Prec@1 91.000 (86.111) Prec@5 99.000 (98.917) +2022-11-14 14:11:04,575 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0819) Prec@1 91.000 (86.178) Prec@5 100.000 (98.932) +2022-11-14 14:11:04,589 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0817) Prec@1 90.000 (86.230) Prec@5 100.000 (98.946) +2022-11-14 14:11:04,604 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0820) Prec@1 81.000 (86.160) Prec@5 98.000 (98.933) +2022-11-14 14:11:04,620 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0819) Prec@1 87.000 (86.171) Prec@5 99.000 (98.934) +2022-11-14 14:11:04,636 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0818) Prec@1 87.000 (86.182) Prec@5 100.000 (98.948) +2022-11-14 14:11:04,651 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0817) Prec@1 87.000 (86.192) Prec@5 98.000 (98.936) +2022-11-14 14:11:04,666 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0818) Prec@1 86.000 (86.190) Prec@5 100.000 (98.949) +2022-11-14 14:11:04,680 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0819) Prec@1 80.000 (86.112) Prec@5 99.000 (98.950) +2022-11-14 14:11:04,695 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0820) Prec@1 86.000 (86.111) Prec@5 98.000 (98.938) +2022-11-14 14:11:04,710 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0821) Prec@1 82.000 (86.061) Prec@5 99.000 (98.939) +2022-11-14 14:11:04,725 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0820) Prec@1 84.000 (86.036) Prec@5 100.000 (98.952) +2022-11-14 14:11:04,741 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0819) Prec@1 88.000 (86.060) Prec@5 99.000 (98.952) +2022-11-14 14:11:04,755 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0820) Prec@1 82.000 (86.012) Prec@5 100.000 (98.965) +2022-11-14 14:11:04,768 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1231 (0.0825) Prec@1 82.000 (85.965) Prec@5 100.000 (98.977) +2022-11-14 14:11:04,781 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0825) Prec@1 81.000 (85.908) Prec@5 99.000 (98.977) +2022-11-14 14:11:04,797 Test: [87/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0823) Prec@1 90.000 (85.955) Prec@5 98.000 (98.966) +2022-11-14 14:11:04,812 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0824) Prec@1 85.000 (85.944) Prec@5 100.000 (98.978) +2022-11-14 14:11:04,825 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0823) Prec@1 88.000 (85.967) Prec@5 99.000 (98.978) +2022-11-14 14:11:04,840 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0819) Prec@1 93.000 (86.044) Prec@5 99.000 (98.978) +2022-11-14 14:11:04,857 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0817) Prec@1 89.000 (86.076) Prec@5 99.000 (98.978) +2022-11-14 14:11:04,875 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0821) Prec@1 79.000 (86.000) Prec@5 100.000 (98.989) +2022-11-14 14:11:04,889 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0819) Prec@1 88.000 (86.021) Prec@5 100.000 (99.000) +2022-11-14 14:11:04,903 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0819) Prec@1 87.000 (86.032) Prec@5 99.000 (99.000) +2022-11-14 14:11:04,918 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0817) Prec@1 90.000 (86.073) Prec@5 99.000 (99.000) +2022-11-14 14:11:04,932 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0815) Prec@1 90.000 (86.113) Prec@5 98.000 (98.990) +2022-11-14 14:11:04,946 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0817) Prec@1 82.000 (86.071) Prec@5 99.000 (98.990) +2022-11-14 14:11:04,960 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.0820) Prec@1 81.000 (86.020) Prec@5 99.000 (98.990) +2022-11-14 14:11:04,975 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0821) Prec@1 83.000 (85.990) Prec@5 99.000 (98.990) +2022-11-14 14:11:05,034 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:11:05,377 Epoch: [160][0/500] Time 0.037 (0.037) Data 0.239 (0.239) Loss 0.0393 (0.0393) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:11:05,671 Epoch: [160][10/500] Time 0.021 (0.027) Data 0.002 (0.024) Loss 0.0365 (0.0379) Prec@1 94.000 (93.500) Prec@5 99.000 (99.000) +2022-11-14 14:11:05,940 Epoch: [160][20/500] Time 0.030 (0.025) Data 0.002 (0.013) Loss 0.0439 (0.0399) Prec@1 93.000 (93.333) Prec@5 100.000 (99.333) +2022-11-14 14:11:06,344 Epoch: [160][30/500] Time 0.038 (0.029) Data 0.002 (0.010) Loss 0.0491 (0.0422) Prec@1 91.000 (92.750) Prec@5 100.000 (99.500) +2022-11-14 14:11:06,839 Epoch: [160][40/500] Time 0.035 (0.033) Data 0.002 (0.008) Loss 0.0733 (0.0484) Prec@1 88.000 (91.800) Prec@5 99.000 (99.400) +2022-11-14 14:11:07,266 Epoch: [160][50/500] Time 0.044 (0.034) Data 0.002 (0.007) Loss 0.0437 (0.0476) Prec@1 94.000 (92.167) Prec@5 100.000 (99.500) +2022-11-14 14:11:07,703 Epoch: [160][60/500] Time 0.052 (0.035) Data 0.002 (0.006) Loss 0.0517 (0.0482) Prec@1 91.000 (92.000) Prec@5 100.000 (99.571) +2022-11-14 14:11:08,137 Epoch: [160][70/500] Time 0.039 (0.035) Data 0.002 (0.005) Loss 0.0392 (0.0471) Prec@1 91.000 (91.875) Prec@5 99.000 (99.500) +2022-11-14 14:11:08,639 Epoch: [160][80/500] Time 0.036 (0.036) Data 0.002 (0.005) Loss 0.0412 (0.0465) Prec@1 93.000 (92.000) Prec@5 100.000 (99.556) +2022-11-14 14:11:09,066 Epoch: [160][90/500] Time 0.038 (0.036) Data 0.002 (0.005) Loss 0.0417 (0.0460) Prec@1 92.000 (92.000) Prec@5 99.000 (99.500) +2022-11-14 14:11:09,490 Epoch: [160][100/500] Time 0.036 (0.037) Data 0.002 (0.004) Loss 0.0406 (0.0455) Prec@1 94.000 (92.182) Prec@5 100.000 (99.545) +2022-11-14 14:11:09,966 Epoch: [160][110/500] Time 0.034 (0.037) Data 0.002 (0.004) Loss 0.0430 (0.0453) Prec@1 93.000 (92.250) Prec@5 100.000 (99.583) +2022-11-14 14:11:10,391 Epoch: [160][120/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0432 (0.0451) Prec@1 92.000 (92.231) Prec@5 100.000 (99.615) +2022-11-14 14:11:10,833 Epoch: [160][130/500] Time 0.037 (0.037) Data 0.002 (0.004) Loss 0.0641 (0.0465) Prec@1 89.000 (92.000) Prec@5 100.000 (99.643) +2022-11-14 14:11:11,320 Epoch: [160][140/500] Time 0.036 (0.038) Data 0.002 (0.004) Loss 0.0330 (0.0456) Prec@1 95.000 (92.200) Prec@5 100.000 (99.667) +2022-11-14 14:11:11,742 Epoch: [160][150/500] Time 0.033 (0.038) Data 0.002 (0.004) Loss 0.0554 (0.0462) Prec@1 90.000 (92.062) Prec@5 100.000 (99.688) +2022-11-14 14:11:12,259 Epoch: [160][160/500] Time 0.063 (0.038) Data 0.002 (0.003) Loss 0.0371 (0.0456) Prec@1 96.000 (92.294) Prec@5 100.000 (99.706) +2022-11-14 14:11:12,797 Epoch: [160][170/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0375 (0.0452) Prec@1 95.000 (92.444) Prec@5 99.000 (99.667) +2022-11-14 14:11:13,211 Epoch: [160][180/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0490 (0.0454) Prec@1 92.000 (92.421) Prec@5 100.000 (99.684) +2022-11-14 14:11:13,634 Epoch: [160][190/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0397 (0.0451) Prec@1 95.000 (92.550) Prec@5 100.000 (99.700) +2022-11-14 14:11:14,058 Epoch: [160][200/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0588 (0.0458) Prec@1 91.000 (92.476) Prec@5 100.000 (99.714) +2022-11-14 14:11:14,548 Epoch: [160][210/500] Time 0.090 (0.039) Data 0.002 (0.003) Loss 0.0741 (0.0470) Prec@1 87.000 (92.227) Prec@5 99.000 (99.682) +2022-11-14 14:11:15,149 Epoch: [160][220/500] Time 0.055 (0.040) Data 0.002 (0.003) Loss 0.0566 (0.0475) Prec@1 91.000 (92.174) Prec@5 99.000 (99.652) +2022-11-14 14:11:15,731 Epoch: [160][230/500] Time 0.054 (0.040) Data 0.002 (0.003) Loss 0.0407 (0.0472) Prec@1 92.000 (92.167) Prec@5 100.000 (99.667) +2022-11-14 14:11:16,329 Epoch: [160][240/500] Time 0.059 (0.041) Data 0.002 (0.003) Loss 0.0475 (0.0472) Prec@1 92.000 (92.160) Prec@5 99.000 (99.640) +2022-11-14 14:11:16,771 Epoch: [160][250/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0568 (0.0476) Prec@1 89.000 (92.038) Prec@5 100.000 (99.654) +2022-11-14 14:11:17,241 Epoch: [160][260/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0598 (0.0480) Prec@1 91.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:11:17,722 Epoch: [160][270/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0333 (0.0475) Prec@1 95.000 (92.107) Prec@5 100.000 (99.679) +2022-11-14 14:11:18,189 Epoch: [160][280/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0491 (0.0475) Prec@1 92.000 (92.103) Prec@5 100.000 (99.690) +2022-11-14 14:11:18,668 Epoch: [160][290/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0571 (0.0479) Prec@1 91.000 (92.067) Prec@5 100.000 (99.700) +2022-11-14 14:11:19,132 Epoch: [160][300/500] Time 0.030 (0.041) Data 0.002 (0.003) Loss 0.0418 (0.0477) Prec@1 92.000 (92.065) Prec@5 100.000 (99.710) +2022-11-14 14:11:19,602 Epoch: [160][310/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0447 (0.0476) Prec@1 91.000 (92.031) Prec@5 100.000 (99.719) +2022-11-14 14:11:20,077 Epoch: [160][320/500] Time 0.062 (0.041) Data 0.002 (0.003) Loss 0.0703 (0.0483) Prec@1 89.000 (91.939) Prec@5 100.000 (99.727) +2022-11-14 14:11:20,547 Epoch: [160][330/500] Time 0.082 (0.041) Data 0.002 (0.003) Loss 0.0426 (0.0481) Prec@1 95.000 (92.029) Prec@5 100.000 (99.735) +2022-11-14 14:11:20,997 Epoch: [160][340/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0655 (0.0486) Prec@1 90.000 (91.971) Prec@5 99.000 (99.714) +2022-11-14 14:11:21,412 Epoch: [160][350/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0597 (0.0489) Prec@1 91.000 (91.944) Prec@5 100.000 (99.722) +2022-11-14 14:11:21,866 Epoch: [160][360/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0669 (0.0494) Prec@1 92.000 (91.946) Prec@5 100.000 (99.730) +2022-11-14 14:11:22,335 Epoch: [160][370/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0471 (0.0493) Prec@1 94.000 (92.000) Prec@5 100.000 (99.737) +2022-11-14 14:11:22,790 Epoch: [160][380/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0376 (0.0490) Prec@1 95.000 (92.077) Prec@5 98.000 (99.692) +2022-11-14 14:11:23,263 Epoch: [160][390/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0794 (0.0498) Prec@1 89.000 (92.000) Prec@5 99.000 (99.675) +2022-11-14 14:11:23,741 Epoch: [160][400/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0647 (0.0501) Prec@1 89.000 (91.927) Prec@5 99.000 (99.659) +2022-11-14 14:11:24,207 Epoch: [160][410/500] Time 0.038 (0.041) Data 0.001 (0.003) Loss 0.0499 (0.0501) Prec@1 89.000 (91.857) Prec@5 100.000 (99.667) +2022-11-14 14:11:24,667 Epoch: [160][420/500] Time 0.034 (0.041) Data 0.002 (0.003) Loss 0.0515 (0.0502) Prec@1 92.000 (91.860) Prec@5 100.000 (99.674) +2022-11-14 14:11:25,132 Epoch: [160][430/500] Time 0.031 (0.041) Data 0.002 (0.003) Loss 0.0662 (0.0505) Prec@1 90.000 (91.818) Prec@5 99.000 (99.659) +2022-11-14 14:11:25,606 Epoch: [160][440/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0284 (0.0500) Prec@1 97.000 (91.933) Prec@5 100.000 (99.667) +2022-11-14 14:11:26,107 Epoch: [160][450/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0506 (0.0501) Prec@1 91.000 (91.913) Prec@5 100.000 (99.674) +2022-11-14 14:11:26,583 Epoch: [160][460/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0569 (0.0502) Prec@1 90.000 (91.872) Prec@5 99.000 (99.660) +2022-11-14 14:11:27,019 Epoch: [160][470/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0575 (0.0504) Prec@1 93.000 (91.896) Prec@5 100.000 (99.667) +2022-11-14 14:11:27,550 Epoch: [160][480/500] Time 0.048 (0.041) Data 0.002 (0.003) Loss 0.0557 (0.0505) Prec@1 90.000 (91.857) Prec@5 100.000 (99.673) +2022-11-14 14:11:27,972 Epoch: [160][490/500] Time 0.039 (0.041) Data 0.002 (0.003) Loss 0.0827 (0.0511) Prec@1 87.000 (91.760) Prec@5 99.000 (99.660) +2022-11-14 14:11:28,371 Epoch: [160][499/500] Time 0.052 (0.041) Data 0.002 (0.002) Loss 0.0603 (0.0513) Prec@1 91.000 (91.745) Prec@5 100.000 (99.667) +2022-11-14 14:11:28,671 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0751 (0.0751) Prec@1 90.000 (90.000) Prec@5 98.000 (98.000) +2022-11-14 14:11:28,686 Test: [1/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0974 (0.0862) Prec@1 85.000 (87.500) Prec@5 100.000 (99.000) +2022-11-14 14:11:28,697 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0718 (0.0814) Prec@1 89.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 14:11:28,708 Test: [3/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0931 (0.0843) Prec@1 83.000 (86.750) Prec@5 98.000 (99.000) +2022-11-14 14:11:28,719 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0984 (0.0872) Prec@1 85.000 (86.400) Prec@5 100.000 (99.200) +2022-11-14 14:11:28,734 Test: [5/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0513 (0.0812) Prec@1 90.000 (87.000) Prec@5 100.000 (99.333) +2022-11-14 14:11:28,746 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0733 (0.0801) Prec@1 88.000 (87.143) Prec@5 99.000 (99.286) +2022-11-14 14:11:28,759 Test: [7/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0917 (0.0815) Prec@1 84.000 (86.750) Prec@5 100.000 (99.375) +2022-11-14 14:11:28,772 Test: [8/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0954 (0.0830) Prec@1 85.000 (86.556) Prec@5 99.000 (99.333) +2022-11-14 14:11:28,787 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0623 (0.0810) Prec@1 90.000 (86.900) Prec@5 98.000 (99.200) +2022-11-14 14:11:28,801 Test: [10/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0735 (0.0803) Prec@1 87.000 (86.909) Prec@5 100.000 (99.273) +2022-11-14 14:11:28,814 Test: [11/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0797 (0.0802) Prec@1 88.000 (87.000) Prec@5 99.000 (99.250) +2022-11-14 14:11:28,828 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0641 (0.0790) Prec@1 88.000 (87.077) Prec@5 99.000 (99.231) +2022-11-14 14:11:28,841 Test: [13/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1013 (0.0806) Prec@1 82.000 (86.714) Prec@5 98.000 (99.143) +2022-11-14 14:11:28,855 Test: [14/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0919 (0.0813) Prec@1 84.000 (86.533) Prec@5 100.000 (99.200) +2022-11-14 14:11:28,869 Test: [15/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0904 (0.0819) Prec@1 83.000 (86.312) Prec@5 100.000 (99.250) +2022-11-14 14:11:28,883 Test: [16/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0622 (0.0808) Prec@1 90.000 (86.529) Prec@5 98.000 (99.176) +2022-11-14 14:11:28,899 Test: [17/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0981 (0.0817) Prec@1 83.000 (86.333) Prec@5 99.000 (99.167) +2022-11-14 14:11:28,911 Test: [18/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0864 (0.0820) Prec@1 86.000 (86.316) Prec@5 99.000 (99.158) +2022-11-14 14:11:28,922 Test: [19/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1024 (0.0830) Prec@1 83.000 (86.150) Prec@5 98.000 (99.100) +2022-11-14 14:11:28,936 Test: [20/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0799 (0.0828) Prec@1 88.000 (86.238) Prec@5 99.000 (99.095) +2022-11-14 14:11:28,949 Test: [21/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0863 (0.0830) Prec@1 85.000 (86.182) Prec@5 100.000 (99.136) +2022-11-14 14:11:28,963 Test: [22/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0962 (0.0836) Prec@1 83.000 (86.043) Prec@5 100.000 (99.174) +2022-11-14 14:11:28,976 Test: [23/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0856 (0.0837) Prec@1 87.000 (86.083) Prec@5 99.000 (99.167) +2022-11-14 14:11:28,989 Test: [24/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0809 (0.0835) Prec@1 89.000 (86.200) Prec@5 100.000 (99.200) +2022-11-14 14:11:29,000 Test: [25/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1317 (0.0854) Prec@1 81.000 (86.000) Prec@5 96.000 (99.077) +2022-11-14 14:11:29,010 Test: [26/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0699 (0.0848) Prec@1 89.000 (86.111) Prec@5 100.000 (99.111) +2022-11-14 14:11:29,021 Test: [27/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0782 (0.0846) Prec@1 86.000 (86.107) Prec@5 100.000 (99.143) +2022-11-14 14:11:29,032 Test: [28/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0649 (0.0839) Prec@1 91.000 (86.276) Prec@5 99.000 (99.138) +2022-11-14 14:11:29,042 Test: [29/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0669 (0.0833) Prec@1 87.000 (86.300) Prec@5 100.000 (99.167) +2022-11-14 14:11:29,053 Test: [30/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0760 (0.0831) Prec@1 87.000 (86.323) Prec@5 100.000 (99.194) +2022-11-14 14:11:29,064 Test: [31/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0639 (0.0825) Prec@1 91.000 (86.469) Prec@5 99.000 (99.188) +2022-11-14 14:11:29,075 Test: [32/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1001 (0.0830) Prec@1 82.000 (86.333) Prec@5 97.000 (99.121) +2022-11-14 14:11:29,087 Test: [33/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0857 (0.0831) Prec@1 84.000 (86.265) Prec@5 99.000 (99.118) +2022-11-14 14:11:29,099 Test: [34/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.0830) Prec@1 89.000 (86.343) Prec@5 100.000 (99.143) +2022-11-14 14:11:29,110 Test: [35/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0651 (0.0825) Prec@1 89.000 (86.417) Prec@5 100.000 (99.167) +2022-11-14 14:11:29,125 Test: [36/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0791 (0.0824) Prec@1 84.000 (86.351) Prec@5 99.000 (99.162) +2022-11-14 14:11:29,139 Test: [37/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1066 (0.0831) Prec@1 82.000 (86.237) Prec@5 100.000 (99.184) +2022-11-14 14:11:29,155 Test: [38/100] Model Time 0.013 (0.010) Loss Time 0.001 (0.000) Loss 0.0649 (0.0826) Prec@1 88.000 (86.282) Prec@5 99.000 (99.179) +2022-11-14 14:11:29,172 Test: [39/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.0826) Prec@1 87.000 (86.300) Prec@5 100.000 (99.200) +2022-11-14 14:11:29,188 Test: [40/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0850 (0.0827) Prec@1 85.000 (86.268) Prec@5 100.000 (99.220) +2022-11-14 14:11:29,205 Test: [41/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0818 (0.0827) Prec@1 87.000 (86.286) Prec@5 98.000 (99.190) +2022-11-14 14:11:29,221 Test: [42/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0631 (0.0822) Prec@1 92.000 (86.419) Prec@5 100.000 (99.209) +2022-11-14 14:11:29,233 Test: [43/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0714 (0.0820) Prec@1 86.000 (86.409) Prec@5 99.000 (99.205) +2022-11-14 14:11:29,244 Test: [44/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0819) Prec@1 87.000 (86.422) Prec@5 99.000 (99.200) +2022-11-14 14:11:29,259 Test: [45/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1027 (0.0823) Prec@1 82.000 (86.326) Prec@5 99.000 (99.196) +2022-11-14 14:11:29,275 Test: [46/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0831 (0.0824) Prec@1 83.000 (86.255) Prec@5 99.000 (99.191) +2022-11-14 14:11:29,291 Test: [47/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0792 (0.0823) Prec@1 88.000 (86.292) Prec@5 99.000 (99.188) +2022-11-14 14:11:29,308 Test: [48/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0859 (0.0824) Prec@1 86.000 (86.286) Prec@5 100.000 (99.204) +2022-11-14 14:11:29,324 Test: [49/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1402 (0.0835) Prec@1 80.000 (86.160) Prec@5 100.000 (99.220) +2022-11-14 14:11:29,340 Test: [50/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0679 (0.0832) Prec@1 88.000 (86.196) Prec@5 100.000 (99.235) +2022-11-14 14:11:29,356 Test: [51/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0929 (0.0834) Prec@1 82.000 (86.115) Prec@5 99.000 (99.231) +2022-11-14 14:11:29,374 Test: [52/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0872 (0.0835) Prec@1 83.000 (86.057) Prec@5 100.000 (99.245) +2022-11-14 14:11:29,385 Test: [53/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0755 (0.0833) Prec@1 87.000 (86.074) Prec@5 96.000 (99.185) +2022-11-14 14:11:29,395 Test: [54/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0876 (0.0834) Prec@1 87.000 (86.091) Prec@5 99.000 (99.182) +2022-11-14 14:11:29,405 Test: [55/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0823 (0.0834) Prec@1 87.000 (86.107) Prec@5 99.000 (99.179) +2022-11-14 14:11:29,415 Test: [56/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0748 (0.0832) Prec@1 86.000 (86.105) Prec@5 100.000 (99.193) +2022-11-14 14:11:29,425 Test: [57/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0747 (0.0831) Prec@1 89.000 (86.155) Prec@5 100.000 (99.207) +2022-11-14 14:11:29,435 Test: [58/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0857 (0.0831) Prec@1 87.000 (86.169) Prec@5 100.000 (99.220) +2022-11-14 14:11:29,445 Test: [59/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1180 (0.0837) Prec@1 78.000 (86.033) Prec@5 99.000 (99.217) +2022-11-14 14:11:29,455 Test: [60/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0981 (0.0840) Prec@1 83.000 (85.984) Prec@5 100.000 (99.230) +2022-11-14 14:11:29,465 Test: [61/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0876 (0.0840) Prec@1 84.000 (85.952) Prec@5 99.000 (99.226) +2022-11-14 14:11:29,475 Test: [62/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0576 (0.0836) Prec@1 92.000 (86.048) Prec@5 100.000 (99.238) +2022-11-14 14:11:29,487 Test: [63/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0476 (0.0830) Prec@1 91.000 (86.125) Prec@5 100.000 (99.250) +2022-11-14 14:11:29,496 Test: [64/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1060 (0.0834) Prec@1 80.000 (86.031) Prec@5 100.000 (99.262) +2022-11-14 14:11:29,506 Test: [65/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0668 (0.0831) Prec@1 88.000 (86.061) Prec@5 98.000 (99.242) +2022-11-14 14:11:29,515 Test: [66/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0398 (0.0825) Prec@1 93.000 (86.164) Prec@5 100.000 (99.254) +2022-11-14 14:11:29,526 Test: [67/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0930 (0.0826) Prec@1 86.000 (86.162) Prec@5 99.000 (99.250) +2022-11-14 14:11:29,537 Test: [68/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0609 (0.0823) Prec@1 88.000 (86.188) Prec@5 99.000 (99.246) +2022-11-14 14:11:29,548 Test: [69/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0607 (0.0820) Prec@1 89.000 (86.229) Prec@5 99.000 (99.243) +2022-11-14 14:11:29,558 Test: [70/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1152 (0.0825) Prec@1 85.000 (86.211) Prec@5 100.000 (99.254) +2022-11-14 14:11:29,569 Test: [71/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0789 (0.0824) Prec@1 89.000 (86.250) Prec@5 99.000 (99.250) +2022-11-14 14:11:29,580 Test: [72/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0516 (0.0820) Prec@1 93.000 (86.342) Prec@5 99.000 (99.247) +2022-11-14 14:11:29,590 Test: [73/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0678 (0.0818) Prec@1 89.000 (86.378) Prec@5 100.000 (99.257) +2022-11-14 14:11:29,602 Test: [74/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1042 (0.0821) Prec@1 83.000 (86.333) Prec@5 99.000 (99.253) +2022-11-14 14:11:29,613 Test: [75/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0822 (0.0821) Prec@1 85.000 (86.316) Prec@5 98.000 (99.237) +2022-11-14 14:11:29,628 Test: [76/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0821 (0.0821) Prec@1 85.000 (86.299) Prec@5 99.000 (99.234) +2022-11-14 14:11:29,645 Test: [77/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0899 (0.0822) Prec@1 85.000 (86.282) Prec@5 98.000 (99.218) +2022-11-14 14:11:29,663 Test: [78/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0806 (0.0822) Prec@1 87.000 (86.291) Prec@5 100.000 (99.228) +2022-11-14 14:11:29,688 Test: [79/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0895 (0.0823) Prec@1 82.000 (86.237) Prec@5 98.000 (99.213) +2022-11-14 14:11:29,714 Test: [80/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0781 (0.0822) Prec@1 85.000 (86.222) Prec@5 99.000 (99.210) +2022-11-14 14:11:29,741 Test: [81/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0843 (0.0823) Prec@1 87.000 (86.232) Prec@5 100.000 (99.220) +2022-11-14 14:11:29,765 Test: [82/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0876 (0.0823) Prec@1 84.000 (86.205) Prec@5 99.000 (99.217) +2022-11-14 14:11:29,784 Test: [83/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0735 (0.0822) Prec@1 87.000 (86.214) Prec@5 100.000 (99.226) +2022-11-14 14:11:29,802 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1042 (0.0825) Prec@1 80.000 (86.141) Prec@5 100.000 (99.235) +2022-11-14 14:11:29,821 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.0827) Prec@1 85.000 (86.128) Prec@5 100.000 (99.244) +2022-11-14 14:11:29,842 Test: [86/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0827) Prec@1 88.000 (86.149) Prec@5 99.000 (99.241) +2022-11-14 14:11:29,862 Test: [87/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.0826) Prec@1 86.000 (86.148) Prec@5 100.000 (99.250) +2022-11-14 14:11:29,885 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0828) Prec@1 84.000 (86.124) Prec@5 100.000 (99.258) +2022-11-14 14:11:29,905 Test: [89/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0828) Prec@1 87.000 (86.133) Prec@5 98.000 (99.244) +2022-11-14 14:11:29,922 Test: [90/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0828) Prec@1 86.000 (86.132) Prec@5 100.000 (99.253) +2022-11-14 14:11:29,940 Test: [91/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0538 (0.0824) Prec@1 91.000 (86.185) Prec@5 99.000 (99.250) +2022-11-14 14:11:29,961 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0825) Prec@1 89.000 (86.215) Prec@5 99.000 (99.247) +2022-11-14 14:11:29,980 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0824) Prec@1 89.000 (86.245) Prec@5 99.000 (99.245) +2022-11-14 14:11:30,001 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0824) Prec@1 84.000 (86.221) Prec@5 98.000 (99.232) +2022-11-14 14:11:30,019 Test: [95/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0793 (0.0823) Prec@1 85.000 (86.208) Prec@5 100.000 (99.240) +2022-11-14 14:11:30,039 Test: [96/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0422 (0.0819) Prec@1 91.000 (86.258) Prec@5 99.000 (99.237) +2022-11-14 14:11:30,059 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1179 (0.0823) Prec@1 84.000 (86.235) Prec@5 97.000 (99.214) +2022-11-14 14:11:30,080 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0965 (0.0824) Prec@1 83.000 (86.202) Prec@5 100.000 (99.222) +2022-11-14 14:11:30,100 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0824) Prec@1 86.000 (86.200) Prec@5 98.000 (99.210) +2022-11-14 14:11:30,160 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:11:30,501 Epoch: [161][0/500] Time 0.029 (0.029) Data 0.257 (0.257) Loss 0.0415 (0.0415) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:11:30,818 Epoch: [161][10/500] Time 0.022 (0.029) Data 0.002 (0.025) Loss 0.0547 (0.0481) Prec@1 91.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:11:31,151 Epoch: [161][20/500] Time 0.029 (0.028) Data 0.002 (0.014) Loss 0.0532 (0.0498) Prec@1 93.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:11:31,510 Epoch: [161][30/500] Time 0.043 (0.029) Data 0.003 (0.010) Loss 0.0679 (0.0543) Prec@1 88.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:11:31,885 Epoch: [161][40/500] Time 0.028 (0.030) Data 0.002 (0.008) Loss 0.0324 (0.0499) Prec@1 95.000 (91.800) Prec@5 100.000 (99.600) +2022-11-14 14:11:32,356 Epoch: [161][50/500] Time 0.043 (0.033) Data 0.002 (0.007) Loss 0.0325 (0.0470) Prec@1 97.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:11:32,828 Epoch: [161][60/500] Time 0.052 (0.034) Data 0.002 (0.006) Loss 0.0472 (0.0470) Prec@1 91.000 (92.429) Prec@5 100.000 (99.714) +2022-11-14 14:11:33,452 Epoch: [161][70/500] Time 0.089 (0.037) Data 0.002 (0.006) Loss 0.0676 (0.0496) Prec@1 89.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:11:34,100 Epoch: [161][80/500] Time 0.043 (0.040) Data 0.002 (0.005) Loss 0.0325 (0.0477) Prec@1 94.000 (92.222) Prec@5 100.000 (99.778) +2022-11-14 14:11:34,651 Epoch: [161][90/500] Time 0.044 (0.041) Data 0.002 (0.005) Loss 0.0360 (0.0465) Prec@1 94.000 (92.400) Prec@5 100.000 (99.800) +2022-11-14 14:11:35,219 Epoch: [161][100/500] Time 0.043 (0.042) Data 0.002 (0.004) Loss 0.0448 (0.0464) Prec@1 92.000 (92.364) Prec@5 99.000 (99.727) +2022-11-14 14:11:35,768 Epoch: [161][110/500] Time 0.044 (0.043) Data 0.002 (0.004) Loss 0.0305 (0.0451) Prec@1 96.000 (92.667) Prec@5 100.000 (99.750) +2022-11-14 14:11:36,330 Epoch: [161][120/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.0444 (0.0450) Prec@1 92.000 (92.615) Prec@5 100.000 (99.769) +2022-11-14 14:11:36,888 Epoch: [161][130/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0302 (0.0439) Prec@1 92.000 (92.571) Prec@5 100.000 (99.786) +2022-11-14 14:11:37,477 Epoch: [161][140/500] Time 0.047 (0.045) Data 0.002 (0.004) Loss 0.0343 (0.0433) Prec@1 94.000 (92.667) Prec@5 100.000 (99.800) +2022-11-14 14:11:38,033 Epoch: [161][150/500] Time 0.048 (0.045) Data 0.002 (0.004) Loss 0.0408 (0.0431) Prec@1 94.000 (92.750) Prec@5 100.000 (99.812) +2022-11-14 14:11:38,623 Epoch: [161][160/500] Time 0.068 (0.046) Data 0.002 (0.004) Loss 0.0415 (0.0430) Prec@1 95.000 (92.882) Prec@5 100.000 (99.824) +2022-11-14 14:11:39,292 Epoch: [161][170/500] Time 0.079 (0.046) Data 0.002 (0.003) Loss 0.0404 (0.0429) Prec@1 93.000 (92.889) Prec@5 100.000 (99.833) +2022-11-14 14:11:39,830 Epoch: [161][180/500] Time 0.061 (0.046) Data 0.002 (0.003) Loss 0.0658 (0.0441) Prec@1 90.000 (92.737) Prec@5 100.000 (99.842) +2022-11-14 14:11:40,590 Epoch: [161][190/500] Time 0.085 (0.047) Data 0.002 (0.003) Loss 0.0538 (0.0446) Prec@1 91.000 (92.650) Prec@5 100.000 (99.850) +2022-11-14 14:11:41,209 Epoch: [161][200/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0527 (0.0450) Prec@1 91.000 (92.571) Prec@5 99.000 (99.810) +2022-11-14 14:11:41,807 Epoch: [161][210/500] Time 0.102 (0.048) Data 0.002 (0.003) Loss 0.0590 (0.0456) Prec@1 92.000 (92.545) Prec@5 98.000 (99.727) +2022-11-14 14:11:42,310 Epoch: [161][220/500] Time 0.041 (0.048) Data 0.003 (0.003) Loss 0.0283 (0.0449) Prec@1 97.000 (92.739) Prec@5 99.000 (99.696) +2022-11-14 14:11:42,871 Epoch: [161][230/500] Time 0.044 (0.048) Data 0.003 (0.003) Loss 0.0540 (0.0452) Prec@1 90.000 (92.625) Prec@5 100.000 (99.708) +2022-11-14 14:11:43,521 Epoch: [161][240/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0660 (0.0461) Prec@1 87.000 (92.400) Prec@5 100.000 (99.720) +2022-11-14 14:11:44,014 Epoch: [161][250/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0563 (0.0465) Prec@1 89.000 (92.269) Prec@5 99.000 (99.692) +2022-11-14 14:11:44,503 Epoch: [161][260/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0480 (0.0465) Prec@1 89.000 (92.148) Prec@5 99.000 (99.667) +2022-11-14 14:11:45,105 Epoch: [161][270/500] Time 0.042 (0.048) Data 0.002 (0.003) Loss 0.0643 (0.0472) Prec@1 88.000 (92.000) Prec@5 100.000 (99.679) +2022-11-14 14:11:45,596 Epoch: [161][280/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0573 (0.0475) Prec@1 90.000 (91.931) Prec@5 99.000 (99.655) +2022-11-14 14:11:46,264 Epoch: [161][290/500] Time 0.042 (0.048) Data 0.002 (0.003) Loss 0.0437 (0.0474) Prec@1 92.000 (91.933) Prec@5 100.000 (99.667) +2022-11-14 14:11:46,825 Epoch: [161][300/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0669 (0.0480) Prec@1 88.000 (91.806) Prec@5 100.000 (99.677) +2022-11-14 14:11:47,392 Epoch: [161][310/500] Time 0.069 (0.048) Data 0.002 (0.003) Loss 0.0305 (0.0475) Prec@1 95.000 (91.906) Prec@5 100.000 (99.688) +2022-11-14 14:11:47,932 Epoch: [161][320/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0454 (0.0474) Prec@1 93.000 (91.939) Prec@5 99.000 (99.667) +2022-11-14 14:11:48,470 Epoch: [161][330/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0526 (0.0475) Prec@1 88.000 (91.824) Prec@5 100.000 (99.676) +2022-11-14 14:11:49,039 Epoch: [161][340/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0486 (0.0476) Prec@1 93.000 (91.857) Prec@5 100.000 (99.686) +2022-11-14 14:11:49,674 Epoch: [161][350/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0484 (0.0476) Prec@1 91.000 (91.833) Prec@5 98.000 (99.639) +2022-11-14 14:11:50,180 Epoch: [161][360/500] Time 0.040 (0.049) Data 0.002 (0.003) Loss 0.0315 (0.0472) Prec@1 96.000 (91.946) Prec@5 100.000 (99.649) +2022-11-14 14:11:50,660 Epoch: [161][370/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0350 (0.0468) Prec@1 94.000 (92.000) Prec@5 100.000 (99.658) +2022-11-14 14:11:51,212 Epoch: [161][380/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0526 (0.0470) Prec@1 90.000 (91.949) Prec@5 99.000 (99.641) +2022-11-14 14:11:51,755 Epoch: [161][390/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0417 (0.0469) Prec@1 94.000 (92.000) Prec@5 99.000 (99.625) +2022-11-14 14:11:52,332 Epoch: [161][400/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0414 (0.0467) Prec@1 92.000 (92.000) Prec@5 100.000 (99.634) +2022-11-14 14:11:53,017 Epoch: [161][410/500] Time 0.043 (0.049) Data 0.001 (0.003) Loss 0.0711 (0.0473) Prec@1 87.000 (91.881) Prec@5 99.000 (99.619) +2022-11-14 14:11:53,493 Epoch: [161][420/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0369 (0.0471) Prec@1 94.000 (91.930) Prec@5 100.000 (99.628) +2022-11-14 14:11:53,974 Epoch: [161][430/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0506 (0.0471) Prec@1 92.000 (91.932) Prec@5 99.000 (99.614) +2022-11-14 14:11:54,463 Epoch: [161][440/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0297 (0.0468) Prec@1 96.000 (92.022) Prec@5 100.000 (99.622) +2022-11-14 14:11:55,020 Epoch: [161][450/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0366 (0.0465) Prec@1 94.000 (92.065) Prec@5 100.000 (99.630) +2022-11-14 14:11:55,578 Epoch: [161][460/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0497 (0.0466) Prec@1 91.000 (92.043) Prec@5 100.000 (99.638) +2022-11-14 14:11:56,233 Epoch: [161][470/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.0408 (0.0465) Prec@1 93.000 (92.062) Prec@5 99.000 (99.625) +2022-11-14 14:11:56,846 Epoch: [161][480/500] Time 0.073 (0.049) Data 0.002 (0.003) Loss 0.0906 (0.0474) Prec@1 84.000 (91.898) Prec@5 99.000 (99.612) +2022-11-14 14:11:57,497 Epoch: [161][490/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0559 (0.0476) Prec@1 93.000 (91.920) Prec@5 100.000 (99.620) +2022-11-14 14:11:57,939 Epoch: [161][499/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0739 (0.0481) Prec@1 89.000 (91.863) Prec@5 100.000 (99.627) +2022-11-14 14:11:58,230 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0534 (0.0534) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:11:58,244 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0584 (0.0559) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:11:58,255 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0716 (0.0612) Prec@1 90.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 14:11:58,270 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0647) Prec@1 87.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 14:11:58,280 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0582 (0.0634) Prec@1 92.000 (89.400) Prec@5 100.000 (99.800) +2022-11-14 14:11:58,292 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0237 (0.0568) Prec@1 95.000 (90.333) Prec@5 100.000 (99.833) +2022-11-14 14:11:58,304 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0585) Prec@1 90.000 (90.286) Prec@5 99.000 (99.714) +2022-11-14 14:11:58,317 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0634) Prec@1 81.000 (89.125) Prec@5 100.000 (99.750) +2022-11-14 14:11:58,330 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0648) Prec@1 86.000 (88.778) Prec@5 99.000 (99.667) +2022-11-14 14:11:58,342 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0655) Prec@1 88.000 (88.700) Prec@5 98.000 (99.500) +2022-11-14 14:11:58,356 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0643) Prec@1 92.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 14:11:58,366 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0650) Prec@1 90.000 (89.083) Prec@5 99.000 (99.500) +2022-11-14 14:11:58,377 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0637) Prec@1 92.000 (89.308) Prec@5 100.000 (99.538) +2022-11-14 14:11:58,387 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0647) Prec@1 90.000 (89.357) Prec@5 99.000 (99.500) +2022-11-14 14:11:58,399 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0656) Prec@1 88.000 (89.267) Prec@5 99.000 (99.467) +2022-11-14 14:11:58,409 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0666) Prec@1 86.000 (89.062) Prec@5 100.000 (99.500) +2022-11-14 14:11:58,419 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0661) Prec@1 91.000 (89.176) Prec@5 97.000 (99.353) +2022-11-14 14:11:58,428 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0680) Prec@1 87.000 (89.056) Prec@5 100.000 (99.389) +2022-11-14 14:11:58,440 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0685) Prec@1 87.000 (88.947) Prec@5 98.000 (99.316) +2022-11-14 14:11:58,452 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0698) Prec@1 86.000 (88.800) Prec@5 98.000 (99.250) +2022-11-14 14:11:58,466 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0705) Prec@1 85.000 (88.619) Prec@5 99.000 (99.238) +2022-11-14 14:11:58,478 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0710) Prec@1 84.000 (88.409) Prec@5 98.000 (99.182) +2022-11-14 14:11:58,488 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0720) Prec@1 86.000 (88.304) Prec@5 97.000 (99.087) +2022-11-14 14:11:58,499 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0719) Prec@1 87.000 (88.250) Prec@5 100.000 (99.125) +2022-11-14 14:11:58,511 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0727) Prec@1 86.000 (88.160) Prec@5 100.000 (99.160) +2022-11-14 14:11:58,522 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0730) Prec@1 86.000 (88.077) Prec@5 100.000 (99.192) +2022-11-14 14:11:58,532 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0726) Prec@1 90.000 (88.148) Prec@5 100.000 (99.222) +2022-11-14 14:11:58,543 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0730) Prec@1 89.000 (88.179) Prec@5 99.000 (99.214) +2022-11-14 14:11:58,554 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0732) Prec@1 87.000 (88.138) Prec@5 98.000 (99.172) +2022-11-14 14:11:58,568 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0733) Prec@1 88.000 (88.133) Prec@5 99.000 (99.167) +2022-11-14 14:11:58,580 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0732) Prec@1 86.000 (88.065) Prec@5 100.000 (99.194) +2022-11-14 14:11:58,593 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0728) Prec@1 88.000 (88.062) Prec@5 99.000 (99.188) +2022-11-14 14:11:58,606 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0736) Prec@1 82.000 (87.879) Prec@5 99.000 (99.182) +2022-11-14 14:11:58,620 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0738) Prec@1 86.000 (87.824) Prec@5 99.000 (99.176) +2022-11-14 14:11:58,631 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0746) Prec@1 80.000 (87.600) Prec@5 99.000 (99.171) +2022-11-14 14:11:58,644 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0745) Prec@1 89.000 (87.639) Prec@5 100.000 (99.194) +2022-11-14 14:11:58,655 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0745) Prec@1 87.000 (87.622) Prec@5 99.000 (99.189) +2022-11-14 14:11:58,669 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0750) Prec@1 83.000 (87.500) Prec@5 99.000 (99.184) +2022-11-14 14:11:58,682 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0417 (0.0742) Prec@1 94.000 (87.667) Prec@5 99.000 (99.179) +2022-11-14 14:11:58,695 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0743) Prec@1 85.000 (87.600) Prec@5 99.000 (99.175) +2022-11-14 14:11:58,707 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0746) Prec@1 85.000 (87.537) Prec@5 98.000 (99.146) +2022-11-14 14:11:58,720 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0748) Prec@1 87.000 (87.524) Prec@5 98.000 (99.119) +2022-11-14 14:11:58,733 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0743) Prec@1 91.000 (87.605) Prec@5 100.000 (99.140) +2022-11-14 14:11:58,746 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0741) Prec@1 89.000 (87.636) Prec@5 97.000 (99.091) +2022-11-14 14:11:58,759 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0738) Prec@1 89.000 (87.667) Prec@5 100.000 (99.111) +2022-11-14 14:11:58,774 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0745) Prec@1 82.000 (87.543) Prec@5 99.000 (99.109) +2022-11-14 14:11:58,786 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0744) Prec@1 89.000 (87.574) Prec@5 100.000 (99.128) +2022-11-14 14:11:58,800 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0750) Prec@1 81.000 (87.438) Prec@5 100.000 (99.146) +2022-11-14 14:11:58,814 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0749) Prec@1 86.000 (87.408) Prec@5 100.000 (99.163) +2022-11-14 14:11:58,826 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0754) Prec@1 83.000 (87.320) Prec@5 100.000 (99.180) +2022-11-14 14:11:58,838 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0753) Prec@1 89.000 (87.353) Prec@5 100.000 (99.196) +2022-11-14 14:11:58,852 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0753) Prec@1 87.000 (87.346) Prec@5 100.000 (99.212) +2022-11-14 14:11:58,868 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0750) Prec@1 90.000 (87.396) Prec@5 100.000 (99.226) +2022-11-14 14:11:58,882 Test: [53/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0749) Prec@1 88.000 (87.407) Prec@5 99.000 (99.222) +2022-11-14 14:11:58,893 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0754) Prec@1 85.000 (87.364) Prec@5 100.000 (99.236) +2022-11-14 14:11:58,905 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0754) Prec@1 87.000 (87.357) Prec@5 99.000 (99.232) +2022-11-14 14:11:58,919 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 88.000 (87.368) Prec@5 100.000 (99.246) +2022-11-14 14:11:58,932 Test: [57/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0753) Prec@1 90.000 (87.414) Prec@5 99.000 (99.241) +2022-11-14 14:11:58,946 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0757) Prec@1 85.000 (87.373) Prec@5 100.000 (99.254) +2022-11-14 14:11:58,962 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0756) Prec@1 87.000 (87.367) Prec@5 99.000 (99.250) +2022-11-14 14:11:58,979 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0759) Prec@1 88.000 (87.377) Prec@5 100.000 (99.262) +2022-11-14 14:11:58,998 Test: [61/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0755) Prec@1 90.000 (87.419) Prec@5 100.000 (99.274) +2022-11-14 14:11:59,015 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0753) Prec@1 89.000 (87.444) Prec@5 100.000 (99.286) +2022-11-14 14:11:59,031 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0496 (0.0749) Prec@1 91.000 (87.500) Prec@5 100.000 (99.297) +2022-11-14 14:11:59,048 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0751) Prec@1 87.000 (87.492) Prec@5 100.000 (99.308) +2022-11-14 14:11:59,065 Test: [65/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0752) Prec@1 85.000 (87.455) Prec@5 100.000 (99.318) +2022-11-14 14:11:59,083 Test: [66/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0371 (0.0746) Prec@1 95.000 (87.567) Prec@5 99.000 (99.313) +2022-11-14 14:11:59,096 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0744) Prec@1 89.000 (87.588) Prec@5 100.000 (99.324) +2022-11-14 14:11:59,108 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0744) Prec@1 88.000 (87.594) Prec@5 100.000 (99.333) +2022-11-14 14:11:59,122 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0743) Prec@1 90.000 (87.629) Prec@5 99.000 (99.329) +2022-11-14 14:11:59,134 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0746) Prec@1 84.000 (87.577) Prec@5 99.000 (99.324) +2022-11-14 14:11:59,145 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0743) Prec@1 90.000 (87.611) Prec@5 98.000 (99.306) +2022-11-14 14:11:59,158 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0461 (0.0740) Prec@1 93.000 (87.685) Prec@5 100.000 (99.315) +2022-11-14 14:11:59,172 Test: [73/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0737) Prec@1 91.000 (87.730) Prec@5 100.000 (99.324) +2022-11-14 14:11:59,183 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0741) Prec@1 79.000 (87.613) Prec@5 100.000 (99.333) +2022-11-14 14:11:59,196 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0738) Prec@1 91.000 (87.658) Prec@5 99.000 (99.329) +2022-11-14 14:11:59,207 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0738) Prec@1 88.000 (87.662) Prec@5 98.000 (99.312) +2022-11-14 14:11:59,221 Test: [77/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0739) Prec@1 85.000 (87.628) Prec@5 99.000 (99.308) +2022-11-14 14:11:59,233 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0741) Prec@1 84.000 (87.582) Prec@5 100.000 (99.316) +2022-11-14 14:11:59,244 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0742) Prec@1 87.000 (87.575) Prec@5 99.000 (99.312) +2022-11-14 14:11:59,255 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0744) Prec@1 83.000 (87.519) Prec@5 99.000 (99.309) +2022-11-14 14:11:59,269 Test: [81/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0746) Prec@1 85.000 (87.488) Prec@5 100.000 (99.317) +2022-11-14 14:11:59,281 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0747) Prec@1 87.000 (87.482) Prec@5 100.000 (99.325) +2022-11-14 14:11:59,293 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0744) Prec@1 90.000 (87.512) Prec@5 100.000 (99.333) +2022-11-14 14:11:59,304 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0746) Prec@1 85.000 (87.482) Prec@5 100.000 (99.341) +2022-11-14 14:11:59,317 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0748) Prec@1 84.000 (87.442) Prec@5 99.000 (99.337) +2022-11-14 14:11:59,330 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0749) Prec@1 89.000 (87.460) Prec@5 97.000 (99.310) +2022-11-14 14:11:59,342 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0750) Prec@1 86.000 (87.443) Prec@5 100.000 (99.318) +2022-11-14 14:11:59,353 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0749) Prec@1 89.000 (87.461) Prec@5 100.000 (99.326) +2022-11-14 14:11:59,366 Test: [89/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0750) Prec@1 87.000 (87.456) Prec@5 98.000 (99.311) +2022-11-14 14:11:59,378 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0748) Prec@1 88.000 (87.462) Prec@5 100.000 (99.319) +2022-11-14 14:11:59,389 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0745) Prec@1 91.000 (87.500) Prec@5 99.000 (99.315) +2022-11-14 14:11:59,398 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0746) Prec@1 88.000 (87.505) Prec@5 100.000 (99.323) +2022-11-14 14:11:59,410 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0745) Prec@1 90.000 (87.532) Prec@5 99.000 (99.319) +2022-11-14 14:11:59,421 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0746) Prec@1 84.000 (87.495) Prec@5 99.000 (99.316) +2022-11-14 14:11:59,433 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0746) Prec@1 86.000 (87.479) Prec@5 99.000 (99.312) +2022-11-14 14:11:59,445 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0435 (0.0743) Prec@1 94.000 (87.546) Prec@5 99.000 (99.309) +2022-11-14 14:11:59,460 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0745) Prec@1 85.000 (87.520) Prec@5 100.000 (99.316) +2022-11-14 14:11:59,477 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0748) Prec@1 84.000 (87.485) Prec@5 99.000 (99.313) +2022-11-14 14:11:59,493 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0747) Prec@1 89.000 (87.500) Prec@5 100.000 (99.320) +2022-11-14 14:11:59,555 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:12:00,044 Epoch: [162][0/500] Time 0.032 (0.032) Data 0.242 (0.242) Loss 0.0570 (0.0570) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:12:00,292 Epoch: [162][10/500] Time 0.019 (0.023) Data 0.002 (0.024) Loss 0.0309 (0.0439) Prec@1 94.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:12:00,597 Epoch: [162][20/500] Time 0.031 (0.025) Data 0.002 (0.014) Loss 0.0380 (0.0419) Prec@1 93.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:12:00,855 Epoch: [162][30/500] Time 0.021 (0.024) Data 0.002 (0.010) Loss 0.0590 (0.0462) Prec@1 91.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:12:01,144 Epoch: [162][40/500] Time 0.022 (0.025) Data 0.002 (0.008) Loss 0.0355 (0.0441) Prec@1 93.000 (92.200) Prec@5 100.000 (99.800) +2022-11-14 14:12:01,510 Epoch: [162][50/500] Time 0.035 (0.026) Data 0.002 (0.007) Loss 0.0682 (0.0481) Prec@1 91.000 (92.000) Prec@5 100.000 (99.833) +2022-11-14 14:12:01,867 Epoch: [162][60/500] Time 0.029 (0.027) Data 0.002 (0.006) Loss 0.0545 (0.0490) Prec@1 92.000 (92.000) Prec@5 99.000 (99.714) +2022-11-14 14:12:02,248 Epoch: [162][70/500] Time 0.027 (0.028) Data 0.003 (0.005) Loss 0.0340 (0.0471) Prec@1 93.000 (92.125) Prec@5 100.000 (99.750) +2022-11-14 14:12:02,633 Epoch: [162][80/500] Time 0.035 (0.029) Data 0.002 (0.005) Loss 0.0401 (0.0464) Prec@1 94.000 (92.333) Prec@5 100.000 (99.778) +2022-11-14 14:12:03,050 Epoch: [162][90/500] Time 0.042 (0.030) Data 0.002 (0.005) Loss 0.0348 (0.0452) Prec@1 94.000 (92.500) Prec@5 99.000 (99.700) +2022-11-14 14:12:03,405 Epoch: [162][100/500] Time 0.028 (0.030) Data 0.002 (0.004) Loss 0.0269 (0.0435) Prec@1 96.000 (92.818) Prec@5 100.000 (99.727) +2022-11-14 14:12:03,813 Epoch: [162][110/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0641 (0.0453) Prec@1 90.000 (92.583) Prec@5 100.000 (99.750) +2022-11-14 14:12:04,158 Epoch: [162][120/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0587 (0.0463) Prec@1 89.000 (92.308) Prec@5 99.000 (99.692) +2022-11-14 14:12:04,543 Epoch: [162][130/500] Time 0.031 (0.031) Data 0.002 (0.004) Loss 0.0319 (0.0453) Prec@1 93.000 (92.357) Prec@5 100.000 (99.714) +2022-11-14 14:12:04,950 Epoch: [162][140/500] Time 0.027 (0.031) Data 0.002 (0.004) Loss 0.0513 (0.0457) Prec@1 94.000 (92.467) Prec@5 100.000 (99.733) +2022-11-14 14:12:05,378 Epoch: [162][150/500] Time 0.024 (0.032) Data 0.002 (0.004) Loss 0.0574 (0.0464) Prec@1 90.000 (92.312) Prec@5 100.000 (99.750) +2022-11-14 14:12:05,745 Epoch: [162][160/500] Time 0.043 (0.032) Data 0.002 (0.004) Loss 0.0540 (0.0468) Prec@1 90.000 (92.176) Prec@5 100.000 (99.765) +2022-11-14 14:12:06,101 Epoch: [162][170/500] Time 0.028 (0.032) Data 0.002 (0.003) Loss 0.0462 (0.0468) Prec@1 91.000 (92.111) Prec@5 100.000 (99.778) +2022-11-14 14:12:06,458 Epoch: [162][180/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0575 (0.0474) Prec@1 90.000 (92.000) Prec@5 100.000 (99.789) +2022-11-14 14:12:06,847 Epoch: [162][190/500] Time 0.061 (0.032) Data 0.002 (0.003) Loss 0.0553 (0.0478) Prec@1 91.000 (91.950) Prec@5 100.000 (99.800) +2022-11-14 14:12:07,195 Epoch: [162][200/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0394 (0.0474) Prec@1 93.000 (92.000) Prec@5 99.000 (99.762) +2022-11-14 14:12:07,578 Epoch: [162][210/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0261 (0.0464) Prec@1 96.000 (92.182) Prec@5 100.000 (99.773) +2022-11-14 14:12:08,031 Epoch: [162][220/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.0606 (0.0470) Prec@1 89.000 (92.043) Prec@5 100.000 (99.783) +2022-11-14 14:12:08,476 Epoch: [162][230/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0394 (0.0467) Prec@1 96.000 (92.208) Prec@5 100.000 (99.792) +2022-11-14 14:12:08,984 Epoch: [162][240/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0543 (0.0470) Prec@1 88.000 (92.040) Prec@5 100.000 (99.800) +2022-11-14 14:12:09,503 Epoch: [162][250/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0335 (0.0465) Prec@1 96.000 (92.192) Prec@5 100.000 (99.808) +2022-11-14 14:12:09,986 Epoch: [162][260/500] Time 0.051 (0.034) Data 0.002 (0.003) Loss 0.0516 (0.0467) Prec@1 90.000 (92.111) Prec@5 100.000 (99.815) +2022-11-14 14:12:10,461 Epoch: [162][270/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0773 (0.0478) Prec@1 88.000 (91.964) Prec@5 100.000 (99.821) +2022-11-14 14:12:10,942 Epoch: [162][280/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0681 (0.0485) Prec@1 89.000 (91.862) Prec@5 99.000 (99.793) +2022-11-14 14:12:11,418 Epoch: [162][290/500] Time 0.051 (0.035) Data 0.002 (0.003) Loss 0.0383 (0.0481) Prec@1 94.000 (91.933) Prec@5 100.000 (99.800) +2022-11-14 14:12:11,909 Epoch: [162][300/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0549 (0.0484) Prec@1 91.000 (91.903) Prec@5 100.000 (99.806) +2022-11-14 14:12:12,385 Epoch: [162][310/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0572 (0.0486) Prec@1 90.000 (91.844) Prec@5 98.000 (99.750) +2022-11-14 14:12:12,868 Epoch: [162][320/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0473 (0.0486) Prec@1 92.000 (91.848) Prec@5 99.000 (99.727) +2022-11-14 14:12:13,340 Epoch: [162][330/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0246 (0.0479) Prec@1 97.000 (92.000) Prec@5 100.000 (99.735) +2022-11-14 14:12:13,807 Epoch: [162][340/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0506 (0.0480) Prec@1 92.000 (92.000) Prec@5 98.000 (99.686) +2022-11-14 14:12:14,276 Epoch: [162][350/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0513 (0.0481) Prec@1 92.000 (92.000) Prec@5 99.000 (99.667) +2022-11-14 14:12:14,776 Epoch: [162][360/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0582 (0.0483) Prec@1 91.000 (91.973) Prec@5 100.000 (99.676) +2022-11-14 14:12:15,265 Epoch: [162][370/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0556 (0.0485) Prec@1 91.000 (91.947) Prec@5 100.000 (99.684) +2022-11-14 14:12:15,766 Epoch: [162][380/500] Time 0.038 (0.037) Data 0.001 (0.003) Loss 0.0668 (0.0490) Prec@1 87.000 (91.821) Prec@5 99.000 (99.667) +2022-11-14 14:12:16,242 Epoch: [162][390/500] Time 0.054 (0.037) Data 0.001 (0.003) Loss 0.0312 (0.0485) Prec@1 95.000 (91.900) Prec@5 100.000 (99.675) +2022-11-14 14:12:16,708 Epoch: [162][400/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0366 (0.0483) Prec@1 95.000 (91.976) Prec@5 100.000 (99.683) +2022-11-14 14:12:17,171 Epoch: [162][410/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0390 (0.0480) Prec@1 94.000 (92.024) Prec@5 100.000 (99.690) +2022-11-14 14:12:17,655 Epoch: [162][420/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.0590 (0.0483) Prec@1 90.000 (91.977) Prec@5 99.000 (99.674) +2022-11-14 14:12:18,141 Epoch: [162][430/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0390 (0.0481) Prec@1 94.000 (92.023) Prec@5 100.000 (99.682) +2022-11-14 14:12:18,615 Epoch: [162][440/500] Time 0.057 (0.038) Data 0.002 (0.002) Loss 0.0559 (0.0482) Prec@1 90.000 (91.978) Prec@5 98.000 (99.644) +2022-11-14 14:12:19,083 Epoch: [162][450/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0420 (0.0481) Prec@1 92.000 (91.978) Prec@5 100.000 (99.652) +2022-11-14 14:12:19,550 Epoch: [162][460/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0591 (0.0483) Prec@1 90.000 (91.936) Prec@5 100.000 (99.660) +2022-11-14 14:12:20,008 Epoch: [162][470/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0551 (0.0485) Prec@1 91.000 (91.917) Prec@5 99.000 (99.646) +2022-11-14 14:12:20,531 Epoch: [162][480/500] Time 0.088 (0.038) Data 0.002 (0.002) Loss 0.0483 (0.0485) Prec@1 94.000 (91.959) Prec@5 99.000 (99.633) +2022-11-14 14:12:21,032 Epoch: [162][490/500] Time 0.089 (0.038) Data 0.002 (0.002) Loss 0.0391 (0.0483) Prec@1 94.000 (92.000) Prec@5 100.000 (99.640) +2022-11-14 14:12:21,425 Epoch: [162][499/500] Time 0.036 (0.038) Data 0.002 (0.002) Loss 0.0483 (0.0483) Prec@1 92.000 (92.000) Prec@5 99.000 (99.627) +2022-11-14 14:12:21,720 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0640 (0.0640) Prec@1 88.000 (88.000) Prec@5 98.000 (98.000) +2022-11-14 14:12:21,728 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0633) Prec@1 90.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 14:12:21,737 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0709) Prec@1 84.000 (87.333) Prec@5 100.000 (99.333) +2022-11-14 14:12:21,749 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0702) Prec@1 88.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 14:12:21,757 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0724) Prec@1 85.000 (87.000) Prec@5 100.000 (99.600) +2022-11-14 14:12:21,765 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0686) Prec@1 89.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:12:21,774 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0683) Prec@1 88.000 (87.429) Prec@5 100.000 (99.714) +2022-11-14 14:12:21,784 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0697) Prec@1 88.000 (87.500) Prec@5 99.000 (99.625) +2022-11-14 14:12:21,792 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0716) Prec@1 85.000 (87.222) Prec@5 99.000 (99.556) +2022-11-14 14:12:21,799 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0708) Prec@1 91.000 (87.600) Prec@5 99.000 (99.500) +2022-11-14 14:12:21,809 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0703) Prec@1 89.000 (87.727) Prec@5 100.000 (99.545) +2022-11-14 14:12:21,818 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0712) Prec@1 87.000 (87.667) Prec@5 100.000 (99.583) +2022-11-14 14:12:21,827 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0707) Prec@1 90.000 (87.846) Prec@5 100.000 (99.615) +2022-11-14 14:12:21,837 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0720) Prec@1 85.000 (87.643) Prec@5 100.000 (99.643) +2022-11-14 14:12:21,846 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0727) Prec@1 86.000 (87.533) Prec@5 100.000 (99.667) +2022-11-14 14:12:21,855 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0727) Prec@1 89.000 (87.625) Prec@5 99.000 (99.625) +2022-11-14 14:12:21,864 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0718) Prec@1 93.000 (87.941) Prec@5 99.000 (99.588) +2022-11-14 14:12:21,874 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0738) Prec@1 83.000 (87.667) Prec@5 100.000 (99.611) +2022-11-14 14:12:21,884 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0732) Prec@1 89.000 (87.737) Prec@5 99.000 (99.579) +2022-11-14 14:12:21,893 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0749) Prec@1 82.000 (87.450) Prec@5 99.000 (99.550) +2022-11-14 14:12:21,903 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0750) Prec@1 85.000 (87.333) Prec@5 100.000 (99.571) +2022-11-14 14:12:21,912 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0754) Prec@1 84.000 (87.182) Prec@5 98.000 (99.500) +2022-11-14 14:12:21,922 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0766) Prec@1 83.000 (87.000) Prec@5 99.000 (99.478) +2022-11-14 14:12:21,936 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0759) Prec@1 90.000 (87.125) Prec@5 100.000 (99.500) +2022-11-14 14:12:21,949 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0769) Prec@1 83.000 (86.960) Prec@5 100.000 (99.520) +2022-11-14 14:12:21,962 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0779) Prec@1 84.000 (86.846) Prec@5 97.000 (99.423) +2022-11-14 14:12:21,976 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0768) Prec@1 93.000 (87.074) Prec@5 100.000 (99.444) +2022-11-14 14:12:21,989 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0766) Prec@1 89.000 (87.143) Prec@5 100.000 (99.464) +2022-11-14 14:12:22,003 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0763) Prec@1 88.000 (87.172) Prec@5 99.000 (99.448) +2022-11-14 14:12:22,016 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0758) Prec@1 90.000 (87.267) Prec@5 99.000 (99.433) +2022-11-14 14:12:22,029 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0757) Prec@1 89.000 (87.323) Prec@5 99.000 (99.419) +2022-11-14 14:12:22,043 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0756) Prec@1 86.000 (87.281) Prec@5 100.000 (99.438) +2022-11-14 14:12:22,056 Test: [32/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0759) Prec@1 87.000 (87.273) Prec@5 98.000 (99.394) +2022-11-14 14:12:22,067 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0766) Prec@1 81.000 (87.088) Prec@5 99.000 (99.382) +2022-11-14 14:12:22,079 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0768) Prec@1 85.000 (87.029) Prec@5 99.000 (99.371) +2022-11-14 14:12:22,091 Test: [35/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0768) Prec@1 87.000 (87.028) Prec@5 100.000 (99.389) +2022-11-14 14:12:22,102 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0769) Prec@1 88.000 (87.054) Prec@5 99.000 (99.378) +2022-11-14 14:12:22,111 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0769) Prec@1 84.000 (86.974) Prec@5 100.000 (99.395) +2022-11-14 14:12:22,121 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0759) Prec@1 96.000 (87.205) Prec@5 99.000 (99.385) +2022-11-14 14:12:22,133 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0759) Prec@1 87.000 (87.200) Prec@5 100.000 (99.400) +2022-11-14 14:12:22,144 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 86.000 (87.171) Prec@5 99.000 (99.390) +2022-11-14 14:12:22,152 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0758) Prec@1 87.000 (87.167) Prec@5 100.000 (99.405) +2022-11-14 14:12:22,162 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0756) Prec@1 88.000 (87.186) Prec@5 100.000 (99.419) +2022-11-14 14:12:22,174 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0753) Prec@1 90.000 (87.250) Prec@5 98.000 (99.386) +2022-11-14 14:12:22,185 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0748) Prec@1 95.000 (87.422) Prec@5 99.000 (99.378) +2022-11-14 14:12:22,194 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0755) Prec@1 82.000 (87.304) Prec@5 100.000 (99.391) +2022-11-14 14:12:22,203 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0753) Prec@1 87.000 (87.298) Prec@5 100.000 (99.404) +2022-11-14 14:12:22,215 Test: [47/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0756) Prec@1 86.000 (87.271) Prec@5 99.000 (99.396) +2022-11-14 14:12:22,226 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0752) Prec@1 89.000 (87.306) Prec@5 99.000 (99.388) +2022-11-14 14:12:22,236 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.0762) Prec@1 81.000 (87.180) Prec@5 99.000 (99.380) +2022-11-14 14:12:22,245 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0760) Prec@1 89.000 (87.216) Prec@5 100.000 (99.392) +2022-11-14 14:12:22,257 Test: [51/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0763) Prec@1 85.000 (87.173) Prec@5 100.000 (99.404) +2022-11-14 14:12:22,267 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0760) Prec@1 90.000 (87.226) Prec@5 99.000 (99.396) +2022-11-14 14:12:22,276 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0760) Prec@1 87.000 (87.222) Prec@5 98.000 (99.370) +2022-11-14 14:12:22,285 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0765) Prec@1 82.000 (87.127) Prec@5 99.000 (99.364) +2022-11-14 14:12:22,296 Test: [55/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0766) Prec@1 86.000 (87.107) Prec@5 99.000 (99.357) +2022-11-14 14:12:22,306 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0766) Prec@1 87.000 (87.105) Prec@5 100.000 (99.368) +2022-11-14 14:12:22,316 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0763) Prec@1 92.000 (87.190) Prec@5 98.000 (99.345) +2022-11-14 14:12:22,324 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0765) Prec@1 84.000 (87.136) Prec@5 100.000 (99.356) +2022-11-14 14:12:22,333 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0766) Prec@1 86.000 (87.117) Prec@5 100.000 (99.367) +2022-11-14 14:12:22,343 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0769) Prec@1 84.000 (87.066) Prec@5 99.000 (99.361) +2022-11-14 14:12:22,352 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0770) Prec@1 85.000 (87.032) Prec@5 98.000 (99.339) +2022-11-14 14:12:22,362 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0767) Prec@1 91.000 (87.095) Prec@5 100.000 (99.349) +2022-11-14 14:12:22,372 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0763) Prec@1 90.000 (87.141) Prec@5 99.000 (99.344) +2022-11-14 14:12:22,382 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0769) Prec@1 82.000 (87.062) Prec@5 99.000 (99.338) +2022-11-14 14:12:22,392 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0770) Prec@1 87.000 (87.061) Prec@5 98.000 (99.318) +2022-11-14 14:12:22,401 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0765) Prec@1 92.000 (87.134) Prec@5 100.000 (99.328) +2022-11-14 14:12:22,410 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0764) Prec@1 90.000 (87.176) Prec@5 100.000 (99.338) +2022-11-14 14:12:22,420 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0764) Prec@1 85.000 (87.145) Prec@5 100.000 (99.348) +2022-11-14 14:12:22,430 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0765) Prec@1 87.000 (87.143) Prec@5 99.000 (99.343) +2022-11-14 14:12:22,440 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0764) Prec@1 88.000 (87.155) Prec@5 98.000 (99.324) +2022-11-14 14:12:22,449 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0764) Prec@1 87.000 (87.153) Prec@5 99.000 (99.319) +2022-11-14 14:12:22,459 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0762) Prec@1 89.000 (87.178) Prec@5 100.000 (99.329) +2022-11-14 14:12:22,472 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0759) Prec@1 90.000 (87.216) Prec@5 99.000 (99.324) +2022-11-14 14:12:22,485 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0762) Prec@1 84.000 (87.173) Prec@5 100.000 (99.333) +2022-11-14 14:12:22,498 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0760) Prec@1 90.000 (87.211) Prec@5 99.000 (99.329) +2022-11-14 14:12:22,510 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0757) Prec@1 91.000 (87.260) Prec@5 99.000 (99.325) +2022-11-14 14:12:22,522 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0759) Prec@1 85.000 (87.231) Prec@5 98.000 (99.308) +2022-11-14 14:12:22,538 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0763) Prec@1 83.000 (87.177) Prec@5 100.000 (99.316) +2022-11-14 14:12:22,552 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0762) Prec@1 87.000 (87.175) Prec@5 100.000 (99.325) +2022-11-14 14:12:22,575 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0761) Prec@1 87.000 (87.173) Prec@5 99.000 (99.321) +2022-11-14 14:12:22,600 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0762) Prec@1 86.000 (87.159) Prec@5 99.000 (99.317) +2022-11-14 14:12:22,626 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0764) Prec@1 84.000 (87.120) Prec@5 100.000 (99.325) +2022-11-14 14:12:22,651 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0764) Prec@1 85.000 (87.095) Prec@5 99.000 (99.321) +2022-11-14 14:12:22,675 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0765) Prec@1 87.000 (87.094) Prec@5 100.000 (99.329) +2022-11-14 14:12:22,697 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0769) Prec@1 80.000 (87.012) Prec@5 99.000 (99.326) +2022-11-14 14:12:22,716 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0769) Prec@1 89.000 (87.034) Prec@5 99.000 (99.322) +2022-11-14 14:12:22,731 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0770) Prec@1 85.000 (87.011) Prec@5 98.000 (99.307) +2022-11-14 14:12:22,746 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0770) Prec@1 86.000 (87.000) Prec@5 99.000 (99.303) +2022-11-14 14:12:22,762 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0769) Prec@1 88.000 (87.011) Prec@5 99.000 (99.300) +2022-11-14 14:12:22,777 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0766) Prec@1 91.000 (87.055) Prec@5 100.000 (99.308) +2022-11-14 14:12:22,794 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0762) Prec@1 93.000 (87.120) Prec@5 99.000 (99.304) +2022-11-14 14:12:22,811 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0764) Prec@1 84.000 (87.086) Prec@5 100.000 (99.312) +2022-11-14 14:12:22,827 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0763) Prec@1 90.000 (87.117) Prec@5 98.000 (99.298) +2022-11-14 14:12:22,843 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0764) Prec@1 82.000 (87.063) Prec@5 99.000 (99.295) +2022-11-14 14:12:22,858 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0762) Prec@1 89.000 (87.083) Prec@5 99.000 (99.292) +2022-11-14 14:12:22,874 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0759) Prec@1 91.000 (87.124) Prec@5 100.000 (99.299) +2022-11-14 14:12:22,890 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0760) Prec@1 84.000 (87.092) Prec@5 99.000 (99.296) +2022-11-14 14:12:22,908 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0762) Prec@1 85.000 (87.071) Prec@5 100.000 (99.303) +2022-11-14 14:12:22,924 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0761) Prec@1 89.000 (87.090) Prec@5 100.000 (99.310) +2022-11-14 14:12:22,997 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:12:23,576 Epoch: [163][0/500] Time 0.029 (0.029) Data 0.223 (0.223) Loss 0.0449 (0.0449) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:12:23,818 Epoch: [163][10/500] Time 0.018 (0.022) Data 0.001 (0.022) Loss 0.0310 (0.0380) Prec@1 93.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:12:24,045 Epoch: [163][20/500] Time 0.025 (0.021) Data 0.002 (0.012) Loss 0.0474 (0.0411) Prec@1 93.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:12:24,352 Epoch: [163][30/500] Time 0.026 (0.023) Data 0.002 (0.009) Loss 0.0499 (0.0433) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:12:24,749 Epoch: [163][40/500] Time 0.029 (0.026) Data 0.002 (0.007) Loss 0.0683 (0.0483) Prec@1 89.000 (91.800) Prec@5 99.000 (99.800) +2022-11-14 14:12:25,141 Epoch: [163][50/500] Time 0.046 (0.028) Data 0.002 (0.006) Loss 0.0426 (0.0474) Prec@1 93.000 (92.000) Prec@5 100.000 (99.833) +2022-11-14 14:12:25,503 Epoch: [163][60/500] Time 0.034 (0.028) Data 0.002 (0.005) Loss 0.0590 (0.0490) Prec@1 90.000 (91.714) Prec@5 100.000 (99.857) +2022-11-14 14:12:25,867 Epoch: [163][70/500] Time 0.038 (0.029) Data 0.002 (0.005) Loss 0.0698 (0.0516) Prec@1 88.000 (91.250) Prec@5 100.000 (99.875) +2022-11-14 14:12:26,223 Epoch: [163][80/500] Time 0.033 (0.029) Data 0.002 (0.005) Loss 0.0506 (0.0515) Prec@1 90.000 (91.111) Prec@5 99.000 (99.778) +2022-11-14 14:12:26,596 Epoch: [163][90/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0485 (0.0512) Prec@1 93.000 (91.300) Prec@5 99.000 (99.700) +2022-11-14 14:12:26,964 Epoch: [163][100/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0422 (0.0504) Prec@1 96.000 (91.727) Prec@5 100.000 (99.727) +2022-11-14 14:12:27,326 Epoch: [163][110/500] Time 0.034 (0.030) Data 0.002 (0.004) Loss 0.0304 (0.0487) Prec@1 95.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:12:27,731 Epoch: [163][120/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0415 (0.0482) Prec@1 93.000 (92.077) Prec@5 100.000 (99.769) +2022-11-14 14:12:28,100 Epoch: [163][130/500] Time 0.030 (0.031) Data 0.002 (0.004) Loss 0.0359 (0.0473) Prec@1 94.000 (92.214) Prec@5 100.000 (99.786) +2022-11-14 14:12:28,458 Epoch: [163][140/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0499 (0.0475) Prec@1 90.000 (92.067) Prec@5 100.000 (99.800) +2022-11-14 14:12:28,824 Epoch: [163][150/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0578 (0.0481) Prec@1 92.000 (92.062) Prec@5 99.000 (99.750) +2022-11-14 14:12:29,208 Epoch: [163][160/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0314 (0.0471) Prec@1 94.000 (92.176) Prec@5 100.000 (99.765) +2022-11-14 14:12:29,584 Epoch: [163][170/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0474 (0.0471) Prec@1 91.000 (92.111) Prec@5 100.000 (99.778) +2022-11-14 14:12:29,945 Epoch: [163][180/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0573 (0.0477) Prec@1 89.000 (91.947) Prec@5 98.000 (99.684) +2022-11-14 14:12:30,314 Epoch: [163][190/500] Time 0.038 (0.031) Data 0.003 (0.003) Loss 0.0205 (0.0463) Prec@1 97.000 (92.200) Prec@5 100.000 (99.700) +2022-11-14 14:12:30,692 Epoch: [163][200/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0489 (0.0464) Prec@1 93.000 (92.238) Prec@5 100.000 (99.714) +2022-11-14 14:12:31,058 Epoch: [163][210/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0284 (0.0456) Prec@1 95.000 (92.364) Prec@5 98.000 (99.636) +2022-11-14 14:12:31,421 Epoch: [163][220/500] Time 0.036 (0.032) Data 0.001 (0.003) Loss 0.0432 (0.0455) Prec@1 93.000 (92.391) Prec@5 99.000 (99.609) +2022-11-14 14:12:31,795 Epoch: [163][230/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0526 (0.0458) Prec@1 91.000 (92.333) Prec@5 100.000 (99.625) +2022-11-14 14:12:32,160 Epoch: [163][240/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0328 (0.0453) Prec@1 94.000 (92.400) Prec@5 100.000 (99.640) +2022-11-14 14:12:32,546 Epoch: [163][250/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0749 (0.0464) Prec@1 87.000 (92.192) Prec@5 100.000 (99.654) +2022-11-14 14:12:32,916 Epoch: [163][260/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0394 (0.0462) Prec@1 93.000 (92.222) Prec@5 100.000 (99.667) +2022-11-14 14:12:33,271 Epoch: [163][270/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0599 (0.0467) Prec@1 90.000 (92.143) Prec@5 99.000 (99.643) +2022-11-14 14:12:33,638 Epoch: [163][280/500] Time 0.029 (0.032) Data 0.002 (0.003) Loss 0.0370 (0.0463) Prec@1 93.000 (92.172) Prec@5 100.000 (99.655) +2022-11-14 14:12:34,008 Epoch: [163][290/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0561 (0.0467) Prec@1 90.000 (92.100) Prec@5 99.000 (99.633) +2022-11-14 14:12:34,432 Epoch: [163][300/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0346 (0.0463) Prec@1 95.000 (92.194) Prec@5 100.000 (99.645) +2022-11-14 14:12:34,917 Epoch: [163][310/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0441 (0.0462) Prec@1 92.000 (92.188) Prec@5 100.000 (99.656) +2022-11-14 14:12:35,389 Epoch: [163][320/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0432 (0.0461) Prec@1 94.000 (92.242) Prec@5 100.000 (99.667) +2022-11-14 14:12:35,951 Epoch: [163][330/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0694 (0.0468) Prec@1 88.000 (92.118) Prec@5 99.000 (99.647) +2022-11-14 14:12:36,468 Epoch: [163][340/500] Time 0.050 (0.034) Data 0.003 (0.003) Loss 0.0585 (0.0471) Prec@1 88.000 (92.000) Prec@5 100.000 (99.657) +2022-11-14 14:12:36,944 Epoch: [163][350/500] Time 0.041 (0.034) Data 0.003 (0.003) Loss 0.0250 (0.0465) Prec@1 97.000 (92.139) Prec@5 100.000 (99.667) +2022-11-14 14:12:37,434 Epoch: [163][360/500] Time 0.043 (0.034) Data 0.001 (0.003) Loss 0.0394 (0.0463) Prec@1 95.000 (92.216) Prec@5 100.000 (99.676) +2022-11-14 14:12:37,998 Epoch: [163][370/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0328 (0.0460) Prec@1 94.000 (92.263) Prec@5 100.000 (99.684) +2022-11-14 14:12:38,552 Epoch: [163][380/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0525 (0.0461) Prec@1 91.000 (92.231) Prec@5 100.000 (99.692) +2022-11-14 14:12:39,051 Epoch: [163][390/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0525 (0.0463) Prec@1 92.000 (92.225) Prec@5 100.000 (99.700) +2022-11-14 14:12:39,638 Epoch: [163][400/500] Time 0.056 (0.036) Data 0.002 (0.002) Loss 0.0428 (0.0462) Prec@1 91.000 (92.195) Prec@5 100.000 (99.707) +2022-11-14 14:12:40,108 Epoch: [163][410/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0447 (0.0462) Prec@1 93.000 (92.214) Prec@5 100.000 (99.714) +2022-11-14 14:12:40,682 Epoch: [163][420/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0697 (0.0467) Prec@1 87.000 (92.093) Prec@5 100.000 (99.721) +2022-11-14 14:12:41,201 Epoch: [163][430/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0452 (0.0467) Prec@1 92.000 (92.091) Prec@5 100.000 (99.727) +2022-11-14 14:12:41,674 Epoch: [163][440/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0577 (0.0469) Prec@1 89.000 (92.022) Prec@5 99.000 (99.711) +2022-11-14 14:12:42,138 Epoch: [163][450/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0574 (0.0472) Prec@1 89.000 (91.957) Prec@5 100.000 (99.717) +2022-11-14 14:12:42,668 Epoch: [163][460/500] Time 0.053 (0.037) Data 0.002 (0.002) Loss 0.0371 (0.0469) Prec@1 93.000 (91.979) Prec@5 100.000 (99.723) +2022-11-14 14:12:43,175 Epoch: [163][470/500] Time 0.049 (0.037) Data 0.002 (0.002) Loss 0.0462 (0.0469) Prec@1 93.000 (92.000) Prec@5 100.000 (99.729) +2022-11-14 14:12:43,676 Epoch: [163][480/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0326 (0.0466) Prec@1 93.000 (92.020) Prec@5 100.000 (99.735) +2022-11-14 14:12:44,165 Epoch: [163][490/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0469 (0.0466) Prec@1 92.000 (92.020) Prec@5 99.000 (99.720) +2022-11-14 14:12:44,620 Epoch: [163][499/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0511 (0.0467) Prec@1 92.000 (92.020) Prec@5 99.000 (99.706) +2022-11-14 14:12:44,918 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0483 (0.0483) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:12:44,926 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0602) Prec@1 87.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:12:44,936 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0680) Prec@1 84.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 14:12:44,949 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0727) Prec@1 85.000 (87.000) Prec@5 98.000 (99.500) +2022-11-14 14:12:44,958 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0713) Prec@1 89.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 14:12:44,968 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0356 (0.0654) Prec@1 95.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:12:44,977 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0657) Prec@1 88.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 14:12:44,988 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0664) Prec@1 88.000 (88.500) Prec@5 100.000 (99.625) +2022-11-14 14:12:44,999 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0706) Prec@1 85.000 (88.111) Prec@5 98.000 (99.444) +2022-11-14 14:12:45,009 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0691) Prec@1 89.000 (88.200) Prec@5 98.000 (99.300) +2022-11-14 14:12:45,020 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0682) Prec@1 89.000 (88.273) Prec@5 99.000 (99.273) +2022-11-14 14:12:45,030 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0699) Prec@1 84.000 (87.917) Prec@5 99.000 (99.250) +2022-11-14 14:12:45,040 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0681) Prec@1 93.000 (88.308) Prec@5 100.000 (99.308) +2022-11-14 14:12:45,052 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0695) Prec@1 86.000 (88.143) Prec@5 99.000 (99.286) +2022-11-14 14:12:45,063 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0690) Prec@1 91.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:12:45,075 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0687) Prec@1 88.000 (88.312) Prec@5 100.000 (99.375) +2022-11-14 14:12:45,088 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0673) Prec@1 92.000 (88.529) Prec@5 99.000 (99.353) +2022-11-14 14:12:45,100 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0693) Prec@1 85.000 (88.333) Prec@5 97.000 (99.222) +2022-11-14 14:12:45,111 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0702) Prec@1 86.000 (88.211) Prec@5 98.000 (99.158) +2022-11-14 14:12:45,124 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0716) Prec@1 84.000 (88.000) Prec@5 98.000 (99.100) +2022-11-14 14:12:45,137 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0721) Prec@1 87.000 (87.952) Prec@5 100.000 (99.143) +2022-11-14 14:12:45,149 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0726) Prec@1 87.000 (87.909) Prec@5 99.000 (99.136) +2022-11-14 14:12:45,161 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0739) Prec@1 85.000 (87.783) Prec@5 99.000 (99.130) +2022-11-14 14:12:45,175 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0738) Prec@1 88.000 (87.792) Prec@5 100.000 (99.167) +2022-11-14 14:12:45,188 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0740) Prec@1 88.000 (87.800) Prec@5 100.000 (99.200) +2022-11-14 14:12:45,202 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.0760) Prec@1 81.000 (87.538) Prec@5 96.000 (99.077) +2022-11-14 14:12:45,216 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0756) Prec@1 92.000 (87.704) Prec@5 100.000 (99.111) +2022-11-14 14:12:45,229 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0762) Prec@1 86.000 (87.643) Prec@5 99.000 (99.107) +2022-11-14 14:12:45,243 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0759) Prec@1 92.000 (87.793) Prec@5 99.000 (99.103) +2022-11-14 14:12:45,256 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0756) Prec@1 89.000 (87.833) Prec@5 100.000 (99.133) +2022-11-14 14:12:45,268 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0754) Prec@1 87.000 (87.806) Prec@5 99.000 (99.129) +2022-11-14 14:12:45,280 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0755) Prec@1 90.000 (87.875) Prec@5 99.000 (99.125) +2022-11-14 14:12:45,291 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0759) Prec@1 85.000 (87.788) Prec@5 100.000 (99.152) +2022-11-14 14:12:45,307 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0768) Prec@1 82.000 (87.618) Prec@5 99.000 (99.147) +2022-11-14 14:12:45,320 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0770) Prec@1 86.000 (87.571) Prec@5 98.000 (99.114) +2022-11-14 14:12:45,332 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0770) Prec@1 87.000 (87.556) Prec@5 100.000 (99.139) +2022-11-14 14:12:45,345 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0768) Prec@1 86.000 (87.514) Prec@5 100.000 (99.162) +2022-11-14 14:12:45,357 Test: [37/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0774) Prec@1 81.000 (87.342) Prec@5 100.000 (99.184) +2022-11-14 14:12:45,370 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0769) Prec@1 91.000 (87.436) Prec@5 99.000 (99.179) +2022-11-14 14:12:45,383 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0768) Prec@1 86.000 (87.400) Prec@5 98.000 (99.150) +2022-11-14 14:12:45,396 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0770) Prec@1 86.000 (87.366) Prec@5 100.000 (99.171) +2022-11-14 14:12:45,410 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0766) Prec@1 90.000 (87.429) Prec@5 99.000 (99.167) +2022-11-14 14:12:45,423 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0760) Prec@1 92.000 (87.535) Prec@5 100.000 (99.186) +2022-11-14 14:12:45,434 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0757) Prec@1 90.000 (87.591) Prec@5 97.000 (99.136) +2022-11-14 14:12:45,447 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0755) Prec@1 91.000 (87.667) Prec@5 100.000 (99.156) +2022-11-14 14:12:45,458 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0755) Prec@1 85.000 (87.609) Prec@5 100.000 (99.174) +2022-11-14 14:12:45,470 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0753) Prec@1 88.000 (87.617) Prec@5 99.000 (99.170) +2022-11-14 14:12:45,482 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0759) Prec@1 83.000 (87.521) Prec@5 99.000 (99.167) +2022-11-14 14:12:45,493 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0758) Prec@1 89.000 (87.551) Prec@5 98.000 (99.143) +2022-11-14 14:12:45,506 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.0766) Prec@1 81.000 (87.420) Prec@5 99.000 (99.140) +2022-11-14 14:12:45,519 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0768) Prec@1 87.000 (87.412) Prec@5 97.000 (99.098) +2022-11-14 14:12:45,530 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0768) Prec@1 87.000 (87.404) Prec@5 100.000 (99.115) +2022-11-14 14:12:45,542 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0768) Prec@1 88.000 (87.415) Prec@5 100.000 (99.132) +2022-11-14 14:12:45,555 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0766) Prec@1 90.000 (87.463) Prec@5 98.000 (99.111) +2022-11-14 14:12:45,570 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0770) Prec@1 83.000 (87.382) Prec@5 99.000 (99.109) +2022-11-14 14:12:45,583 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0769) Prec@1 89.000 (87.411) Prec@5 99.000 (99.107) +2022-11-14 14:12:45,596 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0769) Prec@1 86.000 (87.386) Prec@5 99.000 (99.105) +2022-11-14 14:12:45,608 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0768) Prec@1 88.000 (87.397) Prec@5 100.000 (99.121) +2022-11-14 14:12:45,620 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0772) Prec@1 82.000 (87.305) Prec@5 99.000 (99.119) +2022-11-14 14:12:45,631 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0771) Prec@1 89.000 (87.333) Prec@5 100.000 (99.133) +2022-11-14 14:12:45,644 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0771) Prec@1 86.000 (87.311) Prec@5 100.000 (99.148) +2022-11-14 14:12:45,655 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0772) Prec@1 86.000 (87.290) Prec@5 99.000 (99.145) +2022-11-14 14:12:45,667 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0769) Prec@1 93.000 (87.381) Prec@5 100.000 (99.159) +2022-11-14 14:12:45,680 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0767) Prec@1 88.000 (87.391) Prec@5 99.000 (99.156) +2022-11-14 14:12:45,692 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.0773) Prec@1 80.000 (87.277) Prec@5 98.000 (99.138) +2022-11-14 14:12:45,704 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0772) Prec@1 89.000 (87.303) Prec@5 99.000 (99.136) +2022-11-14 14:12:45,716 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0768) Prec@1 91.000 (87.358) Prec@5 100.000 (99.149) +2022-11-14 14:12:45,729 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0767) Prec@1 89.000 (87.382) Prec@5 99.000 (99.147) +2022-11-14 14:12:45,742 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0765) Prec@1 88.000 (87.391) Prec@5 98.000 (99.130) +2022-11-14 14:12:45,754 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0766) Prec@1 87.000 (87.386) Prec@5 100.000 (99.143) +2022-11-14 14:12:45,766 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0769) Prec@1 82.000 (87.310) Prec@5 100.000 (99.155) +2022-11-14 14:12:45,777 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0768) Prec@1 89.000 (87.333) Prec@5 99.000 (99.153) +2022-11-14 14:12:45,790 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0765) Prec@1 92.000 (87.397) Prec@5 100.000 (99.164) +2022-11-14 14:12:45,803 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0763) Prec@1 90.000 (87.432) Prec@5 100.000 (99.176) +2022-11-14 14:12:45,815 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1273 (0.0769) Prec@1 78.000 (87.307) Prec@5 98.000 (99.160) +2022-11-14 14:12:45,827 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0768) Prec@1 91.000 (87.355) Prec@5 100.000 (99.171) +2022-11-14 14:12:45,840 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0769) Prec@1 86.000 (87.338) Prec@5 97.000 (99.143) +2022-11-14 14:12:45,853 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0768) Prec@1 89.000 (87.359) Prec@5 97.000 (99.115) +2022-11-14 14:12:45,866 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0772) Prec@1 79.000 (87.253) Prec@5 99.000 (99.114) +2022-11-14 14:12:45,878 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0773) Prec@1 82.000 (87.188) Prec@5 98.000 (99.100) +2022-11-14 14:12:45,891 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0773) Prec@1 88.000 (87.198) Prec@5 100.000 (99.111) +2022-11-14 14:12:45,905 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0774) Prec@1 85.000 (87.171) Prec@5 99.000 (99.110) +2022-11-14 14:12:45,919 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0775) Prec@1 86.000 (87.157) Prec@5 100.000 (99.120) +2022-11-14 14:12:45,933 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0506 (0.0772) Prec@1 89.000 (87.179) Prec@5 100.000 (99.131) +2022-11-14 14:12:45,946 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0773) Prec@1 89.000 (87.200) Prec@5 100.000 (99.141) +2022-11-14 14:12:45,958 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0776) Prec@1 81.000 (87.128) Prec@5 99.000 (99.140) +2022-11-14 14:12:45,971 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0776) Prec@1 86.000 (87.115) Prec@5 99.000 (99.138) +2022-11-14 14:12:45,984 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0775) Prec@1 89.000 (87.136) Prec@5 99.000 (99.136) +2022-11-14 14:12:45,996 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0774) Prec@1 88.000 (87.146) Prec@5 100.000 (99.146) +2022-11-14 14:12:46,007 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0774) Prec@1 89.000 (87.167) Prec@5 98.000 (99.133) +2022-11-14 14:12:46,021 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0773) Prec@1 89.000 (87.187) Prec@5 100.000 (99.143) +2022-11-14 14:12:46,035 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0770) Prec@1 91.000 (87.228) Prec@5 99.000 (99.141) +2022-11-14 14:12:46,049 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0772) Prec@1 85.000 (87.204) Prec@5 100.000 (99.151) +2022-11-14 14:12:46,061 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0772) Prec@1 89.000 (87.223) Prec@5 100.000 (99.160) +2022-11-14 14:12:46,073 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0770) Prec@1 90.000 (87.253) Prec@5 100.000 (99.168) +2022-11-14 14:12:46,085 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0770) Prec@1 89.000 (87.271) Prec@5 99.000 (99.167) +2022-11-14 14:12:46,097 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0766) Prec@1 95.000 (87.351) Prec@5 98.000 (99.155) +2022-11-14 14:12:46,110 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0769) Prec@1 87.000 (87.347) Prec@5 99.000 (99.153) +2022-11-14 14:12:46,123 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0770) Prec@1 86.000 (87.333) Prec@5 99.000 (99.152) +2022-11-14 14:12:46,135 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0769) Prec@1 88.000 (87.340) Prec@5 100.000 (99.160) +2022-11-14 14:12:46,193 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:12:46,712 Epoch: [164][0/500] Time 0.033 (0.033) Data 0.234 (0.234) Loss 0.0351 (0.0351) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:12:46,961 Epoch: [164][10/500] Time 0.031 (0.023) Data 0.002 (0.023) Loss 0.0254 (0.0302) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:12:47,182 Epoch: [164][20/500] Time 0.019 (0.021) Data 0.002 (0.013) Loss 0.0535 (0.0380) Prec@1 93.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:12:47,617 Epoch: [164][30/500] Time 0.079 (0.025) Data 0.002 (0.009) Loss 0.0586 (0.0431) Prec@1 90.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 14:12:48,075 Epoch: [164][40/500] Time 0.043 (0.029) Data 0.002 (0.008) Loss 0.0579 (0.0461) Prec@1 91.000 (92.800) Prec@5 100.000 (100.000) +2022-11-14 14:12:48,647 Epoch: [164][50/500] Time 0.052 (0.034) Data 0.002 (0.006) Loss 0.0235 (0.0423) Prec@1 96.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:12:49,147 Epoch: [164][60/500] Time 0.049 (0.035) Data 0.002 (0.006) Loss 0.0708 (0.0464) Prec@1 87.000 (92.429) Prec@5 100.000 (100.000) +2022-11-14 14:12:49,646 Epoch: [164][70/500] Time 0.047 (0.037) Data 0.002 (0.005) Loss 0.0393 (0.0455) Prec@1 93.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:12:50,185 Epoch: [164][80/500] Time 0.042 (0.038) Data 0.002 (0.005) Loss 0.0329 (0.0441) Prec@1 95.000 (92.778) Prec@5 99.000 (99.889) +2022-11-14 14:12:50,682 Epoch: [164][90/500] Time 0.055 (0.039) Data 0.002 (0.004) Loss 0.0240 (0.0421) Prec@1 96.000 (93.100) Prec@5 100.000 (99.900) +2022-11-14 14:12:51,183 Epoch: [164][100/500] Time 0.052 (0.040) Data 0.002 (0.004) Loss 0.0468 (0.0425) Prec@1 93.000 (93.091) Prec@5 100.000 (99.909) +2022-11-14 14:12:51,682 Epoch: [164][110/500] Time 0.042 (0.040) Data 0.002 (0.004) Loss 0.0172 (0.0404) Prec@1 97.000 (93.417) Prec@5 99.000 (99.833) +2022-11-14 14:12:52,178 Epoch: [164][120/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0509 (0.0412) Prec@1 91.000 (93.231) Prec@5 100.000 (99.846) +2022-11-14 14:12:52,684 Epoch: [164][130/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0464 (0.0416) Prec@1 93.000 (93.214) Prec@5 100.000 (99.857) +2022-11-14 14:12:53,167 Epoch: [164][140/500] Time 0.042 (0.041) Data 0.002 (0.004) Loss 0.0654 (0.0432) Prec@1 87.000 (92.800) Prec@5 99.000 (99.800) +2022-11-14 14:12:53,643 Epoch: [164][150/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0644 (0.0445) Prec@1 89.000 (92.562) Prec@5 99.000 (99.750) +2022-11-14 14:12:54,173 Epoch: [164][160/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0469 (0.0446) Prec@1 88.000 (92.294) Prec@5 100.000 (99.765) +2022-11-14 14:12:54,675 Epoch: [164][170/500] Time 0.042 (0.042) Data 0.003 (0.003) Loss 0.0613 (0.0456) Prec@1 89.000 (92.111) Prec@5 100.000 (99.778) +2022-11-14 14:12:55,171 Epoch: [164][180/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0508 (0.0458) Prec@1 92.000 (92.105) Prec@5 100.000 (99.789) +2022-11-14 14:12:55,642 Epoch: [164][190/500] Time 0.050 (0.042) Data 0.003 (0.003) Loss 0.0289 (0.0450) Prec@1 95.000 (92.250) Prec@5 100.000 (99.800) +2022-11-14 14:12:56,123 Epoch: [164][200/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0623 (0.0458) Prec@1 88.000 (92.048) Prec@5 100.000 (99.810) +2022-11-14 14:12:56,634 Epoch: [164][210/500] Time 0.056 (0.042) Data 0.002 (0.003) Loss 0.0592 (0.0464) Prec@1 89.000 (91.909) Prec@5 98.000 (99.727) +2022-11-14 14:12:57,164 Epoch: [164][220/500] Time 0.032 (0.042) Data 0.002 (0.003) Loss 0.0291 (0.0457) Prec@1 95.000 (92.043) Prec@5 99.000 (99.696) +2022-11-14 14:12:57,704 Epoch: [164][230/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0603 (0.0463) Prec@1 91.000 (92.000) Prec@5 99.000 (99.667) +2022-11-14 14:12:58,188 Epoch: [164][240/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0357 (0.0459) Prec@1 93.000 (92.040) Prec@5 100.000 (99.680) +2022-11-14 14:12:58,763 Epoch: [164][250/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0398 (0.0456) Prec@1 94.000 (92.115) Prec@5 100.000 (99.692) +2022-11-14 14:12:59,250 Epoch: [164][260/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0404 (0.0454) Prec@1 93.000 (92.148) Prec@5 100.000 (99.704) +2022-11-14 14:12:59,733 Epoch: [164][270/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0439 (0.0454) Prec@1 91.000 (92.107) Prec@5 99.000 (99.679) +2022-11-14 14:13:00,282 Epoch: [164][280/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0527 (0.0456) Prec@1 93.000 (92.138) Prec@5 99.000 (99.655) +2022-11-14 14:13:00,777 Epoch: [164][290/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0403 (0.0455) Prec@1 94.000 (92.200) Prec@5 99.000 (99.633) +2022-11-14 14:13:01,321 Epoch: [164][300/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0465 (0.0455) Prec@1 91.000 (92.161) Prec@5 99.000 (99.613) +2022-11-14 14:13:01,870 Epoch: [164][310/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0389 (0.0453) Prec@1 95.000 (92.250) Prec@5 100.000 (99.625) 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(0.003) Loss 0.0563 (0.0455) Prec@1 88.000 (92.154) Prec@5 100.000 (99.692) +2022-11-14 14:13:06,238 Epoch: [164][390/500] Time 0.031 (0.045) Data 0.002 (0.003) Loss 0.0346 (0.0453) Prec@1 93.000 (92.175) Prec@5 100.000 (99.700) +2022-11-14 14:13:06,734 Epoch: [164][400/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0348 (0.0450) Prec@1 95.000 (92.244) Prec@5 99.000 (99.683) +2022-11-14 14:13:07,255 Epoch: [164][410/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0485 (0.0451) Prec@1 94.000 (92.286) Prec@5 100.000 (99.690) +2022-11-14 14:13:07,808 Epoch: [164][420/500] Time 0.080 (0.045) Data 0.002 (0.003) Loss 0.0475 (0.0451) Prec@1 92.000 (92.279) Prec@5 100.000 (99.698) +2022-11-14 14:13:08,271 Epoch: [164][430/500] Time 0.061 (0.045) Data 0.002 (0.002) Loss 0.0397 (0.0450) Prec@1 95.000 (92.341) Prec@5 100.000 (99.705) +2022-11-14 14:13:08,754 Epoch: [164][440/500] Time 0.043 (0.045) Data 0.002 (0.002) Loss 0.0453 (0.0450) Prec@1 93.000 (92.356) Prec@5 99.000 (99.689) 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(99.286) +2022-11-14 14:13:12,196 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0802) Prec@1 85.000 (86.750) Prec@5 100.000 (99.375) +2022-11-14 14:13:12,205 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0792) Prec@1 87.000 (86.778) Prec@5 100.000 (99.444) +2022-11-14 14:13:12,214 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0782) Prec@1 88.000 (86.900) Prec@5 99.000 (99.400) +2022-11-14 14:13:12,226 Test: [10/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0771) Prec@1 90.000 (87.182) Prec@5 100.000 (99.455) +2022-11-14 14:13:12,237 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0775) Prec@1 87.000 (87.167) Prec@5 99.000 (99.417) +2022-11-14 14:13:12,248 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0771) Prec@1 86.000 (87.077) Prec@5 100.000 (99.462) +2022-11-14 14:13:12,258 Test: [13/100] Model Time 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Prec@1 87.000 (87.300) Prec@5 99.000 (99.350) +2022-11-14 14:13:12,332 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0760) Prec@1 87.000 (87.286) Prec@5 100.000 (99.381) +2022-11-14 14:13:12,341 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0763) Prec@1 87.000 (87.273) Prec@5 100.000 (99.409) +2022-11-14 14:13:12,352 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0771) Prec@1 86.000 (87.217) Prec@5 97.000 (99.304) +2022-11-14 14:13:12,364 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0770) Prec@1 86.000 (87.167) Prec@5 100.000 (99.333) +2022-11-14 14:13:12,373 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0774) Prec@1 85.000 (87.080) Prec@5 99.000 (99.320) +2022-11-14 14:13:12,384 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0783) Prec@1 84.000 (86.962) Prec@5 97.000 (99.231) +2022-11-14 14:13:12,395 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0777) Prec@1 90.000 (87.074) Prec@5 99.000 (99.222) +2022-11-14 14:13:12,409 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0777) Prec@1 86.000 (87.036) Prec@5 100.000 (99.250) +2022-11-14 14:13:12,420 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0772) Prec@1 89.000 (87.103) Prec@5 98.000 (99.207) +2022-11-14 14:13:12,430 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0767) Prec@1 91.000 (87.233) Prec@5 100.000 (99.233) +2022-11-14 14:13:12,441 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0768) Prec@1 88.000 (87.258) Prec@5 99.000 (99.226) +2022-11-14 14:13:12,451 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0767) Prec@1 90.000 (87.344) Prec@5 99.000 (99.219) +2022-11-14 14:13:12,463 Test: [32/100] Model Time 0.007 (0.008) Loss Time 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Prec@5 99.000 (99.256) +2022-11-14 14:13:12,538 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0767) Prec@1 88.000 (87.375) Prec@5 100.000 (99.275) +2022-11-14 14:13:12,548 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0769) Prec@1 89.000 (87.415) Prec@5 99.000 (99.268) +2022-11-14 14:13:12,560 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0771) Prec@1 84.000 (87.333) Prec@5 99.000 (99.262) +2022-11-14 14:13:12,573 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0766) Prec@1 90.000 (87.395) Prec@5 99.000 (99.256) +2022-11-14 14:13:12,583 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0765) Prec@1 89.000 (87.432) Prec@5 99.000 (99.250) +2022-11-14 14:13:12,595 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0762) Prec@1 91.000 (87.511) Prec@5 99.000 (99.244) +2022-11-14 14:13:12,606 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0768) Prec@1 86.000 (87.478) Prec@5 99.000 (99.239) +2022-11-14 14:13:12,616 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0763) Prec@1 90.000 (87.532) Prec@5 100.000 (99.255) +2022-11-14 14:13:12,626 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0766) Prec@1 85.000 (87.479) Prec@5 100.000 (99.271) +2022-11-14 14:13:12,640 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0762) Prec@1 89.000 (87.510) Prec@5 100.000 (99.286) +2022-11-14 14:13:12,651 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0769) Prec@1 84.000 (87.440) Prec@5 100.000 (99.300) +2022-11-14 14:13:12,662 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0767) Prec@1 89.000 (87.471) Prec@5 100.000 (99.314) +2022-11-14 14:13:12,671 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0768) Prec@1 85.000 (87.423) Prec@5 99.000 (99.308) +2022-11-14 14:13:12,682 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0764) Prec@1 89.000 (87.453) Prec@5 100.000 (99.321) +2022-11-14 14:13:12,696 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0763) Prec@1 89.000 (87.481) Prec@5 100.000 (99.333) +2022-11-14 14:13:12,708 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0768) Prec@1 83.000 (87.400) Prec@5 99.000 (99.327) +2022-11-14 14:13:12,719 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0767) Prec@1 89.000 (87.429) Prec@5 99.000 (99.321) +2022-11-14 14:13:12,729 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0766) Prec@1 88.000 (87.439) Prec@5 100.000 (99.333) +2022-11-14 14:13:12,739 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0767) Prec@1 88.000 (87.448) Prec@5 99.000 (99.328) +2022-11-14 14:13:12,749 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0773) Prec@1 80.000 (87.322) Prec@5 98.000 (99.305) +2022-11-14 14:13:12,761 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0771) Prec@1 89.000 (87.350) Prec@5 100.000 (99.317) +2022-11-14 14:13:12,772 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0772) Prec@1 86.000 (87.328) Prec@5 99.000 (99.311) +2022-11-14 14:13:12,781 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0773) Prec@1 87.000 (87.323) Prec@5 100.000 (99.323) +2022-11-14 14:13:12,791 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0773) Prec@1 85.000 (87.286) Prec@5 100.000 (99.333) +2022-11-14 14:13:12,802 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0767) Prec@1 92.000 (87.359) Prec@5 100.000 (99.344) +2022-11-14 14:13:12,812 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0769) Prec@1 86.000 (87.338) Prec@5 99.000 (99.338) +2022-11-14 14:13:12,825 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0767) Prec@1 89.000 (87.364) Prec@5 100.000 (99.348) +2022-11-14 14:13:12,836 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0764) Prec@1 91.000 (87.418) Prec@5 100.000 (99.358) +2022-11-14 14:13:12,846 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0762) Prec@1 90.000 (87.456) Prec@5 100.000 (99.368) +2022-11-14 14:13:12,857 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0761) Prec@1 87.000 (87.449) Prec@5 99.000 (99.362) +2022-11-14 14:13:12,868 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0762) Prec@1 89.000 (87.471) Prec@5 99.000 (99.357) +2022-11-14 14:13:12,879 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0763) Prec@1 88.000 (87.479) Prec@5 99.000 (99.352) +2022-11-14 14:13:12,889 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0762) Prec@1 87.000 (87.472) Prec@5 100.000 (99.361) +2022-11-14 14:13:12,900 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0758) Prec@1 94.000 (87.562) Prec@5 99.000 (99.356) +2022-11-14 14:13:12,911 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0753) Prec@1 93.000 (87.635) Prec@5 100.000 (99.365) +2022-11-14 14:13:12,922 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0757) Prec@1 83.000 (87.573) Prec@5 99.000 (99.360) +2022-11-14 14:13:12,934 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0756) Prec@1 89.000 (87.592) Prec@5 100.000 (99.368) +2022-11-14 14:13:12,944 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0755) Prec@1 88.000 (87.597) Prec@5 95.000 (99.312) +2022-11-14 14:13:12,956 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0756) Prec@1 85.000 (87.564) Prec@5 98.000 (99.295) +2022-11-14 14:13:12,966 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0757) Prec@1 85.000 (87.532) Prec@5 100.000 (99.304) +2022-11-14 14:13:12,977 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0755) Prec@1 90.000 (87.562) Prec@5 99.000 (99.300) +2022-11-14 14:13:12,988 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0757) Prec@1 84.000 (87.519) Prec@5 100.000 (99.309) +2022-11-14 14:13:12,999 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0757) Prec@1 87.000 (87.512) Prec@5 98.000 (99.293) +2022-11-14 14:13:13,011 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0757) Prec@1 86.000 (87.494) Prec@5 100.000 (99.301) +2022-11-14 14:13:13,021 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0756) Prec@1 87.000 (87.488) Prec@5 99.000 (99.298) +2022-11-14 14:13:13,032 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0756) Prec@1 89.000 (87.506) Prec@5 100.000 (99.306) +2022-11-14 14:13:13,042 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0758) Prec@1 84.000 (87.465) Prec@5 100.000 (99.314) +2022-11-14 14:13:13,053 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0757) Prec@1 87.000 (87.460) Prec@5 99.000 (99.310) +2022-11-14 14:13:13,066 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0756) Prec@1 91.000 (87.500) Prec@5 99.000 (99.307) +2022-11-14 14:13:13,077 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0755) Prec@1 90.000 (87.528) Prec@5 99.000 (99.303) +2022-11-14 14:13:13,087 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0755) Prec@1 88.000 (87.533) Prec@5 100.000 (99.311) +2022-11-14 14:13:13,097 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0753) Prec@1 91.000 (87.571) Prec@5 100.000 (99.319) +2022-11-14 14:13:13,108 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0750) Prec@1 92.000 (87.620) Prec@5 99.000 (99.315) +2022-11-14 14:13:13,118 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0753) Prec@1 82.000 (87.559) Prec@5 100.000 (99.323) +2022-11-14 14:13:13,129 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0753) Prec@1 90.000 (87.585) Prec@5 99.000 (99.319) +2022-11-14 14:13:13,145 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0752) Prec@1 90.000 (87.611) Prec@5 100.000 (99.326) +2022-11-14 14:13:13,161 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0750) Prec@1 90.000 (87.635) Prec@5 99.000 (99.323) +2022-11-14 14:13:13,176 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0748) Prec@1 91.000 (87.670) Prec@5 100.000 (99.330) +2022-11-14 14:13:13,189 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0750) Prec@1 87.000 (87.663) Prec@5 98.000 (99.316) +2022-11-14 14:13:13,202 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0753) Prec@1 82.000 (87.606) Prec@5 97.000 (99.293) +2022-11-14 14:13:13,217 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0753) Prec@1 90.000 (87.630) Prec@5 100.000 (99.300) +2022-11-14 14:13:13,277 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:13:13,984 Epoch: [165][0/500] Time 0.025 (0.025) Data 0.235 (0.235) Loss 0.0681 (0.0681) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:13:14,215 Epoch: [165][10/500] Time 0.019 (0.021) Data 0.002 (0.023) Loss 0.0550 (0.0616) Prec@1 93.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:13:14,431 Epoch: [165][20/500] Time 0.018 (0.020) Data 0.002 (0.013) Loss 0.0452 (0.0561) Prec@1 90.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 14:13:14,723 Epoch: [165][30/500] Time 0.025 (0.022) Data 0.002 (0.010) Loss 0.0417 (0.0525) Prec@1 93.000 (90.500) Prec@5 99.000 (99.750) +2022-11-14 14:13:14,961 Epoch: [165][40/500] Time 0.017 (0.022) Data 0.002 (0.008) Loss 0.0339 (0.0488) Prec@1 95.000 (91.400) Prec@5 99.000 (99.600) +2022-11-14 14:13:15,173 Epoch: [165][50/500] Time 0.020 (0.021) Data 0.002 (0.006) Loss 0.0704 (0.0524) Prec@1 86.000 (90.500) Prec@5 100.000 (99.667) +2022-11-14 14:13:15,452 Epoch: [165][60/500] Time 0.030 (0.022) Data 0.002 (0.006) Loss 0.0462 (0.0515) Prec@1 93.000 (90.857) Prec@5 98.000 (99.429) +2022-11-14 14:13:15,737 Epoch: [165][70/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0267 (0.0484) Prec@1 95.000 (91.375) Prec@5 100.000 (99.500) +2022-11-14 14:13:16,020 Epoch: [165][80/500] Time 0.025 (0.023) Data 0.002 (0.005) Loss 0.0541 (0.0490) Prec@1 90.000 (91.222) Prec@5 100.000 (99.556) +2022-11-14 14:13:16,304 Epoch: [165][90/500] Time 0.026 (0.023) Data 0.003 (0.004) Loss 0.0431 (0.0484) Prec@1 93.000 (91.400) Prec@5 100.000 (99.600) +2022-11-14 14:13:16,746 Epoch: [165][100/500] Time 0.042 (0.024) Data 0.002 (0.004) Loss 0.0542 (0.0490) Prec@1 92.000 (91.455) Prec@5 99.000 (99.545) +2022-11-14 14:13:17,271 Epoch: [165][110/500] Time 0.045 (0.027) Data 0.001 (0.004) Loss 0.0419 (0.0484) Prec@1 93.000 (91.583) Prec@5 100.000 (99.583) +2022-11-14 14:13:17,777 Epoch: [165][120/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0357 (0.0474) Prec@1 95.000 (91.846) Prec@5 100.000 (99.615) +2022-11-14 14:13:18,248 Epoch: [165][130/500] Time 0.044 (0.029) Data 0.001 (0.004) Loss 0.0433 (0.0471) Prec@1 92.000 (91.857) Prec@5 100.000 (99.643) +2022-11-14 14:13:18,735 Epoch: [165][140/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0557 (0.0477) Prec@1 92.000 (91.867) Prec@5 99.000 (99.600) +2022-11-14 14:13:19,235 Epoch: [165][150/500] Time 0.049 (0.031) Data 0.002 (0.003) Loss 0.0450 (0.0475) Prec@1 91.000 (91.812) Prec@5 100.000 (99.625) +2022-11-14 14:13:19,729 Epoch: [165][160/500] Time 0.044 (0.032) Data 0.001 (0.003) Loss 0.0649 (0.0485) Prec@1 88.000 (91.588) Prec@5 100.000 (99.647) +2022-11-14 14:13:20,222 Epoch: [165][170/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0530 (0.0488) Prec@1 91.000 (91.556) Prec@5 99.000 (99.611) +2022-11-14 14:13:20,701 Epoch: [165][180/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0496 (0.0488) Prec@1 92.000 (91.579) Prec@5 100.000 (99.632) +2022-11-14 14:13:21,175 Epoch: [165][190/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0372 (0.0482) Prec@1 92.000 (91.600) Prec@5 100.000 (99.650) +2022-11-14 14:13:21,664 Epoch: [165][200/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0573 (0.0487) Prec@1 93.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:13:22,144 Epoch: [165][210/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0673 (0.0495) Prec@1 89.000 (91.545) Prec@5 99.000 (99.636) +2022-11-14 14:13:22,653 Epoch: [165][220/500] Time 0.069 (0.035) Data 0.002 (0.003) Loss 0.0206 (0.0483) Prec@1 98.000 (91.826) Prec@5 100.000 (99.652) +2022-11-14 14:13:23,175 Epoch: [165][230/500] Time 0.064 (0.035) Data 0.002 (0.003) Loss 0.0738 (0.0493) Prec@1 89.000 (91.708) Prec@5 97.000 (99.542) +2022-11-14 14:13:23,709 Epoch: [165][240/500] Time 0.097 (0.036) Data 0.002 (0.003) Loss 0.0367 (0.0488) Prec@1 93.000 (91.760) Prec@5 100.000 (99.560) +2022-11-14 14:13:24,222 Epoch: [165][250/500] Time 0.103 (0.036) Data 0.002 (0.003) Loss 0.0487 (0.0488) Prec@1 93.000 (91.808) Prec@5 100.000 (99.577) +2022-11-14 14:13:24,738 Epoch: [165][260/500] Time 0.077 (0.037) Data 0.002 (0.003) Loss 0.0293 (0.0481) Prec@1 94.000 (91.889) Prec@5 100.000 (99.593) +2022-11-14 14:13:25,262 Epoch: [165][270/500] Time 0.054 (0.037) Data 0.002 (0.003) Loss 0.0510 (0.0482) Prec@1 92.000 (91.893) Prec@5 100.000 (99.607) +2022-11-14 14:13:25,792 Epoch: [165][280/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.0462 (0.0481) Prec@1 93.000 (91.931) Prec@5 100.000 (99.621) +2022-11-14 14:13:26,313 Epoch: [165][290/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0668 (0.0487) Prec@1 87.000 (91.767) Prec@5 98.000 (99.567) +2022-11-14 14:13:26,831 Epoch: [165][300/500] Time 0.039 (0.038) Data 0.001 (0.003) Loss 0.0197 (0.0478) Prec@1 97.000 (91.935) Prec@5 100.000 (99.581) +2022-11-14 14:13:27,368 Epoch: [165][310/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0458 (0.0477) Prec@1 94.000 (92.000) Prec@5 98.000 (99.531) +2022-11-14 14:13:27,899 Epoch: [165][320/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0607 (0.0481) Prec@1 90.000 (91.939) Prec@5 98.000 (99.485) +2022-11-14 14:13:28,433 Epoch: [165][330/500] Time 0.082 (0.039) Data 0.002 (0.003) Loss 0.0580 (0.0484) Prec@1 90.000 (91.882) Prec@5 100.000 (99.500) +2022-11-14 14:13:28,888 Epoch: [165][340/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0639 (0.0489) Prec@1 89.000 (91.800) Prec@5 100.000 (99.514) +2022-11-14 14:13:29,409 Epoch: [165][350/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0516 (0.0489) Prec@1 90.000 (91.750) Prec@5 100.000 (99.528) +2022-11-14 14:13:29,934 Epoch: [165][360/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0458 (0.0489) Prec@1 93.000 (91.784) Prec@5 100.000 (99.541) +2022-11-14 14:13:30,456 Epoch: [165][370/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0542 (0.0490) Prec@1 90.000 (91.737) Prec@5 100.000 (99.553) +2022-11-14 14:13:30,971 Epoch: [165][380/500] Time 0.045 (0.040) Data 0.002 (0.002) Loss 0.0524 (0.0491) Prec@1 91.000 (91.718) Prec@5 100.000 (99.564) +2022-11-14 14:13:31,500 Epoch: [165][390/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0508 (0.0491) Prec@1 91.000 (91.700) Prec@5 99.000 (99.550) +2022-11-14 14:13:32,007 Epoch: [165][400/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0332 (0.0487) Prec@1 96.000 (91.805) Prec@5 100.000 (99.561) +2022-11-14 14:13:32,489 Epoch: [165][410/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0503 (0.0488) Prec@1 92.000 (91.810) Prec@5 99.000 (99.548) +2022-11-14 14:13:32,974 Epoch: [165][420/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.0210 (0.0481) Prec@1 95.000 (91.884) Prec@5 100.000 (99.558) +2022-11-14 14:13:33,456 Epoch: [165][430/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0551 (0.0483) Prec@1 91.000 (91.864) Prec@5 100.000 (99.568) +2022-11-14 14:13:33,933 Epoch: [165][440/500] Time 0.046 (0.040) Data 0.002 (0.002) Loss 0.0598 (0.0485) Prec@1 89.000 (91.800) Prec@5 99.000 (99.556) +2022-11-14 14:13:34,465 Epoch: [165][450/500] Time 0.073 (0.040) Data 0.002 (0.002) Loss 0.0463 (0.0485) Prec@1 92.000 (91.804) Prec@5 98.000 (99.522) +2022-11-14 14:13:34,979 Epoch: [165][460/500] Time 0.084 (0.041) Data 0.002 (0.002) Loss 0.0330 (0.0482) Prec@1 93.000 (91.830) Prec@5 99.000 (99.511) +2022-11-14 14:13:35,486 Epoch: [165][470/500] Time 0.090 (0.041) Data 0.002 (0.002) Loss 0.0636 (0.0485) Prec@1 90.000 (91.792) Prec@5 99.000 (99.500) +2022-11-14 14:13:35,951 Epoch: [165][480/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0513 (0.0485) Prec@1 92.000 (91.796) Prec@5 100.000 (99.510) +2022-11-14 14:13:36,430 Epoch: [165][490/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0561 (0.0487) Prec@1 92.000 (91.800) Prec@5 99.000 (99.500) +2022-11-14 14:13:36,873 Epoch: [165][499/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0267 (0.0483) Prec@1 95.000 (91.863) Prec@5 100.000 (99.510) +2022-11-14 14:13:37,143 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0688 (0.0688) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:13:37,151 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0755) Prec@1 89.000 (89.500) Prec@5 98.000 (98.500) +2022-11-14 14:13:37,161 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0786) Prec@1 85.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 14:13:37,172 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0828) Prec@1 86.000 (87.500) Prec@5 99.000 (99.000) +2022-11-14 14:13:37,179 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0813) Prec@1 90.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 14:13:37,188 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0472 (0.0756) Prec@1 90.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:13:37,197 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0734) Prec@1 92.000 (88.857) Prec@5 99.000 (99.286) +2022-11-14 14:13:37,205 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0736) Prec@1 87.000 (88.625) Prec@5 99.000 (99.250) +2022-11-14 14:13:37,214 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0753) Prec@1 86.000 (88.333) Prec@5 99.000 (99.222) +2022-11-14 14:13:37,224 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0756) Prec@1 86.000 (88.100) Prec@5 99.000 (99.200) +2022-11-14 14:13:37,233 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0747) Prec@1 89.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 14:13:37,241 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0748) Prec@1 87.000 (88.083) Prec@5 99.000 (99.250) +2022-11-14 14:13:37,251 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0740) Prec@1 91.000 (88.308) Prec@5 100.000 (99.308) +2022-11-14 14:13:37,262 Test: [13/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0729) Prec@1 91.000 (88.500) Prec@5 100.000 (99.357) +2022-11-14 14:13:37,274 Test: [14/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0726) Prec@1 88.000 (88.467) Prec@5 100.000 (99.400) +2022-11-14 14:13:37,284 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0721) Prec@1 90.000 (88.562) Prec@5 99.000 (99.375) +2022-11-14 14:13:37,293 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0718) Prec@1 91.000 (88.706) Prec@5 98.000 (99.294) +2022-11-14 14:13:37,302 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0732) Prec@1 84.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 14:13:37,311 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0729) Prec@1 87.000 (88.368) Prec@5 99.000 (99.316) +2022-11-14 14:13:37,320 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0735) Prec@1 83.000 (88.100) Prec@5 100.000 (99.350) +2022-11-14 14:13:37,329 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0748) Prec@1 85.000 (87.952) Prec@5 99.000 (99.333) +2022-11-14 14:13:37,338 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0751) Prec@1 84.000 (87.773) Prec@5 98.000 (99.273) +2022-11-14 14:13:37,348 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0756) Prec@1 84.000 (87.609) Prec@5 99.000 (99.261) +2022-11-14 14:13:37,357 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0751) Prec@1 91.000 (87.750) Prec@5 100.000 (99.292) +2022-11-14 14:13:37,366 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0750) Prec@1 89.000 (87.800) Prec@5 100.000 (99.320) +2022-11-14 14:13:37,376 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0761) Prec@1 84.000 (87.654) Prec@5 99.000 (99.308) +2022-11-14 14:13:37,385 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0752) Prec@1 92.000 (87.815) Prec@5 100.000 (99.333) +2022-11-14 14:13:37,394 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0752) Prec@1 87.000 (87.786) Prec@5 100.000 (99.357) +2022-11-14 14:13:37,403 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0750) Prec@1 89.000 (87.828) Prec@5 99.000 (99.345) +2022-11-14 14:13:37,413 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0755) Prec@1 81.000 (87.600) Prec@5 99.000 (99.333) +2022-11-14 14:13:37,422 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0750) Prec@1 89.000 (87.645) Prec@5 100.000 (99.355) +2022-11-14 14:13:37,433 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0750) Prec@1 86.000 (87.594) Prec@5 99.000 (99.344) +2022-11-14 14:13:37,443 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0755) Prec@1 85.000 (87.515) Prec@5 98.000 (99.303) +2022-11-14 14:13:37,453 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0755) Prec@1 86.000 (87.471) Prec@5 100.000 (99.324) +2022-11-14 14:13:37,463 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0757) Prec@1 86.000 (87.429) Prec@5 98.000 (99.286) +2022-11-14 14:13:37,474 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0754) Prec@1 88.000 (87.444) Prec@5 99.000 (99.278) +2022-11-14 14:13:37,483 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0754) Prec@1 88.000 (87.459) Prec@5 98.000 (99.243) +2022-11-14 14:13:37,493 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.0764) Prec@1 83.000 (87.342) Prec@5 100.000 (99.263) +2022-11-14 14:13:37,503 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0761) Prec@1 92.000 (87.462) Prec@5 99.000 (99.256) +2022-11-14 14:13:37,512 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0761) Prec@1 86.000 (87.425) Prec@5 99.000 (99.250) +2022-11-14 14:13:37,522 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0769) Prec@1 81.000 (87.268) Prec@5 97.000 (99.195) +2022-11-14 14:13:37,531 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0764) Prec@1 91.000 (87.357) Prec@5 98.000 (99.167) +2022-11-14 14:13:37,540 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0760) Prec@1 91.000 (87.442) Prec@5 100.000 (99.186) +2022-11-14 14:13:37,550 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0757) Prec@1 89.000 (87.477) Prec@5 99.000 (99.182) +2022-11-14 14:13:37,560 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0756) Prec@1 86.000 (87.444) Prec@5 100.000 (99.200) +2022-11-14 14:13:37,569 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0756) Prec@1 90.000 (87.500) Prec@5 98.000 (99.174) +2022-11-14 14:13:37,579 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0753) Prec@1 91.000 (87.574) Prec@5 99.000 (99.170) +2022-11-14 14:13:37,588 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0759) Prec@1 82.000 (87.458) Prec@5 97.000 (99.125) +2022-11-14 14:13:37,596 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0756) Prec@1 90.000 (87.510) Prec@5 99.000 (99.122) +2022-11-14 14:13:37,606 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0762) Prec@1 82.000 (87.400) Prec@5 99.000 (99.120) +2022-11-14 14:13:37,616 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0762) Prec@1 87.000 (87.392) Prec@5 100.000 (99.137) +2022-11-14 14:13:37,625 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0763) Prec@1 86.000 (87.365) Prec@5 99.000 (99.135) +2022-11-14 14:13:37,635 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0761) Prec@1 86.000 (87.340) Prec@5 100.000 (99.151) +2022-11-14 14:13:37,644 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0763) Prec@1 85.000 (87.296) Prec@5 100.000 (99.167) +2022-11-14 14:13:37,654 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0765) Prec@1 87.000 (87.291) Prec@5 100.000 (99.182) +2022-11-14 14:13:37,663 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0764) Prec@1 89.000 (87.321) Prec@5 99.000 (99.179) +2022-11-14 14:13:37,672 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0763) Prec@1 88.000 (87.333) Prec@5 99.000 (99.175) +2022-11-14 14:13:37,682 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0761) Prec@1 89.000 (87.362) Prec@5 99.000 (99.172) +2022-11-14 14:13:37,691 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1208 (0.0769) Prec@1 82.000 (87.271) Prec@5 100.000 (99.186) +2022-11-14 14:13:37,700 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0768) Prec@1 87.000 (87.267) Prec@5 100.000 (99.200) +2022-11-14 14:13:37,708 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0772) Prec@1 81.000 (87.164) Prec@5 100.000 (99.213) +2022-11-14 14:13:37,716 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0771) Prec@1 86.000 (87.145) Prec@5 99.000 (99.210) +2022-11-14 14:13:37,724 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0769) Prec@1 88.000 (87.159) Prec@5 100.000 (99.222) +2022-11-14 14:13:37,734 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0764) Prec@1 94.000 (87.266) Prec@5 100.000 (99.234) +2022-11-14 14:13:37,742 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0768) Prec@1 83.000 (87.200) Prec@5 99.000 (99.231) +2022-11-14 14:13:37,752 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0767) Prec@1 91.000 (87.258) Prec@5 99.000 (99.227) +2022-11-14 14:13:37,761 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0765) Prec@1 88.000 (87.269) Prec@5 99.000 (99.224) +2022-11-14 14:13:37,770 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0765) Prec@1 86.000 (87.250) Prec@5 100.000 (99.235) +2022-11-14 14:13:37,781 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0765) Prec@1 89.000 (87.275) Prec@5 99.000 (99.232) +2022-11-14 14:13:37,792 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0767) Prec@1 86.000 (87.257) Prec@5 100.000 (99.243) +2022-11-14 14:13:37,803 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0768) Prec@1 88.000 (87.268) Prec@5 98.000 (99.225) +2022-11-14 14:13:37,815 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0764) Prec@1 92.000 (87.333) Prec@5 100.000 (99.236) +2022-11-14 14:13:37,826 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0761) Prec@1 91.000 (87.384) Prec@5 100.000 (99.247) +2022-11-14 14:13:37,838 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0759) Prec@1 91.000 (87.432) Prec@5 100.000 (99.257) +2022-11-14 14:13:37,851 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1242 (0.0765) Prec@1 81.000 (87.347) Prec@5 99.000 (99.253) +2022-11-14 14:13:37,862 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0763) Prec@1 90.000 (87.382) Prec@5 99.000 (99.250) +2022-11-14 14:13:37,875 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0765) Prec@1 85.000 (87.351) Prec@5 99.000 (99.247) +2022-11-14 14:13:37,889 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0764) Prec@1 87.000 (87.346) Prec@5 100.000 (99.256) +2022-11-14 14:13:37,901 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0766) Prec@1 85.000 (87.316) Prec@5 100.000 (99.266) +2022-11-14 14:13:37,912 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0766) Prec@1 87.000 (87.312) Prec@5 99.000 (99.263) +2022-11-14 14:13:37,923 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0769) Prec@1 84.000 (87.272) Prec@5 100.000 (99.272) +2022-11-14 14:13:37,933 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0768) Prec@1 90.000 (87.305) Prec@5 100.000 (99.280) +2022-11-14 14:13:37,942 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0768) Prec@1 87.000 (87.301) Prec@5 100.000 (99.289) +2022-11-14 14:13:37,952 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0769) Prec@1 85.000 (87.274) Prec@5 99.000 (99.286) +2022-11-14 14:13:37,961 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0774) Prec@1 79.000 (87.176) Prec@5 99.000 (99.282) +2022-11-14 14:13:37,970 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0778) Prec@1 83.000 (87.128) Prec@5 99.000 (99.279) +2022-11-14 14:13:37,982 Test: [86/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0777) Prec@1 89.000 (87.149) Prec@5 100.000 (99.287) +2022-11-14 14:13:37,993 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0775) Prec@1 88.000 (87.159) Prec@5 100.000 (99.295) +2022-11-14 14:13:38,002 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0774) Prec@1 86.000 (87.146) Prec@5 97.000 (99.270) +2022-11-14 14:13:38,011 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0774) Prec@1 88.000 (87.156) Prec@5 100.000 (99.278) +2022-11-14 14:13:38,023 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0773) Prec@1 90.000 (87.187) Prec@5 100.000 (99.286) +2022-11-14 14:13:38,033 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0771) Prec@1 91.000 (87.228) Prec@5 99.000 (99.283) +2022-11-14 14:13:38,042 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0774) Prec@1 82.000 (87.172) Prec@5 98.000 (99.269) +2022-11-14 14:13:38,052 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0772) Prec@1 92.000 (87.223) Prec@5 99.000 (99.266) +2022-11-14 14:13:38,061 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0771) Prec@1 87.000 (87.221) Prec@5 100.000 (99.274) +2022-11-14 14:13:38,070 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0771) Prec@1 86.000 (87.208) Prec@5 100.000 (99.281) +2022-11-14 14:13:38,079 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0768) Prec@1 92.000 (87.258) Prec@5 99.000 (99.278) +2022-11-14 14:13:38,089 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0769) Prec@1 88.000 (87.265) Prec@5 98.000 (99.265) +2022-11-14 14:13:38,099 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0771) Prec@1 85.000 (87.242) Prec@5 100.000 (99.273) +2022-11-14 14:13:38,110 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0771) Prec@1 87.000 (87.240) Prec@5 99.000 (99.270) +2022-11-14 14:13:38,177 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:13:38,688 Epoch: [166][0/500] Time 0.030 (0.030) Data 0.224 (0.224) Loss 0.0750 (0.0750) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 14:13:38,909 Epoch: [166][10/500] Time 0.016 (0.020) Data 0.002 (0.022) Loss 0.0604 (0.0677) Prec@1 92.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:13:39,122 Epoch: [166][20/500] Time 0.020 (0.020) Data 0.002 (0.012) Loss 0.0774 (0.0710) Prec@1 86.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:13:39,319 Epoch: [166][30/500] Time 0.018 (0.019) Data 0.002 (0.009) Loss 0.0337 (0.0616) Prec@1 93.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 14:13:39,522 Epoch: [166][40/500] Time 0.019 (0.019) Data 0.002 (0.007) Loss 0.0583 (0.0610) Prec@1 90.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 14:13:39,810 Epoch: [166][50/500] Time 0.035 (0.020) Data 0.002 (0.006) Loss 0.0386 (0.0572) Prec@1 93.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 14:13:40,238 Epoch: [166][60/500] Time 0.040 (0.023) Data 0.002 (0.005) Loss 0.0550 (0.0569) Prec@1 91.000 (89.857) Prec@5 100.000 (99.714) +2022-11-14 14:13:40,664 Epoch: [166][70/500] Time 0.037 (0.025) Data 0.002 (0.005) Loss 0.0677 (0.0583) Prec@1 90.000 (89.875) Prec@5 99.000 (99.625) +2022-11-14 14:13:41,102 Epoch: [166][80/500] Time 0.038 (0.027) Data 0.002 (0.005) Loss 0.0489 (0.0572) Prec@1 92.000 (90.111) Prec@5 100.000 (99.667) +2022-11-14 14:13:41,578 Epoch: [166][90/500] Time 0.073 (0.028) Data 0.002 (0.004) Loss 0.0451 (0.0560) Prec@1 92.000 (90.300) Prec@5 100.000 (99.700) +2022-11-14 14:13:42,013 Epoch: [166][100/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.0475 (0.0552) Prec@1 93.000 (90.545) Prec@5 100.000 (99.727) +2022-11-14 14:13:42,496 Epoch: [166][110/500] Time 0.029 (0.030) Data 0.002 (0.004) Loss 0.0598 (0.0556) Prec@1 89.000 (90.417) Prec@5 100.000 (99.750) +2022-11-14 14:13:42,909 Epoch: [166][120/500] Time 0.041 (0.031) Data 0.002 (0.004) Loss 0.0375 (0.0542) Prec@1 94.000 (90.692) Prec@5 100.000 (99.769) +2022-11-14 14:13:43,442 Epoch: [166][130/500] Time 0.052 (0.032) Data 0.002 (0.004) Loss 0.0626 (0.0548) Prec@1 87.000 (90.429) Prec@5 100.000 (99.786) +2022-11-14 14:13:43,866 Epoch: [166][140/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0582 (0.0550) Prec@1 90.000 (90.400) Prec@5 100.000 (99.800) +2022-11-14 14:13:44,287 Epoch: [166][150/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0490 (0.0547) Prec@1 91.000 (90.438) Prec@5 100.000 (99.812) +2022-11-14 14:13:44,708 Epoch: [166][160/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0569 (0.0548) Prec@1 89.000 (90.353) Prec@5 100.000 (99.824) +2022-11-14 14:13:45,124 Epoch: [166][170/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0457 (0.0543) Prec@1 93.000 (90.500) Prec@5 100.000 (99.833) +2022-11-14 14:13:45,608 Epoch: [166][180/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0595 (0.0546) Prec@1 90.000 (90.474) Prec@5 100.000 (99.842) +2022-11-14 14:13:46,031 Epoch: [166][190/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0325 (0.0535) Prec@1 96.000 (90.750) Prec@5 99.000 (99.800) +2022-11-14 14:13:46,452 Epoch: [166][200/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0713 (0.0543) Prec@1 88.000 (90.619) Prec@5 99.000 (99.762) +2022-11-14 14:13:46,888 Epoch: [166][210/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0430 (0.0538) Prec@1 91.000 (90.636) Prec@5 100.000 (99.773) +2022-11-14 14:13:47,351 Epoch: [166][220/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0378 (0.0531) Prec@1 94.000 (90.783) Prec@5 99.000 (99.739) +2022-11-14 14:13:47,772 Epoch: [166][230/500] Time 0.038 (0.035) Data 0.001 (0.003) Loss 0.0624 (0.0535) Prec@1 91.000 (90.792) Prec@5 96.000 (99.583) +2022-11-14 14:13:48,192 Epoch: [166][240/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0402 (0.0530) Prec@1 92.000 (90.840) Prec@5 100.000 (99.600) +2022-11-14 14:13:48,610 Epoch: [166][250/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0393 (0.0524) Prec@1 94.000 (90.962) Prec@5 99.000 (99.577) +2022-11-14 14:13:49,077 Epoch: [166][260/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0572 (0.0526) Prec@1 91.000 (90.963) Prec@5 99.000 (99.556) +2022-11-14 14:13:49,517 Epoch: [166][270/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0619 (0.0529) Prec@1 90.000 (90.929) Prec@5 99.000 (99.536) +2022-11-14 14:13:49,952 Epoch: [166][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0500 (0.0528) Prec@1 94.000 (91.034) Prec@5 99.000 (99.517) +2022-11-14 14:13:50,408 Epoch: [166][290/500] Time 0.042 (0.036) Data 0.001 (0.003) Loss 0.0550 (0.0529) Prec@1 93.000 (91.100) Prec@5 99.000 (99.500) +2022-11-14 14:13:50,855 Epoch: [166][300/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0420 (0.0526) Prec@1 94.000 (91.194) Prec@5 99.000 (99.484) +2022-11-14 14:13:51,324 Epoch: [166][310/500] Time 0.066 (0.036) Data 0.002 (0.003) Loss 0.0705 (0.0531) Prec@1 88.000 (91.094) Prec@5 99.000 (99.469) +2022-11-14 14:13:51,728 Epoch: [166][320/500] Time 0.039 (0.036) Data 0.001 (0.003) Loss 0.0383 (0.0527) Prec@1 93.000 (91.152) Prec@5 100.000 (99.485) +2022-11-14 14:13:52,188 Epoch: [166][330/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0505 (0.0526) Prec@1 92.000 (91.176) Prec@5 100.000 (99.500) +2022-11-14 14:13:52,645 Epoch: [166][340/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0541 (0.0526) Prec@1 92.000 (91.200) Prec@5 99.000 (99.486) +2022-11-14 14:13:53,097 Epoch: [166][350/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0610 (0.0529) Prec@1 90.000 (91.167) Prec@5 100.000 (99.500) +2022-11-14 14:13:53,552 Epoch: [166][360/500] Time 0.035 (0.037) Data 0.002 (0.002) Loss 0.0270 (0.0522) Prec@1 96.000 (91.297) Prec@5 100.000 (99.514) +2022-11-14 14:13:54,005 Epoch: [166][370/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0374 (0.0518) Prec@1 94.000 (91.368) Prec@5 100.000 (99.526) +2022-11-14 14:13:54,461 Epoch: [166][380/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.0392 (0.0515) Prec@1 93.000 (91.410) Prec@5 99.000 (99.513) +2022-11-14 14:13:54,934 Epoch: [166][390/500] Time 0.069 (0.037) Data 0.002 (0.002) Loss 0.0322 (0.0510) Prec@1 94.000 (91.475) Prec@5 100.000 (99.525) +2022-11-14 14:13:55,384 Epoch: [166][400/500] Time 0.074 (0.037) Data 0.002 (0.002) Loss 0.0383 (0.0507) Prec@1 95.000 (91.561) Prec@5 100.000 (99.537) +2022-11-14 14:13:55,805 Epoch: [166][410/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0516 (0.0507) Prec@1 92.000 (91.571) Prec@5 100.000 (99.548) +2022-11-14 14:13:56,207 Epoch: [166][420/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0312 (0.0502) Prec@1 95.000 (91.651) Prec@5 100.000 (99.558) +2022-11-14 14:13:56,668 Epoch: [166][430/500] Time 0.035 (0.037) Data 0.002 (0.002) Loss 0.0470 (0.0502) Prec@1 90.000 (91.614) Prec@5 100.000 (99.568) +2022-11-14 14:13:57,090 Epoch: [166][440/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0532 (0.0502) Prec@1 90.000 (91.578) Prec@5 100.000 (99.578) +2022-11-14 14:13:57,514 Epoch: [166][450/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0387 (0.0500) Prec@1 96.000 (91.674) Prec@5 100.000 (99.587) +2022-11-14 14:13:57,948 Epoch: [166][460/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0607 (0.0502) Prec@1 90.000 (91.638) Prec@5 99.000 (99.574) +2022-11-14 14:13:58,375 Epoch: [166][470/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0683 (0.0506) Prec@1 89.000 (91.583) Prec@5 100.000 (99.583) +2022-11-14 14:13:58,806 Epoch: [166][480/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0439 (0.0505) Prec@1 93.000 (91.612) Prec@5 100.000 (99.592) +2022-11-14 14:13:59,235 Epoch: [166][490/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0753 (0.0510) Prec@1 88.000 (91.540) Prec@5 100.000 (99.600) +2022-11-14 14:13:59,621 Epoch: [166][499/500] Time 0.049 (0.037) Data 0.002 (0.002) Loss 0.0603 (0.0511) Prec@1 88.000 (91.471) Prec@5 99.000 (99.588) +2022-11-14 14:13:59,901 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0804 (0.0804) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:13:59,911 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0729) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:13:59,920 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0786) Prec@1 84.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:13:59,931 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0801) Prec@1 89.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 14:13:59,938 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0782) Prec@1 86.000 (87.000) Prec@5 100.000 (99.800) +2022-11-14 14:13:59,945 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0735) Prec@1 91.000 (87.667) Prec@5 100.000 (99.833) +2022-11-14 14:13:59,952 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0721) Prec@1 90.000 (88.000) Prec@5 100.000 (99.857) +2022-11-14 14:13:59,961 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0720) Prec@1 84.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 14:13:59,969 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0724) Prec@1 88.000 (87.556) Prec@5 100.000 (99.778) +2022-11-14 14:13:59,978 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0729) Prec@1 86.000 (87.400) Prec@5 97.000 (99.500) +2022-11-14 14:13:59,986 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0724) Prec@1 89.000 (87.545) Prec@5 100.000 (99.545) +2022-11-14 14:13:59,996 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0744) Prec@1 84.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:14:00,005 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0298 (0.0710) Prec@1 96.000 (87.923) Prec@5 100.000 (99.538) +2022-11-14 14:14:00,016 Test: [13/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0717) Prec@1 84.000 (87.643) Prec@5 100.000 (99.571) +2022-11-14 14:14:00,025 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0717) Prec@1 87.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 14:14:00,035 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0712) Prec@1 92.000 (87.875) Prec@5 98.000 (99.500) +2022-11-14 14:14:00,044 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0703) Prec@1 92.000 (88.118) Prec@5 99.000 (99.471) +2022-11-14 14:14:00,053 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0727) Prec@1 83.000 (87.833) Prec@5 100.000 (99.500) +2022-11-14 14:14:00,063 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0726) Prec@1 89.000 (87.895) Prec@5 99.000 (99.474) +2022-11-14 14:14:00,072 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0730) Prec@1 89.000 (87.950) Prec@5 99.000 (99.450) +2022-11-14 14:14:00,081 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0739) Prec@1 85.000 (87.810) Prec@5 99.000 (99.429) +2022-11-14 14:14:00,090 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0750) Prec@1 82.000 (87.545) Prec@5 99.000 (99.409) +2022-11-14 14:14:00,100 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.0767) Prec@1 79.000 (87.174) Prec@5 97.000 (99.304) +2022-11-14 14:14:00,109 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0763) Prec@1 86.000 (87.125) Prec@5 100.000 (99.333) +2022-11-14 14:14:00,118 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0770) Prec@1 87.000 (87.120) Prec@5 100.000 (99.360) +2022-11-14 14:14:00,128 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0780) Prec@1 84.000 (87.000) Prec@5 98.000 (99.308) +2022-11-14 14:14:00,136 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0774) Prec@1 90.000 (87.111) Prec@5 100.000 (99.333) +2022-11-14 14:14:00,146 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0772) Prec@1 86.000 (87.071) Prec@5 99.000 (99.321) +2022-11-14 14:14:00,155 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0770) Prec@1 88.000 (87.103) Prec@5 100.000 (99.345) +2022-11-14 14:14:00,164 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0769) Prec@1 88.000 (87.133) Prec@5 100.000 (99.367) +2022-11-14 14:14:00,173 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0766) Prec@1 87.000 (87.129) Prec@5 100.000 (99.387) +2022-11-14 14:14:00,183 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0769) Prec@1 86.000 (87.094) Prec@5 99.000 (99.375) +2022-11-14 14:14:00,191 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0769) Prec@1 84.000 (87.000) Prec@5 98.000 (99.333) +2022-11-14 14:14:00,200 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0769) Prec@1 87.000 (87.000) Prec@5 100.000 (99.353) +2022-11-14 14:14:00,209 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0777) Prec@1 84.000 (86.914) Prec@5 98.000 (99.314) +2022-11-14 14:14:00,218 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0770) Prec@1 91.000 (87.028) Prec@5 100.000 (99.333) +2022-11-14 14:14:00,227 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0769) Prec@1 87.000 (87.027) Prec@5 99.000 (99.324) +2022-11-14 14:14:00,235 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0772) Prec@1 85.000 (86.974) Prec@5 100.000 (99.342) +2022-11-14 14:14:00,244 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0769) Prec@1 91.000 (87.077) Prec@5 99.000 (99.333) +2022-11-14 14:14:00,254 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0770) Prec@1 85.000 (87.025) Prec@5 98.000 (99.300) +2022-11-14 14:14:00,263 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0771) Prec@1 85.000 (86.976) Prec@5 98.000 (99.268) +2022-11-14 14:14:00,273 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0770) Prec@1 87.000 (86.976) Prec@5 100.000 (99.286) +2022-11-14 14:14:00,282 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0764) Prec@1 89.000 (87.023) Prec@5 99.000 (99.279) +2022-11-14 14:14:00,292 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0761) Prec@1 90.000 (87.091) Prec@5 99.000 (99.273) +2022-11-14 14:14:00,302 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0759) Prec@1 88.000 (87.111) Prec@5 100.000 (99.289) +2022-11-14 14:14:00,313 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0760) Prec@1 88.000 (87.130) Prec@5 100.000 (99.304) +2022-11-14 14:14:00,325 Test: [46/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0759) Prec@1 87.000 (87.128) Prec@5 100.000 (99.319) +2022-11-14 14:14:00,338 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1082 (0.0766) Prec@1 81.000 (87.000) Prec@5 98.000 (99.292) +2022-11-14 14:14:00,350 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0761) Prec@1 91.000 (87.082) Prec@5 100.000 (99.306) +2022-11-14 14:14:00,361 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.0768) Prec@1 83.000 (87.000) Prec@5 98.000 (99.280) +2022-11-14 14:14:00,372 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0770) Prec@1 86.000 (86.980) Prec@5 100.000 (99.294) +2022-11-14 14:14:00,384 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0772) Prec@1 85.000 (86.942) Prec@5 99.000 (99.288) +2022-11-14 14:14:00,396 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0769) Prec@1 89.000 (86.981) Prec@5 99.000 (99.283) +2022-11-14 14:14:00,407 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0769) Prec@1 90.000 (87.037) Prec@5 99.000 (99.278) +2022-11-14 14:14:00,419 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0773) Prec@1 83.000 (86.964) Prec@5 100.000 (99.291) +2022-11-14 14:14:00,430 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0772) Prec@1 90.000 (87.018) Prec@5 99.000 (99.286) +2022-11-14 14:14:00,442 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0770) Prec@1 89.000 (87.053) Prec@5 100.000 (99.298) +2022-11-14 14:14:00,452 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0767) Prec@1 90.000 (87.103) Prec@5 99.000 (99.293) +2022-11-14 14:14:00,463 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1219 (0.0775) Prec@1 78.000 (86.949) Prec@5 99.000 (99.288) +2022-11-14 14:14:00,474 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0773) Prec@1 88.000 (86.967) Prec@5 100.000 (99.300) +2022-11-14 14:14:00,484 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0777) Prec@1 84.000 (86.918) Prec@5 99.000 (99.295) +2022-11-14 14:14:00,497 Test: [61/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0775) Prec@1 89.000 (86.952) Prec@5 99.000 (99.290) +2022-11-14 14:14:00,511 Test: [62/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0772) Prec@1 90.000 (87.000) Prec@5 98.000 (99.270) +2022-11-14 14:14:00,521 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0409 (0.0766) Prec@1 93.000 (87.094) Prec@5 100.000 (99.281) +2022-11-14 14:14:00,531 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0771) Prec@1 85.000 (87.062) Prec@5 99.000 (99.277) +2022-11-14 14:14:00,540 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0772) Prec@1 86.000 (87.045) Prec@5 98.000 (99.258) +2022-11-14 14:14:00,550 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0768) Prec@1 92.000 (87.119) Prec@5 100.000 (99.269) +2022-11-14 14:14:00,562 Test: [67/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0767) Prec@1 88.000 (87.132) Prec@5 99.000 (99.265) +2022-11-14 14:14:00,571 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0767) Prec@1 87.000 (87.130) Prec@5 99.000 (99.261) +2022-11-14 14:14:00,581 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0767) Prec@1 87.000 (87.129) Prec@5 100.000 (99.271) +2022-11-14 14:14:00,590 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0768) Prec@1 89.000 (87.155) Prec@5 100.000 (99.282) +2022-11-14 14:14:00,600 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0766) Prec@1 88.000 (87.167) Prec@5 100.000 (99.292) +2022-11-14 14:14:00,608 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0396 (0.0761) Prec@1 94.000 (87.260) Prec@5 99.000 (99.288) +2022-11-14 14:14:00,617 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0757) Prec@1 93.000 (87.338) Prec@5 100.000 (99.297) +2022-11-14 14:14:00,627 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0762) Prec@1 83.000 (87.280) Prec@5 99.000 (99.293) +2022-11-14 14:14:00,636 Test: 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0.0808 (0.0758) Prec@1 83.000 (87.305) Prec@5 100.000 (99.280) +2022-11-14 14:14:00,700 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0762) Prec@1 83.000 (87.253) Prec@5 99.000 (99.277) +2022-11-14 14:14:00,709 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0760) Prec@1 89.000 (87.274) Prec@5 100.000 (99.286) +2022-11-14 14:14:00,718 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0760) Prec@1 89.000 (87.294) Prec@5 100.000 (99.294) +2022-11-14 14:14:00,727 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0764) Prec@1 81.000 (87.221) Prec@5 98.000 (99.279) +2022-11-14 14:14:00,736 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0762) Prec@1 91.000 (87.264) Prec@5 98.000 (99.264) +2022-11-14 14:14:00,746 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0762) Prec@1 86.000 (87.250) Prec@5 99.000 (99.261) +2022-11-14 14:14:00,755 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0763) Prec@1 86.000 (87.236) Prec@5 99.000 (99.258) +2022-11-14 14:14:00,764 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0764) Prec@1 86.000 (87.222) Prec@5 99.000 (99.256) +2022-11-14 14:14:00,773 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0763) Prec@1 88.000 (87.231) Prec@5 99.000 (99.253) +2022-11-14 14:14:00,782 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0761) Prec@1 92.000 (87.283) Prec@5 100.000 (99.261) +2022-11-14 14:14:00,792 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0761) Prec@1 86.000 (87.269) Prec@5 100.000 (99.269) +2022-11-14 14:14:00,801 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 88.000 (87.277) Prec@5 100.000 (99.277) +2022-11-14 14:14:00,813 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0760) Prec@1 86.000 (87.263) Prec@5 99.000 (99.274) +2022-11-14 14:14:00,824 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0759) Prec@1 90.000 (87.292) Prec@5 99.000 (99.271) +2022-11-14 14:14:00,835 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0756) Prec@1 93.000 (87.351) Prec@5 99.000 (99.268) +2022-11-14 14:14:00,846 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0759) Prec@1 83.000 (87.306) Prec@5 98.000 (99.255) +2022-11-14 14:14:00,858 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0761) Prec@1 83.000 (87.263) Prec@5 99.000 (99.253) +2022-11-14 14:14:00,870 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0760) Prec@1 91.000 (87.300) Prec@5 100.000 (99.260) +2022-11-14 14:14:00,931 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:14:01,566 Epoch: [167][0/500] Time 0.031 (0.031) Data 0.240 (0.240) Loss 0.0531 (0.0531) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:01,791 Epoch: [167][10/500] Time 0.024 (0.021) Data 0.002 (0.024) Loss 0.0527 (0.0529) Prec@1 92.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 14:14:02,004 Epoch: [167][20/500] Time 0.018 (0.020) Data 0.002 (0.013) Loss 0.0330 (0.0463) Prec@1 95.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:02,293 Epoch: [167][30/500] Time 0.033 (0.022) Data 0.002 (0.010) Loss 0.0256 (0.0411) Prec@1 96.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:02,611 Epoch: [167][40/500] Time 0.036 (0.023) Data 0.002 (0.008) Loss 0.0469 (0.0423) Prec@1 91.000 (92.600) Prec@5 100.000 (100.000) +2022-11-14 14:14:02,914 Epoch: [167][50/500] Time 0.027 (0.024) Data 0.002 (0.007) Loss 0.0437 (0.0425) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:14:03,217 Epoch: [167][60/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.0388 (0.0420) Prec@1 94.000 (92.714) Prec@5 100.000 (100.000) +2022-11-14 14:14:03,520 Epoch: [167][70/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0300 (0.0405) Prec@1 97.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 14:14:03,830 Epoch: [167][80/500] Time 0.029 (0.025) Data 0.002 (0.005) Loss 0.0374 (0.0401) Prec@1 93.000 (93.222) Prec@5 99.000 (99.889) +2022-11-14 14:14:04,134 Epoch: [167][90/500] Time 0.027 (0.025) Data 0.002 (0.005) Loss 0.0308 (0.0392) Prec@1 95.000 (93.400) Prec@5 100.000 (99.900) +2022-11-14 14:14:04,441 Epoch: [167][100/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0793 (0.0428) Prec@1 88.000 (92.909) Prec@5 99.000 (99.818) +2022-11-14 14:14:04,753 Epoch: [167][110/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.0363 (0.0423) Prec@1 94.000 (93.000) Prec@5 99.000 (99.750) +2022-11-14 14:14:05,062 Epoch: [167][120/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.0553 (0.0433) Prec@1 89.000 (92.692) Prec@5 100.000 (99.769) +2022-11-14 14:14:05,371 Epoch: [167][130/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0511 (0.0438) Prec@1 92.000 (92.643) Prec@5 99.000 (99.714) +2022-11-14 14:14:05,677 Epoch: [167][140/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.0426 (0.0438) Prec@1 94.000 (92.733) Prec@5 99.000 (99.667) +2022-11-14 14:14:05,985 Epoch: [167][150/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0347 (0.0432) Prec@1 97.000 (93.000) Prec@5 100.000 (99.688) +2022-11-14 14:14:06,390 Epoch: [167][160/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0292 (0.0424) Prec@1 97.000 (93.235) Prec@5 99.000 (99.647) +2022-11-14 14:14:06,870 Epoch: [167][170/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0342 (0.0419) Prec@1 93.000 (93.222) Prec@5 99.000 (99.611) +2022-11-14 14:14:07,405 Epoch: [167][180/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0213 (0.0408) Prec@1 96.000 (93.368) Prec@5 100.000 (99.632) +2022-11-14 14:14:07,941 Epoch: [167][190/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0598 (0.0418) Prec@1 91.000 (93.250) Prec@5 99.000 (99.600) +2022-11-14 14:14:08,468 Epoch: [167][200/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0521 (0.0423) Prec@1 92.000 (93.190) Prec@5 100.000 (99.619) +2022-11-14 14:14:09,026 Epoch: [167][210/500] Time 0.044 (0.032) Data 0.003 (0.003) Loss 0.0388 (0.0421) Prec@1 94.000 (93.227) Prec@5 100.000 (99.636) +2022-11-14 14:14:09,559 Epoch: [167][220/500] Time 0.094 (0.032) Data 0.002 (0.003) Loss 0.0613 (0.0429) Prec@1 90.000 (93.087) Prec@5 99.000 (99.609) +2022-11-14 14:14:10,019 Epoch: [167][230/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0516 (0.0433) Prec@1 89.000 (92.917) Prec@5 99.000 (99.583) +2022-11-14 14:14:10,622 Epoch: [167][240/500] Time 0.052 (0.034) Data 0.002 (0.003) Loss 0.0470 (0.0435) Prec@1 90.000 (92.800) Prec@5 100.000 (99.600) +2022-11-14 14:14:11,118 Epoch: [167][250/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0375 (0.0432) Prec@1 92.000 (92.769) Prec@5 100.000 (99.615) +2022-11-14 14:14:11,649 Epoch: [167][260/500] Time 0.062 (0.034) Data 0.002 (0.003) Loss 0.0484 (0.0434) Prec@1 92.000 (92.741) Prec@5 100.000 (99.630) +2022-11-14 14:14:12,259 Epoch: [167][270/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0533 (0.0438) Prec@1 91.000 (92.679) Prec@5 99.000 (99.607) +2022-11-14 14:14:12,801 Epoch: [167][280/500] Time 0.052 (0.036) Data 0.002 (0.003) Loss 0.0482 (0.0439) Prec@1 91.000 (92.621) Prec@5 100.000 (99.621) +2022-11-14 14:14:13,399 Epoch: [167][290/500] Time 0.076 (0.036) Data 0.002 (0.003) Loss 0.0446 (0.0439) Prec@1 92.000 (92.600) Prec@5 100.000 (99.633) +2022-11-14 14:14:13,967 Epoch: [167][300/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.0402 (0.0438) Prec@1 94.000 (92.645) Prec@5 100.000 (99.645) +2022-11-14 14:14:14,537 Epoch: [167][310/500] Time 0.058 (0.037) Data 0.002 (0.003) Loss 0.0528 (0.0441) Prec@1 92.000 (92.625) Prec@5 100.000 (99.656) +2022-11-14 14:14:15,066 Epoch: [167][320/500] Time 0.064 (0.038) Data 0.002 (0.003) Loss 0.0538 (0.0444) Prec@1 92.000 (92.606) Prec@5 98.000 (99.606) +2022-11-14 14:14:15,611 Epoch: [167][330/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0640 (0.0450) Prec@1 88.000 (92.471) Prec@5 100.000 (99.618) +2022-11-14 14:14:16,121 Epoch: [167][340/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0469 (0.0450) Prec@1 92.000 (92.457) Prec@5 100.000 (99.629) +2022-11-14 14:14:16,698 Epoch: [167][350/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.0392 (0.0449) Prec@1 94.000 (92.500) Prec@5 98.000 (99.583) +2022-11-14 14:14:17,231 Epoch: [167][360/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0372 (0.0447) Prec@1 93.000 (92.514) Prec@5 100.000 (99.595) +2022-11-14 14:14:17,766 Epoch: [167][370/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0477 (0.0447) Prec@1 89.000 (92.421) Prec@5 100.000 (99.605) +2022-11-14 14:14:18,350 Epoch: [167][380/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0467 (0.0448) Prec@1 93.000 (92.436) Prec@5 100.000 (99.615) +2022-11-14 14:14:18,960 Epoch: [167][390/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0392 (0.0446) Prec@1 95.000 (92.500) Prec@5 99.000 (99.600) +2022-11-14 14:14:19,487 Epoch: [167][400/500] Time 0.078 (0.040) Data 0.002 (0.003) Loss 0.0532 (0.0449) Prec@1 93.000 (92.512) Prec@5 100.000 (99.610) +2022-11-14 14:14:20,011 Epoch: [167][410/500] Time 0.099 (0.040) Data 0.002 (0.002) Loss 0.0538 (0.0451) Prec@1 91.000 (92.476) Prec@5 99.000 (99.595) +2022-11-14 14:14:20,540 Epoch: [167][420/500] Time 0.078 (0.040) Data 0.002 (0.002) Loss 0.0674 (0.0456) Prec@1 90.000 (92.419) Prec@5 99.000 (99.581) +2022-11-14 14:14:21,062 Epoch: [167][430/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0351 (0.0454) Prec@1 93.000 (92.432) Prec@5 100.000 (99.591) +2022-11-14 14:14:21,594 Epoch: [167][440/500] Time 0.035 (0.040) Data 0.002 (0.002) Loss 0.0671 (0.0458) Prec@1 88.000 (92.333) Prec@5 97.000 (99.533) +2022-11-14 14:14:22,146 Epoch: [167][450/500] Time 0.039 (0.041) Data 0.002 (0.002) Loss 0.0450 (0.0458) Prec@1 94.000 (92.370) Prec@5 100.000 (99.543) +2022-11-14 14:14:22,722 Epoch: [167][460/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0445 (0.0458) Prec@1 92.000 (92.362) Prec@5 100.000 (99.553) +2022-11-14 14:14:23,247 Epoch: [167][470/500] Time 0.043 (0.041) Data 0.001 (0.002) Loss 0.0678 (0.0463) Prec@1 87.000 (92.250) Prec@5 100.000 (99.562) +2022-11-14 14:14:23,784 Epoch: [167][480/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0492 (0.0463) Prec@1 92.000 (92.245) Prec@5 100.000 (99.571) +2022-11-14 14:14:24,317 Epoch: [167][490/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0698 (0.0468) Prec@1 88.000 (92.160) Prec@5 100.000 (99.580) +2022-11-14 14:14:24,801 Epoch: [167][499/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0379 (0.0466) Prec@1 93.000 (92.176) Prec@5 99.000 (99.569) +2022-11-14 14:14:25,097 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0544 (0.0544) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:25,105 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0623) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:25,114 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0716) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:25,128 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0745) Prec@1 88.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:14:25,138 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0759) Prec@1 89.000 (88.200) Prec@5 99.000 (99.600) +2022-11-14 14:14:25,148 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0377 (0.0695) Prec@1 94.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 14:14:25,158 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0670) Prec@1 93.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 14:14:25,170 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0707) Prec@1 83.000 (88.875) Prec@5 100.000 (99.750) +2022-11-14 14:14:25,181 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0722) Prec@1 86.000 (88.556) Prec@5 100.000 (99.778) +2022-11-14 14:14:25,191 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0722) Prec@1 89.000 (88.600) Prec@5 99.000 (99.700) +2022-11-14 14:14:25,203 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0721) Prec@1 88.000 (88.545) Prec@5 99.000 (99.636) +2022-11-14 14:14:25,214 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0725) Prec@1 87.000 (88.417) Prec@5 99.000 (99.583) +2022-11-14 14:14:25,225 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0702) Prec@1 94.000 (88.846) Prec@5 100.000 (99.615) +2022-11-14 14:14:25,236 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0704) Prec@1 87.000 (88.714) Prec@5 100.000 (99.643) +2022-11-14 14:14:25,248 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0704) Prec@1 87.000 (88.600) Prec@5 100.000 (99.667) +2022-11-14 14:14:25,260 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0705) Prec@1 88.000 (88.562) Prec@5 100.000 (99.688) +2022-11-14 14:14:25,273 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0690) Prec@1 93.000 (88.824) Prec@5 98.000 (99.588) +2022-11-14 14:14:25,286 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0705) Prec@1 85.000 (88.611) Prec@5 100.000 (99.611) +2022-11-14 14:14:25,297 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0715) Prec@1 83.000 (88.316) Prec@5 98.000 (99.526) +2022-11-14 14:14:25,308 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0721) Prec@1 85.000 (88.150) Prec@5 99.000 (99.500) +2022-11-14 14:14:25,319 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0728) Prec@1 85.000 (88.000) Prec@5 99.000 (99.476) +2022-11-14 14:14:25,332 Test: [21/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0733) Prec@1 85.000 (87.864) Prec@5 99.000 (99.455) +2022-11-14 14:14:25,344 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0745) Prec@1 84.000 (87.696) Prec@5 98.000 (99.391) +2022-11-14 14:14:25,357 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0747) Prec@1 87.000 (87.667) Prec@5 100.000 (99.417) +2022-11-14 14:14:25,369 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0745) Prec@1 88.000 (87.680) Prec@5 100.000 (99.440) +2022-11-14 14:14:25,382 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0751) Prec@1 87.000 (87.654) Prec@5 97.000 (99.346) +2022-11-14 14:14:25,395 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0743) Prec@1 92.000 (87.815) Prec@5 100.000 (99.370) +2022-11-14 14:14:25,408 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0736) Prec@1 91.000 (87.929) Prec@5 99.000 (99.357) +2022-11-14 14:14:25,420 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0736) Prec@1 88.000 (87.931) Prec@5 99.000 (99.345) +2022-11-14 14:14:25,433 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0733) Prec@1 90.000 (88.000) Prec@5 100.000 (99.367) +2022-11-14 14:14:25,444 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0729) Prec@1 89.000 (88.032) Prec@5 100.000 (99.387) +2022-11-14 14:14:25,458 Test: [31/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0735) Prec@1 84.000 (87.906) Prec@5 99.000 (99.375) +2022-11-14 14:14:25,472 Test: [32/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0736) Prec@1 87.000 (87.879) Prec@5 100.000 (99.394) +2022-11-14 14:14:25,485 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0738) Prec@1 85.000 (87.794) Prec@5 100.000 (99.412) +2022-11-14 14:14:25,497 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0741) Prec@1 87.000 (87.771) Prec@5 98.000 (99.371) +2022-11-14 14:14:25,509 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0740) Prec@1 89.000 (87.806) Prec@5 99.000 (99.361) +2022-11-14 14:14:25,521 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0738) Prec@1 89.000 (87.838) Prec@5 100.000 (99.378) +2022-11-14 14:14:25,533 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0744) Prec@1 82.000 (87.684) Prec@5 99.000 (99.368) +2022-11-14 14:14:25,543 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0739) Prec@1 93.000 (87.821) Prec@5 99.000 (99.359) +2022-11-14 14:14:25,553 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0736) Prec@1 89.000 (87.850) Prec@5 98.000 (99.325) +2022-11-14 14:14:25,563 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0742) Prec@1 82.000 (87.707) Prec@5 98.000 (99.293) +2022-11-14 14:14:25,572 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0743) Prec@1 86.000 (87.667) Prec@5 99.000 (99.286) +2022-11-14 14:14:25,581 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0738) Prec@1 91.000 (87.744) Prec@5 99.000 (99.279) +2022-11-14 14:14:25,590 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0738) Prec@1 87.000 (87.727) Prec@5 97.000 (99.227) +2022-11-14 14:14:25,602 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0736) Prec@1 89.000 (87.756) Prec@5 99.000 (99.222) +2022-11-14 14:14:25,612 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0743) Prec@1 82.000 (87.630) Prec@5 99.000 (99.217) +2022-11-14 14:14:25,620 Test: [46/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0746) Prec@1 85.000 (87.574) Prec@5 100.000 (99.234) +2022-11-14 14:14:25,629 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.0754) Prec@1 83.000 (87.479) Prec@5 100.000 (99.250) +2022-11-14 14:14:25,641 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0749) Prec@1 92.000 (87.571) Prec@5 100.000 (99.265) +2022-11-14 14:14:25,651 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0755) Prec@1 84.000 (87.500) Prec@5 100.000 (99.280) +2022-11-14 14:14:25,661 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0754) Prec@1 87.000 (87.490) Prec@5 100.000 (99.294) +2022-11-14 14:14:25,669 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0756) Prec@1 87.000 (87.481) Prec@5 100.000 (99.308) +2022-11-14 14:14:25,680 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0757) Prec@1 88.000 (87.491) Prec@5 99.000 (99.302) +2022-11-14 14:14:25,691 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0757) Prec@1 87.000 (87.481) Prec@5 99.000 (99.296) +2022-11-14 14:14:25,700 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0760) Prec@1 83.000 (87.400) Prec@5 100.000 (99.309) +2022-11-14 14:14:25,710 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0758) Prec@1 88.000 (87.411) Prec@5 98.000 (99.286) +2022-11-14 14:14:25,723 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0757) Prec@1 88.000 (87.421) Prec@5 100.000 (99.298) +2022-11-14 14:14:25,734 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0754) Prec@1 91.000 (87.483) Prec@5 100.000 (99.310) +2022-11-14 14:14:25,743 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0759) Prec@1 83.000 (87.407) Prec@5 99.000 (99.305) +2022-11-14 14:14:25,752 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0758) Prec@1 88.000 (87.417) Prec@5 100.000 (99.317) +2022-11-14 14:14:25,764 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0764) Prec@1 80.000 (87.295) Prec@5 100.000 (99.328) +2022-11-14 14:14:25,775 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0765) Prec@1 84.000 (87.242) Prec@5 98.000 (99.306) +2022-11-14 14:14:25,785 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0761) Prec@1 91.000 (87.302) Prec@5 100.000 (99.317) +2022-11-14 14:14:25,794 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0443 (0.0756) Prec@1 92.000 (87.375) Prec@5 100.000 (99.328) +2022-11-14 14:14:25,806 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0760) Prec@1 86.000 (87.354) Prec@5 99.000 (99.323) +2022-11-14 14:14:25,817 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0764) Prec@1 81.000 (87.258) Prec@5 99.000 (99.318) +2022-11-14 14:14:25,827 Test: [66/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0759) Prec@1 91.000 (87.313) Prec@5 99.000 (99.313) +2022-11-14 14:14:25,835 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0763) Prec@1 84.000 (87.265) Prec@5 98.000 (99.294) +2022-11-14 14:14:25,845 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0762) Prec@1 89.000 (87.290) Prec@5 100.000 (99.304) +2022-11-14 14:14:25,855 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0763) Prec@1 88.000 (87.300) Prec@5 98.000 (99.286) +2022-11-14 14:14:25,865 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0763) Prec@1 88.000 (87.310) Prec@5 99.000 (99.282) +2022-11-14 14:14:25,877 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0413 (0.0758) Prec@1 94.000 (87.403) Prec@5 100.000 (99.292) +2022-11-14 14:14:25,889 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0486 (0.0754) Prec@1 94.000 (87.493) Prec@5 99.000 (99.288) +2022-11-14 14:14:25,902 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0750) Prec@1 90.000 (87.527) Prec@5 100.000 (99.297) +2022-11-14 14:14:25,914 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0755) Prec@1 81.000 (87.440) Prec@5 99.000 (99.293) +2022-11-14 14:14:25,925 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0753) Prec@1 90.000 (87.474) Prec@5 100.000 (99.303) +2022-11-14 14:14:25,936 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0751) Prec@1 88.000 (87.481) Prec@5 100.000 (99.312) +2022-11-14 14:14:25,948 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0751) Prec@1 89.000 (87.500) Prec@5 97.000 (99.282) +2022-11-14 14:14:25,960 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0751) Prec@1 88.000 (87.506) Prec@5 100.000 (99.291) +2022-11-14 14:14:25,972 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0753) Prec@1 84.000 (87.463) Prec@5 99.000 (99.287) +2022-11-14 14:14:25,985 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0753) Prec@1 88.000 (87.469) Prec@5 99.000 (99.284) +2022-11-14 14:14:25,996 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0754) Prec@1 86.000 (87.451) Prec@5 99.000 (99.280) +2022-11-14 14:14:26,007 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0754) Prec@1 85.000 (87.422) Prec@5 99.000 (99.277) +2022-11-14 14:14:26,019 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0753) Prec@1 89.000 (87.440) Prec@5 99.000 (99.274) +2022-11-14 14:14:26,029 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0754) Prec@1 86.000 (87.424) Prec@5 99.000 (99.271) +2022-11-14 14:14:26,040 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0758) Prec@1 82.000 (87.360) Prec@5 99.000 (99.267) +2022-11-14 14:14:26,051 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0755) Prec@1 91.000 (87.402) Prec@5 99.000 (99.264) +2022-11-14 14:14:26,064 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0755) Prec@1 87.000 (87.398) Prec@5 99.000 (99.261) +2022-11-14 14:14:26,074 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0755) Prec@1 88.000 (87.404) Prec@5 99.000 (99.258) +2022-11-14 14:14:26,084 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0756) Prec@1 90.000 (87.433) Prec@5 99.000 (99.256) +2022-11-14 14:14:26,093 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0754) Prec@1 90.000 (87.462) Prec@5 99.000 (99.253) +2022-11-14 14:14:26,103 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0753) Prec@1 90.000 (87.489) Prec@5 99.000 (99.250) +2022-11-14 14:14:26,113 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0755) Prec@1 84.000 (87.452) Prec@5 100.000 (99.258) +2022-11-14 14:14:26,122 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0755) Prec@1 90.000 (87.479) Prec@5 99.000 (99.255) +2022-11-14 14:14:26,132 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0757) Prec@1 84.000 (87.442) Prec@5 99.000 (99.253) +2022-11-14 14:14:26,141 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0756) Prec@1 89.000 (87.458) Prec@5 100.000 (99.260) +2022-11-14 14:14:26,150 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0754) Prec@1 91.000 (87.495) Prec@5 98.000 (99.247) +2022-11-14 14:14:26,160 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0754) Prec@1 87.000 (87.490) Prec@5 99.000 (99.245) +2022-11-14 14:14:26,169 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0756) Prec@1 85.000 (87.465) Prec@5 100.000 (99.253) +2022-11-14 14:14:26,177 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0755) Prec@1 87.000 (87.460) Prec@5 100.000 (99.260) +2022-11-14 14:14:26,237 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:14:26,596 Epoch: [168][0/500] Time 0.032 (0.032) Data 0.227 (0.227) Loss 0.0258 (0.0258) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:26,818 Epoch: [168][10/500] Time 0.018 (0.021) Data 0.002 (0.022) Loss 0.0546 (0.0402) Prec@1 90.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:27,072 Epoch: [168][20/500] Time 0.019 (0.022) Data 0.001 (0.012) Loss 0.0358 (0.0387) Prec@1 92.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:14:27,287 Epoch: [168][30/500] Time 0.022 (0.021) Data 0.002 (0.009) Loss 0.0506 (0.0417) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:14:27,678 Epoch: [168][40/500] Time 0.035 (0.024) Data 0.002 (0.007) Loss 0.0641 (0.0462) Prec@1 90.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:28,161 Epoch: [168][50/500] Time 0.038 (0.028) Data 0.002 (0.006) Loss 0.0704 (0.0502) Prec@1 87.000 (91.167) Prec@5 100.000 (100.000) +2022-11-14 14:14:28,697 Epoch: [168][60/500] Time 0.033 (0.031) Data 0.002 (0.006) Loss 0.0527 (0.0506) Prec@1 93.000 (91.429) Prec@5 100.000 (100.000) +2022-11-14 14:14:29,143 Epoch: [168][70/500] Time 0.041 (0.033) Data 0.002 (0.005) Loss 0.0322 (0.0483) Prec@1 95.000 (91.875) Prec@5 99.000 (99.875) +2022-11-14 14:14:29,607 Epoch: [168][80/500] Time 0.044 (0.034) Data 0.001 (0.005) Loss 0.0476 (0.0482) Prec@1 91.000 (91.778) Prec@5 100.000 (99.889) +2022-11-14 14:14:30,040 Epoch: [168][90/500] Time 0.040 (0.034) Data 0.002 (0.004) Loss 0.0305 (0.0464) Prec@1 94.000 (92.000) Prec@5 100.000 (99.900) +2022-11-14 14:14:30,580 Epoch: [168][100/500] Time 0.066 (0.036) Data 0.002 (0.004) Loss 0.0261 (0.0446) Prec@1 97.000 (92.455) Prec@5 100.000 (99.909) +2022-11-14 14:14:31,136 Epoch: [168][110/500] Time 0.051 (0.037) Data 0.002 (0.004) Loss 0.0506 (0.0451) Prec@1 90.000 (92.250) Prec@5 100.000 (99.917) +2022-11-14 14:14:31,602 Epoch: [168][120/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0359 (0.0444) Prec@1 95.000 (92.462) Prec@5 99.000 (99.846) +2022-11-14 14:14:32,053 Epoch: [168][130/500] Time 0.049 (0.037) Data 0.002 (0.004) Loss 0.0544 (0.0451) Prec@1 91.000 (92.357) Prec@5 100.000 (99.857) +2022-11-14 14:14:32,511 Epoch: [168][140/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0382 (0.0446) Prec@1 95.000 (92.533) Prec@5 100.000 (99.867) +2022-11-14 14:14:32,974 Epoch: [168][150/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0560 (0.0453) Prec@1 91.000 (92.438) Prec@5 100.000 (99.875) +2022-11-14 14:14:33,419 Epoch: [168][160/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0356 (0.0448) Prec@1 95.000 (92.588) Prec@5 99.000 (99.824) +2022-11-14 14:14:33,870 Epoch: [168][170/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0439 (0.0447) Prec@1 93.000 (92.611) Prec@5 100.000 (99.833) +2022-11-14 14:14:34,319 Epoch: [168][180/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0302 (0.0440) Prec@1 96.000 (92.789) Prec@5 100.000 (99.842) +2022-11-14 14:14:34,771 Epoch: [168][190/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0291 (0.0432) Prec@1 95.000 (92.900) Prec@5 100.000 (99.850) +2022-11-14 14:14:35,219 Epoch: [168][200/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0492 (0.0435) Prec@1 93.000 (92.905) Prec@5 100.000 (99.857) +2022-11-14 14:14:35,670 Epoch: [168][210/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0584 (0.0442) Prec@1 91.000 (92.818) Prec@5 100.000 (99.864) +2022-11-14 14:14:36,129 Epoch: [168][220/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0536 (0.0446) Prec@1 90.000 (92.696) Prec@5 99.000 (99.826) +2022-11-14 14:14:36,579 Epoch: [168][230/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0562 (0.0451) Prec@1 92.000 (92.667) Prec@5 99.000 (99.792) +2022-11-14 14:14:37,029 Epoch: [168][240/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0383 (0.0448) Prec@1 95.000 (92.760) Prec@5 100.000 (99.800) +2022-11-14 14:14:37,489 Epoch: [168][250/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0500 (0.0450) Prec@1 91.000 (92.692) Prec@5 99.000 (99.769) +2022-11-14 14:14:37,944 Epoch: [168][260/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.0533 (0.0453) Prec@1 91.000 (92.630) Prec@5 100.000 (99.778) +2022-11-14 14:14:38,386 Epoch: [168][270/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0398 (0.0451) Prec@1 94.000 (92.679) Prec@5 100.000 (99.786) +2022-11-14 14:14:38,851 Epoch: [168][280/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0457 (0.0451) Prec@1 91.000 (92.621) Prec@5 100.000 (99.793) +2022-11-14 14:14:39,285 Epoch: [168][290/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0235 (0.0444) Prec@1 97.000 (92.767) Prec@5 100.000 (99.800) +2022-11-14 14:14:39,735 Epoch: [168][300/500] Time 0.044 (0.039) Data 0.001 (0.003) Loss 0.0583 (0.0449) Prec@1 89.000 (92.645) Prec@5 100.000 (99.806) +2022-11-14 14:14:40,179 Epoch: [168][310/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0171 (0.0440) Prec@1 98.000 (92.812) Prec@5 100.000 (99.812) +2022-11-14 14:14:40,624 Epoch: [168][320/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0257 (0.0434) Prec@1 97.000 (92.939) Prec@5 100.000 (99.818) +2022-11-14 14:14:41,108 Epoch: [168][330/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0350 (0.0432) Prec@1 95.000 (93.000) Prec@5 100.000 (99.824) +2022-11-14 14:14:41,542 Epoch: [168][340/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0569 (0.0436) Prec@1 91.000 (92.943) Prec@5 100.000 (99.829) +2022-11-14 14:14:42,028 Epoch: [168][350/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0724 (0.0444) Prec@1 88.000 (92.806) Prec@5 100.000 (99.833) +2022-11-14 14:14:42,519 Epoch: [168][360/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0310 (0.0440) Prec@1 94.000 (92.838) Prec@5 100.000 (99.838) +2022-11-14 14:14:43,069 Epoch: [168][370/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0486 (0.0441) Prec@1 93.000 (92.842) Prec@5 99.000 (99.816) +2022-11-14 14:14:43,549 Epoch: [168][380/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0480 (0.0442) Prec@1 91.000 (92.795) Prec@5 100.000 (99.821) +2022-11-14 14:14:44,034 Epoch: [168][390/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0371 (0.0441) Prec@1 94.000 (92.825) Prec@5 100.000 (99.825) +2022-11-14 14:14:44,511 Epoch: [168][400/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0302 (0.0437) Prec@1 96.000 (92.902) Prec@5 100.000 (99.829) +2022-11-14 14:14:44,968 Epoch: [168][410/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0508 (0.0439) Prec@1 92.000 (92.881) Prec@5 100.000 (99.833) +2022-11-14 14:14:45,456 Epoch: [168][420/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.0344 (0.0437) Prec@1 97.000 (92.977) Prec@5 100.000 (99.837) +2022-11-14 14:14:45,933 Epoch: [168][430/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0356 (0.0435) Prec@1 94.000 (93.000) Prec@5 100.000 (99.841) +2022-11-14 14:14:46,382 Epoch: [168][440/500] Time 0.039 (0.040) Data 0.002 (0.002) Loss 0.0341 (0.0433) Prec@1 94.000 (93.022) Prec@5 100.000 (99.844) +2022-11-14 14:14:46,843 Epoch: [168][450/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.0580 (0.0436) Prec@1 91.000 (92.978) Prec@5 98.000 (99.804) +2022-11-14 14:14:47,283 Epoch: [168][460/500] Time 0.045 (0.040) Data 0.002 (0.002) Loss 0.0288 (0.0433) Prec@1 94.000 (93.000) Prec@5 100.000 (99.809) +2022-11-14 14:14:47,734 Epoch: [168][470/500] Time 0.040 (0.040) Data 0.002 (0.002) Loss 0.0339 (0.0431) Prec@1 94.000 (93.021) Prec@5 99.000 (99.792) +2022-11-14 14:14:48,182 Epoch: [168][480/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0357 (0.0429) Prec@1 95.000 (93.061) Prec@5 100.000 (99.796) +2022-11-14 14:14:48,644 Epoch: [168][490/500] Time 0.045 (0.040) Data 0.003 (0.002) Loss 0.0555 (0.0432) Prec@1 91.000 (93.020) Prec@5 99.000 (99.780) +2022-11-14 14:14:49,047 Epoch: [168][499/500] Time 0.054 (0.040) Data 0.002 (0.002) Loss 0.0524 (0.0434) Prec@1 90.000 (92.961) Prec@5 100.000 (99.784) +2022-11-14 14:14:49,336 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0495 (0.0495) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:14:49,346 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0601) Prec@1 88.000 (90.000) Prec@5 98.000 (98.500) +2022-11-14 14:14:49,356 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0656) Prec@1 85.000 (88.333) Prec@5 100.000 (99.000) +2022-11-14 14:14:49,369 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0696) Prec@1 86.000 (87.750) Prec@5 100.000 (99.250) +2022-11-14 14:14:49,377 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0701) Prec@1 86.000 (87.400) Prec@5 100.000 (99.400) +2022-11-14 14:14:49,385 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0661) Prec@1 93.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 14:14:49,393 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0697) Prec@1 84.000 (87.714) Prec@5 100.000 (99.571) +2022-11-14 14:14:49,404 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0710) Prec@1 84.000 (87.250) Prec@5 100.000 (99.625) +2022-11-14 14:14:49,413 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0724) Prec@1 85.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:14:49,421 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0716) Prec@1 89.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 14:14:49,430 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0711) Prec@1 90.000 (87.455) Prec@5 100.000 (99.636) +2022-11-14 14:14:49,440 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0714) Prec@1 88.000 (87.500) Prec@5 100.000 (99.667) +2022-11-14 14:14:49,449 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0690) Prec@1 93.000 (87.923) Prec@5 100.000 (99.692) +2022-11-14 14:14:49,459 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0701) Prec@1 86.000 (87.786) Prec@5 100.000 (99.714) +2022-11-14 14:14:49,469 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0700) Prec@1 88.000 (87.800) Prec@5 100.000 (99.733) +2022-11-14 14:14:49,480 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0709) Prec@1 84.000 (87.562) Prec@5 100.000 (99.750) +2022-11-14 14:14:49,491 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0707) Prec@1 89.000 (87.647) Prec@5 98.000 (99.647) +2022-11-14 14:14:49,500 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0720) Prec@1 87.000 (87.611) Prec@5 100.000 (99.667) +2022-11-14 14:14:49,511 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0719) Prec@1 88.000 (87.632) Prec@5 100.000 (99.684) +2022-11-14 14:14:49,521 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0729) Prec@1 86.000 (87.550) Prec@5 97.000 (99.550) +2022-11-14 14:14:49,530 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0735) Prec@1 85.000 (87.429) Prec@5 100.000 (99.571) +2022-11-14 14:14:49,540 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0737) Prec@1 88.000 (87.455) Prec@5 99.000 (99.545) +2022-11-14 14:14:49,550 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0743) Prec@1 86.000 (87.391) Prec@5 99.000 (99.522) +2022-11-14 14:14:49,561 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0741) Prec@1 85.000 (87.292) Prec@5 100.000 (99.542) +2022-11-14 14:14:49,571 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0744) Prec@1 88.000 (87.320) Prec@5 100.000 (99.560) +2022-11-14 14:14:49,581 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0752) Prec@1 84.000 (87.192) Prec@5 99.000 (99.538) +2022-11-14 14:14:49,591 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0742) Prec@1 93.000 (87.407) Prec@5 100.000 (99.556) +2022-11-14 14:14:49,602 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0734) Prec@1 92.000 (87.571) Prec@5 100.000 (99.571) +2022-11-14 14:14:49,612 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0731) Prec@1 88.000 (87.586) Prec@5 99.000 (99.552) +2022-11-14 14:14:49,622 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0730) Prec@1 87.000 (87.567) Prec@5 100.000 (99.567) +2022-11-14 14:14:49,631 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0726) Prec@1 89.000 (87.613) Prec@5 100.000 (99.581) +2022-11-14 14:14:49,641 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0727) Prec@1 88.000 (87.625) Prec@5 99.000 (99.562) +2022-11-14 14:14:49,650 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0728) Prec@1 87.000 (87.606) Prec@5 99.000 (99.545) +2022-11-14 14:14:49,659 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0729) Prec@1 87.000 (87.588) Prec@5 100.000 (99.559) +2022-11-14 14:14:49,669 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0737) Prec@1 83.000 (87.457) Prec@5 99.000 (99.543) +2022-11-14 14:14:49,678 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0732) Prec@1 90.000 (87.528) Prec@5 99.000 (99.528) +2022-11-14 14:14:49,688 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0733) Prec@1 85.000 (87.459) Prec@5 98.000 (99.486) +2022-11-14 14:14:49,698 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1231 (0.0746) Prec@1 80.000 (87.263) Prec@5 99.000 (99.474) +2022-11-14 14:14:49,707 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0739) Prec@1 94.000 (87.436) Prec@5 100.000 (99.487) +2022-11-14 14:14:49,716 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0736) Prec@1 90.000 (87.500) Prec@5 99.000 (99.475) +2022-11-14 14:14:49,725 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0740) Prec@1 87.000 (87.488) Prec@5 97.000 (99.415) +2022-11-14 14:14:49,735 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0737) Prec@1 91.000 (87.571) Prec@5 99.000 (99.405) +2022-11-14 14:14:49,745 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0731) Prec@1 93.000 (87.698) Prec@5 100.000 (99.419) +2022-11-14 14:14:49,754 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0731) Prec@1 90.000 (87.750) Prec@5 98.000 (99.386) +2022-11-14 14:14:49,764 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0730) Prec@1 90.000 (87.800) Prec@5 99.000 (99.378) +2022-11-14 14:14:49,774 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0729) Prec@1 87.000 (87.783) Prec@5 100.000 (99.391) +2022-11-14 14:14:49,785 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0729) Prec@1 88.000 (87.787) Prec@5 99.000 (99.383) +2022-11-14 14:14:49,795 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0735) Prec@1 86.000 (87.750) Prec@5 97.000 (99.333) +2022-11-14 14:14:49,804 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0732) Prec@1 89.000 (87.776) Prec@5 100.000 (99.347) +2022-11-14 14:14:49,815 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1155 (0.0740) Prec@1 80.000 (87.620) Prec@5 99.000 (99.340) +2022-11-14 14:14:49,825 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0739) Prec@1 88.000 (87.627) Prec@5 100.000 (99.353) +2022-11-14 14:14:49,835 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0740) Prec@1 86.000 (87.596) Prec@5 100.000 (99.365) +2022-11-14 14:14:49,844 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0743) Prec@1 85.000 (87.547) Prec@5 100.000 (99.377) +2022-11-14 14:14:49,855 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0741) Prec@1 89.000 (87.574) Prec@5 99.000 (99.370) +2022-11-14 14:14:49,864 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0745) Prec@1 86.000 (87.545) Prec@5 100.000 (99.382) +2022-11-14 14:14:49,873 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0748) Prec@1 86.000 (87.518) Prec@5 99.000 (99.375) +2022-11-14 14:14:49,883 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0751) Prec@1 81.000 (87.404) Prec@5 99.000 (99.368) +2022-11-14 14:14:49,892 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0750) Prec@1 89.000 (87.431) Prec@5 100.000 (99.379) +2022-11-14 14:14:49,901 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0753) Prec@1 85.000 (87.390) Prec@5 100.000 (99.390) +2022-11-14 14:14:49,911 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0750) Prec@1 90.000 (87.433) Prec@5 100.000 (99.400) +2022-11-14 14:14:49,921 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0752) Prec@1 84.000 (87.377) Prec@5 99.000 (99.393) +2022-11-14 14:14:49,933 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0753) Prec@1 87.000 (87.371) Prec@5 98.000 (99.371) +2022-11-14 14:14:49,943 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0751) Prec@1 91.000 (87.429) Prec@5 100.000 (99.381) +2022-11-14 14:14:49,954 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0748) Prec@1 90.000 (87.469) Prec@5 99.000 (99.375) +2022-11-14 14:14:49,963 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0748) Prec@1 87.000 (87.462) Prec@5 100.000 (99.385) +2022-11-14 14:14:49,973 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0750) Prec@1 86.000 (87.439) Prec@5 98.000 (99.364) +2022-11-14 14:14:49,982 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0746) Prec@1 92.000 (87.507) Prec@5 100.000 (99.373) +2022-11-14 14:14:49,991 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0747) Prec@1 86.000 (87.485) Prec@5 99.000 (99.368) +2022-11-14 14:14:50,002 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0747) Prec@1 88.000 (87.493) Prec@5 100.000 (99.377) +2022-11-14 14:14:50,011 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0747) Prec@1 88.000 (87.500) Prec@5 99.000 (99.371) +2022-11-14 14:14:50,022 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0747) Prec@1 88.000 (87.507) Prec@5 99.000 (99.366) +2022-11-14 14:14:50,031 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0748) Prec@1 88.000 (87.514) Prec@5 99.000 (99.361) +2022-11-14 14:14:50,040 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0746) Prec@1 93.000 (87.589) Prec@5 100.000 (99.370) +2022-11-14 14:14:50,051 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0746) Prec@1 86.000 (87.568) Prec@5 100.000 (99.378) +2022-11-14 14:14:50,060 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0751) Prec@1 79.000 (87.453) Prec@5 100.000 (99.387) +2022-11-14 14:14:50,071 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0750) Prec@1 89.000 (87.474) Prec@5 100.000 (99.395) +2022-11-14 14:14:50,082 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0749) Prec@1 90.000 (87.506) Prec@5 100.000 (99.403) +2022-11-14 14:14:50,093 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0750) Prec@1 84.000 (87.462) Prec@5 97.000 (99.372) +2022-11-14 14:14:50,103 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0754) Prec@1 82.000 (87.392) Prec@5 99.000 (99.367) +2022-11-14 14:14:50,113 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0755) Prec@1 87.000 (87.388) Prec@5 100.000 (99.375) +2022-11-14 14:14:50,123 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0757) Prec@1 84.000 (87.346) Prec@5 98.000 (99.358) +2022-11-14 14:14:50,133 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0756) Prec@1 88.000 (87.354) Prec@5 99.000 (99.354) +2022-11-14 14:14:50,143 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0758) Prec@1 83.000 (87.301) Prec@5 98.000 (99.337) +2022-11-14 14:14:50,152 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0756) Prec@1 88.000 (87.310) Prec@5 99.000 (99.333) +2022-11-14 14:14:50,162 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0756) Prec@1 89.000 (87.329) Prec@5 100.000 (99.341) +2022-11-14 14:14:50,170 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0758) Prec@1 84.000 (87.291) Prec@5 99.000 (99.337) +2022-11-14 14:14:50,180 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0758) Prec@1 86.000 (87.276) Prec@5 100.000 (99.345) +2022-11-14 14:14:50,190 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0759) Prec@1 87.000 (87.273) Prec@5 99.000 (99.341) +2022-11-14 14:14:50,199 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0758) Prec@1 90.000 (87.303) Prec@5 100.000 (99.348) +2022-11-14 14:14:50,209 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0757) Prec@1 89.000 (87.322) Prec@5 99.000 (99.344) +2022-11-14 14:14:50,218 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0756) Prec@1 90.000 (87.352) Prec@5 100.000 (99.352) +2022-11-14 14:14:50,227 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0456 (0.0753) Prec@1 91.000 (87.391) Prec@5 99.000 (99.348) +2022-11-14 14:14:50,238 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0753) Prec@1 86.000 (87.376) Prec@5 100.000 (99.355) +2022-11-14 14:14:50,247 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0752) Prec@1 90.000 (87.404) Prec@5 98.000 (99.340) +2022-11-14 14:14:50,257 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0752) Prec@1 87.000 (87.400) Prec@5 98.000 (99.326) +2022-11-14 14:14:50,266 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0750) Prec@1 90.000 (87.427) Prec@5 100.000 (99.333) +2022-11-14 14:14:50,275 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0748) Prec@1 90.000 (87.454) Prec@5 99.000 (99.330) +2022-11-14 14:14:50,286 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0750) Prec@1 84.000 (87.418) Prec@5 98.000 (99.316) +2022-11-14 14:14:50,294 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0753) Prec@1 84.000 (87.384) Prec@5 99.000 (99.313) +2022-11-14 14:14:50,303 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0753) Prec@1 88.000 (87.390) Prec@5 100.000 (99.320) +2022-11-14 14:14:50,362 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:14:50,971 Epoch: [169][0/500] Time 0.026 (0.026) Data 0.224 (0.224) Loss 0.0473 (0.0473) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:14:51,196 Epoch: [169][10/500] Time 0.025 (0.021) Data 0.002 (0.022) Loss 0.0452 (0.0463) Prec@1 93.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 14:14:51,410 Epoch: [169][20/500] Time 0.018 (0.020) Data 0.001 (0.012) Loss 0.0378 (0.0435) Prec@1 93.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:14:51,622 Epoch: [169][30/500] Time 0.019 (0.019) Data 0.002 (0.009) Loss 0.0362 (0.0417) Prec@1 94.000 (93.250) Prec@5 99.000 (99.500) +2022-11-14 14:14:51,891 Epoch: [169][40/500] Time 0.026 (0.020) Data 0.002 (0.007) Loss 0.0455 (0.0424) Prec@1 94.000 (93.400) Prec@5 98.000 (99.200) +2022-11-14 14:14:52,162 Epoch: [169][50/500] Time 0.024 (0.021) Data 0.002 (0.006) Loss 0.0431 (0.0425) Prec@1 94.000 (93.500) Prec@5 100.000 (99.333) +2022-11-14 14:14:52,436 Epoch: [169][60/500] Time 0.023 (0.022) Data 0.002 (0.005) Loss 0.0737 (0.0470) Prec@1 90.000 (93.000) Prec@5 100.000 (99.429) +2022-11-14 14:14:52,709 Epoch: [169][70/500] Time 0.024 (0.022) Data 0.002 (0.005) Loss 0.0383 (0.0459) Prec@1 94.000 (93.125) Prec@5 100.000 (99.500) +2022-11-14 14:14:52,983 Epoch: [169][80/500] Time 0.027 (0.022) Data 0.001 (0.005) Loss 0.0937 (0.0512) Prec@1 84.000 (92.111) Prec@5 100.000 (99.556) +2022-11-14 14:14:53,429 Epoch: [169][90/500] Time 0.044 (0.024) Data 0.002 (0.004) Loss 0.0457 (0.0507) Prec@1 91.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:14:53,926 Epoch: [169][100/500] Time 0.043 (0.026) Data 0.002 (0.004) Loss 0.0390 (0.0496) Prec@1 92.000 (92.000) Prec@5 100.000 (99.636) +2022-11-14 14:14:54,403 Epoch: [169][110/500] Time 0.045 (0.028) Data 0.002 (0.004) Loss 0.0281 (0.0478) Prec@1 95.000 (92.250) Prec@5 100.000 (99.667) +2022-11-14 14:14:54,878 Epoch: [169][120/500] Time 0.044 (0.029) Data 0.002 (0.004) Loss 0.0492 (0.0479) Prec@1 92.000 (92.231) Prec@5 100.000 (99.692) +2022-11-14 14:14:55,348 Epoch: [169][130/500] Time 0.041 (0.030) Data 0.002 (0.004) Loss 0.0718 (0.0496) Prec@1 86.000 (91.786) Prec@5 100.000 (99.714) +2022-11-14 14:14:55,890 Epoch: [169][140/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0521 (0.0498) Prec@1 92.000 (91.800) Prec@5 99.000 (99.667) +2022-11-14 14:14:56,485 Epoch: [169][150/500] Time 0.064 (0.033) Data 0.002 (0.003) Loss 0.0541 (0.0501) Prec@1 90.000 (91.688) Prec@5 99.000 (99.625) +2022-11-14 14:14:57,082 Epoch: [169][160/500] Time 0.069 (0.034) Data 0.002 (0.003) Loss 0.0613 (0.0507) Prec@1 89.000 (91.529) Prec@5 100.000 (99.647) +2022-11-14 14:14:57,598 Epoch: [169][170/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0463 (0.0505) Prec@1 92.000 (91.556) Prec@5 100.000 (99.667) +2022-11-14 14:14:58,149 Epoch: [169][180/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0486 (0.0504) Prec@1 92.000 (91.579) Prec@5 100.000 (99.684) +2022-11-14 14:14:58,733 Epoch: [169][190/500] Time 0.057 (0.036) Data 0.002 (0.003) Loss 0.0457 (0.0501) Prec@1 90.000 (91.500) Prec@5 100.000 (99.700) +2022-11-14 14:14:59,353 Epoch: [169][200/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0770 (0.0514) Prec@1 84.000 (91.143) Prec@5 98.000 (99.619) +2022-11-14 14:14:59,868 Epoch: [169][210/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0217 (0.0501) Prec@1 96.000 (91.364) Prec@5 100.000 (99.636) +2022-11-14 14:15:00,401 Epoch: [169][220/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0542 (0.0502) Prec@1 92.000 (91.391) Prec@5 99.000 (99.609) +2022-11-14 14:15:00,937 Epoch: [169][230/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0812 (0.0515) Prec@1 86.000 (91.167) Prec@5 100.000 (99.625) +2022-11-14 14:15:01,494 Epoch: [169][240/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0176 (0.0502) Prec@1 98.000 (91.440) Prec@5 100.000 (99.640) +2022-11-14 14:15:02,102 Epoch: [169][250/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0494 (0.0502) Prec@1 91.000 (91.423) Prec@5 100.000 (99.654) +2022-11-14 14:15:02,580 Epoch: [169][260/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0404 (0.0498) Prec@1 93.000 (91.481) Prec@5 100.000 (99.667) +2022-11-14 14:15:03,049 Epoch: [169][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0595 (0.0501) Prec@1 92.000 (91.500) Prec@5 100.000 (99.679) +2022-11-14 14:15:03,534 Epoch: [169][280/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0536 (0.0503) Prec@1 92.000 (91.517) Prec@5 99.000 (99.655) +2022-11-14 14:15:04,003 Epoch: [169][290/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0305 (0.0496) Prec@1 95.000 (91.633) Prec@5 100.000 (99.667) +2022-11-14 14:15:04,473 Epoch: [169][300/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0572 (0.0498) Prec@1 91.000 (91.613) Prec@5 100.000 (99.677) +2022-11-14 14:15:04,961 Epoch: [169][310/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0773 (0.0507) Prec@1 87.000 (91.469) Prec@5 100.000 (99.688) +2022-11-14 14:15:05,490 Epoch: [169][320/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0324 (0.0501) Prec@1 96.000 (91.606) Prec@5 99.000 (99.667) +2022-11-14 14:15:05,964 Epoch: [169][330/500] Time 0.042 (0.041) Data 0.003 (0.003) Loss 0.0598 (0.0504) Prec@1 91.000 (91.588) Prec@5 100.000 (99.676) +2022-11-14 14:15:06,474 Epoch: [169][340/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0447 (0.0503) Prec@1 93.000 (91.629) Prec@5 100.000 (99.686) +2022-11-14 14:15:06,958 Epoch: [169][350/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0558 (0.0504) Prec@1 90.000 (91.583) Prec@5 99.000 (99.667) +2022-11-14 14:15:07,425 Epoch: [169][360/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0513 (0.0504) Prec@1 92.000 (91.595) Prec@5 100.000 (99.676) +2022-11-14 14:15:07,906 Epoch: [169][370/500] Time 0.041 (0.041) Data 0.002 (0.002) Loss 0.0460 (0.0503) Prec@1 93.000 (91.632) Prec@5 100.000 (99.684) +2022-11-14 14:15:08,441 Epoch: [169][380/500] Time 0.095 (0.041) Data 0.002 (0.002) Loss 0.0502 (0.0503) Prec@1 91.000 (91.615) Prec@5 100.000 (99.692) +2022-11-14 14:15:08,935 Epoch: [169][390/500] Time 0.046 (0.041) Data 0.002 (0.002) Loss 0.0446 (0.0502) Prec@1 92.000 (91.625) Prec@5 99.000 (99.675) +2022-11-14 14:15:09,416 Epoch: [169][400/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0371 (0.0499) Prec@1 95.000 (91.707) Prec@5 100.000 (99.683) +2022-11-14 14:15:09,900 Epoch: [169][410/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0431 (0.0497) Prec@1 93.000 (91.738) Prec@5 100.000 (99.690) +2022-11-14 14:15:10,372 Epoch: [169][420/500] Time 0.046 (0.041) Data 0.001 (0.002) Loss 0.0527 (0.0498) Prec@1 91.000 (91.721) Prec@5 100.000 (99.698) +2022-11-14 14:15:10,854 Epoch: [169][430/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0514 (0.0498) Prec@1 91.000 (91.705) Prec@5 100.000 (99.705) +2022-11-14 14:15:11,356 Epoch: [169][440/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0237 (0.0492) Prec@1 98.000 (91.844) Prec@5 100.000 (99.711) +2022-11-14 14:15:11,868 Epoch: [169][450/500] Time 0.050 (0.041) Data 0.003 (0.002) Loss 0.0204 (0.0486) Prec@1 98.000 (91.978) Prec@5 100.000 (99.717) +2022-11-14 14:15:12,368 Epoch: [169][460/500] Time 0.050 (0.042) Data 0.002 (0.002) Loss 0.0702 (0.0491) Prec@1 86.000 (91.851) Prec@5 100.000 (99.723) +2022-11-14 14:15:12,844 Epoch: [169][470/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0414 (0.0489) Prec@1 92.000 (91.854) Prec@5 99.000 (99.708) +2022-11-14 14:15:13,339 Epoch: [169][480/500] Time 0.045 (0.042) Data 0.002 (0.002) Loss 0.0433 (0.0488) Prec@1 95.000 (91.918) Prec@5 99.000 (99.694) +2022-11-14 14:15:13,827 Epoch: [169][490/500] Time 0.050 (0.042) Data 0.002 (0.002) Loss 0.0350 (0.0485) Prec@1 94.000 (91.960) Prec@5 100.000 (99.700) +2022-11-14 14:15:14,275 Epoch: [169][499/500] Time 0.046 (0.042) Data 0.002 (0.002) Loss 0.0370 (0.0483) Prec@1 95.000 (92.020) Prec@5 100.000 (99.706) +2022-11-14 14:15:14,573 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0692 (0.0692) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:15:14,584 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0674) Prec@1 89.000 (89.500) Prec@5 99.000 (99.000) +2022-11-14 14:15:14,595 Test: [2/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0697) Prec@1 86.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,608 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.0738) Prec@1 86.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 14:15:14,618 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0708) Prec@1 91.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 14:15:14,627 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0355 (0.0649) Prec@1 93.000 (89.167) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,635 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0663) Prec@1 88.000 (89.000) Prec@5 99.000 (99.286) +2022-11-14 14:15:14,644 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.0716) Prec@1 81.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 14:15:14,653 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0731) Prec@1 87.000 (87.889) Prec@5 99.000 (99.333) +2022-11-14 14:15:14,664 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0734) Prec@1 89.000 (88.000) Prec@5 99.000 (99.300) +2022-11-14 14:15:14,674 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0723) Prec@1 90.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 14:15:14,684 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0746) Prec@1 84.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 14:15:14,695 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0334 (0.0715) Prec@1 94.000 (88.308) Prec@5 100.000 (99.385) +2022-11-14 14:15:14,705 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0717) Prec@1 89.000 (88.357) Prec@5 98.000 (99.286) +2022-11-14 14:15:14,715 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0715) Prec@1 90.000 (88.467) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,724 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0717) Prec@1 85.000 (88.250) Prec@5 100.000 (99.375) +2022-11-14 14:15:14,734 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0709) Prec@1 91.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 14:15:14,744 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0726) Prec@1 85.000 (88.222) Prec@5 100.000 (99.389) +2022-11-14 14:15:14,754 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0735) Prec@1 82.000 (87.895) Prec@5 100.000 (99.421) +2022-11-14 14:15:14,765 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0750) Prec@1 84.000 (87.700) Prec@5 98.000 (99.350) +2022-11-14 14:15:14,775 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0746) Prec@1 87.000 (87.667) Prec@5 100.000 (99.381) +2022-11-14 14:15:14,785 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0741) Prec@1 88.000 (87.682) Prec@5 100.000 (99.409) +2022-11-14 14:15:14,794 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0743) Prec@1 86.000 (87.609) Prec@5 98.000 (99.348) +2022-11-14 14:15:14,804 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0747) Prec@1 87.000 (87.583) Prec@5 98.000 (99.292) +2022-11-14 14:15:14,815 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0750) Prec@1 86.000 (87.520) Prec@5 100.000 (99.320) +2022-11-14 14:15:14,827 Test: [25/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1252 (0.0769) Prec@1 78.000 (87.154) Prec@5 99.000 (99.308) +2022-11-14 14:15:14,841 Test: [26/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0766) Prec@1 88.000 (87.185) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,853 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0763) Prec@1 90.000 (87.286) Prec@5 99.000 (99.321) +2022-11-14 14:15:14,864 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0766) Prec@1 84.000 (87.172) Prec@5 99.000 (99.310) +2022-11-14 14:15:14,874 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0762) Prec@1 89.000 (87.233) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,884 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0762) Prec@1 89.000 (87.290) Prec@5 99.000 (99.323) +2022-11-14 14:15:14,893 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0765) Prec@1 87.000 (87.281) Prec@5 99.000 (99.312) +2022-11-14 14:15:14,904 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0765) Prec@1 86.000 (87.242) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,914 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0766) Prec@1 86.000 (87.206) Prec@5 100.000 (99.353) +2022-11-14 14:15:14,925 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0766) Prec@1 86.000 (87.171) Prec@5 98.000 (99.314) +2022-11-14 14:15:14,935 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0763) Prec@1 88.000 (87.194) Prec@5 100.000 (99.333) +2022-11-14 14:15:14,945 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0761) Prec@1 87.000 (87.189) Prec@5 98.000 (99.297) +2022-11-14 14:15:14,954 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0770) Prec@1 83.000 (87.079) Prec@5 100.000 (99.316) +2022-11-14 14:15:14,964 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0765) Prec@1 90.000 (87.154) Prec@5 99.000 (99.308) +2022-11-14 14:15:14,976 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0762) Prec@1 91.000 (87.250) Prec@5 99.000 (99.300) +2022-11-14 14:15:14,990 Test: [40/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0766) Prec@1 84.000 (87.171) Prec@5 100.000 (99.317) +2022-11-14 14:15:15,003 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0765) Prec@1 87.000 (87.167) Prec@5 100.000 (99.333) +2022-11-14 14:15:15,015 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0760) Prec@1 89.000 (87.209) Prec@5 100.000 (99.349) +2022-11-14 14:15:15,025 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0758) Prec@1 89.000 (87.250) Prec@5 98.000 (99.318) +2022-11-14 14:15:15,035 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0759) Prec@1 86.000 (87.222) Prec@5 99.000 (99.311) +2022-11-14 14:15:15,045 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0763) Prec@1 84.000 (87.152) Prec@5 98.000 (99.283) +2022-11-14 14:15:15,056 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0763) Prec@1 88.000 (87.170) Prec@5 99.000 (99.277) +2022-11-14 14:15:15,070 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0769) Prec@1 83.000 (87.083) Prec@5 99.000 (99.271) +2022-11-14 14:15:15,082 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0767) Prec@1 91.000 (87.163) Prec@5 100.000 (99.286) +2022-11-14 14:15:15,093 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0771) Prec@1 83.000 (87.080) Prec@5 100.000 (99.300) +2022-11-14 14:15:15,102 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0771) Prec@1 86.000 (87.059) Prec@5 100.000 (99.314) +2022-11-14 14:15:15,113 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0769) Prec@1 89.000 (87.096) Prec@5 100.000 (99.327) +2022-11-14 14:15:15,123 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0771) Prec@1 83.000 (87.019) Prec@5 100.000 (99.340) +2022-11-14 14:15:15,134 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0770) Prec@1 86.000 (87.000) Prec@5 99.000 (99.333) +2022-11-14 14:15:15,144 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0767) Prec@1 92.000 (87.091) Prec@5 100.000 (99.345) +2022-11-14 14:15:15,154 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0766) Prec@1 88.000 (87.107) Prec@5 98.000 (99.321) +2022-11-14 14:15:15,164 Test: 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Loss 0.0743 (0.0769) Prec@1 89.000 (87.111) Prec@5 100.000 (99.365) +2022-11-14 14:15:15,237 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0177 (0.0759) Prec@1 98.000 (87.281) Prec@5 100.000 (99.375) +2022-11-14 14:15:15,251 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0761) Prec@1 84.000 (87.231) Prec@5 100.000 (99.385) +2022-11-14 14:15:15,262 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0764) Prec@1 83.000 (87.167) Prec@5 97.000 (99.348) +2022-11-14 14:15:15,272 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0760) Prec@1 93.000 (87.254) Prec@5 100.000 (99.358) +2022-11-14 14:15:15,282 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0760) Prec@1 90.000 (87.294) Prec@5 99.000 (99.353) +2022-11-14 14:15:15,292 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0759) Prec@1 86.000 (87.275) Prec@5 99.000 (99.348) +2022-11-14 14:15:15,304 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0759) Prec@1 89.000 (87.300) Prec@5 98.000 (99.329) +2022-11-14 14:15:15,317 Test: [70/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0762) Prec@1 85.000 (87.268) Prec@5 99.000 (99.324) +2022-11-14 14:15:15,331 Test: [71/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0759) Prec@1 90.000 (87.306) Prec@5 99.000 (99.319) +2022-11-14 14:15:15,342 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0759) Prec@1 88.000 (87.315) Prec@5 100.000 (99.329) +2022-11-14 14:15:15,353 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0756) Prec@1 90.000 (87.351) Prec@5 100.000 (99.338) +2022-11-14 14:15:15,363 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0759) Prec@1 83.000 (87.293) Prec@5 98.000 (99.320) +2022-11-14 14:15:15,372 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0758) Prec@1 88.000 (87.303) Prec@5 99.000 (99.316) +2022-11-14 14:15:15,383 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0758) Prec@1 87.000 (87.299) Prec@5 99.000 (99.312) +2022-11-14 14:15:15,395 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0761) Prec@1 83.000 (87.244) Prec@5 98.000 (99.295) +2022-11-14 14:15:15,409 Test: [78/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0762) Prec@1 86.000 (87.228) Prec@5 100.000 (99.304) +2022-11-14 14:15:15,420 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0761) Prec@1 86.000 (87.213) Prec@5 100.000 (99.312) +2022-11-14 14:15:15,431 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0763) Prec@1 85.000 (87.185) Prec@5 99.000 (99.309) +2022-11-14 14:15:15,443 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0764) Prec@1 85.000 (87.159) Prec@5 100.000 (99.317) +2022-11-14 14:15:15,453 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1089 (0.0768) Prec@1 82.000 (87.096) Prec@5 100.000 (99.325) +2022-11-14 14:15:15,463 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0767) Prec@1 89.000 (87.119) Prec@5 100.000 (99.333) +2022-11-14 14:15:15,473 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0768) Prec@1 87.000 (87.118) Prec@5 100.000 (99.341) +2022-11-14 14:15:15,481 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0770) Prec@1 85.000 (87.093) Prec@5 99.000 (99.337) +2022-11-14 14:15:15,491 Test: [86/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0771) Prec@1 85.000 (87.069) Prec@5 100.000 (99.345) +2022-11-14 14:15:15,501 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1116 (0.0775) Prec@1 80.000 (86.989) Prec@5 99.000 (99.341) +2022-11-14 14:15:15,511 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0773) Prec@1 90.000 (87.022) Prec@5 100.000 (99.348) +2022-11-14 14:15:15,521 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0774) Prec@1 87.000 (87.022) Prec@5 99.000 (99.344) +2022-11-14 14:15:15,530 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0770) Prec@1 92.000 (87.077) Prec@5 100.000 (99.352) +2022-11-14 14:15:15,540 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0450 (0.0767) Prec@1 90.000 (87.109) Prec@5 100.000 (99.359) +2022-11-14 14:15:15,551 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0769) Prec@1 85.000 (87.086) Prec@5 100.000 (99.366) +2022-11-14 14:15:15,563 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0769) Prec@1 88.000 (87.096) Prec@5 97.000 (99.340) +2022-11-14 14:15:15,573 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0770) Prec@1 85.000 (87.074) Prec@5 100.000 (99.347) +2022-11-14 14:15:15,583 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0769) Prec@1 88.000 (87.083) Prec@5 99.000 (99.344) +2022-11-14 14:15:15,593 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0766) Prec@1 94.000 (87.155) Prec@5 99.000 (99.340) +2022-11-14 14:15:15,602 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0769) Prec@1 86.000 (87.143) Prec@5 97.000 (99.316) +2022-11-14 14:15:15,613 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0772) Prec@1 82.000 (87.091) Prec@5 99.000 (99.313) +2022-11-14 14:15:15,623 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0772) Prec@1 90.000 (87.120) Prec@5 100.000 (99.320) +2022-11-14 14:15:15,692 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:15:16,249 Epoch: [170][0/500] Time 0.023 (0.023) Data 0.223 (0.223) Loss 0.0481 (0.0481) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:15:16,468 Epoch: [170][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.0385 (0.0433) Prec@1 94.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:15:16,686 Epoch: [170][20/500] Time 0.018 (0.020) Data 0.002 (0.012) Loss 0.0354 (0.0407) Prec@1 93.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 14:15:16,929 Epoch: [170][30/500] Time 0.023 (0.020) Data 0.002 (0.009) Loss 0.0496 (0.0429) Prec@1 91.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:15:17,258 Epoch: [170][40/500] Time 0.032 (0.023) Data 0.002 (0.007) Loss 0.0313 (0.0406) Prec@1 94.000 (92.400) Prec@5 100.000 (100.000) +2022-11-14 14:15:17,524 Epoch: [170][50/500] Time 0.026 (0.023) Data 0.002 (0.006) Loss 0.0258 (0.0381) Prec@1 96.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:15:17,806 Epoch: [170][60/500] Time 0.025 (0.023) Data 0.002 (0.005) Loss 0.0478 (0.0395) Prec@1 91.000 (92.714) Prec@5 100.000 (100.000) +2022-11-14 14:15:18,121 Epoch: [170][70/500] Time 0.040 (0.024) Data 0.002 (0.005) Loss 0.0230 (0.0374) Prec@1 98.000 (93.375) Prec@5 100.000 (100.000) +2022-11-14 14:15:18,414 Epoch: [170][80/500] Time 0.027 (0.024) Data 0.002 (0.005) Loss 0.0344 (0.0371) Prec@1 94.000 (93.444) Prec@5 100.000 (100.000) +2022-11-14 14:15:18,694 Epoch: [170][90/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0481 (0.0382) Prec@1 90.000 (93.100) Prec@5 100.000 (100.000) +2022-11-14 14:15:18,984 Epoch: [170][100/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0447 (0.0388) Prec@1 93.000 (93.091) Prec@5 100.000 (100.000) +2022-11-14 14:15:19,442 Epoch: [170][110/500] Time 0.042 (0.026) Data 0.002 (0.004) Loss 0.0254 (0.0377) Prec@1 97.000 (93.417) Prec@5 99.000 (99.917) +2022-11-14 14:15:19,924 Epoch: [170][120/500] Time 0.048 (0.027) Data 0.002 (0.004) Loss 0.0496 (0.0386) Prec@1 91.000 (93.231) Prec@5 99.000 (99.846) +2022-11-14 14:15:20,406 Epoch: [170][130/500] Time 0.044 (0.028) Data 0.002 (0.004) Loss 0.0352 (0.0383) Prec@1 96.000 (93.429) Prec@5 100.000 (99.857) +2022-11-14 14:15:20,887 Epoch: [170][140/500] Time 0.044 (0.029) Data 0.001 (0.003) Loss 0.0239 (0.0374) Prec@1 97.000 (93.667) Prec@5 100.000 (99.867) +2022-11-14 14:15:21,368 Epoch: [170][150/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0410 (0.0376) Prec@1 92.000 (93.562) Prec@5 100.000 (99.875) +2022-11-14 14:15:21,840 Epoch: [170][160/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0293 (0.0371) Prec@1 96.000 (93.706) Prec@5 100.000 (99.882) +2022-11-14 14:15:22,327 Epoch: [170][170/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0524 (0.0380) Prec@1 91.000 (93.556) Prec@5 99.000 (99.833) +2022-11-14 14:15:22,820 Epoch: [170][180/500] Time 0.049 (0.032) Data 0.002 (0.003) Loss 0.0587 (0.0391) Prec@1 88.000 (93.263) Prec@5 99.000 (99.789) +2022-11-14 14:15:23,316 Epoch: [170][190/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0502 (0.0396) Prec@1 93.000 (93.250) Prec@5 100.000 (99.800) +2022-11-14 14:15:23,795 Epoch: [170][200/500] Time 0.042 (0.034) Data 0.003 (0.003) Loss 0.0297 (0.0391) Prec@1 96.000 (93.381) Prec@5 100.000 (99.810) +2022-11-14 14:15:24,323 Epoch: [170][210/500] Time 0.054 (0.034) Data 0.002 (0.003) Loss 0.0505 (0.0397) Prec@1 92.000 (93.318) Prec@5 100.000 (99.818) +2022-11-14 14:15:24,827 Epoch: [170][220/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0682 (0.0409) Prec@1 87.000 (93.043) Prec@5 100.000 (99.826) +2022-11-14 14:15:25,350 Epoch: [170][230/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0435 (0.0410) Prec@1 95.000 (93.125) Prec@5 100.000 (99.833) +2022-11-14 14:15:25,864 Epoch: [170][240/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0458 (0.0412) Prec@1 93.000 (93.120) Prec@5 100.000 (99.840) +2022-11-14 14:15:26,347 Epoch: [170][250/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0280 (0.0407) Prec@1 96.000 (93.231) Prec@5 100.000 (99.846) +2022-11-14 14:15:26,810 Epoch: [170][260/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0274 (0.0402) Prec@1 95.000 (93.296) Prec@5 100.000 (99.852) +2022-11-14 14:15:27,302 Epoch: [170][270/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0375 (0.0401) Prec@1 92.000 (93.250) Prec@5 100.000 (99.857) +2022-11-14 14:15:27,877 Epoch: [170][280/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0432 (0.0402) Prec@1 93.000 (93.241) Prec@5 99.000 (99.828) +2022-11-14 14:15:28,452 Epoch: [170][290/500] Time 0.108 (0.037) Data 0.002 (0.003) Loss 0.0349 (0.0400) Prec@1 95.000 (93.300) Prec@5 100.000 (99.833) +2022-11-14 14:15:28,980 Epoch: [170][300/500] Time 0.060 (0.038) Data 0.002 (0.003) Loss 0.0341 (0.0398) Prec@1 95.000 (93.355) Prec@5 100.000 (99.839) +2022-11-14 14:15:29,525 Epoch: [170][310/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0323 (0.0396) Prec@1 95.000 (93.406) Prec@5 100.000 (99.844) +2022-11-14 14:15:30,077 Epoch: [170][320/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0363 (0.0395) Prec@1 94.000 (93.424) Prec@5 100.000 (99.848) +2022-11-14 14:15:30,612 Epoch: [170][330/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0523 (0.0399) Prec@1 91.000 (93.353) Prec@5 98.000 (99.794) +2022-11-14 14:15:31,163 Epoch: [170][340/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0619 (0.0405) Prec@1 86.000 (93.143) Prec@5 100.000 (99.800) +2022-11-14 14:15:31,728 Epoch: [170][350/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0591 (0.0410) Prec@1 90.000 (93.056) Prec@5 99.000 (99.778) +2022-11-14 14:15:32,291 Epoch: [170][360/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0337 (0.0408) Prec@1 94.000 (93.081) Prec@5 100.000 (99.784) +2022-11-14 14:15:32,839 Epoch: [170][370/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0133 (0.0401) Prec@1 98.000 (93.211) Prec@5 100.000 (99.789) +2022-11-14 14:15:33,397 Epoch: [170][380/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0665 (0.0408) Prec@1 90.000 (93.128) Prec@5 97.000 (99.718) +2022-11-14 14:15:34,083 Epoch: [170][390/500] Time 0.087 (0.041) Data 0.003 (0.003) Loss 0.0434 (0.0409) Prec@1 93.000 (93.125) Prec@5 100.000 (99.725) +2022-11-14 14:15:34,626 Epoch: [170][400/500] Time 0.032 (0.041) Data 0.002 (0.002) Loss 0.0739 (0.0417) Prec@1 87.000 (92.976) Prec@5 98.000 (99.683) +2022-11-14 14:15:34,953 Epoch: [170][410/500] Time 0.040 (0.041) Data 0.002 (0.002) Loss 0.0316 (0.0414) Prec@1 95.000 (93.024) Prec@5 100.000 (99.690) +2022-11-14 14:15:35,322 Epoch: [170][420/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0450 (0.0415) Prec@1 93.000 (93.023) Prec@5 99.000 (99.674) +2022-11-14 14:15:35,682 Epoch: [170][430/500] Time 0.022 (0.040) Data 0.002 (0.002) Loss 0.0468 (0.0416) Prec@1 93.000 (93.023) Prec@5 100.000 (99.682) +2022-11-14 14:15:36,004 Epoch: [170][440/500] Time 0.034 (0.040) Data 0.002 (0.002) Loss 0.0511 (0.0418) Prec@1 92.000 (93.000) Prec@5 100.000 (99.689) +2022-11-14 14:15:36,325 Epoch: [170][450/500] Time 0.030 (0.040) Data 0.002 (0.002) Loss 0.0584 (0.0422) Prec@1 91.000 (92.957) Prec@5 100.000 (99.696) +2022-11-14 14:15:36,646 Epoch: [170][460/500] Time 0.035 (0.040) Data 0.002 (0.002) Loss 0.0621 (0.0426) Prec@1 90.000 (92.894) Prec@5 100.000 (99.702) +2022-11-14 14:15:36,974 Epoch: [170][470/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.0626 (0.0430) Prec@1 92.000 (92.875) Prec@5 99.000 (99.688) +2022-11-14 14:15:37,302 Epoch: [170][480/500] Time 0.028 (0.039) Data 0.002 (0.002) Loss 0.0445 (0.0431) Prec@1 93.000 (92.878) Prec@5 99.000 (99.673) +2022-11-14 14:15:37,635 Epoch: [170][490/500] Time 0.031 (0.039) Data 0.002 (0.002) Loss 0.0537 (0.0433) Prec@1 93.000 (92.880) Prec@5 99.000 (99.660) +2022-11-14 14:15:37,929 Epoch: [170][499/500] Time 0.030 (0.039) Data 0.002 (0.002) Loss 0.0382 (0.0432) Prec@1 94.000 (92.902) Prec@5 100.000 (99.667) +2022-11-14 14:15:38,253 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0810 (0.0810) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:15:38,264 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0735 (0.0772) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:15:38,274 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0805 (0.0783) Prec@1 87.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 14:15:38,282 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0991 (0.0835) Prec@1 80.000 (85.750) Prec@5 99.000 (99.250) +2022-11-14 14:15:38,294 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0814) Prec@1 90.000 (86.600) Prec@5 99.000 (99.200) +2022-11-14 14:15:38,303 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0318 (0.0732) Prec@1 94.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 14:15:38,311 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0734) Prec@1 88.000 (87.857) Prec@5 100.000 (99.429) +2022-11-14 14:15:38,319 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0755) Prec@1 82.000 (87.125) Prec@5 98.000 (99.250) +2022-11-14 14:15:38,332 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0756) Prec@1 87.000 (87.111) Prec@5 99.000 (99.222) +2022-11-14 14:15:38,342 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0745) Prec@1 89.000 (87.300) Prec@5 99.000 (99.200) +2022-11-14 14:15:38,351 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0732) Prec@1 90.000 (87.545) Prec@5 98.000 (99.091) +2022-11-14 14:15:38,360 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0740) Prec@1 86.000 (87.417) Prec@5 99.000 (99.083) +2022-11-14 14:15:38,372 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0356 (0.0711) Prec@1 94.000 (87.923) Prec@5 99.000 (99.077) +2022-11-14 14:15:38,382 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0717) Prec@1 89.000 (88.000) Prec@5 100.000 (99.143) +2022-11-14 14:15:38,391 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0734) Prec@1 80.000 (87.467) Prec@5 100.000 (99.200) +2022-11-14 14:15:38,399 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0733) Prec@1 89.000 (87.562) Prec@5 100.000 (99.250) +2022-11-14 14:15:38,409 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0725) Prec@1 88.000 (87.588) Prec@5 99.000 (99.235) +2022-11-14 14:15:38,418 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0742) Prec@1 81.000 (87.222) Prec@5 98.000 (99.167) +2022-11-14 14:15:38,426 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0744) Prec@1 86.000 (87.158) Prec@5 98.000 (99.105) +2022-11-14 14:15:38,434 Test: [19/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.1075 (0.0760) Prec@1 83.000 (86.950) Prec@5 97.000 (99.000) +2022-11-14 14:15:38,441 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0763) Prec@1 88.000 (87.000) Prec@5 100.000 (99.048) +2022-11-14 14:15:38,451 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0768) Prec@1 85.000 (86.909) Prec@5 99.000 (99.045) +2022-11-14 14:15:38,460 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0775) Prec@1 85.000 (86.826) Prec@5 97.000 (98.957) +2022-11-14 14:15:38,468 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0773) Prec@1 87.000 (86.833) Prec@5 100.000 (99.000) +2022-11-14 14:15:38,478 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0776) Prec@1 88.000 (86.880) Prec@5 99.000 (99.000) +2022-11-14 14:15:38,487 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0776) Prec@1 85.000 (86.808) Prec@5 98.000 (98.962) +2022-11-14 14:15:38,496 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0360 (0.0761) Prec@1 95.000 (87.111) Prec@5 100.000 (99.000) +2022-11-14 14:15:38,505 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0758) Prec@1 89.000 (87.179) Prec@5 100.000 (99.036) +2022-11-14 14:15:38,514 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0753) Prec@1 90.000 (87.276) Prec@5 100.000 (99.069) +2022-11-14 14:15:38,523 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0756) Prec@1 83.000 (87.133) Prec@5 100.000 (99.100) +2022-11-14 14:15:38,531 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0755) Prec@1 89.000 (87.194) Prec@5 100.000 (99.129) +2022-11-14 14:15:38,540 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0753) Prec@1 90.000 (87.281) Prec@5 99.000 (99.125) +2022-11-14 14:15:38,550 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0752) Prec@1 87.000 (87.273) Prec@5 100.000 (99.152) +2022-11-14 14:15:38,559 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0755) Prec@1 87.000 (87.265) Prec@5 98.000 (99.118) +2022-11-14 14:15:38,568 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0752) Prec@1 89.000 (87.314) Prec@5 100.000 (99.143) +2022-11-14 14:15:38,577 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0754) Prec@1 89.000 (87.361) Prec@5 100.000 (99.167) +2022-11-14 14:15:38,586 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0758) Prec@1 84.000 (87.270) Prec@5 98.000 (99.135) +2022-11-14 14:15:38,593 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0764) Prec@1 83.000 (87.158) Prec@5 99.000 (99.132) +2022-11-14 14:15:38,601 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0761) Prec@1 90.000 (87.231) Prec@5 99.000 (99.128) +2022-11-14 14:15:38,611 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0761) Prec@1 89.000 (87.275) Prec@5 98.000 (99.100) +2022-11-14 14:15:38,620 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0764) Prec@1 84.000 (87.195) Prec@5 98.000 (99.073) +2022-11-14 14:15:38,628 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0762) Prec@1 90.000 (87.262) Prec@5 99.000 (99.071) +2022-11-14 14:15:38,638 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0757) Prec@1 91.000 (87.349) Prec@5 100.000 (99.093) +2022-11-14 14:15:38,647 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0754) Prec@1 91.000 (87.432) Prec@5 98.000 (99.068) +2022-11-14 14:15:38,656 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0752) Prec@1 89.000 (87.467) Prec@5 99.000 (99.067) +2022-11-14 14:15:38,664 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0761) Prec@1 80.000 (87.304) Prec@5 100.000 (99.087) +2022-11-14 14:15:38,674 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0762) Prec@1 86.000 (87.277) Prec@5 100.000 (99.106) +2022-11-14 14:15:38,684 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0769) Prec@1 83.000 (87.188) Prec@5 100.000 (99.125) +2022-11-14 14:15:38,693 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0762) Prec@1 93.000 (87.306) Prec@5 99.000 (99.122) +2022-11-14 14:15:38,703 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0768) Prec@1 85.000 (87.260) Prec@5 100.000 (99.140) +2022-11-14 14:15:38,712 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0768) Prec@1 83.000 (87.176) Prec@5 100.000 (99.157) +2022-11-14 14:15:38,721 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0770) Prec@1 84.000 (87.115) Prec@5 99.000 (99.154) +2022-11-14 14:15:38,730 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0768) Prec@1 89.000 (87.151) Prec@5 99.000 (99.151) +2022-11-14 14:15:38,739 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0766) Prec@1 89.000 (87.185) Prec@5 98.000 (99.130) +2022-11-14 14:15:38,748 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0768) Prec@1 87.000 (87.182) Prec@5 99.000 (99.127) +2022-11-14 14:15:38,757 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0767) Prec@1 87.000 (87.179) Prec@5 99.000 (99.125) +2022-11-14 14:15:38,765 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0766) Prec@1 89.000 (87.211) Prec@5 100.000 (99.140) +2022-11-14 14:15:38,774 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0766) Prec@1 87.000 (87.207) Prec@5 99.000 (99.138) +2022-11-14 14:15:38,782 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0769) Prec@1 83.000 (87.136) Prec@5 99.000 (99.136) +2022-11-14 14:15:38,792 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0770) Prec@1 84.000 (87.083) Prec@5 100.000 (99.150) +2022-11-14 14:15:38,800 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0767) Prec@1 92.000 (87.164) Prec@5 99.000 (99.148) +2022-11-14 14:15:38,809 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0764) Prec@1 89.000 (87.194) Prec@5 100.000 (99.161) +2022-11-14 14:15:38,819 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0764) Prec@1 88.000 (87.206) Prec@5 99.000 (99.159) +2022-11-14 14:15:38,828 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0761) Prec@1 90.000 (87.250) Prec@5 100.000 (99.172) +2022-11-14 14:15:38,836 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0762) Prec@1 87.000 (87.246) Prec@5 99.000 (99.169) +2022-11-14 14:15:38,845 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0763) Prec@1 81.000 (87.152) Prec@5 100.000 (99.182) +2022-11-14 14:15:38,855 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0760) Prec@1 90.000 (87.194) Prec@5 100.000 (99.194) +2022-11-14 14:15:38,863 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0757) Prec@1 88.000 (87.206) Prec@5 99.000 (99.191) +2022-11-14 14:15:38,871 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0758) Prec@1 86.000 (87.188) Prec@5 100.000 (99.203) +2022-11-14 14:15:38,878 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0759) Prec@1 86.000 (87.171) Prec@5 99.000 (99.200) +2022-11-14 14:15:38,886 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0760) Prec@1 86.000 (87.155) Prec@5 100.000 (99.211) +2022-11-14 14:15:38,894 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0760) Prec@1 87.000 (87.153) Prec@5 99.000 (99.208) +2022-11-14 14:15:38,904 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0759) Prec@1 89.000 (87.178) Prec@5 100.000 (99.219) +2022-11-14 14:15:38,913 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0754) Prec@1 94.000 (87.270) Prec@5 100.000 (99.230) +2022-11-14 14:15:38,923 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0757) Prec@1 83.000 (87.213) Prec@5 99.000 (99.227) +2022-11-14 14:15:38,932 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0757) Prec@1 85.000 (87.184) Prec@5 99.000 (99.224) +2022-11-14 14:15:38,941 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0758) Prec@1 88.000 (87.195) Prec@5 100.000 (99.234) +2022-11-14 14:15:38,951 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0761) Prec@1 84.000 (87.154) Prec@5 97.000 (99.205) +2022-11-14 14:15:38,959 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0762) Prec@1 88.000 (87.165) Prec@5 100.000 (99.215) +2022-11-14 14:15:38,968 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0765) Prec@1 81.000 (87.088) Prec@5 100.000 (99.225) +2022-11-14 14:15:38,977 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0766) Prec@1 86.000 (87.074) Prec@5 99.000 (99.222) +2022-11-14 14:15:38,986 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0764) Prec@1 91.000 (87.122) Prec@5 99.000 (99.220) +2022-11-14 14:15:38,996 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0767) Prec@1 85.000 (87.096) Prec@5 100.000 (99.229) +2022-11-14 14:15:39,006 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0454 (0.0764) Prec@1 92.000 (87.155) Prec@5 99.000 (99.226) +2022-11-14 14:15:39,016 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0766) Prec@1 84.000 (87.118) Prec@5 99.000 (99.224) +2022-11-14 14:15:39,027 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0767) Prec@1 88.000 (87.128) Prec@5 99.000 (99.221) +2022-11-14 14:15:39,039 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0768) Prec@1 85.000 (87.103) Prec@5 99.000 (99.218) +2022-11-14 14:15:39,051 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0768) Prec@1 88.000 (87.114) Prec@5 99.000 (99.216) +2022-11-14 14:15:39,063 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0770) Prec@1 84.000 (87.079) Prec@5 99.000 (99.213) +2022-11-14 14:15:39,074 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0770) Prec@1 89.000 (87.100) Prec@5 99.000 (99.211) +2022-11-14 14:15:39,086 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0769) Prec@1 90.000 (87.132) Prec@5 100.000 (99.220) +2022-11-14 14:15:39,097 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0765) Prec@1 93.000 (87.196) Prec@5 100.000 (99.228) +2022-11-14 14:15:39,109 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0767) Prec@1 86.000 (87.183) Prec@5 100.000 (99.237) +2022-11-14 14:15:39,120 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0766) Prec@1 86.000 (87.170) Prec@5 99.000 (99.234) +2022-11-14 14:15:39,132 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0768) Prec@1 85.000 (87.147) Prec@5 99.000 (99.232) +2022-11-14 14:15:39,143 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0768) Prec@1 88.000 (87.156) Prec@5 97.000 (99.208) +2022-11-14 14:15:39,153 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0766) Prec@1 94.000 (87.227) Prec@5 99.000 (99.206) +2022-11-14 14:15:39,162 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0767) Prec@1 82.000 (87.173) Prec@5 99.000 (99.204) +2022-11-14 14:15:39,170 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0769) Prec@1 86.000 (87.162) Prec@5 100.000 (99.212) +2022-11-14 14:15:39,179 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0770) Prec@1 86.000 (87.150) Prec@5 98.000 (99.200) +2022-11-14 14:15:39,235 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:15:39,553 Epoch: [171][0/500] Time 0.026 (0.026) Data 0.228 (0.228) Loss 0.0404 (0.0404) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:15:39,793 Epoch: [171][10/500] Time 0.021 (0.022) Data 0.002 (0.023) Loss 0.0366 (0.0385) Prec@1 94.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:15:40,027 Epoch: [171][20/500] Time 0.025 (0.021) Data 0.002 (0.013) Loss 0.0412 (0.0394) Prec@1 93.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:15:40,338 Epoch: [171][30/500] Time 0.027 (0.023) Data 0.002 (0.009) Loss 0.0669 (0.0463) Prec@1 91.000 (92.250) Prec@5 98.000 (99.500) +2022-11-14 14:15:40,613 Epoch: [171][40/500] Time 0.026 (0.023) Data 0.001 (0.007) Loss 0.0497 (0.0469) Prec@1 93.000 (92.400) Prec@5 100.000 (99.600) +2022-11-14 14:15:40,946 Epoch: [171][50/500] Time 0.044 (0.025) Data 0.002 (0.006) Loss 0.0769 (0.0519) Prec@1 86.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:15:41,251 Epoch: [171][60/500] Time 0.039 (0.025) Data 0.002 (0.005) Loss 0.0431 (0.0507) Prec@1 92.000 (91.429) Prec@5 100.000 (99.714) +2022-11-14 14:15:41,743 Epoch: [171][70/500] Time 0.042 (0.027) Data 0.002 (0.005) Loss 0.0933 (0.0560) Prec@1 85.000 (90.625) Prec@5 97.000 (99.375) +2022-11-14 14:15:42,247 Epoch: [171][80/500] Time 0.043 (0.029) Data 0.002 (0.005) Loss 0.0646 (0.0570) Prec@1 90.000 (90.556) Prec@5 98.000 (99.222) +2022-11-14 14:15:42,741 Epoch: [171][90/500] Time 0.049 (0.031) Data 0.002 (0.004) Loss 0.1035 (0.0616) Prec@1 84.000 (89.900) Prec@5 96.000 (98.900) +2022-11-14 14:15:43,206 Epoch: [171][100/500] Time 0.043 (0.032) Data 0.002 (0.004) Loss 0.0500 (0.0606) Prec@1 91.000 (90.000) Prec@5 100.000 (99.000) +2022-11-14 14:15:43,710 Epoch: [171][110/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0399 (0.0588) Prec@1 91.000 (90.083) Prec@5 100.000 (99.083) +2022-11-14 14:15:44,181 Epoch: [171][120/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0609 (0.0590) Prec@1 90.000 (90.077) Prec@5 99.000 (99.077) +2022-11-14 14:15:44,702 Epoch: [171][130/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0469 (0.0581) Prec@1 92.000 (90.214) Prec@5 100.000 (99.143) +2022-11-14 14:15:45,208 Epoch: [171][140/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0491 (0.0575) Prec@1 91.000 (90.267) Prec@5 100.000 (99.200) +2022-11-14 14:15:45,685 Epoch: [171][150/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0708 (0.0584) Prec@1 88.000 (90.125) Prec@5 100.000 (99.250) +2022-11-14 14:15:46,173 Epoch: [171][160/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0361 (0.0570) Prec@1 95.000 (90.412) Prec@5 100.000 (99.294) +2022-11-14 14:15:46,654 Epoch: [171][170/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0453 (0.0564) Prec@1 92.000 (90.500) Prec@5 100.000 (99.333) +2022-11-14 14:15:47,116 Epoch: [171][180/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0601 (0.0566) Prec@1 89.000 (90.421) Prec@5 100.000 (99.368) +2022-11-14 14:15:47,578 Epoch: [171][190/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0214 (0.0548) Prec@1 96.000 (90.700) Prec@5 100.000 (99.400) +2022-11-14 14:15:48,051 Epoch: [171][200/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0586 (0.0550) Prec@1 91.000 (90.714) Prec@5 100.000 (99.429) +2022-11-14 14:15:48,509 Epoch: [171][210/500] Time 0.039 (0.038) Data 0.003 (0.003) Loss 0.0449 (0.0545) Prec@1 93.000 (90.818) Prec@5 99.000 (99.409) +2022-11-14 14:15:48,974 Epoch: [171][220/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0456 (0.0542) Prec@1 92.000 (90.870) Prec@5 100.000 (99.435) +2022-11-14 14:15:49,435 Epoch: [171][230/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0585 (0.0543) Prec@1 91.000 (90.875) Prec@5 100.000 (99.458) +2022-11-14 14:15:49,919 Epoch: [171][240/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0348 (0.0536) Prec@1 94.000 (91.000) Prec@5 100.000 (99.480) +2022-11-14 14:15:50,392 Epoch: [171][250/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.0342 (0.0528) Prec@1 93.000 (91.077) Prec@5 100.000 (99.500) +2022-11-14 14:15:50,873 Epoch: [171][260/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0647 (0.0533) Prec@1 89.000 (91.000) Prec@5 99.000 (99.481) +2022-11-14 14:15:51,357 Epoch: [171][270/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0385 (0.0527) Prec@1 95.000 (91.143) Prec@5 100.000 (99.500) +2022-11-14 14:15:51,838 Epoch: [171][280/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0625 (0.0531) Prec@1 89.000 (91.069) Prec@5 100.000 (99.517) +2022-11-14 14:15:52,324 Epoch: [171][290/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0349 (0.0525) Prec@1 95.000 (91.200) Prec@5 100.000 (99.533) +2022-11-14 14:15:52,788 Epoch: [171][300/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0171 (0.0513) Prec@1 98.000 (91.419) Prec@5 100.000 (99.548) +2022-11-14 14:15:53,252 Epoch: [171][310/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0398 (0.0510) Prec@1 94.000 (91.500) Prec@5 100.000 (99.562) +2022-11-14 14:15:53,709 Epoch: [171][320/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0667 (0.0514) Prec@1 87.000 (91.364) Prec@5 100.000 (99.576) +2022-11-14 14:15:54,227 Epoch: [171][330/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0344 (0.0509) Prec@1 95.000 (91.471) Prec@5 99.000 (99.559) +2022-11-14 14:15:54,777 Epoch: [171][340/500] Time 0.032 (0.040) Data 0.002 (0.003) Loss 0.0412 (0.0507) Prec@1 93.000 (91.514) Prec@5 100.000 (99.571) +2022-11-14 14:15:55,250 Epoch: [171][350/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0421 (0.0504) Prec@1 93.000 (91.556) Prec@5 100.000 (99.583) +2022-11-14 14:15:55,881 Epoch: [171][360/500] Time 0.059 (0.040) Data 0.002 (0.003) Loss 0.0457 (0.0503) Prec@1 94.000 (91.622) Prec@5 99.000 (99.568) +2022-11-14 14:15:56,324 Epoch: [171][370/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0503 (0.0503) Prec@1 90.000 (91.579) Prec@5 100.000 (99.579) +2022-11-14 14:15:56,833 Epoch: [171][380/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0375 (0.0500) Prec@1 94.000 (91.641) Prec@5 100.000 (99.590) +2022-11-14 14:15:57,418 Epoch: [171][390/500] Time 0.072 (0.041) Data 0.002 (0.002) Loss 0.0440 (0.0498) Prec@1 93.000 (91.675) Prec@5 99.000 (99.575) +2022-11-14 14:15:57,920 Epoch: [171][400/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0467 (0.0497) Prec@1 94.000 (91.732) Prec@5 100.000 (99.585) +2022-11-14 14:15:58,432 Epoch: [171][410/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0631 (0.0501) Prec@1 89.000 (91.667) Prec@5 99.000 (99.571) +2022-11-14 14:15:58,941 Epoch: [171][420/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0503 (0.0501) Prec@1 92.000 (91.674) Prec@5 99.000 (99.558) +2022-11-14 14:15:59,453 Epoch: [171][430/500] Time 0.043 (0.041) Data 0.001 (0.002) Loss 0.0731 (0.0506) Prec@1 86.000 (91.545) Prec@5 100.000 (99.568) +2022-11-14 14:15:59,961 Epoch: [171][440/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0344 (0.0502) Prec@1 96.000 (91.644) Prec@5 100.000 (99.578) +2022-11-14 14:16:00,464 Epoch: [171][450/500] Time 0.042 (0.041) Data 0.003 (0.002) Loss 0.0548 (0.0503) Prec@1 92.000 (91.652) Prec@5 99.000 (99.565) +2022-11-14 14:16:00,956 Epoch: [171][460/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0223 (0.0497) Prec@1 97.000 (91.766) Prec@5 100.000 (99.574) +2022-11-14 14:16:01,458 Epoch: [171][470/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0338 (0.0494) Prec@1 95.000 (91.833) Prec@5 100.000 (99.583) +2022-11-14 14:16:01,966 Epoch: [171][480/500] Time 0.044 (0.042) Data 0.001 (0.002) Loss 0.0712 (0.0498) Prec@1 88.000 (91.755) Prec@5 98.000 (99.551) +2022-11-14 14:16:02,464 Epoch: [171][490/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0492 (0.0498) Prec@1 90.000 (91.720) Prec@5 99.000 (99.540) +2022-11-14 14:16:02,917 Epoch: [171][499/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0619 (0.0501) Prec@1 89.000 (91.667) Prec@5 100.000 (99.549) +2022-11-14 14:16:03,226 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0748 (0.0748) Prec@1 84.000 (84.000) Prec@5 99.000 (99.000) +2022-11-14 14:16:03,238 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0797 (0.0772) Prec@1 85.000 (84.500) Prec@5 99.000 (99.000) +2022-11-14 14:16:03,251 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0769 (0.0771) Prec@1 88.000 (85.667) Prec@5 100.000 (99.333) +2022-11-14 14:16:03,264 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0597 (0.0728) Prec@1 90.000 (86.750) Prec@5 99.000 (99.250) +2022-11-14 14:16:03,272 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0760 (0.0734) Prec@1 85.000 (86.400) Prec@5 100.000 (99.400) +2022-11-14 14:16:03,279 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0702) Prec@1 91.000 (87.167) Prec@5 99.000 (99.333) +2022-11-14 14:16:03,288 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0553 (0.0681) Prec@1 91.000 (87.714) Prec@5 99.000 (99.286) +2022-11-14 14:16:03,298 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0708) Prec@1 86.000 (87.500) Prec@5 100.000 (99.375) +2022-11-14 14:16:03,307 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0733) Prec@1 85.000 (87.222) Prec@5 100.000 (99.444) +2022-11-14 14:16:03,314 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0729) Prec@1 88.000 (87.300) Prec@5 98.000 (99.300) +2022-11-14 14:16:03,323 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0709) Prec@1 90.000 (87.545) Prec@5 100.000 (99.364) +2022-11-14 14:16:03,332 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0730) Prec@1 83.000 (87.167) Prec@5 99.000 (99.333) +2022-11-14 14:16:03,343 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0446 (0.0708) Prec@1 93.000 (87.615) Prec@5 100.000 (99.385) +2022-11-14 14:16:03,352 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0697) Prec@1 88.000 (87.643) Prec@5 100.000 (99.429) +2022-11-14 14:16:03,362 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0700) Prec@1 87.000 (87.600) Prec@5 100.000 (99.467) +2022-11-14 14:16:03,371 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0705) Prec@1 88.000 (87.625) Prec@5 100.000 (99.500) +2022-11-14 14:16:03,380 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0432 (0.0689) Prec@1 93.000 (87.941) Prec@5 99.000 (99.471) +2022-11-14 14:16:03,390 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0709) Prec@1 84.000 (87.722) Prec@5 100.000 (99.500) +2022-11-14 14:16:03,399 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0720) Prec@1 85.000 (87.579) Prec@5 98.000 (99.421) +2022-11-14 14:16:03,409 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0726) Prec@1 88.000 (87.600) Prec@5 97.000 (99.300) +2022-11-14 14:16:03,418 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0737) Prec@1 87.000 (87.571) Prec@5 98.000 (99.238) +2022-11-14 14:16:03,426 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0742) Prec@1 87.000 (87.545) Prec@5 99.000 (99.227) +2022-11-14 14:16:03,434 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0752) Prec@1 84.000 (87.391) Prec@5 100.000 (99.261) +2022-11-14 14:16:03,443 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0747) Prec@1 89.000 (87.458) Prec@5 100.000 (99.292) +2022-11-14 14:16:03,452 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0745) Prec@1 91.000 (87.600) Prec@5 99.000 (99.280) +2022-11-14 14:16:03,461 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0751) Prec@1 84.000 (87.462) Prec@5 98.000 (99.231) +2022-11-14 14:16:03,472 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0743) Prec@1 91.000 (87.593) Prec@5 100.000 (99.259) +2022-11-14 14:16:03,482 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0739) Prec@1 91.000 (87.714) Prec@5 99.000 (99.250) +2022-11-14 14:16:03,494 Test: [28/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0504 (0.0731) Prec@1 94.000 (87.931) Prec@5 99.000 (99.241) +2022-11-14 14:16:03,507 Test: [29/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0731) Prec@1 88.000 (87.933) Prec@5 100.000 (99.267) +2022-11-14 14:16:03,520 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0727) Prec@1 90.000 (88.000) Prec@5 99.000 (99.258) +2022-11-14 14:16:03,533 Test: [31/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0724) Prec@1 88.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 14:16:03,544 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0724) Prec@1 88.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 14:16:03,556 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0727) Prec@1 85.000 (87.912) Prec@5 100.000 (99.294) +2022-11-14 14:16:03,565 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0727) Prec@1 88.000 (87.914) Prec@5 98.000 (99.257) +2022-11-14 14:16:03,575 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0726) Prec@1 88.000 (87.917) Prec@5 100.000 (99.278) +2022-11-14 14:16:03,584 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0723) Prec@1 89.000 (87.946) Prec@5 99.000 (99.270) +2022-11-14 14:16:03,593 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0730) Prec@1 82.000 (87.789) Prec@5 98.000 (99.237) +2022-11-14 14:16:03,603 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0723) Prec@1 93.000 (87.923) Prec@5 99.000 (99.231) +2022-11-14 14:16:03,614 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0722) Prec@1 90.000 (87.975) Prec@5 99.000 (99.225) +2022-11-14 14:16:03,624 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0726) Prec@1 87.000 (87.951) Prec@5 98.000 (99.195) +2022-11-14 14:16:03,635 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0726) Prec@1 90.000 (88.000) Prec@5 99.000 (99.190) +2022-11-14 14:16:03,646 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0341 (0.0717) Prec@1 95.000 (88.163) Prec@5 100.000 (99.209) +2022-11-14 14:16:03,655 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0720) Prec@1 85.000 (88.091) Prec@5 98.000 (99.182) +2022-11-14 14:16:03,665 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0722) Prec@1 86.000 (88.044) Prec@5 100.000 (99.200) +2022-11-14 14:16:03,674 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0728) Prec@1 81.000 (87.891) Prec@5 98.000 (99.174) +2022-11-14 14:16:03,683 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0731) Prec@1 83.000 (87.787) Prec@5 100.000 (99.191) +2022-11-14 14:16:03,696 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0734) Prec@1 84.000 (87.708) Prec@5 100.000 (99.208) +2022-11-14 14:16:03,708 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0281 (0.0725) Prec@1 97.000 (87.898) Prec@5 100.000 (99.224) +2022-11-14 14:16:03,717 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.0733) Prec@1 84.000 (87.820) Prec@5 99.000 (99.220) +2022-11-14 14:16:03,726 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0729) Prec@1 89.000 (87.843) Prec@5 100.000 (99.235) +2022-11-14 14:16:03,739 Test: [51/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0730) Prec@1 86.000 (87.808) Prec@5 100.000 (99.250) +2022-11-14 14:16:03,752 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0728) Prec@1 88.000 (87.811) Prec@5 99.000 (99.245) +2022-11-14 14:16:03,761 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0729) Prec@1 86.000 (87.778) Prec@5 100.000 (99.259) +2022-11-14 14:16:03,771 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0729) Prec@1 91.000 (87.836) Prec@5 100.000 (99.273) +2022-11-14 14:16:03,780 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0729) Prec@1 88.000 (87.839) Prec@5 99.000 (99.268) +2022-11-14 14:16:03,790 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0734) Prec@1 82.000 (87.737) Prec@5 99.000 (99.263) +2022-11-14 14:16:03,800 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0733) Prec@1 91.000 (87.793) Prec@5 100.000 (99.276) +2022-11-14 14:16:03,809 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0737) Prec@1 84.000 (87.729) Prec@5 100.000 (99.288) +2022-11-14 14:16:03,819 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0741) Prec@1 84.000 (87.667) Prec@5 99.000 (99.283) +2022-11-14 14:16:03,828 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0745) Prec@1 86.000 (87.639) Prec@5 99.000 (99.279) +2022-11-14 14:16:03,837 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0747) Prec@1 86.000 (87.613) Prec@5 100.000 (99.290) +2022-11-14 14:16:03,846 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0747) Prec@1 88.000 (87.619) Prec@5 100.000 (99.302) +2022-11-14 14:16:03,856 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0744) Prec@1 91.000 (87.672) Prec@5 99.000 (99.297) +2022-11-14 14:16:03,866 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0746) Prec@1 85.000 (87.631) Prec@5 100.000 (99.308) +2022-11-14 14:16:03,876 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0748) Prec@1 86.000 (87.606) Prec@5 98.000 (99.288) +2022-11-14 14:16:03,886 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0743) Prec@1 92.000 (87.672) Prec@5 100.000 (99.299) +2022-11-14 14:16:03,896 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0743) Prec@1 90.000 (87.706) Prec@5 100.000 (99.309) +2022-11-14 14:16:03,905 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0744) Prec@1 88.000 (87.710) Prec@5 99.000 (99.304) +2022-11-14 14:16:03,914 Test: [69/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0748) Prec@1 85.000 (87.671) Prec@5 98.000 (99.286) +2022-11-14 14:16:03,923 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0750) Prec@1 88.000 (87.676) Prec@5 99.000 (99.282) +2022-11-14 14:16:03,933 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0748) Prec@1 89.000 (87.694) Prec@5 100.000 (99.292) +2022-11-14 14:16:03,941 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0745) Prec@1 92.000 (87.753) Prec@5 98.000 (99.274) +2022-11-14 14:16:03,951 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0743) Prec@1 92.000 (87.811) Prec@5 100.000 (99.284) +2022-11-14 14:16:03,960 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0748) Prec@1 82.000 (87.733) Prec@5 98.000 (99.267) +2022-11-14 14:16:03,971 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0746) Prec@1 90.000 (87.763) Prec@5 100.000 (99.276) +2022-11-14 14:16:03,980 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0745) Prec@1 90.000 (87.792) Prec@5 98.000 (99.260) +2022-11-14 14:16:03,990 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0747) Prec@1 84.000 (87.744) Prec@5 97.000 (99.231) +2022-11-14 14:16:03,999 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0749) Prec@1 86.000 (87.722) Prec@5 100.000 (99.241) +2022-11-14 14:16:04,009 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0749) Prec@1 87.000 (87.713) Prec@5 99.000 (99.237) +2022-11-14 14:16:04,018 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0750) Prec@1 84.000 (87.667) Prec@5 99.000 (99.235) +2022-11-14 14:16:04,027 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0752) Prec@1 88.000 (87.671) Prec@5 100.000 (99.244) +2022-11-14 14:16:04,036 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0753) Prec@1 86.000 (87.651) Prec@5 99.000 (99.241) +2022-11-14 14:16:04,045 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0753) Prec@1 86.000 (87.631) Prec@5 100.000 (99.250) +2022-11-14 14:16:04,055 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0753) Prec@1 86.000 (87.612) Prec@5 100.000 (99.259) +2022-11-14 14:16:04,063 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0755) Prec@1 85.000 (87.581) Prec@5 99.000 (99.256) +2022-11-14 14:16:04,072 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0756) Prec@1 87.000 (87.575) Prec@5 99.000 (99.253) +2022-11-14 14:16:04,082 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0754) Prec@1 91.000 (87.614) Prec@5 99.000 (99.250) +2022-11-14 14:16:04,091 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0754) Prec@1 87.000 (87.607) Prec@5 99.000 (99.247) +2022-11-14 14:16:04,100 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0755) Prec@1 86.000 (87.589) Prec@5 99.000 (99.244) +2022-11-14 14:16:04,110 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0754) Prec@1 89.000 (87.604) Prec@5 100.000 (99.253) +2022-11-14 14:16:04,119 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0751) Prec@1 93.000 (87.663) Prec@5 100.000 (99.261) +2022-11-14 14:16:04,128 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0753) Prec@1 84.000 (87.624) Prec@5 100.000 (99.269) +2022-11-14 14:16:04,137 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0752) Prec@1 89.000 (87.638) Prec@5 99.000 (99.266) +2022-11-14 14:16:04,147 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0753) Prec@1 85.000 (87.611) Prec@5 99.000 (99.263) +2022-11-14 14:16:04,155 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0463 (0.0750) Prec@1 93.000 (87.667) Prec@5 100.000 (99.271) +2022-11-14 14:16:04,165 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0486 (0.0747) Prec@1 92.000 (87.711) Prec@5 99.000 (99.268) +2022-11-14 14:16:04,175 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0747) Prec@1 87.000 (87.704) Prec@5 98.000 (99.255) +2022-11-14 14:16:04,183 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0749) Prec@1 87.000 (87.697) Prec@5 99.000 (99.253) +2022-11-14 14:16:04,193 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0747) Prec@1 88.000 (87.700) Prec@5 100.000 (99.260) +2022-11-14 14:16:04,268 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:16:04,592 Epoch: [172][0/500] Time 0.025 (0.025) Data 0.239 (0.239) Loss 0.0442 (0.0442) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:04,815 Epoch: [172][10/500] Time 0.023 (0.020) Data 0.002 (0.024) Loss 0.0454 (0.0448) Prec@1 92.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:16:05,068 Epoch: [172][20/500] Time 0.019 (0.022) Data 0.002 (0.013) Loss 0.0409 (0.0435) Prec@1 93.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:05,291 Epoch: [172][30/500] Time 0.024 (0.021) Data 0.002 (0.010) Loss 0.0449 (0.0438) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:05,556 Epoch: [172][40/500] Time 0.024 (0.022) Data 0.002 (0.008) Loss 0.0181 (0.0387) Prec@1 96.000 (92.800) Prec@5 100.000 (100.000) +2022-11-14 14:16:05,847 Epoch: [172][50/500] Time 0.030 (0.022) Data 0.002 (0.007) Loss 0.0724 (0.0443) Prec@1 88.000 (92.000) Prec@5 99.000 (99.833) +2022-11-14 14:16:06,137 Epoch: [172][60/500] Time 0.025 (0.023) Data 0.002 (0.006) Loss 0.0522 (0.0454) Prec@1 89.000 (91.571) Prec@5 100.000 (99.857) +2022-11-14 14:16:06,436 Epoch: [172][70/500] Time 0.036 (0.024) Data 0.002 (0.005) Loss 0.0303 (0.0435) Prec@1 95.000 (92.000) Prec@5 100.000 (99.875) +2022-11-14 14:16:06,724 Epoch: [172][80/500] Time 0.025 (0.024) Data 0.002 (0.005) Loss 0.0802 (0.0476) Prec@1 88.000 (91.556) Prec@5 99.000 (99.778) +2022-11-14 14:16:07,011 Epoch: [172][90/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0201 (0.0449) Prec@1 97.000 (92.100) Prec@5 100.000 (99.800) +2022-11-14 14:16:07,299 Epoch: [172][100/500] Time 0.027 (0.024) Data 0.003 (0.004) Loss 0.0281 (0.0433) Prec@1 96.000 (92.455) Prec@5 100.000 (99.818) +2022-11-14 14:16:07,594 Epoch: [172][110/500] Time 0.031 (0.024) Data 0.002 (0.004) Loss 0.0377 (0.0429) Prec@1 93.000 (92.500) Prec@5 100.000 (99.833) +2022-11-14 14:16:07,884 Epoch: [172][120/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0470 (0.0432) Prec@1 92.000 (92.462) Prec@5 100.000 (99.846) +2022-11-14 14:16:08,180 Epoch: [172][130/500] Time 0.026 (0.025) Data 0.002 (0.004) Loss 0.0502 (0.0437) Prec@1 94.000 (92.571) Prec@5 100.000 (99.857) +2022-11-14 14:16:08,571 Epoch: [172][140/500] Time 0.053 (0.025) Data 0.002 (0.004) Loss 0.0348 (0.0431) Prec@1 95.000 (92.733) Prec@5 100.000 (99.867) +2022-11-14 14:16:09,065 Epoch: [172][150/500] Time 0.054 (0.026) Data 0.002 (0.003) Loss 0.0247 (0.0419) Prec@1 97.000 (93.000) Prec@5 100.000 (99.875) +2022-11-14 14:16:09,565 Epoch: [172][160/500] Time 0.051 (0.027) Data 0.002 (0.003) Loss 0.0524 (0.0426) Prec@1 88.000 (92.706) Prec@5 100.000 (99.882) +2022-11-14 14:16:10,055 Epoch: [172][170/500] Time 0.050 (0.028) Data 0.002 (0.003) Loss 0.0326 (0.0420) Prec@1 95.000 (92.833) Prec@5 100.000 (99.889) +2022-11-14 14:16:10,560 Epoch: [172][180/500] Time 0.048 (0.029) Data 0.002 (0.003) Loss 0.0651 (0.0432) Prec@1 90.000 (92.684) Prec@5 99.000 (99.842) +2022-11-14 14:16:11,064 Epoch: [172][190/500] Time 0.053 (0.030) Data 0.003 (0.003) Loss 0.0301 (0.0426) Prec@1 94.000 (92.750) Prec@5 100.000 (99.850) +2022-11-14 14:16:11,538 Epoch: [172][200/500] Time 0.044 (0.031) Data 0.001 (0.003) Loss 0.0482 (0.0428) Prec@1 90.000 (92.619) Prec@5 100.000 (99.857) +2022-11-14 14:16:12,121 Epoch: [172][210/500] Time 0.061 (0.032) Data 0.002 (0.003) Loss 0.0287 (0.0422) Prec@1 95.000 (92.727) Prec@5 100.000 (99.864) +2022-11-14 14:16:12,634 Epoch: [172][220/500] Time 0.052 (0.033) Data 0.002 (0.003) Loss 0.0225 (0.0413) Prec@1 95.000 (92.826) Prec@5 100.000 (99.870) +2022-11-14 14:16:13,175 Epoch: [172][230/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0436 (0.0414) Prec@1 92.000 (92.792) Prec@5 99.000 (99.833) +2022-11-14 14:16:13,689 Epoch: [172][240/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0471 (0.0417) Prec@1 92.000 (92.760) Prec@5 99.000 (99.800) +2022-11-14 14:16:14,206 Epoch: [172][250/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0388 (0.0415) Prec@1 94.000 (92.808) Prec@5 100.000 (99.808) +2022-11-14 14:16:14,694 Epoch: [172][260/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0238 (0.0409) Prec@1 96.000 (92.926) Prec@5 100.000 (99.815) +2022-11-14 14:16:15,199 Epoch: [172][270/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0579 (0.0415) Prec@1 90.000 (92.821) Prec@5 100.000 (99.821) +2022-11-14 14:16:15,697 Epoch: [172][280/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0535 (0.0419) Prec@1 92.000 (92.793) Prec@5 99.000 (99.793) +2022-11-14 14:16:16,184 Epoch: [172][290/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0456 (0.0420) Prec@1 93.000 (92.800) Prec@5 98.000 (99.733) +2022-11-14 14:16:16,680 Epoch: [172][300/500] Time 0.050 (0.036) Data 0.002 (0.003) Loss 0.0311 (0.0417) Prec@1 95.000 (92.871) Prec@5 100.000 (99.742) +2022-11-14 14:16:17,196 Epoch: [172][310/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0538 (0.0421) Prec@1 91.000 (92.812) Prec@5 100.000 (99.750) +2022-11-14 14:16:17,679 Epoch: [172][320/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0697 (0.0429) Prec@1 88.000 (92.667) Prec@5 100.000 (99.758) +2022-11-14 14:16:18,195 Epoch: [172][330/500] Time 0.085 (0.037) Data 0.002 (0.003) Loss 0.0450 (0.0430) Prec@1 91.000 (92.618) Prec@5 100.000 (99.765) +2022-11-14 14:16:18,694 Epoch: [172][340/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0480 (0.0431) Prec@1 90.000 (92.543) Prec@5 100.000 (99.771) +2022-11-14 14:16:19,217 Epoch: [172][350/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0473 (0.0432) Prec@1 93.000 (92.556) Prec@5 100.000 (99.778) +2022-11-14 14:16:19,681 Epoch: [172][360/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0339 (0.0430) Prec@1 94.000 (92.595) Prec@5 100.000 (99.784) +2022-11-14 14:16:20,234 Epoch: [172][370/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0414 (0.0429) Prec@1 92.000 (92.579) Prec@5 100.000 (99.789) +2022-11-14 14:16:20,785 Epoch: [172][380/500] Time 0.117 (0.038) Data 0.002 (0.003) Loss 0.0467 (0.0430) Prec@1 94.000 (92.615) Prec@5 99.000 (99.769) +2022-11-14 14:16:21,266 Epoch: [172][390/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0402 (0.0430) Prec@1 93.000 (92.625) Prec@5 99.000 (99.750) +2022-11-14 14:16:21,809 Epoch: [172][400/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0287 (0.0426) Prec@1 95.000 (92.683) Prec@5 100.000 (99.756) +2022-11-14 14:16:22,378 Epoch: [172][410/500] Time 0.048 (0.039) Data 0.002 (0.002) Loss 0.0462 (0.0427) Prec@1 93.000 (92.690) Prec@5 98.000 (99.714) +2022-11-14 14:16:22,856 Epoch: [172][420/500] Time 0.044 (0.039) Data 0.002 (0.002) Loss 0.0588 (0.0431) Prec@1 91.000 (92.651) Prec@5 99.000 (99.698) +2022-11-14 14:16:23,338 Epoch: [172][430/500] Time 0.045 (0.039) Data 0.002 (0.002) Loss 0.0549 (0.0433) Prec@1 91.000 (92.614) Prec@5 99.000 (99.682) +2022-11-14 14:16:23,818 Epoch: [172][440/500] Time 0.042 (0.039) Data 0.002 (0.002) Loss 0.0492 (0.0435) Prec@1 90.000 (92.556) Prec@5 100.000 (99.689) +2022-11-14 14:16:24,337 Epoch: [172][450/500] Time 0.055 (0.039) Data 0.002 (0.002) Loss 0.0331 (0.0432) Prec@1 94.000 (92.587) Prec@5 100.000 (99.696) +2022-11-14 14:16:24,844 Epoch: [172][460/500] Time 0.050 (0.039) Data 0.002 (0.002) Loss 0.0535 (0.0435) Prec@1 90.000 (92.532) Prec@5 99.000 (99.681) +2022-11-14 14:16:25,319 Epoch: [172][470/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0400 (0.0434) Prec@1 91.000 (92.500) Prec@5 99.000 (99.667) +2022-11-14 14:16:25,781 Epoch: [172][480/500] Time 0.043 (0.039) Data 0.001 (0.002) Loss 0.0492 (0.0435) Prec@1 93.000 (92.510) Prec@5 100.000 (99.673) +2022-11-14 14:16:26,338 Epoch: [172][490/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0913 (0.0445) Prec@1 86.000 (92.380) Prec@5 100.000 (99.680) +2022-11-14 14:16:26,849 Epoch: [172][499/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0776 (0.0451) Prec@1 86.000 (92.255) Prec@5 99.000 (99.667) +2022-11-14 14:16:27,136 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0628 (0.0628) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:27,145 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0687) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:27,153 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0749) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:27,167 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0777) Prec@1 84.000 (86.250) Prec@5 100.000 (100.000) +2022-11-14 14:16:27,174 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0798) Prec@1 86.000 (86.200) Prec@5 99.000 (99.800) +2022-11-14 14:16:27,182 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0759) Prec@1 90.000 (86.833) Prec@5 100.000 (99.833) +2022-11-14 14:16:27,190 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0750) Prec@1 90.000 (87.286) Prec@5 98.000 (99.571) +2022-11-14 14:16:27,201 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0765) Prec@1 86.000 (87.125) Prec@5 100.000 (99.625) +2022-11-14 14:16:27,210 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0766) Prec@1 87.000 (87.111) Prec@5 100.000 (99.667) +2022-11-14 14:16:27,220 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0766) Prec@1 86.000 (87.000) Prec@5 99.000 (99.600) +2022-11-14 14:16:27,230 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0743) Prec@1 92.000 (87.455) Prec@5 100.000 (99.636) +2022-11-14 14:16:27,239 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0772) Prec@1 81.000 (86.917) Prec@5 99.000 (99.583) +2022-11-14 14:16:27,249 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0759) Prec@1 87.000 (86.923) Prec@5 100.000 (99.615) +2022-11-14 14:16:27,258 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0755) Prec@1 88.000 (87.000) Prec@5 100.000 (99.643) +2022-11-14 14:16:27,267 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0758) Prec@1 85.000 (86.867) Prec@5 98.000 (99.533) +2022-11-14 14:16:27,277 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0755) Prec@1 87.000 (86.875) Prec@5 100.000 (99.562) +2022-11-14 14:16:27,287 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0740) Prec@1 94.000 (87.294) Prec@5 98.000 (99.471) +2022-11-14 14:16:27,297 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0751) Prec@1 84.000 (87.111) Prec@5 98.000 (99.389) +2022-11-14 14:16:27,306 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0758) Prec@1 85.000 (87.000) Prec@5 99.000 (99.368) +2022-11-14 14:16:27,315 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0765) Prec@1 87.000 (87.000) Prec@5 96.000 (99.200) +2022-11-14 14:16:27,324 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0769) Prec@1 86.000 (86.952) Prec@5 98.000 (99.143) +2022-11-14 14:16:27,333 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0769) Prec@1 85.000 (86.864) Prec@5 98.000 (99.091) +2022-11-14 14:16:27,340 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0782) Prec@1 83.000 (86.696) Prec@5 100.000 (99.130) +2022-11-14 14:16:27,349 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0769) Prec@1 91.000 (86.875) Prec@5 100.000 (99.167) +2022-11-14 14:16:27,359 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0773) Prec@1 86.000 (86.840) Prec@5 100.000 (99.200) +2022-11-14 14:16:27,370 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0782) Prec@1 85.000 (86.769) Prec@5 98.000 (99.154) +2022-11-14 14:16:27,381 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0769) Prec@1 93.000 (87.000) Prec@5 100.000 (99.185) +2022-11-14 14:16:27,393 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0764) Prec@1 89.000 (87.071) Prec@5 100.000 (99.214) +2022-11-14 14:16:27,404 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0763) Prec@1 87.000 (87.069) Prec@5 99.000 (99.207) +2022-11-14 14:16:27,416 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0761) Prec@1 89.000 (87.133) Prec@5 100.000 (99.233) +2022-11-14 14:16:27,428 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0754) Prec@1 90.000 (87.226) Prec@5 100.000 (99.258) +2022-11-14 14:16:27,439 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0756) Prec@1 88.000 (87.250) Prec@5 99.000 (99.250) +2022-11-14 14:16:27,451 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0752) Prec@1 89.000 (87.303) Prec@5 100.000 (99.273) +2022-11-14 14:16:27,463 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1348 (0.0770) Prec@1 75.000 (86.941) Prec@5 100.000 (99.294) +2022-11-14 14:16:27,474 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0772) Prec@1 89.000 (87.000) Prec@5 98.000 (99.257) +2022-11-14 14:16:27,486 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0769) Prec@1 89.000 (87.056) Prec@5 99.000 (99.250) +2022-11-14 14:16:27,497 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0771) Prec@1 89.000 (87.108) Prec@5 98.000 (99.216) +2022-11-14 14:16:27,507 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0773) Prec@1 87.000 (87.105) Prec@5 100.000 (99.237) +2022-11-14 14:16:27,515 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0769) Prec@1 93.000 (87.256) Prec@5 99.000 (99.231) +2022-11-14 14:16:27,524 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0766) Prec@1 88.000 (87.275) Prec@5 100.000 (99.250) +2022-11-14 14:16:27,533 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0772) Prec@1 85.000 (87.220) Prec@5 98.000 (99.220) +2022-11-14 14:16:27,543 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0770) Prec@1 91.000 (87.310) Prec@5 99.000 (99.214) +2022-11-14 14:16:27,552 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0769) Prec@1 88.000 (87.326) Prec@5 100.000 (99.233) +2022-11-14 14:16:27,561 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0774) Prec@1 84.000 (87.250) Prec@5 99.000 (99.227) +2022-11-14 14:16:27,570 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0771) Prec@1 88.000 (87.267) Prec@5 100.000 (99.244) +2022-11-14 14:16:27,579 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0774) Prec@1 87.000 (87.261) Prec@5 99.000 (99.239) +2022-11-14 14:16:27,587 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0768) Prec@1 91.000 (87.340) Prec@5 100.000 (99.255) +2022-11-14 14:16:27,596 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0775) Prec@1 81.000 (87.208) Prec@5 98.000 (99.229) +2022-11-14 14:16:27,605 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0770) Prec@1 92.000 (87.306) Prec@5 100.000 (99.245) +2022-11-14 14:16:27,614 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0775) Prec@1 85.000 (87.260) Prec@5 99.000 (99.240) +2022-11-14 14:16:27,623 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0775) Prec@1 84.000 (87.196) Prec@5 100.000 (99.255) +2022-11-14 14:16:27,633 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0778) Prec@1 81.000 (87.077) Prec@5 100.000 (99.269) +2022-11-14 14:16:27,642 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0779) Prec@1 88.000 (87.094) Prec@5 99.000 (99.264) +2022-11-14 14:16:27,650 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0780) Prec@1 87.000 (87.093) Prec@5 98.000 (99.241) +2022-11-14 14:16:27,658 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0784) Prec@1 82.000 (87.000) Prec@5 100.000 (99.255) +2022-11-14 14:16:27,666 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0783) Prec@1 87.000 (87.000) Prec@5 99.000 (99.250) +2022-11-14 14:16:27,675 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0786) Prec@1 84.000 (86.947) Prec@5 100.000 (99.263) +2022-11-14 14:16:27,684 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0785) Prec@1 88.000 (86.966) Prec@5 98.000 (99.241) +2022-11-14 14:16:27,693 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.0790) Prec@1 80.000 (86.847) Prec@5 100.000 (99.254) +2022-11-14 14:16:27,703 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0794) Prec@1 83.000 (86.783) Prec@5 99.000 (99.250) +2022-11-14 14:16:27,711 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0796) Prec@1 83.000 (86.721) Prec@5 99.000 (99.246) +2022-11-14 14:16:27,721 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0797) Prec@1 88.000 (86.742) Prec@5 100.000 (99.258) +2022-11-14 14:16:27,729 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0794) Prec@1 88.000 (86.762) Prec@5 100.000 (99.270) +2022-11-14 14:16:27,738 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0792) Prec@1 87.000 (86.766) Prec@5 99.000 (99.266) +2022-11-14 14:16:27,747 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0794) Prec@1 83.000 (86.708) Prec@5 99.000 (99.262) +2022-11-14 14:16:27,756 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0793) Prec@1 88.000 (86.727) Prec@5 99.000 (99.258) +2022-11-14 14:16:27,765 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0789) Prec@1 92.000 (86.806) Prec@5 100.000 (99.269) +2022-11-14 14:16:27,774 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0790) Prec@1 86.000 (86.794) Prec@5 98.000 (99.250) +2022-11-14 14:16:27,783 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0789) Prec@1 88.000 (86.812) Prec@5 97.000 (99.217) +2022-11-14 14:16:27,792 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0789) Prec@1 87.000 (86.814) Prec@5 100.000 (99.229) +2022-11-14 14:16:27,801 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0793) Prec@1 84.000 (86.775) Prec@5 98.000 (99.211) +2022-11-14 14:16:27,810 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0791) Prec@1 89.000 (86.806) Prec@5 100.000 (99.222) +2022-11-14 14:16:27,820 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0788) Prec@1 91.000 (86.863) Prec@5 99.000 (99.219) +2022-11-14 14:16:27,829 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0344 (0.0782) Prec@1 96.000 (86.986) Prec@5 100.000 (99.230) +2022-11-14 14:16:27,837 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0786) Prec@1 83.000 (86.933) Prec@5 100.000 (99.240) +2022-11-14 14:16:27,847 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0785) Prec@1 89.000 (86.961) Prec@5 100.000 (99.250) +2022-11-14 14:16:27,855 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0784) Prec@1 88.000 (86.974) Prec@5 100.000 (99.260) +2022-11-14 14:16:27,867 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0788) Prec@1 80.000 (86.885) Prec@5 97.000 (99.231) +2022-11-14 14:16:27,879 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0787) Prec@1 87.000 (86.886) Prec@5 100.000 (99.241) +2022-11-14 14:16:27,891 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0786) Prec@1 91.000 (86.938) Prec@5 99.000 (99.237) +2022-11-14 14:16:27,903 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0786) Prec@1 84.000 (86.901) Prec@5 98.000 (99.222) +2022-11-14 14:16:27,914 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0787) Prec@1 86.000 (86.890) Prec@5 100.000 (99.232) +2022-11-14 14:16:27,927 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0787) Prec@1 86.000 (86.880) Prec@5 99.000 (99.229) +2022-11-14 14:16:27,938 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0786) Prec@1 86.000 (86.869) Prec@5 99.000 (99.226) +2022-11-14 14:16:27,949 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0786) Prec@1 86.000 (86.859) Prec@5 100.000 (99.235) +2022-11-14 14:16:27,960 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0789) Prec@1 84.000 (86.826) Prec@5 100.000 (99.244) +2022-11-14 14:16:27,971 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0790) Prec@1 87.000 (86.828) Prec@5 99.000 (99.241) +2022-11-14 14:16:27,983 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0787) Prec@1 92.000 (86.886) Prec@5 100.000 (99.250) +2022-11-14 14:16:27,995 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0784) Prec@1 87.000 (86.888) Prec@5 100.000 (99.258) +2022-11-14 14:16:28,006 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0784) Prec@1 89.000 (86.911) Prec@5 99.000 (99.256) +2022-11-14 14:16:28,015 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0782) Prec@1 90.000 (86.945) Prec@5 100.000 (99.264) +2022-11-14 14:16:28,023 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0781) Prec@1 91.000 (86.989) Prec@5 100.000 (99.272) +2022-11-14 14:16:28,033 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0781) Prec@1 88.000 (87.000) Prec@5 100.000 (99.280) +2022-11-14 14:16:28,042 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0780) Prec@1 87.000 (87.000) Prec@5 97.000 (99.255) +2022-11-14 14:16:28,051 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0782) Prec@1 82.000 (86.947) Prec@5 100.000 (99.263) +2022-11-14 14:16:28,060 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0781) Prec@1 90.000 (86.979) Prec@5 100.000 (99.271) +2022-11-14 14:16:28,070 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0778) Prec@1 90.000 (87.010) Prec@5 100.000 (99.278) +2022-11-14 14:16:28,079 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0779) Prec@1 85.000 (86.990) Prec@5 99.000 (99.276) +2022-11-14 14:16:28,088 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0782) Prec@1 83.000 (86.949) Prec@5 100.000 (99.283) +2022-11-14 14:16:28,098 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0780) Prec@1 90.000 (86.980) Prec@5 100.000 (99.290) +2022-11-14 14:16:28,154 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:16:28,481 Epoch: [173][0/500] Time 0.027 (0.027) Data 0.234 (0.234) Loss 0.0652 (0.0652) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:28,697 Epoch: [173][10/500] Time 0.019 (0.020) Data 0.001 (0.023) Loss 0.0404 (0.0528) Prec@1 94.000 (91.500) Prec@5 99.000 (99.500) +2022-11-14 14:16:28,912 Epoch: [173][20/500] Time 0.017 (0.020) Data 0.002 (0.013) Loss 0.0521 (0.0526) Prec@1 92.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:16:29,121 Epoch: [173][30/500] Time 0.018 (0.019) Data 0.002 (0.009) Loss 0.0293 (0.0467) Prec@1 95.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:16:29,376 Epoch: [173][40/500] Time 0.034 (0.020) Data 0.002 (0.007) Loss 0.0393 (0.0453) Prec@1 94.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 14:16:29,667 Epoch: [173][50/500] Time 0.031 (0.021) Data 0.002 (0.006) Loss 0.0287 (0.0425) Prec@1 96.000 (93.333) Prec@5 100.000 (99.833) +2022-11-14 14:16:29,956 Epoch: [173][60/500] Time 0.026 (0.022) Data 0.002 (0.006) Loss 0.0397 (0.0421) Prec@1 93.000 (93.286) Prec@5 100.000 (99.857) +2022-11-14 14:16:30,253 Epoch: [173][70/500] Time 0.031 (0.022) Data 0.002 (0.005) Loss 0.0255 (0.0400) Prec@1 95.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 14:16:30,538 Epoch: [173][80/500] Time 0.025 (0.023) Data 0.002 (0.005) Loss 0.0470 (0.0408) Prec@1 91.000 (93.222) Prec@5 100.000 (99.889) +2022-11-14 14:16:30,865 Epoch: [173][90/500] Time 0.048 (0.023) Data 0.002 (0.004) Loss 0.0594 (0.0427) Prec@1 90.000 (92.900) Prec@5 100.000 (99.900) +2022-11-14 14:16:31,146 Epoch: [173][100/500] Time 0.022 (0.024) Data 0.002 (0.004) Loss 0.0648 (0.0447) Prec@1 89.000 (92.545) Prec@5 100.000 (99.909) +2022-11-14 14:16:31,437 Epoch: [173][110/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0320 (0.0436) Prec@1 94.000 (92.667) Prec@5 100.000 (99.917) +2022-11-14 14:16:31,736 Epoch: [173][120/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0386 (0.0432) Prec@1 92.000 (92.615) Prec@5 100.000 (99.923) +2022-11-14 14:16:32,038 Epoch: [173][130/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0289 (0.0422) Prec@1 98.000 (93.000) Prec@5 100.000 (99.929) +2022-11-14 14:16:32,328 Epoch: [173][140/500] Time 0.028 (0.024) Data 0.001 (0.003) Loss 0.0443 (0.0423) Prec@1 93.000 (93.000) Prec@5 100.000 (99.933) +2022-11-14 14:16:32,683 Epoch: [173][150/500] Time 0.045 (0.025) Data 0.002 (0.003) Loss 0.0542 (0.0431) Prec@1 91.000 (92.875) Prec@5 99.000 (99.875) +2022-11-14 14:16:33,180 Epoch: [173][160/500] Time 0.069 (0.026) Data 0.002 (0.003) Loss 0.0366 (0.0427) Prec@1 96.000 (93.059) Prec@5 100.000 (99.882) +2022-11-14 14:16:33,666 Epoch: [173][170/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0285 (0.0419) Prec@1 94.000 (93.111) Prec@5 100.000 (99.889) +2022-11-14 14:16:34,140 Epoch: [173][180/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0409 (0.0419) Prec@1 92.000 (93.053) Prec@5 100.000 (99.895) +2022-11-14 14:16:34,608 Epoch: [173][190/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0612 (0.0428) Prec@1 89.000 (92.850) Prec@5 99.000 (99.850) +2022-11-14 14:16:35,182 Epoch: [173][200/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0317 (0.0423) Prec@1 93.000 (92.857) Prec@5 100.000 (99.857) +2022-11-14 14:16:35,671 Epoch: [173][210/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0407 (0.0422) Prec@1 93.000 (92.864) Prec@5 100.000 (99.864) +2022-11-14 14:16:36,155 Epoch: [173][220/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0415 (0.0422) Prec@1 92.000 (92.826) Prec@5 100.000 (99.870) +2022-11-14 14:16:36,634 Epoch: [173][230/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0452 (0.0423) Prec@1 93.000 (92.833) Prec@5 100.000 (99.875) +2022-11-14 14:16:37,124 Epoch: [173][240/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0559 (0.0429) Prec@1 91.000 (92.760) Prec@5 99.000 (99.840) +2022-11-14 14:16:37,588 Epoch: [173][250/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0322 (0.0425) Prec@1 94.000 (92.808) Prec@5 100.000 (99.846) +2022-11-14 14:16:38,061 Epoch: [173][260/500] Time 0.053 (0.033) Data 0.002 (0.003) Loss 0.0425 (0.0425) Prec@1 91.000 (92.741) Prec@5 100.000 (99.852) +2022-11-14 14:16:38,606 Epoch: [173][270/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0224 (0.0417) Prec@1 97.000 (92.893) Prec@5 100.000 (99.857) +2022-11-14 14:16:39,235 Epoch: [173][280/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0395 (0.0417) Prec@1 94.000 (92.931) Prec@5 99.000 (99.828) +2022-11-14 14:16:39,790 Epoch: [173][290/500] Time 0.098 (0.034) Data 0.002 (0.003) Loss 0.0481 (0.0419) Prec@1 91.000 (92.867) Prec@5 98.000 (99.767) +2022-11-14 14:16:40,342 Epoch: [173][300/500] Time 0.059 (0.035) Data 0.002 (0.003) Loss 0.0623 (0.0425) Prec@1 89.000 (92.742) Prec@5 98.000 (99.710) +2022-11-14 14:16:40,891 Epoch: [173][310/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0535 (0.0429) Prec@1 91.000 (92.688) Prec@5 99.000 (99.688) +2022-11-14 14:16:41,442 Epoch: [173][320/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0437 (0.0429) Prec@1 92.000 (92.667) Prec@5 100.000 (99.697) +2022-11-14 14:16:41,989 Epoch: [173][330/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0354 (0.0427) Prec@1 95.000 (92.735) Prec@5 100.000 (99.706) +2022-11-14 14:16:42,544 Epoch: [173][340/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0509 (0.0429) Prec@1 92.000 (92.714) Prec@5 100.000 (99.714) +2022-11-14 14:16:43,108 Epoch: [173][350/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0232 (0.0424) Prec@1 98.000 (92.861) Prec@5 100.000 (99.722) +2022-11-14 14:16:43,676 Epoch: [173][360/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0488 (0.0425) Prec@1 90.000 (92.784) Prec@5 100.000 (99.730) +2022-11-14 14:16:44,228 Epoch: [173][370/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0499 (0.0427) Prec@1 90.000 (92.711) Prec@5 98.000 (99.684) +2022-11-14 14:16:44,769 Epoch: [173][380/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0588 (0.0431) Prec@1 89.000 (92.615) Prec@5 100.000 (99.692) +2022-11-14 14:16:45,441 Epoch: [173][390/500] Time 0.096 (0.039) Data 0.002 (0.002) Loss 0.0383 (0.0430) Prec@1 93.000 (92.625) Prec@5 100.000 (99.700) +2022-11-14 14:16:45,818 Epoch: [173][400/500] Time 0.026 (0.039) Data 0.002 (0.002) Loss 0.0377 (0.0429) Prec@1 96.000 (92.707) Prec@5 100.000 (99.707) +2022-11-14 14:16:46,161 Epoch: [173][410/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0457 (0.0430) Prec@1 92.000 (92.690) Prec@5 100.000 (99.714) +2022-11-14 14:16:46,497 Epoch: [173][420/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0267 (0.0426) Prec@1 95.000 (92.744) Prec@5 100.000 (99.721) +2022-11-14 14:16:46,837 Epoch: [173][430/500] Time 0.029 (0.038) Data 0.003 (0.002) Loss 0.0458 (0.0427) Prec@1 92.000 (92.727) Prec@5 100.000 (99.727) +2022-11-14 14:16:47,187 Epoch: [173][440/500] Time 0.025 (0.038) Data 0.003 (0.002) Loss 0.0393 (0.0426) Prec@1 91.000 (92.689) Prec@5 100.000 (99.733) +2022-11-14 14:16:47,508 Epoch: [173][450/500] Time 0.031 (0.038) Data 0.002 (0.002) Loss 0.0338 (0.0424) Prec@1 94.000 (92.717) Prec@5 100.000 (99.739) +2022-11-14 14:16:47,840 Epoch: [173][460/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0403 (0.0423) Prec@1 95.000 (92.766) Prec@5 99.000 (99.723) +2022-11-14 14:16:48,177 Epoch: [173][470/500] Time 0.032 (0.037) Data 0.001 (0.002) Loss 0.0480 (0.0425) Prec@1 93.000 (92.771) Prec@5 100.000 (99.729) +2022-11-14 14:16:48,593 Epoch: [173][480/500] Time 0.034 (0.037) Data 0.003 (0.002) Loss 0.0567 (0.0428) Prec@1 89.000 (92.694) Prec@5 100.000 (99.735) +2022-11-14 14:16:48,921 Epoch: [173][490/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.0470 (0.0428) Prec@1 92.000 (92.680) Prec@5 100.000 (99.740) +2022-11-14 14:16:49,217 Epoch: [173][499/500] Time 0.029 (0.037) Data 0.002 (0.002) Loss 0.0484 (0.0429) Prec@1 94.000 (92.706) Prec@5 100.000 (99.745) +2022-11-14 14:16:49,522 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0471 (0.0471) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 14:16:49,530 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0766 (0.0619) Prec@1 87.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:16:49,539 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0727) Prec@1 87.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:16:49,549 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0729) Prec@1 88.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 14:16:49,558 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0727) Prec@1 89.000 (88.400) Prec@5 100.000 (99.400) +2022-11-14 14:16:49,566 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0412 (0.0674) Prec@1 92.000 (89.000) Prec@5 99.000 (99.333) +2022-11-14 14:16:49,575 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0504 (0.0650) Prec@1 89.000 (89.000) Prec@5 100.000 (99.429) +2022-11-14 14:16:49,586 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0677) Prec@1 85.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:16:49,596 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0711) Prec@1 83.000 (87.889) Prec@5 99.000 (99.444) +2022-11-14 14:16:49,607 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0691) Prec@1 91.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 14:16:49,617 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0682) Prec@1 91.000 (88.455) Prec@5 99.000 (99.364) +2022-11-14 14:16:49,626 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0697) Prec@1 86.000 (88.250) Prec@5 99.000 (99.333) +2022-11-14 14:16:49,636 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0684) Prec@1 89.000 (88.308) Prec@5 100.000 (99.385) +2022-11-14 14:16:49,646 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0688) Prec@1 89.000 (88.357) Prec@5 100.000 (99.429) +2022-11-14 14:16:49,656 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0699) Prec@1 86.000 (88.200) Prec@5 100.000 (99.467) +2022-11-14 14:16:49,666 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0711) Prec@1 86.000 (88.062) Prec@5 99.000 (99.438) +2022-11-14 14:16:49,676 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0700) Prec@1 92.000 (88.294) Prec@5 99.000 (99.412) +2022-11-14 14:16:49,686 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0713) Prec@1 84.000 (88.056) Prec@5 100.000 (99.444) +2022-11-14 14:16:49,695 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0715) Prec@1 87.000 (88.000) Prec@5 99.000 (99.421) +2022-11-14 14:16:49,705 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0729) Prec@1 87.000 (87.950) Prec@5 98.000 (99.350) +2022-11-14 14:16:49,714 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0734) Prec@1 85.000 (87.810) Prec@5 100.000 (99.381) +2022-11-14 14:16:49,724 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0727) Prec@1 91.000 (87.955) Prec@5 98.000 (99.318) +2022-11-14 14:16:49,734 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0737) Prec@1 87.000 (87.913) Prec@5 100.000 (99.348) +2022-11-14 14:16:49,744 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0730) Prec@1 92.000 (88.083) Prec@5 99.000 (99.333) +2022-11-14 14:16:49,754 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0739) Prec@1 84.000 (87.920) Prec@5 100.000 (99.360) +2022-11-14 14:16:49,764 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0748) Prec@1 84.000 (87.769) Prec@5 98.000 (99.308) +2022-11-14 14:16:49,773 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0741) Prec@1 92.000 (87.926) Prec@5 100.000 (99.333) +2022-11-14 14:16:49,782 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0740) Prec@1 88.000 (87.929) Prec@5 99.000 (99.321) +2022-11-14 14:16:49,791 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0739) Prec@1 88.000 (87.931) Prec@5 99.000 (99.310) +2022-11-14 14:16:49,799 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 87.000 (87.900) Prec@5 98.000 (99.267) +2022-11-14 14:16:49,809 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0731) Prec@1 93.000 (88.065) Prec@5 100.000 (99.290) +2022-11-14 14:16:49,818 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0731) Prec@1 87.000 (88.031) Prec@5 100.000 (99.312) +2022-11-14 14:16:49,828 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0731) Prec@1 89.000 (88.061) Prec@5 100.000 (99.333) +2022-11-14 14:16:49,837 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0734) Prec@1 85.000 (87.971) Prec@5 100.000 (99.353) +2022-11-14 14:16:49,847 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0739) Prec@1 86.000 (87.914) Prec@5 99.000 (99.343) +2022-11-14 14:16:49,856 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0737) Prec@1 89.000 (87.944) Prec@5 98.000 (99.306) +2022-11-14 14:16:49,865 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0740) Prec@1 88.000 (87.946) Prec@5 99.000 (99.297) +2022-11-14 14:16:49,875 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0749) Prec@1 82.000 (87.789) Prec@5 98.000 (99.263) +2022-11-14 14:16:49,885 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0741) Prec@1 93.000 (87.923) Prec@5 99.000 (99.256) +2022-11-14 14:16:49,894 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0740) Prec@1 89.000 (87.950) Prec@5 99.000 (99.250) +2022-11-14 14:16:49,904 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0743) Prec@1 87.000 (87.927) Prec@5 100.000 (99.268) +2022-11-14 14:16:49,913 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0742) Prec@1 88.000 (87.929) Prec@5 99.000 (99.262) +2022-11-14 14:16:49,922 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0331 (0.0732) Prec@1 94.000 (88.070) Prec@5 100.000 (99.279) +2022-11-14 14:16:49,931 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0729) Prec@1 92.000 (88.159) Prec@5 97.000 (99.227) +2022-11-14 14:16:49,941 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0728) Prec@1 89.000 (88.178) Prec@5 100.000 (99.244) +2022-11-14 14:16:49,951 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0735) Prec@1 83.000 (88.065) Prec@5 100.000 (99.261) +2022-11-14 14:16:49,960 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0730) Prec@1 92.000 (88.149) Prec@5 100.000 (99.277) +2022-11-14 14:16:49,970 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0735) Prec@1 83.000 (88.042) Prec@5 98.000 (99.250) +2022-11-14 14:16:49,979 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0730) Prec@1 93.000 (88.143) Prec@5 100.000 (99.265) +2022-11-14 14:16:49,990 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1196 (0.0739) Prec@1 82.000 (88.020) Prec@5 99.000 (99.260) +2022-11-14 14:16:50,000 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0739) Prec@1 88.000 (88.020) Prec@5 100.000 (99.275) +2022-11-14 14:16:50,010 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0740) Prec@1 89.000 (88.038) Prec@5 98.000 (99.250) +2022-11-14 14:16:50,019 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0737) Prec@1 92.000 (88.113) Prec@5 99.000 (99.245) +2022-11-14 14:16:50,029 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0734) Prec@1 92.000 (88.185) Prec@5 99.000 (99.241) +2022-11-14 14:16:50,038 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0735) Prec@1 88.000 (88.182) Prec@5 100.000 (99.255) +2022-11-14 14:16:50,047 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0735) Prec@1 85.000 (88.125) Prec@5 100.000 (99.268) +2022-11-14 14:16:50,057 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0740) Prec@1 85.000 (88.070) Prec@5 100.000 (99.281) +2022-11-14 14:16:50,066 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0737) Prec@1 91.000 (88.121) Prec@5 100.000 (99.293) +2022-11-14 14:16:50,076 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0738) Prec@1 87.000 (88.102) Prec@5 100.000 (99.305) +2022-11-14 14:16:50,085 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0739) Prec@1 85.000 (88.050) Prec@5 99.000 (99.300) +2022-11-14 14:16:50,095 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0742) Prec@1 85.000 (88.000) Prec@5 99.000 (99.295) +2022-11-14 14:16:50,103 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0746) Prec@1 86.000 (87.968) Prec@5 98.000 (99.274) +2022-11-14 14:16:50,111 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0743) Prec@1 89.000 (87.984) Prec@5 99.000 (99.270) +2022-11-14 14:16:50,120 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0739) Prec@1 93.000 (88.062) Prec@5 100.000 (99.281) +2022-11-14 14:16:50,130 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0744) Prec@1 83.000 (87.985) Prec@5 100.000 (99.292) +2022-11-14 14:16:50,140 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0746) Prec@1 83.000 (87.909) Prec@5 100.000 (99.303) +2022-11-14 14:16:50,149 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0742) Prec@1 93.000 (87.985) Prec@5 100.000 (99.313) +2022-11-14 14:16:50,159 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0742) Prec@1 88.000 (87.985) Prec@5 100.000 (99.324) +2022-11-14 14:16:50,169 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0741) Prec@1 87.000 (87.971) Prec@5 99.000 (99.319) +2022-11-14 14:16:50,181 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0743) Prec@1 87.000 (87.957) Prec@5 99.000 (99.314) +2022-11-14 14:16:50,190 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0743) Prec@1 90.000 (87.986) Prec@5 99.000 (99.310) +2022-11-14 14:16:50,199 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0742) Prec@1 88.000 (87.986) Prec@5 100.000 (99.319) +2022-11-14 14:16:50,209 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0739) Prec@1 92.000 (88.041) Prec@5 100.000 (99.329) +2022-11-14 14:16:50,219 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0737) Prec@1 90.000 (88.068) Prec@5 100.000 (99.338) +2022-11-14 14:16:50,229 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0741) Prec@1 82.000 (87.987) Prec@5 100.000 (99.347) +2022-11-14 14:16:50,239 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0738) Prec@1 91.000 (88.026) Prec@5 100.000 (99.355) +2022-11-14 14:16:50,249 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0738) Prec@1 86.000 (88.000) Prec@5 99.000 (99.351) +2022-11-14 14:16:50,259 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0739) Prec@1 86.000 (87.974) Prec@5 98.000 (99.333) +2022-11-14 14:16:50,269 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0737) Prec@1 87.000 (87.962) Prec@5 100.000 (99.342) +2022-11-14 14:16:50,279 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0738) Prec@1 85.000 (87.925) Prec@5 99.000 (99.338) +2022-11-14 14:16:50,288 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0737) Prec@1 89.000 (87.938) Prec@5 100.000 (99.346) +2022-11-14 14:16:50,298 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0739) Prec@1 85.000 (87.902) Prec@5 99.000 (99.341) +2022-11-14 14:16:50,309 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0740) Prec@1 86.000 (87.880) Prec@5 100.000 (99.349) +2022-11-14 14:16:50,319 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0738) Prec@1 87.000 (87.869) Prec@5 100.000 (99.357) +2022-11-14 14:16:50,330 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0740) Prec@1 85.000 (87.835) Prec@5 99.000 (99.353) +2022-11-14 14:16:50,341 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0744) Prec@1 81.000 (87.756) Prec@5 99.000 (99.349) +2022-11-14 14:16:50,352 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0746) Prec@1 85.000 (87.724) Prec@5 99.000 (99.345) +2022-11-14 14:16:50,364 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0746) Prec@1 88.000 (87.727) Prec@5 100.000 (99.352) +2022-11-14 14:16:50,374 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0746) Prec@1 89.000 (87.742) Prec@5 99.000 (99.348) +2022-11-14 14:16:50,386 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0748) Prec@1 83.000 (87.689) Prec@5 97.000 (99.322) +2022-11-14 14:16:50,397 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0747) Prec@1 90.000 (87.714) Prec@5 100.000 (99.330) +2022-11-14 14:16:50,408 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0460 (0.0743) Prec@1 91.000 (87.750) Prec@5 100.000 (99.337) +2022-11-14 14:16:50,416 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0746) Prec@1 85.000 (87.720) Prec@5 99.000 (99.333) +2022-11-14 14:16:50,424 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0746) Prec@1 87.000 (87.713) Prec@5 97.000 (99.309) +2022-11-14 14:16:50,432 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0747) Prec@1 86.000 (87.695) Prec@5 98.000 (99.295) +2022-11-14 14:16:50,442 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0746) Prec@1 89.000 (87.708) Prec@5 99.000 (99.292) +2022-11-14 14:16:50,451 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0744) Prec@1 91.000 (87.742) Prec@5 99.000 (99.289) +2022-11-14 14:16:50,461 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1149 (0.0748) Prec@1 83.000 (87.694) Prec@5 98.000 (99.276) +2022-11-14 14:16:50,471 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.0752) Prec@1 82.000 (87.636) Prec@5 99.000 (99.273) +2022-11-14 14:16:50,482 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0750) Prec@1 91.000 (87.670) Prec@5 99.000 (99.270) +2022-11-14 14:16:50,541 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:16:50,851 Epoch: [174][0/500] Time 0.023 (0.023) Data 0.226 (0.226) Loss 0.0455 (0.0455) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:16:51,066 Epoch: [174][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0204 (0.0330) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:16:51,302 Epoch: [174][20/500] Time 0.024 (0.020) Data 0.002 (0.012) Loss 0.0312 (0.0324) Prec@1 94.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 14:16:51,597 Epoch: [174][30/500] Time 0.032 (0.022) Data 0.002 (0.009) Loss 0.0527 (0.0375) Prec@1 91.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:16:51,889 Epoch: [174][40/500] Time 0.026 (0.023) Data 0.002 (0.007) Loss 0.0277 (0.0355) Prec@1 95.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:16:52,209 Epoch: [174][50/500] Time 0.031 (0.024) Data 0.002 (0.006) Loss 0.0287 (0.0344) Prec@1 96.000 (94.167) Prec@5 99.000 (99.667) +2022-11-14 14:16:52,537 Epoch: [174][60/500] Time 0.022 (0.025) Data 0.002 (0.006) Loss 0.0570 (0.0376) Prec@1 91.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 14:16:52,861 Epoch: [174][70/500] Time 0.022 (0.025) Data 0.002 (0.005) Loss 0.0324 (0.0369) Prec@1 95.000 (93.875) Prec@5 100.000 (99.750) +2022-11-14 14:16:53,162 Epoch: [174][80/500] Time 0.023 (0.026) Data 0.002 (0.005) Loss 0.0640 (0.0400) Prec@1 89.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:16:53,547 Epoch: [174][90/500] Time 0.062 (0.026) Data 0.002 (0.004) Loss 0.0438 (0.0403) Prec@1 92.000 (93.200) Prec@5 100.000 (99.700) +2022-11-14 14:16:54,135 Epoch: [174][100/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.0275 (0.0392) Prec@1 95.000 (93.364) Prec@5 100.000 (99.727) +2022-11-14 14:16:54,664 Epoch: [174][110/500] Time 0.044 (0.030) Data 0.002 (0.004) Loss 0.0286 (0.0383) Prec@1 96.000 (93.583) Prec@5 100.000 (99.750) +2022-11-14 14:16:55,147 Epoch: [174][120/500] Time 0.042 (0.031) Data 0.002 (0.004) Loss 0.0403 (0.0384) Prec@1 92.000 (93.462) Prec@5 99.000 (99.692) +2022-11-14 14:16:55,707 Epoch: [174][130/500] Time 0.044 (0.033) Data 0.002 (0.004) Loss 0.0391 (0.0385) Prec@1 94.000 (93.500) Prec@5 100.000 (99.714) +2022-11-14 14:16:56,220 Epoch: [174][140/500] Time 0.042 (0.034) Data 0.002 (0.004) Loss 0.0495 (0.0392) Prec@1 92.000 (93.400) Prec@5 100.000 (99.733) +2022-11-14 14:16:56,719 Epoch: [174][150/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0318 (0.0388) Prec@1 95.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:16:57,210 Epoch: [174][160/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0627 (0.0402) Prec@1 87.000 (93.118) Prec@5 100.000 (99.765) +2022-11-14 14:16:57,691 Epoch: [174][170/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0418 (0.0403) Prec@1 94.000 (93.167) Prec@5 100.000 (99.778) +2022-11-14 14:16:58,243 Epoch: [174][180/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0568 (0.0411) Prec@1 89.000 (92.947) Prec@5 100.000 (99.789) +2022-11-14 14:16:58,752 Epoch: [174][190/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0459 (0.0414) Prec@1 93.000 (92.950) Prec@5 99.000 (99.750) +2022-11-14 14:16:59,259 Epoch: [174][200/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0414 (0.0414) Prec@1 93.000 (92.952) Prec@5 99.000 (99.714) +2022-11-14 14:16:59,756 Epoch: [174][210/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0641 (0.0424) Prec@1 90.000 (92.818) Prec@5 97.000 (99.591) +2022-11-14 14:17:00,320 Epoch: [174][220/500] Time 0.111 (0.038) Data 0.003 (0.003) Loss 0.0513 (0.0428) Prec@1 90.000 (92.696) Prec@5 98.000 (99.522) +2022-11-14 14:17:00,794 Epoch: [174][230/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0389 (0.0426) Prec@1 94.000 (92.750) Prec@5 99.000 (99.500) +2022-11-14 14:17:01,381 Epoch: [174][240/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0273 (0.0420) Prec@1 97.000 (92.920) Prec@5 100.000 (99.520) +2022-11-14 14:17:01,857 Epoch: [174][250/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0385 (0.0419) Prec@1 93.000 (92.923) Prec@5 100.000 (99.538) +2022-11-14 14:17:02,431 Epoch: [174][260/500] Time 0.092 (0.040) Data 0.002 (0.003) Loss 0.0506 (0.0422) Prec@1 93.000 (92.926) Prec@5 100.000 (99.556) +2022-11-14 14:17:02,906 Epoch: [174][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0387 (0.0421) Prec@1 94.000 (92.964) Prec@5 99.000 (99.536) +2022-11-14 14:17:03,447 Epoch: [174][280/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0511 (0.0424) Prec@1 91.000 (92.897) Prec@5 99.000 (99.517) +2022-11-14 14:17:03,920 Epoch: [174][290/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0309 (0.0420) Prec@1 95.000 (92.967) Prec@5 99.000 (99.500) +2022-11-14 14:17:04,491 Epoch: [174][300/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0458 (0.0421) Prec@1 92.000 (92.935) Prec@5 100.000 (99.516) +2022-11-14 14:17:04,980 Epoch: [174][310/500] Time 0.044 (0.041) Data 0.001 (0.003) Loss 0.0591 (0.0427) Prec@1 91.000 (92.875) Prec@5 99.000 (99.500) +2022-11-14 14:17:05,468 Epoch: [174][320/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0544 (0.0430) Prec@1 91.000 (92.818) Prec@5 100.000 (99.515) +2022-11-14 14:17:06,069 Epoch: [174][330/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0403 (0.0429) Prec@1 95.000 (92.882) Prec@5 100.000 (99.529) +2022-11-14 14:17:06,705 Epoch: [174][340/500] Time 0.028 (0.042) Data 0.002 (0.003) Loss 0.0391 (0.0428) Prec@1 94.000 (92.914) Prec@5 100.000 (99.543) +2022-11-14 14:17:07,069 Epoch: [174][350/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0241 (0.0423) Prec@1 97.000 (93.028) Prec@5 100.000 (99.556) +2022-11-14 14:17:07,388 Epoch: [174][360/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0304 (0.0420) Prec@1 94.000 (93.054) Prec@5 100.000 (99.568) +2022-11-14 14:17:07,786 Epoch: [174][370/500] Time 0.023 (0.041) Data 0.002 (0.003) Loss 0.0359 (0.0418) Prec@1 96.000 (93.132) Prec@5 100.000 (99.579) +2022-11-14 14:17:08,110 Epoch: [174][380/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0263 (0.0414) Prec@1 96.000 (93.205) Prec@5 99.000 (99.564) +2022-11-14 14:17:08,506 Epoch: [174][390/500] Time 0.023 (0.041) Data 0.002 (0.003) Loss 0.0552 (0.0418) Prec@1 93.000 (93.200) Prec@5 100.000 (99.575) +2022-11-14 14:17:08,926 Epoch: [174][400/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0460 (0.0419) Prec@1 94.000 (93.220) Prec@5 100.000 (99.585) +2022-11-14 14:17:09,240 Epoch: [174][410/500] Time 0.030 (0.040) Data 0.002 (0.003) Loss 0.0740 (0.0426) Prec@1 88.000 (93.095) Prec@5 100.000 (99.595) +2022-11-14 14:17:09,565 Epoch: [174][420/500] Time 0.031 (0.040) Data 0.002 (0.002) Loss 0.0687 (0.0432) Prec@1 92.000 (93.070) Prec@5 99.000 (99.581) +2022-11-14 14:17:09,954 Epoch: [174][430/500] Time 0.057 (0.040) Data 0.002 (0.002) Loss 0.0653 (0.0438) Prec@1 90.000 (93.000) Prec@5 98.000 (99.545) +2022-11-14 14:17:10,272 Epoch: [174][440/500] Time 0.033 (0.039) Data 0.002 (0.002) Loss 0.0411 (0.0437) Prec@1 93.000 (93.000) Prec@5 100.000 (99.556) +2022-11-14 14:17:10,596 Epoch: [174][450/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0306 (0.0434) Prec@1 94.000 (93.022) Prec@5 100.000 (99.565) +2022-11-14 14:17:10,926 Epoch: [174][460/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.0265 (0.0430) Prec@1 95.000 (93.064) Prec@5 99.000 (99.553) +2022-11-14 14:17:11,260 Epoch: [174][470/500] Time 0.030 (0.039) Data 0.002 (0.002) Loss 0.0511 (0.0432) Prec@1 90.000 (93.000) Prec@5 100.000 (99.562) +2022-11-14 14:17:11,603 Epoch: [174][480/500] Time 0.031 (0.039) Data 0.002 (0.002) Loss 0.0642 (0.0436) Prec@1 89.000 (92.918) Prec@5 99.000 (99.551) +2022-11-14 14:17:11,951 Epoch: [174][490/500] Time 0.035 (0.038) Data 0.002 (0.002) Loss 0.0438 (0.0436) Prec@1 91.000 (92.880) Prec@5 99.000 (99.540) +2022-11-14 14:17:12,293 Epoch: [174][499/500] Time 0.030 (0.038) Data 0.002 (0.002) Loss 0.0440 (0.0437) Prec@1 93.000 (92.882) Prec@5 99.000 (99.529) +2022-11-14 14:17:12,584 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0657 (0.0657) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:17:12,593 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0742) Prec@1 88.000 (89.500) Prec@5 98.000 (99.000) +2022-11-14 14:17:12,605 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0724) Prec@1 90.000 (89.667) Prec@5 98.000 (98.667) +2022-11-14 14:17:12,617 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0701) Prec@1 90.000 (89.750) Prec@5 99.000 (98.750) +2022-11-14 14:17:12,624 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0714) Prec@1 87.000 (89.200) Prec@5 99.000 (98.800) +2022-11-14 14:17:12,632 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0689) Prec@1 89.000 (89.167) Prec@5 100.000 (99.000) +2022-11-14 14:17:12,639 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0709) Prec@1 86.000 (88.714) Prec@5 99.000 (99.000) +2022-11-14 14:17:12,647 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0724) Prec@1 86.000 (88.375) Prec@5 99.000 (99.000) +2022-11-14 14:17:12,658 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0749) Prec@1 86.000 (88.111) Prec@5 100.000 (99.111) +2022-11-14 14:17:12,668 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0746) Prec@1 90.000 (88.300) Prec@5 99.000 (99.100) +2022-11-14 14:17:12,678 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0731) Prec@1 89.000 (88.364) Prec@5 100.000 (99.182) +2022-11-14 14:17:12,690 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0751) Prec@1 85.000 (88.083) Prec@5 99.000 (99.167) +2022-11-14 14:17:12,701 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0411 (0.0725) Prec@1 92.000 (88.385) Prec@5 100.000 (99.231) +2022-11-14 14:17:12,711 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0738) Prec@1 86.000 (88.214) Prec@5 99.000 (99.214) +2022-11-14 14:17:12,723 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0744) Prec@1 84.000 (87.933) Prec@5 100.000 (99.267) +2022-11-14 14:17:12,733 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0764) Prec@1 79.000 (87.375) Prec@5 99.000 (99.250) +2022-11-14 14:17:12,745 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0749) Prec@1 93.000 (87.706) Prec@5 99.000 (99.235) +2022-11-14 14:17:12,757 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0765) Prec@1 83.000 (87.444) Prec@5 99.000 (99.222) +2022-11-14 14:17:12,767 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0781) Prec@1 84.000 (87.263) Prec@5 98.000 (99.158) +2022-11-14 14:17:12,779 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0791) Prec@1 86.000 (87.200) Prec@5 98.000 (99.100) +2022-11-14 14:17:12,791 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0804) Prec@1 82.000 (86.952) Prec@5 98.000 (99.048) +2022-11-14 14:17:12,802 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0804) Prec@1 85.000 (86.864) Prec@5 99.000 (99.045) +2022-11-14 14:17:12,814 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0815) Prec@1 85.000 (86.783) Prec@5 100.000 (99.087) +2022-11-14 14:17:12,827 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0805) Prec@1 92.000 (87.000) Prec@5 100.000 (99.125) +2022-11-14 14:17:12,838 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0817) Prec@1 82.000 (86.800) Prec@5 99.000 (99.120) +2022-11-14 14:17:12,851 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.0833) Prec@1 78.000 (86.462) Prec@5 99.000 (99.115) +2022-11-14 14:17:12,865 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0817) Prec@1 94.000 (86.741) Prec@5 99.000 (99.111) +2022-11-14 14:17:12,879 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0813) Prec@1 89.000 (86.821) Prec@5 98.000 (99.071) +2022-11-14 14:17:12,892 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0809) Prec@1 87.000 (86.828) Prec@5 98.000 (99.034) +2022-11-14 14:17:12,904 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0805) Prec@1 90.000 (86.933) Prec@5 100.000 (99.067) +2022-11-14 14:17:12,917 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0802) Prec@1 86.000 (86.903) Prec@5 100.000 (99.097) +2022-11-14 14:17:12,930 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0800) Prec@1 90.000 (87.000) Prec@5 99.000 (99.094) +2022-11-14 14:17:12,943 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0804) Prec@1 84.000 (86.909) Prec@5 99.000 (99.091) +2022-11-14 14:17:12,957 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0805) Prec@1 83.000 (86.794) Prec@5 100.000 (99.118) +2022-11-14 14:17:12,976 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0812) Prec@1 82.000 (86.657) Prec@5 98.000 (99.086) +2022-11-14 14:17:12,996 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0806) Prec@1 91.000 (86.778) Prec@5 99.000 (99.083) +2022-11-14 14:17:13,013 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0808) Prec@1 84.000 (86.703) Prec@5 99.000 (99.081) +2022-11-14 14:17:13,031 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0811) Prec@1 86.000 (86.684) Prec@5 98.000 (99.053) +2022-11-14 14:17:13,047 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0805) Prec@1 93.000 (86.846) Prec@5 100.000 (99.077) +2022-11-14 14:17:13,065 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0801) Prec@1 89.000 (86.900) Prec@5 99.000 (99.075) +2022-11-14 14:17:13,083 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0805) Prec@1 86.000 (86.878) Prec@5 97.000 (99.024) +2022-11-14 14:17:13,096 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0803) Prec@1 87.000 (86.881) Prec@5 99.000 (99.024) +2022-11-14 14:17:13,109 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0795) Prec@1 93.000 (87.023) Prec@5 100.000 (99.047) +2022-11-14 14:17:13,122 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0796) Prec@1 86.000 (87.000) Prec@5 98.000 (99.023) +2022-11-14 14:17:13,135 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0797) Prec@1 86.000 (86.978) Prec@5 99.000 (99.022) +2022-11-14 14:17:13,147 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0803) Prec@1 81.000 (86.848) Prec@5 99.000 (99.022) +2022-11-14 14:17:13,161 Test: [46/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0798) Prec@1 88.000 (86.872) Prec@5 100.000 (99.043) +2022-11-14 14:17:13,174 Test: [47/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0796) Prec@1 88.000 (86.896) Prec@5 100.000 (99.062) +2022-11-14 14:17:13,186 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0790) Prec@1 90.000 (86.959) Prec@5 100.000 (99.082) +2022-11-14 14:17:13,197 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0794) Prec@1 83.000 (86.880) Prec@5 100.000 (99.100) +2022-11-14 14:17:13,210 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0794) Prec@1 88.000 (86.902) Prec@5 100.000 (99.118) +2022-11-14 14:17:13,224 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0796) Prec@1 84.000 (86.846) Prec@5 100.000 (99.135) +2022-11-14 14:17:13,236 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0791) Prec@1 92.000 (86.943) Prec@5 100.000 (99.151) +2022-11-14 14:17:13,248 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0792) Prec@1 86.000 (86.926) Prec@5 100.000 (99.167) +2022-11-14 14:17:13,260 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0792) Prec@1 84.000 (86.873) Prec@5 100.000 (99.182) +2022-11-14 14:17:13,273 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0791) Prec@1 89.000 (86.911) Prec@5 99.000 (99.179) +2022-11-14 14:17:13,286 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0788) Prec@1 90.000 (86.965) Prec@5 100.000 (99.193) +2022-11-14 14:17:13,299 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0788) Prec@1 89.000 (87.000) Prec@5 100.000 (99.207) +2022-11-14 14:17:13,316 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0793) Prec@1 80.000 (86.881) Prec@5 100.000 (99.220) +2022-11-14 14:17:13,330 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0794) Prec@1 82.000 (86.800) Prec@5 99.000 (99.217) +2022-11-14 14:17:13,342 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0796) Prec@1 85.000 (86.770) Prec@5 99.000 (99.213) +2022-11-14 14:17:13,355 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0796) Prec@1 87.000 (86.774) Prec@5 100.000 (99.226) +2022-11-14 14:17:13,369 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0795) Prec@1 88.000 (86.794) Prec@5 99.000 (99.222) +2022-11-14 14:17:13,383 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0793) Prec@1 88.000 (86.812) Prec@5 100.000 (99.234) +2022-11-14 14:17:13,396 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0794) Prec@1 87.000 (86.815) Prec@5 99.000 (99.231) +2022-11-14 14:17:13,410 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0794) Prec@1 85.000 (86.788) Prec@5 99.000 (99.227) +2022-11-14 14:17:13,423 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0792) Prec@1 89.000 (86.821) Prec@5 100.000 (99.239) +2022-11-14 14:17:13,434 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0792) Prec@1 87.000 (86.824) Prec@5 100.000 (99.250) +2022-11-14 14:17:13,446 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0790) Prec@1 90.000 (86.870) Prec@5 99.000 (99.246) +2022-11-14 14:17:13,460 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0791) Prec@1 86.000 (86.857) Prec@5 99.000 (99.243) +2022-11-14 14:17:13,474 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0792) Prec@1 86.000 (86.845) Prec@5 100.000 (99.254) +2022-11-14 14:17:13,487 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0791) Prec@1 90.000 (86.889) Prec@5 100.000 (99.264) +2022-11-14 14:17:13,501 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0789) Prec@1 90.000 (86.932) Prec@5 99.000 (99.260) +2022-11-14 14:17:13,514 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0784) Prec@1 94.000 (87.027) Prec@5 100.000 (99.270) +2022-11-14 14:17:13,528 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0787) Prec@1 83.000 (86.973) Prec@5 97.000 (99.240) +2022-11-14 14:17:13,541 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0784) Prec@1 89.000 (87.000) Prec@5 99.000 (99.237) +2022-11-14 14:17:13,553 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0784) Prec@1 88.000 (87.013) Prec@5 99.000 (99.234) +2022-11-14 14:17:13,565 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0786) Prec@1 86.000 (87.000) Prec@5 99.000 (99.231) +2022-11-14 14:17:13,578 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0785) Prec@1 88.000 (87.013) Prec@5 100.000 (99.241) +2022-11-14 14:17:13,589 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0783) Prec@1 89.000 (87.037) Prec@5 100.000 (99.250) +2022-11-14 14:17:13,604 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0784) Prec@1 87.000 (87.037) Prec@5 99.000 (99.247) +2022-11-14 14:17:13,616 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0785) Prec@1 86.000 (87.024) Prec@5 100.000 (99.256) +2022-11-14 14:17:13,627 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0787) Prec@1 82.000 (86.964) Prec@5 99.000 (99.253) +2022-11-14 14:17:13,640 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0787) Prec@1 86.000 (86.952) Prec@5 100.000 (99.262) +2022-11-14 14:17:13,651 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0788) Prec@1 85.000 (86.929) Prec@5 99.000 (99.259) +2022-11-14 14:17:13,663 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0791) Prec@1 85.000 (86.907) Prec@5 100.000 (99.267) +2022-11-14 14:17:13,676 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0791) Prec@1 86.000 (86.897) Prec@5 100.000 (99.276) +2022-11-14 14:17:13,689 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0791) Prec@1 90.000 (86.932) Prec@5 98.000 (99.261) +2022-11-14 14:17:13,701 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0790) Prec@1 87.000 (86.933) Prec@5 100.000 (99.270) +2022-11-14 14:17:13,712 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0791) Prec@1 85.000 (86.911) Prec@5 100.000 (99.278) +2022-11-14 14:17:13,724 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0789) Prec@1 92.000 (86.967) Prec@5 100.000 (99.286) +2022-11-14 14:17:13,737 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0785) Prec@1 94.000 (87.043) Prec@5 100.000 (99.293) +2022-11-14 14:17:13,749 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0784) Prec@1 86.000 (87.032) Prec@5 100.000 (99.301) +2022-11-14 14:17:13,762 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0784) Prec@1 87.000 (87.032) Prec@5 100.000 (99.309) +2022-11-14 14:17:13,773 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0783) Prec@1 87.000 (87.032) Prec@5 99.000 (99.305) +2022-11-14 14:17:13,785 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0782) Prec@1 89.000 (87.052) Prec@5 100.000 (99.312) +2022-11-14 14:17:13,796 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0779) Prec@1 89.000 (87.072) Prec@5 99.000 (99.309) +2022-11-14 14:17:13,808 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0782) Prec@1 86.000 (87.061) Prec@5 97.000 (99.286) +2022-11-14 14:17:13,820 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0783) Prec@1 85.000 (87.040) Prec@5 98.000 (99.273) +2022-11-14 14:17:13,830 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0782) Prec@1 89.000 (87.060) Prec@5 99.000 (99.270) +2022-11-14 14:17:13,887 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:17:14,225 Epoch: [175][0/500] Time 0.032 (0.032) Data 0.246 (0.246) Loss 0.0472 (0.0472) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:17:14,440 Epoch: [175][10/500] Time 0.019 (0.020) Data 0.002 (0.024) Loss 0.0242 (0.0357) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:17:14,709 Epoch: [175][20/500] Time 0.029 (0.022) Data 0.002 (0.013) Loss 0.0571 (0.0429) Prec@1 90.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:17:15,059 Epoch: [175][30/500] Time 0.043 (0.025) Data 0.002 (0.010) Loss 0.0622 (0.0477) Prec@1 88.000 (91.750) Prec@5 98.000 (99.500) +2022-11-14 14:17:15,498 Epoch: [175][40/500] Time 0.041 (0.029) Data 0.002 (0.008) Loss 0.0588 (0.0499) Prec@1 87.000 (90.800) Prec@5 100.000 (99.600) +2022-11-14 14:17:15,966 Epoch: [175][50/500] Time 0.053 (0.031) Data 0.002 (0.007) Loss 0.0541 (0.0506) Prec@1 91.000 (90.833) Prec@5 99.000 (99.500) +2022-11-14 14:17:16,330 Epoch: [175][60/500] Time 0.050 (0.031) Data 0.002 (0.006) Loss 0.0350 (0.0484) Prec@1 95.000 (91.429) Prec@5 100.000 (99.571) +2022-11-14 14:17:16,744 Epoch: [175][70/500] Time 0.044 (0.032) Data 0.002 (0.005) Loss 0.0614 (0.0500) Prec@1 90.000 (91.250) Prec@5 100.000 (99.625) +2022-11-14 14:17:17,135 Epoch: [175][80/500] Time 0.033 (0.032) Data 0.001 (0.005) Loss 0.0295 (0.0477) Prec@1 96.000 (91.778) Prec@5 100.000 (99.667) +2022-11-14 14:17:17,522 Epoch: [175][90/500] Time 0.034 (0.033) Data 0.002 (0.005) Loss 0.0412 (0.0471) Prec@1 94.000 (92.000) Prec@5 99.000 (99.600) +2022-11-14 14:17:18,007 Epoch: [175][100/500] Time 0.049 (0.034) Data 0.002 (0.004) Loss 0.0491 (0.0473) Prec@1 94.000 (92.182) Prec@5 100.000 (99.636) +2022-11-14 14:17:18,426 Epoch: [175][110/500] Time 0.051 (0.034) Data 0.002 (0.004) Loss 0.0334 (0.0461) Prec@1 94.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:17:18,861 Epoch: [175][120/500] Time 0.083 (0.034) Data 0.002 (0.004) Loss 0.0347 (0.0452) Prec@1 93.000 (92.385) Prec@5 100.000 (99.692) +2022-11-14 14:17:19,293 Epoch: [175][130/500] Time 0.055 (0.035) Data 0.002 (0.004) Loss 0.0504 (0.0456) Prec@1 91.000 (92.286) Prec@5 100.000 (99.714) +2022-11-14 14:17:19,687 Epoch: [175][140/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0495 (0.0459) Prec@1 94.000 (92.400) Prec@5 100.000 (99.733) +2022-11-14 14:17:20,091 Epoch: [175][150/500] Time 0.033 (0.035) Data 0.002 (0.004) Loss 0.0490 (0.0461) Prec@1 91.000 (92.312) Prec@5 100.000 (99.750) +2022-11-14 14:17:20,483 Epoch: [175][160/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0553 (0.0466) Prec@1 92.000 (92.294) Prec@5 100.000 (99.765) +2022-11-14 14:17:20,875 Epoch: [175][170/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0181 (0.0450) Prec@1 98.000 (92.611) Prec@5 100.000 (99.778) +2022-11-14 14:17:21,371 Epoch: [175][180/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0460 (0.0451) Prec@1 93.000 (92.632) Prec@5 100.000 (99.789) +2022-11-14 14:17:21,777 Epoch: [175][190/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0516 (0.0454) Prec@1 91.000 (92.550) Prec@5 99.000 (99.750) +2022-11-14 14:17:22,250 Epoch: [175][200/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0485 (0.0455) Prec@1 93.000 (92.571) Prec@5 100.000 (99.762) +2022-11-14 14:17:22,625 Epoch: [175][210/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0461 (0.0456) Prec@1 92.000 (92.545) Prec@5 100.000 (99.773) +2022-11-14 14:17:23,089 Epoch: [175][220/500] Time 0.030 (0.036) Data 0.002 (0.003) Loss 0.0517 (0.0458) Prec@1 90.000 (92.435) Prec@5 100.000 (99.783) +2022-11-14 14:17:23,513 Epoch: [175][230/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0223 (0.0449) Prec@1 97.000 (92.625) Prec@5 100.000 (99.792) +2022-11-14 14:17:23,934 Epoch: [175][240/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0435 (0.0448) Prec@1 93.000 (92.640) Prec@5 100.000 (99.800) +2022-11-14 14:17:24,327 Epoch: [175][250/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0407 (0.0446) Prec@1 92.000 (92.615) Prec@5 100.000 (99.808) +2022-11-14 14:17:24,773 Epoch: [175][260/500] Time 0.054 (0.036) Data 0.002 (0.003) Loss 0.0454 (0.0447) Prec@1 91.000 (92.556) Prec@5 100.000 (99.815) +2022-11-14 14:17:25,156 Epoch: [175][270/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0516 (0.0449) Prec@1 91.000 (92.500) Prec@5 99.000 (99.786) +2022-11-14 14:17:25,549 Epoch: [175][280/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0444 (0.0449) Prec@1 94.000 (92.552) Prec@5 99.000 (99.759) +2022-11-14 14:17:26,006 Epoch: [175][290/500] Time 0.064 (0.036) Data 0.002 (0.003) Loss 0.0440 (0.0449) Prec@1 94.000 (92.600) Prec@5 100.000 (99.767) +2022-11-14 14:17:26,412 Epoch: [175][300/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0532 (0.0451) Prec@1 91.000 (92.548) Prec@5 100.000 (99.774) +2022-11-14 14:17:26,804 Epoch: [175][310/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0509 (0.0453) Prec@1 92.000 (92.531) Prec@5 99.000 (99.750) +2022-11-14 14:17:27,264 Epoch: [175][320/500] Time 0.082 (0.036) Data 0.002 (0.003) Loss 0.0499 (0.0455) Prec@1 92.000 (92.515) Prec@5 100.000 (99.758) +2022-11-14 14:17:27,657 Epoch: [175][330/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0456 (0.0455) Prec@1 91.000 (92.471) Prec@5 100.000 (99.765) +2022-11-14 14:17:28,113 Epoch: [175][340/500] Time 0.065 (0.036) Data 0.002 (0.003) Loss 0.0176 (0.0447) Prec@1 97.000 (92.600) Prec@5 100.000 (99.771) +2022-11-14 14:17:28,596 Epoch: [175][350/500] Time 0.065 (0.037) Data 0.002 (0.003) Loss 0.0379 (0.0445) Prec@1 93.000 (92.611) Prec@5 99.000 (99.750) +2022-11-14 14:17:29,027 Epoch: [175][360/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.0370 (0.0443) Prec@1 95.000 (92.676) Prec@5 99.000 (99.730) +2022-11-14 14:17:29,471 Epoch: [175][370/500] Time 0.067 (0.037) Data 0.002 (0.003) Loss 0.0540 (0.0445) Prec@1 91.000 (92.632) Prec@5 99.000 (99.711) +2022-11-14 14:17:29,843 Epoch: [175][380/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0485 (0.0446) Prec@1 92.000 (92.615) Prec@5 99.000 (99.692) +2022-11-14 14:17:30,243 Epoch: [175][390/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0381 (0.0445) Prec@1 94.000 (92.650) Prec@5 100.000 (99.700) +2022-11-14 14:17:30,683 Epoch: [175][400/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0657 (0.0450) Prec@1 87.000 (92.512) Prec@5 100.000 (99.707) +2022-11-14 14:17:31,119 Epoch: [175][410/500] Time 0.030 (0.037) Data 0.002 (0.003) Loss 0.0703 (0.0456) Prec@1 87.000 (92.381) Prec@5 99.000 (99.690) +2022-11-14 14:17:31,510 Epoch: [175][420/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.0530 (0.0458) Prec@1 91.000 (92.349) Prec@5 100.000 (99.698) +2022-11-14 14:17:31,946 Epoch: [175][430/500] Time 0.031 (0.037) Data 0.002 (0.003) Loss 0.0539 (0.0459) Prec@1 92.000 (92.341) Prec@5 100.000 (99.705) +2022-11-14 14:17:32,385 Epoch: [175][440/500] Time 0.026 (0.037) Data 0.002 (0.002) Loss 0.0197 (0.0454) Prec@1 98.000 (92.467) Prec@5 100.000 (99.711) +2022-11-14 14:17:32,825 Epoch: [175][450/500] Time 0.084 (0.037) Data 0.002 (0.002) Loss 0.0249 (0.0449) Prec@1 95.000 (92.522) Prec@5 100.000 (99.717) +2022-11-14 14:17:33,303 Epoch: [175][460/500] Time 0.052 (0.037) Data 0.002 (0.002) Loss 0.0661 (0.0454) Prec@1 87.000 (92.404) Prec@5 98.000 (99.681) +2022-11-14 14:17:33,684 Epoch: [175][470/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0477 (0.0454) Prec@1 92.000 (92.396) Prec@5 100.000 (99.688) +2022-11-14 14:17:34,084 Epoch: [175][480/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0594 (0.0457) Prec@1 89.000 (92.327) Prec@5 99.000 (99.673) +2022-11-14 14:17:34,463 Epoch: [175][490/500] Time 0.035 (0.037) Data 0.002 (0.002) Loss 0.0537 (0.0459) Prec@1 91.000 (92.300) Prec@5 100.000 (99.680) +2022-11-14 14:17:34,819 Epoch: [175][499/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0625 (0.0462) Prec@1 90.000 (92.255) Prec@5 98.000 (99.647) +2022-11-14 14:17:35,108 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0792 (0.0792) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 14:17:35,121 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0725 (0.0759) Prec@1 86.000 (86.500) Prec@5 100.000 (99.000) +2022-11-14 14:17:35,133 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0609 (0.0709) Prec@1 90.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 14:17:35,148 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0653 (0.0695) Prec@1 91.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 14:17:35,157 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0849 (0.0726) Prec@1 85.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 14:17:35,168 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0516 (0.0691) Prec@1 91.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 14:17:35,178 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.0732) Prec@1 84.000 (87.714) Prec@5 100.000 (99.571) +2022-11-14 14:17:35,190 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0735) Prec@1 85.000 (87.375) Prec@5 100.000 (99.625) +2022-11-14 14:17:35,202 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0742) Prec@1 88.000 (87.444) Prec@5 99.000 (99.556) +2022-11-14 14:17:35,214 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0734) Prec@1 87.000 (87.400) Prec@5 98.000 (99.400) +2022-11-14 14:17:35,226 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0405 (0.0704) Prec@1 94.000 (88.000) Prec@5 100.000 (99.455) +2022-11-14 14:17:35,239 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0726) Prec@1 81.000 (87.417) Prec@5 100.000 (99.500) +2022-11-14 14:17:35,252 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0712) Prec@1 90.000 (87.615) Prec@5 100.000 (99.538) +2022-11-14 14:17:35,265 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0710) Prec@1 90.000 (87.786) Prec@5 100.000 (99.571) +2022-11-14 14:17:35,284 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0720) Prec@1 86.000 (87.667) Prec@5 98.000 (99.467) +2022-11-14 14:17:35,302 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0727) Prec@1 88.000 (87.688) Prec@5 99.000 (99.438) +2022-11-14 14:17:35,322 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0718) Prec@1 90.000 (87.824) Prec@5 99.000 (99.412) +2022-11-14 14:17:35,340 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0733) Prec@1 84.000 (87.611) Prec@5 100.000 (99.444) +2022-11-14 14:17:35,355 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0737) Prec@1 86.000 (87.526) Prec@5 99.000 (99.421) +2022-11-14 14:17:35,373 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0746) Prec@1 84.000 (87.350) Prec@5 95.000 (99.200) +2022-11-14 14:17:35,393 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0759) Prec@1 84.000 (87.190) Prec@5 99.000 (99.190) +2022-11-14 14:17:35,411 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0762) Prec@1 85.000 (87.091) Prec@5 99.000 (99.182) +2022-11-14 14:17:35,430 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.0779) Prec@1 82.000 (86.870) Prec@5 100.000 (99.217) +2022-11-14 14:17:35,450 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0782) Prec@1 84.000 (86.750) Prec@5 100.000 (99.250) +2022-11-14 14:17:35,467 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0785) Prec@1 85.000 (86.680) Prec@5 100.000 (99.280) +2022-11-14 14:17:35,485 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0791) Prec@1 86.000 (86.654) Prec@5 99.000 (99.269) +2022-11-14 14:17:35,503 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0784) Prec@1 90.000 (86.778) Prec@5 100.000 (99.296) +2022-11-14 14:17:35,521 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0780) Prec@1 89.000 (86.857) Prec@5 100.000 (99.321) +2022-11-14 14:17:35,535 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0773) Prec@1 90.000 (86.966) Prec@5 99.000 (99.310) +2022-11-14 14:17:35,547 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1116 (0.0785) Prec@1 80.000 (86.733) Prec@5 99.000 (99.300) +2022-11-14 14:17:35,558 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0777) Prec@1 91.000 (86.871) Prec@5 99.000 (99.290) +2022-11-14 14:17:35,571 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0776) Prec@1 88.000 (86.906) Prec@5 99.000 (99.281) +2022-11-14 14:17:35,583 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0774) Prec@1 86.000 (86.879) Prec@5 100.000 (99.303) +2022-11-14 14:17:35,596 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0775) Prec@1 86.000 (86.853) Prec@5 99.000 (99.294) +2022-11-14 14:17:35,607 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0774) Prec@1 88.000 (86.886) Prec@5 97.000 (99.229) +2022-11-14 14:17:35,621 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0771) Prec@1 89.000 (86.944) Prec@5 100.000 (99.250) +2022-11-14 14:17:35,635 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0773) Prec@1 85.000 (86.892) Prec@5 100.000 (99.270) +2022-11-14 14:17:35,650 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.0781) Prec@1 80.000 (86.711) Prec@5 99.000 (99.263) +2022-11-14 14:17:35,663 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0772) Prec@1 94.000 (86.897) Prec@5 99.000 (99.256) +2022-11-14 14:17:35,677 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0773) Prec@1 85.000 (86.850) Prec@5 100.000 (99.275) +2022-11-14 14:17:35,691 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0777) Prec@1 86.000 (86.829) Prec@5 98.000 (99.244) +2022-11-14 14:17:35,705 Test: [41/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0776) Prec@1 89.000 (86.881) Prec@5 99.000 (99.238) +2022-11-14 14:17:35,719 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0771) Prec@1 91.000 (86.977) Prec@5 100.000 (99.256) +2022-11-14 14:17:35,733 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0771) Prec@1 89.000 (87.023) Prec@5 99.000 (99.250) +2022-11-14 14:17:35,748 Test: [44/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0771) Prec@1 88.000 (87.044) Prec@5 100.000 (99.267) +2022-11-14 14:17:35,759 Test: [45/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0771) Prec@1 87.000 (87.043) Prec@5 97.000 (99.217) +2022-11-14 14:17:35,773 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0770) Prec@1 87.000 (87.043) Prec@5 100.000 (99.234) +2022-11-14 14:17:35,788 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0777) Prec@1 80.000 (86.896) Prec@5 98.000 (99.208) +2022-11-14 14:17:35,803 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0773) Prec@1 89.000 (86.939) Prec@5 99.000 (99.204) +2022-11-14 14:17:35,818 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1240 (0.0782) Prec@1 81.000 (86.820) Prec@5 99.000 (99.200) +2022-11-14 14:17:35,830 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0778) Prec@1 89.000 (86.863) Prec@5 100.000 (99.216) +2022-11-14 14:17:35,844 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0780) Prec@1 85.000 (86.827) Prec@5 99.000 (99.212) +2022-11-14 14:17:35,859 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0778) Prec@1 91.000 (86.906) Prec@5 99.000 (99.208) +2022-11-14 14:17:35,873 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0779) Prec@1 85.000 (86.870) Prec@5 99.000 (99.204) +2022-11-14 14:17:35,886 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0779) Prec@1 86.000 (86.855) Prec@5 100.000 (99.218) +2022-11-14 14:17:35,901 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0777) Prec@1 90.000 (86.911) Prec@5 99.000 (99.214) +2022-11-14 14:17:35,913 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0776) Prec@1 88.000 (86.930) Prec@5 100.000 (99.228) +2022-11-14 14:17:35,929 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0775) Prec@1 87.000 (86.931) Prec@5 99.000 (99.224) +2022-11-14 14:17:35,944 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0777) Prec@1 86.000 (86.915) Prec@5 100.000 (99.237) +2022-11-14 14:17:35,957 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0776) Prec@1 86.000 (86.900) Prec@5 100.000 (99.250) +2022-11-14 14:17:35,971 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0776) Prec@1 86.000 (86.885) Prec@5 100.000 (99.262) +2022-11-14 14:17:35,983 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0774) Prec@1 91.000 (86.952) Prec@5 100.000 (99.274) +2022-11-14 14:17:35,999 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0772) Prec@1 87.000 (86.952) Prec@5 99.000 (99.270) +2022-11-14 14:17:36,014 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0768) Prec@1 89.000 (86.984) Prec@5 100.000 (99.281) +2022-11-14 14:17:36,027 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0771) Prec@1 83.000 (86.923) Prec@5 100.000 (99.292) +2022-11-14 14:17:36,040 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0773) Prec@1 84.000 (86.879) Prec@5 99.000 (99.288) +2022-11-14 14:17:36,054 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0769) Prec@1 93.000 (86.970) Prec@5 100.000 (99.299) +2022-11-14 14:17:36,066 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0771) Prec@1 85.000 (86.941) Prec@5 100.000 (99.309) +2022-11-14 14:17:36,082 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0767) Prec@1 89.000 (86.971) Prec@5 100.000 (99.319) +2022-11-14 14:17:36,094 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0767) Prec@1 88.000 (86.986) Prec@5 99.000 (99.314) +2022-11-14 14:17:36,110 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0767) Prec@1 89.000 (87.014) Prec@5 100.000 (99.324) +2022-11-14 14:17:36,122 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0766) Prec@1 88.000 (87.028) Prec@5 100.000 (99.333) +2022-11-14 14:17:36,137 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0764) Prec@1 91.000 (87.082) Prec@5 99.000 (99.329) +2022-11-14 14:17:36,150 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0760) Prec@1 92.000 (87.149) Prec@5 100.000 (99.338) +2022-11-14 14:17:36,165 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0760) Prec@1 86.000 (87.133) Prec@5 99.000 (99.333) +2022-11-14 14:17:36,177 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0759) Prec@1 91.000 (87.184) Prec@5 98.000 (99.316) +2022-11-14 14:17:36,188 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0758) Prec@1 87.000 (87.182) Prec@5 100.000 (99.325) +2022-11-14 14:17:36,200 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0761) Prec@1 84.000 (87.141) Prec@5 98.000 (99.308) +2022-11-14 14:17:36,215 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0761) Prec@1 88.000 (87.152) Prec@5 100.000 (99.316) +2022-11-14 14:17:36,230 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0760) Prec@1 87.000 (87.150) Prec@5 100.000 (99.325) +2022-11-14 14:17:36,244 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0761) Prec@1 87.000 (87.148) Prec@5 99.000 (99.321) +2022-11-14 14:17:36,260 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0761) Prec@1 88.000 (87.159) Prec@5 100.000 (99.329) +2022-11-14 14:17:36,277 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0763) Prec@1 86.000 (87.145) Prec@5 100.000 (99.337) +2022-11-14 14:17:36,292 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0759) Prec@1 95.000 (87.238) Prec@5 100.000 (99.345) +2022-11-14 14:17:36,306 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0762) Prec@1 84.000 (87.200) Prec@5 99.000 (99.341) +2022-11-14 14:17:36,320 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0765) Prec@1 84.000 (87.163) Prec@5 100.000 (99.349) +2022-11-14 14:17:36,334 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0765) Prec@1 86.000 (87.149) Prec@5 100.000 (99.356) +2022-11-14 14:17:36,349 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0765) Prec@1 89.000 (87.170) Prec@5 100.000 (99.364) +2022-11-14 14:17:36,365 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0763) Prec@1 87.000 (87.169) Prec@5 100.000 (99.371) +2022-11-14 14:17:36,382 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0764) Prec@1 87.000 (87.167) Prec@5 99.000 (99.367) +2022-11-14 14:17:36,395 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0764) Prec@1 88.000 (87.176) Prec@5 100.000 (99.374) +2022-11-14 14:17:36,407 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0761) Prec@1 93.000 (87.239) Prec@5 99.000 (99.370) +2022-11-14 14:17:36,422 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0761) Prec@1 87.000 (87.237) Prec@5 99.000 (99.366) +2022-11-14 14:17:36,437 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0761) Prec@1 90.000 (87.266) Prec@5 99.000 (99.362) +2022-11-14 14:17:36,450 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0761) Prec@1 85.000 (87.242) Prec@5 100.000 (99.368) +2022-11-14 14:17:36,462 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0760) Prec@1 89.000 (87.260) Prec@5 99.000 (99.365) +2022-11-14 14:17:36,477 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0757) Prec@1 91.000 (87.299) Prec@5 99.000 (99.361) +2022-11-14 14:17:36,490 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0759) Prec@1 82.000 (87.245) Prec@5 99.000 (99.357) +2022-11-14 14:17:36,506 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0762) Prec@1 86.000 (87.232) Prec@5 97.000 (99.333) +2022-11-14 14:17:36,519 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0762) Prec@1 85.000 (87.210) Prec@5 100.000 (99.340) +2022-11-14 14:17:36,575 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:17:36,901 Epoch: [176][0/500] Time 0.027 (0.027) Data 0.232 (0.232) Loss 0.0451 (0.0451) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:17:37,317 Epoch: [176][10/500] Time 0.028 (0.037) Data 0.002 (0.023) Loss 0.0585 (0.0518) Prec@1 91.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:17:37,704 Epoch: [176][20/500] Time 0.035 (0.035) Data 0.002 (0.013) Loss 0.0528 (0.0521) Prec@1 88.000 (90.667) Prec@5 100.000 (99.667) +2022-11-14 14:17:38,095 Epoch: [176][30/500] Time 0.032 (0.035) Data 0.002 (0.010) Loss 0.0367 (0.0483) Prec@1 92.000 (91.000) Prec@5 100.000 (99.750) +2022-11-14 14:17:38,480 Epoch: [176][40/500] Time 0.034 (0.035) Data 0.002 (0.008) Loss 0.0581 (0.0502) Prec@1 90.000 (90.800) Prec@5 99.000 (99.600) +2022-11-14 14:17:38,907 Epoch: [176][50/500] Time 0.035 (0.035) Data 0.002 (0.007) Loss 0.0395 (0.0484) Prec@1 95.000 (91.500) Prec@5 100.000 (99.667) +2022-11-14 14:17:39,369 Epoch: [176][60/500] Time 0.030 (0.036) Data 0.002 (0.006) Loss 0.0519 (0.0489) Prec@1 91.000 (91.429) Prec@5 100.000 (99.714) +2022-11-14 14:17:39,858 Epoch: [176][70/500] Time 0.055 (0.037) Data 0.002 (0.005) Loss 0.0470 (0.0487) Prec@1 92.000 (91.500) Prec@5 100.000 (99.750) +2022-11-14 14:17:40,230 Epoch: [176][80/500] Time 0.036 (0.037) Data 0.002 (0.005) Loss 0.0264 (0.0462) Prec@1 95.000 (91.889) Prec@5 100.000 (99.778) +2022-11-14 14:17:40,626 Epoch: [176][90/500] Time 0.037 (0.036) Data 0.002 (0.005) Loss 0.0263 (0.0442) Prec@1 95.000 (92.200) Prec@5 100.000 (99.800) +2022-11-14 14:17:41,042 Epoch: [176][100/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.0377 (0.0436) Prec@1 94.000 (92.364) Prec@5 99.000 (99.727) +2022-11-14 14:17:41,430 Epoch: [176][110/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.0673 (0.0456) Prec@1 88.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:17:41,819 Epoch: [176][120/500] Time 0.037 (0.036) Data 0.001 (0.004) Loss 0.0638 (0.0470) Prec@1 90.000 (91.846) Prec@5 100.000 (99.769) +2022-11-14 14:17:42,226 Epoch: [176][130/500] Time 0.033 (0.036) Data 0.002 (0.004) Loss 0.0521 (0.0474) Prec@1 92.000 (91.857) Prec@5 100.000 (99.786) +2022-11-14 14:17:42,630 Epoch: [176][140/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0378 (0.0467) Prec@1 94.000 (92.000) Prec@5 100.000 (99.800) +2022-11-14 14:17:43,020 Epoch: [176][150/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0355 (0.0460) Prec@1 95.000 (92.188) Prec@5 100.000 (99.812) +2022-11-14 14:17:43,423 Epoch: [176][160/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.0472 (0.0461) Prec@1 93.000 (92.235) Prec@5 99.000 (99.765) +2022-11-14 14:17:43,824 Epoch: [176][170/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0532 (0.0465) Prec@1 88.000 (92.000) Prec@5 100.000 (99.778) +2022-11-14 14:17:44,242 Epoch: [176][180/500] Time 0.036 (0.036) Data 0.001 (0.003) Loss 0.0240 (0.0453) Prec@1 95.000 (92.158) Prec@5 100.000 (99.789) +2022-11-14 14:17:44,645 Epoch: [176][190/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0576 (0.0459) Prec@1 90.000 (92.050) Prec@5 100.000 (99.800) +2022-11-14 14:17:45,078 Epoch: [176][200/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0576 (0.0465) Prec@1 93.000 (92.095) Prec@5 99.000 (99.762) +2022-11-14 14:17:45,460 Epoch: [176][210/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0544 (0.0468) Prec@1 91.000 (92.045) Prec@5 100.000 (99.773) +2022-11-14 14:17:45,843 Epoch: [176][220/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0478 (0.0469) Prec@1 91.000 (92.000) Prec@5 99.000 (99.739) +2022-11-14 14:17:46,275 Epoch: [176][230/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.0466 (0.0469) Prec@1 93.000 (92.042) Prec@5 100.000 (99.750) +2022-11-14 14:17:46,701 Epoch: [176][240/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0512 (0.0470) Prec@1 93.000 (92.080) Prec@5 99.000 (99.720) +2022-11-14 14:17:47,131 Epoch: [176][250/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.0186 (0.0459) Prec@1 98.000 (92.308) Prec@5 100.000 (99.731) +2022-11-14 14:17:47,587 Epoch: [176][260/500] Time 0.074 (0.036) Data 0.002 (0.003) Loss 0.0352 (0.0455) Prec@1 94.000 (92.370) Prec@5 100.000 (99.741) +2022-11-14 14:17:48,044 Epoch: [176][270/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0635 (0.0462) Prec@1 89.000 (92.250) Prec@5 99.000 (99.714) +2022-11-14 14:17:48,535 Epoch: [176][280/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.0518 (0.0464) Prec@1 90.000 (92.172) Prec@5 100.000 (99.724) +2022-11-14 14:17:49,019 Epoch: [176][290/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0624 (0.0469) Prec@1 89.000 (92.067) Prec@5 100.000 (99.733) +2022-11-14 14:17:49,571 Epoch: [176][300/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0454 (0.0469) Prec@1 92.000 (92.065) Prec@5 100.000 (99.742) +2022-11-14 14:17:50,130 Epoch: [176][310/500] Time 0.101 (0.038) Data 0.002 (0.003) Loss 0.0272 (0.0463) Prec@1 96.000 (92.188) Prec@5 100.000 (99.750) +2022-11-14 14:17:50,695 Epoch: [176][320/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0365 (0.0460) Prec@1 92.000 (92.182) Prec@5 100.000 (99.758) +2022-11-14 14:17:51,201 Epoch: [176][330/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0306 (0.0455) Prec@1 93.000 (92.206) Prec@5 100.000 (99.765) +2022-11-14 14:17:51,694 Epoch: [176][340/500] Time 0.042 (0.039) Data 0.003 (0.003) Loss 0.0355 (0.0452) Prec@1 95.000 (92.286) Prec@5 100.000 (99.771) +2022-11-14 14:17:52,200 Epoch: [176][350/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0339 (0.0449) Prec@1 94.000 (92.333) Prec@5 100.000 (99.778) +2022-11-14 14:17:52,768 Epoch: [176][360/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0442 (0.0449) Prec@1 92.000 (92.324) Prec@5 100.000 (99.784) +2022-11-14 14:17:53,456 Epoch: [176][370/500] Time 0.107 (0.040) Data 0.002 (0.003) Loss 0.0684 (0.0455) Prec@1 91.000 (92.289) Prec@5 97.000 (99.711) +2022-11-14 14:17:53,996 Epoch: [176][380/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0396 (0.0454) Prec@1 92.000 (92.282) Prec@5 99.000 (99.692) +2022-11-14 14:17:54,515 Epoch: [176][390/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0379 (0.0452) Prec@1 92.000 (92.275) Prec@5 100.000 (99.700) +2022-11-14 14:17:54,982 Epoch: [176][400/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0265 (0.0447) Prec@1 96.000 (92.366) Prec@5 100.000 (99.707) +2022-11-14 14:17:55,492 Epoch: [176][410/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0374 (0.0445) Prec@1 94.000 (92.405) Prec@5 100.000 (99.714) +2022-11-14 14:17:56,061 Epoch: [176][420/500] Time 0.054 (0.041) Data 0.001 (0.002) Loss 0.0672 (0.0451) Prec@1 88.000 (92.302) Prec@5 98.000 (99.674) +2022-11-14 14:17:56,711 Epoch: [176][430/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0583 (0.0454) Prec@1 91.000 (92.273) Prec@5 100.000 (99.682) +2022-11-14 14:17:57,228 Epoch: [176][440/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0306 (0.0450) Prec@1 96.000 (92.356) Prec@5 100.000 (99.689) +2022-11-14 14:17:58,084 Epoch: [176][450/500] Time 0.065 (0.042) Data 0.002 (0.002) Loss 0.0291 (0.0447) Prec@1 94.000 (92.391) Prec@5 100.000 (99.696) +2022-11-14 14:17:58,617 Epoch: [176][460/500] Time 0.046 (0.042) Data 0.002 (0.002) Loss 0.0465 (0.0447) Prec@1 93.000 (92.404) Prec@5 98.000 (99.660) +2022-11-14 14:17:59,205 Epoch: [176][470/500] Time 0.121 (0.042) Data 0.002 (0.002) Loss 0.0701 (0.0453) Prec@1 88.000 (92.312) Prec@5 99.000 (99.646) +2022-11-14 14:17:59,832 Epoch: [176][480/500] Time 0.101 (0.042) Data 0.002 (0.002) Loss 0.0504 (0.0454) Prec@1 92.000 (92.306) Prec@5 98.000 (99.612) +2022-11-14 14:18:00,486 Epoch: [176][490/500] Time 0.058 (0.043) Data 0.002 (0.002) Loss 0.0340 (0.0451) Prec@1 93.000 (92.320) Prec@5 99.000 (99.600) +2022-11-14 14:18:01,144 Epoch: [176][499/500] Time 0.118 (0.043) Data 0.002 (0.002) Loss 0.0325 (0.0449) Prec@1 95.000 (92.373) Prec@5 100.000 (99.608) +2022-11-14 14:18:01,462 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0554 (0.0554) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:01,475 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0730 (0.0642) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:18:01,486 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0809 (0.0697) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:01,500 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0737 (0.0707) Prec@1 89.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 14:18:01,513 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0827 (0.0731) Prec@1 85.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 14:18:01,526 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0402 (0.0676) Prec@1 94.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 14:18:01,540 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0663) Prec@1 91.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 14:18:01,552 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0854 (0.0687) Prec@1 86.000 (89.000) Prec@5 100.000 (99.875) +2022-11-14 14:18:01,561 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0700) Prec@1 89.000 (89.000) Prec@5 100.000 (99.889) +2022-11-14 14:18:01,570 Test: [9/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0704) Prec@1 88.000 (88.900) Prec@5 99.000 (99.800) +2022-11-14 14:18:01,581 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0512 (0.0686) Prec@1 91.000 (89.091) Prec@5 100.000 (99.818) +2022-11-14 14:18:01,592 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0707) Prec@1 86.000 (88.833) Prec@5 100.000 (99.833) +2022-11-14 14:18:01,604 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0689) Prec@1 92.000 (89.077) Prec@5 100.000 (99.846) +2022-11-14 14:18:01,615 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0701) Prec@1 84.000 (88.714) Prec@5 100.000 (99.857) +2022-11-14 14:18:01,627 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0703) Prec@1 86.000 (88.533) Prec@5 100.000 (99.867) +2022-11-14 14:18:01,640 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0705) Prec@1 87.000 (88.438) Prec@5 100.000 (99.875) +2022-11-14 14:18:01,651 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0694) Prec@1 93.000 (88.706) Prec@5 98.000 (99.765) +2022-11-14 14:18:01,661 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0710) Prec@1 84.000 (88.444) Prec@5 100.000 (99.778) +2022-11-14 14:18:01,674 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0720) Prec@1 81.000 (88.053) Prec@5 98.000 (99.684) +2022-11-14 14:18:01,686 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0726) Prec@1 86.000 (87.950) Prec@5 99.000 (99.650) +2022-11-14 14:18:01,697 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0728) Prec@1 88.000 (87.952) Prec@5 99.000 (99.619) +2022-11-14 14:18:01,708 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0734) Prec@1 85.000 (87.818) Prec@5 100.000 (99.636) +2022-11-14 14:18:01,720 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0746) Prec@1 85.000 (87.696) Prec@5 99.000 (99.609) +2022-11-14 14:18:01,732 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0745) Prec@1 86.000 (87.625) Prec@5 99.000 (99.583) +2022-11-14 14:18:01,745 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0755) Prec@1 86.000 (87.560) Prec@5 100.000 (99.600) +2022-11-14 14:18:01,759 Test: [25/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0757) Prec@1 87.000 (87.538) Prec@5 99.000 (99.577) +2022-11-14 14:18:01,773 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0753) Prec@1 87.000 (87.519) Prec@5 100.000 (99.593) +2022-11-14 14:18:01,786 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0750) Prec@1 89.000 (87.571) Prec@5 100.000 (99.607) +2022-11-14 14:18:01,799 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0744) Prec@1 89.000 (87.621) Prec@5 99.000 (99.586) +2022-11-14 14:18:01,813 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0749) Prec@1 86.000 (87.567) Prec@5 100.000 (99.600) +2022-11-14 14:18:01,826 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0741) Prec@1 94.000 (87.774) Prec@5 100.000 (99.613) +2022-11-14 14:18:01,838 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0740) Prec@1 88.000 (87.781) Prec@5 99.000 (99.594) +2022-11-14 14:18:01,849 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0744) Prec@1 83.000 (87.636) Prec@5 98.000 (99.545) +2022-11-14 14:18:01,864 Test: [33/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.0757) Prec@1 82.000 (87.471) Prec@5 100.000 (99.559) +2022-11-14 14:18:01,877 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0764) Prec@1 83.000 (87.343) Prec@5 99.000 (99.543) +2022-11-14 14:18:01,890 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0760) Prec@1 88.000 (87.361) Prec@5 100.000 (99.556) +2022-11-14 14:18:01,902 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0763) Prec@1 86.000 (87.324) Prec@5 98.000 (99.514) +2022-11-14 14:18:01,921 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1220 (0.0775) Prec@1 79.000 (87.105) Prec@5 100.000 (99.526) +2022-11-14 14:18:01,936 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0769) Prec@1 92.000 (87.231) Prec@5 99.000 (99.513) +2022-11-14 14:18:01,949 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0767) Prec@1 90.000 (87.300) Prec@5 99.000 (99.500) +2022-11-14 14:18:01,960 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0772) Prec@1 84.000 (87.220) Prec@5 99.000 (99.488) +2022-11-14 14:18:01,972 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0767) Prec@1 92.000 (87.333) Prec@5 100.000 (99.500) +2022-11-14 14:18:01,985 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0762) Prec@1 92.000 (87.442) Prec@5 100.000 (99.512) +2022-11-14 14:18:01,998 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0762) Prec@1 87.000 (87.432) Prec@5 98.000 (99.477) +2022-11-14 14:18:02,010 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0761) Prec@1 89.000 (87.467) Prec@5 99.000 (99.467) +2022-11-14 14:18:02,023 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0762) Prec@1 87.000 (87.457) Prec@5 100.000 (99.478) +2022-11-14 14:18:02,037 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 88.000 (87.468) Prec@5 100.000 (99.489) +2022-11-14 14:18:02,050 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0764) Prec@1 84.000 (87.396) Prec@5 100.000 (99.500) +2022-11-14 14:18:02,062 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0758) Prec@1 91.000 (87.469) Prec@5 100.000 (99.510) +2022-11-14 14:18:02,075 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.0766) Prec@1 84.000 (87.400) Prec@5 100.000 (99.520) +2022-11-14 14:18:02,087 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0765) Prec@1 87.000 (87.392) Prec@5 99.000 (99.510) +2022-11-14 14:18:02,099 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0768) Prec@1 83.000 (87.308) Prec@5 100.000 (99.519) +2022-11-14 14:18:02,112 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0768) Prec@1 84.000 (87.245) Prec@5 100.000 (99.528) +2022-11-14 14:18:02,123 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0767) Prec@1 87.000 (87.241) Prec@5 100.000 (99.537) +2022-11-14 14:18:02,133 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0768) Prec@1 86.000 (87.218) Prec@5 99.000 (99.527) +2022-11-14 14:18:02,146 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0765) Prec@1 92.000 (87.304) Prec@5 98.000 (99.500) +2022-11-14 14:18:02,157 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0762) Prec@1 91.000 (87.368) Prec@5 100.000 (99.509) +2022-11-14 14:18:02,169 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0762) Prec@1 87.000 (87.362) Prec@5 100.000 (99.517) +2022-11-14 14:18:02,181 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0764) Prec@1 86.000 (87.339) Prec@5 98.000 (99.492) +2022-11-14 14:18:02,193 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0766) Prec@1 84.000 (87.283) Prec@5 99.000 (99.483) +2022-11-14 14:18:02,203 Test: [60/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0767) Prec@1 87.000 (87.279) Prec@5 99.000 (99.475) +2022-11-14 14:18:02,217 Test: [61/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0765) Prec@1 89.000 (87.306) Prec@5 100.000 (99.484) +2022-11-14 14:18:02,230 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0765) Prec@1 86.000 (87.286) Prec@5 100.000 (99.492) +2022-11-14 14:18:02,242 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0407 (0.0759) Prec@1 93.000 (87.375) Prec@5 100.000 (99.500) +2022-11-14 14:18:02,252 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0763) Prec@1 84.000 (87.323) Prec@5 100.000 (99.508) +2022-11-14 14:18:02,265 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0763) Prec@1 86.000 (87.303) Prec@5 100.000 (99.515) +2022-11-14 14:18:02,278 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0761) Prec@1 89.000 (87.328) Prec@5 100.000 (99.522) +2022-11-14 14:18:02,289 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 88.000 (87.338) Prec@5 99.000 (99.515) +2022-11-14 14:18:02,301 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0760) Prec@1 89.000 (87.362) Prec@5 99.000 (99.507) +2022-11-14 14:18:02,316 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0759) Prec@1 91.000 (87.414) Prec@5 97.000 (99.471) +2022-11-14 14:18:02,329 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0759) Prec@1 88.000 (87.423) Prec@5 98.000 (99.451) +2022-11-14 14:18:02,342 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0757) Prec@1 87.000 (87.417) Prec@5 100.000 (99.458) +2022-11-14 14:18:02,354 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0753) Prec@1 93.000 (87.493) Prec@5 99.000 (99.452) +2022-11-14 14:18:02,366 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0753) Prec@1 88.000 (87.500) Prec@5 100.000 (99.459) +2022-11-14 14:18:02,379 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0755) Prec@1 86.000 (87.480) Prec@5 99.000 (99.453) +2022-11-14 14:18:02,391 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0753) Prec@1 91.000 (87.526) Prec@5 100.000 (99.461) +2022-11-14 14:18:02,404 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0752) Prec@1 86.000 (87.506) Prec@5 99.000 (99.455) +2022-11-14 14:18:02,417 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0754) Prec@1 86.000 (87.487) Prec@5 99.000 (99.449) +2022-11-14 14:18:02,430 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0755) Prec@1 86.000 (87.468) Prec@5 100.000 (99.456) +2022-11-14 14:18:02,447 Test: [79/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0756) Prec@1 85.000 (87.438) Prec@5 98.000 (99.438) +2022-11-14 14:18:02,463 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0755) Prec@1 91.000 (87.481) Prec@5 100.000 (99.444) +2022-11-14 14:18:02,481 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0757) Prec@1 84.000 (87.439) Prec@5 100.000 (99.451) +2022-11-14 14:18:02,501 Test: [82/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0757) Prec@1 87.000 (87.434) Prec@5 100.000 (99.458) +2022-11-14 14:18:02,519 Test: [83/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0755) Prec@1 89.000 (87.452) Prec@5 100.000 (99.464) +2022-11-14 14:18:02,535 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0757) Prec@1 84.000 (87.412) Prec@5 100.000 (99.471) +2022-11-14 14:18:02,552 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1188 (0.0762) Prec@1 81.000 (87.337) Prec@5 97.000 (99.442) +2022-11-14 14:18:02,567 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0764) Prec@1 83.000 (87.287) Prec@5 99.000 (99.437) +2022-11-14 14:18:02,581 Test: [87/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0764) Prec@1 88.000 (87.295) Prec@5 98.000 (99.420) +2022-11-14 14:18:02,594 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0763) Prec@1 86.000 (87.281) Prec@5 100.000 (99.427) +2022-11-14 14:18:02,606 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0763) Prec@1 88.000 (87.289) Prec@5 100.000 (99.433) +2022-11-14 14:18:02,618 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0761) Prec@1 91.000 (87.330) Prec@5 100.000 (99.440) +2022-11-14 14:18:02,631 Test: [91/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0758) Prec@1 91.000 (87.370) Prec@5 100.000 (99.446) +2022-11-14 14:18:02,643 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0758) Prec@1 91.000 (87.409) Prec@5 99.000 (99.441) +2022-11-14 14:18:02,655 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0759) Prec@1 85.000 (87.383) Prec@5 100.000 (99.447) +2022-11-14 14:18:02,668 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0759) Prec@1 88.000 (87.389) Prec@5 99.000 (99.442) +2022-11-14 14:18:02,680 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0757) Prec@1 91.000 (87.427) Prec@5 99.000 (99.438) +2022-11-14 14:18:02,691 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0376 (0.0753) Prec@1 95.000 (87.505) Prec@5 100.000 (99.443) +2022-11-14 14:18:02,703 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0755) Prec@1 84.000 (87.469) Prec@5 98.000 (99.429) +2022-11-14 14:18:02,717 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0756) Prec@1 87.000 (87.465) Prec@5 99.000 (99.424) +2022-11-14 14:18:02,729 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0755) Prec@1 90.000 (87.490) Prec@5 100.000 (99.430) +2022-11-14 14:18:02,805 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:18:03,145 Epoch: [177][0/500] Time 0.025 (0.025) Data 0.248 (0.248) Loss 0.0341 (0.0341) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:03,370 Epoch: [177][10/500] Time 0.023 (0.021) Data 0.002 (0.024) Loss 0.0386 (0.0363) Prec@1 95.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:18:03,644 Epoch: [177][20/500] Time 0.019 (0.023) Data 0.002 (0.013) Loss 0.0134 (0.0287) Prec@1 99.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:03,883 Epoch: [177][30/500] Time 0.021 (0.022) Data 0.002 (0.010) Loss 0.0328 (0.0297) Prec@1 95.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 14:18:04,177 Epoch: [177][40/500] Time 0.028 (0.023) Data 0.002 (0.008) Loss 0.0214 (0.0280) Prec@1 97.000 (96.000) Prec@5 99.000 (99.800) +2022-11-14 14:18:04,524 Epoch: [177][50/500] Time 0.024 (0.025) Data 0.002 (0.007) Loss 0.0410 (0.0302) Prec@1 93.000 (95.500) Prec@5 99.000 (99.667) +2022-11-14 14:18:04,881 Epoch: [177][60/500] Time 0.032 (0.026) Data 0.002 (0.006) Loss 0.0417 (0.0318) Prec@1 93.000 (95.143) Prec@5 100.000 (99.714) +2022-11-14 14:18:05,176 Epoch: [177][70/500] Time 0.027 (0.026) Data 0.002 (0.005) Loss 0.0402 (0.0329) Prec@1 95.000 (95.125) Prec@5 99.000 (99.625) +2022-11-14 14:18:05,518 Epoch: [177][80/500] Time 0.028 (0.027) Data 0.002 (0.005) Loss 0.0355 (0.0332) Prec@1 95.000 (95.111) Prec@5 100.000 (99.667) +2022-11-14 14:18:05,915 Epoch: [177][90/500] Time 0.034 (0.028) Data 0.002 (0.005) Loss 0.0506 (0.0349) Prec@1 92.000 (94.800) Prec@5 99.000 (99.600) +2022-11-14 14:18:06,218 Epoch: [177][100/500] Time 0.027 (0.028) Data 0.002 (0.004) Loss 0.0553 (0.0368) Prec@1 91.000 (94.455) Prec@5 100.000 (99.636) +2022-11-14 14:18:06,536 Epoch: [177][110/500] Time 0.028 (0.028) Data 0.002 (0.004) Loss 0.0276 (0.0360) Prec@1 95.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 14:18:07,003 Epoch: [177][120/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.0550 (0.0375) Prec@1 91.000 (94.231) Prec@5 99.000 (99.615) +2022-11-14 14:18:07,480 Epoch: [177][130/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.0411 (0.0377) Prec@1 95.000 (94.286) Prec@5 100.000 (99.643) +2022-11-14 14:18:08,167 Epoch: [177][140/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.0350 (0.0375) Prec@1 95.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 14:18:08,636 Epoch: [177][150/500] Time 0.039 (0.033) Data 0.002 (0.004) Loss 0.0634 (0.0392) Prec@1 89.000 (94.000) Prec@5 100.000 (99.688) +2022-11-14 14:18:09,112 Epoch: [177][160/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0460 (0.0396) Prec@1 91.000 (93.824) Prec@5 99.000 (99.647) +2022-11-14 14:18:09,576 Epoch: [177][170/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0467 (0.0400) Prec@1 94.000 (93.833) Prec@5 99.000 (99.611) +2022-11-14 14:18:10,051 Epoch: [177][180/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0476 (0.0404) Prec@1 91.000 (93.684) Prec@5 99.000 (99.579) +2022-11-14 14:18:10,682 Epoch: [177][190/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0464 (0.0407) Prec@1 91.000 (93.550) Prec@5 99.000 (99.550) +2022-11-14 14:18:11,211 Epoch: [177][200/500] Time 0.052 (0.036) Data 0.002 (0.003) Loss 0.0413 (0.0407) Prec@1 92.000 (93.476) Prec@5 99.000 (99.524) +2022-11-14 14:18:11,688 Epoch: [177][210/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0690 (0.0420) Prec@1 89.000 (93.273) Prec@5 100.000 (99.545) +2022-11-14 14:18:12,177 Epoch: [177][220/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0365 (0.0417) Prec@1 96.000 (93.391) Prec@5 99.000 (99.522) +2022-11-14 14:18:12,744 Epoch: [177][230/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.0379 (0.0416) Prec@1 93.000 (93.375) Prec@5 100.000 (99.542) +2022-11-14 14:18:13,271 Epoch: [177][240/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0312 (0.0412) Prec@1 93.000 (93.360) Prec@5 99.000 (99.520) +2022-11-14 14:18:13,817 Epoch: [177][250/500] Time 0.066 (0.038) Data 0.002 (0.003) Loss 0.0520 (0.0416) Prec@1 90.000 (93.231) Prec@5 100.000 (99.538) +2022-11-14 14:18:14,302 Epoch: [177][260/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0313 (0.0412) Prec@1 96.000 (93.333) Prec@5 100.000 (99.556) +2022-11-14 14:18:14,811 Epoch: [177][270/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0425 (0.0412) Prec@1 92.000 (93.286) Prec@5 99.000 (99.536) +2022-11-14 14:18:15,355 Epoch: [177][280/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0465 (0.0414) Prec@1 94.000 (93.310) Prec@5 99.000 (99.517) +2022-11-14 14:18:15,907 Epoch: [177][290/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0386 (0.0413) Prec@1 94.000 (93.333) Prec@5 100.000 (99.533) +2022-11-14 14:18:16,580 Epoch: [177][300/500] Time 0.085 (0.040) Data 0.002 (0.003) Loss 0.0312 (0.0410) Prec@1 97.000 (93.452) Prec@5 100.000 (99.548) +2022-11-14 14:18:17,044 Epoch: [177][310/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0510 (0.0413) Prec@1 90.000 (93.344) Prec@5 100.000 (99.562) +2022-11-14 14:18:17,518 Epoch: [177][320/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0492 (0.0416) Prec@1 92.000 (93.303) Prec@5 100.000 (99.576) +2022-11-14 14:18:18,001 Epoch: [177][330/500] Time 0.049 (0.040) Data 0.003 (0.003) Loss 0.0640 (0.0422) Prec@1 88.000 (93.147) Prec@5 100.000 (99.588) +2022-11-14 14:18:18,523 Epoch: [177][340/500] Time 0.073 (0.040) Data 0.002 (0.003) Loss 0.0703 (0.0430) Prec@1 91.000 (93.086) Prec@5 98.000 (99.543) +2022-11-14 14:18:19,057 Epoch: [177][350/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0571 (0.0434) Prec@1 89.000 (92.972) Prec@5 99.000 (99.528) +2022-11-14 14:18:19,557 Epoch: [177][360/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0410 (0.0433) Prec@1 92.000 (92.946) Prec@5 100.000 (99.541) +2022-11-14 14:18:20,151 Epoch: [177][370/500] Time 0.039 (0.041) Data 0.002 (0.003) Loss 0.0351 (0.0431) Prec@1 94.000 (92.974) Prec@5 98.000 (99.500) +2022-11-14 14:18:20,704 Epoch: [177][380/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0676 (0.0438) Prec@1 88.000 (92.846) Prec@5 99.000 (99.487) +2022-11-14 14:18:21,290 Epoch: [177][390/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0294 (0.0434) Prec@1 96.000 (92.925) Prec@5 100.000 (99.500) +2022-11-14 14:18:21,799 Epoch: [177][400/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0305 (0.0431) Prec@1 96.000 (93.000) Prec@5 100.000 (99.512) +2022-11-14 14:18:22,405 Epoch: [177][410/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0264 (0.0427) Prec@1 96.000 (93.071) Prec@5 100.000 (99.524) +2022-11-14 14:18:23,032 Epoch: [177][420/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0439 (0.0427) Prec@1 93.000 (93.070) Prec@5 99.000 (99.512) +2022-11-14 14:18:23,646 Epoch: [177][430/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0549 (0.0430) Prec@1 90.000 (93.000) Prec@5 100.000 (99.523) +2022-11-14 14:18:24,220 Epoch: [177][440/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0645 (0.0435) Prec@1 90.000 (92.933) Prec@5 99.000 (99.511) +2022-11-14 14:18:24,905 Epoch: [177][450/500] Time 0.069 (0.043) Data 0.003 (0.003) Loss 0.0442 (0.0435) Prec@1 93.000 (92.935) Prec@5 100.000 (99.522) +2022-11-14 14:18:25,390 Epoch: [177][460/500] Time 0.041 (0.043) Data 0.003 (0.003) Loss 0.0499 (0.0436) Prec@1 91.000 (92.894) Prec@5 99.000 (99.511) +2022-11-14 14:18:25,867 Epoch: [177][470/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0776 (0.0443) Prec@1 88.000 (92.792) Prec@5 99.000 (99.500) +2022-11-14 14:18:26,422 Epoch: [177][480/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0404 (0.0442) Prec@1 92.000 (92.776) Prec@5 100.000 (99.510) +2022-11-14 14:18:27,068 Epoch: [177][490/500] Time 0.057 (0.044) Data 0.002 (0.003) Loss 0.0783 (0.0449) Prec@1 87.000 (92.660) Prec@5 100.000 (99.520) +2022-11-14 14:18:27,555 Epoch: [177][499/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0414 (0.0449) Prec@1 94.000 (92.686) Prec@5 100.000 (99.529) +2022-11-14 14:18:27,882 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0638 (0.0638) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:18:27,895 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0602 (0.0620) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:18:27,908 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1031 (0.0757) Prec@1 80.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 14:18:27,923 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0776 (0.0762) Prec@1 88.000 (86.500) Prec@5 99.000 (99.000) +2022-11-14 14:18:27,934 Test: [4/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0594 (0.0728) Prec@1 90.000 (87.200) Prec@5 99.000 (99.000) +2022-11-14 14:18:27,945 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0230 (0.0645) Prec@1 96.000 (88.667) Prec@5 100.000 (99.167) +2022-11-14 14:18:27,957 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0752 (0.0660) Prec@1 89.000 (88.714) Prec@5 100.000 (99.286) +2022-11-14 14:18:27,970 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1085 (0.0713) Prec@1 81.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 14:18:27,979 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0852 (0.0729) Prec@1 85.000 (87.444) Prec@5 98.000 (99.111) +2022-11-14 14:18:27,990 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0627 (0.0719) Prec@1 88.000 (87.500) Prec@5 99.000 (99.100) +2022-11-14 14:18:28,000 Test: [10/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0626 (0.0710) Prec@1 90.000 (87.727) Prec@5 100.000 (99.182) +2022-11-14 14:18:28,011 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0715) Prec@1 88.000 (87.750) Prec@5 98.000 (99.083) +2022-11-14 14:18:28,022 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0457 (0.0695) Prec@1 91.000 (88.000) Prec@5 100.000 (99.154) +2022-11-14 14:18:28,032 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0956 (0.0714) Prec@1 85.000 (87.786) Prec@5 99.000 (99.143) +2022-11-14 14:18:28,041 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0717) Prec@1 89.000 (87.867) Prec@5 100.000 (99.200) +2022-11-14 14:18:28,052 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0717) Prec@1 88.000 (87.875) Prec@5 100.000 (99.250) +2022-11-14 14:18:28,063 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0416 (0.0700) Prec@1 93.000 (88.176) Prec@5 99.000 (99.235) +2022-11-14 14:18:28,073 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1071 (0.0720) Prec@1 83.000 (87.889) Prec@5 99.000 (99.222) +2022-11-14 14:18:28,083 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0722) Prec@1 85.000 (87.737) Prec@5 98.000 (99.158) +2022-11-14 14:18:28,093 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0729) Prec@1 86.000 (87.650) Prec@5 100.000 (99.200) +2022-11-14 14:18:28,104 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0732) Prec@1 84.000 (87.476) Prec@5 99.000 (99.190) +2022-11-14 14:18:28,114 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0731) Prec@1 89.000 (87.545) Prec@5 99.000 (99.182) +2022-11-14 14:18:28,124 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0937 (0.0740) Prec@1 85.000 (87.435) Prec@5 98.000 (99.130) +2022-11-14 14:18:28,134 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0741) Prec@1 86.000 (87.375) Prec@5 99.000 (99.125) +2022-11-14 14:18:28,144 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0741) Prec@1 90.000 (87.480) Prec@5 100.000 (99.160) +2022-11-14 14:18:28,154 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0749) Prec@1 83.000 (87.308) Prec@5 98.000 (99.115) +2022-11-14 14:18:28,164 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0741) Prec@1 92.000 (87.481) Prec@5 100.000 (99.148) +2022-11-14 14:18:28,174 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0739) Prec@1 91.000 (87.607) Prec@5 99.000 (99.143) +2022-11-14 14:18:28,182 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0738) Prec@1 87.000 (87.586) Prec@5 96.000 (99.034) +2022-11-14 14:18:28,192 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1100 (0.0750) Prec@1 84.000 (87.467) Prec@5 98.000 (99.000) +2022-11-14 14:18:28,201 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0752) Prec@1 87.000 (87.452) Prec@5 99.000 (99.000) +2022-11-14 14:18:28,210 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0747) Prec@1 90.000 (87.531) Prec@5 99.000 (99.000) +2022-11-14 14:18:28,220 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0752) Prec@1 83.000 (87.394) Prec@5 100.000 (99.030) +2022-11-14 14:18:28,230 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0751) Prec@1 88.000 (87.412) Prec@5 100.000 (99.059) +2022-11-14 14:18:28,239 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0758) Prec@1 82.000 (87.257) Prec@5 97.000 (99.000) +2022-11-14 14:18:28,250 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0758) Prec@1 87.000 (87.250) Prec@5 99.000 (99.000) +2022-11-14 14:18:28,260 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0756) Prec@1 92.000 (87.378) Prec@5 98.000 (98.973) +2022-11-14 14:18:28,270 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0762) Prec@1 80.000 (87.184) Prec@5 99.000 (98.974) +2022-11-14 14:18:28,280 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0758) Prec@1 91.000 (87.282) Prec@5 99.000 (98.974) +2022-11-14 14:18:28,290 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0755) Prec@1 86.000 (87.250) Prec@5 99.000 (98.975) +2022-11-14 14:18:28,299 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0757) Prec@1 87.000 (87.244) Prec@5 99.000 (98.976) +2022-11-14 14:18:28,309 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0757) Prec@1 86.000 (87.214) Prec@5 100.000 (99.000) +2022-11-14 14:18:28,319 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0749) Prec@1 94.000 (87.372) Prec@5 100.000 (99.023) +2022-11-14 14:18:28,329 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0746) Prec@1 92.000 (87.477) Prec@5 98.000 (99.000) +2022-11-14 14:18:28,339 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0744) Prec@1 89.000 (87.511) Prec@5 100.000 (99.022) +2022-11-14 14:18:28,350 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0747) Prec@1 87.000 (87.500) Prec@5 99.000 (99.022) +2022-11-14 14:18:28,360 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0750) Prec@1 85.000 (87.447) Prec@5 99.000 (99.021) +2022-11-14 14:18:28,370 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0751) Prec@1 85.000 (87.396) Prec@5 98.000 (99.000) +2022-11-14 14:18:28,380 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0748) Prec@1 90.000 (87.449) Prec@5 100.000 (99.020) +2022-11-14 14:18:28,389 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1252 (0.0758) Prec@1 79.000 (87.280) Prec@5 99.000 (99.020) +2022-11-14 14:18:28,399 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0757) Prec@1 87.000 (87.275) Prec@5 100.000 (99.039) +2022-11-14 14:18:28,409 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0760) Prec@1 83.000 (87.192) Prec@5 99.000 (99.038) +2022-11-14 14:18:28,418 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0757) Prec@1 90.000 (87.245) Prec@5 99.000 (99.038) +2022-11-14 14:18:28,428 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0756) Prec@1 89.000 (87.278) Prec@5 99.000 (99.037) +2022-11-14 14:18:28,437 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0757) Prec@1 86.000 (87.255) Prec@5 100.000 (99.055) +2022-11-14 14:18:28,446 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0761) Prec@1 84.000 (87.196) Prec@5 99.000 (99.054) +2022-11-14 14:18:28,455 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0764) Prec@1 83.000 (87.123) Prec@5 100.000 (99.070) +2022-11-14 14:18:28,465 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0762) Prec@1 88.000 (87.138) Prec@5 100.000 (99.086) +2022-11-14 14:18:28,475 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0764) Prec@1 86.000 (87.119) Prec@5 99.000 (99.085) +2022-11-14 14:18:28,485 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0765) Prec@1 82.000 (87.033) Prec@5 100.000 (99.100) +2022-11-14 14:18:28,495 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0765) Prec@1 89.000 (87.066) Prec@5 100.000 (99.115) +2022-11-14 14:18:28,504 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0768) Prec@1 86.000 (87.048) Prec@5 98.000 (99.097) +2022-11-14 14:18:28,514 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0768) Prec@1 86.000 (87.032) Prec@5 99.000 (99.095) +2022-11-14 14:18:28,523 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0764) Prec@1 93.000 (87.125) Prec@5 100.000 (99.109) +2022-11-14 14:18:28,532 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0765) Prec@1 86.000 (87.108) Prec@5 99.000 (99.108) +2022-11-14 14:18:28,542 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0769) Prec@1 82.000 (87.030) Prec@5 99.000 (99.106) +2022-11-14 14:18:28,553 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0765) Prec@1 91.000 (87.090) Prec@5 100.000 (99.119) +2022-11-14 14:18:28,563 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0767) Prec@1 84.000 (87.044) Prec@5 98.000 (99.103) +2022-11-14 14:18:28,574 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0764) Prec@1 90.000 (87.087) Prec@5 98.000 (99.087) +2022-11-14 14:18:28,586 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0767) Prec@1 86.000 (87.071) Prec@5 99.000 (99.086) +2022-11-14 14:18:28,599 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0770) Prec@1 85.000 (87.042) Prec@5 99.000 (99.085) +2022-11-14 14:18:28,614 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0768) Prec@1 90.000 (87.083) Prec@5 99.000 (99.083) +2022-11-14 14:18:28,626 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0766) Prec@1 91.000 (87.137) Prec@5 100.000 (99.096) +2022-11-14 14:18:28,639 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0764) Prec@1 90.000 (87.176) Prec@5 100.000 (99.108) +2022-11-14 14:18:28,652 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0765) Prec@1 86.000 (87.160) Prec@5 99.000 (99.107) +2022-11-14 14:18:28,664 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0764) Prec@1 88.000 (87.171) Prec@5 100.000 (99.118) +2022-11-14 14:18:28,677 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0763) Prec@1 89.000 (87.195) Prec@5 100.000 (99.130) +2022-11-14 14:18:28,689 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0766) Prec@1 82.000 (87.128) Prec@5 99.000 (99.128) +2022-11-14 14:18:28,701 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0767) Prec@1 87.000 (87.127) Prec@5 100.000 (99.139) +2022-11-14 14:18:28,715 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0768) Prec@1 84.000 (87.088) Prec@5 98.000 (99.125) +2022-11-14 14:18:28,727 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0768) Prec@1 88.000 (87.099) Prec@5 99.000 (99.123) +2022-11-14 14:18:28,739 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0769) Prec@1 86.000 (87.085) Prec@5 98.000 (99.110) +2022-11-14 14:18:28,755 Test: [82/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0770) Prec@1 85.000 (87.060) Prec@5 99.000 (99.108) +2022-11-14 14:18:28,769 Test: [83/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0769) Prec@1 87.000 (87.060) Prec@5 100.000 (99.119) +2022-11-14 14:18:28,781 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0771) Prec@1 86.000 (87.047) Prec@5 99.000 (99.118) +2022-11-14 14:18:28,794 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0772) Prec@1 87.000 (87.047) Prec@5 99.000 (99.116) +2022-11-14 14:18:28,807 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0773) Prec@1 83.000 (87.000) Prec@5 100.000 (99.126) +2022-11-14 14:18:28,820 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0773) Prec@1 89.000 (87.023) Prec@5 100.000 (99.136) +2022-11-14 14:18:28,832 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0772) Prec@1 87.000 (87.022) Prec@5 99.000 (99.135) +2022-11-14 14:18:28,842 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0773) Prec@1 87.000 (87.022) Prec@5 99.000 (99.133) +2022-11-14 14:18:28,853 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0422 (0.0770) Prec@1 92.000 (87.077) Prec@5 100.000 (99.143) +2022-11-14 14:18:28,862 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0452 (0.0766) Prec@1 94.000 (87.152) Prec@5 99.000 (99.141) +2022-11-14 14:18:28,872 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0767) Prec@1 87.000 (87.151) Prec@5 100.000 (99.151) +2022-11-14 14:18:28,881 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0770) Prec@1 83.000 (87.106) Prec@5 98.000 (99.138) +2022-11-14 14:18:28,891 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0768) Prec@1 88.000 (87.116) Prec@5 98.000 (99.126) +2022-11-14 14:18:28,900 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0766) Prec@1 93.000 (87.177) Prec@5 100.000 (99.135) +2022-11-14 14:18:28,911 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0763) Prec@1 93.000 (87.237) Prec@5 99.000 (99.134) +2022-11-14 14:18:28,921 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0764) Prec@1 84.000 (87.204) Prec@5 99.000 (99.133) +2022-11-14 14:18:28,930 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0767) Prec@1 85.000 (87.182) Prec@5 98.000 (99.121) +2022-11-14 14:18:28,938 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0767) Prec@1 88.000 (87.190) Prec@5 99.000 (99.120) +2022-11-14 14:18:29,010 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:18:29,373 Epoch: [178][0/500] Time 0.040 (0.040) Data 0.261 (0.261) Loss 0.0510 (0.0510) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:29,640 Epoch: [178][10/500] Time 0.019 (0.025) Data 0.003 (0.026) Loss 0.0505 (0.0508) Prec@1 92.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:18:29,850 Epoch: [178][20/500] Time 0.018 (0.022) Data 0.002 (0.014) Loss 0.0538 (0.0518) Prec@1 89.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 14:18:30,124 Epoch: [178][30/500] Time 0.026 (0.023) Data 0.002 (0.010) Loss 0.0581 (0.0534) Prec@1 93.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:18:30,447 Epoch: [178][40/500] Time 0.029 (0.024) Data 0.002 (0.008) Loss 0.0464 (0.0520) Prec@1 92.000 (91.200) Prec@5 100.000 (99.600) +2022-11-14 14:18:30,741 Epoch: [178][50/500] Time 0.028 (0.024) Data 0.002 (0.007) Loss 0.0481 (0.0513) Prec@1 90.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:18:31,079 Epoch: [178][60/500] Time 0.025 (0.025) Data 0.002 (0.006) Loss 0.0585 (0.0524) Prec@1 91.000 (91.000) Prec@5 100.000 (99.714) +2022-11-14 14:18:31,379 Epoch: [178][70/500] Time 0.034 (0.025) Data 0.002 (0.006) Loss 0.0706 (0.0546) Prec@1 88.000 (90.625) Prec@5 100.000 (99.750) +2022-11-14 14:18:31,691 Epoch: [178][80/500] Time 0.028 (0.026) Data 0.002 (0.005) Loss 0.0531 (0.0545) Prec@1 92.000 (90.778) Prec@5 98.000 (99.556) +2022-11-14 14:18:32,000 Epoch: [178][90/500] Time 0.028 (0.026) Data 0.002 (0.005) Loss 0.0250 (0.0515) Prec@1 97.000 (91.400) Prec@5 100.000 (99.600) +2022-11-14 14:18:32,352 Epoch: [178][100/500] Time 0.050 (0.026) Data 0.002 (0.004) Loss 0.0450 (0.0509) Prec@1 93.000 (91.545) Prec@5 99.000 (99.545) +2022-11-14 14:18:32,694 Epoch: [178][110/500] Time 0.039 (0.027) Data 0.001 (0.004) Loss 0.0489 (0.0508) Prec@1 92.000 (91.583) Prec@5 100.000 (99.583) +2022-11-14 14:18:33,200 Epoch: [178][120/500] Time 0.057 (0.028) Data 0.002 (0.004) Loss 0.0543 (0.0510) Prec@1 91.000 (91.538) Prec@5 99.000 (99.538) +2022-11-14 14:18:33,707 Epoch: [178][130/500] Time 0.052 (0.030) Data 0.002 (0.004) Loss 0.0641 (0.0520) Prec@1 88.000 (91.286) Prec@5 100.000 (99.571) +2022-11-14 14:18:34,147 Epoch: [178][140/500] Time 0.062 (0.030) Data 0.002 (0.004) Loss 0.0442 (0.0514) Prec@1 91.000 (91.267) Prec@5 100.000 (99.600) +2022-11-14 14:18:34,577 Epoch: [178][150/500] Time 0.042 (0.031) Data 0.002 (0.004) Loss 0.0361 (0.0505) Prec@1 93.000 (91.375) Prec@5 100.000 (99.625) +2022-11-14 14:18:35,009 Epoch: [178][160/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.0360 (0.0496) Prec@1 94.000 (91.529) Prec@5 100.000 (99.647) +2022-11-14 14:18:35,492 Epoch: [178][170/500] Time 0.029 (0.032) Data 0.002 (0.003) Loss 0.0383 (0.0490) Prec@1 96.000 (91.778) Prec@5 100.000 (99.667) +2022-11-14 14:18:35,922 Epoch: [178][180/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0473 (0.0489) Prec@1 93.000 (91.842) Prec@5 100.000 (99.684) +2022-11-14 14:18:36,452 Epoch: [178][190/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0608 (0.0495) Prec@1 90.000 (91.750) Prec@5 100.000 (99.700) +2022-11-14 14:18:36,995 Epoch: [178][200/500] Time 0.053 (0.034) Data 0.002 (0.003) Loss 0.0523 (0.0496) Prec@1 90.000 (91.667) Prec@5 98.000 (99.619) +2022-11-14 14:18:37,480 Epoch: [178][210/500] Time 0.031 (0.035) Data 0.002 (0.003) Loss 0.0475 (0.0495) Prec@1 93.000 (91.727) Prec@5 99.000 (99.591) +2022-11-14 14:18:37,950 Epoch: [178][220/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0270 (0.0486) Prec@1 95.000 (91.870) Prec@5 100.000 (99.609) +2022-11-14 14:18:38,433 Epoch: [178][230/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.0259 (0.0476) Prec@1 94.000 (91.958) Prec@5 100.000 (99.625) +2022-11-14 14:18:38,924 Epoch: [178][240/500] Time 0.071 (0.036) Data 0.002 (0.003) Loss 0.0712 (0.0486) Prec@1 88.000 (91.800) Prec@5 100.000 (99.640) +2022-11-14 14:18:39,384 Epoch: [178][250/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0511 (0.0487) Prec@1 92.000 (91.808) Prec@5 99.000 (99.615) +2022-11-14 14:18:39,821 Epoch: [178][260/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0352 (0.0482) Prec@1 95.000 (91.926) Prec@5 99.000 (99.593) +2022-11-14 14:18:40,317 Epoch: [178][270/500] Time 0.069 (0.036) Data 0.002 (0.003) Loss 0.0575 (0.0485) Prec@1 90.000 (91.857) Prec@5 100.000 (99.607) +2022-11-14 14:18:40,734 Epoch: [178][280/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0403 (0.0482) Prec@1 94.000 (91.931) Prec@5 98.000 (99.552) +2022-11-14 14:18:41,230 Epoch: [178][290/500] Time 0.032 (0.036) Data 0.002 (0.003) Loss 0.0455 (0.0481) Prec@1 92.000 (91.933) Prec@5 99.000 (99.533) +2022-11-14 14:18:41,733 Epoch: [178][300/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.0529 (0.0483) Prec@1 91.000 (91.903) Prec@5 100.000 (99.548) +2022-11-14 14:18:42,155 Epoch: [178][310/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0820 (0.0493) Prec@1 85.000 (91.688) Prec@5 100.000 (99.562) +2022-11-14 14:18:42,711 Epoch: [178][320/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0750 (0.0501) Prec@1 87.000 (91.545) Prec@5 99.000 (99.545) +2022-11-14 14:18:43,204 Epoch: [178][330/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.0410 (0.0498) Prec@1 93.000 (91.588) Prec@5 100.000 (99.559) +2022-11-14 14:18:43,660 Epoch: [178][340/500] Time 0.068 (0.037) Data 0.002 (0.003) Loss 0.0363 (0.0495) Prec@1 93.000 (91.629) Prec@5 100.000 (99.571) +2022-11-14 14:18:44,091 Epoch: [178][350/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0366 (0.0491) Prec@1 93.000 (91.667) Prec@5 100.000 (99.583) +2022-11-14 14:18:44,571 Epoch: [178][360/500] Time 0.030 (0.038) Data 0.002 (0.003) Loss 0.0484 (0.0491) Prec@1 93.000 (91.703) Prec@5 100.000 (99.595) +2022-11-14 14:18:45,036 Epoch: [178][370/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0292 (0.0486) Prec@1 95.000 (91.789) Prec@5 100.000 (99.605) +2022-11-14 14:18:45,473 Epoch: [178][380/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0469 (0.0485) Prec@1 92.000 (91.795) Prec@5 100.000 (99.615) +2022-11-14 14:18:45,912 Epoch: [178][390/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0489 (0.0485) Prec@1 92.000 (91.800) Prec@5 99.000 (99.600) +2022-11-14 14:18:46,353 Epoch: [178][400/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0679 (0.0490) Prec@1 87.000 (91.683) Prec@5 100.000 (99.610) +2022-11-14 14:18:46,795 Epoch: [178][410/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0562 (0.0492) Prec@1 91.000 (91.667) Prec@5 100.000 (99.619) +2022-11-14 14:18:47,229 Epoch: [178][420/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0622 (0.0495) Prec@1 90.000 (91.628) Prec@5 99.000 (99.605) +2022-11-14 14:18:47,729 Epoch: [178][430/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0517 (0.0495) Prec@1 90.000 (91.591) Prec@5 100.000 (99.614) +2022-11-14 14:18:48,169 Epoch: [178][440/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0412 (0.0493) Prec@1 94.000 (91.644) Prec@5 100.000 (99.622) +2022-11-14 14:18:48,624 Epoch: [178][450/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0486 (0.0493) Prec@1 93.000 (91.674) Prec@5 100.000 (99.630) +2022-11-14 14:18:49,073 Epoch: [178][460/500] Time 0.047 (0.038) Data 0.003 (0.003) Loss 0.0355 (0.0490) Prec@1 94.000 (91.723) Prec@5 99.000 (99.617) +2022-11-14 14:18:49,516 Epoch: [178][470/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0426 (0.0489) Prec@1 93.000 (91.750) Prec@5 100.000 (99.625) +2022-11-14 14:18:49,943 Epoch: [178][480/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0392 (0.0487) Prec@1 93.000 (91.776) Prec@5 100.000 (99.633) +2022-11-14 14:18:50,392 Epoch: [178][490/500] Time 0.050 (0.038) Data 0.002 (0.002) Loss 0.0175 (0.0481) Prec@1 97.000 (91.880) Prec@5 100.000 (99.640) +2022-11-14 14:18:50,784 Epoch: [178][499/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0358 (0.0478) Prec@1 92.000 (91.882) Prec@5 100.000 (99.647) +2022-11-14 14:18:51,088 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0791 (0.0791) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 14:18:51,096 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0681 (0.0736) Prec@1 88.000 (87.500) Prec@5 99.000 (99.000) +2022-11-14 14:18:51,105 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0772) Prec@1 85.000 (86.667) Prec@5 100.000 (99.333) +2022-11-14 14:18:51,116 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0807) Prec@1 84.000 (86.000) Prec@5 99.000 (99.250) +2022-11-14 14:18:51,124 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0813) Prec@1 84.000 (85.600) Prec@5 99.000 (99.200) +2022-11-14 14:18:51,131 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0765) Prec@1 92.000 (86.667) Prec@5 100.000 (99.333) +2022-11-14 14:18:51,138 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0781) Prec@1 88.000 (86.857) Prec@5 99.000 (99.286) +2022-11-14 14:18:51,147 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0791) Prec@1 86.000 (86.750) Prec@5 99.000 (99.250) +2022-11-14 14:18:51,157 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0796) Prec@1 89.000 (87.000) Prec@5 98.000 (99.111) +2022-11-14 14:18:51,166 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0791) Prec@1 87.000 (87.000) Prec@5 99.000 (99.100) +2022-11-14 14:18:51,175 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0769) Prec@1 89.000 (87.182) Prec@5 99.000 (99.091) +2022-11-14 14:18:51,184 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0768) Prec@1 89.000 (87.333) Prec@5 99.000 (99.083) +2022-11-14 14:18:51,193 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0742) Prec@1 94.000 (87.846) Prec@5 100.000 (99.154) +2022-11-14 14:18:51,203 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0734) Prec@1 87.000 (87.786) Prec@5 100.000 (99.214) +2022-11-14 14:18:51,212 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0737) Prec@1 89.000 (87.867) Prec@5 100.000 (99.267) +2022-11-14 14:18:51,221 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0741) Prec@1 88.000 (87.875) Prec@5 99.000 (99.250) +2022-11-14 14:18:51,231 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0736) Prec@1 89.000 (87.941) Prec@5 99.000 (99.235) +2022-11-14 14:18:51,241 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0754) Prec@1 84.000 (87.722) Prec@5 100.000 (99.278) +2022-11-14 14:18:51,251 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0754) Prec@1 86.000 (87.632) Prec@5 99.000 (99.263) +2022-11-14 14:18:51,261 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0767) Prec@1 84.000 (87.450) Prec@5 97.000 (99.150) +2022-11-14 14:18:51,270 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0780) Prec@1 84.000 (87.286) Prec@5 99.000 (99.143) +2022-11-14 14:18:51,280 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0786) Prec@1 84.000 (87.136) Prec@5 98.000 (99.091) +2022-11-14 14:18:51,289 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0794) Prec@1 85.000 (87.043) Prec@5 99.000 (99.087) +2022-11-14 14:18:51,300 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0786) Prec@1 91.000 (87.208) Prec@5 100.000 (99.125) +2022-11-14 14:18:51,309 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0787) Prec@1 86.000 (87.160) Prec@5 100.000 (99.160) +2022-11-14 14:18:51,319 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0798) Prec@1 80.000 (86.885) Prec@5 98.000 (99.115) +2022-11-14 14:18:51,327 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0786) Prec@1 92.000 (87.074) Prec@5 100.000 (99.148) +2022-11-14 14:18:51,336 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0782) Prec@1 89.000 (87.143) Prec@5 100.000 (99.179) +2022-11-14 14:18:51,346 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0779) Prec@1 87.000 (87.138) Prec@5 99.000 (99.172) +2022-11-14 14:18:51,356 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0775) Prec@1 89.000 (87.200) Prec@5 99.000 (99.167) +2022-11-14 14:18:51,365 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0772) Prec@1 89.000 (87.258) Prec@5 99.000 (99.161) +2022-11-14 14:18:51,374 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0767) Prec@1 90.000 (87.344) Prec@5 99.000 (99.156) +2022-11-14 14:18:51,383 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0766) Prec@1 85.000 (87.273) Prec@5 100.000 (99.182) +2022-11-14 14:18:51,392 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0768) Prec@1 86.000 (87.235) Prec@5 100.000 (99.206) +2022-11-14 14:18:51,402 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0775) Prec@1 84.000 (87.143) Prec@5 98.000 (99.171) +2022-11-14 14:18:51,413 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0770) Prec@1 91.000 (87.250) Prec@5 99.000 (99.167) +2022-11-14 14:18:51,421 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0770) Prec@1 87.000 (87.243) Prec@5 99.000 (99.162) +2022-11-14 14:18:51,430 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0777) Prec@1 85.000 (87.184) Prec@5 99.000 (99.158) +2022-11-14 14:18:51,438 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0770) Prec@1 93.000 (87.333) Prec@5 99.000 (99.154) +2022-11-14 14:18:51,447 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0769) Prec@1 87.000 (87.325) Prec@5 99.000 (99.150) +2022-11-14 14:18:51,460 Test: [40/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0774) Prec@1 86.000 (87.293) Prec@5 98.000 (99.122) +2022-11-14 14:18:51,473 Test: [41/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0773) Prec@1 88.000 (87.310) Prec@5 99.000 (99.119) +2022-11-14 14:18:51,482 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0765) Prec@1 93.000 (87.442) Prec@5 100.000 (99.140) +2022-11-14 14:18:51,492 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0766) Prec@1 89.000 (87.477) Prec@5 99.000 (99.136) +2022-11-14 14:18:51,501 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0762) Prec@1 87.000 (87.467) Prec@5 100.000 (99.156) +2022-11-14 14:18:51,512 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0765) Prec@1 85.000 (87.413) Prec@5 100.000 (99.174) +2022-11-14 14:18:51,521 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0764) Prec@1 89.000 (87.447) Prec@5 100.000 (99.191) +2022-11-14 14:18:51,531 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0767) Prec@1 83.000 (87.354) Prec@5 98.000 (99.167) +2022-11-14 14:18:51,541 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0764) Prec@1 89.000 (87.388) Prec@5 100.000 (99.184) +2022-11-14 14:18:51,551 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0769) Prec@1 84.000 (87.320) Prec@5 99.000 (99.180) +2022-11-14 14:18:51,562 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0768) Prec@1 90.000 (87.373) Prec@5 98.000 (99.157) +2022-11-14 14:18:51,571 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0771) Prec@1 84.000 (87.308) Prec@5 100.000 (99.173) +2022-11-14 14:18:51,581 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0774) Prec@1 84.000 (87.245) Prec@5 99.000 (99.170) +2022-11-14 14:18:51,590 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0773) Prec@1 87.000 (87.241) Prec@5 99.000 (99.167) +2022-11-14 14:18:51,601 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0770) Prec@1 91.000 (87.309) Prec@5 100.000 (99.182) +2022-11-14 14:18:51,611 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0768) Prec@1 88.000 (87.321) Prec@5 98.000 (99.161) +2022-11-14 14:18:51,621 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0770) Prec@1 88.000 (87.333) Prec@5 100.000 (99.175) +2022-11-14 14:18:51,631 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0768) Prec@1 91.000 (87.397) Prec@5 99.000 (99.172) +2022-11-14 14:18:51,640 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0773) Prec@1 80.000 (87.271) Prec@5 99.000 (99.169) +2022-11-14 14:18:51,651 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0771) Prec@1 88.000 (87.283) Prec@5 100.000 (99.183) +2022-11-14 14:18:51,662 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0771) Prec@1 87.000 (87.279) Prec@5 100.000 (99.197) +2022-11-14 14:18:51,673 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0773) Prec@1 85.000 (87.242) Prec@5 99.000 (99.194) +2022-11-14 14:18:51,682 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0771) Prec@1 89.000 (87.270) Prec@5 100.000 (99.206) +2022-11-14 14:18:51,692 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0300 (0.0763) Prec@1 96.000 (87.406) Prec@5 100.000 (99.219) +2022-11-14 14:18:51,701 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0765) Prec@1 86.000 (87.385) Prec@5 100.000 (99.231) +2022-11-14 14:18:51,710 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0766) Prec@1 86.000 (87.364) Prec@5 100.000 (99.242) +2022-11-14 14:18:51,721 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0761) Prec@1 94.000 (87.463) Prec@5 100.000 (99.254) +2022-11-14 14:18:51,730 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0763) Prec@1 87.000 (87.456) Prec@5 99.000 (99.250) +2022-11-14 14:18:51,739 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0762) Prec@1 87.000 (87.449) Prec@5 99.000 (99.246) +2022-11-14 14:18:51,749 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0765) Prec@1 86.000 (87.429) Prec@5 98.000 (99.229) +2022-11-14 14:18:51,758 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0766) Prec@1 89.000 (87.451) Prec@5 98.000 (99.211) +2022-11-14 14:18:51,767 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0766) Prec@1 88.000 (87.458) Prec@5 100.000 (99.222) +2022-11-14 14:18:51,776 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0763) Prec@1 93.000 (87.534) Prec@5 100.000 (99.233) +2022-11-14 14:18:51,785 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0759) Prec@1 92.000 (87.595) Prec@5 100.000 (99.243) +2022-11-14 14:18:51,796 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0762) Prec@1 84.000 (87.547) Prec@5 99.000 (99.240) +2022-11-14 14:18:51,805 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0760) Prec@1 91.000 (87.592) Prec@5 99.000 (99.237) +2022-11-14 14:18:51,815 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0759) Prec@1 91.000 (87.636) Prec@5 98.000 (99.221) +2022-11-14 14:18:51,825 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0762) Prec@1 81.000 (87.551) Prec@5 98.000 (99.205) +2022-11-14 14:18:51,834 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0762) Prec@1 89.000 (87.570) Prec@5 100.000 (99.215) +2022-11-14 14:18:51,844 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0761) Prec@1 88.000 (87.575) Prec@5 97.000 (99.188) +2022-11-14 14:18:51,854 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0763) Prec@1 84.000 (87.531) Prec@5 98.000 (99.173) +2022-11-14 14:18:51,863 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0765) Prec@1 85.000 (87.500) Prec@5 100.000 (99.183) +2022-11-14 14:18:51,874 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0764) Prec@1 89.000 (87.518) Prec@5 100.000 (99.193) +2022-11-14 14:18:51,886 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0763) Prec@1 90.000 (87.548) Prec@5 99.000 (99.190) +2022-11-14 14:18:51,896 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0767) Prec@1 83.000 (87.494) Prec@5 98.000 (99.176) +2022-11-14 14:18:51,907 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0768) Prec@1 84.000 (87.453) Prec@5 100.000 (99.186) +2022-11-14 14:18:51,918 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0768) Prec@1 87.000 (87.448) Prec@5 100.000 (99.195) +2022-11-14 14:18:51,928 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0767) Prec@1 91.000 (87.489) Prec@5 100.000 (99.205) +2022-11-14 14:18:51,938 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0768) Prec@1 87.000 (87.483) Prec@5 100.000 (99.213) +2022-11-14 14:18:51,948 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0767) Prec@1 92.000 (87.533) Prec@5 99.000 (99.211) +2022-11-14 14:18:51,959 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0765) Prec@1 89.000 (87.549) Prec@5 100.000 (99.220) +2022-11-14 14:18:51,971 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0763) Prec@1 90.000 (87.576) Prec@5 100.000 (99.228) +2022-11-14 14:18:51,981 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0763) Prec@1 84.000 (87.538) Prec@5 100.000 (99.237) +2022-11-14 14:18:51,991 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0762) Prec@1 91.000 (87.574) Prec@5 100.000 (99.245) +2022-11-14 14:18:52,001 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0760) Prec@1 90.000 (87.600) Prec@5 98.000 (99.232) +2022-11-14 14:18:52,011 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0760) Prec@1 87.000 (87.594) Prec@5 100.000 (99.240) +2022-11-14 14:18:52,020 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0758) Prec@1 89.000 (87.608) Prec@5 100.000 (99.247) +2022-11-14 14:18:52,030 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0760) Prec@1 85.000 (87.582) Prec@5 99.000 (99.245) +2022-11-14 14:18:52,041 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0763) Prec@1 84.000 (87.545) Prec@5 100.000 (99.253) +2022-11-14 14:18:52,052 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0762) Prec@1 90.000 (87.570) Prec@5 99.000 (99.250) +2022-11-14 14:18:52,112 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:18:52,423 Epoch: [179][0/500] Time 0.024 (0.024) Data 0.227 (0.227) Loss 0.0274 (0.0274) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:18:52,628 Epoch: [179][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0365 (0.0319) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:18:52,830 Epoch: [179][20/500] Time 0.018 (0.018) Data 0.002 (0.012) Loss 0.0451 (0.0363) Prec@1 94.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 14:18:53,100 Epoch: [179][30/500] Time 0.036 (0.020) Data 0.002 (0.009) Loss 0.0597 (0.0422) Prec@1 88.000 (92.750) Prec@5 99.000 (99.500) +2022-11-14 14:18:53,459 Epoch: [179][40/500] Time 0.032 (0.023) Data 0.002 (0.007) Loss 0.0315 (0.0400) Prec@1 96.000 (93.400) Prec@5 100.000 (99.600) +2022-11-14 14:18:53,826 Epoch: [179][50/500] Time 0.034 (0.025) Data 0.002 (0.006) Loss 0.0313 (0.0386) Prec@1 94.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 14:18:54,188 Epoch: [179][60/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.0341 (0.0379) Prec@1 94.000 (93.571) Prec@5 100.000 (99.571) +2022-11-14 14:18:54,593 Epoch: [179][70/500] Time 0.027 (0.028) Data 0.002 (0.005) Loss 0.0480 (0.0392) Prec@1 92.000 (93.375) Prec@5 100.000 (99.625) +2022-11-14 14:18:55,016 Epoch: [179][80/500] Time 0.055 (0.029) Data 0.003 (0.005) Loss 0.0342 (0.0387) Prec@1 96.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:18:55,355 Epoch: [179][90/500] Time 0.043 (0.029) Data 0.002 (0.004) Loss 0.0681 (0.0416) Prec@1 86.000 (92.900) Prec@5 99.000 (99.600) +2022-11-14 14:18:55,709 Epoch: [179][100/500] Time 0.034 (0.029) Data 0.002 (0.004) Loss 0.0522 (0.0426) Prec@1 90.000 (92.636) Prec@5 98.000 (99.455) +2022-11-14 14:18:56,113 Epoch: [179][110/500] Time 0.037 (0.030) Data 0.003 (0.004) Loss 0.0326 (0.0417) Prec@1 93.000 (92.667) Prec@5 100.000 (99.500) +2022-11-14 14:18:56,569 Epoch: [179][120/500] Time 0.045 (0.031) Data 0.002 (0.004) Loss 0.0417 (0.0417) Prec@1 93.000 (92.692) Prec@5 100.000 (99.538) +2022-11-14 14:18:56,967 Epoch: [179][130/500] Time 0.025 (0.031) Data 0.002 (0.004) Loss 0.0410 (0.0417) Prec@1 94.000 (92.786) Prec@5 99.000 (99.500) +2022-11-14 14:18:57,376 Epoch: [179][140/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0289 (0.0408) Prec@1 96.000 (93.000) Prec@5 99.000 (99.467) +2022-11-14 14:18:57,919 Epoch: [179][150/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0405 (0.0408) Prec@1 92.000 (92.938) Prec@5 100.000 (99.500) +2022-11-14 14:18:58,459 Epoch: [179][160/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0420 (0.0409) Prec@1 94.000 (93.000) Prec@5 100.000 (99.529) +2022-11-14 14:18:58,998 Epoch: [179][170/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0475 (0.0412) Prec@1 93.000 (93.000) Prec@5 100.000 (99.556) +2022-11-14 14:18:59,570 Epoch: [179][180/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0523 (0.0418) Prec@1 92.000 (92.947) Prec@5 100.000 (99.579) +2022-11-14 14:19:00,130 Epoch: [179][190/500] Time 0.069 (0.036) Data 0.002 (0.003) Loss 0.0270 (0.0411) Prec@1 94.000 (93.000) Prec@5 100.000 (99.600) +2022-11-14 14:19:00,658 Epoch: [179][200/500] Time 0.101 (0.036) Data 0.002 (0.003) Loss 0.0361 (0.0408) Prec@1 96.000 (93.143) Prec@5 100.000 (99.619) +2022-11-14 14:19:01,139 Epoch: [179][210/500] Time 0.058 (0.037) Data 0.002 (0.003) Loss 0.0781 (0.0425) Prec@1 86.000 (92.818) Prec@5 99.000 (99.591) +2022-11-14 14:19:01,612 Epoch: [179][220/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0486 (0.0428) Prec@1 90.000 (92.696) Prec@5 100.000 (99.609) +2022-11-14 14:19:02,094 Epoch: [179][230/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.0321 (0.0424) Prec@1 94.000 (92.750) Prec@5 100.000 (99.625) +2022-11-14 14:19:02,557 Epoch: [179][240/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0343 (0.0420) Prec@1 93.000 (92.760) Prec@5 100.000 (99.640) +2022-11-14 14:19:03,022 Epoch: [179][250/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0654 (0.0429) Prec@1 90.000 (92.654) Prec@5 100.000 (99.654) +2022-11-14 14:19:03,578 Epoch: [179][260/500] Time 0.059 (0.038) Data 0.002 (0.003) Loss 0.0384 (0.0428) Prec@1 94.000 (92.704) Prec@5 100.000 (99.667) +2022-11-14 14:19:04,063 Epoch: [179][270/500] Time 0.045 (0.038) Data 0.001 (0.003) Loss 0.0412 (0.0427) Prec@1 92.000 (92.679) Prec@5 99.000 (99.643) +2022-11-14 14:19:04,531 Epoch: [179][280/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0647 (0.0435) Prec@1 88.000 (92.517) Prec@5 99.000 (99.621) +2022-11-14 14:19:05,074 Epoch: [179][290/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0434 (0.0435) Prec@1 92.000 (92.500) Prec@5 99.000 (99.600) +2022-11-14 14:19:05,620 Epoch: [179][300/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0679 (0.0443) Prec@1 89.000 (92.387) Prec@5 99.000 (99.581) +2022-11-14 14:19:06,105 Epoch: [179][310/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0317 (0.0439) Prec@1 96.000 (92.500) Prec@5 100.000 (99.594) +2022-11-14 14:19:06,596 Epoch: [179][320/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0646 (0.0445) Prec@1 88.000 (92.364) Prec@5 100.000 (99.606) +2022-11-14 14:19:07,094 Epoch: [179][330/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0361 (0.0442) Prec@1 96.000 (92.471) Prec@5 100.000 (99.618) +2022-11-14 14:19:07,642 Epoch: [179][340/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0335 (0.0439) Prec@1 93.000 (92.486) Prec@5 100.000 (99.629) +2022-11-14 14:19:08,152 Epoch: [179][350/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0427 (0.0439) Prec@1 93.000 (92.500) Prec@5 100.000 (99.639) +2022-11-14 14:19:08,653 Epoch: [179][360/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0519 (0.0441) Prec@1 92.000 (92.486) Prec@5 99.000 (99.622) +2022-11-14 14:19:09,158 Epoch: [179][370/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.0225 (0.0435) Prec@1 98.000 (92.632) Prec@5 100.000 (99.632) +2022-11-14 14:19:09,700 Epoch: [179][380/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0672 (0.0442) Prec@1 88.000 (92.513) Prec@5 100.000 (99.641) +2022-11-14 14:19:10,242 Epoch: [179][390/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0344 (0.0439) Prec@1 94.000 (92.550) Prec@5 100.000 (99.650) +2022-11-14 14:19:10,801 Epoch: [179][400/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0351 (0.0437) Prec@1 95.000 (92.610) Prec@5 100.000 (99.659) +2022-11-14 14:19:11,349 Epoch: [179][410/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0320 (0.0434) Prec@1 95.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:19:11,887 Epoch: [179][420/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0426 (0.0434) Prec@1 92.000 (92.651) Prec@5 100.000 (99.674) +2022-11-14 14:19:12,425 Epoch: [179][430/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0363 (0.0432) Prec@1 93.000 (92.659) Prec@5 100.000 (99.682) +2022-11-14 14:19:12,993 Epoch: [179][440/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0363 (0.0431) Prec@1 93.000 (92.667) Prec@5 100.000 (99.689) +2022-11-14 14:19:13,564 Epoch: [179][450/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0591 (0.0434) Prec@1 91.000 (92.630) Prec@5 99.000 (99.674) +2022-11-14 14:19:14,120 Epoch: [179][460/500] Time 0.102 (0.042) Data 0.002 (0.002) Loss 0.0904 (0.0444) Prec@1 85.000 (92.468) Prec@5 99.000 (99.660) +2022-11-14 14:19:14,657 Epoch: [179][470/500] Time 0.064 (0.042) Data 0.002 (0.002) Loss 0.0481 (0.0445) Prec@1 92.000 (92.458) Prec@5 100.000 (99.667) +2022-11-14 14:19:15,311 Epoch: [179][480/500] Time 0.073 (0.042) Data 0.002 (0.002) Loss 0.0329 (0.0443) Prec@1 93.000 (92.469) Prec@5 100.000 (99.673) +2022-11-14 14:19:15,832 Epoch: [179][490/500] Time 0.042 (0.042) Data 0.002 (0.002) Loss 0.0312 (0.0440) Prec@1 94.000 (92.500) Prec@5 100.000 (99.680) +2022-11-14 14:19:16,290 Epoch: [179][499/500] Time 0.044 (0.043) Data 0.002 (0.002) Loss 0.0276 (0.0437) Prec@1 97.000 (92.588) Prec@5 100.000 (99.686) +2022-11-14 14:19:16,592 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0671 (0.0671) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 14:19:16,604 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0840 (0.0755) Prec@1 87.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 14:19:16,615 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0878 (0.0796) Prec@1 83.000 (86.333) Prec@5 100.000 (99.333) +2022-11-14 14:19:16,626 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0792) Prec@1 88.000 (86.750) Prec@5 98.000 (99.000) +2022-11-14 14:19:16,635 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0795) Prec@1 89.000 (87.200) Prec@5 99.000 (99.000) +2022-11-14 14:19:16,644 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0293 (0.0711) Prec@1 96.000 (88.667) Prec@5 100.000 (99.167) +2022-11-14 14:19:16,652 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0702) Prec@1 92.000 (89.143) Prec@5 100.000 (99.286) +2022-11-14 14:19:16,662 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0723) Prec@1 84.000 (88.500) Prec@5 98.000 (99.125) +2022-11-14 14:19:16,670 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0740) Prec@1 86.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 14:19:16,679 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0733) Prec@1 88.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 14:19:16,688 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0709) Prec@1 95.000 (88.818) Prec@5 100.000 (99.273) +2022-11-14 14:19:16,698 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0704) Prec@1 90.000 (88.917) Prec@5 99.000 (99.250) +2022-11-14 14:19:16,707 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0706) Prec@1 89.000 (88.923) Prec@5 98.000 (99.154) +2022-11-14 14:19:16,715 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0710) Prec@1 87.000 (88.786) Prec@5 100.000 (99.214) +2022-11-14 14:19:16,723 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0710) Prec@1 87.000 (88.667) Prec@5 100.000 (99.267) +2022-11-14 14:19:16,731 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0714) Prec@1 82.000 (88.250) Prec@5 100.000 (99.312) +2022-11-14 14:19:16,741 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0708) Prec@1 91.000 (88.412) Prec@5 98.000 (99.235) +2022-11-14 14:19:16,750 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0733) Prec@1 82.000 (88.056) Prec@5 99.000 (99.222) +2022-11-14 14:19:16,760 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0735) Prec@1 87.000 (88.000) Prec@5 100.000 (99.263) +2022-11-14 14:19:16,772 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0749) Prec@1 84.000 (87.800) Prec@5 96.000 (99.100) +2022-11-14 14:19:16,782 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0755) Prec@1 86.000 (87.714) Prec@5 98.000 (99.048) +2022-11-14 14:19:16,791 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0768) Prec@1 84.000 (87.545) Prec@5 98.000 (99.000) +2022-11-14 14:19:16,800 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0776) Prec@1 85.000 (87.435) Prec@5 98.000 (98.957) +2022-11-14 14:19:16,810 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0780) Prec@1 87.000 (87.417) Prec@5 100.000 (99.000) +2022-11-14 14:19:16,819 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0789) Prec@1 84.000 (87.280) Prec@5 100.000 (99.040) +2022-11-14 14:19:16,827 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0792) Prec@1 85.000 (87.192) Prec@5 98.000 (99.000) +2022-11-14 14:19:16,837 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0789) Prec@1 86.000 (87.148) Prec@5 100.000 (99.037) +2022-11-14 14:19:16,846 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0783) Prec@1 88.000 (87.179) Prec@5 100.000 (99.071) +2022-11-14 14:19:16,855 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0783) Prec@1 88.000 (87.207) Prec@5 96.000 (98.966) +2022-11-14 14:19:16,864 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0778) Prec@1 88.000 (87.233) Prec@5 100.000 (99.000) +2022-11-14 14:19:16,874 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0777) Prec@1 89.000 (87.290) Prec@5 100.000 (99.032) +2022-11-14 14:19:16,883 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0772) Prec@1 87.000 (87.281) Prec@5 99.000 (99.031) +2022-11-14 14:19:16,893 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0773) Prec@1 88.000 (87.303) Prec@5 100.000 (99.061) +2022-11-14 14:19:16,902 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0781) Prec@1 82.000 (87.147) Prec@5 99.000 (99.059) +2022-11-14 14:19:16,911 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0778) Prec@1 86.000 (87.114) Prec@5 99.000 (99.057) +2022-11-14 14:19:16,921 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0777) Prec@1 90.000 (87.194) Prec@5 100.000 (99.083) +2022-11-14 14:19:16,930 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0780) Prec@1 81.000 (87.027) Prec@5 99.000 (99.081) +2022-11-14 14:19:16,939 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.0791) Prec@1 81.000 (86.868) Prec@5 99.000 (99.079) +2022-11-14 14:19:16,949 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0784) Prec@1 92.000 (87.000) Prec@5 99.000 (99.077) +2022-11-14 14:19:16,958 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0778) Prec@1 92.000 (87.125) Prec@5 98.000 (99.050) +2022-11-14 14:19:16,967 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0783) Prec@1 84.000 (87.049) Prec@5 99.000 (99.049) +2022-11-14 14:19:16,977 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0786) Prec@1 86.000 (87.024) Prec@5 99.000 (99.048) +2022-11-14 14:19:16,986 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0780) Prec@1 93.000 (87.163) Prec@5 98.000 (99.023) +2022-11-14 14:19:16,995 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0777) Prec@1 93.000 (87.295) Prec@5 98.000 (99.000) +2022-11-14 14:19:17,005 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0778) Prec@1 87.000 (87.289) Prec@5 100.000 (99.022) +2022-11-14 14:19:17,014 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0783) Prec@1 84.000 (87.217) Prec@5 100.000 (99.043) +2022-11-14 14:19:17,024 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0783) Prec@1 87.000 (87.213) Prec@5 100.000 (99.064) +2022-11-14 14:19:17,033 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0788) Prec@1 85.000 (87.167) Prec@5 99.000 (99.062) +2022-11-14 14:19:17,042 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0786) Prec@1 91.000 (87.245) Prec@5 100.000 (99.082) +2022-11-14 14:19:17,053 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0792) Prec@1 83.000 (87.160) Prec@5 100.000 (99.100) +2022-11-14 14:19:17,063 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0790) Prec@1 89.000 (87.196) Prec@5 100.000 (99.118) +2022-11-14 14:19:17,073 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0795) Prec@1 83.000 (87.115) Prec@5 98.000 (99.096) +2022-11-14 14:19:17,082 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0792) Prec@1 88.000 (87.132) Prec@5 99.000 (99.094) +2022-11-14 14:19:17,092 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0789) Prec@1 88.000 (87.148) Prec@5 100.000 (99.111) +2022-11-14 14:19:17,101 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0789) Prec@1 85.000 (87.109) Prec@5 100.000 (99.127) +2022-11-14 14:19:17,111 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0793) Prec@1 81.000 (87.000) Prec@5 99.000 (99.125) +2022-11-14 14:19:17,119 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0793) Prec@1 88.000 (87.018) Prec@5 100.000 (99.140) +2022-11-14 14:19:17,129 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0791) Prec@1 90.000 (87.069) Prec@5 99.000 (99.138) +2022-11-14 14:19:17,138 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0794) Prec@1 84.000 (87.017) Prec@5 99.000 (99.136) +2022-11-14 14:19:17,147 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0795) Prec@1 85.000 (86.983) Prec@5 100.000 (99.150) +2022-11-14 14:19:17,156 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0793) Prec@1 91.000 (87.049) Prec@5 99.000 (99.148) +2022-11-14 14:19:17,166 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0789) Prec@1 89.000 (87.081) Prec@5 99.000 (99.145) +2022-11-14 14:19:17,174 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0787) Prec@1 91.000 (87.143) Prec@5 100.000 (99.159) +2022-11-14 14:19:17,184 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0781) Prec@1 93.000 (87.234) Prec@5 100.000 (99.172) +2022-11-14 14:19:17,193 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0783) Prec@1 85.000 (87.200) Prec@5 100.000 (99.185) +2022-11-14 14:19:17,202 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0785) Prec@1 86.000 (87.182) Prec@5 99.000 (99.182) +2022-11-14 14:19:17,210 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0398 (0.0779) Prec@1 94.000 (87.284) Prec@5 99.000 (99.179) +2022-11-14 14:19:17,219 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0779) Prec@1 90.000 (87.324) Prec@5 100.000 (99.191) +2022-11-14 14:19:17,228 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0480 (0.0774) Prec@1 94.000 (87.420) Prec@5 99.000 (99.188) +2022-11-14 14:19:17,236 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0776) Prec@1 86.000 (87.400) Prec@5 98.000 (99.171) +2022-11-14 14:19:17,247 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0777) Prec@1 87.000 (87.394) Prec@5 99.000 (99.169) +2022-11-14 14:19:17,259 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0775) Prec@1 88.000 (87.403) Prec@5 99.000 (99.167) +2022-11-14 14:19:17,272 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0773) Prec@1 89.000 (87.425) Prec@5 99.000 (99.164) +2022-11-14 14:19:17,284 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0771) Prec@1 91.000 (87.473) Prec@5 99.000 (99.162) +2022-11-14 14:19:17,296 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0774) Prec@1 83.000 (87.413) Prec@5 99.000 (99.160) +2022-11-14 14:19:17,308 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0772) Prec@1 90.000 (87.447) Prec@5 99.000 (99.158) +2022-11-14 14:19:17,320 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0773) Prec@1 85.000 (87.416) Prec@5 99.000 (99.156) +2022-11-14 14:19:17,332 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0773) Prec@1 87.000 (87.410) Prec@5 100.000 (99.167) +2022-11-14 14:19:17,344 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0772) Prec@1 89.000 (87.430) Prec@5 100.000 (99.177) +2022-11-14 14:19:17,358 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0773) Prec@1 80.000 (87.338) Prec@5 100.000 (99.188) +2022-11-14 14:19:17,371 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0774) Prec@1 85.000 (87.309) Prec@5 99.000 (99.185) +2022-11-14 14:19:17,383 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0775) Prec@1 86.000 (87.293) Prec@5 99.000 (99.183) +2022-11-14 14:19:17,395 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0777) Prec@1 86.000 (87.277) Prec@5 99.000 (99.181) +2022-11-14 14:19:17,404 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0775) Prec@1 89.000 (87.298) Prec@5 100.000 (99.190) +2022-11-14 14:19:17,413 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0775) Prec@1 89.000 (87.318) Prec@5 99.000 (99.188) +2022-11-14 14:19:17,427 Test: [85/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0776) Prec@1 83.000 (87.267) Prec@5 99.000 (99.186) +2022-11-14 14:19:17,438 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0775) Prec@1 86.000 (87.253) Prec@5 100.000 (99.195) +2022-11-14 14:19:17,448 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0776) Prec@1 90.000 (87.284) Prec@5 98.000 (99.182) +2022-11-14 14:19:17,458 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0777) Prec@1 85.000 (87.258) Prec@5 97.000 (99.157) +2022-11-14 14:19:17,471 Test: [89/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0778) Prec@1 87.000 (87.256) Prec@5 99.000 (99.156) +2022-11-14 14:19:17,484 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0777) Prec@1 87.000 (87.253) Prec@5 100.000 (99.165) +2022-11-14 14:19:17,494 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0775) Prec@1 90.000 (87.283) Prec@5 100.000 (99.174) +2022-11-14 14:19:17,505 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0776) Prec@1 88.000 (87.290) Prec@5 99.000 (99.172) +2022-11-14 14:19:17,516 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0775) Prec@1 90.000 (87.319) Prec@5 98.000 (99.160) +2022-11-14 14:19:17,527 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0775) Prec@1 83.000 (87.274) Prec@5 100.000 (99.168) +2022-11-14 14:19:17,537 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0773) Prec@1 92.000 (87.323) Prec@5 100.000 (99.177) +2022-11-14 14:19:17,548 Test: [96/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0771) Prec@1 91.000 (87.361) Prec@5 99.000 (99.175) +2022-11-14 14:19:17,559 Test: [97/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0772) Prec@1 87.000 (87.357) Prec@5 99.000 (99.173) +2022-11-14 14:19:17,569 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0773) Prec@1 87.000 (87.354) Prec@5 100.000 (99.182) +2022-11-14 14:19:17,580 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0773) Prec@1 88.000 (87.360) Prec@5 99.000 (99.180) +2022-11-14 14:19:17,641 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:19:17,986 Epoch: [180][0/500] Time 0.023 (0.023) Data 0.245 (0.245) Loss 0.0478 (0.0478) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:19:18,215 Epoch: [180][10/500] Time 0.021 (0.021) Data 0.002 (0.024) Loss 0.0331 (0.0404) Prec@1 97.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 14:19:18,438 Epoch: [180][20/500] Time 0.021 (0.020) Data 0.002 (0.014) Loss 0.0480 (0.0429) Prec@1 92.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:19:18,810 Epoch: [180][30/500] Time 0.078 (0.023) Data 0.002 (0.010) Loss 0.0348 (0.0409) Prec@1 95.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 14:19:19,283 Epoch: [180][40/500] Time 0.044 (0.028) Data 0.001 (0.008) Loss 0.0267 (0.0381) Prec@1 96.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:19:19,742 Epoch: [180][50/500] Time 0.042 (0.030) Data 0.002 (0.007) Loss 0.0543 (0.0408) Prec@1 92.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 14:19:20,214 Epoch: [180][60/500] Time 0.044 (0.032) Data 0.002 (0.006) Loss 0.0520 (0.0424) Prec@1 91.000 (93.571) Prec@5 100.000 (99.714) +2022-11-14 14:19:20,675 Epoch: [180][70/500] Time 0.043 (0.034) Data 0.002 (0.005) Loss 0.0468 (0.0429) Prec@1 91.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:19:21,140 Epoch: [180][80/500] Time 0.051 (0.035) Data 0.002 (0.005) Loss 0.0417 (0.0428) Prec@1 94.000 (93.333) Prec@5 100.000 (99.778) +2022-11-14 14:19:21,604 Epoch: [180][90/500] Time 0.044 (0.035) Data 0.002 (0.005) Loss 0.0342 (0.0419) Prec@1 95.000 (93.500) Prec@5 100.000 (99.800) +2022-11-14 14:19:22,078 Epoch: [180][100/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0574 (0.0433) Prec@1 91.000 (93.273) Prec@5 99.000 (99.727) +2022-11-14 14:19:22,532 Epoch: [180][110/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.0462 (0.0436) Prec@1 91.000 (93.083) Prec@5 100.000 (99.750) +2022-11-14 14:19:22,995 Epoch: [180][120/500] Time 0.045 (0.037) Data 0.002 (0.004) Loss 0.0373 (0.0431) Prec@1 92.000 (93.000) Prec@5 100.000 (99.769) +2022-11-14 14:19:23,537 Epoch: [180][130/500] Time 0.049 (0.038) Data 0.002 (0.004) Loss 0.0286 (0.0421) Prec@1 94.000 (93.071) Prec@5 100.000 (99.786) +2022-11-14 14:19:24,050 Epoch: [180][140/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0320 (0.0414) Prec@1 95.000 (93.200) Prec@5 99.000 (99.733) +2022-11-14 14:19:24,512 Epoch: [180][150/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0549 (0.0422) Prec@1 92.000 (93.125) Prec@5 100.000 (99.750) +2022-11-14 14:19:24,991 Epoch: [180][160/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0496 (0.0427) Prec@1 91.000 (93.000) Prec@5 99.000 (99.706) +2022-11-14 14:19:25,496 Epoch: [180][170/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0547 (0.0433) Prec@1 92.000 (92.944) Prec@5 100.000 (99.722) +2022-11-14 14:19:26,006 Epoch: [180][180/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0302 (0.0426) Prec@1 95.000 (93.053) Prec@5 100.000 (99.737) +2022-11-14 14:19:26,587 Epoch: [180][190/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0590 (0.0435) Prec@1 88.000 (92.800) Prec@5 100.000 (99.750) +2022-11-14 14:19:27,044 Epoch: [180][200/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0540 (0.0440) Prec@1 91.000 (92.714) Prec@5 99.000 (99.714) +2022-11-14 14:19:27,517 Epoch: [180][210/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0373 (0.0437) Prec@1 94.000 (92.773) Prec@5 100.000 (99.727) +2022-11-14 14:19:27,978 Epoch: [180][220/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0544 (0.0441) Prec@1 93.000 (92.783) Prec@5 100.000 (99.739) +2022-11-14 14:19:28,458 Epoch: [180][230/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0280 (0.0435) Prec@1 95.000 (92.875) Prec@5 99.000 (99.708) +2022-11-14 14:19:28,944 Epoch: [180][240/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0727 (0.0446) Prec@1 88.000 (92.680) Prec@5 100.000 (99.720) +2022-11-14 14:19:29,405 Epoch: [180][250/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0488 (0.0448) Prec@1 91.000 (92.615) Prec@5 99.000 (99.692) +2022-11-14 14:19:29,870 Epoch: [180][260/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0533 (0.0451) Prec@1 92.000 (92.593) Prec@5 100.000 (99.704) +2022-11-14 14:19:30,341 Epoch: [180][270/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0493 (0.0453) Prec@1 93.000 (92.607) Prec@5 99.000 (99.679) +2022-11-14 14:19:30,800 Epoch: [180][280/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0454 (0.0453) Prec@1 92.000 (92.586) Prec@5 100.000 (99.690) +2022-11-14 14:19:31,307 Epoch: [180][290/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0568 (0.0456) Prec@1 91.000 (92.533) Prec@5 100.000 (99.700) +2022-11-14 14:19:31,767 Epoch: [180][300/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0527 (0.0459) Prec@1 92.000 (92.516) Prec@5 98.000 (99.645) +2022-11-14 14:19:32,290 Epoch: [180][310/500] Time 0.080 (0.041) Data 0.002 (0.003) Loss 0.0480 (0.0459) Prec@1 91.000 (92.469) Prec@5 100.000 (99.656) +2022-11-14 14:19:32,797 Epoch: [180][320/500] Time 0.070 (0.041) Data 0.002 (0.003) Loss 0.0273 (0.0454) Prec@1 95.000 (92.545) Prec@5 100.000 (99.667) +2022-11-14 14:19:33,242 Epoch: [180][330/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0297 (0.0449) Prec@1 95.000 (92.618) Prec@5 99.000 (99.647) +2022-11-14 14:19:33,711 Epoch: [180][340/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0624 (0.0454) Prec@1 89.000 (92.514) Prec@5 100.000 (99.657) +2022-11-14 14:19:34,180 Epoch: [180][350/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0920 (0.0467) Prec@1 84.000 (92.278) Prec@5 100.000 (99.667) +2022-11-14 14:19:34,643 Epoch: [180][360/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0355 (0.0464) Prec@1 95.000 (92.351) Prec@5 100.000 (99.676) +2022-11-14 14:19:35,112 Epoch: [180][370/500] Time 0.056 (0.041) Data 0.002 (0.003) Loss 0.0272 (0.0459) Prec@1 96.000 (92.447) Prec@5 99.000 (99.658) +2022-11-14 14:19:35,569 Epoch: [180][380/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0423 (0.0458) Prec@1 91.000 (92.410) Prec@5 99.000 (99.641) +2022-11-14 14:19:36,050 Epoch: [180][390/500] Time 0.050 (0.041) Data 0.003 (0.003) Loss 0.0342 (0.0455) Prec@1 96.000 (92.500) Prec@5 100.000 (99.650) +2022-11-14 14:19:36,528 Epoch: [180][400/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0374 (0.0453) Prec@1 92.000 (92.488) Prec@5 100.000 (99.659) +2022-11-14 14:19:37,011 Epoch: [180][410/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0700 (0.0459) Prec@1 88.000 (92.381) Prec@5 100.000 (99.667) +2022-11-14 14:19:37,467 Epoch: [180][420/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0669 (0.0464) Prec@1 89.000 (92.302) Prec@5 100.000 (99.674) +2022-11-14 14:19:37,936 Epoch: [180][430/500] Time 0.051 (0.041) Data 0.002 (0.002) Loss 0.0380 (0.0462) Prec@1 93.000 (92.318) Prec@5 100.000 (99.682) +2022-11-14 14:19:38,391 Epoch: [180][440/500] Time 0.040 (0.041) Data 0.002 (0.002) Loss 0.0499 (0.0463) Prec@1 92.000 (92.311) Prec@5 100.000 (99.689) +2022-11-14 14:19:38,851 Epoch: [180][450/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0268 (0.0459) Prec@1 96.000 (92.391) Prec@5 100.000 (99.696) +2022-11-14 14:19:39,356 Epoch: [180][460/500] Time 0.041 (0.041) Data 0.002 (0.002) Loss 0.0550 (0.0461) Prec@1 90.000 (92.340) Prec@5 100.000 (99.702) +2022-11-14 14:19:39,872 Epoch: [180][470/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0352 (0.0458) Prec@1 95.000 (92.396) Prec@5 100.000 (99.708) +2022-11-14 14:19:40,371 Epoch: [180][480/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0302 (0.0455) Prec@1 96.000 (92.469) Prec@5 100.000 (99.714) +2022-11-14 14:19:40,825 Epoch: [180][490/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0521 (0.0456) Prec@1 91.000 (92.440) Prec@5 100.000 (99.720) +2022-11-14 14:19:41,299 Epoch: [180][499/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0627 (0.0460) Prec@1 90.000 (92.392) Prec@5 98.000 (99.686) +2022-11-14 14:19:41,605 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0708 (0.0708) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 14:19:41,618 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.0703) Prec@1 88.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 14:19:41,629 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0862 (0.0756) Prec@1 85.000 (86.667) Prec@5 99.000 (99.333) +2022-11-14 14:19:41,644 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0781 (0.0762) Prec@1 88.000 (87.000) Prec@5 98.000 (99.000) +2022-11-14 14:19:41,654 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0646 (0.0739) Prec@1 88.000 (87.200) Prec@5 100.000 (99.200) +2022-11-14 14:19:41,666 Test: [5/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0490 (0.0697) Prec@1 90.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 14:19:41,677 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0720 (0.0701) Prec@1 90.000 (88.000) Prec@5 99.000 (99.286) +2022-11-14 14:19:41,688 Test: [7/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0826 (0.0716) Prec@1 87.000 (87.875) Prec@5 99.000 (99.250) +2022-11-14 14:19:41,697 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0708) Prec@1 91.000 (88.222) Prec@5 99.000 (99.222) +2022-11-14 14:19:41,710 Test: [9/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0711) Prec@1 87.000 (88.100) Prec@5 99.000 (99.200) +2022-11-14 14:19:41,721 Test: [10/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0550 (0.0697) Prec@1 89.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 14:19:41,731 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0700) Prec@1 88.000 (88.167) Prec@5 99.000 (99.250) +2022-11-14 14:19:41,741 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0496 (0.0684) Prec@1 91.000 (88.385) Prec@5 100.000 (99.308) +2022-11-14 14:19:41,754 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0679) Prec@1 89.000 (88.429) Prec@5 100.000 (99.357) +2022-11-14 14:19:41,767 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0688) Prec@1 87.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 14:19:41,777 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0529 (0.0678) Prec@1 92.000 (88.562) Prec@5 100.000 (99.375) +2022-11-14 14:19:41,788 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0676) Prec@1 90.000 (88.647) Prec@5 97.000 (99.235) +2022-11-14 14:19:41,799 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0935 (0.0690) Prec@1 86.000 (88.500) Prec@5 100.000 (99.278) +2022-11-14 14:19:41,809 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0703) Prec@1 82.000 (88.158) Prec@5 100.000 (99.316) +2022-11-14 14:19:41,819 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1137 (0.0725) Prec@1 81.000 (87.800) Prec@5 98.000 (99.250) +2022-11-14 14:19:41,828 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0733) Prec@1 84.000 (87.619) Prec@5 99.000 (99.238) +2022-11-14 14:19:41,841 Test: [21/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0731) Prec@1 88.000 (87.636) Prec@5 100.000 (99.273) +2022-11-14 14:19:41,853 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.0742) Prec@1 85.000 (87.522) Prec@5 98.000 (99.217) +2022-11-14 14:19:41,865 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0745) Prec@1 85.000 (87.417) Prec@5 99.000 (99.208) +2022-11-14 14:19:41,878 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.0754) Prec@1 85.000 (87.320) Prec@5 99.000 (99.200) +2022-11-14 14:19:41,891 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0808 (0.0756) Prec@1 88.000 (87.346) Prec@5 99.000 (99.192) +2022-11-14 14:19:41,904 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0473 (0.0745) Prec@1 90.000 (87.444) Prec@5 100.000 (99.222) +2022-11-14 14:19:41,917 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0773 (0.0746) Prec@1 88.000 (87.464) Prec@5 99.000 (99.214) +2022-11-14 14:19:41,930 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0626 (0.0742) Prec@1 90.000 (87.552) Prec@5 99.000 (99.207) +2022-11-14 14:19:41,942 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0747) Prec@1 85.000 (87.467) Prec@5 100.000 (99.233) +2022-11-14 14:19:41,954 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0749) Prec@1 86.000 (87.419) Prec@5 100.000 (99.258) +2022-11-14 14:19:41,967 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0745) Prec@1 89.000 (87.469) Prec@5 99.000 (99.250) +2022-11-14 14:19:41,979 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0739) Prec@1 90.000 (87.545) Prec@5 100.000 (99.273) +2022-11-14 14:19:41,989 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0741) Prec@1 86.000 (87.500) Prec@5 100.000 (99.294) +2022-11-14 14:19:41,999 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0745) Prec@1 85.000 (87.429) Prec@5 100.000 (99.314) +2022-11-14 14:19:42,011 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0744) Prec@1 90.000 (87.500) Prec@5 99.000 (99.306) +2022-11-14 14:19:42,020 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0745) Prec@1 86.000 (87.459) Prec@5 99.000 (99.297) +2022-11-14 14:19:42,029 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1136 (0.0756) Prec@1 82.000 (87.316) Prec@5 99.000 (99.289) +2022-11-14 14:19:42,040 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0751) Prec@1 92.000 (87.436) Prec@5 99.000 (99.282) +2022-11-14 14:19:42,051 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0749) Prec@1 89.000 (87.475) Prec@5 98.000 (99.250) +2022-11-14 14:19:42,066 Test: [40/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0753) Prec@1 86.000 (87.439) Prec@5 99.000 (99.244) +2022-11-14 14:19:42,077 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0750) Prec@1 90.000 (87.500) Prec@5 99.000 (99.238) +2022-11-14 14:19:42,087 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0744) Prec@1 92.000 (87.605) Prec@5 99.000 (99.233) +2022-11-14 14:19:42,097 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0743) Prec@1 89.000 (87.636) Prec@5 98.000 (99.205) +2022-11-14 14:19:42,108 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0738) Prec@1 92.000 (87.733) Prec@5 98.000 (99.178) +2022-11-14 14:19:42,118 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1167 (0.0748) Prec@1 84.000 (87.652) Prec@5 98.000 (99.152) +2022-11-14 14:19:42,128 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0746) Prec@1 90.000 (87.702) Prec@5 100.000 (99.170) +2022-11-14 14:19:42,138 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0751) Prec@1 83.000 (87.604) Prec@5 98.000 (99.146) +2022-11-14 14:19:42,148 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0441 (0.0745) Prec@1 94.000 (87.735) Prec@5 100.000 (99.163) +2022-11-14 14:19:42,158 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0752) Prec@1 81.000 (87.600) Prec@5 100.000 (99.180) +2022-11-14 14:19:42,167 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0751) Prec@1 88.000 (87.608) Prec@5 100.000 (99.196) +2022-11-14 14:19:42,177 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0757) Prec@1 81.000 (87.481) Prec@5 100.000 (99.212) +2022-11-14 14:19:42,186 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0757) Prec@1 88.000 (87.491) Prec@5 99.000 (99.208) +2022-11-14 14:19:42,195 Test: [53/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0758) Prec@1 85.000 (87.444) Prec@5 99.000 (99.204) +2022-11-14 14:19:42,203 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0762) Prec@1 86.000 (87.418) Prec@5 100.000 (99.218) +2022-11-14 14:19:42,212 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0763) Prec@1 87.000 (87.411) Prec@5 99.000 (99.214) +2022-11-14 14:19:42,221 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0759) Prec@1 87.000 (87.404) Prec@5 100.000 (99.228) +2022-11-14 14:19:42,231 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0759) Prec@1 88.000 (87.414) Prec@5 98.000 (99.207) +2022-11-14 14:19:42,244 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0758) Prec@1 87.000 (87.407) Prec@5 100.000 (99.220) +2022-11-14 14:19:42,258 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0758) Prec@1 87.000 (87.400) Prec@5 99.000 (99.217) +2022-11-14 14:19:42,272 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0761) Prec@1 86.000 (87.377) Prec@5 100.000 (99.230) +2022-11-14 14:19:42,286 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0761) Prec@1 86.000 (87.355) Prec@5 100.000 (99.242) +2022-11-14 14:19:42,300 Test: [62/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0757) Prec@1 91.000 (87.413) Prec@5 100.000 (99.254) +2022-11-14 14:19:42,315 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0466 (0.0753) Prec@1 93.000 (87.500) Prec@5 100.000 (99.266) +2022-11-14 14:19:42,329 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0756) Prec@1 81.000 (87.400) Prec@5 98.000 (99.246) +2022-11-14 14:19:42,341 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0759) Prec@1 84.000 (87.348) Prec@5 97.000 (99.212) +2022-11-14 14:19:42,354 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0346 (0.0753) Prec@1 95.000 (87.463) Prec@5 100.000 (99.224) +2022-11-14 14:19:42,366 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0755) Prec@1 85.000 (87.426) Prec@5 99.000 (99.221) +2022-11-14 14:19:42,378 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0752) Prec@1 92.000 (87.493) Prec@5 99.000 (99.217) +2022-11-14 14:19:42,391 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0753) Prec@1 87.000 (87.486) Prec@5 97.000 (99.186) +2022-11-14 14:19:42,405 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0755) Prec@1 86.000 (87.465) Prec@5 99.000 (99.183) +2022-11-14 14:19:42,418 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 88.000 (87.472) Prec@5 99.000 (99.181) +2022-11-14 14:19:42,431 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0752) Prec@1 90.000 (87.507) Prec@5 98.000 (99.164) +2022-11-14 14:19:42,444 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0749) Prec@1 93.000 (87.581) Prec@5 100.000 (99.176) +2022-11-14 14:19:42,458 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0750) Prec@1 87.000 (87.573) Prec@5 99.000 (99.173) +2022-11-14 14:19:42,471 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0749) Prec@1 87.000 (87.566) Prec@5 98.000 (99.158) +2022-11-14 14:19:42,484 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0748) Prec@1 87.000 (87.558) Prec@5 100.000 (99.169) +2022-11-14 14:19:42,496 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0751) Prec@1 82.000 (87.487) Prec@5 98.000 (99.154) +2022-11-14 14:19:42,510 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0749) Prec@1 89.000 (87.506) Prec@5 100.000 (99.165) +2022-11-14 14:19:42,523 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0751) Prec@1 83.000 (87.450) Prec@5 99.000 (99.162) +2022-11-14 14:19:42,534 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0752) Prec@1 87.000 (87.444) Prec@5 100.000 (99.173) +2022-11-14 14:19:42,544 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0755) Prec@1 82.000 (87.378) Prec@5 100.000 (99.183) +2022-11-14 14:19:42,554 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0755) Prec@1 86.000 (87.361) Prec@5 99.000 (99.181) +2022-11-14 14:19:42,563 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0755) Prec@1 86.000 (87.345) Prec@5 99.000 (99.179) +2022-11-14 14:19:42,573 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0758) Prec@1 81.000 (87.271) Prec@5 99.000 (99.176) +2022-11-14 14:19:42,583 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0761) Prec@1 86.000 (87.256) Prec@5 100.000 (99.186) +2022-11-14 14:19:42,591 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0762) Prec@1 84.000 (87.218) Prec@5 100.000 (99.195) +2022-11-14 14:19:42,600 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0763) Prec@1 86.000 (87.205) Prec@5 100.000 (99.205) +2022-11-14 14:19:42,610 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0762) Prec@1 89.000 (87.225) Prec@5 100.000 (99.213) +2022-11-14 14:19:42,620 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0760) Prec@1 92.000 (87.278) Prec@5 99.000 (99.211) +2022-11-14 14:19:42,630 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0759) Prec@1 86.000 (87.264) Prec@5 100.000 (99.220) +2022-11-14 14:19:42,639 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0756) Prec@1 90.000 (87.293) Prec@5 99.000 (99.217) +2022-11-14 14:19:42,650 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0758) Prec@1 85.000 (87.269) Prec@5 100.000 (99.226) +2022-11-14 14:19:42,659 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0757) Prec@1 87.000 (87.266) Prec@5 100.000 (99.234) +2022-11-14 14:19:42,669 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0758) Prec@1 84.000 (87.232) Prec@5 99.000 (99.232) +2022-11-14 14:19:42,679 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0756) Prec@1 91.000 (87.271) Prec@5 100.000 (99.240) +2022-11-14 14:19:42,688 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0466 (0.0753) Prec@1 93.000 (87.330) Prec@5 99.000 (99.237) +2022-11-14 14:19:42,698 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0755) Prec@1 86.000 (87.316) Prec@5 98.000 (99.224) +2022-11-14 14:19:42,707 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0758) Prec@1 84.000 (87.283) Prec@5 100.000 (99.232) +2022-11-14 14:19:42,716 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0757) Prec@1 87.000 (87.280) Prec@5 100.000 (99.240) +2022-11-14 14:19:42,784 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:19:43,140 Epoch: [181][0/500] Time 0.034 (0.034) Data 0.259 (0.259) Loss 0.0526 (0.0526) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:19:43,399 Epoch: [181][10/500] Time 0.018 (0.024) Data 0.002 (0.025) Loss 0.0625 (0.0576) Prec@1 89.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 14:19:43,688 Epoch: [181][20/500] Time 0.026 (0.025) Data 0.002 (0.014) Loss 0.0422 (0.0524) Prec@1 95.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:19:43,916 Epoch: [181][30/500] Time 0.024 (0.023) Data 0.002 (0.010) Loss 0.0389 (0.0491) Prec@1 94.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:19:44,287 Epoch: [181][40/500] Time 0.030 (0.026) Data 0.002 (0.008) Loss 0.0372 (0.0467) Prec@1 94.000 (92.800) Prec@5 99.000 (99.600) +2022-11-14 14:19:44,569 Epoch: [181][50/500] Time 0.026 (0.026) Data 0.002 (0.007) Loss 0.0373 (0.0451) Prec@1 94.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 14:19:44,872 Epoch: [181][60/500] Time 0.023 (0.026) Data 0.002 (0.006) Loss 0.0549 (0.0465) Prec@1 91.000 (92.714) Prec@5 99.000 (99.429) +2022-11-14 14:19:45,162 Epoch: [181][70/500] Time 0.025 (0.026) Data 0.002 (0.006) Loss 0.0491 (0.0469) Prec@1 91.000 (92.500) Prec@5 98.000 (99.250) +2022-11-14 14:19:45,484 Epoch: [181][80/500] Time 0.026 (0.026) Data 0.002 (0.005) Loss 0.0520 (0.0474) Prec@1 91.000 (92.333) Prec@5 100.000 (99.333) +2022-11-14 14:19:45,826 Epoch: [181][90/500] Time 0.043 (0.027) Data 0.002 (0.005) Loss 0.0447 (0.0472) Prec@1 92.000 (92.300) Prec@5 100.000 (99.400) +2022-11-14 14:19:46,123 Epoch: [181][100/500] Time 0.037 (0.027) Data 0.002 (0.004) Loss 0.0999 (0.0519) Prec@1 84.000 (91.545) Prec@5 98.000 (99.273) +2022-11-14 14:19:46,633 Epoch: [181][110/500] Time 0.045 (0.028) Data 0.002 (0.004) Loss 0.0361 (0.0506) Prec@1 93.000 (91.667) Prec@5 100.000 (99.333) +2022-11-14 14:19:47,145 Epoch: [181][120/500] Time 0.047 (0.030) Data 0.002 (0.004) Loss 0.0422 (0.0500) Prec@1 93.000 (91.769) Prec@5 99.000 (99.308) +2022-11-14 14:19:47,666 Epoch: [181][130/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.0542 (0.0503) Prec@1 90.000 (91.643) Prec@5 99.000 (99.286) +2022-11-14 14:19:48,189 Epoch: [181][140/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0936 (0.0532) Prec@1 83.000 (91.067) Prec@5 100.000 (99.333) +2022-11-14 14:19:48,664 Epoch: [181][150/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0569 (0.0534) Prec@1 89.000 (90.938) Prec@5 100.000 (99.375) +2022-11-14 14:19:49,182 Epoch: [181][160/500] Time 0.035 (0.034) Data 0.001 (0.004) Loss 0.0271 (0.0518) Prec@1 96.000 (91.235) Prec@5 100.000 (99.412) +2022-11-14 14:19:49,671 Epoch: [181][170/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0771 (0.0532) Prec@1 87.000 (91.000) Prec@5 98.000 (99.333) +2022-11-14 14:19:50,246 Epoch: [181][180/500] Time 0.063 (0.035) Data 0.003 (0.003) Loss 0.0699 (0.0541) Prec@1 89.000 (90.895) Prec@5 99.000 (99.316) +2022-11-14 14:19:50,720 Epoch: [181][190/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0352 (0.0532) Prec@1 93.000 (91.000) Prec@5 99.000 (99.300) +2022-11-14 14:19:51,253 Epoch: [181][200/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0529 (0.0532) Prec@1 91.000 (91.000) Prec@5 100.000 (99.333) +2022-11-14 14:19:51,729 Epoch: [181][210/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0201 (0.0517) Prec@1 96.000 (91.227) Prec@5 100.000 (99.364) +2022-11-14 14:19:52,221 Epoch: [181][220/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.0246 (0.0505) Prec@1 96.000 (91.435) Prec@5 100.000 (99.391) +2022-11-14 14:19:52,907 Epoch: [181][230/500] Time 0.068 (0.038) Data 0.003 (0.003) Loss 0.0266 (0.0495) Prec@1 97.000 (91.667) Prec@5 100.000 (99.417) +2022-11-14 14:19:53,486 Epoch: [181][240/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.0338 (0.0489) Prec@1 95.000 (91.800) Prec@5 100.000 (99.440) +2022-11-14 14:19:54,025 Epoch: [181][250/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0405 (0.0485) Prec@1 93.000 (91.846) Prec@5 100.000 (99.462) +2022-11-14 14:19:54,561 Epoch: [181][260/500] Time 0.092 (0.039) Data 0.002 (0.003) Loss 0.0494 (0.0486) Prec@1 92.000 (91.852) Prec@5 100.000 (99.481) +2022-11-14 14:19:55,070 Epoch: [181][270/500] Time 0.100 (0.039) Data 0.003 (0.003) Loss 0.0360 (0.0481) Prec@1 95.000 (91.964) Prec@5 100.000 (99.500) +2022-11-14 14:19:55,573 Epoch: [181][280/500] Time 0.090 (0.039) Data 0.002 (0.003) Loss 0.0536 (0.0483) Prec@1 93.000 (92.000) Prec@5 99.000 (99.483) +2022-11-14 14:19:56,161 Epoch: [181][290/500] Time 0.064 (0.040) Data 0.002 (0.003) Loss 0.0361 (0.0479) Prec@1 94.000 (92.067) Prec@5 100.000 (99.500) +2022-11-14 14:19:56,607 Epoch: [181][300/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0329 (0.0474) Prec@1 93.000 (92.097) Prec@5 100.000 (99.516) +2022-11-14 14:19:57,085 Epoch: [181][310/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0284 (0.0468) Prec@1 94.000 (92.156) Prec@5 100.000 (99.531) +2022-11-14 14:19:57,549 Epoch: [181][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0534 (0.0470) Prec@1 92.000 (92.152) Prec@5 100.000 (99.545) +2022-11-14 14:19:58,020 Epoch: [181][330/500] Time 0.050 (0.040) Data 0.003 (0.003) Loss 0.0542 (0.0472) Prec@1 89.000 (92.059) Prec@5 100.000 (99.559) +2022-11-14 14:19:58,495 Epoch: [181][340/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0250 (0.0466) Prec@1 98.000 (92.229) Prec@5 100.000 (99.571) +2022-11-14 14:19:58,980 Epoch: [181][350/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0815 (0.0476) Prec@1 85.000 (92.028) Prec@5 99.000 (99.556) +2022-11-14 14:19:59,457 Epoch: [181][360/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0226 (0.0469) Prec@1 98.000 (92.189) Prec@5 100.000 (99.568) +2022-11-14 14:19:59,916 Epoch: [181][370/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0388 (0.0467) Prec@1 93.000 (92.211) Prec@5 100.000 (99.579) +2022-11-14 14:20:00,389 Epoch: [181][380/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0560 (0.0469) Prec@1 92.000 (92.205) Prec@5 100.000 (99.590) +2022-11-14 14:20:00,884 Epoch: [181][390/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0677 (0.0474) Prec@1 89.000 (92.125) Prec@5 99.000 (99.575) +2022-11-14 14:20:01,353 Epoch: [181][400/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0474 (0.0474) Prec@1 91.000 (92.098) Prec@5 100.000 (99.585) +2022-11-14 14:20:01,824 Epoch: [181][410/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0256 (0.0469) Prec@1 97.000 (92.214) Prec@5 100.000 (99.595) +2022-11-14 14:20:02,294 Epoch: [181][420/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0632 (0.0473) Prec@1 91.000 (92.186) Prec@5 100.000 (99.605) +2022-11-14 14:20:02,814 Epoch: [181][430/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0108 (0.0465) Prec@1 99.000 (92.341) Prec@5 100.000 (99.614) +2022-11-14 14:20:03,296 Epoch: [181][440/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0631 (0.0468) Prec@1 90.000 (92.289) Prec@5 100.000 (99.622) +2022-11-14 14:20:03,771 Epoch: [181][450/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0340 (0.0466) Prec@1 94.000 (92.326) Prec@5 100.000 (99.630) +2022-11-14 14:20:04,284 Epoch: [181][460/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0451 (0.0465) Prec@1 93.000 (92.340) Prec@5 100.000 (99.638) +2022-11-14 14:20:04,743 Epoch: [181][470/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0531 (0.0467) Prec@1 91.000 (92.312) Prec@5 100.000 (99.646) +2022-11-14 14:20:05,214 Epoch: [181][480/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0391 (0.0465) Prec@1 94.000 (92.347) Prec@5 100.000 (99.653) +2022-11-14 14:20:05,688 Epoch: [181][490/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0612 (0.0468) Prec@1 88.000 (92.260) Prec@5 100.000 (99.660) +2022-11-14 14:20:06,117 Epoch: [181][499/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.0513 (0.0469) Prec@1 91.000 (92.235) Prec@5 100.000 (99.667) +2022-11-14 14:20:06,399 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0762 (0.0762) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:20:06,408 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0754) Prec@1 86.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:20:06,419 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0718) Prec@1 89.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:20:06,429 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0768) Prec@1 85.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:20:06,438 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0760) Prec@1 88.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 14:20:06,445 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0308 (0.0685) Prec@1 96.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:20:06,455 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0694) Prec@1 89.000 (89.000) Prec@5 100.000 (99.571) +2022-11-14 14:20:06,464 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0694) Prec@1 87.000 (88.750) Prec@5 100.000 (99.625) +2022-11-14 14:20:06,472 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0691) Prec@1 88.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:20:06,481 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0702) Prec@1 86.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 14:20:06,491 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0695) Prec@1 86.000 (88.182) Prec@5 100.000 (99.636) +2022-11-14 14:20:06,501 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0707) Prec@1 85.000 (87.917) Prec@5 98.000 (99.500) +2022-11-14 14:20:06,512 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0699) Prec@1 91.000 (88.154) Prec@5 100.000 (99.538) +2022-11-14 14:20:06,522 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0699) Prec@1 88.000 (88.143) Prec@5 99.000 (99.500) +2022-11-14 14:20:06,532 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0697) Prec@1 89.000 (88.200) Prec@5 100.000 (99.533) +2022-11-14 14:20:06,541 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0705) Prec@1 85.000 (88.000) Prec@5 98.000 (99.438) +2022-11-14 14:20:06,550 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0697) Prec@1 92.000 (88.235) Prec@5 98.000 (99.353) +2022-11-14 14:20:06,561 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0705) Prec@1 87.000 (88.167) Prec@5 100.000 (99.389) +2022-11-14 14:20:06,571 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0709) Prec@1 85.000 (88.000) Prec@5 99.000 (99.368) +2022-11-14 14:20:06,581 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0712) Prec@1 88.000 (88.000) Prec@5 98.000 (99.300) +2022-11-14 14:20:06,591 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0707) Prec@1 89.000 (88.048) Prec@5 100.000 (99.333) +2022-11-14 14:20:06,602 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0719) Prec@1 83.000 (87.818) Prec@5 98.000 (99.273) +2022-11-14 14:20:06,610 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0721) Prec@1 88.000 (87.826) Prec@5 98.000 (99.217) +2022-11-14 14:20:06,620 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0718) Prec@1 89.000 (87.875) Prec@5 100.000 (99.250) +2022-11-14 14:20:06,631 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0720) Prec@1 87.000 (87.840) Prec@5 100.000 (99.280) +2022-11-14 14:20:06,640 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0729) Prec@1 86.000 (87.769) Prec@5 97.000 (99.192) +2022-11-14 14:20:06,651 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0722) Prec@1 91.000 (87.889) Prec@5 99.000 (99.185) +2022-11-14 14:20:06,660 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0721) Prec@1 90.000 (87.964) Prec@5 100.000 (99.214) +2022-11-14 14:20:06,671 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0719) Prec@1 87.000 (87.931) Prec@5 100.000 (99.241) +2022-11-14 14:20:06,680 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0719) Prec@1 89.000 (87.967) Prec@5 100.000 (99.267) +2022-11-14 14:20:06,689 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0715) Prec@1 90.000 (88.032) Prec@5 100.000 (99.290) +2022-11-14 14:20:06,698 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0718) Prec@1 86.000 (87.969) Prec@5 100.000 (99.312) +2022-11-14 14:20:06,709 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0722) Prec@1 85.000 (87.879) Prec@5 99.000 (99.303) +2022-11-14 14:20:06,720 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0721) Prec@1 87.000 (87.853) Prec@5 100.000 (99.324) +2022-11-14 14:20:06,730 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0727) Prec@1 85.000 (87.771) Prec@5 98.000 (99.286) +2022-11-14 14:20:06,741 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0723) Prec@1 90.000 (87.833) Prec@5 99.000 (99.278) +2022-11-14 14:20:06,751 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0726) Prec@1 87.000 (87.811) Prec@5 100.000 (99.297) +2022-11-14 14:20:06,761 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0732) Prec@1 83.000 (87.684) Prec@5 99.000 (99.289) +2022-11-14 14:20:06,770 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0730) Prec@1 90.000 (87.744) Prec@5 99.000 (99.282) +2022-11-14 14:20:06,780 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0727) Prec@1 90.000 (87.800) Prec@5 99.000 (99.275) +2022-11-14 14:20:06,791 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0732) Prec@1 85.000 (87.732) Prec@5 96.000 (99.195) +2022-11-14 14:20:06,800 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0731) Prec@1 89.000 (87.762) Prec@5 99.000 (99.190) +2022-11-14 14:20:06,810 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0724) Prec@1 93.000 (87.884) Prec@5 99.000 (99.186) +2022-11-14 14:20:06,820 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0722) Prec@1 91.000 (87.955) Prec@5 99.000 (99.182) +2022-11-14 14:20:06,830 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0721) Prec@1 88.000 (87.956) Prec@5 99.000 (99.178) +2022-11-14 14:20:06,841 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0728) Prec@1 84.000 (87.870) Prec@5 99.000 (99.174) +2022-11-14 14:20:06,851 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0728) Prec@1 84.000 (87.787) Prec@5 100.000 (99.191) +2022-11-14 14:20:06,860 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0733) Prec@1 82.000 (87.667) Prec@5 98.000 (99.167) +2022-11-14 14:20:06,871 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0728) Prec@1 89.000 (87.694) Prec@5 100.000 (99.184) +2022-11-14 14:20:06,885 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0735) Prec@1 83.000 (87.600) Prec@5 99.000 (99.180) +2022-11-14 14:20:06,896 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0736) Prec@1 87.000 (87.588) Prec@5 100.000 (99.196) +2022-11-14 14:20:06,907 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0740) Prec@1 81.000 (87.462) Prec@5 100.000 (99.212) +2022-11-14 14:20:06,917 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0739) Prec@1 89.000 (87.491) Prec@5 100.000 (99.226) +2022-11-14 14:20:06,927 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0739) Prec@1 85.000 (87.444) Prec@5 99.000 (99.222) +2022-11-14 14:20:06,937 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0741) Prec@1 84.000 (87.382) Prec@5 100.000 (99.236) +2022-11-14 14:20:06,946 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0743) Prec@1 88.000 (87.393) Prec@5 99.000 (99.232) +2022-11-14 14:20:06,957 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0739) Prec@1 90.000 (87.439) Prec@5 100.000 (99.246) +2022-11-14 14:20:06,967 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0738) Prec@1 91.000 (87.500) Prec@5 97.000 (99.207) +2022-11-14 14:20:06,977 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1212 (0.0746) Prec@1 80.000 (87.373) Prec@5 100.000 (99.220) +2022-11-14 14:20:06,987 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0747) Prec@1 86.000 (87.350) Prec@5 98.000 (99.200) +2022-11-14 14:20:06,997 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0749) Prec@1 84.000 (87.295) Prec@5 99.000 (99.197) +2022-11-14 14:20:07,007 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0751) Prec@1 84.000 (87.242) Prec@5 99.000 (99.194) +2022-11-14 14:20:07,018 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0748) Prec@1 89.000 (87.270) Prec@5 100.000 (99.206) +2022-11-14 14:20:07,029 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0744) Prec@1 92.000 (87.344) Prec@5 100.000 (99.219) +2022-11-14 14:20:07,039 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0744) Prec@1 87.000 (87.338) Prec@5 99.000 (99.215) +2022-11-14 14:20:07,050 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0747) Prec@1 85.000 (87.303) Prec@5 100.000 (99.227) +2022-11-14 14:20:07,061 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0742) Prec@1 94.000 (87.403) Prec@5 99.000 (99.224) +2022-11-14 14:20:07,071 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0742) Prec@1 88.000 (87.412) Prec@5 99.000 (99.221) +2022-11-14 14:20:07,081 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0740) Prec@1 89.000 (87.435) Prec@5 99.000 (99.217) +2022-11-14 14:20:07,091 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0741) Prec@1 86.000 (87.414) Prec@5 100.000 (99.229) +2022-11-14 14:20:07,102 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0745) Prec@1 85.000 (87.380) Prec@5 98.000 (99.211) +2022-11-14 14:20:07,111 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0745) Prec@1 89.000 (87.403) Prec@5 98.000 (99.194) +2022-11-14 14:20:07,123 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0744) Prec@1 89.000 (87.425) Prec@5 100.000 (99.205) +2022-11-14 14:20:07,133 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0742) Prec@1 91.000 (87.473) Prec@5 100.000 (99.216) +2022-11-14 14:20:07,144 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0745) Prec@1 85.000 (87.440) Prec@5 100.000 (99.227) +2022-11-14 14:20:07,153 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0742) Prec@1 90.000 (87.474) Prec@5 98.000 (99.211) +2022-11-14 14:20:07,164 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0743) Prec@1 90.000 (87.506) Prec@5 97.000 (99.182) +2022-11-14 14:20:07,173 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0744) Prec@1 87.000 (87.500) Prec@5 98.000 (99.167) +2022-11-14 14:20:07,184 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0744) Prec@1 86.000 (87.481) Prec@5 100.000 (99.177) +2022-11-14 14:20:07,193 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0745) Prec@1 83.000 (87.425) Prec@5 99.000 (99.175) +2022-11-14 14:20:07,203 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0749) Prec@1 81.000 (87.346) Prec@5 98.000 (99.160) +2022-11-14 14:20:07,213 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0750) Prec@1 87.000 (87.341) Prec@5 99.000 (99.159) +2022-11-14 14:20:07,223 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0751) Prec@1 87.000 (87.337) Prec@5 100.000 (99.169) +2022-11-14 14:20:07,233 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0754) Prec@1 82.000 (87.274) Prec@5 98.000 (99.155) +2022-11-14 14:20:07,243 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0756) Prec@1 84.000 (87.235) Prec@5 100.000 (99.165) +2022-11-14 14:20:07,253 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0760) Prec@1 85.000 (87.209) Prec@5 99.000 (99.163) +2022-11-14 14:20:07,263 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0758) Prec@1 90.000 (87.241) Prec@5 99.000 (99.161) +2022-11-14 14:20:07,273 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0757) Prec@1 88.000 (87.250) Prec@5 100.000 (99.170) +2022-11-14 14:20:07,283 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0756) Prec@1 88.000 (87.258) Prec@5 99.000 (99.169) +2022-11-14 14:20:07,293 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0756) Prec@1 88.000 (87.267) Prec@5 100.000 (99.178) +2022-11-14 14:20:07,303 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0754) Prec@1 89.000 (87.286) Prec@5 100.000 (99.187) +2022-11-14 14:20:07,313 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0751) Prec@1 90.000 (87.315) Prec@5 99.000 (99.185) +2022-11-14 14:20:07,323 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0752) Prec@1 87.000 (87.312) Prec@5 98.000 (99.172) +2022-11-14 14:20:07,333 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0752) Prec@1 88.000 (87.319) Prec@5 100.000 (99.181) +2022-11-14 14:20:07,343 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0753) Prec@1 89.000 (87.337) Prec@5 99.000 (99.179) +2022-11-14 14:20:07,352 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0750) Prec@1 92.000 (87.385) Prec@5 99.000 (99.177) +2022-11-14 14:20:07,362 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0747) Prec@1 94.000 (87.454) Prec@5 99.000 (99.175) +2022-11-14 14:20:07,373 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0748) Prec@1 86.000 (87.439) Prec@5 98.000 (99.163) +2022-11-14 14:20:07,383 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0750) Prec@1 85.000 (87.414) Prec@5 100.000 (99.172) +2022-11-14 14:20:07,394 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0752) Prec@1 83.000 (87.370) Prec@5 99.000 (99.170) +2022-11-14 14:20:07,451 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:20:07,770 Epoch: [182][0/500] Time 0.024 (0.024) Data 0.235 (0.235) Loss 0.0626 (0.0626) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:07,982 Epoch: [182][10/500] Time 0.019 (0.019) Data 0.001 (0.023) Loss 0.0421 (0.0524) Prec@1 91.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:20:08,237 Epoch: [182][20/500] Time 0.021 (0.021) Data 0.002 (0.013) Loss 0.0560 (0.0536) Prec@1 90.000 (91.000) Prec@5 99.000 (99.667) +2022-11-14 14:20:08,611 Epoch: [182][30/500] Time 0.056 (0.024) Data 0.002 (0.009) Loss 0.0705 (0.0578) Prec@1 87.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:20:08,949 Epoch: [182][40/500] Time 0.027 (0.026) Data 0.002 (0.008) Loss 0.0609 (0.0584) Prec@1 89.000 (89.800) Prec@5 100.000 (99.600) +2022-11-14 14:20:09,282 Epoch: [182][50/500] Time 0.030 (0.026) Data 0.001 (0.006) Loss 0.0379 (0.0550) Prec@1 94.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 14:20:09,644 Epoch: [182][60/500] Time 0.031 (0.027) Data 0.002 (0.006) Loss 0.0428 (0.0533) Prec@1 94.000 (91.000) Prec@5 100.000 (99.571) +2022-11-14 14:20:09,981 Epoch: [182][70/500] Time 0.029 (0.028) Data 0.002 (0.005) Loss 0.0458 (0.0523) Prec@1 94.000 (91.375) Prec@5 100.000 (99.625) +2022-11-14 14:20:10,317 Epoch: [182][80/500] Time 0.031 (0.028) Data 0.002 (0.005) Loss 0.0331 (0.0502) Prec@1 94.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:20:10,677 Epoch: [182][90/500] Time 0.033 (0.028) Data 0.002 (0.004) Loss 0.0569 (0.0509) Prec@1 90.000 (91.500) Prec@5 100.000 (99.700) +2022-11-14 14:20:11,021 Epoch: [182][100/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0476 (0.0506) Prec@1 90.000 (91.364) Prec@5 100.000 (99.727) +2022-11-14 14:20:11,388 Epoch: [182][110/500] Time 0.026 (0.029) Data 0.002 (0.004) Loss 0.0449 (0.0501) Prec@1 95.000 (91.667) Prec@5 97.000 (99.500) +2022-11-14 14:20:11,758 Epoch: [182][120/500] Time 0.056 (0.029) Data 0.002 (0.004) Loss 0.0347 (0.0489) Prec@1 94.000 (91.846) Prec@5 100.000 (99.538) +2022-11-14 14:20:12,087 Epoch: [182][130/500] Time 0.033 (0.029) Data 0.001 (0.004) Loss 0.0399 (0.0483) Prec@1 94.000 (92.000) Prec@5 100.000 (99.571) +2022-11-14 14:20:12,416 Epoch: [182][140/500] Time 0.031 (0.029) Data 0.002 (0.004) Loss 0.0375 (0.0476) Prec@1 94.000 (92.133) Prec@5 99.000 (99.533) +2022-11-14 14:20:12,755 Epoch: [182][150/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0233 (0.0460) Prec@1 96.000 (92.375) Prec@5 100.000 (99.562) +2022-11-14 14:20:13,103 Epoch: [182][160/500] Time 0.040 (0.029) Data 0.002 (0.003) Loss 0.0313 (0.0452) Prec@1 95.000 (92.529) Prec@5 100.000 (99.588) +2022-11-14 14:20:13,438 Epoch: [182][170/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0577 (0.0459) Prec@1 89.000 (92.333) Prec@5 100.000 (99.611) +2022-11-14 14:20:13,767 Epoch: [182][180/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0584 (0.0465) Prec@1 91.000 (92.263) Prec@5 99.000 (99.579) +2022-11-14 14:20:14,123 Epoch: [182][190/500] Time 0.039 (0.030) Data 0.002 (0.003) Loss 0.0484 (0.0466) Prec@1 90.000 (92.150) Prec@5 100.000 (99.600) +2022-11-14 14:20:14,465 Epoch: [182][200/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0376 (0.0462) Prec@1 94.000 (92.238) Prec@5 100.000 (99.619) +2022-11-14 14:20:14,801 Epoch: [182][210/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0433 (0.0461) Prec@1 93.000 (92.273) Prec@5 99.000 (99.591) +2022-11-14 14:20:15,152 Epoch: [182][220/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0196 (0.0449) Prec@1 97.000 (92.478) Prec@5 100.000 (99.609) +2022-11-14 14:20:15,488 Epoch: [182][230/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0516 (0.0452) Prec@1 91.000 (92.417) Prec@5 100.000 (99.625) +2022-11-14 14:20:15,833 Epoch: [182][240/500] Time 0.033 (0.030) Data 0.002 (0.003) Loss 0.0375 (0.0449) Prec@1 93.000 (92.440) Prec@5 100.000 (99.640) +2022-11-14 14:20:16,193 Epoch: [182][250/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0432 (0.0448) Prec@1 93.000 (92.462) Prec@5 100.000 (99.654) +2022-11-14 14:20:16,530 Epoch: [182][260/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0427 (0.0447) Prec@1 94.000 (92.519) Prec@5 99.000 (99.630) +2022-11-14 14:20:16,881 Epoch: [182][270/500] Time 0.039 (0.030) Data 0.002 (0.003) Loss 0.0476 (0.0448) Prec@1 91.000 (92.464) Prec@5 99.000 (99.607) +2022-11-14 14:20:17,243 Epoch: [182][280/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0461 (0.0449) Prec@1 95.000 (92.552) Prec@5 99.000 (99.586) +2022-11-14 14:20:17,734 Epoch: [182][290/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0724 (0.0458) Prec@1 87.000 (92.367) Prec@5 100.000 (99.600) +2022-11-14 14:20:18,225 Epoch: [182][300/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0231 (0.0451) Prec@1 97.000 (92.516) Prec@5 100.000 (99.613) +2022-11-14 14:20:18,710 Epoch: [182][310/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0509 (0.0452) Prec@1 92.000 (92.500) Prec@5 100.000 (99.625) +2022-11-14 14:20:19,187 Epoch: [182][320/500] Time 0.042 (0.032) Data 0.003 (0.003) Loss 0.0399 (0.0451) Prec@1 94.000 (92.545) Prec@5 100.000 (99.636) +2022-11-14 14:20:19,743 Epoch: [182][330/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0466 (0.0451) Prec@1 92.000 (92.529) Prec@5 100.000 (99.647) +2022-11-14 14:20:20,303 Epoch: [182][340/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0168 (0.0443) Prec@1 97.000 (92.657) Prec@5 100.000 (99.657) +2022-11-14 14:20:20,879 Epoch: [182][350/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0804 (0.0453) Prec@1 86.000 (92.472) Prec@5 98.000 (99.611) +2022-11-14 14:20:21,510 Epoch: [182][360/500] Time 0.088 (0.034) Data 0.002 (0.003) Loss 0.0459 (0.0453) Prec@1 94.000 (92.514) Prec@5 100.000 (99.622) +2022-11-14 14:20:22,064 Epoch: [182][370/500] Time 0.081 (0.034) Data 0.002 (0.003) Loss 0.0520 (0.0455) Prec@1 91.000 (92.474) Prec@5 100.000 (99.632) +2022-11-14 14:20:22,612 Epoch: [182][380/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0458 (0.0455) Prec@1 92.000 (92.462) Prec@5 99.000 (99.615) +2022-11-14 14:20:23,175 Epoch: [182][390/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0379 (0.0453) Prec@1 95.000 (92.525) Prec@5 100.000 (99.625) +2022-11-14 14:20:23,725 Epoch: [182][400/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0697 (0.0459) Prec@1 89.000 (92.439) Prec@5 100.000 (99.634) +2022-11-14 14:20:24,303 Epoch: [182][410/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0565 (0.0462) Prec@1 93.000 (92.452) Prec@5 99.000 (99.619) +2022-11-14 14:20:24,848 Epoch: [182][420/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0528 (0.0463) Prec@1 91.000 (92.419) Prec@5 100.000 (99.628) +2022-11-14 14:20:25,449 Epoch: [182][430/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0313 (0.0460) Prec@1 94.000 (92.455) Prec@5 100.000 (99.636) +2022-11-14 14:20:26,013 Epoch: [182][440/500] Time 0.097 (0.037) Data 0.002 (0.002) Loss 0.0418 (0.0459) Prec@1 93.000 (92.467) Prec@5 100.000 (99.644) +2022-11-14 14:20:26,583 Epoch: [182][450/500] Time 0.051 (0.037) Data 0.002 (0.002) Loss 0.0305 (0.0456) Prec@1 94.000 (92.500) Prec@5 100.000 (99.652) +2022-11-14 14:20:27,167 Epoch: [182][460/500] Time 0.052 (0.037) Data 0.003 (0.002) Loss 0.0230 (0.0451) Prec@1 96.000 (92.574) Prec@5 100.000 (99.660) +2022-11-14 14:20:27,726 Epoch: [182][470/500] Time 0.114 (0.038) Data 0.002 (0.002) Loss 0.0565 (0.0453) Prec@1 90.000 (92.521) Prec@5 98.000 (99.625) +2022-11-14 14:20:28,278 Epoch: [182][480/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0507 (0.0454) Prec@1 91.000 (92.490) Prec@5 100.000 (99.633) +2022-11-14 14:20:29,056 Epoch: [182][490/500] Time 0.089 (0.039) Data 0.002 (0.002) Loss 0.0380 (0.0453) Prec@1 93.000 (92.500) Prec@5 100.000 (99.640) +2022-11-14 14:20:29,555 Epoch: [182][499/500] Time 0.044 (0.039) Data 0.001 (0.002) Loss 0.0671 (0.0457) Prec@1 89.000 (92.431) Prec@5 99.000 (99.627) +2022-11-14 14:20:29,842 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0385 (0.0385) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:29,858 Test: [1/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0550 (0.0467) Prec@1 91.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:29,870 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0884 (0.0606) Prec@1 85.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:29,884 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0623) Prec@1 89.000 (90.500) Prec@5 97.000 (99.250) +2022-11-14 14:20:29,895 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0788 (0.0656) Prec@1 88.000 (90.000) Prec@5 100.000 (99.400) +2022-11-14 14:20:29,908 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0479 (0.0627) Prec@1 93.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 14:20:29,919 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0631) Prec@1 90.000 (90.429) Prec@5 99.000 (99.429) +2022-11-14 14:20:29,933 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0927 (0.0668) Prec@1 85.000 (89.750) Prec@5 99.000 (99.375) +2022-11-14 14:20:29,945 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0690) Prec@1 87.000 (89.444) Prec@5 100.000 (99.444) +2022-11-14 14:20:29,960 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0697) Prec@1 86.000 (89.100) Prec@5 99.000 (99.400) +2022-11-14 14:20:29,972 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0688) Prec@1 90.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 14:20:29,985 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0697) Prec@1 88.000 (89.083) Prec@5 99.000 (99.417) +2022-11-14 14:20:29,998 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0685) Prec@1 90.000 (89.154) Prec@5 100.000 (99.462) +2022-11-14 14:20:30,011 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0690) Prec@1 88.000 (89.071) Prec@5 99.000 (99.429) +2022-11-14 14:20:30,024 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0689) Prec@1 88.000 (89.000) Prec@5 100.000 (99.467) +2022-11-14 14:20:30,036 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0695) Prec@1 84.000 (88.688) Prec@5 99.000 (99.438) +2022-11-14 14:20:30,050 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0486 (0.0682) Prec@1 93.000 (88.941) Prec@5 99.000 (99.412) +2022-11-14 14:20:30,062 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1045 (0.0702) Prec@1 83.000 (88.611) Prec@5 97.000 (99.278) +2022-11-14 14:20:30,074 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0919 (0.0714) Prec@1 83.000 (88.316) Prec@5 98.000 (99.211) +2022-11-14 14:20:30,084 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0913 (0.0724) Prec@1 85.000 (88.150) Prec@5 98.000 (99.150) +2022-11-14 14:20:30,094 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0941 (0.0734) Prec@1 84.000 (87.952) Prec@5 100.000 (99.190) +2022-11-14 14:20:30,104 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0738) Prec@1 84.000 (87.773) Prec@5 99.000 (99.182) +2022-11-14 14:20:30,114 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1158 (0.0756) Prec@1 82.000 (87.522) Prec@5 99.000 (99.174) +2022-11-14 14:20:30,124 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0759) Prec@1 86.000 (87.458) Prec@5 99.000 (99.167) +2022-11-14 14:20:30,135 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0772) Prec@1 84.000 (87.320) Prec@5 100.000 (99.200) +2022-11-14 14:20:30,144 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0782) Prec@1 83.000 (87.154) Prec@5 98.000 (99.154) +2022-11-14 14:20:30,154 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0773) Prec@1 91.000 (87.296) Prec@5 100.000 (99.185) +2022-11-14 14:20:30,164 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0771) Prec@1 87.000 (87.286) Prec@5 100.000 (99.214) +2022-11-14 14:20:30,172 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0769) Prec@1 90.000 (87.379) Prec@5 99.000 (99.207) +2022-11-14 14:20:30,181 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0767) Prec@1 89.000 (87.433) Prec@5 99.000 (99.200) +2022-11-14 14:20:30,191 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0766) Prec@1 87.000 (87.419) Prec@5 99.000 (99.194) +2022-11-14 14:20:30,200 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0764) Prec@1 88.000 (87.438) Prec@5 99.000 (99.188) +2022-11-14 14:20:30,208 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0763) Prec@1 87.000 (87.424) Prec@5 100.000 (99.212) +2022-11-14 14:20:30,218 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0771) Prec@1 83.000 (87.294) Prec@5 98.000 (99.176) +2022-11-14 14:20:30,227 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0775) Prec@1 83.000 (87.171) Prec@5 98.000 (99.143) +2022-11-14 14:20:30,236 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0774) Prec@1 89.000 (87.222) Prec@5 100.000 (99.167) +2022-11-14 14:20:30,246 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0771) Prec@1 89.000 (87.270) Prec@5 100.000 (99.189) +2022-11-14 14:20:30,255 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1150 (0.0781) Prec@1 81.000 (87.105) Prec@5 99.000 (99.184) +2022-11-14 14:20:30,264 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0774) Prec@1 93.000 (87.256) Prec@5 98.000 (99.154) +2022-11-14 14:20:30,274 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0770) Prec@1 91.000 (87.350) Prec@5 100.000 (99.175) +2022-11-14 14:20:30,284 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0778) Prec@1 84.000 (87.268) Prec@5 96.000 (99.098) +2022-11-14 14:20:30,294 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0779) Prec@1 88.000 (87.286) Prec@5 100.000 (99.119) +2022-11-14 14:20:30,305 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0772) Prec@1 90.000 (87.349) Prec@5 100.000 (99.140) +2022-11-14 14:20:30,314 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0775) Prec@1 87.000 (87.341) Prec@5 98.000 (99.114) +2022-11-14 14:20:30,324 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0773) Prec@1 88.000 (87.356) Prec@5 99.000 (99.111) +2022-11-14 14:20:30,333 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1175 (0.0781) Prec@1 78.000 (87.152) Prec@5 98.000 (99.087) +2022-11-14 14:20:30,343 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0782) Prec@1 88.000 (87.170) Prec@5 100.000 (99.106) +2022-11-14 14:20:30,352 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0785) Prec@1 84.000 (87.104) Prec@5 98.000 (99.083) +2022-11-14 14:20:30,361 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0780) Prec@1 91.000 (87.184) Prec@5 99.000 (99.082) +2022-11-14 14:20:30,371 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0786) Prec@1 84.000 (87.120) Prec@5 99.000 (99.080) +2022-11-14 14:20:30,381 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0784) Prec@1 90.000 (87.176) Prec@5 100.000 (99.098) +2022-11-14 14:20:30,390 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0788) Prec@1 85.000 (87.135) Prec@5 99.000 (99.096) +2022-11-14 14:20:30,401 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0783) Prec@1 92.000 (87.226) Prec@5 100.000 (99.113) +2022-11-14 14:20:30,410 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0784) Prec@1 85.000 (87.185) Prec@5 98.000 (99.093) +2022-11-14 14:20:30,420 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0783) Prec@1 88.000 (87.200) Prec@5 100.000 (99.109) +2022-11-14 14:20:30,429 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0783) Prec@1 88.000 (87.214) Prec@5 99.000 (99.107) +2022-11-14 14:20:30,438 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0784) Prec@1 85.000 (87.175) Prec@5 100.000 (99.123) +2022-11-14 14:20:30,448 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0785) Prec@1 87.000 (87.172) Prec@5 99.000 (99.121) +2022-11-14 14:20:30,457 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0790) Prec@1 81.000 (87.068) Prec@5 100.000 (99.136) +2022-11-14 14:20:30,466 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0789) Prec@1 89.000 (87.100) Prec@5 100.000 (99.150) +2022-11-14 14:20:30,475 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0790) Prec@1 86.000 (87.082) Prec@5 100.000 (99.164) +2022-11-14 14:20:30,484 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0788) Prec@1 90.000 (87.129) Prec@5 98.000 (99.145) +2022-11-14 14:20:30,493 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0787) Prec@1 85.000 (87.095) Prec@5 100.000 (99.159) +2022-11-14 14:20:30,504 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0386 (0.0781) Prec@1 94.000 (87.203) Prec@5 100.000 (99.172) +2022-11-14 14:20:30,513 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0782) Prec@1 83.000 (87.138) Prec@5 98.000 (99.154) +2022-11-14 14:20:30,522 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0783) Prec@1 87.000 (87.136) Prec@5 96.000 (99.106) +2022-11-14 14:20:30,532 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0778) Prec@1 92.000 (87.209) Prec@5 100.000 (99.119) +2022-11-14 14:20:30,542 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0777) Prec@1 88.000 (87.221) Prec@5 100.000 (99.132) +2022-11-14 14:20:30,552 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0775) Prec@1 89.000 (87.246) Prec@5 99.000 (99.130) +2022-11-14 14:20:30,561 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0775) Prec@1 87.000 (87.243) Prec@5 100.000 (99.143) +2022-11-14 14:20:30,569 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0776) Prec@1 88.000 (87.254) Prec@5 99.000 (99.141) +2022-11-14 14:20:30,578 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0774) Prec@1 91.000 (87.306) Prec@5 98.000 (99.125) +2022-11-14 14:20:30,588 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0769) Prec@1 95.000 (87.411) Prec@5 99.000 (99.123) +2022-11-14 14:20:30,598 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0768) Prec@1 90.000 (87.446) Prec@5 98.000 (99.108) +2022-11-14 14:20:30,608 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0771) Prec@1 85.000 (87.413) Prec@5 99.000 (99.107) +2022-11-14 14:20:30,617 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0770) Prec@1 88.000 (87.421) Prec@5 99.000 (99.105) +2022-11-14 14:20:30,626 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0768) Prec@1 89.000 (87.442) Prec@5 99.000 (99.104) +2022-11-14 14:20:30,636 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0770) Prec@1 84.000 (87.397) Prec@5 99.000 (99.103) +2022-11-14 14:20:30,645 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0771) Prec@1 83.000 (87.342) Prec@5 100.000 (99.114) +2022-11-14 14:20:30,654 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0772) Prec@1 85.000 (87.312) Prec@5 98.000 (99.100) +2022-11-14 14:20:30,664 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0774) Prec@1 84.000 (87.272) Prec@5 99.000 (99.099) +2022-11-14 14:20:30,672 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0771) Prec@1 90.000 (87.305) Prec@5 100.000 (99.110) +2022-11-14 14:20:30,681 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0772) Prec@1 88.000 (87.313) Prec@5 100.000 (99.120) +2022-11-14 14:20:30,690 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0773) Prec@1 84.000 (87.274) Prec@5 99.000 (99.119) +2022-11-14 14:20:30,700 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0772) Prec@1 90.000 (87.306) Prec@5 99.000 (99.118) +2022-11-14 14:20:30,709 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.0776) Prec@1 82.000 (87.244) Prec@5 100.000 (99.128) +2022-11-14 14:20:30,718 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0776) Prec@1 86.000 (87.230) Prec@5 99.000 (99.126) +2022-11-14 14:20:30,727 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0775) Prec@1 88.000 (87.239) Prec@5 98.000 (99.114) +2022-11-14 14:20:30,736 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0775) Prec@1 86.000 (87.225) Prec@5 100.000 (99.124) +2022-11-14 14:20:30,745 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0775) Prec@1 87.000 (87.222) Prec@5 100.000 (99.133) +2022-11-14 14:20:30,755 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0773) Prec@1 90.000 (87.253) Prec@5 100.000 (99.143) +2022-11-14 14:20:30,764 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0771) Prec@1 90.000 (87.283) Prec@5 98.000 (99.130) +2022-11-14 14:20:30,773 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0771) Prec@1 87.000 (87.280) Prec@5 99.000 (99.129) +2022-11-14 14:20:30,783 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0772) Prec@1 88.000 (87.287) Prec@5 98.000 (99.117) +2022-11-14 14:20:30,791 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0773) Prec@1 85.000 (87.263) Prec@5 99.000 (99.116) +2022-11-14 14:20:30,802 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0773) Prec@1 86.000 (87.250) Prec@5 100.000 (99.125) +2022-11-14 14:20:30,811 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0770) Prec@1 93.000 (87.309) Prec@5 99.000 (99.124) +2022-11-14 14:20:30,820 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0771) Prec@1 85.000 (87.286) Prec@5 99.000 (99.122) +2022-11-14 14:20:30,829 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0774) Prec@1 84.000 (87.253) Prec@5 100.000 (99.131) +2022-11-14 14:20:30,838 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0771) Prec@1 94.000 (87.320) Prec@5 99.000 (99.130) +2022-11-14 14:20:30,910 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:20:31,247 Epoch: [183][0/500] Time 0.026 (0.026) Data 0.242 (0.242) Loss 0.0443 (0.0443) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:31,464 Epoch: [183][10/500] Time 0.018 (0.020) Data 0.001 (0.024) Loss 0.0270 (0.0357) Prec@1 95.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:31,720 Epoch: [183][20/500] Time 0.028 (0.021) Data 0.001 (0.013) Loss 0.0394 (0.0369) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:32,114 Epoch: [183][30/500] Time 0.028 (0.026) Data 0.002 (0.010) Loss 0.0568 (0.0419) Prec@1 91.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:20:32,504 Epoch: [183][40/500] Time 0.039 (0.028) Data 0.002 (0.008) Loss 0.0331 (0.0401) Prec@1 94.000 (92.800) Prec@5 99.000 (99.800) +2022-11-14 14:20:32,807 Epoch: [183][50/500] Time 0.027 (0.028) Data 0.002 (0.007) Loss 0.0395 (0.0400) Prec@1 93.000 (92.833) Prec@5 100.000 (99.833) +2022-11-14 14:20:33,129 Epoch: [183][60/500] Time 0.027 (0.028) Data 0.002 (0.006) Loss 0.0375 (0.0397) Prec@1 94.000 (93.000) Prec@5 100.000 (99.857) +2022-11-14 14:20:33,448 Epoch: [183][70/500] Time 0.029 (0.028) Data 0.002 (0.005) Loss 0.0463 (0.0405) Prec@1 90.000 (92.625) Prec@5 100.000 (99.875) +2022-11-14 14:20:33,774 Epoch: [183][80/500] Time 0.029 (0.028) Data 0.002 (0.005) Loss 0.0272 (0.0390) Prec@1 96.000 (93.000) Prec@5 100.000 (99.889) +2022-11-14 14:20:34,090 Epoch: [183][90/500] Time 0.037 (0.028) Data 0.002 (0.005) Loss 0.0520 (0.0403) Prec@1 92.000 (92.900) Prec@5 100.000 (99.900) +2022-11-14 14:20:34,411 Epoch: [183][100/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.0460 (0.0408) Prec@1 93.000 (92.909) Prec@5 99.000 (99.818) +2022-11-14 14:20:34,740 Epoch: [183][110/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.0142 (0.0386) Prec@1 98.000 (93.333) Prec@5 100.000 (99.833) +2022-11-14 14:20:35,052 Epoch: [183][120/500] Time 0.032 (0.028) Data 0.002 (0.004) Loss 0.0568 (0.0400) Prec@1 91.000 (93.154) Prec@5 100.000 (99.846) +2022-11-14 14:20:35,373 Epoch: [183][130/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.0370 (0.0398) Prec@1 95.000 (93.286) Prec@5 99.000 (99.786) +2022-11-14 14:20:35,692 Epoch: [183][140/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0529 (0.0407) Prec@1 93.000 (93.267) Prec@5 100.000 (99.800) +2022-11-14 14:20:36,120 Epoch: [183][150/500] Time 0.053 (0.029) Data 0.002 (0.004) Loss 0.0403 (0.0407) Prec@1 95.000 (93.375) Prec@5 100.000 (99.812) +2022-11-14 14:20:36,610 Epoch: [183][160/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0459 (0.0410) Prec@1 93.000 (93.353) Prec@5 99.000 (99.765) +2022-11-14 14:20:37,108 Epoch: [183][170/500] Time 0.059 (0.031) Data 0.002 (0.003) Loss 0.0400 (0.0409) Prec@1 92.000 (93.278) Prec@5 99.000 (99.722) +2022-11-14 14:20:37,637 Epoch: [183][180/500] Time 0.058 (0.031) Data 0.002 (0.003) Loss 0.0554 (0.0417) Prec@1 93.000 (93.263) Prec@5 100.000 (99.737) +2022-11-14 14:20:38,149 Epoch: [183][190/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0244 (0.0408) Prec@1 97.000 (93.450) Prec@5 100.000 (99.750) +2022-11-14 14:20:38,650 Epoch: [183][200/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0543 (0.0414) Prec@1 93.000 (93.429) Prec@5 98.000 (99.667) +2022-11-14 14:20:39,131 Epoch: [183][210/500] Time 0.051 (0.033) Data 0.002 (0.003) Loss 0.0260 (0.0407) Prec@1 98.000 (93.636) Prec@5 100.000 (99.682) +2022-11-14 14:20:39,612 Epoch: [183][220/500] Time 0.045 (0.034) Data 0.003 (0.003) Loss 0.0346 (0.0405) Prec@1 95.000 (93.696) Prec@5 99.000 (99.652) +2022-11-14 14:20:40,170 Epoch: [183][230/500] Time 0.051 (0.034) Data 0.002 (0.003) Loss 0.0436 (0.0406) Prec@1 93.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:20:40,649 Epoch: [183][240/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0661 (0.0416) Prec@1 88.000 (93.440) Prec@5 100.000 (99.680) +2022-11-14 14:20:41,207 Epoch: [183][250/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0539 (0.0421) Prec@1 92.000 (93.385) Prec@5 99.000 (99.654) +2022-11-14 14:20:41,712 Epoch: [183][260/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0525 (0.0425) Prec@1 91.000 (93.296) Prec@5 100.000 (99.667) +2022-11-14 14:20:42,203 Epoch: [183][270/500] Time 0.049 (0.036) Data 0.002 (0.003) Loss 0.0342 (0.0422) Prec@1 95.000 (93.357) Prec@5 100.000 (99.679) +2022-11-14 14:20:42,681 Epoch: [183][280/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.0405 (0.0421) Prec@1 95.000 (93.414) Prec@5 99.000 (99.655) +2022-11-14 14:20:43,199 Epoch: [183][290/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0626 (0.0428) Prec@1 88.000 (93.233) Prec@5 99.000 (99.633) +2022-11-14 14:20:43,697 Epoch: [183][300/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0697 (0.0437) Prec@1 88.000 (93.065) Prec@5 98.000 (99.581) +2022-11-14 14:20:44,210 Epoch: [183][310/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0457 (0.0437) Prec@1 92.000 (93.031) Prec@5 100.000 (99.594) +2022-11-14 14:20:44,675 Epoch: [183][320/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0373 (0.0436) Prec@1 95.000 (93.091) Prec@5 100.000 (99.606) +2022-11-14 14:20:45,195 Epoch: [183][330/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0349 (0.0433) Prec@1 95.000 (93.147) Prec@5 100.000 (99.618) +2022-11-14 14:20:45,742 Epoch: [183][340/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0417 (0.0433) Prec@1 91.000 (93.086) Prec@5 100.000 (99.629) +2022-11-14 14:20:46,243 Epoch: [183][350/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0370 (0.0431) Prec@1 92.000 (93.056) Prec@5 100.000 (99.639) +2022-11-14 14:20:46,745 Epoch: [183][360/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0437 (0.0431) Prec@1 92.000 (93.027) Prec@5 100.000 (99.649) +2022-11-14 14:20:47,262 Epoch: [183][370/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0502 (0.0433) Prec@1 90.000 (92.947) Prec@5 99.000 (99.632) +2022-11-14 14:20:47,744 Epoch: [183][380/500] Time 0.047 (0.039) Data 0.003 (0.003) Loss 0.0599 (0.0437) Prec@1 92.000 (92.923) Prec@5 100.000 (99.641) +2022-11-14 14:20:48,275 Epoch: [183][390/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0359 (0.0435) Prec@1 94.000 (92.950) Prec@5 100.000 (99.650) +2022-11-14 14:20:48,770 Epoch: [183][400/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0472 (0.0436) Prec@1 93.000 (92.951) Prec@5 100.000 (99.659) +2022-11-14 14:20:49,270 Epoch: [183][410/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0638 (0.0441) Prec@1 88.000 (92.833) Prec@5 98.000 (99.619) +2022-11-14 14:20:49,784 Epoch: [183][420/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0347 (0.0439) Prec@1 94.000 (92.860) Prec@5 99.000 (99.605) +2022-11-14 14:20:50,259 Epoch: [183][430/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0803 (0.0447) Prec@1 84.000 (92.659) Prec@5 100.000 (99.614) +2022-11-14 14:20:50,805 Epoch: [183][440/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0455 (0.0447) Prec@1 91.000 (92.622) Prec@5 100.000 (99.622) +2022-11-14 14:20:51,323 Epoch: [183][450/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0320 (0.0444) Prec@1 96.000 (92.696) Prec@5 100.000 (99.630) +2022-11-14 14:20:51,962 Epoch: [183][460/500] Time 0.096 (0.040) Data 0.002 (0.002) Loss 0.0562 (0.0447) Prec@1 89.000 (92.617) Prec@5 100.000 (99.638) +2022-11-14 14:20:52,447 Epoch: [183][470/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0459 (0.0447) Prec@1 91.000 (92.583) Prec@5 100.000 (99.646) +2022-11-14 14:20:53,009 Epoch: [183][480/500] Time 0.098 (0.040) Data 0.003 (0.002) Loss 0.0436 (0.0447) Prec@1 94.000 (92.612) Prec@5 100.000 (99.653) +2022-11-14 14:20:53,588 Epoch: [183][490/500] Time 0.046 (0.041) Data 0.002 (0.002) Loss 0.0338 (0.0445) Prec@1 94.000 (92.640) Prec@5 100.000 (99.660) +2022-11-14 14:20:54,035 Epoch: [183][499/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0461 (0.0445) Prec@1 92.000 (92.627) Prec@5 100.000 (99.667) +2022-11-14 14:20:54,339 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0711 (0.0711) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:54,351 Test: [1/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.0687 (0.0699) Prec@1 88.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:20:54,362 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0885 (0.0761) Prec@1 85.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:20:54,375 Test: [3/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0848 (0.0783) Prec@1 87.000 (86.750) Prec@5 99.000 (99.750) +2022-11-14 14:20:54,383 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0680 (0.0762) Prec@1 86.000 (86.600) Prec@5 98.000 (99.400) +2022-11-14 14:20:54,390 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0556 (0.0728) Prec@1 87.000 (86.667) Prec@5 100.000 (99.500) +2022-11-14 14:20:54,399 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0731) Prec@1 88.000 (86.857) Prec@5 100.000 (99.571) +2022-11-14 14:20:54,410 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0727) Prec@1 88.000 (87.000) Prec@5 100.000 (99.625) +2022-11-14 14:20:54,419 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0752) Prec@1 85.000 (86.778) Prec@5 100.000 (99.667) +2022-11-14 14:20:54,428 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0735) Prec@1 90.000 (87.100) Prec@5 99.000 (99.600) +2022-11-14 14:20:54,438 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0720) Prec@1 90.000 (87.364) Prec@5 100.000 (99.636) +2022-11-14 14:20:54,448 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0722) Prec@1 87.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:20:54,460 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0712) Prec@1 89.000 (87.462) Prec@5 100.000 (99.692) +2022-11-14 14:20:54,469 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0711) Prec@1 90.000 (87.643) Prec@5 97.000 (99.500) +2022-11-14 14:20:54,478 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0708) Prec@1 91.000 (87.867) Prec@5 99.000 (99.467) +2022-11-14 14:20:54,488 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0712) Prec@1 86.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 14:20:54,499 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0703) Prec@1 91.000 (87.941) Prec@5 99.000 (99.471) +2022-11-14 14:20:54,509 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0718) Prec@1 84.000 (87.722) Prec@5 99.000 (99.444) +2022-11-14 14:20:54,520 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0728) Prec@1 87.000 (87.684) Prec@5 99.000 (99.421) +2022-11-14 14:20:54,530 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0730) Prec@1 84.000 (87.500) Prec@5 100.000 (99.450) +2022-11-14 14:20:54,542 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0741) Prec@1 82.000 (87.238) Prec@5 99.000 (99.429) +2022-11-14 14:20:54,554 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0745) Prec@1 85.000 (87.136) Prec@5 100.000 (99.455) +2022-11-14 14:20:54,564 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0753) Prec@1 86.000 (87.087) Prec@5 98.000 (99.391) +2022-11-14 14:20:54,576 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0748) Prec@1 86.000 (87.042) Prec@5 100.000 (99.417) +2022-11-14 14:20:54,586 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0763) Prec@1 84.000 (86.920) Prec@5 99.000 (99.400) +2022-11-14 14:20:54,599 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0766) Prec@1 87.000 (86.923) Prec@5 100.000 (99.423) +2022-11-14 14:20:54,611 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0760) Prec@1 89.000 (87.000) Prec@5 99.000 (99.407) +2022-11-14 14:20:54,621 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0757) Prec@1 88.000 (87.036) Prec@5 100.000 (99.429) +2022-11-14 14:20:54,632 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0754) Prec@1 88.000 (87.069) Prec@5 100.000 (99.448) +2022-11-14 14:20:54,643 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0756) Prec@1 85.000 (87.000) Prec@5 100.000 (99.467) +2022-11-14 14:20:54,653 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0755) Prec@1 87.000 (87.000) Prec@5 99.000 (99.452) +2022-11-14 14:20:54,665 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0759) Prec@1 87.000 (87.000) Prec@5 98.000 (99.406) +2022-11-14 14:20:54,676 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0765) Prec@1 84.000 (86.909) Prec@5 99.000 (99.394) +2022-11-14 14:20:54,687 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0766) Prec@1 85.000 (86.853) Prec@5 100.000 (99.412) +2022-11-14 14:20:54,699 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0769) Prec@1 84.000 (86.771) Prec@5 99.000 (99.400) +2022-11-14 14:20:54,710 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0767) Prec@1 90.000 (86.861) Prec@5 100.000 (99.417) +2022-11-14 14:20:54,722 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0771) Prec@1 86.000 (86.838) Prec@5 99.000 (99.405) +2022-11-14 14:20:54,734 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0775) Prec@1 79.000 (86.632) Prec@5 100.000 (99.421) +2022-11-14 14:20:54,744 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0773) Prec@1 89.000 (86.692) Prec@5 99.000 (99.410) +2022-11-14 14:20:54,756 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0768) Prec@1 92.000 (86.825) Prec@5 99.000 (99.400) +2022-11-14 14:20:54,767 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0772) Prec@1 86.000 (86.805) Prec@5 98.000 (99.366) +2022-11-14 14:20:54,778 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0773) Prec@1 88.000 (86.833) Prec@5 99.000 (99.357) +2022-11-14 14:20:54,792 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0370 (0.0763) Prec@1 95.000 (87.023) Prec@5 99.000 (99.349) +2022-11-14 14:20:54,806 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0763) Prec@1 88.000 (87.045) Prec@5 99.000 (99.341) +2022-11-14 14:20:54,821 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0761) Prec@1 88.000 (87.067) Prec@5 99.000 (99.333) +2022-11-14 14:20:54,836 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0768) Prec@1 84.000 (87.000) Prec@5 97.000 (99.283) +2022-11-14 14:20:54,851 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0767) Prec@1 87.000 (87.000) Prec@5 100.000 (99.298) +2022-11-14 14:20:54,864 Test: [47/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0771) Prec@1 84.000 (86.938) Prec@5 98.000 (99.271) +2022-11-14 14:20:54,879 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0765) Prec@1 92.000 (87.041) Prec@5 100.000 (99.286) +2022-11-14 14:20:54,893 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0770) Prec@1 85.000 (87.000) Prec@5 100.000 (99.300) +2022-11-14 14:20:54,908 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0774) Prec@1 82.000 (86.902) Prec@5 99.000 (99.294) +2022-11-14 14:20:54,919 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0776) Prec@1 86.000 (86.885) Prec@5 100.000 (99.308) +2022-11-14 14:20:54,932 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0776) Prec@1 89.000 (86.925) Prec@5 99.000 (99.302) +2022-11-14 14:20:54,944 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0773) Prec@1 91.000 (87.000) Prec@5 100.000 (99.315) +2022-11-14 14:20:54,954 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0772) Prec@1 86.000 (86.982) Prec@5 99.000 (99.309) +2022-11-14 14:20:54,964 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0769) Prec@1 91.000 (87.054) Prec@5 99.000 (99.304) +2022-11-14 14:20:54,973 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0769) Prec@1 87.000 (87.053) Prec@5 100.000 (99.316) +2022-11-14 14:20:54,985 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0768) Prec@1 87.000 (87.052) Prec@5 100.000 (99.328) +2022-11-14 14:20:54,995 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0770) Prec@1 84.000 (87.000) Prec@5 100.000 (99.339) +2022-11-14 14:20:55,007 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0770) Prec@1 86.000 (86.983) Prec@5 100.000 (99.350) +2022-11-14 14:20:55,018 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0771) Prec@1 86.000 (86.967) Prec@5 100.000 (99.361) +2022-11-14 14:20:55,028 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0770) Prec@1 87.000 (86.968) Prec@5 100.000 (99.371) +2022-11-14 14:20:55,040 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0767) Prec@1 92.000 (87.048) Prec@5 100.000 (99.381) +2022-11-14 14:20:55,050 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0763) Prec@1 93.000 (87.141) Prec@5 100.000 (99.391) +2022-11-14 14:20:55,063 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1237 (0.0770) Prec@1 77.000 (86.985) Prec@5 98.000 (99.369) +2022-11-14 14:20:55,075 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0774) Prec@1 83.000 (86.924) Prec@5 99.000 (99.364) +2022-11-14 14:20:55,085 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0770) Prec@1 91.000 (86.985) Prec@5 100.000 (99.373) +2022-11-14 14:20:55,096 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0774) Prec@1 82.000 (86.912) Prec@5 98.000 (99.353) +2022-11-14 14:20:55,106 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0773) Prec@1 89.000 (86.942) Prec@5 99.000 (99.348) +2022-11-14 14:20:55,117 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0775) Prec@1 82.000 (86.871) Prec@5 99.000 (99.343) +2022-11-14 14:20:55,129 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0776) Prec@1 85.000 (86.845) Prec@5 99.000 (99.338) +2022-11-14 14:20:55,142 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0776) Prec@1 89.000 (86.875) Prec@5 100.000 (99.347) +2022-11-14 14:20:55,152 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0774) Prec@1 91.000 (86.932) Prec@5 100.000 (99.356) +2022-11-14 14:20:55,161 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0771) Prec@1 90.000 (86.973) Prec@5 100.000 (99.365) +2022-11-14 14:20:55,172 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0772) Prec@1 85.000 (86.947) Prec@5 100.000 (99.373) +2022-11-14 14:20:55,183 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0768) Prec@1 93.000 (87.026) Prec@5 99.000 (99.368) +2022-11-14 14:20:55,194 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0770) Prec@1 86.000 (87.013) Prec@5 99.000 (99.364) +2022-11-14 14:20:55,205 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0773) Prec@1 83.000 (86.962) Prec@5 99.000 (99.359) +2022-11-14 14:20:55,215 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0773) Prec@1 87.000 (86.962) Prec@5 100.000 (99.367) +2022-11-14 14:20:55,226 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0775) Prec@1 86.000 (86.950) Prec@5 98.000 (99.350) +2022-11-14 14:20:55,237 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0776) Prec@1 87.000 (86.951) Prec@5 99.000 (99.346) +2022-11-14 14:20:55,250 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0777) Prec@1 83.000 (86.902) Prec@5 99.000 (99.341) +2022-11-14 14:20:55,261 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0775) Prec@1 89.000 (86.928) Prec@5 99.000 (99.337) +2022-11-14 14:20:55,272 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0775) Prec@1 85.000 (86.905) Prec@5 99.000 (99.333) +2022-11-14 14:20:55,284 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0778) Prec@1 85.000 (86.882) Prec@5 98.000 (99.318) +2022-11-14 14:20:55,300 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0781) Prec@1 85.000 (86.860) Prec@5 100.000 (99.326) +2022-11-14 14:20:55,315 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0782) Prec@1 86.000 (86.851) Prec@5 97.000 (99.299) +2022-11-14 14:20:55,330 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0783) Prec@1 87.000 (86.852) Prec@5 99.000 (99.295) +2022-11-14 14:20:55,345 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0783) Prec@1 87.000 (86.854) Prec@5 100.000 (99.303) +2022-11-14 14:20:55,359 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0783) Prec@1 87.000 (86.856) Prec@5 99.000 (99.300) +2022-11-14 14:20:55,372 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0781) Prec@1 90.000 (86.890) Prec@5 100.000 (99.308) +2022-11-14 14:20:55,387 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0777) Prec@1 92.000 (86.946) Prec@5 100.000 (99.315) +2022-11-14 14:20:55,400 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0778) Prec@1 88.000 (86.957) Prec@5 100.000 (99.323) +2022-11-14 14:20:55,414 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0778) Prec@1 85.000 (86.936) Prec@5 98.000 (99.309) +2022-11-14 14:20:55,427 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0778) Prec@1 87.000 (86.937) Prec@5 100.000 (99.316) +2022-11-14 14:20:55,438 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0776) Prec@1 89.000 (86.958) Prec@5 99.000 (99.312) +2022-11-14 14:20:55,448 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0399 (0.0772) Prec@1 90.000 (86.990) Prec@5 100.000 (99.320) +2022-11-14 14:20:55,458 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0774) Prec@1 84.000 (86.959) Prec@5 99.000 (99.316) +2022-11-14 14:20:55,469 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0775) Prec@1 87.000 (86.960) Prec@5 100.000 (99.323) +2022-11-14 14:20:55,480 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0774) Prec@1 88.000 (86.970) Prec@5 100.000 (99.330) +2022-11-14 14:20:55,538 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:20:55,869 Epoch: [184][0/500] Time 0.032 (0.032) Data 0.234 (0.234) Loss 0.0698 (0.0698) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:56,139 Epoch: [184][10/500] Time 0.019 (0.025) Data 0.002 (0.023) Loss 0.0488 (0.0593) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:20:56,367 Epoch: [184][20/500] Time 0.025 (0.023) Data 0.002 (0.013) Loss 0.0391 (0.0526) Prec@1 93.000 (91.000) Prec@5 99.000 (99.667) +2022-11-14 14:20:56,659 Epoch: [184][30/500] Time 0.027 (0.023) Data 0.002 (0.009) Loss 0.0686 (0.0566) Prec@1 86.000 (89.750) Prec@5 100.000 (99.750) +2022-11-14 14:20:56,985 Epoch: [184][40/500] Time 0.044 (0.025) Data 0.002 (0.007) Loss 0.0396 (0.0532) Prec@1 94.000 (90.600) Prec@5 100.000 (99.800) +2022-11-14 14:20:57,287 Epoch: [184][50/500] Time 0.029 (0.025) Data 0.002 (0.006) Loss 0.0353 (0.0502) Prec@1 94.000 (91.167) Prec@5 99.000 (99.667) +2022-11-14 14:20:57,585 Epoch: [184][60/500] Time 0.028 (0.025) Data 0.002 (0.006) Loss 0.0636 (0.0521) Prec@1 87.000 (90.571) Prec@5 100.000 (99.714) +2022-11-14 14:20:57,886 Epoch: [184][70/500] Time 0.032 (0.026) Data 0.002 (0.005) Loss 0.0390 (0.0505) Prec@1 93.000 (90.875) Prec@5 99.000 (99.625) +2022-11-14 14:20:58,185 Epoch: [184][80/500] Time 0.027 (0.026) Data 0.002 (0.005) Loss 0.0599 (0.0515) Prec@1 92.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:20:58,484 Epoch: [184][90/500] Time 0.028 (0.026) Data 0.001 (0.004) Loss 0.0413 (0.0505) Prec@1 93.000 (91.200) Prec@5 100.000 (99.700) +2022-11-14 14:20:58,792 Epoch: [184][100/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0540 (0.0508) Prec@1 91.000 (91.182) Prec@5 99.000 (99.636) +2022-11-14 14:20:59,152 Epoch: [184][110/500] Time 0.042 (0.026) Data 0.002 (0.004) Loss 0.0381 (0.0498) Prec@1 92.000 (91.250) Prec@5 100.000 (99.667) +2022-11-14 14:20:59,462 Epoch: [184][120/500] Time 0.040 (0.026) Data 0.002 (0.004) Loss 0.0401 (0.0490) Prec@1 94.000 (91.462) Prec@5 100.000 (99.692) +2022-11-14 14:21:00,002 Epoch: [184][130/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0451 (0.0487) Prec@1 92.000 (91.500) Prec@5 100.000 (99.714) +2022-11-14 14:21:00,678 Epoch: [184][140/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0396 (0.0481) Prec@1 93.000 (91.600) Prec@5 100.000 (99.733) +2022-11-14 14:21:01,270 Epoch: [184][150/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0545 (0.0485) Prec@1 89.000 (91.438) Prec@5 100.000 (99.750) +2022-11-14 14:21:01,828 Epoch: [184][160/500] Time 0.050 (0.033) Data 0.002 (0.003) Loss 0.0416 (0.0481) Prec@1 93.000 (91.529) Prec@5 98.000 (99.647) +2022-11-14 14:21:02,553 Epoch: [184][170/500] Time 0.079 (0.035) Data 0.002 (0.003) Loss 0.0356 (0.0474) Prec@1 95.000 (91.722) Prec@5 100.000 (99.667) +2022-11-14 14:21:03,119 Epoch: [184][180/500] Time 0.050 (0.036) Data 0.002 (0.003) Loss 0.0593 (0.0481) Prec@1 91.000 (91.684) Prec@5 99.000 (99.632) +2022-11-14 14:21:03,610 Epoch: [184][190/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.0572 (0.0485) Prec@1 89.000 (91.550) Prec@5 100.000 (99.650) +2022-11-14 14:21:04,105 Epoch: [184][200/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0417 (0.0482) Prec@1 93.000 (91.619) Prec@5 100.000 (99.667) +2022-11-14 14:21:04,716 Epoch: [184][210/500] Time 0.093 (0.038) Data 0.002 (0.003) Loss 0.0562 (0.0486) Prec@1 89.000 (91.500) Prec@5 99.000 (99.636) +2022-11-14 14:21:05,219 Epoch: [184][220/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0555 (0.0489) Prec@1 90.000 (91.435) Prec@5 100.000 (99.652) +2022-11-14 14:21:05,808 Epoch: [184][230/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0383 (0.0484) Prec@1 94.000 (91.542) Prec@5 100.000 (99.667) +2022-11-14 14:21:06,555 Epoch: [184][240/500] Time 0.059 (0.040) Data 0.002 (0.003) Loss 0.0706 (0.0493) Prec@1 89.000 (91.440) Prec@5 99.000 (99.640) +2022-11-14 14:21:07,172 Epoch: [184][250/500] Time 0.045 (0.041) Data 0.003 (0.003) Loss 0.0488 (0.0493) Prec@1 89.000 (91.346) Prec@5 100.000 (99.654) +2022-11-14 14:21:07,811 Epoch: [184][260/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0373 (0.0488) Prec@1 94.000 (91.444) Prec@5 100.000 (99.667) +2022-11-14 14:21:08,445 Epoch: [184][270/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0542 (0.0490) Prec@1 91.000 (91.429) Prec@5 99.000 (99.643) +2022-11-14 14:21:08,943 Epoch: [184][280/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0451 (0.0489) Prec@1 93.000 (91.483) Prec@5 99.000 (99.621) +2022-11-14 14:21:09,447 Epoch: [184][290/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0651 (0.0494) Prec@1 89.000 (91.400) Prec@5 99.000 (99.600) +2022-11-14 14:21:09,928 Epoch: [184][300/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0592 (0.0498) Prec@1 90.000 (91.355) Prec@5 100.000 (99.613) +2022-11-14 14:21:10,401 Epoch: [184][310/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0441 (0.0496) Prec@1 90.000 (91.312) Prec@5 100.000 (99.625) +2022-11-14 14:21:10,946 Epoch: [184][320/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0434 (0.0494) Prec@1 92.000 (91.333) Prec@5 99.000 (99.606) +2022-11-14 14:21:11,442 Epoch: [184][330/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0429 (0.0492) Prec@1 93.000 (91.382) Prec@5 100.000 (99.618) +2022-11-14 14:21:11,994 Epoch: [184][340/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0420 (0.0490) Prec@1 94.000 (91.457) Prec@5 100.000 (99.629) +2022-11-14 14:21:12,535 Epoch: [184][350/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0561 (0.0492) Prec@1 92.000 (91.472) Prec@5 99.000 (99.611) +2022-11-14 14:21:13,091 Epoch: [184][360/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0299 (0.0487) Prec@1 96.000 (91.595) Prec@5 100.000 (99.622) +2022-11-14 14:21:13,631 Epoch: [184][370/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0357 (0.0483) Prec@1 93.000 (91.632) Prec@5 100.000 (99.632) +2022-11-14 14:21:14,174 Epoch: [184][380/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0361 (0.0480) Prec@1 94.000 (91.692) Prec@5 100.000 (99.641) +2022-11-14 14:21:14,711 Epoch: [184][390/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0396 (0.0478) Prec@1 93.000 (91.725) Prec@5 100.000 (99.650) +2022-11-14 14:21:15,290 Epoch: [184][400/500] Time 0.044 (0.044) Data 0.002 (0.002) Loss 0.0286 (0.0473) Prec@1 94.000 (91.780) Prec@5 100.000 (99.659) +2022-11-14 14:21:15,835 Epoch: [184][410/500] Time 0.050 (0.044) Data 0.002 (0.002) Loss 0.0222 (0.0467) Prec@1 98.000 (91.929) Prec@5 99.000 (99.643) +2022-11-14 14:21:16,394 Epoch: [184][420/500] Time 0.105 (0.044) Data 0.002 (0.002) Loss 0.0338 (0.0464) Prec@1 94.000 (91.977) Prec@5 100.000 (99.651) +2022-11-14 14:21:16,924 Epoch: [184][430/500] Time 0.072 (0.044) Data 0.002 (0.002) Loss 0.0440 (0.0464) Prec@1 92.000 (91.977) Prec@5 100.000 (99.659) +2022-11-14 14:21:17,467 Epoch: [184][440/500] Time 0.038 (0.044) Data 0.002 (0.002) Loss 0.0436 (0.0463) Prec@1 91.000 (91.956) Prec@5 100.000 (99.667) +2022-11-14 14:21:18,006 Epoch: [184][450/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0455 (0.0463) Prec@1 94.000 (92.000) Prec@5 100.000 (99.674) +2022-11-14 14:21:18,545 Epoch: [184][460/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0338 (0.0460) Prec@1 94.000 (92.043) Prec@5 100.000 (99.681) +2022-11-14 14:21:19,086 Epoch: [184][470/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0354 (0.0458) Prec@1 96.000 (92.125) Prec@5 100.000 (99.688) +2022-11-14 14:21:19,624 Epoch: [184][480/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0412 (0.0457) Prec@1 94.000 (92.163) Prec@5 100.000 (99.694) +2022-11-14 14:21:20,205 Epoch: [184][490/500] Time 0.051 (0.045) Data 0.002 (0.002) Loss 0.0674 (0.0462) Prec@1 88.000 (92.080) Prec@5 99.000 (99.680) +2022-11-14 14:21:20,652 Epoch: [184][499/500] Time 0.050 (0.045) Data 0.002 (0.002) Loss 0.0233 (0.0457) Prec@1 96.000 (92.157) Prec@5 100.000 (99.686) +2022-11-14 14:21:20,954 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0644 (0.0644) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:21:20,964 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0848 (0.0746) Prec@1 86.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 14:21:20,977 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0738 (0.0743) Prec@1 86.000 (86.333) Prec@5 99.000 (99.333) +2022-11-14 14:21:20,989 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0722) Prec@1 89.000 (87.000) Prec@5 98.000 (99.000) +2022-11-14 14:21:21,001 Test: [4/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0906 (0.0759) Prec@1 85.000 (86.600) Prec@5 99.000 (99.000) +2022-11-14 14:21:21,013 Test: [5/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0397 (0.0699) Prec@1 92.000 (87.500) Prec@5 100.000 (99.167) +2022-11-14 14:21:21,021 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0706) Prec@1 90.000 (87.857) Prec@5 99.000 (99.143) +2022-11-14 14:21:21,030 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1012 (0.0744) Prec@1 81.000 (87.000) Prec@5 100.000 (99.250) +2022-11-14 14:21:21,043 Test: [8/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0756) Prec@1 87.000 (87.000) Prec@5 99.000 (99.222) +2022-11-14 14:21:21,055 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0745) Prec@1 87.000 (87.000) Prec@5 99.000 (99.200) +2022-11-14 14:21:21,065 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0738) Prec@1 88.000 (87.091) Prec@5 100.000 (99.273) +2022-11-14 14:21:21,075 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0788 (0.0742) Prec@1 87.000 (87.083) Prec@5 98.000 (99.167) +2022-11-14 14:21:21,088 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0572 (0.0729) Prec@1 91.000 (87.385) Prec@5 99.000 (99.154) +2022-11-14 14:21:21,099 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0727) Prec@1 88.000 (87.429) Prec@5 100.000 (99.214) +2022-11-14 14:21:21,109 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0736) Prec@1 84.000 (87.200) Prec@5 100.000 (99.267) +2022-11-14 14:21:21,119 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0741) Prec@1 87.000 (87.188) Prec@5 99.000 (99.250) +2022-11-14 14:21:21,129 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0734) Prec@1 87.000 (87.176) Prec@5 99.000 (99.235) +2022-11-14 14:21:21,139 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0743) Prec@1 85.000 (87.056) Prec@5 99.000 (99.222) +2022-11-14 14:21:21,149 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1059 (0.0759) Prec@1 83.000 (86.842) Prec@5 97.000 (99.105) +2022-11-14 14:21:21,159 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0773) Prec@1 83.000 (86.650) Prec@5 99.000 (99.100) +2022-11-14 14:21:21,169 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0775) Prec@1 87.000 (86.667) Prec@5 100.000 (99.143) +2022-11-14 14:21:21,179 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0776) Prec@1 85.000 (86.591) Prec@5 100.000 (99.182) +2022-11-14 14:21:21,188 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0786) Prec@1 85.000 (86.522) Prec@5 99.000 (99.174) +2022-11-14 14:21:21,198 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0780) Prec@1 89.000 (86.625) Prec@5 100.000 (99.208) +2022-11-14 14:21:21,208 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0784) Prec@1 85.000 (86.560) Prec@5 100.000 (99.240) +2022-11-14 14:21:21,220 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0785) Prec@1 86.000 (86.538) Prec@5 99.000 (99.231) +2022-11-14 14:21:21,230 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0775) Prec@1 92.000 (86.741) Prec@5 100.000 (99.259) +2022-11-14 14:21:21,242 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0774) Prec@1 86.000 (86.714) Prec@5 99.000 (99.250) +2022-11-14 14:21:21,254 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0771) Prec@1 88.000 (86.759) Prec@5 99.000 (99.241) +2022-11-14 14:21:21,263 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0765) Prec@1 92.000 (86.933) Prec@5 100.000 (99.267) +2022-11-14 14:21:21,274 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0766) Prec@1 86.000 (86.903) Prec@5 100.000 (99.290) +2022-11-14 14:21:21,284 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0763) Prec@1 88.000 (86.938) Prec@5 99.000 (99.281) +2022-11-14 14:21:21,296 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0768) Prec@1 84.000 (86.848) Prec@5 99.000 (99.273) +2022-11-14 14:21:21,307 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0774) Prec@1 83.000 (86.735) Prec@5 96.000 (99.176) +2022-11-14 14:21:21,319 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0770) Prec@1 88.000 (86.771) Prec@5 98.000 (99.143) +2022-11-14 14:21:21,330 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0770) Prec@1 87.000 (86.778) Prec@5 99.000 (99.139) +2022-11-14 14:21:21,340 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0775) Prec@1 84.000 (86.703) Prec@5 98.000 (99.108) +2022-11-14 14:21:21,352 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0783) Prec@1 82.000 (86.579) Prec@5 98.000 (99.079) +2022-11-14 14:21:21,363 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0775) Prec@1 95.000 (86.795) Prec@5 100.000 (99.103) +2022-11-14 14:21:21,374 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0777) Prec@1 84.000 (86.725) Prec@5 99.000 (99.100) +2022-11-14 14:21:21,386 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0782) Prec@1 84.000 (86.659) Prec@5 98.000 (99.073) +2022-11-14 14:21:21,397 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0781) Prec@1 87.000 (86.667) Prec@5 99.000 (99.071) +2022-11-14 14:21:21,409 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0436 (0.0773) Prec@1 94.000 (86.837) Prec@5 100.000 (99.093) +2022-11-14 14:21:21,421 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0778) Prec@1 84.000 (86.773) Prec@5 99.000 (99.091) +2022-11-14 14:21:21,434 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0775) Prec@1 88.000 (86.800) Prec@5 100.000 (99.111) +2022-11-14 14:21:21,445 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1146 (0.0783) Prec@1 83.000 (86.717) Prec@5 99.000 (99.109) +2022-11-14 14:21:21,457 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0783) Prec@1 86.000 (86.702) Prec@5 100.000 (99.128) +2022-11-14 14:21:21,469 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0790) Prec@1 80.000 (86.562) Prec@5 100.000 (99.146) +2022-11-14 14:21:21,479 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0784) Prec@1 91.000 (86.653) Prec@5 99.000 (99.143) +2022-11-14 14:21:21,490 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1050 (0.0790) Prec@1 82.000 (86.560) Prec@5 100.000 (99.160) +2022-11-14 14:21:21,500 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0784) Prec@1 90.000 (86.627) Prec@5 100.000 (99.176) +2022-11-14 14:21:21,512 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0788) Prec@1 84.000 (86.577) Prec@5 99.000 (99.173) +2022-11-14 14:21:21,523 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0791) Prec@1 85.000 (86.547) Prec@5 100.000 (99.189) +2022-11-14 14:21:21,534 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0790) Prec@1 87.000 (86.556) Prec@5 100.000 (99.204) +2022-11-14 14:21:21,546 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0792) Prec@1 86.000 (86.545) Prec@5 100.000 (99.218) +2022-11-14 14:21:21,556 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0790) Prec@1 90.000 (86.607) Prec@5 99.000 (99.214) +2022-11-14 14:21:21,568 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0791) Prec@1 88.000 (86.632) Prec@5 100.000 (99.228) +2022-11-14 14:21:21,580 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0788) Prec@1 91.000 (86.707) Prec@5 99.000 (99.224) +2022-11-14 14:21:21,591 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0792) Prec@1 84.000 (86.661) Prec@5 99.000 (99.220) +2022-11-14 14:21:21,603 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0790) Prec@1 89.000 (86.700) Prec@5 100.000 (99.233) +2022-11-14 14:21:21,614 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0788) Prec@1 91.000 (86.770) Prec@5 100.000 (99.246) +2022-11-14 14:21:21,624 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0787) Prec@1 86.000 (86.758) Prec@5 99.000 (99.242) +2022-11-14 14:21:21,635 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0786) Prec@1 89.000 (86.794) Prec@5 99.000 (99.238) +2022-11-14 14:21:21,645 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0781) Prec@1 92.000 (86.875) Prec@5 100.000 (99.250) +2022-11-14 14:21:21,658 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0784) Prec@1 84.000 (86.831) Prec@5 97.000 (99.215) +2022-11-14 14:21:21,669 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0785) Prec@1 86.000 (86.818) Prec@5 99.000 (99.212) +2022-11-14 14:21:21,680 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0782) Prec@1 92.000 (86.896) Prec@5 100.000 (99.224) +2022-11-14 14:21:21,692 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0783) Prec@1 88.000 (86.912) Prec@5 99.000 (99.221) +2022-11-14 14:21:21,706 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0780) Prec@1 90.000 (86.957) Prec@5 99.000 (99.217) +2022-11-14 14:21:21,717 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0782) Prec@1 84.000 (86.914) Prec@5 95.000 (99.157) +2022-11-14 14:21:21,728 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0782) Prec@1 88.000 (86.930) Prec@5 100.000 (99.169) +2022-11-14 14:21:21,740 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0783) Prec@1 87.000 (86.931) Prec@5 99.000 (99.167) +2022-11-14 14:21:21,753 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0781) Prec@1 89.000 (86.959) Prec@5 99.000 (99.164) +2022-11-14 14:21:21,762 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0778) Prec@1 90.000 (87.000) Prec@5 100.000 (99.176) +2022-11-14 14:21:21,772 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1191 (0.0784) Prec@1 82.000 (86.933) Prec@5 97.000 (99.147) +2022-11-14 14:21:21,784 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0782) Prec@1 90.000 (86.974) Prec@5 100.000 (99.158) +2022-11-14 14:21:21,796 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0781) Prec@1 88.000 (86.987) Prec@5 98.000 (99.143) +2022-11-14 14:21:21,807 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.0786) Prec@1 79.000 (86.885) Prec@5 96.000 (99.103) +2022-11-14 14:21:21,819 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0787) Prec@1 87.000 (86.886) Prec@5 99.000 (99.101) +2022-11-14 14:21:21,832 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0788) Prec@1 81.000 (86.812) Prec@5 100.000 (99.112) +2022-11-14 14:21:21,844 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0789) Prec@1 85.000 (86.790) Prec@5 98.000 (99.099) +2022-11-14 14:21:21,855 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0790) Prec@1 83.000 (86.744) Prec@5 100.000 (99.110) +2022-11-14 14:21:21,867 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0790) Prec@1 87.000 (86.747) Prec@5 100.000 (99.120) +2022-11-14 14:21:21,878 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0789) Prec@1 88.000 (86.762) Prec@5 99.000 (99.119) +2022-11-14 14:21:21,888 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0791) Prec@1 85.000 (86.741) Prec@5 99.000 (99.118) +2022-11-14 14:21:21,900 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0792) Prec@1 85.000 (86.721) Prec@5 100.000 (99.128) +2022-11-14 14:21:21,910 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0794) Prec@1 83.000 (86.678) Prec@5 99.000 (99.126) +2022-11-14 14:21:21,922 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0794) Prec@1 86.000 (86.670) Prec@5 99.000 (99.125) +2022-11-14 14:21:21,932 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0794) Prec@1 88.000 (86.685) Prec@5 100.000 (99.135) +2022-11-14 14:21:21,943 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0795) Prec@1 85.000 (86.667) Prec@5 100.000 (99.144) +2022-11-14 14:21:21,953 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0793) Prec@1 91.000 (86.714) Prec@5 100.000 (99.154) +2022-11-14 14:21:21,965 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0790) Prec@1 90.000 (86.750) Prec@5 100.000 (99.163) +2022-11-14 14:21:21,976 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0792) Prec@1 84.000 (86.720) Prec@5 99.000 (99.161) +2022-11-14 14:21:21,987 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0792) Prec@1 86.000 (86.713) Prec@5 98.000 (99.149) +2022-11-14 14:21:22,000 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0792) Prec@1 86.000 (86.705) Prec@5 100.000 (99.158) +2022-11-14 14:21:22,012 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0788) Prec@1 92.000 (86.760) Prec@5 100.000 (99.167) +2022-11-14 14:21:22,023 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0786) Prec@1 87.000 (86.763) Prec@5 99.000 (99.165) +2022-11-14 14:21:22,034 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0789) Prec@1 84.000 (86.735) Prec@5 99.000 (99.163) +2022-11-14 14:21:22,047 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0791) Prec@1 84.000 (86.707) Prec@5 99.000 (99.162) +2022-11-14 14:21:22,060 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0789) Prec@1 91.000 (86.750) Prec@5 100.000 (99.170) +2022-11-14 14:21:22,119 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:21:22,472 Epoch: [185][0/500] Time 0.028 (0.028) Data 0.257 (0.257) Loss 0.0461 (0.0461) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:21:22,682 Epoch: [185][10/500] Time 0.017 (0.019) Data 0.002 (0.025) Loss 0.0425 (0.0443) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:21:22,884 Epoch: [185][20/500] Time 0.015 (0.019) Data 0.002 (0.014) Loss 0.0494 (0.0460) Prec@1 93.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:21:23,177 Epoch: [185][30/500] Time 0.027 (0.021) Data 0.002 (0.010) Loss 0.0227 (0.0402) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:21:23,531 Epoch: [185][40/500] Time 0.036 (0.023) Data 0.002 (0.008) Loss 0.0327 (0.0387) Prec@1 94.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 14:21:23,878 Epoch: [185][50/500] Time 0.035 (0.025) Data 0.002 (0.007) Loss 0.0247 (0.0363) Prec@1 98.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:21:24,221 Epoch: [185][60/500] Time 0.032 (0.026) Data 0.002 (0.006) Loss 0.0597 (0.0397) Prec@1 91.000 (93.857) Prec@5 100.000 (100.000) +2022-11-14 14:21:24,570 Epoch: [185][70/500] Time 0.032 (0.026) Data 0.002 (0.005) Loss 0.0845 (0.0453) Prec@1 85.000 (92.750) Prec@5 100.000 (100.000) +2022-11-14 14:21:24,926 Epoch: [185][80/500] Time 0.038 (0.027) Data 0.002 (0.005) Loss 0.0416 (0.0449) Prec@1 93.000 (92.778) Prec@5 100.000 (100.000) +2022-11-14 14:21:25,268 Epoch: [185][90/500] Time 0.031 (0.027) Data 0.002 (0.005) Loss 0.0496 (0.0453) Prec@1 91.000 (92.600) Prec@5 100.000 (100.000) +2022-11-14 14:21:25,653 Epoch: [185][100/500] Time 0.038 (0.028) Data 0.003 (0.004) Loss 0.0685 (0.0475) Prec@1 89.000 (92.273) Prec@5 100.000 (100.000) +2022-11-14 14:21:25,987 Epoch: [185][110/500] Time 0.033 (0.028) Data 0.002 (0.004) Loss 0.0315 (0.0461) Prec@1 95.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:21:26,372 Epoch: [185][120/500] Time 0.029 (0.029) Data 0.002 (0.004) Loss 0.0590 (0.0471) Prec@1 88.000 (92.154) Prec@5 99.000 (99.923) +2022-11-14 14:21:26,765 Epoch: [185][130/500] Time 0.038 (0.029) Data 0.002 (0.004) Loss 0.0535 (0.0476) Prec@1 92.000 (92.143) Prec@5 100.000 (99.929) +2022-11-14 14:21:27,171 Epoch: [185][140/500] Time 0.045 (0.030) Data 0.002 (0.004) Loss 0.0542 (0.0480) Prec@1 91.000 (92.067) Prec@5 100.000 (99.933) +2022-11-14 14:21:27,557 Epoch: [185][150/500] Time 0.040 (0.030) Data 0.002 (0.004) Loss 0.0692 (0.0493) Prec@1 86.000 (91.688) Prec@5 100.000 (99.938) +2022-11-14 14:21:27,964 Epoch: [185][160/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0539 (0.0496) Prec@1 91.000 (91.647) Prec@5 100.000 (99.941) +2022-11-14 14:21:28,350 Epoch: [185][170/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0482 (0.0495) Prec@1 92.000 (91.667) Prec@5 100.000 (99.944) +2022-11-14 14:21:28,689 Epoch: [185][180/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0724 (0.0507) Prec@1 88.000 (91.474) Prec@5 100.000 (99.947) +2022-11-14 14:21:29,035 Epoch: [185][190/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0323 (0.0498) Prec@1 95.000 (91.650) Prec@5 99.000 (99.900) +2022-11-14 14:21:29,399 Epoch: [185][200/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0346 (0.0491) Prec@1 94.000 (91.762) Prec@5 100.000 (99.905) +2022-11-14 14:21:29,755 Epoch: [185][210/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0336 (0.0484) Prec@1 95.000 (91.909) Prec@5 99.000 (99.864) +2022-11-14 14:21:30,138 Epoch: [185][220/500] Time 0.028 (0.031) Data 0.002 (0.003) Loss 0.0545 (0.0486) Prec@1 90.000 (91.826) Prec@5 100.000 (99.870) +2022-11-14 14:21:30,494 Epoch: [185][230/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0358 (0.0481) Prec@1 93.000 (91.875) Prec@5 100.000 (99.875) +2022-11-14 14:21:30,842 Epoch: [185][240/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0408 (0.0478) Prec@1 95.000 (92.000) Prec@5 99.000 (99.840) +2022-11-14 14:21:31,210 Epoch: [185][250/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0666 (0.0485) Prec@1 88.000 (91.846) Prec@5 100.000 (99.846) +2022-11-14 14:21:31,566 Epoch: [185][260/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0377 (0.0481) Prec@1 91.000 (91.815) Prec@5 100.000 (99.852) +2022-11-14 14:21:31,921 Epoch: [185][270/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0316 (0.0475) Prec@1 97.000 (92.000) Prec@5 99.000 (99.821) +2022-11-14 14:21:32,278 Epoch: [185][280/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0473 (0.0475) Prec@1 92.000 (92.000) Prec@5 100.000 (99.828) +2022-11-14 14:21:32,630 Epoch: [185][290/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0583 (0.0479) Prec@1 87.000 (91.833) Prec@5 100.000 (99.833) +2022-11-14 14:21:33,025 Epoch: [185][300/500] Time 0.047 (0.031) Data 0.002 (0.003) Loss 0.0343 (0.0475) Prec@1 93.000 (91.871) Prec@5 100.000 (99.839) +2022-11-14 14:21:33,378 Epoch: [185][310/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0598 (0.0478) Prec@1 90.000 (91.812) Prec@5 100.000 (99.844) +2022-11-14 14:21:33,737 Epoch: [185][320/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0642 (0.0483) Prec@1 85.000 (91.606) Prec@5 100.000 (99.848) +2022-11-14 14:21:34,103 Epoch: [185][330/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0536 (0.0485) Prec@1 90.000 (91.559) Prec@5 100.000 (99.853) +2022-11-14 14:21:34,468 Epoch: [185][340/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0610 (0.0489) Prec@1 91.000 (91.543) Prec@5 100.000 (99.857) +2022-11-14 14:21:34,815 Epoch: [185][350/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0337 (0.0484) Prec@1 94.000 (91.611) Prec@5 100.000 (99.861) +2022-11-14 14:21:35,170 Epoch: [185][360/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0438 (0.0483) Prec@1 93.000 (91.649) Prec@5 100.000 (99.865) +2022-11-14 14:21:35,553 Epoch: [185][370/500] Time 0.044 (0.031) Data 0.001 (0.003) Loss 0.0760 (0.0490) Prec@1 88.000 (91.553) Prec@5 97.000 (99.789) +2022-11-14 14:21:36,122 Epoch: [185][380/500] Time 0.055 (0.032) Data 0.002 (0.003) Loss 0.0506 (0.0491) Prec@1 92.000 (91.564) Prec@5 100.000 (99.795) +2022-11-14 14:21:36,594 Epoch: [185][390/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0459 (0.0490) Prec@1 91.000 (91.550) Prec@5 100.000 (99.800) +2022-11-14 14:21:37,086 Epoch: [185][400/500] Time 0.057 (0.032) Data 0.002 (0.003) Loss 0.0554 (0.0492) Prec@1 93.000 (91.585) Prec@5 99.000 (99.780) +2022-11-14 14:21:37,558 Epoch: [185][410/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0288 (0.0487) Prec@1 96.000 (91.690) Prec@5 100.000 (99.786) +2022-11-14 14:21:38,028 Epoch: [185][420/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0222 (0.0481) Prec@1 97.000 (91.814) Prec@5 100.000 (99.791) +2022-11-14 14:21:38,532 Epoch: [185][430/500] Time 0.045 (0.033) Data 0.001 (0.003) Loss 0.0597 (0.0483) Prec@1 90.000 (91.773) Prec@5 100.000 (99.795) +2022-11-14 14:21:39,036 Epoch: [185][440/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0379 (0.0481) Prec@1 93.000 (91.800) Prec@5 100.000 (99.800) +2022-11-14 14:21:39,525 Epoch: [185][450/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0197 (0.0475) Prec@1 98.000 (91.935) Prec@5 100.000 (99.804) +2022-11-14 14:21:40,002 Epoch: [185][460/500] Time 0.046 (0.034) Data 0.001 (0.002) Loss 0.0442 (0.0474) Prec@1 93.000 (91.957) Prec@5 99.000 (99.787) +2022-11-14 14:21:40,478 Epoch: [185][470/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0423 (0.0473) Prec@1 93.000 (91.979) Prec@5 100.000 (99.792) +2022-11-14 14:21:41,084 Epoch: [185][480/500] Time 0.049 (0.034) Data 0.002 (0.002) Loss 0.0850 (0.0481) Prec@1 88.000 (91.898) Prec@5 97.000 (99.735) +2022-11-14 14:21:41,643 Epoch: [185][490/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0286 (0.0477) Prec@1 97.000 (92.000) Prec@5 100.000 (99.740) +2022-11-14 14:21:42,076 Epoch: [185][499/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0455 (0.0476) Prec@1 92.000 (92.000) Prec@5 100.000 (99.745) +2022-11-14 14:21:42,372 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0639 (0.0639) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:21:42,381 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0638) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:21:42,392 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0632) Prec@1 88.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:21:42,405 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0967 (0.0716) Prec@1 86.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:21:42,414 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0698) Prec@1 90.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 14:21:42,422 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0303 (0.0632) Prec@1 95.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 14:21:42,430 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0627) Prec@1 90.000 (89.571) Prec@5 99.000 (99.571) +2022-11-14 14:21:42,441 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0649) Prec@1 87.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 14:21:42,449 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0687) Prec@1 84.000 (88.667) Prec@5 99.000 (99.556) +2022-11-14 14:21:42,458 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0695) Prec@1 84.000 (88.200) Prec@5 99.000 (99.500) +2022-11-14 14:21:42,469 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0683) Prec@1 88.000 (88.182) Prec@5 100.000 (99.545) +2022-11-14 14:21:42,477 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0718) Prec@1 82.000 (87.667) Prec@5 100.000 (99.583) +2022-11-14 14:21:42,487 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0701) Prec@1 93.000 (88.077) Prec@5 100.000 (99.615) +2022-11-14 14:21:42,499 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0710) Prec@1 84.000 (87.786) Prec@5 100.000 (99.643) +2022-11-14 14:21:42,510 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0700) Prec@1 90.000 (87.933) Prec@5 99.000 (99.600) +2022-11-14 14:21:42,519 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0716) Prec@1 85.000 (87.750) Prec@5 100.000 (99.625) +2022-11-14 14:21:42,528 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0709) Prec@1 91.000 (87.941) Prec@5 99.000 (99.588) +2022-11-14 14:21:42,539 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0729) Prec@1 82.000 (87.611) Prec@5 100.000 (99.611) +2022-11-14 14:21:42,549 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0740) Prec@1 81.000 (87.263) Prec@5 99.000 (99.579) +2022-11-14 14:21:42,560 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0743) Prec@1 87.000 (87.250) Prec@5 99.000 (99.550) +2022-11-14 14:21:42,570 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0748) Prec@1 85.000 (87.143) Prec@5 99.000 (99.524) +2022-11-14 14:21:42,581 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0754) Prec@1 87.000 (87.136) Prec@5 100.000 (99.545) +2022-11-14 14:21:42,591 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0771) Prec@1 84.000 (87.000) Prec@5 99.000 (99.522) +2022-11-14 14:21:42,602 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0767) Prec@1 86.000 (86.958) Prec@5 98.000 (99.458) +2022-11-14 14:21:42,612 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0772) Prec@1 86.000 (86.920) Prec@5 99.000 (99.440) +2022-11-14 14:21:42,624 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0775) Prec@1 85.000 (86.846) Prec@5 97.000 (99.346) +2022-11-14 14:21:42,636 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0767) Prec@1 93.000 (87.074) Prec@5 100.000 (99.370) +2022-11-14 14:21:42,646 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0761) Prec@1 90.000 (87.179) Prec@5 99.000 (99.357) +2022-11-14 14:21:42,657 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0761) Prec@1 88.000 (87.207) Prec@5 98.000 (99.310) +2022-11-14 14:21:42,667 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0762) Prec@1 88.000 (87.233) Prec@5 100.000 (99.333) +2022-11-14 14:21:42,678 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0765) Prec@1 84.000 (87.129) Prec@5 100.000 (99.355) +2022-11-14 14:21:42,688 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0766) Prec@1 88.000 (87.156) Prec@5 99.000 (99.344) +2022-11-14 14:21:42,699 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0771) Prec@1 84.000 (87.061) Prec@5 100.000 (99.364) +2022-11-14 14:21:42,709 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0775) Prec@1 83.000 (86.941) Prec@5 100.000 (99.382) +2022-11-14 14:21:42,719 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0774) Prec@1 88.000 (86.971) Prec@5 99.000 (99.371) +2022-11-14 14:21:42,729 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0772) Prec@1 87.000 (86.972) Prec@5 100.000 (99.389) +2022-11-14 14:21:42,739 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0771) Prec@1 88.000 (87.000) Prec@5 99.000 (99.378) +2022-11-14 14:21:42,751 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0777) Prec@1 83.000 (86.895) Prec@5 100.000 (99.395) +2022-11-14 14:21:42,762 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0772) Prec@1 91.000 (87.000) Prec@5 99.000 (99.385) +2022-11-14 14:21:42,772 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0768) Prec@1 89.000 (87.050) Prec@5 98.000 (99.350) +2022-11-14 14:21:42,783 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0770) Prec@1 87.000 (87.049) Prec@5 96.000 (99.268) +2022-11-14 14:21:42,793 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0768) Prec@1 88.000 (87.071) Prec@5 99.000 (99.262) +2022-11-14 14:21:42,804 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0399 (0.0760) Prec@1 92.000 (87.186) Prec@5 100.000 (99.279) +2022-11-14 14:21:42,816 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0761) Prec@1 88.000 (87.205) Prec@5 98.000 (99.250) +2022-11-14 14:21:42,825 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0759) Prec@1 89.000 (87.244) Prec@5 99.000 (99.244) +2022-11-14 14:21:42,835 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0763) Prec@1 84.000 (87.174) Prec@5 99.000 (99.239) +2022-11-14 14:21:42,846 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0762) Prec@1 89.000 (87.213) Prec@5 99.000 (99.234) +2022-11-14 14:21:42,857 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0765) Prec@1 84.000 (87.146) Prec@5 97.000 (99.188) +2022-11-14 14:21:42,868 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0760) Prec@1 92.000 (87.245) Prec@5 100.000 (99.204) +2022-11-14 14:21:42,879 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0766) Prec@1 82.000 (87.140) Prec@5 99.000 (99.200) +2022-11-14 14:21:42,888 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0767) Prec@1 88.000 (87.157) Prec@5 100.000 (99.216) +2022-11-14 14:21:42,897 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0768) Prec@1 87.000 (87.154) Prec@5 99.000 (99.212) +2022-11-14 14:21:42,909 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0769) Prec@1 88.000 (87.170) Prec@5 98.000 (99.189) +2022-11-14 14:21:42,919 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0769) Prec@1 87.000 (87.167) Prec@5 99.000 (99.185) +2022-11-14 14:21:42,929 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0771) Prec@1 85.000 (87.127) Prec@5 99.000 (99.182) +2022-11-14 14:21:42,941 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0772) Prec@1 88.000 (87.143) Prec@5 99.000 (99.179) +2022-11-14 14:21:42,951 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0771) Prec@1 88.000 (87.158) Prec@5 100.000 (99.193) +2022-11-14 14:21:42,962 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0771) Prec@1 90.000 (87.207) Prec@5 98.000 (99.172) +2022-11-14 14:21:42,973 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0774) Prec@1 84.000 (87.153) Prec@5 99.000 (99.169) +2022-11-14 14:21:42,985 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0773) Prec@1 88.000 (87.167) Prec@5 100.000 (99.183) +2022-11-14 14:21:42,997 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0772) Prec@1 88.000 (87.180) Prec@5 100.000 (99.197) +2022-11-14 14:21:43,006 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0774) Prec@1 84.000 (87.129) Prec@5 99.000 (99.194) +2022-11-14 14:21:43,017 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0772) Prec@1 88.000 (87.143) Prec@5 100.000 (99.206) +2022-11-14 14:21:43,026 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0768) Prec@1 92.000 (87.219) Prec@5 100.000 (99.219) +2022-11-14 14:21:43,038 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0768) Prec@1 85.000 (87.185) Prec@5 100.000 (99.231) +2022-11-14 14:21:43,051 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0769) Prec@1 84.000 (87.136) Prec@5 100.000 (99.242) +2022-11-14 14:21:43,062 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0766) Prec@1 92.000 (87.209) Prec@5 100.000 (99.254) +2022-11-14 14:21:43,074 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0765) Prec@1 90.000 (87.250) Prec@5 100.000 (99.265) +2022-11-14 14:21:43,085 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0763) Prec@1 90.000 (87.290) Prec@5 99.000 (99.261) +2022-11-14 14:21:43,098 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0764) Prec@1 86.000 (87.271) Prec@5 99.000 (99.257) +2022-11-14 14:21:43,110 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0767) Prec@1 87.000 (87.268) Prec@5 97.000 (99.225) +2022-11-14 14:21:43,122 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0765) Prec@1 88.000 (87.278) Prec@5 99.000 (99.222) +2022-11-14 14:21:43,133 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0763) Prec@1 89.000 (87.301) Prec@5 100.000 (99.233) +2022-11-14 14:21:43,145 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0759) Prec@1 93.000 (87.378) Prec@5 100.000 (99.243) +2022-11-14 14:21:43,156 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0760) Prec@1 90.000 (87.413) Prec@5 99.000 (99.240) +2022-11-14 14:21:43,167 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0758) Prec@1 90.000 (87.447) Prec@5 99.000 (99.237) +2022-11-14 14:21:43,178 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0757) Prec@1 90.000 (87.481) Prec@5 99.000 (99.234) +2022-11-14 14:21:43,188 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0760) Prec@1 85.000 (87.449) Prec@5 98.000 (99.218) +2022-11-14 14:21:43,199 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0759) Prec@1 87.000 (87.443) Prec@5 100.000 (99.228) +2022-11-14 14:21:43,210 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0757) Prec@1 90.000 (87.475) Prec@5 100.000 (99.237) +2022-11-14 14:21:43,222 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0758) Prec@1 87.000 (87.469) Prec@5 100.000 (99.247) +2022-11-14 14:21:43,233 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0759) Prec@1 86.000 (87.451) Prec@5 99.000 (99.244) +2022-11-14 14:21:43,243 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0760) Prec@1 87.000 (87.446) Prec@5 100.000 (99.253) +2022-11-14 14:21:43,255 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0763) Prec@1 83.000 (87.393) Prec@5 98.000 (99.238) +2022-11-14 14:21:43,265 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0766) Prec@1 83.000 (87.341) Prec@5 99.000 (99.235) +2022-11-14 14:21:43,275 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0769) Prec@1 85.000 (87.314) Prec@5 99.000 (99.233) +2022-11-14 14:21:43,285 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0768) Prec@1 90.000 (87.345) Prec@5 100.000 (99.241) +2022-11-14 14:21:43,297 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0769) Prec@1 87.000 (87.341) Prec@5 100.000 (99.250) +2022-11-14 14:21:43,306 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0771) Prec@1 83.000 (87.292) Prec@5 99.000 (99.247) +2022-11-14 14:21:43,318 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0771) Prec@1 87.000 (87.289) Prec@5 100.000 (99.256) +2022-11-14 14:21:43,329 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0370 (0.0767) Prec@1 95.000 (87.374) Prec@5 100.000 (99.264) +2022-11-14 14:21:43,340 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0765) Prec@1 89.000 (87.391) Prec@5 100.000 (99.272) +2022-11-14 14:21:43,352 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0767) Prec@1 83.000 (87.344) Prec@5 99.000 (99.269) +2022-11-14 14:21:43,363 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0768) Prec@1 87.000 (87.340) Prec@5 99.000 (99.266) +2022-11-14 14:21:43,374 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0768) Prec@1 86.000 (87.326) Prec@5 98.000 (99.253) +2022-11-14 14:21:43,383 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0766) Prec@1 90.000 (87.354) Prec@5 99.000 (99.250) +2022-11-14 14:21:43,395 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0763) Prec@1 91.000 (87.392) Prec@5 98.000 (99.237) +2022-11-14 14:21:43,408 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0764) Prec@1 86.000 (87.378) Prec@5 100.000 (99.245) +2022-11-14 14:21:43,419 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0766) Prec@1 86.000 (87.364) Prec@5 100.000 (99.253) +2022-11-14 14:21:43,431 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0765) Prec@1 89.000 (87.380) Prec@5 100.000 (99.260) +2022-11-14 14:21:43,502 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:21:43,822 Epoch: [186][0/500] Time 0.033 (0.033) Data 0.228 (0.228) Loss 0.0453 (0.0453) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:21:44,071 Epoch: [186][10/500] Time 0.021 (0.023) Data 0.002 (0.022) Loss 0.0547 (0.0500) Prec@1 90.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 14:21:44,320 Epoch: [186][20/500] Time 0.025 (0.023) Data 0.002 (0.013) Loss 0.0392 (0.0464) Prec@1 93.000 (91.667) Prec@5 100.000 (99.333) +2022-11-14 14:21:44,746 Epoch: [186][30/500] Time 0.047 (0.027) Data 0.002 (0.009) Loss 0.0551 (0.0486) Prec@1 89.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 14:21:45,233 Epoch: [186][40/500] Time 0.052 (0.031) Data 0.002 (0.008) Loss 0.0458 (0.0480) Prec@1 92.000 (91.200) Prec@5 99.000 (99.400) +2022-11-14 14:21:45,745 Epoch: [186][50/500] Time 0.043 (0.034) Data 0.002 (0.006) Loss 0.0225 (0.0438) Prec@1 97.000 (92.167) Prec@5 100.000 (99.500) +2022-11-14 14:21:46,260 Epoch: [186][60/500] Time 0.059 (0.036) Data 0.002 (0.006) Loss 0.0455 (0.0440) Prec@1 94.000 (92.429) Prec@5 100.000 (99.571) +2022-11-14 14:21:46,798 Epoch: [186][70/500] Time 0.064 (0.037) Data 0.002 (0.005) Loss 0.0506 (0.0448) Prec@1 92.000 (92.375) Prec@5 100.000 (99.625) +2022-11-14 14:21:47,258 Epoch: [186][80/500] Time 0.043 (0.037) Data 0.002 (0.005) Loss 0.0603 (0.0466) Prec@1 89.000 (92.000) Prec@5 99.000 (99.556) +2022-11-14 14:21:47,735 Epoch: [186][90/500] Time 0.042 (0.038) Data 0.002 (0.005) Loss 0.0801 (0.0499) Prec@1 88.000 (91.600) Prec@5 100.000 (99.600) +2022-11-14 14:21:48,351 Epoch: [186][100/500] Time 0.029 (0.040) Data 0.002 (0.004) Loss 0.0255 (0.0477) Prec@1 97.000 (92.091) Prec@5 99.000 (99.545) +2022-11-14 14:21:48,923 Epoch: [186][110/500] Time 0.053 (0.041) Data 0.002 (0.004) Loss 0.0508 (0.0480) Prec@1 92.000 (92.083) Prec@5 100.000 (99.583) +2022-11-14 14:21:49,458 Epoch: [186][120/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0494 (0.0481) Prec@1 92.000 (92.077) Prec@5 99.000 (99.538) +2022-11-14 14:21:50,010 Epoch: [186][130/500] Time 0.045 (0.041) Data 0.002 (0.004) Loss 0.0300 (0.0468) Prec@1 96.000 (92.357) Prec@5 100.000 (99.571) +2022-11-14 14:21:50,518 Epoch: [186][140/500] Time 0.070 (0.041) Data 0.002 (0.004) Loss 0.0704 (0.0484) Prec@1 88.000 (92.067) Prec@5 100.000 (99.600) +2022-11-14 14:21:51,027 Epoch: [186][150/500] Time 0.075 (0.041) Data 0.002 (0.004) Loss 0.0305 (0.0472) Prec@1 96.000 (92.312) Prec@5 100.000 (99.625) +2022-11-14 14:21:51,546 Epoch: [186][160/500] Time 0.092 (0.042) Data 0.002 (0.003) Loss 0.0270 (0.0460) Prec@1 95.000 (92.471) Prec@5 100.000 (99.647) +2022-11-14 14:21:51,997 Epoch: [186][170/500] Time 0.046 (0.042) Data 0.002 (0.003) Loss 0.0474 (0.0461) Prec@1 91.000 (92.389) Prec@5 100.000 (99.667) +2022-11-14 14:21:52,526 Epoch: [186][180/500] Time 0.056 (0.042) Data 0.003 (0.003) Loss 0.0646 (0.0471) Prec@1 86.000 (92.053) Prec@5 100.000 (99.684) +2022-11-14 14:21:52,983 Epoch: [186][190/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0459 (0.0470) Prec@1 92.000 (92.050) Prec@5 100.000 (99.700) +2022-11-14 14:21:53,514 Epoch: [186][200/500] Time 0.031 (0.042) Data 0.002 (0.003) Loss 0.0465 (0.0470) Prec@1 93.000 (92.095) Prec@5 99.000 (99.667) +2022-11-14 14:21:54,020 Epoch: [186][210/500] Time 0.033 (0.042) Data 0.002 (0.003) Loss 0.0558 (0.0474) Prec@1 91.000 (92.045) Prec@5 100.000 (99.682) +2022-11-14 14:21:54,618 Epoch: [186][220/500] Time 0.027 (0.043) Data 0.002 (0.003) Loss 0.0365 (0.0469) Prec@1 93.000 (92.087) Prec@5 100.000 (99.696) +2022-11-14 14:21:55,124 Epoch: [186][230/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0394 (0.0466) Prec@1 95.000 (92.208) Prec@5 100.000 (99.708) +2022-11-14 14:21:55,630 Epoch: [186][240/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0430 (0.0465) Prec@1 91.000 (92.160) Prec@5 100.000 (99.720) +2022-11-14 14:21:56,150 Epoch: [186][250/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0233 (0.0456) Prec@1 97.000 (92.346) Prec@5 100.000 (99.731) +2022-11-14 14:21:56,654 Epoch: [186][260/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0500 (0.0457) Prec@1 93.000 (92.370) Prec@5 100.000 (99.741) +2022-11-14 14:21:57,158 Epoch: [186][270/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0413 (0.0456) Prec@1 94.000 (92.429) Prec@5 100.000 (99.750) +2022-11-14 14:21:57,656 Epoch: [186][280/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0500 (0.0457) Prec@1 92.000 (92.414) Prec@5 99.000 (99.724) +2022-11-14 14:21:58,170 Epoch: [186][290/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0354 (0.0454) Prec@1 94.000 (92.467) Prec@5 99.000 (99.700) +2022-11-14 14:21:58,674 Epoch: [186][300/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0420 (0.0453) Prec@1 93.000 (92.484) Prec@5 100.000 (99.710) +2022-11-14 14:21:59,195 Epoch: [186][310/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0300 (0.0448) Prec@1 96.000 (92.594) Prec@5 100.000 (99.719) +2022-11-14 14:21:59,702 Epoch: [186][320/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0377 (0.0446) Prec@1 93.000 (92.606) Prec@5 100.000 (99.727) +2022-11-14 14:22:00,211 Epoch: [186][330/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0329 (0.0443) Prec@1 96.000 (92.706) Prec@5 100.000 (99.735) +2022-11-14 14:22:00,706 Epoch: [186][340/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0532 (0.0445) Prec@1 89.000 (92.600) Prec@5 100.000 (99.743) +2022-11-14 14:22:01,222 Epoch: [186][350/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0580 (0.0449) Prec@1 90.000 (92.528) Prec@5 100.000 (99.750) +2022-11-14 14:22:01,730 Epoch: [186][360/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0466 (0.0449) Prec@1 90.000 (92.459) Prec@5 100.000 (99.757) +2022-11-14 14:22:02,234 Epoch: [186][370/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0255 (0.0444) Prec@1 95.000 (92.526) Prec@5 99.000 (99.737) +2022-11-14 14:22:02,744 Epoch: [186][380/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0470 (0.0445) Prec@1 93.000 (92.538) Prec@5 100.000 (99.744) +2022-11-14 14:22:03,256 Epoch: [186][390/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0596 (0.0449) Prec@1 92.000 (92.525) Prec@5 98.000 (99.700) +2022-11-14 14:22:03,765 Epoch: [186][400/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0536 (0.0451) Prec@1 92.000 (92.512) Prec@5 100.000 (99.707) +2022-11-14 14:22:04,272 Epoch: [186][410/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0528 (0.0453) Prec@1 88.000 (92.405) Prec@5 100.000 (99.714) +2022-11-14 14:22:04,774 Epoch: [186][420/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0493 (0.0454) Prec@1 91.000 (92.372) Prec@5 100.000 (99.721) +2022-11-14 14:22:05,274 Epoch: [186][430/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0399 (0.0452) Prec@1 94.000 (92.409) Prec@5 100.000 (99.727) +2022-11-14 14:22:05,787 Epoch: [186][440/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0444 (0.0452) Prec@1 89.000 (92.333) Prec@5 100.000 (99.733) +2022-11-14 14:22:06,287 Epoch: [186][450/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0261 (0.0448) Prec@1 95.000 (92.391) Prec@5 100.000 (99.739) +2022-11-14 14:22:06,819 Epoch: [186][460/500] Time 0.040 (0.044) Data 0.002 (0.002) Loss 0.0648 (0.0452) Prec@1 88.000 (92.298) Prec@5 100.000 (99.745) +2022-11-14 14:22:07,382 Epoch: [186][470/500] Time 0.047 (0.044) Data 0.002 (0.002) Loss 0.0434 (0.0452) Prec@1 91.000 (92.271) Prec@5 100.000 (99.750) +2022-11-14 14:22:07,913 Epoch: [186][480/500] Time 0.051 (0.045) Data 0.002 (0.002) Loss 0.0422 (0.0451) Prec@1 92.000 (92.265) Prec@5 99.000 (99.735) +2022-11-14 14:22:08,489 Epoch: [186][490/500] Time 0.049 (0.045) Data 0.002 (0.002) Loss 0.0518 (0.0453) Prec@1 90.000 (92.220) Prec@5 100.000 (99.740) +2022-11-14 14:22:08,941 Epoch: [186][499/500] Time 0.041 (0.045) Data 0.002 (0.002) Loss 0.0609 (0.0456) Prec@1 89.000 (92.157) Prec@5 100.000 (99.745) +2022-11-14 14:22:09,223 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0684 (0.0684) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:09,232 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0678) Prec@1 92.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:22:09,242 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0658) Prec@1 92.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 14:22:09,253 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0698) Prec@1 85.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:22:09,263 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0689) Prec@1 90.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 14:22:09,273 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0279 (0.0621) Prec@1 93.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 14:22:09,281 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0610) Prec@1 91.000 (90.000) Prec@5 99.000 (99.571) +2022-11-14 14:22:09,289 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0650) Prec@1 84.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 14:22:09,297 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0683) Prec@1 86.000 (88.889) Prec@5 99.000 (99.556) +2022-11-14 14:22:09,308 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0676) Prec@1 90.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:22:09,318 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0670) Prec@1 92.000 (89.273) Prec@5 100.000 (99.545) +2022-11-14 14:22:09,329 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0680) Prec@1 89.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 14:22:09,340 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0677) Prec@1 92.000 (89.462) Prec@5 99.000 (99.462) +2022-11-14 14:22:09,351 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0678) Prec@1 89.000 (89.429) Prec@5 99.000 (99.429) +2022-11-14 14:22:09,362 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0687) Prec@1 89.000 (89.400) Prec@5 99.000 (99.400) +2022-11-14 14:22:09,373 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0693) Prec@1 85.000 (89.125) Prec@5 100.000 (99.438) +2022-11-14 14:22:09,384 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0679) Prec@1 94.000 (89.412) Prec@5 99.000 (99.412) +2022-11-14 14:22:09,394 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1224 (0.0709) Prec@1 80.000 (88.889) Prec@5 99.000 (99.389) +2022-11-14 14:22:09,405 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0722) Prec@1 81.000 (88.474) Prec@5 97.000 (99.263) +2022-11-14 14:22:09,415 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0737) Prec@1 83.000 (88.200) Prec@5 97.000 (99.150) +2022-11-14 14:22:09,426 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0731) Prec@1 91.000 (88.333) Prec@5 100.000 (99.190) +2022-11-14 14:22:09,437 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0728) Prec@1 86.000 (88.227) Prec@5 100.000 (99.227) +2022-11-14 14:22:09,449 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0739) Prec@1 86.000 (88.130) Prec@5 97.000 (99.130) +2022-11-14 14:22:09,460 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0730) Prec@1 92.000 (88.292) Prec@5 100.000 (99.167) +2022-11-14 14:22:09,472 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0736) Prec@1 88.000 (88.280) Prec@5 100.000 (99.200) +2022-11-14 14:22:09,483 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0744) Prec@1 85.000 (88.154) Prec@5 98.000 (99.154) +2022-11-14 14:22:09,494 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0732) Prec@1 95.000 (88.407) Prec@5 100.000 (99.185) +2022-11-14 14:22:09,505 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0730) Prec@1 88.000 (88.393) Prec@5 100.000 (99.214) +2022-11-14 14:22:09,516 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0728) Prec@1 88.000 (88.379) Prec@5 100.000 (99.241) +2022-11-14 14:22:09,528 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0722) Prec@1 91.000 (88.467) Prec@5 100.000 (99.267) +2022-11-14 14:22:09,540 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0721) Prec@1 89.000 (88.484) Prec@5 100.000 (99.290) +2022-11-14 14:22:09,554 Test: [31/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0720) Prec@1 90.000 (88.531) Prec@5 99.000 (99.281) +2022-11-14 14:22:09,567 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0719) Prec@1 87.000 (88.485) Prec@5 100.000 (99.303) +2022-11-14 14:22:09,578 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0722) Prec@1 89.000 (88.500) Prec@5 99.000 (99.294) +2022-11-14 14:22:09,588 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0730) Prec@1 83.000 (88.343) Prec@5 98.000 (99.257) +2022-11-14 14:22:09,600 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0728) Prec@1 88.000 (88.333) Prec@5 100.000 (99.278) +2022-11-14 14:22:09,613 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0732) Prec@1 87.000 (88.297) Prec@5 99.000 (99.270) +2022-11-14 14:22:09,623 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0740) Prec@1 81.000 (88.105) Prec@5 99.000 (99.263) +2022-11-14 14:22:09,635 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0411 (0.0732) Prec@1 95.000 (88.282) Prec@5 99.000 (99.256) +2022-11-14 14:22:09,647 Test: [39/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0733) Prec@1 86.000 (88.225) Prec@5 100.000 (99.275) +2022-11-14 14:22:09,661 Test: [40/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.0738) Prec@1 86.000 (88.171) Prec@5 97.000 (99.220) +2022-11-14 14:22:09,674 Test: [41/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0738) Prec@1 89.000 (88.190) Prec@5 98.000 (99.190) +2022-11-14 14:22:09,689 Test: [42/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0732) Prec@1 93.000 (88.302) Prec@5 99.000 (99.186) +2022-11-14 14:22:09,703 Test: [43/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0732) Prec@1 88.000 (88.295) Prec@5 98.000 (99.159) +2022-11-14 14:22:09,719 Test: [44/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0731) Prec@1 88.000 (88.289) Prec@5 99.000 (99.156) +2022-11-14 14:22:09,730 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0735) Prec@1 86.000 (88.239) Prec@5 100.000 (99.174) +2022-11-14 14:22:09,742 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0729) Prec@1 92.000 (88.319) Prec@5 100.000 (99.191) +2022-11-14 14:22:09,754 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0731) Prec@1 87.000 (88.292) Prec@5 99.000 (99.188) +2022-11-14 14:22:09,766 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0731) Prec@1 87.000 (88.265) Prec@5 100.000 (99.204) +2022-11-14 14:22:09,777 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0734) Prec@1 84.000 (88.180) Prec@5 99.000 (99.200) +2022-11-14 14:22:09,788 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0734) Prec@1 87.000 (88.157) Prec@5 100.000 (99.216) +2022-11-14 14:22:09,798 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0737) Prec@1 85.000 (88.096) Prec@5 99.000 (99.212) +2022-11-14 14:22:09,809 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0735) Prec@1 88.000 (88.094) Prec@5 99.000 (99.208) +2022-11-14 14:22:09,819 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0735) Prec@1 86.000 (88.056) Prec@5 99.000 (99.204) +2022-11-14 14:22:09,830 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0737) Prec@1 87.000 (88.036) Prec@5 100.000 (99.218) +2022-11-14 14:22:09,840 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0738) Prec@1 87.000 (88.018) Prec@5 99.000 (99.214) +2022-11-14 14:22:09,851 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0737) Prec@1 88.000 (88.018) Prec@5 99.000 (99.211) +2022-11-14 14:22:09,861 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0736) Prec@1 89.000 (88.034) Prec@5 98.000 (99.190) +2022-11-14 14:22:09,873 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0739) Prec@1 84.000 (87.966) Prec@5 99.000 (99.186) +2022-11-14 14:22:09,885 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0738) Prec@1 89.000 (87.983) Prec@5 100.000 (99.200) +2022-11-14 14:22:09,895 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0741) Prec@1 87.000 (87.967) Prec@5 100.000 (99.213) +2022-11-14 14:22:09,906 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0744) Prec@1 85.000 (87.919) Prec@5 99.000 (99.210) +2022-11-14 14:22:09,917 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 88.000 (87.921) Prec@5 100.000 (99.222) +2022-11-14 14:22:09,927 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0741) Prec@1 93.000 (88.000) Prec@5 99.000 (99.219) +2022-11-14 14:22:09,938 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0745) Prec@1 84.000 (87.938) Prec@5 100.000 (99.231) +2022-11-14 14:22:09,948 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0745) Prec@1 90.000 (87.970) Prec@5 98.000 (99.212) +2022-11-14 14:22:09,958 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0741) Prec@1 92.000 (88.030) Prec@5 100.000 (99.224) +2022-11-14 14:22:09,969 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0742) Prec@1 88.000 (88.029) Prec@5 99.000 (99.221) +2022-11-14 14:22:09,979 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0740) Prec@1 90.000 (88.058) Prec@5 100.000 (99.232) +2022-11-14 14:22:09,990 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0743) Prec@1 83.000 (87.986) Prec@5 98.000 (99.214) +2022-11-14 14:22:10,000 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0746) Prec@1 85.000 (87.944) Prec@5 99.000 (99.211) +2022-11-14 14:22:10,011 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0745) Prec@1 89.000 (87.958) Prec@5 100.000 (99.222) +2022-11-14 14:22:10,021 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0743) Prec@1 89.000 (87.973) Prec@5 100.000 (99.233) +2022-11-14 14:22:10,032 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0742) Prec@1 91.000 (88.014) Prec@5 100.000 (99.243) +2022-11-14 14:22:10,046 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1040 (0.0746) Prec@1 83.000 (87.947) Prec@5 100.000 (99.253) +2022-11-14 14:22:10,057 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0744) Prec@1 92.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 14:22:10,068 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0742) Prec@1 89.000 (88.013) Prec@5 100.000 (99.260) +2022-11-14 14:22:10,079 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0743) Prec@1 87.000 (88.000) Prec@5 100.000 (99.269) +2022-11-14 14:22:10,091 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0741) Prec@1 91.000 (88.038) Prec@5 100.000 (99.278) +2022-11-14 14:22:10,104 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0742) Prec@1 86.000 (88.013) Prec@5 99.000 (99.275) +2022-11-14 14:22:10,116 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0743) Prec@1 86.000 (87.988) Prec@5 99.000 (99.272) +2022-11-14 14:22:10,128 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0744) Prec@1 86.000 (87.963) Prec@5 99.000 (99.268) +2022-11-14 14:22:10,139 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0744) Prec@1 87.000 (87.952) Prec@5 100.000 (99.277) +2022-11-14 14:22:10,150 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0741) Prec@1 92.000 (88.000) Prec@5 100.000 (99.286) +2022-11-14 14:22:10,161 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0741) Prec@1 88.000 (88.000) Prec@5 99.000 (99.282) +2022-11-14 14:22:10,173 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0745) Prec@1 82.000 (87.930) Prec@5 100.000 (99.291) +2022-11-14 14:22:10,185 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0745) Prec@1 89.000 (87.943) Prec@5 100.000 (99.299) +2022-11-14 14:22:10,198 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0745) Prec@1 89.000 (87.955) Prec@5 99.000 (99.295) +2022-11-14 14:22:10,208 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0745) Prec@1 86.000 (87.933) Prec@5 100.000 (99.303) +2022-11-14 14:22:10,219 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0746) Prec@1 88.000 (87.933) Prec@5 98.000 (99.289) +2022-11-14 14:22:10,229 Test: [90/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0744) Prec@1 90.000 (87.956) Prec@5 100.000 (99.297) +2022-11-14 14:22:10,240 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0742) Prec@1 92.000 (88.000) Prec@5 100.000 (99.304) +2022-11-14 14:22:10,250 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0745) Prec@1 82.000 (87.935) Prec@5 99.000 (99.301) +2022-11-14 14:22:10,261 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0746) Prec@1 85.000 (87.904) Prec@5 98.000 (99.287) +2022-11-14 14:22:10,271 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0747) Prec@1 86.000 (87.884) Prec@5 98.000 (99.274) +2022-11-14 14:22:10,285 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0459 (0.0744) Prec@1 92.000 (87.927) Prec@5 99.000 (99.271) +2022-11-14 14:22:10,296 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0437 (0.0741) Prec@1 94.000 (87.990) Prec@5 100.000 (99.278) +2022-11-14 14:22:10,306 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0743) Prec@1 88.000 (87.990) Prec@5 99.000 (99.276) +2022-11-14 14:22:10,317 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0746) Prec@1 84.000 (87.949) Prec@5 98.000 (99.263) +2022-11-14 14:22:10,329 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0747) Prec@1 86.000 (87.930) Prec@5 100.000 (99.270) +2022-11-14 14:22:10,391 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:22:10,745 Epoch: [187][0/500] Time 0.024 (0.024) Data 0.255 (0.255) Loss 0.0474 (0.0474) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:10,999 Epoch: [187][10/500] Time 0.026 (0.023) Data 0.002 (0.025) Loss 0.0324 (0.0399) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:22:11,281 Epoch: [187][20/500] Time 0.024 (0.024) Data 0.003 (0.014) Loss 0.0487 (0.0428) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:11,680 Epoch: [187][30/500] Time 0.039 (0.028) Data 0.002 (0.010) Loss 0.0584 (0.0467) Prec@1 91.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:22:12,027 Epoch: [187][40/500] Time 0.024 (0.029) Data 0.002 (0.008) Loss 0.0376 (0.0449) Prec@1 93.000 (92.600) Prec@5 100.000 (100.000) +2022-11-14 14:22:12,361 Epoch: [187][50/500] Time 0.042 (0.029) Data 0.002 (0.007) Loss 0.0571 (0.0469) Prec@1 90.000 (92.167) Prec@5 100.000 (100.000) +2022-11-14 14:22:12,775 Epoch: [187][60/500] Time 0.036 (0.030) Data 0.002 (0.006) Loss 0.0303 (0.0446) Prec@1 95.000 (92.571) Prec@5 98.000 (99.714) +2022-11-14 14:22:13,191 Epoch: [187][70/500] Time 0.039 (0.031) Data 0.002 (0.006) Loss 0.0446 (0.0446) Prec@1 92.000 (92.500) Prec@5 99.000 (99.625) +2022-11-14 14:22:13,608 Epoch: [187][80/500] Time 0.041 (0.032) Data 0.002 (0.005) Loss 0.0462 (0.0448) Prec@1 91.000 (92.333) Prec@5 99.000 (99.556) +2022-11-14 14:22:13,976 Epoch: [187][90/500] Time 0.027 (0.032) Data 0.002 (0.005) Loss 0.0332 (0.0436) Prec@1 94.000 (92.500) Prec@5 100.000 (99.600) +2022-11-14 14:22:14,375 Epoch: [187][100/500] Time 0.026 (0.032) Data 0.002 (0.005) Loss 0.0463 (0.0438) Prec@1 92.000 (92.455) Prec@5 100.000 (99.636) +2022-11-14 14:22:14,758 Epoch: [187][110/500] Time 0.039 (0.032) Data 0.003 (0.004) Loss 0.0198 (0.0418) Prec@1 97.000 (92.833) Prec@5 99.000 (99.583) +2022-11-14 14:22:15,174 Epoch: [187][120/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0649 (0.0436) Prec@1 88.000 (92.462) Prec@5 100.000 (99.615) +2022-11-14 14:22:15,670 Epoch: [187][130/500] Time 0.053 (0.034) Data 0.002 (0.004) Loss 0.0550 (0.0444) Prec@1 91.000 (92.357) Prec@5 100.000 (99.643) +2022-11-14 14:22:16,216 Epoch: [187][140/500] Time 0.072 (0.035) Data 0.002 (0.004) Loss 0.0382 (0.0440) Prec@1 94.000 (92.467) Prec@5 100.000 (99.667) +2022-11-14 14:22:16,823 Epoch: [187][150/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0565 (0.0448) Prec@1 89.000 (92.250) Prec@5 100.000 (99.688) +2022-11-14 14:22:17,313 Epoch: [187][160/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0363 (0.0443) Prec@1 92.000 (92.235) Prec@5 99.000 (99.647) +2022-11-14 14:22:18,069 Epoch: [187][170/500] Time 0.076 (0.038) Data 0.002 (0.004) Loss 0.0659 (0.0455) Prec@1 90.000 (92.111) Prec@5 99.000 (99.611) +2022-11-14 14:22:18,565 Epoch: [187][180/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0381 (0.0451) Prec@1 92.000 (92.105) Prec@5 99.000 (99.579) +2022-11-14 14:22:19,050 Epoch: [187][190/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0511 (0.0454) Prec@1 91.000 (92.050) Prec@5 100.000 (99.600) +2022-11-14 14:22:19,585 Epoch: [187][200/500] Time 0.064 (0.039) Data 0.002 (0.003) Loss 0.0751 (0.0468) Prec@1 88.000 (91.857) Prec@5 97.000 (99.476) +2022-11-14 14:22:20,097 Epoch: [187][210/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0301 (0.0461) Prec@1 95.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:22:20,577 Epoch: [187][220/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0432 (0.0459) Prec@1 92.000 (92.000) Prec@5 99.000 (99.478) +2022-11-14 14:22:21,065 Epoch: [187][230/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0449 (0.0459) Prec@1 93.000 (92.042) Prec@5 99.000 (99.458) +2022-11-14 14:22:21,622 Epoch: [187][240/500] Time 0.077 (0.040) Data 0.002 (0.003) Loss 0.0590 (0.0464) Prec@1 89.000 (91.920) Prec@5 100.000 (99.480) +2022-11-14 14:22:22,113 Epoch: [187][250/500] Time 0.055 (0.040) Data 0.002 (0.003) Loss 0.0521 (0.0466) Prec@1 92.000 (91.923) Prec@5 97.000 (99.385) +2022-11-14 14:22:22,592 Epoch: [187][260/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0492 (0.0467) Prec@1 92.000 (91.926) Prec@5 99.000 (99.370) +2022-11-14 14:22:23,088 Epoch: [187][270/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0328 (0.0462) Prec@1 95.000 (92.036) Prec@5 100.000 (99.393) +2022-11-14 14:22:23,617 Epoch: [187][280/500] Time 0.045 (0.041) Data 0.001 (0.003) Loss 0.0467 (0.0462) Prec@1 93.000 (92.069) Prec@5 99.000 (99.379) +2022-11-14 14:22:24,623 Epoch: [187][290/500] Time 0.079 (0.042) Data 0.002 (0.003) Loss 0.0408 (0.0461) Prec@1 94.000 (92.133) Prec@5 99.000 (99.367) +2022-11-14 14:22:25,295 Epoch: [187][300/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0401 (0.0459) Prec@1 94.000 (92.194) Prec@5 100.000 (99.387) +2022-11-14 14:22:25,776 Epoch: [187][310/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0704 (0.0466) Prec@1 89.000 (92.094) Prec@5 100.000 (99.406) +2022-11-14 14:22:26,266 Epoch: [187][320/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0373 (0.0464) Prec@1 93.000 (92.121) Prec@5 100.000 (99.424) +2022-11-14 14:22:26,761 Epoch: [187][330/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0351 (0.0460) Prec@1 94.000 (92.176) Prec@5 100.000 (99.441) +2022-11-14 14:22:27,324 Epoch: [187][340/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0422 (0.0459) Prec@1 92.000 (92.171) Prec@5 100.000 (99.457) +2022-11-14 14:22:27,819 Epoch: [187][350/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0376 (0.0457) Prec@1 93.000 (92.194) Prec@5 100.000 (99.472) +2022-11-14 14:22:28,306 Epoch: [187][360/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0558 (0.0460) Prec@1 89.000 (92.108) Prec@5 100.000 (99.486) +2022-11-14 14:22:28,784 Epoch: [187][370/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0497 (0.0461) Prec@1 93.000 (92.132) Prec@5 99.000 (99.474) +2022-11-14 14:22:29,265 Epoch: [187][380/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0314 (0.0457) Prec@1 95.000 (92.205) Prec@5 100.000 (99.487) +2022-11-14 14:22:29,738 Epoch: [187][390/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0429 (0.0456) Prec@1 93.000 (92.225) Prec@5 100.000 (99.500) +2022-11-14 14:22:30,219 Epoch: [187][400/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0371 (0.0454) Prec@1 95.000 (92.293) Prec@5 100.000 (99.512) +2022-11-14 14:22:30,692 Epoch: [187][410/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0428 (0.0453) Prec@1 92.000 (92.286) Prec@5 99.000 (99.500) +2022-11-14 14:22:31,249 Epoch: [187][420/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0427 (0.0453) Prec@1 93.000 (92.302) Prec@5 100.000 (99.512) +2022-11-14 14:22:31,722 Epoch: [187][430/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0423 (0.0452) Prec@1 92.000 (92.295) Prec@5 99.000 (99.500) +2022-11-14 14:22:32,210 Epoch: [187][440/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0658 (0.0457) Prec@1 89.000 (92.222) Prec@5 99.000 (99.489) +2022-11-14 14:22:32,762 Epoch: [187][450/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0523 (0.0458) Prec@1 92.000 (92.217) Prec@5 100.000 (99.500) +2022-11-14 14:22:33,265 Epoch: [187][460/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0277 (0.0454) Prec@1 95.000 (92.277) Prec@5 100.000 (99.511) +2022-11-14 14:22:33,778 Epoch: [187][470/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0162 (0.0448) Prec@1 99.000 (92.417) Prec@5 100.000 (99.521) +2022-11-14 14:22:34,337 Epoch: [187][480/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0461 (0.0448) Prec@1 91.000 (92.388) Prec@5 99.000 (99.510) +2022-11-14 14:22:34,819 Epoch: [187][490/500] Time 0.043 (0.044) Data 0.002 (0.002) Loss 0.0204 (0.0444) Prec@1 97.000 (92.480) Prec@5 100.000 (99.520) +2022-11-14 14:22:35,274 Epoch: [187][499/500] Time 0.044 (0.044) Data 0.002 (0.002) Loss 0.0467 (0.0444) Prec@1 93.000 (92.490) Prec@5 99.000 (99.510) +2022-11-14 14:22:35,576 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:35,585 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0775) Prec@1 88.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 14:22:35,597 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0742) Prec@1 89.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 14:22:35,610 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0771) Prec@1 84.000 (86.750) Prec@5 99.000 (99.500) +2022-11-14 14:22:35,620 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0730) Prec@1 91.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 14:22:35,629 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0693) Prec@1 93.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 14:22:35,639 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0699) Prec@1 87.000 (88.286) Prec@5 100.000 (99.714) +2022-11-14 14:22:35,650 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0717) Prec@1 85.000 (87.875) Prec@5 100.000 (99.750) +2022-11-14 14:22:35,660 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0733) Prec@1 85.000 (87.556) Prec@5 100.000 (99.778) +2022-11-14 14:22:35,669 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0744) Prec@1 84.000 (87.200) Prec@5 99.000 (99.700) +2022-11-14 14:22:35,679 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0727) Prec@1 91.000 (87.545) Prec@5 100.000 (99.727) +2022-11-14 14:22:35,689 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0735) Prec@1 85.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 14:22:35,701 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0719) Prec@1 89.000 (87.462) Prec@5 100.000 (99.692) +2022-11-14 14:22:35,711 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0720) Prec@1 86.000 (87.357) Prec@5 100.000 (99.714) +2022-11-14 14:22:35,721 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0724) Prec@1 85.000 (87.200) Prec@5 99.000 (99.667) +2022-11-14 14:22:35,732 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0727) Prec@1 87.000 (87.188) Prec@5 100.000 (99.688) +2022-11-14 14:22:35,741 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0720) Prec@1 89.000 (87.294) Prec@5 99.000 (99.647) +2022-11-14 14:22:35,752 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1294 (0.0752) Prec@1 78.000 (86.778) Prec@5 100.000 (99.667) +2022-11-14 14:22:35,761 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0751) Prec@1 88.000 (86.842) Prec@5 99.000 (99.632) +2022-11-14 14:22:35,771 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0763) Prec@1 83.000 (86.650) Prec@5 98.000 (99.550) +2022-11-14 14:22:35,782 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0766) Prec@1 86.000 (86.619) Prec@5 100.000 (99.571) +2022-11-14 14:22:35,793 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0779) Prec@1 86.000 (86.591) Prec@5 100.000 (99.591) +2022-11-14 14:22:35,803 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0788) Prec@1 86.000 (86.565) Prec@5 100.000 (99.609) +2022-11-14 14:22:35,814 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0785) Prec@1 87.000 (86.583) Prec@5 99.000 (99.583) +2022-11-14 14:22:35,826 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0784) Prec@1 89.000 (86.680) Prec@5 100.000 (99.600) +2022-11-14 14:22:35,837 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0784) Prec@1 89.000 (86.769) Prec@5 97.000 (99.500) +2022-11-14 14:22:35,847 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0773) Prec@1 94.000 (87.037) Prec@5 99.000 (99.481) +2022-11-14 14:22:35,857 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0772) Prec@1 88.000 (87.071) Prec@5 98.000 (99.429) +2022-11-14 14:22:35,867 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0771) Prec@1 87.000 (87.069) Prec@5 97.000 (99.345) +2022-11-14 14:22:35,878 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0769) Prec@1 88.000 (87.100) Prec@5 99.000 (99.333) +2022-11-14 14:22:35,888 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0768) Prec@1 86.000 (87.065) Prec@5 99.000 (99.323) +2022-11-14 14:22:35,899 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0761) Prec@1 90.000 (87.156) Prec@5 100.000 (99.344) +2022-11-14 14:22:35,909 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0766) Prec@1 83.000 (87.030) Prec@5 99.000 (99.333) +2022-11-14 14:22:35,920 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0771) Prec@1 85.000 (86.971) Prec@5 100.000 (99.353) +2022-11-14 14:22:35,929 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0773) Prec@1 86.000 (86.943) Prec@5 97.000 (99.286) +2022-11-14 14:22:35,939 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0771) Prec@1 88.000 (86.972) Prec@5 98.000 (99.250) +2022-11-14 14:22:35,951 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0775) Prec@1 84.000 (86.892) Prec@5 99.000 (99.243) +2022-11-14 14:22:35,961 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0781) Prec@1 84.000 (86.816) Prec@5 99.000 (99.237) +2022-11-14 14:22:35,972 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0773) Prec@1 94.000 (87.000) Prec@5 98.000 (99.205) +2022-11-14 14:22:35,982 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0774) Prec@1 85.000 (86.950) Prec@5 100.000 (99.225) +2022-11-14 14:22:35,992 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0781) Prec@1 82.000 (86.829) Prec@5 98.000 (99.195) +2022-11-14 14:22:36,003 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0780) Prec@1 89.000 (86.881) Prec@5 100.000 (99.214) +2022-11-14 14:22:36,013 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0404 (0.0771) Prec@1 93.000 (87.023) Prec@5 100.000 (99.233) +2022-11-14 14:22:36,023 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0772) Prec@1 87.000 (87.023) Prec@5 98.000 (99.205) +2022-11-14 14:22:36,034 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0766) Prec@1 92.000 (87.133) Prec@5 99.000 (99.200) +2022-11-14 14:22:36,045 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0773) Prec@1 82.000 (87.022) Prec@5 98.000 (99.174) +2022-11-14 14:22:36,055 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0774) Prec@1 85.000 (86.979) Prec@5 100.000 (99.191) +2022-11-14 14:22:36,065 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0779) Prec@1 82.000 (86.875) Prec@5 99.000 (99.188) +2022-11-14 14:22:36,075 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0386 (0.0771) Prec@1 91.000 (86.959) Prec@5 100.000 (99.204) +2022-11-14 14:22:36,084 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0775) Prec@1 83.000 (86.880) Prec@5 100.000 (99.220) +2022-11-14 14:22:36,094 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0774) Prec@1 88.000 (86.902) Prec@5 98.000 (99.196) +2022-11-14 14:22:36,104 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0774) Prec@1 88.000 (86.923) Prec@5 98.000 (99.173) +2022-11-14 14:22:36,116 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0771) Prec@1 88.000 (86.943) Prec@5 99.000 (99.170) +2022-11-14 14:22:36,125 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0774) Prec@1 86.000 (86.926) Prec@5 98.000 (99.148) +2022-11-14 14:22:36,136 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0776) Prec@1 87.000 (86.927) Prec@5 100.000 (99.164) +2022-11-14 14:22:36,146 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0772) Prec@1 90.000 (86.982) Prec@5 99.000 (99.161) +2022-11-14 14:22:36,157 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0769) Prec@1 90.000 (87.035) Prec@5 100.000 (99.175) +2022-11-14 14:22:36,168 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0767) Prec@1 92.000 (87.121) Prec@5 98.000 (99.155) +2022-11-14 14:22:36,179 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0773) Prec@1 85.000 (87.085) Prec@5 99.000 (99.153) +2022-11-14 14:22:36,190 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0774) Prec@1 85.000 (87.050) Prec@5 100.000 (99.167) +2022-11-14 14:22:36,201 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0776) Prec@1 88.000 (87.066) Prec@5 100.000 (99.180) +2022-11-14 14:22:36,212 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0776) Prec@1 83.000 (87.000) Prec@5 100.000 (99.194) +2022-11-14 14:22:36,222 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0773) Prec@1 90.000 (87.048) Prec@5 100.000 (99.206) +2022-11-14 14:22:36,232 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0768) Prec@1 93.000 (87.141) Prec@5 100.000 (99.219) +2022-11-14 14:22:36,242 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0770) Prec@1 84.000 (87.092) Prec@5 98.000 (99.200) +2022-11-14 14:22:36,253 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0772) Prec@1 85.000 (87.061) Prec@5 99.000 (99.197) +2022-11-14 14:22:36,263 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0769) Prec@1 91.000 (87.119) Prec@5 100.000 (99.209) +2022-11-14 14:22:36,274 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0770) Prec@1 85.000 (87.088) Prec@5 99.000 (99.206) +2022-11-14 14:22:36,284 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0769) Prec@1 86.000 (87.072) Prec@5 99.000 (99.203) +2022-11-14 14:22:36,294 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0770) Prec@1 87.000 (87.071) Prec@5 99.000 (99.200) +2022-11-14 14:22:36,303 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0772) Prec@1 87.000 (87.070) Prec@5 100.000 (99.211) +2022-11-14 14:22:36,313 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0771) Prec@1 88.000 (87.083) Prec@5 100.000 (99.222) +2022-11-14 14:22:36,324 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0768) Prec@1 92.000 (87.151) Prec@5 99.000 (99.219) +2022-11-14 14:22:36,334 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0767) Prec@1 89.000 (87.176) Prec@5 100.000 (99.230) +2022-11-14 14:22:36,345 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.0772) Prec@1 82.000 (87.107) Prec@5 99.000 (99.227) +2022-11-14 14:22:36,356 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0769) Prec@1 89.000 (87.132) Prec@5 99.000 (99.224) +2022-11-14 14:22:36,367 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0769) Prec@1 89.000 (87.156) Prec@5 99.000 (99.221) +2022-11-14 14:22:36,378 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0770) Prec@1 87.000 (87.154) Prec@5 96.000 (99.179) +2022-11-14 14:22:36,388 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0771) Prec@1 84.000 (87.114) Prec@5 100.000 (99.190) +2022-11-14 14:22:36,399 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0772) Prec@1 83.000 (87.062) Prec@5 100.000 (99.200) +2022-11-14 14:22:36,408 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0776) Prec@1 83.000 (87.012) Prec@5 97.000 (99.173) +2022-11-14 14:22:36,418 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0777) Prec@1 86.000 (87.000) Prec@5 99.000 (99.171) +2022-11-14 14:22:36,427 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0778) Prec@1 86.000 (86.988) Prec@5 98.000 (99.157) +2022-11-14 14:22:36,437 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0777) Prec@1 89.000 (87.012) Prec@5 99.000 (99.155) +2022-11-14 14:22:36,447 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0780) Prec@1 84.000 (86.976) Prec@5 99.000 (99.153) +2022-11-14 14:22:36,456 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0783) Prec@1 84.000 (86.942) Prec@5 100.000 (99.163) +2022-11-14 14:22:36,466 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0782) Prec@1 90.000 (86.977) Prec@5 100.000 (99.172) +2022-11-14 14:22:36,477 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0780) Prec@1 92.000 (87.034) Prec@5 99.000 (99.170) +2022-11-14 14:22:36,487 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0779) Prec@1 87.000 (87.034) Prec@5 100.000 (99.180) +2022-11-14 14:22:36,498 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0776) Prec@1 93.000 (87.100) Prec@5 100.000 (99.189) +2022-11-14 14:22:36,509 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0777) Prec@1 87.000 (87.099) Prec@5 100.000 (99.198) +2022-11-14 14:22:36,521 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0774) Prec@1 91.000 (87.141) Prec@5 100.000 (99.207) +2022-11-14 14:22:36,532 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0772) Prec@1 90.000 (87.172) Prec@5 100.000 (99.215) +2022-11-14 14:22:36,544 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0771) Prec@1 89.000 (87.191) Prec@5 99.000 (99.213) +2022-11-14 14:22:36,555 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0773) Prec@1 83.000 (87.147) Prec@5 99.000 (99.211) +2022-11-14 14:22:36,565 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0772) Prec@1 89.000 (87.167) Prec@5 98.000 (99.198) +2022-11-14 14:22:36,576 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0771) Prec@1 88.000 (87.175) Prec@5 99.000 (99.196) +2022-11-14 14:22:36,587 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0774) Prec@1 83.000 (87.133) Prec@5 98.000 (99.184) +2022-11-14 14:22:36,597 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0775) Prec@1 86.000 (87.121) Prec@5 100.000 (99.192) +2022-11-14 14:22:36,607 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0776) Prec@1 87.000 (87.120) Prec@5 100.000 (99.200) +2022-11-14 14:22:36,671 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:22:37,002 Epoch: [188][0/500] Time 0.026 (0.026) Data 0.240 (0.240) Loss 0.0384 (0.0384) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:37,228 Epoch: [188][10/500] Time 0.018 (0.021) Data 0.002 (0.024) Loss 0.0454 (0.0419) Prec@1 92.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:22:37,433 Epoch: [188][20/500] Time 0.017 (0.019) Data 0.002 (0.013) Loss 0.0380 (0.0406) Prec@1 92.000 (91.667) Prec@5 100.000 (100.000) +2022-11-14 14:22:37,756 Epoch: [188][30/500] Time 0.038 (0.022) Data 0.002 (0.009) Loss 0.0372 (0.0397) Prec@1 95.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:22:38,140 Epoch: [188][40/500] Time 0.037 (0.025) Data 0.002 (0.008) Loss 0.0259 (0.0370) Prec@1 96.000 (93.200) Prec@5 100.000 (100.000) +2022-11-14 14:22:38,506 Epoch: [188][50/500] Time 0.033 (0.026) Data 0.002 (0.007) Loss 0.0600 (0.0408) Prec@1 91.000 (92.833) Prec@5 100.000 (100.000) +2022-11-14 14:22:38,915 Epoch: [188][60/500] Time 0.028 (0.028) Data 0.002 (0.006) Loss 0.0545 (0.0428) Prec@1 92.000 (92.714) Prec@5 100.000 (100.000) +2022-11-14 14:22:39,280 Epoch: [188][70/500] Time 0.033 (0.029) Data 0.002 (0.005) Loss 0.0433 (0.0428) Prec@1 93.000 (92.750) Prec@5 100.000 (100.000) +2022-11-14 14:22:39,688 Epoch: [188][80/500] Time 0.026 (0.030) Data 0.002 (0.005) Loss 0.0484 (0.0434) Prec@1 92.000 (92.667) Prec@5 99.000 (99.889) +2022-11-14 14:22:40,067 Epoch: [188][90/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0269 (0.0418) Prec@1 94.000 (92.800) Prec@5 100.000 (99.900) +2022-11-14 14:22:40,447 Epoch: [188][100/500] Time 0.032 (0.030) Data 0.003 (0.004) Loss 0.0340 (0.0411) Prec@1 96.000 (93.091) Prec@5 100.000 (99.909) +2022-11-14 14:22:40,817 Epoch: [188][110/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0594 (0.0426) Prec@1 88.000 (92.667) Prec@5 100.000 (99.917) +2022-11-14 14:22:41,211 Epoch: [188][120/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0341 (0.0420) Prec@1 95.000 (92.846) Prec@5 100.000 (99.923) +2022-11-14 14:22:41,586 Epoch: [188][130/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0424 (0.0420) Prec@1 92.000 (92.786) Prec@5 100.000 (99.929) +2022-11-14 14:22:41,965 Epoch: [188][140/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0547 (0.0428) Prec@1 89.000 (92.533) Prec@5 99.000 (99.867) +2022-11-14 14:22:42,347 Epoch: [188][150/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0503 (0.0433) Prec@1 92.000 (92.500) Prec@5 99.000 (99.812) +2022-11-14 14:22:42,724 Epoch: [188][160/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0572 (0.0441) Prec@1 89.000 (92.294) Prec@5 100.000 (99.824) +2022-11-14 14:22:43,103 Epoch: [188][170/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0517 (0.0445) Prec@1 90.000 (92.167) Prec@5 100.000 (99.833) +2022-11-14 14:22:43,477 Epoch: [188][180/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0355 (0.0441) Prec@1 96.000 (92.368) Prec@5 99.000 (99.789) +2022-11-14 14:22:43,870 Epoch: [188][190/500] Time 0.040 (0.032) Data 0.003 (0.003) Loss 0.0320 (0.0435) Prec@1 95.000 (92.500) Prec@5 100.000 (99.800) +2022-11-14 14:22:44,275 Epoch: [188][200/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0631 (0.0444) Prec@1 89.000 (92.333) Prec@5 98.000 (99.714) +2022-11-14 14:22:44,644 Epoch: [188][210/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0433 (0.0443) Prec@1 92.000 (92.318) Prec@5 100.000 (99.727) +2022-11-14 14:22:45,071 Epoch: [188][220/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.0607 (0.0451) Prec@1 91.000 (92.261) Prec@5 100.000 (99.739) +2022-11-14 14:22:45,435 Epoch: [188][230/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0396 (0.0448) Prec@1 93.000 (92.292) Prec@5 100.000 (99.750) +2022-11-14 14:22:45,818 Epoch: [188][240/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0279 (0.0442) Prec@1 96.000 (92.440) Prec@5 100.000 (99.760) +2022-11-14 14:22:46,206 Epoch: [188][250/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0434 (0.0441) Prec@1 94.000 (92.500) Prec@5 99.000 (99.731) +2022-11-14 14:22:46,604 Epoch: [188][260/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0476 (0.0443) Prec@1 92.000 (92.481) Prec@5 100.000 (99.741) +2022-11-14 14:22:46,974 Epoch: [188][270/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0432 (0.0442) Prec@1 92.000 (92.464) Prec@5 99.000 (99.714) +2022-11-14 14:22:47,349 Epoch: [188][280/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0352 (0.0439) Prec@1 95.000 (92.552) Prec@5 100.000 (99.724) +2022-11-14 14:22:47,723 Epoch: [188][290/500] Time 0.037 (0.033) Data 0.001 (0.003) Loss 0.0383 (0.0437) Prec@1 93.000 (92.567) Prec@5 100.000 (99.733) +2022-11-14 14:22:48,107 Epoch: [188][300/500] Time 0.042 (0.033) Data 0.003 (0.003) Loss 0.0300 (0.0433) Prec@1 94.000 (92.613) Prec@5 100.000 (99.742) +2022-11-14 14:22:48,480 Epoch: [188][310/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0486 (0.0434) Prec@1 91.000 (92.562) Prec@5 100.000 (99.750) +2022-11-14 14:22:48,886 Epoch: [188][320/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0281 (0.0430) Prec@1 95.000 (92.636) Prec@5 100.000 (99.758) +2022-11-14 14:22:49,255 Epoch: [188][330/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0314 (0.0426) Prec@1 95.000 (92.706) Prec@5 100.000 (99.765) +2022-11-14 14:22:49,657 Epoch: [188][340/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0636 (0.0432) Prec@1 92.000 (92.686) Prec@5 99.000 (99.743) +2022-11-14 14:22:50,041 Epoch: [188][350/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0459 (0.0433) Prec@1 92.000 (92.667) Prec@5 100.000 (99.750) +2022-11-14 14:22:50,419 Epoch: [188][360/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0173 (0.0426) Prec@1 97.000 (92.784) Prec@5 100.000 (99.757) +2022-11-14 14:22:50,815 Epoch: [188][370/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0350 (0.0424) Prec@1 96.000 (92.868) Prec@5 99.000 (99.737) +2022-11-14 14:22:51,200 Epoch: [188][380/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0442 (0.0425) Prec@1 91.000 (92.821) Prec@5 100.000 (99.744) +2022-11-14 14:22:51,591 Epoch: [188][390/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0807 (0.0434) Prec@1 86.000 (92.650) Prec@5 100.000 (99.750) +2022-11-14 14:22:51,993 Epoch: [188][400/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0702 (0.0441) Prec@1 86.000 (92.488) Prec@5 100.000 (99.756) +2022-11-14 14:22:52,376 Epoch: [188][410/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0569 (0.0444) Prec@1 88.000 (92.381) Prec@5 99.000 (99.738) +2022-11-14 14:22:52,791 Epoch: [188][420/500] Time 0.048 (0.033) Data 0.002 (0.002) Loss 0.0470 (0.0444) Prec@1 90.000 (92.326) Prec@5 100.000 (99.744) +2022-11-14 14:22:53,169 Epoch: [188][430/500] Time 0.033 (0.033) Data 0.002 (0.002) Loss 0.0382 (0.0443) Prec@1 96.000 (92.409) Prec@5 99.000 (99.727) +2022-11-14 14:22:53,546 Epoch: [188][440/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0445 (0.0443) Prec@1 92.000 (92.400) Prec@5 100.000 (99.733) +2022-11-14 14:22:53,923 Epoch: [188][450/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0570 (0.0446) Prec@1 90.000 (92.348) Prec@5 100.000 (99.739) +2022-11-14 14:22:54,337 Epoch: [188][460/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0572 (0.0448) Prec@1 89.000 (92.277) Prec@5 100.000 (99.745) +2022-11-14 14:22:54,728 Epoch: [188][470/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0184 (0.0443) Prec@1 98.000 (92.396) Prec@5 100.000 (99.750) +2022-11-14 14:22:55,112 Epoch: [188][480/500] Time 0.040 (0.033) Data 0.002 (0.002) Loss 0.0637 (0.0447) Prec@1 91.000 (92.367) Prec@5 99.000 (99.735) +2022-11-14 14:22:55,492 Epoch: [188][490/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0368 (0.0445) Prec@1 92.000 (92.360) Prec@5 100.000 (99.740) +2022-11-14 14:22:55,835 Epoch: [188][499/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0400 (0.0444) Prec@1 92.000 (92.353) Prec@5 100.000 (99.745) +2022-11-14 14:22:56,131 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0672 (0.0672) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:22:56,140 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0670) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:22:56,150 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0707) Prec@1 87.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 14:22:56,164 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0776) Prec@1 80.000 (85.500) Prec@5 99.000 (99.500) +2022-11-14 14:22:56,173 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0773) Prec@1 87.000 (85.800) Prec@5 100.000 (99.600) +2022-11-14 14:22:56,183 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0357 (0.0704) Prec@1 95.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 14:22:56,191 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0689) Prec@1 90.000 (87.714) Prec@5 100.000 (99.714) +2022-11-14 14:22:56,205 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0698) Prec@1 85.000 (87.375) Prec@5 99.000 (99.625) +2022-11-14 14:22:56,215 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0710) Prec@1 89.000 (87.556) Prec@5 100.000 (99.667) +2022-11-14 14:22:56,228 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0704) Prec@1 88.000 (87.600) Prec@5 100.000 (99.700) +2022-11-14 14:22:56,242 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0694) Prec@1 88.000 (87.636) Prec@5 100.000 (99.727) +2022-11-14 14:22:56,257 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0699) Prec@1 89.000 (87.750) Prec@5 99.000 (99.667) +2022-11-14 14:22:56,271 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0424 (0.0678) Prec@1 93.000 (88.154) Prec@5 100.000 (99.692) +2022-11-14 14:22:56,285 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0678) Prec@1 89.000 (88.214) Prec@5 99.000 (99.643) +2022-11-14 14:22:56,298 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0685) Prec@1 87.000 (88.133) Prec@5 100.000 (99.667) +2022-11-14 14:22:56,312 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0706) Prec@1 83.000 (87.812) Prec@5 99.000 (99.625) +2022-11-14 14:22:56,327 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0700) Prec@1 91.000 (88.000) Prec@5 99.000 (99.588) +2022-11-14 14:22:56,341 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0719) Prec@1 83.000 (87.722) Prec@5 100.000 (99.611) +2022-11-14 14:22:56,354 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0724) Prec@1 86.000 (87.632) Prec@5 98.000 (99.526) +2022-11-14 14:22:56,368 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0741) Prec@1 81.000 (87.300) Prec@5 97.000 (99.400) +2022-11-14 14:22:56,383 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0753) Prec@1 83.000 (87.095) Prec@5 100.000 (99.429) +2022-11-14 14:22:56,396 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0761) Prec@1 83.000 (86.909) Prec@5 98.000 (99.364) +2022-11-14 14:22:56,410 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0769) Prec@1 86.000 (86.870) Prec@5 99.000 (99.348) +2022-11-14 14:22:56,424 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0760) Prec@1 90.000 (87.000) Prec@5 100.000 (99.375) +2022-11-14 14:22:56,438 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0768) Prec@1 86.000 (86.960) Prec@5 99.000 (99.360) +2022-11-14 14:22:56,452 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0780) Prec@1 83.000 (86.808) Prec@5 96.000 (99.231) +2022-11-14 14:22:56,466 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0773) Prec@1 92.000 (87.000) Prec@5 100.000 (99.259) +2022-11-14 14:22:56,480 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0767) Prec@1 90.000 (87.107) Prec@5 100.000 (99.286) +2022-11-14 14:22:56,494 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0770) Prec@1 85.000 (87.034) Prec@5 100.000 (99.310) +2022-11-14 14:22:56,507 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0763) Prec@1 90.000 (87.133) Prec@5 100.000 (99.333) +2022-11-14 14:22:56,522 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0764) Prec@1 86.000 (87.097) Prec@5 97.000 (99.258) +2022-11-14 14:22:56,536 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0760) Prec@1 91.000 (87.219) Prec@5 97.000 (99.188) +2022-11-14 14:22:56,549 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0756) Prec@1 89.000 (87.273) Prec@5 100.000 (99.212) +2022-11-14 14:22:56,563 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0763) Prec@1 81.000 (87.088) Prec@5 100.000 (99.235) +2022-11-14 14:22:56,578 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0764) Prec@1 86.000 (87.057) Prec@5 99.000 (99.229) +2022-11-14 14:22:56,592 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0757) Prec@1 90.000 (87.139) Prec@5 99.000 (99.222) +2022-11-14 14:22:56,607 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0759) Prec@1 85.000 (87.081) Prec@5 99.000 (99.216) +2022-11-14 14:22:56,622 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0767) Prec@1 83.000 (86.974) Prec@5 99.000 (99.211) +2022-11-14 14:22:56,636 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0763) Prec@1 90.000 (87.051) Prec@5 99.000 (99.205) +2022-11-14 14:22:56,649 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0761) Prec@1 88.000 (87.075) Prec@5 99.000 (99.200) +2022-11-14 14:22:56,663 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0765) Prec@1 84.000 (87.000) Prec@5 99.000 (99.195) +2022-11-14 14:22:56,676 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0765) Prec@1 86.000 (86.976) Prec@5 98.000 (99.167) +2022-11-14 14:22:56,690 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0758) Prec@1 93.000 (87.116) Prec@5 99.000 (99.163) +2022-11-14 14:22:56,704 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0755) Prec@1 92.000 (87.227) Prec@5 98.000 (99.136) +2022-11-14 14:22:56,717 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0752) Prec@1 89.000 (87.267) Prec@5 100.000 (99.156) +2022-11-14 14:22:56,729 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0757) Prec@1 82.000 (87.152) Prec@5 96.000 (99.087) +2022-11-14 14:22:56,745 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0758) Prec@1 86.000 (87.128) Prec@5 99.000 (99.085) +2022-11-14 14:22:56,761 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1151 (0.0766) Prec@1 82.000 (87.021) Prec@5 100.000 (99.104) +2022-11-14 14:22:56,776 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0763) Prec@1 90.000 (87.082) Prec@5 100.000 (99.122) +2022-11-14 14:22:56,792 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0768) Prec@1 85.000 (87.040) Prec@5 100.000 (99.140) +2022-11-14 14:22:56,807 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0766) Prec@1 86.000 (87.020) Prec@5 99.000 (99.137) +2022-11-14 14:22:56,821 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0769) Prec@1 83.000 (86.942) Prec@5 99.000 (99.135) +2022-11-14 14:22:56,838 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0771) Prec@1 87.000 (86.943) Prec@5 100.000 (99.151) +2022-11-14 14:22:56,852 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0771) Prec@1 84.000 (86.889) Prec@5 100.000 (99.167) +2022-11-14 14:22:56,866 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0772) Prec@1 86.000 (86.873) Prec@5 100.000 (99.182) +2022-11-14 14:22:56,883 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0771) Prec@1 88.000 (86.893) Prec@5 99.000 (99.179) +2022-11-14 14:22:56,897 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0771) Prec@1 84.000 (86.842) Prec@5 100.000 (99.193) +2022-11-14 14:22:56,914 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0769) Prec@1 89.000 (86.879) Prec@5 100.000 (99.207) +2022-11-14 14:22:56,929 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0773) Prec@1 84.000 (86.831) Prec@5 99.000 (99.203) +2022-11-14 14:22:56,944 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0773) Prec@1 84.000 (86.783) Prec@5 100.000 (99.217) +2022-11-14 14:22:56,959 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0777) Prec@1 80.000 (86.672) Prec@5 100.000 (99.230) +2022-11-14 14:22:56,975 Test: [61/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0776) Prec@1 90.000 (86.726) Prec@5 100.000 (99.242) +2022-11-14 14:22:56,990 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0773) Prec@1 90.000 (86.778) Prec@5 100.000 (99.254) +2022-11-14 14:22:57,003 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0767) Prec@1 94.000 (86.891) Prec@5 100.000 (99.266) +2022-11-14 14:22:57,016 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0773) Prec@1 84.000 (86.846) Prec@5 98.000 (99.246) +2022-11-14 14:22:57,029 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0771) Prec@1 87.000 (86.848) Prec@5 98.000 (99.227) +2022-11-14 14:22:57,046 Test: [66/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0769) Prec@1 91.000 (86.910) Prec@5 100.000 (99.239) +2022-11-14 14:22:57,063 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0768) Prec@1 89.000 (86.941) Prec@5 98.000 (99.221) +2022-11-14 14:22:57,077 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0769) Prec@1 87.000 (86.942) Prec@5 99.000 (99.217) +2022-11-14 14:22:57,091 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0770) Prec@1 84.000 (86.900) Prec@5 100.000 (99.229) +2022-11-14 14:22:57,105 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0773) Prec@1 84.000 (86.859) Prec@5 99.000 (99.225) +2022-11-14 14:22:57,119 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0772) Prec@1 90.000 (86.903) Prec@5 100.000 (99.236) +2022-11-14 14:22:57,135 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0771) Prec@1 91.000 (86.959) Prec@5 99.000 (99.233) +2022-11-14 14:22:57,150 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0769) Prec@1 91.000 (87.014) Prec@5 100.000 (99.243) +2022-11-14 14:22:57,163 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0771) Prec@1 84.000 (86.973) Prec@5 100.000 (99.253) +2022-11-14 14:22:57,176 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0771) Prec@1 87.000 (86.974) Prec@5 100.000 (99.263) +2022-11-14 14:22:57,190 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0769) Prec@1 89.000 (87.000) Prec@5 98.000 (99.247) +2022-11-14 14:22:57,203 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0772) Prec@1 83.000 (86.949) Prec@5 97.000 (99.218) +2022-11-14 14:22:57,217 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0772) Prec@1 88.000 (86.962) Prec@5 100.000 (99.228) +2022-11-14 14:22:57,229 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0773) Prec@1 87.000 (86.963) Prec@5 97.000 (99.200) +2022-11-14 14:22:57,245 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0772) Prec@1 89.000 (86.988) Prec@5 99.000 (99.198) +2022-11-14 14:22:57,261 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0770) Prec@1 91.000 (87.037) Prec@5 100.000 (99.207) +2022-11-14 14:22:57,276 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0772) Prec@1 83.000 (86.988) Prec@5 100.000 (99.217) +2022-11-14 14:22:57,288 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0770) Prec@1 88.000 (87.000) Prec@5 100.000 (99.226) +2022-11-14 14:22:57,301 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0772) Prec@1 83.000 (86.953) Prec@5 98.000 (99.212) +2022-11-14 14:22:57,313 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0775) Prec@1 83.000 (86.907) Prec@5 100.000 (99.221) +2022-11-14 14:22:57,327 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0774) Prec@1 88.000 (86.920) Prec@5 100.000 (99.230) +2022-11-14 14:22:57,344 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0773) Prec@1 90.000 (86.955) Prec@5 99.000 (99.227) +2022-11-14 14:22:57,359 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0774) Prec@1 88.000 (86.966) Prec@5 98.000 (99.213) +2022-11-14 14:22:57,373 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0775) Prec@1 87.000 (86.967) Prec@5 100.000 (99.222) +2022-11-14 14:22:57,387 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0774) Prec@1 87.000 (86.967) Prec@5 100.000 (99.231) +2022-11-14 14:22:57,403 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0772) Prec@1 91.000 (87.011) Prec@5 100.000 (99.239) +2022-11-14 14:22:57,418 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0772) Prec@1 86.000 (87.000) Prec@5 100.000 (99.247) +2022-11-14 14:22:57,432 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0772) Prec@1 88.000 (87.011) Prec@5 100.000 (99.255) +2022-11-14 14:22:57,446 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0773) Prec@1 89.000 (87.032) Prec@5 99.000 (99.253) +2022-11-14 14:22:57,461 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0771) Prec@1 89.000 (87.052) Prec@5 99.000 (99.250) +2022-11-14 14:22:57,475 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0767) Prec@1 92.000 (87.103) Prec@5 100.000 (99.258) +2022-11-14 14:22:57,489 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0769) Prec@1 86.000 (87.092) Prec@5 99.000 (99.255) +2022-11-14 14:22:57,502 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0769) Prec@1 87.000 (87.091) Prec@5 100.000 (99.263) +2022-11-14 14:22:57,516 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0768) Prec@1 89.000 (87.110) Prec@5 99.000 (99.260) +2022-11-14 14:22:57,575 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:22:57,892 Epoch: [189][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.0448 (0.0448) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 14:22:58,211 Epoch: [189][10/500] Time 0.033 (0.027) Data 0.002 (0.023) Loss 0.0250 (0.0349) Prec@1 97.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:22:58,585 Epoch: [189][20/500] Time 0.036 (0.030) Data 0.002 (0.013) Loss 0.0400 (0.0366) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 14:22:58,970 Epoch: [189][30/500] Time 0.035 (0.032) Data 0.002 (0.009) Loss 0.0209 (0.0327) Prec@1 97.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 14:22:59,352 Epoch: [189][40/500] Time 0.036 (0.032) Data 0.002 (0.008) Loss 0.0507 (0.0363) Prec@1 92.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:22:59,753 Epoch: [189][50/500] Time 0.030 (0.033) Data 0.002 (0.006) Loss 0.0528 (0.0390) Prec@1 91.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 14:23:00,147 Epoch: [189][60/500] Time 0.031 (0.033) Data 0.003 (0.006) Loss 0.0663 (0.0429) Prec@1 89.000 (93.000) Prec@5 99.000 (99.714) +2022-11-14 14:23:00,556 Epoch: [189][70/500] Time 0.029 (0.034) Data 0.002 (0.005) Loss 0.0240 (0.0406) Prec@1 96.000 (93.375) Prec@5 100.000 (99.750) +2022-11-14 14:23:00,929 Epoch: [189][80/500] Time 0.034 (0.034) Data 0.003 (0.005) Loss 0.0441 (0.0409) Prec@1 91.000 (93.111) Prec@5 100.000 (99.778) +2022-11-14 14:23:01,309 Epoch: [189][90/500] Time 0.034 (0.034) Data 0.002 (0.005) Loss 0.0601 (0.0429) Prec@1 88.000 (92.600) Prec@5 100.000 (99.800) +2022-11-14 14:23:01,696 Epoch: [189][100/500] Time 0.038 (0.034) Data 0.002 (0.004) Loss 0.0248 (0.0412) Prec@1 97.000 (93.000) Prec@5 100.000 (99.818) +2022-11-14 14:23:02,078 Epoch: [189][110/500] Time 0.038 (0.034) Data 0.002 (0.004) Loss 0.0467 (0.0417) Prec@1 92.000 (92.917) Prec@5 100.000 (99.833) +2022-11-14 14:23:02,450 Epoch: [189][120/500] Time 0.036 (0.034) Data 0.002 (0.004) Loss 0.0393 (0.0415) Prec@1 94.000 (93.000) Prec@5 100.000 (99.846) +2022-11-14 14:23:02,829 Epoch: [189][130/500] Time 0.033 (0.034) Data 0.002 (0.004) Loss 0.0258 (0.0404) Prec@1 97.000 (93.286) Prec@5 100.000 (99.857) +2022-11-14 14:23:03,218 Epoch: [189][140/500] Time 0.042 (0.034) Data 0.003 (0.004) Loss 0.0464 (0.0408) Prec@1 91.000 (93.133) Prec@5 99.000 (99.800) +2022-11-14 14:23:03,595 Epoch: [189][150/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0286 (0.0400) Prec@1 95.000 (93.250) Prec@5 100.000 (99.812) +2022-11-14 14:23:03,978 Epoch: [189][160/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0240 (0.0391) Prec@1 95.000 (93.353) Prec@5 100.000 (99.824) +2022-11-14 14:23:04,370 Epoch: [189][170/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0348 (0.0388) Prec@1 94.000 (93.389) Prec@5 99.000 (99.778) +2022-11-14 14:23:04,756 Epoch: [189][180/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0225 (0.0380) Prec@1 96.000 (93.526) Prec@5 100.000 (99.789) +2022-11-14 14:23:05,132 Epoch: [189][190/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0478 (0.0385) Prec@1 94.000 (93.550) Prec@5 100.000 (99.800) +2022-11-14 14:23:05,523 Epoch: [189][200/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0419 (0.0386) Prec@1 94.000 (93.571) Prec@5 100.000 (99.810) +2022-11-14 14:23:05,908 Epoch: [189][210/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0497 (0.0391) Prec@1 91.000 (93.455) Prec@5 100.000 (99.818) +2022-11-14 14:23:06,297 Epoch: [189][220/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0496 (0.0396) Prec@1 90.000 (93.304) Prec@5 100.000 (99.826) +2022-11-14 14:23:06,685 Epoch: [189][230/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0553 (0.0402) Prec@1 90.000 (93.167) Prec@5 100.000 (99.833) +2022-11-14 14:23:07,068 Epoch: [189][240/500] Time 0.037 (0.034) Data 0.001 (0.003) Loss 0.0387 (0.0402) Prec@1 96.000 (93.280) Prec@5 100.000 (99.840) +2022-11-14 14:23:07,458 Epoch: [189][250/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0422 (0.0403) Prec@1 91.000 (93.192) Prec@5 100.000 (99.846) +2022-11-14 14:23:07,849 Epoch: [189][260/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0666 (0.0412) Prec@1 88.000 (93.000) Prec@5 99.000 (99.815) +2022-11-14 14:23:08,236 Epoch: [189][270/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0384 (0.0411) Prec@1 94.000 (93.036) Prec@5 100.000 (99.821) +2022-11-14 14:23:08,619 Epoch: [189][280/500] Time 0.035 (0.034) Data 0.001 (0.003) Loss 0.0370 (0.0410) Prec@1 94.000 (93.069) Prec@5 100.000 (99.828) +2022-11-14 14:23:08,998 Epoch: [189][290/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0361 (0.0408) Prec@1 94.000 (93.100) Prec@5 100.000 (99.833) +2022-11-14 14:23:09,388 Epoch: [189][300/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0586 (0.0414) Prec@1 91.000 (93.032) Prec@5 100.000 (99.839) +2022-11-14 14:23:09,764 Epoch: [189][310/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0434 (0.0415) Prec@1 91.000 (92.969) Prec@5 100.000 (99.844) +2022-11-14 14:23:10,159 Epoch: [189][320/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0452 (0.0416) Prec@1 93.000 (92.970) Prec@5 100.000 (99.848) +2022-11-14 14:23:10,538 Epoch: [189][330/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0234 (0.0410) Prec@1 95.000 (93.029) Prec@5 100.000 (99.853) +2022-11-14 14:23:10,921 Epoch: [189][340/500] Time 0.035 (0.034) Data 0.001 (0.003) Loss 0.0557 (0.0415) Prec@1 90.000 (92.943) Prec@5 98.000 (99.800) +2022-11-14 14:23:11,307 Epoch: [189][350/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0305 (0.0412) Prec@1 94.000 (92.972) Prec@5 100.000 (99.806) +2022-11-14 14:23:11,699 Epoch: [189][360/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0762 (0.0421) Prec@1 89.000 (92.865) Prec@5 100.000 (99.811) +2022-11-14 14:23:12,111 Epoch: [189][370/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0456 (0.0422) Prec@1 92.000 (92.842) Prec@5 99.000 (99.789) +2022-11-14 14:23:12,495 Epoch: [189][380/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0368 (0.0421) Prec@1 92.000 (92.821) Prec@5 100.000 (99.795) +2022-11-14 14:23:12,880 Epoch: [189][390/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0324 (0.0418) Prec@1 95.000 (92.875) Prec@5 100.000 (99.800) +2022-11-14 14:23:13,277 Epoch: [189][400/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0480 (0.0420) Prec@1 92.000 (92.854) Prec@5 100.000 (99.805) +2022-11-14 14:23:13,685 Epoch: [189][410/500] Time 0.028 (0.034) Data 0.002 (0.002) Loss 0.0605 (0.0424) Prec@1 90.000 (92.786) Prec@5 99.000 (99.786) +2022-11-14 14:23:14,066 Epoch: [189][420/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0235 (0.0420) Prec@1 97.000 (92.884) Prec@5 100.000 (99.791) +2022-11-14 14:23:14,451 Epoch: [189][430/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0416 (0.0420) Prec@1 93.000 (92.886) Prec@5 100.000 (99.795) +2022-11-14 14:23:14,834 Epoch: [189][440/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0472 (0.0421) Prec@1 90.000 (92.822) Prec@5 100.000 (99.800) +2022-11-14 14:23:15,226 Epoch: [189][450/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0127 (0.0414) Prec@1 98.000 (92.935) Prec@5 100.000 (99.804) +2022-11-14 14:23:15,618 Epoch: [189][460/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0303 (0.0412) Prec@1 96.000 (93.000) Prec@5 100.000 (99.809) +2022-11-14 14:23:16,003 Epoch: [189][470/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0560 (0.0415) Prec@1 91.000 (92.958) Prec@5 99.000 (99.792) +2022-11-14 14:23:16,396 Epoch: [189][480/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0401 (0.0415) Prec@1 95.000 (93.000) Prec@5 100.000 (99.796) +2022-11-14 14:23:16,770 Epoch: [189][490/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0587 (0.0418) Prec@1 91.000 (92.960) Prec@5 100.000 (99.800) +2022-11-14 14:23:17,121 Epoch: [189][499/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0457 (0.0419) Prec@1 94.000 (92.980) Prec@5 99.000 (99.784) +2022-11-14 14:23:17,414 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0911 (0.0911) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 14:23:17,423 Test: [1/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0714 (0.0813) Prec@1 88.000 (86.500) Prec@5 99.000 (98.500) +2022-11-14 14:23:17,432 Test: [2/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0993 (0.0873) Prec@1 84.000 (85.667) Prec@5 100.000 (99.000) +2022-11-14 14:23:17,444 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0850) Prec@1 87.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 14:23:17,455 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0812) Prec@1 90.000 (86.800) Prec@5 100.000 (99.200) +2022-11-14 14:23:17,465 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0461 (0.0753) Prec@1 91.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 14:23:17,477 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0746) Prec@1 87.000 (87.429) Prec@5 100.000 (99.429) +2022-11-14 14:23:17,489 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0751) Prec@1 87.000 (87.375) Prec@5 100.000 (99.500) +2022-11-14 14:23:17,499 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0760) Prec@1 87.000 (87.333) Prec@5 100.000 (99.556) +2022-11-14 14:23:17,514 Test: [9/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0761) Prec@1 87.000 (87.300) Prec@5 98.000 (99.400) +2022-11-14 14:23:17,528 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0758) Prec@1 87.000 (87.273) Prec@5 99.000 (99.364) +2022-11-14 14:23:17,542 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0774) Prec@1 83.000 (86.917) Prec@5 99.000 (99.333) +2022-11-14 14:23:17,556 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0765) Prec@1 87.000 (86.923) Prec@5 100.000 (99.385) +2022-11-14 14:23:17,570 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0760) Prec@1 89.000 (87.071) Prec@5 99.000 (99.357) +2022-11-14 14:23:17,585 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0765) Prec@1 85.000 (86.933) Prec@5 98.000 (99.267) +2022-11-14 14:23:17,600 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0770) Prec@1 86.000 (86.875) Prec@5 100.000 (99.312) +2022-11-14 14:23:17,614 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0763) Prec@1 88.000 (86.941) Prec@5 99.000 (99.294) +2022-11-14 14:23:17,630 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0778) Prec@1 83.000 (86.722) Prec@5 100.000 (99.333) +2022-11-14 14:23:17,645 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0782) Prec@1 83.000 (86.526) Prec@5 99.000 (99.316) +2022-11-14 14:23:17,660 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1016 (0.0793) Prec@1 85.000 (86.450) Prec@5 98.000 (99.250) +2022-11-14 14:23:17,674 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0799) Prec@1 83.000 (86.286) Prec@5 100.000 (99.286) +2022-11-14 14:23:17,688 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0794) Prec@1 90.000 (86.455) Prec@5 100.000 (99.318) +2022-11-14 14:23:17,702 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0808) Prec@1 83.000 (86.304) Prec@5 98.000 (99.261) +2022-11-14 14:23:17,718 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0801) Prec@1 89.000 (86.417) Prec@5 98.000 (99.208) +2022-11-14 14:23:17,731 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0801) Prec@1 87.000 (86.440) Prec@5 100.000 (99.240) +2022-11-14 14:23:17,745 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.0815) Prec@1 80.000 (86.192) Prec@5 97.000 (99.154) +2022-11-14 14:23:17,758 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0810) Prec@1 87.000 (86.222) Prec@5 100.000 (99.185) +2022-11-14 14:23:17,773 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0810) Prec@1 87.000 (86.250) Prec@5 100.000 (99.214) +2022-11-14 14:23:17,788 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0804) Prec@1 89.000 (86.345) Prec@5 99.000 (99.207) +2022-11-14 14:23:17,803 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0795) Prec@1 91.000 (86.500) Prec@5 100.000 (99.233) +2022-11-14 14:23:17,816 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0788) Prec@1 92.000 (86.677) Prec@5 98.000 (99.194) +2022-11-14 14:23:17,829 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0782) Prec@1 91.000 (86.812) Prec@5 100.000 (99.219) +2022-11-14 14:23:17,842 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0782) Prec@1 85.000 (86.758) Prec@5 99.000 (99.212) +2022-11-14 14:23:17,857 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0785) Prec@1 83.000 (86.647) Prec@5 100.000 (99.235) +2022-11-14 14:23:17,872 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0785) Prec@1 87.000 (86.657) Prec@5 98.000 (99.200) +2022-11-14 14:23:17,887 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0780) Prec@1 91.000 (86.778) Prec@5 99.000 (99.194) +2022-11-14 14:23:17,902 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0782) Prec@1 87.000 (86.784) Prec@5 99.000 (99.189) +2022-11-14 14:23:17,917 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0783) Prec@1 88.000 (86.816) Prec@5 100.000 (99.211) +2022-11-14 14:23:17,932 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0780) Prec@1 90.000 (86.897) Prec@5 98.000 (99.179) +2022-11-14 14:23:17,947 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0779) Prec@1 88.000 (86.925) Prec@5 98.000 (99.150) +2022-11-14 14:23:17,962 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0785) Prec@1 83.000 (86.829) Prec@5 99.000 (99.146) +2022-11-14 14:23:17,975 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0785) Prec@1 89.000 (86.881) Prec@5 99.000 (99.143) +2022-11-14 14:23:17,988 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0775) Prec@1 95.000 (87.070) Prec@5 99.000 (99.140) +2022-11-14 14:23:18,004 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0776) Prec@1 88.000 (87.091) Prec@5 99.000 (99.136) +2022-11-14 14:23:18,017 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0774) Prec@1 89.000 (87.133) Prec@5 100.000 (99.156) +2022-11-14 14:23:18,031 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0776) Prec@1 84.000 (87.065) Prec@5 99.000 (99.152) +2022-11-14 14:23:18,047 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0775) Prec@1 87.000 (87.064) Prec@5 100.000 (99.170) +2022-11-14 14:23:18,064 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0781) Prec@1 83.000 (86.979) Prec@5 98.000 (99.146) +2022-11-14 14:23:18,078 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0776) Prec@1 91.000 (87.061) Prec@5 100.000 (99.163) +2022-11-14 14:23:18,092 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0783) Prec@1 83.000 (86.980) Prec@5 100.000 (99.180) +2022-11-14 14:23:18,106 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0782) Prec@1 86.000 (86.961) Prec@5 99.000 (99.176) +2022-11-14 14:23:18,121 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0786) Prec@1 83.000 (86.885) Prec@5 100.000 (99.192) +2022-11-14 14:23:18,135 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0782) Prec@1 89.000 (86.925) Prec@5 99.000 (99.189) +2022-11-14 14:23:18,149 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0778) Prec@1 91.000 (87.000) Prec@5 98.000 (99.167) +2022-11-14 14:23:18,163 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0781) Prec@1 85.000 (86.964) Prec@5 100.000 (99.182) +2022-11-14 14:23:18,178 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0783) Prec@1 86.000 (86.946) Prec@5 98.000 (99.161) +2022-11-14 14:23:18,193 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0783) Prec@1 88.000 (86.965) Prec@5 100.000 (99.175) +2022-11-14 14:23:18,209 Test: [57/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0781) Prec@1 89.000 (87.000) Prec@5 99.000 (99.172) +2022-11-14 14:23:18,224 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0786) Prec@1 82.000 (86.915) Prec@5 99.000 (99.169) +2022-11-14 14:23:18,241 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0785) Prec@1 87.000 (86.917) Prec@5 99.000 (99.167) +2022-11-14 14:23:18,256 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0789) Prec@1 80.000 (86.803) Prec@5 99.000 (99.164) +2022-11-14 14:23:18,272 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0793) Prec@1 84.000 (86.758) Prec@5 100.000 (99.177) +2022-11-14 14:23:18,288 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0791) Prec@1 89.000 (86.794) Prec@5 100.000 (99.190) +2022-11-14 14:23:18,301 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0374 (0.0784) Prec@1 94.000 (86.906) Prec@5 99.000 (99.188) +2022-11-14 14:23:18,316 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1135 (0.0789) Prec@1 81.000 (86.815) Prec@5 100.000 (99.200) +2022-11-14 14:23:18,333 Test: [65/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0791) Prec@1 84.000 (86.773) Prec@5 98.000 (99.182) +2022-11-14 14:23:18,349 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0787) Prec@1 91.000 (86.836) Prec@5 100.000 (99.194) +2022-11-14 14:23:18,364 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0787) Prec@1 88.000 (86.853) Prec@5 98.000 (99.176) +2022-11-14 14:23:18,377 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0786) Prec@1 90.000 (86.899) Prec@5 99.000 (99.174) +2022-11-14 14:23:18,391 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0786) Prec@1 88.000 (86.914) Prec@5 98.000 (99.157) +2022-11-14 14:23:18,406 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0789) Prec@1 85.000 (86.887) Prec@5 99.000 (99.155) +2022-11-14 14:23:18,421 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0787) Prec@1 90.000 (86.931) Prec@5 100.000 (99.167) +2022-11-14 14:23:18,437 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0785) Prec@1 90.000 (86.973) Prec@5 100.000 (99.178) +2022-11-14 14:23:18,452 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0781) Prec@1 91.000 (87.027) Prec@5 100.000 (99.189) +2022-11-14 14:23:18,467 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0781) Prec@1 86.000 (87.013) Prec@5 99.000 (99.187) +2022-11-14 14:23:18,482 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0778) Prec@1 91.000 (87.066) Prec@5 99.000 (99.184) +2022-11-14 14:23:18,496 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0778) Prec@1 88.000 (87.078) Prec@5 99.000 (99.182) +2022-11-14 14:23:18,508 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0781) Prec@1 82.000 (87.013) Prec@5 99.000 (99.179) +2022-11-14 14:23:18,524 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0779) Prec@1 91.000 (87.063) Prec@5 100.000 (99.190) +2022-11-14 14:23:18,538 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0778) Prec@1 90.000 (87.100) Prec@5 100.000 (99.200) +2022-11-14 14:23:18,552 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0779) Prec@1 85.000 (87.074) Prec@5 100.000 (99.210) +2022-11-14 14:23:18,565 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0778) Prec@1 88.000 (87.085) Prec@5 99.000 (99.207) +2022-11-14 14:23:18,580 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0778) Prec@1 86.000 (87.072) Prec@5 100.000 (99.217) +2022-11-14 14:23:18,594 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0779) Prec@1 84.000 (87.036) Prec@5 99.000 (99.214) +2022-11-14 14:23:18,607 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0780) Prec@1 85.000 (87.012) Prec@5 99.000 (99.212) +2022-11-14 14:23:18,621 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.0785) Prec@1 80.000 (86.930) Prec@5 100.000 (99.221) +2022-11-14 14:23:18,635 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0784) Prec@1 89.000 (86.954) Prec@5 100.000 (99.230) +2022-11-14 14:23:18,648 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0783) Prec@1 88.000 (86.966) Prec@5 99.000 (99.227) +2022-11-14 14:23:18,662 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0782) Prec@1 89.000 (86.989) Prec@5 99.000 (99.225) +2022-11-14 14:23:18,677 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0784) Prec@1 85.000 (86.967) Prec@5 99.000 (99.222) +2022-11-14 14:23:18,691 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0780) Prec@1 91.000 (87.011) Prec@5 100.000 (99.231) +2022-11-14 14:23:18,707 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0778) Prec@1 88.000 (87.022) Prec@5 100.000 (99.239) +2022-11-14 14:23:18,722 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0778) Prec@1 87.000 (87.022) Prec@5 99.000 (99.237) +2022-11-14 14:23:18,739 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0778) Prec@1 85.000 (87.000) Prec@5 99.000 (99.234) +2022-11-14 14:23:18,754 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0778) Prec@1 85.000 (86.979) Prec@5 99.000 (99.232) +2022-11-14 14:23:18,767 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0776) Prec@1 88.000 (86.990) Prec@5 100.000 (99.240) +2022-11-14 14:23:18,780 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0773) Prec@1 92.000 (87.041) Prec@5 99.000 (99.237) +2022-11-14 14:23:18,798 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0776) Prec@1 84.000 (87.010) Prec@5 99.000 (99.235) +2022-11-14 14:23:18,815 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0778) Prec@1 83.000 (86.970) Prec@5 98.000 (99.222) +2022-11-14 14:23:18,830 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0776) Prec@1 89.000 (86.990) Prec@5 99.000 (99.220) +2022-11-14 14:23:18,888 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:23:19,207 Epoch: [190][0/500] Time 0.025 (0.025) Data 0.233 (0.233) Loss 0.0570 (0.0570) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:23:19,525 Epoch: [190][10/500] Time 0.035 (0.027) Data 0.002 (0.023) Loss 0.0275 (0.0422) Prec@1 95.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:23:19,928 Epoch: [190][20/500] Time 0.037 (0.031) Data 0.002 (0.013) Loss 0.0707 (0.0517) Prec@1 88.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:23:20,333 Epoch: [190][30/500] Time 0.035 (0.033) Data 0.002 (0.009) Loss 0.0366 (0.0479) Prec@1 95.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:23:20,717 Epoch: [190][40/500] Time 0.044 (0.033) Data 0.002 (0.007) Loss 0.0525 (0.0489) Prec@1 91.000 (91.800) Prec@5 99.000 (99.600) +2022-11-14 14:23:21,100 Epoch: [190][50/500] Time 0.042 (0.033) Data 0.002 (0.006) Loss 0.0311 (0.0459) Prec@1 95.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:23:21,507 Epoch: [190][60/500] Time 0.038 (0.033) Data 0.002 (0.006) Loss 0.0355 (0.0444) Prec@1 92.000 (92.286) Prec@5 100.000 (99.714) +2022-11-14 14:23:21,877 Epoch: [190][70/500] Time 0.036 (0.033) Data 0.002 (0.005) Loss 0.0328 (0.0430) Prec@1 96.000 (92.750) Prec@5 100.000 (99.750) +2022-11-14 14:23:22,290 Epoch: [190][80/500] Time 0.036 (0.034) Data 0.002 (0.005) Loss 0.0411 (0.0428) Prec@1 94.000 (92.889) Prec@5 100.000 (99.778) +2022-11-14 14:23:22,693 Epoch: [190][90/500] Time 0.025 (0.034) Data 0.002 (0.004) Loss 0.0589 (0.0444) Prec@1 91.000 (92.700) Prec@5 100.000 (99.800) +2022-11-14 14:23:23,191 Epoch: [190][100/500] Time 0.047 (0.035) Data 0.002 (0.004) Loss 0.0397 (0.0439) Prec@1 93.000 (92.727) Prec@5 99.000 (99.727) +2022-11-14 14:23:23,657 Epoch: [190][110/500] Time 0.041 (0.035) Data 0.002 (0.004) Loss 0.0329 (0.0430) Prec@1 95.000 (92.917) Prec@5 100.000 (99.750) +2022-11-14 14:23:24,064 Epoch: [190][120/500] Time 0.052 (0.035) Data 0.002 (0.004) Loss 0.0488 (0.0435) Prec@1 92.000 (92.846) Prec@5 99.000 (99.692) +2022-11-14 14:23:24,510 Epoch: [190][130/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0405 (0.0433) Prec@1 94.000 (92.929) Prec@5 100.000 (99.714) +2022-11-14 14:23:24,982 Epoch: [190][140/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0523 (0.0439) Prec@1 90.000 (92.733) Prec@5 100.000 (99.733) +2022-11-14 14:23:25,461 Epoch: [190][150/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0267 (0.0428) Prec@1 95.000 (92.875) Prec@5 100.000 (99.750) +2022-11-14 14:23:25,933 Epoch: [190][160/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0554 (0.0435) Prec@1 90.000 (92.706) Prec@5 100.000 (99.765) +2022-11-14 14:23:26,415 Epoch: [190][170/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0737 (0.0452) Prec@1 87.000 (92.389) Prec@5 100.000 (99.778) +2022-11-14 14:23:26,901 Epoch: [190][180/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0401 (0.0449) Prec@1 93.000 (92.421) Prec@5 100.000 (99.789) +2022-11-14 14:23:27,393 Epoch: [190][190/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0503 (0.0452) Prec@1 91.000 (92.350) Prec@5 100.000 (99.800) +2022-11-14 14:23:27,867 Epoch: [190][200/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0543 (0.0456) Prec@1 91.000 (92.286) Prec@5 100.000 (99.810) +2022-11-14 14:23:28,344 Epoch: [190][210/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0658 (0.0466) Prec@1 89.000 (92.136) Prec@5 100.000 (99.818) +2022-11-14 14:23:28,813 Epoch: [190][220/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0275 (0.0457) Prec@1 96.000 (92.304) Prec@5 99.000 (99.783) +2022-11-14 14:23:29,329 Epoch: [190][230/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0418 (0.0456) Prec@1 93.000 (92.333) Prec@5 99.000 (99.750) +2022-11-14 14:23:29,888 Epoch: [190][240/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0535 (0.0459) Prec@1 92.000 (92.320) Prec@5 100.000 (99.760) +2022-11-14 14:23:30,388 Epoch: [190][250/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0217 (0.0449) Prec@1 96.000 (92.462) Prec@5 100.000 (99.769) +2022-11-14 14:23:30,882 Epoch: [190][260/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0305 (0.0444) Prec@1 97.000 (92.630) Prec@5 100.000 (99.778) +2022-11-14 14:23:31,368 Epoch: [190][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0369 (0.0441) Prec@1 92.000 (92.607) Prec@5 100.000 (99.786) +2022-11-14 14:23:31,867 Epoch: [190][280/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0230 (0.0434) Prec@1 96.000 (92.724) Prec@5 100.000 (99.793) +2022-11-14 14:23:32,393 Epoch: [190][290/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0499 (0.0436) Prec@1 91.000 (92.667) Prec@5 99.000 (99.767) +2022-11-14 14:23:32,874 Epoch: [190][300/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0425 (0.0436) Prec@1 94.000 (92.710) Prec@5 99.000 (99.742) +2022-11-14 14:23:33,363 Epoch: [190][310/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0424 (0.0436) Prec@1 92.000 (92.688) Prec@5 100.000 (99.750) +2022-11-14 14:23:33,841 Epoch: [190][320/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0588 (0.0440) Prec@1 90.000 (92.606) Prec@5 100.000 (99.758) +2022-11-14 14:23:34,380 Epoch: [190][330/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0318 (0.0437) Prec@1 94.000 (92.647) Prec@5 99.000 (99.735) +2022-11-14 14:23:34,962 Epoch: [190][340/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0442 (0.0437) Prec@1 92.000 (92.629) Prec@5 100.000 (99.743) +2022-11-14 14:23:35,459 Epoch: [190][350/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0288 (0.0433) Prec@1 95.000 (92.694) Prec@5 100.000 (99.750) +2022-11-14 14:23:35,967 Epoch: [190][360/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0591 (0.0437) Prec@1 91.000 (92.649) Prec@5 99.000 (99.730) +2022-11-14 14:23:36,461 Epoch: [190][370/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0431 (0.0437) Prec@1 91.000 (92.605) Prec@5 100.000 (99.737) +2022-11-14 14:23:37,233 Epoch: [190][380/500] Time 0.077 (0.042) Data 0.002 (0.003) Loss 0.0476 (0.0438) Prec@1 93.000 (92.615) Prec@5 100.000 (99.744) +2022-11-14 14:23:37,899 Epoch: [190][390/500] Time 0.065 (0.042) Data 0.002 (0.003) Loss 0.0376 (0.0436) Prec@1 92.000 (92.600) Prec@5 100.000 (99.750) +2022-11-14 14:23:38,570 Epoch: [190][400/500] Time 0.072 (0.043) Data 0.002 (0.003) Loss 0.0605 (0.0440) Prec@1 89.000 (92.512) Prec@5 100.000 (99.756) +2022-11-14 14:23:39,318 Epoch: [190][410/500] Time 0.075 (0.043) Data 0.002 (0.003) Loss 0.0422 (0.0440) Prec@1 93.000 (92.524) Prec@5 100.000 (99.762) +2022-11-14 14:23:40,079 Epoch: [190][420/500] Time 0.094 (0.044) Data 0.002 (0.002) Loss 0.0450 (0.0440) Prec@1 92.000 (92.512) Prec@5 100.000 (99.767) +2022-11-14 14:23:40,931 Epoch: [190][430/500] Time 0.088 (0.045) Data 0.002 (0.002) Loss 0.0430 (0.0440) Prec@1 93.000 (92.523) Prec@5 100.000 (99.773) +2022-11-14 14:23:41,681 Epoch: [190][440/500] Time 0.065 (0.045) Data 0.002 (0.002) Loss 0.0446 (0.0440) Prec@1 92.000 (92.511) Prec@5 99.000 (99.756) +2022-11-14 14:23:42,078 Epoch: [190][450/500] Time 0.041 (0.045) Data 0.002 (0.002) Loss 0.0131 (0.0433) Prec@1 99.000 (92.652) Prec@5 100.000 (99.761) +2022-11-14 14:23:42,489 Epoch: [190][460/500] Time 0.040 (0.045) Data 0.002 (0.002) Loss 0.0437 (0.0433) Prec@1 93.000 (92.660) Prec@5 100.000 (99.766) +2022-11-14 14:23:42,903 Epoch: [190][470/500] Time 0.039 (0.045) Data 0.002 (0.002) Loss 0.0504 (0.0435) Prec@1 92.000 (92.646) Prec@5 99.000 (99.750) +2022-11-14 14:23:43,241 Epoch: [190][480/500] Time 0.036 (0.044) Data 0.002 (0.002) Loss 0.0571 (0.0438) Prec@1 91.000 (92.612) Prec@5 100.000 (99.755) +2022-11-14 14:23:43,601 Epoch: [190][490/500] Time 0.027 (0.044) Data 0.002 (0.002) Loss 0.0486 (0.0439) Prec@1 93.000 (92.620) Prec@5 100.000 (99.760) +2022-11-14 14:23:43,902 Epoch: [190][499/500] Time 0.031 (0.044) Data 0.001 (0.002) Loss 0.0442 (0.0439) Prec@1 93.000 (92.627) Prec@5 100.000 (99.765) +2022-11-14 14:23:44,207 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0693 (0.0693) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:23:44,218 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0887 (0.0790) Prec@1 84.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 14:23:44,229 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0762 (0.0781) Prec@1 85.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 14:23:44,242 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0769 (0.0778) Prec@1 86.000 (86.000) Prec@5 98.000 (99.250) +2022-11-14 14:23:44,255 Test: [4/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0943 (0.0811) Prec@1 85.000 (85.800) Prec@5 100.000 (99.400) +2022-11-14 14:23:44,265 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0507 (0.0760) Prec@1 92.000 (86.833) Prec@5 100.000 (99.500) +2022-11-14 14:23:44,274 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0596 (0.0737) Prec@1 90.000 (87.286) Prec@5 100.000 (99.571) +2022-11-14 14:23:44,282 Test: [7/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0971 (0.0766) Prec@1 81.000 (86.500) Prec@5 100.000 (99.625) +2022-11-14 14:23:44,296 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0762) Prec@1 90.000 (86.889) Prec@5 100.000 (99.667) +2022-11-14 14:23:44,306 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0606 (0.0746) Prec@1 90.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 14:23:44,316 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0741) Prec@1 90.000 (87.455) Prec@5 100.000 (99.636) +2022-11-14 14:23:44,325 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0976 (0.0760) Prec@1 84.000 (87.167) Prec@5 100.000 (99.667) +2022-11-14 14:23:44,338 Test: [12/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0424 (0.0735) Prec@1 93.000 (87.615) Prec@5 99.000 (99.615) +2022-11-14 14:23:44,349 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0740) Prec@1 88.000 (87.643) Prec@5 99.000 (99.571) +2022-11-14 14:23:44,359 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0736) Prec@1 89.000 (87.733) Prec@5 100.000 (99.600) +2022-11-14 14:23:44,370 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0743) Prec@1 85.000 (87.562) Prec@5 99.000 (99.562) +2022-11-14 14:23:44,383 Test: [16/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0737) Prec@1 89.000 (87.647) Prec@5 99.000 (99.529) +2022-11-14 14:23:44,395 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1108 (0.0758) Prec@1 81.000 (87.278) Prec@5 99.000 (99.500) +2022-11-14 14:23:44,405 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0771) Prec@1 84.000 (87.105) Prec@5 98.000 (99.421) +2022-11-14 14:23:44,415 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0767) Prec@1 89.000 (87.200) Prec@5 99.000 (99.400) +2022-11-14 14:23:44,425 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0781) Prec@1 80.000 (86.857) Prec@5 98.000 (99.333) +2022-11-14 14:23:44,434 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0787) Prec@1 84.000 (86.727) Prec@5 99.000 (99.318) +2022-11-14 14:23:44,444 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.0795) Prec@1 85.000 (86.652) Prec@5 98.000 (99.261) +2022-11-14 14:23:44,454 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0791) Prec@1 87.000 (86.667) Prec@5 100.000 (99.292) +2022-11-14 14:23:44,468 Test: [24/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0795) Prec@1 86.000 (86.640) Prec@5 100.000 (99.320) +2022-11-14 14:23:44,480 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0805) Prec@1 84.000 (86.538) Prec@5 97.000 (99.231) +2022-11-14 14:23:44,491 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0798) Prec@1 90.000 (86.667) Prec@5 99.000 (99.222) +2022-11-14 14:23:44,502 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0800) Prec@1 87.000 (86.679) Prec@5 100.000 (99.250) +2022-11-14 14:23:44,515 Test: [28/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0793) Prec@1 90.000 (86.793) Prec@5 100.000 (99.276) +2022-11-14 14:23:44,528 Test: [29/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0606 (0.0786) Prec@1 90.000 (86.900) Prec@5 100.000 (99.300) +2022-11-14 14:23:44,538 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0789) Prec@1 84.000 (86.806) Prec@5 99.000 (99.290) +2022-11-14 14:23:44,548 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0787) Prec@1 87.000 (86.812) Prec@5 98.000 (99.250) +2022-11-14 14:23:44,561 Test: [32/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0790) Prec@1 84.000 (86.727) Prec@5 99.000 (99.242) +2022-11-14 14:23:44,574 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0793) Prec@1 85.000 (86.676) Prec@5 99.000 (99.235) +2022-11-14 14:23:44,585 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0796) Prec@1 87.000 (86.686) Prec@5 98.000 (99.200) +2022-11-14 14:23:44,595 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0650 (0.0792) Prec@1 89.000 (86.750) Prec@5 99.000 (99.194) +2022-11-14 14:23:44,609 Test: [36/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0793) Prec@1 86.000 (86.730) Prec@5 97.000 (99.135) +2022-11-14 14:23:44,623 Test: [37/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1092 (0.0801) Prec@1 82.000 (86.605) Prec@5 97.000 (99.079) +2022-11-14 14:23:44,633 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0509 (0.0793) Prec@1 92.000 (86.744) Prec@5 98.000 (99.051) +2022-11-14 14:23:44,643 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0790) Prec@1 88.000 (86.775) Prec@5 99.000 (99.050) +2022-11-14 14:23:44,656 Test: [40/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0795) Prec@1 84.000 (86.707) Prec@5 97.000 (99.000) +2022-11-14 14:23:44,667 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0793) Prec@1 85.000 (86.667) Prec@5 99.000 (99.000) +2022-11-14 14:23:44,679 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0787) Prec@1 90.000 (86.744) Prec@5 100.000 (99.023) +2022-11-14 14:23:44,690 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0788) Prec@1 86.000 (86.727) Prec@5 98.000 (99.000) +2022-11-14 14:23:44,700 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0784) Prec@1 88.000 (86.756) Prec@5 100.000 (99.022) +2022-11-14 14:23:44,714 Test: [45/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0929 (0.0787) Prec@1 86.000 (86.739) Prec@5 100.000 (99.043) +2022-11-14 14:23:44,728 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0787) Prec@1 88.000 (86.766) Prec@5 99.000 (99.043) +2022-11-14 14:23:44,739 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1087 (0.0793) Prec@1 83.000 (86.688) Prec@5 99.000 (99.042) +2022-11-14 14:23:44,750 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0425 (0.0785) Prec@1 93.000 (86.816) Prec@5 100.000 (99.061) +2022-11-14 14:23:44,761 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1172 (0.0793) Prec@1 81.000 (86.700) Prec@5 99.000 (99.060) +2022-11-14 14:23:44,772 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0609 (0.0790) Prec@1 93.000 (86.824) Prec@5 98.000 (99.039) +2022-11-14 14:23:44,784 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1141 (0.0796) Prec@1 78.000 (86.654) Prec@5 98.000 (99.019) +2022-11-14 14:23:44,795 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0795) Prec@1 88.000 (86.679) Prec@5 100.000 (99.038) +2022-11-14 14:23:44,805 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0794) Prec@1 87.000 (86.685) Prec@5 97.000 (99.000) +2022-11-14 14:23:44,816 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0908 (0.0796) Prec@1 84.000 (86.636) Prec@5 100.000 (99.018) +2022-11-14 14:23:44,826 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0777 (0.0796) Prec@1 86.000 (86.625) Prec@5 98.000 (99.000) +2022-11-14 14:23:44,836 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0797) Prec@1 83.000 (86.561) Prec@5 100.000 (99.018) +2022-11-14 14:23:44,846 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0794) Prec@1 89.000 (86.603) Prec@5 100.000 (99.034) +2022-11-14 14:23:44,856 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.0800) Prec@1 81.000 (86.508) Prec@5 100.000 (99.051) +2022-11-14 14:23:44,866 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0804) Prec@1 81.000 (86.417) Prec@5 99.000 (99.050) +2022-11-14 14:23:44,877 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0804) Prec@1 88.000 (86.443) Prec@5 96.000 (99.000) +2022-11-14 14:23:44,888 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0805) Prec@1 86.000 (86.435) Prec@5 97.000 (98.968) +2022-11-14 14:23:44,900 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0803) Prec@1 89.000 (86.476) Prec@5 99.000 (98.968) +2022-11-14 14:23:44,910 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0800) Prec@1 88.000 (86.500) Prec@5 99.000 (98.969) +2022-11-14 14:23:44,922 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0804) Prec@1 82.000 (86.431) Prec@5 99.000 (98.969) +2022-11-14 14:23:44,932 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0802) Prec@1 90.000 (86.485) Prec@5 98.000 (98.955) +2022-11-14 14:23:44,943 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0797) Prec@1 92.000 (86.567) Prec@5 100.000 (98.970) +2022-11-14 14:23:44,953 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0798) Prec@1 88.000 (86.588) Prec@5 98.000 (98.956) +2022-11-14 14:23:44,964 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0796) Prec@1 88.000 (86.609) Prec@5 100.000 (98.971) +2022-11-14 14:23:44,975 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0800) Prec@1 82.000 (86.543) Prec@5 97.000 (98.943) +2022-11-14 14:23:44,985 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0801) Prec@1 86.000 (86.535) Prec@5 100.000 (98.958) +2022-11-14 14:23:44,995 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0801) Prec@1 84.000 (86.500) Prec@5 100.000 (98.972) +2022-11-14 14:23:45,005 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0797) Prec@1 92.000 (86.575) Prec@5 100.000 (98.986) +2022-11-14 14:23:45,018 Test: [73/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0795) Prec@1 91.000 (86.635) Prec@5 100.000 (99.000) +2022-11-14 14:23:45,031 Test: [74/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0798) Prec@1 82.000 (86.573) Prec@5 99.000 (99.000) +2022-11-14 14:23:45,043 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0795) Prec@1 90.000 (86.618) Prec@5 99.000 (99.000) +2022-11-14 14:23:45,055 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0795) Prec@1 87.000 (86.623) Prec@5 98.000 (98.987) +2022-11-14 14:23:45,066 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0798) Prec@1 84.000 (86.590) Prec@5 97.000 (98.962) +2022-11-14 14:23:45,076 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0796) Prec@1 90.000 (86.633) Prec@5 100.000 (98.975) +2022-11-14 14:23:45,085 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0796) Prec@1 86.000 (86.625) Prec@5 99.000 (98.975) +2022-11-14 14:23:45,096 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0797) Prec@1 85.000 (86.605) Prec@5 99.000 (98.975) +2022-11-14 14:23:45,106 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0798) Prec@1 87.000 (86.610) Prec@5 99.000 (98.976) +2022-11-14 14:23:45,116 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0800) Prec@1 84.000 (86.578) Prec@5 99.000 (98.976) +2022-11-14 14:23:45,127 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0798) Prec@1 89.000 (86.607) Prec@5 100.000 (98.988) +2022-11-14 14:23:45,141 Test: [84/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0798) Prec@1 84.000 (86.576) Prec@5 100.000 (99.000) +2022-11-14 14:23:45,151 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0799) Prec@1 87.000 (86.581) Prec@5 100.000 (99.012) +2022-11-14 14:23:45,163 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0800) Prec@1 86.000 (86.575) Prec@5 99.000 (99.011) +2022-11-14 14:23:45,173 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0801) Prec@1 85.000 (86.557) Prec@5 99.000 (99.011) +2022-11-14 14:23:45,184 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0800) Prec@1 91.000 (86.607) Prec@5 99.000 (99.011) +2022-11-14 14:23:45,194 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0799) Prec@1 89.000 (86.633) Prec@5 100.000 (99.022) +2022-11-14 14:23:45,205 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0797) Prec@1 90.000 (86.670) Prec@5 100.000 (99.033) +2022-11-14 14:23:45,215 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0793) Prec@1 91.000 (86.717) Prec@5 100.000 (99.043) +2022-11-14 14:23:45,226 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0794) Prec@1 85.000 (86.699) Prec@5 100.000 (99.054) +2022-11-14 14:23:45,236 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0793) Prec@1 86.000 (86.691) Prec@5 97.000 (99.032) +2022-11-14 14:23:45,247 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0793) Prec@1 89.000 (86.716) Prec@5 99.000 (99.032) +2022-11-14 14:23:45,258 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0792) Prec@1 91.000 (86.760) Prec@5 99.000 (99.031) +2022-11-14 14:23:45,270 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0790) Prec@1 88.000 (86.773) Prec@5 98.000 (99.021) +2022-11-14 14:23:45,280 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0793) Prec@1 83.000 (86.735) Prec@5 99.000 (99.020) +2022-11-14 14:23:45,290 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0795) Prec@1 85.000 (86.717) Prec@5 99.000 (99.020) +2022-11-14 14:23:45,300 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0794) Prec@1 88.000 (86.730) Prec@5 100.000 (99.030) +2022-11-14 14:23:45,362 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:23:45,687 Epoch: [191][0/500] Time 0.026 (0.026) Data 0.237 (0.237) Loss 0.0304 (0.0304) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:23:45,908 Epoch: [191][10/500] Time 0.019 (0.020) Data 0.002 (0.023) Loss 0.0480 (0.0392) Prec@1 90.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:23:46,128 Epoch: [191][20/500] Time 0.020 (0.020) Data 0.002 (0.013) Loss 0.0292 (0.0358) Prec@1 95.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 14:23:46,400 Epoch: [191][30/500] Time 0.024 (0.021) Data 0.002 (0.010) Loss 0.0397 (0.0368) Prec@1 94.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:23:46,682 Epoch: [191][40/500] Time 0.027 (0.022) Data 0.001 (0.008) Loss 0.0242 (0.0343) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:23:47,218 Epoch: [191][50/500] Time 0.043 (0.027) Data 0.002 (0.006) Loss 0.0291 (0.0334) Prec@1 97.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 14:23:47,714 Epoch: [191][60/500] Time 0.043 (0.030) Data 0.002 (0.006) Loss 0.0536 (0.0363) Prec@1 92.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 14:23:48,282 Epoch: [191][70/500] Time 0.083 (0.033) Data 0.002 (0.005) Loss 0.0256 (0.0350) Prec@1 95.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 14:23:48,763 Epoch: [191][80/500] Time 0.044 (0.034) Data 0.002 (0.005) Loss 0.0383 (0.0353) Prec@1 93.000 (94.000) Prec@5 99.000 (99.778) +2022-11-14 14:23:49,286 Epoch: [191][90/500] Time 0.044 (0.036) Data 0.002 (0.005) Loss 0.0441 (0.0362) Prec@1 92.000 (93.800) Prec@5 99.000 (99.700) +2022-11-14 14:23:49,799 Epoch: [191][100/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0233 (0.0350) Prec@1 97.000 (94.091) Prec@5 100.000 (99.727) +2022-11-14 14:23:50,290 Epoch: [191][110/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0363 (0.0351) Prec@1 94.000 (94.083) Prec@5 100.000 (99.750) +2022-11-14 14:23:50,814 Epoch: [191][120/500] Time 0.046 (0.038) Data 0.002 (0.004) Loss 0.0244 (0.0343) Prec@1 97.000 (94.308) Prec@5 100.000 (99.769) +2022-11-14 14:23:51,337 Epoch: [191][130/500] Time 0.046 (0.039) Data 0.002 (0.004) Loss 0.0460 (0.0352) Prec@1 92.000 (94.143) Prec@5 100.000 (99.786) +2022-11-14 14:23:51,813 Epoch: [191][140/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0777 (0.0380) Prec@1 87.000 (93.667) Prec@5 99.000 (99.733) +2022-11-14 14:23:52,348 Epoch: [191][150/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0555 (0.0391) Prec@1 91.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:23:52,828 Epoch: [191][160/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0465 (0.0395) Prec@1 90.000 (93.294) Prec@5 99.000 (99.706) +2022-11-14 14:23:53,368 Epoch: [191][170/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.0290 (0.0389) Prec@1 96.000 (93.444) Prec@5 99.000 (99.667) +2022-11-14 14:23:54,051 Epoch: [191][180/500] Time 0.071 (0.041) Data 0.002 (0.003) Loss 0.0464 (0.0393) Prec@1 91.000 (93.316) Prec@5 100.000 (99.684) +2022-11-14 14:23:54,835 Epoch: [191][190/500] Time 0.078 (0.043) Data 0.002 (0.003) Loss 0.0198 (0.0384) Prec@1 97.000 (93.500) Prec@5 100.000 (99.700) +2022-11-14 14:23:55,323 Epoch: [191][200/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0534 (0.0391) Prec@1 92.000 (93.429) Prec@5 99.000 (99.667) +2022-11-14 14:23:55,845 Epoch: [191][210/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0577 (0.0399) Prec@1 91.000 (93.318) Prec@5 100.000 (99.682) +2022-11-14 14:23:56,395 Epoch: [191][220/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0312 (0.0395) Prec@1 97.000 (93.478) Prec@5 100.000 (99.696) +2022-11-14 14:23:56,897 Epoch: [191][230/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0522 (0.0401) Prec@1 92.000 (93.417) Prec@5 100.000 (99.708) +2022-11-14 14:23:57,377 Epoch: [191][240/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0482 (0.0404) Prec@1 90.000 (93.280) Prec@5 100.000 (99.720) +2022-11-14 14:23:57,847 Epoch: [191][250/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0367 (0.0402) Prec@1 92.000 (93.231) Prec@5 100.000 (99.731) +2022-11-14 14:23:58,327 Epoch: [191][260/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0254 (0.0397) Prec@1 97.000 (93.370) Prec@5 100.000 (99.741) +2022-11-14 14:23:58,797 Epoch: [191][270/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0487 (0.0400) Prec@1 90.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:23:59,277 Epoch: [191][280/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0381 (0.0400) Prec@1 93.000 (93.241) Prec@5 100.000 (99.759) +2022-11-14 14:23:59,749 Epoch: [191][290/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0354 (0.0398) Prec@1 93.000 (93.233) Prec@5 100.000 (99.767) +2022-11-14 14:24:00,235 Epoch: [191][300/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0512 (0.0402) Prec@1 93.000 (93.226) Prec@5 99.000 (99.742) +2022-11-14 14:24:00,707 Epoch: [191][310/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0507 (0.0405) Prec@1 92.000 (93.188) Prec@5 99.000 (99.719) +2022-11-14 14:24:01,187 Epoch: [191][320/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0335 (0.0403) Prec@1 95.000 (93.242) Prec@5 100.000 (99.727) +2022-11-14 14:24:01,693 Epoch: [191][330/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0360 (0.0402) Prec@1 94.000 (93.265) Prec@5 100.000 (99.735) +2022-11-14 14:24:02,209 Epoch: [191][340/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0561 (0.0406) Prec@1 92.000 (93.229) Prec@5 98.000 (99.686) +2022-11-14 14:24:02,691 Epoch: [191][350/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0263 (0.0402) Prec@1 96.000 (93.306) Prec@5 99.000 (99.667) +2022-11-14 14:24:03,179 Epoch: [191][360/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0211 (0.0397) Prec@1 97.000 (93.405) Prec@5 100.000 (99.676) +2022-11-14 14:24:03,662 Epoch: [191][370/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0771 (0.0407) Prec@1 89.000 (93.289) Prec@5 98.000 (99.632) +2022-11-14 14:24:04,154 Epoch: [191][380/500] Time 0.040 (0.043) Data 0.003 (0.003) Loss 0.0453 (0.0408) Prec@1 92.000 (93.256) Prec@5 100.000 (99.641) +2022-11-14 14:24:04,634 Epoch: [191][390/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0369 (0.0407) Prec@1 95.000 (93.300) Prec@5 100.000 (99.650) +2022-11-14 14:24:05,124 Epoch: [191][400/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0266 (0.0404) Prec@1 96.000 (93.366) Prec@5 100.000 (99.659) +2022-11-14 14:24:05,684 Epoch: [191][410/500] Time 0.078 (0.043) Data 0.002 (0.003) Loss 0.0344 (0.0402) Prec@1 95.000 (93.405) Prec@5 100.000 (99.667) +2022-11-14 14:24:06,283 Epoch: [191][420/500] Time 0.078 (0.044) Data 0.002 (0.003) Loss 0.0505 (0.0405) Prec@1 91.000 (93.349) Prec@5 100.000 (99.674) +2022-11-14 14:24:06,749 Epoch: [191][430/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0421 (0.0405) Prec@1 93.000 (93.341) Prec@5 98.000 (99.636) +2022-11-14 14:24:07,073 Epoch: [191][440/500] Time 0.029 (0.043) Data 0.002 (0.003) Loss 0.0415 (0.0405) Prec@1 92.000 (93.311) Prec@5 100.000 (99.644) +2022-11-14 14:24:07,476 Epoch: [191][450/500] Time 0.036 (0.043) Data 0.002 (0.003) Loss 0.0469 (0.0407) Prec@1 90.000 (93.239) Prec@5 100.000 (99.652) +2022-11-14 14:24:07,876 Epoch: [191][460/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0622 (0.0411) Prec@1 89.000 (93.149) Prec@5 99.000 (99.638) +2022-11-14 14:24:08,213 Epoch: [191][470/500] Time 0.026 (0.043) Data 0.002 (0.003) Loss 0.0357 (0.0410) Prec@1 94.000 (93.167) Prec@5 100.000 (99.646) +2022-11-14 14:24:08,540 Epoch: [191][480/500] Time 0.038 (0.042) Data 0.002 (0.002) Loss 0.0323 (0.0408) Prec@1 94.000 (93.184) Prec@5 100.000 (99.653) +2022-11-14 14:24:08,863 Epoch: [191][490/500] Time 0.038 (0.042) Data 0.002 (0.002) Loss 0.0444 (0.0409) Prec@1 94.000 (93.200) Prec@5 100.000 (99.660) +2022-11-14 14:24:09,242 Epoch: [191][499/500] Time 0.042 (0.042) Data 0.002 (0.002) Loss 0.0362 (0.0408) Prec@1 95.000 (93.235) Prec@5 100.000 (99.667) +2022-11-14 14:24:09,546 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0641 (0.0641) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:09,557 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0703) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:24:09,567 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0719) Prec@1 87.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 14:24:09,580 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0796) Prec@1 85.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:24:09,590 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0803) Prec@1 87.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:24:09,600 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0744) Prec@1 92.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:09,610 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0738) Prec@1 89.000 (88.143) Prec@5 99.000 (99.571) +2022-11-14 14:24:09,622 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0777) Prec@1 80.000 (87.125) Prec@5 100.000 (99.625) +2022-11-14 14:24:09,631 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0784) Prec@1 86.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:09,642 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0778) Prec@1 87.000 (87.000) Prec@5 98.000 (99.500) +2022-11-14 14:24:09,653 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0773) Prec@1 89.000 (87.182) Prec@5 100.000 (99.545) +2022-11-14 14:24:09,667 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0773) Prec@1 88.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:24:09,682 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0756) Prec@1 89.000 (87.385) Prec@5 100.000 (99.538) +2022-11-14 14:24:09,695 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0758) Prec@1 88.000 (87.429) Prec@5 100.000 (99.571) +2022-11-14 14:24:09,708 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0770) Prec@1 84.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:24:09,721 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0771) Prec@1 84.000 (87.000) Prec@5 98.000 (99.500) +2022-11-14 14:24:09,735 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0419 (0.0750) Prec@1 93.000 (87.353) Prec@5 98.000 (99.412) +2022-11-14 14:24:09,748 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0767) Prec@1 84.000 (87.167) Prec@5 100.000 (99.444) +2022-11-14 14:24:09,761 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0766) Prec@1 89.000 (87.263) Prec@5 98.000 (99.368) +2022-11-14 14:24:09,775 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0769) Prec@1 88.000 (87.300) Prec@5 98.000 (99.300) +2022-11-14 14:24:09,788 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0783) Prec@1 84.000 (87.143) Prec@5 99.000 (99.286) +2022-11-14 14:24:09,799 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0785) Prec@1 85.000 (87.045) Prec@5 99.000 (99.273) +2022-11-14 14:24:09,813 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0794) Prec@1 82.000 (86.826) Prec@5 96.000 (99.130) +2022-11-14 14:24:09,827 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0792) Prec@1 86.000 (86.792) Prec@5 100.000 (99.167) +2022-11-14 14:24:09,841 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0797) Prec@1 89.000 (86.880) Prec@5 99.000 (99.160) +2022-11-14 14:24:09,854 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0804) Prec@1 83.000 (86.731) Prec@5 98.000 (99.115) +2022-11-14 14:24:09,867 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0798) Prec@1 91.000 (86.889) Prec@5 100.000 (99.148) +2022-11-14 14:24:09,881 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0792) Prec@1 92.000 (87.071) Prec@5 100.000 (99.179) +2022-11-14 14:24:09,894 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0784) Prec@1 91.000 (87.207) Prec@5 100.000 (99.207) +2022-11-14 14:24:09,906 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0786) Prec@1 88.000 (87.233) Prec@5 98.000 (99.167) +2022-11-14 14:24:09,919 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0790) Prec@1 84.000 (87.129) Prec@5 98.000 (99.129) +2022-11-14 14:24:09,930 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0788) Prec@1 89.000 (87.188) Prec@5 99.000 (99.125) +2022-11-14 14:24:09,945 Test: [32/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0792) Prec@1 85.000 (87.121) Prec@5 99.000 (99.121) +2022-11-14 14:24:09,960 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0799) Prec@1 82.000 (86.971) Prec@5 99.000 (99.118) +2022-11-14 14:24:09,973 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0798) Prec@1 89.000 (87.029) Prec@5 98.000 (99.086) +2022-11-14 14:24:09,987 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0801) Prec@1 84.000 (86.944) Prec@5 99.000 (99.083) +2022-11-14 14:24:10,001 Test: [36/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0798) Prec@1 88.000 (86.973) Prec@5 99.000 (99.081) +2022-11-14 14:24:10,015 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0799) Prec@1 85.000 (86.921) Prec@5 99.000 (99.079) +2022-11-14 14:24:10,028 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0793) Prec@1 92.000 (87.051) Prec@5 98.000 (99.051) +2022-11-14 14:24:10,041 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0789) Prec@1 88.000 (87.075) Prec@5 100.000 (99.075) +2022-11-14 14:24:10,056 Test: [40/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0794) Prec@1 84.000 (87.000) Prec@5 98.000 (99.049) +2022-11-14 14:24:10,070 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0793) Prec@1 88.000 (87.024) Prec@5 98.000 (99.024) +2022-11-14 14:24:10,083 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0785) Prec@1 91.000 (87.116) Prec@5 100.000 (99.047) +2022-11-14 14:24:10,096 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0786) Prec@1 89.000 (87.159) Prec@5 100.000 (99.068) +2022-11-14 14:24:10,110 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0783) Prec@1 88.000 (87.178) Prec@5 99.000 (99.067) +2022-11-14 14:24:10,124 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0786) Prec@1 87.000 (87.174) Prec@5 99.000 (99.065) +2022-11-14 14:24:10,138 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0784) Prec@1 87.000 (87.170) Prec@5 100.000 (99.085) +2022-11-14 14:24:10,152 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.0791) Prec@1 82.000 (87.062) Prec@5 98.000 (99.062) +2022-11-14 14:24:10,166 Test: [48/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0788) Prec@1 87.000 (87.061) Prec@5 100.000 (99.082) +2022-11-14 14:24:10,180 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.0796) Prec@1 80.000 (86.920) Prec@5 100.000 (99.100) +2022-11-14 14:24:10,194 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0799) Prec@1 86.000 (86.902) Prec@5 98.000 (99.078) +2022-11-14 14:24:10,207 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0796) Prec@1 91.000 (86.981) Prec@5 99.000 (99.077) +2022-11-14 14:24:10,221 Test: [52/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0794) Prec@1 89.000 (87.019) Prec@5 100.000 (99.094) +2022-11-14 14:24:10,235 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0797) Prec@1 86.000 (87.000) Prec@5 100.000 (99.111) +2022-11-14 14:24:10,249 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0797) Prec@1 90.000 (87.055) Prec@5 100.000 (99.127) +2022-11-14 14:24:10,262 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0796) Prec@1 90.000 (87.107) Prec@5 99.000 (99.125) +2022-11-14 14:24:10,277 Test: [56/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0794) Prec@1 88.000 (87.123) Prec@5 100.000 (99.140) +2022-11-14 14:24:10,289 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0792) Prec@1 91.000 (87.190) Prec@5 100.000 (99.155) +2022-11-14 14:24:10,301 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0793) Prec@1 84.000 (87.136) Prec@5 99.000 (99.153) +2022-11-14 14:24:10,311 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0795) Prec@1 85.000 (87.100) Prec@5 100.000 (99.167) +2022-11-14 14:24:10,326 Test: [60/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0800) Prec@1 84.000 (87.049) Prec@5 98.000 (99.148) +2022-11-14 14:24:10,341 Test: [61/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0796) Prec@1 91.000 (87.113) Prec@5 99.000 (99.145) +2022-11-14 14:24:10,354 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0791) Prec@1 92.000 (87.190) Prec@5 100.000 (99.159) +2022-11-14 14:24:10,367 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0787) Prec@1 92.000 (87.266) Prec@5 100.000 (99.172) +2022-11-14 14:24:10,381 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0787) Prec@1 89.000 (87.292) Prec@5 99.000 (99.169) +2022-11-14 14:24:10,394 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0790) Prec@1 83.000 (87.227) Prec@5 99.000 (99.167) +2022-11-14 14:24:10,406 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0785) Prec@1 92.000 (87.299) Prec@5 99.000 (99.164) +2022-11-14 14:24:10,417 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0784) Prec@1 90.000 (87.338) Prec@5 98.000 (99.147) +2022-11-14 14:24:10,431 Test: [68/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0783) Prec@1 87.000 (87.333) Prec@5 100.000 (99.159) +2022-11-14 14:24:10,443 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0783) Prec@1 88.000 (87.343) Prec@5 97.000 (99.129) +2022-11-14 14:24:10,454 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0785) Prec@1 86.000 (87.324) Prec@5 98.000 (99.113) +2022-11-14 14:24:10,465 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0786) Prec@1 86.000 (87.306) Prec@5 100.000 (99.125) +2022-11-14 14:24:10,478 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0784) Prec@1 90.000 (87.342) Prec@5 99.000 (99.123) +2022-11-14 14:24:10,491 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0781) Prec@1 90.000 (87.378) Prec@5 100.000 (99.135) +2022-11-14 14:24:10,505 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0781) Prec@1 88.000 (87.387) Prec@5 100.000 (99.147) +2022-11-14 14:24:10,518 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0779) Prec@1 89.000 (87.408) Prec@5 100.000 (99.158) +2022-11-14 14:24:10,530 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0777) Prec@1 90.000 (87.442) Prec@5 97.000 (99.130) +2022-11-14 14:24:10,541 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0779) Prec@1 84.000 (87.397) Prec@5 98.000 (99.115) +2022-11-14 14:24:10,554 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0778) Prec@1 90.000 (87.430) Prec@5 100.000 (99.127) +2022-11-14 14:24:10,566 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0778) Prec@1 86.000 (87.412) Prec@5 99.000 (99.125) +2022-11-14 14:24:10,577 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0780) Prec@1 85.000 (87.383) Prec@5 99.000 (99.123) +2022-11-14 14:24:10,589 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0782) Prec@1 86.000 (87.366) Prec@5 99.000 (99.122) +2022-11-14 14:24:10,602 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0781) Prec@1 86.000 (87.349) Prec@5 100.000 (99.133) +2022-11-14 14:24:10,615 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0781) Prec@1 85.000 (87.321) Prec@5 99.000 (99.131) +2022-11-14 14:24:10,627 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0782) Prec@1 87.000 (87.318) Prec@5 100.000 (99.141) +2022-11-14 14:24:10,639 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0784) Prec@1 85.000 (87.291) Prec@5 98.000 (99.128) +2022-11-14 14:24:10,654 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0781) Prec@1 91.000 (87.333) Prec@5 100.000 (99.138) +2022-11-14 14:24:10,668 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0781) Prec@1 86.000 (87.318) Prec@5 100.000 (99.148) +2022-11-14 14:24:10,682 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0778) Prec@1 90.000 (87.348) Prec@5 100.000 (99.157) +2022-11-14 14:24:10,693 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0780) Prec@1 84.000 (87.311) Prec@5 99.000 (99.156) +2022-11-14 14:24:10,708 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0780) Prec@1 90.000 (87.341) Prec@5 100.000 (99.165) +2022-11-14 14:24:10,722 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0777) Prec@1 90.000 (87.370) Prec@5 100.000 (99.174) +2022-11-14 14:24:10,735 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0775) Prec@1 90.000 (87.398) Prec@5 100.000 (99.183) +2022-11-14 14:24:10,749 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0776) Prec@1 87.000 (87.394) Prec@5 100.000 (99.191) +2022-11-14 14:24:10,762 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.0779) Prec@1 82.000 (87.337) Prec@5 98.000 (99.179) +2022-11-14 14:24:10,776 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0776) Prec@1 91.000 (87.375) Prec@5 100.000 (99.188) +2022-11-14 14:24:10,788 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0774) Prec@1 93.000 (87.433) Prec@5 98.000 (99.175) +2022-11-14 14:24:10,799 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0774) Prec@1 85.000 (87.408) Prec@5 99.000 (99.173) +2022-11-14 14:24:10,809 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0775) Prec@1 86.000 (87.394) Prec@5 100.000 (99.182) +2022-11-14 14:24:10,821 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0774) Prec@1 89.000 (87.410) Prec@5 98.000 (99.170) +2022-11-14 14:24:10,891 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:24:11,239 Epoch: [192][0/500] Time 0.023 (0.023) Data 0.263 (0.263) Loss 0.0250 (0.0250) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:11,489 Epoch: [192][10/500] Time 0.024 (0.022) Data 0.002 (0.026) Loss 0.0345 (0.0298) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:11,745 Epoch: [192][20/500] Time 0.021 (0.023) Data 0.002 (0.014) Loss 0.0195 (0.0264) Prec@1 99.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 14:24:11,964 Epoch: [192][30/500] Time 0.025 (0.021) Data 0.002 (0.010) Loss 0.0465 (0.0314) Prec@1 91.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:12,242 Epoch: [192][40/500] Time 0.025 (0.022) Data 0.002 (0.008) Loss 0.0589 (0.0369) Prec@1 88.000 (93.600) Prec@5 98.000 (99.600) +2022-11-14 14:24:12,531 Epoch: [192][50/500] Time 0.033 (0.023) Data 0.002 (0.007) Loss 0.0283 (0.0355) Prec@1 96.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:12,832 Epoch: [192][60/500] Time 0.022 (0.024) Data 0.002 (0.006) Loss 0.0430 (0.0366) Prec@1 92.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 14:24:13,109 Epoch: [192][70/500] Time 0.024 (0.024) Data 0.002 (0.005) Loss 0.0470 (0.0379) Prec@1 92.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:24:13,421 Epoch: [192][80/500] Time 0.021 (0.024) Data 0.002 (0.005) Loss 0.0814 (0.0427) Prec@1 86.000 (92.667) Prec@5 98.000 (99.556) +2022-11-14 14:24:13,850 Epoch: [192][90/500] Time 0.043 (0.026) Data 0.002 (0.005) Loss 0.0431 (0.0427) Prec@1 93.000 (92.700) Prec@5 100.000 (99.600) +2022-11-14 14:24:14,326 Epoch: [192][100/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0316 (0.0417) Prec@1 96.000 (93.000) Prec@5 100.000 (99.636) +2022-11-14 14:24:14,789 Epoch: [192][110/500] Time 0.043 (0.029) Data 0.002 (0.004) Loss 0.0479 (0.0422) Prec@1 91.000 (92.833) Prec@5 100.000 (99.667) +2022-11-14 14:24:15,262 Epoch: [192][120/500] Time 0.044 (0.030) Data 0.002 (0.004) Loss 0.0360 (0.0418) Prec@1 94.000 (92.923) Prec@5 100.000 (99.692) +2022-11-14 14:24:15,843 Epoch: [192][130/500] Time 0.072 (0.031) Data 0.002 (0.004) Loss 0.0376 (0.0415) Prec@1 95.000 (93.071) Prec@5 100.000 (99.714) +2022-11-14 14:24:16,555 Epoch: [192][140/500] Time 0.065 (0.034) Data 0.002 (0.004) Loss 0.0294 (0.0407) Prec@1 96.000 (93.267) Prec@5 100.000 (99.733) +2022-11-14 14:24:17,073 Epoch: [192][150/500] Time 0.044 (0.034) Data 0.002 (0.004) Loss 0.0513 (0.0413) Prec@1 89.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:24:17,639 Epoch: [192][160/500] Time 0.064 (0.035) Data 0.002 (0.003) Loss 0.0579 (0.0423) Prec@1 90.000 (92.824) Prec@5 100.000 (99.765) +2022-11-14 14:24:18,209 Epoch: [192][170/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.0456 (0.0425) Prec@1 93.000 (92.833) Prec@5 99.000 (99.722) +2022-11-14 14:24:18,695 Epoch: [192][180/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0391 (0.0423) Prec@1 94.000 (92.895) Prec@5 99.000 (99.684) +2022-11-14 14:24:19,386 Epoch: [192][190/500] Time 0.072 (0.038) Data 0.002 (0.003) Loss 0.0545 (0.0429) Prec@1 90.000 (92.750) Prec@5 99.000 (99.650) +2022-11-14 14:24:19,863 Epoch: [192][200/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0491 (0.0432) Prec@1 91.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:24:20,402 Epoch: [192][210/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0348 (0.0428) Prec@1 94.000 (92.727) Prec@5 100.000 (99.682) +2022-11-14 14:24:20,873 Epoch: [192][220/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0444 (0.0429) Prec@1 91.000 (92.652) Prec@5 100.000 (99.696) +2022-11-14 14:24:21,357 Epoch: [192][230/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0285 (0.0423) Prec@1 96.000 (92.792) Prec@5 100.000 (99.708) +2022-11-14 14:24:21,821 Epoch: [192][240/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0514 (0.0427) Prec@1 93.000 (92.800) Prec@5 100.000 (99.720) +2022-11-14 14:24:22,297 Epoch: [192][250/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0326 (0.0423) Prec@1 96.000 (92.923) Prec@5 100.000 (99.731) +2022-11-14 14:24:22,770 Epoch: [192][260/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0428 (0.0423) Prec@1 92.000 (92.889) Prec@5 100.000 (99.741) +2022-11-14 14:24:23,262 Epoch: [192][270/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0353 (0.0420) Prec@1 93.000 (92.893) Prec@5 100.000 (99.750) +2022-11-14 14:24:23,874 Epoch: [192][280/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0491 (0.0423) Prec@1 94.000 (92.931) Prec@5 100.000 (99.759) +2022-11-14 14:24:24,370 Epoch: [192][290/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0455 (0.0424) Prec@1 92.000 (92.900) Prec@5 100.000 (99.767) +2022-11-14 14:24:24,843 Epoch: [192][300/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0439 (0.0424) Prec@1 93.000 (92.903) Prec@5 100.000 (99.774) +2022-11-14 14:24:25,369 Epoch: [192][310/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0506 (0.0427) Prec@1 93.000 (92.906) Prec@5 100.000 (99.781) +2022-11-14 14:24:25,863 Epoch: [192][320/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0330 (0.0424) Prec@1 95.000 (92.970) Prec@5 100.000 (99.788) +2022-11-14 14:24:26,340 Epoch: [192][330/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0382 (0.0423) Prec@1 94.000 (93.000) Prec@5 100.000 (99.794) +2022-11-14 14:24:26,821 Epoch: [192][340/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0429 (0.0423) Prec@1 93.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:24:27,327 Epoch: [192][350/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0352 (0.0421) Prec@1 95.000 (93.056) Prec@5 98.000 (99.750) +2022-11-14 14:24:27,801 Epoch: [192][360/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0412 (0.0421) Prec@1 91.000 (93.000) Prec@5 99.000 (99.730) +2022-11-14 14:24:28,298 Epoch: [192][370/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.0554 (0.0424) Prec@1 93.000 (93.000) Prec@5 100.000 (99.737) +2022-11-14 14:24:28,770 Epoch: [192][380/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0502 (0.0426) Prec@1 93.000 (93.000) Prec@5 99.000 (99.718) +2022-11-14 14:24:29,270 Epoch: [192][390/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0371 (0.0425) Prec@1 93.000 (93.000) Prec@5 100.000 (99.725) +2022-11-14 14:24:29,743 Epoch: [192][400/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0387 (0.0424) Prec@1 93.000 (93.000) Prec@5 100.000 (99.732) +2022-11-14 14:24:30,238 Epoch: [192][410/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0443 (0.0425) Prec@1 92.000 (92.976) Prec@5 100.000 (99.738) +2022-11-14 14:24:30,757 Epoch: [192][420/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0502 (0.0426) Prec@1 90.000 (92.907) Prec@5 99.000 (99.721) +2022-11-14 14:24:31,252 Epoch: [192][430/500] Time 0.046 (0.042) Data 0.002 (0.003) Loss 0.0325 (0.0424) Prec@1 96.000 (92.977) Prec@5 99.000 (99.705) +2022-11-14 14:24:31,759 Epoch: [192][440/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0481 (0.0425) Prec@1 93.000 (92.978) Prec@5 99.000 (99.689) +2022-11-14 14:24:32,244 Epoch: [192][450/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0319 (0.0423) Prec@1 94.000 (93.000) Prec@5 100.000 (99.696) +2022-11-14 14:24:32,717 Epoch: [192][460/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0657 (0.0428) Prec@1 87.000 (92.872) Prec@5 100.000 (99.702) +2022-11-14 14:24:33,203 Epoch: [192][470/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0416 (0.0428) Prec@1 94.000 (92.896) Prec@5 100.000 (99.708) +2022-11-14 14:24:33,666 Epoch: [192][480/500] Time 0.050 (0.042) Data 0.002 (0.002) Loss 0.0525 (0.0430) Prec@1 91.000 (92.857) Prec@5 100.000 (99.714) +2022-11-14 14:24:33,995 Epoch: [192][490/500] Time 0.033 (0.041) Data 0.002 (0.002) Loss 0.0673 (0.0435) Prec@1 88.000 (92.760) Prec@5 100.000 (99.720) +2022-11-14 14:24:34,287 Epoch: [192][499/500] Time 0.026 (0.041) Data 0.002 (0.002) Loss 0.0364 (0.0433) Prec@1 94.000 (92.784) Prec@5 100.000 (99.725) +2022-11-14 14:24:34,572 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0713 (0.0713) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:24:34,584 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0637) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:24:34,594 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0684) Prec@1 86.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:34,605 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0667) Prec@1 89.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 14:24:34,613 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0636) Prec@1 92.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 14:24:34,621 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0412 (0.0599) Prec@1 94.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 14:24:34,628 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0612) Prec@1 90.000 (89.857) Prec@5 100.000 (99.714) +2022-11-14 14:24:34,639 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0634) Prec@1 86.000 (89.375) Prec@5 99.000 (99.625) +2022-11-14 14:24:34,648 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0656) Prec@1 87.000 (89.111) Prec@5 99.000 (99.556) +2022-11-14 14:24:34,657 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0665) Prec@1 86.000 (88.800) Prec@5 98.000 (99.400) +2022-11-14 14:24:34,667 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0671) Prec@1 87.000 (88.636) Prec@5 100.000 (99.455) +2022-11-14 14:24:34,677 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0698) Prec@1 84.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 14:24:34,686 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0685) Prec@1 93.000 (88.615) Prec@5 99.000 (99.462) +2022-11-14 14:24:34,697 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0689) Prec@1 90.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 14:24:34,707 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0694) Prec@1 88.000 (88.667) Prec@5 99.000 (99.400) +2022-11-14 14:24:34,717 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0688) Prec@1 89.000 (88.688) Prec@5 99.000 (99.375) +2022-11-14 14:24:34,727 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0677) Prec@1 93.000 (88.941) Prec@5 98.000 (99.294) +2022-11-14 14:24:34,737 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0691) Prec@1 88.000 (88.889) Prec@5 100.000 (99.333) +2022-11-14 14:24:34,746 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0706) Prec@1 83.000 (88.579) Prec@5 97.000 (99.211) +2022-11-14 14:24:34,756 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.0728) Prec@1 81.000 (88.200) Prec@5 95.000 (99.000) +2022-11-14 14:24:34,766 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0734) Prec@1 87.000 (88.143) Prec@5 100.000 (99.048) +2022-11-14 14:24:34,776 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0742) Prec@1 87.000 (88.091) Prec@5 97.000 (98.955) +2022-11-14 14:24:34,785 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0754) Prec@1 83.000 (87.870) Prec@5 98.000 (98.913) +2022-11-14 14:24:34,793 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0752) Prec@1 88.000 (87.875) Prec@5 99.000 (98.917) +2022-11-14 14:24:34,801 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0765) Prec@1 84.000 (87.720) Prec@5 100.000 (98.960) +2022-11-14 14:24:34,808 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0764) Prec@1 89.000 (87.769) Prec@5 99.000 (98.962) +2022-11-14 14:24:34,817 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0760) Prec@1 88.000 (87.778) Prec@5 100.000 (99.000) +2022-11-14 14:24:34,826 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0755) Prec@1 88.000 (87.786) Prec@5 100.000 (99.036) +2022-11-14 14:24:34,835 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0754) Prec@1 90.000 (87.862) Prec@5 98.000 (99.000) +2022-11-14 14:24:34,844 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0756) Prec@1 86.000 (87.800) Prec@5 99.000 (99.000) +2022-11-14 14:24:34,854 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0752) Prec@1 91.000 (87.903) Prec@5 98.000 (98.968) +2022-11-14 14:24:34,863 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0754) Prec@1 88.000 (87.906) Prec@5 100.000 (99.000) +2022-11-14 14:24:34,872 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0755) Prec@1 86.000 (87.848) Prec@5 100.000 (99.030) +2022-11-14 14:24:34,882 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0764) Prec@1 80.000 (87.618) Prec@5 100.000 (99.059) +2022-11-14 14:24:34,891 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0768) Prec@1 87.000 (87.600) Prec@5 97.000 (99.000) +2022-11-14 14:24:34,900 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0765) Prec@1 91.000 (87.694) Prec@5 100.000 (99.028) +2022-11-14 14:24:34,909 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0765) Prec@1 89.000 (87.730) Prec@5 100.000 (99.054) +2022-11-14 14:24:34,919 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0772) Prec@1 82.000 (87.579) Prec@5 100.000 (99.079) +2022-11-14 14:24:34,928 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0767) Prec@1 93.000 (87.718) Prec@5 100.000 (99.103) +2022-11-14 14:24:34,938 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0765) Prec@1 89.000 (87.750) Prec@5 99.000 (99.100) +2022-11-14 14:24:34,948 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0773) Prec@1 83.000 (87.634) Prec@5 98.000 (99.073) +2022-11-14 14:24:34,958 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0775) Prec@1 83.000 (87.524) Prec@5 100.000 (99.095) +2022-11-14 14:24:34,967 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0767) Prec@1 92.000 (87.628) Prec@5 100.000 (99.116) +2022-11-14 14:24:34,976 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0766) Prec@1 88.000 (87.636) Prec@5 99.000 (99.114) +2022-11-14 14:24:34,986 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0765) Prec@1 90.000 (87.689) Prec@5 100.000 (99.133) +2022-11-14 14:24:34,995 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1192 (0.0774) Prec@1 82.000 (87.565) Prec@5 100.000 (99.152) +2022-11-14 14:24:35,004 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0773) Prec@1 89.000 (87.596) Prec@5 99.000 (99.149) +2022-11-14 14:24:35,013 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0778) Prec@1 83.000 (87.500) Prec@5 98.000 (99.125) +2022-11-14 14:24:35,023 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0771) Prec@1 92.000 (87.592) Prec@5 100.000 (99.143) +2022-11-14 14:24:35,032 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0777) Prec@1 82.000 (87.480) Prec@5 99.000 (99.140) +2022-11-14 14:24:35,040 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0774) Prec@1 90.000 (87.529) Prec@5 100.000 (99.157) +2022-11-14 14:24:35,050 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0775) Prec@1 85.000 (87.481) Prec@5 100.000 (99.173) +2022-11-14 14:24:35,061 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0772) Prec@1 91.000 (87.547) Prec@5 99.000 (99.170) +2022-11-14 14:24:35,072 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0773) Prec@1 87.000 (87.537) Prec@5 99.000 (99.167) +2022-11-14 14:24:35,080 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0772) Prec@1 87.000 (87.527) Prec@5 100.000 (99.182) +2022-11-14 14:24:35,088 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0771) Prec@1 89.000 (87.554) Prec@5 100.000 (99.196) +2022-11-14 14:24:35,098 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0770) Prec@1 86.000 (87.526) Prec@5 100.000 (99.211) +2022-11-14 14:24:35,108 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0769) Prec@1 89.000 (87.552) Prec@5 98.000 (99.190) +2022-11-14 14:24:35,118 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0770) Prec@1 86.000 (87.525) Prec@5 99.000 (99.186) +2022-11-14 14:24:35,127 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0770) Prec@1 89.000 (87.550) Prec@5 100.000 (99.200) +2022-11-14 14:24:35,138 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0770) Prec@1 88.000 (87.557) Prec@5 98.000 (99.180) +2022-11-14 14:24:35,149 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0768) Prec@1 90.000 (87.597) Prec@5 98.000 (99.161) +2022-11-14 14:24:35,158 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0765) Prec@1 91.000 (87.651) Prec@5 100.000 (99.175) +2022-11-14 14:24:35,167 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0759) Prec@1 91.000 (87.703) Prec@5 100.000 (99.188) +2022-11-14 14:24:35,177 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0761) Prec@1 85.000 (87.662) Prec@5 99.000 (99.185) +2022-11-14 14:24:35,187 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0763) Prec@1 84.000 (87.606) Prec@5 99.000 (99.182) +2022-11-14 14:24:35,197 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0759) Prec@1 91.000 (87.657) Prec@5 100.000 (99.194) +2022-11-14 14:24:35,205 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0758) Prec@1 87.000 (87.647) Prec@5 99.000 (99.191) +2022-11-14 14:24:35,215 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0755) Prec@1 92.000 (87.710) Prec@5 99.000 (99.188) +2022-11-14 14:24:35,224 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0755) Prec@1 87.000 (87.700) Prec@5 100.000 (99.200) +2022-11-14 14:24:35,233 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0757) Prec@1 84.000 (87.648) Prec@5 99.000 (99.197) +2022-11-14 14:24:35,243 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0754) Prec@1 91.000 (87.694) Prec@5 99.000 (99.194) +2022-11-14 14:24:35,252 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0751) Prec@1 91.000 (87.740) Prec@5 99.000 (99.192) +2022-11-14 14:24:35,261 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0752) Prec@1 85.000 (87.703) Prec@5 100.000 (99.203) +2022-11-14 14:24:35,271 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0756) Prec@1 83.000 (87.640) Prec@5 100.000 (99.213) +2022-11-14 14:24:35,280 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0755) Prec@1 90.000 (87.671) Prec@5 99.000 (99.211) +2022-11-14 14:24:35,289 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0754) Prec@1 89.000 (87.688) Prec@5 98.000 (99.195) +2022-11-14 14:24:35,299 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0758) Prec@1 83.000 (87.628) Prec@5 99.000 (99.192) +2022-11-14 14:24:35,308 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0757) Prec@1 88.000 (87.633) Prec@5 100.000 (99.203) +2022-11-14 14:24:35,317 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0759) Prec@1 85.000 (87.600) Prec@5 100.000 (99.213) +2022-11-14 14:24:35,327 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0760) Prec@1 86.000 (87.580) Prec@5 99.000 (99.210) +2022-11-14 14:24:35,336 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0759) Prec@1 89.000 (87.598) Prec@5 99.000 (99.207) +2022-11-14 14:24:35,345 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0759) Prec@1 87.000 (87.590) Prec@5 100.000 (99.217) +2022-11-14 14:24:35,355 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0759) Prec@1 86.000 (87.571) Prec@5 100.000 (99.226) +2022-11-14 14:24:35,364 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0761) Prec@1 87.000 (87.565) Prec@5 98.000 (99.212) +2022-11-14 14:24:35,372 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0763) Prec@1 84.000 (87.523) Prec@5 99.000 (99.209) +2022-11-14 14:24:35,382 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0764) Prec@1 87.000 (87.517) Prec@5 100.000 (99.218) +2022-11-14 14:24:35,390 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 87.000 (87.511) Prec@5 100.000 (99.227) +2022-11-14 14:24:35,398 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0760) Prec@1 93.000 (87.573) Prec@5 99.000 (99.225) +2022-11-14 14:24:35,406 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0763) Prec@1 85.000 (87.544) Prec@5 100.000 (99.233) +2022-11-14 14:24:35,415 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0761) Prec@1 92.000 (87.593) Prec@5 100.000 (99.242) +2022-11-14 14:24:35,425 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0757) Prec@1 93.000 (87.652) Prec@5 100.000 (99.250) +2022-11-14 14:24:35,434 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0757) Prec@1 90.000 (87.677) Prec@5 100.000 (99.258) +2022-11-14 14:24:35,444 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0757) Prec@1 88.000 (87.681) Prec@5 100.000 (99.266) +2022-11-14 14:24:35,453 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0760) Prec@1 83.000 (87.632) Prec@5 100.000 (99.274) +2022-11-14 14:24:35,462 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0758) Prec@1 93.000 (87.688) Prec@5 100.000 (99.281) +2022-11-14 14:24:35,471 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0755) Prec@1 93.000 (87.742) Prec@5 99.000 (99.278) +2022-11-14 14:24:35,481 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0756) Prec@1 86.000 (87.724) Prec@5 99.000 (99.276) +2022-11-14 14:24:35,491 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.0760) Prec@1 83.000 (87.677) Prec@5 98.000 (99.263) +2022-11-14 14:24:35,501 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0759) Prec@1 89.000 (87.690) Prec@5 100.000 (99.270) +2022-11-14 14:24:35,570 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:24:35,890 Epoch: [193][0/500] Time 0.033 (0.033) Data 0.234 (0.234) Loss 0.0563 (0.0563) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:24:36,102 Epoch: [193][10/500] Time 0.017 (0.020) Data 0.001 (0.023) Loss 0.0338 (0.0451) Prec@1 94.000 (91.500) Prec@5 99.000 (99.000) +2022-11-14 14:24:36,306 Epoch: [193][20/500] Time 0.019 (0.019) Data 0.002 (0.013) Loss 0.0249 (0.0383) Prec@1 97.000 (93.333) Prec@5 100.000 (99.333) +2022-11-14 14:24:36,517 Epoch: [193][30/500] Time 0.020 (0.019) Data 0.002 (0.009) Loss 0.0342 (0.0373) Prec@1 95.000 (93.750) Prec@5 100.000 (99.500) +2022-11-14 14:24:36,791 Epoch: [193][40/500] Time 0.024 (0.020) Data 0.002 (0.007) Loss 0.0235 (0.0345) Prec@1 97.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 14:24:37,079 Epoch: [193][50/500] Time 0.024 (0.021) Data 0.002 (0.006) Loss 0.0478 (0.0367) Prec@1 92.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:37,363 Epoch: [193][60/500] Time 0.025 (0.022) Data 0.002 (0.006) Loss 0.0336 (0.0363) Prec@1 95.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:24:37,635 Epoch: [193][70/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0590 (0.0391) Prec@1 90.000 (93.625) Prec@5 99.000 (99.625) +2022-11-14 14:24:37,909 Epoch: [193][80/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0256 (0.0376) Prec@1 95.000 (93.778) Prec@5 99.000 (99.556) +2022-11-14 14:24:38,184 Epoch: [193][90/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0342 (0.0373) Prec@1 93.000 (93.700) Prec@5 100.000 (99.600) +2022-11-14 14:24:38,468 Epoch: [193][100/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0482 (0.0383) Prec@1 92.000 (93.545) Prec@5 100.000 (99.636) +2022-11-14 14:24:38,744 Epoch: [193][110/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0595 (0.0400) Prec@1 90.000 (93.250) Prec@5 100.000 (99.667) +2022-11-14 14:24:39,027 Epoch: [193][120/500] Time 0.024 (0.023) Data 0.002 (0.004) Loss 0.0362 (0.0397) Prec@1 93.000 (93.231) Prec@5 100.000 (99.692) +2022-11-14 14:24:39,314 Epoch: [193][130/500] Time 0.022 (0.023) Data 0.002 (0.004) Loss 0.0396 (0.0397) Prec@1 93.000 (93.214) Prec@5 99.000 (99.643) +2022-11-14 14:24:39,621 Epoch: [193][140/500] Time 0.036 (0.024) Data 0.002 (0.003) Loss 0.0366 (0.0395) Prec@1 93.000 (93.200) Prec@5 100.000 (99.667) +2022-11-14 14:24:40,103 Epoch: [193][150/500] Time 0.042 (0.025) Data 0.002 (0.003) Loss 0.0497 (0.0402) Prec@1 92.000 (93.125) Prec@5 100.000 (99.688) +2022-11-14 14:24:40,584 Epoch: [193][160/500] Time 0.044 (0.026) Data 0.001 (0.003) Loss 0.0301 (0.0396) Prec@1 94.000 (93.176) Prec@5 100.000 (99.706) +2022-11-14 14:24:41,064 Epoch: [193][170/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0402 (0.0396) Prec@1 93.000 (93.167) Prec@5 100.000 (99.722) +2022-11-14 14:24:41,536 Epoch: [193][180/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0704 (0.0412) Prec@1 89.000 (92.947) Prec@5 99.000 (99.684) +2022-11-14 14:24:42,011 Epoch: [193][190/500] Time 0.053 (0.029) Data 0.002 (0.003) Loss 0.0714 (0.0427) Prec@1 89.000 (92.750) Prec@5 100.000 (99.700) +2022-11-14 14:24:42,482 Epoch: [193][200/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0463 (0.0429) Prec@1 92.000 (92.714) Prec@5 100.000 (99.714) +2022-11-14 14:24:42,964 Epoch: [193][210/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0464 (0.0431) Prec@1 92.000 (92.682) Prec@5 99.000 (99.682) +2022-11-14 14:24:43,437 Epoch: [193][220/500] Time 0.048 (0.030) Data 0.002 (0.003) Loss 0.0351 (0.0427) Prec@1 95.000 (92.783) Prec@5 100.000 (99.696) +2022-11-14 14:24:43,899 Epoch: [193][230/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0414 (0.0427) Prec@1 93.000 (92.792) Prec@5 100.000 (99.708) +2022-11-14 14:24:44,372 Epoch: [193][240/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0390 (0.0425) Prec@1 94.000 (92.840) Prec@5 100.000 (99.720) +2022-11-14 14:24:44,852 Epoch: [193][250/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0270 (0.0419) Prec@1 97.000 (93.000) Prec@5 100.000 (99.731) +2022-11-14 14:24:45,333 Epoch: [193][260/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0330 (0.0416) Prec@1 97.000 (93.148) Prec@5 100.000 (99.741) +2022-11-14 14:24:45,807 Epoch: [193][270/500] Time 0.050 (0.033) Data 0.002 (0.003) Loss 0.0340 (0.0413) Prec@1 93.000 (93.143) Prec@5 100.000 (99.750) +2022-11-14 14:24:46,280 Epoch: [193][280/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0416 (0.0413) Prec@1 91.000 (93.069) Prec@5 100.000 (99.759) +2022-11-14 14:24:46,750 Epoch: [193][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0172 (0.0405) Prec@1 99.000 (93.267) Prec@5 100.000 (99.767) +2022-11-14 14:24:47,228 Epoch: [193][300/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0649 (0.0413) Prec@1 89.000 (93.129) Prec@5 100.000 (99.774) +2022-11-14 14:24:47,700 Epoch: [193][310/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0450 (0.0414) Prec@1 94.000 (93.156) Prec@5 100.000 (99.781) +2022-11-14 14:24:48,183 Epoch: [193][320/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0585 (0.0419) Prec@1 90.000 (93.061) Prec@5 100.000 (99.788) +2022-11-14 14:24:48,644 Epoch: [193][330/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0588 (0.0424) Prec@1 91.000 (93.000) Prec@5 100.000 (99.794) +2022-11-14 14:24:49,135 Epoch: [193][340/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0511 (0.0427) Prec@1 93.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:24:49,607 Epoch: [193][350/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0527 (0.0430) Prec@1 92.000 (92.972) Prec@5 100.000 (99.806) +2022-11-14 14:24:50,080 Epoch: [193][360/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0387 (0.0429) Prec@1 95.000 (93.027) Prec@5 100.000 (99.811) +2022-11-14 14:24:50,545 Epoch: [193][370/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0358 (0.0427) Prec@1 94.000 (93.053) Prec@5 100.000 (99.816) +2022-11-14 14:24:51,053 Epoch: [193][380/500] Time 0.038 (0.035) Data 0.003 (0.002) Loss 0.0838 (0.0437) Prec@1 86.000 (92.872) Prec@5 99.000 (99.795) +2022-11-14 14:24:51,537 Epoch: [193][390/500] Time 0.044 (0.036) Data 0.001 (0.002) Loss 0.0321 (0.0434) Prec@1 94.000 (92.900) Prec@5 100.000 (99.800) +2022-11-14 14:24:52,015 Epoch: [193][400/500] Time 0.052 (0.036) Data 0.002 (0.002) Loss 0.0488 (0.0436) Prec@1 92.000 (92.878) Prec@5 99.000 (99.780) +2022-11-14 14:24:52,425 Epoch: [193][410/500] Time 0.026 (0.036) Data 0.002 (0.002) Loss 0.0658 (0.0441) Prec@1 88.000 (92.762) Prec@5 99.000 (99.762) +2022-11-14 14:24:52,739 Epoch: [193][420/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0443 (0.0441) Prec@1 93.000 (92.767) Prec@5 99.000 (99.744) +2022-11-14 14:24:53,049 Epoch: [193][430/500] Time 0.024 (0.035) Data 0.003 (0.002) Loss 0.0236 (0.0436) Prec@1 96.000 (92.841) Prec@5 100.000 (99.750) +2022-11-14 14:24:53,365 Epoch: [193][440/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0240 (0.0432) Prec@1 97.000 (92.933) Prec@5 100.000 (99.756) +2022-11-14 14:24:53,676 Epoch: [193][450/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.0627 (0.0436) Prec@1 91.000 (92.891) Prec@5 100.000 (99.761) +2022-11-14 14:24:53,992 Epoch: [193][460/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0437 (0.0436) Prec@1 91.000 (92.851) Prec@5 100.000 (99.766) +2022-11-14 14:24:54,297 Epoch: [193][470/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0372 (0.0435) Prec@1 95.000 (92.896) Prec@5 100.000 (99.771) +2022-11-14 14:24:54,610 Epoch: [193][480/500] Time 0.030 (0.035) Data 0.002 (0.002) Loss 0.0379 (0.0434) Prec@1 95.000 (92.939) Prec@5 100.000 (99.776) +2022-11-14 14:24:54,918 Epoch: [193][490/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0287 (0.0431) Prec@1 97.000 (93.020) Prec@5 100.000 (99.780) +2022-11-14 14:24:55,205 Epoch: [193][499/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0420 (0.0431) Prec@1 93.000 (93.020) Prec@5 100.000 (99.784) +2022-11-14 14:24:55,481 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0756 (0.0756) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:55,492 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0689) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:24:55,501 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0775) Prec@1 86.000 (87.667) Prec@5 99.000 (99.667) +2022-11-14 14:24:55,512 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0797) Prec@1 84.000 (86.750) Prec@5 100.000 (99.750) +2022-11-14 14:24:55,521 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0833) Prec@1 82.000 (85.800) Prec@5 99.000 (99.600) +2022-11-14 14:24:55,532 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0788) Prec@1 91.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 14:24:55,540 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0740) Prec@1 93.000 (87.571) Prec@5 100.000 (99.714) +2022-11-14 14:24:55,549 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0768) Prec@1 82.000 (86.875) Prec@5 99.000 (99.625) +2022-11-14 14:24:55,558 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0763) Prec@1 88.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:24:55,568 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0763) Prec@1 85.000 (86.800) Prec@5 99.000 (99.600) +2022-11-14 14:24:55,577 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0760) Prec@1 86.000 (86.727) Prec@5 100.000 (99.636) +2022-11-14 14:24:55,586 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0775) Prec@1 85.000 (86.583) Prec@5 99.000 (99.583) +2022-11-14 14:24:55,596 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0768) Prec@1 89.000 (86.769) Prec@5 100.000 (99.615) +2022-11-14 14:24:55,604 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0764) Prec@1 89.000 (86.929) Prec@5 99.000 (99.571) +2022-11-14 14:24:55,613 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0765) Prec@1 87.000 (86.933) Prec@5 100.000 (99.600) +2022-11-14 14:24:55,622 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0782) Prec@1 81.000 (86.562) Prec@5 98.000 (99.500) +2022-11-14 14:24:55,632 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0770) Prec@1 90.000 (86.765) Prec@5 99.000 (99.471) +2022-11-14 14:24:55,644 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1251 (0.0797) Prec@1 81.000 (86.444) Prec@5 100.000 (99.500) +2022-11-14 14:24:55,654 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0801) Prec@1 87.000 (86.474) Prec@5 99.000 (99.474) +2022-11-14 14:24:55,663 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0812) Prec@1 84.000 (86.350) Prec@5 97.000 (99.350) +2022-11-14 14:24:55,673 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0823) Prec@1 83.000 (86.190) Prec@5 98.000 (99.286) +2022-11-14 14:24:55,683 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0832) Prec@1 82.000 (86.000) Prec@5 99.000 (99.273) +2022-11-14 14:24:55,692 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0848) Prec@1 82.000 (85.826) Prec@5 98.000 (99.217) +2022-11-14 14:24:55,702 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0848) Prec@1 85.000 (85.792) Prec@5 98.000 (99.167) +2022-11-14 14:24:55,711 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0852) Prec@1 84.000 (85.720) Prec@5 100.000 (99.200) +2022-11-14 14:24:55,720 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0854) Prec@1 85.000 (85.692) Prec@5 99.000 (99.192) +2022-11-14 14:24:55,730 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0848) Prec@1 90.000 (85.852) Prec@5 100.000 (99.222) +2022-11-14 14:24:55,739 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0839) Prec@1 92.000 (86.071) Prec@5 99.000 (99.214) +2022-11-14 14:24:55,748 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0832) Prec@1 91.000 (86.241) Prec@5 100.000 (99.241) +2022-11-14 14:24:55,758 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0831) Prec@1 89.000 (86.333) Prec@5 100.000 (99.267) +2022-11-14 14:24:55,766 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0835) Prec@1 82.000 (86.194) Prec@5 100.000 (99.290) +2022-11-14 14:24:55,775 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0835) Prec@1 86.000 (86.188) Prec@5 100.000 (99.312) +2022-11-14 14:24:55,783 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0835) Prec@1 84.000 (86.121) Prec@5 98.000 (99.273) +2022-11-14 14:24:55,790 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0842) Prec@1 82.000 (86.000) Prec@5 99.000 (99.265) +2022-11-14 14:24:55,800 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0849) Prec@1 84.000 (85.943) Prec@5 99.000 (99.257) +2022-11-14 14:24:55,809 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0842) Prec@1 91.000 (86.083) Prec@5 100.000 (99.278) +2022-11-14 14:24:55,818 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0842) Prec@1 87.000 (86.108) Prec@5 98.000 (99.243) +2022-11-14 14:24:55,827 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0842) Prec@1 88.000 (86.158) Prec@5 99.000 (99.237) +2022-11-14 14:24:55,836 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0838) Prec@1 87.000 (86.179) Prec@5 99.000 (99.231) +2022-11-14 14:24:55,845 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0836) Prec@1 88.000 (86.225) Prec@5 98.000 (99.200) +2022-11-14 14:24:55,855 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1236 (0.0846) Prec@1 81.000 (86.098) Prec@5 95.000 (99.098) +2022-11-14 14:24:55,863 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0848) Prec@1 84.000 (86.048) Prec@5 99.000 (99.095) +2022-11-14 14:24:55,872 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0838) Prec@1 92.000 (86.186) Prec@5 99.000 (99.093) +2022-11-14 14:24:55,882 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0840) Prec@1 86.000 (86.182) Prec@5 99.000 (99.091) +2022-11-14 14:24:55,891 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0840) Prec@1 88.000 (86.222) Prec@5 98.000 (99.067) +2022-11-14 14:24:55,900 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0845) Prec@1 80.000 (86.087) Prec@5 100.000 (99.087) +2022-11-14 14:24:55,909 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0846) Prec@1 85.000 (86.064) Prec@5 99.000 (99.085) +2022-11-14 14:24:55,919 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0846) Prec@1 85.000 (86.042) Prec@5 99.000 (99.083) +2022-11-14 14:24:55,928 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0841) Prec@1 90.000 (86.122) Prec@5 100.000 (99.102) +2022-11-14 14:24:55,939 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1222 (0.0849) Prec@1 79.000 (85.980) Prec@5 100.000 (99.120) +2022-11-14 14:24:55,948 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0847) Prec@1 88.000 (86.020) Prec@5 99.000 (99.118) +2022-11-14 14:24:55,958 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0847) Prec@1 85.000 (86.000) Prec@5 100.000 (99.135) +2022-11-14 14:24:55,967 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0846) Prec@1 86.000 (86.000) Prec@5 99.000 (99.132) +2022-11-14 14:24:55,976 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0847) Prec@1 84.000 (85.963) Prec@5 99.000 (99.130) +2022-11-14 14:24:55,986 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0848) Prec@1 84.000 (85.927) Prec@5 100.000 (99.145) +2022-11-14 14:24:55,995 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0848) Prec@1 87.000 (85.946) Prec@5 99.000 (99.143) +2022-11-14 14:24:56,007 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0848) Prec@1 89.000 (86.000) Prec@5 99.000 (99.140) +2022-11-14 14:24:56,016 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0843) Prec@1 91.000 (86.086) Prec@5 98.000 (99.121) +2022-11-14 14:24:56,025 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0843) Prec@1 84.000 (86.051) Prec@5 100.000 (99.136) +2022-11-14 14:24:56,034 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0844) Prec@1 86.000 (86.050) Prec@5 100.000 (99.150) +2022-11-14 14:24:56,044 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0846) Prec@1 87.000 (86.066) Prec@5 99.000 (99.148) +2022-11-14 14:24:56,056 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0848) Prec@1 80.000 (85.968) Prec@5 98.000 (99.129) +2022-11-14 14:24:56,067 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0845) Prec@1 90.000 (86.032) Prec@5 100.000 (99.143) +2022-11-14 14:24:56,076 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0840) Prec@1 91.000 (86.109) Prec@5 100.000 (99.156) +2022-11-14 14:24:56,084 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0841) Prec@1 84.000 (86.077) Prec@5 99.000 (99.154) +2022-11-14 14:24:56,093 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0840) Prec@1 86.000 (86.076) Prec@5 99.000 (99.152) +2022-11-14 14:24:56,102 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0835) Prec@1 92.000 (86.164) Prec@5 99.000 (99.149) +2022-11-14 14:24:56,112 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0834) Prec@1 87.000 (86.176) Prec@5 98.000 (99.132) +2022-11-14 14:24:56,121 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0830) Prec@1 90.000 (86.232) Prec@5 100.000 (99.145) +2022-11-14 14:24:56,130 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0830) Prec@1 87.000 (86.243) Prec@5 100.000 (99.157) +2022-11-14 14:24:56,141 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0833) Prec@1 83.000 (86.197) Prec@5 99.000 (99.155) +2022-11-14 14:24:56,150 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0833) Prec@1 88.000 (86.222) Prec@5 99.000 (99.153) +2022-11-14 14:24:56,160 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0828) Prec@1 92.000 (86.301) Prec@5 99.000 (99.151) +2022-11-14 14:24:56,169 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0825) Prec@1 89.000 (86.338) Prec@5 100.000 (99.162) +2022-11-14 14:24:56,178 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0829) Prec@1 81.000 (86.267) Prec@5 99.000 (99.160) +2022-11-14 14:24:56,188 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0827) Prec@1 90.000 (86.316) Prec@5 99.000 (99.158) +2022-11-14 14:24:56,197 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0827) Prec@1 87.000 (86.325) Prec@5 99.000 (99.156) +2022-11-14 14:24:56,206 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0829) Prec@1 84.000 (86.295) Prec@5 100.000 (99.167) +2022-11-14 14:24:56,215 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0830) Prec@1 85.000 (86.278) Prec@5 100.000 (99.177) +2022-11-14 14:24:56,224 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0831) Prec@1 83.000 (86.237) Prec@5 98.000 (99.162) +2022-11-14 14:24:56,234 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0831) Prec@1 83.000 (86.198) Prec@5 100.000 (99.173) +2022-11-14 14:24:56,244 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0831) Prec@1 88.000 (86.220) Prec@5 98.000 (99.159) +2022-11-14 14:24:56,253 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0830) Prec@1 88.000 (86.241) Prec@5 99.000 (99.157) +2022-11-14 14:24:56,264 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0830) Prec@1 86.000 (86.238) Prec@5 100.000 (99.167) +2022-11-14 14:24:56,274 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0830) Prec@1 85.000 (86.224) Prec@5 100.000 (99.176) +2022-11-14 14:24:56,284 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0831) Prec@1 83.000 (86.186) Prec@5 100.000 (99.186) +2022-11-14 14:24:56,294 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0828) Prec@1 91.000 (86.241) Prec@5 99.000 (99.184) +2022-11-14 14:24:56,302 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0826) Prec@1 88.000 (86.261) Prec@5 98.000 (99.170) +2022-11-14 14:24:56,312 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0825) Prec@1 88.000 (86.281) Prec@5 99.000 (99.169) +2022-11-14 14:24:56,321 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0826) Prec@1 85.000 (86.267) Prec@5 100.000 (99.178) +2022-11-14 14:24:56,330 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0822) Prec@1 95.000 (86.363) Prec@5 100.000 (99.187) +2022-11-14 14:24:56,340 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0820) Prec@1 89.000 (86.391) Prec@5 100.000 (99.196) +2022-11-14 14:24:56,349 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0820) Prec@1 87.000 (86.398) Prec@5 100.000 (99.204) +2022-11-14 14:24:56,358 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0820) Prec@1 88.000 (86.415) Prec@5 98.000 (99.191) +2022-11-14 14:24:56,366 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0823) Prec@1 82.000 (86.368) Prec@5 98.000 (99.179) +2022-11-14 14:24:56,376 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0822) Prec@1 90.000 (86.406) Prec@5 99.000 (99.177) +2022-11-14 14:24:56,383 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0819) Prec@1 90.000 (86.443) Prec@5 100.000 (99.186) +2022-11-14 14:24:56,391 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0819) Prec@1 84.000 (86.418) Prec@5 99.000 (99.184) +2022-11-14 14:24:56,399 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0821) Prec@1 86.000 (86.414) Prec@5 99.000 (99.182) +2022-11-14 14:24:56,409 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0819) Prec@1 89.000 (86.440) Prec@5 99.000 (99.180) +2022-11-14 14:24:56,479 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:24:56,788 Epoch: [194][0/500] Time 0.023 (0.023) Data 0.226 (0.226) Loss 0.0468 (0.0468) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:56,998 Epoch: [194][10/500] Time 0.017 (0.019) Data 0.001 (0.022) Loss 0.0244 (0.0356) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:24:57,198 Epoch: [194][20/500] Time 0.019 (0.018) Data 0.001 (0.012) Loss 0.0455 (0.0389) Prec@1 94.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 14:24:57,468 Epoch: [194][30/500] Time 0.026 (0.020) Data 0.001 (0.009) Loss 0.0574 (0.0435) Prec@1 90.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 14:24:57,747 Epoch: [194][40/500] Time 0.024 (0.021) Data 0.002 (0.007) Loss 0.0370 (0.0422) Prec@1 94.000 (93.200) Prec@5 100.000 (99.600) +2022-11-14 14:24:58,030 Epoch: [194][50/500] Time 0.023 (0.022) Data 0.002 (0.006) Loss 0.0298 (0.0401) Prec@1 94.000 (93.333) Prec@5 100.000 (99.667) +2022-11-14 14:24:58,304 Epoch: [194][60/500] Time 0.027 (0.022) Data 0.002 (0.005) Loss 0.0286 (0.0385) Prec@1 95.000 (93.571) Prec@5 100.000 (99.714) +2022-11-14 14:24:58,588 Epoch: [194][70/500] Time 0.030 (0.023) Data 0.002 (0.005) Loss 0.0509 (0.0401) Prec@1 91.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:24:59,101 Epoch: [194][80/500] Time 0.054 (0.026) Data 0.002 (0.005) Loss 0.0387 (0.0399) Prec@1 92.000 (93.111) Prec@5 100.000 (99.778) +2022-11-14 14:24:59,609 Epoch: [194][90/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0332 (0.0392) Prec@1 95.000 (93.300) Prec@5 99.000 (99.700) +2022-11-14 14:25:00,133 Epoch: [194][100/500] Time 0.044 (0.030) Data 0.002 (0.004) Loss 0.0446 (0.0397) Prec@1 90.000 (93.000) Prec@5 100.000 (99.727) +2022-11-14 14:25:00,610 Epoch: [194][110/500] Time 0.044 (0.031) Data 0.002 (0.004) Loss 0.0377 (0.0396) Prec@1 94.000 (93.083) Prec@5 100.000 (99.750) +2022-11-14 14:25:01,099 Epoch: [194][120/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.0369 (0.0393) Prec@1 94.000 (93.154) Prec@5 99.000 (99.692) +2022-11-14 14:25:01,564 Epoch: [194][130/500] Time 0.044 (0.033) Data 0.002 (0.004) Loss 0.0353 (0.0391) Prec@1 97.000 (93.429) Prec@5 100.000 (99.714) +2022-11-14 14:25:02,044 Epoch: [194][140/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0366 (0.0389) Prec@1 94.000 (93.467) Prec@5 99.000 (99.667) +2022-11-14 14:25:02,543 Epoch: [194][150/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0422 (0.0391) Prec@1 91.000 (93.312) Prec@5 100.000 (99.688) +2022-11-14 14:25:03,061 Epoch: [194][160/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.0498 (0.0397) Prec@1 91.000 (93.176) Prec@5 100.000 (99.706) +2022-11-14 14:25:03,548 Epoch: [194][170/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0412 (0.0398) Prec@1 94.000 (93.222) Prec@5 100.000 (99.722) +2022-11-14 14:25:04,083 Epoch: [194][180/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0820 (0.0420) Prec@1 87.000 (92.895) Prec@5 100.000 (99.737) +2022-11-14 14:25:04,578 Epoch: [194][190/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0359 (0.0417) Prec@1 96.000 (93.050) Prec@5 99.000 (99.700) +2022-11-14 14:25:05,059 Epoch: [194][200/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0448 (0.0419) Prec@1 91.000 (92.952) Prec@5 100.000 (99.714) +2022-11-14 14:25:05,558 Epoch: [194][210/500] Time 0.049 (0.037) Data 0.002 (0.003) Loss 0.0551 (0.0425) Prec@1 92.000 (92.909) Prec@5 100.000 (99.727) +2022-11-14 14:25:06,048 Epoch: [194][220/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0562 (0.0431) Prec@1 92.000 (92.870) Prec@5 100.000 (99.739) +2022-11-14 14:25:06,521 Epoch: [194][230/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0421 (0.0430) Prec@1 94.000 (92.917) Prec@5 100.000 (99.750) +2022-11-14 14:25:07,012 Epoch: [194][240/500] Time 0.055 (0.038) Data 0.003 (0.003) Loss 0.0958 (0.0451) Prec@1 84.000 (92.560) Prec@5 99.000 (99.720) +2022-11-14 14:25:07,477 Epoch: [194][250/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0338 (0.0447) Prec@1 95.000 (92.654) Prec@5 100.000 (99.731) +2022-11-14 14:25:07,958 Epoch: [194][260/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0314 (0.0442) Prec@1 96.000 (92.778) Prec@5 100.000 (99.741) +2022-11-14 14:25:08,433 Epoch: [194][270/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0362 (0.0439) Prec@1 94.000 (92.821) Prec@5 100.000 (99.750) +2022-11-14 14:25:08,906 Epoch: [194][280/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0575 (0.0444) Prec@1 92.000 (92.793) Prec@5 99.000 (99.724) +2022-11-14 14:25:09,382 Epoch: [194][290/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0528 (0.0447) Prec@1 91.000 (92.733) Prec@5 99.000 (99.700) +2022-11-14 14:25:09,845 Epoch: [194][300/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0443 (0.0447) Prec@1 90.000 (92.645) Prec@5 100.000 (99.710) +2022-11-14 14:25:10,328 Epoch: [194][310/500] Time 0.044 (0.039) Data 0.001 (0.003) Loss 0.0577 (0.0451) Prec@1 89.000 (92.531) Prec@5 100.000 (99.719) +2022-11-14 14:25:10,801 Epoch: [194][320/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0382 (0.0449) Prec@1 93.000 (92.545) Prec@5 100.000 (99.727) +2022-11-14 14:25:11,284 Epoch: [194][330/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0237 (0.0442) Prec@1 97.000 (92.676) Prec@5 100.000 (99.735) +2022-11-14 14:25:11,682 Epoch: [194][340/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.0573 (0.0446) Prec@1 88.000 (92.543) Prec@5 100.000 (99.743) +2022-11-14 14:25:12,003 Epoch: [194][350/500] Time 0.027 (0.039) Data 0.002 (0.003) Loss 0.0537 (0.0449) Prec@1 90.000 (92.472) Prec@5 100.000 (99.750) +2022-11-14 14:25:12,318 Epoch: [194][360/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.0373 (0.0447) Prec@1 92.000 (92.459) Prec@5 100.000 (99.757) +2022-11-14 14:25:12,635 Epoch: [194][370/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.0511 (0.0448) Prec@1 91.000 (92.421) Prec@5 100.000 (99.763) +2022-11-14 14:25:12,957 Epoch: [194][380/500] Time 0.032 (0.038) Data 0.001 (0.002) Loss 0.0291 (0.0444) Prec@1 96.000 (92.513) Prec@5 100.000 (99.769) +2022-11-14 14:25:13,267 Epoch: [194][390/500] Time 0.030 (0.038) Data 0.002 (0.002) Loss 0.0387 (0.0443) Prec@1 92.000 (92.500) Prec@5 100.000 (99.775) +2022-11-14 14:25:13,585 Epoch: [194][400/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0409 (0.0442) Prec@1 93.000 (92.512) Prec@5 100.000 (99.780) +2022-11-14 14:25:13,899 Epoch: [194][410/500] Time 0.030 (0.037) Data 0.001 (0.002) Loss 0.0561 (0.0445) Prec@1 91.000 (92.476) Prec@5 100.000 (99.786) +2022-11-14 14:25:14,223 Epoch: [194][420/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0426 (0.0444) Prec@1 95.000 (92.535) Prec@5 100.000 (99.791) +2022-11-14 14:25:14,539 Epoch: [194][430/500] Time 0.030 (0.037) Data 0.001 (0.002) Loss 0.0669 (0.0450) Prec@1 90.000 (92.477) Prec@5 99.000 (99.773) +2022-11-14 14:25:14,854 Epoch: [194][440/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0390 (0.0448) Prec@1 93.000 (92.489) Prec@5 100.000 (99.778) +2022-11-14 14:25:15,170 Epoch: [194][450/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0587 (0.0451) Prec@1 92.000 (92.478) Prec@5 100.000 (99.783) +2022-11-14 14:25:15,493 Epoch: [194][460/500] Time 0.028 (0.036) Data 0.001 (0.002) Loss 0.0466 (0.0452) Prec@1 93.000 (92.489) Prec@5 99.000 (99.766) +2022-11-14 14:25:15,810 Epoch: [194][470/500] Time 0.029 (0.036) Data 0.003 (0.002) Loss 0.0541 (0.0453) Prec@1 90.000 (92.438) Prec@5 100.000 (99.771) +2022-11-14 14:25:16,135 Epoch: [194][480/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0915 (0.0463) Prec@1 85.000 (92.286) Prec@5 99.000 (99.755) +2022-11-14 14:25:16,481 Epoch: [194][490/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0423 (0.0462) Prec@1 93.000 (92.300) Prec@5 99.000 (99.740) +2022-11-14 14:25:16,761 Epoch: [194][499/500] Time 0.039 (0.036) Data 0.001 (0.002) Loss 0.0453 (0.0462) Prec@1 92.000 (92.294) Prec@5 100.000 (99.745) +2022-11-14 14:25:17,059 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0867 (0.0867) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:25:17,068 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0578 (0.0722) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:25:17,077 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0799) Prec@1 84.000 (86.333) Prec@5 100.000 (100.000) +2022-11-14 14:25:17,086 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0865) Prec@1 83.000 (85.500) Prec@5 98.000 (99.500) +2022-11-14 14:25:17,094 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0875) Prec@1 86.000 (85.600) Prec@5 97.000 (99.000) +2022-11-14 14:25:17,103 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0827) Prec@1 90.000 (86.333) Prec@5 100.000 (99.167) +2022-11-14 14:25:17,112 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0825) Prec@1 87.000 (86.429) Prec@5 98.000 (99.000) +2022-11-14 14:25:17,121 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0819) Prec@1 89.000 (86.750) Prec@5 100.000 (99.125) +2022-11-14 14:25:17,128 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0811) Prec@1 88.000 (86.889) Prec@5 100.000 (99.222) +2022-11-14 14:25:17,135 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0803) Prec@1 89.000 (87.100) Prec@5 97.000 (99.000) +2022-11-14 14:25:17,144 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0787) Prec@1 90.000 (87.364) Prec@5 99.000 (99.000) +2022-11-14 14:25:17,154 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0790) Prec@1 86.000 (87.250) Prec@5 100.000 (99.083) +2022-11-14 14:25:17,163 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0780) Prec@1 88.000 (87.308) Prec@5 100.000 (99.154) +2022-11-14 14:25:17,172 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0787) Prec@1 87.000 (87.286) Prec@5 99.000 (99.143) +2022-11-14 14:25:17,181 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0792) Prec@1 85.000 (87.133) Prec@5 100.000 (99.200) +2022-11-14 14:25:17,190 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0800) Prec@1 84.000 (86.938) Prec@5 99.000 (99.188) +2022-11-14 14:25:17,199 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0785) Prec@1 91.000 (87.176) Prec@5 98.000 (99.118) +2022-11-14 14:25:17,208 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0794) Prec@1 84.000 (87.000) Prec@5 100.000 (99.167) +2022-11-14 14:25:17,218 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0801) Prec@1 84.000 (86.842) Prec@5 99.000 (99.158) +2022-11-14 14:25:17,226 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1106 (0.0816) Prec@1 81.000 (86.550) Prec@5 98.000 (99.100) +2022-11-14 14:25:17,236 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0816) Prec@1 85.000 (86.476) Prec@5 100.000 (99.143) +2022-11-14 14:25:17,245 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0823) Prec@1 84.000 (86.364) Prec@5 99.000 (99.136) +2022-11-14 14:25:17,254 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0827) Prec@1 84.000 (86.261) Prec@5 100.000 (99.174) +2022-11-14 14:25:17,264 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0827) Prec@1 88.000 (86.333) Prec@5 100.000 (99.208) +2022-11-14 14:25:17,274 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0829) Prec@1 85.000 (86.280) Prec@5 100.000 (99.240) +2022-11-14 14:25:17,282 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0829) Prec@1 86.000 (86.269) Prec@5 99.000 (99.231) +2022-11-14 14:25:17,292 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0819) Prec@1 88.000 (86.333) Prec@5 100.000 (99.259) +2022-11-14 14:25:17,301 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0810) Prec@1 90.000 (86.464) Prec@5 100.000 (99.286) +2022-11-14 14:25:17,310 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0815) Prec@1 85.000 (86.414) Prec@5 97.000 (99.207) +2022-11-14 14:25:17,319 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0812) Prec@1 88.000 (86.467) Prec@5 99.000 (99.200) +2022-11-14 14:25:17,329 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0808) Prec@1 90.000 (86.581) Prec@5 99.000 (99.194) +2022-11-14 14:25:17,338 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0805) Prec@1 90.000 (86.688) Prec@5 100.000 (99.219) +2022-11-14 14:25:17,348 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0804) Prec@1 86.000 (86.667) Prec@5 100.000 (99.242) +2022-11-14 14:25:17,358 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0807) Prec@1 84.000 (86.588) Prec@5 100.000 (99.265) +2022-11-14 14:25:17,368 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0811) Prec@1 84.000 (86.514) Prec@5 97.000 (99.200) +2022-11-14 14:25:17,377 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0807) Prec@1 89.000 (86.583) Prec@5 100.000 (99.222) +2022-11-14 14:25:17,386 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0807) Prec@1 87.000 (86.595) Prec@5 100.000 (99.243) +2022-11-14 14:25:17,395 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0813) Prec@1 84.000 (86.526) Prec@5 99.000 (99.237) +2022-11-14 14:25:17,404 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0811) Prec@1 88.000 (86.564) Prec@5 99.000 (99.231) +2022-11-14 14:25:17,413 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0810) Prec@1 87.000 (86.575) Prec@5 99.000 (99.225) +2022-11-14 14:25:17,422 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0815) Prec@1 85.000 (86.537) Prec@5 96.000 (99.146) +2022-11-14 14:25:17,430 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0809) Prec@1 90.000 (86.619) Prec@5 100.000 (99.167) +2022-11-14 14:25:17,438 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0801) Prec@1 93.000 (86.767) Prec@5 99.000 (99.163) +2022-11-14 14:25:17,447 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0797) Prec@1 91.000 (86.864) Prec@5 98.000 (99.136) +2022-11-14 14:25:17,456 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0795) Prec@1 89.000 (86.911) Prec@5 100.000 (99.156) +2022-11-14 14:25:17,465 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0803) Prec@1 81.000 (86.783) Prec@5 98.000 (99.130) +2022-11-14 14:25:17,474 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0802) Prec@1 85.000 (86.745) Prec@5 99.000 (99.128) +2022-11-14 14:25:17,483 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0808) Prec@1 82.000 (86.646) Prec@5 99.000 (99.125) +2022-11-14 14:25:17,493 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0801) Prec@1 93.000 (86.776) Prec@5 99.000 (99.122) +2022-11-14 14:25:17,502 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.0807) Prec@1 82.000 (86.680) Prec@5 99.000 (99.120) +2022-11-14 14:25:17,511 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0807) Prec@1 84.000 (86.627) Prec@5 100.000 (99.137) +2022-11-14 14:25:17,520 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0813) Prec@1 80.000 (86.500) Prec@5 100.000 (99.154) +2022-11-14 14:25:17,530 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0808) Prec@1 91.000 (86.585) Prec@5 99.000 (99.151) +2022-11-14 14:25:17,539 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0808) Prec@1 87.000 (86.593) Prec@5 98.000 (99.130) +2022-11-14 14:25:17,549 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0811) Prec@1 85.000 (86.564) Prec@5 100.000 (99.145) +2022-11-14 14:25:17,558 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0808) Prec@1 87.000 (86.571) Prec@5 99.000 (99.143) +2022-11-14 14:25:17,568 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0805) Prec@1 86.000 (86.561) Prec@5 100.000 (99.158) +2022-11-14 14:25:17,578 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0800) Prec@1 91.000 (86.638) Prec@5 98.000 (99.138) +2022-11-14 14:25:17,587 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1206 (0.0807) Prec@1 81.000 (86.542) Prec@5 99.000 (99.136) +2022-11-14 14:25:17,597 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0803) Prec@1 89.000 (86.583) Prec@5 100.000 (99.150) +2022-11-14 14:25:17,607 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0806) Prec@1 85.000 (86.557) Prec@5 99.000 (99.148) +2022-11-14 14:25:17,618 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0804) Prec@1 90.000 (86.613) Prec@5 100.000 (99.161) +2022-11-14 14:25:17,631 Test: [62/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0803) Prec@1 87.000 (86.619) Prec@5 100.000 (99.175) +2022-11-14 14:25:17,643 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0801) Prec@1 88.000 (86.641) Prec@5 100.000 (99.188) +2022-11-14 14:25:17,654 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0801) Prec@1 87.000 (86.646) Prec@5 99.000 (99.185) +2022-11-14 14:25:17,666 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0803) Prec@1 85.000 (86.621) Prec@5 99.000 (99.182) +2022-11-14 14:25:17,678 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0801) Prec@1 89.000 (86.657) Prec@5 100.000 (99.194) +2022-11-14 14:25:17,690 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0800) Prec@1 90.000 (86.706) Prec@5 98.000 (99.176) +2022-11-14 14:25:17,701 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0798) Prec@1 89.000 (86.739) Prec@5 100.000 (99.188) +2022-11-14 14:25:17,714 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0800) Prec@1 86.000 (86.729) Prec@5 97.000 (99.157) +2022-11-14 14:25:17,727 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0800) Prec@1 88.000 (86.746) Prec@5 98.000 (99.141) +2022-11-14 14:25:17,738 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0798) Prec@1 88.000 (86.764) Prec@5 100.000 (99.153) +2022-11-14 14:25:17,748 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0793) Prec@1 93.000 (86.849) Prec@5 99.000 (99.151) +2022-11-14 14:25:17,761 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0790) Prec@1 91.000 (86.905) Prec@5 100.000 (99.162) +2022-11-14 14:25:17,772 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0789) Prec@1 88.000 (86.920) Prec@5 99.000 (99.160) +2022-11-14 14:25:17,783 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0786) Prec@1 89.000 (86.947) Prec@5 100.000 (99.171) +2022-11-14 14:25:17,796 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0783) Prec@1 93.000 (87.026) Prec@5 100.000 (99.182) +2022-11-14 14:25:17,807 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0784) Prec@1 86.000 (87.013) Prec@5 98.000 (99.167) +2022-11-14 14:25:17,818 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0783) Prec@1 89.000 (87.038) Prec@5 100.000 (99.177) +2022-11-14 14:25:17,829 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0782) Prec@1 89.000 (87.062) Prec@5 99.000 (99.175) +2022-11-14 14:25:17,841 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0780) Prec@1 91.000 (87.111) Prec@5 98.000 (99.160) +2022-11-14 14:25:17,851 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0780) Prec@1 87.000 (87.110) Prec@5 99.000 (99.159) +2022-11-14 14:25:17,864 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0782) Prec@1 84.000 (87.072) Prec@5 99.000 (99.157) +2022-11-14 14:25:17,878 Test: [83/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0782) Prec@1 87.000 (87.071) Prec@5 99.000 (99.155) +2022-11-14 14:25:17,891 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0782) Prec@1 87.000 (87.071) Prec@5 99.000 (99.153) +2022-11-14 14:25:17,903 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0784) Prec@1 84.000 (87.035) Prec@5 98.000 (99.140) +2022-11-14 14:25:17,915 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0783) Prec@1 85.000 (87.011) Prec@5 99.000 (99.138) +2022-11-14 14:25:17,930 Test: [87/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0785) Prec@1 87.000 (87.011) Prec@5 99.000 (99.136) +2022-11-14 14:25:17,943 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0786) Prec@1 84.000 (86.978) Prec@5 99.000 (99.135) +2022-11-14 14:25:17,957 Test: [89/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0788) Prec@1 88.000 (86.989) Prec@5 97.000 (99.111) +2022-11-14 14:25:17,971 Test: [90/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0785) Prec@1 91.000 (87.033) Prec@5 100.000 (99.121) +2022-11-14 14:25:17,984 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0783) Prec@1 91.000 (87.076) Prec@5 99.000 (99.120) +2022-11-14 14:25:17,998 Test: [92/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0784) Prec@1 85.000 (87.054) Prec@5 99.000 (99.118) +2022-11-14 14:25:18,010 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0785) Prec@1 85.000 (87.032) Prec@5 99.000 (99.117) +2022-11-14 14:25:18,019 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0787) Prec@1 80.000 (86.958) Prec@5 100.000 (99.126) +2022-11-14 14:25:18,032 Test: [95/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0786) Prec@1 90.000 (86.990) Prec@5 100.000 (99.135) +2022-11-14 14:25:18,043 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0783) Prec@1 93.000 (87.052) Prec@5 99.000 (99.134) +2022-11-14 14:25:18,053 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0786) Prec@1 82.000 (87.000) Prec@5 99.000 (99.133) +2022-11-14 14:25:18,064 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1114 (0.0790) Prec@1 81.000 (86.939) Prec@5 100.000 (99.141) +2022-11-14 14:25:18,073 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0790) Prec@1 86.000 (86.930) Prec@5 100.000 (99.150) +2022-11-14 14:25:18,136 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:25:18,513 Epoch: [195][0/500] Time 0.039 (0.039) Data 0.274 (0.274) Loss 0.0275 (0.0275) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:25:18,805 Epoch: [195][10/500] Time 0.025 (0.027) Data 0.002 (0.027) Loss 0.0617 (0.0446) Prec@1 89.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:25:19,084 Epoch: [195][20/500] Time 0.025 (0.026) Data 0.002 (0.015) Loss 0.0261 (0.0384) Prec@1 96.000 (93.333) Prec@5 100.000 (99.667) +2022-11-14 14:25:19,396 Epoch: [195][30/500] Time 0.034 (0.026) Data 0.002 (0.011) Loss 0.0340 (0.0373) Prec@1 95.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:25:19,732 Epoch: [195][40/500] Time 0.037 (0.027) Data 0.002 (0.009) Loss 0.0376 (0.0374) Prec@1 95.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 14:25:20,074 Epoch: [195][50/500] Time 0.032 (0.028) Data 0.001 (0.007) Loss 0.0566 (0.0406) Prec@1 90.000 (93.333) Prec@5 100.000 (99.833) +2022-11-14 14:25:20,413 Epoch: [195][60/500] Time 0.031 (0.028) Data 0.002 (0.006) Loss 0.0585 (0.0431) Prec@1 92.000 (93.143) Prec@5 100.000 (99.857) +2022-11-14 14:25:20,821 Epoch: [195][70/500] Time 0.037 (0.029) Data 0.002 (0.006) Loss 0.0587 (0.0451) Prec@1 91.000 (92.875) Prec@5 99.000 (99.750) +2022-11-14 14:25:21,240 Epoch: [195][80/500] Time 0.040 (0.030) Data 0.002 (0.005) Loss 0.0430 (0.0449) Prec@1 93.000 (92.889) Prec@5 100.000 (99.778) +2022-11-14 14:25:21,591 Epoch: [195][90/500] Time 0.027 (0.030) Data 0.002 (0.005) Loss 0.0312 (0.0435) Prec@1 93.000 (92.900) Prec@5 100.000 (99.800) +2022-11-14 14:25:21,926 Epoch: [195][100/500] Time 0.031 (0.030) Data 0.002 (0.005) Loss 0.0479 (0.0439) Prec@1 94.000 (93.000) Prec@5 100.000 (99.818) +2022-11-14 14:25:22,260 Epoch: [195][110/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0314 (0.0428) Prec@1 96.000 (93.250) Prec@5 100.000 (99.833) +2022-11-14 14:25:22,607 Epoch: [195][120/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0460 (0.0431) Prec@1 92.000 (93.154) Prec@5 100.000 (99.846) +2022-11-14 14:25:23,043 Epoch: [195][130/500] Time 0.041 (0.031) Data 0.002 (0.004) Loss 0.0688 (0.0449) Prec@1 90.000 (92.929) Prec@5 100.000 (99.857) +2022-11-14 14:25:23,459 Epoch: [195][140/500] Time 0.041 (0.031) Data 0.002 (0.004) Loss 0.0366 (0.0444) Prec@1 94.000 (93.000) Prec@5 100.000 (99.867) +2022-11-14 14:25:23,820 Epoch: [195][150/500] Time 0.042 (0.031) Data 0.002 (0.004) Loss 0.0448 (0.0444) Prec@1 92.000 (92.938) Prec@5 100.000 (99.875) +2022-11-14 14:25:24,176 Epoch: [195][160/500] Time 0.032 (0.031) Data 0.002 (0.004) Loss 0.0411 (0.0442) Prec@1 93.000 (92.941) Prec@5 99.000 (99.824) +2022-11-14 14:25:24,579 Epoch: [195][170/500] Time 0.027 (0.032) Data 0.002 (0.004) Loss 0.0728 (0.0458) Prec@1 87.000 (92.611) Prec@5 99.000 (99.778) +2022-11-14 14:25:24,953 Epoch: [195][180/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.0355 (0.0453) Prec@1 94.000 (92.684) Prec@5 99.000 (99.737) +2022-11-14 14:25:25,301 Epoch: [195][190/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0391 (0.0449) Prec@1 93.000 (92.700) Prec@5 100.000 (99.750) +2022-11-14 14:25:25,660 Epoch: [195][200/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0375 (0.0446) Prec@1 93.000 (92.714) Prec@5 100.000 (99.762) +2022-11-14 14:25:26,018 Epoch: [195][210/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0469 (0.0447) Prec@1 91.000 (92.636) Prec@5 100.000 (99.773) +2022-11-14 14:25:26,376 Epoch: [195][220/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0487 (0.0449) Prec@1 91.000 (92.565) Prec@5 100.000 (99.783) +2022-11-14 14:25:26,768 Epoch: [195][230/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0333 (0.0444) Prec@1 94.000 (92.625) Prec@5 100.000 (99.792) +2022-11-14 14:25:27,237 Epoch: [195][240/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0437 (0.0444) Prec@1 93.000 (92.640) Prec@5 99.000 (99.760) +2022-11-14 14:25:27,713 Epoch: [195][250/500] Time 0.047 (0.033) Data 0.002 (0.003) Loss 0.0289 (0.0438) Prec@1 96.000 (92.769) Prec@5 99.000 (99.731) +2022-11-14 14:25:28,191 Epoch: [195][260/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0384 (0.0436) Prec@1 90.000 (92.667) Prec@5 100.000 (99.741) +2022-11-14 14:25:28,700 Epoch: [195][270/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0373 (0.0433) Prec@1 93.000 (92.679) Prec@5 99.000 (99.714) +2022-11-14 14:25:29,396 Epoch: [195][280/500] Time 0.075 (0.035) Data 0.002 (0.003) Loss 0.0670 (0.0442) Prec@1 87.000 (92.483) Prec@5 100.000 (99.724) +2022-11-14 14:25:30,121 Epoch: [195][290/500] Time 0.070 (0.036) Data 0.002 (0.003) Loss 0.0530 (0.0444) Prec@1 88.000 (92.333) Prec@5 100.000 (99.733) +2022-11-14 14:25:30,598 Epoch: [195][300/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0470 (0.0445) Prec@1 90.000 (92.258) Prec@5 100.000 (99.742) +2022-11-14 14:25:31,090 Epoch: [195][310/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0404 (0.0444) Prec@1 93.000 (92.281) Prec@5 100.000 (99.750) +2022-11-14 14:25:31,600 Epoch: [195][320/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0280 (0.0439) Prec@1 96.000 (92.394) Prec@5 100.000 (99.758) +2022-11-14 14:25:32,117 Epoch: [195][330/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0324 (0.0436) Prec@1 96.000 (92.500) Prec@5 100.000 (99.765) +2022-11-14 14:25:32,596 Epoch: [195][340/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0635 (0.0441) Prec@1 91.000 (92.457) Prec@5 100.000 (99.771) +2022-11-14 14:25:33,075 Epoch: [195][350/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0473 (0.0442) Prec@1 91.000 (92.417) Prec@5 100.000 (99.778) +2022-11-14 14:25:33,551 Epoch: [195][360/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0234 (0.0437) Prec@1 96.000 (92.514) Prec@5 100.000 (99.784) +2022-11-14 14:25:34,033 Epoch: [195][370/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0493 (0.0438) Prec@1 93.000 (92.526) Prec@5 100.000 (99.789) +2022-11-14 14:25:34,510 Epoch: [195][380/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0452 (0.0438) Prec@1 91.000 (92.487) Prec@5 99.000 (99.769) +2022-11-14 14:25:34,999 Epoch: [195][390/500] Time 0.059 (0.038) Data 0.002 (0.003) Loss 0.0389 (0.0437) Prec@1 94.000 (92.525) Prec@5 100.000 (99.775) +2022-11-14 14:25:35,528 Epoch: [195][400/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0324 (0.0434) Prec@1 94.000 (92.561) Prec@5 100.000 (99.780) +2022-11-14 14:25:36,057 Epoch: [195][410/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0343 (0.0432) Prec@1 94.000 (92.595) Prec@5 100.000 (99.786) +2022-11-14 14:25:36,565 Epoch: [195][420/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0431 (0.0432) Prec@1 92.000 (92.581) Prec@5 100.000 (99.791) +2022-11-14 14:25:37,051 Epoch: [195][430/500] Time 0.053 (0.038) Data 0.002 (0.003) Loss 0.0511 (0.0434) Prec@1 91.000 (92.545) Prec@5 99.000 (99.773) +2022-11-14 14:25:37,594 Epoch: [195][440/500] Time 0.092 (0.039) Data 0.002 (0.003) Loss 0.0452 (0.0434) Prec@1 93.000 (92.556) Prec@5 100.000 (99.778) +2022-11-14 14:25:38,081 Epoch: [195][450/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0425 (0.0434) Prec@1 95.000 (92.609) Prec@5 100.000 (99.783) +2022-11-14 14:25:38,570 Epoch: [195][460/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0598 (0.0438) Prec@1 90.000 (92.553) Prec@5 99.000 (99.766) +2022-11-14 14:25:39,057 Epoch: [195][470/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0246 (0.0434) Prec@1 96.000 (92.625) Prec@5 100.000 (99.771) +2022-11-14 14:25:39,538 Epoch: [195][480/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.0264 (0.0430) Prec@1 97.000 (92.714) Prec@5 100.000 (99.776) +2022-11-14 14:25:40,026 Epoch: [195][490/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0660 (0.0435) Prec@1 88.000 (92.620) Prec@5 100.000 (99.780) +2022-11-14 14:25:40,514 Epoch: [195][499/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0508 (0.0436) Prec@1 91.000 (92.588) Prec@5 99.000 (99.765) +2022-11-14 14:25:40,832 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0437 (0.0437) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:25:40,840 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0552) Prec@1 89.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:25:40,851 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0629) Prec@1 89.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 14:25:40,864 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0673) Prec@1 86.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 14:25:40,873 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0700) Prec@1 87.000 (89.000) Prec@5 100.000 (99.800) +2022-11-14 14:25:40,883 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0405 (0.0651) Prec@1 94.000 (89.833) Prec@5 100.000 (99.833) +2022-11-14 14:25:40,895 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0646) Prec@1 91.000 (90.000) Prec@5 100.000 (99.857) +2022-11-14 14:25:40,908 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0648) Prec@1 88.000 (89.750) Prec@5 100.000 (99.875) +2022-11-14 14:25:40,918 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0667) Prec@1 87.000 (89.444) Prec@5 100.000 (99.889) +2022-11-14 14:25:40,929 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0683) Prec@1 84.000 (88.900) Prec@5 99.000 (99.800) +2022-11-14 14:25:40,940 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0678) Prec@1 91.000 (89.091) Prec@5 98.000 (99.636) +2022-11-14 14:25:40,950 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0689) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:25:40,961 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0677) Prec@1 91.000 (89.154) Prec@5 99.000 (99.615) +2022-11-14 14:25:40,973 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0680) Prec@1 88.000 (89.071) Prec@5 100.000 (99.643) +2022-11-14 14:25:40,984 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0673) Prec@1 90.000 (89.133) Prec@5 100.000 (99.667) +2022-11-14 14:25:40,996 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0695) Prec@1 83.000 (88.750) Prec@5 100.000 (99.688) +2022-11-14 14:25:41,009 Test: [16/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0688) Prec@1 91.000 (88.882) Prec@5 99.000 (99.647) +2022-11-14 14:25:41,021 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0702) Prec@1 85.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:25:41,033 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0713) Prec@1 83.000 (88.368) Prec@5 100.000 (99.684) +2022-11-14 14:25:41,045 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0722) Prec@1 85.000 (88.200) Prec@5 98.000 (99.600) +2022-11-14 14:25:41,058 Test: [20/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1162 (0.0743) Prec@1 80.000 (87.810) Prec@5 100.000 (99.619) +2022-11-14 14:25:41,070 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0739) Prec@1 87.000 (87.773) Prec@5 100.000 (99.636) +2022-11-14 14:25:41,080 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0749) Prec@1 85.000 (87.652) Prec@5 97.000 (99.522) +2022-11-14 14:25:41,092 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0747) Prec@1 88.000 (87.667) Prec@5 100.000 (99.542) +2022-11-14 14:25:41,105 Test: [24/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0756) Prec@1 82.000 (87.440) Prec@5 98.000 (99.480) +2022-11-14 14:25:41,118 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0762) Prec@1 87.000 (87.423) Prec@5 99.000 (99.462) +2022-11-14 14:25:41,127 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0754) Prec@1 91.000 (87.556) Prec@5 100.000 (99.481) +2022-11-14 14:25:41,138 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0754) Prec@1 87.000 (87.536) Prec@5 100.000 (99.500) +2022-11-14 14:25:41,149 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0754) Prec@1 87.000 (87.517) Prec@5 99.000 (99.483) +2022-11-14 14:25:41,160 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0747) Prec@1 90.000 (87.600) Prec@5 98.000 (99.433) +2022-11-14 14:25:41,170 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0745) Prec@1 88.000 (87.613) Prec@5 100.000 (99.452) +2022-11-14 14:25:41,184 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0746) Prec@1 87.000 (87.594) Prec@5 100.000 (99.469) +2022-11-14 14:25:41,196 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0746) Prec@1 87.000 (87.576) Prec@5 99.000 (99.455) +2022-11-14 14:25:41,209 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0749) Prec@1 83.000 (87.441) Prec@5 100.000 (99.471) +2022-11-14 14:25:41,222 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0756) Prec@1 85.000 (87.371) Prec@5 98.000 (99.429) +2022-11-14 14:25:41,233 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0753) Prec@1 91.000 (87.472) Prec@5 99.000 (99.417) +2022-11-14 14:25:41,246 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0754) Prec@1 88.000 (87.486) Prec@5 98.000 (99.378) +2022-11-14 14:25:41,258 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0760) Prec@1 85.000 (87.421) Prec@5 100.000 (99.395) +2022-11-14 14:25:41,271 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0755) Prec@1 90.000 (87.487) Prec@5 99.000 (99.385) +2022-11-14 14:25:41,283 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0753) Prec@1 89.000 (87.525) Prec@5 98.000 (99.350) +2022-11-14 14:25:41,296 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0759) Prec@1 85.000 (87.463) Prec@5 99.000 (99.341) +2022-11-14 14:25:41,308 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0756) Prec@1 89.000 (87.500) Prec@5 98.000 (99.310) +2022-11-14 14:25:41,321 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0433 (0.0748) Prec@1 92.000 (87.605) Prec@5 99.000 (99.302) +2022-11-14 14:25:41,333 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0746) Prec@1 90.000 (87.659) Prec@5 99.000 (99.295) +2022-11-14 14:25:41,346 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0742) Prec@1 90.000 (87.711) Prec@5 99.000 (99.289) +2022-11-14 14:25:41,361 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0749) Prec@1 83.000 (87.609) Prec@5 99.000 (99.283) +2022-11-14 14:25:41,374 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0752) Prec@1 85.000 (87.553) Prec@5 100.000 (99.298) +2022-11-14 14:25:41,386 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0757) Prec@1 85.000 (87.500) Prec@5 99.000 (99.292) +2022-11-14 14:25:41,399 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0756) Prec@1 89.000 (87.531) Prec@5 100.000 (99.306) +2022-11-14 14:25:41,411 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1169 (0.0764) Prec@1 80.000 (87.380) Prec@5 100.000 (99.320) +2022-11-14 14:25:41,420 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0762) Prec@1 91.000 (87.451) Prec@5 100.000 (99.333) +2022-11-14 14:25:41,432 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0765) Prec@1 84.000 (87.385) Prec@5 99.000 (99.327) +2022-11-14 14:25:41,445 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0769) Prec@1 81.000 (87.264) Prec@5 99.000 (99.321) +2022-11-14 14:25:41,458 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0766) Prec@1 89.000 (87.296) Prec@5 100.000 (99.333) +2022-11-14 14:25:41,470 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0768) Prec@1 84.000 (87.236) Prec@5 100.000 (99.345) +2022-11-14 14:25:41,482 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0770) Prec@1 87.000 (87.232) Prec@5 99.000 (99.339) +2022-11-14 14:25:41,496 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0769) Prec@1 88.000 (87.246) Prec@5 100.000 (99.351) +2022-11-14 14:25:41,509 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0412 (0.0763) Prec@1 94.000 (87.362) Prec@5 99.000 (99.345) +2022-11-14 14:25:41,520 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1254 (0.0772) Prec@1 79.000 (87.220) Prec@5 100.000 (99.356) +2022-11-14 14:25:41,532 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0774) Prec@1 83.000 (87.150) Prec@5 99.000 (99.350) +2022-11-14 14:25:41,546 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0776) Prec@1 86.000 (87.131) Prec@5 99.000 (99.344) +2022-11-14 14:25:41,562 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0775) Prec@1 87.000 (87.129) Prec@5 99.000 (99.339) +2022-11-14 14:25:41,574 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0774) Prec@1 86.000 (87.111) Prec@5 100.000 (99.349) +2022-11-14 14:25:41,586 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0492 (0.0770) Prec@1 92.000 (87.188) Prec@5 100.000 (99.359) +2022-11-14 14:25:41,599 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0772) Prec@1 85.000 (87.154) Prec@5 97.000 (99.323) +2022-11-14 14:25:41,612 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0772) Prec@1 87.000 (87.152) Prec@5 100.000 (99.333) +2022-11-14 14:25:41,623 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0769) Prec@1 92.000 (87.224) Prec@5 100.000 (99.343) +2022-11-14 14:25:41,634 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0768) Prec@1 89.000 (87.250) Prec@5 99.000 (99.338) +2022-11-14 14:25:41,647 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0767) Prec@1 88.000 (87.261) Prec@5 100.000 (99.348) +2022-11-14 14:25:41,659 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0769) Prec@1 84.000 (87.214) Prec@5 99.000 (99.343) +2022-11-14 14:25:41,672 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0770) Prec@1 88.000 (87.225) Prec@5 99.000 (99.338) +2022-11-14 14:25:41,684 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0770) Prec@1 90.000 (87.264) Prec@5 100.000 (99.347) +2022-11-14 14:25:41,696 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0766) Prec@1 94.000 (87.356) Prec@5 100.000 (99.356) +2022-11-14 14:25:41,707 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0761) Prec@1 94.000 (87.446) Prec@5 100.000 (99.365) +2022-11-14 14:25:41,719 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1126 (0.0766) Prec@1 79.000 (87.333) Prec@5 99.000 (99.360) +2022-11-14 14:25:41,731 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0763) Prec@1 91.000 (87.382) Prec@5 99.000 (99.355) +2022-11-14 14:25:41,741 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0759) Prec@1 90.000 (87.416) Prec@5 100.000 (99.364) +2022-11-14 14:25:41,753 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0761) Prec@1 85.000 (87.385) Prec@5 99.000 (99.359) +2022-11-14 14:25:41,767 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0760) Prec@1 90.000 (87.418) Prec@5 100.000 (99.367) +2022-11-14 14:25:41,778 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 86.000 (87.400) Prec@5 98.000 (99.350) +2022-11-14 14:25:41,790 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0760) Prec@1 88.000 (87.407) Prec@5 99.000 (99.346) +2022-11-14 14:25:41,800 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0763) Prec@1 86.000 (87.390) Prec@5 100.000 (99.354) +2022-11-14 14:25:41,809 Test: [82/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0765) Prec@1 81.000 (87.313) Prec@5 100.000 (99.361) +2022-11-14 14:25:41,820 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0767) Prec@1 84.000 (87.274) Prec@5 99.000 (99.357) +2022-11-14 14:25:41,830 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0768) Prec@1 86.000 (87.259) Prec@5 100.000 (99.365) +2022-11-14 14:25:41,842 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1285 (0.0774) Prec@1 80.000 (87.174) Prec@5 98.000 (99.349) +2022-11-14 14:25:41,854 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0774) Prec@1 89.000 (87.195) Prec@5 100.000 (99.356) +2022-11-14 14:25:41,865 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0772) Prec@1 91.000 (87.239) Prec@5 99.000 (99.352) +2022-11-14 14:25:41,878 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0771) Prec@1 86.000 (87.225) Prec@5 99.000 (99.348) +2022-11-14 14:25:41,888 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0773) Prec@1 82.000 (87.167) Prec@5 100.000 (99.356) +2022-11-14 14:25:41,902 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0771) Prec@1 87.000 (87.165) Prec@5 100.000 (99.363) +2022-11-14 14:25:41,915 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0769) Prec@1 90.000 (87.196) Prec@5 100.000 (99.370) +2022-11-14 14:25:41,929 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0768) Prec@1 90.000 (87.226) Prec@5 100.000 (99.376) +2022-11-14 14:25:41,942 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0769) Prec@1 87.000 (87.223) Prec@5 99.000 (99.372) +2022-11-14 14:25:41,955 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.0772) Prec@1 82.000 (87.168) Prec@5 99.000 (99.368) +2022-11-14 14:25:41,966 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0770) Prec@1 90.000 (87.198) Prec@5 100.000 (99.375) +2022-11-14 14:25:41,977 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0388 (0.0767) Prec@1 94.000 (87.268) Prec@5 98.000 (99.361) +2022-11-14 14:25:41,989 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0769) Prec@1 83.000 (87.224) Prec@5 99.000 (99.357) +2022-11-14 14:25:42,001 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0772) Prec@1 82.000 (87.172) Prec@5 99.000 (99.354) +2022-11-14 14:25:42,013 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0772) Prec@1 88.000 (87.180) Prec@5 99.000 (99.350) +2022-11-14 14:25:42,077 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:25:42,398 Epoch: [196][0/500] Time 0.031 (0.031) Data 0.227 (0.227) Loss 0.0370 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:25:42,620 Epoch: [196][10/500] Time 0.017 (0.021) Data 0.001 (0.022) Loss 0.0452 (0.0411) Prec@1 93.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 14:25:42,826 Epoch: [196][20/500] Time 0.018 (0.020) Data 0.001 (0.012) Loss 0.0482 (0.0434) Prec@1 92.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:25:43,103 Epoch: [196][30/500] Time 0.026 (0.021) Data 0.002 (0.009) Loss 0.0380 (0.0421) Prec@1 93.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:25:43,402 Epoch: [196][40/500] Time 0.026 (0.022) Data 0.002 (0.007) Loss 0.0553 (0.0447) Prec@1 92.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 14:25:43,699 Epoch: [196][50/500] Time 0.026 (0.023) Data 0.002 (0.006) Loss 0.0527 (0.0461) Prec@1 90.000 (92.333) Prec@5 100.000 (99.833) +2022-11-14 14:25:44,003 Epoch: [196][60/500] Time 0.024 (0.024) Data 0.002 (0.005) Loss 0.0526 (0.0470) Prec@1 93.000 (92.429) Prec@5 100.000 (99.857) +2022-11-14 14:25:44,307 Epoch: [196][70/500] Time 0.031 (0.024) Data 0.002 (0.005) Loss 0.0439 (0.0466) Prec@1 94.000 (92.625) Prec@5 100.000 (99.875) +2022-11-14 14:25:44,604 Epoch: [196][80/500] Time 0.027 (0.025) Data 0.002 (0.005) Loss 0.0420 (0.0461) Prec@1 93.000 (92.667) Prec@5 100.000 (99.889) +2022-11-14 14:25:44,919 Epoch: [196][90/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0244 (0.0439) Prec@1 97.000 (93.100) Prec@5 100.000 (99.900) +2022-11-14 14:25:45,270 Epoch: [196][100/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0395 (0.0435) Prec@1 94.000 (93.182) Prec@5 100.000 (99.909) +2022-11-14 14:25:45,619 Epoch: [196][110/500] Time 0.046 (0.026) Data 0.002 (0.004) Loss 0.0361 (0.0429) Prec@1 93.000 (93.167) Prec@5 100.000 (99.917) +2022-11-14 14:25:46,078 Epoch: [196][120/500] Time 0.041 (0.027) Data 0.002 (0.004) Loss 0.0369 (0.0424) Prec@1 94.000 (93.231) Prec@5 100.000 (99.923) +2022-11-14 14:25:46,570 Epoch: [196][130/500] Time 0.038 (0.028) Data 0.002 (0.004) Loss 0.0484 (0.0429) Prec@1 91.000 (93.071) Prec@5 100.000 (99.929) +2022-11-14 14:25:47,055 Epoch: [196][140/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.0363 (0.0424) Prec@1 94.000 (93.133) Prec@5 100.000 (99.933) +2022-11-14 14:25:47,505 Epoch: [196][150/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0326 (0.0418) Prec@1 95.000 (93.250) Prec@5 100.000 (99.938) +2022-11-14 14:25:47,990 Epoch: [196][160/500] Time 0.047 (0.031) Data 0.002 (0.003) Loss 0.0460 (0.0421) Prec@1 92.000 (93.176) Prec@5 100.000 (99.941) +2022-11-14 14:25:48,442 Epoch: [196][170/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0634 (0.0433) Prec@1 91.000 (93.056) Prec@5 99.000 (99.889) +2022-11-14 14:25:48,896 Epoch: [196][180/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0461 (0.0434) Prec@1 91.000 (92.947) Prec@5 100.000 (99.895) +2022-11-14 14:25:49,382 Epoch: [196][190/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0288 (0.0427) Prec@1 94.000 (93.000) Prec@5 100.000 (99.900) +2022-11-14 14:25:49,861 Epoch: [196][200/500] Time 0.076 (0.033) Data 0.002 (0.003) Loss 0.0343 (0.0423) Prec@1 96.000 (93.143) Prec@5 100.000 (99.905) +2022-11-14 14:25:50,295 Epoch: [196][210/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0220 (0.0414) Prec@1 96.000 (93.273) Prec@5 100.000 (99.909) +2022-11-14 14:25:50,753 Epoch: [196][220/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0592 (0.0421) Prec@1 89.000 (93.087) Prec@5 100.000 (99.913) +2022-11-14 14:25:51,232 Epoch: [196][230/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0246 (0.0414) Prec@1 96.000 (93.208) Prec@5 99.000 (99.875) +2022-11-14 14:25:51,683 Epoch: [196][240/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0552 (0.0420) Prec@1 91.000 (93.120) Prec@5 100.000 (99.880) +2022-11-14 14:25:52,133 Epoch: [196][250/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0802 (0.0434) Prec@1 89.000 (92.962) Prec@5 100.000 (99.885) +2022-11-14 14:25:52,583 Epoch: [196][260/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0509 (0.0437) Prec@1 93.000 (92.963) Prec@5 100.000 (99.889) +2022-11-14 14:25:53,030 Epoch: [196][270/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0422 (0.0436) Prec@1 94.000 (93.000) Prec@5 99.000 (99.857) +2022-11-14 14:25:53,452 Epoch: [196][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0498 (0.0439) Prec@1 93.000 (93.000) Prec@5 100.000 (99.862) +2022-11-14 14:25:53,896 Epoch: [196][290/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0369 (0.0436) Prec@1 92.000 (92.967) Prec@5 100.000 (99.867) +2022-11-14 14:25:54,351 Epoch: [196][300/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0396 (0.0435) Prec@1 93.000 (92.968) Prec@5 100.000 (99.871) +2022-11-14 14:25:54,806 Epoch: [196][310/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0578 (0.0439) Prec@1 90.000 (92.875) Prec@5 100.000 (99.875) +2022-11-14 14:25:55,290 Epoch: [196][320/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0096 (0.0429) Prec@1 99.000 (93.061) Prec@5 100.000 (99.879) +2022-11-14 14:25:55,736 Epoch: [196][330/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0305 (0.0425) Prec@1 93.000 (93.059) Prec@5 99.000 (99.853) +2022-11-14 14:25:56,208 Epoch: [196][340/500] Time 0.046 (0.036) Data 0.002 (0.003) Loss 0.0244 (0.0420) Prec@1 97.000 (93.171) Prec@5 100.000 (99.857) +2022-11-14 14:25:56,646 Epoch: [196][350/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0433 (0.0421) Prec@1 94.000 (93.194) Prec@5 99.000 (99.833) +2022-11-14 14:25:57,103 Epoch: [196][360/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0357 (0.0419) Prec@1 95.000 (93.243) Prec@5 100.000 (99.838) +2022-11-14 14:25:57,554 Epoch: [196][370/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0419 (0.0419) Prec@1 93.000 (93.237) Prec@5 100.000 (99.842) +2022-11-14 14:25:58,003 Epoch: [196][380/500] Time 0.057 (0.036) Data 0.002 (0.002) Loss 0.0342 (0.0417) Prec@1 94.000 (93.256) Prec@5 100.000 (99.846) +2022-11-14 14:25:58,444 Epoch: [196][390/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0337 (0.0415) Prec@1 92.000 (93.225) Prec@5 100.000 (99.850) +2022-11-14 14:25:58,878 Epoch: [196][400/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0362 (0.0414) Prec@1 94.000 (93.244) Prec@5 100.000 (99.854) +2022-11-14 14:25:59,329 Epoch: [196][410/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0657 (0.0419) Prec@1 87.000 (93.095) Prec@5 100.000 (99.857) +2022-11-14 14:25:59,754 Epoch: [196][420/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0386 (0.0419) Prec@1 95.000 (93.140) Prec@5 100.000 (99.860) +2022-11-14 14:26:00,207 Epoch: [196][430/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0547 (0.0421) Prec@1 89.000 (93.045) Prec@5 99.000 (99.841) +2022-11-14 14:26:00,650 Epoch: [196][440/500] Time 0.036 (0.037) Data 0.002 (0.002) Loss 0.0418 (0.0421) Prec@1 94.000 (93.067) Prec@5 100.000 (99.844) +2022-11-14 14:26:01,100 Epoch: [196][450/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0530 (0.0424) Prec@1 89.000 (92.978) Prec@5 99.000 (99.826) +2022-11-14 14:26:01,541 Epoch: [196][460/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0789 (0.0432) Prec@1 87.000 (92.851) Prec@5 99.000 (99.809) +2022-11-14 14:26:01,994 Epoch: [196][470/500] Time 0.060 (0.037) Data 0.002 (0.002) Loss 0.0308 (0.0429) Prec@1 96.000 (92.917) Prec@5 100.000 (99.812) +2022-11-14 14:26:02,451 Epoch: [196][480/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0525 (0.0431) Prec@1 89.000 (92.837) Prec@5 100.000 (99.816) +2022-11-14 14:26:02,898 Epoch: [196][490/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0147 (0.0425) Prec@1 98.000 (92.940) Prec@5 100.000 (99.820) +2022-11-14 14:26:03,327 Epoch: [196][499/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0554 (0.0428) Prec@1 90.000 (92.882) Prec@5 100.000 (99.824) +2022-11-14 14:26:03,622 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0753 (0.0753) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:03,632 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0666 (0.0709) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:26:03,642 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0758) Prec@1 81.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:03,655 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0836 (0.0778) Prec@1 88.000 (86.500) Prec@5 98.000 (99.500) +2022-11-14 14:26:03,663 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0730) Prec@1 94.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 14:26:03,670 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0695) Prec@1 91.000 (88.500) Prec@5 99.000 (99.333) +2022-11-14 14:26:03,679 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0668) Prec@1 91.000 (88.857) Prec@5 100.000 (99.429) +2022-11-14 14:26:03,691 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0690) Prec@1 85.000 (88.375) Prec@5 99.000 (99.375) +2022-11-14 14:26:03,701 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0727) Prec@1 85.000 (88.000) Prec@5 98.000 (99.222) +2022-11-14 14:26:03,712 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0728) Prec@1 86.000 (87.800) Prec@5 98.000 (99.100) +2022-11-14 14:26:03,723 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0719) Prec@1 89.000 (87.909) Prec@5 100.000 (99.182) +2022-11-14 14:26:03,735 Test: [11/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0711) Prec@1 93.000 (88.333) Prec@5 99.000 (99.167) +2022-11-14 14:26:03,747 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0707) Prec@1 89.000 (88.385) Prec@5 100.000 (99.231) +2022-11-14 14:26:03,757 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0699) Prec@1 90.000 (88.500) Prec@5 98.000 (99.143) +2022-11-14 14:26:03,768 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0706) Prec@1 85.000 (88.267) Prec@5 98.000 (99.067) +2022-11-14 14:26:03,781 Test: [15/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0703) Prec@1 89.000 (88.312) Prec@5 99.000 (99.062) +2022-11-14 14:26:03,792 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0422 (0.0686) Prec@1 94.000 (88.647) Prec@5 99.000 (99.059) +2022-11-14 14:26:03,802 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1120 (0.0710) Prec@1 83.000 (88.333) Prec@5 100.000 (99.111) +2022-11-14 14:26:03,812 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0715) Prec@1 87.000 (88.263) Prec@5 99.000 (99.105) +2022-11-14 14:26:03,823 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0720) Prec@1 89.000 (88.300) Prec@5 100.000 (99.150) +2022-11-14 14:26:03,833 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0722) Prec@1 88.000 (88.286) Prec@5 100.000 (99.190) +2022-11-14 14:26:03,844 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0730) Prec@1 86.000 (88.182) Prec@5 99.000 (99.182) +2022-11-14 14:26:03,855 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0748) Prec@1 83.000 (87.957) Prec@5 99.000 (99.174) +2022-11-14 14:26:03,866 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0751) Prec@1 86.000 (87.875) Prec@5 100.000 (99.208) +2022-11-14 14:26:03,876 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0758) Prec@1 85.000 (87.760) Prec@5 99.000 (99.200) +2022-11-14 14:26:03,886 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0765) Prec@1 86.000 (87.692) Prec@5 99.000 (99.192) +2022-11-14 14:26:03,897 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0759) Prec@1 90.000 (87.778) Prec@5 100.000 (99.222) +2022-11-14 14:26:03,908 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0761) Prec@1 86.000 (87.714) Prec@5 99.000 (99.214) +2022-11-14 14:26:03,919 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0763) Prec@1 87.000 (87.690) Prec@5 100.000 (99.241) +2022-11-14 14:26:03,932 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0764) Prec@1 87.000 (87.667) Prec@5 99.000 (99.233) +2022-11-14 14:26:03,943 Test: 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Loss 0.0793 (0.0775) Prec@1 87.000 (87.432) Prec@5 99.000 (99.324) +2022-11-14 14:26:04,021 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.0785) Prec@1 82.000 (87.289) Prec@5 98.000 (99.289) +2022-11-14 14:26:04,032 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0778) Prec@1 93.000 (87.436) Prec@5 99.000 (99.282) +2022-11-14 14:26:04,043 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0776) Prec@1 87.000 (87.425) Prec@5 100.000 (99.300) +2022-11-14 14:26:04,053 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0779) Prec@1 88.000 (87.439) Prec@5 98.000 (99.268) +2022-11-14 14:26:04,063 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0775) Prec@1 88.000 (87.452) Prec@5 99.000 (99.262) +2022-11-14 14:26:04,074 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0768) Prec@1 92.000 (87.558) Prec@5 99.000 (99.256) +2022-11-14 14:26:04,084 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0769) Prec@1 87.000 (87.545) Prec@5 99.000 (99.250) +2022-11-14 14:26:04,095 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0765) Prec@1 88.000 (87.556) Prec@5 100.000 (99.267) +2022-11-14 14:26:04,106 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0771) Prec@1 82.000 (87.435) Prec@5 100.000 (99.283) +2022-11-14 14:26:04,116 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0773) Prec@1 84.000 (87.362) Prec@5 99.000 (99.277) +2022-11-14 14:26:04,127 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0779) Prec@1 80.000 (87.208) Prec@5 100.000 (99.292) +2022-11-14 14:26:04,138 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0774) Prec@1 90.000 (87.265) Prec@5 100.000 (99.306) +2022-11-14 14:26:04,148 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0781) Prec@1 83.000 (87.180) Prec@5 99.000 (99.300) +2022-11-14 14:26:04,158 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0780) Prec@1 87.000 (87.176) Prec@5 100.000 (99.314) +2022-11-14 14:26:04,169 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0785) Prec@1 83.000 (87.096) Prec@5 99.000 (99.308) +2022-11-14 14:26:04,181 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0785) Prec@1 83.000 (87.019) Prec@5 99.000 (99.302) +2022-11-14 14:26:04,191 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0783) Prec@1 90.000 (87.074) Prec@5 99.000 (99.296) +2022-11-14 14:26:04,202 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0784) Prec@1 85.000 (87.036) Prec@5 100.000 (99.309) +2022-11-14 14:26:04,210 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0784) Prec@1 87.000 (87.036) Prec@5 99.000 (99.304) +2022-11-14 14:26:04,220 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0786) Prec@1 85.000 (87.000) Prec@5 100.000 (99.316) +2022-11-14 14:26:04,230 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0783) Prec@1 89.000 (87.034) Prec@5 98.000 (99.293) +2022-11-14 14:26:04,240 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0788) Prec@1 82.000 (86.949) Prec@5 100.000 (99.305) +2022-11-14 14:26:04,250 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0786) Prec@1 88.000 (86.967) Prec@5 100.000 (99.317) +2022-11-14 14:26:04,259 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0788) Prec@1 86.000 (86.951) Prec@5 97.000 (99.279) +2022-11-14 14:26:04,269 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0786) Prec@1 90.000 (87.000) Prec@5 99.000 (99.274) +2022-11-14 14:26:04,280 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0785) Prec@1 89.000 (87.032) Prec@5 100.000 (99.286) +2022-11-14 14:26:04,292 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0391 (0.0779) Prec@1 95.000 (87.156) Prec@5 100.000 (99.297) +2022-11-14 14:26:04,303 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0782) Prec@1 84.000 (87.108) Prec@5 100.000 (99.308) +2022-11-14 14:26:04,314 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0784) Prec@1 84.000 (87.061) Prec@5 100.000 (99.318) +2022-11-14 14:26:04,324 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0780) Prec@1 91.000 (87.119) Prec@5 100.000 (99.328) +2022-11-14 14:26:04,335 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0779) Prec@1 87.000 (87.118) Prec@5 98.000 (99.309) +2022-11-14 14:26:04,345 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0777) Prec@1 89.000 (87.145) Prec@5 99.000 (99.304) +2022-11-14 14:26:04,356 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0780) Prec@1 84.000 (87.100) Prec@5 100.000 (99.314) +2022-11-14 14:26:04,366 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0782) Prec@1 85.000 (87.070) Prec@5 99.000 (99.310) +2022-11-14 14:26:04,377 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0780) Prec@1 87.000 (87.069) Prec@5 100.000 (99.319) +2022-11-14 14:26:04,389 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0777) Prec@1 90.000 (87.110) Prec@5 99.000 (99.315) +2022-11-14 14:26:04,401 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0775) Prec@1 92.000 (87.176) Prec@5 100.000 (99.324) +2022-11-14 14:26:04,412 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0778) Prec@1 83.000 (87.120) Prec@5 100.000 (99.333) +2022-11-14 14:26:04,423 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0777) Prec@1 88.000 (87.132) Prec@5 99.000 (99.329) +2022-11-14 14:26:04,436 Test: [76/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0778) Prec@1 85.000 (87.104) Prec@5 97.000 (99.299) +2022-11-14 14:26:04,449 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0778) Prec@1 87.000 (87.103) Prec@5 98.000 (99.282) +2022-11-14 14:26:04,461 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0778) Prec@1 87.000 (87.101) Prec@5 100.000 (99.291) +2022-11-14 14:26:04,472 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0779) Prec@1 85.000 (87.075) Prec@5 98.000 (99.275) +2022-11-14 14:26:04,485 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0779) Prec@1 85.000 (87.049) Prec@5 99.000 (99.272) +2022-11-14 14:26:04,497 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0779) Prec@1 89.000 (87.073) Prec@5 100.000 (99.280) +2022-11-14 14:26:04,507 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0778) Prec@1 87.000 (87.072) Prec@5 100.000 (99.289) +2022-11-14 14:26:04,517 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0776) Prec@1 89.000 (87.095) Prec@5 100.000 (99.298) +2022-11-14 14:26:04,527 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0778) Prec@1 84.000 (87.059) Prec@5 99.000 (99.294) +2022-11-14 14:26:04,538 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0780) Prec@1 85.000 (87.035) Prec@5 98.000 (99.279) +2022-11-14 14:26:04,549 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0780) Prec@1 86.000 (87.023) Prec@5 99.000 (99.276) +2022-11-14 14:26:04,559 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0779) Prec@1 90.000 (87.057) Prec@5 98.000 (99.261) +2022-11-14 14:26:04,572 Test: [88/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0776) Prec@1 89.000 (87.079) Prec@5 99.000 (99.258) +2022-11-14 14:26:04,586 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0776) Prec@1 88.000 (87.089) Prec@5 100.000 (99.267) +2022-11-14 14:26:04,595 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0774) Prec@1 92.000 (87.143) Prec@5 100.000 (99.275) +2022-11-14 14:26:04,606 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0773) Prec@1 92.000 (87.196) Prec@5 99.000 (99.272) +2022-11-14 14:26:04,615 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0776) Prec@1 83.000 (87.151) Prec@5 99.000 (99.269) +2022-11-14 14:26:04,626 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0774) Prec@1 90.000 (87.181) Prec@5 100.000 (99.277) +2022-11-14 14:26:04,636 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0777) Prec@1 84.000 (87.147) Prec@5 99.000 (99.274) +2022-11-14 14:26:04,646 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0775) Prec@1 90.000 (87.177) Prec@5 100.000 (99.281) +2022-11-14 14:26:04,657 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0774) Prec@1 88.000 (87.186) Prec@5 99.000 (99.278) +2022-11-14 14:26:04,668 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0777) Prec@1 82.000 (87.133) Prec@5 99.000 (99.276) +2022-11-14 14:26:04,678 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0780) Prec@1 84.000 (87.101) Prec@5 99.000 (99.273) +2022-11-14 14:26:04,688 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0780) Prec@1 88.000 (87.110) Prec@5 99.000 (99.270) +2022-11-14 14:26:04,749 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:26:05,056 Epoch: [197][0/500] Time 0.028 (0.028) Data 0.221 (0.221) Loss 0.0415 (0.0415) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:05,270 Epoch: [197][10/500] Time 0.020 (0.020) Data 0.002 (0.022) Loss 0.0503 (0.0459) Prec@1 93.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:26:05,503 Epoch: [197][20/500] Time 0.025 (0.020) Data 0.002 (0.012) Loss 0.0475 (0.0464) Prec@1 92.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:26:05,778 Epoch: [197][30/500] Time 0.025 (0.021) Data 0.001 (0.009) Loss 0.0199 (0.0398) Prec@1 98.000 (93.750) Prec@5 99.000 (99.500) +2022-11-14 14:26:06,064 Epoch: [197][40/500] Time 0.025 (0.022) Data 0.001 (0.007) Loss 0.0610 (0.0441) Prec@1 91.000 (93.200) Prec@5 100.000 (99.600) +2022-11-14 14:26:06,345 Epoch: [197][50/500] Time 0.024 (0.023) Data 0.002 (0.006) Loss 0.0429 (0.0439) Prec@1 93.000 (93.167) Prec@5 100.000 (99.667) +2022-11-14 14:26:06,652 Epoch: [197][60/500] Time 0.036 (0.023) Data 0.001 (0.005) Loss 0.0428 (0.0437) Prec@1 93.000 (93.143) Prec@5 99.000 (99.571) +2022-11-14 14:26:07,135 Epoch: [197][70/500] Time 0.044 (0.026) Data 0.002 (0.005) Loss 0.0292 (0.0419) Prec@1 95.000 (93.375) Prec@5 100.000 (99.625) +2022-11-14 14:26:07,692 Epoch: [197][80/500] Time 0.057 (0.029) Data 0.002 (0.004) Loss 0.0472 (0.0425) Prec@1 92.000 (93.222) Prec@5 100.000 (99.667) +2022-11-14 14:26:08,234 Epoch: [197][90/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0508 (0.0433) Prec@1 93.000 (93.200) Prec@5 99.000 (99.600) +2022-11-14 14:26:08,802 Epoch: [197][100/500] Time 0.044 (0.033) Data 0.002 (0.004) Loss 0.0403 (0.0430) Prec@1 93.000 (93.182) Prec@5 100.000 (99.636) +2022-11-14 14:26:09,354 Epoch: [197][110/500] Time 0.044 (0.035) Data 0.002 (0.004) Loss 0.0369 (0.0425) Prec@1 94.000 (93.250) Prec@5 99.000 (99.583) +2022-11-14 14:26:09,854 Epoch: [197][120/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0486 (0.0430) Prec@1 89.000 (92.923) Prec@5 100.000 (99.615) +2022-11-14 14:26:10,338 Epoch: [197][130/500] Time 0.045 (0.036) Data 0.002 (0.004) Loss 0.0587 (0.0441) Prec@1 89.000 (92.643) Prec@5 100.000 (99.643) +2022-11-14 14:26:11,082 Epoch: [197][140/500] Time 0.070 (0.038) Data 0.002 (0.003) Loss 0.0585 (0.0451) Prec@1 88.000 (92.333) Prec@5 99.000 (99.600) +2022-11-14 14:26:11,619 Epoch: [197][150/500] Time 0.051 (0.039) Data 0.002 (0.003) Loss 0.0300 (0.0441) Prec@1 94.000 (92.438) Prec@5 100.000 (99.625) +2022-11-14 14:26:12,201 Epoch: [197][160/500] Time 0.055 (0.040) Data 0.002 (0.003) Loss 0.0456 (0.0442) Prec@1 92.000 (92.412) Prec@5 99.000 (99.588) +2022-11-14 14:26:12,910 Epoch: [197][170/500] Time 0.065 (0.041) Data 0.002 (0.003) Loss 0.0299 (0.0434) Prec@1 97.000 (92.667) Prec@5 100.000 (99.611) +2022-11-14 14:26:13,519 Epoch: [197][180/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0669 (0.0447) Prec@1 89.000 (92.474) Prec@5 98.000 (99.526) +2022-11-14 14:26:14,011 Epoch: [197][190/500] Time 0.061 (0.042) Data 0.002 (0.003) Loss 0.0463 (0.0447) Prec@1 92.000 (92.450) Prec@5 100.000 (99.550) +2022-11-14 14:26:14,547 Epoch: [197][200/500] Time 0.057 (0.042) Data 0.002 (0.003) Loss 0.0384 (0.0444) Prec@1 93.000 (92.476) Prec@5 100.000 (99.571) +2022-11-14 14:26:15,032 Epoch: [197][210/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0462 (0.0445) Prec@1 94.000 (92.545) Prec@5 100.000 (99.591) +2022-11-14 14:26:15,508 Epoch: [197][220/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0542 (0.0449) Prec@1 92.000 (92.522) Prec@5 99.000 (99.565) +2022-11-14 14:26:15,997 Epoch: [197][230/500] Time 0.056 (0.043) Data 0.002 (0.003) Loss 0.0296 (0.0443) Prec@1 95.000 (92.625) Prec@5 100.000 (99.583) +2022-11-14 14:26:16,535 Epoch: [197][240/500] Time 0.062 (0.043) Data 0.003 (0.003) Loss 0.0848 (0.0459) Prec@1 87.000 (92.400) Prec@5 99.000 (99.560) +2022-11-14 14:26:17,066 Epoch: [197][250/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0709 (0.0469) Prec@1 87.000 (92.192) Prec@5 100.000 (99.577) +2022-11-14 14:26:17,618 Epoch: [197][260/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0192 (0.0459) Prec@1 96.000 (92.333) Prec@5 100.000 (99.593) +2022-11-14 14:26:18,183 Epoch: [197][270/500] Time 0.045 (0.044) Data 0.003 (0.003) Loss 0.0524 (0.0461) Prec@1 90.000 (92.250) Prec@5 100.000 (99.607) +2022-11-14 14:26:18,727 Epoch: [197][280/500] Time 0.078 (0.044) Data 0.002 (0.003) Loss 0.0504 (0.0462) Prec@1 91.000 (92.207) Prec@5 100.000 (99.621) +2022-11-14 14:26:19,232 Epoch: [197][290/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0523 (0.0464) Prec@1 93.000 (92.233) Prec@5 100.000 (99.633) +2022-11-14 14:26:19,720 Epoch: [197][300/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0532 (0.0467) Prec@1 91.000 (92.194) Prec@5 100.000 (99.645) +2022-11-14 14:26:20,277 Epoch: [197][310/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0726 (0.0475) Prec@1 87.000 (92.031) Prec@5 99.000 (99.625) +2022-11-14 14:26:20,782 Epoch: [197][320/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0273 (0.0469) Prec@1 95.000 (92.121) Prec@5 100.000 (99.636) +2022-11-14 14:26:21,312 Epoch: [197][330/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0310 (0.0464) Prec@1 93.000 (92.147) Prec@5 100.000 (99.647) +2022-11-14 14:26:21,806 Epoch: [197][340/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0543 (0.0466) Prec@1 90.000 (92.086) Prec@5 99.000 (99.629) +2022-11-14 14:26:22,295 Epoch: [197][350/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.1009 (0.0481) Prec@1 82.000 (91.806) Prec@5 99.000 (99.611) +2022-11-14 14:26:22,797 Epoch: [197][360/500] Time 0.044 (0.044) Data 0.001 (0.003) Loss 0.0336 (0.0477) Prec@1 94.000 (91.865) Prec@5 100.000 (99.622) +2022-11-14 14:26:23,361 Epoch: [197][370/500] Time 0.061 (0.044) Data 0.002 (0.003) Loss 0.0347 (0.0474) Prec@1 94.000 (91.921) Prec@5 99.000 (99.605) +2022-11-14 14:26:23,832 Epoch: [197][380/500] Time 0.044 (0.044) Data 0.001 (0.003) Loss 0.0474 (0.0474) Prec@1 92.000 (91.923) Prec@5 100.000 (99.615) +2022-11-14 14:26:24,352 Epoch: [197][390/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0594 (0.0477) Prec@1 90.000 (91.875) Prec@5 99.000 (99.600) +2022-11-14 14:26:24,862 Epoch: [197][400/500] Time 0.051 (0.044) Data 0.003 (0.002) Loss 0.0446 (0.0476) Prec@1 91.000 (91.854) Prec@5 100.000 (99.610) +2022-11-14 14:26:25,360 Epoch: [197][410/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0462 (0.0476) Prec@1 91.000 (91.833) Prec@5 100.000 (99.619) +2022-11-14 14:26:25,860 Epoch: [197][420/500] Time 0.045 (0.044) Data 0.002 (0.002) Loss 0.0283 (0.0471) Prec@1 96.000 (91.930) Prec@5 98.000 (99.581) +2022-11-14 14:26:26,360 Epoch: [197][430/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0330 (0.0468) Prec@1 95.000 (92.000) Prec@5 99.000 (99.568) +2022-11-14 14:26:26,839 Epoch: [197][440/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0495 (0.0469) Prec@1 89.000 (91.933) Prec@5 100.000 (99.578) +2022-11-14 14:26:27,328 Epoch: [197][450/500] Time 0.042 (0.044) Data 0.002 (0.002) Loss 0.0490 (0.0469) Prec@1 91.000 (91.913) Prec@5 99.000 (99.565) +2022-11-14 14:26:27,736 Epoch: [197][460/500] Time 0.028 (0.044) Data 0.002 (0.002) Loss 0.0484 (0.0470) Prec@1 94.000 (91.957) Prec@5 100.000 (99.574) +2022-11-14 14:26:28,060 Epoch: [197][470/500] Time 0.029 (0.044) Data 0.002 (0.002) Loss 0.0358 (0.0467) Prec@1 94.000 (92.000) Prec@5 100.000 (99.583) +2022-11-14 14:26:28,386 Epoch: [197][480/500] Time 0.027 (0.043) Data 0.002 (0.002) Loss 0.0787 (0.0474) Prec@1 89.000 (91.939) Prec@5 100.000 (99.592) +2022-11-14 14:26:28,697 Epoch: [197][490/500] Time 0.029 (0.043) Data 0.001 (0.002) Loss 0.0303 (0.0470) Prec@1 96.000 (92.020) Prec@5 100.000 (99.600) +2022-11-14 14:26:28,989 Epoch: [197][499/500] Time 0.031 (0.043) Data 0.002 (0.002) Loss 0.0281 (0.0467) Prec@1 96.000 (92.098) Prec@5 100.000 (99.608) +2022-11-14 14:26:29,279 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0754 (0.0754) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:29,295 Test: [1/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0665 (0.0709) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:26:29,306 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0734 (0.0718) Prec@1 87.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 14:26:29,324 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0698 (0.0713) Prec@1 89.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 14:26:29,334 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0614 (0.0693) Prec@1 90.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 14:26:29,344 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0523 (0.0665) Prec@1 91.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 14:26:29,353 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0657) Prec@1 90.000 (88.857) Prec@5 100.000 (99.857) +2022-11-14 14:26:29,364 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0671) Prec@1 90.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 14:26:29,374 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0685) Prec@1 89.000 (89.000) Prec@5 100.000 (99.778) +2022-11-14 14:26:29,384 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.0707) Prec@1 83.000 (88.400) Prec@5 99.000 (99.700) +2022-11-14 14:26:29,394 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0716) Prec@1 87.000 (88.273) Prec@5 98.000 (99.545) +2022-11-14 14:26:29,405 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0722) Prec@1 87.000 (88.167) Prec@5 99.000 (99.500) +2022-11-14 14:26:29,414 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0706) Prec@1 90.000 (88.308) Prec@5 100.000 (99.538) +2022-11-14 14:26:29,424 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0715) Prec@1 88.000 (88.286) Prec@5 99.000 (99.500) +2022-11-14 14:26:29,434 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0731) Prec@1 84.000 (88.000) Prec@5 100.000 (99.533) +2022-11-14 14:26:29,444 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0721) Prec@1 90.000 (88.125) Prec@5 100.000 (99.562) +2022-11-14 14:26:29,456 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0711) Prec@1 92.000 (88.353) Prec@5 98.000 (99.471) +2022-11-14 14:26:29,466 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0731) Prec@1 85.000 (88.167) Prec@5 99.000 (99.444) +2022-11-14 14:26:29,476 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0735) Prec@1 86.000 (88.053) Prec@5 97.000 (99.316) +2022-11-14 14:26:29,488 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0747) Prec@1 87.000 (88.000) Prec@5 98.000 (99.250) +2022-11-14 14:26:29,498 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0758) Prec@1 84.000 (87.810) Prec@5 99.000 (99.238) +2022-11-14 14:26:29,508 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0768) Prec@1 81.000 (87.500) Prec@5 99.000 (99.227) +2022-11-14 14:26:29,521 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1245 (0.0788) Prec@1 81.000 (87.217) Prec@5 100.000 (99.261) +2022-11-14 14:26:29,532 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0793) Prec@1 87.000 (87.208) Prec@5 100.000 (99.292) +2022-11-14 14:26:29,545 Test: [24/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0796) Prec@1 84.000 (87.080) Prec@5 99.000 (99.280) +2022-11-14 14:26:29,556 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0800) Prec@1 88.000 (87.115) Prec@5 98.000 (99.231) +2022-11-14 14:26:29,566 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0790) Prec@1 90.000 (87.222) Prec@5 100.000 (99.259) +2022-11-14 14:26:29,580 Test: [27/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0788) Prec@1 87.000 (87.214) Prec@5 100.000 (99.286) +2022-11-14 14:26:29,591 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0787) Prec@1 86.000 (87.172) Prec@5 100.000 (99.310) +2022-11-14 14:26:29,601 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0789) Prec@1 88.000 (87.200) Prec@5 99.000 (99.300) +2022-11-14 14:26:29,612 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0787) Prec@1 87.000 (87.194) Prec@5 99.000 (99.290) +2022-11-14 14:26:29,622 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0790) Prec@1 87.000 (87.188) Prec@5 99.000 (99.281) +2022-11-14 14:26:29,635 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0787) Prec@1 88.000 (87.212) Prec@5 99.000 (99.273) +2022-11-14 14:26:29,646 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0793) Prec@1 82.000 (87.059) Prec@5 99.000 (99.265) +2022-11-14 14:26:29,657 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0795) Prec@1 84.000 (86.971) Prec@5 99.000 (99.257) +2022-11-14 14:26:29,670 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0794) Prec@1 89.000 (87.028) Prec@5 99.000 (99.250) +2022-11-14 14:26:29,681 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0796) Prec@1 86.000 (87.000) Prec@5 99.000 (99.243) +2022-11-14 14:26:29,691 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0797) Prec@1 88.000 (87.026) Prec@5 100.000 (99.263) +2022-11-14 14:26:29,703 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0789) Prec@1 95.000 (87.231) Prec@5 99.000 (99.256) +2022-11-14 14:26:29,715 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0787) Prec@1 89.000 (87.275) Prec@5 99.000 (99.250) +2022-11-14 14:26:29,726 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0792) Prec@1 85.000 (87.220) Prec@5 97.000 (99.195) +2022-11-14 14:26:29,739 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0789) Prec@1 91.000 (87.310) Prec@5 98.000 (99.167) +2022-11-14 14:26:29,753 Test: [42/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0467 (0.0782) Prec@1 93.000 (87.442) Prec@5 99.000 (99.163) +2022-11-14 14:26:29,768 Test: [43/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0782) Prec@1 88.000 (87.455) Prec@5 99.000 (99.159) +2022-11-14 14:26:29,781 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0781) Prec@1 88.000 (87.467) Prec@5 100.000 (99.178) +2022-11-14 14:26:29,794 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0785) Prec@1 85.000 (87.413) Prec@5 98.000 (99.152) +2022-11-14 14:26:29,808 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0783) Prec@1 87.000 (87.404) Prec@5 100.000 (99.170) +2022-11-14 14:26:29,819 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0789) Prec@1 82.000 (87.292) Prec@5 99.000 (99.167) +2022-11-14 14:26:29,830 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0789) Prec@1 88.000 (87.306) Prec@5 99.000 (99.163) +2022-11-14 14:26:29,841 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.0796) Prec@1 80.000 (87.160) Prec@5 99.000 (99.160) +2022-11-14 14:26:29,851 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0796) Prec@1 84.000 (87.098) Prec@5 100.000 (99.176) +2022-11-14 14:26:29,861 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.0803) Prec@1 77.000 (86.904) Prec@5 100.000 (99.192) +2022-11-14 14:26:29,872 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0804) Prec@1 86.000 (86.887) Prec@5 100.000 (99.208) +2022-11-14 14:26:29,882 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0804) Prec@1 88.000 (86.907) Prec@5 100.000 (99.222) +2022-11-14 14:26:29,892 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0806) Prec@1 86.000 (86.891) Prec@5 100.000 (99.236) +2022-11-14 14:26:29,904 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0806) Prec@1 86.000 (86.875) Prec@5 99.000 (99.232) +2022-11-14 14:26:29,914 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0804) Prec@1 90.000 (86.930) Prec@5 100.000 (99.246) +2022-11-14 14:26:29,925 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0804) Prec@1 89.000 (86.966) Prec@5 99.000 (99.241) +2022-11-14 14:26:29,937 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0808) Prec@1 83.000 (86.898) Prec@5 99.000 (99.237) +2022-11-14 14:26:29,949 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0809) Prec@1 84.000 (86.850) Prec@5 99.000 (99.233) +2022-11-14 14:26:29,960 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0811) Prec@1 86.000 (86.836) Prec@5 98.000 (99.213) +2022-11-14 14:26:29,972 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0813) Prec@1 86.000 (86.823) Prec@5 99.000 (99.210) +2022-11-14 14:26:29,982 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0808) Prec@1 93.000 (86.921) Prec@5 99.000 (99.206) +2022-11-14 14:26:29,992 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0388 (0.0801) Prec@1 95.000 (87.047) Prec@5 100.000 (99.219) +2022-11-14 14:26:30,002 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0804) Prec@1 84.000 (87.000) Prec@5 99.000 (99.215) +2022-11-14 14:26:30,012 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0806) Prec@1 85.000 (86.970) Prec@5 100.000 (99.227) +2022-11-14 14:26:30,022 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0372 (0.0799) Prec@1 94.000 (87.075) Prec@5 100.000 (99.239) +2022-11-14 14:26:30,033 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0796) Prec@1 91.000 (87.132) Prec@5 100.000 (99.250) +2022-11-14 14:26:30,045 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0795) Prec@1 89.000 (87.159) Prec@5 100.000 (99.261) +2022-11-14 14:26:30,055 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0798) Prec@1 81.000 (87.071) Prec@5 98.000 (99.243) +2022-11-14 14:26:30,066 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0798) Prec@1 88.000 (87.085) Prec@5 99.000 (99.239) +2022-11-14 14:26:30,076 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0798) Prec@1 86.000 (87.069) Prec@5 98.000 (99.222) +2022-11-14 14:26:30,086 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0796) Prec@1 89.000 (87.096) Prec@5 99.000 (99.219) +2022-11-14 14:26:30,096 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0792) Prec@1 92.000 (87.162) Prec@5 100.000 (99.230) +2022-11-14 14:26:30,107 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0794) Prec@1 83.000 (87.107) Prec@5 98.000 (99.213) +2022-11-14 14:26:30,117 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0791) Prec@1 91.000 (87.158) Prec@5 99.000 (99.211) +2022-11-14 14:26:30,128 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0790) Prec@1 89.000 (87.182) Prec@5 99.000 (99.208) +2022-11-14 14:26:30,140 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0791) Prec@1 83.000 (87.128) Prec@5 98.000 (99.192) +2022-11-14 14:26:30,152 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0790) Prec@1 88.000 (87.139) Prec@5 100.000 (99.203) +2022-11-14 14:26:30,163 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0792) Prec@1 85.000 (87.112) Prec@5 99.000 (99.200) +2022-11-14 14:26:30,175 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0794) Prec@1 83.000 (87.062) Prec@5 99.000 (99.198) +2022-11-14 14:26:30,186 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0794) Prec@1 88.000 (87.073) Prec@5 99.000 (99.195) +2022-11-14 14:26:30,197 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0794) Prec@1 84.000 (87.036) Prec@5 100.000 (99.205) +2022-11-14 14:26:30,207 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0792) Prec@1 88.000 (87.048) Prec@5 100.000 (99.214) +2022-11-14 14:26:30,217 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1161 (0.0796) Prec@1 80.000 (86.965) Prec@5 99.000 (99.212) +2022-11-14 14:26:30,229 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0800) Prec@1 83.000 (86.919) Prec@5 100.000 (99.221) +2022-11-14 14:26:30,239 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0797) Prec@1 91.000 (86.966) Prec@5 99.000 (99.218) +2022-11-14 14:26:30,250 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0796) Prec@1 89.000 (86.989) Prec@5 100.000 (99.227) +2022-11-14 14:26:30,260 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0796) Prec@1 86.000 (86.978) Prec@5 99.000 (99.225) +2022-11-14 14:26:30,271 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0796) Prec@1 87.000 (86.978) Prec@5 99.000 (99.222) +2022-11-14 14:26:30,282 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0797) Prec@1 82.000 (86.923) Prec@5 100.000 (99.231) +2022-11-14 14:26:30,292 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0796) Prec@1 90.000 (86.957) Prec@5 99.000 (99.228) +2022-11-14 14:26:30,303 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0796) Prec@1 85.000 (86.935) Prec@5 99.000 (99.226) +2022-11-14 14:26:30,313 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0797) Prec@1 87.000 (86.936) Prec@5 99.000 (99.223) +2022-11-14 14:26:30,323 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0797) Prec@1 87.000 (86.937) Prec@5 100.000 (99.232) +2022-11-14 14:26:30,333 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0794) Prec@1 89.000 (86.958) Prec@5 100.000 (99.240) +2022-11-14 14:26:30,343 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0438 (0.0791) Prec@1 94.000 (87.031) Prec@5 99.000 (99.237) +2022-11-14 14:26:30,354 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0791) Prec@1 89.000 (87.051) Prec@5 99.000 (99.235) +2022-11-14 14:26:30,364 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.0794) Prec@1 81.000 (86.990) Prec@5 98.000 (99.222) +2022-11-14 14:26:30,375 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0794) Prec@1 89.000 (87.010) Prec@5 99.000 (99.220) +2022-11-14 14:26:30,433 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:26:30,768 Epoch: [198][0/500] Time 0.024 (0.024) Data 0.241 (0.241) Loss 0.0583 (0.0583) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:31,013 Epoch: [198][10/500] Time 0.021 (0.022) Data 0.002 (0.024) Loss 0.0459 (0.0521) Prec@1 92.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:26:31,242 Epoch: [198][20/500] Time 0.022 (0.021) Data 0.002 (0.013) Loss 0.0319 (0.0454) Prec@1 95.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:26:31,536 Epoch: [198][30/500] Time 0.034 (0.023) Data 0.002 (0.010) Loss 0.0271 (0.0408) Prec@1 96.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:26:31,821 Epoch: [198][40/500] Time 0.026 (0.023) Data 0.002 (0.008) Loss 0.0299 (0.0386) Prec@1 95.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:26:32,121 Epoch: [198][50/500] Time 0.027 (0.024) Data 0.001 (0.006) Loss 0.0413 (0.0391) Prec@1 93.000 (93.500) Prec@5 99.000 (99.667) +2022-11-14 14:26:32,415 Epoch: [198][60/500] Time 0.026 (0.024) Data 0.002 (0.006) Loss 0.0487 (0.0405) Prec@1 91.000 (93.143) Prec@5 100.000 (99.714) +2022-11-14 14:26:32,710 Epoch: [198][70/500] Time 0.028 (0.025) Data 0.002 (0.005) Loss 0.0459 (0.0411) Prec@1 92.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:26:33,010 Epoch: [198][80/500] Time 0.024 (0.025) Data 0.003 (0.005) Loss 0.0400 (0.0410) Prec@1 92.000 (92.889) Prec@5 100.000 (99.778) +2022-11-14 14:26:33,298 Epoch: [198][90/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0466 (0.0416) Prec@1 90.000 (92.600) Prec@5 99.000 (99.700) +2022-11-14 14:26:33,618 Epoch: [198][100/500] Time 0.022 (0.025) Data 0.001 (0.004) Loss 0.0384 (0.0413) Prec@1 94.000 (92.727) Prec@5 100.000 (99.727) +2022-11-14 14:26:33,966 Epoch: [198][110/500] Time 0.044 (0.026) Data 0.002 (0.004) Loss 0.0362 (0.0409) Prec@1 95.000 (92.917) Prec@5 100.000 (99.750) +2022-11-14 14:26:34,443 Epoch: [198][120/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0561 (0.0420) Prec@1 90.000 (92.692) Prec@5 100.000 (99.769) +2022-11-14 14:26:34,916 Epoch: [198][130/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0426 (0.0421) Prec@1 94.000 (92.786) Prec@5 100.000 (99.786) +2022-11-14 14:26:35,390 Epoch: [198][140/500] Time 0.042 (0.029) Data 0.002 (0.004) Loss 0.0468 (0.0424) Prec@1 92.000 (92.733) Prec@5 100.000 (99.800) +2022-11-14 14:26:35,870 Epoch: [198][150/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0354 (0.0420) Prec@1 95.000 (92.875) Prec@5 100.000 (99.812) +2022-11-14 14:26:36,359 Epoch: [198][160/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0454 (0.0422) Prec@1 92.000 (92.824) Prec@5 99.000 (99.765) +2022-11-14 14:26:36,835 Epoch: [198][170/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0396 (0.0420) Prec@1 92.000 (92.778) Prec@5 100.000 (99.778) +2022-11-14 14:26:37,323 Epoch: [198][180/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0603 (0.0430) Prec@1 90.000 (92.632) Prec@5 100.000 (99.789) +2022-11-14 14:26:37,802 Epoch: [198][190/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0355 (0.0426) Prec@1 94.000 (92.700) Prec@5 99.000 (99.750) +2022-11-14 14:26:38,291 Epoch: [198][200/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0264 (0.0418) Prec@1 96.000 (92.857) Prec@5 100.000 (99.762) +2022-11-14 14:26:38,770 Epoch: [198][210/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0284 (0.0412) Prec@1 95.000 (92.955) Prec@5 100.000 (99.773) +2022-11-14 14:26:39,256 Epoch: [198][220/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0524 (0.0417) Prec@1 92.000 (92.913) Prec@5 99.000 (99.739) +2022-11-14 14:26:39,731 Epoch: [198][230/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0492 (0.0420) Prec@1 92.000 (92.875) Prec@5 100.000 (99.750) +2022-11-14 14:26:40,217 Epoch: [198][240/500] Time 0.044 (0.035) Data 0.001 (0.003) Loss 0.0462 (0.0422) Prec@1 90.000 (92.760) Prec@5 100.000 (99.760) +2022-11-14 14:26:40,695 Epoch: [198][250/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0328 (0.0418) Prec@1 94.000 (92.808) Prec@5 100.000 (99.769) +2022-11-14 14:26:41,224 Epoch: [198][260/500] Time 0.059 (0.036) Data 0.002 (0.003) Loss 0.0258 (0.0412) Prec@1 95.000 (92.889) Prec@5 100.000 (99.778) +2022-11-14 14:26:41,701 Epoch: [198][270/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0526 (0.0416) Prec@1 92.000 (92.857) Prec@5 100.000 (99.786) +2022-11-14 14:26:42,187 Epoch: [198][280/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0295 (0.0412) Prec@1 94.000 (92.897) Prec@5 100.000 (99.793) +2022-11-14 14:26:42,665 Epoch: [198][290/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0330 (0.0409) Prec@1 94.000 (92.933) Prec@5 100.000 (99.800) +2022-11-14 14:26:43,150 Epoch: [198][300/500] Time 0.042 (0.037) Data 0.003 (0.003) Loss 0.0401 (0.0409) Prec@1 94.000 (92.968) Prec@5 100.000 (99.806) +2022-11-14 14:26:43,627 Epoch: [198][310/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0380 (0.0408) Prec@1 94.000 (93.000) Prec@5 98.000 (99.750) +2022-11-14 14:26:44,114 Epoch: [198][320/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0451 (0.0410) Prec@1 93.000 (93.000) Prec@5 100.000 (99.758) +2022-11-14 14:26:44,586 Epoch: [198][330/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0385 (0.0409) Prec@1 93.000 (93.000) Prec@5 100.000 (99.765) +2022-11-14 14:26:45,074 Epoch: [198][340/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0454 (0.0410) Prec@1 92.000 (92.971) Prec@5 99.000 (99.743) +2022-11-14 14:26:45,549 Epoch: [198][350/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0505 (0.0413) Prec@1 92.000 (92.944) Prec@5 99.000 (99.722) +2022-11-14 14:26:46,035 Epoch: [198][360/500] Time 0.052 (0.038) Data 0.002 (0.003) Loss 0.0468 (0.0414) Prec@1 92.000 (92.919) Prec@5 100.000 (99.730) +2022-11-14 14:26:46,383 Epoch: [198][370/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.0811 (0.0425) Prec@1 86.000 (92.737) Prec@5 100.000 (99.737) +2022-11-14 14:26:46,690 Epoch: [198][380/500] Time 0.029 (0.037) Data 0.002 (0.003) Loss 0.0289 (0.0421) Prec@1 97.000 (92.846) Prec@5 100.000 (99.744) +2022-11-14 14:26:47,006 Epoch: [198][390/500] Time 0.029 (0.037) Data 0.002 (0.002) Loss 0.0712 (0.0428) Prec@1 90.000 (92.775) Prec@5 99.000 (99.725) +2022-11-14 14:26:47,300 Epoch: [198][400/500] Time 0.025 (0.037) Data 0.002 (0.002) Loss 0.0288 (0.0425) Prec@1 95.000 (92.829) Prec@5 100.000 (99.732) +2022-11-14 14:26:47,604 Epoch: [198][410/500] Time 0.027 (0.037) Data 0.002 (0.002) Loss 0.0686 (0.0431) Prec@1 85.000 (92.643) Prec@5 100.000 (99.738) +2022-11-14 14:26:47,910 Epoch: [198][420/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0532 (0.0434) Prec@1 91.000 (92.605) Prec@5 99.000 (99.721) +2022-11-14 14:26:48,220 Epoch: [198][430/500] Time 0.029 (0.036) Data 0.001 (0.002) Loss 0.0521 (0.0436) Prec@1 91.000 (92.568) Prec@5 100.000 (99.727) +2022-11-14 14:26:48,529 Epoch: [198][440/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0687 (0.0441) Prec@1 90.000 (92.511) Prec@5 98.000 (99.689) +2022-11-14 14:26:48,833 Epoch: [198][450/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0530 (0.0443) Prec@1 92.000 (92.500) Prec@5 100.000 (99.696) +2022-11-14 14:26:49,143 Epoch: [198][460/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0227 (0.0439) Prec@1 96.000 (92.574) Prec@5 100.000 (99.702) +2022-11-14 14:26:49,453 Epoch: [198][470/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0541 (0.0441) Prec@1 90.000 (92.521) Prec@5 100.000 (99.708) +2022-11-14 14:26:49,757 Epoch: [198][480/500] Time 0.029 (0.035) Data 0.001 (0.002) Loss 0.0579 (0.0443) Prec@1 90.000 (92.469) Prec@5 100.000 (99.714) +2022-11-14 14:26:50,067 Epoch: [198][490/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0641 (0.0447) Prec@1 89.000 (92.400) Prec@5 100.000 (99.720) +2022-11-14 14:26:50,342 Epoch: [198][499/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0357 (0.0446) Prec@1 94.000 (92.431) Prec@5 100.000 (99.725) +2022-11-14 14:26:50,630 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0785 (0.0785) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:26:50,639 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0777) Prec@1 89.000 (88.500) Prec@5 98.000 (98.500) +2022-11-14 14:26:50,648 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0769) Prec@1 90.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 14:26:50,660 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0804) Prec@1 87.000 (88.500) Prec@5 99.000 (99.000) +2022-11-14 14:26:50,669 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0789) Prec@1 88.000 (88.400) Prec@5 99.000 (99.000) +2022-11-14 14:26:50,680 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0755) Prec@1 89.000 (88.500) Prec@5 100.000 (99.167) +2022-11-14 14:26:50,689 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0719) Prec@1 92.000 (89.000) Prec@5 100.000 (99.286) +2022-11-14 14:26:50,699 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0719) Prec@1 89.000 (89.000) Prec@5 100.000 (99.375) +2022-11-14 14:26:50,707 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0736) Prec@1 85.000 (88.556) Prec@5 100.000 (99.444) +2022-11-14 14:26:50,716 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0730) Prec@1 88.000 (88.500) Prec@5 98.000 (99.300) +2022-11-14 14:26:50,724 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0757) Prec@1 84.000 (88.091) Prec@5 100.000 (99.364) +2022-11-14 14:26:50,732 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0755) Prec@1 87.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 14:26:50,742 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0739) Prec@1 90.000 (88.154) Prec@5 100.000 (99.385) +2022-11-14 14:26:50,753 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0742) Prec@1 86.000 (88.000) Prec@5 98.000 (99.286) +2022-11-14 14:26:50,763 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0733) Prec@1 90.000 (88.133) Prec@5 100.000 (99.333) +2022-11-14 14:26:50,773 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0737) Prec@1 86.000 (88.000) Prec@5 99.000 (99.312) +2022-11-14 14:26:50,786 Test: [16/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0724) Prec@1 90.000 (88.118) Prec@5 99.000 (99.294) +2022-11-14 14:26:50,797 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0745) Prec@1 82.000 (87.778) Prec@5 100.000 (99.333) +2022-11-14 14:26:50,806 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0757) Prec@1 83.000 (87.526) Prec@5 97.000 (99.211) +2022-11-14 14:26:50,816 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0768) Prec@1 84.000 (87.350) Prec@5 98.000 (99.150) +2022-11-14 14:26:50,826 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0768) Prec@1 85.000 (87.238) Prec@5 99.000 (99.143) +2022-11-14 14:26:50,837 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0778) Prec@1 84.000 (87.091) Prec@5 97.000 (99.045) +2022-11-14 14:26:50,847 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0791) Prec@1 84.000 (86.957) Prec@5 98.000 (99.000) +2022-11-14 14:26:50,858 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0786) Prec@1 87.000 (86.958) Prec@5 98.000 (98.958) +2022-11-14 14:26:50,868 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0789) Prec@1 83.000 (86.800) Prec@5 100.000 (99.000) +2022-11-14 14:26:50,878 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0796) Prec@1 83.000 (86.654) Prec@5 100.000 (99.038) +2022-11-14 14:26:50,888 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0789) Prec@1 90.000 (86.778) Prec@5 100.000 (99.074) +2022-11-14 14:26:50,897 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0785) Prec@1 88.000 (86.821) Prec@5 100.000 (99.107) +2022-11-14 14:26:50,908 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0781) Prec@1 88.000 (86.862) Prec@5 100.000 (99.138) +2022-11-14 14:26:50,917 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0784) Prec@1 86.000 (86.833) Prec@5 98.000 (99.100) +2022-11-14 14:26:50,929 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0786) Prec@1 82.000 (86.677) Prec@5 100.000 (99.129) +2022-11-14 14:26:50,939 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0782) Prec@1 88.000 (86.719) Prec@5 98.000 (99.094) +2022-11-14 14:26:50,950 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0787) Prec@1 83.000 (86.606) Prec@5 99.000 (99.091) +2022-11-14 14:26:50,960 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0794) Prec@1 83.000 (86.500) Prec@5 99.000 (99.088) +2022-11-14 14:26:50,970 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0801) Prec@1 84.000 (86.429) Prec@5 99.000 (99.086) +2022-11-14 14:26:50,980 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0801) Prec@1 88.000 (86.472) Prec@5 99.000 (99.083) +2022-11-14 14:26:50,990 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0800) Prec@1 88.000 (86.514) Prec@5 97.000 (99.027) +2022-11-14 14:26:50,999 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0808) Prec@1 81.000 (86.368) Prec@5 99.000 (99.026) +2022-11-14 14:26:51,008 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0801) Prec@1 92.000 (86.513) Prec@5 99.000 (99.026) +2022-11-14 14:26:51,018 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0799) Prec@1 90.000 (86.600) Prec@5 98.000 (99.000) +2022-11-14 14:26:51,028 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0803) Prec@1 84.000 (86.537) Prec@5 97.000 (98.951) +2022-11-14 14:26:51,038 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0804) Prec@1 87.000 (86.548) Prec@5 99.000 (98.952) +2022-11-14 14:26:51,047 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0797) Prec@1 92.000 (86.674) Prec@5 99.000 (98.953) +2022-11-14 14:26:51,057 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0795) Prec@1 87.000 (86.682) Prec@5 99.000 (98.955) +2022-11-14 14:26:51,068 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0792) Prec@1 87.000 (86.689) Prec@5 100.000 (98.978) +2022-11-14 14:26:51,080 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0795) Prec@1 86.000 (86.674) Prec@5 99.000 (98.978) +2022-11-14 14:26:51,090 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0794) Prec@1 88.000 (86.702) Prec@5 100.000 (99.000) +2022-11-14 14:26:51,100 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0799) Prec@1 80.000 (86.562) Prec@5 99.000 (99.000) +2022-11-14 14:26:51,111 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0797) Prec@1 86.000 (86.551) Prec@5 99.000 (99.000) +2022-11-14 14:26:51,121 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0803) Prec@1 84.000 (86.500) Prec@5 100.000 (99.020) +2022-11-14 14:26:51,132 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0800) Prec@1 87.000 (86.510) Prec@5 100.000 (99.039) +2022-11-14 14:26:51,141 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0800) Prec@1 87.000 (86.519) Prec@5 99.000 (99.038) +2022-11-14 14:26:51,152 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0802) Prec@1 86.000 (86.509) Prec@5 100.000 (99.057) +2022-11-14 14:26:51,163 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0803) Prec@1 86.000 (86.500) Prec@5 100.000 (99.074) +2022-11-14 14:26:51,173 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0801) Prec@1 86.000 (86.491) Prec@5 100.000 (99.091) +2022-11-14 14:26:51,183 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0800) Prec@1 90.000 (86.554) Prec@5 99.000 (99.089) +2022-11-14 14:26:51,194 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0798) Prec@1 87.000 (86.561) Prec@5 100.000 (99.105) +2022-11-14 14:26:51,205 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0795) Prec@1 92.000 (86.655) Prec@5 99.000 (99.103) +2022-11-14 14:26:51,215 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1156 (0.0801) Prec@1 81.000 (86.559) Prec@5 100.000 (99.119) +2022-11-14 14:26:51,226 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0801) Prec@1 87.000 (86.567) Prec@5 100.000 (99.133) +2022-11-14 14:26:51,236 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0802) Prec@1 87.000 (86.574) Prec@5 100.000 (99.148) +2022-11-14 14:26:51,246 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0803) Prec@1 85.000 (86.548) Prec@5 100.000 (99.161) +2022-11-14 14:26:51,257 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0800) Prec@1 89.000 (86.587) Prec@5 100.000 (99.175) +2022-11-14 14:26:51,267 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0797) Prec@1 92.000 (86.672) Prec@5 100.000 (99.188) +2022-11-14 14:26:51,277 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0798) Prec@1 85.000 (86.646) Prec@5 99.000 (99.185) +2022-11-14 14:26:51,288 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0801) Prec@1 81.000 (86.561) Prec@5 98.000 (99.167) +2022-11-14 14:26:51,299 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0797) Prec@1 92.000 (86.642) Prec@5 100.000 (99.179) +2022-11-14 14:26:51,309 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0796) Prec@1 86.000 (86.632) Prec@5 99.000 (99.176) +2022-11-14 14:26:51,318 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0794) Prec@1 89.000 (86.667) Prec@5 99.000 (99.174) +2022-11-14 14:26:51,330 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0795) Prec@1 85.000 (86.643) Prec@5 96.000 (99.129) +2022-11-14 14:26:51,340 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0796) Prec@1 87.000 (86.648) Prec@5 100.000 (99.141) +2022-11-14 14:26:51,351 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0796) Prec@1 86.000 (86.639) Prec@5 99.000 (99.139) +2022-11-14 14:26:51,361 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0792) Prec@1 91.000 (86.699) Prec@5 99.000 (99.137) +2022-11-14 14:26:51,370 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0790) Prec@1 89.000 (86.730) Prec@5 100.000 (99.149) +2022-11-14 14:26:51,379 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0794) Prec@1 81.000 (86.653) Prec@5 100.000 (99.160) +2022-11-14 14:26:51,388 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0793) Prec@1 89.000 (86.684) Prec@5 100.000 (99.171) +2022-11-14 14:26:51,397 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0791) Prec@1 90.000 (86.727) Prec@5 98.000 (99.156) +2022-11-14 14:26:51,407 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0792) Prec@1 84.000 (86.692) Prec@5 98.000 (99.141) +2022-11-14 14:26:51,417 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0791) Prec@1 87.000 (86.696) Prec@5 100.000 (99.152) +2022-11-14 14:26:51,427 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0791) Prec@1 86.000 (86.688) Prec@5 99.000 (99.150) +2022-11-14 14:26:51,438 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0792) Prec@1 85.000 (86.667) Prec@5 100.000 (99.160) +2022-11-14 14:26:51,448 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0792) Prec@1 88.000 (86.683) Prec@5 99.000 (99.159) +2022-11-14 14:26:51,458 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0791) Prec@1 89.000 (86.711) Prec@5 100.000 (99.169) +2022-11-14 14:26:51,469 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0793) Prec@1 81.000 (86.643) Prec@5 99.000 (99.167) +2022-11-14 14:26:51,479 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0793) Prec@1 89.000 (86.671) Prec@5 99.000 (99.165) +2022-11-14 14:26:51,489 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0797) Prec@1 83.000 (86.628) Prec@5 100.000 (99.174) +2022-11-14 14:26:51,499 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0795) Prec@1 88.000 (86.644) Prec@5 100.000 (99.184) +2022-11-14 14:26:51,510 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0796) Prec@1 85.000 (86.625) Prec@5 98.000 (99.170) +2022-11-14 14:26:51,519 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0793) Prec@1 93.000 (86.697) Prec@5 99.000 (99.169) +2022-11-14 14:26:51,529 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0793) Prec@1 87.000 (86.700) Prec@5 99.000 (99.167) +2022-11-14 14:26:51,539 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0792) Prec@1 90.000 (86.736) Prec@5 100.000 (99.176) +2022-11-14 14:26:51,549 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0789) Prec@1 92.000 (86.793) Prec@5 100.000 (99.185) +2022-11-14 14:26:51,559 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0789) Prec@1 87.000 (86.796) Prec@5 100.000 (99.194) +2022-11-14 14:26:51,569 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0787) Prec@1 89.000 (86.819) Prec@5 97.000 (99.170) +2022-11-14 14:26:51,578 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0788) Prec@1 86.000 (86.811) Prec@5 99.000 (99.168) +2022-11-14 14:26:51,589 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0786) Prec@1 88.000 (86.823) Prec@5 99.000 (99.167) +2022-11-14 14:26:51,599 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0784) Prec@1 90.000 (86.856) Prec@5 99.000 (99.165) +2022-11-14 14:26:51,610 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0785) Prec@1 86.000 (86.847) Prec@5 99.000 (99.163) +2022-11-14 14:26:51,620 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0789) Prec@1 83.000 (86.808) Prec@5 99.000 (99.162) +2022-11-14 14:26:51,630 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0788) Prec@1 90.000 (86.840) Prec@5 100.000 (99.170) +2022-11-14 14:26:51,687 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:26:51,987 Epoch: [199][0/500] Time 0.023 (0.023) Data 0.217 (0.217) Loss 0.0416 (0.0416) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:52,346 Epoch: [199][10/500] Time 0.040 (0.031) Data 0.002 (0.021) Loss 0.0391 (0.0404) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:26:52,846 Epoch: [199][20/500] Time 0.065 (0.037) Data 0.002 (0.012) Loss 0.0389 (0.0399) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:53,375 Epoch: [199][30/500] Time 0.051 (0.040) Data 0.002 (0.009) Loss 0.0441 (0.0409) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:26:53,913 Epoch: [199][40/500] Time 0.051 (0.042) Data 0.002 (0.007) Loss 0.0494 (0.0426) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:26:54,371 Epoch: [199][50/500] Time 0.035 (0.042) Data 0.002 (0.006) Loss 0.0489 (0.0437) Prec@1 92.000 (92.833) Prec@5 100.000 (100.000) +2022-11-14 14:26:54,823 Epoch: [199][60/500] Time 0.051 (0.042) Data 0.002 (0.005) Loss 0.0476 (0.0442) Prec@1 92.000 (92.714) Prec@5 100.000 (100.000) +2022-11-14 14:26:55,243 Epoch: [199][70/500] Time 0.042 (0.041) Data 0.002 (0.005) Loss 0.0265 (0.0420) Prec@1 96.000 (93.125) Prec@5 100.000 (100.000) +2022-11-14 14:26:55,700 Epoch: [199][80/500] Time 0.037 (0.041) Data 0.002 (0.005) Loss 0.0653 (0.0446) Prec@1 89.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:26:56,155 Epoch: [199][90/500] Time 0.046 (0.041) Data 0.002 (0.004) Loss 0.0396 (0.0441) Prec@1 92.000 (92.600) Prec@5 100.000 (100.000) +2022-11-14 14:26:56,628 Epoch: [199][100/500] Time 0.062 (0.041) Data 0.002 (0.004) Loss 0.0481 (0.0445) Prec@1 94.000 (92.727) Prec@5 99.000 (99.909) +2022-11-14 14:26:57,067 Epoch: [199][110/500] Time 0.048 (0.041) Data 0.002 (0.004) Loss 0.0319 (0.0434) Prec@1 95.000 (92.917) Prec@5 99.000 (99.833) +2022-11-14 14:26:57,497 Epoch: [199][120/500] Time 0.036 (0.041) Data 0.002 (0.004) Loss 0.0344 (0.0427) Prec@1 93.000 (92.923) Prec@5 100.000 (99.846) +2022-11-14 14:26:57,921 Epoch: [199][130/500] Time 0.041 (0.041) Data 0.002 (0.004) Loss 0.0400 (0.0425) Prec@1 93.000 (92.929) Prec@5 100.000 (99.857) +2022-11-14 14:26:58,453 Epoch: [199][140/500] Time 0.056 (0.041) Data 0.002 (0.003) Loss 0.0593 (0.0436) Prec@1 90.000 (92.733) Prec@5 100.000 (99.867) +2022-11-14 14:26:58,880 Epoch: [199][150/500] Time 0.041 (0.041) Data 0.002 (0.003) Loss 0.0529 (0.0442) Prec@1 93.000 (92.750) Prec@5 100.000 (99.875) +2022-11-14 14:26:59,366 Epoch: [199][160/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0317 (0.0435) Prec@1 96.000 (92.941) Prec@5 100.000 (99.882) +2022-11-14 14:26:59,795 Epoch: [199][170/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0604 (0.0444) Prec@1 87.000 (92.611) Prec@5 100.000 (99.889) +2022-11-14 14:27:00,286 Epoch: [199][180/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0349 (0.0439) Prec@1 94.000 (92.684) Prec@5 100.000 (99.895) +2022-11-14 14:27:00,787 Epoch: [199][190/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0705 (0.0453) Prec@1 86.000 (92.350) Prec@5 100.000 (99.900) +2022-11-14 14:27:01,283 Epoch: [199][200/500] Time 0.048 (0.041) Data 0.002 (0.003) Loss 0.0446 (0.0452) Prec@1 93.000 (92.381) Prec@5 100.000 (99.905) +2022-11-14 14:27:01,813 Epoch: [199][210/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0441 (0.0452) Prec@1 93.000 (92.409) Prec@5 100.000 (99.909) +2022-11-14 14:27:02,270 Epoch: [199][220/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0330 (0.0446) Prec@1 94.000 (92.478) Prec@5 99.000 (99.870) +2022-11-14 14:27:02,755 Epoch: [199][230/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0407 (0.0445) Prec@1 93.000 (92.500) Prec@5 100.000 (99.875) +2022-11-14 14:27:03,236 Epoch: [199][240/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0441 (0.0445) Prec@1 93.000 (92.520) Prec@5 100.000 (99.880) +2022-11-14 14:27:03,817 Epoch: [199][250/500] Time 0.058 (0.042) Data 0.002 (0.003) Loss 0.0465 (0.0445) Prec@1 91.000 (92.462) Prec@5 100.000 (99.885) +2022-11-14 14:27:04,261 Epoch: [199][260/500] Time 0.038 (0.042) Data 0.002 (0.003) Loss 0.0451 (0.0446) Prec@1 94.000 (92.519) Prec@5 100.000 (99.889) +2022-11-14 14:27:04,708 Epoch: [199][270/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0676 (0.0454) Prec@1 88.000 (92.357) Prec@5 100.000 (99.893) +2022-11-14 14:27:05,168 Epoch: [199][280/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0269 (0.0448) Prec@1 95.000 (92.448) Prec@5 100.000 (99.897) +2022-11-14 14:27:05,702 Epoch: [199][290/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0350 (0.0444) Prec@1 95.000 (92.533) Prec@5 100.000 (99.900) +2022-11-14 14:27:06,196 Epoch: [199][300/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0297 (0.0440) Prec@1 96.000 (92.645) Prec@5 99.000 (99.871) +2022-11-14 14:27:06,718 Epoch: [199][310/500] Time 0.065 (0.042) Data 0.002 (0.003) Loss 0.0381 (0.0438) Prec@1 93.000 (92.656) Prec@5 100.000 (99.875) +2022-11-14 14:27:07,314 Epoch: [199][320/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0476 (0.0439) Prec@1 93.000 (92.667) Prec@5 99.000 (99.848) +2022-11-14 14:27:07,844 Epoch: [199][330/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0321 (0.0435) Prec@1 96.000 (92.765) Prec@5 100.000 (99.853) +2022-11-14 14:27:08,294 Epoch: [199][340/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0444 (0.0436) Prec@1 93.000 (92.771) Prec@5 100.000 (99.857) +2022-11-14 14:27:08,780 Epoch: [199][350/500] Time 0.066 (0.043) Data 0.002 (0.003) Loss 0.0478 (0.0437) Prec@1 90.000 (92.694) Prec@5 100.000 (99.861) +2022-11-14 14:27:09,282 Epoch: [199][360/500] Time 0.041 (0.043) Data 0.003 (0.003) Loss 0.0407 (0.0436) Prec@1 93.000 (92.703) Prec@5 100.000 (99.865) +2022-11-14 14:27:09,863 Epoch: [199][370/500] Time 0.062 (0.043) Data 0.002 (0.003) Loss 0.0570 (0.0439) Prec@1 91.000 (92.658) Prec@5 100.000 (99.868) +2022-11-14 14:27:10,323 Epoch: [199][380/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0507 (0.0441) Prec@1 91.000 (92.615) Prec@5 100.000 (99.872) +2022-11-14 14:27:10,807 Epoch: [199][390/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0289 (0.0437) Prec@1 96.000 (92.700) Prec@5 100.000 (99.875) +2022-11-14 14:27:11,258 Epoch: [199][400/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0481 (0.0439) Prec@1 92.000 (92.683) Prec@5 100.000 (99.878) +2022-11-14 14:27:11,753 Epoch: [199][410/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0545 (0.0441) Prec@1 89.000 (92.595) Prec@5 100.000 (99.881) +2022-11-14 14:27:12,325 Epoch: [199][420/500] Time 0.059 (0.043) Data 0.002 (0.003) Loss 0.0300 (0.0438) Prec@1 95.000 (92.651) Prec@5 100.000 (99.884) +2022-11-14 14:27:12,757 Epoch: [199][430/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0469 (0.0438) Prec@1 92.000 (92.636) Prec@5 99.000 (99.864) +2022-11-14 14:27:13,277 Epoch: [199][440/500] Time 0.057 (0.043) Data 0.002 (0.003) Loss 0.0447 (0.0439) Prec@1 93.000 (92.644) Prec@5 100.000 (99.867) +2022-11-14 14:27:13,756 Epoch: [199][450/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0433 (0.0439) Prec@1 92.000 (92.630) Prec@5 100.000 (99.870) +2022-11-14 14:27:14,247 Epoch: [199][460/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0503 (0.0440) Prec@1 90.000 (92.574) Prec@5 100.000 (99.872) +2022-11-14 14:27:14,701 Epoch: [199][470/500] Time 0.038 (0.043) Data 0.002 (0.002) Loss 0.0315 (0.0437) Prec@1 97.000 (92.667) Prec@5 100.000 (99.875) +2022-11-14 14:27:15,211 Epoch: [199][480/500] Time 0.052 (0.043) Data 0.002 (0.002) Loss 0.0400 (0.0437) Prec@1 93.000 (92.673) Prec@5 99.000 (99.857) +2022-11-14 14:27:15,646 Epoch: [199][490/500] Time 0.041 (0.043) Data 0.002 (0.002) Loss 0.0432 (0.0436) Prec@1 93.000 (92.680) Prec@5 100.000 (99.860) +2022-11-14 14:27:16,052 Epoch: [199][499/500] Time 0.038 (0.043) Data 0.002 (0.002) Loss 0.0395 (0.0436) Prec@1 95.000 (92.725) Prec@5 100.000 (99.863) +2022-11-14 14:27:16,338 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0490 (0.0490) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:27:16,348 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0686) Prec@1 85.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:27:16,357 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0683) Prec@1 86.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 14:27:16,372 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0685) Prec@1 88.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 14:27:16,383 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0649) Prec@1 91.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 14:27:16,395 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0631) Prec@1 89.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:27:16,408 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0612) Prec@1 93.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 14:27:16,422 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0664) Prec@1 81.000 (88.125) Prec@5 99.000 (99.500) +2022-11-14 14:27:16,438 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0691) Prec@1 85.000 (87.778) Prec@5 100.000 (99.556) +2022-11-14 14:27:16,452 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0680) Prec@1 89.000 (87.900) Prec@5 99.000 (99.500) +2022-11-14 14:27:16,469 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0663) Prec@1 93.000 (88.364) Prec@5 100.000 (99.545) +2022-11-14 14:27:16,489 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0674) Prec@1 85.000 (88.083) Prec@5 100.000 (99.583) +2022-11-14 14:27:16,511 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0675) Prec@1 85.000 (87.846) Prec@5 100.000 (99.615) +2022-11-14 14:27:16,531 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0681) Prec@1 87.000 (87.786) Prec@5 99.000 (99.571) +2022-11-14 14:27:16,552 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0683) Prec@1 89.000 (87.867) Prec@5 100.000 (99.600) +2022-11-14 14:27:16,571 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0687) Prec@1 84.000 (87.625) Prec@5 98.000 (99.500) +2022-11-14 14:27:16,586 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0685) Prec@1 89.000 (87.706) Prec@5 99.000 (99.471) +2022-11-14 14:27:16,600 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1270 (0.0718) Prec@1 80.000 (87.278) Prec@5 99.000 (99.444) +2022-11-14 14:27:16,616 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0719) Prec@1 84.000 (87.105) Prec@5 99.000 (99.421) +2022-11-14 14:27:16,630 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0731) Prec@1 86.000 (87.050) Prec@5 99.000 (99.400) +2022-11-14 14:27:16,645 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0731) Prec@1 88.000 (87.095) Prec@5 100.000 (99.429) +2022-11-14 14:27:16,660 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0742) Prec@1 84.000 (86.955) Prec@5 98.000 (99.364) +2022-11-14 14:27:16,675 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0754) Prec@1 83.000 (86.783) Prec@5 97.000 (99.261) +2022-11-14 14:27:16,688 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0748) Prec@1 90.000 (86.917) Prec@5 99.000 (99.250) +2022-11-14 14:27:16,702 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0755) Prec@1 85.000 (86.840) Prec@5 99.000 (99.240) +2022-11-14 14:27:16,717 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0766) Prec@1 84.000 (86.731) Prec@5 98.000 (99.192) +2022-11-14 14:27:16,734 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0766) Prec@1 87.000 (86.741) Prec@5 100.000 (99.222) +2022-11-14 14:27:16,750 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0762) Prec@1 93.000 (86.964) Prec@5 98.000 (99.179) +2022-11-14 14:27:16,764 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0760) Prec@1 89.000 (87.034) Prec@5 99.000 (99.172) +2022-11-14 14:27:16,780 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0760) Prec@1 84.000 (86.933) Prec@5 100.000 (99.200) +2022-11-14 14:27:16,799 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0764) Prec@1 84.000 (86.839) Prec@5 99.000 (99.194) +2022-11-14 14:27:16,817 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0760) Prec@1 89.000 (86.906) Prec@5 99.000 (99.188) +2022-11-14 14:27:16,834 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0764) Prec@1 84.000 (86.818) Prec@5 100.000 (99.212) +2022-11-14 14:27:16,848 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.0772) Prec@1 81.000 (86.647) Prec@5 100.000 (99.235) +2022-11-14 14:27:16,861 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0777) Prec@1 84.000 (86.571) Prec@5 98.000 (99.200) +2022-11-14 14:27:16,877 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0774) Prec@1 87.000 (86.583) Prec@5 100.000 (99.222) +2022-11-14 14:27:16,894 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0773) Prec@1 88.000 (86.622) Prec@5 99.000 (99.216) +2022-11-14 14:27:16,909 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0778) Prec@1 81.000 (86.474) Prec@5 100.000 (99.237) +2022-11-14 14:27:16,928 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0774) Prec@1 89.000 (86.538) Prec@5 100.000 (99.256) +2022-11-14 14:27:16,946 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0770) Prec@1 88.000 (86.575) Prec@5 100.000 (99.275) +2022-11-14 14:27:16,962 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0776) Prec@1 83.000 (86.488) Prec@5 99.000 (99.268) +2022-11-14 14:27:16,979 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0772) Prec@1 89.000 (86.548) Prec@5 98.000 (99.238) +2022-11-14 14:27:16,994 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0767) Prec@1 90.000 (86.628) Prec@5 99.000 (99.233) +2022-11-14 14:27:17,010 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0766) Prec@1 86.000 (86.614) Prec@5 98.000 (99.205) +2022-11-14 14:27:17,024 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0763) Prec@1 90.000 (86.689) Prec@5 100.000 (99.222) +2022-11-14 14:27:17,040 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0765) Prec@1 86.000 (86.674) Prec@5 98.000 (99.196) +2022-11-14 14:27:17,057 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0765) Prec@1 87.000 (86.681) Prec@5 100.000 (99.213) +2022-11-14 14:27:17,073 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.0772) Prec@1 83.000 (86.604) Prec@5 100.000 (99.229) +2022-11-14 14:27:17,089 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0768) Prec@1 87.000 (86.612) Prec@5 100.000 (99.245) +2022-11-14 14:27:17,104 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1115 (0.0775) Prec@1 82.000 (86.520) Prec@5 100.000 (99.260) +2022-11-14 14:27:17,119 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0769) Prec@1 93.000 (86.647) Prec@5 100.000 (99.275) +2022-11-14 14:27:17,133 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0772) Prec@1 86.000 (86.635) Prec@5 99.000 (99.269) +2022-11-14 14:27:17,147 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0774) Prec@1 85.000 (86.604) Prec@5 99.000 (99.264) +2022-11-14 14:27:17,160 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0771) Prec@1 90.000 (86.667) Prec@5 100.000 (99.278) +2022-11-14 14:27:17,176 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0773) Prec@1 87.000 (86.673) Prec@5 99.000 (99.273) +2022-11-14 14:27:17,192 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0772) Prec@1 90.000 (86.732) Prec@5 98.000 (99.250) +2022-11-14 14:27:17,210 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0773) Prec@1 83.000 (86.667) Prec@5 100.000 (99.263) +2022-11-14 14:27:17,224 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0770) Prec@1 89.000 (86.707) Prec@5 100.000 (99.276) +2022-11-14 14:27:17,239 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0771) Prec@1 84.000 (86.661) Prec@5 100.000 (99.288) +2022-11-14 14:27:17,255 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0772) Prec@1 87.000 (86.667) Prec@5 99.000 (99.283) +2022-11-14 14:27:17,270 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0776) Prec@1 84.000 (86.623) Prec@5 97.000 (99.246) +2022-11-14 14:27:17,284 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0776) Prec@1 87.000 (86.629) Prec@5 100.000 (99.258) +2022-11-14 14:27:17,301 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0774) Prec@1 89.000 (86.667) Prec@5 100.000 (99.270) +2022-11-14 14:27:17,317 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0375 (0.0768) Prec@1 93.000 (86.766) Prec@5 100.000 (99.281) +2022-11-14 14:27:17,332 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0768) Prec@1 86.000 (86.754) Prec@5 100.000 (99.292) +2022-11-14 14:27:17,345 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0770) Prec@1 83.000 (86.697) Prec@5 99.000 (99.288) +2022-11-14 14:27:17,358 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0766) Prec@1 91.000 (86.761) Prec@5 100.000 (99.299) +2022-11-14 14:27:17,375 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0767) Prec@1 88.000 (86.779) Prec@5 97.000 (99.265) +2022-11-14 14:27:17,391 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0765) Prec@1 88.000 (86.797) Prec@5 99.000 (99.261) +2022-11-14 14:27:17,406 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0765) Prec@1 86.000 (86.786) Prec@5 98.000 (99.243) +2022-11-14 14:27:17,421 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0769) Prec@1 86.000 (86.775) Prec@5 99.000 (99.239) +2022-11-14 14:27:17,437 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0768) Prec@1 89.000 (86.806) Prec@5 99.000 (99.236) +2022-11-14 14:27:17,453 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0764) Prec@1 93.000 (86.890) Prec@5 99.000 (99.233) +2022-11-14 14:27:17,467 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0761) Prec@1 89.000 (86.919) Prec@5 100.000 (99.243) +2022-11-14 14:27:17,483 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0764) Prec@1 83.000 (86.867) Prec@5 100.000 (99.253) +2022-11-14 14:27:17,498 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0761) Prec@1 91.000 (86.921) Prec@5 98.000 (99.237) +2022-11-14 14:27:17,514 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0760) Prec@1 89.000 (86.948) Prec@5 99.000 (99.234) +2022-11-14 14:27:17,530 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0762) Prec@1 86.000 (86.936) Prec@5 96.000 (99.192) +2022-11-14 14:27:17,545 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0761) Prec@1 88.000 (86.949) Prec@5 100.000 (99.203) +2022-11-14 14:27:17,561 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0762) Prec@1 85.000 (86.925) Prec@5 100.000 (99.213) +2022-11-14 14:27:17,577 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0762) Prec@1 88.000 (86.938) Prec@5 98.000 (99.198) +2022-11-14 14:27:17,593 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0763) Prec@1 85.000 (86.915) Prec@5 99.000 (99.195) +2022-11-14 14:27:17,608 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0764) Prec@1 83.000 (86.867) Prec@5 99.000 (99.193) +2022-11-14 14:27:17,624 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0764) Prec@1 89.000 (86.893) Prec@5 99.000 (99.190) +2022-11-14 14:27:17,641 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0767) Prec@1 81.000 (86.824) Prec@5 100.000 (99.200) +2022-11-14 14:27:17,657 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0770) Prec@1 84.000 (86.791) Prec@5 98.000 (99.186) +2022-11-14 14:27:17,674 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0771) Prec@1 89.000 (86.816) Prec@5 98.000 (99.172) +2022-11-14 14:27:17,689 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0769) Prec@1 89.000 (86.841) Prec@5 99.000 (99.170) +2022-11-14 14:27:17,704 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0769) Prec@1 86.000 (86.831) Prec@5 100.000 (99.180) +2022-11-14 14:27:17,719 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0769) Prec@1 88.000 (86.844) Prec@5 99.000 (99.178) +2022-11-14 14:27:17,736 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0767) Prec@1 91.000 (86.890) Prec@5 100.000 (99.187) +2022-11-14 14:27:17,751 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0764) Prec@1 94.000 (86.967) Prec@5 100.000 (99.196) +2022-11-14 14:27:17,764 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0765) Prec@1 86.000 (86.957) Prec@5 100.000 (99.204) +2022-11-14 14:27:17,779 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0766) Prec@1 86.000 (86.947) Prec@5 99.000 (99.202) +2022-11-14 14:27:17,795 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.0770) Prec@1 82.000 (86.895) Prec@5 97.000 (99.179) +2022-11-14 14:27:17,809 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0768) Prec@1 88.000 (86.906) Prec@5 99.000 (99.177) +2022-11-14 14:27:17,824 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0413 (0.0765) Prec@1 94.000 (86.979) Prec@5 99.000 (99.175) +2022-11-14 14:27:17,840 Test: [97/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0768) Prec@1 85.000 (86.959) Prec@5 98.000 (99.163) +2022-11-14 14:27:17,856 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0770) Prec@1 84.000 (86.929) Prec@5 100.000 (99.172) +2022-11-14 14:27:17,873 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0769) Prec@1 88.000 (86.940) Prec@5 100.000 (99.180) +2022-11-14 14:27:17,937 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:27:18,307 Epoch: [200][0/500] Time 0.037 (0.037) Data 0.265 (0.265) Loss 0.0382 (0.0382) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:27:18,565 Epoch: [200][10/500] Time 0.030 (0.025) Data 0.001 (0.026) Loss 0.0705 (0.0544) Prec@1 90.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:27:18,867 Epoch: [200][20/500] Time 0.021 (0.026) Data 0.002 (0.014) Loss 0.0395 (0.0494) Prec@1 94.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:27:19,144 Epoch: [200][30/500] Time 0.025 (0.025) Data 0.002 (0.010) Loss 0.0399 (0.0470) Prec@1 92.000 (92.250) Prec@5 99.000 (99.500) +2022-11-14 14:27:19,419 Epoch: [200][40/500] Time 0.025 (0.025) Data 0.002 (0.008) Loss 0.0279 (0.0432) Prec@1 96.000 (93.000) Prec@5 100.000 (99.600) +2022-11-14 14:27:19,871 Epoch: [200][50/500] Time 0.055 (0.028) Data 0.002 (0.007) Loss 0.0327 (0.0414) Prec@1 94.000 (93.167) Prec@5 100.000 (99.667) +2022-11-14 14:27:20,394 Epoch: [200][60/500] Time 0.045 (0.031) Data 0.002 (0.006) Loss 0.0495 (0.0426) Prec@1 91.000 (92.857) Prec@5 99.000 (99.571) +2022-11-14 14:27:20,922 Epoch: [200][70/500] Time 0.051 (0.033) Data 0.002 (0.006) Loss 0.0424 (0.0426) Prec@1 93.000 (92.875) Prec@5 100.000 (99.625) +2022-11-14 14:27:21,605 Epoch: [200][80/500] Time 0.074 (0.037) Data 0.002 (0.005) Loss 0.0350 (0.0417) Prec@1 94.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:27:22,155 Epoch: [200][90/500] Time 0.042 (0.038) Data 0.002 (0.005) Loss 0.0440 (0.0420) Prec@1 91.000 (92.800) Prec@5 100.000 (99.700) +2022-11-14 14:27:22,737 Epoch: [200][100/500] Time 0.065 (0.039) Data 0.002 (0.004) Loss 0.0509 (0.0428) Prec@1 94.000 (92.909) Prec@5 99.000 (99.636) +2022-11-14 14:27:23,312 Epoch: [200][110/500] Time 0.040 (0.041) Data 0.002 (0.004) Loss 0.0313 (0.0418) Prec@1 94.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:27:23,852 Epoch: [200][120/500] Time 0.041 (0.041) Data 0.002 (0.004) Loss 0.0470 (0.0422) Prec@1 91.000 (92.846) Prec@5 100.000 (99.692) +2022-11-14 14:27:24,379 Epoch: [200][130/500] Time 0.051 (0.042) Data 0.002 (0.004) Loss 0.0321 (0.0415) Prec@1 94.000 (92.929) Prec@5 100.000 (99.714) +2022-11-14 14:27:24,925 Epoch: [200][140/500] Time 0.046 (0.042) Data 0.002 (0.004) Loss 0.0313 (0.0408) Prec@1 96.000 (93.133) Prec@5 100.000 (99.733) +2022-11-14 14:27:25,463 Epoch: [200][150/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0364 (0.0406) Prec@1 93.000 (93.125) Prec@5 100.000 (99.750) +2022-11-14 14:27:26,009 Epoch: [200][160/500] Time 0.053 (0.043) Data 0.002 (0.004) Loss 0.0442 (0.0408) Prec@1 94.000 (93.176) Prec@5 99.000 (99.706) +2022-11-14 14:27:26,521 Epoch: [200][170/500] Time 0.049 (0.043) Data 0.003 (0.003) Loss 0.0618 (0.0419) Prec@1 89.000 (92.944) Prec@5 100.000 (99.722) +2022-11-14 14:27:27,042 Epoch: [200][180/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0412 (0.0419) Prec@1 95.000 (93.053) Prec@5 100.000 (99.737) +2022-11-14 14:27:27,674 Epoch: [200][190/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0444 (0.0420) Prec@1 94.000 (93.100) Prec@5 100.000 (99.750) +2022-11-14 14:27:28,202 Epoch: [200][200/500] Time 0.048 (0.044) Data 0.003 (0.003) Loss 0.0390 (0.0419) Prec@1 93.000 (93.095) Prec@5 100.000 (99.762) +2022-11-14 14:27:28,728 Epoch: [200][210/500] Time 0.054 (0.044) Data 0.002 (0.003) Loss 0.0357 (0.0416) Prec@1 95.000 (93.182) Prec@5 99.000 (99.727) +2022-11-14 14:27:29,239 Epoch: [200][220/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0241 (0.0408) Prec@1 95.000 (93.261) Prec@5 100.000 (99.739) +2022-11-14 14:27:29,879 Epoch: [200][230/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0511 (0.0413) Prec@1 89.000 (93.083) Prec@5 100.000 (99.750) +2022-11-14 14:27:30,385 Epoch: [200][240/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0472 (0.0415) Prec@1 91.000 (93.000) Prec@5 100.000 (99.760) +2022-11-14 14:27:30,908 Epoch: [200][250/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0404 (0.0415) Prec@1 93.000 (93.000) Prec@5 100.000 (99.769) +2022-11-14 14:27:31,423 Epoch: [200][260/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0736 (0.0426) Prec@1 86.000 (92.741) Prec@5 100.000 (99.778) +2022-11-14 14:27:31,959 Epoch: [200][270/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0739 (0.0438) Prec@1 86.000 (92.500) Prec@5 100.000 (99.786) +2022-11-14 14:27:32,483 Epoch: [200][280/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0298 (0.0433) Prec@1 94.000 (92.552) Prec@5 100.000 (99.793) +2022-11-14 14:27:33,013 Epoch: [200][290/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0568 (0.0437) Prec@1 91.000 (92.500) Prec@5 100.000 (99.800) +2022-11-14 14:27:33,554 Epoch: [200][300/500] Time 0.061 (0.046) Data 0.002 (0.003) Loss 0.0482 (0.0439) Prec@1 94.000 (92.548) Prec@5 99.000 (99.774) +2022-11-14 14:27:34,064 Epoch: [200][310/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0328 (0.0435) Prec@1 94.000 (92.594) Prec@5 99.000 (99.750) +2022-11-14 14:27:34,572 Epoch: [200][320/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0380 (0.0434) Prec@1 93.000 (92.606) Prec@5 100.000 (99.758) +2022-11-14 14:27:35,090 Epoch: [200][330/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0800 (0.0444) Prec@1 85.000 (92.382) Prec@5 99.000 (99.735) +2022-11-14 14:27:35,622 Epoch: [200][340/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0509 (0.0446) Prec@1 90.000 (92.314) Prec@5 99.000 (99.714) +2022-11-14 14:27:36,208 Epoch: [200][350/500] Time 0.080 (0.046) Data 0.002 (0.003) Loss 0.0594 (0.0450) Prec@1 92.000 (92.306) Prec@5 99.000 (99.694) +2022-11-14 14:27:36,797 Epoch: [200][360/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0714 (0.0457) Prec@1 87.000 (92.162) Prec@5 100.000 (99.703) +2022-11-14 14:27:37,321 Epoch: [200][370/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0456 (0.0457) Prec@1 93.000 (92.184) Prec@5 100.000 (99.711) +2022-11-14 14:27:37,832 Epoch: [200][380/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0650 (0.0462) Prec@1 90.000 (92.128) Prec@5 99.000 (99.692) +2022-11-14 14:27:38,480 Epoch: [200][390/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0653 (0.0467) Prec@1 89.000 (92.050) Prec@5 100.000 (99.700) +2022-11-14 14:27:38,988 Epoch: [200][400/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0492 (0.0468) Prec@1 92.000 (92.049) Prec@5 99.000 (99.683) +2022-11-14 14:27:39,498 Epoch: [200][410/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0325 (0.0464) Prec@1 95.000 (92.119) Prec@5 100.000 (99.690) +2022-11-14 14:27:40,035 Epoch: [200][420/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0319 (0.0461) Prec@1 93.000 (92.140) Prec@5 100.000 (99.698) +2022-11-14 14:27:40,558 Epoch: [200][430/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0291 (0.0457) Prec@1 96.000 (92.227) Prec@5 99.000 (99.682) +2022-11-14 14:27:41,082 Epoch: [200][440/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0497 (0.0458) Prec@1 92.000 (92.222) Prec@5 100.000 (99.689) +2022-11-14 14:27:41,601 Epoch: [200][450/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0532 (0.0460) Prec@1 91.000 (92.196) Prec@5 99.000 (99.674) +2022-11-14 14:27:42,106 Epoch: [200][460/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0270 (0.0456) Prec@1 95.000 (92.255) Prec@5 100.000 (99.681) +2022-11-14 14:27:42,623 Epoch: [200][470/500] Time 0.050 (0.046) Data 0.002 (0.002) Loss 0.0507 (0.0457) Prec@1 91.000 (92.229) Prec@5 99.000 (99.667) +2022-11-14 14:27:43,144 Epoch: [200][480/500] Time 0.048 (0.046) Data 0.002 (0.002) Loss 0.0229 (0.0452) Prec@1 97.000 (92.327) Prec@5 100.000 (99.673) +2022-11-14 14:27:43,654 Epoch: [200][490/500] Time 0.046 (0.046) Data 0.002 (0.002) Loss 0.0454 (0.0452) Prec@1 93.000 (92.340) Prec@5 100.000 (99.680) +2022-11-14 14:27:44,126 Epoch: [200][499/500] Time 0.045 (0.046) Data 0.002 (0.002) Loss 0.0338 (0.0450) Prec@1 95.000 (92.392) Prec@5 98.000 (99.647) +2022-11-14 14:27:44,414 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0790 (0.0790) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:27:44,422 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0770) Prec@1 88.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:27:44,433 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0758) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:27:44,445 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0789) Prec@1 87.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 14:27:44,454 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0786) Prec@1 89.000 (87.400) Prec@5 100.000 (99.800) +2022-11-14 14:27:44,461 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0310 (0.0707) Prec@1 93.000 (88.333) Prec@5 100.000 (99.833) +2022-11-14 14:27:44,470 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0725) Prec@1 88.000 (88.286) Prec@5 99.000 (99.714) +2022-11-14 14:27:44,481 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0762) Prec@1 81.000 (87.375) Prec@5 98.000 (99.500) +2022-11-14 14:27:44,489 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0782) Prec@1 87.000 (87.333) Prec@5 99.000 (99.444) +2022-11-14 14:27:44,498 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0773) Prec@1 89.000 (87.500) Prec@5 98.000 (99.300) +2022-11-14 14:27:44,507 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0758) Prec@1 90.000 (87.727) Prec@5 100.000 (99.364) +2022-11-14 14:27:44,516 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0764) Prec@1 87.000 (87.667) Prec@5 100.000 (99.417) +2022-11-14 14:27:44,526 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0746) Prec@1 90.000 (87.846) Prec@5 100.000 (99.462) +2022-11-14 14:27:44,535 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0742) Prec@1 88.000 (87.857) Prec@5 99.000 (99.429) +2022-11-14 14:27:44,544 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0744) Prec@1 86.000 (87.733) Prec@5 99.000 (99.400) +2022-11-14 14:27:44,555 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0757) Prec@1 82.000 (87.375) Prec@5 100.000 (99.438) +2022-11-14 14:27:44,564 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0747) Prec@1 91.000 (87.588) Prec@5 99.000 (99.412) +2022-11-14 14:27:44,573 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0764) Prec@1 81.000 (87.222) Prec@5 100.000 (99.444) +2022-11-14 14:27:44,582 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0772) Prec@1 84.000 (87.053) Prec@5 98.000 (99.368) +2022-11-14 14:27:44,591 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0773) Prec@1 86.000 (87.000) Prec@5 100.000 (99.400) +2022-11-14 14:27:44,599 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0773) Prec@1 88.000 (87.048) Prec@5 99.000 (99.381) +2022-11-14 14:27:44,609 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0772) Prec@1 87.000 (87.045) Prec@5 99.000 (99.364) +2022-11-14 14:27:44,619 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0782) Prec@1 83.000 (86.870) Prec@5 98.000 (99.304) +2022-11-14 14:27:44,628 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0782) Prec@1 88.000 (86.917) Prec@5 99.000 (99.292) +2022-11-14 14:27:44,637 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0793) Prec@1 84.000 (86.800) Prec@5 100.000 (99.320) +2022-11-14 14:27:44,645 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0803) Prec@1 82.000 (86.615) Prec@5 98.000 (99.269) +2022-11-14 14:27:44,654 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0799) Prec@1 88.000 (86.667) Prec@5 100.000 (99.296) +2022-11-14 14:27:44,662 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0798) Prec@1 88.000 (86.714) Prec@5 100.000 (99.321) +2022-11-14 14:27:44,672 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0790) Prec@1 91.000 (86.862) Prec@5 99.000 (99.310) +2022-11-14 14:27:44,682 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0797) Prec@1 81.000 (86.667) Prec@5 97.000 (99.233) +2022-11-14 14:27:44,691 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0790) Prec@1 90.000 (86.774) Prec@5 100.000 (99.258) +2022-11-14 14:27:44,700 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0792) Prec@1 86.000 (86.750) Prec@5 99.000 (99.250) +2022-11-14 14:27:44,709 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0787) Prec@1 89.000 (86.818) Prec@5 100.000 (99.273) +2022-11-14 14:27:44,717 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0791) Prec@1 86.000 (86.794) Prec@5 98.000 (99.235) +2022-11-14 14:27:44,727 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0795) Prec@1 84.000 (86.714) Prec@5 100.000 (99.257) +2022-11-14 14:27:44,737 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0793) Prec@1 90.000 (86.806) Prec@5 100.000 (99.278) +2022-11-14 14:27:44,746 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0788) Prec@1 91.000 (86.919) Prec@5 99.000 (99.270) +2022-11-14 14:27:44,756 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0792) Prec@1 84.000 (86.842) Prec@5 99.000 (99.263) +2022-11-14 14:27:44,765 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0786) Prec@1 92.000 (86.974) Prec@5 99.000 (99.256) +2022-11-14 14:27:44,774 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0781) Prec@1 89.000 (87.025) Prec@5 99.000 (99.250) +2022-11-14 14:27:44,784 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0785) Prec@1 84.000 (86.951) Prec@5 98.000 (99.220) +2022-11-14 14:27:44,794 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0782) Prec@1 91.000 (87.048) Prec@5 99.000 (99.214) +2022-11-14 14:27:44,803 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0775) Prec@1 92.000 (87.163) Prec@5 100.000 (99.233) +2022-11-14 14:27:44,813 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0773) Prec@1 88.000 (87.182) Prec@5 99.000 (99.227) +2022-11-14 14:27:44,821 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0773) Prec@1 86.000 (87.156) Prec@5 100.000 (99.244) +2022-11-14 14:27:44,831 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0778) Prec@1 81.000 (87.022) Prec@5 100.000 (99.261) +2022-11-14 14:27:44,841 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0779) Prec@1 85.000 (86.979) Prec@5 100.000 (99.277) +2022-11-14 14:27:44,851 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0783) Prec@1 85.000 (86.938) Prec@5 99.000 (99.271) +2022-11-14 14:27:44,861 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0407 (0.0776) Prec@1 93.000 (87.061) Prec@5 100.000 (99.286) +2022-11-14 14:27:44,870 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1159 (0.0783) Prec@1 80.000 (86.920) Prec@5 100.000 (99.300) +2022-11-14 14:27:44,880 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0785) Prec@1 87.000 (86.922) Prec@5 99.000 (99.294) +2022-11-14 14:27:44,889 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0787) Prec@1 82.000 (86.827) Prec@5 100.000 (99.308) +2022-11-14 14:27:44,898 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0785) Prec@1 88.000 (86.849) Prec@5 99.000 (99.302) +2022-11-14 14:27:44,908 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0783) Prec@1 88.000 (86.870) Prec@5 100.000 (99.315) +2022-11-14 14:27:44,917 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0783) Prec@1 88.000 (86.891) Prec@5 100.000 (99.327) +2022-11-14 14:27:44,926 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0783) Prec@1 88.000 (86.911) Prec@5 99.000 (99.321) +2022-11-14 14:27:44,937 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0780) Prec@1 87.000 (86.912) Prec@5 100.000 (99.333) +2022-11-14 14:27:44,946 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0781) Prec@1 87.000 (86.914) Prec@5 100.000 (99.345) +2022-11-14 14:27:44,955 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0781) Prec@1 86.000 (86.898) Prec@5 100.000 (99.356) +2022-11-14 14:27:44,965 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0782) Prec@1 85.000 (86.867) Prec@5 99.000 (99.350) +2022-11-14 14:27:44,974 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0781) Prec@1 90.000 (86.918) Prec@5 99.000 (99.344) +2022-11-14 14:27:44,984 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0782) Prec@1 87.000 (86.919) Prec@5 99.000 (99.339) +2022-11-14 14:27:44,994 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0781) Prec@1 89.000 (86.952) Prec@5 99.000 (99.333) +2022-11-14 14:27:45,003 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0346 (0.0774) Prec@1 95.000 (87.078) Prec@5 100.000 (99.344) +2022-11-14 14:27:45,012 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0774) Prec@1 87.000 (87.077) Prec@5 99.000 (99.338) +2022-11-14 14:27:45,023 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0775) Prec@1 86.000 (87.061) Prec@5 99.000 (99.333) +2022-11-14 14:27:45,033 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0770) Prec@1 93.000 (87.149) Prec@5 100.000 (99.343) +2022-11-14 14:27:45,042 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0769) Prec@1 87.000 (87.147) Prec@5 100.000 (99.353) +2022-11-14 14:27:45,052 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0767) Prec@1 92.000 (87.217) Prec@5 100.000 (99.362) +2022-11-14 14:27:45,061 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0771) Prec@1 86.000 (87.200) Prec@5 100.000 (99.371) +2022-11-14 14:27:45,070 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0770) Prec@1 89.000 (87.225) Prec@5 99.000 (99.366) +2022-11-14 14:27:45,079 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0767) Prec@1 90.000 (87.264) Prec@5 100.000 (99.375) +2022-11-14 14:27:45,089 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0768) Prec@1 84.000 (87.219) Prec@5 99.000 (99.370) +2022-11-14 14:27:45,098 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0766) Prec@1 89.000 (87.243) Prec@5 100.000 (99.378) +2022-11-14 14:27:45,106 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0768) Prec@1 82.000 (87.173) Prec@5 100.000 (99.387) +2022-11-14 14:27:45,116 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0766) Prec@1 88.000 (87.184) Prec@5 98.000 (99.368) +2022-11-14 14:27:45,126 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0766) Prec@1 89.000 (87.208) Prec@5 98.000 (99.351) +2022-11-14 14:27:45,137 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0769) Prec@1 84.000 (87.167) Prec@5 98.000 (99.333) +2022-11-14 14:27:45,146 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0770) Prec@1 87.000 (87.165) Prec@5 100.000 (99.342) +2022-11-14 14:27:45,155 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0769) Prec@1 86.000 (87.150) Prec@5 100.000 (99.350) +2022-11-14 14:27:45,165 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0768) Prec@1 89.000 (87.173) Prec@5 99.000 (99.346) +2022-11-14 14:27:45,175 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0768) Prec@1 85.000 (87.146) Prec@5 100.000 (99.354) +2022-11-14 14:27:45,184 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0768) Prec@1 88.000 (87.157) Prec@5 98.000 (99.337) +2022-11-14 14:27:45,194 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0768) Prec@1 87.000 (87.155) Prec@5 99.000 (99.333) +2022-11-14 14:27:45,203 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0770) Prec@1 83.000 (87.106) Prec@5 100.000 (99.341) +2022-11-14 14:27:45,212 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1106 (0.0773) Prec@1 81.000 (87.035) Prec@5 97.000 (99.314) +2022-11-14 14:27:45,222 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0775) Prec@1 83.000 (86.989) Prec@5 99.000 (99.310) +2022-11-14 14:27:45,231 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0777) Prec@1 85.000 (86.966) Prec@5 98.000 (99.295) +2022-11-14 14:27:45,240 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0775) Prec@1 90.000 (87.000) Prec@5 99.000 (99.292) +2022-11-14 14:27:45,250 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0777) Prec@1 86.000 (86.989) Prec@5 100.000 (99.300) +2022-11-14 14:27:45,258 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0775) Prec@1 91.000 (87.033) Prec@5 100.000 (99.308) +2022-11-14 14:27:45,267 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0772) Prec@1 92.000 (87.087) Prec@5 99.000 (99.304) +2022-11-14 14:27:45,277 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0774) Prec@1 85.000 (87.065) Prec@5 99.000 (99.301) +2022-11-14 14:27:45,287 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0773) Prec@1 88.000 (87.074) Prec@5 98.000 (99.287) +2022-11-14 14:27:45,297 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0773) Prec@1 88.000 (87.084) Prec@5 100.000 (99.295) +2022-11-14 14:27:45,306 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0772) Prec@1 91.000 (87.125) Prec@5 99.000 (99.292) +2022-11-14 14:27:45,315 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0492 (0.0769) Prec@1 93.000 (87.186) Prec@5 99.000 (99.289) +2022-11-14 14:27:45,324 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0772) Prec@1 83.000 (87.143) Prec@5 96.000 (99.255) +2022-11-14 14:27:45,335 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0775) Prec@1 84.000 (87.111) Prec@5 97.000 (99.232) +2022-11-14 14:27:45,343 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0777) Prec@1 84.000 (87.080) Prec@5 99.000 (99.230) +2022-11-14 14:27:45,418 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:27:45,723 Epoch: [201][0/500] Time 0.023 (0.023) Data 0.220 (0.220) Loss 0.0508 (0.0508) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:27:45,945 Epoch: [201][10/500] Time 0.020 (0.020) Data 0.002 (0.022) Loss 0.0302 (0.0405) Prec@1 94.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 14:27:46,159 Epoch: [201][20/500] Time 0.019 (0.019) Data 0.002 (0.012) Loss 0.0510 (0.0440) Prec@1 90.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:27:46,385 Epoch: [201][30/500] Time 0.022 (0.020) Data 0.002 (0.009) Loss 0.0274 (0.0398) Prec@1 94.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:27:46,663 Epoch: [201][40/500] Time 0.028 (0.021) Data 0.002 (0.007) Loss 0.0274 (0.0374) Prec@1 96.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 14:27:46,948 Epoch: [201][50/500] Time 0.026 (0.022) Data 0.002 (0.006) Loss 0.0309 (0.0363) Prec@1 94.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 14:27:47,229 Epoch: [201][60/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0522 (0.0386) Prec@1 91.000 (92.714) Prec@5 100.000 (99.714) +2022-11-14 14:27:47,507 Epoch: [201][70/500] Time 0.024 (0.022) Data 0.002 (0.005) Loss 0.0441 (0.0393) Prec@1 90.000 (92.375) Prec@5 100.000 (99.750) +2022-11-14 14:27:47,791 Epoch: [201][80/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0372 (0.0390) Prec@1 94.000 (92.556) Prec@5 100.000 (99.778) +2022-11-14 14:27:48,079 Epoch: [201][90/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0297 (0.0381) Prec@1 96.000 (92.900) Prec@5 100.000 (99.800) +2022-11-14 14:27:48,363 Epoch: [201][100/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0446 (0.0387) Prec@1 93.000 (92.909) Prec@5 99.000 (99.727) +2022-11-14 14:27:48,789 Epoch: [201][110/500] Time 0.037 (0.025) Data 0.002 (0.004) Loss 0.0104 (0.0363) Prec@1 98.000 (93.333) Prec@5 100.000 (99.750) +2022-11-14 14:27:49,245 Epoch: [201][120/500] Time 0.042 (0.026) Data 0.003 (0.004) Loss 0.0703 (0.0389) Prec@1 85.000 (92.692) Prec@5 100.000 (99.769) +2022-11-14 14:27:49,689 Epoch: [201][130/500] Time 0.041 (0.027) Data 0.002 (0.004) Loss 0.0741 (0.0415) Prec@1 84.000 (92.071) Prec@5 100.000 (99.786) +2022-11-14 14:27:50,137 Epoch: [201][140/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0561 (0.0424) Prec@1 89.000 (91.867) Prec@5 100.000 (99.800) +2022-11-14 14:27:50,577 Epoch: [201][150/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0625 (0.0437) Prec@1 89.000 (91.688) Prec@5 100.000 (99.812) +2022-11-14 14:27:51,021 Epoch: [201][160/500] Time 0.049 (0.029) Data 0.002 (0.003) Loss 0.0445 (0.0437) Prec@1 93.000 (91.765) Prec@5 98.000 (99.706) +2022-11-14 14:27:51,469 Epoch: [201][170/500] Time 0.040 (0.030) Data 0.002 (0.003) Loss 0.0340 (0.0432) Prec@1 96.000 (92.000) Prec@5 100.000 (99.722) +2022-11-14 14:27:51,915 Epoch: [201][180/500] Time 0.045 (0.030) Data 0.002 (0.003) Loss 0.0560 (0.0439) Prec@1 91.000 (91.947) Prec@5 99.000 (99.684) +2022-11-14 14:27:52,369 Epoch: [201][190/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0647 (0.0449) Prec@1 89.000 (91.800) Prec@5 100.000 (99.700) +2022-11-14 14:27:52,827 Epoch: [201][200/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0363 (0.0445) Prec@1 96.000 (92.000) Prec@5 100.000 (99.714) +2022-11-14 14:27:53,308 Epoch: [201][210/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0291 (0.0438) Prec@1 96.000 (92.182) Prec@5 100.000 (99.727) +2022-11-14 14:27:53,782 Epoch: [201][220/500] Time 0.048 (0.032) Data 0.002 (0.003) Loss 0.0132 (0.0425) Prec@1 98.000 (92.435) Prec@5 100.000 (99.739) +2022-11-14 14:27:54,262 Epoch: [201][230/500] Time 0.044 (0.033) Data 0.001 (0.003) Loss 0.0465 (0.0426) Prec@1 92.000 (92.417) Prec@5 100.000 (99.750) +2022-11-14 14:27:54,806 Epoch: [201][240/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0330 (0.0423) Prec@1 94.000 (92.480) Prec@5 100.000 (99.760) +2022-11-14 14:27:55,247 Epoch: [201][250/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0436 (0.0423) Prec@1 93.000 (92.500) Prec@5 100.000 (99.769) +2022-11-14 14:27:55,813 Epoch: [201][260/500] Time 0.056 (0.035) Data 0.002 (0.003) Loss 0.0494 (0.0426) Prec@1 93.000 (92.519) Prec@5 99.000 (99.741) +2022-11-14 14:27:56,251 Epoch: [201][270/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0382 (0.0424) Prec@1 93.000 (92.536) Prec@5 100.000 (99.750) +2022-11-14 14:27:56,703 Epoch: [201][280/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0667 (0.0433) Prec@1 89.000 (92.414) Prec@5 97.000 (99.655) +2022-11-14 14:27:57,208 Epoch: [201][290/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0652 (0.0440) Prec@1 88.000 (92.267) Prec@5 99.000 (99.633) +2022-11-14 14:27:57,703 Epoch: [201][300/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0226 (0.0433) Prec@1 97.000 (92.419) Prec@5 100.000 (99.645) +2022-11-14 14:27:58,232 Epoch: [201][310/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0329 (0.0430) Prec@1 96.000 (92.531) Prec@5 100.000 (99.656) +2022-11-14 14:27:58,758 Epoch: [201][320/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0239 (0.0424) Prec@1 97.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:27:59,206 Epoch: [201][330/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0516 (0.0427) Prec@1 91.000 (92.618) Prec@5 99.000 (99.647) +2022-11-14 14:27:59,725 Epoch: [201][340/500] Time 0.047 (0.037) Data 0.002 (0.003) Loss 0.0257 (0.0422) Prec@1 97.000 (92.743) Prec@5 100.000 (99.657) +2022-11-14 14:28:00,152 Epoch: [201][350/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0342 (0.0420) Prec@1 95.000 (92.806) Prec@5 100.000 (99.667) +2022-11-14 14:28:00,715 Epoch: [201][360/500] Time 0.063 (0.037) Data 0.002 (0.003) Loss 0.0417 (0.0419) Prec@1 94.000 (92.838) Prec@5 100.000 (99.676) +2022-11-14 14:28:01,152 Epoch: [201][370/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0412 (0.0419) Prec@1 91.000 (92.789) Prec@5 100.000 (99.684) +2022-11-14 14:28:01,597 Epoch: [201][380/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0509 (0.0422) Prec@1 91.000 (92.744) Prec@5 99.000 (99.667) +2022-11-14 14:28:02,159 Epoch: [201][390/500] Time 0.057 (0.037) Data 0.002 (0.003) Loss 0.0462 (0.0423) Prec@1 94.000 (92.775) Prec@5 100.000 (99.675) +2022-11-14 14:28:02,589 Epoch: [201][400/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0357 (0.0421) Prec@1 92.000 (92.756) Prec@5 99.000 (99.659) +2022-11-14 14:28:03,044 Epoch: [201][410/500] Time 0.050 (0.038) Data 0.002 (0.002) Loss 0.0682 (0.0427) Prec@1 90.000 (92.690) Prec@5 100.000 (99.667) +2022-11-14 14:28:03,494 Epoch: [201][420/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0680 (0.0433) Prec@1 88.000 (92.581) Prec@5 100.000 (99.674) +2022-11-14 14:28:03,942 Epoch: [201][430/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0211 (0.0428) Prec@1 97.000 (92.682) Prec@5 100.000 (99.682) +2022-11-14 14:28:04,399 Epoch: [201][440/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0368 (0.0427) Prec@1 94.000 (92.711) Prec@5 100.000 (99.689) +2022-11-14 14:28:04,836 Epoch: [201][450/500] Time 0.048 (0.038) Data 0.002 (0.002) Loss 0.0295 (0.0424) Prec@1 95.000 (92.761) Prec@5 100.000 (99.696) +2022-11-14 14:28:05,284 Epoch: [201][460/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0576 (0.0427) Prec@1 89.000 (92.681) Prec@5 100.000 (99.702) +2022-11-14 14:28:05,724 Epoch: [201][470/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0759 (0.0434) Prec@1 90.000 (92.625) Prec@5 99.000 (99.688) +2022-11-14 14:28:06,172 Epoch: [201][480/500] Time 0.041 (0.038) Data 0.003 (0.002) Loss 0.0356 (0.0432) Prec@1 92.000 (92.612) Prec@5 100.000 (99.694) +2022-11-14 14:28:06,615 Epoch: [201][490/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0608 (0.0436) Prec@1 90.000 (92.560) Prec@5 99.000 (99.680) +2022-11-14 14:28:07,019 Epoch: [201][499/500] Time 0.048 (0.038) Data 0.002 (0.002) Loss 0.0451 (0.0436) Prec@1 93.000 (92.569) Prec@5 100.000 (99.686) +2022-11-14 14:28:07,317 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0528 (0.0528) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:07,325 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0662) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:07,335 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0682) Prec@1 89.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 14:28:07,347 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0715) Prec@1 87.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:28:07,356 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0718) Prec@1 89.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 14:28:07,364 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0677) Prec@1 91.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 14:28:07,376 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0655) Prec@1 92.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 14:28:07,390 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0686) Prec@1 86.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 14:28:07,400 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0679) Prec@1 91.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 14:28:07,413 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0687) Prec@1 87.000 (88.800) Prec@5 99.000 (99.600) +2022-11-14 14:28:07,427 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0689) Prec@1 89.000 (88.818) Prec@5 99.000 (99.545) +2022-11-14 14:28:07,441 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0699) Prec@1 85.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:28:07,455 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0681) Prec@1 93.000 (88.846) Prec@5 100.000 (99.538) +2022-11-14 14:28:07,469 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0683) Prec@1 89.000 (88.857) Prec@5 100.000 (99.571) +2022-11-14 14:28:07,483 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0684) Prec@1 86.000 (88.667) Prec@5 99.000 (99.533) +2022-11-14 14:28:07,499 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0705) Prec@1 81.000 (88.188) Prec@5 99.000 (99.500) +2022-11-14 14:28:07,513 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0691) Prec@1 93.000 (88.471) Prec@5 98.000 (99.412) +2022-11-14 14:28:07,525 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0708) Prec@1 87.000 (88.389) Prec@5 100.000 (99.444) +2022-11-14 14:28:07,541 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0715) Prec@1 85.000 (88.211) Prec@5 99.000 (99.421) +2022-11-14 14:28:07,556 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0725) Prec@1 86.000 (88.100) Prec@5 99.000 (99.400) +2022-11-14 14:28:07,571 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0726) Prec@1 87.000 (88.048) Prec@5 99.000 (99.381) +2022-11-14 14:28:07,586 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0734) Prec@1 86.000 (87.955) Prec@5 97.000 (99.273) +2022-11-14 14:28:07,602 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0748) Prec@1 85.000 (87.826) Prec@5 99.000 (99.261) +2022-11-14 14:28:07,617 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0752) Prec@1 85.000 (87.708) Prec@5 100.000 (99.292) +2022-11-14 14:28:07,631 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0760) Prec@1 87.000 (87.680) Prec@5 100.000 (99.320) +2022-11-14 14:28:07,644 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0764) Prec@1 87.000 (87.654) Prec@5 99.000 (99.308) +2022-11-14 14:28:07,659 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0754) Prec@1 91.000 (87.778) Prec@5 100.000 (99.333) +2022-11-14 14:28:07,675 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0753) Prec@1 87.000 (87.750) Prec@5 100.000 (99.357) +2022-11-14 14:28:07,691 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0752) Prec@1 90.000 (87.828) Prec@5 98.000 (99.310) +2022-11-14 14:28:07,707 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0747) Prec@1 90.000 (87.900) Prec@5 98.000 (99.267) +2022-11-14 14:28:07,723 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0745) Prec@1 88.000 (87.903) Prec@5 100.000 (99.290) +2022-11-14 14:28:07,738 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0750) Prec@1 86.000 (87.844) Prec@5 98.000 (99.250) +2022-11-14 14:28:07,755 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0753) Prec@1 86.000 (87.788) Prec@5 97.000 (99.182) +2022-11-14 14:28:07,770 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0759) Prec@1 87.000 (87.765) Prec@5 100.000 (99.206) +2022-11-14 14:28:07,785 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0764) Prec@1 83.000 (87.629) Prec@5 100.000 (99.229) +2022-11-14 14:28:07,800 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0759) Prec@1 92.000 (87.750) Prec@5 99.000 (99.222) +2022-11-14 14:28:07,819 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0757) Prec@1 86.000 (87.703) Prec@5 99.000 (99.216) +2022-11-14 14:28:07,835 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0762) Prec@1 82.000 (87.553) Prec@5 100.000 (99.237) +2022-11-14 14:28:07,850 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0755) Prec@1 95.000 (87.744) Prec@5 98.000 (99.205) +2022-11-14 14:28:07,865 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0754) Prec@1 87.000 (87.725) Prec@5 100.000 (99.225) +2022-11-14 14:28:07,881 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0763) Prec@1 81.000 (87.561) Prec@5 99.000 (99.220) +2022-11-14 14:28:07,897 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0764) Prec@1 88.000 (87.571) Prec@5 98.000 (99.190) +2022-11-14 14:28:07,913 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0384 (0.0755) Prec@1 93.000 (87.698) Prec@5 99.000 (99.186) +2022-11-14 14:28:07,929 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0752) Prec@1 91.000 (87.773) Prec@5 98.000 (99.159) +2022-11-14 14:28:07,943 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0751) Prec@1 87.000 (87.756) Prec@5 100.000 (99.178) +2022-11-14 14:28:07,961 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0758) Prec@1 82.000 (87.630) Prec@5 100.000 (99.196) +2022-11-14 14:28:07,981 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0755) Prec@1 90.000 (87.681) Prec@5 100.000 (99.213) +2022-11-14 14:28:07,998 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0760) Prec@1 81.000 (87.542) Prec@5 99.000 (99.208) +2022-11-14 14:28:08,013 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0755) Prec@1 92.000 (87.633) Prec@5 100.000 (99.224) +2022-11-14 14:28:08,027 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0761) Prec@1 83.000 (87.540) Prec@5 100.000 (99.240) +2022-11-14 14:28:08,041 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0759) Prec@1 90.000 (87.588) Prec@5 100.000 (99.255) +2022-11-14 14:28:08,056 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0762) Prec@1 85.000 (87.538) Prec@5 100.000 (99.269) +2022-11-14 14:28:08,071 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0761) Prec@1 89.000 (87.566) Prec@5 99.000 (99.264) +2022-11-14 14:28:08,087 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0760) Prec@1 89.000 (87.593) Prec@5 97.000 (99.222) +2022-11-14 14:28:08,104 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0761) Prec@1 88.000 (87.600) Prec@5 100.000 (99.236) +2022-11-14 14:28:08,119 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0760) Prec@1 90.000 (87.643) Prec@5 100.000 (99.250) +2022-11-14 14:28:08,136 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0760) Prec@1 86.000 (87.614) Prec@5 100.000 (99.263) +2022-11-14 14:28:08,152 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0759) Prec@1 90.000 (87.655) Prec@5 99.000 (99.259) +2022-11-14 14:28:08,167 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0765) Prec@1 83.000 (87.576) Prec@5 100.000 (99.271) +2022-11-14 14:28:08,181 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0767) Prec@1 87.000 (87.567) Prec@5 99.000 (99.267) +2022-11-14 14:28:08,198 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0767) Prec@1 87.000 (87.557) Prec@5 100.000 (99.279) +2022-11-14 14:28:08,212 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0765) Prec@1 90.000 (87.597) Prec@5 100.000 (99.290) +2022-11-14 14:28:08,228 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0764) Prec@1 87.000 (87.587) Prec@5 100.000 (99.302) +2022-11-14 14:28:08,244 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0760) Prec@1 93.000 (87.672) Prec@5 99.000 (99.297) +2022-11-14 14:28:08,259 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0757) Prec@1 89.000 (87.692) Prec@5 100.000 (99.308) +2022-11-14 14:28:08,275 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0758) Prec@1 85.000 (87.652) Prec@5 99.000 (99.303) +2022-11-14 14:28:08,290 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0344 (0.0752) Prec@1 96.000 (87.776) Prec@5 100.000 (99.313) +2022-11-14 14:28:08,306 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0752) Prec@1 87.000 (87.765) Prec@5 97.000 (99.279) +2022-11-14 14:28:08,321 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0749) Prec@1 90.000 (87.797) Prec@5 99.000 (99.275) +2022-11-14 14:28:08,337 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0751) Prec@1 86.000 (87.771) Prec@5 99.000 (99.271) +2022-11-14 14:28:08,352 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0754) Prec@1 85.000 (87.732) Prec@5 99.000 (99.268) +2022-11-14 14:28:08,366 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0753) Prec@1 90.000 (87.764) Prec@5 100.000 (99.278) +2022-11-14 14:28:08,381 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0750) Prec@1 92.000 (87.822) Prec@5 100.000 (99.288) +2022-11-14 14:28:08,397 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0747) Prec@1 92.000 (87.878) Prec@5 100.000 (99.297) +2022-11-14 14:28:08,410 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0748) Prec@1 86.000 (87.853) Prec@5 99.000 (99.293) +2022-11-14 14:28:08,425 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0749) Prec@1 87.000 (87.842) Prec@5 98.000 (99.276) +2022-11-14 14:28:08,442 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0749) Prec@1 87.000 (87.831) Prec@5 98.000 (99.260) +2022-11-14 14:28:08,458 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0748) Prec@1 87.000 (87.821) Prec@5 99.000 (99.256) +2022-11-14 14:28:08,473 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0749) Prec@1 87.000 (87.810) Prec@5 100.000 (99.266) +2022-11-14 14:28:08,487 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0750) Prec@1 86.000 (87.787) Prec@5 100.000 (99.275) +2022-11-14 14:28:08,503 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0752) Prec@1 87.000 (87.778) Prec@5 99.000 (99.272) +2022-11-14 14:28:08,519 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0754) Prec@1 79.000 (87.671) Prec@5 100.000 (99.280) +2022-11-14 14:28:08,533 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0754) Prec@1 88.000 (87.675) Prec@5 100.000 (99.289) +2022-11-14 14:28:08,549 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0753) Prec@1 88.000 (87.679) Prec@5 100.000 (99.298) +2022-11-14 14:28:08,567 Test: [84/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0755) Prec@1 85.000 (87.647) Prec@5 100.000 (99.306) +2022-11-14 14:28:08,581 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0758) Prec@1 82.000 (87.581) Prec@5 99.000 (99.302) +2022-11-14 14:28:08,597 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0758) Prec@1 90.000 (87.609) Prec@5 99.000 (99.299) +2022-11-14 14:28:08,613 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0756) Prec@1 91.000 (87.648) Prec@5 99.000 (99.295) +2022-11-14 14:28:08,629 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0754) Prec@1 91.000 (87.685) Prec@5 99.000 (99.292) +2022-11-14 14:28:08,644 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0755) Prec@1 86.000 (87.667) Prec@5 98.000 (99.278) +2022-11-14 14:28:08,660 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0754) Prec@1 88.000 (87.670) Prec@5 100.000 (99.286) +2022-11-14 14:28:08,678 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0751) Prec@1 93.000 (87.728) Prec@5 99.000 (99.283) +2022-11-14 14:28:08,694 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0750) Prec@1 89.000 (87.742) Prec@5 99.000 (99.280) +2022-11-14 14:28:08,708 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0749) Prec@1 91.000 (87.777) Prec@5 98.000 (99.266) +2022-11-14 14:28:08,724 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0750) Prec@1 84.000 (87.737) Prec@5 100.000 (99.274) +2022-11-14 14:28:08,740 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0748) Prec@1 90.000 (87.760) Prec@5 100.000 (99.281) +2022-11-14 14:28:08,756 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0746) Prec@1 91.000 (87.794) Prec@5 99.000 (99.278) +2022-11-14 14:28:08,770 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0747) Prec@1 85.000 (87.765) Prec@5 99.000 (99.276) +2022-11-14 14:28:08,786 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0749) Prec@1 83.000 (87.717) Prec@5 100.000 (99.283) +2022-11-14 14:28:08,801 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0749) Prec@1 87.000 (87.710) Prec@5 100.000 (99.290) +2022-11-14 14:28:08,859 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:28:09,178 Epoch: [202][0/500] Time 0.024 (0.024) Data 0.233 (0.233) Loss 0.0550 (0.0550) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:09,427 Epoch: [202][10/500] Time 0.025 (0.022) Data 0.002 (0.023) Loss 0.0509 (0.0530) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:09,707 Epoch: [202][20/500] Time 0.024 (0.023) Data 0.002 (0.013) Loss 0.0591 (0.0550) Prec@1 90.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 14:28:09,981 Epoch: [202][30/500] Time 0.027 (0.024) Data 0.002 (0.009) Loss 0.0426 (0.0519) Prec@1 94.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 14:28:10,256 Epoch: [202][40/500] Time 0.026 (0.024) Data 0.002 (0.008) Loss 0.0281 (0.0471) Prec@1 98.000 (92.400) Prec@5 100.000 (99.600) +2022-11-14 14:28:10,779 Epoch: [202][50/500] Time 0.055 (0.028) Data 0.001 (0.006) Loss 0.0397 (0.0459) Prec@1 93.000 (92.500) Prec@5 100.000 (99.667) +2022-11-14 14:28:11,342 Epoch: [202][60/500] Time 0.052 (0.032) Data 0.002 (0.006) Loss 0.0254 (0.0430) Prec@1 97.000 (93.143) Prec@5 99.000 (99.571) +2022-11-14 14:28:11,902 Epoch: [202][70/500] Time 0.051 (0.034) Data 0.002 (0.005) Loss 0.0513 (0.0440) Prec@1 91.000 (92.875) Prec@5 100.000 (99.625) +2022-11-14 14:28:12,463 Epoch: [202][80/500] Time 0.055 (0.036) Data 0.002 (0.005) Loss 0.0474 (0.0444) Prec@1 93.000 (92.889) Prec@5 99.000 (99.556) +2022-11-14 14:28:13,026 Epoch: [202][90/500] Time 0.050 (0.038) Data 0.002 (0.004) Loss 0.0321 (0.0432) Prec@1 92.000 (92.800) Prec@5 100.000 (99.600) +2022-11-14 14:28:13,576 Epoch: [202][100/500] Time 0.055 (0.039) Data 0.002 (0.004) Loss 0.0505 (0.0438) Prec@1 91.000 (92.636) Prec@5 99.000 (99.545) +2022-11-14 14:28:14,146 Epoch: [202][110/500] Time 0.050 (0.040) Data 0.002 (0.004) Loss 0.0525 (0.0446) Prec@1 91.000 (92.500) Prec@5 100.000 (99.583) +2022-11-14 14:28:14,706 Epoch: [202][120/500] Time 0.052 (0.041) Data 0.002 (0.004) Loss 0.0276 (0.0432) Prec@1 95.000 (92.692) Prec@5 100.000 (99.615) +2022-11-14 14:28:15,270 Epoch: [202][130/500] Time 0.055 (0.042) Data 0.002 (0.004) Loss 0.0358 (0.0427) Prec@1 95.000 (92.857) Prec@5 100.000 (99.643) +2022-11-14 14:28:15,834 Epoch: [202][140/500] Time 0.058 (0.042) Data 0.002 (0.004) Loss 0.0385 (0.0424) Prec@1 91.000 (92.733) Prec@5 100.000 (99.667) +2022-11-14 14:28:16,387 Epoch: [202][150/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0535 (0.0431) Prec@1 94.000 (92.812) Prec@5 99.000 (99.625) +2022-11-14 14:28:16,943 Epoch: [202][160/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0429 (0.0431) Prec@1 93.000 (92.824) Prec@5 100.000 (99.647) +2022-11-14 14:28:17,490 Epoch: [202][170/500] Time 0.055 (0.043) Data 0.002 (0.003) Loss 0.0589 (0.0440) Prec@1 90.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:28:18,049 Epoch: [202][180/500] Time 0.059 (0.044) Data 0.002 (0.003) Loss 0.0463 (0.0441) Prec@1 92.000 (92.632) Prec@5 99.000 (99.632) +2022-11-14 14:28:18,596 Epoch: [202][190/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0717 (0.0455) Prec@1 86.000 (92.300) Prec@5 100.000 (99.650) +2022-11-14 14:28:19,151 Epoch: [202][200/500] Time 0.056 (0.044) Data 0.002 (0.003) Loss 0.0540 (0.0459) Prec@1 90.000 (92.190) Prec@5 99.000 (99.619) +2022-11-14 14:28:19,699 Epoch: [202][210/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0426 (0.0457) Prec@1 91.000 (92.136) Prec@5 100.000 (99.636) +2022-11-14 14:28:20,250 Epoch: [202][220/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0278 (0.0450) Prec@1 96.000 (92.304) Prec@5 100.000 (99.652) +2022-11-14 14:28:20,611 Epoch: [202][230/500] Time 0.031 (0.044) Data 0.002 (0.003) Loss 0.0410 (0.0448) Prec@1 94.000 (92.375) Prec@5 100.000 (99.667) +2022-11-14 14:28:20,927 Epoch: [202][240/500] Time 0.029 (0.044) Data 0.002 (0.003) Loss 0.0335 (0.0444) Prec@1 95.000 (92.480) Prec@5 100.000 (99.680) +2022-11-14 14:28:21,242 Epoch: [202][250/500] Time 0.028 (0.043) Data 0.002 (0.003) Loss 0.0190 (0.0434) Prec@1 98.000 (92.692) Prec@5 100.000 (99.692) +2022-11-14 14:28:21,555 Epoch: [202][260/500] Time 0.029 (0.042) Data 0.002 (0.003) Loss 0.0511 (0.0437) Prec@1 89.000 (92.556) Prec@5 100.000 (99.704) +2022-11-14 14:28:21,870 Epoch: [202][270/500] Time 0.030 (0.042) Data 0.002 (0.003) Loss 0.0452 (0.0437) Prec@1 94.000 (92.607) Prec@5 100.000 (99.714) +2022-11-14 14:28:22,183 Epoch: [202][280/500] Time 0.027 (0.041) Data 0.002 (0.003) Loss 0.0490 (0.0439) Prec@1 91.000 (92.552) Prec@5 99.000 (99.690) +2022-11-14 14:28:22,498 Epoch: [202][290/500] Time 0.028 (0.041) Data 0.002 (0.003) Loss 0.0669 (0.0447) Prec@1 89.000 (92.433) Prec@5 99.000 (99.667) +2022-11-14 14:28:22,809 Epoch: [202][300/500] Time 0.028 (0.040) Data 0.002 (0.003) Loss 0.0515 (0.0449) Prec@1 91.000 (92.387) Prec@5 100.000 (99.677) +2022-11-14 14:28:23,126 Epoch: [202][310/500] Time 0.031 (0.040) Data 0.002 (0.003) Loss 0.0330 (0.0445) Prec@1 95.000 (92.469) Prec@5 100.000 (99.688) +2022-11-14 14:28:23,440 Epoch: [202][320/500] Time 0.027 (0.040) Data 0.002 (0.003) Loss 0.0241 (0.0439) Prec@1 97.000 (92.606) Prec@5 100.000 (99.697) +2022-11-14 14:28:23,759 Epoch: [202][330/500] Time 0.028 (0.039) Data 0.002 (0.003) Loss 0.0498 (0.0441) Prec@1 92.000 (92.588) Prec@5 98.000 (99.647) +2022-11-14 14:28:24,078 Epoch: [202][340/500] Time 0.028 (0.039) Data 0.002 (0.003) Loss 0.0476 (0.0442) Prec@1 92.000 (92.571) Prec@5 100.000 (99.657) +2022-11-14 14:28:24,395 Epoch: [202][350/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.0583 (0.0446) Prec@1 89.000 (92.472) Prec@5 100.000 (99.667) +2022-11-14 14:28:24,713 Epoch: [202][360/500] Time 0.026 (0.038) Data 0.002 (0.003) Loss 0.0596 (0.0450) Prec@1 92.000 (92.459) Prec@5 99.000 (99.649) +2022-11-14 14:28:25,034 Epoch: [202][370/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.0563 (0.0453) Prec@1 92.000 (92.447) Prec@5 100.000 (99.658) +2022-11-14 14:28:25,352 Epoch: [202][380/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.0375 (0.0451) Prec@1 94.000 (92.487) Prec@5 100.000 (99.667) +2022-11-14 14:28:25,671 Epoch: [202][390/500] Time 0.028 (0.038) Data 0.001 (0.003) Loss 0.0327 (0.0448) Prec@1 96.000 (92.575) Prec@5 100.000 (99.675) +2022-11-14 14:28:25,997 Epoch: [202][400/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0486 (0.0449) Prec@1 93.000 (92.585) Prec@5 100.000 (99.683) +2022-11-14 14:28:26,310 Epoch: [202][410/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0330 (0.0446) Prec@1 96.000 (92.667) Prec@5 100.000 (99.690) +2022-11-14 14:28:26,628 Epoch: [202][420/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0288 (0.0442) Prec@1 96.000 (92.744) Prec@5 100.000 (99.698) +2022-11-14 14:28:26,957 Epoch: [202][430/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0288 (0.0439) Prec@1 96.000 (92.818) Prec@5 99.000 (99.682) +2022-11-14 14:28:27,283 Epoch: [202][440/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0168 (0.0433) Prec@1 98.000 (92.933) Prec@5 100.000 (99.689) +2022-11-14 14:28:27,598 Epoch: [202][450/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0248 (0.0428) Prec@1 95.000 (92.978) Prec@5 99.000 (99.674) +2022-11-14 14:28:27,917 Epoch: [202][460/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0284 (0.0425) Prec@1 94.000 (93.000) Prec@5 100.000 (99.681) +2022-11-14 14:28:28,235 Epoch: [202][470/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0540 (0.0428) Prec@1 90.000 (92.938) Prec@5 100.000 (99.688) +2022-11-14 14:28:28,776 Epoch: [202][480/500] Time 0.054 (0.036) Data 0.002 (0.002) Loss 0.0314 (0.0425) Prec@1 94.000 (92.959) Prec@5 100.000 (99.694) +2022-11-14 14:28:29,362 Epoch: [202][490/500] Time 0.054 (0.037) Data 0.002 (0.002) Loss 0.0455 (0.0426) Prec@1 95.000 (93.000) Prec@5 100.000 (99.700) +2022-11-14 14:28:29,881 Epoch: [202][499/500] Time 0.053 (0.037) Data 0.002 (0.002) Loss 0.0208 (0.0422) Prec@1 97.000 (93.078) Prec@5 100.000 (99.706) +2022-11-14 14:28:30,170 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0563 (0.0563) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:30,181 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0672) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:30,189 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0670) Prec@1 91.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 14:28:30,202 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0697) Prec@1 88.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 14:28:30,211 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0718) Prec@1 86.000 (88.600) Prec@5 100.000 (99.800) +2022-11-14 14:28:30,222 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0432 (0.0670) Prec@1 92.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 14:28:30,233 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0663) Prec@1 91.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 14:28:30,248 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0689) Prec@1 85.000 (88.875) Prec@5 99.000 (99.750) +2022-11-14 14:28:30,260 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0715) Prec@1 87.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 14:28:30,274 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0711) Prec@1 88.000 (88.600) Prec@5 98.000 (99.500) +2022-11-14 14:28:30,290 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0699) Prec@1 93.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 14:28:30,307 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0713) Prec@1 86.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 14:28:30,323 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0696) Prec@1 94.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 14:28:30,340 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0693) Prec@1 89.000 (89.143) Prec@5 99.000 (99.500) +2022-11-14 14:28:30,358 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0693) Prec@1 89.000 (89.133) Prec@5 100.000 (99.533) +2022-11-14 14:28:30,376 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0695) Prec@1 88.000 (89.062) Prec@5 99.000 (99.500) +2022-11-14 14:28:30,393 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0690) Prec@1 92.000 (89.235) Prec@5 98.000 (99.412) +2022-11-14 14:28:30,411 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0711) Prec@1 83.000 (88.889) Prec@5 100.000 (99.444) +2022-11-14 14:28:30,428 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0713) Prec@1 84.000 (88.632) Prec@5 99.000 (99.421) +2022-11-14 14:28:30,446 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0720) Prec@1 87.000 (88.550) Prec@5 98.000 (99.350) +2022-11-14 14:28:30,463 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0729) Prec@1 87.000 (88.476) Prec@5 99.000 (99.333) +2022-11-14 14:28:30,480 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0732) Prec@1 85.000 (88.318) Prec@5 100.000 (99.364) +2022-11-14 14:28:30,499 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0736) Prec@1 90.000 (88.391) Prec@5 98.000 (99.304) +2022-11-14 14:28:30,517 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0732) Prec@1 88.000 (88.375) Prec@5 99.000 (99.292) +2022-11-14 14:28:30,536 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0738) Prec@1 88.000 (88.360) Prec@5 99.000 (99.280) +2022-11-14 14:28:30,554 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0744) Prec@1 84.000 (88.192) Prec@5 99.000 (99.269) +2022-11-14 14:28:30,573 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0733) Prec@1 93.000 (88.370) Prec@5 100.000 (99.296) +2022-11-14 14:28:30,593 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0726) Prec@1 92.000 (88.500) Prec@5 100.000 (99.321) +2022-11-14 14:28:30,610 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0724) Prec@1 88.000 (88.483) Prec@5 100.000 (99.345) +2022-11-14 14:28:30,628 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0719) Prec@1 91.000 (88.567) Prec@5 100.000 (99.367) +2022-11-14 14:28:30,646 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0716) Prec@1 90.000 (88.613) Prec@5 100.000 (99.387) +2022-11-14 14:28:30,663 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0717) Prec@1 86.000 (88.531) Prec@5 100.000 (99.406) +2022-11-14 14:28:30,680 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0718) Prec@1 84.000 (88.394) Prec@5 99.000 (99.394) +2022-11-14 14:28:30,697 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0721) Prec@1 87.000 (88.353) Prec@5 98.000 (99.353) +2022-11-14 14:28:30,717 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0722) Prec@1 89.000 (88.371) Prec@5 98.000 (99.314) +2022-11-14 14:28:30,738 Test: [35/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0719) Prec@1 93.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 14:28:30,758 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0725) Prec@1 86.000 (88.432) Prec@5 98.000 (99.297) +2022-11-14 14:28:30,778 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0730) Prec@1 85.000 (88.342) Prec@5 99.000 (99.289) +2022-11-14 14:28:30,798 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0727) Prec@1 91.000 (88.410) Prec@5 98.000 (99.256) +2022-11-14 14:28:30,818 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0727) Prec@1 88.000 (88.400) Prec@5 99.000 (99.250) +2022-11-14 14:28:30,836 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0733) Prec@1 84.000 (88.293) Prec@5 97.000 (99.195) +2022-11-14 14:28:30,856 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0735) Prec@1 89.000 (88.310) Prec@5 99.000 (99.190) +2022-11-14 14:28:30,877 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0296 (0.0725) Prec@1 95.000 (88.465) Prec@5 99.000 (99.186) +2022-11-14 14:28:30,894 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0725) Prec@1 88.000 (88.455) Prec@5 98.000 (99.159) +2022-11-14 14:28:30,913 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0725) Prec@1 88.000 (88.444) Prec@5 98.000 (99.133) +2022-11-14 14:28:30,931 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0728) Prec@1 84.000 (88.348) Prec@5 100.000 (99.152) +2022-11-14 14:28:30,947 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0726) Prec@1 87.000 (88.319) Prec@5 100.000 (99.170) +2022-11-14 14:28:30,967 Test: [47/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0733) Prec@1 86.000 (88.271) Prec@5 98.000 (99.146) +2022-11-14 14:28:30,987 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0729) Prec@1 87.000 (88.245) Prec@5 100.000 (99.163) +2022-11-14 14:28:31,005 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0734) Prec@1 85.000 (88.180) Prec@5 99.000 (99.160) +2022-11-14 14:28:31,023 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0735) Prec@1 83.000 (88.078) Prec@5 100.000 (99.176) +2022-11-14 14:28:31,044 Test: [51/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0739) Prec@1 82.000 (87.962) Prec@5 100.000 (99.192) +2022-11-14 14:28:31,062 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0738) Prec@1 89.000 (87.981) Prec@5 99.000 (99.189) +2022-11-14 14:28:31,079 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0740) Prec@1 87.000 (87.963) Prec@5 98.000 (99.167) +2022-11-14 14:28:31,098 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0741) Prec@1 85.000 (87.909) Prec@5 100.000 (99.182) +2022-11-14 14:28:31,119 Test: [55/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0740) Prec@1 90.000 (87.946) Prec@5 99.000 (99.179) +2022-11-14 14:28:31,139 Test: 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Loss 0.0791 (0.0746) Prec@1 85.000 (87.698) Prec@5 100.000 (99.206) +2022-11-14 14:28:31,268 Test: [63/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0743) Prec@1 91.000 (87.750) Prec@5 100.000 (99.219) +2022-11-14 14:28:31,286 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0747) Prec@1 85.000 (87.708) Prec@5 100.000 (99.231) +2022-11-14 14:28:31,304 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0748) Prec@1 86.000 (87.682) Prec@5 99.000 (99.227) +2022-11-14 14:28:31,322 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0492 (0.0744) Prec@1 92.000 (87.746) Prec@5 100.000 (99.239) +2022-11-14 14:28:31,340 Test: [67/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0744) Prec@1 88.000 (87.750) Prec@5 98.000 (99.221) +2022-11-14 14:28:31,359 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0743) Prec@1 92.000 (87.812) Prec@5 98.000 (99.203) +2022-11-14 14:28:31,376 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0744) Prec@1 87.000 (87.800) Prec@5 100.000 (99.214) +2022-11-14 14:28:31,394 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0748) Prec@1 82.000 (87.718) Prec@5 100.000 (99.225) +2022-11-14 14:28:31,413 Test: [71/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0748) Prec@1 85.000 (87.681) Prec@5 100.000 (99.236) +2022-11-14 14:28:31,432 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0747) Prec@1 89.000 (87.699) Prec@5 99.000 (99.233) +2022-11-14 14:28:31,449 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0744) Prec@1 91.000 (87.743) Prec@5 100.000 (99.243) +2022-11-14 14:28:31,469 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0745) Prec@1 87.000 (87.733) Prec@5 100.000 (99.253) +2022-11-14 14:28:31,486 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0743) Prec@1 90.000 (87.763) Prec@5 100.000 (99.263) +2022-11-14 14:28:31,506 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0741) Prec@1 89.000 (87.779) Prec@5 99.000 (99.260) +2022-11-14 14:28:31,524 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0744) Prec@1 83.000 (87.718) Prec@5 97.000 (99.231) +2022-11-14 14:28:31,544 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0745) Prec@1 86.000 (87.696) Prec@5 100.000 (99.241) +2022-11-14 14:28:31,563 Test: [79/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0744) Prec@1 88.000 (87.700) Prec@5 100.000 (99.250) +2022-11-14 14:28:31,582 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 90.000 (87.728) Prec@5 98.000 (99.235) +2022-11-14 14:28:31,600 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0746) Prec@1 82.000 (87.659) Prec@5 100.000 (99.244) +2022-11-14 14:28:31,617 Test: [82/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0746) Prec@1 87.000 (87.651) Prec@5 100.000 (99.253) +2022-11-14 14:28:31,636 Test: [83/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0743) Prec@1 92.000 (87.702) Prec@5 99.000 (99.250) +2022-11-14 14:28:31,658 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0747) Prec@1 84.000 (87.659) Prec@5 99.000 (99.247) +2022-11-14 14:28:31,678 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0751) Prec@1 83.000 (87.605) Prec@5 99.000 (99.244) +2022-11-14 14:28:31,696 Test: [86/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0751) Prec@1 87.000 (87.598) Prec@5 99.000 (99.241) +2022-11-14 14:28:31,715 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0749) Prec@1 92.000 (87.648) Prec@5 100.000 (99.250) +2022-11-14 14:28:31,731 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0747) Prec@1 87.000 (87.640) Prec@5 100.000 (99.258) +2022-11-14 14:28:31,748 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0747) Prec@1 91.000 (87.678) Prec@5 99.000 (99.256) +2022-11-14 14:28:31,768 Test: [90/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0745) Prec@1 92.000 (87.725) Prec@5 100.000 (99.264) +2022-11-14 14:28:31,785 Test: [91/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0417 (0.0741) Prec@1 93.000 (87.783) Prec@5 100.000 (99.272) +2022-11-14 14:28:31,801 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0743) Prec@1 86.000 (87.763) Prec@5 100.000 (99.280) +2022-11-14 14:28:31,818 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0742) Prec@1 89.000 (87.777) Prec@5 99.000 (99.277) +2022-11-14 14:28:31,837 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0743) Prec@1 86.000 (87.758) Prec@5 98.000 (99.263) +2022-11-14 14:28:31,858 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0744) Prec@1 86.000 (87.740) Prec@5 100.000 (99.271) +2022-11-14 14:28:31,874 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0496 (0.0741) Prec@1 91.000 (87.773) Prec@5 99.000 (99.268) +2022-11-14 14:28:31,892 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0741) Prec@1 89.000 (87.786) Prec@5 100.000 (99.276) +2022-11-14 14:28:31,911 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0742) Prec@1 87.000 (87.778) Prec@5 100.000 (99.283) +2022-11-14 14:28:31,928 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0742) Prec@1 87.000 (87.770) Prec@5 100.000 (99.290) +2022-11-14 14:28:31,986 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:28:32,298 Epoch: [203][0/500] Time 0.029 (0.029) Data 0.227 (0.227) Loss 0.0177 (0.0177) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:32,565 Epoch: [203][10/500] Time 0.027 (0.024) Data 0.002 (0.022) Loss 0.0470 (0.0323) Prec@1 92.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:28:32,867 Epoch: [203][20/500] Time 0.028 (0.025) Data 0.002 (0.013) Loss 0.0418 (0.0355) Prec@1 92.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 14:28:33,173 Epoch: [203][30/500] Time 0.026 (0.026) Data 0.002 (0.009) Loss 0.0310 (0.0344) Prec@1 96.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 14:28:33,476 Epoch: [203][40/500] Time 0.030 (0.026) Data 0.002 (0.007) Loss 0.0285 (0.0332) Prec@1 96.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 14:28:33,777 Epoch: [203][50/500] Time 0.027 (0.026) Data 0.002 (0.006) Loss 0.0398 (0.0343) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:28:34,080 Epoch: [203][60/500] Time 0.027 (0.026) Data 0.002 (0.006) Loss 0.0184 (0.0320) Prec@1 97.000 (94.857) Prec@5 100.000 (100.000) +2022-11-14 14:28:34,378 Epoch: [203][70/500] Time 0.029 (0.026) Data 0.002 (0.005) Loss 0.0506 (0.0344) Prec@1 93.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 14:28:34,683 Epoch: [203][80/500] Time 0.029 (0.026) Data 0.002 (0.005) Loss 0.0389 (0.0349) Prec@1 94.000 (94.556) Prec@5 100.000 (100.000) +2022-11-14 14:28:34,997 Epoch: [203][90/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0303 (0.0344) Prec@1 95.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 14:28:35,296 Epoch: [203][100/500] Time 0.031 (0.027) Data 0.001 (0.004) Loss 0.0270 (0.0337) Prec@1 96.000 (94.727) Prec@5 100.000 (100.000) +2022-11-14 14:28:35,682 Epoch: [203][110/500] Time 0.048 (0.027) Data 0.002 (0.004) Loss 0.0287 (0.0333) Prec@1 96.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 14:28:36,214 Epoch: [203][120/500] Time 0.049 (0.029) Data 0.002 (0.004) Loss 0.0390 (0.0338) Prec@1 94.000 (94.769) Prec@5 99.000 (99.923) +2022-11-14 14:28:36,750 Epoch: [203][130/500] Time 0.054 (0.030) Data 0.002 (0.004) Loss 0.0393 (0.0342) Prec@1 94.000 (94.714) Prec@5 100.000 (99.929) +2022-11-14 14:28:37,280 Epoch: [203][140/500] Time 0.054 (0.031) Data 0.002 (0.003) Loss 0.0415 (0.0346) Prec@1 94.000 (94.667) Prec@5 100.000 (99.933) +2022-11-14 14:28:37,808 Epoch: [203][150/500] Time 0.046 (0.032) Data 0.002 (0.003) Loss 0.0567 (0.0360) Prec@1 89.000 (94.312) Prec@5 100.000 (99.938) +2022-11-14 14:28:38,334 Epoch: [203][160/500] Time 0.052 (0.033) Data 0.002 (0.003) Loss 0.0370 (0.0361) Prec@1 92.000 (94.176) Prec@5 100.000 (99.941) +2022-11-14 14:28:38,870 Epoch: [203][170/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0130 (0.0348) Prec@1 98.000 (94.389) Prec@5 100.000 (99.944) +2022-11-14 14:28:39,402 Epoch: [203][180/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0500 (0.0356) Prec@1 90.000 (94.158) Prec@5 100.000 (99.947) +2022-11-14 14:28:39,917 Epoch: [203][190/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0423 (0.0359) Prec@1 94.000 (94.150) Prec@5 99.000 (99.900) +2022-11-14 14:28:40,434 Epoch: [203][200/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0348 (0.0359) Prec@1 94.000 (94.143) Prec@5 100.000 (99.905) +2022-11-14 14:28:40,946 Epoch: [203][210/500] Time 0.049 (0.036) Data 0.002 (0.003) Loss 0.0431 (0.0362) Prec@1 93.000 (94.091) Prec@5 100.000 (99.909) +2022-11-14 14:28:41,456 Epoch: [203][220/500] Time 0.045 (0.037) Data 0.003 (0.003) Loss 0.0544 (0.0370) Prec@1 91.000 (93.957) Prec@5 100.000 (99.913) +2022-11-14 14:28:41,969 Epoch: [203][230/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0380 (0.0370) Prec@1 93.000 (93.917) Prec@5 100.000 (99.917) +2022-11-14 14:28:42,491 Epoch: [203][240/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0426 (0.0373) Prec@1 92.000 (93.840) Prec@5 100.000 (99.920) +2022-11-14 14:28:43,002 Epoch: [203][250/500] Time 0.053 (0.038) Data 0.002 (0.003) Loss 0.0329 (0.0371) Prec@1 96.000 (93.923) Prec@5 100.000 (99.923) +2022-11-14 14:28:43,514 Epoch: [203][260/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0333 (0.0370) Prec@1 94.000 (93.926) Prec@5 99.000 (99.889) +2022-11-14 14:28:44,037 Epoch: [203][270/500] Time 0.057 (0.039) Data 0.002 (0.003) Loss 0.0285 (0.0367) Prec@1 95.000 (93.964) Prec@5 100.000 (99.893) +2022-11-14 14:28:44,552 Epoch: [203][280/500] Time 0.047 (0.039) Data 0.002 (0.003) Loss 0.0372 (0.0367) Prec@1 94.000 (93.966) Prec@5 100.000 (99.897) +2022-11-14 14:28:45,083 Epoch: [203][290/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0384 (0.0367) Prec@1 93.000 (93.933) Prec@5 100.000 (99.900) +2022-11-14 14:28:45,592 Epoch: [203][300/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0515 (0.0372) Prec@1 89.000 (93.774) Prec@5 100.000 (99.903) +2022-11-14 14:28:46,091 Epoch: [203][310/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0362 (0.0372) Prec@1 94.000 (93.781) Prec@5 100.000 (99.906) +2022-11-14 14:28:46,602 Epoch: [203][320/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0403 (0.0373) Prec@1 93.000 (93.758) Prec@5 99.000 (99.879) +2022-11-14 14:28:47,115 Epoch: [203][330/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0624 (0.0380) Prec@1 91.000 (93.676) Prec@5 98.000 (99.824) +2022-11-14 14:28:47,647 Epoch: [203][340/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0496 (0.0383) Prec@1 91.000 (93.600) Prec@5 100.000 (99.829) +2022-11-14 14:28:48,166 Epoch: [203][350/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0712 (0.0393) Prec@1 87.000 (93.417) Prec@5 99.000 (99.806) +2022-11-14 14:28:48,673 Epoch: [203][360/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0384 (0.0392) Prec@1 94.000 (93.432) Prec@5 100.000 (99.811) +2022-11-14 14:28:49,185 Epoch: [203][370/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0491 (0.0395) Prec@1 92.000 (93.395) Prec@5 100.000 (99.816) +2022-11-14 14:28:49,692 Epoch: [203][380/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0490 (0.0397) Prec@1 91.000 (93.333) Prec@5 100.000 (99.821) +2022-11-14 14:28:50,200 Epoch: [203][390/500] Time 0.046 (0.041) Data 0.002 (0.002) Loss 0.0328 (0.0396) Prec@1 94.000 (93.350) Prec@5 100.000 (99.825) +2022-11-14 14:28:50,702 Epoch: [203][400/500] Time 0.047 (0.041) Data 0.002 (0.002) Loss 0.0296 (0.0393) Prec@1 96.000 (93.415) Prec@5 99.000 (99.805) +2022-11-14 14:28:51,212 Epoch: [203][410/500] Time 0.050 (0.041) Data 0.002 (0.002) Loss 0.0408 (0.0394) Prec@1 93.000 (93.405) Prec@5 100.000 (99.810) +2022-11-14 14:28:51,723 Epoch: [203][420/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0647 (0.0399) Prec@1 89.000 (93.302) Prec@5 100.000 (99.814) +2022-11-14 14:28:52,242 Epoch: [203][430/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0439 (0.0400) Prec@1 95.000 (93.341) Prec@5 100.000 (99.818) +2022-11-14 14:28:52,759 Epoch: [203][440/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0340 (0.0399) Prec@1 94.000 (93.356) Prec@5 100.000 (99.822) +2022-11-14 14:28:53,282 Epoch: [203][450/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0442 (0.0400) Prec@1 93.000 (93.348) Prec@5 99.000 (99.804) +2022-11-14 14:28:53,623 Epoch: [203][460/500] Time 0.026 (0.041) Data 0.002 (0.002) Loss 0.0206 (0.0396) Prec@1 97.000 (93.426) Prec@5 100.000 (99.809) +2022-11-14 14:28:53,917 Epoch: [203][470/500] Time 0.027 (0.041) Data 0.002 (0.002) Loss 0.0464 (0.0397) Prec@1 93.000 (93.417) Prec@5 100.000 (99.812) +2022-11-14 14:28:54,228 Epoch: [203][480/500] Time 0.025 (0.041) Data 0.002 (0.002) Loss 0.0492 (0.0399) Prec@1 92.000 (93.388) Prec@5 100.000 (99.816) +2022-11-14 14:28:54,578 Epoch: [203][490/500] Time 0.034 (0.040) Data 0.002 (0.002) Loss 0.0411 (0.0399) Prec@1 95.000 (93.420) Prec@5 100.000 (99.820) +2022-11-14 14:28:54,915 Epoch: [203][499/500] Time 0.034 (0.040) Data 0.002 (0.002) Loss 0.0375 (0.0399) Prec@1 94.000 (93.431) Prec@5 100.000 (99.824) +2022-11-14 14:28:55,237 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0669 (0.0669) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:55,250 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0859 (0.0764) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:55,259 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0972 (0.0834) Prec@1 83.000 (86.333) Prec@5 100.000 (100.000) +2022-11-14 14:28:55,278 Test: [3/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1017 (0.0879) Prec@1 84.000 (85.750) Prec@5 98.000 (99.500) +2022-11-14 14:28:55,290 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0746 (0.0853) Prec@1 86.000 (85.800) Prec@5 99.000 (99.400) +2022-11-14 14:28:55,302 Test: [5/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0505 (0.0795) Prec@1 90.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 14:28:55,314 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0562 (0.0762) Prec@1 91.000 (87.143) Prec@5 99.000 (99.429) +2022-11-14 14:28:55,326 Test: [7/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0753 (0.0761) Prec@1 87.000 (87.125) Prec@5 99.000 (99.375) +2022-11-14 14:28:55,335 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.0768) Prec@1 89.000 (87.333) Prec@5 100.000 (99.444) +2022-11-14 14:28:55,348 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0754) Prec@1 88.000 (87.400) Prec@5 99.000 (99.400) +2022-11-14 14:28:55,362 Test: [10/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0621 (0.0742) Prec@1 90.000 (87.636) Prec@5 99.000 (99.364) +2022-11-14 14:28:55,373 Test: [11/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0743 (0.0742) Prec@1 89.000 (87.750) Prec@5 99.000 (99.333) +2022-11-14 14:28:55,383 Test: [12/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0675 (0.0737) Prec@1 89.000 (87.846) Prec@5 100.000 (99.385) +2022-11-14 14:28:55,396 Test: [13/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0670 (0.0732) Prec@1 89.000 (87.929) Prec@5 99.000 (99.357) +2022-11-14 14:28:55,408 Test: [14/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0952 (0.0747) Prec@1 84.000 (87.667) Prec@5 100.000 (99.400) +2022-11-14 14:28:55,418 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0743) Prec@1 90.000 (87.812) Prec@5 100.000 (99.438) +2022-11-14 14:28:55,427 Test: [16/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0724 (0.0742) Prec@1 88.000 (87.824) Prec@5 98.000 (99.353) +2022-11-14 14:28:55,438 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1034 (0.0758) Prec@1 85.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 14:28:55,448 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0655 (0.0753) Prec@1 90.000 (87.789) Prec@5 99.000 (99.316) +2022-11-14 14:28:55,457 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0758) Prec@1 86.000 (87.700) Prec@5 99.000 (99.300) +2022-11-14 14:28:55,467 Test: [20/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0770) Prec@1 83.000 (87.476) Prec@5 100.000 (99.333) +2022-11-14 14:28:55,479 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0854 (0.0773) Prec@1 85.000 (87.364) Prec@5 98.000 (99.273) +2022-11-14 14:28:55,490 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0781) Prec@1 84.000 (87.217) Prec@5 98.000 (99.217) +2022-11-14 14:28:55,501 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0827 (0.0783) Prec@1 87.000 (87.208) Prec@5 100.000 (99.250) +2022-11-14 14:28:55,515 Test: [24/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0916 (0.0789) Prec@1 86.000 (87.160) Prec@5 99.000 (99.240) +2022-11-14 14:28:55,527 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0791) Prec@1 86.000 (87.115) Prec@5 99.000 (99.231) +2022-11-14 14:28:55,536 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0783) Prec@1 90.000 (87.222) Prec@5 100.000 (99.259) +2022-11-14 14:28:55,546 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0640 (0.0777) Prec@1 90.000 (87.321) Prec@5 99.000 (99.250) +2022-11-14 14:28:55,558 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0778) Prec@1 88.000 (87.345) Prec@5 99.000 (99.241) +2022-11-14 14:28:55,569 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0780) Prec@1 86.000 (87.300) Prec@5 98.000 (99.200) +2022-11-14 14:28:55,578 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0693 (0.0777) Prec@1 87.000 (87.290) Prec@5 99.000 (99.194) +2022-11-14 14:28:55,588 Test: [31/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0776) Prec@1 87.000 (87.281) Prec@5 100.000 (99.219) +2022-11-14 14:28:55,600 Test: [32/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0771) Prec@1 89.000 (87.333) Prec@5 100.000 (99.242) +2022-11-14 14:28:55,611 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1044 (0.0779) Prec@1 80.000 (87.118) Prec@5 99.000 (99.235) +2022-11-14 14:28:55,620 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.0783) Prec@1 88.000 (87.143) Prec@5 97.000 (99.171) +2022-11-14 14:28:55,632 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0782) Prec@1 89.000 (87.194) Prec@5 100.000 (99.194) +2022-11-14 14:28:55,647 Test: [36/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0894 (0.0785) Prec@1 85.000 (87.135) Prec@5 99.000 (99.189) +2022-11-14 14:28:55,659 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1104 (0.0793) Prec@1 81.000 (86.974) Prec@5 97.000 (99.132) +2022-11-14 14:28:55,670 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0549 (0.0787) Prec@1 92.000 (87.103) Prec@5 100.000 (99.154) +2022-11-14 14:28:55,681 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0655 (0.0783) Prec@1 89.000 (87.150) Prec@5 99.000 (99.150) +2022-11-14 14:28:55,694 Test: [40/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0918 (0.0787) Prec@1 86.000 (87.122) Prec@5 99.000 (99.146) +2022-11-14 14:28:55,708 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0786) Prec@1 87.000 (87.119) Prec@5 98.000 (99.119) +2022-11-14 14:28:55,721 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0449 (0.0778) Prec@1 92.000 (87.233) Prec@5 100.000 (99.140) +2022-11-14 14:28:55,733 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0597 (0.0774) Prec@1 91.000 (87.318) Prec@5 99.000 (99.136) +2022-11-14 14:28:55,745 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0774) Prec@1 87.000 (87.311) Prec@5 100.000 (99.156) +2022-11-14 14:28:55,759 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0722 (0.0773) Prec@1 87.000 (87.304) Prec@5 99.000 (99.152) +2022-11-14 14:28:55,770 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0658 (0.0770) Prec@1 90.000 (87.362) Prec@5 100.000 (99.170) +2022-11-14 14:28:55,780 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1147 (0.0778) Prec@1 81.000 (87.229) Prec@5 99.000 (99.167) +2022-11-14 14:28:55,794 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0473 (0.0772) Prec@1 92.000 (87.327) Prec@5 100.000 (99.184) +2022-11-14 14:28:55,807 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0995 (0.0776) Prec@1 86.000 (87.300) Prec@5 100.000 (99.200) +2022-11-14 14:28:55,819 Test: [50/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0772) Prec@1 89.000 (87.333) Prec@5 100.000 (99.216) +2022-11-14 14:28:55,833 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0938 (0.0775) Prec@1 84.000 (87.269) Prec@5 99.000 (99.212) +2022-11-14 14:28:55,846 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0775) Prec@1 85.000 (87.226) Prec@5 99.000 (99.208) +2022-11-14 14:28:55,858 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0916 (0.0778) Prec@1 85.000 (87.185) Prec@5 99.000 (99.204) +2022-11-14 14:28:55,872 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0779) Prec@1 87.000 (87.182) Prec@5 100.000 (99.218) +2022-11-14 14:28:55,885 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0519 (0.0774) Prec@1 92.000 (87.268) Prec@5 99.000 (99.214) +2022-11-14 14:28:55,898 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0772) Prec@1 88.000 (87.281) Prec@5 100.000 (99.228) +2022-11-14 14:28:55,911 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0771) Prec@1 89.000 (87.310) Prec@5 99.000 (99.224) +2022-11-14 14:28:55,923 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.0773) Prec@1 87.000 (87.305) Prec@5 100.000 (99.237) +2022-11-14 14:28:55,936 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0773) Prec@1 87.000 (87.300) Prec@5 100.000 (99.250) +2022-11-14 14:28:55,948 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0770) Prec@1 88.000 (87.311) Prec@5 100.000 (99.262) +2022-11-14 14:28:55,962 Test: [61/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0768) Prec@1 88.000 (87.323) Prec@5 100.000 (99.274) +2022-11-14 14:28:55,979 Test: [62/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0767) Prec@1 87.000 (87.317) Prec@5 100.000 (99.286) +2022-11-14 14:28:55,991 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0301 (0.0759) Prec@1 94.000 (87.422) Prec@5 100.000 (99.297) +2022-11-14 14:28:56,003 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0759) Prec@1 88.000 (87.431) Prec@5 100.000 (99.308) +2022-11-14 14:28:56,018 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0759) Prec@1 87.000 (87.424) Prec@5 99.000 (99.303) +2022-11-14 14:28:56,033 Test: [66/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0394 (0.0754) Prec@1 94.000 (87.522) Prec@5 100.000 (99.313) +2022-11-14 14:28:56,046 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0753) Prec@1 90.000 (87.559) Prec@5 99.000 (99.309) +2022-11-14 14:28:56,059 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0750) Prec@1 93.000 (87.638) Prec@5 100.000 (99.319) +2022-11-14 14:28:56,072 Test: [69/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0752) Prec@1 87.000 (87.629) Prec@5 99.000 (99.314) +2022-11-14 14:28:56,086 Test: [70/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0910 (0.0754) Prec@1 85.000 (87.592) Prec@5 100.000 (99.324) +2022-11-14 14:28:56,101 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0754) Prec@1 87.000 (87.583) Prec@5 99.000 (99.319) +2022-11-14 14:28:56,115 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0753) Prec@1 88.000 (87.589) Prec@5 99.000 (99.315) +2022-11-14 14:28:56,129 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0371 (0.0748) Prec@1 96.000 (87.703) Prec@5 100.000 (99.324) +2022-11-14 14:28:56,144 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0899 (0.0750) Prec@1 85.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 14:28:56,157 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0748) Prec@1 89.000 (87.684) Prec@5 100.000 (99.342) +2022-11-14 14:28:56,170 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0747) Prec@1 89.000 (87.701) Prec@5 97.000 (99.312) +2022-11-14 14:28:56,183 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1078 (0.0751) Prec@1 81.000 (87.615) Prec@5 99.000 (99.308) +2022-11-14 14:28:56,198 Test: [78/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0752) Prec@1 86.000 (87.595) Prec@5 100.000 (99.316) +2022-11-14 14:28:56,211 Test: [79/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0751) Prec@1 91.000 (87.638) Prec@5 100.000 (99.325) +2022-11-14 14:28:56,222 Test: [80/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0751) Prec@1 87.000 (87.630) Prec@5 99.000 (99.321) +2022-11-14 14:28:56,232 Test: [81/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1110 (0.0755) Prec@1 82.000 (87.561) Prec@5 100.000 (99.329) +2022-11-14 14:28:56,245 Test: [82/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0756) Prec@1 85.000 (87.530) Prec@5 100.000 (99.337) +2022-11-14 14:28:56,257 Test: [83/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0755) Prec@1 89.000 (87.548) Prec@5 100.000 (99.345) +2022-11-14 14:28:56,266 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1065 (0.0759) Prec@1 80.000 (87.459) Prec@5 99.000 (99.341) +2022-11-14 14:28:56,276 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1073 (0.0762) Prec@1 82.000 (87.395) Prec@5 99.000 (99.337) +2022-11-14 14:28:56,290 Test: [86/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0764) Prec@1 84.000 (87.356) Prec@5 100.000 (99.345) +2022-11-14 14:28:56,302 Test: [87/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0763) Prec@1 90.000 (87.386) Prec@5 99.000 (99.341) +2022-11-14 14:28:56,312 Test: [88/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0761) Prec@1 90.000 (87.416) Prec@5 99.000 (99.337) +2022-11-14 14:28:56,321 Test: [89/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0761) Prec@1 90.000 (87.444) Prec@5 99.000 (99.333) +2022-11-14 14:28:56,334 Test: [90/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0610 (0.0760) Prec@1 89.000 (87.462) Prec@5 100.000 (99.341) +2022-11-14 14:28:56,345 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0757) Prec@1 94.000 (87.533) Prec@5 99.000 (99.337) +2022-11-14 14:28:56,354 Test: [92/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0757) Prec@1 87.000 (87.527) Prec@5 100.000 (99.344) +2022-11-14 14:28:56,365 Test: [93/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0600 (0.0755) Prec@1 91.000 (87.564) Prec@5 99.000 (99.340) +2022-11-14 14:28:56,376 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0800 (0.0756) Prec@1 87.000 (87.558) Prec@5 100.000 (99.347) +2022-11-14 14:28:56,386 Test: [95/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0754) Prec@1 92.000 (87.604) Prec@5 100.000 (99.354) +2022-11-14 14:28:56,396 Test: [96/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0579 (0.0752) Prec@1 92.000 (87.649) Prec@5 99.000 (99.351) +2022-11-14 14:28:56,407 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0961 (0.0755) Prec@1 85.000 (87.622) Prec@5 99.000 (99.347) +2022-11-14 14:28:56,417 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0756) Prec@1 85.000 (87.596) Prec@5 100.000 (99.354) +2022-11-14 14:28:56,426 Test: [99/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0756) Prec@1 88.000 (87.600) Prec@5 100.000 (99.360) +2022-11-14 14:28:56,485 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:28:56,804 Epoch: [204][0/500] Time 0.027 (0.027) Data 0.228 (0.228) Loss 0.0390 (0.0390) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:28:57,103 Epoch: [204][10/500] Time 0.026 (0.026) Data 0.002 (0.023) Loss 0.0348 (0.0369) Prec@1 98.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 14:28:57,338 Epoch: [204][20/500] Time 0.019 (0.024) Data 0.002 (0.013) Loss 0.0372 (0.0370) Prec@1 94.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 14:28:57,657 Epoch: [204][30/500] Time 0.033 (0.025) Data 0.002 (0.009) Loss 0.0439 (0.0387) Prec@1 94.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 14:28:58,033 Epoch: [204][40/500] Time 0.039 (0.027) Data 0.002 (0.008) Loss 0.0403 (0.0391) Prec@1 94.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 14:28:58,432 Epoch: [204][50/500] Time 0.039 (0.029) Data 0.002 (0.006) Loss 0.0531 (0.0414) Prec@1 92.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 14:28:58,797 Epoch: [204][60/500] Time 0.047 (0.029) Data 0.002 (0.006) Loss 0.0282 (0.0395) Prec@1 98.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 14:28:59,237 Epoch: [204][70/500] Time 0.037 (0.031) Data 0.003 (0.005) Loss 0.0319 (0.0386) Prec@1 96.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 14:28:59,701 Epoch: [204][80/500] Time 0.044 (0.032) Data 0.002 (0.005) Loss 0.0409 (0.0388) Prec@1 92.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 14:29:00,153 Epoch: [204][90/500] Time 0.043 (0.033) Data 0.002 (0.005) Loss 0.0313 (0.0381) Prec@1 95.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 14:29:00,507 Epoch: [204][100/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0498 (0.0391) Prec@1 92.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 14:29:00,882 Epoch: [204][110/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0266 (0.0381) Prec@1 96.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 14:29:01,281 Epoch: [204][120/500] Time 0.046 (0.033) Data 0.002 (0.004) Loss 0.0381 (0.0381) Prec@1 94.000 (94.538) Prec@5 99.000 (99.769) +2022-11-14 14:29:01,696 Epoch: [204][130/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0411 (0.0383) Prec@1 92.000 (94.357) Prec@5 100.000 (99.786) +2022-11-14 14:29:02,099 Epoch: [204][140/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.0485 (0.0390) Prec@1 91.000 (94.133) Prec@5 100.000 (99.800) +2022-11-14 14:29:02,511 Epoch: [204][150/500] Time 0.038 (0.034) Data 0.002 (0.004) Loss 0.0252 (0.0381) Prec@1 95.000 (94.188) Prec@5 100.000 (99.812) +2022-11-14 14:29:02,896 Epoch: [204][160/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0433 (0.0384) Prec@1 92.000 (94.059) Prec@5 100.000 (99.824) +2022-11-14 14:29:03,301 Epoch: [204][170/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0414 (0.0386) Prec@1 94.000 (94.056) Prec@5 100.000 (99.833) +2022-11-14 14:29:03,708 Epoch: [204][180/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0447 (0.0389) Prec@1 95.000 (94.105) Prec@5 100.000 (99.842) +2022-11-14 14:29:04,115 Epoch: [204][190/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0281 (0.0384) Prec@1 96.000 (94.200) Prec@5 99.000 (99.800) +2022-11-14 14:29:04,534 Epoch: [204][200/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0323 (0.0381) Prec@1 94.000 (94.190) Prec@5 99.000 (99.762) +2022-11-14 14:29:04,946 Epoch: [204][210/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0459 (0.0384) Prec@1 94.000 (94.182) Prec@5 100.000 (99.773) +2022-11-14 14:29:05,371 Epoch: [204][220/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0543 (0.0391) Prec@1 91.000 (94.043) Prec@5 100.000 (99.783) +2022-11-14 14:29:05,769 Epoch: [204][230/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.0288 (0.0387) Prec@1 95.000 (94.083) Prec@5 100.000 (99.792) +2022-11-14 14:29:06,161 Epoch: [204][240/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0536 (0.0393) Prec@1 89.000 (93.880) Prec@5 100.000 (99.800) +2022-11-14 14:29:06,621 Epoch: [204][250/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0564 (0.0400) Prec@1 91.000 (93.769) Prec@5 99.000 (99.769) +2022-11-14 14:29:07,329 Epoch: [204][260/500] Time 0.070 (0.036) Data 0.003 (0.003) Loss 0.0587 (0.0406) Prec@1 89.000 (93.593) Prec@5 100.000 (99.778) +2022-11-14 14:29:07,857 Epoch: [204][270/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0611 (0.0414) Prec@1 90.000 (93.464) Prec@5 100.000 (99.786) +2022-11-14 14:29:08,417 Epoch: [204][280/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0529 (0.0418) Prec@1 89.000 (93.310) Prec@5 100.000 (99.793) +2022-11-14 14:29:08,913 Epoch: [204][290/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0408 (0.0417) Prec@1 93.000 (93.300) Prec@5 100.000 (99.800) +2022-11-14 14:29:09,406 Epoch: [204][300/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0200 (0.0410) Prec@1 96.000 (93.387) Prec@5 100.000 (99.806) +2022-11-14 14:29:09,880 Epoch: [204][310/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0324 (0.0408) Prec@1 93.000 (93.375) Prec@5 100.000 (99.812) +2022-11-14 14:29:10,370 Epoch: [204][320/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0377 (0.0407) Prec@1 94.000 (93.394) Prec@5 100.000 (99.818) +2022-11-14 14:29:10,897 Epoch: [204][330/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0507 (0.0410) Prec@1 93.000 (93.382) Prec@5 97.000 (99.735) +2022-11-14 14:29:11,445 Epoch: [204][340/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0709 (0.0418) Prec@1 86.000 (93.171) Prec@5 100.000 (99.743) +2022-11-14 14:29:12,024 Epoch: [204][350/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0303 (0.0415) Prec@1 96.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:29:12,591 Epoch: [204][360/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0707 (0.0423) Prec@1 89.000 (93.135) Prec@5 100.000 (99.757) +2022-11-14 14:29:13,070 Epoch: [204][370/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0649 (0.0429) Prec@1 89.000 (93.026) Prec@5 100.000 (99.763) +2022-11-14 14:29:13,533 Epoch: [204][380/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0370 (0.0427) Prec@1 94.000 (93.051) Prec@5 100.000 (99.769) +2022-11-14 14:29:14,004 Epoch: [204][390/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0346 (0.0425) Prec@1 95.000 (93.100) Prec@5 100.000 (99.775) +2022-11-14 14:29:14,468 Epoch: [204][400/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0253 (0.0421) Prec@1 96.000 (93.171) Prec@5 100.000 (99.780) +2022-11-14 14:29:14,949 Epoch: [204][410/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0293 (0.0418) Prec@1 95.000 (93.214) Prec@5 100.000 (99.786) +2022-11-14 14:29:15,418 Epoch: [204][420/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0474 (0.0419) Prec@1 91.000 (93.163) Prec@5 100.000 (99.791) +2022-11-14 14:29:15,882 Epoch: [204][430/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0520 (0.0422) Prec@1 92.000 (93.136) Prec@5 99.000 (99.773) +2022-11-14 14:29:16,355 Epoch: [204][440/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0329 (0.0420) Prec@1 95.000 (93.178) Prec@5 100.000 (99.778) +2022-11-14 14:29:16,819 Epoch: [204][450/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0257 (0.0416) Prec@1 96.000 (93.239) Prec@5 100.000 (99.783) +2022-11-14 14:29:17,290 Epoch: [204][460/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0280 (0.0413) Prec@1 96.000 (93.298) Prec@5 100.000 (99.787) +2022-11-14 14:29:17,754 Epoch: [204][470/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0274 (0.0410) Prec@1 97.000 (93.375) Prec@5 100.000 (99.792) +2022-11-14 14:29:18,227 Epoch: [204][480/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0509 (0.0412) Prec@1 92.000 (93.347) Prec@5 100.000 (99.796) +2022-11-14 14:29:18,696 Epoch: [204][490/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0647 (0.0417) Prec@1 90.000 (93.280) Prec@5 100.000 (99.800) +2022-11-14 14:29:19,142 Epoch: [204][499/500] Time 0.044 (0.040) Data 0.001 (0.002) Loss 0.0447 (0.0418) Prec@1 93.000 (93.275) Prec@5 99.000 (99.784) +2022-11-14 14:29:19,426 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0705 (0.0705) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:29:19,439 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0656 (0.0681) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:29:19,450 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0638 (0.0667) Prec@1 89.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:29:19,463 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.0674) Prec@1 89.000 (89.000) Prec@5 98.000 (99.250) +2022-11-14 14:29:19,472 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0681 (0.0676) Prec@1 89.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 14:29:19,480 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0631) Prec@1 91.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 14:29:19,489 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0483 (0.0610) Prec@1 94.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 14:29:19,498 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0641) Prec@1 85.000 (89.375) Prec@5 99.000 (99.500) +2022-11-14 14:29:19,508 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0656) Prec@1 87.000 (89.111) Prec@5 100.000 (99.556) +2022-11-14 14:29:19,517 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0657) Prec@1 89.000 (89.100) Prec@5 99.000 (99.500) +2022-11-14 14:29:19,525 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0641) Prec@1 92.000 (89.364) Prec@5 100.000 (99.545) +2022-11-14 14:29:19,534 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0658) Prec@1 88.000 (89.250) Prec@5 100.000 (99.583) +2022-11-14 14:29:19,543 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0653) Prec@1 90.000 (89.308) Prec@5 100.000 (99.615) +2022-11-14 14:29:19,552 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0653) Prec@1 91.000 (89.429) Prec@5 100.000 (99.643) +2022-11-14 14:29:19,560 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0647) Prec@1 92.000 (89.600) Prec@5 100.000 (99.667) +2022-11-14 14:29:19,569 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0658) Prec@1 86.000 (89.375) Prec@5 99.000 (99.625) +2022-11-14 14:29:19,579 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0645) Prec@1 93.000 (89.588) Prec@5 98.000 (99.529) +2022-11-14 14:29:19,587 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0664) Prec@1 85.000 (89.333) Prec@5 99.000 (99.500) +2022-11-14 14:29:19,596 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0670) Prec@1 87.000 (89.211) Prec@5 99.000 (99.474) +2022-11-14 14:29:19,606 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0678) Prec@1 89.000 (89.200) Prec@5 99.000 (99.450) +2022-11-14 14:29:19,615 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0686) Prec@1 86.000 (89.048) Prec@5 100.000 (99.476) +2022-11-14 14:29:19,624 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0687) Prec@1 87.000 (88.955) Prec@5 99.000 (99.455) +2022-11-14 14:29:19,633 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0700) Prec@1 85.000 (88.783) Prec@5 97.000 (99.348) +2022-11-14 14:29:19,642 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0703) Prec@1 85.000 (88.625) Prec@5 99.000 (99.333) +2022-11-14 14:29:19,650 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0712) Prec@1 84.000 (88.440) Prec@5 100.000 (99.360) +2022-11-14 14:29:19,658 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0725) Prec@1 83.000 (88.231) Prec@5 99.000 (99.346) +2022-11-14 14:29:19,665 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0713) Prec@1 95.000 (88.481) Prec@5 100.000 (99.370) +2022-11-14 14:29:19,673 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0709) Prec@1 90.000 (88.536) Prec@5 100.000 (99.393) +2022-11-14 14:29:19,683 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0713) Prec@1 86.000 (88.448) Prec@5 98.000 (99.345) +2022-11-14 14:29:19,693 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0704) Prec@1 91.000 (88.533) Prec@5 100.000 (99.367) +2022-11-14 14:29:19,702 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0707) Prec@1 88.000 (88.516) Prec@5 99.000 (99.355) +2022-11-14 14:29:19,711 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0707) Prec@1 87.000 (88.469) Prec@5 100.000 (99.375) +2022-11-14 14:29:19,722 Test: [32/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0708) Prec@1 88.000 (88.455) Prec@5 100.000 (99.394) +2022-11-14 14:29:19,733 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0714) Prec@1 86.000 (88.382) Prec@5 100.000 (99.412) +2022-11-14 14:29:19,742 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0721) Prec@1 83.000 (88.229) Prec@5 98.000 (99.371) +2022-11-14 14:29:19,752 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0718) Prec@1 91.000 (88.306) Prec@5 98.000 (99.333) +2022-11-14 14:29:19,764 Test: [36/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0718) Prec@1 90.000 (88.351) Prec@5 99.000 (99.324) +2022-11-14 14:29:19,776 Test: [37/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0723) Prec@1 84.000 (88.237) Prec@5 99.000 (99.316) +2022-11-14 14:29:19,785 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0719) Prec@1 94.000 (88.385) Prec@5 100.000 (99.333) +2022-11-14 14:29:19,795 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0719) Prec@1 87.000 (88.350) Prec@5 98.000 (99.300) +2022-11-14 14:29:19,805 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0724) Prec@1 86.000 (88.293) Prec@5 99.000 (99.293) +2022-11-14 14:29:19,814 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0725) Prec@1 86.000 (88.238) Prec@5 99.000 (99.286) +2022-11-14 14:29:19,822 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0717) Prec@1 92.000 (88.326) Prec@5 100.000 (99.302) +2022-11-14 14:29:19,831 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0719) Prec@1 88.000 (88.318) Prec@5 98.000 (99.273) +2022-11-14 14:29:19,841 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0720) Prec@1 88.000 (88.311) Prec@5 98.000 (99.244) +2022-11-14 14:29:19,850 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0726) Prec@1 83.000 (88.196) Prec@5 100.000 (99.261) +2022-11-14 14:29:19,860 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0730) Prec@1 85.000 (88.128) Prec@5 100.000 (99.277) +2022-11-14 14:29:19,869 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0738) Prec@1 82.000 (88.000) Prec@5 98.000 (99.250) +2022-11-14 14:29:19,878 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0735) Prec@1 89.000 (88.020) Prec@5 100.000 (99.265) +2022-11-14 14:29:19,888 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0740) Prec@1 84.000 (87.940) Prec@5 98.000 (99.240) +2022-11-14 14:29:19,898 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0737) Prec@1 90.000 (87.980) Prec@5 100.000 (99.255) +2022-11-14 14:29:19,907 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0743) Prec@1 81.000 (87.846) Prec@5 99.000 (99.250) +2022-11-14 14:29:19,915 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0747) Prec@1 82.000 (87.736) Prec@5 100.000 (99.264) +2022-11-14 14:29:19,924 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0746) Prec@1 90.000 (87.778) Prec@5 98.000 (99.241) +2022-11-14 14:29:19,932 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0743) Prec@1 89.000 (87.800) Prec@5 100.000 (99.255) +2022-11-14 14:29:19,942 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0742) Prec@1 88.000 (87.804) Prec@5 100.000 (99.268) +2022-11-14 14:29:19,950 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0740) Prec@1 89.000 (87.825) Prec@5 100.000 (99.281) +2022-11-14 14:29:19,959 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0736) Prec@1 91.000 (87.879) Prec@5 100.000 (99.293) +2022-11-14 14:29:19,969 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0738) Prec@1 84.000 (87.814) Prec@5 100.000 (99.305) +2022-11-14 14:29:19,978 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0739) Prec@1 85.000 (87.767) Prec@5 100.000 (99.317) +2022-11-14 14:29:19,987 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0739) Prec@1 88.000 (87.770) Prec@5 99.000 (99.311) +2022-11-14 14:29:19,997 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0738) Prec@1 91.000 (87.823) Prec@5 100.000 (99.323) +2022-11-14 14:29:20,006 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0738) Prec@1 87.000 (87.810) Prec@5 99.000 (99.317) +2022-11-14 14:29:20,016 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0733) Prec@1 92.000 (87.875) Prec@5 100.000 (99.328) +2022-11-14 14:29:20,026 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0736) Prec@1 86.000 (87.846) Prec@5 99.000 (99.323) +2022-11-14 14:29:20,035 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0738) Prec@1 85.000 (87.803) Prec@5 99.000 (99.318) +2022-11-14 14:29:20,044 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0383 (0.0733) Prec@1 92.000 (87.866) Prec@5 100.000 (99.328) +2022-11-14 14:29:20,053 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0732) Prec@1 89.000 (87.882) Prec@5 99.000 (99.324) +2022-11-14 14:29:20,061 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0731) Prec@1 88.000 (87.884) Prec@5 99.000 (99.319) +2022-11-14 14:29:20,070 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0733) Prec@1 86.000 (87.857) Prec@5 100.000 (99.329) +2022-11-14 14:29:20,080 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0734) Prec@1 87.000 (87.845) Prec@5 100.000 (99.338) +2022-11-14 14:29:20,089 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0735) Prec@1 86.000 (87.819) Prec@5 100.000 (99.347) +2022-11-14 14:29:20,099 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0733) Prec@1 91.000 (87.863) Prec@5 100.000 (99.356) +2022-11-14 14:29:20,108 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0411 (0.0728) Prec@1 95.000 (87.959) Prec@5 100.000 (99.365) +2022-11-14 14:29:20,117 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0730) Prec@1 86.000 (87.933) Prec@5 100.000 (99.373) +2022-11-14 14:29:20,126 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0729) Prec@1 90.000 (87.961) Prec@5 98.000 (99.355) +2022-11-14 14:29:20,135 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0728) Prec@1 90.000 (87.987) Prec@5 99.000 (99.351) +2022-11-14 14:29:20,145 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0731) Prec@1 85.000 (87.949) Prec@5 97.000 (99.321) +2022-11-14 14:29:20,153 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0730) Prec@1 89.000 (87.962) Prec@5 100.000 (99.329) +2022-11-14 14:29:20,162 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0730) Prec@1 89.000 (87.975) Prec@5 100.000 (99.338) +2022-11-14 14:29:20,171 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0729) Prec@1 90.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 14:29:20,181 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0728) Prec@1 90.000 (88.024) Prec@5 100.000 (99.341) +2022-11-14 14:29:20,190 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0728) Prec@1 89.000 (88.036) Prec@5 99.000 (99.337) +2022-11-14 14:29:20,200 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0726) Prec@1 90.000 (88.060) Prec@5 99.000 (99.333) +2022-11-14 14:29:20,209 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0729) Prec@1 83.000 (88.000) Prec@5 98.000 (99.318) +2022-11-14 14:29:20,219 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0732) Prec@1 84.000 (87.953) Prec@5 99.000 (99.314) +2022-11-14 14:29:20,228 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0733) Prec@1 85.000 (87.920) Prec@5 100.000 (99.322) +2022-11-14 14:29:20,236 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0734) Prec@1 87.000 (87.909) Prec@5 99.000 (99.318) +2022-11-14 14:29:20,245 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0732) Prec@1 90.000 (87.933) Prec@5 99.000 (99.315) +2022-11-14 14:29:20,253 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0733) Prec@1 88.000 (87.933) Prec@5 99.000 (99.311) +2022-11-14 14:29:20,261 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0732) Prec@1 89.000 (87.945) Prec@5 100.000 (99.319) +2022-11-14 14:29:20,270 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0309 (0.0727) Prec@1 96.000 (88.033) Prec@5 100.000 (99.326) +2022-11-14 14:29:20,280 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0730) Prec@1 87.000 (88.022) Prec@5 100.000 (99.333) +2022-11-14 14:29:20,289 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0730) Prec@1 88.000 (88.021) Prec@5 99.000 (99.330) +2022-11-14 14:29:20,298 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0730) Prec@1 87.000 (88.011) Prec@5 100.000 (99.337) +2022-11-14 14:29:20,306 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0728) Prec@1 92.000 (88.052) Prec@5 100.000 (99.344) +2022-11-14 14:29:20,316 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0725) Prec@1 92.000 (88.093) Prec@5 100.000 (99.351) +2022-11-14 14:29:20,325 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0725) Prec@1 88.000 (88.092) Prec@5 100.000 (99.357) +2022-11-14 14:29:20,334 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0727) Prec@1 85.000 (88.061) Prec@5 100.000 (99.364) +2022-11-14 14:29:20,342 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0727) Prec@1 88.000 (88.060) Prec@5 100.000 (99.370) +2022-11-14 14:29:20,409 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:29:20,717 Epoch: [205][0/500] Time 0.021 (0.021) Data 0.228 (0.228) Loss 0.0155 (0.0155) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:29:20,926 Epoch: [205][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0591 (0.0373) Prec@1 88.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:29:21,134 Epoch: [205][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0462 (0.0403) Prec@1 93.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:29:21,413 Epoch: [205][30/500] Time 0.037 (0.020) Data 0.002 (0.009) Loss 0.0368 (0.0394) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:29:21,905 Epoch: [205][40/500] Time 0.043 (0.026) Data 0.002 (0.007) Loss 0.0575 (0.0430) Prec@1 91.000 (93.000) Prec@5 99.000 (99.800) +2022-11-14 14:29:22,376 Epoch: [205][50/500] Time 0.044 (0.029) Data 0.002 (0.006) Loss 0.0300 (0.0408) Prec@1 96.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 14:29:22,840 Epoch: [205][60/500] Time 0.043 (0.031) Data 0.002 (0.006) Loss 0.0350 (0.0400) Prec@1 96.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 14:29:23,309 Epoch: [205][70/500] Time 0.043 (0.033) Data 0.002 (0.005) Loss 0.0343 (0.0393) Prec@1 92.000 (93.625) Prec@5 100.000 (99.875) +2022-11-14 14:29:23,774 Epoch: [205][80/500] Time 0.044 (0.034) Data 0.002 (0.005) Loss 0.0459 (0.0400) Prec@1 93.000 (93.556) Prec@5 100.000 (99.889) +2022-11-14 14:29:24,243 Epoch: [205][90/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0435 (0.0404) Prec@1 93.000 (93.500) Prec@5 100.000 (99.900) +2022-11-14 14:29:24,706 Epoch: [205][100/500] Time 0.047 (0.035) Data 0.001 (0.004) Loss 0.0464 (0.0409) Prec@1 92.000 (93.364) Prec@5 99.000 (99.818) +2022-11-14 14:29:25,173 Epoch: [205][110/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0421 (0.0410) Prec@1 94.000 (93.417) Prec@5 100.000 (99.833) +2022-11-14 14:29:25,636 Epoch: [205][120/500] Time 0.044 (0.036) Data 0.002 (0.004) Loss 0.0281 (0.0400) Prec@1 96.000 (93.615) Prec@5 99.000 (99.769) +2022-11-14 14:29:26,100 Epoch: [205][130/500] Time 0.041 (0.037) Data 0.002 (0.004) Loss 0.0535 (0.0410) Prec@1 88.000 (93.214) Prec@5 100.000 (99.786) +2022-11-14 14:29:26,558 Epoch: [205][140/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0375 (0.0408) Prec@1 93.000 (93.200) Prec@5 100.000 (99.800) +2022-11-14 14:29:27,029 Epoch: [205][150/500] Time 0.052 (0.037) Data 0.002 (0.003) Loss 0.0354 (0.0404) Prec@1 95.000 (93.312) Prec@5 100.000 (99.812) +2022-11-14 14:29:27,494 Epoch: [205][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0246 (0.0395) Prec@1 97.000 (93.529) Prec@5 100.000 (99.824) +2022-11-14 14:29:27,960 Epoch: [205][170/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0401 (0.0395) Prec@1 92.000 (93.444) Prec@5 100.000 (99.833) +2022-11-14 14:29:28,421 Epoch: [205][180/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0122 (0.0381) Prec@1 99.000 (93.737) Prec@5 100.000 (99.842) +2022-11-14 14:29:28,886 Epoch: [205][190/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0253 (0.0375) Prec@1 95.000 (93.800) Prec@5 100.000 (99.850) +2022-11-14 14:29:29,350 Epoch: [205][200/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0404 (0.0376) Prec@1 93.000 (93.762) Prec@5 100.000 (99.857) +2022-11-14 14:29:29,814 Epoch: [205][210/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0377 (0.0376) Prec@1 93.000 (93.727) Prec@5 100.000 (99.864) +2022-11-14 14:29:30,284 Epoch: [205][220/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0482 (0.0381) Prec@1 90.000 (93.565) Prec@5 100.000 (99.870) +2022-11-14 14:29:30,746 Epoch: [205][230/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0467 (0.0384) Prec@1 90.000 (93.417) Prec@5 100.000 (99.875) +2022-11-14 14:29:31,215 Epoch: [205][240/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0261 (0.0379) Prec@1 97.000 (93.560) Prec@5 100.000 (99.880) +2022-11-14 14:29:31,676 Epoch: [205][250/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0462 (0.0382) Prec@1 91.000 (93.462) Prec@5 100.000 (99.885) +2022-11-14 14:29:32,141 Epoch: [205][260/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0322 (0.0380) Prec@1 94.000 (93.481) Prec@5 98.000 (99.815) +2022-11-14 14:29:32,603 Epoch: [205][270/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0496 (0.0384) Prec@1 95.000 (93.536) Prec@5 99.000 (99.786) +2022-11-14 14:29:33,074 Epoch: [205][280/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0375 (0.0384) Prec@1 95.000 (93.586) Prec@5 100.000 (99.793) +2022-11-14 14:29:33,546 Epoch: [205][290/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0615 (0.0392) Prec@1 89.000 (93.433) Prec@5 100.000 (99.800) +2022-11-14 14:29:33,890 Epoch: [205][300/500] Time 0.027 (0.039) Data 0.002 (0.003) Loss 0.0402 (0.0392) Prec@1 93.000 (93.419) Prec@5 100.000 (99.806) +2022-11-14 14:29:34,185 Epoch: [205][310/500] Time 0.028 (0.039) Data 0.002 (0.003) Loss 0.0334 (0.0390) Prec@1 95.000 (93.469) Prec@5 100.000 (99.812) +2022-11-14 14:29:34,476 Epoch: [205][320/500] Time 0.027 (0.038) Data 0.002 (0.003) Loss 0.0136 (0.0383) Prec@1 99.000 (93.636) Prec@5 99.000 (99.788) +2022-11-14 14:29:34,770 Epoch: [205][330/500] Time 0.028 (0.038) Data 0.002 (0.003) Loss 0.0392 (0.0383) Prec@1 92.000 (93.588) Prec@5 100.000 (99.794) +2022-11-14 14:29:35,072 Epoch: [205][340/500] Time 0.027 (0.037) Data 0.003 (0.003) Loss 0.0439 (0.0384) Prec@1 93.000 (93.571) Prec@5 100.000 (99.800) +2022-11-14 14:29:35,364 Epoch: [205][350/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.0695 (0.0393) Prec@1 91.000 (93.500) Prec@5 99.000 (99.778) +2022-11-14 14:29:35,656 Epoch: [205][360/500] Time 0.028 (0.037) Data 0.002 (0.003) Loss 0.0584 (0.0398) Prec@1 91.000 (93.432) Prec@5 100.000 (99.784) +2022-11-14 14:29:35,953 Epoch: [205][370/500] Time 0.028 (0.037) Data 0.002 (0.002) Loss 0.0387 (0.0398) Prec@1 94.000 (93.447) Prec@5 99.000 (99.763) +2022-11-14 14:29:36,250 Epoch: [205][380/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0438 (0.0399) Prec@1 91.000 (93.385) Prec@5 100.000 (99.769) +2022-11-14 14:29:36,549 Epoch: [205][390/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0500 (0.0401) Prec@1 92.000 (93.350) Prec@5 100.000 (99.775) +2022-11-14 14:29:36,848 Epoch: [205][400/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0479 (0.0403) Prec@1 91.000 (93.293) Prec@5 99.000 (99.756) +2022-11-14 14:29:37,149 Epoch: [205][410/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0434 (0.0404) Prec@1 93.000 (93.286) Prec@5 99.000 (99.738) +2022-11-14 14:29:37,445 Epoch: [205][420/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0319 (0.0402) Prec@1 94.000 (93.302) Prec@5 100.000 (99.744) +2022-11-14 14:29:37,739 Epoch: [205][430/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0297 (0.0400) Prec@1 96.000 (93.364) Prec@5 100.000 (99.750) +2022-11-14 14:29:38,043 Epoch: [205][440/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0213 (0.0396) Prec@1 96.000 (93.422) Prec@5 100.000 (99.756) +2022-11-14 14:29:38,341 Epoch: [205][450/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0514 (0.0398) Prec@1 92.000 (93.391) Prec@5 100.000 (99.761) +2022-11-14 14:29:38,639 Epoch: [205][460/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.0548 (0.0401) Prec@1 91.000 (93.340) Prec@5 100.000 (99.766) +2022-11-14 14:29:38,939 Epoch: [205][470/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0455 (0.0402) Prec@1 94.000 (93.354) Prec@5 100.000 (99.771) +2022-11-14 14:29:39,238 Epoch: [205][480/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0191 (0.0398) Prec@1 96.000 (93.408) Prec@5 100.000 (99.776) +2022-11-14 14:29:39,536 Epoch: [205][490/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0287 (0.0396) Prec@1 96.000 (93.460) Prec@5 100.000 (99.780) +2022-11-14 14:29:39,939 Epoch: [205][499/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.0483 (0.0398) Prec@1 92.000 (93.431) Prec@5 100.000 (99.784) +2022-11-14 14:29:40,223 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0562 (0.0562) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:29:40,231 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0637) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:29:40,240 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0671) Prec@1 87.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:29:40,253 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0711) Prec@1 84.000 (87.250) Prec@5 98.000 (99.250) +2022-11-14 14:29:40,262 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0734) Prec@1 86.000 (87.000) Prec@5 100.000 (99.400) +2022-11-14 14:29:40,270 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0361 (0.0672) Prec@1 93.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:29:40,278 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0654) Prec@1 91.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 14:29:40,288 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0696) Prec@1 82.000 (87.625) Prec@5 100.000 (99.625) +2022-11-14 14:29:40,298 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0714) Prec@1 85.000 (87.333) Prec@5 99.000 (99.556) +2022-11-14 14:29:40,308 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0723) Prec@1 86.000 (87.200) Prec@5 99.000 (99.500) +2022-11-14 14:29:40,320 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0714) Prec@1 91.000 (87.545) Prec@5 100.000 (99.545) +2022-11-14 14:29:40,330 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0740) Prec@1 84.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:29:40,340 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0735) Prec@1 88.000 (87.308) Prec@5 100.000 (99.538) +2022-11-14 14:29:40,351 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0748) Prec@1 86.000 (87.214) Prec@5 99.000 (99.500) +2022-11-14 14:29:40,362 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0761) Prec@1 83.000 (86.933) Prec@5 100.000 (99.533) +2022-11-14 14:29:40,373 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0764) Prec@1 89.000 (87.062) Prec@5 98.000 (99.438) +2022-11-14 14:29:40,384 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0750) Prec@1 92.000 (87.353) Prec@5 99.000 (99.412) +2022-11-14 14:29:40,396 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0762) Prec@1 84.000 (87.167) Prec@5 100.000 (99.444) +2022-11-14 14:29:40,408 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0764) Prec@1 87.000 (87.158) Prec@5 98.000 (99.368) +2022-11-14 14:29:40,419 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0773) Prec@1 87.000 (87.150) Prec@5 98.000 (99.300) +2022-11-14 14:29:40,431 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0772) Prec@1 87.000 (87.143) Prec@5 100.000 (99.333) +2022-11-14 14:29:40,443 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0775) Prec@1 85.000 (87.045) Prec@5 98.000 (99.273) +2022-11-14 14:29:40,454 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0780) Prec@1 85.000 (86.957) Prec@5 98.000 (99.217) +2022-11-14 14:29:40,467 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0786) Prec@1 85.000 (86.875) Prec@5 100.000 (99.250) +2022-11-14 14:29:40,479 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0785) Prec@1 89.000 (86.960) Prec@5 100.000 (99.280) +2022-11-14 14:29:40,489 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0787) Prec@1 88.000 (87.000) Prec@5 99.000 (99.269) +2022-11-14 14:29:40,502 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0374 (0.0772) Prec@1 92.000 (87.185) Prec@5 100.000 (99.296) +2022-11-14 14:29:40,513 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0766) Prec@1 90.000 (87.286) Prec@5 99.000 (99.286) +2022-11-14 14:29:40,525 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0769) Prec@1 85.000 (87.207) Prec@5 98.000 (99.241) +2022-11-14 14:29:40,537 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0766) Prec@1 88.000 (87.233) Prec@5 99.000 (99.233) +2022-11-14 14:29:40,549 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0759) Prec@1 91.000 (87.355) Prec@5 100.000 (99.258) +2022-11-14 14:29:40,562 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0759) Prec@1 88.000 (87.375) Prec@5 100.000 (99.281) +2022-11-14 14:29:40,572 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0756) Prec@1 89.000 (87.424) Prec@5 99.000 (99.273) +2022-11-14 14:29:40,583 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0764) Prec@1 85.000 (87.353) Prec@5 98.000 (99.235) +2022-11-14 14:29:40,592 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0765) Prec@1 85.000 (87.286) Prec@5 98.000 (99.200) +2022-11-14 14:29:40,604 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0762) Prec@1 89.000 (87.333) Prec@5 100.000 (99.222) +2022-11-14 14:29:40,616 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0762) Prec@1 88.000 (87.351) Prec@5 99.000 (99.216) +2022-11-14 14:29:40,627 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1263 (0.0775) Prec@1 76.000 (87.053) Prec@5 98.000 (99.184) +2022-11-14 14:29:40,639 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0771) Prec@1 93.000 (87.205) Prec@5 99.000 (99.179) +2022-11-14 14:29:40,651 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0768) Prec@1 87.000 (87.200) Prec@5 100.000 (99.200) +2022-11-14 14:29:40,662 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0772) Prec@1 83.000 (87.098) Prec@5 97.000 (99.146) +2022-11-14 14:29:40,675 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0770) Prec@1 89.000 (87.143) Prec@5 100.000 (99.167) +2022-11-14 14:29:40,686 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0763) Prec@1 92.000 (87.256) Prec@5 99.000 (99.163) +2022-11-14 14:29:40,697 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0761) Prec@1 88.000 (87.273) Prec@5 99.000 (99.159) +2022-11-14 14:29:40,709 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0757) Prec@1 91.000 (87.356) Prec@5 99.000 (99.156) +2022-11-14 14:29:40,721 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0764) Prec@1 82.000 (87.239) Prec@5 100.000 (99.174) +2022-11-14 14:29:40,732 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0764) Prec@1 86.000 (87.213) Prec@5 99.000 (99.170) +2022-11-14 14:29:40,744 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0768) Prec@1 88.000 (87.229) Prec@5 99.000 (99.167) +2022-11-14 14:29:40,756 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0761) Prec@1 91.000 (87.306) Prec@5 100.000 (99.184) +2022-11-14 14:29:40,768 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0768) Prec@1 80.000 (87.160) Prec@5 99.000 (99.180) +2022-11-14 14:29:40,778 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0765) Prec@1 89.000 (87.196) Prec@5 99.000 (99.176) +2022-11-14 14:29:40,790 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 86.000 (87.173) Prec@5 100.000 (99.192) +2022-11-14 14:29:40,801 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0762) Prec@1 90.000 (87.226) Prec@5 100.000 (99.208) +2022-11-14 14:29:40,814 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0760) Prec@1 89.000 (87.259) Prec@5 98.000 (99.185) +2022-11-14 14:29:40,826 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0763) Prec@1 83.000 (87.182) Prec@5 100.000 (99.200) +2022-11-14 14:29:40,837 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0764) Prec@1 87.000 (87.179) Prec@5 99.000 (99.196) +2022-11-14 14:29:40,848 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0762) Prec@1 86.000 (87.158) Prec@5 100.000 (99.211) +2022-11-14 14:29:40,860 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0761) Prec@1 89.000 (87.190) Prec@5 100.000 (99.224) +2022-11-14 14:29:40,872 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0765) Prec@1 83.000 (87.119) Prec@5 100.000 (99.237) +2022-11-14 14:29:40,883 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0763) Prec@1 86.000 (87.100) Prec@5 100.000 (99.250) +2022-11-14 14:29:40,895 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0765) Prec@1 85.000 (87.066) Prec@5 99.000 (99.246) +2022-11-14 14:29:40,906 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0761) Prec@1 92.000 (87.145) Prec@5 100.000 (99.258) +2022-11-14 14:29:40,917 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0757) Prec@1 92.000 (87.222) Prec@5 99.000 (99.254) +2022-11-14 14:29:40,929 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0753) Prec@1 91.000 (87.281) Prec@5 100.000 (99.266) +2022-11-14 14:29:40,940 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0753) Prec@1 85.000 (87.246) Prec@5 100.000 (99.277) +2022-11-14 14:29:40,951 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0752) Prec@1 88.000 (87.258) Prec@5 100.000 (99.288) +2022-11-14 14:29:40,964 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0747) Prec@1 92.000 (87.328) Prec@5 100.000 (99.299) +2022-11-14 14:29:40,978 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0748) Prec@1 89.000 (87.353) Prec@5 100.000 (99.309) +2022-11-14 14:29:40,989 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0747) Prec@1 87.000 (87.348) Prec@5 100.000 (99.319) +2022-11-14 14:29:41,001 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0749) Prec@1 86.000 (87.329) Prec@5 100.000 (99.329) +2022-11-14 14:29:41,014 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 87.000 (87.324) Prec@5 100.000 (99.338) +2022-11-14 14:29:41,025 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0749) Prec@1 90.000 (87.361) Prec@5 100.000 (99.347) +2022-11-14 14:29:41,036 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0748) Prec@1 88.000 (87.370) Prec@5 99.000 (99.342) +2022-11-14 14:29:41,048 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0746) Prec@1 91.000 (87.419) Prec@5 100.000 (99.351) +2022-11-14 14:29:41,059 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0749) Prec@1 83.000 (87.360) Prec@5 99.000 (99.347) +2022-11-14 14:29:41,071 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0747) Prec@1 91.000 (87.408) Prec@5 99.000 (99.342) +2022-11-14 14:29:41,083 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0746) Prec@1 88.000 (87.416) Prec@5 100.000 (99.351) +2022-11-14 14:29:41,095 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0745) Prec@1 89.000 (87.436) Prec@5 97.000 (99.321) +2022-11-14 14:29:41,107 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0745) Prec@1 89.000 (87.456) Prec@5 99.000 (99.316) +2022-11-14 14:29:41,119 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0745) Prec@1 86.000 (87.438) Prec@5 99.000 (99.312) +2022-11-14 14:29:41,131 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0746) Prec@1 87.000 (87.432) Prec@5 98.000 (99.296) +2022-11-14 14:29:41,142 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0746) Prec@1 86.000 (87.415) Prec@5 100.000 (99.305) +2022-11-14 14:29:41,154 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0747) Prec@1 85.000 (87.386) Prec@5 100.000 (99.313) +2022-11-14 14:29:41,166 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0747) Prec@1 87.000 (87.381) Prec@5 99.000 (99.310) +2022-11-14 14:29:41,178 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0748) Prec@1 87.000 (87.376) Prec@5 100.000 (99.318) +2022-11-14 14:29:41,189 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0751) Prec@1 83.000 (87.326) Prec@5 99.000 (99.314) +2022-11-14 14:29:41,201 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0752) Prec@1 86.000 (87.310) Prec@5 99.000 (99.310) +2022-11-14 14:29:41,213 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0752) Prec@1 89.000 (87.330) Prec@5 100.000 (99.318) +2022-11-14 14:29:41,224 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0750) Prec@1 92.000 (87.382) Prec@5 99.000 (99.315) +2022-11-14 14:29:41,236 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0753) Prec@1 84.000 (87.344) Prec@5 99.000 (99.311) +2022-11-14 14:29:41,248 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0751) Prec@1 92.000 (87.396) Prec@5 100.000 (99.319) +2022-11-14 14:29:41,261 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0750) Prec@1 88.000 (87.402) Prec@5 100.000 (99.326) +2022-11-14 14:29:41,272 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0751) Prec@1 87.000 (87.398) Prec@5 100.000 (99.333) +2022-11-14 14:29:41,284 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0751) Prec@1 86.000 (87.383) Prec@5 99.000 (99.330) +2022-11-14 14:29:41,298 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0753) Prec@1 81.000 (87.316) Prec@5 99.000 (99.326) +2022-11-14 14:29:41,309 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0751) Prec@1 91.000 (87.354) Prec@5 100.000 (99.333) +2022-11-14 14:29:41,320 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0747) Prec@1 93.000 (87.412) Prec@5 99.000 (99.330) +2022-11-14 14:29:41,331 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0747) Prec@1 88.000 (87.418) Prec@5 100.000 (99.337) +2022-11-14 14:29:41,342 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0750) Prec@1 83.000 (87.374) Prec@5 99.000 (99.333) +2022-11-14 14:29:41,354 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0749) Prec@1 88.000 (87.380) Prec@5 99.000 (99.330) +2022-11-14 14:29:41,410 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:29:41,722 Epoch: [206][0/500] Time 0.023 (0.023) Data 0.228 (0.228) Loss 0.0230 (0.0230) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:29:41,949 Epoch: [206][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.0462 (0.0346) Prec@1 89.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:29:42,176 Epoch: [206][20/500] Time 0.024 (0.020) Data 0.002 (0.013) Loss 0.0267 (0.0320) Prec@1 95.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:29:42,545 Epoch: [206][30/500] Time 0.041 (0.024) Data 0.002 (0.009) Loss 0.0219 (0.0295) Prec@1 97.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 14:29:42,993 Epoch: [206][40/500] Time 0.043 (0.028) Data 0.002 (0.007) Loss 0.0553 (0.0346) Prec@1 89.000 (93.200) Prec@5 100.000 (100.000) +2022-11-14 14:29:43,428 Epoch: [206][50/500] Time 0.042 (0.030) Data 0.002 (0.006) Loss 0.0375 (0.0351) Prec@1 95.000 (93.500) Prec@5 99.000 (99.833) +2022-11-14 14:29:43,874 Epoch: [206][60/500] Time 0.041 (0.032) Data 0.002 (0.006) Loss 0.0397 (0.0358) Prec@1 93.000 (93.429) Prec@5 100.000 (99.857) +2022-11-14 14:29:44,326 Epoch: [206][70/500] Time 0.042 (0.033) Data 0.002 (0.005) Loss 0.0287 (0.0349) Prec@1 96.000 (93.750) Prec@5 100.000 (99.875) +2022-11-14 14:29:44,769 Epoch: [206][80/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0325 (0.0346) Prec@1 94.000 (93.778) Prec@5 100.000 (99.889) +2022-11-14 14:29:45,210 Epoch: [206][90/500] Time 0.041 (0.034) Data 0.001 (0.004) Loss 0.0316 (0.0343) Prec@1 95.000 (93.900) Prec@5 100.000 (99.900) +2022-11-14 14:29:45,658 Epoch: [206][100/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0710 (0.0377) Prec@1 90.000 (93.545) Prec@5 100.000 (99.909) +2022-11-14 14:29:46,102 Epoch: [206][110/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0224 (0.0364) Prec@1 96.000 (93.750) Prec@5 100.000 (99.917) +2022-11-14 14:29:46,516 Epoch: [206][120/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0292 (0.0358) Prec@1 96.000 (93.923) Prec@5 100.000 (99.923) +2022-11-14 14:29:46,960 Epoch: [206][130/500] Time 0.040 (0.036) Data 0.002 (0.004) Loss 0.0331 (0.0356) Prec@1 93.000 (93.857) Prec@5 100.000 (99.929) +2022-11-14 14:29:47,403 Epoch: [206][140/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0471 (0.0364) Prec@1 91.000 (93.667) Prec@5 100.000 (99.933) +2022-11-14 14:29:47,842 Epoch: [206][150/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0309 (0.0361) Prec@1 94.000 (93.688) Prec@5 100.000 (99.938) +2022-11-14 14:29:48,284 Epoch: [206][160/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0238 (0.0353) Prec@1 96.000 (93.824) Prec@5 100.000 (99.941) +2022-11-14 14:29:48,722 Epoch: [206][170/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0398 (0.0356) Prec@1 94.000 (93.833) Prec@5 99.000 (99.889) +2022-11-14 14:29:49,153 Epoch: [206][180/500] Time 0.038 (0.037) Data 0.001 (0.003) Loss 0.0249 (0.0350) Prec@1 95.000 (93.895) Prec@5 99.000 (99.842) +2022-11-14 14:29:49,593 Epoch: [206][190/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0309 (0.0348) Prec@1 96.000 (94.000) Prec@5 100.000 (99.850) +2022-11-14 14:29:50,029 Epoch: [206][200/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0221 (0.0342) Prec@1 96.000 (94.095) Prec@5 100.000 (99.857) +2022-11-14 14:29:50,467 Epoch: [206][210/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0441 (0.0347) Prec@1 92.000 (94.000) Prec@5 100.000 (99.864) +2022-11-14 14:29:50,905 Epoch: [206][220/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0371 (0.0348) Prec@1 94.000 (94.000) Prec@5 100.000 (99.870) +2022-11-14 14:29:51,344 Epoch: [206][230/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0548 (0.0356) Prec@1 89.000 (93.792) Prec@5 100.000 (99.875) +2022-11-14 14:29:51,783 Epoch: [206][240/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0584 (0.0365) Prec@1 91.000 (93.680) Prec@5 100.000 (99.880) +2022-11-14 14:29:52,223 Epoch: [206][250/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0408 (0.0367) Prec@1 92.000 (93.615) Prec@5 100.000 (99.885) +2022-11-14 14:29:52,658 Epoch: [206][260/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0379 (0.0367) Prec@1 94.000 (93.630) Prec@5 100.000 (99.889) +2022-11-14 14:29:53,086 Epoch: [206][270/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0139 (0.0359) Prec@1 98.000 (93.786) Prec@5 100.000 (99.893) +2022-11-14 14:29:53,524 Epoch: [206][280/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0319 (0.0358) Prec@1 95.000 (93.828) Prec@5 100.000 (99.897) +2022-11-14 14:29:53,966 Epoch: [206][290/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0481 (0.0362) Prec@1 93.000 (93.800) Prec@5 100.000 (99.900) +2022-11-14 14:29:54,404 Epoch: [206][300/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0326 (0.0361) Prec@1 93.000 (93.774) Prec@5 100.000 (99.903) +2022-11-14 14:29:54,839 Epoch: [206][310/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0645 (0.0370) Prec@1 88.000 (93.594) Prec@5 100.000 (99.906) +2022-11-14 14:29:55,274 Epoch: [206][320/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0578 (0.0376) Prec@1 91.000 (93.515) Prec@5 99.000 (99.879) +2022-11-14 14:29:55,704 Epoch: [206][330/500] Time 0.040 (0.038) Data 0.001 (0.002) Loss 0.0329 (0.0374) Prec@1 94.000 (93.529) Prec@5 100.000 (99.882) +2022-11-14 14:29:56,136 Epoch: [206][340/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0371 (0.0374) Prec@1 92.000 (93.486) Prec@5 100.000 (99.886) +2022-11-14 14:29:56,567 Epoch: [206][350/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0412 (0.0375) Prec@1 95.000 (93.528) Prec@5 99.000 (99.861) +2022-11-14 14:29:57,012 Epoch: [206][360/500] Time 0.044 (0.038) Data 0.001 (0.002) Loss 0.0376 (0.0375) Prec@1 94.000 (93.541) Prec@5 100.000 (99.865) +2022-11-14 14:29:57,451 Epoch: [206][370/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0466 (0.0378) Prec@1 92.000 (93.500) Prec@5 100.000 (99.868) +2022-11-14 14:29:57,881 Epoch: [206][380/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0413 (0.0379) Prec@1 94.000 (93.513) Prec@5 98.000 (99.821) +2022-11-14 14:29:58,322 Epoch: [206][390/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0354 (0.0378) Prec@1 94.000 (93.525) Prec@5 99.000 (99.800) +2022-11-14 14:29:58,755 Epoch: [206][400/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0328 (0.0377) Prec@1 96.000 (93.585) Prec@5 100.000 (99.805) +2022-11-14 14:29:59,192 Epoch: [206][410/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0502 (0.0380) Prec@1 93.000 (93.571) Prec@5 100.000 (99.810) +2022-11-14 14:29:59,622 Epoch: [206][420/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0429 (0.0381) Prec@1 92.000 (93.535) Prec@5 100.000 (99.814) +2022-11-14 14:30:00,071 Epoch: [206][430/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0341 (0.0380) Prec@1 95.000 (93.568) Prec@5 100.000 (99.818) +2022-11-14 14:30:00,501 Epoch: [206][440/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0491 (0.0383) Prec@1 92.000 (93.533) Prec@5 99.000 (99.800) +2022-11-14 14:30:00,931 Epoch: [206][450/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0401 (0.0383) Prec@1 93.000 (93.522) Prec@5 100.000 (99.804) +2022-11-14 14:30:01,360 Epoch: [206][460/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0230 (0.0380) Prec@1 98.000 (93.617) Prec@5 100.000 (99.809) +2022-11-14 14:30:01,787 Epoch: [206][470/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0470 (0.0382) Prec@1 92.000 (93.583) Prec@5 100.000 (99.812) +2022-11-14 14:30:02,208 Epoch: [206][480/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0418 (0.0382) Prec@1 92.000 (93.551) Prec@5 100.000 (99.816) +2022-11-14 14:30:02,637 Epoch: [206][490/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0346 (0.0382) Prec@1 96.000 (93.600) Prec@5 100.000 (99.820) +2022-11-14 14:30:03,024 Epoch: [206][499/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0474 (0.0383) Prec@1 93.000 (93.588) Prec@5 100.000 (99.824) +2022-11-14 14:30:03,304 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0533 (0.0533) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:03,313 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0654 (0.0593) Prec@1 90.000 (91.500) Prec@5 99.000 (99.500) +2022-11-14 14:30:03,322 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0648) Prec@1 90.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:30:03,334 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0718) Prec@1 85.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:30:03,343 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0719) Prec@1 90.000 (89.600) Prec@5 100.000 (99.600) +2022-11-14 14:30:03,353 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0344 (0.0657) Prec@1 93.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 14:30:03,363 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0645) Prec@1 91.000 (90.286) Prec@5 100.000 (99.714) +2022-11-14 14:30:03,374 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0692) Prec@1 83.000 (89.375) Prec@5 100.000 (99.750) +2022-11-14 14:30:03,382 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0702) Prec@1 89.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 14:30:03,392 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0716) Prec@1 86.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 14:30:03,403 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0710) Prec@1 88.000 (88.909) Prec@5 100.000 (99.636) +2022-11-14 14:30:03,412 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0722) Prec@1 87.000 (88.750) Prec@5 99.000 (99.583) +2022-11-14 14:30:03,421 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0718) Prec@1 90.000 (88.846) Prec@5 99.000 (99.538) +2022-11-14 14:30:03,431 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0719) Prec@1 88.000 (88.786) Prec@5 100.000 (99.571) +2022-11-14 14:30:03,441 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0723) Prec@1 87.000 (88.667) Prec@5 99.000 (99.533) +2022-11-14 14:30:03,450 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0730) Prec@1 85.000 (88.438) Prec@5 99.000 (99.500) +2022-11-14 14:30:03,459 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0726) Prec@1 90.000 (88.529) Prec@5 98.000 (99.412) +2022-11-14 14:30:03,468 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0742) Prec@1 86.000 (88.389) Prec@5 98.000 (99.333) +2022-11-14 14:30:03,478 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0752) Prec@1 85.000 (88.211) Prec@5 98.000 (99.263) +2022-11-14 14:30:03,487 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0753) Prec@1 88.000 (88.200) Prec@5 98.000 (99.200) +2022-11-14 14:30:03,496 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0759) Prec@1 86.000 (88.095) Prec@5 99.000 (99.190) +2022-11-14 14:30:03,505 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0761) Prec@1 86.000 (88.000) Prec@5 99.000 (99.182) +2022-11-14 14:30:03,515 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0772) Prec@1 84.000 (87.826) Prec@5 99.000 (99.174) +2022-11-14 14:30:03,525 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0775) Prec@1 86.000 (87.750) Prec@5 100.000 (99.208) +2022-11-14 14:30:03,533 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0779) Prec@1 86.000 (87.680) Prec@5 100.000 (99.240) +2022-11-14 14:30:03,542 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0786) Prec@1 83.000 (87.500) Prec@5 99.000 (99.231) +2022-11-14 14:30:03,552 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0784) Prec@1 87.000 (87.481) Prec@5 100.000 (99.259) +2022-11-14 14:30:03,561 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0777) Prec@1 89.000 (87.536) Prec@5 99.000 (99.250) +2022-11-14 14:30:03,571 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0772) Prec@1 90.000 (87.621) Prec@5 99.000 (99.241) +2022-11-14 14:30:03,580 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0774) Prec@1 88.000 (87.633) Prec@5 100.000 (99.267) +2022-11-14 14:30:03,590 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0778) Prec@1 84.000 (87.516) Prec@5 100.000 (99.290) +2022-11-14 14:30:03,600 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0776) Prec@1 87.000 (87.500) Prec@5 100.000 (99.312) +2022-11-14 14:30:03,609 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0777) Prec@1 87.000 (87.485) Prec@5 98.000 (99.273) +2022-11-14 14:30:03,618 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0785) Prec@1 78.000 (87.206) Prec@5 100.000 (99.294) +2022-11-14 14:30:03,628 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0786) Prec@1 87.000 (87.200) Prec@5 97.000 (99.229) +2022-11-14 14:30:03,637 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0784) Prec@1 89.000 (87.250) Prec@5 99.000 (99.222) +2022-11-14 14:30:03,646 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0784) Prec@1 88.000 (87.270) Prec@5 99.000 (99.216) +2022-11-14 14:30:03,656 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0792) Prec@1 84.000 (87.184) Prec@5 100.000 (99.237) +2022-11-14 14:30:03,665 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0786) Prec@1 92.000 (87.308) Prec@5 99.000 (99.231) +2022-11-14 14:30:03,675 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0781) Prec@1 89.000 (87.350) Prec@5 99.000 (99.225) +2022-11-14 14:30:03,684 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0782) Prec@1 86.000 (87.317) Prec@5 98.000 (99.195) +2022-11-14 14:30:03,693 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0781) Prec@1 88.000 (87.333) Prec@5 99.000 (99.190) +2022-11-14 14:30:03,702 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0773) Prec@1 92.000 (87.442) Prec@5 99.000 (99.186) +2022-11-14 14:30:03,710 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0771) Prec@1 89.000 (87.477) Prec@5 100.000 (99.205) +2022-11-14 14:30:03,719 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0767) Prec@1 90.000 (87.533) Prec@5 99.000 (99.200) +2022-11-14 14:30:03,729 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0770) Prec@1 85.000 (87.478) Prec@5 99.000 (99.196) +2022-11-14 14:30:03,737 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0768) Prec@1 87.000 (87.468) Prec@5 100.000 (99.213) +2022-11-14 14:30:03,747 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0772) Prec@1 86.000 (87.438) Prec@5 96.000 (99.146) +2022-11-14 14:30:03,756 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0768) Prec@1 89.000 (87.469) Prec@5 100.000 (99.163) +2022-11-14 14:30:03,765 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0773) Prec@1 85.000 (87.420) Prec@5 99.000 (99.160) +2022-11-14 14:30:03,774 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0771) Prec@1 89.000 (87.451) Prec@5 100.000 (99.176) +2022-11-14 14:30:03,784 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0774) Prec@1 83.000 (87.365) Prec@5 100.000 (99.192) +2022-11-14 14:30:03,792 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0771) Prec@1 90.000 (87.415) Prec@5 99.000 (99.189) +2022-11-14 14:30:03,802 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0771) Prec@1 85.000 (87.370) Prec@5 98.000 (99.167) +2022-11-14 14:30:03,811 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0776) Prec@1 81.000 (87.255) Prec@5 100.000 (99.182) +2022-11-14 14:30:03,820 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0775) Prec@1 88.000 (87.268) Prec@5 99.000 (99.179) +2022-11-14 14:30:03,830 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0773) Prec@1 88.000 (87.281) Prec@5 100.000 (99.193) +2022-11-14 14:30:03,840 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0769) Prec@1 91.000 (87.345) Prec@5 100.000 (99.207) +2022-11-14 14:30:03,849 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0771) Prec@1 85.000 (87.305) Prec@5 99.000 (99.203) +2022-11-14 14:30:03,858 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0770) Prec@1 87.000 (87.300) Prec@5 99.000 (99.200) +2022-11-14 14:30:03,868 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0771) Prec@1 84.000 (87.246) Prec@5 100.000 (99.213) +2022-11-14 14:30:03,877 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0768) Prec@1 91.000 (87.306) Prec@5 100.000 (99.226) +2022-11-14 14:30:03,886 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0765) Prec@1 91.000 (87.365) Prec@5 100.000 (99.238) +2022-11-14 14:30:03,895 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0763) Prec@1 91.000 (87.422) Prec@5 99.000 (99.234) +2022-11-14 14:30:03,904 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0766) Prec@1 84.000 (87.369) Prec@5 100.000 (99.246) +2022-11-14 14:30:03,913 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0763) Prec@1 90.000 (87.409) Prec@5 100.000 (99.258) +2022-11-14 14:30:03,922 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0760) Prec@1 92.000 (87.478) Prec@5 100.000 (99.269) +2022-11-14 14:30:03,931 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0758) Prec@1 91.000 (87.529) Prec@5 98.000 (99.250) +2022-11-14 14:30:03,941 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0755) Prec@1 91.000 (87.580) Prec@5 100.000 (99.261) +2022-11-14 14:30:03,950 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0754) Prec@1 90.000 (87.614) Prec@5 100.000 (99.271) +2022-11-14 14:30:03,958 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0755) Prec@1 88.000 (87.620) Prec@5 98.000 (99.254) +2022-11-14 14:30:03,969 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0757) Prec@1 86.000 (87.597) Prec@5 100.000 (99.264) +2022-11-14 14:30:03,978 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0755) Prec@1 90.000 (87.630) Prec@5 100.000 (99.274) +2022-11-14 14:30:03,986 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0751) Prec@1 95.000 (87.730) Prec@5 100.000 (99.284) +2022-11-14 14:30:03,994 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1351 (0.0759) Prec@1 79.000 (87.613) Prec@5 100.000 (99.293) +2022-11-14 14:30:04,004 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0761) Prec@1 85.000 (87.579) Prec@5 98.000 (99.276) +2022-11-14 14:30:04,013 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0759) Prec@1 88.000 (87.584) Prec@5 98.000 (99.260) +2022-11-14 14:30:04,021 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0764) Prec@1 83.000 (87.526) Prec@5 98.000 (99.244) +2022-11-14 14:30:04,031 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0763) Prec@1 87.000 (87.519) Prec@5 100.000 (99.253) +2022-11-14 14:30:04,040 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0761) Prec@1 88.000 (87.525) Prec@5 100.000 (99.263) +2022-11-14 14:30:04,049 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0761) Prec@1 88.000 (87.531) Prec@5 99.000 (99.259) +2022-11-14 14:30:04,058 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0762) Prec@1 87.000 (87.524) Prec@5 100.000 (99.268) +2022-11-14 14:30:04,068 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0762) Prec@1 87.000 (87.518) Prec@5 99.000 (99.265) +2022-11-14 14:30:04,077 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0760) Prec@1 91.000 (87.560) Prec@5 100.000 (99.274) +2022-11-14 14:30:04,086 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0763) Prec@1 80.000 (87.471) Prec@5 100.000 (99.282) +2022-11-14 14:30:04,095 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0766) Prec@1 85.000 (87.442) Prec@5 100.000 (99.291) +2022-11-14 14:30:04,104 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0765) Prec@1 90.000 (87.471) Prec@5 99.000 (99.287) +2022-11-14 14:30:04,114 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0765) Prec@1 89.000 (87.489) Prec@5 99.000 (99.284) +2022-11-14 14:30:04,123 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0763) Prec@1 89.000 (87.506) Prec@5 99.000 (99.281) +2022-11-14 14:30:04,132 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0763) Prec@1 88.000 (87.511) Prec@5 98.000 (99.267) +2022-11-14 14:30:04,140 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0762) Prec@1 89.000 (87.527) Prec@5 100.000 (99.275) +2022-11-14 14:30:04,150 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0759) Prec@1 92.000 (87.576) Prec@5 100.000 (99.283) +2022-11-14 14:30:04,158 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0760) Prec@1 85.000 (87.548) Prec@5 100.000 (99.290) +2022-11-14 14:30:04,167 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 87.000 (87.543) Prec@5 99.000 (99.287) +2022-11-14 14:30:04,176 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0761) Prec@1 89.000 (87.558) Prec@5 99.000 (99.284) +2022-11-14 14:30:04,185 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0759) Prec@1 89.000 (87.573) Prec@5 100.000 (99.292) +2022-11-14 14:30:04,194 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0757) Prec@1 92.000 (87.619) Prec@5 99.000 (99.289) +2022-11-14 14:30:04,203 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0760) Prec@1 81.000 (87.551) Prec@5 98.000 (99.276) +2022-11-14 14:30:04,212 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0761) Prec@1 88.000 (87.556) Prec@5 100.000 (99.283) +2022-11-14 14:30:04,220 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0760) Prec@1 88.000 (87.560) Prec@5 99.000 (99.280) +2022-11-14 14:30:04,275 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:30:04,592 Epoch: [207][0/500] Time 0.023 (0.023) Data 0.234 (0.234) Loss 0.0425 (0.0425) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:04,800 Epoch: [207][10/500] Time 0.018 (0.019) Data 0.002 (0.023) Loss 0.0435 (0.0430) Prec@1 92.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:30:05,004 Epoch: [207][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0330 (0.0396) Prec@1 95.000 (93.333) Prec@5 100.000 (99.667) +2022-11-14 14:30:05,211 Epoch: [207][30/500] Time 0.020 (0.018) Data 0.001 (0.009) Loss 0.0331 (0.0380) Prec@1 95.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:30:05,468 Epoch: [207][40/500] Time 0.024 (0.019) Data 0.002 (0.007) Loss 0.0213 (0.0347) Prec@1 97.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:30:05,729 Epoch: [207][50/500] Time 0.024 (0.020) Data 0.002 (0.006) Loss 0.0508 (0.0373) Prec@1 92.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 14:30:05,994 Epoch: [207][60/500] Time 0.027 (0.021) Data 0.002 (0.006) Loss 0.0414 (0.0379) Prec@1 93.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 14:30:06,254 Epoch: [207][70/500] Time 0.025 (0.021) Data 0.001 (0.005) Loss 0.0477 (0.0391) Prec@1 91.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 14:30:06,521 Epoch: [207][80/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0430 (0.0396) Prec@1 92.000 (93.333) Prec@5 100.000 (99.889) +2022-11-14 14:30:06,786 Epoch: [207][90/500] Time 0.025 (0.021) Data 0.002 (0.004) Loss 0.0324 (0.0389) Prec@1 96.000 (93.600) Prec@5 100.000 (99.900) +2022-11-14 14:30:07,061 Epoch: [207][100/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0218 (0.0373) Prec@1 95.000 (93.727) Prec@5 100.000 (99.909) +2022-11-14 14:30:07,319 Epoch: [207][110/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0611 (0.0393) Prec@1 88.000 (93.250) Prec@5 100.000 (99.917) +2022-11-14 14:30:07,580 Epoch: [207][120/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0194 (0.0378) Prec@1 98.000 (93.615) Prec@5 100.000 (99.923) +2022-11-14 14:30:08,015 Epoch: [207][130/500] Time 0.047 (0.023) Data 0.002 (0.004) Loss 0.0391 (0.0379) Prec@1 95.000 (93.714) Prec@5 100.000 (99.929) +2022-11-14 14:30:08,477 Epoch: [207][140/500] Time 0.044 (0.024) Data 0.002 (0.003) Loss 0.0577 (0.0392) Prec@1 91.000 (93.533) Prec@5 99.000 (99.867) +2022-11-14 14:30:08,941 Epoch: [207][150/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.0459 (0.0396) Prec@1 93.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 14:30:09,408 Epoch: [207][160/500] Time 0.045 (0.027) Data 0.001 (0.003) Loss 0.0483 (0.0401) Prec@1 90.000 (93.294) Prec@5 99.000 (99.824) +2022-11-14 14:30:09,875 Epoch: [207][170/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0350 (0.0398) Prec@1 94.000 (93.333) Prec@5 99.000 (99.778) +2022-11-14 14:30:10,345 Epoch: [207][180/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0214 (0.0389) Prec@1 97.000 (93.526) Prec@5 99.000 (99.737) +2022-11-14 14:30:10,809 Epoch: [207][190/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0204 (0.0379) Prec@1 96.000 (93.650) Prec@5 100.000 (99.750) +2022-11-14 14:30:11,280 Epoch: [207][200/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0307 (0.0376) Prec@1 94.000 (93.667) Prec@5 100.000 (99.762) +2022-11-14 14:30:11,744 Epoch: [207][210/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0477 (0.0381) Prec@1 92.000 (93.591) Prec@5 100.000 (99.773) +2022-11-14 14:30:12,215 Epoch: [207][220/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0266 (0.0376) Prec@1 97.000 (93.739) Prec@5 100.000 (99.783) +2022-11-14 14:30:12,676 Epoch: [207][230/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0382 (0.0376) Prec@1 92.000 (93.667) Prec@5 100.000 (99.792) +2022-11-14 14:30:13,148 Epoch: [207][240/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0415 (0.0377) Prec@1 93.000 (93.640) Prec@5 100.000 (99.800) +2022-11-14 14:30:13,610 Epoch: [207][250/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0565 (0.0385) Prec@1 89.000 (93.462) Prec@5 100.000 (99.808) +2022-11-14 14:30:14,082 Epoch: [207][260/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0307 (0.0382) Prec@1 94.000 (93.481) Prec@5 100.000 (99.815) +2022-11-14 14:30:14,545 Epoch: [207][270/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0497 (0.0386) Prec@1 91.000 (93.393) Prec@5 100.000 (99.821) +2022-11-14 14:30:15,017 Epoch: [207][280/500] Time 0.048 (0.033) Data 0.002 (0.003) Loss 0.0370 (0.0385) Prec@1 93.000 (93.379) Prec@5 100.000 (99.828) +2022-11-14 14:30:15,480 Epoch: [207][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0217 (0.0380) Prec@1 96.000 (93.467) Prec@5 100.000 (99.833) +2022-11-14 14:30:15,943 Epoch: [207][300/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0761 (0.0392) Prec@1 87.000 (93.258) Prec@5 100.000 (99.839) +2022-11-14 14:30:16,282 Epoch: [207][310/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.0350 (0.0391) Prec@1 92.000 (93.219) Prec@5 100.000 (99.844) +2022-11-14 14:30:16,585 Epoch: [207][320/500] Time 0.027 (0.033) Data 0.002 (0.003) Loss 0.0399 (0.0391) Prec@1 93.000 (93.212) Prec@5 99.000 (99.818) +2022-11-14 14:30:16,891 Epoch: [207][330/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.0460 (0.0393) Prec@1 93.000 (93.206) Prec@5 100.000 (99.824) +2022-11-14 14:30:17,193 Epoch: [207][340/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.0432 (0.0394) Prec@1 93.000 (93.200) Prec@5 100.000 (99.829) +2022-11-14 14:30:17,495 Epoch: [207][350/500] Time 0.030 (0.033) Data 0.001 (0.002) Loss 0.0356 (0.0393) Prec@1 95.000 (93.250) Prec@5 100.000 (99.833) +2022-11-14 14:30:17,800 Epoch: [207][360/500] Time 0.028 (0.033) Data 0.001 (0.002) Loss 0.0476 (0.0395) Prec@1 93.000 (93.243) Prec@5 99.000 (99.811) +2022-11-14 14:30:18,106 Epoch: [207][370/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0467 (0.0397) Prec@1 91.000 (93.184) Prec@5 100.000 (99.816) +2022-11-14 14:30:18,410 Epoch: [207][380/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.0444 (0.0398) Prec@1 93.000 (93.179) Prec@5 100.000 (99.821) +2022-11-14 14:30:18,713 Epoch: [207][390/500] Time 0.027 (0.032) Data 0.002 (0.002) Loss 0.0459 (0.0400) Prec@1 93.000 (93.175) Prec@5 99.000 (99.800) +2022-11-14 14:30:19,025 Epoch: [207][400/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.0375 (0.0399) Prec@1 94.000 (93.195) Prec@5 99.000 (99.780) +2022-11-14 14:30:19,326 Epoch: [207][410/500] Time 0.028 (0.032) Data 0.002 (0.002) Loss 0.0457 (0.0401) Prec@1 93.000 (93.190) Prec@5 100.000 (99.786) +2022-11-14 14:30:19,634 Epoch: [207][420/500] Time 0.029 (0.032) Data 0.002 (0.002) Loss 0.0479 (0.0402) Prec@1 91.000 (93.140) Prec@5 100.000 (99.791) +2022-11-14 14:30:19,934 Epoch: [207][430/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0349 (0.0401) Prec@1 94.000 (93.159) Prec@5 100.000 (99.795) +2022-11-14 14:30:20,243 Epoch: [207][440/500] Time 0.029 (0.032) Data 0.001 (0.002) Loss 0.0465 (0.0403) Prec@1 91.000 (93.111) Prec@5 100.000 (99.800) +2022-11-14 14:30:20,544 Epoch: [207][450/500] Time 0.027 (0.031) Data 0.002 (0.002) Loss 0.0541 (0.0406) Prec@1 90.000 (93.043) Prec@5 99.000 (99.783) +2022-11-14 14:30:20,851 Epoch: [207][460/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0342 (0.0404) Prec@1 94.000 (93.064) Prec@5 100.000 (99.787) +2022-11-14 14:30:21,153 Epoch: [207][470/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0434 (0.0405) Prec@1 92.000 (93.042) Prec@5 100.000 (99.792) +2022-11-14 14:30:21,460 Epoch: [207][480/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0373 (0.0404) Prec@1 92.000 (93.020) Prec@5 100.000 (99.796) +2022-11-14 14:30:21,763 Epoch: [207][490/500] Time 0.028 (0.031) Data 0.002 (0.002) Loss 0.0405 (0.0404) Prec@1 93.000 (93.020) Prec@5 100.000 (99.800) +2022-11-14 14:30:22,043 Epoch: [207][499/500] Time 0.026 (0.031) Data 0.002 (0.002) Loss 0.0432 (0.0405) Prec@1 94.000 (93.039) Prec@5 99.000 (99.784) +2022-11-14 14:30:22,325 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0598 (0.0598) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:22,332 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0564) Prec@1 92.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:22,340 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0608) Prec@1 87.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 14:30:22,351 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0627) Prec@1 89.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 14:30:22,359 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0670) Prec@1 86.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 14:30:22,368 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0645) Prec@1 92.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 14:30:22,376 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0631) Prec@1 90.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 14:30:22,387 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0647) Prec@1 87.000 (89.125) Prec@5 99.000 (99.750) +2022-11-14 14:30:22,396 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0659) Prec@1 91.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 14:30:22,404 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0676) Prec@1 87.000 (89.100) Prec@5 99.000 (99.600) +2022-11-14 14:30:22,415 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0669) Prec@1 90.000 (89.182) Prec@5 100.000 (99.636) +2022-11-14 14:30:22,425 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0686) Prec@1 86.000 (88.917) Prec@5 100.000 (99.667) +2022-11-14 14:30:22,436 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0680) Prec@1 91.000 (89.077) Prec@5 100.000 (99.692) +2022-11-14 14:30:22,446 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0672) Prec@1 90.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 14:30:22,457 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0672) Prec@1 91.000 (89.267) Prec@5 100.000 (99.733) +2022-11-14 14:30:22,467 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0679) Prec@1 88.000 (89.188) Prec@5 98.000 (99.625) +2022-11-14 14:30:22,476 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0327 (0.0659) Prec@1 95.000 (89.529) Prec@5 99.000 (99.588) +2022-11-14 14:30:22,485 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1131 (0.0685) Prec@1 82.000 (89.111) Prec@5 99.000 (99.556) +2022-11-14 14:30:22,494 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0689) Prec@1 85.000 (88.895) Prec@5 100.000 (99.579) +2022-11-14 14:30:22,503 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0705) Prec@1 83.000 (88.600) Prec@5 100.000 (99.600) +2022-11-14 14:30:22,515 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0707) Prec@1 87.000 (88.524) Prec@5 100.000 (99.619) +2022-11-14 14:30:22,526 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0710) Prec@1 86.000 (88.409) Prec@5 99.000 (99.591) +2022-11-14 14:30:22,538 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0720) Prec@1 86.000 (88.304) Prec@5 98.000 (99.522) +2022-11-14 14:30:22,550 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0718) Prec@1 85.000 (88.167) Prec@5 100.000 (99.542) +2022-11-14 14:30:22,562 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0723) Prec@1 86.000 (88.080) Prec@5 99.000 (99.520) +2022-11-14 14:30:22,572 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0730) Prec@1 87.000 (88.038) Prec@5 99.000 (99.500) +2022-11-14 14:30:22,584 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0723) Prec@1 90.000 (88.111) Prec@5 100.000 (99.519) +2022-11-14 14:30:22,596 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0726) Prec@1 86.000 (88.036) Prec@5 100.000 (99.536) +2022-11-14 14:30:22,607 Test: [28/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0722) Prec@1 91.000 (88.138) Prec@5 98.000 (99.483) +2022-11-14 14:30:22,619 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0715) Prec@1 90.000 (88.200) Prec@5 100.000 (99.500) +2022-11-14 14:30:22,630 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0719) Prec@1 86.000 (88.129) Prec@5 100.000 (99.516) +2022-11-14 14:30:22,641 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0723) Prec@1 86.000 (88.062) Prec@5 97.000 (99.438) +2022-11-14 14:30:22,653 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0724) Prec@1 85.000 (87.970) Prec@5 100.000 (99.455) +2022-11-14 14:30:22,664 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0733) Prec@1 83.000 (87.824) Prec@5 99.000 (99.441) +2022-11-14 14:30:22,673 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0737) Prec@1 87.000 (87.800) Prec@5 98.000 (99.400) +2022-11-14 14:30:22,684 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0737) Prec@1 90.000 (87.861) Prec@5 100.000 (99.417) +2022-11-14 14:30:22,693 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0736) Prec@1 90.000 (87.919) Prec@5 99.000 (99.405) +2022-11-14 14:30:22,704 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0742) Prec@1 86.000 (87.868) Prec@5 100.000 (99.421) +2022-11-14 14:30:22,715 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0737) Prec@1 91.000 (87.949) Prec@5 100.000 (99.436) +2022-11-14 14:30:22,727 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0404 (0.0729) Prec@1 94.000 (88.100) Prec@5 99.000 (99.425) +2022-11-14 14:30:22,738 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0734) Prec@1 84.000 (88.000) Prec@5 98.000 (99.390) +2022-11-14 14:30:22,750 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0731) Prec@1 91.000 (88.071) Prec@5 98.000 (99.357) +2022-11-14 14:30:22,762 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0726) Prec@1 90.000 (88.116) Prec@5 100.000 (99.372) +2022-11-14 14:30:22,773 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0726) Prec@1 86.000 (88.068) Prec@5 99.000 (99.364) +2022-11-14 14:30:22,785 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0724) Prec@1 91.000 (88.133) Prec@5 100.000 (99.378) +2022-11-14 14:30:22,796 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0726) Prec@1 86.000 (88.087) Prec@5 100.000 (99.391) +2022-11-14 14:30:22,807 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0725) Prec@1 88.000 (88.085) Prec@5 99.000 (99.383) +2022-11-14 14:30:22,819 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0731) Prec@1 83.000 (87.979) Prec@5 100.000 (99.396) +2022-11-14 14:30:22,831 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0344 (0.0723) Prec@1 93.000 (88.082) Prec@5 99.000 (99.388) +2022-11-14 14:30:22,841 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0725) Prec@1 87.000 (88.060) Prec@5 100.000 (99.400) +2022-11-14 14:30:22,852 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0725) Prec@1 87.000 (88.039) Prec@5 99.000 (99.392) +2022-11-14 14:30:22,862 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0730) Prec@1 83.000 (87.942) Prec@5 100.000 (99.404) +2022-11-14 14:30:22,873 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0728) Prec@1 89.000 (87.962) Prec@5 100.000 (99.415) +2022-11-14 14:30:22,884 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0725) Prec@1 88.000 (87.963) Prec@5 100.000 (99.426) +2022-11-14 14:30:22,895 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0727) Prec@1 89.000 (87.982) Prec@5 99.000 (99.418) +2022-11-14 14:30:22,906 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0726) Prec@1 90.000 (88.018) Prec@5 99.000 (99.411) +2022-11-14 14:30:22,916 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0725) Prec@1 90.000 (88.053) Prec@5 100.000 (99.421) +2022-11-14 14:30:22,927 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0723) Prec@1 91.000 (88.103) Prec@5 100.000 (99.431) +2022-11-14 14:30:22,938 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0727) Prec@1 83.000 (88.017) Prec@5 100.000 (99.441) +2022-11-14 14:30:22,949 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0731) Prec@1 85.000 (87.967) Prec@5 100.000 (99.450) +2022-11-14 14:30:22,960 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0730) Prec@1 90.000 (88.000) Prec@5 99.000 (99.443) +2022-11-14 14:30:22,974 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0730) Prec@1 87.000 (87.984) Prec@5 100.000 (99.452) +2022-11-14 14:30:22,985 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0731) Prec@1 88.000 (87.984) Prec@5 100.000 (99.460) +2022-11-14 14:30:22,995 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0726) Prec@1 94.000 (88.078) Prec@5 100.000 (99.469) +2022-11-14 14:30:23,006 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0727) Prec@1 88.000 (88.077) Prec@5 100.000 (99.477) +2022-11-14 14:30:23,018 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0731) Prec@1 85.000 (88.030) Prec@5 99.000 (99.470) +2022-11-14 14:30:23,027 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0459 (0.0727) Prec@1 92.000 (88.090) Prec@5 100.000 (99.478) +2022-11-14 14:30:23,037 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0728) Prec@1 86.000 (88.059) Prec@5 100.000 (99.485) +2022-11-14 14:30:23,049 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0729) Prec@1 88.000 (88.058) Prec@5 99.000 (99.478) +2022-11-14 14:30:23,060 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0732) Prec@1 83.000 (87.986) Prec@5 98.000 (99.457) +2022-11-14 14:30:23,070 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0735) Prec@1 85.000 (87.944) Prec@5 100.000 (99.465) +2022-11-14 14:30:23,082 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0735) Prec@1 89.000 (87.958) Prec@5 100.000 (99.472) +2022-11-14 14:30:23,091 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0733) Prec@1 90.000 (87.986) Prec@5 100.000 (99.479) +2022-11-14 14:30:23,103 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0730) Prec@1 93.000 (88.054) Prec@5 100.000 (99.486) +2022-11-14 14:30:23,113 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0731) Prec@1 85.000 (88.013) Prec@5 99.000 (99.480) +2022-11-14 14:30:23,124 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0730) Prec@1 86.000 (87.987) Prec@5 100.000 (99.487) +2022-11-14 14:30:23,136 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0727) Prec@1 92.000 (88.039) Prec@5 99.000 (99.481) +2022-11-14 14:30:23,145 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0728) Prec@1 88.000 (88.038) Prec@5 97.000 (99.449) +2022-11-14 14:30:23,156 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0724) Prec@1 92.000 (88.089) Prec@5 100.000 (99.456) +2022-11-14 14:30:23,167 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0722) Prec@1 91.000 (88.125) Prec@5 99.000 (99.450) +2022-11-14 14:30:23,177 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0722) Prec@1 88.000 (88.123) Prec@5 98.000 (99.432) +2022-11-14 14:30:23,186 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0723) Prec@1 86.000 (88.098) Prec@5 100.000 (99.439) +2022-11-14 14:30:23,196 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0723) Prec@1 87.000 (88.084) Prec@5 99.000 (99.434) +2022-11-14 14:30:23,208 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0723) Prec@1 87.000 (88.071) Prec@5 100.000 (99.440) +2022-11-14 14:30:23,220 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0724) Prec@1 89.000 (88.082) Prec@5 100.000 (99.447) +2022-11-14 14:30:23,232 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0727) Prec@1 83.000 (88.023) Prec@5 100.000 (99.453) +2022-11-14 14:30:23,243 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0726) Prec@1 89.000 (88.034) Prec@5 99.000 (99.448) +2022-11-14 14:30:23,254 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0725) Prec@1 88.000 (88.034) Prec@5 100.000 (99.455) +2022-11-14 14:30:23,264 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0726) Prec@1 88.000 (88.034) Prec@5 98.000 (99.438) +2022-11-14 14:30:23,275 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0726) Prec@1 87.000 (88.022) Prec@5 99.000 (99.433) +2022-11-14 14:30:23,286 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0723) Prec@1 90.000 (88.044) Prec@5 100.000 (99.440) +2022-11-14 14:30:23,299 Test: [91/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0722) Prec@1 90.000 (88.065) Prec@5 99.000 (99.435) +2022-11-14 14:30:23,311 Test: [92/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0724) Prec@1 85.000 (88.032) Prec@5 99.000 (99.430) +2022-11-14 14:30:23,322 Test: [93/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0723) Prec@1 90.000 (88.053) Prec@5 99.000 (99.426) +2022-11-14 14:30:23,333 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0726) Prec@1 83.000 (88.000) Prec@5 99.000 (99.421) +2022-11-14 14:30:23,344 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0725) Prec@1 90.000 (88.021) Prec@5 100.000 (99.427) +2022-11-14 14:30:23,356 Test: [96/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0420 (0.0722) Prec@1 92.000 (88.062) Prec@5 100.000 (99.433) +2022-11-14 14:30:23,367 Test: [97/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0724) Prec@1 84.000 (88.020) Prec@5 98.000 (99.418) +2022-11-14 14:30:23,377 Test: [98/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0727) Prec@1 86.000 (88.000) Prec@5 100.000 (99.424) +2022-11-14 14:30:23,388 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0727) Prec@1 85.000 (87.970) Prec@5 99.000 (99.420) +2022-11-14 14:30:23,448 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:30:23,766 Epoch: [208][0/500] Time 0.023 (0.023) Data 0.215 (0.215) Loss 0.0293 (0.0293) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:23,979 Epoch: [208][10/500] Time 0.021 (0.019) Data 0.002 (0.021) Loss 0.0323 (0.0308) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 14:30:24,189 Epoch: [208][20/500] Time 0.021 (0.019) Data 0.002 (0.012) Loss 0.0259 (0.0292) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:24,488 Epoch: [208][30/500] Time 0.035 (0.021) Data 0.002 (0.009) Loss 0.0343 (0.0305) Prec@1 95.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 14:30:24,954 Epoch: [208][40/500] Time 0.043 (0.026) Data 0.002 (0.007) Loss 0.0355 (0.0315) Prec@1 92.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 14:30:25,420 Epoch: [208][50/500] Time 0.044 (0.029) Data 0.002 (0.006) Loss 0.0441 (0.0336) Prec@1 93.000 (94.667) Prec@5 99.000 (99.667) +2022-11-14 14:30:25,881 Epoch: [208][60/500] Time 0.043 (0.031) Data 0.001 (0.005) Loss 0.0519 (0.0362) Prec@1 92.000 (94.286) Prec@5 99.000 (99.571) +2022-11-14 14:30:26,354 Epoch: [208][70/500] Time 0.045 (0.032) Data 0.002 (0.005) Loss 0.0367 (0.0362) Prec@1 93.000 (94.125) Prec@5 100.000 (99.625) +2022-11-14 14:30:26,817 Epoch: [208][80/500] Time 0.044 (0.034) Data 0.002 (0.004) Loss 0.0357 (0.0362) Prec@1 95.000 (94.222) Prec@5 100.000 (99.667) +2022-11-14 14:30:27,289 Epoch: [208][90/500] Time 0.044 (0.034) Data 0.002 (0.004) Loss 0.0346 (0.0360) Prec@1 93.000 (94.100) Prec@5 99.000 (99.600) +2022-11-14 14:30:27,753 Epoch: [208][100/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0281 (0.0353) Prec@1 95.000 (94.182) Prec@5 100.000 (99.636) +2022-11-14 14:30:28,226 Epoch: [208][110/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0228 (0.0343) Prec@1 94.000 (94.167) Prec@5 100.000 (99.667) +2022-11-14 14:30:28,689 Epoch: [208][120/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0442 (0.0350) Prec@1 93.000 (94.077) Prec@5 100.000 (99.692) +2022-11-14 14:30:29,163 Epoch: [208][130/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0435 (0.0356) Prec@1 92.000 (93.929) Prec@5 100.000 (99.714) +2022-11-14 14:30:29,625 Epoch: [208][140/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0441 (0.0362) Prec@1 92.000 (93.800) Prec@5 100.000 (99.733) +2022-11-14 14:30:30,097 Epoch: [208][150/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0666 (0.0381) Prec@1 86.000 (93.312) Prec@5 100.000 (99.750) +2022-11-14 14:30:30,561 Epoch: [208][160/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0303 (0.0376) Prec@1 96.000 (93.471) Prec@5 100.000 (99.765) +2022-11-14 14:30:31,032 Epoch: [208][170/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0434 (0.0380) Prec@1 93.000 (93.444) Prec@5 100.000 (99.778) +2022-11-14 14:30:31,496 Epoch: [208][180/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0370 (0.0379) Prec@1 95.000 (93.526) Prec@5 100.000 (99.789) +2022-11-14 14:30:31,960 Epoch: [208][190/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0380 (0.0379) Prec@1 93.000 (93.500) Prec@5 100.000 (99.800) +2022-11-14 14:30:32,425 Epoch: [208][200/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0397 (0.0380) Prec@1 94.000 (93.524) Prec@5 100.000 (99.810) +2022-11-14 14:30:32,887 Epoch: [208][210/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0333 (0.0378) Prec@1 94.000 (93.545) Prec@5 100.000 (99.818) +2022-11-14 14:30:33,357 Epoch: [208][220/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0407 (0.0379) Prec@1 95.000 (93.609) Prec@5 100.000 (99.826) +2022-11-14 14:30:33,820 Epoch: [208][230/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0429 (0.0381) Prec@1 94.000 (93.625) Prec@5 100.000 (99.833) +2022-11-14 14:30:34,293 Epoch: [208][240/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0490 (0.0386) Prec@1 93.000 (93.600) Prec@5 100.000 (99.840) +2022-11-14 14:30:34,754 Epoch: [208][250/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0225 (0.0379) Prec@1 97.000 (93.731) Prec@5 100.000 (99.846) +2022-11-14 14:30:35,189 Epoch: [208][260/500] Time 0.033 (0.039) Data 0.001 (0.003) Loss 0.0268 (0.0375) Prec@1 95.000 (93.778) Prec@5 99.000 (99.815) +2022-11-14 14:30:35,500 Epoch: [208][270/500] Time 0.025 (0.039) Data 0.002 (0.003) Loss 0.0379 (0.0375) Prec@1 94.000 (93.786) Prec@5 99.000 (99.786) +2022-11-14 14:30:35,811 Epoch: [208][280/500] Time 0.029 (0.038) Data 0.001 (0.003) Loss 0.0471 (0.0379) Prec@1 92.000 (93.724) Prec@5 100.000 (99.793) +2022-11-14 14:30:36,120 Epoch: [208][290/500] Time 0.025 (0.038) Data 0.002 (0.003) Loss 0.0337 (0.0377) Prec@1 93.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 14:30:36,427 Epoch: [208][300/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.0388 (0.0378) Prec@1 95.000 (93.742) Prec@5 100.000 (99.806) +2022-11-14 14:30:36,734 Epoch: [208][310/500] Time 0.029 (0.037) Data 0.002 (0.003) Loss 0.0530 (0.0383) Prec@1 92.000 (93.688) Prec@5 100.000 (99.812) +2022-11-14 14:30:37,043 Epoch: [208][320/500] Time 0.027 (0.037) Data 0.002 (0.003) Loss 0.0316 (0.0380) Prec@1 94.000 (93.697) Prec@5 100.000 (99.818) +2022-11-14 14:30:37,355 Epoch: [208][330/500] Time 0.029 (0.037) Data 0.002 (0.002) Loss 0.0512 (0.0384) Prec@1 91.000 (93.618) Prec@5 100.000 (99.824) +2022-11-14 14:30:37,663 Epoch: [208][340/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0310 (0.0382) Prec@1 96.000 (93.686) Prec@5 99.000 (99.800) +2022-11-14 14:30:37,971 Epoch: [208][350/500] Time 0.030 (0.036) Data 0.001 (0.002) Loss 0.0487 (0.0385) Prec@1 92.000 (93.639) Prec@5 100.000 (99.806) +2022-11-14 14:30:38,279 Epoch: [208][360/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0589 (0.0391) Prec@1 90.000 (93.541) Prec@5 100.000 (99.811) +2022-11-14 14:30:38,590 Epoch: [208][370/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0585 (0.0396) Prec@1 90.000 (93.447) Prec@5 100.000 (99.816) +2022-11-14 14:30:38,896 Epoch: [208][380/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0475 (0.0398) Prec@1 92.000 (93.410) Prec@5 100.000 (99.821) +2022-11-14 14:30:39,207 Epoch: [208][390/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.0346 (0.0397) Prec@1 93.000 (93.400) Prec@5 100.000 (99.825) +2022-11-14 14:30:39,514 Epoch: [208][400/500] Time 0.028 (0.035) Data 0.001 (0.002) Loss 0.0266 (0.0393) Prec@1 95.000 (93.439) Prec@5 100.000 (99.829) +2022-11-14 14:30:39,827 Epoch: [208][410/500] Time 0.030 (0.035) Data 0.001 (0.002) Loss 0.0421 (0.0394) Prec@1 91.000 (93.381) Prec@5 100.000 (99.833) +2022-11-14 14:30:40,142 Epoch: [208][420/500] Time 0.028 (0.035) Data 0.002 (0.002) Loss 0.0443 (0.0395) Prec@1 92.000 (93.349) Prec@5 99.000 (99.814) +2022-11-14 14:30:40,451 Epoch: [208][430/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0441 (0.0396) Prec@1 92.000 (93.318) Prec@5 99.000 (99.795) +2022-11-14 14:30:40,764 Epoch: [208][440/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0379 (0.0396) Prec@1 96.000 (93.378) Prec@5 100.000 (99.800) +2022-11-14 14:30:41,077 Epoch: [208][450/500] Time 0.030 (0.034) Data 0.002 (0.002) Loss 0.0525 (0.0399) Prec@1 91.000 (93.326) Prec@5 100.000 (99.804) +2022-11-14 14:30:41,385 Epoch: [208][460/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0440 (0.0399) Prec@1 93.000 (93.319) Prec@5 100.000 (99.809) +2022-11-14 14:30:41,697 Epoch: [208][470/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0327 (0.0398) Prec@1 94.000 (93.333) Prec@5 100.000 (99.812) +2022-11-14 14:30:42,012 Epoch: [208][480/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0351 (0.0397) Prec@1 94.000 (93.347) Prec@5 100.000 (99.816) +2022-11-14 14:30:42,318 Epoch: [208][490/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0438 (0.0398) Prec@1 93.000 (93.340) Prec@5 100.000 (99.820) +2022-11-14 14:30:42,602 Epoch: [208][499/500] Time 0.030 (0.033) Data 0.001 (0.002) Loss 0.0357 (0.0397) Prec@1 94.000 (93.353) Prec@5 100.000 (99.824) +2022-11-14 14:30:42,874 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0694 (0.0694) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:42,884 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0689) Prec@1 91.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:30:42,893 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0715) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 14:30:42,905 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0711) Prec@1 89.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 14:30:42,914 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0728) Prec@1 86.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 14:30:42,923 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0386 (0.0671) Prec@1 93.000 (88.833) Prec@5 100.000 (99.833) +2022-11-14 14:30:42,931 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0659) Prec@1 90.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 14:30:42,940 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0704) Prec@1 83.000 (88.250) Prec@5 98.000 (99.625) +2022-11-14 14:30:42,949 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0723) Prec@1 88.000 (88.222) Prec@5 100.000 (99.667) +2022-11-14 14:30:42,957 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0737) Prec@1 86.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 14:30:42,968 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0731) Prec@1 89.000 (88.091) Prec@5 100.000 (99.636) +2022-11-14 14:30:42,978 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0742) Prec@1 86.000 (87.917) Prec@5 99.000 (99.583) +2022-11-14 14:30:42,987 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0732) Prec@1 89.000 (88.000) Prec@5 100.000 (99.615) +2022-11-14 14:30:42,996 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0722) Prec@1 91.000 (88.214) Prec@5 100.000 (99.643) +2022-11-14 14:30:43,004 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0720) Prec@1 87.000 (88.133) Prec@5 100.000 (99.667) +2022-11-14 14:30:43,013 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0732) Prec@1 83.000 (87.812) Prec@5 100.000 (99.688) +2022-11-14 14:30:43,023 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0729) Prec@1 90.000 (87.941) Prec@5 99.000 (99.647) +2022-11-14 14:30:43,032 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0749) Prec@1 83.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 14:30:43,041 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0750) Prec@1 86.000 (87.579) Prec@5 98.000 (99.579) +2022-11-14 14:30:43,051 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0758) Prec@1 84.000 (87.400) Prec@5 98.000 (99.500) +2022-11-14 14:30:43,060 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0761) Prec@1 87.000 (87.381) Prec@5 99.000 (99.476) +2022-11-14 14:30:43,068 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0761) Prec@1 88.000 (87.409) Prec@5 100.000 (99.500) +2022-11-14 14:30:43,077 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0763) Prec@1 87.000 (87.391) Prec@5 100.000 (99.522) +2022-11-14 14:30:43,087 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0762) Prec@1 88.000 (87.417) Prec@5 100.000 (99.542) +2022-11-14 14:30:43,095 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0763) Prec@1 88.000 (87.440) Prec@5 99.000 (99.520) +2022-11-14 14:30:43,103 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0768) Prec@1 86.000 (87.385) Prec@5 97.000 (99.423) +2022-11-14 14:30:43,111 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0761) Prec@1 91.000 (87.519) Prec@5 100.000 (99.444) +2022-11-14 14:30:43,119 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0757) Prec@1 91.000 (87.643) Prec@5 100.000 (99.464) +2022-11-14 14:30:43,129 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0760) Prec@1 83.000 (87.483) Prec@5 99.000 (99.448) +2022-11-14 14:30:43,137 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0760) Prec@1 87.000 (87.467) Prec@5 99.000 (99.433) +2022-11-14 14:30:43,146 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0756) Prec@1 87.000 (87.452) Prec@5 100.000 (99.452) +2022-11-14 14:30:43,156 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0754) Prec@1 88.000 (87.469) Prec@5 99.000 (99.438) +2022-11-14 14:30:43,164 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0749) Prec@1 91.000 (87.576) Prec@5 100.000 (99.455) +2022-11-14 14:30:43,173 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0760) Prec@1 81.000 (87.382) Prec@5 97.000 (99.382) +2022-11-14 14:30:43,183 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0759) Prec@1 89.000 (87.429) Prec@5 100.000 (99.400) +2022-11-14 14:30:43,193 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0758) Prec@1 89.000 (87.472) Prec@5 99.000 (99.389) +2022-11-14 14:30:43,202 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0758) Prec@1 87.000 (87.459) Prec@5 99.000 (99.378) +2022-11-14 14:30:43,211 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0762) Prec@1 84.000 (87.368) Prec@5 100.000 (99.395) +2022-11-14 14:30:43,220 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0756) Prec@1 91.000 (87.462) Prec@5 98.000 (99.359) +2022-11-14 14:30:43,229 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0754) Prec@1 90.000 (87.525) Prec@5 99.000 (99.350) +2022-11-14 14:30:43,238 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0760) Prec@1 85.000 (87.463) Prec@5 98.000 (99.317) +2022-11-14 14:30:43,248 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0757) Prec@1 91.000 (87.548) Prec@5 100.000 (99.333) +2022-11-14 14:30:43,256 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0750) Prec@1 93.000 (87.674) Prec@5 100.000 (99.349) +2022-11-14 14:30:43,265 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0749) Prec@1 91.000 (87.750) Prec@5 98.000 (99.318) +2022-11-14 14:30:43,275 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0750) Prec@1 88.000 (87.756) Prec@5 100.000 (99.333) +2022-11-14 14:30:43,284 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0754) Prec@1 85.000 (87.696) Prec@5 99.000 (99.326) +2022-11-14 14:30:43,294 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0757) Prec@1 82.000 (87.574) Prec@5 100.000 (99.340) +2022-11-14 14:30:43,303 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0760) Prec@1 86.000 (87.542) Prec@5 98.000 (99.312) +2022-11-14 14:30:43,311 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0756) Prec@1 91.000 (87.612) Prec@5 99.000 (99.306) +2022-11-14 14:30:43,320 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0761) Prec@1 85.000 (87.560) Prec@5 99.000 (99.300) +2022-11-14 14:30:43,330 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0761) Prec@1 84.000 (87.490) Prec@5 100.000 (99.314) +2022-11-14 14:30:43,340 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0764) Prec@1 84.000 (87.423) Prec@5 99.000 (99.308) +2022-11-14 14:30:43,349 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0765) Prec@1 86.000 (87.396) Prec@5 100.000 (99.321) +2022-11-14 14:30:43,358 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0764) Prec@1 89.000 (87.426) Prec@5 100.000 (99.333) +2022-11-14 14:30:43,367 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0767) Prec@1 84.000 (87.364) Prec@5 100.000 (99.345) +2022-11-14 14:30:43,377 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0766) Prec@1 88.000 (87.375) Prec@5 99.000 (99.339) +2022-11-14 14:30:43,386 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0768) Prec@1 86.000 (87.351) Prec@5 100.000 (99.351) +2022-11-14 14:30:43,394 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0766) Prec@1 91.000 (87.414) Prec@5 99.000 (99.345) +2022-11-14 14:30:43,403 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1183 (0.0773) Prec@1 79.000 (87.271) Prec@5 99.000 (99.339) +2022-11-14 14:30:43,412 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0774) Prec@1 87.000 (87.267) Prec@5 99.000 (99.333) +2022-11-14 14:30:43,420 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0773) Prec@1 90.000 (87.311) Prec@5 100.000 (99.344) +2022-11-14 14:30:43,428 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0774) Prec@1 82.000 (87.226) Prec@5 99.000 (99.339) +2022-11-14 14:30:43,436 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0775) Prec@1 88.000 (87.238) Prec@5 99.000 (99.333) +2022-11-14 14:30:43,445 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0346 (0.0768) Prec@1 95.000 (87.359) Prec@5 100.000 (99.344) +2022-11-14 14:30:43,455 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0772) Prec@1 87.000 (87.354) Prec@5 100.000 (99.354) +2022-11-14 14:30:43,464 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0774) Prec@1 87.000 (87.348) Prec@5 99.000 (99.348) +2022-11-14 14:30:43,473 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0769) Prec@1 93.000 (87.433) Prec@5 100.000 (99.358) +2022-11-14 14:30:43,485 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0768) Prec@1 89.000 (87.456) Prec@5 98.000 (99.338) +2022-11-14 14:30:43,496 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0764) Prec@1 92.000 (87.522) Prec@5 100.000 (99.348) +2022-11-14 14:30:43,506 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0764) Prec@1 87.000 (87.514) Prec@5 99.000 (99.343) +2022-11-14 14:30:43,518 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0767) Prec@1 85.000 (87.479) Prec@5 99.000 (99.338) +2022-11-14 14:30:43,530 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0765) Prec@1 90.000 (87.514) Prec@5 100.000 (99.347) +2022-11-14 14:30:43,543 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0763) Prec@1 87.000 (87.507) Prec@5 100.000 (99.356) +2022-11-14 14:30:43,555 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0762) Prec@1 90.000 (87.541) Prec@5 100.000 (99.365) +2022-11-14 14:30:43,568 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0765) Prec@1 81.000 (87.453) Prec@5 100.000 (99.373) +2022-11-14 14:30:43,580 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0762) Prec@1 91.000 (87.500) Prec@5 99.000 (99.368) +2022-11-14 14:30:43,591 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0759) Prec@1 90.000 (87.532) Prec@5 99.000 (99.364) +2022-11-14 14:30:43,604 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0762) Prec@1 83.000 (87.474) Prec@5 98.000 (99.346) +2022-11-14 14:30:43,617 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0762) Prec@1 86.000 (87.456) Prec@5 100.000 (99.354) +2022-11-14 14:30:43,630 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0761) Prec@1 89.000 (87.475) Prec@5 100.000 (99.362) +2022-11-14 14:30:43,643 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0761) Prec@1 87.000 (87.469) Prec@5 98.000 (99.346) +2022-11-14 14:30:43,656 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0762) Prec@1 86.000 (87.451) Prec@5 100.000 (99.354) +2022-11-14 14:30:43,668 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0763) Prec@1 85.000 (87.422) Prec@5 100.000 (99.361) +2022-11-14 14:30:43,681 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0763) Prec@1 86.000 (87.405) Prec@5 99.000 (99.357) +2022-11-14 14:30:43,695 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0765) Prec@1 85.000 (87.376) Prec@5 100.000 (99.365) +2022-11-14 14:30:43,708 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0767) Prec@1 83.000 (87.326) Prec@5 98.000 (99.349) +2022-11-14 14:30:43,721 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0766) Prec@1 90.000 (87.356) Prec@5 99.000 (99.345) +2022-11-14 14:30:43,733 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0767) Prec@1 85.000 (87.330) Prec@5 99.000 (99.341) +2022-11-14 14:30:43,746 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0766) Prec@1 88.000 (87.337) Prec@5 98.000 (99.326) +2022-11-14 14:30:43,758 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0765) Prec@1 89.000 (87.356) Prec@5 99.000 (99.322) +2022-11-14 14:30:43,771 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0762) Prec@1 93.000 (87.418) Prec@5 100.000 (99.330) +2022-11-14 14:30:43,786 Test: [91/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0483 (0.0759) Prec@1 92.000 (87.467) Prec@5 100.000 (99.337) +2022-11-14 14:30:43,801 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0759) Prec@1 86.000 (87.452) Prec@5 100.000 (99.344) +2022-11-14 14:30:43,815 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0760) Prec@1 86.000 (87.436) Prec@5 99.000 (99.340) +2022-11-14 14:30:43,828 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0761) Prec@1 86.000 (87.421) Prec@5 99.000 (99.337) +2022-11-14 14:30:43,842 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0760) Prec@1 88.000 (87.427) Prec@5 100.000 (99.344) +2022-11-14 14:30:43,855 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0757) Prec@1 94.000 (87.495) Prec@5 98.000 (99.330) +2022-11-14 14:30:43,869 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0758) Prec@1 84.000 (87.459) Prec@5 100.000 (99.337) +2022-11-14 14:30:43,882 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0760) Prec@1 85.000 (87.434) Prec@5 100.000 (99.343) +2022-11-14 14:30:43,895 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0759) Prec@1 89.000 (87.450) Prec@5 99.000 (99.340) +2022-11-14 14:30:43,952 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:30:44,274 Epoch: [209][0/500] Time 0.026 (0.026) Data 0.236 (0.236) Loss 0.0333 (0.0333) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:30:44,500 Epoch: [209][10/500] Time 0.020 (0.020) Data 0.002 (0.023) Loss 0.0429 (0.0381) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:30:44,739 Epoch: [209][20/500] Time 0.022 (0.021) Data 0.001 (0.013) Loss 0.0601 (0.0454) Prec@1 90.000 (93.333) Prec@5 99.000 (99.000) +2022-11-14 14:30:45,021 Epoch: [209][30/500] Time 0.038 (0.022) Data 0.002 (0.009) Loss 0.0493 (0.0464) Prec@1 90.000 (92.500) Prec@5 100.000 (99.250) +2022-11-14 14:30:45,399 Epoch: [209][40/500] Time 0.037 (0.025) Data 0.002 (0.007) Loss 0.0384 (0.0448) Prec@1 94.000 (92.800) Prec@5 99.000 (99.200) +2022-11-14 14:30:45,775 Epoch: [209][50/500] Time 0.035 (0.026) Data 0.002 (0.006) Loss 0.0412 (0.0442) Prec@1 95.000 (93.167) Prec@5 99.000 (99.167) +2022-11-14 14:30:46,162 Epoch: [209][60/500] Time 0.035 (0.028) Data 0.002 (0.006) Loss 0.0664 (0.0474) Prec@1 86.000 (92.143) Prec@5 100.000 (99.286) +2022-11-14 14:30:46,543 Epoch: [209][70/500] Time 0.035 (0.028) Data 0.002 (0.005) Loss 0.0364 (0.0460) Prec@1 95.000 (92.500) Prec@5 100.000 (99.375) +2022-11-14 14:30:46,926 Epoch: [209][80/500] Time 0.035 (0.029) Data 0.002 (0.005) Loss 0.0349 (0.0448) Prec@1 95.000 (92.778) Prec@5 100.000 (99.444) +2022-11-14 14:30:47,310 Epoch: [209][90/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0401 (0.0443) Prec@1 93.000 (92.800) Prec@5 100.000 (99.500) +2022-11-14 14:30:47,696 Epoch: [209][100/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0401 (0.0439) Prec@1 95.000 (93.000) Prec@5 100.000 (99.545) +2022-11-14 14:30:48,085 Epoch: [209][110/500] Time 0.034 (0.031) Data 0.002 (0.004) Loss 0.0615 (0.0454) Prec@1 90.000 (92.750) Prec@5 100.000 (99.583) +2022-11-14 14:30:48,469 Epoch: [209][120/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0773 (0.0478) Prec@1 86.000 (92.231) Prec@5 99.000 (99.538) +2022-11-14 14:30:48,845 Epoch: [209][130/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0542 (0.0483) Prec@1 92.000 (92.214) Prec@5 100.000 (99.571) +2022-11-14 14:30:49,228 Epoch: [209][140/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0475 (0.0482) Prec@1 93.000 (92.267) Prec@5 99.000 (99.533) +2022-11-14 14:30:49,609 Epoch: [209][150/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0385 (0.0476) Prec@1 94.000 (92.375) Prec@5 99.000 (99.500) +2022-11-14 14:30:50,001 Epoch: [209][160/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0262 (0.0464) Prec@1 97.000 (92.647) Prec@5 100.000 (99.529) +2022-11-14 14:30:50,384 Epoch: [209][170/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0552 (0.0469) Prec@1 92.000 (92.611) Prec@5 99.000 (99.500) +2022-11-14 14:30:50,770 Epoch: [209][180/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0522 (0.0471) Prec@1 91.000 (92.526) Prec@5 100.000 (99.526) +2022-11-14 14:30:51,158 Epoch: [209][190/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0292 (0.0462) Prec@1 95.000 (92.650) Prec@5 100.000 (99.550) +2022-11-14 14:30:51,538 Epoch: [209][200/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0479 (0.0463) Prec@1 91.000 (92.571) Prec@5 99.000 (99.524) +2022-11-14 14:30:51,924 Epoch: [209][210/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0431 (0.0462) Prec@1 92.000 (92.545) Prec@5 100.000 (99.545) +2022-11-14 14:30:52,310 Epoch: [209][220/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0337 (0.0456) Prec@1 93.000 (92.565) Prec@5 100.000 (99.565) +2022-11-14 14:30:52,694 Epoch: [209][230/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0234 (0.0447) Prec@1 96.000 (92.708) Prec@5 100.000 (99.583) +2022-11-14 14:30:53,077 Epoch: [209][240/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0565 (0.0452) Prec@1 89.000 (92.560) Prec@5 99.000 (99.560) +2022-11-14 14:30:53,458 Epoch: [209][250/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0360 (0.0448) Prec@1 94.000 (92.615) Prec@5 99.000 (99.538) +2022-11-14 14:30:53,846 Epoch: [209][260/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0299 (0.0443) Prec@1 95.000 (92.704) Prec@5 100.000 (99.556) +2022-11-14 14:30:54,238 Epoch: [209][270/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0260 (0.0436) Prec@1 95.000 (92.786) Prec@5 100.000 (99.571) +2022-11-14 14:30:54,621 Epoch: [209][280/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0394 (0.0435) Prec@1 91.000 (92.724) Prec@5 100.000 (99.586) +2022-11-14 14:30:55,014 Epoch: [209][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0462 (0.0436) Prec@1 93.000 (92.733) Prec@5 100.000 (99.600) +2022-11-14 14:30:55,391 Epoch: [209][300/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0397 (0.0434) Prec@1 95.000 (92.806) Prec@5 100.000 (99.613) +2022-11-14 14:30:55,767 Epoch: [209][310/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0487 (0.0436) Prec@1 92.000 (92.781) Prec@5 98.000 (99.562) +2022-11-14 14:30:56,155 Epoch: [209][320/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0254 (0.0431) Prec@1 97.000 (92.909) Prec@5 100.000 (99.576) +2022-11-14 14:30:56,540 Epoch: [209][330/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0278 (0.0426) Prec@1 96.000 (93.000) Prec@5 100.000 (99.588) +2022-11-14 14:30:56,921 Epoch: [209][340/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0326 (0.0423) Prec@1 95.000 (93.057) Prec@5 100.000 (99.600) +2022-11-14 14:30:57,302 Epoch: [209][350/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0296 (0.0420) Prec@1 96.000 (93.139) Prec@5 100.000 (99.611) +2022-11-14 14:30:57,690 Epoch: [209][360/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0277 (0.0416) Prec@1 96.000 (93.216) Prec@5 100.000 (99.622) +2022-11-14 14:30:58,077 Epoch: [209][370/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0474 (0.0417) Prec@1 93.000 (93.211) Prec@5 99.000 (99.605) +2022-11-14 14:30:58,465 Epoch: [209][380/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0368 (0.0416) Prec@1 93.000 (93.205) Prec@5 100.000 (99.615) +2022-11-14 14:30:58,853 Epoch: [209][390/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0355 (0.0415) Prec@1 95.000 (93.250) Prec@5 100.000 (99.625) +2022-11-14 14:30:59,243 Epoch: [209][400/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0450 (0.0415) Prec@1 91.000 (93.195) Prec@5 100.000 (99.634) +2022-11-14 14:30:59,630 Epoch: [209][410/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0397 (0.0415) Prec@1 91.000 (93.143) Prec@5 100.000 (99.643) +2022-11-14 14:31:00,021 Epoch: [209][420/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0549 (0.0418) Prec@1 89.000 (93.047) Prec@5 100.000 (99.651) +2022-11-14 14:31:00,397 Epoch: [209][430/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0353 (0.0417) Prec@1 93.000 (93.045) Prec@5 100.000 (99.659) +2022-11-14 14:31:00,779 Epoch: [209][440/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0442 (0.0417) Prec@1 93.000 (93.044) Prec@5 100.000 (99.667) +2022-11-14 14:31:01,166 Epoch: [209][450/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0503 (0.0419) Prec@1 91.000 (93.000) Prec@5 100.000 (99.674) +2022-11-14 14:31:01,558 Epoch: [209][460/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0226 (0.0415) Prec@1 97.000 (93.085) Prec@5 100.000 (99.681) +2022-11-14 14:31:01,944 Epoch: [209][470/500] Time 0.037 (0.033) Data 0.002 (0.002) Loss 0.0488 (0.0417) Prec@1 93.000 (93.083) Prec@5 100.000 (99.688) +2022-11-14 14:31:02,333 Epoch: [209][480/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0433 (0.0417) Prec@1 94.000 (93.102) Prec@5 99.000 (99.673) +2022-11-14 14:31:02,720 Epoch: [209][490/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0300 (0.0414) Prec@1 94.000 (93.120) Prec@5 100.000 (99.680) +2022-11-14 14:31:03,071 Epoch: [209][499/500] Time 0.033 (0.033) Data 0.002 (0.002) Loss 0.0260 (0.0411) Prec@1 97.000 (93.196) Prec@5 99.000 (99.667) +2022-11-14 14:31:03,365 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0578 (0.0578) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:03,373 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0724 (0.0651) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:03,382 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0663) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:03,394 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0683) Prec@1 86.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 14:31:03,402 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0733) Prec@1 84.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 14:31:03,410 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0709) Prec@1 89.000 (88.167) Prec@5 99.000 (99.667) +2022-11-14 14:31:03,419 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0700) Prec@1 90.000 (88.429) Prec@5 100.000 (99.714) +2022-11-14 14:31:03,428 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0692) Prec@1 89.000 (88.500) Prec@5 100.000 (99.750) +2022-11-14 14:31:03,435 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0705) Prec@1 85.000 (88.111) Prec@5 100.000 (99.778) +2022-11-14 14:31:03,443 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0718) Prec@1 86.000 (87.900) Prec@5 97.000 (99.500) +2022-11-14 14:31:03,452 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0713) Prec@1 87.000 (87.818) Prec@5 100.000 (99.545) +2022-11-14 14:31:03,462 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0717) Prec@1 89.000 (87.917) Prec@5 99.000 (99.500) +2022-11-14 14:31:03,470 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0704) Prec@1 90.000 (88.077) Prec@5 100.000 (99.538) +2022-11-14 14:31:03,479 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0708) Prec@1 88.000 (88.071) Prec@5 100.000 (99.571) +2022-11-14 14:31:03,489 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0712) Prec@1 88.000 (88.067) Prec@5 100.000 (99.600) +2022-11-14 14:31:03,497 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0703) Prec@1 91.000 (88.250) Prec@5 99.000 (99.562) +2022-11-14 14:31:03,506 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0685) Prec@1 92.000 (88.471) Prec@5 99.000 (99.529) +2022-11-14 14:31:03,517 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0710) Prec@1 83.000 (88.167) Prec@5 100.000 (99.556) +2022-11-14 14:31:03,525 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0723) Prec@1 83.000 (87.895) Prec@5 99.000 (99.526) +2022-11-14 14:31:03,534 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0727) Prec@1 86.000 (87.800) Prec@5 98.000 (99.450) +2022-11-14 14:31:03,542 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0736) Prec@1 85.000 (87.667) Prec@5 99.000 (99.429) +2022-11-14 14:31:03,552 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0732) Prec@1 90.000 (87.773) Prec@5 100.000 (99.455) +2022-11-14 14:31:03,562 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0741) Prec@1 86.000 (87.696) Prec@5 98.000 (99.391) +2022-11-14 14:31:03,572 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0743) Prec@1 86.000 (87.625) Prec@5 100.000 (99.417) +2022-11-14 14:31:03,581 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0751) Prec@1 85.000 (87.520) Prec@5 100.000 (99.440) +2022-11-14 14:31:03,590 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0756) Prec@1 88.000 (87.538) Prec@5 98.000 (99.385) +2022-11-14 14:31:03,600 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0752) Prec@1 90.000 (87.630) Prec@5 100.000 (99.407) +2022-11-14 14:31:03,609 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0746) Prec@1 90.000 (87.714) Prec@5 100.000 (99.429) +2022-11-14 14:31:03,617 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0746) Prec@1 87.000 (87.690) Prec@5 98.000 (99.379) +2022-11-14 14:31:03,627 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0741) Prec@1 88.000 (87.700) Prec@5 100.000 (99.400) +2022-11-14 14:31:03,636 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0744) Prec@1 87.000 (87.677) Prec@5 100.000 (99.419) +2022-11-14 14:31:03,646 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0753) Prec@1 85.000 (87.594) Prec@5 100.000 (99.438) +2022-11-14 14:31:03,655 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0752) Prec@1 88.000 (87.606) Prec@5 100.000 (99.455) +2022-11-14 14:31:03,664 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0756) Prec@1 85.000 (87.529) Prec@5 100.000 (99.471) +2022-11-14 14:31:03,671 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0759) Prec@1 86.000 (87.486) Prec@5 99.000 (99.457) +2022-11-14 14:31:03,679 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0757) Prec@1 89.000 (87.528) Prec@5 100.000 (99.472) +2022-11-14 14:31:03,689 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0753) Prec@1 90.000 (87.595) Prec@5 99.000 (99.459) +2022-11-14 14:31:03,699 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0757) Prec@1 85.000 (87.526) Prec@5 98.000 (99.421) +2022-11-14 14:31:03,708 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0416 (0.0749) Prec@1 95.000 (87.718) Prec@5 100.000 (99.436) +2022-11-14 14:31:03,717 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0747) Prec@1 89.000 (87.750) Prec@5 99.000 (99.425) +2022-11-14 14:31:03,727 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0745) Prec@1 88.000 (87.756) Prec@5 99.000 (99.415) +2022-11-14 14:31:03,735 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0742) Prec@1 89.000 (87.786) Prec@5 100.000 (99.429) +2022-11-14 14:31:03,745 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0736) Prec@1 91.000 (87.860) Prec@5 100.000 (99.442) +2022-11-14 14:31:03,754 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0734) Prec@1 89.000 (87.886) Prec@5 99.000 (99.432) +2022-11-14 14:31:03,763 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0734) Prec@1 88.000 (87.889) Prec@5 99.000 (99.422) +2022-11-14 14:31:03,773 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0735) Prec@1 86.000 (87.848) Prec@5 99.000 (99.413) +2022-11-14 14:31:03,782 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0734) Prec@1 88.000 (87.851) Prec@5 100.000 (99.426) +2022-11-14 14:31:03,791 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1186 (0.0744) Prec@1 82.000 (87.729) Prec@5 97.000 (99.375) +2022-11-14 14:31:03,801 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0406 (0.0737) Prec@1 94.000 (87.857) Prec@5 99.000 (99.367) +2022-11-14 14:31:03,810 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0744) Prec@1 83.000 (87.760) Prec@5 100.000 (99.380) +2022-11-14 14:31:03,819 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0742) Prec@1 86.000 (87.725) Prec@5 100.000 (99.392) +2022-11-14 14:31:03,829 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0748) Prec@1 82.000 (87.615) Prec@5 100.000 (99.404) +2022-11-14 14:31:03,838 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0747) Prec@1 89.000 (87.642) Prec@5 100.000 (99.415) +2022-11-14 14:31:03,847 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0750) Prec@1 83.000 (87.556) Prec@5 100.000 (99.426) +2022-11-14 14:31:03,857 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0747) Prec@1 92.000 (87.636) Prec@5 100.000 (99.436) +2022-11-14 14:31:03,865 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0744) Prec@1 91.000 (87.696) Prec@5 99.000 (99.429) +2022-11-14 14:31:03,874 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0741) Prec@1 90.000 (87.737) Prec@5 100.000 (99.439) +2022-11-14 14:31:03,884 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0740) Prec@1 90.000 (87.776) Prec@5 100.000 (99.448) +2022-11-14 14:31:03,893 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0744) Prec@1 85.000 (87.729) Prec@5 100.000 (99.458) +2022-11-14 14:31:03,902 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0748) Prec@1 83.000 (87.650) Prec@5 100.000 (99.467) +2022-11-14 14:31:03,912 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0752) Prec@1 83.000 (87.574) Prec@5 99.000 (99.459) +2022-11-14 14:31:03,921 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0753) Prec@1 86.000 (87.548) Prec@5 99.000 (99.452) +2022-11-14 14:31:03,930 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0749) Prec@1 93.000 (87.635) Prec@5 99.000 (99.444) +2022-11-14 14:31:03,938 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0397 (0.0744) Prec@1 92.000 (87.703) Prec@5 100.000 (99.453) +2022-11-14 14:31:03,947 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0746) Prec@1 81.000 (87.600) Prec@5 100.000 (99.462) +2022-11-14 14:31:03,956 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0747) Prec@1 86.000 (87.576) Prec@5 98.000 (99.439) +2022-11-14 14:31:03,965 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0373 (0.0741) Prec@1 94.000 (87.672) Prec@5 100.000 (99.448) +2022-11-14 14:31:03,973 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0741) Prec@1 88.000 (87.676) Prec@5 98.000 (99.426) +2022-11-14 14:31:03,983 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0738) Prec@1 89.000 (87.696) Prec@5 99.000 (99.420) +2022-11-14 14:31:03,992 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0739) Prec@1 87.000 (87.686) Prec@5 100.000 (99.429) +2022-11-14 14:31:04,002 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0742) Prec@1 85.000 (87.648) Prec@5 99.000 (99.423) +2022-11-14 14:31:04,011 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0741) Prec@1 89.000 (87.667) Prec@5 100.000 (99.431) +2022-11-14 14:31:04,020 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0739) Prec@1 89.000 (87.685) Prec@5 100.000 (99.438) +2022-11-14 14:31:04,030 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0735) Prec@1 94.000 (87.770) Prec@5 100.000 (99.446) +2022-11-14 14:31:04,039 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0738) Prec@1 84.000 (87.720) Prec@5 100.000 (99.453) +2022-11-14 14:31:04,048 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0735) Prec@1 93.000 (87.789) Prec@5 99.000 (99.447) +2022-11-14 14:31:04,058 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0734) Prec@1 89.000 (87.805) Prec@5 96.000 (99.403) +2022-11-14 14:31:04,067 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0735) Prec@1 87.000 (87.795) Prec@5 98.000 (99.385) +2022-11-14 14:31:04,076 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0735) Prec@1 88.000 (87.797) Prec@5 100.000 (99.392) +2022-11-14 14:31:04,087 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0735) Prec@1 89.000 (87.812) Prec@5 100.000 (99.400) +2022-11-14 14:31:04,095 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0736) Prec@1 86.000 (87.790) Prec@5 99.000 (99.395) +2022-11-14 14:31:04,104 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0739) Prec@1 84.000 (87.744) Prec@5 100.000 (99.402) +2022-11-14 14:31:04,114 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0740) Prec@1 85.000 (87.711) Prec@5 100.000 (99.410) +2022-11-14 14:31:04,123 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0740) Prec@1 87.000 (87.702) Prec@5 99.000 (99.405) +2022-11-14 14:31:04,133 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0745) Prec@1 83.000 (87.647) Prec@5 99.000 (99.400) +2022-11-14 14:31:04,144 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0748) Prec@1 83.000 (87.593) Prec@5 100.000 (99.407) +2022-11-14 14:31:04,155 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0748) Prec@1 89.000 (87.609) Prec@5 100.000 (99.414) +2022-11-14 14:31:04,166 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0747) Prec@1 88.000 (87.614) Prec@5 98.000 (99.398) +2022-11-14 14:31:04,178 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0746) Prec@1 90.000 (87.640) Prec@5 100.000 (99.404) +2022-11-14 14:31:04,189 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0748) Prec@1 88.000 (87.644) Prec@5 100.000 (99.411) +2022-11-14 14:31:04,201 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0747) Prec@1 89.000 (87.659) Prec@5 100.000 (99.418) +2022-11-14 14:31:04,213 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0433 (0.0744) Prec@1 93.000 (87.717) Prec@5 99.000 (99.413) +2022-11-14 14:31:04,225 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0746) Prec@1 85.000 (87.688) Prec@5 100.000 (99.419) +2022-11-14 14:31:04,236 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0746) Prec@1 88.000 (87.691) Prec@5 99.000 (99.415) +2022-11-14 14:31:04,248 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0748) Prec@1 85.000 (87.663) Prec@5 99.000 (99.411) +2022-11-14 14:31:04,260 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0747) Prec@1 90.000 (87.688) Prec@5 99.000 (99.406) +2022-11-14 14:31:04,270 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0744) Prec@1 93.000 (87.742) Prec@5 100.000 (99.412) +2022-11-14 14:31:04,280 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0745) Prec@1 87.000 (87.735) Prec@5 100.000 (99.418) +2022-11-14 14:31:04,292 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0746) Prec@1 86.000 (87.717) Prec@5 100.000 (99.424) +2022-11-14 14:31:04,305 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0745) Prec@1 90.000 (87.740) Prec@5 100.000 (99.430) +2022-11-14 14:31:04,374 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:31:04,700 Epoch: [210][0/500] Time 0.030 (0.030) Data 0.236 (0.236) Loss 0.0478 (0.0478) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:04,932 Epoch: [210][10/500] Time 0.019 (0.022) Data 0.002 (0.023) Loss 0.0705 (0.0592) Prec@1 89.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 14:31:05,165 Epoch: [210][20/500] Time 0.026 (0.021) Data 0.002 (0.013) Loss 0.0614 (0.0599) Prec@1 90.000 (90.333) Prec@5 99.000 (99.333) +2022-11-14 14:31:05,533 Epoch: [210][30/500] Time 0.037 (0.025) Data 0.002 (0.009) Loss 0.0395 (0.0548) Prec@1 92.000 (90.750) Prec@5 100.000 (99.500) +2022-11-14 14:31:05,923 Epoch: [210][40/500] Time 0.036 (0.027) Data 0.002 (0.007) Loss 0.0303 (0.0499) Prec@1 96.000 (91.800) Prec@5 100.000 (99.600) +2022-11-14 14:31:06,318 Epoch: [210][50/500] Time 0.041 (0.029) Data 0.001 (0.006) Loss 0.0655 (0.0525) Prec@1 90.000 (91.500) Prec@5 100.000 (99.667) +2022-11-14 14:31:06,715 Epoch: [210][60/500] Time 0.038 (0.030) Data 0.002 (0.006) Loss 0.0662 (0.0545) Prec@1 85.000 (90.571) Prec@5 100.000 (99.714) +2022-11-14 14:31:07,119 Epoch: [210][70/500] Time 0.033 (0.031) Data 0.002 (0.005) Loss 0.0334 (0.0518) Prec@1 96.000 (91.250) Prec@5 100.000 (99.750) +2022-11-14 14:31:07,516 Epoch: [210][80/500] Time 0.038 (0.031) Data 0.002 (0.005) Loss 0.0313 (0.0496) Prec@1 96.000 (91.778) Prec@5 99.000 (99.667) +2022-11-14 14:31:07,909 Epoch: [210][90/500] Time 0.037 (0.032) Data 0.002 (0.004) Loss 0.0491 (0.0495) Prec@1 91.000 (91.700) Prec@5 99.000 (99.600) +2022-11-14 14:31:08,309 Epoch: [210][100/500] Time 0.041 (0.032) Data 0.002 (0.004) Loss 0.0364 (0.0483) Prec@1 93.000 (91.818) Prec@5 100.000 (99.636) +2022-11-14 14:31:08,699 Epoch: [210][110/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0520 (0.0486) Prec@1 92.000 (91.833) Prec@5 100.000 (99.667) +2022-11-14 14:31:09,100 Epoch: [210][120/500] Time 0.039 (0.033) Data 0.002 (0.004) Loss 0.0648 (0.0499) Prec@1 89.000 (91.615) Prec@5 100.000 (99.692) +2022-11-14 14:31:09,495 Epoch: [210][130/500] Time 0.037 (0.033) Data 0.002 (0.004) Loss 0.0404 (0.0492) Prec@1 94.000 (91.786) Prec@5 98.000 (99.571) +2022-11-14 14:31:09,890 Epoch: [210][140/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0227 (0.0474) Prec@1 96.000 (92.067) Prec@5 99.000 (99.533) +2022-11-14 14:31:10,285 Epoch: [210][150/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0399 (0.0470) Prec@1 94.000 (92.188) Prec@5 99.000 (99.500) +2022-11-14 14:31:10,678 Epoch: [210][160/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0375 (0.0464) Prec@1 95.000 (92.353) Prec@5 100.000 (99.529) +2022-11-14 14:31:11,075 Epoch: [210][170/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0313 (0.0456) Prec@1 95.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:31:11,474 Epoch: [210][180/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0650 (0.0466) Prec@1 88.000 (92.263) Prec@5 100.000 (99.526) +2022-11-14 14:31:11,866 Epoch: [210][190/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0497 (0.0467) Prec@1 91.000 (92.200) Prec@5 100.000 (99.550) +2022-11-14 14:31:12,258 Epoch: [210][200/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0523 (0.0470) Prec@1 90.000 (92.095) Prec@5 100.000 (99.571) +2022-11-14 14:31:12,656 Epoch: [210][210/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0274 (0.0461) Prec@1 95.000 (92.227) Prec@5 100.000 (99.591) +2022-11-14 14:31:13,056 Epoch: [210][220/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0406 (0.0459) Prec@1 93.000 (92.261) Prec@5 100.000 (99.609) +2022-11-14 14:31:13,459 Epoch: [210][230/500] Time 0.036 (0.034) Data 0.003 (0.003) Loss 0.0398 (0.0456) Prec@1 95.000 (92.375) Prec@5 100.000 (99.625) +2022-11-14 14:31:13,854 Epoch: [210][240/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0376 (0.0453) Prec@1 93.000 (92.400) Prec@5 99.000 (99.600) +2022-11-14 14:31:14,247 Epoch: [210][250/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0326 (0.0448) Prec@1 96.000 (92.538) Prec@5 100.000 (99.615) +2022-11-14 14:31:14,637 Epoch: [210][260/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0233 (0.0440) Prec@1 98.000 (92.741) Prec@5 100.000 (99.630) +2022-11-14 14:31:15,037 Epoch: [210][270/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0485 (0.0442) Prec@1 93.000 (92.750) Prec@5 100.000 (99.643) +2022-11-14 14:31:15,439 Epoch: [210][280/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0464 (0.0443) Prec@1 92.000 (92.724) Prec@5 99.000 (99.621) +2022-11-14 14:31:15,837 Epoch: [210][290/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0423 (0.0442) Prec@1 93.000 (92.733) Prec@5 100.000 (99.633) +2022-11-14 14:31:16,235 Epoch: [210][300/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0445 (0.0442) Prec@1 91.000 (92.677) Prec@5 100.000 (99.645) +2022-11-14 14:31:16,633 Epoch: [210][310/500] Time 0.038 (0.034) Data 0.001 (0.003) Loss 0.0520 (0.0444) Prec@1 92.000 (92.656) Prec@5 100.000 (99.656) +2022-11-14 14:31:17,033 Epoch: [210][320/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0512 (0.0447) Prec@1 93.000 (92.667) Prec@5 99.000 (99.636) +2022-11-14 14:31:17,434 Epoch: [210][330/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0226 (0.0440) Prec@1 95.000 (92.735) Prec@5 100.000 (99.647) +2022-11-14 14:31:17,834 Epoch: [210][340/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0401 (0.0439) Prec@1 95.000 (92.800) Prec@5 100.000 (99.657) +2022-11-14 14:31:18,234 Epoch: [210][350/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0250 (0.0434) Prec@1 96.000 (92.889) Prec@5 100.000 (99.667) +2022-11-14 14:31:18,635 Epoch: [210][360/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0377 (0.0432) Prec@1 96.000 (92.973) Prec@5 100.000 (99.676) +2022-11-14 14:31:19,037 Epoch: [210][370/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0452 (0.0433) Prec@1 93.000 (92.974) Prec@5 100.000 (99.684) +2022-11-14 14:31:19,435 Epoch: [210][380/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0373 (0.0431) Prec@1 93.000 (92.974) Prec@5 100.000 (99.692) +2022-11-14 14:31:19,831 Epoch: [210][390/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0315 (0.0428) Prec@1 94.000 (93.000) Prec@5 100.000 (99.700) +2022-11-14 14:31:20,225 Epoch: [210][400/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0213 (0.0423) Prec@1 96.000 (93.073) Prec@5 100.000 (99.707) +2022-11-14 14:31:20,625 Epoch: [210][410/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0449 (0.0424) Prec@1 93.000 (93.071) Prec@5 100.000 (99.714) +2022-11-14 14:31:21,025 Epoch: [210][420/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0278 (0.0420) Prec@1 95.000 (93.116) Prec@5 100.000 (99.721) +2022-11-14 14:31:21,417 Epoch: [210][430/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0354 (0.0419) Prec@1 96.000 (93.182) Prec@5 100.000 (99.727) +2022-11-14 14:31:21,802 Epoch: [210][440/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0471 (0.0420) Prec@1 92.000 (93.156) Prec@5 100.000 (99.733) +2022-11-14 14:31:22,191 Epoch: [210][450/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0247 (0.0416) Prec@1 96.000 (93.217) Prec@5 100.000 (99.739) +2022-11-14 14:31:22,587 Epoch: [210][460/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0186 (0.0411) Prec@1 97.000 (93.298) Prec@5 100.000 (99.745) +2022-11-14 14:31:22,984 Epoch: [210][470/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0499 (0.0413) Prec@1 92.000 (93.271) Prec@5 100.000 (99.750) +2022-11-14 14:31:23,380 Epoch: [210][480/500] Time 0.034 (0.035) Data 0.002 (0.002) Loss 0.0552 (0.0416) Prec@1 92.000 (93.245) Prec@5 100.000 (99.755) +2022-11-14 14:31:23,769 Epoch: [210][490/500] Time 0.037 (0.035) Data 0.002 (0.002) Loss 0.0378 (0.0415) Prec@1 94.000 (93.260) Prec@5 100.000 (99.760) +2022-11-14 14:31:24,124 Epoch: [210][499/500] Time 0.038 (0.035) Data 0.001 (0.002) Loss 0.0412 (0.0415) Prec@1 93.000 (93.255) Prec@5 100.000 (99.765) +2022-11-14 14:31:24,401 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0562 (0.0562) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:24,409 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0733) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:24,418 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0688) Prec@1 92.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 14:31:24,431 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0739) Prec@1 87.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 14:31:24,438 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0726) Prec@1 88.000 (88.600) Prec@5 100.000 (99.600) +2022-11-14 14:31:24,446 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0680) Prec@1 91.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:31:24,454 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0656) Prec@1 93.000 (89.571) Prec@5 100.000 (99.571) +2022-11-14 14:31:24,464 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0671) Prec@1 87.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 14:31:24,472 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0689) Prec@1 87.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:31:24,479 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0684) Prec@1 89.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 14:31:24,487 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0669) Prec@1 92.000 (89.273) Prec@5 100.000 (99.545) +2022-11-14 14:31:24,495 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0674) Prec@1 89.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 14:31:24,503 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0667) Prec@1 91.000 (89.385) Prec@5 100.000 (99.538) +2022-11-14 14:31:24,512 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0679) Prec@1 85.000 (89.071) Prec@5 99.000 (99.500) +2022-11-14 14:31:24,521 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0681) Prec@1 88.000 (89.000) Prec@5 100.000 (99.533) +2022-11-14 14:31:24,529 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0684) Prec@1 86.000 (88.812) Prec@5 100.000 (99.562) +2022-11-14 14:31:24,538 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0681) Prec@1 90.000 (88.882) Prec@5 99.000 (99.529) +2022-11-14 14:31:24,548 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0697) Prec@1 85.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 14:31:24,557 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0696) Prec@1 87.000 (88.579) Prec@5 100.000 (99.526) +2022-11-14 14:31:24,566 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0703) Prec@1 88.000 (88.550) Prec@5 98.000 (99.450) +2022-11-14 14:31:24,575 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0715) Prec@1 86.000 (88.429) Prec@5 100.000 (99.476) +2022-11-14 14:31:24,585 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0725) Prec@1 87.000 (88.364) Prec@5 100.000 (99.500) +2022-11-14 14:31:24,594 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0739) Prec@1 84.000 (88.174) Prec@5 97.000 (99.391) +2022-11-14 14:31:24,603 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0742) Prec@1 86.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 14:31:24,612 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0744) Prec@1 89.000 (88.120) Prec@5 100.000 (99.440) +2022-11-14 14:31:24,621 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0751) Prec@1 85.000 (88.000) Prec@5 100.000 (99.462) +2022-11-14 14:31:24,630 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0743) Prec@1 91.000 (88.111) Prec@5 100.000 (99.481) +2022-11-14 14:31:24,640 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0738) Prec@1 91.000 (88.214) Prec@5 100.000 (99.500) +2022-11-14 14:31:24,649 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0737) Prec@1 89.000 (88.241) Prec@5 99.000 (99.483) +2022-11-14 14:31:24,659 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0735) Prec@1 88.000 (88.233) Prec@5 100.000 (99.500) +2022-11-14 14:31:24,669 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0736) Prec@1 88.000 (88.226) Prec@5 100.000 (99.516) +2022-11-14 14:31:24,678 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0739) Prec@1 88.000 (88.219) Prec@5 99.000 (99.500) +2022-11-14 14:31:24,686 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0742) Prec@1 86.000 (88.152) Prec@5 100.000 (99.515) +2022-11-14 14:31:24,696 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0742) Prec@1 86.000 (88.088) Prec@5 100.000 (99.529) +2022-11-14 14:31:24,706 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0748) Prec@1 84.000 (87.971) Prec@5 96.000 (99.429) +2022-11-14 14:31:24,715 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0750) Prec@1 88.000 (87.972) Prec@5 100.000 (99.444) +2022-11-14 14:31:24,724 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0744) Prec@1 91.000 (88.054) Prec@5 98.000 (99.405) +2022-11-14 14:31:24,734 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0747) Prec@1 83.000 (87.921) Prec@5 100.000 (99.421) +2022-11-14 14:31:24,742 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0744) Prec@1 92.000 (88.026) Prec@5 99.000 (99.410) +2022-11-14 14:31:24,752 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0742) Prec@1 88.000 (88.025) Prec@5 100.000 (99.425) +2022-11-14 14:31:24,761 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1194 (0.0753) Prec@1 83.000 (87.902) Prec@5 96.000 (99.341) +2022-11-14 14:31:24,769 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0758) Prec@1 85.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 14:31:24,777 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0751) Prec@1 91.000 (87.907) Prec@5 100.000 (99.349) +2022-11-14 14:31:24,785 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0745) Prec@1 93.000 (88.023) Prec@5 99.000 (99.341) +2022-11-14 14:31:24,795 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0745) Prec@1 89.000 (88.044) Prec@5 100.000 (99.356) +2022-11-14 14:31:24,806 Test: [45/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0743) Prec@1 90.000 (88.087) Prec@5 100.000 (99.370) +2022-11-14 14:31:24,816 Test: [46/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0740) Prec@1 90.000 (88.128) Prec@5 99.000 (99.362) +2022-11-14 14:31:24,825 Test: [47/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1147 (0.0749) Prec@1 81.000 (87.979) Prec@5 98.000 (99.333) +2022-11-14 14:31:24,835 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0744) Prec@1 93.000 (88.082) Prec@5 100.000 (99.347) +2022-11-14 14:31:24,845 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0751) Prec@1 84.000 (88.000) Prec@5 98.000 (99.320) +2022-11-14 14:31:24,854 Test: [50/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0751) Prec@1 87.000 (87.980) Prec@5 100.000 (99.333) +2022-11-14 14:31:24,863 Test: [51/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0750) Prec@1 87.000 (87.962) Prec@5 100.000 (99.346) +2022-11-14 14:31:24,873 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0746) Prec@1 92.000 (88.038) Prec@5 100.000 (99.358) +2022-11-14 14:31:24,882 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0747) Prec@1 86.000 (88.000) Prec@5 99.000 (99.352) +2022-11-14 14:31:24,891 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0750) Prec@1 85.000 (87.945) Prec@5 100.000 (99.364) +2022-11-14 14:31:24,900 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0750) Prec@1 90.000 (87.982) Prec@5 100.000 (99.375) +2022-11-14 14:31:24,909 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0745) Prec@1 93.000 (88.070) Prec@5 99.000 (99.368) +2022-11-14 14:31:24,919 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0743) Prec@1 90.000 (88.103) Prec@5 99.000 (99.362) +2022-11-14 14:31:24,928 Test: [58/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0747) Prec@1 83.000 (88.017) Prec@5 99.000 (99.356) +2022-11-14 14:31:24,937 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0748) Prec@1 86.000 (87.983) Prec@5 100.000 (99.367) +2022-11-14 14:31:24,947 Test: [60/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0748) Prec@1 90.000 (88.016) Prec@5 99.000 (99.361) +2022-11-14 14:31:24,956 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0749) Prec@1 86.000 (87.984) Prec@5 100.000 (99.371) +2022-11-14 14:31:24,965 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0745) Prec@1 91.000 (88.032) Prec@5 100.000 (99.381) +2022-11-14 14:31:24,975 Test: [63/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0741) Prec@1 91.000 (88.078) Prec@5 100.000 (99.391) +2022-11-14 14:31:24,984 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0743) Prec@1 86.000 (88.046) Prec@5 99.000 (99.385) +2022-11-14 14:31:24,993 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0746) Prec@1 83.000 (87.970) Prec@5 99.000 (99.379) +2022-11-14 14:31:25,003 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0741) Prec@1 91.000 (88.015) Prec@5 100.000 (99.388) +2022-11-14 14:31:25,013 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0740) Prec@1 90.000 (88.044) Prec@5 98.000 (99.368) +2022-11-14 14:31:25,022 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0739) Prec@1 89.000 (88.058) Prec@5 99.000 (99.362) +2022-11-14 14:31:25,032 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0738) Prec@1 88.000 (88.057) Prec@5 99.000 (99.357) +2022-11-14 14:31:25,041 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0742) Prec@1 86.000 (88.028) Prec@5 99.000 (99.352) +2022-11-14 14:31:25,051 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0739) Prec@1 91.000 (88.069) Prec@5 99.000 (99.347) +2022-11-14 14:31:25,060 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0443 (0.0735) Prec@1 93.000 (88.137) Prec@5 100.000 (99.356) +2022-11-14 14:31:25,069 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0731) Prec@1 94.000 (88.216) Prec@5 100.000 (99.365) +2022-11-14 14:31:25,077 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1195 (0.0737) Prec@1 81.000 (88.120) Prec@5 99.000 (99.360) +2022-11-14 14:31:25,085 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0736) Prec@1 86.000 (88.092) Prec@5 98.000 (99.342) +2022-11-14 14:31:25,094 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0737) Prec@1 86.000 (88.065) Prec@5 98.000 (99.325) +2022-11-14 14:31:25,103 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0739) Prec@1 86.000 (88.038) Prec@5 99.000 (99.321) +2022-11-14 14:31:25,113 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0739) Prec@1 88.000 (88.038) Prec@5 100.000 (99.329) +2022-11-14 14:31:25,122 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0739) Prec@1 90.000 (88.062) Prec@5 99.000 (99.325) +2022-11-14 14:31:25,131 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0739) Prec@1 88.000 (88.062) Prec@5 99.000 (99.321) +2022-11-14 14:31:25,141 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0741) Prec@1 85.000 (88.024) Prec@5 100.000 (99.329) +2022-11-14 14:31:25,150 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0741) Prec@1 87.000 (88.012) Prec@5 99.000 (99.325) +2022-11-14 14:31:25,159 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0741) Prec@1 88.000 (88.012) Prec@5 99.000 (99.321) +2022-11-14 14:31:25,169 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0744) Prec@1 86.000 (87.988) Prec@5 99.000 (99.318) +2022-11-14 14:31:25,178 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0747) Prec@1 84.000 (87.942) Prec@5 98.000 (99.302) +2022-11-14 14:31:25,187 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0745) Prec@1 89.000 (87.954) Prec@5 100.000 (99.310) +2022-11-14 14:31:25,197 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0745) Prec@1 87.000 (87.943) Prec@5 99.000 (99.307) +2022-11-14 14:31:25,206 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0744) Prec@1 86.000 (87.921) Prec@5 100.000 (99.315) +2022-11-14 14:31:25,214 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0746) Prec@1 84.000 (87.878) Prec@5 99.000 (99.311) +2022-11-14 14:31:25,224 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0745) Prec@1 89.000 (87.890) Prec@5 100.000 (99.319) +2022-11-14 14:31:25,234 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0398 (0.0741) Prec@1 95.000 (87.967) Prec@5 99.000 (99.315) +2022-11-14 14:31:25,243 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0742) Prec@1 88.000 (87.968) Prec@5 99.000 (99.312) +2022-11-14 14:31:25,253 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0741) Prec@1 91.000 (88.000) Prec@5 99.000 (99.309) +2022-11-14 14:31:25,261 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0741) Prec@1 87.000 (87.989) Prec@5 100.000 (99.316) +2022-11-14 14:31:25,270 Test: [95/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0740) Prec@1 89.000 (88.000) Prec@5 99.000 (99.312) +2022-11-14 14:31:25,280 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0432 (0.0737) Prec@1 94.000 (88.062) Prec@5 99.000 (99.309) +2022-11-14 14:31:25,289 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0740) Prec@1 82.000 (88.000) Prec@5 99.000 (99.306) +2022-11-14 14:31:25,299 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0743) Prec@1 84.000 (87.960) Prec@5 100.000 (99.313) +2022-11-14 14:31:25,309 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0742) Prec@1 89.000 (87.970) Prec@5 100.000 (99.320) +2022-11-14 14:31:25,366 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:31:25,674 Epoch: [211][0/500] Time 0.024 (0.024) Data 0.226 (0.226) Loss 0.0418 (0.0418) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:25,877 Epoch: [211][10/500] Time 0.017 (0.018) Data 0.001 (0.022) Loss 0.0353 (0.0386) Prec@1 92.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:31:26,078 Epoch: [211][20/500] Time 0.018 (0.018) Data 0.002 (0.012) Loss 0.0493 (0.0421) Prec@1 92.000 (92.333) Prec@5 99.000 (99.333) +2022-11-14 14:31:26,358 Epoch: [211][30/500] Time 0.029 (0.020) Data 0.002 (0.009) Loss 0.0283 (0.0387) Prec@1 97.000 (93.500) Prec@5 99.000 (99.250) +2022-11-14 14:31:26,749 Epoch: [211][40/500] Time 0.037 (0.024) Data 0.002 (0.007) Loss 0.0341 (0.0378) Prec@1 94.000 (93.600) Prec@5 100.000 (99.400) +2022-11-14 14:31:27,142 Epoch: [211][50/500] Time 0.037 (0.026) Data 0.002 (0.006) Loss 0.0199 (0.0348) Prec@1 96.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:31:27,538 Epoch: [211][60/500] Time 0.036 (0.027) Data 0.002 (0.005) Loss 0.0505 (0.0370) Prec@1 89.000 (93.286) Prec@5 100.000 (99.571) +2022-11-14 14:31:27,926 Epoch: [211][70/500] Time 0.037 (0.028) Data 0.001 (0.005) Loss 0.0433 (0.0378) Prec@1 94.000 (93.375) Prec@5 100.000 (99.625) +2022-11-14 14:31:28,326 Epoch: [211][80/500] Time 0.043 (0.029) Data 0.001 (0.005) Loss 0.0760 (0.0421) Prec@1 84.000 (92.333) Prec@5 98.000 (99.444) +2022-11-14 14:31:28,707 Epoch: [211][90/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0237 (0.0402) Prec@1 95.000 (92.600) Prec@5 100.000 (99.500) +2022-11-14 14:31:29,101 Epoch: [211][100/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0409 (0.0403) Prec@1 94.000 (92.727) Prec@5 100.000 (99.545) +2022-11-14 14:31:29,494 Epoch: [211][110/500] Time 0.036 (0.031) Data 0.002 (0.004) Loss 0.0667 (0.0425) Prec@1 86.000 (92.167) Prec@5 100.000 (99.583) +2022-11-14 14:31:29,889 Epoch: [211][120/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.0369 (0.0420) Prec@1 94.000 (92.308) Prec@5 100.000 (99.615) +2022-11-14 14:31:30,289 Epoch: [211][130/500] Time 0.038 (0.031) Data 0.001 (0.003) Loss 0.0325 (0.0414) Prec@1 95.000 (92.500) Prec@5 100.000 (99.643) +2022-11-14 14:31:30,681 Epoch: [211][140/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0504 (0.0420) Prec@1 91.000 (92.400) Prec@5 100.000 (99.667) +2022-11-14 14:31:31,079 Epoch: [211][150/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0525 (0.0426) Prec@1 91.000 (92.312) Prec@5 100.000 (99.688) +2022-11-14 14:31:31,482 Epoch: [211][160/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0535 (0.0433) Prec@1 91.000 (92.235) Prec@5 98.000 (99.588) +2022-11-14 14:31:31,881 Epoch: [211][170/500] Time 0.036 (0.032) Data 0.003 (0.003) Loss 0.0382 (0.0430) Prec@1 93.000 (92.278) Prec@5 99.000 (99.556) +2022-11-14 14:31:32,276 Epoch: [211][180/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0228 (0.0419) Prec@1 96.000 (92.474) Prec@5 100.000 (99.579) +2022-11-14 14:31:32,672 Epoch: [211][190/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0401 (0.0418) Prec@1 96.000 (92.650) Prec@5 100.000 (99.600) +2022-11-14 14:31:33,067 Epoch: [211][200/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0367 (0.0416) Prec@1 94.000 (92.714) Prec@5 100.000 (99.619) +2022-11-14 14:31:33,465 Epoch: [211][210/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0244 (0.0408) Prec@1 95.000 (92.818) Prec@5 100.000 (99.636) +2022-11-14 14:31:33,860 Epoch: [211][220/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0307 (0.0404) Prec@1 95.000 (92.913) Prec@5 100.000 (99.652) +2022-11-14 14:31:34,254 Epoch: [211][230/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0292 (0.0399) Prec@1 96.000 (93.042) Prec@5 100.000 (99.667) +2022-11-14 14:31:34,651 Epoch: [211][240/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0470 (0.0402) Prec@1 92.000 (93.000) Prec@5 99.000 (99.640) +2022-11-14 14:31:35,049 Epoch: [211][250/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0333 (0.0399) Prec@1 94.000 (93.038) Prec@5 99.000 (99.615) +2022-11-14 14:31:35,452 Epoch: [211][260/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0158 (0.0390) Prec@1 97.000 (93.185) Prec@5 100.000 (99.630) +2022-11-14 14:31:35,850 Epoch: [211][270/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0428 (0.0392) Prec@1 93.000 (93.179) Prec@5 100.000 (99.643) +2022-11-14 14:31:36,249 Epoch: [211][280/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0360 (0.0391) Prec@1 93.000 (93.172) Prec@5 100.000 (99.655) +2022-11-14 14:31:36,646 Epoch: [211][290/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0439 (0.0392) Prec@1 94.000 (93.200) Prec@5 99.000 (99.633) +2022-11-14 14:31:37,039 Epoch: [211][300/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0305 (0.0389) Prec@1 93.000 (93.194) Prec@5 100.000 (99.645) +2022-11-14 14:31:37,438 Epoch: [211][310/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0660 (0.0398) Prec@1 87.000 (93.000) Prec@5 99.000 (99.625) +2022-11-14 14:31:37,838 Epoch: [211][320/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0426 (0.0399) Prec@1 93.000 (93.000) Prec@5 100.000 (99.636) +2022-11-14 14:31:38,237 Epoch: [211][330/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0207 (0.0393) Prec@1 96.000 (93.088) Prec@5 100.000 (99.647) +2022-11-14 14:31:38,629 Epoch: [211][340/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0588 (0.0399) Prec@1 91.000 (93.029) Prec@5 100.000 (99.657) +2022-11-14 14:31:39,021 Epoch: [211][350/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0283 (0.0395) Prec@1 95.000 (93.083) Prec@5 100.000 (99.667) +2022-11-14 14:31:39,415 Epoch: [211][360/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0505 (0.0398) Prec@1 93.000 (93.081) Prec@5 99.000 (99.649) +2022-11-14 14:31:39,809 Epoch: [211][370/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0352 (0.0397) Prec@1 94.000 (93.105) Prec@5 99.000 (99.632) +2022-11-14 14:31:40,208 Epoch: [211][380/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0673 (0.0404) Prec@1 90.000 (93.026) Prec@5 100.000 (99.641) +2022-11-14 14:31:40,608 Epoch: [211][390/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0464 (0.0406) Prec@1 93.000 (93.025) Prec@5 100.000 (99.650) +2022-11-14 14:31:41,008 Epoch: [211][400/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0370 (0.0405) Prec@1 93.000 (93.024) Prec@5 100.000 (99.659) +2022-11-14 14:31:41,401 Epoch: [211][410/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0345 (0.0403) Prec@1 95.000 (93.071) Prec@5 100.000 (99.667) +2022-11-14 14:31:41,797 Epoch: [211][420/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0621 (0.0408) Prec@1 91.000 (93.023) Prec@5 100.000 (99.674) +2022-11-14 14:31:42,188 Epoch: [211][430/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0485 (0.0410) Prec@1 90.000 (92.955) Prec@5 100.000 (99.682) +2022-11-14 14:31:42,580 Epoch: [211][440/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0375 (0.0409) Prec@1 95.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 14:31:42,977 Epoch: [211][450/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0259 (0.0406) Prec@1 94.000 (93.022) Prec@5 100.000 (99.674) +2022-11-14 14:31:43,371 Epoch: [211][460/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0569 (0.0410) Prec@1 89.000 (92.936) Prec@5 99.000 (99.660) +2022-11-14 14:31:43,760 Epoch: [211][470/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0521 (0.0412) Prec@1 91.000 (92.896) Prec@5 99.000 (99.646) +2022-11-14 14:31:44,155 Epoch: [211][480/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0417 (0.0412) Prec@1 92.000 (92.878) Prec@5 99.000 (99.633) +2022-11-14 14:31:44,545 Epoch: [211][490/500] Time 0.036 (0.034) Data 0.001 (0.002) Loss 0.0349 (0.0411) Prec@1 91.000 (92.840) Prec@5 100.000 (99.640) +2022-11-14 14:31:44,902 Epoch: [211][499/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0360 (0.0410) Prec@1 96.000 (92.902) Prec@5 100.000 (99.647) +2022-11-14 14:31:45,171 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0588 (0.0588) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:45,182 Test: [1/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0599 (0.0593) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:31:45,192 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0808 (0.0665) Prec@1 86.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 14:31:45,205 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0709) Prec@1 86.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 14:31:45,213 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0719) Prec@1 86.000 (87.400) Prec@5 100.000 (99.800) +2022-11-14 14:31:45,224 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0404 (0.0667) Prec@1 92.000 (88.167) Prec@5 99.000 (99.667) +2022-11-14 14:31:45,235 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0672) Prec@1 85.000 (87.714) Prec@5 100.000 (99.714) +2022-11-14 14:31:45,245 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0688) Prec@1 88.000 (87.750) Prec@5 100.000 (99.750) +2022-11-14 14:31:45,254 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0696) Prec@1 88.000 (87.778) Prec@5 100.000 (99.778) +2022-11-14 14:31:45,267 Test: [9/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0716) Prec@1 85.000 (87.500) Prec@5 99.000 (99.700) +2022-11-14 14:31:45,279 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0717) Prec@1 88.000 (87.545) Prec@5 100.000 (99.727) +2022-11-14 14:31:45,291 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0739) Prec@1 84.000 (87.250) Prec@5 99.000 (99.667) +2022-11-14 14:31:45,301 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0726) Prec@1 90.000 (87.462) Prec@5 100.000 (99.692) +2022-11-14 14:31:45,310 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0731) Prec@1 86.000 (87.357) Prec@5 100.000 (99.714) +2022-11-14 14:31:45,320 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0727) Prec@1 89.000 (87.467) Prec@5 98.000 (99.600) +2022-11-14 14:31:45,332 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0729) Prec@1 88.000 (87.500) Prec@5 98.000 (99.500) +2022-11-14 14:31:45,342 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0439 (0.0712) Prec@1 94.000 (87.882) Prec@5 99.000 (99.471) +2022-11-14 14:31:45,352 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0725) Prec@1 84.000 (87.667) Prec@5 100.000 (99.500) +2022-11-14 14:31:45,361 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0726) Prec@1 85.000 (87.526) Prec@5 99.000 (99.474) +2022-11-14 14:31:45,372 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0737) Prec@1 85.000 (87.400) Prec@5 100.000 (99.500) +2022-11-14 14:31:45,383 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0743) Prec@1 86.000 (87.333) Prec@5 99.000 (99.476) +2022-11-14 14:31:45,393 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0747) Prec@1 87.000 (87.318) Prec@5 98.000 (99.409) +2022-11-14 14:31:45,402 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0754) Prec@1 89.000 (87.391) Prec@5 100.000 (99.435) +2022-11-14 14:31:45,411 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0756) Prec@1 89.000 (87.458) Prec@5 100.000 (99.458) +2022-11-14 14:31:45,421 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0756) Prec@1 89.000 (87.520) Prec@5 100.000 (99.480) +2022-11-14 14:31:45,429 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0764) Prec@1 84.000 (87.385) Prec@5 98.000 (99.423) +2022-11-14 14:31:45,439 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0757) Prec@1 91.000 (87.519) Prec@5 100.000 (99.444) +2022-11-14 14:31:45,448 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0759) Prec@1 88.000 (87.536) Prec@5 100.000 (99.464) +2022-11-14 14:31:45,457 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0758) Prec@1 87.000 (87.517) Prec@5 99.000 (99.448) +2022-11-14 14:31:45,467 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0754) Prec@1 90.000 (87.600) Prec@5 100.000 (99.467) +2022-11-14 14:31:45,476 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0758) Prec@1 85.000 (87.516) Prec@5 100.000 (99.484) +2022-11-14 14:31:45,485 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0757) Prec@1 88.000 (87.531) Prec@5 100.000 (99.500) +2022-11-14 14:31:45,495 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0759) Prec@1 85.000 (87.455) Prec@5 100.000 (99.515) +2022-11-14 14:31:45,504 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0759) Prec@1 85.000 (87.382) Prec@5 100.000 (99.529) +2022-11-14 14:31:45,513 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0759) Prec@1 86.000 (87.343) Prec@5 99.000 (99.514) +2022-11-14 14:31:45,522 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0755) Prec@1 90.000 (87.417) Prec@5 100.000 (99.528) +2022-11-14 14:31:45,532 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0752) Prec@1 91.000 (87.514) Prec@5 99.000 (99.514) +2022-11-14 14:31:45,541 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0760) Prec@1 81.000 (87.342) Prec@5 100.000 (99.526) +2022-11-14 14:31:45,551 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0755) Prec@1 90.000 (87.410) Prec@5 99.000 (99.513) +2022-11-14 14:31:45,559 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0750) Prec@1 90.000 (87.475) Prec@5 99.000 (99.500) +2022-11-14 14:31:45,568 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0753) Prec@1 86.000 (87.439) Prec@5 99.000 (99.488) +2022-11-14 14:31:45,578 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0752) Prec@1 89.000 (87.476) Prec@5 100.000 (99.500) +2022-11-14 14:31:45,587 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0746) Prec@1 92.000 (87.581) Prec@5 99.000 (99.488) +2022-11-14 14:31:45,596 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0746) Prec@1 88.000 (87.591) Prec@5 97.000 (99.432) +2022-11-14 14:31:45,605 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0749) Prec@1 85.000 (87.533) Prec@5 99.000 (99.422) +2022-11-14 14:31:45,615 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.0758) Prec@1 80.000 (87.370) Prec@5 99.000 (99.413) +2022-11-14 14:31:45,624 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0757) Prec@1 88.000 (87.383) Prec@5 100.000 (99.426) +2022-11-14 14:31:45,633 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0760) Prec@1 86.000 (87.354) Prec@5 98.000 (99.396) +2022-11-14 14:31:45,643 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0757) Prec@1 90.000 (87.408) Prec@5 99.000 (99.388) +2022-11-14 14:31:45,652 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0760) Prec@1 85.000 (87.360) Prec@5 100.000 (99.400) +2022-11-14 14:31:45,660 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0753) Prec@1 91.000 (87.431) Prec@5 100.000 (99.412) +2022-11-14 14:31:45,668 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0755) Prec@1 86.000 (87.404) Prec@5 100.000 (99.423) +2022-11-14 14:31:45,677 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0755) Prec@1 85.000 (87.358) Prec@5 100.000 (99.434) +2022-11-14 14:31:45,686 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0755) Prec@1 87.000 (87.352) Prec@5 99.000 (99.426) +2022-11-14 14:31:45,695 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0754) Prec@1 88.000 (87.364) Prec@5 100.000 (99.436) +2022-11-14 14:31:45,704 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0752) Prec@1 90.000 (87.411) Prec@5 99.000 (99.429) +2022-11-14 14:31:45,713 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0749) Prec@1 90.000 (87.456) Prec@5 100.000 (99.439) +2022-11-14 14:31:45,721 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0747) Prec@1 91.000 (87.517) Prec@5 99.000 (99.431) +2022-11-14 14:31:45,731 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0745) Prec@1 88.000 (87.525) Prec@5 100.000 (99.441) +2022-11-14 14:31:45,741 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0746) Prec@1 86.000 (87.500) Prec@5 100.000 (99.450) +2022-11-14 14:31:45,750 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0745) Prec@1 90.000 (87.541) Prec@5 100.000 (99.459) +2022-11-14 14:31:45,759 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0743) Prec@1 90.000 (87.581) Prec@5 100.000 (99.468) +2022-11-14 14:31:45,768 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0740) Prec@1 92.000 (87.651) Prec@5 100.000 (99.476) +2022-11-14 14:31:45,777 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0736) Prec@1 91.000 (87.703) Prec@5 99.000 (99.469) +2022-11-14 14:31:45,787 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0739) Prec@1 84.000 (87.646) Prec@5 100.000 (99.477) +2022-11-14 14:31:45,796 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0739) Prec@1 86.000 (87.621) Prec@5 98.000 (99.455) +2022-11-14 14:31:45,805 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0738) Prec@1 89.000 (87.642) Prec@5 100.000 (99.463) +2022-11-14 14:31:45,815 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0738) Prec@1 87.000 (87.632) Prec@5 100.000 (99.471) +2022-11-14 14:31:45,824 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0736) Prec@1 92.000 (87.696) Prec@5 100.000 (99.478) +2022-11-14 14:31:45,833 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0737) Prec@1 85.000 (87.657) Prec@5 99.000 (99.471) +2022-11-14 14:31:45,843 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.0743) Prec@1 80.000 (87.549) Prec@5 100.000 (99.479) +2022-11-14 14:31:45,853 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0741) Prec@1 89.000 (87.569) Prec@5 100.000 (99.486) +2022-11-14 14:31:45,861 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0739) Prec@1 91.000 (87.616) Prec@5 100.000 (99.493) +2022-11-14 14:31:45,871 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0735) Prec@1 94.000 (87.703) Prec@5 100.000 (99.500) +2022-11-14 14:31:45,880 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0737) Prec@1 85.000 (87.667) Prec@5 100.000 (99.507) +2022-11-14 14:31:45,890 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0736) Prec@1 91.000 (87.711) Prec@5 98.000 (99.487) +2022-11-14 14:31:45,900 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0735) Prec@1 90.000 (87.740) Prec@5 99.000 (99.481) +2022-11-14 14:31:45,908 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0737) Prec@1 87.000 (87.731) Prec@5 96.000 (99.436) +2022-11-14 14:31:45,918 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0737) Prec@1 85.000 (87.696) Prec@5 99.000 (99.430) +2022-11-14 14:31:45,928 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0736) Prec@1 89.000 (87.713) Prec@5 100.000 (99.438) +2022-11-14 14:31:45,936 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0736) Prec@1 88.000 (87.716) Prec@5 98.000 (99.420) +2022-11-14 14:31:45,946 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0739) Prec@1 85.000 (87.683) Prec@5 98.000 (99.402) +2022-11-14 14:31:45,954 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0742) Prec@1 80.000 (87.590) Prec@5 100.000 (99.410) +2022-11-14 14:31:45,962 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0744) Prec@1 84.000 (87.548) Prec@5 99.000 (99.405) +2022-11-14 14:31:45,971 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0746) Prec@1 86.000 (87.529) Prec@5 98.000 (99.388) +2022-11-14 14:31:45,981 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0748) Prec@1 86.000 (87.512) Prec@5 100.000 (99.395) +2022-11-14 14:31:45,990 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0749) Prec@1 86.000 (87.494) Prec@5 100.000 (99.402) +2022-11-14 14:31:45,999 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0749) Prec@1 86.000 (87.477) Prec@5 99.000 (99.398) +2022-11-14 14:31:46,009 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0747) Prec@1 89.000 (87.494) Prec@5 100.000 (99.404) +2022-11-14 14:31:46,018 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0745) Prec@1 91.000 (87.533) Prec@5 100.000 (99.411) +2022-11-14 14:31:46,027 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0744) Prec@1 91.000 (87.571) Prec@5 99.000 (99.407) +2022-11-14 14:31:46,037 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0742) Prec@1 91.000 (87.609) Prec@5 98.000 (99.391) +2022-11-14 14:31:46,046 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0744) Prec@1 80.000 (87.527) Prec@5 100.000 (99.398) +2022-11-14 14:31:46,055 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 87.000 (87.521) Prec@5 100.000 (99.404) +2022-11-14 14:31:46,064 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0745) Prec@1 86.000 (87.505) Prec@5 99.000 (99.400) +2022-11-14 14:31:46,073 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0744) Prec@1 89.000 (87.521) Prec@5 99.000 (99.396) +2022-11-14 14:31:46,082 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0362 (0.0741) Prec@1 94.000 (87.588) Prec@5 99.000 (99.392) +2022-11-14 14:31:46,090 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0743) Prec@1 86.000 (87.571) Prec@5 99.000 (99.388) +2022-11-14 14:31:46,100 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0744) Prec@1 84.000 (87.535) Prec@5 100.000 (99.394) +2022-11-14 14:31:46,108 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0743) Prec@1 90.000 (87.560) Prec@5 100.000 (99.400) +2022-11-14 14:31:46,163 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:31:46,468 Epoch: [212][0/500] Time 0.026 (0.026) Data 0.222 (0.222) Loss 0.0345 (0.0345) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:46,674 Epoch: [212][10/500] Time 0.020 (0.019) Data 0.001 (0.022) Loss 0.0332 (0.0338) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:31:46,907 Epoch: [212][20/500] Time 0.024 (0.020) Data 0.002 (0.012) Loss 0.0181 (0.0286) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 14:31:47,183 Epoch: [212][30/500] Time 0.026 (0.021) Data 0.002 (0.009) Loss 0.0406 (0.0316) Prec@1 94.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 14:31:47,504 Epoch: [212][40/500] Time 0.037 (0.023) Data 0.002 (0.007) Loss 0.0427 (0.0338) Prec@1 93.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 14:31:47,950 Epoch: [212][50/500] Time 0.043 (0.026) Data 0.001 (0.006) Loss 0.0415 (0.0351) Prec@1 92.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:31:48,394 Epoch: [212][60/500] Time 0.038 (0.028) Data 0.002 (0.005) Loss 0.0554 (0.0380) Prec@1 91.000 (93.857) Prec@5 98.000 (99.714) +2022-11-14 14:31:48,837 Epoch: [212][70/500] Time 0.044 (0.030) Data 0.002 (0.005) Loss 0.0285 (0.0368) Prec@1 95.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 14:31:49,281 Epoch: [212][80/500] Time 0.042 (0.031) Data 0.001 (0.004) Loss 0.0299 (0.0360) Prec@1 95.000 (94.111) Prec@5 100.000 (99.778) +2022-11-14 14:31:49,727 Epoch: [212][90/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.0453 (0.0370) Prec@1 91.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:31:50,162 Epoch: [212][100/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0379 (0.0371) Prec@1 93.000 (93.727) Prec@5 100.000 (99.818) +2022-11-14 14:31:50,605 Epoch: [212][110/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0249 (0.0360) Prec@1 96.000 (93.917) Prec@5 100.000 (99.833) +2022-11-14 14:31:51,041 Epoch: [212][120/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0547 (0.0375) Prec@1 90.000 (93.615) Prec@5 100.000 (99.846) +2022-11-14 14:31:51,485 Epoch: [212][130/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0322 (0.0371) Prec@1 95.000 (93.714) Prec@5 100.000 (99.857) +2022-11-14 14:31:51,921 Epoch: [212][140/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0415 (0.0374) Prec@1 93.000 (93.667) Prec@5 99.000 (99.800) +2022-11-14 14:31:52,365 Epoch: [212][150/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0593 (0.0388) Prec@1 88.000 (93.312) Prec@5 100.000 (99.812) +2022-11-14 14:31:52,800 Epoch: [212][160/500] Time 0.044 (0.035) Data 0.001 (0.003) Loss 0.0536 (0.0396) Prec@1 91.000 (93.176) Prec@5 99.000 (99.765) +2022-11-14 14:31:53,240 Epoch: [212][170/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0406 (0.0397) Prec@1 92.000 (93.111) Prec@5 100.000 (99.778) +2022-11-14 14:31:53,683 Epoch: [212][180/500] Time 0.043 (0.035) Data 0.001 (0.003) Loss 0.0319 (0.0393) Prec@1 95.000 (93.211) Prec@5 100.000 (99.789) +2022-11-14 14:31:54,123 Epoch: [212][190/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0358 (0.0391) Prec@1 95.000 (93.300) Prec@5 100.000 (99.800) +2022-11-14 14:31:54,559 Epoch: [212][200/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0563 (0.0399) Prec@1 90.000 (93.143) Prec@5 99.000 (99.762) +2022-11-14 14:31:54,999 Epoch: [212][210/500] Time 0.043 (0.036) Data 0.001 (0.003) Loss 0.0291 (0.0394) Prec@1 94.000 (93.182) Prec@5 100.000 (99.773) +2022-11-14 14:31:55,436 Epoch: [212][220/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0187 (0.0385) Prec@1 97.000 (93.348) Prec@5 100.000 (99.783) +2022-11-14 14:31:55,880 Epoch: [212][230/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0136 (0.0375) Prec@1 98.000 (93.542) Prec@5 100.000 (99.792) +2022-11-14 14:31:56,320 Epoch: [212][240/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0305 (0.0372) Prec@1 96.000 (93.640) Prec@5 100.000 (99.800) +2022-11-14 14:31:56,744 Epoch: [212][250/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0276 (0.0368) Prec@1 95.000 (93.692) Prec@5 99.000 (99.769) +2022-11-14 14:31:57,174 Epoch: [212][260/500] Time 0.041 (0.036) Data 0.001 (0.003) Loss 0.0621 (0.0378) Prec@1 88.000 (93.481) Prec@5 100.000 (99.778) +2022-11-14 14:31:57,610 Epoch: [212][270/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0373 (0.0378) Prec@1 96.000 (93.571) Prec@5 100.000 (99.786) +2022-11-14 14:31:58,050 Epoch: [212][280/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0790 (0.0392) Prec@1 87.000 (93.345) Prec@5 100.000 (99.793) +2022-11-14 14:31:58,496 Epoch: [212][290/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0444 (0.0394) Prec@1 94.000 (93.367) Prec@5 99.000 (99.767) +2022-11-14 14:31:58,924 Epoch: [212][300/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0430 (0.0395) Prec@1 93.000 (93.355) Prec@5 97.000 (99.677) +2022-11-14 14:31:59,359 Epoch: [212][310/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0395 (0.0395) Prec@1 94.000 (93.375) Prec@5 100.000 (99.688) +2022-11-14 14:31:59,797 Epoch: [212][320/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0358 (0.0394) Prec@1 93.000 (93.364) Prec@5 99.000 (99.667) +2022-11-14 14:32:00,237 Epoch: [212][330/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0491 (0.0396) Prec@1 92.000 (93.324) Prec@5 99.000 (99.647) +2022-11-14 14:32:00,673 Epoch: [212][340/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0285 (0.0393) Prec@1 94.000 (93.343) Prec@5 100.000 (99.657) +2022-11-14 14:32:01,107 Epoch: [212][350/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0536 (0.0397) Prec@1 91.000 (93.278) Prec@5 100.000 (99.667) +2022-11-14 14:32:01,545 Epoch: [212][360/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0249 (0.0393) Prec@1 97.000 (93.378) Prec@5 100.000 (99.676) +2022-11-14 14:32:01,980 Epoch: [212][370/500] Time 0.038 (0.037) Data 0.001 (0.002) Loss 0.0378 (0.0393) Prec@1 93.000 (93.368) Prec@5 100.000 (99.684) +2022-11-14 14:32:02,422 Epoch: [212][380/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0422 (0.0394) Prec@1 94.000 (93.385) Prec@5 100.000 (99.692) +2022-11-14 14:32:02,860 Epoch: [212][390/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0474 (0.0396) Prec@1 91.000 (93.325) Prec@5 100.000 (99.700) +2022-11-14 14:32:03,305 Epoch: [212][400/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0326 (0.0394) Prec@1 94.000 (93.341) Prec@5 100.000 (99.707) +2022-11-14 14:32:03,743 Epoch: [212][410/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0443 (0.0395) Prec@1 92.000 (93.310) Prec@5 100.000 (99.714) +2022-11-14 14:32:04,184 Epoch: [212][420/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0554 (0.0399) Prec@1 92.000 (93.279) Prec@5 100.000 (99.721) +2022-11-14 14:32:04,624 Epoch: [212][430/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0362 (0.0398) Prec@1 96.000 (93.341) Prec@5 100.000 (99.727) +2022-11-14 14:32:05,063 Epoch: [212][440/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0379 (0.0398) Prec@1 95.000 (93.378) Prec@5 99.000 (99.711) +2022-11-14 14:32:05,506 Epoch: [212][450/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0412 (0.0398) Prec@1 95.000 (93.413) Prec@5 100.000 (99.717) +2022-11-14 14:32:05,943 Epoch: [212][460/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0413 (0.0398) Prec@1 92.000 (93.383) Prec@5 100.000 (99.723) +2022-11-14 14:32:06,375 Epoch: [212][470/500] Time 0.035 (0.038) Data 0.002 (0.002) Loss 0.0287 (0.0396) Prec@1 96.000 (93.438) Prec@5 100.000 (99.729) +2022-11-14 14:32:06,801 Epoch: [212][480/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0524 (0.0398) Prec@1 92.000 (93.408) Prec@5 99.000 (99.714) +2022-11-14 14:32:07,235 Epoch: [212][490/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0473 (0.0400) Prec@1 91.000 (93.360) Prec@5 100.000 (99.720) +2022-11-14 14:32:07,623 Epoch: [212][499/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0281 (0.0398) Prec@1 94.000 (93.373) Prec@5 100.000 (99.725) +2022-11-14 14:32:07,911 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0553 (0.0553) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:07,918 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0641) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:07,930 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0689) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:07,941 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0695) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:07,948 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0702) Prec@1 87.000 (88.600) Prec@5 99.000 (99.800) +2022-11-14 14:32:07,956 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0652) Prec@1 95.000 (89.667) Prec@5 100.000 (99.833) +2022-11-14 14:32:07,965 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0674) Prec@1 87.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 14:32:07,975 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0687) Prec@1 87.000 (89.000) Prec@5 98.000 (99.625) +2022-11-14 14:32:07,983 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0696) Prec@1 87.000 (88.778) Prec@5 98.000 (99.444) +2022-11-14 14:32:07,992 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0699) Prec@1 90.000 (88.900) Prec@5 99.000 (99.400) +2022-11-14 14:32:08,002 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0689) Prec@1 92.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 14:32:08,012 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0700) Prec@1 88.000 (89.083) Prec@5 97.000 (99.250) +2022-11-14 14:32:08,022 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0688) Prec@1 91.000 (89.231) Prec@5 100.000 (99.308) +2022-11-14 14:32:08,032 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0682) Prec@1 90.000 (89.286) Prec@5 100.000 (99.357) +2022-11-14 14:32:08,041 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0674) Prec@1 92.000 (89.467) Prec@5 100.000 (99.400) +2022-11-14 14:32:08,052 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0681) Prec@1 88.000 (89.375) Prec@5 100.000 (99.438) +2022-11-14 14:32:08,061 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0678) Prec@1 91.000 (89.471) Prec@5 99.000 (99.412) +2022-11-14 14:32:08,071 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0698) Prec@1 81.000 (89.000) Prec@5 100.000 (99.444) +2022-11-14 14:32:08,080 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0714) Prec@1 82.000 (88.632) Prec@5 99.000 (99.421) +2022-11-14 14:32:08,089 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0722) Prec@1 84.000 (88.400) Prec@5 100.000 (99.450) +2022-11-14 14:32:08,099 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0730) Prec@1 84.000 (88.190) Prec@5 99.000 (99.429) +2022-11-14 14:32:08,108 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0734) Prec@1 87.000 (88.136) Prec@5 100.000 (99.455) +2022-11-14 14:32:08,117 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0747) Prec@1 86.000 (88.043) Prec@5 97.000 (99.348) +2022-11-14 14:32:08,127 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0738) Prec@1 92.000 (88.208) Prec@5 100.000 (99.375) +2022-11-14 14:32:08,136 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0750) Prec@1 84.000 (88.040) Prec@5 99.000 (99.360) +2022-11-14 14:32:08,145 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0756) Prec@1 84.000 (87.885) Prec@5 99.000 (99.346) +2022-11-14 14:32:08,153 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0749) Prec@1 90.000 (87.963) Prec@5 100.000 (99.370) +2022-11-14 14:32:08,162 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0747) Prec@1 90.000 (88.036) Prec@5 100.000 (99.393) +2022-11-14 14:32:08,171 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0750) Prec@1 86.000 (87.966) Prec@5 99.000 (99.379) +2022-11-14 14:32:08,180 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0749) Prec@1 86.000 (87.900) Prec@5 98.000 (99.333) +2022-11-14 14:32:08,191 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0751) Prec@1 87.000 (87.871) Prec@5 100.000 (99.355) +2022-11-14 14:32:08,200 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0758) Prec@1 84.000 (87.750) Prec@5 100.000 (99.375) +2022-11-14 14:32:08,211 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0758) Prec@1 87.000 (87.727) Prec@5 100.000 (99.394) +2022-11-14 14:32:08,221 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0759) Prec@1 85.000 (87.647) Prec@5 100.000 (99.412) +2022-11-14 14:32:08,231 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0756) Prec@1 89.000 (87.686) Prec@5 97.000 (99.343) +2022-11-14 14:32:08,241 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0758) Prec@1 87.000 (87.667) Prec@5 100.000 (99.361) +2022-11-14 14:32:08,250 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0757) Prec@1 89.000 (87.703) Prec@5 99.000 (99.351) +2022-11-14 14:32:08,262 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0766) Prec@1 83.000 (87.579) Prec@5 99.000 (99.342) +2022-11-14 14:32:08,273 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0761) Prec@1 90.000 (87.641) Prec@5 100.000 (99.359) +2022-11-14 14:32:08,284 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0758) Prec@1 89.000 (87.675) Prec@5 99.000 (99.350) +2022-11-14 14:32:08,295 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0762) Prec@1 86.000 (87.634) Prec@5 98.000 (99.317) +2022-11-14 14:32:08,305 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0757) Prec@1 90.000 (87.690) Prec@5 100.000 (99.333) +2022-11-14 14:32:08,315 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0750) Prec@1 94.000 (87.837) Prec@5 99.000 (99.326) +2022-11-14 14:32:08,325 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0748) Prec@1 87.000 (87.818) Prec@5 99.000 (99.318) +2022-11-14 14:32:08,335 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0747) Prec@1 89.000 (87.844) Prec@5 99.000 (99.311) +2022-11-14 14:32:08,344 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0753) Prec@1 82.000 (87.717) Prec@5 99.000 (99.304) +2022-11-14 14:32:08,354 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0753) Prec@1 86.000 (87.681) Prec@5 100.000 (99.319) +2022-11-14 14:32:08,364 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0754) Prec@1 88.000 (87.688) Prec@5 99.000 (99.312) +2022-11-14 14:32:08,373 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0750) Prec@1 90.000 (87.735) Prec@5 99.000 (99.306) +2022-11-14 14:32:08,383 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0757) Prec@1 83.000 (87.640) Prec@5 98.000 (99.280) +2022-11-14 14:32:08,393 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0756) Prec@1 88.000 (87.647) Prec@5 100.000 (99.294) +2022-11-14 14:32:08,405 Test: [51/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 88.000 (87.654) Prec@5 100.000 (99.308) +2022-11-14 14:32:08,414 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0754) Prec@1 88.000 (87.660) Prec@5 100.000 (99.321) +2022-11-14 14:32:08,423 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0753) Prec@1 88.000 (87.667) Prec@5 98.000 (99.296) +2022-11-14 14:32:08,433 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0754) Prec@1 87.000 (87.655) Prec@5 100.000 (99.309) +2022-11-14 14:32:08,441 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0752) Prec@1 89.000 (87.679) Prec@5 99.000 (99.304) +2022-11-14 14:32:08,451 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0752) Prec@1 86.000 (87.649) Prec@5 100.000 (99.316) +2022-11-14 14:32:08,461 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0750) Prec@1 91.000 (87.707) Prec@5 99.000 (99.310) +2022-11-14 14:32:08,470 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0752) Prec@1 87.000 (87.695) Prec@5 100.000 (99.322) +2022-11-14 14:32:08,479 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0755) Prec@1 84.000 (87.633) Prec@5 99.000 (99.317) +2022-11-14 14:32:08,487 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0754) Prec@1 88.000 (87.639) Prec@5 99.000 (99.311) +2022-11-14 14:32:08,495 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0757) Prec@1 82.000 (87.548) Prec@5 99.000 (99.306) +2022-11-14 14:32:08,504 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0754) Prec@1 92.000 (87.619) Prec@5 100.000 (99.317) +2022-11-14 14:32:08,513 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0351 (0.0748) Prec@1 93.000 (87.703) Prec@5 100.000 (99.328) +2022-11-14 14:32:08,524 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0749) Prec@1 88.000 (87.708) Prec@5 99.000 (99.323) +2022-11-14 14:32:08,533 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0749) Prec@1 87.000 (87.697) Prec@5 99.000 (99.318) +2022-11-14 14:32:08,543 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0397 (0.0744) Prec@1 94.000 (87.791) Prec@5 100.000 (99.328) +2022-11-14 14:32:08,553 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0744) Prec@1 89.000 (87.809) Prec@5 99.000 (99.324) +2022-11-14 14:32:08,562 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0741) Prec@1 89.000 (87.826) Prec@5 100.000 (99.333) +2022-11-14 14:32:08,572 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0741) Prec@1 90.000 (87.857) Prec@5 98.000 (99.314) +2022-11-14 14:32:08,582 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0742) Prec@1 88.000 (87.859) Prec@5 100.000 (99.324) +2022-11-14 14:32:08,592 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0743) Prec@1 87.000 (87.847) Prec@5 100.000 (99.333) +2022-11-14 14:32:08,601 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0739) Prec@1 92.000 (87.904) Prec@5 100.000 (99.342) +2022-11-14 14:32:08,611 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0486 (0.0736) Prec@1 92.000 (87.959) Prec@5 100.000 (99.351) +2022-11-14 14:32:08,621 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0737) Prec@1 87.000 (87.947) Prec@5 100.000 (99.360) +2022-11-14 14:32:08,631 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0737) Prec@1 87.000 (87.934) Prec@5 99.000 (99.355) +2022-11-14 14:32:08,641 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0734) Prec@1 90.000 (87.961) Prec@5 100.000 (99.364) +2022-11-14 14:32:08,650 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0737) Prec@1 83.000 (87.897) Prec@5 100.000 (99.372) +2022-11-14 14:32:08,660 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0737) Prec@1 87.000 (87.886) Prec@5 100.000 (99.380) +2022-11-14 14:32:08,670 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0738) Prec@1 88.000 (87.888) Prec@5 100.000 (99.388) +2022-11-14 14:32:08,680 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0738) Prec@1 90.000 (87.914) Prec@5 99.000 (99.383) +2022-11-14 14:32:08,690 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0738) Prec@1 87.000 (87.902) Prec@5 99.000 (99.378) +2022-11-14 14:32:08,699 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0743) Prec@1 84.000 (87.855) Prec@5 100.000 (99.386) +2022-11-14 14:32:08,708 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0741) Prec@1 91.000 (87.893) Prec@5 99.000 (99.381) +2022-11-14 14:32:08,718 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0744) Prec@1 83.000 (87.835) Prec@5 98.000 (99.365) +2022-11-14 14:32:08,728 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0745) Prec@1 86.000 (87.814) Prec@5 100.000 (99.372) +2022-11-14 14:32:08,738 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0745) Prec@1 88.000 (87.816) Prec@5 100.000 (99.379) +2022-11-14 14:32:08,748 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0745) Prec@1 90.000 (87.841) Prec@5 99.000 (99.375) +2022-11-14 14:32:08,757 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0742) Prec@1 91.000 (87.876) Prec@5 100.000 (99.382) +2022-11-14 14:32:08,767 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0742) Prec@1 89.000 (87.889) Prec@5 100.000 (99.389) +2022-11-14 14:32:08,776 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0740) Prec@1 90.000 (87.912) Prec@5 100.000 (99.396) +2022-11-14 14:32:08,786 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0737) Prec@1 93.000 (87.967) Prec@5 99.000 (99.391) +2022-11-14 14:32:08,796 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0740) Prec@1 84.000 (87.925) Prec@5 99.000 (99.387) +2022-11-14 14:32:08,805 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0740) Prec@1 88.000 (87.926) Prec@5 99.000 (99.383) +2022-11-14 14:32:08,815 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0740) Prec@1 89.000 (87.937) Prec@5 99.000 (99.379) +2022-11-14 14:32:08,824 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0739) Prec@1 89.000 (87.948) Prec@5 100.000 (99.385) +2022-11-14 14:32:08,833 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0737) Prec@1 91.000 (87.979) Prec@5 99.000 (99.381) +2022-11-14 14:32:08,843 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0738) Prec@1 87.000 (87.969) Prec@5 99.000 (99.378) +2022-11-14 14:32:08,852 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1091 (0.0742) Prec@1 83.000 (87.919) Prec@5 100.000 (99.384) +2022-11-14 14:32:08,863 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0741) Prec@1 89.000 (87.930) Prec@5 100.000 (99.390) +2022-11-14 14:32:08,937 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:32:09,245 Epoch: [213][0/500] Time 0.030 (0.030) Data 0.223 (0.223) Loss 0.0380 (0.0380) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:09,453 Epoch: [213][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0213 (0.0296) Prec@1 96.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:09,654 Epoch: [213][20/500] Time 0.016 (0.019) Data 0.002 (0.012) Loss 0.0307 (0.0300) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:32:09,857 Epoch: [213][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0316 (0.0304) Prec@1 95.000 (94.750) Prec@5 99.000 (99.750) +2022-11-14 14:32:10,129 Epoch: [213][40/500] Time 0.030 (0.020) Data 0.001 (0.007) Loss 0.0388 (0.0321) Prec@1 92.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:32:10,445 Epoch: [213][50/500] Time 0.030 (0.021) Data 0.002 (0.006) Loss 0.0553 (0.0360) Prec@1 91.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:32:10,760 Epoch: [213][60/500] Time 0.030 (0.022) Data 0.002 (0.005) Loss 0.0373 (0.0361) Prec@1 94.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 14:32:11,078 Epoch: [213][70/500] Time 0.030 (0.023) Data 0.001 (0.005) Loss 0.0384 (0.0364) Prec@1 93.000 (93.625) Prec@5 100.000 (99.750) +2022-11-14 14:32:11,395 Epoch: [213][80/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0363 (0.0364) Prec@1 93.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 14:32:11,704 Epoch: [213][90/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0304 (0.0358) Prec@1 95.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 14:32:12,018 Epoch: [213][100/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0529 (0.0374) Prec@1 91.000 (93.455) Prec@5 100.000 (99.818) +2022-11-14 14:32:12,336 Epoch: [213][110/500] Time 0.032 (0.025) Data 0.002 (0.004) Loss 0.0589 (0.0392) Prec@1 89.000 (93.083) Prec@5 99.000 (99.750) +2022-11-14 14:32:12,648 Epoch: [213][120/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0256 (0.0381) Prec@1 95.000 (93.231) Prec@5 100.000 (99.769) +2022-11-14 14:32:12,959 Epoch: [213][130/500] Time 0.033 (0.025) Data 0.001 (0.003) Loss 0.0275 (0.0374) Prec@1 96.000 (93.429) Prec@5 100.000 (99.786) +2022-11-14 14:32:13,272 Epoch: [213][140/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0299 (0.0369) Prec@1 94.000 (93.467) Prec@5 100.000 (99.800) +2022-11-14 14:32:13,591 Epoch: [213][150/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0353 (0.0368) Prec@1 94.000 (93.500) Prec@5 100.000 (99.812) +2022-11-14 14:32:13,910 Epoch: [213][160/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0381 (0.0368) Prec@1 95.000 (93.588) Prec@5 100.000 (99.824) +2022-11-14 14:32:14,225 Epoch: [213][170/500] Time 0.030 (0.026) Data 0.001 (0.003) Loss 0.0353 (0.0368) Prec@1 93.000 (93.556) Prec@5 99.000 (99.778) +2022-11-14 14:32:14,537 Epoch: [213][180/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0418 (0.0370) Prec@1 93.000 (93.526) Prec@5 100.000 (99.789) +2022-11-14 14:32:14,860 Epoch: [213][190/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0538 (0.0379) Prec@1 91.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:32:15,182 Epoch: [213][200/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0297 (0.0375) Prec@1 96.000 (93.524) Prec@5 100.000 (99.810) +2022-11-14 14:32:15,505 Epoch: [213][210/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.0297 (0.0371) Prec@1 96.000 (93.636) Prec@5 100.000 (99.818) +2022-11-14 14:32:15,820 Epoch: [213][220/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0518 (0.0378) Prec@1 92.000 (93.565) Prec@5 100.000 (99.826) +2022-11-14 14:32:16,176 Epoch: [213][230/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0392 (0.0378) Prec@1 94.000 (93.583) Prec@5 100.000 (99.833) +2022-11-14 14:32:16,650 Epoch: [213][240/500] Time 0.045 (0.027) Data 0.002 (0.003) Loss 0.0348 (0.0377) Prec@1 94.000 (93.600) Prec@5 100.000 (99.840) +2022-11-14 14:32:17,116 Epoch: [213][250/500] Time 0.044 (0.028) Data 0.003 (0.003) Loss 0.0478 (0.0381) Prec@1 93.000 (93.577) Prec@5 99.000 (99.808) +2022-11-14 14:32:17,588 Epoch: [213][260/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0465 (0.0384) Prec@1 90.000 (93.444) Prec@5 100.000 (99.815) +2022-11-14 14:32:18,052 Epoch: [213][270/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0406 (0.0385) Prec@1 95.000 (93.500) Prec@5 100.000 (99.821) +2022-11-14 14:32:18,525 Epoch: [213][280/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0260 (0.0380) Prec@1 96.000 (93.586) Prec@5 100.000 (99.828) +2022-11-14 14:32:18,994 Epoch: [213][290/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0428 (0.0382) Prec@1 94.000 (93.600) Prec@5 100.000 (99.833) +2022-11-14 14:32:19,470 Epoch: [213][300/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0153 (0.0375) Prec@1 99.000 (93.774) Prec@5 100.000 (99.839) +2022-11-14 14:32:19,933 Epoch: [213][310/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0368 (0.0374) Prec@1 93.000 (93.750) Prec@5 100.000 (99.844) +2022-11-14 14:32:20,405 Epoch: [213][320/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0519 (0.0379) Prec@1 92.000 (93.697) Prec@5 100.000 (99.848) +2022-11-14 14:32:20,867 Epoch: [213][330/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0540 (0.0384) Prec@1 90.000 (93.588) Prec@5 100.000 (99.853) +2022-11-14 14:32:21,339 Epoch: [213][340/500] Time 0.053 (0.032) Data 0.002 (0.002) Loss 0.0339 (0.0382) Prec@1 96.000 (93.657) Prec@5 100.000 (99.857) +2022-11-14 14:32:21,802 Epoch: [213][350/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0425 (0.0384) Prec@1 93.000 (93.639) Prec@5 100.000 (99.861) +2022-11-14 14:32:22,264 Epoch: [213][360/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0160 (0.0377) Prec@1 98.000 (93.757) Prec@5 100.000 (99.865) +2022-11-14 14:32:22,730 Epoch: [213][370/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0379 (0.0378) Prec@1 94.000 (93.763) Prec@5 98.000 (99.816) +2022-11-14 14:32:23,190 Epoch: [213][380/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0456 (0.0380) Prec@1 93.000 (93.744) Prec@5 99.000 (99.795) +2022-11-14 14:32:23,661 Epoch: [213][390/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0240 (0.0376) Prec@1 98.000 (93.850) Prec@5 100.000 (99.800) +2022-11-14 14:32:24,123 Epoch: [213][400/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0381 (0.0376) Prec@1 95.000 (93.878) Prec@5 100.000 (99.805) +2022-11-14 14:32:24,593 Epoch: [213][410/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0391 (0.0377) Prec@1 94.000 (93.881) Prec@5 100.000 (99.810) +2022-11-14 14:32:25,057 Epoch: [213][420/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0249 (0.0374) Prec@1 97.000 (93.953) Prec@5 100.000 (99.814) +2022-11-14 14:32:25,527 Epoch: [213][430/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0402 (0.0374) Prec@1 94.000 (93.955) Prec@5 99.000 (99.795) +2022-11-14 14:32:26,164 Epoch: [213][440/500] Time 0.075 (0.034) Data 0.002 (0.002) Loss 0.0269 (0.0372) Prec@1 96.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 14:32:26,653 Epoch: [213][450/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0422 (0.0373) Prec@1 95.000 (94.022) Prec@5 99.000 (99.783) +2022-11-14 14:32:27,359 Epoch: [213][460/500] Time 0.077 (0.035) Data 0.002 (0.002) Loss 0.0474 (0.0375) Prec@1 93.000 (94.000) Prec@5 100.000 (99.787) +2022-11-14 14:32:27,835 Epoch: [213][470/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0639 (0.0381) Prec@1 89.000 (93.896) Prec@5 99.000 (99.771) +2022-11-14 14:32:28,310 Epoch: [213][480/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0304 (0.0379) Prec@1 95.000 (93.918) Prec@5 100.000 (99.776) +2022-11-14 14:32:28,772 Epoch: [213][490/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0803 (0.0387) Prec@1 85.000 (93.740) Prec@5 100.000 (99.780) +2022-11-14 14:32:29,189 Epoch: [213][499/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0448 (0.0389) Prec@1 91.000 (93.686) Prec@5 100.000 (99.784) +2022-11-14 14:32:29,477 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0497 (0.0497) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:29,485 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0652) Prec@1 88.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 14:32:29,493 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0611) Prec@1 92.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:29,504 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0670) Prec@1 87.000 (90.000) Prec@5 99.000 (99.750) +2022-11-14 14:32:29,513 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0694) Prec@1 86.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 14:32:29,522 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0464 (0.0655) Prec@1 91.000 (89.500) Prec@5 100.000 (99.833) +2022-11-14 14:32:29,530 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0657) Prec@1 90.000 (89.571) Prec@5 99.000 (99.714) +2022-11-14 14:32:29,540 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0663) Prec@1 87.000 (89.250) Prec@5 100.000 (99.750) +2022-11-14 14:32:29,548 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0691) Prec@1 84.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 14:32:29,557 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0690) Prec@1 89.000 (88.700) Prec@5 98.000 (99.500) +2022-11-14 14:32:29,567 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0684) Prec@1 89.000 (88.727) Prec@5 100.000 (99.545) +2022-11-14 14:32:29,577 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0706) Prec@1 86.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:32:29,587 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0690) Prec@1 90.000 (88.615) Prec@5 100.000 (99.538) +2022-11-14 14:32:29,595 Test: [13/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0685) Prec@1 90.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 14:32:29,604 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0689) Prec@1 87.000 (88.600) Prec@5 98.000 (99.467) +2022-11-14 14:32:29,612 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0694) Prec@1 84.000 (88.312) Prec@5 99.000 (99.438) +2022-11-14 14:32:29,622 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0687) Prec@1 91.000 (88.471) Prec@5 99.000 (99.412) +2022-11-14 14:32:29,630 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.0708) Prec@1 82.000 (88.111) Prec@5 100.000 (99.444) +2022-11-14 14:32:29,639 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0720) Prec@1 84.000 (87.895) Prec@5 98.000 (99.368) +2022-11-14 14:32:29,648 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0729) Prec@1 85.000 (87.750) Prec@5 100.000 (99.400) +2022-11-14 14:32:29,658 Test: [20/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0736) Prec@1 87.000 (87.714) Prec@5 97.000 (99.286) +2022-11-14 14:32:29,667 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0740) Prec@1 87.000 (87.682) Prec@5 99.000 (99.273) +2022-11-14 14:32:29,676 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1114 (0.0756) Prec@1 84.000 (87.522) Prec@5 98.000 (99.217) +2022-11-14 14:32:29,685 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0752) Prec@1 88.000 (87.542) Prec@5 100.000 (99.250) +2022-11-14 14:32:29,693 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0757) Prec@1 85.000 (87.440) Prec@5 100.000 (99.280) +2022-11-14 14:32:29,702 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0763) Prec@1 84.000 (87.308) Prec@5 99.000 (99.269) +2022-11-14 14:32:29,711 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0759) Prec@1 89.000 (87.370) Prec@5 100.000 (99.296) +2022-11-14 14:32:29,719 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0754) Prec@1 91.000 (87.500) Prec@5 100.000 (99.321) +2022-11-14 14:32:29,728 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0754) Prec@1 88.000 (87.517) Prec@5 96.000 (99.207) +2022-11-14 14:32:29,737 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0752) Prec@1 88.000 (87.533) Prec@5 100.000 (99.233) +2022-11-14 14:32:29,746 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0747) Prec@1 91.000 (87.645) Prec@5 100.000 (99.258) +2022-11-14 14:32:29,755 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0749) Prec@1 88.000 (87.656) Prec@5 99.000 (99.250) +2022-11-14 14:32:29,763 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0752) Prec@1 85.000 (87.576) Prec@5 98.000 (99.212) +2022-11-14 14:32:29,772 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.0764) Prec@1 80.000 (87.353) Prec@5 100.000 (99.235) +2022-11-14 14:32:29,780 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0764) Prec@1 87.000 (87.343) Prec@5 97.000 (99.171) +2022-11-14 14:32:29,787 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0757) Prec@1 91.000 (87.444) Prec@5 100.000 (99.194) +2022-11-14 14:32:29,795 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0753) Prec@1 88.000 (87.459) Prec@5 99.000 (99.189) +2022-11-14 14:32:29,804 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0754) Prec@1 86.000 (87.421) Prec@5 99.000 (99.184) +2022-11-14 14:32:29,813 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0748) Prec@1 93.000 (87.564) Prec@5 99.000 (99.179) +2022-11-14 14:32:29,822 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0746) Prec@1 91.000 (87.650) Prec@5 99.000 (99.175) +2022-11-14 14:32:29,830 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0752) Prec@1 84.000 (87.561) Prec@5 98.000 (99.146) +2022-11-14 14:32:29,838 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0751) Prec@1 87.000 (87.548) Prec@5 99.000 (99.143) +2022-11-14 14:32:29,847 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0746) Prec@1 93.000 (87.674) Prec@5 99.000 (99.140) +2022-11-14 14:32:29,856 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0745) Prec@1 88.000 (87.682) Prec@5 98.000 (99.114) +2022-11-14 14:32:29,865 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0740) Prec@1 91.000 (87.756) Prec@5 100.000 (99.133) +2022-11-14 14:32:29,874 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0738) Prec@1 88.000 (87.761) Prec@5 100.000 (99.152) +2022-11-14 14:32:29,882 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0736) Prec@1 88.000 (87.766) Prec@5 100.000 (99.170) +2022-11-14 14:32:29,892 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0742) Prec@1 84.000 (87.688) Prec@5 99.000 (99.167) +2022-11-14 14:32:29,900 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0736) Prec@1 91.000 (87.755) Prec@5 99.000 (99.163) +2022-11-14 14:32:29,908 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.0743) Prec@1 86.000 (87.720) Prec@5 100.000 (99.180) +2022-11-14 14:32:29,917 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0743) Prec@1 87.000 (87.706) Prec@5 100.000 (99.196) +2022-11-14 14:32:29,926 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0746) Prec@1 87.000 (87.692) Prec@5 100.000 (99.212) +2022-11-14 14:32:29,934 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0749) Prec@1 86.000 (87.660) Prec@5 100.000 (99.226) +2022-11-14 14:32:29,943 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0750) Prec@1 85.000 (87.611) Prec@5 99.000 (99.222) +2022-11-14 14:32:29,952 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0755) Prec@1 84.000 (87.545) Prec@5 99.000 (99.218) +2022-11-14 14:32:29,962 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0754) Prec@1 88.000 (87.554) Prec@5 99.000 (99.214) +2022-11-14 14:32:29,971 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0752) Prec@1 88.000 (87.561) Prec@5 100.000 (99.228) +2022-11-14 14:32:29,980 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0750) Prec@1 90.000 (87.603) Prec@5 100.000 (99.241) +2022-11-14 14:32:29,989 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0753) Prec@1 82.000 (87.508) Prec@5 99.000 (99.237) +2022-11-14 14:32:29,998 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0755) Prec@1 87.000 (87.500) Prec@5 99.000 (99.233) +2022-11-14 14:32:30,008 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0757) Prec@1 87.000 (87.492) Prec@5 99.000 (99.230) +2022-11-14 14:32:30,018 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0756) Prec@1 91.000 (87.548) Prec@5 100.000 (99.242) +2022-11-14 14:32:30,027 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0355 (0.0749) Prec@1 96.000 (87.683) Prec@5 100.000 (99.254) +2022-11-14 14:32:30,038 Test: [63/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0746) Prec@1 92.000 (87.750) Prec@5 100.000 (99.266) +2022-11-14 14:32:30,048 Test: [64/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0748) Prec@1 85.000 (87.708) Prec@5 100.000 (99.277) +2022-11-14 14:32:30,058 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0748) Prec@1 87.000 (87.697) Prec@5 100.000 (99.288) +2022-11-14 14:32:30,067 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0382 (0.0743) Prec@1 94.000 (87.791) Prec@5 100.000 (99.299) +2022-11-14 14:32:30,077 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0744) Prec@1 89.000 (87.809) Prec@5 99.000 (99.294) +2022-11-14 14:32:30,086 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0740) Prec@1 93.000 (87.884) Prec@5 100.000 (99.304) +2022-11-14 14:32:30,096 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0742) Prec@1 87.000 (87.871) Prec@5 99.000 (99.300) +2022-11-14 14:32:30,106 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0745) Prec@1 86.000 (87.845) Prec@5 98.000 (99.282) +2022-11-14 14:32:30,115 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0744) Prec@1 86.000 (87.819) Prec@5 100.000 (99.292) +2022-11-14 14:32:30,124 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0740) Prec@1 92.000 (87.877) Prec@5 100.000 (99.301) +2022-11-14 14:32:30,133 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0297 (0.0734) Prec@1 95.000 (87.973) Prec@5 100.000 (99.311) +2022-11-14 14:32:30,142 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0738) Prec@1 85.000 (87.933) Prec@5 98.000 (99.293) +2022-11-14 14:32:30,151 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0738) Prec@1 87.000 (87.921) Prec@5 99.000 (99.289) +2022-11-14 14:32:30,161 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0737) Prec@1 88.000 (87.922) Prec@5 98.000 (99.273) +2022-11-14 14:32:30,170 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0741) Prec@1 81.000 (87.833) Prec@5 99.000 (99.269) +2022-11-14 14:32:30,179 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0742) Prec@1 86.000 (87.810) Prec@5 99.000 (99.266) +2022-11-14 14:32:30,188 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 88.000 (87.812) Prec@5 100.000 (99.275) +2022-11-14 14:32:30,197 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0740) Prec@1 89.000 (87.827) Prec@5 99.000 (99.272) +2022-11-14 14:32:30,206 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0743) Prec@1 81.000 (87.744) Prec@5 100.000 (99.280) +2022-11-14 14:32:30,216 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0744) Prec@1 86.000 (87.723) Prec@5 99.000 (99.277) +2022-11-14 14:32:30,225 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0745) Prec@1 84.000 (87.679) Prec@5 100.000 (99.286) +2022-11-14 14:32:30,234 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0748) Prec@1 81.000 (87.600) Prec@5 99.000 (99.282) +2022-11-14 14:32:30,243 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0751) Prec@1 84.000 (87.558) Prec@5 99.000 (99.279) +2022-11-14 14:32:30,252 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0751) Prec@1 85.000 (87.529) Prec@5 98.000 (99.264) +2022-11-14 14:32:30,261 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0750) Prec@1 89.000 (87.545) Prec@5 99.000 (99.261) +2022-11-14 14:32:30,270 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0750) Prec@1 90.000 (87.573) Prec@5 99.000 (99.258) +2022-11-14 14:32:30,280 Test: [89/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0749) Prec@1 88.000 (87.578) Prec@5 99.000 (99.256) +2022-11-14 14:32:30,290 Test: [90/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0473 (0.0746) Prec@1 92.000 (87.626) Prec@5 100.000 (99.264) +2022-11-14 14:32:30,299 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0745) Prec@1 89.000 (87.641) Prec@5 100.000 (99.272) +2022-11-14 14:32:30,309 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0745) Prec@1 87.000 (87.634) Prec@5 99.000 (99.269) +2022-11-14 14:32:30,318 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0746) Prec@1 86.000 (87.617) Prec@5 98.000 (99.255) +2022-11-14 14:32:30,327 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0749) Prec@1 81.000 (87.547) Prec@5 99.000 (99.253) +2022-11-14 14:32:30,336 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0747) Prec@1 92.000 (87.594) Prec@5 100.000 (99.260) +2022-11-14 14:32:30,345 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0744) Prec@1 93.000 (87.649) Prec@5 99.000 (99.258) +2022-11-14 14:32:30,353 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0745) Prec@1 88.000 (87.653) Prec@5 98.000 (99.245) +2022-11-14 14:32:30,362 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0748) Prec@1 81.000 (87.586) Prec@5 98.000 (99.232) +2022-11-14 14:32:30,370 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0746) Prec@1 91.000 (87.620) Prec@5 100.000 (99.240) +2022-11-14 14:32:30,433 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:32:30,744 Epoch: [214][0/500] Time 0.024 (0.024) Data 0.226 (0.226) Loss 0.0470 (0.0470) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:30,945 Epoch: [214][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0290 (0.0380) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:32:31,140 Epoch: [214][20/500] Time 0.017 (0.018) Data 0.002 (0.012) Loss 0.0290 (0.0350) Prec@1 96.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:32:31,396 Epoch: [214][30/500] Time 0.028 (0.019) Data 0.002 (0.009) Loss 0.0454 (0.0376) Prec@1 91.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:32:31,687 Epoch: [214][40/500] Time 0.029 (0.021) Data 0.002 (0.007) Loss 0.0310 (0.0363) Prec@1 94.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 14:32:31,981 Epoch: [214][50/500] Time 0.028 (0.022) Data 0.002 (0.006) Loss 0.0402 (0.0369) Prec@1 94.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 14:32:32,277 Epoch: [214][60/500] Time 0.027 (0.022) Data 0.002 (0.005) Loss 0.0338 (0.0365) Prec@1 95.000 (93.857) Prec@5 100.000 (100.000) +2022-11-14 14:32:32,578 Epoch: [214][70/500] Time 0.028 (0.023) Data 0.002 (0.005) Loss 0.0395 (0.0369) Prec@1 93.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 14:32:32,884 Epoch: [214][80/500] Time 0.028 (0.024) Data 0.002 (0.005) Loss 0.0488 (0.0382) Prec@1 92.000 (93.556) Prec@5 99.000 (99.889) +2022-11-14 14:32:33,179 Epoch: [214][90/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0287 (0.0372) Prec@1 96.000 (93.800) Prec@5 99.000 (99.800) +2022-11-14 14:32:33,481 Epoch: [214][100/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0708 (0.0403) Prec@1 89.000 (93.364) Prec@5 99.000 (99.727) +2022-11-14 14:32:33,778 Epoch: [214][110/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.0386 (0.0402) Prec@1 93.000 (93.333) Prec@5 100.000 (99.750) +2022-11-14 14:32:34,084 Epoch: [214][120/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0268 (0.0391) Prec@1 96.000 (93.538) Prec@5 100.000 (99.769) +2022-11-14 14:32:34,385 Epoch: [214][130/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0358 (0.0389) Prec@1 94.000 (93.571) Prec@5 99.000 (99.714) +2022-11-14 14:32:34,682 Epoch: [214][140/500] Time 0.029 (0.025) Data 0.001 (0.003) Loss 0.0299 (0.0383) Prec@1 95.000 (93.667) Prec@5 100.000 (99.733) +2022-11-14 14:32:34,983 Epoch: [214][150/500] Time 0.029 (0.025) Data 0.001 (0.003) Loss 0.0532 (0.0392) Prec@1 93.000 (93.625) Prec@5 100.000 (99.750) +2022-11-14 14:32:35,283 Epoch: [214][160/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0418 (0.0394) Prec@1 94.000 (93.647) Prec@5 100.000 (99.765) +2022-11-14 14:32:35,581 Epoch: [214][170/500] Time 0.026 (0.025) Data 0.002 (0.003) Loss 0.0448 (0.0397) Prec@1 94.000 (93.667) Prec@5 100.000 (99.778) +2022-11-14 14:32:35,879 Epoch: [214][180/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0417 (0.0398) Prec@1 94.000 (93.684) Prec@5 100.000 (99.789) +2022-11-14 14:32:36,179 Epoch: [214][190/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0387 (0.0397) Prec@1 94.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 14:32:36,483 Epoch: [214][200/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0534 (0.0404) Prec@1 91.000 (93.571) Prec@5 100.000 (99.810) +2022-11-14 14:32:36,817 Epoch: [214][210/500] Time 0.043 (0.025) Data 0.001 (0.003) Loss 0.0320 (0.0400) Prec@1 97.000 (93.727) Prec@5 100.000 (99.818) +2022-11-14 14:32:37,287 Epoch: [214][220/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.0148 (0.0389) Prec@1 98.000 (93.913) Prec@5 100.000 (99.826) +2022-11-14 14:32:37,748 Epoch: [214][230/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0487 (0.0393) Prec@1 89.000 (93.708) Prec@5 99.000 (99.792) +2022-11-14 14:32:38,212 Epoch: [214][240/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0275 (0.0388) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:32:38,679 Epoch: [214][250/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0701 (0.0400) Prec@1 91.000 (93.692) Prec@5 100.000 (99.808) +2022-11-14 14:32:39,140 Epoch: [214][260/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0284 (0.0396) Prec@1 95.000 (93.741) Prec@5 100.000 (99.815) +2022-11-14 14:32:39,613 Epoch: [214][270/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0444 (0.0398) Prec@1 93.000 (93.714) Prec@5 100.000 (99.821) +2022-11-14 14:32:40,074 Epoch: [214][280/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0352 (0.0396) Prec@1 95.000 (93.759) Prec@5 100.000 (99.828) +2022-11-14 14:32:40,538 Epoch: [214][290/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0430 (0.0397) Prec@1 91.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 14:32:41,000 Epoch: [214][300/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0431 (0.0398) Prec@1 92.000 (93.613) Prec@5 100.000 (99.839) +2022-11-14 14:32:41,467 Epoch: [214][310/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0394 (0.0398) Prec@1 92.000 (93.562) Prec@5 100.000 (99.844) +2022-11-14 14:32:41,931 Epoch: [214][320/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0356 (0.0397) Prec@1 95.000 (93.606) Prec@5 100.000 (99.848) +2022-11-14 14:32:42,402 Epoch: [214][330/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0269 (0.0393) Prec@1 98.000 (93.735) Prec@5 100.000 (99.853) +2022-11-14 14:32:42,864 Epoch: [214][340/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0343 (0.0392) Prec@1 95.000 (93.771) Prec@5 100.000 (99.857) +2022-11-14 14:32:43,332 Epoch: [214][350/500] Time 0.053 (0.032) Data 0.002 (0.002) Loss 0.0648 (0.0399) Prec@1 89.000 (93.639) Prec@5 99.000 (99.833) +2022-11-14 14:32:43,791 Epoch: [214][360/500] Time 0.041 (0.032) Data 0.002 (0.002) Loss 0.0438 (0.0400) Prec@1 90.000 (93.541) Prec@5 100.000 (99.838) +2022-11-14 14:32:44,251 Epoch: [214][370/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0286 (0.0397) Prec@1 95.000 (93.579) Prec@5 100.000 (99.842) +2022-11-14 14:32:44,714 Epoch: [214][380/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0279 (0.0394) Prec@1 95.000 (93.615) Prec@5 99.000 (99.821) +2022-11-14 14:32:45,175 Epoch: [214][390/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0422 (0.0395) Prec@1 92.000 (93.575) Prec@5 100.000 (99.825) +2022-11-14 14:32:45,646 Epoch: [214][400/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0688 (0.0402) Prec@1 88.000 (93.439) Prec@5 100.000 (99.829) +2022-11-14 14:32:46,110 Epoch: [214][410/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0379 (0.0401) Prec@1 93.000 (93.429) Prec@5 100.000 (99.833) +2022-11-14 14:32:46,621 Epoch: [214][420/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0206 (0.0397) Prec@1 96.000 (93.488) Prec@5 100.000 (99.837) +2022-11-14 14:32:47,169 Epoch: [214][430/500] Time 0.052 (0.034) Data 0.002 (0.002) Loss 0.0260 (0.0394) Prec@1 95.000 (93.523) Prec@5 100.000 (99.841) +2022-11-14 14:32:47,640 Epoch: [214][440/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0196 (0.0389) Prec@1 98.000 (93.622) Prec@5 100.000 (99.844) +2022-11-14 14:32:48,109 Epoch: [214][450/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0512 (0.0392) Prec@1 89.000 (93.522) Prec@5 100.000 (99.848) +2022-11-14 14:32:48,595 Epoch: [214][460/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0218 (0.0388) Prec@1 98.000 (93.617) Prec@5 100.000 (99.851) +2022-11-14 14:32:49,095 Epoch: [214][470/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0489 (0.0390) Prec@1 89.000 (93.521) Prec@5 100.000 (99.854) +2022-11-14 14:32:49,671 Epoch: [214][480/500] Time 0.065 (0.035) Data 0.002 (0.002) Loss 0.0585 (0.0394) Prec@1 91.000 (93.469) Prec@5 99.000 (99.837) +2022-11-14 14:32:50,183 Epoch: [214][490/500] Time 0.046 (0.035) Data 0.002 (0.002) Loss 0.0353 (0.0393) Prec@1 95.000 (93.500) Prec@5 100.000 (99.840) +2022-11-14 14:32:50,694 Epoch: [214][499/500] Time 0.076 (0.035) Data 0.002 (0.002) Loss 0.0530 (0.0396) Prec@1 91.000 (93.451) Prec@5 100.000 (99.843) +2022-11-14 14:32:50,991 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0593 (0.0593) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:51,003 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0801 (0.0697) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:51,014 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0765 (0.0720) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:51,028 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0744) Prec@1 87.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 14:32:51,036 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0776) Prec@1 85.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 14:32:51,045 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0335 (0.0702) Prec@1 94.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 14:32:51,053 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0705) Prec@1 89.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 14:32:51,064 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0718) Prec@1 85.000 (88.750) Prec@5 99.000 (99.625) +2022-11-14 14:32:51,072 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0717) Prec@1 89.000 (88.778) Prec@5 99.000 (99.556) +2022-11-14 14:32:51,080 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0713) Prec@1 90.000 (88.900) Prec@5 98.000 (99.400) +2022-11-14 14:32:51,088 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0512 (0.0695) Prec@1 90.000 (89.000) Prec@5 100.000 (99.455) +2022-11-14 14:32:51,096 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0703) Prec@1 87.000 (88.833) Prec@5 98.000 (99.333) +2022-11-14 14:32:51,105 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0682) Prec@1 94.000 (89.231) Prec@5 100.000 (99.385) +2022-11-14 14:32:51,116 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0688) Prec@1 88.000 (89.143) Prec@5 100.000 (99.429) +2022-11-14 14:32:51,126 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0692) Prec@1 86.000 (88.933) Prec@5 99.000 (99.400) +2022-11-14 14:32:51,135 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0690) Prec@1 91.000 (89.062) Prec@5 100.000 (99.438) +2022-11-14 14:32:51,143 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0689) Prec@1 90.000 (89.118) Prec@5 98.000 (99.353) +2022-11-14 14:32:51,153 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0708) Prec@1 84.000 (88.833) Prec@5 100.000 (99.389) +2022-11-14 14:32:51,163 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0711) Prec@1 86.000 (88.684) Prec@5 100.000 (99.421) +2022-11-14 14:32:51,172 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0720) Prec@1 86.000 (88.550) Prec@5 99.000 (99.400) +2022-11-14 14:32:51,181 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0728) Prec@1 86.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 14:32:51,190 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0735) Prec@1 84.000 (88.227) Prec@5 100.000 (99.455) +2022-11-14 14:32:51,200 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0752) Prec@1 85.000 (88.087) Prec@5 96.000 (99.304) +2022-11-14 14:32:51,209 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0746) Prec@1 88.000 (88.083) Prec@5 100.000 (99.333) +2022-11-14 14:32:51,218 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0745) Prec@1 88.000 (88.080) Prec@5 100.000 (99.360) +2022-11-14 14:32:51,228 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0754) Prec@1 83.000 (87.885) Prec@5 99.000 (99.346) +2022-11-14 14:32:51,237 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0748) Prec@1 92.000 (88.037) Prec@5 100.000 (99.370) +2022-11-14 14:32:51,246 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0747) Prec@1 88.000 (88.036) Prec@5 99.000 (99.357) +2022-11-14 14:32:51,255 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0749) Prec@1 87.000 (88.000) Prec@5 99.000 (99.345) +2022-11-14 14:32:51,266 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0750) Prec@1 87.000 (87.967) Prec@5 99.000 (99.333) +2022-11-14 14:32:51,277 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0750) Prec@1 87.000 (87.935) Prec@5 99.000 (99.323) +2022-11-14 14:32:51,287 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0754) Prec@1 87.000 (87.906) Prec@5 100.000 (99.344) +2022-11-14 14:32:51,298 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0756) Prec@1 87.000 (87.879) Prec@5 99.000 (99.333) +2022-11-14 14:32:51,309 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0757) Prec@1 90.000 (87.941) Prec@5 99.000 (99.324) +2022-11-14 14:32:51,320 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0752) Prec@1 89.000 (87.971) Prec@5 98.000 (99.286) +2022-11-14 14:32:51,330 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0752) Prec@1 88.000 (87.972) Prec@5 99.000 (99.278) +2022-11-14 14:32:51,339 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0751) Prec@1 89.000 (88.000) Prec@5 99.000 (99.270) +2022-11-14 14:32:51,349 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0755) Prec@1 85.000 (87.921) Prec@5 99.000 (99.263) +2022-11-14 14:32:51,358 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0750) Prec@1 93.000 (88.051) Prec@5 99.000 (99.256) +2022-11-14 14:32:51,366 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0747) Prec@1 90.000 (88.100) Prec@5 99.000 (99.250) +2022-11-14 14:32:51,374 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0755) Prec@1 84.000 (88.000) Prec@5 97.000 (99.195) +2022-11-14 14:32:51,382 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0755) Prec@1 88.000 (88.000) Prec@5 98.000 (99.167) +2022-11-14 14:32:51,390 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0750) Prec@1 89.000 (88.023) Prec@5 99.000 (99.163) +2022-11-14 14:32:51,398 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0747) Prec@1 91.000 (88.091) Prec@5 99.000 (99.159) +2022-11-14 14:32:51,407 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0741) Prec@1 94.000 (88.222) Prec@5 99.000 (99.156) +2022-11-14 14:32:51,418 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0744) Prec@1 85.000 (88.152) Prec@5 99.000 (99.152) +2022-11-14 14:32:51,427 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0746) Prec@1 85.000 (88.085) Prec@5 100.000 (99.170) +2022-11-14 14:32:51,436 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0748) Prec@1 87.000 (88.062) Prec@5 99.000 (99.167) +2022-11-14 14:32:51,446 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0743) Prec@1 93.000 (88.163) Prec@5 100.000 (99.184) +2022-11-14 14:32:51,458 Test: [49/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0745) Prec@1 85.000 (88.100) Prec@5 100.000 (99.200) +2022-11-14 14:32:51,470 Test: [50/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0744) Prec@1 90.000 (88.137) Prec@5 99.000 (99.196) +2022-11-14 14:32:51,479 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0748) Prec@1 83.000 (88.038) Prec@5 98.000 (99.173) +2022-11-14 14:32:51,489 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0751) Prec@1 84.000 (87.962) Prec@5 99.000 (99.170) +2022-11-14 14:32:51,501 Test: [53/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0751) Prec@1 86.000 (87.926) Prec@5 99.000 (99.167) +2022-11-14 14:32:51,512 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0755) Prec@1 83.000 (87.836) Prec@5 100.000 (99.182) +2022-11-14 14:32:51,522 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0756) Prec@1 89.000 (87.857) Prec@5 99.000 (99.179) +2022-11-14 14:32:51,532 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0756) Prec@1 85.000 (87.807) Prec@5 100.000 (99.193) +2022-11-14 14:32:51,542 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0755) Prec@1 87.000 (87.793) Prec@5 100.000 (99.207) +2022-11-14 14:32:51,552 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0755) Prec@1 87.000 (87.780) Prec@5 100.000 (99.220) +2022-11-14 14:32:51,562 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0756) Prec@1 88.000 (87.783) Prec@5 100.000 (99.233) +2022-11-14 14:32:51,571 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0756) Prec@1 87.000 (87.770) Prec@5 99.000 (99.230) +2022-11-14 14:32:51,580 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0755) Prec@1 88.000 (87.774) Prec@5 99.000 (99.226) +2022-11-14 14:32:51,590 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0754) Prec@1 87.000 (87.762) Prec@5 100.000 (99.238) +2022-11-14 14:32:51,600 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0750) Prec@1 91.000 (87.812) Prec@5 100.000 (99.250) +2022-11-14 14:32:51,610 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0752) Prec@1 86.000 (87.785) Prec@5 98.000 (99.231) +2022-11-14 14:32:51,620 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0755) Prec@1 86.000 (87.758) Prec@5 99.000 (99.227) +2022-11-14 14:32:51,629 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0752) Prec@1 89.000 (87.776) Prec@5 100.000 (99.239) +2022-11-14 14:32:51,639 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0751) Prec@1 88.000 (87.779) Prec@5 98.000 (99.221) +2022-11-14 14:32:51,649 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0750) Prec@1 89.000 (87.797) Prec@5 100.000 (99.232) +2022-11-14 14:32:51,659 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0753) Prec@1 82.000 (87.714) Prec@5 98.000 (99.214) +2022-11-14 14:32:51,670 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0755) Prec@1 86.000 (87.690) Prec@5 99.000 (99.211) +2022-11-14 14:32:51,679 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0754) Prec@1 91.000 (87.736) Prec@5 100.000 (99.222) +2022-11-14 14:32:51,688 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0750) Prec@1 91.000 (87.781) Prec@5 100.000 (99.233) +2022-11-14 14:32:51,700 Test: [73/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0399 (0.0745) Prec@1 94.000 (87.865) Prec@5 100.000 (99.243) +2022-11-14 14:32:51,710 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0747) Prec@1 84.000 (87.813) Prec@5 100.000 (99.253) +2022-11-14 14:32:51,719 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0744) Prec@1 92.000 (87.868) Prec@5 100.000 (99.263) +2022-11-14 14:32:51,727 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0742) Prec@1 89.000 (87.883) Prec@5 98.000 (99.247) +2022-11-14 14:32:51,739 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0744) Prec@1 82.000 (87.808) Prec@5 98.000 (99.231) +2022-11-14 14:32:51,750 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0745) Prec@1 87.000 (87.797) Prec@5 100.000 (99.241) +2022-11-14 14:32:51,760 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0746) Prec@1 86.000 (87.775) Prec@5 98.000 (99.225) +2022-11-14 14:32:51,773 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0749) Prec@1 84.000 (87.728) Prec@5 97.000 (99.198) +2022-11-14 14:32:51,786 Test: [81/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0749) Prec@1 85.000 (87.695) Prec@5 99.000 (99.195) +2022-11-14 14:32:51,798 Test: [82/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0750) Prec@1 87.000 (87.687) Prec@5 100.000 (99.205) +2022-11-14 14:32:51,811 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0749) Prec@1 87.000 (87.679) Prec@5 100.000 (99.214) +2022-11-14 14:32:51,824 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0750) Prec@1 86.000 (87.659) Prec@5 100.000 (99.224) +2022-11-14 14:32:51,839 Test: [85/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0751) Prec@1 89.000 (87.674) Prec@5 100.000 (99.233) +2022-11-14 14:32:51,851 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0748) Prec@1 91.000 (87.713) Prec@5 100.000 (99.241) +2022-11-14 14:32:51,863 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0748) Prec@1 89.000 (87.727) Prec@5 100.000 (99.250) +2022-11-14 14:32:51,875 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0747) Prec@1 90.000 (87.753) Prec@5 100.000 (99.258) +2022-11-14 14:32:51,888 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0746) Prec@1 90.000 (87.778) Prec@5 100.000 (99.267) +2022-11-14 14:32:51,899 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0744) Prec@1 91.000 (87.813) Prec@5 100.000 (99.275) +2022-11-14 14:32:51,911 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 88.000 (87.815) Prec@5 99.000 (99.272) +2022-11-14 14:32:51,920 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0744) Prec@1 87.000 (87.806) Prec@5 100.000 (99.280) +2022-11-14 14:32:51,929 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0742) Prec@1 90.000 (87.830) Prec@5 99.000 (99.277) +2022-11-14 14:32:51,939 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0743) Prec@1 85.000 (87.800) Prec@5 99.000 (99.274) +2022-11-14 14:32:51,948 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0742) Prec@1 91.000 (87.833) Prec@5 99.000 (99.271) +2022-11-14 14:32:51,956 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0739) Prec@1 94.000 (87.897) Prec@5 100.000 (99.278) +2022-11-14 14:32:51,966 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0741) Prec@1 84.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 14:32:51,975 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0742) Prec@1 87.000 (87.848) Prec@5 100.000 (99.293) +2022-11-14 14:32:51,984 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0741) Prec@1 90.000 (87.870) Prec@5 100.000 (99.300) +2022-11-14 14:32:52,041 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:32:52,361 Epoch: [215][0/500] Time 0.025 (0.025) Data 0.234 (0.234) Loss 0.0350 (0.0350) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:32:52,587 Epoch: [215][10/500] Time 0.018 (0.020) Data 0.002 (0.023) Loss 0.0472 (0.0411) Prec@1 93.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 14:32:52,788 Epoch: [215][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0472 (0.0431) Prec@1 92.000 (93.000) Prec@5 99.000 (99.333) +2022-11-14 14:32:53,043 Epoch: [215][30/500] Time 0.030 (0.020) Data 0.002 (0.009) Loss 0.0410 (0.0426) Prec@1 94.000 (93.250) Prec@5 100.000 (99.500) +2022-11-14 14:32:53,351 Epoch: [215][40/500] Time 0.028 (0.022) Data 0.002 (0.007) Loss 0.0408 (0.0423) Prec@1 93.000 (93.200) Prec@5 100.000 (99.600) +2022-11-14 14:32:53,666 Epoch: [215][50/500] Time 0.029 (0.023) Data 0.001 (0.006) Loss 0.0492 (0.0434) Prec@1 92.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:32:53,974 Epoch: [215][60/500] Time 0.029 (0.024) Data 0.002 (0.006) Loss 0.0267 (0.0410) Prec@1 96.000 (93.429) Prec@5 100.000 (99.714) +2022-11-14 14:32:54,294 Epoch: [215][70/500] Time 0.031 (0.024) Data 0.002 (0.005) Loss 0.0253 (0.0391) Prec@1 95.000 (93.625) Prec@5 100.000 (99.750) +2022-11-14 14:32:54,600 Epoch: [215][80/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0290 (0.0379) Prec@1 95.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 14:32:54,918 Epoch: [215][90/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0453 (0.0387) Prec@1 91.000 (93.500) Prec@5 99.000 (99.700) +2022-11-14 14:32:55,233 Epoch: [215][100/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0338 (0.0382) Prec@1 93.000 (93.455) Prec@5 99.000 (99.636) +2022-11-14 14:32:55,558 Epoch: [215][110/500] Time 0.029 (0.026) Data 0.001 (0.004) Loss 0.0477 (0.0390) Prec@1 93.000 (93.417) Prec@5 99.000 (99.583) +2022-11-14 14:32:55,876 Epoch: [215][120/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0521 (0.0400) Prec@1 93.000 (93.385) Prec@5 98.000 (99.462) +2022-11-14 14:32:56,206 Epoch: [215][130/500] Time 0.035 (0.026) Data 0.002 (0.004) Loss 0.0359 (0.0397) Prec@1 95.000 (93.500) Prec@5 100.000 (99.500) +2022-11-14 14:32:56,521 Epoch: [215][140/500] Time 0.030 (0.026) Data 0.001 (0.003) Loss 0.0502 (0.0404) Prec@1 93.000 (93.467) Prec@5 100.000 (99.533) +2022-11-14 14:32:56,851 Epoch: [215][150/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0475 (0.0409) Prec@1 91.000 (93.312) Prec@5 100.000 (99.562) +2022-11-14 14:32:57,162 Epoch: [215][160/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0392 (0.0408) Prec@1 94.000 (93.353) Prec@5 100.000 (99.588) +2022-11-14 14:32:57,483 Epoch: [215][170/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0358 (0.0405) Prec@1 93.000 (93.333) Prec@5 100.000 (99.611) +2022-11-14 14:32:57,811 Epoch: [215][180/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0343 (0.0402) Prec@1 96.000 (93.474) Prec@5 100.000 (99.632) +2022-11-14 14:32:58,127 Epoch: [215][190/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.0389 (0.0401) Prec@1 95.000 (93.550) Prec@5 100.000 (99.650) +2022-11-14 14:32:58,447 Epoch: [215][200/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.0270 (0.0395) Prec@1 95.000 (93.619) Prec@5 100.000 (99.667) +2022-11-14 14:32:58,766 Epoch: [215][210/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0208 (0.0386) Prec@1 98.000 (93.818) Prec@5 100.000 (99.682) +2022-11-14 14:32:59,082 Epoch: [215][220/500] Time 0.031 (0.027) Data 0.001 (0.003) Loss 0.0548 (0.0393) Prec@1 91.000 (93.696) Prec@5 99.000 (99.652) +2022-11-14 14:32:59,403 Epoch: [215][230/500] Time 0.031 (0.027) Data 0.001 (0.003) Loss 0.0364 (0.0392) Prec@1 94.000 (93.708) Prec@5 100.000 (99.667) +2022-11-14 14:32:59,727 Epoch: [215][240/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0456 (0.0395) Prec@1 93.000 (93.680) Prec@5 100.000 (99.680) +2022-11-14 14:33:00,055 Epoch: [215][250/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0394 (0.0395) Prec@1 94.000 (93.692) Prec@5 100.000 (99.692) +2022-11-14 14:33:00,383 Epoch: [215][260/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0392 (0.0395) Prec@1 94.000 (93.704) Prec@5 99.000 (99.667) +2022-11-14 14:33:00,700 Epoch: [215][270/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0454 (0.0397) Prec@1 92.000 (93.643) Prec@5 100.000 (99.679) +2022-11-14 14:33:01,026 Epoch: [215][280/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0546 (0.0402) Prec@1 89.000 (93.483) Prec@5 100.000 (99.690) +2022-11-14 14:33:01,359 Epoch: [215][290/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0554 (0.0407) Prec@1 89.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:33:01,680 Epoch: [215][300/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0292 (0.0403) Prec@1 95.000 (93.387) Prec@5 100.000 (99.677) +2022-11-14 14:33:02,003 Epoch: [215][310/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0594 (0.0409) Prec@1 91.000 (93.312) Prec@5 100.000 (99.688) +2022-11-14 14:33:02,320 Epoch: [215][320/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.0398 (0.0409) Prec@1 92.000 (93.273) Prec@5 100.000 (99.697) +2022-11-14 14:33:02,698 Epoch: [215][330/500] Time 0.041 (0.028) Data 0.002 (0.002) Loss 0.0269 (0.0405) Prec@1 95.000 (93.324) Prec@5 100.000 (99.706) +2022-11-14 14:33:03,168 Epoch: [215][340/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0726 (0.0414) Prec@1 89.000 (93.200) Prec@5 99.000 (99.686) +2022-11-14 14:33:03,674 Epoch: [215][350/500] Time 0.044 (0.029) Data 0.003 (0.002) Loss 0.0338 (0.0412) Prec@1 95.000 (93.250) Prec@5 99.000 (99.667) +2022-11-14 14:33:04,183 Epoch: [215][360/500] Time 0.046 (0.029) Data 0.002 (0.002) Loss 0.0440 (0.0413) Prec@1 92.000 (93.216) Prec@5 100.000 (99.676) +2022-11-14 14:33:04,680 Epoch: [215][370/500] Time 0.049 (0.029) Data 0.002 (0.002) Loss 0.0450 (0.0414) Prec@1 93.000 (93.211) Prec@5 100.000 (99.684) +2022-11-14 14:33:05,162 Epoch: [215][380/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.0403 (0.0413) Prec@1 94.000 (93.231) Prec@5 100.000 (99.692) +2022-11-14 14:33:05,645 Epoch: [215][390/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0438 (0.0414) Prec@1 94.000 (93.250) Prec@5 99.000 (99.675) +2022-11-14 14:33:06,117 Epoch: [215][400/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.0361 (0.0413) Prec@1 95.000 (93.293) Prec@5 100.000 (99.683) +2022-11-14 14:33:06,592 Epoch: [215][410/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0322 (0.0410) Prec@1 95.000 (93.333) Prec@5 100.000 (99.690) +2022-11-14 14:33:07,071 Epoch: [215][420/500] Time 0.060 (0.031) Data 0.002 (0.002) Loss 0.0436 (0.0411) Prec@1 94.000 (93.349) Prec@5 99.000 (99.674) +2022-11-14 14:33:07,554 Epoch: [215][430/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0310 (0.0409) Prec@1 95.000 (93.386) Prec@5 99.000 (99.659) +2022-11-14 14:33:08,025 Epoch: [215][440/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0321 (0.0407) Prec@1 95.000 (93.422) Prec@5 100.000 (99.667) +2022-11-14 14:33:08,506 Epoch: [215][450/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0343 (0.0405) Prec@1 94.000 (93.435) Prec@5 100.000 (99.674) +2022-11-14 14:33:08,969 Epoch: [215][460/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0600 (0.0410) Prec@1 89.000 (93.340) Prec@5 99.000 (99.660) +2022-11-14 14:33:09,444 Epoch: [215][470/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0290 (0.0407) Prec@1 96.000 (93.396) Prec@5 100.000 (99.667) +2022-11-14 14:33:09,919 Epoch: [215][480/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0425 (0.0407) Prec@1 93.000 (93.388) Prec@5 99.000 (99.653) +2022-11-14 14:33:10,399 Epoch: [215][490/500] Time 0.041 (0.033) Data 0.003 (0.002) Loss 0.0418 (0.0408) Prec@1 91.000 (93.340) Prec@5 100.000 (99.660) +2022-11-14 14:33:10,825 Epoch: [215][499/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0249 (0.0405) Prec@1 97.000 (93.412) Prec@5 100.000 (99.667) +2022-11-14 14:33:11,108 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0698 (0.0698) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:11,116 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0723) Prec@1 87.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:33:11,126 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0664) Prec@1 89.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:33:11,138 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0726) Prec@1 85.000 (87.250) Prec@5 98.000 (99.250) +2022-11-14 14:33:11,147 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0751) Prec@1 85.000 (86.800) Prec@5 100.000 (99.400) +2022-11-14 14:33:11,155 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0326 (0.0681) Prec@1 96.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 14:33:11,163 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0667) Prec@1 93.000 (89.000) Prec@5 100.000 (99.571) +2022-11-14 14:33:11,172 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0665) Prec@1 89.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 14:33:11,181 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0684) Prec@1 85.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 14:33:11,190 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0700) Prec@1 85.000 (88.200) Prec@5 99.000 (99.600) +2022-11-14 14:33:11,199 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0692) Prec@1 92.000 (88.545) Prec@5 99.000 (99.545) +2022-11-14 14:33:11,209 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0704) Prec@1 87.000 (88.417) Prec@5 100.000 (99.583) +2022-11-14 14:33:11,218 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0696) Prec@1 90.000 (88.538) Prec@5 100.000 (99.615) +2022-11-14 14:33:11,227 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0699) Prec@1 89.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 14:33:11,236 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0692) Prec@1 90.000 (88.667) Prec@5 100.000 (99.600) +2022-11-14 14:33:11,246 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0708) Prec@1 84.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 14:33:11,254 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0701) Prec@1 91.000 (88.529) Prec@5 99.000 (99.588) +2022-11-14 14:33:11,262 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1190 (0.0728) Prec@1 80.000 (88.056) Prec@5 100.000 (99.611) +2022-11-14 14:33:11,271 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0725) Prec@1 87.000 (88.000) Prec@5 98.000 (99.526) +2022-11-14 14:33:11,279 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0732) Prec@1 86.000 (87.900) Prec@5 96.000 (99.350) +2022-11-14 14:33:11,289 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0746) Prec@1 82.000 (87.619) Prec@5 98.000 (99.286) +2022-11-14 14:33:11,300 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0753) Prec@1 85.000 (87.500) Prec@5 98.000 (99.227) +2022-11-14 14:33:11,309 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0765) Prec@1 85.000 (87.391) Prec@5 97.000 (99.130) +2022-11-14 14:33:11,318 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0755) Prec@1 95.000 (87.708) Prec@5 99.000 (99.125) +2022-11-14 14:33:11,327 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0750) Prec@1 90.000 (87.800) Prec@5 100.000 (99.160) +2022-11-14 14:33:11,336 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0752) Prec@1 86.000 (87.731) Prec@5 98.000 (99.115) +2022-11-14 14:33:11,345 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0743) Prec@1 92.000 (87.889) Prec@5 100.000 (99.148) +2022-11-14 14:33:11,354 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0740) Prec@1 89.000 (87.929) Prec@5 99.000 (99.143) +2022-11-14 14:33:11,363 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0743) Prec@1 87.000 (87.897) Prec@5 99.000 (99.138) +2022-11-14 14:33:11,373 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0736) Prec@1 92.000 (88.033) Prec@5 99.000 (99.133) +2022-11-14 14:33:11,382 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0740) Prec@1 84.000 (87.903) Prec@5 100.000 (99.161) +2022-11-14 14:33:11,392 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0740) Prec@1 89.000 (87.938) Prec@5 100.000 (99.188) +2022-11-14 14:33:11,401 Test: 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0.0487 (0.0747) Prec@1 93.000 (87.846) Prec@5 99.000 (99.205) +2022-11-14 14:33:11,465 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0743) Prec@1 91.000 (87.925) Prec@5 99.000 (99.200) +2022-11-14 14:33:11,475 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0746) Prec@1 87.000 (87.902) Prec@5 98.000 (99.171) +2022-11-14 14:33:11,484 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0744) Prec@1 88.000 (87.905) Prec@5 99.000 (99.167) +2022-11-14 14:33:11,493 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0444 (0.0737) Prec@1 92.000 (88.000) Prec@5 98.000 (99.140) +2022-11-14 14:33:11,503 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0738) Prec@1 88.000 (88.000) Prec@5 97.000 (99.091) +2022-11-14 14:33:11,511 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0736) Prec@1 91.000 (88.067) Prec@5 100.000 (99.111) +2022-11-14 14:33:11,521 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0738) Prec@1 85.000 (88.000) Prec@5 100.000 (99.130) +2022-11-14 14:33:11,531 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0735) Prec@1 91.000 (88.064) Prec@5 100.000 (99.149) +2022-11-14 14:33:11,539 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0742) Prec@1 82.000 (87.938) Prec@5 97.000 (99.104) +2022-11-14 14:33:11,549 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0739) Prec@1 91.000 (88.000) Prec@5 100.000 (99.122) +2022-11-14 14:33:11,557 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0742) Prec@1 86.000 (87.960) Prec@5 100.000 (99.140) +2022-11-14 14:33:11,565 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0739) Prec@1 92.000 (88.039) Prec@5 100.000 (99.157) +2022-11-14 14:33:11,574 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0744) Prec@1 85.000 (87.981) Prec@5 99.000 (99.154) +2022-11-14 14:33:11,583 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0743) Prec@1 86.000 (87.943) Prec@5 100.000 (99.170) +2022-11-14 14:33:11,592 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0743) Prec@1 90.000 (87.981) Prec@5 99.000 (99.167) +2022-11-14 14:33:11,601 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0745) Prec@1 88.000 (87.982) Prec@5 100.000 (99.182) +2022-11-14 14:33:11,611 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0742) Prec@1 91.000 (88.036) Prec@5 99.000 (99.179) +2022-11-14 14:33:11,621 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0743) Prec@1 84.000 (87.965) Prec@5 100.000 (99.193) +2022-11-14 14:33:11,631 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0742) Prec@1 87.000 (87.948) Prec@5 99.000 (99.190) +2022-11-14 14:33:11,640 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0746) Prec@1 81.000 (87.831) Prec@5 99.000 (99.186) +2022-11-14 14:33:11,649 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0746) Prec@1 87.000 (87.817) Prec@5 100.000 (99.200) +2022-11-14 14:33:11,658 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0749) Prec@1 86.000 (87.787) Prec@5 98.000 (99.180) +2022-11-14 14:33:11,668 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0751) Prec@1 87.000 (87.774) Prec@5 99.000 (99.177) +2022-11-14 14:33:11,677 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0749) Prec@1 91.000 (87.825) Prec@5 100.000 (99.190) +2022-11-14 14:33:11,686 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0745) Prec@1 92.000 (87.891) Prec@5 100.000 (99.203) +2022-11-14 14:33:11,696 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0745) Prec@1 87.000 (87.877) Prec@5 99.000 (99.200) +2022-11-14 14:33:11,705 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0746) Prec@1 86.000 (87.848) Prec@5 98.000 (99.182) +2022-11-14 14:33:11,714 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0742) Prec@1 92.000 (87.910) Prec@5 100.000 (99.194) +2022-11-14 14:33:11,723 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0745) Prec@1 86.000 (87.882) Prec@5 98.000 (99.176) +2022-11-14 14:33:11,732 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0742) Prec@1 90.000 (87.913) Prec@5 99.000 (99.174) +2022-11-14 14:33:11,740 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0744) Prec@1 86.000 (87.886) Prec@5 98.000 (99.157) +2022-11-14 14:33:11,749 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0749) Prec@1 82.000 (87.803) Prec@5 100.000 (99.169) +2022-11-14 14:33:11,759 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0747) Prec@1 92.000 (87.861) Prec@5 98.000 (99.153) +2022-11-14 14:33:11,768 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0744) Prec@1 92.000 (87.918) Prec@5 99.000 (99.151) +2022-11-14 14:33:11,778 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0740) Prec@1 95.000 (88.014) Prec@5 99.000 (99.149) +2022-11-14 14:33:11,787 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0739) Prec@1 87.000 (88.000) Prec@5 100.000 (99.160) +2022-11-14 14:33:11,796 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0738) Prec@1 88.000 (88.000) Prec@5 100.000 (99.171) +2022-11-14 14:33:11,806 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0739) Prec@1 88.000 (88.000) Prec@5 100.000 (99.182) +2022-11-14 14:33:11,815 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0739) Prec@1 87.000 (87.987) Prec@5 97.000 (99.154) +2022-11-14 14:33:11,824 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0741) Prec@1 86.000 (87.962) Prec@5 100.000 (99.165) +2022-11-14 14:33:11,833 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0739) Prec@1 91.000 (88.000) Prec@5 99.000 (99.162) +2022-11-14 14:33:11,843 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0738) Prec@1 89.000 (88.012) Prec@5 97.000 (99.136) +2022-11-14 14:33:11,851 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0740) Prec@1 86.000 (87.988) Prec@5 100.000 (99.146) +2022-11-14 14:33:11,859 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0742) Prec@1 85.000 (87.952) Prec@5 100.000 (99.157) +2022-11-14 14:33:11,867 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0739) Prec@1 91.000 (87.988) Prec@5 99.000 (99.155) +2022-11-14 14:33:11,875 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0741) Prec@1 87.000 (87.976) Prec@5 100.000 (99.165) +2022-11-14 14:33:11,884 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0746) Prec@1 82.000 (87.907) Prec@5 99.000 (99.163) +2022-11-14 14:33:11,893 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0746) Prec@1 88.000 (87.908) Prec@5 100.000 (99.172) +2022-11-14 14:33:11,903 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0748) Prec@1 86.000 (87.886) Prec@5 99.000 (99.170) +2022-11-14 14:33:11,912 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0748) Prec@1 89.000 (87.899) Prec@5 99.000 (99.169) +2022-11-14 14:33:11,921 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0748) Prec@1 89.000 (87.911) Prec@5 100.000 (99.178) +2022-11-14 14:33:11,931 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0747) Prec@1 89.000 (87.923) Prec@5 100.000 (99.187) +2022-11-14 14:33:11,940 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0746) Prec@1 91.000 (87.957) Prec@5 99.000 (99.185) +2022-11-14 14:33:11,949 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0745) Prec@1 91.000 (87.989) Prec@5 99.000 (99.183) +2022-11-14 14:33:11,957 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0747) Prec@1 88.000 (87.989) Prec@5 98.000 (99.170) +2022-11-14 14:33:11,967 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0749) Prec@1 81.000 (87.916) Prec@5 100.000 (99.179) +2022-11-14 14:33:11,975 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0748) Prec@1 90.000 (87.938) Prec@5 100.000 (99.188) +2022-11-14 14:33:11,983 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0744) Prec@1 92.000 (87.979) Prec@5 99.000 (99.186) +2022-11-14 14:33:11,992 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0745) Prec@1 90.000 (88.000) Prec@5 98.000 (99.173) +2022-11-14 14:33:12,002 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0748) Prec@1 84.000 (87.960) Prec@5 99.000 (99.172) +2022-11-14 14:33:12,011 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0748) Prec@1 88.000 (87.960) Prec@5 100.000 (99.180) +2022-11-14 14:33:12,066 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:33:12,378 Epoch: [216][0/500] Time 0.023 (0.023) Data 0.230 (0.230) Loss 0.0386 (0.0386) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:12,575 Epoch: [216][10/500] Time 0.017 (0.018) Data 0.002 (0.022) Loss 0.0532 (0.0459) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:12,804 Epoch: [216][20/500] Time 0.023 (0.019) Data 0.002 (0.013) Loss 0.0454 (0.0458) Prec@1 92.000 (92.667) Prec@5 99.000 (99.667) +2022-11-14 14:33:13,095 Epoch: [216][30/500] Time 0.029 (0.021) Data 0.002 (0.009) Loss 0.0346 (0.0430) Prec@1 94.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:33:13,405 Epoch: [216][40/500] Time 0.026 (0.023) Data 0.002 (0.007) Loss 0.0283 (0.0400) Prec@1 97.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:33:13,713 Epoch: [216][50/500] Time 0.029 (0.023) Data 0.002 (0.006) Loss 0.0457 (0.0410) Prec@1 90.000 (93.167) Prec@5 99.000 (99.667) +2022-11-14 14:33:14,021 Epoch: [216][60/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.0338 (0.0399) Prec@1 96.000 (93.571) Prec@5 100.000 (99.714) +2022-11-14 14:33:14,333 Epoch: [216][70/500] Time 0.035 (0.025) Data 0.002 (0.005) Loss 0.0446 (0.0405) Prec@1 92.000 (93.375) Prec@5 100.000 (99.750) +2022-11-14 14:33:14,643 Epoch: [216][80/500] Time 0.028 (0.025) Data 0.002 (0.005) Loss 0.0535 (0.0420) Prec@1 92.000 (93.222) Prec@5 100.000 (99.778) +2022-11-14 14:33:14,954 Epoch: [216][90/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0301 (0.0408) Prec@1 96.000 (93.500) Prec@5 100.000 (99.800) +2022-11-14 14:33:15,265 Epoch: [216][100/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0353 (0.0403) Prec@1 94.000 (93.545) Prec@5 100.000 (99.818) +2022-11-14 14:33:15,572 Epoch: [216][110/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.0246 (0.0390) Prec@1 96.000 (93.750) Prec@5 100.000 (99.833) +2022-11-14 14:33:15,882 Epoch: [216][120/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0284 (0.0382) Prec@1 96.000 (93.923) Prec@5 100.000 (99.846) +2022-11-14 14:33:16,200 Epoch: [216][130/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0200 (0.0369) Prec@1 98.000 (94.214) Prec@5 100.000 (99.857) +2022-11-14 14:33:16,510 Epoch: [216][140/500] Time 0.029 (0.026) Data 0.001 (0.003) Loss 0.0568 (0.0382) Prec@1 92.000 (94.067) Prec@5 97.000 (99.667) +2022-11-14 14:33:16,906 Epoch: [216][150/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0336 (0.0379) Prec@1 94.000 (94.062) Prec@5 100.000 (99.688) +2022-11-14 14:33:17,381 Epoch: [216][160/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0228 (0.0370) Prec@1 96.000 (94.176) Prec@5 99.000 (99.647) +2022-11-14 14:33:17,849 Epoch: [216][170/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0458 (0.0375) Prec@1 89.000 (93.889) Prec@5 100.000 (99.667) +2022-11-14 14:33:18,334 Epoch: [216][180/500] Time 0.052 (0.029) Data 0.002 (0.003) Loss 0.0374 (0.0375) Prec@1 94.000 (93.895) Prec@5 100.000 (99.684) +2022-11-14 14:33:18,809 Epoch: [216][190/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0560 (0.0384) Prec@1 91.000 (93.750) Prec@5 100.000 (99.700) +2022-11-14 14:33:19,300 Epoch: [216][200/500] Time 0.050 (0.031) Data 0.002 (0.003) Loss 0.0332 (0.0382) Prec@1 96.000 (93.857) Prec@5 100.000 (99.714) +2022-11-14 14:33:19,763 Epoch: [216][210/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0361 (0.0381) Prec@1 95.000 (93.909) Prec@5 100.000 (99.727) +2022-11-14 14:33:20,233 Epoch: [216][220/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0353 (0.0380) Prec@1 95.000 (93.957) Prec@5 100.000 (99.739) +2022-11-14 14:33:20,715 Epoch: [216][230/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0321 (0.0377) Prec@1 95.000 (94.000) Prec@5 99.000 (99.708) +2022-11-14 14:33:21,187 Epoch: [216][240/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0382 (0.0377) Prec@1 93.000 (93.960) Prec@5 100.000 (99.720) +2022-11-14 14:33:21,670 Epoch: [216][250/500] Time 0.054 (0.033) Data 0.002 (0.003) Loss 0.0294 (0.0374) Prec@1 95.000 (94.000) Prec@5 100.000 (99.731) +2022-11-14 14:33:22,132 Epoch: [216][260/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0368 (0.0374) Prec@1 93.000 (93.963) Prec@5 100.000 (99.741) +2022-11-14 14:33:22,615 Epoch: [216][270/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0600 (0.0382) Prec@1 91.000 (93.857) Prec@5 100.000 (99.750) +2022-11-14 14:33:23,093 Epoch: [216][280/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0450 (0.0384) Prec@1 92.000 (93.793) Prec@5 100.000 (99.759) +2022-11-14 14:33:23,573 Epoch: [216][290/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0336 (0.0383) Prec@1 95.000 (93.833) Prec@5 100.000 (99.767) +2022-11-14 14:33:24,045 Epoch: [216][300/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0227 (0.0378) Prec@1 94.000 (93.839) Prec@5 100.000 (99.774) +2022-11-14 14:33:24,517 Epoch: [216][310/500] Time 0.043 (0.035) Data 0.003 (0.003) Loss 0.0439 (0.0380) Prec@1 93.000 (93.812) Prec@5 100.000 (99.781) +2022-11-14 14:33:24,991 Epoch: [216][320/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0451 (0.0382) Prec@1 92.000 (93.758) Prec@5 100.000 (99.788) +2022-11-14 14:33:25,473 Epoch: [216][330/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0391 (0.0382) Prec@1 95.000 (93.794) Prec@5 99.000 (99.765) +2022-11-14 14:33:25,944 Epoch: [216][340/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0313 (0.0380) Prec@1 94.000 (93.800) Prec@5 100.000 (99.771) +2022-11-14 14:33:26,424 Epoch: [216][350/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0519 (0.0384) Prec@1 92.000 (93.750) Prec@5 99.000 (99.750) +2022-11-14 14:33:26,885 Epoch: [216][360/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0294 (0.0382) Prec@1 96.000 (93.811) Prec@5 100.000 (99.757) +2022-11-14 14:33:27,502 Epoch: [216][370/500] Time 0.056 (0.036) Data 0.001 (0.002) Loss 0.0450 (0.0383) Prec@1 91.000 (93.737) Prec@5 100.000 (99.763) +2022-11-14 14:33:27,841 Epoch: [216][380/500] Time 0.027 (0.036) Data 0.002 (0.002) Loss 0.0425 (0.0384) Prec@1 93.000 (93.718) Prec@5 100.000 (99.769) +2022-11-14 14:33:28,165 Epoch: [216][390/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0467 (0.0387) Prec@1 90.000 (93.625) Prec@5 100.000 (99.775) +2022-11-14 14:33:28,492 Epoch: [216][400/500] Time 0.030 (0.036) Data 0.001 (0.002) Loss 0.0396 (0.0387) Prec@1 92.000 (93.585) Prec@5 99.000 (99.756) +2022-11-14 14:33:28,823 Epoch: [216][410/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0392 (0.0387) Prec@1 94.000 (93.595) Prec@5 100.000 (99.762) +2022-11-14 14:33:29,142 Epoch: [216][420/500] Time 0.031 (0.035) Data 0.001 (0.002) Loss 0.0224 (0.0383) Prec@1 96.000 (93.651) Prec@5 100.000 (99.767) +2022-11-14 14:33:29,470 Epoch: [216][430/500] Time 0.030 (0.035) Data 0.002 (0.002) Loss 0.0271 (0.0381) Prec@1 96.000 (93.705) Prec@5 100.000 (99.773) +2022-11-14 14:33:29,794 Epoch: [216][440/500] Time 0.032 (0.035) Data 0.002 (0.002) Loss 0.0281 (0.0378) Prec@1 96.000 (93.756) Prec@5 99.000 (99.756) +2022-11-14 14:33:30,118 Epoch: [216][450/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0579 (0.0383) Prec@1 89.000 (93.652) Prec@5 100.000 (99.761) +2022-11-14 14:33:30,448 Epoch: [216][460/500] Time 0.029 (0.035) Data 0.003 (0.002) Loss 0.0320 (0.0381) Prec@1 97.000 (93.723) Prec@5 100.000 (99.766) +2022-11-14 14:33:30,783 Epoch: [216][470/500] Time 0.031 (0.035) Data 0.001 (0.002) Loss 0.0346 (0.0381) Prec@1 93.000 (93.708) Prec@5 100.000 (99.771) +2022-11-14 14:33:31,108 Epoch: [216][480/500] Time 0.031 (0.035) Data 0.002 (0.002) Loss 0.0409 (0.0381) Prec@1 94.000 (93.714) Prec@5 100.000 (99.776) +2022-11-14 14:33:31,444 Epoch: [216][490/500] Time 0.030 (0.034) Data 0.002 (0.002) Loss 0.0613 (0.0386) Prec@1 91.000 (93.660) Prec@5 100.000 (99.780) +2022-11-14 14:33:31,740 Epoch: [216][499/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0334 (0.0385) Prec@1 94.000 (93.667) Prec@5 100.000 (99.784) +2022-11-14 14:33:32,029 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0451 (0.0451) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:32,038 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0597) Prec@1 87.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:32,047 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0603) Prec@1 91.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 14:33:32,058 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0657) Prec@1 88.000 (89.750) Prec@5 99.000 (99.750) +2022-11-14 14:33:32,065 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0698) Prec@1 87.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 14:33:32,073 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0376 (0.0644) Prec@1 94.000 (90.000) Prec@5 100.000 (99.833) +2022-11-14 14:33:32,081 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0650) Prec@1 88.000 (89.714) Prec@5 100.000 (99.857) +2022-11-14 14:33:32,092 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0686) Prec@1 85.000 (89.125) Prec@5 100.000 (99.875) +2022-11-14 14:33:32,099 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0708) Prec@1 86.000 (88.778) Prec@5 99.000 (99.778) +2022-11-14 14:33:32,108 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0713) Prec@1 87.000 (88.600) Prec@5 99.000 (99.700) +2022-11-14 14:33:32,118 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0698) Prec@1 90.000 (88.727) Prec@5 100.000 (99.727) +2022-11-14 14:33:32,127 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0715) Prec@1 85.000 (88.417) Prec@5 100.000 (99.750) +2022-11-14 14:33:32,136 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0700) Prec@1 91.000 (88.615) Prec@5 100.000 (99.769) +2022-11-14 14:33:32,145 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0710) Prec@1 86.000 (88.429) Prec@5 98.000 (99.643) +2022-11-14 14:33:32,155 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0714) Prec@1 87.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:33:32,163 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0714) Prec@1 88.000 (88.312) Prec@5 100.000 (99.688) +2022-11-14 14:33:32,172 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0712) Prec@1 90.000 (88.412) Prec@5 98.000 (99.588) +2022-11-14 14:33:32,182 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0733) Prec@1 86.000 (88.278) Prec@5 100.000 (99.611) +2022-11-14 14:33:32,191 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0738) Prec@1 86.000 (88.158) Prec@5 98.000 (99.526) +2022-11-14 14:33:32,200 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0744) Prec@1 85.000 (88.000) Prec@5 98.000 (99.450) +2022-11-14 14:33:32,209 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0755) Prec@1 85.000 (87.857) Prec@5 100.000 (99.476) +2022-11-14 14:33:32,218 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0753) Prec@1 90.000 (87.955) Prec@5 98.000 (99.409) +2022-11-14 14:33:32,227 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0766) Prec@1 85.000 (87.826) Prec@5 99.000 (99.391) +2022-11-14 14:33:32,237 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0763) Prec@1 88.000 (87.833) Prec@5 100.000 (99.417) +2022-11-14 14:33:32,245 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0770) Prec@1 86.000 (87.760) Prec@5 100.000 (99.440) +2022-11-14 14:33:32,254 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0771) Prec@1 87.000 (87.731) Prec@5 98.000 (99.385) +2022-11-14 14:33:32,262 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0766) Prec@1 88.000 (87.741) Prec@5 100.000 (99.407) +2022-11-14 14:33:32,271 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0767) Prec@1 87.000 (87.714) Prec@5 100.000 (99.429) +2022-11-14 14:33:32,281 Test: [28/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0769) Prec@1 85.000 (87.621) Prec@5 98.000 (99.379) +2022-11-14 14:33:32,290 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0774) Prec@1 85.000 (87.533) Prec@5 99.000 (99.367) +2022-11-14 14:33:32,300 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0777) Prec@1 84.000 (87.419) Prec@5 98.000 (99.323) +2022-11-14 14:33:32,308 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0773) Prec@1 88.000 (87.438) Prec@5 100.000 (99.344) +2022-11-14 14:33:32,317 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0771) Prec@1 89.000 (87.485) Prec@5 97.000 (99.273) +2022-11-14 14:33:32,326 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0778) Prec@1 82.000 (87.324) Prec@5 100.000 (99.294) +2022-11-14 14:33:32,335 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0778) Prec@1 88.000 (87.343) Prec@5 99.000 (99.286) +2022-11-14 14:33:32,344 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0775) Prec@1 89.000 (87.389) Prec@5 100.000 (99.306) +2022-11-14 14:33:32,354 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0778) Prec@1 85.000 (87.324) Prec@5 100.000 (99.324) +2022-11-14 14:33:32,363 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0782) Prec@1 86.000 (87.289) Prec@5 100.000 (99.342) +2022-11-14 14:33:32,372 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0774) Prec@1 93.000 (87.436) Prec@5 99.000 (99.333) +2022-11-14 14:33:32,381 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0771) Prec@1 89.000 (87.475) Prec@5 99.000 (99.325) +2022-11-14 14:33:32,390 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0778) Prec@1 83.000 (87.366) Prec@5 97.000 (99.268) +2022-11-14 14:33:32,400 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0777) Prec@1 89.000 (87.405) Prec@5 98.000 (99.238) +2022-11-14 14:33:32,410 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0769) Prec@1 91.000 (87.488) Prec@5 100.000 (99.256) +2022-11-14 14:33:32,419 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0768) Prec@1 89.000 (87.523) Prec@5 97.000 (99.205) +2022-11-14 14:33:32,428 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0766) Prec@1 90.000 (87.578) Prec@5 100.000 (99.222) +2022-11-14 14:33:32,437 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0765) Prec@1 89.000 (87.609) Prec@5 99.000 (99.217) +2022-11-14 14:33:32,447 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0768) Prec@1 84.000 (87.532) Prec@5 100.000 (99.234) +2022-11-14 14:33:32,455 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0772) Prec@1 83.000 (87.438) Prec@5 99.000 (99.229) +2022-11-14 14:33:32,465 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0769) Prec@1 91.000 (87.510) Prec@5 100.000 (99.245) +2022-11-14 14:33:32,474 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0771) Prec@1 85.000 (87.460) Prec@5 98.000 (99.220) +2022-11-14 14:33:32,483 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0768) Prec@1 91.000 (87.529) Prec@5 100.000 (99.235) +2022-11-14 14:33:32,493 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0770) Prec@1 87.000 (87.519) Prec@5 100.000 (99.250) +2022-11-14 14:33:32,502 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0767) Prec@1 91.000 (87.585) Prec@5 98.000 (99.226) +2022-11-14 14:33:32,511 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0765) Prec@1 89.000 (87.611) Prec@5 99.000 (99.222) +2022-11-14 14:33:32,521 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.0771) Prec@1 82.000 (87.509) Prec@5 100.000 (99.236) +2022-11-14 14:33:32,530 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0769) Prec@1 87.000 (87.500) Prec@5 100.000 (99.250) +2022-11-14 14:33:32,539 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0771) Prec@1 88.000 (87.509) Prec@5 100.000 (99.263) +2022-11-14 14:33:32,546 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0473 (0.0766) Prec@1 92.000 (87.586) Prec@5 100.000 (99.276) +2022-11-14 14:33:32,554 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0766) Prec@1 87.000 (87.576) Prec@5 100.000 (99.288) +2022-11-14 14:33:32,562 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0769) Prec@1 83.000 (87.500) Prec@5 98.000 (99.267) +2022-11-14 14:33:32,571 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0771) Prec@1 87.000 (87.492) Prec@5 100.000 (99.279) +2022-11-14 14:33:32,579 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0769) Prec@1 87.000 (87.484) Prec@5 98.000 (99.258) +2022-11-14 14:33:32,588 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0768) Prec@1 87.000 (87.476) Prec@5 99.000 (99.254) +2022-11-14 14:33:32,598 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0764) Prec@1 91.000 (87.531) Prec@5 99.000 (99.250) +2022-11-14 14:33:32,606 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0768) Prec@1 81.000 (87.431) Prec@5 99.000 (99.246) +2022-11-14 14:33:32,615 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0769) Prec@1 87.000 (87.424) Prec@5 100.000 (99.258) +2022-11-14 14:33:32,625 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0401 (0.0764) Prec@1 95.000 (87.537) Prec@5 100.000 (99.269) +2022-11-14 14:33:32,634 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0764) Prec@1 89.000 (87.559) Prec@5 99.000 (99.265) +2022-11-14 14:33:32,643 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0762) Prec@1 90.000 (87.594) Prec@5 99.000 (99.261) +2022-11-14 14:33:32,652 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0763) Prec@1 87.000 (87.586) Prec@5 100.000 (99.271) +2022-11-14 14:33:32,661 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0765) Prec@1 83.000 (87.521) Prec@5 99.000 (99.268) +2022-11-14 14:33:32,670 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0765) Prec@1 86.000 (87.500) Prec@5 99.000 (99.264) +2022-11-14 14:33:32,679 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0764) Prec@1 89.000 (87.521) Prec@5 100.000 (99.274) +2022-11-14 14:33:32,688 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0760) Prec@1 92.000 (87.581) Prec@5 100.000 (99.284) +2022-11-14 14:33:32,697 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0760) Prec@1 85.000 (87.547) Prec@5 99.000 (99.280) +2022-11-14 14:33:32,706 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0757) Prec@1 92.000 (87.605) Prec@5 99.000 (99.276) +2022-11-14 14:33:32,715 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0756) Prec@1 89.000 (87.623) Prec@5 99.000 (99.273) +2022-11-14 14:33:32,725 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0759) Prec@1 84.000 (87.577) Prec@5 98.000 (99.256) +2022-11-14 14:33:32,734 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0756) Prec@1 90.000 (87.608) Prec@5 100.000 (99.266) +2022-11-14 14:33:32,743 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0757) Prec@1 87.000 (87.600) Prec@5 98.000 (99.250) +2022-11-14 14:33:32,752 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0757) Prec@1 90.000 (87.630) Prec@5 99.000 (99.247) +2022-11-14 14:33:32,761 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0757) Prec@1 86.000 (87.610) Prec@5 99.000 (99.244) +2022-11-14 14:33:32,772 Test: [82/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0755) Prec@1 91.000 (87.651) Prec@5 99.000 (99.241) +2022-11-14 14:33:32,781 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0754) Prec@1 90.000 (87.679) Prec@5 99.000 (99.238) +2022-11-14 14:33:32,790 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0756) Prec@1 85.000 (87.647) Prec@5 98.000 (99.224) +2022-11-14 14:33:32,800 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0759) Prec@1 82.000 (87.581) Prec@5 99.000 (99.221) +2022-11-14 14:33:32,809 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0759) Prec@1 87.000 (87.575) Prec@5 99.000 (99.218) +2022-11-14 14:33:32,818 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0757) Prec@1 90.000 (87.602) Prec@5 99.000 (99.216) +2022-11-14 14:33:32,827 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0757) Prec@1 87.000 (87.596) Prec@5 99.000 (99.213) +2022-11-14 14:33:32,835 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0759) Prec@1 87.000 (87.589) Prec@5 99.000 (99.211) +2022-11-14 14:33:32,843 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0758) Prec@1 89.000 (87.604) Prec@5 100.000 (99.220) +2022-11-14 14:33:32,851 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0756) Prec@1 94.000 (87.674) Prec@5 99.000 (99.217) +2022-11-14 14:33:32,859 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0756) Prec@1 87.000 (87.667) Prec@5 100.000 (99.226) +2022-11-14 14:33:32,868 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0756) Prec@1 89.000 (87.681) Prec@5 98.000 (99.213) +2022-11-14 14:33:32,877 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0756) Prec@1 86.000 (87.663) Prec@5 100.000 (99.221) +2022-11-14 14:33:32,886 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0755) Prec@1 92.000 (87.708) Prec@5 100.000 (99.229) +2022-11-14 14:33:32,894 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0752) Prec@1 93.000 (87.763) Prec@5 98.000 (99.216) +2022-11-14 14:33:32,904 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0753) Prec@1 85.000 (87.735) Prec@5 100.000 (99.224) +2022-11-14 14:33:32,912 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0755) Prec@1 88.000 (87.737) Prec@5 100.000 (99.232) +2022-11-14 14:33:32,921 Test: [99/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0754) Prec@1 90.000 (87.760) Prec@5 100.000 (99.240) +2022-11-14 14:33:32,976 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:33:33,304 Epoch: [217][0/500] Time 0.034 (0.034) Data 0.237 (0.237) Loss 0.0476 (0.0476) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:33,526 Epoch: [217][10/500] Time 0.021 (0.021) Data 0.002 (0.023) Loss 0.0306 (0.0391) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:33:33,773 Epoch: [217][20/500] Time 0.031 (0.021) Data 0.002 (0.013) Loss 0.0413 (0.0398) Prec@1 95.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 14:33:34,104 Epoch: [217][30/500] Time 0.032 (0.024) Data 0.002 (0.009) Loss 0.0355 (0.0388) Prec@1 93.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:33:34,442 Epoch: [217][40/500] Time 0.034 (0.026) Data 0.002 (0.007) Loss 0.0664 (0.0443) Prec@1 90.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:33:34,774 Epoch: [217][50/500] Time 0.031 (0.026) Data 0.001 (0.006) Loss 0.0348 (0.0427) Prec@1 94.000 (93.167) Prec@5 100.000 (99.833) +2022-11-14 14:33:35,106 Epoch: [217][60/500] Time 0.035 (0.027) Data 0.002 (0.006) Loss 0.0322 (0.0412) Prec@1 94.000 (93.286) Prec@5 100.000 (99.857) +2022-11-14 14:33:35,448 Epoch: [217][70/500] Time 0.038 (0.027) Data 0.002 (0.005) Loss 0.0368 (0.0407) Prec@1 93.000 (93.250) Prec@5 100.000 (99.875) +2022-11-14 14:33:35,774 Epoch: [217][80/500] Time 0.031 (0.028) Data 0.002 (0.005) Loss 0.0232 (0.0387) Prec@1 96.000 (93.556) Prec@5 100.000 (99.889) +2022-11-14 14:33:36,115 Epoch: [217][90/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0409 (0.0389) Prec@1 95.000 (93.700) Prec@5 100.000 (99.900) +2022-11-14 14:33:36,459 Epoch: [217][100/500] Time 0.034 (0.028) Data 0.002 (0.004) Loss 0.0276 (0.0379) Prec@1 95.000 (93.818) Prec@5 100.000 (99.909) +2022-11-14 14:33:36,795 Epoch: [217][110/500] Time 0.031 (0.028) Data 0.003 (0.004) Loss 0.0273 (0.0370) Prec@1 95.000 (93.917) Prec@5 100.000 (99.917) +2022-11-14 14:33:37,132 Epoch: [217][120/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0567 (0.0385) Prec@1 90.000 (93.615) Prec@5 100.000 (99.923) +2022-11-14 14:33:37,472 Epoch: [217][130/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0401 (0.0386) Prec@1 95.000 (93.714) Prec@5 100.000 (99.929) +2022-11-14 14:33:37,816 Epoch: [217][140/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0510 (0.0395) Prec@1 91.000 (93.533) Prec@5 100.000 (99.933) +2022-11-14 14:33:38,146 Epoch: [217][150/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0407 (0.0395) Prec@1 91.000 (93.375) Prec@5 100.000 (99.938) +2022-11-14 14:33:38,486 Epoch: [217][160/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0463 (0.0399) Prec@1 91.000 (93.235) Prec@5 100.000 (99.941) +2022-11-14 14:33:38,822 Epoch: [217][170/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0521 (0.0406) Prec@1 93.000 (93.222) Prec@5 100.000 (99.944) +2022-11-14 14:33:39,157 Epoch: [217][180/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0236 (0.0397) Prec@1 96.000 (93.368) Prec@5 99.000 (99.895) +2022-11-14 14:33:39,490 Epoch: [217][190/500] Time 0.032 (0.029) Data 0.001 (0.003) Loss 0.0381 (0.0396) Prec@1 94.000 (93.400) Prec@5 100.000 (99.900) +2022-11-14 14:33:39,830 Epoch: [217][200/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0148 (0.0385) Prec@1 98.000 (93.619) Prec@5 100.000 (99.905) +2022-11-14 14:33:40,168 Epoch: [217][210/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0441 (0.0387) Prec@1 93.000 (93.591) Prec@5 100.000 (99.909) +2022-11-14 14:33:40,509 Epoch: [217][220/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0365 (0.0386) Prec@1 95.000 (93.652) Prec@5 100.000 (99.913) +2022-11-14 14:33:40,856 Epoch: [217][230/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.0136 (0.0376) Prec@1 96.000 (93.750) Prec@5 100.000 (99.917) +2022-11-14 14:33:41,195 Epoch: [217][240/500] Time 0.033 (0.029) Data 0.001 (0.003) Loss 0.0289 (0.0372) Prec@1 95.000 (93.800) Prec@5 100.000 (99.920) +2022-11-14 14:33:41,541 Epoch: [217][250/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0429 (0.0374) Prec@1 93.000 (93.769) Prec@5 100.000 (99.923) +2022-11-14 14:33:41,879 Epoch: [217][260/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0356 (0.0374) Prec@1 93.000 (93.741) Prec@5 100.000 (99.926) +2022-11-14 14:33:42,221 Epoch: [217][270/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0563 (0.0381) Prec@1 92.000 (93.679) Prec@5 99.000 (99.893) +2022-11-14 14:33:42,561 Epoch: [217][280/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0487 (0.0384) Prec@1 90.000 (93.552) Prec@5 100.000 (99.897) +2022-11-14 14:33:42,901 Epoch: [217][290/500] Time 0.032 (0.029) Data 0.002 (0.003) Loss 0.0269 (0.0380) Prec@1 97.000 (93.667) Prec@5 100.000 (99.900) +2022-11-14 14:33:43,245 Epoch: [217][300/500] Time 0.040 (0.029) Data 0.002 (0.003) Loss 0.0436 (0.0382) Prec@1 93.000 (93.645) Prec@5 100.000 (99.903) +2022-11-14 14:33:43,580 Epoch: [217][310/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0749 (0.0394) Prec@1 88.000 (93.469) Prec@5 100.000 (99.906) +2022-11-14 14:33:43,922 Epoch: [217][320/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0298 (0.0391) Prec@1 94.000 (93.485) Prec@5 100.000 (99.909) +2022-11-14 14:33:44,263 Epoch: [217][330/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0342 (0.0389) Prec@1 93.000 (93.471) Prec@5 100.000 (99.912) +2022-11-14 14:33:44,614 Epoch: [217][340/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0400 (0.0390) Prec@1 91.000 (93.400) Prec@5 100.000 (99.914) +2022-11-14 14:33:44,952 Epoch: [217][350/500] Time 0.031 (0.030) Data 0.002 (0.002) Loss 0.0291 (0.0387) Prec@1 95.000 (93.444) Prec@5 100.000 (99.917) +2022-11-14 14:33:45,302 Epoch: [217][360/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0217 (0.0382) Prec@1 95.000 (93.486) Prec@5 100.000 (99.919) +2022-11-14 14:33:45,643 Epoch: [217][370/500] Time 0.039 (0.030) Data 0.003 (0.002) Loss 0.0104 (0.0375) Prec@1 99.000 (93.632) Prec@5 100.000 (99.921) +2022-11-14 14:33:45,980 Epoch: [217][380/500] Time 0.031 (0.030) Data 0.002 (0.002) Loss 0.0309 (0.0373) Prec@1 95.000 (93.667) Prec@5 100.000 (99.923) +2022-11-14 14:33:46,332 Epoch: [217][390/500] Time 0.040 (0.030) Data 0.002 (0.002) Loss 0.0637 (0.0380) Prec@1 89.000 (93.550) Prec@5 99.000 (99.900) +2022-11-14 14:33:46,668 Epoch: [217][400/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0437 (0.0381) Prec@1 92.000 (93.512) Prec@5 99.000 (99.878) +2022-11-14 14:33:47,013 Epoch: [217][410/500] Time 0.031 (0.030) Data 0.002 (0.002) Loss 0.0599 (0.0386) Prec@1 89.000 (93.405) Prec@5 100.000 (99.881) +2022-11-14 14:33:47,359 Epoch: [217][420/500] Time 0.029 (0.030) Data 0.002 (0.002) Loss 0.0173 (0.0381) Prec@1 97.000 (93.488) Prec@5 99.000 (99.860) +2022-11-14 14:33:47,703 Epoch: [217][430/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0209 (0.0378) Prec@1 96.000 (93.545) Prec@5 100.000 (99.864) +2022-11-14 14:33:48,048 Epoch: [217][440/500] Time 0.041 (0.030) Data 0.002 (0.002) Loss 0.0436 (0.0379) Prec@1 93.000 (93.533) Prec@5 100.000 (99.867) +2022-11-14 14:33:48,391 Epoch: [217][450/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.0694 (0.0386) Prec@1 87.000 (93.391) Prec@5 100.000 (99.870) +2022-11-14 14:33:48,730 Epoch: [217][460/500] Time 0.030 (0.030) Data 0.001 (0.002) Loss 0.0354 (0.0385) Prec@1 96.000 (93.447) Prec@5 99.000 (99.851) +2022-11-14 14:33:49,072 Epoch: [217][470/500] Time 0.032 (0.030) Data 0.001 (0.002) Loss 0.0227 (0.0382) Prec@1 97.000 (93.521) Prec@5 100.000 (99.854) +2022-11-14 14:33:49,420 Epoch: [217][480/500] Time 0.031 (0.030) Data 0.002 (0.002) Loss 0.0827 (0.0391) Prec@1 85.000 (93.347) Prec@5 100.000 (99.857) +2022-11-14 14:33:49,761 Epoch: [217][490/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0317 (0.0389) Prec@1 95.000 (93.380) Prec@5 100.000 (99.860) +2022-11-14 14:33:50,075 Epoch: [217][499/500] Time 0.032 (0.030) Data 0.001 (0.002) Loss 0.0516 (0.0392) Prec@1 91.000 (93.333) Prec@5 100.000 (99.863) +2022-11-14 14:33:50,364 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0610 (0.0610) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:50,372 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0661) Prec@1 88.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:33:50,383 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0685) Prec@1 88.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 14:33:50,395 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0703) Prec@1 85.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 14:33:50,404 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0719) Prec@1 87.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 14:33:50,413 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0297 (0.0648) Prec@1 95.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 14:33:50,423 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0655) Prec@1 89.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 14:33:50,434 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0677) Prec@1 86.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 14:33:50,444 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0685) Prec@1 87.000 (88.556) Prec@5 98.000 (99.556) +2022-11-14 14:33:50,453 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0686) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:33:50,464 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0679) Prec@1 90.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 14:33:50,475 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0689) Prec@1 89.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 14:33:50,486 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0692) Prec@1 87.000 (88.538) Prec@5 100.000 (99.538) +2022-11-14 14:33:50,498 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0696) Prec@1 90.000 (88.643) Prec@5 99.000 (99.500) +2022-11-14 14:33:50,508 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0696) Prec@1 89.000 (88.667) Prec@5 99.000 (99.467) +2022-11-14 14:33:50,521 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0720) Prec@1 82.000 (88.250) Prec@5 99.000 (99.438) +2022-11-14 14:33:50,533 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0708) Prec@1 93.000 (88.529) Prec@5 99.000 (99.412) +2022-11-14 14:33:50,544 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0720) Prec@1 86.000 (88.389) Prec@5 99.000 (99.389) +2022-11-14 14:33:50,556 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0730) Prec@1 85.000 (88.211) Prec@5 98.000 (99.316) +2022-11-14 14:33:50,567 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0733) Prec@1 87.000 (88.150) Prec@5 100.000 (99.350) +2022-11-14 14:33:50,577 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0742) Prec@1 83.000 (87.905) Prec@5 100.000 (99.381) +2022-11-14 14:33:50,590 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0746) Prec@1 85.000 (87.773) Prec@5 99.000 (99.364) +2022-11-14 14:33:50,601 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0753) Prec@1 85.000 (87.652) Prec@5 98.000 (99.304) +2022-11-14 14:33:50,612 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0760) Prec@1 84.000 (87.500) Prec@5 99.000 (99.292) +2022-11-14 14:33:50,624 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0767) Prec@1 87.000 (87.480) Prec@5 99.000 (99.280) +2022-11-14 14:33:50,635 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0770) Prec@1 87.000 (87.462) Prec@5 99.000 (99.269) +2022-11-14 14:33:50,646 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0757) Prec@1 94.000 (87.704) Prec@5 100.000 (99.296) +2022-11-14 14:33:50,658 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0755) Prec@1 88.000 (87.714) Prec@5 100.000 (99.321) +2022-11-14 14:33:50,669 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0755) Prec@1 88.000 (87.724) Prec@5 99.000 (99.310) +2022-11-14 14:33:50,682 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0760) Prec@1 85.000 (87.633) Prec@5 100.000 (99.333) +2022-11-14 14:33:50,695 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0761) Prec@1 85.000 (87.548) Prec@5 100.000 (99.355) +2022-11-14 14:33:50,708 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0758) Prec@1 91.000 (87.656) Prec@5 99.000 (99.344) +2022-11-14 14:33:50,719 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0767) Prec@1 82.000 (87.485) Prec@5 99.000 (99.333) +2022-11-14 14:33:50,729 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0771) Prec@1 85.000 (87.412) Prec@5 100.000 (99.353) +2022-11-14 14:33:50,740 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0772) Prec@1 87.000 (87.400) Prec@5 99.000 (99.343) +2022-11-14 14:33:50,750 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0772) Prec@1 89.000 (87.444) Prec@5 100.000 (99.361) +2022-11-14 14:33:50,761 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0769) Prec@1 88.000 (87.459) Prec@5 99.000 (99.351) +2022-11-14 14:33:50,774 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0779) Prec@1 82.000 (87.316) Prec@5 99.000 (99.342) +2022-11-14 14:33:50,786 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0383 (0.0769) Prec@1 95.000 (87.513) Prec@5 98.000 (99.308) +2022-11-14 14:33:50,799 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0768) Prec@1 86.000 (87.475) Prec@5 100.000 (99.325) +2022-11-14 14:33:50,811 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0773) Prec@1 84.000 (87.390) Prec@5 97.000 (99.268) +2022-11-14 14:33:50,823 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0771) Prec@1 89.000 (87.429) Prec@5 99.000 (99.262) +2022-11-14 14:33:50,836 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0766) Prec@1 91.000 (87.512) Prec@5 99.000 (99.256) +2022-11-14 14:33:50,848 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0764) Prec@1 89.000 (87.545) Prec@5 98.000 (99.227) +2022-11-14 14:33:50,859 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0764) Prec@1 87.000 (87.533) Prec@5 99.000 (99.222) +2022-11-14 14:33:50,872 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0766) Prec@1 85.000 (87.478) Prec@5 99.000 (99.217) +2022-11-14 14:33:50,885 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0764) Prec@1 89.000 (87.511) Prec@5 99.000 (99.213) +2022-11-14 14:33:50,897 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0766) Prec@1 83.000 (87.417) Prec@5 99.000 (99.208) +2022-11-14 14:33:50,910 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0760) Prec@1 94.000 (87.551) Prec@5 100.000 (99.224) +2022-11-14 14:33:50,922 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0764) Prec@1 84.000 (87.480) Prec@5 99.000 (99.220) +2022-11-14 14:33:50,935 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0766) Prec@1 86.000 (87.451) Prec@5 100.000 (99.235) +2022-11-14 14:33:50,948 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0770) Prec@1 85.000 (87.404) Prec@5 99.000 (99.231) +2022-11-14 14:33:50,960 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0771) Prec@1 87.000 (87.396) Prec@5 100.000 (99.245) +2022-11-14 14:33:50,972 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0769) Prec@1 90.000 (87.444) Prec@5 98.000 (99.222) +2022-11-14 14:33:50,984 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0770) Prec@1 85.000 (87.400) Prec@5 100.000 (99.236) +2022-11-14 14:33:50,997 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0770) Prec@1 89.000 (87.429) Prec@5 99.000 (99.232) +2022-11-14 14:33:51,010 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0769) Prec@1 88.000 (87.439) Prec@5 100.000 (99.246) +2022-11-14 14:33:51,022 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0766) Prec@1 91.000 (87.500) Prec@5 100.000 (99.259) +2022-11-14 14:33:51,033 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0770) Prec@1 86.000 (87.475) Prec@5 100.000 (99.271) +2022-11-14 14:33:51,045 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0772) Prec@1 86.000 (87.450) Prec@5 99.000 (99.267) +2022-11-14 14:33:51,057 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0776) Prec@1 84.000 (87.393) Prec@5 99.000 (99.262) +2022-11-14 14:33:51,067 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0775) Prec@1 88.000 (87.403) Prec@5 99.000 (99.258) +2022-11-14 14:33:51,081 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0773) Prec@1 91.000 (87.460) Prec@5 100.000 (99.270) +2022-11-14 14:33:51,094 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0326 (0.0766) Prec@1 97.000 (87.609) Prec@5 100.000 (99.281) +2022-11-14 14:33:51,105 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0768) Prec@1 86.000 (87.585) Prec@5 99.000 (99.277) +2022-11-14 14:33:51,116 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0768) Prec@1 87.000 (87.576) Prec@5 98.000 (99.258) +2022-11-14 14:33:51,128 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0763) Prec@1 92.000 (87.642) Prec@5 100.000 (99.269) +2022-11-14 14:33:51,140 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0764) Prec@1 88.000 (87.647) Prec@5 100.000 (99.279) +2022-11-14 14:33:51,153 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0762) Prec@1 91.000 (87.696) Prec@5 99.000 (99.275) +2022-11-14 14:33:51,164 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0763) Prec@1 85.000 (87.657) Prec@5 100.000 (99.286) +2022-11-14 14:33:51,177 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0764) Prec@1 88.000 (87.662) Prec@5 99.000 (99.282) +2022-11-14 14:33:51,188 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0764) Prec@1 88.000 (87.667) Prec@5 99.000 (99.278) +2022-11-14 14:33:51,199 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0761) Prec@1 93.000 (87.740) Prec@5 99.000 (99.274) +2022-11-14 14:33:51,212 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0757) Prec@1 92.000 (87.797) Prec@5 100.000 (99.284) +2022-11-14 14:33:51,224 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0762) Prec@1 81.000 (87.707) Prec@5 99.000 (99.280) +2022-11-14 14:33:51,236 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0760) Prec@1 88.000 (87.711) Prec@5 99.000 (99.276) +2022-11-14 14:33:51,248 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0761) Prec@1 86.000 (87.688) Prec@5 98.000 (99.260) +2022-11-14 14:33:51,261 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0764) Prec@1 85.000 (87.654) Prec@5 98.000 (99.244) +2022-11-14 14:33:51,276 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1182 (0.0769) Prec@1 80.000 (87.557) Prec@5 100.000 (99.253) +2022-11-14 14:33:51,290 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0769) Prec@1 85.000 (87.525) Prec@5 99.000 (99.250) +2022-11-14 14:33:51,302 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0769) Prec@1 87.000 (87.519) Prec@5 99.000 (99.247) +2022-11-14 14:33:51,313 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0768) Prec@1 90.000 (87.549) Prec@5 99.000 (99.244) +2022-11-14 14:33:51,324 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0767) Prec@1 88.000 (87.554) Prec@5 100.000 (99.253) +2022-11-14 14:33:51,336 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0766) Prec@1 89.000 (87.571) Prec@5 99.000 (99.250) +2022-11-14 14:33:51,347 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0767) Prec@1 87.000 (87.565) Prec@5 99.000 (99.247) +2022-11-14 14:33:51,359 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0771) Prec@1 81.000 (87.488) Prec@5 100.000 (99.256) +2022-11-14 14:33:51,371 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0769) Prec@1 92.000 (87.540) Prec@5 99.000 (99.253) +2022-11-14 14:33:51,383 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0770) Prec@1 88.000 (87.545) Prec@5 99.000 (99.250) +2022-11-14 14:33:51,394 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0769) Prec@1 88.000 (87.551) Prec@5 99.000 (99.247) +2022-11-14 14:33:51,406 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0767) Prec@1 92.000 (87.600) Prec@5 100.000 (99.256) +2022-11-14 14:33:51,418 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0764) Prec@1 92.000 (87.648) Prec@5 100.000 (99.264) +2022-11-14 14:33:51,428 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0762) Prec@1 88.000 (87.652) Prec@5 99.000 (99.261) +2022-11-14 14:33:51,441 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0762) Prec@1 89.000 (87.667) Prec@5 99.000 (99.258) +2022-11-14 14:33:51,453 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0762) Prec@1 90.000 (87.691) Prec@5 100.000 (99.266) +2022-11-14 14:33:51,464 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0765) Prec@1 81.000 (87.621) Prec@5 99.000 (99.263) +2022-11-14 14:33:51,477 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0764) Prec@1 89.000 (87.635) Prec@5 100.000 (99.271) +2022-11-14 14:33:51,489 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0407 (0.0760) Prec@1 92.000 (87.680) Prec@5 98.000 (99.258) +2022-11-14 14:33:51,501 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0763) Prec@1 84.000 (87.643) Prec@5 99.000 (99.255) +2022-11-14 14:33:51,511 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0767) Prec@1 80.000 (87.566) Prec@5 100.000 (99.263) +2022-11-14 14:33:51,522 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0765) Prec@1 90.000 (87.590) Prec@5 100.000 (99.270) +2022-11-14 14:33:51,578 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:33:51,876 Epoch: [218][0/500] Time 0.023 (0.023) Data 0.216 (0.216) Loss 0.0298 (0.0298) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:33:52,093 Epoch: [218][10/500] Time 0.019 (0.019) Data 0.002 (0.021) Loss 0.0434 (0.0366) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:33:52,341 Epoch: [218][20/500] Time 0.026 (0.020) Data 0.002 (0.012) Loss 0.0418 (0.0383) Prec@1 93.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:33:52,744 Epoch: [218][30/500] Time 0.043 (0.025) Data 0.002 (0.009) Loss 0.0371 (0.0380) Prec@1 93.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 14:33:53,215 Epoch: [218][40/500] Time 0.043 (0.029) Data 0.002 (0.007) Loss 0.0536 (0.0411) Prec@1 93.000 (93.200) Prec@5 99.000 (99.800) +2022-11-14 14:33:53,695 Epoch: [218][50/500] Time 0.043 (0.032) Data 0.001 (0.006) Loss 0.0295 (0.0392) Prec@1 93.000 (93.167) Prec@5 100.000 (99.833) +2022-11-14 14:33:54,167 Epoch: [218][60/500] Time 0.043 (0.034) Data 0.002 (0.005) Loss 0.0472 (0.0404) Prec@1 92.000 (93.000) Prec@5 100.000 (99.857) +2022-11-14 14:33:54,646 Epoch: [218][70/500] Time 0.048 (0.035) Data 0.002 (0.005) Loss 0.0387 (0.0401) Prec@1 94.000 (93.125) Prec@5 100.000 (99.875) +2022-11-14 14:33:55,111 Epoch: [218][80/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0256 (0.0385) Prec@1 96.000 (93.444) Prec@5 100.000 (99.889) +2022-11-14 14:33:55,593 Epoch: [218][90/500] Time 0.045 (0.037) Data 0.002 (0.004) Loss 0.0347 (0.0381) Prec@1 95.000 (93.600) Prec@5 100.000 (99.900) +2022-11-14 14:33:56,068 Epoch: [218][100/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0734 (0.0413) Prec@1 86.000 (92.909) Prec@5 98.000 (99.727) +2022-11-14 14:33:56,546 Epoch: [218][110/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0296 (0.0404) Prec@1 95.000 (93.083) Prec@5 100.000 (99.750) +2022-11-14 14:33:57,019 Epoch: [218][120/500] Time 0.042 (0.038) Data 0.002 (0.004) Loss 0.0300 (0.0396) Prec@1 96.000 (93.308) Prec@5 100.000 (99.769) +2022-11-14 14:33:57,492 Epoch: [218][130/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0628 (0.0412) Prec@1 89.000 (93.000) Prec@5 99.000 (99.714) +2022-11-14 14:33:57,963 Epoch: [218][140/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0513 (0.0419) Prec@1 92.000 (92.933) Prec@5 98.000 (99.600) +2022-11-14 14:33:58,442 Epoch: [218][150/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0452 (0.0421) Prec@1 91.000 (92.812) Prec@5 100.000 (99.625) +2022-11-14 14:33:58,915 Epoch: [218][160/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0440 (0.0422) Prec@1 94.000 (92.882) Prec@5 100.000 (99.647) +2022-11-14 14:33:59,388 Epoch: [218][170/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0398 (0.0421) Prec@1 92.000 (92.833) Prec@5 100.000 (99.667) +2022-11-14 14:33:59,854 Epoch: [218][180/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0393 (0.0419) Prec@1 95.000 (92.947) Prec@5 99.000 (99.632) +2022-11-14 14:34:00,338 Epoch: [218][190/500] Time 0.054 (0.040) Data 0.001 (0.003) Loss 0.0348 (0.0416) Prec@1 95.000 (93.050) Prec@5 99.000 (99.600) +2022-11-14 14:34:00,810 Epoch: [218][200/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0515 (0.0421) Prec@1 92.000 (93.000) Prec@5 99.000 (99.571) +2022-11-14 14:34:01,292 Epoch: [218][210/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.0343 (0.0417) Prec@1 92.000 (92.955) Prec@5 100.000 (99.591) +2022-11-14 14:34:01,756 Epoch: [218][220/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0314 (0.0413) Prec@1 94.000 (93.000) Prec@5 100.000 (99.609) +2022-11-14 14:34:02,227 Epoch: [218][230/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0501 (0.0416) Prec@1 93.000 (93.000) Prec@5 100.000 (99.625) +2022-11-14 14:34:02,707 Epoch: [218][240/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0451 (0.0418) Prec@1 93.000 (93.000) Prec@5 100.000 (99.640) +2022-11-14 14:34:03,176 Epoch: [218][250/500] Time 0.044 (0.040) Data 0.001 (0.003) Loss 0.0387 (0.0416) Prec@1 94.000 (93.038) Prec@5 100.000 (99.654) +2022-11-14 14:34:03,658 Epoch: [218][260/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.0359 (0.0414) Prec@1 95.000 (93.111) Prec@5 100.000 (99.667) +2022-11-14 14:34:04,122 Epoch: [218][270/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0248 (0.0408) Prec@1 96.000 (93.214) Prec@5 100.000 (99.679) +2022-11-14 14:34:04,604 Epoch: [218][280/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0604 (0.0415) Prec@1 90.000 (93.103) Prec@5 99.000 (99.655) +2022-11-14 14:34:05,076 Epoch: [218][290/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0525 (0.0419) Prec@1 91.000 (93.033) Prec@5 100.000 (99.667) +2022-11-14 14:34:05,559 Epoch: [218][300/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0380 (0.0418) Prec@1 94.000 (93.065) Prec@5 100.000 (99.677) +2022-11-14 14:34:06,032 Epoch: [218][310/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0421 (0.0418) Prec@1 93.000 (93.062) Prec@5 99.000 (99.656) +2022-11-14 14:34:06,550 Epoch: [218][320/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0592 (0.0423) Prec@1 90.000 (92.970) Prec@5 100.000 (99.667) +2022-11-14 14:34:07,058 Epoch: [218][330/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0417 (0.0423) Prec@1 94.000 (93.000) Prec@5 100.000 (99.676) +2022-11-14 14:34:07,575 Epoch: [218][340/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0230 (0.0417) Prec@1 96.000 (93.086) Prec@5 100.000 (99.686) +2022-11-14 14:34:07,931 Epoch: [218][350/500] Time 0.028 (0.041) Data 0.002 (0.002) Loss 0.0438 (0.0418) Prec@1 94.000 (93.111) Prec@5 100.000 (99.694) +2022-11-14 14:34:08,251 Epoch: [218][360/500] Time 0.028 (0.040) Data 0.002 (0.002) Loss 0.0196 (0.0412) Prec@1 97.000 (93.216) Prec@5 100.000 (99.703) +2022-11-14 14:34:08,574 Epoch: [218][370/500] Time 0.028 (0.040) Data 0.002 (0.002) Loss 0.0332 (0.0410) Prec@1 94.000 (93.237) Prec@5 100.000 (99.711) +2022-11-14 14:34:08,884 Epoch: [218][380/500] Time 0.031 (0.040) Data 0.002 (0.002) Loss 0.0482 (0.0412) Prec@1 92.000 (93.205) Prec@5 99.000 (99.692) +2022-11-14 14:34:09,203 Epoch: [218][390/500] Time 0.032 (0.039) Data 0.002 (0.002) Loss 0.0242 (0.0407) Prec@1 95.000 (93.250) Prec@5 100.000 (99.700) +2022-11-14 14:34:09,523 Epoch: [218][400/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.0408 (0.0407) Prec@1 93.000 (93.244) Prec@5 100.000 (99.707) +2022-11-14 14:34:09,851 Epoch: [218][410/500] Time 0.027 (0.039) Data 0.002 (0.002) Loss 0.0571 (0.0411) Prec@1 89.000 (93.143) Prec@5 100.000 (99.714) +2022-11-14 14:34:10,157 Epoch: [218][420/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0397 (0.0411) Prec@1 94.000 (93.163) Prec@5 100.000 (99.721) +2022-11-14 14:34:10,468 Epoch: [218][430/500] Time 0.027 (0.038) Data 0.002 (0.002) Loss 0.0319 (0.0409) Prec@1 95.000 (93.205) Prec@5 99.000 (99.705) +2022-11-14 14:34:10,788 Epoch: [218][440/500] Time 0.029 (0.038) Data 0.002 (0.002) Loss 0.0692 (0.0415) Prec@1 89.000 (93.111) Prec@5 100.000 (99.711) +2022-11-14 14:34:11,109 Epoch: [218][450/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0632 (0.0420) Prec@1 89.000 (93.022) Prec@5 100.000 (99.717) +2022-11-14 14:34:11,432 Epoch: [218][460/500] Time 0.029 (0.038) Data 0.002 (0.002) Loss 0.0411 (0.0420) Prec@1 92.000 (93.000) Prec@5 100.000 (99.723) +2022-11-14 14:34:11,747 Epoch: [218][470/500] Time 0.034 (0.038) Data 0.003 (0.002) Loss 0.0478 (0.0421) Prec@1 92.000 (92.979) Prec@5 100.000 (99.729) +2022-11-14 14:34:12,069 Epoch: [218][480/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0526 (0.0423) Prec@1 92.000 (92.959) Prec@5 100.000 (99.735) +2022-11-14 14:34:12,390 Epoch: [218][490/500] Time 0.029 (0.037) Data 0.001 (0.002) Loss 0.0501 (0.0425) Prec@1 93.000 (92.960) Prec@5 99.000 (99.720) +2022-11-14 14:34:12,679 Epoch: [218][499/500] Time 0.033 (0.037) Data 0.002 (0.002) Loss 0.0403 (0.0424) Prec@1 92.000 (92.941) Prec@5 100.000 (99.725) +2022-11-14 14:34:12,991 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0552 (0.0552) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:13,003 Test: [1/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.0724 (0.0638) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:13,018 Test: [2/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0710 (0.0662) Prec@1 88.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:34:13,034 Test: [3/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0556 (0.0635) Prec@1 91.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 14:34:13,045 Test: [4/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0632 (0.0635) Prec@1 89.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 14:34:13,054 Test: [5/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0501 (0.0613) Prec@1 91.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 14:34:13,062 Test: [6/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0834 (0.0644) Prec@1 87.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 14:34:13,077 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0734 (0.0655) Prec@1 87.000 (88.875) Prec@5 100.000 (99.625) +2022-11-14 14:34:13,087 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0798 (0.0671) Prec@1 89.000 (88.889) Prec@5 99.000 (99.556) +2022-11-14 14:34:13,094 Test: [9/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0721 (0.0676) Prec@1 89.000 (88.900) Prec@5 99.000 (99.500) +2022-11-14 14:34:13,102 Test: [10/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0660) Prec@1 94.000 (89.364) Prec@5 100.000 (99.545) +2022-11-14 14:34:13,110 Test: [11/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0661) Prec@1 89.000 (89.333) Prec@5 99.000 (99.500) +2022-11-14 14:34:13,118 Test: [12/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0452 (0.0645) Prec@1 93.000 (89.615) Prec@5 100.000 (99.538) +2022-11-14 14:34:13,127 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0650) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:34:13,137 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0661) Prec@1 86.000 (89.267) Prec@5 100.000 (99.533) +2022-11-14 14:34:13,146 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0896 (0.0676) Prec@1 86.000 (89.062) Prec@5 98.000 (99.438) +2022-11-14 14:34:13,157 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0675) Prec@1 88.000 (89.000) Prec@5 99.000 (99.412) +2022-11-14 14:34:13,170 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1045 (0.0695) Prec@1 84.000 (88.722) Prec@5 99.000 (99.389) +2022-11-14 14:34:13,181 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0701) Prec@1 85.000 (88.526) Prec@5 99.000 (99.368) +2022-11-14 14:34:13,191 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0696) Prec@1 92.000 (88.700) Prec@5 99.000 (99.350) +2022-11-14 14:34:13,201 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.0714) Prec@1 84.000 (88.476) Prec@5 99.000 (99.333) +2022-11-14 14:34:13,211 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0721) Prec@1 84.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 14:34:13,220 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0728) Prec@1 86.000 (88.174) Prec@5 98.000 (99.304) +2022-11-14 14:34:13,229 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0730) Prec@1 86.000 (88.083) Prec@5 100.000 (99.333) +2022-11-14 14:34:13,238 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0731) Prec@1 88.000 (88.080) Prec@5 100.000 (99.360) +2022-11-14 14:34:13,246 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0735) Prec@1 87.000 (88.038) Prec@5 99.000 (99.346) +2022-11-14 14:34:13,255 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0723) Prec@1 94.000 (88.259) Prec@5 100.000 (99.370) +2022-11-14 14:34:13,265 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0720) Prec@1 88.000 (88.250) Prec@5 100.000 (99.393) +2022-11-14 14:34:13,273 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0721) Prec@1 87.000 (88.207) Prec@5 98.000 (99.345) +2022-11-14 14:34:13,284 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0717) Prec@1 91.000 (88.300) Prec@5 99.000 (99.333) +2022-11-14 14:34:13,293 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0717) Prec@1 87.000 (88.258) Prec@5 99.000 (99.323) +2022-11-14 14:34:13,302 Test: [31/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0722) Prec@1 86.000 (88.188) Prec@5 100.000 (99.344) +2022-11-14 14:34:13,312 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0722) Prec@1 87.000 (88.152) Prec@5 100.000 (99.364) +2022-11-14 14:34:13,322 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0722) Prec@1 87.000 (88.118) Prec@5 99.000 (99.353) +2022-11-14 14:34:13,330 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0723) Prec@1 87.000 (88.086) Prec@5 98.000 (99.314) +2022-11-14 14:34:13,340 Test: [35/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0718) Prec@1 91.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 14:34:13,349 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0720) Prec@1 88.000 (88.162) Prec@5 99.000 (99.324) +2022-11-14 14:34:13,358 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0725) Prec@1 84.000 (88.053) Prec@5 99.000 (99.316) +2022-11-14 14:34:13,368 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0718) Prec@1 92.000 (88.154) Prec@5 99.000 (99.308) +2022-11-14 14:34:13,377 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0718) Prec@1 87.000 (88.125) Prec@5 100.000 (99.325) +2022-11-14 14:34:13,386 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0724) Prec@1 83.000 (88.000) Prec@5 98.000 (99.293) +2022-11-14 14:34:13,395 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0723) Prec@1 89.000 (88.024) Prec@5 98.000 (99.262) +2022-11-14 14:34:13,405 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0719) Prec@1 92.000 (88.116) Prec@5 99.000 (99.256) +2022-11-14 14:34:13,414 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0714) Prec@1 91.000 (88.182) Prec@5 99.000 (99.250) +2022-11-14 14:34:13,423 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0715) Prec@1 89.000 (88.200) Prec@5 99.000 (99.244) +2022-11-14 14:34:13,432 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0724) Prec@1 82.000 (88.065) Prec@5 98.000 (99.217) +2022-11-14 14:34:13,440 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0722) Prec@1 88.000 (88.064) Prec@5 100.000 (99.234) +2022-11-14 14:34:13,449 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0731) Prec@1 81.000 (87.917) Prec@5 98.000 (99.208) +2022-11-14 14:34:13,459 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0727) Prec@1 92.000 (88.000) Prec@5 100.000 (99.224) +2022-11-14 14:34:13,467 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0733) Prec@1 84.000 (87.920) Prec@5 100.000 (99.240) +2022-11-14 14:34:13,475 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0729) Prec@1 89.000 (87.941) Prec@5 100.000 (99.255) +2022-11-14 14:34:13,484 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1189 (0.0738) Prec@1 78.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 14:34:13,493 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0739) Prec@1 86.000 (87.717) Prec@5 99.000 (99.245) +2022-11-14 14:34:13,502 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0737) Prec@1 90.000 (87.759) Prec@5 100.000 (99.259) +2022-11-14 14:34:13,510 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0741) Prec@1 84.000 (87.691) Prec@5 100.000 (99.273) +2022-11-14 14:34:13,520 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0739) Prec@1 92.000 (87.768) Prec@5 99.000 (99.268) +2022-11-14 14:34:13,529 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0738) Prec@1 89.000 (87.789) Prec@5 100.000 (99.281) +2022-11-14 14:34:13,538 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0739) Prec@1 87.000 (87.776) Prec@5 100.000 (99.293) +2022-11-14 14:34:13,548 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0744) Prec@1 84.000 (87.712) Prec@5 100.000 (99.305) +2022-11-14 14:34:13,557 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0745) Prec@1 85.000 (87.667) Prec@5 100.000 (99.317) +2022-11-14 14:34:13,566 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0748) Prec@1 87.000 (87.656) Prec@5 100.000 (99.328) +2022-11-14 14:34:13,574 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0748) Prec@1 85.000 (87.613) Prec@5 100.000 (99.339) +2022-11-14 14:34:13,584 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0746) Prec@1 89.000 (87.635) Prec@5 100.000 (99.349) +2022-11-14 14:34:13,594 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0741) Prec@1 92.000 (87.703) Prec@5 100.000 (99.359) +2022-11-14 14:34:13,604 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0746) Prec@1 80.000 (87.585) Prec@5 100.000 (99.369) +2022-11-14 14:34:13,613 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0750) Prec@1 84.000 (87.530) Prec@5 99.000 (99.364) +2022-11-14 14:34:13,624 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0747) Prec@1 89.000 (87.552) Prec@5 100.000 (99.373) +2022-11-14 14:34:13,634 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0747) Prec@1 87.000 (87.544) Prec@5 99.000 (99.368) +2022-11-14 14:34:13,643 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0746) Prec@1 89.000 (87.565) Prec@5 99.000 (99.362) +2022-11-14 14:34:13,652 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0749) Prec@1 84.000 (87.514) Prec@5 100.000 (99.371) +2022-11-14 14:34:13,661 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0750) Prec@1 87.000 (87.507) Prec@5 99.000 (99.366) +2022-11-14 14:34:13,670 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0747) Prec@1 91.000 (87.556) Prec@5 99.000 (99.361) +2022-11-14 14:34:13,679 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0744) Prec@1 92.000 (87.616) Prec@5 100.000 (99.370) +2022-11-14 14:34:13,688 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0381 (0.0739) Prec@1 95.000 (87.716) Prec@5 100.000 (99.378) +2022-11-14 14:34:13,696 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0743) Prec@1 82.000 (87.640) Prec@5 99.000 (99.373) +2022-11-14 14:34:13,704 Test: [75/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0741) Prec@1 90.000 (87.671) Prec@5 100.000 (99.382) +2022-11-14 14:34:13,712 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0740) Prec@1 90.000 (87.701) Prec@5 99.000 (99.377) +2022-11-14 14:34:13,722 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0741) Prec@1 86.000 (87.679) Prec@5 98.000 (99.359) +2022-11-14 14:34:13,735 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0744) Prec@1 84.000 (87.633) Prec@5 100.000 (99.367) +2022-11-14 14:34:13,747 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0745) Prec@1 84.000 (87.588) Prec@5 100.000 (99.375) +2022-11-14 14:34:13,757 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0746) Prec@1 84.000 (87.543) Prec@5 98.000 (99.358) +2022-11-14 14:34:13,766 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0746) Prec@1 87.000 (87.537) Prec@5 100.000 (99.366) +2022-11-14 14:34:13,775 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0747) Prec@1 83.000 (87.482) Prec@5 100.000 (99.373) +2022-11-14 14:34:13,786 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0748) Prec@1 85.000 (87.452) Prec@5 99.000 (99.369) +2022-11-14 14:34:13,796 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0747) Prec@1 89.000 (87.471) Prec@5 99.000 (99.365) +2022-11-14 14:34:13,807 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0750) Prec@1 84.000 (87.430) Prec@5 98.000 (99.349) +2022-11-14 14:34:13,818 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0752) Prec@1 88.000 (87.437) Prec@5 98.000 (99.333) +2022-11-14 14:34:13,831 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0750) Prec@1 92.000 (87.489) Prec@5 98.000 (99.318) +2022-11-14 14:34:13,845 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0749) Prec@1 89.000 (87.506) Prec@5 100.000 (99.326) +2022-11-14 14:34:13,859 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0750) Prec@1 85.000 (87.478) Prec@5 98.000 (99.311) +2022-11-14 14:34:13,872 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0750) Prec@1 90.000 (87.505) Prec@5 100.000 (99.319) +2022-11-14 14:34:13,888 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0747) Prec@1 92.000 (87.554) Prec@5 100.000 (99.326) +2022-11-14 14:34:13,901 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0746) Prec@1 90.000 (87.581) Prec@5 100.000 (99.333) +2022-11-14 14:34:13,917 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0746) Prec@1 88.000 (87.585) Prec@5 100.000 (99.340) +2022-11-14 14:34:13,930 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0748) Prec@1 83.000 (87.537) Prec@5 100.000 (99.347) +2022-11-14 14:34:13,945 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0747) Prec@1 89.000 (87.552) Prec@5 100.000 (99.354) +2022-11-14 14:34:13,961 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0745) Prec@1 91.000 (87.588) Prec@5 99.000 (99.351) +2022-11-14 14:34:13,975 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0746) Prec@1 87.000 (87.582) Prec@5 99.000 (99.347) +2022-11-14 14:34:13,989 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0747) Prec@1 88.000 (87.586) Prec@5 100.000 (99.354) +2022-11-14 14:34:14,003 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0747) Prec@1 89.000 (87.600) Prec@5 98.000 (99.340) +2022-11-14 14:34:14,061 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:34:14,368 Epoch: [219][0/500] Time 0.025 (0.025) Data 0.225 (0.225) Loss 0.0357 (0.0357) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:14,628 Epoch: [219][10/500] Time 0.026 (0.023) Data 0.002 (0.022) Loss 0.0278 (0.0318) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:34:14,906 Epoch: [219][20/500] Time 0.027 (0.024) Data 0.002 (0.013) Loss 0.0370 (0.0335) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:34:15,174 Epoch: [219][30/500] Time 0.028 (0.024) Data 0.001 (0.009) Loss 0.0390 (0.0349) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:34:15,449 Epoch: [219][40/500] Time 0.022 (0.024) Data 0.002 (0.007) Loss 0.0342 (0.0347) Prec@1 94.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 14:34:15,717 Epoch: [219][50/500] Time 0.023 (0.024) Data 0.002 (0.006) Loss 0.0610 (0.0391) Prec@1 91.000 (93.833) Prec@5 99.000 (99.833) +2022-11-14 14:34:16,081 Epoch: [219][60/500] Time 0.047 (0.025) Data 0.002 (0.005) Loss 0.0221 (0.0367) Prec@1 96.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 14:34:16,537 Epoch: [219][70/500] Time 0.049 (0.027) Data 0.002 (0.005) Loss 0.0305 (0.0359) Prec@1 94.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 14:34:16,985 Epoch: [219][80/500] Time 0.043 (0.029) Data 0.002 (0.005) Loss 0.0354 (0.0359) Prec@1 94.000 (94.111) Prec@5 100.000 (99.889) +2022-11-14 14:34:17,435 Epoch: [219][90/500] Time 0.041 (0.030) Data 0.002 (0.004) Loss 0.0280 (0.0351) Prec@1 94.000 (94.100) Prec@5 100.000 (99.900) +2022-11-14 14:34:17,871 Epoch: [219][100/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0349 (0.0351) Prec@1 94.000 (94.091) Prec@5 100.000 (99.909) +2022-11-14 14:34:18,321 Epoch: [219][110/500] Time 0.046 (0.032) Data 0.002 (0.004) Loss 0.0436 (0.0358) Prec@1 93.000 (94.000) Prec@5 100.000 (99.917) +2022-11-14 14:34:18,764 Epoch: [219][120/500] Time 0.037 (0.032) Data 0.002 (0.004) Loss 0.0463 (0.0366) Prec@1 92.000 (93.846) Prec@5 100.000 (99.923) +2022-11-14 14:34:19,195 Epoch: [219][130/500] Time 0.039 (0.033) Data 0.002 (0.004) Loss 0.0190 (0.0353) Prec@1 98.000 (94.143) Prec@5 100.000 (99.929) +2022-11-14 14:34:19,644 Epoch: [219][140/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0364 (0.0354) Prec@1 92.000 (94.000) Prec@5 100.000 (99.933) +2022-11-14 14:34:20,093 Epoch: [219][150/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0514 (0.0364) Prec@1 91.000 (93.812) Prec@5 100.000 (99.938) +2022-11-14 14:34:20,528 Epoch: [219][160/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0402 (0.0366) Prec@1 92.000 (93.706) Prec@5 100.000 (99.941) +2022-11-14 14:34:20,974 Epoch: [219][170/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0194 (0.0357) Prec@1 98.000 (93.944) Prec@5 100.000 (99.944) +2022-11-14 14:34:21,424 Epoch: [219][180/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0331 (0.0355) Prec@1 94.000 (93.947) Prec@5 99.000 (99.895) +2022-11-14 14:34:21,879 Epoch: [219][190/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0452 (0.0360) Prec@1 93.000 (93.900) Prec@5 100.000 (99.900) +2022-11-14 14:34:22,349 Epoch: [219][200/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0500 (0.0367) Prec@1 91.000 (93.762) Prec@5 100.000 (99.905) +2022-11-14 14:34:22,801 Epoch: [219][210/500] Time 0.038 (0.036) Data 0.002 (0.003) Loss 0.0285 (0.0363) Prec@1 95.000 (93.818) Prec@5 100.000 (99.909) +2022-11-14 14:34:23,247 Epoch: [219][220/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0562 (0.0372) Prec@1 89.000 (93.609) Prec@5 100.000 (99.913) +2022-11-14 14:34:23,697 Epoch: [219][230/500] Time 0.041 (0.036) Data 0.003 (0.003) Loss 0.0580 (0.0380) Prec@1 93.000 (93.583) Prec@5 99.000 (99.875) +2022-11-14 14:34:24,146 Epoch: [219][240/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0306 (0.0377) Prec@1 95.000 (93.640) Prec@5 100.000 (99.880) +2022-11-14 14:34:24,593 Epoch: [219][250/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0310 (0.0375) Prec@1 95.000 (93.692) Prec@5 100.000 (99.885) +2022-11-14 14:34:25,029 Epoch: [219][260/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0540 (0.0381) Prec@1 90.000 (93.556) Prec@5 100.000 (99.889) +2022-11-14 14:34:25,460 Epoch: [219][270/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0226 (0.0375) Prec@1 95.000 (93.607) Prec@5 99.000 (99.857) +2022-11-14 14:34:25,892 Epoch: [219][280/500] Time 0.041 (0.036) Data 0.001 (0.003) Loss 0.0294 (0.0373) Prec@1 94.000 (93.621) Prec@5 100.000 (99.862) +2022-11-14 14:34:26,345 Epoch: [219][290/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0506 (0.0377) Prec@1 94.000 (93.633) Prec@5 100.000 (99.867) +2022-11-14 14:34:26,781 Epoch: [219][300/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0454 (0.0380) Prec@1 91.000 (93.548) Prec@5 100.000 (99.871) +2022-11-14 14:34:27,241 Epoch: [219][310/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.0300 (0.0377) Prec@1 93.000 (93.531) Prec@5 100.000 (99.875) +2022-11-14 14:34:27,690 Epoch: [219][320/500] Time 0.034 (0.037) Data 0.002 (0.003) Loss 0.0465 (0.0380) Prec@1 94.000 (93.545) Prec@5 100.000 (99.879) +2022-11-14 14:34:28,120 Epoch: [219][330/500] Time 0.035 (0.037) Data 0.002 (0.003) Loss 0.0458 (0.0382) Prec@1 92.000 (93.500) Prec@5 100.000 (99.882) +2022-11-14 14:34:28,551 Epoch: [219][340/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0465 (0.0384) Prec@1 91.000 (93.429) Prec@5 100.000 (99.886) +2022-11-14 14:34:28,996 Epoch: [219][350/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0391 (0.0385) Prec@1 93.000 (93.417) Prec@5 99.000 (99.861) +2022-11-14 14:34:29,442 Epoch: [219][360/500] Time 0.048 (0.037) Data 0.002 (0.003) Loss 0.0263 (0.0381) Prec@1 96.000 (93.486) Prec@5 99.000 (99.838) +2022-11-14 14:34:29,879 Epoch: [219][370/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0728 (0.0390) Prec@1 87.000 (93.316) Prec@5 100.000 (99.842) +2022-11-14 14:34:30,324 Epoch: [219][380/500] Time 0.044 (0.037) Data 0.001 (0.003) Loss 0.0350 (0.0389) Prec@1 96.000 (93.385) Prec@5 100.000 (99.846) +2022-11-14 14:34:30,758 Epoch: [219][390/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0469 (0.0391) Prec@1 93.000 (93.375) Prec@5 100.000 (99.850) +2022-11-14 14:34:31,197 Epoch: [219][400/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0337 (0.0390) Prec@1 95.000 (93.415) Prec@5 100.000 (99.854) +2022-11-14 14:34:31,629 Epoch: [219][410/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0349 (0.0389) Prec@1 96.000 (93.476) Prec@5 100.000 (99.857) +2022-11-14 14:34:32,057 Epoch: [219][420/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0358 (0.0388) Prec@1 93.000 (93.465) Prec@5 100.000 (99.860) +2022-11-14 14:34:32,502 Epoch: [219][430/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0309 (0.0387) Prec@1 96.000 (93.523) Prec@5 100.000 (99.864) +2022-11-14 14:34:32,942 Epoch: [219][440/500] Time 0.042 (0.037) Data 0.001 (0.002) Loss 0.0550 (0.0390) Prec@1 91.000 (93.467) Prec@5 99.000 (99.844) +2022-11-14 14:34:33,377 Epoch: [219][450/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0492 (0.0392) Prec@1 93.000 (93.457) Prec@5 100.000 (99.848) +2022-11-14 14:34:33,809 Epoch: [219][460/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0346 (0.0391) Prec@1 95.000 (93.489) Prec@5 100.000 (99.851) +2022-11-14 14:34:34,238 Epoch: [219][470/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0299 (0.0389) Prec@1 95.000 (93.521) Prec@5 100.000 (99.854) +2022-11-14 14:34:34,660 Epoch: [219][480/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0389 (0.0389) Prec@1 94.000 (93.531) Prec@5 100.000 (99.857) +2022-11-14 14:34:35,108 Epoch: [219][490/500] Time 0.045 (0.038) Data 0.002 (0.002) Loss 0.0538 (0.0392) Prec@1 91.000 (93.480) Prec@5 100.000 (99.860) +2022-11-14 14:34:35,511 Epoch: [219][499/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0288 (0.0390) Prec@1 96.000 (93.529) Prec@5 99.000 (99.843) +2022-11-14 14:34:35,799 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0581 (0.0581) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:34:35,812 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0790 (0.0686) Prec@1 87.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:34:35,825 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.0732) Prec@1 85.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 14:34:35,836 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0748) Prec@1 90.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 14:34:35,844 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0740) Prec@1 87.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 14:34:35,855 Test: [5/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0431 (0.0688) Prec@1 93.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 14:34:35,866 Test: [6/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0576 (0.0672) Prec@1 90.000 (88.857) Prec@5 100.000 (99.429) +2022-11-14 14:34:35,876 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0694) Prec@1 87.000 (88.625) Prec@5 100.000 (99.500) +2022-11-14 14:34:35,884 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0697) Prec@1 88.000 (88.556) Prec@5 99.000 (99.444) +2022-11-14 14:34:35,896 Test: [9/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0888 (0.0716) Prec@1 88.000 (88.500) Prec@5 99.000 (99.400) +2022-11-14 14:34:35,908 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0622 (0.0707) Prec@1 91.000 (88.727) Prec@5 100.000 (99.455) +2022-11-14 14:34:35,917 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.0721) Prec@1 86.000 (88.500) Prec@5 98.000 (99.333) +2022-11-14 14:34:35,926 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0700) Prec@1 91.000 (88.692) Prec@5 100.000 (99.385) +2022-11-14 14:34:35,938 Test: [13/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0699) Prec@1 92.000 (88.929) Prec@5 99.000 (99.357) +2022-11-14 14:34:35,951 Test: [14/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0710) Prec@1 87.000 (88.800) Prec@5 98.000 (99.267) +2022-11-14 14:34:35,960 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0716) Prec@1 87.000 (88.688) Prec@5 100.000 (99.312) +2022-11-14 14:34:35,969 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0711) Prec@1 89.000 (88.706) Prec@5 99.000 (99.294) +2022-11-14 14:34:35,981 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.0736) Prec@1 82.000 (88.333) Prec@5 99.000 (99.278) +2022-11-14 14:34:35,991 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0734) Prec@1 90.000 (88.421) Prec@5 98.000 (99.211) +2022-11-14 14:34:36,002 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0748) Prec@1 85.000 (88.250) Prec@5 98.000 (99.150) +2022-11-14 14:34:36,011 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0755) Prec@1 86.000 (88.143) Prec@5 99.000 (99.143) +2022-11-14 14:34:36,020 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0763) Prec@1 85.000 (88.000) Prec@5 99.000 (99.136) +2022-11-14 14:34:36,029 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0770) Prec@1 87.000 (87.957) Prec@5 97.000 (99.043) +2022-11-14 14:34:36,038 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0774) Prec@1 86.000 (87.875) Prec@5 100.000 (99.083) +2022-11-14 14:34:36,047 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0774) Prec@1 89.000 (87.920) Prec@5 100.000 (99.120) +2022-11-14 14:34:36,057 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0783) Prec@1 84.000 (87.769) Prec@5 99.000 (99.115) +2022-11-14 14:34:36,066 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0774) Prec@1 91.000 (87.889) Prec@5 100.000 (99.148) +2022-11-14 14:34:36,075 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0770) Prec@1 89.000 (87.929) Prec@5 100.000 (99.179) +2022-11-14 14:34:36,085 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0771) Prec@1 86.000 (87.862) Prec@5 97.000 (99.103) +2022-11-14 14:34:36,094 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0773) Prec@1 83.000 (87.700) Prec@5 99.000 (99.100) +2022-11-14 14:34:36,106 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0773) Prec@1 86.000 (87.645) Prec@5 99.000 (99.097) +2022-11-14 14:34:36,117 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0774) Prec@1 87.000 (87.625) Prec@5 100.000 (99.125) +2022-11-14 14:34:36,126 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0773) Prec@1 87.000 (87.606) Prec@5 100.000 (99.152) +2022-11-14 14:34:36,135 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0779) Prec@1 83.000 (87.471) Prec@5 99.000 (99.147) +2022-11-14 14:34:36,147 Test: [34/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0783) Prec@1 85.000 (87.400) Prec@5 98.000 (99.114) +2022-11-14 14:34:36,158 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0782) Prec@1 87.000 (87.389) Prec@5 100.000 (99.139) +2022-11-14 14:34:36,169 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0784) Prec@1 84.000 (87.297) Prec@5 99.000 (99.135) +2022-11-14 14:34:36,178 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0788) Prec@1 83.000 (87.184) Prec@5 100.000 (99.158) +2022-11-14 14:34:36,190 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0782) Prec@1 90.000 (87.256) Prec@5 99.000 (99.154) +2022-11-14 14:34:36,202 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0775) Prec@1 93.000 (87.400) Prec@5 99.000 (99.150) +2022-11-14 14:34:36,211 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0782) Prec@1 84.000 (87.317) Prec@5 99.000 (99.146) +2022-11-14 14:34:36,223 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0778) Prec@1 90.000 (87.381) Prec@5 99.000 (99.143) +2022-11-14 14:34:36,234 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0353 (0.0768) Prec@1 94.000 (87.535) Prec@5 98.000 (99.116) +2022-11-14 14:34:36,244 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0766) Prec@1 89.000 (87.568) Prec@5 100.000 (99.136) +2022-11-14 14:34:36,253 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0764) Prec@1 89.000 (87.600) Prec@5 98.000 (99.111) +2022-11-14 14:34:36,267 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0766) Prec@1 87.000 (87.587) Prec@5 99.000 (99.109) +2022-11-14 14:34:36,279 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0765) Prec@1 88.000 (87.596) Prec@5 99.000 (99.106) +2022-11-14 14:34:36,288 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0771) Prec@1 83.000 (87.500) Prec@5 98.000 (99.083) +2022-11-14 14:34:36,298 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0766) Prec@1 93.000 (87.612) Prec@5 100.000 (99.102) +2022-11-14 14:34:36,311 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1129 (0.0773) Prec@1 83.000 (87.520) Prec@5 99.000 (99.100) +2022-11-14 14:34:36,322 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0773) Prec@1 87.000 (87.510) Prec@5 99.000 (99.098) +2022-11-14 14:34:36,330 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0773) Prec@1 86.000 (87.481) Prec@5 100.000 (99.115) +2022-11-14 14:34:36,339 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0772) Prec@1 87.000 (87.472) Prec@5 99.000 (99.113) +2022-11-14 14:34:36,348 Test: [53/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0773) Prec@1 86.000 (87.444) Prec@5 99.000 (99.111) +2022-11-14 14:34:36,360 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0772) Prec@1 86.000 (87.418) Prec@5 100.000 (99.127) +2022-11-14 14:34:36,372 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0771) Prec@1 89.000 (87.446) Prec@5 99.000 (99.125) +2022-11-14 14:34:36,382 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0769) Prec@1 90.000 (87.491) Prec@5 98.000 (99.105) +2022-11-14 14:34:36,390 Test: [57/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0767) Prec@1 90.000 (87.534) Prec@5 99.000 (99.103) +2022-11-14 14:34:36,402 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0768) Prec@1 85.000 (87.492) Prec@5 99.000 (99.102) +2022-11-14 14:34:36,413 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0770) Prec@1 84.000 (87.433) Prec@5 100.000 (99.117) +2022-11-14 14:34:36,423 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0774) Prec@1 83.000 (87.361) Prec@5 100.000 (99.131) +2022-11-14 14:34:36,432 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0775) Prec@1 88.000 (87.371) Prec@5 100.000 (99.145) +2022-11-14 14:34:36,444 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0773) Prec@1 88.000 (87.381) Prec@5 100.000 (99.159) +2022-11-14 14:34:36,455 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0382 (0.0767) Prec@1 94.000 (87.484) Prec@5 99.000 (99.156) +2022-11-14 14:34:36,464 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0768) Prec@1 86.000 (87.462) Prec@5 100.000 (99.169) +2022-11-14 14:34:36,474 Test: [65/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0767) Prec@1 90.000 (87.500) Prec@5 99.000 (99.167) +2022-11-14 14:34:36,485 Test: [66/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0766) Prec@1 87.000 (87.493) Prec@5 100.000 (99.179) +2022-11-14 14:34:36,497 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0765) Prec@1 90.000 (87.529) Prec@5 99.000 (99.176) +2022-11-14 14:34:36,507 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0766) Prec@1 85.000 (87.493) Prec@5 99.000 (99.174) +2022-11-14 14:34:36,516 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0767) Prec@1 86.000 (87.471) Prec@5 98.000 (99.157) +2022-11-14 14:34:36,525 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0767) Prec@1 86.000 (87.451) Prec@5 100.000 (99.169) +2022-11-14 14:34:36,535 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0765) Prec@1 89.000 (87.472) Prec@5 100.000 (99.181) +2022-11-14 14:34:36,544 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0761) Prec@1 94.000 (87.562) Prec@5 100.000 (99.192) +2022-11-14 14:34:36,552 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0415 (0.0757) Prec@1 94.000 (87.649) Prec@5 100.000 (99.203) +2022-11-14 14:34:36,562 Test: [74/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0759) Prec@1 83.000 (87.587) Prec@5 100.000 (99.213) +2022-11-14 14:34:36,571 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0757) Prec@1 90.000 (87.618) Prec@5 99.000 (99.211) +2022-11-14 14:34:36,580 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0755) Prec@1 91.000 (87.662) Prec@5 99.000 (99.208) +2022-11-14 14:34:36,589 Test: [77/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0757) Prec@1 85.000 (87.628) Prec@5 99.000 (99.205) +2022-11-14 14:34:36,599 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0758) Prec@1 86.000 (87.608) Prec@5 100.000 (99.215) +2022-11-14 14:34:36,608 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0759) Prec@1 84.000 (87.562) Prec@5 99.000 (99.213) +2022-11-14 14:34:36,617 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0762) Prec@1 86.000 (87.543) Prec@5 99.000 (99.210) +2022-11-14 14:34:36,626 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0760) Prec@1 90.000 (87.573) Prec@5 100.000 (99.220) +2022-11-14 14:34:36,634 Test: [82/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0760) Prec@1 87.000 (87.566) Prec@5 100.000 (99.229) +2022-11-14 14:34:36,642 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0759) Prec@1 84.000 (87.524) Prec@5 100.000 (99.238) +2022-11-14 14:34:36,651 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0760) Prec@1 87.000 (87.518) Prec@5 99.000 (99.235) +2022-11-14 14:34:36,660 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0764) Prec@1 83.000 (87.465) Prec@5 98.000 (99.221) +2022-11-14 14:34:36,668 Test: [86/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0762) Prec@1 91.000 (87.506) Prec@5 98.000 (99.207) +2022-11-14 14:34:36,677 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0760) Prec@1 89.000 (87.523) Prec@5 99.000 (99.205) +2022-11-14 14:34:36,685 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 87.000 (87.517) Prec@5 99.000 (99.202) +2022-11-14 14:34:36,695 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0760) Prec@1 88.000 (87.522) Prec@5 99.000 (99.200) +2022-11-14 14:34:36,703 Test: [90/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0760) Prec@1 87.000 (87.516) Prec@5 100.000 (99.209) +2022-11-14 14:34:36,711 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0758) Prec@1 91.000 (87.554) Prec@5 100.000 (99.217) +2022-11-14 14:34:36,721 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0759) Prec@1 87.000 (87.548) Prec@5 100.000 (99.226) +2022-11-14 14:34:36,730 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0760) Prec@1 85.000 (87.521) Prec@5 98.000 (99.213) +2022-11-14 14:34:36,738 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0760) Prec@1 86.000 (87.505) Prec@5 99.000 (99.211) +2022-11-14 14:34:36,747 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0760) Prec@1 87.000 (87.500) Prec@5 99.000 (99.208) +2022-11-14 14:34:36,756 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0420 (0.0756) Prec@1 93.000 (87.557) Prec@5 98.000 (99.196) +2022-11-14 14:34:36,765 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0757) Prec@1 87.000 (87.551) Prec@5 98.000 (99.184) +2022-11-14 14:34:36,774 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0757) Prec@1 86.000 (87.535) Prec@5 99.000 (99.182) +2022-11-14 14:34:36,782 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0756) Prec@1 92.000 (87.580) Prec@5 99.000 (99.180) +2022-11-14 14:34:36,837 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:34:37,151 Epoch: [220][0/500] Time 0.025 (0.025) Data 0.230 (0.230) Loss 0.0389 (0.0389) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:37,360 Epoch: [220][10/500] Time 0.018 (0.019) Data 0.001 (0.023) Loss 0.0363 (0.0376) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:34:37,571 Epoch: [220][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0315 (0.0355) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:34:37,789 Epoch: [220][30/500] Time 0.025 (0.019) Data 0.002 (0.009) Loss 0.0219 (0.0321) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:38,006 Epoch: [220][40/500] Time 0.019 (0.019) Data 0.002 (0.007) Loss 0.0380 (0.0333) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:38,278 Epoch: [220][50/500] Time 0.024 (0.020) Data 0.001 (0.006) Loss 0.0417 (0.0347) Prec@1 93.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:34:38,553 Epoch: [220][60/500] Time 0.025 (0.021) Data 0.002 (0.006) Loss 0.0131 (0.0316) Prec@1 98.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 14:34:38,831 Epoch: [220][70/500] Time 0.026 (0.021) Data 0.001 (0.005) Loss 0.0443 (0.0332) Prec@1 92.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 14:34:39,106 Epoch: [220][80/500] Time 0.025 (0.021) Data 0.002 (0.005) Loss 0.0277 (0.0326) Prec@1 95.000 (94.778) Prec@5 99.000 (99.889) +2022-11-14 14:34:39,385 Epoch: [220][90/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0533 (0.0347) Prec@1 91.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 14:34:39,663 Epoch: [220][100/500] Time 0.027 (0.022) Data 0.002 (0.004) Loss 0.0631 (0.0373) Prec@1 90.000 (94.000) Prec@5 100.000 (99.909) +2022-11-14 14:34:39,939 Epoch: [220][110/500] Time 0.025 (0.022) Data 0.001 (0.004) Loss 0.0455 (0.0379) Prec@1 93.000 (93.917) Prec@5 100.000 (99.917) +2022-11-14 14:34:40,214 Epoch: [220][120/500] Time 0.024 (0.022) Data 0.001 (0.004) Loss 0.0297 (0.0373) Prec@1 95.000 (94.000) Prec@5 100.000 (99.923) +2022-11-14 14:34:40,491 Epoch: [220][130/500] Time 0.025 (0.023) Data 0.001 (0.004) Loss 0.0275 (0.0366) Prec@1 96.000 (94.143) Prec@5 100.000 (99.929) +2022-11-14 14:34:40,764 Epoch: [220][140/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0381 (0.0367) Prec@1 93.000 (94.067) Prec@5 100.000 (99.933) +2022-11-14 14:34:41,042 Epoch: [220][150/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0468 (0.0373) Prec@1 94.000 (94.062) Prec@5 100.000 (99.938) +2022-11-14 14:34:41,325 Epoch: [220][160/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0666 (0.0391) Prec@1 89.000 (93.765) Prec@5 100.000 (99.941) +2022-11-14 14:34:41,599 Epoch: [220][170/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0620 (0.0403) Prec@1 91.000 (93.611) Prec@5 100.000 (99.944) +2022-11-14 14:34:42,025 Epoch: [220][180/500] Time 0.042 (0.024) Data 0.002 (0.003) Loss 0.0409 (0.0404) Prec@1 93.000 (93.579) Prec@5 99.000 (99.895) +2022-11-14 14:34:42,499 Epoch: [220][190/500] Time 0.043 (0.025) Data 0.002 (0.003) Loss 0.0310 (0.0399) Prec@1 94.000 (93.600) Prec@5 100.000 (99.900) +2022-11-14 14:34:42,961 Epoch: [220][200/500] Time 0.042 (0.026) Data 0.001 (0.003) Loss 0.0237 (0.0391) Prec@1 96.000 (93.714) Prec@5 100.000 (99.905) +2022-11-14 14:34:43,433 Epoch: [220][210/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.0545 (0.0398) Prec@1 91.000 (93.591) Prec@5 99.000 (99.864) +2022-11-14 14:34:43,895 Epoch: [220][220/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0420 (0.0399) Prec@1 92.000 (93.522) Prec@5 100.000 (99.870) +2022-11-14 14:34:44,368 Epoch: [220][230/500] Time 0.049 (0.028) Data 0.002 (0.003) Loss 0.0306 (0.0395) Prec@1 96.000 (93.625) Prec@5 100.000 (99.875) +2022-11-14 14:34:44,830 Epoch: [220][240/500] Time 0.044 (0.028) Data 0.001 (0.003) Loss 0.0520 (0.0400) Prec@1 89.000 (93.440) Prec@5 100.000 (99.880) +2022-11-14 14:34:45,302 Epoch: [220][250/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0306 (0.0397) Prec@1 94.000 (93.462) Prec@5 100.000 (99.885) +2022-11-14 14:34:45,766 Epoch: [220][260/500] Time 0.043 (0.029) Data 0.001 (0.003) Loss 0.0238 (0.0391) Prec@1 97.000 (93.593) Prec@5 100.000 (99.889) +2022-11-14 14:34:46,229 Epoch: [220][270/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0270 (0.0386) Prec@1 97.000 (93.714) Prec@5 100.000 (99.893) +2022-11-14 14:34:46,700 Epoch: [220][280/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0400 (0.0387) Prec@1 94.000 (93.724) Prec@5 100.000 (99.897) +2022-11-14 14:34:47,185 Epoch: [220][290/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0442 (0.0389) Prec@1 93.000 (93.700) Prec@5 100.000 (99.900) +2022-11-14 14:34:47,666 Epoch: [220][300/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0494 (0.0392) Prec@1 90.000 (93.581) Prec@5 100.000 (99.903) +2022-11-14 14:34:48,135 Epoch: [220][310/500] Time 0.049 (0.031) Data 0.002 (0.003) Loss 0.0254 (0.0388) Prec@1 95.000 (93.625) Prec@5 100.000 (99.906) +2022-11-14 14:34:48,609 Epoch: [220][320/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0404 (0.0388) Prec@1 93.000 (93.606) Prec@5 100.000 (99.909) +2022-11-14 14:34:49,081 Epoch: [220][330/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0475 (0.0391) Prec@1 92.000 (93.559) Prec@5 100.000 (99.912) +2022-11-14 14:34:49,564 Epoch: [220][340/500] Time 0.043 (0.032) Data 0.001 (0.003) Loss 0.0281 (0.0388) Prec@1 93.000 (93.543) Prec@5 100.000 (99.914) +2022-11-14 14:34:50,036 Epoch: [220][350/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0321 (0.0386) Prec@1 96.000 (93.611) Prec@5 100.000 (99.917) +2022-11-14 14:34:50,517 Epoch: [220][360/500] Time 0.055 (0.033) Data 0.002 (0.002) Loss 0.0479 (0.0388) Prec@1 92.000 (93.568) Prec@5 99.000 (99.892) +2022-11-14 14:34:50,981 Epoch: [220][370/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0405 (0.0389) Prec@1 93.000 (93.553) Prec@5 99.000 (99.868) +2022-11-14 14:34:51,462 Epoch: [220][380/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0512 (0.0392) Prec@1 92.000 (93.513) Prec@5 99.000 (99.846) +2022-11-14 14:34:51,933 Epoch: [220][390/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0389 (0.0392) Prec@1 93.000 (93.500) Prec@5 100.000 (99.850) +2022-11-14 14:34:52,413 Epoch: [220][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0639 (0.0398) Prec@1 92.000 (93.463) Prec@5 100.000 (99.854) +2022-11-14 14:34:52,776 Epoch: [220][410/500] Time 0.030 (0.034) Data 0.001 (0.002) Loss 0.0231 (0.0394) Prec@1 96.000 (93.524) Prec@5 100.000 (99.857) +2022-11-14 14:34:53,096 Epoch: [220][420/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0356 (0.0393) Prec@1 96.000 (93.581) Prec@5 100.000 (99.860) +2022-11-14 14:34:53,412 Epoch: [220][430/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0217 (0.0389) Prec@1 97.000 (93.659) Prec@5 100.000 (99.864) +2022-11-14 14:34:53,726 Epoch: [220][440/500] Time 0.030 (0.033) Data 0.002 (0.002) Loss 0.0465 (0.0391) Prec@1 92.000 (93.622) Prec@5 100.000 (99.867) +2022-11-14 14:34:54,035 Epoch: [220][450/500] Time 0.029 (0.033) Data 0.001 (0.002) Loss 0.0571 (0.0395) Prec@1 90.000 (93.543) Prec@5 100.000 (99.870) +2022-11-14 14:34:54,358 Epoch: [220][460/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0321 (0.0393) Prec@1 94.000 (93.553) Prec@5 100.000 (99.872) +2022-11-14 14:34:54,680 Epoch: [220][470/500] Time 0.030 (0.033) Data 0.002 (0.002) Loss 0.0426 (0.0394) Prec@1 92.000 (93.521) Prec@5 100.000 (99.875) +2022-11-14 14:34:54,985 Epoch: [220][480/500] Time 0.029 (0.033) Data 0.002 (0.002) Loss 0.0536 (0.0397) Prec@1 92.000 (93.490) Prec@5 99.000 (99.857) +2022-11-14 14:34:55,305 Epoch: [220][490/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0338 (0.0396) Prec@1 96.000 (93.540) Prec@5 100.000 (99.860) +2022-11-14 14:34:55,582 Epoch: [220][499/500] Time 0.029 (0.033) Data 0.002 (0.002) Loss 0.0439 (0.0396) Prec@1 94.000 (93.549) Prec@5 100.000 (99.863) +2022-11-14 14:34:55,866 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0601 (0.0601) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:34:55,878 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0720 (0.0660) Prec@1 89.000 (89.500) Prec@5 99.000 (99.000) +2022-11-14 14:34:55,889 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0724 (0.0682) Prec@1 89.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 14:34:55,901 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0598 (0.0661) Prec@1 88.000 (89.000) Prec@5 98.000 (99.000) +2022-11-14 14:34:55,910 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0675) Prec@1 87.000 (88.600) Prec@5 100.000 (99.200) +2022-11-14 14:34:55,919 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0291 (0.0611) Prec@1 95.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 14:34:55,927 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0626) Prec@1 89.000 (89.571) Prec@5 100.000 (99.429) +2022-11-14 14:34:55,938 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0637) Prec@1 90.000 (89.625) Prec@5 99.000 (99.375) +2022-11-14 14:34:55,946 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0662) Prec@1 85.000 (89.111) Prec@5 99.000 (99.333) +2022-11-14 14:34:55,955 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0669) Prec@1 89.000 (89.100) Prec@5 98.000 (99.200) +2022-11-14 14:34:55,966 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0658) Prec@1 89.000 (89.091) Prec@5 100.000 (99.273) +2022-11-14 14:34:55,976 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0691) Prec@1 83.000 (88.583) Prec@5 98.000 (99.167) +2022-11-14 14:34:55,986 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0685) Prec@1 90.000 (88.692) Prec@5 100.000 (99.231) +2022-11-14 14:34:55,995 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0680) Prec@1 91.000 (88.857) Prec@5 100.000 (99.286) +2022-11-14 14:34:56,004 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0687) Prec@1 89.000 (88.867) Prec@5 100.000 (99.333) +2022-11-14 14:34:56,014 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0690) Prec@1 89.000 (88.875) Prec@5 100.000 (99.375) +2022-11-14 14:34:56,023 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0676) Prec@1 92.000 (89.059) Prec@5 99.000 (99.353) +2022-11-14 14:34:56,032 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0700) Prec@1 84.000 (88.778) Prec@5 100.000 (99.389) +2022-11-14 14:34:56,041 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0703) Prec@1 85.000 (88.579) Prec@5 97.000 (99.263) +2022-11-14 14:34:56,050 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0713) Prec@1 85.000 (88.400) Prec@5 98.000 (99.200) +2022-11-14 14:34:56,059 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0726) Prec@1 84.000 (88.190) Prec@5 100.000 (99.238) +2022-11-14 14:34:56,069 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0722) Prec@1 89.000 (88.227) Prec@5 99.000 (99.227) +2022-11-14 14:34:56,078 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0736) Prec@1 86.000 (88.130) Prec@5 98.000 (99.174) +2022-11-14 14:34:56,087 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0736) Prec@1 88.000 (88.125) Prec@5 100.000 (99.208) +2022-11-14 14:34:56,096 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0743) Prec@1 88.000 (88.120) Prec@5 99.000 (99.200) +2022-11-14 14:34:56,104 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0743) Prec@1 90.000 (88.192) Prec@5 100.000 (99.231) +2022-11-14 14:34:56,112 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0734) Prec@1 92.000 (88.333) Prec@5 100.000 (99.259) +2022-11-14 14:34:56,120 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0736) Prec@1 88.000 (88.321) Prec@5 100.000 (99.286) +2022-11-14 14:34:56,128 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0748) Prec@1 83.000 (88.138) Prec@5 99.000 (99.276) +2022-11-14 14:34:56,136 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0742) Prec@1 90.000 (88.200) Prec@5 100.000 (99.300) +2022-11-14 14:34:56,146 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0739) Prec@1 88.000 (88.194) Prec@5 100.000 (99.323) +2022-11-14 14:34:56,155 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0740) Prec@1 91.000 (88.281) Prec@5 100.000 (99.344) +2022-11-14 14:34:56,164 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0740) Prec@1 87.000 (88.242) Prec@5 98.000 (99.303) +2022-11-14 14:34:56,174 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0748) Prec@1 82.000 (88.059) Prec@5 99.000 (99.294) +2022-11-14 14:34:56,183 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0750) Prec@1 88.000 (88.057) Prec@5 98.000 (99.257) +2022-11-14 14:34:56,192 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0750) Prec@1 87.000 (88.028) Prec@5 100.000 (99.278) +2022-11-14 14:34:56,202 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0751) Prec@1 86.000 (87.973) Prec@5 99.000 (99.270) +2022-11-14 14:34:56,212 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0756) Prec@1 84.000 (87.868) Prec@5 99.000 (99.263) +2022-11-14 14:34:56,221 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0752) Prec@1 91.000 (87.949) Prec@5 98.000 (99.231) +2022-11-14 14:34:56,231 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0749) Prec@1 91.000 (88.025) Prec@5 99.000 (99.225) +2022-11-14 14:34:56,240 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0752) Prec@1 87.000 (88.000) Prec@5 98.000 (99.195) +2022-11-14 14:34:56,249 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0751) Prec@1 87.000 (87.976) Prec@5 100.000 (99.214) +2022-11-14 14:34:56,259 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0745) Prec@1 91.000 (88.047) Prec@5 99.000 (99.209) +2022-11-14 14:34:56,267 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0743) Prec@1 90.000 (88.091) Prec@5 100.000 (99.227) +2022-11-14 14:34:56,278 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0740) Prec@1 91.000 (88.156) Prec@5 99.000 (99.222) +2022-11-14 14:34:56,288 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0748) Prec@1 82.000 (88.022) Prec@5 99.000 (99.217) +2022-11-14 14:34:56,297 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0749) Prec@1 88.000 (88.021) Prec@5 100.000 (99.234) +2022-11-14 14:34:56,307 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0756) Prec@1 80.000 (87.854) Prec@5 99.000 (99.229) +2022-11-14 14:34:56,316 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0754) Prec@1 90.000 (87.898) Prec@5 100.000 (99.245) +2022-11-14 14:34:56,325 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0759) Prec@1 82.000 (87.780) Prec@5 100.000 (99.260) +2022-11-14 14:34:56,335 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0760) Prec@1 86.000 (87.745) Prec@5 99.000 (99.255) +2022-11-14 14:34:56,344 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0760) Prec@1 90.000 (87.788) Prec@5 97.000 (99.212) +2022-11-14 14:34:56,353 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0756) Prec@1 90.000 (87.830) Prec@5 99.000 (99.208) +2022-11-14 14:34:56,364 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0756) Prec@1 89.000 (87.852) Prec@5 100.000 (99.222) +2022-11-14 14:34:56,375 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0756) Prec@1 86.000 (87.818) Prec@5 100.000 (99.236) +2022-11-14 14:34:56,383 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0756) Prec@1 86.000 (87.786) Prec@5 99.000 (99.232) +2022-11-14 14:34:56,391 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0754) Prec@1 87.000 (87.772) Prec@5 99.000 (99.228) +2022-11-14 14:34:56,401 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0752) Prec@1 90.000 (87.810) Prec@5 100.000 (99.241) +2022-11-14 14:34:56,411 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0755) Prec@1 83.000 (87.729) Prec@5 99.000 (99.237) +2022-11-14 14:34:56,418 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0756) Prec@1 87.000 (87.717) Prec@5 100.000 (99.250) +2022-11-14 14:34:56,426 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0755) Prec@1 85.000 (87.672) Prec@5 100.000 (99.262) +2022-11-14 14:34:56,436 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0757) Prec@1 85.000 (87.629) Prec@5 100.000 (99.274) +2022-11-14 14:34:56,445 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0756) Prec@1 90.000 (87.667) Prec@5 99.000 (99.270) +2022-11-14 14:34:56,455 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0751) Prec@1 92.000 (87.734) Prec@5 98.000 (99.250) +2022-11-14 14:34:56,465 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0756) Prec@1 82.000 (87.646) Prec@5 100.000 (99.262) +2022-11-14 14:34:56,475 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0758) Prec@1 85.000 (87.606) Prec@5 100.000 (99.273) +2022-11-14 14:34:56,484 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0755) Prec@1 91.000 (87.657) Prec@5 100.000 (99.284) +2022-11-14 14:34:56,493 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0754) Prec@1 86.000 (87.632) Prec@5 99.000 (99.279) +2022-11-14 14:34:56,503 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 86.000 (87.609) Prec@5 99.000 (99.275) +2022-11-14 14:34:56,511 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0757) Prec@1 84.000 (87.557) Prec@5 99.000 (99.271) +2022-11-14 14:34:56,521 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0756) Prec@1 88.000 (87.563) Prec@5 100.000 (99.282) +2022-11-14 14:34:56,530 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0756) Prec@1 88.000 (87.569) Prec@5 100.000 (99.292) +2022-11-14 14:34:56,540 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0755) Prec@1 88.000 (87.575) Prec@5 99.000 (99.288) +2022-11-14 14:34:56,550 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0424 (0.0750) Prec@1 94.000 (87.662) Prec@5 99.000 (99.284) +2022-11-14 14:34:56,558 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.0756) Prec@1 81.000 (87.573) Prec@5 99.000 (99.280) +2022-11-14 14:34:56,567 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0756) Prec@1 87.000 (87.566) Prec@5 99.000 (99.276) +2022-11-14 14:34:56,576 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0756) Prec@1 87.000 (87.558) Prec@5 98.000 (99.260) +2022-11-14 14:34:56,585 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0760) Prec@1 83.000 (87.500) Prec@5 98.000 (99.244) +2022-11-14 14:34:56,594 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0759) Prec@1 89.000 (87.519) Prec@5 100.000 (99.253) +2022-11-14 14:34:56,604 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0758) Prec@1 91.000 (87.562) Prec@5 100.000 (99.263) +2022-11-14 14:34:56,612 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0757) Prec@1 89.000 (87.580) Prec@5 99.000 (99.259) +2022-11-14 14:34:56,621 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0757) Prec@1 88.000 (87.585) Prec@5 99.000 (99.256) +2022-11-14 14:34:56,629 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0761) Prec@1 82.000 (87.518) Prec@5 99.000 (99.253) +2022-11-14 14:34:56,639 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0759) Prec@1 89.000 (87.536) Prec@5 99.000 (99.250) +2022-11-14 14:34:56,647 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0761) Prec@1 85.000 (87.506) Prec@5 99.000 (99.247) +2022-11-14 14:34:56,656 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0764) Prec@1 82.000 (87.442) Prec@5 100.000 (99.256) +2022-11-14 14:34:56,664 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0765) Prec@1 87.000 (87.437) Prec@5 98.000 (99.241) +2022-11-14 14:34:56,674 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0765) Prec@1 87.000 (87.432) Prec@5 98.000 (99.227) +2022-11-14 14:34:56,682 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0764) Prec@1 85.000 (87.404) Prec@5 99.000 (99.225) +2022-11-14 14:34:56,690 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0763) Prec@1 89.000 (87.422) Prec@5 100.000 (99.233) +2022-11-14 14:34:56,697 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0763) Prec@1 88.000 (87.429) Prec@5 100.000 (99.242) +2022-11-14 14:34:56,705 Test: [91/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0759) Prec@1 93.000 (87.489) Prec@5 100.000 (99.250) +2022-11-14 14:34:56,714 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0761) Prec@1 84.000 (87.452) Prec@5 99.000 (99.247) +2022-11-14 14:34:56,724 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0760) Prec@1 91.000 (87.489) Prec@5 99.000 (99.245) +2022-11-14 14:34:56,732 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0758) Prec@1 91.000 (87.526) Prec@5 100.000 (99.253) +2022-11-14 14:34:56,741 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0757) Prec@1 89.000 (87.542) Prec@5 99.000 (99.250) +2022-11-14 14:34:56,750 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0333 (0.0753) Prec@1 95.000 (87.619) Prec@5 99.000 (99.247) +2022-11-14 14:34:56,758 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0754) Prec@1 87.000 (87.612) Prec@5 97.000 (99.224) +2022-11-14 14:34:56,767 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0756) Prec@1 85.000 (87.586) Prec@5 100.000 (99.232) +2022-11-14 14:34:56,775 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0755) Prec@1 91.000 (87.620) Prec@5 100.000 (99.240) +2022-11-14 14:34:56,832 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:34:57,134 Epoch: [221][0/500] Time 0.034 (0.034) Data 0.216 (0.216) Loss 0.0323 (0.0323) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:57,342 Epoch: [221][10/500] Time 0.018 (0.020) Data 0.001 (0.021) Loss 0.0389 (0.0356) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:57,546 Epoch: [221][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0280 (0.0330) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:34:57,796 Epoch: [221][30/500] Time 0.028 (0.020) Data 0.002 (0.009) Loss 0.0172 (0.0291) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:34:58,099 Epoch: [221][40/500] Time 0.029 (0.022) Data 0.002 (0.007) Loss 0.0439 (0.0320) Prec@1 91.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 14:34:58,410 Epoch: [221][50/500] Time 0.027 (0.023) Data 0.001 (0.006) Loss 0.0308 (0.0318) Prec@1 94.000 (94.167) Prec@5 100.000 (100.000) +2022-11-14 14:34:58,715 Epoch: [221][60/500] Time 0.027 (0.023) Data 0.002 (0.005) Loss 0.0279 (0.0313) Prec@1 96.000 (94.429) Prec@5 100.000 (100.000) +2022-11-14 14:34:59,026 Epoch: [221][70/500] Time 0.028 (0.024) Data 0.002 (0.005) Loss 0.0092 (0.0285) Prec@1 100.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 14:34:59,366 Epoch: [221][80/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0286 (0.0285) Prec@1 96.000 (95.222) Prec@5 100.000 (100.000) +2022-11-14 14:34:59,714 Epoch: [221][90/500] Time 0.020 (0.026) Data 0.002 (0.004) Loss 0.0363 (0.0293) Prec@1 95.000 (95.200) Prec@5 98.000 (99.800) +2022-11-14 14:35:00,066 Epoch: [221][100/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0536 (0.0315) Prec@1 93.000 (95.000) Prec@5 99.000 (99.727) +2022-11-14 14:35:00,372 Epoch: [221][110/500] Time 0.025 (0.026) Data 0.002 (0.004) Loss 0.0475 (0.0328) Prec@1 89.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 14:35:00,682 Epoch: [221][120/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.0755 (0.0361) Prec@1 87.000 (93.923) Prec@5 100.000 (99.769) +2022-11-14 14:35:01,023 Epoch: [221][130/500] Time 0.027 (0.027) Data 0.002 (0.004) Loss 0.0316 (0.0358) Prec@1 93.000 (93.857) Prec@5 100.000 (99.786) +2022-11-14 14:35:01,361 Epoch: [221][140/500] Time 0.021 (0.027) Data 0.002 (0.003) Loss 0.0319 (0.0355) Prec@1 94.000 (93.867) Prec@5 100.000 (99.800) +2022-11-14 14:35:01,708 Epoch: [221][150/500] Time 0.025 (0.027) Data 0.002 (0.003) Loss 0.0305 (0.0352) Prec@1 96.000 (94.000) Prec@5 100.000 (99.812) +2022-11-14 14:35:02,008 Epoch: [221][160/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0189 (0.0343) Prec@1 97.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 14:35:02,388 Epoch: [221][170/500] Time 0.045 (0.028) Data 0.002 (0.003) Loss 0.0293 (0.0340) Prec@1 95.000 (94.222) Prec@5 100.000 (99.833) +2022-11-14 14:35:02,740 Epoch: [221][180/500] Time 0.019 (0.028) Data 0.002 (0.003) Loss 0.0361 (0.0341) Prec@1 94.000 (94.211) Prec@5 100.000 (99.842) +2022-11-14 14:35:03,094 Epoch: [221][190/500] Time 0.054 (0.028) Data 0.002 (0.003) Loss 0.0567 (0.0352) Prec@1 91.000 (94.050) Prec@5 100.000 (99.850) +2022-11-14 14:35:03,449 Epoch: [221][200/500] Time 0.045 (0.028) Data 0.002 (0.003) Loss 0.0622 (0.0365) Prec@1 88.000 (93.762) Prec@5 100.000 (99.857) +2022-11-14 14:35:04,033 Epoch: [221][210/500] Time 0.091 (0.029) Data 0.002 (0.003) Loss 0.0470 (0.0370) Prec@1 91.000 (93.636) Prec@5 100.000 (99.864) +2022-11-14 14:35:04,552 Epoch: [221][220/500] Time 0.079 (0.030) Data 0.002 (0.003) Loss 0.0294 (0.0367) Prec@1 97.000 (93.783) Prec@5 100.000 (99.870) +2022-11-14 14:35:05,043 Epoch: [221][230/500] Time 0.070 (0.030) Data 0.002 (0.003) Loss 0.0274 (0.0363) Prec@1 97.000 (93.917) Prec@5 100.000 (99.875) +2022-11-14 14:35:05,577 Epoch: [221][240/500] Time 0.064 (0.031) Data 0.002 (0.003) Loss 0.0290 (0.0360) Prec@1 95.000 (93.960) Prec@5 100.000 (99.880) +2022-11-14 14:35:06,181 Epoch: [221][250/500] Time 0.064 (0.032) Data 0.002 (0.003) Loss 0.0394 (0.0361) Prec@1 94.000 (93.962) Prec@5 100.000 (99.885) +2022-11-14 14:35:06,641 Epoch: [221][260/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0194 (0.0355) Prec@1 96.000 (94.037) Prec@5 100.000 (99.889) +2022-11-14 14:35:07,110 Epoch: [221][270/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0334 (0.0354) Prec@1 95.000 (94.071) Prec@5 100.000 (99.893) +2022-11-14 14:35:07,583 Epoch: [221][280/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0359 (0.0354) Prec@1 94.000 (94.069) Prec@5 100.000 (99.897) +2022-11-14 14:35:08,118 Epoch: [221][290/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0422 (0.0357) Prec@1 93.000 (94.033) Prec@5 100.000 (99.900) +2022-11-14 14:35:08,697 Epoch: [221][300/500] Time 0.086 (0.034) Data 0.002 (0.003) Loss 0.0140 (0.0350) Prec@1 100.000 (94.226) Prec@5 100.000 (99.903) +2022-11-14 14:35:09,168 Epoch: [221][310/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0347 (0.0350) Prec@1 95.000 (94.250) Prec@5 99.000 (99.875) +2022-11-14 14:35:09,741 Epoch: [221][320/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0453 (0.0353) Prec@1 93.000 (94.212) Prec@5 100.000 (99.879) +2022-11-14 14:35:10,213 Epoch: [221][330/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0409 (0.0354) Prec@1 93.000 (94.176) Prec@5 99.000 (99.853) +2022-11-14 14:35:10,711 Epoch: [221][340/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0362 (0.0355) Prec@1 95.000 (94.200) Prec@5 99.000 (99.829) +2022-11-14 14:35:11,177 Epoch: [221][350/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0406 (0.0356) Prec@1 94.000 (94.194) Prec@5 100.000 (99.833) +2022-11-14 14:35:11,644 Epoch: [221][360/500] Time 0.043 (0.036) Data 0.001 (0.003) Loss 0.0660 (0.0364) Prec@1 87.000 (94.000) Prec@5 100.000 (99.838) +2022-11-14 14:35:12,115 Epoch: [221][370/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0669 (0.0372) Prec@1 87.000 (93.816) Prec@5 100.000 (99.842) +2022-11-14 14:35:12,593 Epoch: [221][380/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0392 (0.0373) Prec@1 92.000 (93.769) Prec@5 100.000 (99.846) +2022-11-14 14:35:13,125 Epoch: [221][390/500] Time 0.070 (0.036) Data 0.003 (0.002) Loss 0.0485 (0.0376) Prec@1 92.000 (93.725) Prec@5 100.000 (99.850) +2022-11-14 14:35:13,664 Epoch: [221][400/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0267 (0.0373) Prec@1 95.000 (93.756) Prec@5 100.000 (99.854) +2022-11-14 14:35:14,201 Epoch: [221][410/500] Time 0.077 (0.037) Data 0.002 (0.002) Loss 0.0268 (0.0370) Prec@1 96.000 (93.810) Prec@5 100.000 (99.857) +2022-11-14 14:35:14,733 Epoch: [221][420/500] Time 0.063 (0.037) Data 0.002 (0.002) Loss 0.0300 (0.0369) Prec@1 95.000 (93.837) Prec@5 100.000 (99.860) +2022-11-14 14:35:15,292 Epoch: [221][430/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0378 (0.0369) Prec@1 96.000 (93.886) Prec@5 99.000 (99.841) +2022-11-14 14:35:15,838 Epoch: [221][440/500] Time 0.072 (0.038) Data 0.002 (0.002) Loss 0.0260 (0.0367) Prec@1 96.000 (93.933) Prec@5 100.000 (99.844) +2022-11-14 14:35:16,399 Epoch: [221][450/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0155 (0.0362) Prec@1 97.000 (94.000) Prec@5 100.000 (99.848) +2022-11-14 14:35:16,886 Epoch: [221][460/500] Time 0.035 (0.038) Data 0.002 (0.002) Loss 0.0287 (0.0360) Prec@1 95.000 (94.021) Prec@5 98.000 (99.809) +2022-11-14 14:35:17,364 Epoch: [221][470/500] Time 0.043 (0.038) Data 0.001 (0.002) Loss 0.0525 (0.0364) Prec@1 91.000 (93.958) Prec@5 99.000 (99.792) +2022-11-14 14:35:17,845 Epoch: [221][480/500] Time 0.058 (0.038) Data 0.002 (0.002) Loss 0.0792 (0.0373) Prec@1 84.000 (93.755) Prec@5 99.000 (99.776) +2022-11-14 14:35:18,344 Epoch: [221][490/500] Time 0.057 (0.038) Data 0.002 (0.002) Loss 0.0582 (0.0377) Prec@1 89.000 (93.660) Prec@5 98.000 (99.740) +2022-11-14 14:35:18,762 Epoch: [221][499/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0596 (0.0381) Prec@1 91.000 (93.608) Prec@5 100.000 (99.745) +2022-11-14 14:35:19,062 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0573 (0.0573) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,074 Test: [1/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0759 (0.0666) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,089 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0622 (0.0651) Prec@1 91.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,103 Test: [3/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0716 (0.0667) Prec@1 88.000 (89.250) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,113 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0701 (0.0674) Prec@1 90.000 (89.400) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,125 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0463 (0.0639) Prec@1 93.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,138 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0595 (0.0632) Prec@1 93.000 (90.429) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,150 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0642) Prec@1 88.000 (90.125) Prec@5 100.000 (100.000) +2022-11-14 14:35:19,162 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0650) Prec@1 90.000 (90.111) Prec@5 99.000 (99.889) +2022-11-14 14:35:19,174 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0658) Prec@1 88.000 (89.900) Prec@5 99.000 (99.800) +2022-11-14 14:35:19,184 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0466 (0.0641) Prec@1 92.000 (90.091) Prec@5 100.000 (99.818) +2022-11-14 14:35:19,194 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0677 (0.0644) Prec@1 90.000 (90.083) Prec@5 100.000 (99.833) +2022-11-14 14:35:19,204 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0562 (0.0637) Prec@1 90.000 (90.077) Prec@5 100.000 (99.846) +2022-11-14 14:35:19,213 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1010 (0.0664) Prec@1 82.000 (89.500) Prec@5 99.000 (99.786) +2022-11-14 14:35:19,223 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0469 (0.0651) Prec@1 92.000 (89.667) Prec@5 99.000 (99.733) +2022-11-14 14:35:19,233 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0651) Prec@1 89.000 (89.625) Prec@5 99.000 (99.688) +2022-11-14 14:35:19,243 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0647) Prec@1 90.000 (89.647) Prec@5 99.000 (99.647) +2022-11-14 14:35:19,253 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0673) Prec@1 83.000 (89.278) Prec@5 98.000 (99.556) +2022-11-14 14:35:19,264 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0675) Prec@1 87.000 (89.158) Prec@5 98.000 (99.474) +2022-11-14 14:35:19,274 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0681) Prec@1 87.000 (89.050) Prec@5 98.000 (99.400) +2022-11-14 14:35:19,284 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0690) Prec@1 87.000 (88.952) Prec@5 100.000 (99.429) +2022-11-14 14:35:19,294 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0701) Prec@1 82.000 (88.636) Prec@5 99.000 (99.409) +2022-11-14 14:35:19,304 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0714) Prec@1 86.000 (88.522) Prec@5 99.000 (99.391) +2022-11-14 14:35:19,315 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0712) Prec@1 88.000 (88.500) Prec@5 100.000 (99.417) +2022-11-14 14:35:19,325 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0721) Prec@1 85.000 (88.360) Prec@5 99.000 (99.400) +2022-11-14 14:35:19,335 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0726) Prec@1 85.000 (88.231) Prec@5 99.000 (99.385) +2022-11-14 14:35:19,345 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0721) Prec@1 88.000 (88.222) Prec@5 100.000 (99.407) +2022-11-14 14:35:19,355 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0725) Prec@1 85.000 (88.107) Prec@5 100.000 (99.429) +2022-11-14 14:35:19,366 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0718) Prec@1 92.000 (88.241) Prec@5 99.000 (99.414) +2022-11-14 14:35:19,377 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0712) Prec@1 92.000 (88.367) Prec@5 100.000 (99.433) +2022-11-14 14:35:19,388 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0709) Prec@1 89.000 (88.387) Prec@5 100.000 (99.452) +2022-11-14 14:35:19,400 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0712) Prec@1 89.000 (88.406) Prec@5 98.000 (99.406) +2022-11-14 14:35:19,412 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0711) Prec@1 88.000 (88.394) Prec@5 100.000 (99.424) +2022-11-14 14:35:19,423 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0715) Prec@1 85.000 (88.294) Prec@5 99.000 (99.412) +2022-11-14 14:35:19,434 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0719) Prec@1 87.000 (88.257) Prec@5 99.000 (99.400) +2022-11-14 14:35:19,445 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0712) Prec@1 94.000 (88.417) Prec@5 100.000 (99.417) +2022-11-14 14:35:19,457 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0713) Prec@1 90.000 (88.459) Prec@5 98.000 (99.378) +2022-11-14 14:35:19,469 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0719) Prec@1 87.000 (88.421) Prec@5 100.000 (99.395) +2022-11-14 14:35:19,481 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0717) Prec@1 90.000 (88.462) Prec@5 98.000 (99.359) +2022-11-14 14:35:19,494 Test: [39/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0718) Prec@1 87.000 (88.425) Prec@5 99.000 (99.350) +2022-11-14 14:35:19,507 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0723) Prec@1 86.000 (88.366) Prec@5 98.000 (99.317) +2022-11-14 14:35:19,520 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0726) Prec@1 87.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:35:19,535 Test: [42/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0719) Prec@1 93.000 (88.442) Prec@5 99.000 (99.326) +2022-11-14 14:35:19,549 Test: [43/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0718) Prec@1 90.000 (88.477) Prec@5 99.000 (99.318) +2022-11-14 14:35:19,562 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0720) Prec@1 87.000 (88.444) Prec@5 98.000 (99.289) +2022-11-14 14:35:19,576 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0724) Prec@1 87.000 (88.413) Prec@5 97.000 (99.239) +2022-11-14 14:35:19,590 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0722) Prec@1 91.000 (88.468) Prec@5 99.000 (99.234) +2022-11-14 14:35:19,604 Test: [47/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.0729) Prec@1 83.000 (88.354) Prec@5 98.000 (99.208) +2022-11-14 14:35:19,618 Test: [48/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0301 (0.0721) Prec@1 96.000 (88.510) Prec@5 99.000 (99.204) +2022-11-14 14:35:19,632 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.0727) Prec@1 83.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 14:35:19,645 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0724) Prec@1 88.000 (88.392) Prec@5 100.000 (99.216) +2022-11-14 14:35:19,658 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0727) Prec@1 83.000 (88.288) Prec@5 99.000 (99.212) +2022-11-14 14:35:19,671 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0727) Prec@1 87.000 (88.264) Prec@5 100.000 (99.226) +2022-11-14 14:35:19,685 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0728) Prec@1 88.000 (88.259) Prec@5 100.000 (99.241) +2022-11-14 14:35:19,699 Test: [54/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0928 (0.0731) Prec@1 85.000 (88.200) Prec@5 100.000 (99.255) +2022-11-14 14:35:19,713 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0732) Prec@1 88.000 (88.196) Prec@5 98.000 (99.232) +2022-11-14 14:35:19,724 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0734) Prec@1 87.000 (88.175) Prec@5 98.000 (99.211) +2022-11-14 14:35:19,736 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0734) Prec@1 88.000 (88.172) Prec@5 99.000 (99.207) +2022-11-14 14:35:19,746 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0736) Prec@1 84.000 (88.102) Prec@5 100.000 (99.220) +2022-11-14 14:35:19,758 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0738) Prec@1 86.000 (88.067) Prec@5 100.000 (99.233) +2022-11-14 14:35:19,771 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0740) Prec@1 88.000 (88.066) Prec@5 100.000 (99.246) +2022-11-14 14:35:19,783 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0738) Prec@1 89.000 (88.081) Prec@5 99.000 (99.242) +2022-11-14 14:35:19,796 Test: [62/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0526 (0.0735) Prec@1 88.000 (88.079) Prec@5 100.000 (99.254) +2022-11-14 14:35:19,809 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0306 (0.0728) Prec@1 97.000 (88.219) Prec@5 100.000 (99.266) +2022-11-14 14:35:19,822 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.0733) Prec@1 84.000 (88.154) Prec@5 100.000 (99.277) +2022-11-14 14:35:19,834 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0735) Prec@1 87.000 (88.136) Prec@5 100.000 (99.288) +2022-11-14 14:35:19,846 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0732) Prec@1 91.000 (88.179) Prec@5 99.000 (99.284) +2022-11-14 14:35:19,859 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0734) Prec@1 84.000 (88.118) Prec@5 99.000 (99.279) +2022-11-14 14:35:19,873 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0733) Prec@1 92.000 (88.174) Prec@5 99.000 (99.275) +2022-11-14 14:35:19,887 Test: [69/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0777 (0.0733) Prec@1 89.000 (88.186) Prec@5 100.000 (99.286) +2022-11-14 14:35:19,901 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0935 (0.0736) Prec@1 86.000 (88.155) Prec@5 100.000 (99.296) +2022-11-14 14:35:19,915 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0521 (0.0733) Prec@1 92.000 (88.208) Prec@5 98.000 (99.278) +2022-11-14 14:35:19,928 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0481 (0.0730) Prec@1 95.000 (88.301) Prec@5 100.000 (99.288) +2022-11-14 14:35:19,941 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0726) Prec@1 94.000 (88.378) Prec@5 100.000 (99.297) +2022-11-14 14:35:19,954 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0869 (0.0727) Prec@1 84.000 (88.320) Prec@5 99.000 (99.293) +2022-11-14 14:35:19,969 Test: [75/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.0731) Prec@1 84.000 (88.263) Prec@5 99.000 (99.289) +2022-11-14 14:35:19,984 Test: [76/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0730) Prec@1 87.000 (88.247) Prec@5 99.000 (99.286) +2022-11-14 14:35:19,997 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0732) Prec@1 87.000 (88.231) Prec@5 98.000 (99.269) +2022-11-14 14:35:20,011 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0732) Prec@1 89.000 (88.241) Prec@5 100.000 (99.278) +2022-11-14 14:35:20,026 Test: [79/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0733) Prec@1 88.000 (88.237) Prec@5 100.000 (99.287) +2022-11-14 14:35:20,039 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0733) Prec@1 88.000 (88.235) Prec@5 99.000 (99.284) +2022-11-14 14:35:20,053 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0885 (0.0735) Prec@1 87.000 (88.220) Prec@5 100.000 (99.293) +2022-11-14 14:35:20,066 Test: [82/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0735) Prec@1 88.000 (88.217) Prec@5 100.000 (99.301) +2022-11-14 14:35:20,079 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0646 (0.0734) Prec@1 89.000 (88.226) Prec@5 100.000 (99.310) +2022-11-14 14:35:20,092 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0734) Prec@1 85.000 (88.188) Prec@5 100.000 (99.318) +2022-11-14 14:35:20,105 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.0736) Prec@1 87.000 (88.174) Prec@5 99.000 (99.314) +2022-11-14 14:35:20,118 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0737) Prec@1 88.000 (88.172) Prec@5 100.000 (99.322) +2022-11-14 14:35:20,131 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0736) Prec@1 91.000 (88.205) Prec@5 99.000 (99.318) +2022-11-14 14:35:20,143 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0738) Prec@1 86.000 (88.180) Prec@5 100.000 (99.326) +2022-11-14 14:35:20,156 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0739) Prec@1 88.000 (88.178) Prec@5 99.000 (99.322) +2022-11-14 14:35:20,167 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0737) Prec@1 92.000 (88.220) Prec@5 100.000 (99.330) +2022-11-14 14:35:20,182 Test: [91/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0736) Prec@1 90.000 (88.239) Prec@5 99.000 (99.326) +2022-11-14 14:35:20,195 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0735) Prec@1 87.000 (88.226) Prec@5 100.000 (99.333) +2022-11-14 14:35:20,205 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0734) Prec@1 90.000 (88.245) Prec@5 99.000 (99.330) +2022-11-14 14:35:20,217 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0734) Prec@1 88.000 (88.242) Prec@5 99.000 (99.326) +2022-11-14 14:35:20,227 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0636 (0.0733) Prec@1 89.000 (88.250) Prec@5 100.000 (99.333) +2022-11-14 14:35:20,238 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0446 (0.0730) Prec@1 92.000 (88.289) Prec@5 99.000 (99.330) +2022-11-14 14:35:20,249 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0730) Prec@1 86.000 (88.265) Prec@5 97.000 (99.306) +2022-11-14 14:35:20,260 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0733) Prec@1 86.000 (88.242) Prec@5 100.000 (99.313) +2022-11-14 14:35:20,270 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0733) Prec@1 87.000 (88.230) Prec@5 99.000 (99.310) +2022-11-14 14:35:20,349 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:35:20,734 Epoch: [222][0/500] Time 0.035 (0.035) Data 0.277 (0.277) Loss 0.0302 (0.0302) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:21,053 Epoch: [222][10/500] Time 0.036 (0.029) Data 0.003 (0.028) Loss 0.0532 (0.0417) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:21,415 Epoch: [222][20/500] Time 0.028 (0.031) Data 0.002 (0.016) Loss 0.0660 (0.0498) Prec@1 91.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 14:35:21,701 Epoch: [222][30/500] Time 0.020 (0.029) Data 0.002 (0.012) Loss 0.0100 (0.0399) Prec@1 99.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:21,955 Epoch: [222][40/500] Time 0.023 (0.028) Data 0.002 (0.009) Loss 0.0396 (0.0398) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:22,317 Epoch: [222][50/500] Time 0.040 (0.028) Data 0.002 (0.008) Loss 0.0253 (0.0374) Prec@1 95.000 (94.167) Prec@5 100.000 (100.000) +2022-11-14 14:35:22,800 Epoch: [222][60/500] Time 0.039 (0.031) Data 0.002 (0.007) Loss 0.0210 (0.0350) Prec@1 96.000 (94.429) Prec@5 100.000 (100.000) +2022-11-14 14:35:23,256 Epoch: [222][70/500] Time 0.033 (0.032) Data 0.002 (0.006) Loss 0.0347 (0.0350) Prec@1 92.000 (94.125) Prec@5 99.000 (99.875) +2022-11-14 14:35:23,739 Epoch: [222][80/500] Time 0.047 (0.034) Data 0.002 (0.006) Loss 0.0483 (0.0365) Prec@1 93.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 14:35:24,255 Epoch: [222][90/500] Time 0.047 (0.035) Data 0.002 (0.005) Loss 0.0468 (0.0375) Prec@1 91.000 (93.700) Prec@5 100.000 (99.900) +2022-11-14 14:35:24,776 Epoch: [222][100/500] Time 0.063 (0.036) Data 0.003 (0.005) Loss 0.0411 (0.0378) Prec@1 92.000 (93.545) Prec@5 100.000 (99.909) +2022-11-14 14:35:25,288 Epoch: [222][110/500] Time 0.055 (0.037) Data 0.003 (0.005) Loss 0.0273 (0.0370) Prec@1 95.000 (93.667) Prec@5 100.000 (99.917) +2022-11-14 14:35:25,759 Epoch: [222][120/500] Time 0.036 (0.038) Data 0.002 (0.005) Loss 0.0373 (0.0370) Prec@1 94.000 (93.692) Prec@5 100.000 (99.923) +2022-11-14 14:35:26,201 Epoch: [222][130/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0174 (0.0356) Prec@1 97.000 (93.929) Prec@5 100.000 (99.929) +2022-11-14 14:35:26,655 Epoch: [222][140/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0415 (0.0360) Prec@1 93.000 (93.867) Prec@5 99.000 (99.867) +2022-11-14 14:35:27,120 Epoch: [222][150/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0348 (0.0359) Prec@1 94.000 (93.875) Prec@5 100.000 (99.875) +2022-11-14 14:35:27,582 Epoch: [222][160/500] Time 0.061 (0.038) Data 0.002 (0.004) Loss 0.0318 (0.0357) Prec@1 95.000 (93.941) Prec@5 100.000 (99.882) +2022-11-14 14:35:28,028 Epoch: [222][170/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0308 (0.0354) Prec@1 94.000 (93.944) Prec@5 100.000 (99.889) +2022-11-14 14:35:28,473 Epoch: [222][180/500] Time 0.042 (0.038) Data 0.002 (0.004) Loss 0.0429 (0.0358) Prec@1 91.000 (93.789) Prec@5 100.000 (99.895) +2022-11-14 14:35:28,932 Epoch: [222][190/500] Time 0.042 (0.039) Data 0.002 (0.004) Loss 0.0311 (0.0356) Prec@1 94.000 (93.800) Prec@5 100.000 (99.900) +2022-11-14 14:35:29,384 Epoch: [222][200/500] Time 0.039 (0.039) Data 0.002 (0.004) Loss 0.0356 (0.0356) Prec@1 94.000 (93.810) Prec@5 100.000 (99.905) +2022-11-14 14:35:29,839 Epoch: [222][210/500] Time 0.052 (0.039) Data 0.002 (0.004) Loss 0.0438 (0.0359) Prec@1 91.000 (93.682) Prec@5 100.000 (99.909) +2022-11-14 14:35:30,287 Epoch: [222][220/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0386 (0.0361) Prec@1 92.000 (93.609) Prec@5 100.000 (99.913) +2022-11-14 14:35:30,737 Epoch: [222][230/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0342 (0.0360) Prec@1 94.000 (93.625) Prec@5 100.000 (99.917) +2022-11-14 14:35:31,191 Epoch: [222][240/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0343 (0.0359) Prec@1 96.000 (93.720) Prec@5 100.000 (99.920) +2022-11-14 14:35:31,631 Epoch: [222][250/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0231 (0.0354) Prec@1 96.000 (93.808) Prec@5 100.000 (99.923) +2022-11-14 14:35:32,093 Epoch: [222][260/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0501 (0.0360) Prec@1 93.000 (93.778) Prec@5 100.000 (99.926) +2022-11-14 14:35:32,532 Epoch: [222][270/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0327 (0.0358) Prec@1 96.000 (93.857) Prec@5 99.000 (99.893) +2022-11-14 14:35:33,009 Epoch: [222][280/500] Time 0.043 (0.039) Data 0.001 (0.003) Loss 0.0553 (0.0365) Prec@1 90.000 (93.724) Prec@5 100.000 (99.897) +2022-11-14 14:35:33,456 Epoch: [222][290/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0313 (0.0363) Prec@1 95.000 (93.767) Prec@5 100.000 (99.900) +2022-11-14 14:35:33,914 Epoch: [222][300/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0503 (0.0368) Prec@1 90.000 (93.645) Prec@5 100.000 (99.903) +2022-11-14 14:35:34,369 Epoch: [222][310/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0620 (0.0376) Prec@1 88.000 (93.469) Prec@5 99.000 (99.875) +2022-11-14 14:35:34,823 Epoch: [222][320/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0370 (0.0376) Prec@1 93.000 (93.455) Prec@5 99.000 (99.848) +2022-11-14 14:35:35,276 Epoch: [222][330/500] Time 0.043 (0.039) Data 0.001 (0.003) Loss 0.0356 (0.0375) Prec@1 96.000 (93.529) Prec@5 100.000 (99.853) +2022-11-14 14:35:35,717 Epoch: [222][340/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0397 (0.0376) Prec@1 94.000 (93.543) Prec@5 98.000 (99.800) +2022-11-14 14:35:36,180 Epoch: [222][350/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0353 (0.0375) Prec@1 94.000 (93.556) Prec@5 100.000 (99.806) +2022-11-14 14:35:36,625 Epoch: [222][360/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0840 (0.0388) Prec@1 89.000 (93.432) Prec@5 99.000 (99.784) +2022-11-14 14:35:37,105 Epoch: [222][370/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0327 (0.0386) Prec@1 95.000 (93.474) Prec@5 100.000 (99.789) +2022-11-14 14:35:37,569 Epoch: [222][380/500] Time 0.032 (0.040) Data 0.003 (0.003) Loss 0.0405 (0.0386) Prec@1 94.000 (93.487) Prec@5 100.000 (99.795) +2022-11-14 14:35:38,105 Epoch: [222][390/500] Time 0.060 (0.040) Data 0.002 (0.003) Loss 0.0334 (0.0385) Prec@1 94.000 (93.500) Prec@5 100.000 (99.800) +2022-11-14 14:35:38,532 Epoch: [222][400/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0574 (0.0390) Prec@1 91.000 (93.439) Prec@5 100.000 (99.805) +2022-11-14 14:35:39,035 Epoch: [222][410/500] Time 0.067 (0.040) Data 0.002 (0.003) Loss 0.0358 (0.0389) Prec@1 95.000 (93.476) Prec@5 100.000 (99.810) +2022-11-14 14:35:39,556 Epoch: [222][420/500] Time 0.067 (0.040) Data 0.002 (0.003) Loss 0.0429 (0.0390) Prec@1 94.000 (93.488) Prec@5 100.000 (99.814) +2022-11-14 14:35:40,039 Epoch: [222][430/500] Time 0.070 (0.040) Data 0.002 (0.003) Loss 0.0366 (0.0389) Prec@1 94.000 (93.500) Prec@5 100.000 (99.818) +2022-11-14 14:35:40,506 Epoch: [222][440/500] Time 0.039 (0.040) Data 0.001 (0.003) Loss 0.0377 (0.0389) Prec@1 94.000 (93.511) Prec@5 99.000 (99.800) +2022-11-14 14:35:40,955 Epoch: [222][450/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.0361 (0.0389) Prec@1 93.000 (93.500) Prec@5 100.000 (99.804) +2022-11-14 14:35:41,391 Epoch: [222][460/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0242 (0.0385) Prec@1 95.000 (93.532) Prec@5 100.000 (99.809) +2022-11-14 14:35:41,908 Epoch: [222][470/500] Time 0.056 (0.040) Data 0.002 (0.003) Loss 0.0486 (0.0388) Prec@1 94.000 (93.542) Prec@5 98.000 (99.771) +2022-11-14 14:35:42,352 Epoch: [222][480/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0554 (0.0391) Prec@1 90.000 (93.469) Prec@5 100.000 (99.776) +2022-11-14 14:35:42,810 Epoch: [222][490/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0495 (0.0393) Prec@1 89.000 (93.380) Prec@5 100.000 (99.780) +2022-11-14 14:35:43,213 Epoch: [222][499/500] Time 0.040 (0.040) Data 0.001 (0.003) Loss 0.0342 (0.0392) Prec@1 94.000 (93.392) Prec@5 100.000 (99.784) +2022-11-14 14:35:43,565 Test: [0/100] Model Time 0.018 (0.018) Loss Time 0.000 (0.000) Loss 0.0672 (0.0672) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:43,580 Test: [1/100] Model Time 0.011 (0.014) Loss Time 0.000 (0.000) Loss 0.0859 (0.0766) Prec@1 86.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:35:43,593 Test: [2/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.0803 (0.0778) Prec@1 85.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:35:43,611 Test: [3/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.1021 (0.0839) Prec@1 83.000 (85.750) Prec@5 98.000 (99.500) +2022-11-14 14:35:43,622 Test: [4/100] Model Time 0.007 (0.012) Loss Time 0.000 (0.000) Loss 0.0818 (0.0835) Prec@1 85.000 (85.600) Prec@5 100.000 (99.600) +2022-11-14 14:35:43,633 Test: [5/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0258 (0.0738) Prec@1 95.000 (87.167) Prec@5 100.000 (99.667) +2022-11-14 14:35:43,644 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0655 (0.0726) Prec@1 90.000 (87.571) Prec@5 100.000 (99.714) +2022-11-14 14:35:43,657 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1012 (0.0762) Prec@1 83.000 (87.000) Prec@5 100.000 (99.750) +2022-11-14 14:35:43,670 Test: [8/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0902 (0.0778) Prec@1 85.000 (86.778) Prec@5 100.000 (99.778) +2022-11-14 14:35:43,681 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0688 (0.0769) Prec@1 90.000 (87.100) Prec@5 99.000 (99.700) +2022-11-14 14:35:43,694 Test: [10/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0558 (0.0750) Prec@1 91.000 (87.455) Prec@5 100.000 (99.727) +2022-11-14 14:35:43,706 Test: [11/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0904 (0.0762) Prec@1 84.000 (87.167) Prec@5 100.000 (99.750) +2022-11-14 14:35:43,720 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0547 (0.0746) Prec@1 90.000 (87.385) Prec@5 100.000 (99.769) +2022-11-14 14:35:43,732 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0707 (0.0743) Prec@1 88.000 (87.429) Prec@5 99.000 (99.714) +2022-11-14 14:35:43,746 Test: [14/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0868 (0.0751) Prec@1 89.000 (87.533) Prec@5 99.000 (99.667) +2022-11-14 14:35:43,758 Test: [15/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0832 (0.0757) Prec@1 88.000 (87.562) Prec@5 100.000 (99.688) +2022-11-14 14:35:43,769 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0460 (0.0739) Prec@1 94.000 (87.941) Prec@5 98.000 (99.588) +2022-11-14 14:35:43,781 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0754) Prec@1 84.000 (87.722) Prec@5 99.000 (99.556) +2022-11-14 14:35:43,795 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0759) Prec@1 86.000 (87.632) Prec@5 99.000 (99.526) +2022-11-14 14:35:43,809 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0927 (0.0767) Prec@1 86.000 (87.550) Prec@5 98.000 (99.450) +2022-11-14 14:35:43,823 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0769) Prec@1 86.000 (87.476) Prec@5 98.000 (99.381) +2022-11-14 14:35:43,835 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0768) Prec@1 84.000 (87.318) Prec@5 100.000 (99.409) +2022-11-14 14:35:43,845 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1091 (0.0782) Prec@1 82.000 (87.087) Prec@5 98.000 (99.348) +2022-11-14 14:35:43,858 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0782) Prec@1 88.000 (87.125) Prec@5 100.000 (99.375) +2022-11-14 14:35:43,871 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0785) Prec@1 85.000 (87.040) Prec@5 99.000 (99.360) +2022-11-14 14:35:43,884 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0785) Prec@1 86.000 (87.000) Prec@5 99.000 (99.346) +2022-11-14 14:35:43,896 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0782) Prec@1 89.000 (87.074) Prec@5 100.000 (99.370) +2022-11-14 14:35:43,906 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0783) Prec@1 85.000 (87.000) Prec@5 98.000 (99.321) +2022-11-14 14:35:43,919 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0777) Prec@1 90.000 (87.103) Prec@5 97.000 (99.241) +2022-11-14 14:35:43,929 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0774) Prec@1 89.000 (87.167) Prec@5 100.000 (99.267) +2022-11-14 14:35:43,939 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0899 (0.0778) Prec@1 85.000 (87.097) Prec@5 100.000 (99.290) +2022-11-14 14:35:43,948 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0777) Prec@1 88.000 (87.125) Prec@5 100.000 (99.312) +2022-11-14 14:35:43,959 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0775) Prec@1 86.000 (87.091) Prec@5 100.000 (99.333) +2022-11-14 14:35:43,968 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0777) Prec@1 87.000 (87.088) Prec@5 100.000 (99.353) +2022-11-14 14:35:43,978 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0775) Prec@1 90.000 (87.171) Prec@5 99.000 (99.343) +2022-11-14 14:35:43,987 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0581 (0.0769) Prec@1 90.000 (87.250) Prec@5 100.000 (99.361) +2022-11-14 14:35:43,996 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0770) Prec@1 88.000 (87.270) Prec@5 98.000 (99.324) +2022-11-14 14:35:44,006 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0771) Prec@1 86.000 (87.237) Prec@5 100.000 (99.342) +2022-11-14 14:35:44,018 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0768) Prec@1 91.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 14:35:44,030 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0588 (0.0763) Prec@1 90.000 (87.400) Prec@5 99.000 (99.325) +2022-11-14 14:35:44,041 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0761) Prec@1 91.000 (87.488) Prec@5 97.000 (99.268) +2022-11-14 14:35:44,052 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0762) Prec@1 87.000 (87.476) Prec@5 99.000 (99.262) +2022-11-14 14:35:44,063 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0756) Prec@1 92.000 (87.581) Prec@5 99.000 (99.256) +2022-11-14 14:35:44,072 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0756) Prec@1 88.000 (87.591) Prec@5 98.000 (99.227) +2022-11-14 14:35:44,084 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0755) Prec@1 90.000 (87.644) Prec@5 100.000 (99.244) +2022-11-14 14:35:44,096 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0757) Prec@1 85.000 (87.587) Prec@5 98.000 (99.217) +2022-11-14 14:35:44,107 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0760) Prec@1 86.000 (87.553) Prec@5 100.000 (99.234) +2022-11-14 14:35:44,118 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0765) Prec@1 82.000 (87.438) Prec@5 99.000 (99.229) +2022-11-14 14:35:44,128 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0761) Prec@1 90.000 (87.490) Prec@5 99.000 (99.224) +2022-11-14 14:35:44,137 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0765) Prec@1 87.000 (87.480) Prec@5 100.000 (99.240) +2022-11-14 14:35:44,147 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0760) Prec@1 90.000 (87.529) Prec@5 100.000 (99.255) +2022-11-14 14:35:44,157 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0758) Prec@1 87.000 (87.519) Prec@5 100.000 (99.269) +2022-11-14 14:35:44,168 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0755) Prec@1 90.000 (87.566) Prec@5 99.000 (99.264) +2022-11-14 14:35:44,177 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0752) Prec@1 92.000 (87.648) Prec@5 100.000 (99.278) +2022-11-14 14:35:44,187 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0755) Prec@1 88.000 (87.655) Prec@5 100.000 (99.291) +2022-11-14 14:35:44,197 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0754) Prec@1 87.000 (87.643) Prec@5 100.000 (99.304) +2022-11-14 14:35:44,207 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0754) Prec@1 88.000 (87.649) Prec@5 98.000 (99.281) +2022-11-14 14:35:44,216 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0754) Prec@1 87.000 (87.638) Prec@5 98.000 (99.259) +2022-11-14 14:35:44,225 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0760) Prec@1 80.000 (87.508) Prec@5 100.000 (99.271) +2022-11-14 14:35:44,235 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0761) Prec@1 85.000 (87.467) Prec@5 100.000 (99.283) +2022-11-14 14:35:44,244 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0761) Prec@1 88.000 (87.475) Prec@5 98.000 (99.262) +2022-11-14 14:35:44,253 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0760) Prec@1 89.000 (87.500) Prec@5 99.000 (99.258) +2022-11-14 14:35:44,263 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0758) Prec@1 90.000 (87.540) Prec@5 100.000 (99.270) +2022-11-14 14:35:44,272 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0370 (0.0752) Prec@1 95.000 (87.656) Prec@5 99.000 (99.266) +2022-11-14 14:35:44,281 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.0757) Prec@1 83.000 (87.585) Prec@5 100.000 (99.277) +2022-11-14 14:35:44,292 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0755) Prec@1 89.000 (87.606) Prec@5 98.000 (99.258) +2022-11-14 14:35:44,302 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0755) Prec@1 87.000 (87.597) Prec@5 99.000 (99.254) +2022-11-14 14:35:44,312 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0755) Prec@1 91.000 (87.647) Prec@5 100.000 (99.265) +2022-11-14 14:35:44,321 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0755) Prec@1 86.000 (87.623) Prec@5 100.000 (99.275) +2022-11-14 14:35:44,331 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0756) Prec@1 86.000 (87.600) Prec@5 99.000 (99.271) +2022-11-14 14:35:44,341 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.0761) Prec@1 84.000 (87.549) Prec@5 100.000 (99.282) +2022-11-14 14:35:44,351 Test: [71/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0758) Prec@1 92.000 (87.611) Prec@5 100.000 (99.292) +2022-11-14 14:35:44,361 Test: [72/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0756) Prec@1 91.000 (87.658) Prec@5 100.000 (99.301) +2022-11-14 14:35:44,370 Test: [73/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0752) Prec@1 92.000 (87.716) Prec@5 100.000 (99.311) +2022-11-14 14:35:44,378 Test: [74/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1187 (0.0758) Prec@1 82.000 (87.640) Prec@5 100.000 (99.320) +2022-11-14 14:35:44,387 Test: [75/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0758) Prec@1 89.000 (87.658) Prec@5 99.000 (99.316) +2022-11-14 14:35:44,395 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0757) Prec@1 87.000 (87.649) Prec@5 98.000 (99.299) +2022-11-14 14:35:44,404 Test: [77/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0758) Prec@1 85.000 (87.615) Prec@5 98.000 (99.282) +2022-11-14 14:35:44,413 Test: [78/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0757) Prec@1 91.000 (87.658) Prec@5 100.000 (99.291) +2022-11-14 14:35:44,423 Test: [79/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0756) Prec@1 89.000 (87.675) Prec@5 100.000 (99.300) +2022-11-14 14:35:44,432 Test: [80/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0757) Prec@1 88.000 (87.679) Prec@5 100.000 (99.309) +2022-11-14 14:35:44,442 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0756) Prec@1 90.000 (87.707) Prec@5 100.000 (99.317) +2022-11-14 14:35:44,452 Test: [82/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0756) Prec@1 86.000 (87.687) Prec@5 100.000 (99.325) +2022-11-14 14:35:44,462 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0756) Prec@1 86.000 (87.667) Prec@5 99.000 (99.321) +2022-11-14 14:35:44,473 Test: [84/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0755) Prec@1 90.000 (87.694) Prec@5 100.000 (99.329) +2022-11-14 14:35:44,483 Test: [85/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0755) Prec@1 87.000 (87.686) Prec@5 98.000 (99.314) +2022-11-14 14:35:44,494 Test: [86/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0755) Prec@1 90.000 (87.713) Prec@5 100.000 (99.322) +2022-11-14 14:35:44,503 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0756) Prec@1 88.000 (87.716) Prec@5 99.000 (99.318) +2022-11-14 14:35:44,514 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0756) Prec@1 88.000 (87.719) Prec@5 100.000 (99.326) +2022-11-14 14:35:44,522 Test: [89/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0755) Prec@1 91.000 (87.756) Prec@5 100.000 (99.333) +2022-11-14 14:35:44,532 Test: [90/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0753) Prec@1 91.000 (87.791) Prec@5 100.000 (99.341) +2022-11-14 14:35:44,543 Test: [91/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0750) Prec@1 92.000 (87.837) Prec@5 100.000 (99.348) +2022-11-14 14:35:44,553 Test: [92/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0751) Prec@1 86.000 (87.817) Prec@5 100.000 (99.355) +2022-11-14 14:35:44,563 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0750) Prec@1 87.000 (87.809) Prec@5 100.000 (99.362) +2022-11-14 14:35:44,573 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0750) Prec@1 89.000 (87.821) Prec@5 99.000 (99.358) +2022-11-14 14:35:44,583 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0748) Prec@1 90.000 (87.844) Prec@5 100.000 (99.365) +2022-11-14 14:35:44,591 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0745) Prec@1 92.000 (87.887) Prec@5 99.000 (99.361) +2022-11-14 14:35:44,601 Test: [97/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0748) Prec@1 81.000 (87.816) Prec@5 99.000 (99.357) +2022-11-14 14:35:44,611 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0749) Prec@1 88.000 (87.818) Prec@5 99.000 (99.354) +2022-11-14 14:35:44,620 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0748) Prec@1 89.000 (87.830) Prec@5 99.000 (99.350) +2022-11-14 14:35:44,694 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:35:45,007 Epoch: [223][0/500] Time 0.028 (0.028) Data 0.225 (0.225) Loss 0.0274 (0.0274) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:35:45,215 Epoch: [223][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0476 (0.0375) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:35:45,434 Epoch: [223][20/500] Time 0.025 (0.019) Data 0.002 (0.012) Loss 0.0342 (0.0364) Prec@1 94.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:35:45,703 Epoch: [223][30/500] Time 0.027 (0.021) Data 0.002 (0.009) Loss 0.0381 (0.0368) Prec@1 94.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:35:46,122 Epoch: [223][40/500] Time 0.035 (0.025) Data 0.002 (0.007) Loss 0.0481 (0.0391) Prec@1 92.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:35:46,504 Epoch: [223][50/500] Time 0.037 (0.027) Data 0.002 (0.006) Loss 0.0477 (0.0405) Prec@1 92.000 (93.500) Prec@5 99.000 (99.667) +2022-11-14 14:35:46,851 Epoch: [223][60/500] Time 0.030 (0.027) Data 0.002 (0.006) Loss 0.0620 (0.0436) Prec@1 87.000 (92.571) Prec@5 100.000 (99.714) +2022-11-14 14:35:47,208 Epoch: [223][70/500] Time 0.033 (0.028) Data 0.002 (0.005) Loss 0.0427 (0.0435) Prec@1 92.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:35:47,562 Epoch: [223][80/500] Time 0.033 (0.028) Data 0.002 (0.005) Loss 0.0562 (0.0449) Prec@1 90.000 (92.222) Prec@5 99.000 (99.667) +2022-11-14 14:35:47,909 Epoch: [223][90/500] Time 0.031 (0.029) Data 0.002 (0.004) Loss 0.0608 (0.0465) Prec@1 92.000 (92.200) Prec@5 99.000 (99.600) +2022-11-14 14:35:48,300 Epoch: [223][100/500] Time 0.050 (0.029) Data 0.002 (0.004) Loss 0.0338 (0.0453) Prec@1 97.000 (92.636) Prec@5 100.000 (99.636) +2022-11-14 14:35:48,671 Epoch: [223][110/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0398 (0.0449) Prec@1 96.000 (92.917) Prec@5 100.000 (99.667) +2022-11-14 14:35:49,081 Epoch: [223][120/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0485 (0.0451) Prec@1 91.000 (92.769) Prec@5 98.000 (99.538) +2022-11-14 14:35:49,434 Epoch: [223][130/500] Time 0.034 (0.030) Data 0.002 (0.004) Loss 0.0625 (0.0464) Prec@1 89.000 (92.500) Prec@5 100.000 (99.571) +2022-11-14 14:35:49,862 Epoch: [223][140/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0479 (0.0465) Prec@1 94.000 (92.600) Prec@5 100.000 (99.600) +2022-11-14 14:35:50,231 Epoch: [223][150/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0406 (0.0461) Prec@1 93.000 (92.625) Prec@5 99.000 (99.562) +2022-11-14 14:35:50,623 Epoch: [223][160/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0210 (0.0446) Prec@1 97.000 (92.882) Prec@5 100.000 (99.588) +2022-11-14 14:35:51,013 Epoch: [223][170/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0427 (0.0445) Prec@1 91.000 (92.778) Prec@5 100.000 (99.611) +2022-11-14 14:35:51,361 Epoch: [223][180/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0369 (0.0441) Prec@1 93.000 (92.789) Prec@5 100.000 (99.632) +2022-11-14 14:35:51,734 Epoch: [223][190/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0587 (0.0449) Prec@1 91.000 (92.700) Prec@5 100.000 (99.650) +2022-11-14 14:35:52,102 Epoch: [223][200/500] Time 0.035 (0.031) Data 0.003 (0.003) Loss 0.0548 (0.0453) Prec@1 90.000 (92.571) Prec@5 99.000 (99.619) +2022-11-14 14:35:52,461 Epoch: [223][210/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0296 (0.0446) Prec@1 96.000 (92.727) Prec@5 100.000 (99.636) +2022-11-14 14:35:52,873 Epoch: [223][220/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0306 (0.0440) Prec@1 95.000 (92.826) Prec@5 100.000 (99.652) +2022-11-14 14:35:53,232 Epoch: [223][230/500] Time 0.035 (0.032) Data 0.001 (0.003) Loss 0.0577 (0.0446) Prec@1 90.000 (92.708) Prec@5 100.000 (99.667) +2022-11-14 14:35:53,661 Epoch: [223][240/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0766 (0.0459) Prec@1 87.000 (92.480) Prec@5 100.000 (99.680) +2022-11-14 14:35:54,005 Epoch: [223][250/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0377 (0.0455) Prec@1 94.000 (92.538) Prec@5 100.000 (99.692) +2022-11-14 14:35:54,364 Epoch: [223][260/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0405 (0.0454) Prec@1 92.000 (92.519) Prec@5 100.000 (99.704) +2022-11-14 14:35:54,728 Epoch: [223][270/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0464 (0.0454) Prec@1 91.000 (92.464) Prec@5 98.000 (99.643) +2022-11-14 14:35:55,139 Epoch: [223][280/500] Time 0.030 (0.032) Data 0.002 (0.003) Loss 0.0606 (0.0459) Prec@1 89.000 (92.345) Prec@5 100.000 (99.655) +2022-11-14 14:35:55,562 Epoch: [223][290/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0484 (0.0460) Prec@1 92.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:35:55,957 Epoch: [223][300/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0413 (0.0459) Prec@1 94.000 (92.387) Prec@5 100.000 (99.677) +2022-11-14 14:35:56,355 Epoch: [223][310/500] Time 0.025 (0.033) Data 0.002 (0.003) Loss 0.0305 (0.0454) Prec@1 94.000 (92.438) Prec@5 99.000 (99.656) +2022-11-14 14:35:56,712 Epoch: [223][320/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.0651 (0.0460) Prec@1 87.000 (92.273) Prec@5 100.000 (99.667) +2022-11-14 14:35:57,172 Epoch: [223][330/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0333 (0.0456) Prec@1 94.000 (92.324) Prec@5 100.000 (99.676) +2022-11-14 14:35:57,624 Epoch: [223][340/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0252 (0.0450) Prec@1 95.000 (92.400) Prec@5 100.000 (99.686) +2022-11-14 14:35:58,039 Epoch: [223][350/500] Time 0.023 (0.033) Data 0.002 (0.003) Loss 0.0483 (0.0451) Prec@1 92.000 (92.389) Prec@5 100.000 (99.694) +2022-11-14 14:35:58,524 Epoch: [223][360/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0321 (0.0448) Prec@1 95.000 (92.459) Prec@5 100.000 (99.703) +2022-11-14 14:35:59,011 Epoch: [223][370/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0511 (0.0449) Prec@1 90.000 (92.395) Prec@5 100.000 (99.711) +2022-11-14 14:35:59,488 Epoch: [223][380/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0415 (0.0448) Prec@1 93.000 (92.410) Prec@5 100.000 (99.718) +2022-11-14 14:35:59,978 Epoch: [223][390/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0489 (0.0449) Prec@1 92.000 (92.400) Prec@5 100.000 (99.725) +2022-11-14 14:36:00,464 Epoch: [223][400/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0174 (0.0443) Prec@1 97.000 (92.512) Prec@5 100.000 (99.732) +2022-11-14 14:36:00,952 Epoch: [223][410/500] Time 0.046 (0.035) Data 0.002 (0.002) Loss 0.0317 (0.0440) Prec@1 94.000 (92.548) Prec@5 100.000 (99.738) +2022-11-14 14:36:01,454 Epoch: [223][420/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0328 (0.0437) Prec@1 96.000 (92.628) Prec@5 100.000 (99.744) +2022-11-14 14:36:01,953 Epoch: [223][430/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0456 (0.0437) Prec@1 91.000 (92.591) Prec@5 99.000 (99.727) +2022-11-14 14:36:02,435 Epoch: [223][440/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0482 (0.0438) Prec@1 89.000 (92.511) Prec@5 100.000 (99.733) +2022-11-14 14:36:02,922 Epoch: [223][450/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0159 (0.0432) Prec@1 98.000 (92.630) Prec@5 100.000 (99.739) +2022-11-14 14:36:03,403 Epoch: [223][460/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0328 (0.0430) Prec@1 95.000 (92.681) Prec@5 100.000 (99.745) +2022-11-14 14:36:03,890 Epoch: [223][470/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0369 (0.0429) Prec@1 95.000 (92.729) Prec@5 99.000 (99.729) +2022-11-14 14:36:04,370 Epoch: [223][480/500] Time 0.050 (0.036) Data 0.002 (0.002) Loss 0.0494 (0.0430) Prec@1 93.000 (92.735) Prec@5 99.000 (99.714) +2022-11-14 14:36:04,855 Epoch: [223][490/500] Time 0.059 (0.036) Data 0.002 (0.002) Loss 0.0431 (0.0430) Prec@1 93.000 (92.740) Prec@5 100.000 (99.720) +2022-11-14 14:36:05,289 Epoch: [223][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0349 (0.0429) Prec@1 94.000 (92.765) Prec@5 100.000 (99.725) +2022-11-14 14:36:05,589 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0587 (0.0587) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:36:05,598 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0599) Prec@1 89.000 (89.500) Prec@5 98.000 (99.000) +2022-11-14 14:36:05,607 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0578) Prec@1 92.000 (90.333) Prec@5 99.000 (99.000) +2022-11-14 14:36:05,620 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0625) Prec@1 86.000 (89.250) Prec@5 99.000 (99.000) +2022-11-14 14:36:05,630 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0635) Prec@1 89.000 (89.200) Prec@5 100.000 (99.200) +2022-11-14 14:36:05,641 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0415 (0.0598) Prec@1 93.000 (89.833) Prec@5 100.000 (99.333) +2022-11-14 14:36:05,653 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0594) Prec@1 90.000 (89.857) Prec@5 100.000 (99.429) +2022-11-14 14:36:05,664 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0622) Prec@1 87.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:36:05,676 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0651) Prec@1 86.000 (89.111) Prec@5 100.000 (99.556) +2022-11-14 14:36:05,689 Test: [9/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0665) Prec@1 87.000 (88.900) Prec@5 98.000 (99.400) +2022-11-14 14:36:05,703 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0668) Prec@1 86.000 (88.636) Prec@5 99.000 (99.364) +2022-11-14 14:36:05,714 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0689) Prec@1 83.000 (88.167) Prec@5 100.000 (99.417) +2022-11-14 14:36:05,725 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0668) Prec@1 92.000 (88.462) Prec@5 100.000 (99.462) +2022-11-14 14:36:05,740 Test: [13/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0665) Prec@1 91.000 (88.643) Prec@5 98.000 (99.357) +2022-11-14 14:36:05,754 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0673) Prec@1 87.000 (88.533) Prec@5 98.000 (99.267) +2022-11-14 14:36:05,769 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0681) Prec@1 83.000 (88.188) Prec@5 100.000 (99.312) +2022-11-14 14:36:05,782 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0675) Prec@1 92.000 (88.412) Prec@5 98.000 (99.235) +2022-11-14 14:36:05,795 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1180 (0.0703) Prec@1 81.000 (88.000) Prec@5 100.000 (99.278) +2022-11-14 14:36:05,809 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0715) Prec@1 86.000 (87.895) Prec@5 97.000 (99.158) +2022-11-14 14:36:05,822 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0720) Prec@1 88.000 (87.900) Prec@5 98.000 (99.100) +2022-11-14 14:36:05,835 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0721) Prec@1 90.000 (88.000) Prec@5 99.000 (99.095) +2022-11-14 14:36:05,849 Test: [21/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0728) Prec@1 86.000 (87.909) Prec@5 98.000 (99.045) +2022-11-14 14:36:05,862 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0731) Prec@1 88.000 (87.913) Prec@5 99.000 (99.043) +2022-11-14 14:36:05,874 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0735) Prec@1 87.000 (87.875) Prec@5 99.000 (99.042) +2022-11-14 14:36:05,885 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0744) Prec@1 86.000 (87.800) Prec@5 100.000 (99.080) +2022-11-14 14:36:05,900 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0749) Prec@1 86.000 (87.731) Prec@5 97.000 (99.000) +2022-11-14 14:36:05,914 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0741) Prec@1 91.000 (87.852) Prec@5 100.000 (99.037) +2022-11-14 14:36:05,927 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0740) Prec@1 89.000 (87.893) Prec@5 100.000 (99.071) +2022-11-14 14:36:05,941 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0737) Prec@1 92.000 (88.034) Prec@5 99.000 (99.069) +2022-11-14 14:36:05,955 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0736) Prec@1 88.000 (88.033) Prec@5 98.000 (99.033) +2022-11-14 14:36:05,969 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0739) Prec@1 85.000 (87.935) Prec@5 100.000 (99.065) +2022-11-14 14:36:05,982 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0744) Prec@1 83.000 (87.781) Prec@5 100.000 (99.094) +2022-11-14 14:36:05,995 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0747) Prec@1 85.000 (87.697) Prec@5 100.000 (99.121) +2022-11-14 14:36:06,009 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0751) Prec@1 87.000 (87.676) Prec@5 100.000 (99.147) +2022-11-14 14:36:06,023 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0754) Prec@1 84.000 (87.571) Prec@5 100.000 (99.171) +2022-11-14 14:36:06,036 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0747) Prec@1 91.000 (87.667) Prec@5 100.000 (99.194) +2022-11-14 14:36:06,048 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0750) Prec@1 87.000 (87.649) Prec@5 99.000 (99.189) +2022-11-14 14:36:06,060 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1232 (0.0763) Prec@1 81.000 (87.474) Prec@5 99.000 (99.184) +2022-11-14 14:36:06,074 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0759) Prec@1 92.000 (87.590) Prec@5 98.000 (99.154) +2022-11-14 14:36:06,087 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0755) Prec@1 91.000 (87.675) Prec@5 100.000 (99.175) +2022-11-14 14:36:06,101 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0761) Prec@1 84.000 (87.585) Prec@5 98.000 (99.146) +2022-11-14 14:36:06,114 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0761) Prec@1 89.000 (87.619) Prec@5 100.000 (99.167) +2022-11-14 14:36:06,128 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0758) Prec@1 90.000 (87.674) Prec@5 99.000 (99.163) +2022-11-14 14:36:06,142 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0756) Prec@1 89.000 (87.705) Prec@5 99.000 (99.159) +2022-11-14 14:36:06,156 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0754) Prec@1 89.000 (87.733) Prec@5 99.000 (99.156) +2022-11-14 14:36:06,169 Test: [45/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.0762) Prec@1 81.000 (87.587) Prec@5 98.000 (99.130) +2022-11-14 14:36:06,182 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0757) Prec@1 94.000 (87.723) Prec@5 100.000 (99.149) +2022-11-14 14:36:06,194 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0760) Prec@1 83.000 (87.625) Prec@5 99.000 (99.146) +2022-11-14 14:36:06,206 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0757) Prec@1 88.000 (87.633) Prec@5 100.000 (99.163) +2022-11-14 14:36:06,219 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0763) Prec@1 84.000 (87.560) Prec@5 100.000 (99.180) +2022-11-14 14:36:06,232 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0762) Prec@1 88.000 (87.569) Prec@5 99.000 (99.176) +2022-11-14 14:36:06,245 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0763) Prec@1 87.000 (87.558) Prec@5 99.000 (99.173) +2022-11-14 14:36:06,259 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0764) Prec@1 86.000 (87.528) Prec@5 100.000 (99.189) +2022-11-14 14:36:06,272 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0759) Prec@1 93.000 (87.630) Prec@5 100.000 (99.204) +2022-11-14 14:36:06,285 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0760) Prec@1 88.000 (87.636) Prec@5 100.000 (99.218) +2022-11-14 14:36:06,296 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0763) Prec@1 88.000 (87.643) Prec@5 98.000 (99.196) +2022-11-14 14:36:06,308 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0765) Prec@1 84.000 (87.579) Prec@5 99.000 (99.193) +2022-11-14 14:36:06,322 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0765) Prec@1 86.000 (87.552) Prec@5 98.000 (99.172) +2022-11-14 14:36:06,336 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0770) Prec@1 82.000 (87.458) Prec@5 100.000 (99.186) +2022-11-14 14:36:06,350 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0769) Prec@1 87.000 (87.450) Prec@5 100.000 (99.200) +2022-11-14 14:36:06,365 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0770) Prec@1 86.000 (87.426) Prec@5 98.000 (99.180) +2022-11-14 14:36:06,379 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0769) Prec@1 89.000 (87.452) Prec@5 99.000 (99.177) +2022-11-14 14:36:06,393 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0767) Prec@1 89.000 (87.476) Prec@5 99.000 (99.175) +2022-11-14 14:36:06,407 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0762) Prec@1 91.000 (87.531) Prec@5 99.000 (99.172) +2022-11-14 14:36:06,421 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0765) Prec@1 80.000 (87.415) Prec@5 99.000 (99.169) +2022-11-14 14:36:06,435 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0764) Prec@1 91.000 (87.470) Prec@5 99.000 (99.167) +2022-11-14 14:36:06,448 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0760) Prec@1 92.000 (87.537) Prec@5 100.000 (99.179) +2022-11-14 14:36:06,462 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0760) Prec@1 88.000 (87.544) Prec@5 97.000 (99.147) +2022-11-14 14:36:06,474 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0758) Prec@1 90.000 (87.580) Prec@5 98.000 (99.130) +2022-11-14 14:36:06,488 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0757) Prec@1 89.000 (87.600) Prec@5 99.000 (99.129) +2022-11-14 14:36:06,501 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0758) Prec@1 86.000 (87.577) Prec@5 99.000 (99.127) +2022-11-14 14:36:06,514 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0758) Prec@1 88.000 (87.583) Prec@5 99.000 (99.125) +2022-11-14 14:36:06,526 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0755) Prec@1 91.000 (87.630) Prec@5 99.000 (99.123) +2022-11-14 14:36:06,539 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0752) Prec@1 92.000 (87.689) Prec@5 100.000 (99.135) +2022-11-14 14:36:06,552 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0753) Prec@1 86.000 (87.667) Prec@5 99.000 (99.133) +2022-11-14 14:36:06,566 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0750) Prec@1 90.000 (87.697) Prec@5 98.000 (99.118) +2022-11-14 14:36:06,579 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0750) Prec@1 87.000 (87.688) Prec@5 98.000 (99.104) +2022-11-14 14:36:06,593 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0750) Prec@1 86.000 (87.667) Prec@5 99.000 (99.103) +2022-11-14 14:36:06,606 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0752) Prec@1 86.000 (87.646) Prec@5 100.000 (99.114) +2022-11-14 14:36:06,619 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0752) Prec@1 88.000 (87.650) Prec@5 100.000 (99.125) +2022-11-14 14:36:06,631 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0753) Prec@1 87.000 (87.642) Prec@5 98.000 (99.111) +2022-11-14 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0.000 (0.000) Loss 0.0960 (0.0759) Prec@1 84.000 (87.500) Prec@5 99.000 (99.091) +2022-11-14 14:36:06,739 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0758) Prec@1 90.000 (87.528) Prec@5 100.000 (99.101) +2022-11-14 14:36:06,755 Test: [89/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0758) Prec@1 90.000 (87.556) Prec@5 98.000 (99.089) +2022-11-14 14:36:06,769 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0755) Prec@1 93.000 (87.615) Prec@5 100.000 (99.099) +2022-11-14 14:36:06,785 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0752) Prec@1 93.000 (87.674) Prec@5 99.000 (99.098) +2022-11-14 14:36:06,799 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0753) Prec@1 85.000 (87.645) Prec@5 99.000 (99.097) +2022-11-14 14:36:06,815 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0754) Prec@1 84.000 (87.606) Prec@5 100.000 (99.106) +2022-11-14 14:36:06,829 Test: [94/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0755) Prec@1 87.000 (87.600) Prec@5 100.000 (99.116) +2022-11-14 14:36:06,843 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0753) Prec@1 90.000 (87.625) Prec@5 100.000 (99.125) +2022-11-14 14:36:06,856 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0751) Prec@1 90.000 (87.649) Prec@5 99.000 (99.124) +2022-11-14 14:36:06,869 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0750) Prec@1 90.000 (87.673) Prec@5 100.000 (99.133) +2022-11-14 14:36:06,882 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0751) Prec@1 88.000 (87.677) Prec@5 99.000 (99.131) +2022-11-14 14:36:06,894 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0750) Prec@1 87.000 (87.670) Prec@5 100.000 (99.140) +2022-11-14 14:36:06,953 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:36:07,270 Epoch: [224][0/500] Time 0.023 (0.023) Data 0.240 (0.240) Loss 0.0542 (0.0542) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 14:36:07,492 Epoch: [224][10/500] Time 0.020 (0.020) Data 0.002 (0.023) Loss 0.0399 (0.0470) Prec@1 95.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 14:36:07,755 Epoch: [224][20/500] Time 0.030 (0.021) Data 0.002 (0.013) Loss 0.0520 (0.0487) Prec@1 92.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 14:36:08,116 Epoch: [224][30/500] Time 0.033 (0.025) Data 0.002 (0.009) Loss 0.0421 (0.0471) Prec@1 91.000 (92.250) Prec@5 99.000 (99.500) +2022-11-14 14:36:08,571 Epoch: [224][40/500] Time 0.039 (0.029) Data 0.002 (0.008) Loss 0.0638 (0.0504) Prec@1 91.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:36:09,014 Epoch: [224][50/500] Time 0.045 (0.031) Data 0.002 (0.006) Loss 0.0149 (0.0445) Prec@1 98.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:36:09,459 Epoch: [224][60/500] Time 0.045 (0.032) Data 0.002 (0.006) Loss 0.0155 (0.0404) Prec@1 98.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 14:36:09,867 Epoch: [224][70/500] Time 0.023 (0.033) Data 0.002 (0.005) Loss 0.0354 (0.0397) Prec@1 95.000 (93.875) Prec@5 100.000 (99.750) +2022-11-14 14:36:10,234 Epoch: [224][80/500] Time 0.039 (0.033) Data 0.002 (0.005) Loss 0.0372 (0.0394) Prec@1 94.000 (93.889) Prec@5 100.000 (99.778) +2022-11-14 14:36:10,589 Epoch: [224][90/500] Time 0.033 (0.033) Data 0.002 (0.005) Loss 0.0232 (0.0378) Prec@1 96.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 14:36:10,988 Epoch: [224][100/500] Time 0.032 (0.033) Data 0.002 (0.004) Loss 0.0427 (0.0383) Prec@1 94.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 14:36:11,381 Epoch: [224][110/500] Time 0.031 (0.033) Data 0.002 (0.004) Loss 0.0316 (0.0377) Prec@1 94.000 (94.083) Prec@5 100.000 (99.833) +2022-11-14 14:36:11,760 Epoch: [224][120/500] Time 0.045 (0.033) Data 0.002 (0.004) Loss 0.0431 (0.0381) Prec@1 93.000 (94.000) Prec@5 100.000 (99.846) +2022-11-14 14:36:12,120 Epoch: [224][130/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0571 (0.0395) Prec@1 90.000 (93.714) Prec@5 100.000 (99.857) +2022-11-14 14:36:12,552 Epoch: [224][140/500] Time 0.041 (0.033) Data 0.002 (0.004) Loss 0.0319 (0.0390) Prec@1 95.000 (93.800) Prec@5 100.000 (99.867) +2022-11-14 14:36:12,929 Epoch: [224][150/500] Time 0.025 (0.034) Data 0.002 (0.004) Loss 0.0694 (0.0409) Prec@1 88.000 (93.438) Prec@5 99.000 (99.812) +2022-11-14 14:36:13,298 Epoch: [224][160/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.0339 (0.0405) Prec@1 93.000 (93.412) Prec@5 100.000 (99.824) +2022-11-14 14:36:13,714 Epoch: [224][170/500] Time 0.027 (0.034) Data 0.002 (0.003) Loss 0.0375 (0.0403) Prec@1 94.000 (93.444) Prec@5 100.000 (99.833) +2022-11-14 14:36:14,105 Epoch: [224][180/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0842 (0.0426) Prec@1 87.000 (93.105) Prec@5 99.000 (99.789) +2022-11-14 14:36:14,480 Epoch: [224][190/500] Time 0.029 (0.034) Data 0.002 (0.003) Loss 0.0563 (0.0433) Prec@1 89.000 (92.900) Prec@5 99.000 (99.750) +2022-11-14 14:36:14,902 Epoch: [224][200/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0451 (0.0434) Prec@1 91.000 (92.810) Prec@5 100.000 (99.762) +2022-11-14 14:36:15,283 Epoch: [224][210/500] Time 0.029 (0.034) Data 0.002 (0.003) Loss 0.0494 (0.0436) Prec@1 92.000 (92.773) Prec@5 100.000 (99.773) +2022-11-14 14:36:15,686 Epoch: [224][220/500] Time 0.054 (0.034) Data 0.002 (0.003) Loss 0.0509 (0.0440) Prec@1 90.000 (92.652) Prec@5 100.000 (99.783) +2022-11-14 14:36:16,042 Epoch: [224][230/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0257 (0.0432) Prec@1 95.000 (92.750) Prec@5 100.000 (99.792) +2022-11-14 14:36:16,425 Epoch: [224][240/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0264 (0.0425) Prec@1 95.000 (92.840) Prec@5 100.000 (99.800) +2022-11-14 14:36:16,801 Epoch: [224][250/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0357 (0.0423) Prec@1 95.000 (92.923) Prec@5 100.000 (99.808) +2022-11-14 14:36:17,166 Epoch: [224][260/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0359 (0.0420) Prec@1 94.000 (92.963) Prec@5 100.000 (99.815) +2022-11-14 14:36:17,525 Epoch: [224][270/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0184 (0.0412) Prec@1 97.000 (93.107) Prec@5 100.000 (99.821) +2022-11-14 14:36:17,897 Epoch: [224][280/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0239 (0.0406) Prec@1 96.000 (93.207) Prec@5 100.000 (99.828) +2022-11-14 14:36:18,270 Epoch: [224][290/500] Time 0.031 (0.034) Data 0.002 (0.003) Loss 0.0359 (0.0404) Prec@1 94.000 (93.233) Prec@5 100.000 (99.833) +2022-11-14 14:36:18,628 Epoch: [224][300/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0380 (0.0404) Prec@1 94.000 (93.258) Prec@5 100.000 (99.839) +2022-11-14 14:36:19,017 Epoch: [224][310/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0479 (0.0406) Prec@1 91.000 (93.188) Prec@5 100.000 (99.844) +2022-11-14 14:36:19,590 Epoch: [224][320/500] Time 0.083 (0.034) Data 0.003 (0.003) Loss 0.0422 (0.0406) Prec@1 92.000 (93.152) Prec@5 100.000 (99.848) +2022-11-14 14:36:20,326 Epoch: [224][330/500] Time 0.072 (0.035) Data 0.002 (0.003) Loss 0.0352 (0.0405) Prec@1 95.000 (93.206) Prec@5 100.000 (99.853) +2022-11-14 14:36:20,805 Epoch: [224][340/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0245 (0.0400) Prec@1 97.000 (93.314) Prec@5 100.000 (99.857) +2022-11-14 14:36:21,458 Epoch: [224][350/500] Time 0.077 (0.036) Data 0.002 (0.003) Loss 0.0735 (0.0409) Prec@1 85.000 (93.083) Prec@5 100.000 (99.861) +2022-11-14 14:36:21,985 Epoch: [224][360/500] Time 0.070 (0.036) Data 0.002 (0.003) Loss 0.0566 (0.0414) Prec@1 90.000 (93.000) Prec@5 99.000 (99.838) +2022-11-14 14:36:22,448 Epoch: [224][370/500] Time 0.042 (0.036) Data 0.003 (0.003) Loss 0.0474 (0.0415) Prec@1 93.000 (93.000) Prec@5 100.000 (99.842) +2022-11-14 14:36:23,072 Epoch: [224][380/500] Time 0.058 (0.037) Data 0.002 (0.003) Loss 0.0513 (0.0418) Prec@1 93.000 (93.000) Prec@5 100.000 (99.846) +2022-11-14 14:36:23,689 Epoch: [224][390/500] Time 0.093 (0.037) Data 0.002 (0.003) Loss 0.0596 (0.0422) Prec@1 93.000 (93.000) Prec@5 99.000 (99.825) +2022-11-14 14:36:24,328 Epoch: [224][400/500] Time 0.069 (0.038) Data 0.002 (0.003) Loss 0.0586 (0.0426) Prec@1 90.000 (92.927) Prec@5 100.000 (99.829) +2022-11-14 14:36:24,875 Epoch: [224][410/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0500 (0.0428) Prec@1 91.000 (92.881) Prec@5 100.000 (99.833) +2022-11-14 14:36:25,415 Epoch: [224][420/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0407 (0.0428) Prec@1 94.000 (92.907) Prec@5 100.000 (99.837) +2022-11-14 14:36:26,033 Epoch: [224][430/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0477 (0.0429) Prec@1 93.000 (92.909) Prec@5 100.000 (99.841) +2022-11-14 14:36:26,837 Epoch: [224][440/500] Time 0.093 (0.040) Data 0.002 (0.002) Loss 0.0229 (0.0424) Prec@1 97.000 (93.000) Prec@5 100.000 (99.844) +2022-11-14 14:36:27,524 Epoch: [224][450/500] Time 0.053 (0.040) Data 0.002 (0.002) Loss 0.0476 (0.0425) Prec@1 92.000 (92.978) Prec@5 100.000 (99.848) +2022-11-14 14:36:28,128 Epoch: [224][460/500] Time 0.063 (0.040) Data 0.002 (0.002) Loss 0.0153 (0.0420) Prec@1 99.000 (93.106) Prec@5 100.000 (99.851) +2022-11-14 14:36:28,690 Epoch: [224][470/500] Time 0.053 (0.041) Data 0.002 (0.002) Loss 0.0524 (0.0422) Prec@1 91.000 (93.062) Prec@5 99.000 (99.833) +2022-11-14 14:36:29,257 Epoch: [224][480/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0454 (0.0422) Prec@1 93.000 (93.061) Prec@5 100.000 (99.837) +2022-11-14 14:36:29,799 Epoch: [224][490/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0690 (0.0428) Prec@1 87.000 (92.940) Prec@5 100.000 (99.840) +2022-11-14 14:36:30,228 Epoch: [224][499/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0384 (0.0427) Prec@1 95.000 (92.980) Prec@5 100.000 (99.843) +2022-11-14 14:36:30,523 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0651 (0.0651) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:36:30,532 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0660) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:36:30,541 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0641) Prec@1 90.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:36:30,557 Test: [3/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0669) Prec@1 88.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 14:36:30,568 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0677) Prec@1 90.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 14:36:30,580 Test: [5/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0194 (0.0596) Prec@1 97.000 (90.333) Prec@5 100.000 (99.500) +2022-11-14 14:36:30,591 Test: [6/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0509 (0.0584) Prec@1 92.000 (90.571) Prec@5 100.000 (99.571) +2022-11-14 14:36:30,604 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0594) Prec@1 89.000 (90.375) Prec@5 99.000 (99.500) +2022-11-14 14:36:30,613 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0724 (0.0608) Prec@1 90.000 (90.333) Prec@5 99.000 (99.444) +2022-11-14 14:36:30,622 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0570 (0.0604) Prec@1 90.000 (90.300) Prec@5 98.000 (99.300) +2022-11-14 14:36:30,631 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0569 (0.0601) Prec@1 90.000 (90.273) Prec@5 100.000 (99.364) +2022-11-14 14:36:30,641 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0618) Prec@1 88.000 (90.083) Prec@5 98.000 (99.250) +2022-11-14 14:36:30,651 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0620) Prec@1 89.000 (90.000) Prec@5 100.000 (99.308) +2022-11-14 14:36:30,661 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0627) Prec@1 89.000 (89.929) Prec@5 100.000 (99.357) +2022-11-14 14:36:30,671 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0623) Prec@1 92.000 (90.067) Prec@5 99.000 (99.333) +2022-11-14 14:36:30,681 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0631) Prec@1 87.000 (89.875) Prec@5 100.000 (99.375) +2022-11-14 14:36:30,691 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0425 (0.0619) Prec@1 95.000 (90.176) Prec@5 99.000 (99.353) +2022-11-14 14:36:30,702 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0642) Prec@1 83.000 (89.778) Prec@5 100.000 (99.389) +2022-11-14 14:36:30,712 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0664) Prec@1 83.000 (89.421) Prec@5 97.000 (99.263) +2022-11-14 14:36:30,722 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0680) Prec@1 84.000 (89.150) Prec@5 98.000 (99.200) +2022-11-14 14:36:30,732 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0694) Prec@1 83.000 (88.857) Prec@5 100.000 (99.238) +2022-11-14 14:36:30,742 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0702) Prec@1 85.000 (88.682) Prec@5 100.000 (99.273) +2022-11-14 14:36:30,751 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0713) Prec@1 85.000 (88.522) Prec@5 99.000 (99.261) +2022-11-14 14:36:30,761 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0713) Prec@1 87.000 (88.458) Prec@5 100.000 (99.292) +2022-11-14 14:36:30,772 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0714) Prec@1 89.000 (88.480) Prec@5 100.000 (99.320) +2022-11-14 14:36:30,784 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0721) Prec@1 85.000 (88.346) Prec@5 99.000 (99.308) +2022-11-14 14:36:30,795 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0718) Prec@1 90.000 (88.407) Prec@5 100.000 (99.333) +2022-11-14 14:36:30,804 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0718) Prec@1 87.000 (88.357) Prec@5 100.000 (99.357) +2022-11-14 14:36:30,814 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0716) Prec@1 89.000 (88.379) Prec@5 99.000 (99.345) +2022-11-14 14:36:30,824 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0719) Prec@1 86.000 (88.300) Prec@5 100.000 (99.367) +2022-11-14 14:36:30,835 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0713) Prec@1 92.000 (88.419) Prec@5 100.000 (99.387) +2022-11-14 14:36:30,843 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0715) Prec@1 89.000 (88.438) Prec@5 100.000 (99.406) +2022-11-14 14:36:30,853 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0721) Prec@1 85.000 (88.333) Prec@5 98.000 (99.364) +2022-11-14 14:36:30,864 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0731) Prec@1 80.000 (88.088) Prec@5 99.000 (99.353) +2022-11-14 14:36:30,873 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0732) Prec@1 89.000 (88.114) Prec@5 97.000 (99.286) +2022-11-14 14:36:30,881 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0733) Prec@1 89.000 (88.139) Prec@5 99.000 (99.278) +2022-11-14 14:36:30,889 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0733) Prec@1 89.000 (88.162) Prec@5 99.000 (99.270) +2022-11-14 14:36:30,900 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0741) Prec@1 85.000 (88.079) Prec@5 98.000 (99.237) +2022-11-14 14:36:30,910 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0736) Prec@1 93.000 (88.205) Prec@5 100.000 (99.256) +2022-11-14 14:36:30,918 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0736) Prec@1 89.000 (88.225) Prec@5 99.000 (99.250) +2022-11-14 14:36:30,926 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0742) Prec@1 85.000 (88.146) Prec@5 97.000 (99.195) +2022-11-14 14:36:30,936 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0743) Prec@1 88.000 (88.143) Prec@5 99.000 (99.190) +2022-11-14 14:36:30,947 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0737) Prec@1 93.000 (88.256) Prec@5 99.000 (99.186) +2022-11-14 14:36:30,957 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0734) Prec@1 89.000 (88.273) Prec@5 99.000 (99.182) +2022-11-14 14:36:30,966 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0729) Prec@1 90.000 (88.311) Prec@5 100.000 (99.200) +2022-11-14 14:36:30,977 Test: [45/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0735) Prec@1 85.000 (88.239) Prec@5 100.000 (99.217) +2022-11-14 14:36:30,988 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0731) Prec@1 91.000 (88.298) Prec@5 100.000 (99.234) +2022-11-14 14:36:30,998 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0732) Prec@1 83.000 (88.188) Prec@5 98.000 (99.208) +2022-11-14 14:36:31,007 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0472 (0.0727) Prec@1 91.000 (88.245) Prec@5 100.000 (99.224) +2022-11-14 14:36:31,019 Test: [49/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0734) Prec@1 82.000 (88.120) Prec@5 97.000 (99.180) +2022-11-14 14:36:31,030 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0733) Prec@1 89.000 (88.137) Prec@5 100.000 (99.196) +2022-11-14 14:36:31,040 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0731) Prec@1 90.000 (88.173) Prec@5 99.000 (99.192) +2022-11-14 14:36:31,049 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0729) Prec@1 90.000 (88.208) Prec@5 99.000 (99.189) +2022-11-14 14:36:31,060 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0727) Prec@1 89.000 (88.222) Prec@5 100.000 (99.204) +2022-11-14 14:36:31,071 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0730) Prec@1 83.000 (88.127) Prec@5 100.000 (99.218) +2022-11-14 14:36:31,081 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0729) Prec@1 89.000 (88.143) Prec@5 100.000 (99.232) +2022-11-14 14:36:31,090 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0730) Prec@1 88.000 (88.140) Prec@5 99.000 (99.228) +2022-11-14 14:36:31,101 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0733) Prec@1 87.000 (88.121) Prec@5 100.000 (99.241) +2022-11-14 14:36:31,111 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0739) Prec@1 82.000 (88.017) Prec@5 100.000 (99.254) +2022-11-14 14:36:31,120 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0739) Prec@1 86.000 (87.983) Prec@5 100.000 (99.267) +2022-11-14 14:36:31,130 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0738) Prec@1 91.000 (88.033) Prec@5 100.000 (99.279) +2022-11-14 14:36:31,142 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0735) Prec@1 91.000 (88.081) Prec@5 98.000 (99.258) +2022-11-14 14:36:31,154 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0734) Prec@1 91.000 (88.127) Prec@5 100.000 (99.270) +2022-11-14 14:36:31,164 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0729) Prec@1 93.000 (88.203) Prec@5 100.000 (99.281) +2022-11-14 14:36:31,174 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0732) Prec@1 85.000 (88.154) Prec@5 100.000 (99.292) +2022-11-14 14:36:31,186 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0734) Prec@1 83.000 (88.076) Prec@5 100.000 (99.303) +2022-11-14 14:36:31,197 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0730) Prec@1 93.000 (88.149) Prec@5 99.000 (99.299) +2022-11-14 14:36:31,207 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0730) Prec@1 87.000 (88.132) Prec@5 98.000 (99.279) +2022-11-14 14:36:31,216 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0727) Prec@1 92.000 (88.188) Prec@5 100.000 (99.290) +2022-11-14 14:36:31,229 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0727) Prec@1 89.000 (88.200) Prec@5 99.000 (99.286) +2022-11-14 14:36:31,241 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0731) Prec@1 86.000 (88.169) Prec@5 99.000 (99.282) +2022-11-14 14:36:31,252 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0461 (0.0727) Prec@1 92.000 (88.222) Prec@5 100.000 (99.292) +2022-11-14 14:36:31,265 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0394 (0.0723) Prec@1 92.000 (88.274) Prec@5 100.000 (99.301) +2022-11-14 14:36:31,279 Test: [73/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0721) Prec@1 91.000 (88.311) Prec@5 99.000 (99.297) +2022-11-14 14:36:31,292 Test: [74/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0725) Prec@1 83.000 (88.240) Prec@5 100.000 (99.307) +2022-11-14 14:36:31,305 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0723) Prec@1 91.000 (88.276) Prec@5 98.000 (99.289) +2022-11-14 14:36:31,316 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0724) Prec@1 88.000 (88.273) Prec@5 98.000 (99.273) +2022-11-14 14:36:31,328 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0725) Prec@1 84.000 (88.218) Prec@5 99.000 (99.269) +2022-11-14 14:36:31,341 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0727) Prec@1 87.000 (88.203) Prec@5 100.000 (99.278) +2022-11-14 14:36:31,352 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0731) Prec@1 84.000 (88.150) Prec@5 99.000 (99.275) +2022-11-14 14:36:31,363 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0730) Prec@1 91.000 (88.185) Prec@5 100.000 (99.284) +2022-11-14 14:36:31,373 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0730) Prec@1 88.000 (88.183) Prec@5 98.000 (99.268) +2022-11-14 14:36:31,384 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0730) Prec@1 86.000 (88.157) Prec@5 100.000 (99.277) +2022-11-14 14:36:31,394 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0729) Prec@1 91.000 (88.190) Prec@5 98.000 (99.262) +2022-11-14 14:36:31,404 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0730) Prec@1 87.000 (88.176) Prec@5 100.000 (99.271) +2022-11-14 14:36:31,414 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0729) Prec@1 90.000 (88.198) Prec@5 99.000 (99.267) +2022-11-14 14:36:31,424 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0732) Prec@1 84.000 (88.149) Prec@5 100.000 (99.276) +2022-11-14 14:36:31,434 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0733) Prec@1 86.000 (88.125) Prec@5 99.000 (99.273) +2022-11-14 14:36:31,444 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0731) Prec@1 90.000 (88.146) Prec@5 100.000 (99.281) +2022-11-14 14:36:31,453 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0732) Prec@1 88.000 (88.144) Prec@5 99.000 (99.278) +2022-11-14 14:36:31,463 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0730) Prec@1 90.000 (88.165) Prec@5 100.000 (99.286) +2022-11-14 14:36:31,472 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0728) Prec@1 91.000 (88.196) Prec@5 99.000 (99.283) +2022-11-14 14:36:31,482 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0728) Prec@1 85.000 (88.161) Prec@5 99.000 (99.280) +2022-11-14 14:36:31,492 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0728) Prec@1 87.000 (88.149) Prec@5 99.000 (99.277) +2022-11-14 14:36:31,501 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0730) Prec@1 84.000 (88.105) Prec@5 99.000 (99.274) +2022-11-14 14:36:31,510 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0729) Prec@1 91.000 (88.135) Prec@5 99.000 (99.271) +2022-11-14 14:36:31,520 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0727) Prec@1 92.000 (88.175) Prec@5 99.000 (99.268) +2022-11-14 14:36:31,529 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0730) Prec@1 81.000 (88.102) Prec@5 99.000 (99.265) +2022-11-14 14:36:31,539 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0732) Prec@1 88.000 (88.101) Prec@5 99.000 (99.263) +2022-11-14 14:36:31,549 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0731) Prec@1 90.000 (88.120) Prec@5 100.000 (99.270) +2022-11-14 14:36:31,607 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:36:31,918 Epoch: [225][0/500] Time 0.027 (0.027) Data 0.226 (0.226) Loss 0.0354 (0.0354) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:36:32,129 Epoch: [225][10/500] Time 0.020 (0.020) Data 0.001 (0.022) Loss 0.0363 (0.0358) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:36:32,364 Epoch: [225][20/500] Time 0.026 (0.020) Data 0.002 (0.012) Loss 0.0353 (0.0357) Prec@1 94.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 14:36:32,615 Epoch: [225][30/500] Time 0.022 (0.021) Data 0.002 (0.009) Loss 0.0109 (0.0295) Prec@1 99.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 14:36:32,915 Epoch: [225][40/500] Time 0.035 (0.022) Data 0.002 (0.007) Loss 0.0343 (0.0304) Prec@1 94.000 (95.000) Prec@5 99.000 (99.600) +2022-11-14 14:36:33,247 Epoch: [225][50/500] Time 0.033 (0.024) Data 0.001 (0.006) Loss 0.0409 (0.0322) Prec@1 93.000 (94.667) Prec@5 99.000 (99.500) +2022-11-14 14:36:33,585 Epoch: [225][60/500] Time 0.031 (0.025) Data 0.003 (0.006) Loss 0.0619 (0.0364) Prec@1 90.000 (94.000) Prec@5 100.000 (99.571) +2022-11-14 14:36:33,931 Epoch: [225][70/500] Time 0.032 (0.025) Data 0.002 (0.005) Loss 0.0680 (0.0404) Prec@1 88.000 (93.250) Prec@5 99.000 (99.500) +2022-11-14 14:36:34,271 Epoch: [225][80/500] Time 0.030 (0.026) Data 0.002 (0.005) Loss 0.0272 (0.0389) Prec@1 97.000 (93.667) Prec@5 100.000 (99.556) +2022-11-14 14:36:34,610 Epoch: [225][90/500] Time 0.033 (0.026) Data 0.002 (0.004) Loss 0.0374 (0.0388) Prec@1 94.000 (93.700) Prec@5 100.000 (99.600) +2022-11-14 14:36:34,959 Epoch: [225][100/500] Time 0.028 (0.027) Data 0.002 (0.004) Loss 0.0389 (0.0388) Prec@1 93.000 (93.636) Prec@5 100.000 (99.636) +2022-11-14 14:36:35,301 Epoch: [225][110/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0425 (0.0391) Prec@1 92.000 (93.500) Prec@5 99.000 (99.583) +2022-11-14 14:36:35,645 Epoch: [225][120/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0503 (0.0399) Prec@1 91.000 (93.308) Prec@5 100.000 (99.615) +2022-11-14 14:36:35,983 Epoch: [225][130/500] Time 0.033 (0.028) Data 0.002 (0.004) Loss 0.0424 (0.0401) Prec@1 94.000 (93.357) Prec@5 100.000 (99.643) +2022-11-14 14:36:36,334 Epoch: [225][140/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.0201 (0.0388) Prec@1 97.000 (93.600) Prec@5 100.000 (99.667) +2022-11-14 14:36:36,685 Epoch: [225][150/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0303 (0.0383) Prec@1 95.000 (93.688) Prec@5 100.000 (99.688) +2022-11-14 14:36:37,026 Epoch: [225][160/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0312 (0.0378) Prec@1 95.000 (93.765) Prec@5 100.000 (99.706) +2022-11-14 14:36:37,363 Epoch: [225][170/500] Time 0.030 (0.028) Data 0.001 (0.003) Loss 0.0592 (0.0390) Prec@1 92.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:36:37,720 Epoch: [225][180/500] Time 0.038 (0.029) Data 0.002 (0.003) Loss 0.0321 (0.0387) Prec@1 95.000 (93.737) Prec@5 100.000 (99.684) +2022-11-14 14:36:38,070 Epoch: [225][190/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0377 (0.0386) Prec@1 94.000 (93.750) Prec@5 99.000 (99.650) +2022-11-14 14:36:38,412 Epoch: [225][200/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.0416 (0.0388) Prec@1 92.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:36:38,750 Epoch: [225][210/500] Time 0.030 (0.029) Data 0.003 (0.003) Loss 0.0439 (0.0390) Prec@1 92.000 (93.591) Prec@5 100.000 (99.682) +2022-11-14 14:36:39,089 Epoch: [225][220/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0433 (0.0392) Prec@1 92.000 (93.522) Prec@5 100.000 (99.696) +2022-11-14 14:36:39,429 Epoch: [225][230/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0530 (0.0398) Prec@1 92.000 (93.458) Prec@5 100.000 (99.708) +2022-11-14 14:36:39,777 Epoch: [225][240/500] Time 0.033 (0.029) Data 0.001 (0.003) Loss 0.0483 (0.0401) Prec@1 92.000 (93.400) Prec@5 100.000 (99.720) +2022-11-14 14:36:40,128 Epoch: [225][250/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0510 (0.0405) Prec@1 91.000 (93.308) Prec@5 99.000 (99.692) +2022-11-14 14:36:40,482 Epoch: [225][260/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0419 (0.0406) Prec@1 92.000 (93.259) Prec@5 100.000 (99.704) +2022-11-14 14:36:40,985 Epoch: [225][270/500] Time 0.051 (0.030) Data 0.002 (0.003) Loss 0.0301 (0.0402) Prec@1 95.000 (93.321) Prec@5 100.000 (99.714) +2022-11-14 14:36:41,482 Epoch: [225][280/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0292 (0.0398) Prec@1 94.000 (93.345) Prec@5 100.000 (99.724) +2022-11-14 14:36:41,974 Epoch: [225][290/500] Time 0.051 (0.031) Data 0.002 (0.003) Loss 0.0394 (0.0398) Prec@1 92.000 (93.300) Prec@5 99.000 (99.700) +2022-11-14 14:36:42,481 Epoch: [225][300/500] Time 0.053 (0.031) Data 0.002 (0.003) Loss 0.0232 (0.0393) Prec@1 94.000 (93.323) Prec@5 100.000 (99.710) +2022-11-14 14:36:42,962 Epoch: [225][310/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0454 (0.0395) Prec@1 92.000 (93.281) Prec@5 99.000 (99.688) +2022-11-14 14:36:43,441 Epoch: [225][320/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0323 (0.0392) Prec@1 95.000 (93.333) Prec@5 100.000 (99.697) +2022-11-14 14:36:43,930 Epoch: [225][330/500] Time 0.050 (0.032) Data 0.002 (0.003) Loss 0.0483 (0.0395) Prec@1 92.000 (93.294) Prec@5 100.000 (99.706) +2022-11-14 14:36:44,418 Epoch: [225][340/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0197 (0.0389) Prec@1 96.000 (93.371) Prec@5 100.000 (99.714) +2022-11-14 14:36:44,935 Epoch: [225][350/500] Time 0.053 (0.033) Data 0.002 (0.003) Loss 0.0369 (0.0389) Prec@1 95.000 (93.417) Prec@5 100.000 (99.722) +2022-11-14 14:36:45,431 Epoch: [225][360/500] Time 0.047 (0.033) Data 0.002 (0.003) Loss 0.0466 (0.0391) Prec@1 93.000 (93.405) Prec@5 100.000 (99.730) +2022-11-14 14:36:45,913 Epoch: [225][370/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0391 (0.0391) Prec@1 93.000 (93.395) Prec@5 100.000 (99.737) +2022-11-14 14:36:46,377 Epoch: [225][380/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0579 (0.0396) Prec@1 90.000 (93.308) Prec@5 100.000 (99.744) +2022-11-14 14:36:46,869 Epoch: [225][390/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0218 (0.0391) Prec@1 95.000 (93.350) Prec@5 100.000 (99.750) +2022-11-14 14:36:47,342 Epoch: [225][400/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0135 (0.0385) Prec@1 98.000 (93.463) Prec@5 100.000 (99.756) +2022-11-14 14:36:47,834 Epoch: [225][410/500] Time 0.052 (0.035) Data 0.002 (0.002) Loss 0.0221 (0.0381) Prec@1 97.000 (93.548) Prec@5 100.000 (99.762) +2022-11-14 14:36:48,340 Epoch: [225][420/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0384 (0.0381) Prec@1 93.000 (93.535) Prec@5 100.000 (99.767) +2022-11-14 14:36:48,892 Epoch: [225][430/500] Time 0.066 (0.035) Data 0.002 (0.002) Loss 0.0687 (0.0388) Prec@1 89.000 (93.432) Prec@5 99.000 (99.750) +2022-11-14 14:36:49,376 Epoch: [225][440/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0294 (0.0386) Prec@1 94.000 (93.444) Prec@5 99.000 (99.733) +2022-11-14 14:36:49,855 Epoch: [225][450/500] Time 0.049 (0.035) Data 0.002 (0.002) Loss 0.0508 (0.0389) Prec@1 94.000 (93.457) Prec@5 99.000 (99.717) +2022-11-14 14:36:50,349 Epoch: [225][460/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0332 (0.0387) Prec@1 94.000 (93.468) Prec@5 100.000 (99.723) +2022-11-14 14:36:50,828 Epoch: [225][470/500] Time 0.053 (0.036) Data 0.002 (0.002) Loss 0.0326 (0.0386) Prec@1 95.000 (93.500) Prec@5 99.000 (99.708) +2022-11-14 14:36:51,317 Epoch: [225][480/500] Time 0.048 (0.036) Data 0.002 (0.002) Loss 0.0662 (0.0392) Prec@1 88.000 (93.388) Prec@5 99.000 (99.694) +2022-11-14 14:36:51,813 Epoch: [225][490/500] Time 0.048 (0.036) Data 0.001 (0.002) Loss 0.0465 (0.0393) Prec@1 91.000 (93.340) Prec@5 100.000 (99.700) +2022-11-14 14:36:52,289 Epoch: [225][499/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0590 (0.0397) Prec@1 88.000 (93.235) Prec@5 100.000 (99.706) +2022-11-14 14:36:52,570 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0756 (0.0756) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:36:52,579 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0742) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:36:52,587 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0800) Prec@1 86.000 (86.000) Prec@5 99.000 (99.667) +2022-11-14 14:36:52,598 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0758) Prec@1 90.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 14:36:52,607 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0749) Prec@1 88.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:36:52,615 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0691) Prec@1 94.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:36:52,624 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0654) Prec@1 93.000 (89.000) Prec@5 100.000 (99.714) +2022-11-14 14:36:52,635 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0666) Prec@1 88.000 (88.875) Prec@5 100.000 (99.750) +2022-11-14 14:36:52,646 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0674) Prec@1 89.000 (88.889) Prec@5 100.000 (99.778) +2022-11-14 14:36:52,658 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0682) Prec@1 85.000 (88.500) Prec@5 99.000 (99.700) +2022-11-14 14:36:52,670 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0678) Prec@1 86.000 (88.273) Prec@5 100.000 (99.727) +2022-11-14 14:36:52,684 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0676) Prec@1 88.000 (88.250) Prec@5 99.000 (99.667) +2022-11-14 14:36:52,696 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0671) Prec@1 89.000 (88.308) Prec@5 99.000 (99.615) +2022-11-14 14:36:52,707 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0658) Prec@1 92.000 (88.571) Prec@5 100.000 (99.643) +2022-11-14 14:36:52,719 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0665) Prec@1 87.000 (88.467) Prec@5 100.000 (99.667) +2022-11-14 14:36:52,733 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0671) Prec@1 88.000 (88.438) Prec@5 99.000 (99.625) +2022-11-14 14:36:52,746 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0667) Prec@1 90.000 (88.529) Prec@5 99.000 (99.588) +2022-11-14 14:36:52,759 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0688) Prec@1 86.000 (88.389) Prec@5 100.000 (99.611) +2022-11-14 14:36:52,775 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0702) Prec@1 84.000 (88.158) Prec@5 98.000 (99.526) +2022-11-14 14:36:52,788 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0713) Prec@1 84.000 (87.950) Prec@5 98.000 (99.450) +2022-11-14 14:36:52,801 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0718) Prec@1 85.000 (87.810) Prec@5 99.000 (99.429) +2022-11-14 14:36:52,814 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0716) Prec@1 88.000 (87.818) Prec@5 99.000 (99.409) +2022-11-14 14:36:52,826 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0730) Prec@1 82.000 (87.565) Prec@5 98.000 (99.348) +2022-11-14 14:36:52,838 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0730) Prec@1 86.000 (87.500) Prec@5 100.000 (99.375) +2022-11-14 14:36:52,853 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0738) Prec@1 88.000 (87.520) Prec@5 99.000 (99.360) +2022-11-14 14:36:52,870 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0735) Prec@1 91.000 (87.654) Prec@5 100.000 (99.385) +2022-11-14 14:36:52,882 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0732) Prec@1 89.000 (87.704) Prec@5 100.000 (99.407) +2022-11-14 14:36:52,895 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0728) Prec@1 89.000 (87.750) Prec@5 100.000 (99.429) +2022-11-14 14:36:52,908 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0727) Prec@1 91.000 (87.862) Prec@5 99.000 (99.414) +2022-11-14 14:36:52,926 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0731) Prec@1 85.000 (87.767) Prec@5 100.000 (99.433) +2022-11-14 14:36:52,941 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0734) Prec@1 88.000 (87.774) Prec@5 100.000 (99.452) +2022-11-14 14:36:52,957 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0735) Prec@1 86.000 (87.719) Prec@5 100.000 (99.469) +2022-11-14 14:36:52,969 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0736) Prec@1 84.000 (87.606) Prec@5 100.000 (99.485) +2022-11-14 14:36:52,983 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0739) Prec@1 83.000 (87.471) Prec@5 99.000 (99.471) +2022-11-14 14:36:52,999 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0740) Prec@1 88.000 (87.486) Prec@5 99.000 (99.457) +2022-11-14 14:36:53,013 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0737) Prec@1 89.000 (87.528) Prec@5 100.000 (99.472) +2022-11-14 14:36:53,026 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0738) Prec@1 88.000 (87.541) Prec@5 99.000 (99.459) +2022-11-14 14:36:53,038 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0741) Prec@1 87.000 (87.526) Prec@5 99.000 (99.447) +2022-11-14 14:36:53,053 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0735) Prec@1 94.000 (87.692) Prec@5 99.000 (99.436) +2022-11-14 14:36:53,066 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0736) Prec@1 88.000 (87.700) Prec@5 99.000 (99.425) +2022-11-14 14:36:53,080 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0740) Prec@1 86.000 (87.659) Prec@5 98.000 (99.390) +2022-11-14 14:36:53,094 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0739) Prec@1 90.000 (87.714) Prec@5 98.000 (99.357) +2022-11-14 14:36:53,108 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0733) Prec@1 93.000 (87.837) Prec@5 98.000 (99.326) +2022-11-14 14:36:53,123 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0734) Prec@1 88.000 (87.841) Prec@5 99.000 (99.318) +2022-11-14 14:36:53,138 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0727) Prec@1 91.000 (87.911) Prec@5 100.000 (99.333) +2022-11-14 14:36:53,151 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0734) Prec@1 81.000 (87.761) Prec@5 99.000 (99.326) +2022-11-14 14:36:53,165 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0731) Prec@1 91.000 (87.830) Prec@5 100.000 (99.340) +2022-11-14 14:36:53,177 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0734) Prec@1 88.000 (87.833) Prec@5 98.000 (99.312) +2022-11-14 14:36:53,191 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0409 (0.0727) Prec@1 95.000 (87.980) Prec@5 100.000 (99.327) +2022-11-14 14:36:53,205 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1138 (0.0735) Prec@1 83.000 (87.880) Prec@5 100.000 (99.340) +2022-11-14 14:36:53,219 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0737) Prec@1 86.000 (87.843) Prec@5 100.000 (99.353) +2022-11-14 14:36:53,237 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0738) Prec@1 85.000 (87.788) Prec@5 100.000 (99.365) +2022-11-14 14:36:53,252 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0736) Prec@1 90.000 (87.830) Prec@5 99.000 (99.358) +2022-11-14 14:36:53,266 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0739) Prec@1 86.000 (87.796) Prec@5 99.000 (99.352) +2022-11-14 14:36:53,279 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0741) Prec@1 85.000 (87.745) Prec@5 100.000 (99.364) +2022-11-14 14:36:53,292 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0741) Prec@1 88.000 (87.750) Prec@5 99.000 (99.357) +2022-11-14 14:36:53,304 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0740) Prec@1 88.000 (87.754) Prec@5 100.000 (99.368) +2022-11-14 14:36:53,316 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0741) Prec@1 88.000 (87.759) Prec@5 99.000 (99.362) +2022-11-14 14:36:53,329 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0746) Prec@1 81.000 (87.644) Prec@5 100.000 (99.373) +2022-11-14 14:36:53,342 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0748) Prec@1 85.000 (87.600) Prec@5 100.000 (99.383) +2022-11-14 14:36:53,355 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0748) Prec@1 86.000 (87.574) Prec@5 100.000 (99.393) +2022-11-14 14:36:53,369 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0748) Prec@1 84.000 (87.516) Prec@5 100.000 (99.403) +2022-11-14 14:36:53,381 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0746) Prec@1 88.000 (87.524) Prec@5 100.000 (99.413) +2022-11-14 14:36:53,395 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0741) Prec@1 92.000 (87.594) Prec@5 100.000 (99.422) +2022-11-14 14:36:53,409 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0747) Prec@1 83.000 (87.523) Prec@5 98.000 (99.400) +2022-11-14 14:36:53,422 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0748) Prec@1 87.000 (87.515) Prec@5 99.000 (99.394) +2022-11-14 14:36:53,433 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0349 (0.0742) Prec@1 95.000 (87.627) Prec@5 100.000 (99.403) +2022-11-14 14:36:53,447 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0742) Prec@1 88.000 (87.632) Prec@5 98.000 (99.382) +2022-11-14 14:36:53,460 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0743) Prec@1 85.000 (87.594) Prec@5 100.000 (99.391) +2022-11-14 14:36:53,474 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0744) Prec@1 85.000 (87.557) Prec@5 100.000 (99.400) +2022-11-14 14:36:53,490 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0746) Prec@1 86.000 (87.535) Prec@5 98.000 (99.380) +2022-11-14 14:36:53,504 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0743) Prec@1 93.000 (87.611) Prec@5 100.000 (99.389) +2022-11-14 14:36:53,518 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0740) Prec@1 94.000 (87.699) Prec@5 99.000 (99.384) +2022-11-14 14:36:53,531 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0737) Prec@1 90.000 (87.730) Prec@5 100.000 (99.392) +2022-11-14 14:36:53,546 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0739) Prec@1 85.000 (87.693) Prec@5 100.000 (99.400) +2022-11-14 14:36:53,562 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0737) Prec@1 89.000 (87.711) Prec@5 99.000 (99.395) +2022-11-14 14:36:53,575 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0734) Prec@1 90.000 (87.740) Prec@5 98.000 (99.377) +2022-11-14 14:36:53,588 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0736) Prec@1 86.000 (87.718) Prec@5 100.000 (99.385) +2022-11-14 14:36:53,601 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0735) Prec@1 88.000 (87.722) Prec@5 100.000 (99.392) +2022-11-14 14:36:53,614 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0735) Prec@1 86.000 (87.700) Prec@5 100.000 (99.400) +2022-11-14 14:36:53,629 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0734) Prec@1 90.000 (87.728) Prec@5 97.000 (99.370) +2022-11-14 14:36:53,645 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0733) Prec@1 90.000 (87.756) Prec@5 99.000 (99.366) +2022-11-14 14:36:53,658 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0734) Prec@1 84.000 (87.711) Prec@5 100.000 (99.373) +2022-11-14 14:36:53,670 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0734) Prec@1 87.000 (87.702) Prec@5 99.000 (99.369) +2022-11-14 14:36:53,684 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0736) Prec@1 83.000 (87.647) Prec@5 99.000 (99.365) +2022-11-14 14:36:53,697 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0738) Prec@1 86.000 (87.628) Prec@5 99.000 (99.360) +2022-11-14 14:36:53,711 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0740) Prec@1 87.000 (87.621) Prec@5 100.000 (99.368) +2022-11-14 14:36:53,726 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0742) Prec@1 84.000 (87.580) Prec@5 100.000 (99.375) +2022-11-14 14:36:53,739 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0741) Prec@1 87.000 (87.573) Prec@5 100.000 (99.382) +2022-11-14 14:36:53,753 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0741) Prec@1 86.000 (87.556) Prec@5 99.000 (99.378) +2022-11-14 14:36:53,769 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0738) Prec@1 93.000 (87.615) Prec@5 100.000 (99.385) +2022-11-14 14:36:53,783 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0735) Prec@1 94.000 (87.685) Prec@5 99.000 (99.380) +2022-11-14 14:36:53,796 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0736) Prec@1 86.000 (87.667) Prec@5 99.000 (99.376) +2022-11-14 14:36:53,808 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0737) Prec@1 86.000 (87.649) Prec@5 98.000 (99.362) +2022-11-14 14:36:53,821 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0737) Prec@1 88.000 (87.653) Prec@5 98.000 (99.347) +2022-11-14 14:36:53,834 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0735) Prec@1 91.000 (87.688) Prec@5 100.000 (99.354) +2022-11-14 14:36:53,846 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0732) Prec@1 92.000 (87.732) Prec@5 99.000 (99.351) +2022-11-14 14:36:53,858 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0734) Prec@1 86.000 (87.714) Prec@5 100.000 (99.357) +2022-11-14 14:36:53,872 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0736) Prec@1 85.000 (87.687) Prec@5 100.000 (99.364) +2022-11-14 14:36:53,885 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0736) Prec@1 89.000 (87.700) Prec@5 100.000 (99.370) +2022-11-14 14:36:53,957 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:36:54,265 Epoch: [226][0/500] Time 0.032 (0.032) Data 0.220 (0.220) Loss 0.0482 (0.0482) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:36:54,494 Epoch: [226][10/500] Time 0.023 (0.021) Data 0.002 (0.022) Loss 0.0277 (0.0380) Prec@1 96.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:36:54,743 Epoch: [226][20/500] Time 0.021 (0.022) Data 0.002 (0.012) Loss 0.0355 (0.0372) Prec@1 96.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 14:36:55,006 Epoch: [226][30/500] Time 0.031 (0.022) Data 0.002 (0.009) Loss 0.0354 (0.0367) Prec@1 94.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 14:36:55,327 Epoch: [226][40/500] Time 0.030 (0.024) Data 0.002 (0.007) Loss 0.0299 (0.0354) Prec@1 97.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 14:36:55,665 Epoch: [226][50/500] Time 0.032 (0.025) Data 0.002 (0.006) Loss 0.0629 (0.0400) Prec@1 88.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:36:56,003 Epoch: [226][60/500] Time 0.029 (0.026) Data 0.002 (0.005) Loss 0.0524 (0.0417) Prec@1 90.000 (93.286) Prec@5 99.000 (99.714) +2022-11-14 14:36:56,346 Epoch: [226][70/500] Time 0.040 (0.027) Data 0.002 (0.005) Loss 0.0509 (0.0429) Prec@1 92.000 (93.125) Prec@5 100.000 (99.750) +2022-11-14 14:36:56,673 Epoch: [226][80/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0311 (0.0416) Prec@1 95.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:36:57,006 Epoch: [226][90/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0444 (0.0419) Prec@1 94.000 (93.400) Prec@5 99.000 (99.600) +2022-11-14 14:36:57,333 Epoch: [226][100/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0349 (0.0412) Prec@1 93.000 (93.364) Prec@5 99.000 (99.545) +2022-11-14 14:36:57,674 Epoch: [226][110/500] Time 0.040 (0.028) Data 0.002 (0.004) Loss 0.0308 (0.0404) Prec@1 96.000 (93.583) Prec@5 100.000 (99.583) +2022-11-14 14:36:58,007 Epoch: [226][120/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0201 (0.0388) Prec@1 97.000 (93.846) Prec@5 100.000 (99.615) +2022-11-14 14:36:58,350 Epoch: [226][130/500] Time 0.033 (0.028) Data 0.002 (0.003) Loss 0.0408 (0.0390) Prec@1 94.000 (93.857) Prec@5 100.000 (99.643) +2022-11-14 14:36:58,689 Epoch: [226][140/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0237 (0.0379) Prec@1 96.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 14:36:59,024 Epoch: [226][150/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0415 (0.0382) Prec@1 92.000 (93.875) Prec@5 100.000 (99.688) +2022-11-14 14:36:59,372 Epoch: [226][160/500] Time 0.031 (0.028) Data 0.002 (0.003) Loss 0.0481 (0.0387) Prec@1 90.000 (93.647) Prec@5 100.000 (99.706) +2022-11-14 14:36:59,707 Epoch: [226][170/500] Time 0.036 (0.028) Data 0.002 (0.003) Loss 0.0563 (0.0397) Prec@1 89.000 (93.389) Prec@5 100.000 (99.722) +2022-11-14 14:37:00,050 Epoch: [226][180/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0376 (0.0396) Prec@1 92.000 (93.316) Prec@5 99.000 (99.684) +2022-11-14 14:37:00,389 Epoch: [226][190/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0301 (0.0391) Prec@1 95.000 (93.400) Prec@5 100.000 (99.700) +2022-11-14 14:37:00,733 Epoch: [226][200/500] Time 0.039 (0.029) Data 0.002 (0.003) Loss 0.0473 (0.0395) Prec@1 93.000 (93.381) Prec@5 99.000 (99.667) +2022-11-14 14:37:01,067 Epoch: [226][210/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0304 (0.0391) Prec@1 94.000 (93.409) Prec@5 100.000 (99.682) +2022-11-14 14:37:01,442 Epoch: [226][220/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0220 (0.0384) Prec@1 97.000 (93.565) Prec@5 100.000 (99.696) +2022-11-14 14:37:01,930 Epoch: [226][230/500] Time 0.051 (0.030) Data 0.002 (0.003) Loss 0.0447 (0.0386) Prec@1 93.000 (93.542) Prec@5 100.000 (99.708) +2022-11-14 14:37:02,394 Epoch: [226][240/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0459 (0.0389) Prec@1 92.000 (93.480) Prec@5 100.000 (99.720) +2022-11-14 14:37:02,874 Epoch: [226][250/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0447 (0.0391) Prec@1 93.000 (93.462) Prec@5 100.000 (99.731) +2022-11-14 14:37:03,377 Epoch: [226][260/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0342 (0.0390) Prec@1 95.000 (93.519) Prec@5 99.000 (99.704) +2022-11-14 14:37:03,881 Epoch: [226][270/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0336 (0.0388) Prec@1 93.000 (93.500) Prec@5 100.000 (99.714) +2022-11-14 14:37:04,371 Epoch: [226][280/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0190 (0.0381) Prec@1 98.000 (93.655) Prec@5 100.000 (99.724) +2022-11-14 14:37:04,888 Epoch: [226][290/500] Time 0.063 (0.033) Data 0.002 (0.003) Loss 0.0277 (0.0377) Prec@1 96.000 (93.733) Prec@5 100.000 (99.733) +2022-11-14 14:37:05,415 Epoch: [226][300/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0556 (0.0383) Prec@1 90.000 (93.613) Prec@5 100.000 (99.742) +2022-11-14 14:37:05,943 Epoch: [226][310/500] Time 0.054 (0.034) Data 0.002 (0.003) Loss 0.0464 (0.0386) Prec@1 92.000 (93.562) Prec@5 100.000 (99.750) +2022-11-14 14:37:06,442 Epoch: [226][320/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0464 (0.0388) Prec@1 93.000 (93.545) Prec@5 100.000 (99.758) +2022-11-14 14:37:06,941 Epoch: [226][330/500] Time 0.049 (0.034) Data 0.002 (0.003) Loss 0.0338 (0.0387) Prec@1 93.000 (93.529) Prec@5 100.000 (99.765) +2022-11-14 14:37:07,438 Epoch: [226][340/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0563 (0.0392) Prec@1 92.000 (93.486) Prec@5 100.000 (99.771) +2022-11-14 14:37:07,964 Epoch: [226][350/500] Time 0.042 (0.035) Data 0.003 (0.002) Loss 0.0236 (0.0387) Prec@1 96.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 14:37:08,439 Epoch: [226][360/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0413 (0.0388) Prec@1 94.000 (93.568) Prec@5 99.000 (99.757) +2022-11-14 14:37:08,946 Epoch: [226][370/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0351 (0.0387) Prec@1 93.000 (93.553) Prec@5 100.000 (99.763) +2022-11-14 14:37:09,470 Epoch: [226][380/500] Time 0.049 (0.036) Data 0.002 (0.002) Loss 0.0123 (0.0380) Prec@1 99.000 (93.692) Prec@5 100.000 (99.769) +2022-11-14 14:37:09,994 Epoch: [226][390/500] Time 0.056 (0.036) Data 0.002 (0.002) Loss 0.0329 (0.0379) Prec@1 96.000 (93.750) Prec@5 99.000 (99.750) +2022-11-14 14:37:10,516 Epoch: [226][400/500] Time 0.062 (0.036) Data 0.002 (0.002) Loss 0.0830 (0.0390) Prec@1 88.000 (93.610) Prec@5 100.000 (99.756) +2022-11-14 14:37:11,027 Epoch: [226][410/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0296 (0.0388) Prec@1 96.000 (93.667) Prec@5 100.000 (99.762) +2022-11-14 14:37:11,529 Epoch: [226][420/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.0464 (0.0390) Prec@1 91.000 (93.605) Prec@5 100.000 (99.767) +2022-11-14 14:37:12,023 Epoch: [226][430/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0501 (0.0392) Prec@1 90.000 (93.523) Prec@5 100.000 (99.773) +2022-11-14 14:37:12,532 Epoch: [226][440/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0298 (0.0390) Prec@1 94.000 (93.533) Prec@5 99.000 (99.756) +2022-11-14 14:37:13,030 Epoch: [226][450/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0290 (0.0388) Prec@1 95.000 (93.565) Prec@5 100.000 (99.761) +2022-11-14 14:37:13,506 Epoch: [226][460/500] Time 0.045 (0.037) Data 0.002 (0.002) Loss 0.0430 (0.0389) Prec@1 93.000 (93.553) Prec@5 99.000 (99.745) +2022-11-14 14:37:13,998 Epoch: [226][470/500] Time 0.048 (0.037) Data 0.002 (0.002) Loss 0.0335 (0.0388) Prec@1 94.000 (93.562) Prec@5 100.000 (99.750) +2022-11-14 14:37:14,462 Epoch: [226][480/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0290 (0.0386) Prec@1 96.000 (93.612) Prec@5 100.000 (99.755) +2022-11-14 14:37:14,963 Epoch: [226][490/500] Time 0.042 (0.038) Data 0.003 (0.002) Loss 0.0476 (0.0387) Prec@1 91.000 (93.560) Prec@5 100.000 (99.760) +2022-11-14 14:37:15,432 Epoch: [226][499/500] Time 0.047 (0.038) Data 0.002 (0.002) Loss 0.0199 (0.0384) Prec@1 97.000 (93.627) Prec@5 100.000 (99.765) +2022-11-14 14:37:15,721 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0727 (0.0727) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:37:15,733 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0644) Prec@1 92.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 14:37:15,742 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0672) Prec@1 89.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 14:37:15,754 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0706) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:37:15,763 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0748) Prec@1 86.000 (88.800) Prec@5 100.000 (99.600) +2022-11-14 14:37:15,774 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0324 (0.0677) Prec@1 94.000 (89.667) Prec@5 99.000 (99.500) +2022-11-14 14:37:15,785 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0676) Prec@1 89.000 (89.571) Prec@5 100.000 (99.571) +2022-11-14 14:37:15,800 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0694) Prec@1 89.000 (89.500) Prec@5 100.000 (99.625) +2022-11-14 14:37:15,813 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0713) Prec@1 88.000 (89.333) Prec@5 99.000 (99.556) +2022-11-14 14:37:15,825 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0728) Prec@1 84.000 (88.800) Prec@5 99.000 (99.500) +2022-11-14 14:37:15,836 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0327 (0.0691) Prec@1 96.000 (89.455) Prec@5 100.000 (99.545) +2022-11-14 14:37:15,848 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0727) Prec@1 81.000 (88.750) Prec@5 98.000 (99.417) +2022-11-14 14:37:15,860 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0504 (0.0710) Prec@1 89.000 (88.769) Prec@5 100.000 (99.462) +2022-11-14 14:37:15,877 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0720) Prec@1 86.000 (88.571) Prec@5 100.000 (99.500) +2022-11-14 14:37:15,892 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0719) Prec@1 87.000 (88.467) Prec@5 99.000 (99.467) +2022-11-14 14:37:15,909 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0725) Prec@1 85.000 (88.250) Prec@5 99.000 (99.438) +2022-11-14 14:37:15,925 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0714) Prec@1 91.000 (88.412) Prec@5 98.000 (99.353) +2022-11-14 14:37:15,941 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0728) Prec@1 86.000 (88.278) Prec@5 100.000 (99.389) +2022-11-14 14:37:15,958 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0740) Prec@1 83.000 (88.000) Prec@5 97.000 (99.263) +2022-11-14 14:37:15,972 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0743) Prec@1 88.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 14:37:15,988 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0748) Prec@1 86.000 (87.905) Prec@5 99.000 (99.238) +2022-11-14 14:37:16,006 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0753) Prec@1 86.000 (87.818) Prec@5 100.000 (99.273) +2022-11-14 14:37:16,024 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1221 (0.0773) Prec@1 83.000 (87.609) Prec@5 97.000 (99.174) +2022-11-14 14:37:16,041 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0775) Prec@1 87.000 (87.583) Prec@5 100.000 (99.208) +2022-11-14 14:37:16,055 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0783) Prec@1 85.000 (87.480) Prec@5 99.000 (99.200) +2022-11-14 14:37:16,069 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0791) Prec@1 82.000 (87.269) Prec@5 99.000 (99.192) +2022-11-14 14:37:16,084 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0789) Prec@1 88.000 (87.296) Prec@5 100.000 (99.222) +2022-11-14 14:37:16,099 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0784) Prec@1 88.000 (87.321) Prec@5 100.000 (99.250) +2022-11-14 14:37:16,116 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0780) Prec@1 89.000 (87.379) Prec@5 99.000 (99.241) +2022-11-14 14:37:16,133 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0776) Prec@1 86.000 (87.333) Prec@5 99.000 (99.233) +2022-11-14 14:37:16,148 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0774) Prec@1 88.000 (87.355) Prec@5 100.000 (99.258) +2022-11-14 14:37:16,163 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0769) Prec@1 91.000 (87.469) Prec@5 99.000 (99.250) +2022-11-14 14:37:16,179 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0766) Prec@1 88.000 (87.485) Prec@5 100.000 (99.273) +2022-11-14 14:37:16,194 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0773) Prec@1 83.000 (87.353) Prec@5 97.000 (99.206) +2022-11-14 14:37:16,209 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0777) Prec@1 82.000 (87.200) Prec@5 99.000 (99.200) +2022-11-14 14:37:16,223 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0773) Prec@1 89.000 (87.250) Prec@5 99.000 (99.194) +2022-11-14 14:37:16,239 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0771) Prec@1 88.000 (87.270) Prec@5 98.000 (99.162) +2022-11-14 14:37:16,256 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0773) Prec@1 84.000 (87.184) Prec@5 99.000 (99.158) +2022-11-14 14:37:16,271 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0767) Prec@1 92.000 (87.308) Prec@5 99.000 (99.154) +2022-11-14 14:37:16,289 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0764) Prec@1 89.000 (87.350) Prec@5 98.000 (99.125) +2022-11-14 14:37:16,309 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0768) Prec@1 86.000 (87.317) Prec@5 99.000 (99.122) +2022-11-14 14:37:16,326 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0768) Prec@1 88.000 (87.333) Prec@5 99.000 (99.119) +2022-11-14 14:37:16,341 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0762) Prec@1 93.000 (87.465) Prec@5 100.000 (99.140) +2022-11-14 14:37:16,357 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0760) Prec@1 89.000 (87.500) Prec@5 98.000 (99.114) +2022-11-14 14:37:16,375 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0755) Prec@1 92.000 (87.600) Prec@5 98.000 (99.089) +2022-11-14 14:37:16,390 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1212 (0.0765) Prec@1 82.000 (87.478) Prec@5 99.000 (99.087) +2022-11-14 14:37:16,406 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0761) Prec@1 91.000 (87.553) Prec@5 100.000 (99.106) +2022-11-14 14:37:16,422 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0763) Prec@1 87.000 (87.542) Prec@5 97.000 (99.062) +2022-11-14 14:37:16,438 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0760) Prec@1 90.000 (87.592) Prec@5 100.000 (99.082) +2022-11-14 14:37:16,457 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0766) Prec@1 82.000 (87.480) Prec@5 99.000 (99.080) +2022-11-14 14:37:16,472 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0764) Prec@1 89.000 (87.510) Prec@5 99.000 (99.078) +2022-11-14 14:37:16,487 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0764) Prec@1 87.000 (87.500) Prec@5 99.000 (99.077) +2022-11-14 14:37:16,503 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0765) Prec@1 85.000 (87.453) Prec@5 99.000 (99.075) +2022-11-14 14:37:16,520 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0765) Prec@1 87.000 (87.444) Prec@5 100.000 (99.093) +2022-11-14 14:37:16,535 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0765) Prec@1 85.000 (87.400) Prec@5 100.000 (99.109) +2022-11-14 14:37:16,549 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0764) Prec@1 89.000 (87.429) Prec@5 99.000 (99.107) +2022-11-14 14:37:16,564 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0764) Prec@1 89.000 (87.456) Prec@5 100.000 (99.123) +2022-11-14 14:37:16,582 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0763) Prec@1 88.000 (87.466) Prec@5 100.000 (99.138) +2022-11-14 14:37:16,600 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0765) Prec@1 86.000 (87.441) Prec@5 98.000 (99.119) +2022-11-14 14:37:16,616 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0766) Prec@1 86.000 (87.417) Prec@5 99.000 (99.117) +2022-11-14 14:37:16,633 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0766) Prec@1 86.000 (87.393) Prec@5 99.000 (99.115) +2022-11-14 14:37:16,649 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0767) Prec@1 86.000 (87.371) Prec@5 99.000 (99.113) +2022-11-14 14:37:16,665 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0764) Prec@1 90.000 (87.413) Prec@5 99.000 (99.111) +2022-11-14 14:37:16,681 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0759) Prec@1 94.000 (87.516) Prec@5 100.000 (99.125) +2022-11-14 14:37:16,701 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1278 (0.0767) Prec@1 79.000 (87.385) Prec@5 100.000 (99.138) +2022-11-14 14:37:16,717 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0769) Prec@1 88.000 (87.394) Prec@5 98.000 (99.121) +2022-11-14 14:37:16,733 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0764) Prec@1 93.000 (87.478) Prec@5 100.000 (99.134) +2022-11-14 14:37:16,748 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0763) Prec@1 88.000 (87.485) Prec@5 99.000 (99.132) +2022-11-14 14:37:16,766 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0759) Prec@1 91.000 (87.536) Prec@5 100.000 (99.145) +2022-11-14 14:37:16,785 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0761) Prec@1 86.000 (87.514) Prec@5 99.000 (99.143) +2022-11-14 14:37:16,800 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0764) Prec@1 85.000 (87.479) Prec@5 98.000 (99.127) +2022-11-14 14:37:16,816 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0762) Prec@1 89.000 (87.500) Prec@5 100.000 (99.139) +2022-11-14 14:37:16,833 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0758) Prec@1 93.000 (87.575) Prec@5 99.000 (99.137) +2022-11-14 14:37:16,848 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0755) Prec@1 92.000 (87.635) Prec@5 100.000 (99.149) +2022-11-14 14:37:16,863 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0760) Prec@1 81.000 (87.547) Prec@5 100.000 (99.160) +2022-11-14 14:37:16,878 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0757) Prec@1 90.000 (87.579) Prec@5 99.000 (99.158) +2022-11-14 14:37:16,893 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0755) Prec@1 89.000 (87.597) Prec@5 99.000 (99.156) +2022-11-14 14:37:16,908 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0755) Prec@1 87.000 (87.590) Prec@5 100.000 (99.167) +2022-11-14 14:37:16,924 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0758) Prec@1 84.000 (87.544) Prec@5 100.000 (99.177) +2022-11-14 14:37:16,940 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0756) Prec@1 92.000 (87.600) Prec@5 100.000 (99.188) +2022-11-14 14:37:16,956 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0754) Prec@1 89.000 (87.617) Prec@5 99.000 (99.185) +2022-11-14 14:37:16,971 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0754) Prec@1 90.000 (87.646) Prec@5 99.000 (99.183) +2022-11-14 14:37:16,987 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0754) Prec@1 88.000 (87.651) Prec@5 100.000 (99.193) +2022-11-14 14:37:17,003 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0754) Prec@1 88.000 (87.655) Prec@5 98.000 (99.179) +2022-11-14 14:37:17,021 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0757) Prec@1 85.000 (87.624) Prec@5 99.000 (99.176) +2022-11-14 14:37:17,036 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0760) Prec@1 85.000 (87.593) Prec@5 99.000 (99.174) +2022-11-14 14:37:17,052 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0758) Prec@1 90.000 (87.621) Prec@5 99.000 (99.172) +2022-11-14 14:37:17,069 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0758) Prec@1 87.000 (87.614) Prec@5 100.000 (99.182) +2022-11-14 14:37:17,084 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0758) Prec@1 86.000 (87.596) Prec@5 100.000 (99.191) +2022-11-14 14:37:17,101 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0758) Prec@1 88.000 (87.600) Prec@5 98.000 (99.178) +2022-11-14 14:37:17,117 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0757) Prec@1 90.000 (87.626) Prec@5 100.000 (99.187) +2022-11-14 14:37:17,133 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0756) Prec@1 90.000 (87.652) Prec@5 99.000 (99.185) +2022-11-14 14:37:17,150 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0755) Prec@1 88.000 (87.656) Prec@5 100.000 (99.194) +2022-11-14 14:37:17,166 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0756) Prec@1 88.000 (87.660) Prec@5 98.000 (99.181) +2022-11-14 14:37:17,180 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0755) Prec@1 91.000 (87.695) Prec@5 99.000 (99.179) +2022-11-14 14:37:17,195 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0755) Prec@1 88.000 (87.698) Prec@5 99.000 (99.177) +2022-11-14 14:37:17,210 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0752) Prec@1 91.000 (87.732) Prec@5 99.000 (99.175) +2022-11-14 14:37:17,225 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0754) Prec@1 85.000 (87.704) Prec@5 100.000 (99.184) +2022-11-14 14:37:17,245 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0757) Prec@1 86.000 (87.687) Prec@5 100.000 (99.192) +2022-11-14 14:37:17,260 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0755) Prec@1 87.000 (87.680) Prec@5 100.000 (99.200) +2022-11-14 14:37:17,320 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:37:17,636 Epoch: [227][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.0317 (0.0317) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:37:17,854 Epoch: [227][10/500] Time 0.018 (0.020) Data 0.001 (0.023) Loss 0.0385 (0.0351) Prec@1 94.000 (95.000) Prec@5 99.000 (99.500) +2022-11-14 14:37:18,061 Epoch: [227][20/500] Time 0.017 (0.019) Data 0.002 (0.013) Loss 0.0439 (0.0381) Prec@1 94.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 14:37:18,266 Epoch: [227][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.0617 (0.0440) Prec@1 90.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 14:37:18,563 Epoch: [227][40/500] Time 0.032 (0.020) Data 0.002 (0.007) Loss 0.0171 (0.0386) Prec@1 98.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 14:37:18,937 Epoch: [227][50/500] Time 0.042 (0.023) Data 0.002 (0.006) Loss 0.0472 (0.0400) Prec@1 93.000 (94.167) Prec@5 100.000 (99.667) +2022-11-14 14:37:19,291 Epoch: [227][60/500] Time 0.031 (0.024) Data 0.002 (0.006) Loss 0.0371 (0.0396) Prec@1 95.000 (94.286) Prec@5 99.000 (99.571) +2022-11-14 14:37:19,645 Epoch: [227][70/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0360 (0.0392) Prec@1 94.000 (94.250) Prec@5 100.000 (99.625) +2022-11-14 14:37:20,002 Epoch: [227][80/500] Time 0.033 (0.026) Data 0.002 (0.005) Loss 0.0401 (0.0393) Prec@1 92.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 14:37:20,364 Epoch: [227][90/500] Time 0.036 (0.027) Data 0.002 (0.004) Loss 0.0391 (0.0392) Prec@1 94.000 (94.000) Prec@5 100.000 (99.700) +2022-11-14 14:37:20,730 Epoch: [227][100/500] Time 0.037 (0.027) Data 0.002 (0.004) Loss 0.0310 (0.0385) Prec@1 96.000 (94.182) Prec@5 100.000 (99.727) +2022-11-14 14:37:21,088 Epoch: [227][110/500] Time 0.035 (0.028) Data 0.002 (0.004) Loss 0.0397 (0.0386) Prec@1 93.000 (94.083) Prec@5 98.000 (99.583) +2022-11-14 14:37:21,454 Epoch: [227][120/500] Time 0.033 (0.028) Data 0.002 (0.004) Loss 0.0312 (0.0380) Prec@1 95.000 (94.154) Prec@5 100.000 (99.615) +2022-11-14 14:37:21,819 Epoch: [227][130/500] Time 0.042 (0.028) Data 0.002 (0.004) Loss 0.0359 (0.0379) Prec@1 94.000 (94.143) Prec@5 100.000 (99.643) +2022-11-14 14:37:22,184 Epoch: [227][140/500] Time 0.038 (0.029) Data 0.002 (0.003) Loss 0.0353 (0.0377) Prec@1 95.000 (94.200) Prec@5 100.000 (99.667) +2022-11-14 14:37:22,542 Epoch: [227][150/500] Time 0.033 (0.029) Data 0.002 (0.003) Loss 0.0302 (0.0372) Prec@1 96.000 (94.312) Prec@5 100.000 (99.688) +2022-11-14 14:37:22,906 Epoch: [227][160/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0487 (0.0379) Prec@1 91.000 (94.118) Prec@5 100.000 (99.706) +2022-11-14 14:37:23,278 Epoch: [227][170/500] Time 0.031 (0.029) Data 0.002 (0.003) Loss 0.0193 (0.0369) Prec@1 97.000 (94.278) Prec@5 100.000 (99.722) +2022-11-14 14:37:23,644 Epoch: [227][180/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0332 (0.0367) Prec@1 95.000 (94.316) Prec@5 100.000 (99.737) +2022-11-14 14:37:24,001 Epoch: [227][190/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0453 (0.0371) Prec@1 93.000 (94.250) Prec@5 99.000 (99.700) +2022-11-14 14:37:24,371 Epoch: [227][200/500] Time 0.038 (0.030) Data 0.001 (0.003) Loss 0.0406 (0.0373) Prec@1 93.000 (94.190) Prec@5 100.000 (99.714) +2022-11-14 14:37:24,730 Epoch: [227][210/500] Time 0.029 (0.030) Data 0.002 (0.003) Loss 0.0438 (0.0376) Prec@1 93.000 (94.136) Prec@5 100.000 (99.727) +2022-11-14 14:37:25,093 Epoch: [227][220/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0125 (0.0365) Prec@1 99.000 (94.348) Prec@5 100.000 (99.739) +2022-11-14 14:37:25,451 Epoch: [227][230/500] Time 0.038 (0.030) Data 0.002 (0.003) Loss 0.0373 (0.0365) Prec@1 95.000 (94.375) Prec@5 99.000 (99.708) +2022-11-14 14:37:25,825 Epoch: [227][240/500] Time 0.038 (0.030) Data 0.002 (0.003) Loss 0.0245 (0.0360) Prec@1 96.000 (94.440) Prec@5 100.000 (99.720) +2022-11-14 14:37:26,183 Epoch: [227][250/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0264 (0.0357) Prec@1 96.000 (94.500) Prec@5 100.000 (99.731) +2022-11-14 14:37:26,551 Epoch: [227][260/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0338 (0.0356) Prec@1 95.000 (94.519) Prec@5 100.000 (99.741) +2022-11-14 14:37:26,915 Epoch: [227][270/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0575 (0.0364) Prec@1 90.000 (94.357) Prec@5 100.000 (99.750) +2022-11-14 14:37:27,277 Epoch: [227][280/500] Time 0.034 (0.030) Data 0.001 (0.003) Loss 0.0410 (0.0365) Prec@1 93.000 (94.310) Prec@5 100.000 (99.759) +2022-11-14 14:37:27,634 Epoch: [227][290/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0412 (0.0367) Prec@1 92.000 (94.233) Prec@5 99.000 (99.733) +2022-11-14 14:37:28,006 Epoch: [227][300/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.0368 (0.0367) Prec@1 93.000 (94.194) Prec@5 100.000 (99.742) +2022-11-14 14:37:28,374 Epoch: [227][310/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0421 (0.0369) Prec@1 94.000 (94.188) Prec@5 99.000 (99.719) +2022-11-14 14:37:28,728 Epoch: [227][320/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0299 (0.0367) Prec@1 95.000 (94.212) Prec@5 99.000 (99.697) +2022-11-14 14:37:29,096 Epoch: [227][330/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0248 (0.0363) Prec@1 97.000 (94.294) Prec@5 100.000 (99.706) +2022-11-14 14:37:29,462 Epoch: [227][340/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0416 (0.0365) Prec@1 93.000 (94.257) Prec@5 100.000 (99.714) +2022-11-14 14:37:29,864 Epoch: [227][350/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0450 (0.0367) Prec@1 92.000 (94.194) Prec@5 100.000 (99.722) +2022-11-14 14:37:30,238 Epoch: [227][360/500] Time 0.027 (0.031) Data 0.002 (0.003) Loss 0.0541 (0.0372) Prec@1 91.000 (94.108) Prec@5 100.000 (99.730) +2022-11-14 14:37:30,616 Epoch: [227][370/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0346 (0.0371) Prec@1 94.000 (94.105) Prec@5 100.000 (99.737) +2022-11-14 14:37:31,025 Epoch: [227][380/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0384 (0.0371) Prec@1 94.000 (94.103) Prec@5 99.000 (99.718) +2022-11-14 14:37:31,403 Epoch: [227][390/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0527 (0.0375) Prec@1 92.000 (94.050) Prec@5 98.000 (99.675) +2022-11-14 14:37:31,771 Epoch: [227][400/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0321 (0.0374) Prec@1 96.000 (94.098) Prec@5 100.000 (99.683) +2022-11-14 14:37:32,135 Epoch: [227][410/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0226 (0.0370) Prec@1 96.000 (94.143) Prec@5 100.000 (99.690) +2022-11-14 14:37:32,481 Epoch: [227][420/500] Time 0.035 (0.031) Data 0.002 (0.002) Loss 0.0408 (0.0371) Prec@1 94.000 (94.140) Prec@5 100.000 (99.698) +2022-11-14 14:37:32,860 Epoch: [227][430/500] Time 0.026 (0.031) Data 0.002 (0.002) Loss 0.0426 (0.0373) Prec@1 94.000 (94.136) Prec@5 100.000 (99.705) +2022-11-14 14:37:33,223 Epoch: [227][440/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0424 (0.0374) Prec@1 94.000 (94.133) Prec@5 99.000 (99.689) +2022-11-14 14:37:33,601 Epoch: [227][450/500] Time 0.029 (0.031) Data 0.002 (0.002) Loss 0.0342 (0.0373) Prec@1 94.000 (94.130) Prec@5 100.000 (99.696) +2022-11-14 14:37:33,972 Epoch: [227][460/500] Time 0.030 (0.031) Data 0.002 (0.002) Loss 0.0545 (0.0377) Prec@1 92.000 (94.085) Prec@5 100.000 (99.702) +2022-11-14 14:37:34,332 Epoch: [227][470/500] Time 0.032 (0.031) Data 0.002 (0.002) Loss 0.0374 (0.0377) Prec@1 94.000 (94.083) Prec@5 100.000 (99.708) +2022-11-14 14:37:34,687 Epoch: [227][480/500] Time 0.034 (0.031) Data 0.001 (0.002) Loss 0.0647 (0.0382) Prec@1 90.000 (94.000) Prec@5 100.000 (99.714) +2022-11-14 14:37:35,058 Epoch: [227][490/500] Time 0.033 (0.031) Data 0.002 (0.002) Loss 0.0441 (0.0383) Prec@1 92.000 (93.960) Prec@5 100.000 (99.720) +2022-11-14 14:37:35,396 Epoch: [227][499/500] Time 0.040 (0.031) Data 0.002 (0.002) Loss 0.0618 (0.0388) Prec@1 90.000 (93.882) Prec@5 98.000 (99.686) +2022-11-14 14:37:35,681 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0648 (0.0648) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:37:35,689 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0677) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:37:35,698 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0678) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:37:35,710 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0673) Prec@1 88.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 14:37:35,719 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0668) Prec@1 86.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 14:37:35,730 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0640) Prec@1 92.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 14:37:35,742 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0647) Prec@1 89.000 (89.286) Prec@5 100.000 (99.714) 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(0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0732) Prec@1 88.000 (88.143) Prec@5 100.000 (99.714) +2022-11-14 14:37:35,834 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0735) Prec@1 87.000 (88.067) Prec@5 100.000 (99.733) +2022-11-14 14:37:35,846 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0740) Prec@1 82.000 (87.688) Prec@5 99.000 (99.688) +2022-11-14 14:37:35,858 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0726) Prec@1 93.000 (88.000) Prec@5 98.000 (99.588) +2022-11-14 14:37:35,869 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0751) Prec@1 84.000 (87.778) Prec@5 98.000 (99.500) +2022-11-14 14:37:35,879 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0760) Prec@1 83.000 (87.526) Prec@5 97.000 (99.368) +2022-11-14 14:37:35,890 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0769) Prec@1 88.000 (87.550) Prec@5 98.000 (99.300) +2022-11-14 14:37:35,900 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0770) Prec@1 85.000 (87.429) Prec@5 99.000 (99.286) +2022-11-14 14:37:35,912 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0776) Prec@1 84.000 (87.273) Prec@5 100.000 (99.318) +2022-11-14 14:37:35,925 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0782) Prec@1 85.000 (87.174) Prec@5 99.000 (99.304) +2022-11-14 14:37:35,938 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0777) Prec@1 88.000 (87.208) Prec@5 100.000 (99.333) +2022-11-14 14:37:35,951 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0782) Prec@1 87.000 (87.200) Prec@5 100.000 (99.360) +2022-11-14 14:37:35,964 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0782) Prec@1 87.000 (87.192) Prec@5 99.000 (99.346) +2022-11-14 14:37:35,978 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0782) Prec@1 88.000 (87.222) Prec@5 100.000 (99.370) +2022-11-14 14:37:35,991 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0774) Prec@1 91.000 (87.357) Prec@5 100.000 (99.393) +2022-11-14 14:37:36,004 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0772) Prec@1 89.000 (87.414) Prec@5 98.000 (99.345) +2022-11-14 14:37:36,017 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0767) Prec@1 91.000 (87.533) Prec@5 100.000 (99.367) +2022-11-14 14:37:36,030 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0770) Prec@1 85.000 (87.452) Prec@5 100.000 (99.387) +2022-11-14 14:37:36,043 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0779) Prec@1 84.000 (87.344) Prec@5 100.000 (99.406) +2022-11-14 14:37:36,056 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0782) Prec@1 85.000 (87.273) Prec@5 98.000 (99.364) +2022-11-14 14:37:36,069 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0788) Prec@1 83.000 (87.147) Prec@5 100.000 (99.382) +2022-11-14 14:37:36,082 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0786) Prec@1 89.000 (87.200) Prec@5 96.000 (99.286) +2022-11-14 14:37:36,095 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0785) Prec@1 85.000 (87.139) Prec@5 99.000 (99.278) +2022-11-14 14:37:36,109 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0784) Prec@1 88.000 (87.162) Prec@5 99.000 (99.270) +2022-11-14 14:37:36,122 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.0792) Prec@1 81.000 (87.000) Prec@5 99.000 (99.263) +2022-11-14 14:37:36,134 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0788) Prec@1 89.000 (87.051) Prec@5 99.000 (99.256) +2022-11-14 14:37:36,148 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0783) Prec@1 90.000 (87.125) Prec@5 99.000 (99.250) +2022-11-14 14:37:36,161 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1114 (0.0791) Prec@1 81.000 (86.976) Prec@5 98.000 (99.220) +2022-11-14 14:37:36,174 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0789) Prec@1 88.000 (87.000) Prec@5 98.000 (99.190) +2022-11-14 14:37:36,187 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0781) Prec@1 90.000 (87.070) Prec@5 100.000 (99.209) +2022-11-14 14:37:36,199 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0785) Prec@1 84.000 (87.000) Prec@5 98.000 (99.182) +2022-11-14 14:37:36,211 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0781) Prec@1 92.000 (87.111) Prec@5 99.000 (99.178) +2022-11-14 14:37:36,225 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0786) Prec@1 81.000 (86.978) Prec@5 99.000 (99.174) +2022-11-14 14:37:36,238 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0785) Prec@1 87.000 (86.979) Prec@5 99.000 (99.170) +2022-11-14 14:37:36,251 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1272 (0.0795) Prec@1 78.000 (86.792) Prec@5 99.000 (99.167) +2022-11-14 14:37:36,264 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0789) Prec@1 91.000 (86.878) Prec@5 99.000 (99.163) +2022-11-14 14:37:36,277 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1238 (0.0798) Prec@1 79.000 (86.720) Prec@5 99.000 (99.160) +2022-11-14 14:37:36,289 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0795) Prec@1 89.000 (86.765) Prec@5 100.000 (99.176) +2022-11-14 14:37:36,301 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0795) Prec@1 87.000 (86.769) Prec@5 100.000 (99.192) +2022-11-14 14:37:36,314 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0795) Prec@1 86.000 (86.755) Prec@5 100.000 (99.208) +2022-11-14 14:37:36,329 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0794) Prec@1 89.000 (86.796) Prec@5 99.000 (99.204) +2022-11-14 14:37:36,343 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0795) Prec@1 88.000 (86.818) Prec@5 100.000 (99.218) +2022-11-14 14:37:36,356 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0792) Prec@1 91.000 (86.893) Prec@5 99.000 (99.214) +2022-11-14 14:37:36,369 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0790) Prec@1 87.000 (86.895) Prec@5 100.000 (99.228) +2022-11-14 14:37:36,381 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0789) Prec@1 88.000 (86.914) Prec@5 100.000 (99.241) +2022-11-14 14:37:36,393 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0792) Prec@1 80.000 (86.797) Prec@5 100.000 (99.254) +2022-11-14 14:37:36,404 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0792) Prec@1 88.000 (86.817) Prec@5 98.000 (99.233) +2022-11-14 14:37:36,418 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0796) Prec@1 82.000 (86.738) Prec@5 100.000 (99.246) +2022-11-14 14:37:36,430 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0797) Prec@1 86.000 (86.726) Prec@5 98.000 (99.226) +2022-11-14 14:37:36,442 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0793) Prec@1 90.000 (86.778) Prec@5 100.000 (99.238) +2022-11-14 14:37:36,454 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0790) Prec@1 87.000 (86.781) Prec@5 99.000 (99.234) +2022-11-14 14:37:36,467 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0796) Prec@1 82.000 (86.708) Prec@5 97.000 (99.200) +2022-11-14 14:37:36,480 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0794) Prec@1 88.000 (86.727) Prec@5 99.000 (99.197) +2022-11-14 14:37:36,492 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0791) Prec@1 91.000 (86.791) Prec@5 98.000 (99.179) +2022-11-14 14:37:36,504 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0790) Prec@1 89.000 (86.824) Prec@5 100.000 (99.191) +2022-11-14 14:37:36,517 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0790) Prec@1 89.000 (86.855) Prec@5 99.000 (99.188) +2022-11-14 14:37:36,530 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0791) Prec@1 88.000 (86.871) Prec@5 99.000 (99.186) +2022-11-14 14:37:36,543 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.0796) Prec@1 81.000 (86.789) Prec@5 99.000 (99.183) +2022-11-14 14:37:36,556 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0795) Prec@1 88.000 (86.806) Prec@5 99.000 (99.181) +2022-11-14 14:37:36,568 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0793) Prec@1 92.000 (86.877) Prec@5 100.000 (99.192) +2022-11-14 14:37:36,579 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0394 (0.0788) Prec@1 94.000 (86.973) Prec@5 100.000 (99.203) +2022-11-14 14:37:36,591 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0792) Prec@1 83.000 (86.920) Prec@5 98.000 (99.187) +2022-11-14 14:37:36,604 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0790) Prec@1 90.000 (86.961) Prec@5 99.000 (99.184) +2022-11-14 14:37:36,617 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0789) Prec@1 87.000 (86.961) Prec@5 98.000 (99.169) +2022-11-14 14:37:36,629 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0789) Prec@1 88.000 (86.974) Prec@5 100.000 (99.179) +2022-11-14 14:37:36,642 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0791) Prec@1 86.000 (86.962) Prec@5 100.000 (99.190) +2022-11-14 14:37:36,655 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0791) Prec@1 85.000 (86.938) Prec@5 98.000 (99.175) +2022-11-14 14:37:36,669 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0792) Prec@1 87.000 (86.938) Prec@5 97.000 (99.148) +2022-11-14 14:37:36,683 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0796) Prec@1 81.000 (86.866) Prec@5 98.000 (99.134) +2022-11-14 14:37:36,696 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0795) Prec@1 87.000 (86.867) Prec@5 100.000 (99.145) +2022-11-14 14:37:36,709 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0793) Prec@1 88.000 (86.881) Prec@5 99.000 (99.143) +2022-11-14 14:37:36,722 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0793) Prec@1 86.000 (86.871) Prec@5 99.000 (99.141) +2022-11-14 14:37:36,734 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0796) Prec@1 83.000 (86.826) Prec@5 98.000 (99.128) +2022-11-14 14:37:36,745 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0796) Prec@1 87.000 (86.828) Prec@5 99.000 (99.126) +2022-11-14 14:37:36,760 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0795) Prec@1 89.000 (86.852) Prec@5 100.000 (99.136) +2022-11-14 14:37:36,777 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0794) Prec@1 87.000 (86.854) Prec@5 100.000 (99.146) +2022-11-14 14:37:36,789 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0794) Prec@1 88.000 (86.867) Prec@5 100.000 (99.156) +2022-11-14 14:37:36,800 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0794) Prec@1 87.000 (86.868) Prec@5 100.000 (99.165) +2022-11-14 14:37:36,814 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0791) Prec@1 89.000 (86.891) Prec@5 99.000 (99.163) +2022-11-14 14:37:36,829 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0791) Prec@1 89.000 (86.914) Prec@5 100.000 (99.172) +2022-11-14 14:37:36,841 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0789) Prec@1 92.000 (86.968) Prec@5 99.000 (99.170) +2022-11-14 14:37:36,853 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0789) Prec@1 87.000 (86.968) Prec@5 99.000 (99.168) +2022-11-14 14:37:36,865 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0787) Prec@1 90.000 (87.000) Prec@5 99.000 (99.167) +2022-11-14 14:37:36,880 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0407 (0.0783) Prec@1 94.000 (87.072) Prec@5 99.000 (99.165) +2022-11-14 14:37:36,892 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0783) Prec@1 88.000 (87.082) Prec@5 99.000 (99.163) +2022-11-14 14:37:36,906 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0785) Prec@1 83.000 (87.040) Prec@5 98.000 (99.152) +2022-11-14 14:37:36,919 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0783) Prec@1 91.000 (87.080) Prec@5 99.000 (99.150) +2022-11-14 14:37:36,976 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:37:37,285 Epoch: [228][0/500] Time 0.025 (0.025) Data 0.226 (0.226) Loss 0.0416 (0.0416) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:37:37,594 Epoch: [228][10/500] Time 0.035 (0.027) Data 0.002 (0.022) Loss 0.0298 (0.0357) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 14:37:37,960 Epoch: [228][20/500] Time 0.040 (0.029) Data 0.002 (0.013) Loss 0.0354 (0.0356) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 14:37:38,319 Epoch: [228][30/500] Time 0.029 (0.030) Data 0.002 (0.009) Loss 0.0484 (0.0388) Prec@1 92.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 14:37:38,694 Epoch: [228][40/500] Time 0.033 (0.031) Data 0.002 (0.007) Loss 0.0167 (0.0344) Prec@1 97.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 14:37:39,061 Epoch: [228][50/500] Time 0.032 (0.031) Data 0.002 (0.006) Loss 0.0625 (0.0391) Prec@1 91.000 (94.500) Prec@5 99.000 (99.833) +2022-11-14 14:37:39,431 Epoch: [228][60/500] Time 0.031 (0.032) Data 0.002 (0.006) Loss 0.0469 (0.0402) Prec@1 94.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 14:37:39,797 Epoch: [228][70/500] Time 0.034 (0.032) Data 0.002 (0.005) Loss 0.0289 (0.0388) Prec@1 96.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 14:37:40,163 Epoch: [228][80/500] Time 0.041 (0.032) Data 0.002 (0.005) Loss 0.0316 (0.0380) Prec@1 96.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 14:37:40,514 Epoch: [228][90/500] Time 0.035 (0.032) Data 0.002 (0.004) Loss 0.0406 (0.0382) Prec@1 92.000 (94.500) Prec@5 99.000 (99.800) +2022-11-14 14:37:40,932 Epoch: [228][100/500] Time 0.034 (0.032) Data 0.002 (0.004) Loss 0.0465 (0.0390) Prec@1 93.000 (94.364) Prec@5 100.000 (99.818) +2022-11-14 14:37:41,314 Epoch: [228][110/500] Time 0.029 (0.032) Data 0.002 (0.004) Loss 0.0437 (0.0394) Prec@1 92.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 14:37:41,723 Epoch: [228][120/500] Time 0.046 (0.033) Data 0.002 (0.004) Loss 0.0422 (0.0396) Prec@1 92.000 (94.000) Prec@5 99.000 (99.769) +2022-11-14 14:37:42,114 Epoch: [228][130/500] Time 0.053 (0.033) Data 0.002 (0.004) Loss 0.0492 (0.0403) Prec@1 92.000 (93.857) Prec@5 100.000 (99.786) +2022-11-14 14:37:42,518 Epoch: [228][140/500] Time 0.045 (0.033) Data 0.002 (0.004) Loss 0.0567 (0.0414) Prec@1 93.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:37:42,879 Epoch: [228][150/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.0386 (0.0412) Prec@1 94.000 (93.812) Prec@5 100.000 (99.812) +2022-11-14 14:37:43,288 Epoch: [228][160/500] Time 0.030 (0.033) Data 0.002 (0.003) Loss 0.0571 (0.0421) Prec@1 89.000 (93.529) Prec@5 100.000 (99.824) +2022-11-14 14:37:43,658 Epoch: [228][170/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0147 (0.0406) Prec@1 99.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:37:44,087 Epoch: [228][180/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0468 (0.0409) Prec@1 93.000 (93.789) Prec@5 100.000 (99.842) +2022-11-14 14:37:44,482 Epoch: [228][190/500] Time 0.025 (0.034) Data 0.002 (0.003) Loss 0.0328 (0.0405) Prec@1 95.000 (93.850) Prec@5 98.000 (99.750) +2022-11-14 14:37:44,991 Epoch: [228][200/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0140 (0.0393) Prec@1 98.000 (94.048) Prec@5 100.000 (99.762) +2022-11-14 14:37:45,581 Epoch: [228][210/500] Time 0.061 (0.035) Data 0.002 (0.003) Loss 0.0607 (0.0402) Prec@1 90.000 (93.864) Prec@5 100.000 (99.773) +2022-11-14 14:37:46,194 Epoch: [228][220/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0415 (0.0403) Prec@1 93.000 (93.826) Prec@5 100.000 (99.783) +2022-11-14 14:37:46,808 Epoch: [228][230/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0505 (0.0407) Prec@1 90.000 (93.667) Prec@5 100.000 (99.792) +2022-11-14 14:37:47,495 Epoch: [228][240/500] Time 0.074 (0.038) Data 0.002 (0.003) Loss 0.0221 (0.0400) Prec@1 98.000 (93.840) Prec@5 100.000 (99.800) +2022-11-14 14:37:48,066 Epoch: [228][250/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0615 (0.0408) Prec@1 89.000 (93.654) Prec@5 99.000 (99.769) +2022-11-14 14:37:48,654 Epoch: [228][260/500] Time 0.058 (0.039) Data 0.002 (0.003) Loss 0.0355 (0.0406) Prec@1 95.000 (93.704) Prec@5 99.000 (99.741) +2022-11-14 14:37:49,141 Epoch: [228][270/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0508 (0.0410) Prec@1 91.000 (93.607) Prec@5 100.000 (99.750) +2022-11-14 14:37:49,683 Epoch: [228][280/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0128 (0.0400) Prec@1 98.000 (93.759) Prec@5 100.000 (99.759) +2022-11-14 14:37:50,277 Epoch: [228][290/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0251 (0.0395) Prec@1 98.000 (93.900) Prec@5 100.000 (99.767) +2022-11-14 14:37:50,850 Epoch: [228][300/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0430 (0.0396) Prec@1 91.000 (93.806) Prec@5 100.000 (99.774) +2022-11-14 14:37:51,323 Epoch: [228][310/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0477 (0.0399) Prec@1 93.000 (93.781) Prec@5 99.000 (99.750) +2022-11-14 14:37:51,796 Epoch: [228][320/500] Time 0.045 (0.040) Data 0.001 (0.003) Loss 0.0538 (0.0403) Prec@1 93.000 (93.758) Prec@5 99.000 (99.727) +2022-11-14 14:37:52,259 Epoch: [228][330/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0290 (0.0400) Prec@1 95.000 (93.794) Prec@5 100.000 (99.735) +2022-11-14 14:37:52,836 Epoch: [228][340/500] Time 0.062 (0.041) Data 0.002 (0.003) Loss 0.0382 (0.0399) Prec@1 93.000 (93.771) Prec@5 100.000 (99.743) +2022-11-14 14:37:53,417 Epoch: [228][350/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0560 (0.0404) Prec@1 90.000 (93.667) Prec@5 100.000 (99.750) +2022-11-14 14:37:53,898 Epoch: [228][360/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0324 (0.0401) Prec@1 94.000 (93.676) Prec@5 100.000 (99.757) +2022-11-14 14:37:54,418 Epoch: [228][370/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0425 (0.0402) Prec@1 93.000 (93.658) Prec@5 100.000 (99.763) +2022-11-14 14:37:54,921 Epoch: [228][380/500] Time 0.043 (0.041) Data 0.003 (0.003) Loss 0.0394 (0.0402) Prec@1 94.000 (93.667) Prec@5 99.000 (99.744) +2022-11-14 14:37:55,431 Epoch: [228][390/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0211 (0.0397) Prec@1 97.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:37:55,944 Epoch: [228][400/500] Time 0.052 (0.042) Data 0.002 (0.003) Loss 0.0408 (0.0397) Prec@1 94.000 (93.756) Prec@5 99.000 (99.732) +2022-11-14 14:37:56,446 Epoch: [228][410/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0341 (0.0396) Prec@1 94.000 (93.762) Prec@5 99.000 (99.714) +2022-11-14 14:37:56,947 Epoch: [228][420/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0427 (0.0397) Prec@1 93.000 (93.744) Prec@5 100.000 (99.721) +2022-11-14 14:37:57,462 Epoch: [228][430/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0591 (0.0401) Prec@1 91.000 (93.682) Prec@5 98.000 (99.682) +2022-11-14 14:37:57,950 Epoch: [228][440/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0353 (0.0400) Prec@1 94.000 (93.689) Prec@5 100.000 (99.689) +2022-11-14 14:37:58,434 Epoch: [228][450/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0389 (0.0400) Prec@1 93.000 (93.674) Prec@5 99.000 (99.674) +2022-11-14 14:37:58,932 Epoch: [228][460/500] Time 0.054 (0.042) Data 0.002 (0.002) Loss 0.0167 (0.0395) Prec@1 97.000 (93.745) Prec@5 100.000 (99.681) +2022-11-14 14:37:59,405 Epoch: [228][470/500] Time 0.045 (0.042) Data 0.002 (0.002) Loss 0.0383 (0.0395) Prec@1 94.000 (93.750) Prec@5 100.000 (99.688) +2022-11-14 14:37:59,894 Epoch: [228][480/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0351 (0.0394) Prec@1 94.000 (93.755) Prec@5 100.000 (99.694) +2022-11-14 14:38:00,402 Epoch: [228][490/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0271 (0.0391) Prec@1 96.000 (93.800) Prec@5 100.000 (99.700) +2022-11-14 14:38:00,819 Epoch: [228][499/500] Time 0.043 (0.042) Data 0.001 (0.002) Loss 0.0463 (0.0393) Prec@1 93.000 (93.784) Prec@5 100.000 (99.706) +2022-11-14 14:38:01,096 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0729 (0.0729) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:01,105 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0597 (0.0663) Prec@1 91.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:38:01,115 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0686) Prec@1 88.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 14:38:01,125 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0737) Prec@1 85.000 (88.250) Prec@5 98.000 (99.000) +2022-11-14 14:38:01,136 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0739) Prec@1 87.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:38:01,144 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0697) Prec@1 91.000 (88.500) Prec@5 99.000 (99.000) +2022-11-14 14:38:01,155 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0702) Prec@1 90.000 (88.714) Prec@5 100.000 (99.143) +2022-11-14 14:38:01,165 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0720) Prec@1 86.000 (88.375) Prec@5 100.000 (99.250) +2022-11-14 14:38:01,178 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0732) Prec@1 86.000 (88.111) Prec@5 98.000 (99.111) +2022-11-14 14:38:01,188 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0747) Prec@1 89.000 (88.200) Prec@5 98.000 (99.000) +2022-11-14 14:38:01,201 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0741) Prec@1 89.000 (88.273) Prec@5 100.000 (99.091) +2022-11-14 14:38:01,213 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0766) Prec@1 86.000 (88.083) Prec@5 100.000 (99.167) +2022-11-14 14:38:01,224 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0750) Prec@1 91.000 (88.308) Prec@5 100.000 (99.231) +2022-11-14 14:38:01,237 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0744) Prec@1 90.000 (88.429) Prec@5 97.000 (99.071) +2022-11-14 14:38:01,250 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0750) Prec@1 86.000 (88.267) Prec@5 100.000 (99.133) +2022-11-14 14:38:01,262 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0739) Prec@1 91.000 (88.438) Prec@5 100.000 (99.188) +2022-11-14 14:38:01,276 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0738) Prec@1 89.000 (88.471) Prec@5 98.000 (99.118) +2022-11-14 14:38:01,287 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0755) Prec@1 84.000 (88.222) Prec@5 100.000 (99.167) +2022-11-14 14:38:01,302 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0756) Prec@1 86.000 (88.105) Prec@5 99.000 (99.158) +2022-11-14 14:38:01,318 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0770) Prec@1 86.000 (88.000) Prec@5 99.000 (99.150) +2022-11-14 14:38:01,331 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0778) Prec@1 84.000 (87.810) Prec@5 100.000 (99.190) +2022-11-14 14:38:01,343 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0780) Prec@1 85.000 (87.682) Prec@5 100.000 (99.227) +2022-11-14 14:38:01,358 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0787) Prec@1 86.000 (87.609) Prec@5 98.000 (99.174) +2022-11-14 14:38:01,371 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0787) Prec@1 87.000 (87.583) Prec@5 100.000 (99.208) +2022-11-14 14:38:01,386 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0791) Prec@1 87.000 (87.560) Prec@5 100.000 (99.240) +2022-11-14 14:38:01,402 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0802) Prec@1 81.000 (87.308) Prec@5 98.000 (99.192) +2022-11-14 14:38:01,416 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0793) Prec@1 91.000 (87.444) Prec@5 100.000 (99.222) +2022-11-14 14:38:01,428 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0786) Prec@1 90.000 (87.536) Prec@5 100.000 (99.250) +2022-11-14 14:38:01,443 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0783) Prec@1 89.000 (87.586) Prec@5 99.000 (99.241) +2022-11-14 14:38:01,457 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0781) Prec@1 90.000 (87.667) Prec@5 100.000 (99.267) +2022-11-14 14:38:01,473 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0782) Prec@1 83.000 (87.516) Prec@5 99.000 (99.258) +2022-11-14 14:38:01,489 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0782) Prec@1 84.000 (87.406) Prec@5 99.000 (99.250) +2022-11-14 14:38:01,505 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0779) Prec@1 90.000 (87.485) Prec@5 99.000 (99.242) +2022-11-14 14:38:01,519 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0786) Prec@1 82.000 (87.324) Prec@5 99.000 (99.235) +2022-11-14 14:38:01,533 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0788) Prec@1 83.000 (87.200) Prec@5 99.000 (99.229) +2022-11-14 14:38:01,546 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0785) Prec@1 91.000 (87.306) Prec@5 98.000 (99.194) +2022-11-14 14:38:01,560 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0784) Prec@1 88.000 (87.324) Prec@5 99.000 (99.189) +2022-11-14 14:38:01,576 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0789) Prec@1 82.000 (87.184) Prec@5 98.000 (99.158) +2022-11-14 14:38:01,590 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0785) Prec@1 91.000 (87.282) Prec@5 100.000 (99.179) +2022-11-14 14:38:01,604 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0784) Prec@1 89.000 (87.325) Prec@5 99.000 (99.175) +2022-11-14 14:38:01,619 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0791) Prec@1 82.000 (87.195) Prec@5 96.000 (99.098) +2022-11-14 14:38:01,633 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0788) Prec@1 89.000 (87.238) Prec@5 100.000 (99.119) +2022-11-14 14:38:01,647 Test: [42/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0780) Prec@1 94.000 (87.395) Prec@5 99.000 (99.116) +2022-11-14 14:38:01,662 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0779) Prec@1 87.000 (87.386) Prec@5 98.000 (99.091) +2022-11-14 14:38:01,675 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0773) Prec@1 92.000 (87.489) Prec@5 100.000 (99.111) +2022-11-14 14:38:01,689 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0776) Prec@1 83.000 (87.391) Prec@5 100.000 (99.130) +2022-11-14 14:38:01,703 Test: [46/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0773) Prec@1 89.000 (87.426) Prec@5 100.000 (99.149) +2022-11-14 14:38:01,720 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0774) Prec@1 87.000 (87.417) Prec@5 100.000 (99.167) +2022-11-14 14:38:01,731 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0769) Prec@1 91.000 (87.490) Prec@5 100.000 (99.184) +2022-11-14 14:38:01,745 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0775) Prec@1 85.000 (87.440) Prec@5 99.000 (99.180) +2022-11-14 14:38:01,759 Test: [50/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0771) Prec@1 91.000 (87.510) Prec@5 100.000 (99.196) +2022-11-14 14:38:01,773 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0775) Prec@1 82.000 (87.404) Prec@5 100.000 (99.212) +2022-11-14 14:38:01,787 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0778) Prec@1 87.000 (87.396) Prec@5 99.000 (99.208) +2022-11-14 14:38:01,803 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0778) Prec@1 88.000 (87.407) Prec@5 100.000 (99.222) +2022-11-14 14:38:01,820 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0781) Prec@1 82.000 (87.309) Prec@5 100.000 (99.236) +2022-11-14 14:38:01,837 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0776) Prec@1 92.000 (87.393) Prec@5 99.000 (99.232) +2022-11-14 14:38:01,856 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0773) Prec@1 89.000 (87.421) Prec@5 100.000 (99.246) +2022-11-14 14:38:01,874 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0775) Prec@1 86.000 (87.397) Prec@5 99.000 (99.241) +2022-11-14 14:38:01,890 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1170 (0.0782) Prec@1 82.000 (87.305) Prec@5 99.000 (99.237) +2022-11-14 14:38:01,905 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0779) Prec@1 88.000 (87.317) Prec@5 100.000 (99.250) +2022-11-14 14:38:01,920 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0778) Prec@1 86.000 (87.295) Prec@5 99.000 (99.246) +2022-11-14 14:38:01,933 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0777) Prec@1 89.000 (87.323) Prec@5 99.000 (99.242) +2022-11-14 14:38:01,946 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0774) Prec@1 91.000 (87.381) Prec@5 100.000 (99.254) +2022-11-14 14:38:01,959 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0394 (0.0768) Prec@1 92.000 (87.453) Prec@5 100.000 (99.266) +2022-11-14 14:38:01,973 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0771) Prec@1 83.000 (87.385) Prec@5 100.000 (99.277) +2022-11-14 14:38:01,987 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0770) Prec@1 90.000 (87.424) Prec@5 99.000 (99.273) +2022-11-14 14:38:02,001 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0764) Prec@1 93.000 (87.507) Prec@5 100.000 (99.284) +2022-11-14 14:38:02,015 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0765) Prec@1 86.000 (87.485) Prec@5 98.000 (99.265) +2022-11-14 14:38:02,029 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0764) Prec@1 90.000 (87.522) Prec@5 99.000 (99.261) +2022-11-14 14:38:02,043 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0766) Prec@1 87.000 (87.514) Prec@5 100.000 (99.271) +2022-11-14 14:38:02,057 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0768) Prec@1 85.000 (87.479) Prec@5 100.000 (99.282) +2022-11-14 14:38:02,073 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0768) Prec@1 87.000 (87.472) Prec@5 100.000 (99.292) +2022-11-14 14:38:02,088 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0763) Prec@1 94.000 (87.562) Prec@5 100.000 (99.301) +2022-11-14 14:38:02,102 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0346 (0.0758) Prec@1 96.000 (87.676) Prec@5 100.000 (99.311) +2022-11-14 14:38:02,114 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0762) Prec@1 83.000 (87.613) Prec@5 99.000 (99.307) +2022-11-14 14:38:02,129 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0764) Prec@1 86.000 (87.592) Prec@5 99.000 (99.303) +2022-11-14 14:38:02,144 Test: [76/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0763) Prec@1 87.000 (87.584) Prec@5 100.000 (99.312) +2022-11-14 14:38:02,158 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0763) Prec@1 87.000 (87.577) Prec@5 100.000 (99.321) +2022-11-14 14:38:02,172 Test: [78/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0765) Prec@1 88.000 (87.582) Prec@5 100.000 (99.329) +2022-11-14 14:38:02,185 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0765) Prec@1 87.000 (87.575) Prec@5 98.000 (99.312) +2022-11-14 14:38:02,199 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0764) Prec@1 91.000 (87.617) Prec@5 100.000 (99.321) +2022-11-14 14:38:02,214 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0764) Prec@1 88.000 (87.622) Prec@5 100.000 (99.329) +2022-11-14 14:38:02,228 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0767) Prec@1 83.000 (87.566) Prec@5 100.000 (99.337) +2022-11-14 14:38:02,241 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0324 (0.0761) Prec@1 95.000 (87.655) Prec@5 100.000 (99.345) +2022-11-14 14:38:02,255 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0761) Prec@1 90.000 (87.682) Prec@5 99.000 (99.341) +2022-11-14 14:38:02,268 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0764) Prec@1 84.000 (87.640) Prec@5 97.000 (99.314) +2022-11-14 14:38:02,282 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0764) Prec@1 86.000 (87.621) Prec@5 99.000 (99.310) +2022-11-14 14:38:02,298 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0764) Prec@1 91.000 (87.659) Prec@5 99.000 (99.307) +2022-11-14 14:38:02,313 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0764) Prec@1 88.000 (87.663) Prec@5 99.000 (99.303) +2022-11-14 14:38:02,328 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0761) Prec@1 91.000 (87.700) Prec@5 100.000 (99.311) +2022-11-14 14:38:02,341 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0759) Prec@1 90.000 (87.725) Prec@5 100.000 (99.319) +2022-11-14 14:38:02,354 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0756) Prec@1 92.000 (87.772) Prec@5 100.000 (99.326) +2022-11-14 14:38:02,370 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0758) Prec@1 83.000 (87.720) Prec@5 100.000 (99.333) +2022-11-14 14:38:02,384 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0757) Prec@1 89.000 (87.734) Prec@5 99.000 (99.330) +2022-11-14 14:38:02,399 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0758) Prec@1 87.000 (87.726) Prec@5 100.000 (99.337) +2022-11-14 14:38:02,414 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0757) Prec@1 89.000 (87.740) Prec@5 98.000 (99.323) +2022-11-14 14:38:02,426 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0754) Prec@1 95.000 (87.814) Prec@5 99.000 (99.320) +2022-11-14 14:38:02,440 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0754) Prec@1 88.000 (87.816) Prec@5 100.000 (99.327) +2022-11-14 14:38:02,455 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0758) Prec@1 82.000 (87.758) Prec@5 99.000 (99.323) +2022-11-14 14:38:02,469 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0756) Prec@1 91.000 (87.790) Prec@5 99.000 (99.320) +2022-11-14 14:38:02,536 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:38:02,845 Epoch: [229][0/500] Time 0.023 (0.023) Data 0.225 (0.225) Loss 0.0610 (0.0610) Prec@1 90.000 (90.000) Prec@5 98.000 (98.000) +2022-11-14 14:38:03,076 Epoch: [229][10/500] Time 0.021 (0.020) Data 0.002 (0.022) Loss 0.0241 (0.0426) Prec@1 96.000 (93.000) Prec@5 100.000 (99.000) +2022-11-14 14:38:03,337 Epoch: [229][20/500] Time 0.022 (0.022) Data 0.002 (0.012) Loss 0.0329 (0.0393) Prec@1 95.000 (93.667) Prec@5 100.000 (99.333) +2022-11-14 14:38:03,601 Epoch: [229][30/500] Time 0.024 (0.022) Data 0.002 (0.009) Loss 0.0406 (0.0397) Prec@1 93.000 (93.500) Prec@5 99.000 (99.250) +2022-11-14 14:38:03,854 Epoch: [229][40/500] Time 0.020 (0.022) Data 0.002 (0.007) Loss 0.0519 (0.0421) Prec@1 87.000 (92.200) Prec@5 100.000 (99.400) +2022-11-14 14:38:04,121 Epoch: [229][50/500] Time 0.023 (0.023) Data 0.002 (0.006) Loss 0.0369 (0.0412) Prec@1 94.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 14:38:04,372 Epoch: [229][60/500] Time 0.023 (0.022) Data 0.002 (0.005) Loss 0.0538 (0.0430) Prec@1 94.000 (92.714) Prec@5 98.000 (99.286) +2022-11-14 14:38:04,649 Epoch: [229][70/500] Time 0.021 (0.023) Data 0.002 (0.005) Loss 0.0391 (0.0425) Prec@1 93.000 (92.750) Prec@5 99.000 (99.250) +2022-11-14 14:38:04,941 Epoch: [229][80/500] Time 0.035 (0.023) Data 0.001 (0.004) Loss 0.0430 (0.0426) Prec@1 93.000 (92.778) Prec@5 100.000 (99.333) +2022-11-14 14:38:05,338 Epoch: [229][90/500] Time 0.040 (0.024) Data 0.001 (0.004) Loss 0.0499 (0.0433) Prec@1 91.000 (92.600) Prec@5 99.000 (99.300) +2022-11-14 14:38:05,770 Epoch: [229][100/500] Time 0.049 (0.026) Data 0.002 (0.004) Loss 0.0394 (0.0430) Prec@1 95.000 (92.818) Prec@5 100.000 (99.364) +2022-11-14 14:38:06,198 Epoch: [229][110/500] Time 0.045 (0.027) Data 0.002 (0.004) Loss 0.0316 (0.0420) Prec@1 95.000 (93.000) Prec@5 100.000 (99.417) +2022-11-14 14:38:06,610 Epoch: [229][120/500] Time 0.043 (0.028) Data 0.002 (0.004) Loss 0.0504 (0.0427) Prec@1 89.000 (92.692) Prec@5 100.000 (99.462) +2022-11-14 14:38:07,027 Epoch: [229][130/500] Time 0.043 (0.028) Data 0.003 (0.003) Loss 0.0243 (0.0413) Prec@1 95.000 (92.857) Prec@5 100.000 (99.500) +2022-11-14 14:38:07,416 Epoch: [229][140/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0394 (0.0412) Prec@1 94.000 (92.933) Prec@5 99.000 (99.467) +2022-11-14 14:38:07,834 Epoch: [229][150/500] Time 0.035 (0.029) Data 0.002 (0.003) Loss 0.0318 (0.0406) Prec@1 95.000 (93.062) Prec@5 99.000 (99.438) +2022-11-14 14:38:08,234 Epoch: [229][160/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0191 (0.0394) Prec@1 97.000 (93.294) Prec@5 100.000 (99.471) +2022-11-14 14:38:08,693 Epoch: [229][170/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0576 (0.0404) Prec@1 90.000 (93.111) Prec@5 100.000 (99.500) +2022-11-14 14:38:09,071 Epoch: [229][180/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.0368 (0.0402) Prec@1 94.000 (93.158) Prec@5 100.000 (99.526) +2022-11-14 14:38:09,489 Epoch: [229][190/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0570 (0.0410) Prec@1 89.000 (92.950) Prec@5 100.000 (99.550) +2022-11-14 14:38:09,887 Epoch: [229][200/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0207 (0.0401) Prec@1 97.000 (93.143) Prec@5 100.000 (99.571) +2022-11-14 14:38:10,288 Epoch: [229][210/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0167 (0.0390) Prec@1 97.000 (93.318) Prec@5 100.000 (99.591) +2022-11-14 14:38:10,715 Epoch: [229][220/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0345 (0.0388) Prec@1 96.000 (93.435) Prec@5 99.000 (99.565) +2022-11-14 14:38:11,189 Epoch: [229][230/500] Time 0.047 (0.032) Data 0.002 (0.003) Loss 0.0428 (0.0390) Prec@1 92.000 (93.375) Prec@5 100.000 (99.583) +2022-11-14 14:38:11,603 Epoch: [229][240/500] Time 0.063 (0.032) Data 0.002 (0.003) Loss 0.0319 (0.0387) Prec@1 95.000 (93.440) Prec@5 100.000 (99.600) +2022-11-14 14:38:12,037 Epoch: [229][250/500] Time 0.029 (0.033) Data 0.002 (0.003) Loss 0.0496 (0.0391) Prec@1 91.000 (93.346) Prec@5 100.000 (99.615) +2022-11-14 14:38:12,430 Epoch: [229][260/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0340 (0.0389) Prec@1 97.000 (93.481) Prec@5 99.000 (99.593) +2022-11-14 14:38:12,828 Epoch: [229][270/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0375 (0.0389) Prec@1 93.000 (93.464) Prec@5 100.000 (99.607) +2022-11-14 14:38:13,228 Epoch: [229][280/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0432 (0.0390) Prec@1 92.000 (93.414) Prec@5 99.000 (99.586) +2022-11-14 14:38:13,620 Epoch: [229][290/500] Time 0.037 (0.033) Data 0.001 (0.003) Loss 0.0360 (0.0389) Prec@1 94.000 (93.433) Prec@5 100.000 (99.600) +2022-11-14 14:38:14,024 Epoch: [229][300/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0277 (0.0386) Prec@1 96.000 (93.516) Prec@5 98.000 (99.548) +2022-11-14 14:38:14,417 Epoch: [229][310/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0273 (0.0382) Prec@1 96.000 (93.594) Prec@5 100.000 (99.562) +2022-11-14 14:38:14,812 Epoch: [229][320/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0483 (0.0385) Prec@1 92.000 (93.545) Prec@5 100.000 (99.576) +2022-11-14 14:38:15,214 Epoch: [229][330/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0277 (0.0382) Prec@1 96.000 (93.618) Prec@5 100.000 (99.588) +2022-11-14 14:38:15,633 Epoch: [229][340/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0225 (0.0377) Prec@1 97.000 (93.714) Prec@5 100.000 (99.600) +2022-11-14 14:38:16,071 Epoch: [229][350/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0319 (0.0376) Prec@1 95.000 (93.750) Prec@5 100.000 (99.611) +2022-11-14 14:38:16,539 Epoch: [229][360/500] Time 0.047 (0.034) Data 0.002 (0.002) Loss 0.0401 (0.0376) Prec@1 94.000 (93.757) Prec@5 100.000 (99.622) +2022-11-14 14:38:16,910 Epoch: [229][370/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0497 (0.0380) Prec@1 91.000 (93.684) Prec@5 100.000 (99.632) +2022-11-14 14:38:17,307 Epoch: [229][380/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0361 (0.0379) Prec@1 93.000 (93.667) Prec@5 100.000 (99.641) +2022-11-14 14:38:17,713 Epoch: [229][390/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0242 (0.0376) Prec@1 96.000 (93.725) Prec@5 100.000 (99.650) +2022-11-14 14:38:18,174 Epoch: [229][400/500] Time 0.028 (0.034) Data 0.002 (0.002) Loss 0.0434 (0.0377) Prec@1 94.000 (93.732) Prec@5 100.000 (99.659) +2022-11-14 14:38:18,568 Epoch: [229][410/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0508 (0.0380) Prec@1 92.000 (93.690) Prec@5 99.000 (99.643) +2022-11-14 14:38:18,968 Epoch: [229][420/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0380 (0.0380) Prec@1 93.000 (93.674) Prec@5 100.000 (99.651) +2022-11-14 14:38:19,366 Epoch: [229][430/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0284 (0.0378) Prec@1 95.000 (93.705) Prec@5 100.000 (99.659) +2022-11-14 14:38:19,763 Epoch: [229][440/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0196 (0.0374) Prec@1 96.000 (93.756) Prec@5 100.000 (99.667) +2022-11-14 14:38:20,164 Epoch: [229][450/500] Time 0.036 (0.034) Data 0.003 (0.002) Loss 0.0305 (0.0372) Prec@1 96.000 (93.804) Prec@5 100.000 (99.674) +2022-11-14 14:38:20,562 Epoch: [229][460/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0302 (0.0371) Prec@1 95.000 (93.830) Prec@5 99.000 (99.660) +2022-11-14 14:38:20,963 Epoch: [229][470/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0388 (0.0371) Prec@1 93.000 (93.812) Prec@5 100.000 (99.667) +2022-11-14 14:38:21,363 Epoch: [229][480/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0401 (0.0372) Prec@1 94.000 (93.816) Prec@5 100.000 (99.673) +2022-11-14 14:38:21,762 Epoch: [229][490/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0339 (0.0371) Prec@1 94.000 (93.820) Prec@5 100.000 (99.680) +2022-11-14 14:38:22,122 Epoch: [229][499/500] Time 0.038 (0.034) Data 0.001 (0.002) Loss 0.0640 (0.0377) Prec@1 87.000 (93.686) Prec@5 98.000 (99.647) +2022-11-14 14:38:22,405 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0724 (0.0724) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:22,412 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0810) Prec@1 85.000 (85.000) Prec@5 99.000 (99.500) +2022-11-14 14:38:22,421 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0749) Prec@1 88.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 14:38:22,434 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0749) Prec@1 89.000 (86.750) Prec@5 100.000 (99.750) +2022-11-14 14:38:22,441 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0752) Prec@1 89.000 (87.200) Prec@5 100.000 (99.800) +2022-11-14 14:38:22,450 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0410 (0.0695) Prec@1 93.000 (88.167) Prec@5 100.000 (99.833) +2022-11-14 14:38:22,459 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0690) Prec@1 91.000 (88.571) Prec@5 100.000 (99.857) +2022-11-14 14:38:22,471 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0713) Prec@1 87.000 (88.375) Prec@5 100.000 (99.875) +2022-11-14 14:38:22,480 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0723) Prec@1 86.000 (88.111) Prec@5 100.000 (99.889) +2022-11-14 14:38:22,490 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0727) Prec@1 87.000 (88.000) Prec@5 99.000 (99.800) +2022-11-14 14:38:22,500 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0709) Prec@1 92.000 (88.364) Prec@5 99.000 (99.727) +2022-11-14 14:38:22,512 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0729) Prec@1 85.000 (88.083) Prec@5 100.000 (99.750) +2022-11-14 14:38:22,522 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0723) Prec@1 89.000 (88.154) Prec@5 100.000 (99.769) +2022-11-14 14:38:22,534 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0724) Prec@1 85.000 (87.929) Prec@5 100.000 (99.786) +2022-11-14 14:38:22,544 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0721) Prec@1 89.000 (88.000) Prec@5 99.000 (99.733) +2022-11-14 14:38:22,553 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0740) Prec@1 85.000 (87.812) Prec@5 99.000 (99.688) +2022-11-14 14:38:22,563 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0505 (0.0726) Prec@1 91.000 (88.000) Prec@5 98.000 (99.588) +2022-11-14 14:38:22,572 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0739) Prec@1 87.000 (87.944) Prec@5 99.000 (99.556) +2022-11-14 14:38:22,582 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0741) Prec@1 86.000 (87.842) Prec@5 97.000 (99.421) +2022-11-14 14:38:22,591 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0746) Prec@1 88.000 (87.850) Prec@5 98.000 (99.350) +2022-11-14 14:38:22,600 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0750) Prec@1 86.000 (87.762) Prec@5 98.000 (99.286) +2022-11-14 14:38:22,610 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0752) Prec@1 88.000 (87.773) Prec@5 99.000 (99.273) +2022-11-14 14:38:22,619 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0764) Prec@1 86.000 (87.696) Prec@5 97.000 (99.174) +2022-11-14 14:38:22,628 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0762) Prec@1 89.000 (87.750) Prec@5 99.000 (99.167) +2022-11-14 14:38:22,638 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0764) Prec@1 86.000 (87.680) Prec@5 100.000 (99.200) +2022-11-14 14:38:22,648 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0771) Prec@1 83.000 (87.500) Prec@5 99.000 (99.192) +2022-11-14 14:38:22,656 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0761) Prec@1 92.000 (87.667) Prec@5 100.000 (99.222) +2022-11-14 14:38:22,665 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0763) Prec@1 87.000 (87.643) Prec@5 100.000 (99.250) +2022-11-14 14:38:22,675 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0760) Prec@1 88.000 (87.655) Prec@5 99.000 (99.241) +2022-11-14 14:38:22,684 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0758) Prec@1 88.000 (87.667) Prec@5 100.000 (99.267) +2022-11-14 14:38:22,693 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0757) Prec@1 86.000 (87.613) Prec@5 99.000 (99.258) +2022-11-14 14:38:22,703 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0757) Prec@1 88.000 (87.625) Prec@5 100.000 (99.281) +2022-11-14 14:38:22,712 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0757) Prec@1 87.000 (87.606) Prec@5 98.000 (99.242) +2022-11-14 14:38:22,720 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0762) Prec@1 85.000 (87.529) Prec@5 100.000 (99.265) +2022-11-14 14:38:22,729 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0764) Prec@1 86.000 (87.486) Prec@5 98.000 (99.229) +2022-11-14 14:38:22,739 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0760) Prec@1 90.000 (87.556) Prec@5 99.000 (99.222) +2022-11-14 14:38:22,747 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0765) Prec@1 84.000 (87.459) Prec@5 99.000 (99.216) +2022-11-14 14:38:22,755 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0770) Prec@1 83.000 (87.342) Prec@5 99.000 (99.211) +2022-11-14 14:38:22,764 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0766) Prec@1 91.000 (87.436) Prec@5 99.000 (99.205) +2022-11-14 14:38:22,772 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0761) Prec@1 89.000 (87.475) Prec@5 99.000 (99.200) +2022-11-14 14:38:22,782 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0763) Prec@1 86.000 (87.439) Prec@5 100.000 (99.220) +2022-11-14 14:38:22,791 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0762) Prec@1 88.000 (87.452) Prec@5 99.000 (99.214) +2022-11-14 14:38:22,800 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0754) Prec@1 92.000 (87.558) Prec@5 99.000 (99.209) +2022-11-14 14:38:22,810 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0753) Prec@1 90.000 (87.614) Prec@5 98.000 (99.182) +2022-11-14 14:38:22,818 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0749) Prec@1 91.000 (87.689) Prec@5 99.000 (99.178) +2022-11-14 14:38:22,828 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0756) Prec@1 82.000 (87.565) Prec@5 99.000 (99.174) +2022-11-14 14:38:22,838 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0751) Prec@1 90.000 (87.617) Prec@5 100.000 (99.191) +2022-11-14 14:38:22,847 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0753) Prec@1 84.000 (87.542) Prec@5 99.000 (99.188) +2022-11-14 14:38:22,857 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0748) Prec@1 91.000 (87.612) Prec@5 100.000 (99.204) +2022-11-14 14:38:22,866 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0754) Prec@1 82.000 (87.500) Prec@5 100.000 (99.220) +2022-11-14 14:38:22,876 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0754) Prec@1 85.000 (87.451) Prec@5 100.000 (99.235) +2022-11-14 14:38:22,885 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0756) Prec@1 87.000 (87.442) Prec@5 100.000 (99.250) +2022-11-14 14:38:22,894 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0756) Prec@1 86.000 (87.415) Prec@5 99.000 (99.245) +2022-11-14 14:38:22,904 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0756) Prec@1 88.000 (87.426) Prec@5 99.000 (99.241) +2022-11-14 14:38:22,914 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0759) Prec@1 84.000 (87.364) Prec@5 100.000 (99.255) +2022-11-14 14:38:22,923 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0756) Prec@1 92.000 (87.446) Prec@5 99.000 (99.250) +2022-11-14 14:38:22,932 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0756) Prec@1 86.000 (87.421) Prec@5 100.000 (99.263) +2022-11-14 14:38:22,943 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0758) Prec@1 86.000 (87.397) Prec@5 98.000 (99.241) +2022-11-14 14:38:22,952 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0762) Prec@1 84.000 (87.339) Prec@5 100.000 (99.254) +2022-11-14 14:38:22,962 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0760) Prec@1 91.000 (87.400) Prec@5 99.000 (99.250) +2022-11-14 14:38:22,971 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0759) Prec@1 88.000 (87.410) Prec@5 100.000 (99.262) +2022-11-14 14:38:22,980 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0758) Prec@1 90.000 (87.452) Prec@5 99.000 (99.258) +2022-11-14 14:38:22,990 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0755) Prec@1 89.000 (87.476) Prec@5 100.000 (99.270) +2022-11-14 14:38:23,000 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0750) Prec@1 93.000 (87.562) Prec@5 100.000 (99.281) +2022-11-14 14:38:23,010 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0756) Prec@1 81.000 (87.462) Prec@5 98.000 (99.262) +2022-11-14 14:38:23,019 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0757) Prec@1 85.000 (87.424) Prec@5 99.000 (99.258) +2022-11-14 14:38:23,028 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0753) Prec@1 91.000 (87.478) Prec@5 100.000 (99.269) +2022-11-14 14:38:23,038 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0752) Prec@1 89.000 (87.500) Prec@5 100.000 (99.279) +2022-11-14 14:38:23,046 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0749) Prec@1 89.000 (87.522) Prec@5 100.000 (99.290) +2022-11-14 14:38:23,055 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0752) Prec@1 83.000 (87.457) Prec@5 99.000 (99.286) +2022-11-14 14:38:23,064 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0753) Prec@1 86.000 (87.437) Prec@5 100.000 (99.296) +2022-11-14 14:38:23,073 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0752) Prec@1 88.000 (87.444) Prec@5 100.000 (99.306) +2022-11-14 14:38:23,082 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0749) Prec@1 94.000 (87.534) Prec@5 99.000 (99.301) +2022-11-14 14:38:23,091 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0746) Prec@1 91.000 (87.581) Prec@5 100.000 (99.311) +2022-11-14 14:38:23,101 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0749) Prec@1 82.000 (87.507) Prec@5 99.000 (99.307) +2022-11-14 14:38:23,111 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0746) Prec@1 92.000 (87.566) Prec@5 98.000 (99.289) +2022-11-14 14:38:23,121 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0749) Prec@1 84.000 (87.519) Prec@5 98.000 (99.273) +2022-11-14 14:38:23,130 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1140 (0.0754) Prec@1 83.000 (87.462) Prec@5 98.000 (99.256) +2022-11-14 14:38:23,139 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0755) Prec@1 85.000 (87.430) Prec@5 100.000 (99.266) +2022-11-14 14:38:23,149 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0756) Prec@1 83.000 (87.375) Prec@5 100.000 (99.275) +2022-11-14 14:38:23,158 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0756) Prec@1 87.000 (87.370) Prec@5 98.000 (99.259) +2022-11-14 14:38:23,167 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0757) Prec@1 84.000 (87.329) Prec@5 99.000 (99.256) +2022-11-14 14:38:23,177 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0758) Prec@1 86.000 (87.313) Prec@5 100.000 (99.265) +2022-11-14 14:38:23,186 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0759) Prec@1 85.000 (87.286) Prec@5 99.000 (99.262) +2022-11-14 14:38:23,195 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0760) Prec@1 85.000 (87.259) Prec@5 98.000 (99.247) +2022-11-14 14:38:23,205 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.0764) Prec@1 83.000 (87.209) Prec@5 99.000 (99.244) +2022-11-14 14:38:23,214 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0764) Prec@1 88.000 (87.218) Prec@5 99.000 (99.241) +2022-11-14 14:38:23,223 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0764) Prec@1 88.000 (87.227) Prec@5 98.000 (99.227) +2022-11-14 14:38:23,233 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0764) Prec@1 86.000 (87.213) Prec@5 99.000 (99.225) +2022-11-14 14:38:23,241 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0763) Prec@1 89.000 (87.233) Prec@5 99.000 (99.222) +2022-11-14 14:38:23,251 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0762) Prec@1 91.000 (87.275) Prec@5 100.000 (99.231) +2022-11-14 14:38:23,260 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0758) Prec@1 94.000 (87.348) Prec@5 100.000 (99.239) +2022-11-14 14:38:23,270 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0760) Prec@1 86.000 (87.333) Prec@5 100.000 (99.247) +2022-11-14 14:38:23,279 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0759) Prec@1 88.000 (87.340) Prec@5 98.000 (99.234) +2022-11-14 14:38:23,289 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0759) Prec@1 83.000 (87.295) Prec@5 99.000 (99.232) +2022-11-14 14:38:23,297 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0760) Prec@1 86.000 (87.281) Prec@5 98.000 (99.219) +2022-11-14 14:38:23,306 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0757) Prec@1 91.000 (87.320) Prec@5 99.000 (99.216) +2022-11-14 14:38:23,316 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0759) Prec@1 86.000 (87.306) Prec@5 98.000 (99.204) +2022-11-14 14:38:23,324 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0761) Prec@1 87.000 (87.303) Prec@5 100.000 (99.212) +2022-11-14 14:38:23,332 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0760) Prec@1 88.000 (87.310) Prec@5 99.000 (99.210) +2022-11-14 14:38:23,389 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:38:23,685 Epoch: [230][0/500] Time 0.024 (0.024) Data 0.221 (0.221) Loss 0.0386 (0.0386) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:23,891 Epoch: [230][10/500] Time 0.016 (0.019) Data 0.002 (0.021) Loss 0.0195 (0.0291) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:24,096 Epoch: [230][20/500] Time 0.019 (0.018) Data 0.001 (0.012) Loss 0.0430 (0.0337) Prec@1 93.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:38:24,426 Epoch: [230][30/500] Time 0.043 (0.022) Data 0.002 (0.009) Loss 0.0296 (0.0327) Prec@1 96.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 14:38:24,888 Epoch: [230][40/500] Time 0.043 (0.026) Data 0.002 (0.007) Loss 0.0297 (0.0321) Prec@1 95.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 14:38:25,347 Epoch: [230][50/500] Time 0.045 (0.029) Data 0.002 (0.006) Loss 0.0704 (0.0385) Prec@1 89.000 (93.833) Prec@5 100.000 (100.000) +2022-11-14 14:38:25,801 Epoch: [230][60/500] Time 0.043 (0.031) Data 0.002 (0.005) Loss 0.0355 (0.0381) Prec@1 94.000 (93.857) Prec@5 100.000 (100.000) +2022-11-14 14:38:26,263 Epoch: [230][70/500] Time 0.042 (0.032) Data 0.002 (0.005) Loss 0.0184 (0.0356) Prec@1 97.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 14:38:26,720 Epoch: [230][80/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0335 (0.0354) Prec@1 95.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:38:27,192 Epoch: [230][90/500] Time 0.042 (0.034) Data 0.002 (0.004) Loss 0.0354 (0.0354) Prec@1 93.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 14:38:27,655 Epoch: [230][100/500] Time 0.042 (0.035) Data 0.003 (0.004) Loss 0.0375 (0.0356) Prec@1 94.000 (94.182) Prec@5 100.000 (100.000) +2022-11-14 14:38:28,145 Epoch: [230][110/500] Time 0.047 (0.036) Data 0.002 (0.004) Loss 0.0336 (0.0354) Prec@1 95.000 (94.250) Prec@5 99.000 (99.917) +2022-11-14 14:38:28,639 Epoch: [230][120/500] Time 0.042 (0.036) Data 0.003 (0.004) Loss 0.0213 (0.0343) Prec@1 97.000 (94.462) Prec@5 100.000 (99.923) +2022-11-14 14:38:29,095 Epoch: [230][130/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0300 (0.0340) Prec@1 95.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 14:38:29,549 Epoch: [230][140/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0366 (0.0342) Prec@1 94.000 (94.467) Prec@5 100.000 (99.933) +2022-11-14 14:38:30,007 Epoch: [230][150/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0389 (0.0345) Prec@1 93.000 (94.375) Prec@5 100.000 (99.938) +2022-11-14 14:38:30,465 Epoch: [230][160/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0212 (0.0337) Prec@1 96.000 (94.471) Prec@5 100.000 (99.941) +2022-11-14 14:38:30,996 Epoch: [230][170/500] Time 0.074 (0.038) Data 0.002 (0.003) Loss 0.0339 (0.0337) Prec@1 94.000 (94.444) Prec@5 99.000 (99.889) +2022-11-14 14:38:31,453 Epoch: [230][180/500] Time 0.044 (0.038) Data 0.001 (0.003) Loss 0.0610 (0.0351) Prec@1 89.000 (94.158) Prec@5 98.000 (99.789) +2022-11-14 14:38:32,002 Epoch: [230][190/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0418 (0.0355) Prec@1 94.000 (94.150) Prec@5 100.000 (99.800) +2022-11-14 14:38:32,440 Epoch: [230][200/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0329 (0.0354) Prec@1 95.000 (94.190) Prec@5 100.000 (99.810) +2022-11-14 14:38:32,926 Epoch: [230][210/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0337 (0.0353) Prec@1 95.000 (94.227) Prec@5 100.000 (99.818) +2022-11-14 14:38:33,410 Epoch: [230][220/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0330 (0.0352) Prec@1 95.000 (94.261) Prec@5 100.000 (99.826) +2022-11-14 14:38:33,873 Epoch: [230][230/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0699 (0.0366) Prec@1 87.000 (93.958) Prec@5 99.000 (99.792) +2022-11-14 14:38:34,330 Epoch: [230][240/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0367 (0.0366) Prec@1 94.000 (93.960) Prec@5 100.000 (99.800) +2022-11-14 14:38:34,790 Epoch: [230][250/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0403 (0.0368) Prec@1 92.000 (93.885) Prec@5 100.000 (99.808) +2022-11-14 14:38:35,248 Epoch: [230][260/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0466 (0.0371) Prec@1 91.000 (93.778) Prec@5 100.000 (99.815) +2022-11-14 14:38:35,707 Epoch: [230][270/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0321 (0.0370) Prec@1 94.000 (93.786) Prec@5 100.000 (99.821) +2022-11-14 14:38:36,181 Epoch: [230][280/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0412 (0.0371) Prec@1 92.000 (93.724) Prec@5 100.000 (99.828) +2022-11-14 14:38:36,651 Epoch: [230][290/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0400 (0.0372) Prec@1 93.000 (93.700) Prec@5 100.000 (99.833) +2022-11-14 14:38:37,111 Epoch: [230][300/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0332 (0.0371) Prec@1 95.000 (93.742) Prec@5 100.000 (99.839) +2022-11-14 14:38:37,568 Epoch: [230][310/500] Time 0.043 (0.040) Data 0.001 (0.003) Loss 0.0675 (0.0380) Prec@1 89.000 (93.594) Prec@5 99.000 (99.812) +2022-11-14 14:38:38,030 Epoch: [230][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0681 (0.0389) Prec@1 88.000 (93.424) Prec@5 100.000 (99.818) +2022-11-14 14:38:38,501 Epoch: [230][330/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0301 (0.0387) Prec@1 93.000 (93.412) Prec@5 100.000 (99.824) +2022-11-14 14:38:38,970 Epoch: [230][340/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0288 (0.0384) Prec@1 94.000 (93.429) Prec@5 100.000 (99.829) +2022-11-14 14:38:39,426 Epoch: [230][350/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0619 (0.0390) Prec@1 91.000 (93.361) Prec@5 100.000 (99.833) +2022-11-14 14:38:39,895 Epoch: [230][360/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0162 (0.0384) Prec@1 98.000 (93.486) Prec@5 100.000 (99.838) +2022-11-14 14:38:40,353 Epoch: [230][370/500] Time 0.047 (0.040) Data 0.002 (0.002) Loss 0.0369 (0.0384) Prec@1 94.000 (93.500) Prec@5 99.000 (99.816) +2022-11-14 14:38:40,846 Epoch: [230][380/500] Time 0.033 (0.040) Data 0.002 (0.002) Loss 0.0300 (0.0382) Prec@1 96.000 (93.564) Prec@5 100.000 (99.821) +2022-11-14 14:38:41,323 Epoch: [230][390/500] Time 0.059 (0.040) Data 0.002 (0.002) Loss 0.0436 (0.0383) Prec@1 93.000 (93.550) Prec@5 100.000 (99.825) +2022-11-14 14:38:41,835 Epoch: [230][400/500] Time 0.070 (0.040) Data 0.002 (0.002) Loss 0.0445 (0.0385) Prec@1 93.000 (93.537) Prec@5 99.000 (99.805) +2022-11-14 14:38:42,314 Epoch: [230][410/500] Time 0.049 (0.040) Data 0.002 (0.002) Loss 0.0268 (0.0382) Prec@1 95.000 (93.571) Prec@5 100.000 (99.810) +2022-11-14 14:38:42,823 Epoch: [230][420/500] Time 0.049 (0.040) Data 0.002 (0.002) Loss 0.0385 (0.0382) Prec@1 94.000 (93.581) Prec@5 100.000 (99.814) +2022-11-14 14:38:43,283 Epoch: [230][430/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0472 (0.0384) Prec@1 93.000 (93.568) Prec@5 100.000 (99.818) +2022-11-14 14:38:43,734 Epoch: [230][440/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0497 (0.0386) Prec@1 92.000 (93.533) Prec@5 99.000 (99.800) +2022-11-14 14:38:44,195 Epoch: [230][450/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0350 (0.0386) Prec@1 93.000 (93.522) Prec@5 100.000 (99.804) +2022-11-14 14:38:44,693 Epoch: [230][460/500] Time 0.038 (0.041) Data 0.002 (0.002) Loss 0.0367 (0.0385) Prec@1 94.000 (93.532) Prec@5 100.000 (99.809) +2022-11-14 14:38:45,162 Epoch: [230][470/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0355 (0.0385) Prec@1 96.000 (93.583) Prec@5 100.000 (99.812) +2022-11-14 14:38:45,622 Epoch: [230][480/500] Time 0.047 (0.041) Data 0.002 (0.002) Loss 0.0333 (0.0384) Prec@1 96.000 (93.633) Prec@5 100.000 (99.816) +2022-11-14 14:38:46,084 Epoch: [230][490/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0392 (0.0384) Prec@1 94.000 (93.640) Prec@5 100.000 (99.820) +2022-11-14 14:38:46,537 Epoch: [230][499/500] Time 0.047 (0.041) Data 0.002 (0.002) Loss 0.0297 (0.0382) Prec@1 95.000 (93.667) Prec@5 99.000 (99.804) +2022-11-14 14:38:46,827 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0766 (0.0766) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:46,835 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0669) Prec@1 92.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:38:46,844 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0753) Prec@1 86.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 14:38:46,856 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0762) Prec@1 86.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 14:38:46,866 Test: [4/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0763) Prec@1 89.000 (87.600) Prec@5 100.000 (99.800) +2022-11-14 14:38:46,875 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0375 (0.0699) Prec@1 95.000 (88.833) Prec@5 100.000 (99.833) +2022-11-14 14:38:46,885 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0703) Prec@1 88.000 (88.714) Prec@5 100.000 (99.857) +2022-11-14 14:38:46,896 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0717) Prec@1 85.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 14:38:46,906 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0731) Prec@1 87.000 (88.111) Prec@5 100.000 (99.778) +2022-11-14 14:38:46,914 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0744) Prec@1 82.000 (87.500) Prec@5 98.000 (99.600) +2022-11-14 14:38:46,923 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0735) Prec@1 89.000 (87.636) Prec@5 100.000 (99.636) +2022-11-14 14:38:46,933 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0745) Prec@1 86.000 (87.500) Prec@5 100.000 (99.667) +2022-11-14 14:38:46,943 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 89.000 (87.615) Prec@5 100.000 (99.692) +2022-11-14 14:38:46,951 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0753) Prec@1 86.000 (87.500) Prec@5 99.000 (99.643) +2022-11-14 14:38:46,961 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0739) Prec@1 91.000 (87.733) Prec@5 100.000 (99.667) +2022-11-14 14:38:46,970 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0734) Prec@1 92.000 (88.000) Prec@5 98.000 (99.562) +2022-11-14 14:38:46,979 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0726) Prec@1 90.000 (88.118) Prec@5 99.000 (99.529) +2022-11-14 14:38:46,989 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1301 (0.0758) Prec@1 79.000 (87.611) Prec@5 100.000 (99.556) +2022-11-14 14:38:46,998 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0760) Prec@1 85.000 (87.474) Prec@5 98.000 (99.474) +2022-11-14 14:38:47,007 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0773) Prec@1 84.000 (87.300) Prec@5 99.000 (99.450) +2022-11-14 14:38:47,018 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0778) Prec@1 85.000 (87.190) Prec@5 100.000 (99.476) +2022-11-14 14:38:47,028 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0782) Prec@1 85.000 (87.091) Prec@5 99.000 (99.455) +2022-11-14 14:38:47,038 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0787) Prec@1 86.000 (87.043) Prec@5 99.000 (99.435) +2022-11-14 14:38:47,047 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0778) Prec@1 92.000 (87.250) Prec@5 100.000 (99.458) +2022-11-14 14:38:47,057 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0785) Prec@1 86.000 (87.200) Prec@5 100.000 (99.480) +2022-11-14 14:38:47,067 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0793) Prec@1 83.000 (87.038) Prec@5 97.000 (99.385) +2022-11-14 14:38:47,077 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0784) Prec@1 93.000 (87.259) Prec@5 100.000 (99.407) +2022-11-14 14:38:47,087 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0778) Prec@1 90.000 (87.357) Prec@5 100.000 (99.429) +2022-11-14 14:38:47,097 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0773) Prec@1 91.000 (87.483) Prec@5 98.000 (99.379) +2022-11-14 14:38:47,107 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0774) Prec@1 84.000 (87.367) Prec@5 100.000 (99.400) +2022-11-14 14:38:47,116 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0775) Prec@1 88.000 (87.387) Prec@5 100.000 (99.419) +2022-11-14 14:38:47,126 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0770) Prec@1 88.000 (87.406) Prec@5 100.000 (99.438) +2022-11-14 14:38:47,137 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0767) Prec@1 89.000 (87.455) Prec@5 100.000 (99.455) +2022-11-14 14:38:47,146 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0771) Prec@1 84.000 (87.353) Prec@5 99.000 (99.441) +2022-11-14 14:38:47,156 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0768) Prec@1 89.000 (87.400) Prec@5 100.000 (99.457) +2022-11-14 14:38:47,167 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0763) Prec@1 90.000 (87.472) Prec@5 100.000 (99.472) +2022-11-14 14:38:47,178 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0766) Prec@1 84.000 (87.378) Prec@5 100.000 (99.486) +2022-11-14 14:38:47,187 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0768) Prec@1 86.000 (87.342) Prec@5 98.000 (99.447) +2022-11-14 14:38:47,197 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0760) Prec@1 93.000 (87.487) Prec@5 99.000 (99.436) +2022-11-14 14:38:47,207 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0758) Prec@1 87.000 (87.475) Prec@5 100.000 (99.450) +2022-11-14 14:38:47,216 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0763) Prec@1 80.000 (87.293) Prec@5 98.000 (99.415) +2022-11-14 14:38:47,228 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0766) Prec@1 89.000 (87.333) Prec@5 98.000 (99.381) +2022-11-14 14:38:47,237 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0761) Prec@1 92.000 (87.442) Prec@5 99.000 (99.372) +2022-11-14 14:38:47,247 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0761) Prec@1 88.000 (87.455) Prec@5 97.000 (99.318) +2022-11-14 14:38:47,255 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0757) Prec@1 92.000 (87.556) Prec@5 99.000 (99.311) +2022-11-14 14:38:47,264 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0761) Prec@1 83.000 (87.457) Prec@5 98.000 (99.283) +2022-11-14 14:38:47,274 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0759) Prec@1 90.000 (87.511) Prec@5 100.000 (99.298) +2022-11-14 14:38:47,284 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0765) Prec@1 85.000 (87.458) Prec@5 97.000 (99.250) +2022-11-14 14:38:47,295 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0759) Prec@1 93.000 (87.571) Prec@5 100.000 (99.265) +2022-11-14 14:38:47,304 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.0766) Prec@1 83.000 (87.480) Prec@5 100.000 (99.280) +2022-11-14 14:38:47,313 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0762) Prec@1 91.000 (87.549) Prec@5 100.000 (99.294) +2022-11-14 14:38:47,323 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0764) Prec@1 84.000 (87.481) Prec@5 100.000 (99.308) +2022-11-14 14:38:47,332 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0767) Prec@1 86.000 (87.453) Prec@5 100.000 (99.321) +2022-11-14 14:38:47,342 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0766) Prec@1 87.000 (87.444) Prec@5 100.000 (99.333) +2022-11-14 14:38:47,352 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0767) Prec@1 86.000 (87.418) Prec@5 100.000 (99.345) +2022-11-14 14:38:47,361 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0766) Prec@1 90.000 (87.464) Prec@5 100.000 (99.357) +2022-11-14 14:38:47,370 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0767) Prec@1 87.000 (87.456) Prec@5 100.000 (99.368) +2022-11-14 14:38:47,382 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0766) Prec@1 89.000 (87.483) Prec@5 98.000 (99.345) +2022-11-14 14:38:47,392 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0768) Prec@1 84.000 (87.424) Prec@5 100.000 (99.356) +2022-11-14 14:38:47,401 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0768) Prec@1 87.000 (87.417) Prec@5 100.000 (99.367) +2022-11-14 14:38:47,412 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0767) Prec@1 90.000 (87.459) Prec@5 100.000 (99.377) +2022-11-14 14:38:47,422 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0770) Prec@1 83.000 (87.387) Prec@5 100.000 (99.387) +2022-11-14 14:38:47,432 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0767) Prec@1 89.000 (87.413) Prec@5 100.000 (99.397) +2022-11-14 14:38:47,442 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0764) Prec@1 90.000 (87.453) Prec@5 100.000 (99.406) +2022-11-14 14:38:47,452 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0766) Prec@1 88.000 (87.462) Prec@5 99.000 (99.400) +2022-11-14 14:38:47,463 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0768) Prec@1 84.000 (87.409) Prec@5 98.000 (99.379) +2022-11-14 14:38:47,474 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0389 (0.0762) Prec@1 94.000 (87.507) Prec@5 99.000 (99.373) +2022-11-14 14:38:47,484 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0762) Prec@1 87.000 (87.500) Prec@5 99.000 (99.368) +2022-11-14 14:38:47,494 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0757) Prec@1 93.000 (87.580) Prec@5 99.000 (99.362) +2022-11-14 14:38:47,507 Test: [69/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0755) Prec@1 92.000 (87.643) Prec@5 100.000 (99.371) +2022-11-14 14:38:47,517 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0757) Prec@1 86.000 (87.620) Prec@5 100.000 (99.380) +2022-11-14 14:38:47,526 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0755) Prec@1 91.000 (87.667) Prec@5 100.000 (99.389) +2022-11-14 14:38:47,536 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0752) Prec@1 91.000 (87.712) Prec@5 100.000 (99.397) +2022-11-14 14:38:47,546 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0749) Prec@1 91.000 (87.757) Prec@5 100.000 (99.405) +2022-11-14 14:38:47,555 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0752) Prec@1 81.000 (87.667) Prec@5 100.000 (99.413) +2022-11-14 14:38:47,564 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0748) Prec@1 94.000 (87.750) Prec@5 99.000 (99.408) +2022-11-14 14:38:47,574 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0749) Prec@1 87.000 (87.740) Prec@5 99.000 (99.403) +2022-11-14 14:38:47,583 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0751) Prec@1 86.000 (87.718) Prec@5 96.000 (99.359) +2022-11-14 14:38:47,593 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0751) Prec@1 87.000 (87.709) Prec@5 100.000 (99.367) +2022-11-14 14:38:47,603 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0753) Prec@1 83.000 (87.650) Prec@5 99.000 (99.362) +2022-11-14 14:38:47,613 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0753) Prec@1 87.000 (87.642) Prec@5 98.000 (99.346) +2022-11-14 14:38:47,624 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0756) Prec@1 83.000 (87.585) Prec@5 99.000 (99.341) +2022-11-14 14:38:47,633 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0756) Prec@1 90.000 (87.614) Prec@5 99.000 (99.337) +2022-11-14 14:38:47,643 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0756) Prec@1 85.000 (87.583) Prec@5 100.000 (99.345) +2022-11-14 14:38:47,652 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0757) Prec@1 84.000 (87.541) Prec@5 100.000 (99.353) +2022-11-14 14:38:47,661 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0758) Prec@1 87.000 (87.535) Prec@5 99.000 (99.349) +2022-11-14 14:38:47,671 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0758) Prec@1 85.000 (87.506) Prec@5 98.000 (99.333) +2022-11-14 14:38:47,683 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0761) Prec@1 86.000 (87.489) Prec@5 98.000 (99.318) +2022-11-14 14:38:47,695 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0758) Prec@1 93.000 (87.551) Prec@5 100.000 (99.326) +2022-11-14 14:38:47,707 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0757) Prec@1 91.000 (87.589) Prec@5 99.000 (99.322) +2022-11-14 14:38:47,717 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0755) Prec@1 91.000 (87.626) Prec@5 99.000 (99.319) +2022-11-14 14:38:47,727 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0752) Prec@1 92.000 (87.674) Prec@5 99.000 (99.315) +2022-11-14 14:38:47,736 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0754) Prec@1 83.000 (87.624) Prec@5 99.000 (99.312) +2022-11-14 14:38:47,746 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0754) Prec@1 87.000 (87.617) Prec@5 100.000 (99.319) +2022-11-14 14:38:47,755 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0754) Prec@1 87.000 (87.611) Prec@5 99.000 (99.316) +2022-11-14 14:38:47,765 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0752) Prec@1 93.000 (87.667) Prec@5 99.000 (99.312) +2022-11-14 14:38:47,775 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0750) Prec@1 91.000 (87.701) Prec@5 98.000 (99.299) +2022-11-14 14:38:47,785 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0753) Prec@1 83.000 (87.653) Prec@5 99.000 (99.296) +2022-11-14 14:38:47,795 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0756) Prec@1 84.000 (87.616) Prec@5 99.000 (99.293) +2022-11-14 14:38:47,804 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0757) Prec@1 89.000 (87.630) Prec@5 100.000 (99.300) +2022-11-14 14:38:47,863 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:38:48,194 Epoch: [231][0/500] Time 0.033 (0.033) Data 0.241 (0.241) Loss 0.0220 (0.0220) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:48,427 Epoch: [231][10/500] Time 0.020 (0.021) Data 0.002 (0.024) Loss 0.0255 (0.0238) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 14:38:48,657 Epoch: [231][20/500] Time 0.016 (0.021) Data 0.002 (0.013) Loss 0.0273 (0.0250) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:48,872 Epoch: [231][30/500] Time 0.020 (0.020) Data 0.002 (0.010) Loss 0.0420 (0.0292) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 14:38:49,085 Epoch: [231][40/500] Time 0.018 (0.020) Data 0.002 (0.008) Loss 0.0302 (0.0294) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:38:49,374 Epoch: [231][50/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.0494 (0.0327) Prec@1 93.000 (94.667) Prec@5 99.000 (99.833) +2022-11-14 14:38:49,659 Epoch: [231][60/500] Time 0.029 (0.022) Data 0.002 (0.006) Loss 0.0227 (0.0313) Prec@1 97.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 14:38:49,961 Epoch: [231][70/500] Time 0.043 (0.022) Data 0.002 (0.005) Loss 0.0626 (0.0352) Prec@1 90.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 14:38:50,354 Epoch: [231][80/500] Time 0.031 (0.024) Data 0.002 (0.005) Loss 0.0474 (0.0366) Prec@1 92.000 (94.111) Prec@5 99.000 (99.778) +2022-11-14 14:38:50,728 Epoch: [231][90/500] Time 0.032 (0.025) Data 0.002 (0.004) Loss 0.0208 (0.0350) Prec@1 97.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:38:51,101 Epoch: [231][100/500] Time 0.033 (0.026) Data 0.002 (0.004) Loss 0.0369 (0.0352) Prec@1 95.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 14:38:51,500 Epoch: [231][110/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0384 (0.0354) Prec@1 93.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 14:38:51,893 Epoch: [231][120/500] Time 0.036 (0.027) Data 0.002 (0.004) Loss 0.0438 (0.0361) Prec@1 94.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 14:38:52,297 Epoch: [231][130/500] Time 0.040 (0.028) Data 0.002 (0.004) Loss 0.0393 (0.0363) Prec@1 94.000 (94.286) Prec@5 99.000 (99.786) +2022-11-14 14:38:52,713 Epoch: [231][140/500] Time 0.041 (0.029) Data 0.002 (0.004) Loss 0.0416 (0.0367) Prec@1 94.000 (94.267) Prec@5 100.000 (99.800) +2022-11-14 14:38:53,155 Epoch: [231][150/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0135 (0.0352) Prec@1 98.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 14:38:53,609 Epoch: [231][160/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0288 (0.0348) Prec@1 96.000 (94.588) Prec@5 100.000 (99.824) +2022-11-14 14:38:54,041 Epoch: [231][170/500] Time 0.040 (0.031) Data 0.003 (0.003) Loss 0.0545 (0.0359) Prec@1 89.000 (94.278) Prec@5 100.000 (99.833) +2022-11-14 14:38:54,427 Epoch: [231][180/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0502 (0.0367) Prec@1 89.000 (94.000) Prec@5 100.000 (99.842) +2022-11-14 14:38:54,836 Epoch: [231][190/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0429 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (99.850) +2022-11-14 14:38:55,216 Epoch: [231][200/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0648 (0.0383) Prec@1 89.000 (93.762) Prec@5 100.000 (99.857) +2022-11-14 14:38:55,593 Epoch: [231][210/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0502 (0.0389) Prec@1 91.000 (93.636) Prec@5 100.000 (99.864) +2022-11-14 14:38:55,969 Epoch: [231][220/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0286 (0.0384) Prec@1 96.000 (93.739) Prec@5 100.000 (99.870) +2022-11-14 14:38:56,351 Epoch: [231][230/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0228 (0.0378) Prec@1 98.000 (93.917) Prec@5 100.000 (99.875) +2022-11-14 14:38:56,807 Epoch: [231][240/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0313 (0.0375) Prec@1 95.000 (93.960) Prec@5 100.000 (99.880) +2022-11-14 14:38:57,213 Epoch: [231][250/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0357 (0.0374) Prec@1 93.000 (93.923) Prec@5 100.000 (99.885) +2022-11-14 14:38:57,648 Epoch: [231][260/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0601 (0.0383) Prec@1 89.000 (93.741) Prec@5 100.000 (99.889) +2022-11-14 14:38:58,091 Epoch: [231][270/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0275 (0.0379) Prec@1 95.000 (93.786) Prec@5 100.000 (99.893) +2022-11-14 14:38:58,454 Epoch: [231][280/500] Time 0.030 (0.033) Data 0.002 (0.003) Loss 0.0324 (0.0377) Prec@1 96.000 (93.862) Prec@5 100.000 (99.897) +2022-11-14 14:38:58,888 Epoch: [231][290/500] Time 0.025 (0.033) Data 0.002 (0.003) Loss 0.0568 (0.0383) Prec@1 92.000 (93.800) Prec@5 100.000 (99.900) +2022-11-14 14:38:59,256 Epoch: [231][300/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0540 (0.0388) Prec@1 92.000 (93.742) Prec@5 100.000 (99.903) +2022-11-14 14:38:59,665 Epoch: [231][310/500] Time 0.050 (0.033) Data 0.002 (0.003) Loss 0.0498 (0.0392) Prec@1 90.000 (93.625) Prec@5 100.000 (99.906) +2022-11-14 14:39:00,049 Epoch: [231][320/500] Time 0.047 (0.033) Data 0.002 (0.003) Loss 0.0509 (0.0395) Prec@1 93.000 (93.606) Prec@5 99.000 (99.879) +2022-11-14 14:39:00,419 Epoch: [231][330/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0423 (0.0396) Prec@1 94.000 (93.618) Prec@5 100.000 (99.882) +2022-11-14 14:39:00,842 Epoch: [231][340/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0480 (0.0399) Prec@1 95.000 (93.657) Prec@5 98.000 (99.829) +2022-11-14 14:39:01,207 Epoch: [231][350/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0170 (0.0392) Prec@1 98.000 (93.778) Prec@5 100.000 (99.833) +2022-11-14 14:39:01,663 Epoch: [231][360/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0174 (0.0386) Prec@1 95.000 (93.811) Prec@5 100.000 (99.838) +2022-11-14 14:39:02,035 Epoch: [231][370/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0354 (0.0385) Prec@1 93.000 (93.789) Prec@5 100.000 (99.842) +2022-11-14 14:39:02,450 Epoch: [231][380/500] Time 0.036 (0.033) Data 0.003 (0.003) Loss 0.0298 (0.0383) Prec@1 96.000 (93.846) Prec@5 99.000 (99.821) +2022-11-14 14:39:02,853 Epoch: [231][390/500] Time 0.028 (0.033) Data 0.003 (0.003) Loss 0.0500 (0.0386) Prec@1 94.000 (93.850) Prec@5 100.000 (99.825) +2022-11-14 14:39:03,246 Epoch: [231][400/500] Time 0.031 (0.034) Data 0.003 (0.003) Loss 0.0504 (0.0389) Prec@1 92.000 (93.805) Prec@5 100.000 (99.829) +2022-11-14 14:39:03,626 Epoch: [231][410/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0362 (0.0388) Prec@1 95.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:39:04,028 Epoch: [231][420/500] Time 0.027 (0.034) Data 0.002 (0.003) Loss 0.0333 (0.0387) Prec@1 93.000 (93.814) Prec@5 99.000 (99.814) +2022-11-14 14:39:04,456 Epoch: [231][430/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0273 (0.0384) Prec@1 96.000 (93.864) Prec@5 100.000 (99.818) +2022-11-14 14:39:04,823 Epoch: [231][440/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0420 (0.0385) Prec@1 94.000 (93.867) Prec@5 100.000 (99.822) +2022-11-14 14:39:05,201 Epoch: [231][450/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0600 (0.0390) Prec@1 89.000 (93.761) Prec@5 100.000 (99.826) +2022-11-14 14:39:05,585 Epoch: [231][460/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0462 (0.0391) Prec@1 92.000 (93.723) Prec@5 100.000 (99.830) +2022-11-14 14:39:05,969 Epoch: [231][470/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0235 (0.0388) Prec@1 97.000 (93.792) Prec@5 100.000 (99.833) +2022-11-14 14:39:06,351 Epoch: [231][480/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0386 (0.0388) Prec@1 95.000 (93.816) Prec@5 99.000 (99.816) +2022-11-14 14:39:06,729 Epoch: [231][490/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0392 (0.0388) Prec@1 93.000 (93.800) Prec@5 100.000 (99.820) +2022-11-14 14:39:07,073 Epoch: [231][499/500] Time 0.036 (0.034) Data 0.001 (0.002) Loss 0.0362 (0.0388) Prec@1 93.000 (93.784) Prec@5 100.000 (99.824) +2022-11-14 14:39:07,354 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:39:07,361 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0608) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:39:07,370 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0655) Prec@1 90.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 14:39:07,381 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0610) Prec@1 92.000 (90.000) Prec@5 98.000 (99.250) +2022-11-14 14:39:07,391 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0645) Prec@1 88.000 (89.600) Prec@5 99.000 (99.200) +2022-11-14 14:39:07,400 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0609) Prec@1 93.000 (90.167) Prec@5 100.000 (99.333) +2022-11-14 14:39:07,408 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0598) Prec@1 92.000 (90.429) Prec@5 100.000 (99.429) +2022-11-14 14:39:07,420 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0618) Prec@1 86.000 (89.875) Prec@5 99.000 (99.375) +2022-11-14 14:39:07,432 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0650) Prec@1 88.000 (89.667) Prec@5 100.000 (99.444) +2022-11-14 14:39:07,442 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0674) Prec@1 82.000 (88.900) Prec@5 99.000 (99.400) +2022-11-14 14:39:07,454 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0669) Prec@1 91.000 (89.091) Prec@5 99.000 (99.364) +2022-11-14 14:39:07,466 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0683) Prec@1 85.000 (88.750) Prec@5 100.000 (99.417) +2022-11-14 14:39:07,478 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0665) Prec@1 92.000 (89.000) Prec@5 100.000 (99.462) +2022-11-14 14:39:07,490 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0679) Prec@1 90.000 (89.071) Prec@5 98.000 (99.357) +2022-11-14 14:39:07,500 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0674) Prec@1 91.000 (89.200) Prec@5 99.000 (99.333) +2022-11-14 14:39:07,513 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0677) Prec@1 87.000 (89.062) Prec@5 99.000 (99.312) +2022-11-14 14:39:07,525 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0673) Prec@1 91.000 (89.176) Prec@5 98.000 (99.235) +2022-11-14 14:39:07,536 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0688) Prec@1 87.000 (89.056) Prec@5 99.000 (99.222) +2022-11-14 14:39:07,549 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0698) Prec@1 82.000 (88.684) Prec@5 99.000 (99.211) +2022-11-14 14:39:07,562 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0706) Prec@1 86.000 (88.550) Prec@5 98.000 (99.150) +2022-11-14 14:39:07,575 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0711) Prec@1 89.000 (88.571) Prec@5 100.000 (99.190) +2022-11-14 14:39:07,587 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0713) Prec@1 88.000 (88.545) Prec@5 100.000 (99.227) +2022-11-14 14:39:07,599 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0726) Prec@1 84.000 (88.348) Prec@5 99.000 (99.217) +2022-11-14 14:39:07,612 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0724) Prec@1 86.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 14:39:07,626 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0737) Prec@1 84.000 (88.080) Prec@5 100.000 (99.280) +2022-11-14 14:39:07,640 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0744) Prec@1 86.000 (88.000) Prec@5 99.000 (99.269) +2022-11-14 14:39:07,653 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0740) Prec@1 90.000 (88.074) Prec@5 100.000 (99.296) +2022-11-14 14:39:07,666 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0735) Prec@1 88.000 (88.071) Prec@5 100.000 (99.321) +2022-11-14 14:39:07,678 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0732) Prec@1 90.000 (88.138) Prec@5 98.000 (99.276) +2022-11-14 14:39:07,690 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0729) Prec@1 89.000 (88.167) Prec@5 100.000 (99.300) +2022-11-14 14:39:07,705 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0731) Prec@1 88.000 (88.161) Prec@5 100.000 (99.323) +2022-11-14 14:39:07,717 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0729) Prec@1 90.000 (88.219) Prec@5 99.000 (99.312) +2022-11-14 14:39:07,730 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0734) Prec@1 84.000 (88.091) Prec@5 100.000 (99.333) +2022-11-14 14:39:07,745 Test: [33/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0736) Prec@1 88.000 (88.088) Prec@5 100.000 (99.353) +2022-11-14 14:39:07,759 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0738) Prec@1 84.000 (87.971) Prec@5 98.000 (99.314) +2022-11-14 14:39:07,772 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0738) Prec@1 87.000 (87.944) Prec@5 100.000 (99.333) +2022-11-14 14:39:07,786 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0739) Prec@1 88.000 (87.946) Prec@5 98.000 (99.297) +2022-11-14 14:39:07,800 Test: [37/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0744) Prec@1 83.000 (87.816) Prec@5 100.000 (99.316) +2022-11-14 14:39:07,814 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0484 (0.0737) Prec@1 93.000 (87.949) Prec@5 99.000 (99.308) +2022-11-14 14:39:07,827 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0734) Prec@1 91.000 (88.025) Prec@5 99.000 (99.300) +2022-11-14 14:39:07,840 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0737) Prec@1 83.000 (87.902) Prec@5 97.000 (99.244) +2022-11-14 14:39:07,852 Test: [41/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0735) Prec@1 89.000 (87.929) Prec@5 99.000 (99.238) +2022-11-14 14:39:07,866 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0729) Prec@1 90.000 (87.977) Prec@5 100.000 (99.256) +2022-11-14 14:39:07,878 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0729) Prec@1 90.000 (88.023) Prec@5 98.000 (99.227) +2022-11-14 14:39:07,889 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0723) Prec@1 93.000 (88.133) Prec@5 100.000 (99.244) +2022-11-14 14:39:07,902 Test: [45/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0728) Prec@1 82.000 (88.000) Prec@5 100.000 (99.261) +2022-11-14 14:39:07,916 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0724) Prec@1 91.000 (88.064) Prec@5 100.000 (99.277) +2022-11-14 14:39:07,930 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0730) Prec@1 83.000 (87.958) Prec@5 99.000 (99.271) +2022-11-14 14:39:07,943 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0725) Prec@1 94.000 (88.082) Prec@5 100.000 (99.286) +2022-11-14 14:39:07,957 Test: [49/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1216 (0.0735) Prec@1 79.000 (87.900) Prec@5 99.000 (99.280) +2022-11-14 14:39:07,971 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0732) Prec@1 89.000 (87.922) Prec@5 100.000 (99.294) +2022-11-14 14:39:07,984 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0735) Prec@1 85.000 (87.865) Prec@5 100.000 (99.308) +2022-11-14 14:39:07,997 Test: [52/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0734) Prec@1 89.000 (87.887) Prec@5 99.000 (99.302) +2022-11-14 14:39:08,010 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0737) Prec@1 88.000 (87.889) Prec@5 100.000 (99.315) +2022-11-14 14:39:08,024 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 86.000 (87.855) Prec@5 100.000 (99.327) +2022-11-14 14:39:08,036 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0738) Prec@1 91.000 (87.911) Prec@5 99.000 (99.321) +2022-11-14 14:39:08,050 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0739) Prec@1 87.000 (87.895) Prec@5 100.000 (99.333) +2022-11-14 14:39:08,064 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0738) Prec@1 91.000 (87.948) Prec@5 100.000 (99.345) +2022-11-14 14:39:08,077 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0745) Prec@1 82.000 (87.847) Prec@5 98.000 (99.322) +2022-11-14 14:39:08,090 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0745) Prec@1 87.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 14:39:08,103 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0743) Prec@1 89.000 (87.852) Prec@5 100.000 (99.344) +2022-11-14 14:39:08,117 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0743) Prec@1 89.000 (87.871) Prec@5 100.000 (99.355) +2022-11-14 14:39:08,129 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0738) Prec@1 95.000 (87.984) Prec@5 100.000 (99.365) +2022-11-14 14:39:08,141 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0734) Prec@1 91.000 (88.031) Prec@5 100.000 (99.375) +2022-11-14 14:39:08,156 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0738) Prec@1 83.000 (87.954) Prec@5 98.000 (99.354) +2022-11-14 14:39:08,169 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0738) Prec@1 86.000 (87.924) Prec@5 99.000 (99.348) +2022-11-14 14:39:08,183 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0736) Prec@1 91.000 (87.970) Prec@5 100.000 (99.358) +2022-11-14 14:39:08,196 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0737) Prec@1 88.000 (87.971) Prec@5 99.000 (99.353) +2022-11-14 14:39:08,209 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0736) Prec@1 90.000 (88.000) Prec@5 100.000 (99.362) +2022-11-14 14:39:08,224 Test: [69/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0737) Prec@1 89.000 (88.014) Prec@5 98.000 (99.343) +2022-11-14 14:39:08,237 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0741) Prec@1 85.000 (87.972) Prec@5 99.000 (99.338) +2022-11-14 14:39:08,250 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0738) Prec@1 90.000 (88.000) Prec@5 100.000 (99.347) +2022-11-14 14:39:08,263 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0737) Prec@1 90.000 (88.027) Prec@5 100.000 (99.356) +2022-11-14 14:39:08,276 Test: [73/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0395 (0.0732) Prec@1 94.000 (88.108) Prec@5 100.000 (99.365) +2022-11-14 14:39:08,289 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0735) Prec@1 85.000 (88.067) Prec@5 99.000 (99.360) +2022-11-14 14:39:08,301 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0732) Prec@1 91.000 (88.105) Prec@5 100.000 (99.368) +2022-11-14 14:39:08,315 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0731) Prec@1 87.000 (88.091) Prec@5 99.000 (99.364) +2022-11-14 14:39:08,329 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0731) Prec@1 88.000 (88.090) Prec@5 100.000 (99.372) +2022-11-14 14:39:08,342 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0729) Prec@1 90.000 (88.114) Prec@5 100.000 (99.380) +2022-11-14 14:39:08,355 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0728) Prec@1 89.000 (88.125) Prec@5 100.000 (99.388) +2022-11-14 14:39:08,369 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0729) Prec@1 88.000 (88.123) Prec@5 98.000 (99.370) +2022-11-14 14:39:08,383 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0734) Prec@1 84.000 (88.073) Prec@5 100.000 (99.378) +2022-11-14 14:39:08,396 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0733) Prec@1 89.000 (88.084) Prec@5 99.000 (99.373) +2022-11-14 14:39:08,409 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0733) Prec@1 87.000 (88.071) Prec@5 99.000 (99.369) +2022-11-14 14:39:08,422 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0733) Prec@1 88.000 (88.071) Prec@5 100.000 (99.376) +2022-11-14 14:39:08,435 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0736) Prec@1 85.000 (88.035) Prec@5 99.000 (99.372) +2022-11-14 14:39:08,448 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0735) Prec@1 92.000 (88.080) Prec@5 100.000 (99.379) +2022-11-14 14:39:08,459 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0737) Prec@1 87.000 (88.068) Prec@5 98.000 (99.364) +2022-11-14 14:39:08,473 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0734) Prec@1 92.000 (88.112) Prec@5 100.000 (99.371) +2022-11-14 14:39:08,487 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0732) Prec@1 93.000 (88.167) Prec@5 100.000 (99.378) +2022-11-14 14:39:08,500 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0730) Prec@1 91.000 (88.198) Prec@5 100.000 (99.385) +2022-11-14 14:39:08,513 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0335 (0.0726) Prec@1 95.000 (88.272) Prec@5 99.000 (99.380) +2022-11-14 14:39:08,525 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0728) Prec@1 86.000 (88.247) Prec@5 100.000 (99.387) +2022-11-14 14:39:08,539 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0728) Prec@1 90.000 (88.266) Prec@5 100.000 (99.394) +2022-11-14 14:39:08,552 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0728) Prec@1 87.000 (88.253) Prec@5 99.000 (99.389) +2022-11-14 14:39:08,564 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0726) Prec@1 92.000 (88.292) Prec@5 99.000 (99.385) +2022-11-14 14:39:08,577 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0723) Prec@1 92.000 (88.330) Prec@5 99.000 (99.381) +2022-11-14 14:39:08,590 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0726) Prec@1 85.000 (88.296) Prec@5 100.000 (99.388) +2022-11-14 14:39:08,602 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0728) Prec@1 83.000 (88.242) Prec@5 99.000 (99.384) +2022-11-14 14:39:08,615 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0729) Prec@1 87.000 (88.230) Prec@5 98.000 (99.370) +2022-11-14 14:39:08,684 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:39:09,001 Epoch: [232][0/500] Time 0.033 (0.033) Data 0.224 (0.224) Loss 0.0442 (0.0442) Prec@1 93.000 (93.000) Prec@5 98.000 (98.000) +2022-11-14 14:39:09,229 Epoch: [232][10/500] Time 0.021 (0.021) Data 0.003 (0.022) Loss 0.0496 (0.0469) Prec@1 90.000 (91.500) Prec@5 100.000 (99.000) +2022-11-14 14:39:09,529 Epoch: [232][20/500] Time 0.031 (0.023) Data 0.002 (0.012) Loss 0.0186 (0.0374) Prec@1 98.000 (93.667) Prec@5 100.000 (99.333) +2022-11-14 14:39:09,896 Epoch: [232][30/500] Time 0.043 (0.026) Data 0.002 (0.009) Loss 0.0652 (0.0444) Prec@1 88.000 (92.250) Prec@5 100.000 (99.500) +2022-11-14 14:39:10,250 Epoch: [232][40/500] Time 0.043 (0.028) Data 0.002 (0.007) Loss 0.0281 (0.0411) Prec@1 95.000 (92.800) Prec@5 100.000 (99.600) +2022-11-14 14:39:10,610 Epoch: [232][50/500] Time 0.033 (0.028) Data 0.002 (0.006) Loss 0.0289 (0.0391) Prec@1 94.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:39:10,961 Epoch: [232][60/500] Time 0.030 (0.029) Data 0.002 (0.006) Loss 0.0248 (0.0371) Prec@1 96.000 (93.429) Prec@5 100.000 (99.714) +2022-11-14 14:39:11,314 Epoch: [232][70/500] Time 0.031 (0.029) Data 0.002 (0.005) Loss 0.0506 (0.0388) Prec@1 91.000 (93.125) Prec@5 100.000 (99.750) +2022-11-14 14:39:11,665 Epoch: [232][80/500] Time 0.032 (0.029) Data 0.002 (0.005) Loss 0.0633 (0.0415) Prec@1 89.000 (92.667) Prec@5 100.000 (99.778) +2022-11-14 14:39:12,021 Epoch: [232][90/500] Time 0.034 (0.030) Data 0.002 (0.004) Loss 0.0184 (0.0392) Prec@1 96.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:39:12,388 Epoch: [232][100/500] Time 0.033 (0.030) Data 0.002 (0.004) Loss 0.0244 (0.0378) Prec@1 96.000 (93.273) Prec@5 100.000 (99.818) +2022-11-14 14:39:12,748 Epoch: [232][110/500] Time 0.033 (0.030) Data 0.002 (0.004) Loss 0.0205 (0.0364) Prec@1 98.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 14:39:13,115 Epoch: [232][120/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0438 (0.0370) Prec@1 93.000 (93.615) Prec@5 100.000 (99.846) +2022-11-14 14:39:13,469 Epoch: [232][130/500] Time 0.028 (0.030) Data 0.002 (0.004) Loss 0.0508 (0.0379) Prec@1 92.000 (93.500) Prec@5 100.000 (99.857) +2022-11-14 14:39:13,829 Epoch: [232][140/500] Time 0.029 (0.030) Data 0.002 (0.004) Loss 0.0685 (0.0400) Prec@1 90.000 (93.267) Prec@5 100.000 (99.867) +2022-11-14 14:39:14,192 Epoch: [232][150/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.0270 (0.0392) Prec@1 97.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 14:39:14,544 Epoch: [232][160/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0347 (0.0389) Prec@1 96.000 (93.647) Prec@5 100.000 (99.882) +2022-11-14 14:39:14,902 Epoch: [232][170/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0442 (0.0392) Prec@1 89.000 (93.389) Prec@5 100.000 (99.889) +2022-11-14 14:39:15,274 Epoch: [232][180/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0503 (0.0398) Prec@1 92.000 (93.316) Prec@5 99.000 (99.842) +2022-11-14 14:39:15,640 Epoch: [232][190/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0516 (0.0404) Prec@1 91.000 (93.200) Prec@5 100.000 (99.850) +2022-11-14 14:39:15,998 Epoch: [232][200/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0193 (0.0394) Prec@1 97.000 (93.381) Prec@5 100.000 (99.857) +2022-11-14 14:39:16,364 Epoch: [232][210/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0246 (0.0387) Prec@1 96.000 (93.500) Prec@5 100.000 (99.864) +2022-11-14 14:39:16,741 Epoch: [232][220/500] Time 0.029 (0.031) Data 0.003 (0.003) Loss 0.0575 (0.0395) Prec@1 90.000 (93.348) Prec@5 100.000 (99.870) +2022-11-14 14:39:17,100 Epoch: [232][230/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0426 (0.0396) Prec@1 93.000 (93.333) Prec@5 100.000 (99.875) +2022-11-14 14:39:17,463 Epoch: [232][240/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0564 (0.0403) Prec@1 90.000 (93.200) Prec@5 100.000 (99.880) +2022-11-14 14:39:17,827 Epoch: [232][250/500] Time 0.029 (0.031) Data 0.002 (0.003) Loss 0.0290 (0.0399) Prec@1 95.000 (93.269) Prec@5 100.000 (99.885) +2022-11-14 14:39:18,201 Epoch: [232][260/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0305 (0.0395) Prec@1 94.000 (93.296) Prec@5 100.000 (99.889) +2022-11-14 14:39:18,557 Epoch: [232][270/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0490 (0.0399) Prec@1 93.000 (93.286) Prec@5 100.000 (99.893) +2022-11-14 14:39:18,933 Epoch: [232][280/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0265 (0.0394) Prec@1 96.000 (93.379) Prec@5 100.000 (99.897) +2022-11-14 14:39:19,294 Epoch: [232][290/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0387 (0.0394) Prec@1 93.000 (93.367) Prec@5 99.000 (99.867) +2022-11-14 14:39:19,650 Epoch: [232][300/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0494 (0.0397) Prec@1 91.000 (93.290) Prec@5 99.000 (99.839) +2022-11-14 14:39:20,026 Epoch: [232][310/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0297 (0.0394) Prec@1 95.000 (93.344) Prec@5 100.000 (99.844) +2022-11-14 14:39:20,389 Epoch: [232][320/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0317 (0.0392) Prec@1 95.000 (93.394) Prec@5 100.000 (99.848) +2022-11-14 14:39:20,754 Epoch: [232][330/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0465 (0.0394) Prec@1 92.000 (93.353) Prec@5 100.000 (99.853) +2022-11-14 14:39:21,198 Epoch: [232][340/500] Time 0.056 (0.032) Data 0.002 (0.003) Loss 0.0342 (0.0392) Prec@1 94.000 (93.371) Prec@5 100.000 (99.857) +2022-11-14 14:39:21,787 Epoch: [232][350/500] Time 0.053 (0.032) Data 0.002 (0.003) Loss 0.0292 (0.0390) Prec@1 97.000 (93.472) Prec@5 100.000 (99.861) +2022-11-14 14:39:22,281 Epoch: [232][360/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0552 (0.0394) Prec@1 93.000 (93.459) Prec@5 98.000 (99.811) +2022-11-14 14:39:22,751 Epoch: [232][370/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0491 (0.0396) Prec@1 91.000 (93.395) Prec@5 100.000 (99.816) +2022-11-14 14:39:23,290 Epoch: [232][380/500] Time 0.063 (0.033) Data 0.002 (0.003) Loss 0.0681 (0.0404) Prec@1 90.000 (93.308) Prec@5 100.000 (99.821) +2022-11-14 14:39:23,920 Epoch: [232][390/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0197 (0.0399) Prec@1 97.000 (93.400) Prec@5 100.000 (99.825) +2022-11-14 14:39:24,388 Epoch: [232][400/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0422 (0.0399) Prec@1 91.000 (93.341) Prec@5 99.000 (99.805) +2022-11-14 14:39:24,864 Epoch: [232][410/500] Time 0.058 (0.034) Data 0.002 (0.002) Loss 0.0359 (0.0398) Prec@1 93.000 (93.333) Prec@5 100.000 (99.810) +2022-11-14 14:39:25,326 Epoch: [232][420/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0691 (0.0405) Prec@1 89.000 (93.233) Prec@5 100.000 (99.814) +2022-11-14 14:39:25,788 Epoch: [232][430/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0490 (0.0407) Prec@1 93.000 (93.227) Prec@5 99.000 (99.795) +2022-11-14 14:39:26,249 Epoch: [232][440/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0420 (0.0407) Prec@1 95.000 (93.267) Prec@5 100.000 (99.800) +2022-11-14 14:39:26,711 Epoch: [232][450/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0413 (0.0407) Prec@1 94.000 (93.283) Prec@5 99.000 (99.783) +2022-11-14 14:39:27,172 Epoch: [232][460/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0322 (0.0406) Prec@1 95.000 (93.319) Prec@5 100.000 (99.787) +2022-11-14 14:39:27,633 Epoch: [232][470/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0373 (0.0405) Prec@1 94.000 (93.333) Prec@5 100.000 (99.792) +2022-11-14 14:39:28,095 Epoch: [232][480/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0321 (0.0403) Prec@1 96.000 (93.388) Prec@5 100.000 (99.796) +2022-11-14 14:39:28,558 Epoch: [232][490/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0311 (0.0401) Prec@1 95.000 (93.420) Prec@5 100.000 (99.800) +2022-11-14 14:39:28,975 Epoch: [232][499/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0422 (0.0402) Prec@1 95.000 (93.451) Prec@5 100.000 (99.804) +2022-11-14 14:39:29,244 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0673) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 14:39:29,252 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0645) Prec@1 89.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:39:29,261 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0633) Prec@1 91.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 14:39:29,272 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0644) Prec@1 87.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 14:39:29,281 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0652) Prec@1 90.000 (89.400) Prec@5 100.000 (99.600) +2022-11-14 14:39:29,291 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0323 (0.0597) Prec@1 94.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 14:39:29,302 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0583) Prec@1 93.000 (90.571) Prec@5 99.000 (99.571) +2022-11-14 14:39:29,314 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0638) Prec@1 84.000 (89.750) Prec@5 99.000 (99.500) +2022-11-14 14:39:29,325 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0679) Prec@1 84.000 (89.111) Prec@5 99.000 (99.444) +2022-11-14 14:39:29,338 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0699) Prec@1 86.000 (88.800) Prec@5 99.000 (99.400) +2022-11-14 14:39:29,353 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0702) Prec@1 88.000 (88.727) Prec@5 100.000 (99.455) +2022-11-14 14:39:29,367 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0727) Prec@1 85.000 (88.417) Prec@5 99.000 (99.417) +2022-11-14 14:39:29,382 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0713) Prec@1 93.000 (88.769) Prec@5 100.000 (99.462) +2022-11-14 14:39:29,395 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0729) Prec@1 86.000 (88.571) Prec@5 98.000 (99.357) +2022-11-14 14:39:29,410 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0724) Prec@1 90.000 (88.667) Prec@5 98.000 (99.267) +2022-11-14 14:39:29,425 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0735) Prec@1 86.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 14:39:29,441 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0726) Prec@1 90.000 (88.588) Prec@5 99.000 (99.235) +2022-11-14 14:39:29,456 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0740) Prec@1 85.000 (88.389) Prec@5 100.000 (99.278) +2022-11-14 14:39:29,470 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0752) Prec@1 83.000 (88.105) Prec@5 98.000 (99.211) +2022-11-14 14:39:29,483 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0759) Prec@1 86.000 (88.000) Prec@5 97.000 (99.100) +2022-11-14 14:39:29,497 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0760) Prec@1 85.000 (87.857) Prec@5 99.000 (99.095) +2022-11-14 14:39:29,512 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0766) Prec@1 83.000 (87.636) Prec@5 100.000 (99.136) +2022-11-14 14:39:29,526 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0771) Prec@1 85.000 (87.522) Prec@5 99.000 (99.130) +2022-11-14 14:39:29,541 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0773) Prec@1 89.000 (87.583) Prec@5 100.000 (99.167) +2022-11-14 14:39:29,555 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0782) Prec@1 81.000 (87.320) Prec@5 100.000 (99.200) +2022-11-14 14:39:29,570 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0792) Prec@1 86.000 (87.269) Prec@5 97.000 (99.115) +2022-11-14 14:39:29,585 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0780) Prec@1 93.000 (87.481) Prec@5 100.000 (99.148) +2022-11-14 14:39:29,600 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0778) Prec@1 88.000 (87.500) Prec@5 100.000 (99.179) +2022-11-14 14:39:29,614 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0781) Prec@1 84.000 (87.379) Prec@5 98.000 (99.138) +2022-11-14 14:39:29,629 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0780) Prec@1 87.000 (87.367) Prec@5 100.000 (99.167) +2022-11-14 14:39:29,643 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0777) Prec@1 89.000 (87.419) Prec@5 99.000 (99.161) +2022-11-14 14:39:29,658 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0777) Prec@1 86.000 (87.375) Prec@5 98.000 (99.125) +2022-11-14 14:39:29,673 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0773) Prec@1 87.000 (87.364) Prec@5 99.000 (99.121) +2022-11-14 14:39:29,689 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0784) Prec@1 81.000 (87.176) Prec@5 98.000 (99.088) +2022-11-14 14:39:29,706 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0783) Prec@1 86.000 (87.143) Prec@5 99.000 (99.086) +2022-11-14 14:39:29,722 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0781) Prec@1 89.000 (87.194) Prec@5 100.000 (99.111) +2022-11-14 14:39:29,737 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0782) Prec@1 85.000 (87.135) Prec@5 98.000 (99.081) +2022-11-14 14:39:29,754 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0790) Prec@1 82.000 (87.000) Prec@5 99.000 (99.079) +2022-11-14 14:39:29,769 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0784) Prec@1 92.000 (87.128) Prec@5 99.000 (99.077) +2022-11-14 14:39:29,784 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0783) Prec@1 87.000 (87.125) Prec@5 100.000 (99.100) +2022-11-14 14:39:29,799 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0786) Prec@1 86.000 (87.098) Prec@5 98.000 (99.073) +2022-11-14 14:39:29,814 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0784) Prec@1 88.000 (87.119) Prec@5 99.000 (99.071) +2022-11-14 14:39:29,830 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0776) Prec@1 93.000 (87.256) Prec@5 100.000 (99.093) +2022-11-14 14:39:29,846 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0775) Prec@1 90.000 (87.318) Prec@5 96.000 (99.023) +2022-11-14 14:39:29,860 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0773) Prec@1 88.000 (87.333) Prec@5 99.000 (99.022) +2022-11-14 14:39:29,876 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0782) Prec@1 82.000 (87.217) Prec@5 100.000 (99.043) +2022-11-14 14:39:29,892 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0783) Prec@1 87.000 (87.213) Prec@5 99.000 (99.043) +2022-11-14 14:39:29,908 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0785) Prec@1 85.000 (87.167) Prec@5 99.000 (99.042) +2022-11-14 14:39:29,923 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0779) Prec@1 91.000 (87.245) Prec@5 100.000 (99.061) +2022-11-14 14:39:29,936 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0786) Prec@1 85.000 (87.200) Prec@5 99.000 (99.060) +2022-11-14 14:39:29,950 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0784) Prec@1 90.000 (87.255) Prec@5 99.000 (99.059) +2022-11-14 14:39:29,964 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0789) Prec@1 84.000 (87.192) Prec@5 99.000 (99.058) +2022-11-14 14:39:29,978 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0786) Prec@1 88.000 (87.208) Prec@5 99.000 (99.057) +2022-11-14 14:39:29,992 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0782) Prec@1 90.000 (87.259) Prec@5 100.000 (99.074) +2022-11-14 14:39:30,008 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0786) Prec@1 85.000 (87.218) Prec@5 99.000 (99.073) +2022-11-14 14:39:30,023 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0781) Prec@1 93.000 (87.321) Prec@5 99.000 (99.071) +2022-11-14 14:39:30,038 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0781) Prec@1 87.000 (87.316) Prec@5 100.000 (99.088) +2022-11-14 14:39:30,054 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0781) Prec@1 89.000 (87.345) Prec@5 99.000 (99.086) +2022-11-14 14:39:30,069 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0786) Prec@1 83.000 (87.271) Prec@5 99.000 (99.085) +2022-11-14 14:39:30,084 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0787) Prec@1 84.000 (87.217) Prec@5 99.000 (99.083) +2022-11-14 14:39:30,098 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0784) Prec@1 90.000 (87.262) Prec@5 100.000 (99.098) +2022-11-14 14:39:30,113 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0786) Prec@1 84.000 (87.210) Prec@5 99.000 (99.097) +2022-11-14 14:39:30,130 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0782) Prec@1 90.000 (87.254) Prec@5 99.000 (99.095) +2022-11-14 14:39:30,144 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0778) Prec@1 91.000 (87.312) Prec@5 100.000 (99.109) +2022-11-14 14:39:30,159 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0780) Prec@1 84.000 (87.262) Prec@5 99.000 (99.108) +2022-11-14 14:39:30,175 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0783) Prec@1 86.000 (87.242) Prec@5 99.000 (99.106) +2022-11-14 14:39:30,190 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0386 (0.0777) Prec@1 95.000 (87.358) Prec@5 100.000 (99.119) +2022-11-14 14:39:30,207 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0778) Prec@1 85.000 (87.324) Prec@5 100.000 (99.132) +2022-11-14 14:39:30,221 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0774) Prec@1 94.000 (87.420) Prec@5 99.000 (99.130) +2022-11-14 14:39:30,235 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0774) Prec@1 86.000 (87.400) Prec@5 99.000 (99.129) +2022-11-14 14:39:30,250 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0775) Prec@1 84.000 (87.352) Prec@5 100.000 (99.141) +2022-11-14 14:39:30,265 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0775) Prec@1 87.000 (87.347) Prec@5 100.000 (99.153) +2022-11-14 14:39:30,281 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0770) Prec@1 95.000 (87.452) Prec@5 100.000 (99.164) +2022-11-14 14:39:30,297 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0463 (0.0766) Prec@1 93.000 (87.527) Prec@5 99.000 (99.162) +2022-11-14 14:39:30,312 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0767) Prec@1 87.000 (87.520) Prec@5 100.000 (99.173) +2022-11-14 14:39:30,327 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0766) Prec@1 89.000 (87.539) Prec@5 100.000 (99.184) +2022-11-14 14:39:30,341 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0765) Prec@1 89.000 (87.558) Prec@5 98.000 (99.169) +2022-11-14 14:39:30,356 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0766) Prec@1 89.000 (87.577) Prec@5 99.000 (99.167) +2022-11-14 14:39:30,371 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0770) Prec@1 82.000 (87.506) Prec@5 100.000 (99.177) +2022-11-14 14:39:30,387 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0769) Prec@1 90.000 (87.537) Prec@5 99.000 (99.175) +2022-11-14 14:39:30,403 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0771) Prec@1 85.000 (87.506) Prec@5 98.000 (99.160) +2022-11-14 14:39:30,417 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0770) Prec@1 87.000 (87.500) Prec@5 100.000 (99.171) +2022-11-14 14:39:30,432 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0772) Prec@1 88.000 (87.506) Prec@5 100.000 (99.181) +2022-11-14 14:39:30,447 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0771) Prec@1 90.000 (87.536) Prec@5 99.000 (99.179) +2022-11-14 14:39:30,461 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0775) Prec@1 81.000 (87.459) Prec@5 99.000 (99.176) +2022-11-14 14:39:30,476 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1169 (0.0780) Prec@1 80.000 (87.372) Prec@5 98.000 (99.163) +2022-11-14 14:39:30,496 Test: [86/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0781) Prec@1 86.000 (87.356) Prec@5 100.000 (99.172) +2022-11-14 14:39:30,516 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0782) Prec@1 85.000 (87.330) Prec@5 99.000 (99.170) +2022-11-14 14:39:30,536 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0780) Prec@1 87.000 (87.326) Prec@5 99.000 (99.169) +2022-11-14 14:39:30,554 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0778) Prec@1 91.000 (87.367) Prec@5 99.000 (99.167) +2022-11-14 14:39:30,572 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0776) Prec@1 92.000 (87.418) Prec@5 99.000 (99.165) +2022-11-14 14:39:30,589 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0774) Prec@1 90.000 (87.446) Prec@5 99.000 (99.163) +2022-11-14 14:39:30,607 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0777) Prec@1 83.000 (87.398) Prec@5 99.000 (99.161) +2022-11-14 14:39:30,623 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0775) Prec@1 91.000 (87.436) Prec@5 100.000 (99.170) +2022-11-14 14:39:30,638 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.0779) Prec@1 83.000 (87.389) Prec@5 100.000 (99.179) +2022-11-14 14:39:30,656 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0778) Prec@1 91.000 (87.427) Prec@5 98.000 (99.167) +2022-11-14 14:39:30,671 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0777) Prec@1 88.000 (87.433) Prec@5 99.000 (99.165) +2022-11-14 14:39:30,690 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0780) Prec@1 83.000 (87.388) Prec@5 99.000 (99.163) +2022-11-14 14:39:30,707 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0780) Prec@1 87.000 (87.384) Prec@5 98.000 (99.152) +2022-11-14 14:39:30,723 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0780) Prec@1 89.000 (87.400) Prec@5 99.000 (99.150) +2022-11-14 14:39:30,781 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:39:31,109 Epoch: [233][0/500] Time 0.034 (0.034) Data 0.232 (0.232) Loss 0.0308 (0.0308) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:39:31,351 Epoch: [233][10/500] Time 0.021 (0.023) Data 0.002 (0.023) Loss 0.0353 (0.0331) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:39:31,662 Epoch: [233][20/500] Time 0.023 (0.025) Data 0.003 (0.013) Loss 0.0381 (0.0347) Prec@1 94.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:39:31,924 Epoch: [233][30/500] Time 0.023 (0.024) Data 0.002 (0.009) Loss 0.0569 (0.0403) Prec@1 92.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:39:32,185 Epoch: [233][40/500] Time 0.024 (0.024) Data 0.002 (0.007) Loss 0.0408 (0.0404) Prec@1 93.000 (93.800) Prec@5 99.000 (99.800) +2022-11-14 14:39:32,478 Epoch: [233][50/500] Time 0.023 (0.025) Data 0.002 (0.006) Loss 0.0352 (0.0395) Prec@1 93.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:39:32,767 Epoch: [233][60/500] Time 0.029 (0.025) Data 0.001 (0.006) Loss 0.0252 (0.0375) Prec@1 97.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:39:33,101 Epoch: [233][70/500] Time 0.035 (0.025) Data 0.002 (0.005) Loss 0.0333 (0.0370) Prec@1 94.000 (94.125) Prec@5 100.000 (99.750) +2022-11-14 14:39:33,479 Epoch: [233][80/500] Time 0.035 (0.026) Data 0.002 (0.005) Loss 0.0351 (0.0367) Prec@1 93.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 14:39:33,857 Epoch: [233][90/500] Time 0.036 (0.027) Data 0.002 (0.004) Loss 0.0229 (0.0354) Prec@1 95.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 14:39:34,251 Epoch: [233][100/500] Time 0.038 (0.028) Data 0.002 (0.004) Loss 0.0464 (0.0364) Prec@1 92.000 (93.909) Prec@5 100.000 (99.818) +2022-11-14 14:39:34,630 Epoch: [233][110/500] Time 0.034 (0.028) Data 0.001 (0.004) Loss 0.0451 (0.0371) Prec@1 95.000 (94.000) Prec@5 99.000 (99.750) +2022-11-14 14:39:35,024 Epoch: [233][120/500] Time 0.033 (0.029) Data 0.002 (0.004) Loss 0.0574 (0.0387) Prec@1 92.000 (93.846) Prec@5 100.000 (99.769) +2022-11-14 14:39:35,420 Epoch: [233][130/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0457 (0.0392) Prec@1 93.000 (93.786) Prec@5 100.000 (99.786) +2022-11-14 14:39:35,812 Epoch: [233][140/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0240 (0.0381) Prec@1 96.000 (93.933) Prec@5 100.000 (99.800) +2022-11-14 14:39:36,198 Epoch: [233][150/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0257 (0.0374) Prec@1 96.000 (94.062) Prec@5 100.000 (99.812) +2022-11-14 14:39:36,589 Epoch: [233][160/500] Time 0.035 (0.030) Data 0.001 (0.003) Loss 0.0511 (0.0382) Prec@1 92.000 (93.941) Prec@5 99.000 (99.765) +2022-11-14 14:39:36,991 Epoch: [233][170/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0488 (0.0388) Prec@1 91.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 14:39:37,376 Epoch: [233][180/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.0273 (0.0382) Prec@1 96.000 (93.895) Prec@5 100.000 (99.789) +2022-11-14 14:39:37,766 Epoch: [233][190/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.0439 (0.0384) Prec@1 92.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:39:38,167 Epoch: [233][200/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0346 (0.0383) Prec@1 94.000 (93.810) Prec@5 100.000 (99.810) +2022-11-14 14:39:38,564 Epoch: [233][210/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0295 (0.0379) Prec@1 93.000 (93.773) Prec@5 100.000 (99.818) +2022-11-14 14:39:38,961 Epoch: [233][220/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0445 (0.0382) Prec@1 93.000 (93.739) Prec@5 100.000 (99.826) +2022-11-14 14:39:39,356 Epoch: [233][230/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0274 (0.0377) Prec@1 96.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:39:39,744 Epoch: [233][240/500] Time 0.031 (0.032) Data 0.002 (0.003) Loss 0.0362 (0.0376) Prec@1 94.000 (93.840) Prec@5 100.000 (99.840) +2022-11-14 14:39:40,139 Epoch: [233][250/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0294 (0.0373) Prec@1 94.000 (93.846) Prec@5 100.000 (99.846) +2022-11-14 14:39:40,530 Epoch: [233][260/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0263 (0.0369) Prec@1 96.000 (93.926) Prec@5 100.000 (99.852) +2022-11-14 14:39:40,897 Epoch: [233][270/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0731 (0.0382) Prec@1 86.000 (93.643) Prec@5 100.000 (99.857) +2022-11-14 14:39:41,295 Epoch: [233][280/500] Time 0.045 (0.032) Data 0.002 (0.003) Loss 0.0475 (0.0385) Prec@1 92.000 (93.586) Prec@5 99.000 (99.828) +2022-11-14 14:39:41,673 Epoch: [233][290/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0371 (0.0385) Prec@1 95.000 (93.633) Prec@5 100.000 (99.833) +2022-11-14 14:39:42,075 Epoch: [233][300/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0290 (0.0382) Prec@1 95.000 (93.677) Prec@5 100.000 (99.839) +2022-11-14 14:39:42,463 Epoch: [233][310/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0355 (0.0381) Prec@1 96.000 (93.750) Prec@5 100.000 (99.844) +2022-11-14 14:39:42,844 Epoch: [233][320/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0602 (0.0388) Prec@1 91.000 (93.667) Prec@5 100.000 (99.848) +2022-11-14 14:39:43,234 Epoch: [233][330/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0272 (0.0384) Prec@1 96.000 (93.735) Prec@5 100.000 (99.853) +2022-11-14 14:39:43,642 Epoch: [233][340/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0274 (0.0381) Prec@1 94.000 (93.743) Prec@5 100.000 (99.857) +2022-11-14 14:39:44,133 Epoch: [233][350/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0369 (0.0381) Prec@1 92.000 (93.694) Prec@5 100.000 (99.861) +2022-11-14 14:39:44,492 Epoch: [233][360/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0518 (0.0384) Prec@1 91.000 (93.622) Prec@5 100.000 (99.865) +2022-11-14 14:39:44,946 Epoch: [233][370/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.0182 (0.0379) Prec@1 96.000 (93.684) Prec@5 100.000 (99.868) +2022-11-14 14:39:45,323 Epoch: [233][380/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0484 (0.0382) Prec@1 90.000 (93.590) Prec@5 100.000 (99.872) +2022-11-14 14:39:45,737 Epoch: [233][390/500] Time 0.034 (0.033) Data 0.002 (0.002) Loss 0.0469 (0.0384) Prec@1 90.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 14:39:46,119 Epoch: [233][400/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0412 (0.0385) Prec@1 94.000 (93.512) Prec@5 99.000 (99.854) +2022-11-14 14:39:46,508 Epoch: [233][410/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0357 (0.0384) Prec@1 92.000 (93.476) Prec@5 100.000 (99.857) +2022-11-14 14:39:46,892 Epoch: [233][420/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0254 (0.0381) Prec@1 94.000 (93.488) Prec@5 100.000 (99.860) +2022-11-14 14:39:47,283 Epoch: [233][430/500] Time 0.047 (0.033) Data 0.002 (0.002) Loss 0.0223 (0.0377) Prec@1 96.000 (93.545) Prec@5 100.000 (99.864) +2022-11-14 14:39:47,668 Epoch: [233][440/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0346 (0.0377) Prec@1 94.000 (93.556) Prec@5 100.000 (99.867) +2022-11-14 14:39:48,057 Epoch: [233][450/500] Time 0.035 (0.033) Data 0.002 (0.002) Loss 0.0334 (0.0376) Prec@1 94.000 (93.565) Prec@5 100.000 (99.870) +2022-11-14 14:39:48,442 Epoch: [233][460/500] Time 0.036 (0.033) Data 0.002 (0.002) Loss 0.0278 (0.0374) Prec@1 96.000 (93.617) Prec@5 100.000 (99.872) +2022-11-14 14:39:48,882 Epoch: [233][470/500] Time 0.029 (0.034) Data 0.002 (0.002) Loss 0.0406 (0.0374) Prec@1 93.000 (93.604) Prec@5 100.000 (99.875) +2022-11-14 14:39:49,273 Epoch: [233][480/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0534 (0.0378) Prec@1 91.000 (93.551) Prec@5 100.000 (99.878) +2022-11-14 14:39:49,653 Epoch: [233][490/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0263 (0.0375) Prec@1 96.000 (93.600) Prec@5 100.000 (99.880) +2022-11-14 14:39:49,992 Epoch: [233][499/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0264 (0.0373) Prec@1 95.000 (93.627) Prec@5 100.000 (99.882) +2022-11-14 14:39:50,271 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0733 (0.0733) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:39:50,281 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0704) Prec@1 87.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:39:50,289 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0714) Prec@1 88.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:39:50,302 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0741) Prec@1 87.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 14:39:50,310 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0777) Prec@1 87.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 14:39:50,318 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0722) Prec@1 92.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:39:50,326 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0691) Prec@1 93.000 (89.000) Prec@5 100.000 (99.714) +2022-11-14 14:39:50,338 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0704) Prec@1 87.000 (88.750) Prec@5 99.000 (99.625) +2022-11-14 14:39:50,346 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0725) Prec@1 88.000 (88.667) Prec@5 99.000 (99.556) +2022-11-14 14:39:50,355 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0721) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:39:50,365 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0712) Prec@1 92.000 (88.818) Prec@5 100.000 (99.545) +2022-11-14 14:39:50,375 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0722) Prec@1 86.000 (88.583) Prec@5 99.000 (99.500) +2022-11-14 14:39:50,385 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0717) Prec@1 90.000 (88.692) Prec@5 100.000 (99.538) +2022-11-14 14:39:50,394 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0716) Prec@1 88.000 (88.643) Prec@5 100.000 (99.571) +2022-11-14 14:39:50,404 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0726) Prec@1 84.000 (88.333) Prec@5 100.000 (99.600) +2022-11-14 14:39:50,414 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0726) Prec@1 87.000 (88.250) Prec@5 99.000 (99.562) +2022-11-14 14:39:50,423 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0724) Prec@1 90.000 (88.353) Prec@5 96.000 (99.353) +2022-11-14 14:39:50,432 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0747) Prec@1 82.000 (88.000) Prec@5 100.000 (99.389) +2022-11-14 14:39:50,442 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0756) Prec@1 86.000 (87.895) Prec@5 97.000 (99.263) +2022-11-14 14:39:50,450 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0768) Prec@1 85.000 (87.750) Prec@5 97.000 (99.150) +2022-11-14 14:39:50,460 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0782) Prec@1 84.000 (87.571) Prec@5 100.000 (99.190) +2022-11-14 14:39:50,469 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0788) Prec@1 86.000 (87.500) Prec@5 100.000 (99.227) +2022-11-14 14:39:50,478 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0802) Prec@1 83.000 (87.304) Prec@5 98.000 (99.174) +2022-11-14 14:39:50,487 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0799) Prec@1 88.000 (87.333) Prec@5 100.000 (99.208) +2022-11-14 14:39:50,497 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0801) Prec@1 86.000 (87.280) Prec@5 100.000 (99.240) +2022-11-14 14:39:50,507 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0807) Prec@1 83.000 (87.115) Prec@5 98.000 (99.192) +2022-11-14 14:39:50,516 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0794) Prec@1 92.000 (87.296) Prec@5 100.000 (99.222) +2022-11-14 14:39:50,525 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0786) Prec@1 92.000 (87.464) Prec@5 100.000 (99.250) +2022-11-14 14:39:50,534 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0785) Prec@1 90.000 (87.552) Prec@5 98.000 (99.207) +2022-11-14 14:39:50,544 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0456 (0.0774) Prec@1 93.000 (87.733) Prec@5 99.000 (99.200) +2022-11-14 14:39:50,553 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0769) Prec@1 91.000 (87.839) Prec@5 99.000 (99.194) +2022-11-14 14:39:50,562 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0765) Prec@1 89.000 (87.875) Prec@5 99.000 (99.188) +2022-11-14 14:39:50,571 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0763) Prec@1 88.000 (87.879) Prec@5 100.000 (99.212) +2022-11-14 14:39:50,580 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0768) Prec@1 86.000 (87.824) Prec@5 99.000 (99.206) +2022-11-14 14:39:50,589 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0769) Prec@1 87.000 (87.800) Prec@5 98.000 (99.171) +2022-11-14 14:39:50,597 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0766) Prec@1 87.000 (87.778) Prec@5 100.000 (99.194) +2022-11-14 14:39:50,605 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0767) Prec@1 88.000 (87.784) Prec@5 100.000 (99.216) +2022-11-14 14:39:50,613 Test: [37/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0774) Prec@1 85.000 (87.711) Prec@5 99.000 (99.211) +2022-11-14 14:39:50,622 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0770) Prec@1 92.000 (87.821) Prec@5 100.000 (99.231) +2022-11-14 14:39:50,631 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0764) Prec@1 90.000 (87.875) Prec@5 99.000 (99.225) +2022-11-14 14:39:50,642 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0766) Prec@1 86.000 (87.829) Prec@5 100.000 (99.244) +2022-11-14 14:39:50,652 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0763) Prec@1 88.000 (87.833) Prec@5 98.000 (99.214) +2022-11-14 14:39:50,662 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0758) Prec@1 92.000 (87.930) Prec@5 100.000 (99.233) +2022-11-14 14:39:50,673 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0757) Prec@1 89.000 (87.955) Prec@5 97.000 (99.182) +2022-11-14 14:39:50,683 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0756) Prec@1 89.000 (87.978) Prec@5 100.000 (99.200) +2022-11-14 14:39:50,693 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0758) Prec@1 83.000 (87.870) Prec@5 100.000 (99.217) +2022-11-14 14:39:50,701 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0758) Prec@1 88.000 (87.872) Prec@5 99.000 (99.213) +2022-11-14 14:39:50,711 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0763) Prec@1 82.000 (87.750) Prec@5 98.000 (99.188) +2022-11-14 14:39:50,719 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0472 (0.0757) Prec@1 91.000 (87.816) Prec@5 100.000 (99.204) +2022-11-14 14:39:50,728 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0762) Prec@1 85.000 (87.760) Prec@5 99.000 (99.200) +2022-11-14 14:39:50,738 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0762) Prec@1 87.000 (87.745) Prec@5 100.000 (99.216) +2022-11-14 14:39:50,749 Test: [51/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0765) Prec@1 86.000 (87.712) Prec@5 99.000 (99.212) +2022-11-14 14:39:50,759 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0767) Prec@1 85.000 (87.660) Prec@5 100.000 (99.226) +2022-11-14 14:39:50,768 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0767) Prec@1 86.000 (87.630) Prec@5 100.000 (99.241) +2022-11-14 14:39:50,777 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0769) Prec@1 84.000 (87.564) Prec@5 100.000 (99.255) +2022-11-14 14:39:50,786 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0767) Prec@1 90.000 (87.607) Prec@5 100.000 (99.268) +2022-11-14 14:39:50,796 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0765) Prec@1 90.000 (87.649) Prec@5 99.000 (99.263) +2022-11-14 14:39:50,805 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0762) Prec@1 93.000 (87.741) Prec@5 100.000 (99.276) +2022-11-14 14:39:50,814 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1210 (0.0770) Prec@1 80.000 (87.610) Prec@5 99.000 (99.271) +2022-11-14 14:39:50,823 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0770) Prec@1 85.000 (87.567) Prec@5 99.000 (99.267) +2022-11-14 14:39:50,833 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0769) Prec@1 88.000 (87.574) Prec@5 99.000 (99.262) +2022-11-14 14:39:50,843 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0766) Prec@1 91.000 (87.629) Prec@5 98.000 (99.242) +2022-11-14 14:39:50,852 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0767) Prec@1 85.000 (87.587) Prec@5 100.000 (99.254) +2022-11-14 14:39:50,863 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0763) Prec@1 91.000 (87.641) Prec@5 100.000 (99.266) +2022-11-14 14:39:50,872 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0767) Prec@1 83.000 (87.569) Prec@5 100.000 (99.277) +2022-11-14 14:39:50,881 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0765) Prec@1 88.000 (87.576) Prec@5 99.000 (99.273) +2022-11-14 14:39:50,889 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0760) Prec@1 94.000 (87.672) Prec@5 100.000 (99.284) +2022-11-14 14:39:50,899 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0762) Prec@1 86.000 (87.647) Prec@5 98.000 (99.265) +2022-11-14 14:39:50,907 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0760) Prec@1 91.000 (87.696) Prec@5 99.000 (99.261) +2022-11-14 14:39:50,915 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0762) Prec@1 85.000 (87.657) Prec@5 100.000 (99.271) +2022-11-14 14:39:50,924 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0765) Prec@1 84.000 (87.606) Prec@5 100.000 (99.282) +2022-11-14 14:39:50,934 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0761) Prec@1 91.000 (87.653) Prec@5 99.000 (99.278) +2022-11-14 14:39:50,942 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0365 (0.0756) Prec@1 94.000 (87.740) Prec@5 100.000 (99.288) +2022-11-14 14:39:50,951 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0752) Prec@1 93.000 (87.811) Prec@5 100.000 (99.297) +2022-11-14 14:39:50,960 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0754) Prec@1 83.000 (87.747) Prec@5 99.000 (99.293) +2022-11-14 14:39:50,969 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0752) Prec@1 90.000 (87.776) Prec@5 99.000 (99.289) +2022-11-14 14:39:50,978 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0752) Prec@1 86.000 (87.753) Prec@5 100.000 (99.299) +2022-11-14 14:39:50,988 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0971 (0.0755) Prec@1 84.000 (87.705) Prec@5 99.000 (99.295) +2022-11-14 14:39:50,997 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0757) Prec@1 87.000 (87.696) Prec@5 100.000 (99.304) +2022-11-14 14:39:51,006 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0757) Prec@1 89.000 (87.713) Prec@5 99.000 (99.300) +2022-11-14 14:39:51,015 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0759) Prec@1 85.000 (87.679) Prec@5 100.000 (99.309) +2022-11-14 14:39:51,025 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0759) Prec@1 88.000 (87.683) Prec@5 99.000 (99.305) +2022-11-14 14:39:51,034 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0761) Prec@1 86.000 (87.663) Prec@5 99.000 (99.301) +2022-11-14 14:39:51,042 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0760) Prec@1 88.000 (87.667) Prec@5 100.000 (99.310) +2022-11-14 14:39:51,052 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0762) Prec@1 85.000 (87.635) Prec@5 100.000 (99.318) +2022-11-14 14:39:51,060 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0764) Prec@1 88.000 (87.640) Prec@5 100.000 (99.326) +2022-11-14 14:39:51,068 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0764) Prec@1 88.000 (87.644) Prec@5 100.000 (99.333) +2022-11-14 14:39:51,079 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0765) Prec@1 87.000 (87.636) Prec@5 99.000 (99.330) +2022-11-14 14:39:51,089 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0765) Prec@1 86.000 (87.618) Prec@5 98.000 (99.315) +2022-11-14 14:39:51,100 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0764) Prec@1 89.000 (87.633) Prec@5 99.000 (99.311) +2022-11-14 14:39:51,111 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0762) Prec@1 92.000 (87.681) Prec@5 100.000 (99.319) +2022-11-14 14:39:51,124 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0355 (0.0758) Prec@1 94.000 (87.750) Prec@5 100.000 (99.326) +2022-11-14 14:39:51,137 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0759) Prec@1 86.000 (87.731) Prec@5 98.000 (99.312) +2022-11-14 14:39:51,150 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0758) Prec@1 88.000 (87.734) Prec@5 99.000 (99.309) +2022-11-14 14:39:51,162 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0758) Prec@1 89.000 (87.747) Prec@5 100.000 (99.316) +2022-11-14 14:39:51,176 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0758) Prec@1 89.000 (87.760) Prec@5 99.000 (99.312) +2022-11-14 14:39:51,190 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0757) Prec@1 90.000 (87.784) Prec@5 99.000 (99.309) +2022-11-14 14:39:51,207 Test: [97/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0757) Prec@1 90.000 (87.806) Prec@5 97.000 (99.286) +2022-11-14 14:39:51,222 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0758) Prec@1 86.000 (87.788) Prec@5 99.000 (99.283) +2022-11-14 14:39:51,235 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0758) Prec@1 87.000 (87.780) Prec@5 100.000 (99.290) +2022-11-14 14:39:51,291 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:39:51,620 Epoch: [234][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.0494 (0.0494) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:39:52,006 Epoch: [234][10/500] Time 0.040 (0.033) Data 0.002 (0.023) Loss 0.0289 (0.0391) Prec@1 94.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:39:52,439 Epoch: [234][20/500] Time 0.043 (0.036) Data 0.001 (0.013) Loss 0.0238 (0.0340) Prec@1 97.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:39:52,871 Epoch: [234][30/500] Time 0.039 (0.036) Data 0.002 (0.009) Loss 0.0499 (0.0380) Prec@1 88.000 (92.750) Prec@5 100.000 (100.000) +2022-11-14 14:39:53,306 Epoch: [234][40/500] Time 0.046 (0.037) Data 0.002 (0.007) Loss 0.0860 (0.0476) Prec@1 86.000 (91.400) Prec@5 99.000 (99.800) +2022-11-14 14:39:53,737 Epoch: [234][50/500] Time 0.042 (0.037) Data 0.002 (0.006) Loss 0.0311 (0.0448) Prec@1 96.000 (92.167) Prec@5 100.000 (99.833) +2022-11-14 14:39:54,165 Epoch: [234][60/500] Time 0.039 (0.037) Data 0.002 (0.006) Loss 0.0223 (0.0416) Prec@1 97.000 (92.857) Prec@5 100.000 (99.857) +2022-11-14 14:39:54,600 Epoch: [234][70/500] Time 0.040 (0.038) Data 0.002 (0.005) Loss 0.0369 (0.0410) Prec@1 95.000 (93.125) Prec@5 99.000 (99.750) +2022-11-14 14:39:55,027 Epoch: [234][80/500] Time 0.038 (0.038) Data 0.002 (0.005) Loss 0.0260 (0.0394) Prec@1 97.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 14:39:55,469 Epoch: [234][90/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0252 (0.0379) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:39:55,971 Epoch: [234][100/500] Time 0.047 (0.039) Data 0.002 (0.004) Loss 0.0582 (0.0398) Prec@1 92.000 (93.636) Prec@5 99.000 (99.727) +2022-11-14 14:39:56,377 Epoch: [234][110/500] Time 0.039 (0.038) Data 0.002 (0.004) Loss 0.0463 (0.0403) Prec@1 90.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:39:56,804 Epoch: [234][120/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0443 (0.0406) Prec@1 93.000 (93.308) Prec@5 100.000 (99.692) +2022-11-14 14:39:57,316 Epoch: [234][130/500] Time 0.047 (0.039) Data 0.002 (0.004) Loss 0.0218 (0.0393) Prec@1 98.000 (93.643) Prec@5 100.000 (99.714) +2022-11-14 14:39:57,710 Epoch: [234][140/500] Time 0.037 (0.039) Data 0.002 (0.004) Loss 0.0364 (0.0391) Prec@1 93.000 (93.600) Prec@5 100.000 (99.733) +2022-11-14 14:39:58,197 Epoch: [234][150/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0130 (0.0375) Prec@1 98.000 (93.875) Prec@5 100.000 (99.750) +2022-11-14 14:39:58,625 Epoch: [234][160/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0259 (0.0368) Prec@1 95.000 (93.941) Prec@5 100.000 (99.765) +2022-11-14 14:39:59,062 Epoch: [234][170/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0707 (0.0387) Prec@1 87.000 (93.556) Prec@5 98.000 (99.667) +2022-11-14 14:39:59,493 Epoch: [234][180/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0577 (0.0397) Prec@1 90.000 (93.368) Prec@5 100.000 (99.684) +2022-11-14 14:39:59,917 Epoch: [234][190/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0426 (0.0398) Prec@1 92.000 (93.300) Prec@5 99.000 (99.650) +2022-11-14 14:40:00,340 Epoch: [234][200/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.0209 (0.0389) Prec@1 98.000 (93.524) Prec@5 100.000 (99.667) +2022-11-14 14:40:00,768 Epoch: [234][210/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0257 (0.0383) Prec@1 96.000 (93.636) Prec@5 99.000 (99.636) +2022-11-14 14:40:01,186 Epoch: [234][220/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0379 (0.0383) Prec@1 95.000 (93.696) Prec@5 100.000 (99.652) +2022-11-14 14:40:01,606 Epoch: [234][230/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0529 (0.0389) Prec@1 91.000 (93.583) Prec@5 100.000 (99.667) +2022-11-14 14:40:02,039 Epoch: [234][240/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0375 (0.0388) Prec@1 95.000 (93.640) Prec@5 100.000 (99.680) +2022-11-14 14:40:02,467 Epoch: [234][250/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0592 (0.0396) Prec@1 91.000 (93.538) Prec@5 99.000 (99.654) +2022-11-14 14:40:02,961 Epoch: [234][260/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0525 (0.0401) Prec@1 91.000 (93.444) Prec@5 100.000 (99.667) +2022-11-14 14:40:03,365 Epoch: [234][270/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0306 (0.0398) Prec@1 96.000 (93.536) Prec@5 99.000 (99.643) +2022-11-14 14:40:03,792 Epoch: [234][280/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0432 (0.0399) Prec@1 93.000 (93.517) Prec@5 100.000 (99.655) +2022-11-14 14:40:04,234 Epoch: [234][290/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0263 (0.0394) Prec@1 95.000 (93.567) Prec@5 100.000 (99.667) +2022-11-14 14:40:04,660 Epoch: [234][300/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0639 (0.0402) Prec@1 88.000 (93.387) Prec@5 98.000 (99.613) +2022-11-14 14:40:05,080 Epoch: [234][310/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0395 (0.0402) Prec@1 93.000 (93.375) Prec@5 100.000 (99.625) +2022-11-14 14:40:05,499 Epoch: [234][320/500] Time 0.039 (0.039) Data 0.001 (0.003) Loss 0.0349 (0.0400) Prec@1 94.000 (93.394) Prec@5 100.000 (99.636) +2022-11-14 14:40:05,935 Epoch: [234][330/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0264 (0.0396) Prec@1 95.000 (93.441) Prec@5 100.000 (99.647) +2022-11-14 14:40:06,347 Epoch: [234][340/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0597 (0.0402) Prec@1 92.000 (93.400) Prec@5 100.000 (99.657) +2022-11-14 14:40:06,774 Epoch: [234][350/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0303 (0.0399) Prec@1 94.000 (93.417) Prec@5 100.000 (99.667) +2022-11-14 14:40:07,198 Epoch: [234][360/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0319 (0.0397) Prec@1 93.000 (93.405) Prec@5 100.000 (99.676) +2022-11-14 14:40:07,620 Epoch: [234][370/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0421 (0.0398) Prec@1 93.000 (93.395) Prec@5 100.000 (99.684) +2022-11-14 14:40:08,061 Epoch: [234][380/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0112 (0.0390) Prec@1 98.000 (93.513) Prec@5 100.000 (99.692) +2022-11-14 14:40:08,557 Epoch: [234][390/500] Time 0.036 (0.039) Data 0.002 (0.002) Loss 0.0632 (0.0396) Prec@1 90.000 (93.425) Prec@5 99.000 (99.675) +2022-11-14 14:40:08,998 Epoch: [234][400/500] Time 0.048 (0.039) Data 0.002 (0.002) Loss 0.0319 (0.0395) Prec@1 94.000 (93.439) Prec@5 100.000 (99.683) +2022-11-14 14:40:09,420 Epoch: [234][410/500] Time 0.040 (0.039) Data 0.002 (0.002) Loss 0.0334 (0.0393) Prec@1 95.000 (93.476) Prec@5 100.000 (99.690) +2022-11-14 14:40:09,851 Epoch: [234][420/500] Time 0.040 (0.039) Data 0.002 (0.002) Loss 0.0454 (0.0395) Prec@1 91.000 (93.419) Prec@5 100.000 (99.698) +2022-11-14 14:40:10,274 Epoch: [234][430/500] Time 0.039 (0.039) Data 0.002 (0.002) Loss 0.0360 (0.0394) Prec@1 93.000 (93.409) Prec@5 100.000 (99.705) +2022-11-14 14:40:10,779 Epoch: [234][440/500] Time 0.044 (0.039) Data 0.002 (0.002) Loss 0.0491 (0.0396) Prec@1 93.000 (93.400) Prec@5 100.000 (99.711) +2022-11-14 14:40:11,242 Epoch: [234][450/500] Time 0.046 (0.039) Data 0.002 (0.002) Loss 0.0464 (0.0397) Prec@1 92.000 (93.370) Prec@5 99.000 (99.696) +2022-11-14 14:40:11,741 Epoch: [234][460/500] Time 0.052 (0.039) Data 0.002 (0.002) Loss 0.0207 (0.0393) Prec@1 97.000 (93.447) Prec@5 100.000 (99.702) +2022-11-14 14:40:12,172 Epoch: [234][470/500] Time 0.040 (0.039) Data 0.002 (0.002) Loss 0.0390 (0.0393) Prec@1 96.000 (93.500) Prec@5 100.000 (99.708) +2022-11-14 14:40:12,591 Epoch: [234][480/500] Time 0.039 (0.039) Data 0.002 (0.002) Loss 0.0400 (0.0393) Prec@1 94.000 (93.510) Prec@5 100.000 (99.714) +2022-11-14 14:40:13,008 Epoch: [234][490/500] Time 0.040 (0.039) Data 0.002 (0.002) Loss 0.0158 (0.0389) Prec@1 97.000 (93.580) Prec@5 100.000 (99.720) +2022-11-14 14:40:13,395 Epoch: [234][499/500] Time 0.044 (0.039) Data 0.002 (0.002) Loss 0.0321 (0.0387) Prec@1 96.000 (93.627) Prec@5 100.000 (99.725) +2022-11-14 14:40:13,689 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0771 (0.0771) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:13,697 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0744) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:40:13,708 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0768) Prec@1 85.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 14:40:13,719 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0793) Prec@1 89.000 (87.250) Prec@5 98.000 (99.500) +2022-11-14 14:40:13,726 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0778) Prec@1 89.000 (87.600) Prec@5 98.000 (99.200) +2022-11-14 14:40:13,735 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0736) Prec@1 91.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 14:40:13,743 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0726) Prec@1 90.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 14:40:13,753 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0744) Prec@1 85.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:40:13,761 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0778) Prec@1 85.000 (87.667) Prec@5 98.000 (99.333) +2022-11-14 14:40:13,770 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0766) Prec@1 88.000 (87.700) Prec@5 99.000 (99.300) +2022-11-14 14:40:13,780 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0778) Prec@1 87.000 (87.636) Prec@5 99.000 (99.273) +2022-11-14 14:40:13,789 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0785) Prec@1 86.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 14:40:13,797 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0776) Prec@1 88.000 (87.538) Prec@5 99.000 (99.308) +2022-11-14 14:40:13,805 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0772) Prec@1 87.000 (87.500) Prec@5 100.000 (99.357) +2022-11-14 14:40:13,813 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0781) Prec@1 84.000 (87.267) Prec@5 99.000 (99.333) +2022-11-14 14:40:13,824 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0784) Prec@1 86.000 (87.188) Prec@5 100.000 (99.375) +2022-11-14 14:40:13,833 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0776) Prec@1 90.000 (87.353) Prec@5 99.000 (99.353) +2022-11-14 14:40:13,843 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0787) Prec@1 87.000 (87.333) Prec@5 100.000 (99.389) +2022-11-14 14:40:13,851 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0784) Prec@1 86.000 (87.263) Prec@5 99.000 (99.368) +2022-11-14 14:40:13,861 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0786) Prec@1 86.000 (87.200) Prec@5 98.000 (99.300) +2022-11-14 14:40:13,871 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0791) Prec@1 87.000 (87.190) Prec@5 100.000 (99.333) +2022-11-14 14:40:13,879 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0785) Prec@1 90.000 (87.318) Prec@5 100.000 (99.364) +2022-11-14 14:40:13,889 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0794) Prec@1 84.000 (87.174) Prec@5 97.000 (99.261) +2022-11-14 14:40:13,899 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0794) Prec@1 85.000 (87.083) Prec@5 100.000 (99.292) +2022-11-14 14:40:13,907 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0801) Prec@1 85.000 (87.000) Prec@5 100.000 (99.320) +2022-11-14 14:40:13,916 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0805) Prec@1 83.000 (86.846) Prec@5 99.000 (99.308) +2022-11-14 14:40:13,926 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0800) Prec@1 89.000 (86.926) Prec@5 100.000 (99.333) +2022-11-14 14:40:13,935 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0795) Prec@1 88.000 (86.964) Prec@5 99.000 (99.321) +2022-11-14 14:40:13,944 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0792) Prec@1 91.000 (87.103) Prec@5 98.000 (99.276) +2022-11-14 14:40:13,956 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0790) Prec@1 88.000 (87.133) Prec@5 99.000 (99.267) +2022-11-14 14:40:13,965 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0795) Prec@1 85.000 (87.065) Prec@5 99.000 (99.258) +2022-11-14 14:40:13,975 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0796) Prec@1 88.000 (87.094) Prec@5 100.000 (99.281) +2022-11-14 14:40:13,985 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0800) Prec@1 85.000 (87.030) Prec@5 100.000 (99.303) +2022-11-14 14:40:13,995 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1168 (0.0811) Prec@1 78.000 (86.765) Prec@5 100.000 (99.324) +2022-11-14 14:40:14,004 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0812) Prec@1 87.000 (86.771) Prec@5 97.000 (99.257) +2022-11-14 14:40:14,014 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0807) Prec@1 90.000 (86.861) Prec@5 100.000 (99.278) +2022-11-14 14:40:14,024 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0804) Prec@1 89.000 (86.919) Prec@5 99.000 (99.270) +2022-11-14 14:40:14,032 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0805) Prec@1 87.000 (86.921) Prec@5 98.000 (99.237) +2022-11-14 14:40:14,042 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0799) Prec@1 91.000 (87.026) Prec@5 99.000 (99.231) +2022-11-14 14:40:14,052 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0796) Prec@1 90.000 (87.100) Prec@5 99.000 (99.225) +2022-11-14 14:40:14,061 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0800) Prec@1 87.000 (87.098) Prec@5 98.000 (99.195) +2022-11-14 14:40:14,071 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0797) Prec@1 89.000 (87.143) Prec@5 99.000 (99.190) +2022-11-14 14:40:14,080 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0790) Prec@1 93.000 (87.279) Prec@5 100.000 (99.209) +2022-11-14 14:40:14,090 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0792) Prec@1 86.000 (87.250) Prec@5 99.000 (99.205) +2022-11-14 14:40:14,098 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0792) Prec@1 87.000 (87.244) Prec@5 100.000 (99.222) +2022-11-14 14:40:14,107 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0798) Prec@1 85.000 (87.196) Prec@5 100.000 (99.239) +2022-11-14 14:40:14,115 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0797) Prec@1 88.000 (87.213) Prec@5 100.000 (99.255) +2022-11-14 14:40:14,125 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0802) Prec@1 83.000 (87.125) Prec@5 97.000 (99.208) +2022-11-14 14:40:14,135 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0425 (0.0794) Prec@1 94.000 (87.265) Prec@5 100.000 (99.224) +2022-11-14 14:40:14,143 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0797) Prec@1 83.000 (87.180) Prec@5 99.000 (99.220) +2022-11-14 14:40:14,153 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0794) Prec@1 89.000 (87.216) Prec@5 99.000 (99.216) +2022-11-14 14:40:14,163 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0795) Prec@1 85.000 (87.173) Prec@5 100.000 (99.231) +2022-11-14 14:40:14,171 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0792) Prec@1 91.000 (87.245) Prec@5 100.000 (99.245) +2022-11-14 14:40:14,181 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0791) Prec@1 89.000 (87.278) Prec@5 100.000 (99.259) +2022-11-14 14:40:14,191 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0789) Prec@1 88.000 (87.291) Prec@5 100.000 (99.273) +2022-11-14 14:40:14,201 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0787) Prec@1 89.000 (87.321) Prec@5 99.000 (99.268) +2022-11-14 14:40:14,211 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0784) Prec@1 91.000 (87.386) Prec@5 99.000 (99.263) +2022-11-14 14:40:14,220 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0784) Prec@1 89.000 (87.414) Prec@5 98.000 (99.241) +2022-11-14 14:40:14,230 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0789) Prec@1 84.000 (87.356) Prec@5 99.000 (99.237) +2022-11-14 14:40:14,240 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0791) Prec@1 84.000 (87.300) Prec@5 98.000 (99.217) +2022-11-14 14:40:14,249 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0788) Prec@1 91.000 (87.361) Prec@5 99.000 (99.213) +2022-11-14 14:40:14,260 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0786) Prec@1 89.000 (87.387) Prec@5 99.000 (99.210) +2022-11-14 14:40:14,268 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0785) Prec@1 88.000 (87.397) Prec@5 100.000 (99.222) +2022-11-14 14:40:14,278 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0781) Prec@1 91.000 (87.453) Prec@5 99.000 (99.219) +2022-11-14 14:40:14,288 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0784) Prec@1 82.000 (87.369) Prec@5 99.000 (99.215) +2022-11-14 14:40:14,298 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0786) Prec@1 85.000 (87.333) Prec@5 98.000 (99.197) +2022-11-14 14:40:14,308 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0781) Prec@1 91.000 (87.388) Prec@5 100.000 (99.209) +2022-11-14 14:40:14,317 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0782) Prec@1 85.000 (87.353) Prec@5 100.000 (99.221) +2022-11-14 14:40:14,327 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0781) Prec@1 89.000 (87.377) Prec@5 99.000 (99.217) +2022-11-14 14:40:14,337 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0781) Prec@1 86.000 (87.357) Prec@5 100.000 (99.229) +2022-11-14 14:40:14,346 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0783) Prec@1 87.000 (87.352) Prec@5 98.000 (99.211) +2022-11-14 14:40:14,357 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0781) Prec@1 92.000 (87.417) Prec@5 100.000 (99.222) +2022-11-14 14:40:14,365 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0777) Prec@1 93.000 (87.493) Prec@5 99.000 (99.219) +2022-11-14 14:40:14,375 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0776) Prec@1 90.000 (87.527) Prec@5 100.000 (99.230) +2022-11-14 14:40:14,385 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0779) Prec@1 80.000 (87.427) Prec@5 100.000 (99.240) +2022-11-14 14:40:14,394 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0778) Prec@1 91.000 (87.474) Prec@5 99.000 (99.237) +2022-11-14 14:40:14,403 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0779) Prec@1 86.000 (87.455) Prec@5 100.000 (99.247) +2022-11-14 14:40:14,412 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0781) Prec@1 85.000 (87.423) Prec@5 98.000 (99.231) +2022-11-14 14:40:14,421 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0782) Prec@1 86.000 (87.405) Prec@5 100.000 (99.241) +2022-11-14 14:40:14,430 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0783) Prec@1 86.000 (87.388) Prec@5 99.000 (99.237) +2022-11-14 14:40:14,441 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0785) Prec@1 84.000 (87.346) Prec@5 98.000 (99.222) +2022-11-14 14:40:14,451 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0784) Prec@1 84.000 (87.305) Prec@5 99.000 (99.220) +2022-11-14 14:40:14,462 Test: [82/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0786) Prec@1 84.000 (87.265) Prec@5 99.000 (99.217) +2022-11-14 14:40:14,474 Test: [83/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0783) Prec@1 91.000 (87.310) Prec@5 99.000 (99.214) +2022-11-14 14:40:14,483 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0785) Prec@1 87.000 (87.306) Prec@5 99.000 (99.212) +2022-11-14 14:40:14,492 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0786) Prec@1 87.000 (87.302) Prec@5 99.000 (99.209) +2022-11-14 14:40:14,503 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0786) Prec@1 87.000 (87.299) Prec@5 100.000 (99.218) +2022-11-14 14:40:14,511 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0786) Prec@1 87.000 (87.295) Prec@5 98.000 (99.205) +2022-11-14 14:40:14,521 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0787) Prec@1 87.000 (87.292) Prec@5 99.000 (99.202) +2022-11-14 14:40:14,531 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0786) Prec@1 90.000 (87.322) Prec@5 97.000 (99.178) +2022-11-14 14:40:14,539 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0784) Prec@1 91.000 (87.363) Prec@5 100.000 (99.187) +2022-11-14 14:40:14,550 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0378 (0.0780) Prec@1 94.000 (87.435) Prec@5 99.000 (99.185) +2022-11-14 14:40:14,560 Test: [92/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0782) Prec@1 83.000 (87.387) Prec@5 100.000 (99.194) +2022-11-14 14:40:14,569 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0781) Prec@1 88.000 (87.394) Prec@5 99.000 (99.191) +2022-11-14 14:40:14,579 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0782) Prec@1 84.000 (87.358) Prec@5 99.000 (99.189) +2022-11-14 14:40:14,588 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0780) Prec@1 92.000 (87.406) Prec@5 99.000 (99.188) +2022-11-14 14:40:14,598 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0778) Prec@1 91.000 (87.443) Prec@5 99.000 (99.186) +2022-11-14 14:40:14,608 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0780) Prec@1 84.000 (87.408) Prec@5 100.000 (99.194) +2022-11-14 14:40:14,618 Test: [98/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.0784) Prec@1 82.000 (87.354) Prec@5 100.000 (99.202) +2022-11-14 14:40:14,628 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0782) Prec@1 88.000 (87.360) Prec@5 98.000 (99.190) +2022-11-14 14:40:14,698 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:40:15,008 Epoch: [235][0/500] Time 0.024 (0.024) Data 0.219 (0.219) Loss 0.0599 (0.0599) Prec@1 91.000 (91.000) Prec@5 98.000 (98.000) +2022-11-14 14:40:15,263 Epoch: [235][10/500] Time 0.018 (0.023) Data 0.001 (0.021) Loss 0.0322 (0.0460) Prec@1 98.000 (94.500) Prec@5 100.000 (99.000) +2022-11-14 14:40:15,472 Epoch: [235][20/500] Time 0.020 (0.021) Data 0.002 (0.012) Loss 0.0549 (0.0490) Prec@1 89.000 (92.667) Prec@5 99.000 (99.000) +2022-11-14 14:40:15,861 Epoch: [235][30/500] Time 0.034 (0.025) Data 0.002 (0.009) Loss 0.0627 (0.0524) Prec@1 91.000 (92.250) Prec@5 97.000 (98.500) +2022-11-14 14:40:16,187 Epoch: [235][40/500] Time 0.029 (0.026) Data 0.002 (0.007) Loss 0.0468 (0.0513) Prec@1 91.000 (92.000) Prec@5 98.000 (98.400) +2022-11-14 14:40:16,576 Epoch: [235][50/500] Time 0.039 (0.028) Data 0.002 (0.006) Loss 0.0644 (0.0535) Prec@1 91.000 (91.833) Prec@5 100.000 (98.667) +2022-11-14 14:40:16,959 Epoch: [235][60/500] Time 0.037 (0.029) Data 0.002 (0.005) Loss 0.0265 (0.0496) Prec@1 96.000 (92.429) Prec@5 100.000 (98.857) +2022-11-14 14:40:17,292 Epoch: [235][70/500] Time 0.027 (0.029) Data 0.002 (0.005) Loss 0.0381 (0.0482) Prec@1 93.000 (92.500) Prec@5 100.000 (99.000) +2022-11-14 14:40:17,675 Epoch: [235][80/500] Time 0.022 (0.030) Data 0.002 (0.004) Loss 0.0309 (0.0463) Prec@1 95.000 (92.778) Prec@5 99.000 (99.000) +2022-11-14 14:40:17,999 Epoch: [235][90/500] Time 0.029 (0.029) Data 0.002 (0.004) Loss 0.0415 (0.0458) Prec@1 94.000 (92.900) Prec@5 100.000 (99.100) +2022-11-14 14:40:18,330 Epoch: [235][100/500] Time 0.031 (0.029) Data 0.002 (0.004) Loss 0.0609 (0.0472) Prec@1 91.000 (92.727) Prec@5 100.000 (99.182) +2022-11-14 14:40:18,684 Epoch: [235][110/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0354 (0.0462) Prec@1 95.000 (92.917) Prec@5 100.000 (99.250) +2022-11-14 14:40:19,035 Epoch: [235][120/500] Time 0.028 (0.030) Data 0.002 (0.004) Loss 0.0411 (0.0458) Prec@1 92.000 (92.846) Prec@5 100.000 (99.308) +2022-11-14 14:40:19,417 Epoch: [235][130/500] Time 0.042 (0.030) Data 0.002 (0.004) Loss 0.0372 (0.0452) Prec@1 96.000 (93.071) Prec@5 100.000 (99.357) +2022-11-14 14:40:19,751 Epoch: [235][140/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0406 (0.0449) Prec@1 92.000 (93.000) Prec@5 100.000 (99.400) +2022-11-14 14:40:20,126 Epoch: [235][150/500] Time 0.052 (0.030) Data 0.002 (0.003) Loss 0.0476 (0.0450) Prec@1 92.000 (92.938) Prec@5 100.000 (99.438) +2022-11-14 14:40:20,530 Epoch: [235][160/500] Time 0.038 (0.030) Data 0.002 (0.003) Loss 0.0349 (0.0444) Prec@1 94.000 (93.000) Prec@5 100.000 (99.471) +2022-11-14 14:40:20,923 Epoch: [235][170/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0334 (0.0438) Prec@1 95.000 (93.111) Prec@5 100.000 (99.500) +2022-11-14 14:40:21,260 Epoch: [235][180/500] Time 0.028 (0.031) Data 0.002 (0.003) Loss 0.0452 (0.0439) Prec@1 93.000 (93.105) Prec@5 100.000 (99.526) +2022-11-14 14:40:21,662 Epoch: [235][190/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.0393 (0.0437) Prec@1 94.000 (93.150) Prec@5 100.000 (99.550) +2022-11-14 14:40:21,972 Epoch: [235][200/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0351 (0.0433) Prec@1 94.000 (93.190) Prec@5 100.000 (99.571) +2022-11-14 14:40:22,390 Epoch: [235][210/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0460 (0.0434) Prec@1 94.000 (93.227) Prec@5 100.000 (99.591) +2022-11-14 14:40:22,738 Epoch: [235][220/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0425 (0.0434) Prec@1 92.000 (93.174) Prec@5 100.000 (99.609) +2022-11-14 14:40:23,069 Epoch: [235][230/500] Time 0.030 (0.031) Data 0.002 (0.003) Loss 0.0406 (0.0432) Prec@1 93.000 (93.167) Prec@5 100.000 (99.625) +2022-11-14 14:40:23,455 Epoch: [235][240/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0273 (0.0426) Prec@1 96.000 (93.280) Prec@5 99.000 (99.600) +2022-11-14 14:40:23,819 Epoch: [235][250/500] Time 0.038 (0.031) Data 0.003 (0.003) Loss 0.0457 (0.0427) Prec@1 95.000 (93.346) Prec@5 99.000 (99.577) +2022-11-14 14:40:24,148 Epoch: [235][260/500] Time 0.029 (0.031) Data 0.002 (0.003) Loss 0.0672 (0.0436) Prec@1 89.000 (93.185) Prec@5 100.000 (99.593) +2022-11-14 14:40:24,529 Epoch: [235][270/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0346 (0.0433) Prec@1 94.000 (93.214) Prec@5 100.000 (99.607) +2022-11-14 14:40:24,863 Epoch: [235][280/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0317 (0.0429) Prec@1 96.000 (93.310) Prec@5 100.000 (99.621) +2022-11-14 14:40:25,321 Epoch: [235][290/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0439 (0.0429) Prec@1 92.000 (93.267) Prec@5 100.000 (99.633) +2022-11-14 14:40:25,952 Epoch: [235][300/500] Time 0.081 (0.032) Data 0.002 (0.003) Loss 0.0223 (0.0423) Prec@1 96.000 (93.355) Prec@5 99.000 (99.613) +2022-11-14 14:40:26,524 Epoch: [235][310/500] Time 0.064 (0.033) Data 0.002 (0.003) Loss 0.0450 (0.0424) Prec@1 92.000 (93.312) Prec@5 99.000 (99.594) +2022-11-14 14:40:27,052 Epoch: [235][320/500] Time 0.045 (0.033) Data 0.002 (0.003) Loss 0.0291 (0.0420) Prec@1 95.000 (93.364) Prec@5 100.000 (99.606) +2022-11-14 14:40:27,588 Epoch: [235][330/500] Time 0.080 (0.034) Data 0.002 (0.003) Loss 0.0355 (0.0418) Prec@1 93.000 (93.353) Prec@5 100.000 (99.618) +2022-11-14 14:40:28,377 Epoch: [235][340/500] Time 0.087 (0.035) Data 0.002 (0.003) Loss 0.0306 (0.0414) Prec@1 93.000 (93.343) Prec@5 100.000 (99.629) +2022-11-14 14:40:29,078 Epoch: [235][350/500] Time 0.087 (0.036) Data 0.002 (0.003) Loss 0.0360 (0.0413) Prec@1 93.000 (93.333) Prec@5 100.000 (99.639) +2022-11-14 14:40:29,900 Epoch: [235][360/500] Time 0.091 (0.037) Data 0.003 (0.003) Loss 0.0518 (0.0416) Prec@1 91.000 (93.270) Prec@5 100.000 (99.649) +2022-11-14 14:40:30,486 Epoch: [235][370/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0364 (0.0414) Prec@1 95.000 (93.316) Prec@5 100.000 (99.658) +2022-11-14 14:40:30,972 Epoch: [235][380/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0531 (0.0417) Prec@1 91.000 (93.256) Prec@5 100.000 (99.667) +2022-11-14 14:40:31,450 Epoch: [235][390/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0558 (0.0421) Prec@1 90.000 (93.175) Prec@5 100.000 (99.675) +2022-11-14 14:40:31,927 Epoch: [235][400/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0475 (0.0422) Prec@1 93.000 (93.171) Prec@5 99.000 (99.659) +2022-11-14 14:40:32,407 Epoch: [235][410/500] Time 0.052 (0.038) Data 0.002 (0.002) Loss 0.0516 (0.0424) Prec@1 92.000 (93.143) Prec@5 100.000 (99.667) +2022-11-14 14:40:32,886 Epoch: [235][420/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0417 (0.0424) Prec@1 94.000 (93.163) Prec@5 100.000 (99.674) +2022-11-14 14:40:33,371 Epoch: [235][430/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0415 (0.0424) Prec@1 92.000 (93.136) Prec@5 100.000 (99.682) +2022-11-14 14:40:33,854 Epoch: [235][440/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0287 (0.0421) Prec@1 94.000 (93.156) Prec@5 100.000 (99.689) +2022-11-14 14:40:34,327 Epoch: [235][450/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0588 (0.0425) Prec@1 91.000 (93.109) Prec@5 98.000 (99.652) +2022-11-14 14:40:34,823 Epoch: [235][460/500] Time 0.045 (0.038) Data 0.002 (0.002) Loss 0.0680 (0.0430) Prec@1 88.000 (93.000) Prec@5 99.000 (99.638) +2022-11-14 14:40:35,304 Epoch: [235][470/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0528 (0.0432) Prec@1 90.000 (92.938) Prec@5 98.000 (99.604) +2022-11-14 14:40:35,783 Epoch: [235][480/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0268 (0.0429) Prec@1 95.000 (92.980) Prec@5 100.000 (99.612) +2022-11-14 14:40:36,261 Epoch: [235][490/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0191 (0.0424) Prec@1 96.000 (93.040) Prec@5 100.000 (99.620) +2022-11-14 14:40:36,696 Epoch: [235][499/500] Time 0.044 (0.039) Data 0.001 (0.002) Loss 0.0548 (0.0426) Prec@1 90.000 (92.980) Prec@5 100.000 (99.627) +2022-11-14 14:40:36,966 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0549 (0.0549) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:36,976 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0650) Prec@1 87.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:40:36,984 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0682) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:36,998 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0708) Prec@1 87.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:40:37,008 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0736) Prec@1 87.000 (88.200) Prec@5 99.000 (99.800) +2022-11-14 14:40:37,020 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0688) Prec@1 92.000 (88.833) Prec@5 99.000 (99.667) +2022-11-14 14:40:37,030 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0679) Prec@1 89.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 14:40:37,044 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0684) Prec@1 87.000 (88.625) Prec@5 99.000 (99.625) +2022-11-14 14:40:37,056 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0691) Prec@1 88.000 (88.556) Prec@5 99.000 (99.556) +2022-11-14 14:40:37,069 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0697) Prec@1 87.000 (88.400) Prec@5 98.000 (99.400) +2022-11-14 14:40:37,086 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0686) Prec@1 91.000 (88.636) Prec@5 100.000 (99.455) +2022-11-14 14:40:37,100 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0684) Prec@1 90.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 14:40:37,117 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0674) Prec@1 90.000 (88.846) Prec@5 98.000 (99.385) +2022-11-14 14:40:37,135 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0683) Prec@1 88.000 (88.786) Prec@5 99.000 (99.357) +2022-11-14 14:40:37,151 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0697) Prec@1 85.000 (88.533) Prec@5 100.000 (99.400) +2022-11-14 14:40:37,168 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0706) Prec@1 88.000 (88.500) Prec@5 99.000 (99.375) +2022-11-14 14:40:37,187 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0703) Prec@1 90.000 (88.588) Prec@5 99.000 (99.353) +2022-11-14 14:40:37,205 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1142 (0.0728) Prec@1 82.000 (88.222) Prec@5 99.000 (99.333) +2022-11-14 14:40:37,221 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0736) Prec@1 84.000 (88.000) Prec@5 98.000 (99.263) +2022-11-14 14:40:37,237 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0745) Prec@1 85.000 (87.850) Prec@5 95.000 (99.050) +2022-11-14 14:40:37,256 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0747) Prec@1 86.000 (87.762) Prec@5 100.000 (99.095) +2022-11-14 14:40:37,273 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0758) Prec@1 86.000 (87.682) Prec@5 100.000 (99.136) +2022-11-14 14:40:37,291 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1151 (0.0775) Prec@1 83.000 (87.478) Prec@5 99.000 (99.130) +2022-11-14 14:40:37,308 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0768) Prec@1 87.000 (87.458) Prec@5 100.000 (99.167) +2022-11-14 14:40:37,325 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0771) Prec@1 86.000 (87.400) Prec@5 100.000 (99.200) +2022-11-14 14:40:37,343 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0776) Prec@1 85.000 (87.308) Prec@5 97.000 (99.115) +2022-11-14 14:40:37,359 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0772) Prec@1 88.000 (87.333) Prec@5 100.000 (99.148) +2022-11-14 14:40:37,377 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0769) Prec@1 87.000 (87.321) Prec@5 100.000 (99.179) +2022-11-14 14:40:37,394 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0761) Prec@1 90.000 (87.414) Prec@5 98.000 (99.138) +2022-11-14 14:40:37,412 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0760) Prec@1 88.000 (87.433) Prec@5 98.000 (99.100) +2022-11-14 14:40:37,429 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0756) Prec@1 90.000 (87.516) Prec@5 100.000 (99.129) +2022-11-14 14:40:37,446 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0751) Prec@1 90.000 (87.594) Prec@5 100.000 (99.156) +2022-11-14 14:40:37,461 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0751) Prec@1 86.000 (87.545) Prec@5 100.000 (99.182) +2022-11-14 14:40:37,478 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0757) Prec@1 80.000 (87.324) Prec@5 100.000 (99.206) +2022-11-14 14:40:37,496 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0763) Prec@1 84.000 (87.229) Prec@5 98.000 (99.171) +2022-11-14 14:40:37,513 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0760) Prec@1 90.000 (87.306) Prec@5 99.000 (99.167) +2022-11-14 14:40:37,530 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0762) Prec@1 86.000 (87.270) Prec@5 98.000 (99.135) +2022-11-14 14:40:37,549 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0765) Prec@1 87.000 (87.263) Prec@5 98.000 (99.105) +2022-11-14 14:40:37,566 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0760) Prec@1 92.000 (87.385) Prec@5 98.000 (99.077) +2022-11-14 14:40:37,583 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0756) Prec@1 90.000 (87.450) Prec@5 99.000 (99.075) +2022-11-14 14:40:37,600 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0761) Prec@1 81.000 (87.293) Prec@5 98.000 (99.049) +2022-11-14 14:40:37,619 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0763) Prec@1 86.000 (87.262) Prec@5 99.000 (99.048) +2022-11-14 14:40:37,636 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0760) Prec@1 88.000 (87.279) Prec@5 100.000 (99.070) +2022-11-14 14:40:37,655 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0761) Prec@1 87.000 (87.273) Prec@5 98.000 (99.045) +2022-11-14 14:40:37,674 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0758) Prec@1 90.000 (87.333) Prec@5 99.000 (99.044) +2022-11-14 14:40:37,692 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0760) Prec@1 84.000 (87.261) Prec@5 100.000 (99.065) +2022-11-14 14:40:37,709 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0757) Prec@1 88.000 (87.277) Prec@5 100.000 (99.085) +2022-11-14 14:40:37,726 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0762) Prec@1 83.000 (87.188) Prec@5 98.000 (99.062) +2022-11-14 14:40:37,743 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0760) Prec@1 90.000 (87.245) Prec@5 100.000 (99.082) +2022-11-14 14:40:37,760 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1220 (0.0769) Prec@1 78.000 (87.060) Prec@5 99.000 (99.080) +2022-11-14 14:40:37,778 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0766) Prec@1 89.000 (87.098) Prec@5 100.000 (99.098) +2022-11-14 14:40:37,796 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0768) Prec@1 83.000 (87.019) Prec@5 100.000 (99.115) +2022-11-14 14:40:37,813 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0762) Prec@1 92.000 (87.113) Prec@5 99.000 (99.113) +2022-11-14 14:40:37,830 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0763) Prec@1 87.000 (87.111) Prec@5 98.000 (99.093) +2022-11-14 14:40:37,848 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0764) Prec@1 87.000 (87.109) Prec@5 100.000 (99.109) +2022-11-14 14:40:37,870 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 90.000 (87.161) Prec@5 99.000 (99.107) +2022-11-14 14:40:37,889 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0765) Prec@1 85.000 (87.123) Prec@5 100.000 (99.123) +2022-11-14 14:40:37,907 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0764) Prec@1 89.000 (87.155) Prec@5 100.000 (99.138) +2022-11-14 14:40:37,924 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0769) Prec@1 83.000 (87.085) Prec@5 100.000 (99.153) +2022-11-14 14:40:37,941 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0771) Prec@1 86.000 (87.067) Prec@5 100.000 (99.167) +2022-11-14 14:40:37,958 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0771) Prec@1 88.000 (87.082) Prec@5 100.000 (99.180) +2022-11-14 14:40:37,976 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0768) Prec@1 88.000 (87.097) Prec@5 100.000 (99.194) +2022-11-14 14:40:37,994 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0765) Prec@1 90.000 (87.143) Prec@5 100.000 (99.206) +2022-11-14 14:40:38,014 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0762) Prec@1 92.000 (87.219) Prec@5 99.000 (99.203) +2022-11-14 14:40:38,031 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0763) Prec@1 87.000 (87.215) Prec@5 100.000 (99.215) +2022-11-14 14:40:38,049 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0761) Prec@1 86.000 (87.197) Prec@5 100.000 (99.227) +2022-11-14 14:40:38,066 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0756) Prec@1 93.000 (87.284) Prec@5 100.000 (99.239) +2022-11-14 14:40:38,085 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0757) Prec@1 89.000 (87.309) Prec@5 100.000 (99.250) +2022-11-14 14:40:38,105 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0757) Prec@1 88.000 (87.319) Prec@5 99.000 (99.246) +2022-11-14 14:40:38,122 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0757) Prec@1 87.000 (87.314) Prec@5 100.000 (99.257) +2022-11-14 14:40:38,139 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0759) Prec@1 83.000 (87.254) Prec@5 99.000 (99.254) +2022-11-14 14:40:38,156 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0757) Prec@1 89.000 (87.278) Prec@5 100.000 (99.264) +2022-11-14 14:40:38,174 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0756) Prec@1 89.000 (87.301) Prec@5 100.000 (99.274) +2022-11-14 14:40:38,192 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0752) Prec@1 92.000 (87.365) Prec@5 100.000 (99.284) +2022-11-14 14:40:38,212 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0756) Prec@1 80.000 (87.267) Prec@5 99.000 (99.280) +2022-11-14 14:40:38,230 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0753) Prec@1 91.000 (87.316) Prec@5 100.000 (99.289) +2022-11-14 14:40:38,249 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0754) Prec@1 84.000 (87.273) Prec@5 98.000 (99.273) +2022-11-14 14:40:38,266 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0757) Prec@1 83.000 (87.218) Prec@5 99.000 (99.269) +2022-11-14 14:40:38,284 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0759) Prec@1 84.000 (87.177) Prec@5 99.000 (99.266) +2022-11-14 14:40:38,304 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0760) Prec@1 87.000 (87.175) Prec@5 99.000 (99.263) +2022-11-14 14:40:38,322 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0760) Prec@1 87.000 (87.173) Prec@5 99.000 (99.259) +2022-11-14 14:40:38,341 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0761) Prec@1 85.000 (87.146) Prec@5 99.000 (99.256) +2022-11-14 14:40:38,357 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0761) Prec@1 89.000 (87.169) Prec@5 100.000 (99.265) +2022-11-14 14:40:38,375 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0762) Prec@1 86.000 (87.155) Prec@5 99.000 (99.262) +2022-11-14 14:40:38,393 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0766) Prec@1 82.000 (87.094) Prec@5 99.000 (99.259) +2022-11-14 14:40:38,410 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0769) Prec@1 84.000 (87.058) Prec@5 100.000 (99.267) +2022-11-14 14:40:38,428 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0770) Prec@1 88.000 (87.069) Prec@5 100.000 (99.276) +2022-11-14 14:40:38,445 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0771) Prec@1 86.000 (87.057) Prec@5 100.000 (99.284) +2022-11-14 14:40:38,463 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0769) Prec@1 91.000 (87.101) Prec@5 100.000 (99.292) +2022-11-14 14:40:38,480 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0769) Prec@1 90.000 (87.133) Prec@5 100.000 (99.300) +2022-11-14 14:40:38,496 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0767) Prec@1 90.000 (87.165) Prec@5 100.000 (99.308) +2022-11-14 14:40:38,513 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0764) Prec@1 91.000 (87.207) Prec@5 99.000 (99.304) +2022-11-14 14:40:38,531 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0765) Prec@1 88.000 (87.215) Prec@5 100.000 (99.312) +2022-11-14 14:40:38,547 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0765) Prec@1 87.000 (87.213) Prec@5 99.000 (99.309) +2022-11-14 14:40:38,564 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0766) Prec@1 87.000 (87.211) Prec@5 98.000 (99.295) +2022-11-14 14:40:38,581 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0764) Prec@1 92.000 (87.260) Prec@5 99.000 (99.292) +2022-11-14 14:40:38,598 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0760) Prec@1 97.000 (87.361) Prec@5 99.000 (99.289) +2022-11-14 14:40:38,614 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0762) Prec@1 85.000 (87.337) Prec@5 99.000 (99.286) +2022-11-14 14:40:38,632 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0765) Prec@1 86.000 (87.323) Prec@5 100.000 (99.293) +2022-11-14 14:40:38,650 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0764) Prec@1 89.000 (87.340) Prec@5 98.000 (99.280) +2022-11-14 14:40:38,706 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:40:39,019 Epoch: [236][0/500] Time 0.025 (0.025) Data 0.230 (0.230) Loss 0.0580 (0.0580) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:39,226 Epoch: [236][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0406 (0.0493) Prec@1 95.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:39,432 Epoch: [236][20/500] Time 0.018 (0.018) Data 0.001 (0.013) Loss 0.0503 (0.0496) Prec@1 92.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 14:40:39,646 Epoch: [236][30/500] Time 0.021 (0.019) Data 0.002 (0.009) Loss 0.0467 (0.0489) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:40:39,921 Epoch: [236][40/500] Time 0.025 (0.020) Data 0.002 (0.007) Loss 0.0485 (0.0488) Prec@1 92.000 (92.400) Prec@5 99.000 (99.800) +2022-11-14 14:40:40,204 Epoch: [236][50/500] Time 0.023 (0.021) Data 0.002 (0.006) Loss 0.0361 (0.0467) Prec@1 93.000 (92.500) Prec@5 100.000 (99.833) +2022-11-14 14:40:40,483 Epoch: [236][60/500] Time 0.026 (0.022) Data 0.001 (0.005) Loss 0.0295 (0.0442) Prec@1 96.000 (93.000) Prec@5 99.000 (99.714) +2022-11-14 14:40:40,762 Epoch: [236][70/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0378 (0.0434) Prec@1 93.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:40:41,042 Epoch: [236][80/500] Time 0.025 (0.022) Data 0.001 (0.005) Loss 0.0279 (0.0417) Prec@1 95.000 (93.222) Prec@5 100.000 (99.778) +2022-11-14 14:40:41,362 Epoch: [236][90/500] Time 0.037 (0.023) Data 0.002 (0.004) Loss 0.0335 (0.0409) Prec@1 94.000 (93.300) Prec@5 100.000 (99.800) +2022-11-14 14:40:41,885 Epoch: [236][100/500] Time 0.061 (0.025) Data 0.002 (0.004) Loss 0.0338 (0.0402) Prec@1 94.000 (93.364) Prec@5 100.000 (99.818) +2022-11-14 14:40:42,631 Epoch: [236][110/500] Time 0.079 (0.029) Data 0.002 (0.004) Loss 0.0484 (0.0409) Prec@1 92.000 (93.250) Prec@5 99.000 (99.750) +2022-11-14 14:40:43,205 Epoch: [236][120/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0442 (0.0412) Prec@1 93.000 (93.231) Prec@5 100.000 (99.769) +2022-11-14 14:40:43,688 Epoch: [236][130/500] Time 0.043 (0.032) Data 0.002 (0.004) Loss 0.0500 (0.0418) Prec@1 92.000 (93.143) Prec@5 99.000 (99.714) +2022-11-14 14:40:44,169 Epoch: [236][140/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0336 (0.0413) Prec@1 95.000 (93.267) Prec@5 100.000 (99.733) +2022-11-14 14:40:44,647 Epoch: [236][150/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0454 (0.0415) Prec@1 92.000 (93.188) Prec@5 100.000 (99.750) +2022-11-14 14:40:45,126 Epoch: [236][160/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0147 (0.0399) Prec@1 99.000 (93.529) Prec@5 100.000 (99.765) +2022-11-14 14:40:45,605 Epoch: [236][170/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0206 (0.0389) Prec@1 96.000 (93.667) Prec@5 100.000 (99.778) +2022-11-14 14:40:46,084 Epoch: [236][180/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0416 (0.0390) Prec@1 93.000 (93.632) Prec@5 99.000 (99.737) +2022-11-14 14:40:46,564 Epoch: [236][190/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0247 (0.0383) Prec@1 97.000 (93.800) Prec@5 100.000 (99.750) +2022-11-14 14:40:47,043 Epoch: [236][200/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0340 (0.0381) Prec@1 94.000 (93.810) Prec@5 100.000 (99.762) +2022-11-14 14:40:47,522 Epoch: [236][210/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0352 (0.0380) Prec@1 95.000 (93.864) Prec@5 100.000 (99.773) +2022-11-14 14:40:48,001 Epoch: [236][220/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0341 (0.0378) Prec@1 95.000 (93.913) Prec@5 100.000 (99.783) +2022-11-14 14:40:48,481 Epoch: [236][230/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0262 (0.0373) Prec@1 96.000 (94.000) Prec@5 100.000 (99.792) +2022-11-14 14:40:48,961 Epoch: [236][240/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0519 (0.0379) Prec@1 91.000 (93.880) Prec@5 99.000 (99.760) +2022-11-14 14:40:49,441 Epoch: [236][250/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0389 (0.0379) Prec@1 94.000 (93.885) Prec@5 100.000 (99.769) +2022-11-14 14:40:49,921 Epoch: [236][260/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0343 (0.0378) Prec@1 94.000 (93.889) Prec@5 100.000 (99.778) +2022-11-14 14:40:50,401 Epoch: [236][270/500] Time 0.051 (0.037) Data 0.002 (0.003) Loss 0.0173 (0.0371) Prec@1 98.000 (94.036) Prec@5 100.000 (99.786) +2022-11-14 14:40:50,879 Epoch: [236][280/500] Time 0.045 (0.038) Data 0.001 (0.003) Loss 0.0270 (0.0367) Prec@1 95.000 (94.069) Prec@5 100.000 (99.793) +2022-11-14 14:40:51,360 Epoch: [236][290/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0288 (0.0365) Prec@1 95.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 14:40:51,830 Epoch: [236][300/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0399 (0.0366) Prec@1 93.000 (94.065) Prec@5 100.000 (99.806) +2022-11-14 14:40:52,303 Epoch: [236][310/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0455 (0.0369) Prec@1 91.000 (93.969) Prec@5 100.000 (99.812) +2022-11-14 14:40:52,780 Epoch: [236][320/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0356 (0.0368) Prec@1 96.000 (94.030) Prec@5 100.000 (99.818) +2022-11-14 14:40:53,256 Epoch: [236][330/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0330 (0.0367) Prec@1 94.000 (94.029) Prec@5 100.000 (99.824) +2022-11-14 14:40:53,732 Epoch: [236][340/500] Time 0.043 (0.038) Data 0.001 (0.003) Loss 0.0552 (0.0372) Prec@1 90.000 (93.914) Prec@5 100.000 (99.829) +2022-11-14 14:40:54,210 Epoch: [236][350/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0313 (0.0371) Prec@1 95.000 (93.944) Prec@5 100.000 (99.833) +2022-11-14 14:40:54,607 Epoch: [236][360/500] Time 0.030 (0.038) Data 0.001 (0.003) Loss 0.0219 (0.0367) Prec@1 95.000 (93.973) Prec@5 100.000 (99.838) +2022-11-14 14:40:54,927 Epoch: [236][370/500] Time 0.029 (0.038) Data 0.002 (0.003) Loss 0.0249 (0.0363) Prec@1 96.000 (94.026) Prec@5 100.000 (99.842) +2022-11-14 14:40:55,245 Epoch: [236][380/500] Time 0.030 (0.038) Data 0.002 (0.002) Loss 0.0365 (0.0363) Prec@1 93.000 (94.000) Prec@5 100.000 (99.846) +2022-11-14 14:40:55,563 Epoch: [236][390/500] Time 0.029 (0.038) Data 0.003 (0.002) Loss 0.0288 (0.0362) Prec@1 95.000 (94.025) Prec@5 100.000 (99.850) +2022-11-14 14:40:55,888 Epoch: [236][400/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0255 (0.0359) Prec@1 96.000 (94.073) Prec@5 99.000 (99.829) +2022-11-14 14:40:56,203 Epoch: [236][410/500] Time 0.028 (0.037) Data 0.002 (0.002) Loss 0.0364 (0.0359) Prec@1 95.000 (94.095) Prec@5 100.000 (99.833) +2022-11-14 14:40:56,524 Epoch: [236][420/500] Time 0.025 (0.037) Data 0.002 (0.002) Loss 0.0529 (0.0363) Prec@1 90.000 (94.000) Prec@5 100.000 (99.837) +2022-11-14 14:40:56,843 Epoch: [236][430/500] Time 0.030 (0.037) Data 0.001 (0.002) Loss 0.0095 (0.0357) Prec@1 99.000 (94.114) Prec@5 100.000 (99.841) +2022-11-14 14:40:57,160 Epoch: [236][440/500] Time 0.026 (0.037) Data 0.002 (0.002) Loss 0.0401 (0.0358) Prec@1 93.000 (94.089) Prec@5 100.000 (99.844) +2022-11-14 14:40:57,480 Epoch: [236][450/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0227 (0.0355) Prec@1 97.000 (94.152) Prec@5 100.000 (99.848) +2022-11-14 14:40:57,794 Epoch: [236][460/500] Time 0.024 (0.036) Data 0.003 (0.002) Loss 0.0343 (0.0355) Prec@1 93.000 (94.128) Prec@5 100.000 (99.851) +2022-11-14 14:40:58,115 Epoch: [236][470/500] Time 0.031 (0.036) Data 0.002 (0.002) Loss 0.0416 (0.0356) Prec@1 94.000 (94.125) Prec@5 100.000 (99.854) +2022-11-14 14:40:58,442 Epoch: [236][480/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.0295 (0.0355) Prec@1 95.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 14:40:58,761 Epoch: [236][490/500] Time 0.029 (0.036) Data 0.002 (0.002) Loss 0.0641 (0.0361) Prec@1 92.000 (94.100) Prec@5 99.000 (99.840) +2022-11-14 14:40:59,053 Epoch: [236][499/500] Time 0.030 (0.036) Data 0.001 (0.002) Loss 0.0457 (0.0362) Prec@1 91.000 (94.039) Prec@5 99.000 (99.824) +2022-11-14 14:40:59,340 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0533 (0.0533) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:59,351 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.0615) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:59,362 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0906 (0.0712) Prec@1 85.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:40:59,377 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0729) Prec@1 86.000 (88.250) Prec@5 100.000 (100.000) +2022-11-14 14:40:59,386 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0733) Prec@1 87.000 (88.000) Prec@5 99.000 (99.800) +2022-11-14 14:40:59,396 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0515 (0.0696) Prec@1 90.000 (88.333) Prec@5 100.000 (99.833) +2022-11-14 14:40:59,406 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0535 (0.0673) Prec@1 93.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 14:40:59,418 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0626 (0.0667) Prec@1 88.000 (88.875) Prec@5 100.000 (99.875) +2022-11-14 14:40:59,429 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0688) Prec@1 87.000 (88.667) Prec@5 99.000 (99.778) +2022-11-14 14:40:59,439 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0696) Prec@1 89.000 (88.700) Prec@5 97.000 (99.500) +2022-11-14 14:40:59,450 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0696) Prec@1 89.000 (88.727) Prec@5 100.000 (99.545) +2022-11-14 14:40:59,461 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0691) Prec@1 91.000 (88.917) Prec@5 99.000 (99.500) +2022-11-14 14:40:59,472 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0291 (0.0660) Prec@1 96.000 (89.462) Prec@5 100.000 (99.538) +2022-11-14 14:40:59,484 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0669) Prec@1 88.000 (89.357) Prec@5 99.000 (99.500) +2022-11-14 14:40:59,493 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0675) Prec@1 86.000 (89.133) Prec@5 100.000 (99.533) +2022-11-14 14:40:59,503 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0669) Prec@1 91.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 14:40:59,512 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0665) Prec@1 90.000 (89.294) Prec@5 99.000 (99.471) +2022-11-14 14:40:59,522 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0683) Prec@1 86.000 (89.111) Prec@5 99.000 (99.444) +2022-11-14 14:40:59,533 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0703) Prec@1 81.000 (88.684) Prec@5 100.000 (99.474) +2022-11-14 14:40:59,543 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0712) Prec@1 86.000 (88.550) Prec@5 99.000 (99.450) +2022-11-14 14:40:59,552 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0709) Prec@1 88.000 (88.524) Prec@5 100.000 (99.476) +2022-11-14 14:40:59,562 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0717) Prec@1 85.000 (88.364) Prec@5 99.000 (99.455) +2022-11-14 14:40:59,572 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1224 (0.0739) Prec@1 80.000 (88.000) Prec@5 99.000 (99.435) +2022-11-14 14:40:59,582 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0739) Prec@1 85.000 (87.875) Prec@5 100.000 (99.458) +2022-11-14 14:40:59,592 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0747) Prec@1 83.000 (87.680) Prec@5 100.000 (99.480) +2022-11-14 14:40:59,603 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0759) Prec@1 83.000 (87.500) Prec@5 98.000 (99.423) +2022-11-14 14:40:59,613 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0750) Prec@1 91.000 (87.630) Prec@5 100.000 (99.444) +2022-11-14 14:40:59,623 Test: [27/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0745) Prec@1 90.000 (87.714) Prec@5 100.000 (99.464) +2022-11-14 14:40:59,632 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0745) Prec@1 88.000 (87.724) Prec@5 100.000 (99.483) +2022-11-14 14:40:59,643 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0743) Prec@1 88.000 (87.733) Prec@5 100.000 (99.500) +2022-11-14 14:40:59,652 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0741) Prec@1 89.000 (87.774) Prec@5 100.000 (99.516) +2022-11-14 14:40:59,663 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0738) Prec@1 91.000 (87.875) Prec@5 98.000 (99.469) +2022-11-14 14:40:59,672 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0745) Prec@1 83.000 (87.727) Prec@5 99.000 (99.455) +2022-11-14 14:40:59,682 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1187 (0.0758) Prec@1 79.000 (87.471) Prec@5 99.000 (99.441) +2022-11-14 14:40:59,690 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0761) Prec@1 84.000 (87.371) Prec@5 98.000 (99.400) +2022-11-14 14:40:59,698 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0757) Prec@1 89.000 (87.417) Prec@5 100.000 (99.417) +2022-11-14 14:40:59,707 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0761) Prec@1 85.000 (87.351) Prec@5 100.000 (99.432) +2022-11-14 14:40:59,716 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0767) Prec@1 83.000 (87.237) Prec@5 99.000 (99.421) +2022-11-14 14:40:59,726 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0766) Prec@1 89.000 (87.282) Prec@5 99.000 (99.410) +2022-11-14 14:40:59,735 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0764) Prec@1 89.000 (87.325) Prec@5 100.000 (99.425) +2022-11-14 14:40:59,744 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0767) Prec@1 84.000 (87.244) Prec@5 100.000 (99.439) +2022-11-14 14:40:59,753 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0766) Prec@1 88.000 (87.262) Prec@5 99.000 (99.429) +2022-11-14 14:40:59,762 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0760) Prec@1 92.000 (87.372) Prec@5 100.000 (99.442) +2022-11-14 14:40:59,772 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0760) Prec@1 90.000 (87.432) Prec@5 99.000 (99.432) +2022-11-14 14:40:59,783 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0760) Prec@1 88.000 (87.444) Prec@5 99.000 (99.422) +2022-11-14 14:40:59,793 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0766) Prec@1 84.000 (87.370) Prec@5 98.000 (99.391) +2022-11-14 14:40:59,804 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0761) Prec@1 92.000 (87.468) Prec@5 98.000 (99.362) +2022-11-14 14:40:59,814 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0766) Prec@1 84.000 (87.396) Prec@5 98.000 (99.333) +2022-11-14 14:40:59,825 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0764) Prec@1 89.000 (87.429) Prec@5 99.000 (99.327) +2022-11-14 14:40:59,835 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0769) Prec@1 84.000 (87.360) Prec@5 99.000 (99.320) +2022-11-14 14:40:59,846 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0769) Prec@1 87.000 (87.353) Prec@5 98.000 (99.294) +2022-11-14 14:40:59,856 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0769) Prec@1 88.000 (87.365) Prec@5 99.000 (99.288) +2022-11-14 14:40:59,864 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0769) Prec@1 87.000 (87.358) Prec@5 100.000 (99.302) +2022-11-14 14:40:59,875 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0772) Prec@1 84.000 (87.296) Prec@5 98.000 (99.278) +2022-11-14 14:40:59,885 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0776) Prec@1 83.000 (87.218) Prec@5 100.000 (99.291) +2022-11-14 14:40:59,894 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0773) Prec@1 89.000 (87.250) Prec@5 99.000 (99.286) +2022-11-14 14:40:59,904 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0773) Prec@1 88.000 (87.263) Prec@5 99.000 (99.281) +2022-11-14 14:40:59,915 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0773) Prec@1 89.000 (87.293) Prec@5 100.000 (99.293) +2022-11-14 14:40:59,925 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1293 (0.0782) Prec@1 80.000 (87.169) Prec@5 100.000 (99.305) +2022-11-14 14:40:59,934 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0785) Prec@1 85.000 (87.133) Prec@5 100.000 (99.317) +2022-11-14 14:40:59,944 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0785) Prec@1 89.000 (87.164) Prec@5 100.000 (99.328) +2022-11-14 14:40:59,954 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0787) Prec@1 83.000 (87.097) Prec@5 100.000 (99.339) +2022-11-14 14:40:59,964 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0785) Prec@1 88.000 (87.111) Prec@5 100.000 (99.349) +2022-11-14 14:40:59,973 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0782) Prec@1 91.000 (87.172) Prec@5 99.000 (99.344) +2022-11-14 14:40:59,983 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0785) Prec@1 85.000 (87.138) Prec@5 99.000 (99.338) +2022-11-14 14:40:59,994 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0787) Prec@1 86.000 (87.121) Prec@5 98.000 (99.318) +2022-11-14 14:41:00,004 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0460 (0.0782) Prec@1 91.000 (87.179) Prec@5 100.000 (99.328) +2022-11-14 14:41:00,015 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0781) Prec@1 89.000 (87.206) Prec@5 99.000 (99.324) +2022-11-14 14:41:00,026 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0782) Prec@1 85.000 (87.174) Prec@5 100.000 (99.333) +2022-11-14 14:41:00,035 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0783) Prec@1 84.000 (87.129) Prec@5 100.000 (99.343) +2022-11-14 14:41:00,045 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0784) Prec@1 86.000 (87.113) Prec@5 100.000 (99.352) +2022-11-14 14:41:00,054 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0783) Prec@1 88.000 (87.125) Prec@5 100.000 (99.361) +2022-11-14 14:41:00,064 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0779) Prec@1 92.000 (87.192) Prec@5 100.000 (99.370) +2022-11-14 14:41:00,075 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0774) Prec@1 92.000 (87.257) Prec@5 99.000 (99.365) +2022-11-14 14:41:00,085 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0776) Prec@1 83.000 (87.200) Prec@5 100.000 (99.373) +2022-11-14 14:41:00,094 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0774) Prec@1 90.000 (87.237) Prec@5 100.000 (99.382) +2022-11-14 14:41:00,103 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0776) Prec@1 86.000 (87.221) Prec@5 98.000 (99.364) +2022-11-14 14:41:00,114 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0778) Prec@1 87.000 (87.218) Prec@5 99.000 (99.359) +2022-11-14 14:41:00,124 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0776) Prec@1 88.000 (87.228) Prec@5 100.000 (99.367) +2022-11-14 14:41:00,134 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0777) Prec@1 86.000 (87.213) Prec@5 100.000 (99.375) +2022-11-14 14:41:00,144 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0780) Prec@1 81.000 (87.136) Prec@5 99.000 (99.370) +2022-11-14 14:41:00,155 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0781) Prec@1 88.000 (87.146) Prec@5 98.000 (99.354) +2022-11-14 14:41:00,166 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0779) Prec@1 90.000 (87.181) Prec@5 99.000 (99.349) +2022-11-14 14:41:00,178 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0778) Prec@1 87.000 (87.179) Prec@5 100.000 (99.357) +2022-11-14 14:41:00,190 Test: [84/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0778) Prec@1 85.000 (87.153) Prec@5 100.000 (99.365) +2022-11-14 14:41:00,202 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0782) Prec@1 82.000 (87.093) Prec@5 98.000 (99.349) +2022-11-14 14:41:00,214 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0781) Prec@1 86.000 (87.080) Prec@5 100.000 (99.356) +2022-11-14 14:41:00,224 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0785) Prec@1 82.000 (87.023) Prec@5 97.000 (99.330) +2022-11-14 14:41:00,236 Test: [88/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0784) Prec@1 87.000 (87.022) Prec@5 99.000 (99.326) +2022-11-14 14:41:00,247 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0785) Prec@1 89.000 (87.044) Prec@5 99.000 (99.322) +2022-11-14 14:41:00,257 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0784) Prec@1 87.000 (87.044) Prec@5 100.000 (99.330) +2022-11-14 14:41:00,266 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0781) Prec@1 92.000 (87.098) Prec@5 98.000 (99.315) +2022-11-14 14:41:00,274 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0783) Prec@1 85.000 (87.075) Prec@5 100.000 (99.323) +2022-11-14 14:41:00,286 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0783) Prec@1 89.000 (87.096) Prec@5 100.000 (99.330) +2022-11-14 14:41:00,297 Test: [94/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0783) Prec@1 87.000 (87.095) Prec@5 99.000 (99.326) +2022-11-14 14:41:00,309 Test: [95/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0783) Prec@1 88.000 (87.104) Prec@5 98.000 (99.312) +2022-11-14 14:41:00,320 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0780) Prec@1 92.000 (87.155) Prec@5 100.000 (99.320) +2022-11-14 14:41:00,330 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0780) Prec@1 85.000 (87.133) Prec@5 97.000 (99.296) +2022-11-14 14:41:00,340 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0783) Prec@1 86.000 (87.121) Prec@5 99.000 (99.293) +2022-11-14 14:41:00,352 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0780) Prec@1 93.000 (87.180) Prec@5 100.000 (99.300) +2022-11-14 14:41:00,412 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:41:00,728 Epoch: [237][0/500] Time 0.022 (0.022) Data 0.236 (0.236) Loss 0.0466 (0.0466) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:00,938 Epoch: [237][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0569 (0.0517) Prec@1 91.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:01,137 Epoch: [237][20/500] Time 0.016 (0.018) Data 0.002 (0.013) Loss 0.0350 (0.0462) Prec@1 93.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 14:41:01,407 Epoch: [237][30/500] Time 0.035 (0.020) Data 0.001 (0.009) Loss 0.0666 (0.0513) Prec@1 89.000 (91.500) Prec@5 99.000 (99.750) +2022-11-14 14:41:01,839 Epoch: [237][40/500] Time 0.040 (0.024) Data 0.002 (0.007) Loss 0.0424 (0.0495) Prec@1 91.000 (91.400) Prec@5 99.000 (99.600) +2022-11-14 14:41:02,274 Epoch: [237][50/500] Time 0.040 (0.027) Data 0.002 (0.006) Loss 0.0463 (0.0490) Prec@1 92.000 (91.500) Prec@5 100.000 (99.667) +2022-11-14 14:41:02,718 Epoch: [237][60/500] Time 0.042 (0.029) Data 0.002 (0.006) Loss 0.0381 (0.0474) Prec@1 92.000 (91.571) Prec@5 100.000 (99.714) +2022-11-14 14:41:03,163 Epoch: [237][70/500] Time 0.041 (0.031) Data 0.002 (0.005) Loss 0.0406 (0.0466) Prec@1 95.000 (92.000) Prec@5 99.000 (99.625) +2022-11-14 14:41:03,601 Epoch: [237][80/500] Time 0.040 (0.032) Data 0.001 (0.005) Loss 0.0248 (0.0441) Prec@1 94.000 (92.222) Prec@5 100.000 (99.667) +2022-11-14 14:41:04,038 Epoch: [237][90/500] Time 0.040 (0.032) Data 0.002 (0.004) Loss 0.0293 (0.0426) Prec@1 95.000 (92.500) Prec@5 99.000 (99.600) +2022-11-14 14:41:04,479 Epoch: [237][100/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.0433 (0.0427) Prec@1 92.000 (92.455) Prec@5 99.000 (99.545) +2022-11-14 14:41:04,926 Epoch: [237][110/500] Time 0.049 (0.034) Data 0.003 (0.004) Loss 0.0282 (0.0415) Prec@1 96.000 (92.750) Prec@5 100.000 (99.583) +2022-11-14 14:41:05,365 Epoch: [237][120/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0547 (0.0425) Prec@1 92.000 (92.692) Prec@5 99.000 (99.538) +2022-11-14 14:41:05,801 Epoch: [237][130/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0239 (0.0412) Prec@1 96.000 (92.929) Prec@5 100.000 (99.571) +2022-11-14 14:41:06,237 Epoch: [237][140/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0239 (0.0400) Prec@1 95.000 (93.067) Prec@5 100.000 (99.600) +2022-11-14 14:41:06,674 Epoch: [237][150/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0335 (0.0396) Prec@1 93.000 (93.062) Prec@5 100.000 (99.625) +2022-11-14 14:41:07,116 Epoch: [237][160/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0248 (0.0387) Prec@1 97.000 (93.294) Prec@5 100.000 (99.647) +2022-11-14 14:41:07,553 Epoch: [237][170/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0445 (0.0391) Prec@1 90.000 (93.111) Prec@5 100.000 (99.667) +2022-11-14 14:41:07,985 Epoch: [237][180/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0560 (0.0400) Prec@1 91.000 (93.000) Prec@5 97.000 (99.526) +2022-11-14 14:41:08,423 Epoch: [237][190/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0416 (0.0400) Prec@1 91.000 (92.900) Prec@5 100.000 (99.550) +2022-11-14 14:41:08,866 Epoch: [237][200/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0308 (0.0396) Prec@1 95.000 (93.000) Prec@5 100.000 (99.571) +2022-11-14 14:41:09,296 Epoch: [237][210/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0489 (0.0400) Prec@1 91.000 (92.909) Prec@5 99.000 (99.545) +2022-11-14 14:41:09,743 Epoch: [237][220/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0395 (0.0400) Prec@1 94.000 (92.957) Prec@5 100.000 (99.565) +2022-11-14 14:41:10,179 Epoch: [237][230/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0459 (0.0402) Prec@1 92.000 (92.917) Prec@5 100.000 (99.583) +2022-11-14 14:41:10,613 Epoch: [237][240/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0365 (0.0401) Prec@1 92.000 (92.880) Prec@5 100.000 (99.600) +2022-11-14 14:41:11,052 Epoch: [237][250/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0274 (0.0396) Prec@1 94.000 (92.923) Prec@5 100.000 (99.615) +2022-11-14 14:41:11,495 Epoch: [237][260/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0392 (0.0396) Prec@1 94.000 (92.963) Prec@5 100.000 (99.630) +2022-11-14 14:41:11,932 Epoch: [237][270/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0423 (0.0397) Prec@1 95.000 (93.036) Prec@5 100.000 (99.643) +2022-11-14 14:41:12,359 Epoch: [237][280/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0295 (0.0393) Prec@1 94.000 (93.069) Prec@5 100.000 (99.655) +2022-11-14 14:41:12,786 Epoch: [237][290/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0307 (0.0390) Prec@1 94.000 (93.100) Prec@5 100.000 (99.667) +2022-11-14 14:41:13,219 Epoch: [237][300/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0320 (0.0388) Prec@1 93.000 (93.097) Prec@5 100.000 (99.677) +2022-11-14 14:41:13,660 Epoch: [237][310/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.0641 (0.0396) Prec@1 86.000 (92.875) Prec@5 99.000 (99.656) +2022-11-14 14:41:14,102 Epoch: [237][320/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0419 (0.0397) Prec@1 92.000 (92.848) Prec@5 100.000 (99.667) +2022-11-14 14:41:14,542 Epoch: [237][330/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0505 (0.0400) Prec@1 90.000 (92.765) Prec@5 99.000 (99.647) +2022-11-14 14:41:14,982 Epoch: [237][340/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0265 (0.0396) Prec@1 95.000 (92.829) Prec@5 100.000 (99.657) +2022-11-14 14:41:15,416 Epoch: [237][350/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0206 (0.0391) Prec@1 96.000 (92.917) Prec@5 100.000 (99.667) +2022-11-14 14:41:15,859 Epoch: [237][360/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0482 (0.0393) Prec@1 93.000 (92.919) Prec@5 100.000 (99.676) +2022-11-14 14:41:16,295 Epoch: [237][370/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0305 (0.0391) Prec@1 95.000 (92.974) Prec@5 100.000 (99.684) +2022-11-14 14:41:16,734 Epoch: [237][380/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0394 (0.0391) Prec@1 94.000 (93.000) Prec@5 100.000 (99.692) +2022-11-14 14:41:17,172 Epoch: [237][390/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0371 (0.0391) Prec@1 93.000 (93.000) Prec@5 100.000 (99.700) +2022-11-14 14:41:17,608 Epoch: [237][400/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0323 (0.0389) Prec@1 94.000 (93.024) Prec@5 100.000 (99.707) +2022-11-14 14:41:18,049 Epoch: [237][410/500] Time 0.040 (0.037) Data 0.002 (0.002) Loss 0.0502 (0.0392) Prec@1 90.000 (92.952) Prec@5 100.000 (99.714) +2022-11-14 14:41:18,481 Epoch: [237][420/500] Time 0.037 (0.037) Data 0.002 (0.002) Loss 0.0197 (0.0387) Prec@1 97.000 (93.047) Prec@5 100.000 (99.721) +2022-11-14 14:41:18,915 Epoch: [237][430/500] Time 0.052 (0.038) Data 0.002 (0.002) Loss 0.0302 (0.0385) Prec@1 94.000 (93.068) Prec@5 100.000 (99.727) +2022-11-14 14:41:19,348 Epoch: [237][440/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0284 (0.0383) Prec@1 95.000 (93.111) Prec@5 99.000 (99.711) +2022-11-14 14:41:19,782 Epoch: [237][450/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0376 (0.0383) Prec@1 95.000 (93.152) Prec@5 100.000 (99.717) +2022-11-14 14:41:20,221 Epoch: [237][460/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.0483 (0.0385) Prec@1 92.000 (93.128) Prec@5 100.000 (99.723) +2022-11-14 14:41:20,660 Epoch: [237][470/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0259 (0.0382) Prec@1 97.000 (93.208) Prec@5 100.000 (99.729) +2022-11-14 14:41:21,095 Epoch: [237][480/500] Time 0.040 (0.038) Data 0.001 (0.002) Loss 0.0397 (0.0383) Prec@1 91.000 (93.163) Prec@5 100.000 (99.735) +2022-11-14 14:41:21,525 Epoch: [237][490/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0318 (0.0381) Prec@1 95.000 (93.200) Prec@5 100.000 (99.740) +2022-11-14 14:41:21,910 Epoch: [237][499/500] Time 0.049 (0.038) Data 0.002 (0.002) Loss 0.0232 (0.0378) Prec@1 97.000 (93.275) Prec@5 100.000 (99.745) +2022-11-14 14:41:22,178 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0590 (0.0590) Prec@1 89.000 (89.000) Prec@5 98.000 (98.000) +2022-11-14 14:41:22,186 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0584) Prec@1 93.000 (91.000) Prec@5 100.000 (99.000) +2022-11-14 14:41:22,194 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0634) Prec@1 88.000 (90.000) Prec@5 100.000 (99.333) +2022-11-14 14:41:22,208 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0644) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 14:41:22,215 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0699) Prec@1 87.000 (89.400) Prec@5 100.000 (99.600) +2022-11-14 14:41:22,224 Test: [5/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0671) Prec@1 92.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 14:41:22,235 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0639) Prec@1 93.000 (90.286) Prec@5 99.000 (99.571) +2022-11-14 14:41:22,245 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0648) Prec@1 84.000 (89.500) Prec@5 100.000 (99.625) +2022-11-14 14:41:22,254 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0669) Prec@1 86.000 (89.111) Prec@5 100.000 (99.667) +2022-11-14 14:41:22,265 Test: [9/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0670) Prec@1 89.000 (89.100) Prec@5 99.000 (99.600) +2022-11-14 14:41:22,277 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0387 (0.0644) Prec@1 94.000 (89.545) Prec@5 99.000 (99.545) +2022-11-14 14:41:22,287 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0670) Prec@1 83.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:41:22,298 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0654) Prec@1 92.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 14:41:22,310 Test: [13/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0666) Prec@1 90.000 (89.286) Prec@5 98.000 (99.429) +2022-11-14 14:41:22,321 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0669) Prec@1 89.000 (89.267) Prec@5 100.000 (99.467) +2022-11-14 14:41:22,332 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0668) Prec@1 90.000 (89.312) Prec@5 100.000 (99.500) +2022-11-14 14:41:22,343 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0668) Prec@1 87.000 (89.176) Prec@5 99.000 (99.471) +2022-11-14 14:41:22,355 Test: [17/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1205 (0.0698) Prec@1 80.000 (88.667) Prec@5 99.000 (99.444) +2022-11-14 14:41:22,366 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0699) Prec@1 89.000 (88.684) Prec@5 100.000 (99.474) +2022-11-14 14:41:22,376 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0713) Prec@1 86.000 (88.550) Prec@5 98.000 (99.400) +2022-11-14 14:41:22,386 Test: [20/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0713) Prec@1 87.000 (88.476) Prec@5 100.000 (99.429) +2022-11-14 14:41:22,398 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0719) Prec@1 89.000 (88.500) Prec@5 99.000 (99.409) +2022-11-14 14:41:22,409 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0725) Prec@1 88.000 (88.478) Prec@5 98.000 (99.348) +2022-11-14 14:41:22,419 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0727) Prec@1 87.000 (88.417) Prec@5 99.000 (99.333) +2022-11-14 14:41:22,430 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0737) Prec@1 83.000 (88.200) Prec@5 100.000 (99.360) +2022-11-14 14:41:22,442 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0744) Prec@1 86.000 (88.115) Prec@5 98.000 (99.308) +2022-11-14 14:41:22,454 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0740) Prec@1 87.000 (88.074) Prec@5 99.000 (99.296) +2022-11-14 14:41:22,464 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0738) Prec@1 88.000 (88.071) Prec@5 99.000 (99.286) +2022-11-14 14:41:22,474 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0735) Prec@1 89.000 (88.103) Prec@5 98.000 (99.241) +2022-11-14 14:41:22,487 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0732) Prec@1 89.000 (88.133) Prec@5 99.000 (99.233) +2022-11-14 14:41:22,499 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0728) Prec@1 88.000 (88.129) Prec@5 100.000 (99.258) +2022-11-14 14:41:22,509 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0726) Prec@1 89.000 (88.156) Prec@5 100.000 (99.281) +2022-11-14 14:41:22,518 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0732) Prec@1 83.000 (88.000) Prec@5 99.000 (99.273) +2022-11-14 14:41:22,529 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0736) Prec@1 87.000 (87.971) Prec@5 98.000 (99.235) +2022-11-14 14:41:22,540 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0741) Prec@1 85.000 (87.886) Prec@5 99.000 (99.229) +2022-11-14 14:41:22,550 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0738) Prec@1 90.000 (87.944) Prec@5 100.000 (99.250) +2022-11-14 14:41:22,559 Test: [36/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0740) Prec@1 86.000 (87.892) Prec@5 98.000 (99.216) +2022-11-14 14:41:22,569 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.0750) Prec@1 80.000 (87.684) Prec@5 100.000 (99.237) +2022-11-14 14:41:22,579 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0748) Prec@1 90.000 (87.744) Prec@5 98.000 (99.205) +2022-11-14 14:41:22,588 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0748) Prec@1 88.000 (87.750) Prec@5 98.000 (99.175) +2022-11-14 14:41:22,599 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0751) Prec@1 87.000 (87.732) Prec@5 99.000 (99.171) +2022-11-14 14:41:22,611 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0749) Prec@1 89.000 (87.762) Prec@5 99.000 (99.167) +2022-11-14 14:41:22,622 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0744) Prec@1 92.000 (87.860) Prec@5 98.000 (99.140) +2022-11-14 14:41:22,631 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0744) Prec@1 89.000 (87.886) Prec@5 98.000 (99.114) +2022-11-14 14:41:22,642 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0743) Prec@1 87.000 (87.867) Prec@5 98.000 (99.089) +2022-11-14 14:41:22,651 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0744) Prec@1 87.000 (87.848) Prec@5 100.000 (99.109) +2022-11-14 14:41:22,661 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0743) Prec@1 88.000 (87.851) Prec@5 99.000 (99.106) +2022-11-14 14:41:22,670 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1151 (0.0752) Prec@1 84.000 (87.771) Prec@5 96.000 (99.042) +2022-11-14 14:41:22,680 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0751) Prec@1 88.000 (87.776) Prec@5 100.000 (99.061) +2022-11-14 14:41:22,691 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.0759) Prec@1 81.000 (87.640) Prec@5 100.000 (99.080) +2022-11-14 14:41:22,699 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0758) Prec@1 89.000 (87.667) Prec@5 99.000 (99.078) +2022-11-14 14:41:22,711 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0761) Prec@1 82.000 (87.558) Prec@5 100.000 (99.096) +2022-11-14 14:41:22,719 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0765) Prec@1 83.000 (87.472) Prec@5 100.000 (99.113) +2022-11-14 14:41:22,728 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0764) Prec@1 89.000 (87.500) Prec@5 98.000 (99.093) +2022-11-14 14:41:22,739 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0766) Prec@1 86.000 (87.473) Prec@5 100.000 (99.109) +2022-11-14 14:41:22,748 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0764) Prec@1 91.000 (87.536) Prec@5 100.000 (99.125) +2022-11-14 14:41:22,758 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0765) Prec@1 85.000 (87.491) Prec@5 99.000 (99.123) +2022-11-14 14:41:22,767 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0766) Prec@1 88.000 (87.500) Prec@5 100.000 (99.138) +2022-11-14 14:41:22,777 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0771) Prec@1 80.000 (87.373) Prec@5 99.000 (99.136) +2022-11-14 14:41:22,789 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0772) Prec@1 84.000 (87.317) Prec@5 100.000 (99.150) +2022-11-14 14:41:22,798 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0774) Prec@1 86.000 (87.295) Prec@5 100.000 (99.164) +2022-11-14 14:41:22,809 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0774) Prec@1 86.000 (87.274) Prec@5 100.000 (99.177) +2022-11-14 14:41:22,818 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0773) Prec@1 88.000 (87.286) Prec@5 99.000 (99.175) +2022-11-14 14:41:22,829 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0768) Prec@1 94.000 (87.391) Prec@5 100.000 (99.188) +2022-11-14 14:41:22,839 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0768) Prec@1 89.000 (87.415) Prec@5 100.000 (99.200) +2022-11-14 14:41:22,849 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0771) Prec@1 84.000 (87.364) Prec@5 99.000 (99.197) +2022-11-14 14:41:22,858 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0766) Prec@1 92.000 (87.433) Prec@5 100.000 (99.209) +2022-11-14 14:41:22,868 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0765) Prec@1 89.000 (87.456) Prec@5 99.000 (99.206) +2022-11-14 14:41:22,879 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0762) Prec@1 89.000 (87.478) Prec@5 99.000 (99.203) +2022-11-14 14:41:22,889 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0764) Prec@1 85.000 (87.443) Prec@5 100.000 (99.214) +2022-11-14 14:41:22,900 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0769) Prec@1 83.000 (87.380) Prec@5 98.000 (99.197) +2022-11-14 14:41:22,911 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0770) Prec@1 87.000 (87.375) Prec@5 100.000 (99.208) +2022-11-14 14:41:22,922 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0506 (0.0766) Prec@1 92.000 (87.438) Prec@5 100.000 (99.219) +2022-11-14 14:41:22,933 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0763) Prec@1 93.000 (87.514) Prec@5 100.000 (99.230) +2022-11-14 14:41:22,943 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0767) Prec@1 80.000 (87.413) Prec@5 99.000 (99.227) +2022-11-14 14:41:22,953 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0768) Prec@1 86.000 (87.395) Prec@5 99.000 (99.224) +2022-11-14 14:41:22,963 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0767) Prec@1 88.000 (87.403) Prec@5 99.000 (99.221) +2022-11-14 14:41:22,974 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0771) Prec@1 82.000 (87.333) Prec@5 99.000 (99.218) +2022-11-14 14:41:22,984 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0773) Prec@1 83.000 (87.278) Prec@5 98.000 (99.203) +2022-11-14 14:41:22,995 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0773) Prec@1 87.000 (87.275) Prec@5 99.000 (99.200) +2022-11-14 14:41:23,005 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0773) Prec@1 88.000 (87.284) Prec@5 98.000 (99.185) +2022-11-14 14:41:23,015 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0772) Prec@1 87.000 (87.280) Prec@5 99.000 (99.183) +2022-11-14 14:41:23,026 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0776) Prec@1 80.000 (87.193) Prec@5 99.000 (99.181) +2022-11-14 14:41:23,037 Test: [83/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0775) Prec@1 88.000 (87.202) Prec@5 99.000 (99.179) +2022-11-14 14:41:23,047 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0775) Prec@1 87.000 (87.200) Prec@5 100.000 (99.188) +2022-11-14 14:41:23,057 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0779) Prec@1 83.000 (87.151) Prec@5 100.000 (99.198) +2022-11-14 14:41:23,066 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0780) Prec@1 84.000 (87.115) Prec@5 99.000 (99.195) +2022-11-14 14:41:23,075 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0782) Prec@1 85.000 (87.091) Prec@5 97.000 (99.170) +2022-11-14 14:41:23,085 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0781) Prec@1 85.000 (87.067) Prec@5 100.000 (99.180) +2022-11-14 14:41:23,095 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0781) Prec@1 88.000 (87.078) Prec@5 98.000 (99.167) +2022-11-14 14:41:23,105 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0777) Prec@1 93.000 (87.143) Prec@5 100.000 (99.176) +2022-11-14 14:41:23,116 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0774) Prec@1 93.000 (87.207) Prec@5 100.000 (99.185) +2022-11-14 14:41:23,126 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0776) Prec@1 85.000 (87.183) Prec@5 100.000 (99.194) +2022-11-14 14:41:23,137 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0775) Prec@1 90.000 (87.213) Prec@5 100.000 (99.202) +2022-11-14 14:41:23,150 Test: [94/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0774) Prec@1 89.000 (87.232) Prec@5 99.000 (99.200) +2022-11-14 14:41:23,160 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0773) Prec@1 89.000 (87.250) Prec@5 99.000 (99.198) +2022-11-14 14:41:23,171 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0769) Prec@1 93.000 (87.309) Prec@5 99.000 (99.196) +2022-11-14 14:41:23,181 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0770) Prec@1 87.000 (87.306) Prec@5 99.000 (99.194) +2022-11-14 14:41:23,191 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0773) Prec@1 83.000 (87.263) Prec@5 99.000 (99.192) +2022-11-14 14:41:23,200 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0772) Prec@1 89.000 (87.280) Prec@5 99.000 (99.190) +2022-11-14 14:41:23,257 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:41:23,567 Epoch: [238][0/500] Time 0.024 (0.024) Data 0.226 (0.226) Loss 0.0341 (0.0341) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:23,780 Epoch: [238][10/500] Time 0.017 (0.019) Data 0.001 (0.022) Loss 0.0421 (0.0381) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:41:23,982 Epoch: [238][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0521 (0.0428) Prec@1 93.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:41:24,206 Epoch: [238][30/500] Time 0.024 (0.019) Data 0.002 (0.009) Loss 0.0260 (0.0386) Prec@1 96.000 (94.000) Prec@5 99.000 (99.750) +2022-11-14 14:41:24,472 Epoch: [238][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.0441 (0.0397) Prec@1 90.000 (93.200) Prec@5 100.000 (99.800) +2022-11-14 14:41:24,737 Epoch: [238][50/500] Time 0.024 (0.021) Data 0.001 (0.006) Loss 0.0321 (0.0384) Prec@1 95.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 14:41:25,004 Epoch: [238][60/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0423 (0.0390) Prec@1 95.000 (93.714) Prec@5 100.000 (99.857) +2022-11-14 14:41:25,271 Epoch: [238][70/500] Time 0.026 (0.021) Data 0.001 (0.005) Loss 0.0258 (0.0373) Prec@1 94.000 (93.750) Prec@5 100.000 (99.875) +2022-11-14 14:41:25,538 Epoch: [238][80/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0583 (0.0397) Prec@1 91.000 (93.444) Prec@5 100.000 (99.889) +2022-11-14 14:41:25,850 Epoch: [238][90/500] Time 0.037 (0.022) Data 0.002 (0.004) Loss 0.0473 (0.0404) Prec@1 92.000 (93.300) Prec@5 100.000 (99.900) +2022-11-14 14:41:26,299 Epoch: [238][100/500] Time 0.042 (0.024) Data 0.002 (0.004) Loss 0.0187 (0.0385) Prec@1 98.000 (93.727) Prec@5 100.000 (99.909) +2022-11-14 14:41:26,750 Epoch: [238][110/500] Time 0.042 (0.025) Data 0.002 (0.004) Loss 0.0416 (0.0387) Prec@1 93.000 (93.667) Prec@5 99.000 (99.833) +2022-11-14 14:41:27,203 Epoch: [238][120/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0471 (0.0394) Prec@1 92.000 (93.538) Prec@5 99.000 (99.769) +2022-11-14 14:41:27,657 Epoch: [238][130/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0391 (0.0393) Prec@1 93.000 (93.500) Prec@5 100.000 (99.786) +2022-11-14 14:41:28,093 Epoch: [238][140/500] Time 0.040 (0.029) Data 0.002 (0.003) Loss 0.0335 (0.0390) Prec@1 95.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:41:28,548 Epoch: [238][150/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0349 (0.0387) Prec@1 93.000 (93.562) Prec@5 100.000 (99.812) +2022-11-14 14:41:29,003 Epoch: [238][160/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0465 (0.0392) Prec@1 93.000 (93.529) Prec@5 98.000 (99.706) +2022-11-14 14:41:29,461 Epoch: [238][170/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0397 (0.0392) Prec@1 92.000 (93.444) Prec@5 100.000 (99.722) +2022-11-14 14:41:29,915 Epoch: [238][180/500] Time 0.050 (0.031) Data 0.002 (0.003) Loss 0.0378 (0.0391) Prec@1 94.000 (93.474) Prec@5 100.000 (99.737) +2022-11-14 14:41:30,365 Epoch: [238][190/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0252 (0.0384) Prec@1 96.000 (93.600) Prec@5 100.000 (99.750) +2022-11-14 14:41:30,811 Epoch: [238][200/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0308 (0.0381) Prec@1 94.000 (93.619) Prec@5 100.000 (99.762) +2022-11-14 14:41:31,255 Epoch: [238][210/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0495 (0.0386) Prec@1 92.000 (93.545) Prec@5 99.000 (99.727) +2022-11-14 14:41:31,707 Epoch: [238][220/500] Time 0.042 (0.033) Data 0.003 (0.003) Loss 0.0358 (0.0385) Prec@1 94.000 (93.565) Prec@5 100.000 (99.739) +2022-11-14 14:41:32,151 Epoch: [238][230/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0431 (0.0387) Prec@1 95.000 (93.625) Prec@5 100.000 (99.750) +2022-11-14 14:41:32,596 Epoch: [238][240/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0693 (0.0399) Prec@1 88.000 (93.400) Prec@5 99.000 (99.720) +2022-11-14 14:41:33,041 Epoch: [238][250/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0518 (0.0403) Prec@1 93.000 (93.385) Prec@5 100.000 (99.731) +2022-11-14 14:41:33,489 Epoch: [238][260/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0207 (0.0396) Prec@1 97.000 (93.519) Prec@5 100.000 (99.741) +2022-11-14 14:41:33,938 Epoch: [238][270/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0383 (0.0396) Prec@1 94.000 (93.536) Prec@5 100.000 (99.750) +2022-11-14 14:41:34,380 Epoch: [238][280/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0485 (0.0399) Prec@1 93.000 (93.517) Prec@5 100.000 (99.759) +2022-11-14 14:41:34,813 Epoch: [238][290/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0530 (0.0403) Prec@1 90.000 (93.400) Prec@5 99.000 (99.733) +2022-11-14 14:41:35,252 Epoch: [238][300/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0490 (0.0406) Prec@1 92.000 (93.355) Prec@5 100.000 (99.742) +2022-11-14 14:41:35,700 Epoch: [238][310/500] Time 0.042 (0.035) Data 0.001 (0.003) Loss 0.0439 (0.0407) Prec@1 95.000 (93.406) Prec@5 100.000 (99.750) +2022-11-14 14:41:36,145 Epoch: [238][320/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0327 (0.0405) Prec@1 95.000 (93.455) Prec@5 100.000 (99.758) +2022-11-14 14:41:36,589 Epoch: [238][330/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0540 (0.0409) Prec@1 91.000 (93.382) Prec@5 100.000 (99.765) +2022-11-14 14:41:37,035 Epoch: [238][340/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0266 (0.0404) Prec@1 96.000 (93.457) Prec@5 100.000 (99.771) +2022-11-14 14:41:37,476 Epoch: [238][350/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0341 (0.0403) Prec@1 95.000 (93.500) Prec@5 99.000 (99.750) +2022-11-14 14:41:37,902 Epoch: [238][360/500] Time 0.047 (0.035) Data 0.002 (0.003) Loss 0.0443 (0.0404) Prec@1 91.000 (93.432) Prec@5 100.000 (99.757) +2022-11-14 14:41:38,328 Epoch: [238][370/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0240 (0.0399) Prec@1 96.000 (93.500) Prec@5 100.000 (99.763) +2022-11-14 14:41:38,776 Epoch: [238][380/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.0336 (0.0398) Prec@1 95.000 (93.538) Prec@5 100.000 (99.769) +2022-11-14 14:41:39,211 Epoch: [238][390/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0485 (0.0400) Prec@1 89.000 (93.425) Prec@5 100.000 (99.775) +2022-11-14 14:41:39,653 Epoch: [238][400/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0578 (0.0404) Prec@1 90.000 (93.341) Prec@5 99.000 (99.756) +2022-11-14 14:41:40,090 Epoch: [238][410/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0361 (0.0403) Prec@1 93.000 (93.333) Prec@5 99.000 (99.738) +2022-11-14 14:41:40,533 Epoch: [238][420/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0467 (0.0405) Prec@1 92.000 (93.302) Prec@5 100.000 (99.744) +2022-11-14 14:41:40,979 Epoch: [238][430/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0410 (0.0405) Prec@1 90.000 (93.227) Prec@5 100.000 (99.750) +2022-11-14 14:41:41,412 Epoch: [238][440/500] Time 0.046 (0.036) Data 0.002 (0.002) Loss 0.0484 (0.0407) Prec@1 90.000 (93.156) Prec@5 98.000 (99.711) +2022-11-14 14:41:41,728 Epoch: [238][450/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.0558 (0.0410) Prec@1 89.000 (93.065) Prec@5 100.000 (99.717) +2022-11-14 14:41:42,006 Epoch: [238][460/500] Time 0.025 (0.036) Data 0.002 (0.002) Loss 0.0442 (0.0411) Prec@1 91.000 (93.021) Prec@5 100.000 (99.723) +2022-11-14 14:41:42,277 Epoch: [238][470/500] Time 0.024 (0.035) Data 0.002 (0.002) Loss 0.0333 (0.0409) Prec@1 96.000 (93.083) Prec@5 99.000 (99.708) +2022-11-14 14:41:42,548 Epoch: [238][480/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0377 (0.0408) Prec@1 94.000 (93.102) Prec@5 99.000 (99.694) +2022-11-14 14:41:42,821 Epoch: [238][490/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0288 (0.0406) Prec@1 95.000 (93.140) Prec@5 100.000 (99.700) +2022-11-14 14:41:43,071 Epoch: [238][499/500] Time 0.025 (0.035) Data 0.001 (0.002) Loss 0.0640 (0.0411) Prec@1 89.000 (93.059) Prec@5 100.000 (99.706) +2022-11-14 14:41:43,351 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0578 (0.0578) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:43,359 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0654) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:41:43,369 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0844 (0.0717) Prec@1 89.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 14:41:43,383 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0964 (0.0779) Prec@1 86.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 14:41:43,392 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0800) Prec@1 84.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 14:41:43,402 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0748) Prec@1 93.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 14:41:43,412 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0728) Prec@1 91.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 14:41:43,422 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0748) Prec@1 84.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 14:41:43,430 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.0784) Prec@1 84.000 (87.778) Prec@5 98.000 (99.556) +2022-11-14 14:41:43,437 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0780) Prec@1 87.000 (87.700) Prec@5 99.000 (99.500) +2022-11-14 14:41:43,446 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0772) Prec@1 89.000 (87.818) Prec@5 99.000 (99.455) +2022-11-14 14:41:43,457 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0765) Prec@1 89.000 (87.917) Prec@5 100.000 (99.500) +2022-11-14 14:41:43,467 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0757) Prec@1 88.000 (87.923) Prec@5 99.000 (99.462) +2022-11-14 14:41:43,478 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0751) Prec@1 90.000 (88.071) Prec@5 100.000 (99.500) +2022-11-14 14:41:43,486 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0756) Prec@1 88.000 (88.067) Prec@5 99.000 (99.467) +2022-11-14 14:41:43,496 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0768) Prec@1 82.000 (87.688) Prec@5 99.000 (99.438) +2022-11-14 14:41:43,507 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0761) Prec@1 89.000 (87.765) Prec@5 99.000 (99.412) +2022-11-14 14:41:43,520 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0777) Prec@1 85.000 (87.611) Prec@5 100.000 (99.444) +2022-11-14 14:41:43,530 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0785) Prec@1 85.000 (87.474) Prec@5 98.000 (99.368) +2022-11-14 14:41:43,542 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0785) Prec@1 87.000 (87.450) Prec@5 98.000 (99.300) +2022-11-14 14:41:43,553 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0799) Prec@1 80.000 (87.095) Prec@5 100.000 (99.333) +2022-11-14 14:41:43,563 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0804) Prec@1 85.000 (87.000) Prec@5 99.000 (99.318) +2022-11-14 14:41:43,574 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0809) Prec@1 86.000 (86.957) Prec@5 98.000 (99.261) +2022-11-14 14:41:43,585 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0803) Prec@1 90.000 (87.083) Prec@5 100.000 (99.292) +2022-11-14 14:41:43,593 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0804) Prec@1 89.000 (87.160) Prec@5 99.000 (99.280) +2022-11-14 14:41:43,603 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0812) Prec@1 84.000 (87.038) Prec@5 99.000 (99.269) +2022-11-14 14:41:43,613 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0803) Prec@1 91.000 (87.185) Prec@5 100.000 (99.296) +2022-11-14 14:41:43,623 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0799) Prec@1 90.000 (87.286) Prec@5 100.000 (99.321) +2022-11-14 14:41:43,634 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0801) Prec@1 84.000 (87.172) Prec@5 99.000 (99.310) +2022-11-14 14:41:43,643 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0797) Prec@1 88.000 (87.200) Prec@5 100.000 (99.333) +2022-11-14 14:41:43,652 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0791) Prec@1 91.000 (87.323) Prec@5 100.000 (99.355) +2022-11-14 14:41:43,662 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0797) Prec@1 84.000 (87.219) Prec@5 99.000 (99.344) +2022-11-14 14:41:43,673 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0803) Prec@1 83.000 (87.091) Prec@5 100.000 (99.364) +2022-11-14 14:41:43,683 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0807) Prec@1 84.000 (87.000) Prec@5 99.000 (99.353) +2022-11-14 14:41:43,692 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0808) Prec@1 86.000 (86.971) Prec@5 99.000 (99.343) +2022-11-14 14:41:43,703 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0806) Prec@1 89.000 (87.028) Prec@5 98.000 (99.306) +2022-11-14 14:41:43,713 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0805) Prec@1 87.000 (87.027) Prec@5 98.000 (99.270) +2022-11-14 14:41:43,723 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0810) Prec@1 83.000 (86.921) Prec@5 100.000 (99.289) +2022-11-14 14:41:43,734 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0803) Prec@1 93.000 (87.077) Prec@5 99.000 (99.282) +2022-11-14 14:41:43,745 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0799) Prec@1 87.000 (87.075) Prec@5 99.000 (99.275) +2022-11-14 14:41:43,754 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0799) Prec@1 84.000 (87.000) Prec@5 99.000 (99.268) +2022-11-14 14:41:43,765 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0797) Prec@1 87.000 (87.000) Prec@5 100.000 (99.286) +2022-11-14 14:41:43,776 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0791) Prec@1 92.000 (87.116) Prec@5 100.000 (99.302) +2022-11-14 14:41:43,786 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0789) Prec@1 90.000 (87.182) Prec@5 97.000 (99.250) +2022-11-14 14:41:43,797 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0785) Prec@1 92.000 (87.289) Prec@5 99.000 (99.244) +2022-11-14 14:41:43,807 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0792) Prec@1 80.000 (87.130) Prec@5 98.000 (99.217) +2022-11-14 14:41:43,816 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0791) Prec@1 88.000 (87.149) Prec@5 100.000 (99.234) +2022-11-14 14:41:43,826 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1216 (0.0799) Prec@1 79.000 (86.979) Prec@5 99.000 (99.229) +2022-11-14 14:41:43,836 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0796) Prec@1 90.000 (87.041) Prec@5 99.000 (99.224) +2022-11-14 14:41:43,846 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0802) Prec@1 83.000 (86.960) Prec@5 99.000 (99.220) +2022-11-14 14:41:43,856 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0797) Prec@1 88.000 (86.980) Prec@5 99.000 (99.216) +2022-11-14 14:41:43,866 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0796) Prec@1 89.000 (87.019) Prec@5 100.000 (99.231) +2022-11-14 14:41:43,876 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0792) Prec@1 92.000 (87.113) Prec@5 99.000 (99.226) +2022-11-14 14:41:43,885 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0792) Prec@1 84.000 (87.056) Prec@5 99.000 (99.222) +2022-11-14 14:41:43,894 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0795) Prec@1 84.000 (87.000) Prec@5 99.000 (99.218) +2022-11-14 14:41:43,904 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0795) Prec@1 89.000 (87.036) Prec@5 98.000 (99.196) +2022-11-14 14:41:43,914 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0794) Prec@1 90.000 (87.088) Prec@5 100.000 (99.211) +2022-11-14 14:41:43,925 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0793) Prec@1 88.000 (87.103) Prec@5 100.000 (99.224) +2022-11-14 14:41:43,936 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0798) Prec@1 84.000 (87.051) Prec@5 100.000 (99.237) +2022-11-14 14:41:43,947 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0797) Prec@1 88.000 (87.067) Prec@5 100.000 (99.250) +2022-11-14 14:41:43,956 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0798) Prec@1 86.000 (87.049) Prec@5 97.000 (99.213) +2022-11-14 14:41:43,967 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0794) Prec@1 91.000 (87.113) Prec@5 100.000 (99.226) +2022-11-14 14:41:43,977 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0790) Prec@1 91.000 (87.175) Prec@5 100.000 (99.238) +2022-11-14 14:41:43,988 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0784) Prec@1 92.000 (87.250) Prec@5 100.000 (99.250) +2022-11-14 14:41:43,997 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0786) Prec@1 84.000 (87.200) Prec@5 100.000 (99.262) +2022-11-14 14:41:44,007 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0789) Prec@1 82.000 (87.121) Prec@5 99.000 (99.258) +2022-11-14 14:41:44,019 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0784) Prec@1 94.000 (87.224) Prec@5 100.000 (99.269) +2022-11-14 14:41:44,029 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0784) Prec@1 89.000 (87.250) Prec@5 98.000 (99.250) +2022-11-14 14:41:44,039 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0782) Prec@1 92.000 (87.319) Prec@5 99.000 (99.246) +2022-11-14 14:41:44,050 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0784) Prec@1 87.000 (87.314) Prec@5 99.000 (99.243) +2022-11-14 14:41:44,061 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0786) Prec@1 86.000 (87.296) Prec@5 98.000 (99.225) +2022-11-14 14:41:44,071 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0786) Prec@1 88.000 (87.306) Prec@5 100.000 (99.236) +2022-11-14 14:41:44,080 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0472 (0.0782) Prec@1 93.000 (87.384) Prec@5 100.000 (99.247) +2022-11-14 14:41:44,090 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0336 (0.0776) Prec@1 94.000 (87.473) Prec@5 100.000 (99.257) +2022-11-14 14:41:44,102 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0779) Prec@1 84.000 (87.427) Prec@5 100.000 (99.267) +2022-11-14 14:41:44,112 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0776) Prec@1 90.000 (87.461) Prec@5 99.000 (99.263) +2022-11-14 14:41:44,122 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0777) Prec@1 87.000 (87.455) Prec@5 100.000 (99.273) +2022-11-14 14:41:44,132 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0781) Prec@1 82.000 (87.385) Prec@5 98.000 (99.256) +2022-11-14 14:41:44,143 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0784) Prec@1 85.000 (87.354) Prec@5 100.000 (99.266) +2022-11-14 14:41:44,155 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0783) Prec@1 87.000 (87.350) Prec@5 100.000 (99.275) +2022-11-14 14:41:44,165 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0782) Prec@1 88.000 (87.358) Prec@5 100.000 (99.284) +2022-11-14 14:41:44,175 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0781) Prec@1 89.000 (87.378) Prec@5 100.000 (99.293) +2022-11-14 14:41:44,185 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0782) Prec@1 85.000 (87.349) Prec@5 100.000 (99.301) +2022-11-14 14:41:44,197 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0782) Prec@1 83.000 (87.298) Prec@5 99.000 (99.298) +2022-11-14 14:41:44,207 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0783) Prec@1 86.000 (87.282) Prec@5 98.000 (99.282) +2022-11-14 14:41:44,217 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0784) Prec@1 88.000 (87.291) Prec@5 99.000 (99.279) +2022-11-14 14:41:44,227 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0785) Prec@1 85.000 (87.264) Prec@5 100.000 (99.287) +2022-11-14 14:41:44,238 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0786) Prec@1 87.000 (87.261) Prec@5 98.000 (99.273) +2022-11-14 14:41:44,246 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0785) Prec@1 89.000 (87.281) Prec@5 99.000 (99.270) +2022-11-14 14:41:44,256 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0782) Prec@1 90.000 (87.311) Prec@5 98.000 (99.256) +2022-11-14 14:41:44,265 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0447 (0.0779) Prec@1 94.000 (87.385) Prec@5 100.000 (99.264) +2022-11-14 14:41:44,274 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0777) Prec@1 90.000 (87.413) Prec@5 98.000 (99.250) +2022-11-14 14:41:44,284 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0778) Prec@1 86.000 (87.398) Prec@5 100.000 (99.258) +2022-11-14 14:41:44,294 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0779) Prec@1 89.000 (87.415) Prec@5 100.000 (99.266) +2022-11-14 14:41:44,303 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0780) Prec@1 80.000 (87.337) Prec@5 100.000 (99.274) +2022-11-14 14:41:44,313 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0780) Prec@1 89.000 (87.354) Prec@5 100.000 (99.281) +2022-11-14 14:41:44,326 Test: [96/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0778) Prec@1 91.000 (87.392) Prec@5 99.000 (99.278) +2022-11-14 14:41:44,337 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0778) Prec@1 88.000 (87.398) Prec@5 100.000 (99.286) +2022-11-14 14:41:44,348 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0780) Prec@1 83.000 (87.354) Prec@5 99.000 (99.283) +2022-11-14 14:41:44,359 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0781) Prec@1 87.000 (87.350) Prec@5 98.000 (99.270) +2022-11-14 14:41:44,422 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:41:44,730 Epoch: [239][0/500] Time 0.023 (0.023) Data 0.226 (0.226) Loss 0.0510 (0.0510) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:44,937 Epoch: [239][10/500] Time 0.017 (0.019) Data 0.001 (0.022) Loss 0.0470 (0.0490) Prec@1 94.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:41:45,136 Epoch: [239][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0404 (0.0461) Prec@1 94.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 14:41:45,399 Epoch: [239][30/500] Time 0.025 (0.020) Data 0.002 (0.009) Loss 0.0568 (0.0488) Prec@1 92.000 (93.000) Prec@5 98.000 (99.250) +2022-11-14 14:41:45,685 Epoch: [239][40/500] Time 0.027 (0.021) Data 0.002 (0.007) Loss 0.0459 (0.0482) Prec@1 95.000 (93.400) Prec@5 100.000 (99.400) +2022-11-14 14:41:45,985 Epoch: [239][50/500] Time 0.028 (0.022) Data 0.001 (0.006) Loss 0.0422 (0.0472) Prec@1 93.000 (93.333) Prec@5 100.000 (99.500) +2022-11-14 14:41:46,278 Epoch: [239][60/500] Time 0.027 (0.023) Data 0.001 (0.005) Loss 0.0310 (0.0449) Prec@1 95.000 (93.571) Prec@5 99.000 (99.429) +2022-11-14 14:41:46,568 Epoch: [239][70/500] Time 0.026 (0.023) Data 0.002 (0.005) Loss 0.0344 (0.0436) Prec@1 96.000 (93.875) Prec@5 100.000 (99.500) +2022-11-14 14:41:46,872 Epoch: [239][80/500] Time 0.031 (0.024) Data 0.002 (0.004) Loss 0.0385 (0.0430) Prec@1 95.000 (94.000) Prec@5 100.000 (99.556) +2022-11-14 14:41:47,167 Epoch: [239][90/500] Time 0.028 (0.024) Data 0.001 (0.004) Loss 0.0158 (0.0403) Prec@1 98.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 14:41:47,468 Epoch: [239][100/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0382 (0.0401) Prec@1 93.000 (94.273) Prec@5 100.000 (99.636) +2022-11-14 14:41:47,765 Epoch: [239][110/500] Time 0.028 (0.024) Data 0.002 (0.004) Loss 0.0429 (0.0403) Prec@1 94.000 (94.250) Prec@5 99.000 (99.583) +2022-11-14 14:41:48,061 Epoch: [239][120/500] Time 0.027 (0.025) Data 0.002 (0.004) Loss 0.0219 (0.0389) Prec@1 96.000 (94.385) Prec@5 99.000 (99.538) +2022-11-14 14:41:48,365 Epoch: [239][130/500] Time 0.030 (0.025) Data 0.001 (0.003) Loss 0.0563 (0.0402) Prec@1 90.000 (94.071) Prec@5 100.000 (99.571) +2022-11-14 14:41:48,656 Epoch: [239][140/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0263 (0.0392) Prec@1 95.000 (94.133) Prec@5 100.000 (99.600) +2022-11-14 14:41:48,958 Epoch: [239][150/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0438 (0.0395) Prec@1 92.000 (94.000) Prec@5 100.000 (99.625) +2022-11-14 14:41:49,252 Epoch: [239][160/500] Time 0.027 (0.025) Data 0.001 (0.003) Loss 0.0263 (0.0387) Prec@1 95.000 (94.059) Prec@5 100.000 (99.647) +2022-11-14 14:41:49,550 Epoch: [239][170/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0287 (0.0382) Prec@1 96.000 (94.167) Prec@5 100.000 (99.667) +2022-11-14 14:41:49,853 Epoch: [239][180/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0308 (0.0378) Prec@1 94.000 (94.158) Prec@5 100.000 (99.684) +2022-11-14 14:41:50,309 Epoch: [239][190/500] Time 0.045 (0.026) Data 0.002 (0.003) Loss 0.0511 (0.0385) Prec@1 92.000 (94.050) Prec@5 100.000 (99.700) +2022-11-14 14:41:50,790 Epoch: [239][200/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0222 (0.0377) Prec@1 96.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:41:51,269 Epoch: [239][210/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0510 (0.0383) Prec@1 92.000 (94.045) Prec@5 100.000 (99.727) +2022-11-14 14:41:51,749 Epoch: [239][220/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0663 (0.0395) Prec@1 89.000 (93.826) Prec@5 99.000 (99.696) +2022-11-14 14:41:52,232 Epoch: [239][230/500] Time 0.043 (0.029) Data 0.003 (0.003) Loss 0.0530 (0.0401) Prec@1 91.000 (93.708) Prec@5 100.000 (99.708) +2022-11-14 14:41:52,714 Epoch: [239][240/500] Time 0.045 (0.029) Data 0.002 (0.003) Loss 0.0393 (0.0400) Prec@1 93.000 (93.680) Prec@5 100.000 (99.720) +2022-11-14 14:41:53,194 Epoch: [239][250/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0273 (0.0396) Prec@1 95.000 (93.731) Prec@5 100.000 (99.731) +2022-11-14 14:41:53,678 Epoch: [239][260/500] Time 0.043 (0.030) Data 0.001 (0.003) Loss 0.0557 (0.0402) Prec@1 90.000 (93.593) Prec@5 100.000 (99.741) +2022-11-14 14:41:54,157 Epoch: [239][270/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0418 (0.0402) Prec@1 94.000 (93.607) Prec@5 100.000 (99.750) +2022-11-14 14:41:54,641 Epoch: [239][280/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0307 (0.0399) Prec@1 94.000 (93.621) Prec@5 100.000 (99.759) +2022-11-14 14:41:55,124 Epoch: [239][290/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0713 (0.0409) Prec@1 88.000 (93.433) Prec@5 99.000 (99.733) +2022-11-14 14:41:55,608 Epoch: [239][300/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0211 (0.0403) Prec@1 97.000 (93.548) Prec@5 100.000 (99.742) +2022-11-14 14:41:56,091 Epoch: [239][310/500] Time 0.043 (0.033) Data 0.001 (0.003) Loss 0.0446 (0.0404) Prec@1 92.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:41:56,572 Epoch: [239][320/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0519 (0.0408) Prec@1 92.000 (93.455) Prec@5 100.000 (99.758) +2022-11-14 14:41:57,052 Epoch: [239][330/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0300 (0.0405) Prec@1 95.000 (93.500) Prec@5 100.000 (99.765) +2022-11-14 14:41:57,537 Epoch: [239][340/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0380 (0.0404) Prec@1 93.000 (93.486) Prec@5 100.000 (99.771) +2022-11-14 14:41:58,019 Epoch: [239][350/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0275 (0.0400) Prec@1 95.000 (93.528) Prec@5 99.000 (99.750) +2022-11-14 14:41:58,500 Epoch: [239][360/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0471 (0.0402) Prec@1 90.000 (93.432) Prec@5 100.000 (99.757) +2022-11-14 14:41:58,986 Epoch: [239][370/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0373 (0.0401) Prec@1 93.000 (93.421) Prec@5 100.000 (99.763) +2022-11-14 14:41:59,472 Epoch: [239][380/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0475 (0.0403) Prec@1 92.000 (93.385) Prec@5 100.000 (99.769) +2022-11-14 14:41:59,954 Epoch: [239][390/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0237 (0.0399) Prec@1 97.000 (93.475) Prec@5 100.000 (99.775) +2022-11-14 14:42:00,442 Epoch: [239][400/500] Time 0.050 (0.035) Data 0.002 (0.002) Loss 0.0241 (0.0395) Prec@1 96.000 (93.537) Prec@5 100.000 (99.780) +2022-11-14 14:42:00,923 Epoch: [239][410/500] Time 0.052 (0.035) Data 0.002 (0.002) Loss 0.0630 (0.0401) Prec@1 90.000 (93.452) Prec@5 99.000 (99.762) +2022-11-14 14:42:01,404 Epoch: [239][420/500] Time 0.051 (0.035) Data 0.002 (0.002) Loss 0.0251 (0.0397) Prec@1 96.000 (93.512) Prec@5 100.000 (99.767) +2022-11-14 14:42:01,885 Epoch: [239][430/500] Time 0.045 (0.035) Data 0.002 (0.002) Loss 0.0318 (0.0396) Prec@1 94.000 (93.523) Prec@5 100.000 (99.773) +2022-11-14 14:42:02,365 Epoch: [239][440/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0469 (0.0397) Prec@1 91.000 (93.467) Prec@5 100.000 (99.778) +2022-11-14 14:42:02,839 Epoch: [239][450/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0289 (0.0395) Prec@1 95.000 (93.500) Prec@5 100.000 (99.783) +2022-11-14 14:42:03,272 Epoch: [239][460/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0347 (0.0394) Prec@1 95.000 (93.532) Prec@5 99.000 (99.766) +2022-11-14 14:42:03,667 Epoch: [239][470/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0473 (0.0396) Prec@1 93.000 (93.521) Prec@5 99.000 (99.750) +2022-11-14 14:42:04,057 Epoch: [239][480/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0363 (0.0395) Prec@1 93.000 (93.510) Prec@5 100.000 (99.755) +2022-11-14 14:42:04,453 Epoch: [239][490/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0592 (0.0399) Prec@1 89.000 (93.420) Prec@5 99.000 (99.740) +2022-11-14 14:42:04,806 Epoch: [239][499/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0419 (0.0399) Prec@1 94.000 (93.431) Prec@5 100.000 (99.745) +2022-11-14 14:42:05,098 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0591 (0.0591) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:05,109 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0675) Prec@1 87.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:42:05,118 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0659) Prec@1 89.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:42:05,130 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0673) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:42:05,138 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0670) Prec@1 91.000 (89.000) Prec@5 99.000 (99.800) +2022-11-14 14:42:05,148 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0645) Prec@1 92.000 (89.500) Prec@5 100.000 (99.833) +2022-11-14 14:42:05,156 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0635) Prec@1 90.000 (89.571) Prec@5 100.000 (99.857) +2022-11-14 14:42:05,166 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0646) Prec@1 88.000 (89.375) Prec@5 100.000 (99.875) +2022-11-14 14:42:05,176 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0661) Prec@1 87.000 (89.111) Prec@5 99.000 (99.778) +2022-11-14 14:42:05,185 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0661) Prec@1 90.000 (89.200) Prec@5 99.000 (99.700) +2022-11-14 14:42:05,196 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0649) Prec@1 92.000 (89.455) Prec@5 100.000 (99.727) +2022-11-14 14:42:05,206 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0677) Prec@1 83.000 (88.917) Prec@5 99.000 (99.667) +2022-11-14 14:42:05,217 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0667) Prec@1 92.000 (89.154) Prec@5 100.000 (99.692) +2022-11-14 14:42:05,227 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0660) Prec@1 90.000 (89.214) Prec@5 99.000 (99.643) +2022-11-14 14:42:05,238 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0669) Prec@1 86.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:42:05,248 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0681) Prec@1 86.000 (88.812) Prec@5 100.000 (99.688) +2022-11-14 14:42:05,259 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0675) Prec@1 91.000 (88.941) Prec@5 99.000 (99.647) +2022-11-14 14:42:05,269 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0700) Prec@1 81.000 (88.500) Prec@5 99.000 (99.611) +2022-11-14 14:42:05,280 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0709) Prec@1 85.000 (88.316) Prec@5 99.000 (99.579) +2022-11-14 14:42:05,290 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0717) Prec@1 87.000 (88.250) Prec@5 98.000 (99.500) +2022-11-14 14:42:05,300 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0720) Prec@1 85.000 (88.095) Prec@5 100.000 (99.524) +2022-11-14 14:42:05,310 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0721) Prec@1 86.000 (88.000) Prec@5 100.000 (99.545) +2022-11-14 14:42:05,320 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0729) Prec@1 85.000 (87.870) Prec@5 99.000 (99.522) +2022-11-14 14:42:05,329 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0733) Prec@1 85.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 14:42:05,339 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0735) Prec@1 87.000 (87.720) Prec@5 99.000 (99.480) +2022-11-14 14:42:05,350 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0746) Prec@1 85.000 (87.615) Prec@5 99.000 (99.462) +2022-11-14 14:42:05,359 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0739) Prec@1 91.000 (87.741) Prec@5 100.000 (99.481) +2022-11-14 14:42:05,369 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0737) Prec@1 88.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 14:42:05,379 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0735) Prec@1 90.000 (87.828) Prec@5 99.000 (99.483) +2022-11-14 14:42:05,389 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0729) Prec@1 91.000 (87.933) Prec@5 99.000 (99.467) +2022-11-14 14:42:05,399 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0729) Prec@1 89.000 (87.968) Prec@5 100.000 (99.484) +2022-11-14 14:42:05,409 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0726) Prec@1 91.000 (88.062) Prec@5 98.000 (99.438) +2022-11-14 14:42:05,420 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0731) Prec@1 85.000 (87.970) Prec@5 99.000 (99.424) +2022-11-14 14:42:05,431 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0730) Prec@1 87.000 (87.941) Prec@5 100.000 (99.441) +2022-11-14 14:42:05,442 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0732) Prec@1 90.000 (88.000) Prec@5 99.000 (99.429) +2022-11-14 14:42:05,453 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0730) Prec@1 90.000 (88.056) Prec@5 100.000 (99.444) +2022-11-14 14:42:05,463 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0732) Prec@1 87.000 (88.027) Prec@5 98.000 (99.405) +2022-11-14 14:42:05,473 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0731) Prec@1 88.000 (88.026) Prec@5 100.000 (99.421) +2022-11-14 14:42:05,484 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0727) Prec@1 93.000 (88.154) Prec@5 99.000 (99.410) +2022-11-14 14:42:05,495 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0722) Prec@1 92.000 (88.250) Prec@5 100.000 (99.425) +2022-11-14 14:42:05,504 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0728) Prec@1 84.000 (88.146) Prec@5 98.000 (99.390) +2022-11-14 14:42:05,515 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0729) Prec@1 87.000 (88.119) Prec@5 100.000 (99.405) +2022-11-14 14:42:05,525 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0725) Prec@1 92.000 (88.209) Prec@5 100.000 (99.419) +2022-11-14 14:42:05,536 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0724) Prec@1 89.000 (88.227) Prec@5 98.000 (99.386) +2022-11-14 14:42:05,546 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0720) Prec@1 90.000 (88.267) Prec@5 100.000 (99.400) +2022-11-14 14:42:05,558 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0727) Prec@1 81.000 (88.109) Prec@5 98.000 (99.370) +2022-11-14 14:42:05,568 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0726) Prec@1 90.000 (88.149) Prec@5 100.000 (99.383) +2022-11-14 14:42:05,580 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0732) Prec@1 83.000 (88.042) Prec@5 99.000 (99.375) +2022-11-14 14:42:05,591 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0727) Prec@1 92.000 (88.122) Prec@5 100.000 (99.388) +2022-11-14 14:42:05,603 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0731) Prec@1 85.000 (88.060) Prec@5 100.000 (99.400) +2022-11-14 14:42:05,613 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0730) Prec@1 88.000 (88.059) Prec@5 100.000 (99.412) +2022-11-14 14:42:05,623 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0731) Prec@1 88.000 (88.058) Prec@5 99.000 (99.404) +2022-11-14 14:42:05,633 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0733) Prec@1 88.000 (88.057) Prec@5 99.000 (99.396) +2022-11-14 14:42:05,644 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0732) Prec@1 87.000 (88.037) Prec@5 98.000 (99.370) +2022-11-14 14:42:05,654 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0733) Prec@1 88.000 (88.036) Prec@5 100.000 (99.382) +2022-11-14 14:42:05,664 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0731) Prec@1 89.000 (88.054) Prec@5 99.000 (99.375) +2022-11-14 14:42:05,675 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0733) Prec@1 85.000 (88.000) Prec@5 99.000 (99.368) +2022-11-14 14:42:05,685 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0733) Prec@1 88.000 (88.000) Prec@5 99.000 (99.362) +2022-11-14 14:42:05,696 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0738) Prec@1 83.000 (87.915) Prec@5 99.000 (99.356) +2022-11-14 14:42:05,706 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0737) Prec@1 88.000 (87.917) Prec@5 99.000 (99.350) +2022-11-14 14:42:05,716 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0739) Prec@1 85.000 (87.869) Prec@5 98.000 (99.328) +2022-11-14 14:42:05,727 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0740) Prec@1 90.000 (87.903) Prec@5 99.000 (99.323) +2022-11-14 14:42:05,737 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0738) Prec@1 90.000 (87.937) Prec@5 99.000 (99.317) +2022-11-14 14:42:05,746 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0734) Prec@1 91.000 (87.984) Prec@5 99.000 (99.312) +2022-11-14 14:42:05,756 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0736) Prec@1 87.000 (87.969) Prec@5 99.000 (99.308) +2022-11-14 14:42:05,767 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0739) Prec@1 84.000 (87.909) Prec@5 99.000 (99.303) +2022-11-14 14:42:05,777 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0733) Prec@1 94.000 (88.000) Prec@5 100.000 (99.313) +2022-11-14 14:42:05,788 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0735) Prec@1 87.000 (87.985) Prec@5 99.000 (99.309) +2022-11-14 14:42:05,798 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0735) Prec@1 89.000 (88.000) Prec@5 99.000 (99.304) +2022-11-14 14:42:05,809 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0734) Prec@1 89.000 (88.014) Prec@5 100.000 (99.314) +2022-11-14 14:42:05,820 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0737) Prec@1 85.000 (87.972) Prec@5 100.000 (99.324) +2022-11-14 14:42:05,831 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0735) Prec@1 91.000 (88.014) Prec@5 99.000 (99.319) +2022-11-14 14:42:05,842 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0397 (0.0731) Prec@1 94.000 (88.096) Prec@5 100.000 (99.329) +2022-11-14 14:42:05,852 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0727) Prec@1 92.000 (88.149) Prec@5 100.000 (99.338) +2022-11-14 14:42:05,863 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1270 (0.0734) Prec@1 81.000 (88.053) Prec@5 99.000 (99.333) +2022-11-14 14:42:05,873 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0419 (0.0730) Prec@1 94.000 (88.132) Prec@5 100.000 (99.342) +2022-11-14 14:42:05,884 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0729) Prec@1 87.000 (88.117) Prec@5 100.000 (99.351) +2022-11-14 14:42:05,894 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0734) Prec@1 81.000 (88.026) Prec@5 99.000 (99.346) +2022-11-14 14:42:05,905 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0735) Prec@1 90.000 (88.051) Prec@5 100.000 (99.354) +2022-11-14 14:42:05,915 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0735) Prec@1 87.000 (88.037) Prec@5 100.000 (99.362) +2022-11-14 14:42:05,926 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0734) Prec@1 87.000 (88.025) Prec@5 99.000 (99.358) +2022-11-14 14:42:05,936 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0734) Prec@1 89.000 (88.037) Prec@5 100.000 (99.366) +2022-11-14 14:42:05,946 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0738) Prec@1 84.000 (87.988) Prec@5 100.000 (99.373) +2022-11-14 14:42:05,957 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0736) Prec@1 88.000 (87.988) Prec@5 100.000 (99.381) +2022-11-14 14:42:05,967 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0738) Prec@1 85.000 (87.953) Prec@5 100.000 (99.388) +2022-11-14 14:42:05,978 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0740) Prec@1 86.000 (87.930) Prec@5 99.000 (99.384) +2022-11-14 14:42:05,988 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0740) Prec@1 88.000 (87.931) Prec@5 99.000 (99.379) +2022-11-14 14:42:05,998 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0740) Prec@1 88.000 (87.932) Prec@5 99.000 (99.375) +2022-11-14 14:42:06,008 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0738) Prec@1 91.000 (87.966) Prec@5 99.000 (99.371) +2022-11-14 14:42:06,019 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0740) Prec@1 88.000 (87.967) Prec@5 100.000 (99.378) +2022-11-14 14:42:06,030 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0738) Prec@1 87.000 (87.956) Prec@5 100.000 (99.385) +2022-11-14 14:42:06,039 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0735) Prec@1 93.000 (88.011) Prec@5 100.000 (99.391) +2022-11-14 14:42:06,050 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0736) Prec@1 89.000 (88.022) Prec@5 99.000 (99.387) +2022-11-14 14:42:06,061 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0737) Prec@1 84.000 (87.979) Prec@5 99.000 (99.383) +2022-11-14 14:42:06,071 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0736) Prec@1 91.000 (88.011) Prec@5 100.000 (99.389) +2022-11-14 14:42:06,081 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0736) Prec@1 90.000 (88.031) Prec@5 99.000 (99.385) +2022-11-14 14:42:06,091 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0733) Prec@1 93.000 (88.082) Prec@5 100.000 (99.392) +2022-11-14 14:42:06,100 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0736) Prec@1 84.000 (88.041) Prec@5 99.000 (99.388) +2022-11-14 14:42:06,110 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1267 (0.0741) Prec@1 81.000 (87.970) Prec@5 98.000 (99.374) +2022-11-14 14:42:06,121 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0742) Prec@1 86.000 (87.950) Prec@5 100.000 (99.380) +2022-11-14 14:42:06,177 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:42:06,473 Epoch: [240][0/500] Time 0.022 (0.022) Data 0.215 (0.215) Loss 0.0618 (0.0618) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:42:06,683 Epoch: [240][10/500] Time 0.016 (0.019) Data 0.002 (0.021) Loss 0.0413 (0.0516) Prec@1 93.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 14:42:06,892 Epoch: [240][20/500] Time 0.019 (0.019) Data 0.001 (0.012) Loss 0.0372 (0.0468) Prec@1 92.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:42:07,101 Epoch: [240][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.0342 (0.0436) Prec@1 94.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 14:42:07,356 Epoch: [240][40/500] Time 0.026 (0.020) Data 0.002 (0.007) Loss 0.0360 (0.0421) Prec@1 96.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 14:42:07,616 Epoch: [240][50/500] Time 0.021 (0.020) Data 0.002 (0.006) Loss 0.0496 (0.0434) Prec@1 89.000 (92.167) Prec@5 100.000 (99.833) +2022-11-14 14:42:07,880 Epoch: [240][60/500] Time 0.029 (0.021) Data 0.002 (0.005) Loss 0.0791 (0.0485) Prec@1 86.000 (91.286) Prec@5 97.000 (99.429) +2022-11-14 14:42:08,137 Epoch: [240][70/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0469 (0.0483) Prec@1 93.000 (91.500) Prec@5 100.000 (99.500) +2022-11-14 14:42:08,405 Epoch: [240][80/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0453 (0.0479) Prec@1 92.000 (91.556) Prec@5 100.000 (99.556) +2022-11-14 14:42:08,663 Epoch: [240][90/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0317 (0.0463) Prec@1 96.000 (92.000) Prec@5 100.000 (99.600) +2022-11-14 14:42:08,933 Epoch: [240][100/500] Time 0.023 (0.022) Data 0.002 (0.004) Loss 0.0231 (0.0442) Prec@1 98.000 (92.545) Prec@5 100.000 (99.636) +2022-11-14 14:42:09,351 Epoch: [240][110/500] Time 0.042 (0.023) Data 0.002 (0.004) Loss 0.0390 (0.0438) Prec@1 92.000 (92.500) Prec@5 100.000 (99.667) +2022-11-14 14:42:09,781 Epoch: [240][120/500] Time 0.043 (0.024) Data 0.002 (0.003) Loss 0.0582 (0.0449) Prec@1 89.000 (92.231) Prec@5 100.000 (99.692) +2022-11-14 14:42:10,219 Epoch: [240][130/500] Time 0.038 (0.025) Data 0.002 (0.003) Loss 0.0385 (0.0444) Prec@1 95.000 (92.429) Prec@5 100.000 (99.714) +2022-11-14 14:42:10,655 Epoch: [240][140/500] Time 0.046 (0.026) Data 0.002 (0.003) Loss 0.0490 (0.0447) Prec@1 93.000 (92.467) Prec@5 100.000 (99.733) +2022-11-14 14:42:11,095 Epoch: [240][150/500] Time 0.040 (0.027) Data 0.002 (0.003) Loss 0.0406 (0.0445) Prec@1 93.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:42:11,529 Epoch: [240][160/500] Time 0.040 (0.028) Data 0.002 (0.003) Loss 0.0164 (0.0428) Prec@1 98.000 (92.824) Prec@5 100.000 (99.765) +2022-11-14 14:42:11,970 Epoch: [240][170/500] Time 0.036 (0.029) Data 0.002 (0.003) Loss 0.0458 (0.0430) Prec@1 92.000 (92.778) Prec@5 100.000 (99.778) +2022-11-14 14:42:12,404 Epoch: [240][180/500] Time 0.050 (0.029) Data 0.002 (0.003) Loss 0.0612 (0.0439) Prec@1 90.000 (92.632) Prec@5 99.000 (99.737) +2022-11-14 14:42:12,840 Epoch: [240][190/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.0214 (0.0428) Prec@1 97.000 (92.850) Prec@5 100.000 (99.750) +2022-11-14 14:42:13,275 Epoch: [240][200/500] Time 0.039 (0.030) Data 0.002 (0.003) Loss 0.0345 (0.0424) Prec@1 95.000 (92.952) Prec@5 100.000 (99.762) +2022-11-14 14:42:13,714 Epoch: [240][210/500] Time 0.039 (0.031) Data 0.002 (0.003) Loss 0.0609 (0.0433) Prec@1 89.000 (92.773) Prec@5 100.000 (99.773) +2022-11-14 14:42:14,154 Epoch: [240][220/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0230 (0.0424) Prec@1 96.000 (92.913) Prec@5 100.000 (99.783) +2022-11-14 14:42:14,592 Epoch: [240][230/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.0460 (0.0425) Prec@1 95.000 (93.000) Prec@5 100.000 (99.792) +2022-11-14 14:42:15,028 Epoch: [240][240/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0343 (0.0422) Prec@1 95.000 (93.080) Prec@5 100.000 (99.800) +2022-11-14 14:42:15,454 Epoch: [240][250/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0416 (0.0422) Prec@1 91.000 (93.000) Prec@5 100.000 (99.808) +2022-11-14 14:42:15,902 Epoch: [240][260/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0323 (0.0418) Prec@1 96.000 (93.111) Prec@5 100.000 (99.815) +2022-11-14 14:42:16,336 Epoch: [240][270/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0248 (0.0412) Prec@1 97.000 (93.250) Prec@5 99.000 (99.786) +2022-11-14 14:42:16,767 Epoch: [240][280/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0294 (0.0408) Prec@1 96.000 (93.345) Prec@5 100.000 (99.793) +2022-11-14 14:42:17,200 Epoch: [240][290/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0503 (0.0411) Prec@1 92.000 (93.300) Prec@5 100.000 (99.800) +2022-11-14 14:42:17,630 Epoch: [240][300/500] Time 0.041 (0.033) Data 0.001 (0.003) Loss 0.0309 (0.0408) Prec@1 96.000 (93.387) Prec@5 100.000 (99.806) +2022-11-14 14:42:18,061 Epoch: [240][310/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0547 (0.0412) Prec@1 92.000 (93.344) Prec@5 99.000 (99.781) +2022-11-14 14:42:18,491 Epoch: [240][320/500] Time 0.039 (0.033) Data 0.002 (0.002) Loss 0.0603 (0.0418) Prec@1 88.000 (93.182) Prec@5 99.000 (99.758) +2022-11-14 14:42:18,928 Epoch: [240][330/500] Time 0.047 (0.034) Data 0.002 (0.002) Loss 0.0480 (0.0420) Prec@1 93.000 (93.176) Prec@5 100.000 (99.765) +2022-11-14 14:42:19,362 Epoch: [240][340/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0340 (0.0417) Prec@1 93.000 (93.171) Prec@5 99.000 (99.743) +2022-11-14 14:42:19,788 Epoch: [240][350/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.0489 (0.0419) Prec@1 91.000 (93.111) Prec@5 99.000 (99.722) +2022-11-14 14:42:20,203 Epoch: [240][360/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0433 (0.0420) Prec@1 92.000 (93.081) Prec@5 100.000 (99.730) +2022-11-14 14:42:20,631 Epoch: [240][370/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0471 (0.0421) Prec@1 92.000 (93.053) Prec@5 100.000 (99.737) +2022-11-14 14:42:21,075 Epoch: [240][380/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0311 (0.0418) Prec@1 94.000 (93.077) Prec@5 100.000 (99.744) +2022-11-14 14:42:21,513 Epoch: [240][390/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0353 (0.0417) Prec@1 94.000 (93.100) Prec@5 100.000 (99.750) +2022-11-14 14:42:21,939 Epoch: [240][400/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0512 (0.0419) Prec@1 90.000 (93.024) Prec@5 100.000 (99.756) +2022-11-14 14:42:22,373 Epoch: [240][410/500] Time 0.040 (0.034) Data 0.002 (0.002) Loss 0.0347 (0.0417) Prec@1 93.000 (93.024) Prec@5 100.000 (99.762) +2022-11-14 14:42:22,802 Epoch: [240][420/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0310 (0.0415) Prec@1 94.000 (93.047) Prec@5 100.000 (99.767) +2022-11-14 14:42:23,228 Epoch: [240][430/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0304 (0.0412) Prec@1 95.000 (93.091) Prec@5 100.000 (99.773) +2022-11-14 14:42:23,653 Epoch: [240][440/500] Time 0.040 (0.035) Data 0.002 (0.002) Loss 0.0416 (0.0412) Prec@1 93.000 (93.089) Prec@5 100.000 (99.778) +2022-11-14 14:42:24,078 Epoch: [240][450/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0236 (0.0409) Prec@1 96.000 (93.152) Prec@5 100.000 (99.783) +2022-11-14 14:42:24,518 Epoch: [240][460/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.0279 (0.0406) Prec@1 94.000 (93.170) Prec@5 100.000 (99.787) +2022-11-14 14:42:24,951 Epoch: [240][470/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0381 (0.0405) Prec@1 94.000 (93.188) Prec@5 100.000 (99.792) +2022-11-14 14:42:25,378 Epoch: [240][480/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0236 (0.0402) Prec@1 96.000 (93.245) Prec@5 100.000 (99.796) +2022-11-14 14:42:25,807 Epoch: [240][490/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0358 (0.0401) Prec@1 95.000 (93.280) Prec@5 99.000 (99.780) +2022-11-14 14:42:26,194 Epoch: [240][499/500] Time 0.039 (0.035) Data 0.002 (0.002) Loss 0.0574 (0.0404) Prec@1 91.000 (93.235) Prec@5 100.000 (99.784) +2022-11-14 14:42:26,486 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0523 (0.0523) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:26,494 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0549) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:26,506 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0684) Prec@1 84.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:42:26,517 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0756) Prec@1 86.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:42:26,526 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0775) Prec@1 87.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 14:42:26,536 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0714) Prec@1 92.000 (88.500) Prec@5 100.000 (99.833) +2022-11-14 14:42:26,545 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0723) Prec@1 87.000 (88.286) Prec@5 100.000 (99.857) +2022-11-14 14:42:26,555 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0725) Prec@1 87.000 (88.125) Prec@5 100.000 (99.875) +2022-11-14 14:42:26,565 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0763) Prec@1 83.000 (87.556) Prec@5 98.000 (99.667) +2022-11-14 14:42:26,575 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0756) Prec@1 87.000 (87.500) Prec@5 99.000 (99.600) +2022-11-14 14:42:26,585 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0736) Prec@1 89.000 (87.636) Prec@5 100.000 (99.636) +2022-11-14 14:42:26,595 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0738) Prec@1 89.000 (87.750) Prec@5 99.000 (99.583) +2022-11-14 14:42:26,607 Test: [12/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0724) Prec@1 90.000 (87.923) Prec@5 99.000 (99.538) +2022-11-14 14:42:26,618 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0720) Prec@1 89.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:42:26,627 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0737) Prec@1 85.000 (87.800) Prec@5 99.000 (99.467) +2022-11-14 14:42:26,637 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0736) Prec@1 89.000 (87.875) Prec@5 100.000 (99.500) +2022-11-14 14:42:26,650 Test: [16/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0723) Prec@1 94.000 (88.235) Prec@5 99.000 (99.471) +2022-11-14 14:42:26,661 Test: [17/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0745) Prec@1 83.000 (87.944) Prec@5 100.000 (99.500) +2022-11-14 14:42:26,671 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0749) Prec@1 87.000 (87.895) Prec@5 98.000 (99.421) +2022-11-14 14:42:26,681 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0756) Prec@1 84.000 (87.700) Prec@5 99.000 (99.400) +2022-11-14 14:42:26,694 Test: [20/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0759) Prec@1 86.000 (87.619) Prec@5 98.000 (99.333) +2022-11-14 14:42:26,706 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0763) Prec@1 86.000 (87.545) Prec@5 99.000 (99.318) +2022-11-14 14:42:26,716 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0774) Prec@1 83.000 (87.348) Prec@5 98.000 (99.261) +2022-11-14 14:42:26,727 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0773) Prec@1 89.000 (87.417) Prec@5 99.000 (99.250) +2022-11-14 14:42:26,740 Test: [24/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0778) Prec@1 85.000 (87.320) Prec@5 100.000 (99.280) +2022-11-14 14:42:26,752 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0789) Prec@1 83.000 (87.154) Prec@5 99.000 (99.269) +2022-11-14 14:42:26,761 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0786) Prec@1 88.000 (87.185) Prec@5 100.000 (99.296) +2022-11-14 14:42:26,771 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0780) Prec@1 87.000 (87.179) Prec@5 100.000 (99.321) +2022-11-14 14:42:26,783 Test: [28/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0774) Prec@1 91.000 (87.310) Prec@5 98.000 (99.276) +2022-11-14 14:42:26,794 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0765) Prec@1 93.000 (87.500) Prec@5 98.000 (99.233) +2022-11-14 14:42:26,804 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0767) Prec@1 85.000 (87.419) Prec@5 100.000 (99.258) +2022-11-14 14:42:26,814 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0774) Prec@1 82.000 (87.250) Prec@5 100.000 (99.281) +2022-11-14 14:42:26,826 Test: [32/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0783) Prec@1 80.000 (87.030) Prec@5 100.000 (99.303) +2022-11-14 14:42:26,837 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0793) Prec@1 81.000 (86.853) Prec@5 100.000 (99.324) +2022-11-14 14:42:26,848 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0790) Prec@1 90.000 (86.943) Prec@5 99.000 (99.314) +2022-11-14 14:42:26,858 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0784) Prec@1 92.000 (87.083) Prec@5 99.000 (99.306) +2022-11-14 14:42:26,871 Test: [36/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0781) Prec@1 88.000 (87.108) Prec@5 99.000 (99.297) +2022-11-14 14:42:26,882 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0779) Prec@1 88.000 (87.132) Prec@5 100.000 (99.316) +2022-11-14 14:42:26,892 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0775) Prec@1 91.000 (87.231) Prec@5 100.000 (99.333) +2022-11-14 14:42:26,902 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0771) Prec@1 91.000 (87.325) Prec@5 98.000 (99.300) +2022-11-14 14:42:26,913 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0775) Prec@1 85.000 (87.268) Prec@5 99.000 (99.293) +2022-11-14 14:42:26,924 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0773) Prec@1 91.000 (87.357) Prec@5 99.000 (99.286) +2022-11-14 14:42:26,935 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0765) Prec@1 94.000 (87.512) Prec@5 100.000 (99.302) +2022-11-14 14:42:26,947 Test: [43/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0766) Prec@1 89.000 (87.545) Prec@5 99.000 (99.295) +2022-11-14 14:42:26,956 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0767) Prec@1 89.000 (87.578) Prec@5 99.000 (99.289) +2022-11-14 14:42:26,966 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0771) Prec@1 83.000 (87.478) Prec@5 98.000 (99.261) +2022-11-14 14:42:26,976 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0766) Prec@1 92.000 (87.574) Prec@5 99.000 (99.255) +2022-11-14 14:42:26,987 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0771) Prec@1 84.000 (87.500) Prec@5 100.000 (99.271) +2022-11-14 14:42:26,997 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0769) Prec@1 88.000 (87.510) Prec@5 100.000 (99.286) +2022-11-14 14:42:27,007 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0771) Prec@1 89.000 (87.540) Prec@5 98.000 (99.260) +2022-11-14 14:42:27,018 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0771) Prec@1 85.000 (87.490) Prec@5 100.000 (99.275) +2022-11-14 14:42:27,029 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0773) Prec@1 85.000 (87.442) Prec@5 98.000 (99.250) +2022-11-14 14:42:27,039 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0773) Prec@1 86.000 (87.415) Prec@5 100.000 (99.264) +2022-11-14 14:42:27,050 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0777) Prec@1 84.000 (87.352) Prec@5 99.000 (99.259) +2022-11-14 14:42:27,060 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0778) Prec@1 87.000 (87.345) Prec@5 100.000 (99.273) +2022-11-14 14:42:27,070 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0776) Prec@1 91.000 (87.411) Prec@5 100.000 (99.286) +2022-11-14 14:42:27,081 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0778) Prec@1 86.000 (87.386) Prec@5 100.000 (99.298) +2022-11-14 14:42:27,092 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0778) Prec@1 87.000 (87.379) Prec@5 100.000 (99.310) +2022-11-14 14:42:27,101 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0784) Prec@1 80.000 (87.254) Prec@5 99.000 (99.305) +2022-11-14 14:42:27,112 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0784) Prec@1 87.000 (87.250) Prec@5 100.000 (99.317) +2022-11-14 14:42:27,124 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0784) Prec@1 88.000 (87.262) Prec@5 99.000 (99.311) +2022-11-14 14:42:27,135 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0786) Prec@1 83.000 (87.194) Prec@5 100.000 (99.323) +2022-11-14 14:42:27,145 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0784) Prec@1 90.000 (87.238) Prec@5 100.000 (99.333) +2022-11-14 14:42:27,155 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0369 (0.0778) Prec@1 92.000 (87.312) Prec@5 99.000 (99.328) +2022-11-14 14:42:27,165 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0779) Prec@1 84.000 (87.262) Prec@5 100.000 (99.338) +2022-11-14 14:42:27,176 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0782) Prec@1 84.000 (87.212) Prec@5 99.000 (99.333) +2022-11-14 14:42:27,188 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0777) Prec@1 93.000 (87.299) Prec@5 99.000 (99.328) +2022-11-14 14:42:27,199 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0778) Prec@1 87.000 (87.294) Prec@5 98.000 (99.309) +2022-11-14 14:42:27,209 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0777) Prec@1 89.000 (87.319) Prec@5 99.000 (99.304) +2022-11-14 14:42:27,220 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0777) Prec@1 86.000 (87.300) Prec@5 99.000 (99.300) +2022-11-14 14:42:27,230 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0779) Prec@1 84.000 (87.254) Prec@5 98.000 (99.282) +2022-11-14 14:42:27,240 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0779) Prec@1 87.000 (87.250) Prec@5 100.000 (99.292) +2022-11-14 14:42:27,251 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0775) Prec@1 93.000 (87.329) Prec@5 100.000 (99.301) +2022-11-14 14:42:27,262 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0316 (0.0769) Prec@1 94.000 (87.419) Prec@5 100.000 (99.311) +2022-11-14 14:42:27,274 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0774) Prec@1 82.000 (87.347) Prec@5 99.000 (99.307) +2022-11-14 14:42:27,285 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0772) Prec@1 89.000 (87.368) Prec@5 100.000 (99.316) +2022-11-14 14:42:27,296 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0774) Prec@1 84.000 (87.325) Prec@5 99.000 (99.312) +2022-11-14 14:42:27,308 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0776) Prec@1 84.000 (87.282) Prec@5 100.000 (99.321) +2022-11-14 14:42:27,318 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0776) Prec@1 88.000 (87.291) Prec@5 99.000 (99.316) +2022-11-14 14:42:27,329 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0777) Prec@1 85.000 (87.263) Prec@5 100.000 (99.325) +2022-11-14 14:42:27,339 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0775) Prec@1 90.000 (87.296) Prec@5 99.000 (99.321) +2022-11-14 14:42:27,350 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0778) Prec@1 84.000 (87.256) Prec@5 99.000 (99.317) +2022-11-14 14:42:27,360 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0776) Prec@1 88.000 (87.265) Prec@5 100.000 (99.325) +2022-11-14 14:42:27,369 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0779) Prec@1 84.000 (87.226) Prec@5 99.000 (99.321) +2022-11-14 14:42:27,377 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0780) Prec@1 86.000 (87.212) Prec@5 100.000 (99.329) +2022-11-14 14:42:27,386 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0783) Prec@1 82.000 (87.151) Prec@5 99.000 (99.326) +2022-11-14 14:42:27,396 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0782) Prec@1 89.000 (87.172) Prec@5 100.000 (99.333) +2022-11-14 14:42:27,408 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0782) Prec@1 87.000 (87.170) Prec@5 99.000 (99.330) +2022-11-14 14:42:27,418 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0782) Prec@1 87.000 (87.169) Prec@5 99.000 (99.326) +2022-11-14 14:42:27,428 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0779) Prec@1 91.000 (87.211) Prec@5 99.000 (99.322) +2022-11-14 14:42:27,438 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0778) Prec@1 92.000 (87.264) Prec@5 100.000 (99.330) +2022-11-14 14:42:27,449 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0775) Prec@1 92.000 (87.315) Prec@5 99.000 (99.326) +2022-11-14 14:42:27,460 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0774) Prec@1 88.000 (87.323) Prec@5 99.000 (99.323) +2022-11-14 14:42:27,469 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0771) Prec@1 90.000 (87.351) Prec@5 100.000 (99.330) +2022-11-14 14:42:27,477 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0772) Prec@1 85.000 (87.326) Prec@5 99.000 (99.326) +2022-11-14 14:42:27,486 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0771) Prec@1 91.000 (87.365) Prec@5 100.000 (99.333) +2022-11-14 14:42:27,495 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0390 (0.0767) Prec@1 94.000 (87.433) Prec@5 99.000 (99.330) +2022-11-14 14:42:27,506 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0769) Prec@1 84.000 (87.398) Prec@5 100.000 (99.337) +2022-11-14 14:42:27,516 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0772) Prec@1 82.000 (87.343) Prec@5 98.000 (99.323) +2022-11-14 14:42:27,527 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0772) Prec@1 86.000 (87.330) Prec@5 99.000 (99.320) +2022-11-14 14:42:27,582 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:42:27,890 Epoch: [241][0/500] Time 0.023 (0.023) Data 0.226 (0.226) Loss 0.0357 (0.0357) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:28,096 Epoch: [241][10/500] Time 0.018 (0.018) Data 0.001 (0.022) Loss 0.0189 (0.0273) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:28,298 Epoch: [241][20/500] Time 0.018 (0.018) Data 0.001 (0.012) Loss 0.0376 (0.0307) Prec@1 94.000 (95.333) Prec@5 99.000 (99.667) +2022-11-14 14:42:28,559 Epoch: [241][30/500] Time 0.029 (0.020) Data 0.002 (0.009) Loss 0.0533 (0.0364) Prec@1 92.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 14:42:28,886 Epoch: [241][40/500] Time 0.038 (0.022) Data 0.002 (0.007) Loss 0.0086 (0.0308) Prec@1 99.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 14:42:29,198 Epoch: [241][50/500] Time 0.029 (0.023) Data 0.002 (0.006) Loss 0.0403 (0.0324) Prec@1 92.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 14:42:29,515 Epoch: [241][60/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0391 (0.0334) Prec@1 93.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 14:42:29,836 Epoch: [241][70/500] Time 0.030 (0.024) Data 0.002 (0.005) Loss 0.0613 (0.0368) Prec@1 91.000 (94.125) Prec@5 99.000 (99.750) +2022-11-14 14:42:30,149 Epoch: [241][80/500] Time 0.028 (0.025) Data 0.002 (0.005) Loss 0.0173 (0.0347) Prec@1 99.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 14:42:30,465 Epoch: [241][90/500] Time 0.027 (0.025) Data 0.001 (0.004) Loss 0.0516 (0.0364) Prec@1 93.000 (94.500) Prec@5 100.000 (99.800) +2022-11-14 14:42:30,784 Epoch: [241][100/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0308 (0.0359) Prec@1 95.000 (94.545) Prec@5 99.000 (99.727) +2022-11-14 14:42:31,108 Epoch: [241][110/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0338 (0.0357) Prec@1 93.000 (94.417) Prec@5 100.000 (99.750) +2022-11-14 14:42:31,427 Epoch: [241][120/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.0452 (0.0364) Prec@1 94.000 (94.385) Prec@5 100.000 (99.769) +2022-11-14 14:42:31,744 Epoch: [241][130/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0549 (0.0377) Prec@1 90.000 (94.071) Prec@5 100.000 (99.786) +2022-11-14 14:42:32,070 Epoch: [241][140/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0505 (0.0386) Prec@1 92.000 (93.933) Prec@5 100.000 (99.800) +2022-11-14 14:42:32,396 Epoch: [241][150/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.0359 (0.0384) Prec@1 93.000 (93.875) Prec@5 100.000 (99.812) +2022-11-14 14:42:32,715 Epoch: [241][160/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.0323 (0.0381) Prec@1 94.000 (93.882) Prec@5 100.000 (99.824) +2022-11-14 14:42:33,039 Epoch: [241][170/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0188 (0.0370) Prec@1 97.000 (94.056) Prec@5 100.000 (99.833) +2022-11-14 14:42:33,370 Epoch: [241][180/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0410 (0.0372) Prec@1 93.000 (94.000) Prec@5 100.000 (99.842) +2022-11-14 14:42:33,690 Epoch: [241][190/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0332 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (99.850) +2022-11-14 14:42:34,016 Epoch: [241][200/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0435 (0.0373) Prec@1 93.000 (93.952) Prec@5 100.000 (99.857) +2022-11-14 14:42:34,380 Epoch: [241][210/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0467 (0.0377) Prec@1 92.000 (93.864) Prec@5 100.000 (99.864) +2022-11-14 14:42:34,705 Epoch: [241][220/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0569 (0.0386) Prec@1 90.000 (93.696) Prec@5 100.000 (99.870) +2022-11-14 14:42:35,024 Epoch: [241][230/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0265 (0.0381) Prec@1 96.000 (93.792) Prec@5 99.000 (99.833) +2022-11-14 14:42:35,406 Epoch: [241][240/500] Time 0.040 (0.028) Data 0.002 (0.003) Loss 0.0153 (0.0372) Prec@1 98.000 (93.960) Prec@5 100.000 (99.840) +2022-11-14 14:42:35,763 Epoch: [241][250/500] Time 0.034 (0.028) Data 0.002 (0.003) Loss 0.0668 (0.0383) Prec@1 88.000 (93.731) Prec@5 99.000 (99.808) +2022-11-14 14:42:36,070 Epoch: [241][260/500] Time 0.029 (0.028) Data 0.001 (0.003) Loss 0.0254 (0.0378) Prec@1 96.000 (93.815) Prec@5 100.000 (99.815) +2022-11-14 14:42:36,388 Epoch: [241][270/500] Time 0.035 (0.028) Data 0.002 (0.003) Loss 0.0275 (0.0375) Prec@1 95.000 (93.857) Prec@5 100.000 (99.821) +2022-11-14 14:42:36,705 Epoch: [241][280/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0373 (0.0374) Prec@1 94.000 (93.862) Prec@5 100.000 (99.828) +2022-11-14 14:42:37,028 Epoch: [241][290/500] Time 0.030 (0.028) Data 0.001 (0.003) Loss 0.0262 (0.0371) Prec@1 93.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:42:37,358 Epoch: [241][300/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0337 (0.0370) Prec@1 95.000 (93.871) Prec@5 99.000 (99.806) +2022-11-14 14:42:37,681 Epoch: [241][310/500] Time 0.030 (0.028) Data 0.001 (0.002) Loss 0.0227 (0.0365) Prec@1 98.000 (94.000) Prec@5 100.000 (99.812) +2022-11-14 14:42:38,003 Epoch: [241][320/500] Time 0.029 (0.028) Data 0.002 (0.002) Loss 0.0348 (0.0365) Prec@1 94.000 (94.000) Prec@5 99.000 (99.788) +2022-11-14 14:42:38,322 Epoch: [241][330/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.0484 (0.0368) Prec@1 91.000 (93.912) Prec@5 100.000 (99.794) +2022-11-14 14:42:38,647 Epoch: [241][340/500] Time 0.030 (0.028) Data 0.002 (0.002) Loss 0.0596 (0.0375) Prec@1 91.000 (93.829) Prec@5 99.000 (99.771) +2022-11-14 14:42:38,968 Epoch: [241][350/500] Time 0.028 (0.028) Data 0.003 (0.002) Loss 0.0305 (0.0373) Prec@1 94.000 (93.833) Prec@5 100.000 (99.778) +2022-11-14 14:42:39,288 Epoch: [241][360/500] Time 0.030 (0.028) Data 0.001 (0.002) Loss 0.0525 (0.0377) Prec@1 94.000 (93.838) Prec@5 100.000 (99.784) +2022-11-14 14:42:39,695 Epoch: [241][370/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0478 (0.0380) Prec@1 90.000 (93.737) Prec@5 100.000 (99.789) +2022-11-14 14:42:40,174 Epoch: [241][380/500] Time 0.044 (0.029) Data 0.002 (0.002) Loss 0.0322 (0.0378) Prec@1 95.000 (93.769) Prec@5 100.000 (99.795) +2022-11-14 14:42:40,652 Epoch: [241][390/500] Time 0.042 (0.029) Data 0.002 (0.002) Loss 0.0539 (0.0382) Prec@1 91.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 14:42:41,129 Epoch: [241][400/500] Time 0.042 (0.029) Data 0.002 (0.002) Loss 0.0388 (0.0382) Prec@1 94.000 (93.707) Prec@5 100.000 (99.805) +2022-11-14 14:42:41,604 Epoch: [241][410/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0378 (0.0382) Prec@1 92.000 (93.667) Prec@5 100.000 (99.810) +2022-11-14 14:42:42,078 Epoch: [241][420/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0557 (0.0386) Prec@1 91.000 (93.605) Prec@5 100.000 (99.814) +2022-11-14 14:42:42,553 Epoch: [241][430/500] Time 0.042 (0.030) Data 0.002 (0.002) Loss 0.0434 (0.0387) Prec@1 91.000 (93.545) Prec@5 99.000 (99.795) +2022-11-14 14:42:43,028 Epoch: [241][440/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0727 (0.0395) Prec@1 88.000 (93.422) Prec@5 100.000 (99.800) +2022-11-14 14:42:43,505 Epoch: [241][450/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0410 (0.0395) Prec@1 92.000 (93.391) Prec@5 100.000 (99.804) +2022-11-14 14:42:43,980 Epoch: [241][460/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0346 (0.0394) Prec@1 94.000 (93.404) Prec@5 100.000 (99.809) +2022-11-14 14:42:44,456 Epoch: [241][470/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0413 (0.0395) Prec@1 93.000 (93.396) Prec@5 100.000 (99.812) +2022-11-14 14:42:44,932 Epoch: [241][480/500] Time 0.050 (0.032) Data 0.002 (0.002) Loss 0.0305 (0.0393) Prec@1 93.000 (93.388) Prec@5 100.000 (99.816) +2022-11-14 14:42:45,412 Epoch: [241][490/500] Time 0.057 (0.032) Data 0.002 (0.002) Loss 0.0252 (0.0390) Prec@1 95.000 (93.420) Prec@5 100.000 (99.820) +2022-11-14 14:42:45,838 Epoch: [241][499/500] Time 0.043 (0.032) Data 0.001 (0.002) Loss 0.0267 (0.0387) Prec@1 95.000 (93.451) Prec@5 100.000 (99.824) +2022-11-14 14:42:46,129 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0503 (0.0503) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:46,142 Test: [1/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.0567 (0.0535) Prec@1 91.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 14:42:46,153 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0869 (0.0646) Prec@1 85.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:42:46,169 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0776 (0.0679) Prec@1 87.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 14:42:46,179 Test: [4/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0844 (0.0712) Prec@1 86.000 (87.800) Prec@5 100.000 (99.600) +2022-11-14 14:42:46,187 Test: [5/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0445 (0.0667) Prec@1 92.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 14:42:46,195 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0587 (0.0656) Prec@1 90.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 14:42:46,209 Test: [7/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0668 (0.0657) Prec@1 89.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 14:42:46,220 Test: [8/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0711 (0.0663) Prec@1 89.000 (88.778) Prec@5 99.000 (99.667) +2022-11-14 14:42:46,229 Test: [9/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0624 (0.0659) Prec@1 90.000 (88.900) Prec@5 99.000 (99.600) +2022-11-14 14:42:46,238 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0433 (0.0639) Prec@1 94.000 (89.364) Prec@5 100.000 (99.636) +2022-11-14 14:42:46,248 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.0661) Prec@1 86.000 (89.083) Prec@5 98.000 (99.500) +2022-11-14 14:42:46,259 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0528 (0.0651) Prec@1 90.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 14:42:46,268 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0667) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:42:46,278 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0671) Prec@1 89.000 (89.000) Prec@5 99.000 (99.467) +2022-11-14 14:42:46,287 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0466 (0.0658) Prec@1 92.000 (89.188) Prec@5 100.000 (99.500) +2022-11-14 14:42:46,297 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0420 (0.0644) Prec@1 95.000 (89.529) Prec@5 99.000 (99.471) +2022-11-14 14:42:46,308 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1258 (0.0678) Prec@1 80.000 (89.000) Prec@5 98.000 (99.389) +2022-11-14 14:42:46,318 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0686) Prec@1 84.000 (88.737) Prec@5 98.000 (99.316) +2022-11-14 14:42:46,329 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0693) Prec@1 87.000 (88.650) Prec@5 97.000 (99.200) +2022-11-14 14:42:46,339 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0705) Prec@1 85.000 (88.476) Prec@5 100.000 (99.238) +2022-11-14 14:42:46,350 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0704) Prec@1 89.000 (88.500) Prec@5 100.000 (99.273) +2022-11-14 14:42:46,360 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0719) Prec@1 85.000 (88.348) Prec@5 97.000 (99.174) +2022-11-14 14:42:46,371 Test: [23/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0719) Prec@1 86.000 (88.250) Prec@5 100.000 (99.208) +2022-11-14 14:42:46,381 Test: [24/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0728) Prec@1 86.000 (88.160) Prec@5 100.000 (99.240) +2022-11-14 14:42:46,392 Test: [25/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0738) Prec@1 83.000 (87.962) Prec@5 98.000 (99.192) +2022-11-14 14:42:46,402 Test: [26/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0732) Prec@1 92.000 (88.111) Prec@5 100.000 (99.222) +2022-11-14 14:42:46,412 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0729) Prec@1 89.000 (88.143) Prec@5 100.000 (99.250) +2022-11-14 14:42:46,423 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0729) Prec@1 84.000 (88.000) Prec@5 100.000 (99.276) +2022-11-14 14:42:46,433 Test: [29/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0724) Prec@1 92.000 (88.133) Prec@5 99.000 (99.267) +2022-11-14 14:42:46,443 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0724) Prec@1 88.000 (88.129) Prec@5 100.000 (99.290) +2022-11-14 14:42:46,454 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0725) Prec@1 89.000 (88.156) Prec@5 98.000 (99.250) +2022-11-14 14:42:46,464 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0728) Prec@1 87.000 (88.121) Prec@5 99.000 (99.242) +2022-11-14 14:42:46,475 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0732) Prec@1 84.000 (88.000) Prec@5 99.000 (99.235) +2022-11-14 14:42:46,485 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0737) Prec@1 85.000 (87.914) Prec@5 97.000 (99.171) +2022-11-14 14:42:46,496 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0732) Prec@1 92.000 (88.028) Prec@5 100.000 (99.194) +2022-11-14 14:42:46,506 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0734) Prec@1 88.000 (88.027) Prec@5 99.000 (99.189) +2022-11-14 14:42:46,515 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0740) Prec@1 82.000 (87.868) Prec@5 100.000 (99.211) +2022-11-14 14:42:46,524 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0737) Prec@1 91.000 (87.949) Prec@5 99.000 (99.205) +2022-11-14 14:42:46,535 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0734) Prec@1 90.000 (88.000) Prec@5 98.000 (99.175) +2022-11-14 14:42:46,544 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0738) Prec@1 86.000 (87.951) Prec@5 99.000 (99.171) +2022-11-14 14:42:46,554 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0736) Prec@1 89.000 (87.976) Prec@5 99.000 (99.167) +2022-11-14 14:42:46,565 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0731) Prec@1 93.000 (88.093) Prec@5 98.000 (99.140) +2022-11-14 14:42:46,575 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0729) Prec@1 89.000 (88.114) Prec@5 98.000 (99.114) +2022-11-14 14:42:46,586 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0724) Prec@1 93.000 (88.222) Prec@5 100.000 (99.133) +2022-11-14 14:42:46,596 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0723) Prec@1 89.000 (88.239) Prec@5 99.000 (99.130) +2022-11-14 14:42:46,607 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0720) Prec@1 89.000 (88.255) Prec@5 100.000 (99.149) +2022-11-14 14:42:46,616 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0722) Prec@1 84.000 (88.167) Prec@5 99.000 (99.146) +2022-11-14 14:42:46,628 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0719) Prec@1 91.000 (88.224) Prec@5 99.000 (99.143) +2022-11-14 14:42:46,638 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0726) Prec@1 83.000 (88.120) Prec@5 99.000 (99.140) +2022-11-14 14:42:46,649 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0728) Prec@1 85.000 (88.059) Prec@5 99.000 (99.137) +2022-11-14 14:42:46,660 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0730) Prec@1 86.000 (88.019) Prec@5 100.000 (99.154) +2022-11-14 14:42:46,669 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0728) Prec@1 90.000 (88.057) Prec@5 99.000 (99.151) +2022-11-14 14:42:46,679 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0728) Prec@1 86.000 (88.019) Prec@5 100.000 (99.167) +2022-11-14 14:42:46,689 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0732) Prec@1 84.000 (87.945) Prec@5 100.000 (99.182) +2022-11-14 14:42:46,698 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0734) Prec@1 88.000 (87.946) Prec@5 99.000 (99.179) +2022-11-14 14:42:46,709 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0732) Prec@1 88.000 (87.947) Prec@5 100.000 (99.193) +2022-11-14 14:42:46,719 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0730) Prec@1 92.000 (88.017) Prec@5 100.000 (99.207) +2022-11-14 14:42:46,730 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0734) Prec@1 83.000 (87.932) Prec@5 99.000 (99.203) +2022-11-14 14:42:46,739 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0740) Prec@1 84.000 (87.867) Prec@5 98.000 (99.183) +2022-11-14 14:42:46,749 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0739) Prec@1 91.000 (87.918) Prec@5 99.000 (99.180) +2022-11-14 14:42:46,760 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0740) Prec@1 83.000 (87.839) Prec@5 99.000 (99.177) +2022-11-14 14:42:46,770 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0741) Prec@1 85.000 (87.794) Prec@5 99.000 (99.175) +2022-11-14 14:42:46,781 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0736) Prec@1 93.000 (87.875) Prec@5 100.000 (99.188) +2022-11-14 14:42:46,791 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0738) Prec@1 87.000 (87.862) Prec@5 99.000 (99.185) +2022-11-14 14:42:46,801 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0738) Prec@1 81.000 (87.758) Prec@5 99.000 (99.182) +2022-11-14 14:42:46,811 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0302 (0.0732) Prec@1 95.000 (87.866) Prec@5 100.000 (99.194) +2022-11-14 14:42:46,822 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0733) Prec@1 85.000 (87.824) Prec@5 100.000 (99.206) +2022-11-14 14:42:46,832 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0729) Prec@1 93.000 (87.899) Prec@5 100.000 (99.217) +2022-11-14 14:42:46,842 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0730) Prec@1 86.000 (87.871) Prec@5 99.000 (99.214) +2022-11-14 14:42:46,852 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0732) Prec@1 86.000 (87.845) Prec@5 99.000 (99.211) +2022-11-14 14:42:46,863 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0728) Prec@1 92.000 (87.903) Prec@5 99.000 (99.208) +2022-11-14 14:42:46,872 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0725) Prec@1 94.000 (87.986) Prec@5 100.000 (99.219) +2022-11-14 14:42:46,882 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0721) Prec@1 94.000 (88.068) Prec@5 100.000 (99.230) +2022-11-14 14:42:46,893 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0725) Prec@1 82.000 (87.987) Prec@5 99.000 (99.227) +2022-11-14 14:42:46,904 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0724) Prec@1 90.000 (88.013) Prec@5 98.000 (99.211) +2022-11-14 14:42:46,914 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0723) Prec@1 87.000 (88.000) Prec@5 99.000 (99.208) +2022-11-14 14:42:46,924 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0727) Prec@1 84.000 (87.949) Prec@5 97.000 (99.179) +2022-11-14 14:42:46,936 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0727) Prec@1 91.000 (87.987) Prec@5 100.000 (99.190) +2022-11-14 14:42:46,946 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0730) Prec@1 84.000 (87.938) Prec@5 99.000 (99.188) +2022-11-14 14:42:46,956 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0730) Prec@1 88.000 (87.938) Prec@5 99.000 (99.185) +2022-11-14 14:42:46,967 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0732) Prec@1 85.000 (87.902) Prec@5 100.000 (99.195) +2022-11-14 14:42:46,977 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0733) Prec@1 87.000 (87.892) Prec@5 99.000 (99.193) +2022-11-14 14:42:46,987 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0731) Prec@1 91.000 (87.929) Prec@5 100.000 (99.202) +2022-11-14 14:42:46,998 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0733) Prec@1 85.000 (87.894) Prec@5 99.000 (99.200) +2022-11-14 14:42:47,010 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0735) Prec@1 85.000 (87.860) Prec@5 100.000 (99.209) +2022-11-14 14:42:47,022 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0734) Prec@1 87.000 (87.851) Prec@5 100.000 (99.218) +2022-11-14 14:42:47,034 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0736) Prec@1 87.000 (87.841) Prec@5 98.000 (99.205) +2022-11-14 14:42:47,048 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0736) Prec@1 88.000 (87.843) Prec@5 100.000 (99.213) +2022-11-14 14:42:47,064 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0735) Prec@1 90.000 (87.867) Prec@5 99.000 (99.211) +2022-11-14 14:42:47,078 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0734) Prec@1 92.000 (87.912) Prec@5 100.000 (99.220) +2022-11-14 14:42:47,091 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0730) Prec@1 93.000 (87.967) Prec@5 99.000 (99.217) +2022-11-14 14:42:47,104 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0732) Prec@1 87.000 (87.957) Prec@5 100.000 (99.226) +2022-11-14 14:42:47,119 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0732) Prec@1 88.000 (87.957) Prec@5 99.000 (99.223) +2022-11-14 14:42:47,132 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0731) Prec@1 91.000 (87.989) Prec@5 99.000 (99.221) +2022-11-14 14:42:47,146 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0730) Prec@1 87.000 (87.979) Prec@5 99.000 (99.219) +2022-11-14 14:42:47,161 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0728) Prec@1 91.000 (88.010) Prec@5 99.000 (99.216) +2022-11-14 14:42:47,177 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0730) Prec@1 86.000 (87.990) Prec@5 99.000 (99.214) +2022-11-14 14:42:47,193 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0732) Prec@1 83.000 (87.939) Prec@5 100.000 (99.222) +2022-11-14 14:42:47,209 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0733) Prec@1 86.000 (87.920) Prec@5 100.000 (99.230) +2022-11-14 14:42:47,268 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:42:47,582 Epoch: [242][0/500] Time 0.026 (0.026) Data 0.227 (0.227) Loss 0.0462 (0.0462) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:42:47,793 Epoch: [242][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0430 (0.0446) Prec@1 94.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 14:42:47,999 Epoch: [242][20/500] Time 0.018 (0.019) Data 0.001 (0.013) Loss 0.0428 (0.0440) Prec@1 91.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 14:42:48,263 Epoch: [242][30/500] Time 0.027 (0.020) Data 0.002 (0.009) Loss 0.0261 (0.0395) Prec@1 96.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:42:48,573 Epoch: [242][40/500] Time 0.029 (0.022) Data 0.002 (0.007) Loss 0.0390 (0.0394) Prec@1 95.000 (93.600) Prec@5 99.000 (99.600) +2022-11-14 14:42:48,890 Epoch: [242][50/500] Time 0.034 (0.023) Data 0.002 (0.006) Loss 0.0296 (0.0378) Prec@1 94.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:42:49,194 Epoch: [242][60/500] Time 0.028 (0.024) Data 0.002 (0.006) Loss 0.0224 (0.0356) Prec@1 97.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:42:49,509 Epoch: [242][70/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0195 (0.0336) Prec@1 98.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 14:42:49,820 Epoch: [242][80/500] Time 0.027 (0.025) Data 0.002 (0.005) Loss 0.0482 (0.0352) Prec@1 90.000 (94.111) Prec@5 100.000 (99.778) +2022-11-14 14:42:50,130 Epoch: [242][90/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0422 (0.0359) Prec@1 95.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:42:50,441 Epoch: [242][100/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0137 (0.0339) Prec@1 98.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 14:42:50,751 Epoch: [242][110/500] Time 0.028 (0.025) Data 0.002 (0.004) Loss 0.0197 (0.0327) Prec@1 96.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 14:42:51,061 Epoch: [242][120/500] Time 0.025 (0.026) Data 0.002 (0.004) Loss 0.0250 (0.0321) Prec@1 96.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 14:42:51,401 Epoch: [242][130/500] Time 0.050 (0.026) Data 0.002 (0.003) Loss 0.0371 (0.0325) Prec@1 94.000 (94.714) Prec@5 99.000 (99.786) +2022-11-14 14:42:51,872 Epoch: [242][140/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0371 (0.0328) Prec@1 92.000 (94.533) Prec@5 99.000 (99.733) +2022-11-14 14:42:52,339 Epoch: [242][150/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0526 (0.0340) Prec@1 92.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 14:42:52,807 Epoch: [242][160/500] Time 0.043 (0.029) Data 0.002 (0.003) Loss 0.0364 (0.0342) Prec@1 92.000 (94.235) Prec@5 100.000 (99.765) +2022-11-14 14:42:53,273 Epoch: [242][170/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0429 (0.0346) Prec@1 90.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 14:42:53,742 Epoch: [242][180/500] Time 0.042 (0.030) Data 0.003 (0.003) Loss 0.0329 (0.0345) Prec@1 93.000 (93.947) Prec@5 100.000 (99.789) +2022-11-14 14:42:54,217 Epoch: [242][190/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0300 (0.0343) Prec@1 95.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 14:42:54,690 Epoch: [242][200/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0336 (0.0343) Prec@1 93.000 (93.952) Prec@5 100.000 (99.810) +2022-11-14 14:42:55,164 Epoch: [242][210/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0239 (0.0338) Prec@1 97.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 14:42:55,637 Epoch: [242][220/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0364 (0.0339) Prec@1 93.000 (94.043) Prec@5 100.000 (99.826) +2022-11-14 14:42:56,108 Epoch: [242][230/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0179 (0.0333) Prec@1 98.000 (94.208) Prec@5 100.000 (99.833) +2022-11-14 14:42:56,581 Epoch: [242][240/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0354 (0.0333) Prec@1 94.000 (94.200) Prec@5 100.000 (99.840) +2022-11-14 14:42:57,051 Epoch: [242][250/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0327 (0.0333) Prec@1 95.000 (94.231) Prec@5 100.000 (99.846) +2022-11-14 14:42:57,526 Epoch: [242][260/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0427 (0.0337) Prec@1 92.000 (94.148) Prec@5 100.000 (99.852) +2022-11-14 14:42:57,996 Epoch: [242][270/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0371 (0.0338) Prec@1 95.000 (94.179) Prec@5 100.000 (99.857) +2022-11-14 14:42:58,470 Epoch: [242][280/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0516 (0.0344) Prec@1 92.000 (94.103) Prec@5 99.000 (99.828) +2022-11-14 14:42:58,941 Epoch: [242][290/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0367 (0.0345) Prec@1 94.000 (94.100) Prec@5 100.000 (99.833) +2022-11-14 14:42:59,415 Epoch: [242][300/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0296 (0.0343) Prec@1 95.000 (94.129) Prec@5 100.000 (99.839) +2022-11-14 14:42:59,889 Epoch: [242][310/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0356 (0.0344) Prec@1 94.000 (94.125) Prec@5 100.000 (99.844) +2022-11-14 14:43:00,365 Epoch: [242][320/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0314 (0.0343) Prec@1 94.000 (94.121) Prec@5 100.000 (99.848) +2022-11-14 14:43:00,830 Epoch: [242][330/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0570 (0.0349) Prec@1 88.000 (93.941) Prec@5 100.000 (99.853) +2022-11-14 14:43:01,300 Epoch: [242][340/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0494 (0.0354) Prec@1 94.000 (93.943) Prec@5 100.000 (99.857) +2022-11-14 14:43:01,772 Epoch: [242][350/500] Time 0.043 (0.036) Data 0.001 (0.003) Loss 0.0227 (0.0350) Prec@1 97.000 (94.028) Prec@5 100.000 (99.861) +2022-11-14 14:43:02,244 Epoch: [242][360/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0482 (0.0354) Prec@1 92.000 (93.973) Prec@5 100.000 (99.865) +2022-11-14 14:43:02,710 Epoch: [242][370/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0268 (0.0351) Prec@1 95.000 (94.000) Prec@5 99.000 (99.842) +2022-11-14 14:43:03,182 Epoch: [242][380/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0585 (0.0357) Prec@1 90.000 (93.897) Prec@5 100.000 (99.846) +2022-11-14 14:43:03,656 Epoch: [242][390/500] Time 0.039 (0.037) Data 0.002 (0.002) Loss 0.0193 (0.0353) Prec@1 97.000 (93.975) Prec@5 100.000 (99.850) +2022-11-14 14:43:04,127 Epoch: [242][400/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0582 (0.0359) Prec@1 91.000 (93.902) Prec@5 99.000 (99.829) +2022-11-14 14:43:04,602 Epoch: [242][410/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0104 (0.0353) Prec@1 99.000 (94.024) Prec@5 100.000 (99.833) +2022-11-14 14:43:05,074 Epoch: [242][420/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0505 (0.0356) Prec@1 92.000 (93.977) Prec@5 100.000 (99.837) +2022-11-14 14:43:05,548 Epoch: [242][430/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0312 (0.0355) Prec@1 94.000 (93.977) Prec@5 99.000 (99.818) +2022-11-14 14:43:06,020 Epoch: [242][440/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0272 (0.0353) Prec@1 95.000 (94.000) Prec@5 100.000 (99.822) +2022-11-14 14:43:06,493 Epoch: [242][450/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0371 (0.0354) Prec@1 94.000 (94.000) Prec@5 100.000 (99.826) +2022-11-14 14:43:06,965 Epoch: [242][460/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0365 (0.0354) Prec@1 93.000 (93.979) Prec@5 99.000 (99.809) +2022-11-14 14:43:07,430 Epoch: [242][470/500] Time 0.050 (0.037) Data 0.002 (0.002) Loss 0.0395 (0.0355) Prec@1 90.000 (93.896) Prec@5 100.000 (99.812) +2022-11-14 14:43:07,902 Epoch: [242][480/500] Time 0.051 (0.038) Data 0.002 (0.002) Loss 0.0261 (0.0353) Prec@1 97.000 (93.959) Prec@5 100.000 (99.816) +2022-11-14 14:43:08,375 Epoch: [242][490/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0431 (0.0355) Prec@1 91.000 (93.900) Prec@5 99.000 (99.800) +2022-11-14 14:43:08,793 Epoch: [242][499/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0212 (0.0352) Prec@1 96.000 (93.941) Prec@5 100.000 (99.804) +2022-11-14 14:43:09,059 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0636 (0.0636) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:09,068 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0660) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:43:09,077 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0648) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:09,088 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0672) Prec@1 88.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 14:43:09,101 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0685) Prec@1 90.000 (89.600) Prec@5 99.000 (99.600) +2022-11-14 14:43:09,111 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0658) Prec@1 94.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 14:43:09,121 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0643) Prec@1 94.000 (90.857) Prec@5 100.000 (99.714) +2022-11-14 14:43:09,131 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0666) Prec@1 85.000 (90.125) Prec@5 98.000 (99.500) +2022-11-14 14:43:09,143 Test: [8/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0678) Prec@1 88.000 (89.889) Prec@5 99.000 (99.444) +2022-11-14 14:43:09,153 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0689) Prec@1 87.000 (89.600) Prec@5 99.000 (99.400) +2022-11-14 14:43:09,164 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0694) Prec@1 89.000 (89.545) Prec@5 100.000 (99.455) +2022-11-14 14:43:09,175 Test: [11/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0713) Prec@1 83.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:43:09,185 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0692) Prec@1 92.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 14:43:09,193 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0691) Prec@1 91.000 (89.357) Prec@5 100.000 (99.571) +2022-11-14 14:43:09,202 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0697) Prec@1 87.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 14:43:09,211 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0700) Prec@1 86.000 (89.000) Prec@5 99.000 (99.562) +2022-11-14 14:43:09,220 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0683) Prec@1 93.000 (89.235) Prec@5 99.000 (99.529) +2022-11-14 14:43:09,231 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0706) Prec@1 82.000 (88.833) Prec@5 100.000 (99.556) +2022-11-14 14:43:09,241 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0714) Prec@1 85.000 (88.632) Prec@5 97.000 (99.421) +2022-11-14 14:43:09,252 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0732) Prec@1 83.000 (88.350) Prec@5 98.000 (99.350) +2022-11-14 14:43:09,261 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0741) Prec@1 85.000 (88.190) Prec@5 100.000 (99.381) +2022-11-14 14:43:09,271 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0740) Prec@1 86.000 (88.091) Prec@5 100.000 (99.409) +2022-11-14 14:43:09,281 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0754) Prec@1 84.000 (87.913) Prec@5 97.000 (99.304) +2022-11-14 14:43:09,291 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0748) Prec@1 90.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 14:43:09,301 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0758) Prec@1 84.000 (87.840) Prec@5 100.000 (99.360) +2022-11-14 14:43:09,311 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0764) Prec@1 86.000 (87.769) Prec@5 99.000 (99.346) +2022-11-14 14:43:09,321 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0761) Prec@1 88.000 (87.778) Prec@5 100.000 (99.370) +2022-11-14 14:43:09,333 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0762) Prec@1 87.000 (87.750) Prec@5 100.000 (99.393) +2022-11-14 14:43:09,344 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0756) Prec@1 93.000 (87.931) Prec@5 98.000 (99.345) +2022-11-14 14:43:09,354 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0755) Prec@1 90.000 (88.000) Prec@5 98.000 (99.300) +2022-11-14 14:43:09,363 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0752) Prec@1 88.000 (88.000) Prec@5 100.000 (99.323) +2022-11-14 14:43:09,375 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0745) Prec@1 91.000 (88.094) Prec@5 99.000 (99.312) +2022-11-14 14:43:09,386 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0743) Prec@1 90.000 (88.152) Prec@5 100.000 (99.333) +2022-11-14 14:43:09,397 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0742) Prec@1 87.000 (88.118) Prec@5 99.000 (99.324) +2022-11-14 14:43:09,406 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0747) Prec@1 85.000 (88.029) Prec@5 98.000 (99.286) +2022-11-14 14:43:09,419 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0743) Prec@1 90.000 (88.083) Prec@5 100.000 (99.306) +2022-11-14 14:43:09,430 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0746) Prec@1 86.000 (88.027) Prec@5 98.000 (99.270) +2022-11-14 14:43:09,441 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0750) Prec@1 88.000 (88.026) Prec@5 100.000 (99.289) +2022-11-14 14:43:09,452 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0751) Prec@1 89.000 (88.051) Prec@5 99.000 (99.282) +2022-11-14 14:43:09,464 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0749) Prec@1 90.000 (88.100) Prec@5 99.000 (99.275) +2022-11-14 14:43:09,476 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0752) Prec@1 88.000 (88.098) Prec@5 99.000 (99.268) +2022-11-14 14:43:09,486 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0750) Prec@1 88.000 (88.095) Prec@5 100.000 (99.286) +2022-11-14 14:43:09,497 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0444 (0.0743) Prec@1 94.000 (88.233) Prec@5 99.000 (99.279) +2022-11-14 14:43:09,509 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0745) Prec@1 88.000 (88.227) Prec@5 98.000 (99.250) +2022-11-14 14:43:09,520 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0744) Prec@1 89.000 (88.244) Prec@5 98.000 (99.222) +2022-11-14 14:43:09,529 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0747) Prec@1 85.000 (88.174) Prec@5 100.000 (99.239) +2022-11-14 14:43:09,539 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0745) Prec@1 88.000 (88.170) Prec@5 100.000 (99.255) +2022-11-14 14:43:09,551 Test: [47/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0749) Prec@1 82.000 (88.042) Prec@5 99.000 (99.250) +2022-11-14 14:43:09,563 Test: [48/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0745) Prec@1 90.000 (88.082) Prec@5 99.000 (99.245) +2022-11-14 14:43:09,574 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0753) Prec@1 85.000 (88.020) Prec@5 99.000 (99.240) +2022-11-14 14:43:09,584 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0484 (0.0747) Prec@1 92.000 (88.098) Prec@5 100.000 (99.255) +2022-11-14 14:43:09,594 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0751) Prec@1 84.000 (88.019) Prec@5 99.000 (99.250) +2022-11-14 14:43:09,605 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0747) Prec@1 93.000 (88.113) Prec@5 100.000 (99.264) +2022-11-14 14:43:09,615 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0748) Prec@1 88.000 (88.111) Prec@5 99.000 (99.259) +2022-11-14 14:43:09,625 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0749) Prec@1 87.000 (88.091) Prec@5 100.000 (99.273) +2022-11-14 14:43:09,636 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0748) Prec@1 90.000 (88.125) Prec@5 99.000 (99.268) +2022-11-14 14:43:09,648 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0746) Prec@1 88.000 (88.123) Prec@5 100.000 (99.281) +2022-11-14 14:43:09,660 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0746) Prec@1 88.000 (88.121) Prec@5 100.000 (99.293) +2022-11-14 14:43:09,670 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0750) Prec@1 84.000 (88.051) Prec@5 99.000 (99.288) +2022-11-14 14:43:09,681 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0748) Prec@1 89.000 (88.067) Prec@5 99.000 (99.283) +2022-11-14 14:43:09,694 Test: [60/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0750) Prec@1 86.000 (88.033) Prec@5 98.000 (99.262) +2022-11-14 14:43:09,705 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0749) Prec@1 88.000 (88.032) Prec@5 100.000 (99.274) +2022-11-14 14:43:09,715 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0746) Prec@1 91.000 (88.079) Prec@5 100.000 (99.286) +2022-11-14 14:43:09,724 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0742) Prec@1 91.000 (88.125) Prec@5 100.000 (99.297) +2022-11-14 14:43:09,736 Test: [64/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0743) Prec@1 88.000 (88.123) Prec@5 100.000 (99.308) +2022-11-14 14:43:09,747 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0745) Prec@1 87.000 (88.106) Prec@5 99.000 (99.303) +2022-11-14 14:43:09,759 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0741) Prec@1 92.000 (88.164) Prec@5 100.000 (99.313) +2022-11-14 14:43:09,770 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0741) Prec@1 89.000 (88.176) Prec@5 99.000 (99.309) +2022-11-14 14:43:09,783 Test: [68/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0736) Prec@1 93.000 (88.246) Prec@5 99.000 (99.304) +2022-11-14 14:43:09,794 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0735) Prec@1 90.000 (88.271) Prec@5 99.000 (99.300) +2022-11-14 14:43:09,804 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0737) Prec@1 86.000 (88.239) Prec@5 100.000 (99.310) +2022-11-14 14:43:09,815 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0737) Prec@1 90.000 (88.264) Prec@5 99.000 (99.306) +2022-11-14 14:43:09,826 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0733) Prec@1 93.000 (88.329) Prec@5 100.000 (99.315) +2022-11-14 14:43:09,837 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0731) Prec@1 92.000 (88.378) Prec@5 100.000 (99.324) +2022-11-14 14:43:09,848 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0734) Prec@1 79.000 (88.253) Prec@5 99.000 (99.320) +2022-11-14 14:43:09,858 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0733) Prec@1 89.000 (88.263) Prec@5 100.000 (99.329) +2022-11-14 14:43:09,869 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0733) Prec@1 87.000 (88.247) Prec@5 100.000 (99.338) +2022-11-14 14:43:09,878 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0735) Prec@1 84.000 (88.192) Prec@5 99.000 (99.333) +2022-11-14 14:43:09,888 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0737) Prec@1 85.000 (88.152) Prec@5 99.000 (99.329) +2022-11-14 14:43:09,898 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0739) Prec@1 87.000 (88.138) Prec@5 99.000 (99.325) +2022-11-14 14:43:09,907 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0738) Prec@1 90.000 (88.160) Prec@5 98.000 (99.309) +2022-11-14 14:43:09,919 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0737) Prec@1 88.000 (88.159) Prec@5 100.000 (99.317) +2022-11-14 14:43:09,929 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0740) Prec@1 83.000 (88.096) Prec@5 99.000 (99.313) +2022-11-14 14:43:09,939 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0741) Prec@1 84.000 (88.048) Prec@5 99.000 (99.310) +2022-11-14 14:43:09,948 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0743) Prec@1 86.000 (88.024) Prec@5 97.000 (99.282) +2022-11-14 14:43:09,956 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0745) Prec@1 86.000 (88.000) Prec@5 99.000 (99.279) +2022-11-14 14:43:09,965 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0745) Prec@1 85.000 (87.966) Prec@5 98.000 (99.264) +2022-11-14 14:43:09,974 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0744) Prec@1 90.000 (87.989) Prec@5 98.000 (99.250) +2022-11-14 14:43:09,983 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0743) Prec@1 88.000 (87.989) Prec@5 100.000 (99.258) +2022-11-14 14:43:09,993 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0743) Prec@1 90.000 (88.011) Prec@5 99.000 (99.256) +2022-11-14 14:43:10,004 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0742) Prec@1 90.000 (88.033) Prec@5 100.000 (99.264) +2022-11-14 14:43:10,014 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0739) Prec@1 92.000 (88.076) Prec@5 100.000 (99.272) +2022-11-14 14:43:10,025 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0739) Prec@1 87.000 (88.065) Prec@5 99.000 (99.269) +2022-11-14 14:43:10,036 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0739) Prec@1 88.000 (88.064) Prec@5 100.000 (99.277) +2022-11-14 14:43:10,046 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0738) Prec@1 90.000 (88.084) Prec@5 99.000 (99.274) +2022-11-14 14:43:10,056 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0738) Prec@1 88.000 (88.083) Prec@5 98.000 (99.260) +2022-11-14 14:43:10,066 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0736) Prec@1 91.000 (88.113) Prec@5 99.000 (99.258) +2022-11-14 14:43:10,077 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0739) Prec@1 83.000 (88.061) Prec@5 99.000 (99.255) +2022-11-14 14:43:10,087 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0741) Prec@1 86.000 (88.040) Prec@5 100.000 (99.263) +2022-11-14 14:43:10,097 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0741) Prec@1 87.000 (88.030) Prec@5 100.000 (99.270) +2022-11-14 14:43:10,173 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:43:10,484 Epoch: [243][0/500] Time 0.031 (0.031) Data 0.220 (0.220) Loss 0.0297 (0.0297) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:10,694 Epoch: [243][10/500] Time 0.016 (0.020) Data 0.002 (0.022) Loss 0.0513 (0.0405) Prec@1 92.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:10,907 Epoch: [243][20/500] Time 0.015 (0.019) Data 0.002 (0.012) Loss 0.0687 (0.0499) Prec@1 89.000 (92.333) Prec@5 99.000 (99.667) +2022-11-14 14:43:11,113 Epoch: [243][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.0238 (0.0434) Prec@1 97.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:43:11,315 Epoch: [243][40/500] Time 0.017 (0.019) Data 0.001 (0.007) Loss 0.0206 (0.0388) Prec@1 98.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:43:11,562 Epoch: [243][50/500] Time 0.026 (0.019) Data 0.002 (0.006) Loss 0.0684 (0.0437) Prec@1 89.000 (93.500) Prec@5 99.000 (99.667) +2022-11-14 14:43:11,860 Epoch: [243][60/500] Time 0.028 (0.020) Data 0.001 (0.005) Loss 0.0374 (0.0428) Prec@1 95.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 14:43:12,149 Epoch: [243][70/500] Time 0.027 (0.021) Data 0.002 (0.005) Loss 0.0346 (0.0418) Prec@1 92.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 14:43:12,448 Epoch: [243][80/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0319 (0.0407) Prec@1 94.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 14:43:12,740 Epoch: [243][90/500] Time 0.027 (0.022) Data 0.002 (0.004) Loss 0.0402 (0.0407) Prec@1 92.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:43:13,037 Epoch: [243][100/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0299 (0.0397) Prec@1 94.000 (93.455) Prec@5 100.000 (99.818) +2022-11-14 14:43:13,333 Epoch: [243][110/500] Time 0.026 (0.023) Data 0.002 (0.004) Loss 0.0369 (0.0394) Prec@1 94.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 14:43:13,630 Epoch: [243][120/500] Time 0.027 (0.023) Data 0.001 (0.004) Loss 0.0509 (0.0403) Prec@1 92.000 (93.385) Prec@5 99.000 (99.769) +2022-11-14 14:43:13,931 Epoch: [243][130/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0204 (0.0389) Prec@1 97.000 (93.643) Prec@5 100.000 (99.786) +2022-11-14 14:43:14,227 Epoch: [243][140/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0215 (0.0377) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:43:14,524 Epoch: [243][150/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0330 (0.0375) Prec@1 93.000 (93.750) Prec@5 100.000 (99.812) +2022-11-14 14:43:14,818 Epoch: [243][160/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0371 (0.0374) Prec@1 94.000 (93.765) Prec@5 100.000 (99.824) +2022-11-14 14:43:15,111 Epoch: [243][170/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0165 (0.0363) Prec@1 97.000 (93.944) Prec@5 100.000 (99.833) +2022-11-14 14:43:15,411 Epoch: [243][180/500] Time 0.025 (0.024) Data 0.001 (0.003) Loss 0.0483 (0.0369) Prec@1 92.000 (93.842) Prec@5 99.000 (99.789) +2022-11-14 14:43:15,703 Epoch: [243][190/500] Time 0.023 (0.024) Data 0.002 (0.003) Loss 0.0402 (0.0371) Prec@1 94.000 (93.850) Prec@5 100.000 (99.800) +2022-11-14 14:43:15,999 Epoch: [243][200/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0439 (0.0374) Prec@1 91.000 (93.714) Prec@5 99.000 (99.762) +2022-11-14 14:43:16,294 Epoch: [243][210/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0366 (0.0374) Prec@1 95.000 (93.773) Prec@5 100.000 (99.773) +2022-11-14 14:43:16,589 Epoch: [243][220/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0388 (0.0374) Prec@1 92.000 (93.696) Prec@5 100.000 (99.783) +2022-11-14 14:43:16,891 Epoch: [243][230/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0462 (0.0378) Prec@1 92.000 (93.625) Prec@5 100.000 (99.792) +2022-11-14 14:43:17,209 Epoch: [243][240/500] Time 0.038 (0.025) Data 0.002 (0.003) Loss 0.0290 (0.0374) Prec@1 95.000 (93.680) Prec@5 100.000 (99.800) +2022-11-14 14:43:17,673 Epoch: [243][250/500] Time 0.043 (0.025) Data 0.002 (0.003) Loss 0.0384 (0.0375) Prec@1 95.000 (93.731) Prec@5 99.000 (99.769) +2022-11-14 14:43:18,141 Epoch: [243][260/500] Time 0.043 (0.026) Data 0.002 (0.003) Loss 0.0446 (0.0377) Prec@1 91.000 (93.630) Prec@5 99.000 (99.741) +2022-11-14 14:43:18,603 Epoch: [243][270/500] Time 0.044 (0.027) Data 0.002 (0.003) Loss 0.0600 (0.0385) Prec@1 90.000 (93.500) Prec@5 99.000 (99.714) +2022-11-14 14:43:19,064 Epoch: [243][280/500] Time 0.043 (0.027) Data 0.003 (0.003) Loss 0.0337 (0.0384) Prec@1 96.000 (93.586) Prec@5 100.000 (99.724) +2022-11-14 14:43:19,528 Epoch: [243][290/500] Time 0.044 (0.028) Data 0.001 (0.003) Loss 0.0190 (0.0377) Prec@1 97.000 (93.700) Prec@5 100.000 (99.733) +2022-11-14 14:43:19,997 Epoch: [243][300/500] Time 0.043 (0.028) Data 0.002 (0.002) Loss 0.0302 (0.0375) Prec@1 96.000 (93.774) Prec@5 100.000 (99.742) +2022-11-14 14:43:20,457 Epoch: [243][310/500] Time 0.039 (0.029) Data 0.002 (0.002) Loss 0.0448 (0.0377) Prec@1 92.000 (93.719) Prec@5 99.000 (99.719) +2022-11-14 14:43:20,925 Epoch: [243][320/500] Time 0.049 (0.029) Data 0.002 (0.002) Loss 0.0530 (0.0382) Prec@1 91.000 (93.636) Prec@5 99.000 (99.697) +2022-11-14 14:43:21,395 Epoch: [243][330/500] Time 0.051 (0.029) Data 0.002 (0.002) Loss 0.0474 (0.0384) Prec@1 92.000 (93.588) Prec@5 100.000 (99.706) +2022-11-14 14:43:21,859 Epoch: [243][340/500] Time 0.045 (0.030) Data 0.002 (0.002) Loss 0.0417 (0.0385) Prec@1 94.000 (93.600) Prec@5 100.000 (99.714) +2022-11-14 14:43:22,316 Epoch: [243][350/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0228 (0.0381) Prec@1 96.000 (93.667) Prec@5 99.000 (99.694) +2022-11-14 14:43:22,776 Epoch: [243][360/500] Time 0.046 (0.030) Data 0.002 (0.002) Loss 0.0198 (0.0376) Prec@1 97.000 (93.757) Prec@5 100.000 (99.703) +2022-11-14 14:43:23,260 Epoch: [243][370/500] Time 0.037 (0.031) Data 0.002 (0.002) Loss 0.0325 (0.0375) Prec@1 95.000 (93.789) Prec@5 100.000 (99.711) +2022-11-14 14:43:23,719 Epoch: [243][380/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0465 (0.0377) Prec@1 92.000 (93.744) Prec@5 100.000 (99.718) +2022-11-14 14:43:24,179 Epoch: [243][390/500] Time 0.042 (0.031) Data 0.002 (0.002) Loss 0.0372 (0.0377) Prec@1 94.000 (93.750) Prec@5 100.000 (99.725) +2022-11-14 14:43:24,636 Epoch: [243][400/500] Time 0.041 (0.031) Data 0.002 (0.002) Loss 0.0400 (0.0377) Prec@1 93.000 (93.732) Prec@5 99.000 (99.707) +2022-11-14 14:43:25,091 Epoch: [243][410/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0350 (0.0377) Prec@1 94.000 (93.738) Prec@5 100.000 (99.714) +2022-11-14 14:43:25,559 Epoch: [243][420/500] Time 0.045 (0.032) Data 0.002 (0.002) Loss 0.0175 (0.0372) Prec@1 98.000 (93.837) Prec@5 100.000 (99.721) +2022-11-14 14:43:26,015 Epoch: [243][430/500] Time 0.040 (0.032) Data 0.002 (0.002) Loss 0.0306 (0.0371) Prec@1 94.000 (93.841) Prec@5 100.000 (99.727) +2022-11-14 14:43:26,476 Epoch: [243][440/500] Time 0.043 (0.032) Data 0.001 (0.002) Loss 0.0534 (0.0374) Prec@1 91.000 (93.778) Prec@5 99.000 (99.711) +2022-11-14 14:43:26,941 Epoch: [243][450/500] Time 0.041 (0.032) Data 0.002 (0.002) Loss 0.0301 (0.0373) Prec@1 97.000 (93.848) Prec@5 100.000 (99.717) +2022-11-14 14:43:27,396 Epoch: [243][460/500] Time 0.051 (0.033) Data 0.002 (0.002) Loss 0.0322 (0.0372) Prec@1 95.000 (93.872) Prec@5 98.000 (99.681) +2022-11-14 14:43:27,861 Epoch: [243][470/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0210 (0.0368) Prec@1 98.000 (93.958) Prec@5 100.000 (99.688) +2022-11-14 14:43:28,301 Epoch: [243][480/500] Time 0.042 (0.033) Data 0.001 (0.002) Loss 0.0493 (0.0371) Prec@1 91.000 (93.898) Prec@5 100.000 (99.694) +2022-11-14 14:43:28,756 Epoch: [243][490/500] Time 0.043 (0.033) Data 0.001 (0.002) Loss 0.0229 (0.0368) Prec@1 97.000 (93.960) Prec@5 100.000 (99.700) +2022-11-14 14:43:29,171 Epoch: [243][499/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0440 (0.0369) Prec@1 94.000 (93.961) Prec@5 100.000 (99.706) +2022-11-14 14:43:29,458 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0710 (0.0710) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:43:29,469 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0744) Prec@1 88.000 (88.500) Prec@5 99.000 (99.000) +2022-11-14 14:43:29,477 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0715) Prec@1 89.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 14:43:29,489 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0705) Prec@1 90.000 (89.000) Prec@5 99.000 (99.250) +2022-11-14 14:43:29,498 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0696) Prec@1 89.000 (89.000) Prec@5 99.000 (99.200) +2022-11-14 14:43:29,506 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0382 (0.0644) Prec@1 93.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 14:43:29,515 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0635) Prec@1 91.000 (89.857) Prec@5 100.000 (99.429) +2022-11-14 14:43:29,528 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0651) Prec@1 87.000 (89.500) Prec@5 99.000 (99.375) +2022-11-14 14:43:29,536 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0660) Prec@1 87.000 (89.222) Prec@5 99.000 (99.333) +2022-11-14 14:43:29,546 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0679) Prec@1 85.000 (88.800) Prec@5 99.000 (99.300) +2022-11-14 14:43:29,556 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0664) Prec@1 91.000 (89.000) Prec@5 100.000 (99.364) +2022-11-14 14:43:29,566 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0681) Prec@1 85.000 (88.667) Prec@5 98.000 (99.250) +2022-11-14 14:43:29,577 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0669) Prec@1 90.000 (88.769) Prec@5 100.000 (99.308) +2022-11-14 14:43:29,588 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0682) Prec@1 87.000 (88.643) Prec@5 100.000 (99.357) +2022-11-14 14:43:29,600 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0688) Prec@1 90.000 (88.733) Prec@5 99.000 (99.333) +2022-11-14 14:43:29,609 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0701) Prec@1 85.000 (88.500) Prec@5 100.000 (99.375) +2022-11-14 14:43:29,620 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0486 (0.0688) Prec@1 92.000 (88.706) Prec@5 99.000 (99.353) +2022-11-14 14:43:29,630 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1161 (0.0714) Prec@1 83.000 (88.389) Prec@5 99.000 (99.333) +2022-11-14 14:43:29,641 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0725) Prec@1 85.000 (88.211) Prec@5 97.000 (99.211) +2022-11-14 14:43:29,653 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0726) Prec@1 88.000 (88.200) Prec@5 97.000 (99.100) +2022-11-14 14:43:29,663 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0727) Prec@1 88.000 (88.190) Prec@5 99.000 (99.095) +2022-11-14 14:43:29,674 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0741) Prec@1 82.000 (87.909) Prec@5 99.000 (99.091) +2022-11-14 14:43:29,684 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0754) Prec@1 82.000 (87.652) Prec@5 97.000 (99.000) +2022-11-14 14:43:29,695 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0758) Prec@1 86.000 (87.583) Prec@5 99.000 (99.000) +2022-11-14 14:43:29,705 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0761) Prec@1 88.000 (87.600) Prec@5 100.000 (99.040) +2022-11-14 14:43:29,717 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0763) Prec@1 87.000 (87.577) Prec@5 99.000 (99.038) +2022-11-14 14:43:29,727 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0760) Prec@1 88.000 (87.593) Prec@5 100.000 (99.074) +2022-11-14 14:43:29,738 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0751) Prec@1 92.000 (87.750) Prec@5 99.000 (99.071) +2022-11-14 14:43:29,748 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0747) Prec@1 89.000 (87.793) Prec@5 98.000 (99.034) +2022-11-14 14:43:29,760 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0748) Prec@1 88.000 (87.800) Prec@5 99.000 (99.033) +2022-11-14 14:43:29,770 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0744) Prec@1 90.000 (87.871) Prec@5 100.000 (99.065) +2022-11-14 14:43:29,780 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0741) Prec@1 90.000 (87.938) Prec@5 99.000 (99.062) +2022-11-14 14:43:29,792 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0743) Prec@1 87.000 (87.909) Prec@5 100.000 (99.091) +2022-11-14 14:43:29,802 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0752) Prec@1 82.000 (87.735) Prec@5 99.000 (99.088) +2022-11-14 14:43:29,812 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0758) Prec@1 84.000 (87.629) Prec@5 99.000 (99.086) +2022-11-14 14:43:29,823 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0757) Prec@1 90.000 (87.694) Prec@5 99.000 (99.083) +2022-11-14 14:43:29,835 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0759) Prec@1 86.000 (87.649) Prec@5 97.000 (99.027) +2022-11-14 14:43:29,845 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0759) Prec@1 85.000 (87.579) Prec@5 99.000 (99.026) +2022-11-14 14:43:29,856 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0755) Prec@1 92.000 (87.692) Prec@5 99.000 (99.026) +2022-11-14 14:43:29,866 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0754) Prec@1 89.000 (87.725) Prec@5 98.000 (99.000) +2022-11-14 14:43:29,878 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0758) Prec@1 87.000 (87.707) Prec@5 98.000 (98.976) +2022-11-14 14:43:29,888 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0755) Prec@1 89.000 (87.738) Prec@5 100.000 (99.000) +2022-11-14 14:43:29,899 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0748) Prec@1 92.000 (87.837) Prec@5 99.000 (99.000) +2022-11-14 14:43:29,909 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0747) Prec@1 89.000 (87.864) Prec@5 97.000 (98.955) +2022-11-14 14:43:29,920 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0744) Prec@1 91.000 (87.933) Prec@5 99.000 (98.956) +2022-11-14 14:43:29,931 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0747) Prec@1 84.000 (87.848) Prec@5 99.000 (98.957) +2022-11-14 14:43:29,941 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0749) Prec@1 87.000 (87.830) Prec@5 100.000 (98.979) +2022-11-14 14:43:29,952 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0753) Prec@1 84.000 (87.750) Prec@5 98.000 (98.958) +2022-11-14 14:43:29,962 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0752) Prec@1 88.000 (87.755) Prec@5 100.000 (98.980) +2022-11-14 14:43:29,975 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0755) Prec@1 84.000 (87.680) Prec@5 100.000 (99.000) +2022-11-14 14:43:29,985 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0752) Prec@1 89.000 (87.706) Prec@5 100.000 (99.020) +2022-11-14 14:43:29,997 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0749) Prec@1 87.000 (87.692) Prec@5 100.000 (99.038) +2022-11-14 14:43:30,008 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0747) Prec@1 89.000 (87.717) Prec@5 99.000 (99.038) +2022-11-14 14:43:30,018 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0749) Prec@1 87.000 (87.704) Prec@5 99.000 (99.037) +2022-11-14 14:43:30,029 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0750) Prec@1 88.000 (87.709) Prec@5 100.000 (99.055) +2022-11-14 14:43:30,039 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0748) Prec@1 91.000 (87.768) Prec@5 100.000 (99.071) +2022-11-14 14:43:30,051 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0746) Prec@1 88.000 (87.772) Prec@5 98.000 (99.053) +2022-11-14 14:43:30,061 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0745) Prec@1 89.000 (87.793) Prec@5 99.000 (99.052) +2022-11-14 14:43:30,073 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0751) Prec@1 83.000 (87.712) Prec@5 100.000 (99.068) +2022-11-14 14:43:30,085 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0753) Prec@1 83.000 (87.633) Prec@5 100.000 (99.083) +2022-11-14 14:43:30,096 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0754) Prec@1 88.000 (87.639) Prec@5 100.000 (99.098) +2022-11-14 14:43:30,107 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0757) Prec@1 84.000 (87.581) Prec@5 98.000 (99.081) +2022-11-14 14:43:30,118 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0758) Prec@1 86.000 (87.556) Prec@5 100.000 (99.095) +2022-11-14 14:43:30,128 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0752) Prec@1 93.000 (87.641) Prec@5 100.000 (99.109) +2022-11-14 14:43:30,139 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0755) Prec@1 86.000 (87.615) Prec@5 99.000 (99.108) +2022-11-14 14:43:30,148 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0755) Prec@1 88.000 (87.621) Prec@5 100.000 (99.121) +2022-11-14 14:43:30,158 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0750) Prec@1 93.000 (87.701) Prec@5 100.000 (99.134) +2022-11-14 14:43:30,170 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0751) Prec@1 89.000 (87.721) Prec@5 97.000 (99.103) +2022-11-14 14:43:30,180 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0749) Prec@1 92.000 (87.783) Prec@5 100.000 (99.116) +2022-11-14 14:43:30,192 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0748) Prec@1 88.000 (87.786) Prec@5 99.000 (99.114) +2022-11-14 14:43:30,203 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0751) Prec@1 87.000 (87.775) Prec@5 99.000 (99.113) +2022-11-14 14:43:30,213 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0750) Prec@1 87.000 (87.764) Prec@5 100.000 (99.125) +2022-11-14 14:43:30,225 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0746) Prec@1 94.000 (87.849) Prec@5 100.000 (99.137) +2022-11-14 14:43:30,236 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0742) Prec@1 93.000 (87.919) Prec@5 100.000 (99.149) +2022-11-14 14:43:30,245 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0747) Prec@1 82.000 (87.840) Prec@5 99.000 (99.147) +2022-11-14 14:43:30,257 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0744) Prec@1 90.000 (87.868) Prec@5 100.000 (99.158) +2022-11-14 14:43:30,267 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0743) Prec@1 88.000 (87.870) Prec@5 99.000 (99.156) +2022-11-14 14:43:30,279 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0744) Prec@1 87.000 (87.859) Prec@5 97.000 (99.128) +2022-11-14 14:43:30,290 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0744) Prec@1 87.000 (87.848) Prec@5 100.000 (99.139) +2022-11-14 14:43:30,301 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0745) Prec@1 86.000 (87.825) Prec@5 98.000 (99.125) +2022-11-14 14:43:30,313 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0744) Prec@1 90.000 (87.852) Prec@5 100.000 (99.136) +2022-11-14 14:43:30,324 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0746) Prec@1 84.000 (87.805) Prec@5 100.000 (99.146) +2022-11-14 14:43:30,336 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0748) Prec@1 84.000 (87.759) Prec@5 100.000 (99.157) +2022-11-14 14:43:30,347 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0747) Prec@1 87.000 (87.750) Prec@5 98.000 (99.143) +2022-11-14 14:43:30,356 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0747) Prec@1 90.000 (87.776) Prec@5 100.000 (99.153) +2022-11-14 14:43:30,367 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0750) Prec@1 83.000 (87.721) Prec@5 100.000 (99.163) +2022-11-14 14:43:30,379 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0749) Prec@1 90.000 (87.747) Prec@5 100.000 (99.172) +2022-11-14 14:43:30,391 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0748) Prec@1 89.000 (87.761) Prec@5 99.000 (99.170) +2022-11-14 14:43:30,401 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0749) Prec@1 85.000 (87.730) Prec@5 100.000 (99.180) +2022-11-14 14:43:30,412 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0747) Prec@1 91.000 (87.767) Prec@5 98.000 (99.167) +2022-11-14 14:43:30,424 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0745) Prec@1 87.000 (87.758) Prec@5 100.000 (99.176) +2022-11-14 14:43:30,434 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0743) Prec@1 92.000 (87.804) Prec@5 100.000 (99.185) +2022-11-14 14:43:30,445 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0743) Prec@1 87.000 (87.796) Prec@5 100.000 (99.194) +2022-11-14 14:43:30,455 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0743) Prec@1 87.000 (87.787) Prec@5 99.000 (99.191) +2022-11-14 14:43:30,467 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0746) Prec@1 86.000 (87.768) Prec@5 99.000 (99.189) +2022-11-14 14:43:30,476 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0745) Prec@1 88.000 (87.771) Prec@5 100.000 (99.198) +2022-11-14 14:43:30,487 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0742) Prec@1 94.000 (87.835) Prec@5 99.000 (99.196) +2022-11-14 14:43:30,495 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0744) Prec@1 84.000 (87.796) Prec@5 99.000 (99.194) +2022-11-14 14:43:30,506 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0747) Prec@1 86.000 (87.778) Prec@5 99.000 (99.192) +2022-11-14 14:43:30,519 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0747) Prec@1 87.000 (87.770) Prec@5 97.000 (99.170) +2022-11-14 14:43:30,577 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:43:30,891 Epoch: [244][0/500] Time 0.025 (0.025) Data 0.232 (0.232) Loss 0.0144 (0.0144) Prec@1 99.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:31,108 Epoch: [244][10/500] Time 0.017 (0.020) Data 0.001 (0.023) Loss 0.0262 (0.0203) Prec@1 96.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 14:43:31,330 Epoch: [244][20/500] Time 0.022 (0.020) Data 0.001 (0.013) Loss 0.0375 (0.0261) Prec@1 93.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:31,611 Epoch: [244][30/500] Time 0.025 (0.021) Data 0.002 (0.009) Loss 0.0279 (0.0265) Prec@1 94.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 14:43:31,905 Epoch: [244][40/500] Time 0.029 (0.023) Data 0.002 (0.007) Loss 0.0448 (0.0302) Prec@1 92.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 14:43:32,191 Epoch: [244][50/500] Time 0.024 (0.023) Data 0.002 (0.006) Loss 0.0650 (0.0360) Prec@1 90.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 14:43:32,482 Epoch: [244][60/500] Time 0.030 (0.024) Data 0.002 (0.006) Loss 0.0500 (0.0380) Prec@1 91.000 (93.571) Prec@5 99.000 (99.714) +2022-11-14 14:43:32,764 Epoch: [244][70/500] Time 0.026 (0.024) Data 0.002 (0.005) Loss 0.0344 (0.0375) Prec@1 95.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 14:43:33,053 Epoch: [244][80/500] Time 0.026 (0.024) Data 0.001 (0.005) Loss 0.0387 (0.0377) Prec@1 93.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:43:33,336 Epoch: [244][90/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0585 (0.0397) Prec@1 90.000 (93.300) Prec@5 100.000 (99.700) +2022-11-14 14:43:33,622 Epoch: [244][100/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0280 (0.0387) Prec@1 95.000 (93.455) Prec@5 100.000 (99.727) +2022-11-14 14:43:33,913 Epoch: [244][110/500] Time 0.023 (0.024) Data 0.002 (0.004) Loss 0.0247 (0.0375) Prec@1 96.000 (93.667) Prec@5 100.000 (99.750) +2022-11-14 14:43:34,249 Epoch: [244][120/500] Time 0.042 (0.025) Data 0.002 (0.004) Loss 0.0324 (0.0371) Prec@1 94.000 (93.692) Prec@5 100.000 (99.769) +2022-11-14 14:43:34,729 Epoch: [244][130/500] Time 0.042 (0.026) Data 0.002 (0.004) Loss 0.0157 (0.0356) Prec@1 98.000 (94.000) Prec@5 100.000 (99.786) +2022-11-14 14:43:35,223 Epoch: [244][140/500] Time 0.044 (0.027) Data 0.002 (0.003) Loss 0.0275 (0.0350) Prec@1 95.000 (94.067) Prec@5 100.000 (99.800) +2022-11-14 14:43:35,699 Epoch: [244][150/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0516 (0.0361) Prec@1 91.000 (93.875) Prec@5 100.000 (99.812) +2022-11-14 14:43:36,175 Epoch: [244][160/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0558 (0.0372) Prec@1 89.000 (93.588) Prec@5 100.000 (99.824) +2022-11-14 14:43:36,645 Epoch: [244][170/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0448 (0.0377) Prec@1 93.000 (93.556) Prec@5 100.000 (99.833) +2022-11-14 14:43:37,120 Epoch: [244][180/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0384 (0.0377) Prec@1 94.000 (93.579) Prec@5 99.000 (99.789) +2022-11-14 14:43:37,595 Epoch: [244][190/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0265 (0.0371) Prec@1 98.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:43:38,064 Epoch: [244][200/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0432 (0.0374) Prec@1 93.000 (93.762) Prec@5 100.000 (99.810) +2022-11-14 14:43:38,537 Epoch: [244][210/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0389 (0.0375) Prec@1 93.000 (93.727) Prec@5 99.000 (99.773) +2022-11-14 14:43:39,012 Epoch: [244][220/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0298 (0.0372) Prec@1 95.000 (93.783) Prec@5 100.000 (99.783) +2022-11-14 14:43:39,484 Epoch: [244][230/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0408 (0.0373) Prec@1 95.000 (93.833) Prec@5 99.000 (99.750) +2022-11-14 14:43:39,962 Epoch: [244][240/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0307 (0.0370) Prec@1 95.000 (93.880) Prec@5 100.000 (99.760) +2022-11-14 14:43:40,433 Epoch: [244][250/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0377 (0.0371) Prec@1 95.000 (93.923) Prec@5 100.000 (99.769) +2022-11-14 14:43:40,909 Epoch: [244][260/500] Time 0.054 (0.034) Data 0.001 (0.003) Loss 0.0245 (0.0366) Prec@1 98.000 (94.074) Prec@5 100.000 (99.778) +2022-11-14 14:43:41,384 Epoch: [244][270/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0301 (0.0364) Prec@1 96.000 (94.143) Prec@5 100.000 (99.786) +2022-11-14 14:43:41,853 Epoch: [244][280/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0416 (0.0365) Prec@1 92.000 (94.069) Prec@5 100.000 (99.793) +2022-11-14 14:43:42,321 Epoch: [244][290/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0175 (0.0359) Prec@1 96.000 (94.133) Prec@5 100.000 (99.800) +2022-11-14 14:43:42,793 Epoch: [244][300/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0222 (0.0355) Prec@1 97.000 (94.226) Prec@5 100.000 (99.806) +2022-11-14 14:43:43,258 Epoch: [244][310/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0733 (0.0367) Prec@1 89.000 (94.062) Prec@5 100.000 (99.812) +2022-11-14 14:43:43,732 Epoch: [244][320/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0320 (0.0365) Prec@1 94.000 (94.061) Prec@5 99.000 (99.788) +2022-11-14 14:43:44,205 Epoch: [244][330/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0433 (0.0367) Prec@1 92.000 (94.000) Prec@5 100.000 (99.794) +2022-11-14 14:43:44,680 Epoch: [244][340/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0508 (0.0371) Prec@1 92.000 (93.943) Prec@5 100.000 (99.800) +2022-11-14 14:43:45,029 Epoch: [244][350/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0281 (0.0369) Prec@1 96.000 (94.000) Prec@5 100.000 (99.806) +2022-11-14 14:43:45,328 Epoch: [244][360/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.0214 (0.0364) Prec@1 96.000 (94.054) Prec@5 100.000 (99.811) +2022-11-14 14:43:45,630 Epoch: [244][370/500] Time 0.031 (0.035) Data 0.002 (0.003) Loss 0.0344 (0.0364) Prec@1 95.000 (94.079) Prec@5 100.000 (99.816) +2022-11-14 14:43:45,931 Epoch: [244][380/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.0315 (0.0363) Prec@1 96.000 (94.128) Prec@5 100.000 (99.821) +2022-11-14 14:43:46,233 Epoch: [244][390/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.0137 (0.0357) Prec@1 98.000 (94.225) Prec@5 100.000 (99.825) +2022-11-14 14:43:46,537 Epoch: [244][400/500] Time 0.027 (0.035) Data 0.002 (0.002) Loss 0.0470 (0.0360) Prec@1 92.000 (94.171) Prec@5 100.000 (99.829) +2022-11-14 14:43:46,840 Epoch: [244][410/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0621 (0.0366) Prec@1 88.000 (94.024) Prec@5 100.000 (99.833) +2022-11-14 14:43:47,138 Epoch: [244][420/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0240 (0.0363) Prec@1 96.000 (94.070) Prec@5 100.000 (99.837) +2022-11-14 14:43:47,441 Epoch: [244][430/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0455 (0.0365) Prec@1 93.000 (94.045) Prec@5 98.000 (99.795) +2022-11-14 14:43:47,738 Epoch: [244][440/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0536 (0.0369) Prec@1 90.000 (93.956) Prec@5 99.000 (99.778) +2022-11-14 14:43:48,036 Epoch: [244][450/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0307 (0.0368) Prec@1 96.000 (94.000) Prec@5 100.000 (99.783) +2022-11-14 14:43:48,338 Epoch: [244][460/500] Time 0.028 (0.034) Data 0.002 (0.002) Loss 0.0248 (0.0365) Prec@1 97.000 (94.064) Prec@5 99.000 (99.766) +2022-11-14 14:43:48,636 Epoch: [244][470/500] Time 0.027 (0.033) Data 0.001 (0.002) Loss 0.0566 (0.0369) Prec@1 90.000 (93.979) Prec@5 100.000 (99.771) +2022-11-14 14:43:48,940 Epoch: [244][480/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0650 (0.0375) Prec@1 90.000 (93.898) Prec@5 100.000 (99.776) +2022-11-14 14:43:49,237 Epoch: [244][490/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0425 (0.0376) Prec@1 92.000 (93.860) Prec@5 100.000 (99.780) +2022-11-14 14:43:49,506 Epoch: [244][499/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0480 (0.0378) Prec@1 92.000 (93.824) Prec@5 99.000 (99.765) +2022-11-14 14:43:49,789 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0623 (0.0623) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:49,796 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0926 (0.0775) Prec@1 84.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:49,805 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0795) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:43:49,819 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0787) Prec@1 87.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 14:43:49,829 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0773) Prec@1 86.000 (86.800) Prec@5 100.000 (99.800) +2022-11-14 14:43:49,839 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0727) Prec@1 92.000 (87.667) Prec@5 99.000 (99.667) +2022-11-14 14:43:49,849 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0705) Prec@1 91.000 (88.143) Prec@5 99.000 (99.571) +2022-11-14 14:43:49,859 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0721) Prec@1 85.000 (87.750) Prec@5 100.000 (99.625) +2022-11-14 14:43:49,869 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0730) Prec@1 87.000 (87.667) Prec@5 98.000 (99.444) +2022-11-14 14:43:49,880 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0745) Prec@1 85.000 (87.400) Prec@5 97.000 (99.200) +2022-11-14 14:43:49,891 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0740) Prec@1 88.000 (87.455) Prec@5 99.000 (99.182) +2022-11-14 14:43:49,902 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0752) Prec@1 86.000 (87.333) Prec@5 100.000 (99.250) +2022-11-14 14:43:49,913 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0728) Prec@1 92.000 (87.692) Prec@5 99.000 (99.231) +2022-11-14 14:43:49,924 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0732) Prec@1 86.000 (87.571) Prec@5 99.000 (99.214) +2022-11-14 14:43:49,935 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0739) Prec@1 88.000 (87.600) Prec@5 99.000 (99.200) +2022-11-14 14:43:49,948 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0746) Prec@1 84.000 (87.375) Prec@5 100.000 (99.250) +2022-11-14 14:43:49,960 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0731) Prec@1 94.000 (87.765) Prec@5 99.000 (99.235) +2022-11-14 14:43:49,972 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0751) Prec@1 82.000 (87.444) Prec@5 100.000 (99.278) +2022-11-14 14:43:49,985 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0754) Prec@1 85.000 (87.316) Prec@5 100.000 (99.316) +2022-11-14 14:43:49,998 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0761) Prec@1 87.000 (87.300) Prec@5 99.000 (99.300) +2022-11-14 14:43:50,011 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0763) Prec@1 86.000 (87.238) Prec@5 100.000 (99.333) +2022-11-14 14:43:50,021 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0774) Prec@1 84.000 (87.091) Prec@5 98.000 (99.273) +2022-11-14 14:43:50,031 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0781) Prec@1 84.000 (86.957) Prec@5 99.000 (99.261) +2022-11-14 14:43:50,043 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0788) Prec@1 83.000 (86.792) Prec@5 99.000 (99.250) +2022-11-14 14:43:50,054 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0797) Prec@1 83.000 (86.640) Prec@5 100.000 (99.280) +2022-11-14 14:43:50,066 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0800) Prec@1 84.000 (86.538) Prec@5 98.000 (99.231) +2022-11-14 14:43:50,079 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0791) Prec@1 91.000 (86.704) Prec@5 100.000 (99.259) +2022-11-14 14:43:50,091 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0777) Prec@1 93.000 (86.929) Prec@5 100.000 (99.286) +2022-11-14 14:43:50,100 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0778) Prec@1 89.000 (87.000) Prec@5 97.000 (99.207) +2022-11-14 14:43:50,109 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0777) Prec@1 88.000 (87.033) Prec@5 100.000 (99.233) +2022-11-14 14:43:50,118 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0778) Prec@1 87.000 (87.032) Prec@5 100.000 (99.258) +2022-11-14 14:43:50,128 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0778) Prec@1 87.000 (87.031) Prec@5 99.000 (99.250) +2022-11-14 14:43:50,139 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0782) Prec@1 85.000 (86.970) Prec@5 100.000 (99.273) +2022-11-14 14:43:50,152 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0788) Prec@1 83.000 (86.853) Prec@5 99.000 (99.265) +2022-11-14 14:43:50,165 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0792) Prec@1 85.000 (86.800) Prec@5 99.000 (99.257) +2022-11-14 14:43:50,180 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0789) Prec@1 90.000 (86.889) Prec@5 100.000 (99.278) +2022-11-14 14:43:50,193 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0787) Prec@1 87.000 (86.892) Prec@5 98.000 (99.243) +2022-11-14 14:43:50,205 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0792) Prec@1 84.000 (86.816) Prec@5 99.000 (99.237) +2022-11-14 14:43:50,218 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0787) Prec@1 90.000 (86.897) Prec@5 99.000 (99.231) +2022-11-14 14:43:50,230 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0787) Prec@1 88.000 (86.925) Prec@5 99.000 (99.225) +2022-11-14 14:43:50,240 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0788) Prec@1 85.000 (86.878) Prec@5 98.000 (99.195) +2022-11-14 14:43:50,252 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0784) Prec@1 90.000 (86.952) Prec@5 100.000 (99.214) +2022-11-14 14:43:50,266 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0777) Prec@1 93.000 (87.093) Prec@5 99.000 (99.209) +2022-11-14 14:43:50,276 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0772) Prec@1 93.000 (87.227) Prec@5 97.000 (99.159) +2022-11-14 14:43:50,289 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0768) Prec@1 91.000 (87.311) Prec@5 100.000 (99.178) +2022-11-14 14:43:50,300 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0770) Prec@1 85.000 (87.261) Prec@5 99.000 (99.174) +2022-11-14 14:43:50,310 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0767) Prec@1 90.000 (87.319) Prec@5 100.000 (99.191) +2022-11-14 14:43:50,321 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0769) Prec@1 84.000 (87.250) Prec@5 99.000 (99.188) +2022-11-14 14:43:50,332 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0765) Prec@1 90.000 (87.306) Prec@5 100.000 (99.204) +2022-11-14 14:43:50,342 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0766) Prec@1 89.000 (87.340) Prec@5 100.000 (99.220) +2022-11-14 14:43:50,354 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0769) Prec@1 84.000 (87.275) Prec@5 99.000 (99.216) +2022-11-14 14:43:50,363 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0767) Prec@1 89.000 (87.308) Prec@5 100.000 (99.231) +2022-11-14 14:43:50,374 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0766) Prec@1 89.000 (87.340) Prec@5 100.000 (99.245) +2022-11-14 14:43:50,386 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0763) Prec@1 92.000 (87.426) Prec@5 98.000 (99.222) +2022-11-14 14:43:50,398 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0764) Prec@1 87.000 (87.418) Prec@5 100.000 (99.236) +2022-11-14 14:43:50,410 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0764) Prec@1 89.000 (87.446) Prec@5 99.000 (99.232) +2022-11-14 14:43:50,421 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0762) Prec@1 91.000 (87.509) Prec@5 99.000 (99.228) +2022-11-14 14:43:50,433 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0761) Prec@1 89.000 (87.534) Prec@5 98.000 (99.207) +2022-11-14 14:43:50,445 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0765) Prec@1 85.000 (87.492) Prec@5 100.000 (99.220) +2022-11-14 14:43:50,455 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0766) Prec@1 88.000 (87.500) Prec@5 100.000 (99.233) +2022-11-14 14:43:50,467 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0766) Prec@1 89.000 (87.525) Prec@5 98.000 (99.213) +2022-11-14 14:43:50,478 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0766) Prec@1 90.000 (87.565) Prec@5 99.000 (99.210) +2022-11-14 14:43:50,490 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0764) Prec@1 89.000 (87.587) Prec@5 100.000 (99.222) +2022-11-14 14:43:50,503 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0282 (0.0756) Prec@1 95.000 (87.703) Prec@5 100.000 (99.234) +2022-11-14 14:43:50,515 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0756) Prec@1 85.000 (87.662) Prec@5 100.000 (99.246) +2022-11-14 14:43:50,524 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0754) Prec@1 90.000 (87.697) Prec@5 99.000 (99.242) +2022-11-14 14:43:50,536 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0387 (0.0748) Prec@1 94.000 (87.791) Prec@5 99.000 (99.239) +2022-11-14 14:43:50,547 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0748) Prec@1 91.000 (87.838) Prec@5 98.000 (99.221) +2022-11-14 14:43:50,561 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0748) Prec@1 87.000 (87.826) Prec@5 99.000 (99.217) +2022-11-14 14:43:50,574 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0747) Prec@1 89.000 (87.843) Prec@5 100.000 (99.229) +2022-11-14 14:43:50,585 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0751) Prec@1 83.000 (87.775) Prec@5 99.000 (99.225) +2022-11-14 14:43:50,595 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0751) Prec@1 85.000 (87.736) Prec@5 100.000 (99.236) +2022-11-14 14:43:50,608 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0747) Prec@1 92.000 (87.795) Prec@5 99.000 (99.233) +2022-11-14 14:43:50,619 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0744) Prec@1 92.000 (87.851) Prec@5 100.000 (99.243) +2022-11-14 14:43:50,629 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0747) Prec@1 84.000 (87.800) Prec@5 99.000 (99.240) +2022-11-14 14:43:50,643 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0745) Prec@1 89.000 (87.816) Prec@5 98.000 (99.224) +2022-11-14 14:43:50,655 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0746) Prec@1 88.000 (87.818) Prec@5 98.000 (99.208) +2022-11-14 14:43:50,664 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0749) Prec@1 82.000 (87.744) Prec@5 99.000 (99.205) +2022-11-14 14:43:50,675 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0749) Prec@1 87.000 (87.734) Prec@5 99.000 (99.203) +2022-11-14 14:43:50,686 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0747) Prec@1 89.000 (87.750) Prec@5 99.000 (99.200) +2022-11-14 14:43:50,698 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0748) Prec@1 87.000 (87.741) Prec@5 99.000 (99.198) +2022-11-14 14:43:50,710 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0750) Prec@1 85.000 (87.707) Prec@5 100.000 (99.207) +2022-11-14 14:43:50,720 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0752) Prec@1 87.000 (87.699) Prec@5 100.000 (99.217) +2022-11-14 14:43:50,732 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0752) Prec@1 89.000 (87.714) Prec@5 99.000 (99.214) +2022-11-14 14:43:50,744 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0753) Prec@1 85.000 (87.682) Prec@5 99.000 (99.212) +2022-11-14 14:43:50,754 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0757) Prec@1 83.000 (87.628) Prec@5 99.000 (99.209) +2022-11-14 14:43:50,765 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0755) Prec@1 89.000 (87.644) Prec@5 100.000 (99.218) +2022-11-14 14:43:50,776 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0756) Prec@1 86.000 (87.625) Prec@5 99.000 (99.216) +2022-11-14 14:43:50,790 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0756) Prec@1 85.000 (87.596) Prec@5 100.000 (99.225) +2022-11-14 14:43:50,803 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0756) Prec@1 88.000 (87.600) Prec@5 99.000 (99.222) +2022-11-14 14:43:50,815 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0753) Prec@1 94.000 (87.670) Prec@5 100.000 (99.231) +2022-11-14 14:43:50,828 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0463 (0.0750) Prec@1 94.000 (87.739) Prec@5 100.000 (99.239) +2022-11-14 14:43:50,838 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0750) Prec@1 89.000 (87.753) Prec@5 99.000 (99.237) +2022-11-14 14:43:50,849 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0749) Prec@1 90.000 (87.777) Prec@5 98.000 (99.223) +2022-11-14 14:43:50,861 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0752) Prec@1 85.000 (87.747) Prec@5 98.000 (99.211) +2022-11-14 14:43:50,870 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0749) Prec@1 91.000 (87.781) Prec@5 100.000 (99.219) +2022-11-14 14:43:50,880 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0418 (0.0746) Prec@1 94.000 (87.845) Prec@5 99.000 (99.216) +2022-11-14 14:43:50,891 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0749) Prec@1 84.000 (87.806) Prec@5 99.000 (99.214) +2022-11-14 14:43:50,902 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0753) Prec@1 82.000 (87.747) Prec@5 98.000 (99.202) +2022-11-14 14:43:50,915 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0753) Prec@1 88.000 (87.750) Prec@5 100.000 (99.210) +2022-11-14 14:43:50,973 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:43:51,278 Epoch: [245][0/500] Time 0.022 (0.022) Data 0.222 (0.222) Loss 0.0238 (0.0238) Prec@1 97.000 (97.000) Prec@5 99.000 (99.000) +2022-11-14 14:43:51,489 Epoch: [245][10/500] Time 0.018 (0.019) Data 0.001 (0.022) Loss 0.0383 (0.0311) Prec@1 93.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 14:43:51,700 Epoch: [245][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0300 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 14:43:51,999 Epoch: [245][30/500] Time 0.030 (0.021) Data 0.002 (0.009) Loss 0.0310 (0.0308) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 14:43:52,313 Epoch: [245][40/500] Time 0.029 (0.023) Data 0.001 (0.007) Loss 0.0623 (0.0371) Prec@1 88.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:43:52,629 Epoch: [245][50/500] Time 0.031 (0.024) Data 0.001 (0.006) Loss 0.0394 (0.0375) Prec@1 95.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:43:52,950 Epoch: [245][60/500] Time 0.029 (0.025) Data 0.002 (0.005) Loss 0.0188 (0.0348) Prec@1 96.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 14:43:53,264 Epoch: [245][70/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0165 (0.0325) Prec@1 97.000 (94.500) Prec@5 99.000 (99.750) +2022-11-14 14:43:53,579 Epoch: [245][80/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0421 (0.0336) Prec@1 92.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 14:43:53,903 Epoch: [245][90/500] Time 0.035 (0.026) Data 0.002 (0.004) Loss 0.0535 (0.0356) Prec@1 90.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 14:43:54,219 Epoch: [245][100/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0250 (0.0346) Prec@1 95.000 (93.909) Prec@5 100.000 (99.818) +2022-11-14 14:43:54,537 Epoch: [245][110/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0433 (0.0353) Prec@1 93.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:43:54,862 Epoch: [245][120/500] Time 0.031 (0.026) Data 0.002 (0.004) Loss 0.0383 (0.0356) Prec@1 94.000 (93.846) Prec@5 100.000 (99.846) +2022-11-14 14:43:55,175 Epoch: [245][130/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0352 (0.0356) Prec@1 95.000 (93.929) Prec@5 100.000 (99.857) +2022-11-14 14:43:55,491 Epoch: [245][140/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0345 (0.0355) Prec@1 94.000 (93.933) Prec@5 100.000 (99.867) +2022-11-14 14:43:55,802 Epoch: [245][150/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0293 (0.0351) Prec@1 96.000 (94.062) Prec@5 100.000 (99.875) +2022-11-14 14:43:56,127 Epoch: [245][160/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0460 (0.0357) Prec@1 92.000 (93.941) Prec@5 99.000 (99.824) +2022-11-14 14:43:56,448 Epoch: [245][170/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0506 (0.0366) Prec@1 90.000 (93.722) Prec@5 100.000 (99.833) +2022-11-14 14:43:56,762 Epoch: [245][180/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0423 (0.0369) Prec@1 91.000 (93.579) Prec@5 100.000 (99.842) +2022-11-14 14:43:57,085 Epoch: [245][190/500] Time 0.033 (0.027) Data 0.002 (0.003) Loss 0.0354 (0.0368) Prec@1 95.000 (93.650) Prec@5 100.000 (99.850) +2022-11-14 14:43:57,471 Epoch: [245][200/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0247 (0.0362) Prec@1 94.000 (93.667) Prec@5 99.000 (99.810) +2022-11-14 14:43:57,949 Epoch: [245][210/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0324 (0.0360) Prec@1 96.000 (93.773) Prec@5 100.000 (99.818) +2022-11-14 14:43:58,421 Epoch: [245][220/500] Time 0.052 (0.029) Data 0.002 (0.003) Loss 0.0370 (0.0361) Prec@1 93.000 (93.739) Prec@5 100.000 (99.826) +2022-11-14 14:43:58,894 Epoch: [245][230/500] Time 0.049 (0.029) Data 0.002 (0.003) Loss 0.0568 (0.0369) Prec@1 92.000 (93.667) Prec@5 99.000 (99.792) +2022-11-14 14:43:59,368 Epoch: [245][240/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0617 (0.0379) Prec@1 91.000 (93.560) Prec@5 100.000 (99.800) +2022-11-14 14:43:59,823 Epoch: [245][250/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0320 (0.0377) Prec@1 94.000 (93.577) Prec@5 100.000 (99.808) +2022-11-14 14:44:00,295 Epoch: [245][260/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0426 (0.0379) Prec@1 95.000 (93.630) Prec@5 100.000 (99.815) +2022-11-14 14:44:00,767 Epoch: [245][270/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0230 (0.0374) Prec@1 96.000 (93.714) Prec@5 100.000 (99.821) +2022-11-14 14:44:01,240 Epoch: [245][280/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0345 (0.0373) Prec@1 94.000 (93.724) Prec@5 100.000 (99.828) +2022-11-14 14:44:01,709 Epoch: [245][290/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0493 (0.0377) Prec@1 91.000 (93.633) Prec@5 100.000 (99.833) +2022-11-14 14:44:02,184 Epoch: [245][300/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0221 (0.0372) Prec@1 96.000 (93.710) Prec@5 100.000 (99.839) +2022-11-14 14:44:02,651 Epoch: [245][310/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0349 (0.0371) Prec@1 93.000 (93.688) Prec@5 100.000 (99.844) +2022-11-14 14:44:03,122 Epoch: [245][320/500] Time 0.044 (0.033) Data 0.001 (0.002) Loss 0.0471 (0.0374) Prec@1 92.000 (93.636) Prec@5 99.000 (99.818) +2022-11-14 14:44:03,595 Epoch: [245][330/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0432 (0.0376) Prec@1 92.000 (93.588) Prec@5 100.000 (99.824) +2022-11-14 14:44:04,065 Epoch: [245][340/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0517 (0.0380) Prec@1 91.000 (93.514) Prec@5 99.000 (99.800) +2022-11-14 14:44:04,534 Epoch: [245][350/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0155 (0.0373) Prec@1 98.000 (93.639) Prec@5 100.000 (99.806) +2022-11-14 14:44:05,009 Epoch: [245][360/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0253 (0.0370) Prec@1 95.000 (93.676) Prec@5 100.000 (99.811) +2022-11-14 14:44:05,483 Epoch: [245][370/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0558 (0.0375) Prec@1 90.000 (93.579) Prec@5 100.000 (99.816) +2022-11-14 14:44:05,948 Epoch: [245][380/500] Time 0.038 (0.034) Data 0.002 (0.002) Loss 0.0389 (0.0375) Prec@1 93.000 (93.564) Prec@5 99.000 (99.795) +2022-11-14 14:44:06,419 Epoch: [245][390/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.0269 (0.0373) Prec@1 97.000 (93.650) Prec@5 100.000 (99.800) +2022-11-14 14:44:06,893 Epoch: [245][400/500] Time 0.042 (0.035) Data 0.003 (0.002) Loss 0.0402 (0.0374) Prec@1 94.000 (93.659) Prec@5 100.000 (99.805) +2022-11-14 14:44:07,359 Epoch: [245][410/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0461 (0.0376) Prec@1 92.000 (93.619) Prec@5 99.000 (99.786) +2022-11-14 14:44:07,825 Epoch: [245][420/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0168 (0.0371) Prec@1 98.000 (93.721) Prec@5 100.000 (99.791) +2022-11-14 14:44:08,290 Epoch: [245][430/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0448 (0.0373) Prec@1 92.000 (93.682) Prec@5 100.000 (99.795) +2022-11-14 14:44:08,763 Epoch: [245][440/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0274 (0.0370) Prec@1 96.000 (93.733) Prec@5 100.000 (99.800) +2022-11-14 14:44:09,228 Epoch: [245][450/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0258 (0.0368) Prec@1 94.000 (93.739) Prec@5 100.000 (99.804) +2022-11-14 14:44:09,697 Epoch: [245][460/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0205 (0.0364) Prec@1 95.000 (93.766) Prec@5 100.000 (99.809) +2022-11-14 14:44:10,172 Epoch: [245][470/500] Time 0.043 (0.036) Data 0.003 (0.002) Loss 0.0350 (0.0364) Prec@1 95.000 (93.792) Prec@5 100.000 (99.812) +2022-11-14 14:44:10,644 Epoch: [245][480/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0347 (0.0364) Prec@1 94.000 (93.796) Prec@5 100.000 (99.816) +2022-11-14 14:44:11,109 Epoch: [245][490/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0187 (0.0360) Prec@1 98.000 (93.880) Prec@5 100.000 (99.820) +2022-11-14 14:44:11,537 Epoch: [245][499/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0366 (0.0360) Prec@1 94.000 (93.882) Prec@5 99.000 (99.804) +2022-11-14 14:44:11,835 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0419 (0.0419) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:11,846 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0692 (0.0556) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:11,856 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0539) Prec@1 93.000 (91.667) Prec@5 100.000 (100.000) +2022-11-14 14:44:11,869 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0565) Prec@1 89.000 (91.000) Prec@5 99.000 (99.750) +2022-11-14 14:44:11,878 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0613) Prec@1 89.000 (90.600) Prec@5 99.000 (99.600) +2022-11-14 14:44:11,886 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0619) Prec@1 87.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 14:44:11,893 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0600) Prec@1 91.000 (90.143) Prec@5 100.000 (99.714) +2022-11-14 14:44:11,902 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0650) Prec@1 82.000 (89.125) Prec@5 99.000 (99.625) +2022-11-14 14:44:11,911 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0654) Prec@1 89.000 (89.111) Prec@5 99.000 (99.556) +2022-11-14 14:44:11,921 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0653) Prec@1 89.000 (89.100) Prec@5 99.000 (99.500) +2022-11-14 14:44:11,933 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0646) Prec@1 90.000 (89.182) Prec@5 100.000 (99.545) +2022-11-14 14:44:11,944 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0681) Prec@1 83.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 14:44:11,955 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0344 (0.0655) Prec@1 93.000 (89.000) Prec@5 100.000 (99.538) +2022-11-14 14:44:11,966 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0673) Prec@1 87.000 (88.857) Prec@5 99.000 (99.500) +2022-11-14 14:44:11,976 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0678) Prec@1 88.000 (88.800) Prec@5 100.000 (99.533) +2022-11-14 14:44:11,986 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0689) Prec@1 87.000 (88.688) Prec@5 99.000 (99.500) +2022-11-14 14:44:11,996 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0671) Prec@1 95.000 (89.059) Prec@5 99.000 (99.471) +2022-11-14 14:44:12,007 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0686) Prec@1 86.000 (88.889) Prec@5 100.000 (99.500) +2022-11-14 14:44:12,018 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0690) Prec@1 86.000 (88.737) Prec@5 98.000 (99.421) +2022-11-14 14:44:12,029 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0697) Prec@1 89.000 (88.750) Prec@5 98.000 (99.350) +2022-11-14 14:44:12,039 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0696) Prec@1 87.000 (88.667) Prec@5 100.000 (99.381) +2022-11-14 14:44:12,050 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0704) Prec@1 84.000 (88.455) Prec@5 100.000 (99.409) +2022-11-14 14:44:12,060 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0718) Prec@1 85.000 (88.304) Prec@5 99.000 (99.391) +2022-11-14 14:44:12,072 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0718) Prec@1 90.000 (88.375) Prec@5 100.000 (99.417) +2022-11-14 14:44:12,083 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0721) Prec@1 87.000 (88.320) Prec@5 100.000 (99.440) +2022-11-14 14:44:12,094 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0732) Prec@1 85.000 (88.192) Prec@5 99.000 (99.423) +2022-11-14 14:44:12,106 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0735) Prec@1 84.000 (88.037) Prec@5 100.000 (99.444) +2022-11-14 14:44:12,117 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0733) Prec@1 88.000 (88.036) Prec@5 100.000 (99.464) +2022-11-14 14:44:12,129 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0733) Prec@1 89.000 (88.069) Prec@5 99.000 (99.448) +2022-11-14 14:44:12,140 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0730) Prec@1 88.000 (88.067) Prec@5 100.000 (99.467) +2022-11-14 14:44:12,150 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0732) Prec@1 86.000 (88.000) Prec@5 99.000 (99.452) +2022-11-14 14:44:12,160 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0732) Prec@1 89.000 (88.031) Prec@5 99.000 (99.438) +2022-11-14 14:44:12,171 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0730) Prec@1 88.000 (88.030) Prec@5 99.000 (99.424) +2022-11-14 14:44:12,182 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0733) Prec@1 88.000 (88.029) Prec@5 99.000 (99.412) +2022-11-14 14:44:12,192 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0740) Prec@1 83.000 (87.886) Prec@5 97.000 (99.343) +2022-11-14 14:44:12,203 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0739) Prec@1 90.000 (87.944) Prec@5 100.000 (99.361) +2022-11-14 14:44:12,213 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0742) Prec@1 85.000 (87.865) Prec@5 98.000 (99.324) +2022-11-14 14:44:12,224 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0749) Prec@1 84.000 (87.763) Prec@5 99.000 (99.316) +2022-11-14 14:44:12,234 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0523 (0.0743) Prec@1 91.000 (87.846) Prec@5 99.000 (99.308) +2022-11-14 14:44:12,244 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0740) Prec@1 89.000 (87.875) Prec@5 100.000 (99.325) +2022-11-14 14:44:12,255 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0745) Prec@1 86.000 (87.829) Prec@5 96.000 (99.244) +2022-11-14 14:44:12,266 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0746) Prec@1 88.000 (87.833) Prec@5 100.000 (99.262) +2022-11-14 14:44:12,277 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0742) Prec@1 91.000 (87.907) Prec@5 99.000 (99.256) +2022-11-14 14:44:12,287 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0740) Prec@1 89.000 (87.932) Prec@5 99.000 (99.250) +2022-11-14 14:44:12,298 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0738) Prec@1 92.000 (88.022) Prec@5 100.000 (99.267) +2022-11-14 14:44:12,311 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0741) Prec@1 86.000 (87.978) Prec@5 99.000 (99.261) +2022-11-14 14:44:12,321 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0739) Prec@1 90.000 (88.021) Prec@5 100.000 (99.277) +2022-11-14 14:44:12,332 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0743) Prec@1 84.000 (87.938) Prec@5 99.000 (99.271) +2022-11-14 14:44:12,344 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0739) Prec@1 89.000 (87.959) Prec@5 100.000 (99.286) +2022-11-14 14:44:12,355 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0745) Prec@1 85.000 (87.900) Prec@5 99.000 (99.280) +2022-11-14 14:44:12,366 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0742) Prec@1 89.000 (87.922) Prec@5 99.000 (99.275) +2022-11-14 14:44:12,377 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0742) Prec@1 87.000 (87.904) Prec@5 99.000 (99.269) +2022-11-14 14:44:12,388 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0744) Prec@1 87.000 (87.887) Prec@5 100.000 (99.283) +2022-11-14 14:44:12,400 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0744) Prec@1 89.000 (87.907) Prec@5 99.000 (99.278) +2022-11-14 14:44:12,410 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0745) Prec@1 87.000 (87.891) Prec@5 99.000 (99.273) +2022-11-14 14:44:12,420 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0742) Prec@1 90.000 (87.929) Prec@5 99.000 (99.268) +2022-11-14 14:44:12,431 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0744) Prec@1 86.000 (87.895) Prec@5 100.000 (99.281) +2022-11-14 14:44:12,441 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0743) Prec@1 87.000 (87.879) Prec@5 100.000 (99.293) +2022-11-14 14:44:12,454 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0747) Prec@1 85.000 (87.831) Prec@5 100.000 (99.305) +2022-11-14 14:44:12,465 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0747) Prec@1 81.000 (87.717) Prec@5 100.000 (99.317) +2022-11-14 14:44:12,476 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0749) Prec@1 84.000 (87.656) Prec@5 99.000 (99.311) +2022-11-14 14:44:12,488 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0748) Prec@1 88.000 (87.661) Prec@5 100.000 (99.323) +2022-11-14 14:44:12,498 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0745) Prec@1 92.000 (87.730) Prec@5 100.000 (99.333) +2022-11-14 14:44:12,511 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0740) Prec@1 92.000 (87.797) Prec@5 100.000 (99.344) +2022-11-14 14:44:12,522 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0743) Prec@1 86.000 (87.769) Prec@5 99.000 (99.338) +2022-11-14 14:44:12,532 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0741) Prec@1 89.000 (87.788) Prec@5 99.000 (99.333) +2022-11-14 14:44:12,543 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0418 (0.0736) Prec@1 93.000 (87.866) Prec@5 100.000 (99.343) +2022-11-14 14:44:12,554 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0736) Prec@1 90.000 (87.897) Prec@5 98.000 (99.324) +2022-11-14 14:44:12,566 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0734) Prec@1 92.000 (87.957) Prec@5 100.000 (99.333) +2022-11-14 14:44:12,576 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0733) Prec@1 91.000 (88.000) Prec@5 99.000 (99.329) +2022-11-14 14:44:12,587 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0737) Prec@1 85.000 (87.958) Prec@5 100.000 (99.338) +2022-11-14 14:44:12,598 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0735) Prec@1 89.000 (87.972) Prec@5 99.000 (99.333) +2022-11-14 14:44:12,608 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0320 (0.0729) Prec@1 96.000 (88.082) Prec@5 100.000 (99.342) +2022-11-14 14:44:12,620 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0398 (0.0725) Prec@1 92.000 (88.135) Prec@5 100.000 (99.351) +2022-11-14 14:44:12,631 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0729) Prec@1 84.000 (88.080) Prec@5 99.000 (99.347) +2022-11-14 14:44:12,643 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0727) Prec@1 90.000 (88.105) Prec@5 99.000 (99.342) +2022-11-14 14:44:12,655 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0726) Prec@1 91.000 (88.143) Prec@5 98.000 (99.325) +2022-11-14 14:44:12,666 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0726) Prec@1 89.000 (88.154) Prec@5 98.000 (99.308) +2022-11-14 14:44:12,677 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0723) Prec@1 92.000 (88.203) Prec@5 99.000 (99.304) +2022-11-14 14:44:12,689 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0724) Prec@1 89.000 (88.213) Prec@5 100.000 (99.312) +2022-11-14 14:44:12,699 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0723) Prec@1 90.000 (88.235) Prec@5 100.000 (99.321) +2022-11-14 14:44:12,708 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0725) Prec@1 87.000 (88.220) Prec@5 100.000 (99.329) +2022-11-14 14:44:12,719 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0726) Prec@1 87.000 (88.205) Prec@5 100.000 (99.337) +2022-11-14 14:44:12,729 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0724) Prec@1 90.000 (88.226) Prec@5 100.000 (99.345) +2022-11-14 14:44:12,740 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0726) Prec@1 84.000 (88.176) Prec@5 100.000 (99.353) +2022-11-14 14:44:12,751 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1205 (0.0731) Prec@1 81.000 (88.093) Prec@5 100.000 (99.360) +2022-11-14 14:44:12,762 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0731) Prec@1 87.000 (88.080) Prec@5 100.000 (99.368) +2022-11-14 14:44:12,775 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0730) Prec@1 91.000 (88.114) Prec@5 99.000 (99.364) +2022-11-14 14:44:12,791 Test: [88/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0729) Prec@1 88.000 (88.112) Prec@5 100.000 (99.371) +2022-11-14 14:44:12,808 Test: [89/100] Model Time 0.013 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0731) Prec@1 87.000 (88.100) Prec@5 100.000 (99.378) +2022-11-14 14:44:12,820 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0730) Prec@1 90.000 (88.121) Prec@5 100.000 (99.385) +2022-11-14 14:44:12,833 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0727) Prec@1 93.000 (88.174) Prec@5 100.000 (99.391) +2022-11-14 14:44:12,845 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0728) Prec@1 87.000 (88.161) Prec@5 100.000 (99.398) +2022-11-14 14:44:12,855 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0728) Prec@1 89.000 (88.170) Prec@5 99.000 (99.394) +2022-11-14 14:44:12,865 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0728) Prec@1 88.000 (88.168) Prec@5 99.000 (99.389) +2022-11-14 14:44:12,875 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0727) Prec@1 87.000 (88.156) Prec@5 100.000 (99.396) +2022-11-14 14:44:12,885 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0725) Prec@1 91.000 (88.186) Prec@5 99.000 (99.392) +2022-11-14 14:44:12,896 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0727) Prec@1 88.000 (88.184) Prec@5 99.000 (99.388) +2022-11-14 14:44:12,906 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0731) Prec@1 83.000 (88.131) Prec@5 98.000 (99.374) +2022-11-14 14:44:12,916 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0731) Prec@1 87.000 (88.120) Prec@5 100.000 (99.380) +2022-11-14 14:44:12,976 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:44:13,287 Epoch: [246][0/500] Time 0.023 (0.023) Data 0.227 (0.227) Loss 0.0535 (0.0535) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:13,498 Epoch: [246][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0353 (0.0444) Prec@1 94.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 14:44:13,706 Epoch: [246][20/500] Time 0.018 (0.019) Data 0.002 (0.012) Loss 0.0468 (0.0452) Prec@1 93.000 (92.000) Prec@5 98.000 (99.333) +2022-11-14 14:44:13,932 Epoch: [246][30/500] Time 0.022 (0.019) Data 0.002 (0.009) Loss 0.0273 (0.0407) Prec@1 96.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 14:44:14,214 Epoch: [246][40/500] Time 0.028 (0.020) Data 0.001 (0.007) Loss 0.0373 (0.0400) Prec@1 94.000 (93.200) Prec@5 98.000 (99.200) +2022-11-14 14:44:14,501 Epoch: [246][50/500] Time 0.025 (0.021) Data 0.003 (0.006) Loss 0.0298 (0.0383) Prec@1 95.000 (93.500) Prec@5 100.000 (99.333) +2022-11-14 14:44:14,787 Epoch: [246][60/500] Time 0.027 (0.022) Data 0.002 (0.005) Loss 0.0343 (0.0377) Prec@1 95.000 (93.714) Prec@5 100.000 (99.429) +2022-11-14 14:44:15,076 Epoch: [246][70/500] Time 0.026 (0.023) Data 0.002 (0.005) Loss 0.0615 (0.0407) Prec@1 89.000 (93.125) Prec@5 100.000 (99.500) +2022-11-14 14:44:15,370 Epoch: [246][80/500] Time 0.027 (0.023) Data 0.002 (0.004) Loss 0.0402 (0.0407) Prec@1 92.000 (93.000) Prec@5 100.000 (99.556) +2022-11-14 14:44:15,656 Epoch: [246][90/500] Time 0.026 (0.023) Data 0.001 (0.004) Loss 0.0632 (0.0429) Prec@1 90.000 (92.700) Prec@5 98.000 (99.400) +2022-11-14 14:44:15,948 Epoch: [246][100/500] Time 0.026 (0.023) Data 0.001 (0.004) Loss 0.0448 (0.0431) Prec@1 93.000 (92.727) Prec@5 100.000 (99.455) +2022-11-14 14:44:16,234 Epoch: [246][110/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0280 (0.0418) Prec@1 97.000 (93.083) Prec@5 99.000 (99.417) +2022-11-14 14:44:16,525 Epoch: [246][120/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0376 (0.0415) Prec@1 94.000 (93.154) Prec@5 100.000 (99.462) +2022-11-14 14:44:16,814 Epoch: [246][130/500] Time 0.027 (0.024) Data 0.001 (0.003) Loss 0.0277 (0.0405) Prec@1 96.000 (93.357) Prec@5 100.000 (99.500) +2022-11-14 14:44:17,103 Epoch: [246][140/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0257 (0.0395) Prec@1 96.000 (93.533) Prec@5 100.000 (99.533) +2022-11-14 14:44:17,397 Epoch: [246][150/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0386 (0.0395) Prec@1 91.000 (93.375) Prec@5 100.000 (99.562) +2022-11-14 14:44:17,682 Epoch: [246][160/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0413 (0.0396) Prec@1 95.000 (93.471) Prec@5 100.000 (99.588) +2022-11-14 14:44:17,975 Epoch: [246][170/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0295 (0.0390) Prec@1 95.000 (93.556) Prec@5 100.000 (99.611) +2022-11-14 14:44:18,265 Epoch: [246][180/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0353 (0.0388) Prec@1 93.000 (93.526) Prec@5 100.000 (99.632) +2022-11-14 14:44:18,568 Epoch: [246][190/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0382 (0.0388) Prec@1 93.000 (93.500) Prec@5 100.000 (99.650) +2022-11-14 14:44:19,055 Epoch: [246][200/500] Time 0.044 (0.025) Data 0.002 (0.003) Loss 0.0312 (0.0384) Prec@1 94.000 (93.524) Prec@5 100.000 (99.667) +2022-11-14 14:44:19,536 Epoch: [246][210/500] Time 0.043 (0.026) Data 0.001 (0.003) Loss 0.0462 (0.0388) Prec@1 91.000 (93.409) Prec@5 100.000 (99.682) +2022-11-14 14:44:20,012 Epoch: [246][220/500] Time 0.043 (0.027) Data 0.002 (0.003) Loss 0.0230 (0.0381) Prec@1 96.000 (93.522) Prec@5 100.000 (99.696) +2022-11-14 14:44:20,486 Epoch: [246][230/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0363 (0.0380) Prec@1 96.000 (93.625) Prec@5 100.000 (99.708) +2022-11-14 14:44:20,965 Epoch: [246][240/500] Time 0.044 (0.028) Data 0.002 (0.003) Loss 0.0456 (0.0383) Prec@1 93.000 (93.600) Prec@5 100.000 (99.720) +2022-11-14 14:44:21,441 Epoch: [246][250/500] Time 0.042 (0.029) Data 0.002 (0.003) Loss 0.0122 (0.0373) Prec@1 99.000 (93.808) Prec@5 100.000 (99.731) +2022-11-14 14:44:21,916 Epoch: [246][260/500] Time 0.050 (0.029) Data 0.002 (0.003) Loss 0.0103 (0.0363) Prec@1 99.000 (94.000) Prec@5 100.000 (99.741) +2022-11-14 14:44:22,389 Epoch: [246][270/500] Time 0.047 (0.030) Data 0.002 (0.003) Loss 0.0331 (0.0362) Prec@1 95.000 (94.036) Prec@5 100.000 (99.750) +2022-11-14 14:44:22,870 Epoch: [246][280/500] Time 0.044 (0.030) Data 0.002 (0.003) Loss 0.0523 (0.0368) Prec@1 89.000 (93.862) Prec@5 100.000 (99.759) +2022-11-14 14:44:23,341 Epoch: [246][290/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0503 (0.0372) Prec@1 91.000 (93.767) Prec@5 100.000 (99.767) +2022-11-14 14:44:23,807 Epoch: [246][300/500] Time 0.045 (0.031) Data 0.002 (0.002) Loss 0.0505 (0.0376) Prec@1 92.000 (93.710) Prec@5 100.000 (99.774) +2022-11-14 14:44:24,282 Epoch: [246][310/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0267 (0.0373) Prec@1 95.000 (93.750) Prec@5 99.000 (99.750) +2022-11-14 14:44:24,757 Epoch: [246][320/500] Time 0.044 (0.032) Data 0.001 (0.002) Loss 0.0578 (0.0379) Prec@1 91.000 (93.667) Prec@5 100.000 (99.758) +2022-11-14 14:44:25,231 Epoch: [246][330/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0300 (0.0377) Prec@1 96.000 (93.735) Prec@5 99.000 (99.735) +2022-11-14 14:44:25,709 Epoch: [246][340/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0451 (0.0379) Prec@1 92.000 (93.686) Prec@5 100.000 (99.743) +2022-11-14 14:44:26,186 Epoch: [246][350/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0389 (0.0379) Prec@1 94.000 (93.694) Prec@5 100.000 (99.750) +2022-11-14 14:44:26,661 Epoch: [246][360/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0343 (0.0378) Prec@1 94.000 (93.703) Prec@5 100.000 (99.757) +2022-11-14 14:44:27,140 Epoch: [246][370/500] Time 0.042 (0.033) Data 0.002 (0.002) Loss 0.0312 (0.0377) Prec@1 94.000 (93.711) Prec@5 100.000 (99.763) +2022-11-14 14:44:27,617 Epoch: [246][380/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0225 (0.0373) Prec@1 96.000 (93.769) Prec@5 100.000 (99.769) +2022-11-14 14:44:28,094 Epoch: [246][390/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0373 (0.0373) Prec@1 94.000 (93.775) Prec@5 100.000 (99.775) +2022-11-14 14:44:28,569 Epoch: [246][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0204 (0.0369) Prec@1 97.000 (93.854) Prec@5 100.000 (99.780) +2022-11-14 14:44:29,052 Epoch: [246][410/500] Time 0.045 (0.034) Data 0.002 (0.002) Loss 0.0308 (0.0367) Prec@1 95.000 (93.881) Prec@5 100.000 (99.786) +2022-11-14 14:44:29,531 Epoch: [246][420/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0408 (0.0368) Prec@1 92.000 (93.837) Prec@5 100.000 (99.791) +2022-11-14 14:44:30,013 Epoch: [246][430/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0429 (0.0369) Prec@1 92.000 (93.795) Prec@5 100.000 (99.795) +2022-11-14 14:44:30,491 Epoch: [246][440/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0403 (0.0370) Prec@1 95.000 (93.822) Prec@5 100.000 (99.800) +2022-11-14 14:44:30,970 Epoch: [246][450/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0441 (0.0372) Prec@1 92.000 (93.783) Prec@5 100.000 (99.804) +2022-11-14 14:44:31,450 Epoch: [246][460/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0313 (0.0370) Prec@1 96.000 (93.830) Prec@5 100.000 (99.809) +2022-11-14 14:44:31,930 Epoch: [246][470/500] Time 0.051 (0.035) Data 0.002 (0.002) Loss 0.0362 (0.0370) Prec@1 93.000 (93.812) Prec@5 100.000 (99.812) +2022-11-14 14:44:32,410 Epoch: [246][480/500] Time 0.055 (0.035) Data 0.002 (0.002) Loss 0.0478 (0.0373) Prec@1 91.000 (93.755) Prec@5 100.000 (99.816) +2022-11-14 14:44:32,892 Epoch: [246][490/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0569 (0.0376) Prec@1 92.000 (93.720) Prec@5 100.000 (99.820) +2022-11-14 14:44:33,315 Epoch: [246][499/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0179 (0.0373) Prec@1 98.000 (93.804) Prec@5 100.000 (99.824) +2022-11-14 14:44:33,582 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0785 (0.0785) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:33,590 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0789) Prec@1 87.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:44:33,598 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0877) Prec@1 83.000 (86.000) Prec@5 100.000 (99.667) +2022-11-14 14:44:33,611 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0872) Prec@1 87.000 (86.250) Prec@5 100.000 (99.750) +2022-11-14 14:44:33,619 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0864) Prec@1 85.000 (86.000) Prec@5 100.000 (99.800) +2022-11-14 14:44:33,626 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0318 (0.0773) Prec@1 93.000 (87.167) Prec@5 100.000 (99.833) +2022-11-14 14:44:33,634 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0738) Prec@1 90.000 (87.571) Prec@5 100.000 (99.857) +2022-11-14 14:44:33,646 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0769) Prec@1 84.000 (87.125) Prec@5 100.000 (99.875) +2022-11-14 14:44:33,654 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0767) Prec@1 88.000 (87.222) Prec@5 100.000 (99.889) +2022-11-14 14:44:33,663 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0748) Prec@1 91.000 (87.600) Prec@5 99.000 (99.800) +2022-11-14 14:44:33,674 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0730) Prec@1 88.000 (87.636) Prec@5 100.000 (99.818) +2022-11-14 14:44:33,685 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1161 (0.0766) Prec@1 81.000 (87.083) Prec@5 99.000 (99.750) +2022-11-14 14:44:33,698 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0476 (0.0744) Prec@1 93.000 (87.538) Prec@5 100.000 (99.769) +2022-11-14 14:44:33,711 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0753) Prec@1 85.000 (87.357) Prec@5 100.000 (99.786) +2022-11-14 14:44:33,723 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0755) Prec@1 88.000 (87.400) Prec@5 97.000 (99.600) +2022-11-14 14:44:33,732 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0761) Prec@1 87.000 (87.375) Prec@5 98.000 (99.500) +2022-11-14 14:44:33,745 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0743) Prec@1 94.000 (87.765) Prec@5 99.000 (99.471) +2022-11-14 14:44:33,757 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1259 (0.0771) Prec@1 82.000 (87.444) Prec@5 99.000 (99.444) +2022-11-14 14:44:33,769 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0782) Prec@1 84.000 (87.263) Prec@5 98.000 (99.368) +2022-11-14 14:44:33,782 Test: [19/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0788) Prec@1 84.000 (87.100) Prec@5 99.000 (99.350) +2022-11-14 14:44:33,793 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0779) Prec@1 91.000 (87.286) Prec@5 100.000 (99.381) +2022-11-14 14:44:33,804 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0780) Prec@1 86.000 (87.227) Prec@5 98.000 (99.318) +2022-11-14 14:44:33,816 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0784) Prec@1 86.000 (87.174) Prec@5 97.000 (99.217) +2022-11-14 14:44:33,828 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0780) Prec@1 88.000 (87.208) Prec@5 100.000 (99.250) +2022-11-14 14:44:33,841 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0789) Prec@1 82.000 (87.000) Prec@5 99.000 (99.240) +2022-11-14 14:44:33,851 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0794) Prec@1 86.000 (86.962) Prec@5 98.000 (99.192) +2022-11-14 14:44:33,865 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0414 (0.0780) Prec@1 92.000 (87.148) Prec@5 100.000 (99.222) +2022-11-14 14:44:33,878 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0772) Prec@1 92.000 (87.321) Prec@5 100.000 (99.250) +2022-11-14 14:44:33,890 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0768) Prec@1 90.000 (87.414) Prec@5 98.000 (99.207) +2022-11-14 14:44:33,901 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0764) Prec@1 92.000 (87.567) Prec@5 100.000 (99.233) +2022-11-14 14:44:33,912 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0759) Prec@1 93.000 (87.742) Prec@5 99.000 (99.226) +2022-11-14 14:44:33,927 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0752) Prec@1 92.000 (87.875) Prec@5 99.000 (99.219) +2022-11-14 14:44:33,939 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0753) Prec@1 87.000 (87.848) Prec@5 100.000 (99.242) +2022-11-14 14:44:33,951 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0759) Prec@1 83.000 (87.706) Prec@5 99.000 (99.235) +2022-11-14 14:44:33,964 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0762) Prec@1 85.000 (87.629) Prec@5 99.000 (99.229) +2022-11-14 14:44:33,976 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0760) Prec@1 89.000 (87.667) Prec@5 99.000 (99.222) +2022-11-14 14:44:33,989 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0759) Prec@1 89.000 (87.703) Prec@5 99.000 (99.216) +2022-11-14 14:44:34,002 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0765) Prec@1 81.000 (87.526) Prec@5 100.000 (99.237) +2022-11-14 14:44:34,014 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0758) Prec@1 91.000 (87.615) Prec@5 99.000 (99.231) +2022-11-14 14:44:34,026 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0757) Prec@1 86.000 (87.575) Prec@5 99.000 (99.225) +2022-11-14 14:44:34,038 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0762) Prec@1 85.000 (87.512) Prec@5 98.000 (99.195) +2022-11-14 14:44:34,052 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0762) Prec@1 87.000 (87.500) Prec@5 99.000 (99.190) +2022-11-14 14:44:34,065 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0754) Prec@1 92.000 (87.605) Prec@5 100.000 (99.209) +2022-11-14 14:44:34,077 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0755) Prec@1 87.000 (87.591) Prec@5 98.000 (99.182) +2022-11-14 14:44:34,087 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0754) Prec@1 89.000 (87.622) Prec@5 99.000 (99.178) +2022-11-14 14:44:34,100 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0761) Prec@1 81.000 (87.478) Prec@5 99.000 (99.174) +2022-11-14 14:44:34,114 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0760) Prec@1 88.000 (87.489) Prec@5 100.000 (99.191) +2022-11-14 14:44:34,126 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0760) Prec@1 88.000 (87.500) Prec@5 98.000 (99.167) +2022-11-14 14:44:34,138 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0757) Prec@1 91.000 (87.571) Prec@5 100.000 (99.184) +2022-11-14 14:44:34,147 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0763) Prec@1 85.000 (87.520) Prec@5 98.000 (99.160) +2022-11-14 14:44:34,159 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0398 (0.0756) Prec@1 94.000 (87.647) Prec@5 100.000 (99.176) +2022-11-14 14:44:34,172 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0759) Prec@1 83.000 (87.558) Prec@5 100.000 (99.192) +2022-11-14 14:44:34,185 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0757) Prec@1 90.000 (87.604) Prec@5 100.000 (99.208) +2022-11-14 14:44:34,200 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0755) Prec@1 89.000 (87.630) Prec@5 99.000 (99.204) +2022-11-14 14:44:34,212 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0758) Prec@1 85.000 (87.582) Prec@5 100.000 (99.218) +2022-11-14 14:44:34,226 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0756) Prec@1 90.000 (87.625) Prec@5 99.000 (99.214) +2022-11-14 14:44:34,240 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0753) Prec@1 90.000 (87.667) Prec@5 100.000 (99.228) +2022-11-14 14:44:34,252 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0751) Prec@1 90.000 (87.707) Prec@5 100.000 (99.241) +2022-11-14 14:44:34,264 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0757) Prec@1 82.000 (87.610) Prec@5 98.000 (99.220) +2022-11-14 14:44:34,275 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0759) Prec@1 86.000 (87.583) Prec@5 99.000 (99.217) +2022-11-14 14:44:34,289 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0761) Prec@1 85.000 (87.541) Prec@5 99.000 (99.213) +2022-11-14 14:44:34,303 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0762) Prec@1 89.000 (87.565) Prec@5 100.000 (99.226) +2022-11-14 14:44:34,317 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0760) Prec@1 90.000 (87.603) Prec@5 99.000 (99.222) +2022-11-14 14:44:34,329 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0756) Prec@1 90.000 (87.641) Prec@5 100.000 (99.234) +2022-11-14 14:44:34,341 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0757) Prec@1 85.000 (87.600) Prec@5 100.000 (99.246) +2022-11-14 14:44:34,352 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0758) Prec@1 87.000 (87.591) Prec@5 100.000 (99.258) +2022-11-14 14:44:34,365 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0370 (0.0752) Prec@1 94.000 (87.687) Prec@5 100.000 (99.269) +2022-11-14 14:44:34,379 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0751) Prec@1 89.000 (87.706) Prec@5 100.000 (99.279) +2022-11-14 14:44:34,392 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0750) Prec@1 87.000 (87.696) Prec@5 99.000 (99.275) +2022-11-14 14:44:34,405 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0749) Prec@1 89.000 (87.714) Prec@5 100.000 (99.286) +2022-11-14 14:44:34,417 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0752) Prec@1 87.000 (87.704) Prec@5 100.000 (99.296) +2022-11-14 14:44:34,428 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0750) Prec@1 89.000 (87.722) Prec@5 100.000 (99.306) +2022-11-14 14:44:34,441 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0747) Prec@1 92.000 (87.781) Prec@5 99.000 (99.301) +2022-11-14 14:44:34,453 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0364 (0.0742) Prec@1 96.000 (87.892) Prec@5 100.000 (99.311) +2022-11-14 14:44:34,465 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0742) Prec@1 86.000 (87.867) Prec@5 100.000 (99.320) +2022-11-14 14:44:34,476 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0739) Prec@1 92.000 (87.921) Prec@5 99.000 (99.316) +2022-11-14 14:44:34,487 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0739) Prec@1 89.000 (87.935) Prec@5 99.000 (99.312) +2022-11-14 14:44:34,498 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0741) Prec@1 85.000 (87.897) Prec@5 97.000 (99.282) +2022-11-14 14:44:34,509 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0739) Prec@1 90.000 (87.924) Prec@5 100.000 (99.291) +2022-11-14 14:44:34,523 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0737) Prec@1 89.000 (87.938) Prec@5 100.000 (99.300) +2022-11-14 14:44:34,535 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0739) Prec@1 88.000 (87.938) Prec@5 100.000 (99.309) +2022-11-14 14:44:34,547 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0740) Prec@1 84.000 (87.890) Prec@5 100.000 (99.317) +2022-11-14 14:44:34,559 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0743) Prec@1 83.000 (87.831) Prec@5 99.000 (99.313) +2022-11-14 14:44:34,572 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0744) Prec@1 87.000 (87.821) Prec@5 99.000 (99.310) +2022-11-14 14:44:34,586 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0744) Prec@1 85.000 (87.788) Prec@5 99.000 (99.306) +2022-11-14 14:44:34,598 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1150 (0.0749) Prec@1 83.000 (87.733) Prec@5 100.000 (99.314) +2022-11-14 14:44:34,609 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0750) Prec@1 87.000 (87.724) Prec@5 100.000 (99.322) +2022-11-14 14:44:34,621 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0750) Prec@1 90.000 (87.750) Prec@5 99.000 (99.318) +2022-11-14 14:44:34,634 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0749) Prec@1 90.000 (87.775) Prec@5 99.000 (99.315) +2022-11-14 14:44:34,647 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0750) Prec@1 88.000 (87.778) Prec@5 99.000 (99.311) +2022-11-14 14:44:34,658 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0747) Prec@1 93.000 (87.835) Prec@5 100.000 (99.319) +2022-11-14 14:44:34,671 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0746) Prec@1 89.000 (87.848) Prec@5 100.000 (99.326) +2022-11-14 14:44:34,684 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0748) Prec@1 84.000 (87.806) Prec@5 100.000 (99.333) +2022-11-14 14:44:34,698 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0747) Prec@1 90.000 (87.830) Prec@5 99.000 (99.330) +2022-11-14 14:44:34,711 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0747) Prec@1 86.000 (87.811) Prec@5 99.000 (99.326) +2022-11-14 14:44:34,723 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0746) Prec@1 89.000 (87.823) Prec@5 98.000 (99.312) +2022-11-14 14:44:34,734 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0743) Prec@1 93.000 (87.876) Prec@5 99.000 (99.309) +2022-11-14 14:44:34,747 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0743) Prec@1 88.000 (87.878) Prec@5 99.000 (99.306) +2022-11-14 14:44:34,760 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0746) Prec@1 84.000 (87.838) Prec@5 99.000 (99.303) +2022-11-14 14:44:34,771 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0744) Prec@1 89.000 (87.850) Prec@5 99.000 (99.300) +2022-11-14 14:44:34,840 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:44:35,137 Epoch: [247][0/500] Time 0.022 (0.022) Data 0.217 (0.217) Loss 0.0290 (0.0290) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:35,345 Epoch: [247][10/500] Time 0.018 (0.019) Data 0.002 (0.021) Loss 0.0302 (0.0296) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:35,546 Epoch: [247][20/500] Time 0.018 (0.018) Data 0.002 (0.012) Loss 0.0429 (0.0341) Prec@1 94.000 (94.667) Prec@5 99.000 (99.667) +2022-11-14 14:44:35,800 Epoch: [247][30/500] Time 0.025 (0.019) Data 0.001 (0.009) Loss 0.0551 (0.0393) Prec@1 89.000 (93.250) Prec@5 99.000 (99.500) +2022-11-14 14:44:36,255 Epoch: [247][40/500] Time 0.044 (0.024) Data 0.002 (0.007) Loss 0.0333 (0.0381) Prec@1 93.000 (93.200) Prec@5 100.000 (99.600) +2022-11-14 14:44:36,721 Epoch: [247][50/500] Time 0.043 (0.028) Data 0.002 (0.006) Loss 0.0313 (0.0370) Prec@1 96.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:44:37,188 Epoch: [247][60/500] Time 0.044 (0.030) Data 0.002 (0.005) Loss 0.0427 (0.0378) Prec@1 93.000 (93.571) Prec@5 100.000 (99.714) +2022-11-14 14:44:37,653 Epoch: [247][70/500] Time 0.042 (0.032) Data 0.002 (0.005) Loss 0.0194 (0.0355) Prec@1 97.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 14:44:38,119 Epoch: [247][80/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0470 (0.0368) Prec@1 92.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 14:44:38,585 Epoch: [247][90/500] Time 0.043 (0.034) Data 0.002 (0.004) Loss 0.0282 (0.0359) Prec@1 95.000 (93.900) Prec@5 100.000 (99.800) +2022-11-14 14:44:39,054 Epoch: [247][100/500] Time 0.045 (0.035) Data 0.002 (0.004) Loss 0.0446 (0.0367) Prec@1 93.000 (93.818) Prec@5 100.000 (99.818) +2022-11-14 14:44:39,516 Epoch: [247][110/500] Time 0.043 (0.035) Data 0.002 (0.004) Loss 0.0355 (0.0366) Prec@1 94.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:44:39,990 Epoch: [247][120/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0180 (0.0352) Prec@1 97.000 (94.077) Prec@5 100.000 (99.846) +2022-11-14 14:44:40,457 Epoch: [247][130/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0185 (0.0340) Prec@1 98.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 14:44:40,926 Epoch: [247][140/500] Time 0.050 (0.037) Data 0.002 (0.003) Loss 0.0380 (0.0342) Prec@1 93.000 (94.267) Prec@5 100.000 (99.867) +2022-11-14 14:44:41,393 Epoch: [247][150/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0480 (0.0351) Prec@1 92.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 14:44:41,865 Epoch: [247][160/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0597 (0.0365) Prec@1 91.000 (93.941) Prec@5 99.000 (99.824) +2022-11-14 14:44:42,322 Epoch: [247][170/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0497 (0.0373) Prec@1 92.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:44:42,784 Epoch: [247][180/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0468 (0.0378) Prec@1 91.000 (93.684) Prec@5 100.000 (99.842) +2022-11-14 14:44:43,251 Epoch: [247][190/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0349 (0.0376) Prec@1 95.000 (93.750) Prec@5 100.000 (99.850) +2022-11-14 14:44:43,710 Epoch: [247][200/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0383 (0.0377) Prec@1 94.000 (93.762) Prec@5 100.000 (99.857) +2022-11-14 14:44:44,172 Epoch: [247][210/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0192 (0.0368) Prec@1 96.000 (93.864) Prec@5 100.000 (99.864) +2022-11-14 14:44:44,625 Epoch: [247][220/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0339 (0.0367) Prec@1 94.000 (93.870) Prec@5 100.000 (99.870) +2022-11-14 14:44:45,095 Epoch: [247][230/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0406 (0.0369) Prec@1 92.000 (93.792) Prec@5 100.000 (99.875) +2022-11-14 14:44:45,565 Epoch: [247][240/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0272 (0.0365) Prec@1 94.000 (93.800) Prec@5 100.000 (99.880) +2022-11-14 14:44:45,962 Epoch: [247][250/500] Time 0.027 (0.038) Data 0.002 (0.003) Loss 0.0214 (0.0359) Prec@1 97.000 (93.923) Prec@5 100.000 (99.885) +2022-11-14 14:44:46,245 Epoch: [247][260/500] Time 0.025 (0.038) Data 0.002 (0.003) Loss 0.0193 (0.0353) Prec@1 98.000 (94.074) Prec@5 100.000 (99.889) +2022-11-14 14:44:46,532 Epoch: [247][270/500] Time 0.026 (0.037) Data 0.001 (0.003) Loss 0.0368 (0.0353) Prec@1 94.000 (94.071) Prec@5 100.000 (99.893) +2022-11-14 14:44:46,816 Epoch: [247][280/500] Time 0.026 (0.037) Data 0.002 (0.003) Loss 0.0331 (0.0353) Prec@1 93.000 (94.034) Prec@5 100.000 (99.897) +2022-11-14 14:44:47,101 Epoch: [247][290/500] Time 0.026 (0.037) Data 0.002 (0.003) Loss 0.0748 (0.0366) Prec@1 87.000 (93.800) Prec@5 99.000 (99.867) +2022-11-14 14:44:47,392 Epoch: [247][300/500] Time 0.031 (0.036) Data 0.002 (0.003) Loss 0.0333 (0.0365) Prec@1 93.000 (93.774) Prec@5 100.000 (99.871) +2022-11-14 14:44:47,677 Epoch: [247][310/500] Time 0.025 (0.036) Data 0.002 (0.003) Loss 0.0204 (0.0360) Prec@1 97.000 (93.875) Prec@5 100.000 (99.875) +2022-11-14 14:44:47,969 Epoch: [247][320/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.0298 (0.0358) Prec@1 95.000 (93.909) Prec@5 100.000 (99.879) +2022-11-14 14:44:48,252 Epoch: [247][330/500] Time 0.026 (0.035) Data 0.002 (0.002) Loss 0.0526 (0.0363) Prec@1 94.000 (93.912) Prec@5 99.000 (99.853) +2022-11-14 14:44:48,539 Epoch: [247][340/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0196 (0.0358) Prec@1 98.000 (94.029) Prec@5 100.000 (99.857) +2022-11-14 14:44:48,823 Epoch: [247][350/500] Time 0.025 (0.035) Data 0.002 (0.002) Loss 0.0460 (0.0361) Prec@1 91.000 (93.944) Prec@5 100.000 (99.861) +2022-11-14 14:44:49,111 Epoch: [247][360/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0143 (0.0355) Prec@1 98.000 (94.054) Prec@5 100.000 (99.865) +2022-11-14 14:44:49,404 Epoch: [247][370/500] Time 0.028 (0.034) Data 0.002 (0.002) Loss 0.0486 (0.0358) Prec@1 91.000 (93.974) Prec@5 99.000 (99.842) +2022-11-14 14:44:49,690 Epoch: [247][380/500] Time 0.026 (0.034) Data 0.002 (0.002) Loss 0.0253 (0.0356) Prec@1 95.000 (94.000) Prec@5 100.000 (99.846) +2022-11-14 14:44:49,983 Epoch: [247][390/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0188 (0.0351) Prec@1 98.000 (94.100) Prec@5 100.000 (99.850) +2022-11-14 14:44:50,270 Epoch: [247][400/500] Time 0.027 (0.034) Data 0.002 (0.002) Loss 0.0232 (0.0349) Prec@1 97.000 (94.171) Prec@5 100.000 (99.854) +2022-11-14 14:44:50,562 Epoch: [247][410/500] Time 0.029 (0.033) Data 0.002 (0.002) Loss 0.0262 (0.0347) Prec@1 96.000 (94.214) Prec@5 100.000 (99.857) +2022-11-14 14:44:50,859 Epoch: [247][420/500] Time 0.031 (0.033) Data 0.002 (0.002) Loss 0.0301 (0.0345) Prec@1 96.000 (94.256) Prec@5 100.000 (99.860) +2022-11-14 14:44:51,144 Epoch: [247][430/500] Time 0.025 (0.033) Data 0.002 (0.002) Loss 0.0419 (0.0347) Prec@1 93.000 (94.227) Prec@5 100.000 (99.864) +2022-11-14 14:44:51,439 Epoch: [247][440/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0487 (0.0350) Prec@1 92.000 (94.178) Prec@5 98.000 (99.822) +2022-11-14 14:44:51,726 Epoch: [247][450/500] Time 0.026 (0.033) Data 0.002 (0.002) Loss 0.0301 (0.0349) Prec@1 95.000 (94.196) Prec@5 99.000 (99.804) +2022-11-14 14:44:52,022 Epoch: [247][460/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0313 (0.0348) Prec@1 93.000 (94.170) Prec@5 100.000 (99.809) +2022-11-14 14:44:52,312 Epoch: [247][470/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0314 (0.0348) Prec@1 96.000 (94.208) Prec@5 99.000 (99.792) +2022-11-14 14:44:52,601 Epoch: [247][480/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0451 (0.0350) Prec@1 92.000 (94.163) Prec@5 100.000 (99.796) +2022-11-14 14:44:52,894 Epoch: [247][490/500] Time 0.030 (0.032) Data 0.002 (0.002) Loss 0.0339 (0.0350) Prec@1 94.000 (94.160) Prec@5 100.000 (99.800) +2022-11-14 14:44:53,154 Epoch: [247][499/500] Time 0.026 (0.032) Data 0.002 (0.002) Loss 0.0373 (0.0350) Prec@1 92.000 (94.118) Prec@5 100.000 (99.804) +2022-11-14 14:44:53,452 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0534 (0.0534) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:53,461 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0678) Prec@1 87.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:44:53,472 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0722) Prec@1 86.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 14:44:53,484 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0706) Prec@1 88.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 14:44:53,494 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0681) Prec@1 90.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 14:44:53,504 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0349 (0.0626) Prec@1 94.000 (89.667) Prec@5 100.000 (99.833) +2022-11-14 14:44:53,515 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0616) Prec@1 91.000 (89.857) Prec@5 100.000 (99.857) +2022-11-14 14:44:53,527 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0644) Prec@1 87.000 (89.500) Prec@5 100.000 (99.875) +2022-11-14 14:44:53,535 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0648) Prec@1 90.000 (89.556) Prec@5 98.000 (99.667) +2022-11-14 14:44:53,545 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0655) Prec@1 87.000 (89.300) Prec@5 99.000 (99.600) +2022-11-14 14:44:53,556 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0652) Prec@1 87.000 (89.091) Prec@5 100.000 (99.636) +2022-11-14 14:44:53,566 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0682) Prec@1 84.000 (88.667) Prec@5 99.000 (99.583) +2022-11-14 14:44:53,577 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0662) Prec@1 95.000 (89.154) Prec@5 99.000 (99.538) +2022-11-14 14:44:53,587 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0675) Prec@1 86.000 (88.929) Prec@5 99.000 (99.500) +2022-11-14 14:44:53,600 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0682) Prec@1 87.000 (88.800) Prec@5 100.000 (99.533) +2022-11-14 14:44:53,612 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0678) Prec@1 89.000 (88.812) Prec@5 100.000 (99.562) +2022-11-14 14:44:53,622 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0673) Prec@1 92.000 (89.000) Prec@5 99.000 (99.529) +2022-11-14 14:44:53,633 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0695) Prec@1 83.000 (88.667) Prec@5 100.000 (99.556) +2022-11-14 14:44:53,644 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0707) Prec@1 85.000 (88.474) Prec@5 98.000 (99.474) +2022-11-14 14:44:53,655 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0716) Prec@1 85.000 (88.300) Prec@5 99.000 (99.450) +2022-11-14 14:44:53,669 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0722) Prec@1 85.000 (88.143) Prec@5 100.000 (99.476) +2022-11-14 14:44:53,679 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0729) Prec@1 82.000 (87.864) Prec@5 99.000 (99.455) +2022-11-14 14:44:53,689 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0742) Prec@1 84.000 (87.696) Prec@5 99.000 (99.435) +2022-11-14 14:44:53,699 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0741) Prec@1 87.000 (87.667) Prec@5 100.000 (99.458) +2022-11-14 14:44:53,710 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0745) Prec@1 87.000 (87.640) Prec@5 100.000 (99.480) +2022-11-14 14:44:53,721 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0751) Prec@1 87.000 (87.615) Prec@5 99.000 (99.462) +2022-11-14 14:44:53,732 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0748) Prec@1 87.000 (87.593) Prec@5 100.000 (99.481) +2022-11-14 14:44:53,743 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0746) Prec@1 87.000 (87.571) Prec@5 100.000 (99.500) +2022-11-14 14:44:53,754 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0746) Prec@1 85.000 (87.483) Prec@5 99.000 (99.483) +2022-11-14 14:44:53,764 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0745) Prec@1 87.000 (87.467) Prec@5 99.000 (99.467) +2022-11-14 14:44:53,775 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0738) Prec@1 92.000 (87.613) Prec@5 100.000 (99.484) +2022-11-14 14:44:53,786 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0736) Prec@1 89.000 (87.656) Prec@5 98.000 (99.438) +2022-11-14 14:44:53,798 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0736) Prec@1 88.000 (87.667) Prec@5 99.000 (99.424) +2022-11-14 14:44:53,807 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0742) Prec@1 82.000 (87.500) Prec@5 100.000 (99.441) +2022-11-14 14:44:53,819 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0741) Prec@1 87.000 (87.486) Prec@5 98.000 (99.400) +2022-11-14 14:44:53,830 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0744) Prec@1 87.000 (87.472) Prec@5 100.000 (99.417) +2022-11-14 14:44:53,844 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0747) Prec@1 88.000 (87.486) Prec@5 99.000 (99.405) +2022-11-14 14:44:53,857 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0754) Prec@1 83.000 (87.368) Prec@5 100.000 (99.421) +2022-11-14 14:44:53,870 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0751) Prec@1 90.000 (87.436) Prec@5 99.000 (99.410) +2022-11-14 14:44:53,881 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0749) Prec@1 89.000 (87.475) Prec@5 100.000 (99.425) +2022-11-14 14:44:53,890 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0753) Prec@1 85.000 (87.415) Prec@5 97.000 (99.366) +2022-11-14 14:44:53,900 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0751) Prec@1 88.000 (87.429) Prec@5 99.000 (99.357) +2022-11-14 14:44:53,913 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0420 (0.0743) Prec@1 93.000 (87.558) Prec@5 100.000 (99.372) +2022-11-14 14:44:53,924 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0742) Prec@1 91.000 (87.636) Prec@5 99.000 (99.364) +2022-11-14 14:44:53,934 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0738) Prec@1 91.000 (87.711) Prec@5 100.000 (99.378) +2022-11-14 14:44:53,947 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0741) Prec@1 86.000 (87.674) Prec@5 100.000 (99.391) +2022-11-14 14:44:53,958 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0737) Prec@1 91.000 (87.745) Prec@5 100.000 (99.404) +2022-11-14 14:44:53,968 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0743) Prec@1 84.000 (87.667) Prec@5 98.000 (99.375) +2022-11-14 14:44:53,981 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0738) Prec@1 93.000 (87.776) Prec@5 99.000 (99.367) +2022-11-14 14:44:53,992 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0742) Prec@1 88.000 (87.780) Prec@5 99.000 (99.360) +2022-11-14 14:44:54,001 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0740) Prec@1 89.000 (87.804) Prec@5 99.000 (99.353) +2022-11-14 14:44:54,011 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0743) Prec@1 86.000 (87.769) Prec@5 100.000 (99.365) +2022-11-14 14:44:54,024 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0743) Prec@1 87.000 (87.755) Prec@5 100.000 (99.377) +2022-11-14 14:44:54,035 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0744) Prec@1 86.000 (87.722) Prec@5 99.000 (99.370) +2022-11-14 14:44:54,045 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0749) Prec@1 84.000 (87.655) Prec@5 100.000 (99.382) +2022-11-14 14:44:54,058 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0750) Prec@1 85.000 (87.607) Prec@5 98.000 (99.357) +2022-11-14 14:44:54,069 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0748) Prec@1 89.000 (87.632) Prec@5 100.000 (99.368) +2022-11-14 14:44:54,080 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0748) Prec@1 87.000 (87.621) Prec@5 99.000 (99.362) +2022-11-14 14:44:54,092 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0754) Prec@1 83.000 (87.542) Prec@5 100.000 (99.373) +2022-11-14 14:44:54,105 Test: [59/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0756) Prec@1 83.000 (87.467) Prec@5 100.000 (99.383) +2022-11-14 14:44:54,116 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0758) Prec@1 87.000 (87.459) Prec@5 98.000 (99.361) +2022-11-14 14:44:54,128 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0757) Prec@1 88.000 (87.468) Prec@5 99.000 (99.355) +2022-11-14 14:44:54,139 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0757) Prec@1 87.000 (87.460) Prec@5 100.000 (99.365) +2022-11-14 14:44:54,151 Test: [63/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0334 (0.0751) Prec@1 94.000 (87.562) Prec@5 100.000 (99.375) +2022-11-14 14:44:54,163 Test: [64/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0755) Prec@1 82.000 (87.477) Prec@5 100.000 (99.385) +2022-11-14 14:44:54,174 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0757) Prec@1 80.000 (87.364) Prec@5 98.000 (99.364) +2022-11-14 14:44:54,184 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0752) Prec@1 93.000 (87.448) Prec@5 100.000 (99.373) +2022-11-14 14:44:54,197 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0750) Prec@1 91.000 (87.500) Prec@5 99.000 (99.368) +2022-11-14 14:44:54,210 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0749) Prec@1 91.000 (87.551) Prec@5 100.000 (99.377) +2022-11-14 14:44:54,221 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0750) Prec@1 87.000 (87.543) Prec@5 98.000 (99.357) +2022-11-14 14:44:54,230 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0752) Prec@1 87.000 (87.535) Prec@5 99.000 (99.352) +2022-11-14 14:44:54,242 Test: [71/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0751) Prec@1 89.000 (87.556) Prec@5 100.000 (99.361) +2022-11-14 14:44:54,254 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0748) Prec@1 92.000 (87.616) Prec@5 100.000 (99.370) +2022-11-14 14:44:54,266 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0744) Prec@1 92.000 (87.676) Prec@5 100.000 (99.378) +2022-11-14 14:44:54,277 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0746) Prec@1 85.000 (87.640) Prec@5 99.000 (99.373) +2022-11-14 14:44:54,290 Test: [75/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0744) Prec@1 89.000 (87.658) Prec@5 100.000 (99.382) +2022-11-14 14:44:54,301 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0745) Prec@1 87.000 (87.649) Prec@5 99.000 (99.377) +2022-11-14 14:44:54,313 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0746) Prec@1 88.000 (87.654) Prec@5 97.000 (99.346) +2022-11-14 14:44:54,323 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0744) Prec@1 89.000 (87.671) Prec@5 100.000 (99.354) +2022-11-14 14:44:54,335 Test: [79/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0745) Prec@1 86.000 (87.650) Prec@5 100.000 (99.362) +2022-11-14 14:44:54,347 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0745) Prec@1 90.000 (87.679) Prec@5 99.000 (99.358) +2022-11-14 14:44:54,357 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0745) Prec@1 89.000 (87.695) Prec@5 100.000 (99.366) +2022-11-14 14:44:54,369 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0747) Prec@1 87.000 (87.687) Prec@5 100.000 (99.373) +2022-11-14 14:44:54,381 Test: [83/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0747) Prec@1 87.000 (87.679) Prec@5 99.000 (99.369) +2022-11-14 14:44:54,395 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0748) Prec@1 87.000 (87.671) Prec@5 99.000 (99.365) +2022-11-14 14:44:54,406 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0751) Prec@1 84.000 (87.628) Prec@5 100.000 (99.372) +2022-11-14 14:44:54,422 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0752) Prec@1 88.000 (87.632) Prec@5 98.000 (99.356) +2022-11-14 14:44:54,440 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0753) Prec@1 86.000 (87.614) Prec@5 99.000 (99.352) +2022-11-14 14:44:54,457 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0751) Prec@1 89.000 (87.629) Prec@5 100.000 (99.360) +2022-11-14 14:44:54,477 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0751) Prec@1 90.000 (87.656) Prec@5 97.000 (99.333) +2022-11-14 14:44:54,500 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0750) Prec@1 87.000 (87.648) Prec@5 100.000 (99.341) +2022-11-14 14:44:54,522 Test: [91/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0748) Prec@1 93.000 (87.707) Prec@5 100.000 (99.348) +2022-11-14 14:44:54,542 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0750) Prec@1 83.000 (87.656) Prec@5 100.000 (99.355) +2022-11-14 14:44:54,562 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0750) Prec@1 89.000 (87.670) Prec@5 99.000 (99.351) +2022-11-14 14:44:54,587 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0752) Prec@1 83.000 (87.621) Prec@5 99.000 (99.347) +2022-11-14 14:44:54,610 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0752) Prec@1 88.000 (87.625) Prec@5 99.000 (99.344) +2022-11-14 14:44:54,630 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0749) Prec@1 94.000 (87.691) Prec@5 99.000 (99.340) +2022-11-14 14:44:54,657 Test: [97/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0751) Prec@1 86.000 (87.673) Prec@5 99.000 (99.337) +2022-11-14 14:44:54,679 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0753) Prec@1 85.000 (87.646) Prec@5 98.000 (99.323) +2022-11-14 14:44:54,706 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0752) Prec@1 89.000 (87.660) Prec@5 99.000 (99.320) +2022-11-14 14:44:54,778 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:44:55,081 Epoch: [248][0/500] Time 0.030 (0.030) Data 0.214 (0.214) Loss 0.0371 (0.0371) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 14:44:55,362 Epoch: [248][10/500] Time 0.030 (0.025) Data 0.002 (0.021) Loss 0.0302 (0.0337) Prec@1 94.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:44:55,679 Epoch: [248][20/500] Time 0.031 (0.026) Data 0.001 (0.012) Loss 0.0431 (0.0368) Prec@1 93.000 (93.667) Prec@5 98.000 (99.000) +2022-11-14 14:44:56,004 Epoch: [248][30/500] Time 0.028 (0.027) Data 0.002 (0.009) Loss 0.0264 (0.0342) Prec@1 96.000 (94.250) Prec@5 100.000 (99.250) +2022-11-14 14:44:56,327 Epoch: [248][40/500] Time 0.029 (0.027) Data 0.002 (0.007) Loss 0.0216 (0.0317) Prec@1 97.000 (94.800) Prec@5 99.000 (99.200) +2022-11-14 14:44:56,648 Epoch: [248][50/500] Time 0.029 (0.028) Data 0.002 (0.006) Loss 0.0393 (0.0329) Prec@1 95.000 (94.833) Prec@5 100.000 (99.333) +2022-11-14 14:44:56,971 Epoch: [248][60/500] Time 0.027 (0.028) Data 0.002 (0.005) Loss 0.0480 (0.0351) Prec@1 94.000 (94.714) Prec@5 100.000 (99.429) +2022-11-14 14:44:57,291 Epoch: [248][70/500] Time 0.029 (0.028) Data 0.002 (0.005) Loss 0.0430 (0.0361) Prec@1 94.000 (94.625) Prec@5 100.000 (99.500) +2022-11-14 14:44:57,615 Epoch: [248][80/500] Time 0.029 (0.028) Data 0.002 (0.004) Loss 0.0438 (0.0369) Prec@1 93.000 (94.444) Prec@5 100.000 (99.556) +2022-11-14 14:44:57,941 Epoch: [248][90/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0274 (0.0360) Prec@1 95.000 (94.500) Prec@5 100.000 (99.600) +2022-11-14 14:44:58,265 Epoch: [248][100/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0244 (0.0349) Prec@1 97.000 (94.727) Prec@5 100.000 (99.636) +2022-11-14 14:44:58,600 Epoch: [248][110/500] Time 0.032 (0.028) Data 0.002 (0.004) Loss 0.0299 (0.0345) Prec@1 95.000 (94.750) Prec@5 100.000 (99.667) +2022-11-14 14:44:58,938 Epoch: [248][120/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0244 (0.0337) Prec@1 96.000 (94.846) Prec@5 100.000 (99.692) +2022-11-14 14:44:59,255 Epoch: [248][130/500] Time 0.029 (0.028) Data 0.001 (0.003) Loss 0.0474 (0.0347) Prec@1 92.000 (94.643) Prec@5 100.000 (99.714) +2022-11-14 14:44:59,581 Epoch: [248][140/500] Time 0.029 (0.028) Data 0.002 (0.003) Loss 0.0193 (0.0337) Prec@1 97.000 (94.800) Prec@5 100.000 (99.733) +2022-11-14 14:44:59,913 Epoch: [248][150/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0398 (0.0341) Prec@1 92.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 14:45:00,238 Epoch: [248][160/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0183 (0.0331) Prec@1 97.000 (94.765) Prec@5 100.000 (99.765) +2022-11-14 14:45:00,563 Epoch: [248][170/500] Time 0.029 (0.029) Data 0.003 (0.003) Loss 0.0294 (0.0329) Prec@1 95.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 14:45:00,961 Epoch: [248][180/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.0338 (0.0330) Prec@1 93.000 (94.684) Prec@5 100.000 (99.789) +2022-11-14 14:45:01,439 Epoch: [248][190/500] Time 0.047 (0.030) Data 0.002 (0.003) Loss 0.0333 (0.0330) Prec@1 93.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 14:45:01,920 Epoch: [248][200/500] Time 0.054 (0.030) Data 0.002 (0.003) Loss 0.0330 (0.0330) Prec@1 94.000 (94.571) Prec@5 100.000 (99.810) +2022-11-14 14:45:02,398 Epoch: [248][210/500] Time 0.050 (0.031) Data 0.002 (0.003) Loss 0.0560 (0.0340) Prec@1 93.000 (94.500) Prec@5 100.000 (99.818) +2022-11-14 14:45:02,876 Epoch: [248][220/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0462 (0.0346) Prec@1 93.000 (94.435) Prec@5 99.000 (99.783) +2022-11-14 14:45:03,338 Epoch: [248][230/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0428 (0.0349) Prec@1 92.000 (94.333) Prec@5 100.000 (99.792) +2022-11-14 14:45:03,809 Epoch: [248][240/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0449 (0.0353) Prec@1 92.000 (94.240) Prec@5 100.000 (99.800) +2022-11-14 14:45:04,281 Epoch: [248][250/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0422 (0.0356) Prec@1 92.000 (94.154) Prec@5 100.000 (99.808) +2022-11-14 14:45:04,756 Epoch: [248][260/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0413 (0.0358) Prec@1 91.000 (94.037) Prec@5 100.000 (99.815) +2022-11-14 14:45:05,228 Epoch: [248][270/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0305 (0.0356) Prec@1 96.000 (94.107) Prec@5 99.000 (99.786) +2022-11-14 14:45:05,708 Epoch: [248][280/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0291 (0.0354) Prec@1 96.000 (94.172) Prec@5 100.000 (99.793) +2022-11-14 14:45:06,186 Epoch: [248][290/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0475 (0.0358) Prec@1 91.000 (94.067) Prec@5 100.000 (99.800) +2022-11-14 14:45:06,663 Epoch: [248][300/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.0231 (0.0354) Prec@1 97.000 (94.161) Prec@5 100.000 (99.806) +2022-11-14 14:45:07,136 Epoch: [248][310/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0391 (0.0355) Prec@1 95.000 (94.188) Prec@5 100.000 (99.812) +2022-11-14 14:45:07,615 Epoch: [248][320/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0332 (0.0354) Prec@1 94.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 14:45:08,095 Epoch: [248][330/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0413 (0.0356) Prec@1 93.000 (94.147) Prec@5 100.000 (99.824) +2022-11-14 14:45:08,573 Epoch: [248][340/500] Time 0.042 (0.035) Data 0.002 (0.002) Loss 0.0219 (0.0352) Prec@1 96.000 (94.200) Prec@5 100.000 (99.829) +2022-11-14 14:45:09,048 Epoch: [248][350/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0522 (0.0357) Prec@1 91.000 (94.111) Prec@5 99.000 (99.806) +2022-11-14 14:45:09,526 Epoch: [248][360/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0354 (0.0357) Prec@1 94.000 (94.108) Prec@5 100.000 (99.811) +2022-11-14 14:45:10,004 Epoch: [248][370/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0358 (0.0357) Prec@1 94.000 (94.105) Prec@5 99.000 (99.789) +2022-11-14 14:45:10,479 Epoch: [248][380/500] Time 0.044 (0.036) Data 0.002 (0.002) Loss 0.0360 (0.0357) Prec@1 95.000 (94.128) Prec@5 100.000 (99.795) +2022-11-14 14:45:10,958 Epoch: [248][390/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0408 (0.0358) Prec@1 94.000 (94.125) Prec@5 99.000 (99.775) +2022-11-14 14:45:11,436 Epoch: [248][400/500] Time 0.051 (0.036) Data 0.002 (0.002) Loss 0.0280 (0.0356) Prec@1 95.000 (94.146) Prec@5 100.000 (99.780) +2022-11-14 14:45:11,916 Epoch: [248][410/500] Time 0.052 (0.036) Data 0.002 (0.002) Loss 0.0372 (0.0357) Prec@1 95.000 (94.167) Prec@5 99.000 (99.762) +2022-11-14 14:45:12,393 Epoch: [248][420/500] Time 0.047 (0.037) Data 0.001 (0.002) Loss 0.0179 (0.0352) Prec@1 97.000 (94.233) Prec@5 100.000 (99.767) +2022-11-14 14:45:12,868 Epoch: [248][430/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0437 (0.0354) Prec@1 93.000 (94.205) Prec@5 100.000 (99.773) +2022-11-14 14:45:13,330 Epoch: [248][440/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0318 (0.0354) Prec@1 94.000 (94.200) Prec@5 100.000 (99.778) +2022-11-14 14:45:13,799 Epoch: [248][450/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0454 (0.0356) Prec@1 94.000 (94.196) Prec@5 100.000 (99.783) +2022-11-14 14:45:14,267 Epoch: [248][460/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0498 (0.0359) Prec@1 90.000 (94.106) Prec@5 100.000 (99.787) +2022-11-14 14:45:14,742 Epoch: [248][470/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0555 (0.0363) Prec@1 91.000 (94.042) Prec@5 99.000 (99.771) +2022-11-14 14:45:15,217 Epoch: [248][480/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0385 (0.0363) Prec@1 93.000 (94.020) Prec@5 100.000 (99.776) +2022-11-14 14:45:15,692 Epoch: [248][490/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0400 (0.0364) Prec@1 91.000 (93.960) Prec@5 100.000 (99.780) +2022-11-14 14:45:16,127 Epoch: [248][499/500] Time 0.041 (0.037) Data 0.002 (0.002) Loss 0.0364 (0.0364) Prec@1 93.000 (93.941) Prec@5 100.000 (99.784) +2022-11-14 14:45:16,425 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0590 (0.0590) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:16,434 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0602) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:16,443 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0640) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 14:45:16,456 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0665) Prec@1 87.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:45:16,465 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0669) Prec@1 89.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 14:45:16,474 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0665) Prec@1 91.000 (88.667) Prec@5 98.000 (99.500) +2022-11-14 14:45:16,484 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0661) Prec@1 90.000 (88.857) Prec@5 100.000 (99.571) +2022-11-14 14:45:16,496 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0679) Prec@1 84.000 (88.250) Prec@5 100.000 (99.625) +2022-11-14 14:45:16,506 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0708) Prec@1 86.000 (88.000) Prec@5 99.000 (99.556) +2022-11-14 14:45:16,515 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0687) Prec@1 91.000 (88.300) Prec@5 99.000 (99.500) +2022-11-14 14:45:16,526 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0676) Prec@1 90.000 (88.455) Prec@5 100.000 (99.545) +2022-11-14 14:45:16,538 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0708) Prec@1 84.000 (88.083) Prec@5 100.000 (99.583) +2022-11-14 14:45:16,550 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0689) Prec@1 91.000 (88.308) Prec@5 99.000 (99.538) +2022-11-14 14:45:16,562 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0702) Prec@1 86.000 (88.143) Prec@5 100.000 (99.571) +2022-11-14 14:45:16,572 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0701) Prec@1 88.000 (88.133) Prec@5 100.000 (99.600) +2022-11-14 14:45:16,583 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0698) Prec@1 90.000 (88.250) Prec@5 99.000 (99.562) +2022-11-14 14:45:16,595 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0692) Prec@1 91.000 (88.412) Prec@5 99.000 (99.529) +2022-11-14 14:45:16,605 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0720) Prec@1 81.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:45:16,616 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0728) Prec@1 85.000 (87.842) Prec@5 96.000 (99.316) +2022-11-14 14:45:16,628 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0730) Prec@1 87.000 (87.800) Prec@5 100.000 (99.350) +2022-11-14 14:45:16,642 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0733) Prec@1 87.000 (87.762) Prec@5 98.000 (99.286) +2022-11-14 14:45:16,653 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0743) Prec@1 86.000 (87.682) Prec@5 99.000 (99.273) +2022-11-14 14:45:16,664 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0755) Prec@1 84.000 (87.522) Prec@5 98.000 (99.217) +2022-11-14 14:45:16,675 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0754) Prec@1 87.000 (87.500) Prec@5 100.000 (99.250) +2022-11-14 14:45:16,687 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0759) Prec@1 87.000 (87.480) Prec@5 99.000 (99.240) +2022-11-14 14:45:16,699 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1157 (0.0774) Prec@1 81.000 (87.231) Prec@5 99.000 (99.231) +2022-11-14 14:45:16,709 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0770) Prec@1 88.000 (87.259) Prec@5 100.000 (99.259) +2022-11-14 14:45:16,720 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0761) Prec@1 91.000 (87.393) Prec@5 99.000 (99.250) +2022-11-14 14:45:16,732 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0761) Prec@1 89.000 (87.448) Prec@5 97.000 (99.172) +2022-11-14 14:45:16,745 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0760) Prec@1 87.000 (87.433) Prec@5 99.000 (99.167) +2022-11-14 14:45:16,757 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0761) Prec@1 85.000 (87.355) Prec@5 100.000 (99.194) +2022-11-14 14:45:16,768 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0758) Prec@1 89.000 (87.406) Prec@5 99.000 (99.188) +2022-11-14 14:45:16,780 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0759) Prec@1 87.000 (87.394) Prec@5 99.000 (99.182) +2022-11-14 14:45:16,794 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0767) Prec@1 82.000 (87.235) Prec@5 99.000 (99.176) +2022-11-14 14:45:16,805 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0769) Prec@1 85.000 (87.171) Prec@5 99.000 (99.171) +2022-11-14 14:45:16,816 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0762) Prec@1 91.000 (87.278) Prec@5 100.000 (99.194) +2022-11-14 14:45:16,830 Test: [36/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0758) Prec@1 89.000 (87.324) Prec@5 99.000 (99.189) +2022-11-14 14:45:16,843 Test: [37/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1104 (0.0767) Prec@1 82.000 (87.184) Prec@5 98.000 (99.158) +2022-11-14 14:45:16,855 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0760) Prec@1 94.000 (87.359) Prec@5 99.000 (99.154) +2022-11-14 14:45:16,868 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0759) Prec@1 90.000 (87.425) Prec@5 99.000 (99.150) +2022-11-14 14:45:16,878 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0761) Prec@1 86.000 (87.390) Prec@5 99.000 (99.146) +2022-11-14 14:45:16,890 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0757) Prec@1 91.000 (87.476) Prec@5 99.000 (99.143) +2022-11-14 14:45:16,902 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0480 (0.0750) Prec@1 92.000 (87.581) Prec@5 99.000 (99.140) +2022-11-14 14:45:16,912 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0748) Prec@1 91.000 (87.659) Prec@5 99.000 (99.136) +2022-11-14 14:45:16,924 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0744) Prec@1 88.000 (87.667) Prec@5 99.000 (99.133) +2022-11-14 14:45:16,934 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0749) Prec@1 82.000 (87.543) Prec@5 98.000 (99.109) +2022-11-14 14:45:16,947 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0747) Prec@1 90.000 (87.596) Prec@5 99.000 (99.106) +2022-11-14 14:45:16,958 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0750) Prec@1 85.000 (87.542) Prec@5 98.000 (99.083) +2022-11-14 14:45:16,969 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0747) Prec@1 90.000 (87.592) Prec@5 100.000 (99.102) +2022-11-14 14:45:16,979 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1243 (0.0757) Prec@1 81.000 (87.460) Prec@5 98.000 (99.080) +2022-11-14 14:45:16,990 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0757) Prec@1 88.000 (87.471) Prec@5 100.000 (99.098) +2022-11-14 14:45:17,003 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0757) Prec@1 87.000 (87.462) Prec@5 99.000 (99.096) +2022-11-14 14:45:17,014 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0757) Prec@1 88.000 (87.472) Prec@5 99.000 (99.094) +2022-11-14 14:45:17,025 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0759) Prec@1 85.000 (87.426) Prec@5 100.000 (99.111) +2022-11-14 14:45:17,037 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0763) Prec@1 84.000 (87.364) Prec@5 100.000 (99.127) +2022-11-14 14:45:17,049 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0761) Prec@1 91.000 (87.429) Prec@5 99.000 (99.125) +2022-11-14 14:45:17,060 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0756) Prec@1 91.000 (87.491) Prec@5 100.000 (99.140) +2022-11-14 14:45:17,072 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0754) Prec@1 91.000 (87.552) Prec@5 99.000 (99.138) +2022-11-14 14:45:17,085 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0758) Prec@1 84.000 (87.492) Prec@5 100.000 (99.153) +2022-11-14 14:45:17,096 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0761) Prec@1 83.000 (87.417) Prec@5 99.000 (99.150) +2022-11-14 14:45:17,105 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0762) Prec@1 86.000 (87.393) Prec@5 100.000 (99.164) +2022-11-14 14:45:17,116 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0763) Prec@1 86.000 (87.371) Prec@5 99.000 (99.161) +2022-11-14 14:45:17,126 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0761) Prec@1 89.000 (87.397) Prec@5 99.000 (99.159) +2022-11-14 14:45:17,138 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0757) Prec@1 90.000 (87.438) Prec@5 99.000 (99.156) +2022-11-14 14:45:17,150 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0756) Prec@1 89.000 (87.462) Prec@5 98.000 (99.138) +2022-11-14 14:45:17,163 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0757) Prec@1 87.000 (87.455) Prec@5 99.000 (99.136) +2022-11-14 14:45:17,176 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0751) Prec@1 94.000 (87.552) Prec@5 100.000 (99.149) +2022-11-14 14:45:17,188 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0753) Prec@1 84.000 (87.500) Prec@5 99.000 (99.147) +2022-11-14 14:45:17,199 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0752) Prec@1 89.000 (87.522) Prec@5 99.000 (99.145) +2022-11-14 14:45:17,210 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0752) Prec@1 89.000 (87.543) Prec@5 100.000 (99.157) +2022-11-14 14:45:17,223 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0756) Prec@1 85.000 (87.507) Prec@5 99.000 (99.155) +2022-11-14 14:45:17,235 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0755) Prec@1 90.000 (87.542) Prec@5 100.000 (99.167) +2022-11-14 14:45:17,246 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0752) Prec@1 92.000 (87.603) Prec@5 100.000 (99.178) +2022-11-14 14:45:17,259 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0748) Prec@1 94.000 (87.689) Prec@5 100.000 (99.189) +2022-11-14 14:45:17,271 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0747) Prec@1 87.000 (87.680) Prec@5 99.000 (99.187) +2022-11-14 14:45:17,282 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0746) Prec@1 91.000 (87.724) Prec@5 99.000 (99.184) +2022-11-14 14:45:17,292 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0744) Prec@1 89.000 (87.740) Prec@5 97.000 (99.156) +2022-11-14 14:45:17,304 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0747) Prec@1 84.000 (87.692) Prec@5 98.000 (99.141) +2022-11-14 14:45:17,315 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0749) Prec@1 85.000 (87.658) Prec@5 99.000 (99.139) +2022-11-14 14:45:17,329 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0748) Prec@1 87.000 (87.650) Prec@5 99.000 (99.138) +2022-11-14 14:45:17,343 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0748) Prec@1 88.000 (87.654) Prec@5 99.000 (99.136) +2022-11-14 14:45:17,357 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0749) Prec@1 85.000 (87.622) Prec@5 100.000 (99.146) +2022-11-14 14:45:17,370 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0752) Prec@1 81.000 (87.542) Prec@5 99.000 (99.145) +2022-11-14 14:45:17,381 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0750) Prec@1 89.000 (87.560) Prec@5 100.000 (99.155) +2022-11-14 14:45:17,391 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0750) Prec@1 88.000 (87.565) Prec@5 100.000 (99.165) +2022-11-14 14:45:17,402 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0752) Prec@1 85.000 (87.535) Prec@5 100.000 (99.174) +2022-11-14 14:45:17,412 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0752) Prec@1 88.000 (87.540) Prec@5 100.000 (99.184) +2022-11-14 14:45:17,423 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0754) Prec@1 85.000 (87.511) Prec@5 99.000 (99.182) +2022-11-14 14:45:17,434 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0752) Prec@1 88.000 (87.517) Prec@5 100.000 (99.191) +2022-11-14 14:45:17,447 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0751) Prec@1 89.000 (87.533) Prec@5 97.000 (99.167) +2022-11-14 14:45:17,460 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0749) Prec@1 92.000 (87.582) Prec@5 100.000 (99.176) +2022-11-14 14:45:17,471 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0746) Prec@1 93.000 (87.641) Prec@5 99.000 (99.174) +2022-11-14 14:45:17,482 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0748) Prec@1 85.000 (87.613) Prec@5 100.000 (99.183) +2022-11-14 14:45:17,493 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0749) Prec@1 88.000 (87.617) Prec@5 100.000 (99.191) +2022-11-14 14:45:17,504 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0748) Prec@1 91.000 (87.653) Prec@5 99.000 (99.189) +2022-11-14 14:45:17,516 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0746) Prec@1 91.000 (87.688) Prec@5 99.000 (99.188) +2022-11-14 14:45:17,529 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0743) Prec@1 92.000 (87.732) Prec@5 99.000 (99.186) +2022-11-14 14:45:17,541 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0744) Prec@1 88.000 (87.735) Prec@5 99.000 (99.184) +2022-11-14 14:45:17,551 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1232 (0.0749) Prec@1 81.000 (87.667) Prec@5 100.000 (99.192) +2022-11-14 14:45:17,562 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0749) Prec@1 87.000 (87.660) Prec@5 99.000 (99.190) +2022-11-14 14:45:17,635 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:45:17,945 Epoch: [249][0/500] Time 0.026 (0.026) Data 0.224 (0.224) Loss 0.0364 (0.0364) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:45:18,149 Epoch: [249][10/500] Time 0.016 (0.019) Data 0.003 (0.022) Loss 0.0713 (0.0539) Prec@1 87.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 14:45:18,354 Epoch: [249][20/500] Time 0.019 (0.018) Data 0.002 (0.012) Loss 0.0354 (0.0477) Prec@1 94.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 14:45:18,589 Epoch: [249][30/500] Time 0.022 (0.019) Data 0.001 (0.009) Loss 0.0167 (0.0399) Prec@1 99.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 14:45:18,839 Epoch: [249][40/500] Time 0.023 (0.020) Data 0.002 (0.007) Loss 0.0322 (0.0384) Prec@1 95.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:45:19,090 Epoch: [249][50/500] Time 0.023 (0.020) Data 0.002 (0.006) Loss 0.0591 (0.0419) Prec@1 90.000 (93.000) Prec@5 100.000 (99.833) +2022-11-14 14:45:19,343 Epoch: [249][60/500] Time 0.023 (0.021) Data 0.002 (0.005) Loss 0.0248 (0.0394) Prec@1 96.000 (93.429) Prec@5 100.000 (99.857) +2022-11-14 14:45:19,595 Epoch: [249][70/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0325 (0.0386) Prec@1 95.000 (93.625) Prec@5 100.000 (99.875) +2022-11-14 14:45:20,015 Epoch: [249][80/500] Time 0.039 (0.023) Data 0.002 (0.005) Loss 0.0442 (0.0392) Prec@1 92.000 (93.444) Prec@5 100.000 (99.889) +2022-11-14 14:45:20,454 Epoch: [249][90/500] Time 0.036 (0.025) Data 0.002 (0.004) Loss 0.0422 (0.0395) Prec@1 92.000 (93.300) Prec@5 100.000 (99.900) +2022-11-14 14:45:20,900 Epoch: [249][100/500] Time 0.053 (0.026) Data 0.002 (0.004) Loss 0.0464 (0.0401) Prec@1 93.000 (93.273) Prec@5 100.000 (99.909) +2022-11-14 14:45:21,330 Epoch: [249][110/500] Time 0.039 (0.027) Data 0.002 (0.004) Loss 0.0318 (0.0394) Prec@1 97.000 (93.583) Prec@5 100.000 (99.917) +2022-11-14 14:45:21,775 Epoch: [249][120/500] Time 0.041 (0.028) Data 0.002 (0.004) Loss 0.0393 (0.0394) Prec@1 93.000 (93.538) Prec@5 100.000 (99.923) +2022-11-14 14:45:22,215 Epoch: [249][130/500] Time 0.040 (0.029) Data 0.002 (0.004) Loss 0.0196 (0.0380) Prec@1 98.000 (93.857) Prec@5 100.000 (99.929) +2022-11-14 14:45:22,656 Epoch: [249][140/500] Time 0.039 (0.030) Data 0.002 (0.003) Loss 0.0294 (0.0374) Prec@1 97.000 (94.067) Prec@5 99.000 (99.867) +2022-11-14 14:45:23,098 Epoch: [249][150/500] Time 0.040 (0.030) Data 0.002 (0.003) Loss 0.0410 (0.0376) Prec@1 93.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 14:45:23,545 Epoch: [249][160/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0424 (0.0379) Prec@1 92.000 (93.882) Prec@5 100.000 (99.882) +2022-11-14 14:45:23,992 Epoch: [249][170/500] Time 0.042 (0.031) Data 0.002 (0.003) Loss 0.0333 (0.0377) Prec@1 95.000 (93.944) Prec@5 100.000 (99.889) +2022-11-14 14:45:24,428 Epoch: [249][180/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0279 (0.0372) Prec@1 95.000 (94.000) Prec@5 100.000 (99.895) +2022-11-14 14:45:24,863 Epoch: [249][190/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0346 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (99.900) +2022-11-14 14:45:25,295 Epoch: [249][200/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0325 (0.0368) Prec@1 95.000 (94.048) Prec@5 100.000 (99.905) +2022-11-14 14:45:25,733 Epoch: [249][210/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0399 (0.0369) Prec@1 93.000 (94.000) Prec@5 100.000 (99.909) +2022-11-14 14:45:26,178 Epoch: [249][220/500] Time 0.040 (0.033) Data 0.001 (0.003) Loss 0.0212 (0.0363) Prec@1 96.000 (94.087) Prec@5 100.000 (99.913) +2022-11-14 14:45:26,618 Epoch: [249][230/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0531 (0.0370) Prec@1 91.000 (93.958) Prec@5 100.000 (99.917) +2022-11-14 14:45:27,055 Epoch: [249][240/500] Time 0.040 (0.034) Data 0.001 (0.003) Loss 0.0543 (0.0377) Prec@1 92.000 (93.880) Prec@5 100.000 (99.920) +2022-11-14 14:45:27,492 Epoch: [249][250/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0264 (0.0372) Prec@1 97.000 (94.000) Prec@5 99.000 (99.885) +2022-11-14 14:45:27,930 Epoch: [249][260/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0292 (0.0369) Prec@1 96.000 (94.074) Prec@5 100.000 (99.889) +2022-11-14 14:45:28,370 Epoch: [249][270/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0514 (0.0374) Prec@1 92.000 (94.000) Prec@5 99.000 (99.857) +2022-11-14 14:45:28,799 Epoch: [249][280/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0522 (0.0380) Prec@1 90.000 (93.862) Prec@5 100.000 (99.862) +2022-11-14 14:45:29,218 Epoch: [249][290/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0334 (0.0378) Prec@1 96.000 (93.933) Prec@5 100.000 (99.867) +2022-11-14 14:45:29,638 Epoch: [249][300/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0529 (0.0383) Prec@1 91.000 (93.839) Prec@5 99.000 (99.839) +2022-11-14 14:45:30,074 Epoch: [249][310/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0307 (0.0381) Prec@1 95.000 (93.875) Prec@5 100.000 (99.844) +2022-11-14 14:45:30,516 Epoch: [249][320/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0312 (0.0378) Prec@1 95.000 (93.909) Prec@5 100.000 (99.848) +2022-11-14 14:45:30,957 Epoch: [249][330/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0281 (0.0376) Prec@1 94.000 (93.912) Prec@5 100.000 (99.853) +2022-11-14 14:45:31,392 Epoch: [249][340/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0337 (0.0375) Prec@1 96.000 (93.971) Prec@5 100.000 (99.857) +2022-11-14 14:45:31,823 Epoch: [249][350/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0431 (0.0376) Prec@1 94.000 (93.972) Prec@5 100.000 (99.861) +2022-11-14 14:45:32,269 Epoch: [249][360/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0167 (0.0370) Prec@1 97.000 (94.054) Prec@5 100.000 (99.865) +2022-11-14 14:45:32,705 Epoch: [249][370/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0227 (0.0367) Prec@1 97.000 (94.132) Prec@5 100.000 (99.868) +2022-11-14 14:45:33,139 Epoch: [249][380/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.0496 (0.0370) Prec@1 92.000 (94.077) Prec@5 100.000 (99.872) +2022-11-14 14:45:33,578 Epoch: [249][390/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0307 (0.0368) Prec@1 94.000 (94.075) Prec@5 100.000 (99.875) +2022-11-14 14:45:34,014 Epoch: [249][400/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0302 (0.0367) Prec@1 97.000 (94.146) Prec@5 100.000 (99.878) +2022-11-14 14:45:34,452 Epoch: [249][410/500] Time 0.036 (0.036) Data 0.002 (0.002) Loss 0.0400 (0.0368) Prec@1 94.000 (94.143) Prec@5 99.000 (99.857) +2022-11-14 14:45:34,892 Epoch: [249][420/500] Time 0.046 (0.036) Data 0.002 (0.002) Loss 0.0217 (0.0364) Prec@1 97.000 (94.209) Prec@5 100.000 (99.860) +2022-11-14 14:45:35,332 Epoch: [249][430/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0357 (0.0364) Prec@1 94.000 (94.205) Prec@5 99.000 (99.841) +2022-11-14 14:45:35,762 Epoch: [249][440/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0403 (0.0365) Prec@1 94.000 (94.200) Prec@5 100.000 (99.844) +2022-11-14 14:45:36,192 Epoch: [249][450/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0274 (0.0363) Prec@1 95.000 (94.217) Prec@5 100.000 (99.848) +2022-11-14 14:45:36,630 Epoch: [249][460/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0446 (0.0365) Prec@1 92.000 (94.170) Prec@5 100.000 (99.851) +2022-11-14 14:45:37,075 Epoch: [249][470/500] Time 0.040 (0.036) Data 0.002 (0.002) Loss 0.0478 (0.0367) Prec@1 89.000 (94.062) Prec@5 100.000 (99.854) +2022-11-14 14:45:37,519 Epoch: [249][480/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0225 (0.0364) Prec@1 97.000 (94.122) Prec@5 100.000 (99.857) +2022-11-14 14:45:37,954 Epoch: [249][490/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0272 (0.0362) Prec@1 97.000 (94.180) Prec@5 100.000 (99.860) +2022-11-14 14:45:38,347 Epoch: [249][499/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0153 (0.0358) Prec@1 98.000 (94.255) Prec@5 100.000 (99.863) +2022-11-14 14:45:38,627 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0702 (0.0702) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:38,635 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0700) Prec@1 88.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:45:38,643 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0744) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:38,656 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0726) Prec@1 89.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 14:45:38,666 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0716) Prec@1 89.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 14:45:38,674 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0697) Prec@1 90.000 (88.167) Prec@5 99.000 (99.500) +2022-11-14 14:45:38,681 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0705) Prec@1 87.000 (88.000) Prec@5 100.000 (99.571) +2022-11-14 14:45:38,690 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0713) Prec@1 87.000 (87.875) Prec@5 100.000 (99.625) +2022-11-14 14:45:38,698 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0717) Prec@1 88.000 (87.889) Prec@5 100.000 (99.667) +2022-11-14 14:45:38,709 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0727) Prec@1 86.000 (87.700) Prec@5 99.000 (99.600) +2022-11-14 14:45:38,719 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0703) Prec@1 93.000 (88.182) Prec@5 100.000 (99.636) +2022-11-14 14:45:38,729 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0713) Prec@1 87.000 (88.083) Prec@5 99.000 (99.583) +2022-11-14 14:45:38,739 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0694) Prec@1 92.000 (88.385) Prec@5 100.000 (99.615) +2022-11-14 14:45:38,749 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0706) Prec@1 86.000 (88.214) Prec@5 99.000 (99.571) +2022-11-14 14:45:38,760 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0703) Prec@1 88.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 14:45:38,770 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0703) Prec@1 88.000 (88.188) Prec@5 99.000 (99.562) +2022-11-14 14:45:38,779 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0483 (0.0690) Prec@1 94.000 (88.529) Prec@5 99.000 (99.529) +2022-11-14 14:45:38,791 Test: [17/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0704) Prec@1 88.000 (88.500) Prec@5 100.000 (99.556) +2022-11-14 14:45:38,802 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0713) Prec@1 82.000 (88.158) Prec@5 98.000 (99.474) +2022-11-14 14:45:38,813 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0724) Prec@1 83.000 (87.900) Prec@5 99.000 (99.450) +2022-11-14 14:45:38,823 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0725) Prec@1 88.000 (87.905) Prec@5 100.000 (99.476) +2022-11-14 14:45:38,837 Test: [21/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0734) Prec@1 86.000 (87.818) Prec@5 99.000 (99.455) +2022-11-14 14:45:38,850 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1110 (0.0750) Prec@1 83.000 (87.609) Prec@5 99.000 (99.435) +2022-11-14 14:45:38,860 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0752) Prec@1 86.000 (87.542) Prec@5 100.000 (99.458) +2022-11-14 14:45:38,869 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0756) Prec@1 85.000 (87.440) Prec@5 100.000 (99.480) +2022-11-14 14:45:38,882 Test: [25/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0762) Prec@1 84.000 (87.308) Prec@5 99.000 (99.462) +2022-11-14 14:45:38,893 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0754) Prec@1 92.000 (87.481) Prec@5 100.000 (99.481) +2022-11-14 14:45:38,904 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0746) Prec@1 90.000 (87.571) Prec@5 100.000 (99.500) +2022-11-14 14:45:38,914 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0741) Prec@1 90.000 (87.655) Prec@5 99.000 (99.483) +2022-11-14 14:45:38,927 Test: [29/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0743) Prec@1 87.000 (87.633) Prec@5 100.000 (99.500) +2022-11-14 14:45:38,937 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0743) Prec@1 86.000 (87.581) Prec@5 100.000 (99.516) +2022-11-14 14:45:38,947 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0737) Prec@1 92.000 (87.719) Prec@5 99.000 (99.500) +2022-11-14 14:45:38,957 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0743) Prec@1 85.000 (87.636) Prec@5 98.000 (99.455) +2022-11-14 14:45:38,969 Test: [33/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0754) Prec@1 81.000 (87.441) Prec@5 100.000 (99.471) +2022-11-14 14:45:38,981 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0754) Prec@1 90.000 (87.514) Prec@5 98.000 (99.429) +2022-11-14 14:45:38,992 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0752) Prec@1 91.000 (87.611) Prec@5 100.000 (99.444) +2022-11-14 14:45:39,001 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0749) Prec@1 90.000 (87.676) Prec@5 99.000 (99.432) +2022-11-14 14:45:39,012 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0757) Prec@1 78.000 (87.421) Prec@5 98.000 (99.395) +2022-11-14 14:45:39,023 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0753) Prec@1 92.000 (87.538) Prec@5 99.000 (99.385) +2022-11-14 14:45:39,034 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0755) Prec@1 87.000 (87.525) Prec@5 99.000 (99.375) +2022-11-14 14:45:39,043 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0757) Prec@1 88.000 (87.537) Prec@5 99.000 (99.366) +2022-11-14 14:45:39,055 Test: [41/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0756) Prec@1 88.000 (87.548) Prec@5 98.000 (99.333) +2022-11-14 14:45:39,066 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0480 (0.0749) Prec@1 92.000 (87.651) Prec@5 100.000 (99.349) +2022-11-14 14:45:39,077 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0747) Prec@1 91.000 (87.727) Prec@5 98.000 (99.318) +2022-11-14 14:45:39,086 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0744) Prec@1 91.000 (87.800) Prec@5 99.000 (99.311) +2022-11-14 14:45:39,099 Test: [45/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0748) Prec@1 85.000 (87.739) Prec@5 100.000 (99.326) +2022-11-14 14:45:39,111 Test: [46/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0746) Prec@1 88.000 (87.745) Prec@5 99.000 (99.319) +2022-11-14 14:45:39,120 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0749) Prec@1 83.000 (87.646) Prec@5 99.000 (99.312) +2022-11-14 14:45:39,129 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0744) Prec@1 93.000 (87.755) Prec@5 99.000 (99.306) +2022-11-14 14:45:39,142 Test: [49/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0750) Prec@1 87.000 (87.740) Prec@5 99.000 (99.300) +2022-11-14 14:45:39,153 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0745) Prec@1 91.000 (87.804) Prec@5 100.000 (99.314) +2022-11-14 14:45:39,162 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0744) Prec@1 88.000 (87.808) Prec@5 99.000 (99.308) +2022-11-14 14:45:39,172 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0745) Prec@1 87.000 (87.792) Prec@5 99.000 (99.302) +2022-11-14 14:45:39,181 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0742) Prec@1 91.000 (87.852) Prec@5 100.000 (99.315) +2022-11-14 14:45:39,191 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0745) Prec@1 86.000 (87.818) Prec@5 100.000 (99.327) +2022-11-14 14:45:39,201 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0743) Prec@1 89.000 (87.839) Prec@5 99.000 (99.321) +2022-11-14 14:45:39,211 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0744) Prec@1 87.000 (87.825) Prec@5 100.000 (99.333) +2022-11-14 14:45:39,221 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0740) Prec@1 90.000 (87.862) Prec@5 100.000 (99.345) +2022-11-14 14:45:39,231 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1084 (0.0746) Prec@1 83.000 (87.780) Prec@5 99.000 (99.339) +2022-11-14 14:45:39,241 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0747) Prec@1 85.000 (87.733) Prec@5 99.000 (99.333) +2022-11-14 14:45:39,251 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0748) Prec@1 85.000 (87.689) Prec@5 100.000 (99.344) +2022-11-14 14:45:39,261 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0747) Prec@1 88.000 (87.694) Prec@5 99.000 (99.339) +2022-11-14 14:45:39,271 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0744) Prec@1 92.000 (87.762) Prec@5 99.000 (99.333) +2022-11-14 14:45:39,280 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0739) Prec@1 92.000 (87.828) Prec@5 99.000 (99.328) +2022-11-14 14:45:39,291 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0742) Prec@1 86.000 (87.800) Prec@5 100.000 (99.338) +2022-11-14 14:45:39,300 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0744) Prec@1 82.000 (87.712) Prec@5 100.000 (99.348) +2022-11-14 14:45:39,311 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0740) Prec@1 92.000 (87.776) Prec@5 100.000 (99.358) +2022-11-14 14:45:39,320 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0741) Prec@1 86.000 (87.750) Prec@5 98.000 (99.338) +2022-11-14 14:45:39,330 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0741) Prec@1 87.000 (87.739) Prec@5 99.000 (99.333) +2022-11-14 14:45:39,340 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0742) Prec@1 89.000 (87.757) Prec@5 100.000 (99.343) +2022-11-14 14:45:39,349 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0746) Prec@1 86.000 (87.732) Prec@5 98.000 (99.324) +2022-11-14 14:45:39,360 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0746) Prec@1 86.000 (87.708) Prec@5 100.000 (99.333) +2022-11-14 14:45:39,370 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0745) Prec@1 89.000 (87.726) Prec@5 99.000 (99.329) +2022-11-14 14:45:39,380 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0741) Prec@1 94.000 (87.811) Prec@5 100.000 (99.338) +2022-11-14 14:45:39,389 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0746) Prec@1 82.000 (87.733) Prec@5 99.000 (99.333) +2022-11-14 14:45:39,399 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0744) Prec@1 89.000 (87.750) Prec@5 99.000 (99.329) +2022-11-14 14:45:39,411 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0744) Prec@1 90.000 (87.779) Prec@5 99.000 (99.325) +2022-11-14 14:45:39,421 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0745) Prec@1 86.000 (87.756) Prec@5 97.000 (99.295) +2022-11-14 14:45:39,430 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0745) Prec@1 88.000 (87.759) Prec@5 100.000 (99.304) +2022-11-14 14:45:39,441 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0744) Prec@1 88.000 (87.763) Prec@5 100.000 (99.312) +2022-11-14 14:45:39,453 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0744) Prec@1 89.000 (87.778) Prec@5 99.000 (99.309) +2022-11-14 14:45:39,464 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0746) Prec@1 84.000 (87.732) Prec@5 100.000 (99.317) +2022-11-14 14:45:39,474 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0750) Prec@1 84.000 (87.687) Prec@5 100.000 (99.325) +2022-11-14 14:45:39,485 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0749) Prec@1 89.000 (87.702) Prec@5 98.000 (99.310) +2022-11-14 14:45:39,495 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0751) Prec@1 86.000 (87.682) Prec@5 98.000 (99.294) +2022-11-14 14:45:39,507 Test: [85/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0755) Prec@1 84.000 (87.640) Prec@5 100.000 (99.302) +2022-11-14 14:45:39,518 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0754) Prec@1 87.000 (87.632) Prec@5 100.000 (99.310) +2022-11-14 14:45:39,528 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0755) Prec@1 88.000 (87.636) Prec@5 98.000 (99.295) +2022-11-14 14:45:39,537 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0754) Prec@1 88.000 (87.640) Prec@5 100.000 (99.303) +2022-11-14 14:45:39,549 Test: [89/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0754) Prec@1 89.000 (87.656) Prec@5 99.000 (99.300) +2022-11-14 14:45:39,560 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0752) Prec@1 91.000 (87.692) Prec@5 100.000 (99.308) +2022-11-14 14:45:39,570 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0751) Prec@1 89.000 (87.707) Prec@5 99.000 (99.304) +2022-11-14 14:45:39,580 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0751) Prec@1 86.000 (87.688) Prec@5 100.000 (99.312) +2022-11-14 14:45:39,590 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0751) Prec@1 89.000 (87.702) Prec@5 100.000 (99.319) +2022-11-14 14:45:39,601 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 88.000 (87.705) Prec@5 100.000 (99.326) +2022-11-14 14:45:39,612 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0752) Prec@1 89.000 (87.719) Prec@5 100.000 (99.333) +2022-11-14 14:45:39,622 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0749) Prec@1 92.000 (87.763) Prec@5 99.000 (99.330) +2022-11-14 14:45:39,632 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0752) Prec@1 86.000 (87.745) Prec@5 99.000 (99.327) +2022-11-14 14:45:39,642 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0755) Prec@1 87.000 (87.737) Prec@5 99.000 (99.323) +2022-11-14 14:45:39,652 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0754) Prec@1 89.000 (87.750) Prec@5 100.000 (99.330) +2022-11-14 14:45:39,707 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:45:40,005 Epoch: [250][0/500] Time 0.022 (0.022) Data 0.218 (0.218) Loss 0.0428 (0.0428) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:40,221 Epoch: [250][10/500] Time 0.018 (0.019) Data 0.001 (0.021) Loss 0.0528 (0.0478) Prec@1 90.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:45:40,433 Epoch: [250][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0289 (0.0415) Prec@1 95.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:45:40,629 Epoch: [250][30/500] Time 0.016 (0.019) Data 0.002 (0.009) Loss 0.0317 (0.0391) Prec@1 97.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:45:40,890 Epoch: [250][40/500] Time 0.035 (0.020) Data 0.002 (0.007) Loss 0.0220 (0.0356) Prec@1 98.000 (95.000) Prec@5 99.000 (99.600) +2022-11-14 14:45:41,195 Epoch: [250][50/500] Time 0.027 (0.021) Data 0.002 (0.006) Loss 0.0274 (0.0343) Prec@1 96.000 (95.167) Prec@5 100.000 (99.667) +2022-11-14 14:45:41,511 Epoch: [250][60/500] Time 0.028 (0.022) Data 0.002 (0.005) Loss 0.0372 (0.0347) Prec@1 94.000 (95.000) Prec@5 100.000 (99.714) +2022-11-14 14:45:41,820 Epoch: [250][70/500] Time 0.029 (0.023) Data 0.001 (0.005) Loss 0.0395 (0.0353) Prec@1 93.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 14:45:42,130 Epoch: [250][80/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0199 (0.0336) Prec@1 97.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 14:45:42,445 Epoch: [250][90/500] Time 0.028 (0.024) Data 0.001 (0.004) Loss 0.0505 (0.0353) Prec@1 92.000 (94.700) Prec@5 99.000 (99.700) +2022-11-14 14:45:42,755 Epoch: [250][100/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0403 (0.0357) Prec@1 92.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 14:45:43,070 Epoch: [250][110/500] Time 0.029 (0.025) Data 0.001 (0.004) Loss 0.0449 (0.0365) Prec@1 93.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 14:45:43,386 Epoch: [250][120/500] Time 0.035 (0.025) Data 0.002 (0.003) Loss 0.0318 (0.0361) Prec@1 93.000 (94.231) Prec@5 100.000 (99.692) +2022-11-14 14:45:43,694 Epoch: [250][130/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0332 (0.0359) Prec@1 95.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 14:45:44,003 Epoch: [250][140/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.0376 (0.0360) Prec@1 96.000 (94.400) Prec@5 100.000 (99.733) +2022-11-14 14:45:44,313 Epoch: [250][150/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0363 (0.0360) Prec@1 96.000 (94.500) Prec@5 99.000 (99.688) +2022-11-14 14:45:44,629 Epoch: [250][160/500] Time 0.028 (0.026) Data 0.002 (0.003) Loss 0.0320 (0.0358) Prec@1 95.000 (94.529) Prec@5 100.000 (99.706) +2022-11-14 14:45:44,943 Epoch: [250][170/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0314 (0.0356) Prec@1 95.000 (94.556) Prec@5 100.000 (99.722) +2022-11-14 14:45:45,254 Epoch: [250][180/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0412 (0.0359) Prec@1 94.000 (94.526) Prec@5 100.000 (99.737) +2022-11-14 14:45:45,567 Epoch: [250][190/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0225 (0.0352) Prec@1 98.000 (94.700) Prec@5 100.000 (99.750) +2022-11-14 14:45:45,887 Epoch: [250][200/500] Time 0.037 (0.026) Data 0.001 (0.003) Loss 0.0196 (0.0344) Prec@1 98.000 (94.857) Prec@5 100.000 (99.762) +2022-11-14 14:45:46,194 Epoch: [250][210/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0361 (0.0345) Prec@1 94.000 (94.818) Prec@5 100.000 (99.773) +2022-11-14 14:45:46,511 Epoch: [250][220/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0268 (0.0342) Prec@1 96.000 (94.870) Prec@5 100.000 (99.783) +2022-11-14 14:45:46,829 Epoch: [250][230/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0238 (0.0338) Prec@1 97.000 (94.958) Prec@5 99.000 (99.750) +2022-11-14 14:45:47,148 Epoch: [250][240/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0298 (0.0336) Prec@1 95.000 (94.960) Prec@5 100.000 (99.760) +2022-11-14 14:45:47,468 Epoch: [250][250/500] Time 0.029 (0.027) Data 0.001 (0.002) Loss 0.0222 (0.0332) Prec@1 97.000 (95.038) Prec@5 100.000 (99.769) +2022-11-14 14:45:47,783 Epoch: [250][260/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0203 (0.0327) Prec@1 98.000 (95.148) Prec@5 100.000 (99.778) +2022-11-14 14:45:48,100 Epoch: [250][270/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0222 (0.0323) Prec@1 96.000 (95.179) Prec@5 100.000 (99.786) +2022-11-14 14:45:48,420 Epoch: [250][280/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0341 (0.0324) Prec@1 95.000 (95.172) Prec@5 100.000 (99.793) +2022-11-14 14:45:48,769 Epoch: [250][290/500] Time 0.043 (0.027) Data 0.002 (0.002) Loss 0.0496 (0.0329) Prec@1 92.000 (95.067) Prec@5 100.000 (99.800) +2022-11-14 14:45:49,247 Epoch: [250][300/500] Time 0.042 (0.027) Data 0.002 (0.002) Loss 0.0399 (0.0332) Prec@1 93.000 (95.000) Prec@5 99.000 (99.774) +2022-11-14 14:45:49,726 Epoch: [250][310/500] Time 0.044 (0.028) Data 0.001 (0.002) Loss 0.0263 (0.0330) Prec@1 96.000 (95.031) Prec@5 100.000 (99.781) +2022-11-14 14:45:50,206 Epoch: [250][320/500] Time 0.044 (0.028) Data 0.001 (0.002) Loss 0.0358 (0.0330) Prec@1 92.000 (94.939) Prec@5 100.000 (99.788) +2022-11-14 14:45:50,684 Epoch: [250][330/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.0574 (0.0338) Prec@1 91.000 (94.824) Prec@5 99.000 (99.765) +2022-11-14 14:45:51,165 Epoch: [250][340/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.0410 (0.0340) Prec@1 95.000 (94.829) Prec@5 99.000 (99.743) +2022-11-14 14:45:51,645 Epoch: [250][350/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0458 (0.0343) Prec@1 92.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 14:45:52,123 Epoch: [250][360/500] Time 0.044 (0.030) Data 0.002 (0.002) Loss 0.0258 (0.0341) Prec@1 94.000 (94.730) Prec@5 100.000 (99.757) +2022-11-14 14:45:52,602 Epoch: [250][370/500] Time 0.043 (0.030) Data 0.002 (0.002) Loss 0.0133 (0.0335) Prec@1 99.000 (94.842) Prec@5 100.000 (99.763) +2022-11-14 14:45:53,081 Epoch: [250][380/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0313 (0.0335) Prec@1 94.000 (94.821) Prec@5 100.000 (99.769) +2022-11-14 14:45:53,561 Epoch: [250][390/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0312 (0.0334) Prec@1 96.000 (94.850) Prec@5 100.000 (99.775) +2022-11-14 14:45:54,041 Epoch: [250][400/500] Time 0.044 (0.031) Data 0.002 (0.002) Loss 0.0428 (0.0336) Prec@1 92.000 (94.780) Prec@5 100.000 (99.780) +2022-11-14 14:45:54,522 Epoch: [250][410/500] Time 0.045 (0.031) Data 0.002 (0.002) Loss 0.0357 (0.0337) Prec@1 95.000 (94.786) Prec@5 100.000 (99.786) +2022-11-14 14:45:55,000 Epoch: [250][420/500] Time 0.044 (0.032) Data 0.001 (0.002) Loss 0.0400 (0.0338) Prec@1 94.000 (94.767) Prec@5 100.000 (99.791) +2022-11-14 14:45:55,479 Epoch: [250][430/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0400 (0.0340) Prec@1 92.000 (94.705) Prec@5 100.000 (99.795) +2022-11-14 14:45:55,961 Epoch: [250][440/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0368 (0.0340) Prec@1 94.000 (94.689) Prec@5 100.000 (99.800) +2022-11-14 14:45:56,438 Epoch: [250][450/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0212 (0.0337) Prec@1 97.000 (94.739) Prec@5 100.000 (99.804) +2022-11-14 14:45:56,917 Epoch: [250][460/500] Time 0.052 (0.033) Data 0.002 (0.002) Loss 0.0193 (0.0334) Prec@1 97.000 (94.787) Prec@5 100.000 (99.809) +2022-11-14 14:45:57,393 Epoch: [250][470/500] Time 0.050 (0.033) Data 0.002 (0.002) Loss 0.0312 (0.0334) Prec@1 94.000 (94.771) Prec@5 99.000 (99.792) +2022-11-14 14:45:57,871 Epoch: [250][480/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0225 (0.0332) Prec@1 97.000 (94.816) Prec@5 100.000 (99.796) +2022-11-14 14:45:58,346 Epoch: [250][490/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0245 (0.0330) Prec@1 97.000 (94.860) Prec@5 100.000 (99.800) +2022-11-14 14:45:58,771 Epoch: [250][499/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0385 (0.0331) Prec@1 94.000 (94.843) Prec@5 100.000 (99.804) +2022-11-14 14:45:59,060 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0581 (0.0581) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:45:59,071 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0710) Prec@1 88.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:45:59,082 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0769) Prec@1 83.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 14:45:59,095 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0765) Prec@1 88.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:45:59,106 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0754) Prec@1 87.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:45:59,115 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0359 (0.0688) Prec@1 94.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 14:45:59,125 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0690) Prec@1 91.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 14:45:59,137 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0703) Prec@1 87.000 (88.500) Prec@5 99.000 (99.625) +2022-11-14 14:45:59,146 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0713) Prec@1 88.000 (88.444) Prec@5 100.000 (99.667) +2022-11-14 14:45:59,156 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0707) Prec@1 89.000 (88.500) Prec@5 99.000 (99.600) +2022-11-14 14:45:59,167 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0706) Prec@1 87.000 (88.364) Prec@5 100.000 (99.636) +2022-11-14 14:45:59,176 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0730) Prec@1 85.000 (88.083) Prec@5 100.000 (99.667) +2022-11-14 14:45:59,187 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0706) Prec@1 93.000 (88.462) Prec@5 100.000 (99.692) +2022-11-14 14:45:59,196 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0710) Prec@1 85.000 (88.214) Prec@5 100.000 (99.714) +2022-11-14 14:45:59,206 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0716) Prec@1 88.000 (88.200) Prec@5 100.000 (99.733) +2022-11-14 14:45:59,216 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0715) Prec@1 89.000 (88.250) Prec@5 99.000 (99.688) +2022-11-14 14:45:59,229 Test: [16/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0710) Prec@1 90.000 (88.353) Prec@5 98.000 (99.588) +2022-11-14 14:45:59,240 Test: [17/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1203 (0.0737) Prec@1 81.000 (87.944) Prec@5 99.000 (99.556) +2022-11-14 14:45:59,251 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0735) Prec@1 87.000 (87.895) Prec@5 99.000 (99.526) +2022-11-14 14:45:59,262 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0749) Prec@1 85.000 (87.750) Prec@5 100.000 (99.550) +2022-11-14 14:45:59,273 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0755) Prec@1 86.000 (87.667) Prec@5 100.000 (99.571) +2022-11-14 14:45:59,284 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0758) Prec@1 86.000 (87.591) Prec@5 100.000 (99.591) +2022-11-14 14:45:59,293 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0771) Prec@1 83.000 (87.391) Prec@5 97.000 (99.478) +2022-11-14 14:45:59,304 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0772) Prec@1 86.000 (87.333) Prec@5 100.000 (99.500) +2022-11-14 14:45:59,313 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0778) Prec@1 85.000 (87.240) Prec@5 100.000 (99.520) +2022-11-14 14:45:59,324 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0786) Prec@1 86.000 (87.192) Prec@5 99.000 (99.500) +2022-11-14 14:45:59,335 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0780) Prec@1 90.000 (87.296) Prec@5 100.000 (99.519) +2022-11-14 14:45:59,347 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0772) Prec@1 91.000 (87.429) Prec@5 100.000 (99.536) +2022-11-14 14:45:59,358 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0763) Prec@1 92.000 (87.586) Prec@5 100.000 (99.552) +2022-11-14 14:45:59,369 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0761) Prec@1 89.000 (87.633) Prec@5 99.000 (99.533) +2022-11-14 14:45:59,380 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0753) Prec@1 91.000 (87.742) Prec@5 100.000 (99.548) +2022-11-14 14:45:59,390 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0753) Prec@1 88.000 (87.750) Prec@5 100.000 (99.562) +2022-11-14 14:45:59,401 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0756) Prec@1 85.000 (87.667) Prec@5 99.000 (99.545) +2022-11-14 14:45:59,411 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0763) Prec@1 83.000 (87.529) Prec@5 100.000 (99.559) +2022-11-14 14:45:59,422 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0762) Prec@1 89.000 (87.571) Prec@5 99.000 (99.543) +2022-11-14 14:45:59,431 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0760) Prec@1 90.000 (87.639) Prec@5 100.000 (99.556) +2022-11-14 14:45:59,442 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0760) Prec@1 87.000 (87.622) Prec@5 99.000 (99.541) +2022-11-14 14:45:59,453 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0766) Prec@1 83.000 (87.500) Prec@5 99.000 (99.526) +2022-11-14 14:45:59,464 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0760) Prec@1 92.000 (87.615) Prec@5 99.000 (99.513) +2022-11-14 14:45:59,473 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0756) Prec@1 91.000 (87.700) Prec@5 99.000 (99.500) +2022-11-14 14:45:59,486 Test: [40/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0756) Prec@1 88.000 (87.707) Prec@5 99.000 (99.488) +2022-11-14 14:45:59,498 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0755) Prec@1 89.000 (87.738) Prec@5 99.000 (99.476) +2022-11-14 14:45:59,508 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0750) Prec@1 89.000 (87.767) Prec@5 99.000 (99.465) +2022-11-14 14:45:59,519 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0748) Prec@1 90.000 (87.818) Prec@5 97.000 (99.409) +2022-11-14 14:45:59,529 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0745) Prec@1 90.000 (87.867) Prec@5 99.000 (99.400) +2022-11-14 14:45:59,539 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0750) Prec@1 83.000 (87.761) Prec@5 98.000 (99.370) +2022-11-14 14:45:59,550 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0746) Prec@1 92.000 (87.851) Prec@5 99.000 (99.362) +2022-11-14 14:45:59,560 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0749) Prec@1 85.000 (87.792) Prec@5 99.000 (99.354) +2022-11-14 14:45:59,571 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0744) Prec@1 90.000 (87.837) Prec@5 100.000 (99.367) +2022-11-14 14:45:59,581 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0751) Prec@1 82.000 (87.720) Prec@5 99.000 (99.360) +2022-11-14 14:45:59,592 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0750) Prec@1 89.000 (87.745) Prec@5 100.000 (99.373) +2022-11-14 14:45:59,603 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0748) Prec@1 90.000 (87.788) Prec@5 100.000 (99.385) +2022-11-14 14:45:59,613 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0752) Prec@1 84.000 (87.717) Prec@5 99.000 (99.377) +2022-11-14 14:45:59,624 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0752) Prec@1 89.000 (87.741) Prec@5 99.000 (99.370) +2022-11-14 14:45:59,633 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0754) Prec@1 84.000 (87.673) Prec@5 100.000 (99.382) +2022-11-14 14:45:59,644 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0755) Prec@1 88.000 (87.679) Prec@5 100.000 (99.393) +2022-11-14 14:45:59,654 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0749) Prec@1 94.000 (87.789) Prec@5 100.000 (99.404) +2022-11-14 14:45:59,664 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0749) Prec@1 91.000 (87.845) Prec@5 100.000 (99.414) +2022-11-14 14:45:59,675 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0751) Prec@1 84.000 (87.780) Prec@5 100.000 (99.424) +2022-11-14 14:45:59,686 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0751) Prec@1 85.000 (87.733) Prec@5 99.000 (99.417) +2022-11-14 14:45:59,696 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0752) Prec@1 87.000 (87.721) Prec@5 100.000 (99.426) +2022-11-14 14:45:59,707 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0751) Prec@1 89.000 (87.742) Prec@5 99.000 (99.419) +2022-11-14 14:45:59,717 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0747) Prec@1 92.000 (87.810) Prec@5 99.000 (99.413) +2022-11-14 14:45:59,728 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0743) Prec@1 92.000 (87.875) Prec@5 100.000 (99.422) +2022-11-14 14:45:59,737 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0741) Prec@1 88.000 (87.877) Prec@5 100.000 (99.431) +2022-11-14 14:45:59,748 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0742) Prec@1 86.000 (87.848) Prec@5 99.000 (99.424) +2022-11-14 14:45:59,759 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0737) Prec@1 94.000 (87.940) Prec@5 100.000 (99.433) +2022-11-14 14:45:59,769 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0738) Prec@1 87.000 (87.926) Prec@5 99.000 (99.426) +2022-11-14 14:45:59,779 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0736) Prec@1 91.000 (87.971) Prec@5 99.000 (99.420) +2022-11-14 14:45:59,789 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0738) Prec@1 85.000 (87.929) Prec@5 99.000 (99.414) +2022-11-14 14:45:59,799 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0743) Prec@1 84.000 (87.873) Prec@5 100.000 (99.423) +2022-11-14 14:45:59,810 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0740) Prec@1 92.000 (87.931) Prec@5 100.000 (99.431) +2022-11-14 14:45:59,821 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0737) Prec@1 92.000 (87.986) Prec@5 100.000 (99.438) +2022-11-14 14:45:59,832 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0735) Prec@1 92.000 (88.041) Prec@5 100.000 (99.446) +2022-11-14 14:45:59,842 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0738) Prec@1 83.000 (87.973) Prec@5 100.000 (99.453) +2022-11-14 14:45:59,853 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0735) Prec@1 91.000 (88.013) Prec@5 99.000 (99.447) +2022-11-14 14:45:59,863 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0734) Prec@1 88.000 (88.013) Prec@5 99.000 (99.442) +2022-11-14 14:45:59,873 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0735) Prec@1 88.000 (88.013) Prec@5 99.000 (99.436) +2022-11-14 14:45:59,884 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0735) Prec@1 88.000 (88.013) Prec@5 100.000 (99.443) +2022-11-14 14:45:59,896 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0735) Prec@1 88.000 (88.013) Prec@5 99.000 (99.438) +2022-11-14 14:45:59,908 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0737) Prec@1 86.000 (87.988) Prec@5 99.000 (99.432) +2022-11-14 14:45:59,919 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1178 (0.0742) Prec@1 81.000 (87.902) Prec@5 99.000 (99.427) +2022-11-14 14:45:59,929 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0744) Prec@1 83.000 (87.843) Prec@5 99.000 (99.422) +2022-11-14 14:45:59,938 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0743) Prec@1 90.000 (87.869) Prec@5 99.000 (99.417) +2022-11-14 14:45:59,948 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0744) Prec@1 88.000 (87.871) Prec@5 99.000 (99.412) +2022-11-14 14:45:59,957 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0744) Prec@1 87.000 (87.860) Prec@5 100.000 (99.419) +2022-11-14 14:45:59,966 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 90.000 (87.885) Prec@5 99.000 (99.414) +2022-11-14 14:45:59,976 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0746) Prec@1 88.000 (87.886) Prec@5 99.000 (99.409) +2022-11-14 14:45:59,987 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0748) Prec@1 85.000 (87.854) Prec@5 99.000 (99.404) +2022-11-14 14:45:59,997 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0746) Prec@1 91.000 (87.889) Prec@5 100.000 (99.411) +2022-11-14 14:46:00,009 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0745) Prec@1 91.000 (87.923) Prec@5 100.000 (99.418) +2022-11-14 14:46:00,021 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0742) Prec@1 91.000 (87.957) Prec@5 99.000 (99.413) +2022-11-14 14:46:00,030 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0746) Prec@1 83.000 (87.903) Prec@5 99.000 (99.409) +2022-11-14 14:46:00,040 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0744) Prec@1 91.000 (87.936) Prec@5 100.000 (99.415) +2022-11-14 14:46:00,051 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0746) Prec@1 85.000 (87.905) Prec@5 99.000 (99.411) +2022-11-14 14:46:00,061 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0744) Prec@1 92.000 (87.948) Prec@5 99.000 (99.406) +2022-11-14 14:46:00,070 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0741) Prec@1 93.000 (88.000) Prec@5 99.000 (99.402) +2022-11-14 14:46:00,081 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0744) Prec@1 85.000 (87.969) Prec@5 97.000 (99.378) +2022-11-14 14:46:00,092 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0745) Prec@1 88.000 (87.970) Prec@5 97.000 (99.354) +2022-11-14 14:46:00,101 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0744) Prec@1 90.000 (87.990) Prec@5 99.000 (99.350) +2022-11-14 14:46:00,165 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:46:00,464 Epoch: [251][0/500] Time 0.022 (0.022) Data 0.215 (0.215) Loss 0.0374 (0.0374) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:00,673 Epoch: [251][10/500] Time 0.017 (0.019) Data 0.002 (0.021) Loss 0.0416 (0.0395) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:46:00,927 Epoch: [251][20/500] Time 0.025 (0.020) Data 0.002 (0.012) Loss 0.0345 (0.0378) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:01,244 Epoch: [251][30/500] Time 0.030 (0.023) Data 0.002 (0.009) Loss 0.0204 (0.0335) Prec@1 97.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:01,561 Epoch: [251][40/500] Time 0.030 (0.024) Data 0.002 (0.007) Loss 0.0438 (0.0355) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:01,877 Epoch: [251][50/500] Time 0.032 (0.025) Data 0.002 (0.006) Loss 0.0248 (0.0338) Prec@1 95.000 (94.167) Prec@5 100.000 (100.000) +2022-11-14 14:46:02,193 Epoch: [251][60/500] Time 0.030 (0.025) Data 0.002 (0.005) Loss 0.0467 (0.0356) Prec@1 95.000 (94.286) Prec@5 100.000 (100.000) +2022-11-14 14:46:02,513 Epoch: [251][70/500] Time 0.029 (0.026) Data 0.002 (0.005) Loss 0.0243 (0.0342) Prec@1 98.000 (94.750) Prec@5 99.000 (99.875) +2022-11-14 14:46:02,833 Epoch: [251][80/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0151 (0.0321) Prec@1 98.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 14:46:03,148 Epoch: [251][90/500] Time 0.028 (0.026) Data 0.002 (0.004) Loss 0.0446 (0.0333) Prec@1 91.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 14:46:03,459 Epoch: [251][100/500] Time 0.027 (0.026) Data 0.002 (0.004) Loss 0.0302 (0.0330) Prec@1 94.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 14:46:03,773 Epoch: [251][110/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0345 (0.0332) Prec@1 94.000 (94.583) Prec@5 100.000 (99.917) +2022-11-14 14:46:04,091 Epoch: [251][120/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0434 (0.0339) Prec@1 91.000 (94.308) Prec@5 100.000 (99.923) +2022-11-14 14:46:04,414 Epoch: [251][130/500] Time 0.025 (0.027) Data 0.003 (0.003) Loss 0.0551 (0.0355) Prec@1 91.000 (94.071) Prec@5 100.000 (99.929) +2022-11-14 14:46:04,728 Epoch: [251][140/500] Time 0.027 (0.027) Data 0.002 (0.003) Loss 0.0514 (0.0365) Prec@1 90.000 (93.800) Prec@5 100.000 (99.933) +2022-11-14 14:46:05,049 Epoch: [251][150/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0254 (0.0358) Prec@1 97.000 (94.000) Prec@5 99.000 (99.875) +2022-11-14 14:46:05,373 Epoch: [251][160/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0201 (0.0349) Prec@1 97.000 (94.176) Prec@5 100.000 (99.882) +2022-11-14 14:46:05,689 Epoch: [251][170/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0488 (0.0357) Prec@1 93.000 (94.111) Prec@5 100.000 (99.889) +2022-11-14 14:46:06,008 Epoch: [251][180/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0542 (0.0366) Prec@1 91.000 (93.947) Prec@5 100.000 (99.895) +2022-11-14 14:46:06,327 Epoch: [251][190/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0536 (0.0375) Prec@1 91.000 (93.800) Prec@5 100.000 (99.900) +2022-11-14 14:46:06,648 Epoch: [251][200/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0327 (0.0373) Prec@1 95.000 (93.857) Prec@5 100.000 (99.905) +2022-11-14 14:46:06,974 Epoch: [251][210/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0376 (0.0373) Prec@1 93.000 (93.818) Prec@5 100.000 (99.909) +2022-11-14 14:46:07,294 Epoch: [251][220/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0235 (0.0367) Prec@1 96.000 (93.913) Prec@5 100.000 (99.913) +2022-11-14 14:46:07,773 Epoch: [251][230/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0257 (0.0362) Prec@1 96.000 (94.000) Prec@5 100.000 (99.917) +2022-11-14 14:46:08,253 Epoch: [251][240/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0432 (0.0365) Prec@1 90.000 (93.840) Prec@5 99.000 (99.880) +2022-11-14 14:46:08,733 Epoch: [251][250/500] Time 0.046 (0.029) Data 0.002 (0.003) Loss 0.0245 (0.0360) Prec@1 95.000 (93.885) Prec@5 100.000 (99.885) +2022-11-14 14:46:09,210 Epoch: [251][260/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0263 (0.0357) Prec@1 96.000 (93.963) Prec@5 100.000 (99.889) +2022-11-14 14:46:09,690 Epoch: [251][270/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0433 (0.0359) Prec@1 93.000 (93.929) Prec@5 99.000 (99.857) +2022-11-14 14:46:10,170 Epoch: [251][280/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0468 (0.0363) Prec@1 91.000 (93.828) Prec@5 99.000 (99.828) +2022-11-14 14:46:10,651 Epoch: [251][290/500] Time 0.043 (0.031) Data 0.002 (0.002) Loss 0.0157 (0.0356) Prec@1 97.000 (93.933) Prec@5 100.000 (99.833) +2022-11-14 14:46:11,135 Epoch: [251][300/500] Time 0.043 (0.032) Data 0.002 (0.002) Loss 0.0315 (0.0355) Prec@1 95.000 (93.968) Prec@5 100.000 (99.839) +2022-11-14 14:46:11,614 Epoch: [251][310/500] Time 0.044 (0.032) Data 0.002 (0.002) Loss 0.0345 (0.0355) Prec@1 93.000 (93.938) Prec@5 100.000 (99.844) +2022-11-14 14:46:12,096 Epoch: [251][320/500] Time 0.042 (0.032) Data 0.002 (0.002) Loss 0.0432 (0.0357) Prec@1 92.000 (93.879) Prec@5 100.000 (99.848) +2022-11-14 14:46:12,576 Epoch: [251][330/500] Time 0.044 (0.033) Data 0.002 (0.002) Loss 0.0420 (0.0359) Prec@1 92.000 (93.824) Prec@5 100.000 (99.853) +2022-11-14 14:46:13,056 Epoch: [251][340/500] Time 0.041 (0.033) Data 0.002 (0.002) Loss 0.0634 (0.0367) Prec@1 90.000 (93.714) Prec@5 99.000 (99.829) +2022-11-14 14:46:13,536 Epoch: [251][350/500] Time 0.044 (0.033) Data 0.001 (0.002) Loss 0.0211 (0.0362) Prec@1 95.000 (93.750) Prec@5 100.000 (99.833) +2022-11-14 14:46:14,012 Epoch: [251][360/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0357 (0.0362) Prec@1 93.000 (93.730) Prec@5 100.000 (99.838) +2022-11-14 14:46:14,495 Epoch: [251][370/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0471 (0.0365) Prec@1 94.000 (93.737) Prec@5 100.000 (99.842) +2022-11-14 14:46:14,970 Epoch: [251][380/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0314 (0.0364) Prec@1 97.000 (93.821) Prec@5 100.000 (99.846) +2022-11-14 14:46:15,449 Epoch: [251][390/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0329 (0.0363) Prec@1 94.000 (93.825) Prec@5 100.000 (99.850) +2022-11-14 14:46:15,929 Epoch: [251][400/500] Time 0.051 (0.034) Data 0.002 (0.002) Loss 0.0533 (0.0367) Prec@1 87.000 (93.659) Prec@5 100.000 (99.854) +2022-11-14 14:46:16,412 Epoch: [251][410/500] Time 0.052 (0.035) Data 0.002 (0.002) Loss 0.0441 (0.0369) Prec@1 91.000 (93.595) Prec@5 100.000 (99.857) +2022-11-14 14:46:16,891 Epoch: [251][420/500] Time 0.049 (0.035) Data 0.002 (0.002) Loss 0.0270 (0.0367) Prec@1 95.000 (93.628) Prec@5 100.000 (99.860) +2022-11-14 14:46:17,375 Epoch: [251][430/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0286 (0.0365) Prec@1 95.000 (93.659) Prec@5 100.000 (99.864) +2022-11-14 14:46:17,852 Epoch: [251][440/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0401 (0.0366) Prec@1 92.000 (93.622) Prec@5 100.000 (99.867) +2022-11-14 14:46:18,324 Epoch: [251][450/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0493 (0.0368) Prec@1 93.000 (93.609) Prec@5 100.000 (99.870) +2022-11-14 14:46:18,795 Epoch: [251][460/500] Time 0.043 (0.035) Data 0.002 (0.002) Loss 0.0227 (0.0365) Prec@1 95.000 (93.638) Prec@5 100.000 (99.872) +2022-11-14 14:46:19,275 Epoch: [251][470/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0626 (0.0371) Prec@1 89.000 (93.542) Prec@5 100.000 (99.875) +2022-11-14 14:46:19,937 Epoch: [251][480/500] Time 0.070 (0.036) Data 0.002 (0.002) Loss 0.0373 (0.0371) Prec@1 93.000 (93.531) Prec@5 100.000 (99.878) +2022-11-14 14:46:20,441 Epoch: [251][490/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0322 (0.0370) Prec@1 95.000 (93.560) Prec@5 100.000 (99.880) +2022-11-14 14:46:20,727 Epoch: [251][499/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0401 (0.0370) Prec@1 93.000 (93.549) Prec@5 100.000 (99.882) +2022-11-14 14:46:21,004 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0984 (0.0984) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:21,015 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0778) Prec@1 90.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:21,024 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0788) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:21,036 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0799) Prec@1 87.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 14:46:21,045 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0773) Prec@1 88.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 14:46:21,055 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0358 (0.0704) Prec@1 95.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 14:46:21,066 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0714) Prec@1 90.000 (88.714) Prec@5 99.000 (99.571) +2022-11-14 14:46:21,078 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0713) Prec@1 88.000 (88.625) Prec@5 99.000 (99.500) +2022-11-14 14:46:21,087 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0733) Prec@1 87.000 (88.444) Prec@5 98.000 (99.333) +2022-11-14 14:46:21,097 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0745) Prec@1 87.000 (88.300) Prec@5 99.000 (99.300) +2022-11-14 14:46:21,108 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0727) Prec@1 91.000 (88.545) Prec@5 100.000 (99.364) +2022-11-14 14:46:21,119 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0747) Prec@1 86.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 14:46:21,129 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0444 (0.0724) Prec@1 92.000 (88.615) Prec@5 100.000 (99.385) +2022-11-14 14:46:21,140 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0729) Prec@1 87.000 (88.500) Prec@5 99.000 (99.357) +2022-11-14 14:46:21,150 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0732) Prec@1 88.000 (88.467) Prec@5 98.000 (99.267) +2022-11-14 14:46:21,160 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0730) Prec@1 89.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 14:46:21,171 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0715) Prec@1 93.000 (88.765) Prec@5 99.000 (99.235) +2022-11-14 14:46:21,181 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0735) Prec@1 83.000 (88.444) Prec@5 100.000 (99.278) +2022-11-14 14:46:21,191 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0724) Prec@1 90.000 (88.526) Prec@5 98.000 (99.211) +2022-11-14 14:46:21,202 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0728) Prec@1 87.000 (88.450) Prec@5 99.000 (99.200) +2022-11-14 14:46:21,211 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0724) Prec@1 91.000 (88.571) Prec@5 100.000 (99.238) +2022-11-14 14:46:21,219 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0725) Prec@1 90.000 (88.636) Prec@5 97.000 (99.136) +2022-11-14 14:46:21,227 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0734) Prec@1 84.000 (88.435) Prec@5 98.000 (99.087) +2022-11-14 14:46:21,234 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0738) Prec@1 89.000 (88.458) Prec@5 98.000 (99.042) +2022-11-14 14:46:21,244 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0749) Prec@1 85.000 (88.320) Prec@5 100.000 (99.080) +2022-11-14 14:46:21,254 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0758) Prec@1 85.000 (88.192) Prec@5 100.000 (99.115) +2022-11-14 14:46:21,264 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0753) Prec@1 90.000 (88.259) Prec@5 100.000 (99.148) +2022-11-14 14:46:21,273 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0747) Prec@1 89.000 (88.286) Prec@5 100.000 (99.179) +2022-11-14 14:46:21,284 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0745) Prec@1 88.000 (88.276) Prec@5 99.000 (99.172) +2022-11-14 14:46:21,294 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0751) Prec@1 85.000 (88.167) Prec@5 100.000 (99.200) +2022-11-14 14:46:21,305 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0751) Prec@1 86.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 14:46:21,315 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0753) Prec@1 85.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 14:46:21,326 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0749) Prec@1 90.000 (88.061) Prec@5 100.000 (99.273) +2022-11-14 14:46:21,337 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0756) Prec@1 83.000 (87.912) Prec@5 100.000 (99.294) +2022-11-14 14:46:21,348 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0749) Prec@1 90.000 (87.971) Prec@5 99.000 (99.286) +2022-11-14 14:46:21,357 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0748) Prec@1 90.000 (88.028) Prec@5 99.000 (99.278) +2022-11-14 14:46:21,366 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0745) Prec@1 91.000 (88.108) Prec@5 99.000 (99.270) +2022-11-14 14:46:21,376 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0753) Prec@1 83.000 (87.974) Prec@5 99.000 (99.263) +2022-11-14 14:46:21,386 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0752) Prec@1 90.000 (88.026) Prec@5 99.000 (99.256) +2022-11-14 14:46:21,397 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0749) Prec@1 89.000 (88.050) Prec@5 99.000 (99.250) +2022-11-14 14:46:21,408 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0752) Prec@1 87.000 (88.024) Prec@5 99.000 (99.244) +2022-11-14 14:46:21,418 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0749) Prec@1 88.000 (88.024) Prec@5 99.000 (99.238) +2022-11-14 14:46:21,429 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0745) Prec@1 91.000 (88.093) Prec@5 100.000 (99.256) +2022-11-14 14:46:21,439 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0745) Prec@1 87.000 (88.068) Prec@5 99.000 (99.250) +2022-11-14 14:46:21,449 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0740) Prec@1 92.000 (88.156) Prec@5 99.000 (99.244) +2022-11-14 14:46:21,459 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0745) Prec@1 83.000 (88.043) Prec@5 98.000 (99.217) +2022-11-14 14:46:21,469 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0746) Prec@1 87.000 (88.021) Prec@5 100.000 (99.234) +2022-11-14 14:46:21,480 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0753) Prec@1 81.000 (87.875) Prec@5 97.000 (99.188) +2022-11-14 14:46:21,491 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0750) Prec@1 90.000 (87.918) Prec@5 100.000 (99.204) +2022-11-14 14:46:21,501 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0754) Prec@1 85.000 (87.860) Prec@5 99.000 (99.200) +2022-11-14 14:46:21,512 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0752) Prec@1 90.000 (87.902) Prec@5 99.000 (99.196) +2022-11-14 14:46:21,522 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0751) Prec@1 86.000 (87.865) Prec@5 99.000 (99.192) +2022-11-14 14:46:21,533 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0753) Prec@1 84.000 (87.792) Prec@5 100.000 (99.208) +2022-11-14 14:46:21,543 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0753) Prec@1 87.000 (87.778) Prec@5 100.000 (99.222) +2022-11-14 14:46:21,553 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0755) Prec@1 84.000 (87.709) Prec@5 100.000 (99.236) +2022-11-14 14:46:21,563 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0755) Prec@1 89.000 (87.732) Prec@5 99.000 (99.232) +2022-11-14 14:46:21,572 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0754) Prec@1 88.000 (87.737) Prec@5 100.000 (99.246) +2022-11-14 14:46:21,581 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0753) Prec@1 91.000 (87.793) Prec@5 99.000 (99.241) +2022-11-14 14:46:21,592 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0756) Prec@1 85.000 (87.746) Prec@5 100.000 (99.254) +2022-11-14 14:46:21,603 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0754) Prec@1 88.000 (87.750) Prec@5 100.000 (99.267) +2022-11-14 14:46:21,614 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0752) Prec@1 90.000 (87.787) Prec@5 100.000 (99.279) +2022-11-14 14:46:21,624 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0753) Prec@1 87.000 (87.774) Prec@5 100.000 (99.290) +2022-11-14 14:46:21,634 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0749) Prec@1 91.000 (87.825) Prec@5 100.000 (99.302) +2022-11-14 14:46:21,645 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0747) Prec@1 90.000 (87.859) Prec@5 100.000 (99.312) +2022-11-14 14:46:21,655 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0749) Prec@1 87.000 (87.846) Prec@5 100.000 (99.323) +2022-11-14 14:46:21,665 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0750) Prec@1 84.000 (87.788) Prec@5 99.000 (99.318) +2022-11-14 14:46:21,676 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0747) Prec@1 93.000 (87.866) Prec@5 99.000 (99.313) +2022-11-14 14:46:21,687 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0746) Prec@1 90.000 (87.897) Prec@5 97.000 (99.279) +2022-11-14 14:46:21,698 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0742) Prec@1 92.000 (87.957) Prec@5 99.000 (99.275) +2022-11-14 14:46:21,710 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0743) Prec@1 85.000 (87.914) Prec@5 99.000 (99.271) +2022-11-14 14:46:21,722 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1268 (0.0750) Prec@1 80.000 (87.803) Prec@5 98.000 (99.254) +2022-11-14 14:46:21,735 Test: [71/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0750) Prec@1 89.000 (87.819) Prec@5 100.000 (99.264) +2022-11-14 14:46:21,748 Test: [72/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0747) Prec@1 92.000 (87.877) Prec@5 100.000 (99.274) +2022-11-14 14:46:21,761 Test: [73/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0744) Prec@1 90.000 (87.905) Prec@5 100.000 (99.284) +2022-11-14 14:46:21,773 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0745) Prec@1 83.000 (87.840) Prec@5 100.000 (99.293) +2022-11-14 14:46:21,785 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0744) Prec@1 90.000 (87.868) Prec@5 99.000 (99.289) +2022-11-14 14:46:21,796 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0744) Prec@1 87.000 (87.857) Prec@5 99.000 (99.286) +2022-11-14 14:46:21,808 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0745) Prec@1 86.000 (87.833) Prec@5 98.000 (99.269) +2022-11-14 14:46:21,820 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0745) Prec@1 86.000 (87.810) Prec@5 100.000 (99.278) +2022-11-14 14:46:21,831 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0745) Prec@1 86.000 (87.787) Prec@5 99.000 (99.275) +2022-11-14 14:46:21,842 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0747) Prec@1 87.000 (87.778) Prec@5 99.000 (99.272) +2022-11-14 14:46:21,852 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0750) Prec@1 85.000 (87.744) Prec@5 100.000 (99.280) +2022-11-14 14:46:21,863 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0752) Prec@1 84.000 (87.699) Prec@5 100.000 (99.289) +2022-11-14 14:46:21,874 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0752) Prec@1 86.000 (87.679) Prec@5 99.000 (99.286) +2022-11-14 14:46:21,885 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0756) Prec@1 81.000 (87.600) Prec@5 99.000 (99.282) +2022-11-14 14:46:21,897 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0758) Prec@1 87.000 (87.593) Prec@5 100.000 (99.291) +2022-11-14 14:46:21,908 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0759) Prec@1 85.000 (87.563) Prec@5 100.000 (99.299) +2022-11-14 14:46:21,919 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0760) Prec@1 84.000 (87.523) Prec@5 99.000 (99.295) +2022-11-14 14:46:21,929 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0759) Prec@1 90.000 (87.551) Prec@5 100.000 (99.303) +2022-11-14 14:46:21,940 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0759) Prec@1 86.000 (87.533) Prec@5 100.000 (99.311) +2022-11-14 14:46:21,950 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0756) Prec@1 94.000 (87.604) Prec@5 99.000 (99.308) +2022-11-14 14:46:21,960 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0753) Prec@1 92.000 (87.652) Prec@5 99.000 (99.304) +2022-11-14 14:46:21,972 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0756) Prec@1 82.000 (87.591) Prec@5 98.000 (99.290) +2022-11-14 14:46:21,983 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0757) Prec@1 88.000 (87.596) Prec@5 100.000 (99.298) +2022-11-14 14:46:21,994 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0758) Prec@1 84.000 (87.558) Prec@5 99.000 (99.295) +2022-11-14 14:46:22,005 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0760) Prec@1 84.000 (87.521) Prec@5 99.000 (99.292) +2022-11-14 14:46:22,015 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0372 (0.0756) Prec@1 95.000 (87.598) Prec@5 98.000 (99.278) +2022-11-14 14:46:22,025 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0757) Prec@1 86.000 (87.582) Prec@5 97.000 (99.255) +2022-11-14 14:46:22,035 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0761) Prec@1 85.000 (87.556) Prec@5 99.000 (99.253) +2022-11-14 14:46:22,046 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0762) Prec@1 86.000 (87.540) Prec@5 99.000 (99.250) +2022-11-14 14:46:22,103 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:46:22,426 Epoch: [252][0/500] Time 0.026 (0.026) Data 0.233 (0.233) Loss 0.0229 (0.0229) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:22,706 Epoch: [252][10/500] Time 0.021 (0.025) Data 0.002 (0.023) Loss 0.0225 (0.0227) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 14:46:22,922 Epoch: [252][20/500] Time 0.023 (0.023) Data 0.002 (0.013) Loss 0.0148 (0.0201) Prec@1 97.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 14:46:23,151 Epoch: [252][30/500] Time 0.020 (0.022) Data 0.001 (0.009) Loss 0.0260 (0.0215) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 14:46:23,454 Epoch: [252][40/500] Time 0.028 (0.023) Data 0.002 (0.007) Loss 0.0288 (0.0230) Prec@1 96.000 (96.400) Prec@5 100.000 (100.000) +2022-11-14 14:46:23,819 Epoch: [252][50/500] Time 0.034 (0.025) Data 0.002 (0.006) Loss 0.0462 (0.0269) Prec@1 91.000 (95.500) Prec@5 98.000 (99.667) +2022-11-14 14:46:24,192 Epoch: [252][60/500] Time 0.023 (0.026) Data 0.002 (0.006) Loss 0.0446 (0.0294) Prec@1 91.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 14:46:24,575 Epoch: [252][70/500] Time 0.039 (0.027) Data 0.002 (0.005) Loss 0.0257 (0.0289) Prec@1 96.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 14:46:24,932 Epoch: [252][80/500] Time 0.041 (0.028) Data 0.002 (0.005) Loss 0.0284 (0.0289) Prec@1 94.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 14:46:25,292 Epoch: [252][90/500] Time 0.047 (0.028) Data 0.002 (0.004) Loss 0.0215 (0.0281) Prec@1 95.000 (94.900) Prec@5 100.000 (99.800) +2022-11-14 14:46:25,676 Epoch: [252][100/500] Time 0.037 (0.029) Data 0.002 (0.004) Loss 0.0397 (0.0292) Prec@1 93.000 (94.727) Prec@5 100.000 (99.818) +2022-11-14 14:46:26,063 Epoch: [252][110/500] Time 0.041 (0.029) Data 0.002 (0.004) Loss 0.0329 (0.0295) Prec@1 95.000 (94.750) Prec@5 100.000 (99.833) +2022-11-14 14:46:26,437 Epoch: [252][120/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0281 (0.0294) Prec@1 96.000 (94.846) Prec@5 100.000 (99.846) +2022-11-14 14:46:26,765 Epoch: [252][130/500] Time 0.025 (0.030) Data 0.002 (0.004) Loss 0.0344 (0.0297) Prec@1 94.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 14:46:27,118 Epoch: [252][140/500] Time 0.038 (0.030) Data 0.002 (0.004) Loss 0.0664 (0.0322) Prec@1 90.000 (94.467) Prec@5 99.000 (99.800) +2022-11-14 14:46:27,464 Epoch: [252][150/500] Time 0.027 (0.030) Data 0.002 (0.003) Loss 0.0559 (0.0337) Prec@1 93.000 (94.375) Prec@5 99.000 (99.750) +2022-11-14 14:46:27,786 Epoch: [252][160/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0384 (0.0340) Prec@1 94.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 14:46:28,124 Epoch: [252][170/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0215 (0.0333) Prec@1 96.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 14:46:28,461 Epoch: [252][180/500] Time 0.027 (0.030) Data 0.002 (0.003) Loss 0.0467 (0.0340) Prec@1 92.000 (94.316) Prec@5 100.000 (99.789) +2022-11-14 14:46:28,823 Epoch: [252][190/500] Time 0.027 (0.030) Data 0.001 (0.003) Loss 0.0335 (0.0339) Prec@1 94.000 (94.300) Prec@5 100.000 (99.800) +2022-11-14 14:46:29,629 Epoch: [252][200/500] Time 0.072 (0.032) Data 0.002 (0.003) Loss 0.0426 (0.0344) Prec@1 94.000 (94.286) Prec@5 100.000 (99.810) +2022-11-14 14:46:30,124 Epoch: [252][210/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0147 (0.0335) Prec@1 99.000 (94.500) Prec@5 100.000 (99.818) +2022-11-14 14:46:30,708 Epoch: [252][220/500] Time 0.088 (0.033) Data 0.003 (0.003) Loss 0.0570 (0.0345) Prec@1 91.000 (94.348) Prec@5 99.000 (99.783) +2022-11-14 14:46:31,173 Epoch: [252][230/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0490 (0.0351) Prec@1 92.000 (94.250) Prec@5 100.000 (99.792) +2022-11-14 14:46:31,645 Epoch: [252][240/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0299 (0.0349) Prec@1 95.000 (94.280) Prec@5 100.000 (99.800) +2022-11-14 14:46:32,277 Epoch: [252][250/500] Time 0.083 (0.035) Data 0.002 (0.003) Loss 0.0534 (0.0356) Prec@1 92.000 (94.192) Prec@5 100.000 (99.808) +2022-11-14 14:46:33,080 Epoch: [252][260/500] Time 0.068 (0.036) Data 0.002 (0.003) Loss 0.0314 (0.0354) Prec@1 94.000 (94.185) Prec@5 100.000 (99.815) +2022-11-14 14:46:33,995 Epoch: [252][270/500] Time 0.088 (0.038) Data 0.002 (0.003) Loss 0.0223 (0.0350) Prec@1 98.000 (94.321) Prec@5 100.000 (99.821) +2022-11-14 14:46:34,923 Epoch: [252][280/500] Time 0.092 (0.040) Data 0.002 (0.003) Loss 0.0601 (0.0358) Prec@1 91.000 (94.207) Prec@5 99.000 (99.793) +2022-11-14 14:46:35,644 Epoch: [252][290/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0235 (0.0354) Prec@1 97.000 (94.300) Prec@5 100.000 (99.800) +2022-11-14 14:46:36,259 Epoch: [252][300/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0351 (0.0354) Prec@1 94.000 (94.290) Prec@5 100.000 (99.806) +2022-11-14 14:46:36,730 Epoch: [252][310/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0469 (0.0358) Prec@1 93.000 (94.250) Prec@5 100.000 (99.812) +2022-11-14 14:46:37,341 Epoch: [252][320/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0449 (0.0360) Prec@1 91.000 (94.152) Prec@5 99.000 (99.788) +2022-11-14 14:46:37,983 Epoch: [252][330/500] Time 0.063 (0.042) Data 0.002 (0.003) Loss 0.0305 (0.0359) Prec@1 96.000 (94.206) Prec@5 99.000 (99.765) +2022-11-14 14:46:38,455 Epoch: [252][340/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0404 (0.0360) Prec@1 94.000 (94.200) Prec@5 99.000 (99.743) +2022-11-14 14:46:38,969 Epoch: [252][350/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0658 (0.0368) Prec@1 90.000 (94.083) Prec@5 100.000 (99.750) +2022-11-14 14:46:39,438 Epoch: [252][360/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0440 (0.0370) Prec@1 92.000 (94.027) Prec@5 100.000 (99.757) +2022-11-14 14:46:39,902 Epoch: [252][370/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0356 (0.0370) Prec@1 93.000 (94.000) Prec@5 100.000 (99.763) +2022-11-14 14:46:40,384 Epoch: [252][380/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0320 (0.0369) Prec@1 94.000 (94.000) Prec@5 100.000 (99.769) +2022-11-14 14:46:40,850 Epoch: [252][390/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0284 (0.0367) Prec@1 94.000 (94.000) Prec@5 100.000 (99.775) +2022-11-14 14:46:41,323 Epoch: [252][400/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0426 (0.0368) Prec@1 92.000 (93.951) Prec@5 100.000 (99.780) +2022-11-14 14:46:42,019 Epoch: [252][410/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0580 (0.0373) Prec@1 90.000 (93.857) Prec@5 99.000 (99.762) +2022-11-14 14:46:42,490 Epoch: [252][420/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0531 (0.0377) Prec@1 92.000 (93.814) Prec@5 100.000 (99.767) +2022-11-14 14:46:42,962 Epoch: [252][430/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0560 (0.0381) Prec@1 91.000 (93.750) Prec@5 100.000 (99.773) +2022-11-14 14:46:43,432 Epoch: [252][440/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0273 (0.0378) Prec@1 95.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 14:46:43,909 Epoch: [252][450/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0342 (0.0378) Prec@1 94.000 (93.783) Prec@5 100.000 (99.783) +2022-11-14 14:46:44,431 Epoch: [252][460/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0298 (0.0376) Prec@1 95.000 (93.809) Prec@5 100.000 (99.787) +2022-11-14 14:46:44,912 Epoch: [252][470/500] Time 0.042 (0.043) Data 0.002 (0.002) Loss 0.0141 (0.0371) Prec@1 97.000 (93.875) Prec@5 100.000 (99.792) +2022-11-14 14:46:45,383 Epoch: [252][480/500] Time 0.044 (0.043) Data 0.002 (0.002) Loss 0.0336 (0.0370) Prec@1 94.000 (93.878) Prec@5 100.000 (99.796) +2022-11-14 14:46:45,849 Epoch: [252][490/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0280 (0.0369) Prec@1 95.000 (93.900) Prec@5 100.000 (99.800) +2022-11-14 14:46:46,285 Epoch: [252][499/500] Time 0.044 (0.043) Data 0.002 (0.002) Loss 0.0325 (0.0368) Prec@1 94.000 (93.902) Prec@5 100.000 (99.804) +2022-11-14 14:46:46,630 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0608 (0.0608) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:46:46,640 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0608) Prec@1 90.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:46:46,649 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0680) Prec@1 85.000 (88.000) Prec@5 98.000 (99.000) +2022-11-14 14:46:46,659 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0733) Prec@1 85.000 (87.250) Prec@5 99.000 (99.000) +2022-11-14 14:46:46,667 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0728) Prec@1 89.000 (87.600) Prec@5 100.000 (99.200) +2022-11-14 14:46:46,675 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0360 (0.0667) Prec@1 95.000 (88.833) Prec@5 100.000 (99.333) +2022-11-14 14:46:46,684 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0646) Prec@1 94.000 (89.571) Prec@5 99.000 (99.286) +2022-11-14 14:46:46,693 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0673) Prec@1 82.000 (88.625) Prec@5 99.000 (99.250) +2022-11-14 14:46:46,700 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0685) Prec@1 90.000 (88.778) Prec@5 100.000 (99.333) +2022-11-14 14:46:46,709 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0687) Prec@1 89.000 (88.800) Prec@5 99.000 (99.300) +2022-11-14 14:46:46,719 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0480 (0.0669) Prec@1 90.000 (88.909) Prec@5 100.000 (99.364) +2022-11-14 14:46:46,728 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0685) Prec@1 85.000 (88.583) Prec@5 100.000 (99.417) +2022-11-14 14:46:46,736 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0679) Prec@1 89.000 (88.615) Prec@5 100.000 (99.462) +2022-11-14 14:46:46,746 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0682) Prec@1 88.000 (88.571) Prec@5 99.000 (99.429) +2022-11-14 14:46:46,755 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0692) Prec@1 84.000 (88.267) Prec@5 100.000 (99.467) +2022-11-14 14:46:46,764 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0690) Prec@1 89.000 (88.312) Prec@5 100.000 (99.500) +2022-11-14 14:46:46,772 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0677) Prec@1 92.000 (88.529) Prec@5 99.000 (99.471) +2022-11-14 14:46:46,782 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0701) Prec@1 84.000 (88.278) Prec@5 100.000 (99.500) +2022-11-14 14:46:46,791 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0705) Prec@1 83.000 (88.000) Prec@5 100.000 (99.526) +2022-11-14 14:46:46,799 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0720) Prec@1 82.000 (87.700) Prec@5 98.000 (99.450) +2022-11-14 14:46:46,809 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0716) Prec@1 89.000 (87.762) Prec@5 100.000 (99.476) +2022-11-14 14:46:46,817 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1151 (0.0736) Prec@1 83.000 (87.545) Prec@5 99.000 (99.455) +2022-11-14 14:46:46,826 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0746) Prec@1 85.000 (87.435) Prec@5 98.000 (99.391) +2022-11-14 14:46:46,835 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0743) Prec@1 89.000 (87.500) Prec@5 100.000 (99.417) +2022-11-14 14:46:46,844 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0749) Prec@1 84.000 (87.360) Prec@5 99.000 (99.400) +2022-11-14 14:46:46,853 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0753) Prec@1 86.000 (87.308) Prec@5 99.000 (99.385) +2022-11-14 14:46:46,861 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0748) Prec@1 91.000 (87.444) Prec@5 100.000 (99.407) +2022-11-14 14:46:46,871 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0748) Prec@1 88.000 (87.464) Prec@5 100.000 (99.429) +2022-11-14 14:46:46,879 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0744) Prec@1 90.000 (87.552) Prec@5 99.000 (99.414) +2022-11-14 14:46:46,887 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0736) Prec@1 91.000 (87.667) Prec@5 100.000 (99.433) +2022-11-14 14:46:46,895 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0739) Prec@1 86.000 (87.613) Prec@5 99.000 (99.419) +2022-11-14 14:46:46,903 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0738) Prec@1 89.000 (87.656) Prec@5 99.000 (99.406) +2022-11-14 14:46:46,911 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0740) Prec@1 87.000 (87.636) Prec@5 100.000 (99.424) +2022-11-14 14:46:46,920 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0748) Prec@1 82.000 (87.471) Prec@5 100.000 (99.441) +2022-11-14 14:46:46,929 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0754) Prec@1 86.000 (87.429) Prec@5 98.000 (99.400) +2022-11-14 14:46:46,939 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0750) Prec@1 90.000 (87.500) Prec@5 100.000 (99.417) +2022-11-14 14:46:46,948 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0747) Prec@1 89.000 (87.541) Prec@5 99.000 (99.405) +2022-11-14 14:46:46,957 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0752) Prec@1 82.000 (87.395) Prec@5 99.000 (99.395) +2022-11-14 14:46:46,966 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0754) Prec@1 88.000 (87.410) Prec@5 99.000 (99.385) +2022-11-14 14:46:46,975 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0753) Prec@1 90.000 (87.475) Prec@5 99.000 (99.375) +2022-11-14 14:46:46,985 Test: [40/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0762) Prec@1 83.000 (87.366) Prec@5 98.000 (99.341) +2022-11-14 14:46:46,995 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0759) Prec@1 91.000 (87.452) Prec@5 98.000 (99.310) +2022-11-14 14:46:47,005 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0756) Prec@1 89.000 (87.488) Prec@5 99.000 (99.302) +2022-11-14 14:46:47,014 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0755) Prec@1 88.000 (87.500) Prec@5 98.000 (99.273) +2022-11-14 14:46:47,024 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0753) Prec@1 90.000 (87.556) Prec@5 99.000 (99.267) +2022-11-14 14:46:47,034 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0752) Prec@1 87.000 (87.543) Prec@5 100.000 (99.283) +2022-11-14 14:46:47,042 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0753) Prec@1 87.000 (87.532) Prec@5 100.000 (99.298) +2022-11-14 14:46:47,051 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0758) Prec@1 84.000 (87.458) Prec@5 99.000 (99.292) +2022-11-14 14:46:47,061 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0750) Prec@1 94.000 (87.592) Prec@5 100.000 (99.306) +2022-11-14 14:46:47,070 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0755) Prec@1 87.000 (87.580) Prec@5 100.000 (99.320) +2022-11-14 14:46:47,079 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0754) Prec@1 88.000 (87.588) Prec@5 99.000 (99.314) +2022-11-14 14:46:47,088 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0756) Prec@1 86.000 (87.558) Prec@5 99.000 (99.308) +2022-11-14 14:46:47,097 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0757) Prec@1 86.000 (87.528) Prec@5 100.000 (99.321) +2022-11-14 14:46:47,107 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0757) Prec@1 88.000 (87.537) Prec@5 100.000 (99.333) +2022-11-14 14:46:47,116 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0761) Prec@1 83.000 (87.455) Prec@5 100.000 (99.345) +2022-11-14 14:46:47,125 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0763) Prec@1 85.000 (87.411) Prec@5 98.000 (99.321) +2022-11-14 14:46:47,135 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0764) Prec@1 85.000 (87.368) Prec@5 100.000 (99.333) +2022-11-14 14:46:47,144 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0764) Prec@1 88.000 (87.379) Prec@5 100.000 (99.345) +2022-11-14 14:46:47,153 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0770) Prec@1 82.000 (87.288) Prec@5 99.000 (99.339) +2022-11-14 14:46:47,163 Test: [59/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0767) Prec@1 89.000 (87.317) Prec@5 100.000 (99.350) +2022-11-14 14:46:47,172 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0767) Prec@1 87.000 (87.311) Prec@5 100.000 (99.361) +2022-11-14 14:46:47,180 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0769) Prec@1 88.000 (87.323) Prec@5 99.000 (99.355) +2022-11-14 14:46:47,188 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0767) Prec@1 89.000 (87.349) Prec@5 100.000 (99.365) +2022-11-14 14:46:47,196 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0762) Prec@1 92.000 (87.422) Prec@5 100.000 (99.375) +2022-11-14 14:46:47,205 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0763) Prec@1 87.000 (87.415) Prec@5 99.000 (99.369) +2022-11-14 14:46:47,214 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0763) Prec@1 84.000 (87.364) Prec@5 98.000 (99.348) +2022-11-14 14:46:47,222 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0457 (0.0759) Prec@1 94.000 (87.463) Prec@5 99.000 (99.343) +2022-11-14 14:46:47,232 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0758) Prec@1 87.000 (87.456) Prec@5 99.000 (99.338) +2022-11-14 14:46:47,241 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0758) Prec@1 88.000 (87.464) Prec@5 99.000 (99.333) +2022-11-14 14:46:47,250 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.0762) Prec@1 84.000 (87.414) Prec@5 98.000 (99.314) +2022-11-14 14:46:47,260 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.0767) Prec@1 85.000 (87.380) Prec@5 97.000 (99.282) +2022-11-14 14:46:47,269 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0765) Prec@1 88.000 (87.389) Prec@5 100.000 (99.292) +2022-11-14 14:46:47,278 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0761) Prec@1 93.000 (87.466) Prec@5 100.000 (99.301) +2022-11-14 14:46:47,287 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0419 (0.0756) Prec@1 93.000 (87.541) Prec@5 100.000 (99.311) +2022-11-14 14:46:47,297 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0761) Prec@1 81.000 (87.453) Prec@5 99.000 (99.307) +2022-11-14 14:46:47,306 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0759) Prec@1 90.000 (87.487) Prec@5 99.000 (99.303) +2022-11-14 14:46:47,315 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0761) Prec@1 84.000 (87.442) Prec@5 98.000 (99.286) +2022-11-14 14:46:47,327 Test: [77/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0762) Prec@1 86.000 (87.423) Prec@5 97.000 (99.256) +2022-11-14 14:46:47,339 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0762) Prec@1 88.000 (87.430) Prec@5 100.000 (99.266) +2022-11-14 14:46:47,351 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0763) Prec@1 86.000 (87.412) Prec@5 99.000 (99.263) +2022-11-14 14:46:47,364 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0762) Prec@1 89.000 (87.432) Prec@5 99.000 (99.259) +2022-11-14 14:46:47,377 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0763) Prec@1 87.000 (87.427) Prec@5 100.000 (99.268) +2022-11-14 14:46:47,391 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0764) Prec@1 86.000 (87.410) Prec@5 100.000 (99.277) +2022-11-14 14:46:47,403 Test: [83/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0763) Prec@1 87.000 (87.405) Prec@5 99.000 (99.274) +2022-11-14 14:46:47,416 Test: [84/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0764) Prec@1 87.000 (87.400) Prec@5 100.000 (99.282) +2022-11-14 14:46:47,428 Test: [85/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0766) Prec@1 86.000 (87.384) Prec@5 99.000 (99.279) +2022-11-14 14:46:47,441 Test: [86/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0765) Prec@1 89.000 (87.402) Prec@5 100.000 (99.287) +2022-11-14 14:46:47,454 Test: [87/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0765) Prec@1 90.000 (87.432) Prec@5 98.000 (99.273) +2022-11-14 14:46:47,467 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0765) Prec@1 85.000 (87.404) Prec@5 100.000 (99.281) +2022-11-14 14:46:47,479 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0766) Prec@1 87.000 (87.400) Prec@5 98.000 (99.267) +2022-11-14 14:46:47,492 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0764) Prec@1 91.000 (87.440) Prec@5 100.000 (99.275) +2022-11-14 14:46:47,504 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0761) Prec@1 93.000 (87.500) Prec@5 100.000 (99.283) +2022-11-14 14:46:47,516 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0763) Prec@1 86.000 (87.484) Prec@5 100.000 (99.290) +2022-11-14 14:46:47,529 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0762) Prec@1 87.000 (87.479) Prec@5 100.000 (99.298) +2022-11-14 14:46:47,540 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0760) Prec@1 90.000 (87.505) Prec@5 100.000 (99.305) +2022-11-14 14:46:47,549 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0758) Prec@1 91.000 (87.542) Prec@5 99.000 (99.302) +2022-11-14 14:46:47,558 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0755) Prec@1 94.000 (87.608) Prec@5 99.000 (99.299) +2022-11-14 14:46:47,568 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0757) Prec@1 84.000 (87.571) Prec@5 99.000 (99.296) +2022-11-14 14:46:47,577 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0758) Prec@1 87.000 (87.566) Prec@5 100.000 (99.303) +2022-11-14 14:46:47,586 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0757) Prec@1 88.000 (87.570) Prec@5 100.000 (99.310) +2022-11-14 14:46:47,656 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:46:47,970 Epoch: [253][0/500] Time 0.025 (0.025) Data 0.228 (0.228) Loss 0.0299 (0.0299) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:48,196 Epoch: [253][10/500] Time 0.027 (0.020) Data 0.002 (0.022) Loss 0.0421 (0.0360) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:48,407 Epoch: [253][20/500] Time 0.017 (0.019) Data 0.002 (0.012) Loss 0.0578 (0.0433) Prec@1 90.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:46:48,706 Epoch: [253][30/500] Time 0.034 (0.021) Data 0.001 (0.009) Loss 0.0360 (0.0415) Prec@1 93.000 (92.250) Prec@5 100.000 (100.000) +2022-11-14 14:46:49,154 Epoch: [253][40/500] Time 0.044 (0.026) Data 0.002 (0.007) Loss 0.0303 (0.0392) Prec@1 95.000 (92.800) Prec@5 100.000 (100.000) +2022-11-14 14:46:49,571 Epoch: [253][50/500] Time 0.029 (0.029) Data 0.002 (0.006) Loss 0.0207 (0.0362) Prec@1 98.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 14:46:50,002 Epoch: [253][60/500] Time 0.064 (0.030) Data 0.002 (0.006) Loss 0.0330 (0.0357) Prec@1 95.000 (93.857) Prec@5 99.000 (99.857) +2022-11-14 14:46:50,462 Epoch: [253][70/500] Time 0.044 (0.032) Data 0.002 (0.005) Loss 0.0351 (0.0356) Prec@1 93.000 (93.750) Prec@5 100.000 (99.875) +2022-11-14 14:46:50,888 Epoch: [253][80/500] Time 0.044 (0.033) Data 0.002 (0.005) Loss 0.0373 (0.0358) Prec@1 96.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 14:46:51,256 Epoch: [253][90/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0451 (0.0367) Prec@1 93.000 (93.900) Prec@5 99.000 (99.800) +2022-11-14 14:46:51,625 Epoch: [253][100/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0259 (0.0358) Prec@1 96.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 14:46:51,999 Epoch: [253][110/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0663 (0.0383) Prec@1 89.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 14:46:52,455 Epoch: [253][120/500] Time 0.052 (0.033) Data 0.002 (0.004) Loss 0.0319 (0.0378) Prec@1 94.000 (93.692) Prec@5 100.000 (99.846) +2022-11-14 14:46:52,844 Epoch: [253][130/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0271 (0.0370) Prec@1 97.000 (93.929) Prec@5 100.000 (99.857) +2022-11-14 14:46:53,221 Epoch: [253][140/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0238 (0.0362) Prec@1 97.000 (94.133) Prec@5 100.000 (99.867) +2022-11-14 14:46:53,587 Epoch: [253][150/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0508 (0.0371) Prec@1 94.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 14:46:53,963 Epoch: [253][160/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0472 (0.0377) Prec@1 92.000 (94.000) Prec@5 99.000 (99.824) +2022-11-14 14:46:54,345 Epoch: [253][170/500] Time 0.031 (0.033) Data 0.002 (0.003) Loss 0.0200 (0.0367) Prec@1 97.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 14:46:54,714 Epoch: [253][180/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0245 (0.0361) Prec@1 95.000 (94.211) Prec@5 99.000 (99.789) +2022-11-14 14:46:55,082 Epoch: [253][190/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0367 (0.0361) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:46:55,488 Epoch: [253][200/500] Time 0.055 (0.033) Data 0.002 (0.003) Loss 0.0620 (0.0373) Prec@1 90.000 (94.000) Prec@5 99.000 (99.762) +2022-11-14 14:46:55,902 Epoch: [253][210/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0418 (0.0375) Prec@1 94.000 (94.000) Prec@5 100.000 (99.773) +2022-11-14 14:46:56,288 Epoch: [253][220/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0345 (0.0374) Prec@1 93.000 (93.957) Prec@5 99.000 (99.739) +2022-11-14 14:46:56,711 Epoch: [253][230/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0313 (0.0371) Prec@1 96.000 (94.042) Prec@5 100.000 (99.750) +2022-11-14 14:46:57,076 Epoch: [253][240/500] Time 0.034 (0.034) Data 0.003 (0.003) Loss 0.0242 (0.0366) Prec@1 96.000 (94.120) Prec@5 100.000 (99.760) +2022-11-14 14:46:57,463 Epoch: [253][250/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0376 (0.0367) Prec@1 92.000 (94.038) Prec@5 100.000 (99.769) +2022-11-14 14:46:57,843 Epoch: [253][260/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0513 (0.0372) Prec@1 91.000 (93.926) Prec@5 100.000 (99.778) +2022-11-14 14:46:58,214 Epoch: [253][270/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0403 (0.0373) Prec@1 93.000 (93.893) Prec@5 100.000 (99.786) +2022-11-14 14:46:58,603 Epoch: [253][280/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0579 (0.0380) Prec@1 91.000 (93.793) Prec@5 99.000 (99.759) +2022-11-14 14:46:58,989 Epoch: [253][290/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0236 (0.0375) Prec@1 96.000 (93.867) Prec@5 100.000 (99.767) +2022-11-14 14:46:59,372 Epoch: [253][300/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0542 (0.0381) Prec@1 91.000 (93.774) Prec@5 99.000 (99.742) +2022-11-14 14:46:59,748 Epoch: [253][310/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0388 (0.0381) Prec@1 94.000 (93.781) Prec@5 100.000 (99.750) +2022-11-14 14:47:00,143 Epoch: [253][320/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0407 (0.0382) Prec@1 93.000 (93.758) Prec@5 100.000 (99.758) +2022-11-14 14:47:00,526 Epoch: [253][330/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0429 (0.0383) Prec@1 92.000 (93.706) Prec@5 100.000 (99.765) +2022-11-14 14:47:00,912 Epoch: [253][340/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0282 (0.0380) Prec@1 94.000 (93.714) Prec@5 100.000 (99.771) +2022-11-14 14:47:01,307 Epoch: [253][350/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0442 (0.0382) Prec@1 92.000 (93.667) Prec@5 100.000 (99.778) +2022-11-14 14:47:01,682 Epoch: [253][360/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0264 (0.0379) Prec@1 98.000 (93.784) Prec@5 100.000 (99.784) +2022-11-14 14:47:02,066 Epoch: [253][370/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0327 (0.0377) Prec@1 94.000 (93.789) Prec@5 100.000 (99.789) +2022-11-14 14:47:02,449 Epoch: [253][380/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0254 (0.0374) Prec@1 95.000 (93.821) Prec@5 100.000 (99.795) +2022-11-14 14:47:02,834 Epoch: [253][390/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0389 (0.0375) Prec@1 91.000 (93.750) Prec@5 100.000 (99.800) +2022-11-14 14:47:03,209 Epoch: [253][400/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0430 (0.0376) Prec@1 93.000 (93.732) Prec@5 100.000 (99.805) +2022-11-14 14:47:03,591 Epoch: [253][410/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0359 (0.0376) Prec@1 93.000 (93.714) Prec@5 100.000 (99.810) +2022-11-14 14:47:03,974 Epoch: [253][420/500] Time 0.034 (0.034) Data 0.001 (0.002) Loss 0.0391 (0.0376) Prec@1 92.000 (93.674) Prec@5 99.000 (99.791) +2022-11-14 14:47:04,366 Epoch: [253][430/500] Time 0.044 (0.034) Data 0.002 (0.002) Loss 0.0343 (0.0375) Prec@1 96.000 (93.727) Prec@5 100.000 (99.795) +2022-11-14 14:47:04,742 Epoch: [253][440/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0346 (0.0375) Prec@1 95.000 (93.756) Prec@5 100.000 (99.800) +2022-11-14 14:47:05,122 Epoch: [253][450/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0270 (0.0372) Prec@1 95.000 (93.783) Prec@5 100.000 (99.804) +2022-11-14 14:47:05,500 Epoch: [253][460/500] Time 0.037 (0.034) Data 0.001 (0.002) Loss 0.0439 (0.0374) Prec@1 93.000 (93.766) Prec@5 99.000 (99.787) +2022-11-14 14:47:05,882 Epoch: [253][470/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0335 (0.0373) Prec@1 93.000 (93.750) Prec@5 99.000 (99.771) +2022-11-14 14:47:06,263 Epoch: [253][480/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0578 (0.0377) Prec@1 89.000 (93.653) Prec@5 99.000 (99.755) +2022-11-14 14:47:06,647 Epoch: [253][490/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0260 (0.0375) Prec@1 96.000 (93.700) Prec@5 100.000 (99.760) +2022-11-14 14:47:06,990 Epoch: [253][499/500] Time 0.035 (0.034) Data 0.001 (0.002) Loss 0.0217 (0.0372) Prec@1 97.000 (93.765) Prec@5 100.000 (99.765) +2022-11-14 14:47:07,277 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0642 (0.0642) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:07,287 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0668) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 14:47:07,298 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0671) Prec@1 89.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 14:47:07,311 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0671) Prec@1 90.000 (90.000) Prec@5 98.000 (99.250) +2022-11-14 14:47:07,321 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0658) Prec@1 91.000 (90.200) Prec@5 100.000 (99.400) +2022-11-14 14:47:07,331 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0618) Prec@1 92.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 14:47:07,340 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0609) Prec@1 92.000 (90.714) Prec@5 100.000 (99.571) +2022-11-14 14:47:07,351 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0619) Prec@1 87.000 (90.250) Prec@5 100.000 (99.625) +2022-11-14 14:47:07,361 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0629) Prec@1 88.000 (90.000) Prec@5 99.000 (99.556) +2022-11-14 14:47:07,372 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0631) Prec@1 90.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 14:47:07,383 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0635) Prec@1 90.000 (90.000) Prec@5 100.000 (99.545) +2022-11-14 14:47:07,398 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0641) Prec@1 89.000 (89.917) Prec@5 100.000 (99.583) +2022-11-14 14:47:07,412 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0633) Prec@1 90.000 (89.923) Prec@5 99.000 (99.538) +2022-11-14 14:47:07,426 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0643) Prec@1 87.000 (89.714) Prec@5 98.000 (99.429) +2022-11-14 14:47:07,440 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0654) Prec@1 88.000 (89.600) Prec@5 100.000 (99.467) +2022-11-14 14:47:07,456 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0657) Prec@1 87.000 (89.438) Prec@5 100.000 (99.500) +2022-11-14 14:47:07,469 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0650) Prec@1 91.000 (89.529) Prec@5 98.000 (99.412) +2022-11-14 14:47:07,483 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0668) Prec@1 85.000 (89.278) Prec@5 100.000 (99.444) +2022-11-14 14:47:07,495 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0668) Prec@1 88.000 (89.211) Prec@5 99.000 (99.421) +2022-11-14 14:47:07,510 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0675) Prec@1 89.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 14:47:07,525 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0676) Prec@1 89.000 (89.190) Prec@5 100.000 (99.429) +2022-11-14 14:47:07,538 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0684) Prec@1 88.000 (89.136) Prec@5 98.000 (99.364) +2022-11-14 14:47:07,551 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0695) Prec@1 86.000 (89.000) Prec@5 99.000 (99.348) +2022-11-14 14:47:07,566 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0693) Prec@1 92.000 (89.125) Prec@5 99.000 (99.333) +2022-11-14 14:47:07,582 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0695) Prec@1 87.000 (89.040) Prec@5 100.000 (99.360) +2022-11-14 14:47:07,597 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0698) Prec@1 88.000 (89.000) Prec@5 99.000 (99.346) +2022-11-14 14:47:07,612 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0697) Prec@1 88.000 (88.963) Prec@5 100.000 (99.370) +2022-11-14 14:47:07,627 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0690) Prec@1 91.000 (89.036) Prec@5 100.000 (99.393) +2022-11-14 14:47:07,642 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0684) Prec@1 91.000 (89.103) Prec@5 98.000 (99.345) +2022-11-14 14:47:07,657 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0684) Prec@1 89.000 (89.100) Prec@5 100.000 (99.367) +2022-11-14 14:47:07,671 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0689) Prec@1 86.000 (89.000) Prec@5 100.000 (99.387) +2022-11-14 14:47:07,685 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0693) Prec@1 89.000 (89.000) Prec@5 98.000 (99.344) +2022-11-14 14:47:07,700 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0691) Prec@1 89.000 (89.000) Prec@5 100.000 (99.364) +2022-11-14 14:47:07,713 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0696) Prec@1 85.000 (88.882) Prec@5 100.000 (99.382) +2022-11-14 14:47:07,726 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0696) Prec@1 90.000 (88.914) Prec@5 99.000 (99.371) +2022-11-14 14:47:07,741 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0697) Prec@1 91.000 (88.972) Prec@5 100.000 (99.389) +2022-11-14 14:47:07,754 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0697) Prec@1 90.000 (89.000) Prec@5 97.000 (99.324) +2022-11-14 14:47:07,766 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0705) Prec@1 83.000 (88.842) Prec@5 99.000 (99.316) +2022-11-14 14:47:07,782 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0702) Prec@1 91.000 (88.897) Prec@5 99.000 (99.308) +2022-11-14 14:47:07,796 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0699) Prec@1 89.000 (88.900) Prec@5 99.000 (99.300) +2022-11-14 14:47:07,810 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0705) Prec@1 84.000 (88.780) Prec@5 99.000 (99.293) +2022-11-14 14:47:07,823 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0702) Prec@1 89.000 (88.786) Prec@5 99.000 (99.286) +2022-11-14 14:47:07,838 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0697) Prec@1 92.000 (88.860) Prec@5 99.000 (99.279) +2022-11-14 14:47:07,852 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0698) Prec@1 90.000 (88.886) Prec@5 99.000 (99.273) +2022-11-14 14:47:07,866 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0697) Prec@1 89.000 (88.889) Prec@5 99.000 (99.267) +2022-11-14 14:47:07,880 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0703) Prec@1 85.000 (88.804) Prec@5 99.000 (99.261) +2022-11-14 14:47:07,894 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0704) Prec@1 89.000 (88.809) Prec@5 100.000 (99.277) +2022-11-14 14:47:07,909 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0712) Prec@1 85.000 (88.729) Prec@5 99.000 (99.271) +2022-11-14 14:47:07,925 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0708) Prec@1 94.000 (88.837) Prec@5 99.000 (99.265) +2022-11-14 14:47:07,941 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0715) Prec@1 85.000 (88.760) Prec@5 100.000 (99.280) +2022-11-14 14:47:07,957 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0712) Prec@1 90.000 (88.784) Prec@5 100.000 (99.294) +2022-11-14 14:47:07,972 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0718) Prec@1 82.000 (88.654) Prec@5 99.000 (99.288) +2022-11-14 14:47:07,988 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0718) Prec@1 91.000 (88.698) Prec@5 99.000 (99.283) +2022-11-14 14:47:08,003 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0721) Prec@1 87.000 (88.667) Prec@5 100.000 (99.296) +2022-11-14 14:47:08,018 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0726) Prec@1 85.000 (88.600) Prec@5 99.000 (99.291) +2022-11-14 14:47:08,032 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0728) Prec@1 86.000 (88.554) Prec@5 99.000 (99.286) +2022-11-14 14:47:08,046 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0726) Prec@1 91.000 (88.596) Prec@5 100.000 (99.298) +2022-11-14 14:47:08,059 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0726) Prec@1 88.000 (88.586) Prec@5 100.000 (99.310) +2022-11-14 14:47:08,074 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0732) Prec@1 82.000 (88.475) Prec@5 99.000 (99.305) +2022-11-14 14:47:08,088 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0729) Prec@1 89.000 (88.483) Prec@5 100.000 (99.317) +2022-11-14 14:47:08,101 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0734) Prec@1 87.000 (88.459) Prec@5 100.000 (99.328) +2022-11-14 14:47:08,115 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0733) Prec@1 87.000 (88.435) Prec@5 99.000 (99.323) +2022-11-14 14:47:08,129 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0729) Prec@1 94.000 (88.524) Prec@5 100.000 (99.333) +2022-11-14 14:47:08,143 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0330 (0.0723) Prec@1 94.000 (88.609) Prec@5 100.000 (99.344) +2022-11-14 14:47:08,155 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0724) Prec@1 87.000 (88.585) Prec@5 100.000 (99.354) +2022-11-14 14:47:08,169 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0724) Prec@1 86.000 (88.545) Prec@5 98.000 (99.333) +2022-11-14 14:47:08,184 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0420 (0.0720) Prec@1 94.000 (88.627) Prec@5 100.000 (99.343) +2022-11-14 14:47:08,201 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0720) Prec@1 89.000 (88.632) Prec@5 99.000 (99.338) +2022-11-14 14:47:08,216 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0720) Prec@1 86.000 (88.594) Prec@5 99.000 (99.333) +2022-11-14 14:47:08,230 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0720) Prec@1 86.000 (88.557) Prec@5 100.000 (99.343) +2022-11-14 14:47:08,244 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0726) Prec@1 85.000 (88.507) Prec@5 100.000 (99.352) +2022-11-14 14:47:08,260 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0729) Prec@1 86.000 (88.472) Prec@5 99.000 (99.347) +2022-11-14 14:47:08,276 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0504 (0.0726) Prec@1 91.000 (88.507) Prec@5 100.000 (99.356) +2022-11-14 14:47:08,289 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0372 (0.0721) Prec@1 96.000 (88.608) Prec@5 100.000 (99.365) +2022-11-14 14:47:08,303 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0723) Prec@1 85.000 (88.560) Prec@5 100.000 (99.373) +2022-11-14 14:47:08,315 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0721) Prec@1 89.000 (88.566) Prec@5 99.000 (99.368) +2022-11-14 14:47:08,331 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0723) Prec@1 86.000 (88.532) Prec@5 98.000 (99.351) +2022-11-14 14:47:08,346 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0726) Prec@1 85.000 (88.487) Prec@5 97.000 (99.321) +2022-11-14 14:47:08,360 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0725) Prec@1 90.000 (88.506) Prec@5 99.000 (99.316) +2022-11-14 14:47:08,374 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0723) Prec@1 90.000 (88.525) Prec@5 100.000 (99.325) +2022-11-14 14:47:08,389 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0725) Prec@1 87.000 (88.506) Prec@5 99.000 (99.321) +2022-11-14 14:47:08,405 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0728) Prec@1 84.000 (88.451) Prec@5 100.000 (99.329) +2022-11-14 14:47:08,420 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0730) Prec@1 83.000 (88.386) Prec@5 100.000 (99.337) +2022-11-14 14:47:08,435 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0732) Prec@1 86.000 (88.357) Prec@5 98.000 (99.321) +2022-11-14 14:47:08,449 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0734) Prec@1 85.000 (88.318) Prec@5 97.000 (99.294) +2022-11-14 14:47:08,461 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0736) Prec@1 87.000 (88.302) Prec@5 100.000 (99.302) +2022-11-14 14:47:08,479 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0735) Prec@1 90.000 (88.322) Prec@5 99.000 (99.299) +2022-11-14 14:47:08,495 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0734) Prec@1 92.000 (88.364) Prec@5 99.000 (99.295) +2022-11-14 14:47:08,510 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0733) Prec@1 89.000 (88.371) Prec@5 100.000 (99.303) +2022-11-14 14:47:08,525 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0735) Prec@1 87.000 (88.356) Prec@5 98.000 (99.289) +2022-11-14 14:47:08,539 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0733) Prec@1 90.000 (88.374) Prec@5 100.000 (99.297) +2022-11-14 14:47:08,551 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0730) Prec@1 93.000 (88.424) Prec@5 100.000 (99.304) +2022-11-14 14:47:08,564 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0731) Prec@1 88.000 (88.419) Prec@5 100.000 (99.312) +2022-11-14 14:47:08,579 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0732) Prec@1 88.000 (88.415) Prec@5 99.000 (99.309) +2022-11-14 14:47:08,594 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0732) Prec@1 87.000 (88.400) Prec@5 98.000 (99.295) +2022-11-14 14:47:08,608 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0732) Prec@1 89.000 (88.406) Prec@5 99.000 (99.292) +2022-11-14 14:47:08,620 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0730) Prec@1 91.000 (88.433) Prec@5 98.000 (99.278) +2022-11-14 14:47:08,635 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0731) Prec@1 85.000 (88.398) Prec@5 97.000 (99.255) +2022-11-14 14:47:08,650 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0733) Prec@1 83.000 (88.343) Prec@5 99.000 (99.253) +2022-11-14 14:47:08,663 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0735) Prec@1 86.000 (88.320) Prec@5 100.000 (99.260) +2022-11-14 14:47:08,721 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 14:47:09,035 Epoch: [254][0/500] Time 0.027 (0.027) Data 0.231 (0.231) Loss 0.0455 (0.0455) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:09,356 Epoch: [254][10/500] Time 0.038 (0.028) Data 0.002 (0.023) Loss 0.0338 (0.0397) Prec@1 95.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:47:09,728 Epoch: [254][20/500] Time 0.034 (0.030) Data 0.002 (0.013) Loss 0.0146 (0.0313) Prec@1 99.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 14:47:10,113 Epoch: [254][30/500] Time 0.035 (0.032) Data 0.002 (0.009) Loss 0.0377 (0.0329) Prec@1 94.000 (94.500) Prec@5 98.000 (99.250) +2022-11-14 14:47:10,495 Epoch: [254][40/500] Time 0.035 (0.032) Data 0.002 (0.007) Loss 0.0246 (0.0313) Prec@1 97.000 (95.000) Prec@5 100.000 (99.400) +2022-11-14 14:47:10,964 Epoch: [254][50/500] Time 0.046 (0.034) Data 0.002 (0.006) Loss 0.0248 (0.0302) Prec@1 98.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 14:47:11,436 Epoch: [254][60/500] Time 0.047 (0.035) Data 0.002 (0.006) Loss 0.0289 (0.0300) Prec@1 94.000 (95.286) Prec@5 100.000 (99.571) +2022-11-14 14:47:11,905 Epoch: [254][70/500] Time 0.043 (0.036) Data 0.002 (0.005) Loss 0.0343 (0.0305) Prec@1 95.000 (95.250) Prec@5 100.000 (99.625) +2022-11-14 14:47:12,325 Epoch: [254][80/500] Time 0.031 (0.036) Data 0.002 (0.005) Loss 0.0357 (0.0311) Prec@1 92.000 (94.889) Prec@5 100.000 (99.667) +2022-11-14 14:47:12,698 Epoch: [254][90/500] Time 0.032 (0.036) Data 0.002 (0.004) Loss 0.0282 (0.0308) Prec@1 96.000 (95.000) Prec@5 100.000 (99.700) +2022-11-14 14:47:13,078 Epoch: [254][100/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.0366 (0.0313) Prec@1 91.000 (94.636) Prec@5 100.000 (99.727) +2022-11-14 14:47:13,454 Epoch: [254][110/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.0331 (0.0315) Prec@1 95.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 14:47:13,842 Epoch: [254][120/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0465 (0.0327) Prec@1 93.000 (94.538) Prec@5 100.000 (99.769) +2022-11-14 14:47:14,217 Epoch: [254][130/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0429 (0.0334) Prec@1 94.000 (94.500) Prec@5 100.000 (99.786) +2022-11-14 14:47:14,603 Epoch: [254][140/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0265 (0.0329) Prec@1 96.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 14:47:15,047 Epoch: [254][150/500] Time 0.029 (0.035) Data 0.002 (0.003) Loss 0.0540 (0.0342) Prec@1 93.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 14:47:15,460 Epoch: [254][160/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0297 (0.0340) Prec@1 94.000 (94.471) Prec@5 100.000 (99.824) +2022-11-14 14:47:15,827 Epoch: [254][170/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0266 (0.0336) Prec@1 96.000 (94.556) Prec@5 100.000 (99.833) +2022-11-14 14:47:16,201 Epoch: [254][180/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0479 (0.0343) Prec@1 91.000 (94.368) Prec@5 99.000 (99.789) +2022-11-14 14:47:16,583 Epoch: [254][190/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0520 (0.0352) Prec@1 92.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:47:16,970 Epoch: [254][200/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.0212 (0.0345) Prec@1 96.000 (94.333) Prec@5 100.000 (99.762) +2022-11-14 14:47:17,380 Epoch: [254][210/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0271 (0.0342) Prec@1 95.000 (94.364) Prec@5 100.000 (99.773) +2022-11-14 14:47:17,861 Epoch: [254][220/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.0223 (0.0337) Prec@1 97.000 (94.478) Prec@5 100.000 (99.783) +2022-11-14 14:47:18,261 Epoch: [254][230/500] Time 0.029 (0.035) Data 0.002 (0.003) Loss 0.0384 (0.0339) Prec@1 95.000 (94.500) Prec@5 100.000 (99.792) +2022-11-14 14:47:18,653 Epoch: [254][240/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0506 (0.0346) Prec@1 90.000 (94.320) Prec@5 100.000 (99.800) +2022-11-14 14:47:19,025 Epoch: [254][250/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0357 (0.0346) Prec@1 94.000 (94.308) Prec@5 100.000 (99.808) +2022-11-14 14:47:19,410 Epoch: [254][260/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0450 (0.0350) Prec@1 92.000 (94.222) Prec@5 100.000 (99.815) +2022-11-14 14:47:19,796 Epoch: [254][270/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0223 (0.0345) Prec@1 96.000 (94.286) Prec@5 100.000 (99.821) +2022-11-14 14:47:20,173 Epoch: [254][280/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0221 (0.0341) Prec@1 97.000 (94.379) Prec@5 100.000 (99.828) +2022-11-14 14:47:20,553 Epoch: [254][290/500] Time 0.035 (0.035) Data 0.002 (0.003) Loss 0.0271 (0.0339) Prec@1 95.000 (94.400) Prec@5 100.000 (99.833) +2022-11-14 14:47:20,936 Epoch: [254][300/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0487 (0.0344) Prec@1 90.000 (94.258) Prec@5 100.000 (99.839) +2022-11-14 14:47:21,427 Epoch: [254][310/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0313 (0.0343) Prec@1 95.000 (94.281) Prec@5 100.000 (99.844) +2022-11-14 14:47:21,901 Epoch: [254][320/500] Time 0.047 (0.036) Data 0.002 (0.003) Loss 0.0339 (0.0342) Prec@1 97.000 (94.364) Prec@5 100.000 (99.848) +2022-11-14 14:47:22,312 Epoch: [254][330/500] Time 0.049 (0.036) Data 0.002 (0.003) Loss 0.0404 (0.0344) Prec@1 93.000 (94.324) Prec@5 100.000 (99.853) +2022-11-14 14:47:22,689 Epoch: [254][340/500] Time 0.030 (0.035) Data 0.003 (0.003) Loss 0.0375 (0.0345) Prec@1 92.000 (94.257) Prec@5 100.000 (99.857) +2022-11-14 14:47:23,134 Epoch: [254][350/500] Time 0.065 (0.036) Data 0.002 (0.003) Loss 0.0165 (0.0340) Prec@1 98.000 (94.361) Prec@5 100.000 (99.861) +2022-11-14 14:47:23,530 Epoch: [254][360/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0417 (0.0342) Prec@1 93.000 (94.324) Prec@5 99.000 (99.838) +2022-11-14 14:47:23,965 Epoch: [254][370/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0508 (0.0347) Prec@1 92.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 14:47:24,415 Epoch: [254][380/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0272 (0.0345) Prec@1 93.000 (94.231) Prec@5 100.000 (99.846) +2022-11-14 14:47:24,885 Epoch: [254][390/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0290 (0.0343) Prec@1 96.000 (94.275) Prec@5 99.000 (99.825) +2022-11-14 14:47:25,318 Epoch: [254][400/500] Time 0.040 (0.036) Data 0.002 (0.003) Loss 0.0435 (0.0346) Prec@1 93.000 (94.244) Prec@5 100.000 (99.829) +2022-11-14 14:47:25,700 Epoch: [254][410/500] Time 0.033 (0.036) Data 0.002 (0.003) Loss 0.0432 (0.0348) Prec@1 93.000 (94.214) Prec@5 100.000 (99.833) +2022-11-14 14:47:26,139 Epoch: [254][420/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.0352 (0.0348) Prec@1 95.000 (94.233) Prec@5 100.000 (99.837) +2022-11-14 14:47:26,560 Epoch: [254][430/500] Time 0.036 (0.036) Data 0.002 (0.003) Loss 0.0316 (0.0347) Prec@1 96.000 (94.273) Prec@5 100.000 (99.841) +2022-11-14 14:47:26,976 Epoch: [254][440/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0351 (0.0347) Prec@1 94.000 (94.267) Prec@5 99.000 (99.822) +2022-11-14 14:47:27,405 Epoch: [254][450/500] Time 0.028 (0.036) Data 0.002 (0.002) Loss 0.0294 (0.0346) Prec@1 96.000 (94.304) Prec@5 100.000 (99.826) +2022-11-14 14:47:27,826 Epoch: [254][460/500] Time 0.050 (0.036) Data 0.002 (0.002) Loss 0.0472 (0.0349) Prec@1 91.000 (94.234) Prec@5 99.000 (99.809) +2022-11-14 14:47:28,270 Epoch: [254][470/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0320 (0.0348) Prec@1 94.000 (94.229) Prec@5 100.000 (99.812) +2022-11-14 14:47:28,752 Epoch: [254][480/500] Time 0.059 (0.036) Data 0.003 (0.002) Loss 0.0177 (0.0345) Prec@1 97.000 (94.286) Prec@5 100.000 (99.816) +2022-11-14 14:47:29,150 Epoch: [254][490/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0513 (0.0348) Prec@1 91.000 (94.220) Prec@5 100.000 (99.820) +2022-11-14 14:47:29,549 Epoch: [254][499/500] Time 0.034 (0.036) Data 0.002 (0.002) Loss 0.0161 (0.0344) Prec@1 97.000 (94.275) Prec@5 100.000 (99.824) +2022-11-14 14:47:29,856 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0799 (0.0799) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:29,871 Test: [1/100] Model Time 0.012 (0.014) Loss Time 0.000 (0.000) Loss 0.0632 (0.0716) Prec@1 91.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:29,883 Test: [2/100] Model Time 0.011 (0.013) Loss Time 0.000 (0.000) Loss 0.0882 (0.0771) Prec@1 86.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:29,898 Test: [3/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0811 (0.0781) Prec@1 87.000 (87.750) Prec@5 100.000 (100.000) +2022-11-14 14:47:29,907 Test: [4/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0669 (0.0759) Prec@1 91.000 (88.400) Prec@5 100.000 (100.000) +2022-11-14 14:47:29,917 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0407 (0.0700) Prec@1 95.000 (89.500) Prec@5 99.000 (99.833) +2022-11-14 14:47:29,927 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0706 (0.0701) Prec@1 88.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 14:47:29,940 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0791 (0.0712) Prec@1 86.000 (88.875) Prec@5 100.000 (99.875) +2022-11-14 14:47:29,952 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0836 (0.0726) Prec@1 87.000 (88.667) Prec@5 98.000 (99.667) +2022-11-14 14:47:29,965 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0729) Prec@1 88.000 (88.600) Prec@5 99.000 (99.600) +2022-11-14 14:47:29,979 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0734) Prec@1 87.000 (88.455) Prec@5 100.000 (99.636) +2022-11-14 14:47:29,992 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0750) Prec@1 86.000 (88.250) Prec@5 99.000 (99.583) +2022-11-14 14:47:30,005 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0445 (0.0727) Prec@1 91.000 (88.462) Prec@5 100.000 (99.615) +2022-11-14 14:47:30,017 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.0737) Prec@1 86.000 (88.286) Prec@5 99.000 (99.571) +2022-11-14 14:47:30,030 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0746) Prec@1 86.000 (88.133) Prec@5 99.000 (99.533) +2022-11-14 14:47:30,046 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0744) Prec@1 88.000 (88.125) Prec@5 100.000 (99.562) +2022-11-14 14:47:30,060 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0742) Prec@1 90.000 (88.235) Prec@5 98.000 (99.471) +2022-11-14 14:47:30,071 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0756) Prec@1 84.000 (88.000) Prec@5 99.000 (99.444) +2022-11-14 14:47:30,086 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0756) Prec@1 86.000 (87.895) Prec@5 98.000 (99.368) +2022-11-14 14:47:30,101 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0762) Prec@1 84.000 (87.700) Prec@5 97.000 (99.250) +2022-11-14 14:47:30,115 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0769) Prec@1 87.000 (87.667) Prec@5 98.000 (99.190) +2022-11-14 14:47:30,129 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1074 (0.0782) Prec@1 85.000 (87.545) Prec@5 98.000 (99.136) +2022-11-14 14:47:30,143 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0790) Prec@1 83.000 (87.348) Prec@5 99.000 (99.130) +2022-11-14 14:47:30,155 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0794) Prec@1 84.000 (87.208) Prec@5 99.000 (99.125) +2022-11-14 14:47:30,169 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0793) Prec@1 87.000 (87.200) Prec@5 100.000 (99.160) +2022-11-14 14:47:30,182 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0794) Prec@1 88.000 (87.231) Prec@5 100.000 (99.192) +2022-11-14 14:47:30,199 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0782) Prec@1 93.000 (87.444) Prec@5 100.000 (99.222) +2022-11-14 14:47:30,215 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0777) Prec@1 89.000 (87.500) Prec@5 100.000 (99.250) +2022-11-14 14:47:30,230 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0777) Prec@1 90.000 (87.586) Prec@5 97.000 (99.172) +2022-11-14 14:47:30,248 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0776) Prec@1 87.000 (87.567) Prec@5 99.000 (99.167) +2022-11-14 14:47:30,263 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0776) Prec@1 87.000 (87.548) Prec@5 99.000 (99.161) +2022-11-14 14:47:30,277 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0776) Prec@1 87.000 (87.531) Prec@5 99.000 (99.156) +2022-11-14 14:47:30,291 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0770) Prec@1 88.000 (87.545) Prec@5 100.000 (99.182) +2022-11-14 14:47:30,305 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0777) Prec@1 84.000 (87.441) Prec@5 99.000 (99.176) +2022-11-14 14:47:30,320 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0783) Prec@1 84.000 (87.343) Prec@5 99.000 (99.171) +2022-11-14 14:47:30,335 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0779) Prec@1 91.000 (87.444) Prec@5 100.000 (99.194) +2022-11-14 14:47:30,350 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0777) Prec@1 89.000 (87.486) Prec@5 98.000 (99.162) +2022-11-14 14:47:30,365 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0783) Prec@1 83.000 (87.368) Prec@5 98.000 (99.132) +2022-11-14 14:47:30,379 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0781) Prec@1 92.000 (87.487) Prec@5 100.000 (99.154) +2022-11-14 14:47:30,392 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0776) Prec@1 90.000 (87.550) Prec@5 99.000 (99.150) +2022-11-14 14:47:30,407 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0781) Prec@1 85.000 (87.488) Prec@5 98.000 (99.122) +2022-11-14 14:47:30,422 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0781) Prec@1 87.000 (87.476) Prec@5 99.000 (99.119) +2022-11-14 14:47:30,436 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0773) Prec@1 94.000 (87.628) Prec@5 99.000 (99.116) +2022-11-14 14:47:30,452 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0771) Prec@1 89.000 (87.659) Prec@5 100.000 (99.136) +2022-11-14 14:47:30,467 Test: [44/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0349 (0.0762) Prec@1 94.000 (87.800) Prec@5 99.000 (99.133) +2022-11-14 14:47:30,482 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0765) Prec@1 85.000 (87.739) Prec@5 99.000 (99.130) +2022-11-14 14:47:30,495 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0766) Prec@1 87.000 (87.723) Prec@5 100.000 (99.149) +2022-11-14 14:47:30,513 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0767) Prec@1 86.000 (87.688) Prec@5 98.000 (99.125) +2022-11-14 14:47:30,527 Test: [48/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0763) Prec@1 93.000 (87.796) Prec@5 100.000 (99.143) +2022-11-14 14:47:30,542 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0765) Prec@1 87.000 (87.780) Prec@5 100.000 (99.160) +2022-11-14 14:47:30,557 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0761) Prec@1 90.000 (87.824) Prec@5 100.000 (99.176) +2022-11-14 14:47:30,572 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0759) Prec@1 86.000 (87.788) Prec@5 100.000 (99.192) +2022-11-14 14:47:30,588 Test: [52/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0759) Prec@1 88.000 (87.792) Prec@5 100.000 (99.208) +2022-11-14 14:47:30,602 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0759) Prec@1 88.000 (87.796) Prec@5 100.000 (99.222) +2022-11-14 14:47:30,615 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0762) Prec@1 86.000 (87.764) Prec@5 100.000 (99.236) +2022-11-14 14:47:30,629 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0763) Prec@1 87.000 (87.750) Prec@5 99.000 (99.232) +2022-11-14 14:47:30,644 Test: [56/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0762) Prec@1 87.000 (87.737) Prec@5 100.000 (99.246) +2022-11-14 14:47:30,660 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0761) Prec@1 89.000 (87.759) Prec@5 100.000 (99.259) +2022-11-14 14:47:30,675 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.0767) Prec@1 84.000 (87.695) Prec@5 100.000 (99.271) +2022-11-14 14:47:30,690 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0765) Prec@1 88.000 (87.700) Prec@5 99.000 (99.267) +2022-11-14 14:47:30,706 Test: [60/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0764) Prec@1 89.000 (87.721) Prec@5 99.000 (99.262) +2022-11-14 14:47:30,720 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0761) Prec@1 91.000 (87.774) Prec@5 98.000 (99.242) +2022-11-14 14:47:30,734 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0759) Prec@1 86.000 (87.746) Prec@5 100.000 (99.254) +2022-11-14 14:47:30,747 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0450 (0.0755) Prec@1 92.000 (87.812) Prec@5 100.000 (99.266) +2022-11-14 14:47:30,762 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0757) Prec@1 85.000 (87.769) Prec@5 99.000 (99.262) +2022-11-14 14:47:30,776 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0758) Prec@1 89.000 (87.788) Prec@5 100.000 (99.273) +2022-11-14 14:47:30,791 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0754) Prec@1 91.000 (87.836) Prec@5 100.000 (99.284) +2022-11-14 14:47:30,804 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0754) Prec@1 90.000 (87.868) Prec@5 99.000 (99.279) +2022-11-14 14:47:30,819 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0750) Prec@1 92.000 (87.928) Prec@5 99.000 (99.275) +2022-11-14 14:47:30,834 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0750) Prec@1 87.000 (87.914) Prec@5 100.000 (99.286) +2022-11-14 14:47:30,850 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0753) Prec@1 86.000 (87.887) Prec@5 99.000 (99.282) +2022-11-14 14:47:30,865 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0753) Prec@1 88.000 (87.889) Prec@5 100.000 (99.292) +2022-11-14 14:47:30,879 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0750) Prec@1 92.000 (87.945) Prec@5 100.000 (99.301) +2022-11-14 14:47:30,894 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0422 (0.0746) Prec@1 93.000 (88.014) Prec@5 100.000 (99.311) +2022-11-14 14:47:30,908 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0750) Prec@1 80.000 (87.907) Prec@5 100.000 (99.320) +2022-11-14 14:47:30,921 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0747) Prec@1 91.000 (87.947) Prec@5 99.000 (99.316) +2022-11-14 14:47:30,936 Test: [76/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0746) Prec@1 89.000 (87.961) Prec@5 100.000 (99.325) +2022-11-14 14:47:30,951 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0749) Prec@1 84.000 (87.910) Prec@5 99.000 (99.321) +2022-11-14 14:47:30,965 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0749) Prec@1 88.000 (87.911) Prec@5 100.000 (99.329) +2022-11-14 14:47:30,980 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0749) Prec@1 89.000 (87.925) Prec@5 99.000 (99.325) +2022-11-14 14:47:30,996 Test: [80/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0752) Prec@1 83.000 (87.864) Prec@5 99.000 (99.321) +2022-11-14 14:47:31,010 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0756) Prec@1 85.000 (87.829) Prec@5 99.000 (99.317) +2022-11-14 14:47:31,023 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0757) Prec@1 86.000 (87.807) Prec@5 99.000 (99.313) +2022-11-14 14:47:31,037 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0759) Prec@1 82.000 (87.738) Prec@5 99.000 (99.310) +2022-11-14 14:47:31,051 Test: [84/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0760) Prec@1 85.000 (87.706) Prec@5 100.000 (99.318) +2022-11-14 14:47:31,064 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.0765) Prec@1 82.000 (87.640) Prec@5 99.000 (99.314) +2022-11-14 14:47:31,079 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0765) Prec@1 86.000 (87.621) Prec@5 100.000 (99.322) +2022-11-14 14:47:31,096 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0765) Prec@1 87.000 (87.614) Prec@5 98.000 (99.307) +2022-11-14 14:47:31,113 Test: [88/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0763) Prec@1 90.000 (87.640) Prec@5 100.000 (99.315) +2022-11-14 14:47:31,128 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0763) Prec@1 87.000 (87.633) Prec@5 98.000 (99.300) +2022-11-14 14:47:31,143 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0761) Prec@1 92.000 (87.681) Prec@5 100.000 (99.308) +2022-11-14 14:47:31,158 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0758) Prec@1 93.000 (87.739) Prec@5 100.000 (99.315) +2022-11-14 14:47:31,171 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0760) Prec@1 85.000 (87.710) Prec@5 100.000 (99.323) +2022-11-14 14:47:31,185 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 89.000 (87.723) Prec@5 100.000 (99.330) +2022-11-14 14:47:31,197 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0762) Prec@1 82.000 (87.663) Prec@5 100.000 (99.337) +2022-11-14 14:47:31,210 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0762) Prec@1 89.000 (87.677) Prec@5 100.000 (99.344) +2022-11-14 14:47:31,224 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0759) Prec@1 93.000 (87.732) Prec@5 99.000 (99.340) +2022-11-14 14:47:31,239 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0761) Prec@1 85.000 (87.704) Prec@5 99.000 (99.337) +2022-11-14 14:47:31,256 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1151 (0.0765) Prec@1 83.000 (87.657) Prec@5 98.000 (99.323) +2022-11-14 14:47:31,272 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0765) Prec@1 88.000 (87.660) Prec@5 99.000 (99.320) +2022-11-14 14:47:31,336 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:47:31,672 Epoch: [255][0/500] Time 0.025 (0.025) Data 0.252 (0.252) Loss 0.0595 (0.0595) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:47:32,108 Epoch: [255][10/500] Time 0.045 (0.037) Data 0.002 (0.024) Loss 0.0288 (0.0442) Prec@1 97.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 14:47:32,565 Epoch: [255][20/500] Time 0.041 (0.039) Data 0.002 (0.014) Loss 0.0581 (0.0488) Prec@1 92.000 (92.333) Prec@5 99.000 (99.333) +2022-11-14 14:47:32,969 Epoch: [255][30/500] Time 0.050 (0.038) Data 0.002 (0.010) Loss 0.0305 (0.0442) Prec@1 96.000 (93.250) Prec@5 99.000 (99.250) +2022-11-14 14:47:33,480 Epoch: [255][40/500] Time 0.043 (0.040) Data 0.002 (0.008) Loss 0.0202 (0.0394) Prec@1 98.000 (94.200) Prec@5 100.000 (99.400) +2022-11-14 14:47:34,220 Epoch: [255][50/500] Time 0.109 (0.045) Data 0.002 (0.007) Loss 0.0298 (0.0378) Prec@1 94.000 (94.167) Prec@5 100.000 (99.500) +2022-11-14 14:47:34,845 Epoch: [255][60/500] Time 0.050 (0.047) Data 0.002 (0.006) Loss 0.0404 (0.0382) Prec@1 93.000 (94.000) Prec@5 99.000 (99.429) +2022-11-14 14:47:35,404 Epoch: [255][70/500] Time 0.043 (0.048) Data 0.002 (0.006) Loss 0.0259 (0.0366) Prec@1 95.000 (94.125) Prec@5 100.000 (99.500) +2022-11-14 14:47:35,966 Epoch: [255][80/500] Time 0.046 (0.048) Data 0.002 (0.005) Loss 0.0402 (0.0370) Prec@1 94.000 (94.111) Prec@5 100.000 (99.556) +2022-11-14 14:47:36,555 Epoch: [255][90/500] Time 0.044 (0.049) Data 0.002 (0.005) Loss 0.0395 (0.0373) Prec@1 94.000 (94.100) Prec@5 100.000 (99.600) +2022-11-14 14:47:37,126 Epoch: [255][100/500] Time 0.043 (0.049) Data 0.002 (0.004) Loss 0.0145 (0.0352) Prec@1 98.000 (94.455) Prec@5 100.000 (99.636) +2022-11-14 14:47:37,621 Epoch: [255][110/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0415 (0.0357) Prec@1 93.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 14:47:38,192 Epoch: [255][120/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0296 (0.0353) Prec@1 95.000 (94.385) Prec@5 100.000 (99.692) +2022-11-14 14:47:38,936 Epoch: [255][130/500] Time 0.052 (0.050) Data 0.002 (0.004) Loss 0.0304 (0.0349) Prec@1 95.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 14:47:39,527 Epoch: [255][140/500] Time 0.043 (0.050) Data 0.002 (0.004) Loss 0.0437 (0.0355) Prec@1 92.000 (94.267) Prec@5 100.000 (99.733) +2022-11-14 14:47:40,226 Epoch: [255][150/500] Time 0.101 (0.051) Data 0.002 (0.004) Loss 0.0338 (0.0354) Prec@1 92.000 (94.125) Prec@5 100.000 (99.750) +2022-11-14 14:47:40,701 Epoch: [255][160/500] Time 0.043 (0.051) Data 0.002 (0.004) Loss 0.0334 (0.0353) Prec@1 96.000 (94.235) Prec@5 99.000 (99.706) +2022-11-14 14:47:41,171 Epoch: [255][170/500] Time 0.042 (0.050) Data 0.002 (0.003) Loss 0.0377 (0.0354) Prec@1 94.000 (94.222) Prec@5 100.000 (99.722) +2022-11-14 14:47:41,780 Epoch: [255][180/500] Time 0.112 (0.050) Data 0.002 (0.003) Loss 0.0688 (0.0372) Prec@1 87.000 (93.842) Prec@5 100.000 (99.737) +2022-11-14 14:47:42,261 Epoch: [255][190/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0377 (0.0372) Prec@1 94.000 (93.850) Prec@5 100.000 (99.750) +2022-11-14 14:47:42,787 Epoch: [255][200/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0318 (0.0369) Prec@1 95.000 (93.905) Prec@5 100.000 (99.762) +2022-11-14 14:47:43,405 Epoch: [255][210/500] Time 0.126 (0.050) Data 0.002 (0.003) Loss 0.0515 (0.0376) Prec@1 90.000 (93.727) Prec@5 100.000 (99.773) +2022-11-14 14:47:44,305 Epoch: [255][220/500] Time 0.126 (0.051) Data 0.002 (0.003) Loss 0.0781 (0.0394) Prec@1 86.000 (93.391) Prec@5 100.000 (99.783) +2022-11-14 14:47:44,789 Epoch: [255][230/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.0467 (0.0397) Prec@1 91.000 (93.292) Prec@5 100.000 (99.792) +2022-11-14 14:47:45,348 Epoch: [255][240/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0281 (0.0392) Prec@1 95.000 (93.360) Prec@5 100.000 (99.800) +2022-11-14 14:47:45,938 Epoch: [255][250/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0489 (0.0396) Prec@1 92.000 (93.308) Prec@5 100.000 (99.808) +2022-11-14 14:47:46,454 Epoch: [255][260/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0449 (0.0398) Prec@1 93.000 (93.296) Prec@5 99.000 (99.778) +2022-11-14 14:47:47,037 Epoch: [255][270/500] Time 0.089 (0.051) Data 0.002 (0.003) Loss 0.0256 (0.0393) Prec@1 97.000 (93.429) Prec@5 100.000 (99.786) +2022-11-14 14:47:47,629 Epoch: [255][280/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0373 (0.0392) Prec@1 95.000 (93.483) Prec@5 100.000 (99.793) +2022-11-14 14:47:48,110 Epoch: [255][290/500] Time 0.041 (0.050) Data 0.002 (0.003) Loss 0.0363 (0.0391) Prec@1 93.000 (93.467) Prec@5 99.000 (99.767) +2022-11-14 14:47:48,588 Epoch: [255][300/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0331 (0.0389) Prec@1 96.000 (93.548) Prec@5 100.000 (99.774) +2022-11-14 14:47:49,060 Epoch: [255][310/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0460 (0.0391) Prec@1 93.000 (93.531) Prec@5 100.000 (99.781) +2022-11-14 14:47:49,745 Epoch: [255][320/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0166 (0.0384) Prec@1 97.000 (93.636) Prec@5 100.000 (99.788) +2022-11-14 14:47:50,217 Epoch: [255][330/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0332 (0.0383) Prec@1 95.000 (93.676) Prec@5 100.000 (99.794) +2022-11-14 14:47:50,679 Epoch: [255][340/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0525 (0.0387) Prec@1 92.000 (93.629) Prec@5 100.000 (99.800) +2022-11-14 14:47:51,142 Epoch: [255][350/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0285 (0.0384) Prec@1 95.000 (93.667) Prec@5 100.000 (99.806) +2022-11-14 14:47:51,614 Epoch: [255][360/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0474 (0.0387) Prec@1 92.000 (93.622) Prec@5 100.000 (99.811) +2022-11-14 14:47:52,074 Epoch: [255][370/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0358 (0.0386) Prec@1 94.000 (93.632) Prec@5 100.000 (99.816) +2022-11-14 14:47:52,538 Epoch: [255][380/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.0405 (0.0386) Prec@1 94.000 (93.641) Prec@5 100.000 (99.821) +2022-11-14 14:47:53,001 Epoch: [255][390/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0314 (0.0384) Prec@1 95.000 (93.675) Prec@5 100.000 (99.825) +2022-11-14 14:47:53,463 Epoch: [255][400/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0435 (0.0386) Prec@1 92.000 (93.634) Prec@5 100.000 (99.829) +2022-11-14 14:47:53,924 Epoch: [255][410/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0539 (0.0389) Prec@1 90.000 (93.548) Prec@5 100.000 (99.833) +2022-11-14 14:47:54,385 Epoch: [255][420/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0381 (0.0389) Prec@1 93.000 (93.535) Prec@5 100.000 (99.837) +2022-11-14 14:47:54,848 Epoch: [255][430/500] Time 0.044 (0.048) Data 0.001 (0.003) Loss 0.0575 (0.0393) Prec@1 90.000 (93.455) Prec@5 98.000 (99.795) +2022-11-14 14:47:55,313 Epoch: [255][440/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0490 (0.0396) Prec@1 91.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:47:55,775 Epoch: [255][450/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0385 (0.0395) Prec@1 95.000 (93.435) Prec@5 99.000 (99.783) +2022-11-14 14:47:56,237 Epoch: [255][460/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0244 (0.0392) Prec@1 96.000 (93.489) Prec@5 100.000 (99.787) +2022-11-14 14:47:56,701 Epoch: [255][470/500] Time 0.042 (0.047) Data 0.002 (0.002) Loss 0.0302 (0.0390) Prec@1 96.000 (93.542) Prec@5 100.000 (99.792) +2022-11-14 14:47:57,162 Epoch: [255][480/500] Time 0.043 (0.047) Data 0.001 (0.002) Loss 0.0473 (0.0392) Prec@1 91.000 (93.490) Prec@5 100.000 (99.796) +2022-11-14 14:47:57,623 Epoch: [255][490/500] Time 0.043 (0.047) Data 0.002 (0.002) Loss 0.0446 (0.0393) Prec@1 93.000 (93.480) Prec@5 100.000 (99.800) +2022-11-14 14:47:58,040 Epoch: [255][499/500] Time 0.044 (0.047) Data 0.002 (0.002) Loss 0.0310 (0.0391) Prec@1 96.000 (93.529) Prec@5 100.000 (99.804) +2022-11-14 14:47:58,310 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0853 (0.0853) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 14:47:58,318 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0802) Prec@1 87.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 14:47:58,327 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0766) Prec@1 90.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 14:47:58,339 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0760) Prec@1 86.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 14:47:58,348 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0767) Prec@1 88.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 14:47:58,356 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0405 (0.0707) Prec@1 92.000 (88.167) Prec@5 99.000 (99.500) +2022-11-14 14:47:58,365 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0684) Prec@1 92.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 14:47:58,377 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0696) Prec@1 89.000 (88.750) Prec@5 100.000 (99.625) +2022-11-14 14:47:58,386 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0706) Prec@1 88.000 (88.667) Prec@5 99.000 (99.556) +2022-11-14 14:47:58,397 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0720) Prec@1 88.000 (88.600) Prec@5 99.000 (99.500) +2022-11-14 14:47:58,408 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0711) Prec@1 90.000 (88.727) Prec@5 100.000 (99.545) +2022-11-14 14:47:58,418 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0723) Prec@1 87.000 (88.583) Prec@5 99.000 (99.500) +2022-11-14 14:47:58,427 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0712) Prec@1 90.000 (88.692) Prec@5 100.000 (99.538) +2022-11-14 14:47:58,436 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0712) Prec@1 89.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 14:47:58,446 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0711) Prec@1 88.000 (88.667) Prec@5 99.000 (99.533) +2022-11-14 14:47:58,458 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0719) Prec@1 87.000 (88.562) Prec@5 100.000 (99.562) +2022-11-14 14:47:58,471 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0713) Prec@1 90.000 (88.647) Prec@5 99.000 (99.529) +2022-11-14 14:47:58,482 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1223 (0.0742) Prec@1 82.000 (88.278) Prec@5 100.000 (99.556) +2022-11-14 14:47:58,495 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0745) Prec@1 88.000 (88.263) Prec@5 98.000 (99.474) +2022-11-14 14:47:58,508 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0753) Prec@1 84.000 (88.050) Prec@5 99.000 (99.450) +2022-11-14 14:47:58,521 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0761) Prec@1 87.000 (88.000) Prec@5 99.000 (99.429) +2022-11-14 14:47:58,531 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0764) Prec@1 86.000 (87.909) Prec@5 99.000 (99.409) +2022-11-14 14:47:58,541 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0773) Prec@1 83.000 (87.696) Prec@5 100.000 (99.435) +2022-11-14 14:47:58,551 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0774) Prec@1 87.000 (87.667) Prec@5 100.000 (99.458) +2022-11-14 14:47:58,563 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0775) Prec@1 87.000 (87.640) Prec@5 100.000 (99.480) +2022-11-14 14:47:58,576 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0780) Prec@1 87.000 (87.615) Prec@5 97.000 (99.385) +2022-11-14 14:47:58,589 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0770) Prec@1 89.000 (87.667) Prec@5 100.000 (99.407) +2022-11-14 14:47:58,602 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0759) Prec@1 92.000 (87.821) Prec@5 100.000 (99.429) +2022-11-14 14:47:58,614 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0757) Prec@1 90.000 (87.897) Prec@5 99.000 (99.414) +2022-11-14 14:47:58,625 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0755) Prec@1 89.000 (87.933) Prec@5 100.000 (99.433) +2022-11-14 14:47:58,638 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0753) Prec@1 88.000 (87.935) Prec@5 100.000 (99.452) +2022-11-14 14:47:58,651 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0751) Prec@1 88.000 (87.938) Prec@5 99.000 (99.438) +2022-11-14 14:47:58,662 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0752) Prec@1 87.000 (87.909) Prec@5 100.000 (99.455) +2022-11-14 14:47:58,674 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1215 (0.0766) Prec@1 81.000 (87.706) Prec@5 99.000 (99.441) +2022-11-14 14:47:58,687 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0764) Prec@1 85.000 (87.629) Prec@5 99.000 (99.429) +2022-11-14 14:47:58,699 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0761) Prec@1 89.000 (87.667) Prec@5 100.000 (99.444) +2022-11-14 14:47:58,711 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0764) Prec@1 82.000 (87.514) Prec@5 99.000 (99.432) +2022-11-14 14:47:58,723 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0770) Prec@1 83.000 (87.395) Prec@5 100.000 (99.447) +2022-11-14 14:47:58,735 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0771) Prec@1 89.000 (87.436) Prec@5 100.000 (99.462) +2022-11-14 14:47:58,748 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0771) Prec@1 87.000 (87.425) Prec@5 100.000 (99.475) +2022-11-14 14:47:58,760 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0774) Prec@1 86.000 (87.390) Prec@5 99.000 (99.463) +2022-11-14 14:47:58,771 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0771) Prec@1 90.000 (87.452) Prec@5 98.000 (99.429) +2022-11-14 14:47:58,784 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0364 (0.0761) Prec@1 96.000 (87.651) Prec@5 99.000 (99.419) +2022-11-14 14:47:58,797 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0760) Prec@1 88.000 (87.659) Prec@5 97.000 (99.364) +2022-11-14 14:47:58,809 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0756) Prec@1 91.000 (87.733) Prec@5 100.000 (99.378) +2022-11-14 14:47:58,820 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0758) Prec@1 87.000 (87.717) Prec@5 100.000 (99.391) +2022-11-14 14:47:58,832 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0756) Prec@1 87.000 (87.702) Prec@5 100.000 (99.404) +2022-11-14 14:47:58,844 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0761) Prec@1 83.000 (87.604) Prec@5 98.000 (99.375) +2022-11-14 14:47:58,855 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0756) Prec@1 91.000 (87.673) Prec@5 100.000 (99.388) +2022-11-14 14:47:58,868 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0760) Prec@1 86.000 (87.640) Prec@5 100.000 (99.400) +2022-11-14 14:47:58,880 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0759) Prec@1 89.000 (87.667) Prec@5 100.000 (99.412) +2022-11-14 14:47:58,892 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0760) Prec@1 87.000 (87.654) Prec@5 100.000 (99.423) +2022-11-14 14:47:58,903 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0757) Prec@1 92.000 (87.736) Prec@5 99.000 (99.415) +2022-11-14 14:47:58,915 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0760) Prec@1 86.000 (87.704) Prec@5 99.000 (99.407) +2022-11-14 14:47:58,927 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0760) Prec@1 87.000 (87.691) Prec@5 100.000 (99.418) +2022-11-14 14:47:58,938 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0758) Prec@1 90.000 (87.732) Prec@5 99.000 (99.411) +2022-11-14 14:47:58,951 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0760) Prec@1 86.000 (87.702) Prec@5 99.000 (99.404) +2022-11-14 14:47:58,964 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0756) Prec@1 92.000 (87.776) Prec@5 100.000 (99.414) +2022-11-14 14:47:58,977 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0762) Prec@1 84.000 (87.712) Prec@5 99.000 (99.407) +2022-11-14 14:47:58,989 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0761) Prec@1 90.000 (87.750) Prec@5 100.000 (99.417) +2022-11-14 14:47:59,000 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0760) Prec@1 89.000 (87.770) Prec@5 98.000 (99.393) +2022-11-14 14:47:59,012 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0758) Prec@1 90.000 (87.806) Prec@5 100.000 (99.403) +2022-11-14 14:47:59,024 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0753) Prec@1 93.000 (87.889) Prec@5 100.000 (99.413) +2022-11-14 14:47:59,035 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0748) Prec@1 93.000 (87.969) Prec@5 100.000 (99.422) +2022-11-14 14:47:59,047 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0749) Prec@1 89.000 (87.985) Prec@5 100.000 (99.431) +2022-11-14 14:47:59,059 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0747) Prec@1 89.000 (88.000) Prec@5 99.000 (99.424) +2022-11-14 14:47:59,070 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0743) Prec@1 92.000 (88.060) Prec@5 100.000 (99.433) +2022-11-14 14:47:59,082 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0743) Prec@1 89.000 (88.074) Prec@5 98.000 (99.412) +2022-11-14 14:47:59,094 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0743) Prec@1 87.000 (88.058) Prec@5 99.000 (99.406) +2022-11-14 14:47:59,105 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0742) Prec@1 89.000 (88.071) Prec@5 99.000 (99.400) +2022-11-14 14:47:59,118 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0744) Prec@1 88.000 (88.070) Prec@5 100.000 (99.408) +2022-11-14 14:47:59,131 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0742) Prec@1 92.000 (88.125) Prec@5 98.000 (99.389) +2022-11-14 14:47:59,144 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0737) Prec@1 93.000 (88.192) Prec@5 100.000 (99.397) +2022-11-14 14:47:59,155 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0737) Prec@1 89.000 (88.203) Prec@5 100.000 (99.405) +2022-11-14 14:47:59,167 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0741) Prec@1 86.000 (88.173) Prec@5 100.000 (99.413) +2022-11-14 14:47:59,180 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0739) Prec@1 91.000 (88.211) Prec@5 99.000 (99.408) +2022-11-14 14:47:59,192 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0739) Prec@1 89.000 (88.221) Prec@5 98.000 (99.390) +2022-11-14 14:47:59,204 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0740) Prec@1 87.000 (88.205) Prec@5 98.000 (99.372) +2022-11-14 14:47:59,216 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0738) Prec@1 92.000 (88.253) Prec@5 100.000 (99.380) +2022-11-14 14:47:59,228 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0737) Prec@1 88.000 (88.250) Prec@5 100.000 (99.388) +2022-11-14 14:47:59,241 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0739) Prec@1 86.000 (88.222) Prec@5 97.000 (99.358) +2022-11-14 14:47:59,253 Test: [81/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0738) Prec@1 90.000 (88.244) Prec@5 99.000 (99.354) +2022-11-14 14:47:59,264 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0739) Prec@1 87.000 (88.229) Prec@5 100.000 (99.361) +2022-11-14 14:47:59,277 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0735) Prec@1 91.000 (88.262) Prec@5 100.000 (99.369) +2022-11-14 14:47:59,289 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0737) Prec@1 87.000 (88.247) Prec@5 99.000 (99.365) +2022-11-14 14:47:59,301 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0741) Prec@1 84.000 (88.198) Prec@5 100.000 (99.372) +2022-11-14 14:47:59,312 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0742) Prec@1 85.000 (88.161) Prec@5 99.000 (99.368) +2022-11-14 14:47:59,324 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0740) Prec@1 92.000 (88.205) Prec@5 99.000 (99.364) +2022-11-14 14:47:59,336 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0740) Prec@1 90.000 (88.225) Prec@5 100.000 (99.371) +2022-11-14 14:47:59,348 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0738) Prec@1 89.000 (88.233) Prec@5 100.000 (99.378) +2022-11-14 14:47:59,360 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0738) Prec@1 89.000 (88.242) Prec@5 100.000 (99.385) +2022-11-14 14:47:59,373 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0736) Prec@1 91.000 (88.272) Prec@5 100.000 (99.391) +2022-11-14 14:47:59,385 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0738) Prec@1 86.000 (88.247) Prec@5 100.000 (99.398) +2022-11-14 14:47:59,396 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0739) Prec@1 84.000 (88.202) Prec@5 99.000 (99.394) +2022-11-14 14:47:59,408 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0739) Prec@1 85.000 (88.168) Prec@5 100.000 (99.400) +2022-11-14 14:47:59,419 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0739) Prec@1 91.000 (88.198) Prec@5 99.000 (99.396) +2022-11-14 14:47:59,432 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0736) Prec@1 91.000 (88.227) Prec@5 99.000 (99.392) +2022-11-14 14:47:59,444 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0738) Prec@1 88.000 (88.224) Prec@5 99.000 (99.388) +2022-11-14 14:47:59,455 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0740) Prec@1 85.000 (88.192) Prec@5 100.000 (99.394) +2022-11-14 14:47:59,466 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0741) Prec@1 83.000 (88.140) Prec@5 99.000 (99.390) +2022-11-14 14:47:59,528 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:47:59,842 Epoch: [256][0/500] Time 0.024 (0.024) Data 0.232 (0.232) Loss 0.0517 (0.0517) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 14:48:00,060 Epoch: [256][10/500] Time 0.020 (0.019) Data 0.001 (0.023) Loss 0.0327 (0.0422) Prec@1 95.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 14:48:00,291 Epoch: [256][20/500] Time 0.022 (0.020) Data 0.002 (0.013) Loss 0.0427 (0.0424) Prec@1 93.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:48:00,520 Epoch: [256][30/500] Time 0.020 (0.020) Data 0.002 (0.009) Loss 0.0446 (0.0430) Prec@1 93.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:48:00,763 Epoch: [256][40/500] Time 0.019 (0.020) Data 0.002 (0.007) Loss 0.0449 (0.0433) Prec@1 92.000 (92.800) Prec@5 98.000 (99.400) +2022-11-14 14:48:00,997 Epoch: [256][50/500] Time 0.023 (0.020) Data 0.002 (0.006) Loss 0.0577 (0.0457) Prec@1 91.000 (92.500) Prec@5 98.000 (99.167) +2022-11-14 14:48:01,302 Epoch: [256][60/500] Time 0.030 (0.021) Data 0.001 (0.005) Loss 0.0364 (0.0444) Prec@1 94.000 (92.714) Prec@5 100.000 (99.286) +2022-11-14 14:48:01,617 Epoch: [256][70/500] Time 0.029 (0.022) Data 0.002 (0.005) Loss 0.0547 (0.0457) Prec@1 90.000 (92.375) Prec@5 100.000 (99.375) +2022-11-14 14:48:01,929 Epoch: [256][80/500] Time 0.029 (0.023) Data 0.002 (0.005) Loss 0.0425 (0.0453) Prec@1 92.000 (92.333) Prec@5 99.000 (99.333) +2022-11-14 14:48:02,244 Epoch: [256][90/500] Time 0.030 (0.024) Data 0.001 (0.004) Loss 0.0174 (0.0425) Prec@1 97.000 (92.800) Prec@5 100.000 (99.400) +2022-11-14 14:48:02,562 Epoch: [256][100/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0178 (0.0403) Prec@1 96.000 (93.091) Prec@5 100.000 (99.455) +2022-11-14 14:48:02,880 Epoch: [256][110/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0223 (0.0388) Prec@1 97.000 (93.417) Prec@5 99.000 (99.417) +2022-11-14 14:48:03,193 Epoch: [256][120/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0203 (0.0374) Prec@1 96.000 (93.615) Prec@5 100.000 (99.462) +2022-11-14 14:48:03,513 Epoch: [256][130/500] Time 0.030 (0.025) Data 0.002 (0.004) Loss 0.0327 (0.0370) Prec@1 95.000 (93.714) Prec@5 100.000 (99.500) +2022-11-14 14:48:03,894 Epoch: [256][140/500] Time 0.025 (0.026) Data 0.001 (0.003) Loss 0.0404 (0.0373) Prec@1 94.000 (93.733) Prec@5 99.000 (99.467) +2022-11-14 14:48:04,265 Epoch: [256][150/500] Time 0.047 (0.026) Data 0.002 (0.003) Loss 0.0308 (0.0369) Prec@1 94.000 (93.750) Prec@5 100.000 (99.500) +2022-11-14 14:48:04,600 Epoch: [256][160/500] Time 0.028 (0.026) Data 0.001 (0.003) Loss 0.0329 (0.0366) Prec@1 93.000 (93.706) Prec@5 100.000 (99.529) +2022-11-14 14:48:04,915 Epoch: [256][170/500] Time 0.027 (0.026) Data 0.002 (0.003) Loss 0.0262 (0.0360) Prec@1 94.000 (93.722) Prec@5 100.000 (99.556) +2022-11-14 14:48:05,227 Epoch: [256][180/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0165 (0.0350) Prec@1 98.000 (93.947) Prec@5 100.000 (99.579) +2022-11-14 14:48:05,544 Epoch: [256][190/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0358 (0.0351) Prec@1 95.000 (94.000) Prec@5 100.000 (99.600) +2022-11-14 14:48:05,861 Epoch: [256][200/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0341 (0.0350) Prec@1 94.000 (94.000) Prec@5 100.000 (99.619) +2022-11-14 14:48:06,259 Epoch: [256][210/500] Time 0.042 (0.027) Data 0.002 (0.003) Loss 0.0392 (0.0352) Prec@1 94.000 (94.000) Prec@5 100.000 (99.636) +2022-11-14 14:48:06,609 Epoch: [256][220/500] Time 0.057 (0.027) Data 0.002 (0.003) Loss 0.0393 (0.0354) Prec@1 94.000 (94.000) Prec@5 99.000 (99.609) +2022-11-14 14:48:06,915 Epoch: [256][230/500] Time 0.026 (0.027) Data 0.002 (0.003) Loss 0.0242 (0.0349) Prec@1 96.000 (94.083) Prec@5 100.000 (99.625) +2022-11-14 14:48:07,245 Epoch: [256][240/500] Time 0.026 (0.027) Data 0.002 (0.003) Loss 0.0208 (0.0343) Prec@1 97.000 (94.200) Prec@5 100.000 (99.640) +2022-11-14 14:48:07,571 Epoch: [256][250/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0146 (0.0336) Prec@1 100.000 (94.423) Prec@5 100.000 (99.654) +2022-11-14 14:48:07,894 Epoch: [256][260/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0245 (0.0333) Prec@1 96.000 (94.481) Prec@5 100.000 (99.667) +2022-11-14 14:48:08,249 Epoch: [256][270/500] Time 0.043 (0.028) Data 0.002 (0.003) Loss 0.0323 (0.0332) Prec@1 94.000 (94.464) Prec@5 99.000 (99.643) +2022-11-14 14:48:08,813 Epoch: [256][280/500] Time 0.042 (0.028) Data 0.002 (0.003) Loss 0.0186 (0.0327) Prec@1 98.000 (94.586) Prec@5 100.000 (99.655) +2022-11-14 14:48:09,488 Epoch: [256][290/500] Time 0.051 (0.029) Data 0.002 (0.003) Loss 0.0324 (0.0327) Prec@1 96.000 (94.633) Prec@5 100.000 (99.667) +2022-11-14 14:48:10,053 Epoch: [256][300/500] Time 0.043 (0.030) Data 0.002 (0.003) Loss 0.0335 (0.0327) Prec@1 96.000 (94.677) Prec@5 100.000 (99.677) +2022-11-14 14:48:10,520 Epoch: [256][310/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.0393 (0.0329) Prec@1 94.000 (94.656) Prec@5 100.000 (99.688) +2022-11-14 14:48:11,042 Epoch: [256][320/500] Time 0.045 (0.031) Data 0.002 (0.003) Loss 0.0457 (0.0333) Prec@1 92.000 (94.576) Prec@5 100.000 (99.697) +2022-11-14 14:48:11,745 Epoch: [256][330/500] Time 0.054 (0.032) Data 0.002 (0.003) Loss 0.0474 (0.0337) Prec@1 92.000 (94.500) Prec@5 100.000 (99.706) +2022-11-14 14:48:12,241 Epoch: [256][340/500] Time 0.048 (0.032) Data 0.002 (0.003) Loss 0.0325 (0.0337) Prec@1 95.000 (94.514) Prec@5 100.000 (99.714) +2022-11-14 14:48:12,729 Epoch: [256][350/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0202 (0.0333) Prec@1 97.000 (94.583) Prec@5 100.000 (99.722) +2022-11-14 14:48:13,212 Epoch: [256][360/500] Time 0.043 (0.033) Data 0.001 (0.002) Loss 0.0406 (0.0335) Prec@1 94.000 (94.568) Prec@5 100.000 (99.730) +2022-11-14 14:48:13,717 Epoch: [256][370/500] Time 0.043 (0.033) Data 0.002 (0.002) Loss 0.0359 (0.0336) Prec@1 94.000 (94.553) Prec@5 100.000 (99.737) +2022-11-14 14:48:14,209 Epoch: [256][380/500] Time 0.045 (0.033) Data 0.002 (0.002) Loss 0.0386 (0.0337) Prec@1 94.000 (94.538) Prec@5 100.000 (99.744) +2022-11-14 14:48:14,682 Epoch: [256][390/500] Time 0.042 (0.034) Data 0.002 (0.002) Loss 0.0397 (0.0339) Prec@1 94.000 (94.525) Prec@5 100.000 (99.750) +2022-11-14 14:48:15,153 Epoch: [256][400/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0482 (0.0342) Prec@1 93.000 (94.488) Prec@5 100.000 (99.756) +2022-11-14 14:48:15,625 Epoch: [256][410/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0147 (0.0338) Prec@1 97.000 (94.548) Prec@5 100.000 (99.762) +2022-11-14 14:48:16,098 Epoch: [256][420/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0205 (0.0334) Prec@1 97.000 (94.605) Prec@5 100.000 (99.767) +2022-11-14 14:48:16,577 Epoch: [256][430/500] Time 0.048 (0.034) Data 0.002 (0.002) Loss 0.0365 (0.0335) Prec@1 94.000 (94.591) Prec@5 100.000 (99.773) +2022-11-14 14:48:17,058 Epoch: [256][440/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.0441 (0.0337) Prec@1 92.000 (94.533) Prec@5 99.000 (99.756) +2022-11-14 14:48:17,546 Epoch: [256][450/500] Time 0.041 (0.035) Data 0.002 (0.002) Loss 0.0276 (0.0336) Prec@1 96.000 (94.565) Prec@5 100.000 (99.761) +2022-11-14 14:48:18,034 Epoch: [256][460/500] Time 0.043 (0.035) Data 0.003 (0.002) Loss 0.0259 (0.0334) Prec@1 96.000 (94.596) Prec@5 100.000 (99.766) +2022-11-14 14:48:18,543 Epoch: [256][470/500] Time 0.050 (0.035) Data 0.002 (0.002) Loss 0.0422 (0.0336) Prec@1 94.000 (94.583) Prec@5 100.000 (99.771) +2022-11-14 14:48:19,026 Epoch: [256][480/500] Time 0.044 (0.035) Data 0.002 (0.002) Loss 0.0434 (0.0338) Prec@1 93.000 (94.551) Prec@5 100.000 (99.776) +2022-11-14 14:48:19,513 Epoch: [256][490/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0567 (0.0343) Prec@1 90.000 (94.460) Prec@5 99.000 (99.760) +2022-11-14 14:48:19,973 Epoch: [256][499/500] Time 0.046 (0.036) Data 0.002 (0.002) Loss 0.0243 (0.0341) Prec@1 95.000 (94.471) Prec@5 100.000 (99.765) +2022-11-14 14:48:20,263 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0551 (0.0551) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:20,273 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0637) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:20,282 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0634) Prec@1 90.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 14:48:20,295 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0649) Prec@1 88.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 14:48:20,303 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0638) Prec@1 91.000 (89.400) Prec@5 100.000 (99.800) +2022-11-14 14:48:20,312 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0615) Prec@1 92.000 (89.833) Prec@5 100.000 (99.833) +2022-11-14 14:48:20,321 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0603) Prec@1 93.000 (90.286) Prec@5 100.000 (99.857) +2022-11-14 14:48:20,332 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0625) Prec@1 88.000 (90.000) Prec@5 98.000 (99.625) +2022-11-14 14:48:20,342 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0647) Prec@1 87.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 14:48:20,351 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0672) Prec@1 85.000 (89.200) Prec@5 98.000 (99.500) +2022-11-14 14:48:20,361 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0670) Prec@1 91.000 (89.364) Prec@5 100.000 (99.545) +2022-11-14 14:48:20,370 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1067 (0.0704) Prec@1 82.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 14:48:20,380 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0694) Prec@1 89.000 (88.769) Prec@5 100.000 (99.538) +2022-11-14 14:48:20,390 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0714) Prec@1 83.000 (88.357) Prec@5 99.000 (99.500) +2022-11-14 14:48:20,401 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0719) Prec@1 88.000 (88.333) Prec@5 98.000 (99.400) +2022-11-14 14:48:20,412 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0721) Prec@1 88.000 (88.312) Prec@5 100.000 (99.438) +2022-11-14 14:48:20,424 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0711) Prec@1 93.000 (88.588) Prec@5 99.000 (99.412) +2022-11-14 14:48:20,435 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0733) Prec@1 83.000 (88.278) Prec@5 100.000 (99.444) +2022-11-14 14:48:20,446 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0742) Prec@1 85.000 (88.105) Prec@5 98.000 (99.368) +2022-11-14 14:48:20,458 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0749) Prec@1 86.000 (88.000) Prec@5 97.000 (99.250) +2022-11-14 14:48:20,468 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0758) Prec@1 86.000 (87.905) Prec@5 98.000 (99.190) +2022-11-14 14:48:20,480 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0768) Prec@1 85.000 (87.773) Prec@5 97.000 (99.091) +2022-11-14 14:48:20,491 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0772) Prec@1 87.000 (87.739) Prec@5 99.000 (99.087) +2022-11-14 14:48:20,503 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0768) Prec@1 87.000 (87.708) Prec@5 100.000 (99.125) +2022-11-14 14:48:20,515 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0782) Prec@1 85.000 (87.600) Prec@5 99.000 (99.120) +2022-11-14 14:48:20,526 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1108 (0.0794) Prec@1 84.000 (87.462) Prec@5 98.000 (99.077) +2022-11-14 14:48:20,537 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0784) Prec@1 94.000 (87.704) Prec@5 100.000 (99.111) +2022-11-14 14:48:20,549 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0776) Prec@1 90.000 (87.786) Prec@5 100.000 (99.143) +2022-11-14 14:48:20,561 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0779) Prec@1 85.000 (87.690) Prec@5 99.000 (99.138) +2022-11-14 14:48:20,570 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0776) Prec@1 90.000 (87.767) Prec@5 100.000 (99.167) +2022-11-14 14:48:20,580 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0771) Prec@1 92.000 (87.903) Prec@5 100.000 (99.194) +2022-11-14 14:48:20,589 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0768) Prec@1 90.000 (87.969) Prec@5 98.000 (99.156) +2022-11-14 14:48:20,600 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0766) Prec@1 89.000 (88.000) Prec@5 100.000 (99.182) +2022-11-14 14:48:20,612 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0765) Prec@1 86.000 (87.941) Prec@5 99.000 (99.176) +2022-11-14 14:48:20,623 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0764) Prec@1 91.000 (88.029) Prec@5 98.000 (99.143) +2022-11-14 14:48:20,633 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0761) Prec@1 90.000 (88.083) Prec@5 99.000 (99.139) +2022-11-14 14:48:20,645 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0760) Prec@1 90.000 (88.135) Prec@5 97.000 (99.081) +2022-11-14 14:48:20,657 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0770) Prec@1 81.000 (87.947) Prec@5 99.000 (99.079) +2022-11-14 14:48:20,671 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0764) Prec@1 92.000 (88.051) Prec@5 99.000 (99.077) +2022-11-14 14:48:20,684 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0763) Prec@1 87.000 (88.025) Prec@5 99.000 (99.075) +2022-11-14 14:48:20,695 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0768) Prec@1 86.000 (87.976) Prec@5 97.000 (99.024) +2022-11-14 14:48:20,707 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0767) Prec@1 89.000 (88.000) Prec@5 98.000 (99.000) +2022-11-14 14:48:20,720 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0353 (0.0758) Prec@1 93.000 (88.116) Prec@5 100.000 (99.023) +2022-11-14 14:48:20,732 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0758) Prec@1 89.000 (88.136) Prec@5 98.000 (99.000) +2022-11-14 14:48:20,744 Test: [44/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0754) Prec@1 91.000 (88.200) Prec@5 99.000 (99.000) +2022-11-14 14:48:20,757 Test: [45/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0754) Prec@1 87.000 (88.174) Prec@5 100.000 (99.022) +2022-11-14 14:48:20,770 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0752) Prec@1 88.000 (88.170) Prec@5 99.000 (99.021) +2022-11-14 14:48:20,782 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0755) Prec@1 86.000 (88.125) Prec@5 100.000 (99.042) +2022-11-14 14:48:20,794 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0754) Prec@1 89.000 (88.143) Prec@5 99.000 (99.041) +2022-11-14 14:48:20,806 Test: [49/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0759) Prec@1 83.000 (88.040) Prec@5 100.000 (99.060) +2022-11-14 14:48:20,819 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0758) Prec@1 87.000 (88.020) Prec@5 99.000 (99.059) +2022-11-14 14:48:20,832 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0758) Prec@1 89.000 (88.038) Prec@5 99.000 (99.058) +2022-11-14 14:48:20,846 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0758) Prec@1 88.000 (88.038) Prec@5 100.000 (99.075) +2022-11-14 14:48:20,858 Test: [53/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0758) Prec@1 88.000 (88.037) Prec@5 98.000 (99.056) +2022-11-14 14:48:20,870 Test: [54/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0758) Prec@1 89.000 (88.055) Prec@5 100.000 (99.073) +2022-11-14 14:48:20,882 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0759) Prec@1 89.000 (88.071) Prec@5 98.000 (99.054) +2022-11-14 14:48:20,893 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0758) Prec@1 85.000 (88.018) Prec@5 100.000 (99.070) +2022-11-14 14:48:20,906 Test: [57/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0757) Prec@1 90.000 (88.052) Prec@5 99.000 (99.069) +2022-11-14 14:48:20,917 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0760) Prec@1 85.000 (88.000) Prec@5 100.000 (99.085) +2022-11-14 14:48:20,929 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0763) Prec@1 83.000 (87.917) Prec@5 98.000 (99.067) +2022-11-14 14:48:20,940 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0762) Prec@1 87.000 (87.902) Prec@5 100.000 (99.082) +2022-11-14 14:48:20,952 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0761) Prec@1 89.000 (87.919) Prec@5 100.000 (99.097) +2022-11-14 14:48:20,963 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0757) Prec@1 92.000 (87.984) Prec@5 100.000 (99.111) +2022-11-14 14:48:20,973 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0339 (0.0750) Prec@1 94.000 (88.078) Prec@5 100.000 (99.125) +2022-11-14 14:48:20,985 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0751) Prec@1 87.000 (88.062) Prec@5 100.000 (99.138) +2022-11-14 14:48:20,998 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0751) Prec@1 87.000 (88.045) Prec@5 99.000 (99.136) +2022-11-14 14:48:21,012 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0746) Prec@1 93.000 (88.119) Prec@5 100.000 (99.149) +2022-11-14 14:48:21,023 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0745) Prec@1 90.000 (88.147) Prec@5 98.000 (99.132) +2022-11-14 14:48:21,034 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0744) Prec@1 88.000 (88.145) Prec@5 99.000 (99.130) +2022-11-14 14:48:21,047 Test: [69/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0745) Prec@1 86.000 (88.114) Prec@5 98.000 (99.114) +2022-11-14 14:48:21,057 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0747) Prec@1 87.000 (88.099) Prec@5 98.000 (99.099) +2022-11-14 14:48:21,068 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0747) Prec@1 89.000 (88.111) Prec@5 100.000 (99.111) +2022-11-14 14:48:21,080 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0743) Prec@1 90.000 (88.137) Prec@5 99.000 (99.110) +2022-11-14 14:48:21,090 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0426 (0.0739) Prec@1 94.000 (88.216) Prec@5 100.000 (99.122) +2022-11-14 14:48:21,101 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0741) Prec@1 81.000 (88.120) Prec@5 100.000 (99.133) +2022-11-14 14:48:21,113 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0741) Prec@1 90.000 (88.145) Prec@5 99.000 (99.132) +2022-11-14 14:48:21,125 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0740) Prec@1 91.000 (88.182) Prec@5 97.000 (99.104) +2022-11-14 14:48:21,138 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0741) Prec@1 87.000 (88.167) Prec@5 98.000 (99.090) +2022-11-14 14:48:21,150 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0743) Prec@1 84.000 (88.114) Prec@5 100.000 (99.101) +2022-11-14 14:48:21,161 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0743) Prec@1 85.000 (88.075) Prec@5 100.000 (99.112) +2022-11-14 14:48:21,172 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0745) Prec@1 86.000 (88.049) Prec@5 98.000 (99.099) +2022-11-14 14:48:21,184 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0748) Prec@1 85.000 (88.012) Prec@5 98.000 (99.085) +2022-11-14 14:48:21,193 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0749) Prec@1 87.000 (88.000) Prec@5 100.000 (99.096) +2022-11-14 14:48:21,204 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0747) Prec@1 85.000 (87.964) Prec@5 100.000 (99.107) +2022-11-14 14:48:21,215 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0747) Prec@1 89.000 (87.976) Prec@5 100.000 (99.118) +2022-11-14 14:48:21,228 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0749) Prec@1 86.000 (87.953) Prec@5 100.000 (99.128) +2022-11-14 14:48:21,240 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0751) Prec@1 86.000 (87.931) Prec@5 99.000 (99.126) +2022-11-14 14:48:21,251 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0752) Prec@1 88.000 (87.932) Prec@5 99.000 (99.125) +2022-11-14 14:48:21,263 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0752) Prec@1 86.000 (87.910) Prec@5 100.000 (99.135) +2022-11-14 14:48:21,275 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0753) Prec@1 89.000 (87.922) Prec@5 100.000 (99.144) +2022-11-14 14:48:21,286 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0751) Prec@1 90.000 (87.945) Prec@5 100.000 (99.154) +2022-11-14 14:48:21,298 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0306 (0.0746) Prec@1 95.000 (88.022) Prec@5 99.000 (99.152) +2022-11-14 14:48:21,310 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0749) Prec@1 84.000 (87.978) Prec@5 100.000 (99.161) +2022-11-14 14:48:21,321 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0749) Prec@1 88.000 (87.979) Prec@5 99.000 (99.160) +2022-11-14 14:48:21,331 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0749) Prec@1 88.000 (87.979) Prec@5 100.000 (99.168) +2022-11-14 14:48:21,342 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0748) Prec@1 91.000 (88.010) Prec@5 99.000 (99.167) +2022-11-14 14:48:21,354 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0746) Prec@1 94.000 (88.072) Prec@5 99.000 (99.165) +2022-11-14 14:48:21,366 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0749) Prec@1 83.000 (88.020) Prec@5 99.000 (99.163) +2022-11-14 14:48:21,377 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0752) Prec@1 83.000 (87.970) Prec@5 99.000 (99.162) +2022-11-14 14:48:21,389 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0752) Prec@1 84.000 (87.930) Prec@5 100.000 (99.170) +2022-11-14 14:48:21,446 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:48:21,739 Epoch: [257][0/500] Time 0.021 (0.021) Data 0.213 (0.213) Loss 0.0263 (0.0263) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:21,961 Epoch: [257][10/500] Time 0.021 (0.020) Data 0.002 (0.021) Loss 0.0444 (0.0353) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:48:22,185 Epoch: [257][20/500] Time 0.018 (0.020) Data 0.002 (0.012) Loss 0.0190 (0.0299) Prec@1 97.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:48:22,406 Epoch: [257][30/500] Time 0.021 (0.020) Data 0.002 (0.008) Loss 0.0339 (0.0309) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:48:22,807 Epoch: [257][40/500] Time 0.052 (0.023) Data 0.002 (0.007) Loss 0.0303 (0.0308) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:23,231 Epoch: [257][50/500] Time 0.037 (0.026) Data 0.002 (0.006) Loss 0.0297 (0.0306) Prec@1 93.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:48:23,662 Epoch: [257][60/500] Time 0.041 (0.028) Data 0.001 (0.005) Loss 0.0252 (0.0298) Prec@1 96.000 (94.857) Prec@5 99.000 (99.857) +2022-11-14 14:48:24,138 Epoch: [257][70/500] Time 0.041 (0.030) Data 0.002 (0.005) Loss 0.0295 (0.0298) Prec@1 95.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 14:48:24,598 Epoch: [257][80/500] Time 0.070 (0.031) Data 0.002 (0.004) Loss 0.0430 (0.0313) Prec@1 93.000 (94.667) Prec@5 99.000 (99.778) +2022-11-14 14:48:25,010 Epoch: [257][90/500] Time 0.038 (0.032) Data 0.002 (0.004) Loss 0.0530 (0.0334) Prec@1 90.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:48:25,465 Epoch: [257][100/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.0280 (0.0329) Prec@1 96.000 (94.364) Prec@5 99.000 (99.727) +2022-11-14 14:48:25,912 Epoch: [257][110/500] Time 0.046 (0.033) Data 0.003 (0.004) Loss 0.0478 (0.0342) Prec@1 89.000 (93.917) Prec@5 100.000 (99.750) +2022-11-14 14:48:26,346 Epoch: [257][120/500] Time 0.041 (0.034) Data 0.002 (0.004) Loss 0.0451 (0.0350) Prec@1 92.000 (93.769) Prec@5 100.000 (99.769) +2022-11-14 14:48:26,797 Epoch: [257][130/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0412 (0.0355) Prec@1 92.000 (93.643) Prec@5 98.000 (99.643) +2022-11-14 14:48:27,240 Epoch: [257][140/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0240 (0.0347) Prec@1 96.000 (93.800) Prec@5 100.000 (99.667) +2022-11-14 14:48:27,683 Epoch: [257][150/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0239 (0.0340) Prec@1 95.000 (93.875) Prec@5 100.000 (99.688) +2022-11-14 14:48:28,125 Epoch: [257][160/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0465 (0.0348) Prec@1 91.000 (93.706) Prec@5 100.000 (99.706) +2022-11-14 14:48:28,558 Epoch: [257][170/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0269 (0.0343) Prec@1 96.000 (93.833) Prec@5 99.000 (99.667) +2022-11-14 14:48:28,987 Epoch: [257][180/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0464 (0.0350) Prec@1 94.000 (93.842) Prec@5 100.000 (99.684) +2022-11-14 14:48:29,442 Epoch: [257][190/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0740 (0.0369) Prec@1 88.000 (93.550) Prec@5 100.000 (99.700) +2022-11-14 14:48:29,872 Epoch: [257][200/500] Time 0.039 (0.036) Data 0.002 (0.003) Loss 0.0306 (0.0366) Prec@1 95.000 (93.619) Prec@5 100.000 (99.714) +2022-11-14 14:48:30,309 Epoch: [257][210/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0155 (0.0356) Prec@1 98.000 (93.818) Prec@5 100.000 (99.727) +2022-11-14 14:48:30,757 Epoch: [257][220/500] Time 0.042 (0.036) Data 0.002 (0.003) Loss 0.0366 (0.0357) Prec@1 95.000 (93.870) Prec@5 100.000 (99.739) +2022-11-14 14:48:31,204 Epoch: [257][230/500] Time 0.052 (0.036) Data 0.002 (0.003) Loss 0.0598 (0.0367) Prec@1 91.000 (93.750) Prec@5 98.000 (99.667) +2022-11-14 14:48:31,634 Epoch: [257][240/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0361 (0.0367) Prec@1 95.000 (93.800) Prec@5 100.000 (99.680) +2022-11-14 14:48:32,070 Epoch: [257][250/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0372 (0.0367) Prec@1 92.000 (93.731) Prec@5 100.000 (99.692) +2022-11-14 14:48:32,496 Epoch: [257][260/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0418 (0.0369) Prec@1 92.000 (93.667) Prec@5 100.000 (99.704) +2022-11-14 14:48:32,927 Epoch: [257][270/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0312 (0.0367) Prec@1 96.000 (93.750) Prec@5 99.000 (99.679) +2022-11-14 14:48:33,377 Epoch: [257][280/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0330 (0.0365) Prec@1 94.000 (93.759) Prec@5 100.000 (99.690) +2022-11-14 14:48:33,798 Epoch: [257][290/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0563 (0.0372) Prec@1 91.000 (93.667) Prec@5 100.000 (99.700) +2022-11-14 14:48:34,265 Epoch: [257][300/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0498 (0.0376) Prec@1 90.000 (93.548) Prec@5 100.000 (99.710) +2022-11-14 14:48:34,699 Epoch: [257][310/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.0232 (0.0372) Prec@1 95.000 (93.594) Prec@5 100.000 (99.719) +2022-11-14 14:48:35,186 Epoch: [257][320/500] Time 0.073 (0.037) Data 0.002 (0.003) Loss 0.0617 (0.0379) Prec@1 91.000 (93.515) Prec@5 100.000 (99.727) +2022-11-14 14:48:35,596 Epoch: [257][330/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0293 (0.0376) Prec@1 95.000 (93.559) Prec@5 100.000 (99.735) +2022-11-14 14:48:36,043 Epoch: [257][340/500] Time 0.038 (0.037) Data 0.002 (0.002) Loss 0.0397 (0.0377) Prec@1 94.000 (93.571) Prec@5 100.000 (99.743) +2022-11-14 14:48:36,522 Epoch: [257][350/500] Time 0.035 (0.037) Data 0.002 (0.002) Loss 0.0441 (0.0379) Prec@1 92.000 (93.528) Prec@5 99.000 (99.722) +2022-11-14 14:48:36,937 Epoch: [257][360/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0426 (0.0380) Prec@1 93.000 (93.514) Prec@5 100.000 (99.730) +2022-11-14 14:48:37,401 Epoch: [257][370/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.0364 (0.0380) Prec@1 96.000 (93.579) Prec@5 100.000 (99.737) +2022-11-14 14:48:37,882 Epoch: [257][380/500] Time 0.044 (0.038) Data 0.001 (0.002) Loss 0.0300 (0.0378) Prec@1 94.000 (93.590) Prec@5 100.000 (99.744) +2022-11-14 14:48:38,438 Epoch: [257][390/500] Time 0.060 (0.038) Data 0.002 (0.002) Loss 0.0201 (0.0373) Prec@1 99.000 (93.725) Prec@5 100.000 (99.750) +2022-11-14 14:48:38,879 Epoch: [257][400/500] Time 0.035 (0.038) Data 0.001 (0.002) Loss 0.0459 (0.0375) Prec@1 91.000 (93.659) Prec@5 100.000 (99.756) +2022-11-14 14:48:39,404 Epoch: [257][410/500] Time 0.028 (0.038) Data 0.002 (0.002) Loss 0.0362 (0.0375) Prec@1 94.000 (93.667) Prec@5 100.000 (99.762) +2022-11-14 14:48:39,817 Epoch: [257][420/500] Time 0.041 (0.038) Data 0.002 (0.002) Loss 0.0450 (0.0377) Prec@1 93.000 (93.651) Prec@5 100.000 (99.767) +2022-11-14 14:48:40,246 Epoch: [257][430/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0527 (0.0380) Prec@1 91.000 (93.591) Prec@5 100.000 (99.773) +2022-11-14 14:48:40,671 Epoch: [257][440/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0435 (0.0381) Prec@1 92.000 (93.556) Prec@5 99.000 (99.756) 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99.000 (99.429) +2022-11-14 14:48:43,745 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0706) Prec@1 85.000 (88.500) Prec@5 99.000 (99.375) +2022-11-14 14:48:43,752 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0713) Prec@1 88.000 (88.444) Prec@5 100.000 (99.444) +2022-11-14 14:48:43,761 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0702) Prec@1 89.000 (88.500) Prec@5 99.000 (99.400) +2022-11-14 14:48:43,770 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0694) Prec@1 89.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 14:48:43,780 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0700) Prec@1 89.000 (88.583) Prec@5 100.000 (99.500) +2022-11-14 14:48:43,789 Test: [12/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0681) Prec@1 93.000 (88.923) Prec@5 100.000 (99.538) +2022-11-14 14:48:43,798 Test: [13/100] Model 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91.000 (87.923) Prec@5 100.000 (99.333) +2022-11-14 14:48:44,046 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0740) Prec@1 90.000 (87.975) Prec@5 98.000 (99.300) +2022-11-14 14:48:44,055 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0741) Prec@1 88.000 (87.976) Prec@5 97.000 (99.244) +2022-11-14 14:48:44,065 Test: [41/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0744) Prec@1 87.000 (87.952) Prec@5 99.000 (99.238) +2022-11-14 14:48:44,075 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0739) Prec@1 92.000 (88.047) Prec@5 99.000 (99.233) +2022-11-14 14:48:44,085 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0736) Prec@1 90.000 (88.091) Prec@5 99.000 (99.227) +2022-11-14 14:48:44,094 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0733) Prec@1 90.000 (88.133) Prec@5 100.000 (99.244) +2022-11-14 14:48:44,104 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0943 (0.0738) Prec@1 83.000 (88.022) Prec@5 100.000 (99.261) +2022-11-14 14:48:44,115 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0737) Prec@1 89.000 (88.043) Prec@5 100.000 (99.277) +2022-11-14 14:48:44,128 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0742) Prec@1 84.000 (87.958) Prec@5 99.000 (99.271) +2022-11-14 14:48:44,141 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0739) Prec@1 87.000 (87.939) Prec@5 100.000 (99.286) +2022-11-14 14:48:44,154 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0745) Prec@1 83.000 (87.840) Prec@5 99.000 (99.280) +2022-11-14 14:48:44,167 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0742) Prec@1 91.000 (87.902) Prec@5 100.000 (99.294) +2022-11-14 14:48:44,181 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0741) Prec@1 89.000 (87.923) Prec@5 100.000 (99.308) +2022-11-14 14:48:44,194 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0743) Prec@1 84.000 (87.849) Prec@5 100.000 (99.321) +2022-11-14 14:48:44,208 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0740) Prec@1 90.000 (87.889) Prec@5 100.000 (99.333) +2022-11-14 14:48:44,221 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0743) Prec@1 86.000 (87.855) Prec@5 100.000 (99.345) +2022-11-14 14:48:44,233 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0743) Prec@1 88.000 (87.857) Prec@5 99.000 (99.339) +2022-11-14 14:48:44,247 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0741) Prec@1 91.000 (87.912) Prec@5 100.000 (99.351) +2022-11-14 14:48:44,258 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0738) Prec@1 93.000 (88.000) Prec@5 99.000 (99.345) +2022-11-14 14:48:44,271 Test: [58/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0742) Prec@1 87.000 (87.983) Prec@5 100.000 (99.356) +2022-11-14 14:48:44,285 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0741) Prec@1 88.000 (87.983) Prec@5 100.000 (99.367) +2022-11-14 14:48:44,298 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0742) Prec@1 89.000 (88.000) Prec@5 99.000 (99.361) +2022-11-14 14:48:44,310 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0742) Prec@1 89.000 (88.016) Prec@5 99.000 (99.355) +2022-11-14 14:48:44,323 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0738) Prec@1 90.000 (88.048) Prec@5 100.000 (99.365) +2022-11-14 14:48:44,335 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0735) Prec@1 91.000 (88.094) Prec@5 99.000 (99.359) +2022-11-14 14:48:44,347 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0740) Prec@1 82.000 (88.000) Prec@5 100.000 (99.369) +2022-11-14 14:48:44,360 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0738) Prec@1 90.000 (88.030) Prec@5 99.000 (99.364) +2022-11-14 14:48:44,373 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0337 (0.0732) Prec@1 95.000 (88.134) Prec@5 100.000 (99.373) +2022-11-14 14:48:44,384 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0734) Prec@1 89.000 (88.147) Prec@5 96.000 (99.324) +2022-11-14 14:48:44,396 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0733) Prec@1 88.000 (88.145) Prec@5 99.000 (99.319) +2022-11-14 14:48:44,410 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0736) Prec@1 84.000 (88.086) Prec@5 98.000 (99.300) +2022-11-14 14:48:44,422 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.0741) Prec@1 83.000 (88.014) Prec@5 99.000 (99.296) +2022-11-14 14:48:44,436 Test: [71/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0739) Prec@1 90.000 (88.042) Prec@5 99.000 (99.292) +2022-11-14 14:48:44,448 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0737) Prec@1 91.000 (88.082) Prec@5 100.000 (99.301) +2022-11-14 14:48:44,461 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0733) Prec@1 93.000 (88.149) Prec@5 99.000 (99.297) +2022-11-14 14:48:44,473 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0737) Prec@1 83.000 (88.080) Prec@5 100.000 (99.307) +2022-11-14 14:48:44,487 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0735) Prec@1 89.000 (88.092) Prec@5 99.000 (99.303) +2022-11-14 14:48:44,501 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0735) Prec@1 89.000 (88.104) Prec@5 99.000 (99.299) +2022-11-14 14:48:44,515 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0738) Prec@1 84.000 (88.051) Prec@5 97.000 (99.269) +2022-11-14 14:48:44,528 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0739) Prec@1 87.000 (88.038) Prec@5 100.000 (99.278) +2022-11-14 14:48:44,542 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0740) Prec@1 85.000 (88.000) Prec@5 100.000 (99.287) +2022-11-14 14:48:44,555 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0739) Prec@1 89.000 (88.012) Prec@5 98.000 (99.272) +2022-11-14 14:48:44,567 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0741) Prec@1 86.000 (87.988) Prec@5 100.000 (99.280) +2022-11-14 14:48:44,581 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0745) Prec@1 84.000 (87.940) Prec@5 100.000 (99.289) +2022-11-14 14:48:44,593 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0744) Prec@1 88.000 (87.940) Prec@5 99.000 (99.286) +2022-11-14 14:48:44,605 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0745) Prec@1 88.000 (87.941) Prec@5 100.000 (99.294) +2022-11-14 14:48:44,618 Test: [85/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0748) Prec@1 84.000 (87.895) Prec@5 99.000 (99.291) +2022-11-14 14:48:44,632 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0749) Prec@1 85.000 (87.862) Prec@5 100.000 (99.299) +2022-11-14 14:48:44,645 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0750) Prec@1 87.000 (87.852) Prec@5 98.000 (99.284) +2022-11-14 14:48:44,658 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0749) Prec@1 89.000 (87.865) Prec@5 100.000 (99.292) +2022-11-14 14:48:44,671 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0750) Prec@1 87.000 (87.856) Prec@5 99.000 (99.289) +2022-11-14 14:48:44,683 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0748) Prec@1 91.000 (87.890) Prec@5 100.000 (99.297) +2022-11-14 14:48:44,695 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0744) Prec@1 93.000 (87.946) Prec@5 99.000 (99.293) +2022-11-14 14:48:44,708 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0745) Prec@1 86.000 (87.925) Prec@5 99.000 (99.290) +2022-11-14 14:48:44,721 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0746) Prec@1 88.000 (87.926) Prec@5 100.000 (99.298) +2022-11-14 14:48:44,733 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0748) Prec@1 85.000 (87.895) Prec@5 98.000 (99.284) +2022-11-14 14:48:44,745 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0746) Prec@1 91.000 (87.927) Prec@5 99.000 (99.281) +2022-11-14 14:48:44,758 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0745) Prec@1 90.000 (87.948) Prec@5 99.000 (99.278) +2022-11-14 14:48:44,770 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0745) Prec@1 89.000 (87.959) Prec@5 99.000 (99.276) +2022-11-14 14:48:44,782 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0747) Prec@1 84.000 (87.919) Prec@5 100.000 (99.283) +2022-11-14 14:48:44,796 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0749) Prec@1 87.000 (87.910) Prec@5 99.000 (99.280) +2022-11-14 14:48:44,859 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:48:45,180 Epoch: [258][0/500] Time 0.025 (0.025) Data 0.228 (0.228) Loss 0.0127 (0.0127) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:45,388 Epoch: [258][10/500] Time 0.017 (0.019) Data 0.002 (0.022) Loss 0.0590 (0.0358) Prec@1 91.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:48:45,635 Epoch: [258][20/500] Time 0.017 (0.020) Data 0.002 (0.013) Loss 0.0211 (0.0309) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 14:48:46,026 Epoch: [258][30/500] Time 0.047 (0.023) Data 0.002 (0.009) Loss 0.0583 (0.0378) Prec@1 91.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 14:48:46,582 Epoch: [258][40/500] Time 0.102 (0.029) Data 0.002 (0.007) Loss 0.0473 (0.0397) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:47,123 Epoch: [258][50/500] Time 0.056 (0.033) Data 0.002 (0.006) Loss 0.0168 (0.0359) Prec@1 99.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 14:48:47,668 Epoch: [258][60/500] Time 0.041 (0.036) Data 0.002 (0.006) Loss 0.0157 (0.0330) Prec@1 99.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 14:48:48,212 Epoch: [258][70/500] Time 0.043 (0.038) Data 0.002 (0.005) Loss 0.0392 (0.0338) Prec@1 92.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:48:48,751 Epoch: [258][80/500] Time 0.044 (0.039) Data 0.002 (0.005) Loss 0.0278 (0.0331) Prec@1 97.000 (95.222) Prec@5 100.000 (100.000) +2022-11-14 14:48:49,301 Epoch: [258][90/500] Time 0.043 (0.040) Data 0.002 (0.004) Loss 0.0376 (0.0335) Prec@1 94.000 (95.100) Prec@5 99.000 (99.900) +2022-11-14 14:48:49,845 Epoch: [258][100/500] Time 0.043 (0.041) Data 0.002 (0.004) Loss 0.0482 (0.0349) Prec@1 91.000 (94.727) Prec@5 100.000 (99.909) +2022-11-14 14:48:50,388 Epoch: [258][110/500] Time 0.044 (0.042) Data 0.002 (0.004) Loss 0.0131 (0.0331) Prec@1 99.000 (95.083) Prec@5 100.000 (99.917) +2022-11-14 14:48:51,047 Epoch: [258][120/500] Time 0.111 (0.043) Data 0.002 (0.004) Loss 0.0446 (0.0340) Prec@1 93.000 (94.923) Prec@5 100.000 (99.923) +2022-11-14 14:48:51,544 Epoch: [258][130/500] Time 0.045 (0.043) Data 0.002 (0.004) Loss 0.0270 (0.0335) Prec@1 95.000 (94.929) Prec@5 100.000 (99.929) +2022-11-14 14:48:52,026 Epoch: [258][140/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0411 (0.0340) Prec@1 91.000 (94.667) Prec@5 99.000 (99.867) +2022-11-14 14:48:52,508 Epoch: [258][150/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0468 (0.0348) Prec@1 93.000 (94.562) Prec@5 100.000 (99.875) +2022-11-14 14:48:53,059 Epoch: [258][160/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0394 (0.0350) Prec@1 95.000 (94.588) Prec@5 99.000 (99.824) +2022-11-14 14:48:53,603 Epoch: [258][170/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0329 (0.0349) Prec@1 95.000 (94.611) Prec@5 99.000 (99.778) +2022-11-14 14:48:54,195 Epoch: [258][180/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0263 (0.0345) Prec@1 95.000 (94.632) Prec@5 100.000 (99.789) +2022-11-14 14:48:54,548 Epoch: [258][190/500] Time 0.029 (0.044) Data 0.002 (0.003) Loss 0.0275 (0.0341) Prec@1 96.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 14:48:54,911 Epoch: [258][200/500] Time 0.027 (0.043) Data 0.002 (0.003) Loss 0.0424 (0.0345) Prec@1 93.000 (94.619) Prec@5 100.000 (99.810) +2022-11-14 14:48:55,351 Epoch: [258][210/500] Time 0.036 (0.043) Data 0.002 (0.003) Loss 0.0316 (0.0344) Prec@1 94.000 (94.591) Prec@5 100.000 (99.818) +2022-11-14 14:48:55,677 Epoch: [258][220/500] Time 0.041 (0.042) Data 0.003 (0.003) Loss 0.0345 (0.0344) Prec@1 94.000 (94.565) Prec@5 100.000 (99.826) +2022-11-14 14:48:56,002 Epoch: [258][230/500] Time 0.029 (0.042) Data 0.001 (0.003) Loss 0.0173 (0.0337) Prec@1 98.000 (94.708) Prec@5 100.000 (99.833) +2022-11-14 14:48:56,370 Epoch: [258][240/500] Time 0.027 (0.041) Data 0.001 (0.003) Loss 0.0268 (0.0334) Prec@1 95.000 (94.720) Prec@5 100.000 (99.840) +2022-11-14 14:48:56,747 Epoch: [258][250/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0348 (0.0334) Prec@1 95.000 (94.731) Prec@5 99.000 (99.808) +2022-11-14 14:48:57,123 Epoch: [258][260/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0383 (0.0336) Prec@1 94.000 (94.704) Prec@5 100.000 (99.815) +2022-11-14 14:48:57,450 Epoch: [258][270/500] Time 0.033 (0.040) Data 0.002 (0.003) Loss 0.0568 (0.0345) Prec@1 90.000 (94.536) Prec@5 100.000 (99.821) +2022-11-14 14:48:57,787 Epoch: [258][280/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0152 (0.0338) Prec@1 98.000 (94.655) Prec@5 100.000 (99.828) +2022-11-14 14:48:58,111 Epoch: [258][290/500] Time 0.030 (0.039) Data 0.001 (0.003) Loss 0.0464 (0.0342) Prec@1 92.000 (94.567) Prec@5 99.000 (99.800) +2022-11-14 14:48:58,449 Epoch: [258][300/500] Time 0.031 (0.039) Data 0.002 (0.003) Loss 0.0503 (0.0347) Prec@1 92.000 (94.484) Prec@5 100.000 (99.806) +2022-11-14 14:48:58,806 Epoch: [258][310/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0432 (0.0350) Prec@1 94.000 (94.469) Prec@5 99.000 (99.781) +2022-11-14 14:48:59,142 Epoch: [258][320/500] Time 0.032 (0.039) Data 0.002 (0.003) Loss 0.0295 (0.0348) Prec@1 94.000 (94.455) Prec@5 99.000 (99.758) +2022-11-14 14:48:59,469 Epoch: [258][330/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0316 (0.0347) Prec@1 95.000 (94.471) Prec@5 100.000 (99.765) +2022-11-14 14:48:59,798 Epoch: [258][340/500] Time 0.033 (0.038) Data 0.001 (0.003) Loss 0.0425 (0.0350) Prec@1 94.000 (94.457) Prec@5 100.000 (99.771) +2022-11-14 14:49:00,132 Epoch: [258][350/500] Time 0.032 (0.038) Data 0.002 (0.002) Loss 0.0383 (0.0350) Prec@1 93.000 (94.417) Prec@5 100.000 (99.778) +2022-11-14 14:49:00,560 Epoch: [258][360/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0411 (0.0352) Prec@1 94.000 (94.405) Prec@5 100.000 (99.784) +2022-11-14 14:49:00,867 Epoch: [258][370/500] Time 0.029 (0.038) Data 0.002 (0.002) Loss 0.0417 (0.0354) Prec@1 94.000 (94.395) Prec@5 100.000 (99.789) +2022-11-14 14:49:01,202 Epoch: [258][380/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0475 (0.0357) Prec@1 94.000 (94.385) Prec@5 100.000 (99.795) +2022-11-14 14:49:01,538 Epoch: [258][390/500] Time 0.029 (0.037) Data 0.002 (0.002) Loss 0.0465 (0.0360) Prec@1 91.000 (94.300) Prec@5 99.000 (99.775) +2022-11-14 14:49:01,873 Epoch: [258][400/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0272 (0.0357) Prec@1 97.000 (94.366) Prec@5 100.000 (99.780) +2022-11-14 14:49:02,202 Epoch: [258][410/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0445 (0.0360) Prec@1 93.000 (94.333) Prec@5 100.000 (99.786) +2022-11-14 14:49:02,533 Epoch: [258][420/500] Time 0.031 (0.037) Data 0.002 (0.002) Loss 0.0110 (0.0354) Prec@1 99.000 (94.442) Prec@5 100.000 (99.791) +2022-11-14 14:49:02,869 Epoch: [258][430/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.0407 (0.0355) Prec@1 94.000 (94.432) Prec@5 100.000 (99.795) +2022-11-14 14:49:03,214 Epoch: [258][440/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0219 (0.0352) Prec@1 96.000 (94.467) Prec@5 100.000 (99.800) +2022-11-14 14:49:03,554 Epoch: [258][450/500] Time 0.032 (0.036) Data 0.002 (0.002) Loss 0.0246 (0.0350) Prec@1 96.000 (94.500) Prec@5 100.000 (99.804) +2022-11-14 14:49:03,905 Epoch: [258][460/500] Time 0.035 (0.036) Data 0.002 (0.002) Loss 0.0481 (0.0352) Prec@1 92.000 (94.447) Prec@5 100.000 (99.809) +2022-11-14 14:49:04,242 Epoch: [258][470/500] Time 0.030 (0.036) Data 0.002 (0.002) Loss 0.0372 (0.0353) Prec@1 94.000 (94.438) Prec@5 100.000 (99.812) +2022-11-14 14:49:04,920 Epoch: [258][480/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0228 (0.0350) Prec@1 97.000 (94.490) Prec@5 100.000 (99.816) +2022-11-14 14:49:05,543 Epoch: [258][490/500] Time 0.089 (0.037) Data 0.002 (0.002) Loss 0.0257 (0.0348) Prec@1 95.000 (94.500) Prec@5 100.000 (99.820) +2022-11-14 14:49:06,064 Epoch: [258][499/500] Time 0.047 (0.037) Data 0.002 (0.002) Loss 0.0348 (0.0348) Prec@1 94.000 (94.490) Prec@5 100.000 (99.824) +2022-11-14 14:49:06,359 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0705 (0.0705) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:06,370 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0753) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:49:06,379 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0729) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:06,388 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0728) Prec@1 88.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 14:49:06,397 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0710) Prec@1 90.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 14:49:06,410 Test: [5/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0435 (0.0665) Prec@1 93.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 14:49:06,422 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0638) Prec@1 93.000 (89.714) Prec@5 100.000 (99.857) +2022-11-14 14:49:06,433 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0653) Prec@1 88.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 14:49:06,443 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0670) Prec@1 88.000 (89.333) Prec@5 100.000 (99.778) +2022-11-14 14:49:06,458 Test: [9/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0672) Prec@1 89.000 (89.300) Prec@5 98.000 (99.600) +2022-11-14 14:49:06,471 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0651) Prec@1 92.000 (89.545) Prec@5 100.000 (99.636) +2022-11-14 14:49:06,484 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0673) Prec@1 86.000 (89.250) Prec@5 100.000 (99.667) +2022-11-14 14:49:06,498 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0661) Prec@1 92.000 (89.462) Prec@5 100.000 (99.692) +2022-11-14 14:49:06,512 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0673) Prec@1 85.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 14:49:06,526 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0669) Prec@1 91.000 (89.267) Prec@5 100.000 (99.733) +2022-11-14 14:49:06,539 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0669) Prec@1 90.000 (89.312) Prec@5 100.000 (99.750) +2022-11-14 14:49:06,556 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0446 (0.0656) Prec@1 94.000 (89.588) Prec@5 99.000 (99.706) +2022-11-14 14:49:06,572 Test: [17/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.1135 (0.0683) Prec@1 83.000 (89.222) Prec@5 99.000 (99.667) +2022-11-14 14:49:06,584 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0684) Prec@1 87.000 (89.105) Prec@5 97.000 (99.526) +2022-11-14 14:49:06,599 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.0694) Prec@1 85.000 (88.900) Prec@5 98.000 (99.450) +2022-11-14 14:49:06,612 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.0702) Prec@1 85.000 (88.714) Prec@5 100.000 (99.476) +2022-11-14 14:49:06,625 Test: [21/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0713) Prec@1 83.000 (88.455) Prec@5 99.000 (99.455) +2022-11-14 14:49:06,637 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1045 (0.0728) Prec@1 84.000 (88.261) Prec@5 97.000 (99.348) +2022-11-14 14:49:06,648 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0724) Prec@1 89.000 (88.292) Prec@5 100.000 (99.375) +2022-11-14 14:49:06,657 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0726) Prec@1 88.000 (88.280) Prec@5 100.000 (99.400) +2022-11-14 14:49:06,670 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0732) Prec@1 88.000 (88.269) Prec@5 98.000 (99.346) +2022-11-14 14:49:06,682 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0729) Prec@1 89.000 (88.296) Prec@5 99.000 (99.333) +2022-11-14 14:49:06,693 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0555 (0.0723) Prec@1 91.000 (88.393) Prec@5 100.000 (99.357) +2022-11-14 14:49:06,704 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0720) Prec@1 91.000 (88.483) Prec@5 98.000 (99.310) +2022-11-14 14:49:06,717 Test: [29/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0716) Prec@1 90.000 (88.533) Prec@5 99.000 (99.300) +2022-11-14 14:49:06,733 Test: [30/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0611 (0.0713) Prec@1 90.000 (88.581) Prec@5 100.000 (99.323) +2022-11-14 14:49:06,746 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0890 (0.0718) Prec@1 87.000 (88.531) Prec@5 99.000 (99.312) +2022-11-14 14:49:06,758 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0719) Prec@1 86.000 (88.455) Prec@5 100.000 (99.333) +2022-11-14 14:49:06,771 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0986 (0.0726) Prec@1 85.000 (88.353) Prec@5 99.000 (99.324) +2022-11-14 14:49:06,788 Test: [34/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0730) Prec@1 88.000 (88.343) Prec@5 97.000 (99.257) +2022-11-14 14:49:06,802 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0569 (0.0726) Prec@1 91.000 (88.417) Prec@5 100.000 (99.278) +2022-11-14 14:49:06,821 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0724) Prec@1 90.000 (88.459) Prec@5 97.000 (99.216) +2022-11-14 14:49:06,838 Test: [37/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0726) Prec@1 86.000 (88.395) Prec@5 100.000 (99.237) +2022-11-14 14:49:06,856 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0552 (0.0722) Prec@1 93.000 (88.513) Prec@5 98.000 (99.205) +2022-11-14 14:49:06,872 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0722) Prec@1 88.000 (88.500) Prec@5 99.000 (99.200) +2022-11-14 14:49:06,889 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0725) Prec@1 84.000 (88.390) Prec@5 99.000 (99.195) +2022-11-14 14:49:06,906 Test: [41/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0724) Prec@1 88.000 (88.381) Prec@5 98.000 (99.167) +2022-11-14 14:49:06,922 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0434 (0.0718) Prec@1 93.000 (88.488) Prec@5 100.000 (99.186) +2022-11-14 14:49:06,938 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0716) Prec@1 90.000 (88.523) Prec@5 97.000 (99.136) +2022-11-14 14:49:06,954 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0716) Prec@1 87.000 (88.489) Prec@5 99.000 (99.133) +2022-11-14 14:49:06,969 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1011 (0.0722) Prec@1 83.000 (88.370) Prec@5 100.000 (99.152) +2022-11-14 14:49:06,984 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0721) Prec@1 88.000 (88.362) Prec@5 100.000 (99.170) +2022-11-14 14:49:06,998 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0824 (0.0723) Prec@1 87.000 (88.333) Prec@5 99.000 (99.167) +2022-11-14 14:49:07,011 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0720) Prec@1 91.000 (88.388) Prec@5 99.000 (99.163) +2022-11-14 14:49:07,027 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.0728) Prec@1 81.000 (88.240) Prec@5 99.000 (99.160) +2022-11-14 14:49:07,041 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0728) Prec@1 90.000 (88.275) Prec@5 99.000 (99.157) +2022-11-14 14:49:07,053 Test: [51/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1102 (0.0735) Prec@1 83.000 (88.173) Prec@5 100.000 (99.173) +2022-11-14 14:49:07,063 Test: [52/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0734) Prec@1 88.000 (88.170) Prec@5 98.000 (99.151) +2022-11-14 14:49:07,075 Test: [53/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0735) Prec@1 86.000 (88.130) Prec@5 100.000 (99.167) +2022-11-14 14:49:07,087 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0843 (0.0737) Prec@1 84.000 (88.055) Prec@5 100.000 (99.182) +2022-11-14 14:49:07,098 Test: [55/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0918 (0.0740) Prec@1 86.000 (88.018) Prec@5 99.000 (99.179) +2022-11-14 14:49:07,110 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0673 (0.0739) Prec@1 89.000 (88.035) Prec@5 100.000 (99.193) +2022-11-14 14:49:07,122 Test: [57/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0736) Prec@1 90.000 (88.069) Prec@5 100.000 (99.207) +2022-11-14 14:49:07,134 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0739) Prec@1 85.000 (88.017) Prec@5 100.000 (99.220) +2022-11-14 14:49:07,146 Test: [59/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0921 (0.0742) Prec@1 83.000 (87.933) Prec@5 100.000 (99.233) +2022-11-14 14:49:07,160 Test: [60/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0743) Prec@1 86.000 (87.902) Prec@5 100.000 (99.246) +2022-11-14 14:49:07,173 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0744) Prec@1 87.000 (87.887) Prec@5 100.000 (99.258) +2022-11-14 14:49:07,185 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0745) Prec@1 85.000 (87.841) Prec@5 100.000 (99.270) +2022-11-14 14:49:07,196 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0373 (0.0739) Prec@1 94.000 (87.938) Prec@5 100.000 (99.281) +2022-11-14 14:49:07,207 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0742) Prec@1 84.000 (87.877) Prec@5 100.000 (99.292) +2022-11-14 14:49:07,218 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0743) Prec@1 89.000 (87.894) Prec@5 99.000 (99.288) +2022-11-14 14:49:07,230 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0740) Prec@1 94.000 (87.985) Prec@5 99.000 (99.284) +2022-11-14 14:49:07,242 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0743) Prec@1 85.000 (87.941) Prec@5 100.000 (99.294) +2022-11-14 14:49:07,255 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0742) Prec@1 87.000 (87.928) Prec@5 99.000 (99.290) +2022-11-14 14:49:07,266 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0743) Prec@1 86.000 (87.900) Prec@5 99.000 (99.286) +2022-11-14 14:49:07,277 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0744) Prec@1 88.000 (87.901) Prec@5 100.000 (99.296) +2022-11-14 14:49:07,289 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 89.000 (87.917) Prec@5 100.000 (99.306) +2022-11-14 14:49:07,301 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0743) Prec@1 89.000 (87.932) Prec@5 100.000 (99.315) +2022-11-14 14:49:07,312 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0738) Prec@1 93.000 (88.000) Prec@5 100.000 (99.324) +2022-11-14 14:49:07,324 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.0744) Prec@1 80.000 (87.893) Prec@5 100.000 (99.333) +2022-11-14 14:49:07,336 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0740) Prec@1 93.000 (87.961) Prec@5 99.000 (99.329) +2022-11-14 14:49:07,346 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0740) Prec@1 89.000 (87.974) Prec@5 98.000 (99.312) +2022-11-14 14:49:07,358 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0741) Prec@1 87.000 (87.962) Prec@5 99.000 (99.308) +2022-11-14 14:49:07,370 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0739) Prec@1 89.000 (87.975) Prec@5 99.000 (99.304) +2022-11-14 14:49:07,383 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0741) Prec@1 84.000 (87.925) Prec@5 100.000 (99.312) +2022-11-14 14:49:07,395 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0741) Prec@1 86.000 (87.901) Prec@5 99.000 (99.309) +2022-11-14 14:49:07,408 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0743) Prec@1 86.000 (87.878) Prec@5 100.000 (99.317) +2022-11-14 14:49:07,419 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0746) Prec@1 83.000 (87.819) Prec@5 99.000 (99.313) +2022-11-14 14:49:07,433 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0745) Prec@1 88.000 (87.821) Prec@5 99.000 (99.310) +2022-11-14 14:49:07,445 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0747) Prec@1 88.000 (87.824) Prec@5 99.000 (99.306) +2022-11-14 14:49:07,458 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0749) Prec@1 84.000 (87.779) Prec@5 100.000 (99.314) +2022-11-14 14:49:07,470 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0753) Prec@1 83.000 (87.724) Prec@5 99.000 (99.310) +2022-11-14 14:49:07,483 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0754) Prec@1 87.000 (87.716) Prec@5 99.000 (99.307) +2022-11-14 14:49:07,494 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0751) Prec@1 90.000 (87.742) Prec@5 99.000 (99.303) +2022-11-14 14:49:07,506 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0750) Prec@1 89.000 (87.756) Prec@5 99.000 (99.300) +2022-11-14 14:49:07,518 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0750) Prec@1 88.000 (87.758) Prec@5 100.000 (99.308) +2022-11-14 14:49:07,530 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0746) Prec@1 93.000 (87.815) Prec@5 99.000 (99.304) +2022-11-14 14:49:07,541 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0747) Prec@1 85.000 (87.785) Prec@5 100.000 (99.312) +2022-11-14 14:49:07,554 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0747) Prec@1 88.000 (87.787) Prec@5 100.000 (99.319) +2022-11-14 14:49:07,565 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0747) Prec@1 87.000 (87.779) Prec@5 98.000 (99.305) +2022-11-14 14:49:07,576 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0748) Prec@1 88.000 (87.781) Prec@5 98.000 (99.292) +2022-11-14 14:49:07,587 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0745) Prec@1 93.000 (87.835) Prec@5 99.000 (99.289) +2022-11-14 14:49:07,599 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0747) Prec@1 84.000 (87.796) Prec@5 98.000 (99.276) +2022-11-14 14:49:07,610 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0749) Prec@1 87.000 (87.788) Prec@5 99.000 (99.273) +2022-11-14 14:49:07,623 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0749) Prec@1 90.000 (87.810) Prec@5 99.000 (99.270) +2022-11-14 14:49:07,679 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:49:08,002 Epoch: [259][0/500] Time 0.025 (0.025) Data 0.235 (0.235) Loss 0.0407 (0.0407) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:49:08,221 Epoch: [259][10/500] Time 0.019 (0.020) Data 0.002 (0.023) Loss 0.0433 (0.0420) Prec@1 94.000 (93.500) Prec@5 99.000 (99.000) +2022-11-14 14:49:08,454 Epoch: [259][20/500] Time 0.019 (0.020) Data 0.002 (0.013) Loss 0.0243 (0.0361) Prec@1 96.000 (94.333) Prec@5 100.000 (99.333) +2022-11-14 14:49:08,769 Epoch: [259][30/500] Time 0.040 (0.023) Data 0.002 (0.009) Loss 0.0253 (0.0334) Prec@1 95.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 14:49:09,148 Epoch: [259][40/500] Time 0.040 (0.026) Data 0.002 (0.007) Loss 0.0313 (0.0330) Prec@1 94.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 14:49:09,606 Epoch: [259][50/500] Time 0.052 (0.028) Data 0.002 (0.006) Loss 0.0542 (0.0365) Prec@1 91.000 (93.833) Prec@5 100.000 (99.667) +2022-11-14 14:49:10,020 Epoch: [259][60/500] Time 0.070 (0.030) Data 0.002 (0.006) Loss 0.0461 (0.0379) Prec@1 90.000 (93.286) Prec@5 99.000 (99.571) +2022-11-14 14:49:10,377 Epoch: [259][70/500] Time 0.040 (0.030) Data 0.002 (0.005) Loss 0.0316 (0.0371) Prec@1 95.000 (93.500) Prec@5 98.000 (99.375) +2022-11-14 14:49:10,782 Epoch: [259][80/500] Time 0.034 (0.031) Data 0.002 (0.005) Loss 0.0586 (0.0395) Prec@1 91.000 (93.222) Prec@5 100.000 (99.444) +2022-11-14 14:49:11,191 Epoch: [259][90/500] Time 0.031 (0.032) Data 0.002 (0.004) Loss 0.0341 (0.0390) Prec@1 94.000 (93.300) Prec@5 99.000 (99.400) +2022-11-14 14:49:11,604 Epoch: [259][100/500] Time 0.025 (0.032) Data 0.002 (0.004) Loss 0.0413 (0.0392) Prec@1 95.000 (93.455) Prec@5 100.000 (99.455) +2022-11-14 14:49:12,031 Epoch: [259][110/500] Time 0.056 (0.033) Data 0.002 (0.004) Loss 0.0365 (0.0390) Prec@1 93.000 (93.417) Prec@5 100.000 (99.500) +2022-11-14 14:49:12,413 Epoch: [259][120/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0318 (0.0384) Prec@1 95.000 (93.538) Prec@5 100.000 (99.538) +2022-11-14 14:49:12,802 Epoch: [259][130/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0410 (0.0386) Prec@1 95.000 (93.643) Prec@5 100.000 (99.571) +2022-11-14 14:49:13,209 Epoch: [259][140/500] Time 0.033 (0.033) Data 0.002 (0.004) Loss 0.0385 (0.0386) Prec@1 94.000 (93.667) Prec@5 99.000 (99.533) +2022-11-14 14:49:13,628 Epoch: [259][150/500] Time 0.030 (0.033) Data 0.002 (0.003) Loss 0.0568 (0.0397) Prec@1 91.000 (93.500) Prec@5 100.000 (99.562) +2022-11-14 14:49:14,050 Epoch: [259][160/500] Time 0.040 (0.034) Data 0.002 (0.003) Loss 0.0325 (0.0393) Prec@1 95.000 (93.588) Prec@5 100.000 (99.588) +2022-11-14 14:49:14,455 Epoch: [259][170/500] Time 0.045 (0.034) Data 0.001 (0.003) Loss 0.0462 (0.0397) Prec@1 93.000 (93.556) Prec@5 100.000 (99.611) +2022-11-14 14:49:14,851 Epoch: [259][180/500] Time 0.047 (0.034) Data 0.002 (0.003) Loss 0.0327 (0.0393) Prec@1 95.000 (93.632) Prec@5 100.000 (99.632) +2022-11-14 14:49:15,334 Epoch: [259][190/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0566 (0.0402) Prec@1 91.000 (93.500) Prec@5 100.000 (99.650) +2022-11-14 14:49:15,815 Epoch: [259][200/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.0285 (0.0396) Prec@1 95.000 (93.571) Prec@5 100.000 (99.667) +2022-11-14 14:49:16,316 Epoch: [259][210/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0305 (0.0392) Prec@1 95.000 (93.636) Prec@5 100.000 (99.682) +2022-11-14 14:49:16,720 Epoch: [259][220/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0340 (0.0390) Prec@1 95.000 (93.696) Prec@5 100.000 (99.696) +2022-11-14 14:49:17,202 Epoch: [259][230/500] Time 0.043 (0.035) Data 0.003 (0.003) Loss 0.0494 (0.0394) Prec@1 92.000 (93.625) Prec@5 100.000 (99.708) +2022-11-14 14:49:17,680 Epoch: [259][240/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.0532 (0.0400) Prec@1 91.000 (93.520) Prec@5 100.000 (99.720) +2022-11-14 14:49:18,160 Epoch: [259][250/500] Time 0.051 (0.036) Data 0.002 (0.003) Loss 0.0174 (0.0391) Prec@1 97.000 (93.654) Prec@5 100.000 (99.731) +2022-11-14 14:49:18,678 Epoch: [259][260/500] Time 0.057 (0.036) Data 0.002 (0.003) Loss 0.0344 (0.0389) Prec@1 95.000 (93.704) Prec@5 100.000 (99.741) +2022-11-14 14:49:19,460 Epoch: [259][270/500] Time 0.073 (0.038) Data 0.002 (0.003) Loss 0.0395 (0.0389) Prec@1 94.000 (93.714) Prec@5 99.000 (99.714) +2022-11-14 14:49:20,090 Epoch: [259][280/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0133 (0.0381) Prec@1 99.000 (93.897) Prec@5 100.000 (99.724) +2022-11-14 14:49:20,646 Epoch: [259][290/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0394 (0.0381) Prec@1 95.000 (93.933) Prec@5 100.000 (99.733) +2022-11-14 14:49:21,190 Epoch: [259][300/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0292 (0.0378) Prec@1 95.000 (93.968) Prec@5 100.000 (99.742) +2022-11-14 14:49:21,733 Epoch: [259][310/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0442 (0.0380) Prec@1 94.000 (93.969) Prec@5 100.000 (99.750) +2022-11-14 14:49:22,274 Epoch: [259][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0075 (0.0371) Prec@1 100.000 (94.152) Prec@5 100.000 (99.758) +2022-11-14 14:49:22,819 Epoch: [259][330/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0503 (0.0375) Prec@1 89.000 (94.000) Prec@5 100.000 (99.765) +2022-11-14 14:49:23,592 Epoch: [259][340/500] Time 0.085 (0.041) Data 0.002 (0.003) Loss 0.0285 (0.0372) Prec@1 95.000 (94.029) Prec@5 100.000 (99.771) +2022-11-14 14:49:24,131 Epoch: [259][350/500] Time 0.084 (0.041) Data 0.002 (0.003) Loss 0.0149 (0.0366) Prec@1 98.000 (94.139) Prec@5 100.000 (99.778) +2022-11-14 14:49:24,671 Epoch: [259][360/500] Time 0.037 (0.041) Data 0.002 (0.003) Loss 0.0555 (0.0371) Prec@1 92.000 (94.081) Prec@5 100.000 (99.784) +2022-11-14 14:49:25,208 Epoch: [259][370/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0250 (0.0368) Prec@1 97.000 (94.158) Prec@5 100.000 (99.789) +2022-11-14 14:49:25,680 Epoch: [259][380/500] Time 0.043 (0.042) Data 0.001 (0.003) Loss 0.0326 (0.0367) Prec@1 94.000 (94.154) Prec@5 99.000 (99.769) +2022-11-14 14:49:26,178 Epoch: [259][390/500] Time 0.052 (0.042) Data 0.002 (0.003) Loss 0.0301 (0.0365) Prec@1 94.000 (94.150) Prec@5 100.000 (99.775) +2022-11-14 14:49:26,662 Epoch: [259][400/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0588 (0.0371) Prec@1 91.000 (94.073) Prec@5 98.000 (99.732) +2022-11-14 14:49:27,125 Epoch: [259][410/500] Time 0.042 (0.042) Data 0.002 (0.002) Loss 0.0351 (0.0370) Prec@1 93.000 (94.048) Prec@5 100.000 (99.738) +2022-11-14 14:49:27,606 Epoch: [259][420/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0380 (0.0370) Prec@1 94.000 (94.047) Prec@5 100.000 (99.744) +2022-11-14 14:49:28,155 Epoch: [259][430/500] Time 0.042 (0.042) Data 0.001 (0.002) Loss 0.0390 (0.0371) Prec@1 94.000 (94.045) Prec@5 100.000 (99.750) +2022-11-14 14:49:28,691 Epoch: [259][440/500] Time 0.096 (0.042) Data 0.002 (0.002) Loss 0.0566 (0.0375) Prec@1 91.000 (93.978) Prec@5 100.000 (99.756) +2022-11-14 14:49:29,196 Epoch: [259][450/500] Time 0.046 (0.042) Data 0.002 (0.002) Loss 0.0468 (0.0377) Prec@1 93.000 (93.957) Prec@5 100.000 (99.761) +2022-11-14 14:49:29,687 Epoch: [259][460/500] Time 0.052 (0.042) Data 0.002 (0.002) Loss 0.0433 (0.0378) Prec@1 93.000 (93.936) Prec@5 99.000 (99.745) +2022-11-14 14:49:30,192 Epoch: [259][470/500] Time 0.053 (0.042) Data 0.002 (0.002) Loss 0.0227 (0.0375) Prec@1 96.000 (93.979) Prec@5 100.000 (99.750) +2022-11-14 14:49:30,693 Epoch: [259][480/500] Time 0.051 (0.042) Data 0.002 (0.002) Loss 0.0121 (0.0370) Prec@1 98.000 (94.061) Prec@5 100.000 (99.755) +2022-11-14 14:49:31,169 Epoch: [259][490/500] Time 0.044 (0.042) Data 0.001 (0.002) Loss 0.0363 (0.0370) Prec@1 94.000 (94.060) Prec@5 100.000 (99.760) +2022-11-14 14:49:31,590 Epoch: [259][499/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0488 (0.0372) Prec@1 94.000 (94.059) Prec@5 99.000 (99.745) +2022-11-14 14:49:31,872 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0669 (0.0669) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:31,882 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0561 (0.0615) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 14:49:31,891 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0659) Prec@1 89.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 14:49:31,904 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0698) Prec@1 86.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:49:31,913 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0731) Prec@1 88.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 14:49:31,922 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0319 (0.0662) Prec@1 95.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:49:31,930 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0645) Prec@1 92.000 (89.857) Prec@5 100.000 (99.571) +2022-11-14 14:49:31,942 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0667) Prec@1 85.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 14:49:31,951 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0689) Prec@1 88.000 (89.111) Prec@5 99.000 (99.444) +2022-11-14 14:49:31,961 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0696) Prec@1 90.000 (89.200) Prec@5 98.000 (99.300) +2022-11-14 14:49:31,971 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0690) Prec@1 90.000 (89.273) Prec@5 99.000 (99.273) +2022-11-14 14:49:31,982 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0697) Prec@1 89.000 (89.250) Prec@5 100.000 (99.333) +2022-11-14 14:49:31,991 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0679) Prec@1 92.000 (89.462) Prec@5 100.000 (99.385) +2022-11-14 14:49:32,002 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0683) Prec@1 90.000 (89.500) Prec@5 98.000 (99.286) +2022-11-14 14:49:32,012 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0685) Prec@1 91.000 (89.600) Prec@5 99.000 (99.267) +2022-11-14 14:49:32,024 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0688) Prec@1 88.000 (89.500) Prec@5 100.000 (99.312) +2022-11-14 14:49:32,034 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0324 (0.0666) Prec@1 95.000 (89.824) Prec@5 98.000 (99.235) +2022-11-14 14:49:32,045 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1288 (0.0701) Prec@1 79.000 (89.222) Prec@5 99.000 (99.222) +2022-11-14 14:49:32,058 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0707) Prec@1 86.000 (89.053) Prec@5 99.000 (99.211) +2022-11-14 14:49:32,069 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0720) Prec@1 84.000 (88.800) Prec@5 99.000 (99.200) +2022-11-14 14:49:32,081 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0722) Prec@1 87.000 (88.714) Prec@5 99.000 (99.190) +2022-11-14 14:49:32,092 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0727) Prec@1 84.000 (88.500) Prec@5 100.000 (99.227) +2022-11-14 14:49:32,101 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0739) Prec@1 85.000 (88.348) Prec@5 98.000 (99.174) +2022-11-14 14:49:32,110 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0737) Prec@1 89.000 (88.375) Prec@5 100.000 (99.208) +2022-11-14 14:49:32,120 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0744) Prec@1 86.000 (88.280) Prec@5 100.000 (99.240) +2022-11-14 14:49:32,132 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0752) Prec@1 84.000 (88.115) Prec@5 99.000 (99.231) +2022-11-14 14:49:32,143 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0742) Prec@1 92.000 (88.259) Prec@5 100.000 (99.259) +2022-11-14 14:49:32,154 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0735) Prec@1 92.000 (88.393) Prec@5 99.000 (99.250) +2022-11-14 14:49:32,166 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0728) Prec@1 90.000 (88.448) Prec@5 99.000 (99.241) +2022-11-14 14:49:32,177 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0725) Prec@1 89.000 (88.467) Prec@5 100.000 (99.267) +2022-11-14 14:49:32,188 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0725) Prec@1 89.000 (88.484) Prec@5 100.000 (99.290) +2022-11-14 14:49:32,197 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0727) Prec@1 87.000 (88.438) Prec@5 100.000 (99.312) +2022-11-14 14:49:32,207 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0735) Prec@1 83.000 (88.273) Prec@5 98.000 (99.273) +2022-11-14 14:49:32,219 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0739) Prec@1 86.000 (88.206) Prec@5 99.000 (99.265) +2022-11-14 14:49:32,229 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0734) Prec@1 92.000 (88.314) Prec@5 99.000 (99.257) +2022-11-14 14:49:32,240 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0730) Prec@1 91.000 (88.389) Prec@5 100.000 (99.278) +2022-11-14 14:49:32,248 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0734) Prec@1 86.000 (88.324) Prec@5 98.000 (99.243) +2022-11-14 14:49:32,260 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0742) Prec@1 84.000 (88.211) Prec@5 99.000 (99.237) +2022-11-14 14:49:32,271 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0737) Prec@1 92.000 (88.308) Prec@5 99.000 (99.231) +2022-11-14 14:49:32,285 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0736) Prec@1 87.000 (88.275) Prec@5 99.000 (99.225) +2022-11-14 14:49:32,298 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0736) Prec@1 89.000 (88.293) Prec@5 99.000 (99.220) +2022-11-14 14:49:32,312 Test: [41/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0736) Prec@1 88.000 (88.286) Prec@5 99.000 (99.214) +2022-11-14 14:49:32,324 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0735) Prec@1 90.000 (88.326) Prec@5 99.000 (99.209) +2022-11-14 14:49:32,336 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0738) Prec@1 85.000 (88.250) Prec@5 99.000 (99.205) +2022-11-14 14:49:32,345 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0739) Prec@1 89.000 (88.267) Prec@5 98.000 (99.178) +2022-11-14 14:49:32,359 Test: [45/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0743) Prec@1 86.000 (88.217) Prec@5 98.000 (99.152) +2022-11-14 14:49:32,372 Test: [46/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0747) Prec@1 85.000 (88.149) Prec@5 99.000 (99.149) +2022-11-14 14:49:32,382 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0753) Prec@1 85.000 (88.083) Prec@5 98.000 (99.125) +2022-11-14 14:49:32,395 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0748) Prec@1 91.000 (88.143) Prec@5 100.000 (99.143) +2022-11-14 14:49:32,406 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0754) Prec@1 85.000 (88.080) Prec@5 98.000 (99.120) +2022-11-14 14:49:32,416 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0751) Prec@1 88.000 (88.078) Prec@5 100.000 (99.137) +2022-11-14 14:49:32,427 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0750) Prec@1 88.000 (88.077) Prec@5 99.000 (99.135) +2022-11-14 14:49:32,438 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0747) Prec@1 90.000 (88.113) Prec@5 100.000 (99.151) +2022-11-14 14:49:32,449 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0748) Prec@1 88.000 (88.111) Prec@5 98.000 (99.130) +2022-11-14 14:49:32,460 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0746) Prec@1 89.000 (88.127) Prec@5 100.000 (99.145) +2022-11-14 14:49:32,469 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0747) Prec@1 90.000 (88.161) Prec@5 99.000 (99.143) +2022-11-14 14:49:32,479 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0744) Prec@1 92.000 (88.228) Prec@5 98.000 (99.123) +2022-11-14 14:49:32,491 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0744) Prec@1 89.000 (88.241) Prec@5 100.000 (99.138) +2022-11-14 14:49:32,505 Test: [58/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1252 (0.0752) Prec@1 80.000 (88.102) Prec@5 100.000 (99.153) +2022-11-14 14:49:32,517 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0755) Prec@1 82.000 (88.000) Prec@5 100.000 (99.167) +2022-11-14 14:49:32,527 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0757) Prec@1 87.000 (87.984) Prec@5 98.000 (99.148) +2022-11-14 14:49:32,538 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0757) Prec@1 89.000 (88.000) Prec@5 98.000 (99.129) +2022-11-14 14:49:32,548 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0754) Prec@1 92.000 (88.063) Prec@5 99.000 (99.127) +2022-11-14 14:49:32,559 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0382 (0.0748) Prec@1 93.000 (88.141) Prec@5 100.000 (99.141) +2022-11-14 14:49:32,569 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0751) Prec@1 85.000 (88.092) Prec@5 98.000 (99.123) +2022-11-14 14:49:32,580 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0750) Prec@1 87.000 (88.076) Prec@5 98.000 (99.106) +2022-11-14 14:49:32,591 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0745) Prec@1 93.000 (88.149) Prec@5 100.000 (99.119) +2022-11-14 14:49:32,602 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0746) Prec@1 87.000 (88.132) Prec@5 99.000 (99.118) +2022-11-14 14:49:32,614 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0746) Prec@1 89.000 (88.145) Prec@5 99.000 (99.116) +2022-11-14 14:49:32,625 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0747) Prec@1 90.000 (88.171) Prec@5 98.000 (99.100) +2022-11-14 14:49:32,637 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0752) Prec@1 85.000 (88.127) Prec@5 99.000 (99.099) +2022-11-14 14:49:32,649 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0751) Prec@1 88.000 (88.125) Prec@5 100.000 (99.111) +2022-11-14 14:49:32,660 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0747) Prec@1 93.000 (88.192) Prec@5 100.000 (99.123) +2022-11-14 14:49:32,673 Test: [73/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0743) Prec@1 92.000 (88.243) Prec@5 100.000 (99.135) +2022-11-14 14:49:32,686 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0746) Prec@1 85.000 (88.200) Prec@5 99.000 (99.133) +2022-11-14 14:49:32,697 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0744) Prec@1 91.000 (88.237) Prec@5 99.000 (99.132) +2022-11-14 14:49:32,707 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0745) Prec@1 85.000 (88.195) Prec@5 98.000 (99.117) +2022-11-14 14:49:32,720 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0747) Prec@1 85.000 (88.154) Prec@5 100.000 (99.128) +2022-11-14 14:49:32,732 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0747) Prec@1 88.000 (88.152) Prec@5 100.000 (99.139) +2022-11-14 14:49:32,742 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0747) Prec@1 87.000 (88.138) Prec@5 100.000 (99.150) +2022-11-14 14:49:32,753 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0751) Prec@1 84.000 (88.086) Prec@5 98.000 (99.136) +2022-11-14 14:49:32,766 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0753) Prec@1 86.000 (88.061) Prec@5 100.000 (99.146) +2022-11-14 14:49:32,778 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0757) Prec@1 82.000 (87.988) Prec@5 98.000 (99.133) +2022-11-14 14:49:32,790 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0755) Prec@1 89.000 (88.000) Prec@5 100.000 (99.143) +2022-11-14 14:49:32,803 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0757) Prec@1 85.000 (87.965) Prec@5 99.000 (99.141) +2022-11-14 14:49:32,816 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0760) Prec@1 82.000 (87.895) Prec@5 100.000 (99.151) +2022-11-14 14:49:32,827 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0760) Prec@1 88.000 (87.897) Prec@5 100.000 (99.161) +2022-11-14 14:49:32,836 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0761) Prec@1 83.000 (87.841) Prec@5 99.000 (99.159) +2022-11-14 14:49:32,844 Test: [88/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0762) Prec@1 89.000 (87.854) Prec@5 100.000 (99.169) +2022-11-14 14:49:32,854 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0763) Prec@1 88.000 (87.856) Prec@5 97.000 (99.144) +2022-11-14 14:49:32,867 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0761) Prec@1 92.000 (87.901) Prec@5 100.000 (99.154) +2022-11-14 14:49:32,880 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0422 (0.0757) Prec@1 94.000 (87.967) Prec@5 100.000 (99.163) +2022-11-14 14:49:32,892 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0759) Prec@1 86.000 (87.946) Prec@5 100.000 (99.172) +2022-11-14 14:49:32,903 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0759) Prec@1 87.000 (87.936) Prec@5 100.000 (99.181) +2022-11-14 14:49:32,915 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0758) Prec@1 89.000 (87.947) Prec@5 99.000 (99.179) +2022-11-14 14:49:32,927 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0759) Prec@1 88.000 (87.948) Prec@5 99.000 (99.177) +2022-11-14 14:49:32,938 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0465 (0.0756) Prec@1 93.000 (88.000) Prec@5 98.000 (99.165) +2022-11-14 14:49:32,950 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0756) Prec@1 89.000 (88.010) Prec@5 100.000 (99.173) +2022-11-14 14:49:32,962 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0759) Prec@1 83.000 (87.960) Prec@5 100.000 (99.182) +2022-11-14 14:49:32,973 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0759) Prec@1 87.000 (87.950) Prec@5 99.000 (99.180) +2022-11-14 14:49:33,032 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:49:33,345 Epoch: [260][0/500] Time 0.024 (0.024) Data 0.228 (0.228) Loss 0.0449 (0.0449) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:33,556 Epoch: [260][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0273 (0.0361) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:49:33,787 Epoch: [260][20/500] Time 0.020 (0.019) Data 0.002 (0.013) Loss 0.0346 (0.0356) Prec@1 94.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:49:34,078 Epoch: [260][30/500] Time 0.027 (0.021) Data 0.002 (0.009) Loss 0.0282 (0.0338) Prec@1 97.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 14:49:34,383 Epoch: [260][40/500] Time 0.027 (0.023) Data 0.002 (0.007) Loss 0.0377 (0.0345) Prec@1 95.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 14:49:34,680 Epoch: [260][50/500] Time 0.029 (0.024) Data 0.001 (0.006) Loss 0.0639 (0.0394) Prec@1 90.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:49:34,983 Epoch: [260][60/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.0212 (0.0368) Prec@1 96.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 14:49:35,284 Epoch: [260][70/500] Time 0.028 (0.024) Data 0.002 (0.005) Loss 0.0362 (0.0367) Prec@1 94.000 (94.125) Prec@5 99.000 (99.750) +2022-11-14 14:49:35,597 Epoch: [260][80/500] Time 0.030 (0.025) Data 0.001 (0.005) Loss 0.0418 (0.0373) Prec@1 93.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 14:49:36,055 Epoch: [260][90/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0356 (0.0371) Prec@1 94.000 (94.000) Prec@5 100.000 (99.700) +2022-11-14 14:49:36,649 Epoch: [260][100/500] Time 0.044 (0.029) Data 0.002 (0.004) Loss 0.0460 (0.0379) Prec@1 93.000 (93.909) Prec@5 99.000 (99.636) +2022-11-14 14:49:37,160 Epoch: [260][110/500] Time 0.042 (0.030) Data 0.002 (0.004) Loss 0.0119 (0.0358) Prec@1 98.000 (94.250) Prec@5 100.000 (99.667) +2022-11-14 14:49:37,641 Epoch: [260][120/500] Time 0.043 (0.031) Data 0.002 (0.004) Loss 0.0329 (0.0356) Prec@1 95.000 (94.308) Prec@5 100.000 (99.692) +2022-11-14 14:49:38,114 Epoch: [260][130/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.0339 (0.0354) Prec@1 96.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 14:49:38,663 Epoch: [260][140/500] Time 0.095 (0.033) Data 0.002 (0.003) Loss 0.0441 (0.0360) Prec@1 92.000 (94.267) Prec@5 100.000 (99.733) +2022-11-14 14:49:39,136 Epoch: [260][150/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0122 (0.0345) Prec@1 99.000 (94.562) Prec@5 100.000 (99.750) +2022-11-14 14:49:39,599 Epoch: [260][160/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0449 (0.0351) Prec@1 94.000 (94.529) Prec@5 100.000 (99.765) +2022-11-14 14:49:40,156 Epoch: [260][170/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0259 (0.0346) Prec@1 97.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 14:49:40,650 Epoch: [260][180/500] Time 0.044 (0.036) Data 0.001 (0.003) Loss 0.0080 (0.0332) Prec@1 99.000 (94.895) Prec@5 100.000 (99.789) +2022-11-14 14:49:41,193 Epoch: [260][190/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0231 (0.0327) Prec@1 96.000 (94.950) Prec@5 100.000 (99.800) +2022-11-14 14:49:41,769 Epoch: [260][200/500] Time 0.068 (0.037) Data 0.002 (0.003) Loss 0.0414 (0.0331) Prec@1 93.000 (94.857) Prec@5 100.000 (99.810) +2022-11-14 14:49:42,337 Epoch: [260][210/500] Time 0.060 (0.038) Data 0.002 (0.003) Loss 0.0291 (0.0329) Prec@1 95.000 (94.864) Prec@5 100.000 (99.818) +2022-11-14 14:49:42,826 Epoch: [260][220/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0104 (0.0320) Prec@1 98.000 (95.000) Prec@5 100.000 (99.826) +2022-11-14 14:49:43,304 Epoch: [260][230/500] Time 0.054 (0.038) Data 0.002 (0.003) Loss 0.0277 (0.0318) Prec@1 94.000 (94.958) Prec@5 100.000 (99.833) +2022-11-14 14:49:43,781 Epoch: [260][240/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0207 (0.0313) Prec@1 97.000 (95.040) Prec@5 99.000 (99.800) +2022-11-14 14:49:44,259 Epoch: [260][250/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0446 (0.0318) Prec@1 94.000 (95.000) Prec@5 100.000 (99.808) +2022-11-14 14:49:44,727 Epoch: [260][260/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0390 (0.0321) Prec@1 92.000 (94.889) Prec@5 100.000 (99.815) +2022-11-14 14:49:45,199 Epoch: [260][270/500] Time 0.044 (0.039) Data 0.001 (0.003) Loss 0.0473 (0.0327) Prec@1 93.000 (94.821) Prec@5 100.000 (99.821) +2022-11-14 14:49:45,686 Epoch: [260][280/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0195 (0.0322) Prec@1 98.000 (94.931) Prec@5 100.000 (99.828) +2022-11-14 14:49:46,162 Epoch: [260][290/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0262 (0.0320) Prec@1 96.000 (94.967) Prec@5 100.000 (99.833) +2022-11-14 14:49:46,639 Epoch: [260][300/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0410 (0.0323) Prec@1 94.000 (94.935) Prec@5 99.000 (99.806) +2022-11-14 14:49:47,127 Epoch: [260][310/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0426 (0.0326) Prec@1 92.000 (94.844) Prec@5 100.000 (99.812) +2022-11-14 14:49:47,620 Epoch: [260][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0347 (0.0327) Prec@1 96.000 (94.879) Prec@5 99.000 (99.788) +2022-11-14 14:49:48,097 Epoch: [260][330/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0336 (0.0327) Prec@1 94.000 (94.853) Prec@5 100.000 (99.794) +2022-11-14 14:49:48,576 Epoch: [260][340/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0363 (0.0328) Prec@1 95.000 (94.857) Prec@5 99.000 (99.771) +2022-11-14 14:49:49,051 Epoch: [260][350/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0205 (0.0325) Prec@1 97.000 (94.917) Prec@5 100.000 (99.778) +2022-11-14 14:49:49,531 Epoch: [260][360/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0287 (0.0324) Prec@1 93.000 (94.865) Prec@5 100.000 (99.784) +2022-11-14 14:49:50,007 Epoch: [260][370/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0347 (0.0324) Prec@1 95.000 (94.868) Prec@5 100.000 (99.789) +2022-11-14 14:49:50,484 Epoch: [260][380/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0392 (0.0326) Prec@1 94.000 (94.846) Prec@5 100.000 (99.795) +2022-11-14 14:49:50,966 Epoch: [260][390/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0320 (0.0326) Prec@1 95.000 (94.850) Prec@5 100.000 (99.800) +2022-11-14 14:49:51,445 Epoch: [260][400/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0422 (0.0328) Prec@1 93.000 (94.805) Prec@5 100.000 (99.805) +2022-11-14 14:49:51,924 Epoch: [260][410/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0622 (0.0335) Prec@1 88.000 (94.643) Prec@5 99.000 (99.786) +2022-11-14 14:49:52,404 Epoch: [260][420/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0438 (0.0338) Prec@1 92.000 (94.581) Prec@5 100.000 (99.791) +2022-11-14 14:49:52,884 Epoch: [260][430/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0503 (0.0341) Prec@1 91.000 (94.500) Prec@5 100.000 (99.795) +2022-11-14 14:49:53,363 Epoch: [260][440/500] Time 0.042 (0.040) Data 0.002 (0.002) Loss 0.0533 (0.0346) Prec@1 93.000 (94.467) Prec@5 99.000 (99.778) +2022-11-14 14:49:53,839 Epoch: [260][450/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0322 (0.0345) Prec@1 95.000 (94.478) Prec@5 100.000 (99.783) +2022-11-14 14:49:54,319 Epoch: [260][460/500] Time 0.053 (0.040) Data 0.002 (0.002) Loss 0.0246 (0.0343) Prec@1 94.000 (94.468) Prec@5 100.000 (99.787) +2022-11-14 14:49:54,799 Epoch: [260][470/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0456 (0.0345) Prec@1 92.000 (94.417) Prec@5 99.000 (99.771) +2022-11-14 14:49:55,278 Epoch: [260][480/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0357 (0.0346) Prec@1 94.000 (94.408) Prec@5 100.000 (99.776) +2022-11-14 14:49:55,755 Epoch: [260][490/500] Time 0.046 (0.041) Data 0.002 (0.002) Loss 0.0314 (0.0345) Prec@1 95.000 (94.420) Prec@5 100.000 (99.780) +2022-11-14 14:49:56,180 Epoch: [260][499/500] Time 0.043 (0.041) Data 0.001 (0.002) Loss 0.0531 (0.0349) Prec@1 90.000 (94.333) Prec@5 100.000 (99.784) +2022-11-14 14:49:56,478 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0609 (0.0609) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:56,487 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0649) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:56,496 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0652) Prec@1 88.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 14:49:56,508 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0675) Prec@1 88.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:49:56,517 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0744) Prec@1 83.000 (86.600) Prec@5 99.000 (99.400) +2022-11-14 14:49:56,527 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0366 (0.0681) Prec@1 96.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 14:49:56,537 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0661) Prec@1 92.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 14:49:56,548 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0664) Prec@1 89.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 14:49:56,557 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0693) Prec@1 84.000 (88.222) Prec@5 98.000 (99.333) +2022-11-14 14:49:56,565 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0699) Prec@1 89.000 (88.300) Prec@5 99.000 (99.300) +2022-11-14 14:49:56,575 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0676) Prec@1 93.000 (88.727) Prec@5 100.000 (99.364) +2022-11-14 14:49:56,585 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1114 (0.0712) Prec@1 84.000 (88.333) Prec@5 100.000 (99.417) +2022-11-14 14:49:56,596 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0691) Prec@1 94.000 (88.769) Prec@5 100.000 (99.462) +2022-11-14 14:49:56,607 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0700) Prec@1 86.000 (88.571) Prec@5 99.000 (99.429) +2022-11-14 14:49:56,617 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0704) Prec@1 89.000 (88.600) Prec@5 99.000 (99.400) +2022-11-14 14:49:56,629 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0705) Prec@1 86.000 (88.438) Prec@5 100.000 (99.438) +2022-11-14 14:49:56,639 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0696) Prec@1 92.000 (88.647) Prec@5 99.000 (99.412) +2022-11-14 14:49:56,649 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.0725) Prec@1 82.000 (88.278) Prec@5 100.000 (99.444) +2022-11-14 14:49:56,660 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0731) Prec@1 87.000 (88.211) Prec@5 99.000 (99.421) +2022-11-14 14:49:56,671 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0745) Prec@1 82.000 (87.900) Prec@5 96.000 (99.250) +2022-11-14 14:49:56,680 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0744) Prec@1 87.000 (87.857) Prec@5 99.000 (99.238) +2022-11-14 14:49:56,691 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0753) Prec@1 85.000 (87.727) Prec@5 100.000 (99.273) +2022-11-14 14:49:56,701 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0756) Prec@1 88.000 (87.739) Prec@5 98.000 (99.217) +2022-11-14 14:49:56,712 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0750) Prec@1 89.000 (87.792) Prec@5 99.000 (99.208) +2022-11-14 14:49:56,723 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0753) Prec@1 86.000 (87.720) Prec@5 100.000 (99.240) +2022-11-14 14:49:56,734 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0762) Prec@1 86.000 (87.654) Prec@5 99.000 (99.231) +2022-11-14 14:49:56,746 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0756) Prec@1 91.000 (87.778) Prec@5 99.000 (99.222) +2022-11-14 14:49:56,756 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0755) Prec@1 89.000 (87.821) Prec@5 99.000 (99.214) +2022-11-14 14:49:56,767 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0751) Prec@1 89.000 (87.862) Prec@5 99.000 (99.207) +2022-11-14 14:49:56,777 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0749) Prec@1 85.000 (87.767) Prec@5 99.000 (99.200) +2022-11-14 14:49:56,788 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0753) Prec@1 85.000 (87.677) Prec@5 99.000 (99.194) +2022-11-14 14:49:56,798 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0752) Prec@1 89.000 (87.719) Prec@5 98.000 (99.156) +2022-11-14 14:49:56,808 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0753) Prec@1 87.000 (87.697) Prec@5 100.000 (99.182) +2022-11-14 14:49:56,818 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0755) Prec@1 88.000 (87.706) Prec@5 100.000 (99.206) +2022-11-14 14:49:56,828 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0754) Prec@1 89.000 (87.743) Prec@5 98.000 (99.171) +2022-11-14 14:49:56,839 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0753) Prec@1 90.000 (87.806) Prec@5 99.000 (99.167) +2022-11-14 14:49:56,849 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0756) Prec@1 86.000 (87.757) Prec@5 99.000 (99.162) +2022-11-14 14:49:56,860 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0761) Prec@1 85.000 (87.684) Prec@5 98.000 (99.132) +2022-11-14 14:49:56,871 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0756) Prec@1 93.000 (87.821) Prec@5 99.000 (99.128) +2022-11-14 14:49:56,881 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0751) Prec@1 90.000 (87.875) Prec@5 100.000 (99.150) +2022-11-14 14:49:56,890 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0752) Prec@1 87.000 (87.854) Prec@5 98.000 (99.122) +2022-11-14 14:49:56,899 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0749) Prec@1 90.000 (87.905) Prec@5 99.000 (99.119) +2022-11-14 14:49:56,909 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0743) Prec@1 91.000 (87.977) Prec@5 99.000 (99.116) +2022-11-14 14:49:56,919 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0740) Prec@1 92.000 (88.068) Prec@5 97.000 (99.068) +2022-11-14 14:49:56,929 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0741) Prec@1 86.000 (88.022) Prec@5 100.000 (99.089) +2022-11-14 14:49:56,940 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0743) Prec@1 85.000 (87.957) Prec@5 100.000 (99.109) +2022-11-14 14:49:56,950 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0745) Prec@1 88.000 (87.957) Prec@5 100.000 (99.128) +2022-11-14 14:49:56,961 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0752) Prec@1 83.000 (87.854) Prec@5 98.000 (99.104) +2022-11-14 14:49:56,971 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0747) Prec@1 93.000 (87.959) Prec@5 100.000 (99.122) +2022-11-14 14:49:56,981 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0754) Prec@1 82.000 (87.840) Prec@5 99.000 (99.120) +2022-11-14 14:49:56,990 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0757) Prec@1 87.000 (87.824) Prec@5 98.000 (99.098) +2022-11-14 14:49:57,001 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0759) Prec@1 85.000 (87.769) Prec@5 100.000 (99.115) +2022-11-14 14:49:57,013 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0757) Prec@1 90.000 (87.811) Prec@5 99.000 (99.113) +2022-11-14 14:49:57,024 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0755) Prec@1 87.000 (87.796) Prec@5 100.000 (99.130) +2022-11-14 14:49:57,036 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0757) Prec@1 84.000 (87.727) Prec@5 100.000 (99.145) +2022-11-14 14:49:57,047 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0758) Prec@1 85.000 (87.679) Prec@5 99.000 (99.143) +2022-11-14 14:49:57,057 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0756) Prec@1 91.000 (87.737) Prec@5 100.000 (99.158) +2022-11-14 14:49:57,068 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0757) Prec@1 90.000 (87.776) Prec@5 99.000 (99.155) +2022-11-14 14:49:57,080 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0759) Prec@1 84.000 (87.712) Prec@5 100.000 (99.169) +2022-11-14 14:49:57,091 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0760) Prec@1 85.000 (87.667) Prec@5 100.000 (99.183) +2022-11-14 14:49:57,103 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0760) Prec@1 86.000 (87.639) Prec@5 99.000 (99.180) +2022-11-14 14:49:57,114 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0763) Prec@1 86.000 (87.613) Prec@5 98.000 (99.161) +2022-11-14 14:49:57,124 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0764) Prec@1 85.000 (87.571) Prec@5 100.000 (99.175) +2022-11-14 14:49:57,135 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0757) Prec@1 93.000 (87.656) Prec@5 99.000 (99.172) +2022-11-14 14:49:57,144 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0761) Prec@1 83.000 (87.585) Prec@5 99.000 (99.169) +2022-11-14 14:49:57,154 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0764) Prec@1 85.000 (87.545) Prec@5 99.000 (99.167) +2022-11-14 14:49:57,164 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0759) Prec@1 92.000 (87.612) Prec@5 100.000 (99.179) +2022-11-14 14:49:57,175 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0758) Prec@1 88.000 (87.618) Prec@5 99.000 (99.176) +2022-11-14 14:49:57,184 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0756) Prec@1 89.000 (87.638) Prec@5 100.000 (99.188) +2022-11-14 14:49:57,192 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0756) Prec@1 86.000 (87.614) Prec@5 100.000 (99.200) +2022-11-14 14:49:57,200 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0757) Prec@1 88.000 (87.620) Prec@5 99.000 (99.197) +2022-11-14 14:49:57,209 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0756) Prec@1 88.000 (87.625) Prec@5 100.000 (99.208) +2022-11-14 14:49:57,219 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0753) Prec@1 92.000 (87.685) Prec@5 100.000 (99.219) +2022-11-14 14:49:57,228 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0750) Prec@1 93.000 (87.757) Prec@5 100.000 (99.230) +2022-11-14 14:49:57,236 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0750) Prec@1 87.000 (87.747) Prec@5 99.000 (99.227) +2022-11-14 14:49:57,246 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0748) Prec@1 91.000 (87.789) Prec@5 99.000 (99.224) +2022-11-14 14:49:57,256 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0748) Prec@1 88.000 (87.792) Prec@5 99.000 (99.221) +2022-11-14 14:49:57,266 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0749) Prec@1 87.000 (87.782) Prec@5 99.000 (99.218) +2022-11-14 14:49:57,275 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0749) Prec@1 89.000 (87.797) Prec@5 100.000 (99.228) +2022-11-14 14:49:57,284 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0751) Prec@1 84.000 (87.750) Prec@5 99.000 (99.225) +2022-11-14 14:49:57,294 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0753) Prec@1 86.000 (87.728) Prec@5 99.000 (99.222) +2022-11-14 14:49:57,303 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0752) Prec@1 87.000 (87.720) Prec@5 100.000 (99.232) +2022-11-14 14:49:57,313 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0754) Prec@1 85.000 (87.687) Prec@5 100.000 (99.241) +2022-11-14 14:49:57,325 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0752) Prec@1 90.000 (87.714) Prec@5 100.000 (99.250) +2022-11-14 14:49:57,336 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0750) Prec@1 92.000 (87.765) Prec@5 99.000 (99.247) +2022-11-14 14:49:57,346 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0754) Prec@1 84.000 (87.721) Prec@5 99.000 (99.244) +2022-11-14 14:49:57,358 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0755) Prec@1 88.000 (87.724) Prec@5 98.000 (99.230) +2022-11-14 14:49:57,367 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0756) Prec@1 88.000 (87.727) Prec@5 99.000 (99.227) +2022-11-14 14:49:57,377 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0756) Prec@1 88.000 (87.730) Prec@5 100.000 (99.236) +2022-11-14 14:49:57,386 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0757) Prec@1 85.000 (87.700) Prec@5 98.000 (99.222) +2022-11-14 14:49:57,396 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0755) Prec@1 91.000 (87.736) Prec@5 100.000 (99.231) +2022-11-14 14:49:57,407 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0753) Prec@1 91.000 (87.772) Prec@5 99.000 (99.228) +2022-11-14 14:49:57,418 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0753) Prec@1 89.000 (87.785) Prec@5 100.000 (99.237) +2022-11-14 14:49:57,429 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0753) Prec@1 86.000 (87.766) Prec@5 99.000 (99.234) +2022-11-14 14:49:57,439 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0753) Prec@1 87.000 (87.758) Prec@5 99.000 (99.232) +2022-11-14 14:49:57,448 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0753) Prec@1 91.000 (87.792) Prec@5 99.000 (99.229) +2022-11-14 14:49:57,457 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0750) Prec@1 92.000 (87.835) Prec@5 99.000 (99.227) +2022-11-14 14:49:57,467 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0750) Prec@1 89.000 (87.847) Prec@5 100.000 (99.235) +2022-11-14 14:49:57,476 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0753) Prec@1 83.000 (87.798) Prec@5 99.000 (99.232) +2022-11-14 14:49:57,487 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0753) Prec@1 88.000 (87.800) Prec@5 100.000 (99.240) +2022-11-14 14:49:57,548 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:49:57,869 Epoch: [261][0/500] Time 0.026 (0.026) Data 0.237 (0.237) Loss 0.0449 (0.0449) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:49:58,083 Epoch: [261][10/500] Time 0.017 (0.019) Data 0.001 (0.023) Loss 0.0364 (0.0406) Prec@1 95.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 14:49:58,293 Epoch: [261][20/500] Time 0.017 (0.019) Data 0.002 (0.013) Loss 0.0480 (0.0431) Prec@1 93.000 (93.667) Prec@5 99.000 (99.333) +2022-11-14 14:49:58,508 Epoch: [261][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.0462 (0.0439) Prec@1 92.000 (93.250) Prec@5 100.000 (99.500) +2022-11-14 14:49:58,782 Epoch: [261][40/500] Time 0.030 (0.020) Data 0.002 (0.008) Loss 0.0393 (0.0429) Prec@1 92.000 (93.000) Prec@5 99.000 (99.400) +2022-11-14 14:49:59,062 Epoch: [261][50/500] Time 0.023 (0.021) Data 0.002 (0.007) Loss 0.0283 (0.0405) Prec@1 96.000 (93.500) Prec@5 99.000 (99.333) +2022-11-14 14:49:59,344 Epoch: [261][60/500] Time 0.023 (0.022) Data 0.002 (0.006) Loss 0.0428 (0.0408) Prec@1 92.000 (93.286) Prec@5 100.000 (99.429) +2022-11-14 14:49:59,623 Epoch: [261][70/500] Time 0.025 (0.022) Data 0.002 (0.005) Loss 0.0311 (0.0396) Prec@1 93.000 (93.250) Prec@5 100.000 (99.500) +2022-11-14 14:49:59,914 Epoch: [261][80/500] Time 0.024 (0.023) Data 0.002 (0.005) Loss 0.0155 (0.0369) Prec@1 97.000 (93.667) Prec@5 100.000 (99.556) +2022-11-14 14:50:00,200 Epoch: [261][90/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0290 (0.0361) Prec@1 95.000 (93.800) Prec@5 99.000 (99.500) +2022-11-14 14:50:00,488 Epoch: [261][100/500] Time 0.023 (0.023) Data 0.002 (0.004) Loss 0.0376 (0.0363) Prec@1 93.000 (93.727) Prec@5 100.000 (99.545) +2022-11-14 14:50:00,818 Epoch: [261][110/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0577 (0.0381) Prec@1 90.000 (93.417) Prec@5 99.000 (99.500) +2022-11-14 14:50:01,092 Epoch: [261][120/500] Time 0.027 (0.024) Data 0.002 (0.004) Loss 0.0355 (0.0379) Prec@1 93.000 (93.385) Prec@5 100.000 (99.538) +2022-11-14 14:50:01,388 Epoch: [261][130/500] Time 0.025 (0.024) Data 0.002 (0.004) Loss 0.0335 (0.0376) Prec@1 94.000 (93.429) Prec@5 100.000 (99.571) +2022-11-14 14:50:01,855 Epoch: [261][140/500] Time 0.042 (0.025) Data 0.002 (0.004) Loss 0.0280 (0.0369) Prec@1 94.000 (93.467) Prec@5 99.000 (99.533) +2022-11-14 14:50:02,331 Epoch: [261][150/500] Time 0.048 (0.026) Data 0.002 (0.003) Loss 0.0572 (0.0382) Prec@1 91.000 (93.312) Prec@5 100.000 (99.562) +2022-11-14 14:50:02,806 Epoch: [261][160/500] Time 0.052 (0.027) Data 0.003 (0.003) Loss 0.0433 (0.0385) Prec@1 92.000 (93.235) Prec@5 100.000 (99.588) +2022-11-14 14:50:03,282 Epoch: [261][170/500] Time 0.045 (0.028) Data 0.002 (0.003) Loss 0.0179 (0.0373) Prec@1 97.000 (93.444) Prec@5 100.000 (99.611) +2022-11-14 14:50:03,790 Epoch: [261][180/500] Time 0.044 (0.029) Data 0.002 (0.003) Loss 0.0430 (0.0376) Prec@1 92.000 (93.368) Prec@5 100.000 (99.632) +2022-11-14 14:50:04,328 Epoch: [261][190/500] Time 0.064 (0.030) Data 0.002 (0.003) Loss 0.0369 (0.0376) Prec@1 91.000 (93.250) Prec@5 100.000 (99.650) +2022-11-14 14:50:04,817 Epoch: [261][200/500] Time 0.046 (0.031) Data 0.002 (0.003) Loss 0.0308 (0.0373) Prec@1 94.000 (93.286) Prec@5 100.000 (99.667) +2022-11-14 14:50:05,350 Epoch: [261][210/500] Time 0.046 (0.032) Data 0.002 (0.003) Loss 0.0299 (0.0369) Prec@1 96.000 (93.409) Prec@5 100.000 (99.682) +2022-11-14 14:50:05,830 Epoch: [261][220/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0609 (0.0380) Prec@1 90.000 (93.261) Prec@5 99.000 (99.652) +2022-11-14 14:50:06,360 Epoch: [261][230/500] Time 0.044 (0.033) Data 0.002 (0.003) Loss 0.0368 (0.0379) Prec@1 92.000 (93.208) Prec@5 100.000 (99.667) +2022-11-14 14:50:06,921 Epoch: [261][240/500] Time 0.058 (0.033) Data 0.002 (0.003) Loss 0.0609 (0.0389) Prec@1 89.000 (93.040) Prec@5 100.000 (99.680) +2022-11-14 14:50:07,603 Epoch: [261][250/500] Time 0.057 (0.034) Data 0.002 (0.003) Loss 0.0309 (0.0385) Prec@1 95.000 (93.115) Prec@5 100.000 (99.692) +2022-11-14 14:50:08,120 Epoch: [261][260/500] Time 0.043 (0.035) Data 0.002 (0.003) Loss 0.0189 (0.0378) Prec@1 97.000 (93.259) Prec@5 100.000 (99.704) +2022-11-14 14:50:08,624 Epoch: [261][270/500] Time 0.066 (0.035) Data 0.002 (0.003) Loss 0.0395 (0.0379) Prec@1 94.000 (93.286) Prec@5 100.000 (99.714) +2022-11-14 14:50:09,120 Epoch: [261][280/500] Time 0.066 (0.035) Data 0.002 (0.003) Loss 0.0354 (0.0378) Prec@1 92.000 (93.241) Prec@5 100.000 (99.724) +2022-11-14 14:50:09,629 Epoch: [261][290/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0235 (0.0373) Prec@1 96.000 (93.333) Prec@5 100.000 (99.733) +2022-11-14 14:50:10,136 Epoch: [261][300/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.0151 (0.0366) Prec@1 99.000 (93.516) Prec@5 100.000 (99.742) +2022-11-14 14:50:10,681 Epoch: [261][310/500] Time 0.057 (0.037) Data 0.002 (0.003) Loss 0.0228 (0.0362) Prec@1 97.000 (93.625) Prec@5 100.000 (99.750) +2022-11-14 14:50:11,192 Epoch: [261][320/500] Time 0.076 (0.037) Data 0.002 (0.003) Loss 0.0431 (0.0364) Prec@1 94.000 (93.636) Prec@5 100.000 (99.758) +2022-11-14 14:50:11,654 Epoch: [261][330/500] Time 0.042 (0.037) Data 0.001 (0.003) Loss 0.0255 (0.0361) Prec@1 97.000 (93.735) Prec@5 100.000 (99.765) +2022-11-14 14:50:12,173 Epoch: [261][340/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0313 (0.0359) Prec@1 94.000 (93.743) Prec@5 100.000 (99.771) +2022-11-14 14:50:12,704 Epoch: [261][350/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0334 (0.0359) Prec@1 95.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 14:50:13,196 Epoch: [261][360/500] Time 0.042 (0.038) Data 0.001 (0.003) Loss 0.0197 (0.0354) Prec@1 96.000 (93.838) Prec@5 100.000 (99.784) +2022-11-14 14:50:13,701 Epoch: [261][370/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0365 (0.0355) Prec@1 94.000 (93.842) Prec@5 100.000 (99.789) +2022-11-14 14:50:14,211 Epoch: [261][380/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0389 (0.0355) Prec@1 94.000 (93.846) Prec@5 100.000 (99.795) +2022-11-14 14:50:14,727 Epoch: [261][390/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0599 (0.0361) Prec@1 90.000 (93.750) Prec@5 100.000 (99.800) +2022-11-14 14:50:15,218 Epoch: [261][400/500] Time 0.052 (0.038) Data 0.002 (0.002) Loss 0.0432 (0.0363) Prec@1 93.000 (93.732) Prec@5 100.000 (99.805) +2022-11-14 14:50:15,753 Epoch: [261][410/500] Time 0.049 (0.039) Data 0.002 (0.002) Loss 0.0273 (0.0361) Prec@1 95.000 (93.762) Prec@5 100.000 (99.810) +2022-11-14 14:50:16,264 Epoch: [261][420/500] Time 0.042 (0.039) Data 0.002 (0.002) Loss 0.0343 (0.0361) Prec@1 93.000 (93.744) Prec@5 100.000 (99.814) +2022-11-14 14:50:16,785 Epoch: [261][430/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0333 (0.0360) Prec@1 95.000 (93.773) Prec@5 100.000 (99.818) +2022-11-14 14:50:17,312 Epoch: [261][440/500] Time 0.048 (0.039) Data 0.002 (0.002) Loss 0.0174 (0.0356) Prec@1 96.000 (93.822) Prec@5 100.000 (99.822) +2022-11-14 14:50:17,942 Epoch: [261][450/500] Time 0.061 (0.039) Data 0.002 (0.002) Loss 0.0446 (0.0358) Prec@1 93.000 (93.804) Prec@5 100.000 (99.826) +2022-11-14 14:50:18,522 Epoch: [261][460/500] Time 0.043 (0.040) Data 0.002 (0.002) Loss 0.0297 (0.0357) Prec@1 94.000 (93.809) Prec@5 99.000 (99.809) +2022-11-14 14:50:19,291 Epoch: [261][470/500] Time 0.073 (0.040) Data 0.002 (0.002) Loss 0.0277 (0.0355) Prec@1 96.000 (93.854) Prec@5 100.000 (99.812) +2022-11-14 14:50:19,813 Epoch: [261][480/500] Time 0.066 (0.040) Data 0.002 (0.002) Loss 0.0294 (0.0354) Prec@1 94.000 (93.857) Prec@5 100.000 (99.816) +2022-11-14 14:50:20,308 Epoch: [261][490/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0278 (0.0352) Prec@1 95.000 (93.880) Prec@5 100.000 (99.820) +2022-11-14 14:50:20,768 Epoch: [261][499/500] Time 0.051 (0.041) Data 0.001 (0.002) Loss 0.0226 (0.0350) Prec@1 97.000 (93.941) Prec@5 100.000 (99.824) +2022-11-14 14:50:21,045 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0839 (0.0839) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:50:21,054 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0746) Prec@1 91.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:50:21,064 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0709) Prec@1 89.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 14:50:21,077 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0773) Prec@1 82.000 (87.500) Prec@5 99.000 (99.250) +2022-11-14 14:50:21,087 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0753) Prec@1 88.000 (87.600) Prec@5 100.000 (99.400) +2022-11-14 14:50:21,096 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0316 (0.0680) Prec@1 95.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 14:50:21,104 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0670) Prec@1 91.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 14:50:21,113 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0697) Prec@1 84.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 14:50:21,121 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0726) Prec@1 85.000 (88.111) Prec@5 99.000 (99.333) +2022-11-14 14:50:21,130 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0727) Prec@1 88.000 (88.100) Prec@5 99.000 (99.300) +2022-11-14 14:50:21,140 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0709) Prec@1 92.000 (88.455) Prec@5 100.000 (99.364) +2022-11-14 14:50:21,151 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0726) Prec@1 84.000 (88.083) Prec@5 99.000 (99.333) +2022-11-14 14:50:21,162 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0710) Prec@1 91.000 (88.308) Prec@5 99.000 (99.308) +2022-11-14 14:50:21,172 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0717) Prec@1 86.000 (88.143) Prec@5 99.000 (99.286) +2022-11-14 14:50:21,182 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0724) Prec@1 86.000 (88.000) Prec@5 99.000 (99.267) +2022-11-14 14:50:21,193 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0731) Prec@1 87.000 (87.938) Prec@5 100.000 (99.312) +2022-11-14 14:50:21,204 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0713) Prec@1 94.000 (88.294) Prec@5 99.000 (99.294) +2022-11-14 14:50:21,215 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.0734) Prec@1 83.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 14:50:21,225 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0743) Prec@1 83.000 (87.737) Prec@5 99.000 (99.316) +2022-11-14 14:50:21,235 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0759) Prec@1 83.000 (87.500) Prec@5 97.000 (99.200) +2022-11-14 14:50:21,246 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0752) Prec@1 90.000 (87.619) Prec@5 100.000 (99.238) +2022-11-14 14:50:21,256 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0756) Prec@1 86.000 (87.545) Prec@5 98.000 (99.182) +2022-11-14 14:50:21,266 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0765) Prec@1 85.000 (87.435) Prec@5 98.000 (99.130) +2022-11-14 14:50:21,277 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0759) Prec@1 88.000 (87.458) Prec@5 100.000 (99.167) +2022-11-14 14:50:21,287 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0760) Prec@1 89.000 (87.520) Prec@5 100.000 (99.200) +2022-11-14 14:50:21,298 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0762) Prec@1 90.000 (87.615) Prec@5 99.000 (99.192) +2022-11-14 14:50:21,308 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0756) Prec@1 91.000 (87.741) Prec@5 99.000 (99.185) +2022-11-14 14:50:21,318 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0748) Prec@1 92.000 (87.893) Prec@5 100.000 (99.214) +2022-11-14 14:50:21,328 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0748) Prec@1 87.000 (87.862) Prec@5 99.000 (99.207) +2022-11-14 14:50:21,339 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0752) Prec@1 86.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 14:50:21,350 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0754) Prec@1 86.000 (87.742) Prec@5 99.000 (99.194) +2022-11-14 14:50:21,360 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0753) Prec@1 89.000 (87.781) Prec@5 99.000 (99.188) +2022-11-14 14:50:21,372 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0756) Prec@1 83.000 (87.636) Prec@5 100.000 (99.212) +2022-11-14 14:50:21,383 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0759) Prec@1 86.000 (87.588) Prec@5 99.000 (99.206) +2022-11-14 14:50:21,396 Test: [34/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0757) Prec@1 91.000 (87.686) Prec@5 98.000 (99.171) +2022-11-14 14:50:21,409 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0756) Prec@1 88.000 (87.694) Prec@5 100.000 (99.194) +2022-11-14 14:50:21,419 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0754) Prec@1 87.000 (87.676) Prec@5 99.000 (99.189) +2022-11-14 14:50:21,431 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.0764) Prec@1 82.000 (87.526) Prec@5 100.000 (99.211) +2022-11-14 14:50:21,444 Test: [38/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0759) Prec@1 92.000 (87.641) Prec@5 99.000 (99.205) +2022-11-14 14:50:21,456 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0752) Prec@1 93.000 (87.775) Prec@5 100.000 (99.225) +2022-11-14 14:50:21,467 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0757) Prec@1 84.000 (87.683) Prec@5 98.000 (99.195) +2022-11-14 14:50:21,477 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0757) Prec@1 89.000 (87.714) Prec@5 99.000 (99.190) +2022-11-14 14:50:21,488 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0752) Prec@1 89.000 (87.744) Prec@5 99.000 (99.186) +2022-11-14 14:50:21,498 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0751) Prec@1 92.000 (87.841) Prec@5 98.000 (99.159) +2022-11-14 14:50:21,508 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0747) Prec@1 91.000 (87.911) Prec@5 100.000 (99.178) +2022-11-14 14:50:21,518 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0749) Prec@1 87.000 (87.891) Prec@5 99.000 (99.174) +2022-11-14 14:50:21,529 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0749) Prec@1 89.000 (87.915) Prec@5 100.000 (99.191) +2022-11-14 14:50:21,540 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1323 (0.0761) Prec@1 78.000 (87.708) Prec@5 97.000 (99.146) +2022-11-14 14:50:21,551 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0756) Prec@1 92.000 (87.796) Prec@5 100.000 (99.163) +2022-11-14 14:50:21,560 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0762) Prec@1 81.000 (87.660) Prec@5 99.000 (99.160) +2022-11-14 14:50:21,572 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0757) Prec@1 89.000 (87.686) Prec@5 100.000 (99.176) +2022-11-14 14:50:21,581 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0761) Prec@1 85.000 (87.635) Prec@5 100.000 (99.192) +2022-11-14 14:50:21,592 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0760) Prec@1 90.000 (87.679) Prec@5 99.000 (99.189) +2022-11-14 14:50:21,601 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0759) Prec@1 85.000 (87.630) Prec@5 99.000 (99.185) +2022-11-14 14:50:21,612 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0764) Prec@1 83.000 (87.545) Prec@5 100.000 (99.200) +2022-11-14 14:50:21,621 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0761) Prec@1 91.000 (87.607) Prec@5 99.000 (99.196) +2022-11-14 14:50:21,632 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0762) Prec@1 85.000 (87.561) Prec@5 98.000 (99.175) +2022-11-14 14:50:21,642 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0761) Prec@1 89.000 (87.586) Prec@5 98.000 (99.155) +2022-11-14 14:50:21,652 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0766) Prec@1 81.000 (87.475) Prec@5 100.000 (99.169) +2022-11-14 14:50:21,661 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0765) Prec@1 89.000 (87.500) Prec@5 100.000 (99.183) +2022-11-14 14:50:21,671 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0763) Prec@1 90.000 (87.541) Prec@5 100.000 (99.197) +2022-11-14 14:50:21,682 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0761) Prec@1 89.000 (87.565) Prec@5 100.000 (99.210) +2022-11-14 14:50:21,690 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0758) Prec@1 89.000 (87.587) Prec@5 100.000 (99.222) +2022-11-14 14:50:21,701 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0753) Prec@1 92.000 (87.656) Prec@5 100.000 (99.234) +2022-11-14 14:50:21,712 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0753) Prec@1 89.000 (87.677) Prec@5 100.000 (99.246) +2022-11-14 14:50:21,721 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0753) Prec@1 87.000 (87.667) Prec@5 99.000 (99.242) +2022-11-14 14:50:21,732 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0750) Prec@1 93.000 (87.746) Prec@5 100.000 (99.254) +2022-11-14 14:50:21,741 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0750) Prec@1 90.000 (87.779) Prec@5 99.000 (99.250) +2022-11-14 14:50:21,752 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0748) Prec@1 90.000 (87.812) Prec@5 99.000 (99.246) +2022-11-14 14:50:21,762 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0747) Prec@1 89.000 (87.829) Prec@5 99.000 (99.243) +2022-11-14 14:50:21,772 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0748) Prec@1 87.000 (87.817) Prec@5 100.000 (99.254) +2022-11-14 14:50:21,781 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0749) Prec@1 87.000 (87.806) Prec@5 100.000 (99.264) +2022-11-14 14:50:21,791 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0746) Prec@1 91.000 (87.849) Prec@5 100.000 (99.274) +2022-11-14 14:50:21,801 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0742) Prec@1 93.000 (87.919) Prec@5 100.000 (99.284) +2022-11-14 14:50:21,810 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0744) Prec@1 85.000 (87.880) Prec@5 99.000 (99.280) +2022-11-14 14:50:21,820 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0744) Prec@1 88.000 (87.882) Prec@5 99.000 (99.276) +2022-11-14 14:50:21,830 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0744) Prec@1 88.000 (87.883) Prec@5 98.000 (99.260) +2022-11-14 14:50:21,840 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0746) Prec@1 85.000 (87.846) Prec@5 100.000 (99.269) +2022-11-14 14:50:21,852 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0744) Prec@1 87.000 (87.835) Prec@5 100.000 (99.278) +2022-11-14 14:50:21,865 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0746) Prec@1 83.000 (87.775) Prec@5 100.000 (99.287) +2022-11-14 14:50:21,875 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0748) Prec@1 86.000 (87.753) Prec@5 99.000 (99.284) +2022-11-14 14:50:21,887 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0749) Prec@1 87.000 (87.744) Prec@5 100.000 (99.293) +2022-11-14 14:50:21,901 Test: [82/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0750) Prec@1 86.000 (87.723) Prec@5 100.000 (99.301) +2022-11-14 14:50:21,914 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0749) Prec@1 88.000 (87.726) Prec@5 99.000 (99.298) +2022-11-14 14:50:21,924 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0751) Prec@1 88.000 (87.729) Prec@5 100.000 (99.306) +2022-11-14 14:50:21,936 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1205 (0.0756) Prec@1 80.000 (87.640) Prec@5 100.000 (99.314) +2022-11-14 14:50:21,949 Test: [86/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0756) Prec@1 87.000 (87.632) Prec@5 99.000 (99.310) +2022-11-14 14:50:21,960 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0758) Prec@1 85.000 (87.602) Prec@5 99.000 (99.307) +2022-11-14 14:50:21,971 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0758) Prec@1 88.000 (87.607) Prec@5 99.000 (99.303) +2022-11-14 14:50:21,981 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0757) Prec@1 88.000 (87.611) Prec@5 100.000 (99.311) +2022-11-14 14:50:21,990 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0758) Prec@1 87.000 (87.604) Prec@5 100.000 (99.319) +2022-11-14 14:50:22,001 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0755) Prec@1 91.000 (87.641) Prec@5 99.000 (99.315) +2022-11-14 14:50:22,012 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0756) Prec@1 87.000 (87.634) Prec@5 100.000 (99.323) +2022-11-14 14:50:22,022 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0757) Prec@1 87.000 (87.628) Prec@5 100.000 (99.330) +2022-11-14 14:50:22,033 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0759) Prec@1 86.000 (87.611) Prec@5 99.000 (99.326) +2022-11-14 14:50:22,044 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0756) Prec@1 93.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 14:50:22,053 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0419 (0.0753) Prec@1 94.000 (87.732) Prec@5 99.000 (99.330) +2022-11-14 14:50:22,064 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0754) Prec@1 87.000 (87.724) Prec@5 97.000 (99.306) +2022-11-14 14:50:22,073 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0757) Prec@1 84.000 (87.687) Prec@5 100.000 (99.313) +2022-11-14 14:50:22,082 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0756) Prec@1 89.000 (87.700) Prec@5 100.000 (99.320) +2022-11-14 14:50:22,153 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:50:22,483 Epoch: [262][0/500] Time 0.024 (0.024) Data 0.240 (0.240) Loss 0.0299 (0.0299) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:50:22,720 Epoch: [262][10/500] Time 0.018 (0.021) Data 0.001 (0.024) Loss 0.0391 (0.0345) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 14:50:22,942 Epoch: [262][20/500] Time 0.020 (0.021) Data 0.001 (0.013) Loss 0.0288 (0.0326) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:50:23,203 Epoch: [262][30/500] Time 0.021 (0.021) Data 0.002 (0.009) Loss 0.0294 (0.0318) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:50:23,470 Epoch: [262][40/500] Time 0.029 (0.022) Data 0.002 (0.008) Loss 0.0337 (0.0322) Prec@1 94.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 14:50:23,730 Epoch: [262][50/500] Time 0.022 (0.022) Data 0.002 (0.006) Loss 0.0362 (0.0329) Prec@1 94.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 14:50:24,039 Epoch: [262][60/500] Time 0.037 (0.023) Data 0.002 (0.006) Loss 0.0300 (0.0325) Prec@1 95.000 (94.429) Prec@5 99.000 (99.857) +2022-11-14 14:50:24,360 Epoch: [262][70/500] Time 0.029 (0.024) Data 0.002 (0.005) Loss 0.0668 (0.0367) Prec@1 90.000 (93.875) Prec@5 99.000 (99.750) +2022-11-14 14:50:24,774 Epoch: [262][80/500] Time 0.052 (0.025) Data 0.002 (0.005) Loss 0.0312 (0.0361) Prec@1 95.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 14:50:25,214 Epoch: [262][90/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0261 (0.0351) Prec@1 95.000 (94.100) Prec@5 99.000 (99.700) +2022-11-14 14:50:25,676 Epoch: [262][100/500] Time 0.057 (0.028) Data 0.003 (0.004) Loss 0.0256 (0.0343) Prec@1 96.000 (94.273) Prec@5 100.000 (99.727) +2022-11-14 14:50:26,133 Epoch: [262][110/500] Time 0.049 (0.029) Data 0.002 (0.004) Loss 0.0510 (0.0357) Prec@1 91.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 14:50:26,656 Epoch: [262][120/500] Time 0.051 (0.031) Data 0.002 (0.004) Loss 0.0391 (0.0359) Prec@1 92.000 (93.846) Prec@5 100.000 (99.769) +2022-11-14 14:50:27,180 Epoch: [262][130/500] Time 0.050 (0.032) Data 0.002 (0.004) Loss 0.0198 (0.0348) Prec@1 96.000 (94.000) Prec@5 100.000 (99.786) +2022-11-14 14:50:27,606 Epoch: [262][140/500] Time 0.042 (0.032) Data 0.002 (0.004) Loss 0.0259 (0.0342) Prec@1 96.000 (94.133) Prec@5 99.000 (99.733) +2022-11-14 14:50:28,140 Epoch: [262][150/500] Time 0.050 (0.033) Data 0.002 (0.004) Loss 0.0266 (0.0337) Prec@1 95.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 14:50:28,666 Epoch: [262][160/500] Time 0.053 (0.034) Data 0.003 (0.003) Loss 0.0299 (0.0335) Prec@1 95.000 (94.235) Prec@5 100.000 (99.765) +2022-11-14 14:50:29,098 Epoch: [262][170/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0373 (0.0337) Prec@1 95.000 (94.278) Prec@5 100.000 (99.778) +2022-11-14 14:50:29,529 Epoch: [262][180/500] Time 0.046 (0.035) Data 0.002 (0.003) Loss 0.0449 (0.0343) Prec@1 93.000 (94.211) Prec@5 100.000 (99.789) +2022-11-14 14:50:30,060 Epoch: [262][190/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0319 (0.0342) Prec@1 95.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:50:30,616 Epoch: [262][200/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.0223 (0.0336) Prec@1 97.000 (94.381) Prec@5 100.000 (99.762) +2022-11-14 14:50:31,138 Epoch: [262][210/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0339 (0.0336) Prec@1 95.000 (94.409) Prec@5 100.000 (99.773) +2022-11-14 14:50:31,563 Epoch: [262][220/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.0393 (0.0339) Prec@1 94.000 (94.391) Prec@5 100.000 (99.783) +2022-11-14 14:50:31,992 Epoch: [262][230/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0546 (0.0347) Prec@1 91.000 (94.250) Prec@5 100.000 (99.792) +2022-11-14 14:50:32,424 Epoch: [262][240/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0314 (0.0346) Prec@1 92.000 (94.160) Prec@5 100.000 (99.800) +2022-11-14 14:50:32,856 Epoch: [262][250/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0255 (0.0342) Prec@1 95.000 (94.192) Prec@5 99.000 (99.769) +2022-11-14 14:50:33,311 Epoch: [262][260/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0306 (0.0341) Prec@1 95.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 14:50:33,741 Epoch: [262][270/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0510 (0.0347) Prec@1 92.000 (94.143) Prec@5 99.000 (99.750) +2022-11-14 14:50:34,174 Epoch: [262][280/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0339 (0.0347) Prec@1 96.000 (94.207) Prec@5 99.000 (99.724) +2022-11-14 14:50:34,595 Epoch: [262][290/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0317 (0.0346) Prec@1 93.000 (94.167) Prec@5 100.000 (99.733) +2022-11-14 14:50:35,039 Epoch: [262][300/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0358 (0.0346) Prec@1 96.000 (94.226) Prec@5 99.000 (99.710) +2022-11-14 14:50:35,477 Epoch: [262][310/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0462 (0.0350) Prec@1 92.000 (94.156) Prec@5 100.000 (99.719) +2022-11-14 14:50:35,941 Epoch: [262][320/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0409 (0.0352) Prec@1 93.000 (94.121) Prec@5 99.000 (99.697) +2022-11-14 14:50:36,366 Epoch: [262][330/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0341 (0.0351) Prec@1 96.000 (94.176) Prec@5 99.000 (99.676) +2022-11-14 14:50:36,800 Epoch: [262][340/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0223 (0.0348) Prec@1 96.000 (94.229) Prec@5 100.000 (99.686) +2022-11-14 14:50:37,230 Epoch: [262][350/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0224 (0.0344) Prec@1 97.000 (94.306) Prec@5 100.000 (99.694) +2022-11-14 14:50:37,707 Epoch: [262][360/500] Time 0.047 (0.038) Data 0.002 (0.003) Loss 0.0459 (0.0347) Prec@1 94.000 (94.297) Prec@5 100.000 (99.703) +2022-11-14 14:50:38,136 Epoch: [262][370/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0421 (0.0349) Prec@1 95.000 (94.316) Prec@5 100.000 (99.711) +2022-11-14 14:50:38,569 Epoch: [262][380/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0360 (0.0350) Prec@1 94.000 (94.308) Prec@5 100.000 (99.718) +2022-11-14 14:50:39,040 Epoch: [262][390/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.0312 (0.0349) Prec@1 93.000 (94.275) Prec@5 100.000 (99.725) +2022-11-14 14:50:39,470 Epoch: [262][400/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0465 (0.0351) Prec@1 93.000 (94.244) Prec@5 100.000 (99.732) +2022-11-14 14:50:39,933 Epoch: [262][410/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0462 (0.0354) Prec@1 92.000 (94.190) Prec@5 100.000 (99.738) +2022-11-14 14:50:40,357 Epoch: [262][420/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0333 (0.0354) Prec@1 95.000 (94.209) Prec@5 100.000 (99.744) +2022-11-14 14:50:40,817 Epoch: [262][430/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0361 (0.0354) Prec@1 95.000 (94.227) Prec@5 99.000 (99.727) +2022-11-14 14:50:41,243 Epoch: [262][440/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0265 (0.0352) Prec@1 97.000 (94.289) Prec@5 100.000 (99.733) +2022-11-14 14:50:41,680 Epoch: [262][450/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0535 (0.0356) Prec@1 92.000 (94.239) Prec@5 100.000 (99.739) +2022-11-14 14:50:42,117 Epoch: [262][460/500] Time 0.055 (0.038) Data 0.001 (0.003) Loss 0.0249 (0.0354) Prec@1 97.000 (94.298) Prec@5 100.000 (99.745) +2022-11-14 14:50:42,541 Epoch: [262][470/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0402 (0.0355) Prec@1 96.000 (94.333) Prec@5 100.000 (99.750) +2022-11-14 14:50:42,959 Epoch: [262][480/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0326 (0.0354) Prec@1 96.000 (94.367) Prec@5 100.000 (99.755) +2022-11-14 14:50:43,382 Epoch: [262][490/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0382 (0.0354) Prec@1 94.000 (94.360) Prec@5 100.000 (99.760) +2022-11-14 14:50:43,770 Epoch: [262][499/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0595 (0.0359) Prec@1 90.000 (94.275) Prec@5 100.000 (99.765) +2022-11-14 14:50:44,058 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0635 (0.0635) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:50:44,067 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0705) Prec@1 89.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 14:50:44,075 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0725) Prec@1 87.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 14:50:44,087 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0746) Prec@1 88.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:50:44,096 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0741) Prec@1 88.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 14:50:44,105 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0688) Prec@1 93.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 14:50:44,116 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0691) Prec@1 86.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 14:50:44,126 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0687) Prec@1 89.000 (88.500) Prec@5 100.000 (99.625) +2022-11-14 14:50:44,137 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1174 (0.0741) Prec@1 81.000 (87.667) Prec@5 99.000 (99.556) +2022-11-14 14:50:44,147 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0751) Prec@1 87.000 (87.600) Prec@5 97.000 (99.300) +2022-11-14 14:50:44,155 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0361 (0.0716) Prec@1 94.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 14:50:44,165 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0738) Prec@1 84.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 14:50:44,176 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0724) Prec@1 91.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 14:50:44,185 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0724) Prec@1 88.000 (88.071) Prec@5 100.000 (99.429) +2022-11-14 14:50:44,196 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0731) Prec@1 86.000 (87.933) Prec@5 98.000 (99.333) +2022-11-14 14:50:44,204 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0733) Prec@1 88.000 (87.938) Prec@5 99.000 (99.312) +2022-11-14 14:50:44,214 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0722) Prec@1 91.000 (88.118) Prec@5 98.000 (99.235) +2022-11-14 14:50:44,225 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0744) Prec@1 83.000 (87.833) Prec@5 100.000 (99.278) +2022-11-14 14:50:44,236 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 88.000 (87.842) Prec@5 99.000 (99.263) +2022-11-14 14:50:44,248 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0750) Prec@1 87.000 (87.800) Prec@5 99.000 (99.250) +2022-11-14 14:50:44,259 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0753) Prec@1 89.000 (87.857) Prec@5 99.000 (99.238) +2022-11-14 14:50:44,268 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0758) Prec@1 85.000 (87.727) Prec@5 97.000 (99.136) +2022-11-14 14:50:44,279 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0767) Prec@1 85.000 (87.609) Prec@5 98.000 (99.087) +2022-11-14 14:50:44,290 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0769) Prec@1 87.000 (87.583) Prec@5 100.000 (99.125) +2022-11-14 14:50:44,300 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0775) Prec@1 84.000 (87.440) Prec@5 99.000 (99.120) +2022-11-14 14:50:44,310 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0787) Prec@1 85.000 (87.346) Prec@5 99.000 (99.115) +2022-11-14 14:50:44,321 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0777) Prec@1 91.000 (87.481) Prec@5 100.000 (99.148) +2022-11-14 14:50:44,332 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0768) Prec@1 92.000 (87.643) Prec@5 100.000 (99.179) +2022-11-14 14:50:44,342 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0759) Prec@1 92.000 (87.793) Prec@5 99.000 (99.172) +2022-11-14 14:50:44,351 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0752) Prec@1 91.000 (87.900) Prec@5 100.000 (99.200) +2022-11-14 14:50:44,362 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0745) Prec@1 91.000 (88.000) Prec@5 100.000 (99.226) +2022-11-14 14:50:44,371 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0747) Prec@1 88.000 (88.000) Prec@5 98.000 (99.188) +2022-11-14 14:50:44,381 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0745) Prec@1 91.000 (88.091) Prec@5 99.000 (99.182) +2022-11-14 14:50:44,391 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0748) Prec@1 89.000 (88.118) Prec@5 98.000 (99.147) +2022-11-14 14:50:44,401 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0754) Prec@1 85.000 (88.029) Prec@5 98.000 (99.114) +2022-11-14 14:50:44,411 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0752) Prec@1 91.000 (88.111) Prec@5 100.000 (99.139) +2022-11-14 14:50:44,421 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0753) Prec@1 87.000 (88.081) Prec@5 99.000 (99.135) +2022-11-14 14:50:44,432 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0761) Prec@1 81.000 (87.895) Prec@5 100.000 (99.158) +2022-11-14 14:50:44,442 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0759) Prec@1 89.000 (87.923) Prec@5 99.000 (99.154) +2022-11-14 14:50:44,453 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0755) Prec@1 90.000 (87.975) Prec@5 100.000 (99.175) +2022-11-14 14:50:44,463 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0756) Prec@1 90.000 (88.024) Prec@5 97.000 (99.122) +2022-11-14 14:50:44,474 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0757) Prec@1 87.000 (88.000) Prec@5 98.000 (99.095) +2022-11-14 14:50:44,483 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0376 (0.0748) Prec@1 93.000 (88.116) Prec@5 99.000 (99.093) +2022-11-14 14:50:44,494 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0748) Prec@1 86.000 (88.068) Prec@5 99.000 (99.091) +2022-11-14 14:50:44,504 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0749) Prec@1 88.000 (88.067) Prec@5 99.000 (99.089) +2022-11-14 14:50:44,515 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0754) Prec@1 82.000 (87.935) Prec@5 100.000 (99.109) +2022-11-14 14:50:44,526 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0752) Prec@1 88.000 (87.936) Prec@5 100.000 (99.128) +2022-11-14 14:50:44,537 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0755) Prec@1 86.000 (87.896) Prec@5 99.000 (99.125) +2022-11-14 14:50:44,547 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0749) Prec@1 91.000 (87.959) Prec@5 100.000 (99.143) +2022-11-14 14:50:44,557 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1302 (0.0760) Prec@1 79.000 (87.780) Prec@5 99.000 (99.140) +2022-11-14 14:50:44,567 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0757) Prec@1 92.000 (87.863) Prec@5 100.000 (99.157) +2022-11-14 14:50:44,578 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0757) Prec@1 88.000 (87.865) Prec@5 100.000 (99.173) +2022-11-14 14:50:44,588 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0758) Prec@1 87.000 (87.849) Prec@5 100.000 (99.189) +2022-11-14 14:50:44,599 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0759) Prec@1 84.000 (87.778) Prec@5 100.000 (99.204) +2022-11-14 14:50:44,609 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0760) Prec@1 89.000 (87.800) Prec@5 100.000 (99.218) +2022-11-14 14:50:44,620 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0762) Prec@1 88.000 (87.804) Prec@5 99.000 (99.214) +2022-11-14 14:50:44,629 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0758) Prec@1 90.000 (87.842) Prec@5 100.000 (99.228) +2022-11-14 14:50:44,641 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0757) Prec@1 91.000 (87.897) Prec@5 99.000 (99.224) +2022-11-14 14:50:44,650 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0759) Prec@1 85.000 (87.847) Prec@5 100.000 (99.237) +2022-11-14 14:50:44,662 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0761) Prec@1 84.000 (87.783) Prec@5 100.000 (99.250) +2022-11-14 14:50:44,671 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0762) Prec@1 88.000 (87.787) Prec@5 100.000 (99.262) +2022-11-14 14:50:44,682 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0764) Prec@1 87.000 (87.774) Prec@5 99.000 (99.258) +2022-11-14 14:50:44,692 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0761) Prec@1 90.000 (87.810) Prec@5 100.000 (99.270) +2022-11-14 14:50:44,703 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0352 (0.0754) Prec@1 93.000 (87.891) Prec@5 100.000 (99.281) +2022-11-14 14:50:44,714 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0755) Prec@1 89.000 (87.908) Prec@5 100.000 (99.292) +2022-11-14 14:50:44,725 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0752) Prec@1 90.000 (87.939) Prec@5 100.000 (99.303) +2022-11-14 14:50:44,736 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0748) Prec@1 91.000 (87.985) Prec@5 100.000 (99.313) +2022-11-14 14:50:44,748 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0748) Prec@1 89.000 (88.000) Prec@5 99.000 (99.309) +2022-11-14 14:50:44,759 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0749) Prec@1 87.000 (87.986) Prec@5 100.000 (99.319) +2022-11-14 14:50:44,770 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0746) Prec@1 92.000 (88.043) Prec@5 98.000 (99.300) +2022-11-14 14:50:44,781 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0750) Prec@1 86.000 (88.014) Prec@5 99.000 (99.296) +2022-11-14 14:50:44,792 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0749) Prec@1 88.000 (88.014) Prec@5 100.000 (99.306) +2022-11-14 14:50:44,804 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0746) Prec@1 92.000 (88.068) Prec@5 100.000 (99.315) +2022-11-14 14:50:44,815 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0743) Prec@1 91.000 (88.108) Prec@5 100.000 (99.324) +2022-11-14 14:50:44,825 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0745) Prec@1 87.000 (88.093) Prec@5 100.000 (99.333) +2022-11-14 14:50:44,836 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0744) Prec@1 88.000 (88.092) Prec@5 99.000 (99.329) +2022-11-14 14:50:44,847 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0742) Prec@1 87.000 (88.078) Prec@5 98.000 (99.312) +2022-11-14 14:50:44,860 Test: [77/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0746) Prec@1 81.000 (87.987) Prec@5 100.000 (99.321) +2022-11-14 14:50:44,872 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0744) Prec@1 90.000 (88.013) Prec@5 100.000 (99.329) +2022-11-14 14:50:44,881 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0743) Prec@1 88.000 (88.013) Prec@5 100.000 (99.338) +2022-11-14 14:50:44,891 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0745) Prec@1 87.000 (88.000) Prec@5 97.000 (99.309) +2022-11-14 14:50:44,901 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0748) Prec@1 83.000 (87.939) Prec@5 98.000 (99.293) +2022-11-14 14:50:44,912 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0751) Prec@1 85.000 (87.904) Prec@5 100.000 (99.301) +2022-11-14 14:50:44,921 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0749) Prec@1 89.000 (87.917) Prec@5 100.000 (99.310) +2022-11-14 14:50:44,931 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0747) Prec@1 89.000 (87.929) Prec@5 100.000 (99.318) +2022-11-14 14:50:44,940 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0750) Prec@1 85.000 (87.895) Prec@5 100.000 (99.326) +2022-11-14 14:50:44,949 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 86.000 (87.874) Prec@5 99.000 (99.322) +2022-11-14 14:50:44,960 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0752) Prec@1 86.000 (87.852) Prec@5 98.000 (99.307) +2022-11-14 14:50:44,969 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0753) Prec@1 86.000 (87.831) Prec@5 100.000 (99.315) +2022-11-14 14:50:44,980 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0754) Prec@1 88.000 (87.833) Prec@5 99.000 (99.311) +2022-11-14 14:50:44,991 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0752) Prec@1 89.000 (87.846) Prec@5 99.000 (99.308) +2022-11-14 14:50:45,002 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0749) Prec@1 90.000 (87.870) Prec@5 100.000 (99.315) +2022-11-14 14:50:45,012 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0748) Prec@1 89.000 (87.882) Prec@5 100.000 (99.323) +2022-11-14 14:50:45,023 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0748) Prec@1 89.000 (87.894) Prec@5 99.000 (99.319) +2022-11-14 14:50:45,032 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0747) Prec@1 87.000 (87.884) Prec@5 100.000 (99.326) +2022-11-14 14:50:45,043 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0746) Prec@1 89.000 (87.896) Prec@5 99.000 (99.323) +2022-11-14 14:50:45,053 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0744) Prec@1 89.000 (87.907) Prec@5 99.000 (99.320) +2022-11-14 14:50:45,064 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0745) Prec@1 87.000 (87.898) Prec@5 97.000 (99.296) +2022-11-14 14:50:45,072 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0747) Prec@1 85.000 (87.869) Prec@5 99.000 (99.293) +2022-11-14 14:50:45,082 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0747) Prec@1 87.000 (87.860) Prec@5 100.000 (99.300) +2022-11-14 14:50:45,141 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:50:45,465 Epoch: [263][0/500] Time 0.023 (0.023) Data 0.238 (0.238) Loss 0.0346 (0.0346) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:50:45,676 Epoch: [263][10/500] Time 0.018 (0.019) Data 0.002 (0.023) Loss 0.0532 (0.0439) Prec@1 91.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 14:50:45,893 Epoch: [263][20/500] Time 0.021 (0.019) Data 0.002 (0.013) Loss 0.0353 (0.0411) Prec@1 93.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 14:50:46,213 Epoch: [263][30/500] Time 0.034 (0.022) Data 0.002 (0.009) Loss 0.0165 (0.0349) Prec@1 99.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 14:50:46,682 Epoch: [263][40/500] Time 0.043 (0.027) Data 0.002 (0.008) Loss 0.0381 (0.0356) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:50:47,085 Epoch: [263][50/500] Time 0.026 (0.029) Data 0.002 (0.006) Loss 0.0293 (0.0345) Prec@1 95.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 14:50:47,472 Epoch: [263][60/500] Time 0.037 (0.029) Data 0.002 (0.006) Loss 0.0284 (0.0336) Prec@1 94.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 14:50:47,858 Epoch: [263][70/500] Time 0.040 (0.030) Data 0.002 (0.005) Loss 0.0225 (0.0322) Prec@1 97.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 14:50:48,272 Epoch: [263][80/500] Time 0.028 (0.031) Data 0.002 (0.005) Loss 0.0319 (0.0322) Prec@1 94.000 (94.667) Prec@5 99.000 (99.778) +2022-11-14 14:50:48,751 Epoch: [263][90/500] Time 0.044 (0.032) Data 0.002 (0.005) Loss 0.0457 (0.0336) Prec@1 91.000 (94.300) Prec@5 100.000 (99.800) +2022-11-14 14:50:49,215 Epoch: [263][100/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0322 (0.0334) Prec@1 95.000 (94.364) Prec@5 100.000 (99.818) +2022-11-14 14:50:49,568 Epoch: [263][110/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0329 (0.0334) Prec@1 93.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:50:49,941 Epoch: [263][120/500] Time 0.035 (0.033) Data 0.002 (0.004) Loss 0.0226 (0.0326) Prec@1 97.000 (94.462) Prec@5 100.000 (99.769) +2022-11-14 14:50:50,320 Epoch: [263][130/500] Time 0.035 (0.033) Data 0.001 (0.004) Loss 0.0148 (0.0313) Prec@1 98.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 14:50:50,700 Epoch: [263][140/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0285 (0.0311) Prec@1 94.000 (94.667) Prec@5 100.000 (99.800) +2022-11-14 14:50:51,103 Epoch: [263][150/500] Time 0.043 (0.033) Data 0.002 (0.004) Loss 0.0226 (0.0306) Prec@1 95.000 (94.688) Prec@5 99.000 (99.750) +2022-11-14 14:50:51,473 Epoch: [263][160/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0537 (0.0319) Prec@1 91.000 (94.471) Prec@5 99.000 (99.706) +2022-11-14 14:50:51,850 Epoch: [263][170/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0303 (0.0318) Prec@1 95.000 (94.500) Prec@5 100.000 (99.722) +2022-11-14 14:50:52,228 Epoch: [263][180/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0339 (0.0320) Prec@1 93.000 (94.421) Prec@5 100.000 (99.737) +2022-11-14 14:50:52,616 Epoch: [263][190/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0322 (0.0320) Prec@1 96.000 (94.500) Prec@5 99.000 (99.700) +2022-11-14 14:50:53,021 Epoch: [263][200/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0391 (0.0323) Prec@1 94.000 (94.476) Prec@5 100.000 (99.714) +2022-11-14 14:50:53,394 Epoch: [263][210/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0406 (0.0327) Prec@1 96.000 (94.545) Prec@5 100.000 (99.727) +2022-11-14 14:50:53,779 Epoch: [263][220/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0355 (0.0328) Prec@1 94.000 (94.522) Prec@5 100.000 (99.739) +2022-11-14 14:50:54,200 Epoch: [263][230/500] Time 0.042 (0.034) Data 0.002 (0.003) Loss 0.0768 (0.0346) Prec@1 88.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 14:50:54,567 Epoch: [263][240/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0170 (0.0339) Prec@1 97.000 (94.360) Prec@5 100.000 (99.760) +2022-11-14 14:50:54,938 Epoch: [263][250/500] Time 0.035 (0.034) Data 0.001 (0.003) Loss 0.0335 (0.0339) Prec@1 94.000 (94.346) Prec@5 100.000 (99.769) +2022-11-14 14:50:55,357 Epoch: [263][260/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0376 (0.0340) Prec@1 95.000 (94.370) Prec@5 99.000 (99.741) +2022-11-14 14:50:55,721 Epoch: [263][270/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0346 (0.0341) Prec@1 93.000 (94.321) Prec@5 100.000 (99.750) +2022-11-14 14:50:56,097 Epoch: [263][280/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0244 (0.0337) Prec@1 97.000 (94.414) Prec@5 100.000 (99.759) +2022-11-14 14:50:56,474 Epoch: [263][290/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0272 (0.0335) Prec@1 97.000 (94.500) Prec@5 100.000 (99.767) +2022-11-14 14:50:56,885 Epoch: [263][300/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0535 (0.0342) Prec@1 90.000 (94.355) Prec@5 100.000 (99.774) +2022-11-14 14:50:57,255 Epoch: [263][310/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0257 (0.0339) Prec@1 97.000 (94.438) Prec@5 99.000 (99.750) +2022-11-14 14:50:57,636 Epoch: [263][320/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0357 (0.0340) Prec@1 95.000 (94.455) Prec@5 100.000 (99.758) +2022-11-14 14:50:58,036 Epoch: [263][330/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0542 (0.0345) Prec@1 90.000 (94.324) Prec@5 99.000 (99.735) +2022-11-14 14:50:58,449 Epoch: [263][340/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0644 (0.0354) Prec@1 88.000 (94.143) Prec@5 99.000 (99.714) +2022-11-14 14:50:58,827 Epoch: [263][350/500] Time 0.039 (0.034) Data 0.002 (0.003) Loss 0.0186 (0.0349) Prec@1 97.000 (94.222) Prec@5 99.000 (99.694) +2022-11-14 14:50:59,262 Epoch: [263][360/500] Time 0.051 (0.034) Data 0.002 (0.003) Loss 0.0318 (0.0348) Prec@1 95.000 (94.243) Prec@5 100.000 (99.703) +2022-11-14 14:50:59,695 Epoch: [263][370/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0428 (0.0351) Prec@1 90.000 (94.132) Prec@5 100.000 (99.711) +2022-11-14 14:51:00,097 Epoch: [263][380/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0243 (0.0348) Prec@1 94.000 (94.128) Prec@5 100.000 (99.718) +2022-11-14 14:51:00,490 Epoch: [263][390/500] Time 0.037 (0.034) Data 0.002 (0.003) Loss 0.0217 (0.0345) Prec@1 97.000 (94.200) Prec@5 100.000 (99.725) +2022-11-14 14:51:00,872 Epoch: [263][400/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0371 (0.0345) Prec@1 93.000 (94.171) Prec@5 99.000 (99.707) +2022-11-14 14:51:01,262 Epoch: [263][410/500] Time 0.030 (0.034) Data 0.002 (0.003) Loss 0.0229 (0.0342) Prec@1 97.000 (94.238) Prec@5 100.000 (99.714) +2022-11-14 14:51:01,655 Epoch: [263][420/500] Time 0.046 (0.034) Data 0.002 (0.002) Loss 0.0196 (0.0339) Prec@1 97.000 (94.302) Prec@5 100.000 (99.721) +2022-11-14 14:51:02,032 Epoch: [263][430/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0297 (0.0338) Prec@1 96.000 (94.341) Prec@5 100.000 (99.727) +2022-11-14 14:51:02,421 Epoch: [263][440/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0373 (0.0339) Prec@1 93.000 (94.311) Prec@5 100.000 (99.733) +2022-11-14 14:51:02,868 Epoch: [263][450/500] Time 0.043 (0.034) Data 0.002 (0.002) Loss 0.0411 (0.0340) Prec@1 93.000 (94.283) Prec@5 100.000 (99.739) +2022-11-14 14:51:03,287 Epoch: [263][460/500] Time 0.029 (0.035) Data 0.002 (0.002) Loss 0.0358 (0.0341) Prec@1 95.000 (94.298) Prec@5 100.000 (99.745) +2022-11-14 14:51:03,677 Epoch: [263][470/500] Time 0.047 (0.035) Data 0.002 (0.002) Loss 0.0499 (0.0344) Prec@1 91.000 (94.229) Prec@5 100.000 (99.750) +2022-11-14 14:51:04,049 Epoch: [263][480/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0356 (0.0344) Prec@1 96.000 (94.265) Prec@5 99.000 (99.735) +2022-11-14 14:51:04,439 Epoch: [263][490/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0188 (0.0341) Prec@1 98.000 (94.340) Prec@5 100.000 (99.740) +2022-11-14 14:51:04,792 Epoch: [263][499/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0208 (0.0339) Prec@1 97.000 (94.392) Prec@5 100.000 (99.745) +2022-11-14 14:51:05,078 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0634) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:51:05,088 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0539 (0.0586) Prec@1 92.000 (90.500) Prec@5 99.000 (99.000) +2022-11-14 14:51:05,098 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0639) Prec@1 88.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 14:51:05,112 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0664) Prec@1 87.000 (89.000) Prec@5 99.000 (99.250) +2022-11-14 14:51:05,123 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0674) Prec@1 89.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 14:51:05,133 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0655) Prec@1 91.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 14:51:05,142 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0628) Prec@1 93.000 (89.857) Prec@5 100.000 (99.571) +2022-11-14 14:51:05,156 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0662) Prec@1 85.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 14:51:05,167 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0706) Prec@1 83.000 (88.556) Prec@5 98.000 (99.444) +2022-11-14 14:51:05,181 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0709) Prec@1 87.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 14:51:05,196 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0696) Prec@1 90.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 14:51:05,209 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0704) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:51:05,223 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0686) Prec@1 94.000 (88.923) Prec@5 100.000 (99.538) +2022-11-14 14:51:05,238 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0688) Prec@1 88.000 (88.857) Prec@5 100.000 (99.571) +2022-11-14 14:51:05,251 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0695) Prec@1 87.000 (88.733) Prec@5 99.000 (99.533) +2022-11-14 14:51:05,265 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0704) Prec@1 90.000 (88.812) Prec@5 98.000 (99.438) +2022-11-14 14:51:05,279 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0696) Prec@1 91.000 (88.941) Prec@5 99.000 (99.412) +2022-11-14 14:51:05,293 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0718) Prec@1 83.000 (88.611) Prec@5 100.000 (99.444) +2022-11-14 14:51:05,307 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0720) Prec@1 87.000 (88.526) Prec@5 99.000 (99.421) +2022-11-14 14:51:05,322 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0729) Prec@1 85.000 (88.350) Prec@5 100.000 (99.450) +2022-11-14 14:51:05,335 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0724) Prec@1 90.000 (88.429) Prec@5 98.000 (99.381) +2022-11-14 14:51:05,349 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0732) Prec@1 84.000 (88.227) Prec@5 100.000 (99.409) +2022-11-14 14:51:05,362 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0743) Prec@1 85.000 (88.087) Prec@5 98.000 (99.348) +2022-11-14 14:51:05,376 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0744) Prec@1 86.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 14:51:05,391 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0747) Prec@1 85.000 (87.880) Prec@5 100.000 (99.360) +2022-11-14 14:51:05,404 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0742) Prec@1 91.000 (88.000) Prec@5 100.000 (99.385) +2022-11-14 14:51:05,418 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0503 (0.0733) Prec@1 91.000 (88.111) Prec@5 100.000 (99.407) +2022-11-14 14:51:05,432 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0727) Prec@1 90.000 (88.179) Prec@5 100.000 (99.429) +2022-11-14 14:51:05,446 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0728) Prec@1 88.000 (88.172) Prec@5 99.000 (99.414) +2022-11-14 14:51:05,461 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0720) Prec@1 92.000 (88.300) Prec@5 98.000 (99.367) +2022-11-14 14:51:05,474 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0717) Prec@1 89.000 (88.323) Prec@5 100.000 (99.387) +2022-11-14 14:51:05,488 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0717) Prec@1 90.000 (88.375) Prec@5 97.000 (99.312) +2022-11-14 14:51:05,502 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0719) Prec@1 85.000 (88.273) Prec@5 99.000 (99.303) +2022-11-14 14:51:05,516 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0727) Prec@1 81.000 (88.059) Prec@5 99.000 (99.294) +2022-11-14 14:51:05,530 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0731) Prec@1 85.000 (87.971) Prec@5 98.000 (99.257) +2022-11-14 14:51:05,544 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0727) Prec@1 92.000 (88.083) Prec@5 99.000 (99.250) +2022-11-14 14:51:05,558 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0728) Prec@1 88.000 (88.081) Prec@5 99.000 (99.243) +2022-11-14 14:51:05,572 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0731) Prec@1 87.000 (88.053) Prec@5 100.000 (99.263) +2022-11-14 14:51:05,589 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0726) Prec@1 90.000 (88.103) Prec@5 99.000 (99.256) +2022-11-14 14:51:05,605 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0724) Prec@1 89.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 14:51:05,621 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0731) Prec@1 85.000 (88.049) Prec@5 97.000 (99.195) +2022-11-14 14:51:05,638 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0729) Prec@1 89.000 (88.071) Prec@5 100.000 (99.214) +2022-11-14 14:51:05,655 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0723) Prec@1 93.000 (88.186) Prec@5 98.000 (99.186) +2022-11-14 14:51:05,668 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0723) Prec@1 89.000 (88.205) Prec@5 98.000 (99.159) +2022-11-14 14:51:05,681 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0721) Prec@1 91.000 (88.267) Prec@5 100.000 (99.178) +2022-11-14 14:51:05,697 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0724) Prec@1 87.000 (88.239) Prec@5 100.000 (99.196) +2022-11-14 14:51:05,713 Test: [46/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0721) Prec@1 91.000 (88.298) Prec@5 100.000 (99.213) +2022-11-14 14:51:05,729 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0726) Prec@1 85.000 (88.229) Prec@5 98.000 (99.188) +2022-11-14 14:51:05,743 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0721) Prec@1 93.000 (88.327) Prec@5 100.000 (99.204) +2022-11-14 14:51:05,760 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0729) Prec@1 83.000 (88.220) Prec@5 100.000 (99.220) +2022-11-14 14:51:05,775 Test: [50/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0726) Prec@1 93.000 (88.314) Prec@5 99.000 (99.216) +2022-11-14 14:51:05,791 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0728) Prec@1 87.000 (88.288) Prec@5 100.000 (99.231) +2022-11-14 14:51:05,805 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0730) Prec@1 86.000 (88.245) Prec@5 100.000 (99.245) +2022-11-14 14:51:05,820 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0735) Prec@1 85.000 (88.185) Prec@5 99.000 (99.241) +2022-11-14 14:51:05,834 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0737) Prec@1 83.000 (88.091) Prec@5 99.000 (99.236) +2022-11-14 14:51:05,848 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0735) Prec@1 92.000 (88.161) Prec@5 99.000 (99.232) +2022-11-14 14:51:05,862 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0734) Prec@1 89.000 (88.175) Prec@5 100.000 (99.246) +2022-11-14 14:51:05,877 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0735) Prec@1 89.000 (88.190) Prec@5 100.000 (99.259) +2022-11-14 14:51:05,891 Test: [58/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1199 (0.0742) Prec@1 79.000 (88.034) Prec@5 99.000 (99.254) +2022-11-14 14:51:05,905 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0740) Prec@1 89.000 (88.050) Prec@5 100.000 (99.267) +2022-11-14 14:51:05,919 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0738) Prec@1 90.000 (88.082) Prec@5 100.000 (99.279) +2022-11-14 14:51:05,932 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0736) Prec@1 89.000 (88.097) Prec@5 99.000 (99.274) +2022-11-14 14:51:05,946 Test: [62/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0736) Prec@1 89.000 (88.111) Prec@5 100.000 (99.286) +2022-11-14 14:51:05,960 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0404 (0.0731) Prec@1 93.000 (88.188) Prec@5 99.000 (99.281) +2022-11-14 14:51:05,974 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0734) Prec@1 84.000 (88.123) Prec@5 99.000 (99.277) +2022-11-14 14:51:05,987 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0736) Prec@1 82.000 (88.030) Prec@5 100.000 (99.288) +2022-11-14 14:51:06,002 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0733) Prec@1 91.000 (88.075) Prec@5 100.000 (99.299) +2022-11-14 14:51:06,016 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0730) Prec@1 92.000 (88.132) Prec@5 99.000 (99.294) +2022-11-14 14:51:06,030 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0730) Prec@1 86.000 (88.101) Prec@5 99.000 (99.290) +2022-11-14 14:51:06,043 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0731) Prec@1 86.000 (88.071) Prec@5 99.000 (99.286) +2022-11-14 14:51:06,058 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0733) Prec@1 88.000 (88.070) Prec@5 98.000 (99.268) +2022-11-14 14:51:06,073 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0733) Prec@1 89.000 (88.083) Prec@5 100.000 (99.278) +2022-11-14 14:51:06,087 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0729) Prec@1 92.000 (88.137) Prec@5 100.000 (99.288) +2022-11-14 14:51:06,101 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0396 (0.0725) Prec@1 93.000 (88.203) Prec@5 100.000 (99.297) +2022-11-14 14:51:06,114 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0726) Prec@1 85.000 (88.160) Prec@5 98.000 (99.280) +2022-11-14 14:51:06,128 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0723) Prec@1 91.000 (88.197) Prec@5 100.000 (99.289) +2022-11-14 14:51:06,141 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0724) Prec@1 88.000 (88.195) Prec@5 98.000 (99.273) +2022-11-14 14:51:06,156 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0725) Prec@1 89.000 (88.205) Prec@5 99.000 (99.269) +2022-11-14 14:51:06,173 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0723) Prec@1 91.000 (88.241) Prec@5 100.000 (99.278) +2022-11-14 14:51:06,189 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0722) Prec@1 92.000 (88.287) Prec@5 99.000 (99.275) +2022-11-14 14:51:06,204 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0720) Prec@1 88.000 (88.284) Prec@5 100.000 (99.284) +2022-11-14 14:51:06,221 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0723) Prec@1 83.000 (88.220) Prec@5 99.000 (99.280) +2022-11-14 14:51:06,237 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0724) Prec@1 86.000 (88.193) Prec@5 100.000 (99.289) +2022-11-14 14:51:06,252 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0725) Prec@1 87.000 (88.179) Prec@5 99.000 (99.286) +2022-11-14 14:51:06,266 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0729) Prec@1 84.000 (88.129) Prec@5 100.000 (99.294) +2022-11-14 14:51:06,280 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0732) Prec@1 82.000 (88.058) Prec@5 100.000 (99.302) +2022-11-14 14:51:06,293 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0735) Prec@1 84.000 (88.011) Prec@5 99.000 (99.299) +2022-11-14 14:51:06,307 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0733) Prec@1 90.000 (88.034) Prec@5 99.000 (99.295) +2022-11-14 14:51:06,320 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0731) Prec@1 89.000 (88.045) Prec@5 99.000 (99.292) +2022-11-14 14:51:06,335 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0732) Prec@1 87.000 (88.033) Prec@5 99.000 (99.289) +2022-11-14 14:51:06,348 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0731) Prec@1 90.000 (88.055) Prec@5 100.000 (99.297) +2022-11-14 14:51:06,362 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0729) Prec@1 91.000 (88.087) Prec@5 100.000 (99.304) +2022-11-14 14:51:06,376 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0730) Prec@1 85.000 (88.054) Prec@5 100.000 (99.312) +2022-11-14 14:51:06,390 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0730) Prec@1 88.000 (88.053) Prec@5 100.000 (99.319) +2022-11-14 14:51:06,403 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0730) Prec@1 88.000 (88.053) Prec@5 99.000 (99.316) +2022-11-14 14:51:06,416 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0728) Prec@1 91.000 (88.083) Prec@5 99.000 (99.312) +2022-11-14 14:51:06,431 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0727) Prec@1 92.000 (88.124) Prec@5 99.000 (99.309) +2022-11-14 14:51:06,445 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0728) Prec@1 86.000 (88.102) Prec@5 98.000 (99.296) +2022-11-14 14:51:06,461 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0732) Prec@1 88.000 (88.101) Prec@5 100.000 (99.303) +2022-11-14 14:51:06,479 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0731) Prec@1 88.000 (88.100) Prec@5 100.000 (99.310) +2022-11-14 14:51:06,540 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:51:06,846 Epoch: [264][0/500] Time 0.027 (0.027) Data 0.218 (0.218) Loss 0.0166 (0.0166) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:07,173 Epoch: [264][10/500] Time 0.036 (0.029) Data 0.002 (0.022) Loss 0.0231 (0.0199) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 14:51:07,546 Epoch: [264][20/500] Time 0.034 (0.031) Data 0.002 (0.012) Loss 0.0369 (0.0255) Prec@1 93.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 14:51:07,933 Epoch: [264][30/500] Time 0.035 (0.032) Data 0.002 (0.009) Loss 0.0518 (0.0321) Prec@1 92.000 (94.500) Prec@5 99.000 (99.750) +2022-11-14 14:51:08,316 Epoch: [264][40/500] Time 0.034 (0.032) Data 0.002 (0.007) Loss 0.0572 (0.0371) Prec@1 88.000 (93.200) Prec@5 100.000 (99.800) +2022-11-14 14:51:08,704 Epoch: [264][50/500] Time 0.034 (0.033) Data 0.002 (0.006) Loss 0.0156 (0.0335) Prec@1 98.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 14:51:09,092 Epoch: [264][60/500] Time 0.036 (0.033) Data 0.002 (0.006) Loss 0.0404 (0.0345) Prec@1 94.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 14:51:09,469 Epoch: [264][70/500] Time 0.037 (0.033) Data 0.002 (0.005) Loss 0.0288 (0.0338) Prec@1 95.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 14:51:09,856 Epoch: [264][80/500] Time 0.035 (0.033) Data 0.002 (0.005) Loss 0.0216 (0.0324) Prec@1 96.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 14:51:10,241 Epoch: [264][90/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0312 (0.0323) Prec@1 95.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 14:51:10,623 Epoch: [264][100/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.0641 (0.0352) Prec@1 90.000 (94.000) Prec@5 99.000 (99.818) +2022-11-14 14:51:11,001 Epoch: [264][110/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0488 (0.0363) Prec@1 92.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 14:51:11,387 Epoch: [264][120/500] Time 0.034 (0.033) Data 0.002 (0.004) Loss 0.0361 (0.0363) Prec@1 95.000 (93.923) Prec@5 99.000 (99.769) +2022-11-14 14:51:11,765 Epoch: [264][130/500] Time 0.034 (0.033) Data 0.001 (0.004) Loss 0.0313 (0.0360) Prec@1 95.000 (94.000) Prec@5 100.000 (99.786) +2022-11-14 14:51:12,151 Epoch: [264][140/500] Time 0.031 (0.033) Data 0.003 (0.004) Loss 0.0386 (0.0361) Prec@1 92.000 (93.867) Prec@5 100.000 (99.800) +2022-11-14 14:51:12,524 Epoch: [264][150/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0354 (0.0361) Prec@1 94.000 (93.875) Prec@5 100.000 (99.812) +2022-11-14 14:51:12,898 Epoch: [264][160/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0253 (0.0355) Prec@1 95.000 (93.941) Prec@5 99.000 (99.765) +2022-11-14 14:51:13,268 Epoch: [264][170/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0202 (0.0346) Prec@1 98.000 (94.167) Prec@5 100.000 (99.778) +2022-11-14 14:51:13,655 Epoch: [264][180/500] Time 0.032 (0.033) Data 0.002 (0.003) Loss 0.0239 (0.0340) Prec@1 97.000 (94.316) Prec@5 99.000 (99.737) +2022-11-14 14:51:14,031 Epoch: [264][190/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0529 (0.0350) Prec@1 92.000 (94.200) Prec@5 99.000 (99.700) +2022-11-14 14:51:14,417 Epoch: [264][200/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0308 (0.0348) Prec@1 96.000 (94.286) Prec@5 99.000 (99.667) +2022-11-14 14:51:14,800 Epoch: [264][210/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0302 (0.0346) Prec@1 94.000 (94.273) Prec@5 99.000 (99.636) +2022-11-14 14:51:15,183 Epoch: [264][220/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0311 (0.0344) Prec@1 95.000 (94.304) Prec@5 100.000 (99.652) +2022-11-14 14:51:15,570 Epoch: [264][230/500] Time 0.033 (0.034) Data 0.002 (0.003) Loss 0.0258 (0.0341) Prec@1 97.000 (94.417) Prec@5 100.000 (99.667) +2022-11-14 14:51:15,943 Epoch: [264][240/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0258 (0.0337) Prec@1 96.000 (94.480) Prec@5 100.000 (99.680) +2022-11-14 14:51:16,317 Epoch: [264][250/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0170 (0.0331) Prec@1 98.000 (94.615) Prec@5 100.000 (99.692) +2022-11-14 14:51:16,696 Epoch: [264][260/500] Time 0.033 (0.033) Data 0.002 (0.003) Loss 0.0136 (0.0324) Prec@1 99.000 (94.778) Prec@5 100.000 (99.704) +2022-11-14 14:51:17,080 Epoch: [264][270/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0504 (0.0330) Prec@1 89.000 (94.571) Prec@5 100.000 (99.714) +2022-11-14 14:51:17,450 Epoch: [264][280/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0363 (0.0331) Prec@1 94.000 (94.552) Prec@5 99.000 (99.690) +2022-11-14 14:51:17,833 Epoch: [264][290/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0349 (0.0332) Prec@1 93.000 (94.500) Prec@5 99.000 (99.667) +2022-11-14 14:51:18,218 Epoch: [264][300/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0434 (0.0335) Prec@1 93.000 (94.452) Prec@5 100.000 (99.677) +2022-11-14 14:51:18,605 Epoch: [264][310/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0246 (0.0332) Prec@1 95.000 (94.469) Prec@5 100.000 (99.688) +2022-11-14 14:51:18,986 Epoch: [264][320/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0187 (0.0328) Prec@1 97.000 (94.545) Prec@5 100.000 (99.697) +2022-11-14 14:51:19,370 Epoch: [264][330/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0314 (0.0328) Prec@1 94.000 (94.529) Prec@5 100.000 (99.706) +2022-11-14 14:51:19,759 Epoch: [264][340/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0277 (0.0326) Prec@1 97.000 (94.600) Prec@5 100.000 (99.714) +2022-11-14 14:51:20,143 Epoch: [264][350/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0266 (0.0324) Prec@1 97.000 (94.667) Prec@5 100.000 (99.722) +2022-11-14 14:51:20,522 Epoch: [264][360/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0313 (0.0324) Prec@1 95.000 (94.676) Prec@5 100.000 (99.730) +2022-11-14 14:51:20,907 Epoch: [264][370/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0529 (0.0329) Prec@1 90.000 (94.553) Prec@5 99.000 (99.711) +2022-11-14 14:51:21,293 Epoch: [264][380/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0361 (0.0330) Prec@1 95.000 (94.564) Prec@5 100.000 (99.718) +2022-11-14 14:51:21,672 Epoch: [264][390/500] Time 0.039 (0.034) Data 0.002 (0.002) Loss 0.0227 (0.0328) Prec@1 95.000 (94.575) Prec@5 100.000 (99.725) +2022-11-14 14:51:22,049 Epoch: [264][400/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0219 (0.0325) Prec@1 97.000 (94.634) Prec@5 100.000 (99.732) +2022-11-14 14:51:22,429 Epoch: [264][410/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0360 (0.0326) Prec@1 94.000 (94.619) Prec@5 100.000 (99.738) +2022-11-14 14:51:22,816 Epoch: [264][420/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0421 (0.0328) Prec@1 92.000 (94.558) Prec@5 100.000 (99.744) +2022-11-14 14:51:23,202 Epoch: [264][430/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0324 (0.0328) Prec@1 95.000 (94.568) Prec@5 99.000 (99.727) +2022-11-14 14:51:23,591 Epoch: [264][440/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.0756 (0.0338) Prec@1 88.000 (94.422) Prec@5 98.000 (99.689) +2022-11-14 14:51:23,956 Epoch: [264][450/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0389 (0.0339) Prec@1 94.000 (94.413) Prec@5 100.000 (99.696) +2022-11-14 14:51:24,338 Epoch: [264][460/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0318 (0.0338) Prec@1 95.000 (94.426) Prec@5 100.000 (99.702) +2022-11-14 14:51:24,725 Epoch: [264][470/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0451 (0.0341) Prec@1 91.000 (94.354) Prec@5 99.000 (99.688) +2022-11-14 14:51:25,111 Epoch: [264][480/500] Time 0.041 (0.034) Data 0.002 (0.002) Loss 0.0401 (0.0342) Prec@1 93.000 (94.327) Prec@5 99.000 (99.673) +2022-11-14 14:51:25,490 Epoch: [264][490/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0319 (0.0341) Prec@1 95.000 (94.340) Prec@5 100.000 (99.680) +2022-11-14 14:51:25,831 Epoch: [264][499/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0162 (0.0338) Prec@1 98.000 (94.412) Prec@5 100.000 (99.686) +2022-11-14 14:51:26,106 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0623 (0.0623) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:51:26,117 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0688) Prec@1 88.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 14:51:26,126 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0715) Prec@1 88.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 14:51:26,140 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0681) Prec@1 91.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 14:51:26,150 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0716) Prec@1 85.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 14:51:26,160 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0521 (0.0684) Prec@1 92.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:51:26,170 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0673) Prec@1 90.000 (88.857) Prec@5 99.000 (99.571) +2022-11-14 14:51:26,184 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0687) Prec@1 87.000 (88.625) Prec@5 99.000 (99.500) +2022-11-14 14:51:26,194 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0703) Prec@1 89.000 (88.667) Prec@5 99.000 (99.444) +2022-11-14 14:51:26,206 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0704) Prec@1 88.000 (88.600) Prec@5 99.000 (99.400) +2022-11-14 14:51:26,221 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0686) Prec@1 92.000 (88.909) Prec@5 100.000 (99.455) +2022-11-14 14:51:26,234 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0717) Prec@1 82.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 14:51:26,249 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0702) Prec@1 92.000 (88.615) Prec@5 100.000 (99.538) +2022-11-14 14:51:26,265 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0714) Prec@1 86.000 (88.429) Prec@5 99.000 (99.500) +2022-11-14 14:51:26,278 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0712) Prec@1 89.000 (88.467) Prec@5 100.000 (99.533) +2022-11-14 14:51:26,291 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0720) Prec@1 85.000 (88.250) Prec@5 96.000 (99.312) +2022-11-14 14:51:26,307 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0709) Prec@1 92.000 (88.471) Prec@5 98.000 (99.235) +2022-11-14 14:51:26,320 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.0744) Prec@1 77.000 (87.833) Prec@5 100.000 (99.278) +2022-11-14 14:51:26,333 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0744) Prec@1 88.000 (87.842) Prec@5 98.000 (99.211) +2022-11-14 14:51:26,348 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0758) Prec@1 83.000 (87.600) Prec@5 97.000 (99.100) +2022-11-14 14:51:26,362 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0761) Prec@1 88.000 (87.619) Prec@5 100.000 (99.143) +2022-11-14 14:51:26,375 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0759) Prec@1 88.000 (87.636) Prec@5 99.000 (99.136) +2022-11-14 14:51:26,391 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1210 (0.0779) Prec@1 79.000 (87.261) Prec@5 99.000 (99.130) +2022-11-14 14:51:26,405 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0776) Prec@1 87.000 (87.250) Prec@5 99.000 (99.125) +2022-11-14 14:51:26,418 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0784) Prec@1 84.000 (87.120) Prec@5 100.000 (99.160) +2022-11-14 14:51:26,432 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0789) Prec@1 84.000 (87.000) Prec@5 99.000 (99.154) +2022-11-14 14:51:26,446 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0779) Prec@1 90.000 (87.111) Prec@5 100.000 (99.185) +2022-11-14 14:51:26,460 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0773) Prec@1 92.000 (87.286) Prec@5 100.000 (99.214) +2022-11-14 14:51:26,474 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0768) Prec@1 88.000 (87.310) Prec@5 99.000 (99.207) +2022-11-14 14:51:26,488 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0762) Prec@1 90.000 (87.400) Prec@5 99.000 (99.200) +2022-11-14 14:51:26,502 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0757) Prec@1 90.000 (87.484) Prec@5 100.000 (99.226) +2022-11-14 14:51:26,515 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0751) Prec@1 93.000 (87.656) Prec@5 99.000 (99.219) +2022-11-14 14:51:26,529 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0753) Prec@1 87.000 (87.636) Prec@5 100.000 (99.242) +2022-11-14 14:51:26,543 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0759) Prec@1 84.000 (87.529) Prec@5 99.000 (99.235) +2022-11-14 14:51:26,557 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0762) Prec@1 85.000 (87.457) Prec@5 99.000 (99.229) +2022-11-14 14:51:26,571 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0761) Prec@1 89.000 (87.500) Prec@5 99.000 (99.222) +2022-11-14 14:51:26,585 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0759) Prec@1 90.000 (87.568) Prec@5 98.000 (99.189) +2022-11-14 14:51:26,599 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0768) Prec@1 82.000 (87.421) Prec@5 98.000 (99.158) +2022-11-14 14:51:26,613 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0761) Prec@1 94.000 (87.590) Prec@5 100.000 (99.179) +2022-11-14 14:51:26,627 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0761) Prec@1 86.000 (87.550) Prec@5 99.000 (99.175) +2022-11-14 14:51:26,640 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0766) Prec@1 84.000 (87.463) Prec@5 96.000 (99.098) +2022-11-14 14:51:26,654 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0767) Prec@1 88.000 (87.476) Prec@5 99.000 (99.095) +2022-11-14 14:51:26,668 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0395 (0.0758) Prec@1 94.000 (87.628) Prec@5 98.000 (99.070) +2022-11-14 14:51:26,682 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0755) Prec@1 90.000 (87.682) Prec@5 97.000 (99.023) +2022-11-14 14:51:26,696 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0753) Prec@1 90.000 (87.733) Prec@5 100.000 (99.044) +2022-11-14 14:51:26,710 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0754) Prec@1 88.000 (87.739) Prec@5 98.000 (99.022) +2022-11-14 14:51:26,724 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0753) Prec@1 90.000 (87.787) Prec@5 99.000 (99.021) +2022-11-14 14:51:26,737 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1093 (0.0760) Prec@1 81.000 (87.646) Prec@5 99.000 (99.021) +2022-11-14 14:51:26,753 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0753) Prec@1 96.000 (87.816) Prec@5 100.000 (99.041) +2022-11-14 14:51:26,766 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0757) Prec@1 84.000 (87.740) Prec@5 100.000 (99.060) +2022-11-14 14:51:26,781 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0759) Prec@1 85.000 (87.686) Prec@5 100.000 (99.078) +2022-11-14 14:51:26,797 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0756) Prec@1 90.000 (87.731) Prec@5 100.000 (99.096) +2022-11-14 14:51:26,813 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0758) Prec@1 87.000 (87.717) Prec@5 99.000 (99.094) +2022-11-14 14:51:26,829 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0754) Prec@1 91.000 (87.778) Prec@5 100.000 (99.111) +2022-11-14 14:51:26,842 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0756) Prec@1 87.000 (87.764) Prec@5 100.000 (99.127) +2022-11-14 14:51:26,855 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0753) Prec@1 91.000 (87.821) Prec@5 99.000 (99.125) +2022-11-14 14:51:26,869 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0753) Prec@1 84.000 (87.754) Prec@5 100.000 (99.140) +2022-11-14 14:51:26,883 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0753) Prec@1 90.000 (87.793) Prec@5 98.000 (99.121) +2022-11-14 14:51:26,896 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1143 (0.0760) Prec@1 83.000 (87.712) Prec@5 100.000 (99.136) +2022-11-14 14:51:26,909 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0765) Prec@1 83.000 (87.633) Prec@5 100.000 (99.150) +2022-11-14 14:51:26,923 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0769) Prec@1 82.000 (87.541) Prec@5 100.000 (99.164) +2022-11-14 14:51:26,939 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0770) Prec@1 89.000 (87.565) Prec@5 100.000 (99.177) +2022-11-14 14:51:26,955 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0769) Prec@1 86.000 (87.540) Prec@5 99.000 (99.175) +2022-11-14 14:51:26,970 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0376 (0.0762) Prec@1 94.000 (87.641) Prec@5 99.000 (99.172) +2022-11-14 14:51:26,985 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0765) Prec@1 84.000 (87.585) Prec@5 100.000 (99.185) +2022-11-14 14:51:26,998 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0766) Prec@1 85.000 (87.545) Prec@5 98.000 (99.167) +2022-11-14 14:51:27,013 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0763) Prec@1 90.000 (87.582) Prec@5 100.000 (99.179) +2022-11-14 14:51:27,028 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0761) Prec@1 91.000 (87.632) Prec@5 98.000 (99.162) +2022-11-14 14:51:27,041 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0757) Prec@1 90.000 (87.667) Prec@5 100.000 (99.174) +2022-11-14 14:51:27,055 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0761) Prec@1 83.000 (87.600) Prec@5 100.000 (99.186) +2022-11-14 14:51:27,072 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0763) Prec@1 86.000 (87.577) Prec@5 99.000 (99.183) +2022-11-14 14:51:27,086 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0761) Prec@1 88.000 (87.583) Prec@5 100.000 (99.194) +2022-11-14 14:51:27,098 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0760) Prec@1 89.000 (87.603) Prec@5 100.000 (99.205) +2022-11-14 14:51:27,112 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0304 (0.0754) Prec@1 96.000 (87.716) Prec@5 100.000 (99.216) +2022-11-14 14:51:27,127 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0756) Prec@1 84.000 (87.667) Prec@5 100.000 (99.227) +2022-11-14 14:51:27,141 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0756) Prec@1 87.000 (87.658) Prec@5 98.000 (99.211) +2022-11-14 14:51:27,154 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0755) Prec@1 89.000 (87.675) Prec@5 98.000 (99.195) +2022-11-14 14:51:27,168 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0756) Prec@1 88.000 (87.679) Prec@5 98.000 (99.179) +2022-11-14 14:51:27,182 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0755) Prec@1 87.000 (87.671) Prec@5 100.000 (99.190) +2022-11-14 14:51:27,195 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0755) Prec@1 86.000 (87.650) Prec@5 100.000 (99.200) +2022-11-14 14:51:27,207 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0756) Prec@1 88.000 (87.654) Prec@5 97.000 (99.173) +2022-11-14 14:51:27,222 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0758) Prec@1 84.000 (87.610) Prec@5 99.000 (99.171) +2022-11-14 14:51:27,238 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0757) Prec@1 89.000 (87.627) Prec@5 99.000 (99.169) +2022-11-14 14:51:27,252 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0756) Prec@1 88.000 (87.631) Prec@5 99.000 (99.167) +2022-11-14 14:51:27,267 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0757) Prec@1 86.000 (87.612) Prec@5 100.000 (99.176) +2022-11-14 14:51:27,281 Test: [85/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0759) Prec@1 83.000 (87.558) Prec@5 100.000 (99.186) +2022-11-14 14:51:27,294 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0760) Prec@1 88.000 (87.563) Prec@5 99.000 (99.184) +2022-11-14 14:51:27,309 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0760) Prec@1 88.000 (87.568) Prec@5 99.000 (99.182) +2022-11-14 14:51:27,321 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0759) Prec@1 90.000 (87.596) Prec@5 99.000 (99.180) +2022-11-14 14:51:27,335 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0758) Prec@1 89.000 (87.611) Prec@5 98.000 (99.167) +2022-11-14 14:51:27,351 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0755) Prec@1 91.000 (87.648) Prec@5 100.000 (99.176) +2022-11-14 14:51:27,366 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0753) Prec@1 92.000 (87.696) Prec@5 99.000 (99.174) +2022-11-14 14:51:27,381 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0752) Prec@1 89.000 (87.710) Prec@5 100.000 (99.183) +2022-11-14 14:51:27,396 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0755) Prec@1 82.000 (87.649) Prec@5 99.000 (99.181) +2022-11-14 14:51:27,412 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0756) Prec@1 86.000 (87.632) Prec@5 99.000 (99.179) +2022-11-14 14:51:27,427 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0754) Prec@1 92.000 (87.677) Prec@5 100.000 (99.188) +2022-11-14 14:51:27,440 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0751) Prec@1 92.000 (87.722) Prec@5 99.000 (99.186) +2022-11-14 14:51:27,453 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0751) Prec@1 88.000 (87.724) Prec@5 98.000 (99.173) +2022-11-14 14:51:27,467 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0755) Prec@1 84.000 (87.687) Prec@5 100.000 (99.182) +2022-11-14 14:51:27,480 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0756) Prec@1 85.000 (87.660) Prec@5 100.000 (99.190) +2022-11-14 14:51:27,536 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:51:27,845 Epoch: [265][0/500] Time 0.030 (0.030) Data 0.223 (0.223) Loss 0.0207 (0.0207) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:28,085 Epoch: [265][10/500] Time 0.024 (0.022) Data 0.002 (0.022) Loss 0.0377 (0.0292) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:28,350 Epoch: [265][20/500] Time 0.028 (0.022) Data 0.002 (0.012) Loss 0.0220 (0.0268) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 14:51:28,678 Epoch: [265][30/500] Time 0.030 (0.025) Data 0.002 (0.009) Loss 0.0352 (0.0289) Prec@1 94.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 14:51:28,999 Epoch: [265][40/500] Time 0.029 (0.025) Data 0.002 (0.007) Loss 0.0361 (0.0303) Prec@1 94.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 14:51:29,326 Epoch: [265][50/500] Time 0.031 (0.026) Data 0.002 (0.006) Loss 0.0476 (0.0332) Prec@1 92.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 14:51:29,657 Epoch: [265][60/500] Time 0.029 (0.027) Data 0.002 (0.006) Loss 0.0256 (0.0321) Prec@1 95.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 14:51:29,978 Epoch: [265][70/500] Time 0.029 (0.027) Data 0.002 (0.005) Loss 0.0559 (0.0351) Prec@1 90.000 (93.875) Prec@5 99.000 (99.750) +2022-11-14 14:51:30,301 Epoch: [265][80/500] Time 0.030 (0.027) Data 0.002 (0.005) Loss 0.0456 (0.0363) Prec@1 91.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 14:51:30,636 Epoch: [265][90/500] Time 0.029 (0.027) Data 0.002 (0.004) Loss 0.0421 (0.0368) Prec@1 94.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:51:30,966 Epoch: [265][100/500] Time 0.031 (0.028) Data 0.002 (0.004) Loss 0.0200 (0.0353) Prec@1 96.000 (93.818) Prec@5 100.000 (99.818) +2022-11-14 14:51:31,301 Epoch: [265][110/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0305 (0.0349) Prec@1 95.000 (93.917) Prec@5 100.000 (99.833) +2022-11-14 14:51:31,783 Epoch: [265][120/500] Time 0.041 (0.029) Data 0.002 (0.004) Loss 0.0162 (0.0335) Prec@1 98.000 (94.231) Prec@5 100.000 (99.846) +2022-11-14 14:51:32,265 Epoch: [265][130/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.0372 (0.0337) Prec@1 94.000 (94.214) Prec@5 100.000 (99.857) +2022-11-14 14:51:32,746 Epoch: [265][140/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0277 (0.0333) Prec@1 96.000 (94.333) Prec@5 100.000 (99.867) +2022-11-14 14:51:33,228 Epoch: [265][150/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0208 (0.0325) Prec@1 97.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 14:51:33,709 Epoch: [265][160/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0353 (0.0327) Prec@1 94.000 (94.471) Prec@5 98.000 (99.765) +2022-11-14 14:51:34,189 Epoch: [265][170/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0420 (0.0332) Prec@1 93.000 (94.389) Prec@5 100.000 (99.778) +2022-11-14 14:51:34,671 Epoch: [265][180/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0496 (0.0341) Prec@1 91.000 (94.211) Prec@5 99.000 (99.737) +2022-11-14 14:51:35,151 Epoch: [265][190/500] Time 0.047 (0.034) Data 0.002 (0.003) Loss 0.0330 (0.0340) Prec@1 95.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 14:51:35,631 Epoch: [265][200/500] Time 0.053 (0.035) Data 0.002 (0.003) Loss 0.0503 (0.0348) Prec@1 93.000 (94.190) Prec@5 100.000 (99.762) +2022-11-14 14:51:36,112 Epoch: [265][210/500] Time 0.054 (0.035) Data 0.002 (0.003) Loss 0.0433 (0.0352) Prec@1 94.000 (94.182) Prec@5 100.000 (99.773) +2022-11-14 14:51:36,592 Epoch: [265][220/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0389 (0.0354) Prec@1 93.000 (94.130) Prec@5 100.000 (99.783) +2022-11-14 14:51:37,074 Epoch: [265][230/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0239 (0.0349) Prec@1 97.000 (94.250) Prec@5 100.000 (99.792) +2022-11-14 14:51:37,543 Epoch: [265][240/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0306 (0.0347) Prec@1 96.000 (94.320) Prec@5 100.000 (99.800) +2022-11-14 14:51:38,019 Epoch: [265][250/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0330 (0.0346) Prec@1 95.000 (94.346) Prec@5 100.000 (99.808) +2022-11-14 14:51:38,496 Epoch: [265][260/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0384 (0.0348) Prec@1 93.000 (94.296) Prec@5 100.000 (99.815) +2022-11-14 14:51:38,976 Epoch: [265][270/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0496 (0.0353) Prec@1 92.000 (94.214) Prec@5 100.000 (99.821) +2022-11-14 14:51:39,457 Epoch: [265][280/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0315 (0.0352) Prec@1 95.000 (94.241) Prec@5 99.000 (99.793) +2022-11-14 14:51:39,936 Epoch: [265][290/500] Time 0.042 (0.037) Data 0.001 (0.003) Loss 0.0352 (0.0352) Prec@1 95.000 (94.267) Prec@5 100.000 (99.800) +2022-11-14 14:51:40,452 Epoch: [265][300/500] Time 0.058 (0.037) Data 0.001 (0.003) Loss 0.0392 (0.0353) Prec@1 93.000 (94.226) Prec@5 99.000 (99.774) +2022-11-14 14:51:41,010 Epoch: [265][310/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0325 (0.0352) Prec@1 94.000 (94.219) Prec@5 100.000 (99.781) +2022-11-14 14:51:41,633 Epoch: [265][320/500] Time 0.078 (0.038) Data 0.002 (0.003) Loss 0.0310 (0.0351) Prec@1 94.000 (94.212) Prec@5 100.000 (99.788) +2022-11-14 14:51:42,115 Epoch: [265][330/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0745 (0.0363) Prec@1 90.000 (94.088) Prec@5 100.000 (99.794) +2022-11-14 14:51:42,734 Epoch: [265][340/500] Time 0.049 (0.039) Data 0.002 (0.003) Loss 0.0316 (0.0361) Prec@1 95.000 (94.114) Prec@5 100.000 (99.800) +2022-11-14 14:51:43,310 Epoch: [265][350/500] Time 0.083 (0.039) Data 0.002 (0.002) Loss 0.0323 (0.0360) Prec@1 95.000 (94.139) Prec@5 100.000 (99.806) +2022-11-14 14:51:43,780 Epoch: [265][360/500] Time 0.044 (0.039) Data 0.001 (0.002) Loss 0.0250 (0.0357) Prec@1 95.000 (94.162) Prec@5 100.000 (99.811) +2022-11-14 14:51:44,253 Epoch: [265][370/500] Time 0.043 (0.039) Data 0.002 (0.002) Loss 0.0243 (0.0354) Prec@1 96.000 (94.211) Prec@5 100.000 (99.816) +2022-11-14 14:51:44,779 Epoch: [265][380/500] Time 0.073 (0.040) Data 0.002 (0.002) Loss 0.0177 (0.0350) Prec@1 97.000 (94.282) Prec@5 100.000 (99.821) +2022-11-14 14:51:45,343 Epoch: [265][390/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0548 (0.0355) Prec@1 89.000 (94.150) Prec@5 100.000 (99.825) +2022-11-14 14:51:45,929 Epoch: [265][400/500] Time 0.050 (0.040) Data 0.002 (0.002) Loss 0.0380 (0.0355) Prec@1 93.000 (94.122) Prec@5 100.000 (99.829) +2022-11-14 14:51:46,430 Epoch: [265][410/500] Time 0.053 (0.040) Data 0.002 (0.002) Loss 0.0425 (0.0357) Prec@1 93.000 (94.095) Prec@5 100.000 (99.833) +2022-11-14 14:51:46,913 Epoch: [265][420/500] Time 0.051 (0.040) Data 0.002 (0.002) Loss 0.0233 (0.0354) Prec@1 98.000 (94.186) Prec@5 99.000 (99.814) +2022-11-14 14:51:47,447 Epoch: [265][430/500] Time 0.055 (0.041) Data 0.002 (0.002) Loss 0.0437 (0.0356) Prec@1 94.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 14:51:47,980 Epoch: [265][440/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0336 (0.0355) Prec@1 93.000 (94.156) Prec@5 100.000 (99.822) +2022-11-14 14:51:48,493 Epoch: [265][450/500] Time 0.044 (0.041) Data 0.002 (0.002) Loss 0.0391 (0.0356) Prec@1 91.000 (94.087) Prec@5 100.000 (99.826) +2022-11-14 14:51:49,266 Epoch: [265][460/500] Time 0.047 (0.042) Data 0.003 (0.002) Loss 0.0228 (0.0353) Prec@1 96.000 (94.128) Prec@5 100.000 (99.830) +2022-11-14 14:51:49,604 Epoch: [265][470/500] Time 0.032 (0.041) Data 0.002 (0.002) Loss 0.0325 (0.0353) Prec@1 95.000 (94.146) Prec@5 100.000 (99.833) +2022-11-14 14:51:50,034 Epoch: [265][480/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0141 (0.0349) Prec@1 98.000 (94.224) Prec@5 100.000 (99.837) +2022-11-14 14:51:50,369 Epoch: [265][490/500] Time 0.030 (0.041) Data 0.002 (0.002) Loss 0.0170 (0.0345) Prec@1 99.000 (94.320) Prec@5 100.000 (99.840) +2022-11-14 14:51:50,686 Epoch: [265][499/500] Time 0.035 (0.041) Data 0.002 (0.002) Loss 0.0253 (0.0343) Prec@1 95.000 (94.333) Prec@5 100.000 (99.843) +2022-11-14 14:51:50,973 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0581 (0.0581) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:50,982 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0654) Prec@1 87.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 14:51:50,989 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0679) Prec@1 87.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 14:51:51,002 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0698) Prec@1 87.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 14:51:51,012 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0712) Prec@1 88.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 14:51:51,021 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0667) Prec@1 92.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 14:51:51,029 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0654) Prec@1 91.000 (89.143) Prec@5 99.000 (99.429) +2022-11-14 14:51:51,040 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0656) Prec@1 90.000 (89.250) Prec@5 98.000 (99.250) +2022-11-14 14:51:51,048 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0665) Prec@1 88.000 (89.111) Prec@5 100.000 (99.333) +2022-11-14 14:51:51,055 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0659) Prec@1 90.000 (89.200) Prec@5 98.000 (99.200) +2022-11-14 14:51:51,063 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0640) Prec@1 93.000 (89.545) Prec@5 100.000 (99.273) +2022-11-14 14:51:51,072 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0649) Prec@1 88.000 (89.417) Prec@5 100.000 (99.333) +2022-11-14 14:51:51,082 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0638) Prec@1 89.000 (89.385) Prec@5 100.000 (99.385) +2022-11-14 14:51:51,093 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0641) Prec@1 90.000 (89.429) Prec@5 100.000 (99.429) +2022-11-14 14:51:51,104 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0647) Prec@1 86.000 (89.200) Prec@5 100.000 (99.467) +2022-11-14 14:51:51,115 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0640) Prec@1 91.000 (89.312) Prec@5 100.000 (99.500) +2022-11-14 14:51:51,126 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0630) Prec@1 93.000 (89.529) Prec@5 99.000 (99.471) +2022-11-14 14:51:51,136 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0650) Prec@1 86.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 14:51:51,147 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0659) Prec@1 86.000 (89.158) Prec@5 99.000 (99.474) +2022-11-14 14:51:51,158 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0673) Prec@1 84.000 (88.900) Prec@5 97.000 (99.350) +2022-11-14 14:51:51,170 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0676) Prec@1 89.000 (88.905) Prec@5 98.000 (99.286) +2022-11-14 14:51:51,180 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0690) Prec@1 83.000 (88.636) Prec@5 99.000 (99.273) +2022-11-14 14:51:51,191 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0697) Prec@1 88.000 (88.609) Prec@5 98.000 (99.217) +2022-11-14 14:51:51,203 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0695) Prec@1 88.000 (88.583) Prec@5 100.000 (99.250) +2022-11-14 14:51:51,213 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0701) Prec@1 86.000 (88.480) Prec@5 100.000 (99.280) +2022-11-14 14:51:51,223 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0717) Prec@1 83.000 (88.269) Prec@5 98.000 (99.231) +2022-11-14 14:51:51,233 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0711) Prec@1 90.000 (88.333) Prec@5 100.000 (99.259) +2022-11-14 14:51:51,243 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0714) Prec@1 87.000 (88.286) Prec@5 100.000 (99.286) +2022-11-14 14:51:51,254 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0713) Prec@1 88.000 (88.276) Prec@5 99.000 (99.276) +2022-11-14 14:51:51,264 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0707) Prec@1 92.000 (88.400) Prec@5 100.000 (99.300) +2022-11-14 14:51:51,274 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0700) Prec@1 92.000 (88.516) Prec@5 100.000 (99.323) +2022-11-14 14:51:51,284 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0702) Prec@1 88.000 (88.500) Prec@5 100.000 (99.344) +2022-11-14 14:51:51,296 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0706) Prec@1 86.000 (88.424) Prec@5 100.000 (99.364) +2022-11-14 14:51:51,306 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0712) Prec@1 83.000 (88.265) Prec@5 100.000 (99.382) +2022-11-14 14:51:51,316 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0714) Prec@1 86.000 (88.200) Prec@5 99.000 (99.371) +2022-11-14 14:51:51,327 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0715) Prec@1 88.000 (88.194) Prec@5 100.000 (99.389) +2022-11-14 14:51:51,337 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0717) Prec@1 88.000 (88.189) Prec@5 99.000 (99.378) +2022-11-14 14:51:51,348 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0727) Prec@1 78.000 (87.921) Prec@5 100.000 (99.395) +2022-11-14 14:51:51,358 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0722) Prec@1 94.000 (88.077) Prec@5 100.000 (99.410) +2022-11-14 14:51:51,368 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0721) Prec@1 88.000 (88.075) Prec@5 99.000 (99.400) +2022-11-14 14:51:51,378 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0727) Prec@1 85.000 (88.000) Prec@5 96.000 (99.317) +2022-11-14 14:51:51,388 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0726) Prec@1 89.000 (88.024) Prec@5 99.000 (99.310) +2022-11-14 14:51:51,398 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0723) Prec@1 90.000 (88.070) Prec@5 100.000 (99.326) +2022-11-14 14:51:51,408 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0722) Prec@1 89.000 (88.091) Prec@5 99.000 (99.318) +2022-11-14 14:51:51,419 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0724) Prec@1 85.000 (88.022) Prec@5 100.000 (99.333) +2022-11-14 14:51:51,429 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0727) Prec@1 84.000 (87.935) Prec@5 98.000 (99.304) +2022-11-14 14:51:51,440 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0723) Prec@1 93.000 (88.043) Prec@5 100.000 (99.319) +2022-11-14 14:51:51,450 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0730) Prec@1 82.000 (87.917) Prec@5 98.000 (99.292) +2022-11-14 14:51:51,461 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0727) Prec@1 92.000 (88.000) Prec@5 100.000 (99.306) +2022-11-14 14:51:51,471 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0728) Prec@1 88.000 (88.000) Prec@5 100.000 (99.320) +2022-11-14 14:51:51,483 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0727) Prec@1 89.000 (88.020) Prec@5 100.000 (99.333) +2022-11-14 14:51:51,493 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0730) Prec@1 84.000 (87.942) Prec@5 100.000 (99.346) +2022-11-14 14:51:51,504 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0729) Prec@1 89.000 (87.962) Prec@5 99.000 (99.340) +2022-11-14 14:51:51,515 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0730) Prec@1 86.000 (87.926) Prec@5 99.000 (99.333) +2022-11-14 14:51:51,524 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0735) Prec@1 84.000 (87.855) Prec@5 100.000 (99.345) +2022-11-14 14:51:51,535 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0733) Prec@1 91.000 (87.911) Prec@5 99.000 (99.339) +2022-11-14 14:51:51,546 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0732) Prec@1 90.000 (87.947) Prec@5 100.000 (99.351) +2022-11-14 14:51:51,556 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0731) Prec@1 91.000 (88.000) Prec@5 100.000 (99.362) +2022-11-14 14:51:51,566 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0735) Prec@1 83.000 (87.915) Prec@5 99.000 (99.356) +2022-11-14 14:51:51,576 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0738) Prec@1 83.000 (87.833) Prec@5 99.000 (99.350) +2022-11-14 14:51:51,588 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0740) Prec@1 86.000 (87.803) Prec@5 100.000 (99.361) +2022-11-14 14:51:51,598 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0738) Prec@1 92.000 (87.871) Prec@5 100.000 (99.371) +2022-11-14 14:51:51,608 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0739) Prec@1 88.000 (87.873) Prec@5 100.000 (99.381) +2022-11-14 14:51:51,619 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0735) Prec@1 92.000 (87.938) Prec@5 100.000 (99.391) +2022-11-14 14:51:51,629 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0738) Prec@1 86.000 (87.908) Prec@5 98.000 (99.369) +2022-11-14 14:51:51,639 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0738) Prec@1 87.000 (87.894) Prec@5 100.000 (99.379) +2022-11-14 14:51:51,649 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0737) Prec@1 91.000 (87.940) Prec@5 100.000 (99.388) +2022-11-14 14:51:51,660 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0739) Prec@1 88.000 (87.941) Prec@5 99.000 (99.382) +2022-11-14 14:51:51,670 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0740) Prec@1 85.000 (87.899) Prec@5 100.000 (99.391) +2022-11-14 14:51:51,680 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0742) Prec@1 85.000 (87.857) Prec@5 100.000 (99.400) +2022-11-14 14:51:51,691 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0745) Prec@1 85.000 (87.817) Prec@5 99.000 (99.394) +2022-11-14 14:51:51,702 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0744) Prec@1 89.000 (87.833) Prec@5 100.000 (99.403) +2022-11-14 14:51:51,712 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0740) Prec@1 93.000 (87.904) Prec@5 100.000 (99.411) +2022-11-14 14:51:51,723 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0334 (0.0735) Prec@1 95.000 (88.000) Prec@5 100.000 (99.419) +2022-11-14 14:51:51,733 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1212 (0.0741) Prec@1 80.000 (87.893) Prec@5 100.000 (99.427) +2022-11-14 14:51:51,742 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0737) Prec@1 93.000 (87.961) Prec@5 99.000 (99.421) +2022-11-14 14:51:51,754 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0738) Prec@1 87.000 (87.948) Prec@5 99.000 (99.416) +2022-11-14 14:51:51,765 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0741) Prec@1 86.000 (87.923) Prec@5 98.000 (99.397) +2022-11-14 14:51:51,775 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0742) Prec@1 86.000 (87.899) Prec@5 100.000 (99.405) +2022-11-14 14:51:51,785 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0742) Prec@1 88.000 (87.900) Prec@5 99.000 (99.400) +2022-11-14 14:51:51,795 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0744) Prec@1 88.000 (87.901) Prec@5 97.000 (99.370) +2022-11-14 14:51:51,806 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0745) Prec@1 88.000 (87.902) Prec@5 99.000 (99.366) +2022-11-14 14:51:51,816 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0746) Prec@1 85.000 (87.867) Prec@5 100.000 (99.373) +2022-11-14 14:51:51,827 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0746) Prec@1 89.000 (87.881) Prec@5 99.000 (99.369) +2022-11-14 14:51:51,837 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0747) Prec@1 85.000 (87.847) Prec@5 100.000 (99.376) +2022-11-14 14:51:51,849 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0750) Prec@1 86.000 (87.826) Prec@5 100.000 (99.384) +2022-11-14 14:51:51,858 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0751) Prec@1 85.000 (87.793) Prec@5 98.000 (99.368) +2022-11-14 14:51:51,869 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0751) Prec@1 87.000 (87.784) Prec@5 98.000 (99.352) +2022-11-14 14:51:51,879 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0751) Prec@1 86.000 (87.764) Prec@5 100.000 (99.360) +2022-11-14 14:51:51,889 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0750) Prec@1 89.000 (87.778) Prec@5 98.000 (99.344) +2022-11-14 14:51:51,898 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0748) Prec@1 91.000 (87.813) Prec@5 100.000 (99.352) +2022-11-14 14:51:51,908 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0746) Prec@1 91.000 (87.848) Prec@5 98.000 (99.337) +2022-11-14 14:51:51,919 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0744) Prec@1 92.000 (87.892) Prec@5 99.000 (99.333) +2022-11-14 14:51:51,930 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0743) Prec@1 89.000 (87.904) Prec@5 99.000 (99.330) +2022-11-14 14:51:51,940 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0743) Prec@1 87.000 (87.895) Prec@5 99.000 (99.326) +2022-11-14 14:51:51,951 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0742) Prec@1 89.000 (87.906) Prec@5 99.000 (99.323) +2022-11-14 14:51:51,962 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0740) Prec@1 91.000 (87.938) Prec@5 99.000 (99.320) +2022-11-14 14:51:51,973 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0743) Prec@1 82.000 (87.878) Prec@5 98.000 (99.306) +2022-11-14 14:51:51,983 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0743) Prec@1 88.000 (87.879) Prec@5 99.000 (99.303) +2022-11-14 14:51:51,993 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0743) Prec@1 91.000 (87.910) Prec@5 100.000 (99.310) +2022-11-14 14:51:52,053 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:51:52,387 Epoch: [266][0/500] Time 0.032 (0.032) Data 0.240 (0.240) Loss 0.0283 (0.0283) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:52,616 Epoch: [266][10/500] Time 0.018 (0.021) Data 0.002 (0.024) Loss 0.0342 (0.0312) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:51:52,834 Epoch: [266][20/500] Time 0.023 (0.020) Data 0.002 (0.013) Loss 0.0322 (0.0315) Prec@1 96.000 (95.333) Prec@5 99.000 (99.667) +2022-11-14 14:51:53,179 Epoch: [266][30/500] Time 0.033 (0.024) Data 0.002 (0.010) Loss 0.0461 (0.0352) Prec@1 91.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 14:51:53,521 Epoch: [266][40/500] Time 0.032 (0.025) Data 0.002 (0.008) Loss 0.0233 (0.0328) Prec@1 97.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 14:51:53,814 Epoch: [266][50/500] Time 0.028 (0.026) Data 0.001 (0.007) Loss 0.0222 (0.0310) Prec@1 97.000 (95.167) Prec@5 99.000 (99.667) +2022-11-14 14:51:54,125 Epoch: [266][60/500] Time 0.030 (0.026) Data 0.002 (0.006) Loss 0.0272 (0.0305) Prec@1 95.000 (95.143) Prec@5 100.000 (99.714) +2022-11-14 14:51:54,436 Epoch: [266][70/500] Time 0.038 (0.026) Data 0.002 (0.005) Loss 0.0334 (0.0308) Prec@1 95.000 (95.125) Prec@5 100.000 (99.750) +2022-11-14 14:51:54,737 Epoch: [266][80/500] Time 0.026 (0.026) Data 0.002 (0.005) Loss 0.0323 (0.0310) Prec@1 93.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 14:51:55,048 Epoch: [266][90/500] Time 0.026 (0.026) Data 0.002 (0.004) Loss 0.0362 (0.0315) Prec@1 93.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 14:51:55,380 Epoch: [266][100/500] Time 0.036 (0.027) Data 0.003 (0.004) Loss 0.0236 (0.0308) Prec@1 96.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 14:51:55,691 Epoch: [266][110/500] Time 0.024 (0.027) Data 0.003 (0.004) Loss 0.0520 (0.0326) Prec@1 92.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 14:51:56,057 Epoch: [266][120/500] Time 0.032 (0.027) Data 0.002 (0.004) Loss 0.0360 (0.0328) Prec@1 94.000 (94.538) Prec@5 99.000 (99.769) +2022-11-14 14:51:56,391 Epoch: [266][130/500] Time 0.024 (0.028) Data 0.002 (0.004) Loss 0.0404 (0.0334) Prec@1 93.000 (94.429) Prec@5 99.000 (99.714) +2022-11-14 14:51:56,699 Epoch: [266][140/500] Time 0.026 (0.027) Data 0.002 (0.004) Loss 0.0413 (0.0339) Prec@1 93.000 (94.333) Prec@5 100.000 (99.733) +2022-11-14 14:51:57,131 Epoch: [266][150/500] Time 0.046 (0.028) Data 0.002 (0.003) Loss 0.0302 (0.0337) Prec@1 96.000 (94.438) Prec@5 99.000 (99.688) +2022-11-14 14:51:57,596 Epoch: [266][160/500] Time 0.041 (0.029) Data 0.002 (0.003) Loss 0.0520 (0.0347) Prec@1 92.000 (94.294) Prec@5 100.000 (99.706) +2022-11-14 14:51:58,039 Epoch: [266][170/500] Time 0.041 (0.030) Data 0.002 (0.003) Loss 0.0308 (0.0345) Prec@1 93.000 (94.222) Prec@5 100.000 (99.722) +2022-11-14 14:51:58,491 Epoch: [266][180/500] Time 0.042 (0.030) Data 0.002 (0.003) Loss 0.0447 (0.0351) Prec@1 94.000 (94.211) Prec@5 99.000 (99.684) +2022-11-14 14:51:58,916 Epoch: [266][190/500] Time 0.040 (0.031) Data 0.002 (0.003) Loss 0.0215 (0.0344) Prec@1 96.000 (94.300) Prec@5 100.000 (99.700) +2022-11-14 14:51:59,371 Epoch: [266][200/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0214 (0.0338) Prec@1 96.000 (94.381) Prec@5 100.000 (99.714) +2022-11-14 14:51:59,823 Epoch: [266][210/500] Time 0.044 (0.032) Data 0.002 (0.003) Loss 0.0495 (0.0345) Prec@1 93.000 (94.318) Prec@5 100.000 (99.727) +2022-11-14 14:52:00,265 Epoch: [266][220/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0274 (0.0342) Prec@1 95.000 (94.348) Prec@5 100.000 (99.739) +2022-11-14 14:52:00,701 Epoch: [266][230/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0247 (0.0338) Prec@1 95.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 14:52:01,140 Epoch: [266][240/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0472 (0.0343) Prec@1 93.000 (94.320) Prec@5 100.000 (99.760) +2022-11-14 14:52:01,595 Epoch: [266][250/500] Time 0.061 (0.033) Data 0.002 (0.003) Loss 0.0290 (0.0341) Prec@1 94.000 (94.308) Prec@5 99.000 (99.731) +2022-11-14 14:52:02,040 Epoch: [266][260/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0310 (0.0340) Prec@1 95.000 (94.333) Prec@5 99.000 (99.704) +2022-11-14 14:52:02,476 Epoch: [266][270/500] Time 0.041 (0.033) Data 0.002 (0.003) Loss 0.0484 (0.0345) Prec@1 93.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 14:52:02,918 Epoch: [266][280/500] Time 0.045 (0.034) Data 0.002 (0.003) Loss 0.0129 (0.0338) Prec@1 99.000 (94.448) Prec@5 100.000 (99.724) +2022-11-14 14:52:03,358 Epoch: [266][290/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0332 (0.0337) Prec@1 94.000 (94.433) Prec@5 100.000 (99.733) +2022-11-14 14:52:03,833 Epoch: [266][300/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0249 (0.0335) Prec@1 97.000 (94.516) Prec@5 100.000 (99.742) +2022-11-14 14:52:04,285 Epoch: [266][310/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0417 (0.0337) Prec@1 93.000 (94.469) Prec@5 100.000 (99.750) +2022-11-14 14:52:04,721 Epoch: [266][320/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0308 (0.0336) Prec@1 96.000 (94.515) Prec@5 99.000 (99.727) +2022-11-14 14:52:05,192 Epoch: [266][330/500] Time 0.055 (0.035) Data 0.002 (0.003) Loss 0.0369 (0.0337) Prec@1 92.000 (94.441) Prec@5 99.000 (99.706) +2022-11-14 14:52:05,620 Epoch: [266][340/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0392 (0.0339) Prec@1 94.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 14:52:06,049 Epoch: [266][350/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0297 (0.0338) Prec@1 94.000 (94.417) Prec@5 100.000 (99.722) +2022-11-14 14:52:06,482 Epoch: [266][360/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0330 (0.0337) Prec@1 95.000 (94.432) Prec@5 100.000 (99.730) +2022-11-14 14:52:06,917 Epoch: [266][370/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0281 (0.0336) Prec@1 95.000 (94.447) Prec@5 100.000 (99.737) +2022-11-14 14:52:07,354 Epoch: [266][380/500] Time 0.041 (0.035) Data 0.002 (0.003) Loss 0.0307 (0.0335) Prec@1 96.000 (94.487) Prec@5 100.000 (99.744) +2022-11-14 14:52:07,785 Epoch: [266][390/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0407 (0.0337) Prec@1 93.000 (94.450) Prec@5 100.000 (99.750) +2022-11-14 14:52:08,242 Epoch: [266][400/500] Time 0.049 (0.035) Data 0.002 (0.003) Loss 0.0196 (0.0334) Prec@1 97.000 (94.512) Prec@5 100.000 (99.756) +2022-11-14 14:52:08,719 Epoch: [266][410/500] Time 0.050 (0.035) Data 0.002 (0.003) Loss 0.0440 (0.0336) Prec@1 92.000 (94.452) Prec@5 100.000 (99.762) +2022-11-14 14:52:09,150 Epoch: [266][420/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0335 (0.0336) Prec@1 96.000 (94.488) Prec@5 100.000 (99.767) +2022-11-14 14:52:09,594 Epoch: [266][430/500] Time 0.039 (0.036) Data 0.002 (0.002) Loss 0.0442 (0.0339) Prec@1 93.000 (94.455) Prec@5 100.000 (99.773) +2022-11-14 14:52:10,072 Epoch: [266][440/500] Time 0.055 (0.036) Data 0.002 (0.002) Loss 0.0454 (0.0341) Prec@1 92.000 (94.400) Prec@5 100.000 (99.778) +2022-11-14 14:52:10,535 Epoch: [266][450/500] Time 0.042 (0.036) Data 0.002 (0.002) Loss 0.0471 (0.0344) Prec@1 91.000 (94.326) Prec@5 99.000 (99.761) +2022-11-14 14:52:10,972 Epoch: [266][460/500] Time 0.050 (0.036) Data 0.003 (0.002) Loss 0.0604 (0.0349) Prec@1 91.000 (94.255) Prec@5 100.000 (99.766) +2022-11-14 14:52:11,444 Epoch: [266][470/500] Time 0.064 (0.036) Data 0.002 (0.002) Loss 0.0240 (0.0347) Prec@1 95.000 (94.271) Prec@5 100.000 (99.771) +2022-11-14 14:52:11,912 Epoch: [266][480/500] Time 0.068 (0.036) Data 0.002 (0.002) Loss 0.0572 (0.0352) Prec@1 90.000 (94.184) Prec@5 100.000 (99.776) +2022-11-14 14:52:12,377 Epoch: [266][490/500] Time 0.065 (0.036) Data 0.002 (0.002) Loss 0.0276 (0.0350) Prec@1 95.000 (94.200) Prec@5 100.000 (99.780) +2022-11-14 14:52:12,783 Epoch: [266][499/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0265 (0.0349) Prec@1 96.000 (94.235) Prec@5 99.000 (99.765) +2022-11-14 14:52:13,076 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:52:13,085 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0530 (0.0603) Prec@1 91.000 (89.500) Prec@5 99.000 (99.000) +2022-11-14 14:52:13,095 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0594) Prec@1 93.000 (90.667) Prec@5 100.000 (99.333) +2022-11-14 14:52:13,108 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0637) Prec@1 89.000 (90.250) Prec@5 98.000 (99.000) +2022-11-14 14:52:13,117 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0675) Prec@1 86.000 (89.400) Prec@5 99.000 (99.000) +2022-11-14 14:52:13,127 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0371 (0.0625) Prec@1 94.000 (90.167) Prec@5 100.000 (99.167) +2022-11-14 14:52:13,137 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0614) Prec@1 93.000 (90.571) Prec@5 99.000 (99.143) +2022-11-14 14:52:13,149 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0652) Prec@1 84.000 (89.750) Prec@5 100.000 (99.250) +2022-11-14 14:52:13,159 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0663) Prec@1 88.000 (89.556) Prec@5 100.000 (99.333) +2022-11-14 14:52:13,168 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0661) Prec@1 89.000 (89.500) Prec@5 99.000 (99.300) +2022-11-14 14:52:13,179 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0653) Prec@1 91.000 (89.636) Prec@5 99.000 (99.273) +2022-11-14 14:52:13,190 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0668) Prec@1 87.000 (89.417) Prec@5 100.000 (99.333) +2022-11-14 14:52:13,201 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0661) Prec@1 90.000 (89.462) Prec@5 100.000 (99.385) +2022-11-14 14:52:13,209 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0664) Prec@1 90.000 (89.500) Prec@5 100.000 (99.429) +2022-11-14 14:52:13,219 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0674) Prec@1 85.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 14:52:13,230 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0679) Prec@1 87.000 (89.062) Prec@5 100.000 (99.438) +2022-11-14 14:52:13,240 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0671) Prec@1 92.000 (89.235) Prec@5 98.000 (99.353) +2022-11-14 14:52:13,250 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1191 (0.0700) Prec@1 82.000 (88.833) Prec@5 99.000 (99.333) +2022-11-14 14:52:13,260 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0712) Prec@1 86.000 (88.684) Prec@5 99.000 (99.316) +2022-11-14 14:52:13,271 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0723) Prec@1 84.000 (88.450) Prec@5 98.000 (99.250) +2022-11-14 14:52:13,282 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0735) Prec@1 87.000 (88.381) Prec@5 100.000 (99.286) +2022-11-14 14:52:13,293 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0743) Prec@1 86.000 (88.273) Prec@5 99.000 (99.273) +2022-11-14 14:52:13,303 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0749) Prec@1 86.000 (88.174) Prec@5 98.000 (99.217) +2022-11-14 14:52:13,315 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0739) Prec@1 92.000 (88.333) Prec@5 100.000 (99.250) +2022-11-14 14:52:13,325 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0745) Prec@1 85.000 (88.200) Prec@5 100.000 (99.280) +2022-11-14 14:52:13,337 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0760) Prec@1 84.000 (88.038) Prec@5 97.000 (99.192) +2022-11-14 14:52:13,349 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0753) Prec@1 90.000 (88.111) Prec@5 100.000 (99.222) +2022-11-14 14:52:13,360 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0752) Prec@1 89.000 (88.143) Prec@5 100.000 (99.250) +2022-11-14 14:52:13,371 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0751) Prec@1 87.000 (88.103) Prec@5 98.000 (99.207) +2022-11-14 14:52:13,381 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0745) Prec@1 93.000 (88.267) Prec@5 100.000 (99.233) +2022-11-14 14:52:13,392 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0744) Prec@1 88.000 (88.258) Prec@5 100.000 (99.258) +2022-11-14 14:52:13,403 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0745) Prec@1 88.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 14:52:13,413 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0749) Prec@1 84.000 (88.121) Prec@5 100.000 (99.273) +2022-11-14 14:52:13,423 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0759) Prec@1 83.000 (87.971) Prec@5 98.000 (99.235) +2022-11-14 14:52:13,434 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0764) Prec@1 83.000 (87.829) Prec@5 100.000 (99.257) +2022-11-14 14:52:13,445 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0764) Prec@1 87.000 (87.806) Prec@5 99.000 (99.250) +2022-11-14 14:52:13,458 Test: [36/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0763) Prec@1 87.000 (87.784) Prec@5 98.000 (99.216) +2022-11-14 14:52:13,471 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0770) Prec@1 85.000 (87.711) Prec@5 99.000 (99.211) +2022-11-14 14:52:13,485 Test: [38/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0764) Prec@1 91.000 (87.795) Prec@5 99.000 (99.205) +2022-11-14 14:52:13,499 Test: [39/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0762) Prec@1 89.000 (87.825) Prec@5 100.000 (99.225) +2022-11-14 14:52:13,512 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0767) Prec@1 85.000 (87.756) Prec@5 98.000 (99.195) +2022-11-14 14:52:13,522 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0763) Prec@1 88.000 (87.762) Prec@5 99.000 (99.190) +2022-11-14 14:52:13,534 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0758) Prec@1 90.000 (87.814) Prec@5 97.000 (99.140) +2022-11-14 14:52:13,545 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0754) Prec@1 92.000 (87.909) Prec@5 98.000 (99.114) +2022-11-14 14:52:13,556 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0756) Prec@1 87.000 (87.889) Prec@5 100.000 (99.133) +2022-11-14 14:52:13,566 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0763) Prec@1 81.000 (87.739) Prec@5 100.000 (99.152) +2022-11-14 14:52:13,576 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0760) Prec@1 91.000 (87.809) Prec@5 100.000 (99.170) +2022-11-14 14:52:13,585 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0766) Prec@1 82.000 (87.688) Prec@5 99.000 (99.167) +2022-11-14 14:52:13,595 Test: [48/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0761) Prec@1 91.000 (87.755) Prec@5 99.000 (99.163) +2022-11-14 14:52:13,604 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.0768) Prec@1 80.000 (87.600) Prec@5 99.000 (99.160) +2022-11-14 14:52:13,613 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0765) Prec@1 92.000 (87.686) Prec@5 99.000 (99.157) +2022-11-14 14:52:13,625 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0768) Prec@1 84.000 (87.615) Prec@5 100.000 (99.173) +2022-11-14 14:52:13,635 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0767) Prec@1 89.000 (87.642) Prec@5 99.000 (99.170) +2022-11-14 14:52:13,645 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0768) Prec@1 87.000 (87.630) Prec@5 98.000 (99.148) +2022-11-14 14:52:13,656 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0767) Prec@1 87.000 (87.618) Prec@5 100.000 (99.164) +2022-11-14 14:52:13,667 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0766) Prec@1 88.000 (87.625) Prec@5 99.000 (99.161) +2022-11-14 14:52:13,677 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0763) Prec@1 88.000 (87.632) Prec@5 100.000 (99.175) +2022-11-14 14:52:13,688 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0761) Prec@1 92.000 (87.707) Prec@5 100.000 (99.190) +2022-11-14 14:52:13,698 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.0767) Prec@1 86.000 (87.678) Prec@5 99.000 (99.186) +2022-11-14 14:52:13,708 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0767) Prec@1 87.000 (87.667) Prec@5 100.000 (99.200) +2022-11-14 14:52:13,719 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0768) Prec@1 85.000 (87.623) Prec@5 99.000 (99.197) +2022-11-14 14:52:13,730 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0767) Prec@1 90.000 (87.661) Prec@5 100.000 (99.210) +2022-11-14 14:52:13,740 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0764) Prec@1 91.000 (87.714) Prec@5 100.000 (99.222) +2022-11-14 14:52:13,751 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0761) Prec@1 90.000 (87.750) Prec@5 99.000 (99.219) +2022-11-14 14:52:13,761 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0763) Prec@1 86.000 (87.723) Prec@5 98.000 (99.200) +2022-11-14 14:52:13,772 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0761) Prec@1 90.000 (87.758) Prec@5 99.000 (99.197) +2022-11-14 14:52:13,782 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0366 (0.0755) Prec@1 95.000 (87.866) Prec@5 100.000 (99.209) +2022-11-14 14:52:13,793 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0755) Prec@1 88.000 (87.868) Prec@5 97.000 (99.176) +2022-11-14 14:52:13,803 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0756) Prec@1 90.000 (87.899) Prec@5 100.000 (99.188) +2022-11-14 14:52:13,814 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0756) Prec@1 89.000 (87.914) Prec@5 100.000 (99.200) +2022-11-14 14:52:13,824 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0760) Prec@1 86.000 (87.887) Prec@5 100.000 (99.211) +2022-11-14 14:52:13,834 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0758) Prec@1 87.000 (87.875) Prec@5 99.000 (99.208) +2022-11-14 14:52:13,844 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0755) Prec@1 89.000 (87.890) Prec@5 100.000 (99.219) +2022-11-14 14:52:13,854 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0751) Prec@1 94.000 (87.973) Prec@5 100.000 (99.230) +2022-11-14 14:52:13,865 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0753) Prec@1 86.000 (87.947) Prec@5 100.000 (99.240) +2022-11-14 14:52:13,876 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0750) Prec@1 92.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 14:52:13,886 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0750) Prec@1 89.000 (88.013) Prec@5 98.000 (99.234) +2022-11-14 14:52:13,898 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0754) Prec@1 83.000 (87.949) Prec@5 98.000 (99.218) +2022-11-14 14:52:13,910 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0756) Prec@1 86.000 (87.924) Prec@5 100.000 (99.228) +2022-11-14 14:52:13,920 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0754) Prec@1 89.000 (87.938) Prec@5 100.000 (99.237) +2022-11-14 14:52:13,931 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0755) Prec@1 87.000 (87.926) Prec@5 98.000 (99.222) +2022-11-14 14:52:13,943 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0756) Prec@1 83.000 (87.866) Prec@5 99.000 (99.220) +2022-11-14 14:52:13,954 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0758) Prec@1 84.000 (87.819) Prec@5 100.000 (99.229) +2022-11-14 14:52:13,965 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0757) Prec@1 89.000 (87.833) Prec@5 100.000 (99.238) +2022-11-14 14:52:13,976 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0758) Prec@1 87.000 (87.824) Prec@5 100.000 (99.247) +2022-11-14 14:52:13,987 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.0764) Prec@1 81.000 (87.744) Prec@5 100.000 (99.256) +2022-11-14 14:52:13,997 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0761) Prec@1 91.000 (87.782) Prec@5 100.000 (99.264) +2022-11-14 14:52:14,009 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0762) Prec@1 86.000 (87.761) Prec@5 98.000 (99.250) +2022-11-14 14:52:14,019 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0761) Prec@1 87.000 (87.753) Prec@5 100.000 (99.258) +2022-11-14 14:52:14,031 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0759) Prec@1 92.000 (87.800) Prec@5 99.000 (99.256) +2022-11-14 14:52:14,041 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0759) Prec@1 87.000 (87.791) Prec@5 99.000 (99.253) +2022-11-14 14:52:14,051 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0412 (0.0755) Prec@1 93.000 (87.848) Prec@5 100.000 (99.261) +2022-11-14 14:52:14,060 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0757) Prec@1 87.000 (87.839) Prec@5 100.000 (99.269) +2022-11-14 14:52:14,072 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0756) Prec@1 86.000 (87.819) Prec@5 99.000 (99.266) +2022-11-14 14:52:14,082 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0757) Prec@1 87.000 (87.811) Prec@5 99.000 (99.263) +2022-11-14 14:52:14,093 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0754) Prec@1 92.000 (87.854) Prec@5 99.000 (99.260) +2022-11-14 14:52:14,104 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0751) Prec@1 92.000 (87.897) Prec@5 99.000 (99.258) +2022-11-14 14:52:14,113 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0753) Prec@1 85.000 (87.867) Prec@5 98.000 (99.245) +2022-11-14 14:52:14,123 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0755) Prec@1 85.000 (87.838) Prec@5 100.000 (99.253) +2022-11-14 14:52:14,133 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0755) Prec@1 89.000 (87.850) Prec@5 100.000 (99.260) +2022-11-14 14:52:14,189 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:52:14,504 Epoch: [267][0/500] Time 0.029 (0.029) Data 0.228 (0.228) Loss 0.0459 (0.0459) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:52:14,712 Epoch: [267][10/500] Time 0.018 (0.019) Data 0.001 (0.022) Loss 0.0511 (0.0485) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 14:52:14,915 Epoch: [267][20/500] Time 0.016 (0.019) Data 0.001 (0.012) Loss 0.0310 (0.0426) Prec@1 95.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 14:52:15,186 Epoch: [267][30/500] Time 0.031 (0.020) Data 0.002 (0.009) Loss 0.0311 (0.0398) Prec@1 95.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 14:52:15,555 Epoch: [267][40/500] Time 0.035 (0.023) Data 0.002 (0.007) Loss 0.0187 (0.0356) Prec@1 97.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 14:52:15,930 Epoch: [267][50/500] Time 0.030 (0.025) Data 0.002 (0.006) Loss 0.0201 (0.0330) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 14:52:16,299 Epoch: [267][60/500] Time 0.038 (0.026) Data 0.002 (0.005) Loss 0.0356 (0.0334) Prec@1 94.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 14:52:16,671 Epoch: [267][70/500] Time 0.032 (0.027) Data 0.002 (0.005) Loss 0.0410 (0.0343) Prec@1 93.000 (94.375) Prec@5 99.000 (99.875) +2022-11-14 14:52:17,037 Epoch: [267][80/500] Time 0.037 (0.028) Data 0.002 (0.005) Loss 0.0404 (0.0350) Prec@1 93.000 (94.222) Prec@5 100.000 (99.889) +2022-11-14 14:52:17,407 Epoch: [267][90/500] Time 0.031 (0.029) Data 0.002 (0.004) Loss 0.0583 (0.0373) Prec@1 89.000 (93.700) Prec@5 99.000 (99.800) +2022-11-14 14:52:17,788 Epoch: [267][100/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0231 (0.0360) Prec@1 96.000 (93.909) Prec@5 100.000 (99.818) +2022-11-14 14:52:18,157 Epoch: [267][110/500] Time 0.033 (0.029) Data 0.002 (0.004) Loss 0.0480 (0.0370) Prec@1 92.000 (93.750) Prec@5 99.000 (99.750) +2022-11-14 14:52:18,522 Epoch: [267][120/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0491 (0.0379) Prec@1 93.000 (93.692) Prec@5 100.000 (99.769) +2022-11-14 14:52:18,921 Epoch: [267][130/500] Time 0.032 (0.030) Data 0.002 (0.004) Loss 0.0354 (0.0378) Prec@1 94.000 (93.714) Prec@5 99.000 (99.714) +2022-11-14 14:52:19,286 Epoch: [267][140/500] Time 0.036 (0.030) Data 0.002 (0.003) Loss 0.0392 (0.0379) Prec@1 94.000 (93.733) Prec@5 100.000 (99.733) +2022-11-14 14:52:19,654 Epoch: [267][150/500] Time 0.034 (0.030) Data 0.002 (0.003) Loss 0.0411 (0.0381) Prec@1 93.000 (93.688) Prec@5 99.000 (99.688) +2022-11-14 14:52:20,023 Epoch: [267][160/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0162 (0.0368) Prec@1 98.000 (93.941) Prec@5 100.000 (99.706) +2022-11-14 14:52:20,396 Epoch: [267][170/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0442 (0.0372) Prec@1 93.000 (93.889) Prec@5 100.000 (99.722) +2022-11-14 14:52:20,776 Epoch: [267][180/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0227 (0.0364) Prec@1 96.000 (94.000) Prec@5 100.000 (99.737) +2022-11-14 14:52:21,151 Epoch: [267][190/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0349 (0.0364) Prec@1 94.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 14:52:21,546 Epoch: [267][200/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0354 (0.0363) Prec@1 95.000 (94.048) Prec@5 100.000 (99.762) +2022-11-14 14:52:21,938 Epoch: [267][210/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0261 (0.0358) Prec@1 96.000 (94.136) Prec@5 100.000 (99.773) +2022-11-14 14:52:22,403 Epoch: [267][220/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0259 (0.0354) Prec@1 96.000 (94.217) Prec@5 100.000 (99.783) +2022-11-14 14:52:22,771 Epoch: [267][230/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0188 (0.0347) Prec@1 97.000 (94.333) Prec@5 100.000 (99.792) +2022-11-14 14:52:23,257 Epoch: [267][240/500] Time 0.039 (0.032) Data 0.002 (0.003) Loss 0.0497 (0.0353) Prec@1 93.000 (94.280) Prec@5 100.000 (99.800) +2022-11-14 14:52:23,708 Epoch: [267][250/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0382 (0.0354) Prec@1 94.000 (94.269) Prec@5 100.000 (99.808) +2022-11-14 14:52:24,127 Epoch: [267][260/500] Time 0.025 (0.033) Data 0.002 (0.003) Loss 0.0315 (0.0353) Prec@1 96.000 (94.333) Prec@5 99.000 (99.778) +2022-11-14 14:52:24,485 Epoch: [267][270/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0219 (0.0348) Prec@1 98.000 (94.464) Prec@5 99.000 (99.750) +2022-11-14 14:52:24,865 Epoch: [267][280/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0411 (0.0350) Prec@1 95.000 (94.483) Prec@5 100.000 (99.759) +2022-11-14 14:52:25,246 Epoch: [267][290/500] Time 0.038 (0.033) Data 0.002 (0.003) Loss 0.0484 (0.0355) Prec@1 91.000 (94.367) Prec@5 100.000 (99.767) +2022-11-14 14:52:25,720 Epoch: [267][300/500] Time 0.044 (0.033) Data 0.003 (0.003) Loss 0.0243 (0.0351) Prec@1 97.000 (94.452) Prec@5 100.000 (99.774) +2022-11-14 14:52:26,168 Epoch: [267][310/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0438 (0.0354) Prec@1 92.000 (94.375) Prec@5 100.000 (99.781) +2022-11-14 14:52:26,637 Epoch: [267][320/500] Time 0.048 (0.034) Data 0.002 (0.003) Loss 0.0325 (0.0353) Prec@1 95.000 (94.394) Prec@5 98.000 (99.727) +2022-11-14 14:52:27,090 Epoch: [267][330/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0223 (0.0349) Prec@1 96.000 (94.441) Prec@5 100.000 (99.735) +2022-11-14 14:52:27,551 Epoch: [267][340/500] Time 0.046 (0.034) Data 0.002 (0.003) Loss 0.0243 (0.0346) Prec@1 96.000 (94.486) Prec@5 100.000 (99.743) +2022-11-14 14:52:27,914 Epoch: [267][350/500] Time 0.030 (0.034) Data 0.002 (0.003) Loss 0.0522 (0.0351) Prec@1 92.000 (94.417) Prec@5 99.000 (99.722) +2022-11-14 14:52:28,404 Epoch: [267][360/500] Time 0.038 (0.034) Data 0.003 (0.003) Loss 0.0206 (0.0347) Prec@1 96.000 (94.459) Prec@5 100.000 (99.730) +2022-11-14 14:52:28,841 Epoch: [267][370/500] Time 0.045 (0.035) Data 0.002 (0.003) Loss 0.0417 (0.0349) Prec@1 93.000 (94.421) Prec@5 100.000 (99.737) +2022-11-14 14:52:29,261 Epoch: [267][380/500] Time 0.056 (0.035) Data 0.002 (0.003) Loss 0.0333 (0.0348) Prec@1 94.000 (94.410) Prec@5 100.000 (99.744) +2022-11-14 14:52:29,729 Epoch: [267][390/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0301 (0.0347) Prec@1 95.000 (94.425) Prec@5 100.000 (99.750) +2022-11-14 14:52:30,187 Epoch: [267][400/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0473 (0.0350) Prec@1 92.000 (94.366) Prec@5 100.000 (99.756) +2022-11-14 14:52:30,755 Epoch: [267][410/500] Time 0.083 (0.035) Data 0.002 (0.003) Loss 0.0595 (0.0356) Prec@1 89.000 (94.238) Prec@5 100.000 (99.762) +2022-11-14 14:52:31,302 Epoch: [267][420/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0462 (0.0359) Prec@1 92.000 (94.186) Prec@5 100.000 (99.767) +2022-11-14 14:52:31,781 Epoch: [267][430/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0548 (0.0363) Prec@1 89.000 (94.068) Prec@5 99.000 (99.750) +2022-11-14 14:52:32,350 Epoch: [267][440/500] Time 0.043 (0.036) Data 0.002 (0.002) Loss 0.0424 (0.0364) Prec@1 93.000 (94.044) Prec@5 99.000 (99.733) +2022-11-14 14:52:32,895 Epoch: [267][450/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0263 (0.0362) Prec@1 97.000 (94.109) Prec@5 100.000 (99.739) +2022-11-14 14:52:33,450 Epoch: [267][460/500] Time 0.055 (0.037) Data 0.002 (0.002) Loss 0.0218 (0.0359) Prec@1 98.000 (94.191) Prec@5 100.000 (99.745) +2022-11-14 14:52:33,929 Epoch: [267][470/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0365 (0.0359) Prec@1 94.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 14:52:34,443 Epoch: [267][480/500] Time 0.044 (0.037) Data 0.002 (0.002) Loss 0.0296 (0.0358) Prec@1 96.000 (94.224) Prec@5 100.000 (99.755) +2022-11-14 14:52:34,965 Epoch: [267][490/500] Time 0.062 (0.037) Data 0.002 (0.002) Loss 0.0414 (0.0359) Prec@1 92.000 (94.180) Prec@5 100.000 (99.760) +2022-11-14 14:52:35,402 Epoch: [267][499/500] Time 0.042 (0.037) Data 0.002 (0.002) Loss 0.0235 (0.0357) Prec@1 95.000 (94.196) Prec@5 100.000 (99.765) +2022-11-14 14:52:35,701 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0622 (0.0622) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:52:35,712 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0661 (0.0642) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 14:52:35,726 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0829 (0.0704) Prec@1 87.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 14:52:35,742 Test: [3/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0891 (0.0751) Prec@1 85.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 14:52:35,757 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0836 (0.0768) Prec@1 88.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 14:52:35,770 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0490 (0.0722) Prec@1 91.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:52:35,788 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0476 (0.0687) Prec@1 93.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 14:52:35,813 Test: [7/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0699) Prec@1 88.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:52:35,834 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0713) Prec@1 87.000 (88.778) Prec@5 99.000 (99.444) +2022-11-14 14:52:35,855 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0714) Prec@1 88.000 (88.700) Prec@5 99.000 (99.400) +2022-11-14 14:52:35,882 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0698) Prec@1 91.000 (88.909) Prec@5 100.000 (99.455) +2022-11-14 14:52:35,915 Test: [11/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0708) Prec@1 86.000 (88.667) Prec@5 100.000 (99.500) +2022-11-14 14:52:35,944 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0576 (0.0697) Prec@1 91.000 (88.846) Prec@5 100.000 (99.538) +2022-11-14 14:52:35,973 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0700) Prec@1 89.000 (88.857) Prec@5 100.000 (99.571) +2022-11-14 14:52:36,003 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0707) Prec@1 87.000 (88.733) Prec@5 100.000 (99.600) +2022-11-14 14:52:36,036 Test: [15/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0757 (0.0710) Prec@1 87.000 (88.625) Prec@5 100.000 (99.625) +2022-11-14 14:52:36,069 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0700) Prec@1 91.000 (88.765) Prec@5 98.000 (99.529) +2022-11-14 14:52:36,104 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1319 (0.0735) Prec@1 79.000 (88.222) Prec@5 99.000 (99.500) +2022-11-14 14:52:36,136 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0737) Prec@1 84.000 (88.000) Prec@5 99.000 (99.474) +2022-11-14 14:52:36,167 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0899 (0.0745) Prec@1 84.000 (87.800) Prec@5 96.000 (99.300) +2022-11-14 14:52:36,194 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.0752) Prec@1 86.000 (87.714) Prec@5 100.000 (99.333) +2022-11-14 14:52:36,223 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0752) Prec@1 87.000 (87.682) Prec@5 99.000 (99.318) +2022-11-14 14:52:36,251 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0757) Prec@1 86.000 (87.609) Prec@5 98.000 (99.261) +2022-11-14 14:52:36,279 Test: [23/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0815 (0.0759) Prec@1 85.000 (87.500) Prec@5 100.000 (99.292) +2022-11-14 14:52:36,307 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0955 (0.0767) Prec@1 85.000 (87.400) Prec@5 100.000 (99.320) +2022-11-14 14:52:36,343 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0770) Prec@1 88.000 (87.423) Prec@5 100.000 (99.346) +2022-11-14 14:52:36,377 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0761) Prec@1 91.000 (87.556) Prec@5 100.000 (99.370) +2022-11-14 14:52:36,409 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0753) Prec@1 89.000 (87.607) Prec@5 100.000 (99.393) +2022-11-14 14:52:36,438 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0822 (0.0755) Prec@1 87.000 (87.586) Prec@5 98.000 (99.345) +2022-11-14 14:52:36,465 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0754) Prec@1 90.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 14:52:36,494 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0755) Prec@1 85.000 (87.581) Prec@5 99.000 (99.323) +2022-11-14 14:52:36,528 Test: [31/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0752) Prec@1 91.000 (87.688) Prec@5 99.000 (99.312) +2022-11-14 14:52:36,554 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0755) Prec@1 85.000 (87.606) Prec@5 100.000 (99.333) +2022-11-14 14:52:36,577 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1017 (0.0762) Prec@1 82.000 (87.441) Prec@5 99.000 (99.324) +2022-11-14 14:52:36,610 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0768) Prec@1 85.000 (87.371) Prec@5 99.000 (99.314) +2022-11-14 14:52:36,637 Test: [35/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0764) Prec@1 91.000 (87.472) Prec@5 100.000 (99.333) +2022-11-14 14:52:36,672 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0762) Prec@1 90.000 (87.541) Prec@5 97.000 (99.270) +2022-11-14 14:52:36,705 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0880 (0.0765) Prec@1 85.000 (87.474) Prec@5 99.000 (99.263) +2022-11-14 14:52:36,736 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0423 (0.0757) Prec@1 96.000 (87.692) Prec@5 99.000 (99.256) +2022-11-14 14:52:36,767 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0753) Prec@1 90.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 14:52:36,798 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0940 (0.0758) Prec@1 84.000 (87.659) Prec@5 98.000 (99.220) +2022-11-14 14:52:36,822 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0757) Prec@1 88.000 (87.667) Prec@5 99.000 (99.214) +2022-11-14 14:52:36,849 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0347 (0.0748) Prec@1 95.000 (87.837) Prec@5 99.000 (99.209) +2022-11-14 14:52:36,879 Test: [43/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0746) Prec@1 90.000 (87.886) Prec@5 98.000 (99.182) +2022-11-14 14:52:36,908 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0283 (0.0736) Prec@1 97.000 (88.089) Prec@5 100.000 (99.200) +2022-11-14 14:52:36,937 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1130 (0.0744) Prec@1 82.000 (87.957) Prec@5 99.000 (99.196) +2022-11-14 14:52:36,965 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0744) Prec@1 88.000 (87.957) Prec@5 100.000 (99.213) +2022-11-14 14:52:36,997 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.0752) Prec@1 81.000 (87.812) Prec@5 96.000 (99.146) +2022-11-14 14:52:37,024 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0747) Prec@1 92.000 (87.898) Prec@5 100.000 (99.163) +2022-11-14 14:52:37,053 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1126 (0.0754) Prec@1 81.000 (87.760) Prec@5 100.000 (99.180) +2022-11-14 14:52:37,084 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0756) Prec@1 85.000 (87.706) Prec@5 100.000 (99.196) +2022-11-14 14:52:37,112 Test: [51/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0759) Prec@1 85.000 (87.654) Prec@5 99.000 (99.192) +2022-11-14 14:52:37,142 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0758) Prec@1 88.000 (87.660) Prec@5 100.000 (99.208) +2022-11-14 14:52:37,170 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0763) Prec@1 83.000 (87.574) Prec@5 97.000 (99.167) +2022-11-14 14:52:37,205 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0763) Prec@1 90.000 (87.618) Prec@5 100.000 (99.182) +2022-11-14 14:52:37,236 Test: [55/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0763) Prec@1 88.000 (87.625) Prec@5 98.000 (99.161) +2022-11-14 14:52:37,263 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0764) Prec@1 86.000 (87.596) Prec@5 100.000 (99.175) +2022-11-14 14:52:37,292 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0761) Prec@1 90.000 (87.638) Prec@5 99.000 (99.172) +2022-11-14 14:52:37,324 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1081 (0.0767) Prec@1 85.000 (87.593) Prec@5 98.000 (99.153) +2022-11-14 14:52:37,352 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0766) Prec@1 88.000 (87.600) Prec@5 100.000 (99.167) +2022-11-14 14:52:37,383 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0763) Prec@1 89.000 (87.623) Prec@5 99.000 (99.164) +2022-11-14 14:52:37,414 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0764) Prec@1 87.000 (87.613) Prec@5 100.000 (99.177) +2022-11-14 14:52:37,441 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0762) Prec@1 88.000 (87.619) Prec@5 100.000 (99.190) +2022-11-14 14:52:37,476 Test: [63/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0758) Prec@1 91.000 (87.672) Prec@5 99.000 (99.188) +2022-11-14 14:52:37,508 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0763) Prec@1 81.000 (87.569) Prec@5 99.000 (99.185) +2022-11-14 14:52:37,534 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0764) Prec@1 86.000 (87.545) Prec@5 99.000 (99.182) +2022-11-14 14:52:37,568 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0435 (0.0759) Prec@1 93.000 (87.627) Prec@5 100.000 (99.194) +2022-11-14 14:52:37,603 Test: [67/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0759) Prec@1 86.000 (87.603) Prec@5 97.000 (99.162) +2022-11-14 14:52:37,632 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0757) Prec@1 88.000 (87.609) Prec@5 99.000 (99.159) +2022-11-14 14:52:37,660 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0760) Prec@1 86.000 (87.586) Prec@5 99.000 (99.157) +2022-11-14 14:52:37,694 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0764) Prec@1 84.000 (87.535) Prec@5 99.000 (99.155) +2022-11-14 14:52:37,722 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0763) Prec@1 90.000 (87.569) Prec@5 100.000 (99.167) +2022-11-14 14:52:37,755 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0759) Prec@1 90.000 (87.603) Prec@5 100.000 (99.178) +2022-11-14 14:52:37,786 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0757) Prec@1 92.000 (87.662) Prec@5 100.000 (99.189) +2022-11-14 14:52:37,818 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0760) Prec@1 84.000 (87.613) Prec@5 98.000 (99.173) +2022-11-14 14:52:37,846 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0759) Prec@1 88.000 (87.618) Prec@5 99.000 (99.171) +2022-11-14 14:52:37,873 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0758) Prec@1 90.000 (87.649) Prec@5 99.000 (99.169) +2022-11-14 14:52:37,908 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0759) Prec@1 85.000 (87.615) Prec@5 100.000 (99.179) +2022-11-14 14:52:37,935 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0761) Prec@1 86.000 (87.595) Prec@5 100.000 (99.190) +2022-11-14 14:52:37,967 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0759) Prec@1 89.000 (87.612) Prec@5 100.000 (99.200) +2022-11-14 14:52:37,993 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0760) Prec@1 86.000 (87.593) Prec@5 99.000 (99.198) +2022-11-14 14:52:38,020 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0760) Prec@1 89.000 (87.610) Prec@5 99.000 (99.195) +2022-11-14 14:52:38,051 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0761) Prec@1 86.000 (87.590) Prec@5 100.000 (99.205) +2022-11-14 14:52:38,082 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0761) Prec@1 86.000 (87.571) Prec@5 100.000 (99.214) +2022-11-14 14:52:38,109 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0762) Prec@1 89.000 (87.588) Prec@5 100.000 (99.224) +2022-11-14 14:52:38,138 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1151 (0.0766) Prec@1 81.000 (87.512) Prec@5 97.000 (99.198) +2022-11-14 14:52:38,166 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0764) Prec@1 92.000 (87.563) Prec@5 99.000 (99.195) +2022-11-14 14:52:38,195 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0764) Prec@1 87.000 (87.557) Prec@5 99.000 (99.193) +2022-11-14 14:52:38,220 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0764) Prec@1 89.000 (87.573) Prec@5 97.000 (99.169) +2022-11-14 14:52:38,249 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0764) Prec@1 88.000 (87.578) Prec@5 100.000 (99.178) +2022-11-14 14:52:38,281 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0762) Prec@1 92.000 (87.626) Prec@5 100.000 (99.187) +2022-11-14 14:52:38,312 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0416 (0.0758) Prec@1 93.000 (87.685) Prec@5 100.000 (99.196) +2022-11-14 14:52:38,343 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0759) Prec@1 86.000 (87.667) Prec@5 100.000 (99.204) +2022-11-14 14:52:38,373 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0761) Prec@1 86.000 (87.649) Prec@5 98.000 (99.191) +2022-11-14 14:52:38,398 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0761) Prec@1 86.000 (87.632) Prec@5 100.000 (99.200) +2022-11-14 14:52:38,428 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0760) Prec@1 87.000 (87.625) Prec@5 100.000 (99.208) +2022-11-14 14:52:38,457 Test: [96/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0757) Prec@1 92.000 (87.670) Prec@5 99.000 (99.206) +2022-11-14 14:52:38,489 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0758) Prec@1 89.000 (87.684) Prec@5 99.000 (99.204) +2022-11-14 14:52:38,517 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0761) Prec@1 86.000 (87.667) Prec@5 99.000 (99.202) +2022-11-14 14:52:38,545 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0759) Prec@1 90.000 (87.690) Prec@5 99.000 (99.200) +2022-11-14 14:52:38,603 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:52:38,892 Epoch: [268][0/500] Time 0.026 (0.026) Data 0.212 (0.212) Loss 0.0506 (0.0506) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:52:39,114 Epoch: [268][10/500] Time 0.021 (0.020) Data 0.001 (0.021) Loss 0.0402 (0.0454) Prec@1 93.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 14:52:39,352 Epoch: [268][20/500] Time 0.022 (0.020) Data 0.002 (0.012) Loss 0.0431 (0.0446) Prec@1 90.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 14:52:39,593 Epoch: [268][30/500] Time 0.023 (0.021) Data 0.001 (0.008) Loss 0.0279 (0.0405) Prec@1 95.000 (92.500) Prec@5 100.000 (99.750) +2022-11-14 14:52:39,832 Epoch: [268][40/500] Time 0.023 (0.021) Data 0.001 (0.007) Loss 0.0483 (0.0420) Prec@1 91.000 (92.200) Prec@5 99.000 (99.600) +2022-11-14 14:52:40,225 Epoch: [268][50/500] Time 0.043 (0.023) Data 0.002 (0.006) Loss 0.0422 (0.0421) Prec@1 91.000 (92.000) Prec@5 100.000 (99.667) +2022-11-14 14:52:40,695 Epoch: [268][60/500] Time 0.044 (0.026) Data 0.002 (0.005) Loss 0.0292 (0.0402) Prec@1 96.000 (92.571) Prec@5 100.000 (99.714) +2022-11-14 14:52:41,161 Epoch: [268][70/500] Time 0.043 (0.029) Data 0.002 (0.005) Loss 0.0208 (0.0378) Prec@1 96.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 14:52:41,628 Epoch: [268][80/500] Time 0.044 (0.030) Data 0.002 (0.004) Loss 0.0562 (0.0398) Prec@1 89.000 (92.556) Prec@5 100.000 (99.778) +2022-11-14 14:52:42,099 Epoch: [268][90/500] Time 0.041 (0.032) Data 0.002 (0.004) Loss 0.0137 (0.0372) Prec@1 97.000 (93.000) Prec@5 100.000 (99.800) +2022-11-14 14:52:42,604 Epoch: [268][100/500] Time 0.041 (0.033) Data 0.002 (0.004) Loss 0.0301 (0.0366) Prec@1 96.000 (93.273) Prec@5 100.000 (99.818) +2022-11-14 14:52:43,148 Epoch: [268][110/500] Time 0.053 (0.034) Data 0.002 (0.004) Loss 0.0475 (0.0375) Prec@1 92.000 (93.167) Prec@5 100.000 (99.833) +2022-11-14 14:52:43,691 Epoch: [268][120/500] Time 0.052 (0.036) Data 0.002 (0.004) Loss 0.0255 (0.0366) Prec@1 94.000 (93.231) Prec@5 100.000 (99.846) +2022-11-14 14:52:44,164 Epoch: [268][130/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0255 (0.0358) Prec@1 97.000 (93.500) Prec@5 99.000 (99.786) +2022-11-14 14:52:44,651 Epoch: [268][140/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0312 (0.0355) Prec@1 95.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 14:52:45,186 Epoch: [268][150/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0257 (0.0349) Prec@1 96.000 (93.750) Prec@5 100.000 (99.812) +2022-11-14 14:52:45,670 Epoch: [268][160/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0157 (0.0337) Prec@1 98.000 (94.000) Prec@5 99.000 (99.765) +2022-11-14 14:52:46,145 Epoch: [268][170/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0384 (0.0340) Prec@1 93.000 (93.944) Prec@5 99.000 (99.722) +2022-11-14 14:52:46,664 Epoch: [268][180/500] Time 0.050 (0.039) Data 0.002 (0.003) Loss 0.0310 (0.0338) Prec@1 96.000 (94.053) Prec@5 99.000 (99.684) +2022-11-14 14:52:47,154 Epoch: [268][190/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0377 (0.0340) Prec@1 95.000 (94.100) Prec@5 100.000 (99.700) +2022-11-14 14:52:47,630 Epoch: [268][200/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0284 (0.0338) Prec@1 95.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:52:48,105 Epoch: [268][210/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0197 (0.0331) Prec@1 96.000 (94.227) Prec@5 100.000 (99.727) +2022-11-14 14:52:48,583 Epoch: [268][220/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0269 (0.0328) Prec@1 96.000 (94.304) Prec@5 100.000 (99.739) +2022-11-14 14:52:49,108 Epoch: [268][230/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0280 (0.0326) Prec@1 97.000 (94.417) Prec@5 100.000 (99.750) +2022-11-14 14:52:49,578 Epoch: [268][240/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0428 (0.0330) Prec@1 93.000 (94.360) Prec@5 100.000 (99.760) +2022-11-14 14:52:50,108 Epoch: [268][250/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0284 (0.0329) Prec@1 95.000 (94.385) Prec@5 100.000 (99.769) +2022-11-14 14:52:50,589 Epoch: [268][260/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0200 (0.0324) Prec@1 98.000 (94.519) Prec@5 100.000 (99.778) +2022-11-14 14:52:51,055 Epoch: [268][270/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0457 (0.0329) Prec@1 91.000 (94.393) Prec@5 100.000 (99.786) +2022-11-14 14:52:51,531 Epoch: [268][280/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0274 (0.0327) Prec@1 95.000 (94.414) Prec@5 100.000 (99.793) +2022-11-14 14:52:52,009 Epoch: [268][290/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0381 (0.0329) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:52:52,482 Epoch: [268][300/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0142 (0.0323) Prec@1 98.000 (94.516) Prec@5 100.000 (99.806) +2022-11-14 14:52:52,960 Epoch: [268][310/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0295 (0.0322) Prec@1 94.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 14:52:53,440 Epoch: [268][320/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0304 (0.0321) Prec@1 95.000 (94.515) Prec@5 100.000 (99.818) +2022-11-14 14:52:53,917 Epoch: [268][330/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0426 (0.0324) Prec@1 92.000 (94.441) Prec@5 100.000 (99.824) +2022-11-14 14:52:54,460 Epoch: [268][340/500] Time 0.037 (0.041) Data 0.002 (0.002) Loss 0.0363 (0.0325) Prec@1 92.000 (94.371) Prec@5 100.000 (99.829) +2022-11-14 14:52:55,052 Epoch: [268][350/500] Time 0.057 (0.041) Data 0.002 (0.002) Loss 0.0376 (0.0327) Prec@1 95.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 14:52:55,539 Epoch: [268][360/500] Time 0.041 (0.041) Data 0.002 (0.002) Loss 0.0264 (0.0325) Prec@1 97.000 (94.459) Prec@5 100.000 (99.838) +2022-11-14 14:52:56,204 Epoch: [268][370/500] Time 0.071 (0.042) Data 0.002 (0.002) Loss 0.0392 (0.0327) Prec@1 92.000 (94.395) Prec@5 100.000 (99.842) +2022-11-14 14:52:56,862 Epoch: [268][380/500] Time 0.062 (0.042) Data 0.002 (0.002) Loss 0.0168 (0.0323) Prec@1 98.000 (94.487) Prec@5 100.000 (99.846) +2022-11-14 14:52:57,324 Epoch: [268][390/500] Time 0.041 (0.042) Data 0.002 (0.002) Loss 0.0589 (0.0329) Prec@1 89.000 (94.350) Prec@5 100.000 (99.850) +2022-11-14 14:52:57,802 Epoch: [268][400/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0408 (0.0331) Prec@1 92.000 (94.293) Prec@5 100.000 (99.854) +2022-11-14 14:52:58,302 Epoch: [268][410/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0440 (0.0334) Prec@1 92.000 (94.238) Prec@5 100.000 (99.857) +2022-11-14 14:52:58,817 Epoch: [268][420/500] Time 0.043 (0.042) Data 0.002 (0.002) Loss 0.0445 (0.0337) Prec@1 94.000 (94.233) Prec@5 100.000 (99.860) +2022-11-14 14:52:59,375 Epoch: [268][430/500] Time 0.041 (0.043) Data 0.002 (0.002) Loss 0.0284 (0.0335) Prec@1 95.000 (94.250) Prec@5 100.000 (99.864) +2022-11-14 14:52:59,881 Epoch: [268][440/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0411 (0.0337) Prec@1 92.000 (94.200) Prec@5 100.000 (99.867) +2022-11-14 14:53:00,461 Epoch: [268][450/500] Time 0.044 (0.043) Data 0.002 (0.002) Loss 0.0326 (0.0337) Prec@1 95.000 (94.217) Prec@5 100.000 (99.870) +2022-11-14 14:53:01,060 Epoch: [268][460/500] Time 0.072 (0.043) Data 0.002 (0.002) Loss 0.0394 (0.0338) Prec@1 94.000 (94.213) Prec@5 100.000 (99.872) +2022-11-14 14:53:01,667 Epoch: [268][470/500] Time 0.042 (0.043) Data 0.002 (0.002) Loss 0.0356 (0.0338) Prec@1 93.000 (94.188) Prec@5 100.000 (99.875) +2022-11-14 14:53:02,147 Epoch: [268][480/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0510 (0.0342) Prec@1 92.000 (94.143) Prec@5 100.000 (99.878) +2022-11-14 14:53:02,625 Epoch: [268][490/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0157 (0.0338) Prec@1 98.000 (94.220) Prec@5 100.000 (99.880) +2022-11-14 14:53:03,056 Epoch: [268][499/500] Time 0.043 (0.043) Data 0.002 (0.002) Loss 0.0332 (0.0338) Prec@1 95.000 (94.235) Prec@5 100.000 (99.882) +2022-11-14 14:53:03,349 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0869 (0.0869) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:03,361 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0828) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:03,371 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0772) Prec@1 90.000 (86.667) Prec@5 99.000 (99.667) +2022-11-14 14:53:03,384 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0724) Prec@1 90.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 14:53:03,393 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0744) Prec@1 87.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 14:53:03,403 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0704) Prec@1 92.000 (88.167) Prec@5 100.000 (99.667) +2022-11-14 14:53:03,412 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0672) Prec@1 92.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 14:53:03,423 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0708) Prec@1 83.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 14:53:03,432 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0721) Prec@1 87.000 (87.889) Prec@5 100.000 (99.556) +2022-11-14 14:53:03,442 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0723) Prec@1 87.000 (87.800) Prec@5 99.000 (99.500) +2022-11-14 14:53:03,453 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0712) Prec@1 90.000 (88.000) Prec@5 100.000 (99.545) +2022-11-14 14:53:03,462 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0721) Prec@1 88.000 (88.000) Prec@5 100.000 (99.583) +2022-11-14 14:53:03,473 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0698) Prec@1 92.000 (88.308) Prec@5 100.000 (99.615) +2022-11-14 14:53:03,485 Test: [13/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0715) Prec@1 84.000 (88.000) Prec@5 100.000 (99.643) +2022-11-14 14:53:03,497 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0717) Prec@1 89.000 (88.067) Prec@5 99.000 (99.600) +2022-11-14 14:53:03,509 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0717) Prec@1 87.000 (88.000) Prec@5 99.000 (99.562) +2022-11-14 14:53:03,521 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0707) Prec@1 91.000 (88.176) Prec@5 98.000 (99.471) +2022-11-14 14:53:03,531 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0726) Prec@1 84.000 (87.944) Prec@5 99.000 (99.444) +2022-11-14 14:53:03,542 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0736) Prec@1 86.000 (87.842) Prec@5 98.000 (99.368) +2022-11-14 14:53:03,553 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0748) Prec@1 84.000 (87.650) Prec@5 98.000 (99.300) +2022-11-14 14:53:03,565 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0763) Prec@1 84.000 (87.476) Prec@5 100.000 (99.333) +2022-11-14 14:53:03,575 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0760) Prec@1 89.000 (87.545) Prec@5 99.000 (99.318) +2022-11-14 14:53:03,587 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0767) Prec@1 86.000 (87.478) Prec@5 97.000 (99.217) +2022-11-14 14:53:03,598 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0767) Prec@1 87.000 (87.458) Prec@5 99.000 (99.208) +2022-11-14 14:53:03,609 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0766) Prec@1 87.000 (87.440) Prec@5 100.000 (99.240) +2022-11-14 14:53:03,620 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0770) Prec@1 85.000 (87.346) Prec@5 98.000 (99.192) +2022-11-14 14:53:03,631 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0762) Prec@1 92.000 (87.519) Prec@5 100.000 (99.222) +2022-11-14 14:53:03,640 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0756) Prec@1 89.000 (87.571) Prec@5 100.000 (99.250) +2022-11-14 14:53:03,652 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0755) Prec@1 89.000 (87.621) Prec@5 99.000 (99.241) +2022-11-14 14:53:03,663 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0747) Prec@1 92.000 (87.767) Prec@5 100.000 (99.267) +2022-11-14 14:53:03,675 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0745) Prec@1 89.000 (87.806) Prec@5 99.000 (99.258) +2022-11-14 14:53:03,687 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0744) Prec@1 87.000 (87.781) Prec@5 99.000 (99.250) +2022-11-14 14:53:03,699 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0743) Prec@1 88.000 (87.788) Prec@5 99.000 (99.242) +2022-11-14 14:53:03,711 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0747) Prec@1 85.000 (87.706) Prec@5 100.000 (99.265) +2022-11-14 14:53:03,722 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0751) Prec@1 84.000 (87.600) Prec@5 99.000 (99.257) +2022-11-14 14:53:03,735 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0748) Prec@1 89.000 (87.639) Prec@5 98.000 (99.222) +2022-11-14 14:53:03,748 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0747) Prec@1 89.000 (87.676) Prec@5 99.000 (99.216) +2022-11-14 14:53:03,760 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0757) Prec@1 81.000 (87.500) Prec@5 99.000 (99.211) +2022-11-14 14:53:03,771 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0753) Prec@1 91.000 (87.590) Prec@5 99.000 (99.205) +2022-11-14 14:53:03,783 Test: [39/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0753) Prec@1 87.000 (87.575) Prec@5 99.000 (99.200) +2022-11-14 14:53:03,795 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0759) Prec@1 84.000 (87.488) Prec@5 97.000 (99.146) +2022-11-14 14:53:03,807 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0756) Prec@1 90.000 (87.548) Prec@5 99.000 (99.143) +2022-11-14 14:53:03,817 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0748) Prec@1 94.000 (87.698) Prec@5 100.000 (99.163) +2022-11-14 14:53:03,829 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0750) Prec@1 87.000 (87.682) Prec@5 98.000 (99.136) +2022-11-14 14:53:03,840 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0746) Prec@1 91.000 (87.756) Prec@5 99.000 (99.133) +2022-11-14 14:53:03,851 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0750) Prec@1 84.000 (87.674) Prec@5 99.000 (99.130) +2022-11-14 14:53:03,862 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0751) Prec@1 86.000 (87.638) Prec@5 100.000 (99.149) +2022-11-14 14:53:03,872 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0755) Prec@1 87.000 (87.625) Prec@5 99.000 (99.146) +2022-11-14 14:53:03,884 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0751) Prec@1 89.000 (87.653) Prec@5 100.000 (99.163) +2022-11-14 14:53:03,896 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0757) Prec@1 83.000 (87.560) Prec@5 99.000 (99.160) +2022-11-14 14:53:03,906 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0758) Prec@1 85.000 (87.510) Prec@5 100.000 (99.176) +2022-11-14 14:53:03,917 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0758) Prec@1 84.000 (87.442) Prec@5 100.000 (99.192) +2022-11-14 14:53:03,928 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0759) Prec@1 86.000 (87.415) Prec@5 100.000 (99.208) +2022-11-14 14:53:03,941 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0760) Prec@1 87.000 (87.407) Prec@5 99.000 (99.204) +2022-11-14 14:53:03,952 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0763) Prec@1 85.000 (87.364) Prec@5 99.000 (99.200) +2022-11-14 14:53:03,963 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0764) Prec@1 84.000 (87.304) Prec@5 99.000 (99.196) +2022-11-14 14:53:03,976 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0762) Prec@1 88.000 (87.316) Prec@5 100.000 (99.211) +2022-11-14 14:53:03,987 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0758) Prec@1 93.000 (87.414) Prec@5 100.000 (99.224) +2022-11-14 14:53:04,001 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0761) Prec@1 83.000 (87.339) Prec@5 99.000 (99.220) +2022-11-14 14:53:04,012 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0761) Prec@1 83.000 (87.267) Prec@5 100.000 (99.233) +2022-11-14 14:53:04,025 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0760) Prec@1 90.000 (87.311) Prec@5 100.000 (99.246) +2022-11-14 14:53:04,038 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0757) Prec@1 89.000 (87.339) Prec@5 99.000 (99.242) +2022-11-14 14:53:04,049 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0755) Prec@1 89.000 (87.365) Prec@5 100.000 (99.254) +2022-11-14 14:53:04,060 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0426 (0.0750) Prec@1 91.000 (87.422) Prec@5 99.000 (99.250) +2022-11-14 14:53:04,071 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0753) Prec@1 82.000 (87.338) Prec@5 100.000 (99.262) +2022-11-14 14:53:04,084 Test: [65/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0755) Prec@1 84.000 (87.288) Prec@5 100.000 (99.273) +2022-11-14 14:53:04,094 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0320 (0.0749) Prec@1 95.000 (87.403) Prec@5 100.000 (99.284) +2022-11-14 14:53:04,106 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0745) Prec@1 92.000 (87.471) Prec@5 99.000 (99.279) +2022-11-14 14:53:04,117 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0741) Prec@1 92.000 (87.536) Prec@5 99.000 (99.275) +2022-11-14 14:53:04,129 Test: [69/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0741) Prec@1 85.000 (87.500) Prec@5 99.000 (99.271) +2022-11-14 14:53:04,141 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0746) Prec@1 83.000 (87.437) Prec@5 100.000 (99.282) +2022-11-14 14:53:04,153 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0745) Prec@1 90.000 (87.472) Prec@5 100.000 (99.292) +2022-11-14 14:53:04,164 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0744) Prec@1 89.000 (87.493) Prec@5 100.000 (99.301) +2022-11-14 14:53:04,177 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0740) Prec@1 94.000 (87.581) Prec@5 99.000 (99.297) +2022-11-14 14:53:04,189 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0742) Prec@1 90.000 (87.613) Prec@5 100.000 (99.307) +2022-11-14 14:53:04,199 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0742) Prec@1 87.000 (87.605) Prec@5 100.000 (99.316) +2022-11-14 14:53:04,211 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0740) Prec@1 89.000 (87.623) Prec@5 99.000 (99.312) +2022-11-14 14:53:04,222 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0742) Prec@1 85.000 (87.590) Prec@5 98.000 (99.295) +2022-11-14 14:53:04,231 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0745) Prec@1 83.000 (87.532) Prec@5 99.000 (99.291) +2022-11-14 14:53:04,243 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0747) Prec@1 86.000 (87.513) Prec@5 100.000 (99.300) +2022-11-14 14:53:04,254 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0748) Prec@1 89.000 (87.531) Prec@5 99.000 (99.296) +2022-11-14 14:53:04,266 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0748) Prec@1 88.000 (87.537) Prec@5 99.000 (99.293) +2022-11-14 14:53:04,277 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0749) Prec@1 85.000 (87.506) Prec@5 100.000 (99.301) +2022-11-14 14:53:04,289 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0748) Prec@1 87.000 (87.500) Prec@5 99.000 (99.298) +2022-11-14 14:53:04,301 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0750) Prec@1 86.000 (87.482) Prec@5 99.000 (99.294) +2022-11-14 14:53:04,313 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0753) Prec@1 85.000 (87.453) Prec@5 100.000 (99.302) +2022-11-14 14:53:04,323 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0753) Prec@1 87.000 (87.448) Prec@5 99.000 (99.299) +2022-11-14 14:53:04,334 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0754) Prec@1 87.000 (87.443) Prec@5 98.000 (99.284) +2022-11-14 14:53:04,345 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0754) Prec@1 87.000 (87.438) Prec@5 100.000 (99.292) +2022-11-14 14:53:04,356 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0753) Prec@1 89.000 (87.456) Prec@5 98.000 (99.278) +2022-11-14 14:53:04,368 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0752) Prec@1 91.000 (87.495) Prec@5 100.000 (99.286) +2022-11-14 14:53:04,378 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0749) Prec@1 92.000 (87.543) Prec@5 99.000 (99.283) +2022-11-14 14:53:04,389 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0751) Prec@1 84.000 (87.505) Prec@5 100.000 (99.290) +2022-11-14 14:53:04,399 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0750) Prec@1 88.000 (87.511) Prec@5 99.000 (99.287) +2022-11-14 14:53:04,412 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 87.000 (87.505) Prec@5 100.000 (99.295) +2022-11-14 14:53:04,424 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0750) Prec@1 90.000 (87.531) Prec@5 99.000 (99.292) +2022-11-14 14:53:04,436 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0746) Prec@1 94.000 (87.598) Prec@5 99.000 (99.289) +2022-11-14 14:53:04,449 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0748) Prec@1 87.000 (87.592) Prec@5 99.000 (99.286) +2022-11-14 14:53:04,461 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0750) Prec@1 85.000 (87.566) Prec@5 99.000 (99.283) +2022-11-14 14:53:04,474 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0749) Prec@1 88.000 (87.570) Prec@5 99.000 (99.280) +2022-11-14 14:53:04,544 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:53:04,858 Epoch: [269][0/500] Time 0.026 (0.026) Data 0.227 (0.227) Loss 0.0191 (0.0191) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:05,074 Epoch: [269][10/500] Time 0.018 (0.020) Data 0.002 (0.022) Loss 0.0167 (0.0179) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:05,279 Epoch: [269][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0273 (0.0210) Prec@1 95.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 14:53:05,564 Epoch: [269][30/500] Time 0.022 (0.021) Data 0.002 (0.009) Loss 0.0272 (0.0225) Prec@1 96.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 14:53:05,879 Epoch: [269][40/500] Time 0.032 (0.023) Data 0.002 (0.007) Loss 0.0549 (0.0290) Prec@1 90.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:06,208 Epoch: [269][50/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.0366 (0.0303) Prec@1 94.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 14:53:06,477 Epoch: [269][60/500] Time 0.024 (0.024) Data 0.002 (0.006) Loss 0.0546 (0.0338) Prec@1 89.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:06,756 Epoch: [269][70/500] Time 0.026 (0.024) Data 0.002 (0.005) Loss 0.0678 (0.0380) Prec@1 88.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 14:53:07,032 Epoch: [269][80/500] Time 0.025 (0.024) Data 0.002 (0.005) Loss 0.0575 (0.0402) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:07,307 Epoch: [269][90/500] Time 0.026 (0.024) Data 0.001 (0.004) Loss 0.0261 (0.0388) Prec@1 97.000 (93.400) Prec@5 100.000 (100.000) +2022-11-14 14:53:07,600 Epoch: [269][100/500] Time 0.029 (0.024) Data 0.002 (0.004) Loss 0.0262 (0.0376) Prec@1 95.000 (93.545) Prec@5 100.000 (100.000) +2022-11-14 14:53:08,073 Epoch: [269][110/500] Time 0.042 (0.026) Data 0.002 (0.004) Loss 0.0214 (0.0363) Prec@1 97.000 (93.833) Prec@5 100.000 (100.000) +2022-11-14 14:53:08,547 Epoch: [269][120/500] Time 0.043 (0.027) Data 0.002 (0.004) Loss 0.0146 (0.0346) Prec@1 99.000 (94.231) Prec@5 99.000 (99.923) +2022-11-14 14:53:09,023 Epoch: [269][130/500] Time 0.041 (0.028) Data 0.002 (0.004) Loss 0.0290 (0.0342) Prec@1 94.000 (94.214) Prec@5 100.000 (99.929) +2022-11-14 14:53:09,494 Epoch: [269][140/500] Time 0.047 (0.029) Data 0.002 (0.003) Loss 0.0364 (0.0344) Prec@1 92.000 (94.067) Prec@5 100.000 (99.933) +2022-11-14 14:53:09,967 Epoch: [269][150/500] Time 0.048 (0.030) Data 0.002 (0.003) Loss 0.0367 (0.0345) Prec@1 93.000 (94.000) Prec@5 100.000 (99.938) +2022-11-14 14:53:10,447 Epoch: [269][160/500] Time 0.044 (0.031) Data 0.002 (0.003) Loss 0.0377 (0.0347) Prec@1 94.000 (94.000) Prec@5 100.000 (99.941) +2022-11-14 14:53:10,940 Epoch: [269][170/500] Time 0.046 (0.032) Data 0.002 (0.003) Loss 0.0355 (0.0347) Prec@1 93.000 (93.944) Prec@5 100.000 (99.944) +2022-11-14 14:53:11,423 Epoch: [269][180/500] Time 0.041 (0.032) Data 0.002 (0.003) Loss 0.0261 (0.0343) Prec@1 94.000 (93.947) Prec@5 100.000 (99.947) +2022-11-14 14:53:11,890 Epoch: [269][190/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0484 (0.0350) Prec@1 93.000 (93.900) Prec@5 100.000 (99.950) +2022-11-14 14:53:12,364 Epoch: [269][200/500] Time 0.043 (0.033) Data 0.002 (0.003) Loss 0.0451 (0.0355) Prec@1 94.000 (93.905) Prec@5 99.000 (99.905) +2022-11-14 14:53:12,837 Epoch: [269][210/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0413 (0.0357) Prec@1 93.000 (93.864) Prec@5 100.000 (99.909) +2022-11-14 14:53:13,311 Epoch: [269][220/500] Time 0.044 (0.034) Data 0.002 (0.003) Loss 0.0321 (0.0356) Prec@1 95.000 (93.913) Prec@5 100.000 (99.913) +2022-11-14 14:53:13,782 Epoch: [269][230/500] Time 0.043 (0.034) Data 0.002 (0.003) Loss 0.0454 (0.0360) Prec@1 93.000 (93.875) Prec@5 100.000 (99.917) +2022-11-14 14:53:14,382 Epoch: [269][240/500] Time 0.059 (0.035) Data 0.002 (0.003) Loss 0.0424 (0.0362) Prec@1 93.000 (93.840) Prec@5 100.000 (99.920) +2022-11-14 14:53:15,025 Epoch: [269][250/500] Time 0.067 (0.036) Data 0.002 (0.003) Loss 0.0415 (0.0364) Prec@1 92.000 (93.769) Prec@5 100.000 (99.923) +2022-11-14 14:53:15,494 Epoch: [269][260/500] Time 0.054 (0.036) Data 0.002 (0.003) Loss 0.0294 (0.0362) Prec@1 96.000 (93.852) Prec@5 100.000 (99.926) +2022-11-14 14:53:16,009 Epoch: [269][270/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0280 (0.0359) Prec@1 95.000 (93.893) Prec@5 100.000 (99.929) +2022-11-14 14:53:16,596 Epoch: [269][280/500] Time 0.062 (0.037) Data 0.002 (0.003) Loss 0.0331 (0.0358) Prec@1 95.000 (93.931) Prec@5 100.000 (99.931) +2022-11-14 14:53:17,209 Epoch: [269][290/500] Time 0.059 (0.038) Data 0.002 (0.003) Loss 0.0414 (0.0360) Prec@1 92.000 (93.867) Prec@5 100.000 (99.933) +2022-11-14 14:53:17,825 Epoch: [269][300/500] Time 0.064 (0.038) Data 0.002 (0.003) Loss 0.0439 (0.0362) Prec@1 91.000 (93.774) Prec@5 100.000 (99.935) +2022-11-14 14:53:18,396 Epoch: [269][310/500] Time 0.055 (0.039) Data 0.002 (0.003) Loss 0.0380 (0.0363) Prec@1 93.000 (93.750) Prec@5 100.000 (99.938) +2022-11-14 14:53:18,986 Epoch: [269][320/500] Time 0.058 (0.039) Data 0.002 (0.003) Loss 0.0474 (0.0366) Prec@1 92.000 (93.697) Prec@5 100.000 (99.939) +2022-11-14 14:53:19,509 Epoch: [269][330/500] Time 0.053 (0.039) Data 0.002 (0.003) Loss 0.0565 (0.0372) Prec@1 91.000 (93.618) Prec@5 100.000 (99.941) +2022-11-14 14:53:20,123 Epoch: [269][340/500] Time 0.062 (0.040) Data 0.002 (0.003) Loss 0.0349 (0.0371) Prec@1 96.000 (93.686) Prec@5 100.000 (99.943) +2022-11-14 14:53:20,705 Epoch: [269][350/500] Time 0.053 (0.040) Data 0.002 (0.003) Loss 0.0458 (0.0374) Prec@1 91.000 (93.611) Prec@5 99.000 (99.917) +2022-11-14 14:53:21,201 Epoch: [269][360/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0286 (0.0371) Prec@1 95.000 (93.649) Prec@5 100.000 (99.919) +2022-11-14 14:53:21,677 Epoch: [269][370/500] Time 0.052 (0.040) Data 0.002 (0.003) Loss 0.0378 (0.0372) Prec@1 95.000 (93.684) Prec@5 100.000 (99.921) +2022-11-14 14:53:22,146 Epoch: [269][380/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0355 (0.0371) Prec@1 96.000 (93.744) Prec@5 100.000 (99.923) +2022-11-14 14:53:22,763 Epoch: [269][390/500] Time 0.063 (0.041) Data 0.002 (0.003) Loss 0.0247 (0.0368) Prec@1 98.000 (93.850) Prec@5 100.000 (99.925) +2022-11-14 14:53:23,393 Epoch: [269][400/500] Time 0.068 (0.041) Data 0.002 (0.003) Loss 0.0494 (0.0371) Prec@1 90.000 (93.756) Prec@5 100.000 (99.927) +2022-11-14 14:53:23,855 Epoch: [269][410/500] Time 0.045 (0.041) Data 0.002 (0.002) Loss 0.0318 (0.0370) Prec@1 94.000 (93.762) Prec@5 100.000 (99.929) +2022-11-14 14:53:24,353 Epoch: [269][420/500] Time 0.051 (0.041) Data 0.002 (0.002) Loss 0.0438 (0.0372) Prec@1 93.000 (93.744) Prec@5 100.000 (99.930) +2022-11-14 14:53:24,977 Epoch: [269][430/500] Time 0.066 (0.042) Data 0.002 (0.002) Loss 0.0460 (0.0374) Prec@1 91.000 (93.682) Prec@5 100.000 (99.932) +2022-11-14 14:53:25,508 Epoch: [269][440/500] Time 0.053 (0.042) Data 0.002 (0.002) Loss 0.0813 (0.0383) Prec@1 85.000 (93.489) Prec@5 99.000 (99.911) +2022-11-14 14:53:26,091 Epoch: [269][450/500] Time 0.056 (0.042) Data 0.002 (0.002) Loss 0.0344 (0.0382) Prec@1 95.000 (93.522) Prec@5 100.000 (99.913) +2022-11-14 14:53:26,628 Epoch: [269][460/500] Time 0.061 (0.042) Data 0.002 (0.002) Loss 0.0214 (0.0379) Prec@1 98.000 (93.617) Prec@5 100.000 (99.915) +2022-11-14 14:53:27,166 Epoch: [269][470/500] Time 0.032 (0.042) Data 0.002 (0.002) Loss 0.0496 (0.0381) Prec@1 92.000 (93.583) Prec@5 99.000 (99.896) +2022-11-14 14:53:27,642 Epoch: [269][480/500] Time 0.046 (0.042) Data 0.002 (0.002) Loss 0.0194 (0.0378) Prec@1 98.000 (93.673) Prec@5 100.000 (99.898) +2022-11-14 14:53:28,107 Epoch: [269][490/500] Time 0.044 (0.042) Data 0.002 (0.002) Loss 0.0272 (0.0375) Prec@1 98.000 (93.760) Prec@5 100.000 (99.900) +2022-11-14 14:53:28,531 Epoch: [269][499/500] Time 0.045 (0.042) Data 0.002 (0.002) Loss 0.0261 (0.0373) Prec@1 93.000 (93.745) Prec@5 100.000 (99.902) +2022-11-14 14:53:28,840 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0724 (0.0724) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 14:53:28,849 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0692 (0.0708) Prec@1 88.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 14:53:28,858 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0695) Prec@1 90.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 14:53:28,871 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0704) Prec@1 87.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 14:53:28,881 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0740) Prec@1 88.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 14:53:28,890 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0700) Prec@1 90.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 14:53:28,901 Test: [6/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0692) Prec@1 90.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 14:53:28,912 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0693) Prec@1 88.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 14:53:28,920 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0728) Prec@1 83.000 (87.778) Prec@5 97.000 (99.333) +2022-11-14 14:53:28,927 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0747) Prec@1 84.000 (87.400) Prec@5 99.000 (99.300) +2022-11-14 14:53:28,939 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0727) Prec@1 92.000 (87.818) Prec@5 99.000 (99.273) +2022-11-14 14:53:28,950 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0739) Prec@1 84.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 14:53:28,959 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0434 (0.0715) Prec@1 95.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 14:53:28,969 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0723) Prec@1 87.000 (88.000) Prec@5 99.000 (99.357) +2022-11-14 14:53:28,981 Test: [14/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0729) Prec@1 86.000 (87.867) Prec@5 100.000 (99.400) +2022-11-14 14:53:28,992 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0725) Prec@1 88.000 (87.875) Prec@5 100.000 (99.438) +2022-11-14 14:53:29,001 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0715) Prec@1 92.000 (88.118) Prec@5 98.000 (99.353) +2022-11-14 14:53:29,010 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0732) Prec@1 83.000 (87.833) Prec@5 100.000 (99.389) +2022-11-14 14:53:29,023 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0735) Prec@1 86.000 (87.737) Prec@5 99.000 (99.368) +2022-11-14 14:53:29,035 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0751) Prec@1 85.000 (87.600) Prec@5 96.000 (99.200) +2022-11-14 14:53:29,045 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0747) Prec@1 89.000 (87.667) Prec@5 100.000 (99.238) +2022-11-14 14:53:29,055 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0746) Prec@1 87.000 (87.636) Prec@5 100.000 (99.273) +2022-11-14 14:53:29,066 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0757) Prec@1 85.000 (87.522) Prec@5 97.000 (99.174) +2022-11-14 14:53:29,078 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0750) Prec@1 93.000 (87.750) Prec@5 99.000 (99.167) +2022-11-14 14:53:29,089 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0754) Prec@1 89.000 (87.800) Prec@5 100.000 (99.200) +2022-11-14 14:53:29,100 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0759) Prec@1 86.000 (87.731) Prec@5 99.000 (99.192) +2022-11-14 14:53:29,111 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0752) Prec@1 90.000 (87.815) Prec@5 100.000 (99.222) +2022-11-14 14:53:29,122 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0746) Prec@1 91.000 (87.929) Prec@5 100.000 (99.250) +2022-11-14 14:53:29,132 Test: [28/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0748) Prec@1 88.000 (87.931) Prec@5 99.000 (99.241) +2022-11-14 14:53:29,142 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0742) Prec@1 90.000 (88.000) Prec@5 100.000 (99.267) +2022-11-14 14:53:29,154 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0736) Prec@1 93.000 (88.161) Prec@5 99.000 (99.258) +2022-11-14 14:53:29,165 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0733) Prec@1 91.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 14:53:29,175 Test: [32/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0732) Prec@1 89.000 (88.273) Prec@5 100.000 (99.273) +2022-11-14 14:53:29,185 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.0742) Prec@1 81.000 (88.059) Prec@5 100.000 (99.294) +2022-11-14 14:53:29,197 Test: [34/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0742) Prec@1 87.000 (88.029) Prec@5 98.000 (99.257) +2022-11-14 14:53:29,209 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0742) Prec@1 90.000 (88.083) Prec@5 100.000 (99.278) +2022-11-14 14:53:29,219 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0743) Prec@1 88.000 (88.081) Prec@5 99.000 (99.270) +2022-11-14 14:53:29,230 Test: [37/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0748) Prec@1 84.000 (87.974) Prec@5 99.000 (99.263) +2022-11-14 14:53:29,242 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0744) Prec@1 92.000 (88.077) Prec@5 99.000 (99.256) +2022-11-14 14:53:29,253 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0741) Prec@1 91.000 (88.150) Prec@5 99.000 (99.250) +2022-11-14 14:53:29,263 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0745) Prec@1 86.000 (88.098) Prec@5 98.000 (99.220) +2022-11-14 14:53:29,272 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0742) Prec@1 88.000 (88.095) Prec@5 99.000 (99.214) +2022-11-14 14:53:29,284 Test: [42/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0411 (0.0735) Prec@1 93.000 (88.209) Prec@5 100.000 (99.233) +2022-11-14 14:53:29,296 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0734) Prec@1 90.000 (88.250) Prec@5 99.000 (99.227) +2022-11-14 14:53:29,307 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0728) Prec@1 90.000 (88.289) Prec@5 100.000 (99.244) +2022-11-14 14:53:29,317 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0731) Prec@1 87.000 (88.261) Prec@5 99.000 (99.239) +2022-11-14 14:53:29,329 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0731) Prec@1 87.000 (88.234) Prec@5 100.000 (99.255) +2022-11-14 14:53:29,341 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1182 (0.0740) Prec@1 81.000 (88.083) Prec@5 99.000 (99.250) +2022-11-14 14:53:29,350 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0735) Prec@1 92.000 (88.163) Prec@5 100.000 (99.265) +2022-11-14 14:53:29,361 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0740) Prec@1 86.000 (88.120) Prec@5 98.000 (99.240) +2022-11-14 14:53:29,373 Test: [50/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0741) Prec@1 86.000 (88.078) Prec@5 99.000 (99.235) +2022-11-14 14:53:29,386 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0747) Prec@1 82.000 (87.962) Prec@5 100.000 (99.250) +2022-11-14 14:53:29,397 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0751) Prec@1 83.000 (87.868) Prec@5 99.000 (99.245) +2022-11-14 14:53:29,407 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0754) Prec@1 85.000 (87.815) Prec@5 98.000 (99.222) +2022-11-14 14:53:29,417 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0756) Prec@1 86.000 (87.782) Prec@5 100.000 (99.236) +2022-11-14 14:53:29,427 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0752) Prec@1 92.000 (87.857) Prec@5 99.000 (99.232) +2022-11-14 14:53:29,438 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0748) Prec@1 91.000 (87.912) Prec@5 100.000 (99.246) +2022-11-14 14:53:29,448 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0748) Prec@1 89.000 (87.931) Prec@5 100.000 (99.259) +2022-11-14 14:53:29,458 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0751) Prec@1 86.000 (87.898) Prec@5 99.000 (99.254) +2022-11-14 14:53:29,468 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0753) Prec@1 84.000 (87.833) Prec@5 99.000 (99.250) +2022-11-14 14:53:29,478 Test: [60/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0755) Prec@1 85.000 (87.787) Prec@5 99.000 (99.246) +2022-11-14 14:53:29,487 Test: [61/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0757) Prec@1 86.000 (87.758) Prec@5 99.000 (99.242) +2022-11-14 14:53:29,497 Test: [62/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0758) Prec@1 87.000 (87.746) Prec@5 99.000 (99.238) +2022-11-14 14:53:29,508 Test: [63/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0354 (0.0752) Prec@1 94.000 (87.844) Prec@5 100.000 (99.250) +2022-11-14 14:53:29,518 Test: [64/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0755) Prec@1 86.000 (87.815) Prec@5 99.000 (99.246) +2022-11-14 14:53:29,528 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0756) Prec@1 87.000 (87.803) Prec@5 99.000 (99.242) +2022-11-14 14:53:29,539 Test: [66/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0753) Prec@1 92.000 (87.866) Prec@5 100.000 (99.254) +2022-11-14 14:53:29,550 Test: [67/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0753) Prec@1 88.000 (87.868) Prec@5 98.000 (99.235) +2022-11-14 14:53:29,560 Test: [68/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0753) Prec@1 86.000 (87.841) Prec@5 99.000 (99.232) +2022-11-14 14:53:29,573 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0754) Prec@1 87.000 (87.829) Prec@5 98.000 (99.214) +2022-11-14 14:53:29,583 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1020 (0.0758) Prec@1 87.000 (87.817) Prec@5 99.000 (99.211) +2022-11-14 14:53:29,593 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0757) Prec@1 88.000 (87.819) Prec@5 100.000 (99.222) +2022-11-14 14:53:29,604 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0756) Prec@1 90.000 (87.849) Prec@5 100.000 (99.233) +2022-11-14 14:53:29,613 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0754) Prec@1 89.000 (87.865) Prec@5 100.000 (99.243) +2022-11-14 14:53:29,624 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0758) Prec@1 85.000 (87.827) Prec@5 99.000 (99.240) +2022-11-14 14:53:29,634 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0757) Prec@1 89.000 (87.842) Prec@5 100.000 (99.250) +2022-11-14 14:53:29,645 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0756) Prec@1 87.000 (87.831) Prec@5 98.000 (99.234) +2022-11-14 14:53:29,656 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0760) Prec@1 83.000 (87.769) Prec@5 97.000 (99.205) +2022-11-14 14:53:29,666 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0759) Prec@1 89.000 (87.785) Prec@5 100.000 (99.215) +2022-11-14 14:53:29,676 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0760) Prec@1 86.000 (87.763) Prec@5 100.000 (99.225) +2022-11-14 14:53:29,686 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0761) Prec@1 86.000 (87.741) Prec@5 99.000 (99.222) +2022-11-14 14:53:29,698 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0762) Prec@1 84.000 (87.695) Prec@5 100.000 (99.232) +2022-11-14 14:53:29,709 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0763) Prec@1 87.000 (87.687) Prec@5 100.000 (99.241) +2022-11-14 14:53:29,719 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0762) Prec@1 86.000 (87.667) Prec@5 100.000 (99.250) +2022-11-14 14:53:29,730 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0762) Prec@1 89.000 (87.682) Prec@5 100.000 (99.259) +2022-11-14 14:53:29,740 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0766) Prec@1 85.000 (87.651) Prec@5 100.000 (99.267) +2022-11-14 14:53:29,751 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0766) Prec@1 86.000 (87.632) Prec@5 98.000 (99.253) +2022-11-14 14:53:29,761 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0766) Prec@1 89.000 (87.648) Prec@5 99.000 (99.250) +2022-11-14 14:53:29,771 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0766) Prec@1 89.000 (87.663) Prec@5 100.000 (99.258) +2022-11-14 14:53:29,781 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0766) Prec@1 88.000 (87.667) Prec@5 100.000 (99.267) +2022-11-14 14:53:29,792 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0763) Prec@1 92.000 (87.714) Prec@5 100.000 (99.275) +2022-11-14 14:53:29,801 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0761) Prec@1 92.000 (87.761) Prec@5 100.000 (99.283) +2022-11-14 14:53:29,811 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0762) Prec@1 86.000 (87.742) Prec@5 100.000 (99.290) +2022-11-14 14:53:29,822 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0762) Prec@1 87.000 (87.734) Prec@5 98.000 (99.277) +2022-11-14 14:53:29,833 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0763) Prec@1 85.000 (87.705) Prec@5 98.000 (99.263) +2022-11-14 14:53:29,843 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0763) Prec@1 89.000 (87.719) Prec@5 99.000 (99.260) +2022-11-14 14:53:29,852 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0761) Prec@1 90.000 (87.742) Prec@5 99.000 (99.258) +2022-11-14 14:53:29,864 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0762) Prec@1 86.000 (87.724) Prec@5 99.000 (99.255) +2022-11-14 14:53:29,874 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0764) Prec@1 86.000 (87.707) Prec@5 100.000 (99.263) +2022-11-14 14:53:29,884 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0761) Prec@1 91.000 (87.740) Prec@5 100.000 (99.270) +2022-11-14 14:53:29,943 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:53:30,253 Epoch: [270][0/500] Time 0.025 (0.025) Data 0.225 (0.225) Loss 0.0385 (0.0385) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:30,465 Epoch: [270][10/500] Time 0.022 (0.019) Data 0.002 (0.022) Loss 0.0365 (0.0375) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:53:30,732 Epoch: [270][20/500] Time 0.027 (0.021) Data 0.002 (0.012) Loss 0.0222 (0.0324) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:30,953 Epoch: [270][30/500] Time 0.021 (0.021) Data 0.002 (0.009) Loss 0.0382 (0.0339) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:31,266 Epoch: [270][40/500] Time 0.030 (0.022) Data 0.002 (0.007) Loss 0.0450 (0.0361) Prec@1 91.000 (94.200) Prec@5 99.000 (99.800) +2022-11-14 14:53:31,579 Epoch: [270][50/500] Time 0.028 (0.023) Data 0.002 (0.006) Loss 0.0225 (0.0338) Prec@1 96.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 14:53:31,986 Epoch: [270][60/500] Time 0.046 (0.025) Data 0.003 (0.006) Loss 0.0180 (0.0316) Prec@1 97.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 14:53:32,492 Epoch: [270][70/500] Time 0.048 (0.028) Data 0.002 (0.005) Loss 0.0449 (0.0332) Prec@1 92.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 14:53:32,890 Epoch: [270][80/500] Time 0.037 (0.029) Data 0.002 (0.005) Loss 0.0241 (0.0322) Prec@1 96.000 (94.667) Prec@5 100.000 (99.889) +2022-11-14 14:53:33,300 Epoch: [270][90/500] Time 0.037 (0.030) Data 0.002 (0.004) Loss 0.0336 (0.0324) Prec@1 95.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 14:53:33,712 Epoch: [270][100/500] Time 0.039 (0.031) Data 0.002 (0.004) Loss 0.0263 (0.0318) Prec@1 94.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 14:53:34,136 Epoch: [270][110/500] Time 0.037 (0.031) Data 0.001 (0.004) Loss 0.0149 (0.0304) Prec@1 97.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 14:53:34,568 Epoch: [270][120/500] Time 0.044 (0.032) Data 0.002 (0.004) Loss 0.0277 (0.0302) Prec@1 95.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 14:53:34,966 Epoch: [270][130/500] Time 0.035 (0.032) Data 0.002 (0.004) Loss 0.0380 (0.0308) Prec@1 94.000 (94.786) Prec@5 99.000 (99.857) +2022-11-14 14:53:35,373 Epoch: [270][140/500] Time 0.037 (0.032) Data 0.002 (0.004) Loss 0.0615 (0.0328) Prec@1 87.000 (94.267) Prec@5 99.000 (99.800) +2022-11-14 14:53:35,790 Epoch: [270][150/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0347 (0.0329) Prec@1 94.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 14:53:36,189 Epoch: [270][160/500] Time 0.036 (0.033) Data 0.003 (0.003) Loss 0.0467 (0.0337) Prec@1 93.000 (94.176) Prec@5 100.000 (99.765) +2022-11-14 14:53:36,609 Epoch: [270][170/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0303 (0.0335) Prec@1 95.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 14:53:37,020 Epoch: [270][180/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0359 (0.0337) Prec@1 94.000 (94.211) Prec@5 100.000 (99.789) +2022-11-14 14:53:37,424 Epoch: [270][190/500] Time 0.037 (0.033) Data 0.002 (0.003) Loss 0.0314 (0.0335) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 14:53:37,866 Epoch: [270][200/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0439 (0.0340) Prec@1 94.000 (94.190) Prec@5 100.000 (99.810) +2022-11-14 14:53:38,292 Epoch: [270][210/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0459 (0.0346) Prec@1 93.000 (94.136) Prec@5 100.000 (99.818) +2022-11-14 14:53:38,697 Epoch: [270][220/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0338 (0.0345) Prec@1 95.000 (94.174) Prec@5 100.000 (99.826) +2022-11-14 14:53:39,120 Epoch: [270][230/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0141 (0.0337) Prec@1 99.000 (94.375) Prec@5 100.000 (99.833) +2022-11-14 14:53:39,530 Epoch: [270][240/500] Time 0.032 (0.034) Data 0.002 (0.003) Loss 0.0269 (0.0334) Prec@1 95.000 (94.400) Prec@5 100.000 (99.840) +2022-11-14 14:53:39,938 Epoch: [270][250/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0422 (0.0338) Prec@1 92.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 14:53:40,339 Epoch: [270][260/500] Time 0.038 (0.034) Data 0.002 (0.003) Loss 0.0278 (0.0335) Prec@1 94.000 (94.296) Prec@5 100.000 (99.852) +2022-11-14 14:53:40,793 Epoch: [270][270/500] Time 0.048 (0.035) Data 0.002 (0.003) Loss 0.0400 (0.0338) Prec@1 94.000 (94.286) Prec@5 99.000 (99.821) +2022-11-14 14:53:41,185 Epoch: [270][280/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0295 (0.0336) Prec@1 95.000 (94.310) Prec@5 100.000 (99.828) +2022-11-14 14:53:41,600 Epoch: [270][290/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0201 (0.0332) Prec@1 97.000 (94.400) Prec@5 100.000 (99.833) +2022-11-14 14:53:42,006 Epoch: [270][300/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0175 (0.0327) Prec@1 98.000 (94.516) Prec@5 100.000 (99.839) +2022-11-14 14:53:42,415 Epoch: [270][310/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0137 (0.0321) Prec@1 98.000 (94.625) Prec@5 100.000 (99.844) +2022-11-14 14:53:42,825 Epoch: [270][320/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0457 (0.0325) Prec@1 91.000 (94.515) Prec@5 100.000 (99.848) +2022-11-14 14:53:43,249 Epoch: [270][330/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0240 (0.0322) Prec@1 95.000 (94.529) Prec@5 100.000 (99.853) +2022-11-14 14:53:43,704 Epoch: [270][340/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0195 (0.0319) Prec@1 97.000 (94.600) Prec@5 99.000 (99.829) +2022-11-14 14:53:44,106 Epoch: [270][350/500] Time 0.034 (0.035) Data 0.002 (0.003) Loss 0.0420 (0.0322) Prec@1 93.000 (94.556) Prec@5 100.000 (99.833) +2022-11-14 14:53:44,532 Epoch: [270][360/500] Time 0.038 (0.035) Data 0.002 (0.003) Loss 0.0196 (0.0318) Prec@1 98.000 (94.649) Prec@5 100.000 (99.838) +2022-11-14 14:53:44,985 Epoch: [270][370/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0408 (0.0321) Prec@1 92.000 (94.579) Prec@5 100.000 (99.842) +2022-11-14 14:53:45,448 Epoch: [270][380/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0316 (0.0320) Prec@1 96.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 14:53:45,908 Epoch: [270][390/500] Time 0.062 (0.036) Data 0.002 (0.003) Loss 0.0546 (0.0326) Prec@1 91.000 (94.525) Prec@5 100.000 (99.850) +2022-11-14 14:53:46,429 Epoch: [270][400/500] Time 0.049 (0.036) Data 0.002 (0.003) Loss 0.0306 (0.0326) Prec@1 96.000 (94.561) Prec@5 100.000 (99.854) +2022-11-14 14:53:46,834 Epoch: [270][410/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0332 (0.0326) Prec@1 95.000 (94.571) Prec@5 99.000 (99.833) +2022-11-14 14:53:47,292 Epoch: [270][420/500] Time 0.056 (0.036) Data 0.002 (0.002) Loss 0.0299 (0.0325) Prec@1 96.000 (94.605) Prec@5 100.000 (99.837) +2022-11-14 14:53:47,692 Epoch: [270][430/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0290 (0.0324) Prec@1 95.000 (94.614) Prec@5 100.000 (99.841) +2022-11-14 14:53:48,100 Epoch: [270][440/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0287 (0.0323) Prec@1 96.000 (94.644) Prec@5 100.000 (99.844) +2022-11-14 14:53:48,511 Epoch: [270][450/500] Time 0.045 (0.036) Data 0.002 (0.002) Loss 0.0465 (0.0327) Prec@1 91.000 (94.565) Prec@5 99.000 (99.826) +2022-11-14 14:53:48,910 Epoch: [270][460/500] Time 0.041 (0.036) Data 0.002 (0.002) Loss 0.0426 (0.0329) Prec@1 94.000 (94.553) Prec@5 100.000 (99.830) +2022-11-14 14:53:49,321 Epoch: [270][470/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0477 (0.0332) Prec@1 90.000 (94.458) Prec@5 100.000 (99.833) +2022-11-14 14:53:49,740 Epoch: [270][480/500] Time 0.033 (0.036) Data 0.002 (0.002) Loss 0.0280 (0.0331) Prec@1 97.000 (94.510) Prec@5 99.000 (99.816) +2022-11-14 14:53:50,160 Epoch: [270][490/500] Time 0.037 (0.036) Data 0.002 (0.002) Loss 0.0422 (0.0333) Prec@1 93.000 (94.480) Prec@5 100.000 (99.820) +2022-11-14 14:53:50,566 Epoch: [270][499/500] Time 0.038 (0.036) Data 0.002 (0.002) Loss 0.0491 (0.0336) Prec@1 93.000 (94.451) Prec@5 100.000 (99.824) +2022-11-14 14:53:50,865 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0588 (0.0588) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:53:50,872 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0662) Prec@1 90.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 14:53:50,882 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0693) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:53:50,892 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0728) Prec@1 89.000 (89.000) Prec@5 98.000 (99.250) +2022-11-14 14:53:50,903 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0714) Prec@1 90.000 (89.200) Prec@5 100.000 (99.400) +2022-11-14 14:53:50,912 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0412 (0.0663) Prec@1 93.000 (89.833) Prec@5 100.000 (99.500) +2022-11-14 14:53:50,923 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0649) Prec@1 90.000 (89.857) Prec@5 100.000 (99.571) +2022-11-14 14:53:50,932 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0662) Prec@1 87.000 (89.500) Prec@5 100.000 (99.625) +2022-11-14 14:53:50,943 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0674) Prec@1 86.000 (89.111) Prec@5 98.000 (99.444) +2022-11-14 14:53:50,953 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0675) Prec@1 89.000 (89.100) Prec@5 99.000 (99.400) +2022-11-14 14:53:50,964 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0666) Prec@1 91.000 (89.273) Prec@5 100.000 (99.455) +2022-11-14 14:53:50,973 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0669) Prec@1 91.000 (89.417) Prec@5 99.000 (99.417) +2022-11-14 14:53:50,983 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0661) Prec@1 91.000 (89.538) Prec@5 100.000 (99.462) +2022-11-14 14:53:50,993 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0670) Prec@1 89.000 (89.500) Prec@5 98.000 (99.357) +2022-11-14 14:53:51,003 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0668) Prec@1 88.000 (89.400) Prec@5 100.000 (99.400) +2022-11-14 14:53:51,011 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0669) Prec@1 88.000 (89.312) Prec@5 100.000 (99.438) +2022-11-14 14:53:51,020 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0672) Prec@1 89.000 (89.294) Prec@5 98.000 (99.353) +2022-11-14 14:53:51,028 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.0704) Prec@1 80.000 (88.778) Prec@5 99.000 (99.333) +2022-11-14 14:53:51,038 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0717) Prec@1 83.000 (88.474) Prec@5 100.000 (99.368) +2022-11-14 14:53:51,048 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0723) Prec@1 84.000 (88.250) Prec@5 98.000 (99.300) +2022-11-14 14:53:51,058 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0726) Prec@1 86.000 (88.143) Prec@5 100.000 (99.333) +2022-11-14 14:53:51,069 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0728) Prec@1 87.000 (88.091) Prec@5 100.000 (99.364) +2022-11-14 14:53:51,080 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0731) Prec@1 86.000 (88.000) Prec@5 98.000 (99.304) +2022-11-14 14:53:51,090 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0730) Prec@1 89.000 (88.042) Prec@5 99.000 (99.292) +2022-11-14 14:53:51,100 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0739) Prec@1 88.000 (88.040) Prec@5 98.000 (99.240) +2022-11-14 14:53:51,111 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0747) Prec@1 88.000 (88.038) Prec@5 98.000 (99.192) +2022-11-14 14:53:51,121 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0738) Prec@1 92.000 (88.185) Prec@5 100.000 (99.222) +2022-11-14 14:53:51,130 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0733) Prec@1 91.000 (88.286) Prec@5 99.000 (99.214) +2022-11-14 14:53:51,140 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0732) Prec@1 91.000 (88.379) Prec@5 98.000 (99.172) +2022-11-14 14:53:51,150 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0728) Prec@1 89.000 (88.400) Prec@5 100.000 (99.200) +2022-11-14 14:53:51,161 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0724) Prec@1 90.000 (88.452) Prec@5 100.000 (99.226) +2022-11-14 14:53:51,172 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0724) Prec@1 89.000 (88.469) Prec@5 99.000 (99.219) +2022-11-14 14:53:51,183 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0724) Prec@1 87.000 (88.424) Prec@5 100.000 (99.242) +2022-11-14 14:53:51,194 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0726) Prec@1 88.000 (88.412) Prec@5 100.000 (99.265) +2022-11-14 14:53:51,205 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0729) Prec@1 84.000 (88.286) Prec@5 99.000 (99.257) +2022-11-14 14:53:51,217 Test: [35/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0729) Prec@1 90.000 (88.333) Prec@5 99.000 (99.250) +2022-11-14 14:53:51,229 Test: [36/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0734) Prec@1 85.000 (88.243) Prec@5 99.000 (99.243) +2022-11-14 14:53:51,238 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.0744) Prec@1 83.000 (88.105) Prec@5 97.000 (99.184) +2022-11-14 14:53:51,250 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0748) Prec@1 86.000 (88.051) Prec@5 100.000 (99.205) +2022-11-14 14:53:51,262 Test: [39/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0746) Prec@1 90.000 (88.100) Prec@5 98.000 (99.175) +2022-11-14 14:53:51,274 Test: [40/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0753) Prec@1 83.000 (87.976) Prec@5 99.000 (99.171) +2022-11-14 14:53:51,285 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0748) Prec@1 91.000 (88.048) Prec@5 99.000 (99.167) +2022-11-14 14:53:51,294 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0743) Prec@1 90.000 (88.093) Prec@5 99.000 (99.163) +2022-11-14 14:53:51,307 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0741) Prec@1 91.000 (88.159) Prec@5 99.000 (99.159) +2022-11-14 14:53:51,318 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0740) Prec@1 88.000 (88.156) Prec@5 99.000 (99.156) +2022-11-14 14:53:51,329 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.0748) Prec@1 81.000 (88.000) Prec@5 97.000 (99.109) +2022-11-14 14:53:51,340 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0746) Prec@1 90.000 (88.043) Prec@5 100.000 (99.128) +2022-11-14 14:53:51,349 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0751) Prec@1 83.000 (87.938) Prec@5 98.000 (99.104) +2022-11-14 14:53:51,359 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0747) Prec@1 91.000 (88.000) Prec@5 98.000 (99.082) +2022-11-14 14:53:51,370 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0754) Prec@1 82.000 (87.880) Prec@5 100.000 (99.100) +2022-11-14 14:53:51,380 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0751) Prec@1 89.000 (87.902) Prec@5 100.000 (99.118) +2022-11-14 14:53:51,391 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0751) Prec@1 86.000 (87.865) Prec@5 100.000 (99.135) +2022-11-14 14:53:51,402 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0751) Prec@1 88.000 (87.868) Prec@5 99.000 (99.132) +2022-11-14 14:53:51,412 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0752) Prec@1 87.000 (87.852) Prec@5 98.000 (99.111) +2022-11-14 14:53:51,422 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0755) Prec@1 86.000 (87.818) Prec@5 100.000 (99.127) +2022-11-14 14:53:51,434 Test: [55/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0756) Prec@1 85.000 (87.768) Prec@5 99.000 (99.125) +2022-11-14 14:53:51,446 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0757) Prec@1 86.000 (87.737) Prec@5 100.000 (99.140) +2022-11-14 14:53:51,456 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0754) Prec@1 91.000 (87.793) Prec@5 99.000 (99.138) +2022-11-14 14:53:51,466 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1109 (0.0760) Prec@1 82.000 (87.695) Prec@5 99.000 (99.136) +2022-11-14 14:53:51,477 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0758) Prec@1 89.000 (87.717) Prec@5 100.000 (99.150) +2022-11-14 14:53:51,488 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0756) Prec@1 92.000 (87.787) Prec@5 98.000 (99.131) +2022-11-14 14:53:51,498 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0753) Prec@1 91.000 (87.839) Prec@5 99.000 (99.129) +2022-11-14 14:53:51,509 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0753) Prec@1 89.000 (87.857) Prec@5 100.000 (99.143) +2022-11-14 14:53:51,520 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0748) Prec@1 91.000 (87.906) Prec@5 100.000 (99.156) +2022-11-14 14:53:51,530 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0751) Prec@1 84.000 (87.846) Prec@5 99.000 (99.154) +2022-11-14 14:53:51,543 Test: [65/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0749) Prec@1 90.000 (87.879) Prec@5 100.000 (99.167) +2022-11-14 14:53:51,557 Test: [66/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0405 (0.0743) Prec@1 92.000 (87.940) Prec@5 100.000 (99.179) +2022-11-14 14:53:51,571 Test: [67/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0744) Prec@1 89.000 (87.956) Prec@5 98.000 (99.162) +2022-11-14 14:53:51,583 Test: [68/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0743) Prec@1 87.000 (87.942) Prec@5 100.000 (99.174) +2022-11-14 14:53:51,593 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0744) Prec@1 87.000 (87.929) Prec@5 99.000 (99.171) +2022-11-14 14:53:51,605 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0748) Prec@1 84.000 (87.873) Prec@5 99.000 (99.169) +2022-11-14 14:53:51,616 Test: [71/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0746) Prec@1 87.000 (87.861) Prec@5 100.000 (99.181) +2022-11-14 14:53:51,628 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0745) Prec@1 93.000 (87.932) Prec@5 98.000 (99.164) +2022-11-14 14:53:51,638 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0742) Prec@1 91.000 (87.973) Prec@5 100.000 (99.176) +2022-11-14 14:53:51,649 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0746) Prec@1 82.000 (87.893) Prec@5 99.000 (99.173) +2022-11-14 14:53:51,659 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0745) Prec@1 91.000 (87.934) Prec@5 99.000 (99.171) +2022-11-14 14:53:51,669 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0744) Prec@1 88.000 (87.935) Prec@5 99.000 (99.169) +2022-11-14 14:53:51,680 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0746) Prec@1 85.000 (87.897) Prec@5 97.000 (99.141) +2022-11-14 14:53:51,691 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0747) Prec@1 87.000 (87.886) Prec@5 100.000 (99.152) +2022-11-14 14:53:51,702 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0749) Prec@1 81.000 (87.800) Prec@5 100.000 (99.162) +2022-11-14 14:53:51,711 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0750) Prec@1 86.000 (87.778) Prec@5 99.000 (99.160) +2022-11-14 14:53:51,720 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0753) Prec@1 85.000 (87.744) Prec@5 100.000 (99.171) +2022-11-14 14:53:51,729 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0754) Prec@1 85.000 (87.711) Prec@5 100.000 (99.181) +2022-11-14 14:53:51,739 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0755) Prec@1 83.000 (87.655) Prec@5 97.000 (99.155) +2022-11-14 14:53:51,750 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0757) Prec@1 85.000 (87.624) Prec@5 100.000 (99.165) +2022-11-14 14:53:51,760 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0761) Prec@1 81.000 (87.547) Prec@5 99.000 (99.163) +2022-11-14 14:53:51,770 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0763) Prec@1 84.000 (87.506) Prec@5 100.000 (99.172) +2022-11-14 14:53:51,780 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0764) Prec@1 87.000 (87.500) Prec@5 99.000 (99.170) +2022-11-14 14:53:51,790 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0762) Prec@1 91.000 (87.539) Prec@5 100.000 (99.180) +2022-11-14 14:53:51,801 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0762) Prec@1 89.000 (87.556) Prec@5 100.000 (99.189) +2022-11-14 14:53:51,811 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0759) Prec@1 92.000 (87.604) Prec@5 100.000 (99.198) +2022-11-14 14:53:51,822 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0757) Prec@1 91.000 (87.641) Prec@5 99.000 (99.196) +2022-11-14 14:53:51,833 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0759) Prec@1 83.000 (87.591) Prec@5 100.000 (99.204) +2022-11-14 14:53:51,843 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0760) Prec@1 87.000 (87.585) Prec@5 99.000 (99.202) +2022-11-14 14:53:51,855 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0763) Prec@1 83.000 (87.537) Prec@5 100.000 (99.211) +2022-11-14 14:53:51,866 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0763) Prec@1 86.000 (87.521) Prec@5 100.000 (99.219) +2022-11-14 14:53:51,877 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0352 (0.0759) Prec@1 95.000 (87.598) Prec@5 99.000 (99.216) +2022-11-14 14:53:51,888 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0759) Prec@1 90.000 (87.622) Prec@5 99.000 (99.214) +2022-11-14 14:53:51,899 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0759) Prec@1 87.000 (87.616) Prec@5 97.000 (99.192) +2022-11-14 14:53:51,909 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1083 (0.0763) Prec@1 82.000 (87.560) Prec@5 99.000 (99.190) +2022-11-14 14:53:51,984 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:53:52,310 Epoch: [271][0/500] Time 0.027 (0.027) Data 0.235 (0.235) Loss 0.0343 (0.0343) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:52,538 Epoch: [271][10/500] Time 0.018 (0.021) Data 0.001 (0.023) Loss 0.0322 (0.0332) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:52,861 Epoch: [271][20/500] Time 0.043 (0.024) Data 0.002 (0.013) Loss 0.0330 (0.0331) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:53,300 Epoch: [271][30/500] Time 0.045 (0.029) Data 0.002 (0.009) Loss 0.0461 (0.0364) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 14:53:53,638 Epoch: [271][40/500] Time 0.039 (0.029) Data 0.002 (0.008) Loss 0.0309 (0.0353) Prec@1 94.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 14:53:54,007 Epoch: [271][50/500] Time 0.050 (0.030) Data 0.002 (0.006) Loss 0.0149 (0.0319) Prec@1 98.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:53:54,349 Epoch: [271][60/500] Time 0.031 (0.030) Data 0.002 (0.006) Loss 0.0183 (0.0300) Prec@1 98.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 14:53:54,695 Epoch: [271][70/500] Time 0.033 (0.030) Data 0.002 (0.005) Loss 0.0473 (0.0321) Prec@1 91.000 (94.875) Prec@5 99.000 (99.875) +2022-11-14 14:53:55,044 Epoch: [271][80/500] Time 0.031 (0.030) Data 0.002 (0.005) Loss 0.0454 (0.0336) Prec@1 94.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 14:53:55,388 Epoch: [271][90/500] Time 0.039 (0.030) Data 0.002 (0.004) Loss 0.0574 (0.0360) Prec@1 88.000 (94.100) Prec@5 100.000 (99.900) +2022-11-14 14:53:55,731 Epoch: [271][100/500] Time 0.029 (0.030) Data 0.002 (0.004) Loss 0.0307 (0.0355) Prec@1 94.000 (94.091) Prec@5 100.000 (99.909) +2022-11-14 14:53:56,070 Epoch: [271][110/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0448 (0.0363) Prec@1 93.000 (94.000) Prec@5 100.000 (99.917) +2022-11-14 14:53:56,416 Epoch: [271][120/500] Time 0.030 (0.030) Data 0.002 (0.004) Loss 0.0334 (0.0361) Prec@1 94.000 (94.000) Prec@5 99.000 (99.846) +2022-11-14 14:53:56,770 Epoch: [271][130/500] Time 0.027 (0.030) Data 0.002 (0.004) Loss 0.0351 (0.0360) Prec@1 95.000 (94.071) Prec@5 99.000 (99.786) +2022-11-14 14:53:57,110 Epoch: [271][140/500] Time 0.035 (0.030) Data 0.002 (0.003) Loss 0.0444 (0.0366) Prec@1 92.000 (93.933) Prec@5 100.000 (99.800) +2022-11-14 14:53:57,461 Epoch: [271][150/500] Time 0.034 (0.030) Data 0.001 (0.003) Loss 0.0376 (0.0366) Prec@1 93.000 (93.875) Prec@5 100.000 (99.812) +2022-11-14 14:53:57,836 Epoch: [271][160/500] Time 0.027 (0.031) Data 0.002 (0.003) Loss 0.0179 (0.0355) Prec@1 99.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 14:53:58,185 Epoch: [271][170/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0239 (0.0349) Prec@1 97.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 14:53:58,524 Epoch: [271][180/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0568 (0.0360) Prec@1 89.000 (94.053) Prec@5 98.000 (99.737) +2022-11-14 14:53:58,863 Epoch: [271][190/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0437 (0.0364) Prec@1 93.000 (94.000) Prec@5 98.000 (99.650) +2022-11-14 14:53:59,242 Epoch: [271][200/500] Time 0.025 (0.031) Data 0.002 (0.003) Loss 0.0469 (0.0369) Prec@1 92.000 (93.905) Prec@5 100.000 (99.667) +2022-11-14 14:53:59,581 Epoch: [271][210/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0550 (0.0377) Prec@1 90.000 (93.727) Prec@5 100.000 (99.682) +2022-11-14 14:53:59,944 Epoch: [271][220/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0248 (0.0372) Prec@1 97.000 (93.870) Prec@5 100.000 (99.696) +2022-11-14 14:54:00,367 Epoch: [271][230/500] Time 0.041 (0.031) Data 0.002 (0.003) Loss 0.0529 (0.0378) Prec@1 92.000 (93.792) Prec@5 99.000 (99.667) +2022-11-14 14:54:00,799 Epoch: [271][240/500] Time 0.043 (0.031) Data 0.002 (0.003) Loss 0.0651 (0.0389) Prec@1 90.000 (93.640) Prec@5 100.000 (99.680) +2022-11-14 14:54:01,516 Epoch: [271][250/500] Time 0.094 (0.033) Data 0.002 (0.003) Loss 0.0430 (0.0391) Prec@1 92.000 (93.577) Prec@5 99.000 (99.654) +2022-11-14 14:54:02,033 Epoch: [271][260/500] Time 0.045 (0.033) Data 0.002 (0.003) Loss 0.0453 (0.0393) Prec@1 94.000 (93.593) Prec@5 100.000 (99.667) +2022-11-14 14:54:02,523 Epoch: [271][270/500] Time 0.051 (0.034) Data 0.002 (0.003) Loss 0.0149 (0.0384) Prec@1 98.000 (93.750) Prec@5 100.000 (99.679) +2022-11-14 14:54:03,072 Epoch: [271][280/500] Time 0.051 (0.034) Data 0.002 (0.003) Loss 0.0377 (0.0384) Prec@1 93.000 (93.724) Prec@5 100.000 (99.690) +2022-11-14 14:54:03,562 Epoch: [271][290/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0164 (0.0377) Prec@1 97.000 (93.833) Prec@5 100.000 (99.700) +2022-11-14 14:54:04,038 Epoch: [271][300/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0210 (0.0371) Prec@1 97.000 (93.935) Prec@5 100.000 (99.710) +2022-11-14 14:54:04,606 Epoch: [271][310/500] Time 0.044 (0.035) Data 0.002 (0.003) Loss 0.0528 (0.0376) Prec@1 93.000 (93.906) Prec@5 99.000 (99.688) +2022-11-14 14:54:05,132 Epoch: [271][320/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0386 (0.0377) Prec@1 93.000 (93.879) Prec@5 100.000 (99.697) +2022-11-14 14:54:05,648 Epoch: [271][330/500] Time 0.053 (0.036) Data 0.002 (0.003) Loss 0.0488 (0.0380) Prec@1 94.000 (93.882) Prec@5 99.000 (99.676) +2022-11-14 14:54:06,187 Epoch: [271][340/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0485 (0.0383) Prec@1 92.000 (93.829) Prec@5 98.000 (99.629) +2022-11-14 14:54:06,688 Epoch: [271][350/500] Time 0.045 (0.036) Data 0.002 (0.003) Loss 0.0554 (0.0388) Prec@1 91.000 (93.750) Prec@5 100.000 (99.639) +2022-11-14 14:54:07,190 Epoch: [271][360/500] Time 0.060 (0.037) Data 0.002 (0.003) Loss 0.0465 (0.0390) Prec@1 92.000 (93.703) Prec@5 100.000 (99.649) +2022-11-14 14:54:07,669 Epoch: [271][370/500] Time 0.043 (0.037) Data 0.002 (0.003) Loss 0.0347 (0.0389) Prec@1 93.000 (93.684) Prec@5 100.000 (99.658) +2022-11-14 14:54:08,142 Epoch: [271][380/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0483 (0.0391) Prec@1 93.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:54:08,621 Epoch: [271][390/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0358 (0.0390) Prec@1 93.000 (93.650) Prec@5 100.000 (99.675) +2022-11-14 14:54:09,095 Epoch: [271][400/500] Time 0.044 (0.037) Data 0.002 (0.003) Loss 0.0283 (0.0388) Prec@1 95.000 (93.683) Prec@5 100.000 (99.683) +2022-11-14 14:54:09,586 Epoch: [271][410/500] Time 0.043 (0.037) Data 0.002 (0.002) Loss 0.0247 (0.0384) Prec@1 96.000 (93.738) Prec@5 100.000 (99.690) +2022-11-14 14:54:10,142 Epoch: [271][420/500] Time 0.078 (0.038) Data 0.002 (0.002) Loss 0.0306 (0.0382) Prec@1 96.000 (93.791) Prec@5 100.000 (99.698) +2022-11-14 14:54:10,626 Epoch: [271][430/500] Time 0.044 (0.038) Data 0.002 (0.002) Loss 0.0355 (0.0382) Prec@1 93.000 (93.773) Prec@5 100.000 (99.705) +2022-11-14 14:54:11,102 Epoch: [271][440/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0383 (0.0382) Prec@1 93.000 (93.756) Prec@5 100.000 (99.711) +2022-11-14 14:54:11,582 Epoch: [271][450/500] Time 0.043 (0.038) Data 0.002 (0.002) Loss 0.0636 (0.0387) Prec@1 86.000 (93.587) Prec@5 99.000 (99.696) +2022-11-14 14:54:12,105 Epoch: [271][460/500] Time 0.059 (0.038) Data 0.002 (0.002) Loss 0.0448 (0.0389) Prec@1 93.000 (93.574) Prec@5 100.000 (99.702) +2022-11-14 14:54:12,604 Epoch: [271][470/500] Time 0.048 (0.038) Data 0.002 (0.002) Loss 0.0506 (0.0391) Prec@1 92.000 (93.542) Prec@5 100.000 (99.708) +2022-11-14 14:54:13,085 Epoch: [271][480/500] Time 0.054 (0.038) Data 0.002 (0.002) Loss 0.0323 (0.0390) Prec@1 95.000 (93.571) Prec@5 100.000 (99.714) +2022-11-14 14:54:13,578 Epoch: [271][490/500] Time 0.052 (0.039) Data 0.002 (0.002) Loss 0.0458 (0.0391) Prec@1 94.000 (93.580) Prec@5 100.000 (99.720) +2022-11-14 14:54:14,063 Epoch: [271][499/500] Time 0.046 (0.039) Data 0.002 (0.002) Loss 0.0451 (0.0392) Prec@1 91.000 (93.529) Prec@5 99.000 (99.706) +2022-11-14 14:54:14,347 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0705 (0.0705) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 14:54:14,366 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0701) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:54:14,374 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0724) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:54:14,387 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0762) Prec@1 87.000 (87.000) Prec@5 98.000 (99.500) +2022-11-14 14:54:14,397 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0769) Prec@1 88.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 14:54:14,408 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0412 (0.0710) Prec@1 95.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 14:54:14,420 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0698) Prec@1 90.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 14:54:14,434 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0718) Prec@1 86.000 (88.375) Prec@5 100.000 (99.750) +2022-11-14 14:54:14,448 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0721) Prec@1 88.000 (88.333) Prec@5 99.000 (99.667) +2022-11-14 14:54:14,461 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0717) Prec@1 89.000 (88.400) Prec@5 98.000 (99.500) +2022-11-14 14:54:14,473 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0697) Prec@1 92.000 (88.727) Prec@5 100.000 (99.545) +2022-11-14 14:54:14,487 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0681) Prec@1 91.000 (88.917) Prec@5 99.000 (99.500) +2022-11-14 14:54:14,499 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0678) Prec@1 86.000 (88.692) Prec@5 100.000 (99.538) +2022-11-14 14:54:14,512 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0687) Prec@1 87.000 (88.571) Prec@5 100.000 (99.571) +2022-11-14 14:54:14,526 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0678) Prec@1 90.000 (88.667) Prec@5 99.000 (99.533) +2022-11-14 14:54:14,541 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0683) Prec@1 88.000 (88.625) Prec@5 100.000 (99.562) +2022-11-14 14:54:14,554 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0674) Prec@1 92.000 (88.824) Prec@5 99.000 (99.529) +2022-11-14 14:54:14,565 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0699) Prec@1 83.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:54:14,580 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0715) Prec@1 82.000 (88.158) Prec@5 99.000 (99.474) +2022-11-14 14:54:14,595 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0719) Prec@1 87.000 (88.100) Prec@5 98.000 (99.400) +2022-11-14 14:54:14,607 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0714) Prec@1 90.000 (88.190) Prec@5 100.000 (99.429) +2022-11-14 14:54:14,624 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0716) Prec@1 89.000 (88.227) Prec@5 98.000 (99.364) +2022-11-14 14:54:14,640 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0730) Prec@1 84.000 (88.043) Prec@5 99.000 (99.348) +2022-11-14 14:54:14,654 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0732) Prec@1 87.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 14:54:14,670 Test: [24/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0740) Prec@1 85.000 (87.880) Prec@5 99.000 (99.360) +2022-11-14 14:54:14,684 Test: [25/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0746) Prec@1 86.000 (87.808) Prec@5 99.000 (99.346) +2022-11-14 14:54:14,699 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0737) Prec@1 93.000 (88.000) Prec@5 100.000 (99.370) +2022-11-14 14:54:14,715 Test: [27/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0737) Prec@1 88.000 (88.000) Prec@5 100.000 (99.393) +2022-11-14 14:54:14,728 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0731) Prec@1 91.000 (88.103) Prec@5 99.000 (99.379) +2022-11-14 14:54:14,741 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0730) Prec@1 89.000 (88.133) Prec@5 100.000 (99.400) +2022-11-14 14:54:14,756 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0728) Prec@1 90.000 (88.194) Prec@5 99.000 (99.387) +2022-11-14 14:54:14,769 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0731) Prec@1 89.000 (88.219) Prec@5 98.000 (99.344) +2022-11-14 14:54:14,783 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0728) Prec@1 88.000 (88.212) Prec@5 99.000 (99.333) +2022-11-14 14:54:14,799 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0732) Prec@1 89.000 (88.235) Prec@5 99.000 (99.324) +2022-11-14 14:54:14,812 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0733) Prec@1 88.000 (88.229) Prec@5 98.000 (99.286) +2022-11-14 14:54:14,825 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0733) Prec@1 88.000 (88.222) Prec@5 97.000 (99.222) +2022-11-14 14:54:14,836 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0732) Prec@1 88.000 (88.216) Prec@5 99.000 (99.216) +2022-11-14 14:54:14,852 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0736) Prec@1 86.000 (88.158) Prec@5 98.000 (99.184) +2022-11-14 14:54:14,868 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0551 (0.0732) Prec@1 92.000 (88.256) Prec@5 99.000 (99.179) +2022-11-14 14:54:14,881 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0729) Prec@1 88.000 (88.250) Prec@5 99.000 (99.175) +2022-11-14 14:54:14,895 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0732) Prec@1 85.000 (88.171) Prec@5 98.000 (99.146) +2022-11-14 14:54:14,908 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0730) Prec@1 89.000 (88.190) Prec@5 99.000 (99.143) +2022-11-14 14:54:14,922 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0723) Prec@1 92.000 (88.279) Prec@5 100.000 (99.163) +2022-11-14 14:54:14,936 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0725) Prec@1 89.000 (88.295) Prec@5 99.000 (99.159) +2022-11-14 14:54:14,950 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0724) Prec@1 88.000 (88.289) Prec@5 99.000 (99.156) +2022-11-14 14:54:14,964 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0728) Prec@1 83.000 (88.174) Prec@5 100.000 (99.174) +2022-11-14 14:54:14,978 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0731) Prec@1 86.000 (88.128) Prec@5 99.000 (99.170) +2022-11-14 14:54:14,991 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0736) Prec@1 87.000 (88.104) Prec@5 98.000 (99.146) +2022-11-14 14:54:15,005 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0732) Prec@1 92.000 (88.184) Prec@5 100.000 (99.163) +2022-11-14 14:54:15,019 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.0740) Prec@1 83.000 (88.080) Prec@5 100.000 (99.180) +2022-11-14 14:54:15,033 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0738) Prec@1 89.000 (88.098) Prec@5 100.000 (99.196) +2022-11-14 14:54:15,047 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0741) Prec@1 87.000 (88.077) Prec@5 99.000 (99.192) +2022-11-14 14:54:15,061 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0737) Prec@1 92.000 (88.151) Prec@5 99.000 (99.189) +2022-11-14 14:54:15,075 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0741) Prec@1 85.000 (88.093) Prec@5 98.000 (99.167) +2022-11-14 14:54:15,089 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0746) Prec@1 84.000 (88.018) Prec@5 100.000 (99.182) +2022-11-14 14:54:15,102 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0750) Prec@1 84.000 (87.946) Prec@5 99.000 (99.179) +2022-11-14 14:54:15,117 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0745) Prec@1 91.000 (88.000) Prec@5 100.000 (99.193) +2022-11-14 14:54:15,130 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0744) Prec@1 88.000 (88.000) Prec@5 100.000 (99.207) +2022-11-14 14:54:15,145 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0749) Prec@1 84.000 (87.932) Prec@5 100.000 (99.220) +2022-11-14 14:54:15,160 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0748) Prec@1 87.000 (87.917) Prec@5 100.000 (99.233) +2022-11-14 14:54:15,174 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0750) Prec@1 89.000 (87.934) Prec@5 97.000 (99.197) +2022-11-14 14:54:15,187 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0751) Prec@1 85.000 (87.887) Prec@5 100.000 (99.210) +2022-11-14 14:54:15,200 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0750) Prec@1 89.000 (87.905) Prec@5 100.000 (99.222) +2022-11-14 14:54:15,214 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0365 (0.0744) Prec@1 95.000 (88.016) Prec@5 100.000 (99.234) +2022-11-14 14:54:15,226 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0746) Prec@1 88.000 (88.015) Prec@5 100.000 (99.246) +2022-11-14 14:54:15,241 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0746) Prec@1 88.000 (88.015) Prec@5 99.000 (99.242) +2022-11-14 14:54:15,255 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0368 (0.0740) Prec@1 94.000 (88.104) Prec@5 100.000 (99.254) +2022-11-14 14:54:15,267 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0740) Prec@1 90.000 (88.132) Prec@5 98.000 (99.235) +2022-11-14 14:54:15,283 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0741) Prec@1 85.000 (88.087) Prec@5 99.000 (99.232) +2022-11-14 14:54:15,299 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0744) Prec@1 86.000 (88.057) Prec@5 98.000 (99.214) +2022-11-14 14:54:15,313 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0748) Prec@1 83.000 (87.986) Prec@5 99.000 (99.211) +2022-11-14 14:54:15,326 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0748) Prec@1 84.000 (87.931) Prec@5 100.000 (99.222) +2022-11-14 14:54:15,340 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0747) Prec@1 91.000 (87.973) Prec@5 100.000 (99.233) +2022-11-14 14:54:15,353 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0431 (0.0742) Prec@1 93.000 (88.041) Prec@5 100.000 (99.243) +2022-11-14 14:54:15,367 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1248 (0.0749) Prec@1 80.000 (87.933) Prec@5 99.000 (99.240) +2022-11-14 14:54:15,380 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0749) Prec@1 88.000 (87.934) Prec@5 98.000 (99.224) +2022-11-14 14:54:15,393 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0749) Prec@1 87.000 (87.922) Prec@5 99.000 (99.221) +2022-11-14 14:54:15,409 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0751) Prec@1 87.000 (87.910) Prec@5 99.000 (99.218) +2022-11-14 14:54:15,422 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0750) Prec@1 87.000 (87.899) Prec@5 100.000 (99.228) +2022-11-14 14:54:15,435 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0751) Prec@1 88.000 (87.900) Prec@5 100.000 (99.237) +2022-11-14 14:54:15,450 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0752) Prec@1 87.000 (87.889) Prec@5 97.000 (99.210) +2022-11-14 14:54:15,465 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0751) Prec@1 87.000 (87.878) Prec@5 99.000 (99.207) +2022-11-14 14:54:15,479 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0752) Prec@1 88.000 (87.880) Prec@5 100.000 (99.217) +2022-11-14 14:54:15,493 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0752) Prec@1 88.000 (87.881) Prec@5 98.000 (99.202) +2022-11-14 14:54:15,507 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.0755) Prec@1 83.000 (87.824) Prec@5 100.000 (99.212) +2022-11-14 14:54:15,520 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0758) Prec@1 86.000 (87.802) Prec@5 98.000 (99.198) +2022-11-14 14:54:15,534 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0757) Prec@1 90.000 (87.828) Prec@5 100.000 (99.207) +2022-11-14 14:54:15,548 Test: [87/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0759) Prec@1 84.000 (87.784) Prec@5 98.000 (99.193) +2022-11-14 14:54:15,560 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0756) Prec@1 91.000 (87.820) Prec@5 100.000 (99.202) +2022-11-14 14:54:15,576 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0757) Prec@1 90.000 (87.844) Prec@5 99.000 (99.200) +2022-11-14 14:54:15,590 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0450 (0.0753) Prec@1 94.000 (87.912) Prec@5 99.000 (99.198) +2022-11-14 14:54:15,603 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0753) Prec@1 89.000 (87.924) Prec@5 98.000 (99.185) +2022-11-14 14:54:15,616 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0753) Prec@1 84.000 (87.882) Prec@5 100.000 (99.194) +2022-11-14 14:54:15,628 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0754) Prec@1 87.000 (87.872) Prec@5 100.000 (99.202) +2022-11-14 14:54:15,644 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0754) Prec@1 84.000 (87.832) Prec@5 100.000 (99.211) +2022-11-14 14:54:15,658 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0753) Prec@1 89.000 (87.844) Prec@5 100.000 (99.219) +2022-11-14 14:54:15,671 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0750) Prec@1 92.000 (87.887) Prec@5 98.000 (99.206) +2022-11-14 14:54:15,685 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0751) Prec@1 89.000 (87.898) Prec@5 99.000 (99.204) +2022-11-14 14:54:15,699 Test: [98/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0754) Prec@1 83.000 (87.848) Prec@5 98.000 (99.192) +2022-11-14 14:54:15,715 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0752) Prec@1 90.000 (87.870) Prec@5 100.000 (99.200) +2022-11-14 14:54:15,770 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:54:16,116 Epoch: [272][0/500] Time 0.025 (0.025) Data 0.264 (0.264) Loss 0.0201 (0.0201) Prec@1 99.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 14:54:16,337 Epoch: [272][10/500] Time 0.021 (0.020) Data 0.002 (0.026) Loss 0.0328 (0.0265) Prec@1 93.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 14:54:16,586 Epoch: [272][20/500] Time 0.023 (0.021) Data 0.002 (0.014) Loss 0.0229 (0.0253) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 14:54:16,829 Epoch: [272][30/500] Time 0.021 (0.021) Data 0.002 (0.010) Loss 0.0300 (0.0264) Prec@1 97.000 (96.500) Prec@5 99.000 (99.750) +2022-11-14 14:54:17,081 Epoch: [272][40/500] Time 0.022 (0.021) Data 0.001 (0.008) Loss 0.0325 (0.0277) Prec@1 95.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 14:54:17,408 Epoch: [272][50/500] Time 0.037 (0.023) Data 0.002 (0.007) Loss 0.0277 (0.0277) Prec@1 96.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 14:54:17,789 Epoch: [272][60/500] Time 0.036 (0.024) Data 0.002 (0.006) Loss 0.0310 (0.0281) Prec@1 95.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 14:54:18,209 Epoch: [272][70/500] Time 0.044 (0.026) Data 0.002 (0.005) Loss 0.0238 (0.0276) Prec@1 96.000 (96.000) Prec@5 100.000 (99.875) +2022-11-14 14:54:18,613 Epoch: [272][80/500] Time 0.045 (0.028) Data 0.002 (0.005) Loss 0.0331 (0.0282) Prec@1 94.000 (95.778) Prec@5 100.000 (99.889) +2022-11-14 14:54:19,000 Epoch: [272][90/500] Time 0.036 (0.028) Data 0.002 (0.005) Loss 0.0372 (0.0291) Prec@1 96.000 (95.800) Prec@5 99.000 (99.800) +2022-11-14 14:54:19,386 Epoch: [272][100/500] Time 0.036 (0.029) Data 0.002 (0.004) Loss 0.0086 (0.0272) Prec@1 99.000 (96.091) Prec@5 100.000 (99.818) +2022-11-14 14:54:19,776 Epoch: [272][110/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0266 (0.0272) Prec@1 97.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 14:54:20,162 Epoch: [272][120/500] Time 0.036 (0.030) Data 0.002 (0.004) Loss 0.0390 (0.0281) Prec@1 95.000 (96.077) Prec@5 100.000 (99.846) +2022-11-14 14:54:20,565 Epoch: [272][130/500] Time 0.034 (0.030) Data 0.002 (0.004) Loss 0.0536 (0.0299) Prec@1 92.000 (95.786) Prec@5 99.000 (99.786) +2022-11-14 14:54:20,946 Epoch: [272][140/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0538 (0.0315) Prec@1 90.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 14:54:21,363 Epoch: [272][150/500] Time 0.033 (0.031) Data 0.002 (0.004) Loss 0.0306 (0.0315) Prec@1 95.000 (95.375) Prec@5 99.000 (99.750) +2022-11-14 14:54:21,766 Epoch: [272][160/500] Time 0.035 (0.031) Data 0.002 (0.003) Loss 0.0365 (0.0318) Prec@1 93.000 (95.235) Prec@5 99.000 (99.706) +2022-11-14 14:54:22,148 Epoch: [272][170/500] Time 0.038 (0.031) Data 0.001 (0.003) Loss 0.0217 (0.0312) Prec@1 97.000 (95.333) Prec@5 100.000 (99.722) +2022-11-14 14:54:22,542 Epoch: [272][180/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0263 (0.0309) Prec@1 95.000 (95.316) Prec@5 100.000 (99.737) +2022-11-14 14:54:22,928 Epoch: [272][190/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0523 (0.0320) Prec@1 91.000 (95.100) Prec@5 100.000 (99.750) +2022-11-14 14:54:23,321 Epoch: [272][200/500] Time 0.034 (0.032) Data 0.002 (0.003) Loss 0.0345 (0.0321) Prec@1 93.000 (95.000) Prec@5 100.000 (99.762) +2022-11-14 14:54:23,706 Epoch: [272][210/500] Time 0.038 (0.032) Data 0.002 (0.003) Loss 0.0435 (0.0326) Prec@1 92.000 (94.864) Prec@5 98.000 (99.682) +2022-11-14 14:54:24,110 Epoch: [272][220/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0422 (0.0331) Prec@1 94.000 (94.826) Prec@5 99.000 (99.652) +2022-11-14 14:54:24,503 Epoch: [272][230/500] Time 0.043 (0.032) Data 0.002 (0.003) Loss 0.0419 (0.0334) Prec@1 93.000 (94.750) Prec@5 100.000 (99.667) +2022-11-14 14:54:24,887 Epoch: [272][240/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0352 (0.0335) Prec@1 94.000 (94.720) Prec@5 100.000 (99.680) +2022-11-14 14:54:25,273 Epoch: [272][250/500] Time 0.037 (0.032) Data 0.002 (0.003) Loss 0.0300 (0.0334) Prec@1 97.000 (94.808) Prec@5 100.000 (99.692) +2022-11-14 14:54:25,661 Epoch: [272][260/500] Time 0.036 (0.033) Data 0.001 (0.003) Loss 0.0363 (0.0335) Prec@1 94.000 (94.778) Prec@5 100.000 (99.704) +2022-11-14 14:54:26,045 Epoch: [272][270/500] Time 0.036 (0.033) Data 0.001 (0.003) Loss 0.0525 (0.0342) Prec@1 93.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 14:54:26,431 Epoch: [272][280/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0147 (0.0335) Prec@1 97.000 (94.793) Prec@5 100.000 (99.724) +2022-11-14 14:54:26,817 Epoch: [272][290/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0475 (0.0340) Prec@1 93.000 (94.733) Prec@5 100.000 (99.733) +2022-11-14 14:54:27,275 Epoch: [272][300/500] Time 0.039 (0.033) Data 0.002 (0.003) Loss 0.0493 (0.0344) Prec@1 91.000 (94.613) Prec@5 98.000 (99.677) +2022-11-14 14:54:27,659 Epoch: [272][310/500] Time 0.046 (0.033) Data 0.002 (0.003) Loss 0.0443 (0.0348) Prec@1 92.000 (94.531) Prec@5 99.000 (99.656) +2022-11-14 14:54:28,045 Epoch: [272][320/500] Time 0.036 (0.033) Data 0.002 (0.003) Loss 0.0584 (0.0355) Prec@1 92.000 (94.455) Prec@5 99.000 (99.636) +2022-11-14 14:54:28,434 Epoch: [272][330/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0393 (0.0356) Prec@1 94.000 (94.441) Prec@5 100.000 (99.647) +2022-11-14 14:54:28,865 Epoch: [272][340/500] Time 0.027 (0.033) Data 0.003 (0.003) Loss 0.0466 (0.0359) Prec@1 93.000 (94.400) Prec@5 100.000 (99.657) +2022-11-14 14:54:29,250 Epoch: [272][350/500] Time 0.033 (0.033) Data 0.003 (0.003) Loss 0.0416 (0.0361) Prec@1 93.000 (94.361) Prec@5 100.000 (99.667) +2022-11-14 14:54:29,641 Epoch: [272][360/500] Time 0.042 (0.033) Data 0.002 (0.003) Loss 0.0458 (0.0363) Prec@1 91.000 (94.270) Prec@5 100.000 (99.676) +2022-11-14 14:54:30,026 Epoch: [272][370/500] Time 0.035 (0.033) Data 0.002 (0.003) Loss 0.0209 (0.0359) Prec@1 97.000 (94.342) Prec@5 100.000 (99.684) +2022-11-14 14:54:30,415 Epoch: [272][380/500] Time 0.034 (0.033) Data 0.002 (0.003) Loss 0.0258 (0.0357) Prec@1 96.000 (94.385) Prec@5 100.000 (99.692) +2022-11-14 14:54:30,814 Epoch: [272][390/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0478 (0.0360) Prec@1 93.000 (94.350) Prec@5 100.000 (99.700) +2022-11-14 14:54:31,205 Epoch: [272][400/500] Time 0.035 (0.034) Data 0.002 (0.002) Loss 0.0339 (0.0359) Prec@1 93.000 (94.317) Prec@5 100.000 (99.707) +2022-11-14 14:54:31,593 Epoch: [272][410/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0538 (0.0363) Prec@1 90.000 (94.214) Prec@5 98.000 (99.667) +2022-11-14 14:54:32,005 Epoch: [272][420/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0365 (0.0363) Prec@1 95.000 (94.233) Prec@5 100.000 (99.674) +2022-11-14 14:54:32,399 Epoch: [272][430/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0180 (0.0359) Prec@1 97.000 (94.295) Prec@5 100.000 (99.682) +2022-11-14 14:54:32,797 Epoch: [272][440/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0405 (0.0360) Prec@1 94.000 (94.289) Prec@5 99.000 (99.667) +2022-11-14 14:54:33,190 Epoch: [272][450/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0314 (0.0359) Prec@1 95.000 (94.304) Prec@5 100.000 (99.674) +2022-11-14 14:54:33,590 Epoch: [272][460/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0252 (0.0357) Prec@1 96.000 (94.340) Prec@5 100.000 (99.681) +2022-11-14 14:54:33,971 Epoch: [272][470/500] Time 0.034 (0.034) Data 0.002 (0.002) Loss 0.0377 (0.0357) Prec@1 92.000 (94.292) Prec@5 100.000 (99.688) +2022-11-14 14:54:34,359 Epoch: [272][480/500] Time 0.036 (0.034) Data 0.002 (0.002) Loss 0.0211 (0.0354) Prec@1 97.000 (94.347) Prec@5 100.000 (99.694) +2022-11-14 14:54:34,750 Epoch: [272][490/500] Time 0.033 (0.034) Data 0.002 (0.002) Loss 0.0387 (0.0355) Prec@1 93.000 (94.320) Prec@5 100.000 (99.700) +2022-11-14 14:54:35,099 Epoch: [272][499/500] Time 0.037 (0.034) Data 0.002 (0.002) Loss 0.0391 (0.0356) Prec@1 94.000 (94.314) Prec@5 100.000 (99.706) +2022-11-14 14:54:35,380 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0840 (0.0840) Prec@1 88.000 (88.000) Prec@5 98.000 (98.000) +2022-11-14 14:54:35,388 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0686) Prec@1 93.000 (90.500) Prec@5 100.000 (99.000) +2022-11-14 14:54:35,395 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0630) Prec@1 90.000 (90.333) Prec@5 100.000 (99.333) +2022-11-14 14:54:35,408 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0620) Prec@1 91.000 (90.500) Prec@5 98.000 (99.000) +2022-11-14 14:54:35,418 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0668) Prec@1 86.000 (89.600) Prec@5 100.000 (99.200) +2022-11-14 14:54:35,427 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0624) Prec@1 94.000 (90.333) Prec@5 100.000 (99.333) +2022-11-14 14:54:35,437 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0631) Prec@1 91.000 (90.429) Prec@5 100.000 (99.429) +2022-11-14 14:54:35,448 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0654) Prec@1 86.000 (89.875) Prec@5 100.000 (99.500) +2022-11-14 14:54:35,459 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0669) Prec@1 89.000 (89.778) Prec@5 98.000 (99.333) +2022-11-14 14:54:35,470 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0663) Prec@1 89.000 (89.700) Prec@5 99.000 (99.300) +2022-11-14 14:54:35,482 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0655) Prec@1 90.000 (89.727) Prec@5 100.000 (99.364) +2022-11-14 14:54:35,492 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0686) Prec@1 83.000 (89.167) Prec@5 100.000 (99.417) +2022-11-14 14:54:35,504 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0673) Prec@1 91.000 (89.308) Prec@5 100.000 (99.462) +2022-11-14 14:54:35,515 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0689) Prec@1 85.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:54:35,524 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0686) Prec@1 90.000 (89.067) Prec@5 100.000 (99.533) +2022-11-14 14:54:35,536 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0690) Prec@1 88.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 14:54:35,545 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0688) Prec@1 89.000 (89.000) Prec@5 98.000 (99.412) +2022-11-14 14:54:35,556 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0705) Prec@1 85.000 (88.778) Prec@5 99.000 (99.389) +2022-11-14 14:54:35,567 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0709) Prec@1 86.000 (88.632) Prec@5 100.000 (99.421) +2022-11-14 14:54:35,577 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0725) Prec@1 79.000 (88.150) Prec@5 98.000 (99.350) +2022-11-14 14:54:35,587 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0725) Prec@1 88.000 (88.143) Prec@5 99.000 (99.333) +2022-11-14 14:54:35,598 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0730) Prec@1 84.000 (87.955) Prec@5 99.000 (99.318) +2022-11-14 14:54:35,609 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0740) Prec@1 87.000 (87.913) Prec@5 99.000 (99.304) +2022-11-14 14:54:35,620 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0736) Prec@1 89.000 (87.958) Prec@5 100.000 (99.333) +2022-11-14 14:54:35,631 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0739) Prec@1 87.000 (87.920) Prec@5 100.000 (99.360) +2022-11-14 14:54:35,639 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0744) Prec@1 86.000 (87.846) Prec@5 99.000 (99.346) +2022-11-14 14:54:35,650 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0733) Prec@1 93.000 (88.037) Prec@5 100.000 (99.370) +2022-11-14 14:54:35,661 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0724) Prec@1 93.000 (88.214) Prec@5 99.000 (99.357) +2022-11-14 14:54:35,671 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0719) Prec@1 92.000 (88.345) Prec@5 98.000 (99.310) +2022-11-14 14:54:35,683 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0722) Prec@1 86.000 (88.267) Prec@5 98.000 (99.267) +2022-11-14 14:54:35,694 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0717) Prec@1 91.000 (88.355) Prec@5 98.000 (99.226) +2022-11-14 14:54:35,704 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0719) Prec@1 88.000 (88.344) Prec@5 99.000 (99.219) +2022-11-14 14:54:35,714 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0719) Prec@1 89.000 (88.364) Prec@5 99.000 (99.212) +2022-11-14 14:54:35,724 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0724) Prec@1 85.000 (88.265) Prec@5 100.000 (99.235) +2022-11-14 14:54:35,734 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0726) Prec@1 89.000 (88.286) Prec@5 98.000 (99.200) +2022-11-14 14:54:35,746 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0722) Prec@1 91.000 (88.361) Prec@5 100.000 (99.222) +2022-11-14 14:54:35,756 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0724) Prec@1 87.000 (88.324) Prec@5 98.000 (99.189) +2022-11-14 14:54:35,766 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0734) Prec@1 81.000 (88.132) Prec@5 100.000 (99.211) +2022-11-14 14:54:35,775 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0730) Prec@1 92.000 (88.231) Prec@5 99.000 (99.205) +2022-11-14 14:54:35,785 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 87.000 (88.200) Prec@5 98.000 (99.175) +2022-11-14 14:54:35,795 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0734) Prec@1 86.000 (88.146) Prec@5 98.000 (99.146) +2022-11-14 14:54:35,807 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0734) Prec@1 86.000 (88.095) Prec@5 100.000 (99.167) +2022-11-14 14:54:35,819 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0731) Prec@1 93.000 (88.209) Prec@5 99.000 (99.163) +2022-11-14 14:54:35,832 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0731) Prec@1 89.000 (88.227) Prec@5 98.000 (99.136) +2022-11-14 14:54:35,847 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0724) Prec@1 93.000 (88.333) Prec@5 99.000 (99.133) +2022-11-14 14:54:35,859 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0726) Prec@1 85.000 (88.261) Prec@5 100.000 (99.152) +2022-11-14 14:54:35,874 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0727) Prec@1 86.000 (88.213) Prec@5 100.000 (99.170) +2022-11-14 14:54:35,887 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1286 (0.0739) Prec@1 80.000 (88.042) Prec@5 98.000 (99.146) +2022-11-14 14:54:35,902 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0734) Prec@1 92.000 (88.122) Prec@5 100.000 (99.163) +2022-11-14 14:54:35,916 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0738) Prec@1 85.000 (88.060) Prec@5 100.000 (99.180) +2022-11-14 14:54:35,931 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0734) Prec@1 92.000 (88.137) Prec@5 100.000 (99.196) +2022-11-14 14:54:35,945 Test: [51/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0736) Prec@1 85.000 (88.077) Prec@5 99.000 (99.192) +2022-11-14 14:54:35,960 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0736) Prec@1 88.000 (88.075) Prec@5 99.000 (99.189) +2022-11-14 14:54:35,975 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0736) Prec@1 87.000 (88.056) Prec@5 100.000 (99.204) +2022-11-14 14:54:35,990 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0738) Prec@1 85.000 (88.000) Prec@5 100.000 (99.218) +2022-11-14 14:54:36,005 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0735) Prec@1 92.000 (88.071) Prec@5 99.000 (99.214) +2022-11-14 14:54:36,021 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0731) Prec@1 92.000 (88.140) Prec@5 100.000 (99.228) +2022-11-14 14:54:36,036 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0731) Prec@1 90.000 (88.172) Prec@5 100.000 (99.241) +2022-11-14 14:54:36,051 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0734) Prec@1 87.000 (88.153) Prec@5 97.000 (99.203) +2022-11-14 14:54:36,067 Test: [59/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0735) Prec@1 86.000 (88.117) Prec@5 99.000 (99.200) +2022-11-14 14:54:36,082 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0734) Prec@1 88.000 (88.115) Prec@5 98.000 (99.180) +2022-11-14 14:54:36,097 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0733) Prec@1 90.000 (88.145) Prec@5 99.000 (99.177) +2022-11-14 14:54:36,111 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0731) Prec@1 89.000 (88.159) Prec@5 100.000 (99.190) +2022-11-14 14:54:36,126 Test: [63/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0725) Prec@1 95.000 (88.266) Prec@5 100.000 (99.203) +2022-11-14 14:54:36,141 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0729) Prec@1 84.000 (88.200) Prec@5 100.000 (99.215) +2022-11-14 14:54:36,156 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0730) Prec@1 88.000 (88.197) Prec@5 99.000 (99.212) +2022-11-14 14:54:36,173 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0726) Prec@1 93.000 (88.269) Prec@5 100.000 (99.224) +2022-11-14 14:54:36,190 Test: [67/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0727) Prec@1 89.000 (88.279) Prec@5 98.000 (99.206) +2022-11-14 14:54:36,207 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0724) Prec@1 92.000 (88.333) Prec@5 99.000 (99.203) +2022-11-14 14:54:36,223 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0728) Prec@1 84.000 (88.271) Prec@5 100.000 (99.214) +2022-11-14 14:54:36,237 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0732) Prec@1 86.000 (88.239) Prec@5 97.000 (99.183) +2022-11-14 14:54:36,252 Test: [71/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0728) Prec@1 93.000 (88.306) Prec@5 100.000 (99.194) +2022-11-14 14:54:36,268 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0725) Prec@1 91.000 (88.342) Prec@5 100.000 (99.205) +2022-11-14 14:54:36,283 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0320 (0.0719) Prec@1 95.000 (88.432) Prec@5 100.000 (99.216) +2022-11-14 14:54:36,298 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0722) Prec@1 84.000 (88.373) Prec@5 100.000 (99.227) +2022-11-14 14:54:36,312 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0721) Prec@1 88.000 (88.368) Prec@5 98.000 (99.211) +2022-11-14 14:54:36,328 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0722) Prec@1 86.000 (88.338) Prec@5 100.000 (99.221) +2022-11-14 14:54:36,344 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0725) Prec@1 85.000 (88.295) Prec@5 100.000 (99.231) +2022-11-14 14:54:36,359 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0724) Prec@1 88.000 (88.291) Prec@5 100.000 (99.241) +2022-11-14 14:54:36,375 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0724) Prec@1 87.000 (88.275) Prec@5 100.000 (99.250) +2022-11-14 14:54:36,391 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0726) Prec@1 85.000 (88.235) Prec@5 98.000 (99.235) +2022-11-14 14:54:36,405 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0727) Prec@1 85.000 (88.195) Prec@5 98.000 (99.220) +2022-11-14 14:54:36,422 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0729) Prec@1 83.000 (88.133) Prec@5 100.000 (99.229) +2022-11-14 14:54:36,436 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0728) Prec@1 89.000 (88.143) Prec@5 98.000 (99.214) +2022-11-14 14:54:36,451 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0729) Prec@1 88.000 (88.141) Prec@5 99.000 (99.212) +2022-11-14 14:54:36,467 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0731) Prec@1 87.000 (88.128) Prec@5 100.000 (99.221) +2022-11-14 14:54:36,482 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0734) Prec@1 86.000 (88.103) Prec@5 99.000 (99.218) +2022-11-14 14:54:36,498 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0736) Prec@1 85.000 (88.068) Prec@5 99.000 (99.216) +2022-11-14 14:54:36,512 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0733) Prec@1 92.000 (88.112) Prec@5 99.000 (99.213) +2022-11-14 14:54:36,528 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0733) Prec@1 90.000 (88.133) Prec@5 98.000 (99.200) +2022-11-14 14:54:36,543 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0731) Prec@1 92.000 (88.176) Prec@5 99.000 (99.198) +2022-11-14 14:54:36,558 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0730) Prec@1 88.000 (88.174) Prec@5 99.000 (99.196) +2022-11-14 14:54:36,571 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 88.000 (88.172) Prec@5 99.000 (99.194) +2022-11-14 14:54:36,587 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0730) Prec@1 90.000 (88.191) Prec@5 99.000 (99.191) +2022-11-14 14:54:36,602 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0732) Prec@1 85.000 (88.158) Prec@5 100.000 (99.200) +2022-11-14 14:54:36,616 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0730) Prec@1 92.000 (88.198) Prec@5 99.000 (99.198) +2022-11-14 14:54:36,631 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0728) Prec@1 92.000 (88.237) Prec@5 99.000 (99.196) +2022-11-14 14:54:36,646 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0727) Prec@1 89.000 (88.245) Prec@5 100.000 (99.204) +2022-11-14 14:54:36,660 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0729) Prec@1 86.000 (88.222) Prec@5 96.000 (99.172) +2022-11-14 14:54:36,674 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0729) Prec@1 90.000 (88.240) Prec@5 99.000 (99.170) +2022-11-14 14:54:36,741 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:54:37,039 Epoch: [273][0/500] Time 0.023 (0.023) Data 0.218 (0.218) Loss 0.0364 (0.0364) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:54:37,270 Epoch: [273][10/500] Time 0.023 (0.020) Data 0.002 (0.021) Loss 0.0207 (0.0286) Prec@1 95.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:54:37,529 Epoch: [273][20/500] Time 0.023 (0.022) Data 0.002 (0.012) Loss 0.0913 (0.0495) Prec@1 85.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 14:54:37,850 Epoch: [273][30/500] Time 0.037 (0.024) Data 0.002 (0.009) Loss 0.0186 (0.0418) Prec@1 96.000 (92.250) Prec@5 100.000 (99.750) +2022-11-14 14:54:38,289 Epoch: [273][40/500] Time 0.039 (0.027) Data 0.002 (0.007) Loss 0.0223 (0.0379) Prec@1 98.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:54:38,737 Epoch: [273][50/500] Time 0.045 (0.030) Data 0.002 (0.006) Loss 0.0356 (0.0375) Prec@1 94.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 14:54:39,242 Epoch: [273][60/500] Time 0.047 (0.032) Data 0.002 (0.005) Loss 0.0521 (0.0396) Prec@1 91.000 (93.143) Prec@5 98.000 (99.571) +2022-11-14 14:54:39,697 Epoch: [273][70/500] Time 0.041 (0.033) Data 0.002 (0.005) Loss 0.0312 (0.0385) Prec@1 94.000 (93.250) Prec@5 100.000 (99.625) +2022-11-14 14:54:40,122 Epoch: [273][80/500] Time 0.041 (0.034) Data 0.002 (0.005) Loss 0.0531 (0.0401) Prec@1 90.000 (92.889) Prec@5 98.000 (99.444) +2022-11-14 14:54:40,623 Epoch: [273][90/500] Time 0.047 (0.035) Data 0.002 (0.004) Loss 0.0267 (0.0388) Prec@1 96.000 (93.200) Prec@5 100.000 (99.500) +2022-11-14 14:54:41,063 Epoch: [273][100/500] Time 0.039 (0.035) Data 0.002 (0.004) Loss 0.0263 (0.0377) Prec@1 96.000 (93.455) Prec@5 100.000 (99.545) +2022-11-14 14:54:41,526 Epoch: [273][110/500] Time 0.036 (0.036) Data 0.002 (0.004) Loss 0.0258 (0.0367) Prec@1 95.000 (93.583) Prec@5 100.000 (99.583) +2022-11-14 14:54:41,966 Epoch: [273][120/500] Time 0.047 (0.036) Data 0.002 (0.004) Loss 0.0329 (0.0364) Prec@1 96.000 (93.769) Prec@5 100.000 (99.615) +2022-11-14 14:54:42,403 Epoch: [273][130/500] Time 0.039 (0.037) Data 0.002 (0.004) Loss 0.0233 (0.0354) Prec@1 95.000 (93.857) Prec@5 100.000 (99.643) +2022-11-14 14:54:42,841 Epoch: [273][140/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0458 (0.0361) Prec@1 92.000 (93.733) Prec@5 100.000 (99.667) +2022-11-14 14:54:43,278 Epoch: [273][150/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0421 (0.0365) Prec@1 93.000 (93.688) Prec@5 100.000 (99.688) +2022-11-14 14:54:43,716 Epoch: [273][160/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0303 (0.0361) Prec@1 94.000 (93.706) Prec@5 99.000 (99.647) +2022-11-14 14:54:44,153 Epoch: [273][170/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0368 (0.0362) Prec@1 93.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:54:44,586 Epoch: [273][180/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0451 (0.0366) Prec@1 92.000 (93.579) Prec@5 99.000 (99.632) +2022-11-14 14:54:45,012 Epoch: [273][190/500] Time 0.040 (0.037) Data 0.002 (0.003) Loss 0.0618 (0.0379) Prec@1 87.000 (93.250) Prec@5 100.000 (99.650) +2022-11-14 14:54:45,460 Epoch: [273][200/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0252 (0.0373) Prec@1 94.000 (93.286) Prec@5 100.000 (99.667) +2022-11-14 14:54:45,947 Epoch: [273][210/500] Time 0.053 (0.038) Data 0.002 (0.003) Loss 0.0524 (0.0380) Prec@1 93.000 (93.273) Prec@5 100.000 (99.682) +2022-11-14 14:54:46,378 Epoch: [273][220/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0578 (0.0388) Prec@1 92.000 (93.217) Prec@5 99.000 (99.652) +2022-11-14 14:54:46,833 Epoch: [273][230/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0309 (0.0385) Prec@1 95.000 (93.292) Prec@5 100.000 (99.667) +2022-11-14 14:54:47,268 Epoch: [273][240/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0557 (0.0392) Prec@1 92.000 (93.240) Prec@5 98.000 (99.600) +2022-11-14 14:54:47,692 Epoch: [273][250/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0247 (0.0386) Prec@1 95.000 (93.308) Prec@5 100.000 (99.615) +2022-11-14 14:54:48,121 Epoch: [273][260/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0185 (0.0379) Prec@1 98.000 (93.481) Prec@5 100.000 (99.630) +2022-11-14 14:54:48,583 Epoch: [273][270/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0519 (0.0384) Prec@1 91.000 (93.393) Prec@5 100.000 (99.643) +2022-11-14 14:54:49,021 Epoch: [273][280/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0463 (0.0387) Prec@1 93.000 (93.379) Prec@5 100.000 (99.655) +2022-11-14 14:54:49,465 Epoch: [273][290/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0498 (0.0390) Prec@1 91.000 (93.300) Prec@5 100.000 (99.667) +2022-11-14 14:54:49,993 Epoch: [273][300/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0394 (0.0391) Prec@1 94.000 (93.323) Prec@5 100.000 (99.677) +2022-11-14 14:54:50,437 Epoch: [273][310/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0416 (0.0391) Prec@1 95.000 (93.375) Prec@5 100.000 (99.688) +2022-11-14 14:54:50,854 Epoch: [273][320/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0382 (0.0391) Prec@1 92.000 (93.333) Prec@5 100.000 (99.697) +2022-11-14 14:54:51,280 Epoch: [273][330/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0205 (0.0386) Prec@1 97.000 (93.441) Prec@5 99.000 (99.676) +2022-11-14 14:54:51,724 Epoch: [273][340/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0259 (0.0382) Prec@1 96.000 (93.514) Prec@5 100.000 (99.686) +2022-11-14 14:54:52,167 Epoch: [273][350/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0399 (0.0382) Prec@1 94.000 (93.528) Prec@5 100.000 (99.694) +2022-11-14 14:54:52,594 Epoch: [273][360/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0243 (0.0379) Prec@1 97.000 (93.622) Prec@5 100.000 (99.703) +2022-11-14 14:54:53,010 Epoch: [273][370/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0335 (0.0377) Prec@1 95.000 (93.658) Prec@5 99.000 (99.684) +2022-11-14 14:54:53,436 Epoch: [273][380/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0327 (0.0376) Prec@1 94.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 14:54:53,869 Epoch: [273][390/500] Time 0.042 (0.038) Data 0.002 (0.002) Loss 0.0520 (0.0380) Prec@1 93.000 (93.650) Prec@5 99.000 (99.650) +2022-11-14 14:54:54,304 Epoch: [273][400/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0284 (0.0377) Prec@1 95.000 (93.683) Prec@5 100.000 (99.659) +2022-11-14 14:54:54,741 Epoch: [273][410/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0415 (0.0378) Prec@1 93.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 14:54:55,183 Epoch: [273][420/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0280 (0.0376) Prec@1 95.000 (93.698) Prec@5 100.000 (99.674) +2022-11-14 14:54:55,624 Epoch: [273][430/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0382 (0.0376) Prec@1 95.000 (93.727) Prec@5 100.000 (99.682) +2022-11-14 14:54:56,060 Epoch: [273][440/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0363 (0.0376) Prec@1 93.000 (93.711) Prec@5 100.000 (99.689) +2022-11-14 14:54:56,510 Epoch: [273][450/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0518 (0.0379) Prec@1 90.000 (93.630) Prec@5 100.000 (99.696) +2022-11-14 14:54:56,928 Epoch: [273][460/500] Time 0.037 (0.038) Data 0.002 (0.002) Loss 0.0159 (0.0374) Prec@1 97.000 (93.702) Prec@5 100.000 (99.702) +2022-11-14 14:54:57,350 Epoch: [273][470/500] Time 0.040 (0.038) Data 0.002 (0.002) Loss 0.0320 (0.0373) Prec@1 97.000 (93.771) Prec@5 100.000 (99.708) +2022-11-14 14:54:57,777 Epoch: [273][480/500] Time 0.039 (0.038) Data 0.002 (0.002) Loss 0.0639 (0.0379) Prec@1 90.000 (93.694) Prec@5 99.000 (99.694) +2022-11-14 14:54:58,228 Epoch: [273][490/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.0503 (0.0381) Prec@1 91.000 (93.640) Prec@5 100.000 (99.700) +2022-11-14 14:54:58,619 Epoch: [273][499/500] Time 0.038 (0.038) Data 0.002 (0.002) Loss 0.0392 (0.0381) Prec@1 96.000 (93.686) Prec@5 100.000 (99.706) +2022-11-14 14:54:58,908 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0730 (0.0730) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 14:54:58,919 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0695) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:54:58,928 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0687) Prec@1 90.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 14:54:58,941 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0718) Prec@1 86.000 (88.500) Prec@5 98.000 (99.000) +2022-11-14 14:54:58,950 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0743) Prec@1 86.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 14:54:58,960 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0394 (0.0685) Prec@1 95.000 (89.167) Prec@5 100.000 (99.333) +2022-11-14 14:54:58,969 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0673) Prec@1 91.000 (89.429) Prec@5 100.000 (99.429) +2022-11-14 14:54:58,979 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0699) Prec@1 86.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 14:54:58,989 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0712) Prec@1 86.000 (88.667) Prec@5 98.000 (99.333) +2022-11-14 14:54:58,999 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0710) Prec@1 90.000 (88.800) Prec@5 99.000 (99.300) +2022-11-14 14:54:59,008 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0694) Prec@1 92.000 (89.091) Prec@5 99.000 (99.273) +2022-11-14 14:54:59,017 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0687) Prec@1 90.000 (89.167) Prec@5 100.000 (99.333) +2022-11-14 14:54:59,028 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0688) Prec@1 87.000 (89.000) Prec@5 100.000 (99.385) +2022-11-14 14:54:59,037 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0684) Prec@1 91.000 (89.143) Prec@5 100.000 (99.429) +2022-11-14 14:54:59,048 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0683) Prec@1 87.000 (89.000) Prec@5 100.000 (99.467) +2022-11-14 14:54:59,058 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0682) Prec@1 89.000 (89.000) Prec@5 99.000 (99.438) +2022-11-14 14:54:59,069 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0682) Prec@1 90.000 (89.059) Prec@5 97.000 (99.294) +2022-11-14 14:54:59,079 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0699) Prec@1 86.000 (88.889) Prec@5 100.000 (99.333) +2022-11-14 14:54:59,090 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0716) Prec@1 81.000 (88.474) Prec@5 99.000 (99.316) +2022-11-14 14:54:59,100 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0725) Prec@1 84.000 (88.250) Prec@5 99.000 (99.300) +2022-11-14 14:54:59,111 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0721) Prec@1 90.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 14:54:59,120 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0727) Prec@1 86.000 (88.227) Prec@5 99.000 (99.318) +2022-11-14 14:54:59,131 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0736) Prec@1 87.000 (88.174) Prec@5 100.000 (99.348) +2022-11-14 14:54:59,141 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0733) Prec@1 89.000 (88.208) Prec@5 99.000 (99.333) +2022-11-14 14:54:59,152 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0737) Prec@1 87.000 (88.160) Prec@5 99.000 (99.320) +2022-11-14 14:54:59,161 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0738) Prec@1 89.000 (88.192) Prec@5 98.000 (99.269) +2022-11-14 14:54:59,173 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0730) Prec@1 93.000 (88.370) Prec@5 100.000 (99.296) +2022-11-14 14:54:59,182 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0725) Prec@1 89.000 (88.393) Prec@5 100.000 (99.321) +2022-11-14 14:54:59,193 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0720) Prec@1 92.000 (88.517) Prec@5 98.000 (99.276) +2022-11-14 14:54:59,203 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0719) Prec@1 87.000 (88.467) Prec@5 99.000 (99.267) +2022-11-14 14:54:59,214 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0718) Prec@1 90.000 (88.516) Prec@5 100.000 (99.290) +2022-11-14 14:54:59,224 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0715) Prec@1 89.000 (88.531) Prec@5 99.000 (99.281) +2022-11-14 14:54:59,235 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0716) Prec@1 87.000 (88.485) Prec@5 99.000 (99.273) +2022-11-14 14:54:59,245 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0720) Prec@1 86.000 (88.412) Prec@5 100.000 (99.294) +2022-11-14 14:54:59,256 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0726) Prec@1 86.000 (88.343) Prec@5 99.000 (99.286) +2022-11-14 14:54:59,266 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0724) Prec@1 91.000 (88.417) Prec@5 98.000 (99.250) +2022-11-14 14:54:59,276 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0720) Prec@1 91.000 (88.486) Prec@5 99.000 (99.243) +2022-11-14 14:54:59,286 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0729) Prec@1 85.000 (88.395) Prec@5 98.000 (99.211) +2022-11-14 14:54:59,297 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0724) Prec@1 94.000 (88.538) Prec@5 100.000 (99.231) +2022-11-14 14:54:59,306 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0725) Prec@1 88.000 (88.525) Prec@5 98.000 (99.200) +2022-11-14 14:54:59,316 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1193 (0.0736) Prec@1 83.000 (88.390) Prec@5 98.000 (99.171) +2022-11-14 14:54:59,327 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0735) Prec@1 88.000 (88.381) Prec@5 99.000 (99.167) +2022-11-14 14:54:59,337 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0729) Prec@1 93.000 (88.488) Prec@5 99.000 (99.163) +2022-11-14 14:54:59,348 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0731) Prec@1 88.000 (88.477) Prec@5 99.000 (99.159) +2022-11-14 14:54:59,359 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0384 (0.0723) Prec@1 94.000 (88.600) Prec@5 100.000 (99.178) +2022-11-14 14:54:59,370 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0730) Prec@1 83.000 (88.478) Prec@5 99.000 (99.174) +2022-11-14 14:54:59,381 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0732) Prec@1 85.000 (88.404) Prec@5 100.000 (99.191) +2022-11-14 14:54:59,392 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0736) Prec@1 83.000 (88.292) Prec@5 98.000 (99.167) +2022-11-14 14:54:59,404 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0732) Prec@1 92.000 (88.367) Prec@5 100.000 (99.184) +2022-11-14 14:54:59,415 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1117 (0.0740) Prec@1 84.000 (88.280) Prec@5 99.000 (99.180) +2022-11-14 14:54:59,427 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0739) Prec@1 89.000 (88.294) Prec@5 99.000 (99.176) +2022-11-14 14:54:59,439 Test: [51/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0740) Prec@1 88.000 (88.288) Prec@5 100.000 (99.192) +2022-11-14 14:54:59,450 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0740) Prec@1 87.000 (88.264) Prec@5 99.000 (99.189) +2022-11-14 14:54:59,461 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0738) Prec@1 89.000 (88.278) Prec@5 99.000 (99.185) +2022-11-14 14:54:59,471 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0741) Prec@1 85.000 (88.218) Prec@5 100.000 (99.200) +2022-11-14 14:54:59,480 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0741) Prec@1 88.000 (88.214) Prec@5 99.000 (99.196) +2022-11-14 14:54:59,491 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0739) Prec@1 89.000 (88.228) Prec@5 100.000 (99.211) +2022-11-14 14:54:59,504 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0739) Prec@1 89.000 (88.241) Prec@5 100.000 (99.224) +2022-11-14 14:54:59,515 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0742) Prec@1 86.000 (88.203) Prec@5 99.000 (99.220) +2022-11-14 14:54:59,526 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0742) Prec@1 86.000 (88.167) Prec@5 98.000 (99.200) +2022-11-14 14:54:59,535 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0743) Prec@1 86.000 (88.131) Prec@5 98.000 (99.180) +2022-11-14 14:54:59,545 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0742) Prec@1 90.000 (88.161) Prec@5 99.000 (99.177) +2022-11-14 14:54:59,557 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0741) Prec@1 90.000 (88.190) Prec@5 100.000 (99.190) +2022-11-14 14:54:59,567 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0737) Prec@1 93.000 (88.266) Prec@5 100.000 (99.203) +2022-11-14 14:54:59,579 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1070 (0.0742) Prec@1 81.000 (88.154) Prec@5 100.000 (99.215) +2022-11-14 14:54:59,590 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0745) Prec@1 84.000 (88.091) Prec@5 100.000 (99.227) +2022-11-14 14:54:59,600 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0740) Prec@1 92.000 (88.149) Prec@5 100.000 (99.239) +2022-11-14 14:54:59,611 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0739) Prec@1 90.000 (88.176) Prec@5 97.000 (99.206) +2022-11-14 14:54:59,621 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0738) Prec@1 88.000 (88.174) Prec@5 100.000 (99.217) +2022-11-14 14:54:59,633 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0739) Prec@1 89.000 (88.186) Prec@5 97.000 (99.186) +2022-11-14 14:54:59,643 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0744) Prec@1 83.000 (88.113) Prec@5 97.000 (99.155) +2022-11-14 14:54:59,655 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0744) Prec@1 86.000 (88.083) Prec@5 100.000 (99.167) +2022-11-14 14:54:59,665 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0743) Prec@1 88.000 (88.082) Prec@5 100.000 (99.178) +2022-11-14 14:54:59,677 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0389 (0.0738) Prec@1 95.000 (88.176) Prec@5 100.000 (99.189) +2022-11-14 14:54:59,688 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0741) Prec@1 84.000 (88.120) Prec@5 100.000 (99.200) +2022-11-14 14:54:59,702 Test: [75/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0742) Prec@1 89.000 (88.132) Prec@5 100.000 (99.211) +2022-11-14 14:54:59,713 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0739) Prec@1 90.000 (88.156) Prec@5 98.000 (99.195) +2022-11-14 14:54:59,725 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0741) Prec@1 85.000 (88.115) Prec@5 97.000 (99.167) +2022-11-14 14:54:59,736 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0741) Prec@1 90.000 (88.139) Prec@5 100.000 (99.177) +2022-11-14 14:54:59,748 Test: [79/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0741) Prec@1 88.000 (88.138) Prec@5 100.000 (99.188) +2022-11-14 14:54:59,761 Test: [80/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0741) Prec@1 87.000 (88.123) Prec@5 99.000 (99.185) +2022-11-14 14:54:59,773 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0741) Prec@1 89.000 (88.134) Prec@5 99.000 (99.183) +2022-11-14 14:54:59,784 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 85.000 (88.096) Prec@5 100.000 (99.193) +2022-11-14 14:54:59,797 Test: [83/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0741) Prec@1 90.000 (88.119) Prec@5 99.000 (99.190) +2022-11-14 14:54:59,809 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0740) Prec@1 90.000 (88.141) Prec@5 100.000 (99.200) +2022-11-14 14:54:59,820 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0743) Prec@1 83.000 (88.081) Prec@5 99.000 (99.198) +2022-11-14 14:54:59,830 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0745) Prec@1 88.000 (88.080) Prec@5 100.000 (99.207) +2022-11-14 14:54:59,842 Test: [87/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0745) Prec@1 85.000 (88.045) Prec@5 99.000 (99.205) +2022-11-14 14:54:59,856 Test: [88/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0746) Prec@1 88.000 (88.045) Prec@5 100.000 (99.213) +2022-11-14 14:54:59,867 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0746) Prec@1 88.000 (88.044) Prec@5 98.000 (99.200) +2022-11-14 14:54:59,876 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0745) Prec@1 90.000 (88.066) Prec@5 100.000 (99.209) +2022-11-14 14:54:59,889 Test: [91/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0742) Prec@1 92.000 (88.109) Prec@5 100.000 (99.217) +2022-11-14 14:54:59,902 Test: [92/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0743) Prec@1 87.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 14:54:59,913 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0744) Prec@1 87.000 (88.085) Prec@5 96.000 (99.191) +2022-11-14 14:54:59,924 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0744) Prec@1 88.000 (88.084) Prec@5 99.000 (99.189) +2022-11-14 14:54:59,934 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0743) Prec@1 90.000 (88.104) Prec@5 99.000 (99.188) +2022-11-14 14:54:59,945 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0740) Prec@1 92.000 (88.144) Prec@5 97.000 (99.165) +2022-11-14 14:54:59,956 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0740) Prec@1 89.000 (88.153) Prec@5 99.000 (99.163) +2022-11-14 14:54:59,967 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0742) Prec@1 85.000 (88.121) Prec@5 99.000 (99.162) +2022-11-14 14:54:59,977 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0741) Prec@1 91.000 (88.150) Prec@5 99.000 (99.160) +2022-11-14 14:55:00,052 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:55:00,374 Epoch: [274][0/500] Time 0.026 (0.026) Data 0.230 (0.230) Loss 0.0370 (0.0370) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 14:55:00,585 Epoch: [274][10/500] Time 0.018 (0.019) Data 0.002 (0.022) Loss 0.0222 (0.0296) Prec@1 97.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 14:55:00,795 Epoch: [274][20/500] Time 0.018 (0.019) Data 0.002 (0.013) Loss 0.0238 (0.0277) Prec@1 96.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 14:55:01,087 Epoch: [274][30/500] Time 0.038 (0.021) Data 0.002 (0.009) Loss 0.0355 (0.0296) Prec@1 94.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 14:55:01,621 Epoch: [274][40/500] Time 0.046 (0.027) Data 0.002 (0.007) Loss 0.0637 (0.0364) Prec@1 92.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 14:55:02,124 Epoch: [274][50/500] Time 0.044 (0.031) Data 0.002 (0.006) Loss 0.0361 (0.0364) Prec@1 93.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 14:55:02,644 Epoch: [274][60/500] Time 0.047 (0.033) Data 0.002 (0.006) Loss 0.0416 (0.0371) Prec@1 92.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 14:55:03,121 Epoch: [274][70/500] Time 0.044 (0.034) Data 0.002 (0.005) Loss 0.0328 (0.0366) Prec@1 95.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 14:55:03,666 Epoch: [274][80/500] Time 0.038 (0.036) Data 0.002 (0.005) Loss 0.0309 (0.0360) Prec@1 94.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 14:55:04,157 Epoch: [274][90/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0417 (0.0365) Prec@1 94.000 (94.000) Prec@5 99.000 (99.800) +2022-11-14 14:55:04,700 Epoch: [274][100/500] Time 0.043 (0.038) Data 0.003 (0.004) Loss 0.0341 (0.0363) Prec@1 96.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 14:55:05,178 Epoch: [274][110/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0308 (0.0359) Prec@1 95.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 14:55:05,671 Epoch: [274][120/500] Time 0.049 (0.039) Data 0.002 (0.004) Loss 0.0175 (0.0344) Prec@1 97.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 14:55:06,161 Epoch: [274][130/500] Time 0.045 (0.040) Data 0.002 (0.004) Loss 0.0298 (0.0341) Prec@1 96.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 14:55:06,671 Epoch: [274][140/500] Time 0.039 (0.040) Data 0.002 (0.004) Loss 0.0328 (0.0340) Prec@1 95.000 (94.600) Prec@5 100.000 (99.867) +2022-11-14 14:55:07,175 Epoch: [274][150/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0274 (0.0336) Prec@1 95.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 14:55:07,661 Epoch: [274][160/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0465 (0.0344) Prec@1 94.000 (94.588) Prec@5 99.000 (99.824) +2022-11-14 14:55:08,172 Epoch: [274][170/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0221 (0.0337) Prec@1 98.000 (94.778) Prec@5 100.000 (99.833) +2022-11-14 14:55:08,690 Epoch: [274][180/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0551 (0.0348) Prec@1 93.000 (94.684) Prec@5 100.000 (99.842) +2022-11-14 14:55:09,178 Epoch: [274][190/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0334 (0.0347) Prec@1 96.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 14:55:09,657 Epoch: [274][200/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0385 (0.0349) Prec@1 93.000 (94.667) Prec@5 99.000 (99.810) +2022-11-14 14:55:10,181 Epoch: [274][210/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.0185 (0.0342) Prec@1 98.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 14:55:10,667 Epoch: [274][220/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0514 (0.0349) Prec@1 91.000 (94.652) Prec@5 100.000 (99.826) +2022-11-14 14:55:11,141 Epoch: [274][230/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0235 (0.0344) Prec@1 96.000 (94.708) Prec@5 100.000 (99.833) +2022-11-14 14:55:11,642 Epoch: [274][240/500] Time 0.065 (0.042) Data 0.002 (0.003) Loss 0.0341 (0.0344) Prec@1 94.000 (94.680) Prec@5 100.000 (99.840) +2022-11-14 14:55:12,135 Epoch: [274][250/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0518 (0.0351) Prec@1 92.000 (94.577) Prec@5 100.000 (99.846) +2022-11-14 14:55:12,644 Epoch: [274][260/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0121 (0.0342) Prec@1 98.000 (94.704) Prec@5 100.000 (99.852) +2022-11-14 14:55:13,151 Epoch: [274][270/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0460 (0.0347) Prec@1 92.000 (94.607) Prec@5 100.000 (99.857) +2022-11-14 14:55:13,644 Epoch: [274][280/500] Time 0.041 (0.042) Data 0.002 (0.003) Loss 0.0387 (0.0348) Prec@1 92.000 (94.517) Prec@5 100.000 (99.862) +2022-11-14 14:55:14,121 Epoch: [274][290/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0289 (0.0346) Prec@1 95.000 (94.533) Prec@5 100.000 (99.867) +2022-11-14 14:55:14,604 Epoch: [274][300/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0162 (0.0340) Prec@1 99.000 (94.677) Prec@5 100.000 (99.871) +2022-11-14 14:55:15,113 Epoch: [274][310/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0306 (0.0339) Prec@1 95.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 14:55:15,589 Epoch: [274][320/500] Time 0.043 (0.042) Data 0.001 (0.003) Loss 0.0667 (0.0349) Prec@1 88.000 (94.485) Prec@5 99.000 (99.848) +2022-11-14 14:55:16,081 Epoch: [274][330/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0318 (0.0348) Prec@1 94.000 (94.471) Prec@5 99.000 (99.824) +2022-11-14 14:55:16,562 Epoch: [274][340/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0310 (0.0347) Prec@1 95.000 (94.486) Prec@5 100.000 (99.829) +2022-11-14 14:55:17,055 Epoch: [274][350/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0314 (0.0346) Prec@1 96.000 (94.528) Prec@5 100.000 (99.833) +2022-11-14 14:55:17,570 Epoch: [274][360/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0398 (0.0348) Prec@1 94.000 (94.514) Prec@5 100.000 (99.838) +2022-11-14 14:55:18,044 Epoch: [274][370/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0381 (0.0348) Prec@1 93.000 (94.474) Prec@5 100.000 (99.842) +2022-11-14 14:55:18,531 Epoch: [274][380/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0215 (0.0345) Prec@1 96.000 (94.513) Prec@5 100.000 (99.846) +2022-11-14 14:55:19,012 Epoch: [274][390/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0299 (0.0344) Prec@1 96.000 (94.550) Prec@5 100.000 (99.850) +2022-11-14 14:55:19,421 Epoch: [274][400/500] Time 0.035 (0.042) Data 0.002 (0.003) Loss 0.0387 (0.0345) Prec@1 93.000 (94.512) Prec@5 100.000 (99.854) +2022-11-14 14:55:19,718 Epoch: [274][410/500] Time 0.026 (0.042) Data 0.002 (0.003) Loss 0.0440 (0.0347) Prec@1 94.000 (94.500) Prec@5 100.000 (99.857) +2022-11-14 14:55:20,019 Epoch: [274][420/500] Time 0.026 (0.042) Data 0.002 (0.002) Loss 0.0253 (0.0345) Prec@1 95.000 (94.512) Prec@5 100.000 (99.860) +2022-11-14 14:55:20,319 Epoch: [274][430/500] Time 0.031 (0.041) Data 0.001 (0.002) Loss 0.0236 (0.0342) Prec@1 97.000 (94.568) Prec@5 100.000 (99.864) +2022-11-14 14:55:20,656 Epoch: [274][440/500] Time 0.048 (0.041) Data 0.002 (0.002) Loss 0.0348 (0.0343) Prec@1 94.000 (94.556) Prec@5 100.000 (99.867) +2022-11-14 14:55:20,952 Epoch: [274][450/500] Time 0.031 (0.041) Data 0.002 (0.002) Loss 0.0599 (0.0348) Prec@1 88.000 (94.413) Prec@5 100.000 (99.870) +2022-11-14 14:55:21,323 Epoch: [274][460/500] Time 0.025 (0.041) Data 0.003 (0.002) Loss 0.0311 (0.0347) Prec@1 95.000 (94.426) Prec@5 99.000 (99.851) +2022-11-14 14:55:21,616 Epoch: [274][470/500] Time 0.024 (0.040) Data 0.002 (0.002) Loss 0.0244 (0.0345) Prec@1 96.000 (94.458) Prec@5 100.000 (99.854) +2022-11-14 14:55:21,918 Epoch: [274][480/500] Time 0.033 (0.040) Data 0.002 (0.002) Loss 0.0342 (0.0345) Prec@1 96.000 (94.490) Prec@5 100.000 (99.857) +2022-11-14 14:55:22,214 Epoch: [274][490/500] Time 0.028 (0.040) Data 0.002 (0.002) Loss 0.0221 (0.0343) Prec@1 96.000 (94.520) Prec@5 100.000 (99.860) +2022-11-14 14:55:22,493 Epoch: [274][499/500] Time 0.030 (0.040) Data 0.002 (0.002) Loss 0.0412 (0.0344) Prec@1 95.000 (94.529) Prec@5 100.000 (99.863) +2022-11-14 14:55:22,777 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0666 (0.0666) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:55:22,787 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0880 (0.0773) Prec@1 85.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 14:55:22,799 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0674 (0.0740) Prec@1 91.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 14:55:22,813 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0579 (0.0700) Prec@1 90.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 14:55:22,827 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0819 (0.0723) Prec@1 87.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 14:55:22,837 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0378 (0.0666) Prec@1 93.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 14:55:22,849 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0447 (0.0635) Prec@1 94.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 14:55:22,861 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0657) Prec@1 86.000 (89.250) Prec@5 97.000 (99.375) +2022-11-14 14:55:22,872 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0680) Prec@1 87.000 (89.000) Prec@5 98.000 (99.222) +2022-11-14 14:55:22,883 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0705) Prec@1 86.000 (88.700) Prec@5 98.000 (99.100) +2022-11-14 14:55:22,894 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0699) Prec@1 89.000 (88.727) Prec@5 100.000 (99.182) +2022-11-14 14:55:22,906 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.0721) Prec@1 84.000 (88.333) Prec@5 97.000 (99.000) +2022-11-14 14:55:22,917 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0599 (0.0712) Prec@1 89.000 (88.385) Prec@5 100.000 (99.077) +2022-11-14 14:55:22,929 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0707) Prec@1 89.000 (88.429) Prec@5 100.000 (99.143) +2022-11-14 14:55:22,940 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0712) Prec@1 87.000 (88.333) Prec@5 98.000 (99.067) +2022-11-14 14:55:22,955 Test: [15/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.0726) Prec@1 84.000 (88.062) Prec@5 99.000 (99.062) +2022-11-14 14:55:22,968 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0728) Prec@1 88.000 (88.059) Prec@5 99.000 (99.059) +2022-11-14 14:55:22,979 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0935 (0.0739) Prec@1 86.000 (87.944) Prec@5 99.000 (99.056) +2022-11-14 14:55:22,990 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0738) Prec@1 89.000 (88.000) Prec@5 98.000 (99.000) +2022-11-14 14:55:23,003 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.0753) Prec@1 81.000 (87.650) Prec@5 98.000 (98.950) +2022-11-14 14:55:23,014 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.0759) Prec@1 85.000 (87.524) Prec@5 99.000 (98.952) +2022-11-14 14:55:23,023 Test: [21/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0760) Prec@1 87.000 (87.500) Prec@5 99.000 (98.955) +2022-11-14 14:55:23,032 Test: [22/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.0765) Prec@1 87.000 (87.478) Prec@5 99.000 (98.957) +2022-11-14 14:55:23,045 Test: [23/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0513 (0.0754) Prec@1 91.000 (87.625) Prec@5 100.000 (99.000) +2022-11-14 14:55:23,057 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0936 (0.0761) Prec@1 87.000 (87.600) Prec@5 100.000 (99.040) +2022-11-14 14:55:23,067 Test: [25/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0766) Prec@1 88.000 (87.615) Prec@5 100.000 (99.077) +2022-11-14 14:55:23,078 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0486 (0.0756) Prec@1 93.000 (87.815) Prec@5 100.000 (99.111) +2022-11-14 14:55:23,090 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0567 (0.0749) Prec@1 91.000 (87.929) Prec@5 100.000 (99.143) +2022-11-14 14:55:23,099 Test: [28/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0752) Prec@1 87.000 (87.897) Prec@5 98.000 (99.103) +2022-11-14 14:55:23,110 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0753) Prec@1 88.000 (87.900) Prec@5 99.000 (99.100) +2022-11-14 14:55:23,120 Test: [30/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0751) Prec@1 88.000 (87.903) Prec@5 100.000 (99.129) +2022-11-14 14:55:23,132 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0745) Prec@1 91.000 (88.000) Prec@5 100.000 (99.156) +2022-11-14 14:55:23,142 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0745) Prec@1 87.000 (87.970) Prec@5 100.000 (99.182) +2022-11-14 14:55:23,152 Test: [33/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0748) Prec@1 86.000 (87.912) Prec@5 100.000 (99.206) +2022-11-14 14:55:23,163 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0755) Prec@1 84.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 14:55:23,175 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0753) Prec@1 91.000 (87.889) Prec@5 100.000 (99.222) +2022-11-14 14:55:23,187 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0755) Prec@1 85.000 (87.811) Prec@5 99.000 (99.216) +2022-11-14 14:55:23,199 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0763) Prec@1 85.000 (87.737) Prec@5 98.000 (99.184) +2022-11-14 14:55:23,211 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0760) Prec@1 90.000 (87.795) Prec@5 99.000 (99.179) +2022-11-14 14:55:23,222 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0754) Prec@1 91.000 (87.875) Prec@5 99.000 (99.175) +2022-11-14 14:55:23,232 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0761) Prec@1 85.000 (87.805) Prec@5 97.000 (99.122) +2022-11-14 14:55:23,245 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0758) Prec@1 89.000 (87.833) Prec@5 99.000 (99.119) +2022-11-14 14:55:23,258 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0754) Prec@1 89.000 (87.860) Prec@5 99.000 (99.116) +2022-11-14 14:55:23,270 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0752) Prec@1 91.000 (87.932) Prec@5 99.000 (99.114) +2022-11-14 14:55:23,281 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0748) Prec@1 90.000 (87.978) Prec@5 99.000 (99.111) +2022-11-14 14:55:23,294 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0753) Prec@1 84.000 (87.891) Prec@5 99.000 (99.109) +2022-11-14 14:55:23,306 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0747) Prec@1 89.000 (87.915) Prec@5 100.000 (99.128) +2022-11-14 14:55:23,318 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0754) Prec@1 82.000 (87.792) Prec@5 99.000 (99.125) +2022-11-14 14:55:23,330 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0454 (0.0747) Prec@1 91.000 (87.857) Prec@5 100.000 (99.143) +2022-11-14 14:55:23,341 Test: [49/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.0755) Prec@1 86.000 (87.820) Prec@5 100.000 (99.160) +2022-11-14 14:55:23,351 Test: [50/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0756) Prec@1 85.000 (87.765) Prec@5 99.000 (99.157) +2022-11-14 14:55:23,364 Test: [51/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0760) Prec@1 85.000 (87.712) Prec@5 98.000 (99.135) +2022-11-14 14:55:23,375 Test: [52/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0762) Prec@1 84.000 (87.642) Prec@5 99.000 (99.132) +2022-11-14 14:55:23,387 Test: [53/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0765) Prec@1 84.000 (87.574) Prec@5 98.000 (99.111) +2022-11-14 14:55:23,400 Test: [54/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0767) Prec@1 89.000 (87.600) Prec@5 98.000 (99.091) +2022-11-14 14:55:23,413 Test: [55/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0765) Prec@1 88.000 (87.607) Prec@5 99.000 (99.089) +2022-11-14 14:55:23,426 Test: [56/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0765) Prec@1 87.000 (87.596) Prec@5 100.000 (99.105) +2022-11-14 14:55:23,437 Test: [57/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0764) Prec@1 91.000 (87.655) Prec@5 100.000 (99.121) +2022-11-14 14:55:23,448 Test: [58/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0769) Prec@1 82.000 (87.559) Prec@5 99.000 (99.119) +2022-11-14 14:55:23,461 Test: [59/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0768) Prec@1 87.000 (87.550) Prec@5 100.000 (99.133) +2022-11-14 14:55:23,474 Test: [60/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0769) Prec@1 86.000 (87.525) Prec@5 97.000 (99.098) +2022-11-14 14:55:23,486 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0768) Prec@1 87.000 (87.516) Prec@5 100.000 (99.113) +2022-11-14 14:55:23,496 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0766) Prec@1 89.000 (87.540) Prec@5 99.000 (99.111) +2022-11-14 14:55:23,507 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0350 (0.0760) Prec@1 95.000 (87.656) Prec@5 100.000 (99.125) +2022-11-14 14:55:23,520 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0764) Prec@1 84.000 (87.600) Prec@5 99.000 (99.123) +2022-11-14 14:55:23,531 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0767) Prec@1 85.000 (87.561) Prec@5 99.000 (99.121) +2022-11-14 14:55:23,543 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0764) Prec@1 90.000 (87.597) Prec@5 100.000 (99.134) +2022-11-14 14:55:23,554 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0762) Prec@1 89.000 (87.618) Prec@5 99.000 (99.132) +2022-11-14 14:55:23,565 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0759) Prec@1 92.000 (87.681) Prec@5 99.000 (99.130) +2022-11-14 14:55:23,578 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0761) Prec@1 84.000 (87.629) Prec@5 99.000 (99.129) +2022-11-14 14:55:23,590 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0764) Prec@1 84.000 (87.577) Prec@5 99.000 (99.127) +2022-11-14 14:55:23,601 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0761) Prec@1 91.000 (87.625) Prec@5 100.000 (99.139) +2022-11-14 14:55:23,613 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0757) Prec@1 93.000 (87.699) Prec@5 100.000 (99.151) +2022-11-14 14:55:23,624 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0375 (0.0751) Prec@1 95.000 (87.797) Prec@5 100.000 (99.162) +2022-11-14 14:55:23,636 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0754) Prec@1 84.000 (87.747) Prec@5 100.000 (99.173) +2022-11-14 14:55:23,647 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0753) Prec@1 90.000 (87.776) Prec@5 98.000 (99.158) +2022-11-14 14:55:23,659 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0753) Prec@1 87.000 (87.766) Prec@5 99.000 (99.156) +2022-11-14 14:55:23,672 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0756) Prec@1 82.000 (87.692) Prec@5 98.000 (99.141) +2022-11-14 14:55:23,683 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0757) Prec@1 86.000 (87.671) Prec@5 99.000 (99.139) +2022-11-14 14:55:23,696 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0756) Prec@1 89.000 (87.688) Prec@5 100.000 (99.150) +2022-11-14 14:55:23,707 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0759) Prec@1 85.000 (87.654) Prec@5 98.000 (99.136) +2022-11-14 14:55:23,716 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1099 (0.0763) Prec@1 83.000 (87.598) Prec@5 98.000 (99.122) +2022-11-14 14:55:23,728 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0767) Prec@1 84.000 (87.554) Prec@5 99.000 (99.120) +2022-11-14 14:55:23,740 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0763) Prec@1 94.000 (87.631) Prec@5 99.000 (99.119) +2022-11-14 14:55:23,754 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0765) Prec@1 84.000 (87.588) Prec@5 100.000 (99.129) +2022-11-14 14:55:23,768 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0767) Prec@1 85.000 (87.558) Prec@5 98.000 (99.116) +2022-11-14 14:55:23,782 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0766) Prec@1 87.000 (87.552) Prec@5 99.000 (99.115) +2022-11-14 14:55:23,795 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0763) Prec@1 93.000 (87.614) Prec@5 99.000 (99.114) +2022-11-14 14:55:23,808 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0764) Prec@1 86.000 (87.596) Prec@5 100.000 (99.124) +2022-11-14 14:55:23,819 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0764) Prec@1 88.000 (87.600) Prec@5 100.000 (99.133) +2022-11-14 14:55:23,830 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0762) Prec@1 92.000 (87.648) Prec@5 100.000 (99.143) +2022-11-14 14:55:23,841 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0760) Prec@1 88.000 (87.652) Prec@5 99.000 (99.141) +2022-11-14 14:55:23,853 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0763) Prec@1 84.000 (87.613) Prec@5 99.000 (99.140) +2022-11-14 14:55:23,864 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0764) Prec@1 86.000 (87.596) Prec@5 97.000 (99.117) +2022-11-14 14:55:23,875 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0764) Prec@1 89.000 (87.611) Prec@5 99.000 (99.116) +2022-11-14 14:55:23,886 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0762) Prec@1 91.000 (87.646) Prec@5 98.000 (99.104) +2022-11-14 14:55:23,898 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0760) Prec@1 93.000 (87.701) Prec@5 99.000 (99.103) +2022-11-14 14:55:23,910 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0760) Prec@1 84.000 (87.663) Prec@5 99.000 (99.102) +2022-11-14 14:55:23,921 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0760) Prec@1 86.000 (87.646) Prec@5 99.000 (99.101) +2022-11-14 14:55:23,933 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0760) Prec@1 88.000 (87.650) Prec@5 100.000 (99.110) +2022-11-14 14:55:23,994 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:55:24,311 Epoch: [275][0/500] Time 0.030 (0.030) Data 0.224 (0.224) Loss 0.0313 (0.0313) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:55:24,594 Epoch: [275][10/500] Time 0.024 (0.025) Data 0.002 (0.022) Loss 0.0596 (0.0455) Prec@1 88.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 14:55:24,902 Epoch: [275][20/500] Time 0.025 (0.026) Data 0.002 (0.012) Loss 0.0301 (0.0403) Prec@1 97.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 14:55:25,201 Epoch: [275][30/500] Time 0.027 (0.026) Data 0.002 (0.009) Loss 0.0634 (0.0461) Prec@1 87.000 (91.500) Prec@5 100.000 (99.750) +2022-11-14 14:55:25,507 Epoch: [275][40/500] Time 0.025 (0.026) Data 0.002 (0.007) Loss 0.0320 (0.0433) Prec@1 95.000 (92.200) Prec@5 100.000 (99.800) +2022-11-14 14:55:25,818 Epoch: [275][50/500] Time 0.029 (0.027) Data 0.002 (0.006) Loss 0.0294 (0.0410) Prec@1 95.000 (92.667) Prec@5 100.000 (99.833) +2022-11-14 14:55:26,114 Epoch: [275][60/500] Time 0.028 (0.027) Data 0.002 (0.005) Loss 0.0436 (0.0414) Prec@1 94.000 (92.857) Prec@5 98.000 (99.571) +2022-11-14 14:55:26,420 Epoch: [275][70/500] Time 0.027 (0.027) Data 0.002 (0.005) Loss 0.0324 (0.0402) Prec@1 95.000 (93.125) Prec@5 99.000 (99.500) +2022-11-14 14:55:26,726 Epoch: [275][80/500] Time 0.024 (0.027) Data 0.003 (0.005) Loss 0.0382 (0.0400) Prec@1 93.000 (93.111) Prec@5 100.000 (99.556) +2022-11-14 14:55:27,038 Epoch: [275][90/500] Time 0.033 (0.027) Data 0.002 (0.004) Loss 0.0450 (0.0405) Prec@1 89.000 (92.700) Prec@5 100.000 (99.600) +2022-11-14 14:55:27,377 Epoch: [275][100/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0372 (0.0402) Prec@1 93.000 (92.727) Prec@5 100.000 (99.636) +2022-11-14 14:55:27,880 Epoch: [275][110/500] Time 0.065 (0.029) Data 0.003 (0.004) Loss 0.0375 (0.0400) Prec@1 93.000 (92.750) Prec@5 100.000 (99.667) +2022-11-14 14:55:28,392 Epoch: [275][120/500] Time 0.043 (0.030) Data 0.002 (0.004) Loss 0.0250 (0.0388) Prec@1 96.000 (93.000) Prec@5 100.000 (99.692) +2022-11-14 14:55:28,910 Epoch: [275][130/500] Time 0.045 (0.031) Data 0.003 (0.004) Loss 0.0220 (0.0376) Prec@1 96.000 (93.214) Prec@5 100.000 (99.714) +2022-11-14 14:55:29,521 Epoch: [275][140/500] Time 0.061 (0.033) Data 0.002 (0.003) Loss 0.0468 (0.0382) Prec@1 92.000 (93.133) Prec@5 100.000 (99.733) +2022-11-14 14:55:30,007 Epoch: [275][150/500] Time 0.041 (0.034) Data 0.002 (0.003) Loss 0.0398 (0.0383) Prec@1 92.000 (93.062) Prec@5 99.000 (99.688) +2022-11-14 14:55:30,500 Epoch: [275][160/500] Time 0.053 (0.034) Data 0.002 (0.003) Loss 0.0248 (0.0375) Prec@1 96.000 (93.235) Prec@5 100.000 (99.706) +2022-11-14 14:55:31,022 Epoch: [275][170/500] Time 0.042 (0.035) Data 0.002 (0.003) Loss 0.0302 (0.0371) Prec@1 94.000 (93.278) Prec@5 100.000 (99.722) +2022-11-14 14:55:31,516 Epoch: [275][180/500] Time 0.058 (0.036) Data 0.002 (0.003) Loss 0.0371 (0.0371) Prec@1 94.000 (93.316) Prec@5 100.000 (99.737) +2022-11-14 14:55:32,007 Epoch: [275][190/500] Time 0.043 (0.036) Data 0.002 (0.003) Loss 0.0353 (0.0370) Prec@1 95.000 (93.400) Prec@5 100.000 (99.750) +2022-11-14 14:55:32,571 Epoch: [275][200/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0549 (0.0379) Prec@1 90.000 (93.238) Prec@5 100.000 (99.762) +2022-11-14 14:55:33,070 Epoch: [275][210/500] Time 0.042 (0.037) Data 0.002 (0.003) Loss 0.0149 (0.0368) Prec@1 99.000 (93.500) Prec@5 100.000 (99.773) +2022-11-14 14:55:33,575 Epoch: [275][220/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0299 (0.0365) Prec@1 96.000 (93.609) Prec@5 100.000 (99.783) +2022-11-14 14:55:34,059 Epoch: [275][230/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0401 (0.0367) Prec@1 91.000 (93.500) Prec@5 100.000 (99.792) +2022-11-14 14:55:34,626 Epoch: [275][240/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0543 (0.0374) Prec@1 91.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 14:55:35,127 Epoch: [275][250/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0572 (0.0382) Prec@1 91.000 (93.308) Prec@5 100.000 (99.808) +2022-11-14 14:55:35,648 Epoch: [275][260/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0426 (0.0383) Prec@1 94.000 (93.333) Prec@5 100.000 (99.815) +2022-11-14 14:55:36,175 Epoch: [275][270/500] Time 0.066 (0.039) Data 0.002 (0.003) Loss 0.0275 (0.0379) Prec@1 96.000 (93.429) Prec@5 100.000 (99.821) +2022-11-14 14:55:36,668 Epoch: [275][280/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0272 (0.0376) Prec@1 95.000 (93.483) Prec@5 100.000 (99.828) +2022-11-14 14:55:37,149 Epoch: [275][290/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0423 (0.0377) Prec@1 92.000 (93.433) Prec@5 100.000 (99.833) +2022-11-14 14:55:37,641 Epoch: [275][300/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0424 (0.0379) Prec@1 92.000 (93.387) Prec@5 100.000 (99.839) +2022-11-14 14:55:38,122 Epoch: [275][310/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0397 (0.0379) Prec@1 95.000 (93.438) Prec@5 100.000 (99.844) +2022-11-14 14:55:38,617 Epoch: [275][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0298 (0.0377) Prec@1 94.000 (93.455) Prec@5 100.000 (99.848) +2022-11-14 14:55:39,147 Epoch: [275][330/500] Time 0.065 (0.040) Data 0.002 (0.003) Loss 0.0260 (0.0373) Prec@1 96.000 (93.529) Prec@5 100.000 (99.853) +2022-11-14 14:55:39,708 Epoch: [275][340/500] Time 0.066 (0.041) Data 0.002 (0.003) Loss 0.0469 (0.0376) Prec@1 91.000 (93.457) Prec@5 99.000 (99.829) +2022-11-14 14:55:40,178 Epoch: [275][350/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0237 (0.0372) Prec@1 95.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 14:55:40,661 Epoch: [275][360/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0376 (0.0372) Prec@1 95.000 (93.541) Prec@5 99.000 (99.811) +2022-11-14 14:55:41,149 Epoch: [275][370/500] Time 0.044 (0.041) Data 0.002 (0.003) Loss 0.0503 (0.0376) Prec@1 91.000 (93.474) Prec@5 98.000 (99.763) +2022-11-14 14:55:41,766 Epoch: [275][380/500] Time 0.064 (0.041) Data 0.002 (0.003) Loss 0.0198 (0.0371) Prec@1 96.000 (93.538) Prec@5 100.000 (99.769) +2022-11-14 14:55:42,273 Epoch: [275][390/500] Time 0.047 (0.041) Data 0.003 (0.003) Loss 0.0358 (0.0371) Prec@1 94.000 (93.550) Prec@5 100.000 (99.775) +2022-11-14 14:55:42,813 Epoch: [275][400/500] Time 0.043 (0.041) Data 0.002 (0.002) Loss 0.0310 (0.0369) Prec@1 95.000 (93.585) Prec@5 100.000 (99.780) +2022-11-14 14:55:43,234 Epoch: [275][410/500] Time 0.041 (0.041) Data 0.002 (0.002) Loss 0.0251 (0.0367) Prec@1 95.000 (93.619) Prec@5 100.000 (99.786) +2022-11-14 14:55:43,593 Epoch: [275][420/500] Time 0.033 (0.041) Data 0.002 (0.002) Loss 0.0346 (0.0366) Prec@1 93.000 (93.605) Prec@5 100.000 (99.791) +2022-11-14 14:55:44,000 Epoch: [275][430/500] Time 0.042 (0.041) Data 0.002 (0.002) Loss 0.0384 (0.0367) Prec@1 93.000 (93.591) Prec@5 100.000 (99.795) +2022-11-14 14:55:44,346 Epoch: [275][440/500] Time 0.034 (0.041) Data 0.002 (0.002) Loss 0.0165 (0.0362) Prec@1 97.000 (93.667) Prec@5 100.000 (99.800) +2022-11-14 14:55:44,710 Epoch: [275][450/500] Time 0.031 (0.041) Data 0.002 (0.002) Loss 0.0330 (0.0361) Prec@1 95.000 (93.696) Prec@5 100.000 (99.804) +2022-11-14 14:55:45,068 Epoch: [275][460/500] Time 0.033 (0.040) Data 0.002 (0.002) Loss 0.0328 (0.0361) Prec@1 95.000 (93.723) Prec@5 99.000 (99.787) +2022-11-14 14:55:45,458 Epoch: [275][470/500] Time 0.031 (0.040) Data 0.001 (0.002) Loss 0.0416 (0.0362) Prec@1 95.000 (93.750) Prec@5 99.000 (99.771) +2022-11-14 14:55:45,847 Epoch: [275][480/500] Time 0.041 (0.040) Data 0.002 (0.002) Loss 0.0365 (0.0362) Prec@1 96.000 (93.796) Prec@5 100.000 (99.776) +2022-11-14 14:55:46,257 Epoch: [275][490/500] Time 0.037 (0.040) Data 0.002 (0.002) Loss 0.0282 (0.0360) Prec@1 95.000 (93.820) Prec@5 100.000 (99.780) +2022-11-14 14:55:46,677 Epoch: [275][499/500] Time 0.044 (0.040) Data 0.002 (0.002) Loss 0.0354 (0.0360) Prec@1 95.000 (93.843) Prec@5 100.000 (99.784) +2022-11-14 14:55:46,976 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0576 (0.0576) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 14:55:46,986 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0638) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:55:46,997 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0652) Prec@1 88.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 14:55:47,010 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0658) Prec@1 90.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 14:55:47,023 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0680) Prec@1 87.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 14:55:47,034 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0294 (0.0616) Prec@1 96.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 14:55:47,044 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0610) Prec@1 91.000 (89.857) Prec@5 99.000 (99.286) +2022-11-14 14:55:47,055 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0644) Prec@1 84.000 (89.125) Prec@5 100.000 (99.375) +2022-11-14 14:55:47,067 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0667) Prec@1 87.000 (88.889) Prec@5 100.000 (99.444) +2022-11-14 14:55:47,079 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0672) Prec@1 88.000 (88.800) Prec@5 98.000 (99.300) +2022-11-14 14:55:47,093 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0676) Prec@1 89.000 (88.818) Prec@5 100.000 (99.364) +2022-11-14 14:55:47,107 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.0711) Prec@1 82.000 (88.250) Prec@5 99.000 (99.333) +2022-11-14 14:55:47,121 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0702) Prec@1 91.000 (88.462) Prec@5 100.000 (99.385) +2022-11-14 14:55:47,134 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0695) Prec@1 90.000 (88.571) Prec@5 99.000 (99.357) +2022-11-14 14:55:47,148 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0690) Prec@1 87.000 (88.467) Prec@5 100.000 (99.400) +2022-11-14 14:55:47,161 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0694) Prec@1 88.000 (88.438) Prec@5 100.000 (99.438) +2022-11-14 14:55:47,175 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0687) Prec@1 91.000 (88.588) Prec@5 98.000 (99.353) +2022-11-14 14:55:47,188 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1147 (0.0713) Prec@1 80.000 (88.111) Prec@5 99.000 (99.333) +2022-11-14 14:55:47,202 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0711) Prec@1 87.000 (88.053) Prec@5 100.000 (99.368) +2022-11-14 14:55:47,215 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0726) Prec@1 84.000 (87.850) Prec@5 98.000 (99.300) +2022-11-14 14:55:47,228 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0729) Prec@1 87.000 (87.810) Prec@5 99.000 (99.286) +2022-11-14 14:55:47,241 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0735) Prec@1 87.000 (87.773) Prec@5 97.000 (99.182) +2022-11-14 14:55:47,253 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0747) Prec@1 84.000 (87.609) Prec@5 98.000 (99.130) +2022-11-14 14:55:47,268 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0748) Prec@1 88.000 (87.625) Prec@5 100.000 (99.167) +2022-11-14 14:55:47,284 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0754) Prec@1 86.000 (87.560) Prec@5 100.000 (99.200) +2022-11-14 14:55:47,297 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0760) Prec@1 86.000 (87.500) Prec@5 98.000 (99.154) +2022-11-14 14:55:47,310 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0754) Prec@1 91.000 (87.630) Prec@5 100.000 (99.185) +2022-11-14 14:55:47,326 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0753) Prec@1 90.000 (87.714) Prec@5 100.000 (99.214) +2022-11-14 14:55:47,340 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0759) Prec@1 86.000 (87.655) Prec@5 96.000 (99.103) +2022-11-14 14:55:47,352 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0752) Prec@1 91.000 (87.767) Prec@5 100.000 (99.133) +2022-11-14 14:55:47,366 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0748) Prec@1 88.000 (87.774) Prec@5 100.000 (99.161) +2022-11-14 14:55:47,380 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0744) Prec@1 89.000 (87.812) Prec@5 99.000 (99.156) +2022-11-14 14:55:47,394 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0738) Prec@1 91.000 (87.909) Prec@5 100.000 (99.182) +2022-11-14 14:55:47,408 Test: [33/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0741) Prec@1 86.000 (87.853) Prec@5 100.000 (99.206) +2022-11-14 14:55:47,423 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0742) Prec@1 87.000 (87.829) Prec@5 97.000 (99.143) +2022-11-14 14:55:47,437 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0735) Prec@1 91.000 (87.917) Prec@5 100.000 (99.167) +2022-11-14 14:55:47,450 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0736) Prec@1 89.000 (87.946) Prec@5 98.000 (99.135) +2022-11-14 14:55:47,464 Test: [37/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0746) Prec@1 83.000 (87.816) Prec@5 98.000 (99.105) +2022-11-14 14:55:47,477 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0741) Prec@1 92.000 (87.923) Prec@5 100.000 (99.128) +2022-11-14 14:55:47,489 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0738) Prec@1 89.000 (87.950) Prec@5 98.000 (99.100) +2022-11-14 14:55:47,505 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0742) Prec@1 83.000 (87.829) Prec@5 98.000 (99.073) +2022-11-14 14:55:47,520 Test: [41/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0739) Prec@1 90.000 (87.881) Prec@5 100.000 (99.095) +2022-11-14 14:55:47,533 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0456 (0.0733) Prec@1 92.000 (87.977) Prec@5 99.000 (99.093) +2022-11-14 14:55:47,546 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0730) Prec@1 90.000 (88.023) Prec@5 98.000 (99.068) +2022-11-14 14:55:47,561 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0728) Prec@1 89.000 (88.044) Prec@5 98.000 (99.044) +2022-11-14 14:55:47,575 Test: 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Loss 0.0890 (0.0744) Prec@1 86.000 (87.885) Prec@5 100.000 (99.096) +2022-11-14 14:55:47,672 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0741) Prec@1 88.000 (87.887) Prec@5 100.000 (99.113) +2022-11-14 14:55:47,685 Test: [53/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0743) Prec@1 85.000 (87.833) Prec@5 98.000 (99.093) +2022-11-14 14:55:47,698 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0742) Prec@1 87.000 (87.818) Prec@5 100.000 (99.109) +2022-11-14 14:55:47,712 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0742) Prec@1 90.000 (87.857) Prec@5 98.000 (99.089) +2022-11-14 14:55:47,727 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0739) Prec@1 91.000 (87.912) Prec@5 100.000 (99.105) +2022-11-14 14:55:47,742 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0738) Prec@1 91.000 (87.966) Prec@5 100.000 (99.121) +2022-11-14 14:55:47,755 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0743) Prec@1 84.000 (87.898) Prec@5 99.000 (99.119) +2022-11-14 14:55:47,770 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0744) Prec@1 87.000 (87.883) Prec@5 100.000 (99.133) +2022-11-14 14:55:47,783 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0747) Prec@1 86.000 (87.852) Prec@5 100.000 (99.148) +2022-11-14 14:55:47,797 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0750) Prec@1 86.000 (87.823) Prec@5 98.000 (99.129) +2022-11-14 14:55:47,811 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0751) Prec@1 86.000 (87.794) Prec@5 100.000 (99.143) +2022-11-14 14:55:47,825 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0481 (0.0747) Prec@1 91.000 (87.844) Prec@5 100.000 (99.156) +2022-11-14 14:55:47,839 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0749) Prec@1 88.000 (87.846) Prec@5 100.000 (99.169) +2022-11-14 14:55:47,852 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0749) Prec@1 85.000 (87.803) Prec@5 100.000 (99.182) +2022-11-14 14:55:47,865 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0506 (0.0746) Prec@1 92.000 (87.866) Prec@5 99.000 (99.179) +2022-11-14 14:55:47,879 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0746) Prec@1 88.000 (87.868) Prec@5 99.000 (99.176) +2022-11-14 14:55:47,894 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0743) Prec@1 92.000 (87.928) Prec@5 100.000 (99.188) +2022-11-14 14:55:47,908 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0748) Prec@1 84.000 (87.871) Prec@5 100.000 (99.200) +2022-11-14 14:55:47,922 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.0752) Prec@1 87.000 (87.859) Prec@5 99.000 (99.197) +2022-11-14 14:55:47,936 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0752) Prec@1 88.000 (87.861) Prec@5 100.000 (99.208) +2022-11-14 14:55:47,950 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0748) Prec@1 92.000 (87.918) Prec@5 99.000 (99.205) +2022-11-14 14:55:47,964 Test: [73/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0746) Prec@1 92.000 (87.973) Prec@5 100.000 (99.216) +2022-11-14 14:55:47,978 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0749) Prec@1 86.000 (87.947) Prec@5 98.000 (99.200) +2022-11-14 14:55:47,991 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0748) Prec@1 90.000 (87.974) Prec@5 99.000 (99.197) +2022-11-14 14:55:48,005 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0749) Prec@1 91.000 (88.013) Prec@5 100.000 (99.208) +2022-11-14 14:55:48,020 Test: [77/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0751) Prec@1 83.000 (87.949) Prec@5 98.000 (99.192) +2022-11-14 14:55:48,034 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0752) Prec@1 88.000 (87.949) Prec@5 100.000 (99.203) +2022-11-14 14:55:48,047 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0752) Prec@1 86.000 (87.925) Prec@5 100.000 (99.213) +2022-11-14 14:55:48,061 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0754) Prec@1 86.000 (87.901) Prec@5 98.000 (99.198) +2022-11-14 14:55:48,075 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0755) Prec@1 85.000 (87.866) Prec@5 99.000 (99.195) +2022-11-14 14:55:48,088 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0757) Prec@1 87.000 (87.855) Prec@5 100.000 (99.205) +2022-11-14 14:55:48,101 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0753) Prec@1 93.000 (87.917) Prec@5 99.000 (99.202) +2022-11-14 14:55:48,116 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0755) Prec@1 88.000 (87.918) Prec@5 99.000 (99.200) +2022-11-14 14:55:48,131 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0759) Prec@1 85.000 (87.884) Prec@5 97.000 (99.174) +2022-11-14 14:55:48,143 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0759) Prec@1 88.000 (87.885) Prec@5 98.000 (99.161) +2022-11-14 14:55:48,156 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0759) Prec@1 88.000 (87.886) Prec@5 99.000 (99.159) +2022-11-14 14:55:48,171 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0758) Prec@1 90.000 (87.910) Prec@5 99.000 (99.157) +2022-11-14 14:55:48,187 Test: [89/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0760) Prec@1 84.000 (87.867) Prec@5 99.000 (99.156) +2022-11-14 14:55:48,202 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0759) Prec@1 89.000 (87.879) Prec@5 100.000 (99.165) +2022-11-14 14:55:48,215 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0331 (0.0754) Prec@1 94.000 (87.946) Prec@5 100.000 (99.174) +2022-11-14 14:55:48,227 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0755) Prec@1 86.000 (87.925) Prec@5 100.000 (99.183) +2022-11-14 14:55:48,239 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0755) Prec@1 88.000 (87.926) Prec@5 98.000 (99.170) +2022-11-14 14:55:48,256 Test: [94/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0755) Prec@1 89.000 (87.937) Prec@5 99.000 (99.168) +2022-11-14 14:55:48,270 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0754) Prec@1 92.000 (87.979) Prec@5 99.000 (99.167) +2022-11-14 14:55:48,283 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0751) Prec@1 91.000 (88.010) Prec@5 99.000 (99.165) +2022-11-14 14:55:48,297 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0752) Prec@1 87.000 (88.000) Prec@5 98.000 (99.153) +2022-11-14 14:55:48,310 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1176 (0.0756) Prec@1 83.000 (87.949) Prec@5 99.000 (99.152) +2022-11-14 14:55:48,324 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0757) Prec@1 86.000 (87.930) Prec@5 99.000 (99.150) +2022-11-14 14:55:48,383 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:55:48,705 Epoch: [276][0/500] Time 0.023 (0.023) Data 0.238 (0.238) Loss 0.0300 (0.0300) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:55:48,939 Epoch: [276][10/500] Time 0.025 (0.021) Data 0.002 (0.023) Loss 0.0380 (0.0340) Prec@1 93.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:55:49,171 Epoch: [276][20/500] Time 0.021 (0.021) Data 0.002 (0.013) Loss 0.0384 (0.0354) Prec@1 95.000 (94.333) Prec@5 99.000 (99.333) +2022-11-14 14:55:49,393 Epoch: [276][30/500] Time 0.023 (0.020) Data 0.002 (0.010) Loss 0.0400 (0.0366) Prec@1 93.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 14:55:49,706 Epoch: [276][40/500] Time 0.042 (0.022) Data 0.002 (0.008) Loss 0.0255 (0.0344) Prec@1 96.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 14:55:50,000 Epoch: [276][50/500] Time 0.024 (0.023) Data 0.002 (0.007) Loss 0.0356 (0.0346) Prec@1 95.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 14:55:50,313 Epoch: [276][60/500] Time 0.030 (0.024) Data 0.002 (0.006) Loss 0.0465 (0.0363) Prec@1 93.000 (94.286) Prec@5 99.000 (99.571) +2022-11-14 14:55:50,646 Epoch: [276][70/500] Time 0.022 (0.025) Data 0.002 (0.005) Loss 0.0435 (0.0372) Prec@1 92.000 (94.000) Prec@5 100.000 (99.625) +2022-11-14 14:55:50,954 Epoch: [276][80/500] Time 0.031 (0.025) Data 0.002 (0.005) Loss 0.0379 (0.0373) Prec@1 94.000 (94.000) Prec@5 99.000 (99.556) +2022-11-14 14:55:51,243 Epoch: [276][90/500] Time 0.027 (0.025) Data 0.002 (0.005) Loss 0.0316 (0.0367) Prec@1 95.000 (94.100) Prec@5 100.000 (99.600) +2022-11-14 14:55:51,547 Epoch: [276][100/500] Time 0.025 (0.025) Data 0.002 (0.004) Loss 0.0316 (0.0362) Prec@1 93.000 (94.000) Prec@5 99.000 (99.545) +2022-11-14 14:55:51,865 Epoch: [276][110/500] Time 0.023 (0.026) Data 0.002 (0.004) Loss 0.0203 (0.0349) Prec@1 99.000 (94.417) Prec@5 100.000 (99.583) +2022-11-14 14:55:52,160 Epoch: [276][120/500] Time 0.026 (0.026) Data 0.002 (0.004) Loss 0.0621 (0.0370) Prec@1 91.000 (94.154) Prec@5 100.000 (99.615) +2022-11-14 14:55:52,533 Epoch: [276][130/500] Time 0.035 (0.026) Data 0.002 (0.004) Loss 0.0366 (0.0370) Prec@1 93.000 (94.071) Prec@5 99.000 (99.571) +2022-11-14 14:55:52,880 Epoch: [276][140/500] Time 0.037 (0.027) Data 0.002 (0.004) Loss 0.0412 (0.0372) Prec@1 93.000 (94.000) Prec@5 99.000 (99.533) +2022-11-14 14:55:53,496 Epoch: [276][150/500] Time 0.069 (0.028) Data 0.003 (0.004) Loss 0.0323 (0.0369) Prec@1 94.000 (94.000) Prec@5 100.000 (99.562) +2022-11-14 14:55:54,024 Epoch: [276][160/500] Time 0.062 (0.030) Data 0.002 (0.003) Loss 0.0402 (0.0371) Prec@1 93.000 (93.941) Prec@5 100.000 (99.588) +2022-11-14 14:55:54,521 Epoch: [276][170/500] Time 0.051 (0.030) Data 0.002 (0.003) Loss 0.0182 (0.0361) Prec@1 97.000 (94.111) Prec@5 100.000 (99.611) +2022-11-14 14:55:55,073 Epoch: [276][180/500] Time 0.059 (0.032) Data 0.002 (0.003) Loss 0.0483 (0.0367) Prec@1 93.000 (94.053) Prec@5 100.000 (99.632) +2022-11-14 14:55:55,563 Epoch: [276][190/500] Time 0.042 (0.032) Data 0.002 (0.003) Loss 0.0610 (0.0379) Prec@1 90.000 (93.850) Prec@5 99.000 (99.600) +2022-11-14 14:55:56,054 Epoch: [276][200/500] Time 0.040 (0.033) Data 0.002 (0.003) Loss 0.0366 (0.0379) Prec@1 94.000 (93.857) Prec@5 100.000 (99.619) +2022-11-14 14:55:56,645 Epoch: [276][210/500] Time 0.086 (0.034) Data 0.002 (0.003) Loss 0.0284 (0.0374) Prec@1 94.000 (93.864) Prec@5 100.000 (99.636) +2022-11-14 14:55:57,124 Epoch: [276][220/500] Time 0.050 (0.034) Data 0.002 (0.003) Loss 0.0369 (0.0374) Prec@1 94.000 (93.870) Prec@5 100.000 (99.652) +2022-11-14 14:55:57,776 Epoch: [276][230/500] Time 0.080 (0.035) Data 0.002 (0.003) Loss 0.0353 (0.0373) Prec@1 94.000 (93.875) Prec@5 100.000 (99.667) +2022-11-14 14:55:58,455 Epoch: [276][240/500] Time 0.044 (0.036) Data 0.002 (0.003) Loss 0.0302 (0.0370) Prec@1 93.000 (93.840) Prec@5 100.000 (99.680) +2022-11-14 14:55:59,224 Epoch: [276][250/500] Time 0.078 (0.037) Data 0.002 (0.003) Loss 0.0274 (0.0367) Prec@1 96.000 (93.923) Prec@5 100.000 (99.692) +2022-11-14 14:55:59,813 Epoch: [276][260/500] Time 0.074 (0.038) Data 0.002 (0.003) Loss 0.0088 (0.0356) Prec@1 99.000 (94.111) Prec@5 100.000 (99.704) +2022-11-14 14:56:00,525 Epoch: [276][270/500] Time 0.053 (0.039) Data 0.002 (0.003) Loss 0.0326 (0.0355) Prec@1 95.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 14:56:01,043 Epoch: [276][280/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0218 (0.0351) Prec@1 98.000 (94.276) Prec@5 100.000 (99.724) +2022-11-14 14:56:01,526 Epoch: [276][290/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0596 (0.0359) Prec@1 89.000 (94.100) Prec@5 100.000 (99.733) +2022-11-14 14:56:02,028 Epoch: [276][300/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0237 (0.0355) Prec@1 96.000 (94.161) Prec@5 100.000 (99.742) +2022-11-14 14:56:02,535 Epoch: [276][310/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0295 (0.0353) Prec@1 96.000 (94.219) Prec@5 100.000 (99.750) +2022-11-14 14:56:03,012 Epoch: [276][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0494 (0.0357) Prec@1 91.000 (94.121) Prec@5 100.000 (99.758) +2022-11-14 14:56:03,836 Epoch: [276][330/500] Time 0.083 (0.041) Data 0.002 (0.003) Loss 0.0202 (0.0353) Prec@1 97.000 (94.206) Prec@5 100.000 (99.765) +2022-11-14 14:56:04,478 Epoch: [276][340/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0166 (0.0347) Prec@1 97.000 (94.286) Prec@5 100.000 (99.771) +2022-11-14 14:56:04,873 Epoch: [276][350/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0589 (0.0354) Prec@1 90.000 (94.167) Prec@5 100.000 (99.778) +2022-11-14 14:56:05,250 Epoch: [276][360/500] Time 0.021 (0.041) Data 0.002 (0.003) Loss 0.0408 (0.0356) Prec@1 94.000 (94.162) Prec@5 99.000 (99.757) +2022-11-14 14:56:05,590 Epoch: [276][370/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0355 (0.0356) Prec@1 94.000 (94.158) Prec@5 100.000 (99.763) +2022-11-14 14:56:05,939 Epoch: [276][380/500] Time 0.025 (0.041) Data 0.002 (0.003) Loss 0.0313 (0.0354) Prec@1 95.000 (94.179) Prec@5 99.000 (99.744) +2022-11-14 14:56:06,306 Epoch: [276][390/500] Time 0.021 (0.040) Data 0.002 (0.003) Loss 0.0304 (0.0353) Prec@1 97.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 14:56:06,660 Epoch: [276][400/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0297 (0.0352) Prec@1 96.000 (94.293) Prec@5 100.000 (99.756) +2022-11-14 14:56:07,062 Epoch: [276][410/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.0285 (0.0350) Prec@1 97.000 (94.357) Prec@5 99.000 (99.738) +2022-11-14 14:56:07,376 Epoch: [276][420/500] Time 0.030 (0.040) Data 0.002 (0.003) Loss 0.0127 (0.0345) Prec@1 99.000 (94.465) Prec@5 99.000 (99.721) +2022-11-14 14:56:07,735 Epoch: [276][430/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0313 (0.0344) Prec@1 94.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 14:56:08,069 Epoch: [276][440/500] Time 0.029 (0.039) Data 0.002 (0.003) Loss 0.0307 (0.0343) Prec@1 94.000 (94.444) Prec@5 98.000 (99.689) +2022-11-14 14:56:08,402 Epoch: [276][450/500] Time 0.031 (0.039) Data 0.001 (0.003) Loss 0.0265 (0.0342) Prec@1 95.000 (94.457) Prec@5 100.000 (99.696) +2022-11-14 14:56:08,726 Epoch: [276][460/500] Time 0.029 (0.039) Data 0.002 (0.002) Loss 0.0189 (0.0339) Prec@1 97.000 (94.511) Prec@5 100.000 (99.702) +2022-11-14 14:56:09,078 Epoch: [276][470/500] Time 0.025 (0.039) Data 0.002 (0.002) Loss 0.0464 (0.0341) Prec@1 91.000 (94.438) Prec@5 100.000 (99.708) +2022-11-14 14:56:09,413 Epoch: [276][480/500] Time 0.035 (0.039) Data 0.002 (0.002) Loss 0.0474 (0.0344) Prec@1 92.000 (94.388) Prec@5 99.000 (99.694) +2022-11-14 14:56:09,745 Epoch: [276][490/500] Time 0.031 (0.038) Data 0.002 (0.002) Loss 0.0400 (0.0345) Prec@1 93.000 (94.360) Prec@5 100.000 (99.700) +2022-11-14 14:56:10,083 Epoch: [276][499/500] Time 0.046 (0.038) Data 0.002 (0.002) Loss 0.0274 (0.0344) Prec@1 95.000 (94.373) Prec@5 100.000 (99.706) +2022-11-14 14:56:10,364 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0533 (0.0533) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 14:56:10,372 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0599) Prec@1 90.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 14:56:10,381 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0637) Prec@1 87.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 14:56:10,393 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0706) Prec@1 84.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 14:56:10,402 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0729) Prec@1 87.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 14:56:10,409 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0703) Prec@1 91.000 (88.500) Prec@5 99.000 (99.333) +2022-11-14 14:56:10,419 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0697) Prec@1 89.000 (88.571) Prec@5 100.000 (99.429) +2022-11-14 14:56:10,431 Test: [7/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0705) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:56:10,443 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0707) Prec@1 88.000 (88.444) Prec@5 99.000 (99.444) +2022-11-14 14:56:10,451 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0720) Prec@1 87.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 14:56:10,461 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0709) Prec@1 90.000 (88.455) Prec@5 99.000 (99.364) +2022-11-14 14:56:10,473 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0725) Prec@1 87.000 (88.333) Prec@5 100.000 (99.417) +2022-11-14 14:56:10,485 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0710) Prec@1 93.000 (88.692) Prec@5 100.000 (99.462) +2022-11-14 14:56:10,495 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0713) Prec@1 86.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 14:56:10,507 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0704) Prec@1 91.000 (88.667) Prec@5 99.000 (99.467) +2022-11-14 14:56:10,516 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0706) Prec@1 88.000 (88.625) Prec@5 99.000 (99.438) +2022-11-14 14:56:10,529 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0705) Prec@1 91.000 (88.765) Prec@5 98.000 (99.353) +2022-11-14 14:56:10,542 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0728) Prec@1 84.000 (88.500) Prec@5 100.000 (99.389) +2022-11-14 14:56:10,553 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0742) Prec@1 82.000 (88.158) Prec@5 99.000 (99.368) +2022-11-14 14:56:10,563 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0758) Prec@1 83.000 (87.900) Prec@5 98.000 (99.300) +2022-11-14 14:56:10,575 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0762) Prec@1 87.000 (87.857) Prec@5 100.000 (99.333) +2022-11-14 14:56:10,586 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0766) Prec@1 87.000 (87.818) Prec@5 99.000 (99.318) +2022-11-14 14:56:10,598 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0774) Prec@1 87.000 (87.783) Prec@5 99.000 (99.304) +2022-11-14 14:56:10,610 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0768) Prec@1 90.000 (87.875) Prec@5 100.000 (99.333) +2022-11-14 14:56:10,621 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0771) Prec@1 88.000 (87.880) Prec@5 100.000 (99.360) +2022-11-14 14:56:10,634 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0771) Prec@1 89.000 (87.923) Prec@5 98.000 (99.308) +2022-11-14 14:56:10,646 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0765) Prec@1 91.000 (88.037) Prec@5 100.000 (99.333) +2022-11-14 14:56:10,657 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0761) Prec@1 92.000 (88.179) Prec@5 98.000 (99.286) +2022-11-14 14:56:10,668 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0758) Prec@1 87.000 (88.138) Prec@5 98.000 (99.241) +2022-11-14 14:56:10,680 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0765) Prec@1 83.000 (87.967) Prec@5 98.000 (99.200) +2022-11-14 14:56:10,691 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0760) Prec@1 92.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 14:56:10,703 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0756) Prec@1 90.000 (88.156) Prec@5 98.000 (99.188) +2022-11-14 14:56:10,715 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0756) Prec@1 88.000 (88.152) Prec@5 99.000 (99.182) +2022-11-14 14:56:10,726 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0762) Prec@1 85.000 (88.059) Prec@5 100.000 (99.206) +2022-11-14 14:56:10,738 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0766) Prec@1 86.000 (88.000) Prec@5 99.000 (99.200) +2022-11-14 14:56:10,750 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0764) Prec@1 91.000 (88.083) Prec@5 100.000 (99.222) +2022-11-14 14:56:10,762 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0764) Prec@1 85.000 (88.000) Prec@5 99.000 (99.216) +2022-11-14 14:56:10,772 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0772) Prec@1 83.000 (87.868) Prec@5 98.000 (99.184) +2022-11-14 14:56:10,784 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0767) Prec@1 91.000 (87.949) Prec@5 99.000 (99.179) +2022-11-14 14:56:10,796 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0762) Prec@1 92.000 (88.050) Prec@5 98.000 (99.150) +2022-11-14 14:56:10,807 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0765) Prec@1 86.000 (88.000) Prec@5 99.000 (99.146) +2022-11-14 14:56:10,819 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0763) Prec@1 90.000 (88.048) Prec@5 100.000 (99.167) +2022-11-14 14:56:10,830 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0755) Prec@1 92.000 (88.140) Prec@5 100.000 (99.186) +2022-11-14 14:56:10,843 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0753) Prec@1 89.000 (88.159) Prec@5 99.000 (99.182) +2022-11-14 14:56:10,856 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0756) Prec@1 86.000 (88.111) Prec@5 99.000 (99.178) +2022-11-14 14:56:10,868 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0763) Prec@1 83.000 (88.000) Prec@5 99.000 (99.174) +2022-11-14 14:56:10,879 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0761) Prec@1 90.000 (88.043) Prec@5 100.000 (99.191) +2022-11-14 14:56:10,890 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1114 (0.0768) Prec@1 83.000 (87.938) Prec@5 98.000 (99.167) +2022-11-14 14:56:10,903 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0762) Prec@1 93.000 (88.041) Prec@5 100.000 (99.184) +2022-11-14 14:56:10,914 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0764) Prec@1 88.000 (88.040) Prec@5 99.000 (99.180) +2022-11-14 14:56:10,925 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0762) Prec@1 86.000 (88.000) Prec@5 98.000 (99.157) +2022-11-14 14:56:10,938 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0766) Prec@1 85.000 (87.942) Prec@5 99.000 (99.154) +2022-11-14 14:56:10,949 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0767) Prec@1 84.000 (87.868) Prec@5 100.000 (99.170) +2022-11-14 14:56:10,961 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0766) Prec@1 89.000 (87.889) Prec@5 99.000 (99.167) +2022-11-14 14:56:10,974 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0767) Prec@1 86.000 (87.855) Prec@5 100.000 (99.182) +2022-11-14 14:56:10,986 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0768) Prec@1 88.000 (87.857) Prec@5 99.000 (99.179) +2022-11-14 14:56:10,999 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0764) Prec@1 91.000 (87.912) Prec@5 100.000 (99.193) +2022-11-14 14:56:11,010 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0762) Prec@1 91.000 (87.966) Prec@5 99.000 (99.190) +2022-11-14 14:56:11,023 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1274 (0.0771) Prec@1 80.000 (87.831) Prec@5 98.000 (99.169) +2022-11-14 14:56:11,035 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0768) Prec@1 90.000 (87.867) Prec@5 98.000 (99.150) +2022-11-14 14:56:11,047 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0765) Prec@1 93.000 (87.951) Prec@5 98.000 (99.131) +2022-11-14 14:56:11,058 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0764) Prec@1 89.000 (87.968) Prec@5 100.000 (99.145) +2022-11-14 14:56:11,071 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0761) Prec@1 92.000 (88.032) Prec@5 100.000 (99.159) +2022-11-14 14:56:11,083 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0757) Prec@1 92.000 (88.094) Prec@5 100.000 (99.172) +2022-11-14 14:56:11,095 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0758) Prec@1 89.000 (88.108) Prec@5 99.000 (99.169) +2022-11-14 14:56:11,105 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0755) Prec@1 91.000 (88.152) Prec@5 99.000 (99.167) +2022-11-14 14:56:11,117 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0295 (0.0748) Prec@1 95.000 (88.254) Prec@5 100.000 (99.179) +2022-11-14 14:56:11,128 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0747) Prec@1 89.000 (88.265) Prec@5 100.000 (99.191) +2022-11-14 14:56:11,141 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0748) Prec@1 88.000 (88.261) Prec@5 99.000 (99.188) +2022-11-14 14:56:11,153 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0749) Prec@1 86.000 (88.229) Prec@5 100.000 (99.200) +2022-11-14 14:56:11,165 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0750) Prec@1 89.000 (88.239) Prec@5 98.000 (99.183) +2022-11-14 14:56:11,175 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0750) Prec@1 86.000 (88.208) Prec@5 100.000 (99.194) +2022-11-14 14:56:11,187 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0747) Prec@1 90.000 (88.233) Prec@5 100.000 (99.205) +2022-11-14 14:56:11,199 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0744) Prec@1 91.000 (88.270) Prec@5 99.000 (99.203) +2022-11-14 14:56:11,209 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0750) Prec@1 81.000 (88.173) Prec@5 100.000 (99.213) +2022-11-14 14:56:11,222 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0747) Prec@1 87.000 (88.158) Prec@5 98.000 (99.197) +2022-11-14 14:56:11,233 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0750) Prec@1 84.000 (88.104) Prec@5 98.000 (99.182) +2022-11-14 14:56:11,244 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0752) Prec@1 87.000 (88.090) Prec@5 95.000 (99.128) +2022-11-14 14:56:11,256 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0750) Prec@1 90.000 (88.114) Prec@5 100.000 (99.139) +2022-11-14 14:56:11,270 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0751) Prec@1 88.000 (88.112) Prec@5 100.000 (99.150) +2022-11-14 14:56:11,281 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0753) Prec@1 86.000 (88.086) Prec@5 98.000 (99.136) +2022-11-14 14:56:11,294 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0753) Prec@1 88.000 (88.085) Prec@5 99.000 (99.134) +2022-11-14 14:56:11,306 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0756) Prec@1 83.000 (88.024) Prec@5 99.000 (99.133) +2022-11-14 14:56:11,318 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0754) Prec@1 88.000 (88.024) Prec@5 99.000 (99.131) +2022-11-14 14:56:11,329 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0756) Prec@1 84.000 (87.976) Prec@5 98.000 (99.118) +2022-11-14 14:56:11,342 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0760) Prec@1 83.000 (87.919) Prec@5 99.000 (99.116) +2022-11-14 14:56:11,354 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0761) Prec@1 87.000 (87.908) Prec@5 100.000 (99.126) +2022-11-14 14:56:11,365 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0761) Prec@1 89.000 (87.920) Prec@5 98.000 (99.114) +2022-11-14 14:56:11,376 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0759) Prec@1 88.000 (87.921) Prec@5 98.000 (99.101) +2022-11-14 14:56:11,388 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0757) Prec@1 92.000 (87.967) Prec@5 100.000 (99.111) +2022-11-14 14:56:11,400 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0757) Prec@1 88.000 (87.967) Prec@5 100.000 (99.121) +2022-11-14 14:56:11,411 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0755) Prec@1 91.000 (88.000) Prec@5 98.000 (99.109) +2022-11-14 14:56:11,424 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 90.000 (88.022) Prec@5 100.000 (99.118) +2022-11-14 14:56:11,436 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0754) Prec@1 88.000 (88.021) Prec@5 100.000 (99.128) +2022-11-14 14:56:11,448 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0754) Prec@1 87.000 (88.011) Prec@5 99.000 (99.126) +2022-11-14 14:56:11,461 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0752) Prec@1 93.000 (88.062) Prec@5 100.000 (99.135) +2022-11-14 14:56:11,473 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0749) Prec@1 91.000 (88.093) Prec@5 99.000 (99.134) +2022-11-14 14:56:11,485 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0750) Prec@1 87.000 (88.082) Prec@5 99.000 (99.133) +2022-11-14 14:56:11,496 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0753) Prec@1 85.000 (88.051) Prec@5 99.000 (99.131) +2022-11-14 14:56:11,509 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0751) Prec@1 90.000 (88.070) Prec@5 99.000 (99.130) +2022-11-14 14:56:11,567 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:56:11,891 Epoch: [277][0/500] Time 0.033 (0.033) Data 0.233 (0.233) Loss 0.0366 (0.0366) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 14:56:12,122 Epoch: [277][10/500] Time 0.018 (0.021) Data 0.002 (0.023) Loss 0.0492 (0.0429) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 14:56:12,350 Epoch: [277][20/500] Time 0.023 (0.021) Data 0.002 (0.013) Loss 0.0186 (0.0348) Prec@1 98.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 14:56:12,736 Epoch: [277][30/500] Time 0.043 (0.025) Data 0.002 (0.009) Loss 0.0415 (0.0365) Prec@1 91.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 14:56:13,200 Epoch: [277][40/500] Time 0.046 (0.029) Data 0.002 (0.008) Loss 0.0365 (0.0365) Prec@1 97.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 14:56:13,668 Epoch: [277][50/500] Time 0.043 (0.031) Data 0.002 (0.006) Loss 0.0449 (0.0379) Prec@1 93.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 14:56:14,132 Epoch: [277][60/500] Time 0.045 (0.033) Data 0.001 (0.006) Loss 0.0328 (0.0371) Prec@1 95.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 14:56:14,607 Epoch: [277][70/500] Time 0.043 (0.034) Data 0.002 (0.005) Loss 0.0398 (0.0375) Prec@1 95.000 (94.625) Prec@5 99.000 (99.750) +2022-11-14 14:56:15,075 Epoch: [277][80/500] Time 0.044 (0.035) Data 0.002 (0.005) Loss 0.0367 (0.0374) Prec@1 94.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 14:56:15,562 Epoch: [277][90/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.0369 (0.0373) Prec@1 94.000 (94.500) Prec@5 100.000 (99.800) +2022-11-14 14:56:16,070 Epoch: [277][100/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0306 (0.0367) Prec@1 95.000 (94.545) Prec@5 99.000 (99.727) +2022-11-14 14:56:16,546 Epoch: [277][110/500] Time 0.039 (0.037) Data 0.002 (0.004) Loss 0.0560 (0.0383) Prec@1 91.000 (94.250) Prec@5 99.000 (99.667) +2022-11-14 14:56:17,016 Epoch: [277][120/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0202 (0.0369) Prec@1 98.000 (94.538) Prec@5 100.000 (99.692) +2022-11-14 14:56:17,493 Epoch: [277][130/500] Time 0.058 (0.038) Data 0.002 (0.004) Loss 0.0351 (0.0368) Prec@1 93.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 14:56:18,076 Epoch: [277][140/500] Time 0.039 (0.039) Data 0.002 (0.004) Loss 0.0231 (0.0359) Prec@1 96.000 (94.533) Prec@5 100.000 (99.733) +2022-11-14 14:56:18,646 Epoch: [277][150/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0536 (0.0370) Prec@1 90.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 14:56:19,108 Epoch: [277][160/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0197 (0.0360) Prec@1 96.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 14:56:19,705 Epoch: [277][170/500] Time 0.053 (0.041) Data 0.002 (0.003) Loss 0.0387 (0.0361) Prec@1 95.000 (94.389) Prec@5 99.000 (99.722) +2022-11-14 14:56:20,208 Epoch: [277][180/500] Time 0.051 (0.041) Data 0.002 (0.003) Loss 0.0164 (0.0351) Prec@1 97.000 (94.526) Prec@5 100.000 (99.737) +2022-11-14 14:56:20,738 Epoch: [277][190/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0238 (0.0345) Prec@1 96.000 (94.600) Prec@5 100.000 (99.750) +2022-11-14 14:56:21,209 Epoch: [277][200/500] Time 0.043 (0.041) Data 0.001 (0.003) Loss 0.0362 (0.0346) Prec@1 94.000 (94.571) Prec@5 100.000 (99.762) +2022-11-14 14:56:21,765 Epoch: [277][210/500] Time 0.058 (0.042) Data 0.002 (0.003) Loss 0.0331 (0.0345) Prec@1 93.000 (94.500) Prec@5 100.000 (99.773) +2022-11-14 14:56:22,248 Epoch: [277][220/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0365 (0.0346) Prec@1 94.000 (94.478) Prec@5 100.000 (99.783) +2022-11-14 14:56:22,735 Epoch: [277][230/500] Time 0.043 (0.042) Data 0.003 (0.003) Loss 0.0478 (0.0352) Prec@1 92.000 (94.375) Prec@5 100.000 (99.792) +2022-11-14 14:56:23,205 Epoch: [277][240/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0211 (0.0346) Prec@1 96.000 (94.440) Prec@5 100.000 (99.800) +2022-11-14 14:56:23,782 Epoch: [277][250/500] Time 0.076 (0.042) Data 0.002 (0.003) Loss 0.0478 (0.0351) Prec@1 90.000 (94.269) Prec@5 100.000 (99.808) +2022-11-14 14:56:24,439 Epoch: [277][260/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0374 (0.0352) Prec@1 94.000 (94.259) Prec@5 100.000 (99.815) +2022-11-14 14:56:25,091 Epoch: [277][270/500] Time 0.067 (0.044) Data 0.002 (0.003) Loss 0.0324 (0.0351) Prec@1 96.000 (94.321) Prec@5 100.000 (99.821) +2022-11-14 14:56:25,618 Epoch: [277][280/500] Time 0.068 (0.044) Data 0.002 (0.003) Loss 0.0442 (0.0354) Prec@1 91.000 (94.207) Prec@5 99.000 (99.793) +2022-11-14 14:56:26,186 Epoch: [277][290/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0281 (0.0352) Prec@1 95.000 (94.233) Prec@5 100.000 (99.800) +2022-11-14 14:56:26,742 Epoch: [277][300/500] Time 0.069 (0.044) Data 0.002 (0.003) Loss 0.0326 (0.0351) Prec@1 95.000 (94.258) Prec@5 100.000 (99.806) +2022-11-14 14:56:27,284 Epoch: [277][310/500] Time 0.076 (0.044) Data 0.002 (0.003) Loss 0.0308 (0.0350) Prec@1 95.000 (94.281) Prec@5 100.000 (99.812) +2022-11-14 14:56:27,867 Epoch: [277][320/500] Time 0.075 (0.044) Data 0.002 (0.003) Loss 0.0143 (0.0343) Prec@1 100.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 14:56:28,366 Epoch: [277][330/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0576 (0.0350) Prec@1 90.000 (94.324) Prec@5 100.000 (99.824) +2022-11-14 14:56:28,919 Epoch: [277][340/500] Time 0.063 (0.045) Data 0.002 (0.003) Loss 0.0396 (0.0351) Prec@1 91.000 (94.229) Prec@5 100.000 (99.829) +2022-11-14 14:56:29,476 Epoch: [277][350/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0259 (0.0349) Prec@1 95.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 14:56:30,048 Epoch: [277][360/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0493 (0.0353) Prec@1 91.000 (94.162) Prec@5 100.000 (99.838) +2022-11-14 14:56:30,581 Epoch: [277][370/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0169 (0.0348) Prec@1 98.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 14:56:31,108 Epoch: [277][380/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0366 (0.0348) Prec@1 95.000 (94.282) Prec@5 100.000 (99.846) +2022-11-14 14:56:31,675 Epoch: [277][390/500] Time 0.056 (0.045) Data 0.003 (0.003) Loss 0.0453 (0.0351) Prec@1 96.000 (94.325) Prec@5 100.000 (99.850) +2022-11-14 14:56:32,285 Epoch: [277][400/500] Time 0.037 (0.045) Data 0.002 (0.003) Loss 0.0271 (0.0349) Prec@1 95.000 (94.341) Prec@5 100.000 (99.854) +2022-11-14 14:56:32,947 Epoch: [277][410/500] Time 0.066 (0.046) Data 0.002 (0.002) Loss 0.0327 (0.0349) Prec@1 95.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 14:56:33,539 Epoch: [277][420/500] Time 0.063 (0.046) Data 0.002 (0.002) Loss 0.0339 (0.0348) Prec@1 95.000 (94.372) Prec@5 100.000 (99.860) +2022-11-14 14:56:34,101 Epoch: [277][430/500] Time 0.043 (0.046) Data 0.002 (0.002) Loss 0.0384 (0.0349) Prec@1 92.000 (94.318) Prec@5 100.000 (99.864) +2022-11-14 14:56:34,785 Epoch: [277][440/500] Time 0.077 (0.046) Data 0.002 (0.002) Loss 0.0211 (0.0346) Prec@1 96.000 (94.356) Prec@5 100.000 (99.867) +2022-11-14 14:56:35,336 Epoch: [277][450/500] Time 0.042 (0.046) Data 0.002 (0.002) Loss 0.0608 (0.0352) Prec@1 90.000 (94.261) Prec@5 100.000 (99.870) +2022-11-14 14:56:35,825 Epoch: [277][460/500] Time 0.045 (0.046) Data 0.002 (0.002) Loss 0.0355 (0.0352) Prec@1 96.000 (94.298) Prec@5 100.000 (99.872) +2022-11-14 14:56:36,300 Epoch: [277][470/500] Time 0.043 (0.046) Data 0.002 (0.002) Loss 0.0452 (0.0354) Prec@1 93.000 (94.271) Prec@5 99.000 (99.854) +2022-11-14 14:56:36,787 Epoch: [277][480/500] Time 0.044 (0.046) Data 0.002 (0.002) Loss 0.0358 (0.0354) Prec@1 95.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 14:56:37,266 Epoch: [277][490/500] Time 0.044 (0.046) Data 0.002 (0.002) Loss 0.0280 (0.0352) Prec@1 97.000 (94.340) Prec@5 100.000 (99.860) +2022-11-14 14:56:37,708 Epoch: [277][499/500] Time 0.051 (0.046) Data 0.002 (0.002) Loss 0.0451 (0.0354) Prec@1 94.000 (94.333) Prec@5 100.000 (99.863) +2022-11-14 14:56:37,983 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0782 (0.0782) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:56:37,991 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0786) Prec@1 88.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 14:56:38,000 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0785) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 14:56:38,014 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0753) Prec@1 91.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 14:56:38,024 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0752) Prec@1 86.000 (87.600) Prec@5 99.000 (99.800) +2022-11-14 14:56:38,034 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0711) Prec@1 93.000 (88.500) Prec@5 100.000 (99.833) +2022-11-14 14:56:38,046 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0688) Prec@1 91.000 (88.857) Prec@5 100.000 (99.857) +2022-11-14 14:56:38,058 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0689) Prec@1 88.000 (88.750) Prec@5 100.000 (99.875) +2022-11-14 14:56:38,067 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0714) Prec@1 86.000 (88.444) Prec@5 99.000 (99.778) +2022-11-14 14:56:38,074 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0720) Prec@1 87.000 (88.300) Prec@5 97.000 (99.500) +2022-11-14 14:56:38,084 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0702) Prec@1 92.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 14:56:38,093 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0726) Prec@1 82.000 (88.083) Prec@5 100.000 (99.583) +2022-11-14 14:56:38,104 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0720) Prec@1 89.000 (88.154) Prec@5 99.000 (99.538) +2022-11-14 14:56:38,113 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0721) Prec@1 90.000 (88.286) Prec@5 99.000 (99.500) +2022-11-14 14:56:38,124 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0715) Prec@1 87.000 (88.200) Prec@5 100.000 (99.533) +2022-11-14 14:56:38,133 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0716) Prec@1 89.000 (88.250) Prec@5 98.000 (99.438) +2022-11-14 14:56:38,144 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0706) Prec@1 92.000 (88.471) Prec@5 98.000 (99.353) +2022-11-14 14:56:38,153 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0730) Prec@1 84.000 (88.222) Prec@5 99.000 (99.333) +2022-11-14 14:56:38,163 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0723) Prec@1 89.000 (88.263) Prec@5 99.000 (99.316) +2022-11-14 14:56:38,172 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0728) Prec@1 87.000 (88.200) Prec@5 97.000 (99.200) +2022-11-14 14:56:38,182 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0730) Prec@1 89.000 (88.238) Prec@5 100.000 (99.238) +2022-11-14 14:56:38,193 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0738) Prec@1 87.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 14:56:38,202 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0743) Prec@1 86.000 (88.087) Prec@5 99.000 (99.261) +2022-11-14 14:56:38,212 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0743) Prec@1 89.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 14:56:38,224 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0749) Prec@1 86.000 (88.040) Prec@5 99.000 (99.240) +2022-11-14 14:56:38,235 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0759) Prec@1 83.000 (87.846) Prec@5 98.000 (99.192) +2022-11-14 14:56:38,245 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0755) Prec@1 91.000 (87.963) Prec@5 100.000 (99.222) +2022-11-14 14:56:38,255 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0751) Prec@1 90.000 (88.036) Prec@5 100.000 (99.250) +2022-11-14 14:56:38,265 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0750) Prec@1 89.000 (88.069) Prec@5 100.000 (99.276) +2022-11-14 14:56:38,276 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0749) Prec@1 86.000 (88.000) Prec@5 100.000 (99.300) +2022-11-14 14:56:38,285 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0745) Prec@1 88.000 (88.000) Prec@5 100.000 (99.323) +2022-11-14 14:56:38,295 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0746) Prec@1 87.000 (87.969) Prec@5 100.000 (99.344) +2022-11-14 14:56:38,306 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0742) Prec@1 91.000 (88.061) Prec@5 100.000 (99.364) +2022-11-14 14:56:38,315 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0748) Prec@1 83.000 (87.912) Prec@5 100.000 (99.382) +2022-11-14 14:56:38,325 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0746) Prec@1 90.000 (87.971) Prec@5 98.000 (99.343) +2022-11-14 14:56:38,334 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0745) Prec@1 88.000 (87.972) Prec@5 100.000 (99.361) +2022-11-14 14:56:38,345 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0743) Prec@1 86.000 (87.919) Prec@5 99.000 (99.351) +2022-11-14 14:56:38,356 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0749) Prec@1 82.000 (87.763) Prec@5 99.000 (99.342) +2022-11-14 14:56:38,368 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0745) Prec@1 90.000 (87.821) Prec@5 100.000 (99.359) +2022-11-14 14:56:38,379 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0742) Prec@1 90.000 (87.875) Prec@5 98.000 (99.325) +2022-11-14 14:56:38,393 Test: [40/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.1096 (0.0751) Prec@1 83.000 (87.756) Prec@5 99.000 (99.317) +2022-11-14 14:56:38,405 Test: [41/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0750) Prec@1 89.000 (87.786) Prec@5 97.000 (99.262) +2022-11-14 14:56:38,416 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0742) Prec@1 93.000 (87.907) Prec@5 100.000 (99.279) +2022-11-14 14:56:38,426 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0742) Prec@1 90.000 (87.955) Prec@5 98.000 (99.250) +2022-11-14 14:56:38,437 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0740) Prec@1 87.000 (87.933) Prec@5 99.000 (99.244) +2022-11-14 14:56:38,448 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0744) Prec@1 84.000 (87.848) Prec@5 99.000 (99.239) +2022-11-14 14:56:38,458 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0744) Prec@1 87.000 (87.830) Prec@5 100.000 (99.255) +2022-11-14 14:56:38,469 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0747) Prec@1 85.000 (87.771) Prec@5 98.000 (99.229) +2022-11-14 14:56:38,480 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0743) Prec@1 91.000 (87.837) Prec@5 98.000 (99.204) +2022-11-14 14:56:38,489 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0749) Prec@1 85.000 (87.780) Prec@5 99.000 (99.200) +2022-11-14 14:56:38,498 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0748) Prec@1 87.000 (87.765) Prec@5 100.000 (99.216) +2022-11-14 14:56:38,508 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0748) Prec@1 89.000 (87.788) Prec@5 98.000 (99.192) +2022-11-14 14:56:38,518 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0754) Prec@1 83.000 (87.698) Prec@5 100.000 (99.208) +2022-11-14 14:56:38,530 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0756) Prec@1 87.000 (87.685) Prec@5 97.000 (99.167) +2022-11-14 14:56:38,543 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0759) Prec@1 87.000 (87.673) Prec@5 100.000 (99.182) +2022-11-14 14:56:38,555 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0757) Prec@1 90.000 (87.714) Prec@5 99.000 (99.179) +2022-11-14 14:56:38,566 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0757) Prec@1 88.000 (87.719) Prec@5 100.000 (99.193) +2022-11-14 14:56:38,577 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0756) Prec@1 89.000 (87.741) Prec@5 99.000 (99.190) +2022-11-14 14:56:38,588 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0760) Prec@1 83.000 (87.661) Prec@5 100.000 (99.203) +2022-11-14 14:56:38,600 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0759) Prec@1 88.000 (87.667) Prec@5 100.000 (99.217) +2022-11-14 14:56:38,611 Test: [60/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0758) Prec@1 88.000 (87.672) Prec@5 99.000 (99.213) +2022-11-14 14:56:38,622 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0758) Prec@1 87.000 (87.661) Prec@5 100.000 (99.226) +2022-11-14 14:56:38,633 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0757) Prec@1 86.000 (87.635) Prec@5 100.000 (99.238) +2022-11-14 14:56:38,644 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0752) Prec@1 94.000 (87.734) Prec@5 100.000 (99.250) +2022-11-14 14:56:38,654 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0755) Prec@1 86.000 (87.708) Prec@5 99.000 (99.246) +2022-11-14 14:56:38,665 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0757) Prec@1 84.000 (87.652) Prec@5 98.000 (99.227) +2022-11-14 14:56:38,675 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0753) Prec@1 93.000 (87.731) Prec@5 99.000 (99.224) +2022-11-14 14:56:38,686 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0754) Prec@1 87.000 (87.721) Prec@5 97.000 (99.191) +2022-11-14 14:56:38,697 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0752) Prec@1 90.000 (87.754) Prec@5 99.000 (99.188) +2022-11-14 14:56:38,709 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0751) Prec@1 91.000 (87.800) Prec@5 99.000 (99.186) +2022-11-14 14:56:38,719 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0754) Prec@1 86.000 (87.775) Prec@5 98.000 (99.169) +2022-11-14 14:56:38,731 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0753) Prec@1 88.000 (87.778) Prec@5 100.000 (99.181) +2022-11-14 14:56:38,741 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0751) Prec@1 92.000 (87.836) Prec@5 99.000 (99.178) +2022-11-14 14:56:38,751 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0452 (0.0747) Prec@1 93.000 (87.905) Prec@5 100.000 (99.189) +2022-11-14 14:56:38,762 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.0752) Prec@1 79.000 (87.787) Prec@5 99.000 (99.187) +2022-11-14 14:56:38,771 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0749) Prec@1 91.000 (87.829) Prec@5 99.000 (99.184) +2022-11-14 14:56:38,782 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0748) Prec@1 88.000 (87.831) Prec@5 99.000 (99.182) +2022-11-14 14:56:38,793 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0751) Prec@1 85.000 (87.795) Prec@5 96.000 (99.141) +2022-11-14 14:56:38,804 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0754) Prec@1 84.000 (87.747) Prec@5 99.000 (99.139) +2022-11-14 14:56:38,814 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0752) Prec@1 90.000 (87.775) Prec@5 100.000 (99.150) +2022-11-14 14:56:38,825 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0755) Prec@1 86.000 (87.753) Prec@5 98.000 (99.136) +2022-11-14 14:56:38,835 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0756) Prec@1 86.000 (87.732) Prec@5 99.000 (99.134) +2022-11-14 14:56:38,846 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0758) Prec@1 87.000 (87.723) Prec@5 100.000 (99.145) +2022-11-14 14:56:38,855 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0755) Prec@1 90.000 (87.750) Prec@5 100.000 (99.155) +2022-11-14 14:56:38,866 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0756) Prec@1 90.000 (87.776) Prec@5 99.000 (99.153) +2022-11-14 14:56:38,876 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0758) Prec@1 85.000 (87.744) Prec@5 100.000 (99.163) +2022-11-14 14:56:38,887 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0757) Prec@1 90.000 (87.770) Prec@5 100.000 (99.172) +2022-11-14 14:56:38,896 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0757) Prec@1 89.000 (87.784) Prec@5 99.000 (99.170) +2022-11-14 14:56:38,907 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0757) Prec@1 87.000 (87.775) Prec@5 98.000 (99.157) +2022-11-14 14:56:38,916 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0761) Prec@1 83.000 (87.722) Prec@5 99.000 (99.156) +2022-11-14 14:56:38,926 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0759) Prec@1 90.000 (87.747) Prec@5 100.000 (99.165) +2022-11-14 14:56:38,937 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0759) Prec@1 88.000 (87.750) Prec@5 100.000 (99.174) +2022-11-14 14:56:38,947 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0760) Prec@1 87.000 (87.742) Prec@5 99.000 (99.172) +2022-11-14 14:56:38,958 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0759) Prec@1 88.000 (87.745) Prec@5 99.000 (99.170) +2022-11-14 14:56:38,967 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0761) Prec@1 85.000 (87.716) Prec@5 99.000 (99.168) +2022-11-14 14:56:38,978 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0760) Prec@1 89.000 (87.729) Prec@5 98.000 (99.156) +2022-11-14 14:56:38,988 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0757) Prec@1 94.000 (87.794) Prec@5 99.000 (99.155) +2022-11-14 14:56:38,998 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0758) Prec@1 87.000 (87.786) Prec@5 97.000 (99.133) +2022-11-14 14:56:39,007 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0760) Prec@1 86.000 (87.768) Prec@5 98.000 (99.121) +2022-11-14 14:56:39,017 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0760) Prec@1 91.000 (87.800) Prec@5 100.000 (99.130) +2022-11-14 14:56:39,090 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 14:56:39,418 Epoch: [278][0/500] Time 0.025 (0.025) Data 0.239 (0.239) Loss 0.0335 (0.0335) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 14:56:39,635 Epoch: [278][10/500] Time 0.019 (0.020) Data 0.001 (0.023) Loss 0.0460 (0.0397) Prec@1 92.000 (93.500) Prec@5 100.000 (99.500) +2022-11-14 14:56:39,848 Epoch: [278][20/500] Time 0.019 (0.019) Data 0.002 (0.013) Loss 0.0195 (0.0330) Prec@1 97.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 14:56:40,062 Epoch: [278][30/500] Time 0.023 (0.019) Data 0.002 (0.009) Loss 0.0244 (0.0308) Prec@1 95.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 14:56:40,363 Epoch: [278][40/500] Time 0.031 (0.021) Data 0.001 (0.008) Loss 0.0175 (0.0282) Prec@1 97.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 14:56:40,733 Epoch: [278][50/500] Time 0.032 (0.023) Data 0.002 (0.006) Loss 0.0313 (0.0287) Prec@1 95.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 14:56:41,102 Epoch: [278][60/500] Time 0.035 (0.025) Data 0.002 (0.006) Loss 0.0171 (0.0270) Prec@1 98.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 14:56:41,471 Epoch: [278][70/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.0414 (0.0288) Prec@1 94.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 14:56:41,833 Epoch: [278][80/500] Time 0.033 (0.027) Data 0.002 (0.005) Loss 0.0424 (0.0303) Prec@1 92.000 (95.000) Prec@5 99.000 (99.778) +2022-11-14 14:56:42,202 Epoch: [278][90/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0293 (0.0302) Prec@1 97.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 14:56:42,572 Epoch: [278][100/500] Time 0.036 (0.028) Data 0.002 (0.004) Loss 0.0111 (0.0285) Prec@1 99.000 (95.545) Prec@5 100.000 (99.818) +2022-11-14 14:56:42,948 Epoch: [278][110/500] Time 0.037 (0.028) Data 0.002 (0.004) Loss 0.0318 (0.0288) Prec@1 96.000 (95.583) Prec@5 99.000 (99.750) +2022-11-14 14:56:43,323 Epoch: [278][120/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0282 (0.0287) Prec@1 96.000 (95.615) Prec@5 100.000 (99.769) +2022-11-14 14:56:43,696 Epoch: [278][130/500] Time 0.033 (0.029) Data 0.002 (0.004) Loss 0.0284 (0.0287) Prec@1 95.000 (95.571) Prec@5 100.000 (99.786) +2022-11-14 15:45:36,455 Loading optimizer checkpoint +2022-11-14 15:45:42,708 Epoch: [254][0/500] Time 6.136 (6.136) Data 0.107 (0.107) Loss 0.0244 (0.0244) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:45:45,515 Epoch: [254][10/500] Time 0.025 (0.811) Data 0.002 (0.011) Loss 0.0214 (0.0229) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:45:45,728 Epoch: [254][20/500] Time 0.019 (0.434) Data 0.001 (0.006) Loss 0.0283 (0.0247) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 15:45:45,940 Epoch: [254][30/500] Time 0.019 (0.300) Data 0.001 (0.005) Loss 0.0319 (0.0265) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:45:46,159 Epoch: [254][40/500] Time 0.019 (0.232) Data 0.001 (0.004) Loss 0.0164 (0.0245) Prec@1 98.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 15:45:46,349 Epoch: [254][50/500] Time 0.017 (0.189) Data 0.001 (0.003) Loss 0.0248 (0.0245) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 15:45:46,536 Epoch: [254][60/500] Time 0.019 (0.161) Data 0.001 (0.003) Loss 0.0314 (0.0255) Prec@1 96.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 15:45:46,722 Epoch: [254][70/500] Time 0.016 (0.141) Data 0.001 (0.003) Loss 0.0160 (0.0243) Prec@1 97.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 15:45:46,903 Epoch: [254][80/500] Time 0.016 (0.125) Data 0.001 (0.003) Loss 0.0298 (0.0249) Prec@1 93.000 (95.556) Prec@5 100.000 (100.000) +2022-11-14 15:45:47,085 Epoch: [254][90/500] Time 0.015 (0.113) Data 0.001 (0.003) Loss 0.0525 (0.0277) Prec@1 92.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 15:45:47,264 Epoch: [254][100/500] Time 0.015 (0.104) Data 0.001 (0.002) Loss 0.0511 (0.0298) Prec@1 91.000 (94.818) Prec@5 100.000 (100.000) +2022-11-14 15:45:47,449 Epoch: [254][110/500] Time 0.017 (0.096) Data 0.001 (0.002) Loss 0.0419 (0.0308) Prec@1 94.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 15:45:47,632 Epoch: [254][120/500] Time 0.018 (0.089) Data 0.001 (0.002) Loss 0.0316 (0.0309) Prec@1 95.000 (94.769) Prec@5 99.000 (99.923) +2022-11-14 15:45:47,818 Epoch: [254][130/500] Time 0.014 (0.084) Data 0.001 (0.002) Loss 0.0228 (0.0303) Prec@1 96.000 (94.857) Prec@5 100.000 (99.929) +2022-11-14 15:45:48,006 Epoch: [254][140/500] Time 0.016 (0.079) Data 0.001 (0.002) Loss 0.0338 (0.0305) Prec@1 94.000 (94.800) Prec@5 100.000 (99.933) +2022-11-14 15:45:48,191 Epoch: [254][150/500] Time 0.017 (0.075) Data 0.001 (0.002) Loss 0.0562 (0.0321) Prec@1 91.000 (94.562) Prec@5 99.000 (99.875) +2022-11-14 15:45:48,376 Epoch: [254][160/500] Time 0.015 (0.071) Data 0.001 (0.002) Loss 0.0409 (0.0327) Prec@1 95.000 (94.588) Prec@5 100.000 (99.882) +2022-11-14 15:45:48,558 Epoch: [254][170/500] Time 0.016 (0.068) Data 0.001 (0.002) Loss 0.0285 (0.0324) Prec@1 94.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 15:45:48,750 Epoch: [254][180/500] Time 0.017 (0.065) Data 0.001 (0.002) Loss 0.0216 (0.0319) Prec@1 96.000 (94.632) Prec@5 100.000 (99.895) +2022-11-14 15:45:48,936 Epoch: [254][190/500] Time 0.016 (0.063) Data 0.002 (0.002) Loss 0.0312 (0.0318) Prec@1 94.000 (94.600) Prec@5 99.000 (99.850) +2022-11-14 15:45:49,124 Epoch: [254][200/500] Time 0.016 (0.060) Data 0.001 (0.002) Loss 0.0264 (0.0316) Prec@1 96.000 (94.667) Prec@5 100.000 (99.857) +2022-11-14 15:45:49,308 Epoch: [254][210/500] Time 0.017 (0.058) Data 0.001 (0.002) Loss 0.0340 (0.0317) Prec@1 95.000 (94.682) Prec@5 100.000 (99.864) +2022-11-14 15:45:49,488 Epoch: [254][220/500] Time 0.017 (0.056) Data 0.001 (0.002) Loss 0.0367 (0.0319) Prec@1 95.000 (94.696) Prec@5 100.000 (99.870) +2022-11-14 15:45:49,681 Epoch: [254][230/500] Time 0.016 (0.055) Data 0.001 (0.002) Loss 0.0493 (0.0326) Prec@1 90.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 15:45:49,871 Epoch: [254][240/500] Time 0.018 (0.053) Data 0.002 (0.002) Loss 0.0385 (0.0329) Prec@1 94.000 (94.480) Prec@5 100.000 (99.880) +2022-11-14 15:45:50,056 Epoch: [254][250/500] Time 0.015 (0.052) Data 0.001 (0.002) Loss 0.0449 (0.0333) Prec@1 92.000 (94.385) Prec@5 100.000 (99.885) +2022-11-14 15:45:50,240 Epoch: [254][260/500] Time 0.017 (0.050) Data 0.001 (0.002) Loss 0.0210 (0.0329) Prec@1 96.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 15:45:50,423 Epoch: [254][270/500] Time 0.015 (0.049) Data 0.001 (0.002) Loss 0.0454 (0.0333) Prec@1 93.000 (94.393) Prec@5 99.000 (99.857) +2022-11-14 15:45:50,608 Epoch: [254][280/500] Time 0.018 (0.048) Data 0.001 (0.002) Loss 0.0287 (0.0332) Prec@1 94.000 (94.379) Prec@5 99.000 (99.828) +2022-11-14 15:45:50,795 Epoch: [254][290/500] Time 0.016 (0.047) Data 0.001 (0.002) Loss 0.0582 (0.0340) Prec@1 90.000 (94.233) Prec@5 100.000 (99.833) +2022-11-14 15:45:50,976 Epoch: [254][300/500] Time 0.018 (0.046) Data 0.001 (0.002) Loss 0.0332 (0.0340) Prec@1 95.000 (94.258) Prec@5 100.000 (99.839) +2022-11-14 15:45:51,157 Epoch: [254][310/500] Time 0.017 (0.045) Data 0.001 (0.002) Loss 0.0214 (0.0336) Prec@1 98.000 (94.375) Prec@5 100.000 (99.844) +2022-11-14 15:45:51,339 Epoch: [254][320/500] Time 0.016 (0.044) Data 0.001 (0.002) Loss 0.0287 (0.0334) Prec@1 96.000 (94.424) Prec@5 100.000 (99.848) +2022-11-14 15:45:51,525 Epoch: [254][330/500] Time 0.019 (0.043) Data 0.001 (0.002) Loss 0.0383 (0.0336) Prec@1 92.000 (94.353) Prec@5 100.000 (99.853) +2022-11-14 15:45:51,719 Epoch: [254][340/500] Time 0.021 (0.042) Data 0.001 (0.002) Loss 0.0254 (0.0333) Prec@1 96.000 (94.400) Prec@5 99.000 (99.829) +2022-11-14 15:45:51,915 Epoch: [254][350/500] Time 0.017 (0.042) Data 0.001 (0.002) Loss 0.0283 (0.0332) Prec@1 94.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 15:45:52,104 Epoch: [254][360/500] Time 0.017 (0.041) Data 0.001 (0.002) Loss 0.0297 (0.0331) Prec@1 96.000 (94.432) Prec@5 100.000 (99.838) +2022-11-14 15:45:52,286 Epoch: [254][370/500] Time 0.016 (0.040) Data 0.001 (0.002) Loss 0.0426 (0.0334) Prec@1 92.000 (94.368) Prec@5 98.000 (99.789) +2022-11-14 15:45:52,465 Epoch: [254][380/500] Time 0.017 (0.040) Data 0.001 (0.002) Loss 0.0262 (0.0332) Prec@1 96.000 (94.410) Prec@5 100.000 (99.795) +2022-11-14 15:45:52,650 Epoch: [254][390/500] Time 0.015 (0.039) Data 0.001 (0.002) Loss 0.0257 (0.0330) Prec@1 97.000 (94.475) Prec@5 99.000 (99.775) +2022-11-14 15:45:52,831 Epoch: [254][400/500] Time 0.015 (0.038) Data 0.001 (0.002) Loss 0.0286 (0.0329) Prec@1 94.000 (94.463) Prec@5 100.000 (99.780) +2022-11-14 15:45:53,016 Epoch: [254][410/500] Time 0.017 (0.038) Data 0.001 (0.002) Loss 0.0555 (0.0334) Prec@1 91.000 (94.381) Prec@5 100.000 (99.786) +2022-11-14 15:45:53,200 Epoch: [254][420/500] Time 0.017 (0.037) Data 0.001 (0.002) Loss 0.0441 (0.0337) Prec@1 94.000 (94.372) Prec@5 100.000 (99.791) +2022-11-14 15:45:53,381 Epoch: [254][430/500] Time 0.016 (0.037) Data 0.002 (0.002) Loss 0.0534 (0.0341) Prec@1 89.000 (94.250) Prec@5 100.000 (99.795) +2022-11-14 15:45:53,566 Epoch: [254][440/500] Time 0.017 (0.036) Data 0.001 (0.002) Loss 0.0418 (0.0343) Prec@1 93.000 (94.222) Prec@5 100.000 (99.800) +2022-11-14 15:45:53,750 Epoch: [254][450/500] Time 0.014 (0.036) Data 0.002 (0.002) Loss 0.0230 (0.0340) Prec@1 97.000 (94.283) Prec@5 100.000 (99.804) +2022-11-14 15:45:53,931 Epoch: [254][460/500] Time 0.016 (0.036) Data 0.001 (0.002) Loss 0.0237 (0.0338) Prec@1 97.000 (94.340) Prec@5 100.000 (99.809) +2022-11-14 15:45:54,115 Epoch: [254][470/500] Time 0.015 (0.035) Data 0.001 (0.002) Loss 0.0239 (0.0336) Prec@1 96.000 (94.375) Prec@5 100.000 (99.812) +2022-11-14 15:45:54,301 Epoch: [254][480/500] Time 0.017 (0.035) Data 0.001 (0.002) Loss 0.0207 (0.0334) Prec@1 96.000 (94.408) Prec@5 100.000 (99.816) +2022-11-14 15:45:54,490 Epoch: [254][490/500] Time 0.016 (0.034) Data 0.001 (0.002) Loss 0.0477 (0.0336) Prec@1 91.000 (94.340) Prec@5 100.000 (99.820) +2022-11-14 15:45:54,655 Epoch: [254][499/500] Time 0.016 (0.034) Data 0.001 (0.002) Loss 0.0100 (0.0332) Prec@1 99.000 (94.431) Prec@5 100.000 (99.824) +2022-11-14 15:45:56,567 Test: [0/100] Model Time 1.697 (1.697) Loss Time 0.000 (0.000) Loss 0.0834 (0.0834) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 15:45:57,037 Test: [1/100] Model Time 0.470 (1.083) Loss Time 0.000 (0.000) Loss 0.0781 (0.0808) Prec@1 87.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 15:45:57,046 Test: [2/100] Model Time 0.007 (0.725) Loss Time 0.000 (0.000) Loss 0.0709 (0.0775) Prec@1 88.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 15:45:57,058 Test: [3/100] Model Time 0.005 (0.545) Loss Time 0.000 (0.000) Loss 0.0795 (0.0780) Prec@1 89.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 15:45:57,065 Test: [4/100] Model Time 0.005 (0.437) Loss Time 0.000 (0.000) Loss 0.0660 (0.0756) Prec@1 89.000 (87.600) Prec@5 100.000 (99.800) +2022-11-14 15:45:57,074 Test: [5/100] Model Time 0.005 (0.365) Loss Time 0.000 (0.000) Loss 0.0582 (0.0727) Prec@1 91.000 (88.167) Prec@5 98.000 (99.500) +2022-11-14 15:45:57,083 Test: [6/100] Model Time 0.007 (0.314) Loss Time 0.000 (0.000) Loss 0.0570 (0.0704) Prec@1 91.000 (88.571) Prec@5 100.000 (99.571) +2022-11-14 15:45:57,092 Test: [7/100] Model Time 0.006 (0.275) Loss Time 0.000 (0.000) Loss 0.0909 (0.0730) Prec@1 86.000 (88.250) Prec@5 98.000 (99.375) +2022-11-14 15:45:57,099 Test: [8/100] Model Time 0.005 (0.245) Loss Time 0.000 (0.000) Loss 0.0835 (0.0742) Prec@1 87.000 (88.111) Prec@5 99.000 (99.333) +2022-11-14 15:45:57,108 Test: [9/100] Model Time 0.005 (0.221) Loss Time 0.000 (0.000) Loss 0.0511 (0.0719) Prec@1 92.000 (88.500) Prec@5 99.000 (99.300) +2022-11-14 15:45:57,118 Test: [10/100] Model Time 0.007 (0.202) Loss Time 0.000 (0.000) Loss 0.0602 (0.0708) Prec@1 91.000 (88.727) Prec@5 99.000 (99.273) +2022-11-14 15:45:57,127 Test: [11/100] Model Time 0.006 (0.185) Loss Time 0.000 (0.000) Loss 0.0954 (0.0729) Prec@1 84.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 15:45:57,136 Test: [12/100] Model Time 0.005 (0.172) Loss Time 0.000 (0.000) Loss 0.0471 (0.0709) Prec@1 93.000 (88.692) Prec@5 100.000 (99.385) +2022-11-14 15:45:57,146 Test: [13/100] Model Time 0.005 (0.160) Loss Time 0.000 (0.000) Loss 0.0700 (0.0708) Prec@1 88.000 (88.643) Prec@5 98.000 (99.286) +2022-11-14 15:45:57,156 Test: [14/100] Model Time 0.008 (0.150) Loss Time 0.000 (0.000) Loss 0.0680 (0.0706) Prec@1 90.000 (88.733) Prec@5 99.000 (99.267) +2022-11-14 15:45:57,166 Test: [15/100] Model Time 0.006 (0.141) Loss Time 0.000 (0.000) Loss 0.0860 (0.0716) Prec@1 85.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 15:45:57,174 Test: [16/100] Model Time 0.006 (0.133) Loss Time 0.000 (0.000) Loss 0.0579 (0.0708) Prec@1 90.000 (88.588) Prec@5 98.000 (99.176) +2022-11-14 15:45:57,183 Test: [17/100] Model Time 0.005 (0.126) Loss Time 0.000 (0.000) Loss 0.0954 (0.0721) Prec@1 82.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 15:45:57,192 Test: [18/100] Model Time 0.008 (0.119) Loss Time 0.000 (0.000) Loss 0.1053 (0.0739) Prec@1 81.000 (87.842) Prec@5 98.000 (99.158) +2022-11-14 15:45:57,201 Test: [19/100] Model Time 0.007 (0.114) Loss Time 0.000 (0.000) Loss 0.0858 (0.0745) Prec@1 86.000 (87.750) Prec@5 98.000 (99.100) +2022-11-14 15:45:57,210 Test: [20/100] Model Time 0.005 (0.109) Loss Time 0.000 (0.000) Loss 0.0776 (0.0746) Prec@1 87.000 (87.714) Prec@5 98.000 (99.048) +2022-11-14 15:45:57,217 Test: [21/100] Model Time 0.005 (0.104) Loss Time 0.000 (0.000) Loss 0.1018 (0.0759) Prec@1 83.000 (87.500) Prec@5 100.000 (99.091) +2022-11-14 15:45:57,226 Test: [22/100] Model Time 0.007 (0.100) Loss Time 0.000 (0.000) Loss 0.0895 (0.0765) Prec@1 87.000 (87.478) Prec@5 98.000 (99.043) +2022-11-14 15:45:57,236 Test: [23/100] Model Time 0.007 (0.096) Loss Time 0.000 (0.000) Loss 0.0638 (0.0759) Prec@1 92.000 (87.667) Prec@5 99.000 (99.042) +2022-11-14 15:45:57,245 Test: [24/100] Model Time 0.005 (0.092) Loss Time 0.000 (0.000) Loss 0.0809 (0.0761) Prec@1 85.000 (87.560) Prec@5 100.000 (99.080) +2022-11-14 15:45:57,253 Test: [25/100] Model Time 0.005 (0.089) Loss Time 0.000 (0.000) Loss 0.0921 (0.0768) Prec@1 85.000 (87.462) Prec@5 98.000 (99.038) +2022-11-14 15:45:57,263 Test: [26/100] Model Time 0.008 (0.086) Loss Time 0.000 (0.000) Loss 0.0591 (0.0761) Prec@1 90.000 (87.556) Prec@5 100.000 (99.074) +2022-11-14 15:45:57,272 Test: [27/100] Model Time 0.007 (0.083) Loss Time 0.000 (0.000) Loss 0.0534 (0.0753) Prec@1 89.000 (87.607) Prec@5 100.000 (99.107) +2022-11-14 15:45:57,280 Test: [28/100] Model Time 0.005 (0.080) Loss Time 0.000 (0.000) Loss 0.0696 (0.0751) Prec@1 86.000 (87.552) Prec@5 99.000 (99.103) +2022-11-14 15:45:57,289 Test: [29/100] Model Time 0.005 (0.078) Loss Time 0.000 (0.000) Loss 0.0807 (0.0753) Prec@1 86.000 (87.500) Prec@5 99.000 (99.100) +2022-11-14 15:45:57,299 Test: [30/100] Model Time 0.008 (0.076) Loss Time 0.000 (0.000) Loss 0.0702 (0.0751) Prec@1 88.000 (87.516) Prec@5 99.000 (99.097) +2022-11-14 15:45:57,308 Test: [31/100] Model Time 0.007 (0.073) Loss Time 0.000 (0.000) Loss 0.0797 (0.0753) Prec@1 87.000 (87.500) Prec@5 98.000 (99.062) +2022-11-14 15:45:57,317 Test: [32/100] Model Time 0.005 (0.071) Loss Time 0.000 (0.000) Loss 0.0730 (0.0752) Prec@1 88.000 (87.515) Prec@5 99.000 (99.061) +2022-11-14 15:45:57,326 Test: [33/100] Model Time 0.005 (0.069) Loss Time 0.000 (0.000) Loss 0.0855 (0.0755) Prec@1 86.000 (87.471) Prec@5 99.000 (99.059) +2022-11-14 15:45:57,336 Test: [34/100] Model Time 0.008 (0.068) Loss Time 0.000 (0.000) Loss 0.0907 (0.0759) Prec@1 84.000 (87.371) Prec@5 98.000 (99.029) +2022-11-14 15:45:57,345 Test: [35/100] Model Time 0.007 (0.066) Loss Time 0.000 (0.000) Loss 0.0895 (0.0763) Prec@1 85.000 (87.306) Prec@5 99.000 (99.028) +2022-11-14 15:45:57,354 Test: [36/100] Model Time 0.006 (0.064) Loss Time 0.000 (0.000) Loss 0.0705 (0.0761) Prec@1 89.000 (87.351) Prec@5 97.000 (98.973) +2022-11-14 15:45:57,363 Test: [37/100] Model Time 0.006 (0.063) Loss Time 0.000 (0.000) Loss 0.0996 (0.0768) Prec@1 83.000 (87.237) Prec@5 99.000 (98.974) +2022-11-14 15:45:57,372 Test: [38/100] Model Time 0.005 (0.061) Loss Time 0.000 (0.000) Loss 0.0562 (0.0762) Prec@1 93.000 (87.385) Prec@5 100.000 (99.000) +2022-11-14 15:45:57,382 Test: [39/100] Model Time 0.005 (0.060) Loss Time 0.000 (0.000) Loss 0.0705 (0.0761) Prec@1 86.000 (87.350) Prec@5 99.000 (99.000) +2022-11-14 15:45:57,391 Test: [40/100] Model Time 0.007 (0.059) Loss Time 0.000 (0.000) Loss 0.1021 (0.0767) Prec@1 85.000 (87.293) Prec@5 99.000 (99.000) +2022-11-14 15:45:57,400 Test: [41/100] Model Time 0.006 (0.057) Loss Time 0.000 (0.000) Loss 0.0718 (0.0766) Prec@1 89.000 (87.333) Prec@5 99.000 (99.000) +2022-11-14 15:45:57,408 Test: [42/100] Model Time 0.005 (0.056) Loss Time 0.000 (0.000) Loss 0.0532 (0.0761) Prec@1 93.000 (87.465) Prec@5 99.000 (99.000) +2022-11-14 15:45:57,416 Test: [43/100] Model Time 0.005 (0.055) Loss Time 0.000 (0.000) Loss 0.0714 (0.0760) Prec@1 89.000 (87.500) Prec@5 98.000 (98.977) +2022-11-14 15:45:57,425 Test: [44/100] Model Time 0.007 (0.054) Loss Time 0.000 (0.000) Loss 0.0493 (0.0754) Prec@1 93.000 (87.622) Prec@5 99.000 (98.978) +2022-11-14 15:45:57,434 Test: [45/100] Model Time 0.006 (0.053) Loss Time 0.000 (0.000) Loss 0.0922 (0.0757) Prec@1 85.000 (87.565) Prec@5 98.000 (98.957) +2022-11-14 15:45:57,444 Test: [46/100] Model Time 0.005 (0.052) Loss Time 0.000 (0.000) Loss 0.0603 (0.0754) Prec@1 90.000 (87.617) Prec@5 100.000 (98.979) +2022-11-14 15:45:57,451 Test: [47/100] Model Time 0.005 (0.051) Loss Time 0.000 (0.000) Loss 0.1156 (0.0762) Prec@1 80.000 (87.458) Prec@5 98.000 (98.958) +2022-11-14 15:45:57,460 Test: [48/100] Model Time 0.007 (0.050) Loss Time 0.000 (0.000) Loss 0.0479 (0.0757) Prec@1 93.000 (87.571) Prec@5 100.000 (98.980) +2022-11-14 15:45:57,469 Test: [49/100] Model Time 0.006 (0.049) Loss Time 0.000 (0.000) Loss 0.0983 (0.0761) Prec@1 84.000 (87.500) Prec@5 99.000 (98.980) +2022-11-14 15:45:57,476 Test: [50/100] Model Time 0.004 (0.048) Loss Time 0.000 (0.000) Loss 0.0642 (0.0759) Prec@1 91.000 (87.569) Prec@5 97.000 (98.941) +2022-11-14 15:45:57,483 Test: [51/100] Model Time 0.004 (0.047) Loss Time 0.000 (0.000) Loss 0.0748 (0.0759) Prec@1 87.000 (87.558) Prec@5 99.000 (98.942) +2022-11-14 15:45:57,492 Test: [52/100] Model Time 0.007 (0.047) Loss Time 0.000 (0.000) Loss 0.0570 (0.0755) Prec@1 92.000 (87.642) Prec@5 100.000 (98.962) +2022-11-14 15:45:57,500 Test: [53/100] Model Time 0.005 (0.046) Loss Time 0.000 (0.000) Loss 0.0828 (0.0756) Prec@1 86.000 (87.611) Prec@5 100.000 (98.981) +2022-11-14 15:45:57,508 Test: [54/100] Model Time 0.005 (0.045) Loss Time 0.000 (0.000) Loss 0.0745 (0.0756) Prec@1 87.000 (87.600) Prec@5 100.000 (99.000) +2022-11-14 15:45:57,516 Test: [55/100] Model Time 0.005 (0.044) Loss Time 0.000 (0.000) Loss 0.0826 (0.0757) Prec@1 87.000 (87.589) Prec@5 99.000 (99.000) +2022-11-14 15:45:57,523 Test: [56/100] Model Time 0.005 (0.044) Loss Time 0.000 (0.000) Loss 0.0560 (0.0754) Prec@1 89.000 (87.614) Prec@5 100.000 (99.018) +2022-11-14 15:45:57,532 Test: [57/100] Model Time 0.005 (0.043) Loss Time 0.000 (0.000) Loss 0.0776 (0.0754) Prec@1 88.000 (87.621) Prec@5 99.000 (99.017) +2022-11-14 15:45:57,541 Test: [58/100] Model Time 0.005 (0.042) Loss Time 0.000 (0.000) Loss 0.1314 (0.0764) Prec@1 81.000 (87.508) Prec@5 100.000 (99.034) +2022-11-14 15:45:57,550 Test: [59/100] Model Time 0.005 (0.042) Loss Time 0.000 (0.000) Loss 0.0826 (0.0765) Prec@1 87.000 (87.500) Prec@5 99.000 (99.033) +2022-11-14 15:45:57,558 Test: [60/100] Model Time 0.005 (0.041) Loss Time 0.000 (0.000) Loss 0.0601 (0.0762) Prec@1 92.000 (87.574) Prec@5 100.000 (99.049) +2022-11-14 15:45:57,565 Test: [61/100] Model Time 0.005 (0.041) Loss Time 0.000 (0.000) Loss 0.0916 (0.0765) Prec@1 84.000 (87.516) Prec@5 100.000 (99.065) +2022-11-14 15:45:57,574 Test: [62/100] Model Time 0.005 (0.040) Loss Time 0.000 (0.000) Loss 0.0553 (0.0761) Prec@1 90.000 (87.556) Prec@5 100.000 (99.079) +2022-11-14 15:45:57,583 Test: [63/100] Model Time 0.005 (0.039) Loss Time 0.000 (0.000) Loss 0.0660 (0.0760) Prec@1 88.000 (87.562) Prec@5 100.000 (99.094) +2022-11-14 15:45:57,591 Test: [64/100] Model Time 0.005 (0.039) Loss Time 0.000 (0.000) Loss 0.0868 (0.0761) Prec@1 87.000 (87.554) Prec@5 100.000 (99.108) +2022-11-14 15:45:57,601 Test: [65/100] Model Time 0.005 (0.038) Loss Time 0.000 (0.000) Loss 0.0677 (0.0760) Prec@1 87.000 (87.545) Prec@5 99.000 (99.106) +2022-11-14 15:45:57,609 Test: [66/100] Model Time 0.005 (0.038) Loss Time 0.000 (0.000) Loss 0.0438 (0.0755) Prec@1 94.000 (87.642) Prec@5 99.000 (99.104) +2022-11-14 15:45:57,618 Test: [67/100] Model Time 0.005 (0.037) Loss Time 0.000 (0.000) Loss 0.0601 (0.0753) Prec@1 89.000 (87.662) Prec@5 100.000 (99.118) +2022-11-14 15:45:57,626 Test: [68/100] Model Time 0.005 (0.037) Loss Time 0.000 (0.000) Loss 0.0543 (0.0750) Prec@1 90.000 (87.696) Prec@5 99.000 (99.116) +2022-11-14 15:45:57,635 Test: [69/100] Model Time 0.006 (0.037) Loss Time 0.000 (0.000) Loss 0.0814 (0.0751) Prec@1 86.000 (87.671) Prec@5 99.000 (99.114) +2022-11-14 15:45:57,644 Test: [70/100] Model Time 0.005 (0.036) Loss Time 0.000 (0.000) Loss 0.0877 (0.0753) Prec@1 85.000 (87.634) Prec@5 100.000 (99.127) +2022-11-14 15:45:57,654 Test: [71/100] Model Time 0.006 (0.036) Loss Time 0.000 (0.000) Loss 0.0652 (0.0751) Prec@1 90.000 (87.667) Prec@5 100.000 (99.139) +2022-11-14 15:45:57,661 Test: [72/100] Model Time 0.005 (0.035) Loss Time 0.000 (0.000) Loss 0.0532 (0.0748) Prec@1 92.000 (87.726) Prec@5 100.000 (99.151) +2022-11-14 15:45:57,669 Test: [73/100] Model Time 0.005 (0.035) Loss Time 0.000 (0.000) Loss 0.0457 (0.0744) Prec@1 91.000 (87.770) Prec@5 100.000 (99.162) +2022-11-14 15:45:57,678 Test: [74/100] Model Time 0.005 (0.034) Loss Time 0.000 (0.000) Loss 0.0844 (0.0746) Prec@1 84.000 (87.720) Prec@5 99.000 (99.160) +2022-11-14 15:45:57,687 Test: [75/100] Model Time 0.006 (0.034) Loss Time 0.000 (0.000) Loss 0.0733 (0.0746) Prec@1 89.000 (87.737) Prec@5 99.000 (99.158) +2022-11-14 15:45:57,696 Test: [76/100] Model Time 0.006 (0.034) Loss Time 0.000 (0.000) Loss 0.0784 (0.0746) Prec@1 86.000 (87.714) Prec@5 98.000 (99.143) +2022-11-14 15:45:57,705 Test: [77/100] Model Time 0.005 (0.033) Loss Time 0.000 (0.000) Loss 0.1051 (0.0750) Prec@1 80.000 (87.615) Prec@5 99.000 (99.141) +2022-11-14 15:45:57,714 Test: [78/100] Model Time 0.005 (0.033) Loss Time 0.000 (0.000) Loss 0.0602 (0.0748) Prec@1 89.000 (87.633) Prec@5 99.000 (99.139) +2022-11-14 15:45:57,722 Test: [79/100] Model Time 0.005 (0.033) Loss Time 0.000 (0.000) Loss 0.0747 (0.0748) Prec@1 88.000 (87.638) Prec@5 100.000 (99.150) +2022-11-14 15:45:57,730 Test: [80/100] Model Time 0.007 (0.032) Loss Time 0.000 (0.000) Loss 0.0859 (0.0749) Prec@1 86.000 (87.617) Prec@5 98.000 (99.136) +2022-11-14 15:45:57,738 Test: [81/100] Model Time 0.006 (0.032) Loss Time 0.000 (0.000) Loss 0.0833 (0.0750) Prec@1 85.000 (87.585) Prec@5 100.000 (99.146) +2022-11-14 15:45:57,746 Test: [82/100] Model Time 0.004 (0.032) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 88.000 (87.590) Prec@5 100.000 (99.157) +2022-11-14 15:45:57,753 Test: [83/100] Model Time 0.005 (0.031) Loss Time 0.000 (0.000) Loss 0.0662 (0.0750) Prec@1 86.000 (87.571) Prec@5 97.000 (99.131) +2022-11-14 15:45:57,761 Test: [84/100] Model Time 0.005 (0.031) Loss Time 0.000 (0.000) Loss 0.0954 (0.0753) Prec@1 88.000 (87.576) Prec@5 100.000 (99.141) +2022-11-14 15:45:57,769 Test: [85/100] Model Time 0.005 (0.031) Loss Time 0.000 (0.000) Loss 0.1104 (0.0757) Prec@1 82.000 (87.512) Prec@5 98.000 (99.128) +2022-11-14 15:45:57,777 Test: [86/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.0560 (0.0755) Prec@1 94.000 (87.586) Prec@5 100.000 (99.138) +2022-11-14 15:45:57,785 Test: [87/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.0842 (0.0756) Prec@1 88.000 (87.591) Prec@5 99.000 (99.136) +2022-11-14 15:45:57,795 Test: [88/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.0635 (0.0754) Prec@1 90.000 (87.618) Prec@5 99.000 (99.135) +2022-11-14 15:45:57,804 Test: [89/100] Model Time 0.005 (0.030) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 88.000 (87.622) Prec@5 98.000 (99.122) +2022-11-14 15:45:57,814 Test: [90/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.0643 (0.0753) Prec@1 91.000 (87.659) Prec@5 100.000 (99.132) +2022-11-14 15:45:57,822 Test: [91/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.0458 (0.0749) Prec@1 94.000 (87.728) Prec@5 100.000 (99.141) +2022-11-14 15:45:57,830 Test: [92/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.0925 (0.0751) Prec@1 85.000 (87.699) Prec@5 99.000 (99.140) +2022-11-14 15:45:57,839 Test: [93/100] Model Time 0.005 (0.029) Loss Time 0.000 (0.000) Loss 0.0758 (0.0751) Prec@1 88.000 (87.702) Prec@5 99.000 (99.138) +2022-11-14 15:45:57,848 Test: [94/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.0694 (0.0751) Prec@1 88.000 (87.705) Prec@5 99.000 (99.137) +2022-11-14 15:45:57,856 Test: [95/100] Model Time 0.005 (0.028) Loss Time 0.000 (0.000) Loss 0.0776 (0.0751) Prec@1 87.000 (87.698) Prec@5 100.000 (99.146) +2022-11-14 15:45:57,864 Test: [96/100] Model Time 0.004 (0.028) Loss Time 0.000 (0.000) Loss 0.0439 (0.0748) Prec@1 95.000 (87.773) Prec@5 99.000 (99.144) +2022-11-14 15:45:57,872 Test: [97/100] Model Time 0.004 (0.028) Loss Time 0.000 (0.000) Loss 0.0949 (0.0750) Prec@1 86.000 (87.755) Prec@5 100.000 (99.153) +2022-11-14 15:45:57,880 Test: [98/100] Model Time 0.005 (0.027) Loss Time 0.000 (0.000) Loss 0.0892 (0.0751) Prec@1 86.000 (87.737) Prec@5 99.000 (99.152) +2022-11-14 15:45:57,888 Test: [99/100] Model Time 0.005 (0.027) Loss Time 0.000 (0.000) Loss 0.0872 (0.0752) Prec@1 84.000 (87.700) Prec@5 100.000 (99.160) +2022-11-14 15:45:57,943 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:45:58,206 Epoch: [255][0/500] Time 0.018 (0.018) Data 0.198 (0.198) Loss 0.0165 (0.0165) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 15:45:58,387 Epoch: [255][10/500] Time 0.016 (0.016) Data 0.001 (0.019) Loss 0.0346 (0.0255) Prec@1 93.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:45:58,572 Epoch: [255][20/500] Time 0.017 (0.016) Data 0.001 (0.011) Loss 0.0308 (0.0273) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 15:45:58,759 Epoch: [255][30/500] Time 0.017 (0.016) Data 0.001 (0.008) Loss 0.0309 (0.0282) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 15:45:58,945 Epoch: [255][40/500] Time 0.020 (0.016) Data 0.001 (0.006) Loss 0.0604 (0.0346) Prec@1 90.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 15:45:59,142 Epoch: [255][50/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0483 (0.0369) Prec@1 90.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:45:59,328 Epoch: [255][60/500] Time 0.015 (0.017) Data 0.001 (0.005) Loss 0.0320 (0.0362) Prec@1 95.000 (93.714) Prec@5 100.000 (100.000) +2022-11-14 15:45:59,513 Epoch: [255][70/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0211 (0.0343) Prec@1 97.000 (94.125) Prec@5 100.000 (100.000) +2022-11-14 15:45:59,693 Epoch: [255][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0544 (0.0365) Prec@1 91.000 (93.778) Prec@5 100.000 (100.000) +2022-11-14 15:45:59,879 Epoch: [255][90/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0201 (0.0349) Prec@1 97.000 (94.100) Prec@5 100.000 (100.000) +2022-11-14 15:46:00,068 Epoch: [255][100/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0413 (0.0355) Prec@1 95.000 (94.182) Prec@5 99.000 (99.909) +2022-11-14 15:46:00,261 Epoch: [255][110/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0292 (0.0350) Prec@1 97.000 (94.417) Prec@5 100.000 (99.917) +2022-11-14 15:46:00,447 Epoch: [255][120/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0358 (0.0350) Prec@1 93.000 (94.308) Prec@5 100.000 (99.923) +2022-11-14 15:46:00,629 Epoch: [255][130/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0191 (0.0339) Prec@1 97.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 15:46:00,815 Epoch: [255][140/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0312 (0.0337) Prec@1 95.000 (94.533) Prec@5 100.000 (99.933) +2022-11-14 15:46:01,002 Epoch: [255][150/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0372 (0.0339) Prec@1 94.000 (94.500) Prec@5 99.000 (99.875) +2022-11-14 15:46:01,197 Epoch: [255][160/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0391 (0.0342) Prec@1 92.000 (94.353) Prec@5 100.000 (99.882) +2022-11-14 15:46:01,382 Epoch: [255][170/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0379 (0.0344) Prec@1 94.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 15:46:01,571 Epoch: [255][180/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0339 (0.0344) Prec@1 96.000 (94.421) Prec@5 99.000 (99.842) +2022-11-14 15:46:01,763 Epoch: [255][190/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0626 (0.0358) Prec@1 90.000 (94.200) Prec@5 99.000 (99.800) +2022-11-14 15:46:01,949 Epoch: [255][200/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0636 (0.0371) Prec@1 90.000 (94.000) Prec@5 100.000 (99.810) +2022-11-14 15:46:02,133 Epoch: [255][210/500] Time 0.014 (0.017) Data 0.001 (0.002) Loss 0.0396 (0.0372) Prec@1 94.000 (94.000) Prec@5 100.000 (99.818) +2022-11-14 15:46:02,318 Epoch: [255][220/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0154 (0.0363) Prec@1 98.000 (94.174) Prec@5 99.000 (99.783) +2022-11-14 15:46:02,500 Epoch: [255][230/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0263 (0.0359) Prec@1 97.000 (94.292) Prec@5 100.000 (99.792) +2022-11-14 15:46:02,683 Epoch: [255][240/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0568 (0.0367) Prec@1 91.000 (94.160) Prec@5 99.000 (99.760) +2022-11-14 15:46:02,868 Epoch: [255][250/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0395 (0.0368) Prec@1 93.000 (94.115) Prec@5 99.000 (99.731) +2022-11-14 15:46:03,053 Epoch: [255][260/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0289 (0.0365) Prec@1 94.000 (94.111) Prec@5 99.000 (99.704) +2022-11-14 15:46:03,232 Epoch: [255][270/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0275 (0.0362) Prec@1 96.000 (94.179) Prec@5 100.000 (99.714) +2022-11-14 15:46:03,414 Epoch: [255][280/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0450 (0.0365) Prec@1 93.000 (94.138) Prec@5 100.000 (99.724) +2022-11-14 15:46:03,595 Epoch: [255][290/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0234 (0.0361) Prec@1 95.000 (94.167) Prec@5 100.000 (99.733) +2022-11-14 15:46:03,779 Epoch: [255][300/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.0483 (0.0365) Prec@1 94.000 (94.161) Prec@5 100.000 (99.742) +2022-11-14 15:46:03,961 Epoch: [255][310/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0338 (0.0364) Prec@1 95.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 15:46:04,143 Epoch: [255][320/500] Time 0.016 (0.016) Data 0.001 (0.002) Loss 0.0296 (0.0362) Prec@1 96.000 (94.242) Prec@5 100.000 (99.758) +2022-11-14 15:46:04,324 Epoch: [255][330/500] Time 0.015 (0.016) Data 0.001 (0.002) Loss 0.0413 (0.0363) Prec@1 94.000 (94.235) Prec@5 100.000 (99.765) +2022-11-14 15:46:04,517 Epoch: [255][340/500] Time 0.020 (0.016) Data 0.001 (0.002) Loss 0.0367 (0.0363) Prec@1 95.000 (94.257) Prec@5 99.000 (99.743) +2022-11-14 15:46:04,709 Epoch: [255][350/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0525 (0.0368) Prec@1 92.000 (94.194) Prec@5 99.000 (99.722) +2022-11-14 15:46:04,900 Epoch: [255][360/500] Time 0.020 (0.017) Data 0.001 (0.002) Loss 0.0562 (0.0373) Prec@1 91.000 (94.108) Prec@5 100.000 (99.730) +2022-11-14 15:46:05,084 Epoch: [255][370/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0355 (0.0373) Prec@1 95.000 (94.132) Prec@5 99.000 (99.711) +2022-11-14 15:46:05,269 Epoch: [255][380/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0214 (0.0369) Prec@1 96.000 (94.179) Prec@5 100.000 (99.718) +2022-11-14 15:46:05,455 Epoch: [255][390/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0487 (0.0372) Prec@1 91.000 (94.100) Prec@5 100.000 (99.725) +2022-11-14 15:46:05,644 Epoch: [255][400/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0170 (0.0367) Prec@1 99.000 (94.220) Prec@5 100.000 (99.732) +2022-11-14 15:46:05,831 Epoch: [255][410/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0211 (0.0363) Prec@1 97.000 (94.286) Prec@5 100.000 (99.738) +2022-11-14 15:46:06,014 Epoch: [255][420/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0505 (0.0366) Prec@1 91.000 (94.209) Prec@5 99.000 (99.721) +2022-11-14 15:46:06,196 Epoch: [255][430/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0255 (0.0364) Prec@1 96.000 (94.250) Prec@5 100.000 (99.727) +2022-11-14 15:46:06,382 Epoch: [255][440/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0439 (0.0365) Prec@1 94.000 (94.244) Prec@5 100.000 (99.733) +2022-11-14 15:46:06,567 Epoch: [255][450/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0259 (0.0363) Prec@1 96.000 (94.283) Prec@5 100.000 (99.739) +2022-11-14 15:46:06,766 Epoch: [255][460/500] Time 0.021 (0.017) Data 0.001 (0.002) Loss 0.0248 (0.0361) Prec@1 95.000 (94.298) Prec@5 100.000 (99.745) +2022-11-14 15:46:06,956 Epoch: [255][470/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0344 (0.0360) Prec@1 94.000 (94.292) Prec@5 100.000 (99.750) +2022-11-14 15:46:07,149 Epoch: [255][480/500] Time 0.020 (0.017) Data 0.001 (0.002) Loss 0.0225 (0.0358) Prec@1 97.000 (94.347) Prec@5 100.000 (99.755) +2022-11-14 15:46:07,341 Epoch: [255][490/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0326 (0.0357) Prec@1 94.000 (94.340) Prec@5 100.000 (99.760) +2022-11-14 15:46:07,507 Epoch: [255][499/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0389 (0.0358) Prec@1 94.000 (94.333) Prec@5 100.000 (99.765) +2022-11-14 15:46:07,769 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0787) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:07,776 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0837) Prec@1 87.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:07,784 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0782) Prec@1 89.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 15:46:07,793 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0796) Prec@1 86.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 15:46:07,802 Test: [4/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0759) Prec@1 91.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 15:46:07,811 Test: [5/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0718) Prec@1 92.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 15:46:07,821 Test: [6/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0705) Prec@1 90.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 15:46:07,831 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0699) Prec@1 89.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 15:46:07,841 Test: [8/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0700) Prec@1 89.000 (88.778) Prec@5 99.000 (99.667) +2022-11-14 15:46:07,850 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0690) Prec@1 91.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 15:46:07,859 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0671) Prec@1 94.000 (89.455) Prec@5 100.000 (99.636) +2022-11-14 15:46:07,869 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0694) Prec@1 87.000 (89.250) Prec@5 100.000 (99.667) +2022-11-14 15:46:07,879 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0690) Prec@1 90.000 (89.308) Prec@5 99.000 (99.615) +2022-11-14 15:46:07,889 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0705) Prec@1 86.000 (89.071) Prec@5 99.000 (99.571) +2022-11-14 15:46:07,898 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0708) Prec@1 88.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 15:46:07,907 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0709) Prec@1 89.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 15:46:07,917 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0382 (0.0690) Prec@1 96.000 (89.412) Prec@5 99.000 (99.588) +2022-11-14 15:46:07,927 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1153 (0.0716) Prec@1 83.000 (89.056) Prec@5 100.000 (99.611) +2022-11-14 15:46:07,936 Test: [18/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0716) Prec@1 86.000 (88.895) Prec@5 99.000 (99.579) +2022-11-14 15:46:07,945 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0725) Prec@1 80.000 (88.450) Prec@5 98.000 (99.500) +2022-11-14 15:46:07,956 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0740) Prec@1 83.000 (88.190) Prec@5 100.000 (99.524) +2022-11-14 15:46:07,965 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0742) Prec@1 87.000 (88.136) Prec@5 99.000 (99.500) +2022-11-14 15:46:07,973 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0753) Prec@1 86.000 (88.043) Prec@5 100.000 (99.522) +2022-11-14 15:46:07,982 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0751) Prec@1 88.000 (88.042) Prec@5 100.000 (99.542) +2022-11-14 15:46:07,990 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0755) Prec@1 87.000 (88.000) Prec@5 100.000 (99.560) +2022-11-14 15:46:07,997 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0766) Prec@1 81.000 (87.731) Prec@5 98.000 (99.500) +2022-11-14 15:46:08,004 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0759) Prec@1 91.000 (87.852) Prec@5 100.000 (99.519) +2022-11-14 15:46:08,014 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0748) Prec@1 91.000 (87.964) Prec@5 100.000 (99.536) +2022-11-14 15:46:08,022 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0745) Prec@1 91.000 (88.069) Prec@5 99.000 (99.517) +2022-11-14 15:46:08,030 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0744) Prec@1 88.000 (88.067) Prec@5 99.000 (99.500) +2022-11-14 15:46:08,039 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0743) Prec@1 87.000 (88.032) Prec@5 99.000 (99.484) +2022-11-14 15:46:08,049 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0741) Prec@1 90.000 (88.094) Prec@5 98.000 (99.438) +2022-11-14 15:46:08,059 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0745) Prec@1 88.000 (88.091) Prec@5 99.000 (99.424) +2022-11-14 15:46:08,068 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0748) Prec@1 85.000 (88.000) Prec@5 99.000 (99.412) +2022-11-14 15:46:08,077 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0750) Prec@1 87.000 (87.971) Prec@5 99.000 (99.400) +2022-11-14 15:46:08,086 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0749) Prec@1 90.000 (88.028) Prec@5 100.000 (99.417) +2022-11-14 15:46:08,095 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0747) Prec@1 88.000 (88.027) Prec@5 100.000 (99.432) +2022-11-14 15:46:08,105 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0752) Prec@1 83.000 (87.895) Prec@5 100.000 (99.447) +2022-11-14 15:46:08,113 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0750) Prec@1 90.000 (87.949) Prec@5 100.000 (99.462) +2022-11-14 15:46:08,122 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0748) Prec@1 88.000 (87.950) Prec@5 99.000 (99.450) +2022-11-14 15:46:08,131 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0752) Prec@1 85.000 (87.878) Prec@5 99.000 (99.439) +2022-11-14 15:46:08,141 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0751) Prec@1 90.000 (87.929) Prec@5 98.000 (99.405) +2022-11-14 15:46:08,150 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0743) Prec@1 93.000 (88.047) Prec@5 99.000 (99.395) +2022-11-14 15:46:08,159 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0739) Prec@1 91.000 (88.114) Prec@5 98.000 (99.364) +2022-11-14 15:46:08,169 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0737) Prec@1 90.000 (88.156) Prec@5 99.000 (99.356) +2022-11-14 15:46:08,177 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0744) Prec@1 82.000 (88.022) Prec@5 100.000 (99.370) +2022-11-14 15:46:08,186 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0744) Prec@1 87.000 (88.000) Prec@5 100.000 (99.383) +2022-11-14 15:46:08,194 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0746) Prec@1 89.000 (88.021) Prec@5 98.000 (99.354) +2022-11-14 15:46:08,204 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0743) Prec@1 91.000 (88.082) Prec@5 99.000 (99.347) +2022-11-14 15:46:08,213 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0748) Prec@1 84.000 (88.000) Prec@5 100.000 (99.360) +2022-11-14 15:46:08,223 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0745) Prec@1 89.000 (88.020) Prec@5 100.000 (99.373) +2022-11-14 15:46:08,231 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0747) Prec@1 88.000 (88.019) Prec@5 100.000 (99.385) +2022-11-14 15:46:08,240 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0744) Prec@1 89.000 (88.038) Prec@5 100.000 (99.396) +2022-11-14 15:46:08,249 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0747) Prec@1 85.000 (87.981) Prec@5 98.000 (99.370) +2022-11-14 15:46:08,258 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0749) Prec@1 88.000 (87.982) Prec@5 100.000 (99.382) +2022-11-14 15:46:08,267 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0748) Prec@1 88.000 (87.982) Prec@5 99.000 (99.375) +2022-11-14 15:46:08,276 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0746) Prec@1 90.000 (88.018) Prec@5 100.000 (99.386) +2022-11-14 15:46:08,284 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0745) Prec@1 88.000 (88.017) Prec@5 100.000 (99.397) +2022-11-14 15:46:08,291 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0746) Prec@1 86.000 (87.983) Prec@5 100.000 (99.407) +2022-11-14 15:46:08,299 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0746) Prec@1 88.000 (87.983) Prec@5 100.000 (99.417) +2022-11-14 15:46:08,307 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0746) Prec@1 90.000 (88.016) Prec@5 99.000 (99.410) +2022-11-14 15:46:08,315 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0745) Prec@1 90.000 (88.048) Prec@5 100.000 (99.419) +2022-11-14 15:46:08,324 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0561 (0.0742) Prec@1 90.000 (88.079) Prec@5 100.000 (99.429) +2022-11-14 15:46:08,333 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0737) Prec@1 93.000 (88.156) Prec@5 100.000 (99.438) +2022-11-14 15:46:08,342 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0738) Prec@1 85.000 (88.108) Prec@5 100.000 (99.446) +2022-11-14 15:46:08,350 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0739) Prec@1 86.000 (88.076) Prec@5 99.000 (99.439) +2022-11-14 15:46:08,359 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0737) Prec@1 92.000 (88.134) Prec@5 100.000 (99.448) +2022-11-14 15:46:08,369 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0738) Prec@1 87.000 (88.118) Prec@5 98.000 (99.426) +2022-11-14 15:46:08,378 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0737) Prec@1 86.000 (88.087) Prec@5 100.000 (99.435) +2022-11-14 15:46:08,387 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0738) Prec@1 86.000 (88.057) Prec@5 100.000 (99.443) +2022-11-14 15:46:08,395 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0741) Prec@1 87.000 (88.042) Prec@5 100.000 (99.451) +2022-11-14 15:46:08,404 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0738) Prec@1 90.000 (88.069) Prec@5 100.000 (99.458) +2022-11-14 15:46:08,412 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0738) Prec@1 90.000 (88.096) Prec@5 100.000 (99.466) +2022-11-14 15:46:08,422 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0305 (0.0732) Prec@1 96.000 (88.203) Prec@5 100.000 (99.473) +2022-11-14 15:46:08,430 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1131 (0.0738) Prec@1 82.000 (88.120) Prec@5 99.000 (99.467) +2022-11-14 15:46:08,439 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0735) Prec@1 91.000 (88.158) Prec@5 98.000 (99.447) +2022-11-14 15:46:08,446 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0735) Prec@1 88.000 (88.156) Prec@5 98.000 (99.429) +2022-11-14 15:46:08,455 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0738) Prec@1 84.000 (88.103) Prec@5 98.000 (99.410) +2022-11-14 15:46:08,464 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0737) Prec@1 91.000 (88.139) Prec@5 100.000 (99.418) +2022-11-14 15:46:08,474 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0738) Prec@1 85.000 (88.100) Prec@5 100.000 (99.425) +2022-11-14 15:46:08,483 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0741) Prec@1 80.000 (88.000) Prec@5 100.000 (99.432) +2022-11-14 15:46:08,493 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0744) Prec@1 85.000 (87.963) Prec@5 100.000 (99.439) +2022-11-14 15:46:08,502 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0746) Prec@1 85.000 (87.928) Prec@5 100.000 (99.446) +2022-11-14 15:46:08,511 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0748) Prec@1 85.000 (87.893) Prec@5 99.000 (99.440) +2022-11-14 15:46:08,521 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0749) Prec@1 86.000 (87.871) Prec@5 99.000 (99.435) +2022-11-14 15:46:08,529 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0751) Prec@1 86.000 (87.849) Prec@5 100.000 (99.442) +2022-11-14 15:46:08,538 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0751) Prec@1 89.000 (87.862) Prec@5 100.000 (99.448) +2022-11-14 15:46:08,546 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0752) Prec@1 86.000 (87.841) Prec@5 99.000 (99.443) +2022-11-14 15:46:08,554 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0754) Prec@1 85.000 (87.809) Prec@5 99.000 (99.438) +2022-11-14 15:46:08,561 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0755) Prec@1 87.000 (87.800) Prec@5 100.000 (99.444) +2022-11-14 15:46:08,570 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0752) Prec@1 93.000 (87.857) Prec@5 100.000 (99.451) +2022-11-14 15:46:08,579 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0750) Prec@1 92.000 (87.902) Prec@5 99.000 (99.446) +2022-11-14 15:46:08,589 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0753) Prec@1 86.000 (87.882) Prec@5 99.000 (99.441) +2022-11-14 15:46:08,598 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0751) Prec@1 91.000 (87.915) Prec@5 99.000 (99.436) +2022-11-14 15:46:08,607 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0750) Prec@1 88.000 (87.916) Prec@5 100.000 (99.442) +2022-11-14 15:46:08,616 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0749) Prec@1 89.000 (87.927) Prec@5 99.000 (99.438) +2022-11-14 15:46:08,627 Test: [96/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0747) Prec@1 91.000 (87.959) Prec@5 99.000 (99.433) +2022-11-14 15:46:08,636 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0747) Prec@1 89.000 (87.969) Prec@5 98.000 (99.418) +2022-11-14 15:46:08,646 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0749) Prec@1 85.000 (87.939) Prec@5 100.000 (99.424) +2022-11-14 15:46:08,656 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0749) Prec@1 88.000 (87.940) Prec@5 100.000 (99.430) +2022-11-14 15:46:08,705 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:46:08,979 Epoch: [256][0/500] Time 0.021 (0.021) Data 0.204 (0.204) Loss 0.0389 (0.0389) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:09,170 Epoch: [256][10/500] Time 0.017 (0.017) Data 0.001 (0.020) Loss 0.0318 (0.0353) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:09,363 Epoch: [256][20/500] Time 0.016 (0.017) Data 0.001 (0.011) Loss 0.0333 (0.0347) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:09,551 Epoch: [256][30/500] Time 0.016 (0.017) Data 0.001 (0.008) Loss 0.0221 (0.0315) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:09,743 Epoch: [256][40/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0398 (0.0332) Prec@1 93.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 15:46:09,942 Epoch: [256][50/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0439 (0.0350) Prec@1 92.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 15:46:10,130 Epoch: [256][60/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0478 (0.0368) Prec@1 94.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 15:46:10,315 Epoch: [256][70/500] Time 0.015 (0.017) Data 0.001 (0.004) Loss 0.0093 (0.0334) Prec@1 99.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 15:46:10,497 Epoch: [256][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0368 (0.0337) Prec@1 93.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 15:46:10,685 Epoch: [256][90/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0345 (0.0338) Prec@1 94.000 (94.700) Prec@5 99.000 (99.800) +2022-11-14 15:46:10,877 Epoch: [256][100/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0355 (0.0340) Prec@1 94.000 (94.636) Prec@5 100.000 (99.818) +2022-11-14 15:46:11,070 Epoch: [256][110/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0201 (0.0328) Prec@1 98.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 15:46:11,261 Epoch: [256][120/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.0273 (0.0324) Prec@1 97.000 (95.077) Prec@5 100.000 (99.846) +2022-11-14 15:46:11,449 Epoch: [256][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0336 (0.0325) Prec@1 93.000 (94.929) Prec@5 99.000 (99.786) +2022-11-14 15:46:11,642 Epoch: [256][140/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.0255 (0.0320) Prec@1 96.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 15:46:11,830 Epoch: [256][150/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0411 (0.0326) Prec@1 92.000 (94.812) Prec@5 100.000 (99.812) +2022-11-14 15:46:12,023 Epoch: [256][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0236 (0.0321) Prec@1 97.000 (94.941) Prec@5 100.000 (99.824) +2022-11-14 15:46:12,215 Epoch: [256][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0419 (0.0326) Prec@1 94.000 (94.889) Prec@5 100.000 (99.833) +2022-11-14 15:46:12,404 Epoch: [256][180/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0575 (0.0339) Prec@1 91.000 (94.684) Prec@5 100.000 (99.842) +2022-11-14 15:46:12,591 Epoch: [256][190/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0472 (0.0346) Prec@1 92.000 (94.550) Prec@5 99.000 (99.800) +2022-11-14 15:46:12,787 Epoch: [256][200/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0221 (0.0340) Prec@1 97.000 (94.667) Prec@5 100.000 (99.810) +2022-11-14 15:46:12,974 Epoch: [256][210/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0280 (0.0337) Prec@1 94.000 (94.636) Prec@5 100.000 (99.818) +2022-11-14 15:46:13,162 Epoch: [256][220/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0570 (0.0347) Prec@1 92.000 (94.522) Prec@5 100.000 (99.826) +2022-11-14 15:46:13,349 Epoch: [256][230/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0182 (0.0340) Prec@1 98.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 15:46:13,540 Epoch: [256][240/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0303 (0.0339) Prec@1 95.000 (94.680) Prec@5 100.000 (99.840) +2022-11-14 15:46:13,728 Epoch: [256][250/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0605 (0.0349) Prec@1 92.000 (94.577) Prec@5 100.000 (99.846) +2022-11-14 15:46:13,925 Epoch: [256][260/500] Time 0.017 (0.017) Data 0.002 (0.002) Loss 0.0281 (0.0347) Prec@1 97.000 (94.667) Prec@5 100.000 (99.852) +2022-11-14 15:46:14,116 Epoch: [256][270/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0645 (0.0357) Prec@1 90.000 (94.500) Prec@5 100.000 (99.857) +2022-11-14 15:46:14,308 Epoch: [256][280/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0205 (0.0352) Prec@1 96.000 (94.552) Prec@5 100.000 (99.862) +2022-11-14 15:46:14,497 Epoch: [256][290/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0480 (0.0356) Prec@1 90.000 (94.400) Prec@5 99.000 (99.833) +2022-11-14 15:46:14,683 Epoch: [256][300/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0280 (0.0354) Prec@1 94.000 (94.387) Prec@5 100.000 (99.839) +2022-11-14 15:46:14,873 Epoch: [256][310/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0380 (0.0355) Prec@1 94.000 (94.375) Prec@5 100.000 (99.844) +2022-11-14 15:46:15,066 Epoch: [256][320/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.0344 (0.0354) Prec@1 94.000 (94.364) Prec@5 100.000 (99.848) +2022-11-14 15:46:15,260 Epoch: [256][330/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0573 (0.0361) Prec@1 91.000 (94.265) Prec@5 99.000 (99.824) +2022-11-14 15:46:15,448 Epoch: [256][340/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0684 (0.0370) Prec@1 87.000 (94.057) Prec@5 99.000 (99.800) +2022-11-14 15:46:15,632 Epoch: [256][350/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0443 (0.0372) Prec@1 93.000 (94.028) Prec@5 98.000 (99.750) +2022-11-14 15:46:15,826 Epoch: [256][360/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.0431 (0.0374) Prec@1 92.000 (93.973) Prec@5 99.000 (99.730) +2022-11-14 15:46:16,013 Epoch: [256][370/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.0356 (0.0373) Prec@1 93.000 (93.947) Prec@5 100.000 (99.737) +2022-11-14 15:46:16,204 Epoch: [256][380/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.0137 (0.0367) Prec@1 98.000 (94.051) Prec@5 100.000 (99.744) +2022-11-14 15:46:16,400 Epoch: [256][390/500] Time 0.015 (0.017) Data 0.001 (0.002) Loss 0.0249 (0.0364) Prec@1 96.000 (94.100) Prec@5 100.000 (99.750) +2022-11-14 15:46:16,593 Epoch: [256][400/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0223 (0.0361) Prec@1 98.000 (94.195) Prec@5 100.000 (99.756) +2022-11-14 15:46:16,788 Epoch: [256][410/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0332 (0.0360) Prec@1 95.000 (94.214) Prec@5 100.000 (99.762) +2022-11-14 15:46:16,983 Epoch: [256][420/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0270 (0.0358) Prec@1 95.000 (94.233) Prec@5 100.000 (99.767) +2022-11-14 15:46:17,175 Epoch: [256][430/500] Time 0.017 (0.017) Data 0.002 (0.002) Loss 0.0532 (0.0362) Prec@1 92.000 (94.182) Prec@5 100.000 (99.773) +2022-11-14 15:46:17,367 Epoch: [256][440/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0215 (0.0359) Prec@1 97.000 (94.244) Prec@5 100.000 (99.778) +2022-11-14 15:46:17,560 Epoch: [256][450/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0251 (0.0356) Prec@1 96.000 (94.283) Prec@5 100.000 (99.783) +2022-11-14 15:46:17,751 Epoch: [256][460/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0295 (0.0355) Prec@1 96.000 (94.319) Prec@5 100.000 (99.787) +2022-11-14 15:46:17,939 Epoch: [256][470/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0151 (0.0351) Prec@1 98.000 (94.396) Prec@5 99.000 (99.771) +2022-11-14 15:46:18,129 Epoch: [256][480/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0427 (0.0352) Prec@1 93.000 (94.367) Prec@5 99.000 (99.755) +2022-11-14 15:46:18,317 Epoch: [256][490/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0471 (0.0355) Prec@1 90.000 (94.280) Prec@5 100.000 (99.760) +2022-11-14 15:46:18,489 Epoch: [256][499/500] Time 0.018 (0.017) Data 0.001 (0.002) Loss 0.0267 (0.0353) Prec@1 96.000 (94.314) Prec@5 100.000 (99.765) +2022-11-14 15:46:18,738 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0659) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:18,746 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0702) Prec@1 89.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 15:46:18,755 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0679) Prec@1 91.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 15:46:18,765 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0705) Prec@1 85.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 15:46:18,773 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0724) Prec@1 86.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 15:46:18,781 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0672) Prec@1 94.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 15:46:18,789 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0652) Prec@1 92.000 (89.286) Prec@5 100.000 (99.571) +2022-11-14 15:46:18,798 Test: [7/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0683) Prec@1 83.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 15:46:18,810 Test: [8/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0688) Prec@1 89.000 (88.556) Prec@5 99.000 (99.444) +2022-11-14 15:46:18,818 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0713) Prec@1 87.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 15:46:18,826 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0703) Prec@1 90.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 15:46:18,834 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0705) Prec@1 90.000 (88.667) Prec@5 99.000 (99.417) +2022-11-14 15:46:18,845 Test: [12/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0693) Prec@1 91.000 (88.846) Prec@5 100.000 (99.462) +2022-11-14 15:46:18,855 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0698) Prec@1 88.000 (88.786) Prec@5 100.000 (99.500) +2022-11-14 15:46:18,862 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0712) Prec@1 85.000 (88.533) Prec@5 99.000 (99.467) +2022-11-14 15:46:18,871 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0720) Prec@1 84.000 (88.250) Prec@5 99.000 (99.438) +2022-11-14 15:46:18,881 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0712) Prec@1 91.000 (88.412) Prec@5 98.000 (99.353) +2022-11-14 15:46:18,891 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0729) Prec@1 82.000 (88.056) Prec@5 99.000 (99.333) +2022-11-14 15:46:18,900 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0728) Prec@1 87.000 (88.000) Prec@5 100.000 (99.368) +2022-11-14 15:46:18,909 Test: [19/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0737) Prec@1 87.000 (87.950) Prec@5 99.000 (99.350) +2022-11-14 15:46:18,919 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0748) Prec@1 84.000 (87.762) Prec@5 100.000 (99.381) +2022-11-14 15:46:18,928 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0759) Prec@1 84.000 (87.591) Prec@5 98.000 (99.318) +2022-11-14 15:46:18,937 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0766) Prec@1 86.000 (87.522) Prec@5 97.000 (99.217) +2022-11-14 15:46:18,946 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0765) Prec@1 89.000 (87.583) Prec@5 99.000 (99.208) +2022-11-14 15:46:18,956 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0766) Prec@1 88.000 (87.600) Prec@5 100.000 (99.240) +2022-11-14 15:46:18,965 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0764) Prec@1 88.000 (87.615) Prec@5 99.000 (99.231) +2022-11-14 15:46:18,973 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0761) Prec@1 90.000 (87.704) Prec@5 100.000 (99.259) +2022-11-14 15:46:18,982 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0754) Prec@1 91.000 (87.821) Prec@5 100.000 (99.286) +2022-11-14 15:46:18,994 Test: [28/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0751) Prec@1 89.000 (87.862) Prec@5 97.000 (99.207) +2022-11-14 15:46:19,004 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0750) Prec@1 88.000 (87.867) Prec@5 100.000 (99.233) +2022-11-14 15:46:19,014 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0750) Prec@1 88.000 (87.871) Prec@5 99.000 (99.226) +2022-11-14 15:46:19,022 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0751) Prec@1 87.000 (87.844) Prec@5 99.000 (99.219) +2022-11-14 15:46:19,031 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0752) Prec@1 87.000 (87.818) Prec@5 100.000 (99.242) +2022-11-14 15:46:19,038 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0756) Prec@1 82.000 (87.647) Prec@5 100.000 (99.265) +2022-11-14 15:46:19,046 Test: [34/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0761) Prec@1 85.000 (87.571) Prec@5 99.000 (99.257) +2022-11-14 15:46:19,054 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0762) Prec@1 88.000 (87.583) Prec@5 99.000 (99.250) +2022-11-14 15:46:19,065 Test: [36/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0759) Prec@1 90.000 (87.649) Prec@5 100.000 (99.270) +2022-11-14 15:46:19,075 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0765) Prec@1 83.000 (87.526) Prec@5 99.000 (99.263) +2022-11-14 15:46:19,082 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0761) Prec@1 93.000 (87.667) Prec@5 99.000 (99.256) +2022-11-14 15:46:19,091 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0765) Prec@1 86.000 (87.625) Prec@5 99.000 (99.250) +2022-11-14 15:46:19,101 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1033 (0.0771) Prec@1 84.000 (87.537) Prec@5 99.000 (99.244) +2022-11-14 15:46:19,111 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0771) Prec@1 88.000 (87.548) Prec@5 100.000 (99.262) +2022-11-14 15:46:19,118 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0763) Prec@1 92.000 (87.651) Prec@5 100.000 (99.279) +2022-11-14 15:46:19,127 Test: [43/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0760) Prec@1 89.000 (87.682) Prec@5 100.000 (99.295) +2022-11-14 15:46:19,137 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0760) Prec@1 89.000 (87.711) Prec@5 100.000 (99.311) +2022-11-14 15:46:19,147 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0763) Prec@1 85.000 (87.652) Prec@5 99.000 (99.304) +2022-11-14 15:46:19,155 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0759) Prec@1 90.000 (87.702) Prec@5 99.000 (99.298) +2022-11-14 15:46:19,164 Test: [47/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0765) Prec@1 82.000 (87.583) Prec@5 100.000 (99.312) +2022-11-14 15:46:19,172 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0410 (0.0758) Prec@1 94.000 (87.714) Prec@5 100.000 (99.327) +2022-11-14 15:46:19,180 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0762) Prec@1 85.000 (87.660) Prec@5 100.000 (99.340) +2022-11-14 15:46:19,188 Test: [50/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0759) Prec@1 90.000 (87.706) Prec@5 100.000 (99.353) +2022-11-14 15:46:19,197 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0761) Prec@1 83.000 (87.615) Prec@5 100.000 (99.365) +2022-11-14 15:46:19,205 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0761) Prec@1 88.000 (87.623) Prec@5 100.000 (99.377) +2022-11-14 15:46:19,214 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0758) Prec@1 89.000 (87.648) Prec@5 100.000 (99.389) +2022-11-14 15:46:19,223 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1160 (0.0765) Prec@1 84.000 (87.582) Prec@5 100.000 (99.400) +2022-11-14 15:46:19,231 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0765) Prec@1 88.000 (87.589) Prec@5 98.000 (99.375) +2022-11-14 15:46:19,240 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0763) Prec@1 89.000 (87.614) Prec@5 100.000 (99.386) +2022-11-14 15:46:19,249 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0763) Prec@1 88.000 (87.621) Prec@5 99.000 (99.379) +2022-11-14 15:46:19,256 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0769) Prec@1 81.000 (87.508) Prec@5 99.000 (99.373) +2022-11-14 15:46:19,266 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0767) Prec@1 89.000 (87.533) Prec@5 100.000 (99.383) +2022-11-14 15:46:19,275 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0769) Prec@1 87.000 (87.525) Prec@5 98.000 (99.361) +2022-11-14 15:46:19,284 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0770) Prec@1 86.000 (87.500) Prec@5 99.000 (99.355) +2022-11-14 15:46:19,293 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0769) Prec@1 89.000 (87.524) Prec@5 100.000 (99.365) +2022-11-14 15:46:19,301 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0351 (0.0762) Prec@1 95.000 (87.641) Prec@5 100.000 (99.375) +2022-11-14 15:46:19,309 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0763) Prec@1 85.000 (87.600) Prec@5 99.000 (99.369) +2022-11-14 15:46:19,316 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0766) Prec@1 86.000 (87.576) Prec@5 98.000 (99.348) +2022-11-14 15:46:19,325 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0432 (0.0761) Prec@1 91.000 (87.627) Prec@5 100.000 (99.358) +2022-11-14 15:46:19,334 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0758) Prec@1 91.000 (87.676) Prec@5 100.000 (99.368) +2022-11-14 15:46:19,343 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0754) Prec@1 91.000 (87.725) Prec@5 100.000 (99.377) +2022-11-14 15:46:19,353 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0759) Prec@1 82.000 (87.643) Prec@5 98.000 (99.357) +2022-11-14 15:46:19,362 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0761) Prec@1 86.000 (87.620) Prec@5 100.000 (99.366) +2022-11-14 15:46:19,371 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0761) Prec@1 87.000 (87.611) Prec@5 100.000 (99.375) +2022-11-14 15:46:19,380 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0438 (0.0756) Prec@1 94.000 (87.699) Prec@5 99.000 (99.370) +2022-11-14 15:46:19,389 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0753) Prec@1 92.000 (87.757) Prec@5 100.000 (99.378) +2022-11-14 15:46:19,399 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0758) Prec@1 82.000 (87.680) Prec@5 100.000 (99.387) +2022-11-14 15:46:19,408 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0755) Prec@1 90.000 (87.711) Prec@5 99.000 (99.382) +2022-11-14 15:46:19,417 Test: [76/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0757) Prec@1 86.000 (87.688) Prec@5 98.000 (99.364) +2022-11-14 15:46:19,427 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0761) Prec@1 82.000 (87.615) Prec@5 99.000 (99.359) +2022-11-14 15:46:19,436 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0761) Prec@1 88.000 (87.620) Prec@5 100.000 (99.367) +2022-11-14 15:46:19,445 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0761) Prec@1 90.000 (87.650) Prec@5 100.000 (99.375) +2022-11-14 15:46:19,455 Test: [80/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0762) Prec@1 88.000 (87.654) Prec@5 99.000 (99.370) +2022-11-14 15:46:19,463 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0762) Prec@1 88.000 (87.659) Prec@5 100.000 (99.378) +2022-11-14 15:46:19,472 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0761) Prec@1 89.000 (87.675) Prec@5 100.000 (99.386) +2022-11-14 15:46:19,480 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0760) Prec@1 86.000 (87.655) Prec@5 100.000 (99.393) +2022-11-14 15:46:19,488 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0762) Prec@1 86.000 (87.635) Prec@5 98.000 (99.376) +2022-11-14 15:46:19,497 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.0765) Prec@1 83.000 (87.581) Prec@5 100.000 (99.384) +2022-11-14 15:46:19,507 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0765) Prec@1 85.000 (87.552) Prec@5 100.000 (99.391) +2022-11-14 15:46:19,515 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0764) Prec@1 88.000 (87.557) Prec@5 98.000 (99.375) +2022-11-14 15:46:19,524 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0764) Prec@1 87.000 (87.551) Prec@5 100.000 (99.382) +2022-11-14 15:46:19,533 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0765) Prec@1 87.000 (87.544) Prec@5 99.000 (99.378) +2022-11-14 15:46:19,542 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0766) Prec@1 86.000 (87.527) Prec@5 100.000 (99.385) +2022-11-14 15:46:19,551 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0763) Prec@1 93.000 (87.587) Prec@5 100.000 (99.391) +2022-11-14 15:46:19,560 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0764) Prec@1 89.000 (87.602) Prec@5 99.000 (99.387) +2022-11-14 15:46:19,570 Test: [93/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0761) Prec@1 93.000 (87.660) Prec@5 100.000 (99.394) +2022-11-14 15:46:19,579 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0760) Prec@1 88.000 (87.663) Prec@5 99.000 (99.389) +2022-11-14 15:46:19,587 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0759) Prec@1 88.000 (87.667) Prec@5 99.000 (99.385) +2022-11-14 15:46:19,595 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0757) Prec@1 91.000 (87.701) Prec@5 99.000 (99.381) +2022-11-14 15:46:19,603 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0759) Prec@1 85.000 (87.673) Prec@5 99.000 (99.378) +2022-11-14 15:46:19,612 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0761) Prec@1 86.000 (87.657) Prec@5 100.000 (99.384) +2022-11-14 15:46:19,621 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0759) Prec@1 90.000 (87.680) Prec@5 100.000 (99.390) +2022-11-14 15:46:19,673 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:46:19,972 Epoch: [257][0/500] Time 0.022 (0.022) Data 0.222 (0.222) Loss 0.0267 (0.0267) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:20,174 Epoch: [257][10/500] Time 0.018 (0.018) Data 0.001 (0.022) Loss 0.0418 (0.0342) Prec@1 92.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 15:46:20,366 Epoch: [257][20/500] Time 0.017 (0.018) Data 0.001 (0.012) Loss 0.0353 (0.0346) Prec@1 94.000 (93.667) Prec@5 99.000 (99.333) +2022-11-14 15:46:20,554 Epoch: [257][30/500] Time 0.016 (0.017) Data 0.001 (0.009) Loss 0.0384 (0.0356) Prec@1 94.000 (93.750) Prec@5 100.000 (99.500) +2022-11-14 15:46:20,746 Epoch: [257][40/500] Time 0.019 (0.017) Data 0.001 (0.007) Loss 0.0340 (0.0352) Prec@1 95.000 (94.000) Prec@5 100.000 (99.600) +2022-11-14 15:46:20,956 Epoch: [257][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0451 (0.0369) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 15:46:21,147 Epoch: [257][60/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0491 (0.0386) Prec@1 92.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 15:46:21,336 Epoch: [257][70/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0284 (0.0373) Prec@1 96.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 15:46:21,523 Epoch: [257][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0323 (0.0368) Prec@1 94.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 15:46:21,717 Epoch: [257][90/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0493 (0.0380) Prec@1 92.000 (93.800) Prec@5 100.000 (99.700) +2022-11-14 15:46:21,912 Epoch: [257][100/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0376 (0.0380) Prec@1 93.000 (93.727) Prec@5 100.000 (99.727) +2022-11-14 15:46:22,107 Epoch: [257][110/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0259 (0.0370) Prec@1 97.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 15:46:22,301 Epoch: [257][120/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0135 (0.0352) Prec@1 98.000 (94.308) Prec@5 100.000 (99.769) +2022-11-14 15:46:22,493 Epoch: [257][130/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0355 (0.0352) Prec@1 95.000 (94.357) Prec@5 100.000 (99.786) +2022-11-14 15:46:22,684 Epoch: [257][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0284 (0.0347) Prec@1 96.000 (94.467) Prec@5 100.000 (99.800) +2022-11-14 15:46:22,875 Epoch: [257][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0290 (0.0344) Prec@1 96.000 (94.562) Prec@5 100.000 (99.812) +2022-11-14 15:46:23,068 Epoch: [257][160/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0547 (0.0356) Prec@1 91.000 (94.353) Prec@5 99.000 (99.765) +2022-11-14 15:46:23,263 Epoch: [257][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0344 (0.0355) Prec@1 93.000 (94.278) Prec@5 100.000 (99.778) +2022-11-14 15:46:23,464 Epoch: [257][180/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0218 (0.0348) Prec@1 97.000 (94.421) Prec@5 100.000 (99.789) +2022-11-14 15:46:23,662 Epoch: [257][190/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0218 (0.0341) Prec@1 96.000 (94.500) Prec@5 100.000 (99.800) +2022-11-14 15:46:23,862 Epoch: [257][200/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0243 (0.0337) Prec@1 97.000 (94.619) Prec@5 100.000 (99.810) +2022-11-14 15:46:24,059 Epoch: [257][210/500] Time 0.020 (0.017) Data 0.002 (0.002) Loss 0.0104 (0.0326) Prec@1 98.000 (94.773) Prec@5 100.000 (99.818) +2022-11-14 15:46:24,268 Epoch: [257][220/500] Time 0.016 (0.017) Data 0.001 (0.002) Loss 0.0415 (0.0330) Prec@1 92.000 (94.652) Prec@5 100.000 (99.826) +2022-11-14 15:46:24,478 Epoch: [257][230/500] Time 0.019 (0.017) Data 0.002 (0.002) Loss 0.0285 (0.0328) Prec@1 96.000 (94.708) Prec@5 100.000 (99.833) +2022-11-14 15:46:24,684 Epoch: [257][240/500] Time 0.022 (0.017) Data 0.002 (0.002) Loss 0.0398 (0.0331) Prec@1 93.000 (94.640) Prec@5 100.000 (99.840) +2022-11-14 15:46:24,892 Epoch: [257][250/500] Time 0.018 (0.018) Data 0.002 (0.002) Loss 0.0565 (0.0340) Prec@1 90.000 (94.462) Prec@5 99.000 (99.808) +2022-11-14 15:46:25,100 Epoch: [257][260/500] Time 0.020 (0.018) Data 0.002 (0.002) Loss 0.0628 (0.0351) Prec@1 90.000 (94.296) Prec@5 100.000 (99.815) +2022-11-14 15:46:25,308 Epoch: [257][270/500] Time 0.018 (0.018) Data 0.002 (0.002) Loss 0.0195 (0.0345) Prec@1 98.000 (94.429) Prec@5 100.000 (99.821) +2022-11-14 15:46:25,535 Epoch: [257][280/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0356 (0.0345) Prec@1 91.000 (94.310) Prec@5 99.000 (99.793) +2022-11-14 15:46:25,772 Epoch: [257][290/500] Time 0.020 (0.018) Data 0.002 (0.002) Loss 0.0231 (0.0342) Prec@1 97.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:46:26,000 Epoch: [257][300/500] Time 0.021 (0.018) Data 0.002 (0.002) Loss 0.0261 (0.0339) Prec@1 94.000 (94.387) Prec@5 100.000 (99.806) +2022-11-14 15:46:26,251 Epoch: [257][310/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0399 (0.0341) Prec@1 91.000 (94.281) Prec@5 100.000 (99.812) +2022-11-14 15:46:26,501 Epoch: [257][320/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0221 (0.0337) Prec@1 96.000 (94.333) Prec@5 100.000 (99.818) +2022-11-14 15:46:26,704 Epoch: [257][330/500] Time 0.016 (0.018) Data 0.002 (0.002) Loss 0.0351 (0.0338) Prec@1 93.000 (94.294) Prec@5 100.000 (99.824) +2022-11-14 15:46:26,926 Epoch: [257][340/500] Time 0.026 (0.018) Data 0.002 (0.002) Loss 0.0437 (0.0341) Prec@1 94.000 (94.286) Prec@5 100.000 (99.829) +2022-11-14 15:46:27,164 Epoch: [257][350/500] Time 0.021 (0.018) Data 0.002 (0.002) Loss 0.0171 (0.0336) Prec@1 98.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 15:46:27,394 Epoch: [257][360/500] Time 0.022 (0.018) Data 0.002 (0.002) Loss 0.0494 (0.0340) Prec@1 90.000 (94.270) Prec@5 100.000 (99.838) +2022-11-14 15:46:27,619 Epoch: [257][370/500] Time 0.020 (0.018) Data 0.002 (0.002) Loss 0.0414 (0.0342) Prec@1 94.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 15:46:27,848 Epoch: [257][380/500] Time 0.021 (0.018) Data 0.002 (0.002) Loss 0.0478 (0.0346) Prec@1 93.000 (94.231) Prec@5 100.000 (99.846) +2022-11-14 15:46:28,046 Epoch: [257][390/500] Time 0.017 (0.018) Data 0.001 (0.002) Loss 0.0345 (0.0345) Prec@1 93.000 (94.200) Prec@5 100.000 (99.850) +2022-11-14 15:46:28,249 Epoch: [257][400/500] Time 0.019 (0.018) Data 0.002 (0.002) Loss 0.0360 (0.0346) Prec@1 94.000 (94.195) Prec@5 99.000 (99.829) +2022-11-14 15:46:28,462 Epoch: [257][410/500] Time 0.022 (0.018) Data 0.002 (0.002) Loss 0.0236 (0.0343) Prec@1 97.000 (94.262) Prec@5 100.000 (99.833) +2022-11-14 15:46:28,663 Epoch: [257][420/500] Time 0.021 (0.018) Data 0.001 (0.002) Loss 0.0438 (0.0345) Prec@1 92.000 (94.209) Prec@5 99.000 (99.814) +2022-11-14 15:46:28,861 Epoch: [257][430/500] Time 0.018 (0.018) Data 0.002 (0.002) Loss 0.0045 (0.0339) Prec@1 100.000 (94.341) Prec@5 100.000 (99.818) +2022-11-14 15:46:29,065 Epoch: [257][440/500] Time 0.018 (0.018) Data 0.001 (0.002) Loss 0.0546 (0.0343) Prec@1 92.000 (94.289) Prec@5 99.000 (99.800) +2022-11-14 15:46:29,281 Epoch: [257][450/500] Time 0.024 (0.018) Data 0.001 (0.002) Loss 0.0240 (0.0341) Prec@1 95.000 (94.304) Prec@5 100.000 (99.804) +2022-11-14 15:46:29,490 Epoch: [257][460/500] Time 0.018 (0.018) Data 0.002 (0.002) Loss 0.0573 (0.0346) Prec@1 91.000 (94.234) Prec@5 100.000 (99.809) +2022-11-14 15:46:29,706 Epoch: [257][470/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0339 (0.0346) Prec@1 94.000 (94.229) Prec@5 100.000 (99.812) +2022-11-14 15:46:29,909 Epoch: [257][480/500] Time 0.017 (0.018) Data 0.001 (0.002) Loss 0.0220 (0.0343) Prec@1 97.000 (94.286) Prec@5 100.000 (99.816) +2022-11-14 15:46:30,124 Epoch: [257][490/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0214 (0.0341) Prec@1 96.000 (94.320) Prec@5 100.000 (99.820) +2022-11-14 15:46:30,306 Epoch: [257][499/500] Time 0.017 (0.018) Data 0.001 (0.002) Loss 0.0542 (0.0345) Prec@1 93.000 (94.294) Prec@5 100.000 (99.824) +2022-11-14 15:46:30,601 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0518 (0.0518) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:30,608 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0596) Prec@1 87.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:30,618 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0632) Prec@1 90.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 15:46:30,629 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0672) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 15:46:30,637 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0689) Prec@1 88.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 15:46:30,647 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0680) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 15:46:30,655 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0682) Prec@1 89.000 (88.571) Prec@5 100.000 (99.571) +2022-11-14 15:46:30,665 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0722) Prec@1 81.000 (87.625) Prec@5 99.000 (99.500) +2022-11-14 15:46:30,672 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0734) Prec@1 83.000 (87.111) Prec@5 100.000 (99.556) +2022-11-14 15:46:30,680 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0733) Prec@1 86.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 15:46:30,688 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0725) Prec@1 90.000 (87.273) Prec@5 100.000 (99.545) +2022-11-14 15:46:30,696 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0717) Prec@1 89.000 (87.417) Prec@5 100.000 (99.583) +2022-11-14 15:46:30,705 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0711) Prec@1 89.000 (87.538) Prec@5 99.000 (99.538) +2022-11-14 15:46:30,715 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0717) Prec@1 89.000 (87.643) Prec@5 99.000 (99.500) +2022-11-14 15:46:30,724 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0709) Prec@1 89.000 (87.733) Prec@5 100.000 (99.533) +2022-11-14 15:46:30,734 Test: [15/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0722) Prec@1 86.000 (87.625) Prec@5 100.000 (99.562) +2022-11-14 15:46:30,743 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0710) Prec@1 93.000 (87.941) Prec@5 99.000 (99.529) +2022-11-14 15:46:30,752 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0728) Prec@1 83.000 (87.667) Prec@5 100.000 (99.556) +2022-11-14 15:46:30,762 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0741) Prec@1 84.000 (87.474) Prec@5 99.000 (99.526) +2022-11-14 15:46:30,772 Test: [19/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0745) Prec@1 88.000 (87.500) Prec@5 100.000 (99.550) +2022-11-14 15:46:30,782 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0745) Prec@1 87.000 (87.476) Prec@5 99.000 (99.524) +2022-11-14 15:46:30,791 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0749) Prec@1 85.000 (87.364) Prec@5 99.000 (99.500) +2022-11-14 15:46:30,800 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0755) Prec@1 87.000 (87.348) Prec@5 98.000 (99.435) +2022-11-14 15:46:30,810 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0768) Prec@1 83.000 (87.167) Prec@5 100.000 (99.458) +2022-11-14 15:46:30,819 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0769) Prec@1 85.000 (87.080) Prec@5 100.000 (99.480) +2022-11-14 15:46:30,829 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0772) Prec@1 86.000 (87.038) Prec@5 99.000 (99.462) +2022-11-14 15:46:30,839 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0769) Prec@1 89.000 (87.111) Prec@5 100.000 (99.481) +2022-11-14 15:46:30,848 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0764) Prec@1 90.000 (87.214) Prec@5 100.000 (99.500) +2022-11-14 15:46:30,857 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0760) Prec@1 90.000 (87.310) Prec@5 99.000 (99.483) +2022-11-14 15:46:30,866 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0763) Prec@1 85.000 (87.233) Prec@5 98.000 (99.433) +2022-11-14 15:46:30,876 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0764) Prec@1 88.000 (87.258) Prec@5 100.000 (99.452) +2022-11-14 15:46:30,885 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0761) Prec@1 90.000 (87.344) Prec@5 99.000 (99.438) +2022-11-14 15:46:30,895 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0764) Prec@1 86.000 (87.303) Prec@5 100.000 (99.455) +2022-11-14 15:46:30,905 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.0772) Prec@1 84.000 (87.206) Prec@5 100.000 (99.471) +2022-11-14 15:46:30,914 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0774) Prec@1 87.000 (87.200) Prec@5 99.000 (99.457) +2022-11-14 15:46:30,923 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0770) Prec@1 89.000 (87.250) Prec@5 100.000 (99.472) +2022-11-14 15:46:30,932 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0768) Prec@1 88.000 (87.270) Prec@5 99.000 (99.459) +2022-11-14 15:46:30,941 Test: [37/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1251 (0.0781) Prec@1 75.000 (86.947) Prec@5 99.000 (99.447) +2022-11-14 15:46:30,950 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0775) Prec@1 93.000 (87.103) Prec@5 98.000 (99.410) +2022-11-14 15:46:30,960 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0770) Prec@1 90.000 (87.175) Prec@5 99.000 (99.400) +2022-11-14 15:46:30,968 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0770) Prec@1 88.000 (87.195) Prec@5 98.000 (99.366) +2022-11-14 15:46:30,977 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0771) Prec@1 88.000 (87.214) Prec@5 99.000 (99.357) +2022-11-14 15:46:30,985 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0437 (0.0763) Prec@1 94.000 (87.372) Prec@5 99.000 (99.349) +2022-11-14 15:46:30,994 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0764) Prec@1 88.000 (87.386) Prec@5 96.000 (99.273) +2022-11-14 15:46:31,003 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0760) Prec@1 90.000 (87.444) Prec@5 100.000 (99.289) +2022-11-14 15:46:31,013 Test: [45/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0768) Prec@1 82.000 (87.326) Prec@5 99.000 (99.283) +2022-11-14 15:46:31,023 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0766) Prec@1 89.000 (87.362) Prec@5 100.000 (99.298) +2022-11-14 15:46:31,033 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0768) Prec@1 85.000 (87.312) Prec@5 99.000 (99.292) +2022-11-14 15:46:31,043 Test: [48/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0762) Prec@1 89.000 (87.347) Prec@5 100.000 (99.306) +2022-11-14 15:46:31,051 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0765) Prec@1 87.000 (87.340) Prec@5 98.000 (99.280) +2022-11-14 15:46:31,061 Test: 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Loss 0.0637 (0.0756) Prec@1 90.000 (87.526) Prec@5 100.000 (99.351) +2022-11-14 15:46:31,135 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0755) Prec@1 89.000 (87.552) Prec@5 100.000 (99.362) +2022-11-14 15:46:31,145 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0758) Prec@1 86.000 (87.525) Prec@5 98.000 (99.339) +2022-11-14 15:46:31,155 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0760) Prec@1 86.000 (87.500) Prec@5 100.000 (99.350) +2022-11-14 15:46:31,165 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0757) Prec@1 92.000 (87.574) Prec@5 100.000 (99.361) +2022-11-14 15:46:31,175 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0752) Prec@1 94.000 (87.677) Prec@5 100.000 (99.371) +2022-11-14 15:46:31,186 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0750) Prec@1 90.000 (87.714) Prec@5 99.000 (99.365) +2022-11-14 15:46:31,196 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0293 (0.0743) Prec@1 95.000 (87.828) Prec@5 100.000 (99.375) +2022-11-14 15:46:31,205 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0747) Prec@1 85.000 (87.785) Prec@5 98.000 (99.354) +2022-11-14 15:46:31,215 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0747) Prec@1 86.000 (87.758) Prec@5 100.000 (99.364) +2022-11-14 15:46:31,224 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0381 (0.0741) Prec@1 94.000 (87.851) Prec@5 100.000 (99.373) +2022-11-14 15:46:31,234 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0738) Prec@1 91.000 (87.897) Prec@5 98.000 (99.353) +2022-11-14 15:46:31,244 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0736) Prec@1 90.000 (87.928) Prec@5 99.000 (99.348) +2022-11-14 15:46:31,254 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0738) Prec@1 88.000 (87.929) Prec@5 99.000 (99.343) +2022-11-14 15:46:31,263 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0743) Prec@1 84.000 (87.873) Prec@5 98.000 (99.324) +2022-11-14 15:46:31,272 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0740) Prec@1 93.000 (87.944) Prec@5 100.000 (99.333) +2022-11-14 15:46:31,281 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0738) Prec@1 88.000 (87.945) Prec@5 100.000 (99.342) +2022-11-14 15:46:31,289 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0734) Prec@1 94.000 (88.027) Prec@5 100.000 (99.351) +2022-11-14 15:46:31,299 Test: [74/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0737) Prec@1 82.000 (87.947) Prec@5 100.000 (99.360) +2022-11-14 15:46:31,309 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0735) Prec@1 90.000 (87.974) Prec@5 98.000 (99.342) +2022-11-14 15:46:31,318 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0735) Prec@1 87.000 (87.961) Prec@5 99.000 (99.338) +2022-11-14 15:46:31,327 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0738) Prec@1 84.000 (87.910) Prec@5 98.000 (99.321) +2022-11-14 15:46:31,336 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0738) Prec@1 88.000 (87.911) Prec@5 100.000 (99.329) +2022-11-14 15:46:31,346 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0741) Prec@1 86.000 (87.888) Prec@5 100.000 (99.338) +2022-11-14 15:46:31,355 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0743) Prec@1 85.000 (87.852) Prec@5 99.000 (99.333) +2022-11-14 15:46:31,365 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0746) Prec@1 83.000 (87.793) Prec@5 99.000 (99.329) +2022-11-14 15:46:31,374 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0746) Prec@1 89.000 (87.807) Prec@5 100.000 (99.337) +2022-11-14 15:46:31,384 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0745) Prec@1 88.000 (87.810) Prec@5 99.000 (99.333) +2022-11-14 15:46:31,395 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0746) Prec@1 85.000 (87.776) Prec@5 100.000 (99.341) +2022-11-14 15:46:31,405 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0749) Prec@1 83.000 (87.721) Prec@5 99.000 (99.337) +2022-11-14 15:46:31,414 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0751) Prec@1 85.000 (87.690) Prec@5 100.000 (99.345) +2022-11-14 15:46:31,425 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0750) Prec@1 89.000 (87.705) Prec@5 99.000 (99.341) +2022-11-14 15:46:31,436 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0750) Prec@1 87.000 (87.697) Prec@5 99.000 (99.337) +2022-11-14 15:46:31,446 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0752) Prec@1 87.000 (87.689) Prec@5 100.000 (99.344) +2022-11-14 15:46:31,456 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0751) Prec@1 89.000 (87.703) Prec@5 100.000 (99.352) +2022-11-14 15:46:31,465 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0749) Prec@1 90.000 (87.728) Prec@5 100.000 (99.359) +2022-11-14 15:46:31,473 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0753) Prec@1 84.000 (87.688) Prec@5 100.000 (99.366) +2022-11-14 15:46:31,482 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0754) Prec@1 86.000 (87.670) Prec@5 98.000 (99.351) +2022-11-14 15:46:31,491 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0756) Prec@1 84.000 (87.632) Prec@5 98.000 (99.337) +2022-11-14 15:46:31,500 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0755) Prec@1 90.000 (87.656) Prec@5 99.000 (99.333) +2022-11-14 15:46:31,508 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0751) Prec@1 94.000 (87.722) Prec@5 99.000 (99.330) +2022-11-14 15:46:31,517 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0754) Prec@1 86.000 (87.704) Prec@5 95.000 (99.286) +2022-11-14 15:46:31,527 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0755) Prec@1 85.000 (87.677) Prec@5 99.000 (99.283) +2022-11-14 15:46:31,537 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0755) Prec@1 88.000 (87.680) Prec@5 100.000 (99.290) +2022-11-14 15:46:31,592 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:46:31,898 Epoch: [258][0/500] Time 0.027 (0.027) Data 0.220 (0.220) Loss 0.0679 (0.0679) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 15:46:32,118 Epoch: [258][10/500] Time 0.023 (0.020) Data 0.002 (0.022) Loss 0.0420 (0.0550) Prec@1 92.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 15:46:32,333 Epoch: [258][20/500] Time 0.021 (0.020) Data 0.001 (0.012) Loss 0.0293 (0.0464) Prec@1 95.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 15:46:32,533 Epoch: [258][30/500] Time 0.017 (0.019) Data 0.002 (0.009) Loss 0.0203 (0.0399) Prec@1 97.000 (92.750) Prec@5 100.000 (99.750) +2022-11-14 15:46:32,743 Epoch: [258][40/500] Time 0.020 (0.019) Data 0.002 (0.007) Loss 0.0519 (0.0423) Prec@1 92.000 (92.600) Prec@5 100.000 (99.800) +2022-11-14 15:46:32,983 Epoch: [258][50/500] Time 0.023 (0.020) Data 0.002 (0.006) Loss 0.0427 (0.0423) Prec@1 93.000 (92.667) Prec@5 100.000 (99.833) +2022-11-14 15:46:33,217 Epoch: [258][60/500] Time 0.022 (0.020) Data 0.002 (0.005) Loss 0.0175 (0.0388) Prec@1 98.000 (93.429) Prec@5 100.000 (99.857) +2022-11-14 15:46:33,445 Epoch: [258][70/500] Time 0.021 (0.020) Data 0.001 (0.005) Loss 0.0450 (0.0396) Prec@1 94.000 (93.500) Prec@5 99.000 (99.750) +2022-11-14 15:46:33,674 Epoch: [258][80/500] Time 0.023 (0.020) Data 0.001 (0.004) Loss 0.0238 (0.0378) Prec@1 96.000 (93.778) Prec@5 100.000 (99.778) +2022-11-14 15:46:33,904 Epoch: [258][90/500] Time 0.020 (0.020) Data 0.001 (0.004) Loss 0.0375 (0.0378) Prec@1 94.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 15:46:34,152 Epoch: [258][100/500] Time 0.021 (0.020) Data 0.002 (0.004) Loss 0.0280 (0.0369) Prec@1 95.000 (93.909) Prec@5 99.000 (99.727) +2022-11-14 15:46:34,394 Epoch: [258][110/500] Time 0.020 (0.020) Data 0.002 (0.004) Loss 0.0335 (0.0366) Prec@1 93.000 (93.833) Prec@5 99.000 (99.667) +2022-11-14 15:46:34,637 Epoch: [258][120/500] Time 0.021 (0.020) Data 0.002 (0.003) Loss 0.0230 (0.0356) Prec@1 97.000 (94.077) Prec@5 100.000 (99.692) +2022-11-14 15:46:34,873 Epoch: [258][130/500] Time 0.019 (0.020) Data 0.002 (0.003) Loss 0.0384 (0.0358) Prec@1 93.000 (94.000) Prec@5 100.000 (99.714) +2022-11-14 15:46:35,100 Epoch: [258][140/500] Time 0.021 (0.020) Data 0.001 (0.003) Loss 0.0373 (0.0359) Prec@1 93.000 (93.933) Prec@5 100.000 (99.733) +2022-11-14 15:46:35,347 Epoch: [258][150/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0352 (0.0358) Prec@1 94.000 (93.938) Prec@5 100.000 (99.750) +2022-11-14 15:46:35,588 Epoch: [258][160/500] Time 0.020 (0.021) Data 0.002 (0.003) Loss 0.0261 (0.0353) Prec@1 95.000 (94.000) Prec@5 100.000 (99.765) +2022-11-14 15:46:35,824 Epoch: [258][170/500] Time 0.018 (0.021) Data 0.002 (0.003) Loss 0.0202 (0.0344) Prec@1 98.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 15:46:36,069 Epoch: [258][180/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0403 (0.0347) Prec@1 93.000 (94.158) Prec@5 99.000 (99.737) +2022-11-14 15:46:36,310 Epoch: [258][190/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0540 (0.0357) Prec@1 92.000 (94.050) Prec@5 100.000 (99.750) +2022-11-14 15:46:36,553 Epoch: [258][200/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0308 (0.0355) Prec@1 96.000 (94.143) Prec@5 100.000 (99.762) +2022-11-14 15:46:36,794 Epoch: [258][210/500] Time 0.019 (0.021) Data 0.002 (0.003) Loss 0.0271 (0.0351) Prec@1 96.000 (94.227) Prec@5 100.000 (99.773) +2022-11-14 15:46:37,040 Epoch: [258][220/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0515 (0.0358) Prec@1 90.000 (94.043) Prec@5 99.000 (99.739) +2022-11-14 15:46:37,279 Epoch: [258][230/500] Time 0.018 (0.021) Data 0.001 (0.003) Loss 0.0433 (0.0361) Prec@1 94.000 (94.042) Prec@5 100.000 (99.750) +2022-11-14 15:46:37,516 Epoch: [258][240/500] Time 0.021 (0.021) Data 0.001 (0.003) Loss 0.0528 (0.0368) Prec@1 90.000 (93.880) Prec@5 100.000 (99.760) +2022-11-14 15:46:37,745 Epoch: [258][250/500] Time 0.020 (0.021) Data 0.001 (0.003) Loss 0.0411 (0.0369) Prec@1 94.000 (93.885) Prec@5 100.000 (99.769) +2022-11-14 15:46:37,966 Epoch: [258][260/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0361 (0.0369) Prec@1 94.000 (93.889) Prec@5 100.000 (99.778) +2022-11-14 15:46:38,186 Epoch: [258][270/500] Time 0.018 (0.021) Data 0.001 (0.002) Loss 0.0281 (0.0366) Prec@1 97.000 (94.000) Prec@5 100.000 (99.786) +2022-11-14 15:46:38,409 Epoch: [258][280/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0484 (0.0370) Prec@1 92.000 (93.931) Prec@5 99.000 (99.759) +2022-11-14 15:46:38,643 Epoch: [258][290/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0294 (0.0368) Prec@1 96.000 (94.000) Prec@5 100.000 (99.767) +2022-11-14 15:46:38,870 Epoch: [258][300/500] Time 0.020 (0.021) Data 0.001 (0.002) Loss 0.0446 (0.0370) Prec@1 92.000 (93.935) Prec@5 99.000 (99.742) +2022-11-14 15:46:39,108 Epoch: [258][310/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0436 (0.0372) Prec@1 92.000 (93.875) Prec@5 98.000 (99.688) +2022-11-14 15:46:39,342 Epoch: [258][320/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0464 (0.0375) Prec@1 94.000 (93.879) Prec@5 100.000 (99.697) +2022-11-14 15:46:39,573 Epoch: [258][330/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0308 (0.0373) Prec@1 94.000 (93.882) Prec@5 100.000 (99.706) +2022-11-14 15:46:39,804 Epoch: [258][340/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0589 (0.0379) Prec@1 90.000 (93.771) Prec@5 98.000 (99.657) +2022-11-14 15:46:40,037 Epoch: [258][350/500] Time 0.019 (0.021) Data 0.001 (0.002) Loss 0.0224 (0.0375) Prec@1 95.000 (93.806) Prec@5 100.000 (99.667) +2022-11-14 15:46:40,273 Epoch: [258][360/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0503 (0.0378) Prec@1 92.000 (93.757) Prec@5 99.000 (99.649) +2022-11-14 15:46:40,507 Epoch: [258][370/500] Time 0.020 (0.021) Data 0.001 (0.002) Loss 0.0226 (0.0374) Prec@1 97.000 (93.842) Prec@5 100.000 (99.658) +2022-11-14 15:46:40,732 Epoch: [258][380/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0269 (0.0372) Prec@1 95.000 (93.872) Prec@5 100.000 (99.667) +2022-11-14 15:46:40,963 Epoch: [258][390/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0173 (0.0367) Prec@1 96.000 (93.925) Prec@5 100.000 (99.675) +2022-11-14 15:46:41,202 Epoch: [258][400/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0650 (0.0374) Prec@1 88.000 (93.780) Prec@5 99.000 (99.659) +2022-11-14 15:46:41,435 Epoch: [258][410/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0320 (0.0372) Prec@1 95.000 (93.810) Prec@5 100.000 (99.667) +2022-11-14 15:46:41,664 Epoch: [258][420/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0332 (0.0371) Prec@1 96.000 (93.860) Prec@5 100.000 (99.674) +2022-11-14 15:46:41,896 Epoch: [258][430/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0429 (0.0373) Prec@1 91.000 (93.795) Prec@5 100.000 (99.682) +2022-11-14 15:46:42,129 Epoch: [258][440/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0303 (0.0371) Prec@1 96.000 (93.844) Prec@5 100.000 (99.689) +2022-11-14 15:46:42,367 Epoch: [258][450/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0386 (0.0371) Prec@1 93.000 (93.826) Prec@5 99.000 (99.674) +2022-11-14 15:46:42,601 Epoch: [258][460/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0373 (0.0371) Prec@1 93.000 (93.809) Prec@5 100.000 (99.681) +2022-11-14 15:46:42,835 Epoch: [258][470/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0614 (0.0376) Prec@1 91.000 (93.750) Prec@5 100.000 (99.688) +2022-11-14 15:46:43,068 Epoch: [258][480/500] Time 0.018 (0.021) Data 0.002 (0.002) Loss 0.0290 (0.0375) Prec@1 94.000 (93.755) Prec@5 100.000 (99.694) +2022-11-14 15:46:43,292 Epoch: [258][490/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.0322 (0.0374) Prec@1 93.000 (93.740) Prec@5 100.000 (99.700) +2022-11-14 15:46:43,502 Epoch: [258][499/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0398 (0.0374) Prec@1 93.000 (93.725) Prec@5 100.000 (99.706) +2022-11-14 15:46:43,795 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0635 (0.0635) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:43,804 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0624) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:43,813 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0640) Prec@1 91.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 15:46:43,828 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0656) Prec@1 86.000 (88.750) Prec@5 100.000 (100.000) +2022-11-14 15:46:43,839 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0676) Prec@1 89.000 (88.800) Prec@5 99.000 (99.800) +2022-11-14 15:46:43,851 Test: [5/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0539 (0.0653) Prec@1 92.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 15:46:43,860 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0518 (0.0634) Prec@1 92.000 (89.714) Prec@5 99.000 (99.714) +2022-11-14 15:46:43,876 Test: [7/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0673) Prec@1 83.000 (88.875) Prec@5 99.000 (99.625) +2022-11-14 15:46:43,887 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0686) Prec@1 88.000 (88.778) Prec@5 99.000 (99.556) +2022-11-14 15:46:43,897 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0691) Prec@1 90.000 (88.900) Prec@5 98.000 (99.400) +2022-11-14 15:46:43,908 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0615 (0.0684) Prec@1 88.000 (88.818) Prec@5 99.000 (99.364) +2022-11-14 15:46:43,918 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0697) Prec@1 88.000 (88.750) Prec@5 99.000 (99.333) +2022-11-14 15:46:43,929 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0611 (0.0690) Prec@1 89.000 (88.769) Prec@5 100.000 (99.385) +2022-11-14 15:46:43,940 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0733 (0.0694) Prec@1 88.000 (88.714) Prec@5 99.000 (99.357) +2022-11-14 15:46:43,954 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0698) Prec@1 88.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 15:46:43,964 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0703) Prec@1 86.000 (88.500) Prec@5 100.000 (99.375) +2022-11-14 15:46:43,974 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0695) Prec@1 89.000 (88.529) Prec@5 99.000 (99.353) +2022-11-14 15:46:43,986 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0716) Prec@1 82.000 (88.167) Prec@5 100.000 (99.389) +2022-11-14 15:46:43,996 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0718) Prec@1 86.000 (88.053) Prec@5 99.000 (99.368) +2022-11-14 15:46:44,006 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0726) Prec@1 88.000 (88.050) Prec@5 97.000 (99.250) +2022-11-14 15:46:44,015 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0729) Prec@1 87.000 (88.000) Prec@5 99.000 (99.238) +2022-11-14 15:46:44,026 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0729) Prec@1 89.000 (88.045) Prec@5 98.000 (99.182) +2022-11-14 15:46:44,037 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0730) Prec@1 87.000 (88.000) Prec@5 97.000 (99.087) +2022-11-14 15:46:44,050 Test: [23/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0729) Prec@1 85.000 (87.875) Prec@5 100.000 (99.125) +2022-11-14 15:46:44,061 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0733) Prec@1 87.000 (87.840) Prec@5 100.000 (99.160) +2022-11-14 15:46:44,069 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0739) Prec@1 85.000 (87.731) Prec@5 99.000 (99.154) +2022-11-14 15:46:44,081 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0393 (0.0726) Prec@1 93.000 (87.926) Prec@5 100.000 (99.185) +2022-11-14 15:46:44,094 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0724) Prec@1 87.000 (87.893) Prec@5 100.000 (99.214) +2022-11-14 15:46:44,105 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0728) Prec@1 87.000 (87.862) Prec@5 97.000 (99.138) +2022-11-14 15:46:44,115 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0731) Prec@1 86.000 (87.800) Prec@5 100.000 (99.167) +2022-11-14 15:46:44,126 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0732) Prec@1 87.000 (87.774) Prec@5 100.000 (99.194) +2022-11-14 15:46:44,137 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0731) Prec@1 91.000 (87.875) Prec@5 100.000 (99.219) +2022-11-14 15:46:44,149 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0733) Prec@1 88.000 (87.879) Prec@5 100.000 (99.242) +2022-11-14 15:46:44,159 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0728) Prec@1 88.000 (87.882) Prec@5 99.000 (99.235) +2022-11-14 15:46:44,170 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0729) Prec@1 89.000 (87.914) Prec@5 97.000 (99.171) +2022-11-14 15:46:44,180 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0726) Prec@1 90.000 (87.972) Prec@5 100.000 (99.194) +2022-11-14 15:46:44,192 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0728) Prec@1 87.000 (87.946) Prec@5 99.000 (99.189) +2022-11-14 15:46:44,202 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0734) Prec@1 84.000 (87.842) Prec@5 100.000 (99.211) +2022-11-14 15:46:44,212 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0728) Prec@1 94.000 (88.000) Prec@5 99.000 (99.205) +2022-11-14 15:46:44,222 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0728) Prec@1 87.000 (87.975) Prec@5 99.000 (99.200) +2022-11-14 15:46:44,233 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0734) Prec@1 85.000 (87.902) Prec@5 99.000 (99.195) +2022-11-14 15:46:44,244 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0731) Prec@1 89.000 (87.929) Prec@5 99.000 (99.190) +2022-11-14 15:46:44,255 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0724) Prec@1 93.000 (88.047) Prec@5 99.000 (99.186) +2022-11-14 15:46:44,266 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0724) Prec@1 90.000 (88.091) Prec@5 99.000 (99.182) +2022-11-14 15:46:44,277 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0722) Prec@1 91.000 (88.156) Prec@5 99.000 (99.178) +2022-11-14 15:46:44,286 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0728) Prec@1 81.000 (88.000) Prec@5 100.000 (99.196) +2022-11-14 15:46:44,297 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0725) Prec@1 90.000 (88.043) Prec@5 100.000 (99.213) +2022-11-14 15:46:44,307 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0729) Prec@1 87.000 (88.021) Prec@5 99.000 (99.208) +2022-11-14 15:46:44,317 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0378 (0.0722) Prec@1 95.000 (88.163) Prec@5 100.000 (99.224) +2022-11-14 15:46:44,328 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0727) Prec@1 83.000 (88.060) Prec@5 100.000 (99.240) +2022-11-14 15:46:44,339 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0725) Prec@1 90.000 (88.098) Prec@5 100.000 (99.255) +2022-11-14 15:46:44,350 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0728) Prec@1 83.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 15:46:44,361 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0725) Prec@1 91.000 (88.057) Prec@5 100.000 (99.264) +2022-11-14 15:46:44,371 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0725) Prec@1 90.000 (88.093) Prec@5 99.000 (99.259) +2022-11-14 15:46:44,382 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0731) Prec@1 82.000 (87.982) Prec@5 100.000 (99.273) +2022-11-14 15:46:44,392 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0728) Prec@1 92.000 (88.054) Prec@5 99.000 (99.268) +2022-11-14 15:46:44,403 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0727) Prec@1 88.000 (88.053) Prec@5 100.000 (99.281) +2022-11-14 15:46:44,413 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0728) Prec@1 90.000 (88.086) Prec@5 100.000 (99.293) +2022-11-14 15:46:44,426 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0731) Prec@1 84.000 (88.017) Prec@5 100.000 (99.305) +2022-11-14 15:46:44,437 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0730) Prec@1 87.000 (88.000) Prec@5 100.000 (99.317) +2022-11-14 15:46:44,448 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0731) Prec@1 88.000 (88.000) Prec@5 100.000 (99.328) +2022-11-14 15:46:44,459 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0733) Prec@1 85.000 (87.952) Prec@5 99.000 (99.323) +2022-11-14 15:46:44,470 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0730) Prec@1 92.000 (88.016) Prec@5 100.000 (99.333) +2022-11-14 15:46:44,482 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0382 (0.0724) Prec@1 92.000 (88.078) Prec@5 100.000 (99.344) +2022-11-14 15:46:44,495 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0722) Prec@1 89.000 (88.092) Prec@5 100.000 (99.354) +2022-11-14 15:46:44,506 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0725) Prec@1 84.000 (88.030) Prec@5 100.000 (99.364) +2022-11-14 15:46:44,515 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0484 (0.0721) Prec@1 91.000 (88.075) Prec@5 100.000 (99.373) +2022-11-14 15:46:44,526 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0723) Prec@1 89.000 (88.088) Prec@5 99.000 (99.368) +2022-11-14 15:46:44,537 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0721) Prec@1 89.000 (88.101) Prec@5 98.000 (99.348) +2022-11-14 15:46:44,548 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0722) Prec@1 90.000 (88.129) Prec@5 100.000 (99.357) +2022-11-14 15:46:44,560 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0725) Prec@1 85.000 (88.085) Prec@5 98.000 (99.338) +2022-11-14 15:46:44,572 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0725) Prec@1 88.000 (88.083) Prec@5 100.000 (99.347) +2022-11-14 15:46:44,582 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0721) Prec@1 93.000 (88.151) Prec@5 100.000 (99.356) +2022-11-14 15:46:44,592 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0719) Prec@1 89.000 (88.162) Prec@5 99.000 (99.351) +2022-11-14 15:46:44,604 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0724) Prec@1 84.000 (88.107) Prec@5 98.000 (99.333) +2022-11-14 15:46:44,613 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0722) Prec@1 90.000 (88.132) Prec@5 99.000 (99.329) +2022-11-14 15:46:44,624 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0722) Prec@1 88.000 (88.130) Prec@5 98.000 (99.312) +2022-11-14 15:46:44,634 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0725) Prec@1 86.000 (88.103) Prec@5 100.000 (99.321) +2022-11-14 15:46:44,645 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0726) Prec@1 88.000 (88.101) Prec@5 100.000 (99.329) +2022-11-14 15:46:44,655 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0727) Prec@1 87.000 (88.088) Prec@5 100.000 (99.338) +2022-11-14 15:46:44,666 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0731) Prec@1 84.000 (88.037) Prec@5 98.000 (99.321) +2022-11-14 15:46:44,675 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0731) Prec@1 89.000 (88.049) Prec@5 100.000 (99.329) +2022-11-14 15:46:44,686 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0732) Prec@1 87.000 (88.036) Prec@5 99.000 (99.325) +2022-11-14 15:46:44,697 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0733) Prec@1 87.000 (88.024) Prec@5 100.000 (99.333) +2022-11-14 15:46:44,707 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0734) Prec@1 86.000 (88.000) Prec@5 100.000 (99.341) +2022-11-14 15:46:44,717 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0737) Prec@1 83.000 (87.942) Prec@5 100.000 (99.349) +2022-11-14 15:46:44,727 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0737) Prec@1 87.000 (87.931) Prec@5 99.000 (99.345) +2022-11-14 15:46:44,739 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0738) Prec@1 86.000 (87.909) Prec@5 100.000 (99.352) +2022-11-14 15:46:44,750 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0738) Prec@1 88.000 (87.910) Prec@5 100.000 (99.360) +2022-11-14 15:46:44,762 Test: [89/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0739) Prec@1 87.000 (87.900) Prec@5 99.000 (99.356) +2022-11-14 15:46:44,773 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0737) Prec@1 93.000 (87.956) Prec@5 100.000 (99.363) +2022-11-14 15:46:44,786 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0735) Prec@1 92.000 (88.000) Prec@5 99.000 (99.359) +2022-11-14 15:46:44,797 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0735) Prec@1 84.000 (87.957) Prec@5 100.000 (99.366) +2022-11-14 15:46:44,808 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0733) Prec@1 90.000 (87.979) Prec@5 100.000 (99.372) +2022-11-14 15:46:44,819 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0734) Prec@1 89.000 (87.989) Prec@5 99.000 (99.368) +2022-11-14 15:46:44,828 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0733) Prec@1 89.000 (88.000) Prec@5 99.000 (99.365) +2022-11-14 15:46:44,839 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0357 (0.0729) Prec@1 93.000 (88.052) Prec@5 99.000 (99.361) +2022-11-14 15:46:44,850 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0730) Prec@1 87.000 (88.041) Prec@5 100.000 (99.367) +2022-11-14 15:46:44,861 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0733) Prec@1 86.000 (88.020) Prec@5 99.000 (99.364) +2022-11-14 15:46:44,871 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0735) Prec@1 86.000 (88.000) Prec@5 100.000 (99.370) +2022-11-14 15:46:44,945 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:46:45,269 Epoch: [259][0/500] Time 0.023 (0.023) Data 0.225 (0.225) Loss 0.0564 (0.0564) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:45,507 Epoch: [259][10/500] Time 0.018 (0.021) Data 0.002 (0.022) Loss 0.0361 (0.0462) Prec@1 95.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:45,741 Epoch: [259][20/500] Time 0.021 (0.021) Data 0.002 (0.012) Loss 0.0339 (0.0421) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:45,980 Epoch: [259][30/500] Time 0.021 (0.021) Data 0.002 (0.009) Loss 0.0322 (0.0396) Prec@1 94.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 15:46:46,224 Epoch: [259][40/500] Time 0.019 (0.021) Data 0.002 (0.007) Loss 0.0329 (0.0383) Prec@1 93.000 (93.200) Prec@5 100.000 (100.000) +2022-11-14 15:46:46,463 Epoch: [259][50/500] Time 0.020 (0.021) Data 0.002 (0.006) Loss 0.0260 (0.0362) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:46,701 Epoch: [259][60/500] Time 0.022 (0.021) Data 0.002 (0.005) Loss 0.0402 (0.0368) Prec@1 94.000 (93.571) Prec@5 100.000 (100.000) +2022-11-14 15:46:46,938 Epoch: [259][70/500] Time 0.021 (0.021) Data 0.002 (0.005) Loss 0.0429 (0.0376) Prec@1 92.000 (93.375) Prec@5 100.000 (100.000) +2022-11-14 15:46:47,170 Epoch: [259][80/500] Time 0.020 (0.021) Data 0.002 (0.004) Loss 0.0378 (0.0376) Prec@1 93.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 15:46:47,402 Epoch: [259][90/500] Time 0.024 (0.021) Data 0.001 (0.004) Loss 0.0421 (0.0380) Prec@1 91.000 (93.100) Prec@5 99.000 (99.900) +2022-11-14 15:46:47,639 Epoch: [259][100/500] Time 0.022 (0.021) Data 0.001 (0.004) Loss 0.0194 (0.0363) Prec@1 97.000 (93.455) Prec@5 100.000 (99.909) +2022-11-14 15:46:47,870 Epoch: [259][110/500] Time 0.021 (0.021) Data 0.002 (0.004) Loss 0.0509 (0.0376) Prec@1 92.000 (93.333) Prec@5 100.000 (99.917) +2022-11-14 15:46:48,102 Epoch: [259][120/500] Time 0.017 (0.021) Data 0.001 (0.003) Loss 0.0375 (0.0375) Prec@1 92.000 (93.231) Prec@5 100.000 (99.923) +2022-11-14 15:46:48,328 Epoch: [259][130/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0353 (0.0374) Prec@1 95.000 (93.357) Prec@5 100.000 (99.929) +2022-11-14 15:46:48,563 Epoch: [259][140/500] Time 0.020 (0.021) Data 0.002 (0.003) Loss 0.0273 (0.0367) Prec@1 97.000 (93.600) Prec@5 100.000 (99.933) +2022-11-14 15:46:48,791 Epoch: [259][150/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0444 (0.0372) Prec@1 93.000 (93.562) Prec@5 100.000 (99.938) +2022-11-14 15:46:49,024 Epoch: [259][160/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0389 (0.0373) Prec@1 92.000 (93.471) Prec@5 100.000 (99.941) +2022-11-14 15:46:49,248 Epoch: [259][170/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0250 (0.0366) Prec@1 95.000 (93.556) Prec@5 100.000 (99.944) +2022-11-14 15:46:49,483 Epoch: [259][180/500] Time 0.020 (0.021) Data 0.001 (0.003) Loss 0.0264 (0.0361) Prec@1 98.000 (93.789) Prec@5 100.000 (99.947) +2022-11-14 15:46:49,734 Epoch: [259][190/500] Time 0.020 (0.021) Data 0.002 (0.003) Loss 0.0153 (0.0350) Prec@1 98.000 (94.000) Prec@5 100.000 (99.950) +2022-11-14 15:46:49,959 Epoch: [259][200/500] Time 0.018 (0.021) Data 0.001 (0.003) Loss 0.0414 (0.0353) Prec@1 93.000 (93.952) Prec@5 100.000 (99.952) +2022-11-14 15:46:50,189 Epoch: [259][210/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0431 (0.0357) Prec@1 92.000 (93.864) Prec@5 100.000 (99.955) +2022-11-14 15:46:50,417 Epoch: [259][220/500] Time 0.020 (0.021) Data 0.001 (0.003) Loss 0.0184 (0.0349) Prec@1 98.000 (94.043) Prec@5 100.000 (99.957) +2022-11-14 15:46:50,641 Epoch: [259][230/500] Time 0.019 (0.021) Data 0.001 (0.003) Loss 0.0216 (0.0344) Prec@1 97.000 (94.167) Prec@5 100.000 (99.958) +2022-11-14 15:46:50,885 Epoch: [259][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0119 (0.0335) Prec@1 99.000 (94.360) Prec@5 100.000 (99.960) +2022-11-14 15:46:51,115 Epoch: [259][250/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0188 (0.0329) Prec@1 99.000 (94.538) Prec@5 100.000 (99.962) +2022-11-14 15:46:51,338 Epoch: [259][260/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0424 (0.0333) Prec@1 93.000 (94.481) Prec@5 100.000 (99.963) +2022-11-14 15:46:51,566 Epoch: [259][270/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0168 (0.0327) Prec@1 97.000 (94.571) Prec@5 100.000 (99.964) +2022-11-14 15:46:51,798 Epoch: [259][280/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0209 (0.0323) Prec@1 97.000 (94.655) Prec@5 100.000 (99.966) +2022-11-14 15:46:52,025 Epoch: [259][290/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0274 (0.0321) Prec@1 96.000 (94.700) Prec@5 100.000 (99.967) +2022-11-14 15:46:52,257 Epoch: [259][300/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0476 (0.0326) Prec@1 90.000 (94.548) Prec@5 100.000 (99.968) +2022-11-14 15:46:52,485 Epoch: [259][310/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0495 (0.0331) Prec@1 90.000 (94.406) Prec@5 100.000 (99.969) +2022-11-14 15:46:52,730 Epoch: [259][320/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0239 (0.0329) Prec@1 97.000 (94.485) Prec@5 100.000 (99.970) +2022-11-14 15:46:52,966 Epoch: [259][330/500] Time 0.022 (0.021) Data 0.003 (0.002) Loss 0.0623 (0.0337) Prec@1 88.000 (94.294) Prec@5 100.000 (99.971) +2022-11-14 15:46:53,203 Epoch: [259][340/500] Time 0.018 (0.021) Data 0.001 (0.002) Loss 0.0549 (0.0343) Prec@1 91.000 (94.200) Prec@5 100.000 (99.971) +2022-11-14 15:46:53,440 Epoch: [259][350/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0322 (0.0343) Prec@1 94.000 (94.194) Prec@5 100.000 (99.972) +2022-11-14 15:46:53,672 Epoch: [259][360/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0310 (0.0342) Prec@1 95.000 (94.216) Prec@5 100.000 (99.973) +2022-11-14 15:46:53,906 Epoch: [259][370/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0471 (0.0345) Prec@1 92.000 (94.158) Prec@5 100.000 (99.974) +2022-11-14 15:46:54,137 Epoch: [259][380/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0274 (0.0343) Prec@1 96.000 (94.205) Prec@5 100.000 (99.974) +2022-11-14 15:46:54,366 Epoch: [259][390/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0448 (0.0346) Prec@1 92.000 (94.150) Prec@5 99.000 (99.950) +2022-11-14 15:46:54,592 Epoch: [259][400/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0422 (0.0348) Prec@1 93.000 (94.122) Prec@5 100.000 (99.951) +2022-11-14 15:46:54,822 Epoch: [259][410/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0202 (0.0344) Prec@1 98.000 (94.214) Prec@5 100.000 (99.952) +2022-11-14 15:46:55,058 Epoch: [259][420/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0326 (0.0344) Prec@1 95.000 (94.233) Prec@5 100.000 (99.953) +2022-11-14 15:46:55,277 Epoch: [259][430/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0495 (0.0347) Prec@1 91.000 (94.159) Prec@5 100.000 (99.955) +2022-11-14 15:46:55,511 Epoch: [259][440/500] Time 0.021 (0.021) Data 0.001 (0.002) Loss 0.0420 (0.0349) Prec@1 93.000 (94.133) Prec@5 100.000 (99.956) +2022-11-14 15:46:55,749 Epoch: [259][450/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0418 (0.0350) Prec@1 94.000 (94.130) Prec@5 100.000 (99.957) +2022-11-14 15:46:55,982 Epoch: [259][460/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0282 (0.0349) Prec@1 95.000 (94.149) Prec@5 100.000 (99.957) +2022-11-14 15:46:56,220 Epoch: [259][470/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0286 (0.0348) Prec@1 94.000 (94.146) Prec@5 100.000 (99.958) +2022-11-14 15:46:56,457 Epoch: [259][480/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0271 (0.0346) Prec@1 96.000 (94.184) Prec@5 100.000 (99.959) +2022-11-14 15:46:56,732 Epoch: [259][490/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0400 (0.0347) Prec@1 93.000 (94.160) Prec@5 100.000 (99.960) +2022-11-14 15:46:56,955 Epoch: [259][499/500] Time 0.018 (0.021) Data 0.001 (0.002) Loss 0.0354 (0.0347) Prec@1 96.000 (94.196) Prec@5 100.000 (99.961) +2022-11-14 15:46:57,250 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0623 (0.0623) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 15:46:57,260 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0620) Prec@1 91.000 (91.500) Prec@5 99.000 (99.000) +2022-11-14 15:46:57,271 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0623) Prec@1 89.000 (90.667) Prec@5 100.000 (99.333) +2022-11-14 15:46:57,285 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0642) Prec@1 89.000 (90.250) Prec@5 99.000 (99.250) +2022-11-14 15:46:57,293 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0662) Prec@1 87.000 (89.600) Prec@5 100.000 (99.400) +2022-11-14 15:46:57,303 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0638) Prec@1 91.000 (89.833) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,313 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0624) Prec@1 92.000 (90.143) Prec@5 99.000 (99.429) +2022-11-14 15:46:57,325 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0673) Prec@1 82.000 (89.125) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,336 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0678) Prec@1 89.000 (89.111) Prec@5 98.000 (99.333) +2022-11-14 15:46:57,348 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0690) Prec@1 87.000 (88.900) Prec@5 98.000 (99.200) +2022-11-14 15:46:57,359 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0680) Prec@1 92.000 (89.182) Prec@5 100.000 (99.273) +2022-11-14 15:46:57,372 Test: [11/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0679) Prec@1 87.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 15:46:57,384 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0666) Prec@1 94.000 (89.385) Prec@5 100.000 (99.385) +2022-11-14 15:46:57,395 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0672) Prec@1 90.000 (89.429) Prec@5 100.000 (99.429) +2022-11-14 15:46:57,405 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0686) Prec@1 86.000 (89.200) Prec@5 100.000 (99.467) +2022-11-14 15:46:57,416 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0685) Prec@1 89.000 (89.188) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,425 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0675) Prec@1 91.000 (89.294) Prec@5 98.000 (99.412) +2022-11-14 15:46:57,436 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1181 (0.0703) Prec@1 82.000 (88.889) Prec@5 100.000 (99.444) +2022-11-14 15:46:57,446 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0714) Prec@1 84.000 (88.632) Prec@5 99.000 (99.421) +2022-11-14 15:46:57,459 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0724) Prec@1 84.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 15:46:57,470 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0724) Prec@1 89.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 15:46:57,479 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0717) Prec@1 92.000 (88.591) Prec@5 100.000 (99.455) +2022-11-14 15:46:57,489 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0724) Prec@1 87.000 (88.522) Prec@5 100.000 (99.478) +2022-11-14 15:46:57,500 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0724) Prec@1 87.000 (88.458) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,511 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0730) Prec@1 87.000 (88.400) Prec@5 100.000 (99.520) +2022-11-14 15:46:57,520 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0736) Prec@1 87.000 (88.346) Prec@5 98.000 (99.462) +2022-11-14 15:46:57,528 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0729) Prec@1 91.000 (88.444) Prec@5 100.000 (99.481) +2022-11-14 15:46:57,539 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0725) Prec@1 90.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,552 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0723) Prec@1 89.000 (88.517) Prec@5 100.000 (99.517) +2022-11-14 15:46:57,564 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0727) Prec@1 85.000 (88.400) Prec@5 98.000 (99.467) +2022-11-14 15:46:57,577 Test: [30/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0722) Prec@1 91.000 (88.484) Prec@5 99.000 (99.452) +2022-11-14 15:46:57,589 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0720) Prec@1 89.000 (88.500) Prec@5 100.000 (99.469) +2022-11-14 15:46:57,599 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0716) Prec@1 92.000 (88.606) Prec@5 100.000 (99.485) +2022-11-14 15:46:57,611 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0717) Prec@1 86.000 (88.529) Prec@5 100.000 (99.500) +2022-11-14 15:46:57,621 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0719) Prec@1 86.000 (88.457) Prec@5 98.000 (99.457) +2022-11-14 15:46:57,632 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0716) Prec@1 92.000 (88.556) Prec@5 100.000 (99.472) +2022-11-14 15:46:57,641 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0716) Prec@1 88.000 (88.541) Prec@5 99.000 (99.459) +2022-11-14 15:46:57,652 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0721) Prec@1 85.000 (88.447) Prec@5 97.000 (99.395) +2022-11-14 15:46:57,662 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0724) Prec@1 88.000 (88.436) Prec@5 99.000 (99.385) +2022-11-14 15:46:57,673 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0725) Prec@1 86.000 (88.375) Prec@5 99.000 (99.375) +2022-11-14 15:46:57,683 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0730) Prec@1 86.000 (88.317) Prec@5 99.000 (99.366) +2022-11-14 15:46:57,693 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0729) Prec@1 88.000 (88.310) Prec@5 100.000 (99.381) +2022-11-14 15:46:57,704 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0401 (0.0721) Prec@1 94.000 (88.442) Prec@5 100.000 (99.395) +2022-11-14 15:46:57,715 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0724) Prec@1 86.000 (88.386) Prec@5 99.000 (99.386) +2022-11-14 15:46:57,725 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0719) Prec@1 91.000 (88.444) Prec@5 99.000 (99.378) +2022-11-14 15:46:57,737 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1160 (0.0728) Prec@1 81.000 (88.283) Prec@5 100.000 (99.391) +2022-11-14 15:46:57,748 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0725) Prec@1 89.000 (88.298) Prec@5 100.000 (99.404) +2022-11-14 15:46:57,760 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1116 (0.0733) Prec@1 81.000 (88.146) Prec@5 98.000 (99.375) +2022-11-14 15:46:57,772 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0728) Prec@1 94.000 (88.265) Prec@5 100.000 (99.388) +2022-11-14 15:46:57,783 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0733) Prec@1 85.000 (88.200) Prec@5 100.000 (99.400) +2022-11-14 15:46:57,794 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0731) Prec@1 88.000 (88.196) Prec@5 100.000 (99.412) +2022-11-14 15:46:57,805 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0734) Prec@1 85.000 (88.135) Prec@5 99.000 (99.404) +2022-11-14 15:46:57,815 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0731) Prec@1 92.000 (88.208) Prec@5 99.000 (99.396) +2022-11-14 15:46:57,827 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0730) Prec@1 89.000 (88.222) Prec@5 99.000 (99.389) +2022-11-14 15:46:57,838 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0730) Prec@1 90.000 (88.255) Prec@5 100.000 (99.400) +2022-11-14 15:46:57,850 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0729) Prec@1 91.000 (88.304) Prec@5 99.000 (99.393) +2022-11-14 15:46:57,861 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0727) Prec@1 89.000 (88.316) Prec@5 100.000 (99.404) +2022-11-14 15:46:57,872 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0727) Prec@1 91.000 (88.362) Prec@5 99.000 (99.397) +2022-11-14 15:46:57,882 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0728) Prec@1 86.000 (88.322) Prec@5 100.000 (99.407) +2022-11-14 15:46:57,892 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0728) Prec@1 87.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 15:46:57,904 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0726) Prec@1 90.000 (88.328) Prec@5 100.000 (99.410) +2022-11-14 15:46:57,915 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0724) Prec@1 90.000 (88.355) Prec@5 100.000 (99.419) +2022-11-14 15:46:57,925 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0722) Prec@1 89.000 (88.365) Prec@5 100.000 (99.429) +2022-11-14 15:46:57,937 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0351 (0.0717) Prec@1 95.000 (88.469) Prec@5 100.000 (99.438) +2022-11-14 15:46:57,948 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0718) Prec@1 87.000 (88.446) Prec@5 99.000 (99.431) +2022-11-14 15:46:57,961 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0717) Prec@1 89.000 (88.455) Prec@5 100.000 (99.439) +2022-11-14 15:46:57,972 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0712) Prec@1 94.000 (88.537) Prec@5 100.000 (99.448) +2022-11-14 15:46:57,982 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0712) Prec@1 88.000 (88.529) Prec@5 100.000 (99.456) +2022-11-14 15:46:57,993 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0714) Prec@1 86.000 (88.493) Prec@5 99.000 (99.449) +2022-11-14 15:46:58,005 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0715) Prec@1 87.000 (88.471) Prec@5 99.000 (99.443) +2022-11-14 15:46:58,016 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0719) Prec@1 86.000 (88.437) Prec@5 98.000 (99.423) +2022-11-14 15:46:58,027 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0719) Prec@1 88.000 (88.431) Prec@5 98.000 (99.403) +2022-11-14 15:46:58,038 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0716) Prec@1 93.000 (88.493) Prec@5 99.000 (99.397) +2022-11-14 15:46:58,051 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0331 (0.0711) Prec@1 95.000 (88.581) Prec@5 100.000 (99.405) +2022-11-14 15:46:58,063 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0717) Prec@1 82.000 (88.493) Prec@5 100.000 (99.413) +2022-11-14 15:46:58,073 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0715) Prec@1 88.000 (88.487) Prec@5 98.000 (99.395) +2022-11-14 15:46:58,085 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0713) Prec@1 90.000 (88.506) Prec@5 98.000 (99.377) +2022-11-14 15:46:58,096 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0716) Prec@1 83.000 (88.436) Prec@5 98.000 (99.359) +2022-11-14 15:46:58,106 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0717) Prec@1 87.000 (88.418) Prec@5 100.000 (99.367) +2022-11-14 15:46:58,118 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0715) Prec@1 92.000 (88.463) Prec@5 100.000 (99.375) +2022-11-14 15:46:58,128 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0716) Prec@1 86.000 (88.432) Prec@5 98.000 (99.358) +2022-11-14 15:46:58,138 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0716) Prec@1 90.000 (88.451) Prec@5 100.000 (99.366) +2022-11-14 15:46:58,148 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0718) Prec@1 84.000 (88.398) Prec@5 99.000 (99.361) +2022-11-14 15:46:58,161 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0717) Prec@1 92.000 (88.440) Prec@5 100.000 (99.369) +2022-11-14 15:46:58,172 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0718) Prec@1 88.000 (88.435) Prec@5 99.000 (99.365) +2022-11-14 15:46:58,182 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0719) Prec@1 86.000 (88.407) Prec@5 100.000 (99.372) +2022-11-14 15:46:58,193 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0720) Prec@1 84.000 (88.356) Prec@5 98.000 (99.356) +2022-11-14 15:46:58,203 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0722) Prec@1 84.000 (88.307) Prec@5 99.000 (99.352) +2022-11-14 15:46:58,215 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0722) Prec@1 89.000 (88.315) Prec@5 99.000 (99.348) +2022-11-14 15:46:58,228 Test: [89/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0723) Prec@1 88.000 (88.311) Prec@5 99.000 (99.344) +2022-11-14 15:46:58,240 Test: [90/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0720) Prec@1 94.000 (88.374) Prec@5 100.000 (99.352) +2022-11-14 15:46:58,253 Test: [91/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0717) Prec@1 94.000 (88.435) Prec@5 100.000 (99.359) +2022-11-14 15:46:58,265 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0719) Prec@1 86.000 (88.409) Prec@5 100.000 (99.366) +2022-11-14 15:46:58,277 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0719) Prec@1 87.000 (88.394) Prec@5 99.000 (99.362) +2022-11-14 15:46:58,286 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0719) Prec@1 86.000 (88.368) Prec@5 100.000 (99.368) +2022-11-14 15:46:58,296 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0719) Prec@1 87.000 (88.354) Prec@5 99.000 (99.365) +2022-11-14 15:46:58,309 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0716) Prec@1 92.000 (88.392) Prec@5 99.000 (99.361) +2022-11-14 15:46:58,320 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0719) Prec@1 83.000 (88.337) Prec@5 98.000 (99.347) +2022-11-14 15:46:58,330 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0723) Prec@1 84.000 (88.293) Prec@5 99.000 (99.343) +2022-11-14 15:46:58,342 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0722) Prec@1 90.000 (88.310) Prec@5 100.000 (99.350) +2022-11-14 15:46:58,399 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:46:58,726 Epoch: [260][0/500] Time 0.036 (0.036) Data 0.231 (0.231) Loss 0.0301 (0.0301) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 15:46:58,977 Epoch: [260][10/500] Time 0.021 (0.023) Data 0.002 (0.023) Loss 0.0420 (0.0360) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:59,210 Epoch: [260][20/500] Time 0.020 (0.022) Data 0.002 (0.013) Loss 0.0529 (0.0417) Prec@1 89.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 15:46:59,468 Epoch: [260][30/500] Time 0.024 (0.022) Data 0.002 (0.009) Loss 0.0538 (0.0447) Prec@1 90.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 15:46:59,711 Epoch: [260][40/500] Time 0.021 (0.022) Data 0.001 (0.007) Loss 0.0158 (0.0389) Prec@1 97.000 (93.400) Prec@5 100.000 (100.000) +2022-11-14 15:46:59,943 Epoch: [260][50/500] Time 0.021 (0.022) Data 0.002 (0.006) Loss 0.0346 (0.0382) Prec@1 94.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:47:00,178 Epoch: [260][60/500] Time 0.019 (0.022) Data 0.002 (0.006) Loss 0.0348 (0.0377) Prec@1 93.000 (93.429) Prec@5 100.000 (100.000) +2022-11-14 15:47:00,438 Epoch: [260][70/500] Time 0.020 (0.022) Data 0.002 (0.005) Loss 0.0250 (0.0361) Prec@1 96.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 15:47:00,684 Epoch: [260][80/500] Time 0.021 (0.022) Data 0.002 (0.005) Loss 0.0322 (0.0357) Prec@1 95.000 (93.889) Prec@5 99.000 (99.889) +2022-11-14 15:47:00,933 Epoch: [260][90/500] Time 0.020 (0.022) Data 0.002 (0.004) Loss 0.0163 (0.0338) Prec@1 97.000 (94.200) Prec@5 100.000 (99.900) +2022-11-14 15:47:01,180 Epoch: [260][100/500] Time 0.021 (0.022) Data 0.002 (0.004) Loss 0.0212 (0.0326) Prec@1 97.000 (94.455) Prec@5 100.000 (99.909) +2022-11-14 15:47:01,421 Epoch: [260][110/500] Time 0.020 (0.022) Data 0.002 (0.004) Loss 0.0233 (0.0318) Prec@1 96.000 (94.583) Prec@5 100.000 (99.917) +2022-11-14 15:47:01,670 Epoch: [260][120/500] Time 0.026 (0.022) Data 0.002 (0.004) Loss 0.0287 (0.0316) Prec@1 96.000 (94.692) Prec@5 100.000 (99.923) +2022-11-14 15:47:01,900 Epoch: [260][130/500] Time 0.018 (0.022) Data 0.002 (0.004) Loss 0.0271 (0.0313) Prec@1 95.000 (94.714) Prec@5 100.000 (99.929) +2022-11-14 15:47:02,142 Epoch: [260][140/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0304 (0.0312) Prec@1 95.000 (94.733) Prec@5 100.000 (99.933) +2022-11-14 15:47:02,373 Epoch: [260][150/500] Time 0.019 (0.022) Data 0.002 (0.003) Loss 0.0474 (0.0322) Prec@1 93.000 (94.625) Prec@5 100.000 (99.938) +2022-11-14 15:47:02,605 Epoch: [260][160/500] Time 0.020 (0.022) Data 0.002 (0.003) Loss 0.0264 (0.0319) Prec@1 98.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 15:47:02,839 Epoch: [260][170/500] Time 0.021 (0.022) Data 0.002 (0.003) Loss 0.0178 (0.0311) Prec@1 97.000 (94.944) Prec@5 100.000 (99.944) +2022-11-14 15:47:03,071 Epoch: [260][180/500] Time 0.021 (0.022) Data 0.002 (0.003) Loss 0.0483 (0.0320) Prec@1 93.000 (94.842) Prec@5 100.000 (99.947) +2022-11-14 15:47:03,307 Epoch: [260][190/500] Time 0.021 (0.021) Data 0.001 (0.003) Loss 0.0221 (0.0315) Prec@1 97.000 (94.950) Prec@5 99.000 (99.900) +2022-11-14 15:47:03,538 Epoch: [260][200/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0318 (0.0315) Prec@1 94.000 (94.905) Prec@5 100.000 (99.905) +2022-11-14 15:47:03,773 Epoch: [260][210/500] Time 0.020 (0.021) Data 0.002 (0.003) Loss 0.0414 (0.0320) Prec@1 94.000 (94.864) Prec@5 100.000 (99.909) +2022-11-14 15:47:04,004 Epoch: [260][220/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0415 (0.0324) Prec@1 94.000 (94.826) Prec@5 100.000 (99.913) +2022-11-14 15:47:04,239 Epoch: [260][230/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0293 (0.0323) Prec@1 95.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 15:47:04,475 Epoch: [260][240/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0680 (0.0337) Prec@1 89.000 (94.600) Prec@5 99.000 (99.880) +2022-11-14 15:47:04,707 Epoch: [260][250/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0597 (0.0347) Prec@1 90.000 (94.423) Prec@5 99.000 (99.846) +2022-11-14 15:47:04,951 Epoch: [260][260/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0402 (0.0349) Prec@1 94.000 (94.407) Prec@5 98.000 (99.778) +2022-11-14 15:47:05,186 Epoch: [260][270/500] Time 0.020 (0.021) Data 0.002 (0.003) Loss 0.0218 (0.0344) Prec@1 97.000 (94.500) Prec@5 100.000 (99.786) +2022-11-14 15:47:05,423 Epoch: [260][280/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0124 (0.0337) Prec@1 99.000 (94.655) Prec@5 100.000 (99.793) +2022-11-14 15:47:05,665 Epoch: [260][290/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0303 (0.0335) Prec@1 93.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 15:47:05,896 Epoch: [260][300/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0297 (0.0334) Prec@1 96.000 (94.645) Prec@5 100.000 (99.806) +2022-11-14 15:47:06,133 Epoch: [260][310/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0222 (0.0331) Prec@1 97.000 (94.719) Prec@5 100.000 (99.812) +2022-11-14 15:47:06,363 Epoch: [260][320/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0412 (0.0333) Prec@1 91.000 (94.606) Prec@5 100.000 (99.818) +2022-11-14 15:47:06,599 Epoch: [260][330/500] Time 0.019 (0.021) Data 0.002 (0.002) Loss 0.0280 (0.0332) Prec@1 97.000 (94.676) Prec@5 100.000 (99.824) +2022-11-14 15:47:06,827 Epoch: [260][340/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0348 (0.0332) Prec@1 95.000 (94.686) Prec@5 99.000 (99.800) +2022-11-14 15:47:07,058 Epoch: [260][350/500] Time 0.017 (0.021) Data 0.002 (0.002) Loss 0.0362 (0.0333) Prec@1 94.000 (94.667) Prec@5 99.000 (99.778) +2022-11-14 15:47:07,292 Epoch: [260][360/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0268 (0.0331) Prec@1 96.000 (94.703) Prec@5 100.000 (99.784) +2022-11-14 15:47:07,528 Epoch: [260][370/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0437 (0.0334) Prec@1 93.000 (94.658) Prec@5 100.000 (99.789) +2022-11-14 15:47:07,770 Epoch: [260][380/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0119 (0.0328) Prec@1 99.000 (94.769) Prec@5 100.000 (99.795) +2022-11-14 15:47:08,009 Epoch: [260][390/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0440 (0.0331) Prec@1 93.000 (94.725) Prec@5 99.000 (99.775) +2022-11-14 15:47:08,245 Epoch: [260][400/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0294 (0.0330) Prec@1 95.000 (94.732) Prec@5 100.000 (99.780) +2022-11-14 15:47:08,470 Epoch: [260][410/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0428 (0.0333) Prec@1 91.000 (94.643) Prec@5 100.000 (99.786) +2022-11-14 15:47:08,808 Epoch: [260][420/500] Time 0.034 (0.021) Data 0.002 (0.002) Loss 0.0473 (0.0336) Prec@1 91.000 (94.558) Prec@5 100.000 (99.791) +2022-11-14 15:47:09,157 Epoch: [260][430/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0398 (0.0337) Prec@1 94.000 (94.545) Prec@5 99.000 (99.773) +2022-11-14 15:47:09,487 Epoch: [260][440/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0366 (0.0338) Prec@1 95.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 15:47:09,836 Epoch: [260][450/500] Time 0.033 (0.022) Data 0.002 (0.002) Loss 0.0309 (0.0337) Prec@1 96.000 (94.587) Prec@5 100.000 (99.783) +2022-11-14 15:47:10,177 Epoch: [260][460/500] Time 0.031 (0.022) Data 0.002 (0.002) Loss 0.0314 (0.0337) Prec@1 96.000 (94.617) Prec@5 100.000 (99.787) +2022-11-14 15:47:10,516 Epoch: [260][470/500] Time 0.033 (0.022) Data 0.002 (0.002) Loss 0.0239 (0.0335) Prec@1 97.000 (94.667) Prec@5 100.000 (99.792) +2022-11-14 15:47:10,856 Epoch: [260][480/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0211 (0.0332) Prec@1 95.000 (94.673) Prec@5 100.000 (99.796) +2022-11-14 15:47:11,196 Epoch: [260][490/500] Time 0.034 (0.023) Data 0.002 (0.002) Loss 0.0246 (0.0331) Prec@1 96.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 15:47:11,493 Epoch: [260][499/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0495 (0.0334) Prec@1 90.000 (94.608) Prec@5 100.000 (99.804) +2022-11-14 15:47:11,815 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0670 (0.0670) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 15:47:11,824 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0734 (0.0702) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 15:47:11,834 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0569 (0.0658) Prec@1 92.000 (90.667) Prec@5 100.000 (99.667) +2022-11-14 15:47:11,848 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0661) Prec@1 87.000 (89.750) Prec@5 100.000 (99.750) +2022-11-14 15:47:11,857 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0687) Prec@1 86.000 (89.000) Prec@5 100.000 (99.800) +2022-11-14 15:47:11,869 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0683) Prec@1 89.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 15:47:11,879 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0682) Prec@1 89.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 15:47:11,892 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0687) Prec@1 87.000 (88.750) Prec@5 100.000 (99.875) +2022-11-14 15:47:11,902 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0705) Prec@1 85.000 (88.333) Prec@5 99.000 (99.778) +2022-11-14 15:47:11,912 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0705) Prec@1 89.000 (88.400) Prec@5 99.000 (99.700) +2022-11-14 15:47:11,925 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0689) Prec@1 91.000 (88.636) Prec@5 100.000 (99.727) +2022-11-14 15:47:11,936 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0696) Prec@1 88.000 (88.583) Prec@5 99.000 (99.667) +2022-11-14 15:47:11,946 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0682) Prec@1 89.000 (88.615) Prec@5 100.000 (99.692) +2022-11-14 15:47:11,957 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0683) Prec@1 90.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 15:47:11,969 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0683) Prec@1 88.000 (88.667) Prec@5 100.000 (99.733) +2022-11-14 15:47:11,979 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0685) Prec@1 86.000 (88.500) Prec@5 100.000 (99.750) +2022-11-14 15:47:11,990 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0683) Prec@1 90.000 (88.588) Prec@5 99.000 (99.706) +2022-11-14 15:47:12,001 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.0711) Prec@1 84.000 (88.333) Prec@5 98.000 (99.611) +2022-11-14 15:47:12,012 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0735) Prec@1 81.000 (87.947) Prec@5 97.000 (99.474) +2022-11-14 15:47:12,023 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0742) Prec@1 86.000 (87.850) Prec@5 98.000 (99.400) +2022-11-14 15:47:12,034 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0746) Prec@1 86.000 (87.762) Prec@5 100.000 (99.429) +2022-11-14 15:47:12,043 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0748) Prec@1 88.000 (87.773) Prec@5 99.000 (99.409) +2022-11-14 15:47:12,054 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0753) Prec@1 87.000 (87.739) Prec@5 97.000 (99.304) +2022-11-14 15:47:12,064 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0755) Prec@1 84.000 (87.583) Prec@5 100.000 (99.333) +2022-11-14 15:47:12,076 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0764) Prec@1 85.000 (87.480) Prec@5 100.000 (99.360) +2022-11-14 15:47:12,087 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0773) Prec@1 84.000 (87.346) Prec@5 98.000 (99.308) +2022-11-14 15:47:12,097 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0323 (0.0756) Prec@1 97.000 (87.704) Prec@5 100.000 (99.333) +2022-11-14 15:47:12,106 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0748) Prec@1 92.000 (87.857) Prec@5 99.000 (99.321) +2022-11-14 15:47:12,119 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0748) Prec@1 88.000 (87.862) Prec@5 99.000 (99.310) +2022-11-14 15:47:12,130 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0744) Prec@1 90.000 (87.933) Prec@5 98.000 (99.267) +2022-11-14 15:47:12,138 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0741) Prec@1 89.000 (87.968) Prec@5 100.000 (99.290) +2022-11-14 15:47:12,149 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0738) Prec@1 88.000 (87.969) Prec@5 99.000 (99.281) +2022-11-14 15:47:12,160 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0739) Prec@1 85.000 (87.879) Prec@5 100.000 (99.303) +2022-11-14 15:47:12,172 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0747) Prec@1 81.000 (87.676) Prec@5 99.000 (99.294) +2022-11-14 15:47:12,182 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0748) Prec@1 87.000 (87.657) Prec@5 100.000 (99.314) +2022-11-14 15:47:12,193 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0748) Prec@1 88.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 15:47:12,204 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0745) Prec@1 89.000 (87.703) Prec@5 99.000 (99.324) +2022-11-14 15:47:12,215 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0751) Prec@1 82.000 (87.553) Prec@5 100.000 (99.342) +2022-11-14 15:47:12,227 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0748) Prec@1 92.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 15:47:12,238 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0746) Prec@1 89.000 (87.700) Prec@5 99.000 (99.325) +2022-11-14 15:47:12,249 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0752) Prec@1 85.000 (87.634) Prec@5 97.000 (99.268) +2022-11-14 15:47:12,259 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0752) Prec@1 88.000 (87.643) Prec@5 100.000 (99.286) +2022-11-14 15:47:12,270 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0745) Prec@1 91.000 (87.721) Prec@5 100.000 (99.302) +2022-11-14 15:47:12,281 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0742) Prec@1 88.000 (87.727) Prec@5 99.000 (99.295) +2022-11-14 15:47:12,295 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1069 (0.0749) Prec@1 86.000 (87.689) Prec@5 99.000 (99.289) +2022-11-14 15:47:12,306 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0752) Prec@1 87.000 (87.674) Prec@5 100.000 (99.304) +2022-11-14 15:47:12,317 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0747) Prec@1 93.000 (87.787) Prec@5 100.000 (99.319) +2022-11-14 15:47:12,329 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0748) Prec@1 85.000 (87.729) Prec@5 99.000 (99.312) +2022-11-14 15:47:12,340 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0486 (0.0743) Prec@1 93.000 (87.837) Prec@5 99.000 (99.306) +2022-11-14 15:47:12,350 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0747) Prec@1 84.000 (87.760) Prec@5 100.000 (99.320) +2022-11-14 15:47:12,361 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0747) Prec@1 88.000 (87.765) Prec@5 100.000 (99.333) +2022-11-14 15:47:12,372 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0750) Prec@1 85.000 (87.712) Prec@5 100.000 (99.346) +2022-11-14 15:47:12,385 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0751) Prec@1 87.000 (87.698) Prec@5 100.000 (99.358) +2022-11-14 15:47:12,397 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0751) Prec@1 88.000 (87.704) Prec@5 99.000 (99.352) +2022-11-14 15:47:12,408 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0755) Prec@1 85.000 (87.655) Prec@5 100.000 (99.364) +2022-11-14 15:47:12,418 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0756) Prec@1 87.000 (87.643) Prec@5 99.000 (99.357) +2022-11-14 15:47:12,429 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0755) Prec@1 89.000 (87.667) Prec@5 100.000 (99.368) +2022-11-14 15:47:12,440 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0751) Prec@1 91.000 (87.724) Prec@5 100.000 (99.379) +2022-11-14 15:47:12,451 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0757) Prec@1 83.000 (87.644) Prec@5 100.000 (99.390) +2022-11-14 15:47:12,461 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0756) Prec@1 87.000 (87.633) Prec@5 100.000 (99.400) +2022-11-14 15:47:12,472 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0756) Prec@1 88.000 (87.639) Prec@5 100.000 (99.410) +2022-11-14 15:47:12,482 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0755) Prec@1 87.000 (87.629) Prec@5 100.000 (99.419) +2022-11-14 15:47:12,493 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0752) Prec@1 90.000 (87.667) Prec@5 100.000 (99.429) +2022-11-14 15:47:12,503 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0250 (0.0744) Prec@1 96.000 (87.797) Prec@5 100.000 (99.438) +2022-11-14 15:47:12,513 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0747) Prec@1 83.000 (87.723) Prec@5 100.000 (99.446) +2022-11-14 15:47:12,523 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0747) Prec@1 88.000 (87.727) Prec@5 99.000 (99.439) +2022-11-14 15:47:12,534 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0743) Prec@1 93.000 (87.806) Prec@5 100.000 (99.448) +2022-11-14 15:47:12,546 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0742) Prec@1 90.000 (87.838) Prec@5 96.000 (99.397) +2022-11-14 15:47:12,558 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0741) Prec@1 91.000 (87.884) Prec@5 99.000 (99.391) +2022-11-14 15:47:12,569 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0742) Prec@1 87.000 (87.871) Prec@5 99.000 (99.386) +2022-11-14 15:47:12,580 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0745) Prec@1 86.000 (87.845) Prec@5 99.000 (99.380) +2022-11-14 15:47:12,591 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0743) Prec@1 91.000 (87.889) Prec@5 100.000 (99.389) +2022-11-14 15:47:12,602 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0742) Prec@1 90.000 (87.918) Prec@5 100.000 (99.397) +2022-11-14 15:47:12,614 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0738) Prec@1 93.000 (87.986) Prec@5 100.000 (99.405) +2022-11-14 15:47:12,627 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0744) Prec@1 82.000 (87.907) Prec@5 100.000 (99.413) +2022-11-14 15:47:12,639 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0741) Prec@1 92.000 (87.961) Prec@5 98.000 (99.395) +2022-11-14 15:47:12,649 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0739) Prec@1 90.000 (87.987) Prec@5 98.000 (99.377) +2022-11-14 15:47:12,660 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0741) Prec@1 85.000 (87.949) Prec@5 97.000 (99.346) +2022-11-14 15:47:12,671 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0745) Prec@1 84.000 (87.899) Prec@5 99.000 (99.342) +2022-11-14 15:47:12,684 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0746) Prec@1 86.000 (87.875) Prec@5 99.000 (99.338) +2022-11-14 15:47:12,694 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0748) Prec@1 85.000 (87.840) Prec@5 97.000 (99.309) +2022-11-14 15:47:12,704 Test: [81/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0747) Prec@1 89.000 (87.854) Prec@5 99.000 (99.305) +2022-11-14 15:47:12,714 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0749) Prec@1 86.000 (87.831) Prec@5 100.000 (99.313) +2022-11-14 15:47:12,724 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0748) Prec@1 91.000 (87.869) Prec@5 99.000 (99.310) +2022-11-14 15:47:12,735 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0749) Prec@1 86.000 (87.847) Prec@5 100.000 (99.318) +2022-11-14 15:47:12,746 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0752) Prec@1 84.000 (87.802) Prec@5 100.000 (99.326) +2022-11-14 15:47:12,757 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0752) Prec@1 90.000 (87.828) Prec@5 99.000 (99.322) +2022-11-14 15:47:12,767 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0751) Prec@1 89.000 (87.841) Prec@5 99.000 (99.318) +2022-11-14 15:47:12,778 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0753) Prec@1 87.000 (87.831) Prec@5 98.000 (99.303) +2022-11-14 15:47:12,789 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0753) Prec@1 90.000 (87.856) Prec@5 98.000 (99.289) +2022-11-14 15:47:12,800 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0750) Prec@1 91.000 (87.890) Prec@5 100.000 (99.297) +2022-11-14 15:47:12,812 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0749) Prec@1 91.000 (87.924) Prec@5 100.000 (99.304) +2022-11-14 15:47:12,823 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0749) Prec@1 87.000 (87.914) Prec@5 100.000 (99.312) +2022-11-14 15:47:12,836 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0747) Prec@1 90.000 (87.936) Prec@5 99.000 (99.309) +2022-11-14 15:47:12,847 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0750) Prec@1 84.000 (87.895) Prec@5 98.000 (99.295) +2022-11-14 15:47:12,856 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0751) Prec@1 89.000 (87.906) Prec@5 99.000 (99.292) +2022-11-14 15:47:12,866 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0748) Prec@1 93.000 (87.959) Prec@5 99.000 (99.289) +2022-11-14 15:47:12,875 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0749) Prec@1 87.000 (87.949) Prec@5 98.000 (99.276) +2022-11-14 15:47:12,885 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0752) Prec@1 83.000 (87.899) Prec@5 100.000 (99.283) +2022-11-14 15:47:12,895 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0750) Prec@1 91.000 (87.930) Prec@5 99.000 (99.280) +2022-11-14 15:47:12,954 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:47:13,285 Epoch: [261][0/500] Time 0.030 (0.030) Data 0.238 (0.238) Loss 0.0483 (0.0483) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:13,524 Epoch: [261][10/500] Time 0.021 (0.022) Data 0.002 (0.023) Loss 0.0330 (0.0407) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:47:13,756 Epoch: [261][20/500] Time 0.020 (0.022) Data 0.002 (0.013) Loss 0.0569 (0.0461) Prec@1 90.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:13,986 Epoch: [261][30/500] Time 0.021 (0.021) Data 0.001 (0.009) Loss 0.0196 (0.0395) Prec@1 97.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:14,219 Epoch: [261][40/500] Time 0.019 (0.021) Data 0.002 (0.007) Loss 0.0244 (0.0364) Prec@1 97.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 15:47:14,461 Epoch: [261][50/500] Time 0.022 (0.021) Data 0.002 (0.006) Loss 0.0319 (0.0357) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:47:14,695 Epoch: [261][60/500] Time 0.023 (0.021) Data 0.001 (0.006) Loss 0.0191 (0.0333) Prec@1 97.000 (94.857) Prec@5 100.000 (100.000) +2022-11-14 15:47:14,939 Epoch: [261][70/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0408 (0.0343) Prec@1 95.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 15:47:15,186 Epoch: [261][80/500] Time 0.020 (0.021) Data 0.002 (0.005) Loss 0.0573 (0.0368) Prec@1 88.000 (94.111) Prec@5 100.000 (100.000) +2022-11-14 15:47:15,421 Epoch: [261][90/500] Time 0.021 (0.021) Data 0.001 (0.004) Loss 0.0361 (0.0367) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:15,665 Epoch: [261][100/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0316 (0.0363) Prec@1 95.000 (94.091) Prec@5 99.000 (99.909) +2022-11-14 15:47:15,911 Epoch: [261][110/500] Time 0.022 (0.021) Data 0.002 (0.004) Loss 0.0382 (0.0364) Prec@1 95.000 (94.167) Prec@5 100.000 (99.917) +2022-11-14 15:47:16,154 Epoch: [261][120/500] Time 0.024 (0.021) Data 0.002 (0.004) Loss 0.0402 (0.0367) Prec@1 94.000 (94.154) Prec@5 100.000 (99.923) +2022-11-14 15:47:16,392 Epoch: [261][130/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0217 (0.0357) Prec@1 96.000 (94.286) Prec@5 100.000 (99.929) +2022-11-14 15:47:16,637 Epoch: [261][140/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0557 (0.0370) Prec@1 89.000 (93.933) Prec@5 100.000 (99.933) +2022-11-14 15:47:16,870 Epoch: [261][150/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0331 (0.0367) Prec@1 92.000 (93.812) Prec@5 100.000 (99.938) +2022-11-14 15:47:17,109 Epoch: [261][160/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0139 (0.0354) Prec@1 98.000 (94.059) Prec@5 100.000 (99.941) +2022-11-14 15:47:17,363 Epoch: [261][170/500] Time 0.031 (0.021) Data 0.002 (0.003) Loss 0.0267 (0.0349) Prec@1 96.000 (94.167) Prec@5 100.000 (99.944) +2022-11-14 15:47:17,741 Epoch: [261][180/500] Time 0.033 (0.022) Data 0.002 (0.003) Loss 0.0528 (0.0359) Prec@1 90.000 (93.947) Prec@5 100.000 (99.947) +2022-11-14 15:47:18,117 Epoch: [261][190/500] Time 0.036 (0.023) Data 0.002 (0.003) Loss 0.0301 (0.0356) Prec@1 94.000 (93.950) Prec@5 100.000 (99.950) +2022-11-14 15:47:18,506 Epoch: [261][200/500] Time 0.037 (0.023) Data 0.002 (0.003) Loss 0.0174 (0.0347) Prec@1 98.000 (94.143) Prec@5 100.000 (99.952) +2022-11-14 15:47:18,882 Epoch: [261][210/500] Time 0.037 (0.024) Data 0.002 (0.003) Loss 0.0484 (0.0353) Prec@1 91.000 (94.000) Prec@5 100.000 (99.955) +2022-11-14 15:47:19,260 Epoch: [261][220/500] Time 0.036 (0.024) Data 0.002 (0.003) Loss 0.0283 (0.0350) Prec@1 93.000 (93.957) Prec@5 100.000 (99.957) +2022-11-14 15:47:19,620 Epoch: [261][230/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0662 (0.0363) Prec@1 88.000 (93.708) Prec@5 100.000 (99.958) +2022-11-14 15:47:20,013 Epoch: [261][240/500] Time 0.037 (0.025) Data 0.002 (0.003) Loss 0.0292 (0.0360) Prec@1 97.000 (93.840) Prec@5 100.000 (99.960) +2022-11-14 15:47:20,417 Epoch: [261][250/500] Time 0.044 (0.025) Data 0.002 (0.003) Loss 0.0248 (0.0356) Prec@1 95.000 (93.885) Prec@5 100.000 (99.962) +2022-11-14 15:47:20,851 Epoch: [261][260/500] Time 0.039 (0.026) Data 0.002 (0.003) Loss 0.0396 (0.0358) Prec@1 92.000 (93.815) Prec@5 100.000 (99.963) +2022-11-14 15:47:21,294 Epoch: [261][270/500] Time 0.040 (0.026) Data 0.002 (0.003) Loss 0.0480 (0.0362) Prec@1 91.000 (93.714) Prec@5 100.000 (99.964) +2022-11-14 15:47:21,728 Epoch: [261][280/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0272 (0.0359) Prec@1 95.000 (93.759) Prec@5 99.000 (99.931) +2022-11-14 15:47:22,099 Epoch: [261][290/500] Time 0.034 (0.027) Data 0.002 (0.003) Loss 0.0321 (0.0358) Prec@1 96.000 (93.833) Prec@5 99.000 (99.900) +2022-11-14 15:47:22,484 Epoch: [261][300/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.0291 (0.0355) Prec@1 95.000 (93.871) Prec@5 100.000 (99.903) +2022-11-14 15:47:22,870 Epoch: [261][310/500] Time 0.036 (0.027) Data 0.002 (0.003) Loss 0.0511 (0.0360) Prec@1 92.000 (93.812) Prec@5 99.000 (99.875) +2022-11-14 15:47:23,242 Epoch: [261][320/500] Time 0.030 (0.028) Data 0.002 (0.003) Loss 0.0151 (0.0354) Prec@1 98.000 (93.939) Prec@5 100.000 (99.879) +2022-11-14 15:47:23,611 Epoch: [261][330/500] Time 0.035 (0.028) Data 0.002 (0.003) Loss 0.0282 (0.0352) Prec@1 96.000 (94.000) Prec@5 100.000 (99.882) +2022-11-14 15:47:23,986 Epoch: [261][340/500] Time 0.038 (0.028) Data 0.002 (0.003) Loss 0.0244 (0.0349) Prec@1 96.000 (94.057) Prec@5 100.000 (99.886) +2022-11-14 15:47:24,366 Epoch: [261][350/500] Time 0.035 (0.028) Data 0.002 (0.002) Loss 0.0411 (0.0350) Prec@1 94.000 (94.056) Prec@5 100.000 (99.889) +2022-11-14 15:47:24,735 Epoch: [261][360/500] Time 0.040 (0.028) Data 0.002 (0.002) Loss 0.0429 (0.0353) Prec@1 93.000 (94.027) Prec@5 100.000 (99.892) +2022-11-14 15:47:25,115 Epoch: [261][370/500] Time 0.034 (0.028) Data 0.002 (0.002) Loss 0.0181 (0.0348) Prec@1 98.000 (94.132) Prec@5 100.000 (99.895) +2022-11-14 15:47:25,492 Epoch: [261][380/500] Time 0.030 (0.029) Data 0.002 (0.002) Loss 0.0332 (0.0348) Prec@1 92.000 (94.077) Prec@5 100.000 (99.897) +2022-11-14 15:47:25,885 Epoch: [261][390/500] Time 0.034 (0.029) Data 0.002 (0.002) Loss 0.0201 (0.0344) Prec@1 96.000 (94.125) Prec@5 100.000 (99.900) +2022-11-14 15:47:26,258 Epoch: [261][400/500] Time 0.036 (0.029) Data 0.002 (0.002) Loss 0.0294 (0.0343) Prec@1 95.000 (94.146) Prec@5 100.000 (99.902) +2022-11-14 15:47:26,645 Epoch: [261][410/500] Time 0.036 (0.029) Data 0.002 (0.002) Loss 0.0190 (0.0339) Prec@1 97.000 (94.214) Prec@5 100.000 (99.905) +2022-11-14 15:47:27,035 Epoch: [261][420/500] Time 0.037 (0.029) Data 0.002 (0.002) Loss 0.0331 (0.0339) Prec@1 95.000 (94.233) Prec@5 100.000 (99.907) +2022-11-14 15:47:27,409 Epoch: [261][430/500] Time 0.033 (0.029) Data 0.002 (0.002) Loss 0.0394 (0.0340) Prec@1 95.000 (94.250) Prec@5 100.000 (99.909) +2022-11-14 15:47:27,787 Epoch: [261][440/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.0273 (0.0339) Prec@1 96.000 (94.289) Prec@5 100.000 (99.911) +2022-11-14 15:47:28,156 Epoch: [261][450/500] Time 0.039 (0.029) Data 0.003 (0.002) Loss 0.0251 (0.0337) Prec@1 96.000 (94.326) Prec@5 100.000 (99.913) +2022-11-14 15:47:28,519 Epoch: [261][460/500] Time 0.043 (0.029) Data 0.002 (0.002) Loss 0.0353 (0.0337) Prec@1 94.000 (94.319) Prec@5 100.000 (99.915) +2022-11-14 15:47:28,900 Epoch: [261][470/500] Time 0.029 (0.030) Data 0.002 (0.002) Loss 0.0463 (0.0340) Prec@1 90.000 (94.229) Prec@5 100.000 (99.917) +2022-11-14 15:47:29,278 Epoch: [261][480/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.0338 (0.0340) Prec@1 95.000 (94.245) Prec@5 100.000 (99.918) +2022-11-14 15:47:29,634 Epoch: [261][490/500] Time 0.036 (0.030) Data 0.003 (0.002) Loss 0.0355 (0.0340) Prec@1 94.000 (94.240) Prec@5 100.000 (99.920) +2022-11-14 15:47:29,980 Epoch: [261][499/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0514 (0.0343) Prec@1 92.000 (94.196) Prec@5 99.000 (99.902) +2022-11-14 15:47:30,268 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0801 (0.0801) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:30,279 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0752 (0.0776) Prec@1 87.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 15:47:30,288 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0723 (0.0759) Prec@1 87.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 15:47:30,302 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0915 (0.0798) Prec@1 84.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 15:47:30,313 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0795) Prec@1 84.000 (86.000) Prec@5 100.000 (99.600) +2022-11-14 15:47:30,323 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0754) Prec@1 92.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 15:47:30,333 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0740) Prec@1 91.000 (87.571) Prec@5 100.000 (99.714) +2022-11-14 15:47:30,348 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0756) Prec@1 85.000 (87.250) Prec@5 99.000 (99.625) +2022-11-14 15:47:30,357 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0763) Prec@1 88.000 (87.333) Prec@5 99.000 (99.556) +2022-11-14 15:47:30,367 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0767) Prec@1 86.000 (87.200) Prec@5 99.000 (99.500) +2022-11-14 15:47:30,378 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0750) Prec@1 91.000 (87.545) Prec@5 100.000 (99.545) +2022-11-14 15:47:30,390 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0747) Prec@1 90.000 (87.750) Prec@5 100.000 (99.583) +2022-11-14 15:47:30,402 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0401 (0.0720) Prec@1 94.000 (88.231) Prec@5 100.000 (99.615) +2022-11-14 15:47:30,413 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0723) Prec@1 89.000 (88.286) Prec@5 99.000 (99.571) +2022-11-14 15:47:30,424 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0732) Prec@1 85.000 (88.067) Prec@5 100.000 (99.600) +2022-11-14 15:47:30,435 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0740) Prec@1 84.000 (87.812) Prec@5 100.000 (99.625) +2022-11-14 15:47:30,447 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0391 (0.0720) Prec@1 94.000 (88.176) Prec@5 98.000 (99.529) +2022-11-14 15:47:30,459 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0731) Prec@1 86.000 (88.056) Prec@5 100.000 (99.556) +2022-11-14 15:47:30,469 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0735) Prec@1 87.000 (88.000) Prec@5 99.000 (99.526) +2022-11-14 15:47:30,480 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0745) Prec@1 86.000 (87.900) Prec@5 100.000 (99.550) +2022-11-14 15:47:30,491 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0752) Prec@1 85.000 (87.762) Prec@5 100.000 (99.571) +2022-11-14 15:47:30,503 Test: [21/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0753) Prec@1 90.000 (87.864) Prec@5 98.000 (99.500) +2022-11-14 15:47:30,515 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0757) Prec@1 87.000 (87.826) Prec@5 97.000 (99.391) +2022-11-14 15:47:30,526 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0760) Prec@1 86.000 (87.750) Prec@5 100.000 (99.417) +2022-11-14 15:47:30,536 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0762) Prec@1 86.000 (87.680) Prec@5 99.000 (99.400) +2022-11-14 15:47:30,548 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0771) Prec@1 84.000 (87.538) Prec@5 98.000 (99.346) +2022-11-14 15:47:30,559 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0767) Prec@1 88.000 (87.556) Prec@5 100.000 (99.370) +2022-11-14 15:47:30,570 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0767) Prec@1 88.000 (87.571) Prec@5 100.000 (99.393) +2022-11-14 15:47:30,581 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0765) Prec@1 88.000 (87.586) Prec@5 99.000 (99.379) +2022-11-14 15:47:30,592 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0772) Prec@1 85.000 (87.500) Prec@5 98.000 (99.333) +2022-11-14 15:47:30,602 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0774) Prec@1 88.000 (87.516) Prec@5 99.000 (99.323) +2022-11-14 15:47:30,614 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0772) Prec@1 89.000 (87.562) Prec@5 99.000 (99.312) +2022-11-14 15:47:30,625 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0774) Prec@1 84.000 (87.455) Prec@5 99.000 (99.303) +2022-11-14 15:47:30,635 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0775) Prec@1 87.000 (87.441) Prec@5 100.000 (99.324) +2022-11-14 15:47:30,647 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0780) Prec@1 84.000 (87.343) Prec@5 98.000 (99.286) +2022-11-14 15:47:30,658 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0775) Prec@1 90.000 (87.417) Prec@5 100.000 (99.306) +2022-11-14 15:47:30,668 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0772) Prec@1 90.000 (87.486) Prec@5 99.000 (99.297) +2022-11-14 15:47:30,679 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0777) Prec@1 85.000 (87.421) Prec@5 99.000 (99.289) +2022-11-14 15:47:30,689 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0775) Prec@1 90.000 (87.487) Prec@5 99.000 (99.282) +2022-11-14 15:47:30,700 Test: [39/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0773) Prec@1 87.000 (87.475) Prec@5 100.000 (99.300) +2022-11-14 15:47:30,711 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0774) Prec@1 88.000 (87.488) Prec@5 99.000 (99.293) +2022-11-14 15:47:30,722 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0771) Prec@1 89.000 (87.524) Prec@5 100.000 (99.310) +2022-11-14 15:47:30,734 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0439 (0.0763) Prec@1 94.000 (87.674) Prec@5 99.000 (99.302) +2022-11-14 15:47:30,746 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0763) Prec@1 90.000 (87.727) Prec@5 99.000 (99.295) +2022-11-14 15:47:30,757 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0759) Prec@1 90.000 (87.778) Prec@5 100.000 (99.311) +2022-11-14 15:47:30,767 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0762) Prec@1 85.000 (87.717) Prec@5 99.000 (99.304) +2022-11-14 15:47:30,778 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0760) Prec@1 90.000 (87.766) Prec@5 100.000 (99.319) +2022-11-14 15:47:30,787 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0764) Prec@1 82.000 (87.646) Prec@5 99.000 (99.312) +2022-11-14 15:47:30,799 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0758) Prec@1 91.000 (87.714) Prec@5 100.000 (99.327) +2022-11-14 15:47:30,811 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0763) Prec@1 82.000 (87.600) Prec@5 99.000 (99.320) +2022-11-14 15:47:30,820 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0760) Prec@1 88.000 (87.608) Prec@5 100.000 (99.333) +2022-11-14 15:47:30,830 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0763) Prec@1 84.000 (87.538) Prec@5 100.000 (99.346) +2022-11-14 15:47:30,842 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0761) Prec@1 89.000 (87.566) Prec@5 100.000 (99.358) +2022-11-14 15:47:30,854 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0761) Prec@1 87.000 (87.556) Prec@5 99.000 (99.352) +2022-11-14 15:47:30,865 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0766) Prec@1 86.000 (87.527) Prec@5 100.000 (99.364) +2022-11-14 15:47:30,875 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0770) Prec@1 84.000 (87.464) Prec@5 99.000 (99.357) +2022-11-14 15:47:30,885 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0770) Prec@1 86.000 (87.439) Prec@5 99.000 (99.351) +2022-11-14 15:47:30,899 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0767) Prec@1 91.000 (87.500) Prec@5 99.000 (99.345) +2022-11-14 15:47:30,910 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0772) Prec@1 82.000 (87.407) Prec@5 100.000 (99.356) +2022-11-14 15:47:30,921 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0772) Prec@1 85.000 (87.367) Prec@5 100.000 (99.367) +2022-11-14 15:47:30,930 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0771) Prec@1 90.000 (87.410) Prec@5 100.000 (99.377) +2022-11-14 15:47:30,940 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0768) Prec@1 91.000 (87.468) Prec@5 100.000 (99.387) +2022-11-14 15:47:30,952 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0768) Prec@1 87.000 (87.460) Prec@5 99.000 (99.381) +2022-11-14 15:47:30,962 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0404 (0.0763) Prec@1 94.000 (87.562) Prec@5 100.000 (99.391) +2022-11-14 15:47:30,973 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0762) Prec@1 89.000 (87.585) Prec@5 100.000 (99.400) +2022-11-14 15:47:30,984 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0760) Prec@1 88.000 (87.591) Prec@5 99.000 (99.394) +2022-11-14 15:47:30,995 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0370 (0.0754) Prec@1 94.000 (87.687) Prec@5 100.000 (99.403) +2022-11-14 15:47:31,007 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0753) Prec@1 91.000 (87.735) Prec@5 99.000 (99.397) +2022-11-14 15:47:31,017 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0751) Prec@1 87.000 (87.725) Prec@5 99.000 (99.391) +2022-11-14 15:47:31,028 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0753) Prec@1 88.000 (87.729) Prec@5 98.000 (99.371) +2022-11-14 15:47:31,039 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0758) Prec@1 85.000 (87.690) Prec@5 98.000 (99.352) +2022-11-14 15:47:31,050 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0756) Prec@1 90.000 (87.722) Prec@5 100.000 (99.361) +2022-11-14 15:47:31,062 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0751) Prec@1 94.000 (87.808) Prec@5 100.000 (99.370) +2022-11-14 15:47:31,073 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0368 (0.0746) Prec@1 96.000 (87.919) Prec@5 100.000 (99.378) +2022-11-14 15:47:31,086 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1265 (0.0753) Prec@1 79.000 (87.800) Prec@5 100.000 (99.387) +2022-11-14 15:47:31,099 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0753) Prec@1 88.000 (87.803) Prec@5 97.000 (99.355) +2022-11-14 15:47:31,110 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0752) Prec@1 89.000 (87.818) Prec@5 98.000 (99.338) +2022-11-14 15:47:31,121 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0754) Prec@1 85.000 (87.782) Prec@5 100.000 (99.346) +2022-11-14 15:47:31,132 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0757) Prec@1 84.000 (87.734) Prec@5 100.000 (99.354) +2022-11-14 15:47:31,143 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0757) Prec@1 83.000 (87.675) Prec@5 100.000 (99.362) +2022-11-14 15:47:31,155 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0761) Prec@1 86.000 (87.654) Prec@5 98.000 (99.346) +2022-11-14 15:47:31,166 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0763) Prec@1 84.000 (87.610) Prec@5 100.000 (99.354) +2022-11-14 15:47:31,178 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0763) Prec@1 85.000 (87.578) Prec@5 100.000 (99.361) +2022-11-14 15:47:31,189 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0764) Prec@1 86.000 (87.560) Prec@5 99.000 (99.357) +2022-11-14 15:47:31,202 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0766) Prec@1 84.000 (87.518) Prec@5 99.000 (99.353) +2022-11-14 15:47:31,216 Test: [85/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0769) Prec@1 81.000 (87.442) Prec@5 100.000 (99.360) +2022-11-14 15:47:31,228 Test: [86/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0768) Prec@1 86.000 (87.425) Prec@5 100.000 (99.368) +2022-11-14 15:47:31,240 Test: [87/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0768) Prec@1 87.000 (87.420) Prec@5 99.000 (99.364) +2022-11-14 15:47:31,254 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0767) Prec@1 86.000 (87.404) Prec@5 98.000 (99.348) +2022-11-14 15:47:31,266 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0767) Prec@1 88.000 (87.411) Prec@5 100.000 (99.356) +2022-11-14 15:47:31,277 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0764) Prec@1 89.000 (87.429) Prec@5 100.000 (99.363) +2022-11-14 15:47:31,288 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0417 (0.0760) Prec@1 93.000 (87.489) Prec@5 99.000 (99.359) +2022-11-14 15:47:31,299 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0762) Prec@1 85.000 (87.462) Prec@5 100.000 (99.366) +2022-11-14 15:47:31,310 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0762) Prec@1 88.000 (87.468) Prec@5 99.000 (99.362) +2022-11-14 15:47:31,322 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0763) Prec@1 87.000 (87.463) Prec@5 99.000 (99.358) +2022-11-14 15:47:31,333 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0762) Prec@1 87.000 (87.458) Prec@5 99.000 (99.354) +2022-11-14 15:47:31,345 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0378 (0.0758) Prec@1 93.000 (87.515) Prec@5 99.000 (99.351) +2022-11-14 15:47:31,356 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0760) Prec@1 83.000 (87.469) Prec@5 97.000 (99.327) +2022-11-14 15:47:31,367 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0762) Prec@1 86.000 (87.455) Prec@5 98.000 (99.313) +2022-11-14 15:47:31,377 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0760) Prec@1 92.000 (87.500) Prec@5 100.000 (99.320) +2022-11-14 15:47:31,449 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:47:31,797 Epoch: [262][0/500] Time 0.024 (0.024) Data 0.250 (0.250) Loss 0.0403 (0.0403) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:32,046 Epoch: [262][10/500] Time 0.022 (0.022) Data 0.002 (0.024) Loss 0.0173 (0.0288) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:47:32,278 Epoch: [262][20/500] Time 0.022 (0.022) Data 0.002 (0.014) Loss 0.0357 (0.0311) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 15:47:32,504 Epoch: [262][30/500] Time 0.019 (0.021) Data 0.002 (0.010) Loss 0.0479 (0.0353) Prec@1 91.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 15:47:32,742 Epoch: [262][40/500] Time 0.024 (0.021) Data 0.002 (0.008) Loss 0.0155 (0.0313) Prec@1 99.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 15:47:32,975 Epoch: [262][50/500] Time 0.020 (0.021) Data 0.002 (0.007) Loss 0.0410 (0.0329) Prec@1 93.000 (94.833) Prec@5 99.000 (99.833) +2022-11-14 15:47:33,209 Epoch: [262][60/500] Time 0.021 (0.021) Data 0.002 (0.006) Loss 0.0259 (0.0319) Prec@1 96.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 15:47:33,443 Epoch: [262][70/500] Time 0.023 (0.021) Data 0.002 (0.005) Loss 0.0211 (0.0306) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 15:47:33,674 Epoch: [262][80/500] Time 0.017 (0.021) Data 0.001 (0.005) Loss 0.0430 (0.0320) Prec@1 93.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 15:47:33,907 Epoch: [262][90/500] Time 0.020 (0.021) Data 0.002 (0.004) Loss 0.0314 (0.0319) Prec@1 95.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 15:47:34,138 Epoch: [262][100/500] Time 0.017 (0.021) Data 0.003 (0.004) Loss 0.0338 (0.0321) Prec@1 95.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 15:47:34,380 Epoch: [262][110/500] Time 0.021 (0.021) Data 0.002 (0.004) Loss 0.0544 (0.0339) Prec@1 92.000 (94.667) Prec@5 98.000 (99.750) +2022-11-14 15:47:34,622 Epoch: [262][120/500] Time 0.021 (0.021) Data 0.002 (0.004) Loss 0.0473 (0.0350) Prec@1 93.000 (94.538) Prec@5 100.000 (99.769) +2022-11-14 15:47:34,907 Epoch: [262][130/500] Time 0.028 (0.021) Data 0.002 (0.004) Loss 0.0338 (0.0349) Prec@1 95.000 (94.571) Prec@5 100.000 (99.786) +2022-11-14 15:47:35,237 Epoch: [262][140/500] Time 0.029 (0.022) Data 0.002 (0.004) Loss 0.0459 (0.0356) Prec@1 92.000 (94.400) Prec@5 99.000 (99.733) +2022-11-14 15:47:35,564 Epoch: [262][150/500] Time 0.034 (0.022) Data 0.002 (0.003) Loss 0.0181 (0.0345) Prec@1 96.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 15:47:35,887 Epoch: [262][160/500] Time 0.035 (0.023) Data 0.002 (0.003) Loss 0.0378 (0.0347) Prec@1 92.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 15:47:36,197 Epoch: [262][170/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0277 (0.0343) Prec@1 96.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 15:47:36,524 Epoch: [262][180/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0238 (0.0338) Prec@1 96.000 (94.526) Prec@5 99.000 (99.737) +2022-11-14 15:47:36,843 Epoch: [262][190/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0290 (0.0335) Prec@1 94.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 15:47:37,171 Epoch: [262][200/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0595 (0.0348) Prec@1 91.000 (94.333) Prec@5 98.000 (99.667) +2022-11-14 15:47:37,496 Epoch: [262][210/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0244 (0.0343) Prec@1 96.000 (94.409) Prec@5 100.000 (99.682) +2022-11-14 15:47:37,814 Epoch: [262][220/500] Time 0.035 (0.024) Data 0.002 (0.003) Loss 0.0317 (0.0342) Prec@1 94.000 (94.391) Prec@5 100.000 (99.696) +2022-11-14 15:47:38,144 Epoch: [262][230/500] Time 0.033 (0.024) Data 0.002 (0.003) Loss 0.0320 (0.0341) Prec@1 94.000 (94.375) Prec@5 100.000 (99.708) +2022-11-14 15:47:38,464 Epoch: [262][240/500] Time 0.023 (0.025) Data 0.002 (0.003) Loss 0.0154 (0.0334) Prec@1 98.000 (94.520) Prec@5 100.000 (99.720) +2022-11-14 15:47:38,790 Epoch: [262][250/500] Time 0.025 (0.025) Data 0.002 (0.003) Loss 0.0403 (0.0336) Prec@1 93.000 (94.462) Prec@5 100.000 (99.731) +2022-11-14 15:47:39,111 Epoch: [262][260/500] Time 0.032 (0.025) Data 0.002 (0.003) Loss 0.0459 (0.0341) Prec@1 94.000 (94.444) Prec@5 100.000 (99.741) +2022-11-14 15:47:39,433 Epoch: [262][270/500] Time 0.025 (0.025) Data 0.002 (0.003) Loss 0.0384 (0.0342) Prec@1 93.000 (94.393) Prec@5 100.000 (99.750) +2022-11-14 15:47:39,758 Epoch: [262][280/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0548 (0.0349) Prec@1 93.000 (94.345) Prec@5 98.000 (99.690) +2022-11-14 15:47:40,088 Epoch: [262][290/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0227 (0.0345) Prec@1 97.000 (94.433) Prec@5 100.000 (99.700) +2022-11-14 15:47:40,408 Epoch: [262][300/500] Time 0.032 (0.025) Data 0.002 (0.003) Loss 0.0470 (0.0349) Prec@1 92.000 (94.355) Prec@5 100.000 (99.710) +2022-11-14 15:47:40,730 Epoch: [262][310/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0506 (0.0354) Prec@1 92.000 (94.281) Prec@5 99.000 (99.688) +2022-11-14 15:47:41,054 Epoch: [262][320/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0483 (0.0358) Prec@1 93.000 (94.242) Prec@5 98.000 (99.636) +2022-11-14 15:47:41,374 Epoch: [262][330/500] Time 0.041 (0.026) Data 0.002 (0.003) Loss 0.0327 (0.0357) Prec@1 94.000 (94.235) Prec@5 100.000 (99.647) +2022-11-14 15:47:41,700 Epoch: [262][340/500] Time 0.033 (0.026) Data 0.002 (0.003) Loss 0.0298 (0.0356) Prec@1 96.000 (94.286) Prec@5 99.000 (99.629) +2022-11-14 15:47:42,025 Epoch: [262][350/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0380 (0.0356) Prec@1 94.000 (94.278) Prec@5 99.000 (99.611) +2022-11-14 15:47:42,354 Epoch: [262][360/500] Time 0.040 (0.026) Data 0.002 (0.003) Loss 0.0783 (0.0368) Prec@1 88.000 (94.108) Prec@5 100.000 (99.622) +2022-11-14 15:47:42,680 Epoch: [262][370/500] Time 0.034 (0.026) Data 0.002 (0.003) Loss 0.0343 (0.0367) Prec@1 94.000 (94.105) Prec@5 100.000 (99.632) +2022-11-14 15:47:43,012 Epoch: [262][380/500] Time 0.030 (0.026) Data 0.002 (0.002) Loss 0.0258 (0.0364) Prec@1 94.000 (94.103) Prec@5 100.000 (99.641) +2022-11-14 15:47:43,328 Epoch: [262][390/500] Time 0.029 (0.026) Data 0.002 (0.002) Loss 0.0431 (0.0366) Prec@1 92.000 (94.050) Prec@5 100.000 (99.650) +2022-11-14 15:47:43,656 Epoch: [262][400/500] Time 0.029 (0.026) Data 0.002 (0.002) Loss 0.0277 (0.0364) Prec@1 95.000 (94.073) Prec@5 100.000 (99.659) +2022-11-14 15:47:43,972 Epoch: [262][410/500] Time 0.021 (0.026) Data 0.002 (0.002) Loss 0.0375 (0.0364) Prec@1 92.000 (94.024) Prec@5 100.000 (99.667) +2022-11-14 15:47:44,307 Epoch: [262][420/500] Time 0.035 (0.026) Data 0.002 (0.002) Loss 0.0198 (0.0360) Prec@1 97.000 (94.093) Prec@5 99.000 (99.651) +2022-11-14 15:47:44,628 Epoch: [262][430/500] Time 0.030 (0.026) Data 0.002 (0.002) Loss 0.0354 (0.0360) Prec@1 95.000 (94.114) Prec@5 100.000 (99.659) +2022-11-14 15:47:44,957 Epoch: [262][440/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.0532 (0.0364) Prec@1 91.000 (94.044) Prec@5 100.000 (99.667) +2022-11-14 15:47:45,283 Epoch: [262][450/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0336 (0.0363) Prec@1 93.000 (94.022) Prec@5 100.000 (99.674) +2022-11-14 15:47:45,605 Epoch: [262][460/500] Time 0.032 (0.027) Data 0.002 (0.002) Loss 0.0486 (0.0366) Prec@1 93.000 (94.000) Prec@5 98.000 (99.638) +2022-11-14 15:47:45,929 Epoch: [262][470/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.0290 (0.0364) Prec@1 95.000 (94.021) Prec@5 100.000 (99.646) +2022-11-14 15:47:46,250 Epoch: [262][480/500] Time 0.032 (0.027) Data 0.002 (0.002) Loss 0.0430 (0.0366) Prec@1 94.000 (94.020) Prec@5 100.000 (99.653) +2022-11-14 15:47:46,580 Epoch: [262][490/500] Time 0.036 (0.027) Data 0.002 (0.002) Loss 0.0488 (0.0368) Prec@1 92.000 (93.980) Prec@5 100.000 (99.660) +2022-11-14 15:47:46,860 Epoch: [262][499/500] Time 0.023 (0.027) Data 0.001 (0.002) Loss 0.0293 (0.0367) Prec@1 94.000 (93.980) Prec@5 100.000 (99.667) +2022-11-14 15:47:47,172 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0611 (0.0611) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:47,182 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0629) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 15:47:47,193 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0683) Prec@1 87.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 15:47:47,206 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0699) Prec@1 86.000 (87.500) Prec@5 100.000 (99.750) +2022-11-14 15:47:47,217 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0732) Prec@1 86.000 (87.200) Prec@5 100.000 (99.800) +2022-11-14 15:47:47,227 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0718) Prec@1 90.000 (87.667) Prec@5 99.000 (99.667) +2022-11-14 15:47:47,238 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0727) Prec@1 87.000 (87.571) Prec@5 100.000 (99.714) +2022-11-14 15:47:47,251 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0735) Prec@1 88.000 (87.625) Prec@5 100.000 (99.750) +2022-11-14 15:47:47,261 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 88.000 (87.667) Prec@5 98.000 (99.556) +2022-11-14 15:47:47,272 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0724) Prec@1 91.000 (88.000) Prec@5 98.000 (99.400) +2022-11-14 15:47:47,284 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0710) Prec@1 89.000 (88.091) Prec@5 100.000 (99.455) +2022-11-14 15:47:47,296 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0721) Prec@1 85.000 (87.833) Prec@5 99.000 (99.417) +2022-11-14 15:47:47,308 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0704) Prec@1 94.000 (88.308) Prec@5 100.000 (99.462) +2022-11-14 15:47:47,320 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0710) Prec@1 84.000 (88.000) Prec@5 99.000 (99.429) +2022-11-14 15:47:47,331 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0708) Prec@1 90.000 (88.133) Prec@5 100.000 (99.467) +2022-11-14 15:47:47,342 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0727) Prec@1 82.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 15:47:47,356 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0709) Prec@1 93.000 (88.059) Prec@5 99.000 (99.471) +2022-11-14 15:47:47,367 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0722) Prec@1 84.000 (87.833) Prec@5 100.000 (99.500) +2022-11-14 15:47:47,377 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0728) Prec@1 86.000 (87.737) Prec@5 99.000 (99.474) +2022-11-14 15:47:47,388 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0739) Prec@1 84.000 (87.550) Prec@5 97.000 (99.350) +2022-11-14 15:47:47,398 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0741) Prec@1 86.000 (87.476) Prec@5 99.000 (99.333) +2022-11-14 15:47:47,410 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0750) Prec@1 87.000 (87.455) Prec@5 98.000 (99.273) +2022-11-14 15:47:47,420 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0756) Prec@1 87.000 (87.435) Prec@5 98.000 (99.217) +2022-11-14 15:47:47,430 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0759) Prec@1 85.000 (87.333) Prec@5 99.000 (99.208) +2022-11-14 15:47:47,442 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0758) Prec@1 88.000 (87.360) Prec@5 100.000 (99.240) +2022-11-14 15:47:47,454 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0767) Prec@1 85.000 (87.269) Prec@5 99.000 (99.231) +2022-11-14 15:47:47,465 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0760) Prec@1 92.000 (87.444) Prec@5 99.000 (99.222) +2022-11-14 15:47:47,476 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0753) Prec@1 91.000 (87.571) Prec@5 100.000 (99.250) +2022-11-14 15:47:47,488 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0748) Prec@1 90.000 (87.655) Prec@5 99.000 (99.241) +2022-11-14 15:47:47,500 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 87.000 (87.633) Prec@5 100.000 (99.267) +2022-11-14 15:47:47,511 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0754) Prec@1 87.000 (87.613) Prec@5 99.000 (99.258) +2022-11-14 15:47:47,523 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0754) Prec@1 88.000 (87.625) Prec@5 100.000 (99.281) +2022-11-14 15:47:47,535 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0754) Prec@1 88.000 (87.636) Prec@5 100.000 (99.303) +2022-11-14 15:47:47,546 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0760) Prec@1 85.000 (87.559) Prec@5 100.000 (99.324) +2022-11-14 15:47:47,557 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0763) Prec@1 86.000 (87.514) Prec@5 99.000 (99.314) +2022-11-14 15:47:47,568 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0758) Prec@1 92.000 (87.639) Prec@5 100.000 (99.333) +2022-11-14 15:47:47,578 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0762) Prec@1 84.000 (87.541) Prec@5 99.000 (99.324) +2022-11-14 15:47:47,589 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0767) Prec@1 85.000 (87.474) Prec@5 100.000 (99.342) +2022-11-14 15:47:47,599 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0765) Prec@1 91.000 (87.564) Prec@5 99.000 (99.333) +2022-11-14 15:47:47,610 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0765) Prec@1 87.000 (87.550) Prec@5 99.000 (99.325) +2022-11-14 15:47:47,621 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1105 (0.0773) Prec@1 84.000 (87.463) Prec@5 99.000 (99.317) +2022-11-14 15:47:47,634 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0771) Prec@1 89.000 (87.500) Prec@5 99.000 (99.310) +2022-11-14 15:47:47,645 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0767) Prec@1 89.000 (87.535) Prec@5 99.000 (99.302) +2022-11-14 15:47:47,656 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0769) Prec@1 89.000 (87.568) Prec@5 98.000 (99.273) +2022-11-14 15:47:47,666 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0764) Prec@1 92.000 (87.667) Prec@5 100.000 (99.289) +2022-11-14 15:47:47,677 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0768) Prec@1 85.000 (87.609) Prec@5 99.000 (99.283) +2022-11-14 15:47:47,687 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0764) Prec@1 91.000 (87.681) Prec@5 100.000 (99.298) +2022-11-14 15:47:47,698 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1256 (0.0775) Prec@1 78.000 (87.479) Prec@5 99.000 (99.292) +2022-11-14 15:47:47,707 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0770) Prec@1 91.000 (87.551) Prec@5 100.000 (99.306) +2022-11-14 15:47:47,718 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0777) Prec@1 85.000 (87.500) Prec@5 100.000 (99.320) +2022-11-14 15:47:47,731 Test: [50/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0780) Prec@1 85.000 (87.451) Prec@5 100.000 (99.333) +2022-11-14 15:47:47,743 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0782) Prec@1 85.000 (87.404) Prec@5 98.000 (99.308) +2022-11-14 15:47:47,756 Test: [52/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0781) Prec@1 88.000 (87.415) Prec@5 100.000 (99.321) +2022-11-14 15:47:47,768 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0780) Prec@1 89.000 (87.444) Prec@5 100.000 (99.333) +2022-11-14 15:47:47,781 Test: [54/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0784) Prec@1 84.000 (87.382) Prec@5 100.000 (99.345) +2022-11-14 15:47:47,794 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0783) Prec@1 89.000 (87.411) Prec@5 99.000 (99.339) +2022-11-14 15:47:47,807 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0786) Prec@1 83.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 15:47:47,818 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0785) Prec@1 88.000 (87.345) Prec@5 98.000 (99.310) +2022-11-14 15:47:47,831 Test: [58/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1309 (0.0794) Prec@1 81.000 (87.237) Prec@5 100.000 (99.322) +2022-11-14 15:47:47,843 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0794) Prec@1 85.000 (87.200) Prec@5 100.000 (99.333) +2022-11-14 15:47:47,857 Test: [60/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0796) Prec@1 86.000 (87.180) Prec@5 99.000 (99.328) +2022-11-14 15:47:47,869 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0798) Prec@1 84.000 (87.129) Prec@5 98.000 (99.306) +2022-11-14 15:47:47,882 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0793) Prec@1 92.000 (87.206) Prec@5 100.000 (99.317) +2022-11-14 15:47:47,895 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0384 (0.0787) Prec@1 94.000 (87.312) Prec@5 100.000 (99.328) +2022-11-14 15:47:47,908 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0790) Prec@1 85.000 (87.277) Prec@5 100.000 (99.338) +2022-11-14 15:47:47,920 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0789) Prec@1 87.000 (87.273) Prec@5 99.000 (99.333) +2022-11-14 15:47:47,931 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0784) Prec@1 91.000 (87.328) Prec@5 98.000 (99.313) +2022-11-14 15:47:47,942 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0785) Prec@1 88.000 (87.338) Prec@5 100.000 (99.324) +2022-11-14 15:47:47,953 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0783) Prec@1 85.000 (87.304) Prec@5 98.000 (99.304) +2022-11-14 15:47:47,963 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0785) Prec@1 85.000 (87.271) Prec@5 100.000 (99.314) +2022-11-14 15:47:47,973 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1059 (0.0789) Prec@1 85.000 (87.239) Prec@5 99.000 (99.310) +2022-11-14 15:47:47,983 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0789) Prec@1 87.000 (87.236) Prec@5 99.000 (99.306) +2022-11-14 15:47:47,995 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0786) Prec@1 92.000 (87.301) Prec@5 100.000 (99.315) +2022-11-14 15:47:48,006 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0781) Prec@1 95.000 (87.405) Prec@5 100.000 (99.324) +2022-11-14 15:47:48,018 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0785) Prec@1 83.000 (87.347) Prec@5 100.000 (99.333) +2022-11-14 15:47:48,029 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0783) Prec@1 91.000 (87.395) Prec@5 100.000 (99.342) +2022-11-14 15:47:48,040 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0783) Prec@1 88.000 (87.403) Prec@5 99.000 (99.338) +2022-11-14 15:47:48,052 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0784) Prec@1 83.000 (87.346) Prec@5 100.000 (99.346) +2022-11-14 15:47:48,064 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0787) Prec@1 84.000 (87.304) Prec@5 100.000 (99.354) +2022-11-14 15:47:48,076 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0789) Prec@1 85.000 (87.275) Prec@5 100.000 (99.362) +2022-11-14 15:47:48,087 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0790) Prec@1 86.000 (87.259) Prec@5 100.000 (99.370) +2022-11-14 15:47:48,098 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0792) Prec@1 84.000 (87.220) Prec@5 98.000 (99.354) +2022-11-14 15:47:48,109 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0794) Prec@1 83.000 (87.169) Prec@5 100.000 (99.361) +2022-11-14 15:47:48,120 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0792) Prec@1 89.000 (87.190) Prec@5 100.000 (99.369) +2022-11-14 15:47:48,132 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0792) Prec@1 86.000 (87.176) Prec@5 100.000 (99.376) +2022-11-14 15:47:48,141 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1241 (0.0797) Prec@1 80.000 (87.093) Prec@5 100.000 (99.384) +2022-11-14 15:47:48,152 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0794) Prec@1 92.000 (87.149) Prec@5 99.000 (99.379) +2022-11-14 15:47:48,164 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0795) Prec@1 85.000 (87.125) Prec@5 99.000 (99.375) +2022-11-14 15:47:48,174 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0793) Prec@1 91.000 (87.169) Prec@5 100.000 (99.382) +2022-11-14 15:47:48,185 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0793) Prec@1 87.000 (87.167) Prec@5 100.000 (99.389) +2022-11-14 15:47:48,196 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0791) Prec@1 89.000 (87.187) Prec@5 100.000 (99.396) +2022-11-14 15:47:48,207 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0788) Prec@1 92.000 (87.239) Prec@5 99.000 (99.391) +2022-11-14 15:47:48,218 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0787) Prec@1 90.000 (87.269) Prec@5 100.000 (99.398) +2022-11-14 15:47:48,228 Test: [93/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0788) Prec@1 85.000 (87.245) Prec@5 99.000 (99.394) +2022-11-14 15:47:48,238 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0787) Prec@1 86.000 (87.232) Prec@5 100.000 (99.400) +2022-11-14 15:47:48,249 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0785) Prec@1 90.000 (87.260) Prec@5 99.000 (99.396) +2022-11-14 15:47:48,259 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0784) Prec@1 90.000 (87.289) Prec@5 99.000 (99.392) +2022-11-14 15:47:48,271 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0784) Prec@1 87.000 (87.286) Prec@5 100.000 (99.398) +2022-11-14 15:47:48,282 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0786) Prec@1 83.000 (87.242) Prec@5 100.000 (99.404) +2022-11-14 15:47:48,293 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0785) Prec@1 88.000 (87.250) Prec@5 99.000 (99.400) +2022-11-14 15:47:48,350 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:47:48,679 Epoch: [263][0/500] Time 0.034 (0.034) Data 0.233 (0.233) Loss 0.0368 (0.0368) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:47:48,943 Epoch: [263][10/500] Time 0.022 (0.024) Data 0.002 (0.023) Loss 0.0283 (0.0325) Prec@1 96.000 (94.500) Prec@5 99.000 (99.500) +2022-11-14 15:47:49,197 Epoch: [263][20/500] Time 0.025 (0.024) Data 0.002 (0.013) Loss 0.0350 (0.0334) Prec@1 94.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 15:47:49,444 Epoch: [263][30/500] Time 0.023 (0.023) Data 0.002 (0.009) Loss 0.0495 (0.0374) Prec@1 92.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 15:47:49,695 Epoch: [263][40/500] Time 0.024 (0.023) Data 0.002 (0.008) Loss 0.0397 (0.0379) Prec@1 94.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 15:47:50,034 Epoch: [263][50/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.0433 (0.0388) Prec@1 92.000 (93.500) Prec@5 100.000 (99.833) +2022-11-14 15:47:50,380 Epoch: [263][60/500] Time 0.034 (0.025) Data 0.002 (0.006) Loss 0.0269 (0.0371) Prec@1 96.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 15:47:50,721 Epoch: [263][70/500] Time 0.034 (0.026) Data 0.002 (0.005) Loss 0.0171 (0.0346) Prec@1 98.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 15:47:51,069 Epoch: [263][80/500] Time 0.035 (0.027) Data 0.002 (0.005) Loss 0.0351 (0.0346) Prec@1 95.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 15:47:51,411 Epoch: [263][90/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0427 (0.0354) Prec@1 93.000 (94.300) Prec@5 100.000 (99.900) +2022-11-14 15:47:51,758 Epoch: [263][100/500] Time 0.034 (0.027) Data 0.002 (0.004) Loss 0.0322 (0.0351) Prec@1 95.000 (94.364) Prec@5 100.000 (99.909) +2022-11-14 15:47:52,097 Epoch: [263][110/500] Time 0.030 (0.028) Data 0.002 (0.004) Loss 0.0405 (0.0356) Prec@1 94.000 (94.333) Prec@5 100.000 (99.917) +2022-11-14 15:47:52,438 Epoch: [263][120/500] Time 0.028 (0.028) Data 0.002 (0.004) Loss 0.0240 (0.0347) Prec@1 95.000 (94.385) Prec@5 100.000 (99.923) +2022-11-14 15:47:52,780 Epoch: [263][130/500] Time 0.026 (0.028) Data 0.002 (0.004) Loss 0.0549 (0.0361) Prec@1 91.000 (94.143) Prec@5 99.000 (99.857) +2022-11-14 15:47:53,137 Epoch: [263][140/500] Time 0.032 (0.028) Data 0.002 (0.004) Loss 0.0368 (0.0362) Prec@1 95.000 (94.200) Prec@5 100.000 (99.867) +2022-11-14 15:47:53,473 Epoch: [263][150/500] Time 0.032 (0.028) Data 0.002 (0.003) Loss 0.0254 (0.0355) Prec@1 96.000 (94.312) Prec@5 100.000 (99.875) +2022-11-14 15:47:53,818 Epoch: [263][160/500] Time 0.037 (0.029) Data 0.002 (0.003) Loss 0.0281 (0.0351) Prec@1 95.000 (94.353) Prec@5 100.000 (99.882) +2022-11-14 15:47:54,162 Epoch: [263][170/500] Time 0.038 (0.029) Data 0.002 (0.003) Loss 0.0363 (0.0351) Prec@1 94.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 15:47:54,511 Epoch: [263][180/500] Time 0.026 (0.029) Data 0.002 (0.003) Loss 0.0316 (0.0349) Prec@1 93.000 (94.263) Prec@5 100.000 (99.895) +2022-11-14 15:47:54,861 Epoch: [263][190/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0059 (0.0335) Prec@1 100.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 15:47:55,209 Epoch: [263][200/500] Time 0.030 (0.029) Data 0.002 (0.003) Loss 0.0370 (0.0337) Prec@1 95.000 (94.571) Prec@5 100.000 (99.905) +2022-11-14 15:47:55,542 Epoch: [263][210/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0494 (0.0344) Prec@1 92.000 (94.455) Prec@5 100.000 (99.909) +2022-11-14 15:47:55,889 Epoch: [263][220/500] Time 0.032 (0.029) Data 0.003 (0.003) Loss 0.0217 (0.0338) Prec@1 96.000 (94.522) Prec@5 100.000 (99.913) +2022-11-14 15:47:56,230 Epoch: [263][230/500] Time 0.029 (0.029) Data 0.002 (0.003) Loss 0.0346 (0.0339) Prec@1 93.000 (94.458) Prec@5 100.000 (99.917) +2022-11-14 15:47:56,565 Epoch: [263][240/500] Time 0.027 (0.029) Data 0.002 (0.003) Loss 0.0158 (0.0331) Prec@1 98.000 (94.600) Prec@5 100.000 (99.920) +2022-11-14 15:47:56,915 Epoch: [263][250/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0282 (0.0330) Prec@1 95.000 (94.615) Prec@5 100.000 (99.923) +2022-11-14 15:47:57,262 Epoch: [263][260/500] Time 0.028 (0.029) Data 0.002 (0.003) Loss 0.0305 (0.0329) Prec@1 94.000 (94.593) Prec@5 100.000 (99.926) +2022-11-14 15:47:57,606 Epoch: [263][270/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0348 (0.0329) Prec@1 95.000 (94.607) Prec@5 99.000 (99.893) +2022-11-14 15:47:57,947 Epoch: [263][280/500] Time 0.034 (0.029) Data 0.002 (0.003) Loss 0.0445 (0.0333) Prec@1 91.000 (94.483) Prec@5 100.000 (99.897) +2022-11-14 15:47:58,296 Epoch: [263][290/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0203 (0.0329) Prec@1 97.000 (94.567) Prec@5 100.000 (99.900) +2022-11-14 15:47:58,647 Epoch: [263][300/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0518 (0.0335) Prec@1 92.000 (94.484) Prec@5 98.000 (99.839) +2022-11-14 15:47:58,994 Epoch: [263][310/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0401 (0.0337) Prec@1 93.000 (94.438) Prec@5 100.000 (99.844) +2022-11-14 15:47:59,335 Epoch: [263][320/500] Time 0.031 (0.030) Data 0.002 (0.003) Loss 0.0162 (0.0332) Prec@1 97.000 (94.515) Prec@5 100.000 (99.848) +2022-11-14 15:47:59,678 Epoch: [263][330/500] Time 0.030 (0.030) Data 0.002 (0.003) Loss 0.0501 (0.0337) Prec@1 91.000 (94.412) Prec@5 100.000 (99.853) +2022-11-14 15:48:00,033 Epoch: [263][340/500] Time 0.037 (0.030) Data 0.002 (0.003) Loss 0.0246 (0.0334) Prec@1 96.000 (94.457) Prec@5 100.000 (99.857) +2022-11-14 15:48:00,368 Epoch: [263][350/500] Time 0.032 (0.030) Data 0.002 (0.003) Loss 0.0421 (0.0337) Prec@1 94.000 (94.444) Prec@5 99.000 (99.833) +2022-11-14 15:48:00,717 Epoch: [263][360/500] Time 0.038 (0.030) Data 0.002 (0.002) Loss 0.0379 (0.0338) Prec@1 93.000 (94.405) Prec@5 100.000 (99.838) +2022-11-14 15:48:01,051 Epoch: [263][370/500] Time 0.036 (0.030) Data 0.002 (0.002) Loss 0.0462 (0.0341) Prec@1 89.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 15:48:01,405 Epoch: [263][380/500] Time 0.030 (0.030) Data 0.002 (0.002) Loss 0.0263 (0.0339) Prec@1 95.000 (94.282) Prec@5 100.000 (99.846) +2022-11-14 15:48:01,748 Epoch: [263][390/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.0390 (0.0340) Prec@1 91.000 (94.200) Prec@5 100.000 (99.850) +2022-11-14 15:48:02,095 Epoch: [263][400/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0325 (0.0340) Prec@1 95.000 (94.220) Prec@5 100.000 (99.854) +2022-11-14 15:48:02,437 Epoch: [263][410/500] Time 0.037 (0.030) Data 0.002 (0.002) Loss 0.0513 (0.0344) Prec@1 91.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 15:48:02,776 Epoch: [263][420/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.0134 (0.0339) Prec@1 98.000 (94.233) Prec@5 100.000 (99.860) +2022-11-14 15:48:03,115 Epoch: [263][430/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0260 (0.0337) Prec@1 97.000 (94.295) Prec@5 100.000 (99.864) +2022-11-14 15:48:03,469 Epoch: [263][440/500] Time 0.033 (0.030) Data 0.002 (0.002) Loss 0.0435 (0.0340) Prec@1 94.000 (94.289) Prec@5 100.000 (99.867) +2022-11-14 15:48:03,816 Epoch: [263][450/500] Time 0.032 (0.030) Data 0.002 (0.002) Loss 0.0350 (0.0340) Prec@1 93.000 (94.261) Prec@5 100.000 (99.870) +2022-11-14 15:48:04,165 Epoch: [263][460/500] Time 0.037 (0.030) Data 0.002 (0.002) Loss 0.0324 (0.0339) Prec@1 94.000 (94.255) Prec@5 100.000 (99.872) +2022-11-14 15:48:04,516 Epoch: [263][470/500] Time 0.034 (0.030) Data 0.002 (0.002) Loss 0.0321 (0.0339) Prec@1 92.000 (94.208) Prec@5 100.000 (99.875) +2022-11-14 15:48:04,863 Epoch: [263][480/500] Time 0.027 (0.030) Data 0.002 (0.002) Loss 0.0312 (0.0338) Prec@1 95.000 (94.224) Prec@5 100.000 (99.878) +2022-11-14 15:48:05,204 Epoch: [263][490/500] Time 0.037 (0.030) Data 0.002 (0.002) Loss 0.0313 (0.0338) Prec@1 94.000 (94.220) Prec@5 100.000 (99.880) +2022-11-14 15:48:05,515 Epoch: [263][499/500] Time 0.029 (0.030) Data 0.002 (0.002) Loss 0.0409 (0.0339) Prec@1 94.000 (94.216) Prec@5 100.000 (99.882) +2022-11-14 15:48:05,823 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0681 (0.0681) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 15:48:05,832 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0693) Prec@1 87.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 15:48:05,842 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0773) Prec@1 85.000 (86.333) Prec@5 99.000 (99.333) +2022-11-14 15:48:05,856 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0780) Prec@1 86.000 (86.250) Prec@5 100.000 (99.500) +2022-11-14 15:48:05,866 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0802) Prec@1 87.000 (86.400) Prec@5 100.000 (99.600) +2022-11-14 15:48:05,876 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0749) Prec@1 93.000 (87.500) Prec@5 100.000 (99.667) +2022-11-14 15:48:05,886 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0746) Prec@1 89.000 (87.714) Prec@5 100.000 (99.714) +2022-11-14 15:48:05,897 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0762) Prec@1 85.000 (87.375) Prec@5 100.000 (99.750) +2022-11-14 15:48:05,907 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0764) Prec@1 88.000 (87.444) Prec@5 98.000 (99.556) +2022-11-14 15:48:05,920 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0764) Prec@1 88.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 15:48:05,931 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0742) Prec@1 91.000 (87.818) Prec@5 99.000 (99.455) +2022-11-14 15:48:05,941 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0747) Prec@1 89.000 (87.917) Prec@5 100.000 (99.500) +2022-11-14 15:48:05,952 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0739) Prec@1 88.000 (87.923) Prec@5 100.000 (99.538) +2022-11-14 15:48:05,964 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0734) Prec@1 88.000 (87.929) Prec@5 98.000 (99.429) +2022-11-14 15:48:05,976 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0722) Prec@1 89.000 (88.000) Prec@5 100.000 (99.467) +2022-11-14 15:48:05,987 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0726) Prec@1 86.000 (87.875) Prec@5 99.000 (99.438) +2022-11-14 15:48:05,998 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0463 (0.0710) Prec@1 93.000 (88.176) Prec@5 98.000 (99.353) +2022-11-14 15:48:06,009 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1343 (0.0745) Prec@1 78.000 (87.611) Prec@5 100.000 (99.389) +2022-11-14 15:48:06,020 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0752) Prec@1 85.000 (87.474) Prec@5 99.000 (99.368) +2022-11-14 15:48:06,030 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0751) Prec@1 87.000 (87.450) Prec@5 100.000 (99.400) +2022-11-14 15:48:06,041 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0761) Prec@1 85.000 (87.333) Prec@5 99.000 (99.381) +2022-11-14 15:48:06,053 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0758) Prec@1 85.000 (87.227) Prec@5 100.000 (99.409) +2022-11-14 15:48:06,066 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0771) Prec@1 84.000 (87.087) Prec@5 99.000 (99.391) +2022-11-14 15:48:06,079 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0775) Prec@1 86.000 (87.042) Prec@5 100.000 (99.417) +2022-11-14 15:48:06,089 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1170 (0.0791) Prec@1 81.000 (86.800) Prec@5 100.000 (99.440) +2022-11-14 15:48:06,099 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0799) Prec@1 85.000 (86.731) Prec@5 97.000 (99.346) +2022-11-14 15:48:06,110 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0337 (0.0782) Prec@1 94.000 (87.000) Prec@5 100.000 (99.370) +2022-11-14 15:48:06,120 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0773) Prec@1 92.000 (87.179) Prec@5 100.000 (99.393) +2022-11-14 15:48:06,131 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0770) Prec@1 89.000 (87.241) Prec@5 99.000 (99.379) +2022-11-14 15:48:06,141 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0767) Prec@1 85.000 (87.167) Prec@5 100.000 (99.400) +2022-11-14 15:48:06,151 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0759) Prec@1 91.000 (87.290) Prec@5 100.000 (99.419) +2022-11-14 15:48:06,162 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0754) Prec@1 90.000 (87.375) Prec@5 98.000 (99.375) +2022-11-14 15:48:06,172 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0757) Prec@1 82.000 (87.212) Prec@5 100.000 (99.394) +2022-11-14 15:48:06,183 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0760) Prec@1 88.000 (87.235) Prec@5 100.000 (99.412) +2022-11-14 15:48:06,193 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0766) Prec@1 86.000 (87.200) Prec@5 98.000 (99.371) +2022-11-14 15:48:06,203 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0759) Prec@1 91.000 (87.306) Prec@5 100.000 (99.389) +2022-11-14 15:48:06,214 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0762) Prec@1 85.000 (87.243) Prec@5 97.000 (99.324) +2022-11-14 15:48:06,224 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.0772) Prec@1 82.000 (87.105) Prec@5 99.000 (99.316) +2022-11-14 15:48:06,237 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0766) Prec@1 92.000 (87.231) Prec@5 100.000 (99.333) +2022-11-14 15:48:06,248 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0761) Prec@1 90.000 (87.300) Prec@5 99.000 (99.325) +2022-11-14 15:48:06,258 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1040 (0.0768) Prec@1 82.000 (87.171) Prec@5 99.000 (99.317) +2022-11-14 15:48:06,269 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0770) Prec@1 86.000 (87.143) Prec@5 98.000 (99.286) +2022-11-14 15:48:06,280 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0290 (0.0758) Prec@1 96.000 (87.349) Prec@5 99.000 (99.279) +2022-11-14 15:48:06,290 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0759) Prec@1 87.000 (87.341) Prec@5 99.000 (99.273) +2022-11-14 15:48:06,301 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0758) Prec@1 85.000 (87.289) Prec@5 100.000 (99.289) +2022-11-14 15:48:06,312 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0762) Prec@1 82.000 (87.174) Prec@5 98.000 (99.261) +2022-11-14 15:48:06,323 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0761) Prec@1 89.000 (87.213) Prec@5 100.000 (99.277) +2022-11-14 15:48:06,334 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0767) Prec@1 85.000 (87.167) Prec@5 98.000 (99.250) +2022-11-14 15:48:06,345 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0761) Prec@1 91.000 (87.245) Prec@5 98.000 (99.224) +2022-11-14 15:48:06,355 Test: [49/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0767) Prec@1 83.000 (87.160) Prec@5 100.000 (99.240) +2022-11-14 15:48:06,365 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0763) Prec@1 90.000 (87.216) Prec@5 100.000 (99.255) +2022-11-14 15:48:06,376 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0764) Prec@1 85.000 (87.173) Prec@5 100.000 (99.269) +2022-11-14 15:48:06,387 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0763) Prec@1 91.000 (87.245) Prec@5 99.000 (99.264) +2022-11-14 15:48:06,397 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0763) Prec@1 87.000 (87.241) Prec@5 100.000 (99.278) +2022-11-14 15:48:06,408 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0766) Prec@1 87.000 (87.236) Prec@5 100.000 (99.291) +2022-11-14 15:48:06,418 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0765) Prec@1 89.000 (87.268) Prec@5 100.000 (99.304) +2022-11-14 15:48:06,429 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0764) Prec@1 90.000 (87.316) Prec@5 100.000 (99.316) +2022-11-14 15:48:06,440 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0762) Prec@1 92.000 (87.397) Prec@5 99.000 (99.310) +2022-11-14 15:48:06,451 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0764) Prec@1 84.000 (87.339) Prec@5 100.000 (99.322) +2022-11-14 15:48:06,462 Test: [59/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0769) Prec@1 82.000 (87.250) Prec@5 98.000 (99.300) +2022-11-14 15:48:06,474 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0768) Prec@1 88.000 (87.262) Prec@5 99.000 (99.295) +2022-11-14 15:48:06,486 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0768) Prec@1 87.000 (87.258) Prec@5 99.000 (99.290) +2022-11-14 15:48:06,497 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0767) Prec@1 88.000 (87.270) Prec@5 100.000 (99.302) +2022-11-14 15:48:06,509 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0762) Prec@1 92.000 (87.344) Prec@5 100.000 (99.312) +2022-11-14 15:48:06,520 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0763) Prec@1 87.000 (87.338) Prec@5 99.000 (99.308) +2022-11-14 15:48:06,532 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0767) Prec@1 81.000 (87.242) Prec@5 99.000 (99.303) +2022-11-14 15:48:06,543 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0762) Prec@1 91.000 (87.299) Prec@5 100.000 (99.313) +2022-11-14 15:48:06,554 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0764) Prec@1 86.000 (87.279) Prec@5 98.000 (99.294) +2022-11-14 15:48:06,564 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0760) Prec@1 90.000 (87.319) Prec@5 100.000 (99.304) +2022-11-14 15:48:06,576 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0764) Prec@1 85.000 (87.286) Prec@5 97.000 (99.271) +2022-11-14 15:48:06,587 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0766) Prec@1 87.000 (87.282) Prec@5 100.000 (99.282) +2022-11-14 15:48:06,598 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0765) Prec@1 88.000 (87.292) Prec@5 100.000 (99.292) +2022-11-14 15:48:06,608 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0380 (0.0760) Prec@1 95.000 (87.397) Prec@5 100.000 (99.301) +2022-11-14 15:48:06,619 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0265 (0.0753) Prec@1 96.000 (87.514) Prec@5 100.000 (99.311) +2022-11-14 15:48:06,630 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0754) Prec@1 86.000 (87.493) Prec@5 98.000 (99.293) +2022-11-14 15:48:06,640 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0752) Prec@1 92.000 (87.553) Prec@5 99.000 (99.289) +2022-11-14 15:48:06,651 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0753) Prec@1 87.000 (87.545) Prec@5 100.000 (99.299) +2022-11-14 15:48:06,662 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0756) Prec@1 82.000 (87.474) Prec@5 99.000 (99.295) +2022-11-14 15:48:06,673 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0758) Prec@1 87.000 (87.468) Prec@5 100.000 (99.304) +2022-11-14 15:48:06,683 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0758) Prec@1 86.000 (87.450) Prec@5 100.000 (99.312) +2022-11-14 15:48:06,694 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0759) Prec@1 88.000 (87.457) Prec@5 99.000 (99.309) +2022-11-14 15:48:06,706 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0759) Prec@1 86.000 (87.439) Prec@5 100.000 (99.317) +2022-11-14 15:48:06,717 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0762) Prec@1 82.000 (87.373) Prec@5 100.000 (99.325) +2022-11-14 15:48:06,728 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0761) Prec@1 86.000 (87.357) Prec@5 99.000 (99.321) +2022-11-14 15:48:06,738 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0764) Prec@1 83.000 (87.306) Prec@5 100.000 (99.329) +2022-11-14 15:48:06,749 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0766) Prec@1 87.000 (87.302) Prec@5 100.000 (99.337) +2022-11-14 15:48:06,761 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0767) Prec@1 87.000 (87.299) Prec@5 98.000 (99.322) +2022-11-14 15:48:06,772 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0766) Prec@1 92.000 (87.352) Prec@5 98.000 (99.307) +2022-11-14 15:48:06,783 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0765) Prec@1 90.000 (87.382) Prec@5 100.000 (99.315) +2022-11-14 15:48:06,797 Test: [89/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0766) Prec@1 86.000 (87.367) Prec@5 99.000 (99.311) +2022-11-14 15:48:06,809 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0763) Prec@1 93.000 (87.429) Prec@5 100.000 (99.319) +2022-11-14 15:48:06,821 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0760) Prec@1 93.000 (87.489) Prec@5 100.000 (99.326) +2022-11-14 15:48:06,834 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0760) Prec@1 89.000 (87.505) Prec@5 100.000 (99.333) +2022-11-14 15:48:06,845 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0759) Prec@1 90.000 (87.532) Prec@5 99.000 (99.330) +2022-11-14 15:48:06,856 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0760) Prec@1 87.000 (87.526) Prec@5 99.000 (99.326) +2022-11-14 15:48:06,867 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0758) Prec@1 92.000 (87.573) Prec@5 99.000 (99.323) +2022-11-14 15:48:06,878 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0434 (0.0755) Prec@1 93.000 (87.629) Prec@5 99.000 (99.320) +2022-11-14 15:48:06,889 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0756) Prec@1 86.000 (87.612) Prec@5 99.000 (99.316) +2022-11-14 15:48:06,900 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0760) Prec@1 84.000 (87.576) Prec@5 97.000 (99.293) +2022-11-14 15:48:06,912 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0759) Prec@1 89.000 (87.590) Prec@5 98.000 (99.280) +2022-11-14 15:48:06,975 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:48:07,297 Epoch: [264][0/500] Time 0.023 (0.023) Data 0.232 (0.232) Loss 0.0294 (0.0294) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:07,539 Epoch: [264][10/500] Time 0.024 (0.022) Data 0.002 (0.023) Loss 0.0306 (0.0300) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:07,812 Epoch: [264][20/500] Time 0.036 (0.023) Data 0.002 (0.013) Loss 0.0332 (0.0311) Prec@1 93.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 15:48:08,175 Epoch: [264][30/500] Time 0.035 (0.026) Data 0.002 (0.009) Loss 0.0208 (0.0285) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:48:08,536 Epoch: [264][40/500] Time 0.031 (0.028) Data 0.002 (0.007) Loss 0.0244 (0.0277) Prec@1 96.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 15:48:08,900 Epoch: [264][50/500] Time 0.032 (0.029) Data 0.002 (0.006) Loss 0.0385 (0.0295) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:09,263 Epoch: [264][60/500] Time 0.037 (0.029) Data 0.002 (0.006) Loss 0.0163 (0.0276) Prec@1 97.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 15:48:09,656 Epoch: [264][70/500] Time 0.036 (0.030) Data 0.002 (0.005) Loss 0.0415 (0.0294) Prec@1 93.000 (95.000) Prec@5 99.000 (99.875) +2022-11-14 15:48:10,054 Epoch: [264][80/500] Time 0.042 (0.031) Data 0.002 (0.005) Loss 0.0295 (0.0294) Prec@1 95.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 15:48:10,405 Epoch: [264][90/500] Time 0.034 (0.031) Data 0.003 (0.004) Loss 0.0386 (0.0303) Prec@1 94.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 15:48:10,761 Epoch: [264][100/500] Time 0.029 (0.031) Data 0.002 (0.004) Loss 0.0324 (0.0305) Prec@1 95.000 (94.909) Prec@5 99.000 (99.818) +2022-11-14 15:48:11,115 Epoch: [264][110/500] Time 0.035 (0.031) Data 0.002 (0.004) Loss 0.0521 (0.0323) Prec@1 91.000 (94.583) Prec@5 99.000 (99.750) +2022-11-14 15:48:11,480 Epoch: [264][120/500] Time 0.033 (0.031) Data 0.002 (0.004) Loss 0.0423 (0.0331) Prec@1 92.000 (94.385) Prec@5 100.000 (99.769) +2022-11-14 15:48:11,836 Epoch: [264][130/500] Time 0.040 (0.031) Data 0.002 (0.004) Loss 0.0261 (0.0326) Prec@1 97.000 (94.571) Prec@5 100.000 (99.786) +2022-11-14 15:48:12,197 Epoch: [264][140/500] Time 0.034 (0.031) Data 0.002 (0.004) Loss 0.0231 (0.0319) Prec@1 96.000 (94.667) Prec@5 100.000 (99.800) +2022-11-14 15:48:12,552 Epoch: [264][150/500] Time 0.032 (0.031) Data 0.002 (0.003) Loss 0.0262 (0.0316) Prec@1 95.000 (94.688) Prec@5 100.000 (99.812) +2022-11-14 15:48:12,920 Epoch: [264][160/500] Time 0.037 (0.031) Data 0.002 (0.003) Loss 0.0252 (0.0312) Prec@1 95.000 (94.706) Prec@5 100.000 (99.824) +2022-11-14 15:48:13,275 Epoch: [264][170/500] Time 0.033 (0.031) Data 0.002 (0.003) Loss 0.0402 (0.0317) Prec@1 94.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 15:48:13,654 Epoch: [264][180/500] Time 0.038 (0.031) Data 0.002 (0.003) Loss 0.0332 (0.0318) Prec@1 96.000 (94.737) Prec@5 100.000 (99.842) +2022-11-14 15:48:13,995 Epoch: [264][190/500] Time 0.030 (0.031) Data 0.001 (0.003) Loss 0.0304 (0.0317) Prec@1 95.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 15:48:14,368 Epoch: [264][200/500] Time 0.034 (0.031) Data 0.002 (0.003) Loss 0.0366 (0.0319) Prec@1 94.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 15:48:14,730 Epoch: [264][210/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0364 (0.0321) Prec@1 96.000 (94.773) Prec@5 100.000 (99.864) +2022-11-14 15:48:15,087 Epoch: [264][220/500] Time 0.036 (0.031) Data 0.002 (0.003) Loss 0.0316 (0.0321) Prec@1 95.000 (94.783) Prec@5 100.000 (99.870) +2022-11-14 15:48:15,440 Epoch: [264][230/500] Time 0.031 (0.031) Data 0.002 (0.003) Loss 0.0519 (0.0329) Prec@1 91.000 (94.625) Prec@5 99.000 (99.833) +2022-11-14 15:48:15,810 Epoch: [264][240/500] Time 0.033 (0.032) Data 0.002 (0.003) Loss 0.0483 (0.0336) Prec@1 92.000 (94.520) Prec@5 100.000 (99.840) +2022-11-14 15:48:16,167 Epoch: [264][250/500] Time 0.035 (0.032) Data 0.002 (0.003) Loss 0.0410 (0.0338) Prec@1 93.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 15:48:16,545 Epoch: [264][260/500] Time 0.039 (0.032) Data 0.003 (0.003) Loss 0.0549 (0.0346) Prec@1 91.000 (94.333) Prec@5 100.000 (99.852) +2022-11-14 15:48:16,974 Epoch: [264][270/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0260 (0.0343) Prec@1 95.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 15:48:17,388 Epoch: [264][280/500] Time 0.027 (0.032) Data 0.002 (0.003) Loss 0.0306 (0.0342) Prec@1 95.000 (94.379) Prec@5 100.000 (99.862) +2022-11-14 15:48:17,768 Epoch: [264][290/500] Time 0.040 (0.032) Data 0.002 (0.003) Loss 0.0311 (0.0341) Prec@1 95.000 (94.400) Prec@5 100.000 (99.867) +2022-11-14 15:48:18,134 Epoch: [264][300/500] Time 0.030 (0.032) Data 0.002 (0.003) Loss 0.0200 (0.0336) Prec@1 98.000 (94.516) Prec@5 100.000 (99.871) +2022-11-14 15:48:18,484 Epoch: [264][310/500] Time 0.030 (0.032) Data 0.002 (0.003) Loss 0.0502 (0.0342) Prec@1 93.000 (94.469) Prec@5 99.000 (99.844) +2022-11-14 15:48:18,844 Epoch: [264][320/500] Time 0.036 (0.032) Data 0.002 (0.003) Loss 0.0361 (0.0342) Prec@1 94.000 (94.455) Prec@5 100.000 (99.848) +2022-11-14 15:48:19,218 Epoch: [264][330/500] Time 0.032 (0.032) Data 0.002 (0.003) Loss 0.0185 (0.0337) Prec@1 97.000 (94.529) Prec@5 100.000 (99.853) +2022-11-14 15:48:19,769 Epoch: [264][340/500] Time 0.063 (0.033) Data 0.002 (0.003) Loss 0.0432 (0.0340) Prec@1 95.000 (94.543) Prec@5 100.000 (99.857) +2022-11-14 15:48:20,462 Epoch: [264][350/500] Time 0.063 (0.033) Data 0.002 (0.003) Loss 0.0461 (0.0344) Prec@1 90.000 (94.417) Prec@5 100.000 (99.861) +2022-11-14 15:48:21,111 Epoch: [264][360/500] Time 0.054 (0.034) Data 0.002 (0.003) Loss 0.0345 (0.0344) Prec@1 94.000 (94.405) Prec@5 100.000 (99.865) +2022-11-14 15:48:21,784 Epoch: [264][370/500] Time 0.069 (0.035) Data 0.002 (0.003) Loss 0.0333 (0.0343) Prec@1 94.000 (94.395) Prec@5 100.000 (99.868) +2022-11-14 15:48:22,473 Epoch: [264][380/500] Time 0.052 (0.035) Data 0.002 (0.003) Loss 0.0199 (0.0340) Prec@1 96.000 (94.436) Prec@5 100.000 (99.872) +2022-11-14 15:48:23,120 Epoch: [264][390/500] Time 0.048 (0.036) Data 0.002 (0.003) Loss 0.0230 (0.0337) Prec@1 96.000 (94.475) Prec@5 100.000 (99.875) +2022-11-14 15:48:23,777 Epoch: [264][400/500] Time 0.053 (0.037) Data 0.002 (0.003) Loss 0.0235 (0.0334) Prec@1 95.000 (94.488) Prec@5 100.000 (99.878) +2022-11-14 15:48:24,418 Epoch: [264][410/500] Time 0.059 (0.037) Data 0.002 (0.003) Loss 0.0323 (0.0334) Prec@1 95.000 (94.500) Prec@5 98.000 (99.833) +2022-11-14 15:48:25,038 Epoch: [264][420/500] Time 0.063 (0.038) Data 0.002 (0.003) Loss 0.0327 (0.0334) Prec@1 94.000 (94.488) Prec@5 99.000 (99.814) +2022-11-14 15:48:25,426 Epoch: [264][430/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0199 (0.0331) Prec@1 97.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 15:48:25,776 Epoch: [264][440/500] Time 0.032 (0.037) Data 0.002 (0.003) Loss 0.0284 (0.0330) Prec@1 96.000 (94.578) Prec@5 100.000 (99.822) +2022-11-14 15:48:26,113 Epoch: [264][450/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0346 (0.0330) Prec@1 92.000 (94.522) Prec@5 100.000 (99.826) +2022-11-14 15:48:26,467 Epoch: [264][460/500] Time 0.034 (0.037) Data 0.002 (0.002) Loss 0.0475 (0.0333) Prec@1 92.000 (94.468) Prec@5 100.000 (99.830) +2022-11-14 15:48:26,819 Epoch: [264][470/500] Time 0.033 (0.037) Data 0.001 (0.002) Loss 0.0417 (0.0335) Prec@1 91.000 (94.396) Prec@5 99.000 (99.812) +2022-11-14 15:48:27,174 Epoch: [264][480/500] Time 0.032 (0.037) Data 0.002 (0.002) Loss 0.0371 (0.0336) Prec@1 92.000 (94.347) Prec@5 100.000 (99.816) +2022-11-14 15:48:27,509 Epoch: [264][490/500] Time 0.030 (0.037) Data 0.002 (0.002) Loss 0.0252 (0.0334) Prec@1 96.000 (94.380) Prec@5 100.000 (99.820) +2022-11-14 15:48:27,834 Epoch: [264][499/500] Time 0.033 (0.037) Data 0.002 (0.002) Loss 0.0442 (0.0336) Prec@1 92.000 (94.333) Prec@5 100.000 (99.824) +2022-11-14 15:48:28,138 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0618 (0.0618) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 15:48:28,147 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0514 (0.0566) Prec@1 92.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 15:48:28,157 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0584) Prec@1 90.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 15:48:28,171 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0595) Prec@1 90.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 15:48:28,181 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0650) Prec@1 85.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 15:48:28,192 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0621) Prec@1 91.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 15:48:28,205 Test: [6/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0594 (0.0618) Prec@1 91.000 (89.571) Prec@5 100.000 (99.571) +2022-11-14 15:48:28,219 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0634) Prec@1 85.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 15:48:28,229 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0639) Prec@1 90.000 (89.111) Prec@5 96.000 (99.111) +2022-11-14 15:48:28,240 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0657) Prec@1 88.000 (89.000) Prec@5 97.000 (98.900) +2022-11-14 15:48:28,256 Test: [10/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0538 (0.0646) Prec@1 92.000 (89.273) Prec@5 100.000 (99.000) +2022-11-14 15:48:28,268 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0665) Prec@1 87.000 (89.083) Prec@5 99.000 (99.000) +2022-11-14 15:48:28,280 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0495 (0.0652) Prec@1 92.000 (89.308) Prec@5 100.000 (99.077) +2022-11-14 15:48:28,292 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0658) Prec@1 89.000 (89.286) Prec@5 99.000 (99.071) +2022-11-14 15:48:28,306 Test: [14/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0945 (0.0677) Prec@1 83.000 (88.867) Prec@5 99.000 (99.067) +2022-11-14 15:48:28,320 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0688) Prec@1 85.000 (88.625) Prec@5 97.000 (98.938) +2022-11-14 15:48:28,331 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0566 (0.0680) Prec@1 90.000 (88.706) Prec@5 98.000 (98.882) +2022-11-14 15:48:28,343 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1014 (0.0699) Prec@1 86.000 (88.556) Prec@5 97.000 (98.778) +2022-11-14 15:48:28,357 Test: [18/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0703) Prec@1 86.000 (88.421) Prec@5 100.000 (98.842) +2022-11-14 15:48:28,370 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0715) Prec@1 84.000 (88.200) Prec@5 98.000 (98.800) +2022-11-14 15:48:28,382 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0722) Prec@1 88.000 (88.190) Prec@5 99.000 (98.810) +2022-11-14 15:48:28,393 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0597 (0.0716) Prec@1 88.000 (88.182) Prec@5 100.000 (98.864) +2022-11-14 15:48:28,406 Test: [22/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0972 (0.0727) Prec@1 86.000 (88.087) Prec@5 98.000 (98.826) +2022-11-14 15:48:28,418 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0731) Prec@1 85.000 (87.958) Prec@5 100.000 (98.875) +2022-11-14 15:48:28,430 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0737) Prec@1 86.000 (87.880) Prec@5 100.000 (98.920) +2022-11-14 15:48:28,441 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.0748) Prec@1 83.000 (87.692) Prec@5 97.000 (98.846) +2022-11-14 15:48:28,455 Test: [26/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0741) Prec@1 89.000 (87.741) Prec@5 99.000 (98.852) +2022-11-14 15:48:28,467 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0735) Prec@1 91.000 (87.857) Prec@5 100.000 (98.893) +2022-11-14 15:48:28,480 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0735) Prec@1 87.000 (87.828) Prec@5 98.000 (98.862) +2022-11-14 15:48:28,491 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0734) Prec@1 87.000 (87.800) Prec@5 100.000 (98.900) +2022-11-14 15:48:28,503 Test: [30/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0735) Prec@1 89.000 (87.839) Prec@5 99.000 (98.903) +2022-11-14 15:48:28,516 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0737) Prec@1 89.000 (87.875) Prec@5 99.000 (98.906) +2022-11-14 15:48:28,526 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0740) Prec@1 85.000 (87.788) Prec@5 99.000 (98.909) +2022-11-14 15:48:28,535 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1127 (0.0751) Prec@1 80.000 (87.559) Prec@5 100.000 (98.941) +2022-11-14 15:48:28,548 Test: [34/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1029 (0.0759) Prec@1 83.000 (87.429) Prec@5 97.000 (98.886) +2022-11-14 15:48:28,560 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 89.000 (87.472) Prec@5 99.000 (98.889) +2022-11-14 15:48:28,570 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0760) Prec@1 87.000 (87.459) Prec@5 99.000 (98.892) +2022-11-14 15:48:28,582 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0936 (0.0765) Prec@1 85.000 (87.395) Prec@5 99.000 (98.895) +2022-11-14 15:48:28,593 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0424 (0.0756) Prec@1 95.000 (87.590) Prec@5 99.000 (98.897) +2022-11-14 15:48:28,603 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0640 (0.0753) Prec@1 91.000 (87.675) Prec@5 99.000 (98.900) +2022-11-14 15:48:28,615 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0759) Prec@1 85.000 (87.610) Prec@5 98.000 (98.878) +2022-11-14 15:48:28,626 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0757) Prec@1 87.000 (87.595) Prec@5 99.000 (98.881) +2022-11-14 15:48:28,640 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0317 (0.0747) Prec@1 95.000 (87.767) Prec@5 100.000 (98.907) +2022-11-14 15:48:28,650 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0747) Prec@1 88.000 (87.773) Prec@5 98.000 (98.886) +2022-11-14 15:48:28,661 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0741) Prec@1 92.000 (87.867) Prec@5 98.000 (98.867) +2022-11-14 15:48:28,672 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0742) Prec@1 86.000 (87.826) Prec@5 99.000 (98.870) +2022-11-14 15:48:28,685 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0741) Prec@1 89.000 (87.851) Prec@5 100.000 (98.894) +2022-11-14 15:48:28,697 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0742) Prec@1 87.000 (87.833) Prec@5 100.000 (98.917) +2022-11-14 15:48:28,708 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0738) Prec@1 91.000 (87.898) Prec@5 100.000 (98.939) +2022-11-14 15:48:28,719 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0742) Prec@1 84.000 (87.820) Prec@5 100.000 (98.960) +2022-11-14 15:48:28,733 Test: [50/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0739) Prec@1 88.000 (87.824) Prec@5 99.000 (98.961) +2022-11-14 15:48:28,745 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0743) Prec@1 82.000 (87.712) Prec@5 100.000 (98.981) +2022-11-14 15:48:28,756 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0746) Prec@1 85.000 (87.660) Prec@5 100.000 (99.000) +2022-11-14 15:48:28,767 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0746) Prec@1 85.000 (87.611) Prec@5 98.000 (98.981) +2022-11-14 15:48:28,780 Test: [54/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0750) Prec@1 86.000 (87.582) Prec@5 98.000 (98.964) +2022-11-14 15:48:28,793 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0750) Prec@1 88.000 (87.589) Prec@5 99.000 (98.964) +2022-11-14 15:48:28,803 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0748) Prec@1 91.000 (87.649) Prec@5 98.000 (98.947) +2022-11-14 15:48:28,813 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0747) Prec@1 89.000 (87.672) Prec@5 100.000 (98.966) +2022-11-14 15:48:28,826 Test: [58/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0751) Prec@1 84.000 (87.610) Prec@5 100.000 (98.983) +2022-11-14 15:48:28,838 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0751) Prec@1 87.000 (87.600) Prec@5 100.000 (99.000) +2022-11-14 15:48:28,848 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0751) Prec@1 88.000 (87.607) Prec@5 100.000 (99.016) +2022-11-14 15:48:28,859 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0750) Prec@1 91.000 (87.661) Prec@5 99.000 (99.016) +2022-11-14 15:48:28,872 Test: [62/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0748) Prec@1 91.000 (87.714) Prec@5 99.000 (99.016) +2022-11-14 15:48:28,884 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0746) Prec@1 90.000 (87.750) Prec@5 100.000 (99.031) +2022-11-14 15:48:28,895 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0746) Prec@1 89.000 (87.769) Prec@5 99.000 (99.031) +2022-11-14 15:48:28,906 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0749) Prec@1 85.000 (87.727) Prec@5 100.000 (99.045) +2022-11-14 15:48:28,919 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0746) Prec@1 90.000 (87.761) Prec@5 100.000 (99.060) +2022-11-14 15:48:28,930 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0747) Prec@1 87.000 (87.750) Prec@5 96.000 (99.015) +2022-11-14 15:48:28,942 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0746) Prec@1 87.000 (87.739) Prec@5 100.000 (99.029) +2022-11-14 15:48:28,954 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0750) Prec@1 85.000 (87.700) Prec@5 98.000 (99.014) +2022-11-14 15:48:28,966 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0753) Prec@1 86.000 (87.676) Prec@5 99.000 (99.014) +2022-11-14 15:48:28,977 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0751) Prec@1 90.000 (87.708) Prec@5 100.000 (99.028) +2022-11-14 15:48:28,988 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0748) Prec@1 91.000 (87.753) Prec@5 99.000 (99.027) +2022-11-14 15:48:29,000 Test: [73/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0402 (0.0743) Prec@1 93.000 (87.824) Prec@5 100.000 (99.041) +2022-11-14 15:48:29,011 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1100 (0.0748) Prec@1 83.000 (87.760) Prec@5 100.000 (99.053) +2022-11-14 15:48:29,023 Test: [75/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0749) Prec@1 86.000 (87.737) Prec@5 99.000 (99.053) +2022-11-14 15:48:29,035 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0749) Prec@1 87.000 (87.727) Prec@5 98.000 (99.039) +2022-11-14 15:48:29,046 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 87.000 (87.718) Prec@5 100.000 (99.051) +2022-11-14 15:48:29,055 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0751) Prec@1 86.000 (87.696) Prec@5 100.000 (99.063) +2022-11-14 15:48:29,066 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0749) Prec@1 89.000 (87.713) Prec@5 99.000 (99.062) +2022-11-14 15:48:29,078 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0750) Prec@1 88.000 (87.716) Prec@5 99.000 (99.062) +2022-11-14 15:48:29,091 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1190 (0.0756) Prec@1 81.000 (87.634) Prec@5 98.000 (99.049) +2022-11-14 15:48:29,102 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0757) Prec@1 86.000 (87.614) Prec@5 100.000 (99.060) +2022-11-14 15:48:29,113 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0754) Prec@1 92.000 (87.667) Prec@5 100.000 (99.071) +2022-11-14 15:48:29,124 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0754) Prec@1 88.000 (87.671) Prec@5 99.000 (99.071) +2022-11-14 15:48:29,134 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1081 (0.0758) Prec@1 84.000 (87.628) Prec@5 100.000 (99.081) +2022-11-14 15:48:29,146 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0758) Prec@1 87.000 (87.621) Prec@5 100.000 (99.092) +2022-11-14 15:48:29,157 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0756) Prec@1 90.000 (87.648) Prec@5 98.000 (99.080) +2022-11-14 15:48:29,168 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0754) Prec@1 90.000 (87.674) Prec@5 100.000 (99.090) +2022-11-14 15:48:29,179 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0753) Prec@1 89.000 (87.689) Prec@5 100.000 (99.100) +2022-11-14 15:48:29,190 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0752) Prec@1 90.000 (87.714) Prec@5 100.000 (99.110) +2022-11-14 15:48:29,202 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0751) Prec@1 90.000 (87.739) Prec@5 99.000 (99.109) +2022-11-14 15:48:29,214 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1088 (0.0754) Prec@1 83.000 (87.688) Prec@5 99.000 (99.108) +2022-11-14 15:48:29,226 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0756) Prec@1 84.000 (87.649) Prec@5 100.000 (99.117) +2022-11-14 15:48:29,236 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0757) Prec@1 86.000 (87.632) Prec@5 99.000 (99.116) +2022-11-14 15:48:29,247 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0755) Prec@1 91.000 (87.667) Prec@5 99.000 (99.115) +2022-11-14 15:48:29,257 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0752) Prec@1 91.000 (87.701) Prec@5 99.000 (99.113) +2022-11-14 15:48:29,267 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0756) Prec@1 84.000 (87.663) Prec@5 99.000 (99.112) +2022-11-14 15:48:29,276 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0759) Prec@1 80.000 (87.586) Prec@5 99.000 (99.111) +2022-11-14 15:48:29,287 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0759) Prec@1 85.000 (87.560) Prec@5 100.000 (99.120) +2022-11-14 15:48:29,346 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:48:29,689 Epoch: [265][0/500] Time 0.027 (0.027) Data 0.253 (0.253) Loss 0.0468 (0.0468) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:29,965 Epoch: [265][10/500] Time 0.024 (0.025) Data 0.002 (0.025) Loss 0.0263 (0.0365) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:48:30,210 Epoch: [265][20/500] Time 0.022 (0.024) Data 0.002 (0.014) Loss 0.0144 (0.0292) Prec@1 98.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 15:48:30,463 Epoch: [265][30/500] Time 0.026 (0.023) Data 0.002 (0.010) Loss 0.0244 (0.0280) Prec@1 96.000 (95.750) Prec@5 99.000 (99.750) +2022-11-14 15:48:30,733 Epoch: [265][40/500] Time 0.029 (0.023) Data 0.002 (0.008) Loss 0.0277 (0.0279) Prec@1 95.000 (95.600) Prec@5 99.000 (99.600) +2022-11-14 15:48:31,047 Epoch: [265][50/500] Time 0.026 (0.024) Data 0.002 (0.007) Loss 0.0484 (0.0313) Prec@1 95.000 (95.500) Prec@5 100.000 (99.667) +2022-11-14 15:48:31,362 Epoch: [265][60/500] Time 0.028 (0.025) Data 0.002 (0.006) Loss 0.0638 (0.0360) Prec@1 91.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 15:48:31,686 Epoch: [265][70/500] Time 0.037 (0.025) Data 0.002 (0.005) Loss 0.0320 (0.0355) Prec@1 93.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 15:48:31,996 Epoch: [265][80/500] Time 0.030 (0.026) Data 0.002 (0.005) Loss 0.0246 (0.0343) Prec@1 95.000 (94.667) Prec@5 99.000 (99.667) +2022-11-14 15:48:32,313 Epoch: [265][90/500] Time 0.030 (0.026) Data 0.002 (0.005) Loss 0.0361 (0.0344) Prec@1 92.000 (94.400) Prec@5 100.000 (99.700) +2022-11-14 15:48:32,631 Epoch: [265][100/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0291 (0.0340) Prec@1 97.000 (94.636) Prec@5 100.000 (99.727) +2022-11-14 15:48:32,950 Epoch: [265][110/500] Time 0.034 (0.026) Data 0.002 (0.004) Loss 0.0345 (0.0340) Prec@1 94.000 (94.583) Prec@5 100.000 (99.750) +2022-11-14 15:48:33,270 Epoch: [265][120/500] Time 0.031 (0.027) Data 0.002 (0.004) Loss 0.0493 (0.0352) Prec@1 92.000 (94.385) Prec@5 100.000 (99.769) +2022-11-14 15:48:33,708 Epoch: [265][130/500] Time 0.066 (0.027) Data 0.002 (0.004) Loss 0.0508 (0.0363) Prec@1 92.000 (94.214) Prec@5 100.000 (99.786) +2022-11-14 15:48:34,440 Epoch: [265][140/500] Time 0.074 (0.030) Data 0.002 (0.004) Loss 0.0395 (0.0365) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 15:48:35,171 Epoch: [265][150/500] Time 0.064 (0.032) Data 0.002 (0.004) Loss 0.0401 (0.0367) Prec@1 94.000 (94.188) Prec@5 100.000 (99.812) +2022-11-14 15:48:35,921 Epoch: [265][160/500] Time 0.075 (0.035) Data 0.002 (0.004) Loss 0.0489 (0.0374) Prec@1 91.000 (94.000) Prec@5 100.000 (99.824) +2022-11-14 15:48:36,664 Epoch: [265][170/500] Time 0.073 (0.036) Data 0.002 (0.003) Loss 0.0335 (0.0372) Prec@1 93.000 (93.944) Prec@5 99.000 (99.778) +2022-11-14 15:48:37,116 Epoch: [265][180/500] Time 0.039 (0.037) Data 0.002 (0.003) Loss 0.0367 (0.0372) Prec@1 93.000 (93.895) Prec@5 100.000 (99.789) +2022-11-14 15:48:37,489 Epoch: [265][190/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0240 (0.0365) Prec@1 96.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 15:48:37,852 Epoch: [265][200/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0347 (0.0365) Prec@1 94.000 (94.000) Prec@5 98.000 (99.714) +2022-11-14 15:48:38,215 Epoch: [265][210/500] Time 0.037 (0.036) Data 0.002 (0.003) Loss 0.0343 (0.0364) Prec@1 95.000 (94.045) Prec@5 100.000 (99.727) +2022-11-14 15:48:38,578 Epoch: [265][220/500] Time 0.030 (0.036) Data 0.002 (0.003) Loss 0.0346 (0.0363) Prec@1 94.000 (94.043) Prec@5 100.000 (99.739) +2022-11-14 15:48:38,951 Epoch: [265][230/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.0115 (0.0352) Prec@1 99.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 15:48:39,316 Epoch: [265][240/500] Time 0.028 (0.036) Data 0.002 (0.003) Loss 0.0216 (0.0347) Prec@1 97.000 (94.360) Prec@5 100.000 (99.760) +2022-11-14 15:48:39,695 Epoch: [265][250/500] Time 0.041 (0.036) Data 0.002 (0.003) Loss 0.0415 (0.0350) Prec@1 95.000 (94.385) Prec@5 99.000 (99.731) +2022-11-14 15:48:40,056 Epoch: [265][260/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0598 (0.0359) Prec@1 90.000 (94.222) Prec@5 100.000 (99.741) +2022-11-14 15:48:40,423 Epoch: [265][270/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0357 (0.0359) Prec@1 93.000 (94.179) Prec@5 99.000 (99.714) +2022-11-14 15:48:40,809 Epoch: [265][280/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.0260 (0.0355) Prec@1 98.000 (94.310) Prec@5 100.000 (99.724) +2022-11-14 15:48:41,172 Epoch: [265][290/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.0487 (0.0360) Prec@1 93.000 (94.267) Prec@5 100.000 (99.733) +2022-11-14 15:48:41,563 Epoch: [265][300/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0335 (0.0359) Prec@1 94.000 (94.258) Prec@5 100.000 (99.742) +2022-11-14 15:48:41,938 Epoch: [265][310/500] Time 0.036 (0.035) Data 0.002 (0.003) Loss 0.0149 (0.0352) Prec@1 98.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 15:48:42,313 Epoch: [265][320/500] Time 0.033 (0.035) Data 0.002 (0.003) Loss 0.0312 (0.0351) Prec@1 96.000 (94.424) Prec@5 100.000 (99.758) +2022-11-14 15:48:42,677 Epoch: [265][330/500] Time 0.029 (0.035) Data 0.002 (0.003) Loss 0.0308 (0.0350) Prec@1 94.000 (94.412) Prec@5 100.000 (99.765) +2022-11-14 15:48:43,057 Epoch: [265][340/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.0361 (0.0350) Prec@1 95.000 (94.429) Prec@5 100.000 (99.771) +2022-11-14 15:48:43,426 Epoch: [265][350/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.0303 (0.0349) Prec@1 95.000 (94.444) Prec@5 99.000 (99.750) +2022-11-14 15:48:43,789 Epoch: [265][360/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.0336 (0.0349) Prec@1 95.000 (94.459) Prec@5 100.000 (99.757) +2022-11-14 15:48:44,165 Epoch: [265][370/500] Time 0.035 (0.035) Data 0.003 (0.003) Loss 0.0344 (0.0348) Prec@1 94.000 (94.447) Prec@5 100.000 (99.763) +2022-11-14 15:48:44,540 Epoch: [265][380/500] Time 0.032 (0.035) Data 0.002 (0.003) Loss 0.0400 (0.0350) Prec@1 93.000 (94.410) Prec@5 100.000 (99.769) +2022-11-14 15:48:44,913 Epoch: [265][390/500] Time 0.031 (0.035) Data 0.002 (0.003) Loss 0.0283 (0.0348) Prec@1 96.000 (94.450) Prec@5 100.000 (99.775) +2022-11-14 15:48:45,284 Epoch: [265][400/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.0405 (0.0349) Prec@1 92.000 (94.390) Prec@5 100.000 (99.780) +2022-11-14 15:48:45,657 Epoch: [265][410/500] Time 0.031 (0.035) Data 0.003 (0.003) Loss 0.0278 (0.0348) Prec@1 95.000 (94.405) Prec@5 100.000 (99.786) +2022-11-14 15:48:46,031 Epoch: [265][420/500] Time 0.039 (0.035) Data 0.002 (0.003) Loss 0.0588 (0.0353) Prec@1 90.000 (94.302) Prec@5 100.000 (99.791) +2022-11-14 15:48:46,402 Epoch: [265][430/500] Time 0.040 (0.035) Data 0.002 (0.003) Loss 0.0543 (0.0358) Prec@1 91.000 (94.227) Prec@5 100.000 (99.795) +2022-11-14 15:48:46,777 Epoch: [265][440/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0382 (0.0358) Prec@1 95.000 (94.244) Prec@5 100.000 (99.800) +2022-11-14 15:48:47,144 Epoch: [265][450/500] Time 0.030 (0.035) Data 0.002 (0.003) Loss 0.0227 (0.0355) Prec@1 96.000 (94.283) Prec@5 100.000 (99.804) +2022-11-14 15:48:47,527 Epoch: [265][460/500] Time 0.037 (0.035) Data 0.002 (0.003) Loss 0.0432 (0.0357) Prec@1 92.000 (94.234) Prec@5 100.000 (99.809) +2022-11-14 15:48:47,896 Epoch: [265][470/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0373 (0.0357) Prec@1 92.000 (94.188) Prec@5 100.000 (99.812) +2022-11-14 15:48:48,261 Epoch: [265][480/500] Time 0.036 (0.034) Data 0.002 (0.003) Loss 0.0425 (0.0359) Prec@1 93.000 (94.163) Prec@5 100.000 (99.816) +2022-11-14 15:48:48,637 Epoch: [265][490/500] Time 0.030 (0.034) Data 0.002 (0.003) Loss 0.0486 (0.0361) Prec@1 92.000 (94.120) Prec@5 100.000 (99.820) +2022-11-14 15:48:48,983 Epoch: [265][499/500] Time 0.035 (0.034) Data 0.002 (0.003) Loss 0.0317 (0.0360) Prec@1 95.000 (94.137) Prec@5 100.000 (99.824) +2022-11-14 15:48:49,296 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0634) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:49,308 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0674) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:49,317 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0651) Prec@1 90.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 15:48:49,332 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0690) Prec@1 87.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 15:48:49,341 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0750) Prec@1 85.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 15:48:49,351 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0723) Prec@1 90.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 15:48:49,362 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0719) Prec@1 91.000 (88.714) Prec@5 99.000 (99.571) +2022-11-14 15:48:49,373 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0730) Prec@1 85.000 (88.250) Prec@5 100.000 (99.625) +2022-11-14 15:48:49,382 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0736) Prec@1 88.000 (88.222) Prec@5 99.000 (99.556) +2022-11-14 15:48:49,391 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0732) Prec@1 90.000 (88.400) Prec@5 98.000 (99.400) +2022-11-14 15:48:49,401 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0725) Prec@1 89.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 15:48:49,412 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0725) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 15:48:49,421 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0718) Prec@1 90.000 (88.615) Prec@5 100.000 (99.538) +2022-11-14 15:48:49,432 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0725) Prec@1 87.000 (88.500) Prec@5 100.000 (99.571) +2022-11-14 15:48:49,443 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0947 (0.0740) Prec@1 83.000 (88.133) Prec@5 99.000 (99.533) +2022-11-14 15:48:49,453 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0738) Prec@1 87.000 (88.062) Prec@5 100.000 (99.562) +2022-11-14 15:48:49,464 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0722) Prec@1 92.000 (88.294) Prec@5 99.000 (99.529) +2022-11-14 15:48:49,475 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0738) Prec@1 84.000 (88.056) Prec@5 100.000 (99.556) +2022-11-14 15:48:49,487 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 86.000 (87.947) Prec@5 98.000 (99.474) +2022-11-14 15:48:49,498 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0763) Prec@1 82.000 (87.650) Prec@5 97.000 (99.350) +2022-11-14 15:48:49,509 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0760) Prec@1 87.000 (87.619) Prec@5 99.000 (99.333) +2022-11-14 15:48:49,519 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0773) Prec@1 84.000 (87.455) Prec@5 99.000 (99.318) +2022-11-14 15:48:49,530 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0779) Prec@1 85.000 (87.348) Prec@5 98.000 (99.261) +2022-11-14 15:48:49,541 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0786) Prec@1 85.000 (87.250) Prec@5 100.000 (99.292) +2022-11-14 15:48:49,552 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0793) Prec@1 82.000 (87.040) Prec@5 100.000 (99.320) +2022-11-14 15:48:49,564 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0794) Prec@1 88.000 (87.077) Prec@5 99.000 (99.308) +2022-11-14 15:48:49,575 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0786) Prec@1 92.000 (87.259) Prec@5 100.000 (99.333) +2022-11-14 15:48:49,585 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0410 (0.0772) Prec@1 92.000 (87.429) Prec@5 99.000 (99.321) +2022-11-14 15:48:49,596 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0775) Prec@1 86.000 (87.379) Prec@5 99.000 (99.310) +2022-11-14 15:48:49,607 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0773) Prec@1 86.000 (87.333) Prec@5 99.000 (99.300) +2022-11-14 15:48:49,618 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0774) Prec@1 88.000 (87.355) Prec@5 100.000 (99.323) +2022-11-14 15:48:49,629 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0771) Prec@1 90.000 (87.438) Prec@5 99.000 (99.312) +2022-11-14 15:48:49,641 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0770) Prec@1 87.000 (87.424) Prec@5 99.000 (99.303) +2022-11-14 15:48:49,652 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0772) Prec@1 88.000 (87.441) Prec@5 100.000 (99.324) +2022-11-14 15:48:49,663 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0770) Prec@1 90.000 (87.514) Prec@5 99.000 (99.314) +2022-11-14 15:48:49,674 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0767) Prec@1 88.000 (87.528) Prec@5 99.000 (99.306) +2022-11-14 15:48:49,685 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0766) Prec@1 86.000 (87.486) Prec@5 99.000 (99.297) +2022-11-14 15:48:49,696 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0768) Prec@1 85.000 (87.421) Prec@5 98.000 (99.263) +2022-11-14 15:48:49,707 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0763) Prec@1 93.000 (87.564) Prec@5 99.000 (99.256) +2022-11-14 15:48:49,717 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0760) Prec@1 91.000 (87.650) Prec@5 99.000 (99.250) +2022-11-14 15:48:49,728 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0767) Prec@1 83.000 (87.537) Prec@5 98.000 (99.220) +2022-11-14 15:48:49,737 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0767) Prec@1 89.000 (87.571) Prec@5 98.000 (99.190) +2022-11-14 15:48:49,747 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0760) Prec@1 93.000 (87.698) Prec@5 100.000 (99.209) +2022-11-14 15:48:49,759 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0757) Prec@1 90.000 (87.750) Prec@5 98.000 (99.182) +2022-11-14 15:48:49,769 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0756) Prec@1 89.000 (87.778) Prec@5 100.000 (99.200) +2022-11-14 15:48:49,778 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0761) Prec@1 83.000 (87.674) Prec@5 99.000 (99.196) +2022-11-14 15:48:49,788 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0758) Prec@1 89.000 (87.702) Prec@5 99.000 (99.191) +2022-11-14 15:48:49,798 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1286 (0.0769) Prec@1 78.000 (87.500) Prec@5 98.000 (99.167) +2022-11-14 15:48:49,809 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0335 (0.0761) Prec@1 95.000 (87.653) Prec@5 100.000 (99.184) +2022-11-14 15:48:49,822 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0763) Prec@1 87.000 (87.640) Prec@5 100.000 (99.200) +2022-11-14 15:48:49,834 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0763) Prec@1 88.000 (87.647) Prec@5 100.000 (99.216) +2022-11-14 15:48:49,845 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0760) Prec@1 86.000 (87.615) Prec@5 100.000 (99.231) +2022-11-14 15:48:49,855 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0758) Prec@1 89.000 (87.642) Prec@5 100.000 (99.245) +2022-11-14 15:48:49,866 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0758) Prec@1 86.000 (87.611) Prec@5 100.000 (99.259) +2022-11-14 15:48:49,880 Test: [54/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0759) Prec@1 88.000 (87.618) Prec@5 100.000 (99.273) +2022-11-14 15:48:49,893 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0759) Prec@1 91.000 (87.679) Prec@5 99.000 (99.268) +2022-11-14 15:48:49,903 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0756) Prec@1 91.000 (87.737) Prec@5 100.000 (99.281) +2022-11-14 15:48:49,913 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0752) Prec@1 93.000 (87.828) Prec@5 99.000 (99.276) +2022-11-14 15:48:49,927 Test: [58/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0755) Prec@1 85.000 (87.780) Prec@5 100.000 (99.288) +2022-11-14 15:48:49,941 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0755) Prec@1 85.000 (87.733) Prec@5 100.000 (99.300) +2022-11-14 15:48:49,951 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0755) Prec@1 90.000 (87.770) Prec@5 99.000 (99.295) +2022-11-14 15:48:49,962 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0754) Prec@1 89.000 (87.790) Prec@5 98.000 (99.274) +2022-11-14 15:48:49,975 Test: [62/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0750) Prec@1 91.000 (87.841) Prec@5 99.000 (99.270) +2022-11-14 15:48:49,988 Test: [63/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0747) Prec@1 90.000 (87.875) Prec@5 100.000 (99.281) +2022-11-14 15:48:50,001 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0746) Prec@1 88.000 (87.877) Prec@5 100.000 (99.292) +2022-11-14 15:48:50,012 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0750) Prec@1 82.000 (87.788) Prec@5 99.000 (99.288) +2022-11-14 15:48:50,026 Test: [66/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0746) Prec@1 91.000 (87.836) Prec@5 100.000 (99.299) +2022-11-14 15:48:50,039 Test: [67/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0745) Prec@1 89.000 (87.853) Prec@5 98.000 (99.279) +2022-11-14 15:48:50,050 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0746) Prec@1 87.000 (87.841) Prec@5 99.000 (99.275) +2022-11-14 15:48:50,061 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0748) Prec@1 87.000 (87.829) Prec@5 100.000 (99.286) +2022-11-14 15:48:50,074 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0752) Prec@1 83.000 (87.761) Prec@5 99.000 (99.282) +2022-11-14 15:48:50,085 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0748) Prec@1 93.000 (87.833) Prec@5 100.000 (99.292) +2022-11-14 15:48:50,096 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0746) Prec@1 90.000 (87.863) Prec@5 100.000 (99.301) +2022-11-14 15:48:50,107 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0743) Prec@1 92.000 (87.919) Prec@5 100.000 (99.311) +2022-11-14 15:48:50,118 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0748) Prec@1 80.000 (87.813) Prec@5 100.000 (99.320) +2022-11-14 15:48:50,131 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0745) Prec@1 93.000 (87.882) Prec@5 99.000 (99.316) +2022-11-14 15:48:50,142 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0744) Prec@1 90.000 (87.909) Prec@5 100.000 (99.325) +2022-11-14 15:48:50,153 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1158 (0.0750) Prec@1 82.000 (87.833) Prec@5 98.000 (99.308) +2022-11-14 15:48:50,164 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0749) Prec@1 90.000 (87.861) Prec@5 100.000 (99.316) +2022-11-14 15:48:50,175 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0749) Prec@1 88.000 (87.862) Prec@5 100.000 (99.325) +2022-11-14 15:48:50,187 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0751) Prec@1 84.000 (87.815) Prec@5 100.000 (99.333) +2022-11-14 15:48:50,198 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0751) Prec@1 88.000 (87.817) Prec@5 99.000 (99.329) +2022-11-14 15:48:50,209 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0753) Prec@1 84.000 (87.771) Prec@5 99.000 (99.325) +2022-11-14 15:48:50,220 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0754) Prec@1 85.000 (87.738) Prec@5 100.000 (99.333) +2022-11-14 15:48:50,231 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0754) Prec@1 86.000 (87.718) Prec@5 99.000 (99.329) +2022-11-14 15:48:50,242 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0757) Prec@1 83.000 (87.663) Prec@5 100.000 (99.337) +2022-11-14 15:48:50,253 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0757) Prec@1 90.000 (87.690) Prec@5 100.000 (99.345) +2022-11-14 15:48:50,264 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0758) Prec@1 83.000 (87.636) Prec@5 98.000 (99.330) +2022-11-14 15:48:50,278 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0758) Prec@1 89.000 (87.652) Prec@5 99.000 (99.326) +2022-11-14 15:48:50,294 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0755) Prec@1 92.000 (87.700) Prec@5 99.000 (99.322) +2022-11-14 15:48:50,311 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0752) Prec@1 91.000 (87.736) Prec@5 99.000 (99.319) +2022-11-14 15:48:50,326 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0751) Prec@1 90.000 (87.761) Prec@5 100.000 (99.326) +2022-11-14 15:48:50,344 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0752) Prec@1 85.000 (87.731) Prec@5 100.000 (99.333) +2022-11-14 15:48:50,365 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0752) Prec@1 88.000 (87.734) Prec@5 100.000 (99.340) +2022-11-14 15:48:50,385 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0754) Prec@1 85.000 (87.705) Prec@5 100.000 (99.347) +2022-11-14 15:48:50,408 Test: [95/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0753) Prec@1 92.000 (87.750) Prec@5 100.000 (99.354) +2022-11-14 15:48:50,433 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0751) Prec@1 92.000 (87.794) Prec@5 98.000 (99.340) +2022-11-14 15:48:50,456 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0753) Prec@1 86.000 (87.776) Prec@5 99.000 (99.337) +2022-11-14 15:48:50,480 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0755) Prec@1 84.000 (87.737) Prec@5 99.000 (99.333) +2022-11-14 15:48:50,505 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0754) Prec@1 91.000 (87.770) Prec@5 100.000 (99.340) +2022-11-14 15:48:50,571 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:48:50,950 Epoch: [266][0/500] Time 0.028 (0.028) Data 0.279 (0.279) Loss 0.0283 (0.0283) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:51,263 Epoch: [266][10/500] Time 0.032 (0.028) Data 0.002 (0.027) Loss 0.0262 (0.0273) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:51,626 Epoch: [266][20/500] Time 0.031 (0.030) Data 0.002 (0.015) Loss 0.0465 (0.0337) Prec@1 92.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 15:48:51,977 Epoch: [266][30/500] Time 0.030 (0.030) Data 0.002 (0.011) Loss 0.0324 (0.0334) Prec@1 95.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 15:48:52,334 Epoch: [266][40/500] Time 0.029 (0.031) Data 0.002 (0.009) Loss 0.0410 (0.0349) Prec@1 92.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 15:48:52,683 Epoch: [266][50/500] Time 0.032 (0.031) Data 0.002 (0.007) Loss 0.0384 (0.0355) Prec@1 94.000 (94.167) Prec@5 100.000 (100.000) +2022-11-14 15:48:53,030 Epoch: [266][60/500] Time 0.037 (0.031) Data 0.002 (0.007) Loss 0.0347 (0.0354) Prec@1 94.000 (94.143) Prec@5 100.000 (100.000) +2022-11-14 15:48:53,357 Epoch: [266][70/500] Time 0.031 (0.031) Data 0.002 (0.006) Loss 0.0476 (0.0369) Prec@1 92.000 (93.875) Prec@5 100.000 (100.000) +2022-11-14 15:48:53,704 Epoch: [266][80/500] Time 0.036 (0.031) Data 0.002 (0.005) Loss 0.0270 (0.0358) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:48:54,055 Epoch: [266][90/500] Time 0.029 (0.031) Data 0.003 (0.005) Loss 0.0501 (0.0372) Prec@1 90.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 15:48:54,392 Epoch: [266][100/500] Time 0.030 (0.031) Data 0.002 (0.005) Loss 0.0360 (0.0371) Prec@1 93.000 (93.545) Prec@5 100.000 (100.000) +2022-11-14 15:48:54,732 Epoch: [266][110/500] Time 0.026 (0.031) Data 0.002 (0.004) Loss 0.0487 (0.0381) Prec@1 92.000 (93.417) Prec@5 100.000 (100.000) +2022-11-14 15:48:55,070 Epoch: [266][120/500] Time 0.024 (0.030) Data 0.002 (0.004) Loss 0.0362 (0.0379) Prec@1 94.000 (93.462) Prec@5 100.000 (100.000) +2022-11-14 15:48:55,409 Epoch: [266][130/500] Time 0.033 (0.030) Data 0.002 (0.004) Loss 0.0272 (0.0372) Prec@1 95.000 (93.571) Prec@5 100.000 (100.000) +2022-11-14 15:48:55,760 Epoch: [266][140/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0175 (0.0359) Prec@1 97.000 (93.800) Prec@5 100.000 (100.000) +2022-11-14 15:48:56,101 Epoch: [266][150/500] Time 0.035 (0.030) Data 0.002 (0.004) Loss 0.0307 (0.0355) Prec@1 94.000 (93.812) Prec@5 100.000 (100.000) +2022-11-14 15:48:56,446 Epoch: [266][160/500] Time 0.033 (0.030) Data 0.002 (0.004) Loss 0.0447 (0.0361) Prec@1 92.000 (93.706) Prec@5 100.000 (100.000) +2022-11-14 15:48:56,793 Epoch: [266][170/500] Time 0.031 (0.030) Data 0.002 (0.004) Loss 0.0332 (0.0359) Prec@1 95.000 (93.778) Prec@5 100.000 (100.000) +2022-11-14 15:48:57,293 Epoch: [266][180/500] Time 0.087 (0.031) Data 0.002 (0.003) Loss 0.0330 (0.0358) Prec@1 94.000 (93.789) Prec@5 100.000 (100.000) +2022-11-14 15:48:58,051 Epoch: [266][190/500] Time 0.070 (0.033) Data 0.002 (0.003) Loss 0.0397 (0.0360) Prec@1 92.000 (93.700) Prec@5 100.000 (100.000) +2022-11-14 15:48:58,986 Epoch: [266][200/500] Time 0.067 (0.036) Data 0.002 (0.003) Loss 0.0147 (0.0349) Prec@1 98.000 (93.905) Prec@5 100.000 (100.000) +2022-11-14 15:48:59,759 Epoch: [266][210/500] Time 0.072 (0.037) Data 0.003 (0.003) Loss 0.0477 (0.0355) Prec@1 91.000 (93.773) Prec@5 99.000 (99.955) +2022-11-14 15:49:00,503 Epoch: [266][220/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0314 (0.0353) Prec@1 93.000 (93.739) Prec@5 100.000 (99.957) +2022-11-14 15:49:00,971 Epoch: [266][230/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0777 (0.0371) Prec@1 85.000 (93.375) Prec@5 98.000 (99.875) +2022-11-14 15:49:01,409 Epoch: [266][240/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0402 (0.0372) Prec@1 94.000 (93.400) Prec@5 100.000 (99.880) +2022-11-14 15:49:01,856 Epoch: [266][250/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0229 (0.0367) Prec@1 97.000 (93.538) Prec@5 99.000 (99.846) +2022-11-14 15:49:02,280 Epoch: [266][260/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0409 (0.0368) Prec@1 94.000 (93.556) Prec@5 100.000 (99.852) +2022-11-14 15:49:02,688 Epoch: [266][270/500] Time 0.030 (0.039) Data 0.002 (0.003) Loss 0.0535 (0.0374) Prec@1 91.000 (93.464) Prec@5 99.000 (99.821) +2022-11-14 15:49:03,105 Epoch: [266][280/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0173 (0.0367) Prec@1 97.000 (93.586) Prec@5 100.000 (99.828) +2022-11-14 15:49:03,517 Epoch: [266][290/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.0549 (0.0373) Prec@1 90.000 (93.467) Prec@5 100.000 (99.833) +2022-11-14 15:49:03,927 Epoch: [266][300/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0387 (0.0374) Prec@1 95.000 (93.516) Prec@5 100.000 (99.839) +2022-11-14 15:49:04,342 Epoch: [266][310/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0397 (0.0375) Prec@1 93.000 (93.500) Prec@5 100.000 (99.844) +2022-11-14 15:49:04,767 Epoch: [266][320/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0271 (0.0371) Prec@1 95.000 (93.545) Prec@5 100.000 (99.848) +2022-11-14 15:49:05,195 Epoch: [266][330/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0404 (0.0372) Prec@1 94.000 (93.559) Prec@5 100.000 (99.853) +2022-11-14 15:49:05,637 Epoch: [266][340/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0239 (0.0369) Prec@1 95.000 (93.600) Prec@5 100.000 (99.857) +2022-11-14 15:49:06,076 Epoch: [266][350/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0343 (0.0368) Prec@1 94.000 (93.611) Prec@5 100.000 (99.861) +2022-11-14 15:49:06,499 Epoch: [266][360/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0199 (0.0363) Prec@1 98.000 (93.730) Prec@5 100.000 (99.865) +2022-11-14 15:49:06,911 Epoch: [266][370/500] Time 0.031 (0.038) Data 0.002 (0.003) Loss 0.0324 (0.0362) Prec@1 94.000 (93.737) Prec@5 99.000 (99.842) +2022-11-14 15:49:07,381 Epoch: [266][380/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0317 (0.0361) Prec@1 93.000 (93.718) Prec@5 100.000 (99.846) +2022-11-14 15:49:07,779 Epoch: [266][390/500] Time 0.035 (0.038) Data 0.002 (0.003) Loss 0.0347 (0.0361) Prec@1 95.000 (93.750) Prec@5 99.000 (99.825) +2022-11-14 15:49:08,185 Epoch: [266][400/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0136 (0.0355) Prec@1 98.000 (93.854) Prec@5 100.000 (99.829) +2022-11-14 15:49:08,605 Epoch: [266][410/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0258 (0.0353) Prec@1 94.000 (93.857) Prec@5 100.000 (99.833) +2022-11-14 15:49:09,066 Epoch: [266][420/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0239 (0.0350) Prec@1 97.000 (93.930) Prec@5 100.000 (99.837) +2022-11-14 15:49:09,499 Epoch: [266][430/500] Time 0.049 (0.038) Data 0.002 (0.003) Loss 0.0584 (0.0356) Prec@1 90.000 (93.841) Prec@5 99.000 (99.818) +2022-11-14 15:49:09,926 Epoch: [266][440/500] Time 0.033 (0.038) Data 0.002 (0.003) Loss 0.0357 (0.0356) Prec@1 94.000 (93.844) Prec@5 100.000 (99.822) +2022-11-14 15:49:10,376 Epoch: [266][450/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0428 (0.0357) Prec@1 91.000 (93.783) Prec@5 100.000 (99.826) +2022-11-14 15:49:10,790 Epoch: [266][460/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0310 (0.0356) Prec@1 95.000 (93.809) Prec@5 100.000 (99.830) +2022-11-14 15:49:11,199 Epoch: [266][470/500] Time 0.038 (0.038) Data 0.003 (0.003) Loss 0.0344 (0.0356) Prec@1 93.000 (93.792) Prec@5 100.000 (99.833) +2022-11-14 15:49:11,615 Epoch: [266][480/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0236 (0.0354) Prec@1 96.000 (93.837) Prec@5 100.000 (99.837) +2022-11-14 15:49:12,026 Epoch: [266][490/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0445 (0.0355) Prec@1 91.000 (93.780) Prec@5 100.000 (99.840) +2022-11-14 15:49:12,400 Epoch: [266][499/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0393 (0.0356) Prec@1 94.000 (93.784) Prec@5 100.000 (99.843) +2022-11-14 15:49:12,707 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0770 (0.0770) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,718 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0894 (0.0832) Prec@1 86.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,731 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0675 (0.0780) Prec@1 88.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,745 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0676 (0.0754) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,757 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0795) Prec@1 82.000 (86.800) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,768 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0342 (0.0719) Prec@1 94.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,781 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0548 (0.0695) Prec@1 92.000 (88.571) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,794 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0699) Prec@1 85.000 (88.125) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,805 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0708) Prec@1 86.000 (87.889) Prec@5 100.000 (100.000) +2022-11-14 15:49:12,817 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0733) Prec@1 85.000 (87.600) Prec@5 98.000 (99.800) +2022-11-14 15:49:12,831 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0713) Prec@1 92.000 (88.000) Prec@5 100.000 (99.818) +2022-11-14 15:49:12,845 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0717) Prec@1 88.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 15:49:12,859 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0718) Prec@1 86.000 (87.846) Prec@5 100.000 (99.769) +2022-11-14 15:49:12,872 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0739) Prec@1 84.000 (87.571) Prec@5 99.000 (99.714) +2022-11-14 15:49:12,887 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0738) Prec@1 89.000 (87.667) Prec@5 100.000 (99.733) +2022-11-14 15:49:12,903 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0740) Prec@1 85.000 (87.500) Prec@5 100.000 (99.750) +2022-11-14 15:49:12,917 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0731) Prec@1 92.000 (87.765) Prec@5 99.000 (99.706) +2022-11-14 15:49:12,932 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1239 (0.0760) Prec@1 81.000 (87.389) Prec@5 99.000 (99.667) +2022-11-14 15:49:12,948 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0773) Prec@1 82.000 (87.105) Prec@5 100.000 (99.684) +2022-11-14 15:49:12,963 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0780) Prec@1 86.000 (87.050) Prec@5 98.000 (99.600) +2022-11-14 15:49:12,976 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0787) Prec@1 86.000 (87.000) Prec@5 100.000 (99.619) +2022-11-14 15:49:12,991 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0781) Prec@1 88.000 (87.045) Prec@5 99.000 (99.591) +2022-11-14 15:49:13,008 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0794) Prec@1 87.000 (87.043) Prec@5 98.000 (99.522) +2022-11-14 15:49:13,024 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0785) Prec@1 91.000 (87.208) Prec@5 100.000 (99.542) +2022-11-14 15:49:13,039 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0788) Prec@1 84.000 (87.080) Prec@5 98.000 (99.480) +2022-11-14 15:49:13,056 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0790) Prec@1 87.000 (87.077) Prec@5 98.000 (99.423) +2022-11-14 15:49:13,071 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0783) Prec@1 89.000 (87.148) Prec@5 100.000 (99.444) +2022-11-14 15:49:13,085 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0776) Prec@1 91.000 (87.286) Prec@5 100.000 (99.464) +2022-11-14 15:49:13,100 Test: [28/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0769) Prec@1 91.000 (87.414) Prec@5 99.000 (99.448) +2022-11-14 15:49:13,115 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0769) Prec@1 84.000 (87.300) Prec@5 100.000 (99.467) +2022-11-14 15:49:13,129 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0764) Prec@1 90.000 (87.387) Prec@5 99.000 (99.452) +2022-11-14 15:49:13,144 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0763) Prec@1 87.000 (87.375) Prec@5 99.000 (99.438) +2022-11-14 15:49:13,160 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0764) Prec@1 87.000 (87.364) Prec@5 99.000 (99.424) +2022-11-14 15:49:13,176 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0768) Prec@1 84.000 (87.265) Prec@5 99.000 (99.412) +2022-11-14 15:49:13,190 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0772) Prec@1 86.000 (87.229) Prec@5 98.000 (99.371) +2022-11-14 15:49:13,202 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0774) Prec@1 87.000 (87.222) Prec@5 99.000 (99.361) +2022-11-14 15:49:13,217 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0771) Prec@1 90.000 (87.297) Prec@5 98.000 (99.324) +2022-11-14 15:49:13,232 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0777) Prec@1 81.000 (87.132) Prec@5 99.000 (99.316) +2022-11-14 15:49:13,247 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0775) Prec@1 91.000 (87.231) Prec@5 98.000 (99.282) +2022-11-14 15:49:13,261 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0773) Prec@1 90.000 (87.300) Prec@5 99.000 (99.275) +2022-11-14 15:49:13,276 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0779) Prec@1 86.000 (87.268) Prec@5 99.000 (99.268) +2022-11-14 15:49:13,292 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0781) Prec@1 87.000 (87.262) Prec@5 99.000 (99.262) +2022-11-14 15:49:13,308 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0775) Prec@1 92.000 (87.372) Prec@5 100.000 (99.279) +2022-11-14 15:49:13,324 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0775) Prec@1 86.000 (87.341) Prec@5 99.000 (99.273) +2022-11-14 15:49:13,337 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0773) Prec@1 87.000 (87.333) Prec@5 99.000 (99.267) +2022-11-14 15:49:13,351 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0777) Prec@1 84.000 (87.261) Prec@5 100.000 (99.283) +2022-11-14 15:49:13,369 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0776) Prec@1 88.000 (87.277) Prec@5 100.000 (99.298) +2022-11-14 15:49:13,387 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0779) Prec@1 88.000 (87.292) Prec@5 99.000 (99.292) +2022-11-14 15:49:13,403 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0776) Prec@1 88.000 (87.306) Prec@5 100.000 (99.306) +2022-11-14 15:49:13,418 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1180 (0.0784) Prec@1 83.000 (87.220) Prec@5 99.000 (99.300) +2022-11-14 15:49:13,433 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0784) Prec@1 87.000 (87.216) Prec@5 99.000 (99.294) +2022-11-14 15:49:13,447 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0784) Prec@1 87.000 (87.212) Prec@5 100.000 (99.308) +2022-11-14 15:49:13,463 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0780) Prec@1 91.000 (87.283) Prec@5 100.000 (99.321) +2022-11-14 15:49:13,477 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0778) Prec@1 89.000 (87.315) Prec@5 100.000 (99.333) +2022-11-14 15:49:13,491 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1047 (0.0783) Prec@1 83.000 (87.236) Prec@5 99.000 (99.327) +2022-11-14 15:49:13,504 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0782) Prec@1 89.000 (87.268) Prec@5 99.000 (99.321) +2022-11-14 15:49:13,520 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0777) Prec@1 91.000 (87.333) Prec@5 100.000 (99.333) +2022-11-14 15:49:13,536 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0778) Prec@1 87.000 (87.328) Prec@5 99.000 (99.328) +2022-11-14 15:49:13,552 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1040 (0.0782) Prec@1 83.000 (87.254) Prec@5 99.000 (99.322) +2022-11-14 15:49:13,566 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0782) Prec@1 87.000 (87.250) Prec@5 99.000 (99.317) +2022-11-14 15:49:13,580 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0785) Prec@1 85.000 (87.213) Prec@5 100.000 (99.328) +2022-11-14 15:49:13,597 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0784) Prec@1 89.000 (87.242) Prec@5 99.000 (99.323) +2022-11-14 15:49:13,613 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0783) Prec@1 88.000 (87.254) Prec@5 100.000 (99.333) +2022-11-14 15:49:13,628 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0780) Prec@1 93.000 (87.344) Prec@5 100.000 (99.344) +2022-11-14 15:49:13,643 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0785) Prec@1 82.000 (87.262) Prec@5 99.000 (99.338) +2022-11-14 15:49:13,657 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0783) Prec@1 86.000 (87.242) Prec@5 99.000 (99.333) +2022-11-14 15:49:13,674 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0778) Prec@1 93.000 (87.328) Prec@5 100.000 (99.343) +2022-11-14 15:49:13,689 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0778) Prec@1 86.000 (87.309) Prec@5 99.000 (99.338) +2022-11-14 15:49:13,706 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0776) Prec@1 89.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 15:49:13,722 Test: [69/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1183 (0.0782) Prec@1 81.000 (87.243) Prec@5 99.000 (99.329) +2022-11-14 15:49:13,736 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0784) Prec@1 89.000 (87.268) Prec@5 99.000 (99.324) +2022-11-14 15:49:13,749 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0784) Prec@1 86.000 (87.250) Prec@5 98.000 (99.306) +2022-11-14 15:49:13,765 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0781) Prec@1 92.000 (87.315) Prec@5 100.000 (99.315) +2022-11-14 15:49:13,779 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0779) Prec@1 88.000 (87.324) Prec@5 100.000 (99.324) +2022-11-14 15:49:13,794 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1188 (0.0784) Prec@1 79.000 (87.213) Prec@5 99.000 (99.320) +2022-11-14 15:49:13,808 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0782) Prec@1 90.000 (87.250) Prec@5 98.000 (99.303) +2022-11-14 15:49:13,822 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0782) Prec@1 87.000 (87.247) Prec@5 98.000 (99.286) +2022-11-14 15:49:13,836 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1250 (0.0788) Prec@1 78.000 (87.128) Prec@5 98.000 (99.269) +2022-11-14 15:49:13,850 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0788) Prec@1 89.000 (87.152) Prec@5 99.000 (99.266) +2022-11-14 15:49:13,867 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0787) Prec@1 88.000 (87.162) Prec@5 99.000 (99.263) +2022-11-14 15:49:13,882 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0787) Prec@1 88.000 (87.173) Prec@5 98.000 (99.247) +2022-11-14 15:49:13,896 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0787) Prec@1 87.000 (87.171) Prec@5 99.000 (99.244) +2022-11-14 15:49:13,910 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0789) Prec@1 86.000 (87.157) Prec@5 100.000 (99.253) +2022-11-14 15:49:13,925 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0788) Prec@1 84.000 (87.119) Prec@5 100.000 (99.262) +2022-11-14 15:49:13,940 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0789) Prec@1 85.000 (87.094) Prec@5 99.000 (99.259) +2022-11-14 15:49:13,954 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1201 (0.0794) Prec@1 81.000 (87.023) Prec@5 99.000 (99.256) +2022-11-14 15:49:13,969 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0796) Prec@1 85.000 (87.000) Prec@5 99.000 (99.253) +2022-11-14 15:49:13,984 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0796) Prec@1 86.000 (86.989) Prec@5 99.000 (99.250) +2022-11-14 15:49:13,999 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0796) Prec@1 88.000 (87.000) Prec@5 99.000 (99.247) +2022-11-14 15:49:14,014 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0792) Prec@1 92.000 (87.056) Prec@5 99.000 (99.244) +2022-11-14 15:49:14,028 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0790) Prec@1 89.000 (87.077) Prec@5 100.000 (99.253) +2022-11-14 15:49:14,043 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0787) Prec@1 91.000 (87.120) Prec@5 99.000 (99.250) +2022-11-14 15:49:14,059 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0789) Prec@1 84.000 (87.086) Prec@5 98.000 (99.237) +2022-11-14 15:49:14,075 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0788) Prec@1 87.000 (87.085) Prec@5 100.000 (99.245) +2022-11-14 15:49:14,091 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0789) Prec@1 86.000 (87.074) Prec@5 99.000 (99.242) +2022-11-14 15:49:14,107 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0787) Prec@1 88.000 (87.083) Prec@5 99.000 (99.240) +2022-11-14 15:49:14,122 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0784) Prec@1 91.000 (87.124) Prec@5 99.000 (99.237) +2022-11-14 15:49:14,136 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0786) Prec@1 84.000 (87.092) Prec@5 97.000 (99.214) +2022-11-14 15:49:14,149 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0790) Prec@1 83.000 (87.051) Prec@5 99.000 (99.212) +2022-11-14 15:49:14,161 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0788) Prec@1 88.000 (87.060) Prec@5 99.000 (99.210) +2022-11-14 15:49:14,220 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:49:14,578 Epoch: [267][0/500] Time 0.027 (0.027) Data 0.263 (0.263) Loss 0.0348 (0.0348) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:14,843 Epoch: [267][10/500] Time 0.025 (0.024) Data 0.002 (0.026) Loss 0.0102 (0.0225) Prec@1 99.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 15:49:15,111 Epoch: [267][20/500] Time 0.027 (0.024) Data 0.002 (0.014) Loss 0.0260 (0.0237) Prec@1 96.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 15:49:15,408 Epoch: [267][30/500] Time 0.031 (0.024) Data 0.002 (0.010) Loss 0.0244 (0.0238) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:15,792 Epoch: [267][40/500] Time 0.040 (0.027) Data 0.002 (0.008) Loss 0.0368 (0.0264) Prec@1 95.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 15:49:16,171 Epoch: [267][50/500] Time 0.039 (0.028) Data 0.002 (0.007) Loss 0.0366 (0.0281) Prec@1 94.000 (95.500) Prec@5 99.000 (99.833) +2022-11-14 15:49:16,560 Epoch: [267][60/500] Time 0.039 (0.029) Data 0.002 (0.006) Loss 0.0116 (0.0258) Prec@1 100.000 (96.143) Prec@5 100.000 (99.857) +2022-11-14 15:49:16,952 Epoch: [267][70/500] Time 0.032 (0.030) Data 0.002 (0.006) Loss 0.0223 (0.0253) Prec@1 98.000 (96.375) Prec@5 100.000 (99.875) +2022-11-14 15:49:17,323 Epoch: [267][80/500] Time 0.035 (0.030) Data 0.002 (0.005) Loss 0.0347 (0.0264) Prec@1 95.000 (96.222) Prec@5 99.000 (99.778) +2022-11-14 15:49:17,713 Epoch: [267][90/500] Time 0.042 (0.031) Data 0.002 (0.005) Loss 0.0179 (0.0255) Prec@1 97.000 (96.300) Prec@5 100.000 (99.800) +2022-11-14 15:49:18,130 Epoch: [267][100/500] Time 0.043 (0.031) Data 0.002 (0.005) Loss 0.0435 (0.0272) Prec@1 94.000 (96.091) Prec@5 100.000 (99.818) +2022-11-14 15:49:18,585 Epoch: [267][110/500] Time 0.043 (0.032) Data 0.002 (0.004) Loss 0.0350 (0.0278) Prec@1 93.000 (95.833) Prec@5 99.000 (99.750) +2022-11-14 15:49:19,008 Epoch: [267][120/500] Time 0.040 (0.033) Data 0.002 (0.004) Loss 0.0399 (0.0288) Prec@1 91.000 (95.462) Prec@5 100.000 (99.769) +2022-11-14 15:49:19,382 Epoch: [267][130/500] Time 0.032 (0.033) Data 0.002 (0.004) Loss 0.0662 (0.0314) Prec@1 89.000 (95.000) Prec@5 100.000 (99.786) +2022-11-14 15:49:19,757 Epoch: [267][140/500] Time 0.036 (0.033) Data 0.002 (0.004) Loss 0.0357 (0.0317) Prec@1 93.000 (94.867) Prec@5 100.000 (99.800) +2022-11-14 15:49:20,143 Epoch: [267][150/500] Time 0.029 (0.033) Data 0.002 (0.004) Loss 0.0343 (0.0319) Prec@1 93.000 (94.750) Prec@5 100.000 (99.812) +2022-11-14 15:49:20,533 Epoch: [267][160/500] Time 0.038 (0.033) Data 0.002 (0.004) Loss 0.0203 (0.0312) Prec@1 97.000 (94.882) Prec@5 100.000 (99.824) +2022-11-14 15:49:21,004 Epoch: [267][170/500] Time 0.061 (0.033) Data 0.002 (0.004) Loss 0.0500 (0.0322) Prec@1 92.000 (94.722) Prec@5 100.000 (99.833) +2022-11-14 15:49:21,769 Epoch: [267][180/500] Time 0.069 (0.035) Data 0.002 (0.003) Loss 0.0249 (0.0319) Prec@1 96.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 15:49:22,594 Epoch: [267][190/500] Time 0.086 (0.037) Data 0.002 (0.003) Loss 0.0413 (0.0323) Prec@1 94.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 15:49:23,358 Epoch: [267][200/500] Time 0.076 (0.039) Data 0.002 (0.003) Loss 0.0436 (0.0329) Prec@1 94.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 15:49:24,075 Epoch: [267][210/500] Time 0.064 (0.040) Data 0.002 (0.003) Loss 0.0257 (0.0325) Prec@1 96.000 (94.773) Prec@5 100.000 (99.864) +2022-11-14 15:49:24,835 Epoch: [267][220/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.0373 (0.0327) Prec@1 94.000 (94.739) Prec@5 100.000 (99.870) +2022-11-14 15:49:25,619 Epoch: [267][230/500] Time 0.094 (0.043) Data 0.002 (0.003) Loss 0.0333 (0.0328) Prec@1 94.000 (94.708) Prec@5 100.000 (99.875) +2022-11-14 15:49:26,326 Epoch: [267][240/500] Time 0.066 (0.044) Data 0.002 (0.003) Loss 0.0368 (0.0329) Prec@1 95.000 (94.720) Prec@5 100.000 (99.880) +2022-11-14 15:49:26,739 Epoch: [267][250/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0368 (0.0331) Prec@1 95.000 (94.731) Prec@5 100.000 (99.885) +2022-11-14 15:49:27,172 Epoch: [267][260/500] Time 0.044 (0.043) Data 0.003 (0.003) Loss 0.0278 (0.0329) Prec@1 96.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 15:49:27,584 Epoch: [267][270/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0250 (0.0326) Prec@1 97.000 (94.857) Prec@5 99.000 (99.857) +2022-11-14 15:49:27,973 Epoch: [267][280/500] Time 0.033 (0.043) Data 0.002 (0.003) Loss 0.0333 (0.0326) Prec@1 95.000 (94.862) Prec@5 100.000 (99.862) +2022-11-14 15:49:28,344 Epoch: [267][290/500] Time 0.034 (0.042) Data 0.002 (0.003) Loss 0.0503 (0.0332) Prec@1 91.000 (94.733) Prec@5 100.000 (99.867) +2022-11-14 15:49:28,726 Epoch: [267][300/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0535 (0.0339) Prec@1 90.000 (94.581) Prec@5 99.000 (99.839) +2022-11-14 15:49:29,125 Epoch: [267][310/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0428 (0.0341) Prec@1 93.000 (94.531) Prec@5 100.000 (99.844) +2022-11-14 15:49:29,515 Epoch: [267][320/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0748 (0.0354) Prec@1 87.000 (94.303) Prec@5 99.000 (99.818) +2022-11-14 15:49:29,890 Epoch: [267][330/500] Time 0.032 (0.041) Data 0.002 (0.003) Loss 0.0400 (0.0355) Prec@1 93.000 (94.265) Prec@5 100.000 (99.824) +2022-11-14 15:49:30,279 Epoch: [267][340/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0417 (0.0357) Prec@1 95.000 (94.286) Prec@5 100.000 (99.829) +2022-11-14 15:49:30,667 Epoch: [267][350/500] Time 0.034 (0.041) Data 0.002 (0.003) Loss 0.0218 (0.0353) Prec@1 96.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 15:49:31,072 Epoch: [267][360/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0247 (0.0350) Prec@1 96.000 (94.378) Prec@5 100.000 (99.838) +2022-11-14 15:49:31,512 Epoch: [267][370/500] Time 0.045 (0.041) Data 0.003 (0.003) Loss 0.0300 (0.0349) Prec@1 95.000 (94.395) Prec@5 100.000 (99.842) +2022-11-14 15:49:31,905 Epoch: [267][380/500] Time 0.033 (0.041) Data 0.002 (0.003) Loss 0.0605 (0.0355) Prec@1 91.000 (94.308) Prec@5 99.000 (99.821) +2022-11-14 15:49:32,289 Epoch: [267][390/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0339 (0.0355) Prec@1 95.000 (94.325) Prec@5 99.000 (99.800) +2022-11-14 15:49:32,660 Epoch: [267][400/500] Time 0.033 (0.040) Data 0.002 (0.003) Loss 0.0419 (0.0357) Prec@1 94.000 (94.317) Prec@5 100.000 (99.805) +2022-11-14 15:49:33,043 Epoch: [267][410/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0394 (0.0357) Prec@1 93.000 (94.286) Prec@5 100.000 (99.810) +2022-11-14 15:49:33,424 Epoch: [267][420/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0160 (0.0353) Prec@1 99.000 (94.395) Prec@5 100.000 (99.814) +2022-11-14 15:49:33,803 Epoch: [267][430/500] Time 0.036 (0.040) Data 0.002 (0.003) Loss 0.0283 (0.0351) Prec@1 97.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 15:49:34,178 Epoch: [267][440/500] Time 0.034 (0.040) Data 0.002 (0.003) Loss 0.0521 (0.0355) Prec@1 92.000 (94.400) Prec@5 100.000 (99.822) +2022-11-14 15:49:34,563 Epoch: [267][450/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0376 (0.0355) Prec@1 93.000 (94.370) Prec@5 100.000 (99.826) +2022-11-14 15:49:34,939 Epoch: [267][460/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0386 (0.0356) Prec@1 94.000 (94.362) Prec@5 100.000 (99.830) +2022-11-14 15:49:35,315 Epoch: [267][470/500] Time 0.030 (0.039) Data 0.002 (0.003) Loss 0.0255 (0.0354) Prec@1 95.000 (94.375) Prec@5 100.000 (99.833) +2022-11-14 15:49:35,817 Epoch: [267][480/500] Time 0.072 (0.039) Data 0.002 (0.003) Loss 0.0288 (0.0353) Prec@1 95.000 (94.388) Prec@5 100.000 (99.837) +2022-11-14 15:49:36,541 Epoch: [267][490/500] Time 0.075 (0.040) Data 0.003 (0.003) Loss 0.0306 (0.0352) Prec@1 95.000 (94.400) Prec@5 100.000 (99.840) +2022-11-14 15:49:37,258 Epoch: [267][499/500] Time 0.089 (0.040) Data 0.002 (0.003) Loss 0.0194 (0.0349) Prec@1 98.000 (94.471) Prec@5 100.000 (99.843) +2022-11-14 15:49:37,576 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0649 (0.0649) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:37,590 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0691 (0.0670) Prec@1 89.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 15:49:37,602 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0654 (0.0665) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 15:49:37,618 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0836 (0.0707) Prec@1 84.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 15:49:37,634 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0870 (0.0740) Prec@1 85.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 15:49:37,656 Test: [5/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0548 (0.0708) Prec@1 90.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 15:49:37,674 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0467 (0.0674) Prec@1 92.000 (88.286) Prec@5 100.000 (99.714) +2022-11-14 15:49:37,694 Test: [7/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0885 (0.0700) Prec@1 87.000 (88.125) Prec@5 99.000 (99.625) +2022-11-14 15:49:37,717 Test: [8/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0811 (0.0712) Prec@1 86.000 (87.889) Prec@5 100.000 (99.667) +2022-11-14 15:49:37,745 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0675 (0.0709) Prec@1 90.000 (88.100) Prec@5 99.000 (99.600) +2022-11-14 15:49:37,773 Test: [10/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0616 (0.0700) Prec@1 90.000 (88.273) Prec@5 100.000 (99.636) +2022-11-14 15:49:37,801 Test: [11/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0803 (0.0709) Prec@1 87.000 (88.167) Prec@5 99.000 (99.583) +2022-11-14 15:49:37,829 Test: [12/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0414 (0.0686) Prec@1 94.000 (88.615) Prec@5 100.000 (99.615) +2022-11-14 15:49:37,856 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0765 (0.0692) Prec@1 87.000 (88.500) Prec@5 100.000 (99.643) +2022-11-14 15:49:37,877 Test: [14/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0740 (0.0695) Prec@1 90.000 (88.600) Prec@5 100.000 (99.667) +2022-11-14 15:49:37,903 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0898 (0.0708) Prec@1 88.000 (88.562) Prec@5 99.000 (99.625) +2022-11-14 15:49:37,931 Test: [16/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0508 (0.0696) Prec@1 94.000 (88.882) Prec@5 98.000 (99.529) +2022-11-14 15:49:37,960 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.0715) Prec@1 81.000 (88.444) Prec@5 100.000 (99.556) +2022-11-14 15:49:37,990 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0903 (0.0725) Prec@1 82.000 (88.105) Prec@5 98.000 (99.474) +2022-11-14 15:49:38,017 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0980 (0.0738) Prec@1 83.000 (87.850) Prec@5 99.000 (99.450) +2022-11-14 15:49:38,047 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0734) Prec@1 87.000 (87.810) Prec@5 100.000 (99.476) +2022-11-14 15:49:38,076 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0740) Prec@1 88.000 (87.818) Prec@5 99.000 (99.455) +2022-11-14 15:49:38,103 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0741) Prec@1 88.000 (87.826) Prec@5 100.000 (99.478) +2022-11-14 15:49:38,128 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0742) Prec@1 85.000 (87.708) Prec@5 99.000 (99.458) +2022-11-14 15:49:38,157 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0747) Prec@1 85.000 (87.600) Prec@5 99.000 (99.440) +2022-11-14 15:49:38,183 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0755) Prec@1 86.000 (87.538) Prec@5 99.000 (99.423) +2022-11-14 15:49:38,213 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0750) Prec@1 90.000 (87.630) Prec@5 100.000 (99.444) +2022-11-14 15:49:38,239 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0749) Prec@1 90.000 (87.714) Prec@5 100.000 (99.464) +2022-11-14 15:49:38,269 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0749) Prec@1 89.000 (87.759) Prec@5 98.000 (99.414) +2022-11-14 15:49:38,297 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0747) Prec@1 87.000 (87.733) Prec@5 99.000 (99.400) +2022-11-14 15:49:38,324 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0892 (0.0752) Prec@1 85.000 (87.645) Prec@5 100.000 (99.419) +2022-11-14 15:49:38,354 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0462 (0.0743) Prec@1 93.000 (87.812) Prec@5 100.000 (99.438) +2022-11-14 15:49:38,380 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0527 (0.0736) Prec@1 92.000 (87.939) Prec@5 100.000 (99.455) +2022-11-14 15:49:38,410 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1073 (0.0746) Prec@1 84.000 (87.824) Prec@5 98.000 (99.412) +2022-11-14 15:49:38,435 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0815 (0.0748) Prec@1 87.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 15:49:38,461 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0745) Prec@1 90.000 (87.861) Prec@5 99.000 (99.389) +2022-11-14 15:49:38,491 Test: [36/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0745) Prec@1 89.000 (87.892) Prec@5 98.000 (99.351) +2022-11-14 15:49:38,520 Test: [37/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0946 (0.0750) Prec@1 83.000 (87.763) Prec@5 99.000 (99.342) +2022-11-14 15:49:38,548 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0747) Prec@1 91.000 (87.846) Prec@5 99.000 (99.333) +2022-11-14 15:49:38,579 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0673 (0.0745) Prec@1 89.000 (87.875) Prec@5 98.000 (99.300) +2022-11-14 15:49:38,608 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0748) Prec@1 87.000 (87.854) Prec@5 95.000 (99.195) +2022-11-14 15:49:38,635 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0596 (0.0744) Prec@1 90.000 (87.905) Prec@5 99.000 (99.190) +2022-11-14 15:49:38,662 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0431 (0.0737) Prec@1 94.000 (88.047) Prec@5 99.000 (99.186) +2022-11-14 15:49:38,691 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0777 (0.0738) Prec@1 88.000 (88.045) Prec@5 99.000 (99.182) +2022-11-14 15:49:38,721 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0737) Prec@1 88.000 (88.044) Prec@5 100.000 (99.200) +2022-11-14 15:49:38,749 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1049 (0.0744) Prec@1 81.000 (87.891) Prec@5 100.000 (99.217) +2022-11-14 15:49:38,778 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0545 (0.0740) Prec@1 91.000 (87.957) Prec@5 99.000 (99.213) +2022-11-14 15:49:38,806 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0906 (0.0743) Prec@1 84.000 (87.875) Prec@5 97.000 (99.167) +2022-11-14 15:49:38,833 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0740) Prec@1 92.000 (87.959) Prec@5 100.000 (99.184) +2022-11-14 15:49:38,862 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1047 (0.0746) Prec@1 83.000 (87.860) Prec@5 100.000 (99.200) +2022-11-14 15:49:38,892 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0479 (0.0741) Prec@1 91.000 (87.922) Prec@5 100.000 (99.216) +2022-11-14 15:49:38,918 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0741) Prec@1 85.000 (87.865) Prec@5 100.000 (99.231) +2022-11-14 15:49:38,948 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0740) Prec@1 88.000 (87.868) Prec@5 100.000 (99.245) +2022-11-14 15:49:38,980 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0741) Prec@1 87.000 (87.852) Prec@5 96.000 (99.185) +2022-11-14 15:49:39,010 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0743) Prec@1 87.000 (87.836) Prec@5 99.000 (99.182) +2022-11-14 15:49:39,031 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0741) Prec@1 90.000 (87.875) Prec@5 99.000 (99.179) +2022-11-14 15:49:39,056 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0742) Prec@1 87.000 (87.860) Prec@5 99.000 (99.175) +2022-11-14 15:49:39,080 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0741) Prec@1 91.000 (87.914) Prec@5 99.000 (99.172) +2022-11-14 15:49:39,106 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0745) Prec@1 83.000 (87.831) Prec@5 99.000 (99.169) +2022-11-14 15:49:39,133 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0745) Prec@1 86.000 (87.800) Prec@5 100.000 (99.183) +2022-11-14 15:49:39,161 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0745) Prec@1 89.000 (87.820) Prec@5 100.000 (99.197) +2022-11-14 15:49:39,188 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0745) Prec@1 86.000 (87.790) Prec@5 100.000 (99.210) +2022-11-14 15:49:39,217 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0744) Prec@1 90.000 (87.825) Prec@5 99.000 (99.206) +2022-11-14 15:49:39,245 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0362 (0.0738) Prec@1 93.000 (87.906) Prec@5 100.000 (99.219) +2022-11-14 15:49:39,272 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1000 (0.0742) Prec@1 87.000 (87.892) Prec@5 99.000 (99.215) +2022-11-14 15:49:39,302 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0743) Prec@1 89.000 (87.909) Prec@5 99.000 (99.212) +2022-11-14 15:49:39,330 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0500 (0.0739) Prec@1 92.000 (87.970) Prec@5 100.000 (99.224) +2022-11-14 15:49:39,358 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0935 (0.0742) Prec@1 86.000 (87.941) Prec@5 99.000 (99.221) +2022-11-14 15:49:39,387 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0740) Prec@1 91.000 (87.986) Prec@5 98.000 (99.203) +2022-11-14 15:49:39,415 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0740) Prec@1 86.000 (87.957) Prec@5 100.000 (99.214) +2022-11-14 15:49:39,444 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0742) Prec@1 86.000 (87.930) Prec@5 99.000 (99.211) +2022-11-14 15:49:39,477 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0741) Prec@1 90.000 (87.958) Prec@5 100.000 (99.222) +2022-11-14 15:49:39,507 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0738) Prec@1 93.000 (88.027) Prec@5 100.000 (99.233) +2022-11-14 15:49:39,535 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0470 (0.0734) Prec@1 92.000 (88.081) Prec@5 100.000 (99.243) +2022-11-14 15:49:39,566 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1259 (0.0741) Prec@1 81.000 (87.987) Prec@5 99.000 (99.240) +2022-11-14 15:49:39,595 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0740) Prec@1 91.000 (88.026) Prec@5 100.000 (99.250) +2022-11-14 15:49:39,621 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0742) Prec@1 84.000 (87.974) Prec@5 99.000 (99.247) +2022-11-14 15:49:39,645 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0830 (0.0743) Prec@1 86.000 (87.949) Prec@5 99.000 (99.244) +2022-11-14 15:49:39,673 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0741) Prec@1 89.000 (87.962) Prec@5 100.000 (99.253) +2022-11-14 15:49:39,703 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0742) Prec@1 86.000 (87.938) Prec@5 100.000 (99.263) +2022-11-14 15:49:39,733 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0743) Prec@1 86.000 (87.914) Prec@5 98.000 (99.247) +2022-11-14 15:49:39,760 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0746) Prec@1 83.000 (87.854) Prec@5 100.000 (99.256) +2022-11-14 15:49:39,788 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0902 (0.0748) Prec@1 85.000 (87.819) Prec@5 100.000 (99.265) +2022-11-14 15:49:39,818 Test: [83/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0747) Prec@1 89.000 (87.833) Prec@5 99.000 (99.262) +2022-11-14 15:49:39,849 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0747) Prec@1 90.000 (87.859) Prec@5 99.000 (99.259) +2022-11-14 15:49:39,876 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0990 (0.0749) Prec@1 84.000 (87.814) Prec@5 99.000 (99.256) +2022-11-14 15:49:39,903 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0750) Prec@1 89.000 (87.828) Prec@5 99.000 (99.253) +2022-11-14 15:49:39,931 Test: [87/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0750) Prec@1 89.000 (87.841) Prec@5 99.000 (99.250) +2022-11-14 15:49:39,961 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0500 (0.0747) Prec@1 90.000 (87.865) Prec@5 100.000 (99.258) +2022-11-14 15:49:39,994 Test: [89/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0748) Prec@1 88.000 (87.867) Prec@5 99.000 (99.256) +2022-11-14 15:49:40,023 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0746) Prec@1 91.000 (87.901) Prec@5 100.000 (99.264) +2022-11-14 15:49:40,054 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0517 (0.0744) Prec@1 91.000 (87.935) Prec@5 100.000 (99.272) +2022-11-14 15:49:40,084 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0973 (0.0746) Prec@1 84.000 (87.892) Prec@5 99.000 (99.269) +2022-11-14 15:49:40,111 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0747) Prec@1 86.000 (87.872) Prec@5 98.000 (99.255) +2022-11-14 15:49:40,141 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0747) Prec@1 88.000 (87.874) Prec@5 98.000 (99.242) +2022-11-14 15:49:40,169 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0423 (0.0744) Prec@1 94.000 (87.938) Prec@5 99.000 (99.240) +2022-11-14 15:49:40,195 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0483 (0.0741) Prec@1 91.000 (87.969) Prec@5 98.000 (99.227) +2022-11-14 15:49:40,225 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0741) Prec@1 88.000 (87.969) Prec@5 99.000 (99.224) +2022-11-14 15:49:40,254 Test: [98/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1041 (0.0744) Prec@1 83.000 (87.919) Prec@5 100.000 (99.232) +2022-11-14 15:49:40,279 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0744) Prec@1 87.000 (87.910) Prec@5 99.000 (99.230) +2022-11-14 15:49:40,339 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:49:40,670 Epoch: [268][0/500] Time 0.026 (0.026) Data 0.243 (0.243) Loss 0.0256 (0.0256) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:49:40,924 Epoch: [268][10/500] Time 0.025 (0.023) Data 0.002 (0.024) Loss 0.0241 (0.0249) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:49:41,180 Epoch: [268][20/500] Time 0.025 (0.023) Data 0.002 (0.013) Loss 0.0360 (0.0286) Prec@1 95.000 (95.333) Prec@5 99.000 (99.667) +2022-11-14 15:49:41,437 Epoch: [268][30/500] Time 0.024 (0.023) Data 0.002 (0.010) Loss 0.0345 (0.0301) Prec@1 93.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 15:49:41,858 Epoch: [268][40/500] Time 0.048 (0.026) Data 0.002 (0.008) Loss 0.0179 (0.0276) Prec@1 97.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 15:49:42,291 Epoch: [268][50/500] Time 0.050 (0.029) Data 0.002 (0.007) Loss 0.0315 (0.0283) Prec@1 95.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 15:49:42,742 Epoch: [268][60/500] Time 0.050 (0.030) Data 0.002 (0.006) Loss 0.0275 (0.0282) Prec@1 95.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 15:49:43,255 Epoch: [268][70/500] Time 0.052 (0.032) Data 0.002 (0.005) Loss 0.0366 (0.0292) Prec@1 95.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 15:49:43,720 Epoch: [268][80/500] Time 0.048 (0.034) Data 0.002 (0.005) Loss 0.0116 (0.0273) Prec@1 98.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 15:49:44,194 Epoch: [268][90/500] Time 0.039 (0.035) Data 0.002 (0.005) Loss 0.0387 (0.0284) Prec@1 95.000 (95.400) Prec@5 99.000 (99.800) +2022-11-14 15:49:44,639 Epoch: [268][100/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0291 (0.0285) Prec@1 95.000 (95.364) Prec@5 100.000 (99.818) +2022-11-14 15:49:45,120 Epoch: [268][110/500] Time 0.053 (0.036) Data 0.002 (0.004) Loss 0.0229 (0.0280) Prec@1 97.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 15:49:45,543 Epoch: [268][120/500] Time 0.042 (0.036) Data 0.002 (0.004) Loss 0.0499 (0.0297) Prec@1 91.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 15:49:45,955 Epoch: [268][130/500] Time 0.048 (0.036) Data 0.003 (0.004) Loss 0.0566 (0.0316) Prec@1 90.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 15:49:46,397 Epoch: [268][140/500] Time 0.043 (0.036) Data 0.002 (0.004) Loss 0.0428 (0.0324) Prec@1 93.000 (94.667) Prec@5 99.000 (99.800) +2022-11-14 15:49:46,852 Epoch: [268][150/500] Time 0.048 (0.037) Data 0.002 (0.004) Loss 0.0541 (0.0337) Prec@1 90.000 (94.375) Prec@5 100.000 (99.812) +2022-11-14 15:49:47,324 Epoch: [268][160/500] Time 0.037 (0.037) Data 0.002 (0.004) Loss 0.0250 (0.0332) Prec@1 96.000 (94.471) Prec@5 100.000 (99.824) +2022-11-14 15:49:47,773 Epoch: [268][170/500] Time 0.041 (0.037) Data 0.002 (0.003) Loss 0.0478 (0.0340) Prec@1 92.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 15:49:48,213 Epoch: [268][180/500] Time 0.036 (0.037) Data 0.002 (0.003) Loss 0.0197 (0.0333) Prec@1 96.000 (94.421) Prec@5 100.000 (99.842) +2022-11-14 15:49:48,661 Epoch: [268][190/500] Time 0.046 (0.037) Data 0.002 (0.003) Loss 0.0219 (0.0327) Prec@1 96.000 (94.500) Prec@5 100.000 (99.850) +2022-11-14 15:49:49,102 Epoch: [268][200/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0427 (0.0332) Prec@1 94.000 (94.476) Prec@5 100.000 (99.857) +2022-11-14 15:49:49,523 Epoch: [268][210/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0294 (0.0330) Prec@1 96.000 (94.545) Prec@5 100.000 (99.864) +2022-11-14 15:49:49,959 Epoch: [268][220/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0257 (0.0327) Prec@1 95.000 (94.565) Prec@5 100.000 (99.870) +2022-11-14 15:49:50,396 Epoch: [268][230/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0381 (0.0329) Prec@1 95.000 (94.583) Prec@5 100.000 (99.875) +2022-11-14 15:49:50,829 Epoch: [268][240/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0453 (0.0334) Prec@1 94.000 (94.560) Prec@5 100.000 (99.880) +2022-11-14 15:49:51,276 Epoch: [268][250/500] Time 0.043 (0.038) Data 0.002 (0.003) Loss 0.0641 (0.0346) Prec@1 92.000 (94.462) Prec@5 100.000 (99.885) +2022-11-14 15:49:51,716 Epoch: [268][260/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0291 (0.0344) Prec@1 94.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 15:49:52,159 Epoch: [268][270/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0456 (0.0348) Prec@1 91.000 (94.321) Prec@5 100.000 (99.893) +2022-11-14 15:49:52,607 Epoch: [268][280/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0445 (0.0351) Prec@1 93.000 (94.276) Prec@5 100.000 (99.897) +2022-11-14 15:49:53,059 Epoch: [268][290/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0462 (0.0355) Prec@1 92.000 (94.200) Prec@5 100.000 (99.900) +2022-11-14 15:49:53,493 Epoch: [268][300/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0530 (0.0361) Prec@1 91.000 (94.097) Prec@5 100.000 (99.903) +2022-11-14 15:49:53,969 Epoch: [268][310/500] Time 0.045 (0.038) Data 0.002 (0.003) Loss 0.0417 (0.0362) Prec@1 93.000 (94.062) Prec@5 100.000 (99.906) +2022-11-14 15:49:54,397 Epoch: [268][320/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0499 (0.0366) Prec@1 92.000 (94.000) Prec@5 100.000 (99.909) +2022-11-14 15:49:54,834 Epoch: [268][330/500] Time 0.041 (0.038) Data 0.003 (0.003) Loss 0.0268 (0.0364) Prec@1 95.000 (94.029) Prec@5 100.000 (99.912) +2022-11-14 15:49:55,275 Epoch: [268][340/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0403 (0.0365) Prec@1 94.000 (94.029) Prec@5 100.000 (99.914) +2022-11-14 15:49:55,719 Epoch: [268][350/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0236 (0.0361) Prec@1 98.000 (94.139) Prec@5 99.000 (99.889) +2022-11-14 15:49:56,152 Epoch: [268][360/500] Time 0.039 (0.038) Data 0.002 (0.003) Loss 0.0281 (0.0359) Prec@1 95.000 (94.162) Prec@5 100.000 (99.892) +2022-11-14 15:49:56,587 Epoch: [268][370/500] Time 0.046 (0.038) Data 0.002 (0.003) Loss 0.0516 (0.0363) Prec@1 93.000 (94.132) Prec@5 100.000 (99.895) +2022-11-14 15:49:57,020 Epoch: [268][380/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0279 (0.0361) Prec@1 96.000 (94.179) Prec@5 100.000 (99.897) +2022-11-14 15:49:57,495 Epoch: [268][390/500] Time 0.044 (0.038) Data 0.002 (0.003) Loss 0.0315 (0.0360) Prec@1 96.000 (94.225) Prec@5 100.000 (99.900) +2022-11-14 15:49:57,926 Epoch: [268][400/500] Time 0.034 (0.038) Data 0.002 (0.003) Loss 0.0297 (0.0358) Prec@1 96.000 (94.268) Prec@5 99.000 (99.878) +2022-11-14 15:49:58,400 Epoch: [268][410/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0368 (0.0358) Prec@1 94.000 (94.262) Prec@5 100.000 (99.881) +2022-11-14 15:49:58,871 Epoch: [268][420/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0492 (0.0362) Prec@1 91.000 (94.186) Prec@5 100.000 (99.884) +2022-11-14 15:49:59,307 Epoch: [268][430/500] Time 0.042 (0.039) Data 0.002 (0.003) Loss 0.0218 (0.0358) Prec@1 96.000 (94.227) Prec@5 99.000 (99.864) +2022-11-14 15:49:59,744 Epoch: [268][440/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0390 (0.0359) Prec@1 95.000 (94.244) Prec@5 100.000 (99.867) +2022-11-14 15:50:00,180 Epoch: [268][450/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0412 (0.0360) Prec@1 93.000 (94.217) Prec@5 100.000 (99.870) +2022-11-14 15:50:00,610 Epoch: [268][460/500] Time 0.045 (0.039) Data 0.003 (0.003) Loss 0.0863 (0.0371) Prec@1 85.000 (94.021) Prec@5 99.000 (99.851) +2022-11-14 15:50:01,080 Epoch: [268][470/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0261 (0.0369) Prec@1 95.000 (94.042) Prec@5 100.000 (99.854) +2022-11-14 15:50:01,531 Epoch: [268][480/500] Time 0.045 (0.039) Data 0.002 (0.003) Loss 0.0313 (0.0367) Prec@1 95.000 (94.061) Prec@5 99.000 (99.837) +2022-11-14 15:50:02,053 Epoch: [268][490/500] Time 0.048 (0.039) Data 0.002 (0.003) Loss 0.0535 (0.0371) Prec@1 91.000 (94.000) Prec@5 98.000 (99.800) +2022-11-14 15:50:02,511 Epoch: [268][499/500] Time 0.043 (0.039) Data 0.002 (0.003) Loss 0.0360 (0.0371) Prec@1 95.000 (94.020) Prec@5 100.000 (99.804) +2022-11-14 15:50:02,838 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0820 (0.0820) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:02,848 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0752 (0.0786) Prec@1 89.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:02,859 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0731) Prec@1 89.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 15:50:02,874 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0742) Prec@1 88.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 15:50:02,885 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0737) Prec@1 89.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 15:50:02,896 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0710) Prec@1 91.000 (88.500) Prec@5 100.000 (99.833) +2022-11-14 15:50:02,908 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0698) Prec@1 89.000 (88.571) Prec@5 100.000 (99.857) +2022-11-14 15:50:02,921 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0714) Prec@1 88.000 (88.500) Prec@5 100.000 (99.875) +2022-11-14 15:50:02,932 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0727) Prec@1 85.000 (88.111) Prec@5 100.000 (99.889) +2022-11-14 15:50:02,948 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0731) Prec@1 88.000 (88.100) Prec@5 99.000 (99.800) +2022-11-14 15:50:02,962 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0732) Prec@1 86.000 (87.909) Prec@5 100.000 (99.818) +2022-11-14 15:50:02,975 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0754) Prec@1 85.000 (87.667) Prec@5 99.000 (99.750) +2022-11-14 15:50:02,991 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0355 (0.0723) Prec@1 92.000 (88.000) Prec@5 99.000 (99.692) +2022-11-14 15:50:03,007 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0721) Prec@1 89.000 (88.071) Prec@5 99.000 (99.643) +2022-11-14 15:50:03,024 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0737) Prec@1 84.000 (87.800) Prec@5 100.000 (99.667) +2022-11-14 15:50:03,039 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0739) Prec@1 81.000 (87.375) Prec@5 99.000 (99.625) +2022-11-14 15:50:03,055 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0735) Prec@1 89.000 (87.471) Prec@5 98.000 (99.529) +2022-11-14 15:50:03,072 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0751) Prec@1 84.000 (87.278) Prec@5 100.000 (99.556) +2022-11-14 15:50:03,088 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0754) Prec@1 86.000 (87.211) Prec@5 99.000 (99.526) +2022-11-14 15:50:03,104 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0764) Prec@1 86.000 (87.150) Prec@5 98.000 (99.450) +2022-11-14 15:50:03,121 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0768) Prec@1 86.000 (87.095) Prec@5 100.000 (99.476) +2022-11-14 15:50:03,134 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0762) Prec@1 89.000 (87.182) Prec@5 99.000 (99.455) +2022-11-14 15:50:03,154 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0773) Prec@1 85.000 (87.087) Prec@5 97.000 (99.348) +2022-11-14 15:50:03,170 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0776) Prec@1 87.000 (87.083) Prec@5 100.000 (99.375) +2022-11-14 15:50:03,183 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0778) Prec@1 88.000 (87.120) Prec@5 100.000 (99.400) +2022-11-14 15:50:03,199 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0784) Prec@1 87.000 (87.115) Prec@5 98.000 (99.346) +2022-11-14 15:50:03,215 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0776) Prec@1 91.000 (87.259) Prec@5 100.000 (99.370) +2022-11-14 15:50:03,229 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0766) Prec@1 91.000 (87.393) Prec@5 100.000 (99.393) +2022-11-14 15:50:03,242 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0760) Prec@1 91.000 (87.517) Prec@5 99.000 (99.379) +2022-11-14 15:50:03,258 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0758) Prec@1 89.000 (87.567) Prec@5 100.000 (99.400) +2022-11-14 15:50:03,275 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0755) Prec@1 88.000 (87.581) Prec@5 100.000 (99.419) +2022-11-14 15:50:03,292 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0752) Prec@1 90.000 (87.656) Prec@5 100.000 (99.438) +2022-11-14 15:50:03,307 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0754) Prec@1 86.000 (87.606) Prec@5 100.000 (99.455) +2022-11-14 15:50:03,324 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0762) Prec@1 80.000 (87.382) Prec@5 100.000 (99.471) +2022-11-14 15:50:03,338 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0766) Prec@1 85.000 (87.314) Prec@5 97.000 (99.400) +2022-11-14 15:50:03,352 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0763) Prec@1 92.000 (87.444) Prec@5 99.000 (99.389) +2022-11-14 15:50:03,369 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0766) Prec@1 85.000 (87.378) Prec@5 100.000 (99.405) +2022-11-14 15:50:03,385 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0770) Prec@1 84.000 (87.289) Prec@5 100.000 (99.421) +2022-11-14 15:50:03,400 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0463 (0.0762) Prec@1 94.000 (87.462) Prec@5 99.000 (99.410) +2022-11-14 15:50:03,417 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0760) Prec@1 90.000 (87.525) Prec@5 99.000 (99.400) +2022-11-14 15:50:03,435 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0766) Prec@1 82.000 (87.390) Prec@5 97.000 (99.341) +2022-11-14 15:50:03,454 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0765) Prec@1 90.000 (87.452) Prec@5 100.000 (99.357) +2022-11-14 15:50:03,470 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0759) Prec@1 92.000 (87.558) Prec@5 99.000 (99.349) +2022-11-14 15:50:03,486 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0756) Prec@1 92.000 (87.659) Prec@5 98.000 (99.318) +2022-11-14 15:50:03,502 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0752) Prec@1 91.000 (87.733) Prec@5 100.000 (99.333) +2022-11-14 15:50:03,519 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0756) Prec@1 84.000 (87.652) Prec@5 100.000 (99.348) +2022-11-14 15:50:03,535 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0751) Prec@1 93.000 (87.766) Prec@5 100.000 (99.362) +2022-11-14 15:50:03,550 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0757) Prec@1 83.000 (87.667) Prec@5 98.000 (99.333) +2022-11-14 15:50:03,566 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0756) Prec@1 88.000 (87.673) Prec@5 99.000 (99.327) +2022-11-14 15:50:03,581 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0756) Prec@1 87.000 (87.660) Prec@5 100.000 (99.340) +2022-11-14 15:50:03,595 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0755) Prec@1 89.000 (87.686) Prec@5 100.000 (99.353) +2022-11-14 15:50:03,610 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0755) Prec@1 85.000 (87.635) Prec@5 100.000 (99.365) +2022-11-14 15:50:03,628 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0754) Prec@1 90.000 (87.679) Prec@5 100.000 (99.377) +2022-11-14 15:50:03,645 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0751) Prec@1 90.000 (87.722) Prec@5 99.000 (99.370) +2022-11-14 15:50:03,660 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1147 (0.0758) Prec@1 82.000 (87.618) Prec@5 100.000 (99.382) +2022-11-14 15:50:03,677 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0756) Prec@1 91.000 (87.679) Prec@5 99.000 (99.375) +2022-11-14 15:50:03,691 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0756) Prec@1 87.000 (87.667) Prec@5 99.000 (99.368) +2022-11-14 15:50:03,706 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0754) Prec@1 91.000 (87.724) Prec@5 99.000 (99.362) +2022-11-14 15:50:03,720 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1133 (0.0760) Prec@1 82.000 (87.627) Prec@5 98.000 (99.339) +2022-11-14 15:50:03,738 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0760) Prec@1 86.000 (87.600) Prec@5 99.000 (99.333) +2022-11-14 15:50:03,755 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0760) Prec@1 88.000 (87.607) Prec@5 100.000 (99.344) +2022-11-14 15:50:03,773 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0761) Prec@1 87.000 (87.597) Prec@5 99.000 (99.339) +2022-11-14 15:50:03,788 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0757) Prec@1 92.000 (87.667) Prec@5 100.000 (99.349) +2022-11-14 15:50:03,803 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0285 (0.0750) Prec@1 94.000 (87.766) Prec@5 100.000 (99.359) +2022-11-14 15:50:03,817 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0751) Prec@1 87.000 (87.754) Prec@5 99.000 (99.354) +2022-11-14 15:50:03,831 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0753) Prec@1 83.000 (87.682) Prec@5 98.000 (99.333) +2022-11-14 15:50:03,845 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0438 (0.0748) Prec@1 92.000 (87.746) Prec@5 100.000 (99.343) +2022-11-14 15:50:03,862 Test: 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Loss 0.0537 (0.0742) Prec@1 92.000 (87.932) Prec@5 100.000 (99.392) +2022-11-14 15:50:03,978 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0746) Prec@1 83.000 (87.867) Prec@5 100.000 (99.400) +2022-11-14 15:50:03,995 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0745) Prec@1 90.000 (87.895) Prec@5 99.000 (99.395) +2022-11-14 15:50:04,011 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0746) Prec@1 86.000 (87.870) Prec@5 99.000 (99.390) +2022-11-14 15:50:04,027 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0748) Prec@1 84.000 (87.821) Prec@5 98.000 (99.372) +2022-11-14 15:50:04,043 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0749) Prec@1 87.000 (87.810) Prec@5 100.000 (99.380) +2022-11-14 15:50:04,060 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0746) Prec@1 89.000 (87.825) Prec@5 100.000 (99.388) +2022-11-14 15:50:04,078 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0748) Prec@1 85.000 (87.790) Prec@5 96.000 (99.346) +2022-11-14 15:50:04,095 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0749) Prec@1 86.000 (87.768) Prec@5 100.000 (99.354) +2022-11-14 15:50:04,109 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0748) Prec@1 87.000 (87.759) Prec@5 100.000 (99.361) +2022-11-14 15:50:04,127 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0746) Prec@1 89.000 (87.774) Prec@5 100.000 (99.369) +2022-11-14 15:50:04,143 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0746) Prec@1 88.000 (87.776) Prec@5 99.000 (99.365) +2022-11-14 15:50:04,161 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0750) Prec@1 84.000 (87.733) Prec@5 99.000 (99.360) +2022-11-14 15:50:04,178 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0750) Prec@1 89.000 (87.747) Prec@5 99.000 (99.356) +2022-11-14 15:50:04,197 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0750) Prec@1 87.000 (87.739) Prec@5 99.000 (99.352) +2022-11-14 15:50:04,215 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0751) Prec@1 86.000 (87.719) Prec@5 100.000 (99.360) +2022-11-14 15:50:04,230 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0749) Prec@1 91.000 (87.756) Prec@5 100.000 (99.367) +2022-11-14 15:50:04,247 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0746) Prec@1 92.000 (87.802) Prec@5 100.000 (99.374) +2022-11-14 15:50:04,260 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0745) Prec@1 90.000 (87.826) Prec@5 100.000 (99.380) +2022-11-14 15:50:04,276 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0747) Prec@1 85.000 (87.796) Prec@5 98.000 (99.366) +2022-11-14 15:50:04,292 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0746) Prec@1 89.000 (87.809) Prec@5 100.000 (99.372) +2022-11-14 15:50:04,306 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0746) Prec@1 85.000 (87.779) Prec@5 99.000 (99.368) +2022-11-14 15:50:04,318 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0745) Prec@1 91.000 (87.812) Prec@5 98.000 (99.354) +2022-11-14 15:50:04,336 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0742) Prec@1 95.000 (87.887) Prec@5 99.000 (99.351) +2022-11-14 15:50:04,353 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0743) Prec@1 87.000 (87.878) Prec@5 98.000 (99.337) +2022-11-14 15:50:04,369 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0747) Prec@1 84.000 (87.838) Prec@5 99.000 (99.333) +2022-11-14 15:50:04,384 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0747) Prec@1 88.000 (87.840) Prec@5 100.000 (99.340) +2022-11-14 15:50:04,442 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:50:04,774 Epoch: [269][0/500] Time 0.029 (0.029) Data 0.240 (0.240) Loss 0.0320 (0.0320) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:05,170 Epoch: [269][10/500] Time 0.046 (0.035) Data 0.002 (0.024) Loss 0.0412 (0.0366) Prec@1 94.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 15:50:05,588 Epoch: [269][20/500] Time 0.039 (0.036) Data 0.002 (0.013) Loss 0.0313 (0.0348) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 15:50:06,023 Epoch: [269][30/500] Time 0.039 (0.037) Data 0.002 (0.010) Loss 0.0261 (0.0326) Prec@1 95.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 15:50:06,461 Epoch: [269][40/500] Time 0.042 (0.037) Data 0.002 (0.008) Loss 0.0263 (0.0314) Prec@1 96.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 15:50:06,895 Epoch: [269][50/500] Time 0.036 (0.038) Data 0.002 (0.007) Loss 0.0480 (0.0341) Prec@1 91.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 15:50:07,324 Epoch: [269][60/500] Time 0.043 (0.038) Data 0.002 (0.006) Loss 0.0540 (0.0370) Prec@1 92.000 (93.714) Prec@5 100.000 (99.714) +2022-11-14 15:50:07,750 Epoch: [269][70/500] Time 0.044 (0.038) Data 0.002 (0.005) Loss 0.0218 (0.0351) Prec@1 97.000 (94.125) Prec@5 100.000 (99.750) +2022-11-14 15:50:08,230 Epoch: [269][80/500] Time 0.046 (0.039) Data 0.002 (0.005) Loss 0.0273 (0.0342) Prec@1 96.000 (94.333) Prec@5 100.000 (99.778) +2022-11-14 15:50:08,735 Epoch: [269][90/500] Time 0.053 (0.039) Data 0.002 (0.005) Loss 0.0298 (0.0338) Prec@1 95.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:50:09,166 Epoch: [269][100/500] Time 0.040 (0.039) Data 0.002 (0.004) Loss 0.0257 (0.0330) Prec@1 96.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 15:50:09,617 Epoch: [269][110/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0427 (0.0338) Prec@1 93.000 (94.417) Prec@5 100.000 (99.833) +2022-11-14 15:50:10,059 Epoch: [269][120/500] Time 0.037 (0.039) Data 0.002 (0.004) Loss 0.0315 (0.0337) Prec@1 93.000 (94.308) Prec@5 99.000 (99.769) +2022-11-14 15:50:10,489 Epoch: [269][130/500] Time 0.037 (0.039) Data 0.002 (0.004) Loss 0.0565 (0.0353) Prec@1 90.000 (94.000) Prec@5 100.000 (99.786) +2022-11-14 15:50:10,944 Epoch: [269][140/500] Time 0.042 (0.040) Data 0.002 (0.004) Loss 0.0303 (0.0350) Prec@1 96.000 (94.133) Prec@5 100.000 (99.800) +2022-11-14 15:50:11,383 Epoch: [269][150/500] Time 0.040 (0.039) Data 0.002 (0.004) Loss 0.0323 (0.0348) Prec@1 96.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 15:50:11,837 Epoch: [269][160/500] Time 0.040 (0.040) Data 0.002 (0.004) Loss 0.0596 (0.0363) Prec@1 91.000 (94.059) Prec@5 100.000 (99.765) +2022-11-14 15:50:12,255 Epoch: [269][170/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0252 (0.0356) Prec@1 95.000 (94.111) Prec@5 100.000 (99.778) +2022-11-14 15:50:12,707 Epoch: [269][180/500] Time 0.052 (0.039) Data 0.002 (0.003) Loss 0.0482 (0.0363) Prec@1 94.000 (94.105) Prec@5 100.000 (99.789) +2022-11-14 15:50:13,197 Epoch: [269][190/500] Time 0.054 (0.040) Data 0.002 (0.003) Loss 0.0314 (0.0361) Prec@1 95.000 (94.150) Prec@5 100.000 (99.800) +2022-11-14 15:50:13,707 Epoch: [269][200/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0265 (0.0356) Prec@1 97.000 (94.286) Prec@5 100.000 (99.810) +2022-11-14 15:50:14,151 Epoch: [269][210/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0330 (0.0355) Prec@1 96.000 (94.364) Prec@5 100.000 (99.818) +2022-11-14 15:50:14,649 Epoch: [269][220/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0338 (0.0354) Prec@1 96.000 (94.435) Prec@5 99.000 (99.783) +2022-11-14 15:50:15,167 Epoch: [269][230/500] Time 0.051 (0.040) Data 0.002 (0.003) Loss 0.0188 (0.0347) Prec@1 97.000 (94.542) Prec@5 100.000 (99.792) +2022-11-14 15:50:15,609 Epoch: [269][240/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0515 (0.0354) Prec@1 92.000 (94.440) Prec@5 100.000 (99.800) +2022-11-14 15:50:16,057 Epoch: [269][250/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0218 (0.0349) Prec@1 98.000 (94.577) Prec@5 100.000 (99.808) +2022-11-14 15:50:16,547 Epoch: [269][260/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0626 (0.0359) Prec@1 89.000 (94.370) Prec@5 100.000 (99.815) +2022-11-14 15:50:17,073 Epoch: [269][270/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0262 (0.0355) Prec@1 96.000 (94.429) Prec@5 100.000 (99.821) +2022-11-14 15:50:17,581 Epoch: [269][280/500] Time 0.051 (0.041) Data 0.002 (0.003) Loss 0.0251 (0.0352) Prec@1 95.000 (94.448) Prec@5 100.000 (99.828) +2022-11-14 15:50:18,203 Epoch: [269][290/500] Time 0.078 (0.041) Data 0.002 (0.003) Loss 0.0314 (0.0351) Prec@1 94.000 (94.433) Prec@5 100.000 (99.833) +2022-11-14 15:50:18,980 Epoch: [269][300/500] Time 0.091 (0.042) Data 0.002 (0.003) Loss 0.0389 (0.0352) Prec@1 94.000 (94.419) Prec@5 100.000 (99.839) +2022-11-14 15:50:19,781 Epoch: [269][310/500] Time 0.073 (0.043) Data 0.002 (0.003) Loss 0.0117 (0.0344) Prec@1 98.000 (94.531) Prec@5 100.000 (99.844) +2022-11-14 15:50:20,627 Epoch: [269][320/500] Time 0.092 (0.044) Data 0.002 (0.003) Loss 0.0283 (0.0343) Prec@1 96.000 (94.576) Prec@5 100.000 (99.848) +2022-11-14 15:50:21,426 Epoch: [269][330/500] Time 0.078 (0.045) Data 0.002 (0.003) Loss 0.0452 (0.0346) Prec@1 94.000 (94.559) Prec@5 99.000 (99.824) +2022-11-14 15:50:22,213 Epoch: [269][340/500] Time 0.081 (0.046) Data 0.002 (0.003) Loss 0.0236 (0.0343) Prec@1 98.000 (94.657) Prec@5 100.000 (99.829) +2022-11-14 15:50:23,025 Epoch: [269][350/500] Time 0.066 (0.047) Data 0.002 (0.003) Loss 0.0287 (0.0341) Prec@1 96.000 (94.694) Prec@5 100.000 (99.833) +2022-11-14 15:50:23,826 Epoch: [269][360/500] Time 0.084 (0.047) Data 0.002 (0.003) Loss 0.0215 (0.0338) Prec@1 95.000 (94.703) Prec@5 100.000 (99.838) +2022-11-14 15:50:24,636 Epoch: [269][370/500] Time 0.111 (0.048) Data 0.002 (0.003) Loss 0.0461 (0.0341) Prec@1 91.000 (94.605) Prec@5 100.000 (99.842) +2022-11-14 15:50:25,516 Epoch: [269][380/500] Time 0.075 (0.049) Data 0.002 (0.003) Loss 0.0484 (0.0345) Prec@1 91.000 (94.513) Prec@5 100.000 (99.846) +2022-11-14 15:50:25,935 Epoch: [269][390/500] Time 0.033 (0.049) Data 0.002 (0.003) Loss 0.0483 (0.0348) Prec@1 92.000 (94.450) Prec@5 99.000 (99.825) +2022-11-14 15:50:26,332 Epoch: [269][400/500] Time 0.036 (0.048) Data 0.002 (0.003) Loss 0.0249 (0.0346) Prec@1 97.000 (94.512) Prec@5 100.000 (99.829) +2022-11-14 15:50:26,732 Epoch: [269][410/500] Time 0.039 (0.048) Data 0.002 (0.003) Loss 0.0224 (0.0343) Prec@1 98.000 (94.595) Prec@5 100.000 (99.833) +2022-11-14 15:50:27,158 Epoch: [269][420/500] Time 0.037 (0.048) Data 0.002 (0.003) Loss 0.0451 (0.0345) Prec@1 93.000 (94.558) Prec@5 100.000 (99.837) +2022-11-14 15:50:27,568 Epoch: [269][430/500] Time 0.034 (0.047) Data 0.002 (0.003) Loss 0.0227 (0.0343) Prec@1 96.000 (94.591) Prec@5 100.000 (99.841) +2022-11-14 15:50:27,986 Epoch: [269][440/500] Time 0.033 (0.047) Data 0.002 (0.003) Loss 0.0237 (0.0340) Prec@1 96.000 (94.622) Prec@5 100.000 (99.844) +2022-11-14 15:50:28,414 Epoch: [269][450/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0405 (0.0342) Prec@1 93.000 (94.587) Prec@5 100.000 (99.848) +2022-11-14 15:50:28,825 Epoch: [269][460/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0280 (0.0340) Prec@1 95.000 (94.596) Prec@5 100.000 (99.851) +2022-11-14 15:50:29,224 Epoch: [269][470/500] Time 0.038 (0.047) Data 0.002 (0.003) Loss 0.0555 (0.0345) Prec@1 89.000 (94.479) Prec@5 98.000 (99.812) +2022-11-14 15:50:29,626 Epoch: [269][480/500] Time 0.031 (0.046) Data 0.002 (0.003) Loss 0.0536 (0.0349) Prec@1 91.000 (94.408) Prec@5 99.000 (99.796) +2022-11-14 15:50:30,092 Epoch: [269][490/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0343 (0.0349) Prec@1 95.000 (94.420) Prec@5 100.000 (99.800) +2022-11-14 15:50:30,467 Epoch: [269][499/500] Time 0.041 (0.046) Data 0.002 (0.003) Loss 0.0367 (0.0349) Prec@1 95.000 (94.431) Prec@5 100.000 (99.804) +2022-11-14 15:50:30,789 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0716 (0.0716) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:30,799 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0619 (0.0668) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 15:50:30,809 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0656) Prec@1 92.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 15:50:30,826 Test: [3/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0873 (0.0710) Prec@1 86.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 15:50:30,839 Test: [4/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0706 (0.0709) Prec@1 89.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 15:50:30,851 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0476 (0.0670) Prec@1 91.000 (89.500) Prec@5 99.000 (99.667) +2022-11-14 15:50:30,860 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0705 (0.0675) Prec@1 90.000 (89.571) Prec@5 100.000 (99.714) +2022-11-14 15:50:30,875 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0686) Prec@1 89.000 (89.500) Prec@5 100.000 (99.750) +2022-11-14 15:50:30,886 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0694) Prec@1 87.000 (89.222) Prec@5 100.000 (99.778) +2022-11-14 15:50:30,897 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0693) Prec@1 88.000 (89.100) Prec@5 99.000 (99.700) +2022-11-14 15:50:30,907 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0681) Prec@1 90.000 (89.182) Prec@5 100.000 (99.727) +2022-11-14 15:50:30,917 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0679) Prec@1 91.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 15:50:30,928 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0625 (0.0675) Prec@1 88.000 (89.231) Prec@5 100.000 (99.692) +2022-11-14 15:50:30,939 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0684) Prec@1 88.000 (89.143) Prec@5 99.000 (99.643) +2022-11-14 15:50:30,951 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0957 (0.0702) Prec@1 84.000 (88.800) Prec@5 100.000 (99.667) +2022-11-14 15:50:30,962 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0705) Prec@1 87.000 (88.688) Prec@5 100.000 (99.688) +2022-11-14 15:50:30,973 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0622 (0.0700) Prec@1 88.000 (88.647) Prec@5 99.000 (99.647) +2022-11-14 15:50:30,984 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1024 (0.0718) Prec@1 85.000 (88.444) Prec@5 100.000 (99.667) +2022-11-14 15:50:30,994 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0722) Prec@1 87.000 (88.368) Prec@5 97.000 (99.526) +2022-11-14 15:50:31,006 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0723) Prec@1 87.000 (88.300) Prec@5 100.000 (99.550) +2022-11-14 15:50:31,018 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0726) Prec@1 88.000 (88.286) Prec@5 100.000 (99.571) +2022-11-14 15:50:31,029 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0725) Prec@1 88.000 (88.273) Prec@5 98.000 (99.500) +2022-11-14 15:50:31,042 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0729) Prec@1 88.000 (88.261) Prec@5 98.000 (99.435) +2022-11-14 15:50:31,053 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0737) Prec@1 86.000 (88.167) Prec@5 100.000 (99.458) +2022-11-14 15:50:31,063 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0746) Prec@1 87.000 (88.120) Prec@5 99.000 (99.440) +2022-11-14 15:50:31,074 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0749) Prec@1 89.000 (88.154) Prec@5 97.000 (99.346) +2022-11-14 15:50:31,085 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0739) Prec@1 93.000 (88.333) Prec@5 100.000 (99.370) +2022-11-14 15:50:31,096 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0739) Prec@1 87.000 (88.286) Prec@5 100.000 (99.393) +2022-11-14 15:50:31,107 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0738) Prec@1 88.000 (88.276) Prec@5 99.000 (99.379) +2022-11-14 15:50:31,118 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0736) Prec@1 89.000 (88.300) Prec@5 99.000 (99.367) +2022-11-14 15:50:31,130 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0739) Prec@1 86.000 (88.226) Prec@5 100.000 (99.387) +2022-11-14 15:50:31,141 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0739) Prec@1 87.000 (88.188) Prec@5 98.000 (99.344) +2022-11-14 15:50:31,152 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0736) Prec@1 89.000 (88.212) Prec@5 100.000 (99.364) +2022-11-14 15:50:31,163 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0742) Prec@1 82.000 (88.029) Prec@5 100.000 (99.382) +2022-11-14 15:50:31,174 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0744) Prec@1 89.000 (88.057) Prec@5 100.000 (99.400) +2022-11-14 15:50:31,186 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0743) Prec@1 89.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 15:50:31,197 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0741) Prec@1 88.000 (88.081) Prec@5 99.000 (99.405) +2022-11-14 15:50:31,209 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0745) Prec@1 86.000 (88.026) Prec@5 99.000 (99.395) +2022-11-14 15:50:31,223 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0528 (0.0740) Prec@1 93.000 (88.154) Prec@5 99.000 (99.385) +2022-11-14 15:50:31,236 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0738) Prec@1 87.000 (88.125) Prec@5 99.000 (99.375) +2022-11-14 15:50:31,250 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0741) Prec@1 86.000 (88.073) Prec@5 100.000 (99.390) +2022-11-14 15:50:31,262 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0738) Prec@1 90.000 (88.119) Prec@5 99.000 (99.381) +2022-11-14 15:50:31,276 Test: [42/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0731) Prec@1 93.000 (88.233) Prec@5 99.000 (99.372) +2022-11-14 15:50:31,291 Test: [43/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0734) Prec@1 86.000 (88.182) Prec@5 99.000 (99.364) +2022-11-14 15:50:31,303 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0729) Prec@1 92.000 (88.267) Prec@5 99.000 (99.356) +2022-11-14 15:50:31,318 Test: [45/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0734) Prec@1 84.000 (88.174) Prec@5 99.000 (99.348) +2022-11-14 15:50:31,332 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0733) Prec@1 89.000 (88.191) Prec@5 99.000 (99.340) +2022-11-14 15:50:31,349 Test: [47/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0992 (0.0739) Prec@1 83.000 (88.083) Prec@5 100.000 (99.354) +2022-11-14 15:50:31,361 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0735) Prec@1 91.000 (88.143) Prec@5 100.000 (99.367) +2022-11-14 15:50:31,372 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1019 (0.0741) Prec@1 84.000 (88.060) Prec@5 99.000 (99.360) +2022-11-14 15:50:31,385 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0453 (0.0735) Prec@1 93.000 (88.157) Prec@5 100.000 (99.373) +2022-11-14 15:50:31,398 Test: [51/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0636 (0.0733) Prec@1 89.000 (88.173) Prec@5 100.000 (99.385) +2022-11-14 15:50:31,410 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0735) Prec@1 88.000 (88.170) Prec@5 100.000 (99.396) +2022-11-14 15:50:31,422 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0732) Prec@1 91.000 (88.222) Prec@5 100.000 (99.407) +2022-11-14 15:50:31,433 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0964 (0.0736) Prec@1 82.000 (88.109) Prec@5 100.000 (99.418) +2022-11-14 15:50:31,445 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0736) Prec@1 87.000 (88.089) Prec@5 99.000 (99.411) +2022-11-14 15:50:31,459 Test: [56/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0738) Prec@1 87.000 (88.070) Prec@5 100.000 (99.421) +2022-11-14 15:50:31,473 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0737) Prec@1 89.000 (88.086) Prec@5 100.000 (99.431) +2022-11-14 15:50:31,486 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1075 (0.0743) Prec@1 82.000 (87.983) Prec@5 100.000 (99.441) +2022-11-14 15:50:31,498 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0742) Prec@1 86.000 (87.950) Prec@5 100.000 (99.450) +2022-11-14 15:50:31,510 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0741) Prec@1 89.000 (87.967) Prec@5 100.000 (99.459) +2022-11-14 15:50:31,521 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0741) Prec@1 88.000 (87.968) Prec@5 100.000 (99.468) +2022-11-14 15:50:31,533 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0742) Prec@1 87.000 (87.952) Prec@5 99.000 (99.460) +2022-11-14 15:50:31,544 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0737) Prec@1 92.000 (88.016) Prec@5 99.000 (99.453) +2022-11-14 15:50:31,555 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0738) Prec@1 89.000 (88.031) Prec@5 98.000 (99.431) +2022-11-14 15:50:31,570 Test: [65/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0738) Prec@1 87.000 (88.015) Prec@5 99.000 (99.424) +2022-11-14 15:50:31,584 Test: [66/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0372 (0.0732) Prec@1 94.000 (88.104) Prec@5 100.000 (99.433) +2022-11-14 15:50:31,597 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0735) Prec@1 86.000 (88.074) Prec@5 99.000 (99.426) +2022-11-14 15:50:31,610 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0735) Prec@1 88.000 (88.072) Prec@5 99.000 (99.420) +2022-11-14 15:50:31,621 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0736) Prec@1 90.000 (88.100) Prec@5 98.000 (99.400) +2022-11-14 15:50:31,634 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0738) Prec@1 87.000 (88.085) Prec@5 100.000 (99.408) +2022-11-14 15:50:31,646 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0499 (0.0735) Prec@1 93.000 (88.153) Prec@5 99.000 (99.403) +2022-11-14 15:50:31,659 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0731) Prec@1 94.000 (88.233) Prec@5 100.000 (99.411) +2022-11-14 15:50:31,670 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0456 (0.0727) Prec@1 92.000 (88.284) Prec@5 100.000 (99.419) +2022-11-14 15:50:31,682 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0728) Prec@1 86.000 (88.253) Prec@5 100.000 (99.427) +2022-11-14 15:50:31,694 Test: [75/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0729) Prec@1 90.000 (88.276) Prec@5 99.000 (99.421) +2022-11-14 15:50:31,707 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0729) Prec@1 89.000 (88.286) Prec@5 98.000 (99.403) +2022-11-14 15:50:31,721 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0730) Prec@1 86.000 (88.256) Prec@5 98.000 (99.385) +2022-11-14 15:50:31,734 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0731) Prec@1 87.000 (88.241) Prec@5 100.000 (99.392) +2022-11-14 15:50:31,745 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0731) Prec@1 90.000 (88.263) Prec@5 99.000 (99.388) +2022-11-14 15:50:31,757 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0731) Prec@1 87.000 (88.247) Prec@5 98.000 (99.370) +2022-11-14 15:50:31,770 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0730) Prec@1 87.000 (88.232) Prec@5 100.000 (99.378) +2022-11-14 15:50:31,781 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0731) Prec@1 86.000 (88.205) Prec@5 100.000 (99.386) +2022-11-14 15:50:31,793 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0731) Prec@1 88.000 (88.202) Prec@5 99.000 (99.381) +2022-11-14 15:50:31,806 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0733) Prec@1 87.000 (88.188) Prec@5 99.000 (99.376) +2022-11-14 15:50:31,818 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1032 (0.0736) Prec@1 85.000 (88.151) Prec@5 99.000 (99.372) +2022-11-14 15:50:31,829 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0738) Prec@1 86.000 (88.126) Prec@5 99.000 (99.368) +2022-11-14 15:50:31,840 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0760 (0.0738) Prec@1 87.000 (88.114) Prec@5 98.000 (99.352) +2022-11-14 15:50:31,855 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0737) Prec@1 88.000 (88.112) Prec@5 100.000 (99.360) +2022-11-14 15:50:31,871 Test: [89/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0738) Prec@1 89.000 (88.122) Prec@5 100.000 (99.367) +2022-11-14 15:50:31,888 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0491 (0.0735) Prec@1 91.000 (88.154) Prec@5 100.000 (99.374) +2022-11-14 15:50:31,908 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0734) Prec@1 90.000 (88.174) Prec@5 99.000 (99.370) +2022-11-14 15:50:31,926 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0736) Prec@1 85.000 (88.140) Prec@5 100.000 (99.376) +2022-11-14 15:50:31,947 Test: [93/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0736) Prec@1 87.000 (88.128) Prec@5 100.000 (99.383) +2022-11-14 15:50:31,967 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0737) Prec@1 87.000 (88.116) Prec@5 99.000 (99.379) +2022-11-14 15:50:31,991 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0736) Prec@1 88.000 (88.115) Prec@5 99.000 (99.375) +2022-11-14 15:50:32,018 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0469 (0.0733) Prec@1 93.000 (88.165) Prec@5 99.000 (99.371) +2022-11-14 15:50:32,039 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0788 (0.0733) Prec@1 86.000 (88.143) Prec@5 98.000 (99.357) +2022-11-14 15:50:32,067 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1192 (0.0738) Prec@1 81.000 (88.071) Prec@5 99.000 (99.354) +2022-11-14 15:50:32,095 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0738) Prec@1 90.000 (88.090) Prec@5 100.000 (99.360) +2022-11-14 15:50:32,168 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:50:32,542 Epoch: [270][0/500] Time 0.025 (0.025) Data 0.282 (0.282) Loss 0.0278 (0.0278) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:32,867 Epoch: [270][10/500] Time 0.031 (0.028) Data 0.002 (0.027) Loss 0.0108 (0.0193) Prec@1 98.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:33,225 Epoch: [270][20/500] Time 0.031 (0.030) Data 0.002 (0.015) Loss 0.0227 (0.0204) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:33,583 Epoch: [270][30/500] Time 0.035 (0.031) Data 0.002 (0.011) Loss 0.0484 (0.0274) Prec@1 91.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 15:50:33,937 Epoch: [270][40/500] Time 0.033 (0.031) Data 0.002 (0.009) Loss 0.0379 (0.0295) Prec@1 94.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 15:50:34,296 Epoch: [270][50/500] Time 0.037 (0.031) Data 0.002 (0.008) Loss 0.0258 (0.0289) Prec@1 95.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 15:50:34,708 Epoch: [270][60/500] Time 0.040 (0.032) Data 0.002 (0.007) Loss 0.0392 (0.0304) Prec@1 92.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 15:50:35,120 Epoch: [270][70/500] Time 0.037 (0.032) Data 0.003 (0.006) Loss 0.0481 (0.0326) Prec@1 91.000 (94.250) Prec@5 100.000 (99.875) +2022-11-14 15:50:35,533 Epoch: [270][80/500] Time 0.036 (0.033) Data 0.002 (0.006) Loss 0.0456 (0.0340) Prec@1 93.000 (94.111) Prec@5 98.000 (99.667) +2022-11-14 15:50:35,942 Epoch: [270][90/500] Time 0.034 (0.033) Data 0.002 (0.005) Loss 0.0440 (0.0350) Prec@1 91.000 (93.800) Prec@5 100.000 (99.700) +2022-11-14 15:50:36,767 Epoch: [270][100/500] Time 0.076 (0.038) Data 0.002 (0.005) Loss 0.0248 (0.0341) Prec@1 96.000 (94.000) Prec@5 100.000 (99.727) +2022-11-14 15:50:37,524 Epoch: [270][110/500] Time 0.076 (0.040) Data 0.002 (0.005) Loss 0.0181 (0.0328) Prec@1 97.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 15:50:38,308 Epoch: [270][120/500] Time 0.077 (0.043) Data 0.002 (0.004) Loss 0.0252 (0.0322) Prec@1 97.000 (94.462) Prec@5 100.000 (99.769) +2022-11-14 15:50:39,321 Epoch: [270][130/500] Time 0.106 (0.046) Data 0.002 (0.004) Loss 0.0507 (0.0335) Prec@1 91.000 (94.214) Prec@5 99.000 (99.714) +2022-11-14 15:50:40,189 Epoch: [270][140/500] Time 0.089 (0.049) Data 0.002 (0.004) Loss 0.0173 (0.0324) Prec@1 98.000 (94.467) Prec@5 100.000 (99.733) +2022-11-14 15:50:40,707 Epoch: [270][150/500] Time 0.038 (0.049) Data 0.002 (0.004) Loss 0.0599 (0.0341) Prec@1 90.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 15:50:41,117 Epoch: [270][160/500] Time 0.040 (0.048) Data 0.002 (0.004) Loss 0.0215 (0.0334) Prec@1 96.000 (94.294) Prec@5 100.000 (99.765) +2022-11-14 15:50:41,550 Epoch: [270][170/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0301 (0.0332) Prec@1 95.000 (94.333) Prec@5 100.000 (99.778) +2022-11-14 15:50:42,018 Epoch: [270][180/500] Time 0.049 (0.047) Data 0.002 (0.004) Loss 0.0523 (0.0342) Prec@1 92.000 (94.211) Prec@5 100.000 (99.789) +2022-11-14 15:50:42,448 Epoch: [270][190/500] Time 0.032 (0.047) Data 0.002 (0.004) Loss 0.0337 (0.0342) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 15:50:42,927 Epoch: [270][200/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0539 (0.0351) Prec@1 92.000 (94.095) Prec@5 100.000 (99.810) +2022-11-14 15:50:43,378 Epoch: [270][210/500] Time 0.032 (0.046) Data 0.002 (0.003) Loss 0.0374 (0.0352) Prec@1 94.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 15:50:43,793 Epoch: [270][220/500] Time 0.040 (0.046) Data 0.002 (0.003) Loss 0.0264 (0.0348) Prec@1 97.000 (94.217) Prec@5 100.000 (99.826) +2022-11-14 15:50:44,194 Epoch: [270][230/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0481 (0.0354) Prec@1 91.000 (94.083) Prec@5 100.000 (99.833) +2022-11-14 15:50:44,656 Epoch: [270][240/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0514 (0.0360) Prec@1 91.000 (93.960) Prec@5 100.000 (99.840) +2022-11-14 15:50:45,099 Epoch: [270][250/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0334 (0.0359) Prec@1 96.000 (94.038) Prec@5 100.000 (99.846) +2022-11-14 15:50:45,555 Epoch: [270][260/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0402 (0.0361) Prec@1 92.000 (93.963) Prec@5 100.000 (99.852) +2022-11-14 15:50:46,021 Epoch: [270][270/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0504 (0.0366) Prec@1 92.000 (93.893) Prec@5 99.000 (99.821) +2022-11-14 15:50:46,524 Epoch: [270][280/500] Time 0.046 (0.045) Data 0.003 (0.003) Loss 0.0595 (0.0374) Prec@1 88.000 (93.690) Prec@5 100.000 (99.828) +2022-11-14 15:50:47,006 Epoch: [270][290/500] Time 0.048 (0.045) Data 0.003 (0.003) Loss 0.0240 (0.0369) Prec@1 96.000 (93.767) Prec@5 100.000 (99.833) +2022-11-14 15:50:47,476 Epoch: [270][300/500] Time 0.045 (0.045) Data 0.003 (0.003) Loss 0.0330 (0.0368) Prec@1 95.000 (93.806) Prec@5 100.000 (99.839) +2022-11-14 15:50:47,909 Epoch: [270][310/500] Time 0.029 (0.044) Data 0.002 (0.003) Loss 0.0350 (0.0368) Prec@1 94.000 (93.812) Prec@5 99.000 (99.812) +2022-11-14 15:50:48,365 Epoch: [270][320/500] Time 0.034 (0.044) Data 0.002 (0.003) Loss 0.0399 (0.0369) Prec@1 93.000 (93.788) Prec@5 99.000 (99.788) +2022-11-14 15:50:48,833 Epoch: [270][330/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0339 (0.0368) Prec@1 94.000 (93.794) Prec@5 100.000 (99.794) +2022-11-14 15:50:49,286 Epoch: [270][340/500] Time 0.033 (0.044) Data 0.002 (0.003) Loss 0.0108 (0.0360) Prec@1 99.000 (93.943) Prec@5 100.000 (99.800) +2022-11-14 15:50:49,701 Epoch: [270][350/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0128 (0.0354) Prec@1 98.000 (94.056) Prec@5 100.000 (99.806) +2022-11-14 15:50:50,149 Epoch: [270][360/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0320 (0.0353) Prec@1 94.000 (94.054) Prec@5 100.000 (99.811) +2022-11-14 15:50:50,550 Epoch: [270][370/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0143 (0.0347) Prec@1 98.000 (94.158) Prec@5 100.000 (99.816) +2022-11-14 15:50:50,962 Epoch: [270][380/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0663 (0.0355) Prec@1 89.000 (94.026) Prec@5 100.000 (99.821) +2022-11-14 15:50:51,369 Epoch: [270][390/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0392 (0.0356) Prec@1 94.000 (94.025) Prec@5 100.000 (99.825) +2022-11-14 15:50:51,834 Epoch: [270][400/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0292 (0.0355) Prec@1 94.000 (94.024) Prec@5 100.000 (99.829) +2022-11-14 15:50:52,321 Epoch: [270][410/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0169 (0.0350) Prec@1 98.000 (94.119) Prec@5 100.000 (99.833) +2022-11-14 15:50:52,819 Epoch: [270][420/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0328 (0.0350) Prec@1 95.000 (94.140) Prec@5 100.000 (99.837) +2022-11-14 15:50:53,383 Epoch: [270][430/500] Time 0.079 (0.043) Data 0.002 (0.003) Loss 0.0312 (0.0349) Prec@1 95.000 (94.159) Prec@5 100.000 (99.841) +2022-11-14 15:50:54,506 Epoch: [270][440/500] Time 0.079 (0.045) Data 0.002 (0.003) Loss 0.0430 (0.0351) Prec@1 92.000 (94.111) Prec@5 99.000 (99.822) +2022-11-14 15:50:55,454 Epoch: [270][450/500] Time 0.077 (0.045) Data 0.003 (0.003) Loss 0.0194 (0.0347) Prec@1 98.000 (94.196) Prec@5 100.000 (99.826) +2022-11-14 15:50:56,216 Epoch: [270][460/500] Time 0.066 (0.046) Data 0.002 (0.003) Loss 0.0329 (0.0347) Prec@1 95.000 (94.213) Prec@5 100.000 (99.830) +2022-11-14 15:50:56,980 Epoch: [270][470/500] Time 0.072 (0.046) Data 0.002 (0.003) Loss 0.0286 (0.0346) Prec@1 95.000 (94.229) Prec@5 100.000 (99.833) +2022-11-14 15:50:57,752 Epoch: [270][480/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0408 (0.0347) Prec@1 93.000 (94.204) Prec@5 100.000 (99.837) +2022-11-14 15:50:58,563 Epoch: [270][490/500] Time 0.078 (0.047) Data 0.002 (0.003) Loss 0.0542 (0.0351) Prec@1 91.000 (94.140) Prec@5 100.000 (99.840) +2022-11-14 15:50:59,222 Epoch: [270][499/500] Time 0.072 (0.048) Data 0.002 (0.003) Loss 0.0232 (0.0349) Prec@1 97.000 (94.196) Prec@5 100.000 (99.843) +2022-11-14 15:50:59,561 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0640 (0.0640) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:50:59,573 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0830 (0.0735) Prec@1 87.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 15:50:59,588 Test: [2/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0730 (0.0734) Prec@1 88.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 15:50:59,603 Test: [3/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0824 (0.0756) Prec@1 85.000 (86.750) Prec@5 100.000 (99.750) +2022-11-14 15:50:59,616 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0633 (0.0732) Prec@1 90.000 (87.400) Prec@5 100.000 (99.800) +2022-11-14 15:50:59,629 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0481 (0.0690) Prec@1 91.000 (88.000) Prec@5 100.000 (99.833) +2022-11-14 15:50:59,643 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0571 (0.0673) Prec@1 92.000 (88.571) Prec@5 100.000 (99.857) +2022-11-14 15:50:59,660 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0874 (0.0698) Prec@1 83.000 (87.875) Prec@5 100.000 (99.875) +2022-11-14 15:50:59,674 Test: [8/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0620 (0.0689) Prec@1 91.000 (88.222) Prec@5 99.000 (99.778) +2022-11-14 15:50:59,688 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0726 (0.0693) Prec@1 89.000 (88.300) Prec@5 99.000 (99.700) +2022-11-14 15:50:59,702 Test: [10/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0408 (0.0667) Prec@1 92.000 (88.636) Prec@5 100.000 (99.727) +2022-11-14 15:50:59,716 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0812 (0.0679) Prec@1 87.000 (88.500) Prec@5 99.000 (99.667) +2022-11-14 15:50:59,729 Test: [12/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0642 (0.0676) Prec@1 90.000 (88.615) Prec@5 100.000 (99.692) +2022-11-14 15:50:59,744 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0659 (0.0675) Prec@1 92.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 15:50:59,759 Test: [14/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0699 (0.0677) Prec@1 88.000 (88.800) Prec@5 99.000 (99.667) +2022-11-14 15:50:59,770 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0599 (0.0672) Prec@1 91.000 (88.938) Prec@5 99.000 (99.625) +2022-11-14 15:50:59,784 Test: [16/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0445 (0.0658) Prec@1 95.000 (89.294) Prec@5 99.000 (99.588) +2022-11-14 15:50:59,798 Test: [17/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0904 (0.0672) Prec@1 85.000 (89.056) Prec@5 100.000 (99.611) +2022-11-14 15:50:59,812 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0855 (0.0682) Prec@1 85.000 (88.842) Prec@5 99.000 (99.579) +2022-11-14 15:50:59,828 Test: [19/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0872 (0.0691) Prec@1 86.000 (88.700) Prec@5 97.000 (99.450) +2022-11-14 15:50:59,841 Test: [20/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0874 (0.0700) Prec@1 87.000 (88.619) Prec@5 99.000 (99.429) +2022-11-14 15:50:59,854 Test: [21/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0938 (0.0711) Prec@1 85.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 15:50:59,869 Test: [22/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1091 (0.0727) Prec@1 85.000 (88.304) Prec@5 97.000 (99.348) +2022-11-14 15:50:59,883 Test: [23/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0864 (0.0733) Prec@1 85.000 (88.167) Prec@5 100.000 (99.375) +2022-11-14 15:50:59,895 Test: [24/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0742 (0.0733) Prec@1 88.000 (88.160) Prec@5 99.000 (99.360) +2022-11-14 15:50:59,906 Test: [25/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0981 (0.0743) Prec@1 85.000 (88.038) Prec@5 99.000 (99.346) +2022-11-14 15:50:59,916 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0588 (0.0737) Prec@1 93.000 (88.222) Prec@5 100.000 (99.370) +2022-11-14 15:50:59,927 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0604 (0.0732) Prec@1 90.000 (88.286) Prec@5 100.000 (99.393) +2022-11-14 15:50:59,937 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0627 (0.0729) Prec@1 88.000 (88.276) Prec@5 99.000 (99.379) +2022-11-14 15:50:59,947 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0728) Prec@1 89.000 (88.300) Prec@5 100.000 (99.400) +2022-11-14 15:50:59,957 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0731) Prec@1 86.000 (88.226) Prec@5 100.000 (99.419) +2022-11-14 15:50:59,967 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0730) Prec@1 90.000 (88.281) Prec@5 99.000 (99.406) +2022-11-14 15:50:59,978 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0733) Prec@1 86.000 (88.212) Prec@5 100.000 (99.424) +2022-11-14 15:50:59,990 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.0737) Prec@1 88.000 (88.206) Prec@5 99.000 (99.412) +2022-11-14 15:51:00,000 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0740) Prec@1 84.000 (88.086) Prec@5 99.000 (99.400) +2022-11-14 15:51:00,011 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0744) Prec@1 87.000 (88.056) Prec@5 100.000 (99.417) +2022-11-14 15:51:00,022 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0744) Prec@1 89.000 (88.081) Prec@5 98.000 (99.378) +2022-11-14 15:51:00,033 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0747) Prec@1 87.000 (88.053) Prec@5 100.000 (99.395) +2022-11-14 15:51:00,044 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0743) Prec@1 89.000 (88.077) Prec@5 99.000 (99.385) +2022-11-14 15:51:00,054 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0864 (0.0746) Prec@1 84.000 (87.975) Prec@5 98.000 (99.350) +2022-11-14 15:51:00,065 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0991 (0.0752) Prec@1 86.000 (87.927) Prec@5 98.000 (99.317) +2022-11-14 15:51:00,075 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0749) Prec@1 89.000 (87.952) Prec@5 100.000 (99.333) +2022-11-14 15:51:00,087 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0471 (0.0742) Prec@1 91.000 (88.023) Prec@5 100.000 (99.349) +2022-11-14 15:51:00,098 Test: [43/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0741) Prec@1 91.000 (88.091) Prec@5 99.000 (99.341) +2022-11-14 15:51:00,108 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0740) Prec@1 91.000 (88.156) Prec@5 100.000 (99.356) +2022-11-14 15:51:00,118 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0744) Prec@1 86.000 (88.109) Prec@5 98.000 (99.326) +2022-11-14 15:51:00,131 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0744) Prec@1 85.000 (88.043) Prec@5 100.000 (99.340) +2022-11-14 15:51:00,141 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1224 (0.0754) Prec@1 81.000 (87.896) Prec@5 98.000 (99.312) +2022-11-14 15:51:00,151 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0750) Prec@1 90.000 (87.939) Prec@5 100.000 (99.327) +2022-11-14 15:51:00,161 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0952 (0.0754) Prec@1 85.000 (87.880) Prec@5 99.000 (99.320) +2022-11-14 15:51:00,172 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0751) Prec@1 90.000 (87.922) Prec@5 99.000 (99.314) +2022-11-14 15:51:00,182 Test: [51/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0750) Prec@1 86.000 (87.885) Prec@5 99.000 (99.308) +2022-11-14 15:51:00,192 Test: [52/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0750) Prec@1 87.000 (87.868) Prec@5 100.000 (99.321) +2022-11-14 15:51:00,201 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0748) Prec@1 91.000 (87.926) Prec@5 100.000 (99.333) +2022-11-14 15:51:00,210 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0751) Prec@1 84.000 (87.855) Prec@5 99.000 (99.327) +2022-11-14 15:51:00,220 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0753) Prec@1 88.000 (87.857) Prec@5 99.000 (99.321) +2022-11-14 15:51:00,231 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0752) Prec@1 88.000 (87.860) Prec@5 100.000 (99.333) +2022-11-14 15:51:00,243 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0752) Prec@1 89.000 (87.879) Prec@5 100.000 (99.345) +2022-11-14 15:51:00,254 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1191 (0.0759) Prec@1 80.000 (87.746) Prec@5 100.000 (99.356) +2022-11-14 15:51:00,264 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0757) Prec@1 90.000 (87.783) Prec@5 100.000 (99.367) +2022-11-14 15:51:00,276 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0754) Prec@1 91.000 (87.836) Prec@5 100.000 (99.377) +2022-11-14 15:51:00,287 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0753) Prec@1 88.000 (87.839) Prec@5 100.000 (99.387) +2022-11-14 15:51:00,297 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0749) Prec@1 90.000 (87.873) Prec@5 98.000 (99.365) +2022-11-14 15:51:00,307 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0745) Prec@1 93.000 (87.953) Prec@5 99.000 (99.359) +2022-11-14 15:51:00,317 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0749) Prec@1 86.000 (87.923) Prec@5 100.000 (99.369) +2022-11-14 15:51:00,326 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0749) Prec@1 88.000 (87.924) Prec@5 98.000 (99.348) +2022-11-14 15:51:00,337 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0747) Prec@1 89.000 (87.940) Prec@5 100.000 (99.358) +2022-11-14 15:51:00,347 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0747) Prec@1 89.000 (87.956) Prec@5 99.000 (99.353) +2022-11-14 15:51:00,358 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0746) Prec@1 88.000 (87.957) Prec@5 99.000 (99.348) +2022-11-14 15:51:00,370 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0746) Prec@1 90.000 (87.986) Prec@5 99.000 (99.343) +2022-11-14 15:51:00,381 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0745) Prec@1 91.000 (88.028) Prec@5 100.000 (99.352) +2022-11-14 15:51:00,393 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0744) Prec@1 90.000 (88.056) Prec@5 100.000 (99.361) +2022-11-14 15:51:00,403 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0741) Prec@1 92.000 (88.110) Prec@5 100.000 (99.370) +2022-11-14 15:51:00,413 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0404 (0.0736) Prec@1 94.000 (88.189) Prec@5 100.000 (99.378) +2022-11-14 15:51:00,428 Test: [74/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1252 (0.0743) Prec@1 82.000 (88.107) Prec@5 99.000 (99.373) +2022-11-14 15:51:00,442 Test: [75/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0742) Prec@1 92.000 (88.158) Prec@5 99.000 (99.368) +2022-11-14 15:51:00,453 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0744) Prec@1 87.000 (88.143) Prec@5 100.000 (99.377) +2022-11-14 15:51:00,463 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0746) Prec@1 86.000 (88.115) Prec@5 99.000 (99.372) +2022-11-14 15:51:00,474 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0745) Prec@1 89.000 (88.127) Prec@5 99.000 (99.367) +2022-11-14 15:51:00,485 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0748) Prec@1 85.000 (88.088) Prec@5 99.000 (99.362) +2022-11-14 15:51:00,496 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0751) Prec@1 83.000 (88.025) Prec@5 99.000 (99.358) +2022-11-14 15:51:00,508 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0751) Prec@1 88.000 (88.024) Prec@5 100.000 (99.366) +2022-11-14 15:51:00,519 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0751) Prec@1 87.000 (88.012) Prec@5 100.000 (99.373) +2022-11-14 15:51:00,530 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0750) Prec@1 89.000 (88.024) Prec@5 98.000 (99.357) +2022-11-14 15:51:00,542 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0752) Prec@1 84.000 (87.976) Prec@5 100.000 (99.365) +2022-11-14 15:51:00,554 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0755) Prec@1 83.000 (87.919) Prec@5 100.000 (99.372) +2022-11-14 15:51:00,565 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0753) Prec@1 90.000 (87.943) Prec@5 100.000 (99.379) +2022-11-14 15:51:00,575 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0753) Prec@1 89.000 (87.955) Prec@5 98.000 (99.364) +2022-11-14 15:51:00,585 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0750) Prec@1 91.000 (87.989) Prec@5 100.000 (99.371) +2022-11-14 15:51:00,596 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0751) Prec@1 90.000 (88.011) Prec@5 99.000 (99.367) +2022-11-14 15:51:00,609 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0504 (0.0748) Prec@1 92.000 (88.055) Prec@5 100.000 (99.374) +2022-11-14 15:51:00,621 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0746) Prec@1 91.000 (88.087) Prec@5 99.000 (99.370) +2022-11-14 15:51:00,631 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0747) Prec@1 85.000 (88.054) Prec@5 100.000 (99.376) +2022-11-14 15:51:00,642 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0748) Prec@1 87.000 (88.043) Prec@5 99.000 (99.372) +2022-11-14 15:51:00,654 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0748) Prec@1 87.000 (88.032) Prec@5 99.000 (99.368) +2022-11-14 15:51:00,666 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0746) Prec@1 91.000 (88.062) Prec@5 98.000 (99.354) +2022-11-14 15:51:00,679 Test: [96/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0745) Prec@1 90.000 (88.082) Prec@5 99.000 (99.351) +2022-11-14 15:51:00,689 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0747) Prec@1 85.000 (88.051) Prec@5 98.000 (99.337) +2022-11-14 15:51:00,699 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0749) Prec@1 85.000 (88.020) Prec@5 99.000 (99.333) +2022-11-14 15:51:00,708 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0748) Prec@1 91.000 (88.050) Prec@5 99.000 (99.330) +2022-11-14 15:51:00,769 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:51:01,116 Epoch: [271][0/500] Time 0.027 (0.027) Data 0.254 (0.254) Loss 0.0295 (0.0295) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:01,371 Epoch: [271][10/500] Time 0.020 (0.023) Data 0.002 (0.025) Loss 0.0487 (0.0391) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:01,630 Epoch: [271][20/500] Time 0.023 (0.023) Data 0.002 (0.014) Loss 0.0480 (0.0420) Prec@1 93.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 15:51:01,978 Epoch: [271][30/500] Time 0.039 (0.025) Data 0.002 (0.010) Loss 0.0260 (0.0380) Prec@1 96.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 15:51:02,432 Epoch: [271][40/500] Time 0.038 (0.029) Data 0.002 (0.008) Loss 0.0270 (0.0358) Prec@1 95.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:51:02,842 Epoch: [271][50/500] Time 0.032 (0.031) Data 0.002 (0.007) Loss 0.0143 (0.0322) Prec@1 99.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 15:51:03,292 Epoch: [271][60/500] Time 0.060 (0.032) Data 0.002 (0.006) Loss 0.0160 (0.0299) Prec@1 97.000 (95.429) Prec@5 100.000 (99.857) +2022-11-14 15:51:03,757 Epoch: [271][70/500] Time 0.034 (0.033) Data 0.002 (0.006) Loss 0.0502 (0.0324) Prec@1 93.000 (95.125) Prec@5 99.000 (99.750) +2022-11-14 15:51:04,168 Epoch: [271][80/500] Time 0.036 (0.034) Data 0.002 (0.005) Loss 0.0326 (0.0325) Prec@1 95.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 15:51:04,584 Epoch: [271][90/500] Time 0.037 (0.034) Data 0.002 (0.005) Loss 0.0465 (0.0339) Prec@1 91.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 15:51:05,007 Epoch: [271][100/500] Time 0.036 (0.034) Data 0.003 (0.004) Loss 0.0255 (0.0331) Prec@1 96.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 15:51:05,433 Epoch: [271][110/500] Time 0.033 (0.035) Data 0.002 (0.004) Loss 0.0431 (0.0339) Prec@1 92.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 15:51:05,961 Epoch: [271][120/500] Time 0.049 (0.036) Data 0.002 (0.004) Loss 0.0443 (0.0347) Prec@1 92.000 (94.385) Prec@5 99.000 (99.769) +2022-11-14 15:51:06,388 Epoch: [271][130/500] Time 0.037 (0.036) Data 0.002 (0.004) Loss 0.0311 (0.0345) Prec@1 96.000 (94.500) Prec@5 100.000 (99.786) +2022-11-14 15:51:06,810 Epoch: [271][140/500] Time 0.034 (0.036) Data 0.002 (0.004) Loss 0.0339 (0.0344) Prec@1 93.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:51:07,242 Epoch: [271][150/500] Time 0.041 (0.036) Data 0.002 (0.004) Loss 0.0488 (0.0353) Prec@1 90.000 (94.125) Prec@5 99.000 (99.750) +2022-11-14 15:51:07,683 Epoch: [271][160/500] Time 0.035 (0.036) Data 0.002 (0.004) Loss 0.0291 (0.0350) Prec@1 95.000 (94.176) Prec@5 100.000 (99.765) +2022-11-14 15:51:08,103 Epoch: [271][170/500] Time 0.035 (0.036) Data 0.002 (0.003) Loss 0.0433 (0.0354) Prec@1 93.000 (94.111) Prec@5 100.000 (99.778) +2022-11-14 15:51:08,524 Epoch: [271][180/500] Time 0.034 (0.036) Data 0.002 (0.003) Loss 0.0440 (0.0359) Prec@1 94.000 (94.105) Prec@5 99.000 (99.737) +2022-11-14 15:51:08,993 Epoch: [271][190/500] Time 0.055 (0.037) Data 0.002 (0.003) Loss 0.0228 (0.0352) Prec@1 99.000 (94.350) Prec@5 100.000 (99.750) +2022-11-14 15:51:09,496 Epoch: [271][200/500] Time 0.045 (0.037) Data 0.002 (0.003) Loss 0.0346 (0.0352) Prec@1 96.000 (94.429) Prec@5 99.000 (99.714) +2022-11-14 15:51:09,973 Epoch: [271][210/500] Time 0.032 (0.037) Data 0.002 (0.003) Loss 0.0128 (0.0342) Prec@1 98.000 (94.591) Prec@5 100.000 (99.727) +2022-11-14 15:51:10,487 Epoch: [271][220/500] Time 0.054 (0.038) Data 0.002 (0.003) Loss 0.0354 (0.0342) Prec@1 94.000 (94.565) Prec@5 100.000 (99.739) +2022-11-14 15:51:10,914 Epoch: [271][230/500] Time 0.037 (0.038) Data 0.002 (0.003) Loss 0.0207 (0.0337) Prec@1 97.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 15:51:11,341 Epoch: [271][240/500] Time 0.041 (0.038) Data 0.003 (0.003) Loss 0.0497 (0.0343) Prec@1 92.000 (94.560) Prec@5 100.000 (99.760) +2022-11-14 15:51:11,757 Epoch: [271][250/500] Time 0.042 (0.038) Data 0.002 (0.003) Loss 0.0447 (0.0347) Prec@1 92.000 (94.462) Prec@5 100.000 (99.769) +2022-11-14 15:51:12,179 Epoch: [271][260/500] Time 0.038 (0.038) Data 0.002 (0.003) Loss 0.0191 (0.0341) Prec@1 97.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 15:51:12,598 Epoch: [271][270/500] Time 0.036 (0.038) Data 0.002 (0.003) Loss 0.0422 (0.0344) Prec@1 93.000 (94.500) Prec@5 100.000 (99.786) +2022-11-14 15:51:13,092 Epoch: [271][280/500] Time 0.051 (0.038) Data 0.002 (0.003) Loss 0.0540 (0.0351) Prec@1 92.000 (94.414) Prec@5 100.000 (99.793) +2022-11-14 15:51:13,511 Epoch: [271][290/500] Time 0.040 (0.038) Data 0.002 (0.003) Loss 0.0351 (0.0351) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:51:13,942 Epoch: [271][300/500] Time 0.041 (0.038) Data 0.002 (0.003) Loss 0.0476 (0.0355) Prec@1 94.000 (94.387) Prec@5 100.000 (99.806) +2022-11-14 15:51:14,412 Epoch: [271][310/500] Time 0.059 (0.038) Data 0.002 (0.003) Loss 0.0348 (0.0355) Prec@1 96.000 (94.438) Prec@5 100.000 (99.812) +2022-11-14 15:51:15,153 Epoch: [271][320/500] Time 0.080 (0.039) Data 0.002 (0.003) Loss 0.0286 (0.0353) Prec@1 95.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 15:51:15,965 Epoch: [271][330/500] Time 0.075 (0.040) Data 0.002 (0.003) Loss 0.0345 (0.0352) Prec@1 94.000 (94.441) Prec@5 100.000 (99.824) +2022-11-14 15:51:16,751 Epoch: [271][340/500] Time 0.059 (0.041) Data 0.002 (0.003) Loss 0.0444 (0.0355) Prec@1 92.000 (94.371) Prec@5 100.000 (99.829) +2022-11-14 15:51:17,555 Epoch: [271][350/500] Time 0.077 (0.042) Data 0.002 (0.003) Loss 0.0290 (0.0353) Prec@1 96.000 (94.417) Prec@5 99.000 (99.806) +2022-11-14 15:51:18,343 Epoch: [271][360/500] Time 0.069 (0.043) Data 0.002 (0.003) Loss 0.0560 (0.0359) Prec@1 90.000 (94.297) Prec@5 97.000 (99.730) +2022-11-14 15:51:19,127 Epoch: [271][370/500] Time 0.073 (0.043) Data 0.002 (0.003) Loss 0.0548 (0.0364) Prec@1 92.000 (94.237) Prec@5 100.000 (99.737) +2022-11-14 15:51:19,930 Epoch: [271][380/500] Time 0.076 (0.044) Data 0.003 (0.003) Loss 0.0405 (0.0365) Prec@1 93.000 (94.205) Prec@5 100.000 (99.744) +2022-11-14 15:51:20,499 Epoch: [271][390/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0334 (0.0364) Prec@1 93.000 (94.175) Prec@5 100.000 (99.750) +2022-11-14 15:51:20,962 Epoch: [271][400/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0417 (0.0365) Prec@1 95.000 (94.195) Prec@5 100.000 (99.756) +2022-11-14 15:51:21,411 Epoch: [271][410/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0631 (0.0372) Prec@1 90.000 (94.095) Prec@5 100.000 (99.762) +2022-11-14 15:51:21,865 Epoch: [271][420/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0289 (0.0370) Prec@1 95.000 (94.116) Prec@5 100.000 (99.767) +2022-11-14 15:51:22,322 Epoch: [271][430/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0207 (0.0366) Prec@1 96.000 (94.159) Prec@5 100.000 (99.773) +2022-11-14 15:51:22,781 Epoch: [271][440/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0349 (0.0366) Prec@1 95.000 (94.178) Prec@5 100.000 (99.778) +2022-11-14 15:51:23,245 Epoch: [271][450/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0403 (0.0367) Prec@1 94.000 (94.174) Prec@5 100.000 (99.783) +2022-11-14 15:51:23,708 Epoch: [271][460/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0230 (0.0364) Prec@1 98.000 (94.255) Prec@5 100.000 (99.787) +2022-11-14 15:51:24,156 Epoch: [271][470/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0387 (0.0364) Prec@1 95.000 (94.271) Prec@5 100.000 (99.792) +2022-11-14 15:51:24,624 Epoch: [271][480/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0428 (0.0365) Prec@1 94.000 (94.265) Prec@5 99.000 (99.776) +2022-11-14 15:51:25,066 Epoch: [271][490/500] Time 0.037 (0.044) Data 0.002 (0.003) Loss 0.0454 (0.0367) Prec@1 94.000 (94.260) Prec@5 100.000 (99.780) +2022-11-14 15:51:25,510 Epoch: [271][499/500] Time 0.031 (0.044) Data 0.002 (0.003) Loss 0.0527 (0.0370) Prec@1 91.000 (94.196) Prec@5 98.000 (99.745) +2022-11-14 15:51:25,844 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:25,854 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0753 (0.0714) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 15:51:25,866 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0752) Prec@1 87.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 15:51:25,878 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0649 (0.0726) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:25,887 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.0765) Prec@1 84.000 (87.200) Prec@5 99.000 (99.800) +2022-11-14 15:51:25,896 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0736) Prec@1 91.000 (87.833) Prec@5 100.000 (99.833) +2022-11-14 15:51:25,906 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0722) Prec@1 90.000 (88.143) Prec@5 100.000 (99.857) +2022-11-14 15:51:25,917 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0720) Prec@1 89.000 (88.250) Prec@5 98.000 (99.625) +2022-11-14 15:51:25,926 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0739) Prec@1 85.000 (87.889) Prec@5 99.000 (99.556) +2022-11-14 15:51:25,936 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0737) Prec@1 89.000 (88.000) Prec@5 98.000 (99.400) +2022-11-14 15:51:25,946 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0718) Prec@1 91.000 (88.273) Prec@5 99.000 (99.364) +2022-11-14 15:51:25,958 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0738) Prec@1 87.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 15:51:25,967 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0727) Prec@1 88.000 (88.154) Prec@5 100.000 (99.385) +2022-11-14 15:51:25,977 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0723) Prec@1 89.000 (88.214) Prec@5 100.000 (99.429) +2022-11-14 15:51:25,988 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0734) Prec@1 85.000 (88.000) Prec@5 100.000 (99.467) +2022-11-14 15:51:25,998 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0729) Prec@1 91.000 (88.188) Prec@5 100.000 (99.500) +2022-11-14 15:51:26,007 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0711) Prec@1 95.000 (88.588) Prec@5 99.000 (99.471) +2022-11-14 15:51:26,017 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0729) Prec@1 84.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 15:51:26,027 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0729) Prec@1 87.000 (88.263) Prec@5 99.000 (99.474) +2022-11-14 15:51:26,037 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0739) Prec@1 86.000 (88.150) Prec@5 97.000 (99.350) +2022-11-14 15:51:26,047 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0737) Prec@1 87.000 (88.095) Prec@5 99.000 (99.333) +2022-11-14 15:51:26,056 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0747) Prec@1 87.000 (88.045) Prec@5 100.000 (99.364) +2022-11-14 15:51:26,065 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0757) Prec@1 86.000 (87.957) Prec@5 97.000 (99.261) +2022-11-14 15:51:26,074 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0756) Prec@1 88.000 (87.958) Prec@5 100.000 (99.292) +2022-11-14 15:51:26,085 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0770) Prec@1 83.000 (87.760) Prec@5 100.000 (99.320) +2022-11-14 15:51:26,096 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0779) Prec@1 84.000 (87.615) Prec@5 99.000 (99.308) +2022-11-14 15:51:26,107 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0772) Prec@1 90.000 (87.704) Prec@5 99.000 (99.296) +2022-11-14 15:51:26,120 Test: [27/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0766) Prec@1 91.000 (87.821) Prec@5 100.000 (99.321) +2022-11-14 15:51:26,130 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0768) Prec@1 87.000 (87.793) Prec@5 98.000 (99.276) +2022-11-14 15:51:26,140 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0764) Prec@1 87.000 (87.767) Prec@5 100.000 (99.300) +2022-11-14 15:51:26,150 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0764) Prec@1 88.000 (87.774) Prec@5 100.000 (99.323) +2022-11-14 15:51:26,161 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0767) Prec@1 89.000 (87.812) Prec@5 98.000 (99.281) +2022-11-14 15:51:26,170 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0761) Prec@1 90.000 (87.879) Prec@5 100.000 (99.303) +2022-11-14 15:51:26,180 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0759) Prec@1 88.000 (87.882) Prec@5 99.000 (99.294) +2022-11-14 15:51:26,192 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0763) Prec@1 86.000 (87.829) Prec@5 99.000 (99.286) +2022-11-14 15:51:26,203 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0761) Prec@1 90.000 (87.889) Prec@5 99.000 (99.278) +2022-11-14 15:51:26,213 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0762) Prec@1 87.000 (87.865) Prec@5 99.000 (99.270) +2022-11-14 15:51:26,224 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0759) Prec@1 90.000 (87.921) Prec@5 100.000 (99.289) +2022-11-14 15:51:26,234 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0755) Prec@1 91.000 (88.000) Prec@5 99.000 (99.282) +2022-11-14 15:51:26,244 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0757) Prec@1 86.000 (87.950) Prec@5 99.000 (99.275) +2022-11-14 15:51:26,255 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0761) Prec@1 84.000 (87.854) Prec@5 99.000 (99.268) +2022-11-14 15:51:26,267 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0760) Prec@1 88.000 (87.857) Prec@5 99.000 (99.262) +2022-11-14 15:51:26,276 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0755) Prec@1 90.000 (87.907) Prec@5 100.000 (99.279) +2022-11-14 15:51:26,286 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0751) Prec@1 94.000 (88.045) Prec@5 98.000 (99.250) +2022-11-14 15:51:26,297 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0747) Prec@1 90.000 (88.089) Prec@5 100.000 (99.267) +2022-11-14 15:51:26,307 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0754) Prec@1 84.000 (88.000) Prec@5 98.000 (99.239) +2022-11-14 15:51:26,317 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0755) Prec@1 88.000 (88.000) Prec@5 99.000 (99.234) +2022-11-14 15:51:26,327 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0760) Prec@1 84.000 (87.917) Prec@5 99.000 (99.229) +2022-11-14 15:51:26,337 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0763) Prec@1 85.000 (87.857) Prec@5 100.000 (99.245) +2022-11-14 15:51:26,347 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0767) Prec@1 86.000 (87.820) Prec@5 100.000 (99.260) +2022-11-14 15:51:26,359 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0763) Prec@1 90.000 (87.863) Prec@5 100.000 (99.275) +2022-11-14 15:51:26,370 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0767) Prec@1 83.000 (87.769) Prec@5 99.000 (99.269) +2022-11-14 15:51:26,380 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0766) Prec@1 87.000 (87.755) Prec@5 100.000 (99.283) +2022-11-14 15:51:26,390 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0766) Prec@1 88.000 (87.759) Prec@5 97.000 (99.241) +2022-11-14 15:51:26,401 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0765) Prec@1 87.000 (87.745) Prec@5 100.000 (99.255) +2022-11-14 15:51:26,413 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0767) Prec@1 89.000 (87.768) Prec@5 99.000 (99.250) +2022-11-14 15:51:26,424 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0764) Prec@1 90.000 (87.807) Prec@5 100.000 (99.263) +2022-11-14 15:51:26,434 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0763) Prec@1 88.000 (87.810) Prec@5 100.000 (99.276) +2022-11-14 15:51:26,444 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0766) Prec@1 84.000 (87.746) Prec@5 100.000 (99.288) +2022-11-14 15:51:26,455 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0763) Prec@1 88.000 (87.750) Prec@5 100.000 (99.300) +2022-11-14 15:51:26,465 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0763) Prec@1 85.000 (87.705) Prec@5 99.000 (99.295) +2022-11-14 15:51:26,478 Test: [61/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0766) Prec@1 86.000 (87.677) Prec@5 99.000 (99.290) +2022-11-14 15:51:26,489 Test: [62/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0764) Prec@1 91.000 (87.730) Prec@5 100.000 (99.302) +2022-11-14 15:51:26,500 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0761) Prec@1 90.000 (87.766) Prec@5 100.000 (99.312) +2022-11-14 15:51:26,511 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0763) Prec@1 88.000 (87.769) Prec@5 99.000 (99.308) +2022-11-14 15:51:26,523 Test: [65/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0765) Prec@1 84.000 (87.712) Prec@5 100.000 (99.318) +2022-11-14 15:51:26,536 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0407 (0.0760) Prec@1 93.000 (87.791) Prec@5 100.000 (99.328) +2022-11-14 15:51:26,547 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0759) Prec@1 90.000 (87.824) Prec@5 97.000 (99.294) +2022-11-14 15:51:26,557 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0759) Prec@1 84.000 (87.768) Prec@5 99.000 (99.290) +2022-11-14 15:51:26,567 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0762) Prec@1 85.000 (87.729) Prec@5 98.000 (99.271) +2022-11-14 15:51:26,578 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0763) Prec@1 87.000 (87.718) Prec@5 99.000 (99.268) +2022-11-14 15:51:26,589 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0763) Prec@1 87.000 (87.708) Prec@5 99.000 (99.264) +2022-11-14 15:51:26,599 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0760) Prec@1 91.000 (87.753) Prec@5 100.000 (99.274) +2022-11-14 15:51:26,609 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0758) Prec@1 91.000 (87.797) Prec@5 100.000 (99.284) +2022-11-14 15:51:26,619 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0763) Prec@1 81.000 (87.707) Prec@5 100.000 (99.293) +2022-11-14 15:51:26,629 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0761) Prec@1 88.000 (87.711) Prec@5 100.000 (99.303) +2022-11-14 15:51:26,639 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0761) Prec@1 86.000 (87.688) Prec@5 99.000 (99.299) +2022-11-14 15:51:26,650 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0763) Prec@1 85.000 (87.654) Prec@5 98.000 (99.282) +2022-11-14 15:51:26,660 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0764) Prec@1 87.000 (87.646) Prec@5 100.000 (99.291) +2022-11-14 15:51:26,671 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0764) Prec@1 87.000 (87.638) Prec@5 100.000 (99.300) +2022-11-14 15:51:26,680 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 89.000 (87.654) Prec@5 99.000 (99.296) +2022-11-14 15:51:26,691 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0764) Prec@1 86.000 (87.634) Prec@5 97.000 (99.268) +2022-11-14 15:51:26,702 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0766) Prec@1 84.000 (87.590) Prec@5 99.000 (99.265) +2022-11-14 15:51:26,714 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0764) Prec@1 90.000 (87.619) Prec@5 99.000 (99.262) +2022-11-14 15:51:26,725 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0767) Prec@1 84.000 (87.576) Prec@5 98.000 (99.247) +2022-11-14 15:51:26,734 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0770) Prec@1 83.000 (87.523) Prec@5 99.000 (99.244) +2022-11-14 15:51:26,744 Test: [86/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0767) Prec@1 92.000 (87.575) Prec@5 100.000 (99.253) +2022-11-14 15:51:26,754 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0766) Prec@1 88.000 (87.580) Prec@5 99.000 (99.250) +2022-11-14 15:51:26,764 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0765) Prec@1 89.000 (87.596) Prec@5 100.000 (99.258) +2022-11-14 15:51:26,773 Test: [89/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0765) Prec@1 88.000 (87.600) Prec@5 99.000 (99.256) +2022-11-14 15:51:26,783 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0415 (0.0761) Prec@1 93.000 (87.659) Prec@5 100.000 (99.264) +2022-11-14 15:51:26,794 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0760) Prec@1 91.000 (87.696) Prec@5 99.000 (99.261) +2022-11-14 15:51:26,803 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0760) Prec@1 88.000 (87.699) Prec@5 100.000 (99.269) +2022-11-14 15:51:26,812 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0761) Prec@1 86.000 (87.681) Prec@5 99.000 (99.266) +2022-11-14 15:51:26,821 Test: [94/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0761) Prec@1 87.000 (87.674) Prec@5 99.000 (99.263) +2022-11-14 15:51:26,829 Test: [95/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0759) Prec@1 93.000 (87.729) Prec@5 99.000 (99.260) +2022-11-14 15:51:26,838 Test: [96/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0756) Prec@1 94.000 (87.794) Prec@5 99.000 (99.258) +2022-11-14 15:51:26,846 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0757) Prec@1 86.000 (87.776) Prec@5 99.000 (99.255) +2022-11-14 15:51:26,856 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0760) Prec@1 84.000 (87.737) Prec@5 99.000 (99.253) +2022-11-14 15:51:26,865 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0760) Prec@1 89.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 15:51:26,922 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:51:27,265 Epoch: [272][0/500] Time 0.034 (0.034) Data 0.252 (0.252) Loss 0.0442 (0.0442) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 15:51:27,532 Epoch: [272][10/500] Time 0.025 (0.025) Data 0.002 (0.025) Loss 0.0323 (0.0382) Prec@1 95.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 15:51:27,818 Epoch: [272][20/500] Time 0.026 (0.025) Data 0.002 (0.014) Loss 0.0251 (0.0338) Prec@1 97.000 (95.000) Prec@5 100.000 (99.333) +2022-11-14 15:51:28,212 Epoch: [272][30/500] Time 0.041 (0.027) Data 0.002 (0.010) Loss 0.0263 (0.0320) Prec@1 95.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 15:51:28,773 Epoch: [272][40/500] Time 0.046 (0.033) Data 0.002 (0.008) Loss 0.0333 (0.0322) Prec@1 95.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 15:51:29,285 Epoch: [272][50/500] Time 0.049 (0.036) Data 0.002 (0.007) Loss 0.0348 (0.0327) Prec@1 94.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 15:51:29,771 Epoch: [272][60/500] Time 0.050 (0.037) Data 0.002 (0.006) Loss 0.0348 (0.0330) Prec@1 95.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 15:51:30,267 Epoch: [272][70/500] Time 0.047 (0.038) Data 0.002 (0.006) Loss 0.0346 (0.0332) Prec@1 95.000 (94.875) Prec@5 98.000 (99.500) +2022-11-14 15:51:30,769 Epoch: [272][80/500] Time 0.043 (0.039) Data 0.002 (0.005) Loss 0.0529 (0.0354) Prec@1 93.000 (94.667) Prec@5 99.000 (99.444) +2022-11-14 15:51:31,278 Epoch: [272][90/500] Time 0.045 (0.040) Data 0.002 (0.005) Loss 0.0474 (0.0366) Prec@1 92.000 (94.400) Prec@5 100.000 (99.500) +2022-11-14 15:51:31,773 Epoch: [272][100/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0272 (0.0357) Prec@1 95.000 (94.455) Prec@5 99.000 (99.455) +2022-11-14 15:51:32,305 Epoch: [272][110/500] Time 0.068 (0.041) Data 0.002 (0.004) Loss 0.0270 (0.0350) Prec@1 95.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 15:51:32,867 Epoch: [272][120/500] Time 0.055 (0.041) Data 0.002 (0.004) Loss 0.0333 (0.0349) Prec@1 94.000 (94.462) Prec@5 100.000 (99.538) +2022-11-14 15:51:33,431 Epoch: [272][130/500] Time 0.062 (0.042) Data 0.002 (0.004) Loss 0.0304 (0.0345) Prec@1 96.000 (94.571) Prec@5 100.000 (99.571) +2022-11-14 15:51:33,915 Epoch: [272][140/500] Time 0.048 (0.042) Data 0.002 (0.004) Loss 0.0197 (0.0336) Prec@1 97.000 (94.733) Prec@5 100.000 (99.600) +2022-11-14 15:51:34,425 Epoch: [272][150/500] Time 0.040 (0.042) Data 0.002 (0.004) Loss 0.0230 (0.0329) Prec@1 96.000 (94.812) Prec@5 100.000 (99.625) +2022-11-14 15:51:34,999 Epoch: [272][160/500] Time 0.059 (0.043) Data 0.002 (0.004) Loss 0.0304 (0.0328) Prec@1 96.000 (94.882) Prec@5 99.000 (99.588) +2022-11-14 15:51:35,529 Epoch: [272][170/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0418 (0.0333) Prec@1 92.000 (94.722) Prec@5 100.000 (99.611) +2022-11-14 15:51:36,089 Epoch: [272][180/500] Time 0.071 (0.044) Data 0.002 (0.003) Loss 0.0536 (0.0343) Prec@1 91.000 (94.526) Prec@5 100.000 (99.632) +2022-11-14 15:51:36,650 Epoch: [272][190/500] Time 0.065 (0.044) Data 0.002 (0.003) Loss 0.0327 (0.0342) Prec@1 95.000 (94.550) Prec@5 100.000 (99.650) +2022-11-14 15:51:37,144 Epoch: [272][200/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0375 (0.0344) Prec@1 93.000 (94.476) Prec@5 99.000 (99.619) +2022-11-14 15:51:37,653 Epoch: [272][210/500] Time 0.057 (0.044) Data 0.002 (0.003) Loss 0.0309 (0.0342) Prec@1 96.000 (94.545) Prec@5 100.000 (99.636) +2022-11-14 15:51:38,137 Epoch: [272][220/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0351 (0.0343) Prec@1 96.000 (94.609) Prec@5 100.000 (99.652) +2022-11-14 15:51:38,694 Epoch: [272][230/500] Time 0.061 (0.044) Data 0.002 (0.003) Loss 0.0345 (0.0343) Prec@1 93.000 (94.542) Prec@5 99.000 (99.625) +2022-11-14 15:51:39,214 Epoch: [272][240/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0556 (0.0351) Prec@1 89.000 (94.320) Prec@5 99.000 (99.600) +2022-11-14 15:51:39,724 Epoch: [272][250/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0556 (0.0359) Prec@1 93.000 (94.269) Prec@5 100.000 (99.615) +2022-11-14 15:51:40,239 Epoch: [272][260/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0654 (0.0370) Prec@1 89.000 (94.074) Prec@5 99.000 (99.593) +2022-11-14 15:51:40,726 Epoch: [272][270/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0350 (0.0369) Prec@1 93.000 (94.036) Prec@5 99.000 (99.571) +2022-11-14 15:51:41,237 Epoch: [272][280/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0583 (0.0377) Prec@1 91.000 (93.931) Prec@5 100.000 (99.586) +2022-11-14 15:51:41,756 Epoch: [272][290/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0468 (0.0380) Prec@1 93.000 (93.900) Prec@5 99.000 (99.567) +2022-11-14 15:51:42,310 Epoch: [272][300/500] Time 0.062 (0.045) Data 0.002 (0.003) Loss 0.0332 (0.0378) Prec@1 94.000 (93.903) Prec@5 100.000 (99.581) +2022-11-14 15:51:42,813 Epoch: [272][310/500] Time 0.045 (0.045) Data 0.003 (0.003) Loss 0.0508 (0.0382) Prec@1 91.000 (93.812) Prec@5 100.000 (99.594) +2022-11-14 15:51:43,331 Epoch: [272][320/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0184 (0.0376) Prec@1 98.000 (93.939) Prec@5 100.000 (99.606) +2022-11-14 15:51:43,827 Epoch: [272][330/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0152 (0.0370) Prec@1 97.000 (94.029) Prec@5 100.000 (99.618) +2022-11-14 15:51:44,353 Epoch: [272][340/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0227 (0.0366) Prec@1 97.000 (94.114) Prec@5 100.000 (99.629) +2022-11-14 15:51:44,834 Epoch: [272][350/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0494 (0.0369) Prec@1 92.000 (94.056) Prec@5 98.000 (99.583) +2022-11-14 15:51:45,320 Epoch: [272][360/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0309 (0.0368) Prec@1 95.000 (94.081) Prec@5 100.000 (99.595) +2022-11-14 15:51:45,860 Epoch: [272][370/500] Time 0.067 (0.045) Data 0.002 (0.003) Loss 0.0520 (0.0372) Prec@1 93.000 (94.053) Prec@5 100.000 (99.605) +2022-11-14 15:51:46,358 Epoch: [272][380/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0631 (0.0378) Prec@1 91.000 (93.974) Prec@5 99.000 (99.590) +2022-11-14 15:51:46,863 Epoch: [272][390/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0438 (0.0380) Prec@1 92.000 (93.925) Prec@5 100.000 (99.600) +2022-11-14 15:51:47,387 Epoch: [272][400/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0456 (0.0382) Prec@1 92.000 (93.878) Prec@5 100.000 (99.610) +2022-11-14 15:51:47,878 Epoch: [272][410/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0559 (0.0386) Prec@1 91.000 (93.810) Prec@5 99.000 (99.595) +2022-11-14 15:51:48,445 Epoch: [272][420/500] Time 0.057 (0.045) Data 0.002 (0.003) Loss 0.0369 (0.0385) Prec@1 94.000 (93.814) Prec@5 100.000 (99.605) +2022-11-14 15:51:48,957 Epoch: [272][430/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0184 (0.0381) Prec@1 99.000 (93.932) Prec@5 99.000 (99.591) +2022-11-14 15:51:49,455 Epoch: [272][440/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0558 (0.0385) Prec@1 92.000 (93.889) Prec@5 100.000 (99.600) +2022-11-14 15:51:50,016 Epoch: [272][450/500] Time 0.062 (0.045) Data 0.002 (0.003) Loss 0.0200 (0.0381) Prec@1 95.000 (93.913) Prec@5 100.000 (99.609) +2022-11-14 15:51:50,507 Epoch: [272][460/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0435 (0.0382) Prec@1 92.000 (93.872) Prec@5 100.000 (99.617) +2022-11-14 15:51:51,014 Epoch: [272][470/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0258 (0.0379) Prec@1 96.000 (93.917) Prec@5 99.000 (99.604) +2022-11-14 15:51:51,529 Epoch: [272][480/500] Time 0.073 (0.045) Data 0.002 (0.003) Loss 0.0187 (0.0375) Prec@1 98.000 (94.000) Prec@5 100.000 (99.612) +2022-11-14 15:51:52,004 Epoch: [272][490/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0471 (0.0377) Prec@1 94.000 (94.000) Prec@5 100.000 (99.620) +2022-11-14 15:51:52,440 Epoch: [272][499/500] Time 0.035 (0.045) Data 0.002 (0.003) Loss 0.0360 (0.0377) Prec@1 92.000 (93.961) Prec@5 99.000 (99.608) +2022-11-14 15:51:52,754 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0594 (0.0594) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:52,765 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0682 (0.0638) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:52,774 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0497 (0.0591) Prec@1 94.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:52,791 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0610) Prec@1 91.000 (90.250) Prec@5 99.000 (99.750) +2022-11-14 15:51:52,801 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0630) Prec@1 88.000 (89.800) Prec@5 99.000 (99.600) +2022-11-14 15:51:52,812 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0615) Prec@1 93.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 15:51:52,822 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0604) Prec@1 91.000 (90.429) Prec@5 99.000 (99.571) +2022-11-14 15:51:52,833 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0609) Prec@1 90.000 (90.375) Prec@5 100.000 (99.625) +2022-11-14 15:51:52,841 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0623) Prec@1 89.000 (90.222) Prec@5 99.000 (99.556) +2022-11-14 15:51:52,851 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0637) Prec@1 87.000 (89.900) Prec@5 98.000 (99.400) +2022-11-14 15:51:52,861 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0528 (0.0627) Prec@1 91.000 (90.000) Prec@5 99.000 (99.364) +2022-11-14 15:51:52,871 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0641) Prec@1 87.000 (89.750) Prec@5 99.000 (99.333) +2022-11-14 15:51:52,881 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0632) Prec@1 90.000 (89.769) Prec@5 100.000 (99.385) +2022-11-14 15:51:52,892 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0649) Prec@1 85.000 (89.429) Prec@5 100.000 (99.429) +2022-11-14 15:51:52,901 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0657) Prec@1 88.000 (89.333) Prec@5 99.000 (99.400) +2022-11-14 15:51:52,912 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0657) Prec@1 90.000 (89.375) Prec@5 100.000 (99.438) +2022-11-14 15:51:52,924 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0647) Prec@1 93.000 (89.588) Prec@5 98.000 (99.353) +2022-11-14 15:51:52,935 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0664) Prec@1 85.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 15:51:52,945 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0676) Prec@1 86.000 (89.158) Prec@5 99.000 (99.316) +2022-11-14 15:51:52,956 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0689) Prec@1 85.000 (88.950) Prec@5 96.000 (99.150) +2022-11-14 15:51:52,967 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0696) Prec@1 88.000 (88.905) Prec@5 100.000 (99.190) +2022-11-14 15:51:52,979 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0705) Prec@1 84.000 (88.682) Prec@5 99.000 (99.182) +2022-11-14 15:51:52,991 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0711) Prec@1 89.000 (88.696) Prec@5 99.000 (99.174) +2022-11-14 15:51:53,002 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0718) Prec@1 85.000 (88.542) Prec@5 99.000 (99.167) +2022-11-14 15:51:53,014 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0723) Prec@1 86.000 (88.440) Prec@5 99.000 (99.160) +2022-11-14 15:51:53,025 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0729) Prec@1 85.000 (88.308) Prec@5 100.000 (99.192) +2022-11-14 15:51:53,035 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0725) Prec@1 91.000 (88.407) Prec@5 100.000 (99.222) +2022-11-14 15:51:53,045 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0717) Prec@1 92.000 (88.536) Prec@5 100.000 (99.250) +2022-11-14 15:51:53,055 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0722) Prec@1 86.000 (88.448) Prec@5 98.000 (99.207) +2022-11-14 15:51:53,066 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0721) Prec@1 88.000 (88.433) Prec@5 100.000 (99.233) +2022-11-14 15:51:53,076 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0722) Prec@1 86.000 (88.355) Prec@5 100.000 (99.258) +2022-11-14 15:51:53,085 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0724) Prec@1 87.000 (88.312) Prec@5 100.000 (99.281) +2022-11-14 15:51:53,094 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0724) Prec@1 88.000 (88.303) Prec@5 100.000 (99.303) +2022-11-14 15:51:53,103 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0728) Prec@1 86.000 (88.235) Prec@5 99.000 (99.294) +2022-11-14 15:51:53,114 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0735) Prec@1 84.000 (88.114) Prec@5 97.000 (99.229) +2022-11-14 15:51:53,125 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0730) Prec@1 91.000 (88.194) Prec@5 100.000 (99.250) +2022-11-14 15:51:53,135 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0730) Prec@1 87.000 (88.162) Prec@5 98.000 (99.216) +2022-11-14 15:51:53,144 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0733) Prec@1 85.000 (88.079) Prec@5 99.000 (99.211) +2022-11-14 15:51:53,154 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0732) Prec@1 91.000 (88.154) Prec@5 100.000 (99.231) +2022-11-14 15:51:53,165 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0728) Prec@1 91.000 (88.225) Prec@5 99.000 (99.225) +2022-11-14 15:51:53,176 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0735) Prec@1 85.000 (88.146) Prec@5 99.000 (99.220) +2022-11-14 15:51:53,186 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0740) Prec@1 85.000 (88.071) Prec@5 98.000 (99.190) +2022-11-14 15:51:53,195 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0735) Prec@1 91.000 (88.140) Prec@5 100.000 (99.209) +2022-11-14 15:51:53,206 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0735) Prec@1 90.000 (88.182) Prec@5 99.000 (99.205) +2022-11-14 15:51:53,216 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0443 (0.0729) Prec@1 92.000 (88.267) Prec@5 100.000 (99.222) +2022-11-14 15:51:53,227 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0733) Prec@1 85.000 (88.196) Prec@5 100.000 (99.239) +2022-11-14 15:51:53,237 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0732) Prec@1 89.000 (88.213) Prec@5 100.000 (99.255) +2022-11-14 15:51:53,248 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0739) Prec@1 83.000 (88.104) Prec@5 100.000 (99.271) +2022-11-14 15:51:53,259 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0736) Prec@1 90.000 (88.143) Prec@5 100.000 (99.286) +2022-11-14 15:51:53,269 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0740) Prec@1 86.000 (88.100) Prec@5 99.000 (99.280) +2022-11-14 15:51:53,279 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0736) Prec@1 91.000 (88.157) Prec@5 100.000 (99.294) +2022-11-14 15:51:53,289 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0734) Prec@1 90.000 (88.192) Prec@5 99.000 (99.288) +2022-11-14 15:51:53,300 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0735) Prec@1 89.000 (88.208) Prec@5 100.000 (99.302) +2022-11-14 15:51:53,311 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0735) Prec@1 88.000 (88.204) Prec@5 99.000 (99.296) +2022-11-14 15:51:53,321 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0736) Prec@1 87.000 (88.182) Prec@5 100.000 (99.309) +2022-11-14 15:51:53,331 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0734) Prec@1 89.000 (88.196) Prec@5 98.000 (99.286) +2022-11-14 15:51:53,345 Test: [56/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0733) Prec@1 87.000 (88.175) Prec@5 100.000 (99.298) +2022-11-14 15:51:53,357 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0731) Prec@1 92.000 (88.241) Prec@5 100.000 (99.310) +2022-11-14 15:51:53,367 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0733) Prec@1 86.000 (88.203) Prec@5 100.000 (99.322) +2022-11-14 15:51:53,378 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0734) Prec@1 86.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 15:51:53,391 Test: [60/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0734) Prec@1 88.000 (88.164) Prec@5 98.000 (99.311) +2022-11-14 15:51:53,403 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0734) Prec@1 89.000 (88.177) Prec@5 100.000 (99.323) +2022-11-14 15:51:53,414 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0732) Prec@1 87.000 (88.159) Prec@5 100.000 (99.333) +2022-11-14 15:51:53,424 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0320 (0.0726) Prec@1 94.000 (88.250) Prec@5 100.000 (99.344) +2022-11-14 15:51:53,437 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0730) Prec@1 82.000 (88.154) Prec@5 99.000 (99.338) +2022-11-14 15:51:53,450 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0730) Prec@1 85.000 (88.106) Prec@5 99.000 (99.333) +2022-11-14 15:51:53,461 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0727) Prec@1 92.000 (88.164) Prec@5 100.000 (99.343) +2022-11-14 15:51:53,471 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0726) Prec@1 90.000 (88.191) Prec@5 98.000 (99.324) +2022-11-14 15:51:53,484 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0725) Prec@1 86.000 (88.159) Prec@5 99.000 (99.319) +2022-11-14 15:51:53,496 Test: [69/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0729) Prec@1 86.000 (88.129) Prec@5 98.000 (99.300) +2022-11-14 15:51:53,505 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0731) Prec@1 88.000 (88.127) Prec@5 99.000 (99.296) +2022-11-14 15:51:53,517 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0729) Prec@1 90.000 (88.153) Prec@5 100.000 (99.306) +2022-11-14 15:51:53,527 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0727) Prec@1 91.000 (88.192) Prec@5 100.000 (99.315) +2022-11-14 15:51:53,537 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0725) Prec@1 91.000 (88.230) Prec@5 99.000 (99.311) +2022-11-14 15:51:53,547 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1070 (0.0729) Prec@1 80.000 (88.120) Prec@5 100.000 (99.320) +2022-11-14 15:51:53,558 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0728) Prec@1 88.000 (88.118) Prec@5 99.000 (99.316) +2022-11-14 15:51:53,571 Test: [76/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0730) Prec@1 86.000 (88.091) Prec@5 98.000 (99.299) +2022-11-14 15:51:53,582 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0731) Prec@1 87.000 (88.077) Prec@5 97.000 (99.269) +2022-11-14 15:51:53,592 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0733) Prec@1 83.000 (88.013) Prec@5 100.000 (99.278) +2022-11-14 15:51:53,603 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0732) Prec@1 88.000 (88.013) Prec@5 100.000 (99.287) +2022-11-14 15:51:53,616 Test: [80/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0735) Prec@1 86.000 (87.988) Prec@5 98.000 (99.272) +2022-11-14 15:51:53,628 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0738) Prec@1 85.000 (87.951) Prec@5 98.000 (99.256) +2022-11-14 15:51:53,639 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0740) Prec@1 87.000 (87.940) Prec@5 99.000 (99.253) +2022-11-14 15:51:53,648 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0741) Prec@1 86.000 (87.917) Prec@5 99.000 (99.250) +2022-11-14 15:51:53,661 Test: [84/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0742) Prec@1 87.000 (87.906) Prec@5 99.000 (99.247) +2022-11-14 15:51:53,672 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1244 (0.0748) Prec@1 82.000 (87.837) Prec@5 98.000 (99.233) +2022-11-14 15:51:53,682 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0746) Prec@1 91.000 (87.874) Prec@5 100.000 (99.241) +2022-11-14 15:51:53,692 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0745) Prec@1 91.000 (87.909) Prec@5 99.000 (99.239) +2022-11-14 15:51:53,704 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0744) Prec@1 89.000 (87.921) Prec@5 100.000 (99.247) +2022-11-14 15:51:53,717 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0745) Prec@1 90.000 (87.944) Prec@5 99.000 (99.244) +2022-11-14 15:51:53,728 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0743) Prec@1 93.000 (88.000) Prec@5 99.000 (99.242) +2022-11-14 15:51:53,739 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0378 (0.0739) Prec@1 94.000 (88.065) Prec@5 100.000 (99.250) +2022-11-14 15:51:53,749 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0739) Prec@1 87.000 (88.054) Prec@5 99.000 (99.247) +2022-11-14 15:51:53,760 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0739) Prec@1 85.000 (88.021) Prec@5 97.000 (99.223) +2022-11-14 15:51:53,771 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0738) Prec@1 86.000 (88.000) Prec@5 99.000 (99.221) +2022-11-14 15:51:53,781 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0739) Prec@1 90.000 (88.021) Prec@5 98.000 (99.208) +2022-11-14 15:51:53,791 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0736) Prec@1 91.000 (88.052) Prec@5 98.000 (99.196) +2022-11-14 15:51:53,801 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0739) Prec@1 87.000 (88.041) Prec@5 99.000 (99.194) +2022-11-14 15:51:53,811 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0742) Prec@1 83.000 (87.990) Prec@5 98.000 (99.182) +2022-11-14 15:51:53,822 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0742) Prec@1 90.000 (88.010) Prec@5 99.000 (99.180) +2022-11-14 15:51:53,883 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:51:54,249 Epoch: [273][0/500] Time 0.026 (0.026) Data 0.264 (0.264) Loss 0.0524 (0.0524) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:54,521 Epoch: [273][10/500] Time 0.022 (0.024) Data 0.002 (0.026) Loss 0.0189 (0.0357) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:51:54,842 Epoch: [273][20/500] Time 0.039 (0.026) Data 0.002 (0.015) Loss 0.0420 (0.0378) Prec@1 94.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 15:51:55,216 Epoch: [273][30/500] Time 0.041 (0.029) Data 0.002 (0.011) Loss 0.0143 (0.0319) Prec@1 98.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 15:51:55,621 Epoch: [273][40/500] Time 0.037 (0.031) Data 0.002 (0.008) Loss 0.0339 (0.0323) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:51:56,005 Epoch: [273][50/500] Time 0.035 (0.031) Data 0.002 (0.007) Loss 0.0465 (0.0347) Prec@1 93.000 (94.667) Prec@5 99.000 (99.833) +2022-11-14 15:51:56,376 Epoch: [273][60/500] Time 0.033 (0.032) Data 0.002 (0.006) Loss 0.0184 (0.0323) Prec@1 96.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 15:51:56,775 Epoch: [273][70/500] Time 0.047 (0.032) Data 0.002 (0.006) Loss 0.0533 (0.0350) Prec@1 91.000 (94.375) Prec@5 99.000 (99.750) +2022-11-14 15:51:57,315 Epoch: [273][80/500] Time 0.092 (0.033) Data 0.002 (0.005) Loss 0.0231 (0.0336) Prec@1 96.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 15:51:58,161 Epoch: [273][90/500] Time 0.085 (0.038) Data 0.003 (0.005) Loss 0.0333 (0.0336) Prec@1 96.000 (94.700) Prec@5 98.000 (99.600) +2022-11-14 15:51:59,053 Epoch: [273][100/500] Time 0.108 (0.042) Data 0.002 (0.005) Loss 0.0275 (0.0331) Prec@1 95.000 (94.727) Prec@5 100.000 (99.636) +2022-11-14 15:52:00,056 Epoch: [273][110/500] Time 0.088 (0.047) Data 0.002 (0.004) Loss 0.0302 (0.0328) Prec@1 96.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 15:52:00,604 Epoch: [273][120/500] Time 0.043 (0.047) Data 0.002 (0.004) Loss 0.0339 (0.0329) Prec@1 93.000 (94.692) Prec@5 100.000 (99.692) +2022-11-14 15:52:01,105 Epoch: [273][130/500] Time 0.052 (0.047) Data 0.002 (0.004) Loss 0.0387 (0.0333) Prec@1 94.000 (94.643) Prec@5 99.000 (99.643) +2022-11-14 15:52:01,594 Epoch: [273][140/500] Time 0.038 (0.046) Data 0.002 (0.004) Loss 0.0459 (0.0342) Prec@1 93.000 (94.533) Prec@5 100.000 (99.667) +2022-11-14 15:52:02,083 Epoch: [273][150/500] Time 0.049 (0.046) Data 0.002 (0.004) Loss 0.0504 (0.0352) Prec@1 92.000 (94.375) Prec@5 100.000 (99.688) +2022-11-14 15:52:02,571 Epoch: [273][160/500] Time 0.043 (0.046) Data 0.002 (0.004) Loss 0.0223 (0.0344) Prec@1 97.000 (94.529) Prec@5 100.000 (99.706) +2022-11-14 15:52:03,119 Epoch: [273][170/500] Time 0.051 (0.046) Data 0.003 (0.004) Loss 0.0380 (0.0346) Prec@1 93.000 (94.444) Prec@5 100.000 (99.722) +2022-11-14 15:52:03,654 Epoch: [273][180/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0447 (0.0351) Prec@1 93.000 (94.368) Prec@5 100.000 (99.737) +2022-11-14 15:52:04,187 Epoch: [273][190/500] Time 0.048 (0.046) Data 0.002 (0.004) Loss 0.0442 (0.0356) Prec@1 93.000 (94.300) Prec@5 100.000 (99.750) +2022-11-14 15:52:04,709 Epoch: [273][200/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0262 (0.0352) Prec@1 95.000 (94.333) Prec@5 100.000 (99.762) +2022-11-14 15:52:05,209 Epoch: [273][210/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0441 (0.0356) Prec@1 93.000 (94.273) Prec@5 100.000 (99.773) +2022-11-14 15:52:05,685 Epoch: [273][220/500] Time 0.054 (0.046) Data 0.003 (0.003) Loss 0.0465 (0.0360) Prec@1 91.000 (94.130) Prec@5 100.000 (99.783) +2022-11-14 15:52:06,163 Epoch: [273][230/500] Time 0.050 (0.046) Data 0.003 (0.003) Loss 0.0182 (0.0353) Prec@1 98.000 (94.292) Prec@5 100.000 (99.792) +2022-11-14 15:52:06,728 Epoch: [273][240/500] Time 0.060 (0.046) Data 0.002 (0.003) Loss 0.0404 (0.0355) Prec@1 93.000 (94.240) Prec@5 100.000 (99.800) +2022-11-14 15:52:07,244 Epoch: [273][250/500] Time 0.066 (0.046) Data 0.002 (0.003) Loss 0.0512 (0.0361) Prec@1 91.000 (94.115) Prec@5 97.000 (99.692) +2022-11-14 15:52:07,836 Epoch: [273][260/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0285 (0.0358) Prec@1 94.000 (94.111) Prec@5 100.000 (99.704) +2022-11-14 15:52:08,307 Epoch: [273][270/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0412 (0.0360) Prec@1 94.000 (94.107) Prec@5 99.000 (99.679) +2022-11-14 15:52:08,787 Epoch: [273][280/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0194 (0.0354) Prec@1 97.000 (94.207) Prec@5 100.000 (99.690) +2022-11-14 15:52:09,274 Epoch: [273][290/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0635 (0.0364) Prec@1 90.000 (94.067) Prec@5 99.000 (99.667) +2022-11-14 15:52:09,795 Epoch: [273][300/500] Time 0.041 (0.046) Data 0.002 (0.003) Loss 0.0330 (0.0363) Prec@1 95.000 (94.097) Prec@5 100.000 (99.677) +2022-11-14 15:52:10,275 Epoch: [273][310/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0334 (0.0362) Prec@1 94.000 (94.094) Prec@5 100.000 (99.688) +2022-11-14 15:52:10,831 Epoch: [273][320/500] Time 0.066 (0.046) Data 0.002 (0.003) Loss 0.0369 (0.0362) Prec@1 94.000 (94.091) Prec@5 100.000 (99.697) +2022-11-14 15:52:11,379 Epoch: [273][330/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.0577 (0.0368) Prec@1 90.000 (93.971) Prec@5 100.000 (99.706) +2022-11-14 15:52:11,906 Epoch: [273][340/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0179 (0.0363) Prec@1 97.000 (94.057) Prec@5 100.000 (99.714) +2022-11-14 15:52:12,442 Epoch: [273][350/500] Time 0.069 (0.046) Data 0.002 (0.003) Loss 0.0257 (0.0360) Prec@1 96.000 (94.111) Prec@5 100.000 (99.722) +2022-11-14 15:52:12,904 Epoch: [273][360/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0423 (0.0362) Prec@1 94.000 (94.108) Prec@5 100.000 (99.730) +2022-11-14 15:52:13,432 Epoch: [273][370/500] Time 0.037 (0.046) Data 0.003 (0.003) Loss 0.0288 (0.0360) Prec@1 95.000 (94.132) Prec@5 99.000 (99.711) +2022-11-14 15:52:13,915 Epoch: [273][380/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0540 (0.0364) Prec@1 90.000 (94.026) Prec@5 100.000 (99.718) +2022-11-14 15:52:14,468 Epoch: [273][390/500] Time 0.060 (0.046) Data 0.002 (0.003) Loss 0.0357 (0.0364) Prec@1 96.000 (94.075) Prec@5 100.000 (99.725) +2022-11-14 15:52:14,951 Epoch: [273][400/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0414 (0.0365) Prec@1 91.000 (94.000) Prec@5 100.000 (99.732) +2022-11-14 15:52:15,492 Epoch: [273][410/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0251 (0.0363) Prec@1 95.000 (94.024) Prec@5 100.000 (99.738) +2022-11-14 15:52:16,070 Epoch: [273][420/500] Time 0.068 (0.046) Data 0.002 (0.003) Loss 0.0390 (0.0363) Prec@1 91.000 (93.953) Prec@5 100.000 (99.744) +2022-11-14 15:52:16,633 Epoch: [273][430/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0521 (0.0367) Prec@1 91.000 (93.886) Prec@5 100.000 (99.750) +2022-11-14 15:52:17,107 Epoch: [273][440/500] Time 0.039 (0.046) Data 0.002 (0.003) Loss 0.0335 (0.0366) Prec@1 95.000 (93.911) Prec@5 100.000 (99.756) +2022-11-14 15:52:17,595 Epoch: [273][450/500] Time 0.061 (0.046) Data 0.002 (0.003) Loss 0.0292 (0.0365) Prec@1 97.000 (93.978) Prec@5 100.000 (99.761) +2022-11-14 15:52:18,075 Epoch: [273][460/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0372 (0.0365) Prec@1 94.000 (93.979) Prec@5 100.000 (99.766) +2022-11-14 15:52:18,585 Epoch: [273][470/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0307 (0.0364) Prec@1 94.000 (93.979) Prec@5 100.000 (99.771) +2022-11-14 15:52:19,116 Epoch: [273][480/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0279 (0.0362) Prec@1 96.000 (94.020) Prec@5 100.000 (99.776) +2022-11-14 15:52:19,574 Epoch: [273][490/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0589 (0.0366) Prec@1 89.000 (93.920) Prec@5 100.000 (99.780) +2022-11-14 15:52:20,002 Epoch: [273][499/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0256 (0.0364) Prec@1 95.000 (93.941) Prec@5 99.000 (99.765) +2022-11-14 15:52:20,329 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0691 (0.0691) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:20,338 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0529 (0.0610) Prec@1 93.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:20,346 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0577) Prec@1 89.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 15:52:20,359 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0620) Prec@1 88.000 (89.750) Prec@5 99.000 (99.750) +2022-11-14 15:52:20,369 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0632) Prec@1 88.000 (89.400) Prec@5 99.000 (99.600) +2022-11-14 15:52:20,378 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0605) Prec@1 89.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 15:52:20,390 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0619) Prec@1 90.000 (89.429) Prec@5 98.000 (99.429) +2022-11-14 15:52:20,402 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0635) Prec@1 86.000 (89.000) Prec@5 99.000 (99.375) +2022-11-14 15:52:20,414 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0650) Prec@1 88.000 (88.889) Prec@5 98.000 (99.222) +2022-11-14 15:52:20,427 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0666) Prec@1 86.000 (88.600) Prec@5 100.000 (99.300) +2022-11-14 15:52:20,442 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0652) Prec@1 92.000 (88.909) Prec@5 99.000 (99.273) +2022-11-14 15:52:20,456 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0665) Prec@1 89.000 (88.917) Prec@5 99.000 (99.250) +2022-11-14 15:52:20,470 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0659) Prec@1 91.000 (89.077) Prec@5 100.000 (99.308) +2022-11-14 15:52:20,484 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0655) Prec@1 89.000 (89.071) Prec@5 100.000 (99.357) +2022-11-14 15:52:20,498 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0676) Prec@1 83.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 15:52:20,512 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0690) Prec@1 83.000 (88.312) Prec@5 100.000 (99.375) +2022-11-14 15:52:20,526 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0692) Prec@1 90.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 15:52:20,541 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0710) Prec@1 82.000 (88.056) Prec@5 100.000 (99.389) +2022-11-14 15:52:20,557 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0718) Prec@1 86.000 (87.947) Prec@5 99.000 (99.368) +2022-11-14 15:52:20,572 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0737) Prec@1 84.000 (87.750) Prec@5 96.000 (99.200) +2022-11-14 15:52:20,588 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0736) Prec@1 88.000 (87.762) Prec@5 100.000 (99.238) +2022-11-14 15:52:20,611 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0736) Prec@1 85.000 (87.636) Prec@5 98.000 (99.182) +2022-11-14 15:52:20,634 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0746) Prec@1 88.000 (87.652) Prec@5 96.000 (99.043) +2022-11-14 15:52:20,655 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0750) Prec@1 86.000 (87.583) Prec@5 100.000 (99.083) +2022-11-14 15:52:20,674 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0751) Prec@1 88.000 (87.600) Prec@5 99.000 (99.080) +2022-11-14 15:52:20,696 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0754) Prec@1 87.000 (87.577) Prec@5 99.000 (99.077) +2022-11-14 15:52:20,717 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0747) Prec@1 91.000 (87.704) Prec@5 100.000 (99.111) +2022-11-14 15:52:20,736 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0744) Prec@1 89.000 (87.750) Prec@5 100.000 (99.143) +2022-11-14 15:52:20,757 Test: [28/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0741) Prec@1 91.000 (87.862) Prec@5 99.000 (99.138) +2022-11-14 15:52:20,779 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0739) Prec@1 89.000 (87.900) Prec@5 99.000 (99.133) +2022-11-14 15:52:20,797 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0739) Prec@1 90.000 (87.968) Prec@5 100.000 (99.161) +2022-11-14 15:52:20,818 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0737) Prec@1 89.000 (88.000) Prec@5 100.000 (99.188) +2022-11-14 15:52:20,838 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0737) Prec@1 89.000 (88.030) Prec@5 98.000 (99.152) +2022-11-14 15:52:20,857 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0745) Prec@1 82.000 (87.853) Prec@5 100.000 (99.176) +2022-11-14 15:52:20,876 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0747) Prec@1 87.000 (87.829) Prec@5 97.000 (99.114) +2022-11-14 15:52:20,898 Test: [35/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0747) Prec@1 89.000 (87.861) Prec@5 100.000 (99.139) +2022-11-14 15:52:20,918 Test: [36/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0747) Prec@1 88.000 (87.865) Prec@5 98.000 (99.108) +2022-11-14 15:52:20,938 Test: [37/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0747) Prec@1 88.000 (87.868) Prec@5 100.000 (99.132) +2022-11-14 15:52:20,959 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0743) Prec@1 91.000 (87.949) Prec@5 99.000 (99.128) +2022-11-14 15:52:20,979 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0740) Prec@1 89.000 (87.975) Prec@5 99.000 (99.125) +2022-11-14 15:52:20,995 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1089 (0.0749) Prec@1 83.000 (87.854) Prec@5 99.000 (99.122) +2022-11-14 15:52:21,009 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0747) Prec@1 91.000 (87.929) Prec@5 99.000 (99.119) +2022-11-14 15:52:21,022 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0743) Prec@1 92.000 (88.023) Prec@5 98.000 (99.093) +2022-11-14 15:52:21,035 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0741) Prec@1 90.000 (88.068) Prec@5 99.000 (99.091) +2022-11-14 15:52:21,052 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0738) Prec@1 89.000 (88.089) Prec@5 100.000 (99.111) +2022-11-14 15:52:21,067 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0744) Prec@1 86.000 (88.043) Prec@5 100.000 (99.130) +2022-11-14 15:52:21,083 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0741) Prec@1 91.000 (88.106) Prec@5 100.000 (99.149) +2022-11-14 15:52:21,101 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0749) Prec@1 82.000 (87.979) Prec@5 97.000 (99.104) +2022-11-14 15:52:21,116 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0748) Prec@1 88.000 (87.980) Prec@5 99.000 (99.102) +2022-11-14 15:52:21,131 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1050 (0.0754) Prec@1 84.000 (87.900) Prec@5 100.000 (99.120) +2022-11-14 15:52:21,149 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0750) Prec@1 91.000 (87.961) Prec@5 99.000 (99.118) +2022-11-14 15:52:21,164 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0747) Prec@1 89.000 (87.981) Prec@5 100.000 (99.135) +2022-11-14 15:52:21,178 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0749) Prec@1 83.000 (87.887) Prec@5 100.000 (99.151) +2022-11-14 15:52:21,195 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0747) Prec@1 90.000 (87.926) Prec@5 100.000 (99.167) +2022-11-14 15:52:21,212 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0749) Prec@1 88.000 (87.927) Prec@5 100.000 (99.182) +2022-11-14 15:52:21,228 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0745) Prec@1 93.000 (88.018) Prec@5 99.000 (99.179) +2022-11-14 15:52:21,244 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0743) Prec@1 89.000 (88.035) Prec@5 99.000 (99.175) +2022-11-14 15:52:21,258 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0742) Prec@1 87.000 (88.017) Prec@5 99.000 (99.172) +2022-11-14 15:52:21,272 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0748) Prec@1 82.000 (87.915) Prec@5 100.000 (99.186) +2022-11-14 15:52:21,288 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0748) Prec@1 85.000 (87.867) Prec@5 100.000 (99.200) +2022-11-14 15:52:21,309 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0748) Prec@1 87.000 (87.852) Prec@5 99.000 (99.197) +2022-11-14 15:52:21,325 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0748) Prec@1 88.000 (87.855) Prec@5 100.000 (99.210) +2022-11-14 15:52:21,342 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0747) Prec@1 91.000 (87.905) Prec@5 100.000 (99.222) +2022-11-14 15:52:21,360 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0743) Prec@1 92.000 (87.969) Prec@5 100.000 (99.234) +2022-11-14 15:52:21,375 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0747) Prec@1 86.000 (87.938) Prec@5 100.000 (99.246) +2022-11-14 15:52:21,392 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0750) Prec@1 82.000 (87.848) Prec@5 99.000 (99.242) +2022-11-14 15:52:21,410 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0328 (0.0744) Prec@1 95.000 (87.955) Prec@5 100.000 (99.254) +2022-11-14 15:52:21,427 Test: [67/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0743) Prec@1 89.000 (87.971) Prec@5 100.000 (99.265) +2022-11-14 15:52:21,443 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0740) Prec@1 91.000 (88.014) Prec@5 99.000 (99.261) +2022-11-14 15:52:21,459 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0741) Prec@1 85.000 (87.971) Prec@5 99.000 (99.257) +2022-11-14 15:52:21,471 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0745) Prec@1 86.000 (87.944) Prec@5 98.000 (99.239) +2022-11-14 15:52:21,489 Test: [71/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0741) Prec@1 93.000 (88.014) Prec@5 100.000 (99.250) +2022-11-14 15:52:21,507 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0438 (0.0737) Prec@1 93.000 (88.082) Prec@5 100.000 (99.260) +2022-11-14 15:52:21,524 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0317 (0.0732) Prec@1 93.000 (88.149) Prec@5 100.000 (99.270) +2022-11-14 15:52:21,541 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0735) Prec@1 82.000 (88.067) Prec@5 99.000 (99.267) +2022-11-14 15:52:21,558 Test: [75/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0736) Prec@1 88.000 (88.066) Prec@5 100.000 (99.276) +2022-11-14 15:52:21,573 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0735) Prec@1 88.000 (88.065) Prec@5 98.000 (99.260) +2022-11-14 15:52:21,590 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0737) Prec@1 86.000 (88.038) Prec@5 100.000 (99.269) +2022-11-14 15:52:21,609 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0737) Prec@1 87.000 (88.025) Prec@5 99.000 (99.266) +2022-11-14 15:52:21,625 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0738) Prec@1 87.000 (88.013) Prec@5 100.000 (99.275) +2022-11-14 15:52:21,641 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0739) Prec@1 87.000 (88.000) Prec@5 97.000 (99.247) +2022-11-14 15:52:21,657 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0741) Prec@1 83.000 (87.939) Prec@5 100.000 (99.256) +2022-11-14 15:52:21,670 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0742) Prec@1 85.000 (87.904) Prec@5 99.000 (99.253) +2022-11-14 15:52:21,686 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0742) Prec@1 88.000 (87.905) Prec@5 99.000 (99.250) +2022-11-14 15:52:21,700 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0746) Prec@1 81.000 (87.824) Prec@5 98.000 (99.235) +2022-11-14 15:52:21,715 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0748) Prec@1 85.000 (87.791) Prec@5 100.000 (99.244) +2022-11-14 15:52:21,728 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0747) Prec@1 91.000 (87.828) Prec@5 100.000 (99.253) +2022-11-14 15:52:21,744 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0745) Prec@1 90.000 (87.852) Prec@5 99.000 (99.250) +2022-11-14 15:52:21,763 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0745) Prec@1 87.000 (87.843) Prec@5 98.000 (99.236) +2022-11-14 15:52:21,779 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0745) Prec@1 88.000 (87.844) Prec@5 100.000 (99.244) +2022-11-14 15:52:21,796 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0743) Prec@1 89.000 (87.857) Prec@5 100.000 (99.253) +2022-11-14 15:52:21,812 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0386 (0.0739) Prec@1 95.000 (87.935) Prec@5 100.000 (99.261) +2022-11-14 15:52:21,831 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0740) Prec@1 86.000 (87.914) Prec@5 100.000 (99.269) +2022-11-14 15:52:21,849 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0739) Prec@1 89.000 (87.926) Prec@5 100.000 (99.277) +2022-11-14 15:52:21,864 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0739) Prec@1 89.000 (87.937) Prec@5 99.000 (99.274) +2022-11-14 15:52:21,878 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0737) Prec@1 92.000 (87.979) Prec@5 100.000 (99.281) +2022-11-14 15:52:21,892 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0459 (0.0734) Prec@1 93.000 (88.031) Prec@5 99.000 (99.278) +2022-11-14 15:52:21,906 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0735) Prec@1 88.000 (88.031) Prec@5 98.000 (99.265) +2022-11-14 15:52:21,920 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0738) Prec@1 85.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 15:52:21,936 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0739) Prec@1 87.000 (87.990) Prec@5 100.000 (99.280) +2022-11-14 15:52:22,016 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:52:22,408 Epoch: [274][0/500] Time 0.026 (0.026) Data 0.245 (0.245) Loss 0.0456 (0.0456) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:22,700 Epoch: [274][10/500] Time 0.026 (0.026) Data 0.002 (0.024) Loss 0.0268 (0.0362) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:52:22,987 Epoch: [274][20/500] Time 0.027 (0.026) Data 0.002 (0.013) Loss 0.0264 (0.0329) Prec@1 97.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 15:52:23,293 Epoch: [274][30/500] Time 0.028 (0.026) Data 0.002 (0.010) Loss 0.0285 (0.0318) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:23,792 Epoch: [274][40/500] Time 0.044 (0.030) Data 0.002 (0.008) Loss 0.0371 (0.0329) Prec@1 94.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 15:52:24,363 Epoch: [274][50/500] Time 0.069 (0.034) Data 0.002 (0.007) Loss 0.0446 (0.0348) Prec@1 94.000 (94.667) Prec@5 99.000 (99.833) +2022-11-14 15:52:24,883 Epoch: [274][60/500] Time 0.049 (0.036) Data 0.002 (0.006) Loss 0.0183 (0.0325) Prec@1 97.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 15:52:25,469 Epoch: [274][70/500] Time 0.067 (0.039) Data 0.002 (0.005) Loss 0.0272 (0.0318) Prec@1 96.000 (95.125) Prec@5 99.000 (99.750) +2022-11-14 15:52:25,991 Epoch: [274][80/500] Time 0.051 (0.039) Data 0.002 (0.005) Loss 0.0363 (0.0323) Prec@1 93.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 15:52:26,526 Epoch: [274][90/500] Time 0.043 (0.040) Data 0.002 (0.005) Loss 0.0440 (0.0335) Prec@1 92.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 15:52:27,061 Epoch: [274][100/500] Time 0.049 (0.041) Data 0.002 (0.004) Loss 0.0391 (0.0340) Prec@1 93.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 15:52:27,585 Epoch: [274][110/500] Time 0.040 (0.042) Data 0.002 (0.004) Loss 0.0217 (0.0330) Prec@1 96.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 15:52:28,131 Epoch: [274][120/500] Time 0.053 (0.042) Data 0.002 (0.004) Loss 0.0186 (0.0319) Prec@1 97.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 15:52:28,701 Epoch: [274][130/500] Time 0.039 (0.043) Data 0.002 (0.004) Loss 0.0144 (0.0306) Prec@1 99.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 15:52:29,256 Epoch: [274][140/500] Time 0.048 (0.043) Data 0.003 (0.004) Loss 0.0326 (0.0307) Prec@1 96.000 (95.133) Prec@5 100.000 (99.867) +2022-11-14 15:52:29,793 Epoch: [274][150/500] Time 0.052 (0.044) Data 0.002 (0.004) Loss 0.0454 (0.0317) Prec@1 92.000 (94.938) Prec@5 100.000 (99.875) +2022-11-14 15:52:30,394 Epoch: [274][160/500] Time 0.059 (0.044) Data 0.002 (0.004) Loss 0.0297 (0.0315) Prec@1 96.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 15:52:30,984 Epoch: [274][170/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0483 (0.0325) Prec@1 93.000 (94.889) Prec@5 99.000 (99.833) +2022-11-14 15:52:31,609 Epoch: [274][180/500] Time 0.059 (0.045) Data 0.003 (0.003) Loss 0.0171 (0.0317) Prec@1 98.000 (95.053) Prec@5 100.000 (99.842) +2022-11-14 15:52:32,168 Epoch: [274][190/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0561 (0.0329) Prec@1 90.000 (94.800) Prec@5 100.000 (99.850) +2022-11-14 15:52:32,710 Epoch: [274][200/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0380 (0.0331) Prec@1 95.000 (94.810) Prec@5 99.000 (99.810) +2022-11-14 15:52:33,321 Epoch: [274][210/500] Time 0.062 (0.046) Data 0.002 (0.003) Loss 0.0375 (0.0333) Prec@1 93.000 (94.727) Prec@5 100.000 (99.818) +2022-11-14 15:52:33,971 Epoch: [274][220/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0122 (0.0324) Prec@1 98.000 (94.870) Prec@5 99.000 (99.783) +2022-11-14 15:52:34,535 Epoch: [274][230/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0320 (0.0324) Prec@1 94.000 (94.833) Prec@5 100.000 (99.792) +2022-11-14 15:52:35,115 Epoch: [274][240/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0236 (0.0320) Prec@1 96.000 (94.880) Prec@5 100.000 (99.800) +2022-11-14 15:52:35,663 Epoch: [274][250/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0654 (0.0333) Prec@1 89.000 (94.654) Prec@5 100.000 (99.808) +2022-11-14 15:52:36,244 Epoch: [274][260/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0245 (0.0330) Prec@1 98.000 (94.778) Prec@5 99.000 (99.778) +2022-11-14 15:52:36,763 Epoch: [274][270/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0600 (0.0340) Prec@1 91.000 (94.643) Prec@5 99.000 (99.750) +2022-11-14 15:52:37,367 Epoch: [274][280/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0423 (0.0343) Prec@1 91.000 (94.517) Prec@5 99.000 (99.724) +2022-11-14 15:52:37,909 Epoch: [274][290/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0268 (0.0340) Prec@1 95.000 (94.533) Prec@5 100.000 (99.733) +2022-11-14 15:52:38,431 Epoch: [274][300/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0503 (0.0345) Prec@1 92.000 (94.452) Prec@5 100.000 (99.742) +2022-11-14 15:52:38,949 Epoch: [274][310/500] Time 0.057 (0.048) Data 0.003 (0.003) Loss 0.0658 (0.0355) Prec@1 90.000 (94.312) Prec@5 100.000 (99.750) +2022-11-14 15:52:39,476 Epoch: [274][320/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0203 (0.0351) Prec@1 96.000 (94.364) Prec@5 100.000 (99.758) +2022-11-14 15:52:39,992 Epoch: [274][330/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0500 (0.0355) Prec@1 91.000 (94.265) Prec@5 99.000 (99.735) +2022-11-14 15:52:40,558 Epoch: [274][340/500] Time 0.067 (0.048) Data 0.002 (0.003) Loss 0.0297 (0.0353) Prec@1 95.000 (94.286) Prec@5 100.000 (99.743) +2022-11-14 15:52:41,077 Epoch: [274][350/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0236 (0.0350) Prec@1 97.000 (94.361) Prec@5 100.000 (99.750) +2022-11-14 15:52:41,626 Epoch: [274][360/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0238 (0.0347) Prec@1 97.000 (94.432) Prec@5 100.000 (99.757) +2022-11-14 15:52:42,147 Epoch: [274][370/500] Time 0.045 (0.047) Data 0.003 (0.003) Loss 0.0456 (0.0350) Prec@1 93.000 (94.395) Prec@5 100.000 (99.763) +2022-11-14 15:52:42,712 Epoch: [274][380/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0265 (0.0348) Prec@1 97.000 (94.462) Prec@5 99.000 (99.744) +2022-11-14 15:52:43,241 Epoch: [274][390/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0381 (0.0349) Prec@1 93.000 (94.425) Prec@5 100.000 (99.750) +2022-11-14 15:52:43,757 Epoch: [274][400/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0193 (0.0345) Prec@1 98.000 (94.512) Prec@5 100.000 (99.756) +2022-11-14 15:52:44,284 Epoch: [274][410/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0309 (0.0344) Prec@1 95.000 (94.524) Prec@5 100.000 (99.762) +2022-11-14 15:52:44,796 Epoch: [274][420/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0348 (0.0344) Prec@1 94.000 (94.512) Prec@5 99.000 (99.744) +2022-11-14 15:52:45,312 Epoch: [274][430/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0264 (0.0342) Prec@1 97.000 (94.568) Prec@5 100.000 (99.750) +2022-11-14 15:52:45,837 Epoch: [274][440/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0197 (0.0339) Prec@1 97.000 (94.622) Prec@5 100.000 (99.756) +2022-11-14 15:52:46,367 Epoch: [274][450/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0410 (0.0340) Prec@1 94.000 (94.609) Prec@5 99.000 (99.739) +2022-11-14 15:52:46,884 Epoch: [274][460/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0365 (0.0341) Prec@1 94.000 (94.596) Prec@5 100.000 (99.745) +2022-11-14 15:52:47,464 Epoch: [274][470/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0360 (0.0341) Prec@1 94.000 (94.583) Prec@5 100.000 (99.750) +2022-11-14 15:52:47,985 Epoch: [274][480/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0558 (0.0346) Prec@1 92.000 (94.531) Prec@5 97.000 (99.694) +2022-11-14 15:52:48,537 Epoch: [274][490/500] Time 0.050 (0.048) Data 0.003 (0.003) Loss 0.0086 (0.0341) Prec@1 99.000 (94.620) Prec@5 100.000 (99.700) +2022-11-14 15:52:49,007 Epoch: [274][499/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0220 (0.0338) Prec@1 97.000 (94.667) Prec@5 100.000 (99.706) +2022-11-14 15:52:49,312 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0655 (0.0655) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:49,322 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0636) Prec@1 89.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 15:52:49,331 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0621) Prec@1 88.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 15:52:49,343 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0648) Prec@1 87.000 (88.000) Prec@5 100.000 (99.750) +2022-11-14 15:52:49,351 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0638) Prec@1 90.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 15:52:49,359 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0603) Prec@1 94.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 15:52:49,369 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0596) Prec@1 90.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 15:52:49,380 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0627) Prec@1 84.000 (88.750) Prec@5 99.000 (99.625) +2022-11-14 15:52:49,390 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0649) Prec@1 88.000 (88.667) Prec@5 98.000 (99.444) +2022-11-14 15:52:49,399 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0666) Prec@1 87.000 (88.500) Prec@5 99.000 (99.400) +2022-11-14 15:52:49,409 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0659) Prec@1 90.000 (88.636) Prec@5 100.000 (99.455) +2022-11-14 15:52:49,420 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0683) Prec@1 85.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 15:52:49,431 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0674) Prec@1 90.000 (88.462) Prec@5 100.000 (99.538) +2022-11-14 15:52:49,442 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0672) Prec@1 89.000 (88.500) Prec@5 100.000 (99.571) +2022-11-14 15:52:49,453 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0686) Prec@1 88.000 (88.467) Prec@5 99.000 (99.533) +2022-11-14 15:52:49,462 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0694) Prec@1 87.000 (88.375) Prec@5 100.000 (99.562) +2022-11-14 15:52:49,472 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0683) Prec@1 92.000 (88.588) Prec@5 98.000 (99.471) +2022-11-14 15:52:49,481 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1140 (0.0709) Prec@1 83.000 (88.278) Prec@5 100.000 (99.500) +2022-11-14 15:52:49,491 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0725) Prec@1 85.000 (88.105) Prec@5 100.000 (99.526) +2022-11-14 15:52:49,502 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0735) Prec@1 86.000 (88.000) Prec@5 98.000 (99.450) +2022-11-14 15:52:49,514 Test: [20/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0740) Prec@1 85.000 (87.857) Prec@5 99.000 (99.429) +2022-11-14 15:52:49,526 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0737) Prec@1 91.000 (88.000) Prec@5 99.000 (99.409) +2022-11-14 15:52:49,537 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0747) Prec@1 83.000 (87.783) Prec@5 98.000 (99.348) +2022-11-14 15:52:49,548 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0743) Prec@1 91.000 (87.917) Prec@5 99.000 (99.333) +2022-11-14 15:52:49,561 Test: [24/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0750) Prec@1 86.000 (87.840) Prec@5 100.000 (99.360) +2022-11-14 15:52:49,572 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0755) Prec@1 88.000 (87.846) Prec@5 99.000 (99.346) +2022-11-14 15:52:49,583 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0750) Prec@1 91.000 (87.963) Prec@5 100.000 (99.370) +2022-11-14 15:52:49,593 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0742) Prec@1 92.000 (88.107) Prec@5 100.000 (99.393) +2022-11-14 15:52:49,606 Test: [28/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0744) Prec@1 87.000 (88.069) Prec@5 98.000 (99.345) +2022-11-14 15:52:49,618 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0746) Prec@1 85.000 (87.967) Prec@5 99.000 (99.333) +2022-11-14 15:52:49,629 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0743) Prec@1 89.000 (88.000) Prec@5 100.000 (99.355) +2022-11-14 15:52:49,640 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0750) Prec@1 85.000 (87.906) Prec@5 99.000 (99.344) +2022-11-14 15:52:49,652 Test: [32/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0744) Prec@1 90.000 (87.970) Prec@5 100.000 (99.364) +2022-11-14 15:52:49,664 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0746) Prec@1 86.000 (87.912) Prec@5 98.000 (99.324) +2022-11-14 15:52:49,675 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0749) Prec@1 86.000 (87.857) Prec@5 98.000 (99.286) +2022-11-14 15:52:49,684 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0743) Prec@1 91.000 (87.944) Prec@5 100.000 (99.306) +2022-11-14 15:52:49,698 Test: [36/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0742) Prec@1 90.000 (88.000) Prec@5 98.000 (99.270) +2022-11-14 15:52:49,710 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0747) Prec@1 87.000 (87.974) Prec@5 99.000 (99.263) +2022-11-14 15:52:49,722 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0744) Prec@1 93.000 (88.103) Prec@5 99.000 (99.256) +2022-11-14 15:52:49,735 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0741) Prec@1 91.000 (88.175) Prec@5 99.000 (99.250) +2022-11-14 15:52:49,747 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0745) Prec@1 84.000 (88.073) Prec@5 99.000 (99.244) +2022-11-14 15:52:49,758 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0747) Prec@1 87.000 (88.048) Prec@5 99.000 (99.238) +2022-11-14 15:52:49,769 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0742) Prec@1 93.000 (88.163) Prec@5 100.000 (99.256) +2022-11-14 15:52:49,783 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0743) Prec@1 88.000 (88.159) Prec@5 99.000 (99.250) +2022-11-14 15:52:49,795 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0745) Prec@1 85.000 (88.089) Prec@5 99.000 (99.244) +2022-11-14 15:52:49,807 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0750) Prec@1 84.000 (88.000) Prec@5 98.000 (99.217) +2022-11-14 15:52:49,821 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0456 (0.0744) Prec@1 93.000 (88.106) Prec@5 100.000 (99.234) +2022-11-14 15:52:49,833 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1151 (0.0752) Prec@1 83.000 (88.000) Prec@5 98.000 (99.208) +2022-11-14 15:52:49,847 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0749) Prec@1 90.000 (88.041) Prec@5 100.000 (99.224) +2022-11-14 15:52:49,860 Test: [49/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0753) Prec@1 85.000 (87.980) Prec@5 100.000 (99.240) +2022-11-14 15:52:49,871 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0751) Prec@1 89.000 (88.000) Prec@5 100.000 (99.255) +2022-11-14 15:52:49,884 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0750) Prec@1 89.000 (88.019) Prec@5 99.000 (99.250) +2022-11-14 15:52:49,895 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0750) Prec@1 86.000 (87.981) Prec@5 100.000 (99.264) +2022-11-14 15:52:49,908 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0745) Prec@1 89.000 (88.000) Prec@5 100.000 (99.278) +2022-11-14 15:52:49,921 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0749) Prec@1 85.000 (87.945) Prec@5 100.000 (99.291) +2022-11-14 15:52:49,933 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0747) Prec@1 90.000 (87.982) Prec@5 99.000 (99.286) +2022-11-14 15:52:49,945 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0749) Prec@1 87.000 (87.965) Prec@5 100.000 (99.298) +2022-11-14 15:52:49,958 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0751) Prec@1 86.000 (87.931) Prec@5 100.000 (99.310) +2022-11-14 15:52:49,971 Test: [58/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0754) Prec@1 84.000 (87.864) Prec@5 100.000 (99.322) +2022-11-14 15:52:49,987 Test: [59/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0760) Prec@1 82.000 (87.767) Prec@5 99.000 (99.317) +2022-11-14 15:52:50,000 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0761) Prec@1 88.000 (87.770) Prec@5 99.000 (99.311) +2022-11-14 15:52:50,015 Test: [61/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0763) Prec@1 86.000 (87.742) Prec@5 99.000 (99.306) +2022-11-14 15:52:50,028 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0762) Prec@1 89.000 (87.762) Prec@5 100.000 (99.317) +2022-11-14 15:52:50,041 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0758) Prec@1 93.000 (87.844) Prec@5 100.000 (99.328) +2022-11-14 15:52:50,053 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0762) Prec@1 83.000 (87.769) Prec@5 99.000 (99.323) +2022-11-14 15:52:50,069 Test: [65/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0761) Prec@1 87.000 (87.758) Prec@5 100.000 (99.333) +2022-11-14 15:52:50,084 Test: [66/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0354 (0.0755) Prec@1 94.000 (87.851) Prec@5 100.000 (99.343) +2022-11-14 15:52:50,096 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0757) Prec@1 85.000 (87.809) Prec@5 98.000 (99.324) +2022-11-14 15:52:50,108 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0757) Prec@1 89.000 (87.826) Prec@5 99.000 (99.319) +2022-11-14 15:52:50,120 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0758) Prec@1 88.000 (87.829) Prec@5 98.000 (99.300) +2022-11-14 15:52:50,132 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1167 (0.0764) Prec@1 81.000 (87.732) Prec@5 98.000 (99.282) +2022-11-14 15:52:50,144 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0764) Prec@1 86.000 (87.708) Prec@5 100.000 (99.292) +2022-11-14 15:52:50,155 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0378 (0.0758) Prec@1 95.000 (87.808) Prec@5 100.000 (99.301) +2022-11-14 15:52:50,170 Test: [73/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0412 (0.0754) Prec@1 92.000 (87.865) Prec@5 100.000 (99.311) +2022-11-14 15:52:50,184 Test: [74/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1073 (0.0758) Prec@1 80.000 (87.760) Prec@5 99.000 (99.307) +2022-11-14 15:52:50,195 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0756) Prec@1 90.000 (87.789) Prec@5 99.000 (99.303) +2022-11-14 15:52:50,206 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0756) Prec@1 89.000 (87.805) Prec@5 98.000 (99.286) +2022-11-14 15:52:50,216 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0756) Prec@1 88.000 (87.808) Prec@5 99.000 (99.282) +2022-11-14 15:52:50,227 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0756) Prec@1 89.000 (87.823) Prec@5 99.000 (99.278) +2022-11-14 15:52:50,239 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0755) Prec@1 88.000 (87.825) Prec@5 100.000 (99.287) +2022-11-14 15:52:50,250 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0758) Prec@1 83.000 (87.765) Prec@5 99.000 (99.284) +2022-11-14 15:52:50,260 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0761) Prec@1 85.000 (87.732) Prec@5 99.000 (99.280) +2022-11-14 15:52:50,270 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0761) Prec@1 88.000 (87.735) Prec@5 99.000 (99.277) +2022-11-14 15:52:50,280 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0760) Prec@1 90.000 (87.762) Prec@5 100.000 (99.286) +2022-11-14 15:52:50,292 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0761) Prec@1 85.000 (87.729) Prec@5 100.000 (99.294) +2022-11-14 15:52:50,304 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0764) Prec@1 85.000 (87.698) Prec@5 99.000 (99.291) +2022-11-14 15:52:50,314 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0767) Prec@1 83.000 (87.644) Prec@5 99.000 (99.287) +2022-11-14 15:52:50,325 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0766) Prec@1 88.000 (87.648) Prec@5 98.000 (99.273) +2022-11-14 15:52:50,336 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0767) Prec@1 85.000 (87.618) Prec@5 100.000 (99.281) +2022-11-14 15:52:50,346 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0766) Prec@1 89.000 (87.633) Prec@5 98.000 (99.267) +2022-11-14 15:52:50,356 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0764) Prec@1 91.000 (87.670) Prec@5 100.000 (99.275) +2022-11-14 15:52:50,366 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0761) Prec@1 92.000 (87.717) Prec@5 100.000 (99.283) +2022-11-14 15:52:50,377 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0761) Prec@1 87.000 (87.710) Prec@5 100.000 (99.290) +2022-11-14 15:52:50,388 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0761) Prec@1 87.000 (87.702) Prec@5 100.000 (99.298) +2022-11-14 15:52:50,398 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0761) Prec@1 87.000 (87.695) Prec@5 99.000 (99.295) +2022-11-14 15:52:50,408 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0760) Prec@1 93.000 (87.750) Prec@5 98.000 (99.281) +2022-11-14 15:52:50,419 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0434 (0.0757) Prec@1 91.000 (87.784) Prec@5 99.000 (99.278) +2022-11-14 15:52:50,429 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0758) Prec@1 88.000 (87.786) Prec@5 98.000 (99.265) +2022-11-14 15:52:50,440 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0759) Prec@1 88.000 (87.788) Prec@5 98.000 (99.253) +2022-11-14 15:52:50,450 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0758) Prec@1 88.000 (87.790) Prec@5 99.000 (99.250) +2022-11-14 15:52:50,510 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:52:50,855 Epoch: [275][0/500] Time 0.023 (0.023) Data 0.255 (0.255) Loss 0.0505 (0.0505) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:51,143 Epoch: [275][10/500] Time 0.034 (0.026) Data 0.003 (0.025) Loss 0.0299 (0.0402) Prec@1 95.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:52:51,494 Epoch: [275][20/500] Time 0.025 (0.029) Data 0.002 (0.014) Loss 0.0649 (0.0484) Prec@1 87.000 (91.000) Prec@5 99.000 (99.667) +2022-11-14 15:52:51,990 Epoch: [275][30/500] Time 0.053 (0.033) Data 0.002 (0.010) Loss 0.0353 (0.0451) Prec@1 94.000 (91.750) Prec@5 100.000 (99.750) +2022-11-14 15:52:52,572 Epoch: [275][40/500] Time 0.043 (0.038) Data 0.002 (0.008) Loss 0.0410 (0.0443) Prec@1 91.000 (91.600) Prec@5 100.000 (99.800) +2022-11-14 15:52:53,124 Epoch: [275][50/500] Time 0.041 (0.040) Data 0.002 (0.007) Loss 0.0292 (0.0418) Prec@1 95.000 (92.167) Prec@5 100.000 (99.833) +2022-11-14 15:52:53,652 Epoch: [275][60/500] Time 0.043 (0.041) Data 0.002 (0.006) Loss 0.0096 (0.0372) Prec@1 100.000 (93.286) Prec@5 100.000 (99.857) +2022-11-14 15:52:54,228 Epoch: [275][70/500] Time 0.057 (0.042) Data 0.002 (0.006) Loss 0.0441 (0.0380) Prec@1 92.000 (93.125) Prec@5 100.000 (99.875) +2022-11-14 15:52:54,819 Epoch: [275][80/500] Time 0.040 (0.044) Data 0.003 (0.005) Loss 0.0426 (0.0386) Prec@1 94.000 (93.222) Prec@5 99.000 (99.778) +2022-11-14 15:52:55,453 Epoch: [275][90/500] Time 0.081 (0.045) Data 0.002 (0.005) Loss 0.0185 (0.0366) Prec@1 98.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 15:52:56,008 Epoch: [275][100/500] Time 0.076 (0.045) Data 0.002 (0.005) Loss 0.0316 (0.0361) Prec@1 94.000 (93.727) Prec@5 100.000 (99.818) +2022-11-14 15:52:56,552 Epoch: [275][110/500] Time 0.062 (0.045) Data 0.002 (0.004) Loss 0.0331 (0.0358) Prec@1 94.000 (93.750) Prec@5 100.000 (99.833) +2022-11-14 15:52:57,100 Epoch: [275][120/500] Time 0.059 (0.045) Data 0.002 (0.004) Loss 0.0282 (0.0353) Prec@1 97.000 (94.000) Prec@5 100.000 (99.846) +2022-11-14 15:52:57,626 Epoch: [275][130/500] Time 0.052 (0.046) Data 0.002 (0.004) Loss 0.0449 (0.0359) Prec@1 90.000 (93.714) Prec@5 100.000 (99.857) +2022-11-14 15:52:58,161 Epoch: [275][140/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0270 (0.0353) Prec@1 94.000 (93.733) Prec@5 100.000 (99.867) +2022-11-14 15:52:58,755 Epoch: [275][150/500] Time 0.062 (0.046) Data 0.002 (0.004) Loss 0.0336 (0.0352) Prec@1 95.000 (93.812) Prec@5 100.000 (99.875) +2022-11-14 15:52:59,285 Epoch: [275][160/500] Time 0.047 (0.046) Data 0.002 (0.004) Loss 0.0371 (0.0353) Prec@1 94.000 (93.824) Prec@5 99.000 (99.824) +2022-11-14 15:52:59,880 Epoch: [275][170/500] Time 0.055 (0.047) Data 0.002 (0.004) Loss 0.0310 (0.0351) Prec@1 96.000 (93.944) Prec@5 99.000 (99.778) +2022-11-14 15:53:00,409 Epoch: [275][180/500] Time 0.053 (0.047) Data 0.002 (0.004) Loss 0.0281 (0.0347) Prec@1 93.000 (93.895) Prec@5 100.000 (99.789) +2022-11-14 15:53:00,941 Epoch: [275][190/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0395 (0.0350) Prec@1 92.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 15:53:01,505 Epoch: [275][200/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0407 (0.0352) Prec@1 92.000 (93.714) Prec@5 99.000 (99.762) +2022-11-14 15:53:02,028 Epoch: [275][210/500] Time 0.054 (0.047) Data 0.003 (0.003) Loss 0.0337 (0.0352) Prec@1 96.000 (93.818) Prec@5 100.000 (99.773) +2022-11-14 15:53:02,557 Epoch: [275][220/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0576 (0.0362) Prec@1 90.000 (93.652) Prec@5 100.000 (99.783) +2022-11-14 15:53:03,104 Epoch: [275][230/500] Time 0.082 (0.047) Data 0.002 (0.003) Loss 0.0322 (0.0360) Prec@1 95.000 (93.708) Prec@5 100.000 (99.792) +2022-11-14 15:53:03,671 Epoch: [275][240/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0301 (0.0358) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 15:53:04,187 Epoch: [275][250/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0173 (0.0350) Prec@1 96.000 (93.885) Prec@5 100.000 (99.808) +2022-11-14 15:53:04,723 Epoch: [275][260/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0343 (0.0350) Prec@1 94.000 (93.889) Prec@5 99.000 (99.778) +2022-11-14 15:53:05,248 Epoch: [275][270/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0366 (0.0351) Prec@1 93.000 (93.857) Prec@5 99.000 (99.750) +2022-11-14 15:53:05,786 Epoch: [275][280/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0512 (0.0356) Prec@1 92.000 (93.793) Prec@5 100.000 (99.759) +2022-11-14 15:53:06,348 Epoch: [275][290/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0455 (0.0360) Prec@1 91.000 (93.700) Prec@5 100.000 (99.767) +2022-11-14 15:53:06,877 Epoch: [275][300/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0520 (0.0365) Prec@1 92.000 (93.645) Prec@5 100.000 (99.774) +2022-11-14 15:53:07,465 Epoch: [275][310/500] Time 0.084 (0.048) Data 0.002 (0.003) Loss 0.0361 (0.0365) Prec@1 92.000 (93.594) Prec@5 100.000 (99.781) +2022-11-14 15:53:07,993 Epoch: [275][320/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0611 (0.0372) Prec@1 89.000 (93.455) Prec@5 100.000 (99.788) +2022-11-14 15:53:08,576 Epoch: [275][330/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0273 (0.0369) Prec@1 95.000 (93.500) Prec@5 100.000 (99.794) +2022-11-14 15:53:09,151 Epoch: [275][340/500] Time 0.063 (0.048) Data 0.002 (0.003) Loss 0.0348 (0.0369) Prec@1 93.000 (93.486) Prec@5 100.000 (99.800) +2022-11-14 15:53:09,726 Epoch: [275][350/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0420 (0.0370) Prec@1 93.000 (93.472) Prec@5 100.000 (99.806) +2022-11-14 15:53:10,257 Epoch: [275][360/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0272 (0.0367) Prec@1 96.000 (93.541) Prec@5 100.000 (99.811) +2022-11-14 15:53:10,793 Epoch: [275][370/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0464 (0.0370) Prec@1 93.000 (93.526) Prec@5 100.000 (99.816) +2022-11-14 15:53:11,324 Epoch: [275][380/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0459 (0.0372) Prec@1 91.000 (93.462) Prec@5 99.000 (99.795) +2022-11-14 15:53:11,844 Epoch: [275][390/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0450 (0.0374) Prec@1 91.000 (93.400) Prec@5 99.000 (99.775) +2022-11-14 15:53:12,376 Epoch: [275][400/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0155 (0.0369) Prec@1 97.000 (93.488) Prec@5 100.000 (99.780) +2022-11-14 15:53:12,894 Epoch: [275][410/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0413 (0.0370) Prec@1 94.000 (93.500) Prec@5 98.000 (99.738) +2022-11-14 15:53:13,410 Epoch: [275][420/500] Time 0.048 (0.048) Data 0.003 (0.003) Loss 0.0419 (0.0371) Prec@1 93.000 (93.488) Prec@5 100.000 (99.744) +2022-11-14 15:53:13,924 Epoch: [275][430/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0387 (0.0371) Prec@1 92.000 (93.455) Prec@5 99.000 (99.727) +2022-11-14 15:53:14,507 Epoch: [275][440/500] Time 0.044 (0.048) Data 0.003 (0.003) Loss 0.0340 (0.0371) Prec@1 95.000 (93.489) Prec@5 100.000 (99.733) +2022-11-14 15:53:15,059 Epoch: [275][450/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0249 (0.0368) Prec@1 97.000 (93.565) Prec@5 100.000 (99.739) +2022-11-14 15:53:15,596 Epoch: [275][460/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0291 (0.0366) Prec@1 94.000 (93.574) Prec@5 100.000 (99.745) +2022-11-14 15:53:16,144 Epoch: [275][470/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0420 (0.0368) Prec@1 92.000 (93.542) Prec@5 100.000 (99.750) +2022-11-14 15:53:16,678 Epoch: [275][480/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0286 (0.0366) Prec@1 94.000 (93.551) Prec@5 100.000 (99.755) +2022-11-14 15:53:17,233 Epoch: [275][490/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0366 (0.0366) Prec@1 93.000 (93.540) Prec@5 100.000 (99.760) +2022-11-14 15:53:17,747 Epoch: [275][499/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0341 (0.0365) Prec@1 95.000 (93.569) Prec@5 99.000 (99.745) +2022-11-14 15:53:18,063 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0778 (0.0778) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:18,074 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0708 (0.0743) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 15:53:18,086 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0719) Prec@1 88.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 15:53:18,103 Test: [3/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0618 (0.0694) Prec@1 91.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 15:53:18,116 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0809 (0.0717) Prec@1 87.000 (88.200) Prec@5 99.000 (99.600) +2022-11-14 15:53:18,129 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0493 (0.0680) Prec@1 91.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 15:53:18,141 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0680) Prec@1 91.000 (89.000) Prec@5 100.000 (99.714) +2022-11-14 15:53:18,155 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0596 (0.0669) Prec@1 90.000 (89.125) Prec@5 99.000 (99.625) +2022-11-14 15:53:18,168 Test: [8/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0693) Prec@1 87.000 (88.889) Prec@5 100.000 (99.667) +2022-11-14 15:53:18,179 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0701) Prec@1 88.000 (88.800) Prec@5 98.000 (99.500) +2022-11-14 15:53:18,189 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0511 (0.0684) Prec@1 91.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 15:53:18,198 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0703) Prec@1 85.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 15:53:18,212 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0399 (0.0679) Prec@1 93.000 (89.000) Prec@5 100.000 (99.538) +2022-11-14 15:53:18,224 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0685) Prec@1 88.000 (88.929) Prec@5 99.000 (99.500) +2022-11-14 15:53:18,234 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0685) Prec@1 88.000 (88.867) Prec@5 99.000 (99.467) +2022-11-14 15:53:18,245 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.0709) Prec@1 80.000 (88.312) Prec@5 100.000 (99.500) +2022-11-14 15:53:18,260 Test: [16/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0578 (0.0702) Prec@1 89.000 (88.353) Prec@5 99.000 (99.471) +2022-11-14 15:53:18,272 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1020 (0.0719) Prec@1 83.000 (88.056) Prec@5 100.000 (99.500) +2022-11-14 15:53:18,281 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0716) Prec@1 88.000 (88.053) Prec@5 98.000 (99.421) +2022-11-14 15:53:18,292 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.0730) Prec@1 85.000 (87.900) Prec@5 97.000 (99.300) +2022-11-14 15:53:18,306 Test: [20/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.0737) Prec@1 86.000 (87.810) Prec@5 100.000 (99.333) +2022-11-14 15:53:18,318 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.0739) Prec@1 90.000 (87.909) Prec@5 99.000 (99.318) +2022-11-14 15:53:18,328 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1012 (0.0751) Prec@1 84.000 (87.739) Prec@5 98.000 (99.261) +2022-11-14 15:53:18,337 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0908 (0.0757) Prec@1 85.000 (87.625) Prec@5 100.000 (99.292) +2022-11-14 15:53:18,349 Test: [24/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0760) Prec@1 88.000 (87.640) Prec@5 100.000 (99.320) +2022-11-14 15:53:18,363 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0996 (0.0769) Prec@1 83.000 (87.462) Prec@5 98.000 (99.269) +2022-11-14 15:53:18,373 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0769) Prec@1 88.000 (87.481) Prec@5 99.000 (99.259) +2022-11-14 15:53:18,385 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0767) Prec@1 87.000 (87.464) Prec@5 99.000 (99.250) +2022-11-14 15:53:18,399 Test: [28/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0763) Prec@1 87.000 (87.448) Prec@5 99.000 (99.241) +2022-11-14 15:53:18,412 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0762) Prec@1 87.000 (87.433) Prec@5 100.000 (99.267) +2022-11-14 15:53:18,424 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0630 (0.0758) Prec@1 88.000 (87.452) Prec@5 100.000 (99.290) +2022-11-14 15:53:18,434 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0626 (0.0754) Prec@1 91.000 (87.562) Prec@5 99.000 (99.281) +2022-11-14 15:53:18,444 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0752) Prec@1 89.000 (87.606) Prec@5 99.000 (99.273) +2022-11-14 15:53:18,454 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0975 (0.0758) Prec@1 83.000 (87.471) Prec@5 99.000 (99.265) +2022-11-14 15:53:18,465 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0757) Prec@1 88.000 (87.486) Prec@5 98.000 (99.229) +2022-11-14 15:53:18,477 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0758) Prec@1 89.000 (87.528) Prec@5 99.000 (99.222) +2022-11-14 15:53:18,489 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0759) Prec@1 86.000 (87.486) Prec@5 99.000 (99.216) +2022-11-14 15:53:18,501 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0768) Prec@1 83.000 (87.368) Prec@5 100.000 (99.237) +2022-11-14 15:53:18,512 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0762) Prec@1 93.000 (87.513) Prec@5 99.000 (99.231) +2022-11-14 15:53:18,522 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0759) Prec@1 90.000 (87.575) Prec@5 99.000 (99.225) +2022-11-14 15:53:18,532 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0766) Prec@1 83.000 (87.463) Prec@5 99.000 (99.220) +2022-11-14 15:53:18,544 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0764) Prec@1 91.000 (87.548) Prec@5 98.000 (99.190) +2022-11-14 15:53:18,554 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0759) Prec@1 91.000 (87.628) Prec@5 100.000 (99.209) +2022-11-14 15:53:18,567 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 85.000 (87.568) Prec@5 98.000 (99.182) +2022-11-14 15:53:18,579 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0764) Prec@1 85.000 (87.511) Prec@5 98.000 (99.156) +2022-11-14 15:53:18,590 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0769) Prec@1 85.000 (87.457) Prec@5 99.000 (99.152) +2022-11-14 15:53:18,601 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0768) Prec@1 87.000 (87.447) Prec@5 100.000 (99.170) +2022-11-14 15:53:18,612 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1178 (0.0777) Prec@1 82.000 (87.333) Prec@5 97.000 (99.125) +2022-11-14 15:53:18,623 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0772) Prec@1 91.000 (87.408) Prec@5 100.000 (99.143) +2022-11-14 15:53:18,634 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0773) Prec@1 87.000 (87.400) Prec@5 100.000 (99.160) +2022-11-14 15:53:18,647 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0769) Prec@1 90.000 (87.451) Prec@5 100.000 (99.176) +2022-11-14 15:53:18,661 Test: [51/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0770) Prec@1 87.000 (87.442) Prec@5 99.000 (99.173) +2022-11-14 15:53:18,675 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0772) Prec@1 85.000 (87.396) Prec@5 99.000 (99.170) +2022-11-14 15:53:18,686 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0772) Prec@1 87.000 (87.389) Prec@5 100.000 (99.185) +2022-11-14 15:53:18,699 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1053 (0.0777) Prec@1 84.000 (87.327) Prec@5 99.000 (99.182) +2022-11-14 15:53:18,713 Test: [55/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0776) Prec@1 89.000 (87.357) Prec@5 99.000 (99.179) +2022-11-14 15:53:18,725 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0773) Prec@1 89.000 (87.386) Prec@5 99.000 (99.175) +2022-11-14 15:53:18,736 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0773) Prec@1 88.000 (87.397) Prec@5 98.000 (99.155) +2022-11-14 15:53:18,747 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0776) Prec@1 85.000 (87.356) Prec@5 99.000 (99.153) +2022-11-14 15:53:18,761 Test: [59/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0775) Prec@1 85.000 (87.317) Prec@5 98.000 (99.133) +2022-11-14 15:53:18,773 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0773) Prec@1 92.000 (87.393) Prec@5 100.000 (99.148) +2022-11-14 15:53:18,783 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0772) Prec@1 84.000 (87.339) Prec@5 100.000 (99.161) +2022-11-14 15:53:18,795 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0770) Prec@1 90.000 (87.381) Prec@5 99.000 (99.159) +2022-11-14 15:53:18,809 Test: [63/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0766) Prec@1 92.000 (87.453) Prec@5 99.000 (99.156) +2022-11-14 15:53:18,823 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1102 (0.0771) Prec@1 82.000 (87.369) Prec@5 97.000 (99.123) +2022-11-14 15:53:18,833 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0772) Prec@1 86.000 (87.348) Prec@5 99.000 (99.121) +2022-11-14 15:53:18,843 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0767) Prec@1 93.000 (87.433) Prec@5 100.000 (99.134) +2022-11-14 15:53:18,857 Test: [67/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0765) Prec@1 91.000 (87.485) Prec@5 99.000 (99.132) +2022-11-14 15:53:18,870 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0444 (0.0760) Prec@1 95.000 (87.594) Prec@5 98.000 (99.116) +2022-11-14 15:53:18,882 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0762) Prec@1 86.000 (87.571) Prec@5 99.000 (99.114) +2022-11-14 15:53:18,893 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0895 (0.0763) Prec@1 84.000 (87.521) Prec@5 100.000 (99.127) +2022-11-14 15:53:18,907 Test: [71/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0764) Prec@1 84.000 (87.472) Prec@5 100.000 (99.139) +2022-11-14 15:53:18,920 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0761) Prec@1 90.000 (87.507) Prec@5 100.000 (99.151) +2022-11-14 15:53:18,931 Test: [73/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0491 (0.0757) Prec@1 94.000 (87.595) Prec@5 100.000 (99.162) +2022-11-14 15:53:18,941 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1156 (0.0762) Prec@1 81.000 (87.507) Prec@5 99.000 (99.160) +2022-11-14 15:53:18,956 Test: [75/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0763) Prec@1 87.000 (87.500) Prec@5 98.000 (99.145) +2022-11-14 15:53:18,968 Test: [76/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0763) Prec@1 87.000 (87.494) Prec@5 99.000 (99.143) +2022-11-14 15:53:18,980 Test: [77/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0765) Prec@1 84.000 (87.449) Prec@5 99.000 (99.141) +2022-11-14 15:53:18,990 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0764) Prec@1 87.000 (87.443) Prec@5 100.000 (99.152) +2022-11-14 15:53:19,003 Test: [79/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0764) Prec@1 86.000 (87.425) Prec@5 100.000 (99.162) +2022-11-14 15:53:19,015 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.0765) Prec@1 86.000 (87.407) Prec@5 99.000 (99.160) +2022-11-14 15:53:19,027 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0962 (0.0768) Prec@1 84.000 (87.366) Prec@5 100.000 (99.171) +2022-11-14 15:53:19,039 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0910 (0.0769) Prec@1 87.000 (87.361) Prec@5 100.000 (99.181) +2022-11-14 15:53:19,052 Test: [83/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0768) Prec@1 88.000 (87.369) Prec@5 98.000 (99.167) +2022-11-14 15:53:19,066 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0769) Prec@1 86.000 (87.353) Prec@5 100.000 (99.176) +2022-11-14 15:53:19,077 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.0771) Prec@1 87.000 (87.349) Prec@5 100.000 (99.186) +2022-11-14 15:53:19,087 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0773) Prec@1 85.000 (87.322) Prec@5 99.000 (99.184) +2022-11-14 15:53:19,102 Test: [87/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0774) Prec@1 89.000 (87.341) Prec@5 98.000 (99.170) +2022-11-14 15:53:19,115 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0772) Prec@1 92.000 (87.393) Prec@5 99.000 (99.169) +2022-11-14 15:53:19,126 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0771) Prec@1 89.000 (87.411) Prec@5 100.000 (99.178) +2022-11-14 15:53:19,136 Test: [90/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0770) Prec@1 89.000 (87.429) Prec@5 100.000 (99.187) +2022-11-14 15:53:19,150 Test: [91/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0770) Prec@1 87.000 (87.424) Prec@5 97.000 (99.163) +2022-11-14 15:53:19,163 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0771) Prec@1 89.000 (87.441) Prec@5 100.000 (99.172) +2022-11-14 15:53:19,174 Test: [93/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0771) Prec@1 87.000 (87.436) Prec@5 99.000 (99.170) +2022-11-14 15:53:19,185 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0770) Prec@1 89.000 (87.453) Prec@5 100.000 (99.179) +2022-11-14 15:53:19,198 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0769) Prec@1 90.000 (87.479) Prec@5 100.000 (99.188) +2022-11-14 15:53:19,210 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0494 (0.0766) Prec@1 90.000 (87.505) Prec@5 99.000 (99.186) +2022-11-14 15:53:19,221 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1012 (0.0769) Prec@1 83.000 (87.459) Prec@5 98.000 (99.173) +2022-11-14 15:53:19,234 Test: [98/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0978 (0.0771) Prec@1 86.000 (87.444) Prec@5 99.000 (99.172) +2022-11-14 15:53:19,245 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0769) Prec@1 91.000 (87.480) Prec@5 100.000 (99.180) +2022-11-14 15:53:19,319 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:53:19,679 Epoch: [276][0/500] Time 0.029 (0.029) Data 0.267 (0.267) Loss 0.0462 (0.0462) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:19,988 Epoch: [276][10/500] Time 0.025 (0.028) Data 0.002 (0.026) Loss 0.0213 (0.0338) Prec@1 97.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:53:20,272 Epoch: [276][20/500] Time 0.033 (0.026) Data 0.002 (0.015) Loss 0.0310 (0.0328) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:20,741 Epoch: [276][30/500] Time 0.046 (0.031) Data 0.002 (0.011) Loss 0.0365 (0.0338) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:21,196 Epoch: [276][40/500] Time 0.048 (0.033) Data 0.002 (0.009) Loss 0.0326 (0.0335) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:21,676 Epoch: [276][50/500] Time 0.048 (0.035) Data 0.003 (0.007) Loss 0.0420 (0.0349) Prec@1 92.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 15:53:22,241 Epoch: [276][60/500] Time 0.058 (0.038) Data 0.003 (0.007) Loss 0.0409 (0.0358) Prec@1 92.000 (93.429) Prec@5 100.000 (100.000) +2022-11-14 15:53:22,779 Epoch: [276][70/500] Time 0.061 (0.039) Data 0.002 (0.006) Loss 0.0258 (0.0346) Prec@1 97.000 (93.875) Prec@5 100.000 (100.000) +2022-11-14 15:53:23,306 Epoch: [276][80/500] Time 0.056 (0.040) Data 0.002 (0.006) Loss 0.0253 (0.0335) Prec@1 96.000 (94.111) Prec@5 100.000 (100.000) +2022-11-14 15:53:23,792 Epoch: [276][90/500] Time 0.047 (0.041) Data 0.002 (0.005) Loss 0.0624 (0.0364) Prec@1 89.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 15:53:24,252 Epoch: [276][100/500] Time 0.054 (0.041) Data 0.002 (0.005) Loss 0.0676 (0.0393) Prec@1 89.000 (93.182) Prec@5 100.000 (100.000) +2022-11-14 15:53:24,721 Epoch: [276][110/500] Time 0.047 (0.041) Data 0.002 (0.005) Loss 0.0380 (0.0391) Prec@1 94.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 15:53:25,197 Epoch: [276][120/500] Time 0.047 (0.041) Data 0.002 (0.004) Loss 0.0226 (0.0379) Prec@1 96.000 (93.462) Prec@5 100.000 (100.000) +2022-11-14 15:53:25,674 Epoch: [276][130/500] Time 0.046 (0.041) Data 0.002 (0.004) Loss 0.0345 (0.0376) Prec@1 95.000 (93.571) Prec@5 100.000 (100.000) +2022-11-14 15:53:26,196 Epoch: [276][140/500] Time 0.064 (0.041) Data 0.002 (0.004) Loss 0.0261 (0.0369) Prec@1 97.000 (93.800) Prec@5 100.000 (100.000) +2022-11-14 15:53:26,709 Epoch: [276][150/500] Time 0.070 (0.042) Data 0.002 (0.004) Loss 0.0334 (0.0366) Prec@1 94.000 (93.812) Prec@5 100.000 (100.000) +2022-11-14 15:53:27,224 Epoch: [276][160/500] Time 0.057 (0.042) Data 0.002 (0.004) Loss 0.0358 (0.0366) Prec@1 93.000 (93.765) Prec@5 99.000 (99.941) +2022-11-14 15:53:27,795 Epoch: [276][170/500] Time 0.053 (0.042) Data 0.003 (0.004) Loss 0.0375 (0.0366) Prec@1 94.000 (93.778) Prec@5 100.000 (99.944) +2022-11-14 15:53:28,254 Epoch: [276][180/500] Time 0.043 (0.042) Data 0.002 (0.004) Loss 0.0433 (0.0370) Prec@1 93.000 (93.737) Prec@5 100.000 (99.947) +2022-11-14 15:53:28,723 Epoch: [276][190/500] Time 0.047 (0.042) Data 0.002 (0.004) Loss 0.0278 (0.0365) Prec@1 96.000 (93.850) Prec@5 99.000 (99.900) +2022-11-14 15:53:29,196 Epoch: [276][200/500] Time 0.038 (0.042) Data 0.002 (0.004) Loss 0.0256 (0.0360) Prec@1 96.000 (93.952) Prec@5 100.000 (99.905) +2022-11-14 15:53:29,646 Epoch: [276][210/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0523 (0.0368) Prec@1 90.000 (93.773) Prec@5 100.000 (99.909) +2022-11-14 15:53:30,123 Epoch: [276][220/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0528 (0.0374) Prec@1 93.000 (93.739) Prec@5 99.000 (99.870) +2022-11-14 15:53:30,589 Epoch: [276][230/500] Time 0.045 (0.042) Data 0.002 (0.003) Loss 0.0299 (0.0371) Prec@1 96.000 (93.833) Prec@5 100.000 (99.875) +2022-11-14 15:53:31,088 Epoch: [276][240/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0584 (0.0380) Prec@1 88.000 (93.600) Prec@5 99.000 (99.840) +2022-11-14 15:53:31,585 Epoch: [276][250/500] Time 0.050 (0.042) Data 0.002 (0.003) Loss 0.0480 (0.0384) Prec@1 91.000 (93.500) Prec@5 100.000 (99.846) +2022-11-14 15:53:32,098 Epoch: [276][260/500] Time 0.038 (0.043) Data 0.003 (0.003) Loss 0.0559 (0.0390) Prec@1 91.000 (93.407) Prec@5 100.000 (99.852) +2022-11-14 15:53:32,578 Epoch: [276][270/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0189 (0.0383) Prec@1 98.000 (93.571) Prec@5 100.000 (99.857) +2022-11-14 15:53:33,088 Epoch: [276][280/500] Time 0.048 (0.043) Data 0.003 (0.003) Loss 0.0428 (0.0385) Prec@1 94.000 (93.586) Prec@5 99.000 (99.828) +2022-11-14 15:53:33,554 Epoch: [276][290/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0308 (0.0382) Prec@1 95.000 (93.633) Prec@5 100.000 (99.833) +2022-11-14 15:53:34,104 Epoch: [276][300/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0216 (0.0377) Prec@1 96.000 (93.710) Prec@5 100.000 (99.839) +2022-11-14 15:53:34,659 Epoch: [276][310/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0349 (0.0376) Prec@1 94.000 (93.719) Prec@5 100.000 (99.844) +2022-11-14 15:53:35,137 Epoch: [276][320/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0238 (0.0372) Prec@1 95.000 (93.758) Prec@5 100.000 (99.848) +2022-11-14 15:53:35,598 Epoch: [276][330/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0225 (0.0367) Prec@1 96.000 (93.824) Prec@5 100.000 (99.853) +2022-11-14 15:53:36,098 Epoch: [276][340/500] Time 0.057 (0.043) Data 0.002 (0.003) Loss 0.0614 (0.0374) Prec@1 91.000 (93.743) Prec@5 100.000 (99.857) +2022-11-14 15:53:36,588 Epoch: [276][350/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0319 (0.0373) Prec@1 96.000 (93.806) Prec@5 100.000 (99.861) +2022-11-14 15:53:37,101 Epoch: [276][360/500] Time 0.035 (0.043) Data 0.002 (0.003) Loss 0.0320 (0.0371) Prec@1 96.000 (93.865) Prec@5 100.000 (99.865) +2022-11-14 15:53:37,618 Epoch: [276][370/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0252 (0.0368) Prec@1 96.000 (93.921) Prec@5 100.000 (99.868) +2022-11-14 15:53:38,089 Epoch: [276][380/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0411 (0.0369) Prec@1 94.000 (93.923) Prec@5 99.000 (99.846) +2022-11-14 15:53:38,554 Epoch: [276][390/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0529 (0.0373) Prec@1 93.000 (93.900) Prec@5 98.000 (99.800) +2022-11-14 15:53:39,041 Epoch: [276][400/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0432 (0.0375) Prec@1 93.000 (93.878) Prec@5 100.000 (99.805) +2022-11-14 15:53:39,508 Epoch: [276][410/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0299 (0.0373) Prec@1 96.000 (93.929) Prec@5 100.000 (99.810) +2022-11-14 15:53:39,999 Epoch: [276][420/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0452 (0.0375) Prec@1 91.000 (93.860) Prec@5 99.000 (99.791) +2022-11-14 15:53:40,497 Epoch: [276][430/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0429 (0.0376) Prec@1 96.000 (93.909) Prec@5 99.000 (99.773) +2022-11-14 15:53:40,983 Epoch: [276][440/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0323 (0.0375) Prec@1 96.000 (93.956) Prec@5 100.000 (99.778) +2022-11-14 15:53:41,504 Epoch: [276][450/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0224 (0.0372) Prec@1 96.000 (94.000) Prec@5 100.000 (99.783) +2022-11-14 15:53:42,003 Epoch: [276][460/500] Time 0.056 (0.043) Data 0.002 (0.003) Loss 0.0257 (0.0369) Prec@1 95.000 (94.021) Prec@5 100.000 (99.787) +2022-11-14 15:53:42,482 Epoch: [276][470/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0181 (0.0365) Prec@1 99.000 (94.125) Prec@5 100.000 (99.792) +2022-11-14 15:53:42,966 Epoch: [276][480/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0520 (0.0368) Prec@1 91.000 (94.061) Prec@5 100.000 (99.796) +2022-11-14 15:53:43,434 Epoch: [276][490/500] Time 0.045 (0.043) Data 0.003 (0.003) Loss 0.0438 (0.0370) Prec@1 92.000 (94.020) Prec@5 100.000 (99.800) +2022-11-14 15:53:43,871 Epoch: [276][499/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0359 (0.0370) Prec@1 94.000 (94.020) Prec@5 100.000 (99.804) +2022-11-14 15:53:44,192 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0648 (0.0648) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 15:53:44,208 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0699 (0.0674) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 15:53:44,220 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0732 (0.0693) Prec@1 87.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 15:53:44,235 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0717 (0.0699) Prec@1 89.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 15:53:44,247 Test: [4/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0691 (0.0698) Prec@1 90.000 (88.800) Prec@5 99.000 (99.200) +2022-11-14 15:53:44,260 Test: [5/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0474 (0.0660) Prec@1 92.000 (89.333) Prec@5 99.000 (99.167) +2022-11-14 15:53:44,281 Test: [6/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0517 (0.0640) Prec@1 93.000 (89.857) Prec@5 100.000 (99.286) +2022-11-14 15:53:44,298 Test: [7/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0854 (0.0667) Prec@1 86.000 (89.375) Prec@5 99.000 (99.250) +2022-11-14 15:53:44,310 Test: [8/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0899 (0.0692) Prec@1 86.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 15:53:44,321 Test: [9/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0687) Prec@1 90.000 (89.100) Prec@5 99.000 (99.300) +2022-11-14 15:53:44,334 Test: [10/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0597 (0.0678) Prec@1 90.000 (89.182) Prec@5 100.000 (99.364) +2022-11-14 15:53:44,346 Test: [11/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0737 (0.0683) Prec@1 87.000 (89.000) Prec@5 99.000 (99.333) +2022-11-14 15:53:44,358 Test: [12/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0549 (0.0673) Prec@1 92.000 (89.231) Prec@5 99.000 (99.308) +2022-11-14 15:53:44,374 Test: [13/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0696 (0.0675) Prec@1 89.000 (89.214) Prec@5 98.000 (99.214) +2022-11-14 15:53:44,392 Test: [14/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0650 (0.0673) Prec@1 88.000 (89.133) Prec@5 100.000 (99.267) +2022-11-14 15:53:44,409 Test: [15/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0769 (0.0679) Prec@1 85.000 (88.875) Prec@5 100.000 (99.312) +2022-11-14 15:53:44,426 Test: [16/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0432 (0.0664) Prec@1 93.000 (89.118) Prec@5 98.000 (99.235) +2022-11-14 15:53:44,442 Test: [17/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1117 (0.0690) Prec@1 85.000 (88.889) Prec@5 99.000 (99.222) +2022-11-14 15:53:44,458 Test: [18/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0794 (0.0695) Prec@1 88.000 (88.842) Prec@5 99.000 (99.211) +2022-11-14 15:53:44,472 Test: [19/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0879 (0.0704) Prec@1 86.000 (88.700) Prec@5 99.000 (99.200) +2022-11-14 15:53:44,489 Test: [20/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0731 (0.0706) Prec@1 88.000 (88.667) Prec@5 98.000 (99.143) +2022-11-14 15:53:44,506 Test: [21/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.0947 (0.0717) Prec@1 83.000 (88.409) Prec@5 98.000 (99.091) +2022-11-14 15:53:44,524 Test: [22/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0818 (0.0721) Prec@1 87.000 (88.348) Prec@5 99.000 (99.087) +2022-11-14 15:53:44,541 Test: [23/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0654 (0.0718) Prec@1 89.000 (88.375) Prec@5 100.000 (99.125) +2022-11-14 15:53:44,558 Test: [24/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.0909 (0.0726) Prec@1 87.000 (88.320) Prec@5 100.000 (99.160) +2022-11-14 15:53:44,575 Test: [25/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0819 (0.0729) Prec@1 86.000 (88.231) Prec@5 99.000 (99.154) +2022-11-14 15:53:44,589 Test: [26/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0570 (0.0723) Prec@1 90.000 (88.296) Prec@5 100.000 (99.185) +2022-11-14 15:53:44,602 Test: [27/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0731 (0.0724) Prec@1 87.000 (88.250) Prec@5 100.000 (99.214) +2022-11-14 15:53:44,618 Test: [28/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0712 (0.0723) Prec@1 89.000 (88.276) Prec@5 98.000 (99.172) +2022-11-14 15:53:44,635 Test: [29/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0738 (0.0724) Prec@1 87.000 (88.233) Prec@5 100.000 (99.200) +2022-11-14 15:53:44,651 Test: [30/100] Model Time 0.013 (0.012) Loss Time 0.000 (0.000) Loss 0.0846 (0.0728) Prec@1 84.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 15:53:44,669 Test: [31/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.0709 (0.0727) Prec@1 89.000 (88.125) Prec@5 99.000 (99.219) +2022-11-14 15:53:44,684 Test: [32/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0655 (0.0725) Prec@1 91.000 (88.212) Prec@5 100.000 (99.242) +2022-11-14 15:53:44,699 Test: [33/100] Model Time 0.011 (0.012) Loss Time 0.000 (0.000) Loss 0.0770 (0.0726) Prec@1 87.000 (88.176) Prec@5 99.000 (99.235) +2022-11-14 15:53:44,717 Test: [34/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.0744 (0.0727) Prec@1 89.000 (88.200) Prec@5 99.000 (99.229) +2022-11-14 15:53:44,733 Test: [35/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0698 (0.0726) Prec@1 90.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 15:53:44,749 Test: [36/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0639 (0.0724) Prec@1 90.000 (88.297) Prec@5 99.000 (99.243) +2022-11-14 15:53:44,763 Test: [37/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0961 (0.0730) Prec@1 86.000 (88.237) Prec@5 97.000 (99.184) +2022-11-14 15:53:44,775 Test: [38/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0401 (0.0721) Prec@1 94.000 (88.385) Prec@5 98.000 (99.154) +2022-11-14 15:53:44,788 Test: [39/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0546 (0.0717) Prec@1 92.000 (88.475) Prec@5 99.000 (99.150) +2022-11-14 15:53:44,800 Test: [40/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0987 (0.0724) Prec@1 85.000 (88.390) Prec@5 98.000 (99.122) +2022-11-14 15:53:44,815 Test: [41/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0651 (0.0722) Prec@1 90.000 (88.429) Prec@5 98.000 (99.095) +2022-11-14 15:53:44,830 Test: [42/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0484 (0.0716) Prec@1 92.000 (88.512) Prec@5 99.000 (99.093) +2022-11-14 15:53:44,845 Test: [43/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0671 (0.0715) Prec@1 88.000 (88.500) Prec@5 98.000 (99.068) +2022-11-14 15:53:44,859 Test: [44/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0646 (0.0714) Prec@1 89.000 (88.511) Prec@5 99.000 (99.067) +2022-11-14 15:53:44,873 Test: [45/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0847 (0.0717) Prec@1 89.000 (88.522) Prec@5 98.000 (99.043) +2022-11-14 15:53:44,888 Test: [46/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0832 (0.0719) Prec@1 88.000 (88.511) Prec@5 99.000 (99.043) +2022-11-14 15:53:44,901 Test: [47/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0937 (0.0724) Prec@1 87.000 (88.479) Prec@5 98.000 (99.021) +2022-11-14 15:53:44,915 Test: [48/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0722) Prec@1 90.000 (88.510) Prec@5 100.000 (99.041) +2022-11-14 15:53:44,927 Test: [49/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0947 (0.0726) Prec@1 86.000 (88.460) Prec@5 100.000 (99.060) +2022-11-14 15:53:44,939 Test: [50/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0508 (0.0722) Prec@1 91.000 (88.510) Prec@5 100.000 (99.078) +2022-11-14 15:53:44,952 Test: [51/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0804 (0.0723) Prec@1 87.000 (88.481) Prec@5 100.000 (99.096) +2022-11-14 15:53:44,965 Test: [52/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0745 (0.0724) Prec@1 88.000 (88.472) Prec@5 99.000 (99.094) +2022-11-14 15:53:44,980 Test: [53/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0557 (0.0721) Prec@1 92.000 (88.537) Prec@5 100.000 (99.111) +2022-11-14 15:53:44,995 Test: [54/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0564 (0.0718) Prec@1 92.000 (88.600) Prec@5 100.000 (99.127) +2022-11-14 15:53:45,012 Test: [55/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0731 (0.0718) Prec@1 90.000 (88.625) Prec@5 99.000 (99.125) +2022-11-14 15:53:45,032 Test: [56/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0814 (0.0720) Prec@1 85.000 (88.561) Prec@5 99.000 (99.123) +2022-11-14 15:53:45,051 Test: [57/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0652 (0.0719) Prec@1 90.000 (88.586) Prec@5 99.000 (99.121) +2022-11-14 15:53:45,069 Test: [58/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0869 (0.0721) Prec@1 85.000 (88.525) Prec@5 100.000 (99.136) +2022-11-14 15:53:45,089 Test: [59/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0911 (0.0724) Prec@1 83.000 (88.433) Prec@5 99.000 (99.133) +2022-11-14 15:53:45,111 Test: [60/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0742 (0.0725) Prec@1 89.000 (88.443) Prec@5 100.000 (99.148) +2022-11-14 15:53:45,133 Test: [61/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0759 (0.0725) Prec@1 89.000 (88.452) Prec@5 99.000 (99.145) +2022-11-14 15:53:45,153 Test: [62/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0586 (0.0723) Prec@1 93.000 (88.524) Prec@5 100.000 (99.159) +2022-11-14 15:53:45,171 Test: [63/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0498 (0.0719) Prec@1 92.000 (88.578) Prec@5 99.000 (99.156) +2022-11-14 15:53:45,195 Test: [64/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0897 (0.0722) Prec@1 87.000 (88.554) Prec@5 100.000 (99.169) +2022-11-14 15:53:45,220 Test: [65/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0662 (0.0721) Prec@1 91.000 (88.591) Prec@5 99.000 (99.167) +2022-11-14 15:53:45,244 Test: [66/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0402 (0.0716) Prec@1 94.000 (88.672) Prec@5 100.000 (99.179) +2022-11-14 15:53:45,266 Test: [67/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0719 (0.0717) Prec@1 89.000 (88.676) Prec@5 98.000 (99.162) +2022-11-14 15:53:45,286 Test: [68/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0581 (0.0715) Prec@1 90.000 (88.696) Prec@5 99.000 (99.159) +2022-11-14 15:53:45,311 Test: [69/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0889 (0.0717) Prec@1 84.000 (88.629) Prec@5 99.000 (99.157) +2022-11-14 15:53:45,334 Test: [70/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1025 (0.0721) Prec@1 85.000 (88.577) Prec@5 100.000 (99.169) +2022-11-14 15:53:45,355 Test: [71/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0485 (0.0718) Prec@1 91.000 (88.611) Prec@5 100.000 (99.181) +2022-11-14 15:53:45,379 Test: [72/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0551 (0.0716) Prec@1 92.000 (88.658) Prec@5 100.000 (99.192) +2022-11-14 15:53:45,404 Test: [73/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0552 (0.0714) Prec@1 91.000 (88.689) Prec@5 100.000 (99.203) +2022-11-14 15:53:45,427 Test: [74/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0840 (0.0715) Prec@1 86.000 (88.653) Prec@5 99.000 (99.200) +2022-11-14 15:53:45,449 Test: [75/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0726 (0.0715) Prec@1 88.000 (88.645) Prec@5 98.000 (99.184) +2022-11-14 15:53:45,473 Test: [76/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0664 (0.0715) Prec@1 89.000 (88.649) Prec@5 98.000 (99.169) +2022-11-14 15:53:45,498 Test: [77/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0915 (0.0717) Prec@1 84.000 (88.590) Prec@5 98.000 (99.154) +2022-11-14 15:53:45,520 Test: [78/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.0717) Prec@1 87.000 (88.570) Prec@5 100.000 (99.165) +2022-11-14 15:53:45,544 Test: [79/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0919 (0.0720) Prec@1 85.000 (88.525) Prec@5 100.000 (99.175) +2022-11-14 15:53:45,567 Test: [80/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0720) Prec@1 87.000 (88.506) Prec@5 98.000 (99.160) +2022-11-14 15:53:45,591 Test: [81/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0701 (0.0720) Prec@1 87.000 (88.488) Prec@5 100.000 (99.171) +2022-11-14 15:53:45,615 Test: [82/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0717 (0.0720) Prec@1 89.000 (88.494) Prec@5 100.000 (99.181) +2022-11-14 15:53:45,638 Test: [83/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0668 (0.0720) Prec@1 87.000 (88.476) Prec@5 99.000 (99.179) +2022-11-14 15:53:45,660 Test: [84/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0715 (0.0719) Prec@1 91.000 (88.506) Prec@5 99.000 (99.176) +2022-11-14 15:53:45,685 Test: [85/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0926 (0.0722) Prec@1 85.000 (88.465) Prec@5 99.000 (99.174) +2022-11-14 15:53:45,705 Test: [86/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0776 (0.0723) Prec@1 86.000 (88.437) Prec@5 100.000 (99.184) +2022-11-14 15:53:45,728 Test: [87/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0800 (0.0723) Prec@1 86.000 (88.409) Prec@5 99.000 (99.182) +2022-11-14 15:53:45,749 Test: [88/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0732 (0.0723) Prec@1 89.000 (88.416) Prec@5 100.000 (99.191) +2022-11-14 15:53:45,775 Test: [89/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0772 (0.0724) Prec@1 86.000 (88.389) Prec@5 98.000 (99.178) +2022-11-14 15:53:45,797 Test: [90/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0446 (0.0721) Prec@1 90.000 (88.407) Prec@5 100.000 (99.187) +2022-11-14 15:53:45,815 Test: [91/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0390 (0.0717) Prec@1 92.000 (88.446) Prec@5 100.000 (99.196) +2022-11-14 15:53:45,834 Test: [92/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1031 (0.0721) Prec@1 84.000 (88.398) Prec@5 100.000 (99.204) +2022-11-14 15:53:45,849 Test: [93/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0684 (0.0720) Prec@1 89.000 (88.404) Prec@5 99.000 (99.202) +2022-11-14 15:53:45,867 Test: [94/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1003 (0.0723) Prec@1 83.000 (88.347) Prec@5 98.000 (99.189) +2022-11-14 15:53:45,888 Test: [95/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0661 (0.0723) Prec@1 91.000 (88.375) Prec@5 100.000 (99.198) +2022-11-14 15:53:45,910 Test: [96/100] Model Time 0.017 (0.010) Loss Time 0.000 (0.000) Loss 0.0470 (0.0720) Prec@1 92.000 (88.412) Prec@5 99.000 (99.196) +2022-11-14 15:53:45,930 Test: [97/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1133 (0.0724) Prec@1 83.000 (88.357) Prec@5 99.000 (99.194) +2022-11-14 15:53:45,946 Test: [98/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0914 (0.0726) Prec@1 86.000 (88.333) Prec@5 99.000 (99.192) +2022-11-14 15:53:45,964 Test: [99/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0668 (0.0726) Prec@1 89.000 (88.340) Prec@5 100.000 (99.200) +2022-11-14 15:53:46,032 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 15:53:46,423 Epoch: [277][0/500] Time 0.033 (0.033) Data 0.280 (0.280) Loss 0.0280 (0.0280) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:46,964 Epoch: [277][10/500] Time 0.055 (0.047) Data 0.002 (0.028) Loss 0.0409 (0.0344) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:53:47,509 Epoch: [277][20/500] Time 0.056 (0.048) Data 0.002 (0.015) Loss 0.0313 (0.0334) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:53:48,107 Epoch: [277][30/500] Time 0.066 (0.050) Data 0.002 (0.011) Loss 0.0475 (0.0369) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:53:48,694 Epoch: [277][40/500] Time 0.047 (0.050) Data 0.002 (0.009) Loss 0.0256 (0.0347) Prec@1 97.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 15:53:49,225 Epoch: [277][50/500] Time 0.052 (0.050) Data 0.002 (0.008) Loss 0.0303 (0.0339) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:53:49,782 Epoch: [277][60/500] Time 0.048 (0.050) Data 0.002 (0.007) Loss 0.0268 (0.0329) Prec@1 96.000 (94.714) Prec@5 99.000 (99.857) +2022-11-14 15:53:50,347 Epoch: [277][70/500] Time 0.057 (0.050) Data 0.002 (0.006) Loss 0.0485 (0.0349) Prec@1 94.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 15:53:50,954 Epoch: [277][80/500] Time 0.060 (0.051) Data 0.002 (0.006) Loss 0.0427 (0.0357) Prec@1 93.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 15:53:51,491 Epoch: [277][90/500] Time 0.050 (0.050) Data 0.002 (0.005) Loss 0.0350 (0.0356) Prec@1 92.000 (94.200) Prec@5 100.000 (99.900) +2022-11-14 15:53:52,047 Epoch: [277][100/500] Time 0.049 (0.050) Data 0.002 (0.005) Loss 0.0381 (0.0359) Prec@1 95.000 (94.273) Prec@5 100.000 (99.909) +2022-11-14 15:53:52,667 Epoch: [277][110/500] Time 0.066 (0.051) Data 0.002 (0.005) Loss 0.0349 (0.0358) Prec@1 97.000 (94.500) Prec@5 100.000 (99.917) +2022-11-14 15:53:53,227 Epoch: [277][120/500] Time 0.057 (0.051) Data 0.002 (0.004) Loss 0.0517 (0.0370) Prec@1 92.000 (94.308) Prec@5 100.000 (99.923) +2022-11-14 15:53:53,766 Epoch: [277][130/500] Time 0.054 (0.050) Data 0.002 (0.004) Loss 0.0382 (0.0371) Prec@1 94.000 (94.286) Prec@5 100.000 (99.929) +2022-11-14 15:53:54,307 Epoch: [277][140/500] Time 0.050 (0.050) Data 0.002 (0.004) Loss 0.0478 (0.0378) Prec@1 92.000 (94.133) Prec@5 99.000 (99.867) +2022-11-14 15:53:54,862 Epoch: [277][150/500] Time 0.057 (0.050) Data 0.002 (0.004) Loss 0.0428 (0.0381) Prec@1 93.000 (94.062) Prec@5 99.000 (99.812) +2022-11-14 15:53:55,406 Epoch: [277][160/500] Time 0.048 (0.050) Data 0.002 (0.004) Loss 0.0498 (0.0388) Prec@1 91.000 (93.882) Prec@5 100.000 (99.824) +2022-11-14 15:53:55,928 Epoch: [277][170/500] Time 0.050 (0.050) Data 0.002 (0.004) Loss 0.0191 (0.0377) Prec@1 97.000 (94.056) Prec@5 100.000 (99.833) +2022-11-14 15:53:56,471 Epoch: [277][180/500] Time 0.061 (0.050) Data 0.002 (0.004) Loss 0.0320 (0.0374) Prec@1 94.000 (94.053) Prec@5 100.000 (99.842) +2022-11-14 15:53:57,024 Epoch: [277][190/500] Time 0.053 (0.050) Data 0.002 (0.004) Loss 0.0290 (0.0370) Prec@1 96.000 (94.150) Prec@5 100.000 (99.850) +2022-11-14 15:53:57,560 Epoch: [277][200/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0343 (0.0369) Prec@1 94.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 15:53:58,110 Epoch: [277][210/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0501 (0.0375) Prec@1 91.000 (94.000) Prec@5 100.000 (99.864) +2022-11-14 15:53:58,658 Epoch: [277][220/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0344 (0.0373) Prec@1 95.000 (94.043) Prec@5 99.000 (99.826) +2022-11-14 15:53:59,201 Epoch: [277][230/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0360 (0.0373) Prec@1 95.000 (94.083) Prec@5 100.000 (99.833) +2022-11-14 15:53:59,733 Epoch: [277][240/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0455 (0.0376) Prec@1 92.000 (94.000) Prec@5 100.000 (99.840) +2022-11-14 15:54:00,292 Epoch: [277][250/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0400 (0.0377) Prec@1 92.000 (93.923) Prec@5 99.000 (99.808) +2022-11-14 15:54:00,838 Epoch: [277][260/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0286 (0.0374) Prec@1 95.000 (93.963) Prec@5 99.000 (99.778) +2022-11-14 15:54:01,382 Epoch: [277][270/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0492 (0.0378) Prec@1 93.000 (93.929) Prec@5 99.000 (99.750) +2022-11-14 15:54:01,914 Epoch: [277][280/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.0470 (0.0381) Prec@1 94.000 (93.931) Prec@5 99.000 (99.724) +2022-11-14 15:54:02,457 Epoch: [277][290/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0219 (0.0376) Prec@1 95.000 (93.967) Prec@5 100.000 (99.733) +2022-11-14 15:54:02,998 Epoch: [277][300/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0332 (0.0374) Prec@1 94.000 (93.968) Prec@5 100.000 (99.742) +2022-11-14 15:54:03,513 Epoch: [277][310/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0314 (0.0372) Prec@1 96.000 (94.031) Prec@5 100.000 (99.750) +2022-11-14 15:54:04,058 Epoch: [277][320/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0273 (0.0369) Prec@1 95.000 (94.061) Prec@5 100.000 (99.758) +2022-11-14 15:54:04,606 Epoch: [277][330/500] Time 0.053 (0.049) Data 0.003 (0.003) Loss 0.0302 (0.0367) Prec@1 92.000 (94.000) Prec@5 100.000 (99.765) +2022-11-14 15:54:05,145 Epoch: [277][340/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0331 (0.0366) Prec@1 94.000 (94.000) Prec@5 98.000 (99.714) +2022-11-14 15:54:05,688 Epoch: [277][350/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0572 (0.0372) Prec@1 92.000 (93.944) Prec@5 100.000 (99.722) +2022-11-14 15:54:06,225 Epoch: [277][360/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0448 (0.0374) Prec@1 94.000 (93.946) Prec@5 99.000 (99.703) +2022-11-14 15:54:06,741 Epoch: [277][370/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0262 (0.0371) Prec@1 96.000 (94.000) Prec@5 100.000 (99.711) +2022-11-14 15:54:07,277 Epoch: [277][380/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0239 (0.0368) Prec@1 95.000 (94.026) Prec@5 100.000 (99.718) +2022-11-14 15:54:07,823 Epoch: [277][390/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0266 (0.0365) Prec@1 96.000 (94.075) Prec@5 100.000 (99.725) +2022-11-14 15:54:08,350 Epoch: [277][400/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0442 (0.0367) Prec@1 91.000 (94.000) Prec@5 100.000 (99.732) +2022-11-14 15:54:08,905 Epoch: [277][410/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0515 (0.0371) Prec@1 90.000 (93.905) Prec@5 100.000 (99.738) +2022-11-14 15:54:09,437 Epoch: [277][420/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0247 (0.0368) Prec@1 97.000 (93.977) Prec@5 99.000 (99.721) +2022-11-14 15:54:09,973 Epoch: [277][430/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0449 (0.0370) Prec@1 92.000 (93.932) Prec@5 99.000 (99.705) +2022-11-14 15:54:10,516 Epoch: [277][440/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0411 (0.0370) Prec@1 90.000 (93.844) Prec@5 100.000 (99.711) +2022-11-14 15:54:11,054 Epoch: [277][450/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0484 (0.0373) Prec@1 91.000 (93.783) Prec@5 100.000 (99.717) +2022-11-14 15:54:11,588 Epoch: [277][460/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0278 (0.0371) Prec@1 96.000 (93.830) Prec@5 100.000 (99.723) +2022-11-14 15:54:12,114 Epoch: [277][470/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0388 (0.0371) Prec@1 94.000 (93.833) Prec@5 100.000 (99.729) +2022-11-14 15:54:12,647 Epoch: [277][480/500] Time 0.062 (0.049) Data 0.002 (0.003) Loss 0.0100 (0.0366) Prec@1 99.000 (93.939) Prec@5 100.000 (99.735) +2022-11-14 15:54:13,191 Epoch: [277][490/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0304 (0.0364) Prec@1 95.000 (93.960) Prec@5 100.000 (99.740) +2022-11-14 15:54:13,674 Epoch: [277][499/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0634 (0.0370) Prec@1 88.000 (93.843) Prec@5 100.000 (99.745) +2022-11-14 15:54:13,985 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0810 (0.0810) Prec@1 88.000 (88.000) Prec@5 97.000 (97.000) +2022-11-14 15:54:13,994 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0845) Prec@1 85.000 (86.500) Prec@5 99.000 (98.000) +2022-11-14 15:54:14,004 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0794) Prec@1 91.000 (88.000) Prec@5 100.000 (98.667) +2022-11-14 15:54:14,017 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0768) Prec@1 89.000 (88.250) Prec@5 100.000 (99.000) +2022-11-14 15:54:14,026 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0774) Prec@1 90.000 (88.600) Prec@5 99.000 (99.000) +2022-11-14 15:54:14,036 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0748) Prec@1 88.000 (88.500) Prec@5 100.000 (99.167) +2022-11-14 15:54:14,044 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0717) Prec@1 91.000 (88.857) Prec@5 100.000 (99.286) +2022-11-14 15:54:14,056 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0723) Prec@1 87.000 (88.625) Prec@5 99.000 (99.250) +2022-11-14 15:54:14,064 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0730) Prec@1 87.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 15:54:14,074 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0740) Prec@1 88.000 (88.400) Prec@5 98.000 (99.100) +2022-11-14 15:54:14,085 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0479 (0.0716) Prec@1 92.000 (88.727) Prec@5 100.000 (99.182) +2022-11-14 15:54:14,093 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0736) Prec@1 85.000 (88.417) Prec@5 100.000 (99.250) +2022-11-14 15:54:14,104 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0719) Prec@1 91.000 (88.615) Prec@5 100.000 (99.308) +2022-11-14 15:54:14,115 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0715) Prec@1 91.000 (88.786) Prec@5 98.000 (99.214) +2022-11-14 15:54:14,126 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0710) Prec@1 91.000 (88.933) Prec@5 100.000 (99.267) +2022-11-14 15:54:14,137 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0714) Prec@1 88.000 (88.875) Prec@5 99.000 (99.250) +2022-11-14 15:54:14,147 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0705) Prec@1 93.000 (89.118) Prec@5 98.000 (99.176) +2022-11-14 15:54:14,157 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0718) Prec@1 86.000 (88.944) Prec@5 99.000 (99.167) +2022-11-14 15:54:14,168 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0731) Prec@1 85.000 (88.737) Prec@5 98.000 (99.105) +2022-11-14 15:54:14,181 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0731) Prec@1 91.000 (88.850) Prec@5 97.000 (99.000) +2022-11-14 15:54:14,190 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0737) Prec@1 86.000 (88.714) Prec@5 99.000 (99.000) +2022-11-14 15:54:14,200 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0733) Prec@1 89.000 (88.727) Prec@5 97.000 (98.909) +2022-11-14 15:54:14,212 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0745) Prec@1 85.000 (88.565) Prec@5 99.000 (98.913) +2022-11-14 15:54:14,223 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0744) Prec@1 86.000 (88.458) Prec@5 100.000 (98.958) +2022-11-14 15:54:14,232 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0756) Prec@1 84.000 (88.280) Prec@5 100.000 (99.000) +2022-11-14 15:54:14,242 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0758) Prec@1 88.000 (88.269) Prec@5 100.000 (99.038) +2022-11-14 15:54:14,255 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0751) Prec@1 88.000 (88.259) Prec@5 100.000 (99.074) +2022-11-14 15:54:14,269 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0749) Prec@1 91.000 (88.357) Prec@5 100.000 (99.107) +2022-11-14 15:54:14,281 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0743) Prec@1 91.000 (88.448) Prec@5 99.000 (99.103) +2022-11-14 15:54:14,291 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0747) Prec@1 89.000 (88.467) Prec@5 100.000 (99.133) +2022-11-14 15:54:14,300 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0749) Prec@1 84.000 (88.323) Prec@5 99.000 (99.129) +2022-11-14 15:54:14,311 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0750) Prec@1 85.000 (88.219) Prec@5 99.000 (99.125) +2022-11-14 15:54:14,322 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0751) Prec@1 86.000 (88.152) Prec@5 100.000 (99.152) +2022-11-14 15:54:14,334 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0756) Prec@1 86.000 (88.088) Prec@5 100.000 (99.176) +2022-11-14 15:54:14,345 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0756) Prec@1 88.000 (88.086) Prec@5 97.000 (99.114) +2022-11-14 15:54:14,355 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0756) Prec@1 88.000 (88.083) Prec@5 100.000 (99.139) +2022-11-14 15:54:14,365 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0757) Prec@1 84.000 (87.973) Prec@5 100.000 (99.162) +2022-11-14 15:54:14,377 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1044 (0.0765) Prec@1 84.000 (87.868) Prec@5 100.000 (99.184) +2022-11-14 15:54:14,388 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0756) Prec@1 94.000 (88.026) Prec@5 99.000 (99.179) +2022-11-14 15:54:14,400 Test: [39/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0753) Prec@1 89.000 (88.050) Prec@5 99.000 (99.175) +2022-11-14 15:54:14,413 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0757) Prec@1 87.000 (88.024) Prec@5 98.000 (99.146) +2022-11-14 15:54:14,423 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0758) Prec@1 86.000 (87.976) Prec@5 100.000 (99.167) +2022-11-14 15:54:14,432 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0751) Prec@1 94.000 (88.116) Prec@5 99.000 (99.163) +2022-11-14 15:54:14,442 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0749) Prec@1 90.000 (88.159) Prec@5 99.000 (99.159) +2022-11-14 15:54:14,452 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0749) Prec@1 87.000 (88.133) Prec@5 99.000 (99.156) +2022-11-14 15:54:14,463 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0754) Prec@1 85.000 (88.065) Prec@5 99.000 (99.152) +2022-11-14 15:54:14,474 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0751) Prec@1 90.000 (88.106) Prec@5 99.000 (99.149) +2022-11-14 15:54:14,485 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0758) Prec@1 86.000 (88.062) Prec@5 98.000 (99.125) +2022-11-14 15:54:14,495 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0755) Prec@1 89.000 (88.082) Prec@5 100.000 (99.143) +2022-11-14 15:54:14,506 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0758) Prec@1 87.000 (88.060) Prec@5 100.000 (99.160) +2022-11-14 15:54:14,519 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0755) Prec@1 90.000 (88.098) Prec@5 100.000 (99.176) +2022-11-14 15:54:14,529 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0756) Prec@1 88.000 (88.096) Prec@5 97.000 (99.135) +2022-11-14 15:54:14,539 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0754) Prec@1 89.000 (88.113) Prec@5 100.000 (99.151) +2022-11-14 15:54:14,549 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0755) Prec@1 88.000 (88.111) Prec@5 99.000 (99.148) +2022-11-14 15:54:14,560 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0753) Prec@1 90.000 (88.145) Prec@5 100.000 (99.164) +2022-11-14 15:54:14,571 Test: 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0.0676 (0.0754) Prec@1 90.000 (88.048) Prec@5 99.000 (99.161) +2022-11-14 15:54:14,647 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0750) Prec@1 90.000 (88.079) Prec@5 100.000 (99.175) +2022-11-14 15:54:14,657 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0747) Prec@1 91.000 (88.125) Prec@5 99.000 (99.172) +2022-11-14 15:54:14,668 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0750) Prec@1 86.000 (88.092) Prec@5 99.000 (99.169) +2022-11-14 15:54:14,678 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0752) Prec@1 88.000 (88.091) Prec@5 97.000 (99.136) +2022-11-14 15:54:14,688 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0746) Prec@1 94.000 (88.179) Prec@5 100.000 (99.149) +2022-11-14 15:54:14,698 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0746) Prec@1 90.000 (88.206) Prec@5 99.000 (99.147) +2022-11-14 15:54:14,709 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0742) Prec@1 93.000 (88.275) Prec@5 99.000 (99.145) +2022-11-14 15:54:14,719 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0745) Prec@1 87.000 (88.257) Prec@5 100.000 (99.157) +2022-11-14 15:54:14,732 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0748) Prec@1 85.000 (88.211) Prec@5 98.000 (99.141) +2022-11-14 15:54:14,743 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0746) Prec@1 90.000 (88.236) Prec@5 99.000 (99.139) +2022-11-14 15:54:14,753 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0744) Prec@1 91.000 (88.274) Prec@5 100.000 (99.151) +2022-11-14 15:54:14,763 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0739) Prec@1 94.000 (88.351) Prec@5 100.000 (99.162) +2022-11-14 15:54:14,775 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1120 (0.0744) Prec@1 81.000 (88.253) Prec@5 99.000 (99.160) +2022-11-14 15:54:14,786 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0744) Prec@1 87.000 (88.237) Prec@5 100.000 (99.171) +2022-11-14 15:54:14,795 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0747) Prec@1 85.000 (88.195) Prec@5 97.000 (99.143) +2022-11-14 15:54:14,807 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0750) Prec@1 83.000 (88.128) Prec@5 99.000 (99.141) +2022-11-14 15:54:14,819 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0749) Prec@1 88.000 (88.127) Prec@5 100.000 (99.152) +2022-11-14 15:54:14,831 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0749) Prec@1 85.000 (88.088) Prec@5 99.000 (99.150) +2022-11-14 15:54:14,842 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0750) Prec@1 87.000 (88.074) Prec@5 99.000 (99.148) +2022-11-14 15:54:14,854 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0750) Prec@1 87.000 (88.061) Prec@5 99.000 (99.146) +2022-11-14 15:54:14,866 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0750) Prec@1 86.000 (88.036) Prec@5 100.000 (99.157) +2022-11-14 15:54:14,878 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0750) Prec@1 85.000 (88.000) Prec@5 98.000 (99.143) +2022-11-14 15:54:14,889 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0752) Prec@1 86.000 (87.976) Prec@5 100.000 (99.153) +2022-11-14 15:54:14,897 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0755) Prec@1 84.000 (87.930) Prec@5 100.000 (99.163) +2022-11-14 15:54:14,907 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0759) Prec@1 83.000 (87.874) Prec@5 99.000 (99.161) +2022-11-14 15:54:14,919 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0759) Prec@1 88.000 (87.875) Prec@5 97.000 (99.136) +2022-11-14 15:54:14,931 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0759) Prec@1 88.000 (87.876) Prec@5 100.000 (99.146) +2022-11-14 15:54:14,940 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0758) Prec@1 90.000 (87.900) Prec@5 99.000 (99.144) +2022-11-14 15:54:14,950 Test: [90/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0757) Prec@1 89.000 (87.912) Prec@5 100.000 (99.154) +2022-11-14 15:54:14,961 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0444 (0.0754) Prec@1 93.000 (87.967) Prec@5 99.000 (99.152) +2022-11-14 15:54:14,972 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0753) Prec@1 89.000 (87.978) Prec@5 100.000 (99.161) +2022-11-14 15:54:14,983 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0753) Prec@1 89.000 (87.989) Prec@5 100.000 (99.170) +2022-11-14 15:54:14,993 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0756) Prec@1 83.000 (87.937) Prec@5 99.000 (99.168) +2022-11-14 15:54:15,002 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0755) Prec@1 90.000 (87.958) Prec@5 100.000 (99.177) +2022-11-14 15:54:15,012 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0752) Prec@1 92.000 (88.000) Prec@5 99.000 (99.175) +2022-11-14 15:54:15,023 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0752) Prec@1 89.000 (88.010) Prec@5 100.000 (99.184) +2022-11-14 15:54:15,035 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0755) Prec@1 84.000 (87.970) Prec@5 98.000 (99.172) +2022-11-14 15:54:15,045 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0755) Prec@1 89.000 (87.980) Prec@5 99.000 (99.170) +2022-11-14 15:54:15,105 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:54:15,437 Epoch: [278][0/500] Time 0.023 (0.023) Data 0.243 (0.243) Loss 0.0367 (0.0367) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 15:54:15,682 Epoch: [278][10/500] Time 0.021 (0.022) Data 0.002 (0.024) Loss 0.0621 (0.0494) Prec@1 91.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 15:54:15,923 Epoch: [278][20/500] Time 0.023 (0.022) Data 0.002 (0.013) Loss 0.0236 (0.0408) Prec@1 98.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 15:54:16,266 Epoch: [278][30/500] Time 0.039 (0.025) Data 0.002 (0.010) Loss 0.0182 (0.0351) Prec@1 98.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 15:54:16,610 Epoch: [278][40/500] Time 0.030 (0.026) Data 0.002 (0.008) Loss 0.0324 (0.0346) Prec@1 94.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 15:54:16,962 Epoch: [278][50/500] Time 0.035 (0.027) Data 0.002 (0.007) Loss 0.0367 (0.0349) Prec@1 94.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 15:54:17,295 Epoch: [278][60/500] Time 0.032 (0.028) Data 0.002 (0.006) Loss 0.0340 (0.0348) Prec@1 94.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 15:54:17,653 Epoch: [278][70/500] Time 0.031 (0.028) Data 0.002 (0.005) Loss 0.0447 (0.0360) Prec@1 91.000 (94.250) Prec@5 100.000 (99.875) +2022-11-14 15:54:18,002 Epoch: [278][80/500] Time 0.035 (0.028) Data 0.002 (0.005) Loss 0.0340 (0.0358) Prec@1 93.000 (94.111) Prec@5 99.000 (99.778) +2022-11-14 15:54:18,355 Epoch: [278][90/500] Time 0.039 (0.029) Data 0.002 (0.005) Loss 0.0462 (0.0368) Prec@1 93.000 (94.000) Prec@5 98.000 (99.600) +2022-11-14 15:54:18,706 Epoch: [278][100/500] Time 0.035 (0.029) Data 0.002 (0.004) Loss 0.0503 (0.0381) Prec@1 91.000 (93.727) Prec@5 100.000 (99.636) +2022-11-14 15:54:19,141 Epoch: [278][110/500] Time 0.058 (0.030) Data 0.002 (0.004) Loss 0.0469 (0.0388) Prec@1 90.000 (93.417) Prec@5 100.000 (99.667) +2022-11-14 15:54:19,934 Epoch: [278][120/500] Time 0.074 (0.033) Data 0.002 (0.004) Loss 0.0214 (0.0375) Prec@1 97.000 (93.692) Prec@5 100.000 (99.692) +2022-11-14 15:54:20,657 Epoch: [278][130/500] Time 0.069 (0.035) Data 0.002 (0.004) Loss 0.0623 (0.0392) Prec@1 89.000 (93.357) Prec@5 100.000 (99.714) +2022-11-14 15:54:21,459 Epoch: [278][140/500] Time 0.070 (0.038) Data 0.002 (0.004) Loss 0.0516 (0.0401) Prec@1 90.000 (93.133) Prec@5 98.000 (99.600) +2022-11-14 15:54:22,245 Epoch: [278][150/500] Time 0.078 (0.040) Data 0.002 (0.004) Loss 0.0318 (0.0395) Prec@1 96.000 (93.312) Prec@5 100.000 (99.625) +2022-11-14 15:54:22,999 Epoch: [278][160/500] Time 0.081 (0.042) Data 0.002 (0.003) Loss 0.0310 (0.0390) Prec@1 95.000 (93.412) Prec@5 100.000 (99.647) +2022-11-14 15:54:23,780 Epoch: [278][170/500] Time 0.069 (0.043) Data 0.002 (0.003) Loss 0.0200 (0.0380) Prec@1 97.000 (93.611) Prec@5 100.000 (99.667) +2022-11-14 15:54:24,538 Epoch: [278][180/500] Time 0.079 (0.045) Data 0.002 (0.003) Loss 0.0321 (0.0377) Prec@1 96.000 (93.737) Prec@5 100.000 (99.684) +2022-11-14 15:54:24,933 Epoch: [278][190/500] Time 0.037 (0.044) Data 0.002 (0.003) Loss 0.0359 (0.0376) Prec@1 93.000 (93.700) Prec@5 100.000 (99.700) +2022-11-14 15:54:25,319 Epoch: [278][200/500] Time 0.036 (0.044) Data 0.002 (0.003) Loss 0.0296 (0.0372) Prec@1 95.000 (93.762) Prec@5 100.000 (99.714) +2022-11-14 15:54:25,708 Epoch: [278][210/500] Time 0.035 (0.043) Data 0.002 (0.003) Loss 0.0654 (0.0385) Prec@1 89.000 (93.545) Prec@5 100.000 (99.727) +2022-11-14 15:54:26,094 Epoch: [278][220/500] Time 0.034 (0.043) Data 0.002 (0.003) Loss 0.0276 (0.0380) Prec@1 96.000 (93.652) Prec@5 100.000 (99.739) +2022-11-14 15:54:26,490 Epoch: [278][230/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0347 (0.0379) Prec@1 94.000 (93.667) Prec@5 100.000 (99.750) +2022-11-14 15:54:26,890 Epoch: [278][240/500] Time 0.036 (0.042) Data 0.002 (0.003) Loss 0.0223 (0.0373) Prec@1 94.000 (93.680) Prec@5 100.000 (99.760) +2022-11-14 15:54:27,286 Epoch: [278][250/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0464 (0.0376) Prec@1 94.000 (93.692) Prec@5 100.000 (99.769) +2022-11-14 15:54:27,669 Epoch: [278][260/500] Time 0.036 (0.042) Data 0.002 (0.003) Loss 0.0183 (0.0369) Prec@1 97.000 (93.815) Prec@5 99.000 (99.741) +2022-11-14 15:54:28,060 Epoch: [278][270/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0588 (0.0377) Prec@1 86.000 (93.536) Prec@5 100.000 (99.750) +2022-11-14 15:54:28,451 Epoch: [278][280/500] Time 0.030 (0.041) Data 0.002 (0.003) Loss 0.0719 (0.0389) Prec@1 88.000 (93.345) Prec@5 100.000 (99.759) +2022-11-14 15:54:28,832 Epoch: [278][290/500] Time 0.034 (0.041) Data 0.002 (0.003) Loss 0.0283 (0.0385) Prec@1 96.000 (93.433) Prec@5 100.000 (99.767) +2022-11-14 15:54:29,232 Epoch: [278][300/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0292 (0.0382) Prec@1 95.000 (93.484) Prec@5 100.000 (99.774) +2022-11-14 15:54:29,625 Epoch: [278][310/500] Time 0.042 (0.041) Data 0.002 (0.003) Loss 0.0255 (0.0378) Prec@1 96.000 (93.562) Prec@5 100.000 (99.781) +2022-11-14 15:54:30,012 Epoch: [278][320/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.0316 (0.0376) Prec@1 95.000 (93.606) Prec@5 100.000 (99.788) +2022-11-14 15:54:30,412 Epoch: [278][330/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0751 (0.0387) Prec@1 85.000 (93.353) Prec@5 100.000 (99.794) +2022-11-14 15:54:30,800 Epoch: [278][340/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0216 (0.0382) Prec@1 97.000 (93.457) Prec@5 100.000 (99.800) +2022-11-14 15:54:31,190 Epoch: [278][350/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.0431 (0.0384) Prec@1 93.000 (93.444) Prec@5 99.000 (99.778) +2022-11-14 15:54:31,585 Epoch: [278][360/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.0459 (0.0386) Prec@1 92.000 (93.405) Prec@5 100.000 (99.784) +2022-11-14 15:54:31,980 Epoch: [278][370/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0269 (0.0383) Prec@1 95.000 (93.447) Prec@5 99.000 (99.763) +2022-11-14 15:54:32,372 Epoch: [278][380/500] Time 0.038 (0.040) Data 0.002 (0.003) Loss 0.0746 (0.0392) Prec@1 89.000 (93.333) Prec@5 100.000 (99.769) +2022-11-14 15:54:32,774 Epoch: [278][390/500] Time 0.030 (0.039) Data 0.002 (0.003) Loss 0.0240 (0.0388) Prec@1 98.000 (93.450) Prec@5 99.000 (99.750) +2022-11-14 15:54:33,174 Epoch: [278][400/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0288 (0.0386) Prec@1 95.000 (93.488) Prec@5 99.000 (99.732) +2022-11-14 15:54:33,552 Epoch: [278][410/500] Time 0.028 (0.039) Data 0.002 (0.003) Loss 0.0486 (0.0388) Prec@1 91.000 (93.429) Prec@5 100.000 (99.738) +2022-11-14 15:54:33,958 Epoch: [278][420/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0331 (0.0387) Prec@1 94.000 (93.442) Prec@5 100.000 (99.744) +2022-11-14 15:54:34,362 Epoch: [278][430/500] Time 0.035 (0.039) Data 0.003 (0.003) Loss 0.0391 (0.0387) Prec@1 94.000 (93.455) Prec@5 100.000 (99.750) +2022-11-14 15:54:34,744 Epoch: [278][440/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0246 (0.0384) Prec@1 96.000 (93.511) Prec@5 100.000 (99.756) +2022-11-14 15:54:35,149 Epoch: [278][450/500] Time 0.033 (0.039) Data 0.002 (0.003) Loss 0.0288 (0.0382) Prec@1 95.000 (93.543) Prec@5 100.000 (99.761) +2022-11-14 15:54:35,546 Epoch: [278][460/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0395 (0.0382) Prec@1 94.000 (93.553) Prec@5 100.000 (99.766) +2022-11-14 15:54:35,949 Epoch: [278][470/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0268 (0.0380) Prec@1 96.000 (93.604) Prec@5 100.000 (99.771) +2022-11-14 15:54:36,351 Epoch: [278][480/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0471 (0.0381) Prec@1 91.000 (93.551) Prec@5 100.000 (99.776) +2022-11-14 15:54:36,742 Epoch: [278][490/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.0505 (0.0384) Prec@1 91.000 (93.500) Prec@5 100.000 (99.780) +2022-11-14 15:54:37,085 Epoch: [278][499/500] Time 0.032 (0.038) Data 0.002 (0.003) Loss 0.0181 (0.0380) Prec@1 98.000 (93.588) Prec@5 100.000 (99.784) +2022-11-14 15:54:37,402 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0594 (0.0594) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:54:37,413 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0672) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 15:54:37,422 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0673) Prec@1 87.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 15:54:37,435 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0652) Prec@1 92.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 15:54:37,446 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0678) Prec@1 85.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 15:54:37,455 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0645) Prec@1 92.000 (88.500) Prec@5 100.000 (99.833) +2022-11-14 15:54:37,465 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0626) Prec@1 93.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 15:54:37,477 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0642) Prec@1 87.000 (88.875) Prec@5 100.000 (99.875) +2022-11-14 15:54:37,487 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0653) Prec@1 90.000 (89.000) Prec@5 98.000 (99.667) +2022-11-14 15:54:37,499 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0674) Prec@1 88.000 (88.900) Prec@5 98.000 (99.500) +2022-11-14 15:54:37,513 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0663) Prec@1 91.000 (89.091) Prec@5 100.000 (99.545) +2022-11-14 15:54:37,526 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0671) Prec@1 90.000 (89.167) Prec@5 99.000 (99.500) +2022-11-14 15:54:37,540 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0669) Prec@1 91.000 (89.308) Prec@5 100.000 (99.538) +2022-11-14 15:54:37,554 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0673) Prec@1 88.000 (89.214) Prec@5 99.000 (99.500) +2022-11-14 15:54:37,568 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1088 (0.0700) Prec@1 82.000 (88.733) Prec@5 99.000 (99.467) +2022-11-14 15:54:37,583 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0712) Prec@1 83.000 (88.375) Prec@5 100.000 (99.500) +2022-11-14 15:54:37,597 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0698) Prec@1 94.000 (88.706) Prec@5 98.000 (99.412) +2022-11-14 15:54:37,609 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0714) Prec@1 85.000 (88.500) Prec@5 100.000 (99.444) +2022-11-14 15:54:37,623 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0714) Prec@1 88.000 (88.474) Prec@5 99.000 (99.421) +2022-11-14 15:54:37,637 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0722) Prec@1 86.000 (88.350) Prec@5 100.000 (99.450) +2022-11-14 15:54:37,652 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0725) Prec@1 86.000 (88.238) Prec@5 100.000 (99.476) +2022-11-14 15:54:37,665 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0730) Prec@1 87.000 (88.182) Prec@5 99.000 (99.455) +2022-11-14 15:54:37,677 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0742) Prec@1 86.000 (88.087) Prec@5 98.000 (99.391) +2022-11-14 15:54:37,691 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0751) Prec@1 83.000 (87.875) Prec@5 100.000 (99.417) +2022-11-14 15:54:37,705 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0756) Prec@1 84.000 (87.720) Prec@5 100.000 (99.440) +2022-11-14 15:54:37,718 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0765) Prec@1 86.000 (87.654) Prec@5 98.000 (99.385) +2022-11-14 15:54:37,731 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0479 (0.0755) Prec@1 92.000 (87.815) Prec@5 99.000 (99.370) +2022-11-14 15:54:37,745 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0749) Prec@1 90.000 (87.893) Prec@5 99.000 (99.357) +2022-11-14 15:54:37,760 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0749) Prec@1 89.000 (87.931) Prec@5 99.000 (99.345) +2022-11-14 15:54:37,774 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0745) Prec@1 89.000 (87.967) Prec@5 99.000 (99.333) +2022-11-14 15:54:37,788 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0743) Prec@1 87.000 (87.935) Prec@5 100.000 (99.355) +2022-11-14 15:54:37,800 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0744) Prec@1 87.000 (87.906) Prec@5 98.000 (99.312) +2022-11-14 15:54:37,812 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0747) Prec@1 85.000 (87.818) Prec@5 99.000 (99.303) +2022-11-14 15:54:37,825 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.0757) Prec@1 84.000 (87.706) Prec@5 98.000 (99.265) +2022-11-14 15:54:37,838 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0764) Prec@1 84.000 (87.600) Prec@5 98.000 (99.229) +2022-11-14 15:54:37,851 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0762) Prec@1 91.000 (87.694) Prec@5 100.000 (99.250) +2022-11-14 15:54:37,865 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0761) Prec@1 89.000 (87.730) Prec@5 99.000 (99.243) +2022-11-14 15:54:37,878 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0764) Prec@1 85.000 (87.658) Prec@5 98.000 (99.211) +2022-11-14 15:54:37,894 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0764) Prec@1 88.000 (87.667) Prec@5 99.000 (99.205) +2022-11-14 15:54:37,907 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0763) Prec@1 87.000 (87.650) Prec@5 98.000 (99.175) +2022-11-14 15:54:37,919 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0770) Prec@1 83.000 (87.537) Prec@5 99.000 (99.171) +2022-11-14 15:54:37,934 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0766) Prec@1 91.000 (87.619) Prec@5 100.000 (99.190) +2022-11-14 15:54:37,949 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0766) Prec@1 88.000 (87.628) Prec@5 99.000 (99.186) +2022-11-14 15:54:37,964 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0768) Prec@1 87.000 (87.614) Prec@5 97.000 (99.136) +2022-11-14 15:54:37,979 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0766) Prec@1 89.000 (87.644) Prec@5 98.000 (99.111) +2022-11-14 15:54:37,993 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0773) Prec@1 83.000 (87.543) Prec@5 99.000 (99.109) +2022-11-14 15:54:38,007 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0770) Prec@1 88.000 (87.553) Prec@5 100.000 (99.128) +2022-11-14 15:54:38,020 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0772) Prec@1 87.000 (87.542) Prec@5 98.000 (99.104) +2022-11-14 15:54:38,033 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0766) Prec@1 91.000 (87.612) Prec@5 100.000 (99.122) +2022-11-14 15:54:38,045 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0770) Prec@1 81.000 (87.480) Prec@5 100.000 (99.140) +2022-11-14 15:54:38,060 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0772) Prec@1 88.000 (87.490) Prec@5 100.000 (99.157) +2022-11-14 15:54:38,074 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0771) Prec@1 87.000 (87.481) Prec@5 99.000 (99.154) +2022-11-14 15:54:38,087 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0767) Prec@1 90.000 (87.528) Prec@5 99.000 (99.151) +2022-11-14 15:54:38,101 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0766) Prec@1 89.000 (87.556) Prec@5 99.000 (99.148) +2022-11-14 15:54:38,114 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0766) Prec@1 88.000 (87.564) Prec@5 100.000 (99.164) +2022-11-14 15:54:38,128 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0767) Prec@1 88.000 (87.571) Prec@5 99.000 (99.161) +2022-11-14 15:54:38,143 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0767) Prec@1 87.000 (87.561) Prec@5 99.000 (99.158) +2022-11-14 15:54:38,157 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0766) Prec@1 89.000 (87.586) Prec@5 99.000 (99.155) +2022-11-14 15:54:38,171 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1321 (0.0776) Prec@1 80.000 (87.458) Prec@5 99.000 (99.153) +2022-11-14 15:54:38,184 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0775) Prec@1 89.000 (87.483) Prec@5 99.000 (99.150) +2022-11-14 15:54:38,196 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0776) Prec@1 88.000 (87.492) Prec@5 100.000 (99.164) +2022-11-14 15:54:38,211 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0773) Prec@1 89.000 (87.516) Prec@5 99.000 (99.161) +2022-11-14 15:54:38,224 Test: [62/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0772) Prec@1 88.000 (87.524) Prec@5 100.000 (99.175) +2022-11-14 15:54:38,237 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0435 (0.0767) Prec@1 92.000 (87.594) Prec@5 100.000 (99.188) +2022-11-14 15:54:38,252 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0770) Prec@1 82.000 (87.508) Prec@5 100.000 (99.200) +2022-11-14 15:54:38,266 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0769) Prec@1 88.000 (87.515) Prec@5 99.000 (99.197) +2022-11-14 15:54:38,279 Test: [66/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0439 (0.0765) Prec@1 91.000 (87.567) Prec@5 100.000 (99.209) +2022-11-14 15:54:38,292 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0765) Prec@1 87.000 (87.559) Prec@5 100.000 (99.221) +2022-11-14 15:54:38,304 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0764) Prec@1 89.000 (87.580) Prec@5 98.000 (99.203) +2022-11-14 15:54:38,317 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0766) Prec@1 86.000 (87.557) Prec@5 98.000 (99.186) +2022-11-14 15:54:38,331 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0769) Prec@1 85.000 (87.521) Prec@5 99.000 (99.183) +2022-11-14 15:54:38,346 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0766) Prec@1 90.000 (87.556) Prec@5 100.000 (99.194) +2022-11-14 15:54:38,360 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0762) Prec@1 95.000 (87.658) Prec@5 99.000 (99.192) +2022-11-14 15:54:38,373 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0380 (0.0756) Prec@1 93.000 (87.730) Prec@5 99.000 (99.189) +2022-11-14 15:54:38,386 Test: [74/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1164 (0.0762) Prec@1 82.000 (87.653) Prec@5 100.000 (99.200) +2022-11-14 15:54:38,401 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0758) Prec@1 93.000 (87.724) Prec@5 99.000 (99.197) +2022-11-14 15:54:38,416 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0759) Prec@1 85.000 (87.688) Prec@5 100.000 (99.208) +2022-11-14 15:54:38,429 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0761) Prec@1 84.000 (87.641) Prec@5 97.000 (99.179) +2022-11-14 15:54:38,442 Test: [78/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0762) Prec@1 85.000 (87.608) Prec@5 100.000 (99.190) +2022-11-14 15:54:38,457 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0761) Prec@1 89.000 (87.625) Prec@5 100.000 (99.200) +2022-11-14 15:54:38,472 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0763) Prec@1 84.000 (87.580) Prec@5 98.000 (99.185) +2022-11-14 15:54:38,483 Test: [81/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0764) Prec@1 84.000 (87.537) Prec@5 100.000 (99.195) +2022-11-14 15:54:38,496 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0765) Prec@1 89.000 (87.554) Prec@5 98.000 (99.181) +2022-11-14 15:54:38,510 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0764) Prec@1 87.000 (87.548) Prec@5 98.000 (99.167) +2022-11-14 15:54:38,524 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0764) Prec@1 90.000 (87.576) Prec@5 99.000 (99.165) +2022-11-14 15:54:38,536 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1193 (0.0769) Prec@1 79.000 (87.477) Prec@5 100.000 (99.174) +2022-11-14 15:54:38,549 Test: [86/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0768) Prec@1 89.000 (87.494) Prec@5 100.000 (99.184) +2022-11-14 15:54:38,563 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0768) Prec@1 88.000 (87.500) Prec@5 99.000 (99.182) +2022-11-14 15:54:38,576 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0766) Prec@1 89.000 (87.517) Prec@5 100.000 (99.191) +2022-11-14 15:54:38,591 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0765) Prec@1 90.000 (87.544) Prec@5 100.000 (99.200) +2022-11-14 15:54:38,605 Test: [90/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0764) Prec@1 89.000 (87.560) Prec@5 100.000 (99.209) +2022-11-14 15:54:38,620 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0761) Prec@1 94.000 (87.630) Prec@5 100.000 (99.217) +2022-11-14 15:54:38,633 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0761) Prec@1 87.000 (87.624) Prec@5 100.000 (99.226) +2022-11-14 15:54:38,646 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0760) Prec@1 88.000 (87.628) Prec@5 100.000 (99.234) +2022-11-14 15:54:38,658 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0761) Prec@1 88.000 (87.632) Prec@5 99.000 (99.232) +2022-11-14 15:54:38,671 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0761) Prec@1 87.000 (87.625) Prec@5 100.000 (99.240) +2022-11-14 15:54:38,684 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0758) Prec@1 93.000 (87.680) Prec@5 99.000 (99.237) +2022-11-14 15:54:38,698 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0759) Prec@1 88.000 (87.684) Prec@5 99.000 (99.235) +2022-11-14 15:54:38,714 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0762) Prec@1 85.000 (87.657) Prec@5 99.000 (99.232) +2022-11-14 15:54:38,728 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0762) Prec@1 87.000 (87.650) Prec@5 100.000 (99.240) +2022-11-14 15:54:38,790 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:54:39,120 Epoch: [279][0/500] Time 0.027 (0.027) Data 0.241 (0.241) Loss 0.0577 (0.0577) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:54:39,459 Epoch: [279][10/500] Time 0.031 (0.029) Data 0.002 (0.024) Loss 0.0171 (0.0374) Prec@1 97.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:54:39,850 Epoch: [279][20/500] Time 0.035 (0.032) Data 0.002 (0.013) Loss 0.0359 (0.0369) Prec@1 94.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 15:54:40,250 Epoch: [279][30/500] Time 0.037 (0.033) Data 0.002 (0.010) Loss 0.0304 (0.0353) Prec@1 94.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:54:40,637 Epoch: [279][40/500] Time 0.032 (0.033) Data 0.002 (0.008) Loss 0.0490 (0.0380) Prec@1 92.000 (93.200) Prec@5 100.000 (100.000) +2022-11-14 15:54:41,044 Epoch: [279][50/500] Time 0.042 (0.034) Data 0.002 (0.007) Loss 0.0290 (0.0365) Prec@1 96.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 15:54:41,436 Epoch: [279][60/500] Time 0.034 (0.034) Data 0.002 (0.006) Loss 0.0336 (0.0361) Prec@1 95.000 (93.857) Prec@5 100.000 (100.000) +2022-11-14 15:54:41,833 Epoch: [279][70/500] Time 0.036 (0.034) Data 0.002 (0.005) Loss 0.0390 (0.0365) Prec@1 92.000 (93.625) Prec@5 100.000 (100.000) +2022-11-14 15:54:42,219 Epoch: [279][80/500] Time 0.035 (0.034) Data 0.002 (0.005) Loss 0.0354 (0.0364) Prec@1 96.000 (93.889) Prec@5 100.000 (100.000) +2022-11-14 15:54:42,621 Epoch: [279][90/500] Time 0.030 (0.035) Data 0.002 (0.005) Loss 0.0312 (0.0358) Prec@1 93.000 (93.800) Prec@5 100.000 (100.000) +2022-11-14 15:54:43,016 Epoch: [279][100/500] Time 0.036 (0.035) Data 0.002 (0.004) Loss 0.0272 (0.0351) Prec@1 95.000 (93.909) Prec@5 100.000 (100.000) +2022-11-14 15:54:43,420 Epoch: [279][110/500] Time 0.041 (0.035) Data 0.002 (0.004) Loss 0.0319 (0.0348) Prec@1 92.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 15:54:43,810 Epoch: [279][120/500] Time 0.030 (0.035) Data 0.002 (0.004) Loss 0.0361 (0.0349) Prec@1 94.000 (93.769) Prec@5 100.000 (100.000) +2022-11-14 15:54:44,201 Epoch: [279][130/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0283 (0.0344) Prec@1 96.000 (93.929) Prec@5 99.000 (99.929) +2022-11-14 15:54:44,621 Epoch: [279][140/500] Time 0.035 (0.035) Data 0.002 (0.004) Loss 0.0266 (0.0339) Prec@1 96.000 (94.067) Prec@5 99.000 (99.867) +2022-11-14 15:54:45,393 Epoch: [279][150/500] Time 0.069 (0.037) Data 0.002 (0.004) Loss 0.0299 (0.0336) Prec@1 96.000 (94.188) Prec@5 100.000 (99.875) +2022-11-14 15:54:46,147 Epoch: [279][160/500] Time 0.077 (0.039) Data 0.002 (0.003) Loss 0.0334 (0.0336) Prec@1 94.000 (94.176) Prec@5 100.000 (99.882) +2022-11-14 15:54:46,963 Epoch: [279][170/500] Time 0.088 (0.041) Data 0.002 (0.003) Loss 0.0321 (0.0335) Prec@1 95.000 (94.222) Prec@5 99.000 (99.833) +2022-11-14 15:54:47,758 Epoch: [279][180/500] Time 0.079 (0.042) Data 0.002 (0.003) Loss 0.0292 (0.0333) Prec@1 96.000 (94.316) Prec@5 99.000 (99.789) +2022-11-14 15:54:48,569 Epoch: [279][190/500] Time 0.081 (0.044) Data 0.002 (0.003) Loss 0.0278 (0.0330) Prec@1 97.000 (94.450) Prec@5 100.000 (99.800) +2022-11-14 15:54:49,345 Epoch: [279][200/500] Time 0.074 (0.045) Data 0.002 (0.003) Loss 0.0520 (0.0339) Prec@1 92.000 (94.333) Prec@5 98.000 (99.714) +2022-11-14 15:54:50,126 Epoch: [279][210/500] Time 0.073 (0.046) Data 0.002 (0.003) Loss 0.0206 (0.0333) Prec@1 97.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 15:54:50,873 Epoch: [279][220/500] Time 0.067 (0.047) Data 0.002 (0.003) Loss 0.0500 (0.0341) Prec@1 92.000 (94.348) Prec@5 99.000 (99.696) +2022-11-14 15:54:51,644 Epoch: [279][230/500] Time 0.075 (0.048) Data 0.003 (0.003) Loss 0.0558 (0.0350) Prec@1 92.000 (94.250) Prec@5 98.000 (99.625) +2022-11-14 15:54:52,439 Epoch: [279][240/500] Time 0.083 (0.049) Data 0.002 (0.003) Loss 0.0465 (0.0354) Prec@1 92.000 (94.160) Prec@5 100.000 (99.640) +2022-11-14 15:54:52,987 Epoch: [279][250/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0213 (0.0349) Prec@1 96.000 (94.231) Prec@5 100.000 (99.654) +2022-11-14 15:54:53,453 Epoch: [279][260/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0177 (0.0342) Prec@1 96.000 (94.296) Prec@5 100.000 (99.667) +2022-11-14 15:54:53,930 Epoch: [279][270/500] Time 0.041 (0.049) Data 0.002 (0.003) Loss 0.0367 (0.0343) Prec@1 95.000 (94.321) Prec@5 100.000 (99.679) +2022-11-14 15:54:54,424 Epoch: [279][280/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0292 (0.0342) Prec@1 97.000 (94.414) Prec@5 100.000 (99.690) +2022-11-14 15:54:54,939 Epoch: [279][290/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0392 (0.0343) Prec@1 94.000 (94.400) Prec@5 99.000 (99.667) +2022-11-14 15:54:55,448 Epoch: [279][300/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0202 (0.0339) Prec@1 97.000 (94.484) Prec@5 100.000 (99.677) +2022-11-14 15:54:55,904 Epoch: [279][310/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0239 (0.0336) Prec@1 96.000 (94.531) Prec@5 100.000 (99.688) +2022-11-14 15:54:56,444 Epoch: [279][320/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0270 (0.0334) Prec@1 96.000 (94.576) Prec@5 100.000 (99.697) +2022-11-14 15:54:56,912 Epoch: [279][330/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0270 (0.0332) Prec@1 98.000 (94.676) Prec@5 100.000 (99.706) +2022-11-14 15:54:57,451 Epoch: [279][340/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0441 (0.0335) Prec@1 92.000 (94.600) Prec@5 99.000 (99.686) +2022-11-14 15:54:57,937 Epoch: [279][350/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0382 (0.0336) Prec@1 92.000 (94.528) Prec@5 100.000 (99.694) +2022-11-14 15:54:58,485 Epoch: [279][360/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0210 (0.0333) Prec@1 95.000 (94.541) Prec@5 100.000 (99.703) +2022-11-14 15:54:59,019 Epoch: [279][370/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0148 (0.0328) Prec@1 97.000 (94.605) Prec@5 100.000 (99.711) +2022-11-14 15:54:59,543 Epoch: [279][380/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0343 (0.0328) Prec@1 95.000 (94.615) Prec@5 100.000 (99.718) +2022-11-14 15:55:00,126 Epoch: [279][390/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0238 (0.0326) Prec@1 96.000 (94.650) Prec@5 100.000 (99.725) +2022-11-14 15:55:00,664 Epoch: [279][400/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0355 (0.0327) Prec@1 94.000 (94.634) Prec@5 100.000 (99.732) +2022-11-14 15:55:01,193 Epoch: [279][410/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0193 (0.0324) Prec@1 98.000 (94.714) Prec@5 100.000 (99.738) +2022-11-14 15:55:01,683 Epoch: [279][420/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0540 (0.0329) Prec@1 91.000 (94.628) Prec@5 99.000 (99.721) +2022-11-14 15:55:02,270 Epoch: [279][430/500] Time 0.060 (0.048) Data 0.002 (0.003) Loss 0.0385 (0.0330) Prec@1 94.000 (94.614) Prec@5 100.000 (99.727) +2022-11-14 15:55:02,794 Epoch: [279][440/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0681 (0.0338) Prec@1 87.000 (94.444) Prec@5 99.000 (99.711) +2022-11-14 15:55:03,330 Epoch: [279][450/500] Time 0.042 (0.048) Data 0.003 (0.003) Loss 0.0460 (0.0340) Prec@1 93.000 (94.413) Prec@5 99.000 (99.696) +2022-11-14 15:55:03,844 Epoch: [279][460/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0496 (0.0344) Prec@1 92.000 (94.362) Prec@5 100.000 (99.702) +2022-11-14 15:55:04,415 Epoch: [279][470/500] Time 0.074 (0.048) Data 0.002 (0.003) Loss 0.0335 (0.0343) Prec@1 95.000 (94.375) Prec@5 99.000 (99.688) +2022-11-14 15:55:04,955 Epoch: [279][480/500] Time 0.043 (0.048) Data 0.003 (0.003) Loss 0.0367 (0.0344) Prec@1 94.000 (94.367) Prec@5 100.000 (99.694) +2022-11-14 15:55:05,478 Epoch: [279][490/500] Time 0.042 (0.048) Data 0.002 (0.003) Loss 0.0553 (0.0348) Prec@1 90.000 (94.280) Prec@5 98.000 (99.660) +2022-11-14 15:55:05,969 Epoch: [279][499/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0531 (0.0352) Prec@1 91.000 (94.216) Prec@5 100.000 (99.667) +2022-11-14 15:55:06,305 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0803 (0.0803) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:06,314 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0859 (0.0831) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:06,328 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0594 (0.0752) Prec@1 91.000 (86.333) Prec@5 100.000 (100.000) +2022-11-14 15:55:06,341 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0843 (0.0775) Prec@1 86.000 (86.250) Prec@5 100.000 (100.000) +2022-11-14 15:55:06,351 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0769) Prec@1 88.000 (86.600) Prec@5 99.000 (99.800) +2022-11-14 15:55:06,361 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0379 (0.0704) Prec@1 94.000 (87.833) Prec@5 100.000 (99.833) +2022-11-14 15:55:06,371 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0682) Prec@1 92.000 (88.429) Prec@5 100.000 (99.857) +2022-11-14 15:55:06,384 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.0723) Prec@1 82.000 (87.625) Prec@5 99.000 (99.750) +2022-11-14 15:55:06,396 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0737) Prec@1 88.000 (87.667) Prec@5 100.000 (99.778) +2022-11-14 15:55:06,407 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0733) Prec@1 89.000 (87.800) Prec@5 99.000 (99.700) +2022-11-14 15:55:06,421 Test: [10/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0713) Prec@1 93.000 (88.273) Prec@5 100.000 (99.727) +2022-11-14 15:55:06,435 Test: [11/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0726) Prec@1 85.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 15:55:06,448 Test: [12/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0719) Prec@1 90.000 (88.154) Prec@5 100.000 (99.692) +2022-11-14 15:55:06,463 Test: [13/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0720) Prec@1 86.000 (88.000) Prec@5 100.000 (99.714) +2022-11-14 15:55:06,476 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.0730) Prec@1 85.000 (87.800) Prec@5 99.000 (99.667) +2022-11-14 15:55:06,488 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0734) Prec@1 87.000 (87.750) Prec@5 100.000 (99.688) +2022-11-14 15:55:06,502 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0728) Prec@1 90.000 (87.882) Prec@5 98.000 (99.588) +2022-11-14 15:55:06,516 Test: [17/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0948 (0.0741) Prec@1 84.000 (87.667) Prec@5 99.000 (99.556) +2022-11-14 15:55:06,528 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0934 (0.0751) Prec@1 82.000 (87.368) Prec@5 100.000 (99.579) +2022-11-14 15:55:06,538 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0754) Prec@1 88.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 15:55:06,550 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0754) Prec@1 87.000 (87.381) Prec@5 100.000 (99.619) +2022-11-14 15:55:06,561 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0760) Prec@1 87.000 (87.364) Prec@5 99.000 (99.591) +2022-11-14 15:55:06,574 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0764) Prec@1 88.000 (87.391) Prec@5 99.000 (99.565) +2022-11-14 15:55:06,587 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0808 (0.0765) Prec@1 85.000 (87.292) Prec@5 100.000 (99.583) +2022-11-14 15:55:06,598 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0767) Prec@1 86.000 (87.240) Prec@5 100.000 (99.600) +2022-11-14 15:55:06,608 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0767) Prec@1 86.000 (87.192) Prec@5 100.000 (99.615) +2022-11-14 15:55:06,618 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0765) Prec@1 90.000 (87.296) Prec@5 100.000 (99.630) +2022-11-14 15:55:06,629 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0621 (0.0760) Prec@1 87.000 (87.286) Prec@5 100.000 (99.643) +2022-11-14 15:55:06,640 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0761) Prec@1 89.000 (87.345) Prec@5 99.000 (99.621) +2022-11-14 15:55:06,651 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0765) Prec@1 84.000 (87.233) Prec@5 98.000 (99.567) +2022-11-14 15:55:06,661 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0767) Prec@1 87.000 (87.226) Prec@5 99.000 (99.548) +2022-11-14 15:55:06,673 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0696 (0.0765) Prec@1 88.000 (87.250) Prec@5 100.000 (99.562) +2022-11-14 15:55:06,685 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0772) Prec@1 82.000 (87.091) Prec@5 100.000 (99.576) +2022-11-14 15:55:06,697 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0899 (0.0776) Prec@1 83.000 (86.971) Prec@5 100.000 (99.588) +2022-11-14 15:55:06,711 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0774) Prec@1 91.000 (87.086) Prec@5 98.000 (99.543) +2022-11-14 15:55:06,721 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0773) Prec@1 87.000 (87.083) Prec@5 99.000 (99.528) +2022-11-14 15:55:06,731 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0771) Prec@1 91.000 (87.189) Prec@5 99.000 (99.514) +2022-11-14 15:55:06,743 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1020 (0.0778) Prec@1 83.000 (87.079) Prec@5 99.000 (99.500) +2022-11-14 15:55:06,756 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0771) Prec@1 92.000 (87.205) Prec@5 99.000 (99.487) +2022-11-14 15:55:06,767 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0772) Prec@1 86.000 (87.175) Prec@5 99.000 (99.475) +2022-11-14 15:55:06,781 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.0774) Prec@1 88.000 (87.195) Prec@5 99.000 (99.463) +2022-11-14 15:55:06,794 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0773 (0.0774) Prec@1 86.000 (87.167) Prec@5 99.000 (99.452) +2022-11-14 15:55:06,806 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0771) Prec@1 90.000 (87.233) Prec@5 100.000 (99.465) +2022-11-14 15:55:06,819 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0771) Prec@1 89.000 (87.273) Prec@5 99.000 (99.455) +2022-11-14 15:55:06,831 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0768) Prec@1 88.000 (87.289) Prec@5 99.000 (99.444) +2022-11-14 15:55:06,844 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0974 (0.0773) Prec@1 85.000 (87.239) Prec@5 99.000 (99.435) +2022-11-14 15:55:06,855 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0771) Prec@1 86.000 (87.213) Prec@5 100.000 (99.447) +2022-11-14 15:55:06,866 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.0775) Prec@1 85.000 (87.167) Prec@5 99.000 (99.438) +2022-11-14 15:55:06,877 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0345 (0.0767) Prec@1 93.000 (87.286) Prec@5 100.000 (99.449) +2022-11-14 15:55:06,890 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0960 (0.0770) Prec@1 83.000 (87.200) Prec@5 100.000 (99.460) +2022-11-14 15:55:06,902 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0769) Prec@1 87.000 (87.196) Prec@5 100.000 (99.471) +2022-11-14 15:55:06,913 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0948 (0.0773) Prec@1 85.000 (87.154) Prec@5 99.000 (99.462) +2022-11-14 15:55:06,924 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0771) Prec@1 88.000 (87.170) Prec@5 100.000 (99.472) +2022-11-14 15:55:06,936 Test: [53/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0770) Prec@1 89.000 (87.204) Prec@5 98.000 (99.444) +2022-11-14 15:55:06,947 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0768) Prec@1 88.000 (87.218) Prec@5 100.000 (99.455) +2022-11-14 15:55:06,957 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0765) Prec@1 90.000 (87.268) Prec@5 99.000 (99.446) +2022-11-14 15:55:06,970 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0762) Prec@1 91.000 (87.333) Prec@5 100.000 (99.456) +2022-11-14 15:55:06,984 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0760) Prec@1 92.000 (87.414) Prec@5 100.000 (99.466) +2022-11-14 15:55:06,995 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0762) Prec@1 83.000 (87.339) Prec@5 100.000 (99.475) +2022-11-14 15:55:07,006 Test: [59/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0762) Prec@1 87.000 (87.333) Prec@5 100.000 (99.483) +2022-11-14 15:55:07,017 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0761) Prec@1 90.000 (87.377) Prec@5 99.000 (99.475) +2022-11-14 15:55:07,029 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0566 (0.0758) Prec@1 91.000 (87.435) Prec@5 99.000 (99.468) +2022-11-14 15:55:07,040 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0553 (0.0755) Prec@1 91.000 (87.492) Prec@5 100.000 (99.476) +2022-11-14 15:55:07,052 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0429 (0.0750) Prec@1 95.000 (87.609) Prec@5 100.000 (99.484) +2022-11-14 15:55:07,063 Test: [64/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0751) Prec@1 86.000 (87.585) Prec@5 100.000 (99.492) +2022-11-14 15:55:07,074 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0549 (0.0748) Prec@1 91.000 (87.636) Prec@5 100.000 (99.500) +2022-11-14 15:55:07,087 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0391 (0.0743) Prec@1 95.000 (87.746) Prec@5 100.000 (99.507) +2022-11-14 15:55:07,101 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0741) Prec@1 91.000 (87.794) Prec@5 100.000 (99.515) +2022-11-14 15:55:07,112 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0590 (0.0739) Prec@1 89.000 (87.812) Prec@5 100.000 (99.522) +2022-11-14 15:55:07,122 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0741) Prec@1 86.000 (87.786) Prec@5 97.000 (99.486) +2022-11-14 15:55:07,133 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0745) Prec@1 85.000 (87.746) Prec@5 100.000 (99.493) +2022-11-14 15:55:07,144 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0742) Prec@1 90.000 (87.778) Prec@5 100.000 (99.500) +2022-11-14 15:55:07,157 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0739) Prec@1 94.000 (87.863) Prec@5 100.000 (99.507) +2022-11-14 15:55:07,168 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0321 (0.0733) Prec@1 97.000 (87.986) Prec@5 100.000 (99.514) +2022-11-14 15:55:07,179 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0737) Prec@1 83.000 (87.920) Prec@5 100.000 (99.520) +2022-11-14 15:55:07,192 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0736) Prec@1 90.000 (87.947) Prec@5 98.000 (99.500) +2022-11-14 15:55:07,204 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0738) Prec@1 85.000 (87.909) Prec@5 98.000 (99.481) +2022-11-14 15:55:07,215 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0742) Prec@1 84.000 (87.859) Prec@5 96.000 (99.436) +2022-11-14 15:55:07,227 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0743) Prec@1 87.000 (87.848) Prec@5 100.000 (99.443) +2022-11-14 15:55:07,240 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0743) Prec@1 91.000 (87.888) Prec@5 99.000 (99.438) +2022-11-14 15:55:07,251 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0742) Prec@1 87.000 (87.877) Prec@5 100.000 (99.444) +2022-11-14 15:55:07,264 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0743) Prec@1 86.000 (87.854) Prec@5 100.000 (99.451) +2022-11-14 15:55:07,276 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0744) Prec@1 87.000 (87.843) Prec@5 99.000 (99.446) +2022-11-14 15:55:07,287 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0744) Prec@1 86.000 (87.821) Prec@5 99.000 (99.440) +2022-11-14 15:55:07,299 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0746) Prec@1 86.000 (87.800) Prec@5 99.000 (99.435) +2022-11-14 15:55:07,310 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0749) Prec@1 84.000 (87.756) Prec@5 100.000 (99.442) +2022-11-14 15:55:07,321 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0749) Prec@1 87.000 (87.747) Prec@5 99.000 (99.437) +2022-11-14 15:55:07,331 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0749) Prec@1 86.000 (87.727) Prec@5 99.000 (99.432) +2022-11-14 15:55:07,340 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0749) Prec@1 88.000 (87.730) Prec@5 100.000 (99.438) +2022-11-14 15:55:07,350 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0748) Prec@1 91.000 (87.767) Prec@5 99.000 (99.433) +2022-11-14 15:55:07,360 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0746) Prec@1 92.000 (87.813) Prec@5 100.000 (99.440) +2022-11-14 15:55:07,370 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0375 (0.0742) Prec@1 95.000 (87.891) Prec@5 99.000 (99.435) +2022-11-14 15:55:07,380 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0744) Prec@1 84.000 (87.849) Prec@5 100.000 (99.441) +2022-11-14 15:55:07,392 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0743) Prec@1 90.000 (87.872) Prec@5 99.000 (99.436) +2022-11-14 15:55:07,404 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0744) Prec@1 86.000 (87.853) Prec@5 99.000 (99.432) +2022-11-14 15:55:07,414 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0743) Prec@1 90.000 (87.875) Prec@5 100.000 (99.438) +2022-11-14 15:55:07,424 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0742) Prec@1 90.000 (87.897) Prec@5 98.000 (99.423) +2022-11-14 15:55:07,434 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0745) Prec@1 85.000 (87.867) Prec@5 98.000 (99.408) +2022-11-14 15:55:07,445 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0746) Prec@1 84.000 (87.828) Prec@5 100.000 (99.414) +2022-11-14 15:55:07,456 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0746) Prec@1 88.000 (87.830) Prec@5 99.000 (99.410) +2022-11-14 15:55:07,517 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:55:07,866 Epoch: [280][0/500] Time 0.032 (0.032) Data 0.262 (0.262) Loss 0.0155 (0.0155) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:08,145 Epoch: [280][10/500] Time 0.028 (0.025) Data 0.002 (0.026) Loss 0.0431 (0.0293) Prec@1 93.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:55:08,529 Epoch: [280][20/500] Time 0.047 (0.029) Data 0.002 (0.014) Loss 0.0366 (0.0317) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:09,031 Epoch: [280][30/500] Time 0.036 (0.034) Data 0.002 (0.010) Loss 0.0407 (0.0340) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:09,507 Epoch: [280][40/500] Time 0.042 (0.036) Data 0.002 (0.008) Loss 0.0391 (0.0350) Prec@1 93.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 15:55:10,007 Epoch: [280][50/500] Time 0.052 (0.038) Data 0.002 (0.007) Loss 0.0281 (0.0338) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:55:10,477 Epoch: [280][60/500] Time 0.040 (0.038) Data 0.002 (0.006) Loss 0.0333 (0.0338) Prec@1 95.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 15:55:11,000 Epoch: [280][70/500] Time 0.061 (0.040) Data 0.002 (0.006) Loss 0.0542 (0.0363) Prec@1 91.000 (94.125) Prec@5 100.000 (100.000) +2022-11-14 15:55:11,502 Epoch: [280][80/500] Time 0.046 (0.040) Data 0.003 (0.005) Loss 0.0358 (0.0363) Prec@1 94.000 (94.111) Prec@5 100.000 (100.000) +2022-11-14 15:55:12,019 Epoch: [280][90/500] Time 0.047 (0.041) Data 0.002 (0.005) Loss 0.0356 (0.0362) Prec@1 94.000 (94.100) Prec@5 100.000 (100.000) +2022-11-14 15:55:12,473 Epoch: [280][100/500] Time 0.051 (0.041) Data 0.003 (0.005) Loss 0.0188 (0.0346) Prec@1 97.000 (94.364) Prec@5 100.000 (100.000) +2022-11-14 15:55:12,986 Epoch: [280][110/500] Time 0.045 (0.041) Data 0.002 (0.005) Loss 0.0419 (0.0352) Prec@1 91.000 (94.083) Prec@5 100.000 (100.000) +2022-11-14 15:55:13,410 Epoch: [280][120/500] Time 0.039 (0.041) Data 0.002 (0.004) Loss 0.0178 (0.0339) Prec@1 98.000 (94.385) Prec@5 99.000 (99.923) +2022-11-14 15:55:13,895 Epoch: [280][130/500] Time 0.064 (0.041) Data 0.003 (0.004) Loss 0.0164 (0.0326) Prec@1 97.000 (94.571) Prec@5 100.000 (99.929) +2022-11-14 15:55:14,359 Epoch: [280][140/500] Time 0.053 (0.041) Data 0.002 (0.004) Loss 0.0227 (0.0320) Prec@1 96.000 (94.667) Prec@5 100.000 (99.933) +2022-11-14 15:55:14,793 Epoch: [280][150/500] Time 0.039 (0.041) Data 0.002 (0.004) Loss 0.0519 (0.0332) Prec@1 93.000 (94.562) Prec@5 100.000 (99.938) +2022-11-14 15:55:15,244 Epoch: [280][160/500] Time 0.036 (0.041) Data 0.002 (0.004) Loss 0.0384 (0.0335) Prec@1 95.000 (94.588) Prec@5 100.000 (99.941) +2022-11-14 15:55:15,685 Epoch: [280][170/500] Time 0.039 (0.041) Data 0.002 (0.004) Loss 0.0153 (0.0325) Prec@1 97.000 (94.722) Prec@5 100.000 (99.944) +2022-11-14 15:55:16,125 Epoch: [280][180/500] Time 0.049 (0.041) Data 0.002 (0.004) Loss 0.0224 (0.0320) Prec@1 96.000 (94.789) Prec@5 100.000 (99.947) +2022-11-14 15:55:16,649 Epoch: [280][190/500] Time 0.035 (0.041) Data 0.002 (0.004) Loss 0.0442 (0.0326) Prec@1 93.000 (94.700) Prec@5 100.000 (99.950) +2022-11-14 15:55:17,086 Epoch: [280][200/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0298 (0.0325) Prec@1 95.000 (94.714) Prec@5 100.000 (99.952) +2022-11-14 15:55:17,545 Epoch: [280][210/500] Time 0.069 (0.041) Data 0.002 (0.003) Loss 0.0271 (0.0322) Prec@1 96.000 (94.773) Prec@5 100.000 (99.955) +2022-11-14 15:55:18,112 Epoch: [280][220/500] Time 0.071 (0.041) Data 0.002 (0.003) Loss 0.0378 (0.0324) Prec@1 93.000 (94.696) Prec@5 99.000 (99.913) +2022-11-14 15:55:18,900 Epoch: [280][230/500] Time 0.080 (0.043) Data 0.002 (0.003) Loss 0.0486 (0.0331) Prec@1 92.000 (94.583) Prec@5 100.000 (99.917) +2022-11-14 15:55:19,706 Epoch: [280][240/500] Time 0.083 (0.044) Data 0.002 (0.003) Loss 0.0472 (0.0337) Prec@1 92.000 (94.480) Prec@5 100.000 (99.920) +2022-11-14 15:55:20,540 Epoch: [280][250/500] Time 0.069 (0.045) Data 0.002 (0.003) Loss 0.0456 (0.0341) Prec@1 91.000 (94.346) Prec@5 100.000 (99.923) +2022-11-14 15:55:21,434 Epoch: [280][260/500] Time 0.076 (0.046) Data 0.002 (0.003) Loss 0.0441 (0.0345) Prec@1 92.000 (94.259) Prec@5 100.000 (99.926) +2022-11-14 15:55:22,277 Epoch: [280][270/500] Time 0.073 (0.048) Data 0.002 (0.003) Loss 0.0187 (0.0340) Prec@1 97.000 (94.357) Prec@5 100.000 (99.929) +2022-11-14 15:55:23,080 Epoch: [280][280/500] Time 0.082 (0.048) Data 0.002 (0.003) Loss 0.0454 (0.0343) Prec@1 93.000 (94.310) Prec@5 100.000 (99.931) +2022-11-14 15:55:23,900 Epoch: [280][290/500] Time 0.060 (0.049) Data 0.002 (0.003) Loss 0.0333 (0.0343) Prec@1 95.000 (94.333) Prec@5 100.000 (99.933) +2022-11-14 15:55:24,755 Epoch: [280][300/500] Time 0.073 (0.050) Data 0.002 (0.003) Loss 0.0518 (0.0349) Prec@1 92.000 (94.258) Prec@5 99.000 (99.903) +2022-11-14 15:55:25,574 Epoch: [280][310/500] Time 0.075 (0.051) Data 0.002 (0.003) Loss 0.0389 (0.0350) Prec@1 93.000 (94.219) Prec@5 100.000 (99.906) +2022-11-14 15:55:26,365 Epoch: [280][320/500] Time 0.081 (0.052) Data 0.002 (0.003) Loss 0.0378 (0.0351) Prec@1 91.000 (94.121) Prec@5 100.000 (99.909) +2022-11-14 15:55:27,254 Epoch: [280][330/500] Time 0.082 (0.052) Data 0.002 (0.003) Loss 0.0344 (0.0351) Prec@1 95.000 (94.147) Prec@5 100.000 (99.912) +2022-11-14 15:55:28,066 Epoch: [280][340/500] Time 0.073 (0.053) Data 0.002 (0.003) Loss 0.0539 (0.0356) Prec@1 91.000 (94.057) Prec@5 100.000 (99.914) +2022-11-14 15:55:28,607 Epoch: [280][350/500] Time 0.044 (0.053) Data 0.002 (0.003) Loss 0.0362 (0.0356) Prec@1 96.000 (94.111) Prec@5 99.000 (99.889) +2022-11-14 15:55:29,114 Epoch: [280][360/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0442 (0.0358) Prec@1 93.000 (94.081) Prec@5 100.000 (99.892) +2022-11-14 15:55:29,661 Epoch: [280][370/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0351 (0.0358) Prec@1 94.000 (94.079) Prec@5 99.000 (99.868) +2022-11-14 15:55:30,209 Epoch: [280][380/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0736 (0.0368) Prec@1 87.000 (93.897) Prec@5 100.000 (99.872) +2022-11-14 15:55:30,747 Epoch: [280][390/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0339 (0.0367) Prec@1 95.000 (93.925) Prec@5 100.000 (99.875) +2022-11-14 15:55:31,366 Epoch: [280][400/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0237 (0.0364) Prec@1 95.000 (93.951) Prec@5 100.000 (99.878) +2022-11-14 15:55:31,878 Epoch: [280][410/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0568 (0.0369) Prec@1 89.000 (93.833) Prec@5 100.000 (99.881) +2022-11-14 15:55:32,421 Epoch: [280][420/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0323 (0.0368) Prec@1 95.000 (93.860) Prec@5 100.000 (99.884) +2022-11-14 15:55:32,931 Epoch: [280][430/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0217 (0.0364) Prec@1 98.000 (93.955) Prec@5 100.000 (99.886) +2022-11-14 15:55:33,555 Epoch: [280][440/500] Time 0.064 (0.052) Data 0.002 (0.003) Loss 0.0480 (0.0367) Prec@1 92.000 (93.911) Prec@5 99.000 (99.867) +2022-11-14 15:55:34,078 Epoch: [280][450/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0403 (0.0368) Prec@1 92.000 (93.870) Prec@5 100.000 (99.870) +2022-11-14 15:55:34,626 Epoch: [280][460/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0428 (0.0369) Prec@1 94.000 (93.872) Prec@5 100.000 (99.872) +2022-11-14 15:55:35,184 Epoch: [280][470/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0427 (0.0370) Prec@1 94.000 (93.875) Prec@5 100.000 (99.875) +2022-11-14 15:55:35,726 Epoch: [280][480/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0357 (0.0370) Prec@1 95.000 (93.898) Prec@5 98.000 (99.837) +2022-11-14 15:55:36,280 Epoch: [280][490/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0606 (0.0375) Prec@1 91.000 (93.840) Prec@5 100.000 (99.840) +2022-11-14 15:55:36,777 Epoch: [280][499/500] Time 0.045 (0.052) Data 0.002 (0.003) Loss 0.0195 (0.0371) Prec@1 97.000 (93.902) Prec@5 100.000 (99.843) +2022-11-14 15:55:37,097 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0622 (0.0622) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:37,106 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0666) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:37,115 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0660) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:37,128 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0647) Prec@1 90.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 15:55:37,137 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0641) Prec@1 89.000 (89.200) Prec@5 99.000 (99.600) +2022-11-14 15:55:37,146 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0624) Prec@1 91.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 15:55:37,155 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0626) Prec@1 88.000 (89.286) Prec@5 98.000 (99.429) +2022-11-14 15:55:37,169 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0649) Prec@1 86.000 (88.875) Prec@5 100.000 (99.500) +2022-11-14 15:55:37,179 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0656) Prec@1 88.000 (88.778) Prec@5 98.000 (99.333) +2022-11-14 15:55:37,190 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0657) Prec@1 87.000 (88.600) Prec@5 98.000 (99.200) +2022-11-14 15:55:37,201 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0653) Prec@1 91.000 (88.818) Prec@5 99.000 (99.182) +2022-11-14 15:55:37,212 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0660) Prec@1 90.000 (88.917) Prec@5 99.000 (99.167) +2022-11-14 15:55:37,222 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0646) Prec@1 93.000 (89.231) Prec@5 100.000 (99.231) +2022-11-14 15:55:37,232 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0653) Prec@1 88.000 (89.143) Prec@5 99.000 (99.214) +2022-11-14 15:55:37,244 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0651) Prec@1 88.000 (89.067) Prec@5 99.000 (99.200) +2022-11-14 15:55:37,255 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0668) Prec@1 86.000 (88.875) Prec@5 100.000 (99.250) +2022-11-14 15:55:37,267 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0659) Prec@1 92.000 (89.059) Prec@5 99.000 (99.235) +2022-11-14 15:55:37,280 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0678) Prec@1 85.000 (88.833) Prec@5 100.000 (99.278) +2022-11-14 15:55:37,291 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0685) Prec@1 87.000 (88.737) Prec@5 100.000 (99.316) +2022-11-14 15:55:37,303 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0687) Prec@1 91.000 (88.850) Prec@5 98.000 (99.250) +2022-11-14 15:55:37,315 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0694) Prec@1 87.000 (88.762) Prec@5 100.000 (99.286) +2022-11-14 15:55:37,326 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0704) Prec@1 84.000 (88.545) Prec@5 99.000 (99.273) +2022-11-14 15:55:37,336 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0713) Prec@1 85.000 (88.391) Prec@5 99.000 (99.261) +2022-11-14 15:55:37,348 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0713) Prec@1 87.000 (88.333) Prec@5 100.000 (99.292) +2022-11-14 15:55:37,360 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0726) Prec@1 81.000 (88.040) Prec@5 100.000 (99.320) +2022-11-14 15:55:37,371 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0733) Prec@1 86.000 (87.962) Prec@5 99.000 (99.308) +2022-11-14 15:55:37,383 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0722) Prec@1 92.000 (88.111) Prec@5 99.000 (99.296) +2022-11-14 15:55:37,394 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0719) Prec@1 88.000 (88.107) Prec@5 99.000 (99.286) +2022-11-14 15:55:37,404 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0728) Prec@1 85.000 (88.000) Prec@5 98.000 (99.241) +2022-11-14 15:55:37,414 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0729) Prec@1 89.000 (88.033) Prec@5 100.000 (99.267) +2022-11-14 15:55:37,424 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0724) Prec@1 91.000 (88.129) Prec@5 100.000 (99.290) +2022-11-14 15:55:37,434 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0728) Prec@1 86.000 (88.062) Prec@5 99.000 (99.281) +2022-11-14 15:55:37,445 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0728) Prec@1 88.000 (88.061) Prec@5 99.000 (99.273) +2022-11-14 15:55:37,456 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0735) Prec@1 86.000 (88.000) Prec@5 99.000 (99.265) +2022-11-14 15:55:37,468 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0741) Prec@1 85.000 (87.914) Prec@5 98.000 (99.229) +2022-11-14 15:55:37,479 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0737) Prec@1 91.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 15:55:37,489 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0736) Prec@1 89.000 (88.027) Prec@5 100.000 (99.270) +2022-11-14 15:55:37,500 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0742) Prec@1 85.000 (87.947) Prec@5 98.000 (99.237) +2022-11-14 15:55:37,511 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0736) Prec@1 92.000 (88.051) Prec@5 100.000 (99.256) +2022-11-14 15:55:37,521 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0732) Prec@1 92.000 (88.150) Prec@5 99.000 (99.250) +2022-11-14 15:55:37,532 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0734) Prec@1 85.000 (88.073) Prec@5 99.000 (99.244) +2022-11-14 15:55:37,545 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0730) Prec@1 91.000 (88.143) Prec@5 99.000 (99.238) +2022-11-14 15:55:37,556 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0484 (0.0725) Prec@1 92.000 (88.233) Prec@5 100.000 (99.256) +2022-11-14 15:55:37,566 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0721) Prec@1 92.000 (88.318) Prec@5 97.000 (99.205) +2022-11-14 15:55:37,577 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0720) Prec@1 90.000 (88.356) Prec@5 100.000 (99.222) +2022-11-14 15:55:37,587 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1289 (0.0732) Prec@1 80.000 (88.174) Prec@5 99.000 (99.217) +2022-11-14 15:55:37,599 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0730) Prec@1 87.000 (88.149) Prec@5 100.000 (99.234) +2022-11-14 15:55:37,610 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0736) Prec@1 84.000 (88.062) Prec@5 98.000 (99.208) +2022-11-14 15:55:37,621 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0731) Prec@1 93.000 (88.163) Prec@5 100.000 (99.224) +2022-11-14 15:55:37,632 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0738) Prec@1 84.000 (88.080) Prec@5 100.000 (99.240) +2022-11-14 15:55:37,642 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0737) Prec@1 90.000 (88.118) Prec@5 100.000 (99.255) +2022-11-14 15:55:37,654 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0738) Prec@1 84.000 (88.038) Prec@5 98.000 (99.231) +2022-11-14 15:55:37,665 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0736) Prec@1 91.000 (88.094) Prec@5 100.000 (99.245) +2022-11-14 15:55:37,675 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0734) Prec@1 89.000 (88.111) Prec@5 99.000 (99.241) +2022-11-14 15:55:37,685 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0732) Prec@1 91.000 (88.164) Prec@5 100.000 (99.255) +2022-11-14 15:55:37,694 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0733) Prec@1 86.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 15:55:37,706 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0734) Prec@1 85.000 (88.070) Prec@5 100.000 (99.263) +2022-11-14 15:55:37,717 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0735) Prec@1 88.000 (88.069) Prec@5 100.000 (99.276) +2022-11-14 15:55:37,728 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0738) Prec@1 84.000 (88.000) Prec@5 100.000 (99.288) +2022-11-14 15:55:37,740 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0742) Prec@1 81.000 (87.883) Prec@5 100.000 (99.300) +2022-11-14 15:55:37,752 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0741) Prec@1 90.000 (87.918) Prec@5 98.000 (99.279) +2022-11-14 15:55:37,763 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0738) Prec@1 92.000 (87.984) Prec@5 99.000 (99.274) +2022-11-14 15:55:37,772 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0736) Prec@1 91.000 (88.032) Prec@5 99.000 (99.270) +2022-11-14 15:55:37,784 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0732) Prec@1 90.000 (88.062) Prec@5 100.000 (99.281) +2022-11-14 15:55:37,794 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0736) Prec@1 84.000 (88.000) Prec@5 100.000 (99.292) +2022-11-14 15:55:37,805 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0736) Prec@1 88.000 (88.000) Prec@5 99.000 (99.288) +2022-11-14 15:55:37,815 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0331 (0.0730) Prec@1 95.000 (88.104) Prec@5 100.000 (99.299) +2022-11-14 15:55:37,825 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0734) Prec@1 86.000 (88.074) Prec@5 97.000 (99.265) +2022-11-14 15:55:37,835 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0731) Prec@1 91.000 (88.116) Prec@5 99.000 (99.261) +2022-11-14 15:55:37,845 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0734) Prec@1 83.000 (88.043) Prec@5 99.000 (99.257) +2022-11-14 15:55:37,856 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0736) Prec@1 87.000 (88.028) Prec@5 99.000 (99.254) +2022-11-14 15:55:37,868 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0734) Prec@1 90.000 (88.056) Prec@5 100.000 (99.264) +2022-11-14 15:55:37,879 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0733) Prec@1 91.000 (88.096) Prec@5 99.000 (99.260) +2022-11-14 15:55:37,889 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0357 (0.0728) Prec@1 96.000 (88.203) Prec@5 100.000 (99.270) +2022-11-14 15:55:37,900 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1257 (0.0735) Prec@1 80.000 (88.093) Prec@5 100.000 (99.280) +2022-11-14 15:55:37,911 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0733) Prec@1 92.000 (88.145) Prec@5 100.000 (99.289) +2022-11-14 15:55:37,922 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0735) Prec@1 86.000 (88.117) Prec@5 100.000 (99.299) +2022-11-14 15:55:37,933 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0737) Prec@1 86.000 (88.090) Prec@5 98.000 (99.282) +2022-11-14 15:55:37,944 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0737) Prec@1 88.000 (88.089) Prec@5 100.000 (99.291) +2022-11-14 15:55:37,955 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0738) Prec@1 84.000 (88.037) Prec@5 98.000 (99.275) +2022-11-14 15:55:37,966 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0740) Prec@1 87.000 (88.025) Prec@5 97.000 (99.247) +2022-11-14 15:55:37,978 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0741) Prec@1 86.000 (88.000) Prec@5 100.000 (99.256) +2022-11-14 15:55:37,990 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0740) Prec@1 88.000 (88.000) Prec@5 100.000 (99.265) +2022-11-14 15:55:38,004 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0739) Prec@1 90.000 (88.024) Prec@5 98.000 (99.250) +2022-11-14 15:55:38,016 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0740) Prec@1 84.000 (87.976) Prec@5 99.000 (99.247) +2022-11-14 15:55:38,027 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0744) Prec@1 82.000 (87.907) Prec@5 99.000 (99.244) +2022-11-14 15:55:38,038 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0745) Prec@1 87.000 (87.897) Prec@5 100.000 (99.253) +2022-11-14 15:55:38,049 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0746) Prec@1 87.000 (87.886) Prec@5 99.000 (99.250) +2022-11-14 15:55:38,062 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0746) Prec@1 86.000 (87.865) Prec@5 100.000 (99.258) +2022-11-14 15:55:38,072 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0746) Prec@1 89.000 (87.878) Prec@5 100.000 (99.267) +2022-11-14 15:55:38,084 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0744) Prec@1 91.000 (87.912) Prec@5 100.000 (99.275) +2022-11-14 15:55:38,095 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0742) Prec@1 93.000 (87.967) Prec@5 99.000 (99.272) +2022-11-14 15:55:38,106 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0742) Prec@1 87.000 (87.957) Prec@5 100.000 (99.280) +2022-11-14 15:55:38,117 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0743) Prec@1 86.000 (87.936) Prec@5 100.000 (99.287) +2022-11-14 15:55:38,127 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0745) Prec@1 86.000 (87.916) Prec@5 100.000 (99.295) +2022-11-14 15:55:38,138 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0745) Prec@1 90.000 (87.938) Prec@5 100.000 (99.302) +2022-11-14 15:55:38,148 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0742) Prec@1 92.000 (87.979) Prec@5 98.000 (99.289) +2022-11-14 15:55:38,158 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0743) Prec@1 86.000 (87.959) Prec@5 98.000 (99.276) +2022-11-14 15:55:38,168 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0744) Prec@1 85.000 (87.929) Prec@5 100.000 (99.283) +2022-11-14 15:55:38,178 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0744) Prec@1 88.000 (87.930) Prec@5 100.000 (99.290) +2022-11-14 15:55:38,238 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:55:38,577 Epoch: [281][0/500] Time 0.027 (0.027) Data 0.249 (0.249) Loss 0.0346 (0.0346) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:55:38,874 Epoch: [281][10/500] Time 0.027 (0.026) Data 0.002 (0.025) Loss 0.0479 (0.0413) Prec@1 94.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:55:39,191 Epoch: [281][20/500] Time 0.024 (0.027) Data 0.002 (0.014) Loss 0.0347 (0.0391) Prec@1 96.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 15:55:39,497 Epoch: [281][30/500] Time 0.026 (0.027) Data 0.002 (0.010) Loss 0.0321 (0.0373) Prec@1 94.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 15:55:39,830 Epoch: [281][40/500] Time 0.040 (0.027) Data 0.002 (0.008) Loss 0.0360 (0.0371) Prec@1 94.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 15:55:40,157 Epoch: [281][50/500] Time 0.029 (0.028) Data 0.002 (0.007) Loss 0.0399 (0.0375) Prec@1 94.000 (94.167) Prec@5 100.000 (100.000) +2022-11-14 15:55:40,475 Epoch: [281][60/500] Time 0.029 (0.028) Data 0.003 (0.006) Loss 0.0288 (0.0363) Prec@1 96.000 (94.429) Prec@5 100.000 (100.000) +2022-11-14 15:55:40,958 Epoch: [281][70/500] Time 0.071 (0.030) Data 0.002 (0.006) Loss 0.0368 (0.0364) Prec@1 94.000 (94.375) Prec@5 100.000 (100.000) +2022-11-14 15:55:41,779 Epoch: [281][80/500] Time 0.078 (0.035) Data 0.002 (0.005) Loss 0.0452 (0.0373) Prec@1 92.000 (94.111) Prec@5 99.000 (99.889) +2022-11-14 15:55:42,687 Epoch: [281][90/500] Time 0.109 (0.040) Data 0.002 (0.005) Loss 0.0180 (0.0354) Prec@1 97.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 15:55:43,522 Epoch: [281][100/500] Time 0.074 (0.043) Data 0.002 (0.005) Loss 0.0447 (0.0362) Prec@1 95.000 (94.455) Prec@5 100.000 (99.909) +2022-11-14 15:55:44,391 Epoch: [281][110/500] Time 0.062 (0.046) Data 0.002 (0.004) Loss 0.0147 (0.0344) Prec@1 99.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 15:55:45,290 Epoch: [281][120/500] Time 0.118 (0.049) Data 0.002 (0.004) Loss 0.0323 (0.0343) Prec@1 95.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 15:55:46,072 Epoch: [281][130/500] Time 0.085 (0.051) Data 0.002 (0.004) Loss 0.0521 (0.0356) Prec@1 90.000 (94.500) Prec@5 99.000 (99.857) +2022-11-14 15:55:46,890 Epoch: [281][140/500] Time 0.077 (0.053) Data 0.002 (0.004) Loss 0.0148 (0.0342) Prec@1 97.000 (94.667) Prec@5 100.000 (99.867) +2022-11-14 15:55:47,324 Epoch: [281][150/500] Time 0.039 (0.052) Data 0.002 (0.004) Loss 0.0272 (0.0337) Prec@1 95.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 15:55:47,725 Epoch: [281][160/500] Time 0.038 (0.051) Data 0.002 (0.004) Loss 0.0145 (0.0326) Prec@1 97.000 (94.824) Prec@5 100.000 (99.882) +2022-11-14 15:55:48,205 Epoch: [281][170/500] Time 0.045 (0.050) Data 0.002 (0.004) Loss 0.0291 (0.0324) Prec@1 96.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 15:55:48,609 Epoch: [281][180/500] Time 0.033 (0.049) Data 0.003 (0.003) Loss 0.0497 (0.0333) Prec@1 92.000 (94.737) Prec@5 100.000 (99.895) +2022-11-14 15:55:49,027 Epoch: [281][190/500] Time 0.034 (0.049) Data 0.003 (0.003) Loss 0.0410 (0.0337) Prec@1 92.000 (94.600) Prec@5 99.000 (99.850) +2022-11-14 15:55:49,426 Epoch: [281][200/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0395 (0.0340) Prec@1 92.000 (94.476) Prec@5 100.000 (99.857) +2022-11-14 15:55:49,833 Epoch: [281][210/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0126 (0.0330) Prec@1 99.000 (94.682) Prec@5 100.000 (99.864) +2022-11-14 15:55:50,317 Epoch: [281][220/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0371 (0.0332) Prec@1 94.000 (94.652) Prec@5 100.000 (99.870) +2022-11-14 15:55:50,705 Epoch: [281][230/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0515 (0.0340) Prec@1 92.000 (94.542) Prec@5 100.000 (99.875) +2022-11-14 15:55:51,127 Epoch: [281][240/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.0312 (0.0338) Prec@1 96.000 (94.600) Prec@5 100.000 (99.880) +2022-11-14 15:55:51,553 Epoch: [281][250/500] Time 0.034 (0.046) Data 0.002 (0.003) Loss 0.0292 (0.0337) Prec@1 95.000 (94.615) Prec@5 100.000 (99.885) +2022-11-14 15:55:52,001 Epoch: [281][260/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0197 (0.0331) Prec@1 97.000 (94.704) Prec@5 100.000 (99.889) +2022-11-14 15:55:52,417 Epoch: [281][270/500] Time 0.039 (0.046) Data 0.002 (0.003) Loss 0.0398 (0.0334) Prec@1 94.000 (94.679) Prec@5 100.000 (99.893) +2022-11-14 15:55:52,825 Epoch: [281][280/500] Time 0.037 (0.045) Data 0.002 (0.003) Loss 0.0614 (0.0343) Prec@1 90.000 (94.517) Prec@5 100.000 (99.897) +2022-11-14 15:55:53,244 Epoch: [281][290/500] Time 0.038 (0.045) Data 0.002 (0.003) Loss 0.0242 (0.0340) Prec@1 96.000 (94.567) Prec@5 99.000 (99.867) +2022-11-14 15:55:53,699 Epoch: [281][300/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0322 (0.0340) Prec@1 96.000 (94.613) Prec@5 100.000 (99.871) +2022-11-14 15:55:54,124 Epoch: [281][310/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0174 (0.0334) Prec@1 97.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 15:55:54,537 Epoch: [281][320/500] Time 0.037 (0.044) Data 0.002 (0.003) Loss 0.0228 (0.0331) Prec@1 96.000 (94.727) Prec@5 100.000 (99.879) +2022-11-14 15:55:55,004 Epoch: [281][330/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0189 (0.0327) Prec@1 97.000 (94.794) Prec@5 100.000 (99.882) +2022-11-14 15:55:55,434 Epoch: [281][340/500] Time 0.033 (0.044) Data 0.003 (0.003) Loss 0.0489 (0.0332) Prec@1 92.000 (94.714) Prec@5 100.000 (99.886) +2022-11-14 15:55:55,883 Epoch: [281][350/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0325 (0.0331) Prec@1 95.000 (94.722) Prec@5 99.000 (99.861) +2022-11-14 15:55:56,298 Epoch: [281][360/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0226 (0.0329) Prec@1 96.000 (94.757) Prec@5 100.000 (99.865) +2022-11-14 15:55:56,757 Epoch: [281][370/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0376 (0.0330) Prec@1 92.000 (94.684) Prec@5 99.000 (99.842) +2022-11-14 15:55:57,172 Epoch: [281][380/500] Time 0.035 (0.044) Data 0.002 (0.003) Loss 0.0362 (0.0331) Prec@1 94.000 (94.667) Prec@5 99.000 (99.821) +2022-11-14 15:55:57,575 Epoch: [281][390/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0298 (0.0330) Prec@1 94.000 (94.650) Prec@5 100.000 (99.825) +2022-11-14 15:55:57,994 Epoch: [281][400/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0337 (0.0330) Prec@1 94.000 (94.634) Prec@5 100.000 (99.829) +2022-11-14 15:55:58,411 Epoch: [281][410/500] Time 0.040 (0.043) Data 0.003 (0.003) Loss 0.0270 (0.0329) Prec@1 95.000 (94.643) Prec@5 100.000 (99.833) +2022-11-14 15:55:58,825 Epoch: [281][420/500] Time 0.031 (0.043) Data 0.002 (0.003) Loss 0.0407 (0.0330) Prec@1 94.000 (94.628) Prec@5 99.000 (99.814) +2022-11-14 15:55:59,268 Epoch: [281][430/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0575 (0.0336) Prec@1 91.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 15:55:59,719 Epoch: [281][440/500] Time 0.034 (0.043) Data 0.002 (0.003) Loss 0.0391 (0.0337) Prec@1 93.000 (94.511) Prec@5 98.000 (99.778) +2022-11-14 15:56:00,509 Epoch: [281][450/500] Time 0.076 (0.043) Data 0.002 (0.003) Loss 0.0511 (0.0341) Prec@1 93.000 (94.478) Prec@5 98.000 (99.739) +2022-11-14 15:56:01,251 Epoch: [281][460/500] Time 0.058 (0.044) Data 0.002 (0.003) Loss 0.0216 (0.0338) Prec@1 96.000 (94.511) Prec@5 100.000 (99.745) +2022-11-14 15:56:02,278 Epoch: [281][470/500] Time 0.080 (0.045) Data 0.002 (0.003) Loss 0.0316 (0.0338) Prec@1 92.000 (94.458) Prec@5 100.000 (99.750) +2022-11-14 15:56:03,220 Epoch: [281][480/500] Time 0.126 (0.046) Data 0.002 (0.003) Loss 0.0407 (0.0339) Prec@1 92.000 (94.408) Prec@5 100.000 (99.755) +2022-11-14 15:56:04,302 Epoch: [281][490/500] Time 0.123 (0.047) Data 0.002 (0.003) Loss 0.0326 (0.0339) Prec@1 92.000 (94.360) Prec@5 100.000 (99.760) +2022-11-14 15:56:05,019 Epoch: [281][499/500] Time 0.068 (0.047) Data 0.002 (0.003) Loss 0.0435 (0.0341) Prec@1 93.000 (94.333) Prec@5 100.000 (99.765) +2022-11-14 15:56:05,334 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0750 (0.0750) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:05,342 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0752) Prec@1 87.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 15:56:05,352 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0738) Prec@1 87.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 15:56:05,367 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0704) Prec@1 90.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 15:56:05,378 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0711) Prec@1 88.000 (87.600) Prec@5 100.000 (99.800) +2022-11-14 15:56:05,389 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0425 (0.0663) Prec@1 95.000 (88.833) Prec@5 100.000 (99.833) +2022-11-14 15:56:05,398 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0648) Prec@1 92.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 15:56:05,410 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0667) Prec@1 88.000 (89.125) Prec@5 100.000 (99.875) +2022-11-14 15:56:05,420 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0680) Prec@1 88.000 (89.000) Prec@5 99.000 (99.778) +2022-11-14 15:56:05,434 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0688) Prec@1 88.000 (88.900) Prec@5 99.000 (99.700) +2022-11-14 15:56:05,448 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0680) Prec@1 88.000 (88.818) Prec@5 100.000 (99.727) +2022-11-14 15:56:05,462 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0684) Prec@1 89.000 (88.833) Prec@5 100.000 (99.750) +2022-11-14 15:56:05,478 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0682) Prec@1 89.000 (88.846) Prec@5 100.000 (99.769) +2022-11-14 15:56:05,492 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0682) Prec@1 90.000 (88.929) Prec@5 99.000 (99.714) +2022-11-14 15:56:05,505 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0693) Prec@1 86.000 (88.733) Prec@5 99.000 (99.667) +2022-11-14 15:56:05,518 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0700) Prec@1 87.000 (88.625) Prec@5 99.000 (99.625) +2022-11-14 15:56:05,534 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0698) Prec@1 91.000 (88.765) Prec@5 97.000 (99.471) +2022-11-14 15:56:05,549 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0720) Prec@1 85.000 (88.556) Prec@5 99.000 (99.444) +2022-11-14 15:56:05,566 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0733) Prec@1 82.000 (88.211) Prec@5 100.000 (99.474) +2022-11-14 15:56:05,583 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0746) Prec@1 85.000 (88.050) Prec@5 99.000 (99.450) +2022-11-14 15:56:05,596 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0746) Prec@1 86.000 (87.952) Prec@5 100.000 (99.476) +2022-11-14 15:56:05,608 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0757) Prec@1 82.000 (87.682) Prec@5 100.000 (99.500) +2022-11-14 15:56:05,621 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0759) Prec@1 88.000 (87.696) Prec@5 99.000 (99.478) +2022-11-14 15:56:05,636 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0756) Prec@1 89.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 15:56:05,652 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0763) Prec@1 86.000 (87.680) Prec@5 100.000 (99.520) +2022-11-14 15:56:05,666 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0771) Prec@1 85.000 (87.577) Prec@5 97.000 (99.423) +2022-11-14 15:56:05,682 Test: [26/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0764) Prec@1 92.000 (87.741) Prec@5 100.000 (99.444) +2022-11-14 15:56:05,699 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0757) Prec@1 90.000 (87.821) Prec@5 100.000 (99.464) +2022-11-14 15:56:05,713 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0751) Prec@1 91.000 (87.931) Prec@5 99.000 (99.448) +2022-11-14 15:56:05,727 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0749) Prec@1 87.000 (87.900) Prec@5 100.000 (99.467) +2022-11-14 15:56:05,741 Test: [30/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0743) Prec@1 88.000 (87.903) Prec@5 99.000 (99.452) +2022-11-14 15:56:05,759 Test: [31/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0741) Prec@1 88.000 (87.906) Prec@5 98.000 (99.406) +2022-11-14 15:56:05,773 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0743) Prec@1 87.000 (87.879) Prec@5 99.000 (99.394) +2022-11-14 15:56:05,789 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0750) Prec@1 81.000 (87.676) Prec@5 99.000 (99.382) +2022-11-14 15:56:05,804 Test: [34/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0752) Prec@1 88.000 (87.686) Prec@5 99.000 (99.371) +2022-11-14 15:56:05,818 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0752) Prec@1 89.000 (87.722) Prec@5 100.000 (99.389) +2022-11-14 15:56:05,834 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0753) Prec@1 88.000 (87.730) Prec@5 97.000 (99.324) +2022-11-14 15:56:05,850 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0757) Prec@1 84.000 (87.632) Prec@5 99.000 (99.316) +2022-11-14 15:56:05,864 Test: [38/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0752) Prec@1 92.000 (87.744) Prec@5 100.000 (99.333) +2022-11-14 15:56:05,878 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0751) Prec@1 92.000 (87.850) Prec@5 98.000 (99.300) +2022-11-14 15:56:05,892 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0759) Prec@1 80.000 (87.659) Prec@5 98.000 (99.268) +2022-11-14 15:56:05,907 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0760) Prec@1 87.000 (87.643) Prec@5 98.000 (99.238) +2022-11-14 15:56:05,922 Test: [42/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0756) Prec@1 92.000 (87.744) Prec@5 100.000 (99.256) +2022-11-14 15:56:05,937 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0757) Prec@1 86.000 (87.705) Prec@5 98.000 (99.227) +2022-11-14 15:56:05,954 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0418 (0.0749) Prec@1 94.000 (87.844) Prec@5 100.000 (99.244) +2022-11-14 15:56:05,969 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0756) Prec@1 82.000 (87.717) Prec@5 99.000 (99.239) +2022-11-14 15:56:05,985 Test: [46/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0754) Prec@1 90.000 (87.766) Prec@5 100.000 (99.255) +2022-11-14 15:56:06,000 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0759) Prec@1 83.000 (87.667) Prec@5 98.000 (99.229) +2022-11-14 15:56:06,013 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0756) Prec@1 86.000 (87.633) Prec@5 100.000 (99.245) +2022-11-14 15:56:06,024 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1089 (0.0763) Prec@1 83.000 (87.540) Prec@5 98.000 (99.220) +2022-11-14 15:56:06,041 Test: [50/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0763) Prec@1 85.000 (87.490) Prec@5 100.000 (99.235) +2022-11-14 15:56:06,056 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0763) Prec@1 87.000 (87.481) Prec@5 99.000 (99.231) +2022-11-14 15:56:06,071 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0761) Prec@1 89.000 (87.509) Prec@5 100.000 (99.245) +2022-11-14 15:56:06,086 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0758) Prec@1 90.000 (87.556) Prec@5 98.000 (99.222) +2022-11-14 15:56:06,104 Test: [54/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0763) Prec@1 84.000 (87.491) Prec@5 100.000 (99.236) +2022-11-14 15:56:06,118 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0764) Prec@1 87.000 (87.482) Prec@5 97.000 (99.196) +2022-11-14 15:56:06,135 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0761) Prec@1 90.000 (87.526) Prec@5 100.000 (99.211) +2022-11-14 15:56:06,151 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0762) Prec@1 88.000 (87.534) Prec@5 99.000 (99.207) +2022-11-14 15:56:06,166 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1075 (0.0767) Prec@1 81.000 (87.424) Prec@5 100.000 (99.220) +2022-11-14 15:56:06,178 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0768) Prec@1 87.000 (87.417) Prec@5 100.000 (99.233) +2022-11-14 15:56:06,192 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0765) Prec@1 92.000 (87.492) Prec@5 99.000 (99.230) +2022-11-14 15:56:06,207 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0761) Prec@1 89.000 (87.516) Prec@5 99.000 (99.226) +2022-11-14 15:56:06,221 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0759) Prec@1 90.000 (87.556) Prec@5 100.000 (99.238) +2022-11-14 15:56:06,235 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0756) Prec@1 91.000 (87.609) Prec@5 99.000 (99.234) +2022-11-14 15:56:06,251 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0759) Prec@1 83.000 (87.538) Prec@5 100.000 (99.246) +2022-11-14 15:56:06,269 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0759) Prec@1 87.000 (87.530) Prec@5 99.000 (99.242) +2022-11-14 15:56:06,283 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0756) Prec@1 91.000 (87.582) Prec@5 100.000 (99.254) +2022-11-14 15:56:06,297 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0754) Prec@1 91.000 (87.632) Prec@5 99.000 (99.250) +2022-11-14 15:56:06,309 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0752) Prec@1 91.000 (87.681) Prec@5 98.000 (99.232) +2022-11-14 15:56:06,323 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0754) Prec@1 87.000 (87.671) Prec@5 98.000 (99.214) +2022-11-14 15:56:06,338 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0756) Prec@1 87.000 (87.662) Prec@5 98.000 (99.197) +2022-11-14 15:56:06,353 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0754) Prec@1 89.000 (87.681) Prec@5 100.000 (99.208) +2022-11-14 15:56:06,369 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0751) Prec@1 92.000 (87.740) Prec@5 100.000 (99.219) +2022-11-14 15:56:06,385 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0358 (0.0745) Prec@1 94.000 (87.824) Prec@5 100.000 (99.230) +2022-11-14 15:56:06,400 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1201 (0.0751) Prec@1 83.000 (87.760) Prec@5 100.000 (99.240) +2022-11-14 15:56:06,413 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0751) Prec@1 90.000 (87.789) Prec@5 100.000 (99.250) +2022-11-14 15:56:06,428 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0753) Prec@1 86.000 (87.766) Prec@5 99.000 (99.247) +2022-11-14 15:56:06,443 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0754) Prec@1 86.000 (87.744) Prec@5 98.000 (99.231) +2022-11-14 15:56:06,459 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0756) Prec@1 86.000 (87.722) Prec@5 100.000 (99.241) +2022-11-14 15:56:06,472 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0755) Prec@1 89.000 (87.737) Prec@5 100.000 (99.250) +2022-11-14 15:56:06,486 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0754) Prec@1 89.000 (87.753) Prec@5 98.000 (99.235) +2022-11-14 15:56:06,503 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0757) Prec@1 84.000 (87.707) Prec@5 100.000 (99.244) +2022-11-14 15:56:06,518 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0759) Prec@1 86.000 (87.687) Prec@5 100.000 (99.253) +2022-11-14 15:56:06,532 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0757) Prec@1 89.000 (87.702) Prec@5 98.000 (99.238) +2022-11-14 15:56:06,548 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0758) Prec@1 87.000 (87.694) Prec@5 100.000 (99.247) +2022-11-14 15:56:06,562 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1205 (0.0763) Prec@1 81.000 (87.616) Prec@5 98.000 (99.233) +2022-11-14 15:56:06,575 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0763) Prec@1 86.000 (87.598) Prec@5 100.000 (99.241) +2022-11-14 15:56:06,590 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0763) Prec@1 85.000 (87.568) Prec@5 98.000 (99.227) +2022-11-14 15:56:06,604 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0761) Prec@1 92.000 (87.618) Prec@5 99.000 (99.225) +2022-11-14 15:56:06,617 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0761) Prec@1 88.000 (87.622) Prec@5 99.000 (99.222) +2022-11-14 15:56:06,632 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0366 (0.0757) Prec@1 93.000 (87.681) Prec@5 100.000 (99.231) +2022-11-14 15:56:06,646 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0290 (0.0752) Prec@1 94.000 (87.750) Prec@5 100.000 (99.239) +2022-11-14 15:56:06,660 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0751) Prec@1 89.000 (87.763) Prec@5 100.000 (99.247) +2022-11-14 15:56:06,674 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0749) Prec@1 90.000 (87.787) Prec@5 99.000 (99.245) +2022-11-14 15:56:06,688 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0751) Prec@1 83.000 (87.737) Prec@5 100.000 (99.253) +2022-11-14 15:56:06,702 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0750) Prec@1 89.000 (87.750) Prec@5 98.000 (99.240) +2022-11-14 15:56:06,718 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0748) Prec@1 92.000 (87.794) Prec@5 100.000 (99.247) +2022-11-14 15:56:06,733 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0749) Prec@1 89.000 (87.806) Prec@5 98.000 (99.235) +2022-11-14 15:56:06,749 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0751) Prec@1 86.000 (87.788) Prec@5 100.000 (99.242) +2022-11-14 15:56:06,767 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0752) Prec@1 86.000 (87.770) Prec@5 100.000 (99.250) +2022-11-14 15:56:06,830 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:56:07,190 Epoch: [282][0/500] Time 0.023 (0.023) Data 0.263 (0.263) Loss 0.0255 (0.0255) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:07,471 Epoch: [282][10/500] Time 0.028 (0.025) Data 0.002 (0.026) Loss 0.0223 (0.0239) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:07,762 Epoch: [282][20/500] Time 0.024 (0.025) Data 0.002 (0.014) Loss 0.0182 (0.0220) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 15:56:08,101 Epoch: [282][30/500] Time 0.046 (0.027) Data 0.002 (0.011) Loss 0.0232 (0.0223) Prec@1 96.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 15:56:08,563 Epoch: [282][40/500] Time 0.042 (0.030) Data 0.002 (0.008) Loss 0.0592 (0.0297) Prec@1 89.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 15:56:09,027 Epoch: [282][50/500] Time 0.041 (0.032) Data 0.003 (0.007) Loss 0.0173 (0.0276) Prec@1 98.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 15:56:09,481 Epoch: [282][60/500] Time 0.037 (0.034) Data 0.002 (0.006) Loss 0.0291 (0.0278) Prec@1 95.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 15:56:10,023 Epoch: [282][70/500] Time 0.053 (0.036) Data 0.002 (0.006) Loss 0.0389 (0.0292) Prec@1 93.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 15:56:10,452 Epoch: [282][80/500] Time 0.037 (0.036) Data 0.002 (0.005) Loss 0.0379 (0.0302) Prec@1 93.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 15:56:10,913 Epoch: [282][90/500] Time 0.048 (0.037) Data 0.003 (0.005) Loss 0.0473 (0.0319) Prec@1 89.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 15:56:11,396 Epoch: [282][100/500] Time 0.052 (0.037) Data 0.003 (0.005) Loss 0.0273 (0.0315) Prec@1 94.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 15:56:11,959 Epoch: [282][110/500] Time 0.059 (0.038) Data 0.002 (0.005) Loss 0.0293 (0.0313) Prec@1 95.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 15:56:12,452 Epoch: [282][120/500] Time 0.037 (0.039) Data 0.003 (0.004) Loss 0.0381 (0.0318) Prec@1 93.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 15:56:12,896 Epoch: [282][130/500] Time 0.041 (0.039) Data 0.003 (0.004) Loss 0.0249 (0.0313) Prec@1 95.000 (94.214) Prec@5 100.000 (99.857) +2022-11-14 15:56:13,346 Epoch: [282][140/500] Time 0.039 (0.039) Data 0.002 (0.004) Loss 0.0448 (0.0322) Prec@1 92.000 (94.067) Prec@5 100.000 (99.867) +2022-11-14 15:56:13,795 Epoch: [282][150/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0229 (0.0316) Prec@1 96.000 (94.188) Prec@5 99.000 (99.812) +2022-11-14 15:56:14,254 Epoch: [282][160/500] Time 0.037 (0.039) Data 0.002 (0.004) Loss 0.0347 (0.0318) Prec@1 94.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 15:56:14,716 Epoch: [282][170/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0425 (0.0324) Prec@1 91.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 15:56:15,213 Epoch: [282][180/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0532 (0.0335) Prec@1 90.000 (93.789) Prec@5 100.000 (99.842) +2022-11-14 15:56:15,660 Epoch: [282][190/500] Time 0.039 (0.040) Data 0.002 (0.004) Loss 0.0315 (0.0334) Prec@1 95.000 (93.850) Prec@5 100.000 (99.850) +2022-11-14 15:56:16,150 Epoch: [282][200/500] Time 0.043 (0.040) Data 0.002 (0.004) Loss 0.0227 (0.0329) Prec@1 97.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 15:56:16,603 Epoch: [282][210/500] Time 0.055 (0.040) Data 0.002 (0.004) Loss 0.0483 (0.0336) Prec@1 90.000 (93.818) Prec@5 100.000 (99.864) +2022-11-14 15:56:17,054 Epoch: [282][220/500] Time 0.030 (0.040) Data 0.002 (0.003) Loss 0.0335 (0.0336) Prec@1 94.000 (93.826) Prec@5 100.000 (99.870) +2022-11-14 15:56:17,507 Epoch: [282][230/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0295 (0.0334) Prec@1 97.000 (93.958) Prec@5 100.000 (99.875) +2022-11-14 15:56:17,972 Epoch: [282][240/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0354 (0.0335) Prec@1 95.000 (94.000) Prec@5 99.000 (99.840) +2022-11-14 15:56:18,417 Epoch: [282][250/500] Time 0.044 (0.040) Data 0.002 (0.003) Loss 0.0469 (0.0340) Prec@1 93.000 (93.962) Prec@5 100.000 (99.846) +2022-11-14 15:56:18,876 Epoch: [282][260/500] Time 0.035 (0.040) Data 0.002 (0.003) Loss 0.0210 (0.0335) Prec@1 97.000 (94.074) Prec@5 100.000 (99.852) +2022-11-14 15:56:19,338 Epoch: [282][270/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0443 (0.0339) Prec@1 91.000 (93.964) Prec@5 100.000 (99.857) +2022-11-14 15:56:19,790 Epoch: [282][280/500] Time 0.037 (0.040) Data 0.002 (0.003) Loss 0.0283 (0.0337) Prec@1 95.000 (94.000) Prec@5 100.000 (99.862) +2022-11-14 15:56:20,273 Epoch: [282][290/500] Time 0.054 (0.040) Data 0.002 (0.003) Loss 0.0300 (0.0336) Prec@1 94.000 (94.000) Prec@5 100.000 (99.867) +2022-11-14 15:56:20,750 Epoch: [282][300/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0469 (0.0340) Prec@1 93.000 (93.968) Prec@5 100.000 (99.871) +2022-11-14 15:56:21,261 Epoch: [282][310/500] Time 0.059 (0.040) Data 0.002 (0.003) Loss 0.0321 (0.0340) Prec@1 95.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 15:56:21,745 Epoch: [282][320/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0120 (0.0333) Prec@1 99.000 (94.152) Prec@5 100.000 (99.879) +2022-11-14 15:56:22,258 Epoch: [282][330/500] Time 0.035 (0.041) Data 0.002 (0.003) Loss 0.0334 (0.0333) Prec@1 94.000 (94.147) Prec@5 100.000 (99.882) +2022-11-14 15:56:22,724 Epoch: [282][340/500] Time 0.039 (0.041) Data 0.002 (0.003) Loss 0.0319 (0.0333) Prec@1 96.000 (94.200) Prec@5 99.000 (99.857) +2022-11-14 15:56:23,192 Epoch: [282][350/500] Time 0.051 (0.041) Data 0.003 (0.003) Loss 0.0173 (0.0328) Prec@1 97.000 (94.278) Prec@5 100.000 (99.861) +2022-11-14 15:56:23,652 Epoch: [282][360/500] Time 0.045 (0.041) Data 0.002 (0.003) Loss 0.0253 (0.0326) Prec@1 98.000 (94.378) Prec@5 100.000 (99.865) +2022-11-14 15:56:24,111 Epoch: [282][370/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0369 (0.0327) Prec@1 95.000 (94.395) Prec@5 100.000 (99.868) +2022-11-14 15:56:24,628 Epoch: [282][380/500] Time 0.055 (0.041) Data 0.002 (0.003) Loss 0.0644 (0.0335) Prec@1 89.000 (94.256) Prec@5 98.000 (99.821) +2022-11-14 15:56:25,116 Epoch: [282][390/500] Time 0.048 (0.041) Data 0.002 (0.003) Loss 0.0352 (0.0336) Prec@1 94.000 (94.250) Prec@5 100.000 (99.825) +2022-11-14 15:56:25,655 Epoch: [282][400/500] Time 0.038 (0.041) Data 0.002 (0.003) Loss 0.0239 (0.0334) Prec@1 97.000 (94.317) Prec@5 100.000 (99.829) +2022-11-14 15:56:26,143 Epoch: [282][410/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0470 (0.0337) Prec@1 93.000 (94.286) Prec@5 100.000 (99.833) +2022-11-14 15:56:26,667 Epoch: [282][420/500] Time 0.054 (0.041) Data 0.003 (0.003) Loss 0.0545 (0.0342) Prec@1 90.000 (94.186) Prec@5 100.000 (99.837) +2022-11-14 15:56:27,190 Epoch: [282][430/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0356 (0.0342) Prec@1 94.000 (94.182) Prec@5 100.000 (99.841) +2022-11-14 15:56:27,643 Epoch: [282][440/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0190 (0.0339) Prec@1 99.000 (94.289) Prec@5 100.000 (99.844) +2022-11-14 15:56:28,092 Epoch: [282][450/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0266 (0.0337) Prec@1 95.000 (94.304) Prec@5 100.000 (99.848) +2022-11-14 15:56:28,557 Epoch: [282][460/500] Time 0.036 (0.041) Data 0.002 (0.003) Loss 0.0474 (0.0340) Prec@1 91.000 (94.234) Prec@5 100.000 (99.851) +2022-11-14 15:56:29,032 Epoch: [282][470/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0551 (0.0344) Prec@1 91.000 (94.167) Prec@5 100.000 (99.854) +2022-11-14 15:56:29,486 Epoch: [282][480/500] Time 0.040 (0.041) Data 0.002 (0.003) Loss 0.0195 (0.0341) Prec@1 97.000 (94.224) Prec@5 100.000 (99.857) +2022-11-14 15:56:29,947 Epoch: [282][490/500] Time 0.043 (0.041) Data 0.002 (0.003) Loss 0.0216 (0.0339) Prec@1 97.000 (94.280) Prec@5 100.000 (99.860) +2022-11-14 15:56:30,376 Epoch: [282][499/500] Time 0.048 (0.041) Data 0.002 (0.003) Loss 0.0308 (0.0338) Prec@1 96.000 (94.314) Prec@5 100.000 (99.863) +2022-11-14 15:56:30,713 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0716 (0.0716) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:30,726 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0579 (0.0648) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:30,735 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0640 (0.0645) Prec@1 90.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 15:56:30,748 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0685) Prec@1 88.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 15:56:30,758 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0663) Prec@1 90.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 15:56:30,768 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0492 (0.0635) Prec@1 92.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 15:56:30,780 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0642) Prec@1 87.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 15:56:30,794 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.0677) Prec@1 82.000 (88.125) Prec@5 100.000 (99.875) +2022-11-14 15:56:30,806 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0692) Prec@1 86.000 (87.889) Prec@5 98.000 (99.667) +2022-11-14 15:56:30,819 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0685) Prec@1 91.000 (88.200) Prec@5 99.000 (99.600) +2022-11-14 15:56:30,834 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0671) Prec@1 91.000 (88.455) Prec@5 100.000 (99.636) +2022-11-14 15:56:30,850 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0678) Prec@1 90.000 (88.583) Prec@5 98.000 (99.500) +2022-11-14 15:56:30,864 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0673) Prec@1 88.000 (88.538) Prec@5 100.000 (99.538) +2022-11-14 15:56:30,881 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0681) Prec@1 86.000 (88.357) Prec@5 100.000 (99.571) +2022-11-14 15:56:30,897 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0697) Prec@1 85.000 (88.133) Prec@5 98.000 (99.467) +2022-11-14 15:56:30,913 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0698) Prec@1 87.000 (88.062) Prec@5 100.000 (99.500) +2022-11-14 15:56:30,926 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0685) Prec@1 92.000 (88.294) Prec@5 98.000 (99.412) +2022-11-14 15:56:30,942 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.0710) Prec@1 81.000 (87.889) Prec@5 100.000 (99.444) +2022-11-14 15:56:30,958 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0719) Prec@1 85.000 (87.737) Prec@5 100.000 (99.474) +2022-11-14 15:56:30,975 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0731) Prec@1 83.000 (87.500) Prec@5 97.000 (99.350) +2022-11-14 15:56:30,991 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0731) Prec@1 89.000 (87.571) Prec@5 100.000 (99.381) +2022-11-14 15:56:31,007 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0736) Prec@1 86.000 (87.500) Prec@5 99.000 (99.364) +2022-11-14 15:56:31,022 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0745) Prec@1 84.000 (87.348) Prec@5 99.000 (99.348) +2022-11-14 15:56:31,038 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0746) Prec@1 86.000 (87.292) Prec@5 100.000 (99.375) +2022-11-14 15:56:31,051 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0748) Prec@1 88.000 (87.320) Prec@5 100.000 (99.400) +2022-11-14 15:56:31,066 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0753) Prec@1 87.000 (87.308) Prec@5 99.000 (99.385) +2022-11-14 15:56:31,080 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0750) Prec@1 89.000 (87.370) Prec@5 100.000 (99.407) +2022-11-14 15:56:31,096 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0747) Prec@1 86.000 (87.321) Prec@5 100.000 (99.429) +2022-11-14 15:56:31,110 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0741) Prec@1 92.000 (87.483) Prec@5 97.000 (99.345) +2022-11-14 15:56:31,124 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0738) Prec@1 88.000 (87.500) Prec@5 100.000 (99.367) +2022-11-14 15:56:31,143 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0739) Prec@1 84.000 (87.387) Prec@5 99.000 (99.355) +2022-11-14 15:56:31,162 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0738) Prec@1 87.000 (87.375) Prec@5 99.000 (99.344) +2022-11-14 15:56:31,176 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0741) Prec@1 84.000 (87.273) Prec@5 99.000 (99.333) +2022-11-14 15:56:31,193 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0745) Prec@1 87.000 (87.265) Prec@5 100.000 (99.353) +2022-11-14 15:56:31,207 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0742) Prec@1 91.000 (87.371) Prec@5 97.000 (99.286) +2022-11-14 15:56:31,221 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0741) Prec@1 90.000 (87.444) Prec@5 100.000 (99.306) +2022-11-14 15:56:31,239 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0741) Prec@1 87.000 (87.432) Prec@5 98.000 (99.270) +2022-11-14 15:56:31,258 Test: [37/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0749) Prec@1 83.000 (87.316) Prec@5 100.000 (99.289) +2022-11-14 15:56:31,275 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0743) Prec@1 93.000 (87.462) Prec@5 99.000 (99.282) +2022-11-14 15:56:31,293 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0739) Prec@1 91.000 (87.550) Prec@5 100.000 (99.300) +2022-11-14 15:56:31,311 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0743) Prec@1 85.000 (87.488) Prec@5 97.000 (99.244) +2022-11-14 15:56:31,327 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0739) Prec@1 92.000 (87.595) Prec@5 99.000 (99.238) +2022-11-14 15:56:31,344 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0454 (0.0732) Prec@1 93.000 (87.721) Prec@5 99.000 (99.233) +2022-11-14 15:56:31,360 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0733) Prec@1 89.000 (87.750) Prec@5 98.000 (99.205) +2022-11-14 15:56:31,376 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0521 (0.0728) Prec@1 92.000 (87.844) Prec@5 98.000 (99.178) +2022-11-14 15:56:31,391 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0734) Prec@1 84.000 (87.761) Prec@5 100.000 (99.196) +2022-11-14 15:56:31,408 Test: [46/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0733) Prec@1 88.000 (87.766) Prec@5 100.000 (99.213) +2022-11-14 15:56:31,423 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0737) Prec@1 87.000 (87.750) Prec@5 97.000 (99.167) +2022-11-14 15:56:31,438 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0504 (0.0732) Prec@1 88.000 (87.755) Prec@5 100.000 (99.184) +2022-11-14 15:56:31,455 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1199 (0.0742) Prec@1 81.000 (87.620) Prec@5 100.000 (99.200) +2022-11-14 15:56:31,468 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0740) Prec@1 88.000 (87.627) Prec@5 100.000 (99.216) +2022-11-14 15:56:31,484 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0745) Prec@1 83.000 (87.538) Prec@5 98.000 (99.192) +2022-11-14 15:56:31,501 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0748) Prec@1 86.000 (87.509) Prec@5 100.000 (99.208) +2022-11-14 15:56:31,517 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0745) Prec@1 91.000 (87.574) Prec@5 100.000 (99.222) +2022-11-14 15:56:31,533 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0745) Prec@1 87.000 (87.564) Prec@5 100.000 (99.236) +2022-11-14 15:56:31,548 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0745) Prec@1 88.000 (87.571) Prec@5 99.000 (99.232) +2022-11-14 15:56:31,563 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0741) Prec@1 90.000 (87.614) Prec@5 100.000 (99.246) +2022-11-14 15:56:31,578 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0743) Prec@1 86.000 (87.586) Prec@5 99.000 (99.241) +2022-11-14 15:56:31,597 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1209 (0.0751) Prec@1 80.000 (87.458) Prec@5 97.000 (99.203) +2022-11-14 15:56:31,613 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0755) Prec@1 85.000 (87.417) Prec@5 98.000 (99.183) +2022-11-14 15:56:31,628 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0753) Prec@1 90.000 (87.459) Prec@5 97.000 (99.148) +2022-11-14 15:56:31,644 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0752) Prec@1 88.000 (87.468) Prec@5 99.000 (99.145) +2022-11-14 15:56:31,658 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0751) Prec@1 86.000 (87.444) Prec@5 100.000 (99.159) +2022-11-14 15:56:31,673 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0505 (0.0747) Prec@1 91.000 (87.500) Prec@5 99.000 (99.156) +2022-11-14 15:56:31,690 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0751) Prec@1 83.000 (87.431) Prec@5 99.000 (99.154) +2022-11-14 15:56:31,706 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0751) Prec@1 84.000 (87.379) Prec@5 99.000 (99.152) +2022-11-14 15:56:31,721 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0420 (0.0746) Prec@1 94.000 (87.478) Prec@5 100.000 (99.164) +2022-11-14 15:56:31,735 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0746) Prec@1 89.000 (87.500) Prec@5 98.000 (99.147) +2022-11-14 15:56:31,754 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0745) Prec@1 90.000 (87.536) Prec@5 98.000 (99.130) +2022-11-14 15:56:31,772 Test: [69/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0744) Prec@1 88.000 (87.543) Prec@5 100.000 (99.143) +2022-11-14 15:56:31,787 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0746) Prec@1 87.000 (87.535) Prec@5 97.000 (99.113) +2022-11-14 15:56:31,806 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0746) Prec@1 88.000 (87.542) Prec@5 100.000 (99.125) +2022-11-14 15:56:31,821 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0744) Prec@1 92.000 (87.603) Prec@5 100.000 (99.137) +2022-11-14 15:56:31,836 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0370 (0.0739) Prec@1 94.000 (87.689) Prec@5 99.000 (99.135) +2022-11-14 15:56:31,851 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0742) Prec@1 85.000 (87.653) Prec@5 99.000 (99.133) +2022-11-14 15:56:31,866 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0740) Prec@1 90.000 (87.684) Prec@5 100.000 (99.145) +2022-11-14 15:56:31,882 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0740) Prec@1 89.000 (87.701) Prec@5 97.000 (99.117) +2022-11-14 15:56:31,898 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0742) Prec@1 85.000 (87.667) Prec@5 98.000 (99.103) +2022-11-14 15:56:31,914 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0742) Prec@1 88.000 (87.671) Prec@5 100.000 (99.114) +2022-11-14 15:56:31,929 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0741) Prec@1 88.000 (87.675) Prec@5 100.000 (99.125) +2022-11-14 15:56:31,945 Test: [80/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0743) Prec@1 88.000 (87.679) Prec@5 98.000 (99.111) +2022-11-14 15:56:31,962 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0744) Prec@1 87.000 (87.671) Prec@5 99.000 (99.110) +2022-11-14 15:56:31,977 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0744) Prec@1 86.000 (87.651) Prec@5 100.000 (99.120) +2022-11-14 15:56:31,993 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0745) Prec@1 86.000 (87.631) Prec@5 98.000 (99.107) +2022-11-14 15:56:32,010 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0746) Prec@1 86.000 (87.612) Prec@5 99.000 (99.106) +2022-11-14 15:56:32,027 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0750) Prec@1 82.000 (87.547) Prec@5 100.000 (99.116) +2022-11-14 15:56:32,045 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0750) Prec@1 88.000 (87.552) Prec@5 100.000 (99.126) +2022-11-14 15:56:32,059 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0750) Prec@1 88.000 (87.557) Prec@5 98.000 (99.114) +2022-11-14 15:56:32,072 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0747) Prec@1 91.000 (87.596) Prec@5 100.000 (99.124) +2022-11-14 15:56:32,087 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0746) Prec@1 91.000 (87.633) Prec@5 100.000 (99.133) +2022-11-14 15:56:32,104 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0745) Prec@1 90.000 (87.659) Prec@5 99.000 (99.132) +2022-11-14 15:56:32,122 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0742) Prec@1 92.000 (87.707) Prec@5 100.000 (99.141) +2022-11-14 15:56:32,138 Test: [92/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0742) Prec@1 87.000 (87.699) Prec@5 100.000 (99.151) +2022-11-14 15:56:32,156 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0742) Prec@1 87.000 (87.691) Prec@5 100.000 (99.160) +2022-11-14 15:56:32,171 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0742) Prec@1 87.000 (87.684) Prec@5 99.000 (99.158) +2022-11-14 15:56:32,187 Test: [95/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0570 (0.0741) Prec@1 92.000 (87.729) Prec@5 98.000 (99.146) +2022-11-14 15:56:32,206 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0441 (0.0738) Prec@1 94.000 (87.794) Prec@5 99.000 (99.144) +2022-11-14 15:56:32,224 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0926 (0.0739) Prec@1 87.000 (87.786) Prec@5 98.000 (99.133) +2022-11-14 15:56:32,240 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0958 (0.0742) Prec@1 86.000 (87.768) Prec@5 99.000 (99.131) +2022-11-14 15:56:32,258 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0742) Prec@1 89.000 (87.780) Prec@5 98.000 (99.120) +2022-11-14 15:56:32,356 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:56:32,748 Epoch: [283][0/500] Time 0.034 (0.034) Data 0.285 (0.285) Loss 0.0233 (0.0233) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:33,214 Epoch: [283][10/500] Time 0.044 (0.040) Data 0.003 (0.028) Loss 0.0265 (0.0249) Prec@1 94.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:56:33,681 Epoch: [283][20/500] Time 0.039 (0.041) Data 0.003 (0.016) Loss 0.0253 (0.0250) Prec@1 97.000 (96.333) Prec@5 99.000 (99.667) +2022-11-14 15:56:34,194 Epoch: [283][30/500] Time 0.049 (0.043) Data 0.002 (0.012) Loss 0.0414 (0.0291) Prec@1 92.000 (95.250) Prec@5 99.000 (99.500) +2022-11-14 15:56:34,682 Epoch: [283][40/500] Time 0.041 (0.043) Data 0.002 (0.009) Loss 0.0176 (0.0268) Prec@1 99.000 (96.000) Prec@5 100.000 (99.600) +2022-11-14 15:56:35,187 Epoch: [283][50/500] Time 0.051 (0.043) Data 0.003 (0.008) Loss 0.0338 (0.0280) Prec@1 95.000 (95.833) Prec@5 100.000 (99.667) +2022-11-14 15:56:35,674 Epoch: [283][60/500] Time 0.052 (0.043) Data 0.002 (0.007) Loss 0.0286 (0.0281) Prec@1 95.000 (95.714) Prec@5 100.000 (99.714) +2022-11-14 15:56:36,172 Epoch: [283][70/500] Time 0.047 (0.044) Data 0.002 (0.006) Loss 0.0338 (0.0288) Prec@1 95.000 (95.625) Prec@5 100.000 (99.750) +2022-11-14 15:56:36,645 Epoch: [283][80/500] Time 0.054 (0.043) Data 0.002 (0.006) Loss 0.0296 (0.0289) Prec@1 95.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 15:56:37,151 Epoch: [283][90/500] Time 0.055 (0.044) Data 0.002 (0.005) Loss 0.0381 (0.0298) Prec@1 95.000 (95.500) Prec@5 100.000 (99.800) +2022-11-14 15:56:37,652 Epoch: [283][100/500] Time 0.053 (0.044) Data 0.002 (0.005) Loss 0.0394 (0.0307) Prec@1 93.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 15:56:38,157 Epoch: [283][110/500] Time 0.049 (0.044) Data 0.002 (0.005) Loss 0.0373 (0.0312) Prec@1 93.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 15:56:38,609 Epoch: [283][120/500] Time 0.037 (0.044) Data 0.002 (0.005) Loss 0.0264 (0.0309) Prec@1 95.000 (95.077) Prec@5 100.000 (99.846) +2022-11-14 15:56:39,099 Epoch: [283][130/500] Time 0.044 (0.044) Data 0.002 (0.004) Loss 0.0209 (0.0301) Prec@1 98.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 15:56:39,615 Epoch: [283][140/500] Time 0.051 (0.044) Data 0.002 (0.004) Loss 0.0246 (0.0298) Prec@1 96.000 (95.333) Prec@5 99.000 (99.800) +2022-11-14 15:56:40,150 Epoch: [283][150/500] Time 0.052 (0.044) Data 0.002 (0.004) Loss 0.0441 (0.0307) Prec@1 90.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 15:56:40,656 Epoch: [283][160/500] Time 0.047 (0.044) Data 0.002 (0.004) Loss 0.0375 (0.0311) Prec@1 94.000 (94.941) Prec@5 100.000 (99.765) +2022-11-14 15:56:41,142 Epoch: [283][170/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0249 (0.0307) Prec@1 96.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 15:56:41,668 Epoch: [283][180/500] Time 0.053 (0.044) Data 0.002 (0.004) Loss 0.0389 (0.0312) Prec@1 93.000 (94.895) Prec@5 98.000 (99.684) +2022-11-14 15:56:42,178 Epoch: [283][190/500] Time 0.045 (0.044) Data 0.002 (0.004) Loss 0.0384 (0.0315) Prec@1 93.000 (94.800) Prec@5 100.000 (99.700) +2022-11-14 15:56:42,698 Epoch: [283][200/500] Time 0.050 (0.044) Data 0.002 (0.004) Loss 0.0287 (0.0314) Prec@1 95.000 (94.810) Prec@5 100.000 (99.714) +2022-11-14 15:56:43,207 Epoch: [283][210/500] Time 0.049 (0.044) Data 0.002 (0.004) Loss 0.0343 (0.0315) Prec@1 94.000 (94.773) Prec@5 100.000 (99.727) +2022-11-14 15:56:43,715 Epoch: [283][220/500] Time 0.043 (0.045) Data 0.002 (0.004) Loss 0.0463 (0.0322) Prec@1 94.000 (94.739) Prec@5 99.000 (99.696) +2022-11-14 15:56:44,232 Epoch: [283][230/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0435 (0.0326) Prec@1 93.000 (94.667) Prec@5 100.000 (99.708) +2022-11-14 15:56:44,675 Epoch: [283][240/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0197 (0.0321) Prec@1 95.000 (94.680) Prec@5 100.000 (99.720) +2022-11-14 15:56:45,125 Epoch: [283][250/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0592 (0.0332) Prec@1 89.000 (94.462) Prec@5 100.000 (99.731) +2022-11-14 15:56:45,656 Epoch: [283][260/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0377 (0.0333) Prec@1 93.000 (94.407) Prec@5 100.000 (99.741) +2022-11-14 15:56:46,209 Epoch: [283][270/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0205 (0.0329) Prec@1 98.000 (94.536) Prec@5 100.000 (99.750) +2022-11-14 15:56:46,765 Epoch: [283][280/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0442 (0.0333) Prec@1 92.000 (94.448) Prec@5 100.000 (99.759) +2022-11-14 15:56:47,308 Epoch: [283][290/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0406 (0.0335) Prec@1 91.000 (94.333) Prec@5 100.000 (99.767) +2022-11-14 15:56:47,913 Epoch: [283][300/500] Time 0.088 (0.045) Data 0.003 (0.003) Loss 0.0381 (0.0336) Prec@1 92.000 (94.258) Prec@5 100.000 (99.774) +2022-11-14 15:56:48,824 Epoch: [283][310/500] Time 0.076 (0.046) Data 0.002 (0.003) Loss 0.0281 (0.0335) Prec@1 95.000 (94.281) Prec@5 100.000 (99.781) +2022-11-14 15:56:49,679 Epoch: [283][320/500] Time 0.103 (0.047) Data 0.002 (0.003) Loss 0.0329 (0.0335) Prec@1 95.000 (94.303) Prec@5 100.000 (99.788) +2022-11-14 15:56:50,581 Epoch: [283][330/500] Time 0.089 (0.048) Data 0.002 (0.003) Loss 0.0303 (0.0334) Prec@1 95.000 (94.324) Prec@5 100.000 (99.794) +2022-11-14 15:56:51,470 Epoch: [283][340/500] Time 0.098 (0.049) Data 0.002 (0.003) Loss 0.0204 (0.0330) Prec@1 97.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:56:52,262 Epoch: [283][350/500] Time 0.075 (0.050) Data 0.002 (0.003) Loss 0.0363 (0.0331) Prec@1 93.000 (94.361) Prec@5 100.000 (99.806) +2022-11-14 15:56:53,136 Epoch: [283][360/500] Time 0.097 (0.050) Data 0.002 (0.003) Loss 0.0318 (0.0331) Prec@1 94.000 (94.351) Prec@5 100.000 (99.811) +2022-11-14 15:56:53,944 Epoch: [283][370/500] Time 0.076 (0.051) Data 0.003 (0.003) Loss 0.0441 (0.0333) Prec@1 93.000 (94.316) Prec@5 100.000 (99.816) +2022-11-14 15:56:54,728 Epoch: [283][380/500] Time 0.079 (0.052) Data 0.003 (0.003) Loss 0.0292 (0.0332) Prec@1 96.000 (94.359) Prec@5 99.000 (99.795) +2022-11-14 15:56:55,450 Epoch: [283][390/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0199 (0.0329) Prec@1 98.000 (94.450) Prec@5 100.000 (99.800) +2022-11-14 15:56:56,247 Epoch: [283][400/500] Time 0.074 (0.052) Data 0.002 (0.003) Loss 0.0292 (0.0328) Prec@1 95.000 (94.463) Prec@5 100.000 (99.805) +2022-11-14 15:56:57,022 Epoch: [283][410/500] Time 0.076 (0.053) Data 0.002 (0.003) Loss 0.0314 (0.0328) Prec@1 94.000 (94.452) Prec@5 100.000 (99.810) +2022-11-14 15:56:57,772 Epoch: [283][420/500] Time 0.067 (0.053) Data 0.002 (0.003) Loss 0.0325 (0.0328) Prec@1 95.000 (94.465) Prec@5 100.000 (99.814) +2022-11-14 15:56:58,548 Epoch: [283][430/500] Time 0.075 (0.054) Data 0.002 (0.003) Loss 0.0210 (0.0325) Prec@1 97.000 (94.523) Prec@5 100.000 (99.818) +2022-11-14 15:56:59,341 Epoch: [283][440/500] Time 0.083 (0.054) Data 0.002 (0.003) Loss 0.0294 (0.0324) Prec@1 92.000 (94.467) Prec@5 100.000 (99.822) +2022-11-14 15:57:00,129 Epoch: [283][450/500] Time 0.072 (0.054) Data 0.002 (0.003) Loss 0.0328 (0.0324) Prec@1 92.000 (94.413) Prec@5 100.000 (99.826) +2022-11-14 15:57:00,654 Epoch: [283][460/500] Time 0.040 (0.054) Data 0.002 (0.003) Loss 0.0387 (0.0326) Prec@1 94.000 (94.404) Prec@5 100.000 (99.830) +2022-11-14 15:57:01,027 Epoch: [283][470/500] Time 0.040 (0.054) Data 0.002 (0.003) Loss 0.0290 (0.0325) Prec@1 96.000 (94.438) Prec@5 100.000 (99.833) +2022-11-14 15:57:01,413 Epoch: [283][480/500] Time 0.033 (0.053) Data 0.002 (0.003) Loss 0.0248 (0.0323) Prec@1 95.000 (94.449) Prec@5 100.000 (99.837) +2022-11-14 15:57:01,788 Epoch: [283][490/500] Time 0.032 (0.053) Data 0.002 (0.003) Loss 0.0349 (0.0324) Prec@1 93.000 (94.420) Prec@5 100.000 (99.840) +2022-11-14 15:57:02,142 Epoch: [283][499/500] Time 0.037 (0.053) Data 0.002 (0.003) Loss 0.0470 (0.0327) Prec@1 91.000 (94.353) Prec@5 99.000 (99.824) +2022-11-14 15:57:02,499 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0466 (0.0466) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:02,509 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0659 (0.0562) Prec@1 90.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 15:57:02,519 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0658 (0.0594) Prec@1 87.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:02,530 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0599) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:02,539 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0648) Prec@1 87.000 (89.400) Prec@5 100.000 (100.000) +2022-11-14 15:57:02,548 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0621) Prec@1 93.000 (90.000) Prec@5 99.000 (99.833) +2022-11-14 15:57:02,557 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0632) Prec@1 89.000 (89.857) Prec@5 99.000 (99.714) +2022-11-14 15:57:02,568 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.0688) Prec@1 81.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 15:57:02,577 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0696) Prec@1 89.000 (88.778) Prec@5 97.000 (99.444) +2022-11-14 15:57:02,587 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0695) Prec@1 91.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 15:57:02,598 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0678) Prec@1 91.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 15:57:02,608 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0677) Prec@1 91.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 15:57:02,617 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0664) Prec@1 91.000 (89.462) Prec@5 99.000 (99.462) +2022-11-14 15:57:02,627 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0679) Prec@1 86.000 (89.214) Prec@5 100.000 (99.500) +2022-11-14 15:57:02,637 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0683) Prec@1 89.000 (89.200) Prec@5 100.000 (99.533) +2022-11-14 15:57:02,648 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0686) Prec@1 86.000 (89.000) Prec@5 100.000 (99.562) +2022-11-14 15:57:02,658 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0362 (0.0667) Prec@1 95.000 (89.353) Prec@5 99.000 (99.529) +2022-11-14 15:57:02,667 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0687) Prec@1 84.000 (89.056) Prec@5 99.000 (99.500) +2022-11-14 15:57:02,676 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0704) Prec@1 82.000 (88.684) Prec@5 98.000 (99.421) +2022-11-14 15:57:02,686 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0716) Prec@1 83.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 15:57:02,697 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0727) Prec@1 84.000 (88.190) Prec@5 100.000 (99.429) +2022-11-14 15:57:02,708 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0729) Prec@1 88.000 (88.182) Prec@5 99.000 (99.409) +2022-11-14 15:57:02,718 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0738) Prec@1 87.000 (88.130) Prec@5 98.000 (99.348) +2022-11-14 15:57:02,729 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0738) Prec@1 88.000 (88.125) Prec@5 100.000 (99.375) +2022-11-14 15:57:02,738 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1024 (0.0749) Prec@1 83.000 (87.920) Prec@5 100.000 (99.400) +2022-11-14 15:57:02,748 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0752) Prec@1 85.000 (87.808) Prec@5 98.000 (99.346) +2022-11-14 15:57:02,758 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0745) Prec@1 92.000 (87.963) Prec@5 100.000 (99.370) +2022-11-14 15:57:02,768 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0743) Prec@1 88.000 (87.964) Prec@5 100.000 (99.393) +2022-11-14 15:57:02,777 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0740) Prec@1 89.000 (88.000) Prec@5 99.000 (99.379) +2022-11-14 15:57:02,788 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0740) Prec@1 87.000 (87.967) Prec@5 100.000 (99.400) +2022-11-14 15:57:02,801 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0739) Prec@1 87.000 (87.935) Prec@5 99.000 (99.387) +2022-11-14 15:57:02,812 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0736) Prec@1 89.000 (87.969) Prec@5 99.000 (99.375) +2022-11-14 15:57:02,822 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0737) Prec@1 86.000 (87.909) Prec@5 100.000 (99.394) +2022-11-14 15:57:02,834 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0743) Prec@1 82.000 (87.735) Prec@5 99.000 (99.382) +2022-11-14 15:57:02,844 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0749) Prec@1 83.000 (87.600) Prec@5 98.000 (99.343) +2022-11-14 15:57:02,855 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0747) Prec@1 90.000 (87.667) Prec@5 100.000 (99.361) +2022-11-14 15:57:02,865 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0748) Prec@1 86.000 (87.622) Prec@5 98.000 (99.324) +2022-11-14 15:57:02,875 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0752) Prec@1 85.000 (87.553) Prec@5 100.000 (99.342) +2022-11-14 15:57:02,884 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0745) Prec@1 93.000 (87.692) Prec@5 98.000 (99.308) +2022-11-14 15:57:02,894 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0741) Prec@1 90.000 (87.750) Prec@5 99.000 (99.300) +2022-11-14 15:57:02,904 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0743) Prec@1 87.000 (87.732) Prec@5 100.000 (99.317) +2022-11-14 15:57:02,914 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0742) Prec@1 87.000 (87.714) Prec@5 100.000 (99.333) +2022-11-14 15:57:02,924 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0736) Prec@1 90.000 (87.767) Prec@5 99.000 (99.326) +2022-11-14 15:57:02,935 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0731) Prec@1 92.000 (87.864) Prec@5 99.000 (99.318) +2022-11-14 15:57:02,945 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0727) Prec@1 91.000 (87.933) Prec@5 99.000 (99.311) +2022-11-14 15:57:02,956 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0733) Prec@1 82.000 (87.804) Prec@5 100.000 (99.326) +2022-11-14 15:57:02,966 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0731) Prec@1 88.000 (87.809) Prec@5 100.000 (99.340) +2022-11-14 15:57:02,976 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0735) Prec@1 87.000 (87.792) Prec@5 98.000 (99.312) +2022-11-14 15:57:02,989 Test: [48/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0731) Prec@1 92.000 (87.878) Prec@5 97.000 (99.265) +2022-11-14 15:57:03,000 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1177 (0.0739) Prec@1 80.000 (87.720) Prec@5 99.000 (99.260) +2022-11-14 15:57:03,010 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0737) Prec@1 89.000 (87.745) Prec@5 100.000 (99.275) +2022-11-14 15:57:03,022 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0739) Prec@1 87.000 (87.731) Prec@5 99.000 (99.269) +2022-11-14 15:57:03,035 Test: [52/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0740) Prec@1 87.000 (87.717) Prec@5 100.000 (99.283) +2022-11-14 15:57:03,047 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0741) Prec@1 86.000 (87.685) Prec@5 99.000 (99.278) +2022-11-14 15:57:03,057 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0743) Prec@1 87.000 (87.673) Prec@5 100.000 (99.291) +2022-11-14 15:57:03,068 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0742) Prec@1 89.000 (87.696) Prec@5 97.000 (99.250) +2022-11-14 15:57:03,080 Test: [56/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0742) Prec@1 88.000 (87.702) Prec@5 100.000 (99.263) +2022-11-14 15:57:03,092 Test: [57/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 89.000 (87.724) Prec@5 100.000 (99.276) +2022-11-14 15:57:03,102 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0747) Prec@1 83.000 (87.644) Prec@5 99.000 (99.271) +2022-11-14 15:57:03,114 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0749) Prec@1 88.000 (87.650) Prec@5 100.000 (99.283) +2022-11-14 15:57:03,124 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0749) Prec@1 90.000 (87.689) Prec@5 100.000 (99.295) +2022-11-14 15:57:03,134 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0748) Prec@1 89.000 (87.710) Prec@5 100.000 (99.306) +2022-11-14 15:57:03,144 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0746) Prec@1 90.000 (87.746) Prec@5 100.000 (99.317) +2022-11-14 15:57:03,154 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0743) Prec@1 91.000 (87.797) Prec@5 99.000 (99.312) +2022-11-14 15:57:03,165 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1126 (0.0749) Prec@1 84.000 (87.738) Prec@5 98.000 (99.292) +2022-11-14 15:57:03,175 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0747) Prec@1 88.000 (87.742) Prec@5 99.000 (99.288) +2022-11-14 15:57:03,185 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0744) Prec@1 90.000 (87.776) Prec@5 100.000 (99.299) +2022-11-14 15:57:03,196 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0746) Prec@1 87.000 (87.765) Prec@5 98.000 (99.279) +2022-11-14 15:57:03,208 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0745) Prec@1 89.000 (87.783) Prec@5 99.000 (99.275) +2022-11-14 15:57:03,219 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0747) Prec@1 85.000 (87.743) Prec@5 98.000 (99.257) +2022-11-14 15:57:03,230 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0748) Prec@1 87.000 (87.732) Prec@5 99.000 (99.254) +2022-11-14 15:57:03,241 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0744) Prec@1 92.000 (87.792) Prec@5 100.000 (99.264) +2022-11-14 15:57:03,251 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0741) Prec@1 94.000 (87.877) Prec@5 99.000 (99.260) +2022-11-14 15:57:03,264 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0737) Prec@1 92.000 (87.932) Prec@5 100.000 (99.270) +2022-11-14 15:57:03,275 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0740) Prec@1 83.000 (87.867) Prec@5 100.000 (99.280) +2022-11-14 15:57:03,285 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0737) Prec@1 92.000 (87.921) Prec@5 100.000 (99.289) +2022-11-14 15:57:03,294 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0738) Prec@1 88.000 (87.922) Prec@5 99.000 (99.286) +2022-11-14 15:57:03,304 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0742) Prec@1 84.000 (87.872) Prec@5 99.000 (99.282) +2022-11-14 15:57:03,315 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0742) Prec@1 87.000 (87.861) Prec@5 100.000 (99.291) +2022-11-14 15:57:03,326 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0742) Prec@1 86.000 (87.838) Prec@5 100.000 (99.300) +2022-11-14 15:57:03,337 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0741) Prec@1 89.000 (87.852) Prec@5 99.000 (99.296) +2022-11-14 15:57:03,349 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0743) Prec@1 85.000 (87.817) Prec@5 100.000 (99.305) +2022-11-14 15:57:03,361 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0742) Prec@1 88.000 (87.819) Prec@5 99.000 (99.301) +2022-11-14 15:57:03,372 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0742) Prec@1 86.000 (87.798) Prec@5 100.000 (99.310) +2022-11-14 15:57:03,383 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0746) Prec@1 81.000 (87.718) Prec@5 100.000 (99.318) +2022-11-14 15:57:03,393 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0750) Prec@1 84.000 (87.674) Prec@5 98.000 (99.302) +2022-11-14 15:57:03,404 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0749) Prec@1 88.000 (87.678) Prec@5 100.000 (99.310) +2022-11-14 15:57:03,414 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0748) Prec@1 89.000 (87.693) Prec@5 99.000 (99.307) +2022-11-14 15:57:03,425 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0749) Prec@1 87.000 (87.685) Prec@5 100.000 (99.315) +2022-11-14 15:57:03,436 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0748) Prec@1 90.000 (87.711) Prec@5 99.000 (99.311) +2022-11-14 15:57:03,446 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0746) Prec@1 90.000 (87.736) Prec@5 100.000 (99.319) +2022-11-14 15:57:03,456 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0744) Prec@1 89.000 (87.750) Prec@5 99.000 (99.315) +2022-11-14 15:57:03,468 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1152 (0.0749) Prec@1 84.000 (87.710) Prec@5 97.000 (99.290) +2022-11-14 15:57:03,478 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0751) Prec@1 86.000 (87.691) Prec@5 99.000 (99.287) +2022-11-14 15:57:03,488 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0752) Prec@1 86.000 (87.674) Prec@5 99.000 (99.284) +2022-11-14 15:57:03,499 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0750) Prec@1 91.000 (87.708) Prec@5 100.000 (99.292) +2022-11-14 15:57:03,509 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0407 (0.0747) Prec@1 93.000 (87.763) Prec@5 99.000 (99.289) +2022-11-14 15:57:03,520 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0748) Prec@1 88.000 (87.765) Prec@5 100.000 (99.296) +2022-11-14 15:57:03,529 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0750) Prec@1 84.000 (87.727) Prec@5 99.000 (99.293) +2022-11-14 15:57:03,540 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0750) Prec@1 86.000 (87.710) Prec@5 100.000 (99.300) +2022-11-14 15:57:03,601 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:57:03,919 Epoch: [284][0/500] Time 0.022 (0.022) Data 0.231 (0.231) Loss 0.0107 (0.0107) Prec@1 99.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:04,170 Epoch: [284][10/500] Time 0.024 (0.022) Data 0.002 (0.023) Loss 0.0284 (0.0196) Prec@1 96.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 15:57:04,528 Epoch: [284][20/500] Time 0.047 (0.026) Data 0.002 (0.013) Loss 0.0259 (0.0217) Prec@1 95.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 15:57:04,935 Epoch: [284][30/500] Time 0.033 (0.029) Data 0.002 (0.009) Loss 0.0450 (0.0275) Prec@1 91.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 15:57:05,386 Epoch: [284][40/500] Time 0.044 (0.032) Data 0.002 (0.008) Loss 0.0387 (0.0297) Prec@1 93.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 15:57:05,813 Epoch: [284][50/500] Time 0.044 (0.033) Data 0.002 (0.006) Loss 0.0210 (0.0283) Prec@1 97.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 15:57:06,245 Epoch: [284][60/500] Time 0.035 (0.034) Data 0.002 (0.006) Loss 0.0498 (0.0314) Prec@1 92.000 (94.714) Prec@5 99.000 (99.857) +2022-11-14 15:57:06,698 Epoch: [284][70/500] Time 0.033 (0.035) Data 0.002 (0.005) Loss 0.0443 (0.0330) Prec@1 95.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 15:57:07,143 Epoch: [284][80/500] Time 0.032 (0.036) Data 0.002 (0.005) Loss 0.0264 (0.0322) Prec@1 95.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 15:57:07,602 Epoch: [284][90/500] Time 0.043 (0.036) Data 0.002 (0.005) Loss 0.0337 (0.0324) Prec@1 95.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 15:57:08,054 Epoch: [284][100/500] Time 0.046 (0.037) Data 0.002 (0.004) Loss 0.0298 (0.0322) Prec@1 96.000 (94.909) Prec@5 100.000 (99.818) +2022-11-14 15:57:08,497 Epoch: [284][110/500] Time 0.032 (0.037) Data 0.002 (0.004) Loss 0.0156 (0.0308) Prec@1 98.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 15:57:08,945 Epoch: [284][120/500] Time 0.038 (0.037) Data 0.002 (0.004) Loss 0.0431 (0.0317) Prec@1 92.000 (94.923) Prec@5 99.000 (99.769) +2022-11-14 15:57:09,417 Epoch: [284][130/500] Time 0.046 (0.038) Data 0.002 (0.004) Loss 0.0416 (0.0324) Prec@1 92.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 15:57:09,862 Epoch: [284][140/500] Time 0.028 (0.038) Data 0.002 (0.004) Loss 0.0339 (0.0325) Prec@1 95.000 (94.733) Prec@5 100.000 (99.800) +2022-11-14 15:57:10,350 Epoch: [284][150/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0385 (0.0329) Prec@1 93.000 (94.625) Prec@5 100.000 (99.812) +2022-11-14 15:57:10,857 Epoch: [284][160/500] Time 0.048 (0.039) Data 0.002 (0.004) Loss 0.0433 (0.0335) Prec@1 92.000 (94.471) Prec@5 100.000 (99.824) +2022-11-14 15:57:11,693 Epoch: [284][170/500] Time 0.077 (0.041) Data 0.002 (0.003) Loss 0.0409 (0.0339) Prec@1 91.000 (94.278) Prec@5 100.000 (99.833) +2022-11-14 15:57:12,655 Epoch: [284][180/500] Time 0.082 (0.043) Data 0.002 (0.003) Loss 0.0589 (0.0352) Prec@1 92.000 (94.158) Prec@5 98.000 (99.737) +2022-11-14 15:57:13,433 Epoch: [284][190/500] Time 0.074 (0.045) Data 0.002 (0.003) Loss 0.0381 (0.0354) Prec@1 94.000 (94.150) Prec@5 100.000 (99.750) +2022-11-14 15:57:14,201 Epoch: [284][200/500] Time 0.078 (0.046) Data 0.002 (0.003) Loss 0.0212 (0.0347) Prec@1 95.000 (94.190) Prec@5 100.000 (99.762) +2022-11-14 15:57:14,916 Epoch: [284][210/500] Time 0.066 (0.047) Data 0.003 (0.003) Loss 0.0329 (0.0346) Prec@1 93.000 (94.136) Prec@5 100.000 (99.773) +2022-11-14 15:57:15,742 Epoch: [284][220/500] Time 0.090 (0.048) Data 0.002 (0.003) Loss 0.0380 (0.0348) Prec@1 93.000 (94.087) Prec@5 100.000 (99.783) +2022-11-14 15:57:16,478 Epoch: [284][230/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0235 (0.0343) Prec@1 96.000 (94.167) Prec@5 100.000 (99.792) +2022-11-14 15:57:17,221 Epoch: [284][240/500] Time 0.067 (0.050) Data 0.002 (0.003) Loss 0.0642 (0.0355) Prec@1 89.000 (93.960) Prec@5 100.000 (99.800) +2022-11-14 15:57:18,025 Epoch: [284][250/500] Time 0.077 (0.051) Data 0.002 (0.003) Loss 0.0378 (0.0356) Prec@1 94.000 (93.962) Prec@5 100.000 (99.808) +2022-11-14 15:57:18,785 Epoch: [284][260/500] Time 0.081 (0.051) Data 0.002 (0.003) Loss 0.0372 (0.0356) Prec@1 93.000 (93.926) Prec@5 100.000 (99.815) +2022-11-14 15:57:19,567 Epoch: [284][270/500] Time 0.067 (0.052) Data 0.002 (0.003) Loss 0.0496 (0.0361) Prec@1 92.000 (93.857) Prec@5 98.000 (99.750) +2022-11-14 15:57:20,302 Epoch: [284][280/500] Time 0.074 (0.053) Data 0.002 (0.003) Loss 0.0386 (0.0362) Prec@1 93.000 (93.828) Prec@5 100.000 (99.759) +2022-11-14 15:57:21,154 Epoch: [284][290/500] Time 0.098 (0.053) Data 0.002 (0.003) Loss 0.0429 (0.0364) Prec@1 92.000 (93.767) Prec@5 100.000 (99.767) +2022-11-14 15:57:22,046 Epoch: [284][300/500] Time 0.096 (0.054) Data 0.002 (0.003) Loss 0.0274 (0.0362) Prec@1 95.000 (93.806) Prec@5 100.000 (99.774) +2022-11-14 15:57:23,113 Epoch: [284][310/500] Time 0.050 (0.056) Data 0.002 (0.003) Loss 0.0324 (0.0360) Prec@1 95.000 (93.844) Prec@5 99.000 (99.750) +2022-11-14 15:57:23,676 Epoch: [284][320/500] Time 0.062 (0.055) Data 0.002 (0.003) Loss 0.0314 (0.0359) Prec@1 95.000 (93.879) Prec@5 100.000 (99.758) +2022-11-14 15:57:24,270 Epoch: [284][330/500] Time 0.069 (0.055) Data 0.002 (0.003) Loss 0.0458 (0.0362) Prec@1 91.000 (93.794) Prec@5 100.000 (99.765) +2022-11-14 15:57:24,864 Epoch: [284][340/500] Time 0.062 (0.055) Data 0.002 (0.003) Loss 0.0612 (0.0369) Prec@1 91.000 (93.714) Prec@5 100.000 (99.771) +2022-11-14 15:57:25,459 Epoch: [284][350/500] Time 0.045 (0.055) Data 0.002 (0.003) Loss 0.0357 (0.0369) Prec@1 95.000 (93.750) Prec@5 100.000 (99.778) +2022-11-14 15:57:26,056 Epoch: [284][360/500] Time 0.052 (0.055) Data 0.002 (0.003) Loss 0.0238 (0.0365) Prec@1 96.000 (93.811) Prec@5 100.000 (99.784) +2022-11-14 15:57:26,600 Epoch: [284][370/500] Time 0.050 (0.055) Data 0.002 (0.003) Loss 0.0185 (0.0360) Prec@1 98.000 (93.921) Prec@5 100.000 (99.789) +2022-11-14 15:57:27,167 Epoch: [284][380/500] Time 0.058 (0.055) Data 0.002 (0.003) Loss 0.0238 (0.0357) Prec@1 97.000 (94.000) Prec@5 100.000 (99.795) +2022-11-14 15:57:27,689 Epoch: [284][390/500] Time 0.048 (0.055) Data 0.002 (0.003) Loss 0.0246 (0.0355) Prec@1 95.000 (94.025) Prec@5 100.000 (99.800) +2022-11-14 15:57:28,249 Epoch: [284][400/500] Time 0.052 (0.055) Data 0.002 (0.003) Loss 0.0518 (0.0359) Prec@1 91.000 (93.951) Prec@5 100.000 (99.805) +2022-11-14 15:57:28,816 Epoch: [284][410/500] Time 0.051 (0.054) Data 0.002 (0.003) Loss 0.0345 (0.0358) Prec@1 94.000 (93.952) Prec@5 100.000 (99.810) +2022-11-14 15:57:29,363 Epoch: [284][420/500] Time 0.059 (0.054) Data 0.002 (0.003) Loss 0.0205 (0.0355) Prec@1 98.000 (94.047) Prec@5 100.000 (99.814) +2022-11-14 15:57:29,914 Epoch: [284][430/500] Time 0.045 (0.054) Data 0.002 (0.003) Loss 0.0411 (0.0356) Prec@1 94.000 (94.045) Prec@5 100.000 (99.818) +2022-11-14 15:57:30,549 Epoch: [284][440/500] Time 0.057 (0.054) Data 0.002 (0.003) Loss 0.0219 (0.0353) Prec@1 97.000 (94.111) Prec@5 100.000 (99.822) +2022-11-14 15:57:31,163 Epoch: [284][450/500] Time 0.057 (0.054) Data 0.003 (0.003) Loss 0.0266 (0.0351) Prec@1 95.000 (94.130) Prec@5 100.000 (99.826) +2022-11-14 15:57:31,802 Epoch: [284][460/500] Time 0.045 (0.054) Data 0.003 (0.003) Loss 0.0446 (0.0353) Prec@1 92.000 (94.085) Prec@5 100.000 (99.830) +2022-11-14 15:57:32,460 Epoch: [284][470/500] Time 0.047 (0.054) Data 0.002 (0.003) Loss 0.0288 (0.0352) Prec@1 96.000 (94.125) Prec@5 100.000 (99.833) +2022-11-14 15:57:33,024 Epoch: [284][480/500] Time 0.042 (0.054) Data 0.002 (0.003) Loss 0.0427 (0.0353) Prec@1 93.000 (94.102) Prec@5 99.000 (99.816) +2022-11-14 15:57:33,587 Epoch: [284][490/500] Time 0.071 (0.054) Data 0.002 (0.003) Loss 0.0522 (0.0357) Prec@1 92.000 (94.060) Prec@5 99.000 (99.800) +2022-11-14 15:57:34,030 Epoch: [284][499/500] Time 0.045 (0.054) Data 0.003 (0.003) Loss 0.0104 (0.0352) Prec@1 98.000 (94.137) Prec@5 100.000 (99.804) +2022-11-14 15:57:34,343 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0553 (0.0553) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 15:57:34,354 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0710 (0.0631) Prec@1 87.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 15:57:34,363 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0641) Prec@1 87.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 15:57:34,383 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0678) Prec@1 87.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 15:57:34,393 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0714) Prec@1 85.000 (87.400) Prec@5 99.000 (99.400) +2022-11-14 15:57:34,402 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0397 (0.0661) Prec@1 93.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 15:57:34,411 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0670) Prec@1 87.000 (88.143) Prec@5 100.000 (99.571) +2022-11-14 15:57:34,423 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0877 (0.0696) Prec@1 86.000 (87.875) Prec@5 98.000 (99.375) +2022-11-14 15:57:34,433 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0712) Prec@1 88.000 (87.889) Prec@5 99.000 (99.333) +2022-11-14 15:57:34,444 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0714) Prec@1 87.000 (87.800) Prec@5 99.000 (99.300) +2022-11-14 15:57:34,453 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0699) Prec@1 92.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 15:57:34,463 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0687) Prec@1 93.000 (88.583) Prec@5 99.000 (99.333) +2022-11-14 15:57:34,474 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0677) Prec@1 90.000 (88.692) Prec@5 100.000 (99.385) +2022-11-14 15:57:34,485 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0688) Prec@1 88.000 (88.643) Prec@5 100.000 (99.429) +2022-11-14 15:57:34,495 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0697) Prec@1 83.000 (88.267) Prec@5 99.000 (99.400) +2022-11-14 15:57:34,506 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0706) Prec@1 87.000 (88.188) Prec@5 99.000 (99.375) +2022-11-14 15:57:34,517 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0694) Prec@1 92.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 15:57:34,529 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0714) Prec@1 83.000 (88.111) Prec@5 100.000 (99.389) +2022-11-14 15:57:34,540 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0726) Prec@1 81.000 (87.737) Prec@5 100.000 (99.421) +2022-11-14 15:57:34,550 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0738) Prec@1 85.000 (87.600) Prec@5 97.000 (99.300) +2022-11-14 15:57:34,561 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0744) Prec@1 87.000 (87.571) Prec@5 100.000 (99.333) +2022-11-14 15:57:34,571 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0749) Prec@1 87.000 (87.545) Prec@5 99.000 (99.318) +2022-11-14 15:57:34,583 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0751) Prec@1 87.000 (87.522) Prec@5 99.000 (99.304) +2022-11-14 15:57:34,595 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0748) Prec@1 88.000 (87.542) Prec@5 100.000 (99.333) +2022-11-14 15:57:34,606 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0759) Prec@1 85.000 (87.440) Prec@5 99.000 (99.320) +2022-11-14 15:57:34,619 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0763) Prec@1 86.000 (87.385) Prec@5 98.000 (99.269) +2022-11-14 15:57:34,630 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0757) Prec@1 90.000 (87.481) Prec@5 99.000 (99.259) +2022-11-14 15:57:34,642 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0753) Prec@1 91.000 (87.607) Prec@5 100.000 (99.286) +2022-11-14 15:57:34,656 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0760) Prec@1 87.000 (87.586) Prec@5 99.000 (99.276) +2022-11-14 15:57:34,669 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0754) Prec@1 92.000 (87.733) Prec@5 98.000 (99.233) +2022-11-14 15:57:34,682 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0753) Prec@1 88.000 (87.742) Prec@5 100.000 (99.258) +2022-11-14 15:57:34,697 Test: [31/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0752) Prec@1 88.000 (87.750) Prec@5 98.000 (99.219) +2022-11-14 15:57:34,712 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0754) Prec@1 87.000 (87.727) Prec@5 100.000 (99.242) +2022-11-14 15:57:34,723 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0756) Prec@1 85.000 (87.647) Prec@5 99.000 (99.235) +2022-11-14 15:57:34,736 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0757) Prec@1 88.000 (87.657) Prec@5 97.000 (99.171) +2022-11-14 15:57:34,751 Test: [35/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0755) Prec@1 90.000 (87.722) Prec@5 100.000 (99.194) +2022-11-14 15:57:34,763 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0749) Prec@1 91.000 (87.811) Prec@5 98.000 (99.162) +2022-11-14 15:57:34,773 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0750) Prec@1 87.000 (87.789) Prec@5 100.000 (99.184) +2022-11-14 15:57:34,783 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0744) Prec@1 91.000 (87.872) Prec@5 100.000 (99.205) +2022-11-14 15:57:34,798 Test: [39/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0741) Prec@1 92.000 (87.975) Prec@5 100.000 (99.225) +2022-11-14 15:57:34,810 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0745) Prec@1 85.000 (87.902) Prec@5 97.000 (99.171) +2022-11-14 15:57:34,820 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0742) Prec@1 90.000 (87.952) Prec@5 99.000 (99.167) +2022-11-14 15:57:34,830 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0736) Prec@1 93.000 (88.070) Prec@5 99.000 (99.163) +2022-11-14 15:57:34,844 Test: [43/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0736) Prec@1 88.000 (88.068) Prec@5 98.000 (99.136) +2022-11-14 15:57:34,856 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0734) Prec@1 89.000 (88.089) Prec@5 100.000 (99.156) +2022-11-14 15:57:34,867 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0740) Prec@1 81.000 (87.935) Prec@5 99.000 (99.152) +2022-11-14 15:57:34,877 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0737) Prec@1 91.000 (88.000) Prec@5 100.000 (99.170) +2022-11-14 15:57:34,890 Test: [47/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0741) Prec@1 85.000 (87.938) Prec@5 98.000 (99.146) +2022-11-14 15:57:34,902 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0736) Prec@1 93.000 (88.041) Prec@5 100.000 (99.163) +2022-11-14 15:57:34,913 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1124 (0.0744) Prec@1 82.000 (87.920) Prec@5 100.000 (99.180) +2022-11-14 15:57:34,923 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0745) Prec@1 87.000 (87.902) Prec@5 99.000 (99.176) +2022-11-14 15:57:34,936 Test: [51/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0747) Prec@1 88.000 (87.904) Prec@5 100.000 (99.192) +2022-11-14 15:57:34,948 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0747) Prec@1 88.000 (87.906) Prec@5 99.000 (99.189) +2022-11-14 15:57:34,958 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0750) Prec@1 85.000 (87.852) Prec@5 98.000 (99.167) +2022-11-14 15:57:34,969 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0753) Prec@1 87.000 (87.836) Prec@5 100.000 (99.182) +2022-11-14 15:57:34,983 Test: [55/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0753) Prec@1 87.000 (87.821) Prec@5 99.000 (99.179) +2022-11-14 15:57:34,995 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0751) Prec@1 88.000 (87.825) Prec@5 100.000 (99.193) +2022-11-14 15:57:35,006 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0750) Prec@1 90.000 (87.862) Prec@5 98.000 (99.172) +2022-11-14 15:57:35,017 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0755) Prec@1 82.000 (87.763) Prec@5 98.000 (99.153) +2022-11-14 15:57:35,030 Test: [59/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0757) Prec@1 83.000 (87.683) Prec@5 99.000 (99.150) +2022-11-14 15:57:35,042 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0756) Prec@1 90.000 (87.721) Prec@5 99.000 (99.148) +2022-11-14 15:57:35,052 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0757) Prec@1 86.000 (87.694) Prec@5 99.000 (99.145) +2022-11-14 15:57:35,062 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0756) Prec@1 90.000 (87.730) Prec@5 100.000 (99.159) +2022-11-14 15:57:35,076 Test: [63/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0752) Prec@1 91.000 (87.781) Prec@5 100.000 (99.172) +2022-11-14 15:57:35,088 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0757) Prec@1 84.000 (87.723) Prec@5 100.000 (99.185) +2022-11-14 15:57:35,098 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0757) Prec@1 87.000 (87.712) Prec@5 100.000 (99.197) +2022-11-14 15:57:35,109 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0752) Prec@1 93.000 (87.791) Prec@5 99.000 (99.194) +2022-11-14 15:57:35,121 Test: [67/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0752) Prec@1 89.000 (87.809) Prec@5 98.000 (99.176) +2022-11-14 15:57:35,133 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0749) Prec@1 91.000 (87.855) Prec@5 99.000 (99.174) +2022-11-14 15:57:35,144 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0751) Prec@1 83.000 (87.786) Prec@5 100.000 (99.186) +2022-11-14 15:57:35,154 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.0756) Prec@1 85.000 (87.746) Prec@5 98.000 (99.169) +2022-11-14 15:57:35,165 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0756) Prec@1 86.000 (87.722) Prec@5 99.000 (99.167) +2022-11-14 15:57:35,174 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0753) Prec@1 91.000 (87.767) Prec@5 100.000 (99.178) +2022-11-14 15:57:35,185 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0750) Prec@1 93.000 (87.838) Prec@5 100.000 (99.189) +2022-11-14 15:57:35,195 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0750) Prec@1 88.000 (87.840) Prec@5 99.000 (99.187) +2022-11-14 15:57:35,205 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0747) Prec@1 93.000 (87.908) Prec@5 100.000 (99.197) +2022-11-14 15:57:35,215 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0746) Prec@1 89.000 (87.922) Prec@5 99.000 (99.195) +2022-11-14 15:57:35,226 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.0751) Prec@1 84.000 (87.872) Prec@5 98.000 (99.179) +2022-11-14 15:57:35,236 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0749) Prec@1 89.000 (87.886) Prec@5 100.000 (99.190) +2022-11-14 15:57:35,248 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0751) Prec@1 85.000 (87.850) Prec@5 100.000 (99.200) +2022-11-14 15:57:35,258 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0752) Prec@1 88.000 (87.852) Prec@5 99.000 (99.198) +2022-11-14 15:57:35,268 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0753) Prec@1 83.000 (87.793) Prec@5 99.000 (99.195) +2022-11-14 15:57:35,279 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0754) Prec@1 87.000 (87.783) Prec@5 98.000 (99.181) +2022-11-14 15:57:35,291 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0753) Prec@1 86.000 (87.762) Prec@5 100.000 (99.190) +2022-11-14 15:57:35,301 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0754) Prec@1 87.000 (87.753) Prec@5 99.000 (99.188) +2022-11-14 15:57:35,312 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0755) Prec@1 87.000 (87.744) Prec@5 100.000 (99.198) +2022-11-14 15:57:35,321 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0755) Prec@1 90.000 (87.770) Prec@5 99.000 (99.195) +2022-11-14 15:57:35,333 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0756) Prec@1 87.000 (87.761) Prec@5 98.000 (99.182) +2022-11-14 15:57:35,342 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0756) Prec@1 86.000 (87.742) Prec@5 100.000 (99.191) +2022-11-14 15:57:35,355 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0755) Prec@1 90.000 (87.767) Prec@5 99.000 (99.189) +2022-11-14 15:57:35,367 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0752) Prec@1 93.000 (87.824) Prec@5 100.000 (99.198) +2022-11-14 15:57:35,378 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0431 (0.0748) Prec@1 92.000 (87.870) Prec@5 99.000 (99.196) +2022-11-14 15:57:35,390 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0747) Prec@1 88.000 (87.871) Prec@5 99.000 (99.194) +2022-11-14 15:57:35,400 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0747) Prec@1 88.000 (87.872) Prec@5 99.000 (99.191) +2022-11-14 15:57:35,411 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0748) Prec@1 86.000 (87.853) Prec@5 100.000 (99.200) +2022-11-14 15:57:35,420 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0747) Prec@1 91.000 (87.885) Prec@5 99.000 (99.198) +2022-11-14 15:57:35,431 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0744) Prec@1 93.000 (87.938) Prec@5 99.000 (99.196) +2022-11-14 15:57:35,441 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0745) Prec@1 86.000 (87.918) Prec@5 100.000 (99.204) +2022-11-14 15:57:35,452 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0748) Prec@1 83.000 (87.869) Prec@5 98.000 (99.192) +2022-11-14 15:57:35,463 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0748) Prec@1 88.000 (87.870) Prec@5 99.000 (99.190) +2022-11-14 15:57:35,521 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:57:35,876 Epoch: [285][0/500] Time 0.028 (0.028) Data 0.258 (0.258) Loss 0.0287 (0.0287) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:36,207 Epoch: [285][10/500] Time 0.027 (0.030) Data 0.002 (0.025) Loss 0.0446 (0.0366) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:57:36,581 Epoch: [285][20/500] Time 0.053 (0.030) Data 0.002 (0.014) Loss 0.0194 (0.0309) Prec@1 96.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 15:57:37,171 Epoch: [285][30/500] Time 0.070 (0.037) Data 0.002 (0.010) Loss 0.0332 (0.0315) Prec@1 96.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 15:57:37,714 Epoch: [285][40/500] Time 0.055 (0.040) Data 0.002 (0.008) Loss 0.0338 (0.0319) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 15:57:38,312 Epoch: [285][50/500] Time 0.078 (0.043) Data 0.002 (0.007) Loss 0.0426 (0.0337) Prec@1 94.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 15:57:38,858 Epoch: [285][60/500] Time 0.050 (0.044) Data 0.002 (0.006) Loss 0.0302 (0.0332) Prec@1 94.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 15:57:39,468 Epoch: [285][70/500] Time 0.048 (0.045) Data 0.002 (0.006) Loss 0.0307 (0.0329) Prec@1 95.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 15:57:40,072 Epoch: [285][80/500] Time 0.068 (0.046) Data 0.002 (0.005) Loss 0.0606 (0.0360) Prec@1 91.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 15:57:40,587 Epoch: [285][90/500] Time 0.045 (0.046) Data 0.003 (0.005) Loss 0.0612 (0.0385) Prec@1 89.000 (93.500) Prec@5 98.000 (99.600) +2022-11-14 15:57:41,153 Epoch: [285][100/500] Time 0.056 (0.047) Data 0.002 (0.005) Loss 0.0248 (0.0373) Prec@1 97.000 (93.818) Prec@5 100.000 (99.636) +2022-11-14 15:57:41,706 Epoch: [285][110/500] Time 0.050 (0.047) Data 0.002 (0.004) Loss 0.0432 (0.0377) Prec@1 92.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 15:57:42,313 Epoch: [285][120/500] Time 0.056 (0.048) Data 0.002 (0.004) Loss 0.0105 (0.0357) Prec@1 99.000 (94.077) Prec@5 100.000 (99.692) +2022-11-14 15:57:42,870 Epoch: [285][130/500] Time 0.050 (0.048) Data 0.002 (0.004) Loss 0.0422 (0.0361) Prec@1 94.000 (94.071) Prec@5 99.000 (99.643) +2022-11-14 15:57:43,454 Epoch: [285][140/500] Time 0.047 (0.048) Data 0.002 (0.004) Loss 0.0167 (0.0348) Prec@1 98.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 15:57:44,052 Epoch: [285][150/500] Time 0.058 (0.048) Data 0.002 (0.004) Loss 0.0469 (0.0356) Prec@1 93.000 (94.250) Prec@5 100.000 (99.688) +2022-11-14 15:57:44,643 Epoch: [285][160/500] Time 0.048 (0.049) Data 0.002 (0.004) Loss 0.0271 (0.0351) Prec@1 96.000 (94.353) Prec@5 100.000 (99.706) +2022-11-14 15:57:45,190 Epoch: [285][170/500] Time 0.060 (0.049) Data 0.002 (0.004) Loss 0.0766 (0.0374) Prec@1 86.000 (93.889) Prec@5 100.000 (99.722) +2022-11-14 15:57:45,741 Epoch: [285][180/500] Time 0.060 (0.049) Data 0.002 (0.004) Loss 0.0534 (0.0382) Prec@1 89.000 (93.632) Prec@5 99.000 (99.684) +2022-11-14 15:57:46,294 Epoch: [285][190/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0356 (0.0381) Prec@1 94.000 (93.650) Prec@5 100.000 (99.700) +2022-11-14 15:57:46,840 Epoch: [285][200/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0191 (0.0372) Prec@1 97.000 (93.810) Prec@5 100.000 (99.714) +2022-11-14 15:57:47,383 Epoch: [285][210/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0240 (0.0366) Prec@1 96.000 (93.909) Prec@5 100.000 (99.727) +2022-11-14 15:57:47,940 Epoch: [285][220/500] Time 0.046 (0.049) Data 0.002 (0.003) Loss 0.0336 (0.0365) Prec@1 93.000 (93.870) Prec@5 100.000 (99.739) +2022-11-14 15:57:48,512 Epoch: [285][230/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0291 (0.0362) Prec@1 96.000 (93.958) Prec@5 100.000 (99.750) +2022-11-14 15:57:49,090 Epoch: [285][240/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0239 (0.0357) Prec@1 95.000 (94.000) Prec@5 100.000 (99.760) +2022-11-14 15:57:49,632 Epoch: [285][250/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0144 (0.0348) Prec@1 97.000 (94.115) Prec@5 100.000 (99.769) +2022-11-14 15:57:50,181 Epoch: [285][260/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0259 (0.0345) Prec@1 96.000 (94.185) Prec@5 99.000 (99.741) +2022-11-14 15:57:50,792 Epoch: [285][270/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0385 (0.0347) Prec@1 93.000 (94.143) Prec@5 99.000 (99.714) +2022-11-14 15:57:51,426 Epoch: [285][280/500] Time 0.075 (0.049) Data 0.002 (0.003) Loss 0.0215 (0.0342) Prec@1 98.000 (94.276) Prec@5 100.000 (99.724) +2022-11-14 15:57:52,100 Epoch: [285][290/500] Time 0.044 (0.050) Data 0.002 (0.003) Loss 0.0208 (0.0338) Prec@1 96.000 (94.333) Prec@5 100.000 (99.733) +2022-11-14 15:57:52,733 Epoch: [285][300/500] Time 0.083 (0.050) Data 0.002 (0.003) Loss 0.0171 (0.0332) Prec@1 97.000 (94.419) Prec@5 99.000 (99.710) +2022-11-14 15:57:53,310 Epoch: [285][310/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0265 (0.0330) Prec@1 96.000 (94.469) Prec@5 100.000 (99.719) +2022-11-14 15:57:53,843 Epoch: [285][320/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0131 (0.0324) Prec@1 97.000 (94.545) Prec@5 100.000 (99.727) +2022-11-14 15:57:54,409 Epoch: [285][330/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0241 (0.0322) Prec@1 97.000 (94.618) Prec@5 100.000 (99.735) +2022-11-14 15:57:55,029 Epoch: [285][340/500] Time 0.040 (0.050) Data 0.002 (0.003) Loss 0.0201 (0.0318) Prec@1 96.000 (94.657) Prec@5 100.000 (99.743) +2022-11-14 15:57:55,581 Epoch: [285][350/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0440 (0.0322) Prec@1 93.000 (94.611) Prec@5 100.000 (99.750) +2022-11-14 15:57:56,135 Epoch: [285][360/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0265 (0.0320) Prec@1 95.000 (94.622) Prec@5 100.000 (99.757) +2022-11-14 15:57:56,702 Epoch: [285][370/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0212 (0.0317) Prec@1 99.000 (94.737) Prec@5 100.000 (99.763) +2022-11-14 15:57:57,237 Epoch: [285][380/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0604 (0.0325) Prec@1 91.000 (94.641) Prec@5 100.000 (99.769) +2022-11-14 15:57:57,794 Epoch: [285][390/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0405 (0.0327) Prec@1 95.000 (94.650) Prec@5 100.000 (99.775) +2022-11-14 15:57:58,358 Epoch: [285][400/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0211 (0.0324) Prec@1 97.000 (94.707) Prec@5 100.000 (99.780) +2022-11-14 15:57:58,896 Epoch: [285][410/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0134 (0.0319) Prec@1 98.000 (94.786) Prec@5 100.000 (99.786) +2022-11-14 15:57:59,451 Epoch: [285][420/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0150 (0.0315) Prec@1 97.000 (94.837) Prec@5 100.000 (99.791) +2022-11-14 15:57:59,999 Epoch: [285][430/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0241 (0.0314) Prec@1 97.000 (94.886) Prec@5 100.000 (99.795) +2022-11-14 15:58:00,551 Epoch: [285][440/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0211 (0.0311) Prec@1 96.000 (94.911) Prec@5 100.000 (99.800) +2022-11-14 15:58:01,104 Epoch: [285][450/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0333 (0.0312) Prec@1 93.000 (94.870) Prec@5 100.000 (99.804) +2022-11-14 15:58:01,650 Epoch: [285][460/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0476 (0.0315) Prec@1 92.000 (94.809) Prec@5 98.000 (99.766) +2022-11-14 15:58:02,203 Epoch: [285][470/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0598 (0.0321) Prec@1 91.000 (94.729) Prec@5 100.000 (99.771) +2022-11-14 15:58:02,755 Epoch: [285][480/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0328 (0.0321) Prec@1 94.000 (94.714) Prec@5 100.000 (99.776) +2022-11-14 15:58:03,310 Epoch: [285][490/500] Time 0.052 (0.050) Data 0.003 (0.003) Loss 0.0291 (0.0321) Prec@1 95.000 (94.720) Prec@5 100.000 (99.780) +2022-11-14 15:58:03,786 Epoch: [285][499/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0192 (0.0318) Prec@1 98.000 (94.784) Prec@5 100.000 (99.784) +2022-11-14 15:58:04,095 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0491 (0.0491) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:04,106 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0594) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 15:58:04,115 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0600) Prec@1 88.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 15:58:04,129 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0642) Prec@1 86.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 15:58:04,138 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0663) Prec@1 87.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 15:58:04,146 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0410 (0.0621) Prec@1 92.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 15:58:04,156 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0622) Prec@1 91.000 (89.000) Prec@5 99.000 (99.571) +2022-11-14 15:58:04,169 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0651) Prec@1 84.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 15:58:04,179 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0661) Prec@1 88.000 (88.333) Prec@5 99.000 (99.556) +2022-11-14 15:58:04,189 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0660) Prec@1 88.000 (88.300) Prec@5 99.000 (99.500) +2022-11-14 15:58:04,198 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0650) Prec@1 92.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 15:58:04,209 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0667) Prec@1 88.000 (88.583) Prec@5 100.000 (99.583) +2022-11-14 15:58:04,219 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0668) Prec@1 88.000 (88.538) Prec@5 100.000 (99.615) +2022-11-14 15:58:04,229 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0666) Prec@1 89.000 (88.571) Prec@5 100.000 (99.643) +2022-11-14 15:58:04,240 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0680) Prec@1 85.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 15:58:04,249 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0683) Prec@1 87.000 (88.250) Prec@5 100.000 (99.688) +2022-11-14 15:58:04,260 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0673) Prec@1 94.000 (88.588) Prec@5 98.000 (99.588) +2022-11-14 15:58:04,269 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0694) Prec@1 82.000 (88.222) Prec@5 99.000 (99.556) +2022-11-14 15:58:04,279 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0703) Prec@1 87.000 (88.158) Prec@5 98.000 (99.474) +2022-11-14 15:58:04,289 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0714) Prec@1 85.000 (88.000) Prec@5 98.000 (99.400) +2022-11-14 15:58:04,300 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0720) Prec@1 85.000 (87.857) Prec@5 100.000 (99.429) +2022-11-14 15:58:04,313 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0720) Prec@1 91.000 (88.000) Prec@5 99.000 (99.409) +2022-11-14 15:58:04,324 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0727) Prec@1 87.000 (87.957) Prec@5 98.000 (99.348) +2022-11-14 15:58:04,335 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0726) Prec@1 88.000 (87.958) Prec@5 100.000 (99.375) +2022-11-14 15:58:04,346 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0732) Prec@1 86.000 (87.880) Prec@5 100.000 (99.400) +2022-11-14 15:58:04,357 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0733) Prec@1 88.000 (87.885) Prec@5 99.000 (99.385) +2022-11-14 15:58:04,369 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0722) Prec@1 93.000 (88.074) Prec@5 99.000 (99.370) +2022-11-14 15:58:04,381 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0726) Prec@1 87.000 (88.036) Prec@5 99.000 (99.357) +2022-11-14 15:58:04,391 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0720) Prec@1 92.000 (88.172) Prec@5 99.000 (99.345) +2022-11-14 15:58:04,401 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0721) Prec@1 87.000 (88.133) Prec@5 99.000 (99.333) +2022-11-14 15:58:04,412 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0719) Prec@1 88.000 (88.129) Prec@5 100.000 (99.355) +2022-11-14 15:58:04,423 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0714) Prec@1 93.000 (88.281) Prec@5 100.000 (99.375) +2022-11-14 15:58:04,435 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0720) Prec@1 84.000 (88.152) Prec@5 100.000 (99.394) +2022-11-14 15:58:04,446 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0723) Prec@1 88.000 (88.147) Prec@5 100.000 (99.412) +2022-11-14 15:58:04,458 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0728) Prec@1 87.000 (88.114) Prec@5 98.000 (99.371) +2022-11-14 15:58:04,470 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0725) Prec@1 92.000 (88.222) Prec@5 100.000 (99.389) +2022-11-14 15:58:04,481 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0723) Prec@1 89.000 (88.243) Prec@5 99.000 (99.378) +2022-11-14 15:58:04,494 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0726) Prec@1 86.000 (88.184) Prec@5 100.000 (99.395) +2022-11-14 15:58:04,506 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0719) Prec@1 94.000 (88.333) Prec@5 99.000 (99.385) +2022-11-14 15:58:04,516 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0719) Prec@1 86.000 (88.275) Prec@5 99.000 (99.375) +2022-11-14 15:58:04,526 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0724) Prec@1 86.000 (88.220) Prec@5 99.000 (99.366) +2022-11-14 15:58:04,538 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0724) Prec@1 90.000 (88.262) Prec@5 99.000 (99.357) +2022-11-14 15:58:04,549 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0720) Prec@1 91.000 (88.326) Prec@5 99.000 (99.349) +2022-11-14 15:58:04,561 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0718) Prec@1 91.000 (88.386) Prec@5 97.000 (99.295) +2022-11-14 15:58:04,572 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0715) Prec@1 90.000 (88.422) Prec@5 99.000 (99.289) +2022-11-14 15:58:04,583 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0721) Prec@1 85.000 (88.348) Prec@5 99.000 (99.283) +2022-11-14 15:58:04,594 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0719) Prec@1 88.000 (88.340) Prec@5 100.000 (99.298) +2022-11-14 15:58:04,604 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0727) Prec@1 82.000 (88.208) Prec@5 99.000 (99.292) +2022-11-14 15:58:04,616 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0720) Prec@1 93.000 (88.306) Prec@5 100.000 (99.306) +2022-11-14 15:58:04,626 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1164 (0.0729) Prec@1 82.000 (88.180) Prec@5 99.000 (99.300) +2022-11-14 15:58:04,637 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0727) Prec@1 90.000 (88.216) Prec@5 100.000 (99.314) +2022-11-14 15:58:04,648 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0729) Prec@1 87.000 (88.192) Prec@5 98.000 (99.288) +2022-11-14 15:58:04,660 Test: [52/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0731) Prec@1 88.000 (88.189) Prec@5 98.000 (99.264) +2022-11-14 15:58:04,674 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0731) Prec@1 88.000 (88.185) Prec@5 99.000 (99.259) +2022-11-14 15:58:04,685 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0735) Prec@1 84.000 (88.109) Prec@5 100.000 (99.273) +2022-11-14 15:58:04,696 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0734) Prec@1 92.000 (88.179) Prec@5 98.000 (99.250) +2022-11-14 15:58:04,706 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0736) Prec@1 84.000 (88.105) Prec@5 100.000 (99.263) +2022-11-14 15:58:04,716 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0737) Prec@1 87.000 (88.086) Prec@5 100.000 (99.276) +2022-11-14 15:58:04,727 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0739) Prec@1 86.000 (88.051) Prec@5 100.000 (99.288) +2022-11-14 15:58:04,737 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0737) Prec@1 91.000 (88.100) Prec@5 99.000 (99.283) +2022-11-14 15:58:04,749 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0740) Prec@1 85.000 (88.049) Prec@5 98.000 (99.262) +2022-11-14 15:58:04,759 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0741) Prec@1 87.000 (88.032) Prec@5 100.000 (99.274) +2022-11-14 15:58:04,769 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0742) Prec@1 85.000 (87.984) Prec@5 99.000 (99.270) +2022-11-14 15:58:04,779 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0737) Prec@1 92.000 (88.047) Prec@5 99.000 (99.266) +2022-11-14 15:58:04,792 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0739) Prec@1 88.000 (88.046) Prec@5 100.000 (99.277) +2022-11-14 15:58:04,803 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0742) Prec@1 86.000 (88.015) Prec@5 99.000 (99.273) +2022-11-14 15:58:04,815 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0391 (0.0736) Prec@1 93.000 (88.090) Prec@5 99.000 (99.269) +2022-11-14 15:58:04,827 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0734) Prec@1 90.000 (88.118) Prec@5 100.000 (99.279) +2022-11-14 15:58:04,841 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0732) Prec@1 91.000 (88.159) Prec@5 99.000 (99.275) +2022-11-14 15:58:04,852 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0735) Prec@1 86.000 (88.129) Prec@5 100.000 (99.286) +2022-11-14 15:58:04,862 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0736) Prec@1 88.000 (88.127) Prec@5 99.000 (99.282) +2022-11-14 15:58:04,873 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0735) Prec@1 88.000 (88.125) Prec@5 100.000 (99.292) +2022-11-14 15:58:04,884 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0732) Prec@1 92.000 (88.178) Prec@5 100.000 (99.301) +2022-11-14 15:58:04,896 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0280 (0.0726) Prec@1 96.000 (88.284) Prec@5 100.000 (99.311) +2022-11-14 15:58:04,907 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0729) Prec@1 83.000 (88.213) Prec@5 100.000 (99.320) +2022-11-14 15:58:04,917 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0728) Prec@1 90.000 (88.237) Prec@5 100.000 (99.329) +2022-11-14 15:58:04,927 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0728) Prec@1 87.000 (88.221) Prec@5 99.000 (99.325) +2022-11-14 15:58:04,938 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0732) Prec@1 84.000 (88.167) Prec@5 96.000 (99.282) +2022-11-14 15:58:04,951 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0733) Prec@1 82.000 (88.089) Prec@5 100.000 (99.291) +2022-11-14 15:58:04,962 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0735) Prec@1 86.000 (88.062) Prec@5 99.000 (99.287) +2022-11-14 15:58:04,973 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0736) Prec@1 87.000 (88.049) Prec@5 99.000 (99.284) +2022-11-14 15:58:04,986 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0739) Prec@1 84.000 (88.000) Prec@5 100.000 (99.293) +2022-11-14 15:58:04,998 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0740) Prec@1 86.000 (87.976) Prec@5 99.000 (99.289) +2022-11-14 15:58:05,009 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0738) Prec@1 93.000 (88.036) Prec@5 99.000 (99.286) +2022-11-14 15:58:05,020 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0742) Prec@1 84.000 (87.988) Prec@5 99.000 (99.282) +2022-11-14 15:58:05,029 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0743) Prec@1 87.000 (87.977) Prec@5 100.000 (99.291) +2022-11-14 15:58:05,041 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0743) Prec@1 89.000 (87.989) Prec@5 98.000 (99.276) +2022-11-14 15:58:05,052 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0743) Prec@1 86.000 (87.966) Prec@5 99.000 (99.273) +2022-11-14 15:58:05,064 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0742) Prec@1 89.000 (87.978) Prec@5 100.000 (99.281) +2022-11-14 15:58:05,075 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0742) Prec@1 89.000 (87.989) Prec@5 100.000 (99.289) +2022-11-14 15:58:05,085 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0740) Prec@1 91.000 (88.022) Prec@5 100.000 (99.297) +2022-11-14 15:58:05,096 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0738) Prec@1 92.000 (88.065) Prec@5 99.000 (99.293) +2022-11-14 15:58:05,107 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0740) Prec@1 85.000 (88.032) Prec@5 98.000 (99.280) +2022-11-14 15:58:05,120 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0740) Prec@1 89.000 (88.043) Prec@5 100.000 (99.287) +2022-11-14 15:58:05,132 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0740) Prec@1 86.000 (88.021) Prec@5 99.000 (99.284) +2022-11-14 15:58:05,144 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0737) Prec@1 96.000 (88.104) Prec@5 99.000 (99.281) +2022-11-14 15:58:05,154 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0735) Prec@1 91.000 (88.134) Prec@5 99.000 (99.278) +2022-11-14 15:58:05,167 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0736) Prec@1 87.000 (88.122) Prec@5 99.000 (99.276) +2022-11-14 15:58:05,178 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0738) Prec@1 87.000 (88.111) Prec@5 100.000 (99.283) +2022-11-14 15:58:05,189 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0737) Prec@1 91.000 (88.140) Prec@5 100.000 (99.290) +2022-11-14 15:58:05,263 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:58:05,615 Epoch: [286][0/500] Time 0.026 (0.026) Data 0.259 (0.259) Loss 0.0391 (0.0391) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:05,900 Epoch: [286][10/500] Time 0.029 (0.025) Data 0.002 (0.025) Loss 0.0134 (0.0262) Prec@1 97.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 15:58:06,215 Epoch: [286][20/500] Time 0.031 (0.026) Data 0.002 (0.014) Loss 0.0477 (0.0334) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:06,526 Epoch: [286][30/500] Time 0.023 (0.027) Data 0.002 (0.010) Loss 0.0213 (0.0304) Prec@1 96.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 15:58:06,855 Epoch: [286][40/500] Time 0.035 (0.027) Data 0.002 (0.008) Loss 0.0250 (0.0293) Prec@1 96.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 15:58:07,195 Epoch: [286][50/500] Time 0.038 (0.028) Data 0.002 (0.007) Loss 0.0523 (0.0331) Prec@1 89.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 15:58:07,862 Epoch: [286][60/500] Time 0.073 (0.033) Data 0.002 (0.006) Loss 0.0374 (0.0337) Prec@1 96.000 (93.714) Prec@5 100.000 (100.000) +2022-11-14 15:58:08,565 Epoch: [286][70/500] Time 0.075 (0.037) Data 0.002 (0.006) Loss 0.0450 (0.0352) Prec@1 91.000 (93.375) Prec@5 99.000 (99.875) +2022-11-14 15:58:09,248 Epoch: [286][80/500] Time 0.074 (0.040) Data 0.002 (0.005) Loss 0.0365 (0.0353) Prec@1 94.000 (93.444) Prec@5 99.000 (99.778) +2022-11-14 15:58:09,945 Epoch: [286][90/500] Time 0.074 (0.043) Data 0.002 (0.005) Loss 0.0187 (0.0336) Prec@1 97.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 15:58:10,591 Epoch: [286][100/500] Time 0.063 (0.044) Data 0.002 (0.005) Loss 0.0393 (0.0342) Prec@1 93.000 (93.727) Prec@5 100.000 (99.818) +2022-11-14 15:58:11,263 Epoch: [286][110/500] Time 0.065 (0.046) Data 0.002 (0.004) Loss 0.0291 (0.0337) Prec@1 95.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 15:58:11,935 Epoch: [286][120/500] Time 0.067 (0.047) Data 0.002 (0.004) Loss 0.0286 (0.0333) Prec@1 95.000 (93.923) Prec@5 100.000 (99.846) +2022-11-14 15:58:12,605 Epoch: [286][130/500] Time 0.078 (0.048) Data 0.002 (0.004) Loss 0.0360 (0.0335) Prec@1 93.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 15:58:13,290 Epoch: [286][140/500] Time 0.066 (0.049) Data 0.002 (0.004) Loss 0.0426 (0.0341) Prec@1 92.000 (93.733) Prec@5 99.000 (99.800) +2022-11-14 15:58:13,954 Epoch: [286][150/500] Time 0.055 (0.049) Data 0.002 (0.004) Loss 0.0477 (0.0350) Prec@1 91.000 (93.562) Prec@5 100.000 (99.812) +2022-11-14 15:58:14,656 Epoch: [286][160/500] Time 0.062 (0.050) Data 0.002 (0.004) Loss 0.0414 (0.0354) Prec@1 94.000 (93.588) Prec@5 100.000 (99.824) +2022-11-14 15:58:15,327 Epoch: [286][170/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0440 (0.0358) Prec@1 91.000 (93.444) Prec@5 100.000 (99.833) +2022-11-14 15:58:16,007 Epoch: [286][180/500] Time 0.073 (0.051) Data 0.002 (0.003) Loss 0.0330 (0.0357) Prec@1 94.000 (93.474) Prec@5 100.000 (99.842) +2022-11-14 15:58:16,704 Epoch: [286][190/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0456 (0.0362) Prec@1 93.000 (93.450) Prec@5 100.000 (99.850) +2022-11-14 15:58:17,362 Epoch: [286][200/500] Time 0.060 (0.052) Data 0.003 (0.003) Loss 0.0238 (0.0356) Prec@1 96.000 (93.571) Prec@5 100.000 (99.857) +2022-11-14 15:58:18,046 Epoch: [286][210/500] Time 0.074 (0.053) Data 0.002 (0.003) Loss 0.0064 (0.0343) Prec@1 100.000 (93.864) Prec@5 100.000 (99.864) +2022-11-14 15:58:18,702 Epoch: [286][220/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0297 (0.0341) Prec@1 93.000 (93.826) Prec@5 100.000 (99.870) +2022-11-14 15:58:19,372 Epoch: [286][230/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0137 (0.0332) Prec@1 98.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 15:58:20,052 Epoch: [286][240/500] Time 0.074 (0.054) Data 0.002 (0.003) Loss 0.0518 (0.0340) Prec@1 92.000 (93.920) Prec@5 100.000 (99.880) +2022-11-14 15:58:20,601 Epoch: [286][250/500] Time 0.039 (0.053) Data 0.002 (0.003) Loss 0.0267 (0.0337) Prec@1 96.000 (94.000) Prec@5 100.000 (99.885) +2022-11-14 15:58:20,960 Epoch: [286][260/500] Time 0.031 (0.053) Data 0.002 (0.003) Loss 0.0386 (0.0339) Prec@1 96.000 (94.074) Prec@5 100.000 (99.889) +2022-11-14 15:58:21,314 Epoch: [286][270/500] Time 0.034 (0.052) Data 0.002 (0.003) Loss 0.0209 (0.0334) Prec@1 96.000 (94.143) Prec@5 100.000 (99.893) +2022-11-14 15:58:21,670 Epoch: [286][280/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.0401 (0.0336) Prec@1 94.000 (94.138) Prec@5 100.000 (99.897) +2022-11-14 15:58:22,029 Epoch: [286][290/500] Time 0.035 (0.050) Data 0.002 (0.003) Loss 0.0277 (0.0334) Prec@1 93.000 (94.100) Prec@5 100.000 (99.900) +2022-11-14 15:58:22,377 Epoch: [286][300/500] Time 0.033 (0.050) Data 0.002 (0.003) Loss 0.0331 (0.0334) Prec@1 95.000 (94.129) Prec@5 100.000 (99.903) +2022-11-14 15:58:22,726 Epoch: [286][310/500] Time 0.034 (0.049) Data 0.002 (0.003) Loss 0.0367 (0.0335) Prec@1 94.000 (94.125) Prec@5 100.000 (99.906) +2022-11-14 15:58:23,084 Epoch: [286][320/500] Time 0.038 (0.049) Data 0.002 (0.003) Loss 0.0363 (0.0336) Prec@1 95.000 (94.152) Prec@5 100.000 (99.909) +2022-11-14 15:58:23,446 Epoch: [286][330/500] Time 0.034 (0.048) Data 0.003 (0.003) Loss 0.0400 (0.0338) Prec@1 94.000 (94.147) Prec@5 99.000 (99.882) +2022-11-14 15:58:23,801 Epoch: [286][340/500] Time 0.034 (0.048) Data 0.002 (0.003) Loss 0.0171 (0.0333) Prec@1 98.000 (94.257) Prec@5 100.000 (99.886) +2022-11-14 15:58:24,156 Epoch: [286][350/500] Time 0.033 (0.047) Data 0.002 (0.003) Loss 0.0208 (0.0330) Prec@1 96.000 (94.306) Prec@5 100.000 (99.889) +2022-11-14 15:58:24,517 Epoch: [286][360/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0287 (0.0329) Prec@1 95.000 (94.324) Prec@5 100.000 (99.892) +2022-11-14 15:58:24,888 Epoch: [286][370/500] Time 0.032 (0.046) Data 0.002 (0.003) Loss 0.0255 (0.0327) Prec@1 97.000 (94.395) Prec@5 100.000 (99.895) +2022-11-14 15:58:25,250 Epoch: [286][380/500] Time 0.030 (0.046) Data 0.002 (0.003) Loss 0.0335 (0.0327) Prec@1 93.000 (94.359) Prec@5 100.000 (99.897) +2022-11-14 15:58:25,605 Epoch: [286][390/500] Time 0.038 (0.046) Data 0.002 (0.003) Loss 0.0191 (0.0324) Prec@1 98.000 (94.450) Prec@5 100.000 (99.900) +2022-11-14 15:58:25,964 Epoch: [286][400/500] Time 0.034 (0.045) Data 0.002 (0.003) Loss 0.0288 (0.0323) Prec@1 95.000 (94.463) Prec@5 99.000 (99.878) +2022-11-14 15:58:26,329 Epoch: [286][410/500] Time 0.040 (0.045) Data 0.002 (0.003) Loss 0.0294 (0.0322) Prec@1 94.000 (94.452) Prec@5 100.000 (99.881) +2022-11-14 15:58:26,687 Epoch: [286][420/500] Time 0.030 (0.045) Data 0.002 (0.003) Loss 0.0385 (0.0323) Prec@1 95.000 (94.465) Prec@5 99.000 (99.860) +2022-11-14 15:58:27,099 Epoch: [286][430/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0302 (0.0323) Prec@1 94.000 (94.455) Prec@5 100.000 (99.864) +2022-11-14 15:58:27,797 Epoch: [286][440/500] Time 0.077 (0.045) Data 0.002 (0.003) Loss 0.0284 (0.0322) Prec@1 94.000 (94.444) Prec@5 98.000 (99.822) +2022-11-14 15:58:28,535 Epoch: [286][450/500] Time 0.073 (0.045) Data 0.002 (0.003) Loss 0.0343 (0.0323) Prec@1 93.000 (94.413) Prec@5 100.000 (99.826) +2022-11-14 15:58:29,248 Epoch: [286][460/500] Time 0.080 (0.046) Data 0.002 (0.003) Loss 0.0305 (0.0322) Prec@1 95.000 (94.426) Prec@5 100.000 (99.830) +2022-11-14 15:58:29,994 Epoch: [286][470/500] Time 0.079 (0.046) Data 0.002 (0.003) Loss 0.0174 (0.0319) Prec@1 98.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 15:58:30,705 Epoch: [286][480/500] Time 0.063 (0.047) Data 0.002 (0.003) Loss 0.0296 (0.0319) Prec@1 96.000 (94.531) Prec@5 100.000 (99.837) +2022-11-14 15:58:31,418 Epoch: [286][490/500] Time 0.064 (0.047) Data 0.002 (0.003) Loss 0.0437 (0.0321) Prec@1 94.000 (94.520) Prec@5 99.000 (99.820) +2022-11-14 15:58:32,056 Epoch: [286][499/500] Time 0.064 (0.047) Data 0.002 (0.003) Loss 0.0341 (0.0321) Prec@1 96.000 (94.549) Prec@5 100.000 (99.824) +2022-11-14 15:58:32,375 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0700 (0.0700) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:32,383 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0637) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:32,392 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0605) Prec@1 93.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:32,406 Test: [3/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0652) Prec@1 88.000 (90.250) Prec@5 100.000 (100.000) +2022-11-14 15:58:32,417 Test: [4/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0666) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:32,427 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0651) Prec@1 91.000 (90.167) Prec@5 98.000 (99.667) +2022-11-14 15:58:32,437 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0654) Prec@1 89.000 (90.000) Prec@5 99.000 (99.571) +2022-11-14 15:58:32,450 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0677) Prec@1 85.000 (89.375) Prec@5 99.000 (99.500) +2022-11-14 15:58:32,460 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0681) Prec@1 90.000 (89.444) Prec@5 99.000 (99.444) +2022-11-14 15:58:32,472 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0674) Prec@1 90.000 (89.500) Prec@5 99.000 (99.400) +2022-11-14 15:58:32,484 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0671) Prec@1 91.000 (89.636) Prec@5 100.000 (99.455) +2022-11-14 15:58:32,494 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0696) Prec@1 85.000 (89.250) Prec@5 99.000 (99.417) +2022-11-14 15:58:32,504 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0687) Prec@1 88.000 (89.154) Prec@5 100.000 (99.462) +2022-11-14 15:58:32,514 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0703) Prec@1 85.000 (88.857) Prec@5 100.000 (99.500) +2022-11-14 15:58:32,528 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0712) Prec@1 85.000 (88.600) Prec@5 99.000 (99.467) +2022-11-14 15:58:32,540 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0717) Prec@1 88.000 (88.562) Prec@5 100.000 (99.500) +2022-11-14 15:58:32,553 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0706) Prec@1 91.000 (88.706) Prec@5 97.000 (99.353) +2022-11-14 15:58:32,565 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0728) Prec@1 83.000 (88.389) Prec@5 100.000 (99.389) +2022-11-14 15:58:32,578 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0746) Prec@1 81.000 (88.000) Prec@5 98.000 (99.316) +2022-11-14 15:58:32,592 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0746) Prec@1 89.000 (88.050) Prec@5 97.000 (99.200) +2022-11-14 15:58:32,605 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0758) Prec@1 83.000 (87.810) Prec@5 100.000 (99.238) +2022-11-14 15:58:32,617 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0757) Prec@1 88.000 (87.818) Prec@5 99.000 (99.227) +2022-11-14 15:58:32,630 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0764) Prec@1 85.000 (87.696) Prec@5 98.000 (99.174) +2022-11-14 15:58:32,642 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0766) Prec@1 85.000 (87.583) Prec@5 100.000 (99.208) +2022-11-14 15:58:32,652 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1098 (0.0779) Prec@1 82.000 (87.360) Prec@5 100.000 (99.240) +2022-11-14 15:58:32,665 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0784) Prec@1 85.000 (87.269) Prec@5 98.000 (99.192) +2022-11-14 15:58:32,677 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0775) Prec@1 88.000 (87.296) Prec@5 100.000 (99.222) +2022-11-14 15:58:32,689 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0774) Prec@1 87.000 (87.286) Prec@5 100.000 (99.250) +2022-11-14 15:58:32,701 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0773) Prec@1 89.000 (87.345) Prec@5 99.000 (99.241) +2022-11-14 15:58:32,714 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0776) Prec@1 87.000 (87.333) Prec@5 100.000 (99.267) +2022-11-14 15:58:32,728 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0773) Prec@1 89.000 (87.387) Prec@5 99.000 (99.258) +2022-11-14 15:58:32,739 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0768) Prec@1 89.000 (87.438) Prec@5 98.000 (99.219) +2022-11-14 15:58:32,749 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0770) Prec@1 86.000 (87.394) Prec@5 100.000 (99.242) +2022-11-14 15:58:32,761 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0772) Prec@1 85.000 (87.324) Prec@5 100.000 (99.265) +2022-11-14 15:58:32,773 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0775) Prec@1 87.000 (87.314) Prec@5 98.000 (99.229) +2022-11-14 15:58:32,787 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0774) Prec@1 88.000 (87.333) Prec@5 99.000 (99.222) +2022-11-14 15:58:32,799 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0774) Prec@1 88.000 (87.351) Prec@5 99.000 (99.216) +2022-11-14 15:58:32,813 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0772) Prec@1 85.000 (87.289) Prec@5 100.000 (99.237) +2022-11-14 15:58:32,828 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0768) Prec@1 92.000 (87.410) Prec@5 99.000 (99.231) +2022-11-14 15:58:32,842 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0763) Prec@1 88.000 (87.425) Prec@5 100.000 (99.250) +2022-11-14 15:58:32,856 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1129 (0.0772) Prec@1 84.000 (87.341) Prec@5 98.000 (99.220) +2022-11-14 15:58:32,871 Test: [41/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0770) Prec@1 89.000 (87.381) Prec@5 99.000 (99.214) +2022-11-14 15:58:32,884 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0763) Prec@1 94.000 (87.535) Prec@5 99.000 (99.209) +2022-11-14 15:58:32,895 Test: [43/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0762) Prec@1 88.000 (87.545) Prec@5 99.000 (99.205) +2022-11-14 15:58:32,906 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0760) Prec@1 87.000 (87.533) Prec@5 99.000 (99.200) +2022-11-14 15:58:32,920 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0762) Prec@1 86.000 (87.500) Prec@5 100.000 (99.217) +2022-11-14 15:58:32,932 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0762) Prec@1 87.000 (87.489) Prec@5 100.000 (99.234) +2022-11-14 15:58:32,945 Test: [47/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0766) Prec@1 83.000 (87.396) Prec@5 99.000 (99.229) +2022-11-14 15:58:32,957 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0763) Prec@1 88.000 (87.408) Prec@5 100.000 (99.245) +2022-11-14 15:58:32,970 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.0769) Prec@1 81.000 (87.280) Prec@5 100.000 (99.260) +2022-11-14 15:58:32,980 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0765) Prec@1 90.000 (87.333) Prec@5 100.000 (99.275) +2022-11-14 15:58:32,993 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0766) Prec@1 87.000 (87.327) Prec@5 100.000 (99.288) +2022-11-14 15:58:33,004 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0764) Prec@1 88.000 (87.340) Prec@5 100.000 (99.302) +2022-11-14 15:58:33,018 Test: [53/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0765) Prec@1 88.000 (87.352) Prec@5 100.000 (99.315) +2022-11-14 15:58:33,029 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0765) Prec@1 89.000 (87.382) Prec@5 99.000 (99.309) +2022-11-14 15:58:33,043 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0764) Prec@1 90.000 (87.429) Prec@5 99.000 (99.304) +2022-11-14 15:58:33,057 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0766) Prec@1 86.000 (87.404) Prec@5 100.000 (99.316) +2022-11-14 15:58:33,070 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0764) Prec@1 91.000 (87.466) Prec@5 100.000 (99.328) +2022-11-14 15:58:33,084 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0769) Prec@1 84.000 (87.407) Prec@5 99.000 (99.322) +2022-11-14 15:58:33,096 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0769) Prec@1 87.000 (87.400) Prec@5 100.000 (99.333) +2022-11-14 15:58:33,105 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0769) Prec@1 90.000 (87.443) Prec@5 100.000 (99.344) +2022-11-14 15:58:33,118 Test: [61/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0768) Prec@1 89.000 (87.468) Prec@5 99.000 (99.339) +2022-11-14 15:58:33,131 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0770) Prec@1 88.000 (87.476) Prec@5 100.000 (99.349) +2022-11-14 15:58:33,143 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0767) Prec@1 91.000 (87.531) Prec@5 100.000 (99.359) +2022-11-14 15:58:33,157 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0768) Prec@1 85.000 (87.492) Prec@5 100.000 (99.369) +2022-11-14 15:58:33,169 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0768) Prec@1 89.000 (87.515) Prec@5 100.000 (99.379) +2022-11-14 15:58:33,182 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0394 (0.0762) Prec@1 93.000 (87.597) Prec@5 100.000 (99.388) +2022-11-14 15:58:33,194 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0761) Prec@1 90.000 (87.632) Prec@5 99.000 (99.382) +2022-11-14 15:58:33,208 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0760) Prec@1 88.000 (87.638) Prec@5 99.000 (99.377) +2022-11-14 15:58:33,221 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0763) Prec@1 86.000 (87.614) Prec@5 99.000 (99.371) +2022-11-14 15:58:33,233 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0767) Prec@1 82.000 (87.535) Prec@5 99.000 (99.366) +2022-11-14 15:58:33,246 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0764) Prec@1 89.000 (87.556) Prec@5 100.000 (99.375) +2022-11-14 15:58:33,256 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0763) Prec@1 90.000 (87.589) Prec@5 100.000 (99.384) +2022-11-14 15:58:33,269 Test: [73/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0431 (0.0758) Prec@1 94.000 (87.676) Prec@5 100.000 (99.392) +2022-11-14 15:58:33,282 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0762) Prec@1 83.000 (87.613) Prec@5 100.000 (99.400) +2022-11-14 15:58:33,294 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0760) Prec@1 89.000 (87.632) Prec@5 99.000 (99.395) +2022-11-14 15:58:33,307 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0759) Prec@1 90.000 (87.662) Prec@5 99.000 (99.390) +2022-11-14 15:58:33,320 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0761) Prec@1 86.000 (87.641) Prec@5 99.000 (99.385) +2022-11-14 15:58:33,334 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0764) Prec@1 82.000 (87.570) Prec@5 100.000 (99.392) +2022-11-14 15:58:33,348 Test: [79/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0765) Prec@1 85.000 (87.537) Prec@5 100.000 (99.400) +2022-11-14 15:58:33,360 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0764) Prec@1 90.000 (87.568) Prec@5 99.000 (99.395) +2022-11-14 15:58:33,373 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0765) Prec@1 86.000 (87.549) Prec@5 100.000 (99.402) +2022-11-14 15:58:33,383 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0765) Prec@1 88.000 (87.554) Prec@5 99.000 (99.398) +2022-11-14 15:58:33,395 Test: [83/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0762) Prec@1 92.000 (87.607) Prec@5 98.000 (99.381) +2022-11-14 15:58:33,407 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1008 (0.0764) Prec@1 81.000 (87.529) Prec@5 100.000 (99.388) +2022-11-14 15:58:33,420 Test: [85/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1124 (0.0769) Prec@1 85.000 (87.500) Prec@5 99.000 (99.384) +2022-11-14 15:58:33,435 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0770) Prec@1 84.000 (87.460) Prec@5 98.000 (99.368) +2022-11-14 15:58:33,446 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1110 (0.0774) Prec@1 82.000 (87.398) Prec@5 99.000 (99.364) +2022-11-14 15:58:33,458 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0774) Prec@1 88.000 (87.404) Prec@5 100.000 (99.371) +2022-11-14 15:58:33,472 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0772) Prec@1 91.000 (87.444) Prec@5 100.000 (99.378) +2022-11-14 15:58:33,486 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0769) Prec@1 91.000 (87.484) Prec@5 100.000 (99.385) +2022-11-14 15:58:33,497 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0766) Prec@1 91.000 (87.522) Prec@5 99.000 (99.380) +2022-11-14 15:58:33,510 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0768) Prec@1 86.000 (87.505) Prec@5 100.000 (99.387) +2022-11-14 15:58:33,520 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0767) Prec@1 87.000 (87.500) Prec@5 100.000 (99.394) +2022-11-14 15:58:33,534 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0769) Prec@1 83.000 (87.453) Prec@5 99.000 (99.389) +2022-11-14 15:58:33,548 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0769) Prec@1 88.000 (87.458) Prec@5 98.000 (99.375) +2022-11-14 15:58:33,559 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0473 (0.0766) Prec@1 93.000 (87.515) Prec@5 98.000 (99.361) +2022-11-14 15:58:33,572 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0766) Prec@1 87.000 (87.510) Prec@5 99.000 (99.357) +2022-11-14 15:58:33,586 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0768) Prec@1 83.000 (87.465) Prec@5 100.000 (99.364) +2022-11-14 15:58:33,601 Test: [99/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0767) Prec@1 89.000 (87.480) Prec@5 100.000 (99.370) +2022-11-14 15:58:33,715 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:58:34,073 Epoch: [287][0/500] Time 0.032 (0.032) Data 0.249 (0.249) Loss 0.0277 (0.0277) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:58:34,324 Epoch: [287][10/500] Time 0.024 (0.023) Data 0.002 (0.024) Loss 0.0492 (0.0384) Prec@1 89.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 15:58:34,574 Epoch: [287][20/500] Time 0.026 (0.023) Data 0.002 (0.014) Loss 0.0210 (0.0326) Prec@1 96.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 15:58:34,884 Epoch: [287][30/500] Time 0.033 (0.024) Data 0.002 (0.010) Loss 0.0286 (0.0316) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:58:35,206 Epoch: [287][40/500] Time 0.029 (0.025) Data 0.002 (0.008) Loss 0.0280 (0.0309) Prec@1 97.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 15:58:35,530 Epoch: [287][50/500] Time 0.033 (0.026) Data 0.002 (0.007) Loss 0.0216 (0.0293) Prec@1 97.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 15:58:35,959 Epoch: [287][60/500] Time 0.063 (0.027) Data 0.002 (0.006) Loss 0.0470 (0.0319) Prec@1 93.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 15:58:36,751 Epoch: [287][70/500] Time 0.083 (0.033) Data 0.002 (0.005) Loss 0.0350 (0.0322) Prec@1 93.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 15:58:37,545 Epoch: [287][80/500] Time 0.083 (0.038) Data 0.002 (0.005) Loss 0.0360 (0.0327) Prec@1 93.000 (94.556) Prec@5 99.000 (99.778) +2022-11-14 15:58:38,306 Epoch: [287][90/500] Time 0.066 (0.041) Data 0.002 (0.005) Loss 0.0120 (0.0306) Prec@1 98.000 (94.900) Prec@5 100.000 (99.800) +2022-11-14 15:58:39,022 Epoch: [287][100/500] Time 0.070 (0.044) Data 0.002 (0.004) Loss 0.0349 (0.0310) Prec@1 96.000 (95.000) Prec@5 100.000 (99.818) +2022-11-14 15:58:39,783 Epoch: [287][110/500] Time 0.063 (0.046) Data 0.002 (0.004) Loss 0.0465 (0.0323) Prec@1 93.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 15:58:40,520 Epoch: [287][120/500] Time 0.075 (0.048) Data 0.002 (0.004) Loss 0.0428 (0.0331) Prec@1 92.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 15:58:41,270 Epoch: [287][130/500] Time 0.075 (0.049) Data 0.002 (0.004) Loss 0.0606 (0.0350) Prec@1 89.000 (94.214) Prec@5 99.000 (99.786) +2022-11-14 15:58:42,049 Epoch: [287][140/500] Time 0.076 (0.051) Data 0.002 (0.004) Loss 0.0310 (0.0348) Prec@1 96.000 (94.333) Prec@5 100.000 (99.800) +2022-11-14 15:58:42,900 Epoch: [287][150/500] Time 0.079 (0.052) Data 0.002 (0.004) Loss 0.0386 (0.0350) Prec@1 94.000 (94.312) Prec@5 100.000 (99.812) +2022-11-14 15:58:43,734 Epoch: [287][160/500] Time 0.081 (0.054) Data 0.002 (0.003) Loss 0.0370 (0.0351) Prec@1 93.000 (94.235) Prec@5 100.000 (99.824) +2022-11-14 15:58:44,479 Epoch: [287][170/500] Time 0.065 (0.055) Data 0.002 (0.003) Loss 0.0403 (0.0354) Prec@1 94.000 (94.222) Prec@5 100.000 (99.833) +2022-11-14 15:58:44,908 Epoch: [287][180/500] Time 0.043 (0.054) Data 0.002 (0.003) Loss 0.0160 (0.0344) Prec@1 98.000 (94.421) Prec@5 100.000 (99.842) +2022-11-14 15:58:45,332 Epoch: [287][190/500] Time 0.031 (0.053) Data 0.002 (0.003) Loss 0.0340 (0.0344) Prec@1 95.000 (94.450) Prec@5 100.000 (99.850) +2022-11-14 15:58:45,823 Epoch: [287][200/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0228 (0.0338) Prec@1 97.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 15:58:46,300 Epoch: [287][210/500] Time 0.041 (0.052) Data 0.002 (0.003) Loss 0.0286 (0.0336) Prec@1 97.000 (94.682) Prec@5 100.000 (99.864) +2022-11-14 15:58:46,722 Epoch: [287][220/500] Time 0.038 (0.051) Data 0.002 (0.003) Loss 0.0593 (0.0347) Prec@1 90.000 (94.478) Prec@5 100.000 (99.870) +2022-11-14 15:58:47,195 Epoch: [287][230/500] Time 0.039 (0.051) Data 0.002 (0.003) Loss 0.0236 (0.0342) Prec@1 97.000 (94.583) Prec@5 100.000 (99.875) +2022-11-14 15:58:47,674 Epoch: [287][240/500] Time 0.041 (0.051) Data 0.002 (0.003) Loss 0.0234 (0.0338) Prec@1 97.000 (94.680) Prec@5 100.000 (99.880) +2022-11-14 15:58:48,092 Epoch: [287][250/500] Time 0.040 (0.050) Data 0.002 (0.003) Loss 0.0356 (0.0339) Prec@1 94.000 (94.654) Prec@5 100.000 (99.885) +2022-11-14 15:58:48,533 Epoch: [287][260/500] Time 0.037 (0.050) Data 0.002 (0.003) Loss 0.0453 (0.0343) Prec@1 93.000 (94.593) Prec@5 97.000 (99.778) +2022-11-14 15:58:48,990 Epoch: [287][270/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0424 (0.0346) Prec@1 93.000 (94.536) Prec@5 100.000 (99.786) +2022-11-14 15:58:49,430 Epoch: [287][280/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0192 (0.0341) Prec@1 96.000 (94.586) Prec@5 100.000 (99.793) +2022-11-14 15:58:49,875 Epoch: [287][290/500] Time 0.039 (0.049) Data 0.002 (0.003) Loss 0.0233 (0.0337) Prec@1 97.000 (94.667) Prec@5 100.000 (99.800) +2022-11-14 15:58:50,339 Epoch: [287][300/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0377 (0.0338) Prec@1 92.000 (94.581) Prec@5 100.000 (99.806) +2022-11-14 15:58:50,773 Epoch: [287][310/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0240 (0.0335) Prec@1 96.000 (94.625) Prec@5 100.000 (99.812) +2022-11-14 15:58:51,265 Epoch: [287][320/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0203 (0.0331) Prec@1 97.000 (94.697) Prec@5 100.000 (99.818) +2022-11-14 15:58:51,674 Epoch: [287][330/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0302 (0.0330) Prec@1 95.000 (94.706) Prec@5 100.000 (99.824) +2022-11-14 15:58:52,129 Epoch: [287][340/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0432 (0.0333) Prec@1 91.000 (94.600) Prec@5 100.000 (99.829) +2022-11-14 15:58:52,594 Epoch: [287][350/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0500 (0.0338) Prec@1 92.000 (94.528) Prec@5 100.000 (99.833) +2022-11-14 15:58:53,075 Epoch: [287][360/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0115 (0.0332) Prec@1 98.000 (94.622) Prec@5 100.000 (99.838) +2022-11-14 15:58:53,513 Epoch: [287][370/500] Time 0.033 (0.047) Data 0.002 (0.003) Loss 0.0201 (0.0329) Prec@1 98.000 (94.711) Prec@5 100.000 (99.842) +2022-11-14 15:58:54,013 Epoch: [287][380/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0399 (0.0330) Prec@1 94.000 (94.692) Prec@5 99.000 (99.821) +2022-11-14 15:58:54,454 Epoch: [287][390/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0579 (0.0337) Prec@1 91.000 (94.600) Prec@5 100.000 (99.825) +2022-11-14 15:58:54,954 Epoch: [287][400/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.0266 (0.0335) Prec@1 96.000 (94.634) Prec@5 100.000 (99.829) +2022-11-14 15:58:55,431 Epoch: [287][410/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0280 (0.0334) Prec@1 94.000 (94.619) Prec@5 100.000 (99.833) +2022-11-14 15:58:55,886 Epoch: [287][420/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0454 (0.0336) Prec@1 92.000 (94.558) Prec@5 100.000 (99.837) +2022-11-14 15:58:56,349 Epoch: [287][430/500] Time 0.039 (0.046) Data 0.002 (0.003) Loss 0.0427 (0.0338) Prec@1 91.000 (94.477) Prec@5 100.000 (99.841) +2022-11-14 15:58:56,828 Epoch: [287][440/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0533 (0.0343) Prec@1 90.000 (94.378) Prec@5 100.000 (99.844) +2022-11-14 15:58:57,272 Epoch: [287][450/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0421 (0.0344) Prec@1 91.000 (94.304) Prec@5 100.000 (99.848) +2022-11-14 15:58:57,725 Epoch: [287][460/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0471 (0.0347) Prec@1 91.000 (94.234) Prec@5 100.000 (99.851) +2022-11-14 15:58:58,205 Epoch: [287][470/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0215 (0.0344) Prec@1 96.000 (94.271) Prec@5 100.000 (99.854) +2022-11-14 15:58:58,643 Epoch: [287][480/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0400 (0.0346) Prec@1 94.000 (94.265) Prec@5 100.000 (99.857) +2022-11-14 15:58:59,078 Epoch: [287][490/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0515 (0.0349) Prec@1 92.000 (94.220) Prec@5 99.000 (99.840) +2022-11-14 15:58:59,474 Epoch: [287][499/500] Time 0.029 (0.045) Data 0.002 (0.003) Loss 0.0233 (0.0347) Prec@1 95.000 (94.235) Prec@5 100.000 (99.843) +2022-11-14 15:58:59,817 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0680 (0.0680) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 15:58:59,827 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0705 (0.0692) Prec@1 88.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 15:58:59,837 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0682 (0.0689) Prec@1 89.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 15:58:59,850 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0801 (0.0717) Prec@1 88.000 (88.000) Prec@5 100.000 (99.750) +2022-11-14 15:58:59,862 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0702) Prec@1 88.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 15:58:59,875 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0465 (0.0663) Prec@1 92.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 15:58:59,886 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0656) Prec@1 91.000 (89.000) Prec@5 99.000 (99.571) +2022-11-14 15:58:59,899 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0673) Prec@1 86.000 (88.625) Prec@5 99.000 (99.500) +2022-11-14 15:58:59,911 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0687) Prec@1 88.000 (88.556) Prec@5 99.000 (99.444) +2022-11-14 15:58:59,925 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0693) Prec@1 88.000 (88.500) Prec@5 99.000 (99.400) +2022-11-14 15:58:59,939 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0558 (0.0681) Prec@1 92.000 (88.818) Prec@5 100.000 (99.455) +2022-11-14 15:58:59,954 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0692) Prec@1 90.000 (88.917) Prec@5 98.000 (99.333) +2022-11-14 15:58:59,970 Test: [12/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0530 (0.0679) Prec@1 90.000 (89.000) Prec@5 100.000 (99.385) +2022-11-14 15:58:59,986 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0679) Prec@1 89.000 (89.000) Prec@5 100.000 (99.429) +2022-11-14 15:59:00,002 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0685) Prec@1 88.000 (88.933) Prec@5 100.000 (99.467) +2022-11-14 15:59:00,017 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0580 (0.0678) Prec@1 90.000 (89.000) Prec@5 98.000 (99.375) +2022-11-14 15:59:00,032 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0428 (0.0663) Prec@1 94.000 (89.294) Prec@5 98.000 (99.294) +2022-11-14 15:59:00,045 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1031 (0.0684) Prec@1 84.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 15:59:00,059 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0689) Prec@1 87.000 (88.895) Prec@5 100.000 (99.368) +2022-11-14 15:59:00,073 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.0705) Prec@1 83.000 (88.600) Prec@5 97.000 (99.250) +2022-11-14 15:59:00,088 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0706) Prec@1 87.000 (88.524) Prec@5 99.000 (99.238) +2022-11-14 15:59:00,105 Test: [21/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0708) Prec@1 89.000 (88.545) Prec@5 99.000 (99.227) +2022-11-14 15:59:00,121 Test: [22/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0716) Prec@1 87.000 (88.478) Prec@5 97.000 (99.130) +2022-11-14 15:59:00,136 Test: [23/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0827 (0.0720) Prec@1 85.000 (88.333) Prec@5 100.000 (99.167) +2022-11-14 15:59:00,152 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.0730) Prec@1 86.000 (88.240) Prec@5 100.000 (99.200) +2022-11-14 15:59:00,167 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0735) Prec@1 85.000 (88.115) Prec@5 99.000 (99.192) +2022-11-14 15:59:00,183 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0533 (0.0727) Prec@1 91.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 15:59:00,199 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0725) Prec@1 90.000 (88.286) Prec@5 99.000 (99.214) +2022-11-14 15:59:00,213 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0724) Prec@1 90.000 (88.345) Prec@5 99.000 (99.207) +2022-11-14 15:59:00,229 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0721) Prec@1 90.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 15:59:00,243 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0721) Prec@1 87.000 (88.355) Prec@5 99.000 (99.194) +2022-11-14 15:59:00,260 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0719) Prec@1 89.000 (88.375) Prec@5 99.000 (99.188) +2022-11-14 15:59:00,272 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0717) Prec@1 90.000 (88.424) Prec@5 100.000 (99.212) +2022-11-14 15:59:00,285 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0722) Prec@1 85.000 (88.324) Prec@5 98.000 (99.176) +2022-11-14 15:59:00,301 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0958 (0.0729) Prec@1 85.000 (88.229) Prec@5 98.000 (99.143) +2022-11-14 15:59:00,317 Test: [35/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0729) Prec@1 88.000 (88.222) Prec@5 100.000 (99.167) +2022-11-14 15:59:00,334 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0728) Prec@1 91.000 (88.297) Prec@5 99.000 (99.162) +2022-11-14 15:59:00,351 Test: [37/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.0736) Prec@1 83.000 (88.158) Prec@5 100.000 (99.184) +2022-11-14 15:59:00,368 Test: [38/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0589 (0.0732) Prec@1 93.000 (88.282) Prec@5 99.000 (99.179) +2022-11-14 15:59:00,382 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0580 (0.0728) Prec@1 90.000 (88.325) Prec@5 100.000 (99.200) +2022-11-14 15:59:00,396 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0942 (0.0733) Prec@1 84.000 (88.220) Prec@5 98.000 (99.171) +2022-11-14 15:59:00,410 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0734) Prec@1 90.000 (88.262) Prec@5 99.000 (99.167) +2022-11-14 15:59:00,425 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0322 (0.0725) Prec@1 95.000 (88.419) Prec@5 100.000 (99.186) +2022-11-14 15:59:00,441 Test: [43/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0723) Prec@1 90.000 (88.455) Prec@5 100.000 (99.205) +2022-11-14 15:59:00,455 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0724) Prec@1 90.000 (88.489) Prec@5 99.000 (99.200) +2022-11-14 15:59:00,470 Test: [45/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0877 (0.0727) Prec@1 84.000 (88.391) Prec@5 100.000 (99.217) +2022-11-14 15:59:00,486 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0503 (0.0722) Prec@1 93.000 (88.489) Prec@5 100.000 (99.234) +2022-11-14 15:59:00,501 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1076 (0.0729) Prec@1 83.000 (88.375) Prec@5 97.000 (99.188) +2022-11-14 15:59:00,517 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0727) Prec@1 90.000 (88.408) Prec@5 100.000 (99.204) +2022-11-14 15:59:00,531 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0728) Prec@1 88.000 (88.400) Prec@5 100.000 (99.220) +2022-11-14 15:59:00,544 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0725) Prec@1 88.000 (88.392) Prec@5 100.000 (99.235) +2022-11-14 15:59:00,558 Test: [51/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0725) Prec@1 88.000 (88.385) Prec@5 100.000 (99.250) +2022-11-14 15:59:00,573 Test: [52/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0725) Prec@1 88.000 (88.377) Prec@5 99.000 (99.245) +2022-11-14 15:59:00,587 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0725) Prec@1 87.000 (88.352) Prec@5 100.000 (99.259) +2022-11-14 15:59:00,602 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0727) Prec@1 86.000 (88.309) Prec@5 100.000 (99.273) +2022-11-14 15:59:00,617 Test: [55/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0726) Prec@1 92.000 (88.375) Prec@5 99.000 (99.268) +2022-11-14 15:59:00,633 Test: [56/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0725) Prec@1 86.000 (88.333) Prec@5 100.000 (99.281) +2022-11-14 15:59:00,647 Test: [57/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0725) Prec@1 90.000 (88.362) Prec@5 100.000 (99.293) +2022-11-14 15:59:00,665 Test: [58/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.0727) Prec@1 85.000 (88.305) Prec@5 100.000 (99.305) +2022-11-14 15:59:00,678 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.0730) Prec@1 86.000 (88.267) Prec@5 100.000 (99.317) +2022-11-14 15:59:00,692 Test: [60/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0731) Prec@1 88.000 (88.262) Prec@5 99.000 (99.311) +2022-11-14 15:59:00,707 Test: [61/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0550 (0.0728) Prec@1 90.000 (88.290) Prec@5 99.000 (99.306) +2022-11-14 15:59:00,722 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0727) Prec@1 89.000 (88.302) Prec@5 100.000 (99.317) +2022-11-14 15:59:00,740 Test: [63/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0330 (0.0721) Prec@1 94.000 (88.391) Prec@5 100.000 (99.328) +2022-11-14 15:59:00,754 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.0723) Prec@1 86.000 (88.354) Prec@5 100.000 (99.338) +2022-11-14 15:59:00,767 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0726) Prec@1 87.000 (88.333) Prec@5 98.000 (99.318) +2022-11-14 15:59:00,780 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0527 (0.0723) Prec@1 90.000 (88.358) Prec@5 100.000 (99.328) +2022-11-14 15:59:00,792 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0723) Prec@1 89.000 (88.368) Prec@5 100.000 (99.338) +2022-11-14 15:59:00,810 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0723) Prec@1 87.000 (88.348) Prec@5 99.000 (99.333) +2022-11-14 15:59:00,828 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0725) Prec@1 89.000 (88.357) Prec@5 100.000 (99.343) +2022-11-14 15:59:00,844 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0726) Prec@1 90.000 (88.380) Prec@5 99.000 (99.338) +2022-11-14 15:59:00,858 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0626 (0.0724) Prec@1 91.000 (88.417) Prec@5 99.000 (99.333) +2022-11-14 15:59:00,875 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0517 (0.0721) Prec@1 90.000 (88.438) Prec@5 100.000 (99.342) +2022-11-14 15:59:00,889 Test: [73/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0421 (0.0717) Prec@1 94.000 (88.514) Prec@5 100.000 (99.351) +2022-11-14 15:59:00,904 Test: [74/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0719) Prec@1 85.000 (88.467) Prec@5 99.000 (99.347) +2022-11-14 15:59:00,919 Test: [75/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0460 (0.0716) Prec@1 93.000 (88.526) Prec@5 99.000 (99.342) +2022-11-14 15:59:00,934 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0715) Prec@1 88.000 (88.519) Prec@5 100.000 (99.351) +2022-11-14 15:59:00,948 Test: [77/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.0717) Prec@1 87.000 (88.500) Prec@5 99.000 (99.346) +2022-11-14 15:59:00,963 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0716) Prec@1 87.000 (88.481) Prec@5 100.000 (99.354) +2022-11-14 15:59:00,978 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0716) Prec@1 86.000 (88.450) Prec@5 99.000 (99.350) +2022-11-14 15:59:00,994 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0717) Prec@1 88.000 (88.444) Prec@5 100.000 (99.358) +2022-11-14 15:59:01,010 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0720) Prec@1 83.000 (88.378) Prec@5 99.000 (99.354) +2022-11-14 15:59:01,028 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.0723) Prec@1 83.000 (88.313) Prec@5 98.000 (99.337) +2022-11-14 15:59:01,045 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0723) Prec@1 88.000 (88.310) Prec@5 98.000 (99.321) +2022-11-14 15:59:01,058 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0725) Prec@1 83.000 (88.247) Prec@5 100.000 (99.329) +2022-11-14 15:59:01,073 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.0726) Prec@1 87.000 (88.233) Prec@5 100.000 (99.337) +2022-11-14 15:59:01,086 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0727) Prec@1 86.000 (88.207) Prec@5 100.000 (99.345) +2022-11-14 15:59:01,102 Test: [87/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0728) Prec@1 88.000 (88.205) Prec@5 99.000 (99.341) +2022-11-14 15:59:01,120 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0726) Prec@1 91.000 (88.236) Prec@5 100.000 (99.348) +2022-11-14 15:59:01,136 Test: [89/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0726) Prec@1 88.000 (88.233) Prec@5 100.000 (99.356) +2022-11-14 15:59:01,150 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0397 (0.0723) Prec@1 94.000 (88.297) Prec@5 100.000 (99.363) +2022-11-14 15:59:01,167 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0721) Prec@1 91.000 (88.326) Prec@5 100.000 (99.370) +2022-11-14 15:59:01,181 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0721) Prec@1 89.000 (88.333) Prec@5 100.000 (99.376) +2022-11-14 15:59:01,196 Test: [93/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0720) Prec@1 89.000 (88.340) Prec@5 100.000 (99.383) +2022-11-14 15:59:01,212 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0721) Prec@1 83.000 (88.284) Prec@5 100.000 (99.389) +2022-11-14 15:59:01,227 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0609 (0.0720) Prec@1 91.000 (88.312) Prec@5 99.000 (99.385) +2022-11-14 15:59:01,244 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0718) Prec@1 91.000 (88.340) Prec@5 98.000 (99.371) +2022-11-14 15:59:01,260 Test: [97/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0819 (0.0719) Prec@1 85.000 (88.306) Prec@5 99.000 (99.367) +2022-11-14 15:59:01,275 Test: [98/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0871 (0.0721) Prec@1 87.000 (88.293) Prec@5 100.000 (99.374) +2022-11-14 15:59:01,290 Test: [99/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0720) Prec@1 89.000 (88.300) Prec@5 100.000 (99.380) +2022-11-14 15:59:01,392 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:59:01,785 Epoch: [288][0/500] Time 0.029 (0.029) Data 0.289 (0.289) Loss 0.0453 (0.0453) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:02,212 Epoch: [288][10/500] Time 0.054 (0.036) Data 0.002 (0.028) Loss 0.0179 (0.0316) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 15:59:02,653 Epoch: [288][20/500] Time 0.043 (0.038) Data 0.003 (0.016) Loss 0.0179 (0.0270) Prec@1 98.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 15:59:03,129 Epoch: [288][30/500] Time 0.056 (0.039) Data 0.002 (0.012) Loss 0.0136 (0.0237) Prec@1 98.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 15:59:03,587 Epoch: [288][40/500] Time 0.038 (0.039) Data 0.003 (0.009) Loss 0.0470 (0.0284) Prec@1 90.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:04,029 Epoch: [288][50/500] Time 0.038 (0.039) Data 0.002 (0.008) Loss 0.0283 (0.0283) Prec@1 96.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 15:59:04,468 Epoch: [288][60/500] Time 0.039 (0.039) Data 0.002 (0.007) Loss 0.0095 (0.0256) Prec@1 98.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 15:59:04,917 Epoch: [288][70/500] Time 0.047 (0.039) Data 0.002 (0.006) Loss 0.0343 (0.0267) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 15:59:05,377 Epoch: [288][80/500] Time 0.044 (0.040) Data 0.002 (0.006) Loss 0.0177 (0.0257) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 15:59:05,822 Epoch: [288][90/500] Time 0.042 (0.040) Data 0.002 (0.005) Loss 0.0528 (0.0284) Prec@1 91.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 15:59:06,288 Epoch: [288][100/500] Time 0.045 (0.040) Data 0.002 (0.005) Loss 0.0811 (0.0332) Prec@1 85.000 (94.273) Prec@5 98.000 (99.818) +2022-11-14 15:59:06,724 Epoch: [288][110/500] Time 0.043 (0.040) Data 0.002 (0.005) Loss 0.0118 (0.0314) Prec@1 99.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 15:59:07,209 Epoch: [288][120/500] Time 0.052 (0.040) Data 0.002 (0.005) Loss 0.0391 (0.0320) Prec@1 92.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 15:59:08,059 Epoch: [288][130/500] Time 0.085 (0.043) Data 0.002 (0.004) Loss 0.0197 (0.0312) Prec@1 98.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 15:59:08,894 Epoch: [288][140/500] Time 0.093 (0.045) Data 0.002 (0.004) Loss 0.0265 (0.0308) Prec@1 96.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 15:59:09,673 Epoch: [288][150/500] Time 0.064 (0.046) Data 0.002 (0.004) Loss 0.0328 (0.0310) Prec@1 95.000 (94.812) Prec@5 100.000 (99.875) +2022-11-14 15:59:10,511 Epoch: [288][160/500] Time 0.081 (0.048) Data 0.002 (0.004) Loss 0.0355 (0.0312) Prec@1 94.000 (94.765) Prec@5 100.000 (99.882) +2022-11-14 15:59:11,321 Epoch: [288][170/500] Time 0.084 (0.050) Data 0.002 (0.004) Loss 0.0318 (0.0313) Prec@1 96.000 (94.833) Prec@5 100.000 (99.889) +2022-11-14 15:59:12,133 Epoch: [288][180/500] Time 0.072 (0.051) Data 0.002 (0.004) Loss 0.0487 (0.0322) Prec@1 91.000 (94.632) Prec@5 100.000 (99.895) +2022-11-14 15:59:12,963 Epoch: [288][190/500] Time 0.073 (0.052) Data 0.002 (0.004) Loss 0.0400 (0.0326) Prec@1 94.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 15:59:13,732 Epoch: [288][200/500] Time 0.066 (0.053) Data 0.002 (0.004) Loss 0.0374 (0.0328) Prec@1 94.000 (94.571) Prec@5 100.000 (99.905) +2022-11-14 15:59:14,462 Epoch: [288][210/500] Time 0.080 (0.054) Data 0.002 (0.004) Loss 0.0290 (0.0326) Prec@1 95.000 (94.591) Prec@5 100.000 (99.909) +2022-11-14 15:59:15,275 Epoch: [288][220/500] Time 0.082 (0.054) Data 0.003 (0.003) Loss 0.0376 (0.0328) Prec@1 92.000 (94.478) Prec@5 99.000 (99.870) +2022-11-14 15:59:16,080 Epoch: [288][230/500] Time 0.082 (0.055) Data 0.002 (0.003) Loss 0.0219 (0.0324) Prec@1 96.000 (94.542) Prec@5 100.000 (99.875) +2022-11-14 15:59:16,849 Epoch: [288][240/500] Time 0.077 (0.056) Data 0.002 (0.003) Loss 0.0612 (0.0335) Prec@1 89.000 (94.320) Prec@5 99.000 (99.840) +2022-11-14 15:59:17,680 Epoch: [288][250/500] Time 0.064 (0.057) Data 0.002 (0.003) Loss 0.0336 (0.0335) Prec@1 95.000 (94.346) Prec@5 100.000 (99.846) +2022-11-14 15:59:18,516 Epoch: [288][260/500] Time 0.075 (0.057) Data 0.002 (0.003) Loss 0.0321 (0.0335) Prec@1 95.000 (94.370) Prec@5 100.000 (99.852) +2022-11-14 15:59:19,330 Epoch: [288][270/500] Time 0.076 (0.058) Data 0.002 (0.003) Loss 0.0346 (0.0335) Prec@1 96.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 15:59:19,886 Epoch: [288][280/500] Time 0.043 (0.058) Data 0.002 (0.003) Loss 0.0258 (0.0333) Prec@1 95.000 (94.448) Prec@5 100.000 (99.862) +2022-11-14 15:59:20,378 Epoch: [288][290/500] Time 0.048 (0.057) Data 0.002 (0.003) Loss 0.0047 (0.0323) Prec@1 100.000 (94.633) Prec@5 100.000 (99.867) +2022-11-14 15:59:20,877 Epoch: [288][300/500] Time 0.042 (0.057) Data 0.002 (0.003) Loss 0.0435 (0.0327) Prec@1 92.000 (94.548) Prec@5 100.000 (99.871) +2022-11-14 15:59:21,362 Epoch: [288][310/500] Time 0.046 (0.056) Data 0.002 (0.003) Loss 0.0365 (0.0328) Prec@1 92.000 (94.469) Prec@5 100.000 (99.875) +2022-11-14 15:59:21,858 Epoch: [288][320/500] Time 0.042 (0.056) Data 0.002 (0.003) Loss 0.0246 (0.0325) Prec@1 97.000 (94.545) Prec@5 99.000 (99.848) +2022-11-14 15:59:22,350 Epoch: [288][330/500] Time 0.045 (0.056) Data 0.002 (0.003) Loss 0.0540 (0.0332) Prec@1 90.000 (94.412) Prec@5 99.000 (99.824) +2022-11-14 15:59:22,837 Epoch: [288][340/500] Time 0.041 (0.055) Data 0.002 (0.003) Loss 0.0446 (0.0335) Prec@1 93.000 (94.371) Prec@5 100.000 (99.829) +2022-11-14 15:59:23,335 Epoch: [288][350/500] Time 0.045 (0.055) Data 0.002 (0.003) Loss 0.0276 (0.0333) Prec@1 95.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 15:59:23,833 Epoch: [288][360/500] Time 0.048 (0.055) Data 0.002 (0.003) Loss 0.0343 (0.0334) Prec@1 96.000 (94.432) Prec@5 100.000 (99.838) +2022-11-14 15:59:24,337 Epoch: [288][370/500] Time 0.042 (0.054) Data 0.002 (0.003) Loss 0.0439 (0.0336) Prec@1 94.000 (94.421) Prec@5 100.000 (99.842) +2022-11-14 15:59:24,808 Epoch: [288][380/500] Time 0.040 (0.054) Data 0.002 (0.003) Loss 0.0382 (0.0338) Prec@1 96.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 15:59:25,331 Epoch: [288][390/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0101 (0.0332) Prec@1 99.000 (94.575) Prec@5 99.000 (99.825) +2022-11-14 15:59:25,827 Epoch: [288][400/500] Time 0.046 (0.054) Data 0.002 (0.003) Loss 0.0230 (0.0329) Prec@1 95.000 (94.585) Prec@5 100.000 (99.829) +2022-11-14 15:59:26,342 Epoch: [288][410/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0590 (0.0335) Prec@1 91.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 15:59:26,837 Epoch: [288][420/500] Time 0.047 (0.053) Data 0.002 (0.003) Loss 0.0257 (0.0334) Prec@1 95.000 (94.512) Prec@5 100.000 (99.837) +2022-11-14 15:59:27,328 Epoch: [288][430/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0283 (0.0332) Prec@1 95.000 (94.523) Prec@5 100.000 (99.841) +2022-11-14 15:59:27,840 Epoch: [288][440/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0272 (0.0331) Prec@1 96.000 (94.556) Prec@5 100.000 (99.844) +2022-11-14 15:59:28,361 Epoch: [288][450/500] Time 0.051 (0.053) Data 0.003 (0.003) Loss 0.0482 (0.0334) Prec@1 92.000 (94.500) Prec@5 99.000 (99.826) +2022-11-14 15:59:28,860 Epoch: [288][460/500] Time 0.047 (0.052) Data 0.002 (0.003) Loss 0.0375 (0.0335) Prec@1 93.000 (94.468) Prec@5 100.000 (99.830) +2022-11-14 15:59:29,364 Epoch: [288][470/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0306 (0.0335) Prec@1 93.000 (94.438) Prec@5 100.000 (99.833) +2022-11-14 15:59:29,858 Epoch: [288][480/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0258 (0.0333) Prec@1 95.000 (94.449) Prec@5 99.000 (99.816) +2022-11-14 15:59:30,359 Epoch: [288][490/500] Time 0.048 (0.052) Data 0.002 (0.003) Loss 0.0475 (0.0336) Prec@1 93.000 (94.420) Prec@5 100.000 (99.820) +2022-11-14 15:59:30,810 Epoch: [288][499/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0448 (0.0338) Prec@1 93.000 (94.392) Prec@5 100.000 (99.824) +2022-11-14 15:59:31,129 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0659 (0.0659) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:31,139 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0724 (0.0692) Prec@1 89.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 15:59:31,148 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0708) Prec@1 87.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 15:59:31,162 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0744) Prec@1 84.000 (86.750) Prec@5 100.000 (99.750) +2022-11-14 15:59:31,172 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0759) Prec@1 85.000 (86.400) Prec@5 98.000 (99.400) +2022-11-14 15:59:31,181 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0386 (0.0697) Prec@1 91.000 (87.167) Prec@5 100.000 (99.500) +2022-11-14 15:59:31,192 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0697) Prec@1 89.000 (87.429) Prec@5 100.000 (99.571) +2022-11-14 15:59:31,204 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0723) Prec@1 85.000 (87.125) Prec@5 98.000 (99.375) +2022-11-14 15:59:31,213 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0732) Prec@1 87.000 (87.111) Prec@5 100.000 (99.444) +2022-11-14 15:59:31,222 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0737) Prec@1 89.000 (87.300) Prec@5 99.000 (99.400) +2022-11-14 15:59:31,233 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0730) Prec@1 88.000 (87.364) Prec@5 99.000 (99.364) +2022-11-14 15:59:31,242 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0738) Prec@1 86.000 (87.250) Prec@5 100.000 (99.417) +2022-11-14 15:59:31,254 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0740) Prec@1 88.000 (87.308) Prec@5 99.000 (99.385) +2022-11-14 15:59:31,267 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0726) Prec@1 92.000 (87.643) Prec@5 99.000 (99.357) +2022-11-14 15:59:31,278 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0729) Prec@1 85.000 (87.467) Prec@5 99.000 (99.333) +2022-11-14 15:59:31,289 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0725) Prec@1 88.000 (87.500) Prec@5 99.000 (99.312) +2022-11-14 15:59:31,299 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0720) Prec@1 90.000 (87.647) Prec@5 99.000 (99.294) +2022-11-14 15:59:31,309 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0731) Prec@1 86.000 (87.556) Prec@5 100.000 (99.333) +2022-11-14 15:59:31,320 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0740) Prec@1 84.000 (87.368) Prec@5 98.000 (99.263) +2022-11-14 15:59:31,330 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0750) Prec@1 84.000 (87.200) Prec@5 98.000 (99.200) +2022-11-14 15:59:31,339 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0750) Prec@1 87.000 (87.190) Prec@5 99.000 (99.190) +2022-11-14 15:59:31,349 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0754) Prec@1 86.000 (87.136) Prec@5 99.000 (99.182) +2022-11-14 15:59:31,360 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1100 (0.0769) Prec@1 85.000 (87.043) Prec@5 98.000 (99.130) +2022-11-14 15:59:31,372 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0768) Prec@1 88.000 (87.083) Prec@5 100.000 (99.167) +2022-11-14 15:59:31,382 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0769) Prec@1 87.000 (87.080) Prec@5 100.000 (99.200) +2022-11-14 15:59:31,394 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0777) Prec@1 85.000 (87.000) Prec@5 99.000 (99.192) +2022-11-14 15:59:31,406 Test: [26/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0767) Prec@1 94.000 (87.259) Prec@5 100.000 (99.222) +2022-11-14 15:59:31,418 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0763) Prec@1 88.000 (87.286) Prec@5 100.000 (99.250) +2022-11-14 15:59:31,433 Test: [28/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0759) Prec@1 89.000 (87.345) Prec@5 98.000 (99.207) +2022-11-14 15:59:31,446 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0759) Prec@1 90.000 (87.433) Prec@5 100.000 (99.233) +2022-11-14 15:59:31,459 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0755) Prec@1 89.000 (87.484) Prec@5 99.000 (99.226) +2022-11-14 15:59:31,473 Test: [31/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0753) Prec@1 90.000 (87.562) Prec@5 100.000 (99.250) +2022-11-14 15:59:31,487 Test: [32/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0750) Prec@1 90.000 (87.636) Prec@5 100.000 (99.273) +2022-11-14 15:59:31,500 Test: [33/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0753) Prec@1 84.000 (87.529) Prec@5 100.000 (99.294) +2022-11-14 15:59:31,513 Test: [34/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0754) Prec@1 89.000 (87.571) Prec@5 99.000 (99.286) +2022-11-14 15:59:31,524 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0751) Prec@1 90.000 (87.639) Prec@5 100.000 (99.306) +2022-11-14 15:59:31,536 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0751) Prec@1 89.000 (87.676) Prec@5 99.000 (99.297) +2022-11-14 15:59:31,548 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0759) Prec@1 84.000 (87.579) Prec@5 99.000 (99.289) +2022-11-14 15:59:31,558 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0757) Prec@1 90.000 (87.641) Prec@5 99.000 (99.282) +2022-11-14 15:59:31,570 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0753) Prec@1 90.000 (87.700) Prec@5 99.000 (99.275) +2022-11-14 15:59:31,581 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1198 (0.0763) Prec@1 84.000 (87.610) Prec@5 97.000 (99.220) +2022-11-14 15:59:31,591 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0765) Prec@1 87.000 (87.595) Prec@5 100.000 (99.238) +2022-11-14 15:59:31,603 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0448 (0.0757) Prec@1 94.000 (87.744) Prec@5 99.000 (99.233) +2022-11-14 15:59:31,614 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0758) Prec@1 89.000 (87.773) Prec@5 98.000 (99.205) +2022-11-14 15:59:31,626 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0757) Prec@1 89.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 15:59:31,637 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1179 (0.0766) Prec@1 82.000 (87.674) Prec@5 98.000 (99.174) +2022-11-14 15:59:31,647 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0763) Prec@1 90.000 (87.723) Prec@5 99.000 (99.170) +2022-11-14 15:59:31,657 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0771) Prec@1 81.000 (87.583) Prec@5 99.000 (99.167) +2022-11-14 15:59:31,667 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0765) Prec@1 92.000 (87.673) Prec@5 100.000 (99.184) +2022-11-14 15:59:31,678 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0771) Prec@1 82.000 (87.560) Prec@5 100.000 (99.200) +2022-11-14 15:59:31,688 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0771) Prec@1 85.000 (87.510) Prec@5 100.000 (99.216) +2022-11-14 15:59:31,698 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0774) Prec@1 86.000 (87.481) Prec@5 99.000 (99.212) +2022-11-14 15:59:31,709 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0777) Prec@1 85.000 (87.434) Prec@5 100.000 (99.226) +2022-11-14 15:59:31,722 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0777) Prec@1 86.000 (87.407) Prec@5 99.000 (99.222) +2022-11-14 15:59:31,732 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0783) Prec@1 83.000 (87.327) Prec@5 100.000 (99.236) +2022-11-14 15:59:31,742 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0782) Prec@1 89.000 (87.357) Prec@5 99.000 (99.232) +2022-11-14 15:59:31,753 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0780) Prec@1 90.000 (87.404) Prec@5 100.000 (99.246) +2022-11-14 15:59:31,764 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0779) Prec@1 91.000 (87.466) Prec@5 100.000 (99.259) +2022-11-14 15:59:31,775 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0783) Prec@1 84.000 (87.407) Prec@5 100.000 (99.271) +2022-11-14 15:59:31,788 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0785) Prec@1 84.000 (87.350) Prec@5 99.000 (99.267) +2022-11-14 15:59:31,798 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0787) Prec@1 86.000 (87.328) Prec@5 100.000 (99.279) +2022-11-14 15:59:31,809 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0782) Prec@1 92.000 (87.403) Prec@5 99.000 (99.274) +2022-11-14 15:59:31,821 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0779) Prec@1 91.000 (87.460) Prec@5 100.000 (99.286) +2022-11-14 15:59:31,833 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0774) Prec@1 91.000 (87.516) Prec@5 100.000 (99.297) +2022-11-14 15:59:31,845 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0775) Prec@1 85.000 (87.477) Prec@5 100.000 (99.308) +2022-11-14 15:59:31,855 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0774) Prec@1 90.000 (87.515) Prec@5 100.000 (99.318) +2022-11-14 15:59:31,865 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0302 (0.0767) Prec@1 95.000 (87.627) Prec@5 100.000 (99.328) +2022-11-14 15:59:31,874 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0766) Prec@1 91.000 (87.676) Prec@5 99.000 (99.324) +2022-11-14 15:59:31,885 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0764) Prec@1 93.000 (87.754) Prec@5 99.000 (99.319) +2022-11-14 15:59:31,895 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0765) Prec@1 86.000 (87.729) Prec@5 99.000 (99.314) +2022-11-14 15:59:31,907 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0764) Prec@1 88.000 (87.732) Prec@5 99.000 (99.310) +2022-11-14 15:59:31,920 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0764) Prec@1 88.000 (87.736) Prec@5 100.000 (99.319) +2022-11-14 15:59:31,930 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0760) Prec@1 93.000 (87.808) Prec@5 100.000 (99.329) +2022-11-14 15:59:31,941 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0504 (0.0756) Prec@1 92.000 (87.865) Prec@5 100.000 (99.338) +2022-11-14 15:59:31,952 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0758) Prec@1 84.000 (87.813) Prec@5 100.000 (99.347) +2022-11-14 15:59:31,962 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0757) Prec@1 89.000 (87.829) Prec@5 100.000 (99.355) +2022-11-14 15:59:31,973 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0757) Prec@1 86.000 (87.805) Prec@5 98.000 (99.338) +2022-11-14 15:59:31,983 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0760) Prec@1 82.000 (87.731) Prec@5 99.000 (99.333) +2022-11-14 15:59:31,994 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0762) Prec@1 86.000 (87.709) Prec@5 100.000 (99.342) +2022-11-14 15:59:32,005 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0763) Prec@1 84.000 (87.662) Prec@5 99.000 (99.338) +2022-11-14 15:59:32,016 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0763) Prec@1 86.000 (87.642) Prec@5 98.000 (99.321) +2022-11-14 15:59:32,027 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0765) Prec@1 86.000 (87.622) Prec@5 99.000 (99.317) +2022-11-14 15:59:32,038 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0765) Prec@1 84.000 (87.578) Prec@5 99.000 (99.313) +2022-11-14 15:59:32,049 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0765) Prec@1 87.000 (87.571) Prec@5 99.000 (99.310) +2022-11-14 15:59:32,060 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1117 (0.0769) Prec@1 82.000 (87.506) Prec@5 97.000 (99.282) +2022-11-14 15:59:32,072 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0770) Prec@1 86.000 (87.488) Prec@5 100.000 (99.291) +2022-11-14 15:59:32,082 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0771) Prec@1 85.000 (87.460) Prec@5 99.000 (99.287) +2022-11-14 15:59:32,093 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0773) Prec@1 85.000 (87.432) Prec@5 98.000 (99.273) +2022-11-14 15:59:32,103 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0770) Prec@1 94.000 (87.506) Prec@5 100.000 (99.281) +2022-11-14 15:59:32,115 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0768) Prec@1 92.000 (87.556) Prec@5 100.000 (99.289) +2022-11-14 15:59:32,126 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0357 (0.0763) Prec@1 93.000 (87.615) Prec@5 100.000 (99.297) +2022-11-14 15:59:32,139 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0437 (0.0759) Prec@1 93.000 (87.674) Prec@5 100.000 (99.304) +2022-11-14 15:59:32,154 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0761) Prec@1 85.000 (87.645) Prec@5 100.000 (99.312) +2022-11-14 15:59:32,167 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0761) Prec@1 90.000 (87.670) Prec@5 99.000 (99.309) +2022-11-14 15:59:32,180 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0764) Prec@1 84.000 (87.632) Prec@5 98.000 (99.295) +2022-11-14 15:59:32,196 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0762) Prec@1 91.000 (87.667) Prec@5 99.000 (99.292) +2022-11-14 15:59:32,211 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0368 (0.0758) Prec@1 95.000 (87.742) Prec@5 98.000 (99.278) +2022-11-14 15:59:32,225 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0760) Prec@1 84.000 (87.704) Prec@5 99.000 (99.276) +2022-11-14 15:59:32,242 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0761) Prec@1 87.000 (87.697) Prec@5 98.000 (99.263) +2022-11-14 15:59:32,259 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0760) Prec@1 90.000 (87.720) Prec@5 99.000 (99.260) +2022-11-14 15:59:32,321 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:59:32,662 Epoch: [289][0/500] Time 0.028 (0.028) Data 0.246 (0.246) Loss 0.0396 (0.0396) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:33,085 Epoch: [289][10/500] Time 0.046 (0.037) Data 0.002 (0.024) Loss 0.0448 (0.0422) Prec@1 93.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 15:59:33,557 Epoch: [289][20/500] Time 0.051 (0.039) Data 0.002 (0.014) Loss 0.0265 (0.0369) Prec@1 95.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 15:59:34,056 Epoch: [289][30/500] Time 0.059 (0.041) Data 0.003 (0.010) Loss 0.0507 (0.0404) Prec@1 93.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 15:59:34,521 Epoch: [289][40/500] Time 0.047 (0.041) Data 0.002 (0.008) Loss 0.0443 (0.0412) Prec@1 94.000 (93.400) Prec@5 99.000 (99.800) +2022-11-14 15:59:34,995 Epoch: [289][50/500] Time 0.044 (0.041) Data 0.002 (0.007) Loss 0.0257 (0.0386) Prec@1 97.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 15:59:35,479 Epoch: [289][60/500] Time 0.048 (0.042) Data 0.002 (0.006) Loss 0.0191 (0.0358) Prec@1 97.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 15:59:35,934 Epoch: [289][70/500] Time 0.043 (0.042) Data 0.002 (0.006) Loss 0.0215 (0.0340) Prec@1 97.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 15:59:36,431 Epoch: [289][80/500] Time 0.044 (0.042) Data 0.002 (0.005) Loss 0.0379 (0.0344) Prec@1 93.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 15:59:36,911 Epoch: [289][90/500] Time 0.049 (0.042) Data 0.002 (0.005) Loss 0.0225 (0.0332) Prec@1 95.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 15:59:37,380 Epoch: [289][100/500] Time 0.050 (0.042) Data 0.003 (0.005) Loss 0.0218 (0.0322) Prec@1 96.000 (94.727) Prec@5 100.000 (99.909) +2022-11-14 15:59:37,865 Epoch: [289][110/500] Time 0.047 (0.042) Data 0.002 (0.004) Loss 0.0340 (0.0323) Prec@1 96.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 15:59:38,336 Epoch: [289][120/500] Time 0.049 (0.042) Data 0.002 (0.004) Loss 0.0220 (0.0316) Prec@1 97.000 (95.000) Prec@5 100.000 (99.923) +2022-11-14 15:59:38,895 Epoch: [289][130/500] Time 0.033 (0.043) Data 0.002 (0.004) Loss 0.0284 (0.0313) Prec@1 95.000 (95.000) Prec@5 100.000 (99.929) +2022-11-14 15:59:39,384 Epoch: [289][140/500] Time 0.040 (0.043) Data 0.002 (0.004) Loss 0.0277 (0.0311) Prec@1 95.000 (95.000) Prec@5 100.000 (99.933) +2022-11-14 15:59:39,872 Epoch: [289][150/500] Time 0.042 (0.043) Data 0.002 (0.004) Loss 0.0351 (0.0313) Prec@1 93.000 (94.875) Prec@5 100.000 (99.938) +2022-11-14 15:59:40,355 Epoch: [289][160/500] Time 0.040 (0.043) Data 0.002 (0.004) Loss 0.0356 (0.0316) Prec@1 94.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 15:59:40,823 Epoch: [289][170/500] Time 0.046 (0.043) Data 0.002 (0.004) Loss 0.0172 (0.0308) Prec@1 97.000 (94.944) Prec@5 100.000 (99.944) +2022-11-14 15:59:41,301 Epoch: [289][180/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0377 (0.0312) Prec@1 93.000 (94.842) Prec@5 100.000 (99.947) +2022-11-14 15:59:41,774 Epoch: [289][190/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0226 (0.0307) Prec@1 97.000 (94.950) Prec@5 100.000 (99.950) +2022-11-14 15:59:42,260 Epoch: [289][200/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0185 (0.0301) Prec@1 98.000 (95.095) Prec@5 100.000 (99.952) +2022-11-14 15:59:42,754 Epoch: [289][210/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0308 (0.0302) Prec@1 95.000 (95.091) Prec@5 100.000 (99.955) +2022-11-14 15:59:43,246 Epoch: [289][220/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0317 (0.0302) Prec@1 95.000 (95.087) Prec@5 100.000 (99.957) +2022-11-14 15:59:43,741 Epoch: [289][230/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0259 (0.0301) Prec@1 97.000 (95.167) Prec@5 100.000 (99.958) +2022-11-14 15:59:44,205 Epoch: [289][240/500] Time 0.045 (0.043) Data 0.003 (0.003) Loss 0.0319 (0.0301) Prec@1 94.000 (95.120) Prec@5 100.000 (99.960) +2022-11-14 15:59:44,683 Epoch: [289][250/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0305 (0.0301) Prec@1 96.000 (95.154) Prec@5 100.000 (99.962) +2022-11-14 15:59:45,171 Epoch: [289][260/500] Time 0.044 (0.043) Data 0.003 (0.003) Loss 0.0310 (0.0302) Prec@1 93.000 (95.074) Prec@5 100.000 (99.963) +2022-11-14 15:59:45,656 Epoch: [289][270/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0519 (0.0310) Prec@1 90.000 (94.893) Prec@5 100.000 (99.964) +2022-11-14 15:59:46,128 Epoch: [289][280/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0262 (0.0308) Prec@1 94.000 (94.862) Prec@5 100.000 (99.966) +2022-11-14 15:59:46,640 Epoch: [289][290/500] Time 0.056 (0.043) Data 0.002 (0.003) Loss 0.0470 (0.0313) Prec@1 91.000 (94.733) Prec@5 100.000 (99.967) +2022-11-14 15:59:47,125 Epoch: [289][300/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0320 (0.0314) Prec@1 92.000 (94.645) Prec@5 100.000 (99.968) +2022-11-14 15:59:47,658 Epoch: [289][310/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0437 (0.0317) Prec@1 93.000 (94.594) Prec@5 99.000 (99.938) +2022-11-14 15:59:48,118 Epoch: [289][320/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0317 (0.0317) Prec@1 94.000 (94.576) Prec@5 100.000 (99.939) +2022-11-14 15:59:48,604 Epoch: [289][330/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0164 (0.0313) Prec@1 98.000 (94.676) Prec@5 100.000 (99.941) +2022-11-14 15:59:49,089 Epoch: [289][340/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0293 (0.0312) Prec@1 95.000 (94.686) Prec@5 100.000 (99.943) +2022-11-14 15:59:49,571 Epoch: [289][350/500] Time 0.042 (0.043) Data 0.003 (0.003) Loss 0.0308 (0.0312) Prec@1 94.000 (94.667) Prec@5 100.000 (99.944) +2022-11-14 15:59:50,035 Epoch: [289][360/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0189 (0.0309) Prec@1 96.000 (94.703) Prec@5 100.000 (99.946) +2022-11-14 15:59:50,526 Epoch: [289][370/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0388 (0.0311) Prec@1 93.000 (94.658) Prec@5 99.000 (99.921) +2022-11-14 15:59:51,030 Epoch: [289][380/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0333 (0.0311) Prec@1 94.000 (94.641) Prec@5 100.000 (99.923) +2022-11-14 15:59:51,508 Epoch: [289][390/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0285 (0.0311) Prec@1 95.000 (94.650) Prec@5 100.000 (99.925) +2022-11-14 15:59:52,001 Epoch: [289][400/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0193 (0.0308) Prec@1 98.000 (94.732) Prec@5 100.000 (99.927) +2022-11-14 15:59:52,501 Epoch: [289][410/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0404 (0.0310) Prec@1 94.000 (94.714) Prec@5 98.000 (99.881) +2022-11-14 15:59:52,977 Epoch: [289][420/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0420 (0.0313) Prec@1 93.000 (94.674) Prec@5 100.000 (99.884) +2022-11-14 15:59:53,461 Epoch: [289][430/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0483 (0.0317) Prec@1 92.000 (94.614) Prec@5 100.000 (99.886) +2022-11-14 15:59:53,951 Epoch: [289][440/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0234 (0.0315) Prec@1 97.000 (94.667) Prec@5 100.000 (99.889) +2022-11-14 15:59:54,455 Epoch: [289][450/500] Time 0.062 (0.043) Data 0.003 (0.003) Loss 0.0369 (0.0316) Prec@1 95.000 (94.674) Prec@5 100.000 (99.891) +2022-11-14 15:59:54,952 Epoch: [289][460/500] Time 0.051 (0.043) Data 0.003 (0.003) Loss 0.0365 (0.0317) Prec@1 94.000 (94.660) Prec@5 100.000 (99.894) +2022-11-14 15:59:55,434 Epoch: [289][470/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0412 (0.0319) Prec@1 94.000 (94.646) Prec@5 100.000 (99.896) +2022-11-14 15:59:55,954 Epoch: [289][480/500] Time 0.061 (0.043) Data 0.002 (0.003) Loss 0.0278 (0.0318) Prec@1 95.000 (94.653) Prec@5 100.000 (99.898) +2022-11-14 15:59:56,414 Epoch: [289][490/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0254 (0.0317) Prec@1 95.000 (94.660) Prec@5 100.000 (99.900) +2022-11-14 15:59:56,843 Epoch: [289][499/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0222 (0.0315) Prec@1 96.000 (94.686) Prec@5 100.000 (99.902) +2022-11-14 15:59:57,163 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0679 (0.0679) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:57,175 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0655 (0.0667) Prec@1 89.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 15:59:57,188 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.0752) Prec@1 84.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:57,201 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0735) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 15:59:57,211 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0940 (0.0776) Prec@1 86.000 (87.200) Prec@5 99.000 (99.800) +2022-11-14 15:59:57,221 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0438 (0.0720) Prec@1 94.000 (88.333) Prec@5 99.000 (99.667) +2022-11-14 15:59:57,232 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0710) Prec@1 90.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 15:59:57,249 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1022 (0.0749) Prec@1 83.000 (87.875) Prec@5 99.000 (99.500) +2022-11-14 15:59:57,262 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0748) Prec@1 88.000 (87.889) Prec@5 99.000 (99.444) +2022-11-14 15:59:57,274 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0579 (0.0731) Prec@1 90.000 (88.100) Prec@5 98.000 (99.300) +2022-11-14 15:59:57,290 Test: [10/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0726) Prec@1 90.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 15:59:57,306 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0737) Prec@1 88.000 (88.250) Prec@5 99.000 (99.333) +2022-11-14 15:59:57,323 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0727) Prec@1 90.000 (88.385) Prec@5 100.000 (99.385) +2022-11-14 15:59:57,340 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0734) Prec@1 88.000 (88.357) Prec@5 100.000 (99.429) +2022-11-14 15:59:57,355 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0611 (0.0726) Prec@1 89.000 (88.400) Prec@5 100.000 (99.467) +2022-11-14 15:59:57,375 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0723) Prec@1 90.000 (88.500) Prec@5 99.000 (99.438) +2022-11-14 15:59:57,390 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0716) Prec@1 91.000 (88.647) Prec@5 98.000 (99.353) +2022-11-14 15:59:57,405 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1152 (0.0740) Prec@1 81.000 (88.222) Prec@5 100.000 (99.389) +2022-11-14 15:59:57,420 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0745) Prec@1 85.000 (88.053) Prec@5 98.000 (99.316) +2022-11-14 15:59:57,437 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0750) Prec@1 87.000 (88.000) Prec@5 98.000 (99.250) +2022-11-14 15:59:57,454 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0751) Prec@1 87.000 (87.952) Prec@5 99.000 (99.238) +2022-11-14 15:59:57,469 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0752) Prec@1 88.000 (87.955) Prec@5 98.000 (99.182) +2022-11-14 15:59:57,486 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0982 (0.0762) Prec@1 83.000 (87.739) Prec@5 97.000 (99.087) +2022-11-14 15:59:57,502 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0762) Prec@1 87.000 (87.708) Prec@5 100.000 (99.125) +2022-11-14 15:59:57,518 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0766) Prec@1 87.000 (87.680) Prec@5 100.000 (99.160) +2022-11-14 15:59:57,535 Test: [25/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0999 (0.0775) Prec@1 83.000 (87.500) Prec@5 99.000 (99.154) +2022-11-14 15:59:57,555 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0398 (0.0761) Prec@1 93.000 (87.704) Prec@5 100.000 (99.185) +2022-11-14 15:59:57,572 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0757) Prec@1 90.000 (87.786) Prec@5 99.000 (99.179) +2022-11-14 15:59:57,588 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0751) Prec@1 89.000 (87.828) Prec@5 99.000 (99.172) +2022-11-14 15:59:57,603 Test: [29/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0754) Prec@1 88.000 (87.833) Prec@5 99.000 (99.167) +2022-11-14 15:59:57,619 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0752) Prec@1 88.000 (87.839) Prec@5 99.000 (99.161) +2022-11-14 15:59:57,636 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0752) Prec@1 88.000 (87.844) Prec@5 100.000 (99.188) +2022-11-14 15:59:57,651 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0749) Prec@1 90.000 (87.909) Prec@5 100.000 (99.212) +2022-11-14 15:59:57,666 Test: [33/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1033 (0.0757) Prec@1 81.000 (87.706) Prec@5 99.000 (99.206) +2022-11-14 15:59:57,682 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1013 (0.0765) Prec@1 83.000 (87.571) Prec@5 97.000 (99.143) +2022-11-14 15:59:57,698 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0521 (0.0758) Prec@1 91.000 (87.667) Prec@5 100.000 (99.167) +2022-11-14 15:59:57,713 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0666 (0.0755) Prec@1 89.000 (87.703) Prec@5 100.000 (99.189) +2022-11-14 15:59:57,730 Test: [37/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1080 (0.0764) Prec@1 80.000 (87.500) Prec@5 99.000 (99.184) +2022-11-14 15:59:57,749 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0479 (0.0757) Prec@1 94.000 (87.667) Prec@5 99.000 (99.179) +2022-11-14 15:59:57,766 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0754) Prec@1 89.000 (87.700) Prec@5 99.000 (99.175) +2022-11-14 15:59:57,783 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0756) Prec@1 86.000 (87.659) Prec@5 99.000 (99.171) +2022-11-14 15:59:57,801 Test: [41/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0753) Prec@1 91.000 (87.738) Prec@5 100.000 (99.190) +2022-11-14 15:59:57,817 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0749) Prec@1 87.000 (87.721) Prec@5 100.000 (99.209) +2022-11-14 15:59:57,834 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0746) Prec@1 91.000 (87.795) Prec@5 97.000 (99.159) +2022-11-14 15:59:57,851 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0747) Prec@1 88.000 (87.800) Prec@5 99.000 (99.156) +2022-11-14 15:59:57,865 Test: [45/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1044 (0.0753) Prec@1 83.000 (87.696) Prec@5 99.000 (99.152) +2022-11-14 15:59:57,882 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0752) Prec@1 89.000 (87.723) Prec@5 100.000 (99.170) +2022-11-14 15:59:57,899 Test: [47/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1001 (0.0757) Prec@1 84.000 (87.646) Prec@5 99.000 (99.167) +2022-11-14 15:59:57,914 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0502 (0.0752) Prec@1 92.000 (87.735) Prec@5 100.000 (99.184) +2022-11-14 15:59:57,931 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1053 (0.0758) Prec@1 82.000 (87.620) Prec@5 99.000 (99.180) +2022-11-14 15:59:57,946 Test: [50/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0566 (0.0754) Prec@1 90.000 (87.667) Prec@5 100.000 (99.196) +2022-11-14 15:59:57,963 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0751) Prec@1 89.000 (87.692) Prec@5 98.000 (99.173) +2022-11-14 15:59:57,981 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0750) Prec@1 90.000 (87.736) Prec@5 100.000 (99.189) +2022-11-14 15:59:57,996 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0871 (0.0753) Prec@1 87.000 (87.722) Prec@5 100.000 (99.204) +2022-11-14 15:59:58,010 Test: [54/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1042 (0.0758) Prec@1 85.000 (87.673) Prec@5 100.000 (99.218) +2022-11-14 15:59:58,024 Test: [55/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0611 (0.0755) Prec@1 92.000 (87.750) Prec@5 98.000 (99.196) +2022-11-14 15:59:58,038 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0693 (0.0754) Prec@1 90.000 (87.789) Prec@5 100.000 (99.211) +2022-11-14 15:59:58,053 Test: [57/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0756) Prec@1 88.000 (87.793) Prec@5 100.000 (99.224) +2022-11-14 15:59:58,069 Test: [58/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0946 (0.0759) Prec@1 81.000 (87.678) Prec@5 100.000 (99.237) +2022-11-14 15:59:58,085 Test: [59/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0759) Prec@1 87.000 (87.667) Prec@5 100.000 (99.250) +2022-11-14 15:59:58,105 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0757) Prec@1 90.000 (87.705) Prec@5 99.000 (99.246) +2022-11-14 15:59:58,124 Test: [61/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0757) Prec@1 85.000 (87.661) Prec@5 99.000 (99.242) +2022-11-14 15:59:58,140 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0753) Prec@1 91.000 (87.714) Prec@5 99.000 (99.238) +2022-11-14 15:59:58,154 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0519 (0.0749) Prec@1 92.000 (87.781) Prec@5 100.000 (99.250) +2022-11-14 15:59:58,176 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0751) Prec@1 86.000 (87.754) Prec@5 98.000 (99.231) +2022-11-14 15:59:58,195 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0750) Prec@1 89.000 (87.773) Prec@5 99.000 (99.227) +2022-11-14 15:59:58,212 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0748) Prec@1 90.000 (87.806) Prec@5 100.000 (99.239) +2022-11-14 15:59:58,227 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0750) Prec@1 88.000 (87.809) Prec@5 98.000 (99.221) +2022-11-14 15:59:58,244 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0749) Prec@1 88.000 (87.812) Prec@5 99.000 (99.217) +2022-11-14 15:59:58,259 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0750) Prec@1 85.000 (87.771) Prec@5 99.000 (99.214) +2022-11-14 15:59:58,273 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0753) Prec@1 85.000 (87.732) Prec@5 100.000 (99.225) +2022-11-14 15:59:58,290 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0752) Prec@1 88.000 (87.736) Prec@5 99.000 (99.222) +2022-11-14 15:59:58,307 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0747) Prec@1 94.000 (87.822) Prec@5 100.000 (99.233) +2022-11-14 15:59:58,324 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0744) Prec@1 92.000 (87.878) Prec@5 100.000 (99.243) +2022-11-14 15:59:58,339 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0747) Prec@1 85.000 (87.840) Prec@5 99.000 (99.240) +2022-11-14 15:59:58,356 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0746) Prec@1 89.000 (87.855) Prec@5 99.000 (99.237) +2022-11-14 15:59:58,375 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0747) Prec@1 87.000 (87.844) Prec@5 98.000 (99.221) +2022-11-14 15:59:58,393 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0749) Prec@1 86.000 (87.821) Prec@5 97.000 (99.192) +2022-11-14 15:59:58,411 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0748) Prec@1 88.000 (87.823) Prec@5 100.000 (99.203) +2022-11-14 15:59:58,427 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0748) Prec@1 87.000 (87.812) Prec@5 100.000 (99.213) +2022-11-14 15:59:58,441 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0750) Prec@1 88.000 (87.815) Prec@5 98.000 (99.198) +2022-11-14 15:59:58,456 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0753) Prec@1 83.000 (87.756) Prec@5 99.000 (99.195) +2022-11-14 15:59:58,477 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0755) Prec@1 82.000 (87.687) Prec@5 100.000 (99.205) +2022-11-14 15:59:58,496 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0753) Prec@1 89.000 (87.702) Prec@5 99.000 (99.202) +2022-11-14 15:59:58,512 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1080 (0.0757) Prec@1 85.000 (87.671) Prec@5 98.000 (99.188) +2022-11-14 15:59:58,529 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0759) Prec@1 87.000 (87.663) Prec@5 100.000 (99.198) +2022-11-14 15:59:58,546 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0756) Prec@1 94.000 (87.736) Prec@5 100.000 (99.207) +2022-11-14 15:59:58,564 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0756) Prec@1 86.000 (87.716) Prec@5 99.000 (99.205) +2022-11-14 15:59:58,580 Test: [88/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0754) Prec@1 89.000 (87.730) Prec@5 99.000 (99.202) +2022-11-14 15:59:58,597 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0752) Prec@1 92.000 (87.778) Prec@5 99.000 (99.200) +2022-11-14 15:59:58,615 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0751) Prec@1 89.000 (87.791) Prec@5 100.000 (99.209) +2022-11-14 15:59:58,629 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0748) Prec@1 93.000 (87.848) Prec@5 99.000 (99.207) +2022-11-14 15:59:58,643 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0749) Prec@1 86.000 (87.828) Prec@5 100.000 (99.215) +2022-11-14 15:59:58,661 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0749) Prec@1 88.000 (87.830) Prec@5 100.000 (99.223) +2022-11-14 15:59:58,677 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0752) Prec@1 85.000 (87.800) Prec@5 100.000 (99.232) +2022-11-14 15:59:58,692 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0751) Prec@1 91.000 (87.833) Prec@5 100.000 (99.240) +2022-11-14 15:59:58,710 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0749) Prec@1 90.000 (87.856) Prec@5 97.000 (99.216) +2022-11-14 15:59:58,726 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0752) Prec@1 82.000 (87.796) Prec@5 98.000 (99.204) +2022-11-14 15:59:58,741 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0753) Prec@1 85.000 (87.768) Prec@5 98.000 (99.192) +2022-11-14 15:59:58,759 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0754) Prec@1 89.000 (87.780) Prec@5 100.000 (99.200) +2022-11-14 15:59:58,840 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 15:59:59,202 Epoch: [290][0/500] Time 0.033 (0.033) Data 0.262 (0.262) Loss 0.0263 (0.0263) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 15:59:59,643 Epoch: [290][10/500] Time 0.059 (0.039) Data 0.002 (0.026) Loss 0.0388 (0.0325) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:00:00,134 Epoch: [290][20/500] Time 0.040 (0.041) Data 0.002 (0.014) Loss 0.0364 (0.0338) Prec@1 92.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 16:00:00,599 Epoch: [290][30/500] Time 0.036 (0.041) Data 0.002 (0.010) Loss 0.0288 (0.0326) Prec@1 96.000 (94.500) Prec@5 99.000 (99.500) +2022-11-14 16:00:01,089 Epoch: [290][40/500] Time 0.049 (0.042) Data 0.002 (0.008) Loss 0.0379 (0.0336) Prec@1 93.000 (94.200) Prec@5 99.000 (99.400) +2022-11-14 16:00:01,555 Epoch: [290][50/500] Time 0.048 (0.042) Data 0.002 (0.007) Loss 0.0294 (0.0329) Prec@1 96.000 (94.500) Prec@5 99.000 (99.333) +2022-11-14 16:00:02,050 Epoch: [290][60/500] Time 0.055 (0.042) Data 0.002 (0.006) Loss 0.0418 (0.0342) Prec@1 94.000 (94.429) Prec@5 100.000 (99.429) +2022-11-14 16:00:02,554 Epoch: [290][70/500] Time 0.059 (0.043) Data 0.003 (0.006) Loss 0.0349 (0.0343) Prec@1 93.000 (94.250) Prec@5 100.000 (99.500) +2022-11-14 16:00:03,034 Epoch: [290][80/500] Time 0.061 (0.043) Data 0.002 (0.005) Loss 0.0303 (0.0338) Prec@1 95.000 (94.333) Prec@5 100.000 (99.556) +2022-11-14 16:00:03,537 Epoch: [290][90/500] Time 0.073 (0.043) Data 0.002 (0.005) Loss 0.0298 (0.0334) Prec@1 97.000 (94.600) Prec@5 100.000 (99.600) +2022-11-14 16:00:04,029 Epoch: [290][100/500] Time 0.045 (0.043) Data 0.002 (0.005) Loss 0.0225 (0.0324) Prec@1 97.000 (94.818) Prec@5 100.000 (99.636) +2022-11-14 16:00:04,510 Epoch: [290][110/500] Time 0.050 (0.043) Data 0.002 (0.004) Loss 0.0123 (0.0308) Prec@1 99.000 (95.167) Prec@5 100.000 (99.667) +2022-11-14 16:00:05,001 Epoch: [290][120/500] Time 0.035 (0.043) Data 0.002 (0.004) Loss 0.0349 (0.0311) Prec@1 94.000 (95.077) Prec@5 100.000 (99.692) +2022-11-14 16:00:05,487 Epoch: [290][130/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0235 (0.0305) Prec@1 97.000 (95.214) Prec@5 100.000 (99.714) +2022-11-14 16:00:05,971 Epoch: [290][140/500] Time 0.051 (0.043) Data 0.002 (0.004) Loss 0.0567 (0.0323) Prec@1 90.000 (94.867) Prec@5 100.000 (99.733) +2022-11-14 16:00:06,443 Epoch: [290][150/500] Time 0.047 (0.043) Data 0.002 (0.004) Loss 0.0790 (0.0352) Prec@1 87.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 16:00:06,936 Epoch: [290][160/500] Time 0.054 (0.043) Data 0.002 (0.004) Loss 0.0355 (0.0352) Prec@1 94.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 16:00:07,447 Epoch: [290][170/500] Time 0.053 (0.043) Data 0.002 (0.004) Loss 0.0187 (0.0343) Prec@1 98.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 16:00:07,941 Epoch: [290][180/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0372 (0.0344) Prec@1 96.000 (94.632) Prec@5 100.000 (99.789) +2022-11-14 16:00:08,434 Epoch: [290][190/500] Time 0.042 (0.043) Data 0.003 (0.003) Loss 0.0419 (0.0348) Prec@1 93.000 (94.550) Prec@5 100.000 (99.800) +2022-11-14 16:00:08,926 Epoch: [290][200/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0340 (0.0348) Prec@1 95.000 (94.571) Prec@5 100.000 (99.810) +2022-11-14 16:00:09,405 Epoch: [290][210/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0518 (0.0356) Prec@1 91.000 (94.409) Prec@5 100.000 (99.818) +2022-11-14 16:00:09,885 Epoch: [290][220/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0269 (0.0352) Prec@1 94.000 (94.391) Prec@5 100.000 (99.826) +2022-11-14 16:00:10,366 Epoch: [290][230/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0525 (0.0359) Prec@1 92.000 (94.292) Prec@5 100.000 (99.833) +2022-11-14 16:00:10,855 Epoch: [290][240/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0259 (0.0355) Prec@1 96.000 (94.360) Prec@5 100.000 (99.840) +2022-11-14 16:00:11,325 Epoch: [290][250/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0246 (0.0351) Prec@1 97.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 16:00:11,882 Epoch: [290][260/500] Time 0.037 (0.044) Data 0.003 (0.003) Loss 0.0486 (0.0356) Prec@1 89.000 (94.259) Prec@5 99.000 (99.815) +2022-11-14 16:00:12,353 Epoch: [290][270/500] Time 0.038 (0.044) Data 0.003 (0.003) Loss 0.0452 (0.0359) Prec@1 93.000 (94.214) Prec@5 100.000 (99.821) +2022-11-14 16:00:12,836 Epoch: [290][280/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0207 (0.0354) Prec@1 96.000 (94.276) Prec@5 100.000 (99.828) +2022-11-14 16:00:13,340 Epoch: [290][290/500] Time 0.037 (0.044) Data 0.003 (0.003) Loss 0.0266 (0.0351) Prec@1 97.000 (94.367) Prec@5 100.000 (99.833) +2022-11-14 16:00:13,893 Epoch: [290][300/500] Time 0.054 (0.044) Data 0.002 (0.003) Loss 0.0414 (0.0353) Prec@1 92.000 (94.290) Prec@5 100.000 (99.839) +2022-11-14 16:00:14,410 Epoch: [290][310/500] Time 0.046 (0.044) Data 0.003 (0.003) Loss 0.0211 (0.0349) Prec@1 97.000 (94.375) Prec@5 99.000 (99.812) +2022-11-14 16:00:14,902 Epoch: [290][320/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0335 (0.0348) Prec@1 95.000 (94.394) Prec@5 100.000 (99.818) +2022-11-14 16:00:15,374 Epoch: [290][330/500] Time 0.042 (0.044) Data 0.003 (0.003) Loss 0.0347 (0.0348) Prec@1 95.000 (94.412) Prec@5 99.000 (99.794) +2022-11-14 16:00:15,872 Epoch: [290][340/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0373 (0.0349) Prec@1 95.000 (94.429) Prec@5 100.000 (99.800) +2022-11-14 16:00:16,359 Epoch: [290][350/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0342 (0.0349) Prec@1 94.000 (94.417) Prec@5 100.000 (99.806) +2022-11-14 16:00:16,851 Epoch: [290][360/500] Time 0.046 (0.044) Data 0.003 (0.003) Loss 0.0414 (0.0351) Prec@1 93.000 (94.378) Prec@5 100.000 (99.811) +2022-11-14 16:00:17,331 Epoch: [290][370/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0216 (0.0347) Prec@1 97.000 (94.447) Prec@5 100.000 (99.816) +2022-11-14 16:00:17,811 Epoch: [290][380/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0425 (0.0349) Prec@1 92.000 (94.385) Prec@5 100.000 (99.821) +2022-11-14 16:00:18,282 Epoch: [290][390/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0343 (0.0349) Prec@1 94.000 (94.375) Prec@5 100.000 (99.825) +2022-11-14 16:00:18,766 Epoch: [290][400/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0306 (0.0348) Prec@1 94.000 (94.366) Prec@5 99.000 (99.805) +2022-11-14 16:00:19,252 Epoch: [290][410/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0231 (0.0345) Prec@1 97.000 (94.429) Prec@5 100.000 (99.810) +2022-11-14 16:00:19,736 Epoch: [290][420/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0419 (0.0347) Prec@1 93.000 (94.395) Prec@5 100.000 (99.814) +2022-11-14 16:00:20,223 Epoch: [290][430/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0250 (0.0345) Prec@1 97.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 16:00:20,691 Epoch: [290][440/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0447 (0.0347) Prec@1 92.000 (94.400) Prec@5 100.000 (99.822) +2022-11-14 16:00:21,181 Epoch: [290][450/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0372 (0.0347) Prec@1 92.000 (94.348) Prec@5 100.000 (99.826) +2022-11-14 16:00:21,657 Epoch: [290][460/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0216 (0.0345) Prec@1 96.000 (94.383) Prec@5 100.000 (99.830) +2022-11-14 16:00:22,151 Epoch: [290][470/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0113 (0.0340) Prec@1 98.000 (94.458) Prec@5 100.000 (99.833) +2022-11-14 16:00:22,650 Epoch: [290][480/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0239 (0.0338) Prec@1 95.000 (94.469) Prec@5 100.000 (99.837) +2022-11-14 16:00:23,136 Epoch: [290][490/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0306 (0.0337) Prec@1 94.000 (94.460) Prec@5 100.000 (99.840) +2022-11-14 16:00:23,586 Epoch: [290][499/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0297 (0.0336) Prec@1 94.000 (94.451) Prec@5 100.000 (99.843) +2022-11-14 16:00:23,925 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0727 (0.0727) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 16:00:23,936 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0801 (0.0764) Prec@1 86.000 (86.000) Prec@5 100.000 (99.500) +2022-11-14 16:00:23,944 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0775) Prec@1 84.000 (85.333) Prec@5 100.000 (99.667) +2022-11-14 16:00:23,959 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0779) Prec@1 88.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 16:00:23,969 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0792) Prec@1 86.000 (86.000) Prec@5 99.000 (99.400) +2022-11-14 16:00:23,978 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0318 (0.0713) Prec@1 95.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 16:00:23,988 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0712) Prec@1 91.000 (88.000) Prec@5 100.000 (99.571) +2022-11-14 16:00:24,001 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0731) Prec@1 86.000 (87.750) Prec@5 100.000 (99.625) +2022-11-14 16:00:24,012 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0760) Prec@1 86.000 (87.556) Prec@5 97.000 (99.333) +2022-11-14 16:00:24,027 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0747) Prec@1 91.000 (87.900) Prec@5 99.000 (99.300) +2022-11-14 16:00:24,041 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0726) Prec@1 91.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 16:00:24,059 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0735) Prec@1 88.000 (88.167) Prec@5 100.000 (99.417) +2022-11-14 16:00:24,073 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0742) Prec@1 87.000 (88.077) Prec@5 99.000 (99.385) +2022-11-14 16:00:24,088 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0741) Prec@1 88.000 (88.071) Prec@5 100.000 (99.429) +2022-11-14 16:00:24,106 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0737) Prec@1 88.000 (88.067) Prec@5 100.000 (99.467) +2022-11-14 16:00:24,121 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0728) Prec@1 90.000 (88.188) Prec@5 98.000 (99.375) +2022-11-14 16:00:24,134 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0717) Prec@1 92.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 16:00:24,146 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0732) Prec@1 81.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 16:00:24,166 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0740) Prec@1 87.000 (87.947) Prec@5 99.000 (99.316) +2022-11-14 16:00:24,180 Test: 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0.0838 (0.0786) Prec@1 88.000 (87.423) Prec@5 98.000 (99.154) +2022-11-14 16:00:24,303 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0777) Prec@1 92.000 (87.593) Prec@5 100.000 (99.185) +2022-11-14 16:00:24,321 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0772) Prec@1 91.000 (87.714) Prec@5 98.000 (99.143) +2022-11-14 16:00:24,338 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0768) Prec@1 89.000 (87.759) Prec@5 98.000 (99.103) +2022-11-14 16:00:24,354 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0768) Prec@1 86.000 (87.700) Prec@5 98.000 (99.067) +2022-11-14 16:00:24,370 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0766) Prec@1 87.000 (87.677) Prec@5 99.000 (99.065) +2022-11-14 16:00:24,386 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0764) Prec@1 89.000 (87.719) Prec@5 98.000 (99.031) +2022-11-14 16:00:24,403 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0762) Prec@1 87.000 (87.697) Prec@5 100.000 (99.061) +2022-11-14 16:00:24,421 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0767) Prec@1 85.000 (87.618) Prec@5 99.000 (99.059) +2022-11-14 16:00:24,436 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0768) Prec@1 87.000 (87.600) Prec@5 99.000 (99.057) +2022-11-14 16:00:24,452 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0765) Prec@1 90.000 (87.667) Prec@5 100.000 (99.083) +2022-11-14 16:00:24,466 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0765) Prec@1 88.000 (87.676) Prec@5 98.000 (99.054) +2022-11-14 16:00:24,480 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0766) Prec@1 86.000 (87.632) Prec@5 99.000 (99.053) +2022-11-14 16:00:24,495 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0759) Prec@1 93.000 (87.769) Prec@5 100.000 (99.077) +2022-11-14 16:00:24,515 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0754) Prec@1 91.000 (87.850) Prec@5 99.000 (99.075) +2022-11-14 16:00:24,531 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0758) Prec@1 84.000 (87.756) Prec@5 99.000 (99.073) +2022-11-14 16:00:24,545 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0757) Prec@1 88.000 (87.762) Prec@5 99.000 (99.071) +2022-11-14 16:00:24,563 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0753) Prec@1 92.000 (87.860) Prec@5 100.000 (99.093) +2022-11-14 16:00:24,581 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0752) Prec@1 90.000 (87.909) Prec@5 99.000 (99.091) +2022-11-14 16:00:24,599 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0749) Prec@1 89.000 (87.933) Prec@5 99.000 (99.089) +2022-11-14 16:00:24,615 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0757) Prec@1 84.000 (87.848) Prec@5 100.000 (99.109) +2022-11-14 16:00:24,630 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0757) Prec@1 86.000 (87.809) Prec@5 100.000 (99.128) +2022-11-14 16:00:24,644 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0761) Prec@1 84.000 (87.729) Prec@5 98.000 (99.104) +2022-11-14 16:00:24,662 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0758) Prec@1 92.000 (87.816) Prec@5 100.000 (99.122) +2022-11-14 16:00:24,680 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0762) Prec@1 87.000 (87.800) Prec@5 100.000 (99.140) +2022-11-14 16:00:24,696 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0459 (0.0756) Prec@1 92.000 (87.882) Prec@5 100.000 (99.157) +2022-11-14 16:00:24,714 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0756) Prec@1 85.000 (87.827) Prec@5 100.000 (99.173) +2022-11-14 16:00:24,728 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0754) Prec@1 89.000 (87.849) Prec@5 100.000 (99.189) +2022-11-14 16:00:24,743 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0752) Prec@1 91.000 (87.907) Prec@5 99.000 (99.185) +2022-11-14 16:00:24,762 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0752) Prec@1 87.000 (87.891) Prec@5 100.000 (99.200) +2022-11-14 16:00:24,777 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0751) Prec@1 91.000 (87.946) Prec@5 99.000 (99.196) +2022-11-14 16:00:24,790 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0750) Prec@1 88.000 (87.947) Prec@5 99.000 (99.193) +2022-11-14 16:00:24,805 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0750) Prec@1 89.000 (87.966) Prec@5 100.000 (99.207) +2022-11-14 16:00:24,824 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0755) Prec@1 86.000 (87.932) Prec@5 100.000 (99.220) +2022-11-14 16:00:24,842 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0755) Prec@1 86.000 (87.900) Prec@5 100.000 (99.233) +2022-11-14 16:00:24,859 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0756) Prec@1 88.000 (87.902) Prec@5 100.000 (99.246) +2022-11-14 16:00:24,874 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0756) Prec@1 87.000 (87.887) Prec@5 99.000 (99.242) +2022-11-14 16:00:24,890 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0755) Prec@1 91.000 (87.937) Prec@5 100.000 (99.254) +2022-11-14 16:00:24,907 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0751) Prec@1 92.000 (88.000) Prec@5 100.000 (99.266) +2022-11-14 16:00:24,924 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0751) Prec@1 87.000 (87.985) Prec@5 99.000 (99.262) +2022-11-14 16:00:24,944 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0753) Prec@1 86.000 (87.955) Prec@5 98.000 (99.242) +2022-11-14 16:00:24,959 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0749) Prec@1 90.000 (87.985) Prec@5 100.000 (99.254) +2022-11-14 16:00:24,975 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0748) Prec@1 92.000 (88.044) Prec@5 99.000 (99.250) +2022-11-14 16:00:24,988 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0745) Prec@1 91.000 (88.087) Prec@5 99.000 (99.246) +2022-11-14 16:00:25,003 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0746) Prec@1 87.000 (88.071) Prec@5 100.000 (99.257) +2022-11-14 16:00:25,019 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1255 (0.0753) Prec@1 82.000 (87.986) Prec@5 98.000 (99.239) +2022-11-14 16:00:25,033 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0751) Prec@1 91.000 (88.028) Prec@5 99.000 (99.236) +2022-11-14 16:00:25,048 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0747) Prec@1 93.000 (88.096) Prec@5 99.000 (99.233) +2022-11-14 16:00:25,067 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0743) Prec@1 92.000 (88.149) Prec@5 100.000 (99.243) +2022-11-14 16:00:25,084 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0746) Prec@1 82.000 (88.067) Prec@5 100.000 (99.253) +2022-11-14 16:00:25,100 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0746) Prec@1 88.000 (88.066) Prec@5 100.000 (99.263) +2022-11-14 16:00:25,116 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0746) Prec@1 87.000 (88.052) Prec@5 100.000 (99.273) +2022-11-14 16:00:25,132 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0749) Prec@1 85.000 (88.013) Prec@5 99.000 (99.269) +2022-11-14 16:00:25,148 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0748) Prec@1 90.000 (88.038) Prec@5 100.000 (99.278) +2022-11-14 16:00:25,166 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0749) Prec@1 83.000 (87.975) Prec@5 100.000 (99.287) +2022-11-14 16:00:25,184 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0748) Prec@1 90.000 (88.000) Prec@5 99.000 (99.284) +2022-11-14 16:00:25,198 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0747) Prec@1 89.000 (88.012) Prec@5 100.000 (99.293) +2022-11-14 16:00:25,212 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0748) Prec@1 84.000 (87.964) Prec@5 99.000 (99.289) +2022-11-14 16:00:25,228 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0748) Prec@1 88.000 (87.964) Prec@5 98.000 (99.274) +2022-11-14 16:00:25,246 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0749) Prec@1 86.000 (87.941) Prec@5 99.000 (99.271) +2022-11-14 16:00:25,263 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0751) Prec@1 87.000 (87.930) Prec@5 100.000 (99.279) +2022-11-14 16:00:25,278 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0751) Prec@1 86.000 (87.908) Prec@5 100.000 (99.287) +2022-11-14 16:00:25,293 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0751) Prec@1 89.000 (87.920) Prec@5 98.000 (99.273) +2022-11-14 16:00:25,311 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0753) Prec@1 86.000 (87.899) Prec@5 100.000 (99.281) +2022-11-14 16:00:25,329 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0753) Prec@1 89.000 (87.911) Prec@5 100.000 (99.289) +2022-11-14 16:00:25,348 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0750) Prec@1 90.000 (87.934) Prec@5 100.000 (99.297) +2022-11-14 16:00:25,367 Test: [91/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0748) Prec@1 88.000 (87.935) Prec@5 99.000 (99.293) +2022-11-14 16:00:25,382 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0750) Prec@1 86.000 (87.914) Prec@5 99.000 (99.290) +2022-11-14 16:00:25,399 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0752) Prec@1 84.000 (87.872) Prec@5 98.000 (99.277) +2022-11-14 16:00:25,413 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0753) Prec@1 88.000 (87.874) Prec@5 99.000 (99.274) +2022-11-14 16:00:25,430 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0752) Prec@1 88.000 (87.875) Prec@5 100.000 (99.281) +2022-11-14 16:00:25,448 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0749) Prec@1 93.000 (87.928) Prec@5 98.000 (99.268) +2022-11-14 16:00:25,465 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0749) Prec@1 89.000 (87.939) Prec@5 98.000 (99.255) +2022-11-14 16:00:25,482 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0750) Prec@1 84.000 (87.899) Prec@5 100.000 (99.263) +2022-11-14 16:00:25,499 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0749) Prec@1 90.000 (87.920) Prec@5 99.000 (99.260) +2022-11-14 16:00:25,562 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:00:25,931 Epoch: [291][0/500] Time 0.032 (0.032) Data 0.274 (0.274) Loss 0.0533 (0.0533) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:00:26,373 Epoch: [291][10/500] Time 0.047 (0.038) Data 0.002 (0.027) Loss 0.0420 (0.0477) Prec@1 92.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 16:00:26,863 Epoch: [291][20/500] Time 0.049 (0.040) Data 0.002 (0.015) Loss 0.0464 (0.0473) Prec@1 93.000 (92.333) Prec@5 100.000 (99.667) +2022-11-14 16:00:27,347 Epoch: [291][30/500] Time 0.046 (0.041) Data 0.002 (0.011) Loss 0.0567 (0.0496) Prec@1 90.000 (91.750) Prec@5 99.000 (99.500) +2022-11-14 16:00:27,850 Epoch: [291][40/500] Time 0.044 (0.042) Data 0.002 (0.009) Loss 0.0266 (0.0450) Prec@1 95.000 (92.400) Prec@5 100.000 (99.600) +2022-11-14 16:00:28,344 Epoch: [291][50/500] Time 0.038 (0.043) Data 0.002 (0.007) Loss 0.0161 (0.0402) Prec@1 99.000 (93.500) Prec@5 100.000 (99.667) +2022-11-14 16:00:28,833 Epoch: [291][60/500] Time 0.053 (0.043) Data 0.002 (0.007) Loss 0.0324 (0.0391) Prec@1 95.000 (93.714) Prec@5 99.000 (99.571) +2022-11-14 16:00:29,319 Epoch: [291][70/500] Time 0.042 (0.043) Data 0.002 (0.006) Loss 0.0304 (0.0380) Prec@1 96.000 (94.000) Prec@5 100.000 (99.625) +2022-11-14 16:00:29,802 Epoch: [291][80/500] Time 0.057 (0.043) Data 0.002 (0.005) Loss 0.0307 (0.0372) Prec@1 95.000 (94.111) Prec@5 100.000 (99.667) +2022-11-14 16:00:30,288 Epoch: [291][90/500] Time 0.045 (0.043) Data 0.003 (0.005) Loss 0.0418 (0.0376) Prec@1 94.000 (94.100) Prec@5 98.000 (99.500) +2022-11-14 16:00:30,768 Epoch: [291][100/500] Time 0.053 (0.043) Data 0.002 (0.005) Loss 0.0299 (0.0369) Prec@1 96.000 (94.273) Prec@5 100.000 (99.545) +2022-11-14 16:00:31,253 Epoch: [291][110/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.0425 (0.0374) Prec@1 92.000 (94.083) Prec@5 100.000 (99.583) +2022-11-14 16:00:31,749 Epoch: [291][120/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0419 (0.0377) Prec@1 93.000 (94.000) Prec@5 100.000 (99.615) +2022-11-14 16:00:32,240 Epoch: [291][130/500] Time 0.041 (0.043) Data 0.002 (0.004) Loss 0.0327 (0.0374) Prec@1 96.000 (94.143) Prec@5 100.000 (99.643) +2022-11-14 16:00:32,720 Epoch: [291][140/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0316 (0.0370) Prec@1 94.000 (94.133) Prec@5 100.000 (99.667) +2022-11-14 16:00:33,200 Epoch: [291][150/500] Time 0.037 (0.043) Data 0.002 (0.004) Loss 0.0317 (0.0367) Prec@1 93.000 (94.062) Prec@5 100.000 (99.688) +2022-11-14 16:00:33,679 Epoch: [291][160/500] Time 0.041 (0.043) Data 0.002 (0.004) Loss 0.0172 (0.0355) Prec@1 97.000 (94.235) Prec@5 100.000 (99.706) +2022-11-14 16:00:34,153 Epoch: [291][170/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.0168 (0.0345) Prec@1 98.000 (94.444) Prec@5 100.000 (99.722) +2022-11-14 16:00:34,650 Epoch: [291][180/500] Time 0.047 (0.043) Data 0.002 (0.004) Loss 0.0279 (0.0341) Prec@1 95.000 (94.474) Prec@5 99.000 (99.684) +2022-11-14 16:00:35,124 Epoch: [291][190/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0268 (0.0338) Prec@1 97.000 (94.600) Prec@5 99.000 (99.650) +2022-11-14 16:00:35,619 Epoch: [291][200/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0259 (0.0334) Prec@1 97.000 (94.714) Prec@5 100.000 (99.667) +2022-11-14 16:00:36,108 Epoch: [291][210/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0319 (0.0333) Prec@1 97.000 (94.818) Prec@5 100.000 (99.682) +2022-11-14 16:00:36,599 Epoch: [291][220/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0245 (0.0329) Prec@1 96.000 (94.870) Prec@5 100.000 (99.696) +2022-11-14 16:00:37,097 Epoch: [291][230/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0433 (0.0334) Prec@1 93.000 (94.792) Prec@5 99.000 (99.667) +2022-11-14 16:00:37,588 Epoch: [291][240/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0155 (0.0326) Prec@1 98.000 (94.920) Prec@5 100.000 (99.680) +2022-11-14 16:00:38,080 Epoch: [291][250/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0200 (0.0322) Prec@1 98.000 (95.038) Prec@5 100.000 (99.692) +2022-11-14 16:00:38,576 Epoch: [291][260/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0394 (0.0324) Prec@1 92.000 (94.926) Prec@5 100.000 (99.704) +2022-11-14 16:00:39,071 Epoch: [291][270/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0554 (0.0333) Prec@1 90.000 (94.750) Prec@5 99.000 (99.679) +2022-11-14 16:00:39,551 Epoch: [291][280/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0378 (0.0334) Prec@1 92.000 (94.655) Prec@5 100.000 (99.690) +2022-11-14 16:00:40,038 Epoch: [291][290/500] Time 0.038 (0.043) Data 0.002 (0.003) Loss 0.0337 (0.0334) Prec@1 94.000 (94.633) Prec@5 100.000 (99.700) +2022-11-14 16:00:40,535 Epoch: [291][300/500] Time 0.045 (0.043) Data 0.003 (0.003) Loss 0.0279 (0.0332) Prec@1 96.000 (94.677) Prec@5 100.000 (99.710) +2022-11-14 16:00:41,021 Epoch: [291][310/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0408 (0.0335) Prec@1 93.000 (94.625) Prec@5 100.000 (99.719) +2022-11-14 16:00:41,498 Epoch: [291][320/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0500 (0.0340) Prec@1 91.000 (94.515) Prec@5 100.000 (99.727) +2022-11-14 16:00:41,970 Epoch: [291][330/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0425 (0.0342) Prec@1 93.000 (94.471) Prec@5 99.000 (99.706) +2022-11-14 16:00:42,431 Epoch: [291][340/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0387 (0.0344) Prec@1 93.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 16:00:42,923 Epoch: [291][350/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0335 (0.0343) Prec@1 97.000 (94.500) Prec@5 100.000 (99.722) +2022-11-14 16:00:43,408 Epoch: [291][360/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0359 (0.0344) Prec@1 94.000 (94.486) Prec@5 99.000 (99.703) +2022-11-14 16:00:43,902 Epoch: [291][370/500] Time 0.042 (0.043) Data 0.003 (0.003) Loss 0.0343 (0.0344) Prec@1 95.000 (94.500) Prec@5 100.000 (99.711) +2022-11-14 16:00:44,395 Epoch: [291][380/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0264 (0.0342) Prec@1 97.000 (94.564) Prec@5 100.000 (99.718) +2022-11-14 16:00:44,870 Epoch: [291][390/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0274 (0.0340) Prec@1 95.000 (94.575) Prec@5 100.000 (99.725) +2022-11-14 16:00:45,354 Epoch: [291][400/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0181 (0.0336) Prec@1 97.000 (94.634) Prec@5 100.000 (99.732) +2022-11-14 16:00:45,847 Epoch: [291][410/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0452 (0.0339) Prec@1 93.000 (94.595) Prec@5 99.000 (99.714) +2022-11-14 16:00:46,328 Epoch: [291][420/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0173 (0.0335) Prec@1 98.000 (94.674) Prec@5 100.000 (99.721) +2022-11-14 16:00:46,802 Epoch: [291][430/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0325 (0.0335) Prec@1 93.000 (94.636) Prec@5 100.000 (99.727) +2022-11-14 16:00:47,295 Epoch: [291][440/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0345 (0.0335) Prec@1 94.000 (94.622) Prec@5 100.000 (99.733) +2022-11-14 16:00:47,753 Epoch: [291][450/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0451 (0.0338) Prec@1 92.000 (94.565) Prec@5 100.000 (99.739) +2022-11-14 16:00:48,236 Epoch: [291][460/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0325 (0.0337) Prec@1 93.000 (94.532) Prec@5 100.000 (99.745) +2022-11-14 16:00:48,719 Epoch: [291][470/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0337 (0.0337) Prec@1 97.000 (94.583) Prec@5 100.000 (99.750) +2022-11-14 16:00:49,202 Epoch: [291][480/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0311 (0.0337) Prec@1 94.000 (94.571) Prec@5 100.000 (99.755) +2022-11-14 16:00:49,700 Epoch: [291][490/500] Time 0.047 (0.043) Data 0.003 (0.003) Loss 0.0512 (0.0340) Prec@1 90.000 (94.480) Prec@5 99.000 (99.740) +2022-11-14 16:00:50,123 Epoch: [291][499/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0382 (0.0341) Prec@1 95.000 (94.490) Prec@5 98.000 (99.706) +2022-11-14 16:00:50,446 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0652 (0.0652) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:00:50,455 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0746 (0.0699) Prec@1 89.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:00:50,465 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0713) Prec@1 88.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:00:50,476 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0688) Prec@1 89.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 16:00:50,485 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0684) Prec@1 90.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:00:50,495 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0409 (0.0638) Prec@1 94.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 16:00:50,509 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0656) Prec@1 89.000 (89.714) Prec@5 99.000 (99.571) +2022-11-14 16:00:50,521 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0692) Prec@1 84.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 16:00:50,535 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0724) Prec@1 83.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:00:50,549 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0733) Prec@1 86.000 (88.100) Prec@5 98.000 (99.500) +2022-11-14 16:00:50,567 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0726) Prec@1 92.000 (88.455) Prec@5 100.000 (99.545) +2022-11-14 16:00:50,584 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0733) Prec@1 87.000 (88.333) Prec@5 100.000 (99.583) +2022-11-14 16:00:50,599 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0730) Prec@1 90.000 (88.462) Prec@5 100.000 (99.615) +2022-11-14 16:00:50,615 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0730) Prec@1 89.000 (88.500) Prec@5 99.000 (99.571) +2022-11-14 16:00:50,631 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0729) Prec@1 88.000 (88.467) Prec@5 100.000 (99.600) +2022-11-14 16:00:50,648 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0727) Prec@1 87.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 16:00:50,665 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0715) Prec@1 92.000 (88.588) Prec@5 97.000 (99.471) +2022-11-14 16:00:50,679 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0727) Prec@1 85.000 (88.389) Prec@5 100.000 (99.500) +2022-11-14 16:00:50,691 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0738) Prec@1 84.000 (88.158) Prec@5 99.000 (99.474) +2022-11-14 16:00:50,705 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0743) Prec@1 89.000 (88.200) Prec@5 98.000 (99.400) +2022-11-14 16:00:50,723 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0738) Prec@1 92.000 (88.381) Prec@5 100.000 (99.429) +2022-11-14 16:00:50,741 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0743) Prec@1 84.000 (88.182) Prec@5 98.000 (99.364) +2022-11-14 16:00:50,760 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0749) Prec@1 87.000 (88.130) Prec@5 98.000 (99.304) +2022-11-14 16:00:50,778 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0758) Prec@1 85.000 (88.000) Prec@5 99.000 (99.292) +2022-11-14 16:00:50,797 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0764) Prec@1 85.000 (87.880) Prec@5 100.000 (99.320) +2022-11-14 16:00:50,814 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0771) Prec@1 85.000 (87.769) Prec@5 99.000 (99.308) +2022-11-14 16:00:50,830 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0760) Prec@1 93.000 (87.963) Prec@5 100.000 (99.333) +2022-11-14 16:00:50,843 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0755) Prec@1 90.000 (88.036) Prec@5 100.000 (99.357) +2022-11-14 16:00:50,857 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0753) Prec@1 88.000 (88.034) Prec@5 98.000 (99.310) +2022-11-14 16:00:50,876 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0747) Prec@1 90.000 (88.100) Prec@5 100.000 (99.333) +2022-11-14 16:00:50,891 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0746) Prec@1 87.000 (88.065) Prec@5 99.000 (99.323) +2022-11-14 16:00:50,909 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0744) Prec@1 88.000 (88.062) Prec@5 99.000 (99.312) +2022-11-14 16:00:50,930 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0738) Prec@1 92.000 (88.182) Prec@5 99.000 (99.303) +2022-11-14 16:00:50,946 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0745) Prec@1 86.000 (88.118) Prec@5 100.000 (99.324) +2022-11-14 16:00:50,965 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0747) Prec@1 88.000 (88.114) Prec@5 99.000 (99.314) +2022-11-14 16:00:50,981 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0744) Prec@1 91.000 (88.194) Prec@5 100.000 (99.333) +2022-11-14 16:00:50,995 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0744) Prec@1 88.000 (88.189) Prec@5 99.000 (99.324) +2022-11-14 16:00:51,013 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0749) Prec@1 87.000 (88.158) Prec@5 100.000 (99.342) +2022-11-14 16:00:51,030 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0743) Prec@1 94.000 (88.308) Prec@5 99.000 (99.333) +2022-11-14 16:00:51,043 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0391 (0.0735) Prec@1 94.000 (88.450) Prec@5 99.000 (99.325) +2022-11-14 16:00:51,059 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0739) Prec@1 86.000 (88.390) Prec@5 97.000 (99.268) +2022-11-14 16:00:51,078 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0741) Prec@1 87.000 (88.357) Prec@5 98.000 (99.238) +2022-11-14 16:00:51,096 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0390 (0.0732) Prec@1 94.000 (88.488) Prec@5 100.000 (99.256) +2022-11-14 16:00:51,114 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0728) Prec@1 92.000 (88.568) Prec@5 98.000 (99.227) +2022-11-14 16:00:51,131 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0727) Prec@1 90.000 (88.600) Prec@5 99.000 (99.222) +2022-11-14 16:00:51,146 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.0737) Prec@1 81.000 (88.435) Prec@5 98.000 (99.196) +2022-11-14 16:00:51,161 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0736) Prec@1 90.000 (88.468) Prec@5 100.000 (99.213) +2022-11-14 16:00:51,173 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0740) Prec@1 87.000 (88.438) Prec@5 99.000 (99.208) +2022-11-14 16:00:51,188 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0740) Prec@1 85.000 (88.367) Prec@5 99.000 (99.204) +2022-11-14 16:00:51,207 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0746) Prec@1 82.000 (88.240) Prec@5 100.000 (99.220) +2022-11-14 16:00:51,224 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0744) Prec@1 90.000 (88.275) Prec@5 100.000 (99.235) +2022-11-14 16:00:51,238 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0742) Prec@1 88.000 (88.269) Prec@5 99.000 (99.231) +2022-11-14 16:00:51,256 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0740) Prec@1 90.000 (88.302) Prec@5 100.000 (99.245) +2022-11-14 16:00:51,272 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0744) Prec@1 87.000 (88.278) Prec@5 100.000 (99.259) +2022-11-14 16:00:51,291 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0748) Prec@1 85.000 (88.218) Prec@5 100.000 (99.273) +2022-11-14 16:00:51,306 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0747) Prec@1 89.000 (88.232) Prec@5 98.000 (99.250) +2022-11-14 16:00:51,324 Test: [56/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0749) Prec@1 86.000 (88.193) Prec@5 100.000 (99.263) +2022-11-14 16:00:51,340 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0748) Prec@1 89.000 (88.207) Prec@5 100.000 (99.276) +2022-11-14 16:00:51,356 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1171 (0.0755) Prec@1 83.000 (88.119) Prec@5 99.000 (99.271) +2022-11-14 16:00:51,372 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0757) Prec@1 86.000 (88.083) Prec@5 100.000 (99.283) +2022-11-14 16:00:51,390 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0758) Prec@1 87.000 (88.066) Prec@5 100.000 (99.295) +2022-11-14 16:00:51,406 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0757) Prec@1 87.000 (88.048) Prec@5 99.000 (99.290) +2022-11-14 16:00:51,421 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0756) Prec@1 88.000 (88.048) Prec@5 99.000 (99.286) +2022-11-14 16:00:51,438 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0349 (0.0750) Prec@1 94.000 (88.141) Prec@5 100.000 (99.297) +2022-11-14 16:00:51,455 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0751) Prec@1 84.000 (88.077) Prec@5 100.000 (99.308) +2022-11-14 16:00:51,475 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0755) Prec@1 81.000 (87.970) Prec@5 98.000 (99.288) +2022-11-14 16:00:51,489 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0317 (0.0749) Prec@1 95.000 (88.075) Prec@5 100.000 (99.299) +2022-11-14 16:00:51,504 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0750) Prec@1 88.000 (88.074) Prec@5 98.000 (99.279) +2022-11-14 16:00:51,519 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0750) Prec@1 88.000 (88.072) Prec@5 99.000 (99.275) +2022-11-14 16:00:51,536 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0750) Prec@1 87.000 (88.057) Prec@5 99.000 (99.271) +2022-11-14 16:00:51,555 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0754) Prec@1 83.000 (87.986) Prec@5 99.000 (99.268) +2022-11-14 16:00:51,572 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0754) Prec@1 88.000 (87.986) Prec@5 100.000 (99.278) +2022-11-14 16:00:51,587 Test: [72/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0371 (0.0749) Prec@1 94.000 (88.068) Prec@5 100.000 (99.288) +2022-11-14 16:00:51,603 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0744) Prec@1 92.000 (88.122) Prec@5 100.000 (99.297) +2022-11-14 16:00:51,619 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0748) Prec@1 81.000 (88.027) Prec@5 100.000 (99.307) +2022-11-14 16:00:51,638 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0748) Prec@1 88.000 (88.026) Prec@5 99.000 (99.303) +2022-11-14 16:00:51,653 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0749) Prec@1 85.000 (87.987) Prec@5 98.000 (99.286) +2022-11-14 16:00:51,670 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0750) Prec@1 87.000 (87.974) Prec@5 99.000 (99.282) +2022-11-14 16:00:51,688 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0752) Prec@1 85.000 (87.937) Prec@5 100.000 (99.291) +2022-11-14 16:00:51,705 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0751) Prec@1 87.000 (87.925) Prec@5 100.000 (99.300) +2022-11-14 16:00:51,720 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0752) Prec@1 85.000 (87.889) Prec@5 99.000 (99.296) +2022-11-14 16:00:51,738 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0752) Prec@1 87.000 (87.878) Prec@5 100.000 (99.305) +2022-11-14 16:00:51,754 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0755) Prec@1 83.000 (87.819) Prec@5 98.000 (99.289) +2022-11-14 16:00:51,771 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0755) Prec@1 86.000 (87.798) Prec@5 99.000 (99.286) +2022-11-14 16:00:51,788 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0755) Prec@1 90.000 (87.824) Prec@5 98.000 (99.271) +2022-11-14 16:00:51,801 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.0759) Prec@1 84.000 (87.779) Prec@5 100.000 (99.279) +2022-11-14 16:00:51,814 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0759) Prec@1 86.000 (87.759) Prec@5 99.000 (99.276) +2022-11-14 16:00:51,830 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0758) Prec@1 89.000 (87.773) Prec@5 99.000 (99.273) +2022-11-14 16:00:51,849 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0758) Prec@1 87.000 (87.764) Prec@5 100.000 (99.281) +2022-11-14 16:00:51,863 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0758) Prec@1 89.000 (87.778) Prec@5 98.000 (99.267) +2022-11-14 16:00:51,880 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0755) Prec@1 92.000 (87.824) Prec@5 99.000 (99.264) +2022-11-14 16:00:51,897 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0753) Prec@1 89.000 (87.837) Prec@5 99.000 (99.261) +2022-11-14 16:00:51,916 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0754) Prec@1 85.000 (87.806) Prec@5 99.000 (99.258) +2022-11-14 16:00:51,936 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0754) Prec@1 86.000 (87.787) Prec@5 98.000 (99.245) +2022-11-14 16:00:51,952 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0755) Prec@1 87.000 (87.779) Prec@5 100.000 (99.253) +2022-11-14 16:00:51,969 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0753) Prec@1 91.000 (87.812) Prec@5 98.000 (99.240) +2022-11-14 16:00:51,985 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0752) Prec@1 90.000 (87.835) Prec@5 99.000 (99.237) +2022-11-14 16:00:51,999 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0752) Prec@1 85.000 (87.806) Prec@5 100.000 (99.245) +2022-11-14 16:00:52,012 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0755) Prec@1 85.000 (87.778) Prec@5 100.000 (99.253) +2022-11-14 16:00:52,030 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0754) Prec@1 92.000 (87.820) Prec@5 98.000 (99.240) +2022-11-14 16:00:52,092 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:00:52,425 Epoch: [292][0/500] Time 0.024 (0.024) Data 0.246 (0.246) Loss 0.0373 (0.0373) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:00:52,851 Epoch: [292][10/500] Time 0.050 (0.036) Data 0.002 (0.024) Loss 0.0266 (0.0320) Prec@1 96.000 (94.500) Prec@5 99.000 (99.500) +2022-11-14 16:00:53,330 Epoch: [292][20/500] Time 0.051 (0.039) Data 0.002 (0.014) Loss 0.0354 (0.0331) Prec@1 94.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:00:53,823 Epoch: [292][30/500] Time 0.052 (0.041) Data 0.002 (0.010) Loss 0.0267 (0.0315) Prec@1 95.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:00:54,300 Epoch: [292][40/500] Time 0.049 (0.042) Data 0.002 (0.008) Loss 0.0349 (0.0322) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:00:54,779 Epoch: [292][50/500] Time 0.040 (0.042) Data 0.002 (0.007) Loss 0.0267 (0.0313) Prec@1 95.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 16:00:55,246 Epoch: [292][60/500] Time 0.041 (0.042) Data 0.002 (0.006) Loss 0.0187 (0.0295) Prec@1 97.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:00:55,740 Epoch: [292][70/500] Time 0.049 (0.042) Data 0.002 (0.005) Loss 0.0557 (0.0328) Prec@1 90.000 (94.250) Prec@5 100.000 (99.875) +2022-11-14 16:00:56,235 Epoch: [292][80/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.0433 (0.0339) Prec@1 92.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 16:00:56,708 Epoch: [292][90/500] Time 0.046 (0.042) Data 0.002 (0.005) Loss 0.0375 (0.0343) Prec@1 94.000 (94.000) Prec@5 100.000 (99.900) +2022-11-14 16:00:57,200 Epoch: [292][100/500] Time 0.051 (0.043) Data 0.002 (0.004) Loss 0.0450 (0.0353) Prec@1 92.000 (93.818) Prec@5 98.000 (99.727) +2022-11-14 16:00:57,679 Epoch: [292][110/500] Time 0.039 (0.043) Data 0.002 (0.004) Loss 0.0239 (0.0343) Prec@1 96.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:00:58,156 Epoch: [292][120/500] Time 0.036 (0.043) Data 0.002 (0.004) Loss 0.0192 (0.0332) Prec@1 97.000 (94.231) Prec@5 100.000 (99.769) +2022-11-14 16:00:58,636 Epoch: [292][130/500] Time 0.041 (0.043) Data 0.003 (0.004) Loss 0.0272 (0.0327) Prec@1 97.000 (94.429) Prec@5 100.000 (99.786) +2022-11-14 16:00:59,138 Epoch: [292][140/500] Time 0.044 (0.043) Data 0.002 (0.004) Loss 0.0355 (0.0329) Prec@1 94.000 (94.400) Prec@5 99.000 (99.733) +2022-11-14 16:00:59,631 Epoch: [292][150/500] Time 0.050 (0.043) Data 0.002 (0.004) Loss 0.0598 (0.0346) Prec@1 91.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 16:01:00,111 Epoch: [292][160/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0225 (0.0339) Prec@1 98.000 (94.412) Prec@5 100.000 (99.765) +2022-11-14 16:01:00,579 Epoch: [292][170/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0313 (0.0337) Prec@1 95.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 16:01:01,073 Epoch: [292][180/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0547 (0.0348) Prec@1 91.000 (94.263) Prec@5 100.000 (99.789) +2022-11-14 16:01:01,550 Epoch: [292][190/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0173 (0.0340) Prec@1 96.000 (94.350) Prec@5 100.000 (99.800) +2022-11-14 16:01:02,046 Epoch: [292][200/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0310 (0.0338) Prec@1 95.000 (94.381) Prec@5 100.000 (99.810) +2022-11-14 16:01:02,527 Epoch: [292][210/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0209 (0.0332) Prec@1 96.000 (94.455) Prec@5 100.000 (99.818) +2022-11-14 16:01:03,018 Epoch: [292][220/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0392 (0.0335) Prec@1 93.000 (94.391) Prec@5 100.000 (99.826) +2022-11-14 16:01:03,516 Epoch: [292][230/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0451 (0.0340) Prec@1 92.000 (94.292) Prec@5 99.000 (99.792) +2022-11-14 16:01:04,005 Epoch: [292][240/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0396 (0.0342) Prec@1 94.000 (94.280) Prec@5 100.000 (99.800) +2022-11-14 16:01:04,471 Epoch: [292][250/500] Time 0.057 (0.043) Data 0.002 (0.003) Loss 0.0147 (0.0335) Prec@1 98.000 (94.423) Prec@5 100.000 (99.808) +2022-11-14 16:01:04,967 Epoch: [292][260/500] Time 0.034 (0.043) Data 0.002 (0.003) Loss 0.0270 (0.0332) Prec@1 95.000 (94.444) Prec@5 100.000 (99.815) +2022-11-14 16:01:05,457 Epoch: [292][270/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0484 (0.0338) Prec@1 89.000 (94.250) Prec@5 99.000 (99.786) +2022-11-14 16:01:05,960 Epoch: [292][280/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0238 (0.0334) Prec@1 95.000 (94.276) Prec@5 100.000 (99.793) +2022-11-14 16:01:06,459 Epoch: [292][290/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0152 (0.0328) Prec@1 97.000 (94.367) Prec@5 100.000 (99.800) +2022-11-14 16:01:06,937 Epoch: [292][300/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0249 (0.0326) Prec@1 98.000 (94.484) Prec@5 100.000 (99.806) +2022-11-14 16:01:07,412 Epoch: [292][310/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0517 (0.0332) Prec@1 92.000 (94.406) Prec@5 100.000 (99.812) +2022-11-14 16:01:07,915 Epoch: [292][320/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0384 (0.0333) Prec@1 93.000 (94.364) Prec@5 98.000 (99.758) +2022-11-14 16:01:08,394 Epoch: [292][330/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0191 (0.0329) Prec@1 98.000 (94.471) Prec@5 100.000 (99.765) +2022-11-14 16:01:08,885 Epoch: [292][340/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0495 (0.0334) Prec@1 92.000 (94.400) Prec@5 100.000 (99.771) +2022-11-14 16:01:09,366 Epoch: [292][350/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0407 (0.0336) Prec@1 93.000 (94.361) Prec@5 100.000 (99.778) +2022-11-14 16:01:09,870 Epoch: [292][360/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0253 (0.0333) Prec@1 97.000 (94.432) Prec@5 100.000 (99.784) +2022-11-14 16:01:10,363 Epoch: [292][370/500] Time 0.052 (0.043) Data 0.003 (0.003) Loss 0.0347 (0.0334) Prec@1 94.000 (94.421) Prec@5 100.000 (99.789) +2022-11-14 16:01:10,839 Epoch: [292][380/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0324 (0.0334) Prec@1 94.000 (94.410) Prec@5 100.000 (99.795) +2022-11-14 16:01:11,332 Epoch: [292][390/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0575 (0.0340) Prec@1 93.000 (94.375) Prec@5 100.000 (99.800) +2022-11-14 16:01:11,811 Epoch: [292][400/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0406 (0.0341) Prec@1 94.000 (94.366) Prec@5 99.000 (99.780) +2022-11-14 16:01:12,321 Epoch: [292][410/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0148 (0.0337) Prec@1 97.000 (94.429) Prec@5 100.000 (99.786) +2022-11-14 16:01:12,803 Epoch: [292][420/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0460 (0.0340) Prec@1 92.000 (94.372) Prec@5 99.000 (99.767) +2022-11-14 16:01:13,288 Epoch: [292][430/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0392 (0.0341) Prec@1 94.000 (94.364) Prec@5 100.000 (99.773) +2022-11-14 16:01:13,775 Epoch: [292][440/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0427 (0.0343) Prec@1 92.000 (94.311) Prec@5 100.000 (99.778) +2022-11-14 16:01:14,251 Epoch: [292][450/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0172 (0.0339) Prec@1 98.000 (94.391) Prec@5 100.000 (99.783) +2022-11-14 16:01:14,747 Epoch: [292][460/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0300 (0.0338) Prec@1 94.000 (94.383) Prec@5 100.000 (99.787) +2022-11-14 16:01:15,235 Epoch: [292][470/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0391 (0.0339) Prec@1 93.000 (94.354) Prec@5 99.000 (99.771) +2022-11-14 16:01:15,725 Epoch: [292][480/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0482 (0.0342) Prec@1 93.000 (94.327) Prec@5 100.000 (99.776) +2022-11-14 16:01:16,220 Epoch: [292][490/500] Time 0.035 (0.043) Data 0.003 (0.003) Loss 0.0359 (0.0342) Prec@1 94.000 (94.320) Prec@5 99.000 (99.760) +2022-11-14 16:01:16,673 Epoch: [292][499/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0280 (0.0341) Prec@1 96.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 16:01:16,989 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0757 (0.0757) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:01:17,000 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0763) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:01:17,009 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0719) Prec@1 91.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:01:17,023 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0713) Prec@1 91.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 16:01:17,033 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0730) Prec@1 86.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 16:01:17,043 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0675) Prec@1 94.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 16:01:17,053 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0665) Prec@1 91.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 16:01:17,068 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0689) Prec@1 85.000 (88.750) Prec@5 100.000 (99.875) +2022-11-14 16:01:17,080 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0715) Prec@1 85.000 (88.333) Prec@5 98.000 (99.667) +2022-11-14 16:01:17,094 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0709) Prec@1 89.000 (88.400) Prec@5 98.000 (99.500) +2022-11-14 16:01:17,107 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0690) Prec@1 93.000 (88.818) Prec@5 100.000 (99.545) +2022-11-14 16:01:17,123 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0692) Prec@1 89.000 (88.833) Prec@5 99.000 (99.500) +2022-11-14 16:01:17,139 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0679) Prec@1 91.000 (89.000) Prec@5 100.000 (99.538) +2022-11-14 16:01:17,155 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0680) Prec@1 89.000 (89.000) Prec@5 98.000 (99.429) +2022-11-14 16:01:17,171 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0671) Prec@1 91.000 (89.133) Prec@5 100.000 (99.467) +2022-11-14 16:01:17,186 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0670) Prec@1 91.000 (89.250) Prec@5 99.000 (99.438) +2022-11-14 16:01:17,201 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0665) Prec@1 89.000 (89.235) Prec@5 98.000 (99.353) +2022-11-14 16:01:17,218 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0678) Prec@1 88.000 (89.167) Prec@5 100.000 (99.389) +2022-11-14 16:01:17,234 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0688) Prec@1 84.000 (88.895) Prec@5 100.000 (99.421) +2022-11-14 16:01:17,249 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0703) Prec@1 84.000 (88.650) Prec@5 98.000 (99.350) +2022-11-14 16:01:17,266 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0705) Prec@1 88.000 (88.619) Prec@5 99.000 (99.333) +2022-11-14 16:01:17,281 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0710) Prec@1 88.000 (88.591) Prec@5 99.000 (99.318) +2022-11-14 16:01:17,293 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0719) Prec@1 86.000 (88.478) Prec@5 98.000 (99.261) +2022-11-14 16:01:17,309 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0718) Prec@1 87.000 (88.417) Prec@5 100.000 (99.292) +2022-11-14 16:01:17,329 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0721) Prec@1 90.000 (88.480) Prec@5 99.000 (99.280) +2022-11-14 16:01:17,344 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0729) Prec@1 88.000 (88.462) Prec@5 99.000 (99.269) +2022-11-14 16:01:17,363 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0725) Prec@1 88.000 (88.444) Prec@5 100.000 (99.296) +2022-11-14 16:01:17,382 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0718) Prec@1 90.000 (88.500) Prec@5 100.000 (99.321) +2022-11-14 16:01:17,398 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0715) Prec@1 89.000 (88.517) Prec@5 99.000 (99.310) +2022-11-14 16:01:17,413 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0710) Prec@1 92.000 (88.633) Prec@5 100.000 (99.333) +2022-11-14 16:01:17,432 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0715) Prec@1 85.000 (88.516) Prec@5 99.000 (99.323) +2022-11-14 16:01:17,451 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0720) Prec@1 87.000 (88.469) Prec@5 99.000 (99.312) +2022-11-14 16:01:17,469 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0722) Prec@1 85.000 (88.364) Prec@5 100.000 (99.333) +2022-11-14 16:01:17,484 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0724) Prec@1 89.000 (88.382) Prec@5 100.000 (99.353) +2022-11-14 16:01:17,498 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0730) Prec@1 85.000 (88.286) Prec@5 98.000 (99.314) +2022-11-14 16:01:17,513 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0729) Prec@1 90.000 (88.333) Prec@5 99.000 (99.306) +2022-11-14 16:01:17,530 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0731) Prec@1 88.000 (88.324) Prec@5 100.000 (99.324) +2022-11-14 16:01:17,545 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0736) Prec@1 87.000 (88.289) Prec@5 100.000 (99.342) +2022-11-14 16:01:17,562 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0729) Prec@1 94.000 (88.436) Prec@5 100.000 (99.359) +2022-11-14 16:01:17,580 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0728) Prec@1 89.000 (88.450) Prec@5 99.000 (99.350) +2022-11-14 16:01:17,598 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0729) Prec@1 87.000 (88.415) Prec@5 99.000 (99.341) +2022-11-14 16:01:17,613 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 87.000 (88.381) Prec@5 100.000 (99.357) +2022-11-14 16:01:17,628 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0725) Prec@1 92.000 (88.465) Prec@5 100.000 (99.372) +2022-11-14 16:01:17,646 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0725) Prec@1 87.000 (88.432) Prec@5 98.000 (99.341) +2022-11-14 16:01:17,663 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0725) Prec@1 88.000 (88.422) Prec@5 99.000 (99.333) +2022-11-14 16:01:17,677 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0734) Prec@1 81.000 (88.261) Prec@5 98.000 (99.304) +2022-11-14 16:01:17,695 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0732) Prec@1 86.000 (88.213) Prec@5 100.000 (99.319) +2022-11-14 16:01:17,712 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1228 (0.0742) Prec@1 80.000 (88.042) Prec@5 97.000 (99.271) +2022-11-14 16:01:17,727 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0446 (0.0736) Prec@1 91.000 (88.102) Prec@5 100.000 (99.286) +2022-11-14 16:01:17,742 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0739) Prec@1 89.000 (88.120) Prec@5 100.000 (99.300) +2022-11-14 16:01:17,758 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0742) Prec@1 86.000 (88.078) Prec@5 100.000 (99.314) +2022-11-14 16:01:17,776 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0747) Prec@1 81.000 (87.942) Prec@5 100.000 (99.327) +2022-11-14 16:01:17,791 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0743) Prec@1 90.000 (87.981) Prec@5 100.000 (99.340) +2022-11-14 16:01:17,807 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0740) Prec@1 90.000 (88.019) Prec@5 99.000 (99.333) +2022-11-14 16:01:17,823 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0741) Prec@1 85.000 (87.964) Prec@5 100.000 (99.345) +2022-11-14 16:01:17,840 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0745) Prec@1 86.000 (87.929) Prec@5 98.000 (99.321) +2022-11-14 16:01:17,856 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0744) Prec@1 89.000 (87.947) Prec@5 100.000 (99.333) +2022-11-14 16:01:17,872 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0744) Prec@1 90.000 (87.983) Prec@5 99.000 (99.328) +2022-11-14 16:01:17,888 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0745) Prec@1 88.000 (87.983) Prec@5 100.000 (99.339) +2022-11-14 16:01:17,909 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0745) Prec@1 86.000 (87.950) Prec@5 100.000 (99.350) +2022-11-14 16:01:17,927 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0745) Prec@1 88.000 (87.951) Prec@5 99.000 (99.344) +2022-11-14 16:01:17,943 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0744) Prec@1 87.000 (87.935) Prec@5 100.000 (99.355) +2022-11-14 16:01:17,959 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0740) Prec@1 91.000 (87.984) Prec@5 100.000 (99.365) +2022-11-14 16:01:17,977 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0328 (0.0733) Prec@1 94.000 (88.078) Prec@5 99.000 (99.359) +2022-11-14 16:01:17,992 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0736) Prec@1 85.000 (88.031) Prec@5 100.000 (99.369) +2022-11-14 16:01:18,008 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0739) Prec@1 84.000 (87.970) Prec@5 99.000 (99.364) +2022-11-14 16:01:18,024 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0298 (0.0732) Prec@1 95.000 (88.075) Prec@5 100.000 (99.373) +2022-11-14 16:01:18,039 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0734) Prec@1 88.000 (88.074) Prec@5 98.000 (99.353) +2022-11-14 16:01:18,056 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0734) Prec@1 87.000 (88.058) Prec@5 100.000 (99.362) +2022-11-14 16:01:18,072 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0735) Prec@1 88.000 (88.057) Prec@5 99.000 (99.357) +2022-11-14 16:01:18,089 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0739) Prec@1 86.000 (88.028) Prec@5 98.000 (99.338) +2022-11-14 16:01:18,106 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0739) Prec@1 89.000 (88.042) Prec@5 100.000 (99.347) +2022-11-14 16:01:18,120 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0735) Prec@1 93.000 (88.110) Prec@5 99.000 (99.342) +2022-11-14 16:01:18,135 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0731) Prec@1 93.000 (88.176) Prec@5 100.000 (99.351) +2022-11-14 16:01:18,153 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0735) Prec@1 86.000 (88.147) Prec@5 100.000 (99.360) +2022-11-14 16:01:18,170 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0735) Prec@1 87.000 (88.132) Prec@5 100.000 (99.368) +2022-11-14 16:01:18,188 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0736) Prec@1 87.000 (88.117) Prec@5 99.000 (99.364) +2022-11-14 16:01:18,205 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0739) Prec@1 84.000 (88.064) Prec@5 99.000 (99.359) +2022-11-14 16:01:18,220 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0742) Prec@1 85.000 (88.025) Prec@5 100.000 (99.367) +2022-11-14 16:01:18,235 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0742) Prec@1 89.000 (88.037) Prec@5 99.000 (99.362) +2022-11-14 16:01:18,250 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0741) Prec@1 88.000 (88.037) Prec@5 99.000 (99.358) +2022-11-14 16:01:18,271 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0745) Prec@1 83.000 (87.976) Prec@5 99.000 (99.354) +2022-11-14 16:01:18,289 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0747) Prec@1 84.000 (87.928) Prec@5 98.000 (99.337) +2022-11-14 16:01:18,305 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0747) Prec@1 88.000 (87.929) Prec@5 98.000 (99.321) +2022-11-14 16:01:18,321 Test: [84/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0749) Prec@1 82.000 (87.859) Prec@5 100.000 (99.329) +2022-11-14 16:01:18,336 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0750) Prec@1 86.000 (87.837) Prec@5 100.000 (99.337) +2022-11-14 16:01:18,351 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0749) Prec@1 89.000 (87.851) Prec@5 100.000 (99.345) +2022-11-14 16:01:18,369 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0747) Prec@1 91.000 (87.886) Prec@5 99.000 (99.341) +2022-11-14 16:01:18,387 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0745) Prec@1 91.000 (87.921) Prec@5 100.000 (99.348) +2022-11-14 16:01:18,404 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0744) Prec@1 88.000 (87.922) Prec@5 98.000 (99.333) +2022-11-14 16:01:18,419 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0742) Prec@1 91.000 (87.956) Prec@5 100.000 (99.341) +2022-11-14 16:01:18,432 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0465 (0.0739) Prec@1 93.000 (88.011) Prec@5 99.000 (99.337) +2022-11-14 16:01:18,448 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0741) Prec@1 85.000 (87.978) Prec@5 99.000 (99.333) +2022-11-14 16:01:18,462 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0741) Prec@1 89.000 (87.989) Prec@5 98.000 (99.319) +2022-11-14 16:01:18,481 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0741) Prec@1 90.000 (88.011) Prec@5 100.000 (99.326) +2022-11-14 16:01:18,496 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0739) Prec@1 91.000 (88.042) Prec@5 98.000 (99.312) +2022-11-14 16:01:18,514 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0738) Prec@1 90.000 (88.062) Prec@5 97.000 (99.289) +2022-11-14 16:01:18,528 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0738) Prec@1 89.000 (88.071) Prec@5 98.000 (99.276) +2022-11-14 16:01:18,547 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0740) Prec@1 85.000 (88.040) Prec@5 100.000 (99.283) +2022-11-14 16:01:18,564 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0741) Prec@1 85.000 (88.010) Prec@5 100.000 (99.290) +2022-11-14 16:01:18,647 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:01:18,998 Epoch: [293][0/500] Time 0.026 (0.026) Data 0.259 (0.259) Loss 0.0197 (0.0197) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:01:19,431 Epoch: [293][10/500] Time 0.045 (0.037) Data 0.002 (0.026) Loss 0.0339 (0.0268) Prec@1 93.000 (94.500) Prec@5 98.000 (99.000) +2022-11-14 16:01:19,908 Epoch: [293][20/500] Time 0.042 (0.040) Data 0.002 (0.014) Loss 0.0374 (0.0303) Prec@1 93.000 (94.000) Prec@5 100.000 (99.333) +2022-11-14 16:01:20,401 Epoch: [293][30/500] Time 0.048 (0.041) Data 0.002 (0.010) Loss 0.0228 (0.0285) Prec@1 97.000 (94.750) Prec@5 100.000 (99.500) +2022-11-14 16:01:20,888 Epoch: [293][40/500] Time 0.055 (0.041) Data 0.002 (0.008) Loss 0.0170 (0.0262) Prec@1 96.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 16:01:21,397 Epoch: [293][50/500] Time 0.047 (0.042) Data 0.002 (0.007) Loss 0.0413 (0.0287) Prec@1 92.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 16:01:21,866 Epoch: [293][60/500] Time 0.049 (0.042) Data 0.002 (0.006) Loss 0.0365 (0.0298) Prec@1 93.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 16:01:22,366 Epoch: [293][70/500] Time 0.052 (0.042) Data 0.002 (0.006) Loss 0.0380 (0.0308) Prec@1 94.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:01:22,852 Epoch: [293][80/500] Time 0.045 (0.042) Data 0.002 (0.005) Loss 0.0174 (0.0293) Prec@1 98.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 16:01:23,333 Epoch: [293][90/500] Time 0.045 (0.043) Data 0.002 (0.005) Loss 0.0277 (0.0292) Prec@1 98.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 16:01:23,828 Epoch: [293][100/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.0287 (0.0291) Prec@1 95.000 (95.000) Prec@5 100.000 (99.818) +2022-11-14 16:01:24,307 Epoch: [293][110/500] Time 0.045 (0.043) Data 0.002 (0.004) Loss 0.0283 (0.0291) Prec@1 97.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:01:24,799 Epoch: [293][120/500] Time 0.044 (0.043) Data 0.003 (0.004) Loss 0.0394 (0.0298) Prec@1 95.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 16:01:25,270 Epoch: [293][130/500] Time 0.045 (0.043) Data 0.002 (0.004) Loss 0.0189 (0.0291) Prec@1 97.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:01:25,756 Epoch: [293][140/500] Time 0.040 (0.043) Data 0.002 (0.004) Loss 0.0293 (0.0291) Prec@1 96.000 (95.333) Prec@5 100.000 (99.867) +2022-11-14 16:01:26,245 Epoch: [293][150/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.0233 (0.0287) Prec@1 96.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:01:26,727 Epoch: [293][160/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0339 (0.0290) Prec@1 94.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 16:01:27,207 Epoch: [293][170/500] Time 0.037 (0.043) Data 0.002 (0.004) Loss 0.0378 (0.0295) Prec@1 95.000 (95.278) Prec@5 100.000 (99.889) +2022-11-14 16:01:27,688 Epoch: [293][180/500] Time 0.050 (0.043) Data 0.002 (0.004) Loss 0.0391 (0.0300) Prec@1 93.000 (95.158) Prec@5 100.000 (99.895) +2022-11-14 16:01:28,186 Epoch: [293][190/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0154 (0.0293) Prec@1 97.000 (95.250) Prec@5 100.000 (99.900) +2022-11-14 16:01:28,683 Epoch: [293][200/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0105 (0.0284) Prec@1 98.000 (95.381) Prec@5 100.000 (99.905) +2022-11-14 16:01:29,181 Epoch: [293][210/500] Time 0.050 (0.043) Data 0.003 (0.003) Loss 0.0465 (0.0292) Prec@1 90.000 (95.136) Prec@5 100.000 (99.909) +2022-11-14 16:01:29,683 Epoch: [293][220/500] Time 0.053 (0.043) Data 0.002 (0.003) Loss 0.0450 (0.0299) Prec@1 93.000 (95.043) Prec@5 100.000 (99.913) +2022-11-14 16:01:30,182 Epoch: [293][230/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0366 (0.0302) Prec@1 96.000 (95.083) Prec@5 100.000 (99.917) +2022-11-14 16:01:30,684 Epoch: [293][240/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0443 (0.0307) Prec@1 93.000 (95.000) Prec@5 99.000 (99.880) +2022-11-14 16:01:31,176 Epoch: [293][250/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0417 (0.0312) Prec@1 91.000 (94.846) Prec@5 100.000 (99.885) +2022-11-14 16:01:31,668 Epoch: [293][260/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0206 (0.0308) Prec@1 98.000 (94.963) Prec@5 100.000 (99.889) +2022-11-14 16:01:32,168 Epoch: [293][270/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0205 (0.0304) Prec@1 96.000 (95.000) Prec@5 100.000 (99.893) +2022-11-14 16:01:32,650 Epoch: [293][280/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0517 (0.0311) Prec@1 92.000 (94.897) Prec@5 99.000 (99.862) +2022-11-14 16:01:33,144 Epoch: [293][290/500] Time 0.034 (0.043) Data 0.003 (0.003) Loss 0.0241 (0.0309) Prec@1 96.000 (94.933) Prec@5 100.000 (99.867) +2022-11-14 16:01:33,636 Epoch: [293][300/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0189 (0.0305) Prec@1 96.000 (94.968) Prec@5 100.000 (99.871) +2022-11-14 16:01:34,137 Epoch: [293][310/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0157 (0.0301) Prec@1 98.000 (95.062) Prec@5 100.000 (99.875) +2022-11-14 16:01:34,631 Epoch: [293][320/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0284 (0.0300) Prec@1 96.000 (95.091) Prec@5 99.000 (99.848) +2022-11-14 16:01:35,117 Epoch: [293][330/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0325 (0.0301) Prec@1 94.000 (95.059) Prec@5 100.000 (99.853) +2022-11-14 16:01:35,612 Epoch: [293][340/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0311 (0.0301) Prec@1 95.000 (95.057) Prec@5 100.000 (99.857) +2022-11-14 16:01:36,115 Epoch: [293][350/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0441 (0.0305) Prec@1 93.000 (95.000) Prec@5 100.000 (99.861) +2022-11-14 16:01:36,613 Epoch: [293][360/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0446 (0.0309) Prec@1 94.000 (94.973) Prec@5 100.000 (99.865) +2022-11-14 16:01:37,103 Epoch: [293][370/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0453 (0.0313) Prec@1 90.000 (94.842) Prec@5 100.000 (99.868) +2022-11-14 16:01:37,585 Epoch: [293][380/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0264 (0.0311) Prec@1 95.000 (94.846) Prec@5 100.000 (99.872) +2022-11-14 16:01:38,069 Epoch: [293][390/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0252 (0.0310) Prec@1 96.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 16:01:38,763 Epoch: [293][400/500] Time 0.087 (0.044) Data 0.002 (0.003) Loss 0.0186 (0.0307) Prec@1 97.000 (94.927) Prec@5 100.000 (99.878) +2022-11-14 16:01:39,575 Epoch: [293][410/500] Time 0.087 (0.045) Data 0.002 (0.003) Loss 0.0306 (0.0307) Prec@1 94.000 (94.905) Prec@5 100.000 (99.881) +2022-11-14 16:01:40,333 Epoch: [293][420/500] Time 0.070 (0.045) Data 0.002 (0.003) Loss 0.0313 (0.0307) Prec@1 94.000 (94.884) Prec@5 100.000 (99.884) +2022-11-14 16:01:41,125 Epoch: [293][430/500] Time 0.090 (0.046) Data 0.002 (0.003) Loss 0.0251 (0.0306) Prec@1 96.000 (94.909) Prec@5 100.000 (99.886) +2022-11-14 16:01:42,083 Epoch: [293][440/500] Time 0.143 (0.047) Data 0.002 (0.003) Loss 0.0473 (0.0309) Prec@1 91.000 (94.822) Prec@5 100.000 (99.889) +2022-11-14 16:01:42,993 Epoch: [293][450/500] Time 0.080 (0.047) Data 0.002 (0.003) Loss 0.0459 (0.0313) Prec@1 93.000 (94.783) Prec@5 100.000 (99.891) +2022-11-14 16:01:43,828 Epoch: [293][460/500] Time 0.094 (0.048) Data 0.002 (0.003) Loss 0.0224 (0.0311) Prec@1 97.000 (94.830) Prec@5 100.000 (99.894) +2022-11-14 16:01:44,686 Epoch: [293][470/500] Time 0.094 (0.049) Data 0.002 (0.003) Loss 0.0676 (0.0318) Prec@1 87.000 (94.667) Prec@5 100.000 (99.896) +2022-11-14 16:01:45,485 Epoch: [293][480/500] Time 0.076 (0.049) Data 0.002 (0.003) Loss 0.0414 (0.0320) Prec@1 94.000 (94.653) Prec@5 100.000 (99.898) +2022-11-14 16:01:46,245 Epoch: [293][490/500] Time 0.068 (0.049) Data 0.002 (0.003) Loss 0.0361 (0.0321) Prec@1 95.000 (94.660) Prec@5 99.000 (99.880) +2022-11-14 16:01:47,051 Epoch: [293][499/500] Time 0.074 (0.050) Data 0.002 (0.003) Loss 0.0285 (0.0320) Prec@1 95.000 (94.667) Prec@5 99.000 (99.863) +2022-11-14 16:01:47,392 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0783 (0.0783) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:01:47,403 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0894 (0.0839) Prec@1 87.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 16:01:47,413 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0763) Prec@1 90.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:01:47,427 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0742) Prec@1 91.000 (89.000) Prec@5 100.000 (99.750) +2022-11-14 16:01:47,439 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.0769) Prec@1 86.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 16:01:47,453 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0370 (0.0702) Prec@1 94.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 16:01:47,463 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0695) Prec@1 89.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 16:01:47,479 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0727) Prec@1 85.000 (88.750) Prec@5 100.000 (99.875) +2022-11-14 16:01:47,493 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0737) Prec@1 87.000 (88.556) Prec@5 99.000 (99.778) +2022-11-14 16:01:47,513 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0743) Prec@1 88.000 (88.500) Prec@5 97.000 (99.500) +2022-11-14 16:01:47,535 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0738) Prec@1 87.000 (88.364) Prec@5 100.000 (99.545) +2022-11-14 16:01:47,548 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0752) Prec@1 84.000 (88.000) Prec@5 100.000 (99.583) +2022-11-14 16:01:47,563 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0739) Prec@1 89.000 (88.077) Prec@5 100.000 (99.615) +2022-11-14 16:01:47,583 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0747) Prec@1 87.000 (88.000) Prec@5 100.000 (99.643) +2022-11-14 16:01:47,605 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0733) Prec@1 89.000 (88.067) Prec@5 100.000 (99.667) +2022-11-14 16:01:47,623 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0743) Prec@1 84.000 (87.812) Prec@5 99.000 (99.625) +2022-11-14 16:01:47,644 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0731) Prec@1 91.000 (88.000) Prec@5 98.000 (99.529) +2022-11-14 16:01:47,667 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0747) Prec@1 83.000 (87.722) Prec@5 100.000 (99.556) +2022-11-14 16:01:47,688 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0747) Prec@1 86.000 (87.632) Prec@5 100.000 (99.579) +2022-11-14 16:01:47,709 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0766) Prec@1 82.000 (87.350) Prec@5 97.000 (99.450) +2022-11-14 16:01:47,726 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0768) Prec@1 85.000 (87.238) Prec@5 100.000 (99.476) +2022-11-14 16:01:47,750 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0766) Prec@1 90.000 (87.364) Prec@5 98.000 (99.409) +2022-11-14 16:01:47,771 Test: [22/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0774) Prec@1 84.000 (87.217) Prec@5 100.000 (99.435) +2022-11-14 16:01:47,799 Test: [23/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0772) Prec@1 89.000 (87.292) Prec@5 100.000 (99.458) +2022-11-14 16:01:47,826 Test: [24/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1159 (0.0787) Prec@1 83.000 (87.120) Prec@5 99.000 (99.440) +2022-11-14 16:01:47,852 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0902 (0.0792) Prec@1 85.000 (87.038) Prec@5 99.000 (99.423) +2022-11-14 16:01:47,875 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0497 (0.0781) Prec@1 94.000 (87.296) Prec@5 100.000 (99.444) +2022-11-14 16:01:47,900 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0780) Prec@1 89.000 (87.357) Prec@5 99.000 (99.429) +2022-11-14 16:01:47,925 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0508 (0.0771) Prec@1 94.000 (87.586) Prec@5 99.000 (99.414) +2022-11-14 16:01:47,949 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0770) Prec@1 89.000 (87.633) Prec@5 99.000 (99.400) +2022-11-14 16:01:47,973 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0767) Prec@1 88.000 (87.645) Prec@5 100.000 (99.419) +2022-11-14 16:01:47,998 Test: [31/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0766) Prec@1 89.000 (87.688) Prec@5 98.000 (99.375) +2022-11-14 16:01:48,021 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0768) Prec@1 85.000 (87.606) Prec@5 100.000 (99.394) +2022-11-14 16:01:48,048 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1066 (0.0777) Prec@1 83.000 (87.471) Prec@5 99.000 (99.382) +2022-11-14 16:01:48,069 Test: [34/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0780) Prec@1 85.000 (87.400) Prec@5 98.000 (99.343) +2022-11-14 16:01:48,089 Test: [35/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0780) Prec@1 88.000 (87.417) Prec@5 100.000 (99.361) +2022-11-14 16:01:48,110 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0780) Prec@1 89.000 (87.459) Prec@5 99.000 (99.351) +2022-11-14 16:01:48,127 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1128 (0.0789) Prec@1 85.000 (87.395) Prec@5 100.000 (99.368) +2022-11-14 16:01:48,142 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0785) Prec@1 91.000 (87.487) Prec@5 99.000 (99.359) +2022-11-14 16:01:48,163 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0785) Prec@1 87.000 (87.475) Prec@5 99.000 (99.350) +2022-11-14 16:01:48,188 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0917 (0.0788) Prec@1 82.000 (87.341) Prec@5 99.000 (99.341) +2022-11-14 16:01:48,211 Test: [41/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0787) Prec@1 90.000 (87.405) Prec@5 99.000 (99.333) +2022-11-14 16:01:48,231 Test: [42/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0480 (0.0780) Prec@1 91.000 (87.488) Prec@5 98.000 (99.302) +2022-11-14 16:01:48,251 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0780) Prec@1 88.000 (87.500) Prec@5 98.000 (99.273) +2022-11-14 16:01:48,272 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0580 (0.0776) Prec@1 92.000 (87.600) Prec@5 100.000 (99.289) +2022-11-14 16:01:48,294 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0918 (0.0779) Prec@1 85.000 (87.543) Prec@5 99.000 (99.283) +2022-11-14 16:01:48,318 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0596 (0.0775) Prec@1 90.000 (87.596) Prec@5 99.000 (99.277) +2022-11-14 16:01:48,343 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0777) Prec@1 85.000 (87.542) Prec@5 100.000 (99.292) +2022-11-14 16:01:48,368 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0414 (0.0770) Prec@1 93.000 (87.653) Prec@5 100.000 (99.306) +2022-11-14 16:01:48,394 Test: [49/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1016 (0.0775) Prec@1 85.000 (87.600) Prec@5 100.000 (99.320) +2022-11-14 16:01:48,418 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0774) Prec@1 87.000 (87.588) Prec@5 100.000 (99.333) +2022-11-14 16:01:48,442 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.0778) Prec@1 84.000 (87.519) Prec@5 100.000 (99.346) +2022-11-14 16:01:48,464 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0776) Prec@1 88.000 (87.528) Prec@5 100.000 (99.358) +2022-11-14 16:01:48,488 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0775) Prec@1 89.000 (87.556) Prec@5 99.000 (99.352) +2022-11-14 16:01:48,515 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0777) Prec@1 85.000 (87.509) Prec@5 100.000 (99.364) +2022-11-14 16:01:48,541 Test: [55/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0774) Prec@1 91.000 (87.571) Prec@5 99.000 (99.357) +2022-11-14 16:01:48,565 Test: [56/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0774) Prec@1 86.000 (87.544) Prec@5 98.000 (99.333) +2022-11-14 16:01:48,591 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0774) Prec@1 90.000 (87.586) Prec@5 98.000 (99.310) +2022-11-14 16:01:48,612 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1316 (0.0783) Prec@1 80.000 (87.458) Prec@5 99.000 (99.305) +2022-11-14 16:01:48,640 Test: [59/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.0784) Prec@1 86.000 (87.433) Prec@5 99.000 (99.300) +2022-11-14 16:01:48,662 Test: [60/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0785) Prec@1 86.000 (87.410) Prec@5 100.000 (99.311) +2022-11-14 16:01:48,686 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0782) Prec@1 88.000 (87.419) Prec@5 100.000 (99.323) +2022-11-14 16:01:48,711 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0593 (0.0779) Prec@1 92.000 (87.492) Prec@5 99.000 (99.317) +2022-11-14 16:01:48,736 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0459 (0.0774) Prec@1 94.000 (87.594) Prec@5 100.000 (99.328) +2022-11-14 16:01:48,762 Test: [64/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0910 (0.0776) Prec@1 88.000 (87.600) Prec@5 100.000 (99.338) +2022-11-14 16:01:48,785 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0775) Prec@1 87.000 (87.591) Prec@5 100.000 (99.348) +2022-11-14 16:01:48,805 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0467 (0.0770) Prec@1 91.000 (87.642) Prec@5 100.000 (99.358) +2022-11-14 16:01:48,822 Test: [67/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0686 (0.0769) Prec@1 91.000 (87.691) Prec@5 99.000 (99.353) +2022-11-14 16:01:48,842 Test: [68/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0525 (0.0765) Prec@1 92.000 (87.754) Prec@5 99.000 (99.348) +2022-11-14 16:01:48,863 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0946 (0.0768) Prec@1 84.000 (87.700) Prec@5 100.000 (99.357) +2022-11-14 16:01:48,884 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0910 (0.0770) Prec@1 87.000 (87.690) Prec@5 99.000 (99.352) +2022-11-14 16:01:48,907 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0577 (0.0767) Prec@1 91.000 (87.736) Prec@5 99.000 (99.347) +2022-11-14 16:01:48,924 Test: [72/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0766) Prec@1 91.000 (87.781) Prec@5 100.000 (99.356) +2022-11-14 16:01:48,943 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0399 (0.0761) Prec@1 95.000 (87.878) Prec@5 99.000 (99.351) +2022-11-14 16:01:48,964 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1024 (0.0765) Prec@1 83.000 (87.813) Prec@5 99.000 (99.347) +2022-11-14 16:01:48,985 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0764) Prec@1 89.000 (87.829) Prec@5 99.000 (99.342) +2022-11-14 16:01:49,005 Test: [76/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0763) Prec@1 89.000 (87.844) Prec@5 100.000 (99.351) +2022-11-14 16:01:49,027 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1072 (0.0767) Prec@1 83.000 (87.782) Prec@5 98.000 (99.333) +2022-11-14 16:01:49,044 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0766) Prec@1 89.000 (87.797) Prec@5 99.000 (99.329) +2022-11-14 16:01:49,062 Test: [79/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0965 (0.0768) Prec@1 85.000 (87.763) Prec@5 100.000 (99.338) +2022-11-14 16:01:49,084 Test: [80/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0769) Prec@1 89.000 (87.778) Prec@5 99.000 (99.333) +2022-11-14 16:01:49,105 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0997 (0.0772) Prec@1 82.000 (87.707) Prec@5 100.000 (99.341) +2022-11-14 16:01:49,126 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1026 (0.0775) Prec@1 86.000 (87.687) Prec@5 98.000 (99.325) +2022-11-14 16:01:49,152 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0774) Prec@1 88.000 (87.690) Prec@5 98.000 (99.310) +2022-11-14 16:01:49,176 Test: [84/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0774) Prec@1 85.000 (87.659) Prec@5 99.000 (99.306) +2022-11-14 16:01:49,203 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0776) Prec@1 88.000 (87.663) Prec@5 100.000 (99.314) +2022-11-14 16:01:49,230 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0776) Prec@1 88.000 (87.667) Prec@5 100.000 (99.322) +2022-11-14 16:01:49,257 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0778) Prec@1 86.000 (87.648) Prec@5 98.000 (99.307) +2022-11-14 16:01:49,282 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0777) Prec@1 87.000 (87.640) Prec@5 100.000 (99.315) +2022-11-14 16:01:49,309 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0776) Prec@1 91.000 (87.678) Prec@5 99.000 (99.311) +2022-11-14 16:01:49,332 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0454 (0.0772) Prec@1 93.000 (87.736) Prec@5 100.000 (99.319) +2022-11-14 16:01:49,356 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0770) Prec@1 91.000 (87.772) Prec@5 100.000 (99.326) +2022-11-14 16:01:49,377 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0770) Prec@1 88.000 (87.774) Prec@5 99.000 (99.323) +2022-11-14 16:01:49,402 Test: [93/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0770) Prec@1 88.000 (87.777) Prec@5 98.000 (99.309) +2022-11-14 16:01:49,428 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0771) Prec@1 88.000 (87.779) Prec@5 100.000 (99.316) +2022-11-14 16:01:49,453 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0681 (0.0770) Prec@1 89.000 (87.792) Prec@5 99.000 (99.312) +2022-11-14 16:01:49,478 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0474 (0.0767) Prec@1 92.000 (87.835) Prec@5 99.000 (99.309) +2022-11-14 16:01:49,503 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1029 (0.0769) Prec@1 83.000 (87.786) Prec@5 99.000 (99.306) +2022-11-14 16:01:49,523 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0772) Prec@1 85.000 (87.758) Prec@5 100.000 (99.313) +2022-11-14 16:01:49,540 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0772) Prec@1 85.000 (87.730) Prec@5 100.000 (99.320) +2022-11-14 16:01:49,610 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:01:49,994 Epoch: [294][0/500] Time 0.025 (0.025) Data 0.287 (0.287) Loss 0.0458 (0.0458) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 16:01:50,261 Epoch: [294][10/500] Time 0.024 (0.024) Data 0.002 (0.028) Loss 0.0187 (0.0323) Prec@1 98.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 16:01:50,524 Epoch: [294][20/500] Time 0.025 (0.024) Data 0.002 (0.015) Loss 0.0566 (0.0404) Prec@1 90.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 16:01:50,948 Epoch: [294][30/500] Time 0.047 (0.028) Data 0.002 (0.011) Loss 0.0216 (0.0357) Prec@1 98.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:01:51,375 Epoch: [294][40/500] Time 0.036 (0.030) Data 0.003 (0.009) Loss 0.0457 (0.0377) Prec@1 93.000 (94.400) Prec@5 99.000 (99.600) +2022-11-14 16:01:51,845 Epoch: [294][50/500] Time 0.049 (0.033) Data 0.002 (0.008) Loss 0.0360 (0.0374) Prec@1 95.000 (94.500) Prec@5 99.000 (99.500) +2022-11-14 16:01:52,284 Epoch: [294][60/500] Time 0.046 (0.034) Data 0.003 (0.007) Loss 0.0153 (0.0343) Prec@1 97.000 (94.857) Prec@5 100.000 (99.571) +2022-11-14 16:01:52,709 Epoch: [294][70/500] Time 0.036 (0.034) Data 0.002 (0.006) Loss 0.0422 (0.0352) Prec@1 93.000 (94.625) Prec@5 99.000 (99.500) +2022-11-14 16:01:53,146 Epoch: [294][80/500] Time 0.041 (0.035) Data 0.002 (0.006) Loss 0.0287 (0.0345) Prec@1 95.000 (94.667) Prec@5 100.000 (99.556) +2022-11-14 16:01:53,584 Epoch: [294][90/500] Time 0.040 (0.035) Data 0.002 (0.005) Loss 0.0472 (0.0358) Prec@1 92.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 16:01:54,007 Epoch: [294][100/500] Time 0.036 (0.036) Data 0.002 (0.005) Loss 0.0292 (0.0352) Prec@1 94.000 (94.364) Prec@5 99.000 (99.545) +2022-11-14 16:01:54,450 Epoch: [294][110/500] Time 0.043 (0.036) Data 0.002 (0.005) Loss 0.0443 (0.0360) Prec@1 92.000 (94.167) Prec@5 100.000 (99.583) +2022-11-14 16:01:54,874 Epoch: [294][120/500] Time 0.038 (0.036) Data 0.002 (0.004) Loss 0.0415 (0.0364) Prec@1 92.000 (94.000) Prec@5 100.000 (99.615) +2022-11-14 16:01:55,317 Epoch: [294][130/500] Time 0.040 (0.036) Data 0.002 (0.004) Loss 0.0297 (0.0359) Prec@1 97.000 (94.214) Prec@5 100.000 (99.643) +2022-11-14 16:01:55,750 Epoch: [294][140/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0328 (0.0357) Prec@1 95.000 (94.267) Prec@5 100.000 (99.667) +2022-11-14 16:01:56,201 Epoch: [294][150/500] Time 0.035 (0.037) Data 0.002 (0.004) Loss 0.0484 (0.0365) Prec@1 92.000 (94.125) Prec@5 100.000 (99.688) +2022-11-14 16:01:56,653 Epoch: [294][160/500] Time 0.040 (0.037) Data 0.002 (0.004) Loss 0.0072 (0.0348) Prec@1 99.000 (94.412) Prec@5 100.000 (99.706) +2022-11-14 16:01:57,104 Epoch: [294][170/500] Time 0.043 (0.037) Data 0.002 (0.004) Loss 0.0652 (0.0365) Prec@1 88.000 (94.056) Prec@5 99.000 (99.667) +2022-11-14 16:01:57,530 Epoch: [294][180/500] Time 0.038 (0.037) Data 0.002 (0.004) Loss 0.0315 (0.0362) Prec@1 96.000 (94.158) Prec@5 100.000 (99.684) +2022-11-14 16:01:57,965 Epoch: [294][190/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0296 (0.0359) Prec@1 96.000 (94.250) Prec@5 100.000 (99.700) +2022-11-14 16:01:58,393 Epoch: [294][200/500] Time 0.037 (0.037) Data 0.002 (0.003) Loss 0.0245 (0.0353) Prec@1 97.000 (94.381) Prec@5 100.000 (99.714) +2022-11-14 16:01:58,827 Epoch: [294][210/500] Time 0.038 (0.037) Data 0.002 (0.003) Loss 0.0236 (0.0348) Prec@1 96.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 16:01:59,264 Epoch: [294][220/500] Time 0.050 (0.038) Data 0.002 (0.003) Loss 0.0127 (0.0338) Prec@1 99.000 (94.652) Prec@5 100.000 (99.739) +2022-11-14 16:01:59,840 Epoch: [294][230/500] Time 0.080 (0.038) Data 0.002 (0.003) Loss 0.0492 (0.0345) Prec@1 93.000 (94.583) Prec@5 100.000 (99.750) +2022-11-14 16:02:00,620 Epoch: [294][240/500] Time 0.076 (0.039) Data 0.002 (0.003) Loss 0.0571 (0.0354) Prec@1 90.000 (94.400) Prec@5 99.000 (99.720) +2022-11-14 16:02:01,414 Epoch: [294][250/500] Time 0.072 (0.041) Data 0.002 (0.003) Loss 0.0267 (0.0350) Prec@1 97.000 (94.500) Prec@5 100.000 (99.731) +2022-11-14 16:02:02,193 Epoch: [294][260/500] Time 0.078 (0.042) Data 0.002 (0.003) Loss 0.0203 (0.0345) Prec@1 94.000 (94.481) Prec@5 100.000 (99.741) +2022-11-14 16:02:02,975 Epoch: [294][270/500] Time 0.071 (0.043) Data 0.002 (0.003) Loss 0.0272 (0.0342) Prec@1 95.000 (94.500) Prec@5 99.000 (99.714) +2022-11-14 16:02:03,791 Epoch: [294][280/500] Time 0.074 (0.044) Data 0.002 (0.003) Loss 0.0366 (0.0343) Prec@1 94.000 (94.483) Prec@5 100.000 (99.724) +2022-11-14 16:02:04,569 Epoch: [294][290/500] Time 0.081 (0.045) Data 0.002 (0.003) Loss 0.0328 (0.0343) Prec@1 94.000 (94.467) Prec@5 100.000 (99.733) +2022-11-14 16:02:05,357 Epoch: [294][300/500] Time 0.078 (0.046) Data 0.002 (0.003) Loss 0.0309 (0.0342) Prec@1 94.000 (94.452) Prec@5 100.000 (99.742) +2022-11-14 16:02:06,156 Epoch: [294][310/500] Time 0.092 (0.046) Data 0.002 (0.003) Loss 0.0254 (0.0339) Prec@1 97.000 (94.531) Prec@5 100.000 (99.750) +2022-11-14 16:02:06,968 Epoch: [294][320/500] Time 0.073 (0.047) Data 0.002 (0.003) Loss 0.0381 (0.0340) Prec@1 93.000 (94.485) Prec@5 100.000 (99.758) +2022-11-14 16:02:07,736 Epoch: [294][330/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0312 (0.0339) Prec@1 96.000 (94.529) Prec@5 100.000 (99.765) +2022-11-14 16:02:08,497 Epoch: [294][340/500] Time 0.068 (0.048) Data 0.002 (0.003) Loss 0.0112 (0.0333) Prec@1 99.000 (94.657) Prec@5 99.000 (99.743) +2022-11-14 16:02:09,264 Epoch: [294][350/500] Time 0.066 (0.049) Data 0.002 (0.003) Loss 0.0391 (0.0334) Prec@1 90.000 (94.528) Prec@5 100.000 (99.750) +2022-11-14 16:02:10,027 Epoch: [294][360/500] Time 0.089 (0.050) Data 0.002 (0.003) Loss 0.0296 (0.0333) Prec@1 95.000 (94.541) Prec@5 100.000 (99.757) +2022-11-14 16:02:10,905 Epoch: [294][370/500] Time 0.074 (0.050) Data 0.002 (0.003) Loss 0.0131 (0.0328) Prec@1 97.000 (94.605) Prec@5 100.000 (99.763) +2022-11-14 16:02:11,823 Epoch: [294][380/500] Time 0.114 (0.051) Data 0.002 (0.003) Loss 0.0219 (0.0325) Prec@1 97.000 (94.667) Prec@5 100.000 (99.769) +2022-11-14 16:02:12,361 Epoch: [294][390/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0189 (0.0322) Prec@1 96.000 (94.700) Prec@5 100.000 (99.775) +2022-11-14 16:02:12,882 Epoch: [294][400/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0315 (0.0322) Prec@1 95.000 (94.707) Prec@5 100.000 (99.780) +2022-11-14 16:02:13,402 Epoch: [294][410/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0390 (0.0323) Prec@1 92.000 (94.643) Prec@5 100.000 (99.786) +2022-11-14 16:02:13,904 Epoch: [294][420/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0418 (0.0326) Prec@1 93.000 (94.605) Prec@5 99.000 (99.767) +2022-11-14 16:02:14,396 Epoch: [294][430/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0290 (0.0325) Prec@1 97.000 (94.659) Prec@5 100.000 (99.773) +2022-11-14 16:02:14,913 Epoch: [294][440/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0595 (0.0331) Prec@1 90.000 (94.556) Prec@5 99.000 (99.756) +2022-11-14 16:02:15,417 Epoch: [294][450/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0401 (0.0332) Prec@1 94.000 (94.543) Prec@5 100.000 (99.761) +2022-11-14 16:02:15,949 Epoch: [294][460/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0157 (0.0328) Prec@1 98.000 (94.617) Prec@5 100.000 (99.766) +2022-11-14 16:02:16,533 Epoch: [294][470/500] Time 0.059 (0.050) Data 0.003 (0.003) Loss 0.0384 (0.0330) Prec@1 93.000 (94.583) Prec@5 100.000 (99.771) +2022-11-14 16:02:17,176 Epoch: [294][480/500] Time 0.060 (0.050) Data 0.002 (0.003) Loss 0.0214 (0.0327) Prec@1 96.000 (94.612) Prec@5 100.000 (99.776) +2022-11-14 16:02:17,762 Epoch: [294][490/500] Time 0.051 (0.051) Data 0.003 (0.003) Loss 0.0179 (0.0324) Prec@1 97.000 (94.660) Prec@5 100.000 (99.780) +2022-11-14 16:02:18,227 Epoch: [294][499/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0204 (0.0322) Prec@1 98.000 (94.725) Prec@5 100.000 (99.784) +2022-11-14 16:02:18,601 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0728 (0.0728) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:02:18,612 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0674) Prec@1 91.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:02:18,623 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0588 (0.0645) Prec@1 91.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:02:18,637 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0730 (0.0666) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:02:18,648 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0674) Prec@1 91.000 (89.400) Prec@5 100.000 (99.600) +2022-11-14 16:02:18,660 Test: [5/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0401 (0.0629) Prec@1 93.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 16:02:18,671 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0616) Prec@1 91.000 (90.143) Prec@5 100.000 (99.714) +2022-11-14 16:02:18,684 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0930 (0.0656) Prec@1 83.000 (89.250) Prec@5 99.000 (99.625) +2022-11-14 16:02:18,693 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0684) Prec@1 86.000 (88.889) Prec@5 98.000 (99.444) +2022-11-14 16:02:18,706 Test: [9/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0849 (0.0701) Prec@1 87.000 (88.700) Prec@5 99.000 (99.400) +2022-11-14 16:02:18,719 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0706) Prec@1 86.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 16:02:18,730 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0699) Prec@1 92.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 16:02:18,740 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0566 (0.0688) Prec@1 92.000 (89.000) Prec@5 100.000 (99.538) +2022-11-14 16:02:18,753 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0686 (0.0688) Prec@1 89.000 (89.000) Prec@5 100.000 (99.571) +2022-11-14 16:02:18,765 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0896 (0.0702) Prec@1 86.000 (88.800) Prec@5 99.000 (99.533) +2022-11-14 16:02:18,775 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0710) Prec@1 86.000 (88.625) Prec@5 98.000 (99.438) +2022-11-14 16:02:18,786 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0391 (0.0692) Prec@1 95.000 (89.000) Prec@5 99.000 (99.412) +2022-11-14 16:02:18,799 Test: [17/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1142 (0.0717) Prec@1 85.000 (88.778) Prec@5 100.000 (99.444) +2022-11-14 16:02:18,811 Test: [18/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0716) Prec@1 87.000 (88.684) Prec@5 100.000 (99.474) +2022-11-14 16:02:18,822 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0730) Prec@1 85.000 (88.500) Prec@5 98.000 (99.400) +2022-11-14 16:02:18,832 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0732) Prec@1 85.000 (88.333) Prec@5 99.000 (99.381) +2022-11-14 16:02:18,847 Test: [21/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0733) Prec@1 87.000 (88.273) Prec@5 99.000 (99.364) +2022-11-14 16:02:18,860 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0743) Prec@1 86.000 (88.174) Prec@5 98.000 (99.304) +2022-11-14 16:02:18,871 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0746) Prec@1 87.000 (88.125) Prec@5 100.000 (99.333) +2022-11-14 16:02:18,882 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0749) Prec@1 88.000 (88.120) Prec@5 100.000 (99.360) +2022-11-14 16:02:18,893 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0999 (0.0759) Prec@1 83.000 (87.923) Prec@5 99.000 (99.346) +2022-11-14 16:02:18,904 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0757) Prec@1 87.000 (87.889) Prec@5 100.000 (99.370) +2022-11-14 16:02:18,915 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0542 (0.0750) Prec@1 92.000 (88.036) Prec@5 100.000 (99.393) +2022-11-14 16:02:18,928 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0748) Prec@1 90.000 (88.103) Prec@5 98.000 (99.345) +2022-11-14 16:02:18,939 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0744) Prec@1 89.000 (88.133) Prec@5 99.000 (99.333) +2022-11-14 16:02:18,950 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0742) Prec@1 89.000 (88.161) Prec@5 100.000 (99.355) +2022-11-14 16:02:18,959 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0737) Prec@1 89.000 (88.188) Prec@5 100.000 (99.375) +2022-11-14 16:02:18,971 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0735) Prec@1 88.000 (88.182) Prec@5 100.000 (99.394) +2022-11-14 16:02:18,982 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0744) Prec@1 85.000 (88.088) Prec@5 98.000 (99.353) +2022-11-14 16:02:18,993 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0745) Prec@1 88.000 (88.086) Prec@5 99.000 (99.343) +2022-11-14 16:02:19,004 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0744) Prec@1 88.000 (88.083) Prec@5 100.000 (99.361) +2022-11-14 16:02:19,016 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0740) Prec@1 89.000 (88.108) Prec@5 98.000 (99.324) +2022-11-14 16:02:19,028 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0750) Prec@1 80.000 (87.895) Prec@5 97.000 (99.263) +2022-11-14 16:02:19,038 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0746) Prec@1 90.000 (87.949) Prec@5 100.000 (99.282) +2022-11-14 16:02:19,050 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0742) Prec@1 89.000 (87.975) Prec@5 99.000 (99.275) +2022-11-14 16:02:19,061 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0749) Prec@1 86.000 (87.927) Prec@5 98.000 (99.244) +2022-11-14 16:02:19,074 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0747) Prec@1 87.000 (87.905) Prec@5 99.000 (99.238) +2022-11-14 16:02:19,085 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0740) Prec@1 93.000 (88.023) Prec@5 99.000 (99.233) +2022-11-14 16:02:19,096 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0739) Prec@1 88.000 (88.023) Prec@5 98.000 (99.205) +2022-11-14 16:02:19,107 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0734) Prec@1 92.000 (88.111) Prec@5 100.000 (99.222) +2022-11-14 16:02:19,118 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0740) Prec@1 84.000 (88.022) Prec@5 100.000 (99.239) +2022-11-14 16:02:19,129 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0742) Prec@1 88.000 (88.021) Prec@5 100.000 (99.255) +2022-11-14 16:02:19,140 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.0748) Prec@1 86.000 (87.979) Prec@5 98.000 (99.229) +2022-11-14 16:02:19,152 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0745) Prec@1 90.000 (88.020) Prec@5 100.000 (99.245) +2022-11-14 16:02:19,162 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0750) Prec@1 84.000 (87.940) Prec@5 100.000 (99.260) +2022-11-14 16:02:19,173 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0751) Prec@1 87.000 (87.922) Prec@5 100.000 (99.275) +2022-11-14 16:02:19,185 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0752) Prec@1 86.000 (87.885) Prec@5 99.000 (99.269) +2022-11-14 16:02:19,196 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0750) Prec@1 89.000 (87.906) Prec@5 99.000 (99.264) +2022-11-14 16:02:19,209 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0748) Prec@1 88.000 (87.907) Prec@5 99.000 (99.259) +2022-11-14 16:02:19,221 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0754) Prec@1 85.000 (87.855) Prec@5 99.000 (99.255) +2022-11-14 16:02:19,233 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0754) Prec@1 88.000 (87.857) Prec@5 99.000 (99.250) +2022-11-14 16:02:19,245 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0757) Prec@1 86.000 (87.825) Prec@5 100.000 (99.263) +2022-11-14 16:02:19,256 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0755) Prec@1 91.000 (87.879) Prec@5 99.000 (99.259) +2022-11-14 16:02:19,266 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0758) Prec@1 85.000 (87.831) Prec@5 100.000 (99.271) +2022-11-14 16:02:19,276 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0756) Prec@1 88.000 (87.833) Prec@5 100.000 (99.283) +2022-11-14 16:02:19,288 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0758) Prec@1 87.000 (87.820) Prec@5 99.000 (99.279) +2022-11-14 16:02:19,299 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0758) Prec@1 87.000 (87.806) Prec@5 99.000 (99.274) +2022-11-14 16:02:19,310 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0756) Prec@1 89.000 (87.825) Prec@5 100.000 (99.286) +2022-11-14 16:02:19,324 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0752) Prec@1 91.000 (87.875) Prec@5 100.000 (99.297) +2022-11-14 16:02:19,335 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0757) Prec@1 81.000 (87.769) Prec@5 100.000 (99.308) +2022-11-14 16:02:19,345 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0756) Prec@1 87.000 (87.758) Prec@5 99.000 (99.303) +2022-11-14 16:02:19,357 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0349 (0.0750) Prec@1 94.000 (87.851) Prec@5 100.000 (99.313) +2022-11-14 16:02:19,368 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0752) Prec@1 86.000 (87.824) Prec@5 98.000 (99.294) +2022-11-14 16:02:19,379 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0752) Prec@1 85.000 (87.783) Prec@5 99.000 (99.290) +2022-11-14 16:02:19,390 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0754) Prec@1 85.000 (87.743) Prec@5 100.000 (99.300) +2022-11-14 16:02:19,401 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1106 (0.0759) Prec@1 84.000 (87.690) Prec@5 100.000 (99.310) +2022-11-14 16:02:19,412 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0757) Prec@1 93.000 (87.764) Prec@5 99.000 (99.306) +2022-11-14 16:02:19,423 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0754) Prec@1 92.000 (87.822) Prec@5 99.000 (99.301) +2022-11-14 16:02:19,435 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0750) Prec@1 94.000 (87.905) Prec@5 100.000 (99.311) +2022-11-14 16:02:19,448 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0754) Prec@1 84.000 (87.853) Prec@5 100.000 (99.320) +2022-11-14 16:02:19,460 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0752) Prec@1 91.000 (87.895) Prec@5 98.000 (99.303) +2022-11-14 16:02:19,469 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0753) Prec@1 87.000 (87.883) Prec@5 98.000 (99.286) +2022-11-14 16:02:19,480 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0755) Prec@1 87.000 (87.872) Prec@5 98.000 (99.269) +2022-11-14 16:02:19,491 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0754) Prec@1 88.000 (87.873) Prec@5 100.000 (99.278) +2022-11-14 16:02:19,502 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0753) Prec@1 87.000 (87.862) Prec@5 99.000 (99.275) +2022-11-14 16:02:19,513 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0750) Prec@1 90.000 (87.889) Prec@5 100.000 (99.284) +2022-11-14 16:02:19,527 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0748) Prec@1 90.000 (87.915) Prec@5 99.000 (99.280) +2022-11-14 16:02:19,537 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0749) Prec@1 87.000 (87.904) Prec@5 100.000 (99.289) +2022-11-14 16:02:19,548 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0748) Prec@1 86.000 (87.881) Prec@5 99.000 (99.286) +2022-11-14 16:02:19,559 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0748) Prec@1 89.000 (87.894) Prec@5 99.000 (99.282) +2022-11-14 16:02:19,570 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0752) Prec@1 83.000 (87.837) Prec@5 100.000 (99.291) +2022-11-14 16:02:19,581 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0752) Prec@1 85.000 (87.805) Prec@5 99.000 (99.287) +2022-11-14 16:02:19,592 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0751) Prec@1 90.000 (87.830) Prec@5 99.000 (99.284) +2022-11-14 16:02:19,603 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0749) Prec@1 91.000 (87.865) Prec@5 100.000 (99.292) +2022-11-14 16:02:19,614 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0749) Prec@1 89.000 (87.878) Prec@5 100.000 (99.300) +2022-11-14 16:02:19,626 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0746) Prec@1 91.000 (87.912) Prec@5 100.000 (99.308) +2022-11-14 16:02:19,636 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0745) Prec@1 89.000 (87.924) Prec@5 100.000 (99.315) +2022-11-14 16:02:19,648 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 87.000 (87.914) Prec@5 100.000 (99.323) +2022-11-14 16:02:19,660 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0744) Prec@1 88.000 (87.915) Prec@5 99.000 (99.319) +2022-11-14 16:02:19,671 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0746) Prec@1 85.000 (87.884) Prec@5 100.000 (99.326) +2022-11-14 16:02:19,683 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0745) Prec@1 90.000 (87.906) Prec@5 99.000 (99.323) +2022-11-14 16:02:19,693 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0443 (0.0742) Prec@1 94.000 (87.969) Prec@5 99.000 (99.320) +2022-11-14 16:02:19,705 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0745) Prec@1 85.000 (87.939) Prec@5 99.000 (99.316) +2022-11-14 16:02:19,717 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1142 (0.0749) Prec@1 82.000 (87.879) Prec@5 100.000 (99.323) +2022-11-14 16:02:19,727 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0748) Prec@1 89.000 (87.890) Prec@5 99.000 (99.320) +2022-11-14 16:02:19,811 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:02:20,174 Epoch: [295][0/500] Time 0.034 (0.034) Data 0.264 (0.264) Loss 0.0421 (0.0421) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:02:20,421 Epoch: [295][10/500] Time 0.019 (0.023) Data 0.002 (0.026) Loss 0.0166 (0.0294) Prec@1 98.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:02:20,879 Epoch: [295][20/500] Time 0.048 (0.031) Data 0.002 (0.014) Loss 0.0260 (0.0282) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:02:21,382 Epoch: [295][30/500] Time 0.043 (0.036) Data 0.002 (0.010) Loss 0.0260 (0.0277) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:02:21,905 Epoch: [295][40/500] Time 0.044 (0.038) Data 0.002 (0.008) Loss 0.0310 (0.0284) Prec@1 95.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:02:22,419 Epoch: [295][50/500] Time 0.040 (0.040) Data 0.002 (0.007) Loss 0.0546 (0.0327) Prec@1 92.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 16:02:22,941 Epoch: [295][60/500] Time 0.046 (0.041) Data 0.002 (0.006) Loss 0.0482 (0.0349) Prec@1 92.000 (94.429) Prec@5 99.000 (99.857) +2022-11-14 16:02:23,448 Epoch: [295][70/500] Time 0.045 (0.041) Data 0.002 (0.006) Loss 0.0468 (0.0364) Prec@1 94.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 16:02:23,959 Epoch: [295][80/500] Time 0.036 (0.042) Data 0.002 (0.005) Loss 0.0322 (0.0360) Prec@1 95.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:02:24,485 Epoch: [295][90/500] Time 0.058 (0.042) Data 0.002 (0.005) Loss 0.0239 (0.0348) Prec@1 96.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 16:02:25,003 Epoch: [295][100/500] Time 0.048 (0.043) Data 0.002 (0.005) Loss 0.0257 (0.0339) Prec@1 97.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:02:25,515 Epoch: [295][110/500] Time 0.045 (0.043) Data 0.002 (0.004) Loss 0.0234 (0.0330) Prec@1 97.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 16:02:26,047 Epoch: [295][120/500] Time 0.054 (0.043) Data 0.003 (0.004) Loss 0.0118 (0.0314) Prec@1 98.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 16:02:26,556 Epoch: [295][130/500] Time 0.044 (0.044) Data 0.002 (0.004) Loss 0.0282 (0.0312) Prec@1 96.000 (95.286) Prec@5 100.000 (99.929) +2022-11-14 16:02:27,070 Epoch: [295][140/500] Time 0.048 (0.044) Data 0.002 (0.004) Loss 0.0325 (0.0313) Prec@1 94.000 (95.200) Prec@5 99.000 (99.867) +2022-11-14 16:02:27,591 Epoch: [295][150/500] Time 0.052 (0.044) Data 0.002 (0.004) Loss 0.0453 (0.0321) Prec@1 90.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 16:02:28,103 Epoch: [295][160/500] Time 0.047 (0.044) Data 0.002 (0.004) Loss 0.0332 (0.0322) Prec@1 95.000 (94.882) Prec@5 100.000 (99.882) +2022-11-14 16:02:28,719 Epoch: [295][170/500] Time 0.056 (0.045) Data 0.002 (0.004) Loss 0.0269 (0.0319) Prec@1 96.000 (94.944) Prec@5 100.000 (99.889) +2022-11-14 16:02:29,327 Epoch: [295][180/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0333 (0.0320) Prec@1 95.000 (94.947) Prec@5 100.000 (99.895) +2022-11-14 16:02:29,842 Epoch: [295][190/500] Time 0.058 (0.045) Data 0.002 (0.003) Loss 0.0165 (0.0312) Prec@1 97.000 (95.050) Prec@5 100.000 (99.900) +2022-11-14 16:02:30,359 Epoch: [295][200/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0296 (0.0311) Prec@1 95.000 (95.048) Prec@5 100.000 (99.905) +2022-11-14 16:02:30,899 Epoch: [295][210/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0565 (0.0323) Prec@1 92.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 16:02:31,408 Epoch: [295][220/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0515 (0.0331) Prec@1 93.000 (94.826) Prec@5 98.000 (99.826) +2022-11-14 16:02:31,921 Epoch: [295][230/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0294 (0.0330) Prec@1 95.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:02:32,538 Epoch: [295][240/500] Time 0.063 (0.046) Data 0.002 (0.003) Loss 0.0223 (0.0325) Prec@1 97.000 (94.920) Prec@5 100.000 (99.840) +2022-11-14 16:02:33,094 Epoch: [295][250/500] Time 0.057 (0.046) Data 0.002 (0.003) Loss 0.0258 (0.0323) Prec@1 96.000 (94.962) Prec@5 100.000 (99.846) +2022-11-14 16:02:33,623 Epoch: [295][260/500] Time 0.057 (0.046) Data 0.002 (0.003) Loss 0.0293 (0.0322) Prec@1 96.000 (95.000) Prec@5 100.000 (99.852) +2022-11-14 16:02:34,147 Epoch: [295][270/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0266 (0.0320) Prec@1 96.000 (95.036) Prec@5 100.000 (99.857) +2022-11-14 16:02:34,667 Epoch: [295][280/500] Time 0.057 (0.046) Data 0.002 (0.003) Loss 0.0201 (0.0316) Prec@1 97.000 (95.103) Prec@5 100.000 (99.862) +2022-11-14 16:02:35,209 Epoch: [295][290/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0336 (0.0316) Prec@1 95.000 (95.100) Prec@5 100.000 (99.867) +2022-11-14 16:02:35,723 Epoch: [295][300/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0345 (0.0317) Prec@1 95.000 (95.097) Prec@5 100.000 (99.871) +2022-11-14 16:02:36,297 Epoch: [295][310/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0294 (0.0317) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:02:36,811 Epoch: [295][320/500] Time 0.044 (0.046) Data 0.003 (0.003) Loss 0.0259 (0.0315) Prec@1 97.000 (95.182) Prec@5 100.000 (99.879) +2022-11-14 16:02:37,344 Epoch: [295][330/500] Time 0.044 (0.046) Data 0.003 (0.003) Loss 0.0514 (0.0321) Prec@1 90.000 (95.029) Prec@5 100.000 (99.882) +2022-11-14 16:02:37,876 Epoch: [295][340/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0246 (0.0318) Prec@1 96.000 (95.057) Prec@5 100.000 (99.886) +2022-11-14 16:02:38,404 Epoch: [295][350/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0237 (0.0316) Prec@1 97.000 (95.111) Prec@5 99.000 (99.861) +2022-11-14 16:02:38,914 Epoch: [295][360/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0200 (0.0313) Prec@1 96.000 (95.135) Prec@5 100.000 (99.865) +2022-11-14 16:02:39,475 Epoch: [295][370/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0252 (0.0311) Prec@1 95.000 (95.132) Prec@5 100.000 (99.868) +2022-11-14 16:02:40,036 Epoch: [295][380/500] Time 0.052 (0.047) Data 0.003 (0.003) Loss 0.0210 (0.0309) Prec@1 98.000 (95.205) Prec@5 100.000 (99.872) +2022-11-14 16:02:40,595 Epoch: [295][390/500] Time 0.053 (0.047) Data 0.003 (0.003) Loss 0.0562 (0.0315) Prec@1 92.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:02:41,131 Epoch: [295][400/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0283 (0.0314) Prec@1 96.000 (95.146) Prec@5 99.000 (99.854) +2022-11-14 16:02:41,715 Epoch: [295][410/500] Time 0.064 (0.047) Data 0.002 (0.003) Loss 0.0311 (0.0314) Prec@1 95.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:02:42,270 Epoch: [295][420/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0133 (0.0310) Prec@1 98.000 (95.209) Prec@5 100.000 (99.860) +2022-11-14 16:02:42,897 Epoch: [295][430/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0296 (0.0310) Prec@1 95.000 (95.205) Prec@5 100.000 (99.864) +2022-11-14 16:02:43,458 Epoch: [295][440/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0186 (0.0307) Prec@1 98.000 (95.267) Prec@5 100.000 (99.867) +2022-11-14 16:02:44,006 Epoch: [295][450/500] Time 0.067 (0.047) Data 0.002 (0.003) Loss 0.0116 (0.0303) Prec@1 98.000 (95.326) Prec@5 100.000 (99.870) +2022-11-14 16:02:44,526 Epoch: [295][460/500] Time 0.038 (0.047) Data 0.002 (0.003) Loss 0.0291 (0.0303) Prec@1 94.000 (95.298) Prec@5 100.000 (99.872) +2022-11-14 16:02:45,051 Epoch: [295][470/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0397 (0.0305) Prec@1 92.000 (95.229) Prec@5 100.000 (99.875) +2022-11-14 16:02:45,615 Epoch: [295][480/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0318 (0.0305) Prec@1 94.000 (95.204) Prec@5 100.000 (99.878) +2022-11-14 16:02:46,215 Epoch: [295][490/500] Time 0.036 (0.047) Data 0.002 (0.003) Loss 0.0335 (0.0305) Prec@1 94.000 (95.180) Prec@5 100.000 (99.880) +2022-11-14 16:02:46,737 Epoch: [295][499/500] Time 0.064 (0.047) Data 0.002 (0.003) Loss 0.0404 (0.0307) Prec@1 95.000 (95.176) Prec@5 100.000 (99.882) +2022-11-14 16:02:47,088 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0550 (0.0550) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:02:47,097 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0802 (0.0676) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:02:47,108 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0733) Prec@1 87.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:02:47,122 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0738) Prec@1 87.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 16:02:47,133 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0710) Prec@1 87.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 16:02:47,146 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0671) Prec@1 91.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 16:02:47,160 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0674) Prec@1 89.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 16:02:47,173 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1054 (0.0722) Prec@1 82.000 (87.750) Prec@5 98.000 (99.375) +2022-11-14 16:02:47,186 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0733) Prec@1 88.000 (87.778) Prec@5 100.000 (99.444) +2022-11-14 16:02:47,201 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0728) Prec@1 90.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 16:02:47,218 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0722) Prec@1 90.000 (88.182) Prec@5 100.000 (99.455) +2022-11-14 16:02:47,236 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0717) Prec@1 90.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 16:02:47,251 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0717) Prec@1 89.000 (88.385) Prec@5 100.000 (99.538) +2022-11-14 16:02:47,266 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0707) Prec@1 90.000 (88.500) Prec@5 100.000 (99.571) +2022-11-14 16:02:47,284 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0699) Prec@1 91.000 (88.667) Prec@5 99.000 (99.533) +2022-11-14 16:02:47,303 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0707) Prec@1 87.000 (88.562) Prec@5 100.000 (99.562) +2022-11-14 16:02:47,320 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0695) Prec@1 92.000 (88.765) Prec@5 98.000 (99.471) +2022-11-14 16:02:47,337 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0711) Prec@1 86.000 (88.611) Prec@5 100.000 (99.500) +2022-11-14 16:02:47,353 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0718) Prec@1 85.000 (88.421) Prec@5 99.000 (99.474) +2022-11-14 16:02:47,370 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0722) Prec@1 85.000 (88.250) Prec@5 99.000 (99.450) +2022-11-14 16:02:47,388 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0722) Prec@1 89.000 (88.286) Prec@5 100.000 (99.476) +2022-11-14 16:02:47,404 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0730) Prec@1 85.000 (88.136) Prec@5 99.000 (99.455) +2022-11-14 16:02:47,419 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0733) Prec@1 89.000 (88.174) Prec@5 98.000 (99.391) +2022-11-14 16:02:47,438 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0733) Prec@1 89.000 (88.208) Prec@5 100.000 (99.417) +2022-11-14 16:02:47,456 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0737) Prec@1 86.000 (88.120) Prec@5 100.000 (99.440) +2022-11-14 16:02:47,473 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0739) Prec@1 91.000 (88.231) Prec@5 98.000 (99.385) +2022-11-14 16:02:47,489 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0731) Prec@1 93.000 (88.407) Prec@5 100.000 (99.407) +2022-11-14 16:02:47,507 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0726) Prec@1 89.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 16:02:47,523 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0727) Prec@1 87.000 (88.379) Prec@5 98.000 (99.379) +2022-11-14 16:02:47,541 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0729) Prec@1 90.000 (88.433) Prec@5 98.000 (99.333) +2022-11-14 16:02:47,560 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0724) Prec@1 91.000 (88.516) Prec@5 100.000 (99.355) +2022-11-14 16:02:47,580 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0723) Prec@1 91.000 (88.594) Prec@5 99.000 (99.344) +2022-11-14 16:02:47,597 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0722) Prec@1 89.000 (88.606) Prec@5 100.000 (99.364) +2022-11-14 16:02:47,616 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0725) Prec@1 87.000 (88.559) Prec@5 99.000 (99.353) +2022-11-14 16:02:47,636 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0729) Prec@1 83.000 (88.400) Prec@5 98.000 (99.314) +2022-11-14 16:02:47,652 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0727) Prec@1 90.000 (88.444) Prec@5 99.000 (99.306) +2022-11-14 16:02:47,667 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0727) Prec@1 89.000 (88.459) Prec@5 100.000 (99.324) +2022-11-14 16:02:47,681 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.0737) Prec@1 82.000 (88.289) Prec@5 100.000 (99.342) +2022-11-14 16:02:47,697 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0730) Prec@1 93.000 (88.410) Prec@5 100.000 (99.359) +2022-11-14 16:02:47,713 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0729) Prec@1 87.000 (88.375) Prec@5 99.000 (99.350) +2022-11-14 16:02:47,730 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0733) Prec@1 85.000 (88.293) Prec@5 99.000 (99.341) +2022-11-14 16:02:47,747 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0729) Prec@1 89.000 (88.310) Prec@5 100.000 (99.357) +2022-11-14 16:02:47,765 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0338 (0.0720) Prec@1 94.000 (88.442) Prec@5 100.000 (99.372) +2022-11-14 16:02:47,780 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0721) Prec@1 89.000 (88.455) Prec@5 98.000 (99.341) +2022-11-14 16:02:47,798 Test: [44/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0718) Prec@1 91.000 (88.511) Prec@5 99.000 (99.333) +2022-11-14 16:02:47,817 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0725) Prec@1 83.000 (88.391) Prec@5 98.000 (99.304) +2022-11-14 16:02:47,835 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0726) Prec@1 86.000 (88.340) Prec@5 99.000 (99.298) +2022-11-14 16:02:47,850 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0732) Prec@1 83.000 (88.229) Prec@5 100.000 (99.312) +2022-11-14 16:02:47,868 Test: [48/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0731) Prec@1 90.000 (88.265) Prec@5 100.000 (99.327) +2022-11-14 16:02:47,883 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0737) Prec@1 87.000 (88.240) Prec@5 100.000 (99.340) +2022-11-14 16:02:47,901 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0734) Prec@1 89.000 (88.255) Prec@5 100.000 (99.353) +2022-11-14 16:02:47,921 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0740) Prec@1 81.000 (88.115) Prec@5 99.000 (99.346) +2022-11-14 16:02:47,938 Test: [52/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0741) Prec@1 84.000 (88.038) Prec@5 99.000 (99.340) +2022-11-14 16:02:47,955 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0738) Prec@1 91.000 (88.093) Prec@5 100.000 (99.352) +2022-11-14 16:02:47,972 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0743) Prec@1 83.000 (88.000) Prec@5 100.000 (99.364) +2022-11-14 16:02:47,991 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0743) Prec@1 87.000 (87.982) Prec@5 99.000 (99.357) +2022-11-14 16:02:48,011 Test: [56/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0741) Prec@1 91.000 (88.035) Prec@5 100.000 (99.368) +2022-11-14 16:02:48,029 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0738) Prec@1 92.000 (88.103) Prec@5 100.000 (99.379) +2022-11-14 16:02:48,044 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0744) Prec@1 83.000 (88.017) Prec@5 99.000 (99.373) +2022-11-14 16:02:48,062 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0745) Prec@1 86.000 (87.983) Prec@5 100.000 (99.383) +2022-11-14 16:02:48,082 Test: [60/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0746) Prec@1 88.000 (87.984) Prec@5 100.000 (99.393) +2022-11-14 16:02:48,104 Test: [61/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0745) Prec@1 87.000 (87.968) Prec@5 99.000 (99.387) +2022-11-14 16:02:48,121 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0742) Prec@1 92.000 (88.032) Prec@5 99.000 (99.381) +2022-11-14 16:02:48,138 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0738) Prec@1 92.000 (88.094) Prec@5 100.000 (99.391) +2022-11-14 16:02:48,155 Test: [64/100] Model Time 0.014 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0742) Prec@1 84.000 (88.031) Prec@5 99.000 (99.385) +2022-11-14 16:02:48,173 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0740) Prec@1 89.000 (88.045) Prec@5 98.000 (99.364) +2022-11-14 16:02:48,189 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0737) Prec@1 92.000 (88.104) Prec@5 100.000 (99.373) +2022-11-14 16:02:48,208 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0738) Prec@1 88.000 (88.103) Prec@5 96.000 (99.324) +2022-11-14 16:02:48,225 Test: [68/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0738) Prec@1 87.000 (88.087) Prec@5 99.000 (99.319) +2022-11-14 16:02:48,241 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0738) Prec@1 87.000 (88.071) Prec@5 100.000 (99.329) +2022-11-14 16:02:48,259 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0742) Prec@1 85.000 (88.028) Prec@5 99.000 (99.324) +2022-11-14 16:02:48,282 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0742) Prec@1 88.000 (88.028) Prec@5 99.000 (99.319) +2022-11-14 16:02:48,303 Test: [72/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0422 (0.0737) Prec@1 94.000 (88.110) Prec@5 100.000 (99.329) +2022-11-14 16:02:48,318 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0453 (0.0734) Prec@1 95.000 (88.203) Prec@5 100.000 (99.338) +2022-11-14 16:02:48,335 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1151 (0.0739) Prec@1 83.000 (88.133) Prec@5 99.000 (99.333) +2022-11-14 16:02:48,351 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0737) Prec@1 89.000 (88.145) Prec@5 99.000 (99.329) +2022-11-14 16:02:48,369 Test: [76/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0740) Prec@1 85.000 (88.104) Prec@5 99.000 (99.325) +2022-11-14 16:02:48,390 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0743) Prec@1 84.000 (88.051) Prec@5 97.000 (99.295) +2022-11-14 16:02:48,408 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0743) Prec@1 87.000 (88.038) Prec@5 100.000 (99.304) +2022-11-14 16:02:48,422 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0742) Prec@1 89.000 (88.050) Prec@5 100.000 (99.312) +2022-11-14 16:02:48,439 Test: [80/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0743) Prec@1 87.000 (88.037) Prec@5 99.000 (99.309) +2022-11-14 16:02:48,458 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0743) Prec@1 89.000 (88.049) Prec@5 100.000 (99.317) +2022-11-14 16:02:48,476 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0744) Prec@1 86.000 (88.024) Prec@5 100.000 (99.325) +2022-11-14 16:02:48,493 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0745) Prec@1 85.000 (87.988) Prec@5 100.000 (99.333) +2022-11-14 16:02:48,510 Test: [84/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0748) Prec@1 84.000 (87.941) Prec@5 99.000 (99.329) +2022-11-14 16:02:48,526 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0752) Prec@1 83.000 (87.884) Prec@5 99.000 (99.326) +2022-11-14 16:02:48,543 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0752) Prec@1 85.000 (87.851) Prec@5 100.000 (99.333) +2022-11-14 16:02:48,563 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0751) Prec@1 89.000 (87.864) Prec@5 99.000 (99.330) +2022-11-14 16:02:48,579 Test: [88/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0750) Prec@1 90.000 (87.888) Prec@5 100.000 (99.337) +2022-11-14 16:02:48,597 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0751) Prec@1 88.000 (87.889) Prec@5 100.000 (99.344) +2022-11-14 16:02:48,616 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0451 (0.0748) Prec@1 94.000 (87.956) Prec@5 100.000 (99.352) +2022-11-14 16:02:48,635 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0747) Prec@1 89.000 (87.967) Prec@5 99.000 (99.348) +2022-11-14 16:02:48,653 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0749) Prec@1 85.000 (87.935) Prec@5 99.000 (99.344) +2022-11-14 16:02:48,672 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0748) Prec@1 88.000 (87.936) Prec@5 99.000 (99.340) +2022-11-14 16:02:48,692 Test: [94/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0750) Prec@1 87.000 (87.926) Prec@5 100.000 (99.347) +2022-11-14 16:02:48,713 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0751) Prec@1 85.000 (87.896) Prec@5 99.000 (99.344) +2022-11-14 16:02:48,738 Test: [96/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0748) Prec@1 91.000 (87.928) Prec@5 99.000 (99.340) +2022-11-14 16:02:48,764 Test: [97/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0748) Prec@1 87.000 (87.918) Prec@5 98.000 (99.327) +2022-11-14 16:02:48,788 Test: [98/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0749) Prec@1 87.000 (87.909) Prec@5 99.000 (99.323) +2022-11-14 16:02:48,804 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0749) Prec@1 88.000 (87.910) Prec@5 99.000 (99.320) +2022-11-14 16:02:48,873 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:02:49,258 Epoch: [296][0/500] Time 0.027 (0.027) Data 0.285 (0.285) Loss 0.0400 (0.0400) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:02:49,707 Epoch: [296][10/500] Time 0.057 (0.038) Data 0.002 (0.028) Loss 0.0365 (0.0382) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:02:50,221 Epoch: [296][20/500] Time 0.048 (0.042) Data 0.002 (0.016) Loss 0.0291 (0.0352) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:02:50,761 Epoch: [296][30/500] Time 0.039 (0.044) Data 0.002 (0.011) Loss 0.0205 (0.0315) Prec@1 98.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:02:51,390 Epoch: [296][40/500] Time 0.063 (0.047) Data 0.002 (0.009) Loss 0.0542 (0.0360) Prec@1 91.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 16:02:52,021 Epoch: [296][50/500] Time 0.060 (0.049) Data 0.002 (0.008) Loss 0.0180 (0.0330) Prec@1 97.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:02:52,640 Epoch: [296][60/500] Time 0.058 (0.050) Data 0.003 (0.007) Loss 0.0457 (0.0348) Prec@1 92.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:02:53,232 Epoch: [296][70/500] Time 0.050 (0.050) Data 0.002 (0.006) Loss 0.0409 (0.0356) Prec@1 93.000 (94.500) Prec@5 98.000 (99.625) +2022-11-14 16:02:53,813 Epoch: [296][80/500] Time 0.055 (0.051) Data 0.002 (0.006) Loss 0.0692 (0.0393) Prec@1 87.000 (93.667) Prec@5 99.000 (99.556) +2022-11-14 16:02:54,413 Epoch: [296][90/500] Time 0.055 (0.051) Data 0.002 (0.005) Loss 0.0271 (0.0381) Prec@1 94.000 (93.700) Prec@5 100.000 (99.600) +2022-11-14 16:02:54,988 Epoch: [296][100/500] Time 0.054 (0.051) Data 0.002 (0.005) Loss 0.0344 (0.0378) Prec@1 94.000 (93.727) Prec@5 99.000 (99.545) +2022-11-14 16:02:55,621 Epoch: [296][110/500] Time 0.058 (0.052) Data 0.003 (0.005) Loss 0.0237 (0.0366) Prec@1 97.000 (94.000) Prec@5 100.000 (99.583) +2022-11-14 16:02:56,264 Epoch: [296][120/500] Time 0.067 (0.052) Data 0.002 (0.005) Loss 0.0208 (0.0354) Prec@1 96.000 (94.154) Prec@5 100.000 (99.615) +2022-11-14 16:02:56,790 Epoch: [296][130/500] Time 0.043 (0.052) Data 0.003 (0.004) Loss 0.0543 (0.0367) Prec@1 89.000 (93.786) Prec@5 100.000 (99.643) +2022-11-14 16:02:57,309 Epoch: [296][140/500] Time 0.062 (0.051) Data 0.002 (0.004) Loss 0.0421 (0.0371) Prec@1 94.000 (93.800) Prec@5 100.000 (99.667) +2022-11-14 16:02:57,804 Epoch: [296][150/500] Time 0.050 (0.051) Data 0.002 (0.004) Loss 0.0437 (0.0375) Prec@1 91.000 (93.625) Prec@5 100.000 (99.688) +2022-11-14 16:02:58,316 Epoch: [296][160/500] Time 0.055 (0.050) Data 0.002 (0.004) Loss 0.0346 (0.0373) Prec@1 93.000 (93.588) Prec@5 100.000 (99.706) +2022-11-14 16:02:58,861 Epoch: [296][170/500] Time 0.079 (0.050) Data 0.002 (0.004) Loss 0.0292 (0.0369) Prec@1 95.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 16:02:59,368 Epoch: [296][180/500] Time 0.056 (0.050) Data 0.002 (0.004) Loss 0.0100 (0.0355) Prec@1 99.000 (93.947) Prec@5 100.000 (99.684) +2022-11-14 16:02:59,938 Epoch: [296][190/500] Time 0.038 (0.050) Data 0.003 (0.004) Loss 0.0410 (0.0357) Prec@1 93.000 (93.900) Prec@5 100.000 (99.700) +2022-11-14 16:03:00,512 Epoch: [296][200/500] Time 0.046 (0.050) Data 0.002 (0.004) Loss 0.0356 (0.0357) Prec@1 92.000 (93.810) Prec@5 100.000 (99.714) +2022-11-14 16:03:01,100 Epoch: [296][210/500] Time 0.066 (0.050) Data 0.002 (0.004) Loss 0.0416 (0.0360) Prec@1 93.000 (93.773) Prec@5 100.000 (99.727) +2022-11-14 16:03:01,636 Epoch: [296][220/500] Time 0.037 (0.050) Data 0.002 (0.004) Loss 0.0298 (0.0357) Prec@1 95.000 (93.826) Prec@5 100.000 (99.739) +2022-11-14 16:03:02,165 Epoch: [296][230/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0371 (0.0358) Prec@1 91.000 (93.708) Prec@5 100.000 (99.750) +2022-11-14 16:03:02,739 Epoch: [296][240/500] Time 0.042 (0.050) Data 0.002 (0.003) Loss 0.0586 (0.0367) Prec@1 89.000 (93.520) Prec@5 100.000 (99.760) +2022-11-14 16:03:03,334 Epoch: [296][250/500] Time 0.061 (0.050) Data 0.003 (0.003) Loss 0.0322 (0.0365) Prec@1 95.000 (93.577) Prec@5 100.000 (99.769) +2022-11-14 16:03:03,955 Epoch: [296][260/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0437 (0.0368) Prec@1 92.000 (93.519) Prec@5 99.000 (99.741) +2022-11-14 16:03:04,556 Epoch: [296][270/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0624 (0.0377) Prec@1 91.000 (93.429) Prec@5 100.000 (99.750) +2022-11-14 16:03:05,167 Epoch: [296][280/500] Time 0.051 (0.051) Data 0.003 (0.003) Loss 0.0242 (0.0372) Prec@1 95.000 (93.483) Prec@5 100.000 (99.759) +2022-11-14 16:03:05,688 Epoch: [296][290/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0485 (0.0376) Prec@1 92.000 (93.433) Prec@5 100.000 (99.767) +2022-11-14 16:03:06,211 Epoch: [296][300/500] Time 0.045 (0.051) Data 0.002 (0.003) Loss 0.0355 (0.0376) Prec@1 93.000 (93.419) Prec@5 100.000 (99.774) +2022-11-14 16:03:06,757 Epoch: [296][310/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0287 (0.0373) Prec@1 95.000 (93.469) Prec@5 100.000 (99.781) +2022-11-14 16:03:07,316 Epoch: [296][320/500] Time 0.069 (0.051) Data 0.003 (0.003) Loss 0.0275 (0.0370) Prec@1 95.000 (93.515) Prec@5 100.000 (99.788) +2022-11-14 16:03:07,890 Epoch: [296][330/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0337 (0.0369) Prec@1 95.000 (93.559) Prec@5 100.000 (99.794) +2022-11-14 16:03:08,454 Epoch: [296][340/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0210 (0.0364) Prec@1 97.000 (93.657) Prec@5 100.000 (99.800) +2022-11-14 16:03:09,025 Epoch: [296][350/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0197 (0.0360) Prec@1 98.000 (93.778) Prec@5 100.000 (99.806) +2022-11-14 16:03:09,681 Epoch: [296][360/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0365 (0.0360) Prec@1 94.000 (93.784) Prec@5 100.000 (99.811) +2022-11-14 16:03:10,265 Epoch: [296][370/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0136 (0.0354) Prec@1 98.000 (93.895) Prec@5 100.000 (99.816) +2022-11-14 16:03:10,868 Epoch: [296][380/500] Time 0.062 (0.051) Data 0.002 (0.003) Loss 0.0488 (0.0357) Prec@1 91.000 (93.821) Prec@5 100.000 (99.821) +2022-11-14 16:03:11,392 Epoch: [296][390/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0233 (0.0354) Prec@1 96.000 (93.875) Prec@5 100.000 (99.825) +2022-11-14 16:03:11,967 Epoch: [296][400/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0529 (0.0358) Prec@1 90.000 (93.780) Prec@5 100.000 (99.829) +2022-11-14 16:03:12,562 Epoch: [296][410/500] Time 0.064 (0.051) Data 0.003 (0.003) Loss 0.0522 (0.0362) Prec@1 91.000 (93.714) Prec@5 100.000 (99.833) +2022-11-14 16:03:13,074 Epoch: [296][420/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0593 (0.0368) Prec@1 90.000 (93.628) Prec@5 99.000 (99.814) +2022-11-14 16:03:13,604 Epoch: [296][430/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0239 (0.0365) Prec@1 96.000 (93.682) Prec@5 100.000 (99.818) +2022-11-14 16:03:14,172 Epoch: [296][440/500] Time 0.038 (0.051) Data 0.002 (0.003) Loss 0.0521 (0.0368) Prec@1 92.000 (93.644) Prec@5 99.000 (99.800) +2022-11-14 16:03:14,695 Epoch: [296][450/500] Time 0.037 (0.051) Data 0.002 (0.003) Loss 0.0281 (0.0366) Prec@1 95.000 (93.674) Prec@5 99.000 (99.783) +2022-11-14 16:03:15,240 Epoch: [296][460/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0480 (0.0369) Prec@1 93.000 (93.660) Prec@5 100.000 (99.787) +2022-11-14 16:03:15,764 Epoch: [296][470/500] Time 0.041 (0.050) Data 0.003 (0.003) Loss 0.0253 (0.0366) Prec@1 97.000 (93.729) Prec@5 100.000 (99.792) +2022-11-14 16:03:16,296 Epoch: [296][480/500] Time 0.057 (0.050) Data 0.003 (0.003) Loss 0.0277 (0.0365) Prec@1 95.000 (93.755) Prec@5 100.000 (99.796) +2022-11-14 16:03:16,823 Epoch: [296][490/500] Time 0.055 (0.050) Data 0.003 (0.003) Loss 0.0211 (0.0361) Prec@1 95.000 (93.780) Prec@5 100.000 (99.800) +2022-11-14 16:03:17,288 Epoch: [296][499/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0304 (0.0360) Prec@1 96.000 (93.824) Prec@5 100.000 (99.804) +2022-11-14 16:03:17,611 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0789 (0.0789) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:17,621 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0737) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:03:17,631 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0697) Prec@1 91.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:03:17,643 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0664) Prec@1 89.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 16:03:17,655 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0693) Prec@1 88.000 (88.600) Prec@5 100.000 (99.600) +2022-11-14 16:03:17,666 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0681) Prec@1 91.000 (89.000) Prec@5 98.000 (99.333) +2022-11-14 16:03:17,680 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0692) Prec@1 88.000 (88.857) Prec@5 100.000 (99.429) +2022-11-14 16:03:17,695 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0699) Prec@1 85.000 (88.375) Prec@5 99.000 (99.375) +2022-11-14 16:03:17,709 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0718) Prec@1 85.000 (88.000) Prec@5 100.000 (99.444) +2022-11-14 16:03:17,723 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0728) Prec@1 86.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 16:03:17,737 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0717) Prec@1 90.000 (88.000) Prec@5 100.000 (99.455) +2022-11-14 16:03:17,751 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0728) Prec@1 87.000 (87.917) Prec@5 99.000 (99.417) +2022-11-14 16:03:17,770 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0718) Prec@1 91.000 (88.154) Prec@5 100.000 (99.462) +2022-11-14 16:03:17,786 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0715) Prec@1 88.000 (88.143) Prec@5 99.000 (99.429) +2022-11-14 16:03:17,800 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0713) Prec@1 89.000 (88.200) Prec@5 100.000 (99.467) +2022-11-14 16:03:17,815 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0720) Prec@1 86.000 (88.062) Prec@5 99.000 (99.438) +2022-11-14 16:03:17,832 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0709) Prec@1 91.000 (88.235) Prec@5 98.000 (99.353) +2022-11-14 16:03:17,852 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0726) Prec@1 84.000 (88.000) Prec@5 100.000 (99.389) +2022-11-14 16:03:17,873 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0728) Prec@1 86.000 (87.895) Prec@5 98.000 (99.316) +2022-11-14 16:03:17,893 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0739) Prec@1 83.000 (87.650) Prec@5 98.000 (99.250) +2022-11-14 16:03:17,910 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0732) Prec@1 89.000 (87.714) Prec@5 100.000 (99.286) +2022-11-14 16:03:17,923 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0737) Prec@1 86.000 (87.636) Prec@5 100.000 (99.318) +2022-11-14 16:03:17,941 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0747) Prec@1 84.000 (87.478) Prec@5 97.000 (99.217) +2022-11-14 16:03:17,962 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0756) Prec@1 84.000 (87.333) Prec@5 100.000 (99.250) +2022-11-14 16:03:17,979 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0760) Prec@1 84.000 (87.200) Prec@5 100.000 (99.280) +2022-11-14 16:03:17,998 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0763) Prec@1 86.000 (87.154) Prec@5 99.000 (99.269) +2022-11-14 16:03:18,014 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0752) Prec@1 93.000 (87.370) Prec@5 100.000 (99.296) +2022-11-14 16:03:18,028 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0743) Prec@1 91.000 (87.500) Prec@5 100.000 (99.321) +2022-11-14 16:03:18,049 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0743) Prec@1 90.000 (87.586) Prec@5 99.000 (99.310) +2022-11-14 16:03:18,069 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0743) Prec@1 85.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 16:03:18,084 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0743) Prec@1 86.000 (87.452) Prec@5 100.000 (99.355) +2022-11-14 16:03:18,102 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0741) Prec@1 88.000 (87.469) Prec@5 100.000 (99.375) +2022-11-14 16:03:18,122 Test: 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Loss 0.0560 (0.0741) Prec@1 92.000 (87.692) Prec@5 100.000 (99.436) +2022-11-14 16:03:18,243 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0740) Prec@1 90.000 (87.750) Prec@5 99.000 (99.425) +2022-11-14 16:03:18,261 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0749) Prec@1 82.000 (87.610) Prec@5 99.000 (99.415) +2022-11-14 16:03:18,277 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0749) Prec@1 88.000 (87.619) Prec@5 99.000 (99.405) +2022-11-14 16:03:18,296 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0742) Prec@1 94.000 (87.767) Prec@5 100.000 (99.419) +2022-11-14 16:03:18,312 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0739) Prec@1 90.000 (87.818) Prec@5 99.000 (99.409) +2022-11-14 16:03:18,327 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0738) Prec@1 90.000 (87.867) Prec@5 99.000 (99.400) +2022-11-14 16:03:18,346 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0745) Prec@1 84.000 (87.783) Prec@5 99.000 (99.391) +2022-11-14 16:03:18,366 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0743) Prec@1 88.000 (87.787) Prec@5 100.000 (99.404) +2022-11-14 16:03:18,387 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0748) Prec@1 85.000 (87.729) Prec@5 98.000 (99.375) +2022-11-14 16:03:18,402 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0741) Prec@1 92.000 (87.816) Prec@5 100.000 (99.388) +2022-11-14 16:03:18,419 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0744) Prec@1 87.000 (87.800) Prec@5 98.000 (99.360) +2022-11-14 16:03:18,434 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0743) Prec@1 89.000 (87.824) Prec@5 100.000 (99.373) +2022-11-14 16:03:18,449 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0741) Prec@1 92.000 (87.904) Prec@5 99.000 (99.365) +2022-11-14 16:03:18,465 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0740) Prec@1 90.000 (87.943) Prec@5 100.000 (99.377) +2022-11-14 16:03:18,480 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0742) Prec@1 84.000 (87.870) Prec@5 98.000 (99.352) +2022-11-14 16:03:18,497 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0745) Prec@1 86.000 (87.836) Prec@5 100.000 (99.364) +2022-11-14 16:03:18,514 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0744) Prec@1 90.000 (87.875) Prec@5 99.000 (99.357) +2022-11-14 16:03:18,533 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0741) Prec@1 91.000 (87.930) Prec@5 100.000 (99.368) +2022-11-14 16:03:18,553 Test: [57/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 88.000 (87.931) Prec@5 98.000 (99.345) +2022-11-14 16:03:18,569 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.0748) Prec@1 84.000 (87.864) Prec@5 100.000 (99.356) +2022-11-14 16:03:18,583 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0748) Prec@1 88.000 (87.867) Prec@5 100.000 (99.367) +2022-11-14 16:03:18,598 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0750) Prec@1 88.000 (87.869) Prec@5 97.000 (99.328) +2022-11-14 16:03:18,616 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0750) Prec@1 86.000 (87.839) Prec@5 100.000 (99.339) +2022-11-14 16:03:18,635 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0750) Prec@1 87.000 (87.825) Prec@5 100.000 (99.349) +2022-11-14 16:03:18,654 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0308 (0.0743) Prec@1 93.000 (87.906) Prec@5 100.000 (99.359) +2022-11-14 16:03:18,671 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1068 (0.0748) Prec@1 82.000 (87.815) Prec@5 99.000 (99.354) +2022-11-14 16:03:18,686 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0750) Prec@1 89.000 (87.833) Prec@5 99.000 (99.348) +2022-11-14 16:03:18,707 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0747) Prec@1 91.000 (87.881) Prec@5 99.000 (99.343) +2022-11-14 16:03:18,726 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0746) Prec@1 90.000 (87.912) Prec@5 98.000 (99.324) +2022-11-14 16:03:18,741 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0747) Prec@1 88.000 (87.913) Prec@5 99.000 (99.319) +2022-11-14 16:03:18,757 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0747) Prec@1 87.000 (87.900) Prec@5 100.000 (99.329) +2022-11-14 16:03:18,774 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0748) Prec@1 89.000 (87.915) Prec@5 98.000 (99.310) +2022-11-14 16:03:18,796 Test: [71/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0748) Prec@1 89.000 (87.931) Prec@5 100.000 (99.319) +2022-11-14 16:03:18,816 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0744) Prec@1 92.000 (87.986) Prec@5 100.000 (99.329) +2022-11-14 16:03:18,832 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0740) Prec@1 91.000 (88.027) Prec@5 100.000 (99.338) +2022-11-14 16:03:18,847 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0744) Prec@1 84.000 (87.973) Prec@5 100.000 (99.347) +2022-11-14 16:03:18,863 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0743) Prec@1 89.000 (87.987) Prec@5 100.000 (99.355) +2022-11-14 16:03:18,884 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0740) Prec@1 91.000 (88.026) Prec@5 100.000 (99.364) +2022-11-14 16:03:18,901 Test: [77/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0742) Prec@1 86.000 (88.000) Prec@5 99.000 (99.359) +2022-11-14 16:03:18,921 Test: [78/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0741) Prec@1 88.000 (88.000) Prec@5 99.000 (99.354) +2022-11-14 16:03:18,936 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0741) Prec@1 87.000 (87.987) Prec@5 100.000 (99.362) +2022-11-14 16:03:18,951 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 88.000 (87.988) Prec@5 100.000 (99.370) +2022-11-14 16:03:18,970 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0741) Prec@1 88.000 (87.988) Prec@5 100.000 (99.378) +2022-11-14 16:03:18,991 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0744) Prec@1 84.000 (87.940) Prec@5 99.000 (99.373) +2022-11-14 16:03:19,006 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0743) Prec@1 86.000 (87.917) Prec@5 100.000 (99.381) +2022-11-14 16:03:19,025 Test: [84/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0744) Prec@1 85.000 (87.882) Prec@5 99.000 (99.376) +2022-11-14 16:03:19,048 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0745) Prec@1 86.000 (87.860) Prec@5 99.000 (99.372) +2022-11-14 16:03:19,066 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0743) Prec@1 90.000 (87.885) Prec@5 100.000 (99.379) +2022-11-14 16:03:19,086 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0744) Prec@1 88.000 (87.886) Prec@5 99.000 (99.375) +2022-11-14 16:03:19,103 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0743) Prec@1 88.000 (87.888) Prec@5 99.000 (99.371) +2022-11-14 16:03:19,122 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0742) Prec@1 92.000 (87.933) Prec@5 100.000 (99.378) +2022-11-14 16:03:19,140 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0740) Prec@1 92.000 (87.978) Prec@5 100.000 (99.385) +2022-11-14 16:03:19,157 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0459 (0.0737) Prec@1 94.000 (88.043) Prec@5 100.000 (99.391) +2022-11-14 16:03:19,176 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0737) Prec@1 90.000 (88.065) Prec@5 99.000 (99.387) +2022-11-14 16:03:19,192 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0736) Prec@1 89.000 (88.074) Prec@5 99.000 (99.383) +2022-11-14 16:03:19,211 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0738) Prec@1 84.000 (88.032) Prec@5 99.000 (99.379) +2022-11-14 16:03:19,229 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0737) Prec@1 90.000 (88.052) Prec@5 98.000 (99.365) +2022-11-14 16:03:19,248 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0444 (0.0734) Prec@1 93.000 (88.103) Prec@5 99.000 (99.361) +2022-11-14 16:03:19,268 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0737) Prec@1 86.000 (88.082) Prec@5 98.000 (99.347) +2022-11-14 16:03:19,284 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0739) Prec@1 86.000 (88.061) Prec@5 99.000 (99.343) +2022-11-14 16:03:19,301 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0739) Prec@1 88.000 (88.060) Prec@5 100.000 (99.350) +2022-11-14 16:03:19,364 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:03:19,716 Epoch: [297][0/500] Time 0.025 (0.025) Data 0.259 (0.259) Loss 0.0388 (0.0388) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:20,183 Epoch: [297][10/500] Time 0.046 (0.039) Data 0.003 (0.025) Loss 0.0227 (0.0308) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:03:20,689 Epoch: [297][20/500] Time 0.053 (0.042) Data 0.002 (0.014) Loss 0.0197 (0.0271) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:03:21,179 Epoch: [297][30/500] Time 0.049 (0.043) Data 0.002 (0.010) Loss 0.0508 (0.0330) Prec@1 93.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:03:21,687 Epoch: [297][40/500] Time 0.047 (0.043) Data 0.002 (0.008) Loss 0.0168 (0.0298) Prec@1 98.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:03:22,207 Epoch: [297][50/500] Time 0.053 (0.044) Data 0.002 (0.007) Loss 0.0393 (0.0313) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:03:22,725 Epoch: [297][60/500] Time 0.040 (0.044) Data 0.002 (0.006) Loss 0.0399 (0.0326) Prec@1 94.000 (95.143) Prec@5 99.000 (99.857) +2022-11-14 16:03:23,241 Epoch: [297][70/500] Time 0.046 (0.044) Data 0.002 (0.006) Loss 0.0181 (0.0308) Prec@1 97.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:03:23,771 Epoch: [297][80/500] Time 0.058 (0.045) Data 0.002 (0.005) Loss 0.0288 (0.0306) Prec@1 96.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:03:24,299 Epoch: [297][90/500] Time 0.050 (0.045) Data 0.002 (0.005) Loss 0.0304 (0.0305) Prec@1 94.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 16:03:24,839 Epoch: [297][100/500] Time 0.049 (0.045) Data 0.002 (0.005) Loss 0.0288 (0.0304) Prec@1 96.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 16:03:25,351 Epoch: [297][110/500] Time 0.047 (0.045) Data 0.002 (0.004) Loss 0.0304 (0.0304) Prec@1 94.000 (95.250) Prec@5 100.000 (99.917) +2022-11-14 16:03:25,910 Epoch: [297][120/500] Time 0.053 (0.046) Data 0.002 (0.004) Loss 0.0395 (0.0311) Prec@1 92.000 (95.000) Prec@5 99.000 (99.846) +2022-11-14 16:03:26,429 Epoch: [297][130/500] Time 0.054 (0.046) Data 0.002 (0.004) Loss 0.0256 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 16:03:26,983 Epoch: [297][140/500] Time 0.046 (0.046) Data 0.002 (0.004) Loss 0.0168 (0.0298) Prec@1 96.000 (95.067) Prec@5 100.000 (99.867) +2022-11-14 16:03:27,510 Epoch: [297][150/500] Time 0.049 (0.046) Data 0.002 (0.004) Loss 0.0364 (0.0302) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:03:28,096 Epoch: [297][160/500] Time 0.044 (0.046) Data 0.002 (0.004) Loss 0.0413 (0.0308) Prec@1 94.000 (95.059) Prec@5 100.000 (99.882) +2022-11-14 16:03:28,611 Epoch: [297][170/500] Time 0.049 (0.046) Data 0.002 (0.004) Loss 0.0275 (0.0306) Prec@1 95.000 (95.056) Prec@5 100.000 (99.889) +2022-11-14 16:03:29,120 Epoch: [297][180/500] Time 0.043 (0.046) Data 0.002 (0.004) Loss 0.0623 (0.0323) Prec@1 89.000 (94.737) Prec@5 100.000 (99.895) +2022-11-14 16:03:29,725 Epoch: [297][190/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0490 (0.0331) Prec@1 91.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 16:03:30,232 Epoch: [297][200/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0171 (0.0324) Prec@1 98.000 (94.714) Prec@5 100.000 (99.905) +2022-11-14 16:03:30,778 Epoch: [297][210/500] Time 0.058 (0.047) Data 0.002 (0.003) Loss 0.0358 (0.0325) Prec@1 96.000 (94.773) Prec@5 100.000 (99.909) +2022-11-14 16:03:31,331 Epoch: [297][220/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0374 (0.0327) Prec@1 94.000 (94.739) Prec@5 99.000 (99.870) +2022-11-14 16:03:31,866 Epoch: [297][230/500] Time 0.060 (0.047) Data 0.002 (0.003) Loss 0.0327 (0.0327) Prec@1 94.000 (94.708) Prec@5 100.000 (99.875) +2022-11-14 16:03:32,403 Epoch: [297][240/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0438 (0.0332) Prec@1 92.000 (94.600) Prec@5 100.000 (99.880) +2022-11-14 16:03:32,920 Epoch: [297][250/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0174 (0.0326) Prec@1 97.000 (94.692) Prec@5 100.000 (99.885) +2022-11-14 16:03:33,507 Epoch: [297][260/500] Time 0.063 (0.047) Data 0.002 (0.003) Loss 0.0417 (0.0329) Prec@1 92.000 (94.593) Prec@5 100.000 (99.889) +2022-11-14 16:03:34,061 Epoch: [297][270/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0434 (0.0333) Prec@1 91.000 (94.464) Prec@5 100.000 (99.893) +2022-11-14 16:03:34,610 Epoch: [297][280/500] Time 0.038 (0.047) Data 0.002 (0.003) Loss 0.0201 (0.0328) Prec@1 97.000 (94.552) Prec@5 100.000 (99.897) +2022-11-14 16:03:35,126 Epoch: [297][290/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0299 (0.0327) Prec@1 96.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 16:03:35,691 Epoch: [297][300/500] Time 0.074 (0.047) Data 0.002 (0.003) Loss 0.0378 (0.0329) Prec@1 94.000 (94.581) Prec@5 100.000 (99.903) +2022-11-14 16:03:36,240 Epoch: [297][310/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0412 (0.0332) Prec@1 91.000 (94.469) Prec@5 100.000 (99.906) +2022-11-14 16:03:36,774 Epoch: [297][320/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0316 (0.0331) Prec@1 95.000 (94.485) Prec@5 100.000 (99.909) +2022-11-14 16:03:37,307 Epoch: [297][330/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0394 (0.0333) Prec@1 94.000 (94.471) Prec@5 99.000 (99.882) +2022-11-14 16:03:37,827 Epoch: [297][340/500] Time 0.058 (0.047) Data 0.002 (0.003) Loss 0.0138 (0.0327) Prec@1 99.000 (94.600) Prec@5 100.000 (99.886) +2022-11-14 16:03:38,355 Epoch: [297][350/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0589 (0.0335) Prec@1 89.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:03:38,861 Epoch: [297][360/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0293 (0.0334) Prec@1 96.000 (94.486) Prec@5 100.000 (99.892) +2022-11-14 16:03:39,471 Epoch: [297][370/500] Time 0.065 (0.047) Data 0.002 (0.003) Loss 0.0413 (0.0336) Prec@1 93.000 (94.447) Prec@5 100.000 (99.895) +2022-11-14 16:03:39,957 Epoch: [297][380/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0278 (0.0334) Prec@1 96.000 (94.487) Prec@5 100.000 (99.897) +2022-11-14 16:03:40,507 Epoch: [297][390/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.0365 (0.0335) Prec@1 96.000 (94.525) Prec@5 100.000 (99.900) +2022-11-14 16:03:41,023 Epoch: [297][400/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0275 (0.0333) Prec@1 95.000 (94.537) Prec@5 100.000 (99.902) +2022-11-14 16:03:41,595 Epoch: [297][410/500] Time 0.063 (0.047) Data 0.003 (0.003) Loss 0.0223 (0.0331) Prec@1 97.000 (94.595) Prec@5 100.000 (99.905) +2022-11-14 16:03:42,137 Epoch: [297][420/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0441 (0.0333) Prec@1 92.000 (94.535) Prec@5 100.000 (99.907) +2022-11-14 16:03:42,716 Epoch: [297][430/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0366 (0.0334) Prec@1 94.000 (94.523) Prec@5 99.000 (99.886) +2022-11-14 16:03:43,329 Epoch: [297][440/500] Time 0.060 (0.048) Data 0.002 (0.003) Loss 0.0444 (0.0337) Prec@1 92.000 (94.467) Prec@5 100.000 (99.889) +2022-11-14 16:03:43,936 Epoch: [297][450/500] Time 0.060 (0.048) Data 0.003 (0.003) Loss 0.0230 (0.0334) Prec@1 98.000 (94.543) Prec@5 100.000 (99.891) +2022-11-14 16:03:44,487 Epoch: [297][460/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0354 (0.0335) Prec@1 92.000 (94.489) Prec@5 100.000 (99.894) +2022-11-14 16:03:45,075 Epoch: [297][470/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0205 (0.0332) Prec@1 95.000 (94.500) Prec@5 100.000 (99.896) +2022-11-14 16:03:45,623 Epoch: [297][480/500] Time 0.065 (0.048) Data 0.002 (0.003) Loss 0.0325 (0.0332) Prec@1 95.000 (94.510) Prec@5 100.000 (99.898) +2022-11-14 16:03:46,182 Epoch: [297][490/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0309 (0.0331) Prec@1 95.000 (94.520) Prec@5 100.000 (99.900) +2022-11-14 16:03:46,660 Epoch: [297][499/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0286 (0.0330) Prec@1 95.000 (94.529) Prec@5 100.000 (99.902) +2022-11-14 16:03:47,010 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0517 (0.0517) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:47,020 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0767 (0.0642) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:47,032 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0490 (0.0592) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:47,051 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0871 (0.0662) Prec@1 83.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:03:47,062 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0669) Prec@1 89.000 (87.800) Prec@5 100.000 (100.000) +2022-11-14 16:03:47,077 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0518 (0.0644) Prec@1 91.000 (88.333) Prec@5 99.000 (99.833) +2022-11-14 16:03:47,090 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0535 (0.0628) Prec@1 92.000 (88.857) Prec@5 100.000 (99.857) +2022-11-14 16:03:47,107 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.0663) Prec@1 84.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 16:03:47,126 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0672) Prec@1 88.000 (88.222) Prec@5 98.000 (99.556) +2022-11-14 16:03:47,143 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0666) Prec@1 91.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:03:47,159 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0696 (0.0669) Prec@1 89.000 (88.545) Prec@5 100.000 (99.545) +2022-11-14 16:03:47,173 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0870 (0.0685) Prec@1 86.000 (88.333) Prec@5 99.000 (99.500) +2022-11-14 16:03:47,188 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0666 (0.0684) Prec@1 89.000 (88.385) Prec@5 100.000 (99.538) +2022-11-14 16:03:47,206 Test: [13/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0687) Prec@1 89.000 (88.429) Prec@5 98.000 (99.429) +2022-11-14 16:03:47,226 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0697) Prec@1 85.000 (88.200) Prec@5 97.000 (99.267) +2022-11-14 16:03:47,240 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0704) Prec@1 86.000 (88.062) Prec@5 99.000 (99.250) +2022-11-14 16:03:47,257 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0702) Prec@1 90.000 (88.176) Prec@5 98.000 (99.176) +2022-11-14 16:03:47,276 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1052 (0.0721) Prec@1 85.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 16:03:47,298 Test: [18/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0895 (0.0730) Prec@1 88.000 (88.000) Prec@5 97.000 (99.105) +2022-11-14 16:03:47,319 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0844 (0.0736) Prec@1 86.000 (87.900) Prec@5 99.000 (99.100) +2022-11-14 16:03:47,337 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0739) Prec@1 86.000 (87.810) Prec@5 100.000 (99.143) +2022-11-14 16:03:47,360 Test: [21/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0736) Prec@1 88.000 (87.818) Prec@5 100.000 (99.182) +2022-11-14 16:03:47,386 Test: [22/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1008 (0.0748) Prec@1 86.000 (87.739) Prec@5 97.000 (99.087) +2022-11-14 16:03:47,407 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0744) Prec@1 91.000 (87.875) Prec@5 100.000 (99.125) +2022-11-14 16:03:47,428 Test: [24/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0747) Prec@1 85.000 (87.760) Prec@5 100.000 (99.160) +2022-11-14 16:03:47,441 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0968 (0.0755) Prec@1 85.000 (87.654) Prec@5 99.000 (99.154) +2022-11-14 16:03:47,458 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0677 (0.0752) Prec@1 87.000 (87.630) Prec@5 100.000 (99.185) +2022-11-14 16:03:47,474 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0501 (0.0743) Prec@1 92.000 (87.786) Prec@5 99.000 (99.179) +2022-11-14 16:03:47,490 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0636 (0.0740) Prec@1 89.000 (87.828) Prec@5 97.000 (99.103) +2022-11-14 16:03:47,507 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0740) Prec@1 86.000 (87.767) Prec@5 100.000 (99.133) +2022-11-14 16:03:47,522 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0743) Prec@1 86.000 (87.710) Prec@5 100.000 (99.161) +2022-11-14 16:03:47,540 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0744) Prec@1 89.000 (87.750) Prec@5 99.000 (99.156) +2022-11-14 16:03:47,559 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0885 (0.0748) Prec@1 85.000 (87.667) Prec@5 100.000 (99.182) +2022-11-14 16:03:47,576 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0751) Prec@1 85.000 (87.588) Prec@5 99.000 (99.176) +2022-11-14 16:03:47,594 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0677 (0.0749) Prec@1 87.000 (87.571) Prec@5 99.000 (99.171) +2022-11-14 16:03:47,614 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0746) Prec@1 89.000 (87.611) Prec@5 100.000 (99.194) +2022-11-14 16:03:47,628 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0748) Prec@1 87.000 (87.595) Prec@5 99.000 (99.189) +2022-11-14 16:03:47,645 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.0756) Prec@1 81.000 (87.421) Prec@5 100.000 (99.211) +2022-11-14 16:03:47,664 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0582 (0.0751) Prec@1 90.000 (87.487) Prec@5 99.000 (99.205) +2022-11-14 16:03:47,684 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0748) Prec@1 92.000 (87.600) Prec@5 100.000 (99.225) +2022-11-14 16:03:47,702 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0750) Prec@1 86.000 (87.561) Prec@5 99.000 (99.220) +2022-11-14 16:03:47,717 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0573 (0.0746) Prec@1 92.000 (87.667) Prec@5 100.000 (99.238) +2022-11-14 16:03:47,736 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0744) Prec@1 90.000 (87.721) Prec@5 99.000 (99.233) +2022-11-14 16:03:47,755 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0744) Prec@1 90.000 (87.773) Prec@5 98.000 (99.205) +2022-11-14 16:03:47,775 Test: [44/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0552 (0.0740) Prec@1 93.000 (87.889) Prec@5 98.000 (99.178) +2022-11-14 16:03:47,793 Test: [45/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1010 (0.0746) Prec@1 84.000 (87.804) Prec@5 96.000 (99.109) +2022-11-14 16:03:47,812 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0745) Prec@1 88.000 (87.809) Prec@5 100.000 (99.128) +2022-11-14 16:03:47,828 Test: [47/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1077 (0.0752) Prec@1 84.000 (87.729) Prec@5 97.000 (99.083) +2022-11-14 16:03:47,845 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0416 (0.0745) Prec@1 92.000 (87.816) Prec@5 99.000 (99.082) +2022-11-14 16:03:47,866 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1218 (0.0754) Prec@1 80.000 (87.660) Prec@5 100.000 (99.100) +2022-11-14 16:03:47,885 Test: [50/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0751) Prec@1 92.000 (87.745) Prec@5 99.000 (99.098) +2022-11-14 16:03:47,903 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0751) Prec@1 87.000 (87.731) Prec@5 100.000 (99.115) +2022-11-14 16:03:47,918 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0753) Prec@1 84.000 (87.660) Prec@5 100.000 (99.132) +2022-11-14 16:03:47,937 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0751) Prec@1 90.000 (87.704) Prec@5 100.000 (99.148) +2022-11-14 16:03:47,955 Test: [54/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0752) Prec@1 86.000 (87.673) Prec@5 100.000 (99.164) +2022-11-14 16:03:47,974 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0749) Prec@1 91.000 (87.732) Prec@5 98.000 (99.143) +2022-11-14 16:03:47,993 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0460 (0.0744) Prec@1 92.000 (87.807) Prec@5 100.000 (99.158) +2022-11-14 16:03:48,009 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0803 (0.0745) Prec@1 89.000 (87.828) Prec@5 99.000 (99.155) +2022-11-14 16:03:48,026 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0747) Prec@1 87.000 (87.814) Prec@5 99.000 (99.153) +2022-11-14 16:03:48,045 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0745) Prec@1 88.000 (87.817) Prec@5 100.000 (99.167) +2022-11-14 16:03:48,064 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0745) Prec@1 87.000 (87.803) Prec@5 99.000 (99.164) +2022-11-14 16:03:48,082 Test: [61/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0555 (0.0742) Prec@1 89.000 (87.823) Prec@5 100.000 (99.177) +2022-11-14 16:03:48,102 Test: [62/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0742) Prec@1 90.000 (87.857) Prec@5 99.000 (99.175) +2022-11-14 16:03:48,125 Test: [63/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0737) Prec@1 94.000 (87.953) Prec@5 100.000 (99.188) +2022-11-14 16:03:48,144 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1022 (0.0741) Prec@1 84.000 (87.892) Prec@5 99.000 (99.185) +2022-11-14 16:03:48,170 Test: [65/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0702 (0.0741) Prec@1 89.000 (87.909) Prec@5 99.000 (99.182) +2022-11-14 16:03:48,189 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0422 (0.0736) Prec@1 94.000 (88.000) Prec@5 100.000 (99.194) +2022-11-14 16:03:48,212 Test: [67/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0736) Prec@1 89.000 (88.015) Prec@5 97.000 (99.162) +2022-11-14 16:03:48,232 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0735) Prec@1 88.000 (88.014) Prec@5 99.000 (99.159) +2022-11-14 16:03:48,250 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0737) Prec@1 84.000 (87.957) Prec@5 100.000 (99.171) +2022-11-14 16:03:48,274 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0895 (0.0739) Prec@1 86.000 (87.930) Prec@5 99.000 (99.169) +2022-11-14 16:03:48,297 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0737) Prec@1 91.000 (87.972) Prec@5 100.000 (99.181) +2022-11-14 16:03:48,318 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0569 (0.0735) Prec@1 91.000 (88.014) Prec@5 99.000 (99.178) +2022-11-14 16:03:48,338 Test: [73/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0338 (0.0729) Prec@1 94.000 (88.095) Prec@5 100.000 (99.189) +2022-11-14 16:03:48,356 Test: [74/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0732) Prec@1 86.000 (88.067) Prec@5 100.000 (99.200) +2022-11-14 16:03:48,373 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0732) Prec@1 89.000 (88.079) Prec@5 99.000 (99.197) +2022-11-14 16:03:48,390 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0730) Prec@1 92.000 (88.130) Prec@5 100.000 (99.208) +2022-11-14 16:03:48,406 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0808 (0.0731) Prec@1 87.000 (88.115) Prec@5 99.000 (99.205) +2022-11-14 16:03:48,422 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0732) Prec@1 86.000 (88.089) Prec@5 100.000 (99.215) +2022-11-14 16:03:48,442 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0733) Prec@1 88.000 (88.088) Prec@5 99.000 (99.213) +2022-11-14 16:03:48,462 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0734) Prec@1 89.000 (88.099) Prec@5 100.000 (99.222) +2022-11-14 16:03:48,479 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0735) Prec@1 86.000 (88.073) Prec@5 99.000 (99.220) +2022-11-14 16:03:48,498 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0734) Prec@1 88.000 (88.072) Prec@5 99.000 (99.217) +2022-11-14 16:03:48,519 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0733) Prec@1 88.000 (88.071) Prec@5 100.000 (99.226) +2022-11-14 16:03:48,539 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0777 (0.0733) Prec@1 87.000 (88.059) Prec@5 99.000 (99.224) +2022-11-14 16:03:48,562 Test: [85/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.1246 (0.0739) Prec@1 79.000 (87.953) Prec@5 100.000 (99.233) +2022-11-14 16:03:48,582 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0739) Prec@1 86.000 (87.931) Prec@5 99.000 (99.230) +2022-11-14 16:03:48,602 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0741) Prec@1 88.000 (87.932) Prec@5 98.000 (99.216) +2022-11-14 16:03:48,622 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0615 (0.0739) Prec@1 89.000 (87.944) Prec@5 99.000 (99.213) +2022-11-14 16:03:48,643 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0650 (0.0738) Prec@1 89.000 (87.956) Prec@5 100.000 (99.222) +2022-11-14 16:03:48,663 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0738) Prec@1 90.000 (87.978) Prec@5 100.000 (99.231) +2022-11-14 16:03:48,681 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0417 (0.0734) Prec@1 93.000 (88.033) Prec@5 100.000 (99.239) +2022-11-14 16:03:48,697 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.0736) Prec@1 86.000 (88.011) Prec@5 100.000 (99.247) +2022-11-14 16:03:48,718 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0735) Prec@1 89.000 (88.021) Prec@5 100.000 (99.255) +2022-11-14 16:03:48,734 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0734) Prec@1 87.000 (88.011) Prec@5 99.000 (99.253) +2022-11-14 16:03:48,752 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0734) Prec@1 88.000 (88.010) Prec@5 98.000 (99.240) +2022-11-14 16:03:48,769 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0548 (0.0732) Prec@1 93.000 (88.062) Prec@5 99.000 (99.237) +2022-11-14 16:03:48,785 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0733) Prec@1 86.000 (88.041) Prec@5 99.000 (99.235) +2022-11-14 16:03:48,799 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0996 (0.0736) Prec@1 85.000 (88.010) Prec@5 100.000 (99.242) +2022-11-14 16:03:48,816 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0736) Prec@1 87.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 16:03:48,884 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:03:49,273 Epoch: [298][0/500] Time 0.024 (0.024) Data 0.286 (0.286) Loss 0.0453 (0.0453) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:49,717 Epoch: [298][10/500] Time 0.049 (0.038) Data 0.002 (0.028) Loss 0.0385 (0.0419) Prec@1 93.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:50,318 Epoch: [298][20/500] Time 0.065 (0.046) Data 0.002 (0.016) Loss 0.0131 (0.0323) Prec@1 98.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:50,874 Epoch: [298][30/500] Time 0.059 (0.048) Data 0.003 (0.011) Loss 0.0246 (0.0304) Prec@1 98.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:03:51,519 Epoch: [298][40/500] Time 0.063 (0.050) Data 0.002 (0.009) Loss 0.0412 (0.0326) Prec@1 94.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 16:03:52,043 Epoch: [298][50/500] Time 0.054 (0.050) Data 0.002 (0.008) Loss 0.0480 (0.0351) Prec@1 92.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:03:52,601 Epoch: [298][60/500] Time 0.052 (0.050) Data 0.002 (0.007) Loss 0.0246 (0.0336) Prec@1 96.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 16:03:53,135 Epoch: [298][70/500] Time 0.056 (0.049) Data 0.002 (0.006) Loss 0.0077 (0.0304) Prec@1 99.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 16:03:53,672 Epoch: [298][80/500] Time 0.059 (0.049) Data 0.002 (0.006) Loss 0.0333 (0.0307) Prec@1 95.000 (95.111) Prec@5 99.000 (99.889) +2022-11-14 16:03:54,177 Epoch: [298][90/500] Time 0.046 (0.049) Data 0.003 (0.005) Loss 0.0269 (0.0303) Prec@1 96.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:03:54,701 Epoch: [298][100/500] Time 0.050 (0.048) Data 0.003 (0.005) Loss 0.0336 (0.0306) Prec@1 93.000 (95.000) Prec@5 100.000 (99.909) +2022-11-14 16:03:55,231 Epoch: [298][110/500] Time 0.050 (0.048) Data 0.002 (0.005) Loss 0.0446 (0.0318) Prec@1 92.000 (94.750) Prec@5 100.000 (99.917) +2022-11-14 16:03:55,756 Epoch: [298][120/500] Time 0.048 (0.048) Data 0.002 (0.005) Loss 0.0305 (0.0317) Prec@1 95.000 (94.769) Prec@5 100.000 (99.923) +2022-11-14 16:03:56,311 Epoch: [298][130/500] Time 0.067 (0.048) Data 0.002 (0.004) Loss 0.0126 (0.0303) Prec@1 98.000 (95.000) Prec@5 100.000 (99.929) +2022-11-14 16:03:56,900 Epoch: [298][140/500] Time 0.050 (0.049) Data 0.003 (0.004) Loss 0.0184 (0.0295) Prec@1 98.000 (95.200) Prec@5 99.000 (99.867) +2022-11-14 16:03:57,485 Epoch: [298][150/500] Time 0.043 (0.049) Data 0.003 (0.004) Loss 0.0226 (0.0291) Prec@1 96.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:03:58,031 Epoch: [298][160/500] Time 0.039 (0.049) Data 0.002 (0.004) Loss 0.0315 (0.0292) Prec@1 93.000 (95.118) Prec@5 100.000 (99.882) +2022-11-14 16:03:58,636 Epoch: [298][170/500] Time 0.075 (0.049) Data 0.002 (0.004) Loss 0.0288 (0.0292) Prec@1 97.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 16:03:59,189 Epoch: [298][180/500] Time 0.054 (0.049) Data 0.002 (0.004) Loss 0.0281 (0.0291) Prec@1 96.000 (95.263) Prec@5 99.000 (99.842) +2022-11-14 16:03:59,773 Epoch: [298][190/500] Time 0.047 (0.049) Data 0.002 (0.004) Loss 0.0317 (0.0293) Prec@1 93.000 (95.150) Prec@5 100.000 (99.850) +2022-11-14 16:04:00,285 Epoch: [298][200/500] Time 0.054 (0.049) Data 0.002 (0.004) Loss 0.0598 (0.0307) Prec@1 91.000 (94.952) Prec@5 100.000 (99.857) +2022-11-14 16:04:00,808 Epoch: [298][210/500] Time 0.051 (0.049) Data 0.002 (0.004) Loss 0.0158 (0.0300) Prec@1 97.000 (95.045) Prec@5 100.000 (99.864) +2022-11-14 16:04:01,329 Epoch: [298][220/500] Time 0.032 (0.049) Data 0.002 (0.004) Loss 0.0392 (0.0304) Prec@1 94.000 (95.000) Prec@5 100.000 (99.870) +2022-11-14 16:04:01,841 Epoch: [298][230/500] Time 0.061 (0.049) Data 0.002 (0.003) Loss 0.0314 (0.0305) Prec@1 94.000 (94.958) Prec@5 100.000 (99.875) +2022-11-14 16:04:02,348 Epoch: [298][240/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0172 (0.0300) Prec@1 98.000 (95.080) Prec@5 100.000 (99.880) +2022-11-14 16:04:02,886 Epoch: [298][250/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0335 (0.0301) Prec@1 96.000 (95.115) Prec@5 100.000 (99.885) +2022-11-14 16:04:03,395 Epoch: [298][260/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0543 (0.0310) Prec@1 90.000 (94.926) Prec@5 100.000 (99.889) +2022-11-14 16:04:03,913 Epoch: [298][270/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0557 (0.0319) Prec@1 89.000 (94.714) Prec@5 100.000 (99.893) +2022-11-14 16:04:04,471 Epoch: [298][280/500] Time 0.046 (0.049) Data 0.002 (0.003) Loss 0.0309 (0.0318) Prec@1 95.000 (94.724) Prec@5 100.000 (99.897) +2022-11-14 16:04:05,005 Epoch: [298][290/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0300 (0.0318) Prec@1 96.000 (94.767) Prec@5 100.000 (99.900) +2022-11-14 16:04:05,523 Epoch: [298][300/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0291 (0.0317) Prec@1 95.000 (94.774) Prec@5 100.000 (99.903) +2022-11-14 16:04:06,080 Epoch: [298][310/500] Time 0.062 (0.048) Data 0.002 (0.003) Loss 0.0267 (0.0315) Prec@1 97.000 (94.844) Prec@5 100.000 (99.906) +2022-11-14 16:04:06,650 Epoch: [298][320/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0430 (0.0319) Prec@1 92.000 (94.758) Prec@5 100.000 (99.909) +2022-11-14 16:04:07,173 Epoch: [298][330/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0343 (0.0320) Prec@1 93.000 (94.706) Prec@5 100.000 (99.912) +2022-11-14 16:04:07,690 Epoch: [298][340/500] Time 0.048 (0.048) Data 0.003 (0.003) Loss 0.0519 (0.0325) Prec@1 90.000 (94.571) Prec@5 97.000 (99.829) +2022-11-14 16:04:08,207 Epoch: [298][350/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0287 (0.0324) Prec@1 95.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 16:04:08,762 Epoch: [298][360/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0309 (0.0324) Prec@1 95.000 (94.595) Prec@5 100.000 (99.838) +2022-11-14 16:04:09,287 Epoch: [298][370/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0477 (0.0328) Prec@1 92.000 (94.526) Prec@5 100.000 (99.842) +2022-11-14 16:04:09,904 Epoch: [298][380/500] Time 0.064 (0.049) Data 0.002 (0.003) Loss 0.0158 (0.0323) Prec@1 98.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 16:04:10,406 Epoch: [298][390/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0325 (0.0323) Prec@1 96.000 (94.650) Prec@5 100.000 (99.850) +2022-11-14 16:04:10,930 Epoch: [298][400/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0191 (0.0320) Prec@1 97.000 (94.707) Prec@5 100.000 (99.854) +2022-11-14 16:04:11,451 Epoch: [298][410/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0490 (0.0324) Prec@1 93.000 (94.667) Prec@5 99.000 (99.833) +2022-11-14 16:04:11,990 Epoch: [298][420/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0258 (0.0323) Prec@1 96.000 (94.698) Prec@5 100.000 (99.837) +2022-11-14 16:04:12,506 Epoch: [298][430/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0147 (0.0319) Prec@1 97.000 (94.750) Prec@5 100.000 (99.841) +2022-11-14 16:04:13,107 Epoch: [298][440/500] Time 0.036 (0.048) Data 0.002 (0.003) Loss 0.0223 (0.0317) Prec@1 98.000 (94.822) Prec@5 100.000 (99.844) +2022-11-14 16:04:13,615 Epoch: [298][450/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0354 (0.0317) Prec@1 96.000 (94.848) Prec@5 100.000 (99.848) +2022-11-14 16:04:14,134 Epoch: [298][460/500] Time 0.046 (0.048) Data 0.003 (0.003) Loss 0.0364 (0.0318) Prec@1 95.000 (94.851) Prec@5 100.000 (99.851) +2022-11-14 16:04:14,662 Epoch: [298][470/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0236 (0.0317) Prec@1 96.000 (94.875) Prec@5 100.000 (99.854) +2022-11-14 16:04:15,202 Epoch: [298][480/500] Time 0.039 (0.048) Data 0.002 (0.003) Loss 0.0262 (0.0316) Prec@1 96.000 (94.898) Prec@5 100.000 (99.857) +2022-11-14 16:04:15,733 Epoch: [298][490/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0482 (0.0319) Prec@1 92.000 (94.840) Prec@5 100.000 (99.860) +2022-11-14 16:04:16,204 Epoch: [298][499/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0379 (0.0320) Prec@1 95.000 (94.843) Prec@5 100.000 (99.863) +2022-11-14 16:04:16,600 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0631 (0.0631) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:04:16,613 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0729 (0.0680) Prec@1 90.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 16:04:16,624 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0770 (0.0710) Prec@1 86.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:04:16,639 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0709 (0.0710) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:04:16,650 Test: [4/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0875 (0.0743) Prec@1 86.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 16:04:16,661 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0503 (0.0703) Prec@1 92.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 16:04:16,674 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0627 (0.0692) Prec@1 93.000 (89.286) Prec@5 98.000 (99.286) +2022-11-14 16:04:16,688 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0790 (0.0704) Prec@1 85.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 16:04:16,704 Test: [8/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0867 (0.0722) Prec@1 85.000 (88.333) Prec@5 98.000 (99.111) +2022-11-14 16:04:16,718 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0770 (0.0727) Prec@1 88.000 (88.300) Prec@5 97.000 (98.900) +2022-11-14 16:04:16,732 Test: [10/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0902 (0.0743) Prec@1 85.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 16:04:16,749 Test: [11/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0807 (0.0748) Prec@1 86.000 (87.833) Prec@5 99.000 (99.000) +2022-11-14 16:04:16,764 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0623 (0.0739) Prec@1 89.000 (87.923) Prec@5 100.000 (99.077) +2022-11-14 16:04:16,780 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0451 (0.0718) Prec@1 93.000 (88.286) Prec@5 100.000 (99.143) +2022-11-14 16:04:16,796 Test: [14/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0603 (0.0711) Prec@1 88.000 (88.267) Prec@5 99.000 (99.133) +2022-11-14 16:04:16,812 Test: [15/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.0719) Prec@1 85.000 (88.062) Prec@5 100.000 (99.188) +2022-11-14 16:04:16,826 Test: [16/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0611 (0.0713) Prec@1 90.000 (88.176) Prec@5 99.000 (99.176) +2022-11-14 16:04:16,841 Test: [17/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1000 (0.0729) Prec@1 86.000 (88.056) Prec@5 99.000 (99.167) +2022-11-14 16:04:16,856 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.0736) Prec@1 84.000 (87.842) Prec@5 100.000 (99.211) +2022-11-14 16:04:16,874 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1092 (0.0753) Prec@1 84.000 (87.650) Prec@5 99.000 (99.200) +2022-11-14 16:04:16,893 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0751) Prec@1 87.000 (87.619) Prec@5 98.000 (99.143) +2022-11-14 16:04:16,910 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0753) Prec@1 88.000 (87.636) Prec@5 99.000 (99.136) +2022-11-14 16:04:16,925 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0759) Prec@1 86.000 (87.565) Prec@5 96.000 (99.000) +2022-11-14 16:04:16,940 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0756) Prec@1 89.000 (87.625) Prec@5 100.000 (99.042) +2022-11-14 16:04:16,957 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0763) Prec@1 84.000 (87.480) Prec@5 100.000 (99.080) +2022-11-14 16:04:16,978 Test: [25/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0765) Prec@1 88.000 (87.500) Prec@5 99.000 (99.077) +2022-11-14 16:04:17,006 Test: [26/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0759) Prec@1 87.000 (87.481) Prec@5 100.000 (99.111) +2022-11-14 16:04:17,031 Test: [27/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0693 (0.0756) Prec@1 89.000 (87.536) Prec@5 100.000 (99.143) +2022-11-14 16:04:17,055 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0752) Prec@1 90.000 (87.621) Prec@5 98.000 (99.103) +2022-11-14 16:04:17,077 Test: [29/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0748) Prec@1 91.000 (87.733) Prec@5 100.000 (99.133) +2022-11-14 16:04:17,102 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0749) Prec@1 85.000 (87.645) Prec@5 100.000 (99.161) +2022-11-14 16:04:17,126 Test: [31/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0751) Prec@1 86.000 (87.594) Prec@5 100.000 (99.188) +2022-11-14 16:04:17,148 Test: [32/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0751) Prec@1 81.000 (87.394) Prec@5 100.000 (99.212) +2022-11-14 16:04:17,172 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0754) Prec@1 86.000 (87.353) Prec@5 100.000 (99.235) +2022-11-14 16:04:17,194 Test: [34/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0756) Prec@1 90.000 (87.429) Prec@5 98.000 (99.200) +2022-11-14 16:04:17,213 Test: [35/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0756) Prec@1 87.000 (87.417) Prec@5 98.000 (99.167) +2022-11-14 16:04:17,229 Test: [36/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0727 (0.0755) Prec@1 89.000 (87.459) Prec@5 98.000 (99.135) +2022-11-14 16:04:17,244 Test: [37/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0955 (0.0760) Prec@1 84.000 (87.368) Prec@5 98.000 (99.105) +2022-11-14 16:04:17,258 Test: [38/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0444 (0.0752) Prec@1 94.000 (87.538) Prec@5 99.000 (99.103) +2022-11-14 16:04:17,275 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0747) Prec@1 92.000 (87.650) Prec@5 99.000 (99.100) +2022-11-14 16:04:17,293 Test: [40/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0893 (0.0751) Prec@1 87.000 (87.634) Prec@5 98.000 (99.073) +2022-11-14 16:04:17,311 Test: [41/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0599 (0.0747) Prec@1 89.000 (87.667) Prec@5 100.000 (99.095) +2022-11-14 16:04:17,326 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0745) Prec@1 88.000 (87.674) Prec@5 99.000 (99.093) +2022-11-14 16:04:17,340 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0745) Prec@1 89.000 (87.705) Prec@5 99.000 (99.091) +2022-11-14 16:04:17,356 Test: [44/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0570 (0.0741) Prec@1 92.000 (87.800) Prec@5 98.000 (99.067) +2022-11-14 16:04:17,374 Test: [45/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0998 (0.0747) Prec@1 84.000 (87.717) Prec@5 99.000 (99.065) +2022-11-14 16:04:17,389 Test: [46/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0592 (0.0743) Prec@1 89.000 (87.745) Prec@5 100.000 (99.085) +2022-11-14 16:04:17,405 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1239 (0.0754) Prec@1 81.000 (87.604) Prec@5 98.000 (99.062) +2022-11-14 16:04:17,427 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0749) Prec@1 91.000 (87.673) Prec@5 99.000 (99.061) +2022-11-14 16:04:17,444 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.0755) Prec@1 87.000 (87.660) Prec@5 99.000 (99.060) +2022-11-14 16:04:17,459 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0754) Prec@1 86.000 (87.627) Prec@5 99.000 (99.059) +2022-11-14 16:04:17,475 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0758) Prec@1 82.000 (87.519) Prec@5 98.000 (99.038) +2022-11-14 16:04:17,495 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0759) Prec@1 86.000 (87.491) Prec@5 100.000 (99.057) +2022-11-14 16:04:17,517 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0757) Prec@1 89.000 (87.519) Prec@5 100.000 (99.074) +2022-11-14 16:04:17,533 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0758) Prec@1 88.000 (87.527) Prec@5 100.000 (99.091) +2022-11-14 16:04:17,553 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0839 (0.0760) Prec@1 87.000 (87.518) Prec@5 99.000 (99.089) +2022-11-14 16:04:17,573 Test: [56/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0759) Prec@1 87.000 (87.509) Prec@5 99.000 (99.088) +2022-11-14 16:04:17,590 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0759) Prec@1 88.000 (87.517) Prec@5 100.000 (99.103) +2022-11-14 16:04:17,606 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1036 (0.0764) Prec@1 84.000 (87.458) Prec@5 99.000 (99.102) +2022-11-14 16:04:17,628 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0766) Prec@1 83.000 (87.383) Prec@5 100.000 (99.117) +2022-11-14 16:04:17,649 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0764) Prec@1 89.000 (87.410) Prec@5 100.000 (99.131) +2022-11-14 16:04:17,666 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0762) Prec@1 89.000 (87.435) Prec@5 99.000 (99.129) +2022-11-14 16:04:17,682 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0761) Prec@1 88.000 (87.444) Prec@5 100.000 (99.143) +2022-11-14 16:04:17,696 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0419 (0.0756) Prec@1 94.000 (87.547) Prec@5 100.000 (99.156) +2022-11-14 16:04:17,711 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0999 (0.0760) Prec@1 82.000 (87.462) Prec@5 98.000 (99.138) +2022-11-14 16:04:17,732 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0759) Prec@1 89.000 (87.485) Prec@5 100.000 (99.152) +2022-11-14 16:04:17,751 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0358 (0.0753) Prec@1 94.000 (87.582) Prec@5 100.000 (99.164) +2022-11-14 16:04:17,771 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0752) Prec@1 88.000 (87.588) Prec@5 98.000 (99.147) +2022-11-14 16:04:17,786 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0600 (0.0750) Prec@1 92.000 (87.652) Prec@5 99.000 (99.145) +2022-11-14 16:04:17,804 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0538 (0.0747) Prec@1 93.000 (87.729) Prec@5 100.000 (99.157) +2022-11-14 16:04:17,822 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1063 (0.0751) Prec@1 84.000 (87.676) Prec@5 99.000 (99.155) +2022-11-14 16:04:17,839 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0533 (0.0748) Prec@1 92.000 (87.736) Prec@5 100.000 (99.167) +2022-11-14 16:04:17,855 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0462 (0.0744) Prec@1 94.000 (87.822) Prec@5 100.000 (99.178) +2022-11-14 16:04:17,874 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0557 (0.0742) Prec@1 92.000 (87.878) Prec@5 99.000 (99.176) +2022-11-14 16:04:17,893 Test: [74/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0742) Prec@1 88.000 (87.880) Prec@5 100.000 (99.187) +2022-11-14 16:04:17,911 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0740) Prec@1 91.000 (87.921) Prec@5 100.000 (99.197) +2022-11-14 16:04:17,926 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0923 (0.0743) Prec@1 85.000 (87.883) Prec@5 100.000 (99.208) +2022-11-14 16:04:17,943 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0955 (0.0746) Prec@1 85.000 (87.846) Prec@5 97.000 (99.179) +2022-11-14 16:04:17,961 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0745) Prec@1 88.000 (87.848) Prec@5 100.000 (99.190) +2022-11-14 16:04:17,978 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0746) Prec@1 83.000 (87.787) Prec@5 99.000 (99.188) +2022-11-14 16:04:17,992 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0747) Prec@1 89.000 (87.802) Prec@5 97.000 (99.160) +2022-11-14 16:04:18,012 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0748) Prec@1 88.000 (87.805) Prec@5 100.000 (99.171) +2022-11-14 16:04:18,031 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0749) Prec@1 88.000 (87.807) Prec@5 99.000 (99.169) +2022-11-14 16:04:18,048 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0748) Prec@1 90.000 (87.833) Prec@5 99.000 (99.167) +2022-11-14 16:04:18,065 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0749) Prec@1 86.000 (87.812) Prec@5 100.000 (99.176) +2022-11-14 16:04:18,083 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1031 (0.0753) Prec@1 83.000 (87.756) Prec@5 98.000 (99.163) +2022-11-14 16:04:18,101 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0753) Prec@1 89.000 (87.770) Prec@5 99.000 (99.161) +2022-11-14 16:04:18,122 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0754) Prec@1 88.000 (87.773) Prec@5 98.000 (99.148) +2022-11-14 16:04:18,138 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0752) Prec@1 91.000 (87.809) Prec@5 100.000 (99.157) +2022-11-14 16:04:18,154 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0751) Prec@1 90.000 (87.833) Prec@5 100.000 (99.167) +2022-11-14 16:04:18,173 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0749) Prec@1 91.000 (87.868) Prec@5 100.000 (99.176) +2022-11-14 16:04:18,192 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0747) Prec@1 90.000 (87.891) Prec@5 98.000 (99.163) +2022-11-14 16:04:18,211 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0955 (0.0749) Prec@1 85.000 (87.860) Prec@5 98.000 (99.151) +2022-11-14 16:04:18,230 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0749) Prec@1 89.000 (87.872) Prec@5 98.000 (99.138) +2022-11-14 16:04:18,248 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0941 (0.0751) Prec@1 85.000 (87.842) Prec@5 100.000 (99.147) +2022-11-14 16:04:18,266 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0750) Prec@1 89.000 (87.854) Prec@5 99.000 (99.146) +2022-11-14 16:04:18,286 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0749) Prec@1 92.000 (87.897) Prec@5 98.000 (99.134) +2022-11-14 16:04:18,301 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0750) Prec@1 87.000 (87.888) Prec@5 98.000 (99.122) +2022-11-14 16:04:18,317 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0998 (0.0752) Prec@1 84.000 (87.848) Prec@5 99.000 (99.121) +2022-11-14 16:04:18,333 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0752) Prec@1 87.000 (87.840) Prec@5 100.000 (99.130) +2022-11-14 16:04:18,422 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:04:18,789 Epoch: [299][0/500] Time 0.032 (0.032) Data 0.272 (0.272) Loss 0.0476 (0.0476) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:04:19,278 Epoch: [299][10/500] Time 0.050 (0.042) Data 0.002 (0.027) Loss 0.0389 (0.0432) Prec@1 94.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:04:19,807 Epoch: [299][20/500] Time 0.054 (0.045) Data 0.002 (0.015) Loss 0.0361 (0.0409) Prec@1 94.000 (92.667) Prec@5 100.000 (99.333) +2022-11-14 16:04:20,381 Epoch: [299][30/500] Time 0.044 (0.047) Data 0.002 (0.011) Loss 0.0615 (0.0460) Prec@1 89.000 (91.750) Prec@5 99.000 (99.250) +2022-11-14 16:04:20,887 Epoch: [299][40/500] Time 0.047 (0.047) Data 0.002 (0.009) Loss 0.0153 (0.0399) Prec@1 98.000 (93.000) Prec@5 100.000 (99.400) +2022-11-14 16:04:21,435 Epoch: [299][50/500] Time 0.049 (0.047) Data 0.002 (0.007) Loss 0.0262 (0.0376) Prec@1 96.000 (93.500) Prec@5 100.000 (99.500) +2022-11-14 16:04:21,964 Epoch: [299][60/500] Time 0.050 (0.047) Data 0.002 (0.006) Loss 0.0267 (0.0361) Prec@1 96.000 (93.857) Prec@5 100.000 (99.571) +2022-11-14 16:04:22,478 Epoch: [299][70/500] Time 0.047 (0.047) Data 0.002 (0.006) Loss 0.0286 (0.0351) Prec@1 96.000 (94.125) Prec@5 100.000 (99.625) +2022-11-14 16:04:23,043 Epoch: [299][80/500] Time 0.062 (0.048) Data 0.002 (0.005) Loss 0.0355 (0.0352) Prec@1 95.000 (94.222) Prec@5 100.000 (99.667) +2022-11-14 16:04:23,587 Epoch: [299][90/500] Time 0.041 (0.048) Data 0.002 (0.005) Loss 0.0281 (0.0345) Prec@1 94.000 (94.200) Prec@5 100.000 (99.700) +2022-11-14 16:04:24,101 Epoch: [299][100/500] Time 0.044 (0.048) Data 0.002 (0.005) Loss 0.0352 (0.0345) Prec@1 95.000 (94.273) Prec@5 99.000 (99.636) +2022-11-14 16:04:24,614 Epoch: [299][110/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0313 (0.0343) Prec@1 95.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:04:25,131 Epoch: [299][120/500] Time 0.055 (0.047) Data 0.002 (0.004) Loss 0.0196 (0.0331) Prec@1 96.000 (94.462) Prec@5 100.000 (99.692) +2022-11-14 16:04:25,666 Epoch: [299][130/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0421 (0.0338) Prec@1 94.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 16:04:26,260 Epoch: [299][140/500] Time 0.041 (0.048) Data 0.002 (0.004) Loss 0.0126 (0.0324) Prec@1 98.000 (94.667) Prec@5 100.000 (99.733) +2022-11-14 16:04:26,789 Epoch: [299][150/500] Time 0.042 (0.048) Data 0.002 (0.004) Loss 0.0289 (0.0321) Prec@1 96.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:04:27,297 Epoch: [299][160/500] Time 0.056 (0.048) Data 0.002 (0.004) Loss 0.0212 (0.0315) Prec@1 96.000 (94.824) Prec@5 100.000 (99.765) +2022-11-14 16:04:27,820 Epoch: [299][170/500] Time 0.049 (0.048) Data 0.002 (0.004) Loss 0.0286 (0.0313) Prec@1 93.000 (94.722) Prec@5 100.000 (99.778) +2022-11-14 16:04:28,311 Epoch: [299][180/500] Time 0.046 (0.047) Data 0.002 (0.004) Loss 0.0219 (0.0309) Prec@1 96.000 (94.789) Prec@5 100.000 (99.789) +2022-11-14 16:04:28,833 Epoch: [299][190/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0456 (0.0316) Prec@1 92.000 (94.650) Prec@5 100.000 (99.800) +2022-11-14 16:04:29,387 Epoch: [299][200/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0239 (0.0312) Prec@1 96.000 (94.714) Prec@5 100.000 (99.810) +2022-11-14 16:04:29,887 Epoch: [299][210/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0321 (0.0313) Prec@1 95.000 (94.727) Prec@5 100.000 (99.818) +2022-11-14 16:04:30,406 Epoch: [299][220/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0343 (0.0314) Prec@1 95.000 (94.739) Prec@5 99.000 (99.783) +2022-11-14 16:04:31,016 Epoch: [299][230/500] Time 0.064 (0.048) Data 0.002 (0.003) Loss 0.0159 (0.0307) Prec@1 98.000 (94.875) Prec@5 99.000 (99.750) +2022-11-14 16:04:31,504 Epoch: [299][240/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0293 (0.0307) Prec@1 95.000 (94.880) Prec@5 100.000 (99.760) +2022-11-14 16:04:32,021 Epoch: [299][250/500] Time 0.036 (0.047) Data 0.002 (0.003) Loss 0.0138 (0.0300) Prec@1 98.000 (95.000) Prec@5 100.000 (99.769) +2022-11-14 16:04:32,541 Epoch: [299][260/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0185 (0.0296) Prec@1 96.000 (95.037) Prec@5 99.000 (99.741) +2022-11-14 16:04:33,059 Epoch: [299][270/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0281 (0.0296) Prec@1 97.000 (95.107) Prec@5 100.000 (99.750) +2022-11-14 16:04:33,567 Epoch: [299][280/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0227 (0.0293) Prec@1 97.000 (95.172) Prec@5 100.000 (99.759) +2022-11-14 16:04:34,078 Epoch: [299][290/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0263 (0.0292) Prec@1 96.000 (95.200) Prec@5 100.000 (99.767) +2022-11-14 16:04:34,599 Epoch: [299][300/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0495 (0.0299) Prec@1 92.000 (95.097) Prec@5 100.000 (99.774) +2022-11-14 16:04:35,131 Epoch: [299][310/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0358 (0.0301) Prec@1 96.000 (95.125) Prec@5 100.000 (99.781) +2022-11-14 16:04:35,636 Epoch: [299][320/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0255 (0.0299) Prec@1 97.000 (95.182) Prec@5 100.000 (99.788) +2022-11-14 16:04:36,159 Epoch: [299][330/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0269 (0.0298) Prec@1 95.000 (95.176) Prec@5 100.000 (99.794) +2022-11-14 16:04:36,692 Epoch: [299][340/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0327 (0.0299) Prec@1 94.000 (95.143) Prec@5 100.000 (99.800) +2022-11-14 16:04:37,209 Epoch: [299][350/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0181 (0.0296) Prec@1 97.000 (95.194) Prec@5 100.000 (99.806) +2022-11-14 16:04:37,736 Epoch: [299][360/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0397 (0.0299) Prec@1 92.000 (95.108) Prec@5 100.000 (99.811) +2022-11-14 16:04:38,260 Epoch: [299][370/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0188 (0.0296) Prec@1 98.000 (95.184) Prec@5 99.000 (99.789) +2022-11-14 16:04:38,752 Epoch: [299][380/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0447 (0.0300) Prec@1 92.000 (95.103) Prec@5 99.000 (99.769) +2022-11-14 16:04:39,304 Epoch: [299][390/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0446 (0.0303) Prec@1 93.000 (95.050) Prec@5 99.000 (99.750) +2022-11-14 16:04:39,882 Epoch: [299][400/500] Time 0.069 (0.047) Data 0.002 (0.003) Loss 0.0245 (0.0302) Prec@1 95.000 (95.049) Prec@5 100.000 (99.756) +2022-11-14 16:04:40,394 Epoch: [299][410/500] Time 0.047 (0.047) Data 0.003 (0.003) Loss 0.0368 (0.0303) Prec@1 94.000 (95.024) Prec@5 100.000 (99.762) +2022-11-14 16:04:40,925 Epoch: [299][420/500] Time 0.042 (0.047) Data 0.003 (0.003) Loss 0.0277 (0.0303) Prec@1 95.000 (95.023) Prec@5 100.000 (99.767) +2022-11-14 16:04:41,495 Epoch: [299][430/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0068 (0.0297) Prec@1 100.000 (95.136) Prec@5 100.000 (99.773) +2022-11-14 16:04:42,035 Epoch: [299][440/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0375 (0.0299) Prec@1 93.000 (95.089) Prec@5 100.000 (99.778) +2022-11-14 16:04:42,626 Epoch: [299][450/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0127 (0.0295) Prec@1 98.000 (95.152) Prec@5 100.000 (99.783) +2022-11-14 16:04:43,165 Epoch: [299][460/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0218 (0.0294) Prec@1 97.000 (95.191) Prec@5 100.000 (99.787) +2022-11-14 16:04:43,706 Epoch: [299][470/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0263 (0.0293) Prec@1 97.000 (95.229) Prec@5 100.000 (99.792) +2022-11-14 16:04:44,265 Epoch: [299][480/500] Time 0.052 (0.047) Data 0.003 (0.003) Loss 0.0246 (0.0292) Prec@1 96.000 (95.245) Prec@5 99.000 (99.776) +2022-11-14 16:04:44,792 Epoch: [299][490/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0409 (0.0294) Prec@1 91.000 (95.160) Prec@5 100.000 (99.780) +2022-11-14 16:04:45,276 Epoch: [299][499/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0275 (0.0294) Prec@1 94.000 (95.137) Prec@5 100.000 (99.784) +2022-11-14 16:04:45,628 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0865 (0.0865) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 16:04:45,638 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0733 (0.0799) Prec@1 88.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 16:04:45,651 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0764) Prec@1 90.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:04:45,663 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0758) Prec@1 88.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 16:04:45,672 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0778) Prec@1 85.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 16:04:45,680 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0354 (0.0708) Prec@1 94.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:04:45,693 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0697) Prec@1 90.000 (88.571) Prec@5 98.000 (99.429) +2022-11-14 16:04:45,714 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0721) Prec@1 88.000 (88.500) Prec@5 99.000 (99.375) +2022-11-14 16:04:45,737 Test: [8/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0748) Prec@1 86.000 (88.222) Prec@5 98.000 (99.222) +2022-11-14 16:04:45,763 Test: [9/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0737) Prec@1 89.000 (88.300) Prec@5 99.000 (99.200) +2022-11-14 16:04:45,782 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0732) Prec@1 90.000 (88.455) Prec@5 99.000 (99.182) +2022-11-14 16:04:45,800 Test: [11/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0962 (0.0751) Prec@1 83.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 16:04:45,817 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0746) Prec@1 88.000 (88.000) Prec@5 100.000 (99.308) +2022-11-14 16:04:45,841 Test: [13/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0743) Prec@1 91.000 (88.214) Prec@5 99.000 (99.286) +2022-11-14 16:04:45,858 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0746) Prec@1 88.000 (88.200) Prec@5 100.000 (99.333) +2022-11-14 16:04:45,879 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0610 (0.0737) Prec@1 90.000 (88.312) Prec@5 99.000 (99.312) +2022-11-14 16:04:45,898 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0595 (0.0729) Prec@1 92.000 (88.529) Prec@5 99.000 (99.294) +2022-11-14 16:04:45,915 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1126 (0.0751) Prec@1 84.000 (88.278) Prec@5 100.000 (99.333) +2022-11-14 16:04:45,932 Test: [18/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0751) Prec@1 87.000 (88.211) Prec@5 99.000 (99.316) +2022-11-14 16:04:45,948 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1097 (0.0769) Prec@1 82.000 (87.900) Prec@5 96.000 (99.150) +2022-11-14 16:04:45,964 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0795 (0.0770) Prec@1 86.000 (87.810) Prec@5 98.000 (99.095) +2022-11-14 16:04:45,978 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0779) Prec@1 84.000 (87.636) Prec@5 99.000 (99.091) +2022-11-14 16:04:45,994 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0984 (0.0788) Prec@1 87.000 (87.609) Prec@5 97.000 (99.000) +2022-11-14 16:04:46,017 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0783) Prec@1 91.000 (87.750) Prec@5 100.000 (99.042) +2022-11-14 16:04:46,034 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0913 (0.0788) Prec@1 87.000 (87.720) Prec@5 99.000 (99.040) +2022-11-14 16:04:46,052 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0794) Prec@1 84.000 (87.577) Prec@5 99.000 (99.038) +2022-11-14 16:04:46,070 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0553 (0.0785) Prec@1 93.000 (87.778) Prec@5 100.000 (99.074) +2022-11-14 16:04:46,084 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0789) Prec@1 84.000 (87.643) Prec@5 100.000 (99.107) +2022-11-14 16:04:46,103 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0789) Prec@1 87.000 (87.621) Prec@5 98.000 (99.069) +2022-11-14 16:04:46,121 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0795 (0.0789) Prec@1 89.000 (87.667) Prec@5 99.000 (99.067) +2022-11-14 16:04:46,138 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0783) Prec@1 89.000 (87.710) Prec@5 100.000 (99.097) +2022-11-14 16:04:46,156 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0900 (0.0787) Prec@1 85.000 (87.625) Prec@5 99.000 (99.094) +2022-11-14 16:04:46,173 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0786) Prec@1 84.000 (87.515) Prec@5 100.000 (99.121) +2022-11-14 16:04:46,189 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0786) Prec@1 86.000 (87.471) Prec@5 100.000 (99.147) +2022-11-14 16:04:46,207 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0788) Prec@1 85.000 (87.400) Prec@5 98.000 (99.114) +2022-11-14 16:04:46,225 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0788) Prec@1 89.000 (87.444) Prec@5 100.000 (99.139) +2022-11-14 16:04:46,243 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0786) Prec@1 87.000 (87.432) Prec@5 99.000 (99.135) +2022-11-14 16:04:46,261 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1053 (0.0793) Prec@1 83.000 (87.316) Prec@5 100.000 (99.158) +2022-11-14 16:04:46,281 Test: [38/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0454 (0.0784) Prec@1 93.000 (87.462) Prec@5 100.000 (99.179) +2022-11-14 16:04:46,302 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0782) Prec@1 89.000 (87.500) Prec@5 97.000 (99.125) +2022-11-14 16:04:46,318 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0788) Prec@1 84.000 (87.415) Prec@5 98.000 (99.098) +2022-11-14 16:04:46,333 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0605 (0.0783) Prec@1 91.000 (87.500) Prec@5 100.000 (99.119) +2022-11-14 16:04:46,347 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0780) Prec@1 90.000 (87.558) Prec@5 100.000 (99.140) +2022-11-14 16:04:46,366 Test: [43/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0778) Prec@1 88.000 (87.568) Prec@5 99.000 (99.136) +2022-11-14 16:04:46,385 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0779) Prec@1 86.000 (87.533) Prec@5 99.000 (99.133) +2022-11-14 16:04:46,407 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1155 (0.0788) Prec@1 81.000 (87.391) Prec@5 100.000 (99.152) +2022-11-14 16:04:46,425 Test: [46/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0784) Prec@1 89.000 (87.426) Prec@5 100.000 (99.170) +2022-11-14 16:04:46,441 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0786) Prec@1 86.000 (87.396) Prec@5 99.000 (99.167) +2022-11-14 16:04:46,460 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0782) Prec@1 91.000 (87.469) Prec@5 99.000 (99.163) +2022-11-14 16:04:46,479 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0938 (0.0786) Prec@1 88.000 (87.480) Prec@5 100.000 (99.180) +2022-11-14 16:04:46,498 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0538 (0.0781) Prec@1 91.000 (87.549) Prec@5 100.000 (99.196) +2022-11-14 16:04:46,518 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1095 (0.0787) Prec@1 82.000 (87.442) Prec@5 99.000 (99.192) +2022-11-14 16:04:46,536 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0784) Prec@1 90.000 (87.491) Prec@5 99.000 (99.189) +2022-11-14 16:04:46,555 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0780) Prec@1 90.000 (87.537) Prec@5 100.000 (99.204) +2022-11-14 16:04:46,574 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1101 (0.0786) Prec@1 81.000 (87.418) Prec@5 100.000 (99.218) +2022-11-14 16:04:46,594 Test: [55/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0785) Prec@1 88.000 (87.429) Prec@5 99.000 (99.214) +2022-11-14 16:04:46,613 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0783) Prec@1 87.000 (87.421) Prec@5 100.000 (99.228) +2022-11-14 16:04:46,632 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0733 (0.0782) Prec@1 91.000 (87.483) Prec@5 99.000 (99.224) +2022-11-14 16:04:46,647 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0786) Prec@1 84.000 (87.424) Prec@5 100.000 (99.237) +2022-11-14 16:04:46,665 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0785) Prec@1 87.000 (87.417) Prec@5 99.000 (99.233) +2022-11-14 16:04:46,684 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1031 (0.0789) Prec@1 83.000 (87.344) Prec@5 100.000 (99.246) +2022-11-14 16:04:46,704 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0787) Prec@1 91.000 (87.403) Prec@5 99.000 (99.242) +2022-11-14 16:04:46,724 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0787) Prec@1 84.000 (87.349) Prec@5 100.000 (99.254) +2022-11-14 16:04:46,741 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0782) Prec@1 92.000 (87.422) Prec@5 100.000 (99.266) +2022-11-14 16:04:46,758 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0782) Prec@1 89.000 (87.446) Prec@5 99.000 (99.262) +2022-11-14 16:04:46,776 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0782) Prec@1 87.000 (87.439) Prec@5 100.000 (99.273) +2022-11-14 16:04:46,791 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0373 (0.0776) Prec@1 93.000 (87.522) Prec@5 100.000 (99.284) +2022-11-14 16:04:46,808 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0775) Prec@1 88.000 (87.529) Prec@5 99.000 (99.279) +2022-11-14 16:04:46,833 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0772) Prec@1 91.000 (87.580) Prec@5 99.000 (99.275) +2022-11-14 16:04:46,856 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0771) Prec@1 87.000 (87.571) Prec@5 100.000 (99.286) +2022-11-14 16:04:46,877 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0773) Prec@1 88.000 (87.577) Prec@5 100.000 (99.296) +2022-11-14 16:04:46,900 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0771) Prec@1 91.000 (87.625) Prec@5 99.000 (99.292) +2022-11-14 16:04:46,923 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0768) Prec@1 93.000 (87.699) Prec@5 100.000 (99.301) +2022-11-14 16:04:46,942 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0224 (0.0760) Prec@1 98.000 (87.838) Prec@5 100.000 (99.311) +2022-11-14 16:04:46,965 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0762) Prec@1 84.000 (87.787) Prec@5 99.000 (99.307) +2022-11-14 16:04:46,987 Test: [75/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0479 (0.0758) Prec@1 95.000 (87.882) Prec@5 100.000 (99.316) +2022-11-14 16:04:47,007 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0759) Prec@1 86.000 (87.857) Prec@5 99.000 (99.312) +2022-11-14 16:04:47,030 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0848 (0.0760) Prec@1 87.000 (87.846) Prec@5 97.000 (99.282) +2022-11-14 16:04:47,050 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0759) Prec@1 88.000 (87.848) Prec@5 100.000 (99.291) +2022-11-14 16:04:47,074 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0760) Prec@1 86.000 (87.825) Prec@5 99.000 (99.287) +2022-11-14 16:04:47,094 Test: [80/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0906 (0.0762) Prec@1 84.000 (87.778) Prec@5 99.000 (99.284) +2022-11-14 16:04:47,114 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0925 (0.0764) Prec@1 85.000 (87.744) Prec@5 99.000 (99.280) +2022-11-14 16:04:47,132 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0788 (0.0764) Prec@1 86.000 (87.723) Prec@5 100.000 (99.289) +2022-11-14 16:04:47,152 Test: [83/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0595 (0.0762) Prec@1 90.000 (87.750) Prec@5 98.000 (99.274) +2022-11-14 16:04:47,174 Test: [84/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0764) Prec@1 84.000 (87.706) Prec@5 99.000 (99.271) +2022-11-14 16:04:47,193 Test: [85/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0995 (0.0767) Prec@1 85.000 (87.674) Prec@5 99.000 (99.267) +2022-11-14 16:04:47,215 Test: [86/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0769) Prec@1 83.000 (87.621) Prec@5 99.000 (99.264) +2022-11-14 16:04:47,233 Test: [87/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0769) Prec@1 87.000 (87.614) Prec@5 99.000 (99.261) +2022-11-14 16:04:47,247 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0768) Prec@1 88.000 (87.618) Prec@5 99.000 (99.258) +2022-11-14 16:04:47,265 Test: [89/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0767) Prec@1 89.000 (87.633) Prec@5 100.000 (99.267) +2022-11-14 16:04:47,284 Test: [90/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0599 (0.0765) Prec@1 88.000 (87.637) Prec@5 100.000 (99.275) +2022-11-14 16:04:47,302 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0763) Prec@1 92.000 (87.685) Prec@5 99.000 (99.272) +2022-11-14 16:04:47,319 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0834 (0.0763) Prec@1 87.000 (87.677) Prec@5 100.000 (99.280) +2022-11-14 16:04:47,335 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0764) Prec@1 84.000 (87.638) Prec@5 99.000 (99.277) +2022-11-14 16:04:47,352 Test: [94/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0765) Prec@1 85.000 (87.611) Prec@5 98.000 (99.263) +2022-11-14 16:04:47,369 Test: [95/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0764) Prec@1 89.000 (87.625) Prec@5 98.000 (99.250) +2022-11-14 16:04:47,387 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0433 (0.0760) Prec@1 92.000 (87.670) Prec@5 99.000 (99.247) +2022-11-14 16:04:47,408 Test: [97/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0762) Prec@1 88.000 (87.673) Prec@5 98.000 (99.235) +2022-11-14 16:04:47,424 Test: [98/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0763) Prec@1 87.000 (87.667) Prec@5 100.000 (99.242) +2022-11-14 16:04:47,438 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0761) Prec@1 91.000 (87.700) Prec@5 100.000 (99.250) +2022-11-14 16:04:47,515 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:04:47,910 Epoch: [300][0/500] Time 0.026 (0.026) Data 0.291 (0.291) Loss 0.0315 (0.0315) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:04:48,411 Epoch: [300][10/500] Time 0.046 (0.043) Data 0.002 (0.028) Loss 0.0448 (0.0381) Prec@1 91.000 (92.500) Prec@5 99.000 (99.500) +2022-11-14 16:04:48,970 Epoch: [300][20/500] Time 0.050 (0.046) Data 0.002 (0.016) Loss 0.0244 (0.0336) Prec@1 97.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:04:49,547 Epoch: [300][30/500] Time 0.046 (0.047) Data 0.002 (0.012) Loss 0.0443 (0.0362) Prec@1 91.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 16:04:50,064 Epoch: [300][40/500] Time 0.046 (0.047) Data 0.002 (0.009) Loss 0.0305 (0.0351) Prec@1 94.000 (93.400) Prec@5 100.000 (99.800) +2022-11-14 16:04:50,610 Epoch: [300][50/500] Time 0.048 (0.048) Data 0.002 (0.008) Loss 0.0203 (0.0326) Prec@1 98.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 16:04:51,212 Epoch: [300][60/500] Time 0.060 (0.048) Data 0.002 (0.007) Loss 0.0098 (0.0294) Prec@1 100.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 16:04:51,738 Epoch: [300][70/500] Time 0.054 (0.048) Data 0.002 (0.006) Loss 0.0289 (0.0293) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:04:52,252 Epoch: [300][80/500] Time 0.049 (0.048) Data 0.003 (0.006) Loss 0.0277 (0.0291) Prec@1 96.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 16:04:52,781 Epoch: [300][90/500] Time 0.055 (0.048) Data 0.002 (0.005) Loss 0.0194 (0.0282) Prec@1 98.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 16:04:53,293 Epoch: [300][100/500] Time 0.048 (0.048) Data 0.002 (0.005) Loss 0.0433 (0.0295) Prec@1 93.000 (95.273) Prec@5 100.000 (99.909) +2022-11-14 16:04:53,887 Epoch: [300][110/500] Time 0.041 (0.048) Data 0.002 (0.005) Loss 0.0515 (0.0314) Prec@1 93.000 (95.083) Prec@5 99.000 (99.833) +2022-11-14 16:04:54,437 Epoch: [300][120/500] Time 0.052 (0.048) Data 0.002 (0.005) Loss 0.0558 (0.0332) Prec@1 91.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 16:04:54,937 Epoch: [300][130/500] Time 0.047 (0.048) Data 0.002 (0.004) Loss 0.0411 (0.0338) Prec@1 94.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:04:55,550 Epoch: [300][140/500] Time 0.066 (0.048) Data 0.003 (0.004) Loss 0.0295 (0.0335) Prec@1 96.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 16:04:56,061 Epoch: [300][150/500] Time 0.043 (0.048) Data 0.002 (0.004) Loss 0.0314 (0.0334) Prec@1 96.000 (94.875) Prec@5 100.000 (99.812) +2022-11-14 16:04:56,667 Epoch: [300][160/500] Time 0.061 (0.049) Data 0.002 (0.004) Loss 0.0200 (0.0326) Prec@1 97.000 (95.000) Prec@5 100.000 (99.824) +2022-11-14 16:04:57,173 Epoch: [300][170/500] Time 0.043 (0.048) Data 0.002 (0.004) Loss 0.0465 (0.0334) Prec@1 92.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:04:57,689 Epoch: [300][180/500] Time 0.049 (0.048) Data 0.002 (0.004) Loss 0.0240 (0.0329) Prec@1 96.000 (94.895) Prec@5 100.000 (99.842) +2022-11-14 16:04:58,207 Epoch: [300][190/500] Time 0.055 (0.048) Data 0.002 (0.004) Loss 0.0226 (0.0324) Prec@1 97.000 (95.000) Prec@5 100.000 (99.850) +2022-11-14 16:04:58,751 Epoch: [300][200/500] Time 0.054 (0.048) Data 0.003 (0.004) Loss 0.0188 (0.0317) Prec@1 97.000 (95.095) Prec@5 100.000 (99.857) +2022-11-14 16:04:59,362 Epoch: [300][210/500] Time 0.049 (0.049) Data 0.003 (0.004) Loss 0.0416 (0.0322) Prec@1 93.000 (95.000) Prec@5 100.000 (99.864) +2022-11-14 16:04:59,876 Epoch: [300][220/500] Time 0.049 (0.048) Data 0.004 (0.004) Loss 0.0235 (0.0318) Prec@1 96.000 (95.043) Prec@5 100.000 (99.870) +2022-11-14 16:05:00,379 Epoch: [300][230/500] Time 0.046 (0.048) Data 0.003 (0.004) Loss 0.0454 (0.0324) Prec@1 92.000 (94.917) Prec@5 100.000 (99.875) +2022-11-14 16:05:00,911 Epoch: [300][240/500] Time 0.057 (0.048) Data 0.003 (0.003) Loss 0.0260 (0.0321) Prec@1 96.000 (94.960) Prec@5 100.000 (99.880) +2022-11-14 16:05:01,443 Epoch: [300][250/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0321 (0.0321) Prec@1 95.000 (94.962) Prec@5 100.000 (99.885) +2022-11-14 16:05:01,970 Epoch: [300][260/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0502 (0.0328) Prec@1 91.000 (94.815) Prec@5 99.000 (99.852) +2022-11-14 16:05:02,490 Epoch: [300][270/500] Time 0.043 (0.048) Data 0.003 (0.003) Loss 0.0153 (0.0321) Prec@1 98.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 16:05:03,054 Epoch: [300][280/500] Time 0.077 (0.048) Data 0.002 (0.003) Loss 0.0373 (0.0323) Prec@1 95.000 (94.931) Prec@5 100.000 (99.862) +2022-11-14 16:05:03,586 Epoch: [300][290/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0314 (0.0323) Prec@1 96.000 (94.967) Prec@5 100.000 (99.867) +2022-11-14 16:05:04,098 Epoch: [300][300/500] Time 0.038 (0.048) Data 0.002 (0.003) Loss 0.0450 (0.0327) Prec@1 92.000 (94.871) Prec@5 100.000 (99.871) +2022-11-14 16:05:04,657 Epoch: [300][310/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0580 (0.0335) Prec@1 88.000 (94.656) Prec@5 100.000 (99.875) +2022-11-14 16:05:05,263 Epoch: [300][320/500] Time 0.036 (0.048) Data 0.002 (0.003) Loss 0.0440 (0.0338) Prec@1 92.000 (94.576) Prec@5 100.000 (99.879) +2022-11-14 16:05:05,777 Epoch: [300][330/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0257 (0.0336) Prec@1 96.000 (94.618) Prec@5 100.000 (99.882) +2022-11-14 16:05:06,372 Epoch: [300][340/500] Time 0.070 (0.048) Data 0.002 (0.003) Loss 0.0250 (0.0333) Prec@1 96.000 (94.657) Prec@5 100.000 (99.886) +2022-11-14 16:05:06,900 Epoch: [300][350/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0525 (0.0339) Prec@1 92.000 (94.583) Prec@5 100.000 (99.889) +2022-11-14 16:05:07,431 Epoch: [300][360/500] Time 0.052 (0.048) Data 0.003 (0.003) Loss 0.0275 (0.0337) Prec@1 94.000 (94.568) Prec@5 100.000 (99.892) +2022-11-14 16:05:07,971 Epoch: [300][370/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0176 (0.0333) Prec@1 97.000 (94.632) Prec@5 100.000 (99.895) +2022-11-14 16:05:08,500 Epoch: [300][380/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0236 (0.0330) Prec@1 96.000 (94.667) Prec@5 100.000 (99.897) +2022-11-14 16:05:09,014 Epoch: [300][390/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0212 (0.0327) Prec@1 97.000 (94.725) Prec@5 100.000 (99.900) +2022-11-14 16:05:09,693 Epoch: [300][400/500] Time 0.065 (0.048) Data 0.003 (0.003) Loss 0.0299 (0.0327) Prec@1 96.000 (94.756) Prec@5 100.000 (99.902) +2022-11-14 16:05:10,212 Epoch: [300][410/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0301 (0.0326) Prec@1 94.000 (94.738) Prec@5 100.000 (99.905) +2022-11-14 16:05:10,740 Epoch: [300][420/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0340 (0.0326) Prec@1 95.000 (94.744) Prec@5 100.000 (99.907) +2022-11-14 16:05:11,239 Epoch: [300][430/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0539 (0.0331) Prec@1 91.000 (94.659) Prec@5 99.000 (99.886) +2022-11-14 16:05:11,764 Epoch: [300][440/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0406 (0.0333) Prec@1 93.000 (94.622) Prec@5 100.000 (99.889) +2022-11-14 16:05:12,303 Epoch: [300][450/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0480 (0.0336) Prec@1 91.000 (94.543) Prec@5 100.000 (99.891) +2022-11-14 16:05:12,941 Epoch: [300][460/500] Time 0.066 (0.048) Data 0.002 (0.003) Loss 0.0455 (0.0338) Prec@1 91.000 (94.468) Prec@5 99.000 (99.872) +2022-11-14 16:05:13,436 Epoch: [300][470/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0323 (0.0338) Prec@1 94.000 (94.458) Prec@5 100.000 (99.875) +2022-11-14 16:05:13,980 Epoch: [300][480/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0316 (0.0338) Prec@1 93.000 (94.429) Prec@5 99.000 (99.857) +2022-11-14 16:05:14,495 Epoch: [300][490/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0504 (0.0341) Prec@1 91.000 (94.360) Prec@5 100.000 (99.860) +2022-11-14 16:05:14,967 Epoch: [300][499/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0190 (0.0338) Prec@1 98.000 (94.431) Prec@5 100.000 (99.863) +2022-11-14 16:05:15,310 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0663 (0.0663) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:15,321 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0618 (0.0641) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:15,333 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0695 (0.0659) Prec@1 89.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 16:05:15,350 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0810 (0.0696) Prec@1 88.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 16:05:15,364 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.0750) Prec@1 85.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 16:05:15,375 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0493 (0.0707) Prec@1 92.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:05:15,386 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0704) Prec@1 90.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:05:15,400 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0712) Prec@1 85.000 (88.625) Prec@5 99.000 (99.625) +2022-11-14 16:05:15,415 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0701) Prec@1 92.000 (89.000) Prec@5 99.000 (99.556) +2022-11-14 16:05:15,429 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0706) Prec@1 89.000 (89.000) Prec@5 97.000 (99.300) +2022-11-14 16:05:15,446 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0709) Prec@1 89.000 (89.000) Prec@5 100.000 (99.364) +2022-11-14 16:05:15,463 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0704) Prec@1 87.000 (88.833) Prec@5 100.000 (99.417) +2022-11-14 16:05:15,478 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0701) Prec@1 88.000 (88.769) Prec@5 100.000 (99.462) +2022-11-14 16:05:15,495 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0709) Prec@1 87.000 (88.643) Prec@5 99.000 (99.429) +2022-11-14 16:05:15,512 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0710) Prec@1 90.000 (88.733) Prec@5 98.000 (99.333) +2022-11-14 16:05:15,531 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0471 (0.0695) Prec@1 92.000 (88.938) Prec@5 100.000 (99.375) +2022-11-14 16:05:15,548 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0421 (0.0679) Prec@1 95.000 (89.294) Prec@5 99.000 (99.353) +2022-11-14 16:05:15,563 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1089 (0.0701) Prec@1 83.000 (88.944) Prec@5 100.000 (99.389) +2022-11-14 16:05:15,577 Test: [18/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0906 (0.0712) Prec@1 82.000 (88.579) Prec@5 98.000 (99.316) +2022-11-14 16:05:15,592 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0972 (0.0725) Prec@1 84.000 (88.350) Prec@5 99.000 (99.300) +2022-11-14 16:05:15,610 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0992 (0.0738) Prec@1 83.000 (88.095) Prec@5 100.000 (99.333) +2022-11-14 16:05:15,629 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0974 (0.0749) Prec@1 83.000 (87.864) Prec@5 99.000 (99.318) +2022-11-14 16:05:15,646 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1085 (0.0763) Prec@1 82.000 (87.609) Prec@5 96.000 (99.174) +2022-11-14 16:05:15,666 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0760) Prec@1 88.000 (87.625) Prec@5 99.000 (99.167) +2022-11-14 16:05:15,685 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.0770) Prec@1 86.000 (87.560) Prec@5 99.000 (99.160) +2022-11-14 16:05:15,702 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0775) Prec@1 85.000 (87.462) Prec@5 99.000 (99.154) +2022-11-14 16:05:15,720 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0569 (0.0767) Prec@1 92.000 (87.630) Prec@5 100.000 (99.185) +2022-11-14 16:05:15,739 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0531 (0.0759) Prec@1 93.000 (87.821) Prec@5 100.000 (99.214) +2022-11-14 16:05:15,757 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0760) Prec@1 87.000 (87.793) Prec@5 97.000 (99.138) +2022-11-14 16:05:15,777 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0760) Prec@1 88.000 (87.800) Prec@5 100.000 (99.167) +2022-11-14 16:05:15,797 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0758) Prec@1 89.000 (87.839) Prec@5 100.000 (99.194) +2022-11-14 16:05:15,816 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0762) Prec@1 85.000 (87.750) Prec@5 99.000 (99.188) +2022-11-14 16:05:15,832 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0764) Prec@1 85.000 (87.667) Prec@5 100.000 (99.212) +2022-11-14 16:05:15,849 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0762) Prec@1 91.000 (87.765) Prec@5 100.000 (99.235) +2022-11-14 16:05:15,867 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0761) Prec@1 89.000 (87.800) Prec@5 99.000 (99.229) +2022-11-14 16:05:15,885 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0827 (0.0763) Prec@1 85.000 (87.722) Prec@5 100.000 (99.250) +2022-11-14 16:05:15,906 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0760 (0.0763) Prec@1 88.000 (87.730) Prec@5 98.000 (99.216) +2022-11-14 16:05:15,928 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0956 (0.0768) Prec@1 83.000 (87.605) Prec@5 98.000 (99.184) +2022-11-14 16:05:15,948 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0572 (0.0763) Prec@1 91.000 (87.692) Prec@5 99.000 (99.179) +2022-11-14 16:05:15,969 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0733 (0.0762) Prec@1 90.000 (87.750) Prec@5 99.000 (99.175) +2022-11-14 16:05:15,994 Test: [40/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0767) Prec@1 85.000 (87.683) Prec@5 98.000 (99.146) +2022-11-14 16:05:16,015 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0765) Prec@1 91.000 (87.762) Prec@5 100.000 (99.167) +2022-11-14 16:05:16,033 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0319 (0.0754) Prec@1 94.000 (87.907) Prec@5 100.000 (99.186) +2022-11-14 16:05:16,054 Test: [43/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0755) Prec@1 88.000 (87.909) Prec@5 98.000 (99.159) +2022-11-14 16:05:16,074 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0754) Prec@1 88.000 (87.911) Prec@5 100.000 (99.178) +2022-11-14 16:05:16,094 Test: [45/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.0761) Prec@1 85.000 (87.848) Prec@5 100.000 (99.196) +2022-11-14 16:05:16,115 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0757) Prec@1 90.000 (87.894) Prec@5 100.000 (99.213) +2022-11-14 16:05:16,133 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1178 (0.0766) Prec@1 82.000 (87.771) Prec@5 99.000 (99.208) +2022-11-14 16:05:16,151 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0764) Prec@1 88.000 (87.776) Prec@5 99.000 (99.204) +2022-11-14 16:05:16,166 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0986 (0.0769) Prec@1 84.000 (87.700) Prec@5 98.000 (99.180) +2022-11-14 16:05:16,181 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0769) Prec@1 87.000 (87.686) Prec@5 100.000 (99.196) +2022-11-14 16:05:16,195 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0771) Prec@1 88.000 (87.692) Prec@5 100.000 (99.212) +2022-11-14 16:05:16,212 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0770) Prec@1 89.000 (87.717) Prec@5 99.000 (99.208) +2022-11-14 16:05:16,233 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0769) Prec@1 88.000 (87.722) Prec@5 99.000 (99.204) +2022-11-14 16:05:16,249 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0770) Prec@1 88.000 (87.727) Prec@5 100.000 (99.218) +2022-11-14 16:05:16,269 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0769) Prec@1 89.000 (87.750) Prec@5 98.000 (99.196) +2022-11-14 16:05:16,285 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0766) Prec@1 88.000 (87.754) Prec@5 100.000 (99.211) +2022-11-14 16:05:16,305 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0549 (0.0763) Prec@1 90.000 (87.793) Prec@5 100.000 (99.224) +2022-11-14 16:05:16,327 Test: [58/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1110 (0.0768) Prec@1 85.000 (87.746) Prec@5 98.000 (99.203) +2022-11-14 16:05:16,345 Test: [59/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0770) Prec@1 87.000 (87.733) Prec@5 99.000 (99.200) +2022-11-14 16:05:16,362 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0770) Prec@1 88.000 (87.738) Prec@5 98.000 (99.180) +2022-11-14 16:05:16,379 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0769) Prec@1 88.000 (87.742) Prec@5 100.000 (99.194) +2022-11-14 16:05:16,399 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0769) Prec@1 89.000 (87.762) Prec@5 100.000 (99.206) +2022-11-14 16:05:16,417 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0407 (0.0763) Prec@1 93.000 (87.844) Prec@5 99.000 (99.203) +2022-11-14 16:05:16,436 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0925 (0.0765) Prec@1 85.000 (87.800) Prec@5 100.000 (99.215) +2022-11-14 16:05:16,453 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0766) Prec@1 86.000 (87.773) Prec@5 100.000 (99.227) +2022-11-14 16:05:16,474 Test: [66/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0760) Prec@1 94.000 (87.866) Prec@5 100.000 (99.239) +2022-11-14 16:05:16,495 Test: [67/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0762) Prec@1 87.000 (87.853) Prec@5 99.000 (99.235) +2022-11-14 16:05:16,513 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0760) Prec@1 89.000 (87.870) Prec@5 99.000 (99.232) +2022-11-14 16:05:16,528 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0760) Prec@1 87.000 (87.857) Prec@5 100.000 (99.243) +2022-11-14 16:05:16,546 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0760) Prec@1 90.000 (87.887) Prec@5 99.000 (99.239) +2022-11-14 16:05:16,567 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0443 (0.0756) Prec@1 92.000 (87.944) Prec@5 99.000 (99.236) +2022-11-14 16:05:16,586 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0609 (0.0754) Prec@1 91.000 (87.986) Prec@5 100.000 (99.247) +2022-11-14 16:05:16,607 Test: [73/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0398 (0.0749) Prec@1 94.000 (88.068) Prec@5 100.000 (99.257) +2022-11-14 16:05:16,626 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1087 (0.0754) Prec@1 84.000 (88.013) Prec@5 100.000 (99.267) +2022-11-14 16:05:16,645 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0457 (0.0750) Prec@1 93.000 (88.079) Prec@5 100.000 (99.276) +2022-11-14 16:05:16,663 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0750) Prec@1 87.000 (88.065) Prec@5 99.000 (99.273) +2022-11-14 16:05:16,682 Test: [77/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.0754) Prec@1 85.000 (88.026) Prec@5 98.000 (99.256) +2022-11-14 16:05:16,698 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0753) Prec@1 88.000 (88.025) Prec@5 100.000 (99.266) +2022-11-14 16:05:16,716 Test: [79/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0753) Prec@1 88.000 (88.025) Prec@5 100.000 (99.275) +2022-11-14 16:05:16,734 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0753) Prec@1 89.000 (88.037) Prec@5 99.000 (99.272) +2022-11-14 16:05:16,752 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0539 (0.0751) Prec@1 90.000 (88.061) Prec@5 100.000 (99.280) +2022-11-14 16:05:16,772 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0896 (0.0752) Prec@1 85.000 (88.024) Prec@5 99.000 (99.277) +2022-11-14 16:05:16,790 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0752) Prec@1 89.000 (88.036) Prec@5 99.000 (99.274) +2022-11-14 16:05:16,810 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0754) Prec@1 82.000 (87.965) Prec@5 99.000 (99.271) +2022-11-14 16:05:16,830 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0755) Prec@1 85.000 (87.930) Prec@5 100.000 (99.279) +2022-11-14 16:05:16,849 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0754) Prec@1 88.000 (87.931) Prec@5 99.000 (99.276) +2022-11-14 16:05:16,866 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0753) Prec@1 89.000 (87.943) Prec@5 98.000 (99.261) +2022-11-14 16:05:16,883 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0752) Prec@1 90.000 (87.966) Prec@5 99.000 (99.258) +2022-11-14 16:05:16,900 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0751) Prec@1 90.000 (87.989) Prec@5 98.000 (99.244) +2022-11-14 16:05:16,917 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0425 (0.0747) Prec@1 93.000 (88.044) Prec@5 100.000 (99.253) +2022-11-14 16:05:16,932 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0658 (0.0746) Prec@1 89.000 (88.054) Prec@5 99.000 (99.250) +2022-11-14 16:05:16,953 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0880 (0.0748) Prec@1 87.000 (88.043) Prec@5 100.000 (99.258) +2022-11-14 16:05:16,973 Test: [93/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0750) Prec@1 87.000 (88.032) Prec@5 99.000 (99.255) +2022-11-14 16:05:16,992 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0627 (0.0748) Prec@1 91.000 (88.063) Prec@5 100.000 (99.263) +2022-11-14 16:05:17,009 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0567 (0.0746) Prec@1 90.000 (88.083) Prec@5 100.000 (99.271) +2022-11-14 16:05:17,030 Test: [96/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0743) Prec@1 94.000 (88.144) Prec@5 99.000 (99.268) +2022-11-14 16:05:17,045 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0744) Prec@1 89.000 (88.153) Prec@5 98.000 (99.255) +2022-11-14 16:05:17,065 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0746) Prec@1 87.000 (88.141) Prec@5 98.000 (99.242) +2022-11-14 16:05:17,085 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0745) Prec@1 89.000 (88.150) Prec@5 99.000 (99.240) +2022-11-14 16:05:17,170 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:05:17,539 Epoch: [301][0/500] Time 0.025 (0.025) Data 0.275 (0.275) Loss 0.0456 (0.0456) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:18,019 Epoch: [301][10/500] Time 0.046 (0.041) Data 0.002 (0.027) Loss 0.0262 (0.0359) Prec@1 96.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:18,631 Epoch: [301][20/500] Time 0.075 (0.048) Data 0.002 (0.015) Loss 0.0160 (0.0293) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:19,195 Epoch: [301][30/500] Time 0.068 (0.049) Data 0.002 (0.011) Loss 0.0332 (0.0302) Prec@1 95.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 16:05:19,781 Epoch: [301][40/500] Time 0.055 (0.050) Data 0.002 (0.009) Loss 0.0122 (0.0266) Prec@1 98.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:05:20,347 Epoch: [301][50/500] Time 0.073 (0.050) Data 0.002 (0.008) Loss 0.0241 (0.0262) Prec@1 96.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:05:20,887 Epoch: [301][60/500] Time 0.050 (0.049) Data 0.003 (0.007) Loss 0.0445 (0.0288) Prec@1 92.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:05:21,419 Epoch: [301][70/500] Time 0.052 (0.049) Data 0.002 (0.006) Loss 0.0317 (0.0292) Prec@1 94.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 16:05:22,017 Epoch: [301][80/500] Time 0.069 (0.050) Data 0.002 (0.006) Loss 0.0069 (0.0267) Prec@1 100.000 (95.556) Prec@5 100.000 (99.889) +2022-11-14 16:05:22,551 Epoch: [301][90/500] Time 0.053 (0.049) Data 0.002 (0.005) Loss 0.0362 (0.0277) Prec@1 95.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 16:05:23,129 Epoch: [301][100/500] Time 0.052 (0.050) Data 0.002 (0.005) Loss 0.0654 (0.0311) Prec@1 88.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:05:23,662 Epoch: [301][110/500] Time 0.059 (0.049) Data 0.002 (0.005) Loss 0.0295 (0.0310) Prec@1 94.000 (94.750) Prec@5 100.000 (99.917) +2022-11-14 16:05:24,204 Epoch: [301][120/500] Time 0.055 (0.049) Data 0.002 (0.004) Loss 0.0286 (0.0308) Prec@1 96.000 (94.846) Prec@5 99.000 (99.846) +2022-11-14 16:05:24,810 Epoch: [301][130/500] Time 0.063 (0.050) Data 0.002 (0.004) Loss 0.0273 (0.0305) Prec@1 97.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 16:05:25,329 Epoch: [301][140/500] Time 0.051 (0.049) Data 0.002 (0.004) Loss 0.0372 (0.0310) Prec@1 93.000 (94.867) Prec@5 100.000 (99.867) +2022-11-14 16:05:25,881 Epoch: [301][150/500] Time 0.060 (0.049) Data 0.002 (0.004) Loss 0.0345 (0.0312) Prec@1 93.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 16:05:26,408 Epoch: [301][160/500] Time 0.054 (0.049) Data 0.002 (0.004) Loss 0.0321 (0.0312) Prec@1 95.000 (94.765) Prec@5 100.000 (99.882) +2022-11-14 16:05:26,976 Epoch: [301][170/500] Time 0.045 (0.049) Data 0.002 (0.004) Loss 0.0304 (0.0312) Prec@1 95.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 16:05:27,543 Epoch: [301][180/500] Time 0.047 (0.050) Data 0.002 (0.004) Loss 0.0430 (0.0318) Prec@1 93.000 (94.684) Prec@5 100.000 (99.895) +2022-11-14 16:05:28,103 Epoch: [301][190/500] Time 0.048 (0.050) Data 0.002 (0.004) Loss 0.0366 (0.0321) Prec@1 94.000 (94.650) Prec@5 99.000 (99.850) +2022-11-14 16:05:28,613 Epoch: [301][200/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0517 (0.0330) Prec@1 93.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:05:29,140 Epoch: [301][210/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0398 (0.0333) Prec@1 95.000 (94.591) Prec@5 100.000 (99.864) +2022-11-14 16:05:29,656 Epoch: [301][220/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0352 (0.0334) Prec@1 95.000 (94.609) Prec@5 100.000 (99.870) +2022-11-14 16:05:30,186 Epoch: [301][230/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0166 (0.0327) Prec@1 99.000 (94.792) Prec@5 100.000 (99.875) +2022-11-14 16:05:30,731 Epoch: [301][240/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0188 (0.0321) Prec@1 97.000 (94.880) Prec@5 100.000 (99.880) +2022-11-14 16:05:31,242 Epoch: [301][250/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0393 (0.0324) Prec@1 93.000 (94.808) Prec@5 99.000 (99.846) +2022-11-14 16:05:31,781 Epoch: [301][260/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0239 (0.0321) Prec@1 97.000 (94.889) Prec@5 100.000 (99.852) +2022-11-14 16:05:32,325 Epoch: [301][270/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0325 (0.0321) Prec@1 95.000 (94.893) Prec@5 99.000 (99.821) +2022-11-14 16:05:32,875 Epoch: [301][280/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0369 (0.0323) Prec@1 93.000 (94.828) Prec@5 100.000 (99.828) +2022-11-14 16:05:33,416 Epoch: [301][290/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0343 (0.0323) Prec@1 96.000 (94.867) Prec@5 100.000 (99.833) +2022-11-14 16:05:33,953 Epoch: [301][300/500] Time 0.064 (0.049) Data 0.002 (0.003) Loss 0.0189 (0.0319) Prec@1 96.000 (94.903) Prec@5 100.000 (99.839) +2022-11-14 16:05:34,495 Epoch: [301][310/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0437 (0.0323) Prec@1 92.000 (94.812) Prec@5 99.000 (99.812) +2022-11-14 16:05:35,028 Epoch: [301][320/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.0272 (0.0321) Prec@1 96.000 (94.848) Prec@5 100.000 (99.818) +2022-11-14 16:05:35,561 Epoch: [301][330/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0489 (0.0326) Prec@1 94.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:05:36,078 Epoch: [301][340/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0350 (0.0327) Prec@1 95.000 (94.829) Prec@5 100.000 (99.829) +2022-11-14 16:05:36,611 Epoch: [301][350/500] Time 0.066 (0.049) Data 0.002 (0.003) Loss 0.0385 (0.0328) Prec@1 94.000 (94.806) Prec@5 99.000 (99.806) +2022-11-14 16:05:37,145 Epoch: [301][360/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0209 (0.0325) Prec@1 98.000 (94.892) Prec@5 100.000 (99.811) +2022-11-14 16:05:37,663 Epoch: [301][370/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0245 (0.0323) Prec@1 95.000 (94.895) Prec@5 100.000 (99.816) +2022-11-14 16:05:38,191 Epoch: [301][380/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0353 (0.0324) Prec@1 94.000 (94.872) Prec@5 100.000 (99.821) +2022-11-14 16:05:38,698 Epoch: [301][390/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0448 (0.0327) Prec@1 91.000 (94.775) Prec@5 99.000 (99.800) +2022-11-14 16:05:39,235 Epoch: [301][400/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0282 (0.0326) Prec@1 95.000 (94.780) Prec@5 100.000 (99.805) +2022-11-14 16:05:39,783 Epoch: [301][410/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0558 (0.0331) Prec@1 90.000 (94.667) Prec@5 99.000 (99.786) +2022-11-14 16:05:40,295 Epoch: [301][420/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0228 (0.0329) Prec@1 96.000 (94.698) Prec@5 100.000 (99.791) +2022-11-14 16:05:40,810 Epoch: [301][430/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0273 (0.0328) Prec@1 96.000 (94.727) Prec@5 100.000 (99.795) +2022-11-14 16:05:41,344 Epoch: [301][440/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0285 (0.0327) Prec@1 96.000 (94.756) Prec@5 100.000 (99.800) +2022-11-14 16:05:41,931 Epoch: [301][450/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0283 (0.0326) Prec@1 95.000 (94.761) Prec@5 100.000 (99.804) +2022-11-14 16:05:42,461 Epoch: [301][460/500] Time 0.046 (0.048) Data 0.003 (0.003) Loss 0.0285 (0.0325) Prec@1 95.000 (94.766) Prec@5 100.000 (99.809) +2022-11-14 16:05:42,992 Epoch: [301][470/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0199 (0.0322) Prec@1 96.000 (94.792) Prec@5 100.000 (99.812) +2022-11-14 16:05:43,523 Epoch: [301][480/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0428 (0.0324) Prec@1 94.000 (94.776) Prec@5 99.000 (99.796) +2022-11-14 16:05:44,027 Epoch: [301][490/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0229 (0.0323) Prec@1 97.000 (94.820) Prec@5 100.000 (99.800) +2022-11-14 16:05:44,571 Epoch: [301][499/500] Time 0.063 (0.048) Data 0.002 (0.003) Loss 0.0308 (0.0322) Prec@1 95.000 (94.824) Prec@5 100.000 (99.804) +2022-11-14 16:05:44,923 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0733 (0.0733) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:05:44,934 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0682) Prec@1 90.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:05:44,945 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0695) Prec@1 86.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 16:05:44,959 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0686) Prec@1 89.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 16:05:44,969 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0686) Prec@1 88.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 16:05:44,980 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0643) Prec@1 90.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 16:05:44,991 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0648) Prec@1 88.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 16:05:45,007 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0669) Prec@1 87.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 16:05:45,021 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0700) Prec@1 85.000 (87.889) Prec@5 99.000 (99.444) +2022-11-14 16:05:45,035 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0701) Prec@1 88.000 (87.900) Prec@5 99.000 (99.400) +2022-11-14 16:05:45,053 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0692) Prec@1 91.000 (88.182) Prec@5 99.000 (99.364) +2022-11-14 16:05:45,068 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0701) Prec@1 85.000 (87.917) Prec@5 99.000 (99.333) +2022-11-14 16:05:45,085 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0695) Prec@1 90.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 16:05:45,105 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0698) Prec@1 89.000 (88.143) Prec@5 99.000 (99.357) +2022-11-14 16:05:45,122 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0707) Prec@1 86.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 16:05:45,142 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0712) Prec@1 86.000 (87.875) Prec@5 100.000 (99.375) +2022-11-14 16:05:45,159 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0704) Prec@1 91.000 (88.059) Prec@5 99.000 (99.353) +2022-11-14 16:05:45,173 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0715) Prec@1 85.000 (87.889) Prec@5 100.000 (99.389) +2022-11-14 16:05:45,188 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0726) Prec@1 85.000 (87.737) Prec@5 98.000 (99.316) +2022-11-14 16:05:45,206 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0725) Prec@1 88.000 (87.750) Prec@5 100.000 (99.350) +2022-11-14 16:05:45,225 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0724) Prec@1 88.000 (87.762) Prec@5 100.000 (99.381) +2022-11-14 16:05:45,246 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0722) Prec@1 89.000 (87.818) Prec@5 99.000 (99.364) +2022-11-14 16:05:45,265 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0734) Prec@1 85.000 (87.696) Prec@5 99.000 (99.348) +2022-11-14 16:05:45,281 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0726) Prec@1 91.000 (87.833) Prec@5 100.000 (99.375) +2022-11-14 16:05:45,297 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0726) Prec@1 87.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 16:05:45,316 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0731) Prec@1 88.000 (87.808) Prec@5 97.000 (99.308) +2022-11-14 16:05:45,335 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0730) Prec@1 88.000 (87.815) Prec@5 100.000 (99.333) +2022-11-14 16:05:45,356 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0726) Prec@1 91.000 (87.929) Prec@5 99.000 (99.321) +2022-11-14 16:05:45,372 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0723) Prec@1 89.000 (87.966) Prec@5 99.000 (99.310) +2022-11-14 16:05:45,388 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0718) Prec@1 89.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 16:05:45,403 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0723) Prec@1 85.000 (87.903) Prec@5 100.000 (99.355) +2022-11-14 16:05:45,422 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0724) Prec@1 87.000 (87.875) Prec@5 100.000 (99.375) +2022-11-14 16:05:45,441 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0730) Prec@1 84.000 (87.758) Prec@5 99.000 (99.364) +2022-11-14 16:05:45,460 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0734) Prec@1 85.000 (87.676) Prec@5 99.000 (99.353) +2022-11-14 16:05:45,477 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0733) Prec@1 89.000 (87.714) Prec@5 98.000 (99.314) +2022-11-14 16:05:45,491 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0729) Prec@1 90.000 (87.778) Prec@5 100.000 (99.333) +2022-11-14 16:05:45,507 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0726) Prec@1 91.000 (87.865) Prec@5 98.000 (99.297) +2022-11-14 16:05:45,525 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1169 (0.0738) Prec@1 81.000 (87.684) Prec@5 100.000 (99.316) +2022-11-14 16:05:45,542 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0731) Prec@1 91.000 (87.769) Prec@5 99.000 (99.308) +2022-11-14 16:05:45,558 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0383 (0.0723) Prec@1 94.000 (87.925) Prec@5 100.000 (99.325) +2022-11-14 16:05:45,579 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0729) Prec@1 82.000 (87.780) Prec@5 97.000 (99.268) +2022-11-14 16:05:45,599 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0729) Prec@1 89.000 (87.810) Prec@5 100.000 (99.286) +2022-11-14 16:05:45,615 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0408 (0.0722) Prec@1 91.000 (87.884) Prec@5 100.000 (99.302) +2022-11-14 16:05:45,631 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0722) Prec@1 89.000 (87.909) Prec@5 100.000 (99.318) +2022-11-14 16:05:45,649 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0720) Prec@1 93.000 (88.022) Prec@5 100.000 (99.333) +2022-11-14 16:05:45,667 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0727) Prec@1 82.000 (87.891) Prec@5 99.000 (99.326) +2022-11-14 16:05:45,684 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0727) Prec@1 89.000 (87.915) Prec@5 100.000 (99.340) +2022-11-14 16:05:45,704 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0730) Prec@1 85.000 (87.854) Prec@5 99.000 (99.333) +2022-11-14 16:05:45,722 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0726) Prec@1 91.000 (87.918) Prec@5 100.000 (99.347) +2022-11-14 16:05:45,736 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0732) Prec@1 84.000 (87.840) Prec@5 99.000 (99.340) +2022-11-14 16:05:45,756 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0728) Prec@1 90.000 (87.882) Prec@5 100.000 (99.353) +2022-11-14 16:05:45,772 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0731) Prec@1 86.000 (87.846) Prec@5 99.000 (99.346) +2022-11-14 16:05:45,789 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0730) Prec@1 90.000 (87.887) Prec@5 99.000 (99.340) +2022-11-14 16:05:45,809 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0731) Prec@1 85.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 16:05:45,828 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0732) Prec@1 86.000 (87.800) Prec@5 100.000 (99.345) +2022-11-14 16:05:45,846 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0734) Prec@1 86.000 (87.768) Prec@5 99.000 (99.339) +2022-11-14 16:05:45,862 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0733) Prec@1 89.000 (87.789) Prec@5 100.000 (99.351) +2022-11-14 16:05:45,880 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0733) Prec@1 90.000 (87.828) Prec@5 99.000 (99.345) +2022-11-14 16:05:45,898 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0738) Prec@1 83.000 (87.746) Prec@5 100.000 (99.356) +2022-11-14 16:05:45,918 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0740) Prec@1 86.000 (87.717) Prec@5 99.000 (99.350) +2022-11-14 16:05:45,935 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0739) Prec@1 90.000 (87.754) Prec@5 100.000 (99.361) +2022-11-14 16:05:45,954 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0737) Prec@1 87.000 (87.742) Prec@5 100.000 (99.371) +2022-11-14 16:05:45,971 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0736) Prec@1 90.000 (87.778) Prec@5 100.000 (99.381) +2022-11-14 16:05:45,987 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0732) Prec@1 92.000 (87.844) Prec@5 100.000 (99.391) +2022-11-14 16:05:46,006 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0736) Prec@1 85.000 (87.800) Prec@5 99.000 (99.385) +2022-11-14 16:05:46,024 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0737) Prec@1 86.000 (87.773) Prec@5 99.000 (99.379) +2022-11-14 16:05:46,040 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0734) Prec@1 90.000 (87.806) Prec@5 100.000 (99.388) +2022-11-14 16:05:46,061 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0735) Prec@1 87.000 (87.794) Prec@5 99.000 (99.382) +2022-11-14 16:05:46,079 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0735) Prec@1 86.000 (87.768) Prec@5 100.000 (99.391) +2022-11-14 16:05:46,100 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0737) Prec@1 86.000 (87.743) Prec@5 98.000 (99.371) +2022-11-14 16:05:46,120 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0740) Prec@1 86.000 (87.718) Prec@5 99.000 (99.366) +2022-11-14 16:05:46,142 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0740) Prec@1 87.000 (87.708) Prec@5 100.000 (99.375) +2022-11-14 16:05:46,162 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0737) Prec@1 91.000 (87.753) Prec@5 99.000 (99.370) +2022-11-14 16:05:46,177 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0734) Prec@1 93.000 (87.824) Prec@5 100.000 (99.378) +2022-11-14 16:05:46,193 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0735) Prec@1 88.000 (87.827) Prec@5 99.000 (99.373) +2022-11-14 16:05:46,212 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0733) Prec@1 91.000 (87.868) Prec@5 100.000 (99.382) +2022-11-14 16:05:46,227 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0734) Prec@1 87.000 (87.857) Prec@5 99.000 (99.377) +2022-11-14 16:05:46,246 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0735) Prec@1 87.000 (87.846) Prec@5 98.000 (99.359) +2022-11-14 16:05:46,265 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0736) Prec@1 86.000 (87.823) Prec@5 99.000 (99.354) +2022-11-14 16:05:46,281 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0735) Prec@1 89.000 (87.838) Prec@5 100.000 (99.362) +2022-11-14 16:05:46,301 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0736) Prec@1 87.000 (87.827) Prec@5 100.000 (99.370) +2022-11-14 16:05:46,321 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0735) Prec@1 89.000 (87.841) Prec@5 100.000 (99.378) +2022-11-14 16:05:46,338 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0977 (0.0738) Prec@1 84.000 (87.795) Prec@5 100.000 (99.386) +2022-11-14 16:05:46,356 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0738) Prec@1 89.000 (87.810) Prec@5 98.000 (99.369) +2022-11-14 16:05:46,375 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0741) Prec@1 83.000 (87.753) Prec@5 99.000 (99.365) +2022-11-14 16:05:46,392 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0741) Prec@1 89.000 (87.767) Prec@5 100.000 (99.372) +2022-11-14 16:05:46,408 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0740) Prec@1 90.000 (87.793) Prec@5 98.000 (99.356) +2022-11-14 16:05:46,424 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0741) Prec@1 86.000 (87.773) Prec@5 98.000 (99.341) +2022-11-14 16:05:46,442 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0741) Prec@1 88.000 (87.775) Prec@5 99.000 (99.337) +2022-11-14 16:05:46,460 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0739) Prec@1 90.000 (87.800) Prec@5 100.000 (99.344) +2022-11-14 16:05:46,478 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0737) Prec@1 91.000 (87.835) Prec@5 100.000 (99.352) +2022-11-14 16:05:46,495 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0438 (0.0734) Prec@1 94.000 (87.902) Prec@5 99.000 (99.348) +2022-11-14 16:05:46,512 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0737) Prec@1 86.000 (87.882) Prec@5 99.000 (99.344) +2022-11-14 16:05:46,531 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0736) Prec@1 87.000 (87.872) Prec@5 99.000 (99.340) +2022-11-14 16:05:46,550 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0737) Prec@1 85.000 (87.842) Prec@5 99.000 (99.337) +2022-11-14 16:05:46,569 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0738) Prec@1 87.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 16:05:46,588 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0736) Prec@1 92.000 (87.876) Prec@5 98.000 (99.320) +2022-11-14 16:05:46,605 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1008 (0.0739) Prec@1 85.000 (87.847) Prec@5 100.000 (99.327) +2022-11-14 16:05:46,623 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.0743) Prec@1 81.000 (87.778) Prec@5 98.000 (99.313) +2022-11-14 16:05:46,639 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0742) Prec@1 88.000 (87.780) Prec@5 99.000 (99.310) +2022-11-14 16:05:46,701 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:05:47,061 Epoch: [302][0/500] Time 0.026 (0.026) Data 0.264 (0.264) Loss 0.0469 (0.0469) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:47,533 Epoch: [302][10/500] Time 0.042 (0.040) Data 0.002 (0.026) Loss 0.0435 (0.0452) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 16:05:48,038 Epoch: [302][20/500] Time 0.051 (0.043) Data 0.002 (0.015) Loss 0.0379 (0.0428) Prec@1 92.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 16:05:48,561 Epoch: [302][30/500] Time 0.051 (0.044) Data 0.002 (0.011) Loss 0.0207 (0.0373) Prec@1 97.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:05:49,108 Epoch: [302][40/500] Time 0.048 (0.045) Data 0.002 (0.008) Loss 0.0413 (0.0381) Prec@1 93.000 (93.400) Prec@5 100.000 (100.000) +2022-11-14 16:05:49,622 Epoch: [302][50/500] Time 0.051 (0.045) Data 0.002 (0.007) Loss 0.0213 (0.0353) Prec@1 97.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:05:50,222 Epoch: [302][60/500] Time 0.048 (0.047) Data 0.002 (0.006) Loss 0.0269 (0.0341) Prec@1 96.000 (94.286) Prec@5 100.000 (100.000) +2022-11-14 16:05:50,756 Epoch: [302][70/500] Time 0.041 (0.047) Data 0.002 (0.006) Loss 0.0446 (0.0354) Prec@1 92.000 (94.000) Prec@5 99.000 (99.875) +2022-11-14 16:05:51,309 Epoch: [302][80/500] Time 0.049 (0.047) Data 0.003 (0.005) Loss 0.0195 (0.0336) Prec@1 94.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 16:05:51,818 Epoch: [302][90/500] Time 0.053 (0.047) Data 0.003 (0.005) Loss 0.0163 (0.0319) Prec@1 98.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:05:52,336 Epoch: [302][100/500] Time 0.050 (0.047) Data 0.002 (0.005) Loss 0.0215 (0.0310) Prec@1 98.000 (94.727) Prec@5 100.000 (99.909) +2022-11-14 16:05:52,856 Epoch: [302][110/500] Time 0.043 (0.047) Data 0.002 (0.005) Loss 0.0383 (0.0316) Prec@1 93.000 (94.583) Prec@5 100.000 (99.917) +2022-11-14 16:05:53,396 Epoch: [302][120/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0454 (0.0326) Prec@1 92.000 (94.385) Prec@5 99.000 (99.846) +2022-11-14 16:05:53,920 Epoch: [302][130/500] Time 0.048 (0.047) Data 0.002 (0.004) Loss 0.0403 (0.0332) Prec@1 93.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 16:05:54,459 Epoch: [302][140/500] Time 0.050 (0.047) Data 0.002 (0.004) Loss 0.0431 (0.0338) Prec@1 92.000 (94.133) Prec@5 100.000 (99.867) +2022-11-14 16:05:54,991 Epoch: [302][150/500] Time 0.044 (0.047) Data 0.002 (0.004) Loss 0.0250 (0.0333) Prec@1 96.000 (94.250) Prec@5 100.000 (99.875) +2022-11-14 16:05:55,525 Epoch: [302][160/500] Time 0.053 (0.047) Data 0.002 (0.004) Loss 0.0193 (0.0325) Prec@1 97.000 (94.412) Prec@5 100.000 (99.882) +2022-11-14 16:05:56,103 Epoch: [302][170/500] Time 0.063 (0.047) Data 0.002 (0.004) Loss 0.0270 (0.0322) Prec@1 97.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 16:05:56,655 Epoch: [302][180/500] Time 0.049 (0.048) Data 0.002 (0.004) Loss 0.0347 (0.0323) Prec@1 95.000 (94.579) Prec@5 100.000 (99.895) +2022-11-14 16:05:57,195 Epoch: [302][190/500] Time 0.051 (0.048) Data 0.002 (0.004) Loss 0.0461 (0.0330) Prec@1 94.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 16:05:57,714 Epoch: [302][200/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0206 (0.0324) Prec@1 96.000 (94.619) Prec@5 100.000 (99.905) +2022-11-14 16:05:58,252 Epoch: [302][210/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0539 (0.0334) Prec@1 90.000 (94.409) Prec@5 100.000 (99.909) +2022-11-14 16:05:58,766 Epoch: [302][220/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0358 (0.0335) Prec@1 96.000 (94.478) Prec@5 100.000 (99.913) +2022-11-14 16:05:59,272 Epoch: [302][230/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0486 (0.0341) Prec@1 93.000 (94.417) Prec@5 100.000 (99.917) +2022-11-14 16:05:59,777 Epoch: [302][240/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0261 (0.0338) Prec@1 94.000 (94.400) Prec@5 100.000 (99.920) +2022-11-14 16:06:00,280 Epoch: [302][250/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.0216 (0.0333) Prec@1 97.000 (94.500) Prec@5 100.000 (99.923) +2022-11-14 16:06:00,801 Epoch: [302][260/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0417 (0.0336) Prec@1 93.000 (94.444) Prec@5 100.000 (99.926) +2022-11-14 16:06:01,320 Epoch: [302][270/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0296 (0.0335) Prec@1 95.000 (94.464) Prec@5 100.000 (99.929) +2022-11-14 16:06:01,851 Epoch: [302][280/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0402 (0.0337) Prec@1 94.000 (94.448) Prec@5 100.000 (99.931) +2022-11-14 16:06:02,449 Epoch: [302][290/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0464 (0.0341) Prec@1 91.000 (94.333) Prec@5 100.000 (99.933) +2022-11-14 16:06:02,992 Epoch: [302][300/500] Time 0.057 (0.047) Data 0.002 (0.003) Loss 0.0251 (0.0339) Prec@1 97.000 (94.419) Prec@5 99.000 (99.903) +2022-11-14 16:06:03,529 Epoch: [302][310/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0266 (0.0336) Prec@1 96.000 (94.469) Prec@5 100.000 (99.906) +2022-11-14 16:06:04,025 Epoch: [302][320/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0686 (0.0347) Prec@1 90.000 (94.333) Prec@5 99.000 (99.879) +2022-11-14 16:06:04,558 Epoch: [302][330/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0171 (0.0342) Prec@1 99.000 (94.471) Prec@5 100.000 (99.882) +2022-11-14 16:06:05,101 Epoch: [302][340/500] Time 0.058 (0.047) Data 0.003 (0.003) Loss 0.0304 (0.0341) Prec@1 96.000 (94.514) Prec@5 100.000 (99.886) +2022-11-14 16:06:05,680 Epoch: [302][350/500] Time 0.068 (0.048) Data 0.002 (0.003) Loss 0.0332 (0.0340) Prec@1 94.000 (94.500) Prec@5 100.000 (99.889) +2022-11-14 16:06:06,192 Epoch: [302][360/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0172 (0.0336) Prec@1 98.000 (94.595) Prec@5 100.000 (99.892) +2022-11-14 16:06:06,737 Epoch: [302][370/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0381 (0.0337) Prec@1 92.000 (94.526) Prec@5 99.000 (99.868) +2022-11-14 16:06:07,259 Epoch: [302][380/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0471 (0.0340) Prec@1 91.000 (94.436) Prec@5 100.000 (99.872) +2022-11-14 16:06:07,794 Epoch: [302][390/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0373 (0.0341) Prec@1 96.000 (94.475) Prec@5 100.000 (99.875) +2022-11-14 16:06:08,366 Epoch: [302][400/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0142 (0.0336) Prec@1 99.000 (94.585) Prec@5 100.000 (99.878) +2022-11-14 16:06:08,912 Epoch: [302][410/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0538 (0.0341) Prec@1 92.000 (94.524) Prec@5 100.000 (99.881) +2022-11-14 16:06:09,445 Epoch: [302][420/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0453 (0.0344) Prec@1 92.000 (94.465) Prec@5 100.000 (99.884) +2022-11-14 16:06:10,031 Epoch: [302][430/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0306 (0.0343) Prec@1 94.000 (94.455) Prec@5 99.000 (99.864) +2022-11-14 16:06:10,568 Epoch: [302][440/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0276 (0.0341) Prec@1 95.000 (94.467) Prec@5 100.000 (99.867) +2022-11-14 16:06:11,082 Epoch: [302][450/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0430 (0.0343) Prec@1 93.000 (94.435) Prec@5 99.000 (99.848) +2022-11-14 16:06:11,602 Epoch: [302][460/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0321 (0.0343) Prec@1 96.000 (94.468) Prec@5 100.000 (99.851) +2022-11-14 16:06:12,129 Epoch: [302][470/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0431 (0.0345) Prec@1 93.000 (94.438) Prec@5 100.000 (99.854) +2022-11-14 16:06:12,652 Epoch: [302][480/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0431 (0.0346) Prec@1 93.000 (94.408) Prec@5 100.000 (99.857) +2022-11-14 16:06:13,177 Epoch: [302][490/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0240 (0.0344) Prec@1 96.000 (94.440) Prec@5 100.000 (99.860) +2022-11-14 16:06:13,650 Epoch: [302][499/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0237 (0.0342) Prec@1 95.000 (94.451) Prec@5 100.000 (99.863) +2022-11-14 16:06:13,962 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0744 (0.0744) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:06:13,971 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0817) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:06:13,981 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0778) Prec@1 87.000 (86.333) Prec@5 98.000 (99.333) +2022-11-14 16:06:13,993 Test: [3/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0768) Prec@1 90.000 (87.250) Prec@5 99.000 (99.250) +2022-11-14 16:06:14,003 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0775) Prec@1 88.000 (87.400) Prec@5 99.000 (99.200) +2022-11-14 16:06:14,014 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0721) Prec@1 92.000 (88.167) Prec@5 99.000 (99.167) +2022-11-14 16:06:14,025 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0707) Prec@1 90.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 16:06:14,041 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0732) Prec@1 82.000 (87.625) Prec@5 99.000 (99.250) +2022-11-14 16:06:14,056 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0739) Prec@1 89.000 (87.778) Prec@5 100.000 (99.333) +2022-11-14 16:06:14,069 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0733) Prec@1 87.000 (87.700) Prec@5 98.000 (99.200) +2022-11-14 16:06:14,091 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0721) Prec@1 87.000 (87.636) Prec@5 100.000 (99.273) +2022-11-14 16:06:14,110 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0737) Prec@1 85.000 (87.417) Prec@5 100.000 (99.333) +2022-11-14 16:06:14,129 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0726) Prec@1 89.000 (87.538) Prec@5 100.000 (99.385) +2022-11-14 16:06:14,148 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0731) Prec@1 88.000 (87.571) Prec@5 98.000 (99.286) +2022-11-14 16:06:14,167 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0733) Prec@1 87.000 (87.533) Prec@5 100.000 (99.333) +2022-11-14 16:06:14,186 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0741) Prec@1 87.000 (87.500) Prec@5 100.000 (99.375) +2022-11-14 16:06:14,204 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0730) Prec@1 91.000 (87.706) Prec@5 98.000 (99.294) +2022-11-14 16:06:14,223 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1002 (0.0745) Prec@1 87.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 16:06:14,240 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0752) Prec@1 86.000 (87.579) Prec@5 100.000 (99.368) +2022-11-14 16:06:14,257 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0760) Prec@1 87.000 (87.550) Prec@5 99.000 (99.350) +2022-11-14 16:06:14,270 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0765) Prec@1 88.000 (87.571) Prec@5 100.000 (99.381) +2022-11-14 16:06:14,286 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0769) Prec@1 86.000 (87.500) Prec@5 98.000 (99.318) +2022-11-14 16:06:14,304 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0781) Prec@1 87.000 (87.478) Prec@5 98.000 (99.261) +2022-11-14 16:06:14,321 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0781) Prec@1 86.000 (87.417) Prec@5 99.000 (99.250) +2022-11-14 16:06:14,342 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0784) Prec@1 87.000 (87.400) Prec@5 99.000 (99.240) +2022-11-14 16:06:14,358 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0786) Prec@1 88.000 (87.423) Prec@5 99.000 (99.231) +2022-11-14 16:06:14,373 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0780) Prec@1 91.000 (87.556) Prec@5 100.000 (99.259) +2022-11-14 16:06:14,391 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0772) Prec@1 92.000 (87.714) Prec@5 99.000 (99.250) +2022-11-14 16:06:14,410 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0767) Prec@1 90.000 (87.793) Prec@5 100.000 (99.276) +2022-11-14 16:06:14,431 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0771) Prec@1 85.000 (87.700) Prec@5 98.000 (99.233) +2022-11-14 16:06:14,449 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0767) Prec@1 89.000 (87.742) Prec@5 98.000 (99.194) +2022-11-14 16:06:14,467 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0762) Prec@1 92.000 (87.875) Prec@5 100.000 (99.219) +2022-11-14 16:06:14,483 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0764) Prec@1 88.000 (87.879) Prec@5 98.000 (99.182) +2022-11-14 16:06:14,497 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0766) Prec@1 86.000 (87.824) Prec@5 100.000 (99.206) +2022-11-14 16:06:14,510 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0768) Prec@1 88.000 (87.829) Prec@5 98.000 (99.171) +2022-11-14 16:06:14,530 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0764) Prec@1 91.000 (87.917) Prec@5 100.000 (99.194) +2022-11-14 16:06:14,551 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0761) Prec@1 87.000 (87.892) Prec@5 98.000 (99.162) +2022-11-14 16:06:14,568 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0768) Prec@1 82.000 (87.737) Prec@5 99.000 (99.158) +2022-11-14 16:06:14,584 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0762) Prec@1 94.000 (87.897) Prec@5 98.000 (99.128) +2022-11-14 16:06:14,605 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0469 (0.0755) Prec@1 93.000 (88.025) Prec@5 100.000 (99.150) +2022-11-14 16:06:14,621 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0759) Prec@1 85.000 (87.951) Prec@5 99.000 (99.146) +2022-11-14 16:06:14,642 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0628 (0.0756) Prec@1 92.000 (88.048) Prec@5 98.000 (99.119) +2022-11-14 16:06:14,658 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0749) Prec@1 93.000 (88.163) Prec@5 98.000 (99.093) +2022-11-14 16:06:14,677 Test: [43/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0746) Prec@1 91.000 (88.227) Prec@5 99.000 (99.091) +2022-11-14 16:06:14,699 Test: [44/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0741) Prec@1 91.000 (88.289) Prec@5 100.000 (99.111) +2022-11-14 16:06:14,716 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0741) Prec@1 87.000 (88.261) Prec@5 100.000 (99.130) +2022-11-14 16:06:14,733 Test: [46/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0743) Prec@1 89.000 (88.277) Prec@5 100.000 (99.149) +2022-11-14 16:06:14,753 Test: [47/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0746) Prec@1 85.000 (88.208) Prec@5 100.000 (99.167) +2022-11-14 16:06:14,771 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0741) Prec@1 92.000 (88.286) Prec@5 100.000 (99.184) +2022-11-14 16:06:14,787 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0747) Prec@1 84.000 (88.200) Prec@5 100.000 (99.200) +2022-11-14 16:06:14,808 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0748) Prec@1 89.000 (88.216) Prec@5 100.000 (99.216) +2022-11-14 16:06:14,828 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0746) Prec@1 89.000 (88.231) Prec@5 99.000 (99.212) +2022-11-14 16:06:14,848 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0747) Prec@1 88.000 (88.226) Prec@5 99.000 (99.208) +2022-11-14 16:06:14,866 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0746) Prec@1 90.000 (88.259) Prec@5 98.000 (99.185) +2022-11-14 16:06:14,882 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0751) Prec@1 85.000 (88.200) Prec@5 100.000 (99.200) +2022-11-14 16:06:14,900 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0750) Prec@1 88.000 (88.196) Prec@5 98.000 (99.179) +2022-11-14 16:06:14,919 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0749) Prec@1 90.000 (88.228) Prec@5 99.000 (99.175) +2022-11-14 16:06:14,935 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0748) Prec@1 90.000 (88.259) Prec@5 99.000 (99.172) +2022-11-14 16:06:14,953 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0751) Prec@1 86.000 (88.220) Prec@5 99.000 (99.169) +2022-11-14 16:06:14,975 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0752) Prec@1 87.000 (88.200) Prec@5 100.000 (99.183) +2022-11-14 16:06:14,994 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0750) Prec@1 89.000 (88.213) Prec@5 99.000 (99.180) +2022-11-14 16:06:15,015 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0751) Prec@1 87.000 (88.194) Prec@5 99.000 (99.177) +2022-11-14 16:06:15,032 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0746) Prec@1 92.000 (88.254) Prec@5 100.000 (99.190) +2022-11-14 16:06:15,048 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0743) Prec@1 94.000 (88.344) Prec@5 100.000 (99.203) +2022-11-14 16:06:15,067 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0744) Prec@1 87.000 (88.323) Prec@5 99.000 (99.200) +2022-11-14 16:06:15,085 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0743) Prec@1 90.000 (88.348) Prec@5 99.000 (99.197) +2022-11-14 16:06:15,103 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0740) Prec@1 91.000 (88.388) Prec@5 100.000 (99.209) +2022-11-14 16:06:15,119 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0741) Prec@1 88.000 (88.382) Prec@5 100.000 (99.221) +2022-11-14 16:06:15,135 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0742) Prec@1 87.000 (88.362) Prec@5 99.000 (99.217) +2022-11-14 16:06:15,154 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0744) Prec@1 84.000 (88.300) Prec@5 99.000 (99.214) +2022-11-14 16:06:15,170 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0748) Prec@1 88.000 (88.296) Prec@5 98.000 (99.197) +2022-11-14 16:06:15,188 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0746) Prec@1 92.000 (88.347) Prec@5 100.000 (99.208) +2022-11-14 16:06:15,208 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0742) Prec@1 94.000 (88.425) Prec@5 99.000 (99.205) +2022-11-14 16:06:15,224 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0364 (0.0737) Prec@1 95.000 (88.514) Prec@5 100.000 (99.216) +2022-11-14 16:06:15,239 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1195 (0.0743) Prec@1 80.000 (88.400) Prec@5 99.000 (99.213) +2022-11-14 16:06:15,255 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0742) Prec@1 90.000 (88.421) Prec@5 99.000 (99.211) +2022-11-14 16:06:15,271 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0741) Prec@1 88.000 (88.416) Prec@5 98.000 (99.195) +2022-11-14 16:06:15,287 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0741) Prec@1 89.000 (88.423) Prec@5 97.000 (99.167) +2022-11-14 16:06:15,305 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0740) Prec@1 89.000 (88.430) Prec@5 100.000 (99.177) +2022-11-14 16:06:15,323 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0739) Prec@1 90.000 (88.450) Prec@5 100.000 (99.188) +2022-11-14 16:06:15,340 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0741) Prec@1 84.000 (88.395) Prec@5 98.000 (99.173) +2022-11-14 16:06:15,358 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0741) Prec@1 88.000 (88.390) Prec@5 99.000 (99.171) +2022-11-14 16:06:15,374 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0741) Prec@1 88.000 (88.386) Prec@5 100.000 (99.181) +2022-11-14 16:06:15,390 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0741) Prec@1 87.000 (88.369) Prec@5 99.000 (99.179) +2022-11-14 16:06:15,411 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0745) Prec@1 85.000 (88.329) Prec@5 98.000 (99.165) +2022-11-14 16:06:15,430 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0746) Prec@1 87.000 (88.314) Prec@5 100.000 (99.174) +2022-11-14 16:06:15,449 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0746) Prec@1 87.000 (88.299) Prec@5 100.000 (99.184) +2022-11-14 16:06:15,469 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0746) Prec@1 87.000 (88.284) Prec@5 99.000 (99.182) +2022-11-14 16:06:15,487 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0745) Prec@1 88.000 (88.281) Prec@5 99.000 (99.180) +2022-11-14 16:06:15,503 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0744) Prec@1 90.000 (88.300) Prec@5 99.000 (99.178) +2022-11-14 16:06:15,522 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0744) Prec@1 89.000 (88.308) Prec@5 100.000 (99.187) +2022-11-14 16:06:15,543 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0743) Prec@1 90.000 (88.326) Prec@5 99.000 (99.185) +2022-11-14 16:06:15,562 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0745) Prec@1 84.000 (88.280) Prec@5 100.000 (99.194) +2022-11-14 16:06:15,577 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0745) Prec@1 87.000 (88.266) Prec@5 99.000 (99.191) +2022-11-14 16:06:15,593 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0746) Prec@1 85.000 (88.232) Prec@5 100.000 (99.200) +2022-11-14 16:06:15,612 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0745) Prec@1 90.000 (88.250) Prec@5 99.000 (99.198) +2022-11-14 16:06:15,631 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0743) Prec@1 93.000 (88.299) Prec@5 99.000 (99.196) +2022-11-14 16:06:15,650 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0744) Prec@1 86.000 (88.276) Prec@5 100.000 (99.204) +2022-11-14 16:06:15,672 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0744) Prec@1 90.000 (88.293) Prec@5 100.000 (99.212) +2022-11-14 16:06:15,690 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0744) Prec@1 87.000 (88.280) Prec@5 99.000 (99.210) +2022-11-14 16:06:15,754 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:06:16,099 Epoch: [303][0/500] Time 0.024 (0.024) Data 0.256 (0.256) Loss 0.0253 (0.0253) Prec@1 96.000 (96.000) Prec@5 99.000 (99.000) +2022-11-14 16:06:16,552 Epoch: [303][10/500] Time 0.052 (0.039) Data 0.002 (0.025) Loss 0.0455 (0.0354) Prec@1 92.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 16:06:17,070 Epoch: [303][20/500] Time 0.047 (0.043) Data 0.002 (0.014) Loss 0.0343 (0.0351) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:06:17,600 Epoch: [303][30/500] Time 0.049 (0.044) Data 0.002 (0.010) Loss 0.0338 (0.0347) Prec@1 93.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 16:06:18,127 Epoch: [303][40/500] Time 0.049 (0.045) Data 0.002 (0.008) Loss 0.0297 (0.0337) Prec@1 95.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 16:06:18,661 Epoch: [303][50/500] Time 0.049 (0.045) Data 0.002 (0.007) Loss 0.0161 (0.0308) Prec@1 98.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:06:19,183 Epoch: [303][60/500] Time 0.046 (0.046) Data 0.002 (0.006) Loss 0.0457 (0.0329) Prec@1 90.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 16:06:19,681 Epoch: [303][70/500] Time 0.053 (0.045) Data 0.002 (0.006) Loss 0.0382 (0.0336) Prec@1 94.000 (94.000) Prec@5 99.000 (99.750) +2022-11-14 16:06:20,208 Epoch: [303][80/500] Time 0.043 (0.046) Data 0.002 (0.005) Loss 0.0506 (0.0355) Prec@1 90.000 (93.556) Prec@5 100.000 (99.778) +2022-11-14 16:06:20,724 Epoch: [303][90/500] Time 0.050 (0.046) Data 0.002 (0.005) Loss 0.0248 (0.0344) Prec@1 96.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 16:06:21,233 Epoch: [303][100/500] Time 0.052 (0.046) Data 0.002 (0.005) Loss 0.0487 (0.0357) Prec@1 92.000 (93.636) Prec@5 99.000 (99.727) +2022-11-14 16:06:21,732 Epoch: [303][110/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0380 (0.0359) Prec@1 94.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 16:06:22,258 Epoch: [303][120/500] Time 0.050 (0.046) Data 0.002 (0.004) Loss 0.0442 (0.0365) Prec@1 92.000 (93.538) Prec@5 100.000 (99.692) +2022-11-14 16:06:22,773 Epoch: [303][130/500] Time 0.047 (0.046) Data 0.002 (0.004) Loss 0.0391 (0.0367) Prec@1 92.000 (93.429) Prec@5 100.000 (99.714) +2022-11-14 16:06:23,288 Epoch: [303][140/500] Time 0.047 (0.046) Data 0.002 (0.004) Loss 0.0207 (0.0356) Prec@1 96.000 (93.600) Prec@5 100.000 (99.733) +2022-11-14 16:06:23,823 Epoch: [303][150/500] Time 0.050 (0.046) Data 0.002 (0.004) Loss 0.0430 (0.0361) Prec@1 93.000 (93.562) Prec@5 100.000 (99.750) +2022-11-14 16:06:24,344 Epoch: [303][160/500] Time 0.054 (0.046) Data 0.002 (0.004) Loss 0.0214 (0.0352) Prec@1 98.000 (93.824) Prec@5 100.000 (99.765) +2022-11-14 16:06:24,866 Epoch: [303][170/500] Time 0.042 (0.046) Data 0.002 (0.004) Loss 0.0284 (0.0349) Prec@1 97.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 16:06:25,397 Epoch: [303][180/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0478 (0.0355) Prec@1 92.000 (93.895) Prec@5 100.000 (99.789) +2022-11-14 16:06:25,918 Epoch: [303][190/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0425 (0.0359) Prec@1 91.000 (93.750) Prec@5 100.000 (99.800) +2022-11-14 16:06:26,437 Epoch: [303][200/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0213 (0.0352) Prec@1 98.000 (93.952) Prec@5 100.000 (99.810) +2022-11-14 16:06:26,948 Epoch: [303][210/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0273 (0.0348) Prec@1 95.000 (94.000) Prec@5 100.000 (99.818) +2022-11-14 16:06:27,490 Epoch: [303][220/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0392 (0.0350) Prec@1 94.000 (94.000) Prec@5 99.000 (99.783) +2022-11-14 16:06:27,997 Epoch: [303][230/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0364 (0.0351) Prec@1 92.000 (93.917) Prec@5 100.000 (99.792) +2022-11-14 16:06:28,524 Epoch: [303][240/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0532 (0.0358) Prec@1 93.000 (93.880) Prec@5 99.000 (99.760) +2022-11-14 16:06:29,051 Epoch: [303][250/500] Time 0.040 (0.046) Data 0.002 (0.003) Loss 0.0391 (0.0359) Prec@1 93.000 (93.846) Prec@5 100.000 (99.769) +2022-11-14 16:06:29,575 Epoch: [303][260/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0201 (0.0354) Prec@1 97.000 (93.963) Prec@5 100.000 (99.778) +2022-11-14 16:06:30,089 Epoch: [303][270/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0359 (0.0354) Prec@1 92.000 (93.893) Prec@5 100.000 (99.786) +2022-11-14 16:06:30,608 Epoch: [303][280/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0435 (0.0357) Prec@1 92.000 (93.828) Prec@5 100.000 (99.793) +2022-11-14 16:06:31,112 Epoch: [303][290/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0439 (0.0359) Prec@1 90.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 16:06:31,643 Epoch: [303][300/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0562 (0.0366) Prec@1 92.000 (93.645) Prec@5 100.000 (99.806) +2022-11-14 16:06:32,157 Epoch: [303][310/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.0345 (0.0365) Prec@1 92.000 (93.594) Prec@5 100.000 (99.812) +2022-11-14 16:06:32,682 Epoch: [303][320/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0417 (0.0367) Prec@1 93.000 (93.576) Prec@5 100.000 (99.818) +2022-11-14 16:06:33,211 Epoch: [303][330/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0456 (0.0369) Prec@1 93.000 (93.559) Prec@5 100.000 (99.824) +2022-11-14 16:06:33,733 Epoch: [303][340/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0260 (0.0366) Prec@1 97.000 (93.657) Prec@5 100.000 (99.829) +2022-11-14 16:06:34,244 Epoch: [303][350/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0428 (0.0368) Prec@1 92.000 (93.611) Prec@5 100.000 (99.833) +2022-11-14 16:06:34,767 Epoch: [303][360/500] Time 0.040 (0.046) Data 0.002 (0.003) Loss 0.0482 (0.0371) Prec@1 93.000 (93.595) Prec@5 100.000 (99.838) +2022-11-14 16:06:35,307 Epoch: [303][370/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0433 (0.0373) Prec@1 92.000 (93.553) Prec@5 99.000 (99.816) +2022-11-14 16:06:35,838 Epoch: [303][380/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0223 (0.0369) Prec@1 96.000 (93.615) Prec@5 100.000 (99.821) +2022-11-14 16:06:36,364 Epoch: [303][390/500] Time 0.043 (0.046) Data 0.002 (0.003) Loss 0.0473 (0.0371) Prec@1 94.000 (93.625) Prec@5 99.000 (99.800) +2022-11-14 16:06:36,896 Epoch: [303][400/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0345 (0.0371) Prec@1 96.000 (93.683) Prec@5 100.000 (99.805) +2022-11-14 16:06:37,398 Epoch: [303][410/500] Time 0.041 (0.046) Data 0.002 (0.003) Loss 0.0167 (0.0366) Prec@1 97.000 (93.762) Prec@5 99.000 (99.786) +2022-11-14 16:06:37,906 Epoch: [303][420/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0328 (0.0365) Prec@1 94.000 (93.767) Prec@5 100.000 (99.791) +2022-11-14 16:06:38,450 Epoch: [303][430/500] Time 0.057 (0.046) Data 0.002 (0.003) Loss 0.0447 (0.0367) Prec@1 92.000 (93.727) Prec@5 100.000 (99.795) +2022-11-14 16:06:38,963 Epoch: [303][440/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0394 (0.0368) Prec@1 94.000 (93.733) Prec@5 100.000 (99.800) +2022-11-14 16:06:39,500 Epoch: [303][450/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0377 (0.0368) Prec@1 94.000 (93.739) Prec@5 98.000 (99.761) +2022-11-14 16:06:40,024 Epoch: [303][460/500] Time 0.041 (0.046) Data 0.002 (0.003) Loss 0.0426 (0.0369) Prec@1 94.000 (93.745) Prec@5 100.000 (99.766) +2022-11-14 16:06:40,557 Epoch: [303][470/500] Time 0.060 (0.046) Data 0.002 (0.003) Loss 0.0401 (0.0370) Prec@1 93.000 (93.729) Prec@5 99.000 (99.750) +2022-11-14 16:06:41,082 Epoch: [303][480/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0437 (0.0371) Prec@1 95.000 (93.755) Prec@5 100.000 (99.755) +2022-11-14 16:06:41,603 Epoch: [303][490/500] Time 0.039 (0.046) Data 0.002 (0.003) Loss 0.0505 (0.0374) Prec@1 89.000 (93.660) Prec@5 100.000 (99.760) +2022-11-14 16:06:42,075 Epoch: [303][499/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0280 (0.0372) Prec@1 95.000 (93.686) Prec@5 100.000 (99.765) +2022-11-14 16:06:42,398 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0857 (0.0857) Prec@1 85.000 (85.000) Prec@5 98.000 (98.000) +2022-11-14 16:06:42,407 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0844) Prec@1 88.000 (86.500) Prec@5 99.000 (98.500) +2022-11-14 16:06:42,416 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0809) Prec@1 87.000 (86.667) Prec@5 99.000 (98.667) +2022-11-14 16:06:42,429 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0781) Prec@1 88.000 (87.000) Prec@5 99.000 (98.750) +2022-11-14 16:06:42,440 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0777) Prec@1 88.000 (87.200) Prec@5 99.000 (98.800) +2022-11-14 16:06:42,453 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0740) Prec@1 92.000 (88.000) Prec@5 99.000 (98.833) +2022-11-14 16:06:42,466 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0718) Prec@1 91.000 (88.429) Prec@5 99.000 (98.857) +2022-11-14 16:06:42,481 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0725) Prec@1 89.000 (88.500) Prec@5 99.000 (98.875) +2022-11-14 16:06:42,495 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0735) Prec@1 86.000 (88.222) Prec@5 100.000 (99.000) +2022-11-14 16:06:42,508 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0734) Prec@1 87.000 (88.100) Prec@5 97.000 (98.800) +2022-11-14 16:06:42,522 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0722) Prec@1 91.000 (88.364) Prec@5 100.000 (98.909) +2022-11-14 16:06:42,538 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0724) Prec@1 88.000 (88.333) Prec@5 100.000 (99.000) +2022-11-14 16:06:42,554 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0711) Prec@1 90.000 (88.462) Prec@5 99.000 (99.000) +2022-11-14 16:06:42,571 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0723) Prec@1 86.000 (88.286) Prec@5 99.000 (99.000) +2022-11-14 16:06:42,587 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0735) Prec@1 84.000 (88.000) Prec@5 97.000 (98.867) +2022-11-14 16:06:42,603 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0742) Prec@1 86.000 (87.875) Prec@5 98.000 (98.812) +2022-11-14 16:06:42,620 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0730) Prec@1 91.000 (88.059) Prec@5 98.000 (98.765) +2022-11-14 16:06:42,638 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1029 (0.0747) Prec@1 86.000 (87.944) Prec@5 100.000 (98.833) +2022-11-14 16:06:42,656 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0750) Prec@1 85.000 (87.789) Prec@5 99.000 (98.842) +2022-11-14 16:06:42,678 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0762) Prec@1 85.000 (87.650) Prec@5 96.000 (98.700) +2022-11-14 16:06:42,695 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0759) Prec@1 90.000 (87.762) Prec@5 100.000 (98.762) +2022-11-14 16:06:42,711 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0761) Prec@1 86.000 (87.682) Prec@5 99.000 (98.773) +2022-11-14 16:06:42,730 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0769) Prec@1 85.000 (87.565) Prec@5 98.000 (98.739) +2022-11-14 16:06:42,751 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0774) Prec@1 87.000 (87.542) Prec@5 99.000 (98.750) +2022-11-14 16:06:42,767 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0784) Prec@1 84.000 (87.400) Prec@5 100.000 (98.800) +2022-11-14 16:06:42,783 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0786) Prec@1 86.000 (87.346) Prec@5 100.000 (98.846) +2022-11-14 16:06:42,800 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0784) Prec@1 87.000 (87.333) Prec@5 100.000 (98.889) +2022-11-14 16:06:42,816 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0782) Prec@1 87.000 (87.321) Prec@5 100.000 (98.929) +2022-11-14 16:06:42,832 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0776) Prec@1 91.000 (87.448) Prec@5 99.000 (98.931) +2022-11-14 16:06:42,848 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0775) Prec@1 88.000 (87.467) Prec@5 99.000 (98.933) +2022-11-14 16:06:42,865 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0777) Prec@1 85.000 (87.387) Prec@5 100.000 (98.968) +2022-11-14 16:06:42,883 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0776) Prec@1 88.000 (87.406) Prec@5 99.000 (98.969) +2022-11-14 16:06:42,901 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0776) Prec@1 85.000 (87.333) Prec@5 99.000 (98.970) +2022-11-14 16:06:42,917 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0784) Prec@1 85.000 (87.265) Prec@5 99.000 (98.971) +2022-11-14 16:06:42,935 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0785) Prec@1 88.000 (87.286) Prec@5 97.000 (98.914) +2022-11-14 16:06:42,953 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0781) Prec@1 90.000 (87.361) Prec@5 99.000 (98.917) +2022-11-14 16:06:42,971 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0778) Prec@1 90.000 (87.432) Prec@5 98.000 (98.892) +2022-11-14 16:06:42,985 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0781) Prec@1 84.000 (87.342) Prec@5 98.000 (98.868) +2022-11-14 16:06:43,003 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0775) Prec@1 92.000 (87.462) Prec@5 99.000 (98.872) +2022-11-14 16:06:43,020 Test: [39/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0767) Prec@1 91.000 (87.550) Prec@5 98.000 (98.850) +2022-11-14 16:06:43,038 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0772) Prec@1 83.000 (87.439) Prec@5 99.000 (98.854) +2022-11-14 16:06:43,058 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0766) Prec@1 90.000 (87.500) Prec@5 99.000 (98.857) +2022-11-14 16:06:43,077 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0763) Prec@1 92.000 (87.605) Prec@5 99.000 (98.860) +2022-11-14 16:06:43,095 Test: [43/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0766) Prec@1 87.000 (87.591) Prec@5 97.000 (98.818) +2022-11-14 16:06:43,112 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0763) Prec@1 89.000 (87.622) Prec@5 100.000 (98.844) +2022-11-14 16:06:43,131 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1213 (0.0772) Prec@1 79.000 (87.435) Prec@5 98.000 (98.826) +2022-11-14 16:06:43,150 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0770) Prec@1 88.000 (87.447) Prec@5 100.000 (98.851) +2022-11-14 16:06:43,165 Test: [47/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1163 (0.0778) Prec@1 83.000 (87.354) Prec@5 99.000 (98.854) +2022-11-14 16:06:43,183 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0326 (0.0769) Prec@1 95.000 (87.510) Prec@5 100.000 (98.878) +2022-11-14 16:06:43,204 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1236 (0.0778) Prec@1 82.000 (87.400) Prec@5 100.000 (98.900) +2022-11-14 16:06:43,224 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0775) Prec@1 90.000 (87.451) Prec@5 99.000 (98.902) +2022-11-14 16:06:43,244 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0775) Prec@1 88.000 (87.462) Prec@5 99.000 (98.904) +2022-11-14 16:06:43,260 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0771) Prec@1 91.000 (87.528) Prec@5 99.000 (98.906) +2022-11-14 16:06:43,275 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0771) Prec@1 90.000 (87.574) Prec@5 99.000 (98.907) +2022-11-14 16:06:43,291 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0772) Prec@1 85.000 (87.527) Prec@5 100.000 (98.927) +2022-11-14 16:06:43,308 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0770) Prec@1 90.000 (87.571) Prec@5 99.000 (98.929) +2022-11-14 16:06:43,325 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0769) Prec@1 89.000 (87.596) Prec@5 100.000 (98.947) +2022-11-14 16:06:43,344 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0766) Prec@1 89.000 (87.621) Prec@5 100.000 (98.966) +2022-11-14 16:06:43,360 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1081 (0.0771) Prec@1 82.000 (87.525) Prec@5 98.000 (98.949) +2022-11-14 16:06:43,373 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0769) Prec@1 88.000 (87.533) Prec@5 100.000 (98.967) +2022-11-14 16:06:43,388 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0768) Prec@1 89.000 (87.557) Prec@5 99.000 (98.967) +2022-11-14 16:06:43,407 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0765) Prec@1 90.000 (87.597) Prec@5 99.000 (98.968) +2022-11-14 16:06:43,425 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0762) Prec@1 91.000 (87.651) Prec@5 100.000 (98.984) +2022-11-14 16:06:43,445 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0398 (0.0756) Prec@1 93.000 (87.734) Prec@5 100.000 (99.000) +2022-11-14 16:06:43,466 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0757) Prec@1 89.000 (87.754) Prec@5 99.000 (99.000) +2022-11-14 16:06:43,484 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0756) Prec@1 87.000 (87.742) Prec@5 98.000 (98.985) +2022-11-14 16:06:43,500 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0752) Prec@1 93.000 (87.821) Prec@5 100.000 (99.000) +2022-11-14 16:06:43,518 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0752) Prec@1 89.000 (87.838) Prec@5 99.000 (99.000) +2022-11-14 16:06:43,534 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0747) Prec@1 94.000 (87.928) Prec@5 99.000 (99.000) +2022-11-14 16:06:43,553 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0745) Prec@1 91.000 (87.971) Prec@5 100.000 (99.014) +2022-11-14 16:06:43,570 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0749) Prec@1 86.000 (87.944) Prec@5 99.000 (99.014) +2022-11-14 16:06:43,587 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0749) Prec@1 90.000 (87.972) Prec@5 100.000 (99.028) +2022-11-14 16:06:43,607 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0746) Prec@1 91.000 (88.014) Prec@5 99.000 (99.027) +2022-11-14 16:06:43,624 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0745) Prec@1 88.000 (88.014) Prec@5 100.000 (99.041) +2022-11-14 16:06:43,642 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1170 (0.0751) Prec@1 81.000 (87.920) Prec@5 100.000 (99.053) +2022-11-14 16:06:43,661 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0749) Prec@1 90.000 (87.947) Prec@5 100.000 (99.066) +2022-11-14 16:06:43,679 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0752) Prec@1 83.000 (87.883) Prec@5 99.000 (99.065) +2022-11-14 16:06:43,694 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0755) Prec@1 84.000 (87.833) Prec@5 99.000 (99.064) +2022-11-14 16:06:43,710 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 90.000 (87.861) Prec@5 99.000 (99.063) +2022-11-14 16:06:43,726 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0753) Prec@1 88.000 (87.862) Prec@5 100.000 (99.075) +2022-11-14 16:06:43,744 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0757) Prec@1 85.000 (87.827) Prec@5 99.000 (99.074) +2022-11-14 16:06:43,767 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0758) Prec@1 85.000 (87.793) Prec@5 99.000 (99.073) +2022-11-14 16:06:43,787 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0759) Prec@1 87.000 (87.783) Prec@5 100.000 (99.084) +2022-11-14 16:06:43,804 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0758) Prec@1 88.000 (87.786) Prec@5 99.000 (99.083) +2022-11-14 16:06:43,818 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0758) Prec@1 87.000 (87.776) Prec@5 100.000 (99.094) +2022-11-14 16:06:43,836 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0761) Prec@1 85.000 (87.744) Prec@5 100.000 (99.105) +2022-11-14 16:06:43,857 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0762) Prec@1 86.000 (87.724) Prec@5 98.000 (99.092) +2022-11-14 16:06:43,874 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0762) Prec@1 87.000 (87.716) Prec@5 98.000 (99.080) +2022-11-14 16:06:43,889 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0762) Prec@1 85.000 (87.685) Prec@5 100.000 (99.090) +2022-11-14 16:06:43,906 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0761) Prec@1 90.000 (87.711) Prec@5 100.000 (99.100) +2022-11-14 16:06:43,925 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0759) Prec@1 90.000 (87.736) Prec@5 100.000 (99.110) +2022-11-14 16:06:43,944 Test: [91/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0757) Prec@1 89.000 (87.750) Prec@5 100.000 (99.120) +2022-11-14 16:06:43,961 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0759) Prec@1 85.000 (87.720) Prec@5 100.000 (99.129) +2022-11-14 16:06:43,977 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0760) Prec@1 86.000 (87.702) Prec@5 99.000 (99.128) +2022-11-14 16:06:43,993 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0760) Prec@1 87.000 (87.695) Prec@5 99.000 (99.126) +2022-11-14 16:06:44,008 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0758) Prec@1 90.000 (87.719) Prec@5 98.000 (99.115) +2022-11-14 16:06:44,024 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0755) Prec@1 92.000 (87.763) Prec@5 98.000 (99.103) +2022-11-14 16:06:44,043 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0758) Prec@1 85.000 (87.735) Prec@5 98.000 (99.092) +2022-11-14 16:06:44,059 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0760) Prec@1 85.000 (87.707) Prec@5 98.000 (99.081) +2022-11-14 16:06:44,072 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0759) Prec@1 89.000 (87.720) Prec@5 100.000 (99.090) +2022-11-14 16:06:44,134 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:06:44,480 Epoch: [304][0/500] Time 0.025 (0.025) Data 0.257 (0.257) Loss 0.0334 (0.0334) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:06:44,768 Epoch: [304][10/500] Time 0.026 (0.025) Data 0.002 (0.025) Loss 0.0519 (0.0427) Prec@1 90.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 16:06:45,094 Epoch: [304][20/500] Time 0.031 (0.026) Data 0.002 (0.014) Loss 0.0393 (0.0415) Prec@1 94.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 16:06:45,661 Epoch: [304][30/500] Time 0.060 (0.034) Data 0.002 (0.010) Loss 0.0223 (0.0367) Prec@1 97.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:06:46,280 Epoch: [304][40/500] Time 0.063 (0.039) Data 0.002 (0.008) Loss 0.0338 (0.0361) Prec@1 93.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 16:06:46,904 Epoch: [304][50/500] Time 0.050 (0.043) Data 0.002 (0.007) Loss 0.0470 (0.0379) Prec@1 93.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 16:06:47,558 Epoch: [304][60/500] Time 0.061 (0.045) Data 0.002 (0.006) Loss 0.0595 (0.0410) Prec@1 92.000 (93.429) Prec@5 99.000 (99.714) +2022-11-14 16:06:48,166 Epoch: [304][70/500] Time 0.052 (0.047) Data 0.002 (0.006) Loss 0.0581 (0.0432) Prec@1 92.000 (93.250) Prec@5 99.000 (99.625) +2022-11-14 16:06:48,766 Epoch: [304][80/500] Time 0.067 (0.048) Data 0.002 (0.005) Loss 0.0386 (0.0426) Prec@1 95.000 (93.444) Prec@5 99.000 (99.556) +2022-11-14 16:06:49,405 Epoch: [304][90/500] Time 0.052 (0.049) Data 0.002 (0.005) Loss 0.0097 (0.0394) Prec@1 99.000 (94.000) Prec@5 100.000 (99.600) +2022-11-14 16:06:50,003 Epoch: [304][100/500] Time 0.057 (0.049) Data 0.002 (0.005) Loss 0.0241 (0.0380) Prec@1 94.000 (94.000) Prec@5 100.000 (99.636) +2022-11-14 16:06:50,664 Epoch: [304][110/500] Time 0.062 (0.050) Data 0.002 (0.004) Loss 0.0434 (0.0384) Prec@1 93.000 (93.917) Prec@5 100.000 (99.667) +2022-11-14 16:06:51,226 Epoch: [304][120/500] Time 0.058 (0.050) Data 0.002 (0.004) Loss 0.0321 (0.0379) Prec@1 94.000 (93.923) Prec@5 100.000 (99.692) +2022-11-14 16:06:51,816 Epoch: [304][130/500] Time 0.055 (0.050) Data 0.002 (0.004) Loss 0.0324 (0.0375) Prec@1 96.000 (94.071) Prec@5 100.000 (99.714) +2022-11-14 16:06:52,421 Epoch: [304][140/500] Time 0.052 (0.051) Data 0.002 (0.004) Loss 0.0391 (0.0376) Prec@1 93.000 (94.000) Prec@5 100.000 (99.733) +2022-11-14 16:06:52,986 Epoch: [304][150/500] Time 0.053 (0.051) Data 0.002 (0.004) Loss 0.0246 (0.0368) Prec@1 96.000 (94.125) Prec@5 100.000 (99.750) +2022-11-14 16:06:53,588 Epoch: [304][160/500] Time 0.041 (0.051) Data 0.002 (0.004) Loss 0.0389 (0.0369) Prec@1 93.000 (94.059) Prec@5 100.000 (99.765) +2022-11-14 16:06:54,215 Epoch: [304][170/500] Time 0.058 (0.051) Data 0.002 (0.004) Loss 0.0414 (0.0372) Prec@1 93.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 16:06:54,803 Epoch: [304][180/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0252 (0.0366) Prec@1 95.000 (94.053) Prec@5 100.000 (99.789) +2022-11-14 16:06:55,399 Epoch: [304][190/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0485 (0.0372) Prec@1 92.000 (93.950) Prec@5 100.000 (99.800) +2022-11-14 16:06:55,964 Epoch: [304][200/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0191 (0.0363) Prec@1 97.000 (94.095) Prec@5 100.000 (99.810) +2022-11-14 16:06:56,550 Epoch: [304][210/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0387 (0.0364) Prec@1 93.000 (94.045) Prec@5 100.000 (99.818) +2022-11-14 16:06:57,137 Epoch: [304][220/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0305 (0.0362) Prec@1 94.000 (94.043) Prec@5 100.000 (99.826) +2022-11-14 16:06:57,711 Epoch: [304][230/500] Time 0.048 (0.052) Data 0.002 (0.003) Loss 0.0401 (0.0363) Prec@1 92.000 (93.958) Prec@5 100.000 (99.833) +2022-11-14 16:06:58,308 Epoch: [304][240/500] Time 0.059 (0.052) Data 0.001 (0.003) Loss 0.0265 (0.0359) Prec@1 97.000 (94.080) Prec@5 100.000 (99.840) +2022-11-14 16:06:58,898 Epoch: [304][250/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0200 (0.0353) Prec@1 96.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 16:06:59,465 Epoch: [304][260/500] Time 0.056 (0.052) Data 0.003 (0.003) Loss 0.0278 (0.0350) Prec@1 94.000 (94.148) Prec@5 99.000 (99.815) +2022-11-14 16:07:00,060 Epoch: [304][270/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0127 (0.0342) Prec@1 99.000 (94.321) Prec@5 100.000 (99.821) +2022-11-14 16:07:00,659 Epoch: [304][280/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0566 (0.0350) Prec@1 90.000 (94.172) Prec@5 99.000 (99.793) +2022-11-14 16:07:01,236 Epoch: [304][290/500] Time 0.044 (0.052) Data 0.003 (0.003) Loss 0.0465 (0.0354) Prec@1 90.000 (94.033) Prec@5 100.000 (99.800) +2022-11-14 16:07:01,794 Epoch: [304][300/500] Time 0.057 (0.052) Data 0.003 (0.003) Loss 0.0466 (0.0358) Prec@1 92.000 (93.968) Prec@5 100.000 (99.806) +2022-11-14 16:07:02,392 Epoch: [304][310/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0410 (0.0359) Prec@1 93.000 (93.938) Prec@5 100.000 (99.812) +2022-11-14 16:07:02,979 Epoch: [304][320/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0305 (0.0358) Prec@1 97.000 (94.030) Prec@5 100.000 (99.818) +2022-11-14 16:07:03,581 Epoch: [304][330/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0202 (0.0353) Prec@1 96.000 (94.088) Prec@5 100.000 (99.824) +2022-11-14 16:07:04,242 Epoch: [304][340/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0384 (0.0354) Prec@1 93.000 (94.057) Prec@5 100.000 (99.829) +2022-11-14 16:07:04,864 Epoch: [304][350/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0233 (0.0350) Prec@1 97.000 (94.139) Prec@5 100.000 (99.833) +2022-11-14 16:07:05,496 Epoch: [304][360/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0256 (0.0348) Prec@1 96.000 (94.189) Prec@5 100.000 (99.838) +2022-11-14 16:07:06,104 Epoch: [304][370/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0548 (0.0353) Prec@1 92.000 (94.132) Prec@5 100.000 (99.842) +2022-11-14 16:07:06,778 Epoch: [304][380/500] Time 0.069 (0.052) Data 0.002 (0.003) Loss 0.0297 (0.0352) Prec@1 95.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 16:07:07,411 Epoch: [304][390/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0249 (0.0349) Prec@1 97.000 (94.225) Prec@5 99.000 (99.825) +2022-11-14 16:07:08,018 Epoch: [304][400/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0139 (0.0344) Prec@1 99.000 (94.341) Prec@5 100.000 (99.829) +2022-11-14 16:07:08,645 Epoch: [304][410/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0305 (0.0343) Prec@1 94.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:07:09,177 Epoch: [304][420/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0422 (0.0345) Prec@1 92.000 (94.279) Prec@5 100.000 (99.837) +2022-11-14 16:07:09,788 Epoch: [304][430/500] Time 0.075 (0.053) Data 0.002 (0.003) Loss 0.0316 (0.0344) Prec@1 93.000 (94.250) Prec@5 100.000 (99.841) +2022-11-14 16:07:10,407 Epoch: [304][440/500] Time 0.067 (0.053) Data 0.002 (0.003) Loss 0.0144 (0.0340) Prec@1 98.000 (94.333) Prec@5 100.000 (99.844) +2022-11-14 16:07:11,017 Epoch: [304][450/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0370 (0.0340) Prec@1 95.000 (94.348) Prec@5 100.000 (99.848) +2022-11-14 16:07:11,650 Epoch: [304][460/500] Time 0.074 (0.053) Data 0.003 (0.003) Loss 0.0207 (0.0338) Prec@1 97.000 (94.404) Prec@5 100.000 (99.851) +2022-11-14 16:07:12,194 Epoch: [304][470/500] Time 0.043 (0.053) Data 0.002 (0.003) Loss 0.0331 (0.0337) Prec@1 93.000 (94.375) Prec@5 100.000 (99.854) +2022-11-14 16:07:12,781 Epoch: [304][480/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0378 (0.0338) Prec@1 93.000 (94.347) Prec@5 99.000 (99.837) +2022-11-14 16:07:13,371 Epoch: [304][490/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0360 (0.0339) Prec@1 93.000 (94.320) Prec@5 100.000 (99.840) +2022-11-14 16:07:13,872 Epoch: [304][499/500] Time 0.045 (0.053) Data 0.002 (0.003) Loss 0.0495 (0.0342) Prec@1 95.000 (94.333) Prec@5 100.000 (99.843) +2022-11-14 16:07:14,216 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0714 (0.0714) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:14,227 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0784 (0.0749) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:14,242 Test: [2/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0901 (0.0800) Prec@1 85.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:14,259 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0566 (0.0741) Prec@1 90.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 16:07:14,271 Test: [4/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0723 (0.0738) Prec@1 91.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 16:07:14,280 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0564 (0.0709) Prec@1 92.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 16:07:14,290 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0552 (0.0686) Prec@1 92.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 16:07:14,306 Test: [7/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0937 (0.0718) Prec@1 84.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 16:07:14,319 Test: [8/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0853 (0.0733) Prec@1 85.000 (88.333) Prec@5 98.000 (99.556) +2022-11-14 16:07:14,328 Test: [9/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0766 (0.0736) Prec@1 88.000 (88.300) Prec@5 98.000 (99.400) +2022-11-14 16:07:14,337 Test: [10/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0738 (0.0736) Prec@1 87.000 (88.182) Prec@5 100.000 (99.455) +2022-11-14 16:07:14,352 Test: [11/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0793 (0.0741) Prec@1 86.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 16:07:14,363 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0752 (0.0742) Prec@1 86.000 (87.846) Prec@5 100.000 (99.538) +2022-11-14 16:07:14,373 Test: [13/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0807 (0.0746) Prec@1 87.000 (87.786) Prec@5 99.000 (99.500) +2022-11-14 16:07:14,383 Test: [14/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0822 (0.0751) Prec@1 86.000 (87.667) Prec@5 100.000 (99.533) +2022-11-14 16:07:14,397 Test: [15/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1013 (0.0768) Prec@1 82.000 (87.312) Prec@5 100.000 (99.562) +2022-11-14 16:07:14,410 Test: [16/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0419 (0.0747) Prec@1 95.000 (87.765) Prec@5 99.000 (99.529) +2022-11-14 16:07:14,421 Test: [17/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1088 (0.0766) Prec@1 84.000 (87.556) Prec@5 100.000 (99.556) +2022-11-14 16:07:14,431 Test: [18/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0883 (0.0772) Prec@1 83.000 (87.316) Prec@5 98.000 (99.474) +2022-11-14 16:07:14,446 Test: [19/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1041 (0.0786) Prec@1 86.000 (87.250) Prec@5 97.000 (99.350) +2022-11-14 16:07:14,459 Test: [20/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0844 (0.0789) Prec@1 85.000 (87.143) Prec@5 100.000 (99.381) +2022-11-14 16:07:14,470 Test: [21/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0669 (0.0783) Prec@1 88.000 (87.182) Prec@5 99.000 (99.364) +2022-11-14 16:07:14,481 Test: [22/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0922 (0.0789) Prec@1 84.000 (87.043) Prec@5 97.000 (99.261) +2022-11-14 16:07:14,498 Test: [23/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0964 (0.0796) Prec@1 84.000 (86.917) Prec@5 100.000 (99.292) +2022-11-14 16:07:14,511 Test: [24/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0986 (0.0804) Prec@1 86.000 (86.880) Prec@5 100.000 (99.320) +2022-11-14 16:07:14,521 Test: [25/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0906 (0.0808) Prec@1 85.000 (86.808) Prec@5 98.000 (99.269) +2022-11-14 16:07:14,532 Test: [26/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0651 (0.0802) Prec@1 89.000 (86.889) Prec@5 100.000 (99.296) +2022-11-14 16:07:14,547 Test: [27/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0854 (0.0804) Prec@1 87.000 (86.893) Prec@5 100.000 (99.321) +2022-11-14 16:07:14,559 Test: [28/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0822 (0.0805) Prec@1 86.000 (86.862) Prec@5 99.000 (99.310) +2022-11-14 16:07:14,569 Test: [29/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1046 (0.0813) Prec@1 83.000 (86.733) Prec@5 100.000 (99.333) +2022-11-14 16:07:14,580 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0810) Prec@1 88.000 (86.774) Prec@5 100.000 (99.355) +2022-11-14 16:07:14,592 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0812) Prec@1 86.000 (86.750) Prec@5 99.000 (99.344) +2022-11-14 16:07:14,604 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0813) Prec@1 85.000 (86.697) Prec@5 99.000 (99.333) +2022-11-14 16:07:14,614 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0965 (0.0818) Prec@1 85.000 (86.647) Prec@5 100.000 (99.353) +2022-11-14 16:07:14,625 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0821) Prec@1 84.000 (86.571) Prec@5 97.000 (99.286) +2022-11-14 16:07:14,636 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0649 (0.0816) Prec@1 91.000 (86.694) Prec@5 99.000 (99.278) +2022-11-14 16:07:14,646 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0811) Prec@1 88.000 (86.730) Prec@5 99.000 (99.270) +2022-11-14 16:07:14,656 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0894 (0.0813) Prec@1 84.000 (86.658) Prec@5 99.000 (99.263) +2022-11-14 16:07:14,667 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0487 (0.0805) Prec@1 92.000 (86.795) Prec@5 99.000 (99.256) +2022-11-14 16:07:14,678 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0804) Prec@1 89.000 (86.850) Prec@5 98.000 (99.225) +2022-11-14 16:07:14,688 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0806) Prec@1 86.000 (86.829) Prec@5 99.000 (99.220) +2022-11-14 16:07:14,698 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0805) Prec@1 89.000 (86.881) Prec@5 98.000 (99.190) +2022-11-14 16:07:14,708 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0610 (0.0801) Prec@1 91.000 (86.977) Prec@5 99.000 (99.186) +2022-11-14 16:07:14,720 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0799) Prec@1 89.000 (87.023) Prec@5 99.000 (99.182) +2022-11-14 16:07:14,730 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0797) Prec@1 88.000 (87.044) Prec@5 100.000 (99.200) +2022-11-14 16:07:14,742 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1069 (0.0803) Prec@1 82.000 (86.935) Prec@5 100.000 (99.217) +2022-11-14 16:07:14,753 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0802) Prec@1 88.000 (86.957) Prec@5 100.000 (99.234) +2022-11-14 16:07:14,764 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1063 (0.0808) Prec@1 84.000 (86.896) Prec@5 98.000 (99.208) +2022-11-14 16:07:14,775 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0390 (0.0799) Prec@1 93.000 (87.020) Prec@5 100.000 (99.224) +2022-11-14 16:07:14,787 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1077 (0.0805) Prec@1 83.000 (86.940) Prec@5 99.000 (99.220) +2022-11-14 16:07:14,800 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0553 (0.0800) Prec@1 91.000 (87.020) Prec@5 100.000 (99.235) +2022-11-14 16:07:14,810 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0799) Prec@1 87.000 (87.019) Prec@5 100.000 (99.250) +2022-11-14 16:07:14,821 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0472 (0.0793) Prec@1 93.000 (87.132) Prec@5 100.000 (99.264) +2022-11-14 16:07:14,832 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0791) Prec@1 88.000 (87.148) Prec@5 99.000 (99.259) +2022-11-14 16:07:14,842 Test: [54/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0884 (0.0793) Prec@1 85.000 (87.109) Prec@5 100.000 (99.273) +2022-11-14 16:07:14,853 Test: [55/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0792) Prec@1 89.000 (87.143) Prec@5 99.000 (99.268) +2022-11-14 16:07:14,864 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0792) Prec@1 87.000 (87.140) Prec@5 98.000 (99.246) +2022-11-14 16:07:14,875 Test: [57/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0789) Prec@1 92.000 (87.224) Prec@5 100.000 (99.259) +2022-11-14 16:07:14,886 Test: [58/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1157 (0.0795) Prec@1 83.000 (87.153) Prec@5 98.000 (99.237) +2022-11-14 16:07:14,896 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0586 (0.0792) Prec@1 88.000 (87.167) Prec@5 100.000 (99.250) +2022-11-14 16:07:14,907 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0791) Prec@1 89.000 (87.197) Prec@5 98.000 (99.230) +2022-11-14 16:07:14,917 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0791) Prec@1 87.000 (87.194) Prec@5 99.000 (99.226) +2022-11-14 16:07:14,928 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0787) Prec@1 91.000 (87.254) Prec@5 100.000 (99.238) +2022-11-14 16:07:14,937 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0448 (0.0782) Prec@1 93.000 (87.344) Prec@5 100.000 (99.250) +2022-11-14 16:07:14,948 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0781) Prec@1 89.000 (87.369) Prec@5 100.000 (99.262) +2022-11-14 16:07:14,959 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0948 (0.0784) Prec@1 85.000 (87.333) Prec@5 99.000 (99.258) +2022-11-14 16:07:14,970 Test: [66/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0384 (0.0778) Prec@1 94.000 (87.433) Prec@5 100.000 (99.269) +2022-11-14 16:07:14,980 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0778) Prec@1 89.000 (87.456) Prec@5 98.000 (99.250) +2022-11-14 16:07:14,990 Test: [68/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0627 (0.0775) Prec@1 92.000 (87.522) Prec@5 98.000 (99.232) +2022-11-14 16:07:15,001 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0974 (0.0778) Prec@1 84.000 (87.471) Prec@5 98.000 (99.214) +2022-11-14 16:07:15,012 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.0780) Prec@1 86.000 (87.451) Prec@5 98.000 (99.197) +2022-11-14 16:07:15,022 Test: [71/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0779) Prec@1 90.000 (87.486) Prec@5 99.000 (99.194) +2022-11-14 16:07:15,032 Test: [72/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0353 (0.0773) Prec@1 95.000 (87.589) Prec@5 100.000 (99.205) +2022-11-14 16:07:15,043 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0768) Prec@1 95.000 (87.689) Prec@5 100.000 (99.216) +2022-11-14 16:07:15,055 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.0772) Prec@1 82.000 (87.613) Prec@5 100.000 (99.227) +2022-11-14 16:07:15,067 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0770) Prec@1 91.000 (87.658) Prec@5 99.000 (99.224) +2022-11-14 16:07:15,077 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0770) Prec@1 88.000 (87.662) Prec@5 97.000 (99.195) +2022-11-14 16:07:15,089 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0773) Prec@1 81.000 (87.577) Prec@5 97.000 (99.167) +2022-11-14 16:07:15,101 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0870 (0.0774) Prec@1 85.000 (87.544) Prec@5 100.000 (99.177) +2022-11-14 16:07:15,113 Test: [79/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0774) Prec@1 86.000 (87.525) Prec@5 100.000 (99.188) +2022-11-14 16:07:15,124 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0777) Prec@1 86.000 (87.506) Prec@5 99.000 (99.185) +2022-11-14 16:07:15,133 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0776) Prec@1 88.000 (87.512) Prec@5 99.000 (99.183) +2022-11-14 16:07:15,144 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0777) Prec@1 87.000 (87.506) Prec@5 100.000 (99.193) +2022-11-14 16:07:15,155 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0775) Prec@1 90.000 (87.536) Prec@5 99.000 (99.190) +2022-11-14 16:07:15,165 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0776) Prec@1 86.000 (87.518) Prec@5 98.000 (99.176) +2022-11-14 16:07:15,177 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0778) Prec@1 85.000 (87.488) Prec@5 100.000 (99.186) +2022-11-14 16:07:15,187 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0448 (0.0774) Prec@1 91.000 (87.529) Prec@5 99.000 (99.184) +2022-11-14 16:07:15,198 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0774) Prec@1 88.000 (87.534) Prec@5 99.000 (99.182) +2022-11-14 16:07:15,210 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0773) Prec@1 89.000 (87.551) Prec@5 100.000 (99.191) +2022-11-14 16:07:15,222 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0772) Prec@1 90.000 (87.578) Prec@5 100.000 (99.200) +2022-11-14 16:07:15,232 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0772) Prec@1 84.000 (87.538) Prec@5 99.000 (99.198) +2022-11-14 16:07:15,242 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0768) Prec@1 95.000 (87.620) Prec@5 100.000 (99.207) +2022-11-14 16:07:15,253 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0769) Prec@1 87.000 (87.613) Prec@5 100.000 (99.215) +2022-11-14 16:07:15,264 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0768) Prec@1 88.000 (87.617) Prec@5 99.000 (99.213) +2022-11-14 16:07:15,274 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0769) Prec@1 88.000 (87.621) Prec@5 99.000 (99.211) +2022-11-14 16:07:15,284 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0770) Prec@1 86.000 (87.604) Prec@5 99.000 (99.208) +2022-11-14 16:07:15,299 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0392 (0.0766) Prec@1 94.000 (87.670) Prec@5 100.000 (99.216) +2022-11-14 16:07:15,312 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0767) Prec@1 87.000 (87.663) Prec@5 99.000 (99.214) +2022-11-14 16:07:15,325 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0769) Prec@1 85.000 (87.636) Prec@5 100.000 (99.222) +2022-11-14 16:07:15,338 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0770) Prec@1 88.000 (87.640) Prec@5 99.000 (99.220) +2022-11-14 16:07:15,402 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:07:15,744 Epoch: [305][0/500] Time 0.023 (0.023) Data 0.255 (0.255) Loss 0.0387 (0.0387) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 16:07:16,016 Epoch: [305][10/500] Time 0.026 (0.024) Data 0.002 (0.025) Loss 0.0327 (0.0357) Prec@1 94.000 (93.500) Prec@5 100.000 (99.500) +2022-11-14 16:07:16,394 Epoch: [305][20/500] Time 0.041 (0.028) Data 0.002 (0.014) Loss 0.0246 (0.0320) Prec@1 95.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:07:16,819 Epoch: [305][30/500] Time 0.042 (0.031) Data 0.002 (0.010) Loss 0.0434 (0.0349) Prec@1 94.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:07:17,244 Epoch: [305][40/500] Time 0.042 (0.033) Data 0.002 (0.008) Loss 0.0113 (0.0301) Prec@1 99.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 16:07:17,668 Epoch: [305][50/500] Time 0.044 (0.034) Data 0.002 (0.007) Loss 0.0288 (0.0299) Prec@1 94.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 16:07:18,124 Epoch: [305][60/500] Time 0.039 (0.035) Data 0.002 (0.006) Loss 0.0340 (0.0305) Prec@1 96.000 (95.000) Prec@5 100.000 (99.714) +2022-11-14 16:07:18,623 Epoch: [305][70/500] Time 0.045 (0.037) Data 0.002 (0.006) Loss 0.0313 (0.0306) Prec@1 93.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:07:19,040 Epoch: [305][80/500] Time 0.040 (0.037) Data 0.002 (0.005) Loss 0.0226 (0.0297) Prec@1 96.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 16:07:19,470 Epoch: [305][90/500] Time 0.044 (0.037) Data 0.002 (0.005) Loss 0.0472 (0.0315) Prec@1 91.000 (94.500) Prec@5 99.000 (99.700) +2022-11-14 16:07:19,894 Epoch: [305][100/500] Time 0.038 (0.037) Data 0.002 (0.005) Loss 0.0548 (0.0336) Prec@1 89.000 (94.000) Prec@5 99.000 (99.636) +2022-11-14 16:07:20,322 Epoch: [305][110/500] Time 0.037 (0.037) Data 0.003 (0.004) Loss 0.0377 (0.0339) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:07:20,809 Epoch: [305][120/500] Time 0.052 (0.038) Data 0.002 (0.004) Loss 0.0498 (0.0351) Prec@1 90.000 (93.692) Prec@5 99.000 (99.615) +2022-11-14 16:07:21,294 Epoch: [305][130/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0255 (0.0345) Prec@1 96.000 (93.857) Prec@5 100.000 (99.643) +2022-11-14 16:07:21,721 Epoch: [305][140/500] Time 0.033 (0.038) Data 0.002 (0.004) Loss 0.0417 (0.0349) Prec@1 95.000 (93.933) Prec@5 100.000 (99.667) +2022-11-14 16:07:22,157 Epoch: [305][150/500] Time 0.039 (0.038) Data 0.002 (0.004) Loss 0.0425 (0.0354) Prec@1 94.000 (93.938) Prec@5 100.000 (99.688) +2022-11-14 16:07:22,653 Epoch: [305][160/500] Time 0.055 (0.038) Data 0.002 (0.004) Loss 0.0262 (0.0349) Prec@1 96.000 (94.059) Prec@5 99.000 (99.647) +2022-11-14 16:07:23,120 Epoch: [305][170/500] Time 0.037 (0.039) Data 0.002 (0.004) Loss 0.0520 (0.0358) Prec@1 93.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:07:23,557 Epoch: [305][180/500] Time 0.035 (0.039) Data 0.002 (0.003) Loss 0.0233 (0.0352) Prec@1 96.000 (94.105) Prec@5 100.000 (99.684) +2022-11-14 16:07:23,992 Epoch: [305][190/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0214 (0.0345) Prec@1 98.000 (94.300) Prec@5 100.000 (99.700) +2022-11-14 16:07:24,431 Epoch: [305][200/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0206 (0.0338) Prec@1 97.000 (94.429) Prec@5 100.000 (99.714) +2022-11-14 16:07:24,977 Epoch: [305][210/500] Time 0.054 (0.039) Data 0.002 (0.003) Loss 0.0240 (0.0334) Prec@1 96.000 (94.500) Prec@5 100.000 (99.727) +2022-11-14 16:07:25,393 Epoch: [305][220/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0274 (0.0331) Prec@1 94.000 (94.478) Prec@5 100.000 (99.739) +2022-11-14 16:07:25,813 Epoch: [305][230/500] Time 0.037 (0.039) Data 0.002 (0.003) Loss 0.0413 (0.0334) Prec@1 93.000 (94.417) Prec@5 100.000 (99.750) +2022-11-14 16:07:26,233 Epoch: [305][240/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0550 (0.0343) Prec@1 92.000 (94.320) Prec@5 100.000 (99.760) +2022-11-14 16:07:26,665 Epoch: [305][250/500] Time 0.038 (0.039) Data 0.002 (0.003) Loss 0.0183 (0.0337) Prec@1 97.000 (94.423) Prec@5 100.000 (99.769) +2022-11-14 16:07:27,096 Epoch: [305][260/500] Time 0.053 (0.039) Data 0.002 (0.003) Loss 0.0394 (0.0339) Prec@1 93.000 (94.370) Prec@5 100.000 (99.778) +2022-11-14 16:07:27,531 Epoch: [305][270/500] Time 0.046 (0.039) Data 0.002 (0.003) Loss 0.0441 (0.0343) Prec@1 94.000 (94.357) Prec@5 100.000 (99.786) +2022-11-14 16:07:27,953 Epoch: [305][280/500] Time 0.041 (0.039) Data 0.002 (0.003) Loss 0.0415 (0.0345) Prec@1 93.000 (94.310) Prec@5 100.000 (99.793) +2022-11-14 16:07:28,395 Epoch: [305][290/500] Time 0.036 (0.039) Data 0.002 (0.003) Loss 0.0451 (0.0349) Prec@1 92.000 (94.233) Prec@5 100.000 (99.800) +2022-11-14 16:07:28,834 Epoch: [305][300/500] Time 0.039 (0.039) Data 0.002 (0.003) Loss 0.0423 (0.0351) Prec@1 91.000 (94.129) Prec@5 100.000 (99.806) +2022-11-14 16:07:29,254 Epoch: [305][310/500] Time 0.040 (0.039) Data 0.002 (0.003) Loss 0.0337 (0.0351) Prec@1 94.000 (94.125) Prec@5 100.000 (99.812) +2022-11-14 16:07:29,716 Epoch: [305][320/500] Time 0.040 (0.039) Data 0.003 (0.003) Loss 0.0313 (0.0349) Prec@1 96.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 16:07:30,176 Epoch: [305][330/500] Time 0.044 (0.039) Data 0.002 (0.003) Loss 0.0230 (0.0346) Prec@1 94.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 16:07:30,801 Epoch: [305][340/500] Time 0.096 (0.039) Data 0.002 (0.003) Loss 0.0407 (0.0348) Prec@1 93.000 (94.143) Prec@5 100.000 (99.829) +2022-11-14 16:07:31,530 Epoch: [305][350/500] Time 0.059 (0.040) Data 0.002 (0.003) Loss 0.0249 (0.0345) Prec@1 96.000 (94.194) Prec@5 100.000 (99.833) +2022-11-14 16:07:32,138 Epoch: [305][360/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0285 (0.0343) Prec@1 95.000 (94.216) Prec@5 100.000 (99.838) +2022-11-14 16:07:32,722 Epoch: [305][370/500] Time 0.057 (0.041) Data 0.002 (0.003) Loss 0.0402 (0.0345) Prec@1 93.000 (94.184) Prec@5 99.000 (99.816) +2022-11-14 16:07:33,293 Epoch: [305][380/500] Time 0.054 (0.041) Data 0.002 (0.003) Loss 0.0312 (0.0344) Prec@1 95.000 (94.205) Prec@5 100.000 (99.821) +2022-11-14 16:07:33,882 Epoch: [305][390/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0408 (0.0346) Prec@1 94.000 (94.200) Prec@5 100.000 (99.825) +2022-11-14 16:07:34,505 Epoch: [305][400/500] Time 0.087 (0.042) Data 0.002 (0.003) Loss 0.0270 (0.0344) Prec@1 97.000 (94.268) Prec@5 100.000 (99.829) +2022-11-14 16:07:35,145 Epoch: [305][410/500] Time 0.050 (0.042) Data 0.002 (0.003) Loss 0.0258 (0.0342) Prec@1 95.000 (94.286) Prec@5 100.000 (99.833) +2022-11-14 16:07:35,812 Epoch: [305][420/500] Time 0.085 (0.042) Data 0.002 (0.003) Loss 0.0307 (0.0341) Prec@1 96.000 (94.326) Prec@5 100.000 (99.837) +2022-11-14 16:07:36,426 Epoch: [305][430/500] Time 0.088 (0.043) Data 0.002 (0.003) Loss 0.0340 (0.0341) Prec@1 96.000 (94.364) Prec@5 98.000 (99.795) +2022-11-14 16:07:37,011 Epoch: [305][440/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0267 (0.0339) Prec@1 95.000 (94.378) Prec@5 99.000 (99.778) +2022-11-14 16:07:37,700 Epoch: [305][450/500] Time 0.082 (0.043) Data 0.002 (0.003) Loss 0.0260 (0.0338) Prec@1 94.000 (94.370) Prec@5 100.000 (99.783) +2022-11-14 16:07:38,428 Epoch: [305][460/500] Time 0.056 (0.044) Data 0.002 (0.003) Loss 0.0408 (0.0339) Prec@1 94.000 (94.362) Prec@5 99.000 (99.766) +2022-11-14 16:07:39,191 Epoch: [305][470/500] Time 0.106 (0.044) Data 0.003 (0.003) Loss 0.0397 (0.0340) Prec@1 91.000 (94.292) Prec@5 100.000 (99.771) +2022-11-14 16:07:40,035 Epoch: [305][480/500] Time 0.094 (0.045) Data 0.002 (0.003) Loss 0.0243 (0.0338) Prec@1 96.000 (94.327) Prec@5 100.000 (99.776) +2022-11-14 16:07:40,746 Epoch: [305][490/500] Time 0.076 (0.045) Data 0.002 (0.003) Loss 0.0474 (0.0341) Prec@1 94.000 (94.320) Prec@5 100.000 (99.780) +2022-11-14 16:07:41,411 Epoch: [305][499/500] Time 0.063 (0.046) Data 0.002 (0.003) Loss 0.0327 (0.0341) Prec@1 95.000 (94.333) Prec@5 100.000 (99.784) +2022-11-14 16:07:41,751 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0590 (0.0590) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:41,762 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0596 (0.0593) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:07:41,774 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0875 (0.0687) Prec@1 86.000 (89.000) Prec@5 98.000 (99.333) +2022-11-14 16:07:41,786 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0721 (0.0696) Prec@1 90.000 (89.250) Prec@5 99.000 (99.250) +2022-11-14 16:07:41,795 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0689) Prec@1 92.000 (89.800) Prec@5 99.000 (99.200) +2022-11-14 16:07:41,804 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0382 (0.0638) Prec@1 94.000 (90.500) Prec@5 100.000 (99.333) +2022-11-14 16:07:41,812 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0627) Prec@1 93.000 (90.857) Prec@5 100.000 (99.429) +2022-11-14 16:07:41,823 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0661) Prec@1 84.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 16:07:41,831 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0675) Prec@1 88.000 (89.778) Prec@5 100.000 (99.556) +2022-11-14 16:07:41,839 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0679) Prec@1 88.000 (89.600) Prec@5 98.000 (99.400) +2022-11-14 16:07:41,849 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0685) Prec@1 89.000 (89.545) Prec@5 100.000 (99.455) +2022-11-14 16:07:41,859 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0699) Prec@1 85.000 (89.167) Prec@5 100.000 (99.500) +2022-11-14 16:07:41,868 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0688) Prec@1 92.000 (89.385) Prec@5 100.000 (99.538) +2022-11-14 16:07:41,878 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0684) Prec@1 90.000 (89.429) Prec@5 99.000 (99.500) +2022-11-14 16:07:41,887 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0689) Prec@1 88.000 (89.333) Prec@5 98.000 (99.400) +2022-11-14 16:07:41,897 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0697) Prec@1 87.000 (89.188) Prec@5 99.000 (99.375) +2022-11-14 16:07:41,907 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0694) Prec@1 90.000 (89.235) Prec@5 98.000 (99.294) +2022-11-14 16:07:41,918 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1181 (0.0721) Prec@1 82.000 (88.833) Prec@5 100.000 (99.333) +2022-11-14 16:07:41,928 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0724) Prec@1 88.000 (88.789) Prec@5 98.000 (99.263) +2022-11-14 16:07:41,938 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0737) Prec@1 86.000 (88.650) Prec@5 97.000 (99.150) +2022-11-14 16:07:41,948 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0738) Prec@1 85.000 (88.476) Prec@5 100.000 (99.190) +2022-11-14 16:07:41,957 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0742) Prec@1 87.000 (88.409) Prec@5 98.000 (99.136) +2022-11-14 16:07:41,967 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0756) Prec@1 86.000 (88.304) Prec@5 99.000 (99.130) +2022-11-14 16:07:41,977 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0758) Prec@1 87.000 (88.250) Prec@5 99.000 (99.125) +2022-11-14 16:07:41,986 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0766) Prec@1 84.000 (88.080) Prec@5 100.000 (99.160) +2022-11-14 16:07:41,997 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0777) Prec@1 85.000 (87.962) Prec@5 98.000 (99.115) +2022-11-14 16:07:42,006 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0767) Prec@1 92.000 (88.111) Prec@5 100.000 (99.148) +2022-11-14 16:07:42,016 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0764) Prec@1 90.000 (88.179) Prec@5 100.000 (99.179) +2022-11-14 16:07:42,025 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0764) Prec@1 87.000 (88.138) Prec@5 97.000 (99.103) +2022-11-14 16:07:42,035 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0779 (0.0764) Prec@1 88.000 (88.133) Prec@5 97.000 (99.033) +2022-11-14 16:07:42,044 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0761) Prec@1 89.000 (88.161) Prec@5 100.000 (99.065) +2022-11-14 16:07:42,053 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0761) Prec@1 88.000 (88.156) Prec@5 100.000 (99.094) +2022-11-14 16:07:42,063 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0762) Prec@1 87.000 (88.121) Prec@5 99.000 (99.091) +2022-11-14 16:07:42,073 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0758) Prec@1 88.000 (88.118) Prec@5 100.000 (99.118) +2022-11-14 16:07:42,084 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0759) Prec@1 88.000 (88.114) Prec@5 99.000 (99.114) +2022-11-14 16:07:42,093 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0759) Prec@1 88.000 (88.111) Prec@5 100.000 (99.139) +2022-11-14 16:07:42,102 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0757) Prec@1 88.000 (88.108) Prec@5 100.000 (99.162) +2022-11-14 16:07:42,112 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0763) Prec@1 83.000 (87.974) Prec@5 99.000 (99.158) +2022-11-14 16:07:42,122 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0757) Prec@1 94.000 (88.128) Prec@5 98.000 (99.128) +2022-11-14 16:07:42,131 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0755) Prec@1 86.000 (88.075) Prec@5 99.000 (99.125) +2022-11-14 16:07:42,142 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0755) Prec@1 86.000 (88.024) Prec@5 99.000 (99.122) +2022-11-14 16:07:42,150 Test: [41/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 89.000 (88.048) Prec@5 99.000 (99.119) +2022-11-14 16:07:42,159 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0285 (0.0743) Prec@1 95.000 (88.209) Prec@5 99.000 (99.116) +2022-11-14 16:07:42,169 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0744) Prec@1 86.000 (88.159) Prec@5 99.000 (99.114) +2022-11-14 16:07:42,177 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0741) Prec@1 90.000 (88.200) Prec@5 99.000 (99.111) +2022-11-14 16:07:42,186 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1228 (0.0752) Prec@1 82.000 (88.065) Prec@5 100.000 (99.130) +2022-11-14 16:07:42,196 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0750) Prec@1 87.000 (88.043) Prec@5 100.000 (99.149) +2022-11-14 16:07:42,206 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0756) Prec@1 83.000 (87.938) Prec@5 99.000 (99.146) +2022-11-14 16:07:42,216 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0750) Prec@1 93.000 (88.041) Prec@5 100.000 (99.163) +2022-11-14 16:07:42,228 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0752) Prec@1 86.000 (88.000) Prec@5 100.000 (99.180) +2022-11-14 16:07:42,237 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0751) Prec@1 88.000 (88.000) Prec@5 100.000 (99.196) +2022-11-14 16:07:42,249 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0753) Prec@1 88.000 (88.000) Prec@5 99.000 (99.192) +2022-11-14 16:07:42,260 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0755) Prec@1 86.000 (87.962) Prec@5 100.000 (99.208) +2022-11-14 16:07:42,273 Test: [53/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0754) Prec@1 88.000 (87.963) Prec@5 100.000 (99.222) +2022-11-14 16:07:42,286 Test: [54/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0756) Prec@1 84.000 (87.891) Prec@5 100.000 (99.236) +2022-11-14 16:07:42,296 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0756) Prec@1 88.000 (87.893) Prec@5 99.000 (99.232) +2022-11-14 16:07:42,306 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0756) Prec@1 88.000 (87.895) Prec@5 99.000 (99.228) +2022-11-14 16:07:42,320 Test: [57/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0755) Prec@1 90.000 (87.931) Prec@5 99.000 (99.224) +2022-11-14 16:07:42,332 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0757) Prec@1 85.000 (87.881) Prec@5 100.000 (99.237) +2022-11-14 16:07:42,342 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0754) Prec@1 90.000 (87.917) Prec@5 100.000 (99.250) +2022-11-14 16:07:42,352 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0757) Prec@1 89.000 (87.934) Prec@5 100.000 (99.262) +2022-11-14 16:07:42,366 Test: [61/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0753) Prec@1 89.000 (87.952) Prec@5 98.000 (99.242) +2022-11-14 16:07:42,377 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0754) Prec@1 87.000 (87.937) Prec@5 99.000 (99.238) +2022-11-14 16:07:42,387 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0325 (0.0747) Prec@1 95.000 (88.047) Prec@5 100.000 (99.250) +2022-11-14 16:07:42,400 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1050 (0.0752) Prec@1 83.000 (87.969) Prec@5 100.000 (99.262) +2022-11-14 16:07:42,412 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0751) Prec@1 91.000 (88.015) Prec@5 98.000 (99.242) +2022-11-14 16:07:42,422 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0749) Prec@1 88.000 (88.015) Prec@5 99.000 (99.239) +2022-11-14 16:07:42,433 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0748) Prec@1 90.000 (88.044) Prec@5 98.000 (99.221) +2022-11-14 16:07:42,445 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0749) Prec@1 88.000 (88.043) Prec@5 98.000 (99.203) +2022-11-14 16:07:42,456 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0750) Prec@1 88.000 (88.043) Prec@5 100.000 (99.214) +2022-11-14 16:07:42,465 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.0755) Prec@1 83.000 (87.972) Prec@5 100.000 (99.225) +2022-11-14 16:07:42,474 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0756) Prec@1 87.000 (87.958) Prec@5 100.000 (99.236) +2022-11-14 16:07:42,485 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0754) Prec@1 90.000 (87.986) Prec@5 100.000 (99.247) +2022-11-14 16:07:42,494 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0365 (0.0749) Prec@1 94.000 (88.068) Prec@5 100.000 (99.257) +2022-11-14 16:07:42,504 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0751) Prec@1 84.000 (88.013) Prec@5 100.000 (99.267) +2022-11-14 16:07:42,512 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0751) Prec@1 88.000 (88.013) Prec@5 98.000 (99.250) +2022-11-14 16:07:42,521 Test: [76/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0752) Prec@1 88.000 (88.013) Prec@5 99.000 (99.247) +2022-11-14 16:07:42,531 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0753) Prec@1 86.000 (87.987) Prec@5 100.000 (99.256) +2022-11-14 16:07:42,540 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0752) Prec@1 88.000 (87.987) Prec@5 100.000 (99.266) +2022-11-14 16:07:42,550 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0752) Prec@1 90.000 (88.013) Prec@5 100.000 (99.275) +2022-11-14 16:07:42,560 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0755) Prec@1 85.000 (87.975) Prec@5 99.000 (99.272) +2022-11-14 16:07:42,569 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0756) Prec@1 87.000 (87.963) Prec@5 99.000 (99.268) +2022-11-14 16:07:42,582 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0757) Prec@1 87.000 (87.952) Prec@5 100.000 (99.277) +2022-11-14 16:07:42,597 Test: [83/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0756) Prec@1 88.000 (87.952) Prec@5 100.000 (99.286) +2022-11-14 16:07:42,611 Test: [84/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0757) Prec@1 85.000 (87.918) Prec@5 99.000 (99.282) +2022-11-14 16:07:42,625 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1145 (0.0761) Prec@1 81.000 (87.837) Prec@5 100.000 (99.291) +2022-11-14 16:07:42,639 Test: [86/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0762) Prec@1 87.000 (87.828) Prec@5 100.000 (99.299) +2022-11-14 16:07:42,653 Test: [87/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0763) Prec@1 86.000 (87.807) Prec@5 99.000 (99.295) +2022-11-14 16:07:42,667 Test: [88/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0762) Prec@1 87.000 (87.798) Prec@5 100.000 (99.303) +2022-11-14 16:07:42,679 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0761) Prec@1 89.000 (87.811) Prec@5 99.000 (99.300) +2022-11-14 16:07:42,693 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0365 (0.0757) Prec@1 94.000 (87.879) Prec@5 100.000 (99.308) +2022-11-14 16:07:42,705 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0754) Prec@1 92.000 (87.924) Prec@5 100.000 (99.315) +2022-11-14 16:07:42,719 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0756) Prec@1 85.000 (87.892) Prec@5 100.000 (99.323) +2022-11-14 16:07:42,737 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0756) Prec@1 87.000 (87.883) Prec@5 100.000 (99.330) +2022-11-14 16:07:42,755 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0758) Prec@1 85.000 (87.853) Prec@5 99.000 (99.326) +2022-11-14 16:07:42,773 Test: [95/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0756) Prec@1 90.000 (87.875) Prec@5 98.000 (99.312) +2022-11-14 16:07:42,791 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0754) Prec@1 89.000 (87.887) Prec@5 99.000 (99.309) +2022-11-14 16:07:42,806 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1102 (0.0758) Prec@1 85.000 (87.857) Prec@5 97.000 (99.286) +2022-11-14 16:07:42,822 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0759) Prec@1 86.000 (87.838) Prec@5 100.000 (99.293) +2022-11-14 16:07:42,839 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0758) Prec@1 89.000 (87.850) Prec@5 99.000 (99.290) +2022-11-14 16:07:42,902 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:07:43,261 Epoch: [306][0/500] Time 0.027 (0.027) Data 0.264 (0.264) Loss 0.0307 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:43,768 Epoch: [306][10/500] Time 0.056 (0.043) Data 0.002 (0.026) Loss 0.0465 (0.0386) Prec@1 91.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:44,237 Epoch: [306][20/500] Time 0.048 (0.042) Data 0.002 (0.015) Loss 0.0267 (0.0346) Prec@1 95.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 16:07:44,722 Epoch: [306][30/500] Time 0.049 (0.043) Data 0.002 (0.011) Loss 0.0127 (0.0292) Prec@1 99.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:07:45,202 Epoch: [306][40/500] Time 0.051 (0.043) Data 0.002 (0.008) Loss 0.0394 (0.0312) Prec@1 93.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 16:07:45,676 Epoch: [306][50/500] Time 0.044 (0.042) Data 0.002 (0.007) Loss 0.0522 (0.0347) Prec@1 91.000 (94.000) Prec@5 99.000 (99.833) +2022-11-14 16:07:46,230 Epoch: [306][60/500] Time 0.054 (0.044) Data 0.002 (0.006) Loss 0.0312 (0.0342) Prec@1 95.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 16:07:46,756 Epoch: [306][70/500] Time 0.058 (0.044) Data 0.002 (0.006) Loss 0.0277 (0.0334) Prec@1 93.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 16:07:47,247 Epoch: [306][80/500] Time 0.047 (0.044) Data 0.002 (0.005) Loss 0.0358 (0.0336) Prec@1 93.000 (93.889) Prec@5 100.000 (99.889) +2022-11-14 16:07:47,831 Epoch: [306][90/500] Time 0.051 (0.045) Data 0.002 (0.005) Loss 0.0340 (0.0337) Prec@1 93.000 (93.800) Prec@5 99.000 (99.800) +2022-11-14 16:07:48,369 Epoch: [306][100/500] Time 0.063 (0.045) Data 0.002 (0.005) Loss 0.0387 (0.0341) Prec@1 94.000 (93.818) Prec@5 100.000 (99.818) +2022-11-14 16:07:48,869 Epoch: [306][110/500] Time 0.049 (0.045) Data 0.002 (0.004) Loss 0.0176 (0.0328) Prec@1 98.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 16:07:49,355 Epoch: [306][120/500] Time 0.043 (0.045) Data 0.002 (0.004) Loss 0.0383 (0.0332) Prec@1 94.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 16:07:49,923 Epoch: [306][130/500] Time 0.040 (0.046) Data 0.002 (0.004) Loss 0.0252 (0.0326) Prec@1 97.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 16:07:50,479 Epoch: [306][140/500] Time 0.040 (0.046) Data 0.003 (0.004) Loss 0.0235 (0.0320) Prec@1 96.000 (94.467) Prec@5 100.000 (99.867) +2022-11-14 16:07:50,957 Epoch: [306][150/500] Time 0.046 (0.046) Data 0.002 (0.004) Loss 0.0258 (0.0316) Prec@1 96.000 (94.562) Prec@5 99.000 (99.812) +2022-11-14 16:07:51,451 Epoch: [306][160/500] Time 0.048 (0.046) Data 0.002 (0.004) Loss 0.0439 (0.0323) Prec@1 92.000 (94.412) Prec@5 100.000 (99.824) +2022-11-14 16:07:51,926 Epoch: [306][170/500] Time 0.041 (0.045) Data 0.002 (0.004) Loss 0.0143 (0.0313) Prec@1 97.000 (94.556) Prec@5 100.000 (99.833) +2022-11-14 16:07:52,409 Epoch: [306][180/500] Time 0.041 (0.045) Data 0.002 (0.004) Loss 0.0353 (0.0316) Prec@1 94.000 (94.526) Prec@5 100.000 (99.842) +2022-11-14 16:07:52,887 Epoch: [306][190/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0373 (0.0318) Prec@1 95.000 (94.550) Prec@5 100.000 (99.850) +2022-11-14 16:07:53,377 Epoch: [306][200/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0320 (0.0318) Prec@1 94.000 (94.524) Prec@5 100.000 (99.857) +2022-11-14 16:07:53,868 Epoch: [306][210/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0383 (0.0321) Prec@1 93.000 (94.455) Prec@5 100.000 (99.864) +2022-11-14 16:07:54,370 Epoch: [306][220/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0378 (0.0324) Prec@1 93.000 (94.391) Prec@5 100.000 (99.870) +2022-11-14 16:07:54,950 Epoch: [306][230/500] Time 0.058 (0.045) Data 0.002 (0.003) Loss 0.0229 (0.0320) Prec@1 97.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:07:55,537 Epoch: [306][240/500] Time 0.057 (0.046) Data 0.003 (0.003) Loss 0.0416 (0.0324) Prec@1 95.000 (94.520) Prec@5 100.000 (99.880) +2022-11-14 16:07:56,028 Epoch: [306][250/500] Time 0.046 (0.046) Data 0.003 (0.003) Loss 0.0306 (0.0323) Prec@1 95.000 (94.538) Prec@5 99.000 (99.846) +2022-11-14 16:07:56,513 Epoch: [306][260/500] Time 0.042 (0.045) Data 0.003 (0.003) Loss 0.0162 (0.0317) Prec@1 99.000 (94.704) Prec@5 100.000 (99.852) +2022-11-14 16:07:56,991 Epoch: [306][270/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0312 (0.0317) Prec@1 94.000 (94.679) Prec@5 100.000 (99.857) +2022-11-14 16:07:57,474 Epoch: [306][280/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0401 (0.0320) Prec@1 93.000 (94.621) Prec@5 100.000 (99.862) +2022-11-14 16:07:58,061 Epoch: [306][290/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0490 (0.0325) Prec@1 91.000 (94.500) Prec@5 100.000 (99.867) +2022-11-14 16:07:58,538 Epoch: [306][300/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0291 (0.0324) Prec@1 96.000 (94.548) Prec@5 99.000 (99.839) +2022-11-14 16:07:59,019 Epoch: [306][310/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0305 (0.0324) Prec@1 96.000 (94.594) Prec@5 100.000 (99.844) +2022-11-14 16:07:59,498 Epoch: [306][320/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0348 (0.0324) Prec@1 94.000 (94.576) Prec@5 100.000 (99.848) +2022-11-14 16:07:59,975 Epoch: [306][330/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0426 (0.0327) Prec@1 93.000 (94.529) Prec@5 100.000 (99.853) +2022-11-14 16:08:00,444 Epoch: [306][340/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0477 (0.0332) Prec@1 92.000 (94.457) Prec@5 99.000 (99.829) +2022-11-14 16:08:00,962 Epoch: [306][350/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0593 (0.0339) Prec@1 91.000 (94.361) Prec@5 100.000 (99.833) +2022-11-14 16:08:01,441 Epoch: [306][360/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0455 (0.0342) Prec@1 91.000 (94.270) Prec@5 100.000 (99.838) +2022-11-14 16:08:02,074 Epoch: [306][370/500] Time 0.057 (0.045) Data 0.002 (0.003) Loss 0.0309 (0.0341) Prec@1 95.000 (94.289) Prec@5 100.000 (99.842) +2022-11-14 16:08:02,663 Epoch: [306][380/500] Time 0.060 (0.046) Data 0.003 (0.003) Loss 0.0481 (0.0345) Prec@1 91.000 (94.205) Prec@5 100.000 (99.846) +2022-11-14 16:08:03,304 Epoch: [306][390/500] Time 0.063 (0.046) Data 0.003 (0.003) Loss 0.0270 (0.0343) Prec@1 95.000 (94.225) Prec@5 100.000 (99.850) +2022-11-14 16:08:03,935 Epoch: [306][400/500] Time 0.065 (0.046) Data 0.002 (0.003) Loss 0.0165 (0.0339) Prec@1 98.000 (94.317) Prec@5 100.000 (99.854) +2022-11-14 16:08:04,436 Epoch: [306][410/500] Time 0.040 (0.046) Data 0.002 (0.003) Loss 0.0271 (0.0337) Prec@1 95.000 (94.333) Prec@5 100.000 (99.857) +2022-11-14 16:08:04,916 Epoch: [306][420/500] Time 0.051 (0.046) Data 0.003 (0.003) Loss 0.0235 (0.0335) Prec@1 96.000 (94.372) Prec@5 100.000 (99.860) +2022-11-14 16:08:05,419 Epoch: [306][430/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0177 (0.0331) Prec@1 99.000 (94.477) Prec@5 100.000 (99.864) +2022-11-14 16:08:05,915 Epoch: [306][440/500] Time 0.056 (0.046) Data 0.003 (0.003) Loss 0.0300 (0.0330) Prec@1 95.000 (94.489) Prec@5 100.000 (99.867) +2022-11-14 16:08:06,414 Epoch: [306][450/500] Time 0.041 (0.046) Data 0.002 (0.003) Loss 0.0352 (0.0331) Prec@1 94.000 (94.478) Prec@5 100.000 (99.870) +2022-11-14 16:08:06,903 Epoch: [306][460/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0336 (0.0331) Prec@1 96.000 (94.511) Prec@5 100.000 (99.872) +2022-11-14 16:08:07,443 Epoch: [306][470/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0470 (0.0334) Prec@1 93.000 (94.479) Prec@5 98.000 (99.833) +2022-11-14 16:08:07,961 Epoch: [306][480/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0383 (0.0335) Prec@1 96.000 (94.510) Prec@5 98.000 (99.796) +2022-11-14 16:08:08,587 Epoch: [306][490/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0268 (0.0334) Prec@1 96.000 (94.540) Prec@5 99.000 (99.780) +2022-11-14 16:08:09,021 Epoch: [306][499/500] Time 0.040 (0.046) Data 0.002 (0.003) Loss 0.0368 (0.0334) Prec@1 94.000 (94.529) Prec@5 100.000 (99.784) +2022-11-14 16:08:09,368 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0555 (0.0555) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:09,377 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0591) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:09,387 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0673) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:08:09,402 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0674) Prec@1 91.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:08:09,414 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0693) Prec@1 91.000 (89.400) Prec@5 98.000 (99.400) +2022-11-14 16:08:09,426 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0514 (0.0663) Prec@1 90.000 (89.500) Prec@5 99.000 (99.333) +2022-11-14 16:08:09,437 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0651) Prec@1 91.000 (89.714) Prec@5 100.000 (99.429) +2022-11-14 16:08:09,451 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0666) Prec@1 84.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:08:09,462 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0671) Prec@1 89.000 (89.000) Prec@5 99.000 (99.444) +2022-11-14 16:08:09,472 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.0690) Prec@1 86.000 (88.700) Prec@5 99.000 (99.400) +2022-11-14 16:08:09,483 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0673) Prec@1 90.000 (88.818) Prec@5 100.000 (99.455) +2022-11-14 16:08:09,494 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0695) Prec@1 86.000 (88.583) Prec@5 99.000 (99.417) +2022-11-14 16:08:09,505 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0675) Prec@1 93.000 (88.923) Prec@5 99.000 (99.385) +2022-11-14 16:08:09,517 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0680) Prec@1 89.000 (88.929) Prec@5 98.000 (99.286) +2022-11-14 16:08:09,527 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0692) Prec@1 84.000 (88.600) Prec@5 99.000 (99.267) +2022-11-14 16:08:09,540 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0683) Prec@1 91.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 16:08:09,551 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0488 (0.0672) Prec@1 94.000 (89.059) Prec@5 98.000 (99.176) +2022-11-14 16:08:09,564 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0687) Prec@1 84.000 (88.778) Prec@5 100.000 (99.222) +2022-11-14 16:08:09,576 Test: [18/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0696) Prec@1 84.000 (88.526) Prec@5 99.000 (99.211) +2022-11-14 16:08:09,589 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0701) Prec@1 87.000 (88.450) Prec@5 98.000 (99.150) +2022-11-14 16:08:09,600 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0880 (0.0710) Prec@1 85.000 (88.286) Prec@5 100.000 (99.190) +2022-11-14 16:08:09,611 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0718) Prec@1 86.000 (88.182) Prec@5 99.000 (99.182) +2022-11-14 16:08:09,621 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0721) Prec@1 87.000 (88.130) Prec@5 98.000 (99.130) +2022-11-14 16:08:09,632 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0724) Prec@1 89.000 (88.167) Prec@5 99.000 (99.125) +2022-11-14 16:08:09,643 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0729) Prec@1 85.000 (88.040) Prec@5 99.000 (99.120) +2022-11-14 16:08:09,654 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0953 (0.0738) Prec@1 84.000 (87.885) Prec@5 99.000 (99.115) +2022-11-14 16:08:09,666 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0406 (0.0725) Prec@1 94.000 (88.111) Prec@5 100.000 (99.148) +2022-11-14 16:08:09,676 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0723) Prec@1 90.000 (88.179) Prec@5 99.000 (99.143) +2022-11-14 16:08:09,688 Test: [28/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0728) Prec@1 85.000 (88.069) Prec@5 98.000 (99.103) +2022-11-14 16:08:09,699 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0604 (0.0724) Prec@1 90.000 (88.133) Prec@5 99.000 (99.100) +2022-11-14 16:08:09,710 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0452 (0.0715) Prec@1 95.000 (88.355) Prec@5 99.000 (99.097) +2022-11-14 16:08:09,721 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0715) Prec@1 91.000 (88.438) Prec@5 98.000 (99.062) +2022-11-14 16:08:09,731 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0719) Prec@1 87.000 (88.394) Prec@5 100.000 (99.091) +2022-11-14 16:08:09,744 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0724) Prec@1 84.000 (88.265) Prec@5 99.000 (99.088) +2022-11-14 16:08:09,756 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0925 (0.0729) Prec@1 84.000 (88.143) Prec@5 98.000 (99.057) +2022-11-14 16:08:09,767 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0726) Prec@1 90.000 (88.194) Prec@5 100.000 (99.083) +2022-11-14 16:08:09,779 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0705 (0.0726) Prec@1 88.000 (88.189) Prec@5 98.000 (99.054) +2022-11-14 16:08:09,792 Test: [37/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0991 (0.0733) Prec@1 84.000 (88.079) Prec@5 99.000 (99.053) +2022-11-14 16:08:09,803 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0731) Prec@1 91.000 (88.154) Prec@5 99.000 (99.051) +2022-11-14 16:08:09,814 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0731) Prec@1 88.000 (88.150) Prec@5 99.000 (99.050) +2022-11-14 16:08:09,826 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.0737) Prec@1 87.000 (88.122) Prec@5 99.000 (99.049) +2022-11-14 16:08:09,836 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0523 (0.0732) Prec@1 93.000 (88.238) Prec@5 99.000 (99.048) +2022-11-14 16:08:09,847 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0727) Prec@1 93.000 (88.349) Prec@5 99.000 (99.047) +2022-11-14 16:08:09,857 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0633 (0.0725) Prec@1 90.000 (88.386) Prec@5 98.000 (99.023) +2022-11-14 16:08:09,867 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0720) Prec@1 91.000 (88.444) Prec@5 99.000 (99.022) +2022-11-14 16:08:09,877 Test: [45/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.0728) Prec@1 82.000 (88.304) Prec@5 98.000 (99.000) +2022-11-14 16:08:09,888 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0728) Prec@1 88.000 (88.298) Prec@5 100.000 (99.021) +2022-11-14 16:08:09,898 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0904 (0.0732) Prec@1 87.000 (88.271) Prec@5 100.000 (99.042) +2022-11-14 16:08:09,908 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0730) Prec@1 89.000 (88.286) Prec@5 99.000 (99.041) +2022-11-14 16:08:09,919 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1018 (0.0736) Prec@1 86.000 (88.240) Prec@5 99.000 (99.040) +2022-11-14 16:08:09,929 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0734) Prec@1 91.000 (88.294) Prec@5 100.000 (99.059) +2022-11-14 16:08:09,940 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0990 (0.0739) Prec@1 84.000 (88.212) Prec@5 99.000 (99.058) +2022-11-14 16:08:09,949 Test: [52/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0555 (0.0736) Prec@1 90.000 (88.245) Prec@5 100.000 (99.075) +2022-11-14 16:08:09,959 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0731) Prec@1 93.000 (88.333) Prec@5 100.000 (99.093) +2022-11-14 16:08:09,969 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0734) Prec@1 87.000 (88.309) Prec@5 100.000 (99.109) +2022-11-14 16:08:09,979 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0734) Prec@1 87.000 (88.286) Prec@5 99.000 (99.107) +2022-11-14 16:08:09,990 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0732) Prec@1 91.000 (88.333) Prec@5 99.000 (99.105) +2022-11-14 16:08:10,000 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0730) Prec@1 91.000 (88.379) Prec@5 100.000 (99.121) +2022-11-14 16:08:10,010 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0735) Prec@1 85.000 (88.322) Prec@5 99.000 (99.119) +2022-11-14 16:08:10,020 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0736) Prec@1 86.000 (88.283) Prec@5 100.000 (99.133) +2022-11-14 16:08:10,030 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0737) Prec@1 86.000 (88.246) Prec@5 100.000 (99.148) +2022-11-14 16:08:10,040 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0733) Prec@1 93.000 (88.323) Prec@5 99.000 (99.145) +2022-11-14 16:08:10,051 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0732) Prec@1 88.000 (88.317) Prec@5 99.000 (99.143) +2022-11-14 16:08:10,062 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0728) Prec@1 92.000 (88.375) Prec@5 99.000 (99.141) +2022-11-14 16:08:10,073 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0730) Prec@1 88.000 (88.369) Prec@5 100.000 (99.154) +2022-11-14 16:08:10,083 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0731) Prec@1 87.000 (88.348) Prec@5 97.000 (99.121) +2022-11-14 16:08:10,093 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0417 (0.0726) Prec@1 93.000 (88.418) Prec@5 100.000 (99.134) +2022-11-14 16:08:10,103 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0725) Prec@1 89.000 (88.426) Prec@5 99.000 (99.132) +2022-11-14 16:08:10,113 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0727) Prec@1 84.000 (88.362) Prec@5 99.000 (99.130) +2022-11-14 16:08:10,123 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0729) Prec@1 84.000 (88.300) Prec@5 98.000 (99.114) +2022-11-14 16:08:10,133 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0731) Prec@1 89.000 (88.310) Prec@5 99.000 (99.113) +2022-11-14 16:08:10,143 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0728) Prec@1 92.000 (88.361) Prec@5 100.000 (99.125) +2022-11-14 16:08:10,153 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0726) Prec@1 91.000 (88.397) Prec@5 99.000 (99.123) +2022-11-14 16:08:10,164 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0339 (0.0720) Prec@1 95.000 (88.486) Prec@5 100.000 (99.135) +2022-11-14 16:08:10,173 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0721) Prec@1 87.000 (88.467) Prec@5 99.000 (99.133) +2022-11-14 16:08:10,184 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0720) Prec@1 91.000 (88.500) Prec@5 98.000 (99.118) +2022-11-14 16:08:10,194 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0721) Prec@1 86.000 (88.468) Prec@5 98.000 (99.104) +2022-11-14 16:08:10,204 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0723) Prec@1 87.000 (88.449) Prec@5 98.000 (99.090) +2022-11-14 16:08:10,214 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0722) Prec@1 91.000 (88.481) Prec@5 99.000 (99.089) +2022-11-14 16:08:10,224 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0726) Prec@1 83.000 (88.412) Prec@5 97.000 (99.062) +2022-11-14 16:08:10,235 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0728) Prec@1 86.000 (88.383) Prec@5 98.000 (99.049) +2022-11-14 16:08:10,246 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0730) Prec@1 85.000 (88.341) Prec@5 100.000 (99.061) +2022-11-14 16:08:10,257 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0729) Prec@1 90.000 (88.361) Prec@5 100.000 (99.072) +2022-11-14 16:08:10,271 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0729) Prec@1 89.000 (88.369) Prec@5 99.000 (99.071) +2022-11-14 16:08:10,285 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0731) Prec@1 86.000 (88.341) Prec@5 99.000 (99.071) +2022-11-14 16:08:10,299 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0735) Prec@1 82.000 (88.267) Prec@5 97.000 (99.047) +2022-11-14 16:08:10,314 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0736) Prec@1 87.000 (88.253) Prec@5 100.000 (99.057) +2022-11-14 16:08:10,328 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0738) Prec@1 85.000 (88.216) Prec@5 98.000 (99.045) +2022-11-14 16:08:10,346 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0741) Prec@1 85.000 (88.180) Prec@5 99.000 (99.045) +2022-11-14 16:08:10,362 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0740) Prec@1 88.000 (88.178) Prec@5 100.000 (99.056) +2022-11-14 16:08:10,376 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0739) Prec@1 91.000 (88.209) Prec@5 100.000 (99.066) +2022-11-14 16:08:10,391 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0737) Prec@1 91.000 (88.239) Prec@5 100.000 (99.076) +2022-11-14 16:08:10,408 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0739) Prec@1 84.000 (88.194) Prec@5 97.000 (99.054) +2022-11-14 16:08:10,426 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0738) Prec@1 90.000 (88.213) Prec@5 100.000 (99.064) +2022-11-14 16:08:10,444 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0737) Prec@1 85.000 (88.179) Prec@5 99.000 (99.063) +2022-11-14 16:08:10,461 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0736) Prec@1 89.000 (88.188) Prec@5 98.000 (99.052) +2022-11-14 16:08:10,476 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0735) Prec@1 88.000 (88.186) Prec@5 99.000 (99.052) +2022-11-14 16:08:10,492 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0738) Prec@1 83.000 (88.133) Prec@5 99.000 (99.051) +2022-11-14 16:08:10,511 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1094 (0.0741) Prec@1 85.000 (88.101) Prec@5 99.000 (99.051) +2022-11-14 16:08:10,526 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0744) Prec@1 82.000 (88.040) Prec@5 99.000 (99.050) +2022-11-14 16:08:10,589 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:08:10,965 Epoch: [307][0/500] Time 0.025 (0.025) Data 0.281 (0.281) Loss 0.0317 (0.0317) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:11,428 Epoch: [307][10/500] Time 0.052 (0.040) Data 0.002 (0.028) Loss 0.0296 (0.0307) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:08:11,970 Epoch: [307][20/500] Time 0.047 (0.044) Data 0.002 (0.015) Loss 0.0365 (0.0326) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:12,510 Epoch: [307][30/500] Time 0.047 (0.046) Data 0.002 (0.011) Loss 0.0219 (0.0299) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:08:13,052 Epoch: [307][40/500] Time 0.050 (0.047) Data 0.002 (0.009) Loss 0.0557 (0.0351) Prec@1 90.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:08:13,648 Epoch: [307][50/500] Time 0.067 (0.048) Data 0.002 (0.008) Loss 0.0233 (0.0331) Prec@1 97.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 16:08:14,201 Epoch: [307][60/500] Time 0.055 (0.048) Data 0.002 (0.007) Loss 0.0191 (0.0311) Prec@1 97.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:08:14,728 Epoch: [307][70/500] Time 0.051 (0.048) Data 0.002 (0.006) Loss 0.0179 (0.0295) Prec@1 97.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 16:08:15,254 Epoch: [307][80/500] Time 0.052 (0.048) Data 0.002 (0.006) Loss 0.0328 (0.0298) Prec@1 93.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:08:15,767 Epoch: [307][90/500] Time 0.051 (0.048) Data 0.002 (0.005) Loss 0.0248 (0.0293) Prec@1 95.000 (95.100) Prec@5 100.000 (100.000) +2022-11-14 16:08:16,323 Epoch: [307][100/500] Time 0.045 (0.048) Data 0.002 (0.005) Loss 0.0320 (0.0296) Prec@1 96.000 (95.182) Prec@5 100.000 (100.000) +2022-11-14 16:08:16,858 Epoch: [307][110/500] Time 0.044 (0.048) Data 0.002 (0.005) Loss 0.0318 (0.0298) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:08:17,380 Epoch: [307][120/500] Time 0.054 (0.048) Data 0.003 (0.004) Loss 0.0224 (0.0292) Prec@1 96.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 16:08:17,909 Epoch: [307][130/500] Time 0.064 (0.048) Data 0.002 (0.004) Loss 0.0365 (0.0297) Prec@1 95.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 16:08:18,434 Epoch: [307][140/500] Time 0.056 (0.048) Data 0.002 (0.004) Loss 0.0486 (0.0310) Prec@1 92.000 (95.067) Prec@5 99.000 (99.933) +2022-11-14 16:08:18,963 Epoch: [307][150/500] Time 0.049 (0.048) Data 0.002 (0.004) Loss 0.0345 (0.0312) Prec@1 94.000 (95.000) Prec@5 100.000 (99.938) +2022-11-14 16:08:19,485 Epoch: [307][160/500] Time 0.050 (0.047) Data 0.002 (0.004) Loss 0.0370 (0.0315) Prec@1 92.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 16:08:20,016 Epoch: [307][170/500] Time 0.048 (0.047) Data 0.002 (0.004) Loss 0.0286 (0.0314) Prec@1 96.000 (94.889) Prec@5 100.000 (99.944) +2022-11-14 16:08:20,564 Epoch: [307][180/500] Time 0.040 (0.047) Data 0.002 (0.004) Loss 0.0504 (0.0324) Prec@1 92.000 (94.737) Prec@5 100.000 (99.947) +2022-11-14 16:08:21,082 Epoch: [307][190/500] Time 0.049 (0.047) Data 0.002 (0.004) Loss 0.0173 (0.0316) Prec@1 99.000 (94.950) Prec@5 100.000 (99.950) +2022-11-14 16:08:21,606 Epoch: [307][200/500] Time 0.047 (0.047) Data 0.002 (0.004) Loss 0.0458 (0.0323) Prec@1 93.000 (94.857) Prec@5 100.000 (99.952) +2022-11-14 16:08:22,136 Epoch: [307][210/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0357 (0.0324) Prec@1 92.000 (94.727) Prec@5 100.000 (99.955) +2022-11-14 16:08:22,670 Epoch: [307][220/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0440 (0.0329) Prec@1 93.000 (94.652) Prec@5 100.000 (99.957) +2022-11-14 16:08:23,201 Epoch: [307][230/500] Time 0.046 (0.047) Data 0.004 (0.003) Loss 0.0341 (0.0330) Prec@1 94.000 (94.625) Prec@5 100.000 (99.958) +2022-11-14 16:08:23,744 Epoch: [307][240/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0227 (0.0326) Prec@1 97.000 (94.720) Prec@5 100.000 (99.960) +2022-11-14 16:08:24,279 Epoch: [307][250/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0289 (0.0324) Prec@1 96.000 (94.769) Prec@5 100.000 (99.962) +2022-11-14 16:08:24,779 Epoch: [307][260/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0190 (0.0319) Prec@1 97.000 (94.852) Prec@5 100.000 (99.963) +2022-11-14 16:08:25,328 Epoch: [307][270/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0330 (0.0320) Prec@1 95.000 (94.857) Prec@5 100.000 (99.964) +2022-11-14 16:08:25,874 Epoch: [307][280/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0251 (0.0317) Prec@1 97.000 (94.931) Prec@5 100.000 (99.966) +2022-11-14 16:08:26,387 Epoch: [307][290/500] Time 0.037 (0.047) Data 0.002 (0.003) Loss 0.0399 (0.0320) Prec@1 92.000 (94.833) Prec@5 100.000 (99.967) +2022-11-14 16:08:26,933 Epoch: [307][300/500] Time 0.050 (0.047) Data 0.003 (0.003) Loss 0.0449 (0.0324) Prec@1 93.000 (94.774) Prec@5 100.000 (99.968) +2022-11-14 16:08:27,467 Epoch: [307][310/500] Time 0.051 (0.047) Data 0.003 (0.003) Loss 0.0303 (0.0324) Prec@1 96.000 (94.812) Prec@5 99.000 (99.938) +2022-11-14 16:08:27,997 Epoch: [307][320/500] Time 0.054 (0.047) Data 0.003 (0.003) Loss 0.0155 (0.0318) Prec@1 98.000 (94.909) Prec@5 100.000 (99.939) +2022-11-14 16:08:28,528 Epoch: [307][330/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0362 (0.0320) Prec@1 93.000 (94.853) Prec@5 100.000 (99.941) +2022-11-14 16:08:29,065 Epoch: [307][340/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0670 (0.0330) Prec@1 90.000 (94.714) Prec@5 100.000 (99.943) +2022-11-14 16:08:29,601 Epoch: [307][350/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0369 (0.0331) Prec@1 96.000 (94.750) Prec@5 100.000 (99.944) +2022-11-14 16:08:30,134 Epoch: [307][360/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0374 (0.0332) Prec@1 94.000 (94.730) Prec@5 100.000 (99.946) +2022-11-14 16:08:30,667 Epoch: [307][370/500] Time 0.051 (0.047) Data 0.003 (0.003) Loss 0.0401 (0.0334) Prec@1 96.000 (94.763) Prec@5 100.000 (99.947) +2022-11-14 16:08:31,222 Epoch: [307][380/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0241 (0.0331) Prec@1 96.000 (94.795) Prec@5 100.000 (99.949) +2022-11-14 16:08:31,753 Epoch: [307][390/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0501 (0.0336) Prec@1 92.000 (94.725) Prec@5 100.000 (99.950) +2022-11-14 16:08:32,294 Epoch: [307][400/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0535 (0.0341) Prec@1 92.000 (94.659) Prec@5 100.000 (99.951) +2022-11-14 16:08:32,826 Epoch: [307][410/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0246 (0.0338) Prec@1 96.000 (94.690) Prec@5 100.000 (99.952) +2022-11-14 16:08:33,356 Epoch: [307][420/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0429 (0.0340) Prec@1 92.000 (94.628) Prec@5 100.000 (99.953) +2022-11-14 16:08:33,886 Epoch: [307][430/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0379 (0.0341) Prec@1 93.000 (94.591) Prec@5 100.000 (99.955) +2022-11-14 16:08:34,420 Epoch: [307][440/500] Time 0.050 (0.047) Data 0.002 (0.003) Loss 0.0395 (0.0342) Prec@1 94.000 (94.578) Prec@5 100.000 (99.956) +2022-11-14 16:08:34,966 Epoch: [307][450/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0459 (0.0345) Prec@1 92.000 (94.522) Prec@5 100.000 (99.957) +2022-11-14 16:08:35,486 Epoch: [307][460/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0403 (0.0346) Prec@1 92.000 (94.468) Prec@5 100.000 (99.957) +2022-11-14 16:08:36,027 Epoch: [307][470/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0222 (0.0344) Prec@1 96.000 (94.500) Prec@5 100.000 (99.958) +2022-11-14 16:08:36,557 Epoch: [307][480/500] Time 0.058 (0.047) Data 0.003 (0.003) Loss 0.0436 (0.0346) Prec@1 92.000 (94.449) Prec@5 100.000 (99.959) +2022-11-14 16:08:37,099 Epoch: [307][490/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0592 (0.0350) Prec@1 89.000 (94.340) Prec@5 99.000 (99.940) +2022-11-14 16:08:37,549 Epoch: [307][499/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0352 (0.0351) Prec@1 93.000 (94.314) Prec@5 100.000 (99.941) +2022-11-14 16:08:37,884 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:08:37,893 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0661) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:08:37,905 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0680) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:08:37,917 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0681) Prec@1 89.000 (89.750) Prec@5 99.000 (99.000) +2022-11-14 16:08:37,929 Test: [4/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0737) Prec@1 84.000 (88.600) Prec@5 100.000 (99.200) +2022-11-14 16:08:37,940 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0312 (0.0666) Prec@1 95.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 16:08:37,950 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0672) Prec@1 90.000 (89.714) Prec@5 100.000 (99.429) +2022-11-14 16:08:37,962 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0719) Prec@1 80.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:08:37,974 Test: [8/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0735) Prec@1 87.000 (88.333) Prec@5 98.000 (99.333) +2022-11-14 16:08:37,985 Test: [9/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0737) Prec@1 87.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 16:08:37,996 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0740) Prec@1 87.000 (88.091) Prec@5 100.000 (99.364) +2022-11-14 16:08:38,007 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0741) Prec@1 88.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 16:08:38,018 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0745) Prec@1 89.000 (88.154) Prec@5 100.000 (99.462) +2022-11-14 16:08:38,028 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0742) Prec@1 90.000 (88.286) Prec@5 99.000 (99.429) +2022-11-14 16:08:38,039 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0747) Prec@1 88.000 (88.267) Prec@5 100.000 (99.467) +2022-11-14 16:08:38,050 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0760) Prec@1 85.000 (88.062) Prec@5 100.000 (99.500) +2022-11-14 16:08:38,063 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0755) Prec@1 89.000 (88.118) Prec@5 98.000 (99.412) +2022-11-14 16:08:38,075 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0769) Prec@1 86.000 (88.000) Prec@5 99.000 (99.389) +2022-11-14 16:08:38,086 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0761) Prec@1 88.000 (88.000) Prec@5 99.000 (99.368) +2022-11-14 16:08:38,097 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0768) Prec@1 85.000 (87.850) Prec@5 98.000 (99.300) +2022-11-14 16:08:38,108 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0770) Prec@1 87.000 (87.810) Prec@5 98.000 (99.238) +2022-11-14 16:08:38,118 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0776) Prec@1 85.000 (87.682) Prec@5 100.000 (99.273) +2022-11-14 16:08:38,131 Test: [22/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0779) Prec@1 86.000 (87.609) Prec@5 99.000 (99.261) +2022-11-14 16:08:38,143 Test: [23/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0784) Prec@1 84.000 (87.458) Prec@5 100.000 (99.292) +2022-11-14 16:08:38,155 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0786) Prec@1 85.000 (87.360) Prec@5 99.000 (99.280) +2022-11-14 16:08:38,165 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0792) Prec@1 86.000 (87.308) Prec@5 99.000 (99.269) +2022-11-14 16:08:38,179 Test: [26/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0355 (0.0776) Prec@1 94.000 (87.556) Prec@5 100.000 (99.296) +2022-11-14 16:08:38,192 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0747 (0.0775) Prec@1 89.000 (87.607) Prec@5 100.000 (99.321) +2022-11-14 16:08:38,201 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0775) Prec@1 85.000 (87.517) Prec@5 99.000 (99.310) +2022-11-14 16:08:38,211 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0777) Prec@1 87.000 (87.500) Prec@5 99.000 (99.300) +2022-11-14 16:08:38,225 Test: [30/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0776) Prec@1 86.000 (87.452) Prec@5 100.000 (99.323) +2022-11-14 16:08:38,237 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0776) Prec@1 87.000 (87.438) Prec@5 100.000 (99.344) +2022-11-14 16:08:38,248 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0776) Prec@1 85.000 (87.364) Prec@5 100.000 (99.364) +2022-11-14 16:08:38,258 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0760 (0.0776) Prec@1 88.000 (87.382) Prec@5 100.000 (99.382) +2022-11-14 16:08:38,272 Test: [34/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0776) Prec@1 86.000 (87.343) Prec@5 97.000 (99.314) +2022-11-14 16:08:38,285 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0772) Prec@1 91.000 (87.444) Prec@5 100.000 (99.333) +2022-11-14 16:08:38,295 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0555 (0.0766) Prec@1 92.000 (87.568) Prec@5 99.000 (99.324) +2022-11-14 16:08:38,305 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.0772) Prec@1 84.000 (87.474) Prec@5 98.000 (99.289) +2022-11-14 16:08:38,318 Test: [38/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0487 (0.0765) Prec@1 94.000 (87.641) Prec@5 100.000 (99.308) +2022-11-14 16:08:38,330 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0766) Prec@1 86.000 (87.600) Prec@5 100.000 (99.325) +2022-11-14 16:08:38,340 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.0772) Prec@1 84.000 (87.512) Prec@5 97.000 (99.268) +2022-11-14 16:08:38,351 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0630 (0.0769) Prec@1 92.000 (87.619) Prec@5 99.000 (99.262) +2022-11-14 16:08:38,361 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0765) Prec@1 91.000 (87.698) Prec@5 98.000 (99.233) +2022-11-14 16:08:38,372 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0764) Prec@1 88.000 (87.705) Prec@5 99.000 (99.227) +2022-11-14 16:08:38,383 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0758) Prec@1 91.000 (87.778) Prec@5 99.000 (99.222) +2022-11-14 16:08:38,395 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0763) Prec@1 85.000 (87.717) Prec@5 100.000 (99.239) +2022-11-14 16:08:38,406 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0762) Prec@1 89.000 (87.745) Prec@5 99.000 (99.234) +2022-11-14 16:08:38,417 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0767) Prec@1 86.000 (87.708) Prec@5 99.000 (99.229) +2022-11-14 16:08:38,428 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0761) Prec@1 92.000 (87.796) Prec@5 100.000 (99.245) +2022-11-14 16:08:38,438 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1219 (0.0770) Prec@1 80.000 (87.640) Prec@5 99.000 (99.240) +2022-11-14 16:08:38,448 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0773) Prec@1 83.000 (87.549) Prec@5 100.000 (99.255) +2022-11-14 16:08:38,459 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0772) Prec@1 88.000 (87.558) Prec@5 99.000 (99.250) +2022-11-14 16:08:38,470 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0775) Prec@1 82.000 (87.453) Prec@5 99.000 (99.245) +2022-11-14 16:08:38,480 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0775) Prec@1 87.000 (87.444) Prec@5 100.000 (99.259) +2022-11-14 16:08:38,492 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0779) Prec@1 83.000 (87.364) Prec@5 100.000 (99.273) +2022-11-14 16:08:38,502 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0781) Prec@1 86.000 (87.339) Prec@5 98.000 (99.250) +2022-11-14 16:08:38,513 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0778) Prec@1 88.000 (87.351) Prec@5 100.000 (99.263) +2022-11-14 16:08:38,524 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0778) Prec@1 90.000 (87.397) Prec@5 98.000 (99.241) +2022-11-14 16:08:38,534 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0780) Prec@1 84.000 (87.339) Prec@5 99.000 (99.237) +2022-11-14 16:08:38,544 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0783) Prec@1 86.000 (87.317) Prec@5 100.000 (99.250) +2022-11-14 16:08:38,553 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0785) Prec@1 88.000 (87.328) Prec@5 99.000 (99.246) +2022-11-14 16:08:38,563 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0783) Prec@1 88.000 (87.339) Prec@5 100.000 (99.258) +2022-11-14 16:08:38,573 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0785) Prec@1 85.000 (87.302) Prec@5 100.000 (99.270) +2022-11-14 16:08:38,584 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0779) Prec@1 92.000 (87.375) Prec@5 100.000 (99.281) +2022-11-14 16:08:38,595 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0777) Prec@1 90.000 (87.415) Prec@5 100.000 (99.292) +2022-11-14 16:08:38,604 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0779) Prec@1 87.000 (87.409) Prec@5 99.000 (99.288) +2022-11-14 16:08:38,615 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0368 (0.0772) Prec@1 95.000 (87.522) Prec@5 100.000 (99.299) +2022-11-14 16:08:38,625 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0773) Prec@1 88.000 (87.529) Prec@5 99.000 (99.294) +2022-11-14 16:08:38,636 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0770) Prec@1 89.000 (87.551) Prec@5 99.000 (99.290) +2022-11-14 16:08:38,646 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0769) Prec@1 88.000 (87.557) Prec@5 99.000 (99.286) +2022-11-14 16:08:38,657 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0771) Prec@1 87.000 (87.549) Prec@5 99.000 (99.282) +2022-11-14 16:08:38,667 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0771) Prec@1 86.000 (87.528) Prec@5 100.000 (99.292) +2022-11-14 16:08:38,678 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0769) Prec@1 89.000 (87.548) Prec@5 99.000 (99.288) +2022-11-14 16:08:38,689 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0767) Prec@1 91.000 (87.595) Prec@5 100.000 (99.297) +2022-11-14 16:08:38,700 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0768) Prec@1 87.000 (87.587) Prec@5 100.000 (99.307) +2022-11-14 16:08:38,711 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0766) Prec@1 90.000 (87.618) Prec@5 100.000 (99.316) +2022-11-14 16:08:38,721 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0764) Prec@1 89.000 (87.636) Prec@5 99.000 (99.312) +2022-11-14 16:08:38,731 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0766) Prec@1 84.000 (87.590) Prec@5 99.000 (99.308) +2022-11-14 16:08:38,743 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0767) Prec@1 86.000 (87.570) Prec@5 100.000 (99.316) +2022-11-14 16:08:38,753 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0770) Prec@1 84.000 (87.525) Prec@5 98.000 (99.300) +2022-11-14 16:08:38,764 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0770) Prec@1 88.000 (87.531) Prec@5 99.000 (99.296) +2022-11-14 16:08:38,774 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0770) Prec@1 86.000 (87.512) Prec@5 100.000 (99.305) +2022-11-14 16:08:38,785 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0771) Prec@1 88.000 (87.518) Prec@5 99.000 (99.301) +2022-11-14 16:08:38,797 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0769) Prec@1 89.000 (87.536) Prec@5 100.000 (99.310) +2022-11-14 16:08:38,808 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0773) Prec@1 81.000 (87.459) Prec@5 99.000 (99.306) +2022-11-14 16:08:38,818 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1221 (0.0778) Prec@1 83.000 (87.407) Prec@5 100.000 (99.314) +2022-11-14 16:08:38,828 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0779) Prec@1 86.000 (87.391) Prec@5 100.000 (99.322) +2022-11-14 16:08:38,839 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0779) Prec@1 85.000 (87.364) Prec@5 99.000 (99.318) +2022-11-14 16:08:38,850 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0779) Prec@1 88.000 (87.371) Prec@5 100.000 (99.326) +2022-11-14 16:08:38,861 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0777) Prec@1 91.000 (87.411) Prec@5 98.000 (99.311) +2022-11-14 16:08:38,871 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0776) Prec@1 88.000 (87.418) Prec@5 100.000 (99.319) +2022-11-14 16:08:38,882 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0775) Prec@1 90.000 (87.446) Prec@5 100.000 (99.326) +2022-11-14 16:08:38,892 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0778) Prec@1 85.000 (87.419) Prec@5 99.000 (99.323) +2022-11-14 16:08:38,903 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0777) Prec@1 88.000 (87.426) Prec@5 99.000 (99.319) +2022-11-14 16:08:38,917 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0779) Prec@1 85.000 (87.400) Prec@5 100.000 (99.326) +2022-11-14 16:08:38,932 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0778) Prec@1 89.000 (87.417) Prec@5 100.000 (99.333) +2022-11-14 16:08:38,949 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0466 (0.0775) Prec@1 90.000 (87.443) Prec@5 99.000 (99.330) +2022-11-14 16:08:38,964 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0777) Prec@1 85.000 (87.418) Prec@5 100.000 (99.337) +2022-11-14 16:08:38,981 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1128 (0.0780) Prec@1 82.000 (87.364) Prec@5 98.000 (99.323) +2022-11-14 16:08:39,000 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0779) Prec@1 90.000 (87.390) Prec@5 99.000 (99.320) +2022-11-14 16:08:39,060 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:08:39,407 Epoch: [308][0/500] Time 0.023 (0.023) Data 0.258 (0.258) Loss 0.0213 (0.0213) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:39,901 Epoch: [308][10/500] Time 0.050 (0.042) Data 0.002 (0.025) Loss 0.0344 (0.0278) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:08:40,495 Epoch: [308][20/500] Time 0.060 (0.048) Data 0.002 (0.014) Loss 0.0094 (0.0217) Prec@1 99.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:08:41,071 Epoch: [308][30/500] Time 0.056 (0.049) Data 0.002 (0.010) Loss 0.0416 (0.0267) Prec@1 93.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:08:41,650 Epoch: [308][40/500] Time 0.050 (0.050) Data 0.002 (0.008) Loss 0.0164 (0.0246) Prec@1 99.000 (96.000) Prec@5 99.000 (99.800) +2022-11-14 16:08:42,226 Epoch: [308][50/500] Time 0.056 (0.050) Data 0.002 (0.007) Loss 0.0317 (0.0258) Prec@1 96.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:08:42,803 Epoch: [308][60/500] Time 0.052 (0.050) Data 0.002 (0.006) Loss 0.0353 (0.0272) Prec@1 96.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 16:08:43,385 Epoch: [308][70/500] Time 0.061 (0.050) Data 0.002 (0.006) Loss 0.0667 (0.0321) Prec@1 89.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:08:43,954 Epoch: [308][80/500] Time 0.057 (0.051) Data 0.002 (0.005) Loss 0.0520 (0.0343) Prec@1 93.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 16:08:44,542 Epoch: [308][90/500] Time 0.053 (0.051) Data 0.002 (0.005) Loss 0.0223 (0.0331) Prec@1 96.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 16:08:45,099 Epoch: [308][100/500] Time 0.053 (0.051) Data 0.002 (0.005) Loss 0.0397 (0.0337) Prec@1 94.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 16:08:45,666 Epoch: [308][110/500] Time 0.055 (0.051) Data 0.002 (0.004) Loss 0.0248 (0.0330) Prec@1 96.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 16:08:46,228 Epoch: [308][120/500] Time 0.055 (0.051) Data 0.002 (0.004) Loss 0.0212 (0.0321) Prec@1 98.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 16:08:46,785 Epoch: [308][130/500] Time 0.054 (0.051) Data 0.002 (0.004) Loss 0.0478 (0.0332) Prec@1 94.000 (95.143) Prec@5 100.000 (99.929) +2022-11-14 16:08:47,343 Epoch: [308][140/500] Time 0.056 (0.050) Data 0.002 (0.004) Loss 0.0298 (0.0330) Prec@1 94.000 (95.067) Prec@5 100.000 (99.933) +2022-11-14 16:08:47,919 Epoch: [308][150/500] Time 0.064 (0.051) Data 0.002 (0.004) Loss 0.0274 (0.0326) Prec@1 95.000 (95.062) Prec@5 100.000 (99.938) +2022-11-14 16:08:48,483 Epoch: [308][160/500] Time 0.060 (0.051) Data 0.002 (0.004) Loss 0.0363 (0.0328) Prec@1 94.000 (95.000) Prec@5 100.000 (99.941) +2022-11-14 16:08:49,040 Epoch: [308][170/500] Time 0.054 (0.050) Data 0.002 (0.004) Loss 0.0359 (0.0330) Prec@1 93.000 (94.889) Prec@5 100.000 (99.944) +2022-11-14 16:08:49,618 Epoch: [308][180/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0223 (0.0324) Prec@1 96.000 (94.947) Prec@5 100.000 (99.947) +2022-11-14 16:08:50,182 Epoch: [308][190/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0382 (0.0327) Prec@1 95.000 (94.950) Prec@5 100.000 (99.950) +2022-11-14 16:08:50,750 Epoch: [308][200/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0335 (0.0328) Prec@1 96.000 (95.000) Prec@5 100.000 (99.952) +2022-11-14 16:08:51,309 Epoch: [308][210/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0200 (0.0322) Prec@1 98.000 (95.136) Prec@5 100.000 (99.955) +2022-11-14 16:08:51,868 Epoch: [308][220/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0416 (0.0326) Prec@1 94.000 (95.087) Prec@5 100.000 (99.957) +2022-11-14 16:08:52,437 Epoch: [308][230/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0430 (0.0330) Prec@1 92.000 (94.958) Prec@5 99.000 (99.917) +2022-11-14 16:08:53,011 Epoch: [308][240/500] Time 0.062 (0.051) Data 0.002 (0.003) Loss 0.0344 (0.0331) Prec@1 94.000 (94.920) Prec@5 100.000 (99.920) +2022-11-14 16:08:53,576 Epoch: [308][250/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0288 (0.0329) Prec@1 93.000 (94.846) Prec@5 99.000 (99.885) +2022-11-14 16:08:54,142 Epoch: [308][260/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0293 (0.0328) Prec@1 96.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 16:08:54,720 Epoch: [308][270/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0624 (0.0338) Prec@1 88.000 (94.643) Prec@5 100.000 (99.893) +2022-11-14 16:08:55,276 Epoch: [308][280/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0445 (0.0342) Prec@1 93.000 (94.586) Prec@5 100.000 (99.897) +2022-11-14 16:08:55,834 Epoch: [308][290/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0202 (0.0337) Prec@1 97.000 (94.667) Prec@5 100.000 (99.900) +2022-11-14 16:08:56,407 Epoch: [308][300/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0253 (0.0335) Prec@1 96.000 (94.710) Prec@5 99.000 (99.871) +2022-11-14 16:08:56,965 Epoch: [308][310/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0500 (0.0340) Prec@1 95.000 (94.719) Prec@5 100.000 (99.875) +2022-11-14 16:08:57,538 Epoch: [308][320/500] Time 0.045 (0.050) Data 0.003 (0.003) Loss 0.0246 (0.0337) Prec@1 96.000 (94.758) Prec@5 100.000 (99.879) +2022-11-14 16:08:58,115 Epoch: [308][330/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0250 (0.0334) Prec@1 98.000 (94.853) Prec@5 100.000 (99.882) +2022-11-14 16:08:58,672 Epoch: [308][340/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0309 (0.0334) Prec@1 95.000 (94.857) Prec@5 100.000 (99.886) +2022-11-14 16:08:59,251 Epoch: [308][350/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0375 (0.0335) Prec@1 93.000 (94.806) Prec@5 99.000 (99.861) +2022-11-14 16:08:59,833 Epoch: [308][360/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0303 (0.0334) Prec@1 95.000 (94.811) Prec@5 100.000 (99.865) +2022-11-14 16:09:00,403 Epoch: [308][370/500] Time 0.062 (0.051) Data 0.003 (0.003) Loss 0.0280 (0.0333) Prec@1 96.000 (94.842) Prec@5 100.000 (99.868) +2022-11-14 16:09:00,975 Epoch: [308][380/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0388 (0.0334) Prec@1 95.000 (94.846) Prec@5 100.000 (99.872) +2022-11-14 16:09:01,544 Epoch: [308][390/500] Time 0.047 (0.051) Data 0.003 (0.003) Loss 0.0362 (0.0335) Prec@1 95.000 (94.850) Prec@5 100.000 (99.875) +2022-11-14 16:09:02,096 Epoch: [308][400/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0240 (0.0332) Prec@1 96.000 (94.878) Prec@5 100.000 (99.878) +2022-11-14 16:09:02,657 Epoch: [308][410/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0275 (0.0331) Prec@1 96.000 (94.905) Prec@5 100.000 (99.881) +2022-11-14 16:09:03,213 Epoch: [308][420/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0200 (0.0328) Prec@1 98.000 (94.977) Prec@5 100.000 (99.884) +2022-11-14 16:09:03,793 Epoch: [308][430/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0310 (0.0328) Prec@1 94.000 (94.955) Prec@5 100.000 (99.886) +2022-11-14 16:09:04,364 Epoch: [308][440/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0292 (0.0327) Prec@1 95.000 (94.956) Prec@5 100.000 (99.889) +2022-11-14 16:09:04,951 Epoch: [308][450/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0359 (0.0327) Prec@1 94.000 (94.935) Prec@5 98.000 (99.848) +2022-11-14 16:09:05,521 Epoch: [308][460/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0351 (0.0328) Prec@1 94.000 (94.915) Prec@5 100.000 (99.851) +2022-11-14 16:09:06,099 Epoch: [308][470/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0249 (0.0326) Prec@1 97.000 (94.958) Prec@5 100.000 (99.854) +2022-11-14 16:09:06,681 Epoch: [308][480/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0422 (0.0328) Prec@1 93.000 (94.918) Prec@5 99.000 (99.837) +2022-11-14 16:09:07,243 Epoch: [308][490/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0280 (0.0327) Prec@1 97.000 (94.960) Prec@5 100.000 (99.840) +2022-11-14 16:09:07,768 Epoch: [308][499/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0395 (0.0329) Prec@1 92.000 (94.902) Prec@5 99.000 (99.824) +2022-11-14 16:09:08,087 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0712 (0.0712) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:09:08,097 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0639) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:09:08,108 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0697) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:09:08,121 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0772) Prec@1 85.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 16:09:08,130 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0779) Prec@1 86.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 16:09:08,139 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0745) Prec@1 91.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 16:09:08,148 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0612 (0.0726) Prec@1 91.000 (88.571) Prec@5 100.000 (99.571) +2022-11-14 16:09:08,160 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0737) Prec@1 85.000 (88.125) Prec@5 99.000 (99.500) +2022-11-14 16:09:08,170 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0745) Prec@1 89.000 (88.222) Prec@5 100.000 (99.556) +2022-11-14 16:09:08,179 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0741) Prec@1 89.000 (88.300) Prec@5 99.000 (99.500) +2022-11-14 16:09:08,190 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0725) Prec@1 89.000 (88.364) Prec@5 100.000 (99.545) +2022-11-14 16:09:08,200 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0743) Prec@1 85.000 (88.083) Prec@5 99.000 (99.500) +2022-11-14 16:09:08,212 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0727) Prec@1 90.000 (88.231) Prec@5 98.000 (99.385) +2022-11-14 16:09:08,222 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0738) Prec@1 87.000 (88.143) Prec@5 98.000 (99.286) +2022-11-14 16:09:08,232 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0736) Prec@1 88.000 (88.133) Prec@5 98.000 (99.200) +2022-11-14 16:09:08,242 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0736) Prec@1 88.000 (88.125) Prec@5 99.000 (99.188) +2022-11-14 16:09:08,253 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0734) Prec@1 89.000 (88.176) Prec@5 98.000 (99.118) +2022-11-14 16:09:08,263 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1074 (0.0753) Prec@1 81.000 (87.778) Prec@5 100.000 (99.167) +2022-11-14 16:09:08,274 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0746) Prec@1 89.000 (87.842) Prec@5 100.000 (99.211) +2022-11-14 16:09:08,284 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0755) Prec@1 85.000 (87.700) Prec@5 98.000 (99.150) +2022-11-14 16:09:08,294 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0746) Prec@1 90.000 (87.810) Prec@5 100.000 (99.190) +2022-11-14 16:09:08,303 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0748) Prec@1 87.000 (87.773) Prec@5 97.000 (99.091) +2022-11-14 16:09:08,314 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0756) Prec@1 85.000 (87.652) Prec@5 99.000 (99.087) +2022-11-14 16:09:08,324 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0754) Prec@1 88.000 (87.667) Prec@5 100.000 (99.125) +2022-11-14 16:09:08,335 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0761) Prec@1 86.000 (87.600) Prec@5 100.000 (99.160) +2022-11-14 16:09:08,346 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0761) Prec@1 87.000 (87.577) Prec@5 99.000 (99.154) +2022-11-14 16:09:08,357 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0753) Prec@1 90.000 (87.667) Prec@5 100.000 (99.185) +2022-11-14 16:09:08,368 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0751) Prec@1 89.000 (87.714) Prec@5 100.000 (99.214) +2022-11-14 16:09:08,380 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0754) Prec@1 86.000 (87.655) Prec@5 98.000 (99.172) +2022-11-14 16:09:08,392 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0752) Prec@1 90.000 (87.733) Prec@5 96.000 (99.067) +2022-11-14 16:09:08,402 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0747) Prec@1 91.000 (87.839) Prec@5 100.000 (99.097) +2022-11-14 16:09:08,414 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0746) Prec@1 89.000 (87.875) Prec@5 99.000 (99.094) +2022-11-14 16:09:08,424 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0747) Prec@1 86.000 (87.818) Prec@5 100.000 (99.121) +2022-11-14 16:09:08,434 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0757) Prec@1 82.000 (87.647) Prec@5 100.000 (99.147) +2022-11-14 16:09:08,443 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0754) Prec@1 91.000 (87.743) Prec@5 98.000 (99.114) +2022-11-14 16:09:08,453 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0751) Prec@1 92.000 (87.861) Prec@5 100.000 (99.139) +2022-11-14 16:09:08,464 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0751) Prec@1 86.000 (87.811) Prec@5 97.000 (99.081) +2022-11-14 16:09:08,475 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1154 (0.0761) Prec@1 81.000 (87.632) Prec@5 98.000 (99.053) +2022-11-14 16:09:08,485 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0758) Prec@1 91.000 (87.718) Prec@5 99.000 (99.051) +2022-11-14 16:09:08,497 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0756) Prec@1 89.000 (87.750) Prec@5 100.000 (99.075) +2022-11-14 16:09:08,508 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0758) Prec@1 87.000 (87.732) Prec@5 100.000 (99.098) +2022-11-14 16:09:08,521 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0756) Prec@1 89.000 (87.762) Prec@5 98.000 (99.071) +2022-11-14 16:09:08,534 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0750) Prec@1 91.000 (87.837) Prec@5 100.000 (99.093) +2022-11-14 16:09:08,545 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0752) Prec@1 89.000 (87.864) Prec@5 99.000 (99.091) +2022-11-14 16:09:08,556 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0747) Prec@1 92.000 (87.956) Prec@5 99.000 (99.089) +2022-11-14 16:09:08,567 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0751) Prec@1 85.000 (87.891) Prec@5 100.000 (99.109) +2022-11-14 16:09:08,578 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0749) Prec@1 89.000 (87.915) Prec@5 99.000 (99.106) +2022-11-14 16:09:08,589 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0752) Prec@1 87.000 (87.896) Prec@5 99.000 (99.104) +2022-11-14 16:09:08,601 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0747) Prec@1 91.000 (87.959) Prec@5 99.000 (99.102) +2022-11-14 16:09:08,612 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1227 (0.0757) Prec@1 82.000 (87.840) Prec@5 99.000 (99.100) +2022-11-14 16:09:08,623 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0757) Prec@1 89.000 (87.863) Prec@5 100.000 (99.118) +2022-11-14 16:09:08,634 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0759) Prec@1 86.000 (87.827) Prec@5 98.000 (99.096) +2022-11-14 16:09:08,645 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0760) Prec@1 87.000 (87.811) Prec@5 100.000 (99.113) +2022-11-14 16:09:08,657 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0757) Prec@1 89.000 (87.833) Prec@5 100.000 (99.130) +2022-11-14 16:09:08,669 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0760) Prec@1 83.000 (87.745) Prec@5 100.000 (99.145) +2022-11-14 16:09:08,680 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0761) Prec@1 88.000 (87.750) Prec@5 99.000 (99.143) +2022-11-14 16:09:08,691 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0759) Prec@1 88.000 (87.754) Prec@5 100.000 (99.158) +2022-11-14 16:09:08,702 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0760) Prec@1 87.000 (87.741) Prec@5 99.000 (99.155) +2022-11-14 16:09:08,715 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0761) Prec@1 88.000 (87.746) Prec@5 100.000 (99.169) +2022-11-14 16:09:08,727 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0761) Prec@1 88.000 (87.750) Prec@5 99.000 (99.167) +2022-11-14 16:09:08,738 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0762) Prec@1 86.000 (87.721) Prec@5 99.000 (99.164) +2022-11-14 16:09:08,750 Test: [61/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0759) Prec@1 91.000 (87.774) Prec@5 98.000 (99.145) +2022-11-14 16:09:08,763 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0759) Prec@1 88.000 (87.778) Prec@5 100.000 (99.159) +2022-11-14 16:09:08,775 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0757) Prec@1 88.000 (87.781) Prec@5 100.000 (99.172) +2022-11-14 16:09:08,786 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0760) Prec@1 86.000 (87.754) Prec@5 99.000 (99.169) +2022-11-14 16:09:08,798 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0761) Prec@1 85.000 (87.712) Prec@5 99.000 (99.167) +2022-11-14 16:09:08,809 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0310 (0.0754) Prec@1 94.000 (87.806) Prec@5 100.000 (99.179) +2022-11-14 16:09:08,820 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0753) Prec@1 91.000 (87.853) Prec@5 98.000 (99.162) +2022-11-14 16:09:08,830 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0441 (0.0749) Prec@1 91.000 (87.899) Prec@5 100.000 (99.174) +2022-11-14 16:09:08,842 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0752) Prec@1 86.000 (87.871) Prec@5 100.000 (99.186) +2022-11-14 16:09:08,855 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0757) Prec@1 86.000 (87.845) Prec@5 97.000 (99.155) +2022-11-14 16:09:08,866 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0756) Prec@1 86.000 (87.819) Prec@5 98.000 (99.139) +2022-11-14 16:09:08,875 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0439 (0.0752) Prec@1 94.000 (87.904) Prec@5 100.000 (99.151) +2022-11-14 16:09:08,886 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0748) Prec@1 94.000 (87.986) Prec@5 100.000 (99.162) +2022-11-14 16:09:08,897 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0748) Prec@1 89.000 (88.000) Prec@5 100.000 (99.173) +2022-11-14 16:09:08,909 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0745) Prec@1 90.000 (88.026) Prec@5 98.000 (99.158) +2022-11-14 16:09:08,920 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0744) Prec@1 88.000 (88.026) Prec@5 99.000 (99.156) +2022-11-14 16:09:08,931 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1098 (0.0749) Prec@1 83.000 (87.962) Prec@5 96.000 (99.115) +2022-11-14 16:09:08,943 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0746) Prec@1 90.000 (87.987) Prec@5 100.000 (99.127) +2022-11-14 16:09:08,954 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0746) Prec@1 88.000 (87.987) Prec@5 100.000 (99.138) +2022-11-14 16:09:08,965 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0748) Prec@1 85.000 (87.951) Prec@5 99.000 (99.136) +2022-11-14 16:09:08,977 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1092 (0.0752) Prec@1 83.000 (87.890) Prec@5 99.000 (99.134) +2022-11-14 16:09:08,991 Test: [82/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0753) Prec@1 86.000 (87.867) Prec@5 100.000 (99.145) +2022-11-14 16:09:09,006 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0753) Prec@1 91.000 (87.905) Prec@5 99.000 (99.143) +2022-11-14 16:09:09,018 Test: [84/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0756) Prec@1 85.000 (87.871) Prec@5 99.000 (99.141) +2022-11-14 16:09:09,029 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1115 (0.0761) Prec@1 84.000 (87.826) Prec@5 100.000 (99.151) +2022-11-14 16:09:09,040 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0760) Prec@1 88.000 (87.828) Prec@5 100.000 (99.161) +2022-11-14 16:09:09,052 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0761) Prec@1 88.000 (87.830) Prec@5 99.000 (99.159) +2022-11-14 16:09:09,063 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0759) Prec@1 91.000 (87.865) Prec@5 100.000 (99.169) +2022-11-14 16:09:09,074 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0757) Prec@1 91.000 (87.900) Prec@5 100.000 (99.178) +2022-11-14 16:09:09,084 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0754) Prec@1 93.000 (87.956) Prec@5 100.000 (99.187) +2022-11-14 16:09:09,094 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0752) Prec@1 89.000 (87.967) Prec@5 99.000 (99.185) +2022-11-14 16:09:09,106 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0754) Prec@1 83.000 (87.914) Prec@5 99.000 (99.183) +2022-11-14 16:09:09,118 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0753) Prec@1 89.000 (87.926) Prec@5 99.000 (99.181) +2022-11-14 16:09:09,129 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0754) Prec@1 86.000 (87.905) Prec@5 99.000 (99.179) +2022-11-14 16:09:09,140 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0753) Prec@1 90.000 (87.927) Prec@5 98.000 (99.167) +2022-11-14 16:09:09,151 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0751) Prec@1 91.000 (87.959) Prec@5 98.000 (99.155) +2022-11-14 16:09:09,163 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0755) Prec@1 82.000 (87.898) Prec@5 99.000 (99.153) +2022-11-14 16:09:09,175 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1078 (0.0758) Prec@1 84.000 (87.859) Prec@5 99.000 (99.152) +2022-11-14 16:09:09,186 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0759) Prec@1 87.000 (87.850) Prec@5 99.000 (99.150) +2022-11-14 16:09:09,252 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:09:09,607 Epoch: [309][0/500] Time 0.027 (0.027) Data 0.262 (0.262) Loss 0.0318 (0.0318) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:09:09,874 Epoch: [309][10/500] Time 0.028 (0.024) Data 0.002 (0.026) Loss 0.0244 (0.0281) Prec@1 96.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 16:09:10,150 Epoch: [309][20/500] Time 0.022 (0.025) Data 0.002 (0.014) Loss 0.0155 (0.0239) Prec@1 98.000 (96.333) Prec@5 100.000 (99.667) +2022-11-14 16:09:10,542 Epoch: [309][30/500] Time 0.046 (0.027) Data 0.002 (0.010) Loss 0.0365 (0.0270) Prec@1 95.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 16:09:11,153 Epoch: [309][40/500] Time 0.072 (0.034) Data 0.002 (0.009) Loss 0.0642 (0.0345) Prec@1 89.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 16:09:11,734 Epoch: [309][50/500] Time 0.052 (0.037) Data 0.002 (0.007) Loss 0.0284 (0.0335) Prec@1 96.000 (94.833) Prec@5 99.000 (99.667) +2022-11-14 16:09:12,280 Epoch: [309][60/500] Time 0.055 (0.039) Data 0.002 (0.006) Loss 0.0230 (0.0320) Prec@1 98.000 (95.286) Prec@5 100.000 (99.714) +2022-11-14 16:09:12,808 Epoch: [309][70/500] Time 0.055 (0.041) Data 0.002 (0.006) Loss 0.0296 (0.0317) Prec@1 96.000 (95.375) Prec@5 100.000 (99.750) +2022-11-14 16:09:13,362 Epoch: [309][80/500] Time 0.056 (0.042) Data 0.002 (0.005) Loss 0.0384 (0.0324) Prec@1 94.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 16:09:13,913 Epoch: [309][90/500] Time 0.059 (0.043) Data 0.002 (0.005) Loss 0.0386 (0.0330) Prec@1 93.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 16:09:14,465 Epoch: [309][100/500] Time 0.057 (0.043) Data 0.002 (0.005) Loss 0.0484 (0.0344) Prec@1 92.000 (94.727) Prec@5 100.000 (99.818) +2022-11-14 16:09:15,029 Epoch: [309][110/500] Time 0.046 (0.044) Data 0.002 (0.004) Loss 0.0227 (0.0335) Prec@1 97.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 16:09:15,572 Epoch: [309][120/500] Time 0.057 (0.044) Data 0.002 (0.004) Loss 0.0254 (0.0328) Prec@1 96.000 (95.000) Prec@5 100.000 (99.846) +2022-11-14 16:09:16,145 Epoch: [309][130/500] Time 0.050 (0.045) Data 0.002 (0.004) Loss 0.0211 (0.0320) Prec@1 97.000 (95.143) Prec@5 99.000 (99.786) +2022-11-14 16:09:16,681 Epoch: [309][140/500] Time 0.052 (0.045) Data 0.002 (0.004) Loss 0.0291 (0.0318) Prec@1 95.000 (95.133) Prec@5 100.000 (99.800) +2022-11-14 16:09:17,243 Epoch: [309][150/500] Time 0.052 (0.045) Data 0.002 (0.004) Loss 0.0287 (0.0316) Prec@1 95.000 (95.125) Prec@5 100.000 (99.812) +2022-11-14 16:09:17,799 Epoch: [309][160/500] Time 0.053 (0.046) Data 0.002 (0.004) Loss 0.0280 (0.0314) Prec@1 95.000 (95.118) Prec@5 100.000 (99.824) +2022-11-14 16:09:18,354 Epoch: [309][170/500] Time 0.046 (0.046) Data 0.002 (0.004) Loss 0.0443 (0.0321) Prec@1 93.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:09:18,906 Epoch: [309][180/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0281 (0.0319) Prec@1 96.000 (95.053) Prec@5 100.000 (99.842) +2022-11-14 16:09:19,482 Epoch: [309][190/500] Time 0.053 (0.046) Data 0.003 (0.003) Loss 0.0186 (0.0312) Prec@1 98.000 (95.200) Prec@5 100.000 (99.850) +2022-11-14 16:09:20,037 Epoch: [309][200/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0345 (0.0314) Prec@1 95.000 (95.190) Prec@5 100.000 (99.857) +2022-11-14 16:09:20,608 Epoch: [309][210/500] Time 0.063 (0.047) Data 0.002 (0.003) Loss 0.0307 (0.0314) Prec@1 97.000 (95.273) Prec@5 100.000 (99.864) +2022-11-14 16:09:21,167 Epoch: [309][220/500] Time 0.056 (0.047) Data 0.003 (0.003) Loss 0.0209 (0.0309) Prec@1 97.000 (95.348) Prec@5 100.000 (99.870) +2022-11-14 16:09:21,707 Epoch: [309][230/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0444 (0.0315) Prec@1 94.000 (95.292) Prec@5 100.000 (99.875) +2022-11-14 16:09:22,264 Epoch: [309][240/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0402 (0.0318) Prec@1 91.000 (95.120) Prec@5 100.000 (99.880) +2022-11-14 16:09:22,812 Epoch: [309][250/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0446 (0.0323) Prec@1 94.000 (95.077) Prec@5 99.000 (99.846) +2022-11-14 16:09:23,369 Epoch: [309][260/500] Time 0.061 (0.047) Data 0.002 (0.003) Loss 0.0183 (0.0318) Prec@1 97.000 (95.148) Prec@5 100.000 (99.852) +2022-11-14 16:09:23,923 Epoch: [309][270/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0281 (0.0316) Prec@1 96.000 (95.179) Prec@5 100.000 (99.857) +2022-11-14 16:09:24,468 Epoch: [309][280/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0291 (0.0316) Prec@1 96.000 (95.207) Prec@5 100.000 (99.862) +2022-11-14 16:09:25,015 Epoch: [309][290/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0444 (0.0320) Prec@1 93.000 (95.133) Prec@5 100.000 (99.867) +2022-11-14 16:09:25,583 Epoch: [309][300/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0172 (0.0315) Prec@1 97.000 (95.194) Prec@5 100.000 (99.871) +2022-11-14 16:09:26,150 Epoch: [309][310/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0381 (0.0317) Prec@1 93.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:09:26,702 Epoch: [309][320/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0191 (0.0313) Prec@1 97.000 (95.182) Prec@5 99.000 (99.848) +2022-11-14 16:09:27,242 Epoch: [309][330/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0325 (0.0314) Prec@1 96.000 (95.206) Prec@5 100.000 (99.853) +2022-11-14 16:09:27,774 Epoch: [309][340/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0177 (0.0310) Prec@1 97.000 (95.257) Prec@5 100.000 (99.857) +2022-11-14 16:09:28,339 Epoch: [309][350/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0367 (0.0311) Prec@1 93.000 (95.194) Prec@5 100.000 (99.861) +2022-11-14 16:09:28,891 Epoch: [309][360/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0269 (0.0310) Prec@1 95.000 (95.189) Prec@5 100.000 (99.865) +2022-11-14 16:09:29,414 Epoch: [309][370/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0233 (0.0308) Prec@1 97.000 (95.237) Prec@5 100.000 (99.868) +2022-11-14 16:09:29,978 Epoch: [309][380/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0188 (0.0305) Prec@1 97.000 (95.282) Prec@5 100.000 (99.872) +2022-11-14 16:09:30,542 Epoch: [309][390/500] Time 0.053 (0.048) Data 0.002 (0.003) Loss 0.0265 (0.0304) Prec@1 97.000 (95.325) Prec@5 100.000 (99.875) +2022-11-14 16:09:31,095 Epoch: [309][400/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0478 (0.0308) Prec@1 93.000 (95.268) Prec@5 98.000 (99.829) +2022-11-14 16:09:31,648 Epoch: [309][410/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0237 (0.0307) Prec@1 96.000 (95.286) Prec@5 100.000 (99.833) +2022-11-14 16:09:32,195 Epoch: [309][420/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0394 (0.0309) Prec@1 92.000 (95.209) Prec@5 100.000 (99.837) +2022-11-14 16:09:32,753 Epoch: [309][430/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0354 (0.0310) Prec@1 95.000 (95.205) Prec@5 100.000 (99.841) +2022-11-14 16:09:33,297 Epoch: [309][440/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0206 (0.0307) Prec@1 97.000 (95.244) Prec@5 100.000 (99.844) +2022-11-14 16:09:33,838 Epoch: [309][450/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0540 (0.0312) Prec@1 89.000 (95.109) Prec@5 100.000 (99.848) +2022-11-14 16:09:34,396 Epoch: [309][460/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0253 (0.0311) Prec@1 94.000 (95.085) Prec@5 100.000 (99.851) +2022-11-14 16:09:34,957 Epoch: [309][470/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0636 (0.0318) Prec@1 87.000 (94.917) Prec@5 100.000 (99.854) +2022-11-14 16:09:35,512 Epoch: [309][480/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0270 (0.0317) Prec@1 95.000 (94.918) Prec@5 100.000 (99.857) +2022-11-14 16:09:36,069 Epoch: [309][490/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0456 (0.0320) Prec@1 92.000 (94.860) Prec@5 99.000 (99.840) +2022-11-14 16:09:36,569 Epoch: [309][499/500] Time 0.055 (0.048) Data 0.002 (0.003) Loss 0.0420 (0.0322) Prec@1 95.000 (94.863) Prec@5 100.000 (99.843) +2022-11-14 16:09:36,930 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0397 (0.0397) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:09:36,941 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0566) Prec@1 90.000 (92.000) Prec@5 100.000 (99.500) +2022-11-14 16:09:36,953 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0558 (0.0563) Prec@1 91.000 (91.667) Prec@5 100.000 (99.667) +2022-11-14 16:09:36,965 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0634 (0.0581) Prec@1 92.000 (91.750) Prec@5 98.000 (99.250) +2022-11-14 16:09:36,975 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0655 (0.0596) Prec@1 92.000 (91.800) Prec@5 99.000 (99.200) +2022-11-14 16:09:36,984 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0592) Prec@1 90.000 (91.500) Prec@5 99.000 (99.167) +2022-11-14 16:09:36,997 Test: [6/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0505 (0.0579) Prec@1 92.000 (91.571) Prec@5 100.000 (99.286) +2022-11-14 16:09:37,008 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0640) Prec@1 82.000 (90.375) Prec@5 100.000 (99.375) +2022-11-14 16:09:37,016 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0660) Prec@1 88.000 (90.111) Prec@5 99.000 (99.333) +2022-11-14 16:09:37,026 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0670) Prec@1 87.000 (89.800) Prec@5 99.000 (99.300) +2022-11-14 16:09:37,036 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0664) Prec@1 91.000 (89.909) Prec@5 99.000 (99.273) +2022-11-14 16:09:37,047 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0681) Prec@1 86.000 (89.583) Prec@5 100.000 (99.333) +2022-11-14 16:09:37,058 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0673) Prec@1 89.000 (89.538) Prec@5 100.000 (99.385) +2022-11-14 16:09:37,069 Test: [13/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0683) Prec@1 86.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 16:09:37,080 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0675) Prec@1 92.000 (89.467) Prec@5 99.000 (99.400) +2022-11-14 16:09:37,091 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0681) Prec@1 89.000 (89.438) Prec@5 99.000 (99.375) +2022-11-14 16:09:37,102 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0672) Prec@1 91.000 (89.529) Prec@5 99.000 (99.353) +2022-11-14 16:09:37,113 Test: [17/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1140 (0.0698) Prec@1 83.000 (89.167) Prec@5 100.000 (99.389) +2022-11-14 16:09:37,123 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0703) Prec@1 85.000 (88.947) Prec@5 100.000 (99.421) +2022-11-14 16:09:37,135 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0712) Prec@1 85.000 (88.750) Prec@5 97.000 (99.300) +2022-11-14 16:09:37,145 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0715) Prec@1 89.000 (88.762) Prec@5 100.000 (99.333) +2022-11-14 16:09:37,156 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0720) Prec@1 86.000 (88.636) Prec@5 98.000 (99.273) +2022-11-14 16:09:37,166 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0733) Prec@1 84.000 (88.435) Prec@5 98.000 (99.217) +2022-11-14 16:09:37,176 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0732) Prec@1 86.000 (88.333) Prec@5 100.000 (99.250) +2022-11-14 16:09:37,186 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0735) Prec@1 87.000 (88.280) Prec@5 100.000 (99.280) +2022-11-14 16:09:37,198 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0744) Prec@1 86.000 (88.192) Prec@5 98.000 (99.231) +2022-11-14 16:09:37,208 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0734) Prec@1 94.000 (88.407) Prec@5 100.000 (99.259) +2022-11-14 16:09:37,218 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0728) Prec@1 92.000 (88.536) Prec@5 100.000 (99.286) +2022-11-14 16:09:37,227 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0730) Prec@1 89.000 (88.552) Prec@5 98.000 (99.241) +2022-11-14 16:09:37,235 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0733) Prec@1 89.000 (88.567) Prec@5 99.000 (99.233) +2022-11-14 16:09:37,246 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0732) Prec@1 89.000 (88.581) Prec@5 99.000 (99.226) +2022-11-14 16:09:37,257 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0733) Prec@1 89.000 (88.594) Prec@5 100.000 (99.250) +2022-11-14 16:09:37,267 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0733) Prec@1 88.000 (88.576) Prec@5 100.000 (99.273) +2022-11-14 16:09:37,277 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0733) Prec@1 85.000 (88.471) Prec@5 99.000 (99.265) +2022-11-14 16:09:37,287 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0738) Prec@1 88.000 (88.457) Prec@5 98.000 (99.229) +2022-11-14 16:09:37,299 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0735) Prec@1 89.000 (88.472) Prec@5 100.000 (99.250) +2022-11-14 16:09:37,310 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0734) Prec@1 88.000 (88.459) Prec@5 99.000 (99.243) +2022-11-14 16:09:37,320 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0741) Prec@1 82.000 (88.289) Prec@5 99.000 (99.237) +2022-11-14 16:09:37,330 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0739) Prec@1 91.000 (88.359) Prec@5 99.000 (99.231) +2022-11-14 16:09:37,339 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0741) Prec@1 87.000 (88.325) Prec@5 99.000 (99.225) +2022-11-14 16:09:37,350 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0747) Prec@1 85.000 (88.244) Prec@5 99.000 (99.220) +2022-11-14 16:09:37,359 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0748) Prec@1 89.000 (88.262) Prec@5 99.000 (99.214) +2022-11-14 16:09:37,369 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0392 (0.0740) Prec@1 94.000 (88.395) Prec@5 100.000 (99.233) +2022-11-14 16:09:37,379 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0737) Prec@1 90.000 (88.432) Prec@5 99.000 (99.227) +2022-11-14 16:09:37,389 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0733) Prec@1 90.000 (88.467) Prec@5 100.000 (99.244) +2022-11-14 16:09:37,400 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0738) Prec@1 86.000 (88.413) Prec@5 98.000 (99.217) +2022-11-14 16:09:37,411 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0736) Prec@1 90.000 (88.447) Prec@5 100.000 (99.234) +2022-11-14 16:09:37,422 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0742) Prec@1 85.000 (88.375) Prec@5 99.000 (99.229) +2022-11-14 16:09:37,433 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0442 (0.0736) Prec@1 93.000 (88.469) Prec@5 100.000 (99.245) +2022-11-14 16:09:37,444 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0742) Prec@1 85.000 (88.400) Prec@5 98.000 (99.220) +2022-11-14 16:09:37,455 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0742) Prec@1 89.000 (88.412) Prec@5 100.000 (99.235) +2022-11-14 16:09:37,464 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0742) Prec@1 85.000 (88.346) Prec@5 100.000 (99.250) +2022-11-14 16:09:37,474 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0739) Prec@1 89.000 (88.358) Prec@5 100.000 (99.264) +2022-11-14 16:09:37,484 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0738) Prec@1 91.000 (88.407) Prec@5 99.000 (99.259) +2022-11-14 16:09:37,494 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0740) Prec@1 86.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 16:09:37,504 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0742) Prec@1 84.000 (88.286) Prec@5 99.000 (99.268) +2022-11-14 16:09:37,513 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0740) Prec@1 91.000 (88.333) Prec@5 100.000 (99.281) +2022-11-14 16:09:37,524 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0738) Prec@1 90.000 (88.362) Prec@5 98.000 (99.259) +2022-11-14 16:09:37,533 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1148 (0.0745) Prec@1 80.000 (88.220) Prec@5 98.000 (99.237) +2022-11-14 16:09:37,544 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0748) Prec@1 84.000 (88.150) Prec@5 100.000 (99.250) +2022-11-14 16:09:37,554 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0747) Prec@1 90.000 (88.180) Prec@5 99.000 (99.246) +2022-11-14 16:09:37,565 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0748) Prec@1 87.000 (88.161) Prec@5 99.000 (99.242) +2022-11-14 16:09:37,575 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0749) Prec@1 88.000 (88.159) Prec@5 99.000 (99.238) +2022-11-14 16:09:37,586 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0748) Prec@1 87.000 (88.141) Prec@5 99.000 (99.234) +2022-11-14 16:09:37,595 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0750) Prec@1 87.000 (88.123) Prec@5 99.000 (99.231) +2022-11-14 16:09:37,606 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0752) Prec@1 86.000 (88.091) Prec@5 99.000 (99.227) +2022-11-14 16:09:37,615 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0377 (0.0746) Prec@1 93.000 (88.164) Prec@5 100.000 (99.239) +2022-11-14 16:09:37,626 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0746) Prec@1 91.000 (88.206) Prec@5 97.000 (99.206) +2022-11-14 16:09:37,638 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0743) Prec@1 91.000 (88.246) Prec@5 99.000 (99.203) +2022-11-14 16:09:37,649 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0742) Prec@1 88.000 (88.243) Prec@5 99.000 (99.200) +2022-11-14 16:09:37,660 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0744) Prec@1 87.000 (88.225) Prec@5 98.000 (99.183) +2022-11-14 16:09:37,669 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0484 (0.0740) Prec@1 92.000 (88.278) Prec@5 99.000 (99.181) +2022-11-14 16:09:37,679 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0738) Prec@1 92.000 (88.329) Prec@5 100.000 (99.192) +2022-11-14 16:09:37,690 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0734) Prec@1 94.000 (88.405) Prec@5 100.000 (99.203) +2022-11-14 16:09:37,699 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0735) Prec@1 88.000 (88.400) Prec@5 100.000 (99.213) +2022-11-14 16:09:37,711 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0733) Prec@1 91.000 (88.434) Prec@5 99.000 (99.211) +2022-11-14 16:09:37,721 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0733) Prec@1 90.000 (88.455) Prec@5 97.000 (99.182) +2022-11-14 16:09:37,732 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1007 (0.0736) Prec@1 85.000 (88.410) Prec@5 98.000 (99.167) +2022-11-14 16:09:37,742 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0738) Prec@1 84.000 (88.354) Prec@5 99.000 (99.165) +2022-11-14 16:09:37,752 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0739) Prec@1 86.000 (88.325) Prec@5 100.000 (99.175) +2022-11-14 16:09:37,764 Test: [80/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0739) Prec@1 88.000 (88.321) Prec@5 98.000 (99.160) +2022-11-14 16:09:37,774 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0739) Prec@1 89.000 (88.329) Prec@5 100.000 (99.171) +2022-11-14 16:09:37,785 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0741) Prec@1 85.000 (88.289) Prec@5 100.000 (99.181) +2022-11-14 16:09:37,796 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0740) Prec@1 90.000 (88.310) Prec@5 99.000 (99.179) +2022-11-14 16:09:37,807 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0741) Prec@1 86.000 (88.282) Prec@5 100.000 (99.188) +2022-11-14 16:09:37,818 Test: [85/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0745) Prec@1 84.000 (88.233) Prec@5 99.000 (99.186) +2022-11-14 16:09:37,830 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0747) Prec@1 84.000 (88.184) Prec@5 99.000 (99.184) +2022-11-14 16:09:37,841 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0747) Prec@1 91.000 (88.216) Prec@5 99.000 (99.182) +2022-11-14 16:09:37,851 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0747) Prec@1 85.000 (88.180) Prec@5 100.000 (99.191) +2022-11-14 16:09:37,862 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0748) Prec@1 86.000 (88.156) Prec@5 99.000 (99.189) +2022-11-14 16:09:37,873 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0745) Prec@1 93.000 (88.209) Prec@5 100.000 (99.198) +2022-11-14 16:09:37,884 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0742) Prec@1 95.000 (88.283) Prec@5 100.000 (99.207) +2022-11-14 16:09:37,895 Test: [92/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0743) Prec@1 87.000 (88.269) Prec@5 100.000 (99.215) +2022-11-14 16:09:37,907 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0742) Prec@1 89.000 (88.277) Prec@5 99.000 (99.213) +2022-11-14 16:09:37,919 Test: [94/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0743) Prec@1 85.000 (88.242) Prec@5 99.000 (99.211) +2022-11-14 16:09:37,930 Test: [95/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0744) Prec@1 89.000 (88.250) Prec@5 99.000 (99.208) +2022-11-14 16:09:37,941 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0741) Prec@1 92.000 (88.289) Prec@5 99.000 (99.206) +2022-11-14 16:09:37,954 Test: [97/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0743) Prec@1 87.000 (88.276) Prec@5 98.000 (99.194) +2022-11-14 16:09:37,965 Test: [98/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0746) Prec@1 86.000 (88.253) Prec@5 97.000 (99.172) +2022-11-14 16:09:37,976 Test: [99/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0746) Prec@1 88.000 (88.250) Prec@5 100.000 (99.180) +2022-11-14 16:09:38,043 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:09:38,409 Epoch: [310][0/500] Time 0.031 (0.031) Data 0.263 (0.263) Loss 0.0304 (0.0304) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:09:38,651 Epoch: [310][10/500] Time 0.021 (0.022) Data 0.002 (0.026) Loss 0.0325 (0.0314) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:09:38,900 Epoch: [310][20/500] Time 0.027 (0.022) Data 0.002 (0.014) Loss 0.0411 (0.0347) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:09:39,319 Epoch: [310][30/500] Time 0.040 (0.027) Data 0.002 (0.010) Loss 0.0295 (0.0334) Prec@1 95.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 16:09:39,759 Epoch: [310][40/500] Time 0.051 (0.030) Data 0.002 (0.008) Loss 0.0448 (0.0357) Prec@1 92.000 (93.800) Prec@5 100.000 (100.000) +2022-11-14 16:09:40,225 Epoch: [310][50/500] Time 0.041 (0.032) Data 0.002 (0.007) Loss 0.0392 (0.0363) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:09:40,686 Epoch: [310][60/500] Time 0.048 (0.034) Data 0.002 (0.006) Loss 0.0284 (0.0351) Prec@1 94.000 (93.571) Prec@5 100.000 (100.000) +2022-11-14 16:09:41,131 Epoch: [310][70/500] Time 0.051 (0.035) Data 0.002 (0.006) Loss 0.0381 (0.0355) Prec@1 95.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 16:09:41,578 Epoch: [310][80/500] Time 0.045 (0.035) Data 0.002 (0.005) Loss 0.0583 (0.0380) Prec@1 89.000 (93.222) Prec@5 100.000 (100.000) +2022-11-14 16:09:42,036 Epoch: [310][90/500] Time 0.040 (0.036) Data 0.002 (0.005) Loss 0.0283 (0.0371) Prec@1 97.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 16:09:42,500 Epoch: [310][100/500] Time 0.051 (0.036) Data 0.002 (0.005) Loss 0.0274 (0.0362) Prec@1 96.000 (93.818) Prec@5 99.000 (99.909) +2022-11-14 16:09:42,969 Epoch: [310][110/500] Time 0.044 (0.037) Data 0.002 (0.004) Loss 0.0205 (0.0349) Prec@1 97.000 (94.083) Prec@5 100.000 (99.917) +2022-11-14 16:09:43,446 Epoch: [310][120/500] Time 0.054 (0.037) Data 0.002 (0.004) Loss 0.0307 (0.0345) Prec@1 97.000 (94.308) Prec@5 100.000 (99.923) +2022-11-14 16:09:43,909 Epoch: [310][130/500] Time 0.047 (0.038) Data 0.002 (0.004) Loss 0.0269 (0.0340) Prec@1 97.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 16:09:44,366 Epoch: [310][140/500] Time 0.034 (0.038) Data 0.002 (0.004) Loss 0.0560 (0.0355) Prec@1 92.000 (94.333) Prec@5 100.000 (99.933) +2022-11-14 16:09:44,834 Epoch: [310][150/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0235 (0.0347) Prec@1 95.000 (94.375) Prec@5 100.000 (99.938) +2022-11-14 16:09:45,326 Epoch: [310][160/500] Time 0.045 (0.039) Data 0.002 (0.004) Loss 0.0311 (0.0345) Prec@1 94.000 (94.353) Prec@5 100.000 (99.941) +2022-11-14 16:09:45,863 Epoch: [310][170/500] Time 0.053 (0.039) Data 0.002 (0.004) Loss 0.0340 (0.0345) Prec@1 94.000 (94.333) Prec@5 100.000 (99.944) +2022-11-14 16:09:46,373 Epoch: [310][180/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0694 (0.0363) Prec@1 87.000 (93.947) Prec@5 99.000 (99.895) +2022-11-14 16:09:46,853 Epoch: [310][190/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0343 (0.0362) Prec@1 94.000 (93.950) Prec@5 100.000 (99.900) +2022-11-14 16:09:47,315 Epoch: [310][200/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0395 (0.0364) Prec@1 94.000 (93.952) Prec@5 100.000 (99.905) +2022-11-14 16:09:47,771 Epoch: [310][210/500] Time 0.039 (0.040) Data 0.002 (0.003) Loss 0.0451 (0.0368) Prec@1 92.000 (93.864) Prec@5 100.000 (99.909) +2022-11-14 16:09:48,287 Epoch: [310][220/500] Time 0.063 (0.040) Data 0.002 (0.003) Loss 0.0209 (0.0361) Prec@1 96.000 (93.957) Prec@5 100.000 (99.913) +2022-11-14 16:09:48,729 Epoch: [310][230/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0510 (0.0367) Prec@1 92.000 (93.875) Prec@5 99.000 (99.875) +2022-11-14 16:09:49,193 Epoch: [310][240/500] Time 0.050 (0.040) Data 0.002 (0.003) Loss 0.0316 (0.0365) Prec@1 95.000 (93.920) Prec@5 100.000 (99.880) +2022-11-14 16:09:49,683 Epoch: [310][250/500] Time 0.047 (0.040) Data 0.002 (0.003) Loss 0.0176 (0.0358) Prec@1 98.000 (94.077) Prec@5 100.000 (99.885) +2022-11-14 16:09:50,144 Epoch: [310][260/500] Time 0.046 (0.040) Data 0.002 (0.003) Loss 0.0342 (0.0357) Prec@1 94.000 (94.074) Prec@5 100.000 (99.889) +2022-11-14 16:09:50,617 Epoch: [310][270/500] Time 0.042 (0.040) Data 0.002 (0.003) Loss 0.0288 (0.0355) Prec@1 94.000 (94.071) Prec@5 100.000 (99.893) +2022-11-14 16:09:51,074 Epoch: [310][280/500] Time 0.040 (0.040) Data 0.002 (0.003) Loss 0.0365 (0.0355) Prec@1 91.000 (93.966) Prec@5 100.000 (99.897) +2022-11-14 16:09:51,562 Epoch: [310][290/500] Time 0.052 (0.040) Data 0.003 (0.003) Loss 0.0485 (0.0359) Prec@1 89.000 (93.800) Prec@5 99.000 (99.867) +2022-11-14 16:09:52,018 Epoch: [310][300/500] Time 0.041 (0.040) Data 0.002 (0.003) Loss 0.0366 (0.0360) Prec@1 94.000 (93.806) Prec@5 100.000 (99.871) +2022-11-14 16:09:52,465 Epoch: [310][310/500] Time 0.048 (0.040) Data 0.002 (0.003) Loss 0.0469 (0.0363) Prec@1 93.000 (93.781) Prec@5 99.000 (99.844) +2022-11-14 16:09:52,950 Epoch: [310][320/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0137 (0.0356) Prec@1 98.000 (93.909) Prec@5 100.000 (99.848) +2022-11-14 16:09:53,407 Epoch: [310][330/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0334 (0.0355) Prec@1 93.000 (93.882) Prec@5 100.000 (99.853) +2022-11-14 16:09:53,898 Epoch: [310][340/500] Time 0.047 (0.041) Data 0.003 (0.003) Loss 0.0393 (0.0357) Prec@1 94.000 (93.886) Prec@5 100.000 (99.857) +2022-11-14 16:09:54,375 Epoch: [310][350/500] Time 0.031 (0.041) Data 0.002 (0.003) Loss 0.0241 (0.0353) Prec@1 97.000 (93.972) Prec@5 99.000 (99.833) +2022-11-14 16:09:54,879 Epoch: [310][360/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0344 (0.0353) Prec@1 94.000 (93.973) Prec@5 98.000 (99.784) +2022-11-14 16:09:55,416 Epoch: [310][370/500] Time 0.060 (0.041) Data 0.002 (0.003) Loss 0.0265 (0.0351) Prec@1 96.000 (94.026) Prec@5 100.000 (99.789) +2022-11-14 16:09:55,932 Epoch: [310][380/500] Time 0.051 (0.041) Data 0.003 (0.003) Loss 0.0265 (0.0349) Prec@1 95.000 (94.051) Prec@5 100.000 (99.795) +2022-11-14 16:09:56,410 Epoch: [310][390/500] Time 0.046 (0.041) Data 0.003 (0.003) Loss 0.0416 (0.0350) Prec@1 94.000 (94.050) Prec@5 100.000 (99.800) +2022-11-14 16:09:56,902 Epoch: [310][400/500] Time 0.052 (0.041) Data 0.004 (0.003) Loss 0.0319 (0.0349) Prec@1 96.000 (94.098) Prec@5 100.000 (99.805) +2022-11-14 16:09:57,417 Epoch: [310][410/500] Time 0.040 (0.041) Data 0.004 (0.003) Loss 0.0385 (0.0350) Prec@1 93.000 (94.071) Prec@5 100.000 (99.810) +2022-11-14 16:09:57,926 Epoch: [310][420/500] Time 0.055 (0.042) Data 0.004 (0.003) Loss 0.0396 (0.0351) Prec@1 94.000 (94.070) Prec@5 100.000 (99.814) +2022-11-14 16:09:58,393 Epoch: [310][430/500] Time 0.042 (0.042) Data 0.004 (0.003) Loss 0.0145 (0.0347) Prec@1 99.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 16:09:58,847 Epoch: [310][440/500] Time 0.042 (0.042) Data 0.003 (0.003) Loss 0.0195 (0.0343) Prec@1 97.000 (94.244) Prec@5 100.000 (99.822) +2022-11-14 16:09:59,308 Epoch: [310][450/500] Time 0.047 (0.042) Data 0.003 (0.003) Loss 0.0199 (0.0340) Prec@1 97.000 (94.304) Prec@5 100.000 (99.826) +2022-11-14 16:09:59,782 Epoch: [310][460/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0434 (0.0342) Prec@1 94.000 (94.298) Prec@5 100.000 (99.830) +2022-11-14 16:10:00,292 Epoch: [310][470/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0348 (0.0342) Prec@1 93.000 (94.271) Prec@5 100.000 (99.833) +2022-11-14 16:10:00,818 Epoch: [310][480/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0266 (0.0341) Prec@1 97.000 (94.327) Prec@5 100.000 (99.837) +2022-11-14 16:10:01,322 Epoch: [310][490/500] Time 0.048 (0.042) Data 0.003 (0.003) Loss 0.0401 (0.0342) Prec@1 94.000 (94.320) Prec@5 99.000 (99.820) +2022-11-14 16:10:01,854 Epoch: [310][499/500] Time 0.083 (0.042) Data 0.002 (0.003) Loss 0.0246 (0.0340) Prec@1 97.000 (94.373) Prec@5 99.000 (99.804) +2022-11-14 16:10:02,206 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0894 (0.0894) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 16:10:02,217 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0824 (0.0859) Prec@1 87.000 (86.500) Prec@5 100.000 (99.500) +2022-11-14 16:10:02,232 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0561 (0.0759) Prec@1 91.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:10:02,257 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0776 (0.0763) Prec@1 89.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 16:10:02,294 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0957 (0.0802) Prec@1 83.000 (87.200) Prec@5 99.000 (99.400) +2022-11-14 16:10:02,336 Test: [5/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0389 (0.0733) Prec@1 93.000 (88.167) Prec@5 100.000 (99.500) +2022-11-14 16:10:02,372 Test: [6/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0680 (0.0726) Prec@1 91.000 (88.571) Prec@5 99.000 (99.429) +2022-11-14 16:10:02,412 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0853 (0.0742) Prec@1 85.000 (88.125) Prec@5 99.000 (99.375) +2022-11-14 16:10:02,441 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0872 (0.0756) Prec@1 87.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 16:10:02,482 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0667 (0.0747) Prec@1 88.000 (88.000) Prec@5 99.000 (99.300) +2022-11-14 16:10:02,525 Test: [10/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0685 (0.0742) Prec@1 87.000 (87.909) Prec@5 100.000 (99.364) +2022-11-14 16:10:02,576 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0747 (0.0742) Prec@1 88.000 (87.917) Prec@5 99.000 (99.333) +2022-11-14 16:10:02,630 Test: [12/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0392 (0.0715) Prec@1 92.000 (88.231) Prec@5 100.000 (99.385) +2022-11-14 16:10:02,685 Test: [13/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0793 (0.0721) Prec@1 86.000 (88.071) Prec@5 98.000 (99.286) +2022-11-14 16:10:02,737 Test: [14/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0749 (0.0723) Prec@1 88.000 (88.067) Prec@5 100.000 (99.333) +2022-11-14 16:10:02,783 Test: [15/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0685 (0.0720) Prec@1 89.000 (88.125) Prec@5 100.000 (99.375) +2022-11-14 16:10:02,825 Test: [16/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0715) Prec@1 91.000 (88.294) Prec@5 99.000 (99.353) +2022-11-14 16:10:02,875 Test: [17/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0972 (0.0729) Prec@1 84.000 (88.056) Prec@5 100.000 (99.389) +2022-11-14 16:10:02,928 Test: [18/100] Model Time 0.015 (0.010) Loss Time 0.000 (0.000) Loss 0.0950 (0.0741) Prec@1 87.000 (88.000) Prec@5 100.000 (99.421) +2022-11-14 16:10:02,982 Test: [19/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1111 (0.0759) Prec@1 80.000 (87.600) Prec@5 98.000 (99.350) +2022-11-14 16:10:03,030 Test: [20/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.0761) Prec@1 86.000 (87.524) Prec@5 100.000 (99.381) +2022-11-14 16:10:03,079 Test: [21/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0701 (0.0758) Prec@1 89.000 (87.591) Prec@5 98.000 (99.318) +2022-11-14 16:10:03,129 Test: [22/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0942 (0.0766) Prec@1 87.000 (87.565) Prec@5 97.000 (99.217) +2022-11-14 16:10:03,180 Test: [23/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0716 (0.0764) Prec@1 87.000 (87.542) Prec@5 99.000 (99.208) +2022-11-14 16:10:03,233 Test: [24/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0877 (0.0769) Prec@1 88.000 (87.560) Prec@5 100.000 (99.240) +2022-11-14 16:10:03,283 Test: [25/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0831 (0.0771) Prec@1 89.000 (87.615) Prec@5 99.000 (99.231) +2022-11-14 16:10:03,337 Test: [26/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0553 (0.0763) Prec@1 93.000 (87.815) Prec@5 99.000 (99.222) +2022-11-14 16:10:03,389 Test: [27/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0799 (0.0764) Prec@1 89.000 (87.857) Prec@5 100.000 (99.250) +2022-11-14 16:10:03,442 Test: [28/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0718 (0.0763) Prec@1 88.000 (87.862) Prec@5 99.000 (99.241) +2022-11-14 16:10:03,488 Test: [29/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0529 (0.0755) Prec@1 91.000 (87.967) Prec@5 100.000 (99.267) +2022-11-14 16:10:03,525 Test: [30/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0512 (0.0747) Prec@1 93.000 (88.129) Prec@5 98.000 (99.226) +2022-11-14 16:10:03,558 Test: [31/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0635 (0.0744) Prec@1 91.000 (88.219) Prec@5 99.000 (99.219) +2022-11-14 16:10:03,597 Test: [32/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0626 (0.0740) Prec@1 88.000 (88.212) Prec@5 100.000 (99.242) +2022-11-14 16:10:03,629 Test: [33/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0971 (0.0747) Prec@1 85.000 (88.118) Prec@5 100.000 (99.265) +2022-11-14 16:10:03,662 Test: [34/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0795 (0.0748) Prec@1 87.000 (88.086) Prec@5 98.000 (99.229) +2022-11-14 16:10:03,702 Test: [35/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0653 (0.0746) Prec@1 92.000 (88.194) Prec@5 100.000 (99.250) +2022-11-14 16:10:03,740 Test: [36/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0890 (0.0749) Prec@1 84.000 (88.081) Prec@5 98.000 (99.216) +2022-11-14 16:10:03,778 Test: [37/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0997 (0.0756) Prec@1 84.000 (87.974) Prec@5 100.000 (99.237) +2022-11-14 16:10:03,813 Test: [38/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0636 (0.0753) Prec@1 90.000 (88.026) Prec@5 99.000 (99.231) +2022-11-14 16:10:03,848 Test: [39/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0598 (0.0749) Prec@1 90.000 (88.075) Prec@5 100.000 (99.250) +2022-11-14 16:10:03,899 Test: [40/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0923 (0.0753) Prec@1 85.000 (88.000) Prec@5 99.000 (99.244) +2022-11-14 16:10:03,950 Test: [41/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0716 (0.0752) Prec@1 88.000 (88.000) Prec@5 100.000 (99.262) +2022-11-14 16:10:04,003 Test: [42/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0532 (0.0747) Prec@1 92.000 (88.093) Prec@5 99.000 (99.256) +2022-11-14 16:10:04,054 Test: [43/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0723 (0.0747) Prec@1 91.000 (88.159) Prec@5 98.000 (99.227) +2022-11-14 16:10:04,103 Test: [44/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0660 (0.0745) Prec@1 87.000 (88.133) Prec@5 99.000 (99.222) +2022-11-14 16:10:04,157 Test: [45/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0946 (0.0749) Prec@1 84.000 (88.043) Prec@5 99.000 (99.217) +2022-11-14 16:10:04,206 Test: [46/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0750) Prec@1 88.000 (88.043) Prec@5 100.000 (99.234) +2022-11-14 16:10:04,259 Test: [47/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1114 (0.0758) Prec@1 83.000 (87.938) Prec@5 99.000 (99.229) +2022-11-14 16:10:04,289 Test: [48/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0454 (0.0751) Prec@1 92.000 (88.020) Prec@5 100.000 (99.245) +2022-11-14 16:10:04,323 Test: [49/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0922 (0.0755) Prec@1 87.000 (88.000) Prec@5 100.000 (99.260) +2022-11-14 16:10:04,355 Test: [50/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0536 (0.0750) Prec@1 90.000 (88.039) Prec@5 99.000 (99.255) +2022-11-14 16:10:04,386 Test: [51/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0754) Prec@1 82.000 (87.923) Prec@5 98.000 (99.231) +2022-11-14 16:10:04,417 Test: [52/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0743 (0.0754) Prec@1 88.000 (87.925) Prec@5 100.000 (99.245) +2022-11-14 16:10:04,455 Test: [53/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0644 (0.0752) Prec@1 87.000 (87.907) Prec@5 100.000 (99.259) +2022-11-14 16:10:04,500 Test: [54/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1052 (0.0757) Prec@1 82.000 (87.800) Prec@5 99.000 (99.255) +2022-11-14 16:10:04,553 Test: [55/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0596 (0.0754) Prec@1 90.000 (87.839) Prec@5 99.000 (99.250) +2022-11-14 16:10:04,608 Test: [56/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0606 (0.0752) Prec@1 91.000 (87.895) Prec@5 99.000 (99.246) +2022-11-14 16:10:04,652 Test: [57/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0800 (0.0752) Prec@1 89.000 (87.914) Prec@5 99.000 (99.241) +2022-11-14 16:10:04,689 Test: [58/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0884 (0.0755) Prec@1 87.000 (87.898) Prec@5 99.000 (99.237) +2022-11-14 16:10:04,725 Test: [59/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0858 (0.0756) Prec@1 86.000 (87.867) Prec@5 98.000 (99.217) +2022-11-14 16:10:04,761 Test: [60/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0679 (0.0755) Prec@1 90.000 (87.902) Prec@5 99.000 (99.213) +2022-11-14 16:10:04,797 Test: [61/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0631 (0.0753) Prec@1 90.000 (87.935) Prec@5 99.000 (99.210) +2022-11-14 16:10:04,831 Test: [62/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0805 (0.0754) Prec@1 86.000 (87.905) Prec@5 100.000 (99.222) +2022-11-14 16:10:04,869 Test: [63/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0526 (0.0750) Prec@1 89.000 (87.922) Prec@5 99.000 (99.219) +2022-11-14 16:10:04,900 Test: [64/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0898 (0.0753) Prec@1 83.000 (87.846) Prec@5 98.000 (99.200) +2022-11-14 16:10:04,930 Test: [65/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0805 (0.0753) Prec@1 85.000 (87.803) Prec@5 99.000 (99.197) +2022-11-14 16:10:04,962 Test: [66/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0493 (0.0750) Prec@1 92.000 (87.866) Prec@5 100.000 (99.209) +2022-11-14 16:10:04,998 Test: [67/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0657 (0.0748) Prec@1 91.000 (87.912) Prec@5 98.000 (99.191) +2022-11-14 16:10:05,031 Test: [68/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0585 (0.0746) Prec@1 92.000 (87.971) Prec@5 99.000 (99.188) +2022-11-14 16:10:05,089 Test: [69/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.1073 (0.0750) Prec@1 83.000 (87.900) Prec@5 98.000 (99.171) +2022-11-14 16:10:05,143 Test: [70/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0945 (0.0753) Prec@1 85.000 (87.859) Prec@5 98.000 (99.155) +2022-11-14 16:10:05,193 Test: [71/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0580 (0.0751) Prec@1 90.000 (87.889) Prec@5 100.000 (99.167) +2022-11-14 16:10:05,248 Test: [72/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0444 (0.0747) Prec@1 94.000 (87.973) Prec@5 99.000 (99.164) +2022-11-14 16:10:05,303 Test: [73/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0427 (0.0742) Prec@1 92.000 (88.027) Prec@5 100.000 (99.176) +2022-11-14 16:10:05,355 Test: [74/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0885 (0.0744) Prec@1 84.000 (87.973) Prec@5 99.000 (99.173) +2022-11-14 16:10:05,408 Test: [75/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0621 (0.0743) Prec@1 92.000 (88.026) Prec@5 99.000 (99.171) +2022-11-14 16:10:05,456 Test: [76/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0742) Prec@1 89.000 (88.039) Prec@5 97.000 (99.143) +2022-11-14 16:10:05,491 Test: [77/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0888 (0.0744) Prec@1 86.000 (88.013) Prec@5 99.000 (99.141) +2022-11-14 16:10:05,531 Test: [78/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0643 (0.0742) Prec@1 89.000 (88.025) Prec@5 100.000 (99.152) +2022-11-14 16:10:05,565 Test: [79/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0722 (0.0742) Prec@1 88.000 (88.025) Prec@5 99.000 (99.150) +2022-11-14 16:10:05,597 Test: [80/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0928 (0.0744) Prec@1 84.000 (87.975) Prec@5 98.000 (99.136) +2022-11-14 16:10:05,628 Test: [81/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0948 (0.0747) Prec@1 82.000 (87.902) Prec@5 100.000 (99.146) +2022-11-14 16:10:05,669 Test: [82/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0873 (0.0748) Prec@1 85.000 (87.867) Prec@5 100.000 (99.157) +2022-11-14 16:10:05,705 Test: [83/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0684 (0.0748) Prec@1 89.000 (87.881) Prec@5 100.000 (99.167) +2022-11-14 16:10:05,740 Test: [84/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0809 (0.0748) Prec@1 88.000 (87.882) Prec@5 100.000 (99.176) +2022-11-14 16:10:05,782 Test: [85/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1077 (0.0752) Prec@1 85.000 (87.849) Prec@5 100.000 (99.186) +2022-11-14 16:10:05,816 Test: [86/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0734 (0.0752) Prec@1 89.000 (87.862) Prec@5 100.000 (99.195) +2022-11-14 16:10:05,848 Test: [87/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0676 (0.0751) Prec@1 90.000 (87.886) Prec@5 100.000 (99.205) +2022-11-14 16:10:05,882 Test: [88/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0790 (0.0751) Prec@1 88.000 (87.888) Prec@5 100.000 (99.213) +2022-11-14 16:10:05,913 Test: [89/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0915 (0.0753) Prec@1 86.000 (87.867) Prec@5 98.000 (99.200) +2022-11-14 16:10:05,947 Test: [90/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0625 (0.0752) Prec@1 89.000 (87.879) Prec@5 100.000 (99.209) +2022-11-14 16:10:05,977 Test: [91/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0786 (0.0752) Prec@1 89.000 (87.891) Prec@5 99.000 (99.207) +2022-11-14 16:10:06,009 Test: [92/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1060 (0.0756) Prec@1 84.000 (87.849) Prec@5 100.000 (99.215) +2022-11-14 16:10:06,044 Test: [93/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0818 (0.0756) Prec@1 87.000 (87.840) Prec@5 99.000 (99.213) +2022-11-14 16:10:06,075 Test: [94/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0970 (0.0758) Prec@1 83.000 (87.789) Prec@5 100.000 (99.221) +2022-11-14 16:10:06,108 Test: [95/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0737 (0.0758) Prec@1 90.000 (87.812) Prec@5 99.000 (99.219) +2022-11-14 16:10:06,141 Test: [96/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0445 (0.0755) Prec@1 92.000 (87.856) Prec@5 99.000 (99.216) +2022-11-14 16:10:06,166 Test: [97/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0987 (0.0757) Prec@1 84.000 (87.816) Prec@5 99.000 (99.214) +2022-11-14 16:10:06,203 Test: [98/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0997 (0.0760) Prec@1 82.000 (87.758) Prec@5 99.000 (99.212) +2022-11-14 16:10:06,244 Test: [99/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0718 (0.0759) Prec@1 88.000 (87.760) Prec@5 100.000 (99.220) +2022-11-14 16:10:06,309 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:10:06,677 Epoch: [311][0/500] Time 0.029 (0.029) Data 0.275 (0.275) Loss 0.0678 (0.0678) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:10:07,160 Epoch: [311][10/500] Time 0.047 (0.041) Data 0.002 (0.027) Loss 0.0272 (0.0475) Prec@1 95.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:10:07,732 Epoch: [311][20/500] Time 0.054 (0.046) Data 0.002 (0.015) Loss 0.0412 (0.0454) Prec@1 93.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 16:10:08,328 Epoch: [311][30/500] Time 0.080 (0.048) Data 0.002 (0.011) Loss 0.0250 (0.0403) Prec@1 96.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 16:10:08,920 Epoch: [311][40/500] Time 0.054 (0.049) Data 0.002 (0.009) Loss 0.0343 (0.0391) Prec@1 95.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 16:10:09,502 Epoch: [311][50/500] Time 0.054 (0.050) Data 0.002 (0.007) Loss 0.0407 (0.0394) Prec@1 94.000 (93.667) Prec@5 99.000 (99.833) +2022-11-14 16:10:10,062 Epoch: [311][60/500] Time 0.061 (0.050) Data 0.002 (0.007) Loss 0.0227 (0.0370) Prec@1 97.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 16:10:10,707 Epoch: [311][70/500] Time 0.068 (0.051) Data 0.002 (0.006) Loss 0.0337 (0.0366) Prec@1 95.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 16:10:11,294 Epoch: [311][80/500] Time 0.052 (0.051) Data 0.002 (0.005) Loss 0.0414 (0.0371) Prec@1 92.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 16:10:11,863 Epoch: [311][90/500] Time 0.060 (0.051) Data 0.003 (0.005) Loss 0.0340 (0.0368) Prec@1 95.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 16:10:12,420 Epoch: [311][100/500] Time 0.054 (0.051) Data 0.003 (0.005) Loss 0.0415 (0.0372) Prec@1 94.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 16:10:13,026 Epoch: [311][110/500] Time 0.065 (0.051) Data 0.002 (0.005) Loss 0.0469 (0.0380) Prec@1 91.000 (93.833) Prec@5 99.000 (99.750) +2022-11-14 16:10:13,609 Epoch: [311][120/500] Time 0.063 (0.051) Data 0.002 (0.004) Loss 0.0419 (0.0383) Prec@1 93.000 (93.769) Prec@5 100.000 (99.769) +2022-11-14 16:10:14,187 Epoch: [311][130/500] Time 0.047 (0.051) Data 0.002 (0.004) Loss 0.0253 (0.0374) Prec@1 95.000 (93.857) Prec@5 100.000 (99.786) +2022-11-14 16:10:14,751 Epoch: [311][140/500] Time 0.064 (0.051) Data 0.002 (0.004) Loss 0.0374 (0.0374) Prec@1 93.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 16:10:15,303 Epoch: [311][150/500] Time 0.053 (0.051) Data 0.002 (0.004) Loss 0.0340 (0.0372) Prec@1 94.000 (93.812) Prec@5 100.000 (99.812) +2022-11-14 16:10:15,864 Epoch: [311][160/500] Time 0.055 (0.051) Data 0.002 (0.004) Loss 0.0312 (0.0368) Prec@1 96.000 (93.941) Prec@5 100.000 (99.824) +2022-11-14 16:10:16,420 Epoch: [311][170/500] Time 0.057 (0.051) Data 0.002 (0.004) Loss 0.0363 (0.0368) Prec@1 93.000 (93.889) Prec@5 100.000 (99.833) +2022-11-14 16:10:16,974 Epoch: [311][180/500] Time 0.048 (0.051) Data 0.002 (0.004) Loss 0.0310 (0.0365) Prec@1 93.000 (93.842) Prec@5 99.000 (99.789) +2022-11-14 16:10:17,531 Epoch: [311][190/500] Time 0.055 (0.051) Data 0.002 (0.004) Loss 0.0540 (0.0374) Prec@1 91.000 (93.700) Prec@5 100.000 (99.800) +2022-11-14 16:10:18,098 Epoch: [311][200/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0487 (0.0379) Prec@1 93.000 (93.667) Prec@5 100.000 (99.810) +2022-11-14 16:10:18,658 Epoch: [311][210/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0269 (0.0374) Prec@1 96.000 (93.773) Prec@5 100.000 (99.818) +2022-11-14 16:10:19,229 Epoch: [311][220/500] Time 0.046 (0.051) Data 0.002 (0.003) Loss 0.0227 (0.0368) Prec@1 97.000 (93.913) Prec@5 100.000 (99.826) +2022-11-14 16:10:19,811 Epoch: [311][230/500] Time 0.071 (0.051) Data 0.002 (0.003) Loss 0.0419 (0.0370) Prec@1 92.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 16:10:20,367 Epoch: [311][240/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0289 (0.0367) Prec@1 95.000 (93.880) Prec@5 100.000 (99.840) +2022-11-14 16:10:20,901 Epoch: [311][250/500] Time 0.047 (0.051) Data 0.002 (0.003) Loss 0.0328 (0.0365) Prec@1 94.000 (93.885) Prec@5 100.000 (99.846) +2022-11-14 16:10:21,484 Epoch: [311][260/500] Time 0.062 (0.051) Data 0.002 (0.003) Loss 0.0233 (0.0360) Prec@1 95.000 (93.926) Prec@5 100.000 (99.852) +2022-11-14 16:10:22,036 Epoch: [311][270/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0137 (0.0352) Prec@1 99.000 (94.107) Prec@5 100.000 (99.857) +2022-11-14 16:10:22,634 Epoch: [311][280/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0391 (0.0354) Prec@1 93.000 (94.069) Prec@5 100.000 (99.862) +2022-11-14 16:10:23,198 Epoch: [311][290/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0397 (0.0355) Prec@1 94.000 (94.067) Prec@5 100.000 (99.867) +2022-11-14 16:10:23,837 Epoch: [311][300/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0335 (0.0354) Prec@1 95.000 (94.097) Prec@5 100.000 (99.871) +2022-11-14 16:10:24,413 Epoch: [311][310/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0179 (0.0349) Prec@1 97.000 (94.188) Prec@5 100.000 (99.875) +2022-11-14 16:10:24,988 Epoch: [311][320/500] Time 0.047 (0.051) Data 0.002 (0.003) Loss 0.0343 (0.0349) Prec@1 94.000 (94.182) Prec@5 100.000 (99.879) +2022-11-14 16:10:25,551 Epoch: [311][330/500] Time 0.064 (0.051) Data 0.002 (0.003) Loss 0.0144 (0.0343) Prec@1 99.000 (94.324) Prec@5 100.000 (99.882) +2022-11-14 16:10:26,125 Epoch: [311][340/500] Time 0.051 (0.051) Data 0.003 (0.003) Loss 0.0275 (0.0341) Prec@1 95.000 (94.343) Prec@5 100.000 (99.886) +2022-11-14 16:10:26,688 Epoch: [311][350/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0380 (0.0342) Prec@1 92.000 (94.278) Prec@5 100.000 (99.889) +2022-11-14 16:10:27,235 Epoch: [311][360/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0092 (0.0335) Prec@1 98.000 (94.378) Prec@5 100.000 (99.892) +2022-11-14 16:10:27,789 Epoch: [311][370/500] Time 0.044 (0.051) Data 0.003 (0.003) Loss 0.0346 (0.0335) Prec@1 95.000 (94.395) Prec@5 100.000 (99.895) +2022-11-14 16:10:28,341 Epoch: [311][380/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0465 (0.0339) Prec@1 94.000 (94.385) Prec@5 99.000 (99.872) +2022-11-14 16:10:28,923 Epoch: [311][390/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0361 (0.0339) Prec@1 94.000 (94.375) Prec@5 98.000 (99.825) +2022-11-14 16:10:29,488 Epoch: [311][400/500] Time 0.052 (0.051) Data 0.003 (0.003) Loss 0.0552 (0.0345) Prec@1 90.000 (94.268) Prec@5 100.000 (99.829) +2022-11-14 16:10:30,061 Epoch: [311][410/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0405 (0.0346) Prec@1 92.000 (94.214) Prec@5 100.000 (99.833) +2022-11-14 16:10:30,612 Epoch: [311][420/500] Time 0.045 (0.051) Data 0.002 (0.003) Loss 0.0257 (0.0344) Prec@1 96.000 (94.256) Prec@5 99.000 (99.814) +2022-11-14 16:10:31,162 Epoch: [311][430/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0331 (0.0344) Prec@1 95.000 (94.273) Prec@5 100.000 (99.818) +2022-11-14 16:10:31,738 Epoch: [311][440/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0304 (0.0343) Prec@1 95.000 (94.289) Prec@5 99.000 (99.800) +2022-11-14 16:10:32,297 Epoch: [311][450/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0232 (0.0340) Prec@1 95.000 (94.304) Prec@5 100.000 (99.804) +2022-11-14 16:10:32,865 Epoch: [311][460/500] Time 0.069 (0.051) Data 0.002 (0.003) Loss 0.0277 (0.0339) Prec@1 95.000 (94.319) Prec@5 100.000 (99.809) +2022-11-14 16:10:33,443 Epoch: [311][470/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0325 (0.0339) Prec@1 96.000 (94.354) Prec@5 99.000 (99.792) +2022-11-14 16:10:34,023 Epoch: [311][480/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0329 (0.0338) Prec@1 94.000 (94.347) Prec@5 99.000 (99.776) +2022-11-14 16:10:34,591 Epoch: [311][490/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0462 (0.0341) Prec@1 90.000 (94.260) Prec@5 99.000 (99.760) +2022-11-14 16:10:35,076 Epoch: [311][499/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0330 (0.0341) Prec@1 95.000 (94.275) Prec@5 99.000 (99.745) +2022-11-14 16:10:35,411 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0731 (0.0731) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:10:35,419 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0537 (0.0634) Prec@1 92.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 16:10:35,431 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0465 (0.0578) Prec@1 93.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 16:10:35,447 Test: [3/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0593) Prec@1 90.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 16:10:35,456 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0612) Prec@1 90.000 (90.800) Prec@5 99.000 (99.400) +2022-11-14 16:10:35,466 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0587) Prec@1 92.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:10:35,477 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0596) Prec@1 89.000 (90.714) Prec@5 100.000 (99.571) +2022-11-14 16:10:35,491 Test: [7/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0615) Prec@1 87.000 (90.250) Prec@5 98.000 (99.375) +2022-11-14 16:10:35,501 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0626) Prec@1 88.000 (90.000) Prec@5 100.000 (99.444) +2022-11-14 16:10:35,511 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0646) Prec@1 84.000 (89.400) Prec@5 98.000 (99.300) +2022-11-14 16:10:35,521 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0655) Prec@1 88.000 (89.273) Prec@5 100.000 (99.364) +2022-11-14 16:10:35,531 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0658) Prec@1 87.000 (89.083) Prec@5 100.000 (99.417) +2022-11-14 16:10:35,541 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0647) Prec@1 91.000 (89.231) Prec@5 99.000 (99.385) +2022-11-14 16:10:35,551 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0648) Prec@1 88.000 (89.143) Prec@5 100.000 (99.429) +2022-11-14 16:10:35,560 Test: [14/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0650) Prec@1 89.000 (89.133) Prec@5 100.000 (99.467) +2022-11-14 16:10:35,570 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0658) Prec@1 87.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:10:35,582 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0367 (0.0641) Prec@1 93.000 (89.235) Prec@5 99.000 (99.471) +2022-11-14 16:10:35,592 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0664) Prec@1 84.000 (88.944) Prec@5 100.000 (99.500) +2022-11-14 16:10:35,601 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0669) Prec@1 86.000 (88.789) Prec@5 99.000 (99.474) +2022-11-14 16:10:35,611 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0684) Prec@1 86.000 (88.650) Prec@5 97.000 (99.350) +2022-11-14 16:10:35,623 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0684) Prec@1 87.000 (88.571) Prec@5 100.000 (99.381) +2022-11-14 16:10:35,634 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0684) Prec@1 90.000 (88.636) Prec@5 99.000 (99.364) +2022-11-14 16:10:35,646 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0697) Prec@1 85.000 (88.478) Prec@5 98.000 (99.304) +2022-11-14 16:10:35,656 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0702) Prec@1 87.000 (88.417) Prec@5 99.000 (99.292) +2022-11-14 16:10:35,666 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0709) Prec@1 86.000 (88.320) Prec@5 100.000 (99.320) +2022-11-14 16:10:35,676 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0712) Prec@1 88.000 (88.308) Prec@5 99.000 (99.308) +2022-11-14 16:10:35,685 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0705) Prec@1 91.000 (88.407) Prec@5 100.000 (99.333) +2022-11-14 16:10:35,695 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0700) Prec@1 92.000 (88.536) Prec@5 100.000 (99.357) +2022-11-14 16:10:35,704 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0703) Prec@1 85.000 (88.414) Prec@5 99.000 (99.345) +2022-11-14 16:10:35,714 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0702) Prec@1 88.000 (88.400) Prec@5 97.000 (99.267) +2022-11-14 16:10:35,725 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0706) Prec@1 82.000 (88.194) Prec@5 99.000 (99.258) +2022-11-14 16:10:35,735 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0701) Prec@1 91.000 (88.281) Prec@5 99.000 (99.250) +2022-11-14 16:10:35,745 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0705) Prec@1 87.000 (88.242) Prec@5 100.000 (99.273) +2022-11-14 16:10:35,755 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0707) Prec@1 86.000 (88.176) Prec@5 99.000 (99.265) +2022-11-14 16:10:35,764 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0714) Prec@1 83.000 (88.029) Prec@5 99.000 (99.257) +2022-11-14 16:10:35,776 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0712) Prec@1 90.000 (88.083) Prec@5 99.000 (99.250) +2022-11-14 16:10:35,786 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0709) Prec@1 89.000 (88.108) Prec@5 100.000 (99.270) +2022-11-14 16:10:35,795 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1133 (0.0720) Prec@1 83.000 (87.974) Prec@5 98.000 (99.237) +2022-11-14 16:10:35,804 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0455 (0.0714) Prec@1 94.000 (88.128) Prec@5 99.000 (99.231) +2022-11-14 16:10:35,814 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0709) Prec@1 92.000 (88.225) Prec@5 100.000 (99.250) +2022-11-14 16:10:35,824 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0718) Prec@1 80.000 (88.024) Prec@5 100.000 (99.268) +2022-11-14 16:10:35,834 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0717) Prec@1 91.000 (88.095) Prec@5 99.000 (99.262) +2022-11-14 16:10:35,845 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0712) Prec@1 93.000 (88.209) Prec@5 98.000 (99.233) +2022-11-14 16:10:35,855 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0710) Prec@1 89.000 (88.227) Prec@5 98.000 (99.205) +2022-11-14 16:10:35,866 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0705) Prec@1 92.000 (88.311) Prec@5 99.000 (99.200) +2022-11-14 16:10:35,876 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1162 (0.0715) Prec@1 81.000 (88.152) Prec@5 100.000 (99.217) +2022-11-14 16:10:35,887 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0713) Prec@1 89.000 (88.170) Prec@5 100.000 (99.234) +2022-11-14 16:10:35,896 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1131 (0.0721) Prec@1 83.000 (88.062) Prec@5 100.000 (99.250) +2022-11-14 16:10:35,906 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0716) Prec@1 91.000 (88.122) Prec@5 100.000 (99.265) +2022-11-14 16:10:35,916 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0718) Prec@1 90.000 (88.160) Prec@5 98.000 (99.240) +2022-11-14 16:10:35,926 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0715) Prec@1 90.000 (88.196) Prec@5 100.000 (99.255) +2022-11-14 16:10:35,936 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0715) Prec@1 89.000 (88.212) Prec@5 100.000 (99.269) +2022-11-14 16:10:35,946 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0716) Prec@1 84.000 (88.132) Prec@5 100.000 (99.283) +2022-11-14 16:10:35,956 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0716) Prec@1 89.000 (88.148) Prec@5 99.000 (99.278) +2022-11-14 16:10:35,966 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0718) Prec@1 85.000 (88.091) Prec@5 100.000 (99.291) +2022-11-14 16:10:35,976 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0715) Prec@1 91.000 (88.143) Prec@5 99.000 (99.286) +2022-11-14 16:10:35,987 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0712) Prec@1 91.000 (88.193) Prec@5 100.000 (99.298) +2022-11-14 16:10:35,999 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0712) Prec@1 90.000 (88.224) Prec@5 100.000 (99.310) +2022-11-14 16:10:36,009 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1128 (0.0719) Prec@1 83.000 (88.136) Prec@5 100.000 (99.322) +2022-11-14 16:10:36,018 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0719) Prec@1 86.000 (88.100) Prec@5 100.000 (99.333) +2022-11-14 16:10:36,028 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0719) Prec@1 87.000 (88.082) Prec@5 98.000 (99.311) +2022-11-14 16:10:36,038 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0717) Prec@1 90.000 (88.113) Prec@5 99.000 (99.306) +2022-11-14 16:10:36,047 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0717) Prec@1 90.000 (88.143) Prec@5 100.000 (99.317) +2022-11-14 16:10:36,057 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0712) Prec@1 93.000 (88.219) Prec@5 100.000 (99.328) +2022-11-14 16:10:36,068 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0714) Prec@1 88.000 (88.215) Prec@5 100.000 (99.338) +2022-11-14 16:10:36,078 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0715) Prec@1 86.000 (88.182) Prec@5 100.000 (99.348) +2022-11-14 16:10:36,087 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0711) Prec@1 93.000 (88.254) Prec@5 100.000 (99.358) +2022-11-14 16:10:36,099 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0711) Prec@1 89.000 (88.265) Prec@5 99.000 (99.353) +2022-11-14 16:10:36,109 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0399 (0.0706) Prec@1 95.000 (88.362) Prec@5 99.000 (99.348) +2022-11-14 16:10:36,119 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0707) Prec@1 87.000 (88.343) Prec@5 99.000 (99.343) +2022-11-14 16:10:36,131 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0711) Prec@1 87.000 (88.324) Prec@5 100.000 (99.352) +2022-11-14 16:10:36,143 Test: [71/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0709) Prec@1 89.000 (88.333) Prec@5 100.000 (99.361) +2022-11-14 16:10:36,158 Test: [72/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0706) Prec@1 93.000 (88.397) Prec@5 100.000 (99.370) +2022-11-14 16:10:36,168 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0404 (0.0702) Prec@1 94.000 (88.473) Prec@5 99.000 (99.365) +2022-11-14 16:10:36,177 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0705) Prec@1 86.000 (88.440) Prec@5 100.000 (99.373) +2022-11-14 16:10:36,187 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0703) Prec@1 89.000 (88.447) Prec@5 99.000 (99.368) +2022-11-14 16:10:36,199 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0703) Prec@1 89.000 (88.455) Prec@5 97.000 (99.338) +2022-11-14 16:10:36,210 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0706) Prec@1 84.000 (88.397) Prec@5 98.000 (99.321) +2022-11-14 16:10:36,219 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0707) Prec@1 87.000 (88.380) Prec@5 100.000 (99.329) +2022-11-14 16:10:36,228 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0708) Prec@1 86.000 (88.350) Prec@5 99.000 (99.325) +2022-11-14 16:10:36,239 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0710) Prec@1 86.000 (88.321) Prec@5 98.000 (99.309) +2022-11-14 16:10:36,248 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0709) Prec@1 87.000 (88.305) Prec@5 100.000 (99.317) +2022-11-14 16:10:36,259 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0711) Prec@1 84.000 (88.253) Prec@5 100.000 (99.325) +2022-11-14 16:10:36,269 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0709) Prec@1 89.000 (88.262) Prec@5 99.000 (99.321) +2022-11-14 16:10:36,279 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0711) Prec@1 85.000 (88.224) Prec@5 99.000 (99.318) +2022-11-14 16:10:36,289 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1205 (0.0717) Prec@1 82.000 (88.151) Prec@5 98.000 (99.302) +2022-11-14 16:10:36,299 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0723 (0.0717) Prec@1 86.000 (88.126) Prec@5 100.000 (99.310) +2022-11-14 16:10:36,310 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0717) Prec@1 89.000 (88.136) Prec@5 99.000 (99.307) +2022-11-14 16:10:36,321 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0715) Prec@1 89.000 (88.146) Prec@5 100.000 (99.315) +2022-11-14 16:10:36,331 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0715) Prec@1 90.000 (88.167) Prec@5 99.000 (99.311) +2022-11-14 16:10:36,341 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0715) Prec@1 88.000 (88.165) Prec@5 100.000 (99.319) +2022-11-14 16:10:36,352 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0714) Prec@1 89.000 (88.174) Prec@5 99.000 (99.315) +2022-11-14 16:10:36,362 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0717) Prec@1 83.000 (88.118) Prec@5 100.000 (99.323) +2022-11-14 16:10:36,371 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0720) Prec@1 84.000 (88.074) Prec@5 98.000 (99.309) +2022-11-14 16:10:36,380 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0720) Prec@1 86.000 (88.053) Prec@5 99.000 (99.305) +2022-11-14 16:10:36,389 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0719) Prec@1 93.000 (88.104) Prec@5 98.000 (99.292) +2022-11-14 16:10:36,400 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0470 (0.0716) Prec@1 93.000 (88.155) Prec@5 98.000 (99.278) +2022-11-14 16:10:36,411 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0717) Prec@1 87.000 (88.143) Prec@5 99.000 (99.276) +2022-11-14 16:10:36,420 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1260 (0.0722) Prec@1 80.000 (88.061) Prec@5 98.000 (99.263) +2022-11-14 16:10:36,430 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0721) Prec@1 90.000 (88.080) Prec@5 100.000 (99.270) +2022-11-14 16:10:36,504 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:10:36,862 Epoch: [312][0/500] Time 0.024 (0.024) Data 0.265 (0.265) Loss 0.0400 (0.0400) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:10:37,688 Epoch: [312][10/500] Time 0.086 (0.070) Data 0.002 (0.026) Loss 0.0219 (0.0310) Prec@1 96.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:10:38,520 Epoch: [312][20/500] Time 0.075 (0.071) Data 0.002 (0.015) Loss 0.0163 (0.0261) Prec@1 96.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:10:39,354 Epoch: [312][30/500] Time 0.063 (0.072) Data 0.002 (0.011) Loss 0.0284 (0.0267) Prec@1 95.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 16:10:40,156 Epoch: [312][40/500] Time 0.093 (0.072) Data 0.002 (0.008) Loss 0.0193 (0.0252) Prec@1 96.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 16:10:40,749 Epoch: [312][50/500] Time 0.048 (0.069) Data 0.002 (0.007) Loss 0.0412 (0.0279) Prec@1 94.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:10:41,217 Epoch: [312][60/500] Time 0.043 (0.064) Data 0.002 (0.006) Loss 0.0405 (0.0297) Prec@1 93.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:10:41,689 Epoch: [312][70/500] Time 0.040 (0.061) Data 0.002 (0.006) Loss 0.0230 (0.0288) Prec@1 96.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 16:10:42,143 Epoch: [312][80/500] Time 0.043 (0.059) Data 0.002 (0.005) Loss 0.0423 (0.0303) Prec@1 94.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 16:10:42,607 Epoch: [312][90/500] Time 0.040 (0.057) Data 0.002 (0.005) Loss 0.0411 (0.0314) Prec@1 94.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 16:10:43,073 Epoch: [312][100/500] Time 0.040 (0.055) Data 0.002 (0.005) Loss 0.0239 (0.0307) Prec@1 96.000 (94.909) Prec@5 100.000 (99.818) +2022-11-14 16:10:43,538 Epoch: [312][110/500] Time 0.049 (0.054) Data 0.002 (0.004) Loss 0.0221 (0.0300) Prec@1 97.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 16:10:44,014 Epoch: [312][120/500] Time 0.044 (0.053) Data 0.002 (0.004) Loss 0.0409 (0.0308) Prec@1 93.000 (94.923) Prec@5 99.000 (99.769) +2022-11-14 16:10:44,482 Epoch: [312][130/500] Time 0.044 (0.052) Data 0.002 (0.004) Loss 0.0315 (0.0309) Prec@1 94.000 (94.857) Prec@5 100.000 (99.786) +2022-11-14 16:10:44,951 Epoch: [312][140/500] Time 0.050 (0.051) Data 0.002 (0.004) Loss 0.0242 (0.0304) Prec@1 96.000 (94.933) Prec@5 100.000 (99.800) +2022-11-14 16:10:45,428 Epoch: [312][150/500] Time 0.038 (0.051) Data 0.003 (0.004) Loss 0.0467 (0.0315) Prec@1 94.000 (94.875) Prec@5 100.000 (99.812) +2022-11-14 16:10:45,906 Epoch: [312][160/500] Time 0.040 (0.050) Data 0.002 (0.004) Loss 0.0334 (0.0316) Prec@1 94.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:10:46,380 Epoch: [312][170/500] Time 0.038 (0.050) Data 0.002 (0.004) Loss 0.0278 (0.0314) Prec@1 95.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:10:46,855 Epoch: [312][180/500] Time 0.047 (0.049) Data 0.002 (0.004) Loss 0.0287 (0.0312) Prec@1 95.000 (94.842) Prec@5 100.000 (99.842) +2022-11-14 16:10:47,324 Epoch: [312][190/500] Time 0.040 (0.049) Data 0.002 (0.003) Loss 0.0400 (0.0317) Prec@1 93.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 16:10:47,803 Epoch: [312][200/500] Time 0.044 (0.049) Data 0.002 (0.003) Loss 0.0316 (0.0317) Prec@1 95.000 (94.762) Prec@5 100.000 (99.857) +2022-11-14 16:10:48,269 Epoch: [312][210/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0158 (0.0309) Prec@1 99.000 (94.955) Prec@5 100.000 (99.864) +2022-11-14 16:10:48,745 Epoch: [312][220/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0309 (0.0309) Prec@1 94.000 (94.913) Prec@5 99.000 (99.826) +2022-11-14 16:10:49,222 Epoch: [312][230/500] Time 0.042 (0.048) Data 0.002 (0.003) Loss 0.0346 (0.0311) Prec@1 95.000 (94.917) Prec@5 99.000 (99.792) +2022-11-14 16:10:49,684 Epoch: [312][240/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0416 (0.0315) Prec@1 92.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:10:50,163 Epoch: [312][250/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0164 (0.0309) Prec@1 97.000 (94.885) Prec@5 100.000 (99.808) +2022-11-14 16:10:50,639 Epoch: [312][260/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0173 (0.0304) Prec@1 97.000 (94.963) Prec@5 100.000 (99.815) +2022-11-14 16:10:51,112 Epoch: [312][270/500] Time 0.038 (0.047) Data 0.002 (0.003) Loss 0.0204 (0.0301) Prec@1 96.000 (95.000) Prec@5 100.000 (99.821) +2022-11-14 16:10:51,594 Epoch: [312][280/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0446 (0.0306) Prec@1 92.000 (94.897) Prec@5 99.000 (99.793) +2022-11-14 16:10:52,072 Epoch: [312][290/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0743 (0.0320) Prec@1 88.000 (94.667) Prec@5 98.000 (99.733) +2022-11-14 16:10:52,535 Epoch: [312][300/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0249 (0.0318) Prec@1 94.000 (94.645) Prec@5 100.000 (99.742) +2022-11-14 16:10:53,028 Epoch: [312][310/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0361 (0.0319) Prec@1 92.000 (94.562) Prec@5 99.000 (99.719) +2022-11-14 16:10:53,492 Epoch: [312][320/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0338 (0.0320) Prec@1 95.000 (94.576) Prec@5 100.000 (99.727) +2022-11-14 16:10:53,966 Epoch: [312][330/500] Time 0.047 (0.046) Data 0.003 (0.003) Loss 0.0295 (0.0319) Prec@1 95.000 (94.588) Prec@5 99.000 (99.706) +2022-11-14 16:10:54,431 Epoch: [312][340/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0535 (0.0325) Prec@1 91.000 (94.486) Prec@5 99.000 (99.686) +2022-11-14 16:10:54,901 Epoch: [312][350/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0428 (0.0328) Prec@1 92.000 (94.417) Prec@5 100.000 (99.694) +2022-11-14 16:10:55,380 Epoch: [312][360/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0476 (0.0332) Prec@1 92.000 (94.351) Prec@5 100.000 (99.703) +2022-11-14 16:10:55,869 Epoch: [312][370/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0427 (0.0335) Prec@1 93.000 (94.316) Prec@5 99.000 (99.684) +2022-11-14 16:10:56,334 Epoch: [312][380/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0334 (0.0335) Prec@1 94.000 (94.308) Prec@5 100.000 (99.692) +2022-11-14 16:10:56,814 Epoch: [312][390/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0316 (0.0334) Prec@1 95.000 (94.325) Prec@5 100.000 (99.700) +2022-11-14 16:10:57,304 Epoch: [312][400/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0397 (0.0336) Prec@1 93.000 (94.293) Prec@5 100.000 (99.707) +2022-11-14 16:10:57,792 Epoch: [312][410/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0552 (0.0341) Prec@1 90.000 (94.190) Prec@5 100.000 (99.714) +2022-11-14 16:10:58,259 Epoch: [312][420/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0403 (0.0342) Prec@1 95.000 (94.209) Prec@5 100.000 (99.721) +2022-11-14 16:10:58,729 Epoch: [312][430/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0289 (0.0341) Prec@1 95.000 (94.227) Prec@5 100.000 (99.727) +2022-11-14 16:10:59,188 Epoch: [312][440/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0422 (0.0343) Prec@1 92.000 (94.178) Prec@5 100.000 (99.733) +2022-11-14 16:10:59,674 Epoch: [312][450/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0318 (0.0342) Prec@1 94.000 (94.174) Prec@5 100.000 (99.739) +2022-11-14 16:11:00,146 Epoch: [312][460/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0242 (0.0340) Prec@1 95.000 (94.191) Prec@5 100.000 (99.745) +2022-11-14 16:11:00,637 Epoch: [312][470/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0363 (0.0341) Prec@1 94.000 (94.188) Prec@5 100.000 (99.750) +2022-11-14 16:11:01,107 Epoch: [312][480/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0544 (0.0345) Prec@1 93.000 (94.163) Prec@5 99.000 (99.735) +2022-11-14 16:11:01,588 Epoch: [312][490/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0480 (0.0348) Prec@1 93.000 (94.140) Prec@5 100.000 (99.740) +2022-11-14 16:11:02,010 Epoch: [312][499/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0400 (0.0349) Prec@1 94.000 (94.137) Prec@5 100.000 (99.745) +2022-11-14 16:11:02,334 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0609 (0.0609) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 16:11:02,342 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0647) Prec@1 90.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 16:11:02,352 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0673) Prec@1 88.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 16:11:02,364 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0703) Prec@1 86.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 16:11:02,373 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0704) Prec@1 87.000 (88.400) Prec@5 100.000 (99.400) +2022-11-14 16:11:02,382 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0657) Prec@1 93.000 (89.167) Prec@5 100.000 (99.500) +2022-11-14 16:11:02,391 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0645) Prec@1 90.000 (89.286) Prec@5 100.000 (99.571) +2022-11-14 16:11:02,404 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0672) Prec@1 85.000 (88.750) Prec@5 100.000 (99.625) +2022-11-14 16:11:02,416 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0682) Prec@1 87.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 16:11:02,430 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0688) Prec@1 88.000 (88.500) Prec@5 99.000 (99.600) +2022-11-14 16:11:02,446 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0688) Prec@1 88.000 (88.455) Prec@5 100.000 (99.636) +2022-11-14 16:11:02,460 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0692) Prec@1 87.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:11:02,475 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0672) Prec@1 93.000 (88.692) Prec@5 100.000 (99.692) +2022-11-14 16:11:02,489 Test: [13/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0678) Prec@1 87.000 (88.571) Prec@5 100.000 (99.714) +2022-11-14 16:11:02,506 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0688) Prec@1 88.000 (88.533) Prec@5 100.000 (99.733) +2022-11-14 16:11:02,523 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0690) Prec@1 85.000 (88.312) Prec@5 100.000 (99.750) +2022-11-14 16:11:02,540 Test: [16/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0416 (0.0674) Prec@1 95.000 (88.706) Prec@5 98.000 (99.647) +2022-11-14 16:11:02,558 Test: [17/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1301 (0.0709) Prec@1 80.000 (88.222) Prec@5 100.000 (99.667) +2022-11-14 16:11:02,576 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0716) Prec@1 85.000 (88.053) Prec@5 98.000 (99.579) +2022-11-14 16:11:02,592 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0726) Prec@1 84.000 (87.850) Prec@5 98.000 (99.500) +2022-11-14 16:11:02,607 Test: [20/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0722) Prec@1 90.000 (87.952) Prec@5 99.000 (99.476) +2022-11-14 16:11:02,622 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0728) Prec@1 85.000 (87.818) Prec@5 99.000 (99.455) +2022-11-14 16:11:02,636 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0737) Prec@1 85.000 (87.696) Prec@5 98.000 (99.391) +2022-11-14 16:11:02,652 Test: [23/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0737) Prec@1 87.000 (87.667) Prec@5 100.000 (99.417) +2022-11-14 16:11:02,671 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0741) Prec@1 87.000 (87.640) Prec@5 100.000 (99.440) +2022-11-14 16:11:02,686 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0749) Prec@1 86.000 (87.577) Prec@5 98.000 (99.385) +2022-11-14 16:11:02,703 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0746) Prec@1 89.000 (87.630) Prec@5 100.000 (99.407) +2022-11-14 16:11:02,719 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0740) Prec@1 90.000 (87.714) Prec@5 100.000 (99.429) +2022-11-14 16:11:02,736 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0737) Prec@1 88.000 (87.724) Prec@5 99.000 (99.414) +2022-11-14 16:11:02,752 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0745) Prec@1 83.000 (87.567) Prec@5 99.000 (99.400) +2022-11-14 16:11:02,767 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0746) Prec@1 85.000 (87.484) Prec@5 100.000 (99.419) +2022-11-14 16:11:02,781 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0752) Prec@1 84.000 (87.375) Prec@5 100.000 (99.438) +2022-11-14 16:11:02,797 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0751) Prec@1 89.000 (87.424) Prec@5 100.000 (99.455) +2022-11-14 16:11:02,812 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0757) Prec@1 86.000 (87.382) Prec@5 99.000 (99.441) +2022-11-14 16:11:02,830 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0760) Prec@1 87.000 (87.371) Prec@5 99.000 (99.429) +2022-11-14 16:11:02,847 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0756) Prec@1 90.000 (87.444) Prec@5 99.000 (99.417) +2022-11-14 16:11:02,863 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0756) Prec@1 88.000 (87.459) Prec@5 98.000 (99.378) +2022-11-14 16:11:02,877 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0761) Prec@1 89.000 (87.500) Prec@5 99.000 (99.368) +2022-11-14 16:11:02,895 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0758) Prec@1 92.000 (87.615) Prec@5 99.000 (99.359) +2022-11-14 16:11:02,912 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0754) Prec@1 89.000 (87.650) Prec@5 99.000 (99.350) +2022-11-14 16:11:02,929 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0756) Prec@1 87.000 (87.634) Prec@5 98.000 (99.317) +2022-11-14 16:11:02,944 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0756) Prec@1 85.000 (87.571) Prec@5 100.000 (99.333) +2022-11-14 16:11:02,962 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0752) Prec@1 89.000 (87.605) Prec@5 100.000 (99.349) +2022-11-14 16:11:02,980 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0551 (0.0747) Prec@1 94.000 (87.750) Prec@5 97.000 (99.295) +2022-11-14 16:11:02,996 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0749) Prec@1 85.000 (87.689) Prec@5 100.000 (99.311) +2022-11-14 16:11:03,010 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0755) Prec@1 85.000 (87.630) Prec@5 98.000 (99.283) +2022-11-14 16:11:03,026 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0757) Prec@1 84.000 (87.553) Prec@5 99.000 (99.277) +2022-11-14 16:11:03,042 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0765) Prec@1 81.000 (87.417) Prec@5 99.000 (99.271) +2022-11-14 16:11:03,058 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0762) Prec@1 88.000 (87.429) Prec@5 98.000 (99.245) +2022-11-14 16:11:03,075 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1145 (0.0769) Prec@1 83.000 (87.340) Prec@5 98.000 (99.220) +2022-11-14 16:11:03,091 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0771) Prec@1 85.000 (87.294) Prec@5 100.000 (99.235) +2022-11-14 16:11:03,110 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.0776) Prec@1 86.000 (87.269) Prec@5 99.000 (99.231) +2022-11-14 16:11:03,128 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0771) Prec@1 90.000 (87.321) Prec@5 100.000 (99.245) +2022-11-14 16:11:03,145 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0771) Prec@1 89.000 (87.352) Prec@5 100.000 (99.259) +2022-11-14 16:11:03,161 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0774) Prec@1 85.000 (87.309) Prec@5 100.000 (99.273) +2022-11-14 16:11:03,174 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0770) Prec@1 90.000 (87.357) Prec@5 99.000 (99.268) +2022-11-14 16:11:03,189 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0770) Prec@1 87.000 (87.351) Prec@5 99.000 (99.263) +2022-11-14 16:11:03,207 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0769) Prec@1 89.000 (87.379) Prec@5 100.000 (99.276) +2022-11-14 16:11:03,224 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1184 (0.0776) Prec@1 81.000 (87.271) Prec@5 99.000 (99.271) +2022-11-14 16:11:03,238 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0774) Prec@1 87.000 (87.267) Prec@5 100.000 (99.283) +2022-11-14 16:11:03,252 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0774) Prec@1 87.000 (87.262) Prec@5 100.000 (99.295) +2022-11-14 16:11:03,269 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0772) Prec@1 88.000 (87.274) Prec@5 98.000 (99.274) +2022-11-14 16:11:03,285 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0768) Prec@1 90.000 (87.317) Prec@5 99.000 (99.270) +2022-11-14 16:11:03,301 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0764) Prec@1 93.000 (87.406) Prec@5 99.000 (99.266) +2022-11-14 16:11:03,318 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0765) Prec@1 87.000 (87.400) Prec@5 99.000 (99.262) +2022-11-14 16:11:03,334 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0764) Prec@1 91.000 (87.455) Prec@5 99.000 (99.258) +2022-11-14 16:11:03,350 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0762) Prec@1 86.000 (87.433) Prec@5 100.000 (99.269) +2022-11-14 16:11:03,364 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0762) Prec@1 91.000 (87.485) Prec@5 98.000 (99.250) +2022-11-14 16:11:03,380 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0764) Prec@1 84.000 (87.435) Prec@5 100.000 (99.261) +2022-11-14 16:11:03,395 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0766) Prec@1 85.000 (87.400) Prec@5 99.000 (99.257) +2022-11-14 16:11:03,410 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0770) Prec@1 84.000 (87.352) Prec@5 99.000 (99.254) +2022-11-14 16:11:03,426 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0770) Prec@1 88.000 (87.361) Prec@5 100.000 (99.264) +2022-11-14 16:11:03,441 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0767) Prec@1 89.000 (87.384) Prec@5 100.000 (99.274) +2022-11-14 16:11:03,457 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0381 (0.0762) Prec@1 95.000 (87.486) Prec@5 100.000 (99.284) +2022-11-14 16:11:03,475 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0766) Prec@1 84.000 (87.440) Prec@5 99.000 (99.280) +2022-11-14 16:11:03,491 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0764) Prec@1 90.000 (87.474) Prec@5 99.000 (99.276) +2022-11-14 16:11:03,507 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0764) Prec@1 87.000 (87.468) Prec@5 99.000 (99.273) +2022-11-14 16:11:03,523 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0765) Prec@1 87.000 (87.462) Prec@5 98.000 (99.256) +2022-11-14 16:11:03,540 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0765) Prec@1 85.000 (87.430) Prec@5 100.000 (99.266) +2022-11-14 16:11:03,555 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0765) Prec@1 85.000 (87.400) Prec@5 98.000 (99.250) +2022-11-14 16:11:03,573 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0765) Prec@1 89.000 (87.420) Prec@5 99.000 (99.247) +2022-11-14 16:11:03,588 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0765) Prec@1 89.000 (87.439) Prec@5 100.000 (99.256) +2022-11-14 16:11:03,604 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0766) Prec@1 84.000 (87.398) Prec@5 100.000 (99.265) +2022-11-14 16:11:03,620 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0767) Prec@1 87.000 (87.393) Prec@5 99.000 (99.262) +2022-11-14 16:11:03,634 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0769) Prec@1 86.000 (87.376) Prec@5 99.000 (99.259) +2022-11-14 16:11:03,651 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0772) Prec@1 85.000 (87.349) Prec@5 100.000 (99.267) +2022-11-14 16:11:03,668 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0770) Prec@1 89.000 (87.368) Prec@5 99.000 (99.264) +2022-11-14 16:11:03,686 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0771) Prec@1 85.000 (87.341) Prec@5 98.000 (99.250) +2022-11-14 16:11:03,703 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0772) Prec@1 87.000 (87.337) Prec@5 100.000 (99.258) +2022-11-14 16:11:03,718 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0772) Prec@1 89.000 (87.356) Prec@5 99.000 (99.256) +2022-11-14 16:11:03,736 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0770) Prec@1 90.000 (87.385) Prec@5 100.000 (99.264) +2022-11-14 16:11:03,752 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0768) Prec@1 93.000 (87.446) Prec@5 100.000 (99.272) +2022-11-14 16:11:03,767 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0767) Prec@1 87.000 (87.441) Prec@5 100.000 (99.280) +2022-11-14 16:11:03,781 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0767) Prec@1 88.000 (87.447) Prec@5 99.000 (99.277) +2022-11-14 16:11:03,798 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0769) Prec@1 84.000 (87.411) Prec@5 98.000 (99.263) +2022-11-14 16:11:03,814 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0769) Prec@1 90.000 (87.438) Prec@5 98.000 (99.250) +2022-11-14 16:11:03,828 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0456 (0.0766) Prec@1 92.000 (87.485) Prec@5 98.000 (99.237) +2022-11-14 16:11:03,844 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0767) Prec@1 88.000 (87.490) Prec@5 99.000 (99.235) +2022-11-14 16:11:03,861 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0770) Prec@1 84.000 (87.455) Prec@5 99.000 (99.232) +2022-11-14 16:11:03,878 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0767) Prec@1 94.000 (87.520) Prec@5 100.000 (99.240) +2022-11-14 16:11:03,942 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:11:04,311 Epoch: [313][0/500] Time 0.024 (0.024) Data 0.282 (0.282) Loss 0.0356 (0.0356) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:11:04,731 Epoch: [313][10/500] Time 0.053 (0.036) Data 0.002 (0.027) Loss 0.0306 (0.0331) Prec@1 95.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:11:05,207 Epoch: [313][20/500] Time 0.047 (0.039) Data 0.002 (0.015) Loss 0.0216 (0.0293) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:11:05,675 Epoch: [313][30/500] Time 0.042 (0.040) Data 0.003 (0.011) Loss 0.0197 (0.0269) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:11:06,143 Epoch: [313][40/500] Time 0.038 (0.040) Data 0.002 (0.009) Loss 0.0210 (0.0257) Prec@1 96.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 16:11:06,616 Epoch: [313][50/500] Time 0.048 (0.041) Data 0.002 (0.008) Loss 0.0238 (0.0254) Prec@1 96.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:11:07,084 Epoch: [313][60/500] Time 0.045 (0.041) Data 0.002 (0.007) Loss 0.0554 (0.0297) Prec@1 91.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:11:07,580 Epoch: [313][70/500] Time 0.046 (0.041) Data 0.002 (0.006) Loss 0.0234 (0.0289) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:11:08,053 Epoch: [313][80/500] Time 0.050 (0.041) Data 0.002 (0.006) Loss 0.0254 (0.0285) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:11:08,532 Epoch: [313][90/500] Time 0.051 (0.042) Data 0.002 (0.005) Loss 0.0303 (0.0287) Prec@1 95.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 16:11:09,085 Epoch: [313][100/500] Time 0.041 (0.043) Data 0.002 (0.005) Loss 0.0408 (0.0298) Prec@1 92.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:11:09,561 Epoch: [313][110/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.0097 (0.0281) Prec@1 99.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:11:10,039 Epoch: [313][120/500] Time 0.038 (0.043) Data 0.002 (0.004) Loss 0.0332 (0.0285) Prec@1 94.000 (95.231) Prec@5 100.000 (100.000) +2022-11-14 16:11:10,535 Epoch: [313][130/500] Time 0.055 (0.043) Data 0.002 (0.004) Loss 0.0281 (0.0285) Prec@1 96.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 16:11:11,018 Epoch: [313][140/500] Time 0.046 (0.043) Data 0.002 (0.004) Loss 0.0234 (0.0281) Prec@1 97.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:11:11,507 Epoch: [313][150/500] Time 0.040 (0.043) Data 0.002 (0.004) Loss 0.0167 (0.0274) Prec@1 98.000 (95.562) Prec@5 100.000 (100.000) +2022-11-14 16:11:11,997 Epoch: [313][160/500] Time 0.052 (0.043) Data 0.002 (0.004) Loss 0.0314 (0.0277) Prec@1 94.000 (95.471) Prec@5 100.000 (100.000) +2022-11-14 16:11:12,579 Epoch: [313][170/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.0435 (0.0285) Prec@1 93.000 (95.333) Prec@5 99.000 (99.944) +2022-11-14 16:11:13,070 Epoch: [313][180/500] Time 0.051 (0.043) Data 0.002 (0.004) Loss 0.0323 (0.0287) Prec@1 95.000 (95.316) Prec@5 100.000 (99.947) +2022-11-14 16:11:13,531 Epoch: [313][190/500] Time 0.054 (0.043) Data 0.003 (0.004) Loss 0.0304 (0.0288) Prec@1 97.000 (95.400) Prec@5 100.000 (99.950) +2022-11-14 16:11:14,013 Epoch: [313][200/500] Time 0.043 (0.043) Data 0.003 (0.004) Loss 0.0264 (0.0287) Prec@1 95.000 (95.381) Prec@5 100.000 (99.952) +2022-11-14 16:11:14,492 Epoch: [313][210/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0499 (0.0297) Prec@1 90.000 (95.136) Prec@5 100.000 (99.955) +2022-11-14 16:11:15,007 Epoch: [313][220/500] Time 0.073 (0.043) Data 0.002 (0.003) Loss 0.0299 (0.0297) Prec@1 95.000 (95.130) Prec@5 100.000 (99.957) +2022-11-14 16:11:15,531 Epoch: [313][230/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0389 (0.0301) Prec@1 93.000 (95.042) Prec@5 100.000 (99.958) +2022-11-14 16:11:16,005 Epoch: [313][240/500] Time 0.035 (0.043) Data 0.002 (0.003) Loss 0.0443 (0.0306) Prec@1 94.000 (95.000) Prec@5 100.000 (99.960) +2022-11-14 16:11:16,481 Epoch: [313][250/500] Time 0.040 (0.043) Data 0.002 (0.003) Loss 0.0393 (0.0310) Prec@1 95.000 (95.000) Prec@5 99.000 (99.923) +2022-11-14 16:11:16,971 Epoch: [313][260/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0403 (0.0313) Prec@1 94.000 (94.963) Prec@5 100.000 (99.926) +2022-11-14 16:11:17,441 Epoch: [313][270/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0334 (0.0314) Prec@1 95.000 (94.964) Prec@5 99.000 (99.893) +2022-11-14 16:11:17,932 Epoch: [313][280/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0274 (0.0312) Prec@1 95.000 (94.966) Prec@5 100.000 (99.897) +2022-11-14 16:11:18,394 Epoch: [313][290/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0300 (0.0312) Prec@1 96.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 16:11:18,880 Epoch: [313][300/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0411 (0.0315) Prec@1 92.000 (94.903) Prec@5 100.000 (99.903) +2022-11-14 16:11:19,357 Epoch: [313][310/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0324 (0.0316) Prec@1 95.000 (94.906) Prec@5 100.000 (99.906) +2022-11-14 16:11:19,847 Epoch: [313][320/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0543 (0.0322) Prec@1 91.000 (94.788) Prec@5 99.000 (99.879) +2022-11-14 16:11:20,332 Epoch: [313][330/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0583 (0.0330) Prec@1 90.000 (94.647) Prec@5 100.000 (99.882) +2022-11-14 16:11:20,810 Epoch: [313][340/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0403 (0.0332) Prec@1 93.000 (94.600) Prec@5 100.000 (99.886) +2022-11-14 16:11:21,285 Epoch: [313][350/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0387 (0.0334) Prec@1 91.000 (94.500) Prec@5 100.000 (99.889) +2022-11-14 16:11:21,765 Epoch: [313][360/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0153 (0.0329) Prec@1 97.000 (94.568) Prec@5 100.000 (99.892) +2022-11-14 16:11:22,249 Epoch: [313][370/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0258 (0.0327) Prec@1 97.000 (94.632) Prec@5 100.000 (99.895) +2022-11-14 16:11:22,726 Epoch: [313][380/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0383 (0.0328) Prec@1 96.000 (94.667) Prec@5 99.000 (99.872) +2022-11-14 16:11:23,206 Epoch: [313][390/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0238 (0.0326) Prec@1 94.000 (94.650) Prec@5 100.000 (99.875) +2022-11-14 16:11:23,728 Epoch: [313][400/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0253 (0.0324) Prec@1 98.000 (94.732) Prec@5 100.000 (99.878) +2022-11-14 16:11:24,207 Epoch: [313][410/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0237 (0.0322) Prec@1 95.000 (94.738) Prec@5 100.000 (99.881) +2022-11-14 16:11:24,937 Epoch: [313][420/500] Time 0.128 (0.044) Data 0.002 (0.003) Loss 0.0410 (0.0324) Prec@1 93.000 (94.698) Prec@5 98.000 (99.837) +2022-11-14 16:11:25,768 Epoch: [313][430/500] Time 0.085 (0.044) Data 0.002 (0.003) Loss 0.0237 (0.0322) Prec@1 94.000 (94.682) Prec@5 100.000 (99.841) +2022-11-14 16:11:26,765 Epoch: [313][440/500] Time 0.070 (0.046) Data 0.002 (0.003) Loss 0.0271 (0.0321) Prec@1 96.000 (94.711) Prec@5 100.000 (99.844) +2022-11-14 16:11:27,619 Epoch: [313][450/500] Time 0.069 (0.046) Data 0.002 (0.003) Loss 0.0271 (0.0320) Prec@1 95.000 (94.717) Prec@5 100.000 (99.848) +2022-11-14 16:11:28,473 Epoch: [313][460/500] Time 0.078 (0.047) Data 0.003 (0.003) Loss 0.0378 (0.0321) Prec@1 94.000 (94.702) Prec@5 100.000 (99.851) +2022-11-14 16:11:29,333 Epoch: [313][470/500] Time 0.077 (0.048) Data 0.002 (0.003) Loss 0.0280 (0.0320) Prec@1 96.000 (94.729) Prec@5 100.000 (99.854) +2022-11-14 16:11:30,332 Epoch: [313][480/500] Time 0.109 (0.048) Data 0.002 (0.003) Loss 0.0365 (0.0321) Prec@1 94.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:11:31,133 Epoch: [313][490/500] Time 0.074 (0.049) Data 0.002 (0.003) Loss 0.0429 (0.0324) Prec@1 93.000 (94.680) Prec@5 100.000 (99.860) +2022-11-14 16:11:31,868 Epoch: [313][499/500] Time 0.086 (0.049) Data 0.002 (0.003) Loss 0.0304 (0.0323) Prec@1 93.000 (94.647) Prec@5 100.000 (99.863) +2022-11-14 16:11:32,229 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0806 (0.0806) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:11:32,282 Test: [1/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0656 (0.0731) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:11:32,320 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0708 (0.0723) Prec@1 90.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:11:32,354 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0766 (0.0734) Prec@1 89.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 16:11:32,389 Test: [4/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0932 (0.0774) Prec@1 84.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 16:11:32,420 Test: [5/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0515 (0.0731) Prec@1 92.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:11:32,453 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0716 (0.0728) Prec@1 87.000 (88.286) Prec@5 100.000 (99.571) +2022-11-14 16:11:32,492 Test: [7/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0918 (0.0752) Prec@1 84.000 (87.750) Prec@5 100.000 (99.625) +2022-11-14 16:11:32,528 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0747 (0.0752) Prec@1 90.000 (88.000) Prec@5 99.000 (99.556) +2022-11-14 16:11:32,559 Test: [9/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0906 (0.0767) Prec@1 86.000 (87.800) Prec@5 99.000 (99.500) +2022-11-14 16:11:32,583 Test: [10/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0553 (0.0748) Prec@1 91.000 (88.091) Prec@5 100.000 (99.545) +2022-11-14 16:11:32,616 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0740) Prec@1 90.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 16:11:32,644 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0526 (0.0724) Prec@1 90.000 (88.385) Prec@5 100.000 (99.538) +2022-11-14 16:11:32,676 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0724) Prec@1 89.000 (88.429) Prec@5 98.000 (99.429) +2022-11-14 16:11:32,703 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0902 (0.0736) Prec@1 85.000 (88.200) Prec@5 100.000 (99.467) +2022-11-14 16:11:32,738 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0743) Prec@1 86.000 (88.062) Prec@5 99.000 (99.438) +2022-11-14 16:11:32,769 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0387 (0.0722) Prec@1 94.000 (88.412) Prec@5 98.000 (99.353) +2022-11-14 16:11:32,799 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0905 (0.0732) Prec@1 83.000 (88.111) Prec@5 100.000 (99.389) +2022-11-14 16:11:32,829 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0736) Prec@1 86.000 (88.000) Prec@5 100.000 (99.421) +2022-11-14 16:11:32,867 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0743) Prec@1 88.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 16:11:32,897 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0738) Prec@1 90.000 (88.095) Prec@5 100.000 (99.429) +2022-11-14 16:11:32,933 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0744) Prec@1 86.000 (88.000) Prec@5 99.000 (99.409) +2022-11-14 16:11:32,966 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0746) Prec@1 88.000 (88.000) Prec@5 98.000 (99.348) +2022-11-14 16:11:32,999 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0742) Prec@1 88.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 16:11:33,028 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0751) Prec@1 86.000 (87.920) Prec@5 99.000 (99.360) +2022-11-14 16:11:33,062 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0754) Prec@1 85.000 (87.808) Prec@5 99.000 (99.346) +2022-11-14 16:11:33,099 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0528 (0.0746) Prec@1 91.000 (87.926) Prec@5 100.000 (99.370) +2022-11-14 16:11:33,135 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0739) Prec@1 90.000 (88.000) Prec@5 100.000 (99.393) +2022-11-14 16:11:33,166 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0735) Prec@1 90.000 (88.069) Prec@5 99.000 (99.379) +2022-11-14 16:11:33,201 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0738) Prec@1 86.000 (88.000) Prec@5 99.000 (99.367) +2022-11-14 16:11:33,241 Test: [30/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0737) Prec@1 88.000 (88.000) Prec@5 100.000 (99.387) +2022-11-14 16:11:33,278 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0734) Prec@1 88.000 (88.000) Prec@5 100.000 (99.406) +2022-11-14 16:11:33,302 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0732) Prec@1 88.000 (88.000) Prec@5 100.000 (99.424) +2022-11-14 16:11:33,334 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0736) Prec@1 85.000 (87.912) Prec@5 100.000 (99.441) +2022-11-14 16:11:33,364 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0735) Prec@1 90.000 (87.971) Prec@5 99.000 (99.429) +2022-11-14 16:11:33,396 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0735) Prec@1 90.000 (88.028) Prec@5 99.000 (99.417) +2022-11-14 16:11:33,432 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0738) Prec@1 86.000 (87.973) Prec@5 98.000 (99.378) +2022-11-14 16:11:33,470 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0744) Prec@1 86.000 (87.921) Prec@5 99.000 (99.368) +2022-11-14 16:11:33,508 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0743) Prec@1 87.000 (87.897) Prec@5 99.000 (99.359) +2022-11-14 16:11:33,540 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0745) Prec@1 87.000 (87.875) Prec@5 99.000 (99.350) +2022-11-14 16:11:33,577 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0749) Prec@1 86.000 (87.829) Prec@5 99.000 (99.341) +2022-11-14 16:11:33,606 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0748) Prec@1 88.000 (87.833) Prec@5 100.000 (99.357) +2022-11-14 16:11:33,642 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0473 (0.0742) Prec@1 93.000 (87.953) Prec@5 99.000 (99.349) +2022-11-14 16:11:33,679 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0740) Prec@1 87.000 (87.932) Prec@5 98.000 (99.318) +2022-11-14 16:11:33,708 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0737) Prec@1 91.000 (88.000) Prec@5 99.000 (99.311) +2022-11-14 16:11:33,738 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1205 (0.0748) Prec@1 82.000 (87.870) Prec@5 98.000 (99.283) +2022-11-14 16:11:33,771 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0745) Prec@1 92.000 (87.957) Prec@5 100.000 (99.298) +2022-11-14 16:11:33,807 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1054 (0.0751) Prec@1 83.000 (87.854) Prec@5 99.000 (99.292) +2022-11-14 16:11:33,841 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0750) Prec@1 87.000 (87.837) Prec@5 99.000 (99.286) +2022-11-14 16:11:33,873 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1121 (0.0758) Prec@1 81.000 (87.700) Prec@5 100.000 (99.300) +2022-11-14 16:11:33,903 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0755) Prec@1 87.000 (87.686) Prec@5 100.000 (99.314) +2022-11-14 16:11:33,936 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0757) Prec@1 85.000 (87.635) Prec@5 100.000 (99.327) +2022-11-14 16:11:33,967 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0757) Prec@1 90.000 (87.679) Prec@5 100.000 (99.340) +2022-11-14 16:11:34,002 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0755) Prec@1 90.000 (87.722) Prec@5 99.000 (99.333) +2022-11-14 16:11:34,035 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0754) Prec@1 86.000 (87.691) Prec@5 100.000 (99.345) +2022-11-14 16:11:34,058 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0755) Prec@1 86.000 (87.661) Prec@5 99.000 (99.339) +2022-11-14 16:11:34,096 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0754) Prec@1 89.000 (87.684) Prec@5 100.000 (99.351) +2022-11-14 16:11:34,130 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0753) Prec@1 90.000 (87.724) Prec@5 99.000 (99.345) +2022-11-14 16:11:34,161 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0755) Prec@1 87.000 (87.712) Prec@5 100.000 (99.356) +2022-11-14 16:11:34,188 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0754) Prec@1 88.000 (87.717) Prec@5 100.000 (99.367) +2022-11-14 16:11:34,218 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0754) Prec@1 90.000 (87.754) Prec@5 99.000 (99.361) +2022-11-14 16:11:34,251 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0751) Prec@1 89.000 (87.774) Prec@5 99.000 (99.355) +2022-11-14 16:11:34,287 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0749) Prec@1 87.000 (87.762) Prec@5 99.000 (99.349) +2022-11-14 16:11:34,322 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0382 (0.0744) Prec@1 92.000 (87.828) Prec@5 100.000 (99.359) +2022-11-14 16:11:34,359 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0746) Prec@1 84.000 (87.769) Prec@5 100.000 (99.369) +2022-11-14 16:11:34,391 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0748) Prec@1 86.000 (87.742) Prec@5 100.000 (99.379) +2022-11-14 16:11:34,424 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0453 (0.0744) Prec@1 94.000 (87.836) Prec@5 100.000 (99.388) +2022-11-14 16:11:34,460 Test: [67/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0742) Prec@1 89.000 (87.853) Prec@5 99.000 (99.382) +2022-11-14 16:11:34,499 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0741) Prec@1 91.000 (87.899) Prec@5 99.000 (99.377) +2022-11-14 16:11:34,533 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0738) Prec@1 92.000 (87.957) Prec@5 99.000 (99.371) +2022-11-14 16:11:34,567 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0739) Prec@1 89.000 (87.972) Prec@5 98.000 (99.352) +2022-11-14 16:11:34,600 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0738) Prec@1 89.000 (87.986) Prec@5 100.000 (99.361) +2022-11-14 16:11:34,631 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0736) Prec@1 91.000 (88.027) Prec@5 100.000 (99.370) +2022-11-14 16:11:34,660 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0733) Prec@1 91.000 (88.068) Prec@5 100.000 (99.378) +2022-11-14 16:11:34,693 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0736) Prec@1 83.000 (88.000) Prec@5 100.000 (99.387) +2022-11-14 16:11:34,729 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0735) Prec@1 88.000 (88.000) Prec@5 100.000 (99.395) +2022-11-14 16:11:34,762 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0736) Prec@1 86.000 (87.974) Prec@5 99.000 (99.390) +2022-11-14 16:11:34,798 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0738) Prec@1 86.000 (87.949) Prec@5 99.000 (99.385) +2022-11-14 16:11:34,830 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0737) Prec@1 90.000 (87.975) Prec@5 100.000 (99.392) +2022-11-14 16:11:34,867 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0736) Prec@1 91.000 (88.013) Prec@5 100.000 (99.400) +2022-11-14 16:11:34,897 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0739) Prec@1 84.000 (87.963) Prec@5 98.000 (99.383) +2022-11-14 16:11:34,924 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0738) Prec@1 91.000 (88.000) Prec@5 100.000 (99.390) +2022-11-14 16:11:34,960 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0737) Prec@1 89.000 (88.012) Prec@5 100.000 (99.398) +2022-11-14 16:11:34,994 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0737) Prec@1 89.000 (88.024) Prec@5 99.000 (99.393) +2022-11-14 16:11:35,024 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 88.000 (88.024) Prec@5 99.000 (99.388) +2022-11-14 16:11:35,058 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1090 (0.0742) Prec@1 84.000 (87.977) Prec@5 100.000 (99.395) +2022-11-14 16:11:35,091 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0741) Prec@1 88.000 (87.977) Prec@5 100.000 (99.402) +2022-11-14 16:11:35,120 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0742) Prec@1 88.000 (87.977) Prec@5 99.000 (99.398) +2022-11-14 16:11:35,153 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0743) Prec@1 88.000 (87.978) Prec@5 100.000 (99.404) +2022-11-14 16:11:35,183 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0741) Prec@1 91.000 (88.011) Prec@5 99.000 (99.400) +2022-11-14 16:11:35,217 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0506 (0.0738) Prec@1 93.000 (88.066) Prec@5 100.000 (99.407) +2022-11-14 16:11:35,249 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0736) Prec@1 91.000 (88.098) Prec@5 100.000 (99.413) +2022-11-14 16:11:35,284 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0736) Prec@1 87.000 (88.086) Prec@5 100.000 (99.419) +2022-11-14 16:11:35,315 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0734) Prec@1 92.000 (88.128) Prec@5 99.000 (99.415) +2022-11-14 16:11:35,348 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0737) Prec@1 82.000 (88.063) Prec@5 100.000 (99.421) +2022-11-14 16:11:35,378 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0735) Prec@1 91.000 (88.094) Prec@5 99.000 (99.417) +2022-11-14 16:11:35,409 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0408 (0.0732) Prec@1 94.000 (88.155) Prec@5 100.000 (99.423) +2022-11-14 16:11:35,443 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0735) Prec@1 85.000 (88.122) Prec@5 100.000 (99.429) +2022-11-14 16:11:35,478 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0736) Prec@1 87.000 (88.111) Prec@5 99.000 (99.424) +2022-11-14 16:11:35,514 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0736) Prec@1 88.000 (88.110) Prec@5 100.000 (99.430) +2022-11-14 16:11:35,575 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:11:35,922 Epoch: [314][0/500] Time 0.024 (0.024) Data 0.262 (0.262) Loss 0.0288 (0.0288) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:11:36,223 Epoch: [314][10/500] Time 0.035 (0.027) Data 0.002 (0.025) Loss 0.0264 (0.0276) Prec@1 97.000 (96.000) Prec@5 100.000 (99.500) +2022-11-14 16:11:36,558 Epoch: [314][20/500] Time 0.031 (0.028) Data 0.002 (0.014) Loss 0.0345 (0.0299) Prec@1 92.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:11:36,878 Epoch: [314][30/500] Time 0.026 (0.028) Data 0.002 (0.010) Loss 0.0682 (0.0395) Prec@1 88.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 16:11:37,201 Epoch: [314][40/500] Time 0.033 (0.028) Data 0.002 (0.008) Loss 0.0284 (0.0373) Prec@1 96.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 16:11:37,532 Epoch: [314][50/500] Time 0.026 (0.029) Data 0.003 (0.007) Loss 0.0307 (0.0362) Prec@1 95.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 16:11:37,860 Epoch: [314][60/500] Time 0.032 (0.029) Data 0.002 (0.006) Loss 0.0170 (0.0334) Prec@1 97.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 16:11:38,266 Epoch: [314][70/500] Time 0.051 (0.029) Data 0.002 (0.006) Loss 0.0385 (0.0341) Prec@1 94.000 (94.250) Prec@5 99.000 (99.750) +2022-11-14 16:11:39,040 Epoch: [314][80/500] Time 0.101 (0.034) Data 0.002 (0.005) Loss 0.0264 (0.0332) Prec@1 94.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 16:11:39,723 Epoch: [314][90/500] Time 0.070 (0.037) Data 0.002 (0.005) Loss 0.0417 (0.0341) Prec@1 93.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 16:11:40,453 Epoch: [314][100/500] Time 0.096 (0.040) Data 0.002 (0.005) Loss 0.0263 (0.0334) Prec@1 97.000 (94.364) Prec@5 100.000 (99.818) +2022-11-14 16:11:41,132 Epoch: [314][110/500] Time 0.055 (0.042) Data 0.003 (0.004) Loss 0.0250 (0.0327) Prec@1 95.000 (94.417) Prec@5 100.000 (99.833) +2022-11-14 16:11:41,829 Epoch: [314][120/500] Time 0.073 (0.043) Data 0.002 (0.004) Loss 0.0355 (0.0329) Prec@1 92.000 (94.231) Prec@5 100.000 (99.846) +2022-11-14 16:11:42,550 Epoch: [314][130/500] Time 0.075 (0.045) Data 0.002 (0.004) Loss 0.0220 (0.0321) Prec@1 97.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 16:11:43,223 Epoch: [314][140/500] Time 0.059 (0.046) Data 0.002 (0.004) Loss 0.0338 (0.0322) Prec@1 94.000 (94.400) Prec@5 100.000 (99.867) +2022-11-14 16:11:43,990 Epoch: [314][150/500] Time 0.069 (0.048) Data 0.002 (0.004) Loss 0.0497 (0.0333) Prec@1 91.000 (94.188) Prec@5 99.000 (99.812) +2022-11-14 16:11:44,679 Epoch: [314][160/500] Time 0.077 (0.048) Data 0.002 (0.004) Loss 0.0315 (0.0332) Prec@1 95.000 (94.235) Prec@5 100.000 (99.824) +2022-11-14 16:11:45,484 Epoch: [314][170/500] Time 0.072 (0.050) Data 0.002 (0.004) Loss 0.0236 (0.0327) Prec@1 97.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 16:11:46,229 Epoch: [314][180/500] Time 0.068 (0.051) Data 0.002 (0.004) Loss 0.0333 (0.0327) Prec@1 96.000 (94.474) Prec@5 100.000 (99.842) +2022-11-14 16:11:46,908 Epoch: [314][190/500] Time 0.064 (0.051) Data 0.002 (0.003) Loss 0.0306 (0.0326) Prec@1 95.000 (94.500) Prec@5 100.000 (99.850) +2022-11-14 16:11:47,632 Epoch: [314][200/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0296 (0.0324) Prec@1 94.000 (94.476) Prec@5 100.000 (99.857) +2022-11-14 16:11:48,368 Epoch: [314][210/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0304 (0.0324) Prec@1 95.000 (94.500) Prec@5 100.000 (99.864) +2022-11-14 16:11:49,078 Epoch: [314][220/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0387 (0.0326) Prec@1 94.000 (94.478) Prec@5 99.000 (99.826) +2022-11-14 16:11:49,744 Epoch: [314][230/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0286 (0.0325) Prec@1 97.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 16:11:50,477 Epoch: [314][240/500] Time 0.072 (0.054) Data 0.002 (0.003) Loss 0.0224 (0.0321) Prec@1 96.000 (94.640) Prec@5 100.000 (99.840) +2022-11-14 16:11:51,156 Epoch: [314][250/500] Time 0.055 (0.054) Data 0.002 (0.003) Loss 0.0405 (0.0324) Prec@1 94.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 16:11:51,915 Epoch: [314][260/500] Time 0.071 (0.055) Data 0.002 (0.003) Loss 0.0283 (0.0322) Prec@1 96.000 (94.667) Prec@5 100.000 (99.852) +2022-11-14 16:11:52,591 Epoch: [314][270/500] Time 0.064 (0.055) Data 0.002 (0.003) Loss 0.0240 (0.0319) Prec@1 96.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:11:53,334 Epoch: [314][280/500] Time 0.087 (0.055) Data 0.002 (0.003) Loss 0.0262 (0.0317) Prec@1 96.000 (94.759) Prec@5 99.000 (99.828) +2022-11-14 16:11:54,032 Epoch: [314][290/500] Time 0.069 (0.056) Data 0.002 (0.003) Loss 0.0229 (0.0314) Prec@1 95.000 (94.767) Prec@5 100.000 (99.833) +2022-11-14 16:11:54,742 Epoch: [314][300/500] Time 0.068 (0.056) Data 0.002 (0.003) Loss 0.0255 (0.0313) Prec@1 96.000 (94.806) Prec@5 100.000 (99.839) +2022-11-14 16:11:55,412 Epoch: [314][310/500] Time 0.070 (0.056) Data 0.002 (0.003) Loss 0.0368 (0.0314) Prec@1 96.000 (94.844) Prec@5 100.000 (99.844) +2022-11-14 16:11:56,092 Epoch: [314][320/500] Time 0.051 (0.056) Data 0.002 (0.003) Loss 0.0358 (0.0316) Prec@1 94.000 (94.818) Prec@5 98.000 (99.788) +2022-11-14 16:11:56,850 Epoch: [314][330/500] Time 0.062 (0.057) Data 0.002 (0.003) Loss 0.0300 (0.0315) Prec@1 93.000 (94.765) Prec@5 100.000 (99.794) +2022-11-14 16:11:57,551 Epoch: [314][340/500] Time 0.067 (0.057) Data 0.002 (0.003) Loss 0.0355 (0.0316) Prec@1 96.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:11:58,231 Epoch: [314][350/500] Time 0.069 (0.057) Data 0.002 (0.003) Loss 0.0353 (0.0317) Prec@1 92.000 (94.722) Prec@5 97.000 (99.722) +2022-11-14 16:11:58,919 Epoch: [314][360/500] Time 0.072 (0.057) Data 0.002 (0.003) Loss 0.0203 (0.0314) Prec@1 98.000 (94.811) Prec@5 100.000 (99.730) +2022-11-14 16:11:59,689 Epoch: [314][370/500] Time 0.073 (0.057) Data 0.002 (0.003) Loss 0.0379 (0.0316) Prec@1 94.000 (94.789) Prec@5 100.000 (99.737) +2022-11-14 16:12:00,354 Epoch: [314][380/500] Time 0.064 (0.057) Data 0.002 (0.003) Loss 0.0386 (0.0318) Prec@1 92.000 (94.718) Prec@5 100.000 (99.744) +2022-11-14 16:12:01,027 Epoch: [314][390/500] Time 0.060 (0.057) Data 0.002 (0.003) Loss 0.0232 (0.0316) Prec@1 97.000 (94.775) Prec@5 100.000 (99.750) +2022-11-14 16:12:01,738 Epoch: [314][400/500] Time 0.070 (0.058) Data 0.002 (0.003) Loss 0.0302 (0.0315) Prec@1 94.000 (94.756) Prec@5 100.000 (99.756) +2022-11-14 16:12:02,407 Epoch: [314][410/500] Time 0.064 (0.058) Data 0.002 (0.003) Loss 0.0532 (0.0320) Prec@1 90.000 (94.643) Prec@5 99.000 (99.738) +2022-11-14 16:12:03,081 Epoch: [314][420/500] Time 0.071 (0.058) Data 0.002 (0.003) Loss 0.0312 (0.0320) Prec@1 95.000 (94.651) Prec@5 100.000 (99.744) +2022-11-14 16:12:03,756 Epoch: [314][430/500] Time 0.066 (0.058) Data 0.002 (0.003) Loss 0.0382 (0.0322) Prec@1 94.000 (94.636) Prec@5 100.000 (99.750) +2022-11-14 16:12:04,462 Epoch: [314][440/500] Time 0.064 (0.058) Data 0.002 (0.003) Loss 0.0523 (0.0326) Prec@1 91.000 (94.556) Prec@5 100.000 (99.756) +2022-11-14 16:12:05,125 Epoch: [314][450/500] Time 0.066 (0.058) Data 0.002 (0.003) Loss 0.0372 (0.0327) Prec@1 94.000 (94.543) Prec@5 100.000 (99.761) +2022-11-14 16:12:05,815 Epoch: [314][460/500] Time 0.061 (0.058) Data 0.002 (0.003) Loss 0.0308 (0.0327) Prec@1 94.000 (94.532) Prec@5 100.000 (99.766) +2022-11-14 16:12:06,488 Epoch: [314][470/500] Time 0.051 (0.058) Data 0.002 (0.003) Loss 0.0577 (0.0332) Prec@1 89.000 (94.417) Prec@5 100.000 (99.771) +2022-11-14 16:12:07,164 Epoch: [314][480/500] Time 0.072 (0.058) Data 0.002 (0.003) Loss 0.0364 (0.0333) Prec@1 93.000 (94.388) Prec@5 100.000 (99.776) +2022-11-14 16:12:07,897 Epoch: [314][490/500] Time 0.089 (0.058) Data 0.002 (0.003) Loss 0.0384 (0.0334) Prec@1 94.000 (94.380) Prec@5 99.000 (99.760) +2022-11-14 16:12:08,499 Epoch: [314][499/500] Time 0.062 (0.058) Data 0.002 (0.003) Loss 0.0342 (0.0334) Prec@1 96.000 (94.412) Prec@5 100.000 (99.765) +2022-11-14 16:12:08,812 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0622 (0.0622) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:12:08,824 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0495 (0.0559) Prec@1 92.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:12:08,835 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0449 (0.0522) Prec@1 92.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 16:12:08,848 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0669 (0.0559) Prec@1 89.000 (90.750) Prec@5 100.000 (99.750) +2022-11-14 16:12:08,860 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0614) Prec@1 86.000 (89.800) Prec@5 100.000 (99.800) +2022-11-14 16:12:08,870 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0501 (0.0595) Prec@1 92.000 (90.167) Prec@5 100.000 (99.833) +2022-11-14 16:12:08,879 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0582 (0.0593) Prec@1 91.000 (90.286) Prec@5 98.000 (99.571) +2022-11-14 16:12:08,893 Test: [7/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0636) Prec@1 81.000 (89.125) Prec@5 100.000 (99.625) +2022-11-14 16:12:08,903 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0788 (0.0653) Prec@1 87.000 (88.889) Prec@5 99.000 (99.556) +2022-11-14 16:12:08,913 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0665) Prec@1 88.000 (88.800) Prec@5 98.000 (99.400) +2022-11-14 16:12:08,923 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0665) Prec@1 89.000 (88.818) Prec@5 100.000 (99.455) +2022-11-14 16:12:08,934 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0684) Prec@1 84.000 (88.417) Prec@5 100.000 (99.500) +2022-11-14 16:12:08,946 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0673) Prec@1 90.000 (88.538) Prec@5 100.000 (99.538) +2022-11-14 16:12:08,956 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0668) Prec@1 91.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 16:12:08,968 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0680) Prec@1 86.000 (88.533) Prec@5 99.000 (99.533) +2022-11-14 16:12:08,978 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0687) Prec@1 88.000 (88.500) Prec@5 98.000 (99.438) +2022-11-14 16:12:08,988 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0680) Prec@1 91.000 (88.647) Prec@5 98.000 (99.353) +2022-11-14 16:12:08,998 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1172 (0.0707) Prec@1 83.000 (88.333) Prec@5 100.000 (99.389) +2022-11-14 16:12:09,008 Test: [18/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0715) Prec@1 86.000 (88.211) Prec@5 100.000 (99.421) +2022-11-14 16:12:09,017 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0724) Prec@1 86.000 (88.100) Prec@5 96.000 (99.250) +2022-11-14 16:12:09,027 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0719) Prec@1 90.000 (88.190) Prec@5 100.000 (99.286) +2022-11-14 16:12:09,037 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0719) Prec@1 88.000 (88.182) Prec@5 99.000 (99.273) +2022-11-14 16:12:09,047 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0728) Prec@1 86.000 (88.087) Prec@5 99.000 (99.261) +2022-11-14 16:12:09,058 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0727) Prec@1 89.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 16:12:09,069 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0741) Prec@1 84.000 (87.960) Prec@5 99.000 (99.240) +2022-11-14 16:12:09,079 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0744) Prec@1 87.000 (87.923) Prec@5 99.000 (99.231) +2022-11-14 16:12:09,090 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0735) Prec@1 91.000 (88.037) Prec@5 100.000 (99.259) +2022-11-14 16:12:09,101 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0728) Prec@1 90.000 (88.107) Prec@5 99.000 (99.250) +2022-11-14 16:12:09,111 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0730) Prec@1 87.000 (88.069) Prec@5 98.000 (99.207) +2022-11-14 16:12:09,121 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0732) Prec@1 86.000 (88.000) Prec@5 100.000 (99.233) +2022-11-14 16:12:09,132 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0726) Prec@1 92.000 (88.129) Prec@5 99.000 (99.226) +2022-11-14 16:12:09,144 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0728) Prec@1 88.000 (88.125) Prec@5 99.000 (99.219) +2022-11-14 16:12:09,155 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0728) Prec@1 89.000 (88.152) Prec@5 100.000 (99.242) +2022-11-14 16:12:09,165 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0733) Prec@1 83.000 (88.000) Prec@5 100.000 (99.265) +2022-11-14 16:12:09,174 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0736) Prec@1 87.000 (87.971) Prec@5 98.000 (99.229) +2022-11-14 16:12:09,184 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0735) Prec@1 89.000 (88.000) Prec@5 98.000 (99.194) +2022-11-14 16:12:09,195 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0734) Prec@1 89.000 (88.027) Prec@5 99.000 (99.189) +2022-11-14 16:12:09,205 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0737) Prec@1 86.000 (87.974) Prec@5 99.000 (99.184) +2022-11-14 16:12:09,216 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0732) Prec@1 94.000 (88.128) Prec@5 99.000 (99.179) +2022-11-14 16:12:09,227 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0732) Prec@1 85.000 (88.050) Prec@5 100.000 (99.200) +2022-11-14 16:12:09,237 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1060 (0.0740) Prec@1 85.000 (87.976) Prec@5 98.000 (99.171) +2022-11-14 16:12:09,247 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0738) Prec@1 88.000 (87.976) Prec@5 100.000 (99.190) +2022-11-14 16:12:09,257 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0734) Prec@1 88.000 (87.977) Prec@5 100.000 (99.209) +2022-11-14 16:12:09,267 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0730) Prec@1 92.000 (88.068) Prec@5 98.000 (99.182) +2022-11-14 16:12:09,277 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0728) Prec@1 90.000 (88.111) Prec@5 99.000 (99.178) +2022-11-14 16:12:09,286 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1173 (0.0737) Prec@1 83.000 (88.000) Prec@5 97.000 (99.130) +2022-11-14 16:12:09,295 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0738) Prec@1 87.000 (87.979) Prec@5 100.000 (99.149) +2022-11-14 16:12:09,306 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0745) Prec@1 82.000 (87.854) Prec@5 99.000 (99.146) +2022-11-14 16:12:09,316 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0743) Prec@1 90.000 (87.898) Prec@5 100.000 (99.163) +2022-11-14 16:12:09,326 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0748) Prec@1 86.000 (87.860) Prec@5 99.000 (99.160) +2022-11-14 16:12:09,337 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0743) Prec@1 92.000 (87.941) Prec@5 100.000 (99.176) +2022-11-14 16:12:09,349 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0741) Prec@1 89.000 (87.962) Prec@5 99.000 (99.173) +2022-11-14 16:12:09,359 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0741) Prec@1 85.000 (87.906) Prec@5 99.000 (99.170) +2022-11-14 16:12:09,370 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0739) Prec@1 89.000 (87.926) Prec@5 100.000 (99.185) +2022-11-14 16:12:09,380 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0742) Prec@1 86.000 (87.891) Prec@5 100.000 (99.200) +2022-11-14 16:12:09,390 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0740) Prec@1 86.000 (87.857) Prec@5 99.000 (99.196) +2022-11-14 16:12:09,401 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0741) Prec@1 89.000 (87.877) Prec@5 100.000 (99.211) +2022-11-14 16:12:09,411 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0739) Prec@1 90.000 (87.914) Prec@5 99.000 (99.207) +2022-11-14 16:12:09,420 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0742) Prec@1 85.000 (87.864) Prec@5 100.000 (99.220) +2022-11-14 16:12:09,430 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0744) Prec@1 83.000 (87.783) Prec@5 100.000 (99.233) +2022-11-14 16:12:09,440 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0746) Prec@1 85.000 (87.738) Prec@5 98.000 (99.213) +2022-11-14 16:12:09,451 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0743) Prec@1 90.000 (87.774) Prec@5 98.000 (99.194) +2022-11-14 16:12:09,462 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0743) Prec@1 86.000 (87.746) Prec@5 100.000 (99.206) +2022-11-14 16:12:09,472 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0390 (0.0738) Prec@1 93.000 (87.828) Prec@5 99.000 (99.203) +2022-11-14 16:12:09,483 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1097 (0.0743) Prec@1 81.000 (87.723) Prec@5 99.000 (99.200) +2022-11-14 16:12:09,494 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0743) Prec@1 87.000 (87.712) Prec@5 99.000 (99.197) +2022-11-14 16:12:09,505 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0342 (0.0737) Prec@1 96.000 (87.836) Prec@5 100.000 (99.209) +2022-11-14 16:12:09,515 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0737) Prec@1 87.000 (87.824) Prec@5 98.000 (99.191) +2022-11-14 16:12:09,525 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0735) Prec@1 91.000 (87.870) Prec@5 99.000 (99.188) +2022-11-14 16:12:09,535 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0735) Prec@1 90.000 (87.900) Prec@5 99.000 (99.186) +2022-11-14 16:12:09,547 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0736) Prec@1 87.000 (87.887) Prec@5 99.000 (99.183) +2022-11-14 16:12:09,558 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0733) Prec@1 89.000 (87.903) Prec@5 100.000 (99.194) +2022-11-14 16:12:09,568 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0732) Prec@1 91.000 (87.945) Prec@5 100.000 (99.205) +2022-11-14 16:12:09,579 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0729) Prec@1 90.000 (87.973) Prec@5 100.000 (99.216) +2022-11-14 16:12:09,589 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1336 (0.0738) Prec@1 80.000 (87.867) Prec@5 100.000 (99.227) +2022-11-14 16:12:09,601 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0735) Prec@1 90.000 (87.895) Prec@5 100.000 (99.237) +2022-11-14 16:12:09,612 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0735) Prec@1 89.000 (87.909) Prec@5 99.000 (99.234) +2022-11-14 16:12:09,622 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0736) Prec@1 85.000 (87.872) Prec@5 100.000 (99.244) +2022-11-14 16:12:09,633 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0735) Prec@1 87.000 (87.861) Prec@5 100.000 (99.253) +2022-11-14 16:12:09,643 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0739) Prec@1 83.000 (87.800) Prec@5 99.000 (99.250) +2022-11-14 16:12:09,654 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0740) Prec@1 86.000 (87.778) Prec@5 99.000 (99.247) +2022-11-14 16:12:09,663 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0741) Prec@1 85.000 (87.744) Prec@5 100.000 (99.256) +2022-11-14 16:12:09,675 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0900 (0.0743) Prec@1 84.000 (87.699) Prec@5 100.000 (99.265) +2022-11-14 16:12:09,684 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0742) Prec@1 89.000 (87.714) Prec@5 99.000 (99.262) +2022-11-14 16:12:09,693 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0980 (0.0744) Prec@1 82.000 (87.647) Prec@5 99.000 (99.259) +2022-11-14 16:12:09,704 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1217 (0.0750) Prec@1 81.000 (87.570) Prec@5 99.000 (99.256) +2022-11-14 16:12:09,715 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0748) Prec@1 90.000 (87.598) Prec@5 99.000 (99.253) +2022-11-14 16:12:09,725 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0747) Prec@1 88.000 (87.602) Prec@5 99.000 (99.250) +2022-11-14 16:12:09,735 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0745) Prec@1 90.000 (87.629) Prec@5 100.000 (99.258) +2022-11-14 16:12:09,746 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0746) Prec@1 89.000 (87.644) Prec@5 99.000 (99.256) +2022-11-14 16:12:09,757 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0743) Prec@1 91.000 (87.681) Prec@5 100.000 (99.264) +2022-11-14 16:12:09,768 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0474 (0.0740) Prec@1 93.000 (87.739) Prec@5 100.000 (99.272) +2022-11-14 16:12:09,778 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0741) Prec@1 86.000 (87.720) Prec@5 100.000 (99.280) +2022-11-14 16:12:09,787 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0740) Prec@1 90.000 (87.745) Prec@5 98.000 (99.266) +2022-11-14 16:12:09,798 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0742) Prec@1 85.000 (87.716) Prec@5 98.000 (99.253) +2022-11-14 16:12:09,809 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0740) Prec@1 92.000 (87.760) Prec@5 99.000 (99.250) +2022-11-14 16:12:09,819 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0740) Prec@1 89.000 (87.773) Prec@5 99.000 (99.247) +2022-11-14 16:12:09,829 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0741) Prec@1 85.000 (87.745) Prec@5 100.000 (99.255) +2022-11-14 16:12:09,838 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0743) Prec@1 87.000 (87.737) Prec@5 99.000 (99.253) +2022-11-14 16:12:09,849 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0744) Prec@1 87.000 (87.730) Prec@5 98.000 (99.240) +2022-11-14 16:12:09,923 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:12:10,289 Epoch: [315][0/500] Time 0.032 (0.032) Data 0.266 (0.266) Loss 0.0187 (0.0187) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:10,546 Epoch: [315][10/500] Time 0.021 (0.024) Data 0.002 (0.026) Loss 0.0369 (0.0278) Prec@1 94.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:10,838 Epoch: [315][20/500] Time 0.032 (0.024) Data 0.002 (0.014) Loss 0.0255 (0.0270) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:11,196 Epoch: [315][30/500] Time 0.036 (0.027) Data 0.002 (0.010) Loss 0.0298 (0.0277) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:11,551 Epoch: [315][40/500] Time 0.039 (0.028) Data 0.002 (0.008) Loss 0.0242 (0.0270) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:11,903 Epoch: [315][50/500] Time 0.038 (0.029) Data 0.002 (0.007) Loss 0.0292 (0.0274) Prec@1 95.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:12:12,265 Epoch: [315][60/500] Time 0.033 (0.029) Data 0.002 (0.006) Loss 0.0560 (0.0315) Prec@1 92.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 16:12:12,622 Epoch: [315][70/500] Time 0.032 (0.030) Data 0.002 (0.006) Loss 0.0425 (0.0328) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:12,981 Epoch: [315][80/500] Time 0.035 (0.030) Data 0.002 (0.005) Loss 0.0237 (0.0318) Prec@1 96.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:12:13,332 Epoch: [315][90/500] Time 0.033 (0.030) Data 0.002 (0.005) Loss 0.0401 (0.0326) Prec@1 93.000 (94.900) Prec@5 100.000 (100.000) +2022-11-14 16:12:13,875 Epoch: [315][100/500] Time 0.070 (0.032) Data 0.002 (0.005) Loss 0.0323 (0.0326) Prec@1 95.000 (94.909) Prec@5 100.000 (100.000) +2022-11-14 16:12:14,854 Epoch: [315][110/500] Time 0.090 (0.037) Data 0.002 (0.004) Loss 0.0191 (0.0315) Prec@1 97.000 (95.083) Prec@5 100.000 (100.000) +2022-11-14 16:12:15,606 Epoch: [315][120/500] Time 0.078 (0.039) Data 0.002 (0.004) Loss 0.0207 (0.0307) Prec@1 96.000 (95.154) Prec@5 99.000 (99.923) +2022-11-14 16:12:16,412 Epoch: [315][130/500] Time 0.075 (0.042) Data 0.002 (0.004) Loss 0.0608 (0.0328) Prec@1 90.000 (94.786) Prec@5 99.000 (99.857) +2022-11-14 16:12:17,225 Epoch: [315][140/500] Time 0.075 (0.044) Data 0.002 (0.004) Loss 0.0408 (0.0333) Prec@1 93.000 (94.667) Prec@5 100.000 (99.867) +2022-11-14 16:12:18,012 Epoch: [315][150/500] Time 0.069 (0.046) Data 0.002 (0.004) Loss 0.0373 (0.0336) Prec@1 94.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 16:12:18,828 Epoch: [315][160/500] Time 0.082 (0.047) Data 0.002 (0.004) Loss 0.0464 (0.0343) Prec@1 93.000 (94.529) Prec@5 99.000 (99.824) +2022-11-14 16:12:19,637 Epoch: [315][170/500] Time 0.068 (0.049) Data 0.002 (0.004) Loss 0.0542 (0.0354) Prec@1 93.000 (94.444) Prec@5 99.000 (99.778) +2022-11-14 16:12:20,448 Epoch: [315][180/500] Time 0.081 (0.050) Data 0.002 (0.003) Loss 0.0316 (0.0352) Prec@1 96.000 (94.526) Prec@5 100.000 (99.789) +2022-11-14 16:12:21,259 Epoch: [315][190/500] Time 0.077 (0.051) Data 0.002 (0.003) Loss 0.0459 (0.0358) Prec@1 93.000 (94.450) Prec@5 98.000 (99.700) +2022-11-14 16:12:22,094 Epoch: [315][200/500] Time 0.081 (0.052) Data 0.003 (0.003) Loss 0.0233 (0.0352) Prec@1 97.000 (94.571) Prec@5 100.000 (99.714) +2022-11-14 16:12:22,580 Epoch: [315][210/500] Time 0.042 (0.052) Data 0.002 (0.003) Loss 0.0211 (0.0345) Prec@1 98.000 (94.727) Prec@5 100.000 (99.727) +2022-11-14 16:12:22,997 Epoch: [315][220/500] Time 0.037 (0.051) Data 0.002 (0.003) Loss 0.0454 (0.0350) Prec@1 93.000 (94.652) Prec@5 100.000 (99.739) +2022-11-14 16:12:23,434 Epoch: [315][230/500] Time 0.038 (0.051) Data 0.002 (0.003) Loss 0.0285 (0.0347) Prec@1 95.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 16:12:23,861 Epoch: [315][240/500] Time 0.038 (0.050) Data 0.002 (0.003) Loss 0.0235 (0.0343) Prec@1 97.000 (94.760) Prec@5 100.000 (99.760) +2022-11-14 16:12:24,299 Epoch: [315][250/500] Time 0.033 (0.050) Data 0.002 (0.003) Loss 0.0291 (0.0341) Prec@1 94.000 (94.731) Prec@5 100.000 (99.769) +2022-11-14 16:12:24,738 Epoch: [315][260/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0394 (0.0343) Prec@1 93.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 16:12:25,173 Epoch: [315][270/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0237 (0.0339) Prec@1 96.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 16:12:25,621 Epoch: [315][280/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0468 (0.0343) Prec@1 93.000 (94.655) Prec@5 100.000 (99.793) +2022-11-14 16:12:26,066 Epoch: [315][290/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0264 (0.0341) Prec@1 94.000 (94.633) Prec@5 100.000 (99.800) +2022-11-14 16:12:26,514 Epoch: [315][300/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0363 (0.0342) Prec@1 94.000 (94.613) Prec@5 100.000 (99.806) +2022-11-14 16:12:26,950 Epoch: [315][310/500] Time 0.044 (0.048) Data 0.002 (0.003) Loss 0.0151 (0.0336) Prec@1 98.000 (94.719) Prec@5 100.000 (99.812) +2022-11-14 16:12:27,388 Epoch: [315][320/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0283 (0.0334) Prec@1 97.000 (94.788) Prec@5 100.000 (99.818) +2022-11-14 16:12:27,804 Epoch: [315][330/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0344 (0.0334) Prec@1 93.000 (94.735) Prec@5 100.000 (99.824) +2022-11-14 16:12:28,247 Epoch: [315][340/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0391 (0.0336) Prec@1 93.000 (94.686) Prec@5 100.000 (99.829) +2022-11-14 16:12:28,687 Epoch: [315][350/500] Time 0.034 (0.047) Data 0.002 (0.003) Loss 0.0330 (0.0336) Prec@1 95.000 (94.694) Prec@5 100.000 (99.833) +2022-11-14 16:12:29,139 Epoch: [315][360/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0179 (0.0331) Prec@1 97.000 (94.757) Prec@5 100.000 (99.838) +2022-11-14 16:12:29,574 Epoch: [315][370/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0516 (0.0336) Prec@1 90.000 (94.632) Prec@5 100.000 (99.842) +2022-11-14 16:12:30,020 Epoch: [315][380/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0535 (0.0341) Prec@1 92.000 (94.564) Prec@5 99.000 (99.821) +2022-11-14 16:12:30,461 Epoch: [315][390/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0217 (0.0338) Prec@1 96.000 (94.600) Prec@5 100.000 (99.825) +2022-11-14 16:12:30,908 Epoch: [315][400/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0388 (0.0340) Prec@1 92.000 (94.537) Prec@5 100.000 (99.829) +2022-11-14 16:12:31,342 Epoch: [315][410/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0230 (0.0337) Prec@1 97.000 (94.595) Prec@5 100.000 (99.833) +2022-11-14 16:12:31,787 Epoch: [315][420/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0231 (0.0334) Prec@1 98.000 (94.674) Prec@5 100.000 (99.837) +2022-11-14 16:12:32,232 Epoch: [315][430/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0274 (0.0333) Prec@1 94.000 (94.659) Prec@5 100.000 (99.841) +2022-11-14 16:12:32,709 Epoch: [315][440/500] Time 0.048 (0.045) Data 0.003 (0.003) Loss 0.0399 (0.0335) Prec@1 93.000 (94.622) Prec@5 99.000 (99.822) +2022-11-14 16:12:33,155 Epoch: [315][450/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0191 (0.0331) Prec@1 96.000 (94.652) Prec@5 100.000 (99.826) +2022-11-14 16:12:33,669 Epoch: [315][460/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0206 (0.0329) Prec@1 97.000 (94.702) Prec@5 100.000 (99.830) +2022-11-14 16:12:34,200 Epoch: [315][470/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0258 (0.0327) Prec@1 97.000 (94.750) Prec@5 100.000 (99.833) +2022-11-14 16:12:34,648 Epoch: [315][480/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0220 (0.0325) Prec@1 97.000 (94.796) Prec@5 100.000 (99.837) +2022-11-14 16:12:35,087 Epoch: [315][490/500] Time 0.033 (0.045) Data 0.002 (0.003) Loss 0.0387 (0.0326) Prec@1 94.000 (94.780) Prec@5 100.000 (99.840) +2022-11-14 16:12:35,670 Epoch: [315][499/500] Time 0.070 (0.045) Data 0.002 (0.003) Loss 0.0382 (0.0327) Prec@1 93.000 (94.745) Prec@5 100.000 (99.843) +2022-11-14 16:12:35,999 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0429 (0.0429) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:12:36,013 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0558 (0.0493) Prec@1 91.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 16:12:36,031 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0797 (0.0595) Prec@1 86.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 16:12:36,057 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0689 (0.0618) Prec@1 89.000 (90.000) Prec@5 98.000 (99.500) +2022-11-14 16:12:36,092 Test: [4/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0668 (0.0628) Prec@1 90.000 (90.000) Prec@5 100.000 (99.600) +2022-11-14 16:12:36,143 Test: [5/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0522 (0.0610) Prec@1 91.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 16:12:36,190 Test: [6/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0643 (0.0615) Prec@1 89.000 (90.000) Prec@5 100.000 (99.714) +2022-11-14 16:12:36,245 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0989 (0.0662) Prec@1 84.000 (89.250) Prec@5 99.000 (99.625) +2022-11-14 16:12:36,299 Test: [8/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0912 (0.0690) Prec@1 85.000 (88.778) Prec@5 99.000 (99.556) +2022-11-14 16:12:36,335 Test: [9/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0703 (0.0691) Prec@1 88.000 (88.700) Prec@5 99.000 (99.500) +2022-11-14 16:12:36,371 Test: [10/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0518 (0.0675) Prec@1 92.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 16:12:36,405 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0833 (0.0688) Prec@1 87.000 (88.833) Prec@5 100.000 (99.583) +2022-11-14 16:12:36,439 Test: [12/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0614 (0.0683) Prec@1 89.000 (88.846) Prec@5 100.000 (99.615) +2022-11-14 16:12:36,475 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0898 (0.0698) Prec@1 87.000 (88.714) Prec@5 99.000 (99.571) +2022-11-14 16:12:36,507 Test: [14/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.0705) Prec@1 86.000 (88.533) Prec@5 100.000 (99.600) +2022-11-14 16:12:36,540 Test: [15/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0709 (0.0705) Prec@1 85.000 (88.312) Prec@5 100.000 (99.625) +2022-11-14 16:12:36,574 Test: [16/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0621 (0.0700) Prec@1 91.000 (88.471) Prec@5 98.000 (99.529) +2022-11-14 16:12:36,611 Test: [17/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1084 (0.0721) Prec@1 84.000 (88.222) Prec@5 99.000 (99.500) +2022-11-14 16:12:36,645 Test: [18/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0862 (0.0729) Prec@1 83.000 (87.947) Prec@5 100.000 (99.526) +2022-11-14 16:12:36,678 Test: [19/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0950 (0.0740) Prec@1 86.000 (87.850) Prec@5 96.000 (99.350) +2022-11-14 16:12:36,710 Test: [20/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0914 (0.0748) Prec@1 87.000 (87.810) Prec@5 99.000 (99.333) +2022-11-14 16:12:36,745 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1013 (0.0760) Prec@1 85.000 (87.682) Prec@5 99.000 (99.318) +2022-11-14 16:12:36,777 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1102 (0.0775) Prec@1 84.000 (87.522) Prec@5 98.000 (99.261) +2022-11-14 16:12:36,811 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0776) Prec@1 88.000 (87.542) Prec@5 100.000 (99.292) +2022-11-14 16:12:36,846 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0775) Prec@1 89.000 (87.600) Prec@5 99.000 (99.280) +2022-11-14 16:12:36,882 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0998 (0.0783) Prec@1 84.000 (87.462) Prec@5 98.000 (99.231) +2022-11-14 16:12:36,914 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0777) Prec@1 91.000 (87.593) Prec@5 100.000 (99.259) +2022-11-14 16:12:36,950 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0775) Prec@1 89.000 (87.643) Prec@5 100.000 (99.286) +2022-11-14 16:12:36,981 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0776) Prec@1 84.000 (87.517) Prec@5 98.000 (99.241) +2022-11-14 16:12:37,016 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0554 (0.0769) Prec@1 90.000 (87.600) Prec@5 99.000 (99.233) +2022-11-14 16:12:37,050 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0767) Prec@1 89.000 (87.645) Prec@5 98.000 (99.194) +2022-11-14 16:12:37,081 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0767) Prec@1 89.000 (87.688) Prec@5 99.000 (99.188) +2022-11-14 16:12:37,110 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0854 (0.0770) Prec@1 85.000 (87.606) Prec@5 100.000 (99.212) +2022-11-14 16:12:37,143 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0894 (0.0774) Prec@1 83.000 (87.471) Prec@5 100.000 (99.235) +2022-11-14 16:12:37,177 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0772) Prec@1 89.000 (87.514) Prec@5 98.000 (99.200) +2022-11-14 16:12:37,214 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0792 (0.0773) Prec@1 88.000 (87.528) Prec@5 100.000 (99.222) +2022-11-14 16:12:37,251 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0771) Prec@1 87.000 (87.514) Prec@5 98.000 (99.189) +2022-11-14 16:12:37,283 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1019 (0.0778) Prec@1 85.000 (87.447) Prec@5 98.000 (99.158) +2022-11-14 16:12:37,309 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0423 (0.0769) Prec@1 95.000 (87.641) Prec@5 99.000 (99.154) +2022-11-14 16:12:37,341 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0768) Prec@1 88.000 (87.650) Prec@5 99.000 (99.150) +2022-11-14 16:12:37,375 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0969 (0.0773) Prec@1 85.000 (87.585) Prec@5 97.000 (99.098) +2022-11-14 16:12:37,403 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0773) Prec@1 88.000 (87.595) Prec@5 99.000 (99.095) +2022-11-14 16:12:37,440 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0549 (0.0768) Prec@1 91.000 (87.674) Prec@5 100.000 (99.116) +2022-11-14 16:12:37,473 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0768) Prec@1 89.000 (87.705) Prec@5 98.000 (99.091) +2022-11-14 16:12:37,500 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0769) Prec@1 87.000 (87.689) Prec@5 99.000 (99.089) +2022-11-14 16:12:37,529 Test: [45/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1171 (0.0778) Prec@1 80.000 (87.522) Prec@5 98.000 (99.065) +2022-11-14 16:12:37,561 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0777) Prec@1 87.000 (87.511) Prec@5 100.000 (99.085) +2022-11-14 16:12:37,600 Test: [47/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1078 (0.0783) Prec@1 83.000 (87.417) Prec@5 99.000 (99.083) +2022-11-14 16:12:37,638 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0511 (0.0778) Prec@1 91.000 (87.490) Prec@5 100.000 (99.102) +2022-11-14 16:12:37,670 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0781) Prec@1 88.000 (87.500) Prec@5 100.000 (99.120) +2022-11-14 16:12:37,707 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0594 (0.0778) Prec@1 89.000 (87.529) Prec@5 100.000 (99.137) +2022-11-14 16:12:37,735 Test: [51/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0780) Prec@1 84.000 (87.462) Prec@5 100.000 (99.154) +2022-11-14 16:12:37,766 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0781) Prec@1 86.000 (87.434) Prec@5 99.000 (99.151) +2022-11-14 16:12:37,801 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0780) Prec@1 89.000 (87.463) Prec@5 99.000 (99.148) +2022-11-14 16:12:37,837 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0980 (0.0784) Prec@1 86.000 (87.436) Prec@5 100.000 (99.164) +2022-11-14 16:12:37,873 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0784) Prec@1 87.000 (87.429) Prec@5 99.000 (99.161) +2022-11-14 16:12:37,907 Test: [56/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0785) Prec@1 87.000 (87.421) Prec@5 100.000 (99.175) +2022-11-14 16:12:37,931 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0782) Prec@1 90.000 (87.466) Prec@5 100.000 (99.190) +2022-11-14 16:12:37,962 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1131 (0.0788) Prec@1 81.000 (87.356) Prec@5 99.000 (99.186) +2022-11-14 16:12:37,996 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0790) Prec@1 87.000 (87.350) Prec@5 99.000 (99.183) +2022-11-14 16:12:38,028 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0576 (0.0786) Prec@1 90.000 (87.393) Prec@5 98.000 (99.164) +2022-11-14 16:12:38,056 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0786) Prec@1 88.000 (87.403) Prec@5 100.000 (99.177) +2022-11-14 16:12:38,084 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0783) Prec@1 91.000 (87.460) Prec@5 100.000 (99.190) +2022-11-14 16:12:38,114 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0390 (0.0777) Prec@1 93.000 (87.547) Prec@5 100.000 (99.203) +2022-11-14 16:12:38,145 Test: [64/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0778) Prec@1 88.000 (87.554) Prec@5 100.000 (99.215) +2022-11-14 16:12:38,177 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0938 (0.0780) Prec@1 84.000 (87.500) Prec@5 98.000 (99.197) +2022-11-14 16:12:38,209 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0555 (0.0777) Prec@1 91.000 (87.552) Prec@5 100.000 (99.209) +2022-11-14 16:12:38,244 Test: [67/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0776) Prec@1 88.000 (87.559) Prec@5 97.000 (99.176) +2022-11-14 16:12:38,278 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0774) Prec@1 90.000 (87.594) Prec@5 99.000 (99.174) +2022-11-14 16:12:38,309 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0775) Prec@1 88.000 (87.600) Prec@5 99.000 (99.171) +2022-11-14 16:12:38,346 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0894 (0.0777) Prec@1 87.000 (87.592) Prec@5 97.000 (99.141) +2022-11-14 16:12:38,374 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0776) Prec@1 88.000 (87.597) Prec@5 100.000 (99.153) +2022-11-14 16:12:38,410 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0406 (0.0771) Prec@1 94.000 (87.685) Prec@5 99.000 (99.151) +2022-11-14 16:12:38,444 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0486 (0.0767) Prec@1 93.000 (87.757) Prec@5 100.000 (99.162) +2022-11-14 16:12:38,485 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1046 (0.0771) Prec@1 83.000 (87.693) Prec@5 99.000 (99.160) +2022-11-14 16:12:38,536 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0769) Prec@1 91.000 (87.737) Prec@5 99.000 (99.158) +2022-11-14 16:12:38,575 Test: [76/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0769) Prec@1 88.000 (87.740) Prec@5 99.000 (99.156) +2022-11-14 16:12:38,614 Test: [77/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1012 (0.0772) Prec@1 83.000 (87.679) Prec@5 98.000 (99.141) +2022-11-14 16:12:38,648 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0772) Prec@1 87.000 (87.671) Prec@5 100.000 (99.152) +2022-11-14 16:12:38,678 Test: [79/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0773) Prec@1 86.000 (87.650) Prec@5 99.000 (99.150) +2022-11-14 16:12:38,709 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0819 (0.0774) Prec@1 87.000 (87.642) Prec@5 99.000 (99.148) +2022-11-14 16:12:38,747 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0773) Prec@1 86.000 (87.622) Prec@5 100.000 (99.159) +2022-11-14 16:12:38,782 Test: [82/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0869 (0.0774) Prec@1 87.000 (87.614) Prec@5 99.000 (99.157) +2022-11-14 16:12:38,815 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0774) Prec@1 88.000 (87.619) Prec@5 100.000 (99.167) +2022-11-14 16:12:38,848 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1088 (0.0778) Prec@1 80.000 (87.529) Prec@5 100.000 (99.176) +2022-11-14 16:12:38,888 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1011 (0.0780) Prec@1 85.000 (87.500) Prec@5 99.000 (99.174) +2022-11-14 16:12:38,922 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0779) Prec@1 87.000 (87.494) Prec@5 100.000 (99.184) +2022-11-14 16:12:38,956 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0778) Prec@1 89.000 (87.511) Prec@5 98.000 (99.170) +2022-11-14 16:12:38,988 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0780) Prec@1 82.000 (87.449) Prec@5 100.000 (99.180) +2022-11-14 16:12:39,019 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0778) Prec@1 91.000 (87.489) Prec@5 100.000 (99.189) +2022-11-14 16:12:39,056 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0777) Prec@1 90.000 (87.516) Prec@5 100.000 (99.198) +2022-11-14 16:12:39,090 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0513 (0.0774) Prec@1 93.000 (87.576) Prec@5 99.000 (99.196) +2022-11-14 16:12:39,125 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0772) Prec@1 90.000 (87.602) Prec@5 100.000 (99.204) +2022-11-14 16:12:39,157 Test: [93/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0925 (0.0774) Prec@1 86.000 (87.585) Prec@5 99.000 (99.202) +2022-11-14 16:12:39,190 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0979 (0.0776) Prec@1 84.000 (87.547) Prec@5 99.000 (99.200) +2022-11-14 16:12:39,223 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0775) Prec@1 89.000 (87.562) Prec@5 99.000 (99.198) +2022-11-14 16:12:39,256 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0494 (0.0773) Prec@1 92.000 (87.608) Prec@5 99.000 (99.196) +2022-11-14 16:12:39,287 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1028 (0.0775) Prec@1 85.000 (87.582) Prec@5 98.000 (99.184) +2022-11-14 16:12:39,319 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0915 (0.0777) Prec@1 85.000 (87.556) Prec@5 100.000 (99.192) +2022-11-14 16:12:39,346 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0777) Prec@1 88.000 (87.560) Prec@5 99.000 (99.190) +2022-11-14 16:12:39,407 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:12:39,778 Epoch: [316][0/500] Time 0.025 (0.025) Data 0.284 (0.284) Loss 0.0478 (0.0478) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:12:40,211 Epoch: [316][10/500] Time 0.044 (0.037) Data 0.002 (0.028) Loss 0.0249 (0.0363) Prec@1 97.000 (94.500) Prec@5 99.000 (99.000) +2022-11-14 16:12:40,708 Epoch: [316][20/500] Time 0.050 (0.040) Data 0.002 (0.015) Loss 0.0221 (0.0316) Prec@1 97.000 (95.333) Prec@5 100.000 (99.333) +2022-11-14 16:12:41,208 Epoch: [316][30/500] Time 0.054 (0.042) Data 0.002 (0.011) Loss 0.0310 (0.0315) Prec@1 95.000 (95.250) Prec@5 100.000 (99.500) +2022-11-14 16:12:41,698 Epoch: [316][40/500] Time 0.044 (0.042) Data 0.002 (0.009) Loss 0.0365 (0.0325) Prec@1 92.000 (94.600) Prec@5 100.000 (99.600) +2022-11-14 16:12:42,241 Epoch: [316][50/500] Time 0.067 (0.043) Data 0.002 (0.008) Loss 0.0380 (0.0334) Prec@1 94.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 16:12:42,721 Epoch: [316][60/500] Time 0.052 (0.043) Data 0.002 (0.007) Loss 0.0290 (0.0328) Prec@1 97.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:12:43,220 Epoch: [316][70/500] Time 0.049 (0.044) Data 0.002 (0.006) Loss 0.0552 (0.0356) Prec@1 91.000 (94.375) Prec@5 99.000 (99.625) +2022-11-14 16:12:43,720 Epoch: [316][80/500] Time 0.055 (0.044) Data 0.002 (0.006) Loss 0.0469 (0.0368) Prec@1 91.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:12:44,191 Epoch: [316][90/500] Time 0.052 (0.043) Data 0.002 (0.005) Loss 0.0291 (0.0360) Prec@1 95.000 (94.100) Prec@5 100.000 (99.700) +2022-11-14 16:12:44,675 Epoch: [316][100/500] Time 0.047 (0.043) Data 0.002 (0.005) Loss 0.0305 (0.0355) Prec@1 96.000 (94.273) Prec@5 99.000 (99.636) +2022-11-14 16:12:45,233 Epoch: [316][110/500] Time 0.041 (0.044) Data 0.002 (0.005) Loss 0.0197 (0.0342) Prec@1 97.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 16:12:45,732 Epoch: [316][120/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0377 (0.0345) Prec@1 95.000 (94.538) Prec@5 100.000 (99.692) +2022-11-14 16:12:46,211 Epoch: [316][130/500] Time 0.045 (0.044) Data 0.002 (0.004) Loss 0.0174 (0.0333) Prec@1 97.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 16:12:46,733 Epoch: [316][140/500] Time 0.053 (0.044) Data 0.002 (0.004) Loss 0.0404 (0.0337) Prec@1 93.000 (94.600) Prec@5 99.000 (99.667) +2022-11-14 16:12:47,218 Epoch: [316][150/500] Time 0.042 (0.044) Data 0.002 (0.004) Loss 0.0222 (0.0330) Prec@1 96.000 (94.688) Prec@5 100.000 (99.688) +2022-11-14 16:12:47,706 Epoch: [316][160/500] Time 0.045 (0.044) Data 0.002 (0.004) Loss 0.0251 (0.0326) Prec@1 97.000 (94.824) Prec@5 100.000 (99.706) +2022-11-14 16:12:48,295 Epoch: [316][170/500] Time 0.046 (0.045) Data 0.002 (0.004) Loss 0.0554 (0.0338) Prec@1 90.000 (94.556) Prec@5 100.000 (99.722) +2022-11-14 16:12:48,792 Epoch: [316][180/500] Time 0.042 (0.045) Data 0.002 (0.004) Loss 0.0489 (0.0346) Prec@1 91.000 (94.368) Prec@5 98.000 (99.632) +2022-11-14 16:12:49,299 Epoch: [316][190/500] Time 0.052 (0.045) Data 0.002 (0.004) Loss 0.0517 (0.0355) Prec@1 91.000 (94.200) Prec@5 100.000 (99.650) +2022-11-14 16:12:49,803 Epoch: [316][200/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0273 (0.0351) Prec@1 96.000 (94.286) Prec@5 100.000 (99.667) +2022-11-14 16:12:50,292 Epoch: [316][210/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0266 (0.0347) Prec@1 96.000 (94.364) Prec@5 100.000 (99.682) +2022-11-14 16:12:50,792 Epoch: [316][220/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0306 (0.0345) Prec@1 95.000 (94.391) Prec@5 100.000 (99.696) +2022-11-14 16:12:51,285 Epoch: [316][230/500] Time 0.044 (0.045) Data 0.003 (0.003) Loss 0.0410 (0.0348) Prec@1 93.000 (94.333) Prec@5 100.000 (99.708) +2022-11-14 16:12:51,782 Epoch: [316][240/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0279 (0.0345) Prec@1 94.000 (94.320) Prec@5 100.000 (99.720) +2022-11-14 16:12:52,268 Epoch: [316][250/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0235 (0.0341) Prec@1 95.000 (94.346) Prec@5 100.000 (99.731) +2022-11-14 16:12:52,758 Epoch: [316][260/500] Time 0.036 (0.045) Data 0.002 (0.003) Loss 0.0303 (0.0340) Prec@1 95.000 (94.370) Prec@5 100.000 (99.741) +2022-11-14 16:12:53,263 Epoch: [316][270/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0464 (0.0344) Prec@1 93.000 (94.321) Prec@5 100.000 (99.750) +2022-11-14 16:12:53,748 Epoch: [316][280/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0244 (0.0341) Prec@1 96.000 (94.379) Prec@5 100.000 (99.759) +2022-11-14 16:12:54,261 Epoch: [316][290/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0224 (0.0337) Prec@1 96.000 (94.433) Prec@5 100.000 (99.767) +2022-11-14 16:12:54,779 Epoch: [316][300/500] Time 0.038 (0.045) Data 0.002 (0.003) Loss 0.0140 (0.0330) Prec@1 99.000 (94.581) Prec@5 100.000 (99.774) +2022-11-14 16:12:55,300 Epoch: [316][310/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0378 (0.0332) Prec@1 94.000 (94.562) Prec@5 100.000 (99.781) +2022-11-14 16:12:55,806 Epoch: [316][320/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0165 (0.0327) Prec@1 99.000 (94.697) Prec@5 100.000 (99.788) +2022-11-14 16:12:56,290 Epoch: [316][330/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0275 (0.0325) Prec@1 96.000 (94.735) Prec@5 100.000 (99.794) +2022-11-14 16:12:56,776 Epoch: [316][340/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0314 (0.0325) Prec@1 95.000 (94.743) Prec@5 100.000 (99.800) +2022-11-14 16:12:57,289 Epoch: [316][350/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0174 (0.0321) Prec@1 98.000 (94.833) Prec@5 100.000 (99.806) +2022-11-14 16:12:57,789 Epoch: [316][360/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0527 (0.0326) Prec@1 92.000 (94.757) Prec@5 99.000 (99.784) +2022-11-14 16:12:58,285 Epoch: [316][370/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0215 (0.0323) Prec@1 96.000 (94.789) Prec@5 100.000 (99.789) +2022-11-14 16:12:58,812 Epoch: [316][380/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0514 (0.0328) Prec@1 90.000 (94.667) Prec@5 100.000 (99.795) +2022-11-14 16:12:59,302 Epoch: [316][390/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0282 (0.0327) Prec@1 97.000 (94.725) Prec@5 100.000 (99.800) +2022-11-14 16:12:59,804 Epoch: [316][400/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0344 (0.0328) Prec@1 94.000 (94.707) Prec@5 100.000 (99.805) +2022-11-14 16:13:00,300 Epoch: [316][410/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0283 (0.0326) Prec@1 93.000 (94.667) Prec@5 100.000 (99.810) +2022-11-14 16:13:00,827 Epoch: [316][420/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0269 (0.0325) Prec@1 95.000 (94.674) Prec@5 100.000 (99.814) +2022-11-14 16:13:01,336 Epoch: [316][430/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0277 (0.0324) Prec@1 95.000 (94.682) Prec@5 100.000 (99.818) +2022-11-14 16:13:01,818 Epoch: [316][440/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0301 (0.0324) Prec@1 95.000 (94.689) Prec@5 100.000 (99.822) +2022-11-14 16:13:02,311 Epoch: [316][450/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0124 (0.0319) Prec@1 97.000 (94.739) Prec@5 100.000 (99.826) +2022-11-14 16:13:02,830 Epoch: [316][460/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0318 (0.0319) Prec@1 97.000 (94.787) Prec@5 99.000 (99.809) +2022-11-14 16:13:03,332 Epoch: [316][470/500] Time 0.043 (0.045) Data 0.003 (0.003) Loss 0.0269 (0.0318) Prec@1 95.000 (94.792) Prec@5 99.000 (99.792) +2022-11-14 16:13:03,830 Epoch: [316][480/500] Time 0.058 (0.045) Data 0.002 (0.003) Loss 0.0227 (0.0316) Prec@1 97.000 (94.837) Prec@5 100.000 (99.796) +2022-11-14 16:13:04,342 Epoch: [316][490/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0213 (0.0314) Prec@1 96.000 (94.860) Prec@5 100.000 (99.800) +2022-11-14 16:13:04,798 Epoch: [316][499/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0541 (0.0319) Prec@1 92.000 (94.804) Prec@5 100.000 (99.804) +2022-11-14 16:13:05,135 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0750 (0.0750) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:13:05,146 Test: [1/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0721) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:13:05,156 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0684) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:13:05,170 Test: [3/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0598 (0.0663) Prec@1 91.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 16:13:05,180 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0822 (0.0695) Prec@1 83.000 (87.600) Prec@5 100.000 (99.800) +2022-11-14 16:13:05,189 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0586 (0.0676) Prec@1 92.000 (88.333) Prec@5 99.000 (99.667) +2022-11-14 16:13:05,201 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0662) Prec@1 91.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 16:13:05,218 Test: [7/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0786 (0.0677) Prec@1 88.000 (88.625) Prec@5 100.000 (99.750) +2022-11-14 16:13:05,232 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0683) Prec@1 91.000 (88.889) Prec@5 100.000 (99.778) +2022-11-14 16:13:05,245 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0692) Prec@1 87.000 (88.700) Prec@5 99.000 (99.700) +2022-11-14 16:13:05,256 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0678) Prec@1 92.000 (89.000) Prec@5 100.000 (99.727) +2022-11-14 16:13:05,269 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0696) Prec@1 86.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 16:13:05,285 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0683) Prec@1 91.000 (88.923) Prec@5 100.000 (99.769) +2022-11-14 16:13:05,299 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0695) Prec@1 88.000 (88.857) Prec@5 98.000 (99.643) +2022-11-14 16:13:05,314 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0711) Prec@1 86.000 (88.667) Prec@5 99.000 (99.600) +2022-11-14 16:13:05,331 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0712) Prec@1 89.000 (88.688) Prec@5 100.000 (99.625) +2022-11-14 16:13:05,350 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0699) Prec@1 93.000 (88.941) Prec@5 99.000 (99.588) +2022-11-14 16:13:05,367 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0720) Prec@1 81.000 (88.500) Prec@5 99.000 (99.556) +2022-11-14 16:13:05,383 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0727) Prec@1 86.000 (88.368) Prec@5 100.000 (99.579) +2022-11-14 16:13:05,396 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0730) Prec@1 87.000 (88.300) Prec@5 98.000 (99.500) +2022-11-14 16:13:05,411 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0739) Prec@1 85.000 (88.143) Prec@5 99.000 (99.476) +2022-11-14 16:13:05,428 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0738) Prec@1 87.000 (88.091) Prec@5 99.000 (99.455) +2022-11-14 16:13:05,448 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0744) Prec@1 87.000 (88.043) Prec@5 99.000 (99.435) +2022-11-14 16:13:05,463 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0747) Prec@1 86.000 (87.958) Prec@5 100.000 (99.458) +2022-11-14 16:13:05,480 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0749) Prec@1 88.000 (87.960) Prec@5 99.000 (99.440) +2022-11-14 16:13:05,494 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0750) Prec@1 88.000 (87.962) Prec@5 99.000 (99.423) +2022-11-14 16:13:05,510 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0366 (0.0735) Prec@1 95.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 16:13:05,527 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0729) Prec@1 91.000 (88.321) Prec@5 100.000 (99.464) +2022-11-14 16:13:05,544 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0728) Prec@1 90.000 (88.379) Prec@5 98.000 (99.414) +2022-11-14 16:13:05,560 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0724) Prec@1 92.000 (88.500) Prec@5 100.000 (99.433) +2022-11-14 16:13:05,578 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0720) Prec@1 90.000 (88.548) Prec@5 100.000 (99.452) +2022-11-14 16:13:05,595 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0714) Prec@1 94.000 (88.719) Prec@5 100.000 (99.469) +2022-11-14 16:13:05,611 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0711) Prec@1 89.000 (88.727) Prec@5 100.000 (99.485) +2022-11-14 16:13:05,629 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0713) Prec@1 86.000 (88.647) Prec@5 99.000 (99.471) +2022-11-14 16:13:05,648 Test: [34/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1127 (0.0725) Prec@1 82.000 (88.457) Prec@5 98.000 (99.429) +2022-11-14 16:13:05,663 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0728) Prec@1 88.000 (88.444) Prec@5 99.000 (99.417) +2022-11-14 16:13:05,680 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0728) Prec@1 87.000 (88.405) Prec@5 99.000 (99.405) +2022-11-14 16:13:05,694 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.0737) Prec@1 83.000 (88.263) Prec@5 99.000 (99.395) +2022-11-14 16:13:05,709 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0733) Prec@1 93.000 (88.385) Prec@5 99.000 (99.385) +2022-11-14 16:13:05,726 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0732) Prec@1 88.000 (88.375) Prec@5 99.000 (99.375) +2022-11-14 16:13:05,744 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0734) Prec@1 86.000 (88.317) Prec@5 98.000 (99.341) +2022-11-14 16:13:05,757 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0733) Prec@1 87.000 (88.286) Prec@5 99.000 (99.333) +2022-11-14 16:13:05,773 Test: [42/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0727) Prec@1 92.000 (88.372) Prec@5 99.000 (99.326) +2022-11-14 16:13:05,789 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0729) Prec@1 89.000 (88.386) Prec@5 99.000 (99.318) +2022-11-14 16:13:05,804 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0725) Prec@1 91.000 (88.444) Prec@5 99.000 (99.311) +2022-11-14 16:13:05,822 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0726) Prec@1 86.000 (88.391) Prec@5 100.000 (99.326) +2022-11-14 16:13:05,839 Test: [46/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0724) Prec@1 88.000 (88.383) Prec@5 100.000 (99.340) +2022-11-14 16:13:05,854 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0728) Prec@1 87.000 (88.354) Prec@5 99.000 (99.333) +2022-11-14 16:13:05,869 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0484 (0.0723) Prec@1 92.000 (88.429) Prec@5 100.000 (99.347) +2022-11-14 16:13:05,883 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0731) Prec@1 85.000 (88.360) Prec@5 100.000 (99.360) +2022-11-14 16:13:05,897 Test: [50/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0725) Prec@1 95.000 (88.490) Prec@5 100.000 (99.373) +2022-11-14 16:13:05,913 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0727) Prec@1 87.000 (88.462) Prec@5 99.000 (99.365) +2022-11-14 16:13:05,930 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0726) Prec@1 88.000 (88.453) Prec@5 100.000 (99.377) +2022-11-14 16:13:05,948 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0726) Prec@1 88.000 (88.444) Prec@5 100.000 (99.389) +2022-11-14 16:13:05,967 Test: [54/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0729) Prec@1 85.000 (88.382) Prec@5 100.000 (99.400) +2022-11-14 16:13:05,984 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0729) Prec@1 88.000 (88.375) Prec@5 99.000 (99.393) +2022-11-14 16:13:06,001 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0733) Prec@1 84.000 (88.298) Prec@5 100.000 (99.404) +2022-11-14 16:13:06,018 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0731) Prec@1 89.000 (88.310) Prec@5 100.000 (99.414) +2022-11-14 16:13:06,034 Test: [58/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0734) Prec@1 86.000 (88.271) Prec@5 99.000 (99.407) +2022-11-14 16:13:06,049 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0731) Prec@1 91.000 (88.317) Prec@5 100.000 (99.417) +2022-11-14 16:13:06,064 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0733) Prec@1 86.000 (88.279) Prec@5 99.000 (99.410) +2022-11-14 16:13:06,082 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0732) Prec@1 89.000 (88.290) Prec@5 100.000 (99.419) +2022-11-14 16:13:06,097 Test: [62/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0731) Prec@1 88.000 (88.286) Prec@5 100.000 (99.429) +2022-11-14 16:13:06,114 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0727) Prec@1 92.000 (88.344) Prec@5 100.000 (99.438) +2022-11-14 16:13:06,133 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0732) Prec@1 82.000 (88.246) Prec@5 100.000 (99.446) +2022-11-14 16:13:06,152 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0732) Prec@1 89.000 (88.258) Prec@5 100.000 (99.455) +2022-11-14 16:13:06,171 Test: [66/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0383 (0.0726) Prec@1 94.000 (88.343) Prec@5 100.000 (99.463) +2022-11-14 16:13:06,189 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0725) Prec@1 92.000 (88.397) Prec@5 98.000 (99.441) +2022-11-14 16:13:06,202 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0725) Prec@1 86.000 (88.362) Prec@5 99.000 (99.435) +2022-11-14 16:13:06,217 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0726) Prec@1 87.000 (88.343) Prec@5 97.000 (99.400) +2022-11-14 16:13:06,234 Test: [70/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0731) Prec@1 85.000 (88.296) Prec@5 98.000 (99.380) +2022-11-14 16:13:06,251 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0730) Prec@1 90.000 (88.319) Prec@5 99.000 (99.375) +2022-11-14 16:13:06,268 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0726) Prec@1 94.000 (88.397) Prec@5 100.000 (99.384) +2022-11-14 16:13:06,289 Test: [73/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0436 (0.0723) Prec@1 94.000 (88.473) Prec@5 100.000 (99.392) +2022-11-14 16:13:06,305 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1225 (0.0729) Prec@1 78.000 (88.333) Prec@5 99.000 (99.387) +2022-11-14 16:13:06,320 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0731) Prec@1 87.000 (88.316) Prec@5 99.000 (99.382) +2022-11-14 16:13:06,335 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0730) Prec@1 89.000 (88.325) Prec@5 98.000 (99.364) +2022-11-14 16:13:06,353 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0733) Prec@1 86.000 (88.295) Prec@5 97.000 (99.333) +2022-11-14 16:13:06,373 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0734) Prec@1 86.000 (88.266) Prec@5 100.000 (99.342) +2022-11-14 16:13:06,389 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0734) Prec@1 89.000 (88.275) Prec@5 100.000 (99.350) +2022-11-14 16:13:06,406 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0736) Prec@1 87.000 (88.259) Prec@5 99.000 (99.346) +2022-11-14 16:13:06,425 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0739) Prec@1 83.000 (88.195) Prec@5 100.000 (99.354) +2022-11-14 16:13:06,442 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0740) Prec@1 89.000 (88.205) Prec@5 99.000 (99.349) +2022-11-14 16:13:06,462 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0739) Prec@1 89.000 (88.214) Prec@5 99.000 (99.345) +2022-11-14 16:13:06,481 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0741) Prec@1 88.000 (88.212) Prec@5 99.000 (99.341) +2022-11-14 16:13:06,500 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0743) Prec@1 83.000 (88.151) Prec@5 99.000 (99.337) +2022-11-14 16:13:06,515 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0741) Prec@1 89.000 (88.161) Prec@5 100.000 (99.345) +2022-11-14 16:13:06,533 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0741) Prec@1 89.000 (88.170) Prec@5 99.000 (99.341) +2022-11-14 16:13:06,552 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0741) Prec@1 86.000 (88.146) Prec@5 99.000 (99.337) +2022-11-14 16:13:06,570 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0742) Prec@1 89.000 (88.156) Prec@5 100.000 (99.344) +2022-11-14 16:13:06,587 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0742) Prec@1 88.000 (88.154) Prec@5 99.000 (99.341) +2022-11-14 16:13:06,604 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0740) Prec@1 92.000 (88.196) Prec@5 100.000 (99.348) +2022-11-14 16:13:06,619 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0743) Prec@1 85.000 (88.161) Prec@5 99.000 (99.344) +2022-11-14 16:13:06,634 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0743) Prec@1 87.000 (88.149) Prec@5 100.000 (99.351) +2022-11-14 16:13:06,653 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0744) Prec@1 88.000 (88.147) Prec@5 99.000 (99.347) +2022-11-14 16:13:06,673 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0745) Prec@1 88.000 (88.146) Prec@5 98.000 (99.333) +2022-11-14 16:13:06,692 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0743) Prec@1 91.000 (88.175) Prec@5 99.000 (99.330) +2022-11-14 16:13:06,712 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0746) Prec@1 83.000 (88.122) Prec@5 99.000 (99.327) +2022-11-14 16:13:06,731 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0748) Prec@1 85.000 (88.091) Prec@5 98.000 (99.313) +2022-11-14 16:13:06,749 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0746) Prec@1 91.000 (88.120) Prec@5 100.000 (99.320) +2022-11-14 16:13:06,837 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:13:07,195 Epoch: [317][0/500] Time 0.025 (0.025) Data 0.266 (0.266) Loss 0.0147 (0.0147) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:13:07,475 Epoch: [317][10/500] Time 0.031 (0.025) Data 0.002 (0.026) Loss 0.0270 (0.0209) Prec@1 97.000 (97.000) Prec@5 99.000 (99.500) +2022-11-14 16:13:07,871 Epoch: [317][20/500] Time 0.053 (0.029) Data 0.002 (0.015) Loss 0.0408 (0.0275) Prec@1 94.000 (96.000) Prec@5 100.000 (99.667) +2022-11-14 16:13:08,388 Epoch: [317][30/500] Time 0.048 (0.034) Data 0.002 (0.011) Loss 0.0271 (0.0274) Prec@1 96.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 16:13:08,923 Epoch: [317][40/500] Time 0.052 (0.038) Data 0.002 (0.008) Loss 0.0350 (0.0289) Prec@1 94.000 (95.600) Prec@5 99.000 (99.600) +2022-11-14 16:13:09,436 Epoch: [317][50/500] Time 0.048 (0.039) Data 0.002 (0.007) Loss 0.0224 (0.0278) Prec@1 96.000 (95.667) Prec@5 99.000 (99.500) +2022-11-14 16:13:09,945 Epoch: [317][60/500] Time 0.050 (0.040) Data 0.002 (0.006) Loss 0.0328 (0.0286) Prec@1 94.000 (95.429) Prec@5 99.000 (99.429) +2022-11-14 16:13:10,462 Epoch: [317][70/500] Time 0.039 (0.041) Data 0.003 (0.006) Loss 0.0301 (0.0287) Prec@1 94.000 (95.250) Prec@5 100.000 (99.500) +2022-11-14 16:13:10,990 Epoch: [317][80/500] Time 0.052 (0.042) Data 0.002 (0.005) Loss 0.0263 (0.0285) Prec@1 95.000 (95.222) Prec@5 100.000 (99.556) +2022-11-14 16:13:11,515 Epoch: [317][90/500] Time 0.050 (0.042) Data 0.002 (0.005) Loss 0.0262 (0.0282) Prec@1 95.000 (95.200) Prec@5 100.000 (99.600) +2022-11-14 16:13:12,033 Epoch: [317][100/500] Time 0.044 (0.043) Data 0.002 (0.005) Loss 0.0374 (0.0291) Prec@1 93.000 (95.000) Prec@5 100.000 (99.636) +2022-11-14 16:13:12,566 Epoch: [317][110/500] Time 0.058 (0.043) Data 0.002 (0.004) Loss 0.0224 (0.0285) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:13:13,094 Epoch: [317][120/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0434 (0.0297) Prec@1 94.000 (94.923) Prec@5 100.000 (99.692) +2022-11-14 16:13:13,607 Epoch: [317][130/500] Time 0.052 (0.044) Data 0.002 (0.004) Loss 0.0317 (0.0298) Prec@1 97.000 (95.071) Prec@5 100.000 (99.714) +2022-11-14 16:13:14,131 Epoch: [317][140/500] Time 0.042 (0.044) Data 0.002 (0.004) Loss 0.0345 (0.0301) Prec@1 95.000 (95.067) Prec@5 99.000 (99.667) +2022-11-14 16:13:14,671 Epoch: [317][150/500] Time 0.048 (0.044) Data 0.002 (0.004) Loss 0.0257 (0.0298) Prec@1 95.000 (95.062) Prec@5 100.000 (99.688) +2022-11-14 16:13:15,251 Epoch: [317][160/500] Time 0.048 (0.044) Data 0.003 (0.004) Loss 0.0313 (0.0299) Prec@1 94.000 (95.000) Prec@5 100.000 (99.706) +2022-11-14 16:13:15,775 Epoch: [317][170/500] Time 0.048 (0.045) Data 0.002 (0.004) Loss 0.0314 (0.0300) Prec@1 94.000 (94.944) Prec@5 100.000 (99.722) +2022-11-14 16:13:16,296 Epoch: [317][180/500] Time 0.052 (0.045) Data 0.002 (0.004) Loss 0.0368 (0.0304) Prec@1 94.000 (94.895) Prec@5 99.000 (99.684) +2022-11-14 16:13:16,811 Epoch: [317][190/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0366 (0.0307) Prec@1 93.000 (94.800) Prec@5 100.000 (99.700) +2022-11-14 16:13:17,349 Epoch: [317][200/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0284 (0.0306) Prec@1 96.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:13:17,875 Epoch: [317][210/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0510 (0.0315) Prec@1 90.000 (94.636) Prec@5 99.000 (99.682) +2022-11-14 16:13:18,401 Epoch: [317][220/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0248 (0.0312) Prec@1 96.000 (94.696) Prec@5 100.000 (99.696) +2022-11-14 16:13:18,945 Epoch: [317][230/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0314 (0.0312) Prec@1 93.000 (94.625) Prec@5 100.000 (99.708) +2022-11-14 16:13:19,484 Epoch: [317][240/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0371 (0.0314) Prec@1 95.000 (94.640) Prec@5 100.000 (99.720) +2022-11-14 16:13:20,012 Epoch: [317][250/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0524 (0.0323) Prec@1 90.000 (94.462) Prec@5 100.000 (99.731) +2022-11-14 16:13:20,553 Epoch: [317][260/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0369 (0.0324) Prec@1 93.000 (94.407) Prec@5 100.000 (99.741) +2022-11-14 16:13:21,083 Epoch: [317][270/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0175 (0.0319) Prec@1 98.000 (94.536) Prec@5 100.000 (99.750) +2022-11-14 16:13:21,617 Epoch: [317][280/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0274 (0.0317) Prec@1 96.000 (94.586) Prec@5 100.000 (99.759) +2022-11-14 16:13:22,161 Epoch: [317][290/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0323 (0.0318) Prec@1 94.000 (94.567) Prec@5 99.000 (99.733) +2022-11-14 16:13:22,692 Epoch: [317][300/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0233 (0.0315) Prec@1 94.000 (94.548) Prec@5 100.000 (99.742) +2022-11-14 16:13:23,222 Epoch: [317][310/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0390 (0.0317) Prec@1 93.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:13:23,752 Epoch: [317][320/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0359 (0.0318) Prec@1 95.000 (94.515) Prec@5 100.000 (99.758) +2022-11-14 16:13:24,279 Epoch: [317][330/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0379 (0.0320) Prec@1 94.000 (94.500) Prec@5 100.000 (99.765) +2022-11-14 16:13:24,804 Epoch: [317][340/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0348 (0.0321) Prec@1 95.000 (94.514) Prec@5 99.000 (99.743) +2022-11-14 16:13:25,327 Epoch: [317][350/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0283 (0.0320) Prec@1 96.000 (94.556) Prec@5 100.000 (99.750) +2022-11-14 16:13:25,865 Epoch: [317][360/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0343 (0.0321) Prec@1 95.000 (94.568) Prec@5 99.000 (99.730) +2022-11-14 16:13:26,408 Epoch: [317][370/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0290 (0.0320) Prec@1 96.000 (94.605) Prec@5 100.000 (99.737) +2022-11-14 16:13:26,945 Epoch: [317][380/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0356 (0.0321) Prec@1 94.000 (94.590) Prec@5 100.000 (99.744) +2022-11-14 16:13:27,468 Epoch: [317][390/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0410 (0.0323) Prec@1 93.000 (94.550) Prec@5 100.000 (99.750) +2022-11-14 16:13:28,003 Epoch: [317][400/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0350 (0.0324) Prec@1 96.000 (94.585) Prec@5 100.000 (99.756) +2022-11-14 16:13:28,540 Epoch: [317][410/500] Time 0.059 (0.046) Data 0.002 (0.003) Loss 0.0201 (0.0321) Prec@1 97.000 (94.643) Prec@5 100.000 (99.762) +2022-11-14 16:13:29,061 Epoch: [317][420/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0397 (0.0323) Prec@1 94.000 (94.628) Prec@5 100.000 (99.767) +2022-11-14 16:13:29,600 Epoch: [317][430/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0470 (0.0326) Prec@1 94.000 (94.614) Prec@5 99.000 (99.750) +2022-11-14 16:13:30,132 Epoch: [317][440/500] Time 0.051 (0.046) Data 0.003 (0.003) Loss 0.0264 (0.0324) Prec@1 96.000 (94.644) Prec@5 100.000 (99.756) +2022-11-14 16:13:30,658 Epoch: [317][450/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0304 (0.0324) Prec@1 94.000 (94.630) Prec@5 100.000 (99.761) +2022-11-14 16:13:31,178 Epoch: [317][460/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0372 (0.0325) Prec@1 93.000 (94.596) Prec@5 100.000 (99.766) +2022-11-14 16:13:31,710 Epoch: [317][470/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0344 (0.0325) Prec@1 94.000 (94.583) Prec@5 100.000 (99.771) +2022-11-14 16:13:32,250 Epoch: [317][480/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0405 (0.0327) Prec@1 92.000 (94.531) Prec@5 100.000 (99.776) +2022-11-14 16:13:32,775 Epoch: [317][490/500] Time 0.051 (0.046) Data 0.002 (0.003) Loss 0.0202 (0.0325) Prec@1 96.000 (94.560) Prec@5 100.000 (99.780) +2022-11-14 16:13:33,267 Epoch: [317][499/500] Time 0.062 (0.046) Data 0.002 (0.003) Loss 0.0314 (0.0324) Prec@1 93.000 (94.529) Prec@5 100.000 (99.784) +2022-11-14 16:13:33,582 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0631 (0.0631) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:13:33,595 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0601 (0.0616) Prec@1 89.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:13:33,606 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0673) Prec@1 87.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 16:13:33,619 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0715) Prec@1 87.000 (88.000) Prec@5 98.000 (99.000) +2022-11-14 16:13:33,629 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0704) Prec@1 89.000 (88.200) Prec@5 98.000 (98.800) +2022-11-14 16:13:33,639 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0379 (0.0650) Prec@1 93.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 16:13:33,649 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0665) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:13:33,665 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0697) Prec@1 84.000 (88.375) Prec@5 100.000 (99.125) +2022-11-14 16:13:33,682 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0701) Prec@1 90.000 (88.556) Prec@5 98.000 (99.000) +2022-11-14 16:13:33,698 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0712) Prec@1 88.000 (88.500) Prec@5 98.000 (98.900) +2022-11-14 16:13:33,714 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0704) Prec@1 90.000 (88.636) Prec@5 100.000 (99.000) +2022-11-14 16:13:33,730 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0706) Prec@1 87.000 (88.500) Prec@5 100.000 (99.083) +2022-11-14 16:13:33,745 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0684) Prec@1 91.000 (88.692) Prec@5 100.000 (99.154) +2022-11-14 16:13:33,761 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0683) Prec@1 89.000 (88.714) Prec@5 100.000 (99.214) +2022-11-14 16:13:33,782 Test: [14/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0698) Prec@1 85.000 (88.467) Prec@5 100.000 (99.267) +2022-11-14 16:13:33,802 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0706) Prec@1 87.000 (88.375) Prec@5 99.000 (99.250) +2022-11-14 16:13:33,821 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0700) Prec@1 89.000 (88.412) Prec@5 99.000 (99.235) +2022-11-14 16:13:33,840 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1159 (0.0726) Prec@1 82.000 (88.056) Prec@5 99.000 (99.222) +2022-11-14 16:13:33,859 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0734) Prec@1 85.000 (87.895) Prec@5 99.000 (99.211) +2022-11-14 16:13:33,874 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0738) Prec@1 87.000 (87.850) Prec@5 98.000 (99.150) +2022-11-14 16:13:33,891 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 86.000 (87.762) Prec@5 100.000 (99.190) +2022-11-14 16:13:33,909 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0751) Prec@1 88.000 (87.773) Prec@5 100.000 (99.227) +2022-11-14 16:13:33,928 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0756) Prec@1 88.000 (87.783) Prec@5 98.000 (99.174) +2022-11-14 16:13:33,945 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0751) Prec@1 89.000 (87.833) Prec@5 100.000 (99.208) +2022-11-14 16:13:33,962 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0759) Prec@1 84.000 (87.680) Prec@5 99.000 (99.200) +2022-11-14 16:13:33,979 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0767) Prec@1 85.000 (87.577) Prec@5 99.000 (99.192) +2022-11-14 16:13:33,997 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0762) Prec@1 90.000 (87.667) Prec@5 100.000 (99.222) +2022-11-14 16:13:34,017 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0758) Prec@1 89.000 (87.714) Prec@5 100.000 (99.250) +2022-11-14 16:13:34,034 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0758) Prec@1 86.000 (87.655) Prec@5 98.000 (99.207) +2022-11-14 16:13:34,052 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0757) Prec@1 88.000 (87.667) Prec@5 98.000 (99.167) +2022-11-14 16:13:34,072 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0751) Prec@1 90.000 (87.742) Prec@5 100.000 (99.194) +2022-11-14 16:13:34,089 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0754) Prec@1 86.000 (87.688) Prec@5 99.000 (99.188) +2022-11-14 16:13:34,104 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0753) Prec@1 86.000 (87.636) Prec@5 100.000 (99.212) +2022-11-14 16:13:34,124 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0759) Prec@1 81.000 (87.441) Prec@5 100.000 (99.235) +2022-11-14 16:13:34,143 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0763) Prec@1 86.000 (87.400) Prec@5 99.000 (99.229) +2022-11-14 16:13:34,164 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0757) Prec@1 91.000 (87.500) Prec@5 100.000 (99.250) +2022-11-14 16:13:34,185 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0756) Prec@1 88.000 (87.514) Prec@5 100.000 (99.270) +2022-11-14 16:13:34,204 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1132 (0.0766) Prec@1 80.000 (87.316) Prec@5 98.000 (99.237) +2022-11-14 16:13:34,223 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0761) Prec@1 92.000 (87.436) Prec@5 99.000 (99.231) +2022-11-14 16:13:34,237 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0760) Prec@1 89.000 (87.475) Prec@5 99.000 (99.225) +2022-11-14 16:13:34,256 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0762) Prec@1 88.000 (87.488) Prec@5 99.000 (99.220) +2022-11-14 16:13:34,274 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0756) Prec@1 92.000 (87.595) Prec@5 99.000 (99.214) +2022-11-14 16:13:34,290 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0429 (0.0749) Prec@1 94.000 (87.744) Prec@5 99.000 (99.209) +2022-11-14 16:13:34,305 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0745) Prec@1 91.000 (87.818) Prec@5 99.000 (99.205) +2022-11-14 16:13:34,323 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0744) Prec@1 89.000 (87.844) Prec@5 99.000 (99.200) +2022-11-14 16:13:34,340 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0751) Prec@1 81.000 (87.696) Prec@5 100.000 (99.217) +2022-11-14 16:13:34,357 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0749) Prec@1 90.000 (87.745) Prec@5 100.000 (99.234) +2022-11-14 16:13:34,377 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1045 (0.0755) Prec@1 83.000 (87.646) Prec@5 98.000 (99.208) +2022-11-14 16:13:34,396 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0750) Prec@1 91.000 (87.714) Prec@5 100.000 (99.224) +2022-11-14 16:13:34,413 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0754) Prec@1 87.000 (87.700) Prec@5 100.000 (99.240) +2022-11-14 16:13:34,431 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0751) Prec@1 87.000 (87.686) Prec@5 100.000 (99.255) +2022-11-14 16:13:34,448 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1080 (0.0758) Prec@1 84.000 (87.615) Prec@5 100.000 (99.269) +2022-11-14 16:13:34,470 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0757) Prec@1 89.000 (87.642) Prec@5 100.000 (99.283) +2022-11-14 16:13:34,488 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0755) Prec@1 89.000 (87.667) Prec@5 100.000 (99.296) +2022-11-14 16:13:34,505 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0759) Prec@1 84.000 (87.600) Prec@5 99.000 (99.291) +2022-11-14 16:13:34,526 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0760) Prec@1 87.000 (87.589) Prec@5 99.000 (99.286) +2022-11-14 16:13:34,546 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0760) Prec@1 90.000 (87.632) Prec@5 100.000 (99.298) +2022-11-14 16:13:34,562 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0761) Prec@1 87.000 (87.621) Prec@5 100.000 (99.310) +2022-11-14 16:13:34,581 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0765) Prec@1 86.000 (87.593) Prec@5 99.000 (99.305) +2022-11-14 16:13:34,599 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0764) Prec@1 88.000 (87.600) Prec@5 100.000 (99.317) +2022-11-14 16:13:34,616 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0763) Prec@1 87.000 (87.590) Prec@5 99.000 (99.311) +2022-11-14 16:13:34,636 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0762) Prec@1 87.000 (87.581) Prec@5 100.000 (99.323) +2022-11-14 16:13:34,655 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0763) Prec@1 89.000 (87.603) Prec@5 99.000 (99.317) +2022-11-14 16:13:34,673 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0273 (0.0755) Prec@1 95.000 (87.719) Prec@5 100.000 (99.328) +2022-11-14 16:13:34,689 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0758) Prec@1 83.000 (87.646) Prec@5 100.000 (99.338) +2022-11-14 16:13:34,705 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0757) Prec@1 90.000 (87.682) Prec@5 98.000 (99.318) +2022-11-14 16:13:34,727 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0755) Prec@1 90.000 (87.716) Prec@5 100.000 (99.328) +2022-11-14 16:13:34,744 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0754) Prec@1 87.000 (87.706) Prec@5 100.000 (99.338) +2022-11-14 16:13:34,761 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0751) Prec@1 91.000 (87.754) Prec@5 99.000 (99.333) +2022-11-14 16:13:34,778 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0750) Prec@1 90.000 (87.786) Prec@5 100.000 (99.343) +2022-11-14 16:13:34,795 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0755) Prec@1 86.000 (87.761) Prec@5 98.000 (99.324) +2022-11-14 16:13:34,813 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0751) Prec@1 92.000 (87.819) Prec@5 99.000 (99.319) +2022-11-14 16:13:34,832 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0747) Prec@1 92.000 (87.877) Prec@5 99.000 (99.315) +2022-11-14 16:13:34,853 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0744) Prec@1 93.000 (87.946) Prec@5 99.000 (99.311) +2022-11-14 16:13:34,872 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0746) Prec@1 86.000 (87.920) Prec@5 100.000 (99.320) +2022-11-14 16:13:34,887 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0744) Prec@1 91.000 (87.961) Prec@5 100.000 (99.329) +2022-11-14 16:13:34,903 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0744) Prec@1 88.000 (87.961) Prec@5 98.000 (99.312) +2022-11-14 16:13:34,921 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0746) Prec@1 85.000 (87.923) Prec@5 99.000 (99.308) +2022-11-14 16:13:34,937 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0748) Prec@1 88.000 (87.924) Prec@5 99.000 (99.304) +2022-11-14 16:13:34,954 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0746) Prec@1 90.000 (87.950) Prec@5 100.000 (99.312) +2022-11-14 16:13:34,974 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0747) Prec@1 87.000 (87.938) Prec@5 99.000 (99.309) +2022-11-14 16:13:34,994 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0748) Prec@1 88.000 (87.939) Prec@5 100.000 (99.317) +2022-11-14 16:13:35,011 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0749) Prec@1 88.000 (87.940) Prec@5 100.000 (99.325) +2022-11-14 16:13:35,027 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0749) Prec@1 89.000 (87.952) Prec@5 100.000 (99.333) +2022-11-14 16:13:35,046 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0747) Prec@1 89.000 (87.965) Prec@5 100.000 (99.341) +2022-11-14 16:13:35,067 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1152 (0.0751) Prec@1 82.000 (87.895) Prec@5 99.000 (99.337) +2022-11-14 16:13:35,085 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0751) Prec@1 87.000 (87.885) Prec@5 100.000 (99.345) +2022-11-14 16:13:35,100 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0752) Prec@1 85.000 (87.852) Prec@5 100.000 (99.352) +2022-11-14 16:13:35,117 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0751) Prec@1 87.000 (87.843) Prec@5 100.000 (99.360) +2022-11-14 16:13:35,136 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0750) Prec@1 91.000 (87.878) Prec@5 100.000 (99.367) +2022-11-14 16:13:35,154 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0749) Prec@1 91.000 (87.912) Prec@5 100.000 (99.374) +2022-11-14 16:13:35,174 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0746) Prec@1 92.000 (87.957) Prec@5 99.000 (99.370) +2022-11-14 16:13:35,192 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0748) Prec@1 85.000 (87.925) Prec@5 99.000 (99.366) +2022-11-14 16:13:35,213 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0749) Prec@1 87.000 (87.915) Prec@5 99.000 (99.362) +2022-11-14 16:13:35,230 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0751) Prec@1 86.000 (87.895) Prec@5 99.000 (99.358) +2022-11-14 16:13:35,247 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0750) Prec@1 91.000 (87.927) Prec@5 99.000 (99.354) +2022-11-14 16:13:35,267 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0748) Prec@1 93.000 (87.979) Prec@5 98.000 (99.340) +2022-11-14 16:13:35,283 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0750) Prec@1 83.000 (87.929) Prec@5 97.000 (99.316) +2022-11-14 16:13:35,297 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1072 (0.0753) Prec@1 82.000 (87.869) Prec@5 99.000 (99.313) +2022-11-14 16:13:35,314 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0752) Prec@1 89.000 (87.880) Prec@5 100.000 (99.320) +2022-11-14 16:13:35,378 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:13:35,733 Epoch: [318][0/500] Time 0.026 (0.026) Data 0.262 (0.262) Loss 0.0304 (0.0304) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:13:36,018 Epoch: [318][10/500] Time 0.028 (0.025) Data 0.002 (0.025) Loss 0.0195 (0.0250) Prec@1 97.000 (96.000) Prec@5 100.000 (99.500) +2022-11-14 16:13:36,354 Epoch: [318][20/500] Time 0.038 (0.027) Data 0.002 (0.014) Loss 0.0524 (0.0341) Prec@1 91.000 (94.333) Prec@5 99.000 (99.333) +2022-11-14 16:13:37,044 Epoch: [318][30/500] Time 0.069 (0.038) Data 0.002 (0.010) Loss 0.0130 (0.0289) Prec@1 98.000 (95.250) Prec@5 100.000 (99.500) +2022-11-14 16:13:37,728 Epoch: [318][40/500] Time 0.068 (0.044) Data 0.002 (0.008) Loss 0.0362 (0.0303) Prec@1 94.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 16:13:38,428 Epoch: [318][50/500] Time 0.073 (0.048) Data 0.002 (0.007) Loss 0.0263 (0.0297) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:13:39,138 Epoch: [318][60/500] Time 0.069 (0.050) Data 0.002 (0.006) Loss 0.0500 (0.0326) Prec@1 92.000 (94.571) Prec@5 100.000 (99.714) +2022-11-14 16:13:39,859 Epoch: [318][70/500] Time 0.071 (0.052) Data 0.002 (0.006) Loss 0.0280 (0.0320) Prec@1 95.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 16:13:40,541 Epoch: [318][80/500] Time 0.067 (0.053) Data 0.002 (0.005) Loss 0.0103 (0.0296) Prec@1 99.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:13:41,222 Epoch: [318][90/500] Time 0.064 (0.054) Data 0.002 (0.005) Loss 0.0254 (0.0292) Prec@1 97.000 (95.300) Prec@5 100.000 (99.800) +2022-11-14 16:13:41,906 Epoch: [318][100/500] Time 0.064 (0.055) Data 0.002 (0.005) Loss 0.0318 (0.0294) Prec@1 95.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 16:13:42,587 Epoch: [318][110/500] Time 0.054 (0.055) Data 0.002 (0.004) Loss 0.0231 (0.0289) Prec@1 97.000 (95.417) Prec@5 100.000 (99.833) +2022-11-14 16:13:43,263 Epoch: [318][120/500] Time 0.069 (0.056) Data 0.002 (0.004) Loss 0.0318 (0.0291) Prec@1 94.000 (95.308) Prec@5 100.000 (99.846) +2022-11-14 16:13:43,950 Epoch: [318][130/500] Time 0.068 (0.056) Data 0.002 (0.004) Loss 0.0241 (0.0287) Prec@1 97.000 (95.429) Prec@5 100.000 (99.857) +2022-11-14 16:13:44,627 Epoch: [318][140/500] Time 0.075 (0.056) Data 0.002 (0.004) Loss 0.0350 (0.0292) Prec@1 94.000 (95.333) Prec@5 100.000 (99.867) +2022-11-14 16:13:45,303 Epoch: [318][150/500] Time 0.075 (0.057) Data 0.002 (0.004) Loss 0.0369 (0.0296) Prec@1 94.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:13:46,015 Epoch: [318][160/500] Time 0.069 (0.057) Data 0.002 (0.004) Loss 0.0133 (0.0287) Prec@1 99.000 (95.471) Prec@5 100.000 (99.882) +2022-11-14 16:13:46,704 Epoch: [318][170/500] Time 0.053 (0.057) Data 0.002 (0.004) Loss 0.0346 (0.0290) Prec@1 93.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 16:13:47,375 Epoch: [318][180/500] Time 0.063 (0.057) Data 0.002 (0.004) Loss 0.0554 (0.0304) Prec@1 91.000 (95.105) Prec@5 99.000 (99.842) +2022-11-14 16:13:48,032 Epoch: [318][190/500] Time 0.070 (0.057) Data 0.002 (0.003) Loss 0.0232 (0.0300) Prec@1 97.000 (95.200) Prec@5 100.000 (99.850) +2022-11-14 16:13:48,716 Epoch: [318][200/500] Time 0.066 (0.058) Data 0.002 (0.003) Loss 0.0522 (0.0311) Prec@1 92.000 (95.048) Prec@5 99.000 (99.810) +2022-11-14 16:13:49,389 Epoch: [318][210/500] Time 0.055 (0.058) Data 0.002 (0.003) Loss 0.0581 (0.0323) Prec@1 90.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:13:50,119 Epoch: [318][220/500] Time 0.071 (0.058) Data 0.002 (0.003) Loss 0.0393 (0.0326) Prec@1 93.000 (94.739) Prec@5 100.000 (99.826) +2022-11-14 16:13:50,802 Epoch: [318][230/500] Time 0.057 (0.058) Data 0.002 (0.003) Loss 0.0466 (0.0332) Prec@1 92.000 (94.625) Prec@5 100.000 (99.833) +2022-11-14 16:13:51,474 Epoch: [318][240/500] Time 0.059 (0.058) Data 0.002 (0.003) Loss 0.0312 (0.0331) Prec@1 95.000 (94.640) Prec@5 100.000 (99.840) +2022-11-14 16:13:52,154 Epoch: [318][250/500] Time 0.050 (0.058) Data 0.002 (0.003) Loss 0.0249 (0.0328) Prec@1 95.000 (94.654) Prec@5 100.000 (99.846) +2022-11-14 16:13:52,820 Epoch: [318][260/500] Time 0.064 (0.058) Data 0.002 (0.003) Loss 0.0171 (0.0322) Prec@1 97.000 (94.741) Prec@5 99.000 (99.815) +2022-11-14 16:13:53,501 Epoch: [318][270/500] Time 0.068 (0.059) Data 0.002 (0.003) Loss 0.0346 (0.0323) Prec@1 95.000 (94.750) Prec@5 100.000 (99.821) +2022-11-14 16:13:54,150 Epoch: [318][280/500] Time 0.053 (0.058) Data 0.002 (0.003) Loss 0.0341 (0.0324) Prec@1 95.000 (94.759) Prec@5 100.000 (99.828) +2022-11-14 16:13:54,855 Epoch: [318][290/500] Time 0.071 (0.059) Data 0.002 (0.003) Loss 0.0394 (0.0326) Prec@1 95.000 (94.767) Prec@5 100.000 (99.833) +2022-11-14 16:13:55,519 Epoch: [318][300/500] Time 0.058 (0.059) Data 0.002 (0.003) Loss 0.0456 (0.0330) Prec@1 93.000 (94.710) Prec@5 100.000 (99.839) +2022-11-14 16:13:56,213 Epoch: [318][310/500] Time 0.066 (0.059) Data 0.002 (0.003) Loss 0.0292 (0.0329) Prec@1 94.000 (94.688) Prec@5 99.000 (99.812) +2022-11-14 16:13:56,762 Epoch: [318][320/500] Time 0.039 (0.059) Data 0.002 (0.003) Loss 0.0276 (0.0328) Prec@1 97.000 (94.758) Prec@5 100.000 (99.818) +2022-11-14 16:13:57,120 Epoch: [318][330/500] Time 0.037 (0.058) Data 0.002 (0.003) Loss 0.0245 (0.0325) Prec@1 97.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:13:57,466 Epoch: [318][340/500] Time 0.027 (0.057) Data 0.002 (0.003) Loss 0.0394 (0.0327) Prec@1 93.000 (94.771) Prec@5 100.000 (99.829) +2022-11-14 16:13:57,822 Epoch: [318][350/500] Time 0.031 (0.056) Data 0.004 (0.003) Loss 0.0187 (0.0323) Prec@1 98.000 (94.861) Prec@5 100.000 (99.833) +2022-11-14 16:13:58,178 Epoch: [318][360/500] Time 0.031 (0.056) Data 0.002 (0.003) Loss 0.0418 (0.0326) Prec@1 91.000 (94.757) Prec@5 100.000 (99.838) +2022-11-14 16:13:58,544 Epoch: [318][370/500] Time 0.038 (0.055) Data 0.002 (0.003) Loss 0.0308 (0.0325) Prec@1 96.000 (94.789) Prec@5 99.000 (99.816) +2022-11-14 16:13:58,900 Epoch: [318][380/500] Time 0.032 (0.054) Data 0.002 (0.003) Loss 0.0157 (0.0321) Prec@1 98.000 (94.872) Prec@5 100.000 (99.821) +2022-11-14 16:13:59,267 Epoch: [318][390/500] Time 0.034 (0.054) Data 0.002 (0.003) Loss 0.0285 (0.0320) Prec@1 95.000 (94.875) Prec@5 100.000 (99.825) +2022-11-14 16:13:59,628 Epoch: [318][400/500] Time 0.040 (0.053) Data 0.002 (0.003) Loss 0.0259 (0.0319) Prec@1 96.000 (94.902) Prec@5 100.000 (99.829) +2022-11-14 16:13:59,978 Epoch: [318][410/500] Time 0.038 (0.053) Data 0.002 (0.003) Loss 0.0267 (0.0317) Prec@1 98.000 (94.976) Prec@5 100.000 (99.833) +2022-11-14 16:14:00,344 Epoch: [318][420/500] Time 0.031 (0.052) Data 0.002 (0.003) Loss 0.0304 (0.0317) Prec@1 94.000 (94.953) Prec@5 100.000 (99.837) +2022-11-14 16:14:00,709 Epoch: [318][430/500] Time 0.037 (0.052) Data 0.002 (0.003) Loss 0.0207 (0.0315) Prec@1 96.000 (94.977) Prec@5 100.000 (99.841) +2022-11-14 16:14:01,087 Epoch: [318][440/500] Time 0.032 (0.051) Data 0.002 (0.003) Loss 0.0398 (0.0316) Prec@1 93.000 (94.933) Prec@5 100.000 (99.844) +2022-11-14 16:14:01,454 Epoch: [318][450/500] Time 0.037 (0.051) Data 0.002 (0.003) Loss 0.0354 (0.0317) Prec@1 95.000 (94.935) Prec@5 100.000 (99.848) +2022-11-14 16:14:01,807 Epoch: [318][460/500] Time 0.034 (0.051) Data 0.002 (0.003) Loss 0.0265 (0.0316) Prec@1 95.000 (94.936) Prec@5 100.000 (99.851) +2022-11-14 16:14:02,157 Epoch: [318][470/500] Time 0.031 (0.050) Data 0.001 (0.003) Loss 0.0244 (0.0315) Prec@1 95.000 (94.938) Prec@5 100.000 (99.854) +2022-11-14 16:14:02,569 Epoch: [318][480/500] Time 0.041 (0.050) Data 0.002 (0.003) Loss 0.0443 (0.0317) Prec@1 92.000 (94.878) Prec@5 99.000 (99.837) +2022-11-14 16:14:03,357 Epoch: [318][490/500] Time 0.068 (0.050) Data 0.002 (0.003) Loss 0.0376 (0.0318) Prec@1 93.000 (94.840) Prec@5 100.000 (99.840) +2022-11-14 16:14:04,039 Epoch: [318][499/500] Time 0.078 (0.050) Data 0.002 (0.003) Loss 0.0443 (0.0321) Prec@1 93.000 (94.804) Prec@5 100.000 (99.843) +2022-11-14 16:14:04,372 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0530 (0.0530) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:14:04,381 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0621) Prec@1 89.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 16:14:04,390 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0663) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:14:04,404 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0689) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:14:04,414 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0701) Prec@1 90.000 (88.800) Prec@5 99.000 (99.400) +2022-11-14 16:14:04,424 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0663) Prec@1 92.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 16:14:04,434 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0669) Prec@1 90.000 (89.429) Prec@5 100.000 (99.571) +2022-11-14 16:14:04,447 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0691) Prec@1 87.000 (89.125) Prec@5 100.000 (99.625) +2022-11-14 16:14:04,457 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0697) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:14:04,470 Test: [9/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0710) Prec@1 87.000 (88.800) Prec@5 97.000 (99.400) +2022-11-14 16:14:04,484 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0707) Prec@1 88.000 (88.727) Prec@5 99.000 (99.364) +2022-11-14 16:14:04,497 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0728) Prec@1 86.000 (88.500) Prec@5 100.000 (99.417) +2022-11-14 16:14:04,511 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0710) Prec@1 91.000 (88.692) Prec@5 100.000 (99.462) +2022-11-14 16:14:04,529 Test: [13/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0714) Prec@1 88.000 (88.643) Prec@5 99.000 (99.429) +2022-11-14 16:14:04,543 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0714) Prec@1 90.000 (88.733) Prec@5 100.000 (99.467) +2022-11-14 16:14:04,555 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0716) Prec@1 86.000 (88.562) Prec@5 99.000 (99.438) +2022-11-14 16:14:04,567 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0701) Prec@1 92.000 (88.765) Prec@5 98.000 (99.353) +2022-11-14 16:14:04,580 Test: [17/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0719) Prec@1 83.000 (88.444) Prec@5 100.000 (99.389) +2022-11-14 16:14:04,594 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0735) Prec@1 84.000 (88.211) Prec@5 98.000 (99.316) +2022-11-14 16:14:04,608 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0743) Prec@1 86.000 (88.100) Prec@5 98.000 (99.250) +2022-11-14 16:14:04,622 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0748) Prec@1 86.000 (88.000) Prec@5 99.000 (99.238) +2022-11-14 16:14:04,635 Test: [21/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0753) Prec@1 87.000 (87.955) Prec@5 98.000 (99.182) +2022-11-14 16:14:04,648 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0763) Prec@1 84.000 (87.783) Prec@5 99.000 (99.174) +2022-11-14 16:14:04,661 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0764) Prec@1 88.000 (87.792) Prec@5 100.000 (99.208) +2022-11-14 16:14:04,675 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0773) Prec@1 85.000 (87.680) Prec@5 99.000 (99.200) +2022-11-14 16:14:04,690 Test: [25/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0779) Prec@1 86.000 (87.615) Prec@5 98.000 (99.154) +2022-11-14 16:14:04,704 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0769) Prec@1 92.000 (87.778) Prec@5 100.000 (99.185) +2022-11-14 16:14:04,717 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0766) Prec@1 90.000 (87.857) Prec@5 100.000 (99.214) +2022-11-14 16:14:04,732 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0760) Prec@1 91.000 (87.966) Prec@5 100.000 (99.241) +2022-11-14 16:14:04,747 Test: [29/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0760) Prec@1 86.000 (87.900) Prec@5 100.000 (99.267) +2022-11-14 16:14:04,760 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0758) Prec@1 90.000 (87.968) Prec@5 99.000 (99.258) +2022-11-14 16:14:04,774 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0751) Prec@1 93.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 16:14:04,788 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0748) Prec@1 90.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 16:14:04,803 Test: [33/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0756) Prec@1 84.000 (88.059) Prec@5 99.000 (99.265) +2022-11-14 16:14:04,816 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0761) Prec@1 87.000 (88.029) Prec@5 99.000 (99.257) +2022-11-14 16:14:04,829 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0758) Prec@1 91.000 (88.111) Prec@5 99.000 (99.250) +2022-11-14 16:14:04,844 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0758) Prec@1 87.000 (88.081) Prec@5 98.000 (99.216) +2022-11-14 16:14:04,857 Test: [37/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1004 (0.0764) Prec@1 84.000 (87.974) Prec@5 100.000 (99.237) +2022-11-14 16:14:04,873 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0759) Prec@1 91.000 (88.051) Prec@5 99.000 (99.231) +2022-11-14 16:14:04,888 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0759) Prec@1 86.000 (88.000) Prec@5 97.000 (99.175) +2022-11-14 16:14:04,898 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0765) Prec@1 85.000 (87.927) Prec@5 98.000 (99.146) +2022-11-14 16:14:04,910 Test: [41/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0763) Prec@1 90.000 (87.976) Prec@5 99.000 (99.143) +2022-11-14 16:14:04,925 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0758) Prec@1 90.000 (88.023) Prec@5 99.000 (99.140) +2022-11-14 16:14:04,939 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0755) Prec@1 91.000 (88.091) Prec@5 98.000 (99.114) +2022-11-14 16:14:04,952 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0756) Prec@1 85.000 (88.022) Prec@5 99.000 (99.111) +2022-11-14 16:14:04,966 Test: [45/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0759) Prec@1 85.000 (87.957) Prec@5 100.000 (99.130) +2022-11-14 16:14:04,980 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0754) Prec@1 90.000 (88.000) Prec@5 100.000 (99.149) +2022-11-14 16:14:04,995 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0760) Prec@1 84.000 (87.917) Prec@5 99.000 (99.146) +2022-11-14 16:14:05,010 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0757) Prec@1 89.000 (87.939) Prec@5 100.000 (99.163) +2022-11-14 16:14:05,024 Test: [49/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0763) Prec@1 85.000 (87.880) Prec@5 99.000 (99.160) +2022-11-14 16:14:05,037 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0521 (0.0758) Prec@1 92.000 (87.961) Prec@5 100.000 (99.176) +2022-11-14 16:14:05,050 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0754) Prec@1 90.000 (88.000) Prec@5 100.000 (99.192) +2022-11-14 16:14:05,063 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0751) Prec@1 92.000 (88.075) Prec@5 100.000 (99.208) +2022-11-14 16:14:05,078 Test: [53/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0751) Prec@1 88.000 (88.074) Prec@5 99.000 (99.204) +2022-11-14 16:14:05,092 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0756) Prec@1 85.000 (88.018) Prec@5 100.000 (99.218) +2022-11-14 16:14:05,105 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0755) Prec@1 89.000 (88.036) Prec@5 99.000 (99.214) +2022-11-14 16:14:05,117 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0757) Prec@1 86.000 (88.000) Prec@5 100.000 (99.228) +2022-11-14 16:14:05,132 Test: [57/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0755) Prec@1 91.000 (88.052) Prec@5 100.000 (99.241) +2022-11-14 16:14:05,147 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0757) Prec@1 85.000 (88.000) Prec@5 99.000 (99.237) +2022-11-14 16:14:05,160 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0758) Prec@1 86.000 (87.967) Prec@5 100.000 (99.250) +2022-11-14 16:14:05,173 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0758) Prec@1 89.000 (87.984) Prec@5 99.000 (99.246) +2022-11-14 16:14:05,187 Test: [61/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0757) Prec@1 89.000 (88.000) Prec@5 99.000 (99.242) +2022-11-14 16:14:05,202 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0754) Prec@1 92.000 (88.063) Prec@5 100.000 (99.254) +2022-11-14 16:14:05,214 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0245 (0.0746) Prec@1 96.000 (88.188) Prec@5 100.000 (99.266) +2022-11-14 16:14:05,226 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0747) Prec@1 87.000 (88.169) Prec@5 100.000 (99.277) +2022-11-14 16:14:05,240 Test: [65/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0748) Prec@1 88.000 (88.167) Prec@5 99.000 (99.273) +2022-11-14 16:14:05,254 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0744) Prec@1 92.000 (88.224) Prec@5 100.000 (99.284) +2022-11-14 16:14:05,268 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0742) Prec@1 91.000 (88.265) Prec@5 99.000 (99.279) +2022-11-14 16:14:05,282 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0743) Prec@1 89.000 (88.275) Prec@5 96.000 (99.232) +2022-11-14 16:14:05,297 Test: [69/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0745) Prec@1 85.000 (88.229) Prec@5 98.000 (99.214) +2022-11-14 16:14:05,310 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.0749) Prec@1 81.000 (88.127) Prec@5 99.000 (99.211) +2022-11-14 16:14:05,323 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0746) Prec@1 92.000 (88.181) Prec@5 100.000 (99.222) +2022-11-14 16:14:05,338 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0395 (0.0741) Prec@1 95.000 (88.274) Prec@5 100.000 (99.233) +2022-11-14 16:14:05,354 Test: [73/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0402 (0.0736) Prec@1 94.000 (88.351) Prec@5 100.000 (99.243) +2022-11-14 16:14:05,366 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.0741) Prec@1 83.000 (88.280) Prec@5 99.000 (99.240) +2022-11-14 16:14:05,380 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0739) Prec@1 91.000 (88.316) Prec@5 100.000 (99.250) +2022-11-14 16:14:05,394 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0741) Prec@1 88.000 (88.312) Prec@5 98.000 (99.234) +2022-11-14 16:14:05,408 Test: [77/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0742) Prec@1 86.000 (88.282) Prec@5 98.000 (99.218) +2022-11-14 16:14:05,421 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0743) Prec@1 88.000 (88.278) Prec@5 99.000 (99.215) +2022-11-14 16:14:05,436 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0743) Prec@1 87.000 (88.263) Prec@5 99.000 (99.213) +2022-11-14 16:14:05,451 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0744) Prec@1 86.000 (88.235) Prec@5 100.000 (99.222) +2022-11-14 16:14:05,465 Test: [81/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0746) Prec@1 87.000 (88.220) Prec@5 99.000 (99.220) +2022-11-14 16:14:05,479 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0749) Prec@1 85.000 (88.181) Prec@5 100.000 (99.229) +2022-11-14 16:14:05,492 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0749) Prec@1 85.000 (88.143) Prec@5 99.000 (99.226) +2022-11-14 16:14:05,507 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0752) Prec@1 81.000 (88.059) Prec@5 100.000 (99.235) +2022-11-14 16:14:05,523 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0755) Prec@1 83.000 (88.000) Prec@5 100.000 (99.244) +2022-11-14 16:14:05,538 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 90.000 (88.023) Prec@5 100.000 (99.253) +2022-11-14 16:14:05,552 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0753) Prec@1 89.000 (88.034) Prec@5 97.000 (99.227) +2022-11-14 16:14:05,566 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0751) Prec@1 93.000 (88.090) Prec@5 100.000 (99.236) +2022-11-14 16:14:05,580 Test: [89/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0750) Prec@1 90.000 (88.111) Prec@5 100.000 (99.244) +2022-11-14 16:14:05,593 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0398 (0.0747) Prec@1 93.000 (88.165) Prec@5 100.000 (99.253) +2022-11-14 16:14:05,608 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0745) Prec@1 91.000 (88.196) Prec@5 99.000 (99.250) +2022-11-14 16:14:05,621 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0745) Prec@1 88.000 (88.194) Prec@5 99.000 (99.247) +2022-11-14 16:14:05,636 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0745) Prec@1 88.000 (88.191) Prec@5 99.000 (99.245) +2022-11-14 16:14:05,648 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0744) Prec@1 89.000 (88.200) Prec@5 100.000 (99.253) +2022-11-14 16:14:05,661 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0744) Prec@1 87.000 (88.188) Prec@5 98.000 (99.240) +2022-11-14 16:14:05,676 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0387 (0.0740) Prec@1 94.000 (88.247) Prec@5 99.000 (99.237) +2022-11-14 16:14:05,691 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0743) Prec@1 86.000 (88.224) Prec@5 98.000 (99.224) +2022-11-14 16:14:05,703 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0745) Prec@1 85.000 (88.192) Prec@5 100.000 (99.232) +2022-11-14 16:14:05,714 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0745) Prec@1 87.000 (88.180) Prec@5 100.000 (99.240) +2022-11-14 16:14:05,776 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:14:06,155 Epoch: [319][0/500] Time 0.025 (0.025) Data 0.290 (0.290) Loss 0.0614 (0.0614) Prec@1 91.000 (91.000) Prec@5 97.000 (97.000) +2022-11-14 16:14:06,523 Epoch: [319][10/500] Time 0.035 (0.032) Data 0.002 (0.028) Loss 0.0238 (0.0426) Prec@1 97.000 (94.000) Prec@5 100.000 (98.500) +2022-11-14 16:14:06,915 Epoch: [319][20/500] Time 0.041 (0.033) Data 0.002 (0.015) Loss 0.0408 (0.0420) Prec@1 92.000 (93.333) Prec@5 99.000 (98.667) +2022-11-14 16:14:07,316 Epoch: [319][30/500] Time 0.039 (0.034) Data 0.002 (0.011) Loss 0.0355 (0.0404) Prec@1 94.000 (93.500) Prec@5 100.000 (99.000) +2022-11-14 16:14:07,720 Epoch: [319][40/500] Time 0.039 (0.035) Data 0.002 (0.009) Loss 0.0235 (0.0370) Prec@1 96.000 (94.000) Prec@5 100.000 (99.200) +2022-11-14 16:14:08,123 Epoch: [319][50/500] Time 0.034 (0.035) Data 0.002 (0.008) Loss 0.0473 (0.0387) Prec@1 92.000 (93.667) Prec@5 100.000 (99.333) +2022-11-14 16:14:08,535 Epoch: [319][60/500] Time 0.039 (0.035) Data 0.002 (0.007) Loss 0.0266 (0.0370) Prec@1 95.000 (93.857) Prec@5 100.000 (99.429) +2022-11-14 16:14:08,935 Epoch: [319][70/500] Time 0.037 (0.035) Data 0.002 (0.006) Loss 0.0234 (0.0353) Prec@1 97.000 (94.250) Prec@5 100.000 (99.500) +2022-11-14 16:14:09,352 Epoch: [319][80/500] Time 0.042 (0.035) Data 0.002 (0.006) Loss 0.0226 (0.0339) Prec@1 97.000 (94.556) Prec@5 100.000 (99.556) +2022-11-14 16:14:09,754 Epoch: [319][90/500] Time 0.040 (0.035) Data 0.002 (0.005) Loss 0.0454 (0.0350) Prec@1 92.000 (94.300) Prec@5 99.000 (99.500) +2022-11-14 16:14:10,169 Epoch: [319][100/500] Time 0.032 (0.036) Data 0.002 (0.005) Loss 0.0716 (0.0383) Prec@1 88.000 (93.727) Prec@5 99.000 (99.455) +2022-11-14 16:14:10,573 Epoch: [319][110/500] Time 0.040 (0.036) Data 0.002 (0.005) Loss 0.0286 (0.0375) Prec@1 95.000 (93.833) Prec@5 100.000 (99.500) +2022-11-14 16:14:10,992 Epoch: [319][120/500] Time 0.041 (0.036) Data 0.003 (0.004) Loss 0.0140 (0.0357) Prec@1 97.000 (94.077) Prec@5 100.000 (99.538) +2022-11-14 16:14:11,408 Epoch: [319][130/500] Time 0.038 (0.036) Data 0.002 (0.004) Loss 0.0198 (0.0346) Prec@1 98.000 (94.357) Prec@5 100.000 (99.571) +2022-11-14 16:14:11,829 Epoch: [319][140/500] Time 0.039 (0.036) Data 0.002 (0.004) Loss 0.0358 (0.0347) Prec@1 94.000 (94.333) Prec@5 100.000 (99.600) +2022-11-14 16:14:12,329 Epoch: [319][150/500] Time 0.074 (0.036) Data 0.002 (0.004) Loss 0.0178 (0.0336) Prec@1 97.000 (94.500) Prec@5 100.000 (99.625) +2022-11-14 16:14:13,124 Epoch: [319][160/500] Time 0.080 (0.038) Data 0.002 (0.004) Loss 0.0415 (0.0341) Prec@1 91.000 (94.294) Prec@5 100.000 (99.647) +2022-11-14 16:14:13,888 Epoch: [319][170/500] Time 0.074 (0.040) Data 0.002 (0.004) Loss 0.0271 (0.0337) Prec@1 97.000 (94.444) Prec@5 100.000 (99.667) +2022-11-14 16:14:14,661 Epoch: [319][180/500] Time 0.076 (0.042) Data 0.002 (0.004) Loss 0.0319 (0.0336) Prec@1 94.000 (94.421) Prec@5 100.000 (99.684) +2022-11-14 16:14:15,425 Epoch: [319][190/500] Time 0.066 (0.043) Data 0.002 (0.003) Loss 0.0353 (0.0337) Prec@1 93.000 (94.350) Prec@5 99.000 (99.650) +2022-11-14 16:14:16,138 Epoch: [319][200/500] Time 0.061 (0.044) Data 0.002 (0.003) Loss 0.0145 (0.0328) Prec@1 99.000 (94.571) Prec@5 100.000 (99.667) +2022-11-14 16:14:16,876 Epoch: [319][210/500] Time 0.074 (0.045) Data 0.003 (0.003) Loss 0.0421 (0.0332) Prec@1 94.000 (94.545) Prec@5 100.000 (99.682) +2022-11-14 16:14:17,664 Epoch: [319][220/500] Time 0.082 (0.046) Data 0.002 (0.003) Loss 0.0176 (0.0325) Prec@1 97.000 (94.652) Prec@5 100.000 (99.696) +2022-11-14 16:14:18,436 Epoch: [319][230/500] Time 0.079 (0.047) Data 0.002 (0.003) Loss 0.0640 (0.0338) Prec@1 90.000 (94.458) Prec@5 100.000 (99.708) +2022-11-14 16:14:19,219 Epoch: [319][240/500] Time 0.090 (0.048) Data 0.002 (0.003) Loss 0.0447 (0.0343) Prec@1 92.000 (94.360) Prec@5 100.000 (99.720) +2022-11-14 16:14:20,004 Epoch: [319][250/500] Time 0.071 (0.049) Data 0.002 (0.003) Loss 0.0398 (0.0345) Prec@1 94.000 (94.346) Prec@5 98.000 (99.654) +2022-11-14 16:14:20,790 Epoch: [319][260/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0192 (0.0339) Prec@1 97.000 (94.444) Prec@5 100.000 (99.667) +2022-11-14 16:14:21,580 Epoch: [319][270/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0219 (0.0335) Prec@1 96.000 (94.500) Prec@5 99.000 (99.643) +2022-11-14 16:14:22,361 Epoch: [319][280/500] Time 0.073 (0.052) Data 0.002 (0.003) Loss 0.0133 (0.0328) Prec@1 98.000 (94.621) Prec@5 100.000 (99.655) +2022-11-14 16:14:23,123 Epoch: [319][290/500] Time 0.081 (0.052) Data 0.002 (0.003) Loss 0.0243 (0.0325) Prec@1 94.000 (94.600) Prec@5 100.000 (99.667) +2022-11-14 16:14:23,911 Epoch: [319][300/500] Time 0.077 (0.053) Data 0.002 (0.003) Loss 0.0242 (0.0322) Prec@1 96.000 (94.645) Prec@5 100.000 (99.677) +2022-11-14 16:14:24,711 Epoch: [319][310/500] Time 0.079 (0.053) Data 0.003 (0.003) Loss 0.0111 (0.0316) Prec@1 99.000 (94.781) Prec@5 100.000 (99.688) +2022-11-14 16:14:25,287 Epoch: [319][320/500] Time 0.040 (0.053) Data 0.002 (0.003) Loss 0.0295 (0.0315) Prec@1 96.000 (94.818) Prec@5 99.000 (99.667) +2022-11-14 16:14:25,675 Epoch: [319][330/500] Time 0.039 (0.053) Data 0.002 (0.003) Loss 0.0411 (0.0318) Prec@1 93.000 (94.765) Prec@5 100.000 (99.676) +2022-11-14 16:14:26,068 Epoch: [319][340/500] Time 0.032 (0.052) Data 0.002 (0.003) Loss 0.0248 (0.0316) Prec@1 93.000 (94.714) Prec@5 100.000 (99.686) +2022-11-14 16:14:26,472 Epoch: [319][350/500] Time 0.036 (0.052) Data 0.002 (0.003) Loss 0.0286 (0.0315) Prec@1 94.000 (94.694) Prec@5 100.000 (99.694) +2022-11-14 16:14:26,871 Epoch: [319][360/500] Time 0.040 (0.051) Data 0.002 (0.003) Loss 0.0637 (0.0324) Prec@1 91.000 (94.595) Prec@5 99.000 (99.676) +2022-11-14 16:14:27,288 Epoch: [319][370/500] Time 0.041 (0.051) Data 0.002 (0.003) Loss 0.0293 (0.0323) Prec@1 97.000 (94.658) Prec@5 100.000 (99.684) +2022-11-14 16:14:27,686 Epoch: [319][380/500] Time 0.039 (0.050) Data 0.002 (0.003) Loss 0.0394 (0.0325) Prec@1 95.000 (94.667) Prec@5 100.000 (99.692) +2022-11-14 16:14:28,082 Epoch: [319][390/500] Time 0.035 (0.050) Data 0.002 (0.003) Loss 0.0353 (0.0326) Prec@1 95.000 (94.675) Prec@5 100.000 (99.700) +2022-11-14 16:14:28,489 Epoch: [319][400/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0432 (0.0328) Prec@1 92.000 (94.610) Prec@5 100.000 (99.707) +2022-11-14 16:14:28,881 Epoch: [319][410/500] Time 0.041 (0.049) Data 0.002 (0.003) Loss 0.0429 (0.0331) Prec@1 91.000 (94.524) Prec@5 100.000 (99.714) +2022-11-14 16:14:29,293 Epoch: [319][420/500] Time 0.034 (0.049) Data 0.002 (0.003) Loss 0.0341 (0.0331) Prec@1 92.000 (94.465) Prec@5 100.000 (99.721) +2022-11-14 16:14:29,689 Epoch: [319][430/500] Time 0.038 (0.049) Data 0.002 (0.003) Loss 0.0461 (0.0334) Prec@1 91.000 (94.386) Prec@5 100.000 (99.727) +2022-11-14 16:14:30,073 Epoch: [319][440/500] Time 0.038 (0.048) Data 0.002 (0.003) Loss 0.0322 (0.0333) Prec@1 95.000 (94.400) Prec@5 100.000 (99.733) +2022-11-14 16:14:30,476 Epoch: [319][450/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0257 (0.0332) Prec@1 96.000 (94.435) Prec@5 100.000 (99.739) +2022-11-14 16:14:30,874 Epoch: [319][460/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0259 (0.0330) Prec@1 95.000 (94.447) Prec@5 100.000 (99.745) +2022-11-14 16:14:31,271 Epoch: [319][470/500] Time 0.045 (0.048) Data 0.002 (0.003) Loss 0.0151 (0.0327) Prec@1 98.000 (94.521) Prec@5 100.000 (99.750) +2022-11-14 16:14:31,664 Epoch: [319][480/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0181 (0.0324) Prec@1 97.000 (94.571) Prec@5 99.000 (99.735) +2022-11-14 16:14:32,072 Epoch: [319][490/500] Time 0.040 (0.047) Data 0.002 (0.003) Loss 0.0448 (0.0326) Prec@1 94.000 (94.560) Prec@5 100.000 (99.740) +2022-11-14 16:14:32,425 Epoch: [319][499/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0250 (0.0325) Prec@1 98.000 (94.627) Prec@5 100.000 (99.745) +2022-11-14 16:14:32,753 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0620) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:14:32,761 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0631 (0.0625) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:14:32,771 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0637) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:14:32,784 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0677) Prec@1 88.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 16:14:32,793 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0691) Prec@1 89.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 16:14:32,801 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0707) Prec@1 88.000 (88.667) Prec@5 98.000 (99.500) +2022-11-14 16:14:32,811 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0718) Prec@1 87.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 16:14:32,825 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0730) Prec@1 89.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 16:14:32,833 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0735) Prec@1 88.000 (88.444) Prec@5 100.000 (99.444) +2022-11-14 16:14:32,844 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0749) Prec@1 85.000 (88.100) Prec@5 99.000 (99.400) +2022-11-14 16:14:32,859 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0480 (0.0725) Prec@1 93.000 (88.545) Prec@5 99.000 (99.364) +2022-11-14 16:14:32,872 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0739) Prec@1 85.000 (88.250) Prec@5 100.000 (99.417) +2022-11-14 16:14:32,888 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0733) Prec@1 88.000 (88.231) Prec@5 100.000 (99.462) +2022-11-14 16:14:32,902 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0744) Prec@1 89.000 (88.286) Prec@5 98.000 (99.357) +2022-11-14 16:14:32,916 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0747) Prec@1 88.000 (88.267) Prec@5 99.000 (99.333) +2022-11-14 16:14:32,929 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0747) Prec@1 88.000 (88.250) Prec@5 98.000 (99.250) +2022-11-14 16:14:32,941 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 90.000 (88.353) Prec@5 98.000 (99.176) +2022-11-14 16:14:32,956 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1212 (0.0770) Prec@1 83.000 (88.056) Prec@5 100.000 (99.222) +2022-11-14 16:14:32,971 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0765) Prec@1 89.000 (88.105) Prec@5 97.000 (99.105) +2022-11-14 16:14:32,984 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0774) Prec@1 86.000 (88.000) Prec@5 98.000 (99.050) +2022-11-14 16:14:32,999 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0779) Prec@1 88.000 (88.000) Prec@5 99.000 (99.048) +2022-11-14 16:14:33,014 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0777) Prec@1 87.000 (87.955) Prec@5 99.000 (99.045) +2022-11-14 16:14:33,028 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.0790) Prec@1 85.000 (87.826) Prec@5 99.000 (99.043) +2022-11-14 16:14:33,040 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0797) Prec@1 84.000 (87.667) Prec@5 100.000 (99.083) +2022-11-14 16:14:33,054 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0805) Prec@1 84.000 (87.520) Prec@5 100.000 (99.120) +2022-11-14 16:14:33,067 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0811) Prec@1 84.000 (87.385) Prec@5 99.000 (99.115) +2022-11-14 16:14:33,081 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0448 (0.0797) Prec@1 93.000 (87.593) Prec@5 100.000 (99.148) +2022-11-14 16:14:33,095 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0795) Prec@1 88.000 (87.607) Prec@5 100.000 (99.179) +2022-11-14 16:14:33,107 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0796) Prec@1 86.000 (87.552) Prec@5 100.000 (99.207) +2022-11-14 16:14:33,123 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0791) Prec@1 90.000 (87.633) Prec@5 99.000 (99.200) +2022-11-14 16:14:33,137 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0787) Prec@1 89.000 (87.677) Prec@5 100.000 (99.226) +2022-11-14 16:14:33,152 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0793) Prec@1 84.000 (87.562) Prec@5 97.000 (99.156) +2022-11-14 16:14:33,169 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0797) Prec@1 85.000 (87.485) Prec@5 100.000 (99.182) +2022-11-14 16:14:33,183 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0804) Prec@1 83.000 (87.353) Prec@5 99.000 (99.176) +2022-11-14 16:14:33,197 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0803) Prec@1 84.000 (87.257) Prec@5 98.000 (99.143) +2022-11-14 16:14:33,214 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0801) Prec@1 90.000 (87.333) Prec@5 100.000 (99.167) +2022-11-14 16:14:33,227 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0803) Prec@1 85.000 (87.270) Prec@5 99.000 (99.162) +2022-11-14 16:14:33,241 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.0812) Prec@1 82.000 (87.132) Prec@5 99.000 (99.158) +2022-11-14 16:14:33,254 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0805) Prec@1 92.000 (87.256) Prec@5 99.000 (99.154) +2022-11-14 16:14:33,271 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0800) Prec@1 90.000 (87.325) Prec@5 99.000 (99.150) +2022-11-14 16:14:33,283 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0806) Prec@1 85.000 (87.268) Prec@5 99.000 (99.146) +2022-11-14 16:14:33,296 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0802) Prec@1 91.000 (87.357) Prec@5 98.000 (99.119) +2022-11-14 16:14:33,310 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0798) Prec@1 90.000 (87.419) Prec@5 99.000 (99.116) +2022-11-14 16:14:33,325 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0797) Prec@1 88.000 (87.432) Prec@5 99.000 (99.114) +2022-11-14 16:14:33,340 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0793) Prec@1 90.000 (87.489) Prec@5 99.000 (99.111) +2022-11-14 16:14:33,355 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0798) Prec@1 83.000 (87.391) Prec@5 99.000 (99.109) +2022-11-14 16:14:33,370 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0794) Prec@1 91.000 (87.468) Prec@5 100.000 (99.128) +2022-11-14 16:14:33,382 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0798) Prec@1 84.000 (87.396) Prec@5 99.000 (99.125) +2022-11-14 16:14:33,394 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0796) Prec@1 88.000 (87.408) Prec@5 100.000 (99.143) +2022-11-14 16:14:33,408 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1214 (0.0804) Prec@1 83.000 (87.320) Prec@5 97.000 (99.100) +2022-11-14 16:14:33,423 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0799) Prec@1 92.000 (87.412) Prec@5 99.000 (99.098) +2022-11-14 16:14:33,437 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0798) Prec@1 88.000 (87.423) Prec@5 100.000 (99.115) +2022-11-14 16:14:33,450 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0798) Prec@1 87.000 (87.415) Prec@5 100.000 (99.132) +2022-11-14 16:14:33,463 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0801) Prec@1 85.000 (87.370) Prec@5 99.000 (99.130) +2022-11-14 16:14:33,479 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0805) Prec@1 85.000 (87.327) Prec@5 99.000 (99.127) +2022-11-14 16:14:33,494 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0805) Prec@1 88.000 (87.339) Prec@5 99.000 (99.125) +2022-11-14 16:14:33,508 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0806) Prec@1 86.000 (87.316) Prec@5 99.000 (99.123) +2022-11-14 16:14:33,521 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0805) Prec@1 88.000 (87.328) Prec@5 99.000 (99.121) +2022-11-14 16:14:33,533 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0808) Prec@1 84.000 (87.271) Prec@5 99.000 (99.119) +2022-11-14 16:14:33,547 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0804) Prec@1 91.000 (87.333) Prec@5 100.000 (99.133) +2022-11-14 16:14:33,561 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0806) Prec@1 85.000 (87.295) Prec@5 99.000 (99.131) +2022-11-14 16:14:33,574 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0804) Prec@1 88.000 (87.306) Prec@5 100.000 (99.145) +2022-11-14 16:14:33,588 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0801) Prec@1 90.000 (87.349) Prec@5 100.000 (99.159) +2022-11-14 16:14:33,599 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0796) Prec@1 93.000 (87.438) Prec@5 100.000 (99.172) +2022-11-14 16:14:33,613 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0796) Prec@1 89.000 (87.462) Prec@5 100.000 (99.185) +2022-11-14 16:14:33,628 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0796) Prec@1 87.000 (87.455) Prec@5 98.000 (99.167) +2022-11-14 16:14:33,643 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0791) Prec@1 93.000 (87.537) Prec@5 100.000 (99.179) +2022-11-14 16:14:33,656 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0793) Prec@1 86.000 (87.515) Prec@5 97.000 (99.147) +2022-11-14 16:14:33,671 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0789) Prec@1 92.000 (87.580) Prec@5 99.000 (99.145) +2022-11-14 16:14:33,685 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0789) Prec@1 89.000 (87.600) Prec@5 99.000 (99.143) +2022-11-14 16:14:33,697 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.0794) Prec@1 82.000 (87.521) Prec@5 99.000 (99.141) +2022-11-14 16:14:33,711 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0792) Prec@1 90.000 (87.556) Prec@5 100.000 (99.153) +2022-11-14 16:14:33,725 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0790) Prec@1 90.000 (87.589) Prec@5 100.000 (99.164) +2022-11-14 16:14:33,738 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0786) Prec@1 94.000 (87.676) Prec@5 100.000 (99.176) +2022-11-14 16:14:33,753 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0787) Prec@1 86.000 (87.653) Prec@5 100.000 (99.187) +2022-11-14 16:14:33,767 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0785) Prec@1 91.000 (87.697) Prec@5 98.000 (99.171) +2022-11-14 16:14:33,781 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0783) Prec@1 90.000 (87.727) Prec@5 99.000 (99.169) +2022-11-14 16:14:33,795 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0785) Prec@1 84.000 (87.679) Prec@5 97.000 (99.141) +2022-11-14 16:14:33,808 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0456 (0.0781) Prec@1 94.000 (87.759) Prec@5 99.000 (99.139) +2022-11-14 16:14:33,822 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0780) Prec@1 86.000 (87.737) Prec@5 100.000 (99.150) +2022-11-14 16:14:33,835 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0782) Prec@1 85.000 (87.704) Prec@5 99.000 (99.148) +2022-11-14 16:14:33,848 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0781) Prec@1 87.000 (87.695) Prec@5 99.000 (99.146) +2022-11-14 16:14:33,864 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0782) Prec@1 87.000 (87.687) Prec@5 100.000 (99.157) +2022-11-14 16:14:33,879 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0783) Prec@1 86.000 (87.667) Prec@5 100.000 (99.167) +2022-11-14 16:14:33,893 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1089 (0.0786) Prec@1 83.000 (87.612) Prec@5 100.000 (99.176) +2022-11-14 16:14:33,905 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0788) Prec@1 84.000 (87.570) Prec@5 99.000 (99.174) +2022-11-14 16:14:33,919 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0785) Prec@1 90.000 (87.598) Prec@5 99.000 (99.172) +2022-11-14 16:14:33,934 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0784) Prec@1 90.000 (87.625) Prec@5 99.000 (99.170) +2022-11-14 16:14:33,948 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0783) Prec@1 88.000 (87.629) Prec@5 99.000 (99.169) +2022-11-14 16:14:33,962 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0784) Prec@1 89.000 (87.644) Prec@5 100.000 (99.178) +2022-11-14 16:14:33,977 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0782) Prec@1 88.000 (87.648) Prec@5 100.000 (99.187) +2022-11-14 16:14:33,992 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0780) Prec@1 93.000 (87.707) Prec@5 98.000 (99.174) +2022-11-14 16:14:34,004 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0782) Prec@1 85.000 (87.677) Prec@5 99.000 (99.172) +2022-11-14 16:14:34,021 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0781) Prec@1 88.000 (87.681) Prec@5 99.000 (99.170) +2022-11-14 16:14:34,035 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0784) Prec@1 85.000 (87.653) Prec@5 99.000 (99.168) +2022-11-14 16:14:34,046 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0782) Prec@1 92.000 (87.698) Prec@5 99.000 (99.167) +2022-11-14 16:14:34,061 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0780) Prec@1 91.000 (87.732) Prec@5 98.000 (99.155) +2022-11-14 16:14:34,076 Test: [97/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0782) Prec@1 85.000 (87.704) Prec@5 98.000 (99.143) +2022-11-14 16:14:34,089 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0784) Prec@1 85.000 (87.677) Prec@5 100.000 (99.152) +2022-11-14 16:14:34,100 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0783) Prec@1 89.000 (87.690) Prec@5 100.000 (99.160) +2022-11-14 16:14:34,162 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:14:34,511 Epoch: [320][0/500] Time 0.026 (0.026) Data 0.257 (0.257) Loss 0.0251 (0.0251) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:14:34,772 Epoch: [320][10/500] Time 0.027 (0.024) Data 0.002 (0.025) Loss 0.0394 (0.0323) Prec@1 92.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:14:35,169 Epoch: [320][20/500] Time 0.041 (0.028) Data 0.002 (0.014) Loss 0.0427 (0.0357) Prec@1 91.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 16:14:35,673 Epoch: [320][30/500] Time 0.044 (0.034) Data 0.002 (0.010) Loss 0.0696 (0.0442) Prec@1 89.000 (91.750) Prec@5 99.000 (99.750) +2022-11-14 16:14:36,173 Epoch: [320][40/500] Time 0.053 (0.037) Data 0.002 (0.008) Loss 0.0583 (0.0470) Prec@1 88.000 (91.000) Prec@5 100.000 (99.800) +2022-11-14 16:14:36,673 Epoch: [320][50/500] Time 0.051 (0.038) Data 0.002 (0.007) Loss 0.0222 (0.0429) Prec@1 95.000 (91.667) Prec@5 100.000 (99.833) +2022-11-14 16:14:37,154 Epoch: [320][60/500] Time 0.045 (0.039) Data 0.002 (0.006) Loss 0.0322 (0.0414) Prec@1 94.000 (92.000) Prec@5 100.000 (99.857) +2022-11-14 16:14:37,649 Epoch: [320][70/500] Time 0.045 (0.040) Data 0.002 (0.005) Loss 0.0301 (0.0399) Prec@1 94.000 (92.250) Prec@5 100.000 (99.875) +2022-11-14 16:14:38,134 Epoch: [320][80/500] Time 0.042 (0.040) Data 0.002 (0.005) Loss 0.0477 (0.0408) Prec@1 90.000 (92.000) Prec@5 99.000 (99.778) +2022-11-14 16:14:38,621 Epoch: [320][90/500] Time 0.054 (0.041) Data 0.003 (0.005) Loss 0.0390 (0.0406) Prec@1 94.000 (92.200) Prec@5 100.000 (99.800) +2022-11-14 16:14:39,125 Epoch: [320][100/500] Time 0.044 (0.041) Data 0.002 (0.004) Loss 0.0352 (0.0401) Prec@1 94.000 (92.364) Prec@5 100.000 (99.818) +2022-11-14 16:14:39,633 Epoch: [320][110/500] Time 0.044 (0.042) Data 0.002 (0.004) Loss 0.0221 (0.0386) Prec@1 97.000 (92.750) Prec@5 100.000 (99.833) +2022-11-14 16:14:40,123 Epoch: [320][120/500] Time 0.036 (0.042) Data 0.002 (0.004) Loss 0.0444 (0.0391) Prec@1 91.000 (92.615) Prec@5 100.000 (99.846) +2022-11-14 16:14:40,631 Epoch: [320][130/500] Time 0.045 (0.042) Data 0.002 (0.004) Loss 0.0363 (0.0389) Prec@1 95.000 (92.786) Prec@5 100.000 (99.857) +2022-11-14 16:14:41,124 Epoch: [320][140/500] Time 0.043 (0.042) Data 0.002 (0.004) Loss 0.0361 (0.0387) Prec@1 94.000 (92.867) Prec@5 100.000 (99.867) +2022-11-14 16:14:41,611 Epoch: [320][150/500] Time 0.047 (0.042) Data 0.002 (0.004) Loss 0.0262 (0.0379) Prec@1 96.000 (93.062) Prec@5 100.000 (99.875) +2022-11-14 16:14:42,108 Epoch: [320][160/500] Time 0.038 (0.042) Data 0.002 (0.004) Loss 0.0319 (0.0376) Prec@1 93.000 (93.059) Prec@5 100.000 (99.882) +2022-11-14 16:14:42,613 Epoch: [320][170/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0347 (0.0374) Prec@1 94.000 (93.111) Prec@5 100.000 (99.889) +2022-11-14 16:14:43,104 Epoch: [320][180/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0340 (0.0372) Prec@1 93.000 (93.105) Prec@5 100.000 (99.895) +2022-11-14 16:14:43,608 Epoch: [320][190/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0191 (0.0363) Prec@1 98.000 (93.350) Prec@5 100.000 (99.900) +2022-11-14 16:14:44,110 Epoch: [320][200/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0083 (0.0350) Prec@1 99.000 (93.619) Prec@5 100.000 (99.905) +2022-11-14 16:14:44,598 Epoch: [320][210/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0349 (0.0350) Prec@1 93.000 (93.591) Prec@5 100.000 (99.909) +2022-11-14 16:14:45,080 Epoch: [320][220/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0294 (0.0347) Prec@1 93.000 (93.565) Prec@5 100.000 (99.913) +2022-11-14 16:14:45,599 Epoch: [320][230/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0268 (0.0344) Prec@1 95.000 (93.625) Prec@5 100.000 (99.917) +2022-11-14 16:14:46,090 Epoch: [320][240/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0233 (0.0340) Prec@1 95.000 (93.680) Prec@5 100.000 (99.920) +2022-11-14 16:14:46,603 Epoch: [320][250/500] Time 0.049 (0.043) Data 0.002 (0.003) Loss 0.0203 (0.0334) Prec@1 95.000 (93.731) Prec@5 100.000 (99.923) +2022-11-14 16:14:47,110 Epoch: [320][260/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0418 (0.0337) Prec@1 92.000 (93.667) Prec@5 100.000 (99.926) +2022-11-14 16:14:47,626 Epoch: [320][270/500] Time 0.052 (0.043) Data 0.002 (0.003) Loss 0.0526 (0.0344) Prec@1 91.000 (93.571) Prec@5 99.000 (99.893) +2022-11-14 16:14:48,133 Epoch: [320][280/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0633 (0.0354) Prec@1 89.000 (93.414) Prec@5 99.000 (99.862) +2022-11-14 16:14:48,622 Epoch: [320][290/500] Time 0.057 (0.043) Data 0.002 (0.003) Loss 0.0500 (0.0359) Prec@1 91.000 (93.333) Prec@5 100.000 (99.867) +2022-11-14 16:14:49,128 Epoch: [320][300/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0424 (0.0361) Prec@1 93.000 (93.323) Prec@5 100.000 (99.871) +2022-11-14 16:14:49,636 Epoch: [320][310/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0391 (0.0362) Prec@1 94.000 (93.344) Prec@5 100.000 (99.875) +2022-11-14 16:14:50,122 Epoch: [320][320/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0404 (0.0363) Prec@1 92.000 (93.303) Prec@5 100.000 (99.879) +2022-11-14 16:14:50,623 Epoch: [320][330/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0350 (0.0363) Prec@1 94.000 (93.324) Prec@5 100.000 (99.882) +2022-11-14 16:14:51,109 Epoch: [320][340/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0360 (0.0363) Prec@1 94.000 (93.343) Prec@5 100.000 (99.886) +2022-11-14 16:14:51,620 Epoch: [320][350/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0211 (0.0359) Prec@1 95.000 (93.389) Prec@5 100.000 (99.889) +2022-11-14 16:14:52,122 Epoch: [320][360/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0365 (0.0359) Prec@1 95.000 (93.432) Prec@5 99.000 (99.865) +2022-11-14 16:14:52,621 Epoch: [320][370/500] Time 0.057 (0.044) Data 0.002 (0.003) Loss 0.0341 (0.0358) Prec@1 94.000 (93.447) Prec@5 100.000 (99.868) +2022-11-14 16:14:53,121 Epoch: [320][380/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0350 (0.0358) Prec@1 95.000 (93.487) Prec@5 99.000 (99.846) +2022-11-14 16:14:53,616 Epoch: [320][390/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0240 (0.0355) Prec@1 97.000 (93.575) Prec@5 100.000 (99.850) +2022-11-14 16:14:54,124 Epoch: [320][400/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0393 (0.0356) Prec@1 93.000 (93.561) Prec@5 100.000 (99.854) +2022-11-14 16:14:54,634 Epoch: [320][410/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0376 (0.0357) Prec@1 95.000 (93.595) Prec@5 100.000 (99.857) +2022-11-14 16:14:55,142 Epoch: [320][420/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0290 (0.0355) Prec@1 96.000 (93.651) Prec@5 100.000 (99.860) +2022-11-14 16:14:55,648 Epoch: [320][430/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0333 (0.0354) Prec@1 96.000 (93.705) Prec@5 100.000 (99.864) +2022-11-14 16:14:56,168 Epoch: [320][440/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0280 (0.0353) Prec@1 95.000 (93.733) Prec@5 100.000 (99.867) +2022-11-14 16:14:56,678 Epoch: [320][450/500] Time 0.056 (0.044) Data 0.002 (0.003) Loss 0.0203 (0.0350) Prec@1 97.000 (93.804) Prec@5 100.000 (99.870) +2022-11-14 16:14:57,185 Epoch: [320][460/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0314 (0.0349) Prec@1 95.000 (93.830) Prec@5 100.000 (99.872) +2022-11-14 16:14:57,683 Epoch: [320][470/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0360 (0.0349) Prec@1 94.000 (93.833) Prec@5 100.000 (99.875) +2022-11-14 16:14:58,189 Epoch: [320][480/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0244 (0.0347) Prec@1 97.000 (93.898) Prec@5 99.000 (99.857) +2022-11-14 16:14:58,704 Epoch: [320][490/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0452 (0.0349) Prec@1 92.000 (93.860) Prec@5 100.000 (99.860) +2022-11-14 16:14:59,147 Epoch: [320][499/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0449 (0.0351) Prec@1 91.000 (93.804) Prec@5 100.000 (99.863) +2022-11-14 16:14:59,483 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0635 (0.0635) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:14:59,495 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0792 (0.0713) Prec@1 86.000 (86.000) Prec@5 99.000 (99.500) +2022-11-14 16:14:59,506 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0816 (0.0748) Prec@1 87.000 (86.333) Prec@5 99.000 (99.333) +2022-11-14 16:14:59,519 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0945 (0.0797) Prec@1 85.000 (86.000) Prec@5 99.000 (99.250) +2022-11-14 16:14:59,527 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0799) Prec@1 86.000 (86.000) Prec@5 100.000 (99.400) +2022-11-14 16:14:59,537 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0363 (0.0727) Prec@1 94.000 (87.333) Prec@5 100.000 (99.500) +2022-11-14 16:14:59,549 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0715) Prec@1 90.000 (87.714) Prec@5 99.000 (99.429) +2022-11-14 16:14:59,565 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0737) Prec@1 85.000 (87.375) Prec@5 99.000 (99.375) +2022-11-14 16:14:59,578 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0757) Prec@1 85.000 (87.111) Prec@5 100.000 (99.444) +2022-11-14 16:14:59,593 Test: [9/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0763) Prec@1 89.000 (87.300) Prec@5 99.000 (99.400) +2022-11-14 16:14:59,610 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0748) Prec@1 91.000 (87.636) Prec@5 99.000 (99.364) +2022-11-14 16:14:59,625 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0758) Prec@1 84.000 (87.333) Prec@5 99.000 (99.333) +2022-11-14 16:14:59,639 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0763) Prec@1 87.000 (87.308) Prec@5 100.000 (99.385) +2022-11-14 16:14:59,653 Test: [13/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0744) Prec@1 94.000 (87.786) Prec@5 100.000 (99.429) +2022-11-14 16:14:59,670 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0753) Prec@1 85.000 (87.600) Prec@5 100.000 (99.467) +2022-11-14 16:14:59,688 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0752) Prec@1 88.000 (87.625) Prec@5 100.000 (99.500) +2022-11-14 16:14:59,701 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0512 (0.0738) Prec@1 92.000 (87.882) Prec@5 99.000 (99.471) +2022-11-14 16:14:59,718 Test: [17/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1108 (0.0759) Prec@1 83.000 (87.611) Prec@5 100.000 (99.500) +2022-11-14 16:14:59,734 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0761) Prec@1 85.000 (87.474) Prec@5 97.000 (99.368) +2022-11-14 16:14:59,752 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0767) Prec@1 84.000 (87.300) Prec@5 96.000 (99.200) +2022-11-14 16:14:59,769 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0770) Prec@1 85.000 (87.190) Prec@5 100.000 (99.238) +2022-11-14 16:14:59,785 Test: [21/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0776) Prec@1 86.000 (87.136) Prec@5 97.000 (99.136) +2022-11-14 16:14:59,802 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0778) Prec@1 88.000 (87.174) Prec@5 97.000 (99.043) +2022-11-14 16:14:59,820 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0781) Prec@1 87.000 (87.167) Prec@5 100.000 (99.083) +2022-11-14 16:14:59,835 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0784) Prec@1 85.000 (87.080) Prec@5 100.000 (99.120) +2022-11-14 16:14:59,854 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0790) Prec@1 87.000 (87.077) Prec@5 100.000 (99.154) +2022-11-14 16:14:59,869 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0778) Prec@1 92.000 (87.259) Prec@5 100.000 (99.185) +2022-11-14 16:14:59,886 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0774) Prec@1 88.000 (87.286) Prec@5 98.000 (99.143) +2022-11-14 16:14:59,902 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0777) Prec@1 87.000 (87.276) Prec@5 97.000 (99.069) +2022-11-14 16:14:59,920 Test: [29/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0775) Prec@1 87.000 (87.267) Prec@5 99.000 (99.067) +2022-11-14 16:14:59,936 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0774) Prec@1 88.000 (87.290) Prec@5 100.000 (99.097) +2022-11-14 16:14:59,951 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0771) Prec@1 88.000 (87.312) Prec@5 99.000 (99.094) +2022-11-14 16:14:59,966 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0771) Prec@1 84.000 (87.212) Prec@5 99.000 (99.091) +2022-11-14 16:14:59,983 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0777) Prec@1 83.000 (87.088) Prec@5 99.000 (99.088) +2022-11-14 16:14:59,999 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0779) Prec@1 87.000 (87.086) Prec@5 97.000 (99.029) +2022-11-14 16:15:00,015 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0772) Prec@1 92.000 (87.222) Prec@5 100.000 (99.056) +2022-11-14 16:15:00,033 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0770) Prec@1 89.000 (87.270) Prec@5 98.000 (99.027) +2022-11-14 16:15:00,048 Test: [37/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0778) Prec@1 82.000 (87.132) Prec@5 98.000 (99.000) +2022-11-14 16:15:00,066 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0471 (0.0770) Prec@1 93.000 (87.282) Prec@5 99.000 (99.000) +2022-11-14 16:15:00,084 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0771) Prec@1 87.000 (87.275) Prec@5 100.000 (99.025) +2022-11-14 16:15:00,101 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0775) Prec@1 86.000 (87.244) Prec@5 99.000 (99.024) +2022-11-14 16:15:00,118 Test: [41/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0774) Prec@1 88.000 (87.262) Prec@5 98.000 (99.000) +2022-11-14 16:15:00,134 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0770) Prec@1 90.000 (87.326) Prec@5 100.000 (99.023) +2022-11-14 16:15:00,152 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0767) Prec@1 91.000 (87.409) Prec@5 99.000 (99.023) +2022-11-14 16:15:00,165 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0765) Prec@1 89.000 (87.444) Prec@5 99.000 (99.022) +2022-11-14 16:15:00,180 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0770) Prec@1 83.000 (87.348) Prec@5 99.000 (99.022) +2022-11-14 16:15:00,194 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0769) Prec@1 86.000 (87.319) Prec@5 100.000 (99.043) +2022-11-14 16:15:00,212 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0774) Prec@1 85.000 (87.271) Prec@5 99.000 (99.042) +2022-11-14 16:15:00,232 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0769) Prec@1 92.000 (87.367) Prec@5 100.000 (99.061) +2022-11-14 16:15:00,251 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1165 (0.0777) Prec@1 83.000 (87.280) Prec@5 100.000 (99.080) +2022-11-14 16:15:00,267 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0772) Prec@1 89.000 (87.314) Prec@5 100.000 (99.098) +2022-11-14 16:15:00,284 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0776) Prec@1 86.000 (87.288) Prec@5 99.000 (99.096) +2022-11-14 16:15:00,299 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0774) Prec@1 89.000 (87.321) Prec@5 100.000 (99.113) +2022-11-14 16:15:00,315 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0773) Prec@1 89.000 (87.352) Prec@5 99.000 (99.111) +2022-11-14 16:15:00,333 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0781) Prec@1 81.000 (87.236) Prec@5 98.000 (99.091) +2022-11-14 16:15:00,347 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0782) Prec@1 88.000 (87.250) Prec@5 99.000 (99.089) +2022-11-14 16:15:00,362 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0782) Prec@1 87.000 (87.246) Prec@5 99.000 (99.088) +2022-11-14 16:15:00,377 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0780) Prec@1 92.000 (87.328) Prec@5 99.000 (99.086) +2022-11-14 16:15:00,397 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0783) Prec@1 84.000 (87.271) Prec@5 99.000 (99.085) +2022-11-14 16:15:00,414 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0784) Prec@1 84.000 (87.217) Prec@5 99.000 (99.083) +2022-11-14 16:15:00,434 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0785) Prec@1 84.000 (87.164) Prec@5 100.000 (99.098) +2022-11-14 16:15:00,451 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0781) Prec@1 93.000 (87.258) Prec@5 99.000 (99.097) +2022-11-14 16:15:00,466 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0779) Prec@1 90.000 (87.302) Prec@5 100.000 (99.111) +2022-11-14 16:15:00,483 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0372 (0.0773) Prec@1 94.000 (87.406) Prec@5 100.000 (99.125) +2022-11-14 16:15:00,505 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1059 (0.0777) Prec@1 85.000 (87.369) Prec@5 98.000 (99.108) +2022-11-14 16:15:00,520 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0779) Prec@1 84.000 (87.318) Prec@5 98.000 (99.091) +2022-11-14 16:15:00,534 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0412 (0.0774) Prec@1 93.000 (87.403) Prec@5 100.000 (99.104) +2022-11-14 16:15:00,553 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0774) Prec@1 87.000 (87.397) Prec@5 99.000 (99.103) +2022-11-14 16:15:00,573 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0774) Prec@1 88.000 (87.406) Prec@5 99.000 (99.101) +2022-11-14 16:15:00,590 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0773) Prec@1 90.000 (87.443) Prec@5 98.000 (99.086) +2022-11-14 16:15:00,604 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0774) Prec@1 86.000 (87.423) Prec@5 98.000 (99.070) +2022-11-14 16:15:00,621 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0773) Prec@1 87.000 (87.417) Prec@5 100.000 (99.083) +2022-11-14 16:15:00,639 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0769) Prec@1 92.000 (87.479) Prec@5 100.000 (99.096) +2022-11-14 16:15:00,652 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0766) Prec@1 93.000 (87.554) Prec@5 100.000 (99.108) +2022-11-14 16:15:00,669 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1310 (0.0773) Prec@1 79.000 (87.440) Prec@5 100.000 (99.120) +2022-11-14 16:15:00,691 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0770) Prec@1 91.000 (87.487) Prec@5 100.000 (99.132) +2022-11-14 16:15:00,707 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0768) Prec@1 90.000 (87.519) Prec@5 99.000 (99.130) +2022-11-14 16:15:00,723 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0769) Prec@1 86.000 (87.500) Prec@5 99.000 (99.128) +2022-11-14 16:15:00,739 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0770) Prec@1 87.000 (87.494) Prec@5 100.000 (99.139) +2022-11-14 16:15:00,757 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0769) Prec@1 87.000 (87.487) Prec@5 100.000 (99.150) +2022-11-14 16:15:00,775 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0771) Prec@1 86.000 (87.469) Prec@5 99.000 (99.148) +2022-11-14 16:15:00,791 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0770) Prec@1 87.000 (87.463) Prec@5 100.000 (99.159) +2022-11-14 16:15:00,809 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0772) Prec@1 86.000 (87.446) Prec@5 99.000 (99.157) +2022-11-14 16:15:00,825 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0772) Prec@1 89.000 (87.464) Prec@5 99.000 (99.155) +2022-11-14 16:15:00,839 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0773) Prec@1 87.000 (87.459) Prec@5 98.000 (99.141) +2022-11-14 16:15:00,855 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0774) Prec@1 86.000 (87.442) Prec@5 100.000 (99.151) +2022-11-14 16:15:00,872 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0773) Prec@1 89.000 (87.460) Prec@5 100.000 (99.161) +2022-11-14 16:15:00,891 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0774) Prec@1 88.000 (87.466) Prec@5 98.000 (99.148) +2022-11-14 16:15:00,907 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0774) Prec@1 88.000 (87.472) Prec@5 100.000 (99.157) +2022-11-14 16:15:00,925 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0773) Prec@1 87.000 (87.467) Prec@5 100.000 (99.167) +2022-11-14 16:15:00,941 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0771) Prec@1 90.000 (87.495) Prec@5 100.000 (99.176) +2022-11-14 16:15:00,961 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0771) Prec@1 86.000 (87.478) Prec@5 98.000 (99.163) +2022-11-14 16:15:00,978 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0773) Prec@1 84.000 (87.441) Prec@5 100.000 (99.172) +2022-11-14 16:15:00,994 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0773) Prec@1 88.000 (87.447) Prec@5 99.000 (99.170) +2022-11-14 16:15:01,012 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0773) Prec@1 88.000 (87.453) Prec@5 100.000 (99.179) +2022-11-14 16:15:01,032 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0773) Prec@1 88.000 (87.458) Prec@5 99.000 (99.177) +2022-11-14 16:15:01,050 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0771) Prec@1 91.000 (87.495) Prec@5 99.000 (99.175) +2022-11-14 16:15:01,066 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0771) Prec@1 90.000 (87.520) Prec@5 100.000 (99.184) +2022-11-14 16:15:01,084 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0774) Prec@1 85.000 (87.495) Prec@5 99.000 (99.182) +2022-11-14 16:15:01,101 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0773) Prec@1 88.000 (87.500) Prec@5 98.000 (99.170) +2022-11-14 16:15:01,167 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:15:01,523 Epoch: [321][0/500] Time 0.023 (0.023) Data 0.267 (0.267) Loss 0.0342 (0.0342) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:15:01,979 Epoch: [321][10/500] Time 0.052 (0.038) Data 0.002 (0.026) Loss 0.0326 (0.0334) Prec@1 92.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 16:15:02,474 Epoch: [321][20/500] Time 0.041 (0.041) Data 0.002 (0.015) Loss 0.0410 (0.0360) Prec@1 93.000 (92.667) Prec@5 99.000 (99.667) +2022-11-14 16:15:02,967 Epoch: [321][30/500] Time 0.046 (0.042) Data 0.002 (0.011) Loss 0.0365 (0.0361) Prec@1 95.000 (93.250) Prec@5 100.000 (99.750) +2022-11-14 16:15:03,462 Epoch: [321][40/500] Time 0.043 (0.042) Data 0.002 (0.009) Loss 0.0316 (0.0352) Prec@1 95.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 16:15:03,968 Epoch: [321][50/500] Time 0.048 (0.043) Data 0.002 (0.007) Loss 0.0286 (0.0341) Prec@1 92.000 (93.333) Prec@5 100.000 (99.833) +2022-11-14 16:15:04,464 Epoch: [321][60/500] Time 0.054 (0.043) Data 0.002 (0.006) Loss 0.0511 (0.0365) Prec@1 93.000 (93.286) Prec@5 100.000 (99.857) +2022-11-14 16:15:04,976 Epoch: [321][70/500] Time 0.049 (0.043) Data 0.002 (0.006) Loss 0.0368 (0.0366) Prec@1 95.000 (93.500) Prec@5 100.000 (99.875) +2022-11-14 16:15:05,483 Epoch: [321][80/500] Time 0.046 (0.044) Data 0.002 (0.005) Loss 0.0223 (0.0350) Prec@1 95.000 (93.667) Prec@5 100.000 (99.889) +2022-11-14 16:15:06,009 Epoch: [321][90/500] Time 0.052 (0.044) Data 0.002 (0.005) Loss 0.0186 (0.0333) Prec@1 96.000 (93.900) Prec@5 100.000 (99.900) +2022-11-14 16:15:06,514 Epoch: [321][100/500] Time 0.044 (0.044) Data 0.002 (0.005) Loss 0.0266 (0.0327) Prec@1 97.000 (94.182) Prec@5 100.000 (99.909) +2022-11-14 16:15:07,017 Epoch: [321][110/500] Time 0.049 (0.044) Data 0.002 (0.004) Loss 0.0228 (0.0319) Prec@1 96.000 (94.333) Prec@5 100.000 (99.917) +2022-11-14 16:15:07,511 Epoch: [321][120/500] Time 0.042 (0.044) Data 0.002 (0.004) Loss 0.0353 (0.0322) Prec@1 95.000 (94.385) Prec@5 100.000 (99.923) +2022-11-14 16:15:08,031 Epoch: [321][130/500] Time 0.048 (0.044) Data 0.002 (0.004) Loss 0.0359 (0.0324) Prec@1 94.000 (94.357) Prec@5 100.000 (99.929) +2022-11-14 16:15:08,539 Epoch: [321][140/500] Time 0.050 (0.045) Data 0.002 (0.004) Loss 0.0365 (0.0327) Prec@1 95.000 (94.400) Prec@5 99.000 (99.867) +2022-11-14 16:15:09,051 Epoch: [321][150/500] Time 0.043 (0.045) Data 0.002 (0.004) Loss 0.0234 (0.0321) Prec@1 96.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:15:09,560 Epoch: [321][160/500] Time 0.053 (0.045) Data 0.002 (0.004) Loss 0.0322 (0.0321) Prec@1 95.000 (94.529) Prec@5 100.000 (99.882) +2022-11-14 16:15:10,064 Epoch: [321][170/500] Time 0.046 (0.045) Data 0.002 (0.004) Loss 0.0342 (0.0322) Prec@1 95.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 16:15:10,564 Epoch: [321][180/500] Time 0.048 (0.045) Data 0.003 (0.004) Loss 0.0227 (0.0317) Prec@1 96.000 (94.632) Prec@5 100.000 (99.895) +2022-11-14 16:15:11,052 Epoch: [321][190/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0347 (0.0319) Prec@1 93.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 16:15:11,572 Epoch: [321][200/500] Time 0.063 (0.045) Data 0.002 (0.003) Loss 0.0318 (0.0319) Prec@1 96.000 (94.619) Prec@5 100.000 (99.905) +2022-11-14 16:15:12,081 Epoch: [321][210/500] Time 0.060 (0.045) Data 0.002 (0.003) Loss 0.0248 (0.0316) Prec@1 95.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 16:15:12,578 Epoch: [321][220/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0159 (0.0309) Prec@1 99.000 (94.826) Prec@5 100.000 (99.913) +2022-11-14 16:15:13,112 Epoch: [321][230/500] Time 0.064 (0.045) Data 0.002 (0.003) Loss 0.0429 (0.0314) Prec@1 94.000 (94.792) Prec@5 100.000 (99.917) +2022-11-14 16:15:13,632 Epoch: [321][240/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0290 (0.0313) Prec@1 96.000 (94.840) Prec@5 100.000 (99.920) +2022-11-14 16:15:14,187 Epoch: [321][250/500] Time 0.063 (0.045) Data 0.002 (0.003) Loss 0.0335 (0.0314) Prec@1 94.000 (94.808) Prec@5 100.000 (99.923) +2022-11-14 16:15:14,670 Epoch: [321][260/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0107 (0.0306) Prec@1 99.000 (94.963) Prec@5 100.000 (99.926) +2022-11-14 16:15:15,259 Epoch: [321][270/500] Time 0.067 (0.045) Data 0.002 (0.003) Loss 0.0563 (0.0315) Prec@1 91.000 (94.821) Prec@5 100.000 (99.929) +2022-11-14 16:15:15,747 Epoch: [321][280/500] Time 0.042 (0.045) Data 0.003 (0.003) Loss 0.0355 (0.0317) Prec@1 94.000 (94.793) Prec@5 100.000 (99.931) +2022-11-14 16:15:16,351 Epoch: [321][290/500] Time 0.063 (0.045) Data 0.002 (0.003) Loss 0.0586 (0.0326) Prec@1 89.000 (94.600) Prec@5 100.000 (99.933) +2022-11-14 16:15:16,832 Epoch: [321][300/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0444 (0.0329) Prec@1 94.000 (94.581) Prec@5 100.000 (99.935) +2022-11-14 16:15:17,341 Epoch: [321][310/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0469 (0.0334) Prec@1 94.000 (94.562) Prec@5 99.000 (99.906) +2022-11-14 16:15:17,852 Epoch: [321][320/500] Time 0.042 (0.045) Data 0.002 (0.003) Loss 0.0339 (0.0334) Prec@1 95.000 (94.576) Prec@5 100.000 (99.909) +2022-11-14 16:15:18,390 Epoch: [321][330/500] Time 0.064 (0.045) Data 0.002 (0.003) Loss 0.0347 (0.0334) Prec@1 94.000 (94.559) Prec@5 100.000 (99.912) +2022-11-14 16:15:19,142 Epoch: [321][340/500] Time 0.070 (0.046) Data 0.002 (0.003) Loss 0.0250 (0.0332) Prec@1 96.000 (94.600) Prec@5 100.000 (99.914) +2022-11-14 16:15:19,919 Epoch: [321][350/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0089 (0.0325) Prec@1 99.000 (94.722) Prec@5 100.000 (99.917) +2022-11-14 16:15:20,740 Epoch: [321][360/500] Time 0.081 (0.047) Data 0.002 (0.003) Loss 0.0315 (0.0325) Prec@1 94.000 (94.703) Prec@5 100.000 (99.919) +2022-11-14 16:15:21,535 Epoch: [321][370/500] Time 0.081 (0.048) Data 0.003 (0.003) Loss 0.0208 (0.0322) Prec@1 96.000 (94.737) Prec@5 100.000 (99.921) +2022-11-14 16:15:22,352 Epoch: [321][380/500] Time 0.076 (0.049) Data 0.002 (0.003) Loss 0.0254 (0.0320) Prec@1 96.000 (94.769) Prec@5 100.000 (99.923) +2022-11-14 16:15:23,072 Epoch: [321][390/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0435 (0.0323) Prec@1 94.000 (94.750) Prec@5 98.000 (99.875) +2022-11-14 16:15:23,837 Epoch: [321][400/500] Time 0.081 (0.050) Data 0.002 (0.003) Loss 0.0183 (0.0320) Prec@1 98.000 (94.829) Prec@5 100.000 (99.878) +2022-11-14 16:15:24,623 Epoch: [321][410/500] Time 0.085 (0.050) Data 0.002 (0.003) Loss 0.0224 (0.0317) Prec@1 96.000 (94.857) Prec@5 100.000 (99.881) +2022-11-14 16:15:25,439 Epoch: [321][420/500] Time 0.083 (0.051) Data 0.002 (0.003) Loss 0.0181 (0.0314) Prec@1 98.000 (94.930) Prec@5 100.000 (99.884) +2022-11-14 16:15:26,194 Epoch: [321][430/500] Time 0.071 (0.051) Data 0.002 (0.003) Loss 0.0432 (0.0317) Prec@1 92.000 (94.864) Prec@5 99.000 (99.864) +2022-11-14 16:15:27,130 Epoch: [321][440/500] Time 0.071 (0.052) Data 0.002 (0.003) Loss 0.0571 (0.0322) Prec@1 90.000 (94.756) Prec@5 100.000 (99.867) +2022-11-14 16:15:28,133 Epoch: [321][450/500] Time 0.088 (0.053) Data 0.003 (0.003) Loss 0.0132 (0.0318) Prec@1 99.000 (94.848) Prec@5 100.000 (99.870) +2022-11-14 16:15:29,020 Epoch: [321][460/500] Time 0.080 (0.053) Data 0.002 (0.003) Loss 0.0538 (0.0323) Prec@1 92.000 (94.787) Prec@5 100.000 (99.872) +2022-11-14 16:15:29,897 Epoch: [321][470/500] Time 0.068 (0.054) Data 0.002 (0.003) Loss 0.0251 (0.0321) Prec@1 96.000 (94.812) Prec@5 99.000 (99.854) +2022-11-14 16:15:30,803 Epoch: [321][480/500] Time 0.129 (0.054) Data 0.002 (0.003) Loss 0.0532 (0.0326) Prec@1 91.000 (94.735) Prec@5 100.000 (99.857) +2022-11-14 16:15:31,556 Epoch: [321][490/500] Time 0.079 (0.055) Data 0.002 (0.003) Loss 0.0215 (0.0323) Prec@1 96.000 (94.760) Prec@5 100.000 (99.860) +2022-11-14 16:15:32,394 Epoch: [321][499/500] Time 0.086 (0.055) Data 0.002 (0.003) Loss 0.0299 (0.0323) Prec@1 95.000 (94.765) Prec@5 99.000 (99.843) +2022-11-14 16:15:32,748 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0806 (0.0806) Prec@1 88.000 (88.000) Prec@5 98.000 (98.000) +2022-11-14 16:15:32,762 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0835) Prec@1 87.000 (87.500) Prec@5 100.000 (99.000) +2022-11-14 16:15:32,773 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0778) Prec@1 90.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:15:32,785 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0817) Prec@1 83.000 (87.000) Prec@5 99.000 (99.250) +2022-11-14 16:15:32,795 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0792) Prec@1 91.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 16:15:32,805 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0762) Prec@1 91.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 16:15:32,816 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0721) Prec@1 94.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 16:15:32,827 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0714) Prec@1 89.000 (89.125) Prec@5 99.000 (99.500) +2022-11-14 16:15:32,837 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0711) Prec@1 90.000 (89.222) Prec@5 100.000 (99.556) +2022-11-14 16:15:32,846 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0713) Prec@1 91.000 (89.400) Prec@5 98.000 (99.400) +2022-11-14 16:15:32,856 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0700) Prec@1 92.000 (89.636) Prec@5 100.000 (99.455) +2022-11-14 16:15:32,865 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0716) Prec@1 85.000 (89.250) Prec@5 99.000 (99.417) +2022-11-14 16:15:32,874 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0711) Prec@1 88.000 (89.154) Prec@5 100.000 (99.462) +2022-11-14 16:15:32,883 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0700) Prec@1 92.000 (89.357) Prec@5 99.000 (99.429) +2022-11-14 16:15:32,893 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0717) Prec@1 85.000 (89.067) Prec@5 100.000 (99.467) +2022-11-14 16:15:32,902 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0715) Prec@1 87.000 (88.938) Prec@5 100.000 (99.500) +2022-11-14 16:15:32,912 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0553 (0.0705) Prec@1 91.000 (89.059) Prec@5 99.000 (99.471) +2022-11-14 16:15:32,923 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0720) Prec@1 87.000 (88.944) Prec@5 100.000 (99.500) +2022-11-14 16:15:32,933 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0737) Prec@1 81.000 (88.526) Prec@5 97.000 (99.368) +2022-11-14 16:15:32,944 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0748) Prec@1 85.000 (88.350) Prec@5 97.000 (99.250) +2022-11-14 16:15:32,955 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0754) Prec@1 88.000 (88.333) Prec@5 99.000 (99.238) +2022-11-14 16:15:32,965 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0956 (0.0763) Prec@1 81.000 (88.000) Prec@5 97.000 (99.136) +2022-11-14 16:15:32,975 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0773) Prec@1 82.000 (87.739) Prec@5 99.000 (99.130) +2022-11-14 16:15:32,984 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0774) Prec@1 88.000 (87.750) Prec@5 99.000 (99.125) +2022-11-14 16:15:32,993 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0782) Prec@1 84.000 (87.600) Prec@5 100.000 (99.160) +2022-11-14 16:15:33,004 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0791) Prec@1 84.000 (87.462) Prec@5 98.000 (99.115) +2022-11-14 16:15:33,014 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0783) Prec@1 90.000 (87.556) Prec@5 100.000 (99.148) +2022-11-14 16:15:33,025 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0782) Prec@1 87.000 (87.536) Prec@5 100.000 (99.179) +2022-11-14 16:15:33,035 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0780) Prec@1 88.000 (87.552) Prec@5 98.000 (99.138) +2022-11-14 16:15:33,045 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0783) Prec@1 86.000 (87.500) Prec@5 100.000 (99.167) +2022-11-14 16:15:33,056 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0778) Prec@1 89.000 (87.548) Prec@5 98.000 (99.129) +2022-11-14 16:15:33,066 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0782) Prec@1 85.000 (87.469) Prec@5 99.000 (99.125) +2022-11-14 16:15:33,079 Test: [32/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0783) Prec@1 86.000 (87.424) Prec@5 100.000 (99.152) +2022-11-14 16:15:33,089 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0788) Prec@1 86.000 (87.382) Prec@5 100.000 (99.176) +2022-11-14 16:15:33,099 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0786) Prec@1 90.000 (87.457) Prec@5 98.000 (99.143) +2022-11-14 16:15:33,110 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0781) Prec@1 90.000 (87.528) Prec@5 100.000 (99.167) +2022-11-14 16:15:33,123 Test: [36/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0780) Prec@1 90.000 (87.595) Prec@5 95.000 (99.054) +2022-11-14 16:15:33,134 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0785) Prec@1 82.000 (87.447) Prec@5 99.000 (99.053) +2022-11-14 16:15:33,143 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0779) Prec@1 92.000 (87.564) Prec@5 99.000 (99.051) +2022-11-14 16:15:33,153 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0776) Prec@1 89.000 (87.600) Prec@5 98.000 (99.025) +2022-11-14 16:15:33,165 Test: [40/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0780) Prec@1 86.000 (87.561) Prec@5 97.000 (98.976) +2022-11-14 16:15:33,177 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0775) Prec@1 91.000 (87.643) Prec@5 99.000 (98.976) +2022-11-14 16:15:33,187 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0767) Prec@1 93.000 (87.767) Prec@5 99.000 (98.977) +2022-11-14 16:15:33,197 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0763) Prec@1 90.000 (87.818) Prec@5 99.000 (98.977) +2022-11-14 16:15:33,209 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0758) Prec@1 93.000 (87.933) Prec@5 99.000 (98.978) +2022-11-14 16:15:33,219 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0764) Prec@1 83.000 (87.826) Prec@5 100.000 (99.000) +2022-11-14 16:15:33,230 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0761) Prec@1 89.000 (87.851) Prec@5 100.000 (99.021) +2022-11-14 16:15:33,239 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1074 (0.0767) Prec@1 83.000 (87.750) Prec@5 99.000 (99.021) +2022-11-14 16:15:33,252 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0761) Prec@1 92.000 (87.837) Prec@5 100.000 (99.041) +2022-11-14 16:15:33,264 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0765) Prec@1 82.000 (87.720) Prec@5 99.000 (99.040) +2022-11-14 16:15:33,275 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0759) Prec@1 91.000 (87.784) Prec@5 100.000 (99.059) +2022-11-14 16:15:33,286 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0761) Prec@1 88.000 (87.788) Prec@5 100.000 (99.077) +2022-11-14 16:15:33,299 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0760) Prec@1 88.000 (87.792) Prec@5 99.000 (99.075) +2022-11-14 16:15:33,310 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0758) Prec@1 90.000 (87.833) Prec@5 100.000 (99.093) +2022-11-14 16:15:33,319 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0761) Prec@1 84.000 (87.764) Prec@5 100.000 (99.109) +2022-11-14 16:15:33,328 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0760) Prec@1 89.000 (87.786) Prec@5 99.000 (99.107) +2022-11-14 16:15:33,340 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0759) Prec@1 87.000 (87.772) Prec@5 100.000 (99.123) +2022-11-14 16:15:33,352 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0758) Prec@1 91.000 (87.828) Prec@5 98.000 (99.103) +2022-11-14 16:15:33,362 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0763) Prec@1 81.000 (87.712) Prec@5 99.000 (99.102) +2022-11-14 16:15:33,374 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0766) Prec@1 84.000 (87.650) Prec@5 100.000 (99.117) +2022-11-14 16:15:33,385 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0766) Prec@1 88.000 (87.656) Prec@5 100.000 (99.131) +2022-11-14 16:15:33,398 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0762) Prec@1 92.000 (87.726) Prec@5 100.000 (99.145) +2022-11-14 16:15:33,408 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0761) Prec@1 88.000 (87.730) Prec@5 100.000 (99.159) +2022-11-14 16:15:33,419 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0377 (0.0755) Prec@1 94.000 (87.828) Prec@5 100.000 (99.172) +2022-11-14 16:15:33,431 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0760) Prec@1 82.000 (87.738) Prec@5 100.000 (99.185) +2022-11-14 16:15:33,443 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0762) Prec@1 84.000 (87.682) Prec@5 98.000 (99.167) +2022-11-14 16:15:33,452 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0759) Prec@1 89.000 (87.701) Prec@5 100.000 (99.179) +2022-11-14 16:15:33,463 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0755) Prec@1 91.000 (87.750) Prec@5 100.000 (99.191) +2022-11-14 16:15:33,476 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0754) Prec@1 86.000 (87.725) Prec@5 98.000 (99.174) +2022-11-14 16:15:33,488 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0755) Prec@1 86.000 (87.700) Prec@5 100.000 (99.186) +2022-11-14 16:15:33,497 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0759) Prec@1 85.000 (87.662) Prec@5 100.000 (99.197) +2022-11-14 16:15:33,507 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0758) Prec@1 90.000 (87.694) Prec@5 100.000 (99.208) +2022-11-14 16:15:33,517 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0754) Prec@1 95.000 (87.795) Prec@5 100.000 (99.219) +2022-11-14 16:15:33,528 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0496 (0.0750) Prec@1 93.000 (87.865) Prec@5 99.000 (99.216) +2022-11-14 16:15:33,537 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1280 (0.0757) Prec@1 80.000 (87.760) Prec@5 100.000 (99.227) +2022-11-14 16:15:33,547 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0758) Prec@1 89.000 (87.776) Prec@5 100.000 (99.237) +2022-11-14 16:15:33,557 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0758) Prec@1 87.000 (87.766) Prec@5 99.000 (99.234) +2022-11-14 16:15:33,571 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0758) Prec@1 89.000 (87.782) Prec@5 99.000 (99.231) +2022-11-14 16:15:33,583 Test: [78/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0760) Prec@1 86.000 (87.759) Prec@5 100.000 (99.241) +2022-11-14 16:15:33,597 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0759) Prec@1 88.000 (87.763) Prec@5 100.000 (99.250) +2022-11-14 16:15:33,610 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0760) Prec@1 88.000 (87.765) Prec@5 99.000 (99.247) +2022-11-14 16:15:33,625 Test: [81/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0760) Prec@1 89.000 (87.780) Prec@5 100.000 (99.256) +2022-11-14 16:15:33,639 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0761) Prec@1 87.000 (87.771) Prec@5 100.000 (99.265) +2022-11-14 16:15:33,652 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0760) Prec@1 89.000 (87.786) Prec@5 99.000 (99.262) +2022-11-14 16:15:33,665 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0760) Prec@1 87.000 (87.776) Prec@5 99.000 (99.259) +2022-11-14 16:15:33,682 Test: [85/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0764) Prec@1 83.000 (87.721) Prec@5 100.000 (99.267) +2022-11-14 16:15:33,696 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0763) Prec@1 88.000 (87.724) Prec@5 100.000 (99.276) +2022-11-14 16:15:33,711 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0764) Prec@1 87.000 (87.716) Prec@5 98.000 (99.261) +2022-11-14 16:15:33,723 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0764) Prec@1 86.000 (87.697) Prec@5 100.000 (99.270) +2022-11-14 16:15:33,734 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0763) Prec@1 91.000 (87.733) Prec@5 99.000 (99.267) +2022-11-14 16:15:33,743 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0528 (0.0761) Prec@1 92.000 (87.780) Prec@5 100.000 (99.275) +2022-11-14 16:15:33,754 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0759) Prec@1 89.000 (87.793) Prec@5 98.000 (99.261) +2022-11-14 16:15:33,766 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0760) Prec@1 86.000 (87.774) Prec@5 100.000 (99.269) +2022-11-14 16:15:33,778 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0760) Prec@1 86.000 (87.755) Prec@5 98.000 (99.255) +2022-11-14 16:15:33,789 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0761) Prec@1 85.000 (87.726) Prec@5 100.000 (99.263) +2022-11-14 16:15:33,800 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0759) Prec@1 91.000 (87.760) Prec@5 97.000 (99.240) +2022-11-14 16:15:33,810 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0523 (0.0757) Prec@1 93.000 (87.814) Prec@5 98.000 (99.227) +2022-11-14 16:15:33,821 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0759) Prec@1 84.000 (87.776) Prec@5 100.000 (99.235) +2022-11-14 16:15:33,831 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0762) Prec@1 82.000 (87.717) Prec@5 99.000 (99.232) +2022-11-14 16:15:33,842 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0761) Prec@1 91.000 (87.750) Prec@5 100.000 (99.240) +2022-11-14 16:15:33,909 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:15:34,287 Epoch: [322][0/500] Time 0.029 (0.029) Data 0.280 (0.280) Loss 0.0299 (0.0299) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:15:34,559 Epoch: [322][10/500] Time 0.030 (0.025) Data 0.002 (0.027) Loss 0.0391 (0.0345) Prec@1 94.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:15:34,817 Epoch: [322][20/500] Time 0.022 (0.024) Data 0.002 (0.015) Loss 0.0413 (0.0368) Prec@1 93.000 (93.667) Prec@5 100.000 (99.667) +2022-11-14 16:15:35,180 Epoch: [322][30/500] Time 0.050 (0.026) Data 0.002 (0.011) Loss 0.0285 (0.0347) Prec@1 95.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:15:35,580 Epoch: [322][40/500] Time 0.031 (0.029) Data 0.002 (0.009) Loss 0.0277 (0.0333) Prec@1 96.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:15:35,933 Epoch: [322][50/500] Time 0.039 (0.029) Data 0.002 (0.008) Loss 0.0356 (0.0337) Prec@1 94.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:15:36,303 Epoch: [322][60/500] Time 0.033 (0.030) Data 0.002 (0.007) Loss 0.0261 (0.0326) Prec@1 95.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 16:15:36,671 Epoch: [322][70/500] Time 0.039 (0.030) Data 0.003 (0.006) Loss 0.0308 (0.0324) Prec@1 94.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 16:15:37,030 Epoch: [322][80/500] Time 0.032 (0.031) Data 0.002 (0.006) Loss 0.0151 (0.0304) Prec@1 98.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 16:15:37,491 Epoch: [322][90/500] Time 0.089 (0.031) Data 0.002 (0.005) Loss 0.0372 (0.0311) Prec@1 94.000 (94.700) Prec@5 99.000 (99.800) +2022-11-14 16:15:38,267 Epoch: [322][100/500] Time 0.081 (0.035) Data 0.002 (0.005) Loss 0.0360 (0.0316) Prec@1 93.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 16:15:39,084 Epoch: [322][110/500] Time 0.086 (0.038) Data 0.002 (0.005) Loss 0.0344 (0.0318) Prec@1 94.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 16:15:39,876 Epoch: [322][120/500] Time 0.079 (0.041) Data 0.002 (0.004) Loss 0.0475 (0.0330) Prec@1 90.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 16:15:40,675 Epoch: [322][130/500] Time 0.079 (0.043) Data 0.002 (0.004) Loss 0.0324 (0.0330) Prec@1 96.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 16:15:41,449 Epoch: [322][140/500] Time 0.063 (0.045) Data 0.002 (0.004) Loss 0.0236 (0.0323) Prec@1 97.000 (94.467) Prec@5 100.000 (99.867) +2022-11-14 16:15:42,262 Epoch: [322][150/500] Time 0.081 (0.047) Data 0.002 (0.004) Loss 0.0273 (0.0320) Prec@1 95.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:15:43,027 Epoch: [322][160/500] Time 0.076 (0.048) Data 0.002 (0.004) Loss 0.0352 (0.0322) Prec@1 92.000 (94.353) Prec@5 100.000 (99.882) +2022-11-14 16:15:43,814 Epoch: [322][170/500] Time 0.074 (0.050) Data 0.003 (0.004) Loss 0.0200 (0.0315) Prec@1 97.000 (94.500) Prec@5 100.000 (99.889) +2022-11-14 16:15:44,553 Epoch: [322][180/500] Time 0.070 (0.051) Data 0.002 (0.004) Loss 0.0364 (0.0318) Prec@1 95.000 (94.526) Prec@5 100.000 (99.895) +2022-11-14 16:15:45,316 Epoch: [322][190/500] Time 0.072 (0.051) Data 0.002 (0.004) Loss 0.0560 (0.0330) Prec@1 92.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:15:46,121 Epoch: [322][200/500] Time 0.079 (0.053) Data 0.002 (0.003) Loss 0.0515 (0.0339) Prec@1 93.000 (94.333) Prec@5 99.000 (99.857) +2022-11-14 16:15:46,892 Epoch: [322][210/500] Time 0.072 (0.053) Data 0.003 (0.003) Loss 0.0391 (0.0341) Prec@1 94.000 (94.318) Prec@5 99.000 (99.818) +2022-11-14 16:15:47,670 Epoch: [322][220/500] Time 0.076 (0.054) Data 0.002 (0.003) Loss 0.0470 (0.0347) Prec@1 92.000 (94.217) Prec@5 100.000 (99.826) +2022-11-14 16:15:48,447 Epoch: [322][230/500] Time 0.083 (0.055) Data 0.002 (0.003) Loss 0.0225 (0.0342) Prec@1 96.000 (94.292) Prec@5 100.000 (99.833) +2022-11-14 16:15:49,161 Epoch: [322][240/500] Time 0.075 (0.055) Data 0.002 (0.003) Loss 0.0327 (0.0341) Prec@1 93.000 (94.240) Prec@5 100.000 (99.840) +2022-11-14 16:15:49,928 Epoch: [322][250/500] Time 0.079 (0.056) Data 0.002 (0.003) Loss 0.0286 (0.0339) Prec@1 96.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 16:15:50,406 Epoch: [322][260/500] Time 0.036 (0.055) Data 0.002 (0.003) Loss 0.0314 (0.0338) Prec@1 94.000 (94.296) Prec@5 100.000 (99.852) +2022-11-14 16:15:50,827 Epoch: [322][270/500] Time 0.035 (0.054) Data 0.002 (0.003) Loss 0.0439 (0.0342) Prec@1 92.000 (94.214) Prec@5 98.000 (99.786) +2022-11-14 16:15:51,250 Epoch: [322][280/500] Time 0.042 (0.054) Data 0.002 (0.003) Loss 0.0281 (0.0340) Prec@1 92.000 (94.138) Prec@5 100.000 (99.793) +2022-11-14 16:15:51,666 Epoch: [322][290/500] Time 0.039 (0.053) Data 0.002 (0.003) Loss 0.0228 (0.0336) Prec@1 97.000 (94.233) Prec@5 100.000 (99.800) +2022-11-14 16:15:52,086 Epoch: [322][300/500] Time 0.038 (0.053) Data 0.001 (0.003) Loss 0.0756 (0.0349) Prec@1 86.000 (93.968) Prec@5 100.000 (99.806) +2022-11-14 16:15:52,496 Epoch: [322][310/500] Time 0.039 (0.052) Data 0.002 (0.003) Loss 0.0265 (0.0347) Prec@1 96.000 (94.031) Prec@5 100.000 (99.812) +2022-11-14 16:15:52,930 Epoch: [322][320/500] Time 0.043 (0.052) Data 0.002 (0.003) Loss 0.0209 (0.0343) Prec@1 97.000 (94.121) Prec@5 100.000 (99.818) +2022-11-14 16:15:53,336 Epoch: [322][330/500] Time 0.038 (0.051) Data 0.002 (0.003) Loss 0.0411 (0.0345) Prec@1 94.000 (94.118) Prec@5 99.000 (99.794) +2022-11-14 16:15:53,759 Epoch: [322][340/500] Time 0.047 (0.051) Data 0.002 (0.003) Loss 0.0322 (0.0344) Prec@1 95.000 (94.143) Prec@5 100.000 (99.800) +2022-11-14 16:15:54,179 Epoch: [322][350/500] Time 0.040 (0.051) Data 0.002 (0.003) Loss 0.0340 (0.0344) Prec@1 95.000 (94.167) Prec@5 100.000 (99.806) +2022-11-14 16:15:54,607 Epoch: [322][360/500] Time 0.039 (0.050) Data 0.002 (0.003) Loss 0.0315 (0.0343) Prec@1 93.000 (94.135) Prec@5 100.000 (99.811) +2022-11-14 16:15:55,030 Epoch: [322][370/500] Time 0.041 (0.050) Data 0.002 (0.003) Loss 0.0199 (0.0339) Prec@1 95.000 (94.158) Prec@5 100.000 (99.816) +2022-11-14 16:15:55,453 Epoch: [322][380/500] Time 0.037 (0.050) Data 0.002 (0.003) Loss 0.0348 (0.0340) Prec@1 93.000 (94.128) Prec@5 100.000 (99.821) +2022-11-14 16:15:55,878 Epoch: [322][390/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0279 (0.0338) Prec@1 94.000 (94.125) Prec@5 100.000 (99.825) +2022-11-14 16:15:56,305 Epoch: [322][400/500] Time 0.037 (0.049) Data 0.002 (0.003) Loss 0.0397 (0.0339) Prec@1 93.000 (94.098) Prec@5 99.000 (99.805) +2022-11-14 16:15:56,722 Epoch: [322][410/500] Time 0.035 (0.049) Data 0.002 (0.003) Loss 0.0371 (0.0340) Prec@1 91.000 (94.024) Prec@5 100.000 (99.810) +2022-11-14 16:15:57,148 Epoch: [322][420/500] Time 0.037 (0.048) Data 0.002 (0.003) Loss 0.0551 (0.0345) Prec@1 89.000 (93.907) Prec@5 100.000 (99.814) +2022-11-14 16:15:57,554 Epoch: [322][430/500] Time 0.040 (0.048) Data 0.002 (0.003) Loss 0.0358 (0.0345) Prec@1 94.000 (93.909) Prec@5 100.000 (99.818) +2022-11-14 16:15:57,970 Epoch: [322][440/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0417 (0.0347) Prec@1 94.000 (93.911) Prec@5 100.000 (99.822) +2022-11-14 16:15:58,394 Epoch: [322][450/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0106 (0.0342) Prec@1 99.000 (94.022) Prec@5 100.000 (99.826) +2022-11-14 16:15:58,819 Epoch: [322][460/500] Time 0.044 (0.047) Data 0.002 (0.003) Loss 0.0236 (0.0339) Prec@1 97.000 (94.085) Prec@5 100.000 (99.830) +2022-11-14 16:15:59,236 Epoch: [322][470/500] Time 0.046 (0.047) Data 0.002 (0.003) Loss 0.0487 (0.0343) Prec@1 92.000 (94.042) Prec@5 100.000 (99.833) +2022-11-14 16:15:59,665 Epoch: [322][480/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0314 (0.0342) Prec@1 94.000 (94.041) Prec@5 100.000 (99.837) +2022-11-14 16:16:00,091 Epoch: [322][490/500] Time 0.041 (0.047) Data 0.002 (0.003) Loss 0.0300 (0.0341) Prec@1 95.000 (94.060) Prec@5 99.000 (99.820) +2022-11-14 16:16:00,482 Epoch: [322][499/500] Time 0.042 (0.047) Data 0.002 (0.003) Loss 0.0174 (0.0338) Prec@1 97.000 (94.118) Prec@5 100.000 (99.824) +2022-11-14 16:16:00,807 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0545 (0.0545) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:16:00,816 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0614) Prec@1 90.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:16:00,826 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0656) Prec@1 90.000 (90.667) Prec@5 99.000 (99.333) +2022-11-14 16:16:00,841 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0876 (0.0711) Prec@1 85.000 (89.250) Prec@5 100.000 (99.500) +2022-11-14 16:16:00,852 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0735) Prec@1 87.000 (88.800) Prec@5 98.000 (99.200) +2022-11-14 16:16:00,863 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0684) Prec@1 92.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 16:16:00,874 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0667) Prec@1 92.000 (89.714) Prec@5 100.000 (99.429) +2022-11-14 16:16:00,887 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1115 (0.0723) Prec@1 80.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:16:00,899 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0908 (0.0744) Prec@1 84.000 (88.000) Prec@5 99.000 (99.444) +2022-11-14 16:16:00,913 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0735) Prec@1 91.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 16:16:00,927 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0718) Prec@1 91.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 16:16:00,942 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0724) Prec@1 88.000 (88.500) Prec@5 99.000 (99.417) +2022-11-14 16:16:00,957 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0721) Prec@1 89.000 (88.538) Prec@5 99.000 (99.385) +2022-11-14 16:16:00,970 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0717) Prec@1 88.000 (88.500) Prec@5 98.000 (99.286) +2022-11-14 16:16:00,982 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0728) Prec@1 86.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:16:00,998 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0725) Prec@1 89.000 (88.375) Prec@5 100.000 (99.375) +2022-11-14 16:16:01,011 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0711) Prec@1 94.000 (88.706) Prec@5 99.000 (99.353) +2022-11-14 16:16:01,023 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1048 (0.0729) Prec@1 86.000 (88.556) Prec@5 99.000 (99.333) +2022-11-14 16:16:01,037 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0729) Prec@1 88.000 (88.526) Prec@5 99.000 (99.316) +2022-11-14 16:16:01,051 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0735) Prec@1 87.000 (88.450) Prec@5 97.000 (99.200) +2022-11-14 16:16:01,067 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0735) Prec@1 86.000 (88.333) Prec@5 100.000 (99.238) +2022-11-14 16:16:01,081 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0741) Prec@1 84.000 (88.136) Prec@5 98.000 (99.182) +2022-11-14 16:16:01,096 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0748) Prec@1 87.000 (88.087) Prec@5 98.000 (99.130) +2022-11-14 16:16:01,110 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0745) Prec@1 88.000 (88.083) Prec@5 100.000 (99.167) +2022-11-14 16:16:01,124 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0745) Prec@1 89.000 (88.120) Prec@5 100.000 (99.200) +2022-11-14 16:16:01,138 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0747) Prec@1 87.000 (88.077) Prec@5 99.000 (99.192) +2022-11-14 16:16:01,151 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0739) Prec@1 92.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 16:16:01,165 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0734) Prec@1 91.000 (88.321) Prec@5 99.000 (99.214) +2022-11-14 16:16:01,179 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0736) Prec@1 84.000 (88.172) Prec@5 99.000 (99.207) +2022-11-14 16:16:01,194 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0733) Prec@1 90.000 (88.233) Prec@5 100.000 (99.233) +2022-11-14 16:16:01,207 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0729) Prec@1 90.000 (88.290) Prec@5 100.000 (99.258) +2022-11-14 16:16:01,222 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0731) Prec@1 87.000 (88.250) Prec@5 100.000 (99.281) +2022-11-14 16:16:01,238 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0732) Prec@1 84.000 (88.121) Prec@5 100.000 (99.303) +2022-11-14 16:16:01,255 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0735) Prec@1 85.000 (88.029) Prec@5 99.000 (99.294) +2022-11-14 16:16:01,269 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0741) Prec@1 84.000 (87.914) Prec@5 97.000 (99.229) +2022-11-14 16:16:01,283 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0740) Prec@1 90.000 (87.972) Prec@5 99.000 (99.222) +2022-11-14 16:16:01,297 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0740) Prec@1 87.000 (87.946) Prec@5 98.000 (99.189) +2022-11-14 16:16:01,313 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0746) Prec@1 82.000 (87.789) Prec@5 100.000 (99.211) +2022-11-14 16:16:01,329 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0577 (0.0742) Prec@1 93.000 (87.923) Prec@5 100.000 (99.231) +2022-11-14 16:16:01,346 Test: [39/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0737) Prec@1 91.000 (88.000) Prec@5 99.000 (99.225) +2022-11-14 16:16:01,359 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0742) Prec@1 85.000 (87.927) Prec@5 98.000 (99.195) +2022-11-14 16:16:01,373 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0742) Prec@1 86.000 (87.881) Prec@5 100.000 (99.214) +2022-11-14 16:16:01,388 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0737) Prec@1 90.000 (87.930) Prec@5 99.000 (99.209) +2022-11-14 16:16:01,404 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0734) Prec@1 91.000 (88.000) Prec@5 100.000 (99.227) +2022-11-14 16:16:01,419 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0732) Prec@1 89.000 (88.022) Prec@5 100.000 (99.244) +2022-11-14 16:16:01,436 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1040 (0.0739) Prec@1 84.000 (87.935) Prec@5 100.000 (99.261) +2022-11-14 16:16:01,451 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0738) Prec@1 90.000 (87.979) Prec@5 99.000 (99.255) +2022-11-14 16:16:01,467 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1194 (0.0747) Prec@1 82.000 (87.854) Prec@5 98.000 (99.229) +2022-11-14 16:16:01,483 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0742) Prec@1 92.000 (87.939) Prec@5 100.000 (99.245) +2022-11-14 16:16:01,497 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0748) Prec@1 85.000 (87.880) Prec@5 99.000 (99.240) +2022-11-14 16:16:01,512 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0742) Prec@1 93.000 (87.980) Prec@5 100.000 (99.255) +2022-11-14 16:16:01,526 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0741) Prec@1 87.000 (87.962) Prec@5 100.000 (99.269) +2022-11-14 16:16:01,539 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0742) Prec@1 89.000 (87.981) Prec@5 100.000 (99.283) +2022-11-14 16:16:01,553 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0743) Prec@1 86.000 (87.944) Prec@5 98.000 (99.259) +2022-11-14 16:16:01,568 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1107 (0.0750) Prec@1 85.000 (87.891) Prec@5 100.000 (99.273) +2022-11-14 16:16:01,582 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0750) Prec@1 90.000 (87.929) Prec@5 98.000 (99.250) +2022-11-14 16:16:01,596 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0748) Prec@1 88.000 (87.930) Prec@5 99.000 (99.246) +2022-11-14 16:16:01,611 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0748) Prec@1 88.000 (87.931) Prec@5 99.000 (99.241) +2022-11-14 16:16:01,628 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0752) Prec@1 81.000 (87.814) Prec@5 100.000 (99.254) +2022-11-14 16:16:01,645 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0750) Prec@1 89.000 (87.833) Prec@5 100.000 (99.267) +2022-11-14 16:16:01,662 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0750) Prec@1 89.000 (87.852) Prec@5 100.000 (99.279) +2022-11-14 16:16:01,676 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0750) Prec@1 89.000 (87.871) Prec@5 100.000 (99.290) +2022-11-14 16:16:01,691 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0750) Prec@1 86.000 (87.841) Prec@5 100.000 (99.302) +2022-11-14 16:16:01,705 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0745) Prec@1 91.000 (87.891) Prec@5 100.000 (99.312) +2022-11-14 16:16:01,720 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0747) Prec@1 84.000 (87.831) Prec@5 99.000 (99.308) +2022-11-14 16:16:01,735 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0747) Prec@1 87.000 (87.818) Prec@5 100.000 (99.318) +2022-11-14 16:16:01,749 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0746) Prec@1 90.000 (87.851) Prec@5 100.000 (99.328) +2022-11-14 16:16:01,763 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0748) Prec@1 84.000 (87.794) Prec@5 99.000 (99.324) +2022-11-14 16:16:01,777 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0750) Prec@1 85.000 (87.754) Prec@5 99.000 (99.319) +2022-11-14 16:16:01,791 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0750) Prec@1 87.000 (87.743) Prec@5 100.000 (99.329) +2022-11-14 16:16:01,807 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0753) Prec@1 85.000 (87.704) Prec@5 99.000 (99.324) +2022-11-14 16:16:01,823 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0752) Prec@1 87.000 (87.694) Prec@5 100.000 (99.333) +2022-11-14 16:16:01,837 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0749) Prec@1 93.000 (87.767) Prec@5 99.000 (99.329) +2022-11-14 16:16:01,851 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0437 (0.0745) Prec@1 94.000 (87.851) Prec@5 100.000 (99.338) +2022-11-14 16:16:01,865 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1235 (0.0751) Prec@1 83.000 (87.787) Prec@5 98.000 (99.320) +2022-11-14 16:16:01,878 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0750) Prec@1 91.000 (87.829) Prec@5 99.000 (99.316) +2022-11-14 16:16:01,893 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0749) Prec@1 88.000 (87.831) Prec@5 99.000 (99.312) +2022-11-14 16:16:01,908 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0751) Prec@1 83.000 (87.769) Prec@5 99.000 (99.308) +2022-11-14 16:16:01,923 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0751) Prec@1 87.000 (87.759) Prec@5 99.000 (99.304) +2022-11-14 16:16:01,938 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0750) Prec@1 88.000 (87.763) Prec@5 100.000 (99.312) +2022-11-14 16:16:01,953 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0752) Prec@1 85.000 (87.728) Prec@5 97.000 (99.284) +2022-11-14 16:16:01,968 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0753) Prec@1 87.000 (87.720) Prec@5 100.000 (99.293) +2022-11-14 16:16:01,982 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0754) Prec@1 89.000 (87.735) Prec@5 99.000 (99.289) +2022-11-14 16:16:01,995 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0755) Prec@1 86.000 (87.714) Prec@5 99.000 (99.286) +2022-11-14 16:16:02,009 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0758) Prec@1 85.000 (87.682) Prec@5 99.000 (99.282) +2022-11-14 16:16:02,025 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0760) Prec@1 84.000 (87.640) Prec@5 99.000 (99.279) +2022-11-14 16:16:02,041 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0761) Prec@1 87.000 (87.632) Prec@5 100.000 (99.287) +2022-11-14 16:16:02,056 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0758) Prec@1 90.000 (87.659) Prec@5 99.000 (99.284) +2022-11-14 16:16:02,071 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0755) Prec@1 95.000 (87.742) Prec@5 100.000 (99.292) +2022-11-14 16:16:02,086 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0754) Prec@1 89.000 (87.756) Prec@5 99.000 (99.289) +2022-11-14 16:16:02,102 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0753) Prec@1 89.000 (87.769) Prec@5 100.000 (99.297) +2022-11-14 16:16:02,119 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0449 (0.0749) Prec@1 93.000 (87.826) Prec@5 100.000 (99.304) +2022-11-14 16:16:02,135 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0752) Prec@1 85.000 (87.796) Prec@5 98.000 (99.290) +2022-11-14 16:16:02,148 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0752) Prec@1 89.000 (87.809) Prec@5 99.000 (99.287) +2022-11-14 16:16:02,163 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0754) Prec@1 85.000 (87.779) Prec@5 99.000 (99.284) +2022-11-14 16:16:02,178 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0755) Prec@1 87.000 (87.771) Prec@5 99.000 (99.281) +2022-11-14 16:16:02,191 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0362 (0.0751) Prec@1 95.000 (87.845) Prec@5 98.000 (99.268) +2022-11-14 16:16:02,206 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0753) Prec@1 86.000 (87.827) Prec@5 100.000 (99.276) +2022-11-14 16:16:02,223 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0754) Prec@1 85.000 (87.798) Prec@5 99.000 (99.273) +2022-11-14 16:16:02,238 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0752) Prec@1 90.000 (87.820) Prec@5 100.000 (99.280) +2022-11-14 16:16:02,305 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:16:02,671 Epoch: [323][0/500] Time 0.026 (0.026) Data 0.273 (0.273) Loss 0.0269 (0.0269) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:03,049 Epoch: [323][10/500] Time 0.037 (0.032) Data 0.002 (0.027) Loss 0.0294 (0.0281) Prec@1 95.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 16:16:03,463 Epoch: [323][20/500] Time 0.037 (0.035) Data 0.002 (0.015) Loss 0.0478 (0.0347) Prec@1 92.000 (94.667) Prec@5 98.000 (99.000) +2022-11-14 16:16:03,896 Epoch: [323][30/500] Time 0.044 (0.036) Data 0.002 (0.011) Loss 0.0501 (0.0385) Prec@1 92.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:16:04,324 Epoch: [323][40/500] Time 0.041 (0.037) Data 0.002 (0.009) Loss 0.0177 (0.0344) Prec@1 97.000 (94.600) Prec@5 100.000 (99.200) +2022-11-14 16:16:04,783 Epoch: [323][50/500] Time 0.037 (0.037) Data 0.002 (0.007) Loss 0.0228 (0.0324) Prec@1 97.000 (95.000) Prec@5 100.000 (99.333) +2022-11-14 16:16:05,332 Epoch: [323][60/500] Time 0.067 (0.039) Data 0.002 (0.007) Loss 0.0410 (0.0337) Prec@1 94.000 (94.857) Prec@5 100.000 (99.429) +2022-11-14 16:16:06,082 Epoch: [323][70/500] Time 0.070 (0.043) Data 0.003 (0.006) Loss 0.0344 (0.0338) Prec@1 94.000 (94.750) Prec@5 100.000 (99.500) +2022-11-14 16:16:06,981 Epoch: [323][80/500] Time 0.080 (0.048) Data 0.002 (0.005) Loss 0.0395 (0.0344) Prec@1 94.000 (94.667) Prec@5 100.000 (99.556) +2022-11-14 16:16:07,861 Epoch: [323][90/500] Time 0.073 (0.051) Data 0.002 (0.005) Loss 0.0274 (0.0337) Prec@1 95.000 (94.700) Prec@5 100.000 (99.600) +2022-11-14 16:16:08,763 Epoch: [323][100/500] Time 0.076 (0.054) Data 0.002 (0.005) Loss 0.0320 (0.0335) Prec@1 94.000 (94.636) Prec@5 100.000 (99.636) +2022-11-14 16:16:09,654 Epoch: [323][110/500] Time 0.064 (0.057) Data 0.002 (0.005) Loss 0.0171 (0.0322) Prec@1 98.000 (94.917) Prec@5 100.000 (99.667) +2022-11-14 16:16:10,419 Epoch: [323][120/500] Time 0.083 (0.058) Data 0.002 (0.004) Loss 0.0486 (0.0334) Prec@1 93.000 (94.769) Prec@5 100.000 (99.692) +2022-11-14 16:16:11,223 Epoch: [323][130/500] Time 0.082 (0.059) Data 0.002 (0.004) Loss 0.0476 (0.0344) Prec@1 91.000 (94.500) Prec@5 100.000 (99.714) +2022-11-14 16:16:11,978 Epoch: [323][140/500] Time 0.061 (0.060) Data 0.002 (0.004) Loss 0.0165 (0.0333) Prec@1 99.000 (94.800) Prec@5 100.000 (99.733) +2022-11-14 16:16:12,767 Epoch: [323][150/500] Time 0.078 (0.060) Data 0.002 (0.004) Loss 0.0345 (0.0333) Prec@1 94.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:16:13,531 Epoch: [323][160/500] Time 0.074 (0.061) Data 0.002 (0.004) Loss 0.0299 (0.0331) Prec@1 95.000 (94.765) Prec@5 100.000 (99.765) +2022-11-14 16:16:14,401 Epoch: [323][170/500] Time 0.078 (0.062) Data 0.002 (0.004) Loss 0.0230 (0.0326) Prec@1 96.000 (94.833) Prec@5 99.000 (99.722) +2022-11-14 16:16:15,266 Epoch: [323][180/500] Time 0.084 (0.063) Data 0.002 (0.004) Loss 0.0408 (0.0330) Prec@1 93.000 (94.737) Prec@5 100.000 (99.737) +2022-11-14 16:16:16,122 Epoch: [323][190/500] Time 0.081 (0.063) Data 0.002 (0.004) Loss 0.0101 (0.0319) Prec@1 98.000 (94.900) Prec@5 100.000 (99.750) +2022-11-14 16:16:17,030 Epoch: [323][200/500] Time 0.098 (0.064) Data 0.002 (0.003) Loss 0.0269 (0.0316) Prec@1 97.000 (95.000) Prec@5 99.000 (99.714) +2022-11-14 16:16:17,817 Epoch: [323][210/500] Time 0.082 (0.065) Data 0.002 (0.003) Loss 0.0448 (0.0322) Prec@1 93.000 (94.909) Prec@5 100.000 (99.727) +2022-11-14 16:16:18,685 Epoch: [323][220/500] Time 0.094 (0.065) Data 0.003 (0.003) Loss 0.0370 (0.0324) Prec@1 94.000 (94.870) Prec@5 100.000 (99.739) +2022-11-14 16:16:19,551 Epoch: [323][230/500] Time 0.121 (0.066) Data 0.002 (0.003) Loss 0.0184 (0.0318) Prec@1 98.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:16:20,370 Epoch: [323][240/500] Time 0.073 (0.066) Data 0.002 (0.003) Loss 0.0421 (0.0323) Prec@1 94.000 (94.960) Prec@5 100.000 (99.760) +2022-11-14 16:16:20,994 Epoch: [323][250/500] Time 0.040 (0.066) Data 0.002 (0.003) Loss 0.0421 (0.0326) Prec@1 93.000 (94.885) Prec@5 100.000 (99.769) +2022-11-14 16:16:21,392 Epoch: [323][260/500] Time 0.035 (0.065) Data 0.002 (0.003) Loss 0.0234 (0.0323) Prec@1 96.000 (94.926) Prec@5 100.000 (99.778) +2022-11-14 16:16:21,878 Epoch: [323][270/500] Time 0.047 (0.064) Data 0.002 (0.003) Loss 0.0300 (0.0322) Prec@1 96.000 (94.964) Prec@5 100.000 (99.786) +2022-11-14 16:16:22,307 Epoch: [323][280/500] Time 0.039 (0.063) Data 0.002 (0.003) Loss 0.0390 (0.0324) Prec@1 94.000 (94.931) Prec@5 100.000 (99.793) +2022-11-14 16:16:22,707 Epoch: [323][290/500] Time 0.037 (0.062) Data 0.002 (0.003) Loss 0.0135 (0.0318) Prec@1 99.000 (95.067) Prec@5 100.000 (99.800) +2022-11-14 16:16:23,094 Epoch: [323][300/500] Time 0.041 (0.061) Data 0.002 (0.003) Loss 0.0308 (0.0318) Prec@1 94.000 (95.032) Prec@5 100.000 (99.806) +2022-11-14 16:16:23,503 Epoch: [323][310/500] Time 0.044 (0.060) Data 0.002 (0.003) Loss 0.0202 (0.0314) Prec@1 97.000 (95.094) Prec@5 100.000 (99.812) +2022-11-14 16:16:23,904 Epoch: [323][320/500] Time 0.029 (0.060) Data 0.002 (0.003) Loss 0.0541 (0.0321) Prec@1 89.000 (94.909) Prec@5 99.000 (99.788) +2022-11-14 16:16:24,310 Epoch: [323][330/500] Time 0.033 (0.059) Data 0.002 (0.003) Loss 0.0344 (0.0322) Prec@1 93.000 (94.853) Prec@5 99.000 (99.765) +2022-11-14 16:16:24,726 Epoch: [323][340/500] Time 0.038 (0.058) Data 0.002 (0.003) Loss 0.0197 (0.0318) Prec@1 96.000 (94.886) Prec@5 100.000 (99.771) +2022-11-14 16:16:25,128 Epoch: [323][350/500] Time 0.038 (0.058) Data 0.002 (0.003) Loss 0.0336 (0.0319) Prec@1 96.000 (94.917) Prec@5 100.000 (99.778) +2022-11-14 16:16:25,594 Epoch: [323][360/500] Time 0.046 (0.057) Data 0.003 (0.003) Loss 0.0487 (0.0323) Prec@1 93.000 (94.865) Prec@5 99.000 (99.757) +2022-11-14 16:16:26,032 Epoch: [323][370/500] Time 0.030 (0.057) Data 0.002 (0.003) Loss 0.0354 (0.0324) Prec@1 94.000 (94.842) Prec@5 100.000 (99.763) +2022-11-14 16:16:26,420 Epoch: [323][380/500] Time 0.034 (0.056) Data 0.002 (0.003) Loss 0.0180 (0.0320) Prec@1 98.000 (94.923) Prec@5 100.000 (99.769) +2022-11-14 16:16:26,829 Epoch: [323][390/500] Time 0.040 (0.056) Data 0.002 (0.003) Loss 0.0281 (0.0319) Prec@1 95.000 (94.925) Prec@5 100.000 (99.775) +2022-11-14 16:16:27,535 Epoch: [323][400/500] Time 0.117 (0.056) Data 0.002 (0.003) Loss 0.0155 (0.0315) Prec@1 98.000 (95.000) Prec@5 100.000 (99.780) +2022-11-14 16:16:28,383 Epoch: [323][410/500] Time 0.076 (0.056) Data 0.002 (0.003) Loss 0.0365 (0.0317) Prec@1 93.000 (94.952) Prec@5 100.000 (99.786) +2022-11-14 16:16:29,356 Epoch: [323][420/500] Time 0.111 (0.057) Data 0.003 (0.003) Loss 0.0235 (0.0315) Prec@1 96.000 (94.977) Prec@5 100.000 (99.791) +2022-11-14 16:16:30,144 Epoch: [323][430/500] Time 0.081 (0.057) Data 0.003 (0.003) Loss 0.0545 (0.0320) Prec@1 90.000 (94.864) Prec@5 100.000 (99.795) +2022-11-14 16:16:30,905 Epoch: [323][440/500] Time 0.062 (0.058) Data 0.002 (0.003) Loss 0.0271 (0.0319) Prec@1 94.000 (94.844) Prec@5 100.000 (99.800) +2022-11-14 16:16:31,728 Epoch: [323][450/500] Time 0.085 (0.058) Data 0.002 (0.003) Loss 0.0177 (0.0316) Prec@1 98.000 (94.913) Prec@5 100.000 (99.804) +2022-11-14 16:16:32,643 Epoch: [323][460/500] Time 0.066 (0.058) Data 0.002 (0.003) Loss 0.0345 (0.0316) Prec@1 95.000 (94.915) Prec@5 100.000 (99.809) +2022-11-14 16:16:33,458 Epoch: [323][470/500] Time 0.069 (0.059) Data 0.002 (0.003) Loss 0.0316 (0.0316) Prec@1 95.000 (94.917) Prec@5 99.000 (99.792) +2022-11-14 16:16:34,206 Epoch: [323][480/500] Time 0.063 (0.059) Data 0.002 (0.003) Loss 0.0241 (0.0315) Prec@1 97.000 (94.959) Prec@5 100.000 (99.796) +2022-11-14 16:16:34,994 Epoch: [323][490/500] Time 0.075 (0.059) Data 0.003 (0.003) Loss 0.0286 (0.0314) Prec@1 96.000 (94.980) Prec@5 100.000 (99.800) +2022-11-14 16:16:35,709 Epoch: [323][499/500] Time 0.066 (0.059) Data 0.002 (0.003) Loss 0.0450 (0.0317) Prec@1 92.000 (94.922) Prec@5 100.000 (99.804) +2022-11-14 16:16:36,034 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0694 (0.0694) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:36,043 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0618 (0.0656) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:36,056 Test: [2/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0766 (0.0693) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:16:36,070 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0739) Prec@1 87.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 16:16:36,080 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0780) Prec@1 87.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 16:16:36,089 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0439 (0.0723) Prec@1 92.000 (88.500) Prec@5 99.000 (99.333) +2022-11-14 16:16:36,100 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0718) Prec@1 91.000 (88.857) Prec@5 99.000 (99.286) +2022-11-14 16:16:36,112 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0738) Prec@1 83.000 (88.125) Prec@5 100.000 (99.375) +2022-11-14 16:16:36,123 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0746) Prec@1 87.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 16:16:36,134 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0753) Prec@1 87.000 (87.900) Prec@5 99.000 (99.300) +2022-11-14 16:16:36,146 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0440 (0.0725) Prec@1 94.000 (88.455) Prec@5 100.000 (99.364) +2022-11-14 16:16:36,159 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0736) Prec@1 85.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 16:16:36,172 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0739) Prec@1 87.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 16:16:36,185 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0735) Prec@1 90.000 (88.214) Prec@5 99.000 (99.357) +2022-11-14 16:16:36,197 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0739) Prec@1 87.000 (88.133) Prec@5 98.000 (99.267) +2022-11-14 16:16:36,211 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0737) Prec@1 89.000 (88.188) Prec@5 100.000 (99.312) +2022-11-14 16:16:36,227 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0735) Prec@1 90.000 (88.294) Prec@5 98.000 (99.235) +2022-11-14 16:16:36,241 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0748) Prec@1 86.000 (88.167) Prec@5 100.000 (99.278) +2022-11-14 16:16:36,254 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0750) Prec@1 87.000 (88.105) Prec@5 99.000 (99.263) +2022-11-14 16:16:36,270 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0762) Prec@1 84.000 (87.900) Prec@5 98.000 (99.200) +2022-11-14 16:16:36,285 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0765) Prec@1 86.000 (87.810) Prec@5 99.000 (99.190) +2022-11-14 16:16:36,300 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0767) Prec@1 88.000 (87.818) Prec@5 100.000 (99.227) +2022-11-14 16:16:36,313 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0774) Prec@1 89.000 (87.870) Prec@5 98.000 (99.174) +2022-11-14 16:16:36,326 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0777) Prec@1 84.000 (87.708) Prec@5 100.000 (99.208) +2022-11-14 16:16:36,341 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0779) Prec@1 87.000 (87.680) Prec@5 100.000 (99.240) +2022-11-14 16:16:36,354 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0790) Prec@1 82.000 (87.462) Prec@5 98.000 (99.192) +2022-11-14 16:16:36,369 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0779) Prec@1 92.000 (87.630) Prec@5 100.000 (99.222) +2022-11-14 16:16:36,382 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0778) Prec@1 88.000 (87.643) Prec@5 99.000 (99.214) +2022-11-14 16:16:36,395 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0776) Prec@1 87.000 (87.621) Prec@5 98.000 (99.172) +2022-11-14 16:16:36,408 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0769) Prec@1 92.000 (87.767) Prec@5 100.000 (99.200) +2022-11-14 16:16:36,422 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0766) Prec@1 89.000 (87.806) Prec@5 100.000 (99.226) +2022-11-14 16:16:36,439 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0767) Prec@1 87.000 (87.781) Prec@5 99.000 (99.219) +2022-11-14 16:16:36,453 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0766) Prec@1 88.000 (87.788) Prec@5 100.000 (99.242) +2022-11-14 16:16:36,468 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0992 (0.0772) Prec@1 84.000 (87.676) Prec@5 99.000 (99.235) +2022-11-14 16:16:36,482 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0777) Prec@1 82.000 (87.514) Prec@5 99.000 (99.229) +2022-11-14 16:16:36,493 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0775) Prec@1 90.000 (87.583) Prec@5 100.000 (99.250) +2022-11-14 16:16:36,508 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0778) Prec@1 85.000 (87.514) Prec@5 99.000 (99.243) +2022-11-14 16:16:36,523 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0784) Prec@1 83.000 (87.395) Prec@5 99.000 (99.237) +2022-11-14 16:16:36,537 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0443 (0.0775) Prec@1 94.000 (87.564) Prec@5 98.000 (99.205) +2022-11-14 16:16:36,551 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0768) Prec@1 92.000 (87.675) Prec@5 100.000 (99.225) +2022-11-14 16:16:36,565 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0771) Prec@1 86.000 (87.634) Prec@5 98.000 (99.195) +2022-11-14 16:16:36,580 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0770) Prec@1 89.000 (87.667) Prec@5 100.000 (99.214) +2022-11-14 16:16:36,592 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0763) Prec@1 93.000 (87.791) Prec@5 99.000 (99.209) +2022-11-14 16:16:36,607 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0761) Prec@1 89.000 (87.818) Prec@5 99.000 (99.205) +2022-11-14 16:16:36,623 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0759) Prec@1 89.000 (87.844) Prec@5 99.000 (99.200) +2022-11-14 16:16:36,636 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0762) Prec@1 86.000 (87.804) Prec@5 99.000 (99.196) +2022-11-14 16:16:36,646 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0759) Prec@1 89.000 (87.830) Prec@5 100.000 (99.213) +2022-11-14 16:16:36,660 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0763) Prec@1 85.000 (87.771) Prec@5 98.000 (99.188) +2022-11-14 16:16:36,675 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0759) Prec@1 91.000 (87.837) Prec@5 100.000 (99.204) +2022-11-14 16:16:36,689 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0764) Prec@1 84.000 (87.760) Prec@5 100.000 (99.220) +2022-11-14 16:16:36,703 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0503 (0.0759) Prec@1 91.000 (87.824) Prec@5 100.000 (99.235) +2022-11-14 16:16:36,717 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0757) Prec@1 88.000 (87.827) Prec@5 99.000 (99.231) +2022-11-14 16:16:36,732 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0755) Prec@1 90.000 (87.868) Prec@5 100.000 (99.245) +2022-11-14 16:16:36,747 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0751) Prec@1 92.000 (87.944) Prec@5 98.000 (99.222) +2022-11-14 16:16:36,758 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0752) Prec@1 89.000 (87.964) Prec@5 100.000 (99.236) +2022-11-14 16:16:36,773 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0753) Prec@1 88.000 (87.964) Prec@5 99.000 (99.232) +2022-11-14 16:16:36,788 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0753) Prec@1 87.000 (87.947) Prec@5 100.000 (99.246) +2022-11-14 16:16:36,802 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0752) Prec@1 90.000 (87.983) Prec@5 98.000 (99.224) +2022-11-14 16:16:36,816 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0977 (0.0756) Prec@1 86.000 (87.949) Prec@5 99.000 (99.220) +2022-11-14 16:16:36,830 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0755) Prec@1 86.000 (87.917) Prec@5 100.000 (99.233) +2022-11-14 16:16:36,841 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0753) Prec@1 90.000 (87.951) Prec@5 100.000 (99.246) +2022-11-14 16:16:36,856 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0751) Prec@1 90.000 (87.984) Prec@5 100.000 (99.258) +2022-11-14 16:16:36,871 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0748) Prec@1 93.000 (88.063) Prec@5 100.000 (99.270) +2022-11-14 16:16:36,887 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0308 (0.0741) Prec@1 95.000 (88.172) Prec@5 100.000 (99.281) +2022-11-14 16:16:36,899 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0747) Prec@1 81.000 (88.062) Prec@5 99.000 (99.277) +2022-11-14 16:16:36,914 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0747) Prec@1 89.000 (88.076) Prec@5 100.000 (99.288) +2022-11-14 16:16:36,928 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0452 (0.0742) Prec@1 93.000 (88.149) Prec@5 100.000 (99.299) +2022-11-14 16:16:36,941 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0742) Prec@1 89.000 (88.162) Prec@5 99.000 (99.294) +2022-11-14 16:16:36,957 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0740) Prec@1 89.000 (88.174) Prec@5 99.000 (99.290) +2022-11-14 16:16:36,971 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0744) Prec@1 86.000 (88.143) Prec@5 98.000 (99.271) +2022-11-14 16:16:36,985 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0747) Prec@1 86.000 (88.113) Prec@5 99.000 (99.268) +2022-11-14 16:16:37,001 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0746) Prec@1 89.000 (88.125) Prec@5 99.000 (99.264) +2022-11-14 16:16:37,015 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0459 (0.0742) Prec@1 94.000 (88.205) Prec@5 100.000 (99.274) +2022-11-14 16:16:37,030 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0739) Prec@1 92.000 (88.257) Prec@5 100.000 (99.284) +2022-11-14 16:16:37,046 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0741) Prec@1 85.000 (88.213) Prec@5 100.000 (99.293) +2022-11-14 16:16:37,061 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0739) Prec@1 91.000 (88.250) Prec@5 99.000 (99.289) +2022-11-14 16:16:37,076 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0736) Prec@1 93.000 (88.312) Prec@5 98.000 (99.273) +2022-11-14 16:16:37,090 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0738) Prec@1 84.000 (88.256) Prec@5 98.000 (99.256) +2022-11-14 16:16:37,104 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0739) Prec@1 86.000 (88.228) Prec@5 100.000 (99.266) +2022-11-14 16:16:37,119 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0737) Prec@1 89.000 (88.237) Prec@5 100.000 (99.275) +2022-11-14 16:16:37,132 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0739) Prec@1 85.000 (88.198) Prec@5 98.000 (99.259) +2022-11-14 16:16:37,145 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0739) Prec@1 87.000 (88.183) Prec@5 100.000 (99.268) +2022-11-14 16:16:37,157 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0740) Prec@1 87.000 (88.169) Prec@5 99.000 (99.265) +2022-11-14 16:16:37,171 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0740) Prec@1 85.000 (88.131) Prec@5 100.000 (99.274) +2022-11-14 16:16:37,184 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0740) Prec@1 89.000 (88.141) Prec@5 100.000 (99.282) +2022-11-14 16:16:37,195 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0742) Prec@1 83.000 (88.081) Prec@5 100.000 (99.291) +2022-11-14 16:16:37,209 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0740) Prec@1 90.000 (88.103) Prec@5 100.000 (99.299) +2022-11-14 16:16:37,225 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0741) Prec@1 89.000 (88.114) Prec@5 98.000 (99.284) +2022-11-14 16:16:37,241 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0741) Prec@1 85.000 (88.079) Prec@5 100.000 (99.292) +2022-11-14 16:16:37,253 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0742) Prec@1 88.000 (88.078) Prec@5 99.000 (99.289) +2022-11-14 16:16:37,266 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0740) Prec@1 89.000 (88.088) Prec@5 100.000 (99.297) +2022-11-14 16:16:37,282 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0739) Prec@1 91.000 (88.120) Prec@5 100.000 (99.304) +2022-11-14 16:16:37,295 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0740) Prec@1 87.000 (88.108) Prec@5 100.000 (99.312) +2022-11-14 16:16:37,310 Test: [93/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0739) Prec@1 90.000 (88.128) Prec@5 98.000 (99.298) +2022-11-14 16:16:37,322 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0740) Prec@1 86.000 (88.105) Prec@5 100.000 (99.305) +2022-11-14 16:16:37,338 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0740) Prec@1 88.000 (88.104) Prec@5 99.000 (99.302) +2022-11-14 16:16:37,353 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0738) Prec@1 92.000 (88.144) Prec@5 98.000 (99.289) +2022-11-14 16:16:37,366 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0741) Prec@1 84.000 (88.102) Prec@5 97.000 (99.265) +2022-11-14 16:16:37,379 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0744) Prec@1 85.000 (88.071) Prec@5 100.000 (99.273) +2022-11-14 16:16:37,392 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0744) Prec@1 90.000 (88.090) Prec@5 100.000 (99.280) +2022-11-14 16:16:37,456 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:16:37,820 Epoch: [324][0/500] Time 0.026 (0.026) Data 0.271 (0.271) Loss 0.0308 (0.0308) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:38,091 Epoch: [324][10/500] Time 0.026 (0.024) Data 0.002 (0.026) Loss 0.0445 (0.0377) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:38,365 Epoch: [324][20/500] Time 0.026 (0.024) Data 0.002 (0.015) Loss 0.0293 (0.0349) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:16:38,730 Epoch: [324][30/500] Time 0.035 (0.027) Data 0.002 (0.011) Loss 0.0348 (0.0349) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:16:39,134 Epoch: [324][40/500] Time 0.040 (0.029) Data 0.002 (0.009) Loss 0.0181 (0.0315) Prec@1 98.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:16:39,518 Epoch: [324][50/500] Time 0.038 (0.030) Data 0.002 (0.007) Loss 0.0443 (0.0336) Prec@1 91.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:16:39,908 Epoch: [324][60/500] Time 0.036 (0.031) Data 0.002 (0.006) Loss 0.0287 (0.0329) Prec@1 96.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 16:16:40,295 Epoch: [324][70/500] Time 0.032 (0.031) Data 0.002 (0.006) Loss 0.0182 (0.0311) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:16:40,682 Epoch: [324][80/500] Time 0.031 (0.032) Data 0.002 (0.005) Loss 0.0316 (0.0311) Prec@1 94.000 (94.889) Prec@5 99.000 (99.889) +2022-11-14 16:16:41,121 Epoch: [324][90/500] Time 0.053 (0.032) Data 0.002 (0.005) Loss 0.0337 (0.0314) Prec@1 94.000 (94.800) Prec@5 100.000 (99.900) +2022-11-14 16:16:41,921 Epoch: [324][100/500] Time 0.078 (0.036) Data 0.002 (0.005) Loss 0.0456 (0.0327) Prec@1 94.000 (94.727) Prec@5 100.000 (99.909) +2022-11-14 16:16:42,715 Epoch: [324][110/500] Time 0.072 (0.039) Data 0.002 (0.004) Loss 0.0353 (0.0329) Prec@1 93.000 (94.583) Prec@5 99.000 (99.833) +2022-11-14 16:16:43,476 Epoch: [324][120/500] Time 0.074 (0.041) Data 0.002 (0.004) Loss 0.0176 (0.0317) Prec@1 98.000 (94.846) Prec@5 100.000 (99.846) +2022-11-14 16:16:44,236 Epoch: [324][130/500] Time 0.077 (0.044) Data 0.002 (0.004) Loss 0.0333 (0.0318) Prec@1 94.000 (94.786) Prec@5 99.000 (99.786) +2022-11-14 16:16:45,003 Epoch: [324][140/500] Time 0.070 (0.045) Data 0.002 (0.004) Loss 0.0236 (0.0313) Prec@1 96.000 (94.867) Prec@5 99.000 (99.733) +2022-11-14 16:16:45,785 Epoch: [324][150/500] Time 0.074 (0.047) Data 0.002 (0.004) Loss 0.0248 (0.0309) Prec@1 96.000 (94.938) Prec@5 100.000 (99.750) +2022-11-14 16:16:46,597 Epoch: [324][160/500] Time 0.084 (0.049) Data 0.002 (0.004) Loss 0.0125 (0.0298) Prec@1 99.000 (95.176) Prec@5 100.000 (99.765) +2022-11-14 16:16:47,383 Epoch: [324][170/500] Time 0.075 (0.050) Data 0.002 (0.004) Loss 0.0289 (0.0298) Prec@1 95.000 (95.167) Prec@5 100.000 (99.778) +2022-11-14 16:16:48,181 Epoch: [324][180/500] Time 0.081 (0.051) Data 0.002 (0.004) Loss 0.0344 (0.0300) Prec@1 96.000 (95.211) Prec@5 100.000 (99.789) +2022-11-14 16:16:48,970 Epoch: [324][190/500] Time 0.084 (0.052) Data 0.002 (0.003) Loss 0.0231 (0.0297) Prec@1 96.000 (95.250) Prec@5 100.000 (99.800) +2022-11-14 16:16:49,776 Epoch: [324][200/500] Time 0.087 (0.053) Data 0.002 (0.003) Loss 0.0275 (0.0296) Prec@1 95.000 (95.238) Prec@5 100.000 (99.810) +2022-11-14 16:16:50,573 Epoch: [324][210/500] Time 0.083 (0.054) Data 0.002 (0.003) Loss 0.0379 (0.0299) Prec@1 94.000 (95.182) Prec@5 100.000 (99.818) +2022-11-14 16:16:51,314 Epoch: [324][220/500] Time 0.077 (0.055) Data 0.002 (0.003) Loss 0.0617 (0.0313) Prec@1 87.000 (94.826) Prec@5 100.000 (99.826) +2022-11-14 16:16:51,717 Epoch: [324][230/500] Time 0.029 (0.054) Data 0.002 (0.003) Loss 0.0471 (0.0320) Prec@1 93.000 (94.750) Prec@5 100.000 (99.833) +2022-11-14 16:16:52,118 Epoch: [324][240/500] Time 0.036 (0.053) Data 0.002 (0.003) Loss 0.0355 (0.0321) Prec@1 92.000 (94.640) Prec@5 100.000 (99.840) +2022-11-14 16:16:52,528 Epoch: [324][250/500] Time 0.041 (0.052) Data 0.002 (0.003) Loss 0.0327 (0.0321) Prec@1 94.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 16:16:52,936 Epoch: [324][260/500] Time 0.039 (0.052) Data 0.002 (0.003) Loss 0.0637 (0.0333) Prec@1 90.000 (94.444) Prec@5 100.000 (99.852) +2022-11-14 16:16:53,335 Epoch: [324][270/500] Time 0.031 (0.051) Data 0.002 (0.003) Loss 0.0486 (0.0339) Prec@1 93.000 (94.393) Prec@5 99.000 (99.821) +2022-11-14 16:16:53,737 Epoch: [324][280/500] Time 0.039 (0.051) Data 0.002 (0.003) Loss 0.0328 (0.0338) Prec@1 95.000 (94.414) Prec@5 99.000 (99.793) +2022-11-14 16:16:54,134 Epoch: [324][290/500] Time 0.039 (0.050) Data 0.002 (0.003) Loss 0.0278 (0.0336) Prec@1 95.000 (94.433) Prec@5 100.000 (99.800) +2022-11-14 16:16:54,538 Epoch: [324][300/500] Time 0.035 (0.050) Data 0.002 (0.003) Loss 0.0438 (0.0339) Prec@1 92.000 (94.355) Prec@5 100.000 (99.806) +2022-11-14 16:16:54,932 Epoch: [324][310/500] Time 0.038 (0.049) Data 0.002 (0.003) Loss 0.0365 (0.0340) Prec@1 92.000 (94.281) Prec@5 100.000 (99.812) +2022-11-14 16:16:55,339 Epoch: [324][320/500] Time 0.038 (0.049) Data 0.002 (0.003) Loss 0.0281 (0.0338) Prec@1 95.000 (94.303) Prec@5 100.000 (99.818) +2022-11-14 16:16:55,755 Epoch: [324][330/500] Time 0.037 (0.048) Data 0.003 (0.003) Loss 0.0362 (0.0339) Prec@1 95.000 (94.324) Prec@5 100.000 (99.824) +2022-11-14 16:16:56,149 Epoch: [324][340/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0513 (0.0344) Prec@1 90.000 (94.200) Prec@5 100.000 (99.829) +2022-11-14 16:16:56,552 Epoch: [324][350/500] Time 0.041 (0.048) Data 0.002 (0.003) Loss 0.0320 (0.0343) Prec@1 95.000 (94.222) Prec@5 100.000 (99.833) +2022-11-14 16:16:56,957 Epoch: [324][360/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0212 (0.0340) Prec@1 97.000 (94.297) Prec@5 100.000 (99.838) +2022-11-14 16:16:57,376 Epoch: [324][370/500] Time 0.039 (0.047) Data 0.002 (0.003) Loss 0.0393 (0.0341) Prec@1 93.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 16:16:57,783 Epoch: [324][380/500] Time 0.043 (0.047) Data 0.002 (0.003) Loss 0.0287 (0.0340) Prec@1 97.000 (94.333) Prec@5 99.000 (99.821) +2022-11-14 16:16:58,180 Epoch: [324][390/500] Time 0.036 (0.046) Data 0.002 (0.003) Loss 0.0314 (0.0339) Prec@1 94.000 (94.325) Prec@5 100.000 (99.825) +2022-11-14 16:16:58,587 Epoch: [324][400/500] Time 0.038 (0.046) Data 0.003 (0.003) Loss 0.0172 (0.0335) Prec@1 97.000 (94.390) Prec@5 100.000 (99.829) +2022-11-14 16:16:58,995 Epoch: [324][410/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0373 (0.0336) Prec@1 95.000 (94.405) Prec@5 100.000 (99.833) +2022-11-14 16:16:59,391 Epoch: [324][420/500] Time 0.037 (0.046) Data 0.002 (0.003) Loss 0.0172 (0.0332) Prec@1 98.000 (94.488) Prec@5 100.000 (99.837) +2022-11-14 16:16:59,802 Epoch: [324][430/500] Time 0.042 (0.046) Data 0.002 (0.003) Loss 0.0326 (0.0332) Prec@1 93.000 (94.455) Prec@5 100.000 (99.841) +2022-11-14 16:17:00,200 Epoch: [324][440/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0096 (0.0327) Prec@1 100.000 (94.578) Prec@5 100.000 (99.844) +2022-11-14 16:17:00,607 Epoch: [324][450/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0330 (0.0327) Prec@1 94.000 (94.565) Prec@5 100.000 (99.848) +2022-11-14 16:17:01,017 Epoch: [324][460/500] Time 0.036 (0.045) Data 0.002 (0.003) Loss 0.0472 (0.0330) Prec@1 92.000 (94.511) Prec@5 100.000 (99.851) +2022-11-14 16:17:01,424 Epoch: [324][470/500] Time 0.040 (0.045) Data 0.002 (0.003) Loss 0.0218 (0.0328) Prec@1 96.000 (94.542) Prec@5 100.000 (99.854) +2022-11-14 16:17:01,833 Epoch: [324][480/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0413 (0.0329) Prec@1 95.000 (94.551) Prec@5 100.000 (99.857) +2022-11-14 16:17:02,231 Epoch: [324][490/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0253 (0.0328) Prec@1 96.000 (94.580) Prec@5 100.000 (99.860) +2022-11-14 16:17:02,685 Epoch: [324][499/500] Time 0.078 (0.044) Data 0.002 (0.003) Loss 0.0505 (0.0331) Prec@1 91.000 (94.510) Prec@5 99.000 (99.843) +2022-11-14 16:17:03,033 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0532 (0.0532) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:03,042 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0650) Prec@1 89.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 16:17:03,051 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0665) Prec@1 91.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 16:17:03,066 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0671) Prec@1 88.000 (90.250) Prec@5 98.000 (99.250) +2022-11-14 16:17:03,077 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0712) Prec@1 86.000 (89.400) Prec@5 99.000 (99.200) +2022-11-14 16:17:03,093 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0688) Prec@1 91.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 16:17:03,116 Test: [6/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0662) Prec@1 93.000 (90.143) Prec@5 99.000 (99.286) +2022-11-14 16:17:03,148 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0693) Prec@1 85.000 (89.500) Prec@5 98.000 (99.125) +2022-11-14 16:17:03,182 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0675) Prec@1 92.000 (89.778) Prec@5 100.000 (99.222) +2022-11-14 16:17:03,211 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0695) Prec@1 85.000 (89.300) Prec@5 99.000 (99.200) +2022-11-14 16:17:03,243 Test: [10/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0631 (0.0690) Prec@1 91.000 (89.455) Prec@5 100.000 (99.273) +2022-11-14 16:17:03,278 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0699) Prec@1 85.000 (89.083) Prec@5 100.000 (99.333) +2022-11-14 16:17:03,314 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0689) Prec@1 91.000 (89.231) Prec@5 100.000 (99.385) +2022-11-14 16:17:03,349 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0684) Prec@1 90.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 16:17:03,381 Test: [14/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0697) Prec@1 87.000 (89.133) Prec@5 99.000 (99.400) +2022-11-14 16:17:03,410 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0698) Prec@1 89.000 (89.125) Prec@5 100.000 (99.438) +2022-11-14 16:17:03,440 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0394 (0.0680) Prec@1 94.000 (89.412) Prec@5 99.000 (99.412) +2022-11-14 16:17:03,472 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0918 (0.0694) Prec@1 85.000 (89.167) Prec@5 100.000 (99.444) +2022-11-14 16:17:03,505 Test: [18/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0970 (0.0708) Prec@1 84.000 (88.895) Prec@5 98.000 (99.368) +2022-11-14 16:17:03,540 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.0716) Prec@1 86.000 (88.750) Prec@5 99.000 (99.350) +2022-11-14 16:17:03,573 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0955 (0.0727) Prec@1 84.000 (88.524) Prec@5 100.000 (99.381) +2022-11-14 16:17:03,606 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0902 (0.0735) Prec@1 86.000 (88.409) Prec@5 98.000 (99.318) +2022-11-14 16:17:03,638 Test: [22/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0966 (0.0745) Prec@1 84.000 (88.217) Prec@5 98.000 (99.261) +2022-11-14 16:17:03,667 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0941 (0.0754) Prec@1 86.000 (88.125) Prec@5 100.000 (99.292) +2022-11-14 16:17:03,699 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1022 (0.0764) Prec@1 86.000 (88.040) Prec@5 99.000 (99.280) +2022-11-14 16:17:03,726 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0766) Prec@1 87.000 (88.000) Prec@5 100.000 (99.308) +2022-11-14 16:17:03,758 Test: [26/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0761) Prec@1 90.000 (88.074) Prec@5 100.000 (99.333) +2022-11-14 16:17:03,788 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0550 (0.0754) Prec@1 93.000 (88.250) Prec@5 100.000 (99.357) +2022-11-14 16:17:03,822 Test: [28/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0754) Prec@1 88.000 (88.241) Prec@5 97.000 (99.276) +2022-11-14 16:17:03,854 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0609 (0.0749) Prec@1 90.000 (88.300) Prec@5 100.000 (99.300) +2022-11-14 16:17:03,879 Test: [30/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0746) Prec@1 89.000 (88.323) Prec@5 100.000 (99.323) +2022-11-14 16:17:03,910 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0746) Prec@1 89.000 (88.344) Prec@5 99.000 (99.312) +2022-11-14 16:17:03,936 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0743) Prec@1 90.000 (88.394) Prec@5 100.000 (99.333) +2022-11-14 16:17:03,971 Test: [33/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1020 (0.0751) Prec@1 84.000 (88.265) Prec@5 98.000 (99.294) +2022-11-14 16:17:04,003 Test: [34/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0751) Prec@1 87.000 (88.229) Prec@5 97.000 (99.229) +2022-11-14 16:17:04,033 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0612 (0.0747) Prec@1 90.000 (88.278) Prec@5 100.000 (99.250) +2022-11-14 16:17:04,068 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0746) Prec@1 90.000 (88.324) Prec@5 99.000 (99.243) +2022-11-14 16:17:04,097 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0749) Prec@1 86.000 (88.263) Prec@5 98.000 (99.211) +2022-11-14 16:17:04,130 Test: [38/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0595 (0.0746) Prec@1 90.000 (88.308) Prec@5 99.000 (99.205) +2022-11-14 16:17:04,166 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0745) Prec@1 91.000 (88.375) Prec@5 99.000 (99.200) +2022-11-14 16:17:04,201 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.0750) Prec@1 85.000 (88.293) Prec@5 97.000 (99.146) +2022-11-14 16:17:04,233 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0747) Prec@1 90.000 (88.333) Prec@5 99.000 (99.143) +2022-11-14 16:17:04,264 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0634 (0.0744) Prec@1 87.000 (88.302) Prec@5 99.000 (99.140) +2022-11-14 16:17:04,298 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0742) Prec@1 89.000 (88.318) Prec@5 99.000 (99.136) +2022-11-14 16:17:04,332 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0577 (0.0738) Prec@1 91.000 (88.378) Prec@5 99.000 (99.133) +2022-11-14 16:17:04,366 Test: [45/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0998 (0.0744) Prec@1 84.000 (88.283) Prec@5 99.000 (99.130) +2022-11-14 16:17:04,398 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0686 (0.0743) Prec@1 88.000 (88.277) Prec@5 100.000 (99.149) +2022-11-14 16:17:04,428 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1060 (0.0749) Prec@1 82.000 (88.146) Prec@5 97.000 (99.104) +2022-11-14 16:17:04,459 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0747) Prec@1 89.000 (88.163) Prec@5 100.000 (99.122) +2022-11-14 16:17:04,491 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1094 (0.0754) Prec@1 83.000 (88.060) Prec@5 100.000 (99.140) +2022-11-14 16:17:04,527 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0750) Prec@1 90.000 (88.098) Prec@5 100.000 (99.157) +2022-11-14 16:17:04,551 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0795 (0.0751) Prec@1 86.000 (88.058) Prec@5 99.000 (99.154) +2022-11-14 16:17:04,583 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0903 (0.0754) Prec@1 84.000 (87.981) Prec@5 99.000 (99.151) +2022-11-14 16:17:04,618 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0751) Prec@1 90.000 (88.019) Prec@5 99.000 (99.148) +2022-11-14 16:17:04,652 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0975 (0.0755) Prec@1 85.000 (87.964) Prec@5 100.000 (99.164) +2022-11-14 16:17:04,686 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0842 (0.0757) Prec@1 86.000 (87.929) Prec@5 98.000 (99.143) +2022-11-14 16:17:04,722 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0756) Prec@1 89.000 (87.947) Prec@5 99.000 (99.140) +2022-11-14 16:17:04,759 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0755) Prec@1 90.000 (87.983) Prec@5 100.000 (99.155) +2022-11-14 16:17:04,791 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0754) Prec@1 90.000 (88.017) Prec@5 100.000 (99.169) +2022-11-14 16:17:04,826 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0755) Prec@1 86.000 (87.983) Prec@5 99.000 (99.167) +2022-11-14 16:17:04,860 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0755) Prec@1 89.000 (88.000) Prec@5 100.000 (99.180) +2022-11-14 16:17:04,894 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 88.000 (88.000) Prec@5 99.000 (99.177) +2022-11-14 16:17:04,930 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0511 (0.0750) Prec@1 92.000 (88.063) Prec@5 100.000 (99.190) +2022-11-14 16:17:04,956 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0329 (0.0743) Prec@1 95.000 (88.172) Prec@5 100.000 (99.203) +2022-11-14 16:17:04,986 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0896 (0.0746) Prec@1 85.000 (88.123) Prec@5 99.000 (99.200) +2022-11-14 16:17:05,018 Test: [65/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0746) Prec@1 89.000 (88.136) Prec@5 100.000 (99.212) +2022-11-14 16:17:05,044 Test: [66/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0334 (0.0740) Prec@1 95.000 (88.239) Prec@5 99.000 (99.209) +2022-11-14 16:17:05,073 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0474 (0.0736) Prec@1 92.000 (88.294) Prec@5 100.000 (99.221) +2022-11-14 16:17:05,108 Test: [68/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0735) Prec@1 88.000 (88.290) Prec@5 99.000 (99.217) +2022-11-14 16:17:05,143 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0736) Prec@1 86.000 (88.257) Prec@5 100.000 (99.229) +2022-11-14 16:17:05,174 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0961 (0.0740) Prec@1 86.000 (88.225) Prec@5 99.000 (99.225) +2022-11-14 16:17:05,201 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0613 (0.0738) Prec@1 92.000 (88.278) Prec@5 100.000 (99.236) +2022-11-14 16:17:05,236 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0736) Prec@1 90.000 (88.301) Prec@5 100.000 (99.247) +2022-11-14 16:17:05,267 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0400 (0.0732) Prec@1 93.000 (88.365) Prec@5 100.000 (99.257) +2022-11-14 16:17:05,295 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0734) Prec@1 86.000 (88.333) Prec@5 99.000 (99.253) +2022-11-14 16:17:05,329 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0471 (0.0730) Prec@1 93.000 (88.395) Prec@5 99.000 (99.250) +2022-11-14 16:17:05,355 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0731) Prec@1 90.000 (88.416) Prec@5 100.000 (99.260) +2022-11-14 16:17:05,389 Test: [77/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0961 (0.0733) Prec@1 84.000 (88.359) Prec@5 98.000 (99.244) +2022-11-14 16:17:05,424 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0735) Prec@1 85.000 (88.316) Prec@5 99.000 (99.241) +2022-11-14 16:17:05,460 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0735) Prec@1 86.000 (88.287) Prec@5 100.000 (99.250) +2022-11-14 16:17:05,495 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0736) Prec@1 86.000 (88.259) Prec@5 98.000 (99.235) +2022-11-14 16:17:05,534 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0736) Prec@1 89.000 (88.268) Prec@5 99.000 (99.232) +2022-11-14 16:17:05,569 Test: [82/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0738) Prec@1 87.000 (88.253) Prec@5 99.000 (99.229) +2022-11-14 16:17:05,595 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0942 (0.0740) Prec@1 84.000 (88.202) Prec@5 99.000 (99.226) +2022-11-14 16:17:05,627 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0757 (0.0740) Prec@1 88.000 (88.200) Prec@5 100.000 (99.235) +2022-11-14 16:17:05,660 Test: [85/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1059 (0.0744) Prec@1 83.000 (88.140) Prec@5 99.000 (99.233) +2022-11-14 16:17:05,693 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0744) Prec@1 90.000 (88.161) Prec@5 100.000 (99.241) +2022-11-14 16:17:05,727 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0745) Prec@1 85.000 (88.125) Prec@5 97.000 (99.216) +2022-11-14 16:17:05,757 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0744) Prec@1 87.000 (88.112) Prec@5 100.000 (99.225) +2022-11-14 16:17:05,791 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0743) Prec@1 86.000 (88.089) Prec@5 100.000 (99.233) +2022-11-14 16:17:05,826 Test: [90/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0743) Prec@1 89.000 (88.099) Prec@5 100.000 (99.242) +2022-11-14 16:17:05,860 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0428 (0.0740) Prec@1 93.000 (88.152) Prec@5 100.000 (99.250) +2022-11-14 16:17:05,890 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0741) Prec@1 87.000 (88.140) Prec@5 99.000 (99.247) +2022-11-14 16:17:05,919 Test: [93/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0740) Prec@1 89.000 (88.149) Prec@5 98.000 (99.234) +2022-11-14 16:17:05,952 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0742) Prec@1 87.000 (88.137) Prec@5 100.000 (99.242) +2022-11-14 16:17:05,986 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0742) Prec@1 90.000 (88.156) Prec@5 98.000 (99.229) +2022-11-14 16:17:06,020 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0741) Prec@1 90.000 (88.175) Prec@5 99.000 (99.227) +2022-11-14 16:17:06,052 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.0742) Prec@1 85.000 (88.143) Prec@5 98.000 (99.214) +2022-11-14 16:17:06,083 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0919 (0.0744) Prec@1 84.000 (88.101) Prec@5 99.000 (99.212) +2022-11-14 16:17:06,121 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0742) Prec@1 91.000 (88.130) Prec@5 100.000 (99.220) +2022-11-14 16:17:06,212 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:17:06,662 Epoch: [325][0/500] Time 0.037 (0.037) Data 0.342 (0.342) Loss 0.0552 (0.0552) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:06,948 Epoch: [325][10/500] Time 0.025 (0.027) Data 0.003 (0.033) Loss 0.0309 (0.0431) Prec@1 95.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:07,249 Epoch: [325][20/500] Time 0.026 (0.027) Data 0.002 (0.018) Loss 0.0259 (0.0373) Prec@1 95.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:07,667 Epoch: [325][30/500] Time 0.066 (0.029) Data 0.002 (0.013) Loss 0.0281 (0.0350) Prec@1 97.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:08,400 Epoch: [325][40/500] Time 0.071 (0.038) Data 0.003 (0.011) Loss 0.0292 (0.0339) Prec@1 96.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:17:09,093 Epoch: [325][50/500] Time 0.059 (0.043) Data 0.002 (0.009) Loss 0.0287 (0.0330) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:17:09,779 Epoch: [325][60/500] Time 0.071 (0.046) Data 0.002 (0.008) Loss 0.0520 (0.0357) Prec@1 92.000 (94.286) Prec@5 100.000 (100.000) +2022-11-14 16:17:10,503 Epoch: [325][70/500] Time 0.074 (0.048) Data 0.003 (0.007) Loss 0.0354 (0.0357) Prec@1 93.000 (94.125) Prec@5 100.000 (100.000) +2022-11-14 16:17:11,182 Epoch: [325][80/500] Time 0.066 (0.050) Data 0.002 (0.007) Loss 0.0471 (0.0369) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:11,889 Epoch: [325][90/500] Time 0.074 (0.051) Data 0.002 (0.006) Loss 0.0195 (0.0352) Prec@1 98.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:17:12,613 Epoch: [325][100/500] Time 0.059 (0.053) Data 0.002 (0.006) Loss 0.0369 (0.0354) Prec@1 94.000 (94.364) Prec@5 100.000 (100.000) +2022-11-14 16:17:13,295 Epoch: [325][110/500] Time 0.053 (0.053) Data 0.002 (0.005) Loss 0.0441 (0.0361) Prec@1 93.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 16:17:13,979 Epoch: [325][120/500] Time 0.064 (0.054) Data 0.003 (0.005) Loss 0.0277 (0.0354) Prec@1 97.000 (94.462) Prec@5 100.000 (100.000) +2022-11-14 16:17:14,706 Epoch: [325][130/500] Time 0.063 (0.055) Data 0.003 (0.005) Loss 0.0394 (0.0357) Prec@1 93.000 (94.357) Prec@5 100.000 (100.000) +2022-11-14 16:17:15,384 Epoch: [325][140/500] Time 0.073 (0.055) Data 0.002 (0.005) Loss 0.0463 (0.0364) Prec@1 93.000 (94.267) Prec@5 99.000 (99.933) +2022-11-14 16:17:16,113 Epoch: [325][150/500] Time 0.075 (0.056) Data 0.003 (0.005) Loss 0.0291 (0.0360) Prec@1 94.000 (94.250) Prec@5 100.000 (99.938) +2022-11-14 16:17:16,849 Epoch: [325][160/500] Time 0.067 (0.056) Data 0.002 (0.004) Loss 0.0461 (0.0366) Prec@1 91.000 (94.059) Prec@5 100.000 (99.941) +2022-11-14 16:17:17,533 Epoch: [325][170/500] Time 0.067 (0.057) Data 0.002 (0.004) Loss 0.0173 (0.0355) Prec@1 98.000 (94.278) Prec@5 99.000 (99.889) +2022-11-14 16:17:18,206 Epoch: [325][180/500] Time 0.059 (0.057) Data 0.002 (0.004) Loss 0.0271 (0.0350) Prec@1 96.000 (94.368) Prec@5 100.000 (99.895) +2022-11-14 16:17:18,908 Epoch: [325][190/500] Time 0.073 (0.057) Data 0.002 (0.004) Loss 0.0482 (0.0357) Prec@1 90.000 (94.150) Prec@5 100.000 (99.900) +2022-11-14 16:17:19,669 Epoch: [325][200/500] Time 0.071 (0.058) Data 0.002 (0.004) Loss 0.0411 (0.0360) Prec@1 92.000 (94.048) Prec@5 100.000 (99.905) +2022-11-14 16:17:20,361 Epoch: [325][210/500] Time 0.061 (0.058) Data 0.002 (0.004) Loss 0.0457 (0.0364) Prec@1 93.000 (94.000) Prec@5 100.000 (99.909) +2022-11-14 16:17:21,115 Epoch: [325][220/500] Time 0.059 (0.058) Data 0.002 (0.004) Loss 0.0221 (0.0358) Prec@1 96.000 (94.087) Prec@5 99.000 (99.870) +2022-11-14 16:17:21,846 Epoch: [325][230/500] Time 0.086 (0.059) Data 0.002 (0.004) Loss 0.0431 (0.0361) Prec@1 92.000 (94.000) Prec@5 99.000 (99.833) +2022-11-14 16:17:22,531 Epoch: [325][240/500] Time 0.071 (0.059) Data 0.002 (0.004) Loss 0.0508 (0.0367) Prec@1 92.000 (93.920) Prec@5 100.000 (99.840) +2022-11-14 16:17:23,279 Epoch: [325][250/500] Time 0.072 (0.059) Data 0.002 (0.004) Loss 0.0296 (0.0364) Prec@1 95.000 (93.962) Prec@5 100.000 (99.846) +2022-11-14 16:17:23,969 Epoch: [325][260/500] Time 0.063 (0.059) Data 0.002 (0.004) Loss 0.0318 (0.0362) Prec@1 94.000 (93.963) Prec@5 100.000 (99.852) +2022-11-14 16:17:24,764 Epoch: [325][270/500] Time 0.083 (0.060) Data 0.003 (0.003) Loss 0.0366 (0.0362) Prec@1 94.000 (93.964) Prec@5 100.000 (99.857) +2022-11-14 16:17:25,479 Epoch: [325][280/500] Time 0.063 (0.060) Data 0.002 (0.003) Loss 0.0313 (0.0361) Prec@1 95.000 (94.000) Prec@5 100.000 (99.862) +2022-11-14 16:17:26,155 Epoch: [325][290/500] Time 0.061 (0.060) Data 0.002 (0.003) Loss 0.0291 (0.0358) Prec@1 95.000 (94.033) Prec@5 100.000 (99.867) +2022-11-14 16:17:26,847 Epoch: [325][300/500] Time 0.071 (0.060) Data 0.002 (0.003) Loss 0.0182 (0.0353) Prec@1 98.000 (94.161) Prec@5 100.000 (99.871) +2022-11-14 16:17:27,519 Epoch: [325][310/500] Time 0.063 (0.060) Data 0.002 (0.003) Loss 0.0359 (0.0353) Prec@1 95.000 (94.188) Prec@5 100.000 (99.875) +2022-11-14 16:17:28,196 Epoch: [325][320/500] Time 0.077 (0.060) Data 0.002 (0.003) Loss 0.0405 (0.0354) Prec@1 93.000 (94.152) Prec@5 100.000 (99.879) +2022-11-14 16:17:28,872 Epoch: [325][330/500] Time 0.071 (0.060) Data 0.002 (0.003) Loss 0.0301 (0.0353) Prec@1 95.000 (94.176) Prec@5 100.000 (99.882) +2022-11-14 16:17:29,550 Epoch: [325][340/500] Time 0.063 (0.060) Data 0.002 (0.003) Loss 0.0305 (0.0352) Prec@1 94.000 (94.171) Prec@5 100.000 (99.886) +2022-11-14 16:17:30,246 Epoch: [325][350/500] Time 0.071 (0.060) Data 0.002 (0.003) Loss 0.0260 (0.0349) Prec@1 95.000 (94.194) Prec@5 100.000 (99.889) +2022-11-14 16:17:30,988 Epoch: [325][360/500] Time 0.065 (0.060) Data 0.002 (0.003) Loss 0.0421 (0.0351) Prec@1 94.000 (94.189) Prec@5 100.000 (99.892) +2022-11-14 16:17:31,639 Epoch: [325][370/500] Time 0.063 (0.060) Data 0.002 (0.003) Loss 0.0162 (0.0346) Prec@1 98.000 (94.289) Prec@5 100.000 (99.895) +2022-11-14 16:17:32,010 Epoch: [325][380/500] Time 0.032 (0.059) Data 0.002 (0.003) Loss 0.0259 (0.0344) Prec@1 97.000 (94.359) Prec@5 100.000 (99.897) +2022-11-14 16:17:32,352 Epoch: [325][390/500] Time 0.036 (0.059) Data 0.002 (0.003) Loss 0.0196 (0.0340) Prec@1 97.000 (94.425) Prec@5 100.000 (99.900) +2022-11-14 16:17:32,704 Epoch: [325][400/500] Time 0.034 (0.058) Data 0.002 (0.003) Loss 0.0299 (0.0339) Prec@1 95.000 (94.439) Prec@5 99.000 (99.878) +2022-11-14 16:17:33,056 Epoch: [325][410/500] Time 0.037 (0.057) Data 0.002 (0.003) Loss 0.0416 (0.0341) Prec@1 92.000 (94.381) Prec@5 100.000 (99.881) +2022-11-14 16:17:33,404 Epoch: [325][420/500] Time 0.032 (0.057) Data 0.002 (0.003) Loss 0.0384 (0.0342) Prec@1 93.000 (94.349) Prec@5 100.000 (99.884) +2022-11-14 16:17:33,767 Epoch: [325][430/500] Time 0.035 (0.056) Data 0.002 (0.003) Loss 0.0329 (0.0342) Prec@1 93.000 (94.318) Prec@5 100.000 (99.886) +2022-11-14 16:17:34,110 Epoch: [325][440/500] Time 0.029 (0.056) Data 0.002 (0.003) Loss 0.0477 (0.0345) Prec@1 91.000 (94.244) Prec@5 99.000 (99.867) +2022-11-14 16:17:34,462 Epoch: [325][450/500] Time 0.035 (0.055) Data 0.002 (0.003) Loss 0.0409 (0.0346) Prec@1 95.000 (94.261) Prec@5 99.000 (99.848) +2022-11-14 16:17:34,826 Epoch: [325][460/500] Time 0.038 (0.055) Data 0.002 (0.003) Loss 0.0373 (0.0347) Prec@1 96.000 (94.298) Prec@5 99.000 (99.830) +2022-11-14 16:17:35,178 Epoch: [325][470/500] Time 0.032 (0.054) Data 0.002 (0.003) Loss 0.0263 (0.0345) Prec@1 96.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:17:35,531 Epoch: [325][480/500] Time 0.034 (0.054) Data 0.002 (0.003) Loss 0.0153 (0.0341) Prec@1 97.000 (94.388) Prec@5 100.000 (99.837) +2022-11-14 16:17:35,891 Epoch: [325][490/500] Time 0.028 (0.053) Data 0.002 (0.003) Loss 0.0536 (0.0345) Prec@1 90.000 (94.300) Prec@5 100.000 (99.840) +2022-11-14 16:17:36,217 Epoch: [325][499/500] Time 0.036 (0.053) Data 0.002 (0.003) Loss 0.0511 (0.0348) Prec@1 90.000 (94.216) Prec@5 100.000 (99.843) +2022-11-14 16:17:36,538 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0796 (0.0796) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,549 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0743) Prec@1 90.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,558 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0699) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,570 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0658) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,580 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0662) Prec@1 89.000 (88.600) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,590 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0409 (0.0619) Prec@1 93.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,600 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0616) Prec@1 92.000 (89.714) Prec@5 100.000 (100.000) +2022-11-14 16:17:36,612 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0660) Prec@1 86.000 (89.250) Prec@5 99.000 (99.875) +2022-11-14 16:17:36,621 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0665) Prec@1 90.000 (89.333) Prec@5 100.000 (99.889) +2022-11-14 16:17:36,631 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0693) Prec@1 87.000 (89.100) Prec@5 99.000 (99.800) +2022-11-14 16:17:36,640 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0685) Prec@1 90.000 (89.182) Prec@5 100.000 (99.818) +2022-11-14 16:17:36,650 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0694) Prec@1 87.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:17:36,660 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0699) Prec@1 85.000 (88.692) Prec@5 100.000 (99.769) +2022-11-14 16:17:36,670 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0698) Prec@1 89.000 (88.714) Prec@5 97.000 (99.571) +2022-11-14 16:17:36,679 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0719) Prec@1 85.000 (88.467) Prec@5 100.000 (99.600) +2022-11-14 16:17:36,689 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0714) Prec@1 90.000 (88.562) Prec@5 100.000 (99.625) +2022-11-14 16:17:36,701 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0703) Prec@1 93.000 (88.824) Prec@5 99.000 (99.588) +2022-11-14 16:17:36,710 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0716) Prec@1 85.000 (88.611) Prec@5 100.000 (99.611) +2022-11-14 16:17:36,720 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0719) Prec@1 87.000 (88.526) Prec@5 97.000 (99.474) +2022-11-14 16:17:36,729 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0734) Prec@1 84.000 (88.300) Prec@5 98.000 (99.400) +2022-11-14 16:17:36,740 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0729) Prec@1 88.000 (88.286) Prec@5 100.000 (99.429) +2022-11-14 16:17:36,750 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0896 (0.0736) Prec@1 87.000 (88.227) Prec@5 98.000 (99.364) +2022-11-14 16:17:36,761 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0747) Prec@1 82.000 (87.957) Prec@5 99.000 (99.348) +2022-11-14 16:17:36,771 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0744) Prec@1 89.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 16:17:36,781 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0749) Prec@1 89.000 (88.040) Prec@5 100.000 (99.400) +2022-11-14 16:17:36,791 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0979 (0.0758) Prec@1 84.000 (87.885) Prec@5 98.000 (99.346) +2022-11-14 16:17:36,802 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0750) Prec@1 92.000 (88.037) Prec@5 100.000 (99.370) +2022-11-14 16:17:36,812 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0748) Prec@1 88.000 (88.036) Prec@5 99.000 (99.357) +2022-11-14 16:17:36,825 Test: [28/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0748) Prec@1 89.000 (88.069) Prec@5 100.000 (99.379) +2022-11-14 16:17:36,837 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0750) Prec@1 87.000 (88.033) Prec@5 99.000 (99.367) +2022-11-14 16:17:36,846 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0749) Prec@1 84.000 (87.903) Prec@5 100.000 (99.387) +2022-11-14 16:17:36,856 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0753) Prec@1 87.000 (87.875) Prec@5 99.000 (99.375) +2022-11-14 16:17:36,868 Test: [32/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0970 (0.0759) Prec@1 84.000 (87.758) Prec@5 99.000 (99.364) +2022-11-14 16:17:36,879 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0762) Prec@1 85.000 (87.676) Prec@5 100.000 (99.382) +2022-11-14 16:17:36,889 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0762) Prec@1 90.000 (87.743) Prec@5 99.000 (99.371) +2022-11-14 16:17:36,900 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0759) Prec@1 90.000 (87.806) Prec@5 100.000 (99.389) +2022-11-14 16:17:36,909 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0755) Prec@1 88.000 (87.811) Prec@5 99.000 (99.378) +2022-11-14 16:17:36,920 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0761) Prec@1 84.000 (87.711) Prec@5 99.000 (99.368) +2022-11-14 16:17:36,929 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0757) Prec@1 91.000 (87.795) Prec@5 99.000 (99.359) +2022-11-14 16:17:36,941 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0759) Prec@1 86.000 (87.750) Prec@5 99.000 (99.350) +2022-11-14 16:17:36,952 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0767) Prec@1 83.000 (87.634) Prec@5 98.000 (99.317) +2022-11-14 16:17:36,963 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0764) Prec@1 90.000 (87.690) Prec@5 100.000 (99.333) +2022-11-14 16:17:36,973 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0313 (0.0753) Prec@1 95.000 (87.860) Prec@5 100.000 (99.349) +2022-11-14 16:17:36,984 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0752) Prec@1 90.000 (87.909) Prec@5 97.000 (99.295) +2022-11-14 16:17:36,993 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0752) Prec@1 89.000 (87.933) Prec@5 100.000 (99.311) +2022-11-14 16:17:37,002 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0757) Prec@1 84.000 (87.848) Prec@5 100.000 (99.326) +2022-11-14 16:17:37,011 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0758) Prec@1 88.000 (87.851) Prec@5 100.000 (99.340) +2022-11-14 16:17:37,024 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0760) Prec@1 87.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 16:17:37,035 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0755) Prec@1 90.000 (87.878) Prec@5 100.000 (99.347) +2022-11-14 16:17:37,045 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0758) Prec@1 87.000 (87.860) Prec@5 99.000 (99.340) +2022-11-14 16:17:37,055 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0756) Prec@1 89.000 (87.882) Prec@5 100.000 (99.353) +2022-11-14 16:17:37,066 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0757) Prec@1 86.000 (87.846) Prec@5 99.000 (99.346) +2022-11-14 16:17:37,076 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0758) Prec@1 85.000 (87.792) Prec@5 100.000 (99.358) +2022-11-14 16:17:37,088 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0759) Prec@1 86.000 (87.759) Prec@5 99.000 (99.352) +2022-11-14 16:17:37,098 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0762) Prec@1 85.000 (87.709) Prec@5 100.000 (99.364) +2022-11-14 16:17:37,108 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0763) Prec@1 87.000 (87.696) Prec@5 99.000 (99.357) +2022-11-14 16:17:37,118 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0762) Prec@1 88.000 (87.702) Prec@5 99.000 (99.351) +2022-11-14 16:17:37,130 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0761) Prec@1 87.000 (87.690) Prec@5 100.000 (99.362) +2022-11-14 16:17:37,142 Test: [58/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0762) Prec@1 89.000 (87.712) Prec@5 98.000 (99.339) +2022-11-14 16:17:37,153 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0760) Prec@1 87.000 (87.700) Prec@5 99.000 (99.333) +2022-11-14 16:17:37,166 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0760) Prec@1 88.000 (87.705) Prec@5 100.000 (99.344) +2022-11-14 16:17:37,180 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0611 (0.0758) Prec@1 88.000 (87.710) Prec@5 100.000 (99.355) +2022-11-14 16:17:37,194 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0757) Prec@1 88.000 (87.714) Prec@5 100.000 (99.365) +2022-11-14 16:17:37,209 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0366 (0.0751) Prec@1 93.000 (87.797) Prec@5 100.000 (99.375) +2022-11-14 16:17:37,223 Test: [64/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0753) Prec@1 85.000 (87.754) Prec@5 100.000 (99.385) +2022-11-14 16:17:37,239 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0754) Prec@1 89.000 (87.773) Prec@5 100.000 (99.394) +2022-11-14 16:17:37,254 Test: [66/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0750) Prec@1 92.000 (87.836) Prec@5 100.000 (99.403) +2022-11-14 16:17:37,269 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0751) Prec@1 89.000 (87.853) Prec@5 98.000 (99.382) +2022-11-14 16:17:37,286 Test: [68/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0749) Prec@1 88.000 (87.855) Prec@5 99.000 (99.377) +2022-11-14 16:17:37,305 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0748) Prec@1 90.000 (87.886) Prec@5 99.000 (99.371) +2022-11-14 16:17:37,322 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0753) Prec@1 84.000 (87.831) Prec@5 100.000 (99.380) +2022-11-14 16:17:37,339 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0752) Prec@1 89.000 (87.847) Prec@5 98.000 (99.361) +2022-11-14 16:17:37,358 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0749) Prec@1 90.000 (87.877) Prec@5 99.000 (99.356) +2022-11-14 16:17:37,374 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0749) Prec@1 87.000 (87.865) Prec@5 100.000 (99.365) +2022-11-14 16:17:37,392 Test: [74/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0753) Prec@1 84.000 (87.813) Prec@5 99.000 (99.360) +2022-11-14 16:17:37,408 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0754) Prec@1 85.000 (87.776) Prec@5 100.000 (99.368) +2022-11-14 16:17:37,425 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0755) Prec@1 87.000 (87.766) Prec@5 98.000 (99.351) +2022-11-14 16:17:37,445 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0756) Prec@1 86.000 (87.744) Prec@5 99.000 (99.346) +2022-11-14 16:17:37,462 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0755) Prec@1 90.000 (87.772) Prec@5 100.000 (99.354) +2022-11-14 16:17:37,477 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0756) Prec@1 86.000 (87.750) Prec@5 100.000 (99.362) +2022-11-14 16:17:37,494 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0758) Prec@1 83.000 (87.691) Prec@5 99.000 (99.358) +2022-11-14 16:17:37,512 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0759) Prec@1 85.000 (87.659) Prec@5 100.000 (99.366) +2022-11-14 16:17:37,529 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0763) Prec@1 82.000 (87.590) Prec@5 99.000 (99.361) +2022-11-14 16:17:37,547 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0512 (0.0760) Prec@1 90.000 (87.619) Prec@5 100.000 (99.369) +2022-11-14 16:17:37,562 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0763) Prec@1 82.000 (87.553) Prec@5 98.000 (99.353) +2022-11-14 16:17:37,579 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0764) Prec@1 87.000 (87.547) Prec@5 100.000 (99.360) +2022-11-14 16:17:37,597 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0761) Prec@1 92.000 (87.598) Prec@5 99.000 (99.356) +2022-11-14 16:17:37,615 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0759) Prec@1 90.000 (87.625) Prec@5 99.000 (99.352) +2022-11-14 16:17:37,634 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0758) Prec@1 89.000 (87.640) Prec@5 100.000 (99.360) +2022-11-14 16:17:37,655 Test: [89/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0757) Prec@1 88.000 (87.644) Prec@5 99.000 (99.356) +2022-11-14 16:17:37,674 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0757) Prec@1 89.000 (87.659) Prec@5 99.000 (99.352) +2022-11-14 16:17:37,693 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0755) Prec@1 90.000 (87.685) Prec@5 100.000 (99.359) +2022-11-14 16:17:37,709 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.0757) Prec@1 86.000 (87.667) Prec@5 100.000 (99.366) +2022-11-14 16:17:37,725 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0757) Prec@1 88.000 (87.670) Prec@5 100.000 (99.372) +2022-11-14 16:17:37,745 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0757) Prec@1 84.000 (87.632) Prec@5 100.000 (99.379) +2022-11-14 16:17:37,765 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0755) Prec@1 91.000 (87.667) Prec@5 99.000 (99.375) +2022-11-14 16:17:37,784 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0753) Prec@1 91.000 (87.701) Prec@5 99.000 (99.371) +2022-11-14 16:17:37,801 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0755) Prec@1 88.000 (87.704) Prec@5 99.000 (99.367) +2022-11-14 16:17:37,819 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0756) Prec@1 85.000 (87.677) Prec@5 100.000 (99.374) +2022-11-14 16:17:37,837 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0754) Prec@1 93.000 (87.730) Prec@5 100.000 (99.380) +2022-11-14 16:17:37,900 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:17:38,253 Epoch: [326][0/500] Time 0.026 (0.026) Data 0.263 (0.263) Loss 0.0626 (0.0626) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:17:38,697 Epoch: [326][10/500] Time 0.049 (0.039) Data 0.002 (0.026) Loss 0.0357 (0.0491) Prec@1 95.000 (92.500) Prec@5 99.000 (99.000) +2022-11-14 16:17:39,206 Epoch: [326][20/500] Time 0.049 (0.042) Data 0.002 (0.014) Loss 0.0303 (0.0429) Prec@1 93.000 (92.667) Prec@5 100.000 (99.333) +2022-11-14 16:17:39,698 Epoch: [326][30/500] Time 0.050 (0.043) Data 0.002 (0.010) Loss 0.0323 (0.0402) Prec@1 95.000 (93.250) Prec@5 100.000 (99.500) +2022-11-14 16:17:40,211 Epoch: [326][40/500] Time 0.041 (0.043) Data 0.002 (0.008) Loss 0.0515 (0.0425) Prec@1 91.000 (92.800) Prec@5 100.000 (99.600) +2022-11-14 16:17:40,716 Epoch: [326][50/500] Time 0.040 (0.044) Data 0.002 (0.007) Loss 0.0192 (0.0386) Prec@1 97.000 (93.500) Prec@5 100.000 (99.667) +2022-11-14 16:17:41,226 Epoch: [326][60/500] Time 0.050 (0.044) Data 0.002 (0.006) Loss 0.0249 (0.0366) Prec@1 97.000 (94.000) Prec@5 100.000 (99.714) +2022-11-14 16:17:41,738 Epoch: [326][70/500] Time 0.046 (0.044) Data 0.002 (0.006) Loss 0.0610 (0.0397) Prec@1 89.000 (93.375) Prec@5 100.000 (99.750) +2022-11-14 16:17:42,229 Epoch: [326][80/500] Time 0.049 (0.044) Data 0.002 (0.005) Loss 0.0403 (0.0398) Prec@1 93.000 (93.333) Prec@5 100.000 (99.778) +2022-11-14 16:17:42,733 Epoch: [326][90/500] Time 0.044 (0.044) Data 0.002 (0.005) Loss 0.0329 (0.0391) Prec@1 95.000 (93.500) Prec@5 100.000 (99.800) +2022-11-14 16:17:43,236 Epoch: [326][100/500] Time 0.051 (0.044) Data 0.002 (0.005) Loss 0.0243 (0.0377) Prec@1 95.000 (93.636) Prec@5 100.000 (99.818) +2022-11-14 16:17:43,752 Epoch: [326][110/500] Time 0.049 (0.044) Data 0.002 (0.004) Loss 0.0153 (0.0359) Prec@1 98.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 16:17:44,271 Epoch: [326][120/500] Time 0.036 (0.044) Data 0.002 (0.004) Loss 0.0319 (0.0355) Prec@1 95.000 (94.077) Prec@5 100.000 (99.846) +2022-11-14 16:17:44,780 Epoch: [326][130/500] Time 0.032 (0.044) Data 0.002 (0.004) Loss 0.0392 (0.0358) Prec@1 93.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 16:17:45,280 Epoch: [326][140/500] Time 0.045 (0.044) Data 0.002 (0.004) Loss 0.0215 (0.0349) Prec@1 97.000 (94.200) Prec@5 100.000 (99.867) +2022-11-14 16:17:45,793 Epoch: [326][150/500] Time 0.052 (0.045) Data 0.002 (0.004) Loss 0.0228 (0.0341) Prec@1 98.000 (94.438) Prec@5 99.000 (99.812) +2022-11-14 16:17:46,303 Epoch: [326][160/500] Time 0.048 (0.045) Data 0.002 (0.004) Loss 0.0446 (0.0347) Prec@1 93.000 (94.353) Prec@5 98.000 (99.706) +2022-11-14 16:17:46,794 Epoch: [326][170/500] Time 0.046 (0.045) Data 0.002 (0.004) Loss 0.0362 (0.0348) Prec@1 94.000 (94.333) Prec@5 100.000 (99.722) +2022-11-14 16:17:47,310 Epoch: [326][180/500] Time 0.048 (0.045) Data 0.002 (0.004) Loss 0.0210 (0.0341) Prec@1 97.000 (94.474) Prec@5 100.000 (99.737) +2022-11-14 16:17:47,832 Epoch: [326][190/500] Time 0.044 (0.045) Data 0.002 (0.004) Loss 0.0177 (0.0333) Prec@1 97.000 (94.600) Prec@5 100.000 (99.750) +2022-11-14 16:17:48,334 Epoch: [326][200/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0118 (0.0322) Prec@1 97.000 (94.714) Prec@5 100.000 (99.762) +2022-11-14 16:17:48,837 Epoch: [326][210/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0332 (0.0323) Prec@1 95.000 (94.727) Prec@5 99.000 (99.727) +2022-11-14 16:17:49,338 Epoch: [326][220/500] Time 0.035 (0.045) Data 0.002 (0.003) Loss 0.0356 (0.0324) Prec@1 94.000 (94.696) Prec@5 100.000 (99.739) +2022-11-14 16:17:49,849 Epoch: [326][230/500] Time 0.044 (0.045) Data 0.002 (0.003) Loss 0.0320 (0.0324) Prec@1 94.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 16:17:50,365 Epoch: [326][240/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0290 (0.0323) Prec@1 95.000 (94.680) Prec@5 99.000 (99.720) +2022-11-14 16:17:50,870 Epoch: [326][250/500] Time 0.044 (0.045) Data 0.003 (0.003) Loss 0.0143 (0.0316) Prec@1 99.000 (94.846) Prec@5 100.000 (99.731) +2022-11-14 16:17:51,404 Epoch: [326][260/500] Time 0.059 (0.045) Data 0.002 (0.003) Loss 0.0299 (0.0315) Prec@1 94.000 (94.815) Prec@5 100.000 (99.741) +2022-11-14 16:17:51,903 Epoch: [326][270/500] Time 0.039 (0.045) Data 0.002 (0.003) Loss 0.0399 (0.0318) Prec@1 95.000 (94.821) Prec@5 100.000 (99.750) +2022-11-14 16:17:52,442 Epoch: [326][280/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0206 (0.0314) Prec@1 97.000 (94.897) Prec@5 100.000 (99.759) +2022-11-14 16:17:52,964 Epoch: [326][290/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0224 (0.0311) Prec@1 97.000 (94.967) Prec@5 99.000 (99.733) +2022-11-14 16:17:53,460 Epoch: [326][300/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0262 (0.0310) Prec@1 96.000 (95.000) Prec@5 100.000 (99.742) +2022-11-14 16:17:53,984 Epoch: [326][310/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0398 (0.0312) Prec@1 94.000 (94.969) Prec@5 100.000 (99.750) +2022-11-14 16:17:54,570 Epoch: [326][320/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0217 (0.0310) Prec@1 96.000 (95.000) Prec@5 100.000 (99.758) +2022-11-14 16:17:55,077 Epoch: [326][330/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0371 (0.0311) Prec@1 92.000 (94.912) Prec@5 100.000 (99.765) +2022-11-14 16:17:55,591 Epoch: [326][340/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0165 (0.0307) Prec@1 97.000 (94.971) Prec@5 100.000 (99.771) +2022-11-14 16:17:56,097 Epoch: [326][350/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0192 (0.0304) Prec@1 98.000 (95.056) Prec@5 100.000 (99.778) +2022-11-14 16:17:56,606 Epoch: [326][360/500] Time 0.043 (0.045) Data 0.002 (0.003) Loss 0.0168 (0.0300) Prec@1 97.000 (95.108) Prec@5 100.000 (99.784) +2022-11-14 16:17:57,131 Epoch: [326][370/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0564 (0.0307) Prec@1 91.000 (95.000) Prec@5 99.000 (99.763) +2022-11-14 16:17:57,645 Epoch: [326][380/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0253 (0.0306) Prec@1 94.000 (94.974) Prec@5 100.000 (99.769) +2022-11-14 16:17:58,159 Epoch: [326][390/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0293 (0.0306) Prec@1 96.000 (95.000) Prec@5 100.000 (99.775) +2022-11-14 16:17:58,675 Epoch: [326][400/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0214 (0.0303) Prec@1 96.000 (95.024) Prec@5 100.000 (99.780) +2022-11-14 16:17:59,187 Epoch: [326][410/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0128 (0.0299) Prec@1 98.000 (95.095) Prec@5 100.000 (99.786) +2022-11-14 16:17:59,697 Epoch: [326][420/500] Time 0.052 (0.045) Data 0.002 (0.003) Loss 0.0169 (0.0296) Prec@1 98.000 (95.163) Prec@5 100.000 (99.791) +2022-11-14 16:18:00,207 Epoch: [326][430/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0233 (0.0295) Prec@1 96.000 (95.182) Prec@5 100.000 (99.795) +2022-11-14 16:18:00,733 Epoch: [326][440/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0506 (0.0299) Prec@1 90.000 (95.067) Prec@5 99.000 (99.778) +2022-11-14 16:18:01,250 Epoch: [326][450/500] Time 0.047 (0.045) Data 0.003 (0.003) Loss 0.0197 (0.0297) Prec@1 96.000 (95.087) Prec@5 100.000 (99.783) +2022-11-14 16:18:01,755 Epoch: [326][460/500] Time 0.046 (0.045) Data 0.002 (0.003) Loss 0.0391 (0.0299) Prec@1 93.000 (95.043) Prec@5 100.000 (99.787) +2022-11-14 16:18:02,265 Epoch: [326][470/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0420 (0.0302) Prec@1 93.000 (95.000) Prec@5 100.000 (99.792) +2022-11-14 16:18:02,775 Epoch: [326][480/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0211 (0.0300) Prec@1 95.000 (95.000) Prec@5 100.000 (99.796) +2022-11-14 16:18:03,286 Epoch: [326][490/500] Time 0.046 (0.045) Data 0.003 (0.003) Loss 0.0299 (0.0300) Prec@1 96.000 (95.020) Prec@5 100.000 (99.800) +2022-11-14 16:18:03,759 Epoch: [326][499/500] Time 0.058 (0.045) Data 0.002 (0.003) Loss 0.0503 (0.0304) Prec@1 89.000 (94.902) Prec@5 100.000 (99.804) +2022-11-14 16:18:04,088 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0603 (0.0603) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:04,098 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0573) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:04,110 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0622) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:04,125 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0636) Prec@1 89.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 16:18:04,135 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0679) Prec@1 85.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 16:18:04,143 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0469 (0.0644) Prec@1 91.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:18:04,156 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0534 (0.0629) Prec@1 93.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 16:18:04,171 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0669) Prec@1 82.000 (88.375) Prec@5 99.000 (99.625) +2022-11-14 16:18:04,185 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0685) Prec@1 86.000 (88.111) Prec@5 100.000 (99.667) +2022-11-14 16:18:04,198 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0697) Prec@1 89.000 (88.200) Prec@5 98.000 (99.500) +2022-11-14 16:18:04,212 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0691) Prec@1 92.000 (88.545) Prec@5 99.000 (99.455) +2022-11-14 16:18:04,225 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0701) Prec@1 85.000 (88.250) Prec@5 99.000 (99.417) +2022-11-14 16:18:04,237 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0687) Prec@1 93.000 (88.615) Prec@5 100.000 (99.462) +2022-11-14 16:18:04,255 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0690) Prec@1 89.000 (88.643) Prec@5 99.000 (99.429) +2022-11-14 16:18:04,271 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0704) Prec@1 85.000 (88.400) Prec@5 97.000 (99.267) +2022-11-14 16:18:04,286 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0703) Prec@1 88.000 (88.375) Prec@5 100.000 (99.312) +2022-11-14 16:18:04,299 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0687) Prec@1 95.000 (88.765) Prec@5 99.000 (99.294) +2022-11-14 16:18:04,314 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1087 (0.0709) Prec@1 83.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 16:18:04,334 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0713) Prec@1 87.000 (88.368) Prec@5 98.000 (99.263) +2022-11-14 16:18:04,356 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0715) Prec@1 88.000 (88.350) Prec@5 97.000 (99.150) +2022-11-14 16:18:04,373 Test: [20/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0728) Prec@1 85.000 (88.190) Prec@5 98.000 (99.095) +2022-11-14 16:18:04,386 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0737) Prec@1 85.000 (88.045) Prec@5 99.000 (99.091) +2022-11-14 16:18:04,402 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0752) Prec@1 82.000 (87.783) Prec@5 99.000 (99.087) +2022-11-14 16:18:04,419 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0752) Prec@1 89.000 (87.833) Prec@5 99.000 (99.083) +2022-11-14 16:18:04,438 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0755) Prec@1 88.000 (87.840) Prec@5 100.000 (99.120) +2022-11-14 16:18:04,454 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0760) Prec@1 87.000 (87.808) Prec@5 97.000 (99.038) +2022-11-14 16:18:04,468 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0754) Prec@1 92.000 (87.963) Prec@5 100.000 (99.074) +2022-11-14 16:18:04,485 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0752) Prec@1 86.000 (87.893) Prec@5 100.000 (99.107) +2022-11-14 16:18:04,501 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0752) Prec@1 87.000 (87.862) Prec@5 98.000 (99.069) +2022-11-14 16:18:04,518 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 85.000 (87.767) Prec@5 99.000 (99.067) +2022-11-14 16:18:04,533 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0748) Prec@1 91.000 (87.871) Prec@5 100.000 (99.097) +2022-11-14 16:18:04,554 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0753) Prec@1 85.000 (87.781) Prec@5 100.000 (99.125) +2022-11-14 16:18:04,573 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0749) Prec@1 88.000 (87.788) Prec@5 100.000 (99.152) +2022-11-14 16:18:04,589 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0757) Prec@1 84.000 (87.676) Prec@5 98.000 (99.118) +2022-11-14 16:18:04,607 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0761) Prec@1 87.000 (87.657) Prec@5 97.000 (99.057) +2022-11-14 16:18:04,623 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0761) Prec@1 89.000 (87.694) Prec@5 99.000 (99.056) +2022-11-14 16:18:04,638 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0756) Prec@1 90.000 (87.757) Prec@5 99.000 (99.054) +2022-11-14 16:18:04,656 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0762) Prec@1 83.000 (87.632) Prec@5 100.000 (99.079) +2022-11-14 16:18:04,671 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0447 (0.0754) Prec@1 93.000 (87.769) Prec@5 99.000 (99.077) +2022-11-14 16:18:04,688 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0751) Prec@1 89.000 (87.800) Prec@5 99.000 (99.075) +2022-11-14 16:18:04,705 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0758) Prec@1 85.000 (87.732) Prec@5 100.000 (99.098) +2022-11-14 16:18:04,720 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0757) Prec@1 86.000 (87.690) Prec@5 100.000 (99.119) +2022-11-14 16:18:04,734 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0752) Prec@1 92.000 (87.791) Prec@5 99.000 (99.116) +2022-11-14 16:18:04,752 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0750) Prec@1 89.000 (87.818) Prec@5 99.000 (99.114) +2022-11-14 16:18:04,770 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0745) Prec@1 93.000 (87.933) Prec@5 99.000 (99.111) +2022-11-14 16:18:04,787 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1039 (0.0752) Prec@1 81.000 (87.783) Prec@5 100.000 (99.130) +2022-11-14 16:18:04,804 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0749) Prec@1 89.000 (87.809) Prec@5 100.000 (99.149) +2022-11-14 16:18:04,823 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0753) Prec@1 85.000 (87.750) Prec@5 99.000 (99.146) +2022-11-14 16:18:04,839 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0747) Prec@1 91.000 (87.816) Prec@5 100.000 (99.163) +2022-11-14 16:18:04,856 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0752) Prec@1 83.000 (87.720) Prec@5 98.000 (99.140) +2022-11-14 16:18:04,873 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0754) Prec@1 84.000 (87.647) Prec@5 100.000 (99.157) +2022-11-14 16:18:04,892 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0754) Prec@1 86.000 (87.615) Prec@5 100.000 (99.173) +2022-11-14 16:18:04,910 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0753) Prec@1 89.000 (87.642) Prec@5 100.000 (99.189) +2022-11-14 16:18:04,930 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0752) Prec@1 91.000 (87.704) Prec@5 99.000 (99.185) +2022-11-14 16:18:04,949 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0754) Prec@1 84.000 (87.636) Prec@5 100.000 (99.200) +2022-11-14 16:18:04,966 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0751) Prec@1 90.000 (87.679) Prec@5 99.000 (99.196) +2022-11-14 16:18:04,983 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0750) Prec@1 88.000 (87.684) Prec@5 100.000 (99.211) +2022-11-14 16:18:04,997 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0749) Prec@1 89.000 (87.707) Prec@5 99.000 (99.207) +2022-11-14 16:18:05,012 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0755) Prec@1 84.000 (87.644) Prec@5 99.000 (99.203) +2022-11-14 16:18:05,036 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0754) Prec@1 87.000 (87.633) Prec@5 100.000 (99.217) +2022-11-14 16:18:05,054 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0753) Prec@1 88.000 (87.639) Prec@5 99.000 (99.213) +2022-11-14 16:18:05,072 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0749) Prec@1 91.000 (87.694) Prec@5 100.000 (99.226) +2022-11-14 16:18:05,093 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0747) Prec@1 92.000 (87.762) Prec@5 100.000 (99.238) +2022-11-14 16:18:05,112 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0744) Prec@1 91.000 (87.812) Prec@5 100.000 (99.250) +2022-11-14 16:18:05,130 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1065 (0.0749) Prec@1 84.000 (87.754) Prec@5 99.000 (99.246) +2022-11-14 16:18:05,147 Test: [65/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0748) Prec@1 88.000 (87.758) Prec@5 100.000 (99.258) +2022-11-14 16:18:05,165 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0745) Prec@1 91.000 (87.806) Prec@5 100.000 (99.269) +2022-11-14 16:18:05,182 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0744) Prec@1 89.000 (87.824) Prec@5 98.000 (99.250) +2022-11-14 16:18:05,200 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0741) Prec@1 91.000 (87.870) Prec@5 99.000 (99.246) +2022-11-14 16:18:05,219 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0740) Prec@1 89.000 (87.886) Prec@5 98.000 (99.229) +2022-11-14 16:18:05,236 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0743) Prec@1 86.000 (87.859) Prec@5 100.000 (99.239) +2022-11-14 16:18:05,252 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0741) Prec@1 91.000 (87.903) Prec@5 100.000 (99.250) +2022-11-14 16:18:05,271 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0405 (0.0736) Prec@1 94.000 (87.986) Prec@5 100.000 (99.260) +2022-11-14 16:18:05,292 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0735) Prec@1 91.000 (88.027) Prec@5 100.000 (99.270) +2022-11-14 16:18:05,308 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0738) Prec@1 87.000 (88.013) Prec@5 100.000 (99.280) +2022-11-14 16:18:05,327 Test: [75/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0734) Prec@1 92.000 (88.066) Prec@5 99.000 (99.276) +2022-11-14 16:18:05,344 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0736) Prec@1 87.000 (88.052) Prec@5 99.000 (99.273) +2022-11-14 16:18:05,358 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0736) Prec@1 88.000 (88.051) Prec@5 96.000 (99.231) +2022-11-14 16:18:05,372 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0734) Prec@1 90.000 (88.076) Prec@5 100.000 (99.241) +2022-11-14 16:18:05,389 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0734) Prec@1 85.000 (88.037) Prec@5 100.000 (99.250) +2022-11-14 16:18:05,408 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0736) Prec@1 87.000 (88.025) Prec@5 99.000 (99.247) +2022-11-14 16:18:05,427 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0739) Prec@1 87.000 (88.012) Prec@5 100.000 (99.256) +2022-11-14 16:18:05,444 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0739) Prec@1 87.000 (88.000) Prec@5 99.000 (99.253) +2022-11-14 16:18:05,460 Test: [83/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0464 (0.0736) Prec@1 93.000 (88.060) Prec@5 99.000 (99.250) +2022-11-14 16:18:05,475 Test: [84/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0739) Prec@1 82.000 (87.988) Prec@5 100.000 (99.259) +2022-11-14 16:18:05,493 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0743) Prec@1 83.000 (87.930) Prec@5 99.000 (99.256) +2022-11-14 16:18:05,510 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0741) Prec@1 92.000 (87.977) Prec@5 100.000 (99.264) +2022-11-14 16:18:05,529 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0742) Prec@1 88.000 (87.977) Prec@5 99.000 (99.261) +2022-11-14 16:18:05,548 Test: [88/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0742) Prec@1 86.000 (87.955) Prec@5 100.000 (99.270) +2022-11-14 16:18:05,566 Test: [89/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0743) Prec@1 88.000 (87.956) Prec@5 100.000 (99.278) +2022-11-14 16:18:05,585 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0741) Prec@1 91.000 (87.989) Prec@5 100.000 (99.286) +2022-11-14 16:18:05,604 Test: [91/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0739) Prec@1 91.000 (88.022) Prec@5 99.000 (99.283) +2022-11-14 16:18:05,621 Test: [92/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0741) Prec@1 86.000 (88.000) Prec@5 100.000 (99.290) +2022-11-14 16:18:05,637 Test: [93/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0742) Prec@1 87.000 (87.989) Prec@5 100.000 (99.298) +2022-11-14 16:18:05,653 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0742) Prec@1 87.000 (87.979) Prec@5 99.000 (99.295) +2022-11-14 16:18:05,674 Test: [95/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0742) Prec@1 90.000 (88.000) Prec@5 99.000 (99.292) +2022-11-14 16:18:05,691 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0739) Prec@1 91.000 (88.031) Prec@5 99.000 (99.289) +2022-11-14 16:18:05,705 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1015 (0.0742) Prec@1 85.000 (88.000) Prec@5 98.000 (99.276) +2022-11-14 16:18:05,720 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0743) Prec@1 89.000 (88.010) Prec@5 99.000 (99.273) +2022-11-14 16:18:05,737 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0742) Prec@1 90.000 (88.030) Prec@5 99.000 (99.270) +2022-11-14 16:18:05,829 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:18:06,211 Epoch: [327][0/500] Time 0.028 (0.028) Data 0.283 (0.283) Loss 0.0406 (0.0406) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:06,495 Epoch: [327][10/500] Time 0.026 (0.025) Data 0.002 (0.027) Loss 0.0059 (0.0232) Prec@1 99.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:18:06,805 Epoch: [327][20/500] Time 0.027 (0.026) Data 0.002 (0.015) Loss 0.0386 (0.0283) Prec@1 94.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:18:07,165 Epoch: [327][30/500] Time 0.054 (0.027) Data 0.002 (0.011) Loss 0.0186 (0.0259) Prec@1 98.000 (96.250) Prec@5 99.000 (99.750) +2022-11-14 16:18:07,782 Epoch: [327][40/500] Time 0.055 (0.034) Data 0.002 (0.009) Loss 0.0425 (0.0292) Prec@1 93.000 (95.600) Prec@5 99.000 (99.600) +2022-11-14 16:18:08,361 Epoch: [327][50/500] Time 0.069 (0.038) Data 0.002 (0.007) Loss 0.0301 (0.0294) Prec@1 95.000 (95.500) Prec@5 100.000 (99.667) +2022-11-14 16:18:08,935 Epoch: [327][60/500] Time 0.047 (0.040) Data 0.002 (0.007) Loss 0.0253 (0.0288) Prec@1 95.000 (95.429) Prec@5 100.000 (99.714) +2022-11-14 16:18:09,548 Epoch: [327][70/500] Time 0.066 (0.042) Data 0.003 (0.006) Loss 0.0435 (0.0306) Prec@1 92.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:18:10,129 Epoch: [327][80/500] Time 0.056 (0.043) Data 0.002 (0.005) Loss 0.0432 (0.0320) Prec@1 90.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 16:18:10,727 Epoch: [327][90/500] Time 0.056 (0.044) Data 0.002 (0.005) Loss 0.0391 (0.0327) Prec@1 95.000 (94.500) Prec@5 99.000 (99.700) +2022-11-14 16:18:11,312 Epoch: [327][100/500] Time 0.048 (0.045) Data 0.003 (0.005) Loss 0.0309 (0.0326) Prec@1 95.000 (94.545) Prec@5 100.000 (99.727) +2022-11-14 16:18:11,899 Epoch: [327][110/500] Time 0.050 (0.046) Data 0.002 (0.005) Loss 0.0177 (0.0313) Prec@1 97.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:18:12,476 Epoch: [327][120/500] Time 0.063 (0.046) Data 0.002 (0.004) Loss 0.0476 (0.0326) Prec@1 92.000 (94.538) Prec@5 99.000 (99.692) +2022-11-14 16:18:13,050 Epoch: [327][130/500] Time 0.060 (0.047) Data 0.002 (0.004) Loss 0.0382 (0.0330) Prec@1 93.000 (94.429) Prec@5 99.000 (99.643) +2022-11-14 16:18:13,644 Epoch: [327][140/500] Time 0.056 (0.047) Data 0.002 (0.004) Loss 0.0283 (0.0327) Prec@1 95.000 (94.467) Prec@5 100.000 (99.667) +2022-11-14 16:18:14,234 Epoch: [327][150/500] Time 0.060 (0.048) Data 0.003 (0.004) Loss 0.0270 (0.0323) Prec@1 96.000 (94.562) Prec@5 100.000 (99.688) +2022-11-14 16:18:14,814 Epoch: [327][160/500] Time 0.054 (0.048) Data 0.002 (0.004) Loss 0.0206 (0.0316) Prec@1 95.000 (94.588) Prec@5 100.000 (99.706) +2022-11-14 16:18:15,401 Epoch: [327][170/500] Time 0.059 (0.048) Data 0.003 (0.004) Loss 0.0358 (0.0319) Prec@1 94.000 (94.556) Prec@5 100.000 (99.722) +2022-11-14 16:18:15,975 Epoch: [327][180/500] Time 0.050 (0.048) Data 0.002 (0.004) Loss 0.0308 (0.0318) Prec@1 94.000 (94.526) Prec@5 100.000 (99.737) +2022-11-14 16:18:16,562 Epoch: [327][190/500] Time 0.052 (0.048) Data 0.002 (0.004) Loss 0.0284 (0.0316) Prec@1 95.000 (94.550) Prec@5 100.000 (99.750) +2022-11-14 16:18:17,155 Epoch: [327][200/500] Time 0.067 (0.049) Data 0.002 (0.003) Loss 0.0315 (0.0316) Prec@1 96.000 (94.619) Prec@5 100.000 (99.762) +2022-11-14 16:18:17,714 Epoch: [327][210/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0315 (0.0316) Prec@1 95.000 (94.636) Prec@5 100.000 (99.773) +2022-11-14 16:18:18,298 Epoch: [327][220/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0269 (0.0314) Prec@1 97.000 (94.739) Prec@5 100.000 (99.783) +2022-11-14 16:18:18,891 Epoch: [327][230/500] Time 0.060 (0.049) Data 0.002 (0.003) Loss 0.0252 (0.0312) Prec@1 97.000 (94.833) Prec@5 100.000 (99.792) +2022-11-14 16:18:19,476 Epoch: [327][240/500] Time 0.062 (0.049) Data 0.002 (0.003) Loss 0.0373 (0.0314) Prec@1 94.000 (94.800) Prec@5 99.000 (99.760) +2022-11-14 16:18:20,065 Epoch: [327][250/500] Time 0.065 (0.049) Data 0.002 (0.003) Loss 0.0350 (0.0315) Prec@1 94.000 (94.769) Prec@5 99.000 (99.731) +2022-11-14 16:18:20,651 Epoch: [327][260/500] Time 0.063 (0.049) Data 0.002 (0.003) Loss 0.0376 (0.0318) Prec@1 95.000 (94.778) Prec@5 100.000 (99.741) +2022-11-14 16:18:21,230 Epoch: [327][270/500] Time 0.060 (0.049) Data 0.002 (0.003) Loss 0.0418 (0.0321) Prec@1 93.000 (94.714) Prec@5 100.000 (99.750) +2022-11-14 16:18:21,813 Epoch: [327][280/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0232 (0.0318) Prec@1 96.000 (94.759) Prec@5 100.000 (99.759) +2022-11-14 16:18:22,406 Epoch: [327][290/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0178 (0.0313) Prec@1 96.000 (94.800) Prec@5 100.000 (99.767) +2022-11-14 16:18:23,013 Epoch: [327][300/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0190 (0.0309) Prec@1 97.000 (94.871) Prec@5 100.000 (99.774) +2022-11-14 16:18:23,612 Epoch: [327][310/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0430 (0.0313) Prec@1 93.000 (94.812) Prec@5 100.000 (99.781) +2022-11-14 16:18:24,192 Epoch: [327][320/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0416 (0.0316) Prec@1 93.000 (94.758) Prec@5 100.000 (99.788) +2022-11-14 16:18:24,764 Epoch: [327][330/500] Time 0.067 (0.050) Data 0.002 (0.003) Loss 0.0343 (0.0317) Prec@1 94.000 (94.735) Prec@5 100.000 (99.794) +2022-11-14 16:18:25,364 Epoch: [327][340/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0335 (0.0318) Prec@1 95.000 (94.743) Prec@5 99.000 (99.771) +2022-11-14 16:18:25,951 Epoch: [327][350/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0428 (0.0321) Prec@1 93.000 (94.694) Prec@5 99.000 (99.750) +2022-11-14 16:18:26,530 Epoch: [327][360/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0437 (0.0324) Prec@1 93.000 (94.649) Prec@5 100.000 (99.757) +2022-11-14 16:18:27,117 Epoch: [327][370/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0264 (0.0322) Prec@1 97.000 (94.711) Prec@5 100.000 (99.763) +2022-11-14 16:18:27,694 Epoch: [327][380/500] Time 0.060 (0.050) Data 0.002 (0.003) Loss 0.0434 (0.0325) Prec@1 92.000 (94.641) Prec@5 99.000 (99.744) +2022-11-14 16:18:28,271 Epoch: [327][390/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0406 (0.0327) Prec@1 93.000 (94.600) Prec@5 100.000 (99.750) +2022-11-14 16:18:28,859 Epoch: [327][400/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0348 (0.0328) Prec@1 95.000 (94.610) Prec@5 100.000 (99.756) +2022-11-14 16:18:29,441 Epoch: [327][410/500] Time 0.064 (0.050) Data 0.002 (0.003) Loss 0.0064 (0.0321) Prec@1 100.000 (94.738) Prec@5 100.000 (99.762) +2022-11-14 16:18:30,049 Epoch: [327][420/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0215 (0.0319) Prec@1 97.000 (94.791) Prec@5 99.000 (99.744) +2022-11-14 16:18:30,632 Epoch: [327][430/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0329 (0.0319) Prec@1 95.000 (94.795) Prec@5 99.000 (99.727) +2022-11-14 16:18:31,208 Epoch: [327][440/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0432 (0.0322) Prec@1 95.000 (94.800) Prec@5 99.000 (99.711) +2022-11-14 16:18:31,807 Epoch: [327][450/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0312 (0.0321) Prec@1 95.000 (94.804) Prec@5 100.000 (99.717) +2022-11-14 16:18:32,403 Epoch: [327][460/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0438 (0.0324) Prec@1 91.000 (94.723) Prec@5 99.000 (99.702) +2022-11-14 16:18:32,973 Epoch: [327][470/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0157 (0.0320) Prec@1 97.000 (94.771) Prec@5 100.000 (99.708) +2022-11-14 16:18:33,554 Epoch: [327][480/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0431 (0.0323) Prec@1 94.000 (94.755) Prec@5 100.000 (99.714) +2022-11-14 16:18:34,139 Epoch: [327][490/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0488 (0.0326) Prec@1 91.000 (94.680) Prec@5 100.000 (99.720) +2022-11-14 16:18:34,646 Epoch: [327][499/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0590 (0.0331) Prec@1 90.000 (94.588) Prec@5 99.000 (99.706) +2022-11-14 16:18:34,963 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0600 (0.0600) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:34,974 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0694) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:34,986 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0711) Prec@1 88.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:18:34,996 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0727) Prec@1 89.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 16:18:35,005 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0705) Prec@1 92.000 (89.400) Prec@5 99.000 (99.400) +2022-11-14 16:18:35,014 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0671) Prec@1 91.000 (89.667) Prec@5 100.000 (99.500) +2022-11-14 16:18:35,024 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0659) Prec@1 92.000 (90.000) Prec@5 99.000 (99.429) +2022-11-14 16:18:35,035 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0677) Prec@1 87.000 (89.625) Prec@5 97.000 (99.125) +2022-11-14 16:18:35,046 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0695) Prec@1 87.000 (89.333) Prec@5 99.000 (99.111) +2022-11-14 16:18:35,058 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0713) Prec@1 86.000 (89.000) Prec@5 97.000 (98.900) +2022-11-14 16:18:35,070 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0713) Prec@1 89.000 (89.000) Prec@5 100.000 (99.000) +2022-11-14 16:18:35,083 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0717) Prec@1 90.000 (89.083) Prec@5 99.000 (99.000) +2022-11-14 16:18:35,094 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0710) Prec@1 89.000 (89.077) Prec@5 100.000 (99.077) +2022-11-14 16:18:35,104 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0717) Prec@1 89.000 (89.071) Prec@5 99.000 (99.071) +2022-11-14 16:18:35,115 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0713) Prec@1 91.000 (89.200) Prec@5 99.000 (99.067) +2022-11-14 16:18:35,127 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0707) Prec@1 94.000 (89.500) Prec@5 100.000 (99.125) +2022-11-14 16:18:35,138 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0416 (0.0690) Prec@1 95.000 (89.824) Prec@5 99.000 (99.118) +2022-11-14 16:18:35,149 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0714) Prec@1 83.000 (89.444) Prec@5 100.000 (99.167) +2022-11-14 16:18:35,162 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0715) Prec@1 87.000 (89.316) Prec@5 98.000 (99.105) +2022-11-14 16:18:35,173 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0724) Prec@1 87.000 (89.200) Prec@5 98.000 (99.050) +2022-11-14 16:18:35,185 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0730) Prec@1 86.000 (89.048) Prec@5 99.000 (99.048) +2022-11-14 16:18:35,195 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0738) Prec@1 82.000 (88.727) Prec@5 100.000 (99.091) +2022-11-14 16:18:35,206 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1049 (0.0752) Prec@1 83.000 (88.478) Prec@5 99.000 (99.087) +2022-11-14 16:18:35,217 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0745) Prec@1 92.000 (88.625) Prec@5 100.000 (99.125) +2022-11-14 16:18:35,229 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0747) Prec@1 87.000 (88.560) Prec@5 98.000 (99.080) +2022-11-14 16:18:35,240 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0748) Prec@1 87.000 (88.500) Prec@5 99.000 (99.077) +2022-11-14 16:18:35,251 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0738) Prec@1 92.000 (88.630) Prec@5 100.000 (99.111) +2022-11-14 16:18:35,261 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0735) Prec@1 89.000 (88.643) Prec@5 100.000 (99.143) +2022-11-14 16:18:35,271 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0740) Prec@1 84.000 (88.483) Prec@5 98.000 (99.103) +2022-11-14 16:18:35,282 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0740) Prec@1 87.000 (88.433) Prec@5 99.000 (99.100) +2022-11-14 16:18:35,293 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0735) Prec@1 90.000 (88.484) Prec@5 100.000 (99.129) +2022-11-14 16:18:35,303 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0736) Prec@1 88.000 (88.469) Prec@5 99.000 (99.125) +2022-11-14 16:18:35,313 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0740) Prec@1 85.000 (88.364) Prec@5 99.000 (99.121) +2022-11-14 16:18:35,324 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0739) Prec@1 87.000 (88.324) Prec@5 100.000 (99.147) +2022-11-14 16:18:35,335 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0735) Prec@1 91.000 (88.400) Prec@5 98.000 (99.114) +2022-11-14 16:18:35,347 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0730) Prec@1 93.000 (88.528) Prec@5 100.000 (99.139) +2022-11-14 16:18:35,360 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0728) Prec@1 89.000 (88.541) Prec@5 99.000 (99.135) +2022-11-14 16:18:35,372 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0735) Prec@1 83.000 (88.395) Prec@5 98.000 (99.105) +2022-11-14 16:18:35,383 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0729) Prec@1 93.000 (88.513) Prec@5 99.000 (99.103) +2022-11-14 16:18:35,393 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0724) Prec@1 90.000 (88.550) Prec@5 99.000 (99.100) +2022-11-14 16:18:35,404 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0724) Prec@1 88.000 (88.537) Prec@5 99.000 (99.098) +2022-11-14 16:18:35,418 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0721) Prec@1 91.000 (88.595) Prec@5 99.000 (99.095) +2022-11-14 16:18:35,430 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0467 (0.0715) Prec@1 93.000 (88.698) Prec@5 99.000 (99.093) +2022-11-14 16:18:35,441 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0715) Prec@1 86.000 (88.636) Prec@5 98.000 (99.068) +2022-11-14 16:18:35,451 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0710) Prec@1 91.000 (88.689) Prec@5 100.000 (99.089) +2022-11-14 16:18:35,463 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0717) Prec@1 83.000 (88.565) Prec@5 100.000 (99.109) +2022-11-14 16:18:35,475 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0718) Prec@1 88.000 (88.553) Prec@5 100.000 (99.128) +2022-11-14 16:18:35,487 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0721) Prec@1 88.000 (88.542) Prec@5 98.000 (99.104) +2022-11-14 16:18:35,499 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0448 (0.0715) Prec@1 93.000 (88.633) Prec@5 100.000 (99.122) +2022-11-14 16:18:35,511 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0720) Prec@1 87.000 (88.600) Prec@5 99.000 (99.120) +2022-11-14 16:18:35,523 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0716) Prec@1 92.000 (88.667) Prec@5 99.000 (99.118) +2022-11-14 16:18:35,535 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0713) Prec@1 89.000 (88.673) Prec@5 100.000 (99.135) +2022-11-14 16:18:35,546 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0714) Prec@1 88.000 (88.660) Prec@5 100.000 (99.151) +2022-11-14 16:18:35,558 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0711) Prec@1 89.000 (88.667) Prec@5 99.000 (99.148) +2022-11-14 16:18:35,568 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0716) Prec@1 85.000 (88.600) Prec@5 99.000 (99.145) +2022-11-14 16:18:35,580 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0718) Prec@1 89.000 (88.607) Prec@5 99.000 (99.143) +2022-11-14 16:18:35,591 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0717) Prec@1 91.000 (88.649) Prec@5 100.000 (99.158) +2022-11-14 16:18:35,602 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0715) Prec@1 89.000 (88.655) Prec@5 100.000 (99.172) +2022-11-14 16:18:35,613 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0721) Prec@1 86.000 (88.610) Prec@5 99.000 (99.169) +2022-11-14 16:18:35,624 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0724) Prec@1 84.000 (88.533) Prec@5 100.000 (99.183) +2022-11-14 16:18:35,637 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0727) Prec@1 86.000 (88.492) Prec@5 100.000 (99.197) +2022-11-14 16:18:35,647 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0726) Prec@1 86.000 (88.452) Prec@5 100.000 (99.210) +2022-11-14 16:18:35,659 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0724) Prec@1 89.000 (88.460) Prec@5 100.000 (99.222) +2022-11-14 16:18:35,673 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0721) Prec@1 90.000 (88.484) Prec@5 100.000 (99.234) +2022-11-14 16:18:35,685 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0725) Prec@1 85.000 (88.431) Prec@5 100.000 (99.246) +2022-11-14 16:18:35,696 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0724) Prec@1 91.000 (88.470) Prec@5 99.000 (99.242) +2022-11-14 16:18:35,707 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0421 (0.0719) Prec@1 94.000 (88.552) Prec@5 100.000 (99.254) +2022-11-14 16:18:35,718 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0717) Prec@1 90.000 (88.574) Prec@5 97.000 (99.221) +2022-11-14 16:18:35,728 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0717) Prec@1 89.000 (88.580) Prec@5 100.000 (99.232) +2022-11-14 16:18:35,740 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0716) Prec@1 91.000 (88.614) Prec@5 99.000 (99.229) +2022-11-14 16:18:35,752 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1163 (0.0722) Prec@1 84.000 (88.549) Prec@5 98.000 (99.211) +2022-11-14 16:18:35,764 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0719) Prec@1 93.000 (88.611) Prec@5 99.000 (99.208) +2022-11-14 16:18:35,776 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0717) Prec@1 89.000 (88.616) Prec@5 99.000 (99.205) +2022-11-14 16:18:35,788 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0715) Prec@1 92.000 (88.662) Prec@5 100.000 (99.216) +2022-11-14 16:18:35,798 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0718) Prec@1 84.000 (88.600) Prec@5 100.000 (99.227) +2022-11-14 16:18:35,810 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0716) Prec@1 91.000 (88.632) Prec@5 99.000 (99.224) +2022-11-14 16:18:35,822 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0716) Prec@1 88.000 (88.623) Prec@5 99.000 (99.221) +2022-11-14 16:18:35,832 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0717) Prec@1 88.000 (88.615) Prec@5 98.000 (99.205) +2022-11-14 16:18:35,843 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0715) Prec@1 91.000 (88.646) Prec@5 100.000 (99.215) +2022-11-14 16:18:35,854 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0714) Prec@1 88.000 (88.638) Prec@5 100.000 (99.225) +2022-11-14 16:18:35,866 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0852 (0.0716) Prec@1 88.000 (88.630) Prec@5 99.000 (99.222) +2022-11-14 16:18:35,878 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0719) Prec@1 84.000 (88.573) Prec@5 100.000 (99.232) +2022-11-14 16:18:35,890 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0720) Prec@1 86.000 (88.542) Prec@5 100.000 (99.241) +2022-11-14 16:18:35,902 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0718) Prec@1 90.000 (88.560) Prec@5 100.000 (99.250) +2022-11-14 16:18:35,915 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0719) Prec@1 89.000 (88.565) Prec@5 100.000 (99.259) +2022-11-14 16:18:35,927 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0724) Prec@1 80.000 (88.465) Prec@5 99.000 (99.256) +2022-11-14 16:18:35,937 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0724) Prec@1 87.000 (88.448) Prec@5 100.000 (99.264) +2022-11-14 16:18:35,949 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0725) Prec@1 87.000 (88.432) Prec@5 99.000 (99.261) +2022-11-14 16:18:35,960 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0724) Prec@1 89.000 (88.438) Prec@5 100.000 (99.270) +2022-11-14 16:18:35,972 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0723) Prec@1 90.000 (88.456) Prec@5 100.000 (99.278) +2022-11-14 16:18:35,984 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0722) Prec@1 89.000 (88.462) Prec@5 100.000 (99.286) +2022-11-14 16:18:35,994 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0720) Prec@1 91.000 (88.489) Prec@5 99.000 (99.283) +2022-11-14 16:18:36,004 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0722) Prec@1 85.000 (88.452) Prec@5 99.000 (99.280) +2022-11-14 16:18:36,015 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0722) Prec@1 88.000 (88.447) Prec@5 100.000 (99.287) +2022-11-14 16:18:36,027 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0722) Prec@1 89.000 (88.453) Prec@5 100.000 (99.295) +2022-11-14 16:18:36,039 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0721) Prec@1 89.000 (88.458) Prec@5 100.000 (99.302) +2022-11-14 16:18:36,050 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0720) Prec@1 89.000 (88.464) Prec@5 98.000 (99.289) +2022-11-14 16:18:36,062 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0721) Prec@1 84.000 (88.418) Prec@5 99.000 (99.286) +2022-11-14 16:18:36,074 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0723) Prec@1 84.000 (88.374) Prec@5 98.000 (99.273) +2022-11-14 16:18:36,086 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0723) Prec@1 89.000 (88.380) Prec@5 99.000 (99.270) +2022-11-14 16:18:36,174 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:18:36,539 Epoch: [328][0/500] Time 0.026 (0.026) Data 0.271 (0.271) Loss 0.0182 (0.0182) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:36,799 Epoch: [328][10/500] Time 0.023 (0.023) Data 0.002 (0.027) Loss 0.0234 (0.0208) Prec@1 97.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:18:37,072 Epoch: [328][20/500] Time 0.029 (0.023) Data 0.002 (0.015) Loss 0.0260 (0.0225) Prec@1 95.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:18:37,746 Epoch: [328][30/500] Time 0.063 (0.035) Data 0.002 (0.011) Loss 0.0290 (0.0241) Prec@1 97.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 16:18:38,482 Epoch: [328][40/500] Time 0.073 (0.043) Data 0.002 (0.009) Loss 0.0142 (0.0221) Prec@1 98.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:39,265 Epoch: [328][50/500] Time 0.075 (0.048) Data 0.002 (0.007) Loss 0.0111 (0.0203) Prec@1 99.000 (97.333) Prec@5 100.000 (100.000) +2022-11-14 16:18:40,053 Epoch: [328][60/500] Time 0.071 (0.052) Data 0.002 (0.007) Loss 0.0363 (0.0226) Prec@1 95.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:18:40,816 Epoch: [328][70/500] Time 0.073 (0.054) Data 0.002 (0.006) Loss 0.0449 (0.0254) Prec@1 92.000 (96.375) Prec@5 100.000 (100.000) +2022-11-14 16:18:41,588 Epoch: [328][80/500] Time 0.073 (0.056) Data 0.002 (0.005) Loss 0.0251 (0.0253) Prec@1 96.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:18:42,364 Epoch: [328][90/500] Time 0.069 (0.058) Data 0.002 (0.005) Loss 0.0298 (0.0258) Prec@1 95.000 (96.200) Prec@5 99.000 (99.900) +2022-11-14 16:18:43,133 Epoch: [328][100/500] Time 0.071 (0.059) Data 0.002 (0.005) Loss 0.0278 (0.0260) Prec@1 96.000 (96.182) Prec@5 100.000 (99.909) +2022-11-14 16:18:43,896 Epoch: [328][110/500] Time 0.070 (0.059) Data 0.002 (0.004) Loss 0.0272 (0.0261) Prec@1 96.000 (96.167) Prec@5 100.000 (99.917) +2022-11-14 16:18:44,668 Epoch: [328][120/500] Time 0.079 (0.060) Data 0.002 (0.004) Loss 0.0160 (0.0253) Prec@1 98.000 (96.308) Prec@5 100.000 (99.923) +2022-11-14 16:18:45,447 Epoch: [328][130/500] Time 0.075 (0.061) Data 0.002 (0.004) Loss 0.0158 (0.0246) Prec@1 97.000 (96.357) Prec@5 100.000 (99.929) +2022-11-14 16:18:46,312 Epoch: [328][140/500] Time 0.068 (0.062) Data 0.002 (0.004) Loss 0.0576 (0.0268) Prec@1 91.000 (96.000) Prec@5 100.000 (99.933) +2022-11-14 16:18:47,078 Epoch: [328][150/500] Time 0.072 (0.063) Data 0.002 (0.004) Loss 0.0240 (0.0266) Prec@1 97.000 (96.062) Prec@5 100.000 (99.938) +2022-11-14 16:18:47,537 Epoch: [328][160/500] Time 0.033 (0.061) Data 0.002 (0.004) Loss 0.0426 (0.0276) Prec@1 94.000 (95.941) Prec@5 100.000 (99.941) +2022-11-14 16:18:47,912 Epoch: [328][170/500] Time 0.031 (0.060) Data 0.002 (0.004) Loss 0.0305 (0.0277) Prec@1 96.000 (95.944) Prec@5 100.000 (99.944) +2022-11-14 16:18:48,283 Epoch: [328][180/500] Time 0.037 (0.058) Data 0.002 (0.004) Loss 0.0187 (0.0273) Prec@1 97.000 (96.000) Prec@5 100.000 (99.947) +2022-11-14 16:18:48,669 Epoch: [328][190/500] Time 0.029 (0.057) Data 0.002 (0.003) Loss 0.0490 (0.0283) Prec@1 92.000 (95.800) Prec@5 100.000 (99.950) +2022-11-14 16:18:49,056 Epoch: [328][200/500] Time 0.036 (0.056) Data 0.002 (0.003) Loss 0.0488 (0.0293) Prec@1 92.000 (95.619) Prec@5 100.000 (99.952) +2022-11-14 16:18:49,450 Epoch: [328][210/500] Time 0.042 (0.055) Data 0.002 (0.003) Loss 0.0377 (0.0297) Prec@1 93.000 (95.500) Prec@5 100.000 (99.955) +2022-11-14 16:18:49,833 Epoch: [328][220/500] Time 0.039 (0.054) Data 0.002 (0.003) Loss 0.0167 (0.0291) Prec@1 98.000 (95.609) Prec@5 99.000 (99.913) +2022-11-14 16:18:50,212 Epoch: [328][230/500] Time 0.030 (0.053) Data 0.002 (0.003) Loss 0.0109 (0.0284) Prec@1 99.000 (95.750) Prec@5 100.000 (99.917) +2022-11-14 16:18:50,591 Epoch: [328][240/500] Time 0.029 (0.052) Data 0.002 (0.003) Loss 0.0417 (0.0289) Prec@1 94.000 (95.680) Prec@5 100.000 (99.920) +2022-11-14 16:18:50,995 Epoch: [328][250/500] Time 0.037 (0.052) Data 0.002 (0.003) Loss 0.0203 (0.0286) Prec@1 97.000 (95.731) Prec@5 100.000 (99.923) +2022-11-14 16:18:51,387 Epoch: [328][260/500] Time 0.038 (0.051) Data 0.002 (0.003) Loss 0.0282 (0.0286) Prec@1 97.000 (95.778) Prec@5 99.000 (99.889) +2022-11-14 16:18:51,777 Epoch: [328][270/500] Time 0.039 (0.050) Data 0.002 (0.003) Loss 0.0488 (0.0293) Prec@1 93.000 (95.679) Prec@5 99.000 (99.857) +2022-11-14 16:18:52,166 Epoch: [328][280/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0241 (0.0291) Prec@1 96.000 (95.690) Prec@5 100.000 (99.862) +2022-11-14 16:18:52,546 Epoch: [328][290/500] Time 0.036 (0.049) Data 0.002 (0.003) Loss 0.0440 (0.0296) Prec@1 94.000 (95.633) Prec@5 100.000 (99.867) +2022-11-14 16:18:52,947 Epoch: [328][300/500] Time 0.037 (0.049) Data 0.002 (0.003) Loss 0.0372 (0.0299) Prec@1 92.000 (95.516) Prec@5 100.000 (99.871) +2022-11-14 16:18:53,344 Epoch: [328][310/500] Time 0.033 (0.048) Data 0.002 (0.003) Loss 0.0299 (0.0299) Prec@1 93.000 (95.438) Prec@5 100.000 (99.875) +2022-11-14 16:18:54,039 Epoch: [328][320/500] Time 0.062 (0.049) Data 0.002 (0.003) Loss 0.0226 (0.0296) Prec@1 96.000 (95.455) Prec@5 100.000 (99.879) +2022-11-14 16:18:54,722 Epoch: [328][330/500] Time 0.061 (0.049) Data 0.002 (0.003) Loss 0.0549 (0.0304) Prec@1 91.000 (95.324) Prec@5 100.000 (99.882) +2022-11-14 16:18:55,403 Epoch: [328][340/500] Time 0.073 (0.049) Data 0.002 (0.003) Loss 0.0214 (0.0301) Prec@1 97.000 (95.371) Prec@5 100.000 (99.886) +2022-11-14 16:18:56,100 Epoch: [328][350/500] Time 0.077 (0.050) Data 0.002 (0.003) Loss 0.0189 (0.0298) Prec@1 96.000 (95.389) Prec@5 100.000 (99.889) +2022-11-14 16:18:56,810 Epoch: [328][360/500] Time 0.078 (0.050) Data 0.002 (0.003) Loss 0.0304 (0.0298) Prec@1 98.000 (95.459) Prec@5 100.000 (99.892) +2022-11-14 16:18:57,508 Epoch: [328][370/500] Time 0.072 (0.051) Data 0.003 (0.003) Loss 0.0313 (0.0299) Prec@1 96.000 (95.474) Prec@5 100.000 (99.895) +2022-11-14 16:18:58,205 Epoch: [328][380/500] Time 0.063 (0.051) Data 0.003 (0.003) Loss 0.0179 (0.0296) Prec@1 97.000 (95.513) Prec@5 100.000 (99.897) +2022-11-14 16:18:58,909 Epoch: [328][390/500] Time 0.080 (0.051) Data 0.002 (0.003) Loss 0.0596 (0.0303) Prec@1 89.000 (95.350) Prec@5 100.000 (99.900) +2022-11-14 16:18:59,583 Epoch: [328][400/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0437 (0.0306) Prec@1 93.000 (95.293) Prec@5 100.000 (99.902) +2022-11-14 16:19:00,268 Epoch: [328][410/500] Time 0.073 (0.052) Data 0.002 (0.003) Loss 0.0164 (0.0303) Prec@1 99.000 (95.381) Prec@5 100.000 (99.905) +2022-11-14 16:19:00,975 Epoch: [328][420/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0408 (0.0305) Prec@1 92.000 (95.302) Prec@5 100.000 (99.907) +2022-11-14 16:19:01,686 Epoch: [328][430/500] Time 0.067 (0.052) Data 0.002 (0.003) Loss 0.0115 (0.0301) Prec@1 100.000 (95.409) Prec@5 100.000 (99.909) +2022-11-14 16:19:02,380 Epoch: [328][440/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0466 (0.0305) Prec@1 92.000 (95.333) Prec@5 100.000 (99.911) +2022-11-14 16:19:03,052 Epoch: [328][450/500] Time 0.060 (0.053) Data 0.002 (0.003) Loss 0.0246 (0.0303) Prec@1 97.000 (95.370) Prec@5 100.000 (99.913) +2022-11-14 16:19:03,740 Epoch: [328][460/500] Time 0.066 (0.053) Data 0.002 (0.003) Loss 0.0284 (0.0303) Prec@1 95.000 (95.362) Prec@5 100.000 (99.915) +2022-11-14 16:19:04,439 Epoch: [328][470/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0286 (0.0303) Prec@1 94.000 (95.333) Prec@5 100.000 (99.917) +2022-11-14 16:19:05,136 Epoch: [328][480/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0669 (0.0310) Prec@1 90.000 (95.224) Prec@5 100.000 (99.918) +2022-11-14 16:19:05,834 Epoch: [328][490/500] Time 0.054 (0.053) Data 0.003 (0.003) Loss 0.0305 (0.0310) Prec@1 94.000 (95.200) Prec@5 100.000 (99.920) +2022-11-14 16:19:06,456 Epoch: [328][499/500] Time 0.070 (0.053) Data 0.002 (0.003) Loss 0.0340 (0.0311) Prec@1 96.000 (95.216) Prec@5 99.000 (99.902) +2022-11-14 16:19:06,787 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0683 (0.0683) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:06,796 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0542 (0.0612) Prec@1 92.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:19:06,805 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0653) Prec@1 86.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:19:06,818 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0656) Prec@1 90.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 16:19:06,828 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0702) Prec@1 86.000 (88.600) Prec@5 98.000 (99.200) +2022-11-14 16:19:06,838 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0384 (0.0649) Prec@1 93.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 16:19:06,847 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0656) Prec@1 89.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 16:19:06,858 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0672) Prec@1 88.000 (89.125) Prec@5 100.000 (99.500) +2022-11-14 16:19:06,868 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0680) Prec@1 91.000 (89.333) Prec@5 99.000 (99.444) +2022-11-14 16:19:06,880 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0701) Prec@1 85.000 (88.900) Prec@5 97.000 (99.200) +2022-11-14 16:19:06,893 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0694) Prec@1 90.000 (89.000) Prec@5 100.000 (99.273) +2022-11-14 16:19:06,904 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0708) Prec@1 86.000 (88.750) Prec@5 100.000 (99.333) +2022-11-14 16:19:06,916 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0708) Prec@1 88.000 (88.692) Prec@5 99.000 (99.308) +2022-11-14 16:19:06,929 Test: [13/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0715) Prec@1 86.000 (88.500) Prec@5 99.000 (99.286) +2022-11-14 16:19:06,941 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0717) Prec@1 86.000 (88.333) Prec@5 99.000 (99.267) +2022-11-14 16:19:06,951 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0728) Prec@1 84.000 (88.062) Prec@5 99.000 (99.250) +2022-11-14 16:19:06,966 Test: [16/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0605 (0.0721) Prec@1 91.000 (88.235) Prec@5 99.000 (99.235) +2022-11-14 16:19:06,981 Test: [17/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0734) Prec@1 88.000 (88.222) Prec@5 98.000 (99.167) +2022-11-14 16:19:06,993 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0737) Prec@1 87.000 (88.158) Prec@5 100.000 (99.211) +2022-11-14 16:19:07,004 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0741) Prec@1 87.000 (88.100) Prec@5 99.000 (99.200) +2022-11-14 16:19:07,015 Test: [20/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0753) Prec@1 84.000 (87.905) Prec@5 100.000 (99.238) +2022-11-14 16:19:07,026 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0751) Prec@1 90.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 16:19:07,037 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0759) Prec@1 86.000 (87.913) Prec@5 100.000 (99.304) +2022-11-14 16:19:07,048 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0759) Prec@1 87.000 (87.875) Prec@5 100.000 (99.333) +2022-11-14 16:19:07,060 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0977 (0.0768) Prec@1 86.000 (87.800) Prec@5 99.000 (99.320) +2022-11-14 16:19:07,070 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0769) Prec@1 85.000 (87.692) Prec@5 99.000 (99.308) +2022-11-14 16:19:07,082 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0760) Prec@1 89.000 (87.741) Prec@5 100.000 (99.333) +2022-11-14 16:19:07,093 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0758) Prec@1 90.000 (87.821) Prec@5 99.000 (99.321) +2022-11-14 16:19:07,104 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0582 (0.0752) Prec@1 90.000 (87.897) Prec@5 99.000 (99.310) +2022-11-14 16:19:07,116 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0646 (0.0748) Prec@1 88.000 (87.900) Prec@5 98.000 (99.267) +2022-11-14 16:19:07,127 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0750) Prec@1 88.000 (87.903) Prec@5 99.000 (99.258) +2022-11-14 16:19:07,139 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0747) Prec@1 89.000 (87.938) Prec@5 99.000 (99.250) +2022-11-14 16:19:07,150 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0742) Prec@1 92.000 (88.061) Prec@5 100.000 (99.273) +2022-11-14 16:19:07,161 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0749) Prec@1 81.000 (87.853) Prec@5 99.000 (99.265) +2022-11-14 16:19:07,174 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0752) Prec@1 84.000 (87.743) Prec@5 97.000 (99.200) +2022-11-14 16:19:07,185 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0752) Prec@1 90.000 (87.806) Prec@5 99.000 (99.194) +2022-11-14 16:19:07,196 Test: [36/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0750) Prec@1 89.000 (87.838) Prec@5 98.000 (99.162) +2022-11-14 16:19:07,206 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0986 (0.0756) Prec@1 84.000 (87.737) Prec@5 100.000 (99.184) +2022-11-14 16:19:07,217 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0751) Prec@1 93.000 (87.872) Prec@5 99.000 (99.179) +2022-11-14 16:19:07,228 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0749) Prec@1 86.000 (87.825) Prec@5 100.000 (99.200) +2022-11-14 16:19:07,238 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.0757) Prec@1 84.000 (87.732) Prec@5 98.000 (99.171) +2022-11-14 16:19:07,249 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0756) Prec@1 89.000 (87.762) Prec@5 100.000 (99.190) +2022-11-14 16:19:07,261 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0467 (0.0749) Prec@1 92.000 (87.860) Prec@5 100.000 (99.209) +2022-11-14 16:19:07,272 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0746) Prec@1 93.000 (87.977) Prec@5 98.000 (99.182) +2022-11-14 16:19:07,284 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0743) Prec@1 90.000 (88.022) Prec@5 99.000 (99.178) +2022-11-14 16:19:07,296 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0750) Prec@1 82.000 (87.891) Prec@5 98.000 (99.152) +2022-11-14 16:19:07,307 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0751) Prec@1 87.000 (87.872) Prec@5 100.000 (99.170) +2022-11-14 16:19:07,319 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.0758) Prec@1 82.000 (87.750) Prec@5 98.000 (99.146) +2022-11-14 16:19:07,329 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0754) Prec@1 90.000 (87.796) Prec@5 100.000 (99.163) +2022-11-14 16:19:07,339 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0757) Prec@1 87.000 (87.780) Prec@5 99.000 (99.160) +2022-11-14 16:19:07,349 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0755) Prec@1 90.000 (87.824) Prec@5 99.000 (99.157) +2022-11-14 16:19:07,360 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0754) Prec@1 89.000 (87.846) Prec@5 99.000 (99.154) +2022-11-14 16:19:07,370 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0755) Prec@1 88.000 (87.849) Prec@5 99.000 (99.151) +2022-11-14 16:19:07,381 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0755) Prec@1 88.000 (87.852) Prec@5 100.000 (99.167) +2022-11-14 16:19:07,393 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0754) Prec@1 87.000 (87.836) Prec@5 100.000 (99.182) +2022-11-14 16:19:07,403 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0754) Prec@1 89.000 (87.857) Prec@5 99.000 (99.179) +2022-11-14 16:19:07,415 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0753) Prec@1 87.000 (87.842) Prec@5 100.000 (99.193) +2022-11-14 16:19:07,427 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0750) Prec@1 90.000 (87.879) Prec@5 100.000 (99.207) +2022-11-14 16:19:07,440 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0755) Prec@1 85.000 (87.831) Prec@5 99.000 (99.203) +2022-11-14 16:19:07,450 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0757) Prec@1 83.000 (87.750) Prec@5 100.000 (99.217) +2022-11-14 16:19:07,460 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0759) Prec@1 87.000 (87.738) Prec@5 99.000 (99.213) +2022-11-14 16:19:07,471 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0756) Prec@1 90.000 (87.774) Prec@5 99.000 (99.210) +2022-11-14 16:19:07,482 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0754) Prec@1 88.000 (87.778) Prec@5 100.000 (99.222) +2022-11-14 16:19:07,495 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0750) Prec@1 92.000 (87.844) Prec@5 100.000 (99.234) +2022-11-14 16:19:07,506 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0751) Prec@1 88.000 (87.846) Prec@5 100.000 (99.246) +2022-11-14 16:19:07,518 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0752) Prec@1 86.000 (87.818) Prec@5 99.000 (99.242) +2022-11-14 16:19:07,528 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0750) Prec@1 89.000 (87.836) Prec@5 100.000 (99.254) +2022-11-14 16:19:07,539 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0751) Prec@1 88.000 (87.838) Prec@5 100.000 (99.265) +2022-11-14 16:19:07,549 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0751) Prec@1 87.000 (87.826) Prec@5 99.000 (99.261) +2022-11-14 16:19:07,562 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0752) Prec@1 86.000 (87.800) Prec@5 99.000 (99.257) +2022-11-14 16:19:07,572 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0757) Prec@1 85.000 (87.761) Prec@5 99.000 (99.254) +2022-11-14 16:19:07,582 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0755) Prec@1 89.000 (87.778) Prec@5 100.000 (99.264) +2022-11-14 16:19:07,593 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0483 (0.0751) Prec@1 92.000 (87.836) Prec@5 99.000 (99.260) +2022-11-14 16:19:07,604 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0449 (0.0747) Prec@1 94.000 (87.919) Prec@5 100.000 (99.270) +2022-11-14 16:19:07,616 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1198 (0.0753) Prec@1 80.000 (87.813) Prec@5 99.000 (99.267) +2022-11-14 16:19:07,627 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0752) Prec@1 88.000 (87.816) Prec@5 99.000 (99.263) +2022-11-14 16:19:07,638 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0751) Prec@1 89.000 (87.831) Prec@5 98.000 (99.247) +2022-11-14 16:19:07,650 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0754) Prec@1 85.000 (87.795) Prec@5 98.000 (99.231) +2022-11-14 16:19:07,662 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0755) Prec@1 88.000 (87.797) Prec@5 98.000 (99.215) +2022-11-14 16:19:07,672 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0754) Prec@1 88.000 (87.800) Prec@5 99.000 (99.213) +2022-11-14 16:19:07,683 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1097 (0.0758) Prec@1 85.000 (87.765) Prec@5 98.000 (99.198) +2022-11-14 16:19:07,693 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0758) Prec@1 86.000 (87.744) Prec@5 100.000 (99.207) +2022-11-14 16:19:07,704 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0757) Prec@1 90.000 (87.771) Prec@5 100.000 (99.217) +2022-11-14 16:19:07,714 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0756) Prec@1 88.000 (87.774) Prec@5 98.000 (99.202) +2022-11-14 16:19:07,724 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0758) Prec@1 85.000 (87.741) Prec@5 99.000 (99.200) +2022-11-14 16:19:07,734 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1076 (0.0762) Prec@1 85.000 (87.709) Prec@5 99.000 (99.198) +2022-11-14 16:19:07,745 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0763) Prec@1 86.000 (87.690) Prec@5 100.000 (99.207) +2022-11-14 16:19:07,757 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0762) Prec@1 89.000 (87.705) Prec@5 98.000 (99.193) +2022-11-14 16:19:07,769 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0762) Prec@1 89.000 (87.719) Prec@5 100.000 (99.202) +2022-11-14 16:19:07,780 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0763) Prec@1 87.000 (87.711) Prec@5 99.000 (99.200) +2022-11-14 16:19:07,789 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0416 (0.0759) Prec@1 94.000 (87.780) Prec@5 100.000 (99.209) +2022-11-14 16:19:07,799 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0758) Prec@1 88.000 (87.783) Prec@5 99.000 (99.207) +2022-11-14 16:19:07,811 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0758) Prec@1 87.000 (87.774) Prec@5 100.000 (99.215) +2022-11-14 16:19:07,822 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0758) Prec@1 89.000 (87.787) Prec@5 100.000 (99.223) +2022-11-14 16:19:07,834 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0945 (0.0759) Prec@1 85.000 (87.758) Prec@5 97.000 (99.200) +2022-11-14 16:19:07,847 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0761) Prec@1 87.000 (87.750) Prec@5 97.000 (99.177) +2022-11-14 16:19:07,862 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0758) Prec@1 92.000 (87.794) Prec@5 98.000 (99.165) +2022-11-14 16:19:07,876 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0760) Prec@1 84.000 (87.755) Prec@5 99.000 (99.163) +2022-11-14 16:19:07,890 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0761) Prec@1 86.000 (87.737) Prec@5 98.000 (99.152) +2022-11-14 16:19:07,905 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0760) Prec@1 89.000 (87.750) Prec@5 100.000 (99.160) +2022-11-14 16:19:07,966 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:19:08,329 Epoch: [329][0/500] Time 0.026 (0.026) Data 0.269 (0.269) Loss 0.0231 (0.0231) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:08,641 Epoch: [329][10/500] Time 0.028 (0.027) Data 0.002 (0.026) Loss 0.0278 (0.0255) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:19:08,974 Epoch: [329][20/500] Time 0.037 (0.028) Data 0.002 (0.015) Loss 0.0243 (0.0251) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:09,306 Epoch: [329][30/500] Time 0.030 (0.029) Data 0.002 (0.011) Loss 0.0548 (0.0325) Prec@1 90.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:19:09,806 Epoch: [329][40/500] Time 0.064 (0.032) Data 0.002 (0.008) Loss 0.0393 (0.0338) Prec@1 93.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 16:19:10,500 Epoch: [329][50/500] Time 0.064 (0.038) Data 0.002 (0.007) Loss 0.0485 (0.0363) Prec@1 91.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 16:19:11,252 Epoch: [329][60/500] Time 0.068 (0.043) Data 0.002 (0.006) Loss 0.0362 (0.0363) Prec@1 94.000 (93.714) Prec@5 99.000 (99.857) +2022-11-14 16:19:11,953 Epoch: [329][70/500] Time 0.066 (0.045) Data 0.002 (0.006) Loss 0.0375 (0.0364) Prec@1 94.000 (93.750) Prec@5 100.000 (99.875) +2022-11-14 16:19:12,708 Epoch: [329][80/500] Time 0.080 (0.048) Data 0.002 (0.005) Loss 0.0227 (0.0349) Prec@1 97.000 (94.111) Prec@5 100.000 (99.889) +2022-11-14 16:19:13,413 Epoch: [329][90/500] Time 0.074 (0.050) Data 0.003 (0.005) Loss 0.0391 (0.0353) Prec@1 93.000 (94.000) Prec@5 99.000 (99.800) +2022-11-14 16:19:14,111 Epoch: [329][100/500] Time 0.073 (0.051) Data 0.002 (0.005) Loss 0.0162 (0.0336) Prec@1 96.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 16:19:14,823 Epoch: [329][110/500] Time 0.065 (0.052) Data 0.002 (0.004) Loss 0.0183 (0.0323) Prec@1 97.000 (94.417) Prec@5 100.000 (99.833) +2022-11-14 16:19:15,528 Epoch: [329][120/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0257 (0.0318) Prec@1 94.000 (94.385) Prec@5 100.000 (99.846) +2022-11-14 16:19:16,222 Epoch: [329][130/500] Time 0.069 (0.054) Data 0.002 (0.004) Loss 0.0180 (0.0308) Prec@1 98.000 (94.643) Prec@5 100.000 (99.857) +2022-11-14 16:19:16,939 Epoch: [329][140/500] Time 0.063 (0.054) Data 0.002 (0.004) Loss 0.0299 (0.0308) Prec@1 95.000 (94.667) Prec@5 100.000 (99.867) +2022-11-14 16:19:17,656 Epoch: [329][150/500] Time 0.067 (0.055) Data 0.002 (0.004) Loss 0.0311 (0.0308) Prec@1 94.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 16:19:18,370 Epoch: [329][160/500] Time 0.073 (0.056) Data 0.002 (0.004) Loss 0.0501 (0.0319) Prec@1 89.000 (94.294) Prec@5 99.000 (99.824) +2022-11-14 16:19:19,072 Epoch: [329][170/500] Time 0.078 (0.056) Data 0.002 (0.004) Loss 0.0195 (0.0312) Prec@1 95.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:19:19,762 Epoch: [329][180/500] Time 0.059 (0.056) Data 0.002 (0.004) Loss 0.0501 (0.0322) Prec@1 93.000 (94.263) Prec@5 100.000 (99.842) +2022-11-14 16:19:20,502 Epoch: [329][190/500] Time 0.072 (0.057) Data 0.002 (0.003) Loss 0.0496 (0.0331) Prec@1 91.000 (94.100) Prec@5 100.000 (99.850) +2022-11-14 16:19:21,193 Epoch: [329][200/500] Time 0.058 (0.057) Data 0.002 (0.003) Loss 0.0304 (0.0330) Prec@1 94.000 (94.095) Prec@5 100.000 (99.857) +2022-11-14 16:19:21,915 Epoch: [329][210/500] Time 0.074 (0.057) Data 0.002 (0.003) Loss 0.0319 (0.0329) Prec@1 94.000 (94.091) Prec@5 100.000 (99.864) +2022-11-14 16:19:22,607 Epoch: [329][220/500] Time 0.074 (0.058) Data 0.002 (0.003) Loss 0.0350 (0.0330) Prec@1 93.000 (94.043) Prec@5 100.000 (99.870) +2022-11-14 16:19:23,299 Epoch: [329][230/500] Time 0.069 (0.058) Data 0.002 (0.003) Loss 0.0319 (0.0330) Prec@1 96.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 16:19:24,017 Epoch: [329][240/500] Time 0.067 (0.058) Data 0.002 (0.003) Loss 0.0207 (0.0325) Prec@1 97.000 (94.240) Prec@5 100.000 (99.880) +2022-11-14 16:19:24,728 Epoch: [329][250/500] Time 0.065 (0.058) Data 0.002 (0.003) Loss 0.0343 (0.0325) Prec@1 95.000 (94.269) Prec@5 100.000 (99.885) +2022-11-14 16:19:25,449 Epoch: [329][260/500] Time 0.070 (0.058) Data 0.002 (0.003) Loss 0.0281 (0.0324) Prec@1 97.000 (94.370) Prec@5 100.000 (99.889) +2022-11-14 16:19:26,158 Epoch: [329][270/500] Time 0.069 (0.059) Data 0.002 (0.003) Loss 0.0296 (0.0323) Prec@1 95.000 (94.393) Prec@5 100.000 (99.893) +2022-11-14 16:19:26,862 Epoch: [329][280/500] Time 0.075 (0.059) Data 0.002 (0.003) Loss 0.0292 (0.0322) Prec@1 92.000 (94.310) Prec@5 100.000 (99.897) +2022-11-14 16:19:27,564 Epoch: [329][290/500] Time 0.070 (0.059) Data 0.002 (0.003) Loss 0.0332 (0.0322) Prec@1 93.000 (94.267) Prec@5 100.000 (99.900) +2022-11-14 16:19:28,268 Epoch: [329][300/500] Time 0.062 (0.059) Data 0.002 (0.003) Loss 0.0302 (0.0321) Prec@1 95.000 (94.290) Prec@5 100.000 (99.903) +2022-11-14 16:19:28,988 Epoch: [329][310/500] Time 0.070 (0.059) Data 0.002 (0.003) Loss 0.0432 (0.0325) Prec@1 93.000 (94.250) Prec@5 100.000 (99.906) +2022-11-14 16:19:29,657 Epoch: [329][320/500] Time 0.069 (0.059) Data 0.002 (0.003) Loss 0.0398 (0.0327) Prec@1 91.000 (94.152) Prec@5 100.000 (99.909) +2022-11-14 16:19:30,291 Epoch: [329][330/500] Time 0.047 (0.059) Data 0.002 (0.003) Loss 0.0246 (0.0325) Prec@1 94.000 (94.147) Prec@5 100.000 (99.912) +2022-11-14 16:19:30,653 Epoch: [329][340/500] Time 0.036 (0.058) Data 0.002 (0.003) Loss 0.0407 (0.0327) Prec@1 94.000 (94.143) Prec@5 100.000 (99.914) +2022-11-14 16:19:31,010 Epoch: [329][350/500] Time 0.033 (0.058) Data 0.001 (0.003) Loss 0.0396 (0.0329) Prec@1 92.000 (94.083) Prec@5 100.000 (99.917) +2022-11-14 16:19:31,373 Epoch: [329][360/500] Time 0.036 (0.057) Data 0.002 (0.003) Loss 0.0279 (0.0328) Prec@1 96.000 (94.135) Prec@5 100.000 (99.919) +2022-11-14 16:19:31,743 Epoch: [329][370/500] Time 0.032 (0.056) Data 0.002 (0.003) Loss 0.0267 (0.0326) Prec@1 95.000 (94.158) Prec@5 100.000 (99.921) +2022-11-14 16:19:32,112 Epoch: [329][380/500] Time 0.032 (0.056) Data 0.002 (0.003) Loss 0.0350 (0.0327) Prec@1 93.000 (94.128) Prec@5 100.000 (99.923) +2022-11-14 16:19:32,476 Epoch: [329][390/500] Time 0.038 (0.055) Data 0.002 (0.003) Loss 0.0380 (0.0328) Prec@1 92.000 (94.075) Prec@5 100.000 (99.925) +2022-11-14 16:19:32,848 Epoch: [329][400/500] Time 0.042 (0.055) Data 0.002 (0.003) Loss 0.0416 (0.0330) Prec@1 93.000 (94.049) Prec@5 99.000 (99.902) +2022-11-14 16:19:33,208 Epoch: [329][410/500] Time 0.036 (0.054) Data 0.002 (0.003) Loss 0.0437 (0.0333) Prec@1 94.000 (94.048) Prec@5 98.000 (99.857) +2022-11-14 16:19:33,575 Epoch: [329][420/500] Time 0.036 (0.053) Data 0.002 (0.003) Loss 0.0461 (0.0336) Prec@1 95.000 (94.070) Prec@5 99.000 (99.837) +2022-11-14 16:19:33,946 Epoch: [329][430/500] Time 0.038 (0.053) Data 0.002 (0.003) Loss 0.0179 (0.0332) Prec@1 96.000 (94.114) Prec@5 100.000 (99.841) +2022-11-14 16:19:34,304 Epoch: [329][440/500] Time 0.037 (0.053) Data 0.002 (0.003) Loss 0.0270 (0.0331) Prec@1 95.000 (94.133) Prec@5 100.000 (99.844) +2022-11-14 16:19:34,672 Epoch: [329][450/500] Time 0.035 (0.052) Data 0.002 (0.003) Loss 0.0384 (0.0332) Prec@1 95.000 (94.152) Prec@5 100.000 (99.848) +2022-11-14 16:19:35,030 Epoch: [329][460/500] Time 0.039 (0.052) Data 0.002 (0.003) Loss 0.0395 (0.0333) Prec@1 92.000 (94.106) Prec@5 99.000 (99.830) +2022-11-14 16:19:35,409 Epoch: [329][470/500] Time 0.040 (0.051) Data 0.002 (0.003) Loss 0.0222 (0.0331) Prec@1 97.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 16:19:35,821 Epoch: [329][480/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0299 (0.0330) Prec@1 95.000 (94.184) Prec@5 100.000 (99.837) +2022-11-14 16:19:36,611 Epoch: [329][490/500] Time 0.073 (0.051) Data 0.002 (0.003) Loss 0.0188 (0.0327) Prec@1 96.000 (94.220) Prec@5 100.000 (99.840) +2022-11-14 16:19:37,285 Epoch: [329][499/500] Time 0.073 (0.052) Data 0.002 (0.003) Loss 0.0169 (0.0324) Prec@1 97.000 (94.275) Prec@5 100.000 (99.843) +2022-11-14 16:19:37,619 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0601 (0.0601) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:37,630 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0630 (0.0615) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:37,641 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0667) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:19:37,653 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0694) Prec@1 87.000 (88.000) Prec@5 97.000 (99.250) +2022-11-14 16:19:37,662 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0692) Prec@1 90.000 (88.400) Prec@5 99.000 (99.200) +2022-11-14 16:19:37,672 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0664) Prec@1 91.000 (88.833) Prec@5 100.000 (99.333) +2022-11-14 16:19:37,682 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0650) Prec@1 91.000 (89.143) Prec@5 100.000 (99.429) +2022-11-14 16:19:37,695 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0661) Prec@1 88.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:19:37,706 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0680) Prec@1 89.000 (89.000) Prec@5 99.000 (99.444) +2022-11-14 16:19:37,716 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0699) Prec@1 87.000 (88.800) Prec@5 98.000 (99.300) +2022-11-14 16:19:37,729 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0414 (0.0673) Prec@1 96.000 (89.455) Prec@5 100.000 (99.364) +2022-11-14 16:19:37,740 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0674) Prec@1 87.000 (89.250) Prec@5 99.000 (99.333) +2022-11-14 16:19:37,750 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0665) Prec@1 91.000 (89.385) Prec@5 100.000 (99.385) +2022-11-14 16:19:37,762 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0665) Prec@1 90.000 (89.429) Prec@5 99.000 (99.357) +2022-11-14 16:19:37,774 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0681) Prec@1 87.000 (89.267) Prec@5 100.000 (99.400) +2022-11-14 16:19:37,785 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0682) Prec@1 88.000 (89.188) Prec@5 100.000 (99.438) +2022-11-14 16:19:37,797 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0666) Prec@1 95.000 (89.529) Prec@5 98.000 (99.353) +2022-11-14 16:19:37,810 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0678) Prec@1 86.000 (89.333) Prec@5 100.000 (99.389) +2022-11-14 16:19:37,825 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0676) Prec@1 89.000 (89.316) Prec@5 99.000 (99.368) +2022-11-14 16:19:37,840 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0681) Prec@1 90.000 (89.350) Prec@5 100.000 (99.400) +2022-11-14 16:19:37,853 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0682) Prec@1 89.000 (89.333) Prec@5 100.000 (99.429) +2022-11-14 16:19:37,868 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0693) Prec@1 85.000 (89.136) Prec@5 99.000 (99.409) +2022-11-14 16:19:37,881 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0703) Prec@1 84.000 (88.913) Prec@5 99.000 (99.391) +2022-11-14 16:19:37,895 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0707) Prec@1 88.000 (88.875) Prec@5 100.000 (99.417) +2022-11-14 16:19:37,908 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0715) Prec@1 87.000 (88.800) Prec@5 100.000 (99.440) +2022-11-14 16:19:37,920 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0725) Prec@1 83.000 (88.577) Prec@5 98.000 (99.385) +2022-11-14 16:19:37,931 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0719) Prec@1 92.000 (88.704) Prec@5 100.000 (99.407) +2022-11-14 16:19:37,945 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0713) Prec@1 92.000 (88.821) Prec@5 100.000 (99.429) +2022-11-14 16:19:37,957 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0714) Prec@1 88.000 (88.793) Prec@5 99.000 (99.414) +2022-11-14 16:19:37,969 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0715) Prec@1 86.000 (88.700) Prec@5 100.000 (99.433) +2022-11-14 16:19:37,982 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0712) Prec@1 89.000 (88.710) Prec@5 99.000 (99.419) +2022-11-14 16:19:37,995 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0714) Prec@1 85.000 (88.594) Prec@5 99.000 (99.406) +2022-11-14 16:19:38,006 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0710) Prec@1 89.000 (88.606) Prec@5 100.000 (99.424) +2022-11-14 16:19:38,017 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0713) Prec@1 86.000 (88.529) Prec@5 99.000 (99.412) +2022-11-14 16:19:38,029 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0716) Prec@1 85.000 (88.429) Prec@5 98.000 (99.371) +2022-11-14 16:19:38,042 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0715) Prec@1 91.000 (88.500) Prec@5 100.000 (99.389) +2022-11-14 16:19:38,056 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0715) Prec@1 88.000 (88.486) Prec@5 98.000 (99.351) +2022-11-14 16:19:38,071 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0720) Prec@1 85.000 (88.395) Prec@5 100.000 (99.368) +2022-11-14 16:19:38,085 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0715) Prec@1 94.000 (88.538) Prec@5 99.000 (99.359) +2022-11-14 16:19:38,096 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0713) Prec@1 87.000 (88.500) Prec@5 99.000 (99.350) +2022-11-14 16:19:38,110 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0718) Prec@1 86.000 (88.439) Prec@5 98.000 (99.317) +2022-11-14 16:19:38,124 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0717) Prec@1 90.000 (88.476) Prec@5 98.000 (99.286) +2022-11-14 16:19:38,140 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0714) Prec@1 91.000 (88.535) Prec@5 100.000 (99.302) +2022-11-14 16:19:38,154 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0711) Prec@1 90.000 (88.568) Prec@5 97.000 (99.250) +2022-11-14 16:19:38,167 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0710) Prec@1 90.000 (88.600) Prec@5 100.000 (99.267) +2022-11-14 16:19:38,180 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0717) Prec@1 82.000 (88.457) Prec@5 100.000 (99.283) +2022-11-14 16:19:38,194 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0716) Prec@1 87.000 (88.426) Prec@5 100.000 (99.298) +2022-11-14 16:19:38,208 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0719) Prec@1 88.000 (88.417) Prec@5 99.000 (99.292) +2022-11-14 16:19:38,222 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0714) Prec@1 92.000 (88.490) Prec@5 100.000 (99.306) +2022-11-14 16:19:38,235 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0721) Prec@1 80.000 (88.320) Prec@5 99.000 (99.300) +2022-11-14 16:19:38,249 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0717) Prec@1 91.000 (88.373) Prec@5 99.000 (99.294) +2022-11-14 16:19:38,261 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0717) Prec@1 90.000 (88.404) Prec@5 99.000 (99.288) +2022-11-14 16:19:38,273 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0717) Prec@1 88.000 (88.396) Prec@5 99.000 (99.283) +2022-11-14 16:19:38,284 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0716) Prec@1 89.000 (88.407) Prec@5 99.000 (99.278) +2022-11-14 16:19:38,297 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0722) Prec@1 82.000 (88.291) Prec@5 100.000 (99.291) +2022-11-14 16:19:38,310 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0720) Prec@1 92.000 (88.357) Prec@5 99.000 (99.286) +2022-11-14 16:19:38,323 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0723) Prec@1 85.000 (88.298) Prec@5 100.000 (99.298) +2022-11-14 16:19:38,334 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0722) Prec@1 91.000 (88.345) Prec@5 100.000 (99.310) +2022-11-14 16:19:38,345 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0723) Prec@1 88.000 (88.339) Prec@5 100.000 (99.322) +2022-11-14 16:19:38,359 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0724) Prec@1 88.000 (88.333) Prec@5 99.000 (99.317) +2022-11-14 16:19:38,374 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0723) Prec@1 88.000 (88.328) Prec@5 99.000 (99.311) +2022-11-14 16:19:38,387 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0436 (0.0718) Prec@1 91.000 (88.371) Prec@5 100.000 (99.323) +2022-11-14 16:19:38,403 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0715) Prec@1 92.000 (88.429) Prec@5 100.000 (99.333) +2022-11-14 16:19:38,417 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0419 (0.0710) Prec@1 92.000 (88.484) Prec@5 100.000 (99.344) +2022-11-14 16:19:38,431 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0714) Prec@1 84.000 (88.415) Prec@5 99.000 (99.338) +2022-11-14 16:19:38,444 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0713) Prec@1 88.000 (88.409) Prec@5 99.000 (99.333) +2022-11-14 16:19:38,455 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0708) Prec@1 95.000 (88.507) Prec@5 100.000 (99.343) +2022-11-14 16:19:38,467 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0708) Prec@1 90.000 (88.529) Prec@5 99.000 (99.338) +2022-11-14 16:19:38,479 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0705) Prec@1 92.000 (88.580) Prec@5 99.000 (99.333) +2022-11-14 16:19:38,492 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0707) Prec@1 87.000 (88.557) Prec@5 98.000 (99.314) +2022-11-14 16:19:38,505 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0709) Prec@1 88.000 (88.549) Prec@5 99.000 (99.310) +2022-11-14 16:19:38,518 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0709) Prec@1 89.000 (88.556) Prec@5 100.000 (99.319) +2022-11-14 16:19:38,529 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0706) Prec@1 91.000 (88.589) Prec@5 100.000 (99.329) +2022-11-14 16:19:38,542 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0703) Prec@1 92.000 (88.635) Prec@5 99.000 (99.324) +2022-11-14 16:19:38,555 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0952 (0.0706) Prec@1 85.000 (88.587) Prec@5 100.000 (99.333) +2022-11-14 16:19:38,569 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0706) Prec@1 89.000 (88.592) Prec@5 100.000 (99.342) +2022-11-14 16:19:38,582 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0705) Prec@1 89.000 (88.597) Prec@5 99.000 (99.338) +2022-11-14 16:19:38,595 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0708) Prec@1 84.000 (88.538) Prec@5 98.000 (99.321) +2022-11-14 16:19:38,608 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0707) Prec@1 90.000 (88.557) Prec@5 100.000 (99.329) +2022-11-14 16:19:38,621 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0707) Prec@1 90.000 (88.575) Prec@5 99.000 (99.325) +2022-11-14 16:19:38,634 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0750 (0.0707) Prec@1 88.000 (88.568) Prec@5 100.000 (99.333) +2022-11-14 16:19:38,646 Test: [81/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0707) Prec@1 87.000 (88.549) Prec@5 99.000 (99.329) +2022-11-14 16:19:38,660 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0709) Prec@1 85.000 (88.506) Prec@5 100.000 (99.337) +2022-11-14 16:19:38,672 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0710) Prec@1 87.000 (88.488) Prec@5 97.000 (99.310) +2022-11-14 16:19:38,686 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0711) Prec@1 85.000 (88.447) Prec@5 100.000 (99.318) +2022-11-14 16:19:38,699 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0713) Prec@1 86.000 (88.419) Prec@5 100.000 (99.326) +2022-11-14 16:19:38,712 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0714) Prec@1 86.000 (88.391) Prec@5 99.000 (99.322) +2022-11-14 16:19:38,726 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0713) Prec@1 90.000 (88.409) Prec@5 98.000 (99.307) +2022-11-14 16:19:38,736 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0716) Prec@1 86.000 (88.382) Prec@5 100.000 (99.315) +2022-11-14 16:19:38,749 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0715) Prec@1 89.000 (88.389) Prec@5 99.000 (99.311) +2022-11-14 16:19:38,763 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0715) Prec@1 89.000 (88.396) Prec@5 100.000 (99.319) +2022-11-14 16:19:38,778 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0711) Prec@1 93.000 (88.446) Prec@5 99.000 (99.315) +2022-11-14 16:19:38,791 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0713) Prec@1 87.000 (88.430) Prec@5 100.000 (99.323) +2022-11-14 16:19:38,806 Test: [93/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0713) Prec@1 87.000 (88.415) Prec@5 99.000 (99.319) +2022-11-14 16:19:38,818 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0712) Prec@1 91.000 (88.442) Prec@5 100.000 (99.326) +2022-11-14 16:19:38,830 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0710) Prec@1 91.000 (88.469) Prec@5 100.000 (99.333) +2022-11-14 16:19:38,843 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0708) Prec@1 91.000 (88.495) Prec@5 99.000 (99.330) +2022-11-14 16:19:38,855 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0710) Prec@1 88.000 (88.490) Prec@5 100.000 (99.337) +2022-11-14 16:19:38,865 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0711) Prec@1 86.000 (88.465) Prec@5 100.000 (99.343) +2022-11-14 16:19:38,879 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0713) Prec@1 86.000 (88.440) Prec@5 99.000 (99.340) +2022-11-14 16:19:38,940 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:19:39,308 Epoch: [330][0/500] Time 0.035 (0.035) Data 0.268 (0.268) Loss 0.0333 (0.0333) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:39,571 Epoch: [330][10/500] Time 0.020 (0.025) Data 0.002 (0.026) Loss 0.0248 (0.0290) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:19:39,855 Epoch: [330][20/500] Time 0.028 (0.025) Data 0.002 (0.015) Loss 0.0218 (0.0266) Prec@1 97.000 (95.667) Prec@5 99.000 (99.667) +2022-11-14 16:19:40,258 Epoch: [330][30/500] Time 0.042 (0.028) Data 0.002 (0.011) Loss 0.0374 (0.0293) Prec@1 91.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:19:40,670 Epoch: [330][40/500] Time 0.040 (0.031) Data 0.002 (0.009) Loss 0.0152 (0.0265) Prec@1 99.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 16:19:41,079 Epoch: [330][50/500] Time 0.039 (0.032) Data 0.002 (0.007) Loss 0.0491 (0.0303) Prec@1 91.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:19:41,492 Epoch: [330][60/500] Time 0.036 (0.033) Data 0.003 (0.007) Loss 0.0399 (0.0317) Prec@1 94.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:19:41,918 Epoch: [330][70/500] Time 0.040 (0.033) Data 0.002 (0.006) Loss 0.0437 (0.0332) Prec@1 93.000 (94.375) Prec@5 99.000 (99.750) +2022-11-14 16:19:42,327 Epoch: [330][80/500] Time 0.042 (0.034) Data 0.002 (0.005) Loss 0.0357 (0.0334) Prec@1 93.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 16:19:42,749 Epoch: [330][90/500] Time 0.038 (0.034) Data 0.002 (0.005) Loss 0.0256 (0.0327) Prec@1 96.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:19:43,173 Epoch: [330][100/500] Time 0.030 (0.034) Data 0.003 (0.005) Loss 0.0527 (0.0345) Prec@1 90.000 (94.000) Prec@5 100.000 (99.818) +2022-11-14 16:19:43,608 Epoch: [330][110/500] Time 0.042 (0.035) Data 0.002 (0.005) Loss 0.0428 (0.0352) Prec@1 94.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 16:19:44,032 Epoch: [330][120/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0115 (0.0333) Prec@1 98.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 16:19:44,444 Epoch: [330][130/500] Time 0.042 (0.035) Data 0.002 (0.004) Loss 0.0406 (0.0339) Prec@1 94.000 (94.286) Prec@5 99.000 (99.786) +2022-11-14 16:19:44,847 Epoch: [330][140/500] Time 0.040 (0.035) Data 0.002 (0.004) Loss 0.0246 (0.0332) Prec@1 97.000 (94.467) Prec@5 100.000 (99.800) +2022-11-14 16:19:45,269 Epoch: [330][150/500] Time 0.034 (0.035) Data 0.002 (0.004) Loss 0.0206 (0.0325) Prec@1 95.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 16:19:45,861 Epoch: [330][160/500] Time 0.082 (0.036) Data 0.002 (0.004) Loss 0.0313 (0.0324) Prec@1 96.000 (94.588) Prec@5 100.000 (99.824) +2022-11-14 16:19:46,640 Epoch: [330][170/500] Time 0.074 (0.038) Data 0.003 (0.004) Loss 0.0195 (0.0317) Prec@1 96.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:19:47,446 Epoch: [330][180/500] Time 0.087 (0.040) Data 0.002 (0.004) Loss 0.0490 (0.0326) Prec@1 90.000 (94.421) Prec@5 100.000 (99.842) +2022-11-14 16:19:48,273 Epoch: [330][190/500] Time 0.076 (0.042) Data 0.002 (0.004) Loss 0.0313 (0.0325) Prec@1 95.000 (94.450) Prec@5 99.000 (99.800) +2022-11-14 16:19:49,095 Epoch: [330][200/500] Time 0.078 (0.043) Data 0.002 (0.003) Loss 0.0303 (0.0324) Prec@1 95.000 (94.476) Prec@5 100.000 (99.810) +2022-11-14 16:19:49,868 Epoch: [330][210/500] Time 0.072 (0.045) Data 0.002 (0.003) Loss 0.0296 (0.0323) Prec@1 96.000 (94.545) Prec@5 99.000 (99.773) +2022-11-14 16:19:50,703 Epoch: [330][220/500] Time 0.088 (0.046) Data 0.002 (0.003) Loss 0.0254 (0.0320) Prec@1 94.000 (94.522) Prec@5 100.000 (99.783) +2022-11-14 16:19:51,468 Epoch: [330][230/500] Time 0.073 (0.047) Data 0.002 (0.003) Loss 0.0481 (0.0327) Prec@1 91.000 (94.375) Prec@5 100.000 (99.792) +2022-11-14 16:19:52,298 Epoch: [330][240/500] Time 0.082 (0.048) Data 0.002 (0.003) Loss 0.0464 (0.0332) Prec@1 91.000 (94.240) Prec@5 99.000 (99.760) +2022-11-14 16:19:53,113 Epoch: [330][250/500] Time 0.084 (0.049) Data 0.002 (0.003) Loss 0.0223 (0.0328) Prec@1 97.000 (94.346) Prec@5 100.000 (99.769) +2022-11-14 16:19:53,924 Epoch: [330][260/500] Time 0.077 (0.050) Data 0.002 (0.003) Loss 0.0122 (0.0320) Prec@1 98.000 (94.481) Prec@5 100.000 (99.778) +2022-11-14 16:19:54,728 Epoch: [330][270/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0208 (0.0316) Prec@1 96.000 (94.536) Prec@5 100.000 (99.786) +2022-11-14 16:19:55,546 Epoch: [330][280/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0323 (0.0316) Prec@1 96.000 (94.586) Prec@5 100.000 (99.793) +2022-11-14 16:19:56,352 Epoch: [330][290/500] Time 0.075 (0.052) Data 0.002 (0.003) Loss 0.0411 (0.0320) Prec@1 94.000 (94.567) Prec@5 99.000 (99.767) +2022-11-14 16:19:57,122 Epoch: [330][300/500] Time 0.070 (0.053) Data 0.002 (0.003) Loss 0.0595 (0.0329) Prec@1 92.000 (94.484) Prec@5 100.000 (99.774) +2022-11-14 16:19:57,913 Epoch: [330][310/500] Time 0.075 (0.053) Data 0.002 (0.003) Loss 0.0345 (0.0329) Prec@1 94.000 (94.469) Prec@5 100.000 (99.781) +2022-11-14 16:19:58,733 Epoch: [330][320/500] Time 0.084 (0.054) Data 0.002 (0.003) Loss 0.0356 (0.0330) Prec@1 95.000 (94.485) Prec@5 98.000 (99.727) +2022-11-14 16:19:59,461 Epoch: [330][330/500] Time 0.064 (0.054) Data 0.002 (0.003) Loss 0.0222 (0.0327) Prec@1 97.000 (94.559) Prec@5 100.000 (99.735) +2022-11-14 16:20:00,214 Epoch: [330][340/500] Time 0.080 (0.055) Data 0.002 (0.003) Loss 0.0420 (0.0329) Prec@1 94.000 (94.543) Prec@5 100.000 (99.743) +2022-11-14 16:20:01,023 Epoch: [330][350/500] Time 0.077 (0.055) Data 0.002 (0.003) Loss 0.0319 (0.0329) Prec@1 95.000 (94.556) Prec@5 100.000 (99.750) +2022-11-14 16:20:01,788 Epoch: [330][360/500] Time 0.061 (0.056) Data 0.002 (0.003) Loss 0.0251 (0.0327) Prec@1 97.000 (94.622) Prec@5 100.000 (99.757) +2022-11-14 16:20:02,564 Epoch: [330][370/500] Time 0.082 (0.056) Data 0.003 (0.003) Loss 0.0342 (0.0327) Prec@1 93.000 (94.579) Prec@5 100.000 (99.763) +2022-11-14 16:20:03,233 Epoch: [330][380/500] Time 0.048 (0.056) Data 0.002 (0.003) Loss 0.0373 (0.0329) Prec@1 94.000 (94.564) Prec@5 100.000 (99.769) +2022-11-14 16:20:03,775 Epoch: [330][390/500] Time 0.045 (0.056) Data 0.002 (0.003) Loss 0.0423 (0.0331) Prec@1 92.000 (94.500) Prec@5 100.000 (99.775) +2022-11-14 16:20:04,305 Epoch: [330][400/500] Time 0.059 (0.056) Data 0.002 (0.003) Loss 0.0326 (0.0331) Prec@1 96.000 (94.537) Prec@5 100.000 (99.780) +2022-11-14 16:20:04,863 Epoch: [330][410/500] Time 0.054 (0.056) Data 0.002 (0.003) Loss 0.0368 (0.0332) Prec@1 92.000 (94.476) Prec@5 100.000 (99.786) +2022-11-14 16:20:05,410 Epoch: [330][420/500] Time 0.060 (0.055) Data 0.002 (0.003) Loss 0.0179 (0.0328) Prec@1 98.000 (94.558) Prec@5 100.000 (99.791) +2022-11-14 16:20:05,958 Epoch: [330][430/500] Time 0.059 (0.055) Data 0.002 (0.003) Loss 0.0552 (0.0333) Prec@1 92.000 (94.500) Prec@5 100.000 (99.795) +2022-11-14 16:20:06,527 Epoch: [330][440/500] Time 0.058 (0.055) Data 0.002 (0.003) Loss 0.0196 (0.0330) Prec@1 96.000 (94.533) Prec@5 100.000 (99.800) +2022-11-14 16:20:07,067 Epoch: [330][450/500] Time 0.056 (0.055) Data 0.002 (0.003) Loss 0.0416 (0.0332) Prec@1 92.000 (94.478) Prec@5 100.000 (99.804) +2022-11-14 16:20:07,634 Epoch: [330][460/500] Time 0.055 (0.055) Data 0.002 (0.003) Loss 0.0252 (0.0330) Prec@1 97.000 (94.532) Prec@5 100.000 (99.809) +2022-11-14 16:20:08,194 Epoch: [330][470/500] Time 0.051 (0.055) Data 0.002 (0.003) Loss 0.0452 (0.0333) Prec@1 92.000 (94.479) Prec@5 99.000 (99.792) +2022-11-14 16:20:08,749 Epoch: [330][480/500] Time 0.048 (0.055) Data 0.002 (0.003) Loss 0.0323 (0.0333) Prec@1 95.000 (94.490) Prec@5 100.000 (99.796) +2022-11-14 16:20:09,320 Epoch: [330][490/500] Time 0.054 (0.055) Data 0.002 (0.003) Loss 0.0386 (0.0334) Prec@1 94.000 (94.480) Prec@5 99.000 (99.780) +2022-11-14 16:20:09,816 Epoch: [330][499/500] Time 0.054 (0.055) Data 0.002 (0.003) Loss 0.0306 (0.0333) Prec@1 94.000 (94.471) Prec@5 100.000 (99.784) +2022-11-14 16:20:10,185 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0580 (0.0580) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:20:10,194 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0646 (0.0613) Prec@1 91.000 (90.500) Prec@5 99.000 (99.000) +2022-11-14 16:20:10,204 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0645) Prec@1 89.000 (90.000) Prec@5 100.000 (99.333) +2022-11-14 16:20:10,218 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0656) Prec@1 90.000 (90.000) Prec@5 99.000 (99.250) +2022-11-14 16:20:10,228 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0706) Prec@1 85.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 16:20:10,238 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0435 (0.0661) Prec@1 93.000 (89.667) Prec@5 100.000 (99.500) +2022-11-14 16:20:10,248 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0644) Prec@1 92.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 16:20:10,259 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0681) Prec@1 83.000 (89.125) Prec@5 100.000 (99.625) +2022-11-14 16:20:10,271 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0696) Prec@1 86.000 (88.778) Prec@5 100.000 (99.667) +2022-11-14 16:20:10,282 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0714) Prec@1 86.000 (88.500) Prec@5 99.000 (99.600) +2022-11-14 16:20:10,293 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0377 (0.0684) Prec@1 95.000 (89.091) Prec@5 100.000 (99.636) +2022-11-14 16:20:10,303 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0675) Prec@1 91.000 (89.250) Prec@5 100.000 (99.667) +2022-11-14 16:20:10,314 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0665) Prec@1 92.000 (89.462) Prec@5 100.000 (99.692) +2022-11-14 16:20:10,324 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0669) Prec@1 88.000 (89.357) Prec@5 99.000 (99.643) +2022-11-14 16:20:10,334 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0668) Prec@1 91.000 (89.467) Prec@5 100.000 (99.667) +2022-11-14 16:20:10,345 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0670) Prec@1 86.000 (89.250) Prec@5 100.000 (99.688) +2022-11-14 16:20:10,356 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0655) Prec@1 93.000 (89.471) Prec@5 99.000 (99.647) +2022-11-14 16:20:10,366 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1071 (0.0678) Prec@1 84.000 (89.167) Prec@5 99.000 (99.611) +2022-11-14 16:20:10,377 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0687) Prec@1 86.000 (89.000) Prec@5 98.000 (99.526) +2022-11-14 16:20:10,387 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0691) Prec@1 88.000 (88.950) Prec@5 99.000 (99.500) +2022-11-14 16:20:10,398 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0700) Prec@1 87.000 (88.857) Prec@5 99.000 (99.476) +2022-11-14 16:20:10,408 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0705) Prec@1 88.000 (88.818) Prec@5 99.000 (99.455) +2022-11-14 16:20:10,418 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0714) Prec@1 86.000 (88.696) Prec@5 97.000 (99.348) +2022-11-14 16:20:10,429 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0710) Prec@1 90.000 (88.750) Prec@5 100.000 (99.375) +2022-11-14 16:20:10,440 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0720) Prec@1 86.000 (88.640) Prec@5 100.000 (99.400) +2022-11-14 16:20:10,451 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0726) Prec@1 86.000 (88.538) Prec@5 99.000 (99.385) +2022-11-14 16:20:10,462 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0719) Prec@1 90.000 (88.593) Prec@5 100.000 (99.407) +2022-11-14 16:20:10,473 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0717) Prec@1 88.000 (88.571) Prec@5 100.000 (99.429) +2022-11-14 16:20:10,484 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0716) Prec@1 87.000 (88.517) Prec@5 100.000 (99.448) +2022-11-14 16:20:10,495 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0714) Prec@1 90.000 (88.567) Prec@5 100.000 (99.467) +2022-11-14 16:20:10,506 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0710) Prec@1 90.000 (88.613) Prec@5 98.000 (99.419) +2022-11-14 16:20:10,519 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0709) Prec@1 88.000 (88.594) Prec@5 100.000 (99.438) +2022-11-14 16:20:10,530 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0708) Prec@1 90.000 (88.636) Prec@5 100.000 (99.455) +2022-11-14 16:20:10,540 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0714) Prec@1 83.000 (88.471) Prec@5 100.000 (99.471) +2022-11-14 16:20:10,552 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0720) Prec@1 85.000 (88.371) Prec@5 98.000 (99.429) +2022-11-14 16:20:10,563 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0716) Prec@1 92.000 (88.472) Prec@5 99.000 (99.417) +2022-11-14 16:20:10,575 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0718) Prec@1 87.000 (88.432) Prec@5 99.000 (99.405) +2022-11-14 16:20:10,588 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0726) Prec@1 83.000 (88.289) Prec@5 100.000 (99.421) +2022-11-14 16:20:10,600 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0722) Prec@1 92.000 (88.385) Prec@5 100.000 (99.436) +2022-11-14 16:20:10,610 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0721) Prec@1 88.000 (88.375) Prec@5 99.000 (99.425) +2022-11-14 16:20:10,622 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0728) Prec@1 84.000 (88.268) Prec@5 98.000 (99.390) +2022-11-14 16:20:10,634 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0727) Prec@1 88.000 (88.262) Prec@5 99.000 (99.381) +2022-11-14 16:20:10,643 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0724) Prec@1 92.000 (88.349) Prec@5 99.000 (99.372) +2022-11-14 16:20:10,654 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0727) Prec@1 89.000 (88.364) Prec@5 98.000 (99.341) +2022-11-14 16:20:10,664 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0723) Prec@1 91.000 (88.422) Prec@5 100.000 (99.356) +2022-11-14 16:20:10,674 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0724) Prec@1 88.000 (88.413) Prec@5 99.000 (99.348) +2022-11-14 16:20:10,686 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0428 (0.0718) Prec@1 94.000 (88.532) Prec@5 100.000 (99.362) +2022-11-14 16:20:10,698 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0722) Prec@1 84.000 (88.438) Prec@5 98.000 (99.333) +2022-11-14 16:20:10,709 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0462 (0.0717) Prec@1 93.000 (88.531) Prec@5 100.000 (99.347) +2022-11-14 16:20:10,720 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1035 (0.0723) Prec@1 83.000 (88.420) Prec@5 99.000 (99.340) +2022-11-14 16:20:10,732 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0720) Prec@1 89.000 (88.431) Prec@5 100.000 (99.353) +2022-11-14 16:20:10,742 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0720) Prec@1 89.000 (88.442) Prec@5 100.000 (99.365) +2022-11-14 16:20:10,755 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0720) Prec@1 87.000 (88.415) Prec@5 100.000 (99.377) +2022-11-14 16:20:10,766 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0718) Prec@1 90.000 (88.444) Prec@5 100.000 (99.389) +2022-11-14 16:20:10,776 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0720) Prec@1 87.000 (88.418) Prec@5 100.000 (99.400) +2022-11-14 16:20:10,787 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0718) Prec@1 92.000 (88.482) Prec@5 99.000 (99.393) +2022-11-14 16:20:10,798 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0717) Prec@1 87.000 (88.456) Prec@5 100.000 (99.404) +2022-11-14 16:20:10,812 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0718) Prec@1 90.000 (88.483) Prec@5 99.000 (99.397) +2022-11-14 16:20:10,823 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0722) Prec@1 83.000 (88.390) Prec@5 99.000 (99.390) +2022-11-14 16:20:10,835 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0719) Prec@1 90.000 (88.417) Prec@5 100.000 (99.400) +2022-11-14 16:20:10,845 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0720) Prec@1 89.000 (88.426) Prec@5 100.000 (99.410) +2022-11-14 16:20:10,856 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0717) Prec@1 93.000 (88.500) Prec@5 99.000 (99.403) +2022-11-14 16:20:10,866 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0715) Prec@1 88.000 (88.492) Prec@5 100.000 (99.413) +2022-11-14 16:20:10,877 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0397 (0.0710) Prec@1 95.000 (88.594) Prec@5 99.000 (99.406) +2022-11-14 16:20:10,887 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0712) Prec@1 88.000 (88.585) Prec@5 99.000 (99.400) +2022-11-14 16:20:10,899 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0712) Prec@1 87.000 (88.561) Prec@5 100.000 (99.409) +2022-11-14 16:20:10,910 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0709) Prec@1 90.000 (88.582) Prec@5 99.000 (99.403) +2022-11-14 16:20:10,922 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0708) Prec@1 89.000 (88.588) Prec@5 100.000 (99.412) +2022-11-14 16:20:10,933 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0706) Prec@1 94.000 (88.667) Prec@5 100.000 (99.420) +2022-11-14 16:20:10,944 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0709) Prec@1 84.000 (88.600) Prec@5 98.000 (99.400) +2022-11-14 16:20:10,956 Test: [70/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0712) Prec@1 87.000 (88.577) Prec@5 99.000 (99.394) +2022-11-14 16:20:10,968 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0712) Prec@1 89.000 (88.583) Prec@5 100.000 (99.403) +2022-11-14 16:20:10,978 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0368 (0.0707) Prec@1 94.000 (88.658) Prec@5 100.000 (99.411) +2022-11-14 16:20:10,990 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0703) Prec@1 95.000 (88.743) Prec@5 100.000 (99.419) +2022-11-14 16:20:11,002 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0707) Prec@1 84.000 (88.680) Prec@5 99.000 (99.413) +2022-11-14 16:20:11,013 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0709) Prec@1 90.000 (88.697) Prec@5 99.000 (99.408) +2022-11-14 16:20:11,026 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0709) Prec@1 89.000 (88.701) Prec@5 98.000 (99.390) +2022-11-14 16:20:11,037 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0712) Prec@1 87.000 (88.679) Prec@5 97.000 (99.359) +2022-11-14 16:20:11,048 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0714) Prec@1 87.000 (88.658) Prec@5 100.000 (99.367) +2022-11-14 16:20:11,061 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0713) Prec@1 91.000 (88.688) Prec@5 100.000 (99.375) +2022-11-14 16:20:11,073 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0715) Prec@1 87.000 (88.667) Prec@5 97.000 (99.346) +2022-11-14 16:20:11,084 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0714) Prec@1 91.000 (88.695) Prec@5 100.000 (99.354) +2022-11-14 16:20:11,095 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0716) Prec@1 83.000 (88.627) Prec@5 99.000 (99.349) +2022-11-14 16:20:11,107 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0716) Prec@1 88.000 (88.619) Prec@5 99.000 (99.345) +2022-11-14 16:20:11,118 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0719) Prec@1 81.000 (88.529) Prec@5 98.000 (99.329) +2022-11-14 16:20:11,127 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1010 (0.0722) Prec@1 86.000 (88.500) Prec@5 99.000 (99.326) +2022-11-14 16:20:11,137 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0721) Prec@1 90.000 (88.517) Prec@5 100.000 (99.333) +2022-11-14 16:20:11,149 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0722) Prec@1 85.000 (88.477) Prec@5 98.000 (99.318) +2022-11-14 16:20:11,161 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0723) Prec@1 88.000 (88.472) Prec@5 97.000 (99.292) +2022-11-14 16:20:11,173 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0723) Prec@1 90.000 (88.489) Prec@5 100.000 (99.300) +2022-11-14 16:20:11,184 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0722) Prec@1 90.000 (88.505) Prec@5 100.000 (99.308) +2022-11-14 16:20:11,195 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0718) Prec@1 92.000 (88.543) Prec@5 100.000 (99.315) +2022-11-14 16:20:11,207 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0721) Prec@1 86.000 (88.516) Prec@5 100.000 (99.323) +2022-11-14 16:20:11,218 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0723) Prec@1 87.000 (88.500) Prec@5 99.000 (99.319) +2022-11-14 16:20:11,228 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0724) Prec@1 88.000 (88.495) Prec@5 98.000 (99.305) +2022-11-14 16:20:11,239 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0722) Prec@1 89.000 (88.500) Prec@5 99.000 (99.302) +2022-11-14 16:20:11,249 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0482 (0.0720) Prec@1 93.000 (88.546) Prec@5 99.000 (99.299) +2022-11-14 16:20:11,261 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0722) Prec@1 87.000 (88.531) Prec@5 98.000 (99.286) +2022-11-14 16:20:11,273 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0722) Prec@1 89.000 (88.535) Prec@5 100.000 (99.293) +2022-11-14 16:20:11,283 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0723) Prec@1 87.000 (88.520) Prec@5 99.000 (99.290) +2022-11-14 16:20:11,346 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:20:11,695 Epoch: [331][0/500] Time 0.028 (0.028) Data 0.263 (0.263) Loss 0.0337 (0.0337) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:20:12,003 Epoch: [331][10/500] Time 0.034 (0.027) Data 0.002 (0.026) Loss 0.0293 (0.0315) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:20:12,315 Epoch: [331][20/500] Time 0.033 (0.027) Data 0.002 (0.014) Loss 0.0488 (0.0372) Prec@1 93.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:20:12,630 Epoch: [331][30/500] Time 0.035 (0.027) Data 0.002 (0.010) Loss 0.0308 (0.0356) Prec@1 96.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 16:20:12,949 Epoch: [331][40/500] Time 0.026 (0.028) Data 0.002 (0.008) Loss 0.0129 (0.0311) Prec@1 98.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:20:13,338 Epoch: [331][50/500] Time 0.047 (0.029) Data 0.002 (0.007) Loss 0.0372 (0.0321) Prec@1 95.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 16:20:13,947 Epoch: [331][60/500] Time 0.061 (0.033) Data 0.003 (0.006) Loss 0.0250 (0.0311) Prec@1 95.000 (95.429) Prec@5 100.000 (99.857) +2022-11-14 16:20:14,593 Epoch: [331][70/500] Time 0.065 (0.036) Data 0.002 (0.006) Loss 0.0327 (0.0313) Prec@1 95.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:20:15,185 Epoch: [331][80/500] Time 0.057 (0.038) Data 0.002 (0.005) Loss 0.0332 (0.0315) Prec@1 96.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:20:15,825 Epoch: [331][90/500] Time 0.044 (0.040) Data 0.002 (0.005) Loss 0.0116 (0.0295) Prec@1 99.000 (95.800) Prec@5 100.000 (99.900) +2022-11-14 16:20:16,467 Epoch: [331][100/500] Time 0.058 (0.042) Data 0.002 (0.005) Loss 0.0442 (0.0309) Prec@1 94.000 (95.636) Prec@5 100.000 (99.909) +2022-11-14 16:20:17,079 Epoch: [331][110/500] Time 0.058 (0.043) Data 0.002 (0.004) Loss 0.0511 (0.0325) Prec@1 91.000 (95.250) Prec@5 100.000 (99.917) +2022-11-14 16:20:17,707 Epoch: [331][120/500] Time 0.055 (0.044) Data 0.002 (0.004) Loss 0.0224 (0.0318) Prec@1 96.000 (95.308) Prec@5 100.000 (99.923) +2022-11-14 16:20:18,326 Epoch: [331][130/500] Time 0.049 (0.045) Data 0.002 (0.004) Loss 0.0068 (0.0300) Prec@1 100.000 (95.643) Prec@5 100.000 (99.929) +2022-11-14 16:20:18,941 Epoch: [331][140/500] Time 0.061 (0.046) Data 0.002 (0.004) Loss 0.0367 (0.0304) Prec@1 92.000 (95.400) Prec@5 100.000 (99.933) +2022-11-14 16:20:19,566 Epoch: [331][150/500] Time 0.058 (0.046) Data 0.002 (0.004) Loss 0.0240 (0.0300) Prec@1 96.000 (95.438) Prec@5 100.000 (99.938) +2022-11-14 16:20:20,188 Epoch: [331][160/500] Time 0.055 (0.047) Data 0.002 (0.004) Loss 0.0434 (0.0308) Prec@1 92.000 (95.235) Prec@5 99.000 (99.882) +2022-11-14 16:20:20,787 Epoch: [331][170/500] Time 0.058 (0.047) Data 0.002 (0.004) Loss 0.0301 (0.0308) Prec@1 96.000 (95.278) Prec@5 100.000 (99.889) +2022-11-14 16:20:21,406 Epoch: [331][180/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0409 (0.0313) Prec@1 94.000 (95.211) Prec@5 100.000 (99.895) +2022-11-14 16:20:22,024 Epoch: [331][190/500] Time 0.065 (0.048) Data 0.002 (0.003) Loss 0.0491 (0.0322) Prec@1 93.000 (95.100) Prec@5 98.000 (99.800) +2022-11-14 16:20:22,657 Epoch: [331][200/500] Time 0.063 (0.049) Data 0.002 (0.003) Loss 0.0368 (0.0324) Prec@1 96.000 (95.143) Prec@5 99.000 (99.762) +2022-11-14 16:20:23,315 Epoch: [331][210/500] Time 0.071 (0.049) Data 0.003 (0.003) Loss 0.0193 (0.0318) Prec@1 98.000 (95.273) Prec@5 100.000 (99.773) +2022-11-14 16:20:23,934 Epoch: [331][220/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0334 (0.0319) Prec@1 93.000 (95.174) Prec@5 99.000 (99.739) +2022-11-14 16:20:24,568 Epoch: [331][230/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0422 (0.0323) Prec@1 91.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:20:25,195 Epoch: [331][240/500] Time 0.066 (0.050) Data 0.003 (0.003) Loss 0.0482 (0.0329) Prec@1 93.000 (94.920) Prec@5 99.000 (99.720) +2022-11-14 16:20:25,798 Epoch: [331][250/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0271 (0.0327) Prec@1 96.000 (94.962) Prec@5 100.000 (99.731) +2022-11-14 16:20:26,409 Epoch: [331][260/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0305 (0.0326) Prec@1 96.000 (95.000) Prec@5 100.000 (99.741) +2022-11-14 16:20:27,040 Epoch: [331][270/500] Time 0.068 (0.050) Data 0.002 (0.003) Loss 0.0293 (0.0325) Prec@1 96.000 (95.036) Prec@5 100.000 (99.750) +2022-11-14 16:20:27,650 Epoch: [331][280/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0243 (0.0322) Prec@1 96.000 (95.069) Prec@5 100.000 (99.759) +2022-11-14 16:20:28,257 Epoch: [331][290/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0393 (0.0325) Prec@1 93.000 (95.000) Prec@5 99.000 (99.733) +2022-11-14 16:20:28,884 Epoch: [331][300/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0498 (0.0330) Prec@1 91.000 (94.871) Prec@5 100.000 (99.742) +2022-11-14 16:20:29,500 Epoch: [331][310/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0200 (0.0326) Prec@1 96.000 (94.906) Prec@5 100.000 (99.750) +2022-11-14 16:20:30,135 Epoch: [331][320/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0360 (0.0327) Prec@1 93.000 (94.848) Prec@5 100.000 (99.758) +2022-11-14 16:20:30,764 Epoch: [331][330/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0361 (0.0328) Prec@1 94.000 (94.824) Prec@5 100.000 (99.765) +2022-11-14 16:20:31,447 Epoch: [331][340/500] Time 0.046 (0.051) Data 0.002 (0.003) Loss 0.0239 (0.0326) Prec@1 95.000 (94.829) Prec@5 100.000 (99.771) +2022-11-14 16:20:32,125 Epoch: [331][350/500] Time 0.066 (0.052) Data 0.002 (0.003) Loss 0.0199 (0.0322) Prec@1 99.000 (94.944) Prec@5 100.000 (99.778) +2022-11-14 16:20:32,773 Epoch: [331][360/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0464 (0.0326) Prec@1 94.000 (94.919) Prec@5 100.000 (99.784) +2022-11-14 16:20:33,469 Epoch: [331][370/500] Time 0.072 (0.052) Data 0.002 (0.003) Loss 0.0074 (0.0319) Prec@1 98.000 (95.000) Prec@5 100.000 (99.789) +2022-11-14 16:20:34,050 Epoch: [331][380/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0370 (0.0321) Prec@1 92.000 (94.923) Prec@5 100.000 (99.795) +2022-11-14 16:20:34,671 Epoch: [331][390/500] Time 0.073 (0.052) Data 0.002 (0.003) Loss 0.0405 (0.0323) Prec@1 92.000 (94.850) Prec@5 100.000 (99.800) +2022-11-14 16:20:35,359 Epoch: [331][400/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0157 (0.0319) Prec@1 97.000 (94.902) Prec@5 100.000 (99.805) +2022-11-14 16:20:35,994 Epoch: [331][410/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0185 (0.0316) Prec@1 98.000 (94.976) Prec@5 100.000 (99.810) +2022-11-14 16:20:36,610 Epoch: [331][420/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0392 (0.0317) Prec@1 94.000 (94.953) Prec@5 100.000 (99.814) +2022-11-14 16:20:37,263 Epoch: [331][430/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0346 (0.0318) Prec@1 94.000 (94.932) Prec@5 100.000 (99.818) +2022-11-14 16:20:37,919 Epoch: [331][440/500] Time 0.075 (0.053) Data 0.002 (0.003) Loss 0.0398 (0.0320) Prec@1 92.000 (94.867) Prec@5 100.000 (99.822) +2022-11-14 16:20:38,604 Epoch: [331][450/500] Time 0.076 (0.053) Data 0.002 (0.003) Loss 0.0206 (0.0317) Prec@1 97.000 (94.913) Prec@5 100.000 (99.826) +2022-11-14 16:20:39,232 Epoch: [331][460/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0498 (0.0321) Prec@1 94.000 (94.894) Prec@5 99.000 (99.809) +2022-11-14 16:20:39,879 Epoch: [331][470/500] Time 0.071 (0.053) Data 0.002 (0.003) Loss 0.0185 (0.0318) Prec@1 98.000 (94.958) Prec@5 100.000 (99.812) +2022-11-14 16:20:40,499 Epoch: [331][480/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0170 (0.0315) Prec@1 97.000 (95.000) Prec@5 100.000 (99.816) +2022-11-14 16:20:41,119 Epoch: [331][490/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0287 (0.0315) Prec@1 95.000 (95.000) Prec@5 100.000 (99.820) +2022-11-14 16:20:41,706 Epoch: [331][499/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0316 (0.0315) Prec@1 95.000 (95.000) Prec@5 100.000 (99.824) +2022-11-14 16:20:42,024 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0753 (0.0753) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:20:42,033 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0607 (0.0680) Prec@1 91.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:20:42,042 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0678) Prec@1 88.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:20:42,055 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0710) Prec@1 87.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 16:20:42,063 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0733) Prec@1 87.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 16:20:42,073 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0397 (0.0677) Prec@1 93.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 16:20:42,082 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0680) Prec@1 89.000 (88.857) Prec@5 99.000 (99.571) +2022-11-14 16:20:42,094 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0688) Prec@1 89.000 (88.875) Prec@5 99.000 (99.500) +2022-11-14 16:20:42,104 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0696) Prec@1 90.000 (89.000) Prec@5 100.000 (99.556) +2022-11-14 16:20:42,113 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0704) Prec@1 89.000 (89.000) Prec@5 98.000 (99.400) +2022-11-14 16:20:42,124 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0692) Prec@1 91.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 16:20:42,134 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0691) Prec@1 90.000 (89.250) Prec@5 99.000 (99.417) +2022-11-14 16:20:42,143 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0695) Prec@1 88.000 (89.154) Prec@5 99.000 (99.385) +2022-11-14 16:20:42,152 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0688) Prec@1 91.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 16:20:42,161 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0700) Prec@1 87.000 (89.133) Prec@5 99.000 (99.400) +2022-11-14 16:20:42,172 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0701) Prec@1 88.000 (89.062) Prec@5 99.000 (99.375) +2022-11-14 16:20:42,181 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0693) Prec@1 92.000 (89.235) Prec@5 98.000 (99.294) +2022-11-14 16:20:42,191 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1201 (0.0722) Prec@1 82.000 (88.833) Prec@5 99.000 (99.278) +2022-11-14 16:20:42,200 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0715) Prec@1 90.000 (88.895) Prec@5 98.000 (99.211) +2022-11-14 16:20:42,209 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1006 (0.0729) Prec@1 85.000 (88.700) Prec@5 97.000 (99.100) +2022-11-14 16:20:42,219 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0732) Prec@1 87.000 (88.619) Prec@5 98.000 (99.048) +2022-11-14 16:20:42,228 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0748) Prec@1 84.000 (88.409) Prec@5 99.000 (99.045) +2022-11-14 16:20:42,238 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0753) Prec@1 85.000 (88.261) Prec@5 99.000 (99.043) +2022-11-14 16:20:42,247 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0749) Prec@1 86.000 (88.167) Prec@5 100.000 (99.083) +2022-11-14 16:20:42,256 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0755) Prec@1 84.000 (88.000) Prec@5 99.000 (99.080) +2022-11-14 16:20:42,268 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0762) Prec@1 85.000 (87.885) Prec@5 99.000 (99.077) +2022-11-14 16:20:42,277 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0749) Prec@1 93.000 (88.074) Prec@5 100.000 (99.111) +2022-11-14 16:20:42,286 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0745) Prec@1 89.000 (88.107) Prec@5 100.000 (99.143) +2022-11-14 16:20:42,296 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0744) Prec@1 88.000 (88.103) Prec@5 98.000 (99.103) +2022-11-14 16:20:42,306 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0745) Prec@1 88.000 (88.100) Prec@5 100.000 (99.133) +2022-11-14 16:20:42,314 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0741) Prec@1 91.000 (88.194) Prec@5 100.000 (99.161) +2022-11-14 16:20:42,324 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0743) Prec@1 85.000 (88.094) Prec@5 100.000 (99.188) +2022-11-14 16:20:42,335 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0741) Prec@1 88.000 (88.091) Prec@5 99.000 (99.182) +2022-11-14 16:20:42,345 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0745) Prec@1 86.000 (88.029) Prec@5 98.000 (99.147) +2022-11-14 16:20:42,355 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0747) Prec@1 87.000 (88.000) Prec@5 97.000 (99.086) +2022-11-14 16:20:42,365 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0745) Prec@1 90.000 (88.056) Prec@5 100.000 (99.111) +2022-11-14 16:20:42,376 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0746) Prec@1 88.000 (88.054) Prec@5 98.000 (99.081) +2022-11-14 16:20:42,387 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0752) Prec@1 85.000 (87.974) Prec@5 98.000 (99.053) +2022-11-14 16:20:42,397 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0748) Prec@1 92.000 (88.077) Prec@5 99.000 (99.051) +2022-11-14 16:20:42,406 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0749) Prec@1 88.000 (88.075) Prec@5 97.000 (99.000) +2022-11-14 16:20:42,417 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0752) Prec@1 86.000 (88.024) Prec@5 99.000 (99.000) +2022-11-14 16:20:42,427 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0749) Prec@1 91.000 (88.095) Prec@5 99.000 (99.000) +2022-11-14 16:20:42,438 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0741) Prec@1 94.000 (88.233) Prec@5 98.000 (98.977) +2022-11-14 16:20:42,447 Test: 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Loss 0.1037 (0.0753) Prec@1 84.000 (88.020) Prec@5 100.000 (99.040) +2022-11-14 16:20:42,518 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0749) Prec@1 90.000 (88.059) Prec@5 99.000 (99.039) +2022-11-14 16:20:42,529 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0746) Prec@1 90.000 (88.096) Prec@5 99.000 (99.038) +2022-11-14 16:20:42,539 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0745) Prec@1 89.000 (88.113) Prec@5 100.000 (99.057) +2022-11-14 16:20:42,549 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0747) Prec@1 85.000 (88.056) Prec@5 99.000 (99.056) +2022-11-14 16:20:42,562 Test: [54/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0751) Prec@1 83.000 (87.964) Prec@5 100.000 (99.073) +2022-11-14 16:20:42,574 Test: [55/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0751) Prec@1 87.000 (87.946) Prec@5 99.000 (99.071) +2022-11-14 16:20:42,585 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0753) Prec@1 85.000 (87.895) Prec@5 100.000 (99.088) +2022-11-14 16:20:42,596 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0753) Prec@1 90.000 (87.931) Prec@5 100.000 (99.103) +2022-11-14 16:20:42,607 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1052 (0.0758) Prec@1 86.000 (87.898) Prec@5 100.000 (99.119) +2022-11-14 16:20:42,617 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0760) Prec@1 85.000 (87.850) Prec@5 100.000 (99.133) +2022-11-14 16:20:42,627 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0761) Prec@1 88.000 (87.852) Prec@5 98.000 (99.115) +2022-11-14 16:20:42,637 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0761) Prec@1 89.000 (87.871) Prec@5 98.000 (99.097) +2022-11-14 16:20:42,646 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0759) Prec@1 91.000 (87.921) Prec@5 100.000 (99.111) +2022-11-14 16:20:42,656 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0753) Prec@1 93.000 (88.000) Prec@5 99.000 (99.109) +2022-11-14 16:20:42,667 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1139 (0.0759) Prec@1 82.000 (87.908) Prec@5 100.000 (99.123) +2022-11-14 16:20:42,678 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0760) Prec@1 87.000 (87.894) Prec@5 98.000 (99.106) +2022-11-14 16:20:42,691 Test: [66/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0434 (0.0755) Prec@1 93.000 (87.970) Prec@5 99.000 (99.104) +2022-11-14 16:20:42,702 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0751) Prec@1 92.000 (88.029) Prec@5 98.000 (99.088) +2022-11-14 16:20:42,710 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0750) Prec@1 89.000 (88.043) Prec@5 99.000 (99.087) +2022-11-14 16:20:42,719 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0750) Prec@1 90.000 (88.071) Prec@5 100.000 (99.100) +2022-11-14 16:20:42,732 Test: [70/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1250 (0.0757) Prec@1 83.000 (88.000) Prec@5 98.000 (99.085) +2022-11-14 16:20:42,743 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0755) Prec@1 89.000 (88.014) Prec@5 100.000 (99.097) +2022-11-14 16:20:42,753 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0755) Prec@1 90.000 (88.041) Prec@5 99.000 (99.096) +2022-11-14 16:20:42,764 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0752) Prec@1 89.000 (88.054) Prec@5 100.000 (99.108) +2022-11-14 16:20:42,777 Test: [74/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0754) Prec@1 83.000 (87.987) Prec@5 100.000 (99.120) +2022-11-14 16:20:42,790 Test: [75/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0753) Prec@1 89.000 (88.000) Prec@5 100.000 (99.132) +2022-11-14 16:20:42,800 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0754) Prec@1 86.000 (87.974) Prec@5 99.000 (99.130) +2022-11-14 16:20:42,809 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0755) Prec@1 85.000 (87.936) Prec@5 99.000 (99.128) +2022-11-14 16:20:42,822 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0756) Prec@1 87.000 (87.924) Prec@5 99.000 (99.127) +2022-11-14 16:20:42,834 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0755) Prec@1 89.000 (87.938) Prec@5 98.000 (99.112) +2022-11-14 16:20:42,844 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1005 (0.0758) Prec@1 84.000 (87.889) Prec@5 99.000 (99.111) +2022-11-14 16:20:42,854 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0759) Prec@1 85.000 (87.854) Prec@5 99.000 (99.110) +2022-11-14 16:20:42,867 Test: [82/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0760) Prec@1 89.000 (87.867) Prec@5 100.000 (99.120) +2022-11-14 16:20:42,878 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0760) Prec@1 88.000 (87.869) Prec@5 100.000 (99.131) +2022-11-14 16:20:42,887 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0762) Prec@1 86.000 (87.847) Prec@5 100.000 (99.141) +2022-11-14 16:20:42,898 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0764) Prec@1 85.000 (87.814) Prec@5 99.000 (99.140) +2022-11-14 16:20:42,911 Test: [86/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0763) Prec@1 87.000 (87.805) Prec@5 98.000 (99.126) +2022-11-14 16:20:42,924 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0920 (0.0765) Prec@1 84.000 (87.761) Prec@5 97.000 (99.102) +2022-11-14 16:20:42,935 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0763) Prec@1 89.000 (87.775) Prec@5 100.000 (99.112) +2022-11-14 16:20:42,946 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0762) Prec@1 91.000 (87.811) Prec@5 99.000 (99.111) +2022-11-14 16:20:42,958 Test: [90/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0758) Prec@1 95.000 (87.890) Prec@5 100.000 (99.121) +2022-11-14 16:20:42,970 Test: [91/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0451 (0.0755) Prec@1 92.000 (87.935) Prec@5 100.000 (99.130) +2022-11-14 16:20:42,980 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0757) Prec@1 87.000 (87.925) Prec@5 100.000 (99.140) +2022-11-14 16:20:42,990 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0756) Prec@1 85.000 (87.894) Prec@5 100.000 (99.149) +2022-11-14 16:20:43,000 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0756) Prec@1 88.000 (87.895) Prec@5 100.000 (99.158) +2022-11-14 16:20:43,011 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0754) Prec@1 93.000 (87.948) Prec@5 98.000 (99.146) +2022-11-14 16:20:43,022 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0752) Prec@1 91.000 (87.979) Prec@5 98.000 (99.134) +2022-11-14 16:20:43,033 Test: [97/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0753) Prec@1 87.000 (87.969) Prec@5 100.000 (99.143) +2022-11-14 16:20:43,043 Test: [98/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0756) Prec@1 85.000 (87.939) Prec@5 98.000 (99.131) +2022-11-14 16:20:43,053 Test: [99/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0755) Prec@1 89.000 (87.950) Prec@5 100.000 (99.140) +2022-11-14 16:20:43,132 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:20:43,505 Epoch: [332][0/500] Time 0.026 (0.026) Data 0.280 (0.280) Loss 0.0332 (0.0332) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:20:43,764 Epoch: [332][10/500] Time 0.023 (0.023) Data 0.002 (0.027) Loss 0.0156 (0.0244) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:20:44,066 Epoch: [332][20/500] Time 0.036 (0.024) Data 0.002 (0.015) Loss 0.0504 (0.0331) Prec@1 95.000 (94.667) Prec@5 99.000 (99.667) +2022-11-14 16:20:44,454 Epoch: [332][30/500] Time 0.034 (0.028) Data 0.002 (0.011) Loss 0.0316 (0.0327) Prec@1 94.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:20:44,856 Epoch: [332][40/500] Time 0.036 (0.029) Data 0.002 (0.009) Loss 0.0527 (0.0367) Prec@1 91.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 16:20:45,238 Epoch: [332][50/500] Time 0.038 (0.030) Data 0.002 (0.008) Loss 0.0342 (0.0363) Prec@1 94.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 16:20:45,631 Epoch: [332][60/500] Time 0.035 (0.031) Data 0.002 (0.007) Loss 0.0225 (0.0343) Prec@1 97.000 (94.286) Prec@5 99.000 (99.714) +2022-11-14 16:20:46,027 Epoch: [332][70/500] Time 0.037 (0.032) Data 0.002 (0.006) Loss 0.0182 (0.0323) Prec@1 98.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:20:46,415 Epoch: [332][80/500] Time 0.036 (0.032) Data 0.002 (0.005) Loss 0.0516 (0.0345) Prec@1 91.000 (94.333) Prec@5 100.000 (99.778) +2022-11-14 16:20:46,811 Epoch: [332][90/500] Time 0.029 (0.032) Data 0.002 (0.005) Loss 0.0304 (0.0341) Prec@1 95.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:20:47,213 Epoch: [332][100/500] Time 0.033 (0.033) Data 0.002 (0.005) Loss 0.0372 (0.0344) Prec@1 91.000 (94.091) Prec@5 100.000 (99.818) +2022-11-14 16:20:47,611 Epoch: [332][110/500] Time 0.039 (0.033) Data 0.002 (0.005) Loss 0.0274 (0.0338) Prec@1 96.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 16:20:47,998 Epoch: [332][120/500] Time 0.029 (0.033) Data 0.002 (0.004) Loss 0.0343 (0.0338) Prec@1 95.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 16:20:48,391 Epoch: [332][130/500] Time 0.032 (0.033) Data 0.002 (0.004) Loss 0.0275 (0.0334) Prec@1 95.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 16:20:48,788 Epoch: [332][140/500] Time 0.042 (0.033) Data 0.002 (0.004) Loss 0.0326 (0.0333) Prec@1 95.000 (94.400) Prec@5 100.000 (99.867) +2022-11-14 16:20:49,354 Epoch: [332][150/500] Time 0.088 (0.035) Data 0.003 (0.004) Loss 0.0179 (0.0324) Prec@1 97.000 (94.562) Prec@5 100.000 (99.875) +2022-11-14 16:20:50,131 Epoch: [332][160/500] Time 0.066 (0.037) Data 0.002 (0.004) Loss 0.0382 (0.0327) Prec@1 92.000 (94.412) Prec@5 100.000 (99.882) +2022-11-14 16:20:50,965 Epoch: [332][170/500] Time 0.085 (0.039) Data 0.002 (0.004) Loss 0.0356 (0.0329) Prec@1 93.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 16:20:51,819 Epoch: [332][180/500] Time 0.079 (0.041) Data 0.002 (0.004) Loss 0.0399 (0.0332) Prec@1 94.000 (94.316) Prec@5 100.000 (99.895) +2022-11-14 16:20:52,839 Epoch: [332][190/500] Time 0.110 (0.044) Data 0.002 (0.004) Loss 0.0395 (0.0335) Prec@1 93.000 (94.250) Prec@5 100.000 (99.900) +2022-11-14 16:20:53,674 Epoch: [332][200/500] Time 0.081 (0.045) Data 0.002 (0.003) Loss 0.0217 (0.0330) Prec@1 97.000 (94.381) Prec@5 100.000 (99.905) +2022-11-14 16:20:54,494 Epoch: [332][210/500] Time 0.060 (0.046) Data 0.002 (0.003) Loss 0.0349 (0.0331) Prec@1 94.000 (94.364) Prec@5 100.000 (99.909) +2022-11-14 16:20:55,373 Epoch: [332][220/500] Time 0.088 (0.048) Data 0.002 (0.003) Loss 0.0249 (0.0327) Prec@1 97.000 (94.478) Prec@5 100.000 (99.913) +2022-11-14 16:20:56,166 Epoch: [332][230/500] Time 0.065 (0.049) Data 0.002 (0.003) Loss 0.0368 (0.0329) Prec@1 94.000 (94.458) Prec@5 100.000 (99.917) +2022-11-14 16:20:57,007 Epoch: [332][240/500] Time 0.079 (0.050) Data 0.002 (0.003) Loss 0.0249 (0.0326) Prec@1 95.000 (94.480) Prec@5 100.000 (99.920) +2022-11-14 16:20:57,817 Epoch: [332][250/500] Time 0.091 (0.051) Data 0.002 (0.003) Loss 0.0344 (0.0326) Prec@1 93.000 (94.423) Prec@5 100.000 (99.923) +2022-11-14 16:20:58,691 Epoch: [332][260/500] Time 0.086 (0.052) Data 0.002 (0.003) Loss 0.0355 (0.0327) Prec@1 94.000 (94.407) Prec@5 100.000 (99.926) +2022-11-14 16:20:59,485 Epoch: [332][270/500] Time 0.077 (0.053) Data 0.002 (0.003) Loss 0.0174 (0.0322) Prec@1 96.000 (94.464) Prec@5 100.000 (99.929) +2022-11-14 16:21:00,018 Epoch: [332][280/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0506 (0.0328) Prec@1 93.000 (94.414) Prec@5 99.000 (99.897) +2022-11-14 16:21:00,553 Epoch: [332][290/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0378 (0.0330) Prec@1 95.000 (94.433) Prec@5 100.000 (99.900) +2022-11-14 16:21:01,052 Epoch: [332][300/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0211 (0.0326) Prec@1 96.000 (94.484) Prec@5 100.000 (99.903) +2022-11-14 16:21:01,577 Epoch: [332][310/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0377 (0.0328) Prec@1 93.000 (94.438) Prec@5 100.000 (99.906) +2022-11-14 16:21:02,121 Epoch: [332][320/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0351 (0.0328) Prec@1 94.000 (94.424) Prec@5 100.000 (99.909) +2022-11-14 16:21:02,610 Epoch: [332][330/500] Time 0.040 (0.052) Data 0.002 (0.003) Loss 0.0260 (0.0326) Prec@1 94.000 (94.412) Prec@5 100.000 (99.912) +2022-11-14 16:21:03,135 Epoch: [332][340/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0252 (0.0324) Prec@1 96.000 (94.457) Prec@5 100.000 (99.914) +2022-11-14 16:21:03,658 Epoch: [332][350/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0263 (0.0322) Prec@1 96.000 (94.500) Prec@5 100.000 (99.917) +2022-11-14 16:21:04,167 Epoch: [332][360/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0141 (0.0318) Prec@1 99.000 (94.622) Prec@5 100.000 (99.919) +2022-11-14 16:21:04,683 Epoch: [332][370/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0348 (0.0318) Prec@1 95.000 (94.632) Prec@5 100.000 (99.921) +2022-11-14 16:21:05,181 Epoch: [332][380/500] Time 0.041 (0.051) Data 0.002 (0.003) Loss 0.0450 (0.0322) Prec@1 92.000 (94.564) Prec@5 99.000 (99.897) +2022-11-14 16:21:05,706 Epoch: [332][390/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0266 (0.0320) Prec@1 96.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 16:21:06,217 Epoch: [332][400/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0235 (0.0318) Prec@1 96.000 (94.634) Prec@5 100.000 (99.902) +2022-11-14 16:21:06,710 Epoch: [332][410/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0323 (0.0318) Prec@1 95.000 (94.643) Prec@5 100.000 (99.905) +2022-11-14 16:21:07,232 Epoch: [332][420/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0222 (0.0316) Prec@1 96.000 (94.674) Prec@5 100.000 (99.907) +2022-11-14 16:21:07,735 Epoch: [332][430/500] Time 0.044 (0.050) Data 0.003 (0.003) Loss 0.0465 (0.0320) Prec@1 93.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 16:21:08,255 Epoch: [332][440/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0233 (0.0318) Prec@1 97.000 (94.689) Prec@5 100.000 (99.911) +2022-11-14 16:21:08,778 Epoch: [332][450/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0203 (0.0315) Prec@1 98.000 (94.761) Prec@5 100.000 (99.913) +2022-11-14 16:21:09,293 Epoch: [332][460/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0187 (0.0312) Prec@1 97.000 (94.809) Prec@5 100.000 (99.915) +2022-11-14 16:21:09,820 Epoch: [332][470/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0390 (0.0314) Prec@1 96.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 16:21:10,344 Epoch: [332][480/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0383 (0.0315) Prec@1 96.000 (94.857) Prec@5 100.000 (99.918) +2022-11-14 16:21:10,876 Epoch: [332][490/500] Time 0.049 (0.050) Data 0.003 (0.003) Loss 0.0297 (0.0315) Prec@1 97.000 (94.900) Prec@5 100.000 (99.920) +2022-11-14 16:21:11,359 Epoch: [332][499/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0317 (0.0315) Prec@1 94.000 (94.882) Prec@5 99.000 (99.902) +2022-11-14 16:21:11,683 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0541 (0.0541) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 16:21:11,693 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0621) Prec@1 89.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 16:21:11,704 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0633) Prec@1 89.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:21:11,716 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0637) Prec@1 90.000 (89.750) Prec@5 99.000 (99.500) +2022-11-14 16:21:11,726 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0671) Prec@1 89.000 (89.600) Prec@5 99.000 (99.400) +2022-11-14 16:21:11,734 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0365 (0.0620) Prec@1 94.000 (90.333) Prec@5 100.000 (99.500) +2022-11-14 16:21:11,744 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0450 (0.0596) Prec@1 92.000 (90.571) Prec@5 100.000 (99.571) +2022-11-14 16:21:11,753 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0636) Prec@1 84.000 (89.750) Prec@5 100.000 (99.625) +2022-11-14 16:21:11,761 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0649) Prec@1 91.000 (89.889) Prec@5 99.000 (99.556) +2022-11-14 16:21:11,771 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0658) Prec@1 88.000 (89.700) Prec@5 99.000 (99.500) +2022-11-14 16:21:11,783 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0562 (0.0649) Prec@1 92.000 (89.909) Prec@5 100.000 (99.545) +2022-11-14 16:21:11,794 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0651) Prec@1 89.000 (89.833) Prec@5 100.000 (99.583) +2022-11-14 16:21:11,803 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0657) Prec@1 90.000 (89.846) Prec@5 100.000 (99.615) +2022-11-14 16:21:11,813 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0663) Prec@1 87.000 (89.643) Prec@5 100.000 (99.643) +2022-11-14 16:21:11,824 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0677) Prec@1 86.000 (89.400) Prec@5 100.000 (99.667) +2022-11-14 16:21:11,835 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0674) Prec@1 90.000 (89.438) Prec@5 99.000 (99.625) +2022-11-14 16:21:11,846 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0424 (0.0659) Prec@1 94.000 (89.706) Prec@5 99.000 (99.588) +2022-11-14 16:21:11,856 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1032 (0.0680) Prec@1 84.000 (89.389) Prec@5 99.000 (99.556) +2022-11-14 16:21:11,866 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0694) Prec@1 85.000 (89.158) Prec@5 98.000 (99.474) +2022-11-14 16:21:11,877 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0706) Prec@1 84.000 (88.900) Prec@5 97.000 (99.350) +2022-11-14 16:21:11,890 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0713) Prec@1 86.000 (88.762) Prec@5 100.000 (99.381) +2022-11-14 16:21:11,899 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1072 (0.0729) Prec@1 83.000 (88.500) Prec@5 99.000 (99.364) +2022-11-14 16:21:11,909 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0740) Prec@1 84.000 (88.304) Prec@5 98.000 (99.304) +2022-11-14 16:21:11,921 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0741) Prec@1 87.000 (88.250) Prec@5 100.000 (99.333) +2022-11-14 16:21:11,932 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0751) Prec@1 85.000 (88.120) Prec@5 100.000 (99.360) +2022-11-14 16:21:11,943 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0763) Prec@1 82.000 (87.885) Prec@5 98.000 (99.308) +2022-11-14 16:21:11,956 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0755) Prec@1 92.000 (88.037) Prec@5 100.000 (99.333) +2022-11-14 16:21:11,966 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0744) Prec@1 93.000 (88.214) Prec@5 100.000 (99.357) +2022-11-14 16:21:11,976 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0742) Prec@1 89.000 (88.241) Prec@5 99.000 (99.345) +2022-11-14 16:21:11,986 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0740) Prec@1 87.000 (88.200) Prec@5 100.000 (99.367) +2022-11-14 16:21:11,997 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0743) Prec@1 87.000 (88.161) Prec@5 100.000 (99.387) +2022-11-14 16:21:12,008 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0746) Prec@1 85.000 (88.062) Prec@5 99.000 (99.375) +2022-11-14 16:21:12,019 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0744) Prec@1 90.000 (88.121) Prec@5 100.000 (99.394) +2022-11-14 16:21:12,030 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0742) Prec@1 88.000 (88.118) Prec@5 100.000 (99.412) +2022-11-14 16:21:12,042 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0742) Prec@1 91.000 (88.200) Prec@5 98.000 (99.371) +2022-11-14 16:21:12,051 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0735) Prec@1 93.000 (88.333) Prec@5 100.000 (99.389) +2022-11-14 16:21:12,060 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0731) Prec@1 91.000 (88.405) Prec@5 100.000 (99.405) +2022-11-14 16:21:12,070 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1213 (0.0744) Prec@1 81.000 (88.211) Prec@5 99.000 (99.395) +2022-11-14 16:21:12,081 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0739) Prec@1 93.000 (88.333) Prec@5 99.000 (99.385) +2022-11-14 16:21:12,091 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0735) Prec@1 90.000 (88.375) Prec@5 98.000 (99.350) +2022-11-14 16:21:12,102 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0742) Prec@1 84.000 (88.268) Prec@5 98.000 (99.317) +2022-11-14 16:21:12,112 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0744) Prec@1 88.000 (88.262) Prec@5 98.000 (99.286) +2022-11-14 16:21:12,122 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0364 (0.0735) Prec@1 94.000 (88.395) Prec@5 99.000 (99.279) +2022-11-14 16:21:12,133 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0734) Prec@1 88.000 (88.386) Prec@5 99.000 (99.273) +2022-11-14 16:21:12,144 Test: [44/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0735) Prec@1 90.000 (88.422) Prec@5 98.000 (99.244) +2022-11-14 16:21:12,154 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0743) Prec@1 81.000 (88.261) Prec@5 100.000 (99.261) +2022-11-14 16:21:12,164 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0743) Prec@1 86.000 (88.213) Prec@5 100.000 (99.277) +2022-11-14 16:21:12,174 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1038 (0.0750) Prec@1 80.000 (88.042) Prec@5 98.000 (99.250) +2022-11-14 16:21:12,185 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0745) Prec@1 92.000 (88.122) Prec@5 100.000 (99.265) +2022-11-14 16:21:12,196 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1077 (0.0751) Prec@1 82.000 (88.000) Prec@5 99.000 (99.260) +2022-11-14 16:21:12,207 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0750) Prec@1 90.000 (88.039) Prec@5 100.000 (99.275) +2022-11-14 16:21:12,218 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0753) Prec@1 82.000 (87.923) Prec@5 100.000 (99.288) +2022-11-14 16:21:12,230 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0753) Prec@1 87.000 (87.906) Prec@5 100.000 (99.302) +2022-11-14 16:21:12,241 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0755) Prec@1 86.000 (87.870) Prec@5 99.000 (99.296) +2022-11-14 16:21:12,252 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0757) Prec@1 86.000 (87.836) Prec@5 100.000 (99.309) +2022-11-14 16:21:12,261 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0756) Prec@1 91.000 (87.893) Prec@5 98.000 (99.286) +2022-11-14 16:21:12,272 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0486 (0.0751) Prec@1 92.000 (87.965) Prec@5 99.000 (99.281) +2022-11-14 16:21:12,281 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0748) Prec@1 92.000 (88.034) Prec@5 100.000 (99.293) +2022-11-14 16:21:12,293 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0751) Prec@1 83.000 (87.949) Prec@5 99.000 (99.288) +2022-11-14 16:21:12,302 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0752) Prec@1 84.000 (87.883) Prec@5 100.000 (99.300) +2022-11-14 16:21:12,313 Test: [60/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0752) Prec@1 88.000 (87.885) Prec@5 99.000 (99.295) +2022-11-14 16:21:12,323 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0751) Prec@1 87.000 (87.871) Prec@5 100.000 (99.306) +2022-11-14 16:21:12,334 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0748) Prec@1 91.000 (87.921) Prec@5 98.000 (99.286) +2022-11-14 16:21:12,344 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0498 (0.0744) Prec@1 92.000 (87.984) Prec@5 99.000 (99.281) +2022-11-14 16:21:12,355 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1134 (0.0750) Prec@1 85.000 (87.938) Prec@5 99.000 (99.277) +2022-11-14 16:21:12,364 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0753) Prec@1 83.000 (87.864) Prec@5 98.000 (99.258) +2022-11-14 16:21:12,374 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0381 (0.0747) Prec@1 93.000 (87.940) Prec@5 99.000 (99.254) +2022-11-14 16:21:12,385 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0744) Prec@1 91.000 (87.985) Prec@5 100.000 (99.265) +2022-11-14 16:21:12,397 Test: [68/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0745) Prec@1 87.000 (87.971) Prec@5 99.000 (99.261) +2022-11-14 16:21:12,408 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0745) Prec@1 88.000 (87.971) Prec@5 100.000 (99.271) +2022-11-14 16:21:12,419 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0964 (0.0748) Prec@1 85.000 (87.930) Prec@5 98.000 (99.254) +2022-11-14 16:21:12,430 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0749) Prec@1 86.000 (87.903) Prec@5 99.000 (99.250) +2022-11-14 16:21:12,440 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0746) Prec@1 92.000 (87.959) Prec@5 100.000 (99.260) +2022-11-14 16:21:12,452 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0387 (0.0741) Prec@1 94.000 (88.041) Prec@5 100.000 (99.270) +2022-11-14 16:21:12,462 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0744) Prec@1 84.000 (87.987) Prec@5 100.000 (99.280) +2022-11-14 16:21:12,473 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0744) Prec@1 88.000 (87.987) Prec@5 99.000 (99.276) +2022-11-14 16:21:12,483 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0745) Prec@1 87.000 (87.974) Prec@5 99.000 (99.273) +2022-11-14 16:21:12,495 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0746) Prec@1 88.000 (87.974) Prec@5 100.000 (99.282) +2022-11-14 16:21:12,505 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0747) Prec@1 86.000 (87.949) Prec@5 100.000 (99.291) +2022-11-14 16:21:12,516 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0748) Prec@1 88.000 (87.950) Prec@5 100.000 (99.300) +2022-11-14 16:21:12,525 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0750) Prec@1 87.000 (87.938) Prec@5 98.000 (99.284) +2022-11-14 16:21:12,536 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0751) Prec@1 85.000 (87.902) Prec@5 99.000 (99.280) +2022-11-14 16:21:12,547 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0922 (0.0753) Prec@1 86.000 (87.880) Prec@5 100.000 (99.289) +2022-11-14 16:21:12,557 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0751) Prec@1 89.000 (87.893) Prec@5 99.000 (99.286) +2022-11-14 16:21:12,566 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0753) Prec@1 86.000 (87.871) Prec@5 100.000 (99.294) +2022-11-14 16:21:12,579 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1163 (0.0757) Prec@1 82.000 (87.802) Prec@5 99.000 (99.291) +2022-11-14 16:21:12,591 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0372 (0.0753) Prec@1 96.000 (87.897) Prec@5 100.000 (99.299) +2022-11-14 16:21:12,606 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0752) Prec@1 90.000 (87.920) Prec@5 99.000 (99.295) +2022-11-14 16:21:12,623 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0753) Prec@1 86.000 (87.899) Prec@5 99.000 (99.292) +2022-11-14 16:21:12,638 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0752) Prec@1 90.000 (87.922) Prec@5 99.000 (99.289) +2022-11-14 16:21:12,655 Test: [90/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0753) Prec@1 89.000 (87.934) Prec@5 100.000 (99.297) +2022-11-14 16:21:12,670 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0749) Prec@1 94.000 (88.000) Prec@5 98.000 (99.283) +2022-11-14 16:21:12,686 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0749) Prec@1 89.000 (88.011) Prec@5 99.000 (99.280) +2022-11-14 16:21:12,702 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0749) Prec@1 87.000 (88.000) Prec@5 100.000 (99.287) +2022-11-14 16:21:12,718 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0751) Prec@1 84.000 (87.958) Prec@5 99.000 (99.284) +2022-11-14 16:21:12,732 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0492 (0.0748) Prec@1 92.000 (88.000) Prec@5 100.000 (99.292) +2022-11-14 16:21:12,751 Test: [96/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0381 (0.0744) Prec@1 92.000 (88.041) Prec@5 99.000 (99.289) +2022-11-14 16:21:12,766 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0747) Prec@1 85.000 (88.010) Prec@5 99.000 (99.286) +2022-11-14 16:21:12,783 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0750) Prec@1 85.000 (87.980) Prec@5 99.000 (99.283) +2022-11-14 16:21:12,800 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0749) Prec@1 87.000 (87.970) Prec@5 99.000 (99.280) +2022-11-14 16:21:12,874 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:21:13,229 Epoch: [333][0/500] Time 0.024 (0.024) Data 0.267 (0.267) Loss 0.0244 (0.0244) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:21:13,517 Epoch: [333][10/500] Time 0.028 (0.026) Data 0.001 (0.026) Loss 0.0544 (0.0394) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:21:13,825 Epoch: [333][20/500] Time 0.025 (0.027) Data 0.002 (0.015) Loss 0.0433 (0.0407) Prec@1 92.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 16:21:14,141 Epoch: [333][30/500] Time 0.031 (0.027) Data 0.002 (0.011) Loss 0.0205 (0.0356) Prec@1 94.000 (93.750) Prec@5 100.000 (99.750) +2022-11-14 16:21:14,464 Epoch: [333][40/500] Time 0.033 (0.027) Data 0.002 (0.008) Loss 0.0409 (0.0367) Prec@1 93.000 (93.600) Prec@5 100.000 (99.800) +2022-11-14 16:21:14,974 Epoch: [333][50/500] Time 0.042 (0.031) Data 0.002 (0.007) Loss 0.0400 (0.0372) Prec@1 95.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 16:21:15,498 Epoch: [333][60/500] Time 0.045 (0.033) Data 0.002 (0.006) Loss 0.0212 (0.0349) Prec@1 97.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 16:21:16,042 Epoch: [333][70/500] Time 0.044 (0.036) Data 0.002 (0.006) Loss 0.0296 (0.0343) Prec@1 95.000 (94.375) Prec@5 99.000 (99.750) +2022-11-14 16:21:16,577 Epoch: [333][80/500] Time 0.066 (0.037) Data 0.002 (0.005) Loss 0.0189 (0.0326) Prec@1 97.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 16:21:17,167 Epoch: [333][90/500] Time 0.055 (0.039) Data 0.002 (0.005) Loss 0.0335 (0.0327) Prec@1 96.000 (94.800) Prec@5 99.000 (99.700) +2022-11-14 16:21:17,669 Epoch: [333][100/500] Time 0.046 (0.040) Data 0.002 (0.005) Loss 0.0476 (0.0340) Prec@1 94.000 (94.727) Prec@5 99.000 (99.636) +2022-11-14 16:21:18,209 Epoch: [333][110/500] Time 0.053 (0.040) Data 0.003 (0.005) Loss 0.0286 (0.0336) Prec@1 95.000 (94.750) Prec@5 100.000 (99.667) +2022-11-14 16:21:18,700 Epoch: [333][120/500] Time 0.050 (0.041) Data 0.002 (0.004) Loss 0.0265 (0.0330) Prec@1 97.000 (94.923) Prec@5 100.000 (99.692) +2022-11-14 16:21:19,217 Epoch: [333][130/500] Time 0.055 (0.041) Data 0.002 (0.004) Loss 0.0370 (0.0333) Prec@1 93.000 (94.786) Prec@5 100.000 (99.714) +2022-11-14 16:21:19,726 Epoch: [333][140/500] Time 0.056 (0.041) Data 0.002 (0.004) Loss 0.0206 (0.0325) Prec@1 95.000 (94.800) Prec@5 100.000 (99.733) +2022-11-14 16:21:20,226 Epoch: [333][150/500] Time 0.053 (0.042) Data 0.002 (0.004) Loss 0.0292 (0.0323) Prec@1 96.000 (94.875) Prec@5 100.000 (99.750) +2022-11-14 16:21:20,736 Epoch: [333][160/500] Time 0.051 (0.042) Data 0.002 (0.004) Loss 0.0178 (0.0314) Prec@1 96.000 (94.941) Prec@5 100.000 (99.765) +2022-11-14 16:21:21,240 Epoch: [333][170/500] Time 0.051 (0.042) Data 0.002 (0.004) Loss 0.0247 (0.0310) Prec@1 96.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 16:21:21,738 Epoch: [333][180/500] Time 0.053 (0.042) Data 0.002 (0.004) Loss 0.0205 (0.0305) Prec@1 97.000 (95.105) Prec@5 100.000 (99.789) +2022-11-14 16:21:22,248 Epoch: [333][190/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0308 (0.0305) Prec@1 96.000 (95.150) Prec@5 100.000 (99.800) +2022-11-14 16:21:22,747 Epoch: [333][200/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0294 (0.0304) Prec@1 96.000 (95.190) Prec@5 100.000 (99.810) +2022-11-14 16:21:23,242 Epoch: [333][210/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0212 (0.0300) Prec@1 97.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 16:21:23,762 Epoch: [333][220/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0306 (0.0300) Prec@1 95.000 (95.261) Prec@5 100.000 (99.826) +2022-11-14 16:21:24,268 Epoch: [333][230/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0294 (0.0300) Prec@1 96.000 (95.292) Prec@5 100.000 (99.833) +2022-11-14 16:21:24,772 Epoch: [333][240/500] Time 0.037 (0.043) Data 0.002 (0.003) Loss 0.0209 (0.0297) Prec@1 98.000 (95.400) Prec@5 100.000 (99.840) +2022-11-14 16:21:25,286 Epoch: [333][250/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0281 (0.0296) Prec@1 95.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:21:25,788 Epoch: [333][260/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0155 (0.0291) Prec@1 97.000 (95.444) Prec@5 100.000 (99.852) +2022-11-14 16:21:26,302 Epoch: [333][270/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0437 (0.0296) Prec@1 94.000 (95.393) Prec@5 100.000 (99.857) +2022-11-14 16:21:26,799 Epoch: [333][280/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0349 (0.0298) Prec@1 94.000 (95.345) Prec@5 100.000 (99.862) +2022-11-14 16:21:27,312 Epoch: [333][290/500] Time 0.051 (0.043) Data 0.002 (0.003) Loss 0.0306 (0.0298) Prec@1 94.000 (95.300) Prec@5 100.000 (99.867) +2022-11-14 16:21:27,812 Epoch: [333][300/500] Time 0.047 (0.043) Data 0.002 (0.003) Loss 0.0301 (0.0298) Prec@1 94.000 (95.258) Prec@5 100.000 (99.871) +2022-11-14 16:21:28,309 Epoch: [333][310/500] Time 0.060 (0.043) Data 0.002 (0.003) Loss 0.0349 (0.0300) Prec@1 94.000 (95.219) Prec@5 100.000 (99.875) +2022-11-14 16:21:28,834 Epoch: [333][320/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0325 (0.0300) Prec@1 93.000 (95.152) Prec@5 100.000 (99.879) +2022-11-14 16:21:29,355 Epoch: [333][330/500] Time 0.053 (0.044) Data 0.003 (0.003) Loss 0.0395 (0.0303) Prec@1 93.000 (95.088) Prec@5 99.000 (99.853) +2022-11-14 16:21:29,844 Epoch: [333][340/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0199 (0.0300) Prec@1 97.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:21:30,349 Epoch: [333][350/500] Time 0.056 (0.044) Data 0.002 (0.003) Loss 0.0274 (0.0300) Prec@1 94.000 (95.111) Prec@5 99.000 (99.833) +2022-11-14 16:21:30,846 Epoch: [333][360/500] Time 0.047 (0.044) Data 0.003 (0.003) Loss 0.0312 (0.0300) Prec@1 95.000 (95.108) Prec@5 100.000 (99.838) +2022-11-14 16:21:31,338 Epoch: [333][370/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0323 (0.0300) Prec@1 94.000 (95.079) Prec@5 99.000 (99.816) +2022-11-14 16:21:31,844 Epoch: [333][380/500] Time 0.054 (0.044) Data 0.002 (0.003) Loss 0.0372 (0.0302) Prec@1 95.000 (95.077) Prec@5 99.000 (99.795) +2022-11-14 16:21:32,345 Epoch: [333][390/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0332 (0.0303) Prec@1 95.000 (95.075) Prec@5 100.000 (99.800) +2022-11-14 16:21:32,856 Epoch: [333][400/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0341 (0.0304) Prec@1 94.000 (95.049) Prec@5 100.000 (99.805) +2022-11-14 16:21:33,372 Epoch: [333][410/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0290 (0.0304) Prec@1 94.000 (95.024) Prec@5 100.000 (99.810) +2022-11-14 16:21:33,883 Epoch: [333][420/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0254 (0.0302) Prec@1 96.000 (95.047) Prec@5 100.000 (99.814) +2022-11-14 16:21:34,400 Epoch: [333][430/500] Time 0.055 (0.044) Data 0.002 (0.003) Loss 0.0479 (0.0306) Prec@1 93.000 (95.000) Prec@5 99.000 (99.795) +2022-11-14 16:21:34,903 Epoch: [333][440/500] Time 0.035 (0.044) Data 0.002 (0.003) Loss 0.0214 (0.0304) Prec@1 96.000 (95.022) Prec@5 100.000 (99.800) +2022-11-14 16:21:35,402 Epoch: [333][450/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0224 (0.0303) Prec@1 95.000 (95.022) Prec@5 100.000 (99.804) +2022-11-14 16:21:35,918 Epoch: [333][460/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0254 (0.0302) Prec@1 97.000 (95.064) Prec@5 100.000 (99.809) +2022-11-14 16:21:36,422 Epoch: [333][470/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0083 (0.0297) Prec@1 98.000 (95.125) Prec@5 100.000 (99.812) +2022-11-14 16:21:36,940 Epoch: [333][480/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0749 (0.0306) Prec@1 85.000 (94.918) Prec@5 99.000 (99.796) +2022-11-14 16:21:37,466 Epoch: [333][490/500] Time 0.049 (0.044) Data 0.003 (0.003) Loss 0.0343 (0.0307) Prec@1 94.000 (94.900) Prec@5 99.000 (99.780) +2022-11-14 16:21:37,917 Epoch: [333][499/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0187 (0.0305) Prec@1 97.000 (94.941) Prec@5 100.000 (99.784) +2022-11-14 16:21:38,255 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0633 (0.0633) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:21:38,264 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0667 (0.0650) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:21:38,274 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0507 (0.0603) Prec@1 90.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 16:21:38,289 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0627) Prec@1 88.000 (89.250) Prec@5 98.000 (99.500) +2022-11-14 16:21:38,299 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0646) Prec@1 88.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:21:38,308 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0633) Prec@1 90.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:21:38,320 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0622) Prec@1 93.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 16:21:38,334 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0659) Prec@1 85.000 (89.125) Prec@5 98.000 (99.500) +2022-11-14 16:21:38,347 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0670) Prec@1 89.000 (89.111) Prec@5 100.000 (99.556) +2022-11-14 16:21:38,360 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0672) Prec@1 89.000 (89.100) Prec@5 99.000 (99.500) +2022-11-14 16:21:38,377 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0662) Prec@1 90.000 (89.182) Prec@5 100.000 (99.545) +2022-11-14 16:21:38,392 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0680) Prec@1 87.000 (89.000) Prec@5 100.000 (99.583) +2022-11-14 16:21:38,408 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0671) Prec@1 91.000 (89.154) Prec@5 100.000 (99.615) +2022-11-14 16:21:38,422 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0662) Prec@1 91.000 (89.286) Prec@5 100.000 (99.643) +2022-11-14 16:21:38,438 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0659) Prec@1 90.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:21:38,453 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0453 (0.0646) Prec@1 93.000 (89.562) Prec@5 99.000 (99.625) +2022-11-14 16:21:38,468 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0632) Prec@1 94.000 (89.824) Prec@5 98.000 (99.529) +2022-11-14 16:21:38,482 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1256 (0.0667) Prec@1 80.000 (89.278) Prec@5 100.000 (99.556) +2022-11-14 16:21:38,499 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0677) Prec@1 83.000 (88.947) Prec@5 99.000 (99.526) +2022-11-14 16:21:38,518 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0685) Prec@1 86.000 (88.800) Prec@5 98.000 (99.450) +2022-11-14 16:21:38,539 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0677) Prec@1 92.000 (88.952) Prec@5 100.000 (99.476) +2022-11-14 16:21:38,560 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0683) Prec@1 86.000 (88.818) Prec@5 100.000 (99.500) +2022-11-14 16:21:38,577 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0699) Prec@1 85.000 (88.652) Prec@5 98.000 (99.435) +2022-11-14 16:21:38,593 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0705) Prec@1 89.000 (88.667) Prec@5 100.000 (99.458) +2022-11-14 16:21:38,610 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.0718) Prec@1 84.000 (88.480) Prec@5 100.000 (99.480) +2022-11-14 16:21:38,624 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0723) Prec@1 88.000 (88.462) Prec@5 99.000 (99.462) +2022-11-14 16:21:38,638 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0717) Prec@1 91.000 (88.556) Prec@5 100.000 (99.481) +2022-11-14 16:21:38,660 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0712) Prec@1 91.000 (88.643) Prec@5 100.000 (99.500) +2022-11-14 16:21:38,681 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0713) Prec@1 87.000 (88.586) Prec@5 99.000 (99.483) +2022-11-14 16:21:38,698 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0712) Prec@1 91.000 (88.667) Prec@5 100.000 (99.500) +2022-11-14 16:21:38,716 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0708) Prec@1 91.000 (88.742) Prec@5 100.000 (99.516) +2022-11-14 16:21:38,735 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0706) Prec@1 91.000 (88.812) Prec@5 99.000 (99.500) +2022-11-14 16:21:38,756 Test: [32/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0707) Prec@1 86.000 (88.727) Prec@5 100.000 (99.515) +2022-11-14 16:21:38,775 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0712) Prec@1 85.000 (88.618) Prec@5 99.000 (99.500) +2022-11-14 16:21:38,792 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0710) Prec@1 90.000 (88.657) Prec@5 99.000 (99.486) +2022-11-14 16:21:38,807 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0705) Prec@1 92.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 16:21:38,822 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0705) Prec@1 87.000 (88.703) Prec@5 99.000 (99.486) +2022-11-14 16:21:38,841 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0711) Prec@1 84.000 (88.579) Prec@5 99.000 (99.474) +2022-11-14 16:21:38,859 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0492 (0.0706) Prec@1 93.000 (88.692) Prec@5 99.000 (99.462) +2022-11-14 16:21:38,879 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0708) Prec@1 87.000 (88.650) Prec@5 99.000 (99.450) +2022-11-14 16:21:38,900 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0712) Prec@1 88.000 (88.634) Prec@5 99.000 (99.439) +2022-11-14 16:21:38,918 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0708) Prec@1 91.000 (88.690) Prec@5 99.000 (99.429) +2022-11-14 16:21:38,935 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0353 (0.0700) Prec@1 96.000 (88.860) Prec@5 100.000 (99.442) +2022-11-14 16:21:38,956 Test: [43/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0697) Prec@1 91.000 (88.909) Prec@5 99.000 (99.432) +2022-11-14 16:21:38,974 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0695) Prec@1 90.000 (88.933) Prec@5 100.000 (99.444) +2022-11-14 16:21:38,992 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0704) Prec@1 82.000 (88.783) Prec@5 100.000 (99.457) +2022-11-14 16:21:39,009 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0704) Prec@1 85.000 (88.702) Prec@5 100.000 (99.468) +2022-11-14 16:21:39,025 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0712) Prec@1 83.000 (88.583) Prec@5 98.000 (99.438) +2022-11-14 16:21:39,042 Test: [48/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0421 (0.0706) Prec@1 94.000 (88.694) Prec@5 100.000 (99.449) +2022-11-14 16:21:39,058 Test: [49/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0710) Prec@1 85.000 (88.620) Prec@5 100.000 (99.460) +2022-11-14 16:21:39,075 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0710) Prec@1 89.000 (88.627) Prec@5 100.000 (99.471) +2022-11-14 16:21:39,092 Test: [51/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0712) Prec@1 86.000 (88.577) Prec@5 98.000 (99.442) +2022-11-14 16:21:39,110 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0712) Prec@1 89.000 (88.585) Prec@5 100.000 (99.453) +2022-11-14 16:21:39,127 Test: [53/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0713) Prec@1 88.000 (88.574) Prec@5 99.000 (99.444) +2022-11-14 16:21:39,143 Test: [54/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0714) Prec@1 88.000 (88.564) Prec@5 99.000 (99.436) +2022-11-14 16:21:39,161 Test: [55/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0589 (0.0711) Prec@1 91.000 (88.607) Prec@5 98.000 (99.411) +2022-11-14 16:21:39,179 Test: [56/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0712) Prec@1 88.000 (88.596) Prec@5 99.000 (99.404) +2022-11-14 16:21:39,196 Test: [57/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0713) Prec@1 88.000 (88.586) Prec@5 100.000 (99.414) +2022-11-14 16:21:39,212 Test: [58/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1020 (0.0718) Prec@1 84.000 (88.508) Prec@5 98.000 (99.390) +2022-11-14 16:21:39,228 Test: [59/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0720) Prec@1 86.000 (88.467) Prec@5 100.000 (99.400) +2022-11-14 16:21:39,244 Test: [60/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0719) Prec@1 91.000 (88.508) Prec@5 98.000 (99.377) +2022-11-14 16:21:39,264 Test: [61/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0804 (0.0720) Prec@1 90.000 (88.532) Prec@5 99.000 (99.371) +2022-11-14 16:21:39,281 Test: [62/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0719) Prec@1 90.000 (88.556) Prec@5 99.000 (99.365) +2022-11-14 16:21:39,299 Test: [63/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0328 (0.0713) Prec@1 93.000 (88.625) Prec@5 100.000 (99.375) +2022-11-14 16:21:39,316 Test: [64/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1086 (0.0719) Prec@1 81.000 (88.508) Prec@5 99.000 (99.369) +2022-11-14 16:21:39,332 Test: [65/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0721) Prec@1 86.000 (88.470) Prec@5 99.000 (99.364) +2022-11-14 16:21:39,349 Test: [66/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0506 (0.0717) Prec@1 92.000 (88.522) Prec@5 98.000 (99.343) +2022-11-14 16:21:39,366 Test: [67/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0717) Prec@1 91.000 (88.559) Prec@5 97.000 (99.309) +2022-11-14 16:21:39,383 Test: [68/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0718) Prec@1 87.000 (88.536) Prec@5 99.000 (99.304) +2022-11-14 16:21:39,401 Test: [69/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0717) Prec@1 92.000 (88.586) Prec@5 99.000 (99.300) +2022-11-14 16:21:39,419 Test: [70/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1123 (0.0722) Prec@1 85.000 (88.535) Prec@5 99.000 (99.296) +2022-11-14 16:21:39,434 Test: [71/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0535 (0.0720) Prec@1 91.000 (88.569) Prec@5 99.000 (99.292) +2022-11-14 16:21:39,451 Test: [72/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0438 (0.0716) Prec@1 93.000 (88.630) Prec@5 100.000 (99.301) +2022-11-14 16:21:39,467 Test: [73/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0484 (0.0713) Prec@1 94.000 (88.703) Prec@5 100.000 (99.311) +2022-11-14 16:21:39,483 Test: [74/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0715) Prec@1 87.000 (88.680) Prec@5 100.000 (99.320) +2022-11-14 16:21:39,499 Test: [75/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0693 (0.0715) Prec@1 88.000 (88.671) Prec@5 99.000 (99.316) +2022-11-14 16:21:39,518 Test: [76/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0557 (0.0713) Prec@1 91.000 (88.701) Prec@5 99.000 (99.312) +2022-11-14 16:21:39,535 Test: [77/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0715) Prec@1 87.000 (88.679) Prec@5 98.000 (99.295) +2022-11-14 16:21:39,551 Test: [78/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0713) Prec@1 90.000 (88.696) Prec@5 100.000 (99.304) +2022-11-14 16:21:39,571 Test: [79/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0712) Prec@1 91.000 (88.725) Prec@5 100.000 (99.312) +2022-11-14 16:21:39,590 Test: [80/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0912 (0.0715) Prec@1 86.000 (88.691) Prec@5 98.000 (99.296) +2022-11-14 16:21:39,608 Test: [81/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0859 (0.0716) Prec@1 88.000 (88.683) Prec@5 99.000 (99.293) +2022-11-14 16:21:39,625 Test: [82/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0922 (0.0719) Prec@1 83.000 (88.614) Prec@5 100.000 (99.301) +2022-11-14 16:21:39,641 Test: [83/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0488 (0.0716) Prec@1 90.000 (88.631) Prec@5 99.000 (99.298) +2022-11-14 16:21:39,658 Test: [84/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0929 (0.0718) Prec@1 84.000 (88.576) Prec@5 100.000 (99.306) +2022-11-14 16:21:39,676 Test: [85/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0834 (0.0720) Prec@1 89.000 (88.581) Prec@5 99.000 (99.302) +2022-11-14 16:21:39,691 Test: [86/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0674 (0.0719) Prec@1 88.000 (88.575) Prec@5 100.000 (99.310) +2022-11-14 16:21:39,709 Test: [87/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0760 (0.0720) Prec@1 87.000 (88.557) Prec@5 98.000 (99.295) +2022-11-14 16:21:39,724 Test: [88/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0878 (0.0722) Prec@1 84.000 (88.506) Prec@5 100.000 (99.303) +2022-11-14 16:21:39,742 Test: [89/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0894 (0.0723) Prec@1 86.000 (88.478) Prec@5 100.000 (99.311) +2022-11-14 16:21:39,759 Test: [90/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0446 (0.0720) Prec@1 94.000 (88.538) Prec@5 100.000 (99.319) +2022-11-14 16:21:39,776 Test: [91/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0516 (0.0718) Prec@1 91.000 (88.565) Prec@5 100.000 (99.326) +2022-11-14 16:21:39,794 Test: [92/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0799 (0.0719) Prec@1 88.000 (88.559) Prec@5 99.000 (99.323) +2022-11-14 16:21:39,810 Test: [93/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0886 (0.0721) Prec@1 88.000 (88.553) Prec@5 99.000 (99.319) +2022-11-14 16:21:39,829 Test: [94/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.0722) Prec@1 87.000 (88.537) Prec@5 100.000 (99.326) +2022-11-14 16:21:39,845 Test: [95/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0515 (0.0719) Prec@1 93.000 (88.583) Prec@5 98.000 (99.312) +2022-11-14 16:21:39,863 Test: [96/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0630 (0.0719) Prec@1 90.000 (88.598) Prec@5 99.000 (99.309) +2022-11-14 16:21:39,880 Test: [97/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0997 (0.0721) Prec@1 86.000 (88.571) Prec@5 99.000 (99.306) +2022-11-14 16:21:39,898 Test: [98/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0855 (0.0723) Prec@1 87.000 (88.556) Prec@5 100.000 (99.313) +2022-11-14 16:21:39,915 Test: [99/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0655 (0.0722) Prec@1 90.000 (88.570) Prec@5 100.000 (99.320) +2022-11-14 16:21:40,041 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:21:40,526 Epoch: [334][0/500] Time 0.029 (0.029) Data 0.367 (0.367) Loss 0.0267 (0.0267) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:21:40,804 Epoch: [334][10/500] Time 0.028 (0.025) Data 0.002 (0.035) Loss 0.0427 (0.0347) Prec@1 91.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:21:41,137 Epoch: [334][20/500] Time 0.041 (0.027) Data 0.002 (0.019) Loss 0.0184 (0.0293) Prec@1 96.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:21:41,628 Epoch: [334][30/500] Time 0.050 (0.032) Data 0.003 (0.014) Loss 0.0241 (0.0280) Prec@1 96.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:21:42,155 Epoch: [334][40/500] Time 0.048 (0.036) Data 0.002 (0.011) Loss 0.0146 (0.0253) Prec@1 98.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:21:42,653 Epoch: [334][50/500] Time 0.053 (0.038) Data 0.002 (0.009) Loss 0.0179 (0.0241) Prec@1 98.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:21:43,160 Epoch: [334][60/500] Time 0.043 (0.039) Data 0.002 (0.008) Loss 0.0378 (0.0260) Prec@1 95.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 16:21:43,668 Epoch: [334][70/500] Time 0.050 (0.040) Data 0.002 (0.007) Loss 0.0293 (0.0264) Prec@1 95.000 (95.625) Prec@5 100.000 (100.000) +2022-11-14 16:21:44,163 Epoch: [334][80/500] Time 0.051 (0.040) Data 0.002 (0.007) Loss 0.0282 (0.0266) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:21:44,652 Epoch: [334][90/500] Time 0.041 (0.041) Data 0.002 (0.006) Loss 0.0244 (0.0264) Prec@1 96.000 (95.700) Prec@5 100.000 (100.000) +2022-11-14 16:21:45,144 Epoch: [334][100/500] Time 0.051 (0.041) Data 0.002 (0.006) Loss 0.0358 (0.0273) Prec@1 92.000 (95.364) Prec@5 99.000 (99.909) +2022-11-14 16:21:45,683 Epoch: [334][110/500] Time 0.054 (0.042) Data 0.002 (0.005) Loss 0.0458 (0.0288) Prec@1 93.000 (95.167) Prec@5 99.000 (99.833) +2022-11-14 16:21:46,208 Epoch: [334][120/500] Time 0.048 (0.042) Data 0.002 (0.005) Loss 0.0280 (0.0288) Prec@1 94.000 (95.077) Prec@5 100.000 (99.846) +2022-11-14 16:21:46,713 Epoch: [334][130/500] Time 0.047 (0.042) Data 0.002 (0.005) Loss 0.0143 (0.0277) Prec@1 99.000 (95.357) Prec@5 100.000 (99.857) +2022-11-14 16:21:47,213 Epoch: [334][140/500] Time 0.042 (0.042) Data 0.003 (0.005) Loss 0.0250 (0.0276) Prec@1 96.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:21:47,703 Epoch: [334][150/500] Time 0.048 (0.043) Data 0.002 (0.005) Loss 0.0075 (0.0263) Prec@1 99.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 16:21:48,221 Epoch: [334][160/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0324 (0.0267) Prec@1 93.000 (95.471) Prec@5 100.000 (99.882) +2022-11-14 16:21:48,718 Epoch: [334][170/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0221 (0.0264) Prec@1 98.000 (95.611) Prec@5 100.000 (99.889) +2022-11-14 16:21:49,219 Epoch: [334][180/500] Time 0.040 (0.043) Data 0.002 (0.004) Loss 0.0272 (0.0265) Prec@1 96.000 (95.632) Prec@5 100.000 (99.895) +2022-11-14 16:21:49,713 Epoch: [334][190/500] Time 0.054 (0.043) Data 0.002 (0.004) Loss 0.0269 (0.0265) Prec@1 97.000 (95.700) Prec@5 100.000 (99.900) +2022-11-14 16:21:50,209 Epoch: [334][200/500] Time 0.046 (0.043) Data 0.002 (0.004) Loss 0.0402 (0.0271) Prec@1 93.000 (95.571) Prec@5 100.000 (99.905) +2022-11-14 16:21:50,706 Epoch: [334][210/500] Time 0.044 (0.043) Data 0.002 (0.004) Loss 0.0521 (0.0283) Prec@1 93.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 16:21:51,196 Epoch: [334][220/500] Time 0.042 (0.043) Data 0.002 (0.004) Loss 0.0335 (0.0285) Prec@1 94.000 (95.391) Prec@5 100.000 (99.913) +2022-11-14 16:21:51,700 Epoch: [334][230/500] Time 0.044 (0.043) Data 0.002 (0.004) Loss 0.0364 (0.0288) Prec@1 94.000 (95.333) Prec@5 100.000 (99.917) +2022-11-14 16:21:52,210 Epoch: [334][240/500] Time 0.054 (0.043) Data 0.002 (0.004) Loss 0.0357 (0.0291) Prec@1 95.000 (95.320) Prec@5 100.000 (99.920) +2022-11-14 16:21:52,700 Epoch: [334][250/500] Time 0.045 (0.043) Data 0.002 (0.004) Loss 0.0405 (0.0295) Prec@1 94.000 (95.269) Prec@5 100.000 (99.923) +2022-11-14 16:21:53,210 Epoch: [334][260/500] Time 0.048 (0.043) Data 0.002 (0.004) Loss 0.0368 (0.0298) Prec@1 93.000 (95.185) Prec@5 99.000 (99.889) +2022-11-14 16:21:53,729 Epoch: [334][270/500] Time 0.053 (0.043) Data 0.002 (0.004) Loss 0.0243 (0.0296) Prec@1 97.000 (95.250) Prec@5 100.000 (99.893) +2022-11-14 16:21:54,231 Epoch: [334][280/500] Time 0.055 (0.044) Data 0.003 (0.003) Loss 0.0289 (0.0296) Prec@1 96.000 (95.276) Prec@5 100.000 (99.897) +2022-11-14 16:21:54,752 Epoch: [334][290/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0171 (0.0292) Prec@1 98.000 (95.367) Prec@5 100.000 (99.900) +2022-11-14 16:21:55,265 Epoch: [334][300/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0309 (0.0292) Prec@1 95.000 (95.355) Prec@5 99.000 (99.871) +2022-11-14 16:21:55,806 Epoch: [334][310/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0242 (0.0291) Prec@1 94.000 (95.312) Prec@5 100.000 (99.875) +2022-11-14 16:21:56,312 Epoch: [334][320/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0258 (0.0290) Prec@1 96.000 (95.333) Prec@5 100.000 (99.879) +2022-11-14 16:21:56,822 Epoch: [334][330/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0295 (0.0290) Prec@1 95.000 (95.324) Prec@5 100.000 (99.882) +2022-11-14 16:21:57,320 Epoch: [334][340/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0284 (0.0290) Prec@1 95.000 (95.314) Prec@5 100.000 (99.886) +2022-11-14 16:21:57,821 Epoch: [334][350/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0423 (0.0293) Prec@1 95.000 (95.306) Prec@5 99.000 (99.861) +2022-11-14 16:21:58,331 Epoch: [334][360/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0316 (0.0294) Prec@1 95.000 (95.297) Prec@5 100.000 (99.865) +2022-11-14 16:21:58,816 Epoch: [334][370/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0406 (0.0297) Prec@1 94.000 (95.263) Prec@5 100.000 (99.868) +2022-11-14 16:21:59,311 Epoch: [334][380/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0331 (0.0298) Prec@1 96.000 (95.282) Prec@5 100.000 (99.872) +2022-11-14 16:21:59,845 Epoch: [334][390/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0394 (0.0300) Prec@1 94.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:22:00,346 Epoch: [334][400/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0287 (0.0300) Prec@1 95.000 (95.244) Prec@5 100.000 (99.878) +2022-11-14 16:22:00,834 Epoch: [334][410/500] Time 0.040 (0.044) Data 0.002 (0.003) Loss 0.0192 (0.0297) Prec@1 96.000 (95.262) Prec@5 100.000 (99.881) +2022-11-14 16:22:01,348 Epoch: [334][420/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0458 (0.0301) Prec@1 92.000 (95.186) Prec@5 100.000 (99.884) +2022-11-14 16:22:01,843 Epoch: [334][430/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0245 (0.0300) Prec@1 95.000 (95.182) Prec@5 100.000 (99.886) +2022-11-14 16:22:02,352 Epoch: [334][440/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0376 (0.0301) Prec@1 93.000 (95.133) Prec@5 99.000 (99.867) +2022-11-14 16:22:02,833 Epoch: [334][450/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0219 (0.0300) Prec@1 96.000 (95.152) Prec@5 100.000 (99.870) +2022-11-14 16:22:03,327 Epoch: [334][460/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0370 (0.0301) Prec@1 94.000 (95.128) Prec@5 100.000 (99.872) +2022-11-14 16:22:03,853 Epoch: [334][470/500] Time 0.054 (0.044) Data 0.002 (0.003) Loss 0.0197 (0.0299) Prec@1 96.000 (95.146) Prec@5 100.000 (99.875) +2022-11-14 16:22:04,333 Epoch: [334][480/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0254 (0.0298) Prec@1 96.000 (95.163) Prec@5 100.000 (99.878) +2022-11-14 16:22:04,866 Epoch: [334][490/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0431 (0.0301) Prec@1 93.000 (95.120) Prec@5 99.000 (99.860) +2022-11-14 16:22:05,322 Epoch: [334][499/500] Time 0.055 (0.044) Data 0.002 (0.003) Loss 0.0464 (0.0304) Prec@1 91.000 (95.039) Prec@5 100.000 (99.863) +2022-11-14 16:22:05,671 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0531 (0.0531) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:22:05,681 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0630 (0.0581) Prec@1 90.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:22:05,690 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0822 (0.0661) Prec@1 87.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 16:22:05,706 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0654) Prec@1 90.000 (89.750) Prec@5 99.000 (99.250) +2022-11-14 16:22:05,717 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0674) Prec@1 90.000 (89.800) Prec@5 99.000 (99.200) +2022-11-14 16:22:05,731 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0388 (0.0626) Prec@1 93.000 (90.333) Prec@5 99.000 (99.167) +2022-11-14 16:22:05,748 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0631) Prec@1 89.000 (90.143) Prec@5 99.000 (99.143) +2022-11-14 16:22:05,768 Test: [7/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0654) Prec@1 87.000 (89.750) Prec@5 100.000 (99.250) +2022-11-14 16:22:05,786 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0675) Prec@1 87.000 (89.444) Prec@5 98.000 (99.111) +2022-11-14 16:22:05,802 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0694) Prec@1 88.000 (89.300) Prec@5 98.000 (99.000) +2022-11-14 16:22:05,817 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0679) Prec@1 92.000 (89.545) Prec@5 100.000 (99.091) +2022-11-14 16:22:05,836 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0695) Prec@1 87.000 (89.333) Prec@5 99.000 (99.083) +2022-11-14 16:22:05,857 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0684) Prec@1 89.000 (89.308) Prec@5 100.000 (99.154) +2022-11-14 16:22:05,877 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0685) Prec@1 91.000 (89.429) Prec@5 100.000 (99.214) +2022-11-14 16:22:05,895 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0690) Prec@1 88.000 (89.333) Prec@5 100.000 (99.267) +2022-11-14 16:22:05,917 Test: [15/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0689) Prec@1 87.000 (89.188) Prec@5 100.000 (99.312) +2022-11-14 16:22:05,935 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0525 (0.0680) Prec@1 91.000 (89.294) Prec@5 98.000 (99.235) +2022-11-14 16:22:05,956 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1222 (0.0710) Prec@1 79.000 (88.722) Prec@5 99.000 (99.222) +2022-11-14 16:22:05,974 Test: [18/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0712) Prec@1 87.000 (88.632) Prec@5 100.000 (99.263) +2022-11-14 16:22:05,992 Test: [19/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0718) Prec@1 87.000 (88.550) Prec@5 97.000 (99.150) +2022-11-14 16:22:06,013 Test: [20/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0718) Prec@1 88.000 (88.524) Prec@5 99.000 (99.143) +2022-11-14 16:22:06,034 Test: [21/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0723) Prec@1 85.000 (88.364) Prec@5 100.000 (99.182) +2022-11-14 16:22:06,054 Test: [22/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0723) Prec@1 90.000 (88.435) Prec@5 99.000 (99.174) +2022-11-14 16:22:06,077 Test: [23/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0722) Prec@1 90.000 (88.500) Prec@5 100.000 (99.208) +2022-11-14 16:22:06,097 Test: [24/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0722) Prec@1 90.000 (88.560) Prec@5 100.000 (99.240) +2022-11-14 16:22:06,114 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0893 (0.0729) Prec@1 86.000 (88.462) Prec@5 99.000 (99.231) +2022-11-14 16:22:06,131 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0561 (0.0723) Prec@1 92.000 (88.593) Prec@5 100.000 (99.259) +2022-11-14 16:22:06,152 Test: [27/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0722) Prec@1 90.000 (88.643) Prec@5 100.000 (99.286) +2022-11-14 16:22:06,173 Test: [28/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0662 (0.0720) Prec@1 87.000 (88.586) Prec@5 99.000 (99.276) +2022-11-14 16:22:06,189 Test: [29/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0828 (0.0724) Prec@1 89.000 (88.600) Prec@5 99.000 (99.267) +2022-11-14 16:22:06,203 Test: [30/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0503 (0.0717) Prec@1 90.000 (88.645) Prec@5 100.000 (99.290) +2022-11-14 16:22:06,218 Test: [31/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0925 (0.0723) Prec@1 84.000 (88.500) Prec@5 100.000 (99.312) +2022-11-14 16:22:06,234 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0726) Prec@1 87.000 (88.455) Prec@5 100.000 (99.333) +2022-11-14 16:22:06,252 Test: [33/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.0729) Prec@1 85.000 (88.353) Prec@5 99.000 (99.324) +2022-11-14 16:22:06,271 Test: [34/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0864 (0.0733) Prec@1 86.000 (88.286) Prec@5 99.000 (99.314) +2022-11-14 16:22:06,286 Test: [35/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0649 (0.0730) Prec@1 90.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:22:06,303 Test: [36/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0617 (0.0727) Prec@1 89.000 (88.351) Prec@5 99.000 (99.324) +2022-11-14 16:22:06,322 Test: [37/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0996 (0.0734) Prec@1 82.000 (88.184) Prec@5 99.000 (99.316) +2022-11-14 16:22:06,340 Test: [38/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0424 (0.0727) Prec@1 93.000 (88.308) Prec@5 99.000 (99.308) +2022-11-14 16:22:06,357 Test: [39/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0737 (0.0727) Prec@1 89.000 (88.325) Prec@5 98.000 (99.275) +2022-11-14 16:22:06,375 Test: [40/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0893 (0.0731) Prec@1 84.000 (88.220) Prec@5 100.000 (99.293) +2022-11-14 16:22:06,393 Test: [41/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0707 (0.0730) Prec@1 90.000 (88.262) Prec@5 99.000 (99.286) +2022-11-14 16:22:06,409 Test: [42/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0421 (0.0723) Prec@1 93.000 (88.372) Prec@5 100.000 (99.302) +2022-11-14 16:22:06,426 Test: 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0.0874 (0.0724) Prec@1 86.000 (88.320) Prec@5 100.000 (99.280) +2022-11-14 16:22:06,547 Test: [50/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0592 (0.0722) Prec@1 91.000 (88.373) Prec@5 100.000 (99.294) +2022-11-14 16:22:06,565 Test: [51/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0797 (0.0723) Prec@1 88.000 (88.365) Prec@5 99.000 (99.288) +2022-11-14 16:22:06,581 Test: [52/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0790 (0.0724) Prec@1 88.000 (88.358) Prec@5 99.000 (99.283) +2022-11-14 16:22:06,598 Test: [53/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0781 (0.0725) Prec@1 87.000 (88.333) Prec@5 99.000 (99.278) +2022-11-14 16:22:06,615 Test: [54/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0774 (0.0726) Prec@1 87.000 (88.309) Prec@5 100.000 (99.291) +2022-11-14 16:22:06,632 Test: [55/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0735 (0.0726) Prec@1 88.000 (88.304) Prec@5 99.000 (99.286) +2022-11-14 16:22:06,646 Test: [56/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0793 (0.0728) Prec@1 87.000 (88.281) Prec@5 100.000 (99.298) +2022-11-14 16:22:06,662 Test: [57/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0789 (0.0729) Prec@1 88.000 (88.276) Prec@5 100.000 (99.310) +2022-11-14 16:22:06,679 Test: [58/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0882 (0.0731) Prec@1 86.000 (88.237) Prec@5 99.000 (99.305) +2022-11-14 16:22:06,696 Test: [59/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0652 (0.0730) Prec@1 89.000 (88.250) Prec@5 100.000 (99.317) +2022-11-14 16:22:06,711 Test: [60/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0686 (0.0729) Prec@1 89.000 (88.262) Prec@5 99.000 (99.311) +2022-11-14 16:22:06,727 Test: [61/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0677 (0.0728) Prec@1 88.000 (88.258) Prec@5 100.000 (99.323) +2022-11-14 16:22:06,747 Test: [62/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0773 (0.0729) Prec@1 87.000 (88.238) Prec@5 100.000 (99.333) +2022-11-14 16:22:06,765 Test: [63/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0448 (0.0725) Prec@1 93.000 (88.312) Prec@5 100.000 (99.344) +2022-11-14 16:22:06,781 Test: [64/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0792 (0.0726) Prec@1 85.000 (88.262) Prec@5 99.000 (99.338) +2022-11-14 16:22:06,800 Test: [65/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0760 (0.0726) Prec@1 87.000 (88.242) Prec@5 99.000 (99.333) +2022-11-14 16:22:06,817 Test: [66/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0457 (0.0722) Prec@1 93.000 (88.313) Prec@5 100.000 (99.343) +2022-11-14 16:22:06,835 Test: [67/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0577 (0.0720) Prec@1 91.000 (88.353) Prec@5 98.000 (99.324) +2022-11-14 16:22:06,852 Test: [68/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0719) Prec@1 90.000 (88.377) Prec@5 100.000 (99.333) +2022-11-14 16:22:06,870 Test: [69/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0939 (0.0722) Prec@1 84.000 (88.314) Prec@5 99.000 (99.329) +2022-11-14 16:22:06,888 Test: [70/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0987 (0.0726) Prec@1 86.000 (88.282) Prec@5 99.000 (99.324) +2022-11-14 16:22:06,904 Test: [71/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0384 (0.0721) Prec@1 94.000 (88.361) Prec@5 100.000 (99.333) +2022-11-14 16:22:06,919 Test: [72/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0585 (0.0720) Prec@1 91.000 (88.397) Prec@5 100.000 (99.342) +2022-11-14 16:22:06,938 Test: [73/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0326 (0.0714) Prec@1 96.000 (88.500) Prec@5 100.000 (99.351) +2022-11-14 16:22:06,956 Test: [74/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0916 (0.0717) Prec@1 85.000 (88.453) Prec@5 100.000 (99.360) +2022-11-14 16:22:06,974 Test: [75/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0656 (0.0716) Prec@1 87.000 (88.434) Prec@5 100.000 (99.368) +2022-11-14 16:22:06,991 Test: [76/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0714 (0.0716) Prec@1 90.000 (88.455) Prec@5 99.000 (99.364) +2022-11-14 16:22:07,008 Test: [77/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0719) Prec@1 85.000 (88.410) Prec@5 100.000 (99.372) +2022-11-14 16:22:07,024 Test: [78/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0745 (0.0719) Prec@1 90.000 (88.430) Prec@5 100.000 (99.380) +2022-11-14 16:22:07,042 Test: [79/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0695 (0.0719) Prec@1 91.000 (88.463) Prec@5 100.000 (99.388) +2022-11-14 16:22:07,056 Test: [80/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0707 (0.0719) Prec@1 89.000 (88.469) Prec@5 98.000 (99.370) +2022-11-14 16:22:07,073 Test: [81/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0718) Prec@1 89.000 (88.476) Prec@5 100.000 (99.378) +2022-11-14 16:22:07,089 Test: [82/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0897 (0.0720) Prec@1 84.000 (88.422) Prec@5 98.000 (99.361) +2022-11-14 16:22:07,106 Test: [83/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0539 (0.0718) Prec@1 92.000 (88.464) Prec@5 99.000 (99.357) +2022-11-14 16:22:07,123 Test: [84/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0929 (0.0721) Prec@1 83.000 (88.400) Prec@5 100.000 (99.365) +2022-11-14 16:22:07,139 Test: [85/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1108 (0.0725) Prec@1 84.000 (88.349) Prec@5 99.000 (99.360) +2022-11-14 16:22:07,156 Test: [86/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0807 (0.0726) Prec@1 85.000 (88.310) Prec@5 99.000 (99.356) +2022-11-14 16:22:07,172 Test: [87/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0721 (0.0726) Prec@1 87.000 (88.295) Prec@5 100.000 (99.364) +2022-11-14 16:22:07,188 Test: [88/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0681 (0.0725) Prec@1 89.000 (88.303) Prec@5 100.000 (99.371) +2022-11-14 16:22:07,207 Test: [89/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0674 (0.0725) Prec@1 90.000 (88.322) Prec@5 100.000 (99.378) +2022-11-14 16:22:07,224 Test: [90/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0632 (0.0724) Prec@1 91.000 (88.352) Prec@5 100.000 (99.385) +2022-11-14 16:22:07,242 Test: [91/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0359 (0.0720) Prec@1 95.000 (88.424) Prec@5 100.000 (99.391) +2022-11-14 16:22:07,258 Test: [92/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0926 (0.0722) Prec@1 85.000 (88.387) Prec@5 100.000 (99.398) +2022-11-14 16:22:07,274 Test: [93/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0777 (0.0723) Prec@1 88.000 (88.383) Prec@5 99.000 (99.394) +2022-11-14 16:22:07,295 Test: [94/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0773 (0.0723) Prec@1 87.000 (88.368) Prec@5 99.000 (99.389) +2022-11-14 16:22:07,315 Test: [95/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0477 (0.0721) Prec@1 93.000 (88.417) Prec@5 100.000 (99.396) +2022-11-14 16:22:07,333 Test: [96/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0556 (0.0719) Prec@1 91.000 (88.443) Prec@5 99.000 (99.392) +2022-11-14 16:22:07,350 Test: [97/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0895 (0.0721) Prec@1 85.000 (88.408) Prec@5 99.000 (99.388) +2022-11-14 16:22:07,367 Test: [98/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1002 (0.0724) Prec@1 85.000 (88.374) Prec@5 98.000 (99.374) +2022-11-14 16:22:07,385 Test: [99/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0745 (0.0724) Prec@1 87.000 (88.360) Prec@5 99.000 (99.370) +2022-11-14 16:22:07,460 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:22:07,834 Epoch: [335][0/500] Time 0.026 (0.026) Data 0.276 (0.276) Loss 0.0338 (0.0338) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:22:08,298 Epoch: [335][10/500] Time 0.059 (0.040) Data 0.002 (0.027) Loss 0.0249 (0.0294) Prec@1 95.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:22:08,838 Epoch: [335][20/500] Time 0.062 (0.044) Data 0.002 (0.015) Loss 0.0262 (0.0283) Prec@1 96.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:22:09,334 Epoch: [335][30/500] Time 0.054 (0.044) Data 0.002 (0.011) Loss 0.0301 (0.0287) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:22:09,818 Epoch: [335][40/500] Time 0.045 (0.044) Data 0.002 (0.009) Loss 0.0277 (0.0285) Prec@1 94.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:22:10,327 Epoch: [335][50/500] Time 0.045 (0.044) Data 0.002 (0.007) Loss 0.0433 (0.0310) Prec@1 92.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:22:10,876 Epoch: [335][60/500] Time 0.056 (0.045) Data 0.002 (0.007) Loss 0.0064 (0.0275) Prec@1 100.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:22:11,386 Epoch: [335][70/500] Time 0.051 (0.045) Data 0.003 (0.006) Loss 0.0327 (0.0281) Prec@1 95.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:22:11,899 Epoch: [335][80/500] Time 0.047 (0.045) Data 0.002 (0.006) Loss 0.0213 (0.0274) Prec@1 97.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 16:22:12,416 Epoch: [335][90/500] Time 0.053 (0.045) Data 0.002 (0.005) Loss 0.0456 (0.0292) Prec@1 91.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 16:22:12,921 Epoch: [335][100/500] Time 0.047 (0.045) Data 0.002 (0.005) Loss 0.0282 (0.0291) Prec@1 95.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 16:22:13,473 Epoch: [335][110/500] Time 0.041 (0.046) Data 0.002 (0.005) Loss 0.0629 (0.0319) Prec@1 89.000 (94.417) Prec@5 99.000 (99.833) +2022-11-14 16:22:14,023 Epoch: [335][120/500] Time 0.046 (0.046) Data 0.002 (0.004) Loss 0.0352 (0.0322) Prec@1 95.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 16:22:14,536 Epoch: [335][130/500] Time 0.051 (0.046) Data 0.002 (0.004) Loss 0.0245 (0.0316) Prec@1 96.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:22:15,088 Epoch: [335][140/500] Time 0.056 (0.046) Data 0.002 (0.004) Loss 0.0214 (0.0309) Prec@1 97.000 (94.733) Prec@5 100.000 (99.867) +2022-11-14 16:22:15,594 Epoch: [335][150/500] Time 0.056 (0.046) Data 0.002 (0.004) Loss 0.0302 (0.0309) Prec@1 93.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 16:22:16,115 Epoch: [335][160/500] Time 0.049 (0.046) Data 0.002 (0.004) Loss 0.0390 (0.0314) Prec@1 94.000 (94.588) Prec@5 100.000 (99.882) +2022-11-14 16:22:16,665 Epoch: [335][170/500] Time 0.064 (0.046) Data 0.003 (0.004) Loss 0.0414 (0.0319) Prec@1 92.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:22:17,195 Epoch: [335][180/500] Time 0.049 (0.046) Data 0.003 (0.004) Loss 0.0343 (0.0321) Prec@1 95.000 (94.474) Prec@5 100.000 (99.895) +2022-11-14 16:22:17,696 Epoch: [335][190/500] Time 0.049 (0.046) Data 0.002 (0.004) Loss 0.0203 (0.0315) Prec@1 96.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 16:22:18,198 Epoch: [335][200/500] Time 0.042 (0.046) Data 0.003 (0.004) Loss 0.0163 (0.0307) Prec@1 99.000 (94.762) Prec@5 100.000 (99.905) +2022-11-14 16:22:18,714 Epoch: [335][210/500] Time 0.050 (0.046) Data 0.003 (0.003) Loss 0.0360 (0.0310) Prec@1 92.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 16:22:19,227 Epoch: [335][220/500] Time 0.042 (0.046) Data 0.003 (0.003) Loss 0.0143 (0.0303) Prec@1 99.000 (94.826) Prec@5 100.000 (99.913) +2022-11-14 16:22:19,761 Epoch: [335][230/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0137 (0.0296) Prec@1 99.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 16:22:20,268 Epoch: [335][240/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0461 (0.0302) Prec@1 93.000 (94.920) Prec@5 99.000 (99.880) +2022-11-14 16:22:20,798 Epoch: [335][250/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0366 (0.0305) Prec@1 93.000 (94.846) Prec@5 99.000 (99.846) +2022-11-14 16:22:21,277 Epoch: [335][260/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0221 (0.0302) Prec@1 97.000 (94.926) Prec@5 100.000 (99.852) +2022-11-14 16:22:21,790 Epoch: [335][270/500] Time 0.046 (0.046) Data 0.002 (0.003) Loss 0.0171 (0.0297) Prec@1 97.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 16:22:22,291 Epoch: [335][280/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0168 (0.0292) Prec@1 98.000 (95.103) Prec@5 100.000 (99.862) +2022-11-14 16:22:22,804 Epoch: [335][290/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0150 (0.0288) Prec@1 97.000 (95.167) Prec@5 100.000 (99.867) +2022-11-14 16:22:23,330 Epoch: [335][300/500] Time 0.043 (0.046) Data 0.003 (0.003) Loss 0.0691 (0.0301) Prec@1 88.000 (94.935) Prec@5 99.000 (99.839) +2022-11-14 16:22:23,872 Epoch: [335][310/500] Time 0.059 (0.046) Data 0.003 (0.003) Loss 0.0629 (0.0311) Prec@1 91.000 (94.812) Prec@5 99.000 (99.812) +2022-11-14 16:22:24,403 Epoch: [335][320/500] Time 0.058 (0.046) Data 0.002 (0.003) Loss 0.0342 (0.0312) Prec@1 95.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:22:24,899 Epoch: [335][330/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0239 (0.0310) Prec@1 97.000 (94.882) Prec@5 100.000 (99.824) +2022-11-14 16:22:25,445 Epoch: [335][340/500] Time 0.061 (0.046) Data 0.002 (0.003) Loss 0.0216 (0.0307) Prec@1 97.000 (94.943) Prec@5 100.000 (99.829) +2022-11-14 16:22:25,955 Epoch: [335][350/500] Time 0.048 (0.046) Data 0.003 (0.003) Loss 0.0578 (0.0315) Prec@1 88.000 (94.750) Prec@5 100.000 (99.833) +2022-11-14 16:22:26,464 Epoch: [335][360/500] Time 0.038 (0.046) Data 0.003 (0.003) Loss 0.0321 (0.0315) Prec@1 95.000 (94.757) Prec@5 99.000 (99.811) +2022-11-14 16:22:26,973 Epoch: [335][370/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0373 (0.0316) Prec@1 95.000 (94.763) Prec@5 99.000 (99.789) +2022-11-14 16:22:27,478 Epoch: [335][380/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0184 (0.0313) Prec@1 97.000 (94.821) Prec@5 100.000 (99.795) +2022-11-14 16:22:27,980 Epoch: [335][390/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0204 (0.0310) Prec@1 98.000 (94.900) Prec@5 100.000 (99.800) +2022-11-14 16:22:28,533 Epoch: [335][400/500] Time 0.055 (0.046) Data 0.003 (0.003) Loss 0.0293 (0.0310) Prec@1 94.000 (94.878) Prec@5 100.000 (99.805) +2022-11-14 16:22:29,070 Epoch: [335][410/500] Time 0.050 (0.046) Data 0.002 (0.003) Loss 0.0179 (0.0307) Prec@1 97.000 (94.929) Prec@5 100.000 (99.810) +2022-11-14 16:22:29,596 Epoch: [335][420/500] Time 0.057 (0.046) Data 0.002 (0.003) Loss 0.0114 (0.0302) Prec@1 99.000 (95.023) Prec@5 100.000 (99.814) +2022-11-14 16:22:30,117 Epoch: [335][430/500] Time 0.045 (0.046) Data 0.002 (0.003) Loss 0.0330 (0.0303) Prec@1 94.000 (95.000) Prec@5 99.000 (99.795) +2022-11-14 16:22:30,670 Epoch: [335][440/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0310 (0.0303) Prec@1 95.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 16:22:31,197 Epoch: [335][450/500] Time 0.050 (0.046) Data 0.003 (0.003) Loss 0.0147 (0.0300) Prec@1 98.000 (95.065) Prec@5 100.000 (99.804) +2022-11-14 16:22:31,708 Epoch: [335][460/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0342 (0.0300) Prec@1 94.000 (95.043) Prec@5 100.000 (99.809) +2022-11-14 16:22:32,250 Epoch: [335][470/500] Time 0.052 (0.046) Data 0.002 (0.003) Loss 0.0326 (0.0301) Prec@1 94.000 (95.021) Prec@5 100.000 (99.812) +2022-11-14 16:22:32,759 Epoch: [335][480/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0381 (0.0303) Prec@1 93.000 (94.980) Prec@5 100.000 (99.816) +2022-11-14 16:22:33,320 Epoch: [335][490/500] Time 0.051 (0.046) Data 0.003 (0.003) Loss 0.0192 (0.0300) Prec@1 97.000 (95.020) Prec@5 100.000 (99.820) +2022-11-14 16:22:33,826 Epoch: [335][499/500] Time 0.047 (0.047) Data 0.003 (0.003) Loss 0.0400 (0.0302) Prec@1 93.000 (94.980) Prec@5 100.000 (99.824) +2022-11-14 16:22:34,249 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0554 (0.0554) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:22:34,261 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0835 (0.0694) Prec@1 88.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 16:22:34,272 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0968 (0.0785) Prec@1 82.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 16:22:34,287 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0847 (0.0801) Prec@1 86.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 16:22:34,298 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0760 (0.0793) Prec@1 88.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 16:22:34,310 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0523 (0.0748) Prec@1 92.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 16:22:34,324 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0758) Prec@1 89.000 (88.143) Prec@5 99.000 (99.429) +2022-11-14 16:22:34,340 Test: [7/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1090 (0.0799) Prec@1 82.000 (87.375) Prec@5 99.000 (99.375) +2022-11-14 16:22:34,354 Test: [8/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0799) Prec@1 88.000 (87.444) Prec@5 100.000 (99.444) +2022-11-14 16:22:34,367 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0805) Prec@1 88.000 (87.500) Prec@5 98.000 (99.300) +2022-11-14 16:22:34,382 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0588 (0.0785) Prec@1 88.000 (87.545) Prec@5 100.000 (99.364) +2022-11-14 16:22:34,398 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0922 (0.0797) Prec@1 86.000 (87.417) Prec@5 98.000 (99.250) +2022-11-14 16:22:34,414 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0791) Prec@1 90.000 (87.615) Prec@5 100.000 (99.308) +2022-11-14 16:22:34,431 Test: [13/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0686 (0.0784) Prec@1 90.000 (87.786) Prec@5 100.000 (99.357) +2022-11-14 16:22:34,447 Test: [14/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0783) Prec@1 89.000 (87.867) Prec@5 100.000 (99.400) +2022-11-14 16:22:34,465 Test: [15/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0787) Prec@1 85.000 (87.688) Prec@5 99.000 (99.375) +2022-11-14 16:22:34,482 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0451 (0.0767) Prec@1 93.000 (88.000) Prec@5 98.000 (99.294) +2022-11-14 16:22:34,501 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0921 (0.0776) Prec@1 85.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 16:22:34,519 Test: [18/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0952 (0.0785) Prec@1 82.000 (87.526) Prec@5 98.000 (99.263) +2022-11-14 16:22:34,535 Test: [19/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0794) Prec@1 85.000 (87.400) Prec@5 99.000 (99.250) +2022-11-14 16:22:34,553 Test: [20/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0804 (0.0794) Prec@1 86.000 (87.333) Prec@5 100.000 (99.286) +2022-11-14 16:22:34,568 Test: [21/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0814 (0.0795) Prec@1 86.000 (87.273) Prec@5 99.000 (99.273) +2022-11-14 16:22:34,583 Test: [22/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0898 (0.0800) Prec@1 88.000 (87.304) Prec@5 98.000 (99.217) +2022-11-14 16:22:34,599 Test: [23/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0821 (0.0801) Prec@1 89.000 (87.375) Prec@5 100.000 (99.250) +2022-11-14 16:22:34,616 Test: [24/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0754 (0.0799) Prec@1 88.000 (87.400) Prec@5 100.000 (99.280) +2022-11-14 16:22:34,631 Test: [25/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1007 (0.0807) Prec@1 83.000 (87.231) Prec@5 98.000 (99.231) +2022-11-14 16:22:34,646 Test: [26/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0493 (0.0795) Prec@1 91.000 (87.370) Prec@5 100.000 (99.259) +2022-11-14 16:22:34,665 Test: [27/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0721 (0.0793) Prec@1 89.000 (87.429) Prec@5 99.000 (99.250) +2022-11-14 16:22:34,686 Test: [28/100] Model Time 0.014 (0.010) Loss Time 0.000 (0.000) Loss 0.0745 (0.0791) Prec@1 88.000 (87.448) Prec@5 98.000 (99.207) +2022-11-14 16:22:34,703 Test: [29/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0629 (0.0786) Prec@1 91.000 (87.567) Prec@5 100.000 (99.233) +2022-11-14 16:22:34,720 Test: [30/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0501 (0.0776) Prec@1 92.000 (87.710) Prec@5 100.000 (99.258) +2022-11-14 16:22:34,738 Test: [31/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0812 (0.0777) Prec@1 89.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 16:22:34,755 Test: [32/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0786 (0.0778) Prec@1 86.000 (87.697) Prec@5 100.000 (99.273) +2022-11-14 16:22:34,771 Test: [33/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0920 (0.0782) Prec@1 85.000 (87.618) Prec@5 99.000 (99.265) +2022-11-14 16:22:34,785 Test: [34/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0958 (0.0787) Prec@1 83.000 (87.486) Prec@5 97.000 (99.200) +2022-11-14 16:22:34,803 Test: [35/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0644 (0.0783) Prec@1 89.000 (87.528) Prec@5 99.000 (99.194) +2022-11-14 16:22:34,821 Test: [36/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0692 (0.0780) Prec@1 87.000 (87.514) Prec@5 99.000 (99.189) +2022-11-14 16:22:34,839 Test: [37/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1211 (0.0792) Prec@1 80.000 (87.316) Prec@5 100.000 (99.211) +2022-11-14 16:22:34,857 Test: [38/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0705 (0.0790) Prec@1 88.000 (87.333) Prec@5 99.000 (99.205) +2022-11-14 16:22:34,874 Test: [39/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0575 (0.0784) Prec@1 91.000 (87.425) Prec@5 100.000 (99.225) +2022-11-14 16:22:34,890 Test: [40/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1013 (0.0790) Prec@1 83.000 (87.317) Prec@5 99.000 (99.220) +2022-11-14 16:22:34,906 Test: [41/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0658 (0.0787) Prec@1 90.000 (87.381) Prec@5 97.000 (99.167) +2022-11-14 16:22:34,924 Test: [42/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0445 (0.0779) Prec@1 93.000 (87.512) Prec@5 98.000 (99.140) +2022-11-14 16:22:34,942 Test: [43/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0649 (0.0776) Prec@1 92.000 (87.614) Prec@5 98.000 (99.114) +2022-11-14 16:22:34,959 Test: [44/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0574 (0.0771) Prec@1 90.000 (87.667) Prec@5 98.000 (99.089) +2022-11-14 16:22:34,978 Test: [45/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0935 (0.0775) Prec@1 83.000 (87.565) Prec@5 99.000 (99.087) +2022-11-14 16:22:34,994 Test: [46/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0725 (0.0774) Prec@1 89.000 (87.596) Prec@5 100.000 (99.106) +2022-11-14 16:22:35,013 Test: [47/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1036 (0.0779) Prec@1 83.000 (87.500) Prec@5 98.000 (99.083) +2022-11-14 16:22:35,028 Test: [48/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0776) Prec@1 90.000 (87.551) Prec@5 100.000 (99.102) +2022-11-14 16:22:35,043 Test: [49/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0980 (0.0780) Prec@1 85.000 (87.500) Prec@5 99.000 (99.100) +2022-11-14 16:22:35,061 Test: [50/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0684 (0.0779) Prec@1 88.000 (87.510) Prec@5 100.000 (99.118) +2022-11-14 16:22:35,078 Test: [51/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0678 (0.0777) Prec@1 89.000 (87.538) Prec@5 100.000 (99.135) +2022-11-14 16:22:35,095 Test: [52/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0894 (0.0779) Prec@1 84.000 (87.472) Prec@5 100.000 (99.151) +2022-11-14 16:22:35,110 Test: [53/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0776) Prec@1 89.000 (87.500) Prec@5 98.000 (99.130) +2022-11-14 16:22:35,126 Test: [54/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1095 (0.0782) Prec@1 83.000 (87.418) Prec@5 100.000 (99.145) +2022-11-14 16:22:35,143 Test: [55/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0789 (0.0782) Prec@1 90.000 (87.464) Prec@5 98.000 (99.125) +2022-11-14 16:22:35,158 Test: [56/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0797 (0.0782) Prec@1 85.000 (87.421) Prec@5 100.000 (99.140) +2022-11-14 16:22:35,175 Test: [57/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0652 (0.0780) Prec@1 91.000 (87.483) Prec@5 99.000 (99.138) +2022-11-14 16:22:35,191 Test: [58/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0882 (0.0782) Prec@1 83.000 (87.407) Prec@5 100.000 (99.153) +2022-11-14 16:22:35,206 Test: [59/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0713 (0.0781) Prec@1 87.000 (87.400) Prec@5 99.000 (99.150) +2022-11-14 16:22:35,221 Test: [60/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0766 (0.0780) Prec@1 89.000 (87.426) Prec@5 99.000 (99.148) +2022-11-14 16:22:35,239 Test: [61/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0815 (0.0781) Prec@1 86.000 (87.403) Prec@5 100.000 (99.161) +2022-11-14 16:22:35,256 Test: [62/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0646 (0.0779) Prec@1 91.000 (87.460) Prec@5 100.000 (99.175) +2022-11-14 16:22:35,272 Test: [63/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0372 (0.0772) Prec@1 93.000 (87.547) Prec@5 100.000 (99.188) +2022-11-14 16:22:35,289 Test: [64/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0875 (0.0774) Prec@1 86.000 (87.523) Prec@5 100.000 (99.200) +2022-11-14 16:22:35,304 Test: [65/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0893 (0.0776) Prec@1 86.000 (87.500) Prec@5 100.000 (99.212) +2022-11-14 16:22:35,321 Test: [66/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0539 (0.0772) Prec@1 89.000 (87.522) Prec@5 100.000 (99.224) +2022-11-14 16:22:35,339 Test: [67/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0599 (0.0770) Prec@1 90.000 (87.559) Prec@5 99.000 (99.221) +2022-11-14 16:22:35,357 Test: [68/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0550 (0.0767) Prec@1 90.000 (87.594) Prec@5 99.000 (99.217) +2022-11-14 16:22:35,372 Test: [69/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0859 (0.0768) Prec@1 87.000 (87.586) Prec@5 100.000 (99.229) +2022-11-14 16:22:35,390 Test: [70/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0947 (0.0770) Prec@1 89.000 (87.606) Prec@5 98.000 (99.211) +2022-11-14 16:22:35,407 Test: [71/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0768) Prec@1 88.000 (87.611) Prec@5 100.000 (99.222) +2022-11-14 16:22:35,424 Test: [72/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0545 (0.0765) Prec@1 91.000 (87.658) Prec@5 100.000 (99.233) +2022-11-14 16:22:35,441 Test: [73/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0465 (0.0761) Prec@1 92.000 (87.716) Prec@5 100.000 (99.243) +2022-11-14 16:22:35,458 Test: [74/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1110 (0.0766) Prec@1 83.000 (87.653) Prec@5 99.000 (99.240) +2022-11-14 16:22:35,477 Test: [75/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0663 (0.0764) Prec@1 90.000 (87.684) Prec@5 100.000 (99.250) +2022-11-14 16:22:35,495 Test: [76/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0591 (0.0762) Prec@1 91.000 (87.727) Prec@5 100.000 (99.260) +2022-11-14 16:22:35,512 Test: [77/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0952 (0.0765) Prec@1 84.000 (87.679) Prec@5 97.000 (99.231) +2022-11-14 16:22:35,531 Test: [78/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0979 (0.0767) Prec@1 86.000 (87.658) Prec@5 100.000 (99.241) +2022-11-14 16:22:35,546 Test: [79/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0745 (0.0767) Prec@1 87.000 (87.650) Prec@5 99.000 (99.237) +2022-11-14 16:22:35,562 Test: [80/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0795 (0.0767) Prec@1 87.000 (87.642) Prec@5 98.000 (99.222) +2022-11-14 16:22:35,578 Test: [81/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0997 (0.0770) Prec@1 83.000 (87.585) Prec@5 100.000 (99.232) +2022-11-14 16:22:35,595 Test: [82/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0982 (0.0773) Prec@1 82.000 (87.518) Prec@5 98.000 (99.217) +2022-11-14 16:22:35,613 Test: [83/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0786 (0.0773) Prec@1 88.000 (87.524) Prec@5 98.000 (99.202) +2022-11-14 16:22:35,629 Test: [84/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0984 (0.0775) Prec@1 81.000 (87.447) Prec@5 100.000 (99.212) +2022-11-14 16:22:35,644 Test: [85/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0999 (0.0778) Prec@1 85.000 (87.419) Prec@5 99.000 (99.209) +2022-11-14 16:22:35,660 Test: [86/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0672 (0.0777) Prec@1 86.000 (87.402) Prec@5 100.000 (99.218) +2022-11-14 16:22:35,675 Test: [87/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0788 (0.0777) Prec@1 88.000 (87.409) Prec@5 99.000 (99.216) +2022-11-14 16:22:35,693 Test: [88/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0549 (0.0774) Prec@1 90.000 (87.438) Prec@5 100.000 (99.225) +2022-11-14 16:22:35,713 Test: [89/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0859 (0.0775) Prec@1 86.000 (87.422) Prec@5 99.000 (99.222) +2022-11-14 16:22:35,730 Test: [90/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0515 (0.0772) Prec@1 92.000 (87.473) Prec@5 100.000 (99.231) +2022-11-14 16:22:35,749 Test: [91/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0576 (0.0770) Prec@1 90.000 (87.500) Prec@5 99.000 (99.228) +2022-11-14 16:22:35,765 Test: [92/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1014 (0.0773) Prec@1 85.000 (87.473) Prec@5 99.000 (99.226) +2022-11-14 16:22:35,783 Test: [93/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0926 (0.0775) Prec@1 86.000 (87.457) Prec@5 98.000 (99.213) +2022-11-14 16:22:35,801 Test: [94/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0696 (0.0774) Prec@1 90.000 (87.484) Prec@5 100.000 (99.221) +2022-11-14 16:22:35,819 Test: [95/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0591 (0.0772) Prec@1 92.000 (87.531) Prec@5 100.000 (99.229) +2022-11-14 16:22:35,835 Test: [96/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0485 (0.0769) Prec@1 91.000 (87.567) Prec@5 99.000 (99.227) +2022-11-14 16:22:35,852 Test: [97/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1068 (0.0772) Prec@1 84.000 (87.531) Prec@5 99.000 (99.224) +2022-11-14 16:22:35,870 Test: [98/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.1056 (0.0775) Prec@1 82.000 (87.475) Prec@5 99.000 (99.222) +2022-11-14 16:22:35,887 Test: [99/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0789 (0.0775) Prec@1 86.000 (87.460) Prec@5 100.000 (99.230) +2022-11-14 16:22:35,969 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:22:36,348 Epoch: [336][0/500] Time 0.029 (0.029) Data 0.274 (0.274) Loss 0.0237 (0.0237) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:22:36,624 Epoch: [336][10/500] Time 0.030 (0.025) Data 0.002 (0.027) Loss 0.0447 (0.0342) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:22:36,930 Epoch: [336][20/500] Time 0.026 (0.026) Data 0.002 (0.015) Loss 0.0196 (0.0293) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:22:37,507 Epoch: [336][30/500] Time 0.062 (0.034) Data 0.002 (0.011) Loss 0.0276 (0.0289) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:22:38,127 Epoch: [336][40/500] Time 0.065 (0.039) Data 0.002 (0.009) Loss 0.0177 (0.0267) Prec@1 96.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:22:38,746 Epoch: [336][50/500] Time 0.063 (0.042) Data 0.002 (0.007) Loss 0.0299 (0.0272) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:22:39,380 Epoch: [336][60/500] Time 0.058 (0.045) Data 0.002 (0.007) Loss 0.0328 (0.0280) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:22:39,988 Epoch: [336][70/500] Time 0.051 (0.046) Data 0.002 (0.006) Loss 0.0515 (0.0309) Prec@1 92.000 (94.625) Prec@5 99.000 (99.875) +2022-11-14 16:22:40,605 Epoch: [336][80/500] Time 0.066 (0.047) Data 0.002 (0.005) Loss 0.0303 (0.0309) Prec@1 96.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 16:22:41,218 Epoch: [336][90/500] Time 0.061 (0.048) Data 0.003 (0.005) Loss 0.0356 (0.0313) Prec@1 94.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 16:22:41,839 Epoch: [336][100/500] Time 0.060 (0.049) Data 0.003 (0.005) Loss 0.0332 (0.0315) Prec@1 93.000 (94.545) Prec@5 100.000 (99.909) +2022-11-14 16:22:42,453 Epoch: [336][110/500] Time 0.062 (0.049) Data 0.002 (0.005) Loss 0.0238 (0.0309) Prec@1 96.000 (94.667) Prec@5 100.000 (99.917) +2022-11-14 16:22:43,080 Epoch: [336][120/500] Time 0.054 (0.050) Data 0.002 (0.004) Loss 0.0311 (0.0309) Prec@1 95.000 (94.692) Prec@5 100.000 (99.923) +2022-11-14 16:22:43,689 Epoch: [336][130/500] Time 0.061 (0.050) Data 0.002 (0.004) Loss 0.0155 (0.0298) Prec@1 98.000 (94.929) Prec@5 100.000 (99.929) +2022-11-14 16:22:44,309 Epoch: [336][140/500] Time 0.060 (0.051) Data 0.002 (0.004) Loss 0.0574 (0.0316) Prec@1 92.000 (94.733) Prec@5 100.000 (99.933) +2022-11-14 16:22:44,890 Epoch: [336][150/500] Time 0.056 (0.051) Data 0.002 (0.004) Loss 0.0322 (0.0317) Prec@1 94.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:22:45,505 Epoch: [336][160/500] Time 0.063 (0.051) Data 0.002 (0.004) Loss 0.0232 (0.0312) Prec@1 98.000 (94.882) Prec@5 100.000 (99.941) +2022-11-14 16:22:46,105 Epoch: [336][170/500] Time 0.062 (0.051) Data 0.002 (0.004) Loss 0.0677 (0.0332) Prec@1 89.000 (94.556) Prec@5 99.000 (99.889) +2022-11-14 16:22:46,706 Epoch: [336][180/500] Time 0.050 (0.051) Data 0.002 (0.004) Loss 0.0277 (0.0329) Prec@1 94.000 (94.526) Prec@5 100.000 (99.895) +2022-11-14 16:22:47,312 Epoch: [336][190/500] Time 0.064 (0.051) Data 0.002 (0.004) Loss 0.0337 (0.0329) Prec@1 95.000 (94.550) Prec@5 100.000 (99.900) +2022-11-14 16:22:47,915 Epoch: [336][200/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0372 (0.0331) Prec@1 94.000 (94.524) Prec@5 100.000 (99.905) +2022-11-14 16:22:48,511 Epoch: [336][210/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0262 (0.0328) Prec@1 96.000 (94.591) Prec@5 100.000 (99.909) +2022-11-14 16:22:49,122 Epoch: [336][220/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0221 (0.0324) Prec@1 96.000 (94.652) Prec@5 100.000 (99.913) +2022-11-14 16:22:49,727 Epoch: [336][230/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0462 (0.0329) Prec@1 94.000 (94.625) Prec@5 100.000 (99.917) +2022-11-14 16:22:50,341 Epoch: [336][240/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0343 (0.0330) Prec@1 95.000 (94.640) Prec@5 100.000 (99.920) +2022-11-14 16:22:50,934 Epoch: [336][250/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0286 (0.0328) Prec@1 96.000 (94.692) Prec@5 100.000 (99.923) +2022-11-14 16:22:51,549 Epoch: [336][260/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0261 (0.0326) Prec@1 96.000 (94.741) Prec@5 100.000 (99.926) +2022-11-14 16:22:52,172 Epoch: [336][270/500] Time 0.070 (0.052) Data 0.002 (0.003) Loss 0.0356 (0.0327) Prec@1 95.000 (94.750) Prec@5 100.000 (99.929) +2022-11-14 16:22:52,772 Epoch: [336][280/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0285 (0.0325) Prec@1 95.000 (94.759) Prec@5 100.000 (99.931) +2022-11-14 16:22:53,387 Epoch: [336][290/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0482 (0.0331) Prec@1 91.000 (94.633) Prec@5 99.000 (99.900) +2022-11-14 16:22:54,005 Epoch: [336][300/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0170 (0.0325) Prec@1 98.000 (94.742) Prec@5 100.000 (99.903) +2022-11-14 16:22:54,612 Epoch: [336][310/500] Time 0.067 (0.053) Data 0.002 (0.003) Loss 0.0352 (0.0326) Prec@1 92.000 (94.656) Prec@5 100.000 (99.906) +2022-11-14 16:22:55,243 Epoch: [336][320/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0344 (0.0327) Prec@1 94.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 16:22:55,818 Epoch: [336][330/500] Time 0.049 (0.053) Data 0.002 (0.003) Loss 0.0307 (0.0326) Prec@1 95.000 (94.647) Prec@5 100.000 (99.912) +2022-11-14 16:22:56,408 Epoch: [336][340/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0315 (0.0326) Prec@1 95.000 (94.657) Prec@5 100.000 (99.914) +2022-11-14 16:22:57,043 Epoch: [336][350/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0217 (0.0323) Prec@1 95.000 (94.667) Prec@5 100.000 (99.917) +2022-11-14 16:22:57,654 Epoch: [336][360/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0341 (0.0323) Prec@1 96.000 (94.703) Prec@5 100.000 (99.919) +2022-11-14 16:22:58,253 Epoch: [336][370/500] Time 0.066 (0.053) Data 0.002 (0.003) Loss 0.0174 (0.0319) Prec@1 97.000 (94.763) Prec@5 99.000 (99.895) +2022-11-14 16:22:58,847 Epoch: [336][380/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0288 (0.0319) Prec@1 93.000 (94.718) Prec@5 100.000 (99.897) +2022-11-14 16:22:59,434 Epoch: [336][390/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0556 (0.0325) Prec@1 91.000 (94.625) Prec@5 100.000 (99.900) +2022-11-14 16:23:00,061 Epoch: [336][400/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0387 (0.0326) Prec@1 94.000 (94.610) Prec@5 100.000 (99.902) +2022-11-14 16:23:00,695 Epoch: [336][410/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0446 (0.0329) Prec@1 89.000 (94.476) Prec@5 100.000 (99.905) +2022-11-14 16:23:01,285 Epoch: [336][420/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0236 (0.0327) Prec@1 97.000 (94.535) Prec@5 100.000 (99.907) +2022-11-14 16:23:01,906 Epoch: [336][430/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0276 (0.0326) Prec@1 95.000 (94.545) Prec@5 100.000 (99.909) +2022-11-14 16:23:02,493 Epoch: [336][440/500] Time 0.067 (0.053) Data 0.002 (0.003) Loss 0.0239 (0.0324) Prec@1 97.000 (94.600) Prec@5 100.000 (99.911) +2022-11-14 16:23:03,112 Epoch: [336][450/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0240 (0.0322) Prec@1 97.000 (94.652) Prec@5 100.000 (99.913) +2022-11-14 16:23:03,738 Epoch: [336][460/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0344 (0.0322) Prec@1 94.000 (94.638) Prec@5 100.000 (99.915) +2022-11-14 16:23:04,356 Epoch: [336][470/500] Time 0.069 (0.053) Data 0.002 (0.003) Loss 0.0493 (0.0326) Prec@1 94.000 (94.625) Prec@5 100.000 (99.917) +2022-11-14 16:23:04,978 Epoch: [336][480/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0067 (0.0321) Prec@1 99.000 (94.714) Prec@5 100.000 (99.918) +2022-11-14 16:23:05,566 Epoch: [336][490/500] Time 0.057 (0.053) Data 0.003 (0.003) Loss 0.0159 (0.0317) Prec@1 98.000 (94.780) Prec@5 100.000 (99.920) +2022-11-14 16:23:06,144 Epoch: [336][499/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0274 (0.0317) Prec@1 96.000 (94.804) Prec@5 100.000 (99.922) +2022-11-14 16:23:06,497 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0593 (0.0593) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:23:06,510 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0597 (0.0595) Prec@1 91.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:23:06,522 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0834 (0.0675) Prec@1 86.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:23:06,539 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0719) Prec@1 86.000 (87.750) Prec@5 98.000 (99.500) +2022-11-14 16:23:06,551 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0967 (0.0768) Prec@1 85.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 16:23:06,563 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0584 (0.0738) Prec@1 90.000 (87.667) Prec@5 99.000 (99.500) +2022-11-14 16:23:06,572 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0570 (0.0714) Prec@1 91.000 (88.143) Prec@5 100.000 (99.571) +2022-11-14 16:23:06,587 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0871 (0.0733) Prec@1 85.000 (87.750) Prec@5 98.000 (99.375) +2022-11-14 16:23:06,598 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0966 (0.0759) Prec@1 87.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 16:23:06,611 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0757) Prec@1 88.000 (87.700) Prec@5 98.000 (99.200) +2022-11-14 16:23:06,622 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0495 (0.0733) Prec@1 91.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 16:23:06,637 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0732) Prec@1 90.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 16:23:06,650 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0735) Prec@1 89.000 (88.231) Prec@5 100.000 (99.385) +2022-11-14 16:23:06,664 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0731) Prec@1 90.000 (88.357) Prec@5 100.000 (99.429) +2022-11-14 16:23:06,680 Test: [14/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0739) Prec@1 86.000 (88.200) Prec@5 97.000 (99.267) +2022-11-14 16:23:06,692 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0568 (0.0728) Prec@1 91.000 (88.375) Prec@5 99.000 (99.250) +2022-11-14 16:23:06,706 Test: [16/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0437 (0.0711) Prec@1 95.000 (88.765) Prec@5 99.000 (99.235) +2022-11-14 16:23:06,719 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1028 (0.0729) Prec@1 84.000 (88.500) Prec@5 100.000 (99.278) +2022-11-14 16:23:06,732 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0731) Prec@1 87.000 (88.421) Prec@5 98.000 (99.211) +2022-11-14 16:23:06,744 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0737) Prec@1 89.000 (88.450) Prec@5 96.000 (99.050) +2022-11-14 16:23:06,755 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0741) Prec@1 86.000 (88.333) Prec@5 100.000 (99.095) +2022-11-14 16:23:06,765 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0904 (0.0748) Prec@1 84.000 (88.136) Prec@5 97.000 (99.000) +2022-11-14 16:23:06,777 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0752) Prec@1 87.000 (88.087) Prec@5 96.000 (98.870) +2022-11-14 16:23:06,788 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0756) Prec@1 87.000 (88.042) Prec@5 100.000 (98.917) +2022-11-14 16:23:06,800 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0762) Prec@1 87.000 (88.000) Prec@5 100.000 (98.960) +2022-11-14 16:23:06,812 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0767) Prec@1 84.000 (87.846) Prec@5 99.000 (98.962) +2022-11-14 16:23:06,823 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0759) Prec@1 91.000 (87.963) Prec@5 100.000 (99.000) +2022-11-14 16:23:06,835 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0752) Prec@1 91.000 (88.071) Prec@5 100.000 (99.036) +2022-11-14 16:23:06,847 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0750) Prec@1 89.000 (88.103) Prec@5 98.000 (99.000) +2022-11-14 16:23:06,858 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0750) Prec@1 90.000 (88.167) Prec@5 100.000 (99.033) +2022-11-14 16:23:06,869 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0753) Prec@1 87.000 (88.129) Prec@5 100.000 (99.065) +2022-11-14 16:23:06,882 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0754) Prec@1 86.000 (88.062) Prec@5 99.000 (99.062) +2022-11-14 16:23:06,894 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0749) Prec@1 89.000 (88.091) Prec@5 100.000 (99.091) +2022-11-14 16:23:06,906 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1020 (0.0757) Prec@1 81.000 (87.882) Prec@5 99.000 (99.088) +2022-11-14 16:23:06,918 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0760) Prec@1 87.000 (87.857) Prec@5 99.000 (99.086) +2022-11-14 16:23:06,931 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0756) Prec@1 92.000 (87.972) Prec@5 100.000 (99.111) +2022-11-14 16:23:06,946 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0753) Prec@1 87.000 (87.946) Prec@5 98.000 (99.081) +2022-11-14 16:23:06,959 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1098 (0.0762) Prec@1 80.000 (87.737) Prec@5 99.000 (99.079) +2022-11-14 16:23:06,973 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0548 (0.0756) Prec@1 92.000 (87.846) Prec@5 99.000 (99.077) +2022-11-14 16:23:06,985 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0758) Prec@1 87.000 (87.825) Prec@5 99.000 (99.075) +2022-11-14 16:23:06,997 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0763) Prec@1 84.000 (87.732) Prec@5 99.000 (99.073) +2022-11-14 16:23:07,011 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0762) Prec@1 88.000 (87.738) Prec@5 100.000 (99.095) +2022-11-14 16:23:07,026 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0758) Prec@1 91.000 (87.814) Prec@5 99.000 (99.093) +2022-11-14 16:23:07,039 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0756) Prec@1 90.000 (87.864) Prec@5 98.000 (99.068) +2022-11-14 16:23:07,050 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0752) Prec@1 91.000 (87.933) Prec@5 100.000 (99.089) +2022-11-14 16:23:07,060 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0757) Prec@1 85.000 (87.870) Prec@5 100.000 (99.109) +2022-11-14 16:23:07,070 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0753) Prec@1 89.000 (87.894) Prec@5 100.000 (99.128) +2022-11-14 16:23:07,082 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1015 (0.0758) Prec@1 83.000 (87.792) Prec@5 99.000 (99.125) +2022-11-14 16:23:07,092 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0407 (0.0751) Prec@1 93.000 (87.898) Prec@5 100.000 (99.143) +2022-11-14 16:23:07,105 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0961 (0.0755) Prec@1 86.000 (87.860) Prec@5 100.000 (99.160) +2022-11-14 16:23:07,116 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0751) Prec@1 90.000 (87.902) Prec@5 100.000 (99.176) +2022-11-14 16:23:07,128 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0752) Prec@1 88.000 (87.904) Prec@5 98.000 (99.154) +2022-11-14 16:23:07,141 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0754) Prec@1 86.000 (87.868) Prec@5 99.000 (99.151) +2022-11-14 16:23:07,153 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0754) Prec@1 85.000 (87.815) Prec@5 99.000 (99.148) +2022-11-14 16:23:07,164 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0758) Prec@1 86.000 (87.782) Prec@5 100.000 (99.164) +2022-11-14 16:23:07,177 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0760) Prec@1 86.000 (87.750) Prec@5 99.000 (99.161) +2022-11-14 16:23:07,192 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0759) Prec@1 87.000 (87.737) Prec@5 99.000 (99.158) +2022-11-14 16:23:07,207 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0757) Prec@1 89.000 (87.759) Prec@5 100.000 (99.172) +2022-11-14 16:23:07,218 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0760) Prec@1 83.000 (87.678) Prec@5 100.000 (99.186) +2022-11-14 16:23:07,232 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0760) Prec@1 88.000 (87.683) Prec@5 100.000 (99.200) +2022-11-14 16:23:07,247 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0759) Prec@1 89.000 (87.705) Prec@5 100.000 (99.213) +2022-11-14 16:23:07,260 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0761) Prec@1 85.000 (87.661) Prec@5 98.000 (99.194) +2022-11-14 16:23:07,273 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0757) Prec@1 92.000 (87.730) Prec@5 100.000 (99.206) +2022-11-14 16:23:07,287 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0754) Prec@1 91.000 (87.781) Prec@5 100.000 (99.219) +2022-11-14 16:23:07,301 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 87.000 (87.769) Prec@5 100.000 (99.231) +2022-11-14 16:23:07,314 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0757) Prec@1 84.000 (87.712) Prec@5 100.000 (99.242) +2022-11-14 16:23:07,328 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0754) Prec@1 91.000 (87.761) Prec@5 100.000 (99.254) +2022-11-14 16:23:07,343 Test: [67/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0753) Prec@1 90.000 (87.794) Prec@5 97.000 (99.221) +2022-11-14 16:23:07,355 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0753) Prec@1 90.000 (87.826) Prec@5 99.000 (99.217) +2022-11-14 16:23:07,367 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0754) Prec@1 89.000 (87.843) Prec@5 100.000 (99.229) +2022-11-14 16:23:07,380 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0758) Prec@1 85.000 (87.803) Prec@5 99.000 (99.225) +2022-11-14 16:23:07,393 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0756) Prec@1 88.000 (87.806) Prec@5 100.000 (99.236) +2022-11-14 16:23:07,405 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0752) Prec@1 93.000 (87.877) Prec@5 99.000 (99.233) +2022-11-14 16:23:07,415 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0347 (0.0747) Prec@1 96.000 (87.986) Prec@5 100.000 (99.243) +2022-11-14 16:23:07,427 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0750) Prec@1 87.000 (87.973) Prec@5 100.000 (99.253) +2022-11-14 16:23:07,440 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0551 (0.0747) Prec@1 92.000 (88.026) Prec@5 100.000 (99.263) +2022-11-14 16:23:07,452 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0750) Prec@1 86.000 (88.000) Prec@5 99.000 (99.260) +2022-11-14 16:23:07,462 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0750) Prec@1 87.000 (87.987) Prec@5 100.000 (99.269) +2022-11-14 16:23:07,473 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0752) Prec@1 84.000 (87.937) Prec@5 99.000 (99.266) +2022-11-14 16:23:07,484 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0751) Prec@1 89.000 (87.950) Prec@5 99.000 (99.263) +2022-11-14 16:23:07,497 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0753) Prec@1 84.000 (87.901) Prec@5 99.000 (99.259) +2022-11-14 16:23:07,510 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0755) Prec@1 89.000 (87.915) Prec@5 99.000 (99.256) +2022-11-14 16:23:07,521 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0755) Prec@1 85.000 (87.880) Prec@5 100.000 (99.265) +2022-11-14 16:23:07,531 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0752) Prec@1 92.000 (87.929) Prec@5 99.000 (99.262) +2022-11-14 16:23:07,544 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0753) Prec@1 86.000 (87.906) Prec@5 100.000 (99.271) +2022-11-14 16:23:07,556 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0755) Prec@1 84.000 (87.860) Prec@5 99.000 (99.267) +2022-11-14 16:23:07,566 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0752) Prec@1 94.000 (87.931) Prec@5 98.000 (99.253) +2022-11-14 16:23:07,578 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0752) Prec@1 88.000 (87.932) Prec@5 99.000 (99.250) +2022-11-14 16:23:07,589 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0751) Prec@1 89.000 (87.944) Prec@5 100.000 (99.258) +2022-11-14 16:23:07,600 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0750) Prec@1 91.000 (87.978) Prec@5 98.000 (99.244) +2022-11-14 16:23:07,611 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0748) Prec@1 91.000 (88.011) Prec@5 100.000 (99.253) +2022-11-14 16:23:07,621 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0747) Prec@1 91.000 (88.043) Prec@5 100.000 (99.261) +2022-11-14 16:23:07,632 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0748) Prec@1 89.000 (88.054) Prec@5 100.000 (99.269) +2022-11-14 16:23:07,644 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0747) Prec@1 91.000 (88.085) Prec@5 99.000 (99.266) +2022-11-14 16:23:07,655 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0746) Prec@1 89.000 (88.095) Prec@5 99.000 (99.263) +2022-11-14 16:23:07,666 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0744) Prec@1 91.000 (88.125) Prec@5 97.000 (99.240) +2022-11-14 16:23:07,677 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0394 (0.0741) Prec@1 95.000 (88.196) Prec@5 98.000 (99.227) +2022-11-14 16:23:07,691 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0742) Prec@1 86.000 (88.173) Prec@5 98.000 (99.214) +2022-11-14 16:23:07,703 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0744) Prec@1 84.000 (88.131) Prec@5 99.000 (99.212) +2022-11-14 16:23:07,715 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0744) Prec@1 85.000 (88.100) Prec@5 98.000 (99.200) +2022-11-14 16:23:07,776 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:23:08,154 Epoch: [337][0/500] Time 0.028 (0.028) Data 0.280 (0.280) Loss 0.0397 (0.0397) Prec@1 92.000 (92.000) Prec@5 98.000 (98.000) +2022-11-14 16:23:08,424 Epoch: [337][10/500] Time 0.030 (0.025) Data 0.002 (0.028) Loss 0.0474 (0.0435) Prec@1 94.000 (93.000) Prec@5 100.000 (99.000) +2022-11-14 16:23:08,847 Epoch: [337][20/500] Time 0.047 (0.030) Data 0.002 (0.015) Loss 0.0169 (0.0347) Prec@1 98.000 (94.667) Prec@5 100.000 (99.333) +2022-11-14 16:23:09,361 Epoch: [337][30/500] Time 0.049 (0.035) Data 0.002 (0.011) Loss 0.0309 (0.0337) Prec@1 96.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:23:09,857 Epoch: [337][40/500] Time 0.041 (0.038) Data 0.002 (0.009) Loss 0.0344 (0.0338) Prec@1 93.000 (94.600) Prec@5 100.000 (99.600) +2022-11-14 16:23:10,393 Epoch: [337][50/500] Time 0.046 (0.040) Data 0.002 (0.008) Loss 0.0249 (0.0324) Prec@1 95.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:23:10,895 Epoch: [337][60/500] Time 0.055 (0.041) Data 0.002 (0.007) Loss 0.0249 (0.0313) Prec@1 95.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 16:23:11,384 Epoch: [337][70/500] Time 0.048 (0.041) Data 0.002 (0.006) Loss 0.0194 (0.0298) Prec@1 97.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:23:11,877 Epoch: [337][80/500] Time 0.051 (0.041) Data 0.002 (0.006) Loss 0.0157 (0.0282) Prec@1 96.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:23:12,354 Epoch: [337][90/500] Time 0.053 (0.041) Data 0.002 (0.005) Loss 0.0339 (0.0288) Prec@1 95.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 16:23:12,842 Epoch: [337][100/500] Time 0.039 (0.042) Data 0.002 (0.005) Loss 0.0168 (0.0277) Prec@1 97.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 16:23:13,323 Epoch: [337][110/500] Time 0.051 (0.042) Data 0.003 (0.005) Loss 0.0093 (0.0262) Prec@1 98.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 16:23:13,823 Epoch: [337][120/500] Time 0.054 (0.042) Data 0.002 (0.005) Loss 0.0312 (0.0266) Prec@1 95.000 (95.462) Prec@5 100.000 (99.846) +2022-11-14 16:23:14,309 Epoch: [337][130/500] Time 0.045 (0.042) Data 0.002 (0.004) Loss 0.0542 (0.0285) Prec@1 94.000 (95.357) Prec@5 98.000 (99.714) +2022-11-14 16:23:14,799 Epoch: [337][140/500] Time 0.041 (0.042) Data 0.002 (0.004) Loss 0.0125 (0.0275) Prec@1 99.000 (95.600) Prec@5 100.000 (99.733) +2022-11-14 16:23:15,290 Epoch: [337][150/500] Time 0.046 (0.042) Data 0.003 (0.004) Loss 0.0387 (0.0282) Prec@1 93.000 (95.438) Prec@5 100.000 (99.750) +2022-11-14 16:23:15,790 Epoch: [337][160/500] Time 0.055 (0.042) Data 0.002 (0.004) Loss 0.0333 (0.0285) Prec@1 95.000 (95.412) Prec@5 100.000 (99.765) +2022-11-14 16:23:16,315 Epoch: [337][170/500] Time 0.041 (0.043) Data 0.002 (0.004) Loss 0.0163 (0.0278) Prec@1 97.000 (95.500) Prec@5 100.000 (99.778) +2022-11-14 16:23:16,842 Epoch: [337][180/500] Time 0.052 (0.043) Data 0.002 (0.004) Loss 0.0460 (0.0288) Prec@1 92.000 (95.316) Prec@5 100.000 (99.789) +2022-11-14 16:23:17,361 Epoch: [337][190/500] Time 0.065 (0.043) Data 0.002 (0.004) Loss 0.0408 (0.0294) Prec@1 94.000 (95.250) Prec@5 100.000 (99.800) +2022-11-14 16:23:17,869 Epoch: [337][200/500] Time 0.049 (0.043) Data 0.002 (0.004) Loss 0.0389 (0.0298) Prec@1 95.000 (95.238) Prec@5 99.000 (99.762) +2022-11-14 16:23:18,407 Epoch: [337][210/500] Time 0.043 (0.043) Data 0.002 (0.004) Loss 0.0394 (0.0302) Prec@1 93.000 (95.136) Prec@5 100.000 (99.773) +2022-11-14 16:23:18,910 Epoch: [337][220/500] Time 0.047 (0.043) Data 0.002 (0.004) Loss 0.0477 (0.0310) Prec@1 94.000 (95.087) Prec@5 100.000 (99.783) +2022-11-14 16:23:19,399 Epoch: [337][230/500] Time 0.045 (0.043) Data 0.002 (0.003) Loss 0.0086 (0.0301) Prec@1 99.000 (95.250) Prec@5 100.000 (99.792) +2022-11-14 16:23:19,899 Epoch: [337][240/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0303 (0.0301) Prec@1 95.000 (95.240) Prec@5 100.000 (99.800) +2022-11-14 16:23:20,390 Epoch: [337][250/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0203 (0.0297) Prec@1 96.000 (95.269) Prec@5 100.000 (99.808) +2022-11-14 16:23:20,883 Epoch: [337][260/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0207 (0.0294) Prec@1 95.000 (95.259) Prec@5 100.000 (99.815) +2022-11-14 16:23:21,395 Epoch: [337][270/500] Time 0.047 (0.044) Data 0.003 (0.003) Loss 0.0325 (0.0295) Prec@1 94.000 (95.214) Prec@5 100.000 (99.821) +2022-11-14 16:23:21,896 Epoch: [337][280/500] Time 0.048 (0.044) Data 0.003 (0.003) Loss 0.0363 (0.0297) Prec@1 93.000 (95.138) Prec@5 100.000 (99.828) +2022-11-14 16:23:22,396 Epoch: [337][290/500] Time 0.047 (0.044) Data 0.003 (0.003) Loss 0.0359 (0.0299) Prec@1 94.000 (95.100) Prec@5 100.000 (99.833) +2022-11-14 16:23:22,903 Epoch: [337][300/500] Time 0.050 (0.044) Data 0.003 (0.003) Loss 0.0207 (0.0296) Prec@1 97.000 (95.161) Prec@5 100.000 (99.839) +2022-11-14 16:23:23,397 Epoch: [337][310/500] Time 0.050 (0.044) Data 0.004 (0.003) Loss 0.0373 (0.0299) Prec@1 94.000 (95.125) Prec@5 100.000 (99.844) +2022-11-14 16:23:23,908 Epoch: [337][320/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0387 (0.0301) Prec@1 94.000 (95.091) Prec@5 100.000 (99.848) +2022-11-14 16:23:24,435 Epoch: [337][330/500] Time 0.051 (0.044) Data 0.003 (0.003) Loss 0.0289 (0.0301) Prec@1 96.000 (95.118) Prec@5 100.000 (99.853) +2022-11-14 16:23:24,936 Epoch: [337][340/500] Time 0.060 (0.044) Data 0.002 (0.003) Loss 0.0098 (0.0295) Prec@1 99.000 (95.229) Prec@5 100.000 (99.857) +2022-11-14 16:23:25,429 Epoch: [337][350/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0312 (0.0296) Prec@1 96.000 (95.250) Prec@5 100.000 (99.861) +2022-11-14 16:23:25,927 Epoch: [337][360/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0261 (0.0295) Prec@1 95.000 (95.243) Prec@5 100.000 (99.865) +2022-11-14 16:23:26,431 Epoch: [337][370/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0647 (0.0304) Prec@1 89.000 (95.079) Prec@5 98.000 (99.816) +2022-11-14 16:23:26,931 Epoch: [337][380/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0218 (0.0302) Prec@1 97.000 (95.128) Prec@5 100.000 (99.821) +2022-11-14 16:23:27,430 Epoch: [337][390/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0177 (0.0299) Prec@1 98.000 (95.200) Prec@5 100.000 (99.825) +2022-11-14 16:23:27,923 Epoch: [337][400/500] Time 0.059 (0.044) Data 0.002 (0.003) Loss 0.0387 (0.0301) Prec@1 94.000 (95.171) Prec@5 100.000 (99.829) +2022-11-14 16:23:28,424 Epoch: [337][410/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0236 (0.0299) Prec@1 96.000 (95.190) Prec@5 100.000 (99.833) +2022-11-14 16:23:28,920 Epoch: [337][420/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0362 (0.0301) Prec@1 95.000 (95.186) Prec@5 100.000 (99.837) +2022-11-14 16:23:29,418 Epoch: [337][430/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0267 (0.0300) Prec@1 94.000 (95.159) Prec@5 100.000 (99.841) +2022-11-14 16:23:29,930 Epoch: [337][440/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0345 (0.0301) Prec@1 96.000 (95.178) Prec@5 100.000 (99.844) +2022-11-14 16:23:30,434 Epoch: [337][450/500] Time 0.046 (0.044) Data 0.003 (0.003) Loss 0.0121 (0.0297) Prec@1 98.000 (95.239) Prec@5 100.000 (99.848) +2022-11-14 16:23:30,939 Epoch: [337][460/500] Time 0.046 (0.044) Data 0.002 (0.003) Loss 0.0374 (0.0299) Prec@1 94.000 (95.213) Prec@5 100.000 (99.851) +2022-11-14 16:23:31,444 Epoch: [337][470/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0388 (0.0301) Prec@1 93.000 (95.167) Prec@5 100.000 (99.854) +2022-11-14 16:23:31,975 Epoch: [337][480/500] Time 0.052 (0.044) Data 0.002 (0.003) Loss 0.0283 (0.0300) Prec@1 94.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:23:32,473 Epoch: [337][490/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0192 (0.0298) Prec@1 98.000 (95.200) Prec@5 99.000 (99.840) +2022-11-14 16:23:32,919 Epoch: [337][499/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0204 (0.0296) Prec@1 97.000 (95.235) Prec@5 100.000 (99.843) +2022-11-14 16:23:33,247 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0725 (0.0725) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:23:33,259 Test: [1/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0658 (0.0692) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:23:33,270 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0671 (0.0685) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:23:33,284 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0710 (0.0691) Prec@1 88.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 16:23:33,294 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0723) Prec@1 86.000 (87.600) Prec@5 99.000 (99.600) +2022-11-14 16:23:33,306 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0460 (0.0679) Prec@1 92.000 (88.333) Prec@5 99.000 (99.500) +2022-11-14 16:23:33,317 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0679) Prec@1 91.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 16:23:33,330 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0684) Prec@1 91.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 16:23:33,343 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0692) Prec@1 89.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:23:33,360 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0707) Prec@1 87.000 (88.800) Prec@5 98.000 (99.500) +2022-11-14 16:23:33,374 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0692) Prec@1 91.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 16:23:33,388 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0694) Prec@1 90.000 (89.083) Prec@5 100.000 (99.583) +2022-11-14 16:23:33,400 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0688) Prec@1 93.000 (89.385) Prec@5 100.000 (99.615) +2022-11-14 16:23:33,415 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0697) Prec@1 89.000 (89.357) Prec@5 100.000 (99.643) +2022-11-14 16:23:33,431 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0709) Prec@1 87.000 (89.200) Prec@5 100.000 (99.667) +2022-11-14 16:23:33,445 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0713) Prec@1 86.000 (89.000) Prec@5 99.000 (99.625) +2022-11-14 16:23:33,462 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0701) Prec@1 92.000 (89.176) Prec@5 98.000 (99.529) +2022-11-14 16:23:33,478 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0723) Prec@1 82.000 (88.778) Prec@5 99.000 (99.500) +2022-11-14 16:23:33,493 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0731) Prec@1 84.000 (88.526) Prec@5 99.000 (99.474) +2022-11-14 16:23:33,508 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0739) Prec@1 87.000 (88.450) Prec@5 98.000 (99.400) +2022-11-14 16:23:33,524 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0741) Prec@1 87.000 (88.381) Prec@5 99.000 (99.381) +2022-11-14 16:23:33,543 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0747) Prec@1 86.000 (88.273) Prec@5 98.000 (99.318) +2022-11-14 16:23:33,561 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0751) Prec@1 87.000 (88.217) Prec@5 97.000 (99.217) +2022-11-14 16:23:33,576 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0754) Prec@1 86.000 (88.125) Prec@5 100.000 (99.250) +2022-11-14 16:23:33,592 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0756) Prec@1 89.000 (88.160) Prec@5 99.000 (99.240) +2022-11-14 16:23:33,609 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0763) Prec@1 84.000 (88.000) Prec@5 100.000 (99.269) +2022-11-14 16:23:33,628 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0752) Prec@1 94.000 (88.222) Prec@5 100.000 (99.296) +2022-11-14 16:23:33,646 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0747) Prec@1 91.000 (88.321) Prec@5 99.000 (99.286) +2022-11-14 16:23:33,661 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0752) Prec@1 84.000 (88.172) Prec@5 99.000 (99.276) +2022-11-14 16:23:33,680 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0749) Prec@1 90.000 (88.233) Prec@5 100.000 (99.300) +2022-11-14 16:23:33,695 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0749) Prec@1 87.000 (88.194) Prec@5 99.000 (99.290) +2022-11-14 16:23:33,711 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0751) Prec@1 89.000 (88.219) Prec@5 99.000 (99.281) +2022-11-14 16:23:33,726 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0755) Prec@1 85.000 (88.121) Prec@5 100.000 (99.303) +2022-11-14 16:23:33,741 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0761) Prec@1 83.000 (87.971) Prec@5 97.000 (99.235) +2022-11-14 16:23:33,760 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0761) Prec@1 89.000 (88.000) Prec@5 97.000 (99.171) +2022-11-14 16:23:33,780 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0758) Prec@1 90.000 (88.056) Prec@5 100.000 (99.194) +2022-11-14 16:23:33,795 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0756) Prec@1 89.000 (88.081) Prec@5 100.000 (99.216) +2022-11-14 16:23:33,811 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0759) Prec@1 84.000 (87.974) Prec@5 100.000 (99.237) +2022-11-14 16:23:33,825 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0753) Prec@1 91.000 (88.051) Prec@5 99.000 (99.231) +2022-11-14 16:23:33,842 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0750) Prec@1 90.000 (88.100) Prec@5 99.000 (99.225) +2022-11-14 16:23:33,860 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0757) Prec@1 82.000 (87.951) Prec@5 99.000 (99.220) +2022-11-14 16:23:33,879 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0753) Prec@1 90.000 (88.000) Prec@5 98.000 (99.190) +2022-11-14 16:23:33,897 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0374 (0.0745) Prec@1 94.000 (88.140) Prec@5 99.000 (99.186) +2022-11-14 16:23:33,915 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0746) Prec@1 88.000 (88.136) Prec@5 99.000 (99.182) +2022-11-14 16:23:33,932 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0742) Prec@1 91.000 (88.200) Prec@5 99.000 (99.178) +2022-11-14 16:23:33,947 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0746) Prec@1 85.000 (88.130) Prec@5 99.000 (99.174) +2022-11-14 16:23:33,964 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0746) Prec@1 86.000 (88.085) Prec@5 99.000 (99.170) +2022-11-14 16:23:33,981 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0748) Prec@1 85.000 (88.021) Prec@5 98.000 (99.146) +2022-11-14 16:23:33,996 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0746) Prec@1 89.000 (88.041) Prec@5 100.000 (99.163) +2022-11-14 16:23:34,011 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0750) Prec@1 85.000 (87.980) Prec@5 100.000 (99.180) +2022-11-14 16:23:34,028 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0748) Prec@1 88.000 (87.980) Prec@5 100.000 (99.196) +2022-11-14 16:23:34,043 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0752) Prec@1 83.000 (87.885) Prec@5 99.000 (99.192) +2022-11-14 16:23:34,060 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0751) Prec@1 88.000 (87.887) Prec@5 100.000 (99.208) +2022-11-14 16:23:34,080 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0753) Prec@1 85.000 (87.833) Prec@5 100.000 (99.222) +2022-11-14 16:23:34,098 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0753) Prec@1 86.000 (87.800) Prec@5 100.000 (99.236) +2022-11-14 16:23:34,116 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0752) Prec@1 88.000 (87.804) Prec@5 99.000 (99.232) +2022-11-14 16:23:34,133 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0750) Prec@1 90.000 (87.842) Prec@5 99.000 (99.228) +2022-11-14 16:23:34,148 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0749) Prec@1 90.000 (87.879) Prec@5 99.000 (99.224) +2022-11-14 16:23:34,164 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0754) Prec@1 85.000 (87.831) Prec@5 99.000 (99.220) +2022-11-14 16:23:34,182 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0753) Prec@1 87.000 (87.817) Prec@5 100.000 (99.233) +2022-11-14 16:23:34,199 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0753) Prec@1 90.000 (87.852) Prec@5 100.000 (99.246) +2022-11-14 16:23:34,215 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0751) Prec@1 90.000 (87.887) Prec@5 100.000 (99.258) +2022-11-14 16:23:34,229 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0750) Prec@1 89.000 (87.905) Prec@5 100.000 (99.270) +2022-11-14 16:23:34,245 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0746) Prec@1 91.000 (87.953) Prec@5 100.000 (99.281) +2022-11-14 16:23:34,263 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0746) Prec@1 88.000 (87.954) Prec@5 100.000 (99.292) +2022-11-14 16:23:34,280 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0748) Prec@1 86.000 (87.924) Prec@5 98.000 (99.273) +2022-11-14 16:23:34,295 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0490 (0.0744) Prec@1 93.000 (88.000) Prec@5 99.000 (99.269) +2022-11-14 16:23:34,314 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0745) Prec@1 89.000 (88.015) Prec@5 98.000 (99.250) +2022-11-14 16:23:34,330 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0746) Prec@1 87.000 (88.000) Prec@5 99.000 (99.246) +2022-11-14 16:23:34,348 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0748) Prec@1 87.000 (87.986) Prec@5 99.000 (99.243) +2022-11-14 16:23:34,362 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0751) Prec@1 87.000 (87.972) Prec@5 100.000 (99.254) +2022-11-14 16:23:34,379 Test: [71/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0748) Prec@1 91.000 (88.014) Prec@5 100.000 (99.264) +2022-11-14 16:23:34,396 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0745) Prec@1 93.000 (88.082) Prec@5 100.000 (99.274) +2022-11-14 16:23:34,411 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0469 (0.0741) Prec@1 93.000 (88.149) Prec@5 99.000 (99.270) +2022-11-14 16:23:34,428 Test: [74/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0741) Prec@1 89.000 (88.160) Prec@5 98.000 (99.253) +2022-11-14 16:23:34,446 Test: [75/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0739) Prec@1 92.000 (88.211) Prec@5 100.000 (99.263) +2022-11-14 16:23:34,465 Test: [76/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0738) Prec@1 89.000 (88.221) Prec@5 98.000 (99.247) +2022-11-14 16:23:34,479 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0742) Prec@1 85.000 (88.179) Prec@5 96.000 (99.205) +2022-11-14 16:23:34,496 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0744) Prec@1 87.000 (88.165) Prec@5 99.000 (99.203) +2022-11-14 16:23:34,511 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0743) Prec@1 90.000 (88.188) Prec@5 99.000 (99.200) +2022-11-14 16:23:34,529 Test: [80/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0744) Prec@1 87.000 (88.173) Prec@5 98.000 (99.185) +2022-11-14 16:23:34,546 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0746) Prec@1 85.000 (88.134) Prec@5 99.000 (99.183) +2022-11-14 16:23:34,565 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0748) Prec@1 86.000 (88.108) Prec@5 100.000 (99.193) +2022-11-14 16:23:34,584 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0746) Prec@1 90.000 (88.131) Prec@5 98.000 (99.179) +2022-11-14 16:23:34,598 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0919 (0.0748) Prec@1 86.000 (88.106) Prec@5 100.000 (99.188) +2022-11-14 16:23:34,616 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0751) Prec@1 82.000 (88.035) Prec@5 100.000 (99.198) +2022-11-14 16:23:34,632 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0748) Prec@1 91.000 (88.069) Prec@5 100.000 (99.207) +2022-11-14 16:23:34,649 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0749) Prec@1 88.000 (88.068) Prec@5 99.000 (99.205) +2022-11-14 16:23:34,666 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0750) Prec@1 86.000 (88.045) Prec@5 100.000 (99.213) +2022-11-14 16:23:34,683 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0751) Prec@1 85.000 (88.011) Prec@5 99.000 (99.211) +2022-11-14 16:23:34,700 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0749) Prec@1 90.000 (88.033) Prec@5 100.000 (99.220) +2022-11-14 16:23:34,715 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0450 (0.0746) Prec@1 94.000 (88.098) Prec@5 99.000 (99.217) +2022-11-14 16:23:34,729 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0748) Prec@1 87.000 (88.086) Prec@5 99.000 (99.215) +2022-11-14 16:23:34,743 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0747) Prec@1 88.000 (88.085) Prec@5 100.000 (99.223) +2022-11-14 16:23:34,761 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0747) Prec@1 86.000 (88.063) Prec@5 99.000 (99.221) +2022-11-14 16:23:34,782 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0466 (0.0744) Prec@1 94.000 (88.125) Prec@5 99.000 (99.219) +2022-11-14 16:23:34,800 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0742) Prec@1 93.000 (88.175) Prec@5 98.000 (99.206) +2022-11-14 16:23:34,815 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0742) Prec@1 88.000 (88.173) Prec@5 99.000 (99.204) +2022-11-14 16:23:34,832 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0745) Prec@1 85.000 (88.141) Prec@5 99.000 (99.202) +2022-11-14 16:23:34,848 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0745) Prec@1 88.000 (88.140) Prec@5 99.000 (99.200) +2022-11-14 16:23:34,939 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:23:35,332 Epoch: [338][0/500] Time 0.024 (0.024) Data 0.294 (0.294) Loss 0.0400 (0.0400) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:23:35,622 Epoch: [338][10/500] Time 0.031 (0.026) Data 0.002 (0.028) Loss 0.0195 (0.0298) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:23:35,927 Epoch: [338][20/500] Time 0.027 (0.026) Data 0.002 (0.016) Loss 0.0313 (0.0303) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:23:36,305 Epoch: [338][30/500] Time 0.049 (0.028) Data 0.002 (0.011) Loss 0.0183 (0.0273) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:23:36,841 Epoch: [338][40/500] Time 0.048 (0.033) Data 0.002 (0.009) Loss 0.0272 (0.0273) Prec@1 95.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:23:37,405 Epoch: [338][50/500] Time 0.047 (0.036) Data 0.002 (0.008) Loss 0.0360 (0.0287) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:23:37,949 Epoch: [338][60/500] Time 0.048 (0.038) Data 0.002 (0.007) Loss 0.0332 (0.0294) Prec@1 95.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 16:23:38,506 Epoch: [338][70/500] Time 0.049 (0.040) Data 0.002 (0.006) Loss 0.0300 (0.0295) Prec@1 96.000 (95.625) Prec@5 100.000 (100.000) +2022-11-14 16:23:39,042 Epoch: [338][80/500] Time 0.046 (0.041) Data 0.002 (0.006) Loss 0.0486 (0.0316) Prec@1 93.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:23:39,600 Epoch: [338][90/500] Time 0.058 (0.042) Data 0.002 (0.005) Loss 0.0061 (0.0290) Prec@1 99.000 (95.700) Prec@5 100.000 (100.000) +2022-11-14 16:23:40,145 Epoch: [338][100/500] Time 0.055 (0.042) Data 0.002 (0.005) Loss 0.0308 (0.0292) Prec@1 95.000 (95.636) Prec@5 100.000 (100.000) +2022-11-14 16:23:40,703 Epoch: [338][110/500] Time 0.059 (0.043) Data 0.002 (0.005) Loss 0.0331 (0.0295) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:23:41,281 Epoch: [338][120/500] Time 0.059 (0.044) Data 0.002 (0.004) Loss 0.0191 (0.0287) Prec@1 97.000 (95.615) Prec@5 100.000 (100.000) +2022-11-14 16:23:41,831 Epoch: [338][130/500] Time 0.058 (0.044) Data 0.002 (0.004) Loss 0.0495 (0.0302) Prec@1 91.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 16:23:42,387 Epoch: [338][140/500] Time 0.063 (0.045) Data 0.002 (0.004) Loss 0.0439 (0.0311) Prec@1 93.000 (95.133) Prec@5 100.000 (100.000) +2022-11-14 16:23:42,959 Epoch: [338][150/500] Time 0.066 (0.045) Data 0.002 (0.004) Loss 0.0263 (0.0308) Prec@1 96.000 (95.188) Prec@5 100.000 (100.000) +2022-11-14 16:23:43,509 Epoch: [338][160/500] Time 0.056 (0.045) Data 0.003 (0.004) Loss 0.0184 (0.0301) Prec@1 97.000 (95.294) Prec@5 100.000 (100.000) +2022-11-14 16:23:44,084 Epoch: [338][170/500] Time 0.058 (0.045) Data 0.002 (0.004) Loss 0.0249 (0.0298) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:23:44,621 Epoch: [338][180/500] Time 0.048 (0.046) Data 0.002 (0.004) Loss 0.0157 (0.0291) Prec@1 98.000 (95.474) Prec@5 100.000 (100.000) +2022-11-14 16:23:45,173 Epoch: [338][190/500] Time 0.052 (0.046) Data 0.003 (0.004) Loss 0.0513 (0.0302) Prec@1 93.000 (95.350) Prec@5 100.000 (100.000) +2022-11-14 16:23:45,732 Epoch: [338][200/500] Time 0.049 (0.046) Data 0.003 (0.004) Loss 0.0241 (0.0299) Prec@1 96.000 (95.381) Prec@5 100.000 (100.000) +2022-11-14 16:23:46,295 Epoch: [338][210/500] Time 0.060 (0.046) Data 0.002 (0.003) Loss 0.0321 (0.0300) Prec@1 94.000 (95.318) Prec@5 99.000 (99.955) +2022-11-14 16:23:46,847 Epoch: [338][220/500] Time 0.053 (0.046) Data 0.003 (0.003) Loss 0.0358 (0.0302) Prec@1 93.000 (95.217) Prec@5 99.000 (99.913) +2022-11-14 16:23:47,389 Epoch: [338][230/500] Time 0.044 (0.046) Data 0.002 (0.003) Loss 0.0184 (0.0297) Prec@1 96.000 (95.250) Prec@5 99.000 (99.875) +2022-11-14 16:23:47,953 Epoch: [338][240/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0163 (0.0292) Prec@1 97.000 (95.320) Prec@5 100.000 (99.880) +2022-11-14 16:23:48,500 Epoch: [338][250/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0226 (0.0289) Prec@1 96.000 (95.346) Prec@5 100.000 (99.885) +2022-11-14 16:23:49,058 Epoch: [338][260/500] Time 0.060 (0.047) Data 0.002 (0.003) Loss 0.0042 (0.0280) Prec@1 100.000 (95.519) Prec@5 100.000 (99.889) +2022-11-14 16:23:49,601 Epoch: [338][270/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0497 (0.0288) Prec@1 91.000 (95.357) Prec@5 99.000 (99.857) +2022-11-14 16:23:50,168 Epoch: [338][280/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0306 (0.0289) Prec@1 95.000 (95.345) Prec@5 100.000 (99.862) +2022-11-14 16:23:50,726 Epoch: [338][290/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0249 (0.0287) Prec@1 97.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:23:51,258 Epoch: [338][300/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0163 (0.0283) Prec@1 98.000 (95.484) Prec@5 100.000 (99.871) +2022-11-14 16:23:51,820 Epoch: [338][310/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0165 (0.0280) Prec@1 97.000 (95.531) Prec@5 100.000 (99.875) +2022-11-14 16:23:52,374 Epoch: [338][320/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0465 (0.0285) Prec@1 93.000 (95.455) Prec@5 100.000 (99.879) +2022-11-14 16:23:52,930 Epoch: [338][330/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0210 (0.0283) Prec@1 97.000 (95.500) Prec@5 100.000 (99.882) +2022-11-14 16:23:53,471 Epoch: [338][340/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0258 (0.0282) Prec@1 95.000 (95.486) Prec@5 100.000 (99.886) +2022-11-14 16:23:54,027 Epoch: [338][350/500] Time 0.053 (0.047) Data 0.002 (0.003) Loss 0.0306 (0.0283) Prec@1 95.000 (95.472) Prec@5 100.000 (99.889) +2022-11-14 16:23:54,574 Epoch: [338][360/500] Time 0.048 (0.047) Data 0.003 (0.003) Loss 0.0260 (0.0282) Prec@1 94.000 (95.432) Prec@5 100.000 (99.892) +2022-11-14 16:23:55,112 Epoch: [338][370/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0306 (0.0283) Prec@1 95.000 (95.421) Prec@5 100.000 (99.895) +2022-11-14 16:23:55,673 Epoch: [338][380/500] Time 0.062 (0.048) Data 0.002 (0.003) Loss 0.0435 (0.0287) Prec@1 92.000 (95.333) Prec@5 99.000 (99.872) +2022-11-14 16:23:56,211 Epoch: [338][390/500] Time 0.046 (0.048) Data 0.002 (0.003) Loss 0.0299 (0.0287) Prec@1 95.000 (95.325) Prec@5 99.000 (99.850) +2022-11-14 16:23:56,756 Epoch: [338][400/500] Time 0.054 (0.048) Data 0.003 (0.003) Loss 0.0177 (0.0284) Prec@1 97.000 (95.366) Prec@5 100.000 (99.854) +2022-11-14 16:23:57,323 Epoch: [338][410/500] Time 0.055 (0.048) Data 0.003 (0.003) Loss 0.0348 (0.0286) Prec@1 93.000 (95.310) Prec@5 100.000 (99.857) +2022-11-14 16:23:57,878 Epoch: [338][420/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0155 (0.0283) Prec@1 97.000 (95.349) Prec@5 100.000 (99.860) +2022-11-14 16:23:58,420 Epoch: [338][430/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0346 (0.0284) Prec@1 92.000 (95.273) Prec@5 99.000 (99.841) +2022-11-14 16:23:58,982 Epoch: [338][440/500] Time 0.060 (0.048) Data 0.002 (0.003) Loss 0.0294 (0.0285) Prec@1 95.000 (95.267) Prec@5 100.000 (99.844) +2022-11-14 16:23:59,553 Epoch: [338][450/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0152 (0.0282) Prec@1 98.000 (95.326) Prec@5 100.000 (99.848) +2022-11-14 16:24:00,143 Epoch: [338][460/500] Time 0.062 (0.048) Data 0.002 (0.003) Loss 0.0234 (0.0281) Prec@1 97.000 (95.362) Prec@5 100.000 (99.851) +2022-11-14 16:24:00,698 Epoch: [338][470/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0270 (0.0280) Prec@1 96.000 (95.375) Prec@5 100.000 (99.854) +2022-11-14 16:24:01,255 Epoch: [338][480/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0342 (0.0282) Prec@1 95.000 (95.367) Prec@5 100.000 (99.857) +2022-11-14 16:24:01,811 Epoch: [338][490/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0337 (0.0283) Prec@1 95.000 (95.360) Prec@5 100.000 (99.860) +2022-11-14 16:24:02,317 Epoch: [338][499/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0114 (0.0280) Prec@1 98.000 (95.412) Prec@5 100.000 (99.863) +2022-11-14 16:24:02,631 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0784 (0.0784) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:24:02,640 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0727 (0.0756) Prec@1 89.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:24:02,651 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0784) Prec@1 86.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 16:24:02,663 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0779) Prec@1 88.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 16:24:02,673 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0776) Prec@1 89.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 16:24:02,684 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0726) Prec@1 92.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:24:02,695 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0714) Prec@1 90.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 16:24:02,710 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0721) Prec@1 88.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 16:24:02,725 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0751) Prec@1 84.000 (88.222) Prec@5 98.000 (99.556) +2022-11-14 16:24:02,742 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0756) Prec@1 89.000 (88.300) Prec@5 99.000 (99.500) +2022-11-14 16:24:02,756 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0742) Prec@1 92.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 16:24:02,770 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0741) Prec@1 89.000 (88.667) Prec@5 100.000 (99.583) +2022-11-14 16:24:02,788 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0740) Prec@1 88.000 (88.615) Prec@5 100.000 (99.615) +2022-11-14 16:24:02,807 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0732) Prec@1 89.000 (88.643) Prec@5 99.000 (99.571) +2022-11-14 16:24:02,824 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0745) Prec@1 86.000 (88.467) Prec@5 99.000 (99.533) +2022-11-14 16:24:02,843 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0753) Prec@1 83.000 (88.125) Prec@5 100.000 (99.562) +2022-11-14 16:24:02,860 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0424 (0.0733) Prec@1 94.000 (88.471) Prec@5 98.000 (99.471) +2022-11-14 16:24:02,876 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0749) Prec@1 86.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 16:24:02,894 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0751) Prec@1 89.000 (88.368) Prec@5 100.000 (99.526) +2022-11-14 16:24:02,911 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0750) Prec@1 89.000 (88.400) Prec@5 98.000 (99.450) +2022-11-14 16:24:02,929 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0749) Prec@1 89.000 (88.429) Prec@5 100.000 (99.476) +2022-11-14 16:24:02,949 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0755) Prec@1 81.000 (88.091) Prec@5 98.000 (99.409) +2022-11-14 16:24:02,970 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0759) Prec@1 87.000 (88.043) Prec@5 99.000 (99.391) +2022-11-14 16:24:02,989 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0760) Prec@1 87.000 (88.000) Prec@5 99.000 (99.375) +2022-11-14 16:24:03,008 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0761) Prec@1 87.000 (87.960) Prec@5 99.000 (99.360) +2022-11-14 16:24:03,027 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0768) Prec@1 84.000 (87.808) Prec@5 98.000 (99.308) +2022-11-14 16:24:03,047 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0761) Prec@1 90.000 (87.889) Prec@5 100.000 (99.333) +2022-11-14 16:24:03,067 Test: [27/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0756) Prec@1 91.000 (88.000) Prec@5 100.000 (99.357) +2022-11-14 16:24:03,087 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0750) Prec@1 90.000 (88.069) Prec@5 99.000 (99.345) +2022-11-14 16:24:03,107 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0747) Prec@1 90.000 (88.133) Prec@5 99.000 (99.333) +2022-11-14 16:24:03,124 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0740) Prec@1 91.000 (88.226) Prec@5 100.000 (99.355) +2022-11-14 16:24:03,144 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0741) Prec@1 87.000 (88.188) Prec@5 99.000 (99.344) +2022-11-14 16:24:03,165 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0737) Prec@1 89.000 (88.212) Prec@5 100.000 (99.364) +2022-11-14 16:24:03,185 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0738) Prec@1 83.000 (88.059) Prec@5 100.000 (99.382) +2022-11-14 16:24:03,205 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0740) Prec@1 89.000 (88.086) Prec@5 98.000 (99.343) +2022-11-14 16:24:03,227 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0738) Prec@1 91.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 16:24:03,245 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0736) Prec@1 89.000 (88.189) Prec@5 98.000 (99.297) +2022-11-14 16:24:03,267 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0962 (0.0742) Prec@1 82.000 (88.026) Prec@5 99.000 (99.289) +2022-11-14 16:24:03,286 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0736) Prec@1 93.000 (88.154) Prec@5 100.000 (99.308) +2022-11-14 16:24:03,305 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0737) Prec@1 89.000 (88.175) Prec@5 99.000 (99.300) +2022-11-14 16:24:03,325 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0740) Prec@1 86.000 (88.122) Prec@5 99.000 (99.293) +2022-11-14 16:24:03,344 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0736) Prec@1 91.000 (88.190) Prec@5 100.000 (99.310) +2022-11-14 16:24:03,362 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0730) Prec@1 91.000 (88.256) Prec@5 100.000 (99.326) +2022-11-14 16:24:03,380 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0730) Prec@1 88.000 (88.250) Prec@5 99.000 (99.318) +2022-11-14 16:24:03,401 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0728) Prec@1 90.000 (88.289) Prec@5 99.000 (99.311) +2022-11-14 16:24:03,419 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1149 (0.0737) Prec@1 83.000 (88.174) Prec@5 100.000 (99.326) +2022-11-14 16:24:03,436 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0736) Prec@1 89.000 (88.191) Prec@5 100.000 (99.340) +2022-11-14 16:24:03,455 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0741) Prec@1 84.000 (88.104) Prec@5 98.000 (99.312) +2022-11-14 16:24:03,477 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0737) Prec@1 91.000 (88.163) Prec@5 100.000 (99.327) +2022-11-14 16:24:03,497 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0989 (0.0742) Prec@1 85.000 (88.100) Prec@5 100.000 (99.340) +2022-11-14 16:24:03,516 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0736) Prec@1 92.000 (88.176) Prec@5 100.000 (99.353) +2022-11-14 16:24:03,533 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0739) Prec@1 86.000 (88.135) Prec@5 100.000 (99.365) +2022-11-14 16:24:03,549 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0741) Prec@1 86.000 (88.094) Prec@5 99.000 (99.358) +2022-11-14 16:24:03,567 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0742) Prec@1 88.000 (88.093) Prec@5 100.000 (99.370) +2022-11-14 16:24:03,585 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0744) Prec@1 86.000 (88.055) Prec@5 100.000 (99.382) +2022-11-14 16:24:03,605 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0745) Prec@1 87.000 (88.036) Prec@5 99.000 (99.375) +2022-11-14 16:24:03,621 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0745) Prec@1 87.000 (88.018) Prec@5 99.000 (99.368) +2022-11-14 16:24:03,642 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0744) Prec@1 89.000 (88.034) Prec@5 100.000 (99.379) +2022-11-14 16:24:03,662 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0745) Prec@1 88.000 (88.034) Prec@5 100.000 (99.390) +2022-11-14 16:24:03,680 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0748) Prec@1 83.000 (87.950) Prec@5 99.000 (99.383) +2022-11-14 16:24:03,698 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0749) Prec@1 85.000 (87.902) Prec@5 99.000 (99.377) +2022-11-14 16:24:03,719 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0748) Prec@1 91.000 (87.952) Prec@5 99.000 (99.371) +2022-11-14 16:24:03,738 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0750) Prec@1 85.000 (87.905) Prec@5 99.000 (99.365) +2022-11-14 16:24:03,756 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0390 (0.0744) Prec@1 94.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 16:24:03,778 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0746) Prec@1 85.000 (87.954) Prec@5 99.000 (99.369) +2022-11-14 16:24:03,797 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0746) Prec@1 84.000 (87.894) Prec@5 99.000 (99.364) +2022-11-14 16:24:03,818 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0743) Prec@1 91.000 (87.940) Prec@5 100.000 (99.373) +2022-11-14 16:24:03,836 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0741) Prec@1 90.000 (87.971) Prec@5 98.000 (99.353) +2022-11-14 16:24:03,854 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0739) Prec@1 90.000 (88.000) Prec@5 99.000 (99.348) +2022-11-14 16:24:03,874 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0739) Prec@1 89.000 (88.014) Prec@5 100.000 (99.357) +2022-11-14 16:24:03,891 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0741) Prec@1 89.000 (88.028) Prec@5 98.000 (99.338) +2022-11-14 16:24:03,911 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0740) Prec@1 90.000 (88.056) Prec@5 100.000 (99.347) +2022-11-14 16:24:03,930 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0735) Prec@1 91.000 (88.096) Prec@5 100.000 (99.356) +2022-11-14 16:24:03,948 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0733) Prec@1 90.000 (88.122) Prec@5 100.000 (99.365) +2022-11-14 16:24:03,967 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0736) Prec@1 87.000 (88.107) Prec@5 98.000 (99.347) +2022-11-14 16:24:03,984 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0737) Prec@1 87.000 (88.092) Prec@5 98.000 (99.329) +2022-11-14 16:24:04,005 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0738) Prec@1 87.000 (88.078) Prec@5 100.000 (99.338) +2022-11-14 16:24:04,024 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0738) Prec@1 87.000 (88.064) Prec@5 99.000 (99.333) +2022-11-14 16:24:04,040 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0741) Prec@1 83.000 (88.000) Prec@5 100.000 (99.342) +2022-11-14 16:24:04,059 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0740) Prec@1 89.000 (88.013) Prec@5 100.000 (99.350) +2022-11-14 16:24:04,080 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0741) Prec@1 87.000 (88.000) Prec@5 97.000 (99.321) +2022-11-14 16:24:04,099 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0745) Prec@1 81.000 (87.915) Prec@5 99.000 (99.317) +2022-11-14 16:24:04,117 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0748) Prec@1 83.000 (87.855) Prec@5 99.000 (99.313) +2022-11-14 16:24:04,136 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0748) Prec@1 88.000 (87.857) Prec@5 100.000 (99.321) +2022-11-14 16:24:04,152 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0748) Prec@1 88.000 (87.859) Prec@5 100.000 (99.329) +2022-11-14 16:24:04,169 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0752) Prec@1 83.000 (87.802) Prec@5 98.000 (99.314) +2022-11-14 16:24:04,186 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0752) Prec@1 87.000 (87.793) Prec@5 99.000 (99.310) +2022-11-14 16:24:04,203 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0752) Prec@1 88.000 (87.795) Prec@5 99.000 (99.307) +2022-11-14 16:24:04,224 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0751) Prec@1 88.000 (87.798) Prec@5 100.000 (99.315) +2022-11-14 16:24:04,239 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0749) Prec@1 94.000 (87.867) Prec@5 99.000 (99.311) +2022-11-14 16:24:04,256 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0433 (0.0746) Prec@1 92.000 (87.912) Prec@5 100.000 (99.319) +2022-11-14 16:24:04,276 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0744) Prec@1 90.000 (87.935) Prec@5 100.000 (99.326) +2022-11-14 16:24:04,293 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0745) Prec@1 87.000 (87.925) Prec@5 100.000 (99.333) +2022-11-14 16:24:04,312 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0745) Prec@1 90.000 (87.947) Prec@5 100.000 (99.340) +2022-11-14 16:24:04,330 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0748) Prec@1 84.000 (87.905) Prec@5 99.000 (99.337) +2022-11-14 16:24:04,346 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0748) Prec@1 88.000 (87.906) Prec@5 98.000 (99.323) +2022-11-14 16:24:04,366 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0332 (0.0744) Prec@1 93.000 (87.959) Prec@5 100.000 (99.330) +2022-11-14 16:24:04,385 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0747) Prec@1 86.000 (87.939) Prec@5 98.000 (99.316) +2022-11-14 16:24:04,404 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0863 (0.0748) Prec@1 85.000 (87.909) Prec@5 98.000 (99.303) +2022-11-14 16:24:04,423 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0748) Prec@1 89.000 (87.920) Prec@5 100.000 (99.310) +2022-11-14 16:24:04,485 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:24:04,836 Epoch: [339][0/500] Time 0.024 (0.024) Data 0.261 (0.261) Loss 0.0407 (0.0407) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:24:05,150 Epoch: [339][10/500] Time 0.032 (0.027) Data 0.002 (0.025) Loss 0.0417 (0.0412) Prec@1 91.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:24:05,496 Epoch: [339][20/500] Time 0.035 (0.028) Data 0.002 (0.014) Loss 0.0351 (0.0392) Prec@1 95.000 (92.667) Prec@5 100.000 (100.000) +2022-11-14 16:24:06,208 Epoch: [339][30/500] Time 0.072 (0.040) Data 0.002 (0.010) Loss 0.0477 (0.0413) Prec@1 91.000 (92.250) Prec@5 100.000 (100.000) +2022-11-14 16:24:06,937 Epoch: [339][40/500] Time 0.071 (0.046) Data 0.002 (0.008) Loss 0.0444 (0.0419) Prec@1 93.000 (92.400) Prec@5 100.000 (100.000) +2022-11-14 16:24:07,648 Epoch: [339][50/500] Time 0.067 (0.049) Data 0.002 (0.007) Loss 0.0213 (0.0385) Prec@1 96.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:24:08,371 Epoch: [339][60/500] Time 0.079 (0.052) Data 0.002 (0.006) Loss 0.0214 (0.0360) Prec@1 95.000 (93.286) Prec@5 100.000 (100.000) +2022-11-14 16:24:09,055 Epoch: [339][70/500] Time 0.071 (0.053) Data 0.002 (0.006) Loss 0.0316 (0.0355) Prec@1 93.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 16:24:09,730 Epoch: [339][80/500] Time 0.052 (0.054) Data 0.002 (0.005) Loss 0.0372 (0.0357) Prec@1 94.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 16:24:10,435 Epoch: [339][90/500] Time 0.052 (0.055) Data 0.002 (0.005) Loss 0.0349 (0.0356) Prec@1 94.000 (93.400) Prec@5 100.000 (100.000) +2022-11-14 16:24:11,145 Epoch: [339][100/500] Time 0.062 (0.056) Data 0.002 (0.005) Loss 0.0217 (0.0343) Prec@1 96.000 (93.636) Prec@5 100.000 (100.000) +2022-11-14 16:24:11,841 Epoch: [339][110/500] Time 0.070 (0.057) Data 0.002 (0.004) Loss 0.0327 (0.0342) Prec@1 94.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 16:24:12,531 Epoch: [339][120/500] Time 0.068 (0.057) Data 0.002 (0.004) Loss 0.0284 (0.0338) Prec@1 95.000 (93.769) Prec@5 100.000 (100.000) +2022-11-14 16:24:13,217 Epoch: [339][130/500] Time 0.060 (0.057) Data 0.002 (0.004) Loss 0.0475 (0.0347) Prec@1 92.000 (93.643) Prec@5 99.000 (99.929) +2022-11-14 16:24:13,908 Epoch: [339][140/500] Time 0.074 (0.058) Data 0.002 (0.004) Loss 0.0402 (0.0351) Prec@1 94.000 (93.667) Prec@5 99.000 (99.867) +2022-11-14 16:24:14,606 Epoch: [339][150/500] Time 0.064 (0.058) Data 0.002 (0.004) Loss 0.0317 (0.0349) Prec@1 96.000 (93.812) Prec@5 100.000 (99.875) +2022-11-14 16:24:15,281 Epoch: [339][160/500] Time 0.061 (0.058) Data 0.002 (0.004) Loss 0.0359 (0.0350) Prec@1 94.000 (93.824) Prec@5 100.000 (99.882) +2022-11-14 16:24:15,969 Epoch: [339][170/500] Time 0.075 (0.058) Data 0.002 (0.004) Loss 0.0308 (0.0347) Prec@1 96.000 (93.944) Prec@5 100.000 (99.889) +2022-11-14 16:24:16,669 Epoch: [339][180/500] Time 0.070 (0.058) Data 0.002 (0.004) Loss 0.0249 (0.0342) Prec@1 96.000 (94.053) Prec@5 100.000 (99.895) +2022-11-14 16:24:17,359 Epoch: [339][190/500] Time 0.066 (0.059) Data 0.002 (0.003) Loss 0.0357 (0.0343) Prec@1 93.000 (94.000) Prec@5 100.000 (99.900) +2022-11-14 16:24:18,056 Epoch: [339][200/500] Time 0.060 (0.059) Data 0.002 (0.003) Loss 0.0272 (0.0339) Prec@1 96.000 (94.095) Prec@5 100.000 (99.905) +2022-11-14 16:24:18,761 Epoch: [339][210/500] Time 0.068 (0.059) Data 0.002 (0.003) Loss 0.0378 (0.0341) Prec@1 94.000 (94.091) Prec@5 100.000 (99.909) +2022-11-14 16:24:19,411 Epoch: [339][220/500] Time 0.062 (0.059) Data 0.002 (0.003) Loss 0.0144 (0.0333) Prec@1 97.000 (94.217) Prec@5 100.000 (99.913) +2022-11-14 16:24:20,097 Epoch: [339][230/500] Time 0.074 (0.059) Data 0.002 (0.003) Loss 0.0348 (0.0333) Prec@1 93.000 (94.167) Prec@5 100.000 (99.917) +2022-11-14 16:24:20,796 Epoch: [339][240/500] Time 0.062 (0.059) Data 0.002 (0.003) Loss 0.0248 (0.0330) Prec@1 95.000 (94.200) Prec@5 100.000 (99.920) +2022-11-14 16:24:21,475 Epoch: [339][250/500] Time 0.067 (0.059) Data 0.002 (0.003) Loss 0.0231 (0.0326) Prec@1 98.000 (94.346) Prec@5 98.000 (99.846) +2022-11-14 16:24:22,179 Epoch: [339][260/500] Time 0.075 (0.059) Data 0.002 (0.003) Loss 0.0585 (0.0336) Prec@1 90.000 (94.185) Prec@5 99.000 (99.815) +2022-11-14 16:24:22,877 Epoch: [339][270/500] Time 0.070 (0.059) Data 0.002 (0.003) Loss 0.0348 (0.0336) Prec@1 93.000 (94.143) Prec@5 99.000 (99.786) +2022-11-14 16:24:23,576 Epoch: [339][280/500] Time 0.061 (0.060) Data 0.002 (0.003) Loss 0.0309 (0.0335) Prec@1 93.000 (94.103) Prec@5 100.000 (99.793) +2022-11-14 16:24:24,247 Epoch: [339][290/500] Time 0.060 (0.060) Data 0.002 (0.003) Loss 0.0435 (0.0338) Prec@1 95.000 (94.133) Prec@5 100.000 (99.800) +2022-11-14 16:24:24,924 Epoch: [339][300/500] Time 0.066 (0.060) Data 0.002 (0.003) Loss 0.0349 (0.0339) Prec@1 96.000 (94.194) Prec@5 99.000 (99.774) +2022-11-14 16:24:25,587 Epoch: [339][310/500] Time 0.064 (0.060) Data 0.002 (0.003) Loss 0.0333 (0.0339) Prec@1 93.000 (94.156) Prec@5 100.000 (99.781) +2022-11-14 16:24:26,256 Epoch: [339][320/500] Time 0.049 (0.060) Data 0.002 (0.003) Loss 0.0384 (0.0340) Prec@1 94.000 (94.152) Prec@5 100.000 (99.788) +2022-11-14 16:24:26,944 Epoch: [339][330/500] Time 0.060 (0.060) Data 0.002 (0.003) Loss 0.0247 (0.0337) Prec@1 97.000 (94.235) Prec@5 100.000 (99.794) +2022-11-14 16:24:27,631 Epoch: [339][340/500] Time 0.075 (0.060) Data 0.003 (0.003) Loss 0.0353 (0.0338) Prec@1 95.000 (94.257) Prec@5 100.000 (99.800) +2022-11-14 16:24:28,326 Epoch: [339][350/500] Time 0.067 (0.060) Data 0.003 (0.003) Loss 0.0199 (0.0334) Prec@1 97.000 (94.333) Prec@5 100.000 (99.806) +2022-11-14 16:24:29,012 Epoch: [339][360/500] Time 0.065 (0.060) Data 0.002 (0.003) Loss 0.0340 (0.0334) Prec@1 95.000 (94.351) Prec@5 100.000 (99.811) +2022-11-14 16:24:29,708 Epoch: [339][370/500] Time 0.070 (0.060) Data 0.002 (0.003) Loss 0.0259 (0.0332) Prec@1 95.000 (94.368) Prec@5 100.000 (99.816) +2022-11-14 16:24:30,122 Epoch: [339][380/500] Time 0.038 (0.059) Data 0.002 (0.003) Loss 0.0415 (0.0334) Prec@1 95.000 (94.385) Prec@5 100.000 (99.821) +2022-11-14 16:24:30,472 Epoch: [339][390/500] Time 0.035 (0.059) Data 0.002 (0.003) Loss 0.0232 (0.0332) Prec@1 96.000 (94.425) Prec@5 100.000 (99.825) +2022-11-14 16:24:30,827 Epoch: [339][400/500] Time 0.033 (0.058) Data 0.002 (0.003) Loss 0.0404 (0.0333) Prec@1 92.000 (94.366) Prec@5 100.000 (99.829) +2022-11-14 16:24:31,187 Epoch: [339][410/500] Time 0.037 (0.057) Data 0.002 (0.003) Loss 0.0337 (0.0333) Prec@1 93.000 (94.333) Prec@5 99.000 (99.810) +2022-11-14 16:24:31,542 Epoch: [339][420/500] Time 0.030 (0.057) Data 0.002 (0.003) Loss 0.0521 (0.0338) Prec@1 91.000 (94.256) Prec@5 100.000 (99.814) +2022-11-14 16:24:31,908 Epoch: [339][430/500] Time 0.032 (0.056) Data 0.002 (0.003) Loss 0.0372 (0.0339) Prec@1 94.000 (94.250) Prec@5 99.000 (99.795) +2022-11-14 16:24:32,272 Epoch: [339][440/500] Time 0.032 (0.056) Data 0.002 (0.003) Loss 0.0177 (0.0335) Prec@1 98.000 (94.333) Prec@5 100.000 (99.800) +2022-11-14 16:24:32,628 Epoch: [339][450/500] Time 0.032 (0.055) Data 0.002 (0.003) Loss 0.0396 (0.0336) Prec@1 94.000 (94.326) Prec@5 100.000 (99.804) +2022-11-14 16:24:32,983 Epoch: [339][460/500] Time 0.030 (0.055) Data 0.002 (0.003) Loss 0.0444 (0.0339) Prec@1 92.000 (94.277) Prec@5 100.000 (99.809) +2022-11-14 16:24:33,338 Epoch: [339][470/500] Time 0.032 (0.054) Data 0.002 (0.003) Loss 0.0373 (0.0339) Prec@1 94.000 (94.271) Prec@5 99.000 (99.792) +2022-11-14 16:24:33,700 Epoch: [339][480/500] Time 0.035 (0.054) Data 0.002 (0.003) Loss 0.0279 (0.0338) Prec@1 96.000 (94.306) Prec@5 100.000 (99.796) +2022-11-14 16:24:34,066 Epoch: [339][490/500] Time 0.031 (0.053) Data 0.002 (0.003) Loss 0.0671 (0.0345) Prec@1 87.000 (94.160) Prec@5 100.000 (99.800) +2022-11-14 16:24:34,377 Epoch: [339][499/500] Time 0.034 (0.053) Data 0.002 (0.003) Loss 0.0394 (0.0346) Prec@1 94.000 (94.157) Prec@5 99.000 (99.784) +2022-11-14 16:24:34,698 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0707 (0.0707) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:24:34,708 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0693) Prec@1 90.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:24:34,718 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0759) Prec@1 85.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 16:24:34,730 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0768) Prec@1 89.000 (87.750) Prec@5 98.000 (99.250) +2022-11-14 16:24:34,738 Test: [4/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0758) Prec@1 89.000 (88.000) Prec@5 99.000 (99.200) +2022-11-14 16:24:34,748 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0383 (0.0696) Prec@1 93.000 (88.833) Prec@5 100.000 (99.333) +2022-11-14 16:24:34,756 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0694) Prec@1 89.000 (88.857) Prec@5 100.000 (99.429) +2022-11-14 16:24:34,766 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0707) Prec@1 88.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 16:24:34,775 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0704) Prec@1 88.000 (88.667) Prec@5 98.000 (99.333) +2022-11-14 16:24:34,786 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0701) Prec@1 87.000 (88.500) Prec@5 99.000 (99.300) +2022-11-14 16:24:34,796 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0685) Prec@1 91.000 (88.727) Prec@5 100.000 (99.364) +2022-11-14 16:24:34,809 Test: [11/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0990 (0.0710) Prec@1 85.000 (88.417) Prec@5 99.000 (99.333) +2022-11-14 16:24:34,822 Test: [12/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0700) Prec@1 90.000 (88.538) Prec@5 100.000 (99.385) +2022-11-14 16:24:34,833 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0700) Prec@1 90.000 (88.643) Prec@5 99.000 (99.357) +2022-11-14 16:24:34,843 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0695) Prec@1 90.000 (88.733) Prec@5 100.000 (99.400) +2022-11-14 16:24:34,854 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0704) Prec@1 87.000 (88.625) Prec@5 99.000 (99.375) +2022-11-14 16:24:34,863 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0686) Prec@1 93.000 (88.882) Prec@5 98.000 (99.294) +2022-11-14 16:24:34,873 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1129 (0.0711) Prec@1 83.000 (88.556) Prec@5 100.000 (99.333) +2022-11-14 16:24:34,883 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0719) Prec@1 86.000 (88.421) Prec@5 100.000 (99.368) +2022-11-14 16:24:34,894 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0729) Prec@1 87.000 (88.350) Prec@5 96.000 (99.200) +2022-11-14 16:24:34,904 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0732) Prec@1 87.000 (88.286) Prec@5 97.000 (99.095) +2022-11-14 16:24:34,915 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0739) Prec@1 85.000 (88.136) Prec@5 99.000 (99.091) +2022-11-14 16:24:34,925 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0745) Prec@1 87.000 (88.087) Prec@5 99.000 (99.087) +2022-11-14 16:24:34,937 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0739) Prec@1 91.000 (88.208) Prec@5 100.000 (99.125) +2022-11-14 16:24:34,948 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0740) Prec@1 89.000 (88.240) Prec@5 100.000 (99.160) +2022-11-14 16:24:34,958 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0748) Prec@1 85.000 (88.115) Prec@5 99.000 (99.154) +2022-11-14 16:24:34,969 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0741) Prec@1 91.000 (88.222) Prec@5 100.000 (99.185) +2022-11-14 16:24:34,980 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0420 (0.0729) Prec@1 94.000 (88.429) Prec@5 99.000 (99.179) +2022-11-14 16:24:34,991 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0725) Prec@1 90.000 (88.483) Prec@5 99.000 (99.172) +2022-11-14 16:24:35,001 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0725) Prec@1 89.000 (88.500) Prec@5 100.000 (99.200) +2022-11-14 16:24:35,011 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0723) Prec@1 89.000 (88.516) Prec@5 99.000 (99.194) +2022-11-14 16:24:35,021 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0719) Prec@1 91.000 (88.594) Prec@5 99.000 (99.188) +2022-11-14 16:24:35,032 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0714) Prec@1 91.000 (88.667) Prec@5 100.000 (99.212) +2022-11-14 16:24:35,043 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1019 (0.0723) Prec@1 84.000 (88.529) Prec@5 100.000 (99.235) +2022-11-14 16:24:35,054 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0724) Prec@1 90.000 (88.571) Prec@5 98.000 (99.200) +2022-11-14 16:24:35,064 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0722) Prec@1 90.000 (88.611) Prec@5 100.000 (99.222) +2022-11-14 16:24:35,075 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0727) Prec@1 85.000 (88.514) Prec@5 98.000 (99.189) +2022-11-14 16:24:35,086 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0733) Prec@1 87.000 (88.474) Prec@5 99.000 (99.184) +2022-11-14 16:24:35,098 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0726) Prec@1 94.000 (88.615) Prec@5 99.000 (99.179) +2022-11-14 16:24:35,110 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0727) Prec@1 89.000 (88.625) Prec@5 100.000 (99.200) +2022-11-14 16:24:35,121 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0729) Prec@1 90.000 (88.659) Prec@5 98.000 (99.171) +2022-11-14 16:24:35,133 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0731) Prec@1 89.000 (88.667) Prec@5 99.000 (99.167) +2022-11-14 16:24:35,144 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0725) Prec@1 94.000 (88.791) Prec@5 99.000 (99.163) +2022-11-14 16:24:35,155 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0729) Prec@1 85.000 (88.705) Prec@5 99.000 (99.159) +2022-11-14 16:24:35,166 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0631 (0.0726) Prec@1 91.000 (88.756) Prec@5 99.000 (99.156) +2022-11-14 16:24:35,177 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0733) Prec@1 84.000 (88.652) Prec@5 99.000 (99.152) +2022-11-14 16:24:35,188 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0728) Prec@1 92.000 (88.723) Prec@5 100.000 (99.170) +2022-11-14 16:24:35,199 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0731) Prec@1 85.000 (88.646) Prec@5 99.000 (99.167) +2022-11-14 16:24:35,211 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0729) Prec@1 91.000 (88.694) Prec@5 98.000 (99.143) +2022-11-14 16:24:35,223 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0734) Prec@1 86.000 (88.640) Prec@5 100.000 (99.160) +2022-11-14 16:24:35,234 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0731) Prec@1 89.000 (88.647) Prec@5 100.000 (99.176) +2022-11-14 16:24:35,245 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0733) Prec@1 83.000 (88.538) Prec@5 98.000 (99.154) +2022-11-14 16:24:35,256 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0732) Prec@1 88.000 (88.528) Prec@5 100.000 (99.170) +2022-11-14 16:24:35,267 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0735) Prec@1 84.000 (88.444) Prec@5 100.000 (99.185) +2022-11-14 16:24:35,278 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0738) Prec@1 85.000 (88.382) Prec@5 100.000 (99.200) +2022-11-14 16:24:35,289 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0740) Prec@1 87.000 (88.357) Prec@5 99.000 (99.196) +2022-11-14 16:24:35,300 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0740) Prec@1 90.000 (88.386) Prec@5 100.000 (99.211) +2022-11-14 16:24:35,310 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0741) Prec@1 87.000 (88.362) Prec@5 99.000 (99.207) +2022-11-14 16:24:35,321 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0741) Prec@1 88.000 (88.356) Prec@5 100.000 (99.220) +2022-11-14 16:24:35,332 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0741) Prec@1 90.000 (88.383) Prec@5 98.000 (99.200) +2022-11-14 16:24:35,342 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0742) Prec@1 88.000 (88.377) Prec@5 99.000 (99.197) +2022-11-14 16:24:35,352 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0743) Prec@1 86.000 (88.339) Prec@5 100.000 (99.210) +2022-11-14 16:24:35,363 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0741) Prec@1 92.000 (88.397) Prec@5 100.000 (99.222) +2022-11-14 16:24:35,376 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0358 (0.0735) Prec@1 96.000 (88.516) Prec@5 100.000 (99.234) +2022-11-14 16:24:35,388 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0737) Prec@1 87.000 (88.492) Prec@5 99.000 (99.231) +2022-11-14 16:24:35,398 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0738) Prec@1 88.000 (88.485) Prec@5 99.000 (99.227) +2022-11-14 16:24:35,410 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0319 (0.0732) Prec@1 94.000 (88.567) Prec@5 99.000 (99.224) +2022-11-14 16:24:35,422 Test: [67/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0732) Prec@1 86.000 (88.529) Prec@5 99.000 (99.221) +2022-11-14 16:24:35,435 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0731) Prec@1 90.000 (88.551) Prec@5 99.000 (99.217) +2022-11-14 16:24:35,448 Test: [69/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0732) Prec@1 87.000 (88.529) Prec@5 99.000 (99.214) +2022-11-14 16:24:35,461 Test: [70/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0737) Prec@1 83.000 (88.451) Prec@5 98.000 (99.197) +2022-11-14 16:24:35,474 Test: [71/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0735) Prec@1 91.000 (88.486) Prec@5 100.000 (99.208) +2022-11-14 16:24:35,486 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0350 (0.0729) Prec@1 93.000 (88.548) Prec@5 100.000 (99.219) +2022-11-14 16:24:35,498 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0726) Prec@1 93.000 (88.608) Prec@5 100.000 (99.230) +2022-11-14 16:24:35,509 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0730) Prec@1 84.000 (88.547) Prec@5 99.000 (99.227) +2022-11-14 16:24:35,523 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0730) Prec@1 89.000 (88.553) Prec@5 99.000 (99.224) +2022-11-14 16:24:35,536 Test: [76/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0732) Prec@1 87.000 (88.532) Prec@5 100.000 (99.234) +2022-11-14 16:24:35,549 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0734) Prec@1 86.000 (88.500) Prec@5 98.000 (99.218) +2022-11-14 16:24:35,562 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0732) Prec@1 89.000 (88.506) Prec@5 100.000 (99.228) +2022-11-14 16:24:35,575 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0728) Prec@1 93.000 (88.562) Prec@5 100.000 (99.237) +2022-11-14 16:24:35,588 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0730) Prec@1 87.000 (88.543) Prec@5 98.000 (99.222) +2022-11-14 16:24:35,602 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0733) Prec@1 88.000 (88.537) Prec@5 98.000 (99.207) +2022-11-14 16:24:35,618 Test: [82/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0734) Prec@1 87.000 (88.518) Prec@5 99.000 (99.205) +2022-11-14 16:24:35,635 Test: [83/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0732) Prec@1 93.000 (88.571) Prec@5 98.000 (99.190) +2022-11-14 16:24:35,655 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0734) Prec@1 84.000 (88.518) Prec@5 100.000 (99.200) +2022-11-14 16:24:35,670 Test: [85/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0738) Prec@1 86.000 (88.488) Prec@5 99.000 (99.198) +2022-11-14 16:24:35,688 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0735) Prec@1 91.000 (88.517) Prec@5 100.000 (99.207) +2022-11-14 16:24:35,706 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0735) Prec@1 89.000 (88.523) Prec@5 99.000 (99.205) +2022-11-14 16:24:35,727 Test: [88/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0737) Prec@1 84.000 (88.472) Prec@5 100.000 (99.213) +2022-11-14 16:24:35,746 Test: [89/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0737) Prec@1 87.000 (88.456) Prec@5 99.000 (99.211) +2022-11-14 16:24:35,766 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0737) Prec@1 89.000 (88.462) Prec@5 100.000 (99.220) +2022-11-14 16:24:35,782 Test: [91/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0485 (0.0734) Prec@1 92.000 (88.500) Prec@5 100.000 (99.228) +2022-11-14 16:24:35,803 Test: [92/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0735) Prec@1 87.000 (88.484) Prec@5 100.000 (99.237) +2022-11-14 16:24:35,826 Test: [93/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0734) Prec@1 92.000 (88.521) Prec@5 99.000 (99.234) +2022-11-14 16:24:35,846 Test: [94/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0734) Prec@1 90.000 (88.537) Prec@5 100.000 (99.242) +2022-11-14 16:24:35,866 Test: [95/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0732) Prec@1 92.000 (88.573) Prec@5 99.000 (99.240) +2022-11-14 16:24:35,887 Test: [96/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0463 (0.0729) Prec@1 92.000 (88.608) Prec@5 99.000 (99.237) +2022-11-14 16:24:35,906 Test: [97/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0730) Prec@1 88.000 (88.602) Prec@5 98.000 (99.224) +2022-11-14 16:24:35,925 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0733) Prec@1 83.000 (88.545) Prec@5 99.000 (99.222) +2022-11-14 16:24:35,946 Test: [99/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0734) Prec@1 88.000 (88.540) Prec@5 100.000 (99.230) +2022-11-14 16:24:36,021 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:24:36,399 Epoch: [340][0/500] Time 0.024 (0.024) Data 0.277 (0.277) Loss 0.0548 (0.0548) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:24:36,704 Epoch: [340][10/500] Time 0.032 (0.027) Data 0.002 (0.027) Loss 0.0199 (0.0374) Prec@1 98.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:24:37,020 Epoch: [340][20/500] Time 0.031 (0.027) Data 0.002 (0.015) Loss 0.0485 (0.0411) Prec@1 92.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 16:24:37,337 Epoch: [340][30/500] Time 0.029 (0.028) Data 0.002 (0.011) Loss 0.0107 (0.0335) Prec@1 98.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:24:37,733 Epoch: [340][40/500] Time 0.057 (0.029) Data 0.002 (0.009) Loss 0.0303 (0.0328) Prec@1 95.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 16:24:38,289 Epoch: [340][50/500] Time 0.054 (0.033) Data 0.002 (0.008) Loss 0.0408 (0.0342) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:24:38,833 Epoch: [340][60/500] Time 0.054 (0.036) Data 0.002 (0.007) Loss 0.0318 (0.0338) Prec@1 96.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 16:24:39,394 Epoch: [340][70/500] Time 0.054 (0.038) Data 0.003 (0.006) Loss 0.0355 (0.0340) Prec@1 96.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 16:24:39,929 Epoch: [340][80/500] Time 0.051 (0.039) Data 0.003 (0.006) Loss 0.0421 (0.0349) Prec@1 93.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:24:40,457 Epoch: [340][90/500] Time 0.044 (0.040) Data 0.003 (0.005) Loss 0.0213 (0.0336) Prec@1 97.000 (94.900) Prec@5 100.000 (100.000) +2022-11-14 16:24:41,003 Epoch: [340][100/500] Time 0.049 (0.041) Data 0.002 (0.005) Loss 0.0263 (0.0329) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:24:41,518 Epoch: [340][110/500] Time 0.047 (0.041) Data 0.002 (0.005) Loss 0.0207 (0.0319) Prec@1 97.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 16:24:42,042 Epoch: [340][120/500] Time 0.053 (0.042) Data 0.002 (0.004) Loss 0.0404 (0.0325) Prec@1 94.000 (95.077) Prec@5 100.000 (100.000) +2022-11-14 16:24:42,591 Epoch: [340][130/500] Time 0.049 (0.042) Data 0.002 (0.004) Loss 0.0349 (0.0327) Prec@1 94.000 (95.000) Prec@5 99.000 (99.929) +2022-11-14 16:24:43,134 Epoch: [340][140/500] Time 0.052 (0.043) Data 0.002 (0.004) Loss 0.0493 (0.0338) Prec@1 93.000 (94.867) Prec@5 100.000 (99.933) +2022-11-14 16:24:43,649 Epoch: [340][150/500] Time 0.046 (0.043) Data 0.002 (0.004) Loss 0.0151 (0.0326) Prec@1 98.000 (95.062) Prec@5 100.000 (99.938) +2022-11-14 16:24:44,193 Epoch: [340][160/500] Time 0.058 (0.043) Data 0.002 (0.004) Loss 0.0471 (0.0335) Prec@1 92.000 (94.882) Prec@5 100.000 (99.941) +2022-11-14 16:24:44,728 Epoch: [340][170/500] Time 0.057 (0.043) Data 0.002 (0.004) Loss 0.0361 (0.0336) Prec@1 93.000 (94.778) Prec@5 100.000 (99.944) +2022-11-14 16:24:45,251 Epoch: [340][180/500] Time 0.057 (0.044) Data 0.002 (0.004) Loss 0.0310 (0.0335) Prec@1 93.000 (94.684) Prec@5 100.000 (99.947) +2022-11-14 16:24:45,784 Epoch: [340][190/500] Time 0.053 (0.044) Data 0.002 (0.004) Loss 0.0232 (0.0330) Prec@1 96.000 (94.750) Prec@5 100.000 (99.950) +2022-11-14 16:24:46,305 Epoch: [340][200/500] Time 0.048 (0.044) Data 0.002 (0.004) Loss 0.0312 (0.0329) Prec@1 96.000 (94.810) Prec@5 100.000 (99.952) +2022-11-14 16:24:46,843 Epoch: [340][210/500] Time 0.050 (0.044) Data 0.002 (0.003) Loss 0.0278 (0.0327) Prec@1 96.000 (94.864) Prec@5 100.000 (99.955) +2022-11-14 16:24:47,362 Epoch: [340][220/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0354 (0.0328) Prec@1 94.000 (94.826) Prec@5 100.000 (99.957) +2022-11-14 16:24:47,894 Epoch: [340][230/500] Time 0.055 (0.044) Data 0.002 (0.003) Loss 0.0306 (0.0327) Prec@1 95.000 (94.833) Prec@5 100.000 (99.958) +2022-11-14 16:24:48,433 Epoch: [340][240/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0425 (0.0331) Prec@1 93.000 (94.760) Prec@5 100.000 (99.960) +2022-11-14 16:24:48,958 Epoch: [340][250/500] Time 0.059 (0.045) Data 0.002 (0.003) Loss 0.0435 (0.0335) Prec@1 92.000 (94.654) Prec@5 100.000 (99.962) +2022-11-14 16:24:49,479 Epoch: [340][260/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0408 (0.0338) Prec@1 94.000 (94.630) Prec@5 100.000 (99.963) +2022-11-14 16:24:50,006 Epoch: [340][270/500] Time 0.057 (0.045) Data 0.002 (0.003) Loss 0.0321 (0.0337) Prec@1 95.000 (94.643) Prec@5 100.000 (99.964) +2022-11-14 16:24:50,508 Epoch: [340][280/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0184 (0.0332) Prec@1 95.000 (94.655) Prec@5 100.000 (99.966) +2022-11-14 16:24:51,023 Epoch: [340][290/500] Time 0.045 (0.045) Data 0.002 (0.003) Loss 0.0280 (0.0330) Prec@1 95.000 (94.667) Prec@5 100.000 (99.967) +2022-11-14 16:24:51,545 Epoch: [340][300/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0203 (0.0326) Prec@1 97.000 (94.742) Prec@5 99.000 (99.935) +2022-11-14 16:24:52,072 Epoch: [340][310/500] Time 0.049 (0.045) Data 0.002 (0.003) Loss 0.0352 (0.0327) Prec@1 93.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:24:52,595 Epoch: [340][320/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0424 (0.0330) Prec@1 94.000 (94.667) Prec@5 100.000 (99.939) +2022-11-14 16:24:53,120 Epoch: [340][330/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0390 (0.0331) Prec@1 94.000 (94.647) Prec@5 100.000 (99.941) +2022-11-14 16:24:53,654 Epoch: [340][340/500] Time 0.055 (0.045) Data 0.003 (0.003) Loss 0.0359 (0.0332) Prec@1 94.000 (94.629) Prec@5 100.000 (99.943) +2022-11-14 16:24:54,157 Epoch: [340][350/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0340 (0.0332) Prec@1 93.000 (94.583) Prec@5 100.000 (99.944) +2022-11-14 16:24:54,669 Epoch: [340][360/500] Time 0.051 (0.045) Data 0.002 (0.003) Loss 0.0301 (0.0332) Prec@1 94.000 (94.568) Prec@5 99.000 (99.919) +2022-11-14 16:24:55,186 Epoch: [340][370/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0226 (0.0329) Prec@1 96.000 (94.605) Prec@5 100.000 (99.921) +2022-11-14 16:24:55,709 Epoch: [340][380/500] Time 0.059 (0.045) Data 0.002 (0.003) Loss 0.0299 (0.0328) Prec@1 97.000 (94.667) Prec@5 100.000 (99.923) +2022-11-14 16:24:56,211 Epoch: [340][390/500] Time 0.041 (0.045) Data 0.002 (0.003) Loss 0.0373 (0.0329) Prec@1 93.000 (94.625) Prec@5 100.000 (99.925) +2022-11-14 16:24:56,753 Epoch: [340][400/500] Time 0.055 (0.045) Data 0.002 (0.003) Loss 0.0345 (0.0330) Prec@1 93.000 (94.585) Prec@5 100.000 (99.927) +2022-11-14 16:24:57,268 Epoch: [340][410/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0368 (0.0331) Prec@1 91.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 16:24:57,804 Epoch: [340][420/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0357 (0.0331) Prec@1 95.000 (94.512) Prec@5 100.000 (99.930) +2022-11-14 16:24:58,314 Epoch: [340][430/500] Time 0.047 (0.045) Data 0.002 (0.003) Loss 0.0181 (0.0328) Prec@1 98.000 (94.591) Prec@5 100.000 (99.932) +2022-11-14 16:24:58,835 Epoch: [340][440/500] Time 0.056 (0.045) Data 0.002 (0.003) Loss 0.0480 (0.0331) Prec@1 93.000 (94.556) Prec@5 99.000 (99.911) +2022-11-14 16:24:59,373 Epoch: [340][450/500] Time 0.054 (0.045) Data 0.002 (0.003) Loss 0.0422 (0.0333) Prec@1 93.000 (94.522) Prec@5 99.000 (99.891) +2022-11-14 16:24:59,904 Epoch: [340][460/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0355 (0.0334) Prec@1 94.000 (94.511) Prec@5 100.000 (99.894) +2022-11-14 16:25:00,427 Epoch: [340][470/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0205 (0.0331) Prec@1 98.000 (94.583) Prec@5 100.000 (99.896) +2022-11-14 16:25:00,976 Epoch: [340][480/500] Time 0.061 (0.046) Data 0.002 (0.003) Loss 0.0609 (0.0337) Prec@1 90.000 (94.490) Prec@5 100.000 (99.898) +2022-11-14 16:25:01,501 Epoch: [340][490/500] Time 0.048 (0.046) Data 0.002 (0.003) Loss 0.0195 (0.0334) Prec@1 98.000 (94.560) Prec@5 100.000 (99.900) +2022-11-14 16:25:01,997 Epoch: [340][499/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0198 (0.0331) Prec@1 98.000 (94.627) Prec@5 100.000 (99.902) +2022-11-14 16:25:02,338 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0776 (0.0776) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,348 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0732) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,360 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0731) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,373 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0738) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,384 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0726) Prec@1 90.000 (88.800) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,396 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0447 (0.0680) Prec@1 93.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,408 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0673) Prec@1 90.000 (89.571) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,422 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0712) Prec@1 83.000 (88.750) Prec@5 100.000 (100.000) +2022-11-14 16:25:02,435 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0720) Prec@1 89.000 (88.778) Prec@5 99.000 (99.889) +2022-11-14 16:25:02,450 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0714) Prec@1 90.000 (88.900) Prec@5 99.000 (99.800) +2022-11-14 16:25:02,467 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0700) Prec@1 91.000 (89.091) Prec@5 100.000 (99.818) +2022-11-14 16:25:02,484 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0703) Prec@1 90.000 (89.167) Prec@5 99.000 (99.750) +2022-11-14 16:25:02,502 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0698) Prec@1 89.000 (89.154) Prec@5 100.000 (99.769) +2022-11-14 16:25:02,518 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0705) Prec@1 88.000 (89.071) Prec@5 99.000 (99.714) +2022-11-14 16:25:02,536 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0712) Prec@1 86.000 (88.867) Prec@5 100.000 (99.733) +2022-11-14 16:25:02,554 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0718) Prec@1 85.000 (88.625) Prec@5 99.000 (99.688) +2022-11-14 16:25:02,571 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0703) Prec@1 93.000 (88.882) Prec@5 98.000 (99.588) +2022-11-14 16:25:02,589 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0722) Prec@1 85.000 (88.667) Prec@5 100.000 (99.611) +2022-11-14 16:25:02,605 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0724) Prec@1 90.000 (88.737) Prec@5 100.000 (99.632) +2022-11-14 16:25:02,621 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0732) Prec@1 85.000 (88.550) Prec@5 98.000 (99.550) +2022-11-14 16:25:02,638 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0734) Prec@1 86.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 16:25:02,654 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0741) Prec@1 85.000 (88.273) Prec@5 98.000 (99.500) +2022-11-14 16:25:02,671 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0756) Prec@1 82.000 (88.000) Prec@5 98.000 (99.435) +2022-11-14 16:25:02,690 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0757) Prec@1 87.000 (87.958) Prec@5 100.000 (99.458) +2022-11-14 16:25:02,711 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0765) Prec@1 84.000 (87.800) Prec@5 99.000 (99.440) +2022-11-14 16:25:02,728 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0777) Prec@1 86.000 (87.731) Prec@5 99.000 (99.423) +2022-11-14 16:25:02,743 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0767) Prec@1 90.000 (87.815) Prec@5 100.000 (99.444) +2022-11-14 16:25:02,763 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0765) Prec@1 88.000 (87.821) Prec@5 100.000 (99.464) +2022-11-14 16:25:02,778 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0763) Prec@1 91.000 (87.931) Prec@5 100.000 (99.483) +2022-11-14 16:25:02,796 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0754) Prec@1 93.000 (88.100) Prec@5 100.000 (99.500) +2022-11-14 16:25:02,813 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0748) Prec@1 91.000 (88.194) Prec@5 100.000 (99.516) +2022-11-14 16:25:02,830 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0750) Prec@1 88.000 (88.188) Prec@5 100.000 (99.531) +2022-11-14 16:25:02,844 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0748) Prec@1 89.000 (88.212) Prec@5 100.000 (99.545) +2022-11-14 16:25:02,863 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0750) Prec@1 85.000 (88.118) Prec@5 100.000 (99.559) +2022-11-14 16:25:02,881 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0751) Prec@1 87.000 (88.086) Prec@5 97.000 (99.486) +2022-11-14 16:25:02,899 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0750) Prec@1 90.000 (88.139) Prec@5 100.000 (99.500) +2022-11-14 16:25:02,918 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0752) Prec@1 87.000 (88.108) Prec@5 99.000 (99.486) +2022-11-14 16:25:02,935 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1054 (0.0760) Prec@1 83.000 (87.974) Prec@5 99.000 (99.474) +2022-11-14 16:25:02,954 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0755) Prec@1 92.000 (88.077) Prec@5 99.000 (99.462) +2022-11-14 16:25:02,974 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0749) Prec@1 91.000 (88.150) Prec@5 98.000 (99.425) +2022-11-14 16:25:02,989 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0751) Prec@1 87.000 (88.122) Prec@5 99.000 (99.415) +2022-11-14 16:25:03,005 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0749) Prec@1 91.000 (88.190) Prec@5 99.000 (99.405) +2022-11-14 16:25:03,020 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0747) Prec@1 89.000 (88.209) Prec@5 100.000 (99.419) +2022-11-14 16:25:03,039 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0746) Prec@1 89.000 (88.227) Prec@5 98.000 (99.386) +2022-11-14 16:25:03,056 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0740) Prec@1 92.000 (88.311) Prec@5 99.000 (99.378) +2022-11-14 16:25:03,075 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0747) Prec@1 84.000 (88.217) Prec@5 99.000 (99.370) +2022-11-14 16:25:03,092 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0744) Prec@1 91.000 (88.277) Prec@5 100.000 (99.383) +2022-11-14 16:25:03,110 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1025 (0.0749) Prec@1 86.000 (88.229) Prec@5 97.000 (99.333) +2022-11-14 16:25:03,124 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0397 (0.0742) Prec@1 92.000 (88.306) Prec@5 100.000 (99.347) +2022-11-14 16:25:03,142 Test: 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Loss 0.0825 (0.0741) Prec@1 86.000 (88.304) Prec@5 99.000 (99.357) +2022-11-14 16:25:03,272 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0741) Prec@1 87.000 (88.281) Prec@5 99.000 (99.351) +2022-11-14 16:25:03,289 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0739) Prec@1 91.000 (88.328) Prec@5 99.000 (99.345) +2022-11-14 16:25:03,308 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0741) Prec@1 86.000 (88.288) Prec@5 100.000 (99.356) +2022-11-14 16:25:03,327 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0741) Prec@1 88.000 (88.283) Prec@5 100.000 (99.367) +2022-11-14 16:25:03,345 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0740) Prec@1 89.000 (88.295) Prec@5 100.000 (99.377) +2022-11-14 16:25:03,364 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0741) Prec@1 87.000 (88.274) Prec@5 99.000 (99.371) +2022-11-14 16:25:03,380 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0740) Prec@1 89.000 (88.286) Prec@5 100.000 (99.381) +2022-11-14 16:25:03,399 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0736) Prec@1 93.000 (88.359) Prec@5 100.000 (99.391) +2022-11-14 16:25:03,417 Test: [64/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0738) Prec@1 87.000 (88.338) Prec@5 100.000 (99.400) +2022-11-14 16:25:03,433 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0735) Prec@1 90.000 (88.364) Prec@5 100.000 (99.409) +2022-11-14 16:25:03,453 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0730) Prec@1 93.000 (88.433) Prec@5 99.000 (99.403) +2022-11-14 16:25:03,474 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0730) Prec@1 89.000 (88.441) Prec@5 99.000 (99.397) +2022-11-14 16:25:03,493 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0730) Prec@1 86.000 (88.406) Prec@5 99.000 (99.391) +2022-11-14 16:25:03,510 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0736) Prec@1 80.000 (88.286) Prec@5 100.000 (99.400) +2022-11-14 16:25:03,528 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0739) Prec@1 85.000 (88.239) Prec@5 99.000 (99.394) +2022-11-14 16:25:03,544 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0740) Prec@1 87.000 (88.222) Prec@5 100.000 (99.403) +2022-11-14 16:25:03,562 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0736) Prec@1 93.000 (88.288) Prec@5 99.000 (99.397) +2022-11-14 16:25:03,578 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0461 (0.0733) Prec@1 93.000 (88.351) Prec@5 100.000 (99.405) +2022-11-14 16:25:03,595 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0734) Prec@1 86.000 (88.320) Prec@5 99.000 (99.400) +2022-11-14 16:25:03,613 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0733) Prec@1 88.000 (88.316) Prec@5 100.000 (99.408) +2022-11-14 16:25:03,633 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0734) Prec@1 88.000 (88.312) Prec@5 99.000 (99.403) +2022-11-14 16:25:03,653 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0733) Prec@1 89.000 (88.321) Prec@5 100.000 (99.410) +2022-11-14 16:25:03,672 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0736) Prec@1 85.000 (88.278) Prec@5 100.000 (99.418) +2022-11-14 16:25:03,687 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0736) Prec@1 87.000 (88.263) Prec@5 99.000 (99.412) +2022-11-14 16:25:03,707 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0739) Prec@1 87.000 (88.247) Prec@5 98.000 (99.395) +2022-11-14 16:25:03,726 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0739) Prec@1 88.000 (88.244) Prec@5 98.000 (99.378) +2022-11-14 16:25:03,745 Test: [82/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0739) Prec@1 89.000 (88.253) Prec@5 98.000 (99.361) +2022-11-14 16:25:03,761 Test: [83/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0738) Prec@1 89.000 (88.262) Prec@5 100.000 (99.369) +2022-11-14 16:25:03,778 Test: [84/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0739) Prec@1 85.000 (88.224) Prec@5 99.000 (99.365) +2022-11-14 16:25:03,796 Test: [85/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0741) Prec@1 85.000 (88.186) Prec@5 100.000 (99.372) +2022-11-14 16:25:03,816 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0739) Prec@1 91.000 (88.218) Prec@5 99.000 (99.368) +2022-11-14 16:25:03,833 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0740) Prec@1 88.000 (88.216) Prec@5 99.000 (99.364) +2022-11-14 16:25:03,847 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0739) Prec@1 89.000 (88.225) Prec@5 100.000 (99.371) +2022-11-14 16:25:03,864 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0741) Prec@1 86.000 (88.200) Prec@5 100.000 (99.378) +2022-11-14 16:25:03,884 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0739) Prec@1 92.000 (88.242) Prec@5 100.000 (99.385) +2022-11-14 16:25:03,903 Test: [91/100] Model Time 0.014 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0738) Prec@1 89.000 (88.250) Prec@5 99.000 (99.380) +2022-11-14 16:25:03,921 Test: [92/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0740) Prec@1 85.000 (88.215) Prec@5 99.000 (99.376) +2022-11-14 16:25:03,937 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0739) Prec@1 89.000 (88.223) Prec@5 99.000 (99.372) +2022-11-14 16:25:03,955 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0740) Prec@1 87.000 (88.211) Prec@5 99.000 (99.368) +2022-11-14 16:25:03,974 Test: [95/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0641 (0.0738) Prec@1 91.000 (88.240) Prec@5 99.000 (99.365) +2022-11-14 16:25:03,991 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0739) Prec@1 87.000 (88.227) Prec@5 98.000 (99.351) +2022-11-14 16:25:04,009 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0740) Prec@1 86.000 (88.204) Prec@5 99.000 (99.347) +2022-11-14 16:25:04,027 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1084 (0.0743) Prec@1 83.000 (88.152) Prec@5 99.000 (99.343) +2022-11-14 16:25:04,044 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0743) Prec@1 90.000 (88.170) Prec@5 100.000 (99.350) +2022-11-14 16:25:04,123 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:25:04,496 Epoch: [341][0/500] Time 0.029 (0.029) Data 0.270 (0.270) Loss 0.0361 (0.0361) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:25:04,951 Epoch: [341][10/500] Time 0.052 (0.039) Data 0.002 (0.027) Loss 0.0341 (0.0351) Prec@1 95.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:25:05,463 Epoch: [341][20/500] Time 0.039 (0.042) Data 0.002 (0.015) Loss 0.0377 (0.0360) Prec@1 93.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:25:05,978 Epoch: [341][30/500] Time 0.052 (0.043) Data 0.003 (0.011) Loss 0.0370 (0.0362) Prec@1 94.000 (94.250) Prec@5 99.000 (99.500) +2022-11-14 16:25:06,491 Epoch: [341][40/500] Time 0.051 (0.044) Data 0.002 (0.009) Loss 0.0156 (0.0321) Prec@1 97.000 (94.800) Prec@5 100.000 (99.600) +2022-11-14 16:25:07,081 Epoch: [341][50/500] Time 0.060 (0.046) Data 0.002 (0.008) Loss 0.0186 (0.0299) Prec@1 98.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:25:07,637 Epoch: [341][60/500] Time 0.051 (0.046) Data 0.002 (0.007) Loss 0.0180 (0.0282) Prec@1 96.000 (95.429) Prec@5 100.000 (99.714) +2022-11-14 16:25:08,247 Epoch: [341][70/500] Time 0.060 (0.047) Data 0.003 (0.006) Loss 0.0349 (0.0290) Prec@1 92.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:25:08,769 Epoch: [341][80/500] Time 0.055 (0.047) Data 0.003 (0.006) Loss 0.0286 (0.0290) Prec@1 95.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 16:25:09,296 Epoch: [341][90/500] Time 0.050 (0.047) Data 0.003 (0.005) Loss 0.0276 (0.0288) Prec@1 97.000 (95.200) Prec@5 99.000 (99.700) +2022-11-14 16:25:09,839 Epoch: [341][100/500] Time 0.047 (0.047) Data 0.002 (0.005) Loss 0.0273 (0.0287) Prec@1 96.000 (95.273) Prec@5 100.000 (99.727) +2022-11-14 16:25:10,369 Epoch: [341][110/500] Time 0.047 (0.047) Data 0.002 (0.005) Loss 0.0511 (0.0306) Prec@1 92.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:25:10,906 Epoch: [341][120/500] Time 0.058 (0.047) Data 0.002 (0.005) Loss 0.0268 (0.0303) Prec@1 96.000 (95.077) Prec@5 100.000 (99.769) +2022-11-14 16:25:11,409 Epoch: [341][130/500] Time 0.048 (0.047) Data 0.002 (0.004) Loss 0.0497 (0.0317) Prec@1 90.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 16:25:11,939 Epoch: [341][140/500] Time 0.056 (0.047) Data 0.002 (0.004) Loss 0.0285 (0.0314) Prec@1 96.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:25:12,494 Epoch: [341][150/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0365 (0.0318) Prec@1 94.000 (94.750) Prec@5 100.000 (99.812) +2022-11-14 16:25:13,009 Epoch: [341][160/500] Time 0.052 (0.047) Data 0.002 (0.004) Loss 0.0550 (0.0331) Prec@1 90.000 (94.471) Prec@5 100.000 (99.824) +2022-11-14 16:25:13,533 Epoch: [341][170/500] Time 0.043 (0.047) Data 0.002 (0.004) Loss 0.0176 (0.0323) Prec@1 98.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:25:14,065 Epoch: [341][180/500] Time 0.050 (0.047) Data 0.002 (0.004) Loss 0.0419 (0.0328) Prec@1 92.000 (94.526) Prec@5 100.000 (99.842) +2022-11-14 16:25:14,600 Epoch: [341][190/500] Time 0.054 (0.047) Data 0.002 (0.004) Loss 0.0325 (0.0327) Prec@1 93.000 (94.450) Prec@5 100.000 (99.850) +2022-11-14 16:25:15,131 Epoch: [341][200/500] Time 0.049 (0.047) Data 0.002 (0.004) Loss 0.0349 (0.0329) Prec@1 93.000 (94.381) Prec@5 98.000 (99.762) +2022-11-14 16:25:15,664 Epoch: [341][210/500] Time 0.052 (0.047) Data 0.002 (0.004) Loss 0.0443 (0.0334) Prec@1 93.000 (94.318) Prec@5 100.000 (99.773) +2022-11-14 16:25:16,179 Epoch: [341][220/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0393 (0.0336) Prec@1 94.000 (94.304) Prec@5 100.000 (99.783) +2022-11-14 16:25:16,700 Epoch: [341][230/500] Time 0.045 (0.047) Data 0.003 (0.003) Loss 0.0392 (0.0339) Prec@1 92.000 (94.208) Prec@5 100.000 (99.792) +2022-11-14 16:25:17,234 Epoch: [341][240/500] Time 0.047 (0.047) Data 0.002 (0.003) Loss 0.0406 (0.0341) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 16:25:17,761 Epoch: [341][250/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0246 (0.0338) Prec@1 96.000 (94.269) Prec@5 99.000 (99.769) +2022-11-14 16:25:18,289 Epoch: [341][260/500] Time 0.051 (0.047) Data 0.003 (0.003) Loss 0.0406 (0.0340) Prec@1 92.000 (94.185) Prec@5 100.000 (99.778) +2022-11-14 16:25:18,811 Epoch: [341][270/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0386 (0.0342) Prec@1 93.000 (94.143) Prec@5 100.000 (99.786) +2022-11-14 16:25:19,322 Epoch: [341][280/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0306 (0.0341) Prec@1 95.000 (94.172) Prec@5 100.000 (99.793) +2022-11-14 16:25:19,846 Epoch: [341][290/500] Time 0.049 (0.047) Data 0.002 (0.003) Loss 0.0352 (0.0341) Prec@1 94.000 (94.167) Prec@5 99.000 (99.767) +2022-11-14 16:25:20,373 Epoch: [341][300/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0289 (0.0339) Prec@1 95.000 (94.194) Prec@5 100.000 (99.774) +2022-11-14 16:25:20,954 Epoch: [341][310/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0502 (0.0344) Prec@1 92.000 (94.125) Prec@5 99.000 (99.750) +2022-11-14 16:25:21,552 Epoch: [341][320/500] Time 0.062 (0.048) Data 0.002 (0.003) Loss 0.0373 (0.0345) Prec@1 95.000 (94.152) Prec@5 99.000 (99.727) +2022-11-14 16:25:22,094 Epoch: [341][330/500] Time 0.057 (0.048) Data 0.002 (0.003) Loss 0.0279 (0.0343) Prec@1 95.000 (94.176) Prec@5 100.000 (99.735) +2022-11-14 16:25:22,632 Epoch: [341][340/500] Time 0.039 (0.048) Data 0.002 (0.003) Loss 0.0402 (0.0345) Prec@1 92.000 (94.114) Prec@5 100.000 (99.743) +2022-11-14 16:25:23,166 Epoch: [341][350/500] Time 0.043 (0.048) Data 0.002 (0.003) Loss 0.0176 (0.0340) Prec@1 96.000 (94.167) Prec@5 100.000 (99.750) +2022-11-14 16:25:23,708 Epoch: [341][360/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0612 (0.0348) Prec@1 90.000 (94.054) Prec@5 100.000 (99.757) +2022-11-14 16:25:24,234 Epoch: [341][370/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0226 (0.0344) Prec@1 96.000 (94.105) Prec@5 100.000 (99.763) +2022-11-14 16:25:24,746 Epoch: [341][380/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0149 (0.0339) Prec@1 97.000 (94.179) Prec@5 100.000 (99.769) +2022-11-14 16:25:25,282 Epoch: [341][390/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0205 (0.0336) Prec@1 97.000 (94.250) Prec@5 100.000 (99.775) +2022-11-14 16:25:25,893 Epoch: [341][400/500] Time 0.051 (0.048) Data 0.003 (0.003) Loss 0.0171 (0.0332) Prec@1 97.000 (94.317) Prec@5 100.000 (99.780) +2022-11-14 16:25:26,429 Epoch: [341][410/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0251 (0.0330) Prec@1 97.000 (94.381) Prec@5 100.000 (99.786) +2022-11-14 16:25:26,993 Epoch: [341][420/500] Time 0.079 (0.048) Data 0.002 (0.003) Loss 0.0057 (0.0324) Prec@1 99.000 (94.488) Prec@5 100.000 (99.791) +2022-11-14 16:25:27,516 Epoch: [341][430/500] Time 0.060 (0.048) Data 0.002 (0.003) Loss 0.0321 (0.0324) Prec@1 94.000 (94.477) Prec@5 100.000 (99.795) +2022-11-14 16:25:28,064 Epoch: [341][440/500] Time 0.065 (0.048) Data 0.002 (0.003) Loss 0.0231 (0.0322) Prec@1 95.000 (94.489) Prec@5 100.000 (99.800) +2022-11-14 16:25:28,603 Epoch: [341][450/500] Time 0.048 (0.048) Data 0.003 (0.003) Loss 0.0365 (0.0323) Prec@1 92.000 (94.435) Prec@5 100.000 (99.804) +2022-11-14 16:25:29,162 Epoch: [341][460/500] Time 0.049 (0.048) Data 0.002 (0.003) Loss 0.0208 (0.0320) Prec@1 96.000 (94.468) Prec@5 100.000 (99.809) +2022-11-14 16:25:29,677 Epoch: [341][470/500] Time 0.054 (0.048) Data 0.002 (0.003) Loss 0.0295 (0.0320) Prec@1 96.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 16:25:30,206 Epoch: [341][480/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0316 (0.0320) Prec@1 94.000 (94.490) Prec@5 100.000 (99.816) +2022-11-14 16:25:30,741 Epoch: [341][490/500] Time 0.052 (0.048) Data 0.002 (0.003) Loss 0.0435 (0.0322) Prec@1 94.000 (94.480) Prec@5 100.000 (99.820) +2022-11-14 16:25:31,200 Epoch: [341][499/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0371 (0.0323) Prec@1 95.000 (94.490) Prec@5 100.000 (99.824) +2022-11-14 16:25:31,521 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0496 (0.0496) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:31,533 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0628) Prec@1 89.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:25:31,543 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0682) Prec@1 86.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:31,555 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0676) Prec@1 89.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 16:25:31,563 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0731) Prec@1 82.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 16:25:31,573 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0703) Prec@1 91.000 (88.167) Prec@5 99.000 (99.333) +2022-11-14 16:25:31,584 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0688) Prec@1 91.000 (88.571) Prec@5 100.000 (99.429) +2022-11-14 16:25:31,596 Test: [7/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0700) Prec@1 86.000 (88.250) Prec@5 99.000 (99.375) +2022-11-14 16:25:31,607 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0695 (0.0700) Prec@1 91.000 (88.556) Prec@5 100.000 (99.444) +2022-11-14 16:25:31,618 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0725) Prec@1 85.000 (88.200) Prec@5 99.000 (99.400) +2022-11-14 16:25:31,630 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0704) Prec@1 91.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 16:25:31,641 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0727) Prec@1 84.000 (88.083) Prec@5 100.000 (99.500) +2022-11-14 16:25:31,652 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0704) Prec@1 94.000 (88.538) Prec@5 99.000 (99.462) +2022-11-14 16:25:31,662 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0701) Prec@1 90.000 (88.643) Prec@5 100.000 (99.500) +2022-11-14 16:25:31,671 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0705) Prec@1 87.000 (88.533) Prec@5 100.000 (99.533) +2022-11-14 16:25:31,681 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0700) Prec@1 89.000 (88.562) Prec@5 99.000 (99.500) +2022-11-14 16:25:31,693 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0691) Prec@1 91.000 (88.706) Prec@5 99.000 (99.471) +2022-11-14 16:25:31,705 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1053 (0.0712) Prec@1 85.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:25:31,717 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0721) Prec@1 85.000 (88.316) Prec@5 98.000 (99.421) +2022-11-14 16:25:31,728 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0730) Prec@1 85.000 (88.150) Prec@5 98.000 (99.350) +2022-11-14 16:25:31,739 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0736) Prec@1 84.000 (87.952) Prec@5 100.000 (99.381) +2022-11-14 16:25:31,751 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0738) Prec@1 89.000 (88.000) Prec@5 99.000 (99.364) +2022-11-14 16:25:31,762 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0740) Prec@1 88.000 (88.000) Prec@5 97.000 (99.261) +2022-11-14 16:25:31,772 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0730) Prec@1 92.000 (88.167) Prec@5 100.000 (99.292) +2022-11-14 16:25:31,783 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0737) Prec@1 84.000 (88.000) Prec@5 99.000 (99.280) +2022-11-14 16:25:31,793 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0752) Prec@1 81.000 (87.731) Prec@5 97.000 (99.192) +2022-11-14 16:25:31,803 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0748) Prec@1 86.000 (87.667) Prec@5 100.000 (99.222) +2022-11-14 16:25:31,813 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0743) Prec@1 91.000 (87.786) Prec@5 99.000 (99.214) +2022-11-14 16:25:31,823 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0737) Prec@1 90.000 (87.862) Prec@5 99.000 (99.207) +2022-11-14 16:25:31,834 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0727) Prec@1 93.000 (88.033) Prec@5 100.000 (99.233) +2022-11-14 16:25:31,845 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0727) Prec@1 88.000 (88.032) Prec@5 100.000 (99.258) +2022-11-14 16:25:31,855 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0722) Prec@1 92.000 (88.156) Prec@5 99.000 (99.250) +2022-11-14 16:25:31,866 Test: [32/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0719) Prec@1 89.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 16:25:31,876 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0728) Prec@1 82.000 (88.000) Prec@5 100.000 (99.294) +2022-11-14 16:25:31,888 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0732) Prec@1 85.000 (87.914) Prec@5 98.000 (99.257) +2022-11-14 16:25:31,898 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0727) Prec@1 92.000 (88.028) Prec@5 99.000 (99.250) +2022-11-14 16:25:31,909 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0730) Prec@1 88.000 (88.027) Prec@5 99.000 (99.243) +2022-11-14 16:25:31,920 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0737) Prec@1 84.000 (87.921) Prec@5 97.000 (99.184) +2022-11-14 16:25:31,931 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0735) Prec@1 89.000 (87.949) Prec@5 100.000 (99.205) +2022-11-14 16:25:31,942 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0730) Prec@1 90.000 (88.000) Prec@5 100.000 (99.225) +2022-11-14 16:25:31,953 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0737) Prec@1 83.000 (87.878) Prec@5 98.000 (99.195) +2022-11-14 16:25:31,966 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0734) Prec@1 88.000 (87.881) Prec@5 99.000 (99.190) +2022-11-14 16:25:31,980 Test: [42/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0730) Prec@1 92.000 (87.977) Prec@5 100.000 (99.209) +2022-11-14 16:25:31,993 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0729) Prec@1 88.000 (87.977) Prec@5 99.000 (99.205) +2022-11-14 16:25:32,005 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0724) Prec@1 90.000 (88.022) Prec@5 100.000 (99.222) +2022-11-14 16:25:32,021 Test: [45/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0727) Prec@1 85.000 (87.957) Prec@5 100.000 (99.239) +2022-11-14 16:25:32,035 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0727) Prec@1 87.000 (87.936) Prec@5 100.000 (99.255) +2022-11-14 16:25:32,047 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1022 (0.0733) Prec@1 82.000 (87.812) Prec@5 97.000 (99.208) +2022-11-14 16:25:32,057 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0492 (0.0728) Prec@1 92.000 (87.898) Prec@5 100.000 (99.224) +2022-11-14 16:25:32,071 Test: [49/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0733) Prec@1 85.000 (87.840) Prec@5 100.000 (99.240) +2022-11-14 16:25:32,083 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0734) Prec@1 87.000 (87.824) Prec@5 100.000 (99.255) +2022-11-14 16:25:32,094 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0734) Prec@1 89.000 (87.846) Prec@5 99.000 (99.250) +2022-11-14 16:25:32,107 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0734) Prec@1 87.000 (87.830) Prec@5 100.000 (99.264) +2022-11-14 16:25:32,122 Test: [53/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0735) Prec@1 86.000 (87.796) Prec@5 99.000 (99.259) +2022-11-14 16:25:32,134 Test: [54/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0740) Prec@1 82.000 (87.691) Prec@5 100.000 (99.273) +2022-11-14 16:25:32,146 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0743) Prec@1 86.000 (87.661) Prec@5 99.000 (99.268) +2022-11-14 16:25:32,158 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0743) Prec@1 90.000 (87.702) Prec@5 100.000 (99.281) +2022-11-14 16:25:32,174 Test: [57/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0740) Prec@1 92.000 (87.776) Prec@5 97.000 (99.241) +2022-11-14 16:25:32,187 Test: [58/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0744) Prec@1 84.000 (87.712) Prec@5 99.000 (99.237) +2022-11-14 16:25:32,197 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0743) Prec@1 89.000 (87.733) Prec@5 99.000 (99.233) +2022-11-14 16:25:32,208 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0742) Prec@1 89.000 (87.754) Prec@5 98.000 (99.213) +2022-11-14 16:25:32,222 Test: [61/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0741) Prec@1 90.000 (87.790) Prec@5 99.000 (99.210) +2022-11-14 16:25:32,235 Test: [62/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0740) Prec@1 90.000 (87.825) Prec@5 100.000 (99.222) +2022-11-14 16:25:32,249 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0378 (0.0734) Prec@1 96.000 (87.953) Prec@5 100.000 (99.234) +2022-11-14 16:25:32,261 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0943 (0.0737) Prec@1 85.000 (87.908) Prec@5 100.000 (99.246) +2022-11-14 16:25:32,276 Test: [65/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0735) Prec@1 91.000 (87.955) Prec@5 99.000 (99.242) +2022-11-14 16:25:32,289 Test: [66/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0465 (0.0731) Prec@1 94.000 (88.045) Prec@5 99.000 (99.239) +2022-11-14 16:25:32,301 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0728) Prec@1 93.000 (88.118) Prec@5 97.000 (99.206) +2022-11-14 16:25:32,314 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0730) Prec@1 85.000 (88.072) Prec@5 99.000 (99.203) +2022-11-14 16:25:32,327 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0730) Prec@1 89.000 (88.086) Prec@5 100.000 (99.214) +2022-11-14 16:25:32,341 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1007 (0.0733) Prec@1 84.000 (88.028) Prec@5 97.000 (99.183) +2022-11-14 16:25:32,357 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0732) Prec@1 89.000 (88.042) Prec@5 100.000 (99.194) +2022-11-14 16:25:32,373 Test: [72/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0731) Prec@1 90.000 (88.068) Prec@5 99.000 (99.192) +2022-11-14 16:25:32,387 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0292 (0.0725) Prec@1 96.000 (88.176) Prec@5 100.000 (99.203) +2022-11-14 16:25:32,401 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0729) Prec@1 85.000 (88.133) Prec@5 99.000 (99.200) +2022-11-14 16:25:32,415 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0730) Prec@1 86.000 (88.105) Prec@5 98.000 (99.184) +2022-11-14 16:25:32,430 Test: [76/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0730) Prec@1 86.000 (88.078) Prec@5 99.000 (99.182) +2022-11-14 16:25:32,447 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0733) Prec@1 85.000 (88.038) Prec@5 97.000 (99.154) +2022-11-14 16:25:32,464 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0735) Prec@1 86.000 (88.013) Prec@5 99.000 (99.152) +2022-11-14 16:25:32,479 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0736) Prec@1 84.000 (87.963) Prec@5 100.000 (99.162) +2022-11-14 16:25:32,495 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0740) Prec@1 85.000 (87.926) Prec@5 96.000 (99.123) +2022-11-14 16:25:32,511 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1136 (0.0744) Prec@1 81.000 (87.841) Prec@5 100.000 (99.134) +2022-11-14 16:25:32,527 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0745) Prec@1 85.000 (87.807) Prec@5 100.000 (99.145) +2022-11-14 16:25:32,543 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0742) Prec@1 92.000 (87.857) Prec@5 99.000 (99.143) +2022-11-14 16:25:32,557 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0744) Prec@1 83.000 (87.800) Prec@5 100.000 (99.153) +2022-11-14 16:25:32,572 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0746) Prec@1 84.000 (87.756) Prec@5 99.000 (99.151) +2022-11-14 16:25:32,589 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0746) Prec@1 87.000 (87.747) Prec@5 99.000 (99.149) +2022-11-14 16:25:32,603 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0746) Prec@1 88.000 (87.750) Prec@5 98.000 (99.136) +2022-11-14 16:25:32,617 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0746) Prec@1 89.000 (87.764) Prec@5 99.000 (99.135) +2022-11-14 16:25:32,631 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0746) Prec@1 88.000 (87.767) Prec@5 99.000 (99.133) +2022-11-14 16:25:32,650 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0745) Prec@1 89.000 (87.780) Prec@5 100.000 (99.143) +2022-11-14 16:25:32,669 Test: [91/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0511 (0.0742) Prec@1 91.000 (87.815) Prec@5 100.000 (99.152) +2022-11-14 16:25:32,685 Test: [92/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0743) Prec@1 88.000 (87.817) Prec@5 100.000 (99.161) +2022-11-14 16:25:32,703 Test: [93/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0742) Prec@1 88.000 (87.819) Prec@5 99.000 (99.160) +2022-11-14 16:25:32,721 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0743) Prec@1 87.000 (87.811) Prec@5 100.000 (99.168) +2022-11-14 16:25:32,737 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0493 (0.0740) Prec@1 93.000 (87.865) Prec@5 99.000 (99.167) +2022-11-14 16:25:32,753 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0424 (0.0737) Prec@1 95.000 (87.938) Prec@5 98.000 (99.155) +2022-11-14 16:25:32,768 Test: [97/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0739) Prec@1 84.000 (87.898) Prec@5 97.000 (99.133) +2022-11-14 16:25:32,784 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0741) Prec@1 85.000 (87.869) Prec@5 100.000 (99.141) +2022-11-14 16:25:32,798 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0739) Prec@1 91.000 (87.900) Prec@5 100.000 (99.150) +2022-11-14 16:25:32,884 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:25:33,350 Epoch: [342][0/500] Time 0.032 (0.032) Data 0.347 (0.347) Loss 0.0239 (0.0239) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:33,841 Epoch: [342][10/500] Time 0.054 (0.042) Data 0.002 (0.034) Loss 0.0317 (0.0278) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:25:34,365 Epoch: [342][20/500] Time 0.050 (0.044) Data 0.003 (0.019) Loss 0.0532 (0.0363) Prec@1 91.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:25:34,889 Epoch: [342][30/500] Time 0.047 (0.045) Data 0.003 (0.014) Loss 0.0310 (0.0350) Prec@1 95.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:25:35,489 Epoch: [342][40/500] Time 0.056 (0.047) Data 0.004 (0.011) Loss 0.0513 (0.0382) Prec@1 91.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:36,017 Epoch: [342][50/500] Time 0.043 (0.047) Data 0.003 (0.010) Loss 0.0287 (0.0366) Prec@1 96.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:25:36,525 Epoch: [342][60/500] Time 0.049 (0.047) Data 0.003 (0.009) Loss 0.0311 (0.0358) Prec@1 95.000 (94.429) Prec@5 100.000 (100.000) +2022-11-14 16:25:36,995 Epoch: [342][70/500] Time 0.049 (0.046) Data 0.003 (0.008) Loss 0.0225 (0.0342) Prec@1 96.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 16:25:37,473 Epoch: [342][80/500] Time 0.042 (0.046) Data 0.003 (0.007) Loss 0.0230 (0.0329) Prec@1 96.000 (94.778) Prec@5 100.000 (100.000) +2022-11-14 16:25:37,934 Epoch: [342][90/500] Time 0.037 (0.045) Data 0.003 (0.007) Loss 0.0256 (0.0322) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:25:38,395 Epoch: [342][100/500] Time 0.043 (0.045) Data 0.002 (0.006) Loss 0.0215 (0.0312) Prec@1 97.000 (95.182) Prec@5 100.000 (100.000) +2022-11-14 16:25:38,873 Epoch: [342][110/500] Time 0.050 (0.045) Data 0.002 (0.006) Loss 0.0380 (0.0318) Prec@1 94.000 (95.083) Prec@5 100.000 (100.000) +2022-11-14 16:25:39,338 Epoch: [342][120/500] Time 0.039 (0.045) Data 0.002 (0.006) Loss 0.0426 (0.0326) Prec@1 92.000 (94.846) Prec@5 100.000 (100.000) +2022-11-14 16:25:39,899 Epoch: [342][130/500] Time 0.061 (0.045) Data 0.002 (0.005) Loss 0.0333 (0.0327) Prec@1 95.000 (94.857) Prec@5 99.000 (99.929) +2022-11-14 16:25:40,350 Epoch: [342][140/500] Time 0.033 (0.045) Data 0.002 (0.005) Loss 0.0191 (0.0318) Prec@1 97.000 (95.000) Prec@5 100.000 (99.933) +2022-11-14 16:25:40,811 Epoch: [342][150/500] Time 0.053 (0.044) Data 0.002 (0.005) Loss 0.0559 (0.0333) Prec@1 90.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:25:41,286 Epoch: [342][160/500] Time 0.052 (0.044) Data 0.002 (0.005) Loss 0.0109 (0.0320) Prec@1 99.000 (94.941) Prec@5 100.000 (99.941) +2022-11-14 16:25:41,778 Epoch: [342][170/500] Time 0.050 (0.044) Data 0.002 (0.005) Loss 0.0242 (0.0315) Prec@1 96.000 (95.000) Prec@5 100.000 (99.944) +2022-11-14 16:25:42,239 Epoch: [342][180/500] Time 0.044 (0.044) Data 0.002 (0.004) Loss 0.0378 (0.0319) Prec@1 95.000 (95.000) Prec@5 100.000 (99.947) +2022-11-14 16:25:42,706 Epoch: [342][190/500] Time 0.045 (0.044) Data 0.002 (0.004) Loss 0.0261 (0.0316) Prec@1 97.000 (95.100) Prec@5 100.000 (99.950) +2022-11-14 16:25:43,162 Epoch: [342][200/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0479 (0.0323) Prec@1 93.000 (95.000) Prec@5 100.000 (99.952) +2022-11-14 16:25:43,662 Epoch: [342][210/500] Time 0.049 (0.044) Data 0.002 (0.004) Loss 0.0362 (0.0325) Prec@1 96.000 (95.045) Prec@5 99.000 (99.909) +2022-11-14 16:25:44,180 Epoch: [342][220/500] Time 0.053 (0.044) Data 0.003 (0.004) Loss 0.0380 (0.0328) Prec@1 95.000 (95.043) Prec@5 100.000 (99.913) +2022-11-14 16:25:44,676 Epoch: [342][230/500] Time 0.044 (0.044) Data 0.002 (0.004) Loss 0.0384 (0.0330) Prec@1 94.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 16:25:45,150 Epoch: [342][240/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0216 (0.0325) Prec@1 97.000 (95.080) Prec@5 100.000 (99.920) +2022-11-14 16:25:45,642 Epoch: [342][250/500] Time 0.053 (0.044) Data 0.002 (0.004) Loss 0.0322 (0.0325) Prec@1 93.000 (95.000) Prec@5 100.000 (99.923) +2022-11-14 16:25:46,120 Epoch: [342][260/500] Time 0.053 (0.044) Data 0.002 (0.004) Loss 0.0262 (0.0323) Prec@1 95.000 (95.000) Prec@5 100.000 (99.926) +2022-11-14 16:25:46,623 Epoch: [342][270/500] Time 0.042 (0.044) Data 0.002 (0.004) Loss 0.0156 (0.0317) Prec@1 98.000 (95.107) Prec@5 100.000 (99.929) +2022-11-14 16:25:47,089 Epoch: [342][280/500] Time 0.041 (0.044) Data 0.003 (0.004) Loss 0.0280 (0.0316) Prec@1 96.000 (95.138) Prec@5 100.000 (99.931) +2022-11-14 16:25:47,565 Epoch: [342][290/500] Time 0.043 (0.044) Data 0.002 (0.004) Loss 0.0049 (0.0307) Prec@1 99.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 16:25:48,045 Epoch: [342][300/500] Time 0.060 (0.044) Data 0.002 (0.004) Loss 0.0361 (0.0308) Prec@1 95.000 (95.258) Prec@5 99.000 (99.903) +2022-11-14 16:25:48,512 Epoch: [342][310/500] Time 0.038 (0.044) Data 0.002 (0.003) Loss 0.0381 (0.0311) Prec@1 94.000 (95.219) Prec@5 100.000 (99.906) +2022-11-14 16:25:48,954 Epoch: [342][320/500] Time 0.046 (0.043) Data 0.002 (0.003) Loss 0.0227 (0.0308) Prec@1 95.000 (95.212) Prec@5 100.000 (99.909) +2022-11-14 16:25:49,518 Epoch: [342][330/500] Time 0.068 (0.044) Data 0.002 (0.003) Loss 0.0245 (0.0306) Prec@1 98.000 (95.294) Prec@5 100.000 (99.912) +2022-11-14 16:25:50,241 Epoch: [342][340/500] Time 0.079 (0.044) Data 0.002 (0.003) Loss 0.0218 (0.0304) Prec@1 96.000 (95.314) Prec@5 100.000 (99.914) +2022-11-14 16:25:50,950 Epoch: [342][350/500] Time 0.074 (0.045) Data 0.002 (0.003) Loss 0.0269 (0.0303) Prec@1 95.000 (95.306) Prec@5 100.000 (99.917) +2022-11-14 16:25:51,685 Epoch: [342][360/500] Time 0.064 (0.045) Data 0.002 (0.003) Loss 0.0138 (0.0298) Prec@1 98.000 (95.378) Prec@5 100.000 (99.919) +2022-11-14 16:25:52,468 Epoch: [342][370/500] Time 0.083 (0.046) Data 0.002 (0.003) Loss 0.0195 (0.0296) Prec@1 98.000 (95.447) Prec@5 100.000 (99.921) +2022-11-14 16:25:53,232 Epoch: [342][380/500] Time 0.070 (0.047) Data 0.002 (0.003) Loss 0.0209 (0.0293) Prec@1 97.000 (95.487) Prec@5 100.000 (99.923) +2022-11-14 16:25:53,956 Epoch: [342][390/500] Time 0.067 (0.047) Data 0.002 (0.003) Loss 0.0403 (0.0296) Prec@1 94.000 (95.450) Prec@5 100.000 (99.925) +2022-11-14 16:25:54,675 Epoch: [342][400/500] Time 0.074 (0.047) Data 0.003 (0.003) Loss 0.0571 (0.0303) Prec@1 90.000 (95.317) Prec@5 100.000 (99.927) +2022-11-14 16:25:55,422 Epoch: [342][410/500] Time 0.082 (0.048) Data 0.002 (0.003) Loss 0.0307 (0.0303) Prec@1 95.000 (95.310) Prec@5 100.000 (99.929) +2022-11-14 16:25:56,195 Epoch: [342][420/500] Time 0.069 (0.048) Data 0.002 (0.003) Loss 0.0173 (0.0300) Prec@1 97.000 (95.349) Prec@5 100.000 (99.930) +2022-11-14 16:25:57,003 Epoch: [342][430/500] Time 0.077 (0.049) Data 0.002 (0.003) Loss 0.0263 (0.0299) Prec@1 96.000 (95.364) Prec@5 100.000 (99.932) +2022-11-14 16:25:57,743 Epoch: [342][440/500] Time 0.065 (0.049) Data 0.003 (0.003) Loss 0.0256 (0.0298) Prec@1 96.000 (95.378) Prec@5 100.000 (99.933) +2022-11-14 16:25:58,483 Epoch: [342][450/500] Time 0.078 (0.050) Data 0.002 (0.003) Loss 0.0201 (0.0296) Prec@1 95.000 (95.370) Prec@5 100.000 (99.935) +2022-11-14 16:25:59,240 Epoch: [342][460/500] Time 0.082 (0.050) Data 0.003 (0.003) Loss 0.0349 (0.0297) Prec@1 94.000 (95.340) Prec@5 99.000 (99.915) +2022-11-14 16:25:59,917 Epoch: [342][470/500] Time 0.069 (0.050) Data 0.002 (0.003) Loss 0.0156 (0.0294) Prec@1 98.000 (95.396) Prec@5 100.000 (99.917) +2022-11-14 16:26:00,714 Epoch: [342][480/500] Time 0.071 (0.051) Data 0.002 (0.003) Loss 0.0274 (0.0294) Prec@1 94.000 (95.367) Prec@5 100.000 (99.918) +2022-11-14 16:26:01,440 Epoch: [342][490/500] Time 0.069 (0.051) Data 0.002 (0.003) Loss 0.0197 (0.0292) Prec@1 97.000 (95.400) Prec@5 100.000 (99.920) +2022-11-14 16:26:02,071 Epoch: [342][499/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0144 (0.0289) Prec@1 99.000 (95.471) Prec@5 100.000 (99.922) +2022-11-14 16:26:02,403 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0555 (0.0555) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:02,413 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0634 (0.0594) Prec@1 89.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:02,423 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0655) Prec@1 88.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 16:26:02,436 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0693) Prec@1 85.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 16:26:02,445 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0721) Prec@1 86.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 16:26:02,455 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0335 (0.0656) Prec@1 94.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:26:02,467 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0656) Prec@1 89.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:26:02,480 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0666) Prec@1 87.000 (88.875) Prec@5 100.000 (99.750) +2022-11-14 16:26:02,489 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0694) Prec@1 87.000 (88.667) Prec@5 97.000 (99.444) +2022-11-14 16:26:02,499 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0709) Prec@1 86.000 (88.400) Prec@5 98.000 (99.300) +2022-11-14 16:26:02,510 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0693) Prec@1 89.000 (88.455) Prec@5 100.000 (99.364) +2022-11-14 16:26:02,524 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0692) Prec@1 91.000 (88.667) Prec@5 100.000 (99.417) +2022-11-14 16:26:02,537 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0686) Prec@1 91.000 (88.846) Prec@5 99.000 (99.385) +2022-11-14 16:26:02,548 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0679) Prec@1 90.000 (88.929) Prec@5 100.000 (99.429) +2022-11-14 16:26:02,559 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0681) Prec@1 90.000 (89.000) Prec@5 100.000 (99.467) +2022-11-14 16:26:02,572 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0690) Prec@1 87.000 (88.875) Prec@5 100.000 (99.500) +2022-11-14 16:26:02,584 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0678) Prec@1 93.000 (89.118) Prec@5 97.000 (99.353) +2022-11-14 16:26:02,596 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0687) Prec@1 86.000 (88.944) Prec@5 100.000 (99.389) +2022-11-14 16:26:02,609 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0708) Prec@1 83.000 (88.632) Prec@5 100.000 (99.421) +2022-11-14 16:26:02,620 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0719) Prec@1 87.000 (88.550) Prec@5 99.000 (99.400) +2022-11-14 16:26:02,631 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0721) Prec@1 85.000 (88.381) Prec@5 99.000 (99.381) +2022-11-14 16:26:02,641 Test: [21/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0730) Prec@1 82.000 (88.091) Prec@5 99.000 (99.364) +2022-11-14 16:26:02,651 Test: [22/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0738) Prec@1 84.000 (87.913) Prec@5 98.000 (99.304) +2022-11-14 16:26:02,663 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0737) Prec@1 89.000 (87.958) Prec@5 100.000 (99.333) +2022-11-14 16:26:02,675 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0746) Prec@1 84.000 (87.800) Prec@5 100.000 (99.360) +2022-11-14 16:26:02,688 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0751) Prec@1 85.000 (87.692) Prec@5 98.000 (99.308) +2022-11-14 16:26:02,700 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0288 (0.0734) Prec@1 96.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 16:26:02,714 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0734) Prec@1 88.000 (88.000) Prec@5 100.000 (99.357) +2022-11-14 16:26:02,728 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0735) Prec@1 88.000 (88.000) Prec@5 99.000 (99.345) +2022-11-14 16:26:02,740 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0738) Prec@1 86.000 (87.933) Prec@5 100.000 (99.367) +2022-11-14 16:26:02,754 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0733) Prec@1 90.000 (88.000) Prec@5 100.000 (99.387) +2022-11-14 16:26:02,767 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0733) Prec@1 87.000 (87.969) Prec@5 99.000 (99.375) +2022-11-14 16:26:02,780 Test: [32/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0734) Prec@1 86.000 (87.909) Prec@5 100.000 (99.394) +2022-11-14 16:26:02,794 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0738) Prec@1 86.000 (87.853) Prec@5 99.000 (99.382) +2022-11-14 16:26:02,807 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1260 (0.0753) Prec@1 80.000 (87.629) Prec@5 97.000 (99.314) +2022-11-14 16:26:02,820 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0749) Prec@1 91.000 (87.722) Prec@5 100.000 (99.333) +2022-11-14 16:26:02,834 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0747) Prec@1 90.000 (87.784) Prec@5 98.000 (99.297) +2022-11-14 16:26:02,846 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0752) Prec@1 83.000 (87.658) Prec@5 100.000 (99.316) +2022-11-14 16:26:02,858 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0744) Prec@1 95.000 (87.846) Prec@5 99.000 (99.308) +2022-11-14 16:26:02,869 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0740) Prec@1 90.000 (87.900) Prec@5 100.000 (99.325) +2022-11-14 16:26:02,883 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0748) Prec@1 84.000 (87.805) Prec@5 97.000 (99.268) +2022-11-14 16:26:02,895 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0746) Prec@1 89.000 (87.833) Prec@5 99.000 (99.262) +2022-11-14 16:26:02,909 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0741) Prec@1 93.000 (87.953) Prec@5 99.000 (99.256) +2022-11-14 16:26:02,922 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 88.000 (87.955) Prec@5 99.000 (99.250) +2022-11-14 16:26:02,933 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0477 (0.0735) Prec@1 93.000 (88.067) Prec@5 99.000 (99.244) +2022-11-14 16:26:02,946 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0743) Prec@1 80.000 (87.891) Prec@5 100.000 (99.261) +2022-11-14 16:26:02,959 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0742) Prec@1 87.000 (87.872) Prec@5 100.000 (99.277) +2022-11-14 16:26:02,972 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0746) Prec@1 82.000 (87.750) Prec@5 99.000 (99.271) +2022-11-14 16:26:02,983 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0743) Prec@1 89.000 (87.776) Prec@5 100.000 (99.286) +2022-11-14 16:26:02,996 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0748) Prec@1 83.000 (87.680) Prec@5 100.000 (99.300) +2022-11-14 16:26:03,009 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0747) Prec@1 88.000 (87.686) Prec@5 99.000 (99.294) +2022-11-14 16:26:03,022 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0749) Prec@1 85.000 (87.635) Prec@5 99.000 (99.288) +2022-11-14 16:26:03,034 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0749) Prec@1 87.000 (87.623) Prec@5 100.000 (99.302) +2022-11-14 16:26:03,044 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0744) Prec@1 91.000 (87.685) Prec@5 100.000 (99.315) +2022-11-14 16:26:03,055 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0747) Prec@1 85.000 (87.636) Prec@5 100.000 (99.327) +2022-11-14 16:26:03,066 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0746) Prec@1 88.000 (87.643) Prec@5 99.000 (99.321) +2022-11-14 16:26:03,078 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0743) Prec@1 91.000 (87.702) Prec@5 99.000 (99.316) +2022-11-14 16:26:03,091 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0739) Prec@1 92.000 (87.776) Prec@5 100.000 (99.328) +2022-11-14 16:26:03,104 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0745) Prec@1 84.000 (87.712) Prec@5 99.000 (99.322) +2022-11-14 16:26:03,117 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0749) Prec@1 83.000 (87.633) Prec@5 99.000 (99.317) +2022-11-14 16:26:03,130 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0749) Prec@1 89.000 (87.656) Prec@5 100.000 (99.328) +2022-11-14 16:26:03,142 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0749) Prec@1 86.000 (87.629) Prec@5 98.000 (99.306) +2022-11-14 16:26:03,152 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0748) Prec@1 89.000 (87.651) Prec@5 100.000 (99.317) +2022-11-14 16:26:03,166 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0746) Prec@1 89.000 (87.672) Prec@5 100.000 (99.328) +2022-11-14 16:26:03,180 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0749) Prec@1 83.000 (87.600) Prec@5 100.000 (99.338) +2022-11-14 16:26:03,190 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0751) Prec@1 84.000 (87.545) Prec@5 100.000 (99.348) +2022-11-14 16:26:03,205 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0447 (0.0746) Prec@1 93.000 (87.627) Prec@5 100.000 (99.358) +2022-11-14 16:26:03,219 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0746) Prec@1 89.000 (87.647) Prec@5 100.000 (99.368) +2022-11-14 16:26:03,232 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0749) Prec@1 86.000 (87.623) Prec@5 99.000 (99.362) +2022-11-14 16:26:03,246 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0750) Prec@1 87.000 (87.614) Prec@5 99.000 (99.357) +2022-11-14 16:26:03,260 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0754) Prec@1 85.000 (87.577) Prec@5 99.000 (99.352) +2022-11-14 16:26:03,274 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0751) Prec@1 93.000 (87.653) Prec@5 100.000 (99.361) +2022-11-14 16:26:03,288 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0418 (0.0746) Prec@1 93.000 (87.726) Prec@5 100.000 (99.370) +2022-11-14 16:26:03,298 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0293 (0.0740) Prec@1 94.000 (87.811) Prec@5 100.000 (99.378) +2022-11-14 16:26:03,309 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0743) Prec@1 85.000 (87.773) Prec@5 99.000 (99.373) +2022-11-14 16:26:03,324 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0740) Prec@1 92.000 (87.829) Prec@5 99.000 (99.368) +2022-11-14 16:26:03,337 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0741) Prec@1 86.000 (87.805) Prec@5 99.000 (99.364) +2022-11-14 16:26:03,348 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0745) Prec@1 82.000 (87.731) Prec@5 97.000 (99.333) +2022-11-14 16:26:03,362 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0746) Prec@1 87.000 (87.722) Prec@5 100.000 (99.342) +2022-11-14 16:26:03,377 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0746) Prec@1 87.000 (87.713) Prec@5 99.000 (99.338) +2022-11-14 16:26:03,391 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0747) Prec@1 86.000 (87.691) Prec@5 97.000 (99.309) +2022-11-14 16:26:03,405 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1084 (0.0751) Prec@1 81.000 (87.610) Prec@5 100.000 (99.317) +2022-11-14 16:26:03,418 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0753) Prec@1 84.000 (87.566) Prec@5 100.000 (99.325) +2022-11-14 16:26:03,430 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0754) Prec@1 89.000 (87.583) Prec@5 99.000 (99.321) +2022-11-14 16:26:03,441 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0996 (0.0757) Prec@1 82.000 (87.518) Prec@5 99.000 (99.318) +2022-11-14 16:26:03,453 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0758) Prec@1 87.000 (87.512) Prec@5 99.000 (99.314) +2022-11-14 16:26:03,466 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0759) Prec@1 85.000 (87.483) Prec@5 100.000 (99.322) +2022-11-14 16:26:03,480 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0758) Prec@1 89.000 (87.500) Prec@5 99.000 (99.318) +2022-11-14 16:26:03,490 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0759) Prec@1 87.000 (87.494) Prec@5 98.000 (99.303) +2022-11-14 16:26:03,502 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0759) Prec@1 89.000 (87.511) Prec@5 100.000 (99.311) +2022-11-14 16:26:03,517 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0415 (0.0755) Prec@1 93.000 (87.571) Prec@5 100.000 (99.319) +2022-11-14 16:26:03,531 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0754) Prec@1 89.000 (87.587) Prec@5 99.000 (99.315) +2022-11-14 16:26:03,545 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0756) Prec@1 87.000 (87.581) Prec@5 99.000 (99.312) +2022-11-14 16:26:03,555 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0756) Prec@1 89.000 (87.596) Prec@5 100.000 (99.319) +2022-11-14 16:26:03,566 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0758) Prec@1 84.000 (87.558) Prec@5 99.000 (99.316) +2022-11-14 16:26:03,575 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0757) Prec@1 88.000 (87.562) Prec@5 99.000 (99.312) +2022-11-14 16:26:03,588 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0754) Prec@1 92.000 (87.608) Prec@5 99.000 (99.309) +2022-11-14 16:26:03,599 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0757) Prec@1 85.000 (87.582) Prec@5 97.000 (99.286) +2022-11-14 16:26:03,614 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0757) Prec@1 88.000 (87.586) Prec@5 98.000 (99.273) +2022-11-14 16:26:03,628 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0757) Prec@1 89.000 (87.600) Prec@5 100.000 (99.280) +2022-11-14 16:26:03,709 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:26:04,081 Epoch: [343][0/500] Time 0.025 (0.025) Data 0.277 (0.277) Loss 0.0185 (0.0185) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:04,332 Epoch: [343][10/500] Time 0.019 (0.023) Data 0.002 (0.027) Loss 0.0402 (0.0294) Prec@1 93.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:26:04,630 Epoch: [343][20/500] Time 0.037 (0.024) Data 0.002 (0.015) Loss 0.0190 (0.0259) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:26:04,974 Epoch: [343][30/500] Time 0.035 (0.026) Data 0.002 (0.011) Loss 0.0289 (0.0266) Prec@1 94.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:26:05,366 Epoch: [343][40/500] Time 0.057 (0.028) Data 0.002 (0.009) Loss 0.0430 (0.0299) Prec@1 94.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 16:26:05,940 Epoch: [343][50/500] Time 0.054 (0.033) Data 0.002 (0.007) Loss 0.0451 (0.0324) Prec@1 91.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:26:06,507 Epoch: [343][60/500] Time 0.049 (0.036) Data 0.002 (0.006) Loss 0.0280 (0.0318) Prec@1 95.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 16:26:07,146 Epoch: [343][70/500] Time 0.075 (0.039) Data 0.002 (0.006) Loss 0.0296 (0.0315) Prec@1 95.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:26:07,716 Epoch: [343][80/500] Time 0.060 (0.040) Data 0.002 (0.005) Loss 0.0431 (0.0328) Prec@1 90.000 (94.000) Prec@5 100.000 (99.889) +2022-11-14 16:26:08,346 Epoch: [343][90/500] Time 0.051 (0.042) Data 0.002 (0.005) Loss 0.0509 (0.0346) Prec@1 91.000 (93.700) Prec@5 99.000 (99.800) +2022-11-14 16:26:08,979 Epoch: [343][100/500] Time 0.074 (0.044) Data 0.002 (0.005) Loss 0.0556 (0.0365) Prec@1 89.000 (93.273) Prec@5 100.000 (99.818) +2022-11-14 16:26:09,529 Epoch: [343][110/500] Time 0.060 (0.044) Data 0.003 (0.004) Loss 0.0327 (0.0362) Prec@1 93.000 (93.250) Prec@5 100.000 (99.833) +2022-11-14 16:26:10,114 Epoch: [343][120/500] Time 0.055 (0.045) Data 0.002 (0.004) Loss 0.0444 (0.0368) Prec@1 91.000 (93.077) Prec@5 100.000 (99.846) +2022-11-14 16:26:10,800 Epoch: [343][130/500] Time 0.071 (0.046) Data 0.002 (0.004) Loss 0.0235 (0.0359) Prec@1 98.000 (93.429) Prec@5 100.000 (99.857) +2022-11-14 16:26:11,379 Epoch: [343][140/500] Time 0.047 (0.046) Data 0.002 (0.004) Loss 0.0248 (0.0352) Prec@1 97.000 (93.667) Prec@5 100.000 (99.867) +2022-11-14 16:26:11,987 Epoch: [343][150/500] Time 0.069 (0.047) Data 0.002 (0.004) Loss 0.0330 (0.0350) Prec@1 94.000 (93.688) Prec@5 100.000 (99.875) +2022-11-14 16:26:12,558 Epoch: [343][160/500] Time 0.056 (0.047) Data 0.002 (0.004) Loss 0.0117 (0.0337) Prec@1 99.000 (94.000) Prec@5 100.000 (99.882) +2022-11-14 16:26:13,133 Epoch: [343][170/500] Time 0.055 (0.047) Data 0.002 (0.004) Loss 0.0341 (0.0337) Prec@1 95.000 (94.056) Prec@5 100.000 (99.889) +2022-11-14 16:26:13,728 Epoch: [343][180/500] Time 0.058 (0.048) Data 0.002 (0.004) Loss 0.0318 (0.0336) Prec@1 96.000 (94.158) Prec@5 100.000 (99.895) +2022-11-14 16:26:14,289 Epoch: [343][190/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0430 (0.0340) Prec@1 92.000 (94.050) Prec@5 100.000 (99.900) +2022-11-14 16:26:14,930 Epoch: [343][200/500] Time 0.061 (0.048) Data 0.002 (0.003) Loss 0.0190 (0.0333) Prec@1 97.000 (94.190) Prec@5 99.000 (99.857) +2022-11-14 16:26:15,501 Epoch: [343][210/500] Time 0.056 (0.048) Data 0.002 (0.003) Loss 0.0281 (0.0331) Prec@1 95.000 (94.227) Prec@5 100.000 (99.864) +2022-11-14 16:26:16,065 Epoch: [343][220/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0149 (0.0323) Prec@1 98.000 (94.391) Prec@5 100.000 (99.870) +2022-11-14 16:26:16,650 Epoch: [343][230/500] Time 0.054 (0.049) Data 0.003 (0.003) Loss 0.0331 (0.0323) Prec@1 96.000 (94.458) Prec@5 100.000 (99.875) +2022-11-14 16:26:17,286 Epoch: [343][240/500] Time 0.062 (0.049) Data 0.002 (0.003) Loss 0.0282 (0.0322) Prec@1 94.000 (94.440) Prec@5 100.000 (99.880) +2022-11-14 16:26:17,866 Epoch: [343][250/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0306 (0.0321) Prec@1 94.000 (94.423) Prec@5 100.000 (99.885) +2022-11-14 16:26:18,439 Epoch: [343][260/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0246 (0.0318) Prec@1 96.000 (94.481) Prec@5 100.000 (99.889) +2022-11-14 16:26:19,008 Epoch: [343][270/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0305 (0.0318) Prec@1 97.000 (94.571) Prec@5 100.000 (99.893) +2022-11-14 16:26:19,556 Epoch: [343][280/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0126 (0.0311) Prec@1 98.000 (94.690) Prec@5 100.000 (99.897) +2022-11-14 16:26:20,122 Epoch: [343][290/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0281 (0.0310) Prec@1 95.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 16:26:20,701 Epoch: [343][300/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0288 (0.0310) Prec@1 95.000 (94.710) Prec@5 100.000 (99.903) +2022-11-14 16:26:21,281 Epoch: [343][310/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0386 (0.0312) Prec@1 95.000 (94.719) Prec@5 100.000 (99.906) +2022-11-14 16:26:21,950 Epoch: [343][320/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0379 (0.0314) Prec@1 91.000 (94.606) Prec@5 100.000 (99.909) +2022-11-14 16:26:22,512 Epoch: [343][330/500] Time 0.067 (0.050) Data 0.002 (0.003) Loss 0.0381 (0.0316) Prec@1 92.000 (94.529) Prec@5 100.000 (99.912) +2022-11-14 16:26:23,093 Epoch: [343][340/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0285 (0.0315) Prec@1 97.000 (94.600) Prec@5 100.000 (99.914) +2022-11-14 16:26:23,640 Epoch: [343][350/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0534 (0.0321) Prec@1 90.000 (94.472) Prec@5 100.000 (99.917) +2022-11-14 16:26:24,211 Epoch: [343][360/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0237 (0.0319) Prec@1 95.000 (94.486) Prec@5 100.000 (99.919) +2022-11-14 16:26:24,801 Epoch: [343][370/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0247 (0.0317) Prec@1 95.000 (94.500) Prec@5 100.000 (99.921) +2022-11-14 16:26:25,359 Epoch: [343][380/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0283 (0.0316) Prec@1 96.000 (94.538) Prec@5 100.000 (99.923) +2022-11-14 16:26:25,936 Epoch: [343][390/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0412 (0.0318) Prec@1 92.000 (94.475) Prec@5 100.000 (99.925) +2022-11-14 16:26:26,496 Epoch: [343][400/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0212 (0.0316) Prec@1 97.000 (94.537) Prec@5 100.000 (99.927) +2022-11-14 16:26:27,069 Epoch: [343][410/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0309 (0.0316) Prec@1 95.000 (94.548) Prec@5 100.000 (99.929) +2022-11-14 16:26:27,620 Epoch: [343][420/500] Time 0.046 (0.050) Data 0.002 (0.003) Loss 0.0400 (0.0318) Prec@1 95.000 (94.558) Prec@5 100.000 (99.930) +2022-11-14 16:26:28,177 Epoch: [343][430/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0530 (0.0323) Prec@1 92.000 (94.500) Prec@5 100.000 (99.932) +2022-11-14 16:26:28,749 Epoch: [343][440/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0178 (0.0319) Prec@1 97.000 (94.556) Prec@5 100.000 (99.933) +2022-11-14 16:26:29,325 Epoch: [343][450/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0168 (0.0316) Prec@1 97.000 (94.609) Prec@5 100.000 (99.935) +2022-11-14 16:26:29,889 Epoch: [343][460/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0143 (0.0312) Prec@1 98.000 (94.681) Prec@5 100.000 (99.936) +2022-11-14 16:26:30,455 Epoch: [343][470/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0168 (0.0309) Prec@1 98.000 (94.750) Prec@5 100.000 (99.938) +2022-11-14 16:26:31,015 Epoch: [343][480/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0698 (0.0317) Prec@1 89.000 (94.633) Prec@5 100.000 (99.939) +2022-11-14 16:26:31,579 Epoch: [343][490/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0250 (0.0316) Prec@1 95.000 (94.640) Prec@5 100.000 (99.940) +2022-11-14 16:26:32,105 Epoch: [343][499/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0210 (0.0314) Prec@1 97.000 (94.686) Prec@5 100.000 (99.941) +2022-11-14 16:26:32,433 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0615 (0.0615) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:32,441 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0665) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:32,450 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0628) Prec@1 92.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:32,463 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0629) Prec@1 92.000 (90.500) Prec@5 98.000 (99.500) +2022-11-14 16:26:32,475 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0645) Prec@1 89.000 (90.200) Prec@5 100.000 (99.600) +2022-11-14 16:26:32,489 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0382 (0.0602) Prec@1 94.000 (90.833) Prec@5 100.000 (99.667) +2022-11-14 16:26:32,503 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0613) Prec@1 90.000 (90.714) Prec@5 100.000 (99.714) +2022-11-14 16:26:32,520 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0624) Prec@1 88.000 (90.375) Prec@5 100.000 (99.750) +2022-11-14 16:26:32,537 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0644) Prec@1 87.000 (90.000) Prec@5 98.000 (99.556) +2022-11-14 16:26:32,551 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0651) Prec@1 86.000 (89.600) Prec@5 99.000 (99.500) +2022-11-14 16:26:32,567 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0653) Prec@1 88.000 (89.455) Prec@5 100.000 (99.545) +2022-11-14 16:26:32,583 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0667) Prec@1 88.000 (89.333) Prec@5 100.000 (99.583) +2022-11-14 16:26:32,602 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0670) Prec@1 89.000 (89.308) Prec@5 100.000 (99.615) +2022-11-14 16:26:32,622 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0673) Prec@1 88.000 (89.214) Prec@5 100.000 (99.643) +2022-11-14 16:26:32,638 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0679) Prec@1 87.000 (89.067) Prec@5 100.000 (99.667) +2022-11-14 16:26:32,654 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0687) Prec@1 85.000 (88.812) Prec@5 100.000 (99.688) +2022-11-14 16:26:32,674 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0681) Prec@1 90.000 (88.882) Prec@5 98.000 (99.588) +2022-11-14 16:26:32,696 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0698) Prec@1 84.000 (88.611) Prec@5 100.000 (99.611) +2022-11-14 16:26:32,715 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0702) Prec@1 88.000 (88.579) Prec@5 99.000 (99.579) +2022-11-14 16:26:32,735 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0704) Prec@1 89.000 (88.600) Prec@5 98.000 (99.500) +2022-11-14 16:26:32,754 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0710) Prec@1 88.000 (88.571) Prec@5 100.000 (99.524) +2022-11-14 16:26:32,772 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0715) Prec@1 88.000 (88.545) Prec@5 99.000 (99.500) +2022-11-14 16:26:32,788 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0726) Prec@1 85.000 (88.391) Prec@5 99.000 (99.478) +2022-11-14 16:26:32,808 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0731) Prec@1 88.000 (88.375) Prec@5 99.000 (99.458) +2022-11-14 16:26:32,831 Test: [24/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.0741) Prec@1 85.000 (88.240) Prec@5 99.000 (99.440) +2022-11-14 16:26:32,847 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0741) Prec@1 89.000 (88.269) Prec@5 97.000 (99.346) +2022-11-14 16:26:32,863 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0735) Prec@1 91.000 (88.370) Prec@5 100.000 (99.370) +2022-11-14 16:26:32,883 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0728) Prec@1 91.000 (88.464) Prec@5 100.000 (99.393) +2022-11-14 16:26:32,904 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0732) Prec@1 88.000 (88.448) Prec@5 98.000 (99.345) +2022-11-14 16:26:32,925 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0730) Prec@1 89.000 (88.467) Prec@5 100.000 (99.367) +2022-11-14 16:26:32,944 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0730) Prec@1 87.000 (88.419) Prec@5 100.000 (99.387) +2022-11-14 16:26:32,964 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0728) Prec@1 89.000 (88.438) Prec@5 100.000 (99.406) +2022-11-14 16:26:32,983 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0730) Prec@1 89.000 (88.455) Prec@5 100.000 (99.424) +2022-11-14 16:26:33,002 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0731) Prec@1 84.000 (88.324) Prec@5 99.000 (99.412) +2022-11-14 16:26:33,024 Test: [34/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0736) Prec@1 87.000 (88.286) Prec@5 98.000 (99.371) +2022-11-14 16:26:33,042 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0734) Prec@1 91.000 (88.361) Prec@5 99.000 (99.361) +2022-11-14 16:26:33,059 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0730) Prec@1 91.000 (88.432) Prec@5 100.000 (99.378) +2022-11-14 16:26:33,078 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0739) Prec@1 81.000 (88.237) Prec@5 99.000 (99.368) +2022-11-14 16:26:33,097 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0734) Prec@1 93.000 (88.359) Prec@5 99.000 (99.359) +2022-11-14 16:26:33,117 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0730) Prec@1 90.000 (88.400) Prec@5 99.000 (99.350) +2022-11-14 16:26:33,134 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0734) Prec@1 88.000 (88.390) Prec@5 98.000 (99.317) +2022-11-14 16:26:33,150 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0730) Prec@1 90.000 (88.429) Prec@5 99.000 (99.310) +2022-11-14 16:26:33,168 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0725) Prec@1 89.000 (88.442) Prec@5 99.000 (99.302) +2022-11-14 16:26:33,190 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0727) Prec@1 88.000 (88.432) Prec@5 99.000 (99.295) +2022-11-14 16:26:33,206 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0413 (0.0720) Prec@1 93.000 (88.533) Prec@5 99.000 (99.289) +2022-11-14 16:26:33,223 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1080 (0.0728) Prec@1 83.000 (88.413) Prec@5 99.000 (99.283) +2022-11-14 16:26:33,243 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0726) Prec@1 90.000 (88.447) Prec@5 100.000 (99.298) +2022-11-14 16:26:33,262 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0733) Prec@1 86.000 (88.396) Prec@5 99.000 (99.292) +2022-11-14 16:26:33,283 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0728) Prec@1 91.000 (88.449) Prec@5 100.000 (99.306) +2022-11-14 16:26:33,305 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0731) Prec@1 88.000 (88.440) Prec@5 100.000 (99.320) +2022-11-14 16:26:33,327 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0728) Prec@1 89.000 (88.451) Prec@5 100.000 (99.333) +2022-11-14 16:26:33,348 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0732) Prec@1 83.000 (88.346) Prec@5 100.000 (99.346) +2022-11-14 16:26:33,369 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0727) Prec@1 92.000 (88.415) Prec@5 100.000 (99.358) +2022-11-14 16:26:33,390 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0728) Prec@1 87.000 (88.389) Prec@5 99.000 (99.352) +2022-11-14 16:26:33,412 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0731) Prec@1 88.000 (88.382) Prec@5 100.000 (99.364) +2022-11-14 16:26:33,434 Test: [55/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0731) Prec@1 88.000 (88.375) Prec@5 99.000 (99.357) +2022-11-14 16:26:33,453 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0729) Prec@1 89.000 (88.386) Prec@5 99.000 (99.351) +2022-11-14 16:26:33,471 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0727) Prec@1 89.000 (88.397) Prec@5 99.000 (99.345) +2022-11-14 16:26:33,488 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0728) Prec@1 87.000 (88.373) Prec@5 100.000 (99.356) +2022-11-14 16:26:33,508 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0726) Prec@1 89.000 (88.383) Prec@5 100.000 (99.367) +2022-11-14 16:26:33,529 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0727) Prec@1 88.000 (88.377) Prec@5 99.000 (99.361) +2022-11-14 16:26:33,549 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0727) Prec@1 87.000 (88.355) Prec@5 99.000 (99.355) +2022-11-14 16:26:33,570 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0730) Prec@1 85.000 (88.302) Prec@5 99.000 (99.349) +2022-11-14 16:26:33,591 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0443 (0.0726) Prec@1 94.000 (88.391) Prec@5 100.000 (99.359) +2022-11-14 16:26:33,612 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0729) Prec@1 83.000 (88.308) Prec@5 100.000 (99.369) +2022-11-14 16:26:33,633 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0732) Prec@1 85.000 (88.258) Prec@5 100.000 (99.379) +2022-11-14 16:26:33,653 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0730) Prec@1 89.000 (88.269) Prec@5 100.000 (99.388) +2022-11-14 16:26:33,670 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0731) Prec@1 90.000 (88.294) Prec@5 98.000 (99.368) +2022-11-14 16:26:33,688 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0729) Prec@1 87.000 (88.275) Prec@5 99.000 (99.362) +2022-11-14 16:26:33,709 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0729) Prec@1 88.000 (88.271) Prec@5 98.000 (99.343) +2022-11-14 16:26:33,730 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0733) Prec@1 85.000 (88.225) Prec@5 98.000 (99.324) +2022-11-14 16:26:33,752 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0730) Prec@1 92.000 (88.278) Prec@5 100.000 (99.333) +2022-11-14 16:26:33,770 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0728) Prec@1 90.000 (88.301) Prec@5 100.000 (99.342) +2022-11-14 16:26:33,788 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0417 (0.0724) Prec@1 94.000 (88.378) Prec@5 100.000 (99.351) +2022-11-14 16:26:33,808 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1127 (0.0729) Prec@1 82.000 (88.293) Prec@5 100.000 (99.360) +2022-11-14 16:26:33,828 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0730) Prec@1 87.000 (88.276) Prec@5 99.000 (99.355) +2022-11-14 16:26:33,849 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0730) Prec@1 90.000 (88.299) Prec@5 98.000 (99.338) +2022-11-14 16:26:33,868 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0909 (0.0732) Prec@1 87.000 (88.282) Prec@5 97.000 (99.308) +2022-11-14 16:26:33,886 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0730) Prec@1 91.000 (88.316) Prec@5 100.000 (99.316) +2022-11-14 16:26:33,906 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0730) Prec@1 89.000 (88.325) Prec@5 99.000 (99.312) +2022-11-14 16:26:33,925 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0733) Prec@1 84.000 (88.272) Prec@5 99.000 (99.309) +2022-11-14 16:26:33,944 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0734) Prec@1 84.000 (88.220) Prec@5 100.000 (99.317) +2022-11-14 16:26:33,961 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0735) Prec@1 85.000 (88.181) Prec@5 99.000 (99.313) +2022-11-14 16:26:33,979 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0733) Prec@1 90.000 (88.202) Prec@5 98.000 (99.298) +2022-11-14 16:26:33,999 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0733) Prec@1 88.000 (88.200) Prec@5 99.000 (99.294) +2022-11-14 16:26:34,019 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0735) Prec@1 85.000 (88.163) Prec@5 100.000 (99.302) +2022-11-14 16:26:34,038 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0736) Prec@1 82.000 (88.092) Prec@5 100.000 (99.310) +2022-11-14 16:26:34,058 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0737) Prec@1 90.000 (88.114) Prec@5 98.000 (99.295) +2022-11-14 16:26:34,080 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0735) Prec@1 88.000 (88.112) Prec@5 99.000 (99.292) +2022-11-14 16:26:34,099 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0735) Prec@1 90.000 (88.133) Prec@5 99.000 (99.289) +2022-11-14 16:26:34,119 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0734) Prec@1 91.000 (88.165) Prec@5 100.000 (99.297) +2022-11-14 16:26:34,141 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0733) Prec@1 91.000 (88.196) Prec@5 99.000 (99.293) +2022-11-14 16:26:34,161 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0733) Prec@1 90.000 (88.215) Prec@5 100.000 (99.301) +2022-11-14 16:26:34,177 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0733) Prec@1 90.000 (88.234) Prec@5 99.000 (99.298) +2022-11-14 16:26:34,195 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0734) Prec@1 85.000 (88.200) Prec@5 99.000 (99.295) +2022-11-14 16:26:34,214 Test: [95/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0734) Prec@1 89.000 (88.208) Prec@5 100.000 (99.302) +2022-11-14 16:26:34,232 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0442 (0.0731) Prec@1 94.000 (88.268) Prec@5 99.000 (99.299) +2022-11-14 16:26:34,251 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0733) Prec@1 88.000 (88.265) Prec@5 97.000 (99.276) +2022-11-14 16:26:34,269 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1079 (0.0736) Prec@1 85.000 (88.232) Prec@5 98.000 (99.263) +2022-11-14 16:26:34,287 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0737) Prec@1 88.000 (88.230) Prec@5 99.000 (99.260) +2022-11-14 16:26:34,348 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:26:34,698 Epoch: [344][0/500] Time 0.024 (0.024) Data 0.263 (0.263) Loss 0.0230 (0.0230) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:26:35,004 Epoch: [344][10/500] Time 0.034 (0.027) Data 0.002 (0.026) Loss 0.0631 (0.0431) Prec@1 89.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:26:35,321 Epoch: [344][20/500] Time 0.031 (0.028) Data 0.002 (0.014) Loss 0.0467 (0.0443) Prec@1 94.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 16:26:35,653 Epoch: [344][30/500] Time 0.036 (0.028) Data 0.003 (0.010) Loss 0.0146 (0.0369) Prec@1 97.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:26:35,982 Epoch: [344][40/500] Time 0.029 (0.028) Data 0.002 (0.008) Loss 0.0310 (0.0357) Prec@1 95.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 16:26:36,530 Epoch: [344][50/500] Time 0.052 (0.032) Data 0.003 (0.007) Loss 0.0318 (0.0351) Prec@1 95.000 (94.667) Prec@5 99.000 (99.667) +2022-11-14 16:26:37,077 Epoch: [344][60/500] Time 0.055 (0.035) Data 0.002 (0.006) Loss 0.0277 (0.0340) Prec@1 96.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:26:37,633 Epoch: [344][70/500] Time 0.050 (0.037) Data 0.002 (0.006) Loss 0.0224 (0.0326) Prec@1 97.000 (95.125) Prec@5 100.000 (99.750) +2022-11-14 16:26:38,169 Epoch: [344][80/500] Time 0.047 (0.038) Data 0.003 (0.005) Loss 0.0587 (0.0355) Prec@1 90.000 (94.556) Prec@5 100.000 (99.778) +2022-11-14 16:26:38,718 Epoch: [344][90/500] Time 0.049 (0.040) Data 0.002 (0.005) Loss 0.0248 (0.0344) Prec@1 96.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 16:26:39,278 Epoch: [344][100/500] Time 0.054 (0.041) Data 0.002 (0.005) Loss 0.0291 (0.0339) Prec@1 96.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:26:39,833 Epoch: [344][110/500] Time 0.051 (0.041) Data 0.002 (0.004) Loss 0.0408 (0.0345) Prec@1 90.000 (94.417) Prec@5 99.000 (99.750) +2022-11-14 16:26:40,391 Epoch: [344][120/500] Time 0.055 (0.042) Data 0.002 (0.004) Loss 0.0396 (0.0349) Prec@1 93.000 (94.308) Prec@5 100.000 (99.769) +2022-11-14 16:26:40,939 Epoch: [344][130/500] Time 0.055 (0.043) Data 0.003 (0.004) Loss 0.0426 (0.0354) Prec@1 94.000 (94.286) Prec@5 100.000 (99.786) +2022-11-14 16:26:41,503 Epoch: [344][140/500] Time 0.062 (0.043) Data 0.002 (0.004) Loss 0.0648 (0.0374) Prec@1 90.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 16:26:42,064 Epoch: [344][150/500] Time 0.049 (0.044) Data 0.002 (0.004) Loss 0.0311 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (99.812) +2022-11-14 16:26:42,608 Epoch: [344][160/500] Time 0.050 (0.044) Data 0.002 (0.004) Loss 0.0209 (0.0360) Prec@1 97.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 16:26:43,162 Epoch: [344][170/500] Time 0.058 (0.044) Data 0.002 (0.004) Loss 0.0526 (0.0370) Prec@1 93.000 (94.111) Prec@5 99.000 (99.778) +2022-11-14 16:26:43,706 Epoch: [344][180/500] Time 0.047 (0.044) Data 0.002 (0.004) Loss 0.0370 (0.0370) Prec@1 93.000 (94.053) Prec@5 100.000 (99.789) +2022-11-14 16:26:44,271 Epoch: [344][190/500] Time 0.053 (0.045) Data 0.002 (0.003) Loss 0.0260 (0.0364) Prec@1 95.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 16:26:44,806 Epoch: [344][200/500] Time 0.048 (0.045) Data 0.002 (0.003) Loss 0.0302 (0.0361) Prec@1 95.000 (94.143) Prec@5 100.000 (99.810) +2022-11-14 16:26:45,358 Epoch: [344][210/500] Time 0.050 (0.045) Data 0.002 (0.003) Loss 0.0270 (0.0357) Prec@1 95.000 (94.182) Prec@5 100.000 (99.818) +2022-11-14 16:26:45,905 Epoch: [344][220/500] Time 0.059 (0.045) Data 0.002 (0.003) Loss 0.0299 (0.0355) Prec@1 95.000 (94.217) Prec@5 100.000 (99.826) +2022-11-14 16:26:46,449 Epoch: [344][230/500] Time 0.040 (0.045) Data 0.002 (0.003) Loss 0.0138 (0.0346) Prec@1 98.000 (94.375) Prec@5 100.000 (99.833) +2022-11-14 16:26:47,016 Epoch: [344][240/500] Time 0.049 (0.046) Data 0.002 (0.003) Loss 0.0137 (0.0337) Prec@1 98.000 (94.520) Prec@5 100.000 (99.840) +2022-11-14 16:26:47,566 Epoch: [344][250/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0357 (0.0338) Prec@1 96.000 (94.577) Prec@5 100.000 (99.846) +2022-11-14 16:26:48,129 Epoch: [344][260/500] Time 0.055 (0.046) Data 0.002 (0.003) Loss 0.0258 (0.0335) Prec@1 96.000 (94.630) Prec@5 100.000 (99.852) +2022-11-14 16:26:48,680 Epoch: [344][270/500] Time 0.053 (0.046) Data 0.002 (0.003) Loss 0.0402 (0.0337) Prec@1 92.000 (94.536) Prec@5 100.000 (99.857) +2022-11-14 16:26:49,218 Epoch: [344][280/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0182 (0.0332) Prec@1 98.000 (94.655) Prec@5 100.000 (99.862) +2022-11-14 16:26:49,752 Epoch: [344][290/500] Time 0.054 (0.046) Data 0.002 (0.003) Loss 0.0393 (0.0334) Prec@1 93.000 (94.600) Prec@5 100.000 (99.867) +2022-11-14 16:26:50,319 Epoch: [344][300/500] Time 0.056 (0.046) Data 0.002 (0.003) Loss 0.0336 (0.0334) Prec@1 95.000 (94.613) Prec@5 100.000 (99.871) +2022-11-14 16:26:50,874 Epoch: [344][310/500] Time 0.047 (0.046) Data 0.002 (0.003) Loss 0.0424 (0.0337) Prec@1 93.000 (94.562) Prec@5 100.000 (99.875) +2022-11-14 16:26:51,445 Epoch: [344][320/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0632 (0.0346) Prec@1 87.000 (94.333) Prec@5 100.000 (99.879) +2022-11-14 16:26:52,002 Epoch: [344][330/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0308 (0.0345) Prec@1 95.000 (94.353) Prec@5 100.000 (99.882) +2022-11-14 16:26:52,570 Epoch: [344][340/500] Time 0.054 (0.047) Data 0.002 (0.003) Loss 0.0359 (0.0345) Prec@1 93.000 (94.314) Prec@5 100.000 (99.886) +2022-11-14 16:26:53,134 Epoch: [344][350/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0387 (0.0346) Prec@1 93.000 (94.278) Prec@5 100.000 (99.889) +2022-11-14 16:26:53,686 Epoch: [344][360/500] Time 0.056 (0.047) Data 0.002 (0.003) Loss 0.0320 (0.0346) Prec@1 95.000 (94.297) Prec@5 99.000 (99.865) +2022-11-14 16:26:54,236 Epoch: [344][370/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0470 (0.0349) Prec@1 91.000 (94.211) Prec@5 100.000 (99.868) +2022-11-14 16:26:54,800 Epoch: [344][380/500] Time 0.051 (0.047) Data 0.002 (0.003) Loss 0.0408 (0.0350) Prec@1 93.000 (94.179) Prec@5 99.000 (99.846) +2022-11-14 16:26:55,353 Epoch: [344][390/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0193 (0.0346) Prec@1 96.000 (94.225) Prec@5 100.000 (99.850) +2022-11-14 16:26:55,917 Epoch: [344][400/500] Time 0.052 (0.047) Data 0.002 (0.003) Loss 0.0322 (0.0346) Prec@1 96.000 (94.268) Prec@5 99.000 (99.829) +2022-11-14 16:26:56,450 Epoch: [344][410/500] Time 0.045 (0.047) Data 0.002 (0.003) Loss 0.0258 (0.0344) Prec@1 98.000 (94.357) Prec@5 100.000 (99.833) +2022-11-14 16:26:57,013 Epoch: [344][420/500] Time 0.055 (0.047) Data 0.002 (0.003) Loss 0.0188 (0.0340) Prec@1 96.000 (94.395) Prec@5 100.000 (99.837) +2022-11-14 16:26:57,577 Epoch: [344][430/500] Time 0.059 (0.047) Data 0.002 (0.003) Loss 0.0260 (0.0338) Prec@1 97.000 (94.455) Prec@5 98.000 (99.795) +2022-11-14 16:26:58,134 Epoch: [344][440/500] Time 0.060 (0.047) Data 0.002 (0.003) Loss 0.0320 (0.0338) Prec@1 95.000 (94.467) Prec@5 100.000 (99.800) +2022-11-14 16:26:58,682 Epoch: [344][450/500] Time 0.047 (0.048) Data 0.002 (0.003) Loss 0.0482 (0.0341) Prec@1 94.000 (94.457) Prec@5 100.000 (99.804) +2022-11-14 16:26:59,220 Epoch: [344][460/500] Time 0.048 (0.047) Data 0.002 (0.003) Loss 0.0296 (0.0340) Prec@1 95.000 (94.468) Prec@5 100.000 (99.809) +2022-11-14 16:26:59,775 Epoch: [344][470/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0334 (0.0340) Prec@1 96.000 (94.500) Prec@5 100.000 (99.812) +2022-11-14 16:27:00,333 Epoch: [344][480/500] Time 0.058 (0.048) Data 0.002 (0.003) Loss 0.0159 (0.0336) Prec@1 97.000 (94.551) Prec@5 100.000 (99.816) +2022-11-14 16:27:00,873 Epoch: [344][490/500] Time 0.048 (0.048) Data 0.002 (0.003) Loss 0.0272 (0.0335) Prec@1 97.000 (94.600) Prec@5 99.000 (99.800) +2022-11-14 16:27:01,369 Epoch: [344][499/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0206 (0.0332) Prec@1 95.000 (94.608) Prec@5 100.000 (99.804) +2022-11-14 16:27:01,701 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0576 (0.0576) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 16:27:01,713 Test: [1/100] Model Time 0.010 (0.013) Loss Time 0.000 (0.000) Loss 0.0658 (0.0617) Prec@1 90.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 16:27:01,724 Test: [2/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0577 (0.0604) Prec@1 92.000 (91.000) Prec@5 100.000 (99.667) +2022-11-14 16:27:01,738 Test: [3/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0882 (0.0673) Prec@1 87.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 16:27:01,747 Test: [4/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0739 (0.0686) Prec@1 90.000 (90.000) Prec@5 99.000 (99.400) +2022-11-14 16:27:01,757 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0539 (0.0662) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 16:27:01,769 Test: [6/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0665) Prec@1 90.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 16:27:01,786 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0851 (0.0688) Prec@1 85.000 (89.375) Prec@5 99.000 (99.500) +2022-11-14 16:27:01,801 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0692) Prec@1 91.000 (89.556) Prec@5 100.000 (99.556) +2022-11-14 16:27:01,816 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0696) Prec@1 89.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:27:01,833 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0458 (0.0675) Prec@1 93.000 (89.818) Prec@5 100.000 (99.545) +2022-11-14 16:27:01,847 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0691) Prec@1 87.000 (89.583) Prec@5 100.000 (99.583) +2022-11-14 16:27:01,863 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0689) Prec@1 90.000 (89.615) Prec@5 100.000 (99.615) +2022-11-14 16:27:01,879 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0703) Prec@1 86.000 (89.357) Prec@5 100.000 (99.643) +2022-11-14 16:27:01,897 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0704) Prec@1 89.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:27:01,917 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0703) Prec@1 88.000 (89.250) Prec@5 100.000 (99.688) +2022-11-14 16:27:01,938 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0692) Prec@1 93.000 (89.471) Prec@5 98.000 (99.588) +2022-11-14 16:27:01,959 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1186 (0.0720) Prec@1 82.000 (89.056) Prec@5 100.000 (99.611) +2022-11-14 16:27:01,978 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0729) Prec@1 85.000 (88.842) Prec@5 100.000 (99.632) +2022-11-14 16:27:01,995 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0742) Prec@1 84.000 (88.600) Prec@5 99.000 (99.600) +2022-11-14 16:27:02,016 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0740) Prec@1 88.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 16:27:02,035 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0745) Prec@1 85.000 (88.409) Prec@5 99.000 (99.545) +2022-11-14 16:27:02,052 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0753) Prec@1 87.000 (88.348) Prec@5 97.000 (99.435) +2022-11-14 16:27:02,072 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0752) Prec@1 88.000 (88.333) Prec@5 100.000 (99.458) +2022-11-14 16:27:02,091 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0749) Prec@1 90.000 (88.400) Prec@5 100.000 (99.480) +2022-11-14 16:27:02,108 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1074 (0.0762) Prec@1 82.000 (88.154) Prec@5 99.000 (99.462) +2022-11-14 16:27:02,124 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0463 (0.0751) Prec@1 93.000 (88.333) Prec@5 100.000 (99.481) +2022-11-14 16:27:02,142 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0747) Prec@1 90.000 (88.393) Prec@5 99.000 (99.464) +2022-11-14 16:27:02,160 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0749) Prec@1 86.000 (88.310) Prec@5 98.000 (99.414) +2022-11-14 16:27:02,180 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0748) Prec@1 89.000 (88.333) Prec@5 99.000 (99.400) +2022-11-14 16:27:02,198 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0747) Prec@1 87.000 (88.290) Prec@5 100.000 (99.419) +2022-11-14 16:27:02,217 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0749) Prec@1 86.000 (88.219) Prec@5 99.000 (99.406) +2022-11-14 16:27:02,234 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0750) Prec@1 88.000 (88.212) Prec@5 100.000 (99.424) +2022-11-14 16:27:02,249 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0752) Prec@1 85.000 (88.118) Prec@5 100.000 (99.441) +2022-11-14 16:27:02,271 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0751) Prec@1 89.000 (88.143) Prec@5 99.000 (99.429) +2022-11-14 16:27:02,290 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0749) Prec@1 90.000 (88.194) Prec@5 100.000 (99.444) +2022-11-14 16:27:02,308 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0746) Prec@1 88.000 (88.189) Prec@5 99.000 (99.432) +2022-11-14 16:27:02,328 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1019 (0.0754) Prec@1 82.000 (88.026) Prec@5 99.000 (99.421) +2022-11-14 16:27:02,349 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0748) Prec@1 94.000 (88.179) Prec@5 99.000 (99.410) +2022-11-14 16:27:02,368 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0741) Prec@1 92.000 (88.275) Prec@5 100.000 (99.425) +2022-11-14 16:27:02,388 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0747) Prec@1 85.000 (88.195) Prec@5 97.000 (99.366) +2022-11-14 16:27:02,405 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0743) Prec@1 91.000 (88.262) Prec@5 100.000 (99.381) +2022-11-14 16:27:02,425 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0386 (0.0735) Prec@1 93.000 (88.372) Prec@5 99.000 (99.372) +2022-11-14 16:27:02,444 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0733) Prec@1 88.000 (88.364) Prec@5 99.000 (99.364) +2022-11-14 16:27:02,465 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0732) Prec@1 88.000 (88.356) Prec@5 100.000 (99.378) +2022-11-14 16:27:02,485 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0735) Prec@1 82.000 (88.217) Prec@5 100.000 (99.391) +2022-11-14 16:27:02,503 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0736) Prec@1 87.000 (88.191) Prec@5 100.000 (99.404) +2022-11-14 16:27:02,521 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0741) Prec@1 85.000 (88.125) Prec@5 100.000 (99.417) +2022-11-14 16:27:02,538 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0737) Prec@1 91.000 (88.184) Prec@5 100.000 (99.429) +2022-11-14 16:27:02,556 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1203 (0.0746) Prec@1 82.000 (88.060) Prec@5 100.000 (99.440) +2022-11-14 16:27:02,576 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0742) Prec@1 88.000 (88.059) Prec@5 100.000 (99.451) +2022-11-14 16:27:02,592 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0746) Prec@1 84.000 (87.981) Prec@5 99.000 (99.442) +2022-11-14 16:27:02,611 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1016 (0.0752) Prec@1 85.000 (87.925) Prec@5 100.000 (99.453) +2022-11-14 16:27:02,632 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0749) Prec@1 90.000 (87.963) Prec@5 100.000 (99.463) +2022-11-14 16:27:02,653 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0749) Prec@1 90.000 (88.000) Prec@5 100.000 (99.473) +2022-11-14 16:27:02,673 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 87.000 (87.982) Prec@5 98.000 (99.446) +2022-11-14 16:27:02,692 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0748) Prec@1 87.000 (87.965) Prec@5 100.000 (99.456) +2022-11-14 16:27:02,709 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0748) Prec@1 89.000 (87.983) Prec@5 99.000 (99.448) +2022-11-14 16:27:02,730 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0753) Prec@1 83.000 (87.898) Prec@5 100.000 (99.458) +2022-11-14 16:27:02,751 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0755) Prec@1 84.000 (87.833) Prec@5 99.000 (99.450) +2022-11-14 16:27:02,771 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0755) Prec@1 87.000 (87.820) Prec@5 99.000 (99.443) +2022-11-14 16:27:02,790 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0755) Prec@1 86.000 (87.790) Prec@5 100.000 (99.452) +2022-11-14 16:27:02,808 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0753) Prec@1 91.000 (87.841) Prec@5 100.000 (99.460) +2022-11-14 16:27:02,830 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0453 (0.0748) Prec@1 91.000 (87.891) Prec@5 100.000 (99.469) +2022-11-14 16:27:02,850 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0749) Prec@1 85.000 (87.846) Prec@5 100.000 (99.477) +2022-11-14 16:27:02,865 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0748) Prec@1 85.000 (87.803) Prec@5 99.000 (99.470) +2022-11-14 16:27:02,886 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0332 (0.0742) Prec@1 95.000 (87.910) Prec@5 99.000 (99.463) +2022-11-14 16:27:02,902 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 87.000 (87.897) Prec@5 99.000 (99.456) +2022-11-14 16:27:02,920 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0741) Prec@1 91.000 (87.942) Prec@5 99.000 (99.449) +2022-11-14 16:27:02,938 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0740) Prec@1 89.000 (87.957) Prec@5 99.000 (99.443) +2022-11-14 16:27:02,959 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0743) Prec@1 86.000 (87.930) Prec@5 98.000 (99.423) +2022-11-14 16:27:02,978 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0740) Prec@1 90.000 (87.958) Prec@5 100.000 (99.431) +2022-11-14 16:27:02,996 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0421 (0.0736) Prec@1 93.000 (88.027) Prec@5 100.000 (99.438) +2022-11-14 16:27:03,013 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0418 (0.0732) Prec@1 94.000 (88.108) Prec@5 100.000 (99.446) +2022-11-14 16:27:03,030 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1198 (0.0738) Prec@1 80.000 (88.000) Prec@5 99.000 (99.440) +2022-11-14 16:27:03,048 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0736) Prec@1 90.000 (88.026) Prec@5 100.000 (99.447) +2022-11-14 16:27:03,065 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0737) Prec@1 88.000 (88.026) Prec@5 99.000 (99.442) +2022-11-14 16:27:03,082 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0740) Prec@1 82.000 (87.949) Prec@5 99.000 (99.436) +2022-11-14 16:27:03,100 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0740) Prec@1 88.000 (87.949) Prec@5 100.000 (99.443) +2022-11-14 16:27:03,119 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0739) Prec@1 89.000 (87.963) Prec@5 99.000 (99.438) +2022-11-14 16:27:03,137 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0743) Prec@1 84.000 (87.914) Prec@5 99.000 (99.432) +2022-11-14 16:27:03,155 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0744) Prec@1 85.000 (87.878) Prec@5 100.000 (99.439) +2022-11-14 16:27:03,174 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0744) Prec@1 87.000 (87.867) Prec@5 100.000 (99.446) +2022-11-14 16:27:03,192 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0743) Prec@1 90.000 (87.893) Prec@5 99.000 (99.440) +2022-11-14 16:27:03,210 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0748) Prec@1 81.000 (87.812) Prec@5 98.000 (99.424) +2022-11-14 16:27:03,229 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0750) Prec@1 82.000 (87.744) Prec@5 100.000 (99.430) +2022-11-14 16:27:03,250 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0748) Prec@1 90.000 (87.770) Prec@5 99.000 (99.425) +2022-11-14 16:27:03,272 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0749) Prec@1 86.000 (87.750) Prec@5 99.000 (99.420) +2022-11-14 16:27:03,289 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0751) Prec@1 83.000 (87.697) Prec@5 99.000 (99.416) +2022-11-14 16:27:03,307 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0751) Prec@1 89.000 (87.711) Prec@5 99.000 (99.411) +2022-11-14 16:27:03,325 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0750) Prec@1 90.000 (87.736) Prec@5 100.000 (99.418) +2022-11-14 16:27:03,342 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0433 (0.0747) Prec@1 93.000 (87.793) Prec@5 100.000 (99.424) +2022-11-14 16:27:03,361 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0747) Prec@1 89.000 (87.806) Prec@5 100.000 (99.430) +2022-11-14 16:27:03,378 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0746) Prec@1 90.000 (87.830) Prec@5 100.000 (99.436) +2022-11-14 16:27:03,398 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0746) Prec@1 87.000 (87.821) Prec@5 100.000 (99.442) +2022-11-14 16:27:03,418 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0743) Prec@1 94.000 (87.885) Prec@5 100.000 (99.448) +2022-11-14 16:27:03,439 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0741) Prec@1 94.000 (87.948) Prec@5 99.000 (99.443) +2022-11-14 16:27:03,455 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0743) Prec@1 84.000 (87.908) Prec@5 96.000 (99.408) +2022-11-14 16:27:03,475 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0745) Prec@1 85.000 (87.879) Prec@5 99.000 (99.404) +2022-11-14 16:27:03,495 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0744) Prec@1 87.000 (87.870) Prec@5 100.000 (99.410) +2022-11-14 16:27:03,554 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:27:03,903 Epoch: [345][0/500] Time 0.025 (0.025) Data 0.259 (0.259) Loss 0.0443 (0.0443) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 16:27:04,189 Epoch: [345][10/500] Time 0.032 (0.025) Data 0.002 (0.025) Loss 0.0243 (0.0343) Prec@1 94.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 16:27:04,503 Epoch: [345][20/500] Time 0.032 (0.026) Data 0.002 (0.014) Loss 0.0361 (0.0349) Prec@1 93.000 (92.667) Prec@5 100.000 (99.667) +2022-11-14 16:27:04,828 Epoch: [345][30/500] Time 0.028 (0.027) Data 0.002 (0.010) Loss 0.0521 (0.0392) Prec@1 90.000 (92.000) Prec@5 100.000 (99.750) +2022-11-14 16:27:05,195 Epoch: [345][40/500] Time 0.042 (0.028) Data 0.002 (0.008) Loss 0.0217 (0.0357) Prec@1 96.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 16:27:05,667 Epoch: [345][50/500] Time 0.038 (0.031) Data 0.003 (0.007) Loss 0.0177 (0.0327) Prec@1 98.000 (93.667) Prec@5 100.000 (99.833) +2022-11-14 16:27:06,134 Epoch: [345][60/500] Time 0.038 (0.033) Data 0.002 (0.006) Loss 0.0266 (0.0318) Prec@1 97.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 16:27:06,618 Epoch: [345][70/500] Time 0.044 (0.034) Data 0.002 (0.006) Loss 0.0201 (0.0303) Prec@1 97.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:27:07,109 Epoch: [345][80/500] Time 0.046 (0.035) Data 0.002 (0.005) Loss 0.0363 (0.0310) Prec@1 94.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:27:07,606 Epoch: [345][90/500] Time 0.038 (0.036) Data 0.002 (0.005) Loss 0.0209 (0.0300) Prec@1 97.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 16:27:08,074 Epoch: [345][100/500] Time 0.054 (0.037) Data 0.002 (0.005) Loss 0.0343 (0.0304) Prec@1 93.000 (94.545) Prec@5 99.000 (99.818) +2022-11-14 16:27:08,566 Epoch: [345][110/500] Time 0.045 (0.037) Data 0.002 (0.004) Loss 0.0507 (0.0321) Prec@1 92.000 (94.333) Prec@5 99.000 (99.750) +2022-11-14 16:27:09,053 Epoch: [345][120/500] Time 0.046 (0.038) Data 0.002 (0.004) Loss 0.0241 (0.0315) Prec@1 96.000 (94.462) Prec@5 100.000 (99.769) +2022-11-14 16:27:09,544 Epoch: [345][130/500] Time 0.048 (0.038) Data 0.002 (0.004) Loss 0.0160 (0.0304) Prec@1 97.000 (94.643) Prec@5 100.000 (99.786) +2022-11-14 16:27:10,029 Epoch: [345][140/500] Time 0.048 (0.039) Data 0.002 (0.004) Loss 0.0207 (0.0297) Prec@1 97.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:27:10,503 Epoch: [345][150/500] Time 0.047 (0.039) Data 0.002 (0.004) Loss 0.0365 (0.0301) Prec@1 93.000 (94.688) Prec@5 99.000 (99.750) +2022-11-14 16:27:10,987 Epoch: [345][160/500] Time 0.048 (0.039) Data 0.002 (0.004) Loss 0.0309 (0.0302) Prec@1 95.000 (94.706) Prec@5 100.000 (99.765) +2022-11-14 16:27:11,492 Epoch: [345][170/500] Time 0.052 (0.040) Data 0.002 (0.004) Loss 0.0256 (0.0299) Prec@1 96.000 (94.778) Prec@5 99.000 (99.722) +2022-11-14 16:27:12,006 Epoch: [345][180/500] Time 0.045 (0.040) Data 0.002 (0.003) Loss 0.0114 (0.0290) Prec@1 99.000 (95.000) Prec@5 100.000 (99.737) +2022-11-14 16:27:12,486 Epoch: [345][190/500] Time 0.054 (0.040) Data 0.002 (0.003) Loss 0.0334 (0.0292) Prec@1 96.000 (95.050) Prec@5 99.000 (99.700) +2022-11-14 16:27:12,969 Epoch: [345][200/500] Time 0.043 (0.040) Data 0.002 (0.003) Loss 0.0371 (0.0296) Prec@1 95.000 (95.048) Prec@5 100.000 (99.714) +2022-11-14 16:27:13,465 Epoch: [345][210/500] Time 0.049 (0.040) Data 0.002 (0.003) Loss 0.0289 (0.0295) Prec@1 96.000 (95.091) Prec@5 99.000 (99.682) +2022-11-14 16:27:13,945 Epoch: [345][220/500] Time 0.047 (0.041) Data 0.002 (0.003) Loss 0.0522 (0.0305) Prec@1 90.000 (94.870) Prec@5 100.000 (99.696) +2022-11-14 16:27:14,539 Epoch: [345][230/500] Time 0.052 (0.041) Data 0.003 (0.003) Loss 0.0382 (0.0308) Prec@1 94.000 (94.833) Prec@5 98.000 (99.625) +2022-11-14 16:27:15,019 Epoch: [345][240/500] Time 0.052 (0.041) Data 0.002 (0.003) Loss 0.0311 (0.0308) Prec@1 93.000 (94.760) Prec@5 100.000 (99.640) +2022-11-14 16:27:15,516 Epoch: [345][250/500] Time 0.058 (0.041) Data 0.002 (0.003) Loss 0.0584 (0.0319) Prec@1 91.000 (94.615) Prec@5 98.000 (99.577) +2022-11-14 16:27:16,018 Epoch: [345][260/500] Time 0.057 (0.041) Data 0.002 (0.003) Loss 0.0343 (0.0320) Prec@1 92.000 (94.519) Prec@5 99.000 (99.556) +2022-11-14 16:27:16,507 Epoch: [345][270/500] Time 0.038 (0.042) Data 0.002 (0.003) Loss 0.0530 (0.0327) Prec@1 90.000 (94.357) Prec@5 99.000 (99.536) +2022-11-14 16:27:17,003 Epoch: [345][280/500] Time 0.047 (0.042) Data 0.003 (0.003) Loss 0.0209 (0.0323) Prec@1 98.000 (94.483) Prec@5 100.000 (99.552) +2022-11-14 16:27:17,478 Epoch: [345][290/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0484 (0.0329) Prec@1 88.000 (94.267) Prec@5 100.000 (99.567) +2022-11-14 16:27:17,970 Epoch: [345][300/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0407 (0.0331) Prec@1 93.000 (94.226) Prec@5 100.000 (99.581) +2022-11-14 16:27:18,465 Epoch: [345][310/500] Time 0.047 (0.042) Data 0.002 (0.003) Loss 0.0383 (0.0333) Prec@1 95.000 (94.250) Prec@5 98.000 (99.531) +2022-11-14 16:27:18,951 Epoch: [345][320/500] Time 0.051 (0.042) Data 0.002 (0.003) Loss 0.0258 (0.0331) Prec@1 96.000 (94.303) Prec@5 100.000 (99.545) +2022-11-14 16:27:19,442 Epoch: [345][330/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0094 (0.0324) Prec@1 99.000 (94.441) Prec@5 100.000 (99.559) +2022-11-14 16:27:19,912 Epoch: [345][340/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0441 (0.0327) Prec@1 92.000 (94.371) Prec@5 100.000 (99.571) +2022-11-14 16:27:20,414 Epoch: [345][350/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0180 (0.0323) Prec@1 97.000 (94.444) Prec@5 99.000 (99.556) +2022-11-14 16:27:20,911 Epoch: [345][360/500] Time 0.044 (0.042) Data 0.002 (0.003) Loss 0.0237 (0.0321) Prec@1 96.000 (94.486) Prec@5 100.000 (99.568) +2022-11-14 16:27:21,398 Epoch: [345][370/500] Time 0.040 (0.042) Data 0.002 (0.003) Loss 0.0415 (0.0323) Prec@1 94.000 (94.474) Prec@5 99.000 (99.553) +2022-11-14 16:27:21,891 Epoch: [345][380/500] Time 0.046 (0.042) Data 0.003 (0.003) Loss 0.0367 (0.0324) Prec@1 94.000 (94.462) Prec@5 100.000 (99.564) +2022-11-14 16:27:22,386 Epoch: [345][390/500] Time 0.048 (0.042) Data 0.002 (0.003) Loss 0.0419 (0.0327) Prec@1 94.000 (94.450) Prec@5 100.000 (99.575) +2022-11-14 16:27:22,868 Epoch: [345][400/500] Time 0.043 (0.042) Data 0.002 (0.003) Loss 0.0354 (0.0327) Prec@1 94.000 (94.439) Prec@5 100.000 (99.585) +2022-11-14 16:27:23,364 Epoch: [345][410/500] Time 0.054 (0.042) Data 0.002 (0.003) Loss 0.0281 (0.0326) Prec@1 94.000 (94.429) Prec@5 100.000 (99.595) +2022-11-14 16:27:23,849 Epoch: [345][420/500] Time 0.039 (0.042) Data 0.002 (0.003) Loss 0.0229 (0.0324) Prec@1 97.000 (94.488) Prec@5 100.000 (99.605) +2022-11-14 16:27:24,349 Epoch: [345][430/500] Time 0.050 (0.042) Data 0.002 (0.003) Loss 0.0290 (0.0323) Prec@1 97.000 (94.545) Prec@5 99.000 (99.591) +2022-11-14 16:27:24,822 Epoch: [345][440/500] Time 0.051 (0.042) Data 0.002 (0.003) Loss 0.0291 (0.0322) Prec@1 95.000 (94.556) Prec@5 100.000 (99.600) +2022-11-14 16:27:25,328 Epoch: [345][450/500] Time 0.052 (0.042) Data 0.002 (0.003) Loss 0.0249 (0.0321) Prec@1 97.000 (94.609) Prec@5 99.000 (99.587) +2022-11-14 16:27:25,835 Epoch: [345][460/500] Time 0.038 (0.042) Data 0.002 (0.003) Loss 0.0250 (0.0319) Prec@1 97.000 (94.660) Prec@5 100.000 (99.596) +2022-11-14 16:27:26,494 Epoch: [345][470/500] Time 0.075 (0.043) Data 0.002 (0.003) Loss 0.0239 (0.0318) Prec@1 97.000 (94.708) Prec@5 100.000 (99.604) +2022-11-14 16:27:27,470 Epoch: [345][480/500] Time 0.119 (0.044) Data 0.002 (0.003) Loss 0.0560 (0.0323) Prec@1 93.000 (94.673) Prec@5 100.000 (99.612) +2022-11-14 16:27:28,314 Epoch: [345][490/500] Time 0.071 (0.044) Data 0.002 (0.003) Loss 0.0181 (0.0320) Prec@1 97.000 (94.720) Prec@5 100.000 (99.620) +2022-11-14 16:27:29,031 Epoch: [345][499/500] Time 0.086 (0.045) Data 0.002 (0.003) Loss 0.0291 (0.0319) Prec@1 95.000 (94.725) Prec@5 100.000 (99.627) +2022-11-14 16:27:29,395 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0798 (0.0798) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:27:29,408 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0692 (0.0745) Prec@1 87.000 (87.500) Prec@5 99.000 (99.000) +2022-11-14 16:27:29,422 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0855 (0.0782) Prec@1 87.000 (87.333) Prec@5 100.000 (99.333) +2022-11-14 16:27:29,444 Test: [3/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0864 (0.0802) Prec@1 88.000 (87.500) Prec@5 99.000 (99.250) +2022-11-14 16:27:29,462 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0896 (0.0821) Prec@1 85.000 (87.000) Prec@5 99.000 (99.200) +2022-11-14 16:27:29,483 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0412 (0.0753) Prec@1 93.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 16:27:29,504 Test: [6/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0670 (0.0741) Prec@1 89.000 (88.143) Prec@5 100.000 (99.429) +2022-11-14 16:27:29,528 Test: [7/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0979 (0.0771) Prec@1 88.000 (88.125) Prec@5 98.000 (99.250) +2022-11-14 16:27:29,552 Test: [8/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0805 (0.0775) Prec@1 88.000 (88.111) Prec@5 99.000 (99.222) +2022-11-14 16:27:29,573 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0665 (0.0764) Prec@1 89.000 (88.200) Prec@5 98.000 (99.100) +2022-11-14 16:27:29,589 Test: [10/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0670 (0.0755) Prec@1 88.000 (88.182) Prec@5 100.000 (99.182) +2022-11-14 16:27:29,611 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0787 (0.0758) Prec@1 87.000 (88.083) Prec@5 100.000 (99.250) +2022-11-14 16:27:29,628 Test: [12/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0445 (0.0734) Prec@1 90.000 (88.231) Prec@5 100.000 (99.308) +2022-11-14 16:27:29,646 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0741) Prec@1 88.000 (88.214) Prec@5 98.000 (99.214) +2022-11-14 16:27:29,664 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0927 (0.0753) Prec@1 86.000 (88.067) Prec@5 99.000 (99.200) +2022-11-14 16:27:29,687 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0752) Prec@1 87.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 16:27:29,711 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0469 (0.0735) Prec@1 93.000 (88.294) Prec@5 97.000 (99.118) +2022-11-14 16:27:29,733 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1035 (0.0752) Prec@1 87.000 (88.222) Prec@5 100.000 (99.167) +2022-11-14 16:27:29,756 Test: [18/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0773 (0.0753) Prec@1 88.000 (88.211) Prec@5 97.000 (99.053) +2022-11-14 16:27:29,779 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1007 (0.0766) Prec@1 85.000 (88.050) Prec@5 97.000 (98.950) +2022-11-14 16:27:29,799 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0764) Prec@1 88.000 (88.048) Prec@5 100.000 (99.000) +2022-11-14 16:27:29,819 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0758) Prec@1 90.000 (88.136) Prec@5 99.000 (99.000) +2022-11-14 16:27:29,838 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1033 (0.0770) Prec@1 83.000 (87.913) Prec@5 98.000 (98.957) +2022-11-14 16:27:29,859 Test: [23/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0772) Prec@1 87.000 (87.875) Prec@5 99.000 (98.958) +2022-11-14 16:27:29,880 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0773) Prec@1 87.000 (87.840) Prec@5 99.000 (98.960) +2022-11-14 16:27:29,903 Test: [25/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.0784) Prec@1 82.000 (87.615) Prec@5 97.000 (98.885) +2022-11-14 16:27:29,923 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0776) Prec@1 91.000 (87.741) Prec@5 100.000 (98.926) +2022-11-14 16:27:29,944 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0770) Prec@1 89.000 (87.786) Prec@5 99.000 (98.929) +2022-11-14 16:27:29,966 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0775) Prec@1 87.000 (87.759) Prec@5 99.000 (98.931) +2022-11-14 16:27:29,984 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0772) Prec@1 88.000 (87.767) Prec@5 100.000 (98.967) +2022-11-14 16:27:30,001 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0773) Prec@1 84.000 (87.645) Prec@5 100.000 (99.000) +2022-11-14 16:27:30,022 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0772) Prec@1 87.000 (87.625) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,043 Test: [32/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0773) Prec@1 88.000 (87.636) Prec@5 100.000 (99.030) +2022-11-14 16:27:30,064 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1268 (0.0788) Prec@1 79.000 (87.382) Prec@5 100.000 (99.059) +2022-11-14 16:27:30,083 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1048 (0.0795) Prec@1 85.000 (87.314) Prec@5 96.000 (98.971) +2022-11-14 16:27:30,103 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0696 (0.0792) Prec@1 90.000 (87.389) Prec@5 100.000 (99.000) +2022-11-14 16:27:30,122 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0792) Prec@1 88.000 (87.405) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,142 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1046 (0.0799) Prec@1 81.000 (87.237) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,161 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0792) Prec@1 93.000 (87.385) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,178 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0409 (0.0783) Prec@1 94.000 (87.550) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,197 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1090 (0.0790) Prec@1 82.000 (87.415) Prec@5 98.000 (98.976) +2022-11-14 16:27:30,216 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0948 (0.0794) Prec@1 86.000 (87.381) Prec@5 100.000 (99.000) +2022-11-14 16:27:30,234 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0788) Prec@1 91.000 (87.465) Prec@5 99.000 (99.000) +2022-11-14 16:27:30,257 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0787) Prec@1 89.000 (87.500) Prec@5 98.000 (98.977) +2022-11-14 16:27:30,277 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0418 (0.0779) Prec@1 92.000 (87.600) Prec@5 100.000 (99.000) +2022-11-14 16:27:30,296 Test: [45/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0778) Prec@1 89.000 (87.630) Prec@5 100.000 (99.022) +2022-11-14 16:27:30,317 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0709 (0.0776) Prec@1 89.000 (87.660) Prec@5 99.000 (99.021) +2022-11-14 16:27:30,337 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0916 (0.0779) Prec@1 85.000 (87.604) Prec@5 98.000 (99.000) +2022-11-14 16:27:30,356 Test: [48/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0491 (0.0773) Prec@1 91.000 (87.673) Prec@5 100.000 (99.020) +2022-11-14 16:27:30,379 Test: [49/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0775) Prec@1 85.000 (87.620) Prec@5 100.000 (99.040) +2022-11-14 16:27:30,402 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0774) Prec@1 88.000 (87.627) Prec@5 100.000 (99.059) +2022-11-14 16:27:30,426 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0860 (0.0776) Prec@1 85.000 (87.577) Prec@5 99.000 (99.058) +2022-11-14 16:27:30,445 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0775) Prec@1 87.000 (87.566) Prec@5 99.000 (99.057) +2022-11-14 16:27:30,466 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0772) Prec@1 91.000 (87.630) Prec@5 100.000 (99.074) +2022-11-14 16:27:30,482 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0773) Prec@1 88.000 (87.636) Prec@5 100.000 (99.091) +2022-11-14 16:27:30,501 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0781 (0.0774) Prec@1 88.000 (87.643) Prec@5 100.000 (99.107) +2022-11-14 16:27:30,522 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0806 (0.0774) Prec@1 88.000 (87.649) Prec@5 100.000 (99.123) +2022-11-14 16:27:30,542 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0677 (0.0772) Prec@1 92.000 (87.724) Prec@5 99.000 (99.121) +2022-11-14 16:27:30,564 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0929 (0.0775) Prec@1 81.000 (87.610) Prec@5 100.000 (99.136) +2022-11-14 16:27:30,593 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0773) Prec@1 90.000 (87.650) Prec@5 99.000 (99.133) +2022-11-14 16:27:30,623 Test: [60/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0774) Prec@1 86.000 (87.623) Prec@5 100.000 (99.148) +2022-11-14 16:27:30,654 Test: [61/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0775) Prec@1 85.000 (87.581) Prec@5 99.000 (99.145) +2022-11-14 16:27:30,686 Test: [62/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0773) Prec@1 90.000 (87.619) Prec@5 100.000 (99.159) +2022-11-14 16:27:30,716 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0355 (0.0766) Prec@1 96.000 (87.750) Prec@5 99.000 (99.156) +2022-11-14 16:27:30,744 Test: [64/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0768) Prec@1 87.000 (87.738) Prec@5 99.000 (99.154) +2022-11-14 16:27:30,772 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0768) Prec@1 90.000 (87.773) Prec@5 100.000 (99.167) +2022-11-14 16:27:30,801 Test: [66/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0766) Prec@1 89.000 (87.791) Prec@5 100.000 (99.179) +2022-11-14 16:27:30,830 Test: [67/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0766) Prec@1 89.000 (87.809) Prec@5 97.000 (99.147) +2022-11-14 16:27:30,858 Test: [68/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0767) Prec@1 85.000 (87.768) Prec@5 99.000 (99.145) +2022-11-14 16:27:30,885 Test: [69/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0767) Prec@1 87.000 (87.757) Prec@5 98.000 (99.129) +2022-11-14 16:27:30,911 Test: [70/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0768) Prec@1 87.000 (87.746) Prec@5 98.000 (99.113) +2022-11-14 16:27:30,937 Test: [71/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0545 (0.0765) Prec@1 92.000 (87.806) Prec@5 100.000 (99.125) +2022-11-14 16:27:30,963 Test: [72/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0379 (0.0760) Prec@1 95.000 (87.904) Prec@5 100.000 (99.137) +2022-11-14 16:27:30,988 Test: [73/100] Model Time 0.020 (0.009) Loss Time 0.000 (0.000) Loss 0.0368 (0.0754) Prec@1 93.000 (87.973) Prec@5 100.000 (99.149) +2022-11-14 16:27:31,007 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1008 (0.0758) Prec@1 86.000 (87.947) Prec@5 99.000 (99.147) +2022-11-14 16:27:31,024 Test: [75/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0757) Prec@1 90.000 (87.974) Prec@5 99.000 (99.145) +2022-11-14 16:27:31,040 Test: [76/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0684 (0.0756) Prec@1 90.000 (88.000) Prec@5 99.000 (99.143) +2022-11-14 16:27:31,059 Test: [77/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0759) Prec@1 84.000 (87.949) Prec@5 99.000 (99.141) +2022-11-14 16:27:31,080 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0760) Prec@1 87.000 (87.937) Prec@5 100.000 (99.152) +2022-11-14 16:27:31,096 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0761) Prec@1 88.000 (87.938) Prec@5 100.000 (99.162) +2022-11-14 16:27:31,116 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0762) Prec@1 88.000 (87.938) Prec@5 98.000 (99.148) +2022-11-14 16:27:31,135 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.0763) Prec@1 85.000 (87.902) Prec@5 100.000 (99.159) +2022-11-14 16:27:31,154 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0946 (0.0766) Prec@1 85.000 (87.867) Prec@5 100.000 (99.169) +2022-11-14 16:27:31,174 Test: [83/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0765) Prec@1 87.000 (87.857) Prec@5 100.000 (99.179) +2022-11-14 16:27:31,194 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0773 (0.0765) Prec@1 86.000 (87.835) Prec@5 100.000 (99.188) +2022-11-14 16:27:31,215 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1171 (0.0770) Prec@1 81.000 (87.756) Prec@5 99.000 (99.186) +2022-11-14 16:27:31,232 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0770) Prec@1 87.000 (87.747) Prec@5 100.000 (99.195) +2022-11-14 16:27:31,250 Test: [87/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0769) Prec@1 90.000 (87.773) Prec@5 98.000 (99.182) +2022-11-14 16:27:31,273 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0938 (0.0771) Prec@1 86.000 (87.753) Prec@5 98.000 (99.169) +2022-11-14 16:27:31,292 Test: [89/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0772) Prec@1 89.000 (87.767) Prec@5 98.000 (99.156) +2022-11-14 16:27:31,310 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0512 (0.0769) Prec@1 92.000 (87.813) Prec@5 100.000 (99.165) +2022-11-14 16:27:31,332 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0410 (0.0765) Prec@1 94.000 (87.880) Prec@5 100.000 (99.174) +2022-11-14 16:27:31,354 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0765) Prec@1 86.000 (87.860) Prec@5 100.000 (99.183) +2022-11-14 16:27:31,377 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0764) Prec@1 88.000 (87.862) Prec@5 98.000 (99.170) +2022-11-14 16:27:31,395 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0766) Prec@1 85.000 (87.832) Prec@5 99.000 (99.168) +2022-11-14 16:27:31,413 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0766) Prec@1 90.000 (87.854) Prec@5 100.000 (99.177) +2022-11-14 16:27:31,433 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0578 (0.0764) Prec@1 93.000 (87.907) Prec@5 99.000 (99.175) +2022-11-14 16:27:31,453 Test: [97/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0869 (0.0765) Prec@1 85.000 (87.878) Prec@5 97.000 (99.153) +2022-11-14 16:27:31,474 Test: [98/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0917 (0.0766) Prec@1 87.000 (87.869) Prec@5 98.000 (99.141) +2022-11-14 16:27:31,494 Test: [99/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0518 (0.0764) Prec@1 93.000 (87.920) Prec@5 100.000 (99.150) +2022-11-14 16:27:31,563 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:27:31,937 Epoch: [346][0/500] Time 0.034 (0.034) Data 0.267 (0.267) Loss 0.0478 (0.0478) Prec@1 92.000 (92.000) Prec@5 98.000 (98.000) +2022-11-14 16:27:32,244 Epoch: [346][10/500] Time 0.030 (0.028) Data 0.002 (0.026) Loss 0.0181 (0.0329) Prec@1 98.000 (95.000) Prec@5 99.000 (98.500) +2022-11-14 16:27:32,583 Epoch: [346][20/500] Time 0.030 (0.029) Data 0.002 (0.015) Loss 0.0160 (0.0273) Prec@1 96.000 (95.333) Prec@5 100.000 (99.000) +2022-11-14 16:27:33,231 Epoch: [346][30/500] Time 0.067 (0.038) Data 0.002 (0.011) Loss 0.0349 (0.0292) Prec@1 94.000 (95.000) Prec@5 100.000 (99.250) +2022-11-14 16:27:34,020 Epoch: [346][40/500] Time 0.075 (0.046) Data 0.002 (0.009) Loss 0.0152 (0.0264) Prec@1 98.000 (95.600) Prec@5 100.000 (99.400) +2022-11-14 16:27:34,806 Epoch: [346][50/500] Time 0.072 (0.051) Data 0.002 (0.007) Loss 0.0434 (0.0292) Prec@1 91.000 (94.833) Prec@5 100.000 (99.500) +2022-11-14 16:27:35,604 Epoch: [346][60/500] Time 0.076 (0.054) Data 0.002 (0.006) Loss 0.0354 (0.0301) Prec@1 94.000 (94.714) Prec@5 100.000 (99.571) +2022-11-14 16:27:36,384 Epoch: [346][70/500] Time 0.067 (0.056) Data 0.003 (0.006) Loss 0.0466 (0.0322) Prec@1 91.000 (94.250) Prec@5 100.000 (99.625) +2022-11-14 16:27:37,182 Epoch: [346][80/500] Time 0.065 (0.058) Data 0.002 (0.005) Loss 0.0205 (0.0309) Prec@1 96.000 (94.444) Prec@5 99.000 (99.556) +2022-11-14 16:27:37,944 Epoch: [346][90/500] Time 0.079 (0.059) Data 0.002 (0.005) Loss 0.0167 (0.0295) Prec@1 97.000 (94.700) Prec@5 100.000 (99.600) +2022-11-14 16:27:38,753 Epoch: [346][100/500] Time 0.083 (0.061) Data 0.002 (0.005) Loss 0.0204 (0.0286) Prec@1 96.000 (94.818) Prec@5 100.000 (99.636) +2022-11-14 16:27:39,550 Epoch: [346][110/500] Time 0.079 (0.062) Data 0.002 (0.004) Loss 0.0215 (0.0280) Prec@1 95.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 16:27:40,305 Epoch: [346][120/500] Time 0.070 (0.062) Data 0.002 (0.004) Loss 0.0410 (0.0290) Prec@1 94.000 (94.769) Prec@5 100.000 (99.692) +2022-11-14 16:27:41,094 Epoch: [346][130/500] Time 0.075 (0.063) Data 0.002 (0.004) Loss 0.0222 (0.0285) Prec@1 96.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:27:41,844 Epoch: [346][140/500] Time 0.061 (0.063) Data 0.002 (0.004) Loss 0.0054 (0.0270) Prec@1 100.000 (95.200) Prec@5 100.000 (99.733) +2022-11-14 16:27:42,590 Epoch: [346][150/500] Time 0.063 (0.063) Data 0.002 (0.004) Loss 0.0285 (0.0271) Prec@1 96.000 (95.250) Prec@5 99.000 (99.688) +2022-11-14 16:27:43,383 Epoch: [346][160/500] Time 0.079 (0.064) Data 0.002 (0.004) Loss 0.0268 (0.0271) Prec@1 94.000 (95.176) Prec@5 100.000 (99.706) +2022-11-14 16:27:44,189 Epoch: [346][170/500] Time 0.085 (0.064) Data 0.002 (0.004) Loss 0.0302 (0.0273) Prec@1 93.000 (95.056) Prec@5 100.000 (99.722) +2022-11-14 16:27:44,958 Epoch: [346][180/500] Time 0.069 (0.064) Data 0.002 (0.003) Loss 0.0318 (0.0275) Prec@1 96.000 (95.105) Prec@5 100.000 (99.737) +2022-11-14 16:27:45,728 Epoch: [346][190/500] Time 0.079 (0.065) Data 0.002 (0.003) Loss 0.0413 (0.0282) Prec@1 93.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:27:46,304 Epoch: [346][200/500] Time 0.042 (0.064) Data 0.002 (0.003) Loss 0.0291 (0.0282) Prec@1 96.000 (95.048) Prec@5 100.000 (99.762) +2022-11-14 16:27:46,717 Epoch: [346][210/500] Time 0.045 (0.063) Data 0.002 (0.003) Loss 0.0358 (0.0286) Prec@1 93.000 (94.955) Prec@5 99.000 (99.727) +2022-11-14 16:27:47,128 Epoch: [346][220/500] Time 0.043 (0.062) Data 0.002 (0.003) Loss 0.0243 (0.0284) Prec@1 97.000 (95.043) Prec@5 100.000 (99.739) +2022-11-14 16:27:47,558 Epoch: [346][230/500] Time 0.042 (0.061) Data 0.002 (0.003) Loss 0.0353 (0.0287) Prec@1 94.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:27:47,987 Epoch: [346][240/500] Time 0.048 (0.060) Data 0.002 (0.003) Loss 0.0173 (0.0282) Prec@1 98.000 (95.120) Prec@5 100.000 (99.760) +2022-11-14 16:27:48,413 Epoch: [346][250/500] Time 0.037 (0.059) Data 0.002 (0.003) Loss 0.0172 (0.0278) Prec@1 99.000 (95.269) Prec@5 100.000 (99.769) +2022-11-14 16:27:48,834 Epoch: [346][260/500] Time 0.036 (0.058) Data 0.002 (0.003) Loss 0.0374 (0.0282) Prec@1 95.000 (95.259) Prec@5 99.000 (99.741) +2022-11-14 16:27:49,252 Epoch: [346][270/500] Time 0.041 (0.057) Data 0.002 (0.003) Loss 0.0198 (0.0279) Prec@1 97.000 (95.321) Prec@5 100.000 (99.750) +2022-11-14 16:27:49,680 Epoch: [346][280/500] Time 0.036 (0.057) Data 0.002 (0.003) Loss 0.0378 (0.0282) Prec@1 92.000 (95.207) Prec@5 100.000 (99.759) +2022-11-14 16:27:50,095 Epoch: [346][290/500] Time 0.036 (0.056) Data 0.002 (0.003) Loss 0.0264 (0.0281) Prec@1 97.000 (95.267) Prec@5 99.000 (99.733) +2022-11-14 16:27:50,517 Epoch: [346][300/500] Time 0.043 (0.055) Data 0.002 (0.003) Loss 0.0307 (0.0282) Prec@1 94.000 (95.226) Prec@5 100.000 (99.742) +2022-11-14 16:27:50,935 Epoch: [346][310/500] Time 0.037 (0.055) Data 0.002 (0.003) Loss 0.0094 (0.0276) Prec@1 98.000 (95.312) Prec@5 100.000 (99.750) +2022-11-14 16:27:51,365 Epoch: [346][320/500] Time 0.038 (0.054) Data 0.002 (0.003) Loss 0.0298 (0.0277) Prec@1 94.000 (95.273) Prec@5 100.000 (99.758) +2022-11-14 16:27:51,809 Epoch: [346][330/500] Time 0.037 (0.054) Data 0.002 (0.003) Loss 0.0147 (0.0273) Prec@1 98.000 (95.353) Prec@5 100.000 (99.765) +2022-11-14 16:27:52,234 Epoch: [346][340/500] Time 0.044 (0.053) Data 0.002 (0.003) Loss 0.0479 (0.0279) Prec@1 90.000 (95.200) Prec@5 100.000 (99.771) +2022-11-14 16:27:52,656 Epoch: [346][350/500] Time 0.040 (0.053) Data 0.002 (0.003) Loss 0.0460 (0.0284) Prec@1 92.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:27:53,091 Epoch: [346][360/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0386 (0.0287) Prec@1 95.000 (95.108) Prec@5 100.000 (99.784) +2022-11-14 16:27:53,525 Epoch: [346][370/500] Time 0.036 (0.052) Data 0.002 (0.003) Loss 0.0235 (0.0286) Prec@1 95.000 (95.105) Prec@5 100.000 (99.789) +2022-11-14 16:27:53,955 Epoch: [346][380/500] Time 0.033 (0.052) Data 0.002 (0.003) Loss 0.0161 (0.0282) Prec@1 97.000 (95.154) Prec@5 100.000 (99.795) +2022-11-14 16:27:54,393 Epoch: [346][390/500] Time 0.043 (0.051) Data 0.002 (0.003) Loss 0.0333 (0.0284) Prec@1 92.000 (95.075) Prec@5 100.000 (99.800) +2022-11-14 16:27:54,815 Epoch: [346][400/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.0268 (0.0283) Prec@1 97.000 (95.122) Prec@5 100.000 (99.805) +2022-11-14 16:27:55,231 Epoch: [346][410/500] Time 0.032 (0.051) Data 0.002 (0.003) Loss 0.0345 (0.0285) Prec@1 95.000 (95.119) Prec@5 99.000 (99.786) +2022-11-14 16:27:55,665 Epoch: [346][420/500] Time 0.040 (0.050) Data 0.002 (0.003) Loss 0.0243 (0.0284) Prec@1 96.000 (95.140) Prec@5 100.000 (99.791) +2022-11-14 16:27:56,095 Epoch: [346][430/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0192 (0.0282) Prec@1 96.000 (95.159) Prec@5 100.000 (99.795) +2022-11-14 16:27:56,523 Epoch: [346][440/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0454 (0.0285) Prec@1 91.000 (95.067) Prec@5 100.000 (99.800) +2022-11-14 16:27:56,947 Epoch: [346][450/500] Time 0.039 (0.050) Data 0.002 (0.003) Loss 0.0268 (0.0285) Prec@1 95.000 (95.065) Prec@5 100.000 (99.804) +2022-11-14 16:27:57,389 Epoch: [346][460/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0482 (0.0289) Prec@1 90.000 (94.957) Prec@5 100.000 (99.809) +2022-11-14 16:27:57,822 Epoch: [346][470/500] Time 0.034 (0.049) Data 0.002 (0.003) Loss 0.0545 (0.0295) Prec@1 89.000 (94.833) Prec@5 99.000 (99.792) +2022-11-14 16:27:58,256 Epoch: [346][480/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0305 (0.0295) Prec@1 97.000 (94.878) Prec@5 100.000 (99.796) +2022-11-14 16:27:58,701 Epoch: [346][490/500] Time 0.041 (0.049) Data 0.002 (0.003) Loss 0.0290 (0.0295) Prec@1 94.000 (94.860) Prec@5 100.000 (99.800) +2022-11-14 16:27:59,091 Epoch: [346][499/500] Time 0.040 (0.049) Data 0.002 (0.003) Loss 0.0386 (0.0296) Prec@1 94.000 (94.843) Prec@5 100.000 (99.804) +2022-11-14 16:27:59,436 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0622 (0.0622) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:27:59,446 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0620) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:27:59,458 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0619) Prec@1 92.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 16:27:59,469 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0628) Prec@1 91.000 (90.500) Prec@5 99.000 (99.750) +2022-11-14 16:27:59,478 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0652) Prec@1 90.000 (90.400) Prec@5 99.000 (99.600) +2022-11-14 16:27:59,488 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0334 (0.0599) Prec@1 93.000 (90.833) Prec@5 100.000 (99.667) +2022-11-14 16:27:59,499 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0594) Prec@1 91.000 (90.857) Prec@5 100.000 (99.714) +2022-11-14 16:27:59,511 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0626) Prec@1 85.000 (90.125) Prec@5 99.000 (99.625) +2022-11-14 16:27:59,520 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0644) Prec@1 87.000 (89.778) Prec@5 100.000 (99.667) +2022-11-14 16:27:59,532 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0657) Prec@1 89.000 (89.700) Prec@5 99.000 (99.600) +2022-11-14 16:27:59,546 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0653) Prec@1 89.000 (89.636) Prec@5 100.000 (99.636) +2022-11-14 16:27:59,561 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0676) Prec@1 85.000 (89.250) Prec@5 99.000 (99.583) +2022-11-14 16:27:59,573 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0674) Prec@1 88.000 (89.154) Prec@5 100.000 (99.615) +2022-11-14 16:27:59,586 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0676) Prec@1 88.000 (89.071) Prec@5 100.000 (99.643) +2022-11-14 16:27:59,600 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0680) Prec@1 88.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 16:27:59,614 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0677) Prec@1 90.000 (89.062) Prec@5 100.000 (99.625) +2022-11-14 16:27:59,628 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0672) Prec@1 92.000 (89.235) Prec@5 99.000 (99.588) +2022-11-14 16:27:59,640 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1057 (0.0694) Prec@1 83.000 (88.889) Prec@5 100.000 (99.611) +2022-11-14 16:27:59,656 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0709) Prec@1 84.000 (88.632) Prec@5 99.000 (99.579) +2022-11-14 16:27:59,671 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0721) Prec@1 86.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 16:27:59,685 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0722) Prec@1 86.000 (88.381) Prec@5 100.000 (99.524) +2022-11-14 16:27:59,699 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0727) Prec@1 89.000 (88.409) Prec@5 98.000 (99.455) +2022-11-14 16:27:59,713 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0740) Prec@1 84.000 (88.217) Prec@5 99.000 (99.435) +2022-11-14 16:27:59,726 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0742) Prec@1 86.000 (88.125) Prec@5 100.000 (99.458) +2022-11-14 16:27:59,741 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0738) Prec@1 91.000 (88.240) Prec@5 100.000 (99.480) +2022-11-14 16:27:59,757 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1113 (0.0753) Prec@1 82.000 (88.000) Prec@5 97.000 (99.385) +2022-11-14 16:27:59,770 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0750) Prec@1 89.000 (88.037) Prec@5 100.000 (99.407) +2022-11-14 16:27:59,784 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0748) Prec@1 91.000 (88.143) Prec@5 99.000 (99.393) +2022-11-14 16:27:59,798 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0749) Prec@1 88.000 (88.138) Prec@5 98.000 (99.345) +2022-11-14 16:27:59,814 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0745) Prec@1 88.000 (88.133) Prec@5 100.000 (99.367) +2022-11-14 16:27:59,830 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0743) Prec@1 88.000 (88.129) Prec@5 100.000 (99.387) +2022-11-14 16:27:59,843 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0741) Prec@1 91.000 (88.219) Prec@5 99.000 (99.375) +2022-11-14 16:27:59,857 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0738) Prec@1 89.000 (88.242) Prec@5 100.000 (99.394) +2022-11-14 16:27:59,871 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0743) Prec@1 84.000 (88.118) Prec@5 99.000 (99.382) +2022-11-14 16:27:59,885 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0744) Prec@1 88.000 (88.114) Prec@5 99.000 (99.371) +2022-11-14 16:27:59,900 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0740) Prec@1 90.000 (88.167) Prec@5 99.000 (99.361) +2022-11-14 16:27:59,912 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0738) Prec@1 89.000 (88.189) Prec@5 98.000 (99.324) +2022-11-14 16:27:59,926 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0745) Prec@1 84.000 (88.079) Prec@5 98.000 (99.289) +2022-11-14 16:27:59,938 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0463 (0.0737) Prec@1 94.000 (88.231) Prec@5 99.000 (99.282) +2022-11-14 16:27:59,955 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0738) Prec@1 87.000 (88.200) Prec@5 99.000 (99.275) +2022-11-14 16:27:59,968 Test: [40/100] Model Time 0.011 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0741) Prec@1 88.000 (88.195) Prec@5 98.000 (99.244) +2022-11-14 16:27:59,981 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0740) Prec@1 89.000 (88.214) Prec@5 99.000 (99.238) +2022-11-14 16:27:59,997 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0738) Prec@1 89.000 (88.233) Prec@5 98.000 (99.209) +2022-11-14 16:28:00,012 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0736) Prec@1 91.000 (88.295) Prec@5 99.000 (99.205) +2022-11-14 16:28:00,029 Test: [44/100] Model Time 0.012 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0733) Prec@1 90.000 (88.333) Prec@5 99.000 (99.200) +2022-11-14 16:28:00,046 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0738) Prec@1 84.000 (88.239) Prec@5 99.000 (99.196) +2022-11-14 16:28:00,059 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0739) Prec@1 88.000 (88.234) Prec@5 100.000 (99.213) +2022-11-14 16:28:00,074 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0742) Prec@1 86.000 (88.188) Prec@5 98.000 (99.188) +2022-11-14 16:28:00,089 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0741) Prec@1 88.000 (88.184) Prec@5 100.000 (99.204) +2022-11-14 16:28:00,104 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0743) Prec@1 87.000 (88.160) Prec@5 99.000 (99.200) +2022-11-14 16:28:00,121 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0741) Prec@1 88.000 (88.157) Prec@5 99.000 (99.196) +2022-11-14 16:28:00,134 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0740) Prec@1 88.000 (88.154) Prec@5 99.000 (99.192) +2022-11-14 16:28:00,148 Test: [52/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0356 (0.0732) Prec@1 95.000 (88.283) Prec@5 100.000 (99.208) +2022-11-14 16:28:00,163 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0733) Prec@1 86.000 (88.241) Prec@5 100.000 (99.222) +2022-11-14 16:28:00,179 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0732) Prec@1 89.000 (88.255) Prec@5 100.000 (99.236) +2022-11-14 16:28:00,197 Test: [55/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0731) Prec@1 88.000 (88.250) Prec@5 99.000 (99.232) +2022-11-14 16:28:00,213 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0729) Prec@1 88.000 (88.246) Prec@5 99.000 (99.228) +2022-11-14 16:28:00,229 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0730) Prec@1 87.000 (88.224) Prec@5 100.000 (99.241) +2022-11-14 16:28:00,245 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0732) Prec@1 85.000 (88.169) Prec@5 99.000 (99.237) +2022-11-14 16:28:00,259 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0732) Prec@1 86.000 (88.133) Prec@5 99.000 (99.233) +2022-11-14 16:28:00,272 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0730) Prec@1 90.000 (88.164) Prec@5 99.000 (99.230) +2022-11-14 16:28:00,284 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0728) Prec@1 89.000 (88.177) Prec@5 100.000 (99.242) +2022-11-14 16:28:00,300 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0725) Prec@1 91.000 (88.222) Prec@5 100.000 (99.254) +2022-11-14 16:28:00,317 Test: [63/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0721) Prec@1 91.000 (88.266) Prec@5 100.000 (99.266) +2022-11-14 16:28:00,331 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0723) Prec@1 89.000 (88.277) Prec@5 99.000 (99.262) +2022-11-14 16:28:00,344 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0724) Prec@1 86.000 (88.242) Prec@5 100.000 (99.273) +2022-11-14 16:28:00,357 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0429 (0.0720) Prec@1 91.000 (88.284) Prec@5 100.000 (99.284) +2022-11-14 16:28:00,371 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0721) Prec@1 90.000 (88.309) Prec@5 96.000 (99.235) +2022-11-14 16:28:00,386 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0719) Prec@1 90.000 (88.333) Prec@5 98.000 (99.217) +2022-11-14 16:28:00,399 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0719) Prec@1 88.000 (88.329) Prec@5 100.000 (99.229) +2022-11-14 16:28:00,413 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0721) Prec@1 87.000 (88.310) Prec@5 100.000 (99.239) +2022-11-14 16:28:00,430 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0717) Prec@1 91.000 (88.347) Prec@5 100.000 (99.250) +2022-11-14 16:28:00,445 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0713) Prec@1 93.000 (88.411) Prec@5 100.000 (99.260) +2022-11-14 16:28:00,461 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0709) Prec@1 94.000 (88.486) Prec@5 100.000 (99.270) +2022-11-14 16:28:00,476 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1263 (0.0716) Prec@1 83.000 (88.413) Prec@5 98.000 (99.253) +2022-11-14 16:28:00,489 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0715) Prec@1 90.000 (88.434) Prec@5 99.000 (99.250) +2022-11-14 16:28:00,504 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0716) Prec@1 88.000 (88.429) Prec@5 100.000 (99.260) +2022-11-14 16:28:00,521 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1031 (0.0720) Prec@1 83.000 (88.359) Prec@5 98.000 (99.244) +2022-11-14 16:28:00,535 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0722) Prec@1 86.000 (88.329) Prec@5 100.000 (99.253) +2022-11-14 16:28:00,550 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0721) Prec@1 90.000 (88.350) Prec@5 100.000 (99.263) +2022-11-14 16:28:00,566 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0722) Prec@1 88.000 (88.346) Prec@5 99.000 (99.259) +2022-11-14 16:28:00,580 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0725) Prec@1 85.000 (88.305) Prec@5 99.000 (99.256) +2022-11-14 16:28:00,593 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0726) Prec@1 87.000 (88.289) Prec@5 100.000 (99.265) +2022-11-14 16:28:00,607 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0723) Prec@1 92.000 (88.333) Prec@5 100.000 (99.274) +2022-11-14 16:28:00,622 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0724) Prec@1 87.000 (88.318) Prec@5 99.000 (99.271) +2022-11-14 16:28:00,635 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0725) Prec@1 89.000 (88.326) Prec@5 99.000 (99.267) +2022-11-14 16:28:00,651 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0726) Prec@1 88.000 (88.322) Prec@5 100.000 (99.276) +2022-11-14 16:28:00,667 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0726) Prec@1 88.000 (88.318) Prec@5 98.000 (99.261) +2022-11-14 16:28:00,681 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0725) Prec@1 87.000 (88.303) Prec@5 99.000 (99.258) +2022-11-14 16:28:00,695 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0724) Prec@1 91.000 (88.333) Prec@5 99.000 (99.256) +2022-11-14 16:28:00,711 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0724) Prec@1 88.000 (88.330) Prec@5 100.000 (99.264) +2022-11-14 16:28:00,729 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0722) Prec@1 93.000 (88.380) Prec@5 100.000 (99.272) +2022-11-14 16:28:00,744 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0723) Prec@1 86.000 (88.355) Prec@5 100.000 (99.280) +2022-11-14 16:28:00,758 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0724) Prec@1 89.000 (88.362) Prec@5 100.000 (99.287) +2022-11-14 16:28:00,773 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0725) Prec@1 87.000 (88.347) Prec@5 100.000 (99.295) +2022-11-14 16:28:00,785 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0725) Prec@1 89.000 (88.354) Prec@5 99.000 (99.292) +2022-11-14 16:28:00,800 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0723) Prec@1 93.000 (88.402) Prec@5 99.000 (99.289) +2022-11-14 16:28:00,816 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0725) Prec@1 87.000 (88.388) Prec@5 99.000 (99.286) +2022-11-14 16:28:00,830 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1043 (0.0728) Prec@1 85.000 (88.354) Prec@5 96.000 (99.253) +2022-11-14 16:28:00,843 Test: [99/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0728) Prec@1 89.000 (88.360) Prec@5 98.000 (99.240) +2022-11-14 16:28:00,908 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:28:01,258 Epoch: [347][0/500] Time 0.023 (0.023) Data 0.262 (0.262) Loss 0.0201 (0.0201) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:28:01,647 Epoch: [347][10/500] Time 0.041 (0.033) Data 0.002 (0.026) Loss 0.0151 (0.0176) Prec@1 97.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:28:02,066 Epoch: [347][20/500] Time 0.041 (0.035) Data 0.002 (0.014) Loss 0.0406 (0.0252) Prec@1 93.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:28:02,499 Epoch: [347][30/500] Time 0.038 (0.036) Data 0.002 (0.010) Loss 0.0315 (0.0268) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:28:02,925 Epoch: [347][40/500] Time 0.043 (0.037) Data 0.002 (0.008) Loss 0.0303 (0.0275) Prec@1 96.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:28:03,357 Epoch: [347][50/500] Time 0.045 (0.037) Data 0.002 (0.007) Loss 0.0116 (0.0248) Prec@1 99.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:28:03,769 Epoch: [347][60/500] Time 0.040 (0.037) Data 0.002 (0.006) Loss 0.0297 (0.0255) Prec@1 95.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 16:28:04,210 Epoch: [347][70/500] Time 0.040 (0.037) Data 0.002 (0.006) Loss 0.0379 (0.0271) Prec@1 93.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 16:28:04,641 Epoch: [347][80/500] Time 0.045 (0.038) Data 0.002 (0.005) Loss 0.0319 (0.0276) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:28:05,079 Epoch: [347][90/500] Time 0.054 (0.038) Data 0.002 (0.005) Loss 0.0290 (0.0278) Prec@1 94.000 (95.200) Prec@5 98.000 (99.800) +2022-11-14 16:28:05,505 Epoch: [347][100/500] Time 0.044 (0.038) Data 0.002 (0.005) Loss 0.0358 (0.0285) Prec@1 95.000 (95.182) Prec@5 99.000 (99.727) +2022-11-14 16:28:05,937 Epoch: [347][110/500] Time 0.040 (0.038) Data 0.002 (0.004) Loss 0.0297 (0.0286) Prec@1 94.000 (95.083) Prec@5 100.000 (99.750) +2022-11-14 16:28:06,566 Epoch: [347][120/500] Time 0.075 (0.039) Data 0.002 (0.004) Loss 0.0270 (0.0285) Prec@1 96.000 (95.154) Prec@5 100.000 (99.769) +2022-11-14 16:28:07,319 Epoch: [347][130/500] Time 0.079 (0.041) Data 0.002 (0.004) Loss 0.0275 (0.0284) Prec@1 95.000 (95.143) Prec@5 100.000 (99.786) +2022-11-14 16:28:08,037 Epoch: [347][140/500] Time 0.077 (0.043) Data 0.002 (0.004) Loss 0.0221 (0.0280) Prec@1 95.000 (95.133) Prec@5 100.000 (99.800) +2022-11-14 16:28:08,747 Epoch: [347][150/500] Time 0.065 (0.044) Data 0.002 (0.004) Loss 0.0193 (0.0274) Prec@1 97.000 (95.250) Prec@5 100.000 (99.812) +2022-11-14 16:28:09,534 Epoch: [347][160/500] Time 0.076 (0.046) Data 0.002 (0.004) Loss 0.0345 (0.0279) Prec@1 92.000 (95.059) Prec@5 100.000 (99.824) +2022-11-14 16:28:10,322 Epoch: [347][170/500] Time 0.079 (0.048) Data 0.002 (0.003) Loss 0.0140 (0.0271) Prec@1 98.000 (95.222) Prec@5 100.000 (99.833) +2022-11-14 16:28:11,100 Epoch: [347][180/500] Time 0.082 (0.049) Data 0.003 (0.003) Loss 0.0282 (0.0271) Prec@1 96.000 (95.263) Prec@5 100.000 (99.842) +2022-11-14 16:28:11,912 Epoch: [347][190/500] Time 0.074 (0.050) Data 0.002 (0.003) Loss 0.0258 (0.0271) Prec@1 96.000 (95.300) Prec@5 100.000 (99.850) +2022-11-14 16:28:12,698 Epoch: [347][200/500] Time 0.068 (0.051) Data 0.002 (0.003) Loss 0.0467 (0.0280) Prec@1 92.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:28:13,460 Epoch: [347][210/500] Time 0.064 (0.052) Data 0.002 (0.003) Loss 0.0304 (0.0281) Prec@1 95.000 (95.136) Prec@5 99.000 (99.818) +2022-11-14 16:28:14,221 Epoch: [347][220/500] Time 0.068 (0.053) Data 0.002 (0.003) Loss 0.0352 (0.0284) Prec@1 95.000 (95.130) Prec@5 100.000 (99.826) +2022-11-14 16:28:15,014 Epoch: [347][230/500] Time 0.075 (0.053) Data 0.002 (0.003) Loss 0.0344 (0.0287) Prec@1 95.000 (95.125) Prec@5 100.000 (99.833) +2022-11-14 16:28:15,782 Epoch: [347][240/500] Time 0.072 (0.054) Data 0.002 (0.003) Loss 0.0499 (0.0295) Prec@1 90.000 (94.920) Prec@5 100.000 (99.840) +2022-11-14 16:28:16,615 Epoch: [347][250/500] Time 0.070 (0.055) Data 0.002 (0.003) Loss 0.0323 (0.0296) Prec@1 95.000 (94.923) Prec@5 100.000 (99.846) +2022-11-14 16:28:17,421 Epoch: [347][260/500] Time 0.081 (0.055) Data 0.002 (0.003) Loss 0.0352 (0.0298) Prec@1 93.000 (94.852) Prec@5 99.000 (99.815) +2022-11-14 16:28:18,216 Epoch: [347][270/500] Time 0.063 (0.056) Data 0.002 (0.003) Loss 0.0134 (0.0293) Prec@1 98.000 (94.964) Prec@5 100.000 (99.821) +2022-11-14 16:28:19,038 Epoch: [347][280/500] Time 0.083 (0.057) Data 0.002 (0.003) Loss 0.0264 (0.0292) Prec@1 98.000 (95.069) Prec@5 100.000 (99.828) +2022-11-14 16:28:19,864 Epoch: [347][290/500] Time 0.065 (0.057) Data 0.002 (0.003) Loss 0.0405 (0.0295) Prec@1 93.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:28:20,670 Epoch: [347][300/500] Time 0.085 (0.058) Data 0.002 (0.003) Loss 0.0255 (0.0294) Prec@1 96.000 (95.032) Prec@5 99.000 (99.806) +2022-11-14 16:28:21,516 Epoch: [347][310/500] Time 0.054 (0.058) Data 0.002 (0.003) Loss 0.0352 (0.0296) Prec@1 95.000 (95.031) Prec@5 99.000 (99.781) +2022-11-14 16:28:21,933 Epoch: [347][320/500] Time 0.040 (0.058) Data 0.002 (0.003) Loss 0.0238 (0.0294) Prec@1 96.000 (95.061) Prec@5 100.000 (99.788) +2022-11-14 16:28:22,356 Epoch: [347][330/500] Time 0.036 (0.057) Data 0.002 (0.003) Loss 0.0181 (0.0291) Prec@1 98.000 (95.147) Prec@5 99.000 (99.765) +2022-11-14 16:28:22,834 Epoch: [347][340/500] Time 0.035 (0.057) Data 0.002 (0.003) Loss 0.0263 (0.0290) Prec@1 97.000 (95.200) Prec@5 100.000 (99.771) +2022-11-14 16:28:23,263 Epoch: [347][350/500] Time 0.038 (0.056) Data 0.003 (0.003) Loss 0.0560 (0.0297) Prec@1 89.000 (95.028) Prec@5 100.000 (99.778) +2022-11-14 16:28:23,715 Epoch: [347][360/500] Time 0.031 (0.056) Data 0.002 (0.003) Loss 0.0408 (0.0300) Prec@1 94.000 (95.000) Prec@5 100.000 (99.784) +2022-11-14 16:28:24,140 Epoch: [347][370/500] Time 0.044 (0.055) Data 0.002 (0.003) Loss 0.0323 (0.0301) Prec@1 96.000 (95.026) Prec@5 100.000 (99.789) +2022-11-14 16:28:24,558 Epoch: [347][380/500] Time 0.044 (0.055) Data 0.003 (0.003) Loss 0.0203 (0.0299) Prec@1 97.000 (95.077) Prec@5 100.000 (99.795) +2022-11-14 16:28:24,986 Epoch: [347][390/500] Time 0.047 (0.054) Data 0.002 (0.003) Loss 0.0406 (0.0301) Prec@1 91.000 (94.975) Prec@5 100.000 (99.800) +2022-11-14 16:28:25,410 Epoch: [347][400/500] Time 0.033 (0.054) Data 0.002 (0.003) Loss 0.0093 (0.0296) Prec@1 99.000 (95.073) Prec@5 100.000 (99.805) +2022-11-14 16:28:25,843 Epoch: [347][410/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0266 (0.0295) Prec@1 97.000 (95.119) Prec@5 100.000 (99.810) +2022-11-14 16:28:26,322 Epoch: [347][420/500] Time 0.030 (0.053) Data 0.002 (0.003) Loss 0.0365 (0.0297) Prec@1 93.000 (95.070) Prec@5 99.000 (99.791) +2022-11-14 16:28:26,756 Epoch: [347][430/500] Time 0.042 (0.053) Data 0.002 (0.003) Loss 0.0326 (0.0298) Prec@1 94.000 (95.045) Prec@5 100.000 (99.795) +2022-11-14 16:28:27,254 Epoch: [347][440/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0398 (0.0300) Prec@1 95.000 (95.044) Prec@5 100.000 (99.800) +2022-11-14 16:28:27,753 Epoch: [347][450/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0387 (0.0302) Prec@1 93.000 (95.000) Prec@5 100.000 (99.804) +2022-11-14 16:28:28,173 Epoch: [347][460/500] Time 0.040 (0.052) Data 0.002 (0.003) Loss 0.0322 (0.0302) Prec@1 94.000 (94.979) Prec@5 100.000 (99.809) +2022-11-14 16:28:28,590 Epoch: [347][470/500] Time 0.037 (0.052) Data 0.002 (0.003) Loss 0.0627 (0.0309) Prec@1 88.000 (94.833) Prec@5 99.000 (99.792) +2022-11-14 16:28:29,126 Epoch: [347][480/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0334 (0.0310) Prec@1 94.000 (94.816) Prec@5 100.000 (99.796) +2022-11-14 16:28:29,553 Epoch: [347][490/500] Time 0.047 (0.052) Data 0.002 (0.003) Loss 0.0327 (0.0310) Prec@1 95.000 (94.820) Prec@5 99.000 (99.780) +2022-11-14 16:28:29,939 Epoch: [347][499/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.0222 (0.0308) Prec@1 97.000 (94.863) Prec@5 100.000 (99.784) +2022-11-14 16:28:30,288 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0417 (0.0417) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:28:30,299 Test: [1/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0667 (0.0542) Prec@1 90.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:28:30,309 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0671 (0.0585) Prec@1 88.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 16:28:30,321 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0787 (0.0635) Prec@1 88.000 (89.750) Prec@5 99.000 (99.750) +2022-11-14 16:28:30,336 Test: [4/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0846 (0.0677) Prec@1 86.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 16:28:30,354 Test: [5/100] Model Time 0.016 (0.011) Loss Time 0.000 (0.000) Loss 0.0478 (0.0644) Prec@1 92.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 16:28:30,370 Test: [6/100] Model Time 0.014 (0.012) Loss Time 0.000 (0.000) Loss 0.0721 (0.0655) Prec@1 90.000 (89.571) Prec@5 100.000 (99.714) +2022-11-14 16:28:30,382 Test: [7/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0866 (0.0682) Prec@1 88.000 (89.375) Prec@5 99.000 (99.625) +2022-11-14 16:28:30,394 Test: [8/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0785 (0.0693) Prec@1 87.000 (89.111) Prec@5 98.000 (99.444) +2022-11-14 16:28:30,405 Test: [9/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0892 (0.0713) Prec@1 85.000 (88.700) Prec@5 98.000 (99.300) +2022-11-14 16:28:30,416 Test: [10/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0613 (0.0704) Prec@1 89.000 (88.727) Prec@5 100.000 (99.364) +2022-11-14 16:28:30,428 Test: [11/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0727 (0.0706) Prec@1 87.000 (88.583) Prec@5 100.000 (99.417) +2022-11-14 16:28:30,439 Test: [12/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0470 (0.0688) Prec@1 90.000 (88.692) Prec@5 100.000 (99.462) +2022-11-14 16:28:30,453 Test: [13/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0790 (0.0695) Prec@1 89.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 16:28:30,467 Test: [14/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0921 (0.0710) Prec@1 83.000 (88.333) Prec@5 100.000 (99.467) +2022-11-14 16:28:30,481 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0782 (0.0714) Prec@1 89.000 (88.375) Prec@5 99.000 (99.438) +2022-11-14 16:28:30,494 Test: [16/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0313 (0.0691) Prec@1 95.000 (88.765) Prec@5 99.000 (99.412) +2022-11-14 16:28:30,506 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1149 (0.0716) Prec@1 82.000 (88.389) Prec@5 98.000 (99.333) +2022-11-14 16:28:30,520 Test: [18/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0883 (0.0725) Prec@1 85.000 (88.211) Prec@5 98.000 (99.263) +2022-11-14 16:28:30,534 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0727) Prec@1 92.000 (88.400) Prec@5 97.000 (99.150) +2022-11-14 16:28:30,549 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0733) Prec@1 86.000 (88.286) Prec@5 99.000 (99.143) +2022-11-14 16:28:30,565 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0728) Prec@1 90.000 (88.364) Prec@5 99.000 (99.136) +2022-11-14 16:28:30,579 Test: [22/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0915 (0.0736) Prec@1 87.000 (88.304) Prec@5 98.000 (99.087) +2022-11-14 16:28:30,593 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0736) Prec@1 88.000 (88.292) Prec@5 100.000 (99.125) +2022-11-14 16:28:30,607 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0972 (0.0745) Prec@1 84.000 (88.120) Prec@5 100.000 (99.160) +2022-11-14 16:28:30,621 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1194 (0.0763) Prec@1 80.000 (87.808) Prec@5 97.000 (99.077) +2022-11-14 16:28:30,636 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0757) Prec@1 91.000 (87.926) Prec@5 100.000 (99.111) +2022-11-14 16:28:30,650 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0615 (0.0752) Prec@1 88.000 (87.929) Prec@5 100.000 (99.143) +2022-11-14 16:28:30,664 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0748) Prec@1 88.000 (87.931) Prec@5 99.000 (99.138) +2022-11-14 16:28:30,680 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0747) Prec@1 86.000 (87.867) Prec@5 98.000 (99.100) +2022-11-14 16:28:30,695 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0747) Prec@1 88.000 (87.871) Prec@5 99.000 (99.097) +2022-11-14 16:28:30,710 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0748) Prec@1 87.000 (87.844) Prec@5 100.000 (99.125) +2022-11-14 16:28:30,725 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0748) Prec@1 86.000 (87.788) Prec@5 100.000 (99.152) +2022-11-14 16:28:30,738 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.0752) Prec@1 86.000 (87.735) Prec@5 100.000 (99.176) +2022-11-14 16:28:30,752 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0753) Prec@1 88.000 (87.743) Prec@5 99.000 (99.171) +2022-11-14 16:28:30,766 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0752) Prec@1 90.000 (87.806) Prec@5 99.000 (99.167) +2022-11-14 16:28:30,782 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0751) Prec@1 88.000 (87.811) Prec@5 99.000 (99.162) +2022-11-14 16:28:30,797 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0756) Prec@1 85.000 (87.737) Prec@5 99.000 (99.158) +2022-11-14 16:28:30,812 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0755) Prec@1 90.000 (87.795) Prec@5 99.000 (99.154) +2022-11-14 16:28:30,828 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0750) Prec@1 89.000 (87.825) Prec@5 98.000 (99.125) +2022-11-14 16:28:30,844 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0753) Prec@1 86.000 (87.780) Prec@5 99.000 (99.122) +2022-11-14 16:28:30,857 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0751) Prec@1 90.000 (87.833) Prec@5 100.000 (99.143) +2022-11-14 16:28:30,872 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0748) Prec@1 91.000 (87.907) Prec@5 99.000 (99.140) +2022-11-14 16:28:30,885 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0748) Prec@1 91.000 (87.977) Prec@5 99.000 (99.136) +2022-11-14 16:28:30,899 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0745) Prec@1 91.000 (88.044) Prec@5 99.000 (99.133) +2022-11-14 16:28:30,914 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1119 (0.0753) Prec@1 82.000 (87.913) Prec@5 98.000 (99.109) +2022-11-14 16:28:30,929 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0750) Prec@1 89.000 (87.936) Prec@5 100.000 (99.128) +2022-11-14 16:28:30,943 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1160 (0.0759) Prec@1 81.000 (87.792) Prec@5 99.000 (99.125) +2022-11-14 16:28:30,960 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0611 (0.0756) Prec@1 91.000 (87.857) Prec@5 100.000 (99.143) +2022-11-14 16:28:30,976 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0762) Prec@1 84.000 (87.780) Prec@5 100.000 (99.160) +2022-11-14 16:28:30,990 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0762) Prec@1 87.000 (87.765) Prec@5 99.000 (99.157) +2022-11-14 16:28:31,002 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0763) Prec@1 86.000 (87.731) Prec@5 100.000 (99.173) +2022-11-14 16:28:31,017 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0761) Prec@1 88.000 (87.736) Prec@5 99.000 (99.170) +2022-11-14 16:28:31,031 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0760) Prec@1 88.000 (87.741) Prec@5 99.000 (99.167) +2022-11-14 16:28:31,045 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0759) Prec@1 87.000 (87.727) Prec@5 100.000 (99.182) +2022-11-14 16:28:31,059 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0759) Prec@1 89.000 (87.750) Prec@5 99.000 (99.179) +2022-11-14 16:28:31,074 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0761) Prec@1 86.000 (87.719) Prec@5 99.000 (99.175) +2022-11-14 16:28:31,089 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0761) Prec@1 88.000 (87.724) Prec@5 99.000 (99.172) +2022-11-14 16:28:31,106 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0760) Prec@1 87.000 (87.712) Prec@5 100.000 (99.186) +2022-11-14 16:28:31,122 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0759) Prec@1 89.000 (87.733) Prec@5 100.000 (99.200) +2022-11-14 16:28:31,136 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0762) Prec@1 87.000 (87.721) Prec@5 98.000 (99.180) +2022-11-14 16:28:31,149 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0764) Prec@1 85.000 (87.677) Prec@5 100.000 (99.194) +2022-11-14 16:28:31,168 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0763) Prec@1 89.000 (87.698) Prec@5 99.000 (99.190) +2022-11-14 16:28:31,190 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0345 (0.0757) Prec@1 94.000 (87.797) Prec@5 100.000 (99.203) +2022-11-14 16:28:31,213 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1044 (0.0761) Prec@1 82.000 (87.708) Prec@5 99.000 (99.200) +2022-11-14 16:28:31,232 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0762) Prec@1 85.000 (87.667) Prec@5 99.000 (99.197) +2022-11-14 16:28:31,252 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0758) Prec@1 90.000 (87.701) Prec@5 100.000 (99.209) +2022-11-14 16:28:31,273 Test: [67/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0758) Prec@1 89.000 (87.721) Prec@5 99.000 (99.206) +2022-11-14 16:28:31,295 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0759) Prec@1 88.000 (87.725) Prec@5 99.000 (99.203) +2022-11-14 16:28:31,315 Test: [69/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0758) Prec@1 91.000 (87.771) Prec@5 99.000 (99.200) +2022-11-14 16:28:31,336 Test: [70/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0761) Prec@1 87.000 (87.761) Prec@5 99.000 (99.197) +2022-11-14 16:28:31,357 Test: [71/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0757) Prec@1 94.000 (87.847) Prec@5 100.000 (99.208) +2022-11-14 16:28:31,377 Test: [72/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0501 (0.0754) Prec@1 91.000 (87.890) Prec@5 100.000 (99.219) +2022-11-14 16:28:31,398 Test: [73/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0751) Prec@1 91.000 (87.932) Prec@5 100.000 (99.230) +2022-11-14 16:28:31,417 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0752) Prec@1 85.000 (87.893) Prec@5 98.000 (99.213) +2022-11-14 16:28:31,436 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0754) Prec@1 87.000 (87.882) Prec@5 99.000 (99.211) +2022-11-14 16:28:31,454 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0754) Prec@1 88.000 (87.883) Prec@5 100.000 (99.221) +2022-11-14 16:28:31,474 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0756) Prec@1 87.000 (87.872) Prec@5 100.000 (99.231) +2022-11-14 16:28:31,490 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0756) Prec@1 88.000 (87.873) Prec@5 100.000 (99.241) +2022-11-14 16:28:31,508 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0757) Prec@1 85.000 (87.838) Prec@5 100.000 (99.250) +2022-11-14 16:28:31,527 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0760) Prec@1 85.000 (87.802) Prec@5 98.000 (99.235) +2022-11-14 16:28:31,546 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0759) Prec@1 87.000 (87.793) Prec@5 100.000 (99.244) +2022-11-14 16:28:31,564 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0759) Prec@1 88.000 (87.795) Prec@5 98.000 (99.229) +2022-11-14 16:28:31,583 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0759) Prec@1 87.000 (87.786) Prec@5 99.000 (99.226) +2022-11-14 16:28:31,604 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0760) Prec@1 84.000 (87.741) Prec@5 100.000 (99.235) +2022-11-14 16:28:31,622 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1168 (0.0765) Prec@1 83.000 (87.686) Prec@5 97.000 (99.209) +2022-11-14 16:28:31,641 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0765) Prec@1 88.000 (87.690) Prec@5 100.000 (99.218) +2022-11-14 16:28:31,659 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0766) Prec@1 87.000 (87.682) Prec@5 99.000 (99.216) +2022-11-14 16:28:31,679 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0947 (0.0768) Prec@1 83.000 (87.629) Prec@5 100.000 (99.225) +2022-11-14 16:28:31,696 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0766) Prec@1 93.000 (87.689) Prec@5 99.000 (99.222) +2022-11-14 16:28:31,715 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0763) Prec@1 92.000 (87.736) Prec@5 100.000 (99.231) +2022-11-14 16:28:31,733 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0761) Prec@1 91.000 (87.772) Prec@5 100.000 (99.239) +2022-11-14 16:28:31,751 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0762) Prec@1 86.000 (87.753) Prec@5 100.000 (99.247) +2022-11-14 16:28:31,767 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0762) Prec@1 88.000 (87.755) Prec@5 99.000 (99.245) +2022-11-14 16:28:31,785 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0763) Prec@1 88.000 (87.758) Prec@5 100.000 (99.253) +2022-11-14 16:28:31,803 Test: [95/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0762) Prec@1 88.000 (87.760) Prec@5 99.000 (99.250) +2022-11-14 16:28:31,821 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0368 (0.0758) Prec@1 95.000 (87.835) Prec@5 98.000 (99.237) +2022-11-14 16:28:31,839 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0760) Prec@1 86.000 (87.816) Prec@5 98.000 (99.224) +2022-11-14 16:28:31,857 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0760) Prec@1 87.000 (87.808) Prec@5 100.000 (99.232) +2022-11-14 16:28:31,876 Test: [99/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0630 (0.0759) Prec@1 87.000 (87.800) Prec@5 100.000 (99.240) +2022-11-14 16:28:31,946 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:28:32,386 Epoch: [348][0/500] Time 0.028 (0.028) Data 0.326 (0.326) Loss 0.0403 (0.0403) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:28:32,903 Epoch: [348][10/500] Time 0.056 (0.044) Data 0.002 (0.032) Loss 0.0550 (0.0476) Prec@1 89.000 (91.500) Prec@5 98.000 (99.000) +2022-11-14 16:28:33,399 Epoch: [348][20/500] Time 0.038 (0.045) Data 0.002 (0.018) Loss 0.0349 (0.0434) Prec@1 94.000 (92.333) Prec@5 100.000 (99.333) +2022-11-14 16:28:33,828 Epoch: [348][30/500] Time 0.037 (0.043) Data 0.002 (0.013) Loss 0.0353 (0.0414) Prec@1 92.000 (92.250) Prec@5 100.000 (99.500) +2022-11-14 16:28:34,356 Epoch: [348][40/500] Time 0.054 (0.044) Data 0.002 (0.010) Loss 0.0265 (0.0384) Prec@1 95.000 (92.800) Prec@5 99.000 (99.400) +2022-11-14 16:28:35,384 Epoch: [348][50/500] Time 0.137 (0.053) Data 0.002 (0.008) Loss 0.0363 (0.0381) Prec@1 93.000 (92.833) Prec@5 99.000 (99.333) +2022-11-14 16:28:36,152 Epoch: [348][60/500] Time 0.073 (0.056) Data 0.002 (0.007) Loss 0.0078 (0.0337) Prec@1 99.000 (93.714) Prec@5 100.000 (99.429) +2022-11-14 16:28:37,016 Epoch: [348][70/500] Time 0.079 (0.058) Data 0.002 (0.007) Loss 0.0176 (0.0317) Prec@1 97.000 (94.125) Prec@5 100.000 (99.500) +2022-11-14 16:28:37,972 Epoch: [348][80/500] Time 0.113 (0.061) Data 0.002 (0.006) Loss 0.0121 (0.0295) Prec@1 98.000 (94.556) Prec@5 100.000 (99.556) +2022-11-14 16:28:38,887 Epoch: [348][90/500] Time 0.066 (0.063) Data 0.002 (0.006) Loss 0.0430 (0.0309) Prec@1 92.000 (94.300) Prec@5 100.000 (99.600) +2022-11-14 16:28:39,938 Epoch: [348][100/500] Time 0.081 (0.067) Data 0.002 (0.005) Loss 0.0487 (0.0325) Prec@1 89.000 (93.818) Prec@5 100.000 (99.636) +2022-11-14 16:28:40,752 Epoch: [348][110/500] Time 0.070 (0.067) Data 0.002 (0.005) Loss 0.0395 (0.0331) Prec@1 93.000 (93.750) Prec@5 100.000 (99.667) +2022-11-14 16:28:41,833 Epoch: [348][120/500] Time 0.107 (0.070) Data 0.002 (0.005) Loss 0.0183 (0.0320) Prec@1 98.000 (94.077) Prec@5 100.000 (99.692) +2022-11-14 16:28:42,668 Epoch: [348][130/500] Time 0.083 (0.070) Data 0.002 (0.005) Loss 0.0229 (0.0313) Prec@1 96.000 (94.214) Prec@5 100.000 (99.714) +2022-11-14 16:28:43,454 Epoch: [348][140/500] Time 0.078 (0.070) Data 0.002 (0.004) Loss 0.0417 (0.0320) Prec@1 92.000 (94.067) Prec@5 100.000 (99.733) +2022-11-14 16:28:44,259 Epoch: [348][150/500] Time 0.081 (0.071) Data 0.002 (0.004) Loss 0.0252 (0.0316) Prec@1 97.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:28:44,996 Epoch: [348][160/500] Time 0.063 (0.070) Data 0.002 (0.004) Loss 0.0386 (0.0320) Prec@1 93.000 (94.176) Prec@5 100.000 (99.765) +2022-11-14 16:28:45,763 Epoch: [348][170/500] Time 0.074 (0.070) Data 0.002 (0.004) Loss 0.0327 (0.0320) Prec@1 95.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 16:28:46,570 Epoch: [348][180/500] Time 0.083 (0.070) Data 0.002 (0.004) Loss 0.0371 (0.0323) Prec@1 95.000 (94.263) Prec@5 99.000 (99.737) +2022-11-14 16:28:47,364 Epoch: [348][190/500] Time 0.069 (0.070) Data 0.002 (0.004) Loss 0.0249 (0.0319) Prec@1 96.000 (94.350) Prec@5 100.000 (99.750) +2022-11-14 16:28:48,160 Epoch: [348][200/500] Time 0.072 (0.070) Data 0.002 (0.004) Loss 0.0280 (0.0317) Prec@1 96.000 (94.429) Prec@5 100.000 (99.762) +2022-11-14 16:28:49,083 Epoch: [348][210/500] Time 0.125 (0.071) Data 0.002 (0.004) Loss 0.0133 (0.0309) Prec@1 98.000 (94.591) Prec@5 100.000 (99.773) +2022-11-14 16:28:49,866 Epoch: [348][220/500] Time 0.076 (0.071) Data 0.002 (0.004) Loss 0.0200 (0.0304) Prec@1 97.000 (94.696) Prec@5 100.000 (99.783) +2022-11-14 16:28:50,644 Epoch: [348][230/500] Time 0.077 (0.071) Data 0.002 (0.003) Loss 0.0062 (0.0294) Prec@1 99.000 (94.875) Prec@5 100.000 (99.792) +2022-11-14 16:28:51,425 Epoch: [348][240/500] Time 0.068 (0.071) Data 0.002 (0.003) Loss 0.0323 (0.0295) Prec@1 96.000 (94.920) Prec@5 100.000 (99.800) +2022-11-14 16:28:52,214 Epoch: [348][250/500] Time 0.075 (0.071) Data 0.003 (0.003) Loss 0.0212 (0.0292) Prec@1 96.000 (94.962) Prec@5 100.000 (99.808) +2022-11-14 16:28:53,013 Epoch: [348][260/500] Time 0.087 (0.071) Data 0.002 (0.003) Loss 0.0210 (0.0289) Prec@1 98.000 (95.074) Prec@5 100.000 (99.815) +2022-11-14 16:28:53,851 Epoch: [348][270/500] Time 0.088 (0.071) Data 0.002 (0.003) Loss 0.0421 (0.0294) Prec@1 93.000 (95.000) Prec@5 99.000 (99.786) +2022-11-14 16:28:54,619 Epoch: [348][280/500] Time 0.073 (0.071) Data 0.002 (0.003) Loss 0.0377 (0.0297) Prec@1 94.000 (94.966) Prec@5 100.000 (99.793) +2022-11-14 16:28:55,186 Epoch: [348][290/500] Time 0.044 (0.070) Data 0.002 (0.003) Loss 0.0232 (0.0295) Prec@1 97.000 (95.033) Prec@5 100.000 (99.800) +2022-11-14 16:28:55,662 Epoch: [348][300/500] Time 0.047 (0.069) Data 0.002 (0.003) Loss 0.0268 (0.0294) Prec@1 97.000 (95.097) Prec@5 100.000 (99.806) +2022-11-14 16:28:56,142 Epoch: [348][310/500] Time 0.057 (0.068) Data 0.003 (0.003) Loss 0.0246 (0.0292) Prec@1 96.000 (95.125) Prec@5 100.000 (99.812) +2022-11-14 16:28:56,709 Epoch: [348][320/500] Time 0.060 (0.068) Data 0.002 (0.003) Loss 0.0204 (0.0290) Prec@1 98.000 (95.212) Prec@5 99.000 (99.788) +2022-11-14 16:28:57,171 Epoch: [348][330/500] Time 0.054 (0.067) Data 0.002 (0.003) Loss 0.0258 (0.0289) Prec@1 95.000 (95.206) Prec@5 100.000 (99.794) +2022-11-14 16:28:57,654 Epoch: [348][340/500] Time 0.037 (0.066) Data 0.002 (0.003) Loss 0.0552 (0.0296) Prec@1 89.000 (95.029) Prec@5 99.000 (99.771) +2022-11-14 16:28:58,169 Epoch: [348][350/500] Time 0.067 (0.066) Data 0.002 (0.003) Loss 0.0349 (0.0298) Prec@1 94.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 16:28:58,707 Epoch: [348][360/500] Time 0.042 (0.065) Data 0.002 (0.003) Loss 0.0494 (0.0303) Prec@1 93.000 (94.946) Prec@5 100.000 (99.757) +2022-11-14 16:28:59,188 Epoch: [348][370/500] Time 0.040 (0.065) Data 0.002 (0.003) Loss 0.0419 (0.0306) Prec@1 92.000 (94.868) Prec@5 100.000 (99.763) +2022-11-14 16:28:59,680 Epoch: [348][380/500] Time 0.045 (0.064) Data 0.002 (0.003) Loss 0.0201 (0.0303) Prec@1 97.000 (94.923) Prec@5 100.000 (99.769) +2022-11-14 16:29:00,166 Epoch: [348][390/500] Time 0.054 (0.064) Data 0.002 (0.003) Loss 0.0352 (0.0304) Prec@1 93.000 (94.875) Prec@5 100.000 (99.775) +2022-11-14 16:29:00,643 Epoch: [348][400/500] Time 0.041 (0.063) Data 0.002 (0.003) Loss 0.0290 (0.0304) Prec@1 95.000 (94.878) Prec@5 99.000 (99.756) +2022-11-14 16:29:01,134 Epoch: [348][410/500] Time 0.049 (0.063) Data 0.002 (0.003) Loss 0.0363 (0.0306) Prec@1 93.000 (94.833) Prec@5 100.000 (99.762) +2022-11-14 16:29:01,613 Epoch: [348][420/500] Time 0.052 (0.062) Data 0.002 (0.003) Loss 0.0300 (0.0305) Prec@1 95.000 (94.837) Prec@5 100.000 (99.767) +2022-11-14 16:29:02,066 Epoch: [348][430/500] Time 0.041 (0.062) Data 0.002 (0.003) Loss 0.0384 (0.0307) Prec@1 94.000 (94.818) Prec@5 99.000 (99.750) +2022-11-14 16:29:02,628 Epoch: [348][440/500] Time 0.062 (0.061) Data 0.002 (0.003) Loss 0.0374 (0.0309) Prec@1 94.000 (94.800) Prec@5 100.000 (99.756) +2022-11-14 16:29:03,118 Epoch: [348][450/500] Time 0.045 (0.061) Data 0.002 (0.003) Loss 0.0449 (0.0312) Prec@1 94.000 (94.783) Prec@5 100.000 (99.761) +2022-11-14 16:29:03,611 Epoch: [348][460/500] Time 0.050 (0.061) Data 0.002 (0.003) Loss 0.0154 (0.0308) Prec@1 98.000 (94.851) Prec@5 100.000 (99.766) +2022-11-14 16:29:04,073 Epoch: [348][470/500] Time 0.036 (0.060) Data 0.002 (0.003) Loss 0.0140 (0.0305) Prec@1 98.000 (94.917) Prec@5 100.000 (99.771) +2022-11-14 16:29:04,551 Epoch: [348][480/500] Time 0.047 (0.060) Data 0.002 (0.003) Loss 0.0395 (0.0307) Prec@1 93.000 (94.878) Prec@5 100.000 (99.776) +2022-11-14 16:29:05,025 Epoch: [348][490/500] Time 0.043 (0.059) Data 0.002 (0.003) Loss 0.0268 (0.0306) Prec@1 96.000 (94.900) Prec@5 100.000 (99.780) +2022-11-14 16:29:05,455 Epoch: [348][499/500] Time 0.045 (0.059) Data 0.002 (0.003) Loss 0.0293 (0.0306) Prec@1 95.000 (94.902) Prec@5 100.000 (99.784) +2022-11-14 16:29:05,795 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0579 (0.0579) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:05,803 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0558 (0.0568) Prec@1 93.000 (92.500) Prec@5 100.000 (100.000) +2022-11-14 16:29:05,814 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0584) Prec@1 88.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:05,830 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0589) Prec@1 88.000 (90.250) Prec@5 100.000 (100.000) +2022-11-14 16:29:05,840 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.0685) Prec@1 82.000 (88.600) Prec@5 98.000 (99.600) +2022-11-14 16:29:05,852 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0431 (0.0643) Prec@1 92.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:29:05,864 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0641) Prec@1 90.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 16:29:05,876 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0640) Prec@1 88.000 (89.125) Prec@5 100.000 (99.750) +2022-11-14 16:29:05,889 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0658) Prec@1 88.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:29:05,903 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0688) Prec@1 85.000 (88.600) Prec@5 98.000 (99.500) +2022-11-14 16:29:05,918 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0676) Prec@1 92.000 (88.909) Prec@5 100.000 (99.545) +2022-11-14 16:29:05,932 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0671) Prec@1 92.000 (89.167) Prec@5 99.000 (99.500) +2022-11-14 16:29:05,945 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0640 (0.0669) Prec@1 89.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 16:29:05,961 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0680) Prec@1 89.000 (89.143) Prec@5 100.000 (99.571) +2022-11-14 16:29:05,975 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0685) Prec@1 86.000 (88.933) Prec@5 100.000 (99.600) +2022-11-14 16:29:05,989 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0676) Prec@1 92.000 (89.125) Prec@5 100.000 (99.625) +2022-11-14 16:29:06,004 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0671) Prec@1 92.000 (89.294) Prec@5 99.000 (99.588) +2022-11-14 16:29:06,019 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1241 (0.0703) Prec@1 82.000 (88.889) Prec@5 100.000 (99.611) +2022-11-14 16:29:06,036 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0709) Prec@1 85.000 (88.684) Prec@5 98.000 (99.526) +2022-11-14 16:29:06,052 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0716) Prec@1 85.000 (88.500) Prec@5 100.000 (99.550) +2022-11-14 16:29:06,069 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0727) Prec@1 83.000 (88.238) Prec@5 100.000 (99.571) +2022-11-14 16:29:06,086 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0733) Prec@1 87.000 (88.182) Prec@5 99.000 (99.545) +2022-11-14 16:29:06,101 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1111 (0.0749) Prec@1 83.000 (87.957) Prec@5 99.000 (99.522) +2022-11-14 16:29:06,117 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0749) Prec@1 88.000 (87.958) Prec@5 99.000 (99.500) +2022-11-14 16:29:06,133 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0753) Prec@1 87.000 (87.920) Prec@5 100.000 (99.520) +2022-11-14 16:29:06,149 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1003 (0.0762) Prec@1 87.000 (87.885) Prec@5 99.000 (99.500) +2022-11-14 16:29:06,164 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0753) Prec@1 92.000 (88.037) Prec@5 100.000 (99.519) +2022-11-14 16:29:06,178 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0750) Prec@1 89.000 (88.071) Prec@5 100.000 (99.536) +2022-11-14 16:29:06,193 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0743) Prec@1 92.000 (88.207) Prec@5 99.000 (99.517) +2022-11-14 16:29:06,209 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0744) Prec@1 87.000 (88.167) Prec@5 99.000 (99.500) +2022-11-14 16:29:06,230 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0743) Prec@1 90.000 (88.226) Prec@5 100.000 (99.516) +2022-11-14 16:29:06,245 Test: [31/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0738) Prec@1 91.000 (88.312) Prec@5 98.000 (99.469) +2022-11-14 16:29:06,260 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0737) Prec@1 88.000 (88.303) Prec@5 100.000 (99.485) +2022-11-14 16:29:06,274 Test: [33/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0743) Prec@1 84.000 (88.176) Prec@5 100.000 (99.500) +2022-11-14 16:29:06,292 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0892 (0.0747) Prec@1 85.000 (88.086) Prec@5 98.000 (99.457) +2022-11-14 16:29:06,309 Test: [35/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0748) Prec@1 88.000 (88.083) Prec@5 99.000 (99.444) +2022-11-14 16:29:06,325 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0746) Prec@1 88.000 (88.081) Prec@5 100.000 (99.459) +2022-11-14 16:29:06,340 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0745) Prec@1 88.000 (88.079) Prec@5 99.000 (99.447) +2022-11-14 16:29:06,356 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0745) Prec@1 91.000 (88.154) Prec@5 99.000 (99.436) +2022-11-14 16:29:06,371 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 89.000 (88.175) Prec@5 99.000 (99.425) +2022-11-14 16:29:06,387 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1225 (0.0755) Prec@1 78.000 (87.927) Prec@5 100.000 (99.439) +2022-11-14 16:29:06,403 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0757) Prec@1 85.000 (87.857) Prec@5 99.000 (99.429) +2022-11-14 16:29:06,418 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0749) Prec@1 93.000 (87.977) Prec@5 99.000 (99.419) +2022-11-14 16:29:06,431 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0749) Prec@1 88.000 (87.977) Prec@5 99.000 (99.409) +2022-11-14 16:29:06,448 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0744) Prec@1 90.000 (88.022) Prec@5 99.000 (99.400) +2022-11-14 16:29:06,465 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0748) Prec@1 85.000 (87.957) Prec@5 99.000 (99.391) +2022-11-14 16:29:06,480 Test: [46/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0745) Prec@1 91.000 (88.021) Prec@5 99.000 (99.383) +2022-11-14 16:29:06,496 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1102 (0.0752) Prec@1 81.000 (87.875) Prec@5 98.000 (99.354) +2022-11-14 16:29:06,512 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0622 (0.0750) Prec@1 90.000 (87.918) Prec@5 100.000 (99.367) +2022-11-14 16:29:06,527 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0752) Prec@1 86.000 (87.880) Prec@5 100.000 (99.380) +2022-11-14 16:29:06,547 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0754) Prec@1 87.000 (87.863) Prec@5 100.000 (99.392) +2022-11-14 16:29:06,563 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0752) Prec@1 88.000 (87.865) Prec@5 98.000 (99.365) +2022-11-14 16:29:06,575 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0751) Prec@1 90.000 (87.906) Prec@5 100.000 (99.377) +2022-11-14 16:29:06,590 Test: 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0.0679 (0.0748) Prec@1 87.000 (87.950) Prec@5 100.000 (99.317) +2022-11-14 16:29:06,706 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0747) Prec@1 88.000 (87.951) Prec@5 100.000 (99.328) +2022-11-14 16:29:06,722 Test: [61/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0746) Prec@1 88.000 (87.952) Prec@5 99.000 (99.323) +2022-11-14 16:29:06,738 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0472 (0.0741) Prec@1 91.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 16:29:06,753 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0738) Prec@1 93.000 (88.078) Prec@5 98.000 (99.312) +2022-11-14 16:29:06,767 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0740) Prec@1 87.000 (88.062) Prec@5 100.000 (99.323) +2022-11-14 16:29:06,783 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0741) Prec@1 85.000 (88.015) Prec@5 99.000 (99.318) +2022-11-14 16:29:06,800 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0396 (0.0736) Prec@1 94.000 (88.104) Prec@5 99.000 (99.313) +2022-11-14 16:29:06,816 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0737) Prec@1 88.000 (88.103) Prec@5 99.000 (99.309) +2022-11-14 16:29:06,833 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0737) Prec@1 90.000 (88.130) Prec@5 99.000 (99.304) +2022-11-14 16:29:06,849 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0938 (0.0740) Prec@1 85.000 (88.086) Prec@5 98.000 (99.286) +2022-11-14 16:29:06,863 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0743) Prec@1 86.000 (88.056) Prec@5 98.000 (99.268) +2022-11-14 16:29:06,877 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0742) Prec@1 91.000 (88.097) Prec@5 99.000 (99.264) +2022-11-14 16:29:06,892 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0739) Prec@1 92.000 (88.151) Prec@5 100.000 (99.274) +2022-11-14 16:29:06,909 Test: [73/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0736) Prec@1 92.000 (88.203) Prec@5 100.000 (99.284) +2022-11-14 16:29:06,925 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0738) Prec@1 85.000 (88.160) Prec@5 99.000 (99.280) +2022-11-14 16:29:06,940 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0738) Prec@1 88.000 (88.158) Prec@5 99.000 (99.276) +2022-11-14 16:29:06,958 Test: [76/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0738) Prec@1 90.000 (88.182) Prec@5 98.000 (99.260) +2022-11-14 16:29:06,974 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0739) Prec@1 87.000 (88.167) Prec@5 98.000 (99.244) +2022-11-14 16:29:06,988 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0740) Prec@1 88.000 (88.165) Prec@5 100.000 (99.253) +2022-11-14 16:29:07,002 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0739) Prec@1 89.000 (88.175) Prec@5 100.000 (99.263) +2022-11-14 16:29:07,017 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0740) Prec@1 86.000 (88.148) Prec@5 98.000 (99.247) +2022-11-14 16:29:07,031 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1050 (0.0744) Prec@1 81.000 (88.061) Prec@5 99.000 (99.244) +2022-11-14 16:29:07,050 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0746) Prec@1 85.000 (88.024) Prec@5 99.000 (99.241) +2022-11-14 16:29:07,066 Test: [83/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0743) Prec@1 92.000 (88.071) Prec@5 100.000 (99.250) +2022-11-14 16:29:07,082 Test: [84/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0743) Prec@1 88.000 (88.071) Prec@5 100.000 (99.259) +2022-11-14 16:29:07,099 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0746) Prec@1 83.000 (88.012) Prec@5 100.000 (99.267) +2022-11-14 16:29:07,115 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0746) Prec@1 89.000 (88.023) Prec@5 99.000 (99.264) +2022-11-14 16:29:07,131 Test: [87/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0746) Prec@1 88.000 (88.023) Prec@5 99.000 (99.261) +2022-11-14 16:29:07,147 Test: [88/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0745) Prec@1 89.000 (88.034) Prec@5 99.000 (99.258) +2022-11-14 16:29:07,166 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0745) Prec@1 88.000 (88.033) Prec@5 99.000 (99.256) +2022-11-14 16:29:07,183 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0743) Prec@1 90.000 (88.055) Prec@5 100.000 (99.264) +2022-11-14 16:29:07,198 Test: [91/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0741) Prec@1 92.000 (88.098) Prec@5 100.000 (99.272) +2022-11-14 16:29:07,214 Test: [92/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0743) Prec@1 85.000 (88.065) Prec@5 99.000 (99.269) +2022-11-14 16:29:07,229 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 87.000 (88.053) Prec@5 100.000 (99.277) +2022-11-14 16:29:07,246 Test: [94/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0742) Prec@1 86.000 (88.032) Prec@5 100.000 (99.284) +2022-11-14 16:29:07,260 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0741) Prec@1 91.000 (88.062) Prec@5 97.000 (99.260) +2022-11-14 16:29:07,274 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0570 (0.0739) Prec@1 90.000 (88.082) Prec@5 98.000 (99.247) +2022-11-14 16:29:07,289 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0742) Prec@1 86.000 (88.061) Prec@5 96.000 (99.214) +2022-11-14 16:29:07,308 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1146 (0.0746) Prec@1 82.000 (88.000) Prec@5 99.000 (99.212) +2022-11-14 16:29:07,325 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0747) Prec@1 87.000 (87.990) Prec@5 100.000 (99.220) +2022-11-14 16:29:07,385 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:29:07,738 Epoch: [349][0/500] Time 0.023 (0.023) Data 0.267 (0.267) Loss 0.0117 (0.0117) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:08,173 Epoch: [349][10/500] Time 0.042 (0.037) Data 0.002 (0.026) Loss 0.0333 (0.0225) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:29:08,645 Epoch: [349][20/500] Time 0.047 (0.039) Data 0.002 (0.015) Loss 0.0415 (0.0288) Prec@1 94.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:29:09,108 Epoch: [349][30/500] Time 0.046 (0.040) Data 0.003 (0.011) Loss 0.0224 (0.0272) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:09,599 Epoch: [349][40/500] Time 0.047 (0.041) Data 0.002 (0.009) Loss 0.0353 (0.0288) Prec@1 94.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:29:10,068 Epoch: [349][50/500] Time 0.042 (0.041) Data 0.002 (0.007) Loss 0.0422 (0.0311) Prec@1 93.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 16:29:10,541 Epoch: [349][60/500] Time 0.042 (0.041) Data 0.002 (0.006) Loss 0.0357 (0.0317) Prec@1 95.000 (95.143) Prec@5 99.000 (99.857) +2022-11-14 16:29:11,015 Epoch: [349][70/500] Time 0.047 (0.041) Data 0.002 (0.006) Loss 0.0226 (0.0306) Prec@1 96.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:29:11,489 Epoch: [349][80/500] Time 0.047 (0.041) Data 0.002 (0.005) Loss 0.0205 (0.0295) Prec@1 96.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 16:29:11,975 Epoch: [349][90/500] Time 0.050 (0.042) Data 0.003 (0.005) Loss 0.0188 (0.0284) Prec@1 98.000 (95.600) Prec@5 100.000 (99.900) +2022-11-14 16:29:12,445 Epoch: [349][100/500] Time 0.042 (0.042) Data 0.002 (0.005) Loss 0.0324 (0.0288) Prec@1 93.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 16:29:12,931 Epoch: [349][110/500] Time 0.045 (0.042) Data 0.002 (0.005) Loss 0.0179 (0.0279) Prec@1 96.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 16:29:13,412 Epoch: [349][120/500] Time 0.043 (0.042) Data 0.002 (0.004) Loss 0.0222 (0.0274) Prec@1 96.000 (95.462) Prec@5 100.000 (99.923) +2022-11-14 16:29:13,883 Epoch: [349][130/500] Time 0.042 (0.042) Data 0.002 (0.004) Loss 0.0282 (0.0275) Prec@1 94.000 (95.357) Prec@5 100.000 (99.929) +2022-11-14 16:29:14,356 Epoch: [349][140/500] Time 0.042 (0.042) Data 0.002 (0.004) Loss 0.0183 (0.0269) Prec@1 98.000 (95.533) Prec@5 100.000 (99.933) +2022-11-14 16:29:14,841 Epoch: [349][150/500] Time 0.040 (0.042) Data 0.002 (0.004) Loss 0.0208 (0.0265) Prec@1 97.000 (95.625) Prec@5 100.000 (99.938) +2022-11-14 16:29:15,315 Epoch: [349][160/500] Time 0.045 (0.042) Data 0.002 (0.004) Loss 0.0410 (0.0273) Prec@1 94.000 (95.529) Prec@5 100.000 (99.941) +2022-11-14 16:29:15,779 Epoch: [349][170/500] Time 0.040 (0.042) Data 0.002 (0.004) Loss 0.0325 (0.0276) Prec@1 94.000 (95.444) Prec@5 100.000 (99.944) +2022-11-14 16:29:16,258 Epoch: [349][180/500] Time 0.039 (0.042) Data 0.002 (0.004) Loss 0.0286 (0.0277) Prec@1 96.000 (95.474) Prec@5 100.000 (99.947) +2022-11-14 16:29:16,728 Epoch: [349][190/500] Time 0.046 (0.042) Data 0.002 (0.003) Loss 0.0391 (0.0282) Prec@1 93.000 (95.350) Prec@5 99.000 (99.900) +2022-11-14 16:29:17,298 Epoch: [349][200/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0237 (0.0280) Prec@1 96.000 (95.381) Prec@5 100.000 (99.905) +2022-11-14 16:29:17,785 Epoch: [349][210/500] Time 0.037 (0.042) Data 0.002 (0.003) Loss 0.0424 (0.0287) Prec@1 92.000 (95.227) Prec@5 100.000 (99.909) +2022-11-14 16:29:18,278 Epoch: [349][220/500] Time 0.055 (0.042) Data 0.002 (0.003) Loss 0.0249 (0.0285) Prec@1 96.000 (95.261) Prec@5 100.000 (99.913) +2022-11-14 16:29:18,782 Epoch: [349][230/500] Time 0.039 (0.043) Data 0.002 (0.003) Loss 0.0254 (0.0284) Prec@1 96.000 (95.292) Prec@5 100.000 (99.917) +2022-11-14 16:29:19,264 Epoch: [349][240/500] Time 0.048 (0.043) Data 0.002 (0.003) Loss 0.0213 (0.0281) Prec@1 97.000 (95.360) Prec@5 100.000 (99.920) +2022-11-14 16:29:19,771 Epoch: [349][250/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0240 (0.0279) Prec@1 97.000 (95.423) Prec@5 100.000 (99.923) +2022-11-14 16:29:20,258 Epoch: [349][260/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0153 (0.0275) Prec@1 97.000 (95.481) Prec@5 100.000 (99.926) +2022-11-14 16:29:20,838 Epoch: [349][270/500] Time 0.060 (0.043) Data 0.002 (0.003) Loss 0.0191 (0.0272) Prec@1 97.000 (95.536) Prec@5 100.000 (99.929) +2022-11-14 16:29:21,315 Epoch: [349][280/500] Time 0.042 (0.043) Data 0.002 (0.003) Loss 0.0064 (0.0265) Prec@1 100.000 (95.690) Prec@5 100.000 (99.931) +2022-11-14 16:29:21,799 Epoch: [349][290/500] Time 0.050 (0.043) Data 0.002 (0.003) Loss 0.0284 (0.0265) Prec@1 96.000 (95.700) Prec@5 100.000 (99.933) +2022-11-14 16:29:22,332 Epoch: [349][300/500] Time 0.059 (0.043) Data 0.002 (0.003) Loss 0.0335 (0.0268) Prec@1 95.000 (95.677) Prec@5 99.000 (99.903) +2022-11-14 16:29:23,325 Epoch: [349][310/500] Time 0.086 (0.045) Data 0.002 (0.003) Loss 0.0377 (0.0271) Prec@1 94.000 (95.625) Prec@5 100.000 (99.906) +2022-11-14 16:29:24,218 Epoch: [349][320/500] Time 0.077 (0.046) Data 0.002 (0.003) Loss 0.0244 (0.0270) Prec@1 97.000 (95.667) Prec@5 100.000 (99.909) +2022-11-14 16:29:25,169 Epoch: [349][330/500] Time 0.079 (0.047) Data 0.002 (0.003) Loss 0.0309 (0.0271) Prec@1 95.000 (95.647) Prec@5 100.000 (99.912) +2022-11-14 16:29:25,951 Epoch: [349][340/500] Time 0.086 (0.047) Data 0.002 (0.003) Loss 0.0124 (0.0267) Prec@1 98.000 (95.714) Prec@5 100.000 (99.914) +2022-11-14 16:29:26,701 Epoch: [349][350/500] Time 0.076 (0.048) Data 0.002 (0.003) Loss 0.0375 (0.0270) Prec@1 93.000 (95.639) Prec@5 100.000 (99.917) +2022-11-14 16:29:27,505 Epoch: [349][360/500] Time 0.066 (0.049) Data 0.002 (0.003) Loss 0.0344 (0.0272) Prec@1 95.000 (95.622) Prec@5 100.000 (99.919) +2022-11-14 16:29:28,325 Epoch: [349][370/500] Time 0.079 (0.049) Data 0.002 (0.003) Loss 0.0388 (0.0275) Prec@1 95.000 (95.605) Prec@5 100.000 (99.921) +2022-11-14 16:29:29,131 Epoch: [349][380/500] Time 0.076 (0.050) Data 0.002 (0.003) Loss 0.0223 (0.0274) Prec@1 97.000 (95.641) Prec@5 99.000 (99.897) +2022-11-14 16:29:29,913 Epoch: [349][390/500] Time 0.076 (0.050) Data 0.002 (0.003) Loss 0.0511 (0.0280) Prec@1 91.000 (95.525) Prec@5 100.000 (99.900) +2022-11-14 16:29:30,735 Epoch: [349][400/500] Time 0.074 (0.051) Data 0.002 (0.003) Loss 0.0427 (0.0283) Prec@1 91.000 (95.415) Prec@5 99.000 (99.878) +2022-11-14 16:29:31,503 Epoch: [349][410/500] Time 0.075 (0.051) Data 0.002 (0.003) Loss 0.0212 (0.0282) Prec@1 97.000 (95.452) Prec@5 100.000 (99.881) +2022-11-14 16:29:32,442 Epoch: [349][420/500] Time 0.074 (0.052) Data 0.002 (0.003) Loss 0.0256 (0.0281) Prec@1 96.000 (95.465) Prec@5 100.000 (99.884) +2022-11-14 16:29:33,283 Epoch: [349][430/500] Time 0.079 (0.053) Data 0.002 (0.003) Loss 0.0311 (0.0282) Prec@1 95.000 (95.455) Prec@5 100.000 (99.886) +2022-11-14 16:29:34,294 Epoch: [349][440/500] Time 0.078 (0.054) Data 0.002 (0.003) Loss 0.0384 (0.0284) Prec@1 95.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:29:35,118 Epoch: [349][450/500] Time 0.078 (0.054) Data 0.002 (0.003) Loss 0.0162 (0.0281) Prec@1 98.000 (95.500) Prec@5 100.000 (99.891) +2022-11-14 16:29:35,910 Epoch: [349][460/500] Time 0.077 (0.055) Data 0.003 (0.003) Loss 0.0361 (0.0283) Prec@1 95.000 (95.489) Prec@5 99.000 (99.872) +2022-11-14 16:29:36,672 Epoch: [349][470/500] Time 0.074 (0.055) Data 0.002 (0.003) Loss 0.0397 (0.0285) Prec@1 93.000 (95.438) Prec@5 100.000 (99.875) +2022-11-14 16:29:37,556 Epoch: [349][480/500] Time 0.063 (0.055) Data 0.002 (0.003) Loss 0.0520 (0.0290) Prec@1 90.000 (95.327) Prec@5 100.000 (99.878) +2022-11-14 16:29:38,169 Epoch: [349][490/500] Time 0.050 (0.055) Data 0.002 (0.003) Loss 0.0486 (0.0294) Prec@1 91.000 (95.240) Prec@5 100.000 (99.880) +2022-11-14 16:29:38,729 Epoch: [349][499/500] Time 0.061 (0.055) Data 0.002 (0.003) Loss 0.0221 (0.0293) Prec@1 96.000 (95.255) Prec@5 100.000 (99.882) +2022-11-14 16:29:39,066 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0724 (0.0724) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:39,075 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0650 (0.0687) Prec@1 89.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:29:39,088 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0463 (0.0612) Prec@1 93.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:29:39,102 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0681 (0.0629) Prec@1 86.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:29:39,111 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0654) Prec@1 89.000 (89.000) Prec@5 100.000 (99.800) +2022-11-14 16:29:39,120 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0453 (0.0620) Prec@1 92.000 (89.500) Prec@5 100.000 (99.833) +2022-11-14 16:29:39,131 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0610) Prec@1 91.000 (89.714) Prec@5 98.000 (99.571) +2022-11-14 16:29:39,142 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0653) Prec@1 84.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 16:29:39,152 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0646) Prec@1 93.000 (89.444) Prec@5 98.000 (99.444) +2022-11-14 16:29:39,162 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0661) Prec@1 88.000 (89.300) Prec@5 98.000 (99.300) +2022-11-14 16:29:39,173 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0655) Prec@1 89.000 (89.273) Prec@5 99.000 (99.273) +2022-11-14 16:29:39,184 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0669) Prec@1 87.000 (89.083) Prec@5 100.000 (99.333) +2022-11-14 16:29:39,195 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0664) Prec@1 89.000 (89.077) Prec@5 100.000 (99.385) +2022-11-14 16:29:39,207 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0669) Prec@1 88.000 (89.000) Prec@5 99.000 (99.357) +2022-11-14 16:29:39,219 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0675) Prec@1 87.000 (88.867) Prec@5 100.000 (99.400) +2022-11-14 16:29:39,229 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0687) Prec@1 87.000 (88.750) Prec@5 100.000 (99.438) +2022-11-14 16:29:39,240 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0678) Prec@1 92.000 (88.941) Prec@5 99.000 (99.412) +2022-11-14 16:29:39,252 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0701) Prec@1 83.000 (88.611) Prec@5 99.000 (99.389) +2022-11-14 16:29:39,264 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0710) Prec@1 87.000 (88.526) Prec@5 97.000 (99.263) +2022-11-14 16:29:39,274 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1087 (0.0729) Prec@1 81.000 (88.150) Prec@5 95.000 (99.050) +2022-11-14 16:29:39,287 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0729) Prec@1 88.000 (88.143) Prec@5 100.000 (99.095) +2022-11-14 16:29:39,299 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0743) Prec@1 84.000 (87.955) Prec@5 100.000 (99.136) +2022-11-14 16:29:39,310 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0747) Prec@1 88.000 (87.957) Prec@5 99.000 (99.130) +2022-11-14 16:29:39,322 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0751) Prec@1 87.000 (87.917) Prec@5 100.000 (99.167) +2022-11-14 16:29:39,333 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0763) Prec@1 83.000 (87.720) Prec@5 99.000 (99.160) +2022-11-14 16:29:39,344 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0998 (0.0772) Prec@1 84.000 (87.577) Prec@5 99.000 (99.154) +2022-11-14 16:29:39,355 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0476 (0.0762) Prec@1 93.000 (87.778) Prec@5 100.000 (99.185) +2022-11-14 16:29:39,367 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0754) Prec@1 91.000 (87.893) Prec@5 99.000 (99.179) +2022-11-14 16:29:39,380 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0750) Prec@1 90.000 (87.966) Prec@5 98.000 (99.138) +2022-11-14 16:29:39,393 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0743) Prec@1 91.000 (88.067) Prec@5 100.000 (99.167) +2022-11-14 16:29:39,405 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0740) Prec@1 90.000 (88.129) Prec@5 100.000 (99.194) +2022-11-14 16:29:39,419 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0740) Prec@1 88.000 (88.125) Prec@5 100.000 (99.219) +2022-11-14 16:29:39,430 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0744) Prec@1 86.000 (88.061) Prec@5 99.000 (99.212) +2022-11-14 16:29:39,440 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0745) Prec@1 85.000 (87.971) Prec@5 100.000 (99.235) +2022-11-14 16:29:39,451 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0748) Prec@1 85.000 (87.886) Prec@5 98.000 (99.200) +2022-11-14 16:29:39,461 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0744) Prec@1 92.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 16:29:39,474 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0742) Prec@1 89.000 (88.027) Prec@5 99.000 (99.216) +2022-11-14 16:29:39,485 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0744) Prec@1 87.000 (88.000) Prec@5 99.000 (99.211) +2022-11-14 16:29:39,497 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0496 (0.0738) Prec@1 94.000 (88.154) Prec@5 99.000 (99.205) +2022-11-14 16:29:39,512 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0733) Prec@1 91.000 (88.225) Prec@5 99.000 (99.200) +2022-11-14 16:29:39,528 Test: [40/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0740) Prec@1 84.000 (88.122) Prec@5 98.000 (99.171) +2022-11-14 16:29:39,544 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0745) Prec@1 85.000 (88.048) Prec@5 99.000 (99.167) +2022-11-14 16:29:39,558 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0742) Prec@1 89.000 (88.070) Prec@5 99.000 (99.163) +2022-11-14 16:29:39,574 Test: [43/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0742) Prec@1 89.000 (88.091) Prec@5 98.000 (99.136) +2022-11-14 16:29:39,590 Test: [44/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0531 (0.0738) Prec@1 94.000 (88.222) Prec@5 98.000 (99.111) +2022-11-14 16:29:39,606 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0740) Prec@1 86.000 (88.174) Prec@5 100.000 (99.130) +2022-11-14 16:29:39,620 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0740) Prec@1 90.000 (88.213) Prec@5 100.000 (99.149) +2022-11-14 16:29:39,633 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0743) Prec@1 86.000 (88.167) Prec@5 97.000 (99.104) +2022-11-14 16:29:39,650 Test: [48/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0395 (0.0736) Prec@1 93.000 (88.265) Prec@5 100.000 (99.122) +2022-11-14 16:29:39,667 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0739) Prec@1 88.000 (88.260) Prec@5 99.000 (99.120) +2022-11-14 16:29:39,682 Test: [50/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0739) Prec@1 89.000 (88.275) Prec@5 99.000 (99.118) +2022-11-14 16:29:39,697 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.0746) Prec@1 80.000 (88.115) Prec@5 98.000 (99.096) +2022-11-14 16:29:39,710 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0742) Prec@1 92.000 (88.189) Prec@5 100.000 (99.113) +2022-11-14 16:29:39,725 Test: [53/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0739) Prec@1 91.000 (88.241) Prec@5 100.000 (99.130) +2022-11-14 16:29:39,739 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0739) Prec@1 88.000 (88.236) Prec@5 100.000 (99.145) +2022-11-14 16:29:39,755 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0738) Prec@1 88.000 (88.232) Prec@5 99.000 (99.143) +2022-11-14 16:29:39,771 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0739) Prec@1 86.000 (88.193) Prec@5 100.000 (99.158) +2022-11-14 16:29:39,785 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0738) Prec@1 90.000 (88.224) Prec@5 98.000 (99.138) +2022-11-14 16:29:39,800 Test: [58/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0740) Prec@1 88.000 (88.220) Prec@5 100.000 (99.153) +2022-11-14 16:29:39,814 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0740) Prec@1 87.000 (88.200) Prec@5 100.000 (99.167) +2022-11-14 16:29:39,830 Test: [60/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0741) Prec@1 86.000 (88.164) Prec@5 99.000 (99.164) +2022-11-14 16:29:39,844 Test: [61/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0740) Prec@1 91.000 (88.210) Prec@5 99.000 (99.161) +2022-11-14 16:29:39,861 Test: [62/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0740) Prec@1 89.000 (88.222) Prec@5 100.000 (99.175) +2022-11-14 16:29:39,876 Test: [63/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0399 (0.0734) Prec@1 94.000 (88.312) Prec@5 100.000 (99.188) +2022-11-14 16:29:39,890 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0822 (0.0736) Prec@1 86.000 (88.277) Prec@5 100.000 (99.200) +2022-11-14 16:29:39,905 Test: [65/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0787 (0.0736) Prec@1 86.000 (88.242) Prec@5 99.000 (99.197) +2022-11-14 16:29:39,918 Test: [66/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0733) Prec@1 91.000 (88.284) Prec@5 100.000 (99.209) +2022-11-14 16:29:39,933 Test: [67/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0713 (0.0733) Prec@1 89.000 (88.294) Prec@5 98.000 (99.191) +2022-11-14 16:29:39,947 Test: [68/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0732) Prec@1 90.000 (88.319) Prec@5 100.000 (99.203) +2022-11-14 16:29:39,962 Test: [69/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0733) Prec@1 87.000 (88.300) Prec@5 100.000 (99.214) +2022-11-14 16:29:39,977 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0736) Prec@1 85.000 (88.254) Prec@5 99.000 (99.211) +2022-11-14 16:29:39,992 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0733) Prec@1 93.000 (88.319) Prec@5 100.000 (99.222) +2022-11-14 16:29:40,007 Test: [72/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0468 (0.0729) Prec@1 92.000 (88.370) Prec@5 100.000 (99.233) +2022-11-14 16:29:40,024 Test: [73/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0330 (0.0724) Prec@1 97.000 (88.486) Prec@5 100.000 (99.243) +2022-11-14 16:29:40,038 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0727) Prec@1 84.000 (88.427) Prec@5 99.000 (99.240) +2022-11-14 16:29:40,052 Test: [75/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0728) Prec@1 88.000 (88.421) Prec@5 99.000 (99.237) +2022-11-14 16:29:40,068 Test: [76/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.1038 (0.0732) Prec@1 83.000 (88.351) Prec@5 100.000 (99.247) +2022-11-14 16:29:40,083 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0886 (0.0734) Prec@1 85.000 (88.308) Prec@5 99.000 (99.244) +2022-11-14 16:29:40,097 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0735) Prec@1 87.000 (88.291) Prec@5 100.000 (99.253) +2022-11-14 16:29:40,112 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0735) Prec@1 86.000 (88.263) Prec@5 99.000 (99.250) +2022-11-14 16:29:40,126 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.0737) Prec@1 87.000 (88.247) Prec@5 99.000 (99.247) +2022-11-14 16:29:40,139 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0696 (0.0737) Prec@1 88.000 (88.244) Prec@5 99.000 (99.244) +2022-11-14 16:29:40,155 Test: [82/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0877 (0.0739) Prec@1 86.000 (88.217) Prec@5 100.000 (99.253) +2022-11-14 16:29:40,170 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0737) Prec@1 88.000 (88.214) Prec@5 100.000 (99.262) +2022-11-14 16:29:40,184 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1114 (0.0742) Prec@1 80.000 (88.118) Prec@5 100.000 (99.271) +2022-11-14 16:29:40,198 Test: [85/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1005 (0.0745) Prec@1 86.000 (88.093) Prec@5 99.000 (99.267) +2022-11-14 16:29:40,213 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0767 (0.0745) Prec@1 86.000 (88.069) Prec@5 100.000 (99.276) +2022-11-14 16:29:40,229 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0865 (0.0746) Prec@1 87.000 (88.057) Prec@5 99.000 (99.273) +2022-11-14 16:29:40,244 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0540 (0.0744) Prec@1 90.000 (88.079) Prec@5 100.000 (99.281) +2022-11-14 16:29:40,258 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0745) Prec@1 87.000 (88.067) Prec@5 100.000 (99.289) +2022-11-14 16:29:40,274 Test: [90/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0488 (0.0742) Prec@1 92.000 (88.110) Prec@5 100.000 (99.297) +2022-11-14 16:29:40,288 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0486 (0.0739) Prec@1 92.000 (88.152) Prec@5 100.000 (99.304) +2022-11-14 16:29:40,302 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0921 (0.0741) Prec@1 87.000 (88.140) Prec@5 99.000 (99.301) +2022-11-14 16:29:40,319 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0741) Prec@1 85.000 (88.106) Prec@5 99.000 (99.298) +2022-11-14 16:29:40,335 Test: [94/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0741) Prec@1 90.000 (88.126) Prec@5 99.000 (99.295) +2022-11-14 16:29:40,347 Test: [95/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0537 (0.0739) Prec@1 93.000 (88.177) Prec@5 98.000 (99.281) +2022-11-14 16:29:40,361 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0511 (0.0737) Prec@1 93.000 (88.227) Prec@5 99.000 (99.278) +2022-11-14 16:29:40,376 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0737) Prec@1 89.000 (88.235) Prec@5 99.000 (99.276) +2022-11-14 16:29:40,390 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0739) Prec@1 85.000 (88.202) Prec@5 99.000 (99.273) +2022-11-14 16:29:40,404 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0739) Prec@1 86.000 (88.180) Prec@5 99.000 (99.270) +2022-11-14 16:29:40,477 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:29:40,910 Epoch: [350][0/500] Time 0.030 (0.030) Data 0.318 (0.318) Loss 0.0262 (0.0262) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:29:41,314 Epoch: [350][10/500] Time 0.038 (0.035) Data 0.002 (0.031) Loss 0.0121 (0.0191) Prec@1 98.000 (96.500) Prec@5 100.000 (99.500) +2022-11-14 16:29:41,649 Epoch: [350][20/500] Time 0.026 (0.033) Data 0.002 (0.017) Loss 0.0365 (0.0249) Prec@1 93.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:29:41,987 Epoch: [350][30/500] Time 0.028 (0.032) Data 0.002 (0.012) Loss 0.0348 (0.0274) Prec@1 95.000 (95.250) Prec@5 99.000 (99.500) +2022-11-14 16:29:42,337 Epoch: [350][40/500] Time 0.034 (0.032) Data 0.002 (0.010) Loss 0.0223 (0.0264) Prec@1 96.000 (95.400) Prec@5 100.000 (99.600) +2022-11-14 16:29:42,670 Epoch: [350][50/500] Time 0.032 (0.031) Data 0.002 (0.008) Loss 0.0382 (0.0283) Prec@1 94.000 (95.167) Prec@5 99.000 (99.500) +2022-11-14 16:29:43,018 Epoch: [350][60/500] Time 0.038 (0.031) Data 0.003 (0.007) Loss 0.0424 (0.0303) Prec@1 95.000 (95.143) Prec@5 99.000 (99.429) +2022-11-14 16:29:43,412 Epoch: [350][70/500] Time 0.049 (0.032) Data 0.002 (0.007) Loss 0.0219 (0.0293) Prec@1 98.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 16:29:43,924 Epoch: [350][80/500] Time 0.043 (0.034) Data 0.002 (0.006) Loss 0.0131 (0.0275) Prec@1 99.000 (95.889) Prec@5 100.000 (99.556) +2022-11-14 16:29:44,375 Epoch: [350][90/500] Time 0.043 (0.034) Data 0.002 (0.006) Loss 0.0168 (0.0264) Prec@1 97.000 (96.000) Prec@5 100.000 (99.600) +2022-11-14 16:29:44,925 Epoch: [350][100/500] Time 0.058 (0.036) Data 0.002 (0.005) Loss 0.0417 (0.0278) Prec@1 93.000 (95.727) Prec@5 99.000 (99.545) +2022-11-14 16:29:45,379 Epoch: [350][110/500] Time 0.043 (0.036) Data 0.002 (0.005) Loss 0.0277 (0.0278) Prec@1 96.000 (95.750) Prec@5 100.000 (99.583) +2022-11-14 16:29:45,828 Epoch: [350][120/500] Time 0.040 (0.036) Data 0.002 (0.005) Loss 0.0389 (0.0286) Prec@1 93.000 (95.538) Prec@5 99.000 (99.538) +2022-11-14 16:29:46,289 Epoch: [350][130/500] Time 0.051 (0.037) Data 0.002 (0.005) Loss 0.0220 (0.0282) Prec@1 97.000 (95.643) Prec@5 100.000 (99.571) +2022-11-14 16:29:46,747 Epoch: [350][140/500] Time 0.042 (0.037) Data 0.002 (0.004) Loss 0.0164 (0.0274) Prec@1 98.000 (95.800) Prec@5 100.000 (99.600) +2022-11-14 16:29:47,202 Epoch: [350][150/500] Time 0.034 (0.037) Data 0.002 (0.004) Loss 0.0223 (0.0271) Prec@1 96.000 (95.812) Prec@5 100.000 (99.625) +2022-11-14 16:29:47,648 Epoch: [350][160/500] Time 0.044 (0.037) Data 0.002 (0.004) Loss 0.0280 (0.0271) Prec@1 96.000 (95.824) Prec@5 100.000 (99.647) +2022-11-14 16:29:48,112 Epoch: [350][170/500] Time 0.045 (0.038) Data 0.002 (0.004) Loss 0.0369 (0.0277) Prec@1 94.000 (95.722) Prec@5 100.000 (99.667) +2022-11-14 16:29:48,916 Epoch: [350][180/500] Time 0.133 (0.039) Data 0.002 (0.004) Loss 0.0537 (0.0290) Prec@1 91.000 (95.474) Prec@5 98.000 (99.579) +2022-11-14 16:29:50,160 Epoch: [350][190/500] Time 0.128 (0.043) Data 0.002 (0.004) Loss 0.0234 (0.0288) Prec@1 97.000 (95.550) Prec@5 100.000 (99.600) +2022-11-14 16:29:51,181 Epoch: [350][200/500] Time 0.076 (0.046) Data 0.002 (0.004) Loss 0.0218 (0.0284) Prec@1 97.000 (95.619) Prec@5 100.000 (99.619) +2022-11-14 16:29:51,978 Epoch: [350][210/500] Time 0.075 (0.047) Data 0.002 (0.004) Loss 0.0159 (0.0279) Prec@1 98.000 (95.727) Prec@5 100.000 (99.636) +2022-11-14 16:29:53,040 Epoch: [350][220/500] Time 0.074 (0.049) Data 0.002 (0.004) Loss 0.0327 (0.0281) Prec@1 95.000 (95.696) Prec@5 100.000 (99.652) +2022-11-14 16:29:53,840 Epoch: [350][230/500] Time 0.073 (0.050) Data 0.002 (0.003) Loss 0.0165 (0.0276) Prec@1 96.000 (95.708) Prec@5 100.000 (99.667) +2022-11-14 16:29:54,591 Epoch: [350][240/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0198 (0.0273) Prec@1 97.000 (95.760) Prec@5 100.000 (99.680) +2022-11-14 16:29:55,380 Epoch: [350][250/500] Time 0.076 (0.052) Data 0.002 (0.003) Loss 0.0272 (0.0273) Prec@1 96.000 (95.769) Prec@5 100.000 (99.692) +2022-11-14 16:29:56,203 Epoch: [350][260/500] Time 0.090 (0.053) Data 0.002 (0.003) Loss 0.0369 (0.0276) Prec@1 95.000 (95.741) Prec@5 100.000 (99.704) +2022-11-14 16:29:57,217 Epoch: [350][270/500] Time 0.081 (0.054) Data 0.002 (0.003) Loss 0.0208 (0.0274) Prec@1 97.000 (95.786) Prec@5 100.000 (99.714) +2022-11-14 16:29:58,021 Epoch: [350][280/500] Time 0.077 (0.055) Data 0.002 (0.003) Loss 0.0238 (0.0273) Prec@1 98.000 (95.862) Prec@5 100.000 (99.724) +2022-11-14 16:29:58,821 Epoch: [350][290/500] Time 0.079 (0.055) Data 0.002 (0.003) Loss 0.0168 (0.0269) Prec@1 97.000 (95.900) Prec@5 100.000 (99.733) +2022-11-14 16:29:59,640 Epoch: [350][300/500] Time 0.079 (0.056) Data 0.002 (0.003) Loss 0.0192 (0.0267) Prec@1 97.000 (95.935) Prec@5 100.000 (99.742) +2022-11-14 16:30:00,447 Epoch: [350][310/500] Time 0.068 (0.056) Data 0.002 (0.003) Loss 0.0387 (0.0270) Prec@1 93.000 (95.844) Prec@5 100.000 (99.750) +2022-11-14 16:30:01,391 Epoch: [350][320/500] Time 0.055 (0.057) Data 0.002 (0.003) Loss 0.0466 (0.0276) Prec@1 93.000 (95.758) Prec@5 100.000 (99.758) +2022-11-14 16:30:01,944 Epoch: [350][330/500] Time 0.057 (0.057) Data 0.002 (0.003) Loss 0.0363 (0.0279) Prec@1 96.000 (95.765) Prec@5 100.000 (99.765) +2022-11-14 16:30:02,510 Epoch: [350][340/500] Time 0.056 (0.057) Data 0.002 (0.003) Loss 0.0152 (0.0275) Prec@1 98.000 (95.829) Prec@5 100.000 (99.771) +2022-11-14 16:30:03,124 Epoch: [350][350/500] Time 0.053 (0.057) Data 0.002 (0.003) Loss 0.0275 (0.0275) Prec@1 96.000 (95.833) Prec@5 99.000 (99.750) +2022-11-14 16:30:03,660 Epoch: [350][360/500] Time 0.050 (0.057) Data 0.002 (0.003) Loss 0.0295 (0.0276) Prec@1 95.000 (95.811) Prec@5 100.000 (99.757) +2022-11-14 16:30:04,220 Epoch: [350][370/500] Time 0.052 (0.057) Data 0.003 (0.003) Loss 0.0343 (0.0278) Prec@1 93.000 (95.737) Prec@5 100.000 (99.763) +2022-11-14 16:30:04,791 Epoch: [350][380/500] Time 0.064 (0.056) Data 0.002 (0.003) Loss 0.0302 (0.0278) Prec@1 95.000 (95.718) Prec@5 100.000 (99.769) +2022-11-14 16:30:05,451 Epoch: [350][390/500] Time 0.071 (0.056) Data 0.002 (0.003) Loss 0.0338 (0.0280) Prec@1 94.000 (95.675) Prec@5 99.000 (99.750) +2022-11-14 16:30:06,034 Epoch: [350][400/500] Time 0.062 (0.056) Data 0.002 (0.003) Loss 0.0282 (0.0280) Prec@1 94.000 (95.634) Prec@5 100.000 (99.756) +2022-11-14 16:30:06,617 Epoch: [350][410/500] Time 0.057 (0.056) Data 0.002 (0.003) Loss 0.0129 (0.0276) Prec@1 97.000 (95.667) Prec@5 100.000 (99.762) +2022-11-14 16:30:07,241 Epoch: [350][420/500] Time 0.061 (0.056) Data 0.002 (0.003) Loss 0.0273 (0.0276) Prec@1 96.000 (95.674) Prec@5 99.000 (99.744) +2022-11-14 16:30:07,800 Epoch: [350][430/500] Time 0.060 (0.056) Data 0.002 (0.003) Loss 0.0473 (0.0281) Prec@1 93.000 (95.614) Prec@5 100.000 (99.750) +2022-11-14 16:30:08,367 Epoch: [350][440/500] Time 0.055 (0.056) Data 0.002 (0.003) Loss 0.0326 (0.0282) Prec@1 93.000 (95.556) Prec@5 100.000 (99.756) +2022-11-14 16:30:08,967 Epoch: [350][450/500] Time 0.054 (0.056) Data 0.002 (0.003) Loss 0.0297 (0.0282) Prec@1 95.000 (95.543) Prec@5 100.000 (99.761) +2022-11-14 16:30:09,568 Epoch: [350][460/500] Time 0.049 (0.056) Data 0.002 (0.003) Loss 0.0427 (0.0285) Prec@1 93.000 (95.489) Prec@5 100.000 (99.766) +2022-11-14 16:30:10,150 Epoch: [350][470/500] Time 0.056 (0.056) Data 0.002 (0.003) Loss 0.0268 (0.0285) Prec@1 95.000 (95.479) Prec@5 100.000 (99.771) +2022-11-14 16:30:10,783 Epoch: [350][480/500] Time 0.057 (0.056) Data 0.002 (0.003) Loss 0.0134 (0.0282) Prec@1 99.000 (95.551) Prec@5 100.000 (99.776) +2022-11-14 16:30:11,370 Epoch: [350][490/500] Time 0.063 (0.056) Data 0.002 (0.003) Loss 0.0399 (0.0284) Prec@1 94.000 (95.520) Prec@5 99.000 (99.760) +2022-11-14 16:30:11,871 Epoch: [350][499/500] Time 0.061 (0.056) Data 0.002 (0.003) Loss 0.0777 (0.0294) Prec@1 87.000 (95.353) Prec@5 100.000 (99.765) +2022-11-14 16:30:12,232 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0560 (0.0560) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:30:12,242 Test: [1/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0681 (0.0621) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:30:12,256 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0554 (0.0598) Prec@1 90.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:30:12,269 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0680 (0.0619) Prec@1 91.000 (90.750) Prec@5 99.000 (99.750) +2022-11-14 16:30:12,281 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1042 (0.0703) Prec@1 82.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 16:30:12,291 Test: [5/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0480 (0.0666) Prec@1 92.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:30:12,305 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0610 (0.0658) Prec@1 91.000 (89.714) Prec@5 100.000 (99.571) +2022-11-14 16:30:12,317 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1137 (0.0718) Prec@1 81.000 (88.625) Prec@5 99.000 (99.500) +2022-11-14 16:30:12,330 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0735) Prec@1 87.000 (88.444) Prec@5 98.000 (99.333) +2022-11-14 16:30:12,349 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0913 (0.0752) Prec@1 87.000 (88.300) Prec@5 97.000 (99.100) +2022-11-14 16:30:12,375 Test: [10/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0733) Prec@1 92.000 (88.636) Prec@5 100.000 (99.182) +2022-11-14 16:30:12,401 Test: [11/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0727) Prec@1 92.000 (88.917) Prec@5 100.000 (99.250) +2022-11-14 16:30:12,425 Test: [12/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0714) Prec@1 91.000 (89.077) Prec@5 100.000 (99.308) +2022-11-14 16:30:12,451 Test: [13/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0615 (0.0707) Prec@1 93.000 (89.357) Prec@5 99.000 (99.286) +2022-11-14 16:30:12,478 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0864 (0.0717) Prec@1 86.000 (89.133) Prec@5 99.000 (99.267) +2022-11-14 16:30:12,506 Test: [15/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0719) Prec@1 86.000 (88.938) Prec@5 100.000 (99.312) +2022-11-14 16:30:12,529 Test: [16/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0516 (0.0707) Prec@1 92.000 (89.118) Prec@5 99.000 (99.294) +2022-11-14 16:30:12,551 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1304 (0.0740) Prec@1 79.000 (88.556) Prec@5 99.000 (99.278) +2022-11-14 16:30:12,579 Test: [18/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0738) Prec@1 87.000 (88.474) Prec@5 99.000 (99.263) +2022-11-14 16:30:12,599 Test: [19/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0748) Prec@1 84.000 (88.250) Prec@5 97.000 (99.150) +2022-11-14 16:30:12,622 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0748) Prec@1 89.000 (88.286) Prec@5 100.000 (99.190) +2022-11-14 16:30:12,647 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0750) Prec@1 87.000 (88.227) Prec@5 98.000 (99.136) +2022-11-14 16:30:12,673 Test: [22/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1060 (0.0764) Prec@1 84.000 (88.043) Prec@5 97.000 (99.043) +2022-11-14 16:30:12,696 Test: [23/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0765) Prec@1 87.000 (88.000) Prec@5 100.000 (99.083) +2022-11-14 16:30:12,723 Test: [24/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0768) Prec@1 86.000 (87.920) Prec@5 100.000 (99.120) +2022-11-14 16:30:12,748 Test: [25/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0773) Prec@1 86.000 (87.846) Prec@5 99.000 (99.115) +2022-11-14 16:30:12,776 Test: [26/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0442 (0.0761) Prec@1 93.000 (88.037) Prec@5 100.000 (99.148) +2022-11-14 16:30:12,800 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0520 (0.0752) Prec@1 91.000 (88.143) Prec@5 99.000 (99.143) +2022-11-14 16:30:12,822 Test: [28/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0602 (0.0747) Prec@1 89.000 (88.172) Prec@5 98.000 (99.103) +2022-11-14 16:30:12,847 Test: [29/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0738 (0.0747) Prec@1 87.000 (88.133) Prec@5 100.000 (99.133) +2022-11-14 16:30:12,873 Test: [30/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0633 (0.0743) Prec@1 89.000 (88.161) Prec@5 100.000 (99.161) +2022-11-14 16:30:12,897 Test: [31/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0595 (0.0739) Prec@1 92.000 (88.281) Prec@5 99.000 (99.156) +2022-11-14 16:30:12,923 Test: [32/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0764 (0.0739) Prec@1 89.000 (88.303) Prec@5 100.000 (99.182) +2022-11-14 16:30:12,949 Test: [33/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0933 (0.0745) Prec@1 82.000 (88.118) Prec@5 99.000 (99.176) +2022-11-14 16:30:12,973 Test: [34/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0646 (0.0742) Prec@1 90.000 (88.171) Prec@5 98.000 (99.143) +2022-11-14 16:30:12,995 Test: [35/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0523 (0.0736) Prec@1 93.000 (88.306) Prec@5 100.000 (99.167) +2022-11-14 16:30:13,020 Test: [36/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0734 (0.0736) Prec@1 87.000 (88.270) Prec@5 99.000 (99.162) +2022-11-14 16:30:13,041 Test: [37/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1036 (0.0744) Prec@1 83.000 (88.132) Prec@5 97.000 (99.105) +2022-11-14 16:30:13,064 Test: [38/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0548 (0.0739) Prec@1 92.000 (88.231) Prec@5 98.000 (99.077) +2022-11-14 16:30:13,088 Test: [39/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0533 (0.0734) Prec@1 93.000 (88.350) Prec@5 99.000 (99.075) +2022-11-14 16:30:13,112 Test: [40/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0936 (0.0739) Prec@1 87.000 (88.317) Prec@5 99.000 (99.073) +2022-11-14 16:30:13,137 Test: [41/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0614 (0.0736) Prec@1 90.000 (88.357) Prec@5 100.000 (99.095) +2022-11-14 16:30:13,162 Test: [42/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0393 (0.0728) Prec@1 94.000 (88.488) Prec@5 99.000 (99.093) +2022-11-14 16:30:13,187 Test: [43/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0667 (0.0726) Prec@1 90.000 (88.523) Prec@5 99.000 (99.091) +2022-11-14 16:30:13,210 Test: [44/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0607 (0.0724) Prec@1 89.000 (88.533) Prec@5 99.000 (99.089) +2022-11-14 16:30:13,231 Test: [45/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0925 (0.0728) Prec@1 84.000 (88.435) Prec@5 100.000 (99.109) +2022-11-14 16:30:13,247 Test: [46/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0836 (0.0730) Prec@1 86.000 (88.383) Prec@5 100.000 (99.128) +2022-11-14 16:30:13,263 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1068 (0.0737) Prec@1 80.000 (88.208) Prec@5 98.000 (99.104) +2022-11-14 16:30:13,284 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0736) Prec@1 88.000 (88.204) Prec@5 100.000 (99.122) +2022-11-14 16:30:13,310 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1077 (0.0742) Prec@1 82.000 (88.080) Prec@5 100.000 (99.140) +2022-11-14 16:30:13,338 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0741) Prec@1 91.000 (88.137) Prec@5 99.000 (99.137) +2022-11-14 16:30:13,362 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0743) Prec@1 89.000 (88.154) Prec@5 99.000 (99.135) +2022-11-14 16:30:13,384 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0741) Prec@1 90.000 (88.189) Prec@5 98.000 (99.113) +2022-11-14 16:30:13,410 Test: [53/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0739) Prec@1 92.000 (88.259) Prec@5 99.000 (99.111) +2022-11-14 16:30:13,436 Test: [54/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0870 (0.0741) Prec@1 87.000 (88.236) Prec@5 99.000 (99.109) +2022-11-14 16:30:13,462 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0740) Prec@1 90.000 (88.268) Prec@5 99.000 (99.107) +2022-11-14 16:30:13,480 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0740) Prec@1 88.000 (88.263) Prec@5 99.000 (99.105) +2022-11-14 16:30:13,503 Test: [57/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0741) Prec@1 87.000 (88.241) Prec@5 98.000 (99.086) +2022-11-14 16:30:13,523 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0888 (0.0744) Prec@1 85.000 (88.186) Prec@5 100.000 (99.102) +2022-11-14 16:30:13,548 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0742) Prec@1 91.000 (88.233) Prec@5 99.000 (99.100) +2022-11-14 16:30:13,574 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0741) Prec@1 88.000 (88.230) Prec@5 99.000 (99.098) +2022-11-14 16:30:13,601 Test: [61/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0743) Prec@1 87.000 (88.210) Prec@5 100.000 (99.113) +2022-11-14 16:30:13,625 Test: [62/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0672 (0.0742) Prec@1 89.000 (88.222) Prec@5 100.000 (99.127) +2022-11-14 16:30:13,653 Test: [63/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0356 (0.0736) Prec@1 94.000 (88.312) Prec@5 100.000 (99.141) +2022-11-14 16:30:13,679 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0740) Prec@1 82.000 (88.215) Prec@5 97.000 (99.108) +2022-11-14 16:30:13,702 Test: [65/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0741) Prec@1 88.000 (88.212) Prec@5 98.000 (99.091) +2022-11-14 16:30:13,727 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0400 (0.0736) Prec@1 95.000 (88.313) Prec@5 99.000 (99.090) +2022-11-14 16:30:13,753 Test: [67/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0735) Prec@1 87.000 (88.294) Prec@5 100.000 (99.103) +2022-11-14 16:30:13,778 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0734) Prec@1 89.000 (88.304) Prec@5 99.000 (99.101) +2022-11-14 16:30:13,801 Test: [69/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0734) Prec@1 88.000 (88.300) Prec@5 98.000 (99.086) +2022-11-14 16:30:13,824 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0736) Prec@1 89.000 (88.310) Prec@5 96.000 (99.042) +2022-11-14 16:30:13,852 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0457 (0.0732) Prec@1 91.000 (88.347) Prec@5 100.000 (99.056) +2022-11-14 16:30:13,875 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0370 (0.0727) Prec@1 95.000 (88.438) Prec@5 99.000 (99.055) +2022-11-14 16:30:13,895 Test: [73/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0338 (0.0722) Prec@1 95.000 (88.527) Prec@5 99.000 (99.054) +2022-11-14 16:30:13,914 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0926 (0.0724) Prec@1 86.000 (88.493) Prec@5 99.000 (99.053) +2022-11-14 16:30:13,935 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0723) Prec@1 90.000 (88.513) Prec@5 98.000 (99.039) +2022-11-14 16:30:13,950 Test: [76/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0724) Prec@1 88.000 (88.506) Prec@5 98.000 (99.026) +2022-11-14 16:30:13,969 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.0728) Prec@1 84.000 (88.449) Prec@5 100.000 (99.038) +2022-11-14 16:30:13,988 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0729) Prec@1 88.000 (88.443) Prec@5 100.000 (99.051) +2022-11-14 16:30:14,007 Test: [79/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0673 (0.0728) Prec@1 90.000 (88.463) Prec@5 100.000 (99.062) +2022-11-14 16:30:14,025 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0994 (0.0731) Prec@1 85.000 (88.420) Prec@5 99.000 (99.062) +2022-11-14 16:30:14,044 Test: [81/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0732) Prec@1 89.000 (88.427) Prec@5 100.000 (99.073) +2022-11-14 16:30:14,060 Test: [82/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0962 (0.0734) Prec@1 84.000 (88.373) Prec@5 99.000 (99.072) +2022-11-14 16:30:14,080 Test: [83/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0862 (0.0736) Prec@1 87.000 (88.357) Prec@5 99.000 (99.071) +2022-11-14 16:30:14,098 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0739) Prec@1 84.000 (88.306) Prec@5 100.000 (99.082) +2022-11-14 16:30:14,117 Test: [85/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1210 (0.0744) Prec@1 80.000 (88.209) Prec@5 100.000 (99.093) +2022-11-14 16:30:14,138 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0776 (0.0744) Prec@1 88.000 (88.207) Prec@5 100.000 (99.103) +2022-11-14 16:30:14,157 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0745) Prec@1 84.000 (88.159) Prec@5 99.000 (99.102) +2022-11-14 16:30:14,177 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0693 (0.0745) Prec@1 89.000 (88.169) Prec@5 99.000 (99.101) +2022-11-14 16:30:14,195 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0745) Prec@1 88.000 (88.167) Prec@5 100.000 (99.111) +2022-11-14 16:30:14,213 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0434 (0.0741) Prec@1 91.000 (88.198) Prec@5 100.000 (99.121) +2022-11-14 16:30:14,232 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0616 (0.0740) Prec@1 90.000 (88.217) Prec@5 99.000 (99.120) +2022-11-14 16:30:14,250 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0742) Prec@1 87.000 (88.204) Prec@5 99.000 (99.118) +2022-11-14 16:30:14,269 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0743) Prec@1 86.000 (88.181) Prec@5 99.000 (99.117) +2022-11-14 16:30:14,288 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0743) Prec@1 88.000 (88.179) Prec@5 98.000 (99.105) +2022-11-14 16:30:14,305 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0742) Prec@1 90.000 (88.198) Prec@5 99.000 (99.104) +2022-11-14 16:30:14,325 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0488 (0.0739) Prec@1 92.000 (88.237) Prec@5 99.000 (99.103) +2022-11-14 16:30:14,347 Test: [97/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0739) Prec@1 88.000 (88.235) Prec@5 98.000 (99.092) +2022-11-14 16:30:14,367 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0970 (0.0742) Prec@1 84.000 (88.192) Prec@5 99.000 (99.091) +2022-11-14 16:30:14,387 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0650 (0.0741) Prec@1 91.000 (88.220) Prec@5 99.000 (99.090) +2022-11-14 16:30:14,454 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:30:14,814 Epoch: [351][0/500] Time 0.025 (0.025) Data 0.261 (0.261) Loss 0.0509 (0.0509) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 16:30:15,420 Epoch: [351][10/500] Time 0.065 (0.052) Data 0.002 (0.026) Loss 0.0227 (0.0368) Prec@1 96.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:30:16,006 Epoch: [351][20/500] Time 0.059 (0.052) Data 0.002 (0.014) Loss 0.0357 (0.0365) Prec@1 94.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:30:16,694 Epoch: [351][30/500] Time 0.069 (0.055) Data 0.002 (0.011) Loss 0.0346 (0.0360) Prec@1 94.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:30:17,303 Epoch: [351][40/500] Time 0.037 (0.055) Data 0.002 (0.009) Loss 0.0223 (0.0333) Prec@1 96.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 16:30:17,935 Epoch: [351][50/500] Time 0.079 (0.055) Data 0.002 (0.007) Loss 0.0306 (0.0328) Prec@1 96.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:30:18,600 Epoch: [351][60/500] Time 0.082 (0.055) Data 0.002 (0.006) Loss 0.0440 (0.0344) Prec@1 93.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:30:19,173 Epoch: [351][70/500] Time 0.065 (0.055) Data 0.002 (0.006) Loss 0.0291 (0.0338) Prec@1 95.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 16:30:19,744 Epoch: [351][80/500] Time 0.049 (0.054) Data 0.002 (0.005) Loss 0.0298 (0.0333) Prec@1 96.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 16:30:20,344 Epoch: [351][90/500] Time 0.063 (0.054) Data 0.002 (0.005) Loss 0.0308 (0.0331) Prec@1 94.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 16:30:20,964 Epoch: [351][100/500] Time 0.054 (0.054) Data 0.002 (0.005) Loss 0.0551 (0.0351) Prec@1 89.000 (94.182) Prec@5 100.000 (99.909) +2022-11-14 16:30:21,573 Epoch: [351][110/500] Time 0.052 (0.055) Data 0.002 (0.004) Loss 0.0337 (0.0350) Prec@1 94.000 (94.167) Prec@5 99.000 (99.833) +2022-11-14 16:30:22,136 Epoch: [351][120/500] Time 0.054 (0.054) Data 0.002 (0.004) Loss 0.0312 (0.0347) Prec@1 94.000 (94.154) Prec@5 100.000 (99.846) +2022-11-14 16:30:22,744 Epoch: [351][130/500] Time 0.062 (0.054) Data 0.003 (0.004) Loss 0.0435 (0.0353) Prec@1 92.000 (94.000) Prec@5 100.000 (99.857) +2022-11-14 16:30:23,326 Epoch: [351][140/500] Time 0.054 (0.054) Data 0.002 (0.004) Loss 0.0297 (0.0349) Prec@1 95.000 (94.067) Prec@5 100.000 (99.867) +2022-11-14 16:30:23,895 Epoch: [351][150/500] Time 0.056 (0.054) Data 0.002 (0.004) Loss 0.0346 (0.0349) Prec@1 94.000 (94.062) Prec@5 100.000 (99.875) +2022-11-14 16:30:24,570 Epoch: [351][160/500] Time 0.069 (0.054) Data 0.002 (0.004) Loss 0.0457 (0.0355) Prec@1 92.000 (93.941) Prec@5 99.000 (99.824) +2022-11-14 16:30:25,128 Epoch: [351][170/500] Time 0.053 (0.054) Data 0.002 (0.004) Loss 0.0243 (0.0349) Prec@1 96.000 (94.056) Prec@5 100.000 (99.833) +2022-11-14 16:30:25,733 Epoch: [351][180/500] Time 0.056 (0.054) Data 0.002 (0.004) Loss 0.0325 (0.0348) Prec@1 95.000 (94.105) Prec@5 99.000 (99.789) +2022-11-14 16:30:26,318 Epoch: [351][190/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0119 (0.0336) Prec@1 98.000 (94.300) Prec@5 100.000 (99.800) +2022-11-14 16:30:26,881 Epoch: [351][200/500] Time 0.056 (0.054) Data 0.002 (0.003) Loss 0.0267 (0.0333) Prec@1 94.000 (94.286) Prec@5 100.000 (99.810) +2022-11-14 16:30:27,533 Epoch: [351][210/500] Time 0.064 (0.054) Data 0.003 (0.003) Loss 0.0186 (0.0326) Prec@1 97.000 (94.409) Prec@5 100.000 (99.818) +2022-11-14 16:30:28,089 Epoch: [351][220/500] Time 0.057 (0.054) Data 0.002 (0.003) Loss 0.0368 (0.0328) Prec@1 94.000 (94.391) Prec@5 98.000 (99.739) +2022-11-14 16:30:28,654 Epoch: [351][230/500] Time 0.057 (0.054) Data 0.002 (0.003) Loss 0.0266 (0.0326) Prec@1 96.000 (94.458) Prec@5 100.000 (99.750) +2022-11-14 16:30:29,237 Epoch: [351][240/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0192 (0.0320) Prec@1 97.000 (94.560) Prec@5 100.000 (99.760) +2022-11-14 16:30:29,890 Epoch: [351][250/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0393 (0.0323) Prec@1 94.000 (94.538) Prec@5 100.000 (99.769) +2022-11-14 16:30:30,446 Epoch: [351][260/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0081 (0.0314) Prec@1 99.000 (94.704) Prec@5 100.000 (99.778) +2022-11-14 16:30:31,006 Epoch: [351][270/500] Time 0.052 (0.054) Data 0.002 (0.003) Loss 0.0347 (0.0315) Prec@1 95.000 (94.714) Prec@5 99.000 (99.750) +2022-11-14 16:30:31,578 Epoch: [351][280/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0207 (0.0312) Prec@1 97.000 (94.793) Prec@5 100.000 (99.759) +2022-11-14 16:30:32,147 Epoch: [351][290/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0198 (0.0308) Prec@1 97.000 (94.867) Prec@5 100.000 (99.767) +2022-11-14 16:30:32,732 Epoch: [351][300/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0408 (0.0311) Prec@1 93.000 (94.806) Prec@5 100.000 (99.774) +2022-11-14 16:30:33,321 Epoch: [351][310/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0496 (0.0317) Prec@1 92.000 (94.719) Prec@5 100.000 (99.781) +2022-11-14 16:30:33,936 Epoch: [351][320/500] Time 0.068 (0.053) Data 0.002 (0.003) Loss 0.0116 (0.0311) Prec@1 97.000 (94.788) Prec@5 100.000 (99.788) +2022-11-14 16:30:34,556 Epoch: [351][330/500] Time 0.060 (0.053) Data 0.002 (0.003) Loss 0.0240 (0.0309) Prec@1 96.000 (94.824) Prec@5 100.000 (99.794) +2022-11-14 16:30:35,147 Epoch: [351][340/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0199 (0.0306) Prec@1 98.000 (94.914) Prec@5 100.000 (99.800) +2022-11-14 16:30:35,716 Epoch: [351][350/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0321 (0.0306) Prec@1 96.000 (94.944) Prec@5 100.000 (99.806) +2022-11-14 16:30:36,335 Epoch: [351][360/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0167 (0.0302) Prec@1 98.000 (95.027) Prec@5 100.000 (99.811) +2022-11-14 16:30:37,012 Epoch: [351][370/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0152 (0.0298) Prec@1 98.000 (95.105) Prec@5 100.000 (99.816) +2022-11-14 16:30:37,603 Epoch: [351][380/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0120 (0.0294) Prec@1 98.000 (95.179) Prec@5 100.000 (99.821) +2022-11-14 16:30:38,276 Epoch: [351][390/500] Time 0.075 (0.054) Data 0.002 (0.003) Loss 0.0243 (0.0292) Prec@1 97.000 (95.225) Prec@5 100.000 (99.825) +2022-11-14 16:30:38,841 Epoch: [351][400/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0329 (0.0293) Prec@1 93.000 (95.171) Prec@5 100.000 (99.829) +2022-11-14 16:30:39,442 Epoch: [351][410/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0422 (0.0296) Prec@1 94.000 (95.143) Prec@5 100.000 (99.833) +2022-11-14 16:30:40,068 Epoch: [351][420/500] Time 0.061 (0.054) Data 0.003 (0.003) Loss 0.0329 (0.0297) Prec@1 94.000 (95.116) Prec@5 100.000 (99.837) +2022-11-14 16:30:40,646 Epoch: [351][430/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0395 (0.0299) Prec@1 94.000 (95.091) Prec@5 99.000 (99.818) +2022-11-14 16:30:41,307 Epoch: [351][440/500] Time 0.063 (0.054) Data 0.002 (0.003) Loss 0.0297 (0.0299) Prec@1 96.000 (95.111) Prec@5 99.000 (99.800) +2022-11-14 16:30:41,887 Epoch: [351][450/500] Time 0.045 (0.054) Data 0.002 (0.003) Loss 0.0325 (0.0300) Prec@1 93.000 (95.065) Prec@5 100.000 (99.804) +2022-11-14 16:30:42,468 Epoch: [351][460/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0337 (0.0301) Prec@1 94.000 (95.043) Prec@5 100.000 (99.809) +2022-11-14 16:30:43,040 Epoch: [351][470/500] Time 0.051 (0.054) Data 0.003 (0.003) Loss 0.0161 (0.0298) Prec@1 97.000 (95.083) Prec@5 100.000 (99.812) +2022-11-14 16:30:43,623 Epoch: [351][480/500] Time 0.060 (0.054) Data 0.002 (0.003) Loss 0.0292 (0.0298) Prec@1 96.000 (95.102) Prec@5 99.000 (99.796) +2022-11-14 16:30:44,270 Epoch: [351][490/500] Time 0.064 (0.054) Data 0.002 (0.003) Loss 0.0345 (0.0299) Prec@1 94.000 (95.080) Prec@5 100.000 (99.800) +2022-11-14 16:30:44,798 Epoch: [351][499/500] Time 0.061 (0.054) Data 0.002 (0.003) Loss 0.0438 (0.0301) Prec@1 94.000 (95.059) Prec@5 100.000 (99.804) +2022-11-14 16:30:45,130 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0656 (0.0656) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:30:45,143 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0679 (0.0667) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:30:45,152 Test: [2/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0786 (0.0707) Prec@1 87.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:30:45,170 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0630 (0.0688) Prec@1 89.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 16:30:45,181 Test: [4/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0888 (0.0728) Prec@1 82.000 (86.800) Prec@5 99.000 (99.600) +2022-11-14 16:30:45,193 Test: [5/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0631 (0.0712) Prec@1 91.000 (87.500) Prec@5 100.000 (99.667) +2022-11-14 16:30:45,206 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0919 (0.0741) Prec@1 86.000 (87.286) Prec@5 98.000 (99.429) +2022-11-14 16:30:45,224 Test: [7/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1037 (0.0778) Prec@1 83.000 (86.750) Prec@5 100.000 (99.500) +2022-11-14 16:30:45,240 Test: [8/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0819 (0.0783) Prec@1 87.000 (86.778) Prec@5 99.000 (99.444) +2022-11-14 16:30:45,253 Test: [9/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0851 (0.0790) Prec@1 87.000 (86.800) Prec@5 98.000 (99.300) +2022-11-14 16:30:45,270 Test: [10/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0779) Prec@1 89.000 (87.000) Prec@5 100.000 (99.364) +2022-11-14 16:30:45,289 Test: [11/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0851 (0.0785) Prec@1 87.000 (87.000) Prec@5 99.000 (99.333) +2022-11-14 16:30:45,307 Test: [12/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0531 (0.0765) Prec@1 93.000 (87.462) Prec@5 99.000 (99.308) +2022-11-14 16:30:45,326 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0759) Prec@1 90.000 (87.643) Prec@5 99.000 (99.286) +2022-11-14 16:30:45,343 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0747) Prec@1 90.000 (87.800) Prec@5 100.000 (99.333) +2022-11-14 16:30:45,366 Test: [15/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0744) Prec@1 90.000 (87.938) Prec@5 100.000 (99.375) +2022-11-14 16:30:45,384 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0509 (0.0730) Prec@1 94.000 (88.294) Prec@5 99.000 (99.353) +2022-11-14 16:30:45,409 Test: [17/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1290 (0.0761) Prec@1 80.000 (87.833) Prec@5 100.000 (99.389) +2022-11-14 16:30:45,431 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0903 (0.0769) Prec@1 84.000 (87.632) Prec@5 99.000 (99.368) +2022-11-14 16:30:45,453 Test: [19/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0931 (0.0777) Prec@1 84.000 (87.450) Prec@5 97.000 (99.250) +2022-11-14 16:30:45,471 Test: [20/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0673 (0.0772) Prec@1 91.000 (87.619) Prec@5 100.000 (99.286) +2022-11-14 16:30:45,492 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0990 (0.0782) Prec@1 82.000 (87.364) Prec@5 96.000 (99.136) +2022-11-14 16:30:45,512 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0937 (0.0788) Prec@1 85.000 (87.261) Prec@5 98.000 (99.087) +2022-11-14 16:30:45,532 Test: [23/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0956 (0.0795) Prec@1 86.000 (87.208) Prec@5 100.000 (99.125) +2022-11-14 16:30:45,554 Test: [24/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0954 (0.0802) Prec@1 86.000 (87.160) Prec@5 100.000 (99.160) +2022-11-14 16:30:45,576 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0961 (0.0808) Prec@1 85.000 (87.077) Prec@5 99.000 (99.154) +2022-11-14 16:30:45,596 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0589 (0.0800) Prec@1 90.000 (87.185) Prec@5 100.000 (99.185) +2022-11-14 16:30:45,613 Test: [27/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0554 (0.0791) Prec@1 92.000 (87.357) Prec@5 100.000 (99.214) +2022-11-14 16:30:45,631 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0788) Prec@1 89.000 (87.414) Prec@5 99.000 (99.207) +2022-11-14 16:30:45,651 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0603 (0.0782) Prec@1 90.000 (87.500) Prec@5 99.000 (99.200) +2022-11-14 16:30:45,669 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0779) Prec@1 89.000 (87.548) Prec@5 100.000 (99.226) +2022-11-14 16:30:45,686 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1033 (0.0786) Prec@1 84.000 (87.438) Prec@5 99.000 (99.219) +2022-11-14 16:30:45,709 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0784) Prec@1 86.000 (87.394) Prec@5 100.000 (99.242) +2022-11-14 16:30:45,727 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0786) Prec@1 86.000 (87.353) Prec@5 100.000 (99.265) +2022-11-14 16:30:45,747 Test: [34/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0787) Prec@1 88.000 (87.371) Prec@5 99.000 (99.257) +2022-11-14 16:30:45,770 Test: [35/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0557 (0.0781) Prec@1 92.000 (87.500) Prec@5 99.000 (99.250) +2022-11-14 16:30:45,792 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0781) Prec@1 87.000 (87.486) Prec@5 97.000 (99.189) +2022-11-14 16:30:45,813 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1049 (0.0788) Prec@1 83.000 (87.368) Prec@5 99.000 (99.184) +2022-11-14 16:30:45,833 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0430 (0.0779) Prec@1 95.000 (87.564) Prec@5 99.000 (99.179) +2022-11-14 16:30:45,854 Test: [39/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0775) Prec@1 90.000 (87.625) Prec@5 99.000 (99.175) +2022-11-14 16:30:45,874 Test: [40/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0975 (0.0780) Prec@1 85.000 (87.561) Prec@5 97.000 (99.122) +2022-11-14 16:30:45,895 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0822 (0.0781) Prec@1 87.000 (87.548) Prec@5 98.000 (99.095) +2022-11-14 16:30:45,919 Test: [42/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0446 (0.0773) Prec@1 92.000 (87.651) Prec@5 99.000 (99.093) +2022-11-14 16:30:45,938 Test: [43/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0817 (0.0774) Prec@1 87.000 (87.636) Prec@5 99.000 (99.091) +2022-11-14 16:30:45,959 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0772) Prec@1 91.000 (87.711) Prec@5 99.000 (99.089) +2022-11-14 16:30:45,976 Test: [45/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0772) Prec@1 88.000 (87.717) Prec@5 100.000 (99.109) +2022-11-14 16:30:45,998 Test: [46/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0771) Prec@1 88.000 (87.723) Prec@5 99.000 (99.106) +2022-11-14 16:30:46,021 Test: [47/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0982 (0.0776) Prec@1 83.000 (87.625) Prec@5 99.000 (99.104) +2022-11-14 16:30:46,039 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0563 (0.0771) Prec@1 90.000 (87.673) Prec@5 100.000 (99.122) +2022-11-14 16:30:46,056 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1085 (0.0777) Prec@1 78.000 (87.480) Prec@5 100.000 (99.140) +2022-11-14 16:30:46,077 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0512 (0.0772) Prec@1 90.000 (87.529) Prec@5 100.000 (99.157) +2022-11-14 16:30:46,097 Test: [51/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0900 (0.0775) Prec@1 86.000 (87.500) Prec@5 99.000 (99.154) +2022-11-14 16:30:46,117 Test: [52/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0773) Prec@1 89.000 (87.528) Prec@5 100.000 (99.170) +2022-11-14 16:30:46,139 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0769) Prec@1 90.000 (87.574) Prec@5 99.000 (99.167) +2022-11-14 16:30:46,157 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0770) Prec@1 87.000 (87.564) Prec@5 100.000 (99.182) +2022-11-14 16:30:46,179 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0768) Prec@1 89.000 (87.589) Prec@5 99.000 (99.179) +2022-11-14 16:30:46,200 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0768) Prec@1 84.000 (87.526) Prec@5 100.000 (99.193) +2022-11-14 16:30:46,215 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0768) Prec@1 89.000 (87.552) Prec@5 99.000 (99.190) +2022-11-14 16:30:46,236 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0768) Prec@1 88.000 (87.559) Prec@5 100.000 (99.203) +2022-11-14 16:30:46,252 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0767) Prec@1 87.000 (87.550) Prec@5 100.000 (99.217) +2022-11-14 16:30:46,271 Test: [60/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0771 (0.0767) Prec@1 90.000 (87.590) Prec@5 100.000 (99.230) +2022-11-14 16:30:46,291 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0766) Prec@1 87.000 (87.581) Prec@5 100.000 (99.242) +2022-11-14 16:30:46,312 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0564 (0.0763) Prec@1 90.000 (87.619) Prec@5 100.000 (99.254) +2022-11-14 16:30:46,334 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0278 (0.0755) Prec@1 95.000 (87.734) Prec@5 100.000 (99.266) +2022-11-14 16:30:46,354 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0969 (0.0758) Prec@1 84.000 (87.677) Prec@5 98.000 (99.246) +2022-11-14 16:30:46,372 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0759) Prec@1 88.000 (87.682) Prec@5 99.000 (99.242) +2022-11-14 16:30:46,390 Test: [66/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0352 (0.0753) Prec@1 95.000 (87.791) Prec@5 99.000 (99.239) +2022-11-14 16:30:46,409 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0753) Prec@1 88.000 (87.794) Prec@5 99.000 (99.235) +2022-11-14 16:30:46,429 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0733 (0.0752) Prec@1 87.000 (87.783) Prec@5 100.000 (99.246) +2022-11-14 16:30:46,448 Test: [69/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0751) Prec@1 88.000 (87.786) Prec@5 99.000 (99.243) +2022-11-14 16:30:46,467 Test: [70/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0963 (0.0754) Prec@1 86.000 (87.761) Prec@5 98.000 (99.225) +2022-11-14 16:30:46,489 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0752) Prec@1 91.000 (87.806) Prec@5 99.000 (99.222) +2022-11-14 16:30:46,507 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0455 (0.0748) Prec@1 95.000 (87.904) Prec@5 100.000 (99.233) +2022-11-14 16:30:46,527 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0373 (0.0743) Prec@1 95.000 (88.000) Prec@5 100.000 (99.243) +2022-11-14 16:30:46,548 Test: [74/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1091 (0.0747) Prec@1 84.000 (87.947) Prec@5 98.000 (99.227) +2022-11-14 16:30:46,568 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0744) Prec@1 92.000 (88.000) Prec@5 97.000 (99.197) +2022-11-14 16:30:46,585 Test: [76/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0744) Prec@1 90.000 (88.026) Prec@5 98.000 (99.182) +2022-11-14 16:30:46,603 Test: [77/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0744) Prec@1 89.000 (88.038) Prec@5 100.000 (99.192) +2022-11-14 16:30:46,625 Test: [78/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0690 (0.0744) Prec@1 90.000 (88.063) Prec@5 100.000 (99.203) +2022-11-14 16:30:46,645 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0743) Prec@1 90.000 (88.088) Prec@5 100.000 (99.213) +2022-11-14 16:30:46,665 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0743) Prec@1 89.000 (88.099) Prec@5 98.000 (99.198) +2022-11-14 16:30:46,687 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1008 (0.0746) Prec@1 83.000 (88.037) Prec@5 99.000 (99.195) +2022-11-14 16:30:46,709 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0975 (0.0749) Prec@1 85.000 (88.000) Prec@5 98.000 (99.181) +2022-11-14 16:30:46,728 Test: [83/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0570 (0.0747) Prec@1 91.000 (88.036) Prec@5 99.000 (99.179) +2022-11-14 16:30:46,750 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0748) Prec@1 88.000 (88.035) Prec@5 100.000 (99.188) +2022-11-14 16:30:46,768 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1071 (0.0752) Prec@1 84.000 (87.988) Prec@5 99.000 (99.186) +2022-11-14 16:30:46,785 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0752) Prec@1 88.000 (87.989) Prec@5 100.000 (99.195) +2022-11-14 16:30:46,803 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0750) Prec@1 91.000 (88.023) Prec@5 99.000 (99.193) +2022-11-14 16:30:46,825 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0750) Prec@1 89.000 (88.034) Prec@5 100.000 (99.202) +2022-11-14 16:30:46,847 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0750) Prec@1 88.000 (88.033) Prec@5 100.000 (99.211) +2022-11-14 16:30:46,868 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0749) Prec@1 91.000 (88.066) Prec@5 100.000 (99.220) +2022-11-14 16:30:46,891 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0747) Prec@1 93.000 (88.120) Prec@5 99.000 (99.217) +2022-11-14 16:30:46,910 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0851 (0.0748) Prec@1 86.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 16:30:46,929 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0747) Prec@1 89.000 (88.106) Prec@5 100.000 (99.234) +2022-11-14 16:30:46,945 Test: [94/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0749) Prec@1 84.000 (88.063) Prec@5 99.000 (99.232) +2022-11-14 16:30:46,965 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0748) Prec@1 88.000 (88.062) Prec@5 99.000 (99.229) +2022-11-14 16:30:46,984 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0425 (0.0745) Prec@1 94.000 (88.124) Prec@5 99.000 (99.227) +2022-11-14 16:30:47,006 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0747) Prec@1 84.000 (88.082) Prec@5 100.000 (99.235) +2022-11-14 16:30:47,023 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0749) Prec@1 83.000 (88.030) Prec@5 99.000 (99.232) +2022-11-14 16:30:47,044 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0748) Prec@1 90.000 (88.050) Prec@5 100.000 (99.240) +2022-11-14 16:30:47,104 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:30:47,451 Epoch: [352][0/500] Time 0.031 (0.031) Data 0.256 (0.256) Loss 0.0295 (0.0295) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:30:47,951 Epoch: [352][10/500] Time 0.059 (0.043) Data 0.002 (0.025) Loss 0.0121 (0.0208) Prec@1 98.000 (96.500) Prec@5 100.000 (99.500) +2022-11-14 16:30:48,531 Epoch: [352][20/500] Time 0.049 (0.047) Data 0.002 (0.014) Loss 0.0444 (0.0287) Prec@1 92.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:30:49,102 Epoch: [352][30/500] Time 0.058 (0.049) Data 0.002 (0.010) Loss 0.0249 (0.0277) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:30:49,677 Epoch: [352][40/500] Time 0.048 (0.049) Data 0.002 (0.008) Loss 0.0203 (0.0262) Prec@1 97.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 16:30:50,333 Epoch: [352][50/500] Time 0.049 (0.051) Data 0.003 (0.007) Loss 0.0475 (0.0298) Prec@1 93.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 16:30:50,900 Epoch: [352][60/500] Time 0.048 (0.051) Data 0.002 (0.006) Loss 0.0270 (0.0294) Prec@1 96.000 (95.143) Prec@5 100.000 (99.714) +2022-11-14 16:30:51,469 Epoch: [352][70/500] Time 0.056 (0.051) Data 0.002 (0.006) Loss 0.0229 (0.0286) Prec@1 97.000 (95.375) Prec@5 100.000 (99.750) +2022-11-14 16:30:52,075 Epoch: [352][80/500] Time 0.059 (0.051) Data 0.002 (0.005) Loss 0.0387 (0.0297) Prec@1 92.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 16:30:52,662 Epoch: [352][90/500] Time 0.044 (0.051) Data 0.002 (0.005) Loss 0.0288 (0.0296) Prec@1 95.000 (95.000) Prec@5 100.000 (99.700) +2022-11-14 16:30:53,241 Epoch: [352][100/500] Time 0.056 (0.052) Data 0.002 (0.005) Loss 0.0104 (0.0279) Prec@1 98.000 (95.273) Prec@5 100.000 (99.727) +2022-11-14 16:30:53,909 Epoch: [352][110/500] Time 0.051 (0.052) Data 0.002 (0.004) Loss 0.0195 (0.0272) Prec@1 97.000 (95.417) Prec@5 100.000 (99.750) +2022-11-14 16:30:54,493 Epoch: [352][120/500] Time 0.065 (0.052) Data 0.002 (0.004) Loss 0.0266 (0.0271) Prec@1 96.000 (95.462) Prec@5 99.000 (99.692) +2022-11-14 16:30:55,075 Epoch: [352][130/500] Time 0.067 (0.052) Data 0.002 (0.004) Loss 0.0192 (0.0266) Prec@1 96.000 (95.500) Prec@5 100.000 (99.714) +2022-11-14 16:30:55,667 Epoch: [352][140/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0106 (0.0255) Prec@1 98.000 (95.667) Prec@5 99.000 (99.667) +2022-11-14 16:30:56,279 Epoch: [352][150/500] Time 0.047 (0.052) Data 0.002 (0.004) Loss 0.0220 (0.0253) Prec@1 97.000 (95.750) Prec@5 100.000 (99.688) +2022-11-14 16:30:56,842 Epoch: [352][160/500] Time 0.051 (0.052) Data 0.002 (0.004) Loss 0.0570 (0.0271) Prec@1 91.000 (95.471) Prec@5 99.000 (99.647) +2022-11-14 16:30:57,410 Epoch: [352][170/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0252 (0.0270) Prec@1 96.000 (95.500) Prec@5 100.000 (99.667) +2022-11-14 16:30:57,984 Epoch: [352][180/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0328 (0.0273) Prec@1 96.000 (95.526) Prec@5 99.000 (99.632) +2022-11-14 16:30:58,563 Epoch: [352][190/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0490 (0.0284) Prec@1 92.000 (95.350) Prec@5 100.000 (99.650) +2022-11-14 16:30:59,217 Epoch: [352][200/500] Time 0.040 (0.052) Data 0.002 (0.003) Loss 0.0468 (0.0293) Prec@1 92.000 (95.190) Prec@5 100.000 (99.667) +2022-11-14 16:30:59,807 Epoch: [352][210/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0289 (0.0293) Prec@1 95.000 (95.182) Prec@5 100.000 (99.682) +2022-11-14 16:31:00,380 Epoch: [352][220/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0151 (0.0287) Prec@1 97.000 (95.261) Prec@5 100.000 (99.696) +2022-11-14 16:31:00,966 Epoch: [352][230/500] Time 0.066 (0.052) Data 0.002 (0.003) Loss 0.0490 (0.0295) Prec@1 92.000 (95.125) Prec@5 100.000 (99.708) +2022-11-14 16:31:01,578 Epoch: [352][240/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0199 (0.0291) Prec@1 98.000 (95.240) Prec@5 100.000 (99.720) +2022-11-14 16:31:02,161 Epoch: [352][250/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0172 (0.0287) Prec@1 98.000 (95.346) Prec@5 100.000 (99.731) +2022-11-14 16:31:02,745 Epoch: [352][260/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0235 (0.0285) Prec@1 96.000 (95.370) Prec@5 100.000 (99.741) +2022-11-14 16:31:03,321 Epoch: [352][270/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0160 (0.0280) Prec@1 97.000 (95.429) Prec@5 100.000 (99.750) +2022-11-14 16:31:04,003 Epoch: [352][280/500] Time 0.071 (0.053) Data 0.002 (0.003) Loss 0.0385 (0.0284) Prec@1 95.000 (95.414) Prec@5 100.000 (99.759) +2022-11-14 16:31:04,658 Epoch: [352][290/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0538 (0.0292) Prec@1 90.000 (95.233) Prec@5 100.000 (99.767) +2022-11-14 16:31:05,221 Epoch: [352][300/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0544 (0.0300) Prec@1 90.000 (95.065) Prec@5 99.000 (99.742) +2022-11-14 16:31:05,800 Epoch: [352][310/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0229 (0.0298) Prec@1 96.000 (95.094) Prec@5 100.000 (99.750) +2022-11-14 16:31:06,470 Epoch: [352][320/500] Time 0.083 (0.053) Data 0.002 (0.003) Loss 0.0398 (0.0301) Prec@1 94.000 (95.061) Prec@5 100.000 (99.758) +2022-11-14 16:31:07,464 Epoch: [352][330/500] Time 0.080 (0.054) Data 0.002 (0.003) Loss 0.0319 (0.0302) Prec@1 96.000 (95.088) Prec@5 100.000 (99.765) +2022-11-14 16:31:08,213 Epoch: [352][340/500] Time 0.074 (0.054) Data 0.002 (0.003) Loss 0.0343 (0.0303) Prec@1 93.000 (95.029) Prec@5 100.000 (99.771) +2022-11-14 16:31:08,998 Epoch: [352][350/500] Time 0.063 (0.055) Data 0.002 (0.003) Loss 0.0332 (0.0304) Prec@1 93.000 (94.972) Prec@5 99.000 (99.750) +2022-11-14 16:31:09,782 Epoch: [352][360/500] Time 0.084 (0.055) Data 0.002 (0.003) Loss 0.0463 (0.0308) Prec@1 90.000 (94.838) Prec@5 100.000 (99.757) +2022-11-14 16:31:10,570 Epoch: [352][370/500] Time 0.085 (0.056) Data 0.002 (0.003) Loss 0.0306 (0.0308) Prec@1 95.000 (94.842) Prec@5 100.000 (99.763) +2022-11-14 16:31:11,458 Epoch: [352][380/500] Time 0.137 (0.056) Data 0.002 (0.003) Loss 0.0175 (0.0305) Prec@1 98.000 (94.923) Prec@5 100.000 (99.769) +2022-11-14 16:31:12,266 Epoch: [352][390/500] Time 0.065 (0.057) Data 0.002 (0.003) Loss 0.0407 (0.0307) Prec@1 94.000 (94.900) Prec@5 100.000 (99.775) +2022-11-14 16:31:13,075 Epoch: [352][400/500] Time 0.075 (0.057) Data 0.002 (0.003) Loss 0.0313 (0.0307) Prec@1 96.000 (94.927) Prec@5 100.000 (99.780) +2022-11-14 16:31:13,847 Epoch: [352][410/500] Time 0.067 (0.057) Data 0.002 (0.003) Loss 0.0126 (0.0303) Prec@1 98.000 (95.000) Prec@5 100.000 (99.786) +2022-11-14 16:31:14,638 Epoch: [352][420/500] Time 0.068 (0.058) Data 0.003 (0.003) Loss 0.0207 (0.0301) Prec@1 97.000 (95.047) Prec@5 100.000 (99.791) +2022-11-14 16:31:15,402 Epoch: [352][430/500] Time 0.066 (0.058) Data 0.002 (0.003) Loss 0.0387 (0.0303) Prec@1 93.000 (95.000) Prec@5 100.000 (99.795) +2022-11-14 16:31:16,188 Epoch: [352][440/500] Time 0.078 (0.058) Data 0.002 (0.003) Loss 0.0334 (0.0303) Prec@1 96.000 (95.022) Prec@5 100.000 (99.800) +2022-11-14 16:31:16,999 Epoch: [352][450/500] Time 0.080 (0.059) Data 0.002 (0.003) Loss 0.0318 (0.0304) Prec@1 95.000 (95.022) Prec@5 100.000 (99.804) +2022-11-14 16:31:17,807 Epoch: [352][460/500] Time 0.076 (0.059) Data 0.002 (0.003) Loss 0.0317 (0.0304) Prec@1 95.000 (95.021) Prec@5 100.000 (99.809) +2022-11-14 16:31:18,615 Epoch: [352][470/500] Time 0.084 (0.059) Data 0.002 (0.003) Loss 0.0134 (0.0300) Prec@1 99.000 (95.104) Prec@5 99.000 (99.792) +2022-11-14 16:31:19,407 Epoch: [352][480/500] Time 0.071 (0.059) Data 0.002 (0.003) Loss 0.0386 (0.0302) Prec@1 94.000 (95.082) Prec@5 100.000 (99.796) +2022-11-14 16:31:20,200 Epoch: [352][490/500] Time 0.069 (0.060) Data 0.003 (0.003) Loss 0.0289 (0.0302) Prec@1 96.000 (95.100) Prec@5 99.000 (99.780) +2022-11-14 16:31:20,890 Epoch: [352][499/500] Time 0.082 (0.060) Data 0.002 (0.003) Loss 0.0269 (0.0301) Prec@1 96.000 (95.118) Prec@5 100.000 (99.784) +2022-11-14 16:31:21,215 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0625 (0.0625) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:31:21,225 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0654) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:31:21,236 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0648) Prec@1 89.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:31:21,246 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0812 (0.0689) Prec@1 89.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 16:31:21,257 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0777 (0.0706) Prec@1 88.000 (88.600) Prec@5 100.000 (99.600) +2022-11-14 16:31:21,266 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0329 (0.0644) Prec@1 94.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 16:31:21,276 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0636) Prec@1 90.000 (89.571) Prec@5 99.000 (99.571) +2022-11-14 16:31:21,286 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1027 (0.0685) Prec@1 80.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 16:31:21,296 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0685) Prec@1 91.000 (88.667) Prec@5 98.000 (99.444) +2022-11-14 16:31:21,307 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0691) Prec@1 88.000 (88.600) Prec@5 98.000 (99.300) +2022-11-14 16:31:21,320 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0686) Prec@1 89.000 (88.636) Prec@5 100.000 (99.364) +2022-11-14 16:31:21,333 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0688) Prec@1 89.000 (88.667) Prec@5 100.000 (99.417) +2022-11-14 16:31:21,347 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0677) Prec@1 93.000 (89.000) Prec@5 100.000 (99.462) +2022-11-14 16:31:21,359 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0683) Prec@1 86.000 (88.786) Prec@5 99.000 (99.429) +2022-11-14 16:31:21,374 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0680) Prec@1 89.000 (88.800) Prec@5 100.000 (99.467) +2022-11-14 16:31:21,389 Test: [15/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0673) Prec@1 92.000 (89.000) Prec@5 99.000 (99.438) +2022-11-14 16:31:21,402 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0656) Prec@1 95.000 (89.353) Prec@5 98.000 (99.353) +2022-11-14 16:31:21,416 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1158 (0.0684) Prec@1 82.000 (88.944) Prec@5 100.000 (99.389) +2022-11-14 16:31:21,430 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0705) Prec@1 82.000 (88.579) Prec@5 99.000 (99.368) +2022-11-14 16:31:21,445 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0718) Prec@1 83.000 (88.300) Prec@5 96.000 (99.200) +2022-11-14 16:31:21,458 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0717) Prec@1 88.000 (88.286) Prec@5 99.000 (99.190) +2022-11-14 16:31:21,471 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0729) Prec@1 86.000 (88.182) Prec@5 97.000 (99.091) +2022-11-14 16:31:21,487 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0733) Prec@1 88.000 (88.174) Prec@5 98.000 (99.043) +2022-11-14 16:31:21,502 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0733) Prec@1 87.000 (88.125) Prec@5 99.000 (99.042) +2022-11-14 16:31:21,516 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0729) Prec@1 91.000 (88.240) Prec@5 99.000 (99.040) +2022-11-14 16:31:21,530 Test: [25/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0735) Prec@1 88.000 (88.231) Prec@5 98.000 (99.000) +2022-11-14 16:31:21,544 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0727) Prec@1 91.000 (88.333) Prec@5 100.000 (99.037) +2022-11-14 16:31:21,560 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0723) Prec@1 92.000 (88.464) Prec@5 100.000 (99.071) +2022-11-14 16:31:21,575 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0725) Prec@1 88.000 (88.448) Prec@5 97.000 (99.000) +2022-11-14 16:31:21,588 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0730) Prec@1 87.000 (88.400) Prec@5 100.000 (99.033) +2022-11-14 16:31:21,603 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0730) Prec@1 89.000 (88.419) Prec@5 100.000 (99.065) +2022-11-14 16:31:21,617 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0728) Prec@1 89.000 (88.438) Prec@5 99.000 (99.062) +2022-11-14 16:31:21,634 Test: [32/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0724) Prec@1 89.000 (88.455) Prec@5 99.000 (99.061) +2022-11-14 16:31:21,650 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0731) Prec@1 82.000 (88.265) Prec@5 100.000 (99.088) +2022-11-14 16:31:21,665 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0733) Prec@1 87.000 (88.229) Prec@5 98.000 (99.057) +2022-11-14 16:31:21,680 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0734) Prec@1 88.000 (88.222) Prec@5 100.000 (99.083) +2022-11-14 16:31:21,695 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0731) Prec@1 90.000 (88.270) Prec@5 99.000 (99.081) +2022-11-14 16:31:21,709 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1155 (0.0742) Prec@1 83.000 (88.132) Prec@5 99.000 (99.079) +2022-11-14 16:31:21,723 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0736) Prec@1 94.000 (88.282) Prec@5 100.000 (99.103) +2022-11-14 16:31:21,735 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0733) Prec@1 90.000 (88.325) Prec@5 99.000 (99.100) +2022-11-14 16:31:21,748 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0742) Prec@1 83.000 (88.195) Prec@5 98.000 (99.073) +2022-11-14 16:31:21,763 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0746) Prec@1 84.000 (88.095) Prec@5 99.000 (99.071) +2022-11-14 16:31:21,778 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0362 (0.0737) Prec@1 93.000 (88.209) Prec@5 99.000 (99.070) +2022-11-14 16:31:21,793 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0740) Prec@1 87.000 (88.182) Prec@5 99.000 (99.068) +2022-11-14 16:31:21,806 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0737) Prec@1 90.000 (88.222) Prec@5 99.000 (99.067) +2022-11-14 16:31:21,819 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0744) Prec@1 82.000 (88.087) Prec@5 99.000 (99.065) +2022-11-14 16:31:21,835 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0741) Prec@1 92.000 (88.170) Prec@5 98.000 (99.043) +2022-11-14 16:31:21,849 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0746) Prec@1 84.000 (88.083) Prec@5 98.000 (99.021) +2022-11-14 16:31:21,862 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0742) Prec@1 92.000 (88.163) Prec@5 99.000 (99.020) +2022-11-14 16:31:21,875 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0747) Prec@1 84.000 (88.080) Prec@5 99.000 (99.020) +2022-11-14 16:31:21,887 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0748) Prec@1 89.000 (88.098) Prec@5 100.000 (99.039) +2022-11-14 16:31:21,902 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0751) Prec@1 85.000 (88.038) Prec@5 98.000 (99.019) +2022-11-14 16:31:21,917 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0746) Prec@1 90.000 (88.075) Prec@5 100.000 (99.038) +2022-11-14 16:31:21,932 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0744) Prec@1 91.000 (88.130) Prec@5 99.000 (99.037) +2022-11-14 16:31:21,945 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0745) Prec@1 85.000 (88.073) Prec@5 100.000 (99.055) +2022-11-14 16:31:21,960 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0747) Prec@1 86.000 (88.036) Prec@5 98.000 (99.036) +2022-11-14 16:31:21,975 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0746) Prec@1 87.000 (88.018) Prec@5 98.000 (99.018) +2022-11-14 16:31:21,991 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0746) Prec@1 91.000 (88.069) Prec@5 100.000 (99.034) +2022-11-14 16:31:22,007 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0747) Prec@1 90.000 (88.102) Prec@5 100.000 (99.051) +2022-11-14 16:31:22,022 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1016 (0.0751) Prec@1 84.000 (88.033) Prec@5 100.000 (99.067) +2022-11-14 16:31:22,036 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0753) Prec@1 88.000 (88.033) Prec@5 99.000 (99.066) +2022-11-14 16:31:22,049 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0751) Prec@1 87.000 (88.016) Prec@5 99.000 (99.065) +2022-11-14 16:31:22,063 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0751) Prec@1 87.000 (88.000) Prec@5 100.000 (99.079) +2022-11-14 16:31:22,075 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0335 (0.0744) Prec@1 93.000 (88.078) Prec@5 100.000 (99.094) +2022-11-14 16:31:22,090 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0747) Prec@1 84.000 (88.015) Prec@5 99.000 (99.092) +2022-11-14 16:31:22,104 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0747) Prec@1 87.000 (88.000) Prec@5 99.000 (99.091) +2022-11-14 16:31:22,117 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0746) Prec@1 91.000 (88.045) Prec@5 100.000 (99.104) +2022-11-14 16:31:22,131 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0746) Prec@1 90.000 (88.074) Prec@5 97.000 (99.074) +2022-11-14 16:31:22,146 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0744) Prec@1 91.000 (88.116) Prec@5 100.000 (99.087) +2022-11-14 16:31:22,159 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0745) Prec@1 86.000 (88.086) Prec@5 98.000 (99.071) +2022-11-14 16:31:22,171 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0748) Prec@1 87.000 (88.070) Prec@5 100.000 (99.085) +2022-11-14 16:31:22,185 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0746) Prec@1 89.000 (88.083) Prec@5 100.000 (99.097) +2022-11-14 16:31:22,200 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0366 (0.0741) Prec@1 96.000 (88.192) Prec@5 100.000 (99.110) +2022-11-14 16:31:22,214 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0739) Prec@1 90.000 (88.216) Prec@5 99.000 (99.108) +2022-11-14 16:31:22,228 Test: [74/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0741) Prec@1 86.000 (88.187) Prec@5 98.000 (99.093) +2022-11-14 16:31:22,244 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0742) Prec@1 87.000 (88.171) Prec@5 98.000 (99.079) +2022-11-14 16:31:22,257 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0742) Prec@1 88.000 (88.169) Prec@5 98.000 (99.065) +2022-11-14 16:31:22,271 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0995 (0.0745) Prec@1 82.000 (88.090) Prec@5 98.000 (99.051) +2022-11-14 16:31:22,286 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0746) Prec@1 89.000 (88.101) Prec@5 99.000 (99.051) +2022-11-14 16:31:22,300 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0744) Prec@1 90.000 (88.125) Prec@5 100.000 (99.062) +2022-11-14 16:31:22,313 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0745) Prec@1 88.000 (88.123) Prec@5 99.000 (99.062) +2022-11-14 16:31:22,326 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0745) Prec@1 87.000 (88.110) Prec@5 100.000 (99.073) +2022-11-14 16:31:22,340 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0746) Prec@1 87.000 (88.096) Prec@5 100.000 (99.084) +2022-11-14 16:31:22,353 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0746) Prec@1 90.000 (88.119) Prec@5 99.000 (99.083) +2022-11-14 16:31:22,367 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0746) Prec@1 86.000 (88.094) Prec@5 100.000 (99.094) +2022-11-14 16:31:22,382 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1267 (0.0752) Prec@1 79.000 (87.988) Prec@5 99.000 (99.093) +2022-11-14 16:31:22,396 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0750) Prec@1 89.000 (88.000) Prec@5 99.000 (99.092) +2022-11-14 16:31:22,409 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0750) Prec@1 88.000 (88.000) Prec@5 98.000 (99.080) +2022-11-14 16:31:22,423 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0751) Prec@1 87.000 (87.989) Prec@5 100.000 (99.090) +2022-11-14 16:31:22,438 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0750) Prec@1 92.000 (88.033) Prec@5 100.000 (99.100) +2022-11-14 16:31:22,453 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0747) Prec@1 93.000 (88.088) Prec@5 100.000 (99.110) +2022-11-14 16:31:22,465 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0745) Prec@1 92.000 (88.130) Prec@5 100.000 (99.120) +2022-11-14 16:31:22,479 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0746) Prec@1 88.000 (88.129) Prec@5 100.000 (99.129) +2022-11-14 16:31:22,493 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0747) Prec@1 84.000 (88.085) Prec@5 100.000 (99.138) +2022-11-14 16:31:22,507 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0746) Prec@1 89.000 (88.095) Prec@5 99.000 (99.137) +2022-11-14 16:31:22,522 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0746) Prec@1 91.000 (88.125) Prec@5 100.000 (99.146) +2022-11-14 16:31:22,537 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0743) Prec@1 91.000 (88.155) Prec@5 99.000 (99.144) +2022-11-14 16:31:22,552 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0913 (0.0744) Prec@1 88.000 (88.153) Prec@5 96.000 (99.112) +2022-11-14 16:31:22,568 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0746) Prec@1 85.000 (88.121) Prec@5 100.000 (99.121) +2022-11-14 16:31:22,583 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0746) Prec@1 89.000 (88.130) Prec@5 100.000 (99.130) +2022-11-14 16:31:22,652 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:31:23,020 Epoch: [353][0/500] Time 0.023 (0.023) Data 0.277 (0.277) Loss 0.0152 (0.0152) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:31:23,395 Epoch: [353][10/500] Time 0.043 (0.032) Data 0.002 (0.027) Loss 0.0470 (0.0311) Prec@1 94.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 16:31:23,815 Epoch: [353][20/500] Time 0.039 (0.034) Data 0.002 (0.015) Loss 0.0225 (0.0282) Prec@1 97.000 (96.333) Prec@5 100.000 (99.667) +2022-11-14 16:31:24,232 Epoch: [353][30/500] Time 0.038 (0.035) Data 0.002 (0.011) Loss 0.0286 (0.0283) Prec@1 95.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 16:31:24,652 Epoch: [353][40/500] Time 0.037 (0.036) Data 0.002 (0.009) Loss 0.0087 (0.0244) Prec@1 99.000 (96.600) Prec@5 99.000 (99.600) +2022-11-14 16:31:25,071 Epoch: [353][50/500] Time 0.039 (0.036) Data 0.002 (0.007) Loss 0.0376 (0.0266) Prec@1 95.000 (96.333) Prec@5 100.000 (99.667) +2022-11-14 16:31:25,497 Epoch: [353][60/500] Time 0.035 (0.036) Data 0.002 (0.006) Loss 0.0187 (0.0254) Prec@1 97.000 (96.429) Prec@5 100.000 (99.714) +2022-11-14 16:31:25,915 Epoch: [353][70/500] Time 0.044 (0.037) Data 0.002 (0.006) Loss 0.0352 (0.0267) Prec@1 94.000 (96.125) Prec@5 100.000 (99.750) +2022-11-14 16:31:26,352 Epoch: [353][80/500] Time 0.030 (0.037) Data 0.002 (0.005) Loss 0.0172 (0.0256) Prec@1 97.000 (96.222) Prec@5 100.000 (99.778) +2022-11-14 16:31:26,776 Epoch: [353][90/500] Time 0.035 (0.037) Data 0.002 (0.005) Loss 0.0145 (0.0245) Prec@1 97.000 (96.300) Prec@5 100.000 (99.800) +2022-11-14 16:31:27,529 Epoch: [353][100/500] Time 0.139 (0.039) Data 0.002 (0.005) Loss 0.0195 (0.0240) Prec@1 99.000 (96.545) Prec@5 100.000 (99.818) +2022-11-14 16:31:28,389 Epoch: [353][110/500] Time 0.084 (0.043) Data 0.002 (0.004) Loss 0.0252 (0.0241) Prec@1 96.000 (96.500) Prec@5 100.000 (99.833) +2022-11-14 16:31:29,175 Epoch: [353][120/500] Time 0.074 (0.045) Data 0.002 (0.004) Loss 0.0295 (0.0245) Prec@1 95.000 (96.385) Prec@5 100.000 (99.846) +2022-11-14 16:31:29,995 Epoch: [353][130/500] Time 0.072 (0.047) Data 0.002 (0.004) Loss 0.0160 (0.0239) Prec@1 98.000 (96.500) Prec@5 100.000 (99.857) +2022-11-14 16:31:30,805 Epoch: [353][140/500] Time 0.082 (0.049) Data 0.002 (0.004) Loss 0.0480 (0.0255) Prec@1 94.000 (96.333) Prec@5 100.000 (99.867) +2022-11-14 16:31:31,635 Epoch: [353][150/500] Time 0.082 (0.051) Data 0.002 (0.004) Loss 0.0386 (0.0264) Prec@1 94.000 (96.188) Prec@5 100.000 (99.875) +2022-11-14 16:31:32,448 Epoch: [353][160/500] Time 0.077 (0.052) Data 0.002 (0.004) Loss 0.0073 (0.0252) Prec@1 99.000 (96.353) Prec@5 100.000 (99.882) +2022-11-14 16:31:33,211 Epoch: [353][170/500] Time 0.068 (0.053) Data 0.002 (0.004) Loss 0.0568 (0.0270) Prec@1 92.000 (96.111) Prec@5 100.000 (99.889) +2022-11-14 16:31:33,998 Epoch: [353][180/500] Time 0.071 (0.054) Data 0.002 (0.004) Loss 0.0191 (0.0266) Prec@1 98.000 (96.211) Prec@5 100.000 (99.895) +2022-11-14 16:31:34,921 Epoch: [353][190/500] Time 0.082 (0.055) Data 0.002 (0.003) Loss 0.0348 (0.0270) Prec@1 94.000 (96.100) Prec@5 100.000 (99.900) +2022-11-14 16:31:35,809 Epoch: [353][200/500] Time 0.105 (0.056) Data 0.002 (0.003) Loss 0.0585 (0.0285) Prec@1 90.000 (95.810) Prec@5 100.000 (99.905) +2022-11-14 16:31:36,610 Epoch: [353][210/500] Time 0.062 (0.057) Data 0.002 (0.003) Loss 0.0424 (0.0291) Prec@1 92.000 (95.636) Prec@5 100.000 (99.909) +2022-11-14 16:31:37,417 Epoch: [353][220/500] Time 0.072 (0.058) Data 0.002 (0.003) Loss 0.0228 (0.0288) Prec@1 95.000 (95.609) Prec@5 100.000 (99.913) +2022-11-14 16:31:38,269 Epoch: [353][230/500] Time 0.073 (0.058) Data 0.002 (0.003) Loss 0.0486 (0.0297) Prec@1 91.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 16:31:39,084 Epoch: [353][240/500] Time 0.080 (0.059) Data 0.002 (0.003) Loss 0.0337 (0.0298) Prec@1 94.000 (95.360) Prec@5 99.000 (99.880) +2022-11-14 16:31:39,894 Epoch: [353][250/500] Time 0.083 (0.060) Data 0.002 (0.003) Loss 0.0382 (0.0301) Prec@1 95.000 (95.346) Prec@5 100.000 (99.885) +2022-11-14 16:31:40,657 Epoch: [353][260/500] Time 0.072 (0.060) Data 0.002 (0.003) Loss 0.0357 (0.0304) Prec@1 93.000 (95.259) Prec@5 100.000 (99.889) +2022-11-14 16:31:41,474 Epoch: [353][270/500] Time 0.079 (0.060) Data 0.002 (0.003) Loss 0.0358 (0.0305) Prec@1 95.000 (95.250) Prec@5 100.000 (99.893) +2022-11-14 16:31:42,266 Epoch: [353][280/500] Time 0.077 (0.061) Data 0.002 (0.003) Loss 0.0440 (0.0310) Prec@1 93.000 (95.172) Prec@5 100.000 (99.897) +2022-11-14 16:31:43,057 Epoch: [353][290/500] Time 0.073 (0.061) Data 0.002 (0.003) Loss 0.0215 (0.0307) Prec@1 97.000 (95.233) Prec@5 100.000 (99.900) +2022-11-14 16:31:43,975 Epoch: [353][300/500] Time 0.078 (0.062) Data 0.002 (0.003) Loss 0.0324 (0.0308) Prec@1 96.000 (95.258) Prec@5 100.000 (99.903) +2022-11-14 16:31:44,827 Epoch: [353][310/500] Time 0.085 (0.062) Data 0.002 (0.003) Loss 0.0383 (0.0310) Prec@1 95.000 (95.250) Prec@5 100.000 (99.906) +2022-11-14 16:31:45,436 Epoch: [353][320/500] Time 0.051 (0.062) Data 0.002 (0.003) Loss 0.0300 (0.0310) Prec@1 95.000 (95.242) Prec@5 99.000 (99.879) +2022-11-14 16:31:45,983 Epoch: [353][330/500] Time 0.049 (0.061) Data 0.003 (0.003) Loss 0.0256 (0.0308) Prec@1 97.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 16:31:46,562 Epoch: [353][340/500] Time 0.051 (0.061) Data 0.002 (0.003) Loss 0.0243 (0.0306) Prec@1 94.000 (95.257) Prec@5 100.000 (99.886) +2022-11-14 16:31:47,081 Epoch: [353][350/500] Time 0.048 (0.061) Data 0.002 (0.003) Loss 0.0481 (0.0311) Prec@1 91.000 (95.139) Prec@5 99.000 (99.861) +2022-11-14 16:31:47,606 Epoch: [353][360/500] Time 0.048 (0.060) Data 0.002 (0.003) Loss 0.0328 (0.0311) Prec@1 93.000 (95.081) Prec@5 100.000 (99.865) +2022-11-14 16:31:48,137 Epoch: [353][370/500] Time 0.048 (0.060) Data 0.002 (0.003) Loss 0.0256 (0.0310) Prec@1 97.000 (95.132) Prec@5 100.000 (99.868) +2022-11-14 16:31:48,753 Epoch: [353][380/500] Time 0.044 (0.060) Data 0.002 (0.003) Loss 0.0346 (0.0311) Prec@1 94.000 (95.103) Prec@5 99.000 (99.846) +2022-11-14 16:31:49,280 Epoch: [353][390/500] Time 0.049 (0.060) Data 0.002 (0.003) Loss 0.0318 (0.0311) Prec@1 94.000 (95.075) Prec@5 100.000 (99.850) +2022-11-14 16:31:49,828 Epoch: [353][400/500] Time 0.058 (0.059) Data 0.002 (0.003) Loss 0.0423 (0.0314) Prec@1 93.000 (95.024) Prec@5 100.000 (99.854) +2022-11-14 16:31:50,369 Epoch: [353][410/500] Time 0.059 (0.059) Data 0.002 (0.003) Loss 0.0477 (0.0318) Prec@1 91.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 16:31:50,892 Epoch: [353][420/500] Time 0.056 (0.059) Data 0.002 (0.003) Loss 0.0330 (0.0318) Prec@1 94.000 (94.907) Prec@5 100.000 (99.860) +2022-11-14 16:31:51,419 Epoch: [353][430/500] Time 0.052 (0.059) Data 0.002 (0.003) Loss 0.0455 (0.0321) Prec@1 92.000 (94.841) Prec@5 100.000 (99.864) +2022-11-14 16:31:52,078 Epoch: [353][440/500] Time 0.056 (0.059) Data 0.003 (0.003) Loss 0.0250 (0.0320) Prec@1 97.000 (94.889) Prec@5 100.000 (99.867) +2022-11-14 16:31:52,604 Epoch: [353][450/500] Time 0.052 (0.058) Data 0.002 (0.003) Loss 0.0300 (0.0319) Prec@1 96.000 (94.913) Prec@5 100.000 (99.870) +2022-11-14 16:31:53,137 Epoch: [353][460/500] Time 0.048 (0.058) Data 0.002 (0.003) Loss 0.0243 (0.0317) Prec@1 96.000 (94.936) Prec@5 100.000 (99.872) +2022-11-14 16:31:53,691 Epoch: [353][470/500] Time 0.057 (0.058) Data 0.002 (0.003) Loss 0.0361 (0.0318) Prec@1 94.000 (94.917) Prec@5 100.000 (99.875) +2022-11-14 16:31:54,239 Epoch: [353][480/500] Time 0.052 (0.058) Data 0.002 (0.003) Loss 0.0179 (0.0316) Prec@1 98.000 (94.980) Prec@5 100.000 (99.878) +2022-11-14 16:31:54,786 Epoch: [353][490/500] Time 0.055 (0.058) Data 0.002 (0.003) Loss 0.0277 (0.0315) Prec@1 96.000 (95.000) Prec@5 100.000 (99.880) +2022-11-14 16:31:55,300 Epoch: [353][499/500] Time 0.074 (0.057) Data 0.003 (0.003) Loss 0.0269 (0.0314) Prec@1 96.000 (95.020) Prec@5 100.000 (99.882) +2022-11-14 16:31:55,676 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0441 (0.0441) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:31:55,685 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0574) Prec@1 89.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 16:31:55,694 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0623) Prec@1 90.000 (90.667) Prec@5 99.000 (99.333) +2022-11-14 16:31:55,707 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0662) Prec@1 87.000 (89.750) Prec@5 99.000 (99.250) +2022-11-14 16:31:55,717 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0651) Prec@1 87.000 (89.200) Prec@5 99.000 (99.200) +2022-11-14 16:31:55,728 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0628) Prec@1 93.000 (89.833) Prec@5 99.000 (99.167) +2022-11-14 16:31:55,742 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0635) Prec@1 90.000 (89.857) Prec@5 100.000 (99.286) +2022-11-14 16:31:55,758 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0884 (0.0666) Prec@1 83.000 (89.000) Prec@5 99.000 (99.250) +2022-11-14 16:31:55,776 Test: [8/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0680) Prec@1 89.000 (89.000) Prec@5 98.000 (99.111) +2022-11-14 16:31:55,793 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0682) Prec@1 90.000 (89.100) Prec@5 99.000 (99.100) +2022-11-14 16:31:55,812 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0671) Prec@1 91.000 (89.273) Prec@5 100.000 (99.182) +2022-11-14 16:31:55,830 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0670) Prec@1 91.000 (89.417) Prec@5 99.000 (99.167) +2022-11-14 16:31:55,850 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0681) Prec@1 87.000 (89.231) Prec@5 100.000 (99.231) +2022-11-14 16:31:55,867 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0675) Prec@1 92.000 (89.429) Prec@5 100.000 (99.286) +2022-11-14 16:31:55,883 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0676) Prec@1 89.000 (89.400) Prec@5 99.000 (99.267) +2022-11-14 16:31:55,899 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0679) Prec@1 90.000 (89.438) Prec@5 98.000 (99.188) +2022-11-14 16:31:55,918 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0666) Prec@1 94.000 (89.706) Prec@5 97.000 (99.059) +2022-11-14 16:31:55,934 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0687) Prec@1 84.000 (89.389) Prec@5 100.000 (99.111) +2022-11-14 16:31:55,955 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0690) Prec@1 89.000 (89.368) Prec@5 99.000 (99.105) +2022-11-14 16:31:55,977 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0697) Prec@1 88.000 (89.300) Prec@5 98.000 (99.050) +2022-11-14 16:31:55,994 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0696) Prec@1 89.000 (89.286) Prec@5 100.000 (99.095) +2022-11-14 16:31:56,011 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0703) Prec@1 87.000 (89.182) Prec@5 98.000 (99.045) +2022-11-14 16:31:56,027 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1175 (0.0723) Prec@1 84.000 (88.957) Prec@5 97.000 (98.957) +2022-11-14 16:31:56,044 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0727) Prec@1 88.000 (88.917) Prec@5 100.000 (99.000) +2022-11-14 16:31:56,069 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0731) Prec@1 85.000 (88.760) Prec@5 99.000 (99.000) +2022-11-14 16:31:56,086 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1232 (0.0751) Prec@1 80.000 (88.423) Prec@5 97.000 (98.923) +2022-11-14 16:31:56,110 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0741) Prec@1 93.000 (88.593) Prec@5 100.000 (98.963) +2022-11-14 16:31:56,132 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0736) Prec@1 88.000 (88.571) Prec@5 100.000 (99.000) +2022-11-14 16:31:56,153 Test: [28/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0736) Prec@1 89.000 (88.586) Prec@5 98.000 (98.966) +2022-11-14 16:31:56,174 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0739) Prec@1 90.000 (88.633) Prec@5 98.000 (98.933) +2022-11-14 16:31:56,191 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0740) Prec@1 85.000 (88.516) Prec@5 99.000 (98.935) +2022-11-14 16:31:56,210 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0600 (0.0735) Prec@1 91.000 (88.594) Prec@5 99.000 (98.938) +2022-11-14 16:31:56,229 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0926 (0.0741) Prec@1 83.000 (88.424) Prec@5 99.000 (98.939) +2022-11-14 16:31:56,248 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0740) Prec@1 87.000 (88.382) Prec@5 99.000 (98.941) +2022-11-14 16:31:56,268 Test: [34/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0742) Prec@1 87.000 (88.343) Prec@5 98.000 (98.914) +2022-11-14 16:31:56,284 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0556 (0.0737) Prec@1 93.000 (88.472) Prec@5 99.000 (98.917) +2022-11-14 16:31:56,305 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0733) Prec@1 89.000 (88.486) Prec@5 99.000 (98.919) +2022-11-14 16:31:56,330 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0740) Prec@1 81.000 (88.289) Prec@5 99.000 (98.921) +2022-11-14 16:31:56,348 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0527 (0.0735) Prec@1 94.000 (88.436) Prec@5 99.000 (98.923) +2022-11-14 16:31:56,368 Test: [39/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0733) Prec@1 91.000 (88.500) Prec@5 99.000 (98.925) +2022-11-14 16:31:56,387 Test: [40/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0739) Prec@1 86.000 (88.439) Prec@5 97.000 (98.878) +2022-11-14 16:31:56,407 Test: [41/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0740) Prec@1 87.000 (88.405) Prec@5 99.000 (98.881) +2022-11-14 16:31:56,424 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0501 (0.0735) Prec@1 93.000 (88.512) Prec@5 98.000 (98.860) +2022-11-14 16:31:56,440 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0735) Prec@1 88.000 (88.500) Prec@5 98.000 (98.841) +2022-11-14 16:31:56,457 Test: [44/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0733) Prec@1 90.000 (88.533) Prec@5 99.000 (98.844) +2022-11-14 16:31:56,476 Test: [45/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1134 (0.0741) Prec@1 80.000 (88.348) Prec@5 99.000 (98.848) +2022-11-14 16:31:56,493 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0740) Prec@1 88.000 (88.340) Prec@5 100.000 (98.872) +2022-11-14 16:31:56,511 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1169 (0.0749) Prec@1 80.000 (88.167) Prec@5 97.000 (98.833) +2022-11-14 16:31:56,528 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0392 (0.0742) Prec@1 95.000 (88.306) Prec@5 100.000 (98.857) +2022-11-14 16:31:56,546 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1150 (0.0750) Prec@1 83.000 (88.200) Prec@5 98.000 (98.840) +2022-11-14 16:31:56,564 Test: [50/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0495 (0.0745) Prec@1 90.000 (88.235) Prec@5 100.000 (98.863) +2022-11-14 16:31:56,587 Test: [51/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0912 (0.0748) Prec@1 84.000 (88.154) Prec@5 98.000 (98.846) +2022-11-14 16:31:56,612 Test: [52/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0463 (0.0743) Prec@1 92.000 (88.226) Prec@5 100.000 (98.868) +2022-11-14 16:31:56,633 Test: [53/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0772 (0.0743) Prec@1 89.000 (88.241) Prec@5 99.000 (98.870) +2022-11-14 16:31:56,654 Test: [54/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0882 (0.0746) Prec@1 86.000 (88.200) Prec@5 100.000 (98.891) +2022-11-14 16:31:56,677 Test: [55/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0744) Prec@1 90.000 (88.232) Prec@5 99.000 (98.893) +2022-11-14 16:31:56,697 Test: [56/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0838 (0.0746) Prec@1 87.000 (88.211) Prec@5 100.000 (98.912) +2022-11-14 16:31:56,722 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0577 (0.0743) Prec@1 91.000 (88.259) Prec@5 100.000 (98.931) +2022-11-14 16:31:56,748 Test: [58/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0746) Prec@1 82.000 (88.153) Prec@5 100.000 (98.949) +2022-11-14 16:31:56,766 Test: [59/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0745) Prec@1 89.000 (88.167) Prec@5 100.000 (98.967) +2022-11-14 16:31:56,785 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0799 (0.0745) Prec@1 88.000 (88.164) Prec@5 99.000 (98.967) +2022-11-14 16:31:56,805 Test: [61/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0675 (0.0744) Prec@1 90.000 (88.194) Prec@5 100.000 (98.984) +2022-11-14 16:31:56,830 Test: [62/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0742) Prec@1 90.000 (88.222) Prec@5 99.000 (98.984) +2022-11-14 16:31:56,854 Test: [63/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0487 (0.0738) Prec@1 91.000 (88.266) Prec@5 100.000 (99.000) +2022-11-14 16:31:56,874 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1025 (0.0743) Prec@1 82.000 (88.169) Prec@5 100.000 (99.015) +2022-11-14 16:31:56,893 Test: [65/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0619 (0.0741) Prec@1 90.000 (88.197) Prec@5 100.000 (99.030) +2022-11-14 16:31:56,913 Test: [66/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0459 (0.0737) Prec@1 91.000 (88.239) Prec@5 100.000 (99.045) +2022-11-14 16:31:56,932 Test: [67/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0954 (0.0740) Prec@1 86.000 (88.206) Prec@5 97.000 (99.015) +2022-11-14 16:31:56,953 Test: [68/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0666 (0.0739) Prec@1 90.000 (88.232) Prec@5 99.000 (99.014) +2022-11-14 16:31:56,973 Test: [69/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0625 (0.0737) Prec@1 90.000 (88.257) Prec@5 100.000 (99.029) +2022-11-14 16:31:56,988 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0739) Prec@1 89.000 (88.268) Prec@5 98.000 (99.014) +2022-11-14 16:31:57,003 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0495 (0.0736) Prec@1 92.000 (88.319) Prec@5 99.000 (99.014) +2022-11-14 16:31:57,020 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0736) Prec@1 89.000 (88.329) Prec@5 100.000 (99.027) +2022-11-14 16:31:57,040 Test: [73/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0734) Prec@1 91.000 (88.365) Prec@5 100.000 (99.041) +2022-11-14 16:31:57,057 Test: [74/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0737) Prec@1 85.000 (88.320) Prec@5 100.000 (99.053) +2022-11-14 16:31:57,073 Test: [75/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0735) Prec@1 90.000 (88.342) Prec@5 98.000 (99.039) +2022-11-14 16:31:57,092 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0736) Prec@1 86.000 (88.312) Prec@5 100.000 (99.052) +2022-11-14 16:31:57,111 Test: [77/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0942 (0.0739) Prec@1 86.000 (88.282) Prec@5 99.000 (99.051) +2022-11-14 16:31:57,131 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0739) Prec@1 88.000 (88.278) Prec@5 99.000 (99.051) +2022-11-14 16:31:57,148 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0739) Prec@1 87.000 (88.263) Prec@5 100.000 (99.062) +2022-11-14 16:31:57,165 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0741) Prec@1 89.000 (88.272) Prec@5 99.000 (99.062) +2022-11-14 16:31:57,185 Test: [81/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0740) Prec@1 87.000 (88.256) Prec@5 100.000 (99.073) +2022-11-14 16:31:57,202 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.0742) Prec@1 86.000 (88.229) Prec@5 100.000 (99.084) +2022-11-14 16:31:57,220 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 85.000 (88.190) Prec@5 100.000 (99.095) +2022-11-14 16:31:57,241 Test: [84/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0996 (0.0745) Prec@1 83.000 (88.129) Prec@5 100.000 (99.106) +2022-11-14 16:31:57,256 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1102 (0.0750) Prec@1 83.000 (88.070) Prec@5 98.000 (99.093) +2022-11-14 16:31:57,271 Test: [86/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0844 (0.0751) Prec@1 85.000 (88.034) Prec@5 99.000 (99.092) +2022-11-14 16:31:57,287 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0804 (0.0751) Prec@1 88.000 (88.034) Prec@5 99.000 (99.091) +2022-11-14 16:31:57,306 Test: [88/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0502 (0.0748) Prec@1 92.000 (88.079) Prec@5 100.000 (99.101) +2022-11-14 16:31:57,326 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0749) Prec@1 89.000 (88.089) Prec@5 98.000 (99.089) +2022-11-14 16:31:57,349 Test: [90/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0746) Prec@1 90.000 (88.110) Prec@5 100.000 (99.099) +2022-11-14 16:31:57,368 Test: [91/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0472 (0.0744) Prec@1 93.000 (88.163) Prec@5 99.000 (99.098) +2022-11-14 16:31:57,387 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1098 (0.0747) Prec@1 83.000 (88.108) Prec@5 97.000 (99.075) +2022-11-14 16:31:57,408 Test: [93/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0748) Prec@1 89.000 (88.117) Prec@5 99.000 (99.074) +2022-11-14 16:31:57,429 Test: [94/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0646 (0.0746) Prec@1 89.000 (88.126) Prec@5 99.000 (99.074) +2022-11-14 16:31:57,450 Test: [95/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0746) Prec@1 89.000 (88.135) Prec@5 100.000 (99.083) +2022-11-14 16:31:57,469 Test: [96/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0558 (0.0744) Prec@1 92.000 (88.175) Prec@5 99.000 (99.082) +2022-11-14 16:31:57,486 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0745) Prec@1 87.000 (88.163) Prec@5 98.000 (99.071) +2022-11-14 16:31:57,501 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0871 (0.0746) Prec@1 87.000 (88.152) Prec@5 100.000 (99.081) +2022-11-14 16:31:57,520 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0730 (0.0746) Prec@1 89.000 (88.160) Prec@5 99.000 (99.080) +2022-11-14 16:31:57,588 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:31:57,992 Epoch: [354][0/500] Time 0.025 (0.025) Data 0.300 (0.300) Loss 0.0384 (0.0384) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:31:58,511 Epoch: [354][10/500] Time 0.061 (0.044) Data 0.002 (0.029) Loss 0.0273 (0.0329) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:31:59,070 Epoch: [354][20/500] Time 0.046 (0.047) Data 0.002 (0.016) Loss 0.0358 (0.0338) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:31:59,609 Epoch: [354][30/500] Time 0.052 (0.048) Data 0.002 (0.012) Loss 0.0240 (0.0314) Prec@1 97.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:32:00,160 Epoch: [354][40/500] Time 0.060 (0.048) Data 0.002 (0.009) Loss 0.0477 (0.0346) Prec@1 91.000 (94.000) Prec@5 98.000 (99.600) +2022-11-14 16:32:00,736 Epoch: [354][50/500] Time 0.056 (0.049) Data 0.002 (0.008) Loss 0.0133 (0.0311) Prec@1 98.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:32:01,267 Epoch: [354][60/500] Time 0.053 (0.049) Data 0.002 (0.007) Loss 0.0448 (0.0330) Prec@1 92.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 16:32:01,818 Epoch: [354][70/500] Time 0.045 (0.049) Data 0.002 (0.006) Loss 0.0182 (0.0312) Prec@1 97.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 16:32:02,361 Epoch: [354][80/500] Time 0.058 (0.049) Data 0.002 (0.006) Loss 0.0322 (0.0313) Prec@1 93.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 16:32:02,893 Epoch: [354][90/500] Time 0.047 (0.049) Data 0.002 (0.005) Loss 0.0219 (0.0304) Prec@1 97.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 16:32:03,434 Epoch: [354][100/500] Time 0.052 (0.049) Data 0.002 (0.005) Loss 0.0288 (0.0302) Prec@1 95.000 (94.727) Prec@5 99.000 (99.727) +2022-11-14 16:32:03,986 Epoch: [354][110/500] Time 0.053 (0.049) Data 0.002 (0.005) Loss 0.0208 (0.0294) Prec@1 96.000 (94.833) Prec@5 100.000 (99.750) +2022-11-14 16:32:04,561 Epoch: [354][120/500] Time 0.057 (0.049) Data 0.002 (0.005) Loss 0.0273 (0.0293) Prec@1 94.000 (94.769) Prec@5 100.000 (99.769) +2022-11-14 16:32:05,083 Epoch: [354][130/500] Time 0.052 (0.049) Data 0.003 (0.004) Loss 0.0333 (0.0296) Prec@1 94.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 16:32:05,627 Epoch: [354][140/500] Time 0.051 (0.049) Data 0.003 (0.004) Loss 0.0217 (0.0290) Prec@1 96.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:32:06,165 Epoch: [354][150/500] Time 0.058 (0.049) Data 0.002 (0.004) Loss 0.0456 (0.0301) Prec@1 94.000 (94.750) Prec@5 100.000 (99.812) +2022-11-14 16:32:06,703 Epoch: [354][160/500] Time 0.056 (0.049) Data 0.002 (0.004) Loss 0.0206 (0.0295) Prec@1 96.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:32:07,246 Epoch: [354][170/500] Time 0.054 (0.049) Data 0.002 (0.004) Loss 0.0406 (0.0301) Prec@1 94.000 (94.778) Prec@5 100.000 (99.833) +2022-11-14 16:32:07,813 Epoch: [354][180/500] Time 0.062 (0.049) Data 0.002 (0.004) Loss 0.0246 (0.0298) Prec@1 95.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 16:32:08,374 Epoch: [354][190/500] Time 0.066 (0.049) Data 0.002 (0.004) Loss 0.0285 (0.0298) Prec@1 95.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 16:32:08,906 Epoch: [354][200/500] Time 0.060 (0.049) Data 0.002 (0.004) Loss 0.0385 (0.0302) Prec@1 93.000 (94.714) Prec@5 100.000 (99.810) +2022-11-14 16:32:09,457 Epoch: [354][210/500] Time 0.051 (0.049) Data 0.002 (0.004) Loss 0.0298 (0.0302) Prec@1 96.000 (94.773) Prec@5 100.000 (99.818) +2022-11-14 16:32:10,083 Epoch: [354][220/500] Time 0.053 (0.049) Data 0.002 (0.004) Loss 0.0268 (0.0300) Prec@1 96.000 (94.826) Prec@5 100.000 (99.826) +2022-11-14 16:32:10,723 Epoch: [354][230/500] Time 0.070 (0.049) Data 0.002 (0.003) Loss 0.0172 (0.0295) Prec@1 98.000 (94.958) Prec@5 100.000 (99.833) +2022-11-14 16:32:11,346 Epoch: [354][240/500] Time 0.072 (0.050) Data 0.002 (0.003) Loss 0.0204 (0.0291) Prec@1 96.000 (95.000) Prec@5 100.000 (99.840) +2022-11-14 16:32:11,978 Epoch: [354][250/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0447 (0.0297) Prec@1 92.000 (94.885) Prec@5 100.000 (99.846) +2022-11-14 16:32:12,642 Epoch: [354][260/500] Time 0.066 (0.050) Data 0.002 (0.003) Loss 0.0318 (0.0298) Prec@1 97.000 (94.963) Prec@5 100.000 (99.852) +2022-11-14 16:32:13,252 Epoch: [354][270/500] Time 0.066 (0.051) Data 0.002 (0.003) Loss 0.0221 (0.0295) Prec@1 97.000 (95.036) Prec@5 100.000 (99.857) +2022-11-14 16:32:13,814 Epoch: [354][280/500] Time 0.044 (0.051) Data 0.002 (0.003) Loss 0.0246 (0.0294) Prec@1 96.000 (95.069) Prec@5 100.000 (99.862) +2022-11-14 16:32:14,365 Epoch: [354][290/500] Time 0.048 (0.050) Data 0.002 (0.003) Loss 0.0370 (0.0296) Prec@1 92.000 (94.967) Prec@5 100.000 (99.867) +2022-11-14 16:32:14,936 Epoch: [354][300/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0461 (0.0301) Prec@1 92.000 (94.871) Prec@5 100.000 (99.871) +2022-11-14 16:32:15,469 Epoch: [354][310/500] Time 0.042 (0.050) Data 0.002 (0.003) Loss 0.0199 (0.0298) Prec@1 96.000 (94.906) Prec@5 100.000 (99.875) +2022-11-14 16:32:16,014 Epoch: [354][320/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0521 (0.0305) Prec@1 92.000 (94.818) Prec@5 99.000 (99.848) +2022-11-14 16:32:16,621 Epoch: [354][330/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0250 (0.0303) Prec@1 96.000 (94.853) Prec@5 99.000 (99.824) +2022-11-14 16:32:17,160 Epoch: [354][340/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0311 (0.0304) Prec@1 95.000 (94.857) Prec@5 100.000 (99.829) +2022-11-14 16:32:17,686 Epoch: [354][350/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0230 (0.0302) Prec@1 98.000 (94.944) Prec@5 100.000 (99.833) +2022-11-14 16:32:18,217 Epoch: [354][360/500] Time 0.043 (0.050) Data 0.002 (0.003) Loss 0.0296 (0.0301) Prec@1 95.000 (94.946) Prec@5 100.000 (99.838) +2022-11-14 16:32:18,771 Epoch: [354][370/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0225 (0.0299) Prec@1 97.000 (95.000) Prec@5 100.000 (99.842) +2022-11-14 16:32:19,324 Epoch: [354][380/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0498 (0.0304) Prec@1 90.000 (94.872) Prec@5 99.000 (99.821) +2022-11-14 16:32:19,892 Epoch: [354][390/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0332 (0.0305) Prec@1 93.000 (94.825) Prec@5 100.000 (99.825) +2022-11-14 16:32:20,450 Epoch: [354][400/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0242 (0.0304) Prec@1 96.000 (94.854) Prec@5 100.000 (99.829) +2022-11-14 16:32:20,985 Epoch: [354][410/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0305 (0.0304) Prec@1 96.000 (94.881) Prec@5 100.000 (99.833) +2022-11-14 16:32:21,530 Epoch: [354][420/500] Time 0.053 (0.050) Data 0.003 (0.003) Loss 0.0368 (0.0305) Prec@1 92.000 (94.814) Prec@5 100.000 (99.837) +2022-11-14 16:32:22,088 Epoch: [354][430/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0305 (0.0305) Prec@1 95.000 (94.818) Prec@5 100.000 (99.841) +2022-11-14 16:32:22,654 Epoch: [354][440/500] Time 0.049 (0.050) Data 0.002 (0.003) Loss 0.0453 (0.0308) Prec@1 92.000 (94.756) Prec@5 100.000 (99.844) +2022-11-14 16:32:23,194 Epoch: [354][450/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0258 (0.0307) Prec@1 94.000 (94.739) Prec@5 100.000 (99.848) +2022-11-14 16:32:23,747 Epoch: [354][460/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0162 (0.0304) Prec@1 96.000 (94.766) Prec@5 100.000 (99.851) +2022-11-14 16:32:24,290 Epoch: [354][470/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0368 (0.0306) Prec@1 95.000 (94.771) Prec@5 100.000 (99.854) +2022-11-14 16:32:24,829 Epoch: [354][480/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0326 (0.0306) Prec@1 95.000 (94.776) Prec@5 100.000 (99.857) +2022-11-14 16:32:25,354 Epoch: [354][490/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0326 (0.0306) Prec@1 94.000 (94.760) Prec@5 100.000 (99.860) +2022-11-14 16:32:25,850 Epoch: [354][499/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0391 (0.0308) Prec@1 93.000 (94.725) Prec@5 100.000 (99.863) +2022-11-14 16:32:26,224 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0552 (0.0552) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:32:26,234 Test: [1/100] Model Time 0.009 (0.013) Loss Time 0.000 (0.000) Loss 0.0615 (0.0583) Prec@1 91.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:32:26,246 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0738 (0.0635) Prec@1 89.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:32:26,262 Test: [3/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0820 (0.0681) Prec@1 87.000 (89.750) Prec@5 98.000 (99.500) +2022-11-14 16:32:26,274 Test: [4/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0837 (0.0712) Prec@1 87.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 16:32:26,285 Test: [5/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0549 (0.0685) Prec@1 91.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 16:32:26,299 Test: [6/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0671 (0.0683) Prec@1 91.000 (89.714) Prec@5 99.000 (99.571) +2022-11-14 16:32:26,315 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1105 (0.0736) Prec@1 83.000 (88.875) Prec@5 98.000 (99.375) +2022-11-14 16:32:26,329 Test: [8/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0639 (0.0725) Prec@1 90.000 (89.000) Prec@5 99.000 (99.333) +2022-11-14 16:32:26,344 Test: [9/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0753 (0.0728) Prec@1 88.000 (88.900) Prec@5 99.000 (99.300) +2022-11-14 16:32:26,359 Test: [10/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0449 (0.0702) Prec@1 93.000 (89.273) Prec@5 100.000 (99.364) +2022-11-14 16:32:26,374 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0816 (0.0712) Prec@1 88.000 (89.167) Prec@5 100.000 (99.417) +2022-11-14 16:32:26,390 Test: [12/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0520 (0.0697) Prec@1 91.000 (89.308) Prec@5 100.000 (99.462) +2022-11-14 16:32:26,408 Test: [13/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0802 (0.0705) Prec@1 88.000 (89.214) Prec@5 99.000 (99.429) +2022-11-14 16:32:26,425 Test: [14/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0863 (0.0715) Prec@1 87.000 (89.067) Prec@5 99.000 (99.400) +2022-11-14 16:32:26,442 Test: [15/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0737 (0.0717) Prec@1 86.000 (88.875) Prec@5 99.000 (99.375) +2022-11-14 16:32:26,455 Test: [16/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0395 (0.0698) Prec@1 94.000 (89.176) Prec@5 99.000 (99.353) +2022-11-14 16:32:26,480 Test: [17/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.1245 (0.0728) Prec@1 80.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 16:32:26,501 Test: [18/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0953 (0.0740) Prec@1 85.000 (88.474) Prec@5 100.000 (99.368) +2022-11-14 16:32:26,520 Test: [19/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0968 (0.0751) Prec@1 82.000 (88.150) Prec@5 97.000 (99.250) +2022-11-14 16:32:26,537 Test: [20/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0786 (0.0753) Prec@1 87.000 (88.095) Prec@5 100.000 (99.286) +2022-11-14 16:32:26,558 Test: [21/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0827 (0.0756) Prec@1 86.000 (88.000) Prec@5 99.000 (99.273) +2022-11-14 16:32:26,584 Test: [22/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1023 (0.0768) Prec@1 83.000 (87.783) Prec@5 99.000 (99.261) +2022-11-14 16:32:26,610 Test: [23/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0723 (0.0766) Prec@1 86.000 (87.708) Prec@5 99.000 (99.250) +2022-11-14 16:32:26,633 Test: [24/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0830 (0.0769) Prec@1 87.000 (87.680) Prec@5 100.000 (99.280) +2022-11-14 16:32:26,656 Test: [25/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0756 (0.0768) Prec@1 88.000 (87.692) Prec@5 98.000 (99.231) +2022-11-14 16:32:26,679 Test: [26/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0489 (0.0758) Prec@1 91.000 (87.815) Prec@5 100.000 (99.259) +2022-11-14 16:32:26,700 Test: [27/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0513 (0.0749) Prec@1 91.000 (87.929) Prec@5 100.000 (99.286) +2022-11-14 16:32:26,722 Test: [28/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0509 (0.0741) Prec@1 94.000 (88.138) Prec@5 99.000 (99.276) +2022-11-14 16:32:26,744 Test: [29/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0757 (0.0741) Prec@1 88.000 (88.133) Prec@5 99.000 (99.267) +2022-11-14 16:32:26,768 Test: [30/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0708 (0.0740) Prec@1 88.000 (88.129) Prec@5 99.000 (99.258) +2022-11-14 16:32:26,793 Test: [31/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0717 (0.0739) Prec@1 89.000 (88.156) Prec@5 98.000 (99.219) +2022-11-14 16:32:26,817 Test: [32/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0638 (0.0736) Prec@1 90.000 (88.212) Prec@5 100.000 (99.242) +2022-11-14 16:32:26,841 Test: [33/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0723 (0.0736) Prec@1 87.000 (88.176) Prec@5 100.000 (99.265) +2022-11-14 16:32:26,864 Test: [34/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.0739) Prec@1 87.000 (88.143) Prec@5 98.000 (99.229) +2022-11-14 16:32:26,889 Test: [35/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0742 (0.0739) Prec@1 90.000 (88.194) Prec@5 98.000 (99.194) +2022-11-14 16:32:26,910 Test: [36/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0697 (0.0738) Prec@1 90.000 (88.243) Prec@5 99.000 (99.189) +2022-11-14 16:32:26,932 Test: [37/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0899 (0.0742) Prec@1 84.000 (88.132) Prec@5 100.000 (99.211) +2022-11-14 16:32:26,956 Test: [38/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0583 (0.0738) Prec@1 90.000 (88.179) Prec@5 100.000 (99.231) +2022-11-14 16:32:26,977 Test: [39/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0609 (0.0735) Prec@1 92.000 (88.275) Prec@5 99.000 (99.225) +2022-11-14 16:32:26,999 Test: [40/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0957 (0.0740) Prec@1 85.000 (88.195) Prec@5 98.000 (99.195) +2022-11-14 16:32:27,021 Test: [41/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0823 (0.0742) Prec@1 88.000 (88.190) Prec@5 100.000 (99.214) +2022-11-14 16:32:27,045 Test: [42/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0464 (0.0736) Prec@1 92.000 (88.279) Prec@5 99.000 (99.209) +2022-11-14 16:32:27,069 Test: [43/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0695 (0.0735) Prec@1 88.000 (88.273) Prec@5 99.000 (99.205) +2022-11-14 16:32:27,094 Test: [44/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0634 (0.0733) Prec@1 90.000 (88.311) Prec@5 99.000 (99.200) +2022-11-14 16:32:27,115 Test: [45/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0876 (0.0736) Prec@1 85.000 (88.239) Prec@5 98.000 (99.174) +2022-11-14 16:32:27,136 Test: [46/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0703 (0.0735) Prec@1 87.000 (88.213) Prec@5 100.000 (99.191) +2022-11-14 16:32:27,159 Test: [47/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1059 (0.0742) Prec@1 84.000 (88.125) Prec@5 98.000 (99.167) +2022-11-14 16:32:27,182 Test: [48/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0560 (0.0738) Prec@1 91.000 (88.184) Prec@5 99.000 (99.163) +2022-11-14 16:32:27,207 Test: [49/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.1121 (0.0746) Prec@1 82.000 (88.060) Prec@5 100.000 (99.180) +2022-11-14 16:32:27,229 Test: [50/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0696 (0.0745) Prec@1 87.000 (88.039) Prec@5 100.000 (99.196) +2022-11-14 16:32:27,250 Test: [51/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0859 (0.0747) Prec@1 86.000 (88.000) Prec@5 99.000 (99.192) +2022-11-14 16:32:27,269 Test: [52/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0654 (0.0745) Prec@1 87.000 (87.981) Prec@5 100.000 (99.208) +2022-11-14 16:32:27,293 Test: [53/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0648 (0.0743) Prec@1 88.000 (87.981) Prec@5 99.000 (99.204) +2022-11-14 16:32:27,316 Test: [54/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0921 (0.0747) Prec@1 85.000 (87.927) Prec@5 100.000 (99.218) +2022-11-14 16:32:27,342 Test: [55/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0574 (0.0744) Prec@1 90.000 (87.964) Prec@5 99.000 (99.214) +2022-11-14 16:32:27,369 Test: [56/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0728 (0.0743) Prec@1 87.000 (87.947) Prec@5 99.000 (99.211) +2022-11-14 16:32:27,390 Test: [57/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0769 (0.0744) Prec@1 90.000 (87.983) Prec@5 100.000 (99.224) +2022-11-14 16:32:27,416 Test: [58/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0955 (0.0747) Prec@1 84.000 (87.915) Prec@5 99.000 (99.220) +2022-11-14 16:32:27,441 Test: [59/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0767 (0.0748) Prec@1 86.000 (87.883) Prec@5 100.000 (99.233) +2022-11-14 16:32:27,465 Test: [60/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0871 (0.0750) Prec@1 86.000 (87.852) Prec@5 100.000 (99.246) +2022-11-14 16:32:27,489 Test: [61/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0666 (0.0748) Prec@1 90.000 (87.887) Prec@5 99.000 (99.242) +2022-11-14 16:32:27,511 Test: [62/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0627 (0.0746) Prec@1 89.000 (87.905) Prec@5 100.000 (99.254) +2022-11-14 16:32:27,533 Test: [63/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0474 (0.0742) Prec@1 92.000 (87.969) Prec@5 99.000 (99.250) +2022-11-14 16:32:27,555 Test: [64/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0964 (0.0746) Prec@1 83.000 (87.892) Prec@5 99.000 (99.246) +2022-11-14 16:32:27,576 Test: [65/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0691 (0.0745) Prec@1 88.000 (87.894) Prec@5 100.000 (99.258) +2022-11-14 16:32:27,597 Test: [66/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0491 (0.0741) Prec@1 92.000 (87.955) Prec@5 100.000 (99.269) +2022-11-14 16:32:27,617 Test: [67/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0665 (0.0740) Prec@1 89.000 (87.971) Prec@5 99.000 (99.265) +2022-11-14 16:32:27,639 Test: [68/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0771 (0.0740) Prec@1 86.000 (87.942) Prec@5 99.000 (99.261) +2022-11-14 16:32:27,660 Test: [69/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0686 (0.0740) Prec@1 89.000 (87.957) Prec@5 99.000 (99.257) +2022-11-14 16:32:27,681 Test: [70/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0846 (0.0741) Prec@1 89.000 (87.972) Prec@5 99.000 (99.254) +2022-11-14 16:32:27,703 Test: [71/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0464 (0.0737) Prec@1 93.000 (88.042) Prec@5 99.000 (99.250) +2022-11-14 16:32:27,725 Test: [72/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0404 (0.0733) Prec@1 94.000 (88.123) Prec@5 99.000 (99.247) +2022-11-14 16:32:27,745 Test: [73/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0392 (0.0728) Prec@1 94.000 (88.203) Prec@5 100.000 (99.257) +2022-11-14 16:32:27,763 Test: [74/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0999 (0.0732) Prec@1 85.000 (88.160) Prec@5 99.000 (99.253) +2022-11-14 16:32:27,778 Test: [75/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0529 (0.0729) Prec@1 91.000 (88.197) Prec@5 99.000 (99.250) +2022-11-14 16:32:27,795 Test: [76/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0696 (0.0729) Prec@1 87.000 (88.182) Prec@5 100.000 (99.260) +2022-11-14 16:32:27,811 Test: [77/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0973 (0.0732) Prec@1 85.000 (88.141) Prec@5 99.000 (99.256) +2022-11-14 16:32:27,831 Test: [78/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0568 (0.0730) Prec@1 89.000 (88.152) Prec@5 98.000 (99.241) +2022-11-14 16:32:27,850 Test: [79/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0669 (0.0729) Prec@1 87.000 (88.138) Prec@5 100.000 (99.250) +2022-11-14 16:32:27,867 Test: [80/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0810 (0.0730) Prec@1 88.000 (88.136) Prec@5 98.000 (99.235) +2022-11-14 16:32:27,882 Test: [81/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0732) Prec@1 84.000 (88.085) Prec@5 100.000 (99.244) +2022-11-14 16:32:27,898 Test: [82/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0776 (0.0733) Prec@1 88.000 (88.084) Prec@5 100.000 (99.253) +2022-11-14 16:32:27,915 Test: [83/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0576 (0.0731) Prec@1 89.000 (88.095) Prec@5 99.000 (99.250) +2022-11-14 16:32:27,934 Test: [84/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0883 (0.0733) Prec@1 85.000 (88.059) Prec@5 98.000 (99.235) +2022-11-14 16:32:27,952 Test: [85/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1016 (0.0736) Prec@1 85.000 (88.023) Prec@5 100.000 (99.244) +2022-11-14 16:32:27,967 Test: [86/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0792 (0.0737) Prec@1 86.000 (88.000) Prec@5 99.000 (99.241) +2022-11-14 16:32:27,982 Test: [87/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0669 (0.0736) Prec@1 89.000 (88.011) Prec@5 100.000 (99.250) +2022-11-14 16:32:28,002 Test: [88/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0634 (0.0735) Prec@1 90.000 (88.034) Prec@5 99.000 (99.247) +2022-11-14 16:32:28,021 Test: [89/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0745 (0.0735) Prec@1 89.000 (88.044) Prec@5 99.000 (99.244) +2022-11-14 16:32:28,040 Test: [90/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0663 (0.0734) Prec@1 89.000 (88.055) Prec@5 100.000 (99.253) +2022-11-14 16:32:28,057 Test: [91/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0592 (0.0732) Prec@1 91.000 (88.087) Prec@5 99.000 (99.250) +2022-11-14 16:32:28,074 Test: [92/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0894 (0.0734) Prec@1 87.000 (88.075) Prec@5 100.000 (99.258) +2022-11-14 16:32:28,093 Test: [93/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0647 (0.0733) Prec@1 90.000 (88.096) Prec@5 99.000 (99.255) +2022-11-14 16:32:28,110 Test: [94/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0809 (0.0734) Prec@1 87.000 (88.084) Prec@5 99.000 (99.253) +2022-11-14 16:32:28,126 Test: [95/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0641 (0.0733) Prec@1 90.000 (88.104) Prec@5 99.000 (99.250) +2022-11-14 16:32:28,145 Test: [96/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0544 (0.0731) Prec@1 92.000 (88.144) Prec@5 99.000 (99.247) +2022-11-14 16:32:28,159 Test: [97/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0831 (0.0732) Prec@1 88.000 (88.143) Prec@5 97.000 (99.224) +2022-11-14 16:32:28,177 Test: [98/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0936 (0.0734) Prec@1 85.000 (88.111) Prec@5 98.000 (99.212) +2022-11-14 16:32:28,194 Test: [99/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0678 (0.0734) Prec@1 89.000 (88.120) Prec@5 100.000 (99.220) +2022-11-14 16:32:28,259 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:32:28,634 Epoch: [355][0/500] Time 0.033 (0.033) Data 0.273 (0.273) Loss 0.0239 (0.0239) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:32:29,117 Epoch: [355][10/500] Time 0.050 (0.042) Data 0.002 (0.027) Loss 0.0336 (0.0288) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:32:29,664 Epoch: [355][20/500] Time 0.047 (0.046) Data 0.002 (0.015) Loss 0.0491 (0.0355) Prec@1 92.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 16:32:30,211 Epoch: [355][30/500] Time 0.050 (0.047) Data 0.002 (0.011) Loss 0.0621 (0.0422) Prec@1 92.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 16:32:30,779 Epoch: [355][40/500] Time 0.055 (0.048) Data 0.002 (0.009) Loss 0.0175 (0.0373) Prec@1 97.000 (94.200) Prec@5 100.000 (99.600) +2022-11-14 16:32:31,445 Epoch: [355][50/500] Time 0.059 (0.050) Data 0.002 (0.007) Loss 0.0473 (0.0389) Prec@1 94.000 (94.167) Prec@5 100.000 (99.667) +2022-11-14 16:32:31,960 Epoch: [355][60/500] Time 0.055 (0.049) Data 0.002 (0.006) Loss 0.0204 (0.0363) Prec@1 97.000 (94.571) Prec@5 100.000 (99.714) +2022-11-14 16:32:32,505 Epoch: [355][70/500] Time 0.049 (0.049) Data 0.002 (0.006) Loss 0.0262 (0.0350) Prec@1 96.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 16:32:33,076 Epoch: [355][80/500] Time 0.053 (0.050) Data 0.003 (0.005) Loss 0.0328 (0.0348) Prec@1 94.000 (94.667) Prec@5 100.000 (99.778) +2022-11-14 16:32:33,647 Epoch: [355][90/500] Time 0.064 (0.050) Data 0.002 (0.005) Loss 0.0208 (0.0334) Prec@1 96.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:32:34,191 Epoch: [355][100/500] Time 0.051 (0.050) Data 0.003 (0.005) Loss 0.0219 (0.0323) Prec@1 97.000 (95.000) Prec@5 100.000 (99.818) +2022-11-14 16:32:34,749 Epoch: [355][110/500] Time 0.058 (0.050) Data 0.002 (0.005) Loss 0.0325 (0.0323) Prec@1 96.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 16:32:35,284 Epoch: [355][120/500] Time 0.056 (0.049) Data 0.002 (0.004) Loss 0.0371 (0.0327) Prec@1 95.000 (95.077) Prec@5 100.000 (99.846) +2022-11-14 16:32:35,848 Epoch: [355][130/500] Time 0.067 (0.050) Data 0.002 (0.004) Loss 0.0276 (0.0323) Prec@1 97.000 (95.214) Prec@5 100.000 (99.857) +2022-11-14 16:32:36,379 Epoch: [355][140/500] Time 0.053 (0.049) Data 0.002 (0.004) Loss 0.0288 (0.0321) Prec@1 96.000 (95.267) Prec@5 100.000 (99.867) +2022-11-14 16:32:36,904 Epoch: [355][150/500] Time 0.057 (0.049) Data 0.002 (0.004) Loss 0.0178 (0.0312) Prec@1 97.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:32:37,426 Epoch: [355][160/500] Time 0.050 (0.049) Data 0.002 (0.004) Loss 0.0208 (0.0306) Prec@1 95.000 (95.353) Prec@5 100.000 (99.882) +2022-11-14 16:32:37,964 Epoch: [355][170/500] Time 0.046 (0.049) Data 0.002 (0.004) Loss 0.0191 (0.0300) Prec@1 97.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:32:38,498 Epoch: [355][180/500] Time 0.055 (0.049) Data 0.002 (0.004) Loss 0.0310 (0.0300) Prec@1 95.000 (95.421) Prec@5 100.000 (99.895) +2022-11-14 16:32:39,036 Epoch: [355][190/500] Time 0.046 (0.049) Data 0.002 (0.004) Loss 0.0179 (0.0294) Prec@1 99.000 (95.600) Prec@5 100.000 (99.900) +2022-11-14 16:32:39,573 Epoch: [355][200/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0116 (0.0286) Prec@1 99.000 (95.762) Prec@5 100.000 (99.905) +2022-11-14 16:32:40,197 Epoch: [355][210/500] Time 0.063 (0.049) Data 0.003 (0.003) Loss 0.0609 (0.0300) Prec@1 91.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 16:32:40,728 Epoch: [355][220/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0342 (0.0302) Prec@1 95.000 (95.522) Prec@5 100.000 (99.913) +2022-11-14 16:32:41,275 Epoch: [355][230/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0297 (0.0302) Prec@1 94.000 (95.458) Prec@5 100.000 (99.917) +2022-11-14 16:32:41,816 Epoch: [355][240/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0210 (0.0298) Prec@1 97.000 (95.520) Prec@5 100.000 (99.920) +2022-11-14 16:32:42,377 Epoch: [355][250/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0196 (0.0294) Prec@1 97.000 (95.577) Prec@5 99.000 (99.885) +2022-11-14 16:32:42,910 Epoch: [355][260/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0286 (0.0294) Prec@1 94.000 (95.519) Prec@5 100.000 (99.889) +2022-11-14 16:32:43,451 Epoch: [355][270/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0428 (0.0299) Prec@1 91.000 (95.357) Prec@5 100.000 (99.893) +2022-11-14 16:32:43,989 Epoch: [355][280/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0351 (0.0301) Prec@1 95.000 (95.345) Prec@5 100.000 (99.897) +2022-11-14 16:32:44,528 Epoch: [355][290/500] Time 0.047 (0.049) Data 0.003 (0.003) Loss 0.0274 (0.0300) Prec@1 95.000 (95.333) Prec@5 100.000 (99.900) +2022-11-14 16:32:45,055 Epoch: [355][300/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0382 (0.0302) Prec@1 93.000 (95.258) Prec@5 100.000 (99.903) +2022-11-14 16:32:45,609 Epoch: [355][310/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0677 (0.0314) Prec@1 89.000 (95.062) Prec@5 100.000 (99.906) +2022-11-14 16:32:46,143 Epoch: [355][320/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0205 (0.0311) Prec@1 97.000 (95.121) Prec@5 100.000 (99.909) +2022-11-14 16:32:46,692 Epoch: [355][330/500] Time 0.046 (0.049) Data 0.002 (0.003) Loss 0.0172 (0.0307) Prec@1 97.000 (95.176) Prec@5 100.000 (99.912) +2022-11-14 16:32:47,277 Epoch: [355][340/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0376 (0.0309) Prec@1 93.000 (95.114) Prec@5 100.000 (99.914) +2022-11-14 16:32:47,858 Epoch: [355][350/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0174 (0.0305) Prec@1 97.000 (95.167) Prec@5 100.000 (99.917) +2022-11-14 16:32:48,398 Epoch: [355][360/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0386 (0.0307) Prec@1 93.000 (95.108) Prec@5 99.000 (99.892) +2022-11-14 16:32:48,930 Epoch: [355][370/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0297 (0.0307) Prec@1 94.000 (95.079) Prec@5 100.000 (99.895) +2022-11-14 16:32:49,465 Epoch: [355][380/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0204 (0.0304) Prec@1 97.000 (95.128) Prec@5 100.000 (99.897) +2022-11-14 16:32:50,048 Epoch: [355][390/500] Time 0.079 (0.049) Data 0.002 (0.003) Loss 0.0373 (0.0306) Prec@1 95.000 (95.125) Prec@5 100.000 (99.900) +2022-11-14 16:32:50,624 Epoch: [355][400/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0179 (0.0303) Prec@1 97.000 (95.171) Prec@5 100.000 (99.902) +2022-11-14 16:32:51,166 Epoch: [355][410/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0089 (0.0298) Prec@1 100.000 (95.286) Prec@5 100.000 (99.905) +2022-11-14 16:32:51,696 Epoch: [355][420/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0209 (0.0296) Prec@1 96.000 (95.302) Prec@5 100.000 (99.907) +2022-11-14 16:32:52,232 Epoch: [355][430/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0228 (0.0294) Prec@1 96.000 (95.318) Prec@5 100.000 (99.909) +2022-11-14 16:32:52,773 Epoch: [355][440/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0585 (0.0301) Prec@1 88.000 (95.156) Prec@5 100.000 (99.911) +2022-11-14 16:32:53,301 Epoch: [355][450/500] Time 0.044 (0.049) Data 0.003 (0.003) Loss 0.0393 (0.0303) Prec@1 91.000 (95.065) Prec@5 100.000 (99.913) +2022-11-14 16:32:53,846 Epoch: [355][460/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0370 (0.0304) Prec@1 93.000 (95.021) Prec@5 98.000 (99.872) +2022-11-14 16:32:54,378 Epoch: [355][470/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0303 (0.0304) Prec@1 95.000 (95.021) Prec@5 100.000 (99.875) +2022-11-14 16:32:54,909 Epoch: [355][480/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0317 (0.0304) Prec@1 95.000 (95.020) Prec@5 100.000 (99.878) +2022-11-14 16:32:55,440 Epoch: [355][490/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0260 (0.0303) Prec@1 96.000 (95.040) Prec@5 100.000 (99.880) +2022-11-14 16:32:55,916 Epoch: [355][499/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0204 (0.0301) Prec@1 97.000 (95.078) Prec@5 100.000 (99.882) +2022-11-14 16:32:56,257 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0738 (0.0738) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:32:56,266 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0759) Prec@1 88.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 16:32:56,276 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0688) Prec@1 93.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:32:56,293 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0709) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:32:56,303 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0871 (0.0741) Prec@1 86.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 16:32:56,316 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0501 (0.0701) Prec@1 91.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 16:32:56,328 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0688) Prec@1 91.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:32:56,344 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0702) Prec@1 86.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 16:32:56,359 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0697) Prec@1 91.000 (89.000) Prec@5 100.000 (99.778) +2022-11-14 16:32:56,376 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0710) Prec@1 89.000 (89.000) Prec@5 98.000 (99.600) +2022-11-14 16:32:56,392 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0688) Prec@1 91.000 (89.182) Prec@5 100.000 (99.636) +2022-11-14 16:32:56,407 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0698) Prec@1 88.000 (89.083) Prec@5 100.000 (99.667) +2022-11-14 16:32:56,424 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0677) Prec@1 93.000 (89.385) Prec@5 100.000 (99.692) +2022-11-14 16:32:56,442 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0679) Prec@1 91.000 (89.500) Prec@5 99.000 (99.643) +2022-11-14 16:32:56,458 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0684) Prec@1 87.000 (89.333) Prec@5 99.000 (99.600) +2022-11-14 16:32:56,474 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0680) Prec@1 92.000 (89.500) Prec@5 100.000 (99.625) +2022-11-14 16:32:56,495 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0677) Prec@1 90.000 (89.529) Prec@5 99.000 (99.588) +2022-11-14 16:32:56,514 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1157 (0.0703) Prec@1 84.000 (89.222) Prec@5 100.000 (99.611) +2022-11-14 16:32:56,532 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0718) Prec@1 83.000 (88.895) Prec@5 97.000 (99.474) +2022-11-14 16:32:56,551 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1000 (0.0732) Prec@1 85.000 (88.700) Prec@5 98.000 (99.400) +2022-11-14 16:32:56,569 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1082 (0.0749) Prec@1 81.000 (88.333) Prec@5 100.000 (99.429) +2022-11-14 16:32:56,587 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0758) Prec@1 86.000 (88.227) Prec@5 98.000 (99.364) +2022-11-14 16:32:56,604 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0937 (0.0766) Prec@1 85.000 (88.087) Prec@5 98.000 (99.304) +2022-11-14 16:32:56,624 Test: [23/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0768) Prec@1 89.000 (88.125) Prec@5 100.000 (99.333) +2022-11-14 16:32:56,644 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0952 (0.0775) Prec@1 84.000 (87.960) Prec@5 99.000 (99.320) +2022-11-14 16:32:56,664 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0774) Prec@1 87.000 (87.923) Prec@5 100.000 (99.346) +2022-11-14 16:32:56,682 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0471 (0.0763) Prec@1 93.000 (88.111) Prec@5 100.000 (99.370) +2022-11-14 16:32:56,700 Test: [27/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0758) Prec@1 90.000 (88.179) Prec@5 100.000 (99.393) +2022-11-14 16:32:56,720 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0755) Prec@1 88.000 (88.172) Prec@5 98.000 (99.345) +2022-11-14 16:32:56,743 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0752) Prec@1 89.000 (88.200) Prec@5 100.000 (99.367) +2022-11-14 16:32:56,764 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0823 (0.0754) Prec@1 86.000 (88.129) Prec@5 99.000 (99.355) +2022-11-14 16:32:56,778 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0753) Prec@1 88.000 (88.125) Prec@5 100.000 (99.375) +2022-11-14 16:32:56,794 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0750) Prec@1 90.000 (88.182) Prec@5 100.000 (99.394) +2022-11-14 16:32:56,814 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1046 (0.0758) Prec@1 82.000 (88.000) Prec@5 100.000 (99.412) +2022-11-14 16:32:56,836 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0757) Prec@1 89.000 (88.029) Prec@5 99.000 (99.400) +2022-11-14 16:32:56,854 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0753) Prec@1 89.000 (88.056) Prec@5 100.000 (99.417) +2022-11-14 16:32:56,870 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0752) Prec@1 90.000 (88.108) Prec@5 99.000 (99.405) +2022-11-14 16:32:56,888 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0752) Prec@1 88.000 (88.105) Prec@5 100.000 (99.421) +2022-11-14 16:32:56,908 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0750) Prec@1 89.000 (88.128) Prec@5 99.000 (99.410) +2022-11-14 16:32:56,927 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0744) Prec@1 92.000 (88.225) Prec@5 99.000 (99.400) +2022-11-14 16:32:56,947 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0750) Prec@1 83.000 (88.098) Prec@5 99.000 (99.390) +2022-11-14 16:32:56,965 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0748) Prec@1 92.000 (88.190) Prec@5 99.000 (99.381) +2022-11-14 16:32:56,981 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0400 (0.0740) Prec@1 93.000 (88.302) Prec@5 99.000 (99.372) +2022-11-14 16:32:57,000 Test: [43/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0739) Prec@1 89.000 (88.318) Prec@5 99.000 (99.364) +2022-11-14 16:32:57,020 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0556 (0.0735) Prec@1 89.000 (88.333) Prec@5 100.000 (99.378) +2022-11-14 16:32:57,039 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0741) Prec@1 84.000 (88.239) Prec@5 99.000 (99.370) +2022-11-14 16:32:57,057 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0737) Prec@1 92.000 (88.319) Prec@5 100.000 (99.383) +2022-11-14 16:32:57,076 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0975 (0.0742) Prec@1 84.000 (88.229) Prec@5 100.000 (99.396) +2022-11-14 16:32:57,095 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0504 (0.0737) Prec@1 91.000 (88.286) Prec@5 100.000 (99.408) +2022-11-14 16:32:57,114 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0744) Prec@1 82.000 (88.160) Prec@5 99.000 (99.400) +2022-11-14 16:32:57,132 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0740) Prec@1 92.000 (88.235) Prec@5 100.000 (99.412) +2022-11-14 16:32:57,152 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0743) Prec@1 86.000 (88.192) Prec@5 99.000 (99.404) +2022-11-14 16:32:57,170 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0743) Prec@1 85.000 (88.132) Prec@5 100.000 (99.415) +2022-11-14 16:32:57,189 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0742) Prec@1 90.000 (88.167) Prec@5 98.000 (99.389) +2022-11-14 16:32:57,207 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0766 (0.0743) Prec@1 87.000 (88.145) Prec@5 100.000 (99.400) +2022-11-14 16:32:57,224 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0742) Prec@1 88.000 (88.143) Prec@5 98.000 (99.375) +2022-11-14 16:32:57,241 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0742) Prec@1 88.000 (88.140) Prec@5 100.000 (99.386) +2022-11-14 16:32:57,258 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0741) Prec@1 88.000 (88.138) Prec@5 100.000 (99.397) +2022-11-14 16:32:57,276 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0740) Prec@1 91.000 (88.186) Prec@5 99.000 (99.390) +2022-11-14 16:32:57,298 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0740) Prec@1 85.000 (88.133) Prec@5 99.000 (99.383) +2022-11-14 16:32:57,313 Test: [60/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0742) Prec@1 87.000 (88.115) Prec@5 100.000 (99.393) +2022-11-14 16:32:57,330 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0741) Prec@1 89.000 (88.129) Prec@5 100.000 (99.403) +2022-11-14 16:32:57,348 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0741) Prec@1 86.000 (88.095) Prec@5 100.000 (99.413) +2022-11-14 16:32:57,366 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0739) Prec@1 90.000 (88.125) Prec@5 100.000 (99.422) +2022-11-14 16:32:57,385 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0742) Prec@1 87.000 (88.108) Prec@5 99.000 (99.415) +2022-11-14 16:32:57,402 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0742) Prec@1 88.000 (88.106) Prec@5 99.000 (99.409) +2022-11-14 16:32:57,421 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0473 (0.0738) Prec@1 92.000 (88.164) Prec@5 100.000 (99.418) +2022-11-14 16:32:57,441 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0739) Prec@1 87.000 (88.147) Prec@5 98.000 (99.397) +2022-11-14 16:32:57,457 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0741) Prec@1 85.000 (88.101) Prec@5 99.000 (99.391) +2022-11-14 16:32:57,476 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0740) Prec@1 90.000 (88.129) Prec@5 99.000 (99.386) +2022-11-14 16:32:57,497 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0742) Prec@1 90.000 (88.155) Prec@5 99.000 (99.380) +2022-11-14 16:32:57,516 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0739) Prec@1 91.000 (88.194) Prec@5 100.000 (99.389) +2022-11-14 16:32:57,534 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0737) Prec@1 92.000 (88.247) Prec@5 100.000 (99.397) +2022-11-14 16:32:57,553 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0451 (0.0733) Prec@1 95.000 (88.338) Prec@5 100.000 (99.405) +2022-11-14 16:32:57,569 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1121 (0.0739) Prec@1 84.000 (88.280) Prec@5 100.000 (99.413) +2022-11-14 16:32:57,584 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0737) Prec@1 90.000 (88.303) Prec@5 100.000 (99.421) +2022-11-14 16:32:57,603 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0735) Prec@1 92.000 (88.351) Prec@5 100.000 (99.429) +2022-11-14 16:32:57,620 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1050 (0.0739) Prec@1 84.000 (88.295) Prec@5 99.000 (99.423) +2022-11-14 16:32:57,639 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0741) Prec@1 86.000 (88.266) Prec@5 99.000 (99.418) +2022-11-14 16:32:57,662 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0742) Prec@1 87.000 (88.250) Prec@5 100.000 (99.425) +2022-11-14 16:32:57,680 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0743) Prec@1 87.000 (88.235) Prec@5 98.000 (99.407) +2022-11-14 16:32:57,698 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0747) Prec@1 81.000 (88.146) Prec@5 100.000 (99.415) +2022-11-14 16:32:57,714 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0749) Prec@1 86.000 (88.120) Prec@5 100.000 (99.422) +2022-11-14 16:32:57,733 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0748) Prec@1 90.000 (88.143) Prec@5 99.000 (99.417) +2022-11-14 16:32:57,753 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0883 (0.0750) Prec@1 85.000 (88.106) Prec@5 99.000 (99.412) +2022-11-14 16:32:57,769 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1161 (0.0755) Prec@1 84.000 (88.058) Prec@5 98.000 (99.395) +2022-11-14 16:32:57,783 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0454 (0.0751) Prec@1 92.000 (88.103) Prec@5 99.000 (99.391) +2022-11-14 16:32:57,802 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0753) Prec@1 89.000 (88.114) Prec@5 98.000 (99.375) +2022-11-14 16:32:57,821 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0753) Prec@1 86.000 (88.090) Prec@5 100.000 (99.382) +2022-11-14 16:32:57,837 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0752) Prec@1 88.000 (88.089) Prec@5 99.000 (99.378) +2022-11-14 16:32:57,858 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0752) Prec@1 90.000 (88.110) Prec@5 99.000 (99.374) +2022-11-14 16:32:57,878 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0749) Prec@1 92.000 (88.152) Prec@5 100.000 (99.380) +2022-11-14 16:32:57,897 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0751) Prec@1 86.000 (88.129) Prec@5 100.000 (99.387) +2022-11-14 16:32:57,913 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0750) Prec@1 90.000 (88.149) Prec@5 100.000 (99.394) +2022-11-14 16:32:57,930 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0750) Prec@1 87.000 (88.137) Prec@5 99.000 (99.389) +2022-11-14 16:32:57,948 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0750) Prec@1 87.000 (88.125) Prec@5 99.000 (99.385) +2022-11-14 16:32:57,969 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0747) Prec@1 90.000 (88.144) Prec@5 98.000 (99.371) +2022-11-14 16:32:57,986 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0748) Prec@1 88.000 (88.143) Prec@5 97.000 (99.347) +2022-11-14 16:32:58,005 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1018 (0.0751) Prec@1 83.000 (88.091) Prec@5 98.000 (99.333) +2022-11-14 16:32:58,026 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0751) Prec@1 85.000 (88.060) Prec@5 100.000 (99.340) +2022-11-14 16:32:58,107 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:32:58,520 Epoch: [356][0/500] Time 0.036 (0.036) Data 0.302 (0.302) Loss 0.0248 (0.0248) Prec@1 96.000 (96.000) Prec@5 99.000 (99.000) +2022-11-14 16:32:59,046 Epoch: [356][10/500] Time 0.040 (0.045) Data 0.002 (0.030) Loss 0.0385 (0.0316) Prec@1 94.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:32:59,588 Epoch: [356][20/500] Time 0.060 (0.047) Data 0.002 (0.016) Loss 0.0328 (0.0320) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:33:00,165 Epoch: [356][30/500] Time 0.055 (0.049) Data 0.002 (0.012) Loss 0.0317 (0.0319) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:33:00,723 Epoch: [356][40/500] Time 0.061 (0.049) Data 0.002 (0.010) Loss 0.0164 (0.0288) Prec@1 99.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 16:33:01,249 Epoch: [356][50/500] Time 0.047 (0.049) Data 0.002 (0.008) Loss 0.0114 (0.0259) Prec@1 98.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 16:33:01,789 Epoch: [356][60/500] Time 0.039 (0.049) Data 0.002 (0.007) Loss 0.0197 (0.0250) Prec@1 96.000 (96.143) Prec@5 100.000 (99.857) +2022-11-14 16:33:02,353 Epoch: [356][70/500] Time 0.054 (0.049) Data 0.002 (0.006) Loss 0.0249 (0.0250) Prec@1 95.000 (96.000) Prec@5 100.000 (99.875) +2022-11-14 16:33:02,907 Epoch: [356][80/500] Time 0.051 (0.049) Data 0.002 (0.006) Loss 0.0166 (0.0241) Prec@1 97.000 (96.111) Prec@5 100.000 (99.889) +2022-11-14 16:33:03,462 Epoch: [356][90/500] Time 0.057 (0.049) Data 0.002 (0.005) Loss 0.0507 (0.0267) Prec@1 94.000 (95.900) Prec@5 100.000 (99.900) +2022-11-14 16:33:04,001 Epoch: [356][100/500] Time 0.051 (0.049) Data 0.003 (0.005) Loss 0.0334 (0.0273) Prec@1 93.000 (95.636) Prec@5 100.000 (99.909) +2022-11-14 16:33:04,546 Epoch: [356][110/500] Time 0.057 (0.049) Data 0.002 (0.005) Loss 0.0155 (0.0264) Prec@1 97.000 (95.750) Prec@5 100.000 (99.917) +2022-11-14 16:33:05,128 Epoch: [356][120/500] Time 0.054 (0.049) Data 0.003 (0.005) Loss 0.0276 (0.0264) Prec@1 95.000 (95.692) Prec@5 100.000 (99.923) +2022-11-14 16:33:05,667 Epoch: [356][130/500] Time 0.048 (0.049) Data 0.002 (0.004) Loss 0.0452 (0.0278) Prec@1 92.000 (95.429) Prec@5 99.000 (99.857) +2022-11-14 16:33:06,210 Epoch: [356][140/500] Time 0.060 (0.049) Data 0.002 (0.004) Loss 0.0366 (0.0284) Prec@1 92.000 (95.200) Prec@5 100.000 (99.867) +2022-11-14 16:33:06,730 Epoch: [356][150/500] Time 0.046 (0.049) Data 0.002 (0.004) Loss 0.0357 (0.0288) Prec@1 96.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:33:07,298 Epoch: [356][160/500] Time 0.062 (0.049) Data 0.002 (0.004) Loss 0.0484 (0.0300) Prec@1 94.000 (95.176) Prec@5 100.000 (99.882) +2022-11-14 16:33:07,846 Epoch: [356][170/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0261 (0.0298) Prec@1 95.000 (95.167) Prec@5 100.000 (99.889) +2022-11-14 16:33:08,401 Epoch: [356][180/500] Time 0.046 (0.049) Data 0.002 (0.004) Loss 0.0327 (0.0299) Prec@1 94.000 (95.105) Prec@5 100.000 (99.895) +2022-11-14 16:33:08,963 Epoch: [356][190/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0241 (0.0296) Prec@1 97.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:33:09,510 Epoch: [356][200/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0353 (0.0299) Prec@1 95.000 (95.190) Prec@5 100.000 (99.905) +2022-11-14 16:33:10,055 Epoch: [356][210/500] Time 0.052 (0.049) Data 0.002 (0.004) Loss 0.0184 (0.0294) Prec@1 95.000 (95.182) Prec@5 100.000 (99.909) +2022-11-14 16:33:10,594 Epoch: [356][220/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0356 (0.0297) Prec@1 93.000 (95.087) Prec@5 99.000 (99.870) +2022-11-14 16:33:11,128 Epoch: [356][230/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0576 (0.0308) Prec@1 88.000 (94.792) Prec@5 99.000 (99.833) +2022-11-14 16:33:11,665 Epoch: [356][240/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0321 (0.0309) Prec@1 96.000 (94.840) Prec@5 100.000 (99.840) +2022-11-14 16:33:12,208 Epoch: [356][250/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0063 (0.0299) Prec@1 98.000 (94.962) Prec@5 100.000 (99.846) +2022-11-14 16:33:12,755 Epoch: [356][260/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0246 (0.0297) Prec@1 95.000 (94.963) Prec@5 100.000 (99.852) +2022-11-14 16:33:13,322 Epoch: [356][270/500] Time 0.068 (0.049) Data 0.002 (0.003) Loss 0.0474 (0.0304) Prec@1 92.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:33:13,866 Epoch: [356][280/500] Time 0.059 (0.049) Data 0.002 (0.003) Loss 0.0371 (0.0306) Prec@1 93.000 (94.793) Prec@5 100.000 (99.862) +2022-11-14 16:33:14,409 Epoch: [356][290/500] Time 0.043 (0.049) Data 0.002 (0.003) Loss 0.0294 (0.0306) Prec@1 97.000 (94.867) Prec@5 99.000 (99.833) +2022-11-14 16:33:14,953 Epoch: [356][300/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0287 (0.0305) Prec@1 96.000 (94.903) Prec@5 100.000 (99.839) +2022-11-14 16:33:15,507 Epoch: [356][310/500] Time 0.042 (0.049) Data 0.002 (0.003) Loss 0.0240 (0.0303) Prec@1 97.000 (94.969) Prec@5 100.000 (99.844) +2022-11-14 16:33:16,059 Epoch: [356][320/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0391 (0.0306) Prec@1 94.000 (94.939) Prec@5 98.000 (99.788) +2022-11-14 16:33:16,624 Epoch: [356][330/500] Time 0.061 (0.049) Data 0.002 (0.003) Loss 0.0187 (0.0302) Prec@1 99.000 (95.059) Prec@5 100.000 (99.794) +2022-11-14 16:33:17,165 Epoch: [356][340/500] Time 0.052 (0.049) Data 0.002 (0.003) Loss 0.0332 (0.0303) Prec@1 96.000 (95.086) Prec@5 100.000 (99.800) +2022-11-14 16:33:17,722 Epoch: [356][350/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0320 (0.0303) Prec@1 94.000 (95.056) Prec@5 99.000 (99.778) +2022-11-14 16:33:18,255 Epoch: [356][360/500] Time 0.053 (0.049) Data 0.002 (0.003) Loss 0.0225 (0.0301) Prec@1 97.000 (95.108) Prec@5 100.000 (99.784) +2022-11-14 16:33:18,803 Epoch: [356][370/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0203 (0.0299) Prec@1 98.000 (95.184) Prec@5 100.000 (99.789) +2022-11-14 16:33:19,351 Epoch: [356][380/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0481 (0.0303) Prec@1 92.000 (95.103) Prec@5 100.000 (99.795) +2022-11-14 16:33:19,893 Epoch: [356][390/500] Time 0.057 (0.049) Data 0.002 (0.003) Loss 0.0316 (0.0304) Prec@1 95.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 16:33:20,436 Epoch: [356][400/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0482 (0.0308) Prec@1 92.000 (95.024) Prec@5 99.000 (99.780) +2022-11-14 16:33:20,972 Epoch: [356][410/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0438 (0.0311) Prec@1 92.000 (94.952) Prec@5 100.000 (99.786) +2022-11-14 16:33:21,514 Epoch: [356][420/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0377 (0.0313) Prec@1 94.000 (94.930) Prec@5 100.000 (99.791) +2022-11-14 16:33:22,047 Epoch: [356][430/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0216 (0.0310) Prec@1 94.000 (94.909) Prec@5 100.000 (99.795) +2022-11-14 16:33:22,592 Epoch: [356][440/500] Time 0.049 (0.049) Data 0.002 (0.003) Loss 0.0318 (0.0311) Prec@1 95.000 (94.911) Prec@5 100.000 (99.800) +2022-11-14 16:33:23,124 Epoch: [356][450/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0441 (0.0313) Prec@1 92.000 (94.848) Prec@5 100.000 (99.804) +2022-11-14 16:33:23,683 Epoch: [356][460/500] Time 0.063 (0.049) Data 0.002 (0.003) Loss 0.0369 (0.0315) Prec@1 93.000 (94.809) Prec@5 100.000 (99.809) +2022-11-14 16:33:24,211 Epoch: [356][470/500] Time 0.046 (0.049) Data 0.002 (0.003) Loss 0.0192 (0.0312) Prec@1 95.000 (94.812) Prec@5 100.000 (99.812) +2022-11-14 16:33:24,764 Epoch: [356][480/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0277 (0.0311) Prec@1 95.000 (94.816) Prec@5 100.000 (99.816) +2022-11-14 16:33:25,296 Epoch: [356][490/500] Time 0.048 (0.049) Data 0.002 (0.003) Loss 0.0553 (0.0316) Prec@1 90.000 (94.720) Prec@5 99.000 (99.800) +2022-11-14 16:33:25,798 Epoch: [356][499/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0183 (0.0314) Prec@1 99.000 (94.804) Prec@5 100.000 (99.804) +2022-11-14 16:33:26,136 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0569 (0.0569) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:33:26,145 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0781 (0.0675) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:33:26,154 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0735 (0.0695) Prec@1 88.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 16:33:26,165 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0734) Prec@1 87.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 16:33:26,175 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0700) Prec@1 93.000 (89.600) Prec@5 99.000 (99.600) +2022-11-14 16:33:26,188 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0348 (0.0642) Prec@1 95.000 (90.500) Prec@5 100.000 (99.667) +2022-11-14 16:33:26,201 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0664) Prec@1 88.000 (90.143) Prec@5 99.000 (99.571) +2022-11-14 16:33:26,215 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0687) Prec@1 85.000 (89.500) Prec@5 100.000 (99.625) +2022-11-14 16:33:26,228 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0699) Prec@1 87.000 (89.222) Prec@5 100.000 (99.667) +2022-11-14 16:33:26,245 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0713) Prec@1 87.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 16:33:26,262 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0708) Prec@1 89.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 16:33:26,278 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0730) Prec@1 85.000 (88.667) Prec@5 100.000 (99.583) +2022-11-14 16:33:26,296 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0728) Prec@1 87.000 (88.538) Prec@5 100.000 (99.615) +2022-11-14 16:33:26,311 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0728) Prec@1 88.000 (88.500) Prec@5 100.000 (99.643) +2022-11-14 16:33:26,328 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0726) Prec@1 89.000 (88.533) Prec@5 99.000 (99.600) +2022-11-14 16:33:26,348 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0728) Prec@1 88.000 (88.500) Prec@5 100.000 (99.625) +2022-11-14 16:33:26,367 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0472 (0.0713) Prec@1 92.000 (88.706) Prec@5 99.000 (99.588) +2022-11-14 16:33:26,387 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1099 (0.0735) Prec@1 84.000 (88.444) Prec@5 100.000 (99.611) +2022-11-14 16:33:26,407 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0732) Prec@1 88.000 (88.421) Prec@5 100.000 (99.632) +2022-11-14 16:33:26,424 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0911 (0.0741) Prec@1 85.000 (88.250) Prec@5 95.000 (99.400) +2022-11-14 16:33:26,440 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0742) Prec@1 88.000 (88.238) Prec@5 100.000 (99.429) +2022-11-14 16:33:26,457 Test: [21/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0753) Prec@1 85.000 (88.091) Prec@5 100.000 (99.455) +2022-11-14 16:33:26,476 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0763) Prec@1 85.000 (87.957) Prec@5 98.000 (99.391) +2022-11-14 16:33:26,497 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0764) Prec@1 88.000 (87.958) Prec@5 100.000 (99.417) +2022-11-14 16:33:26,516 Test: [24/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0772) Prec@1 86.000 (87.880) Prec@5 100.000 (99.440) +2022-11-14 16:33:26,535 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0782) Prec@1 84.000 (87.731) Prec@5 98.000 (99.385) +2022-11-14 16:33:26,555 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0776) Prec@1 89.000 (87.778) Prec@5 100.000 (99.407) +2022-11-14 16:33:26,574 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0771) Prec@1 89.000 (87.821) Prec@5 99.000 (99.393) +2022-11-14 16:33:26,594 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0769) Prec@1 88.000 (87.828) Prec@5 99.000 (99.379) +2022-11-14 16:33:26,615 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0769) Prec@1 87.000 (87.800) Prec@5 99.000 (99.367) +2022-11-14 16:33:26,636 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0768) Prec@1 88.000 (87.806) Prec@5 100.000 (99.387) +2022-11-14 16:33:26,653 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0771) Prec@1 87.000 (87.781) Prec@5 99.000 (99.375) +2022-11-14 16:33:26,669 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0771) Prec@1 87.000 (87.758) Prec@5 99.000 (99.364) +2022-11-14 16:33:26,689 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0776) Prec@1 81.000 (87.559) Prec@5 100.000 (99.382) +2022-11-14 16:33:26,710 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0777) Prec@1 87.000 (87.543) Prec@5 97.000 (99.314) +2022-11-14 16:33:26,729 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0771) Prec@1 93.000 (87.694) Prec@5 100.000 (99.333) +2022-11-14 16:33:26,748 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0773) Prec@1 86.000 (87.649) Prec@5 99.000 (99.324) +2022-11-14 16:33:26,766 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0776) Prec@1 85.000 (87.579) Prec@5 98.000 (99.289) +2022-11-14 16:33:26,787 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0771) Prec@1 93.000 (87.718) Prec@5 99.000 (99.282) +2022-11-14 16:33:26,805 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0769) Prec@1 90.000 (87.775) Prec@5 100.000 (99.300) +2022-11-14 16:33:26,822 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0773) Prec@1 83.000 (87.659) Prec@5 97.000 (99.244) +2022-11-14 16:33:26,844 Test: [41/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0770) Prec@1 92.000 (87.762) Prec@5 99.000 (99.238) +2022-11-14 16:33:26,859 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0766) Prec@1 90.000 (87.814) Prec@5 99.000 (99.233) +2022-11-14 16:33:26,878 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0764) Prec@1 88.000 (87.818) Prec@5 99.000 (99.227) +2022-11-14 16:33:26,898 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0759) Prec@1 91.000 (87.889) Prec@5 99.000 (99.222) +2022-11-14 16:33:26,913 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0980 (0.0764) Prec@1 85.000 (87.826) Prec@5 100.000 (99.239) +2022-11-14 16:33:26,935 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0759) Prec@1 91.000 (87.894) Prec@5 99.000 (99.234) +2022-11-14 16:33:26,952 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0765) Prec@1 85.000 (87.833) Prec@5 99.000 (99.229) +2022-11-14 16:33:26,970 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0758) Prec@1 95.000 (87.980) Prec@5 100.000 (99.245) +2022-11-14 16:33:26,990 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1126 (0.0766) Prec@1 81.000 (87.840) Prec@5 99.000 (99.240) +2022-11-14 16:33:27,011 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0763) Prec@1 91.000 (87.902) Prec@5 100.000 (99.255) +2022-11-14 16:33:27,026 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0766) Prec@1 85.000 (87.846) Prec@5 100.000 (99.269) +2022-11-14 16:33:27,044 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0766) Prec@1 88.000 (87.849) Prec@5 100.000 (99.283) +2022-11-14 16:33:27,061 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0764) Prec@1 89.000 (87.870) Prec@5 100.000 (99.296) +2022-11-14 16:33:27,079 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0763) Prec@1 87.000 (87.855) Prec@5 100.000 (99.309) +2022-11-14 16:33:27,098 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0762) Prec@1 89.000 (87.875) Prec@5 99.000 (99.304) +2022-11-14 16:33:27,117 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0761) Prec@1 88.000 (87.877) Prec@5 100.000 (99.316) +2022-11-14 16:33:27,133 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0759) Prec@1 90.000 (87.914) Prec@5 100.000 (99.328) +2022-11-14 16:33:27,151 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0764) Prec@1 82.000 (87.814) Prec@5 99.000 (99.322) +2022-11-14 16:33:27,166 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0766) Prec@1 86.000 (87.783) Prec@5 100.000 (99.333) +2022-11-14 16:33:27,186 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0765) Prec@1 89.000 (87.803) Prec@5 100.000 (99.344) +2022-11-14 16:33:27,204 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0762) Prec@1 91.000 (87.855) Prec@5 100.000 (99.355) +2022-11-14 16:33:27,222 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0760) Prec@1 89.000 (87.873) Prec@5 99.000 (99.349) +2022-11-14 16:33:27,239 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0757) Prec@1 90.000 (87.906) Prec@5 100.000 (99.359) +2022-11-14 16:33:27,255 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0759) Prec@1 86.000 (87.877) Prec@5 100.000 (99.369) +2022-11-14 16:33:27,271 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0759) Prec@1 88.000 (87.879) Prec@5 100.000 (99.379) +2022-11-14 16:33:27,285 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0755) Prec@1 93.000 (87.955) Prec@5 100.000 (99.388) +2022-11-14 16:33:27,303 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0754) Prec@1 89.000 (87.971) Prec@5 100.000 (99.397) +2022-11-14 16:33:27,325 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0514 (0.0750) Prec@1 92.000 (88.029) Prec@5 99.000 (99.391) +2022-11-14 16:33:27,344 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0751) Prec@1 89.000 (88.043) Prec@5 97.000 (99.357) +2022-11-14 16:33:27,365 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0755) Prec@1 85.000 (88.000) Prec@5 98.000 (99.338) +2022-11-14 16:33:27,387 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0752) Prec@1 90.000 (88.028) Prec@5 100.000 (99.347) +2022-11-14 16:33:27,409 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0748) Prec@1 92.000 (88.082) Prec@5 100.000 (99.356) +2022-11-14 16:33:27,426 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0744) Prec@1 93.000 (88.149) Prec@5 100.000 (99.365) +2022-11-14 16:33:27,445 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0745) Prec@1 87.000 (88.133) Prec@5 100.000 (99.373) +2022-11-14 16:33:27,466 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0743) Prec@1 89.000 (88.145) Prec@5 100.000 (99.382) +2022-11-14 16:33:27,485 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0742) Prec@1 90.000 (88.169) Prec@5 100.000 (99.390) +2022-11-14 16:33:27,503 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0745) Prec@1 83.000 (88.103) Prec@5 98.000 (99.372) +2022-11-14 16:33:27,522 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0744) Prec@1 90.000 (88.127) Prec@5 100.000 (99.380) +2022-11-14 16:33:27,542 Test: [79/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0744) Prec@1 87.000 (88.112) Prec@5 100.000 (99.388) +2022-11-14 16:33:27,559 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0745) Prec@1 88.000 (88.111) Prec@5 99.000 (99.383) +2022-11-14 16:33:27,580 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0747) Prec@1 86.000 (88.085) Prec@5 99.000 (99.378) +2022-11-14 16:33:27,600 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0749) Prec@1 84.000 (88.036) Prec@5 100.000 (99.386) +2022-11-14 16:33:27,620 Test: [83/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0750) Prec@1 87.000 (88.024) Prec@5 98.000 (99.369) +2022-11-14 16:33:27,639 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0751) Prec@1 83.000 (87.965) Prec@5 98.000 (99.353) +2022-11-14 16:33:27,658 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0926 (0.0753) Prec@1 83.000 (87.907) Prec@5 100.000 (99.360) +2022-11-14 16:33:27,677 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0753) Prec@1 87.000 (87.897) Prec@5 100.000 (99.368) +2022-11-14 16:33:27,697 Test: [87/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0753) Prec@1 89.000 (87.909) Prec@5 98.000 (99.352) +2022-11-14 16:33:27,717 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0752) Prec@1 89.000 (87.921) Prec@5 99.000 (99.348) +2022-11-14 16:33:27,735 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0751) Prec@1 91.000 (87.956) Prec@5 99.000 (99.344) +2022-11-14 16:33:27,756 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0749) Prec@1 90.000 (87.978) Prec@5 100.000 (99.352) +2022-11-14 16:33:27,774 Test: [91/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0749) Prec@1 91.000 (88.011) Prec@5 99.000 (99.348) +2022-11-14 16:33:27,790 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0750) Prec@1 84.000 (87.968) Prec@5 100.000 (99.355) +2022-11-14 16:33:27,808 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0749) Prec@1 92.000 (88.011) Prec@5 100.000 (99.362) +2022-11-14 16:33:27,828 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0748) Prec@1 88.000 (88.011) Prec@5 100.000 (99.368) +2022-11-14 16:33:27,847 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0749) Prec@1 89.000 (88.021) Prec@5 99.000 (99.365) +2022-11-14 16:33:27,865 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0544 (0.0746) Prec@1 91.000 (88.052) Prec@5 99.000 (99.361) +2022-11-14 16:33:27,884 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0747) Prec@1 88.000 (88.051) Prec@5 100.000 (99.367) +2022-11-14 16:33:27,903 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0750) Prec@1 85.000 (88.020) Prec@5 100.000 (99.374) +2022-11-14 16:33:27,920 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0750) Prec@1 88.000 (88.020) Prec@5 99.000 (99.370) +2022-11-14 16:33:27,986 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:33:28,345 Epoch: [357][0/500] Time 0.023 (0.023) Data 0.269 (0.269) Loss 0.0200 (0.0200) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:33:28,831 Epoch: [357][10/500] Time 0.053 (0.041) Data 0.002 (0.026) Loss 0.0118 (0.0159) Prec@1 98.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:33:29,388 Epoch: [357][20/500] Time 0.050 (0.045) Data 0.002 (0.015) Loss 0.0518 (0.0279) Prec@1 92.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:33:29,956 Epoch: [357][30/500] Time 0.053 (0.047) Data 0.002 (0.011) Loss 0.0380 (0.0304) Prec@1 93.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 16:33:30,515 Epoch: [357][40/500] Time 0.065 (0.048) Data 0.003 (0.009) Loss 0.0343 (0.0312) Prec@1 96.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:33:31,061 Epoch: [357][50/500] Time 0.052 (0.048) Data 0.002 (0.007) Loss 0.0324 (0.0314) Prec@1 96.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 16:33:31,608 Epoch: [357][60/500] Time 0.046 (0.048) Data 0.002 (0.006) Loss 0.0290 (0.0310) Prec@1 98.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 16:33:32,170 Epoch: [357][70/500] Time 0.050 (0.048) Data 0.002 (0.006) Loss 0.0324 (0.0312) Prec@1 95.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 16:33:32,719 Epoch: [357][80/500] Time 0.058 (0.048) Data 0.002 (0.005) Loss 0.0228 (0.0303) Prec@1 96.000 (95.667) Prec@5 100.000 (99.889) +2022-11-14 16:33:33,276 Epoch: [357][90/500] Time 0.057 (0.048) Data 0.002 (0.005) Loss 0.0403 (0.0313) Prec@1 91.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:33:33,842 Epoch: [357][100/500] Time 0.055 (0.049) Data 0.002 (0.005) Loss 0.0354 (0.0317) Prec@1 92.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 16:33:34,378 Epoch: [357][110/500] Time 0.043 (0.049) Data 0.002 (0.005) Loss 0.0288 (0.0314) Prec@1 95.000 (94.917) Prec@5 100.000 (99.917) +2022-11-14 16:33:34,920 Epoch: [357][120/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0283 (0.0312) Prec@1 95.000 (94.923) Prec@5 100.000 (99.923) +2022-11-14 16:33:35,478 Epoch: [357][130/500] Time 0.055 (0.049) Data 0.002 (0.004) Loss 0.0354 (0.0315) Prec@1 95.000 (94.929) Prec@5 100.000 (99.929) +2022-11-14 16:33:36,027 Epoch: [357][140/500] Time 0.040 (0.049) Data 0.002 (0.004) Loss 0.0191 (0.0307) Prec@1 97.000 (95.067) Prec@5 100.000 (99.933) +2022-11-14 16:33:36,601 Epoch: [357][150/500] Time 0.053 (0.049) Data 0.002 (0.004) Loss 0.0426 (0.0314) Prec@1 93.000 (94.938) Prec@5 99.000 (99.875) +2022-11-14 16:33:37,169 Epoch: [357][160/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0346 (0.0316) Prec@1 95.000 (94.941) Prec@5 98.000 (99.765) +2022-11-14 16:33:37,882 Epoch: [357][170/500] Time 0.087 (0.050) Data 0.002 (0.004) Loss 0.0254 (0.0313) Prec@1 98.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:33:38,710 Epoch: [357][180/500] Time 0.079 (0.051) Data 0.002 (0.004) Loss 0.0357 (0.0315) Prec@1 94.000 (95.053) Prec@5 100.000 (99.789) +2022-11-14 16:33:39,514 Epoch: [357][190/500] Time 0.095 (0.052) Data 0.002 (0.004) Loss 0.0263 (0.0312) Prec@1 95.000 (95.050) Prec@5 100.000 (99.800) +2022-11-14 16:33:40,365 Epoch: [357][200/500] Time 0.081 (0.054) Data 0.002 (0.003) Loss 0.0119 (0.0303) Prec@1 99.000 (95.238) Prec@5 100.000 (99.810) +2022-11-14 16:33:41,195 Epoch: [357][210/500] Time 0.076 (0.054) Data 0.002 (0.003) Loss 0.0381 (0.0307) Prec@1 95.000 (95.227) Prec@5 100.000 (99.818) +2022-11-14 16:33:41,970 Epoch: [357][220/500] Time 0.071 (0.055) Data 0.002 (0.003) Loss 0.0246 (0.0304) Prec@1 95.000 (95.217) Prec@5 100.000 (99.826) +2022-11-14 16:33:42,794 Epoch: [357][230/500] Time 0.079 (0.056) Data 0.002 (0.003) Loss 0.0379 (0.0307) Prec@1 93.000 (95.125) Prec@5 100.000 (99.833) +2022-11-14 16:33:43,664 Epoch: [357][240/500] Time 0.082 (0.057) Data 0.002 (0.003) Loss 0.0295 (0.0307) Prec@1 95.000 (95.120) Prec@5 100.000 (99.840) +2022-11-14 16:33:44,482 Epoch: [357][250/500] Time 0.087 (0.058) Data 0.003 (0.003) Loss 0.0301 (0.0306) Prec@1 95.000 (95.115) Prec@5 100.000 (99.846) +2022-11-14 16:33:45,340 Epoch: [357][260/500] Time 0.072 (0.058) Data 0.002 (0.003) Loss 0.0267 (0.0305) Prec@1 96.000 (95.148) Prec@5 100.000 (99.852) +2022-11-14 16:33:46,184 Epoch: [357][270/500] Time 0.083 (0.059) Data 0.002 (0.003) Loss 0.0299 (0.0305) Prec@1 93.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 16:33:46,956 Epoch: [357][280/500] Time 0.078 (0.059) Data 0.002 (0.003) Loss 0.0190 (0.0301) Prec@1 96.000 (95.103) Prec@5 100.000 (99.862) +2022-11-14 16:33:47,794 Epoch: [357][290/500] Time 0.075 (0.060) Data 0.002 (0.003) Loss 0.0239 (0.0299) Prec@1 97.000 (95.167) Prec@5 99.000 (99.833) +2022-11-14 16:33:48,617 Epoch: [357][300/500] Time 0.071 (0.060) Data 0.002 (0.003) Loss 0.0346 (0.0300) Prec@1 94.000 (95.129) Prec@5 100.000 (99.839) +2022-11-14 16:33:49,446 Epoch: [357][310/500] Time 0.066 (0.061) Data 0.002 (0.003) Loss 0.0244 (0.0298) Prec@1 95.000 (95.125) Prec@5 100.000 (99.844) +2022-11-14 16:33:50,289 Epoch: [357][320/500] Time 0.094 (0.061) Data 0.002 (0.003) Loss 0.0209 (0.0296) Prec@1 97.000 (95.182) Prec@5 100.000 (99.848) +2022-11-14 16:33:51,129 Epoch: [357][330/500] Time 0.084 (0.062) Data 0.002 (0.003) Loss 0.0129 (0.0291) Prec@1 98.000 (95.265) Prec@5 100.000 (99.853) +2022-11-14 16:33:51,975 Epoch: [357][340/500] Time 0.086 (0.062) Data 0.002 (0.003) Loss 0.0488 (0.0297) Prec@1 92.000 (95.171) Prec@5 100.000 (99.857) +2022-11-14 16:33:52,824 Epoch: [357][350/500] Time 0.081 (0.062) Data 0.002 (0.003) Loss 0.0295 (0.0296) Prec@1 95.000 (95.167) Prec@5 100.000 (99.861) +2022-11-14 16:33:53,671 Epoch: [357][360/500] Time 0.079 (0.063) Data 0.002 (0.003) Loss 0.0405 (0.0299) Prec@1 94.000 (95.135) Prec@5 100.000 (99.865) +2022-11-14 16:33:54,508 Epoch: [357][370/500] Time 0.090 (0.063) Data 0.002 (0.003) Loss 0.0368 (0.0301) Prec@1 93.000 (95.079) Prec@5 100.000 (99.868) +2022-11-14 16:33:55,371 Epoch: [357][380/500] Time 0.080 (0.064) Data 0.002 (0.003) Loss 0.0150 (0.0297) Prec@1 98.000 (95.154) Prec@5 100.000 (99.872) +2022-11-14 16:33:56,210 Epoch: [357][390/500] Time 0.080 (0.064) Data 0.002 (0.003) Loss 0.0290 (0.0297) Prec@1 96.000 (95.175) Prec@5 100.000 (99.875) +2022-11-14 16:33:57,017 Epoch: [357][400/500] Time 0.077 (0.064) Data 0.002 (0.003) Loss 0.0550 (0.0303) Prec@1 89.000 (95.024) Prec@5 100.000 (99.878) +2022-11-14 16:33:57,828 Epoch: [357][410/500] Time 0.071 (0.064) Data 0.002 (0.003) Loss 0.0301 (0.0303) Prec@1 95.000 (95.024) Prec@5 100.000 (99.881) +2022-11-14 16:33:58,674 Epoch: [357][420/500] Time 0.079 (0.064) Data 0.002 (0.003) Loss 0.0517 (0.0308) Prec@1 92.000 (94.953) Prec@5 99.000 (99.860) +2022-11-14 16:33:59,479 Epoch: [357][430/500] Time 0.076 (0.065) Data 0.002 (0.003) Loss 0.0323 (0.0309) Prec@1 95.000 (94.955) Prec@5 100.000 (99.864) +2022-11-14 16:34:00,274 Epoch: [357][440/500] Time 0.075 (0.065) Data 0.002 (0.003) Loss 0.0215 (0.0307) Prec@1 96.000 (94.978) Prec@5 100.000 (99.867) +2022-11-14 16:34:01,067 Epoch: [357][450/500] Time 0.074 (0.065) Data 0.002 (0.003) Loss 0.0274 (0.0306) Prec@1 95.000 (94.978) Prec@5 100.000 (99.870) +2022-11-14 16:34:01,871 Epoch: [357][460/500] Time 0.084 (0.065) Data 0.002 (0.003) Loss 0.0349 (0.0307) Prec@1 95.000 (94.979) Prec@5 100.000 (99.872) +2022-11-14 16:34:02,532 Epoch: [357][470/500] Time 0.052 (0.065) Data 0.002 (0.003) Loss 0.0225 (0.0305) Prec@1 96.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 16:34:03,132 Epoch: [357][480/500] Time 0.062 (0.065) Data 0.002 (0.003) Loss 0.0353 (0.0306) Prec@1 94.000 (94.980) Prec@5 100.000 (99.878) +2022-11-14 16:34:03,731 Epoch: [357][490/500] Time 0.051 (0.065) Data 0.002 (0.003) Loss 0.0201 (0.0304) Prec@1 97.000 (95.020) Prec@5 100.000 (99.880) +2022-11-14 16:34:04,263 Epoch: [357][499/500] Time 0.053 (0.064) Data 0.002 (0.003) Loss 0.0283 (0.0304) Prec@1 97.000 (95.059) Prec@5 100.000 (99.882) +2022-11-14 16:34:04,633 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0539 (0.0539) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:34:04,642 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0595 (0.0567) Prec@1 91.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:34:04,651 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0634 (0.0589) Prec@1 89.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:34:04,664 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0616) Prec@1 91.000 (90.750) Prec@5 99.000 (99.750) +2022-11-14 16:34:04,673 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0645) Prec@1 86.000 (89.800) Prec@5 99.000 (99.600) +2022-11-14 16:34:04,684 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0619) Prec@1 92.000 (90.167) Prec@5 99.000 (99.500) +2022-11-14 16:34:04,694 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0619) Prec@1 89.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 16:34:04,706 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1040 (0.0672) Prec@1 82.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:34:04,716 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0677) Prec@1 90.000 (89.111) Prec@5 100.000 (99.556) +2022-11-14 16:34:04,726 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0683) Prec@1 89.000 (89.100) Prec@5 99.000 (99.500) +2022-11-14 16:34:04,738 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0671) Prec@1 92.000 (89.364) Prec@5 100.000 (99.545) +2022-11-14 16:34:04,748 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0673) Prec@1 87.000 (89.167) Prec@5 100.000 (99.583) +2022-11-14 16:34:04,758 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0663) Prec@1 92.000 (89.385) Prec@5 100.000 (99.615) +2022-11-14 16:34:04,767 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0908 (0.0680) Prec@1 85.000 (89.071) Prec@5 100.000 (99.643) +2022-11-14 16:34:04,776 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0695) Prec@1 83.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:34:04,785 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0689) Prec@1 91.000 (88.812) Prec@5 100.000 (99.688) +2022-11-14 16:34:04,796 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0453 (0.0675) Prec@1 94.000 (89.118) Prec@5 99.000 (99.647) +2022-11-14 16:34:04,805 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1125 (0.0700) Prec@1 82.000 (88.722) Prec@5 100.000 (99.667) +2022-11-14 16:34:04,815 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0699) Prec@1 87.000 (88.632) Prec@5 100.000 (99.684) +2022-11-14 16:34:04,826 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0708) Prec@1 87.000 (88.550) Prec@5 97.000 (99.550) +2022-11-14 16:34:04,837 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0718) Prec@1 85.000 (88.381) Prec@5 100.000 (99.571) +2022-11-14 16:34:04,849 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0722) Prec@1 88.000 (88.364) Prec@5 100.000 (99.591) +2022-11-14 16:34:04,859 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0739) Prec@1 84.000 (88.174) Prec@5 97.000 (99.478) +2022-11-14 16:34:04,868 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0741) Prec@1 89.000 (88.208) Prec@5 100.000 (99.500) +2022-11-14 16:34:04,879 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0793 (0.0743) Prec@1 87.000 (88.160) Prec@5 100.000 (99.520) +2022-11-14 16:34:04,891 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0751) Prec@1 85.000 (88.038) Prec@5 97.000 (99.423) +2022-11-14 16:34:04,904 Test: [26/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0744) Prec@1 91.000 (88.148) Prec@5 100.000 (99.444) +2022-11-14 16:34:04,915 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0735) Prec@1 94.000 (88.357) Prec@5 100.000 (99.464) +2022-11-14 16:34:04,927 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0734) Prec@1 89.000 (88.379) Prec@5 99.000 (99.448) +2022-11-14 16:34:04,939 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0730) Prec@1 90.000 (88.433) Prec@5 100.000 (99.467) +2022-11-14 16:34:04,950 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0728) Prec@1 88.000 (88.419) Prec@5 100.000 (99.484) +2022-11-14 16:34:04,959 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0728) Prec@1 90.000 (88.469) Prec@5 99.000 (99.469) +2022-11-14 16:34:04,969 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0729) Prec@1 87.000 (88.424) Prec@5 99.000 (99.455) +2022-11-14 16:34:04,980 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0729) Prec@1 88.000 (88.412) Prec@5 100.000 (99.471) +2022-11-14 16:34:04,991 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0732) Prec@1 88.000 (88.400) Prec@5 99.000 (99.457) +2022-11-14 16:34:05,001 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0733) Prec@1 89.000 (88.417) Prec@5 99.000 (99.444) +2022-11-14 16:34:05,011 Test: [36/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0728) Prec@1 89.000 (88.432) Prec@5 99.000 (99.432) +2022-11-14 16:34:05,020 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0987 (0.0735) Prec@1 81.000 (88.237) Prec@5 99.000 (99.421) +2022-11-14 16:34:05,029 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0567 (0.0731) Prec@1 93.000 (88.359) Prec@5 99.000 (99.410) +2022-11-14 16:34:05,040 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0642 (0.0729) Prec@1 90.000 (88.400) Prec@5 100.000 (99.425) +2022-11-14 16:34:05,049 Test: [40/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0733) Prec@1 86.000 (88.341) Prec@5 99.000 (99.415) +2022-11-14 16:34:05,060 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0730) Prec@1 91.000 (88.405) Prec@5 100.000 (99.429) +2022-11-14 16:34:05,071 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0724) Prec@1 92.000 (88.488) Prec@5 99.000 (99.419) +2022-11-14 16:34:05,081 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0721) Prec@1 90.000 (88.523) Prec@5 99.000 (99.409) +2022-11-14 16:34:05,091 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0721) Prec@1 89.000 (88.533) Prec@5 98.000 (99.378) +2022-11-14 16:34:05,102 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0730) Prec@1 81.000 (88.370) Prec@5 99.000 (99.370) +2022-11-14 16:34:05,113 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0726) Prec@1 89.000 (88.383) Prec@5 100.000 (99.383) +2022-11-14 16:34:05,124 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0734) Prec@1 84.000 (88.292) Prec@5 98.000 (99.354) +2022-11-14 16:34:05,135 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0507 (0.0730) Prec@1 92.000 (88.367) Prec@5 100.000 (99.367) +2022-11-14 16:34:05,145 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1054 (0.0736) Prec@1 84.000 (88.280) Prec@5 98.000 (99.340) +2022-11-14 16:34:05,155 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0733) Prec@1 90.000 (88.314) Prec@5 100.000 (99.353) +2022-11-14 16:34:05,165 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0735) Prec@1 86.000 (88.269) Prec@5 99.000 (99.346) +2022-11-14 16:34:05,175 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0735) Prec@1 88.000 (88.264) Prec@5 100.000 (99.358) +2022-11-14 16:34:05,185 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0736) Prec@1 87.000 (88.241) Prec@5 100.000 (99.370) +2022-11-14 16:34:05,196 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0737) Prec@1 87.000 (88.218) Prec@5 100.000 (99.382) +2022-11-14 16:34:05,208 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0739) Prec@1 86.000 (88.179) Prec@5 99.000 (99.375) +2022-11-14 16:34:05,217 Test: [56/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0737) Prec@1 90.000 (88.211) Prec@5 100.000 (99.386) +2022-11-14 16:34:05,227 Test: [57/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0737) Prec@1 89.000 (88.224) Prec@5 100.000 (99.397) +2022-11-14 16:34:05,238 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0740) Prec@1 87.000 (88.203) Prec@5 99.000 (99.390) +2022-11-14 16:34:05,248 Test: [59/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0740) Prec@1 87.000 (88.183) Prec@5 99.000 (99.383) +2022-11-14 16:34:05,258 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0739) Prec@1 87.000 (88.164) Prec@5 98.000 (99.361) +2022-11-14 16:34:05,268 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0739) Prec@1 89.000 (88.177) Prec@5 99.000 (99.355) +2022-11-14 16:34:05,278 Test: [62/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0739) Prec@1 87.000 (88.159) Prec@5 100.000 (99.365) +2022-11-14 16:34:05,287 Test: [63/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0734) Prec@1 94.000 (88.250) Prec@5 100.000 (99.375) +2022-11-14 16:34:05,298 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1031 (0.0739) Prec@1 86.000 (88.215) Prec@5 99.000 (99.369) +2022-11-14 16:34:05,308 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0741) Prec@1 85.000 (88.167) Prec@5 100.000 (99.379) +2022-11-14 16:34:05,319 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0738) Prec@1 90.000 (88.194) Prec@5 100.000 (99.388) +2022-11-14 16:34:05,330 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0736) Prec@1 91.000 (88.235) Prec@5 99.000 (99.382) +2022-11-14 16:34:05,342 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0734) Prec@1 91.000 (88.275) Prec@5 99.000 (99.377) +2022-11-14 16:34:05,353 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0735) Prec@1 88.000 (88.271) Prec@5 100.000 (99.386) +2022-11-14 16:34:05,364 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0735) Prec@1 89.000 (88.282) Prec@5 100.000 (99.394) +2022-11-14 16:34:05,374 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0733) Prec@1 92.000 (88.333) Prec@5 100.000 (99.403) +2022-11-14 16:34:05,385 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0729) Prec@1 92.000 (88.384) Prec@5 100.000 (99.411) +2022-11-14 16:34:05,397 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0726) Prec@1 91.000 (88.419) Prec@5 100.000 (99.419) +2022-11-14 16:34:05,407 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0728) Prec@1 88.000 (88.413) Prec@5 100.000 (99.427) +2022-11-14 16:34:05,416 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0730) Prec@1 88.000 (88.408) Prec@5 100.000 (99.434) +2022-11-14 16:34:05,426 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0730) Prec@1 87.000 (88.390) Prec@5 98.000 (99.416) +2022-11-14 16:34:05,439 Test: [77/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1145 (0.0736) Prec@1 82.000 (88.308) Prec@5 99.000 (99.410) +2022-11-14 16:34:05,452 Test: [78/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0734) Prec@1 90.000 (88.329) Prec@5 100.000 (99.418) +2022-11-14 16:34:05,463 Test: [79/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0734) Prec@1 88.000 (88.325) Prec@5 99.000 (99.412) +2022-11-14 16:34:05,472 Test: [80/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0734) Prec@1 87.000 (88.309) Prec@5 99.000 (99.407) +2022-11-14 16:34:05,483 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0733) Prec@1 90.000 (88.329) Prec@5 100.000 (99.415) +2022-11-14 16:34:05,495 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0735) Prec@1 84.000 (88.277) Prec@5 100.000 (99.422) +2022-11-14 16:34:05,507 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0736) Prec@1 86.000 (88.250) Prec@5 98.000 (99.405) +2022-11-14 16:34:05,516 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0738) Prec@1 83.000 (88.188) Prec@5 100.000 (99.412) +2022-11-14 16:34:05,527 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1118 (0.0743) Prec@1 82.000 (88.116) Prec@5 100.000 (99.419) +2022-11-14 16:34:05,537 Test: [86/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0742) Prec@1 90.000 (88.138) Prec@5 98.000 (99.402) +2022-11-14 16:34:05,547 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0741) Prec@1 91.000 (88.170) Prec@5 99.000 (99.398) +2022-11-14 16:34:05,557 Test: [88/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0743) Prec@1 85.000 (88.135) Prec@5 100.000 (99.404) +2022-11-14 16:34:05,567 Test: [89/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0743) Prec@1 90.000 (88.156) Prec@5 99.000 (99.400) +2022-11-14 16:34:05,577 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0741) Prec@1 91.000 (88.187) Prec@5 100.000 (99.407) +2022-11-14 16:34:05,587 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0738) Prec@1 93.000 (88.239) Prec@5 100.000 (99.413) +2022-11-14 16:34:05,598 Test: [92/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0741) Prec@1 85.000 (88.204) Prec@5 100.000 (99.419) +2022-11-14 16:34:05,609 Test: [93/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0740) Prec@1 89.000 (88.213) Prec@5 98.000 (99.404) +2022-11-14 16:34:05,619 Test: [94/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0835 (0.0741) Prec@1 86.000 (88.189) Prec@5 99.000 (99.400) +2022-11-14 16:34:05,629 Test: [95/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0741) Prec@1 90.000 (88.208) Prec@5 100.000 (99.406) +2022-11-14 16:34:05,640 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0344 (0.0737) Prec@1 93.000 (88.258) Prec@5 99.000 (99.402) +2022-11-14 16:34:05,650 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0736) Prec@1 90.000 (88.276) Prec@5 99.000 (99.398) +2022-11-14 16:34:05,661 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0739) Prec@1 86.000 (88.253) Prec@5 99.000 (99.394) +2022-11-14 16:34:05,672 Test: [99/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0738) Prec@1 90.000 (88.270) Prec@5 100.000 (99.400) +2022-11-14 16:34:05,733 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:34:06,118 Epoch: [358][0/500] Time 0.030 (0.030) Data 0.292 (0.292) Loss 0.0422 (0.0422) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:34:06,420 Epoch: [358][10/500] Time 0.032 (0.027) Data 0.002 (0.028) Loss 0.0227 (0.0324) Prec@1 97.000 (94.500) Prec@5 99.000 (99.000) +2022-11-14 16:34:06,746 Epoch: [358][20/500] Time 0.029 (0.028) Data 0.002 (0.016) Loss 0.0388 (0.0346) Prec@1 93.000 (94.000) Prec@5 100.000 (99.333) +2022-11-14 16:34:07,070 Epoch: [358][30/500] Time 0.030 (0.028) Data 0.002 (0.011) Loss 0.0245 (0.0321) Prec@1 95.000 (94.250) Prec@5 100.000 (99.500) +2022-11-14 16:34:07,394 Epoch: [358][40/500] Time 0.035 (0.029) Data 0.002 (0.009) Loss 0.0424 (0.0341) Prec@1 92.000 (93.800) Prec@5 100.000 (99.600) +2022-11-14 16:34:07,816 Epoch: [358][50/500] Time 0.046 (0.030) Data 0.002 (0.008) Loss 0.0319 (0.0338) Prec@1 95.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:34:08,324 Epoch: [358][60/500] Time 0.044 (0.033) Data 0.002 (0.007) Loss 0.0234 (0.0323) Prec@1 98.000 (94.571) Prec@5 99.000 (99.429) +2022-11-14 16:34:08,817 Epoch: [358][70/500] Time 0.048 (0.034) Data 0.002 (0.006) Loss 0.0118 (0.0297) Prec@1 99.000 (95.125) Prec@5 100.000 (99.500) +2022-11-14 16:34:09,323 Epoch: [358][80/500] Time 0.054 (0.036) Data 0.002 (0.006) Loss 0.0308 (0.0298) Prec@1 95.000 (95.111) Prec@5 99.000 (99.444) +2022-11-14 16:34:09,814 Epoch: [358][90/500] Time 0.055 (0.037) Data 0.002 (0.005) Loss 0.0218 (0.0290) Prec@1 96.000 (95.200) Prec@5 100.000 (99.500) +2022-11-14 16:34:10,312 Epoch: [358][100/500] Time 0.053 (0.037) Data 0.002 (0.005) Loss 0.0288 (0.0290) Prec@1 95.000 (95.182) Prec@5 100.000 (99.545) +2022-11-14 16:34:10,800 Epoch: [358][110/500] Time 0.044 (0.038) Data 0.002 (0.005) Loss 0.0180 (0.0281) Prec@1 96.000 (95.250) Prec@5 100.000 (99.583) +2022-11-14 16:34:11,315 Epoch: [358][120/500] Time 0.044 (0.038) Data 0.002 (0.004) Loss 0.0542 (0.0301) Prec@1 91.000 (94.923) Prec@5 100.000 (99.615) +2022-11-14 16:34:11,809 Epoch: [358][130/500] Time 0.052 (0.039) Data 0.002 (0.004) Loss 0.0373 (0.0306) Prec@1 94.000 (94.857) Prec@5 99.000 (99.571) +2022-11-14 16:34:12,330 Epoch: [358][140/500] Time 0.049 (0.039) Data 0.002 (0.004) Loss 0.0204 (0.0299) Prec@1 95.000 (94.867) Prec@5 100.000 (99.600) +2022-11-14 16:34:12,889 Epoch: [358][150/500] Time 0.066 (0.040) Data 0.002 (0.004) Loss 0.0257 (0.0297) Prec@1 95.000 (94.875) Prec@5 100.000 (99.625) +2022-11-14 16:34:13,381 Epoch: [358][160/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0219 (0.0292) Prec@1 97.000 (95.000) Prec@5 100.000 (99.647) +2022-11-14 16:34:13,898 Epoch: [358][170/500] Time 0.054 (0.041) Data 0.002 (0.004) Loss 0.0302 (0.0293) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:34:14,435 Epoch: [358][180/500] Time 0.057 (0.041) Data 0.002 (0.004) Loss 0.0443 (0.0301) Prec@1 92.000 (94.842) Prec@5 100.000 (99.684) +2022-11-14 16:34:14,941 Epoch: [358][190/500] Time 0.040 (0.041) Data 0.003 (0.004) Loss 0.0309 (0.0301) Prec@1 93.000 (94.750) Prec@5 100.000 (99.700) +2022-11-14 16:34:15,447 Epoch: [358][200/500] Time 0.047 (0.041) Data 0.002 (0.004) Loss 0.0113 (0.0292) Prec@1 99.000 (94.952) Prec@5 100.000 (99.714) +2022-11-14 16:34:15,982 Epoch: [358][210/500] Time 0.053 (0.042) Data 0.002 (0.003) Loss 0.0308 (0.0293) Prec@1 95.000 (94.955) Prec@5 99.000 (99.682) +2022-11-14 16:34:16,508 Epoch: [358][220/500] Time 0.050 (0.042) Data 0.003 (0.003) Loss 0.0275 (0.0292) Prec@1 96.000 (95.000) Prec@5 100.000 (99.696) +2022-11-14 16:34:17,026 Epoch: [358][230/500] Time 0.051 (0.042) Data 0.002 (0.003) Loss 0.0310 (0.0293) Prec@1 96.000 (95.042) Prec@5 100.000 (99.708) +2022-11-14 16:34:17,563 Epoch: [358][240/500] Time 0.052 (0.042) Data 0.003 (0.003) Loss 0.0314 (0.0294) Prec@1 95.000 (95.040) Prec@5 100.000 (99.720) +2022-11-14 16:34:18,116 Epoch: [358][250/500] Time 0.054 (0.043) Data 0.002 (0.003) Loss 0.0301 (0.0294) Prec@1 96.000 (95.077) Prec@5 100.000 (99.731) +2022-11-14 16:34:18,629 Epoch: [358][260/500] Time 0.049 (0.043) Data 0.003 (0.003) Loss 0.0377 (0.0297) Prec@1 93.000 (95.000) Prec@5 99.000 (99.704) +2022-11-14 16:34:19,133 Epoch: [358][270/500] Time 0.044 (0.043) Data 0.003 (0.003) Loss 0.0228 (0.0295) Prec@1 97.000 (95.071) Prec@5 100.000 (99.714) +2022-11-14 16:34:19,664 Epoch: [358][280/500] Time 0.041 (0.043) Data 0.002 (0.003) Loss 0.0365 (0.0297) Prec@1 94.000 (95.034) Prec@5 99.000 (99.690) +2022-11-14 16:34:20,194 Epoch: [358][290/500] Time 0.058 (0.043) Data 0.002 (0.003) Loss 0.0288 (0.0297) Prec@1 95.000 (95.033) Prec@5 100.000 (99.700) +2022-11-14 16:34:20,720 Epoch: [358][300/500] Time 0.047 (0.043) Data 0.003 (0.003) Loss 0.0350 (0.0298) Prec@1 93.000 (94.968) Prec@5 100.000 (99.710) +2022-11-14 16:34:21,249 Epoch: [358][310/500] Time 0.048 (0.044) Data 0.003 (0.003) Loss 0.0271 (0.0298) Prec@1 97.000 (95.031) Prec@5 100.000 (99.719) +2022-11-14 16:34:21,811 Epoch: [358][320/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0259 (0.0296) Prec@1 96.000 (95.061) Prec@5 100.000 (99.727) +2022-11-14 16:34:22,313 Epoch: [358][330/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0291 (0.0296) Prec@1 95.000 (95.059) Prec@5 100.000 (99.735) +2022-11-14 16:34:22,819 Epoch: [358][340/500] Time 0.039 (0.044) Data 0.002 (0.003) Loss 0.0387 (0.0299) Prec@1 93.000 (95.000) Prec@5 100.000 (99.743) +2022-11-14 16:34:23,320 Epoch: [358][350/500] Time 0.048 (0.044) Data 0.002 (0.003) Loss 0.0473 (0.0304) Prec@1 90.000 (94.861) Prec@5 98.000 (99.694) +2022-11-14 16:34:23,838 Epoch: [358][360/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0376 (0.0306) Prec@1 95.000 (94.865) Prec@5 100.000 (99.703) +2022-11-14 16:34:24,385 Epoch: [358][370/500] Time 0.049 (0.044) Data 0.002 (0.003) Loss 0.0650 (0.0315) Prec@1 87.000 (94.658) Prec@5 100.000 (99.711) +2022-11-14 16:34:24,907 Epoch: [358][380/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0275 (0.0314) Prec@1 97.000 (94.718) Prec@5 100.000 (99.718) +2022-11-14 16:34:25,415 Epoch: [358][390/500] Time 0.058 (0.044) Data 0.002 (0.003) Loss 0.0107 (0.0309) Prec@1 99.000 (94.825) Prec@5 100.000 (99.725) +2022-11-14 16:34:25,926 Epoch: [358][400/500] Time 0.044 (0.044) Data 0.002 (0.003) Loss 0.0387 (0.0310) Prec@1 94.000 (94.805) Prec@5 100.000 (99.732) +2022-11-14 16:34:26,435 Epoch: [358][410/500] Time 0.057 (0.044) Data 0.002 (0.003) Loss 0.0262 (0.0309) Prec@1 96.000 (94.833) Prec@5 100.000 (99.738) +2022-11-14 16:34:26,960 Epoch: [358][420/500] Time 0.051 (0.044) Data 0.002 (0.003) Loss 0.0427 (0.0312) Prec@1 92.000 (94.767) Prec@5 100.000 (99.744) +2022-11-14 16:34:27,453 Epoch: [358][430/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0161 (0.0309) Prec@1 99.000 (94.864) Prec@5 100.000 (99.750) +2022-11-14 16:34:27,964 Epoch: [358][440/500] Time 0.043 (0.044) Data 0.002 (0.003) Loss 0.0297 (0.0308) Prec@1 94.000 (94.844) Prec@5 100.000 (99.756) +2022-11-14 16:34:28,466 Epoch: [358][450/500] Time 0.047 (0.044) Data 0.002 (0.003) Loss 0.0524 (0.0313) Prec@1 91.000 (94.761) Prec@5 100.000 (99.761) +2022-11-14 16:34:29,025 Epoch: [358][460/500] Time 0.061 (0.044) Data 0.002 (0.003) Loss 0.0320 (0.0313) Prec@1 95.000 (94.766) Prec@5 100.000 (99.766) +2022-11-14 16:34:29,525 Epoch: [358][470/500] Time 0.042 (0.044) Data 0.002 (0.003) Loss 0.0094 (0.0309) Prec@1 100.000 (94.875) Prec@5 100.000 (99.771) +2022-11-14 16:34:30,026 Epoch: [358][480/500] Time 0.041 (0.044) Data 0.002 (0.003) Loss 0.0273 (0.0308) Prec@1 96.000 (94.898) Prec@5 100.000 (99.776) +2022-11-14 16:34:30,523 Epoch: [358][490/500] Time 0.053 (0.044) Data 0.002 (0.003) Loss 0.0279 (0.0307) Prec@1 97.000 (94.940) Prec@5 99.000 (99.760) +2022-11-14 16:34:30,996 Epoch: [358][499/500] Time 0.045 (0.044) Data 0.002 (0.003) Loss 0.0222 (0.0306) Prec@1 96.000 (94.961) Prec@5 100.000 (99.765) +2022-11-14 16:34:31,344 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:34:31,357 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0692 (0.0684) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:34:31,369 Test: [2/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0537 (0.0635) Prec@1 92.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 16:34:31,380 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0914 (0.0705) Prec@1 85.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 16:34:31,390 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0654 (0.0695) Prec@1 89.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 16:34:31,400 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0510 (0.0664) Prec@1 91.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 16:34:31,412 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0668) Prec@1 89.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 16:34:31,423 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0701) Prec@1 82.000 (88.000) Prec@5 100.000 (99.750) +2022-11-14 16:34:31,437 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0827 (0.0715) Prec@1 89.000 (88.111) Prec@5 99.000 (99.667) +2022-11-14 16:34:31,451 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0739) Prec@1 85.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 16:34:31,466 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0730) Prec@1 91.000 (88.091) Prec@5 100.000 (99.636) +2022-11-14 16:34:31,480 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0743) Prec@1 89.000 (88.167) Prec@5 100.000 (99.667) +2022-11-14 16:34:31,495 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0735) Prec@1 90.000 (88.308) Prec@5 100.000 (99.692) +2022-11-14 16:34:31,512 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0732) Prec@1 91.000 (88.500) Prec@5 98.000 (99.571) +2022-11-14 16:34:31,527 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0742) Prec@1 87.000 (88.400) Prec@5 98.000 (99.467) +2022-11-14 16:34:31,541 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0743) Prec@1 85.000 (88.188) Prec@5 98.000 (99.375) +2022-11-14 16:34:31,556 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0486 (0.0728) Prec@1 93.000 (88.471) Prec@5 98.000 (99.294) +2022-11-14 16:34:31,573 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1173 (0.0753) Prec@1 85.000 (88.278) Prec@5 100.000 (99.333) +2022-11-14 16:34:31,590 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1060 (0.0769) Prec@1 82.000 (87.947) Prec@5 98.000 (99.263) +2022-11-14 16:34:31,605 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0776) Prec@1 84.000 (87.750) Prec@5 96.000 (99.100) +2022-11-14 16:34:31,621 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0779) Prec@1 87.000 (87.714) Prec@5 99.000 (99.095) +2022-11-14 16:34:31,638 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0784) Prec@1 86.000 (87.636) Prec@5 97.000 (99.000) +2022-11-14 16:34:31,653 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1056 (0.0796) Prec@1 84.000 (87.478) Prec@5 98.000 (98.957) +2022-11-14 16:34:31,671 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0798) Prec@1 87.000 (87.458) Prec@5 99.000 (98.958) +2022-11-14 16:34:31,687 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0805) Prec@1 85.000 (87.360) Prec@5 100.000 (99.000) +2022-11-14 16:34:31,704 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0959 (0.0811) Prec@1 84.000 (87.231) Prec@5 99.000 (99.000) +2022-11-14 16:34:31,720 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0803) Prec@1 90.000 (87.333) Prec@5 100.000 (99.037) +2022-11-14 16:34:31,739 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0796) Prec@1 90.000 (87.429) Prec@5 98.000 (99.000) +2022-11-14 16:34:31,757 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0794) Prec@1 89.000 (87.483) Prec@5 98.000 (98.966) +2022-11-14 16:34:31,775 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0791) Prec@1 86.000 (87.433) Prec@5 100.000 (99.000) +2022-11-14 16:34:31,792 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0787) Prec@1 90.000 (87.516) Prec@5 100.000 (99.032) +2022-11-14 16:34:31,808 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0786) Prec@1 88.000 (87.531) Prec@5 100.000 (99.062) +2022-11-14 16:34:31,825 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0787) Prec@1 87.000 (87.515) Prec@5 100.000 (99.091) +2022-11-14 16:34:31,842 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0788) Prec@1 87.000 (87.500) Prec@5 98.000 (99.059) +2022-11-14 16:34:31,861 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0859 (0.0790) Prec@1 87.000 (87.486) Prec@5 98.000 (99.029) +2022-11-14 16:34:31,879 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0785) Prec@1 92.000 (87.611) Prec@5 100.000 (99.056) +2022-11-14 16:34:31,895 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0783) Prec@1 89.000 (87.649) Prec@5 100.000 (99.081) +2022-11-14 16:34:31,910 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0784) Prec@1 86.000 (87.605) Prec@5 98.000 (99.053) +2022-11-14 16:34:31,926 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0780) Prec@1 92.000 (87.718) Prec@5 99.000 (99.051) +2022-11-14 16:34:31,946 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0778) Prec@1 90.000 (87.775) Prec@5 98.000 (99.025) +2022-11-14 16:34:31,962 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0778) Prec@1 87.000 (87.756) Prec@5 99.000 (99.024) +2022-11-14 16:34:31,977 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0778) Prec@1 85.000 (87.690) Prec@5 99.000 (99.024) +2022-11-14 16:34:31,989 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0771) Prec@1 92.000 (87.791) Prec@5 99.000 (99.023) +2022-11-14 16:34:32,007 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0768) Prec@1 91.000 (87.864) Prec@5 99.000 (99.023) +2022-11-14 16:34:32,026 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0766) Prec@1 89.000 (87.889) Prec@5 99.000 (99.022) +2022-11-14 16:34:32,043 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.0779) Prec@1 78.000 (87.674) Prec@5 99.000 (99.022) +2022-11-14 16:34:32,058 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0779) Prec@1 87.000 (87.660) Prec@5 100.000 (99.043) +2022-11-14 16:34:32,077 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1161 (0.0787) Prec@1 83.000 (87.562) Prec@5 98.000 (99.021) +2022-11-14 16:34:32,092 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0783) Prec@1 90.000 (87.612) Prec@5 100.000 (99.041) +2022-11-14 16:34:32,109 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0787) Prec@1 85.000 (87.560) Prec@5 100.000 (99.060) +2022-11-14 16:34:32,124 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0785) Prec@1 87.000 (87.549) Prec@5 100.000 (99.078) +2022-11-14 16:34:32,138 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0788) Prec@1 87.000 (87.538) Prec@5 98.000 (99.058) +2022-11-14 16:34:32,153 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0785) Prec@1 89.000 (87.566) Prec@5 100.000 (99.075) +2022-11-14 16:34:32,169 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0785) Prec@1 89.000 (87.593) Prec@5 99.000 (99.074) +2022-11-14 16:34:32,185 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0788) Prec@1 82.000 (87.491) Prec@5 100.000 (99.091) +2022-11-14 16:34:32,201 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0786) Prec@1 88.000 (87.500) Prec@5 99.000 (99.089) +2022-11-14 16:34:32,219 Test: [56/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0787) Prec@1 84.000 (87.439) Prec@5 100.000 (99.105) +2022-11-14 16:34:32,232 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0499 (0.0782) Prec@1 92.000 (87.517) Prec@5 100.000 (99.121) +2022-11-14 16:34:32,248 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0784) Prec@1 85.000 (87.475) Prec@5 100.000 (99.136) +2022-11-14 16:34:32,264 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0780) Prec@1 91.000 (87.533) Prec@5 100.000 (99.150) +2022-11-14 16:34:32,285 Test: [60/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0779) Prec@1 90.000 (87.574) Prec@5 100.000 (99.164) +2022-11-14 16:34:32,300 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0777) Prec@1 87.000 (87.565) Prec@5 100.000 (99.177) +2022-11-14 16:34:32,317 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0774) Prec@1 90.000 (87.603) Prec@5 100.000 (99.190) +2022-11-14 16:34:32,338 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0486 (0.0770) Prec@1 91.000 (87.656) Prec@5 100.000 (99.203) +2022-11-14 16:34:32,354 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1085 (0.0775) Prec@1 83.000 (87.585) Prec@5 99.000 (99.200) +2022-11-14 16:34:32,371 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0773) Prec@1 88.000 (87.591) Prec@5 99.000 (99.197) +2022-11-14 16:34:32,388 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0772) Prec@1 87.000 (87.582) Prec@5 99.000 (99.194) +2022-11-14 16:34:32,403 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0769) Prec@1 92.000 (87.647) Prec@5 99.000 (99.191) +2022-11-14 16:34:32,422 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0768) Prec@1 87.000 (87.638) Prec@5 99.000 (99.188) +2022-11-14 16:34:32,440 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0939 (0.0770) Prec@1 86.000 (87.614) Prec@5 100.000 (99.200) +2022-11-14 16:34:32,458 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0773) Prec@1 84.000 (87.563) Prec@5 98.000 (99.183) +2022-11-14 16:34:32,475 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0772) Prec@1 89.000 (87.583) Prec@5 99.000 (99.181) +2022-11-14 16:34:32,490 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0576 (0.0769) Prec@1 92.000 (87.644) Prec@5 100.000 (99.192) +2022-11-14 16:34:32,507 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0766) Prec@1 92.000 (87.703) Prec@5 100.000 (99.203) +2022-11-14 16:34:32,525 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0768) Prec@1 84.000 (87.653) Prec@5 100.000 (99.213) +2022-11-14 16:34:32,546 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0766) Prec@1 91.000 (87.697) Prec@5 99.000 (99.211) +2022-11-14 16:34:32,561 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0764) Prec@1 90.000 (87.727) Prec@5 100.000 (99.221) +2022-11-14 16:34:32,579 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0764) Prec@1 87.000 (87.718) Prec@5 97.000 (99.192) +2022-11-14 16:34:32,595 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0764) Prec@1 89.000 (87.734) Prec@5 100.000 (99.203) +2022-11-14 16:34:32,613 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0927 (0.0766) Prec@1 86.000 (87.713) Prec@5 100.000 (99.213) +2022-11-14 16:34:32,628 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0766) Prec@1 86.000 (87.691) Prec@5 99.000 (99.210) +2022-11-14 16:34:32,644 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0767) Prec@1 84.000 (87.646) Prec@5 99.000 (99.207) +2022-11-14 16:34:32,661 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0768) Prec@1 87.000 (87.639) Prec@5 100.000 (99.217) +2022-11-14 16:34:32,679 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0767) Prec@1 89.000 (87.655) Prec@5 99.000 (99.214) +2022-11-14 16:34:32,694 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0768) Prec@1 87.000 (87.647) Prec@5 99.000 (99.212) +2022-11-14 16:34:32,712 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1062 (0.0771) Prec@1 84.000 (87.605) Prec@5 99.000 (99.209) +2022-11-14 16:34:32,729 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0770) Prec@1 88.000 (87.609) Prec@5 100.000 (99.218) +2022-11-14 16:34:32,747 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0769) Prec@1 91.000 (87.648) Prec@5 98.000 (99.205) +2022-11-14 16:34:32,771 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0770) Prec@1 84.000 (87.607) Prec@5 100.000 (99.213) +2022-11-14 16:34:32,795 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0771) Prec@1 84.000 (87.567) Prec@5 100.000 (99.222) +2022-11-14 16:34:32,818 Test: [90/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0769) Prec@1 91.000 (87.604) Prec@5 100.000 (99.231) +2022-11-14 16:34:32,839 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0766) Prec@1 92.000 (87.652) Prec@5 100.000 (99.239) +2022-11-14 16:34:32,861 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0768) Prec@1 85.000 (87.624) Prec@5 99.000 (99.237) +2022-11-14 16:34:32,885 Test: [93/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0769) Prec@1 86.000 (87.606) Prec@5 100.000 (99.245) +2022-11-14 16:34:32,903 Test: [94/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0854 (0.0769) Prec@1 86.000 (87.589) Prec@5 99.000 (99.242) +2022-11-14 16:34:32,923 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0771) Prec@1 86.000 (87.573) Prec@5 100.000 (99.250) +2022-11-14 16:34:32,946 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0768) Prec@1 90.000 (87.598) Prec@5 99.000 (99.247) +2022-11-14 16:34:32,969 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0770) Prec@1 87.000 (87.592) Prec@5 96.000 (99.214) +2022-11-14 16:34:32,993 Test: [98/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0900 (0.0771) Prec@1 87.000 (87.586) Prec@5 99.000 (99.212) +2022-11-14 16:34:33,017 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0770) Prec@1 89.000 (87.600) Prec@5 100.000 (99.220) +2022-11-14 16:34:33,093 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:34:33,457 Epoch: [359][0/500] Time 0.024 (0.024) Data 0.269 (0.269) Loss 0.0317 (0.0317) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:34:33,902 Epoch: [359][10/500] Time 0.042 (0.038) Data 0.002 (0.026) Loss 0.0300 (0.0308) Prec@1 94.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:34:34,406 Epoch: [359][20/500] Time 0.046 (0.041) Data 0.002 (0.015) Loss 0.0254 (0.0290) Prec@1 97.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:34:34,902 Epoch: [359][30/500] Time 0.053 (0.042) Data 0.002 (0.011) Loss 0.0230 (0.0275) Prec@1 97.000 (95.750) Prec@5 99.000 (99.500) +2022-11-14 16:34:35,381 Epoch: [359][40/500] Time 0.047 (0.042) Data 0.002 (0.009) Loss 0.0257 (0.0272) Prec@1 96.000 (95.800) Prec@5 100.000 (99.600) +2022-11-14 16:34:35,876 Epoch: [359][50/500] Time 0.046 (0.043) Data 0.002 (0.007) Loss 0.0307 (0.0277) Prec@1 94.000 (95.500) Prec@5 100.000 (99.667) +2022-11-14 16:34:36,442 Epoch: [359][60/500] Time 0.063 (0.044) Data 0.002 (0.006) Loss 0.0404 (0.0296) Prec@1 94.000 (95.286) Prec@5 98.000 (99.429) +2022-11-14 16:34:36,911 Epoch: [359][70/500] Time 0.054 (0.044) Data 0.002 (0.006) Loss 0.0478 (0.0318) Prec@1 93.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:34:37,413 Epoch: [359][80/500] Time 0.056 (0.044) Data 0.002 (0.005) Loss 0.0143 (0.0299) Prec@1 98.000 (95.333) Prec@5 100.000 (99.556) +2022-11-14 16:34:37,912 Epoch: [359][90/500] Time 0.039 (0.044) Data 0.002 (0.005) Loss 0.0494 (0.0318) Prec@1 90.000 (94.800) Prec@5 100.000 (99.600) +2022-11-14 16:34:38,503 Epoch: [359][100/500] Time 0.060 (0.045) Data 0.002 (0.005) Loss 0.0471 (0.0332) Prec@1 93.000 (94.636) Prec@5 100.000 (99.636) +2022-11-14 16:34:39,051 Epoch: [359][110/500] Time 0.055 (0.045) Data 0.002 (0.005) Loss 0.0288 (0.0329) Prec@1 96.000 (94.750) Prec@5 100.000 (99.667) +2022-11-14 16:34:39,546 Epoch: [359][120/500] Time 0.045 (0.045) Data 0.002 (0.004) Loss 0.0084 (0.0310) Prec@1 99.000 (95.077) Prec@5 100.000 (99.692) +2022-11-14 16:34:40,147 Epoch: [359][130/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0342 (0.0312) Prec@1 95.000 (95.071) Prec@5 100.000 (99.714) +2022-11-14 16:34:40,658 Epoch: [359][140/500] Time 0.042 (0.046) Data 0.002 (0.004) Loss 0.0236 (0.0307) Prec@1 97.000 (95.200) Prec@5 100.000 (99.733) +2022-11-14 16:34:41,208 Epoch: [359][150/500] Time 0.066 (0.046) Data 0.002 (0.004) Loss 0.0417 (0.0314) Prec@1 95.000 (95.188) Prec@5 100.000 (99.750) +2022-11-14 16:34:42,224 Epoch: [359][160/500] Time 0.133 (0.049) Data 0.002 (0.004) Loss 0.0359 (0.0316) Prec@1 94.000 (95.118) Prec@5 100.000 (99.765) +2022-11-14 16:34:43,133 Epoch: [359][170/500] Time 0.084 (0.051) Data 0.002 (0.004) Loss 0.0217 (0.0311) Prec@1 97.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 16:34:43,993 Epoch: [359][180/500] Time 0.070 (0.052) Data 0.002 (0.004) Loss 0.0230 (0.0307) Prec@1 96.000 (95.263) Prec@5 100.000 (99.789) +2022-11-14 16:34:44,865 Epoch: [359][190/500] Time 0.088 (0.053) Data 0.002 (0.003) Loss 0.0117 (0.0297) Prec@1 99.000 (95.450) Prec@5 100.000 (99.800) +2022-11-14 16:34:45,660 Epoch: [359][200/500] Time 0.081 (0.054) Data 0.002 (0.003) Loss 0.0232 (0.0294) Prec@1 96.000 (95.476) Prec@5 100.000 (99.810) +2022-11-14 16:34:46,532 Epoch: [359][210/500] Time 0.080 (0.055) Data 0.002 (0.003) Loss 0.0297 (0.0294) Prec@1 95.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 16:34:47,301 Epoch: [359][220/500] Time 0.075 (0.056) Data 0.002 (0.003) Loss 0.0317 (0.0295) Prec@1 97.000 (95.522) Prec@5 99.000 (99.783) +2022-11-14 16:34:48,177 Epoch: [359][230/500] Time 0.116 (0.057) Data 0.002 (0.003) Loss 0.0214 (0.0292) Prec@1 95.000 (95.500) Prec@5 100.000 (99.792) +2022-11-14 16:34:48,940 Epoch: [359][240/500] Time 0.082 (0.057) Data 0.002 (0.003) Loss 0.0130 (0.0285) Prec@1 98.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:34:49,942 Epoch: [359][250/500] Time 0.077 (0.059) Data 0.002 (0.003) Loss 0.0343 (0.0288) Prec@1 94.000 (95.538) Prec@5 99.000 (99.769) +2022-11-14 16:34:50,728 Epoch: [359][260/500] Time 0.077 (0.059) Data 0.002 (0.003) Loss 0.0312 (0.0288) Prec@1 95.000 (95.519) Prec@5 100.000 (99.778) +2022-11-14 16:34:51,566 Epoch: [359][270/500] Time 0.072 (0.060) Data 0.003 (0.003) Loss 0.0265 (0.0288) Prec@1 97.000 (95.571) Prec@5 100.000 (99.786) +2022-11-14 16:34:52,490 Epoch: [359][280/500] Time 0.114 (0.061) Data 0.002 (0.003) Loss 0.0248 (0.0286) Prec@1 98.000 (95.655) Prec@5 100.000 (99.793) +2022-11-14 16:34:53,569 Epoch: [359][290/500] Time 0.073 (0.062) Data 0.002 (0.003) Loss 0.0446 (0.0292) Prec@1 93.000 (95.567) Prec@5 100.000 (99.800) +2022-11-14 16:34:54,406 Epoch: [359][300/500] Time 0.075 (0.062) Data 0.002 (0.003) Loss 0.0326 (0.0293) Prec@1 95.000 (95.548) Prec@5 100.000 (99.806) +2022-11-14 16:34:55,210 Epoch: [359][310/500] Time 0.081 (0.063) Data 0.002 (0.003) Loss 0.0328 (0.0294) Prec@1 95.000 (95.531) Prec@5 100.000 (99.812) +2022-11-14 16:34:56,135 Epoch: [359][320/500] Time 0.075 (0.063) Data 0.002 (0.003) Loss 0.0367 (0.0296) Prec@1 92.000 (95.424) Prec@5 100.000 (99.818) +2022-11-14 16:34:56,967 Epoch: [359][330/500] Time 0.069 (0.064) Data 0.002 (0.003) Loss 0.0220 (0.0294) Prec@1 96.000 (95.441) Prec@5 100.000 (99.824) +2022-11-14 16:34:57,810 Epoch: [359][340/500] Time 0.066 (0.064) Data 0.002 (0.003) Loss 0.0128 (0.0289) Prec@1 98.000 (95.514) Prec@5 100.000 (99.829) +2022-11-14 16:34:58,752 Epoch: [359][350/500] Time 0.062 (0.064) Data 0.002 (0.003) Loss 0.0093 (0.0284) Prec@1 99.000 (95.611) Prec@5 100.000 (99.833) +2022-11-14 16:34:59,564 Epoch: [359][360/500] Time 0.088 (0.065) Data 0.002 (0.003) Loss 0.0190 (0.0281) Prec@1 97.000 (95.649) Prec@5 100.000 (99.838) +2022-11-14 16:35:00,364 Epoch: [359][370/500] Time 0.060 (0.065) Data 0.002 (0.003) Loss 0.0334 (0.0282) Prec@1 97.000 (95.684) Prec@5 100.000 (99.842) +2022-11-14 16:35:01,154 Epoch: [359][380/500] Time 0.061 (0.065) Data 0.002 (0.003) Loss 0.0430 (0.0286) Prec@1 92.000 (95.590) Prec@5 100.000 (99.846) +2022-11-14 16:35:01,790 Epoch: [359][390/500] Time 0.065 (0.065) Data 0.002 (0.003) Loss 0.0120 (0.0282) Prec@1 98.000 (95.650) Prec@5 100.000 (99.850) +2022-11-14 16:35:02,516 Epoch: [359][400/500] Time 0.068 (0.065) Data 0.002 (0.003) Loss 0.0222 (0.0281) Prec@1 97.000 (95.683) Prec@5 100.000 (99.854) +2022-11-14 16:35:03,155 Epoch: [359][410/500] Time 0.066 (0.065) Data 0.002 (0.003) Loss 0.0479 (0.0285) Prec@1 92.000 (95.595) Prec@5 100.000 (99.857) +2022-11-14 16:35:03,798 Epoch: [359][420/500] Time 0.065 (0.065) Data 0.002 (0.003) Loss 0.0320 (0.0286) Prec@1 95.000 (95.581) Prec@5 99.000 (99.837) +2022-11-14 16:35:04,425 Epoch: [359][430/500] Time 0.062 (0.064) Data 0.002 (0.003) Loss 0.0443 (0.0290) Prec@1 93.000 (95.523) Prec@5 100.000 (99.841) +2022-11-14 16:35:05,077 Epoch: [359][440/500] Time 0.064 (0.064) Data 0.002 (0.003) Loss 0.0238 (0.0289) Prec@1 98.000 (95.578) Prec@5 100.000 (99.844) +2022-11-14 16:35:05,811 Epoch: [359][450/500] Time 0.080 (0.064) Data 0.002 (0.003) Loss 0.0291 (0.0289) Prec@1 93.000 (95.522) Prec@5 100.000 (99.848) +2022-11-14 16:35:06,516 Epoch: [359][460/500] Time 0.089 (0.064) Data 0.002 (0.003) Loss 0.0302 (0.0289) Prec@1 94.000 (95.489) Prec@5 100.000 (99.851) +2022-11-14 16:35:07,172 Epoch: [359][470/500] Time 0.055 (0.064) Data 0.002 (0.003) Loss 0.0518 (0.0294) Prec@1 92.000 (95.417) Prec@5 100.000 (99.854) +2022-11-14 16:35:07,845 Epoch: [359][480/500] Time 0.060 (0.064) Data 0.002 (0.003) Loss 0.0286 (0.0294) Prec@1 95.000 (95.408) Prec@5 100.000 (99.857) +2022-11-14 16:35:08,546 Epoch: [359][490/500] Time 0.061 (0.064) Data 0.002 (0.003) Loss 0.0152 (0.0291) Prec@1 98.000 (95.460) Prec@5 100.000 (99.860) +2022-11-14 16:35:09,160 Epoch: [359][499/500] Time 0.055 (0.064) Data 0.002 (0.003) Loss 0.0430 (0.0293) Prec@1 94.000 (95.431) Prec@5 100.000 (99.863) +2022-11-14 16:35:09,493 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0500 (0.0500) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:35:09,504 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0658 (0.0579) Prec@1 89.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:35:09,514 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0782 (0.0647) Prec@1 86.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:35:09,527 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0655) Prec@1 88.000 (88.750) Prec@5 100.000 (100.000) +2022-11-14 16:35:09,536 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0723 (0.0669) Prec@1 90.000 (89.000) Prec@5 99.000 (99.800) +2022-11-14 16:35:09,544 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0441 (0.0631) Prec@1 92.000 (89.500) Prec@5 100.000 (99.833) +2022-11-14 16:35:09,555 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0634) Prec@1 90.000 (89.571) Prec@5 100.000 (99.857) +2022-11-14 16:35:09,567 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0673) Prec@1 82.000 (88.625) Prec@5 100.000 (99.875) +2022-11-14 16:35:09,575 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0698) Prec@1 88.000 (88.556) Prec@5 98.000 (99.667) +2022-11-14 16:35:09,586 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0705) Prec@1 89.000 (88.600) Prec@5 99.000 (99.600) +2022-11-14 16:35:09,596 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0681) Prec@1 91.000 (88.818) Prec@5 100.000 (99.636) +2022-11-14 16:35:09,608 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0671) Prec@1 93.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:35:09,619 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0455 (0.0654) Prec@1 94.000 (89.538) Prec@5 100.000 (99.692) +2022-11-14 16:35:09,629 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0659) Prec@1 91.000 (89.643) Prec@5 99.000 (99.643) +2022-11-14 16:35:09,640 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0669) Prec@1 87.000 (89.467) Prec@5 100.000 (99.667) +2022-11-14 16:35:09,652 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0671) Prec@1 87.000 (89.312) Prec@5 99.000 (99.625) +2022-11-14 16:35:09,662 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0414 (0.0656) Prec@1 94.000 (89.588) Prec@5 99.000 (99.588) +2022-11-14 16:35:09,674 Test: [17/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.0680) Prec@1 83.000 (89.222) Prec@5 98.000 (99.500) +2022-11-14 16:35:09,685 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0690) Prec@1 86.000 (89.053) Prec@5 98.000 (99.421) +2022-11-14 16:35:09,695 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0705) Prec@1 84.000 (88.800) Prec@5 98.000 (99.350) +2022-11-14 16:35:09,707 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0778 (0.0709) Prec@1 86.000 (88.667) Prec@5 100.000 (99.381) +2022-11-14 16:35:09,718 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0713) Prec@1 85.000 (88.500) Prec@5 98.000 (99.318) +2022-11-14 16:35:09,730 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0723) Prec@1 85.000 (88.348) Prec@5 98.000 (99.261) +2022-11-14 16:35:09,742 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0715) Prec@1 94.000 (88.583) Prec@5 100.000 (99.292) +2022-11-14 16:35:09,754 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1132 (0.0732) Prec@1 82.000 (88.320) Prec@5 100.000 (99.320) +2022-11-14 16:35:09,766 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0731) Prec@1 90.000 (88.385) Prec@5 100.000 (99.346) +2022-11-14 16:35:09,778 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0724) Prec@1 91.000 (88.481) Prec@5 100.000 (99.370) +2022-11-14 16:35:09,789 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0720) Prec@1 91.000 (88.571) Prec@5 100.000 (99.393) +2022-11-14 16:35:09,800 Test: [28/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0719) Prec@1 88.000 (88.552) Prec@5 99.000 (99.379) +2022-11-14 16:35:09,813 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0722) Prec@1 86.000 (88.467) Prec@5 100.000 (99.400) +2022-11-14 16:35:09,825 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0720) Prec@1 89.000 (88.484) Prec@5 100.000 (99.419) +2022-11-14 16:35:09,837 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0722) Prec@1 89.000 (88.500) Prec@5 99.000 (99.406) +2022-11-14 16:35:09,847 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0721) Prec@1 88.000 (88.485) Prec@5 100.000 (99.424) +2022-11-14 16:35:09,859 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0730) Prec@1 85.000 (88.382) Prec@5 100.000 (99.441) +2022-11-14 16:35:09,870 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0736) Prec@1 84.000 (88.257) Prec@5 98.000 (99.400) +2022-11-14 16:35:09,884 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0731) Prec@1 92.000 (88.361) Prec@5 99.000 (99.389) +2022-11-14 16:35:09,898 Test: [36/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0730) Prec@1 90.000 (88.405) Prec@5 100.000 (99.405) +2022-11-14 16:35:09,912 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0737) Prec@1 83.000 (88.263) Prec@5 100.000 (99.421) +2022-11-14 16:35:09,926 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0733) Prec@1 90.000 (88.308) Prec@5 99.000 (99.410) +2022-11-14 16:35:09,936 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0731) Prec@1 89.000 (88.325) Prec@5 100.000 (99.425) +2022-11-14 16:35:09,946 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0734) Prec@1 84.000 (88.220) Prec@5 96.000 (99.341) +2022-11-14 16:35:09,961 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0736) Prec@1 86.000 (88.167) Prec@5 100.000 (99.357) +2022-11-14 16:35:09,975 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0731) Prec@1 92.000 (88.256) Prec@5 100.000 (99.372) +2022-11-14 16:35:09,988 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0731) Prec@1 88.000 (88.250) Prec@5 98.000 (99.341) +2022-11-14 16:35:10,000 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0728) Prec@1 92.000 (88.333) Prec@5 98.000 (99.311) +2022-11-14 16:35:10,014 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0735) Prec@1 82.000 (88.196) Prec@5 99.000 (99.304) +2022-11-14 16:35:10,026 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0735) Prec@1 87.000 (88.170) Prec@5 100.000 (99.319) +2022-11-14 16:35:10,037 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1122 (0.0743) Prec@1 81.000 (88.021) Prec@5 99.000 (99.312) +2022-11-14 16:35:10,051 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0740) Prec@1 90.000 (88.061) Prec@5 100.000 (99.327) +2022-11-14 16:35:10,064 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0745) Prec@1 85.000 (88.000) Prec@5 100.000 (99.340) +2022-11-14 16:35:10,074 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0543 (0.0741) Prec@1 90.000 (88.039) Prec@5 100.000 (99.353) +2022-11-14 16:35:10,086 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0742) Prec@1 86.000 (88.000) Prec@5 100.000 (99.365) +2022-11-14 16:35:10,101 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0741) Prec@1 88.000 (88.000) Prec@5 99.000 (99.358) +2022-11-14 16:35:10,113 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0743) Prec@1 88.000 (88.000) Prec@5 99.000 (99.352) +2022-11-14 16:35:10,127 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0745) Prec@1 87.000 (87.982) Prec@5 100.000 (99.364) +2022-11-14 16:35:10,138 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0745) Prec@1 88.000 (87.982) Prec@5 99.000 (99.357) +2022-11-14 16:35:10,149 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0748) Prec@1 85.000 (87.930) Prec@5 100.000 (99.368) +2022-11-14 16:35:10,161 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0746) Prec@1 91.000 (87.983) Prec@5 100.000 (99.379) +2022-11-14 16:35:10,174 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0752) Prec@1 81.000 (87.864) Prec@5 100.000 (99.390) +2022-11-14 16:35:10,186 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0750) Prec@1 90.000 (87.900) Prec@5 100.000 (99.400) +2022-11-14 16:35:10,196 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0749) Prec@1 88.000 (87.902) Prec@5 100.000 (99.410) +2022-11-14 16:35:10,207 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0747) Prec@1 90.000 (87.935) Prec@5 99.000 (99.403) +2022-11-14 16:35:10,218 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0746) Prec@1 89.000 (87.952) Prec@5 100.000 (99.413) +2022-11-14 16:35:10,232 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0741) Prec@1 92.000 (88.016) Prec@5 100.000 (99.422) +2022-11-14 16:35:10,245 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0904 (0.0744) Prec@1 85.000 (87.969) Prec@5 99.000 (99.415) +2022-11-14 16:35:10,258 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0840 (0.0745) Prec@1 86.000 (87.939) Prec@5 99.000 (99.409) +2022-11-14 16:35:10,269 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0379 (0.0740) Prec@1 95.000 (88.045) Prec@5 100.000 (99.418) +2022-11-14 16:35:10,280 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0741) Prec@1 87.000 (88.029) Prec@5 100.000 (99.426) +2022-11-14 16:35:10,291 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0741) Prec@1 90.000 (88.058) Prec@5 99.000 (99.420) +2022-11-14 16:35:10,301 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0743) Prec@1 86.000 (88.029) Prec@5 99.000 (99.414) +2022-11-14 16:35:10,314 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1046 (0.0747) Prec@1 85.000 (87.986) Prec@5 100.000 (99.423) +2022-11-14 16:35:10,327 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0744) Prec@1 90.000 (88.014) Prec@5 99.000 (99.417) +2022-11-14 16:35:10,339 Test: [72/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0742) Prec@1 91.000 (88.055) Prec@5 100.000 (99.425) +2022-11-14 16:35:10,351 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0738) Prec@1 94.000 (88.135) Prec@5 100.000 (99.432) +2022-11-14 16:35:10,362 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0742) Prec@1 83.000 (88.067) Prec@5 99.000 (99.427) +2022-11-14 16:35:10,375 Test: [75/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0741) Prec@1 90.000 (88.092) Prec@5 100.000 (99.434) +2022-11-14 16:35:10,387 Test: [76/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0803 (0.0741) Prec@1 87.000 (88.078) Prec@5 98.000 (99.416) +2022-11-14 16:35:10,400 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0901 (0.0743) Prec@1 86.000 (88.051) Prec@5 98.000 (99.397) +2022-11-14 16:35:10,414 Test: [78/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0744) Prec@1 89.000 (88.063) Prec@5 100.000 (99.405) +2022-11-14 16:35:10,428 Test: [79/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 88.000 (88.062) Prec@5 99.000 (99.400) +2022-11-14 16:35:10,444 Test: [80/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0744) Prec@1 87.000 (88.049) Prec@5 99.000 (99.395) +2022-11-14 16:35:10,461 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0747) Prec@1 81.000 (87.963) Prec@5 98.000 (99.378) +2022-11-14 16:35:10,474 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0748) Prec@1 85.000 (87.928) Prec@5 100.000 (99.386) +2022-11-14 16:35:10,490 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0750) Prec@1 85.000 (87.893) Prec@5 99.000 (99.381) +2022-11-14 16:35:10,505 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1021 (0.0753) Prec@1 83.000 (87.835) Prec@5 100.000 (99.388) +2022-11-14 16:35:10,520 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0756) Prec@1 81.000 (87.756) Prec@5 100.000 (99.395) +2022-11-14 16:35:10,534 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0756) Prec@1 90.000 (87.782) Prec@5 99.000 (99.391) +2022-11-14 16:35:10,550 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0755) Prec@1 90.000 (87.807) Prec@5 99.000 (99.386) +2022-11-14 16:35:10,566 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0755) Prec@1 87.000 (87.798) Prec@5 99.000 (99.382) +2022-11-14 16:35:10,583 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0754) Prec@1 91.000 (87.833) Prec@5 99.000 (99.378) +2022-11-14 16:35:10,600 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0752) Prec@1 88.000 (87.835) Prec@5 100.000 (99.385) +2022-11-14 16:35:10,614 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0749) Prec@1 91.000 (87.870) Prec@5 100.000 (99.391) +2022-11-14 16:35:10,630 Test: [92/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0747) Prec@1 89.000 (87.882) Prec@5 99.000 (99.387) +2022-11-14 16:35:10,644 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0747) Prec@1 89.000 (87.894) Prec@5 99.000 (99.383) +2022-11-14 16:35:10,658 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0748) Prec@1 87.000 (87.884) Prec@5 99.000 (99.379) +2022-11-14 16:35:10,673 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0747) Prec@1 89.000 (87.896) Prec@5 100.000 (99.385) +2022-11-14 16:35:10,686 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0745) Prec@1 90.000 (87.918) Prec@5 99.000 (99.381) +2022-11-14 16:35:10,701 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0744) Prec@1 89.000 (87.929) Prec@5 99.000 (99.378) +2022-11-14 16:35:10,716 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0744) Prec@1 89.000 (87.939) Prec@5 98.000 (99.364) +2022-11-14 16:35:10,731 Test: [99/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0744) Prec@1 88.000 (87.940) Prec@5 99.000 (99.360) +2022-11-14 16:35:10,798 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:35:11,204 Epoch: [360][0/500] Time 0.027 (0.027) Data 0.299 (0.299) Loss 0.0248 (0.0248) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:35:11,526 Epoch: [360][10/500] Time 0.032 (0.029) Data 0.002 (0.029) Loss 0.0249 (0.0248) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:35:11,873 Epoch: [360][20/500] Time 0.029 (0.030) Data 0.002 (0.016) Loss 0.0148 (0.0215) Prec@1 98.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:35:12,220 Epoch: [360][30/500] Time 0.029 (0.030) Data 0.002 (0.012) Loss 0.0376 (0.0255) Prec@1 93.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:35:12,576 Epoch: [360][40/500] Time 0.033 (0.031) Data 0.002 (0.009) Loss 0.0337 (0.0272) Prec@1 95.000 (95.400) Prec@5 99.000 (99.800) +2022-11-14 16:35:12,920 Epoch: [360][50/500] Time 0.037 (0.031) Data 0.002 (0.008) Loss 0.0258 (0.0269) Prec@1 97.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:35:13,274 Epoch: [360][60/500] Time 0.032 (0.031) Data 0.002 (0.007) Loss 0.0470 (0.0298) Prec@1 92.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:35:13,672 Epoch: [360][70/500] Time 0.029 (0.031) Data 0.002 (0.006) Loss 0.0197 (0.0285) Prec@1 97.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:35:14,131 Epoch: [360][80/500] Time 0.039 (0.033) Data 0.002 (0.006) Loss 0.0172 (0.0273) Prec@1 99.000 (95.778) Prec@5 100.000 (99.889) +2022-11-14 16:35:14,699 Epoch: [360][90/500] Time 0.042 (0.035) Data 0.002 (0.005) Loss 0.0467 (0.0292) Prec@1 91.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 16:35:15,193 Epoch: [360][100/500] Time 0.047 (0.036) Data 0.002 (0.005) Loss 0.0231 (0.0287) Prec@1 97.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 16:35:15,729 Epoch: [360][110/500] Time 0.069 (0.037) Data 0.002 (0.005) Loss 0.0144 (0.0275) Prec@1 99.000 (95.750) Prec@5 100.000 (99.917) +2022-11-14 16:35:16,262 Epoch: [360][120/500] Time 0.047 (0.038) Data 0.002 (0.004) Loss 0.0178 (0.0267) Prec@1 98.000 (95.923) Prec@5 99.000 (99.846) +2022-11-14 16:35:16,781 Epoch: [360][130/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0452 (0.0280) Prec@1 91.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 16:35:17,276 Epoch: [360][140/500] Time 0.043 (0.039) Data 0.002 (0.004) Loss 0.0320 (0.0283) Prec@1 94.000 (95.467) Prec@5 100.000 (99.867) +2022-11-14 16:35:17,849 Epoch: [360][150/500] Time 0.062 (0.040) Data 0.002 (0.004) Loss 0.0277 (0.0283) Prec@1 94.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:35:18,344 Epoch: [360][160/500] Time 0.052 (0.040) Data 0.002 (0.004) Loss 0.0267 (0.0282) Prec@1 95.000 (95.353) Prec@5 100.000 (99.882) +2022-11-14 16:35:18,851 Epoch: [360][170/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0347 (0.0285) Prec@1 94.000 (95.278) Prec@5 99.000 (99.833) +2022-11-14 16:35:19,355 Epoch: [360][180/500] Time 0.049 (0.040) Data 0.002 (0.004) Loss 0.0239 (0.0283) Prec@1 97.000 (95.368) Prec@5 100.000 (99.842) +2022-11-14 16:35:19,852 Epoch: [360][190/500] Time 0.047 (0.041) Data 0.002 (0.004) Loss 0.0234 (0.0281) Prec@1 97.000 (95.450) Prec@5 100.000 (99.850) +2022-11-14 16:35:20,343 Epoch: [360][200/500] Time 0.045 (0.041) Data 0.002 (0.004) Loss 0.0327 (0.0283) Prec@1 94.000 (95.381) Prec@5 99.000 (99.810) +2022-11-14 16:35:20,835 Epoch: [360][210/500] Time 0.046 (0.041) Data 0.002 (0.003) Loss 0.0445 (0.0290) Prec@1 95.000 (95.364) Prec@5 99.000 (99.773) +2022-11-14 16:35:21,328 Epoch: [360][220/500] Time 0.055 (0.041) Data 0.003 (0.003) Loss 0.0320 (0.0291) Prec@1 93.000 (95.261) Prec@5 100.000 (99.783) +2022-11-14 16:35:21,825 Epoch: [360][230/500] Time 0.050 (0.041) Data 0.002 (0.003) Loss 0.0413 (0.0296) Prec@1 94.000 (95.208) Prec@5 100.000 (99.792) +2022-11-14 16:35:22,348 Epoch: [360][240/500] Time 0.049 (0.041) Data 0.002 (0.003) Loss 0.0498 (0.0305) Prec@1 93.000 (95.120) Prec@5 99.000 (99.760) +2022-11-14 16:35:22,845 Epoch: [360][250/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0292 (0.0304) Prec@1 95.000 (95.115) Prec@5 100.000 (99.769) +2022-11-14 16:35:23,363 Epoch: [360][260/500] Time 0.049 (0.042) Data 0.002 (0.003) Loss 0.0580 (0.0314) Prec@1 89.000 (94.889) Prec@5 98.000 (99.704) +2022-11-14 16:35:23,956 Epoch: [360][270/500] Time 0.042 (0.042) Data 0.002 (0.003) Loss 0.0156 (0.0309) Prec@1 97.000 (94.964) Prec@5 100.000 (99.714) +2022-11-14 16:35:24,480 Epoch: [360][280/500] Time 0.051 (0.042) Data 0.002 (0.003) Loss 0.0364 (0.0311) Prec@1 95.000 (94.966) Prec@5 100.000 (99.724) +2022-11-14 16:35:24,984 Epoch: [360][290/500] Time 0.050 (0.042) Data 0.002 (0.003) Loss 0.0362 (0.0312) Prec@1 95.000 (94.967) Prec@5 100.000 (99.733) +2022-11-14 16:35:25,532 Epoch: [360][300/500] Time 0.044 (0.043) Data 0.002 (0.003) Loss 0.0392 (0.0315) Prec@1 94.000 (94.935) Prec@5 100.000 (99.742) +2022-11-14 16:35:26,022 Epoch: [360][310/500] Time 0.043 (0.043) Data 0.002 (0.003) Loss 0.0239 (0.0312) Prec@1 96.000 (94.969) Prec@5 100.000 (99.750) +2022-11-14 16:35:26,901 Epoch: [360][320/500] Time 0.134 (0.044) Data 0.002 (0.003) Loss 0.0212 (0.0309) Prec@1 96.000 (95.000) Prec@5 100.000 (99.758) +2022-11-14 16:35:27,808 Epoch: [360][330/500] Time 0.089 (0.045) Data 0.002 (0.003) Loss 0.0361 (0.0311) Prec@1 96.000 (95.029) Prec@5 100.000 (99.765) +2022-11-14 16:35:28,588 Epoch: [360][340/500] Time 0.071 (0.045) Data 0.003 (0.003) Loss 0.0424 (0.0314) Prec@1 95.000 (95.029) Prec@5 100.000 (99.771) +2022-11-14 16:35:29,553 Epoch: [360][350/500] Time 0.072 (0.047) Data 0.002 (0.003) Loss 0.0309 (0.0314) Prec@1 96.000 (95.056) Prec@5 100.000 (99.778) +2022-11-14 16:35:30,397 Epoch: [360][360/500] Time 0.080 (0.047) Data 0.002 (0.003) Loss 0.0295 (0.0313) Prec@1 94.000 (95.027) Prec@5 100.000 (99.784) +2022-11-14 16:35:31,346 Epoch: [360][370/500] Time 0.113 (0.048) Data 0.002 (0.003) Loss 0.0376 (0.0315) Prec@1 94.000 (95.000) Prec@5 99.000 (99.763) +2022-11-14 16:35:32,182 Epoch: [360][380/500] Time 0.087 (0.049) Data 0.002 (0.003) Loss 0.0415 (0.0318) Prec@1 93.000 (94.949) Prec@5 100.000 (99.769) +2022-11-14 16:35:33,137 Epoch: [360][390/500] Time 0.143 (0.050) Data 0.002 (0.003) Loss 0.0316 (0.0318) Prec@1 93.000 (94.900) Prec@5 100.000 (99.775) +2022-11-14 16:35:34,121 Epoch: [360][400/500] Time 0.087 (0.051) Data 0.003 (0.003) Loss 0.0464 (0.0321) Prec@1 94.000 (94.878) Prec@5 99.000 (99.756) +2022-11-14 16:35:35,079 Epoch: [360][410/500] Time 0.088 (0.052) Data 0.002 (0.003) Loss 0.0233 (0.0319) Prec@1 97.000 (94.929) Prec@5 99.000 (99.738) +2022-11-14 16:35:35,903 Epoch: [360][420/500] Time 0.088 (0.052) Data 0.002 (0.003) Loss 0.0190 (0.0316) Prec@1 97.000 (94.977) Prec@5 100.000 (99.744) +2022-11-14 16:35:36,822 Epoch: [360][430/500] Time 0.103 (0.053) Data 0.002 (0.003) Loss 0.0461 (0.0319) Prec@1 93.000 (94.932) Prec@5 99.000 (99.727) +2022-11-14 16:35:37,623 Epoch: [360][440/500] Time 0.066 (0.054) Data 0.002 (0.003) Loss 0.0250 (0.0318) Prec@1 96.000 (94.956) Prec@5 100.000 (99.733) +2022-11-14 16:35:38,423 Epoch: [360][450/500] Time 0.077 (0.054) Data 0.002 (0.003) Loss 0.0475 (0.0321) Prec@1 92.000 (94.891) Prec@5 100.000 (99.739) +2022-11-14 16:35:39,349 Epoch: [360][460/500] Time 0.110 (0.055) Data 0.002 (0.003) Loss 0.0321 (0.0321) Prec@1 96.000 (94.915) Prec@5 99.000 (99.723) +2022-11-14 16:35:40,198 Epoch: [360][470/500] Time 0.083 (0.055) Data 0.002 (0.003) Loss 0.0246 (0.0320) Prec@1 96.000 (94.938) Prec@5 100.000 (99.729) +2022-11-14 16:35:41,016 Epoch: [360][480/500] Time 0.075 (0.055) Data 0.002 (0.003) Loss 0.0235 (0.0318) Prec@1 96.000 (94.959) Prec@5 100.000 (99.735) +2022-11-14 16:35:41,828 Epoch: [360][490/500] Time 0.067 (0.056) Data 0.002 (0.003) Loss 0.0235 (0.0316) Prec@1 95.000 (94.960) Prec@5 100.000 (99.740) +2022-11-14 16:35:42,579 Epoch: [360][499/500] Time 0.073 (0.056) Data 0.002 (0.003) Loss 0.0361 (0.0317) Prec@1 94.000 (94.941) Prec@5 100.000 (99.745) +2022-11-14 16:35:42,905 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0567 (0.0567) Prec@1 91.000 (91.000) Prec@5 99.000 (99.000) +2022-11-14 16:35:42,914 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0600 (0.0584) Prec@1 88.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 16:35:42,925 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0617) Prec@1 90.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:35:42,937 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0740 (0.0648) Prec@1 88.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 16:35:42,950 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0665) Prec@1 89.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 16:35:42,961 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0659) Prec@1 87.000 (88.833) Prec@5 99.000 (99.500) +2022-11-14 16:35:42,974 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0668) Prec@1 90.000 (89.000) Prec@5 99.000 (99.429) +2022-11-14 16:35:42,990 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0691) Prec@1 87.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 16:35:43,002 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0686 (0.0690) Prec@1 90.000 (88.889) Prec@5 99.000 (99.444) +2022-11-14 16:35:43,012 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0719) Prec@1 83.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 16:35:43,022 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0714) Prec@1 91.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 16:35:43,034 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0722) Prec@1 87.000 (88.417) Prec@5 100.000 (99.500) +2022-11-14 16:35:43,046 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0432 (0.0700) Prec@1 92.000 (88.692) Prec@5 100.000 (99.538) +2022-11-14 16:35:43,057 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0708) Prec@1 87.000 (88.571) Prec@5 98.000 (99.429) +2022-11-14 16:35:43,071 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0711) Prec@1 85.000 (88.333) Prec@5 100.000 (99.467) +2022-11-14 16:35:43,083 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0497 (0.0697) Prec@1 91.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:35:43,093 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0401 (0.0680) Prec@1 94.000 (88.824) Prec@5 98.000 (99.412) +2022-11-14 16:35:43,103 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0703) Prec@1 84.000 (88.556) Prec@5 100.000 (99.444) +2022-11-14 16:35:43,113 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0703) Prec@1 86.000 (88.421) Prec@5 97.000 (99.316) +2022-11-14 16:35:43,126 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1092 (0.0723) Prec@1 83.000 (88.150) Prec@5 96.000 (99.150) +2022-11-14 16:35:43,140 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0711) Prec@1 92.000 (88.333) Prec@5 100.000 (99.190) +2022-11-14 16:35:43,154 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0718) Prec@1 85.000 (88.182) Prec@5 99.000 (99.182) +2022-11-14 16:35:43,166 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.0731) Prec@1 84.000 (88.000) Prec@5 97.000 (99.087) +2022-11-14 16:35:43,177 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0731) Prec@1 88.000 (88.000) Prec@5 100.000 (99.125) +2022-11-14 16:35:43,188 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0869 (0.0737) Prec@1 87.000 (87.960) Prec@5 99.000 (99.120) +2022-11-14 16:35:43,201 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0747) Prec@1 85.000 (87.846) Prec@5 99.000 (99.115) +2022-11-14 16:35:43,213 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0739) Prec@1 91.000 (87.963) Prec@5 100.000 (99.148) +2022-11-14 16:35:43,224 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0736) Prec@1 90.000 (88.036) Prec@5 100.000 (99.179) +2022-11-14 16:35:43,236 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0734) Prec@1 89.000 (88.069) Prec@5 99.000 (99.172) +2022-11-14 16:35:43,251 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0733) Prec@1 88.000 (88.067) Prec@5 99.000 (99.167) +2022-11-14 16:35:43,263 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0730) Prec@1 90.000 (88.129) Prec@5 100.000 (99.194) +2022-11-14 16:35:43,274 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0730) Prec@1 90.000 (88.188) Prec@5 99.000 (99.188) +2022-11-14 16:35:43,284 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0735) Prec@1 85.000 (88.091) Prec@5 98.000 (99.152) +2022-11-14 16:35:43,298 Test: [33/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0740) Prec@1 85.000 (88.000) Prec@5 99.000 (99.147) +2022-11-14 16:35:43,311 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0743) Prec@1 89.000 (88.029) Prec@5 98.000 (99.114) +2022-11-14 16:35:43,323 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0742) Prec@1 90.000 (88.083) Prec@5 98.000 (99.083) +2022-11-14 16:35:43,333 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0742) Prec@1 90.000 (88.135) Prec@5 99.000 (99.081) +2022-11-14 16:35:43,346 Test: [37/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.1139 (0.0752) Prec@1 82.000 (87.974) Prec@5 99.000 (99.079) +2022-11-14 16:35:43,359 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0749) Prec@1 90.000 (88.026) Prec@5 99.000 (99.077) +2022-11-14 16:35:43,370 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0750) Prec@1 88.000 (88.025) Prec@5 99.000 (99.075) +2022-11-14 16:35:43,380 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1061 (0.0758) Prec@1 85.000 (87.951) Prec@5 96.000 (99.000) +2022-11-14 16:35:43,394 Test: [41/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0759) Prec@1 87.000 (87.929) Prec@5 99.000 (99.000) +2022-11-14 16:35:43,408 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0528 (0.0753) Prec@1 91.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:35:43,418 Test: [43/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0753) Prec@1 88.000 (88.000) Prec@5 97.000 (98.955) +2022-11-14 16:35:43,429 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0555 (0.0749) Prec@1 88.000 (88.000) Prec@5 99.000 (98.956) +2022-11-14 16:35:43,439 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0752) Prec@1 82.000 (87.870) Prec@5 99.000 (98.957) +2022-11-14 16:35:43,451 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0749) Prec@1 88.000 (87.872) Prec@5 99.000 (98.957) +2022-11-14 16:35:43,463 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0753) Prec@1 85.000 (87.812) Prec@5 99.000 (98.958) +2022-11-14 16:35:43,474 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0750) Prec@1 91.000 (87.878) Prec@5 100.000 (98.980) +2022-11-14 16:35:43,485 Test: [49/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1073 (0.0757) Prec@1 81.000 (87.740) Prec@5 100.000 (99.000) +2022-11-14 16:35:43,496 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0756) Prec@1 87.000 (87.725) Prec@5 100.000 (99.020) +2022-11-14 16:35:43,506 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0760) Prec@1 84.000 (87.654) Prec@5 97.000 (98.981) +2022-11-14 16:35:43,517 Test: [52/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0758) Prec@1 88.000 (87.660) Prec@5 100.000 (99.000) +2022-11-14 16:35:43,529 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0757) Prec@1 90.000 (87.704) Prec@5 100.000 (99.019) +2022-11-14 16:35:43,542 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0758) Prec@1 85.000 (87.655) Prec@5 100.000 (99.036) +2022-11-14 16:35:43,554 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0759) Prec@1 86.000 (87.625) Prec@5 99.000 (99.036) +2022-11-14 16:35:43,567 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0761) Prec@1 88.000 (87.632) Prec@5 100.000 (99.053) +2022-11-14 16:35:43,578 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0758) Prec@1 91.000 (87.690) Prec@5 100.000 (99.069) +2022-11-14 16:35:43,590 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0763) Prec@1 83.000 (87.610) Prec@5 100.000 (99.085) +2022-11-14 16:35:43,603 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0763) Prec@1 87.000 (87.600) Prec@5 100.000 (99.100) +2022-11-14 16:35:43,615 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1068 (0.0768) Prec@1 81.000 (87.492) Prec@5 100.000 (99.115) +2022-11-14 16:35:43,626 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0767) Prec@1 89.000 (87.516) Prec@5 99.000 (99.113) +2022-11-14 16:35:43,639 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0764) Prec@1 90.000 (87.556) Prec@5 98.000 (99.095) +2022-11-14 16:35:43,652 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0759) Prec@1 92.000 (87.625) Prec@5 100.000 (99.109) +2022-11-14 16:35:43,664 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0762) Prec@1 86.000 (87.600) Prec@5 100.000 (99.123) +2022-11-14 16:35:43,675 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0759) Prec@1 89.000 (87.621) Prec@5 99.000 (99.121) +2022-11-14 16:35:43,687 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0414 (0.0754) Prec@1 93.000 (87.701) Prec@5 100.000 (99.134) +2022-11-14 16:35:43,699 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0754) Prec@1 88.000 (87.706) Prec@5 100.000 (99.147) +2022-11-14 16:35:43,711 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0954 (0.0757) Prec@1 87.000 (87.696) Prec@5 100.000 (99.159) +2022-11-14 16:35:43,724 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0988 (0.0760) Prec@1 86.000 (87.671) Prec@5 99.000 (99.157) +2022-11-14 16:35:43,734 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0762) Prec@1 85.000 (87.634) Prec@5 100.000 (99.169) +2022-11-14 16:35:43,746 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0475 (0.0758) Prec@1 91.000 (87.681) Prec@5 99.000 (99.167) +2022-11-14 16:35:43,757 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0755) Prec@1 92.000 (87.740) Prec@5 99.000 (99.164) +2022-11-14 16:35:43,771 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0751) Prec@1 92.000 (87.797) Prec@5 100.000 (99.176) +2022-11-14 16:35:43,785 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0755) Prec@1 83.000 (87.733) Prec@5 99.000 (99.173) +2022-11-14 16:35:43,797 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0752) Prec@1 93.000 (87.803) Prec@5 100.000 (99.184) +2022-11-14 16:35:43,809 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0754) Prec@1 84.000 (87.753) Prec@5 100.000 (99.195) +2022-11-14 16:35:43,820 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0755) Prec@1 87.000 (87.744) Prec@5 100.000 (99.205) +2022-11-14 16:35:43,833 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0912 (0.0757) Prec@1 85.000 (87.709) Prec@5 100.000 (99.215) +2022-11-14 16:35:43,845 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0755) Prec@1 90.000 (87.737) Prec@5 100.000 (99.225) +2022-11-14 16:35:43,858 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0757) Prec@1 83.000 (87.679) Prec@5 99.000 (99.222) +2022-11-14 16:35:43,870 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0759) Prec@1 86.000 (87.659) Prec@5 98.000 (99.207) +2022-11-14 16:35:43,882 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0760) Prec@1 87.000 (87.651) Prec@5 100.000 (99.217) +2022-11-14 16:35:43,893 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0759) Prec@1 91.000 (87.690) Prec@5 99.000 (99.214) +2022-11-14 16:35:43,908 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0762) Prec@1 80.000 (87.600) Prec@5 98.000 (99.200) +2022-11-14 16:35:43,921 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1112 (0.0767) Prec@1 84.000 (87.558) Prec@5 99.000 (99.198) +2022-11-14 16:35:43,934 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0765) Prec@1 87.000 (87.552) Prec@5 100.000 (99.207) +2022-11-14 16:35:43,945 Test: [87/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0765) Prec@1 88.000 (87.557) Prec@5 98.000 (99.193) +2022-11-14 16:35:43,958 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0765) Prec@1 87.000 (87.551) Prec@5 100.000 (99.202) +2022-11-14 16:35:43,972 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0765) Prec@1 91.000 (87.589) Prec@5 98.000 (99.189) +2022-11-14 16:35:43,986 Test: [90/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0763) Prec@1 90.000 (87.615) Prec@5 100.000 (99.198) +2022-11-14 16:35:43,999 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0760) Prec@1 90.000 (87.641) Prec@5 100.000 (99.207) +2022-11-14 16:35:44,014 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0760) Prec@1 86.000 (87.624) Prec@5 100.000 (99.215) +2022-11-14 16:35:44,026 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0758 (0.0760) Prec@1 87.000 (87.617) Prec@5 100.000 (99.223) +2022-11-14 16:35:44,039 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1152 (0.0764) Prec@1 80.000 (87.537) Prec@5 100.000 (99.232) +2022-11-14 16:35:44,051 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0764) Prec@1 89.000 (87.552) Prec@5 99.000 (99.229) +2022-11-14 16:35:44,065 Test: [96/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0761) Prec@1 92.000 (87.598) Prec@5 99.000 (99.227) +2022-11-14 16:35:44,079 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0761) Prec@1 88.000 (87.602) Prec@5 99.000 (99.224) +2022-11-14 16:35:44,092 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0761) Prec@1 88.000 (87.606) Prec@5 98.000 (99.212) +2022-11-14 16:35:44,104 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0759) Prec@1 92.000 (87.650) Prec@5 100.000 (99.220) +2022-11-14 16:35:44,170 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:35:44,589 Epoch: [361][0/500] Time 0.028 (0.028) Data 0.325 (0.325) Loss 0.0248 (0.0248) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:35:44,858 Epoch: [361][10/500] Time 0.026 (0.025) Data 0.002 (0.031) Loss 0.0487 (0.0367) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:35:45,153 Epoch: [361][20/500] Time 0.029 (0.025) Data 0.002 (0.017) Loss 0.0147 (0.0294) Prec@1 99.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:35:45,485 Epoch: [361][30/500] Time 0.027 (0.027) Data 0.002 (0.012) Loss 0.0360 (0.0310) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:35:45,820 Epoch: [361][40/500] Time 0.038 (0.027) Data 0.002 (0.010) Loss 0.0569 (0.0362) Prec@1 90.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:35:46,144 Epoch: [361][50/500] Time 0.028 (0.028) Data 0.002 (0.008) Loss 0.0415 (0.0371) Prec@1 94.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:35:46,482 Epoch: [361][60/500] Time 0.025 (0.028) Data 0.002 (0.007) Loss 0.0220 (0.0349) Prec@1 96.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 16:35:47,082 Epoch: [361][70/500] Time 0.064 (0.032) Data 0.002 (0.007) Loss 0.0298 (0.0343) Prec@1 95.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 16:35:47,671 Epoch: [361][80/500] Time 0.064 (0.034) Data 0.002 (0.006) Loss 0.0319 (0.0340) Prec@1 93.000 (94.444) Prec@5 100.000 (100.000) +2022-11-14 16:35:48,286 Epoch: [361][90/500] Time 0.064 (0.037) Data 0.003 (0.006) Loss 0.0452 (0.0352) Prec@1 92.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 16:35:48,884 Epoch: [361][100/500] Time 0.064 (0.038) Data 0.002 (0.005) Loss 0.0221 (0.0340) Prec@1 96.000 (94.364) Prec@5 100.000 (100.000) +2022-11-14 16:35:49,491 Epoch: [361][110/500] Time 0.073 (0.040) Data 0.002 (0.005) Loss 0.0382 (0.0343) Prec@1 95.000 (94.417) Prec@5 99.000 (99.917) +2022-11-14 16:35:50,080 Epoch: [361][120/500] Time 0.054 (0.041) Data 0.002 (0.005) Loss 0.0272 (0.0338) Prec@1 97.000 (94.615) Prec@5 99.000 (99.846) +2022-11-14 16:35:50,676 Epoch: [361][130/500] Time 0.062 (0.042) Data 0.002 (0.005) Loss 0.0279 (0.0334) Prec@1 96.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:35:51,277 Epoch: [361][140/500] Time 0.052 (0.043) Data 0.002 (0.004) Loss 0.0438 (0.0340) Prec@1 91.000 (94.467) Prec@5 100.000 (99.867) +2022-11-14 16:35:51,871 Epoch: [361][150/500] Time 0.068 (0.043) Data 0.002 (0.004) Loss 0.0332 (0.0340) Prec@1 94.000 (94.438) Prec@5 100.000 (99.875) +2022-11-14 16:35:52,480 Epoch: [361][160/500] Time 0.057 (0.044) Data 0.002 (0.004) Loss 0.0356 (0.0341) Prec@1 94.000 (94.412) Prec@5 100.000 (99.882) +2022-11-14 16:35:53,053 Epoch: [361][170/500] Time 0.050 (0.044) Data 0.002 (0.004) Loss 0.0181 (0.0332) Prec@1 98.000 (94.611) Prec@5 100.000 (99.889) +2022-11-14 16:35:53,662 Epoch: [361][180/500] Time 0.056 (0.045) Data 0.002 (0.004) Loss 0.0266 (0.0328) Prec@1 97.000 (94.737) Prec@5 100.000 (99.895) +2022-11-14 16:35:54,265 Epoch: [361][190/500] Time 0.056 (0.045) Data 0.002 (0.004) Loss 0.0179 (0.0321) Prec@1 97.000 (94.850) Prec@5 100.000 (99.900) +2022-11-14 16:35:54,869 Epoch: [361][200/500] Time 0.077 (0.046) Data 0.002 (0.004) Loss 0.0133 (0.0312) Prec@1 98.000 (95.000) Prec@5 100.000 (99.905) +2022-11-14 16:35:55,471 Epoch: [361][210/500] Time 0.054 (0.046) Data 0.002 (0.004) Loss 0.0332 (0.0313) Prec@1 95.000 (95.000) Prec@5 99.000 (99.864) +2022-11-14 16:35:56,058 Epoch: [361][220/500] Time 0.045 (0.046) Data 0.002 (0.004) Loss 0.0448 (0.0319) Prec@1 94.000 (94.957) Prec@5 100.000 (99.870) +2022-11-14 16:35:56,636 Epoch: [361][230/500] Time 0.062 (0.047) Data 0.002 (0.003) Loss 0.0432 (0.0323) Prec@1 94.000 (94.917) Prec@5 100.000 (99.875) +2022-11-14 16:35:57,292 Epoch: [361][240/500] Time 0.075 (0.047) Data 0.002 (0.003) Loss 0.0199 (0.0318) Prec@1 97.000 (95.000) Prec@5 99.000 (99.840) +2022-11-14 16:35:57,901 Epoch: [361][250/500] Time 0.060 (0.047) Data 0.002 (0.003) Loss 0.0315 (0.0318) Prec@1 95.000 (95.000) Prec@5 100.000 (99.846) +2022-11-14 16:35:58,481 Epoch: [361][260/500] Time 0.051 (0.048) Data 0.002 (0.003) Loss 0.0230 (0.0315) Prec@1 95.000 (95.000) Prec@5 100.000 (99.852) +2022-11-14 16:35:59,073 Epoch: [361][270/500] Time 0.050 (0.048) Data 0.002 (0.003) Loss 0.0204 (0.0311) Prec@1 96.000 (95.036) Prec@5 100.000 (99.857) +2022-11-14 16:35:59,711 Epoch: [361][280/500] Time 0.063 (0.048) Data 0.002 (0.003) Loss 0.0157 (0.0306) Prec@1 98.000 (95.138) Prec@5 100.000 (99.862) +2022-11-14 16:36:00,321 Epoch: [361][290/500] Time 0.059 (0.048) Data 0.002 (0.003) Loss 0.0301 (0.0306) Prec@1 95.000 (95.133) Prec@5 100.000 (99.867) +2022-11-14 16:36:00,921 Epoch: [361][300/500] Time 0.060 (0.049) Data 0.002 (0.003) Loss 0.0210 (0.0303) Prec@1 96.000 (95.161) Prec@5 100.000 (99.871) +2022-11-14 16:36:01,576 Epoch: [361][310/500] Time 0.077 (0.049) Data 0.002 (0.003) Loss 0.0335 (0.0304) Prec@1 95.000 (95.156) Prec@5 99.000 (99.844) +2022-11-14 16:36:02,247 Epoch: [361][320/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0351 (0.0305) Prec@1 96.000 (95.182) Prec@5 100.000 (99.848) +2022-11-14 16:36:02,877 Epoch: [361][330/500] Time 0.080 (0.049) Data 0.002 (0.003) Loss 0.0202 (0.0302) Prec@1 97.000 (95.235) Prec@5 100.000 (99.853) +2022-11-14 16:36:03,487 Epoch: [361][340/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0144 (0.0297) Prec@1 96.000 (95.257) Prec@5 100.000 (99.857) +2022-11-14 16:36:04,087 Epoch: [361][350/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0234 (0.0296) Prec@1 95.000 (95.250) Prec@5 100.000 (99.861) +2022-11-14 16:36:04,774 Epoch: [361][360/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0310 (0.0296) Prec@1 95.000 (95.243) Prec@5 100.000 (99.865) +2022-11-14 16:36:05,369 Epoch: [361][370/500] Time 0.066 (0.050) Data 0.002 (0.003) Loss 0.0422 (0.0299) Prec@1 93.000 (95.184) Prec@5 100.000 (99.868) +2022-11-14 16:36:05,970 Epoch: [361][380/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0470 (0.0304) Prec@1 91.000 (95.077) Prec@5 100.000 (99.872) +2022-11-14 16:36:06,555 Epoch: [361][390/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0300 (0.0304) Prec@1 94.000 (95.050) Prec@5 100.000 (99.875) +2022-11-14 16:36:07,156 Epoch: [361][400/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0315 (0.0304) Prec@1 94.000 (95.024) Prec@5 100.000 (99.878) +2022-11-14 16:36:07,754 Epoch: [361][410/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0211 (0.0302) Prec@1 97.000 (95.071) Prec@5 100.000 (99.881) +2022-11-14 16:36:08,336 Epoch: [361][420/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0322 (0.0302) Prec@1 94.000 (95.047) Prec@5 100.000 (99.884) +2022-11-14 16:36:08,961 Epoch: [361][430/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0144 (0.0299) Prec@1 98.000 (95.114) Prec@5 100.000 (99.886) +2022-11-14 16:36:09,589 Epoch: [361][440/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0289 (0.0298) Prec@1 95.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:36:10,179 Epoch: [361][450/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0332 (0.0299) Prec@1 94.000 (95.087) Prec@5 100.000 (99.891) +2022-11-14 16:36:10,820 Epoch: [361][460/500] Time 0.082 (0.051) Data 0.002 (0.003) Loss 0.0377 (0.0301) Prec@1 94.000 (95.064) Prec@5 100.000 (99.894) +2022-11-14 16:36:11,447 Epoch: [361][470/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0362 (0.0302) Prec@1 95.000 (95.062) Prec@5 100.000 (99.896) +2022-11-14 16:36:12,046 Epoch: [361][480/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0319 (0.0302) Prec@1 94.000 (95.041) Prec@5 100.000 (99.898) +2022-11-14 16:36:12,651 Epoch: [361][490/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0385 (0.0304) Prec@1 93.000 (95.000) Prec@5 99.000 (99.880) +2022-11-14 16:36:13,196 Epoch: [361][499/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0228 (0.0303) Prec@1 96.000 (95.020) Prec@5 100.000 (99.882) +2022-11-14 16:36:13,594 Test: [0/100] Model Time 0.016 (0.016) Loss Time 0.000 (0.000) Loss 0.0394 (0.0394) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:13,610 Test: [1/100] Model Time 0.011 (0.014) Loss Time 0.000 (0.000) Loss 0.0547 (0.0471) Prec@1 88.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:36:13,620 Test: [2/100] Model Time 0.009 (0.012) Loss Time 0.000 (0.000) Loss 0.0680 (0.0540) Prec@1 91.000 (90.667) Prec@5 99.000 (99.667) +2022-11-14 16:36:13,633 Test: [3/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0714 (0.0584) Prec@1 89.000 (90.250) Prec@5 98.000 (99.250) +2022-11-14 16:36:13,645 Test: [4/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0772 (0.0622) Prec@1 88.000 (89.800) Prec@5 99.000 (99.200) +2022-11-14 16:36:13,657 Test: [5/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0379 (0.0581) Prec@1 93.000 (90.333) Prec@5 100.000 (99.333) +2022-11-14 16:36:13,669 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0713 (0.0600) Prec@1 89.000 (90.143) Prec@5 99.000 (99.286) +2022-11-14 16:36:13,684 Test: [7/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0825 (0.0628) Prec@1 87.000 (89.750) Prec@5 100.000 (99.375) +2022-11-14 16:36:13,699 Test: [8/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0742 (0.0641) Prec@1 90.000 (89.778) Prec@5 99.000 (99.333) +2022-11-14 16:36:13,712 Test: [9/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0693 (0.0646) Prec@1 91.000 (89.900) Prec@5 99.000 (99.300) +2022-11-14 16:36:13,726 Test: [10/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0574 (0.0639) Prec@1 91.000 (90.000) Prec@5 100.000 (99.364) +2022-11-14 16:36:13,744 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0651) Prec@1 88.000 (89.833) Prec@5 100.000 (99.417) +2022-11-14 16:36:13,761 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0520 (0.0641) Prec@1 92.000 (90.000) Prec@5 100.000 (99.462) +2022-11-14 16:36:13,778 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0642) Prec@1 91.000 (90.071) Prec@5 100.000 (99.500) +2022-11-14 16:36:13,797 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0646) Prec@1 89.000 (90.000) Prec@5 99.000 (99.467) +2022-11-14 16:36:13,817 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0657) Prec@1 85.000 (89.688) Prec@5 99.000 (99.438) +2022-11-14 16:36:13,838 Test: [16/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0650) Prec@1 91.000 (89.765) Prec@5 98.000 (99.353) +2022-11-14 16:36:13,859 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0966 (0.0668) Prec@1 85.000 (89.500) Prec@5 100.000 (99.389) +2022-11-14 16:36:13,879 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0830 (0.0677) Prec@1 84.000 (89.211) Prec@5 99.000 (99.368) +2022-11-14 16:36:13,899 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0824 (0.0684) Prec@1 85.000 (89.000) Prec@5 98.000 (99.300) +2022-11-14 16:36:13,919 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0685) Prec@1 89.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 16:36:13,939 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0773 (0.0689) Prec@1 86.000 (88.864) Prec@5 99.000 (99.318) +2022-11-14 16:36:13,955 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1061 (0.0706) Prec@1 83.000 (88.609) Prec@5 99.000 (99.304) +2022-11-14 16:36:13,975 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0709) Prec@1 88.000 (88.583) Prec@5 100.000 (99.333) +2022-11-14 16:36:13,997 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0941 (0.0718) Prec@1 86.000 (88.480) Prec@5 100.000 (99.360) +2022-11-14 16:36:14,018 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0720) Prec@1 90.000 (88.538) Prec@5 99.000 (99.346) +2022-11-14 16:36:14,037 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0403 (0.0708) Prec@1 93.000 (88.704) Prec@5 100.000 (99.370) +2022-11-14 16:36:14,056 Test: [27/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0708) Prec@1 90.000 (88.750) Prec@5 100.000 (99.393) +2022-11-14 16:36:14,078 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0709) Prec@1 88.000 (88.724) Prec@5 100.000 (99.414) +2022-11-14 16:36:14,097 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0708) Prec@1 87.000 (88.667) Prec@5 100.000 (99.433) +2022-11-14 16:36:14,116 Test: [30/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0708) Prec@1 87.000 (88.613) Prec@5 100.000 (99.452) +2022-11-14 16:36:14,135 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0708) Prec@1 88.000 (88.594) Prec@5 98.000 (99.406) +2022-11-14 16:36:14,155 Test: [32/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0753 (0.0710) Prec@1 86.000 (88.515) Prec@5 100.000 (99.424) +2022-11-14 16:36:14,177 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0779 (0.0712) Prec@1 89.000 (88.529) Prec@5 100.000 (99.441) +2022-11-14 16:36:14,197 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0712) Prec@1 89.000 (88.543) Prec@5 98.000 (99.400) +2022-11-14 16:36:14,218 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0662 (0.0710) Prec@1 90.000 (88.583) Prec@5 100.000 (99.417) +2022-11-14 16:36:14,241 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0551 (0.0706) Prec@1 92.000 (88.676) Prec@5 99.000 (99.405) +2022-11-14 16:36:14,261 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0711) Prec@1 86.000 (88.605) Prec@5 98.000 (99.368) +2022-11-14 16:36:14,280 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0706) Prec@1 93.000 (88.718) Prec@5 100.000 (99.385) +2022-11-14 16:36:14,300 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0709) Prec@1 88.000 (88.700) Prec@5 99.000 (99.375) +2022-11-14 16:36:14,319 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0809 (0.0711) Prec@1 87.000 (88.659) Prec@5 98.000 (99.341) +2022-11-14 16:36:14,337 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0710) Prec@1 91.000 (88.714) Prec@5 99.000 (99.333) +2022-11-14 16:36:14,356 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0450 (0.0704) Prec@1 93.000 (88.814) Prec@5 99.000 (99.326) +2022-11-14 16:36:14,372 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0704) Prec@1 89.000 (88.818) Prec@5 99.000 (99.318) +2022-11-14 16:36:14,393 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0704) Prec@1 87.000 (88.778) Prec@5 99.000 (99.311) +2022-11-14 16:36:14,414 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0990 (0.0710) Prec@1 82.000 (88.630) Prec@5 98.000 (99.283) +2022-11-14 16:36:14,436 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0491 (0.0706) Prec@1 92.000 (88.702) Prec@5 100.000 (99.298) +2022-11-14 16:36:14,453 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0714) Prec@1 80.000 (88.521) Prec@5 99.000 (99.292) +2022-11-14 16:36:14,474 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0712) Prec@1 89.000 (88.531) Prec@5 100.000 (99.306) +2022-11-14 16:36:14,495 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0716) Prec@1 86.000 (88.480) Prec@5 100.000 (99.320) +2022-11-14 16:36:14,513 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0712) Prec@1 92.000 (88.549) Prec@5 100.000 (99.333) +2022-11-14 16:36:14,535 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0875 (0.0715) Prec@1 87.000 (88.519) Prec@5 99.000 (99.327) +2022-11-14 16:36:14,555 Test: [52/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0715) Prec@1 89.000 (88.528) Prec@5 99.000 (99.321) +2022-11-14 16:36:14,575 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0715) Prec@1 88.000 (88.519) Prec@5 100.000 (99.333) +2022-11-14 16:36:14,594 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0717) Prec@1 89.000 (88.527) Prec@5 100.000 (99.345) +2022-11-14 16:36:14,610 Test: 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Loss 0.0540 (0.0719) Prec@1 92.000 (88.500) Prec@5 99.000 (99.371) +2022-11-14 16:36:14,753 Test: [62/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0717) Prec@1 90.000 (88.524) Prec@5 99.000 (99.365) +2022-11-14 16:36:14,775 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0715) Prec@1 90.000 (88.547) Prec@5 99.000 (99.359) +2022-11-14 16:36:14,795 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0719) Prec@1 81.000 (88.431) Prec@5 99.000 (99.354) +2022-11-14 16:36:14,817 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0877 (0.0722) Prec@1 84.000 (88.364) Prec@5 99.000 (99.348) +2022-11-14 16:36:14,842 Test: [66/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0485 (0.0718) Prec@1 92.000 (88.418) Prec@5 100.000 (99.358) +2022-11-14 16:36:14,862 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0815 (0.0720) Prec@1 85.000 (88.368) Prec@5 99.000 (99.353) +2022-11-14 16:36:14,879 Test: [68/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0655 (0.0719) Prec@1 89.000 (88.377) Prec@5 99.000 (99.348) +2022-11-14 16:36:14,897 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0718) Prec@1 90.000 (88.400) Prec@5 100.000 (99.357) +2022-11-14 16:36:14,918 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0720) Prec@1 87.000 (88.380) Prec@5 99.000 (99.352) +2022-11-14 16:36:14,938 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0718) Prec@1 89.000 (88.389) Prec@5 100.000 (99.361) +2022-11-14 16:36:14,954 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0716) Prec@1 91.000 (88.425) Prec@5 100.000 (99.370) +2022-11-14 16:36:14,972 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0421 (0.0712) Prec@1 93.000 (88.486) Prec@5 100.000 (99.378) +2022-11-14 16:36:14,994 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0716) Prec@1 83.000 (88.413) Prec@5 98.000 (99.360) +2022-11-14 16:36:15,013 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0716) Prec@1 90.000 (88.434) Prec@5 100.000 (99.368) +2022-11-14 16:36:15,032 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0713) Prec@1 93.000 (88.494) Prec@5 98.000 (99.351) +2022-11-14 16:36:15,052 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0714) Prec@1 86.000 (88.462) Prec@5 97.000 (99.321) +2022-11-14 16:36:15,081 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0716) Prec@1 89.000 (88.468) Prec@5 100.000 (99.329) +2022-11-14 16:36:15,112 Test: [79/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0716) Prec@1 89.000 (88.475) Prec@5 100.000 (99.338) +2022-11-14 16:36:15,142 Test: [80/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0819 (0.0718) Prec@1 86.000 (88.444) Prec@5 98.000 (99.321) +2022-11-14 16:36:15,167 Test: [81/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0664 (0.0717) Prec@1 90.000 (88.463) Prec@5 100.000 (99.329) +2022-11-14 16:36:15,197 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0719) Prec@1 87.000 (88.446) Prec@5 99.000 (99.325) +2022-11-14 16:36:15,225 Test: [83/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0718) Prec@1 91.000 (88.476) Prec@5 100.000 (99.333) +2022-11-14 16:36:15,251 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0719) Prec@1 90.000 (88.494) Prec@5 99.000 (99.329) +2022-11-14 16:36:15,275 Test: [85/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0933 (0.0721) Prec@1 86.000 (88.465) Prec@5 100.000 (99.337) +2022-11-14 16:36:15,302 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0659 (0.0720) Prec@1 90.000 (88.483) Prec@5 99.000 (99.333) +2022-11-14 16:36:15,325 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0708 (0.0720) Prec@1 89.000 (88.489) Prec@5 99.000 (99.330) +2022-11-14 16:36:15,353 Test: [88/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0984 (0.0723) Prec@1 86.000 (88.461) Prec@5 99.000 (99.326) +2022-11-14 16:36:15,377 Test: [89/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0725) Prec@1 87.000 (88.444) Prec@5 99.000 (99.322) +2022-11-14 16:36:15,404 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0589 (0.0724) Prec@1 91.000 (88.473) Prec@5 99.000 (99.319) +2022-11-14 16:36:15,429 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0471 (0.0721) Prec@1 93.000 (88.522) Prec@5 100.000 (99.326) +2022-11-14 16:36:15,455 Test: [92/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0872 (0.0722) Prec@1 87.000 (88.505) Prec@5 100.000 (99.333) +2022-11-14 16:36:15,476 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0724) Prec@1 86.000 (88.479) Prec@5 99.000 (99.330) +2022-11-14 16:36:15,495 Test: [94/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0818 (0.0725) Prec@1 85.000 (88.442) Prec@5 100.000 (99.337) +2022-11-14 16:36:15,513 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0724) Prec@1 91.000 (88.469) Prec@5 99.000 (99.333) +2022-11-14 16:36:15,531 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0391 (0.0720) Prec@1 96.000 (88.546) Prec@5 99.000 (99.330) +2022-11-14 16:36:15,551 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0721) Prec@1 90.000 (88.561) Prec@5 100.000 (99.337) +2022-11-14 16:36:15,571 Test: [98/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0941 (0.0723) Prec@1 86.000 (88.535) Prec@5 99.000 (99.333) +2022-11-14 16:36:15,591 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0614 (0.0722) Prec@1 91.000 (88.560) Prec@5 100.000 (99.340) +2022-11-14 16:36:15,671 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:36:16,057 Epoch: [362][0/500] Time 0.025 (0.025) Data 0.292 (0.292) Loss 0.0271 (0.0271) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:16,363 Epoch: [362][10/500] Time 0.031 (0.027) Data 0.002 (0.028) Loss 0.0254 (0.0263) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:16,702 Epoch: [362][20/500] Time 0.031 (0.028) Data 0.002 (0.016) Loss 0.0273 (0.0266) Prec@1 95.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:36:17,084 Epoch: [362][30/500] Time 0.029 (0.030) Data 0.002 (0.011) Loss 0.0252 (0.0262) Prec@1 96.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:36:17,595 Epoch: [362][40/500] Time 0.060 (0.034) Data 0.002 (0.009) Loss 0.0354 (0.0281) Prec@1 93.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:36:18,199 Epoch: [362][50/500] Time 0.073 (0.038) Data 0.002 (0.008) Loss 0.0492 (0.0316) Prec@1 92.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:36:18,767 Epoch: [362][60/500] Time 0.054 (0.040) Data 0.002 (0.007) Loss 0.0294 (0.0313) Prec@1 96.000 (94.857) Prec@5 100.000 (100.000) +2022-11-14 16:36:19,384 Epoch: [362][70/500] Time 0.073 (0.042) Data 0.002 (0.006) Loss 0.0238 (0.0304) Prec@1 97.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 16:36:19,960 Epoch: [362][80/500] Time 0.056 (0.043) Data 0.002 (0.006) Loss 0.0367 (0.0311) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:20,531 Epoch: [362][90/500] Time 0.054 (0.044) Data 0.003 (0.005) Loss 0.0414 (0.0321) Prec@1 94.000 (94.900) Prec@5 100.000 (100.000) +2022-11-14 16:36:21,191 Epoch: [362][100/500] Time 0.050 (0.046) Data 0.002 (0.005) Loss 0.0305 (0.0320) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:21,772 Epoch: [362][110/500] Time 0.057 (0.046) Data 0.002 (0.005) Loss 0.0408 (0.0327) Prec@1 93.000 (94.833) Prec@5 99.000 (99.917) +2022-11-14 16:36:22,342 Epoch: [362][120/500] Time 0.052 (0.047) Data 0.002 (0.004) Loss 0.0318 (0.0326) Prec@1 95.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 16:36:22,911 Epoch: [362][130/500] Time 0.051 (0.047) Data 0.002 (0.004) Loss 0.0370 (0.0329) Prec@1 94.000 (94.786) Prec@5 100.000 (99.929) +2022-11-14 16:36:23,582 Epoch: [362][140/500] Time 0.050 (0.048) Data 0.002 (0.004) Loss 0.0331 (0.0330) Prec@1 95.000 (94.800) Prec@5 100.000 (99.933) +2022-11-14 16:36:24,172 Epoch: [362][150/500] Time 0.061 (0.048) Data 0.002 (0.004) Loss 0.0437 (0.0336) Prec@1 88.000 (94.375) Prec@5 100.000 (99.938) +2022-11-14 16:36:24,756 Epoch: [362][160/500] Time 0.049 (0.048) Data 0.002 (0.004) Loss 0.0374 (0.0338) Prec@1 94.000 (94.353) Prec@5 100.000 (99.941) +2022-11-14 16:36:25,329 Epoch: [362][170/500] Time 0.048 (0.049) Data 0.002 (0.004) Loss 0.0446 (0.0344) Prec@1 92.000 (94.222) Prec@5 100.000 (99.944) +2022-11-14 16:36:25,911 Epoch: [362][180/500] Time 0.052 (0.049) Data 0.002 (0.004) Loss 0.0456 (0.0350) Prec@1 92.000 (94.105) Prec@5 100.000 (99.947) +2022-11-14 16:36:26,583 Epoch: [362][190/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0294 (0.0348) Prec@1 96.000 (94.200) Prec@5 100.000 (99.950) +2022-11-14 16:36:27,146 Epoch: [362][200/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0394 (0.0350) Prec@1 93.000 (94.143) Prec@5 99.000 (99.905) +2022-11-14 16:36:27,720 Epoch: [362][210/500] Time 0.060 (0.050) Data 0.002 (0.003) Loss 0.0256 (0.0346) Prec@1 95.000 (94.182) Prec@5 99.000 (99.864) +2022-11-14 16:36:28,310 Epoch: [362][220/500] Time 0.060 (0.050) Data 0.002 (0.003) Loss 0.0276 (0.0342) Prec@1 96.000 (94.261) Prec@5 99.000 (99.826) +2022-11-14 16:36:28,899 Epoch: [362][230/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0640 (0.0355) Prec@1 89.000 (94.042) Prec@5 100.000 (99.833) +2022-11-14 16:36:29,469 Epoch: [362][240/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0252 (0.0351) Prec@1 97.000 (94.160) Prec@5 99.000 (99.800) +2022-11-14 16:36:30,151 Epoch: [362][250/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0371 (0.0352) Prec@1 93.000 (94.115) Prec@5 100.000 (99.808) +2022-11-14 16:36:30,837 Epoch: [362][260/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0376 (0.0352) Prec@1 91.000 (94.000) Prec@5 100.000 (99.815) +2022-11-14 16:36:31,408 Epoch: [362][270/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0469 (0.0357) Prec@1 92.000 (93.929) Prec@5 100.000 (99.821) +2022-11-14 16:36:32,008 Epoch: [362][280/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0325 (0.0355) Prec@1 95.000 (93.966) Prec@5 100.000 (99.828) +2022-11-14 16:36:32,610 Epoch: [362][290/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0234 (0.0351) Prec@1 97.000 (94.067) Prec@5 100.000 (99.833) +2022-11-14 16:36:33,188 Epoch: [362][300/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0267 (0.0349) Prec@1 94.000 (94.065) Prec@5 100.000 (99.839) +2022-11-14 16:36:33,738 Epoch: [362][310/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0488 (0.0353) Prec@1 90.000 (93.938) Prec@5 100.000 (99.844) +2022-11-14 16:36:34,299 Epoch: [362][320/500] Time 0.064 (0.051) Data 0.002 (0.003) Loss 0.0220 (0.0349) Prec@1 97.000 (94.030) Prec@5 100.000 (99.848) +2022-11-14 16:36:34,887 Epoch: [362][330/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0207 (0.0345) Prec@1 98.000 (94.147) Prec@5 99.000 (99.824) +2022-11-14 16:36:35,556 Epoch: [362][340/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0443 (0.0348) Prec@1 91.000 (94.057) Prec@5 100.000 (99.829) +2022-11-14 16:36:36,140 Epoch: [362][350/500] Time 0.063 (0.051) Data 0.002 (0.003) Loss 0.0334 (0.0347) Prec@1 96.000 (94.111) Prec@5 100.000 (99.833) +2022-11-14 16:36:36,719 Epoch: [362][360/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0261 (0.0345) Prec@1 95.000 (94.135) Prec@5 100.000 (99.838) +2022-11-14 16:36:37,263 Epoch: [362][370/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0278 (0.0343) Prec@1 95.000 (94.158) Prec@5 100.000 (99.842) +2022-11-14 16:36:37,836 Epoch: [362][380/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0216 (0.0340) Prec@1 98.000 (94.256) Prec@5 100.000 (99.846) +2022-11-14 16:36:38,419 Epoch: [362][390/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0223 (0.0337) Prec@1 97.000 (94.325) Prec@5 100.000 (99.850) +2022-11-14 16:36:38,999 Epoch: [362][400/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0296 (0.0336) Prec@1 96.000 (94.366) Prec@5 100.000 (99.854) +2022-11-14 16:36:39,591 Epoch: [362][410/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0144 (0.0331) Prec@1 98.000 (94.452) Prec@5 100.000 (99.857) +2022-11-14 16:36:40,163 Epoch: [362][420/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0185 (0.0328) Prec@1 97.000 (94.512) Prec@5 100.000 (99.860) +2022-11-14 16:36:40,754 Epoch: [362][430/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0244 (0.0326) Prec@1 95.000 (94.523) Prec@5 100.000 (99.864) +2022-11-14 16:36:41,318 Epoch: [362][440/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0231 (0.0324) Prec@1 95.000 (94.533) Prec@5 100.000 (99.867) +2022-11-14 16:36:41,913 Epoch: [362][450/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0153 (0.0320) Prec@1 98.000 (94.609) Prec@5 100.000 (99.870) +2022-11-14 16:36:42,485 Epoch: [362][460/500] Time 0.048 (0.051) Data 0.003 (0.003) Loss 0.0078 (0.0315) Prec@1 100.000 (94.723) Prec@5 100.000 (99.872) +2022-11-14 16:36:43,074 Epoch: [362][470/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0356 (0.0316) Prec@1 93.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 16:36:43,637 Epoch: [362][480/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0387 (0.0317) Prec@1 94.000 (94.673) Prec@5 100.000 (99.878) +2022-11-14 16:36:44,226 Epoch: [362][490/500] Time 0.049 (0.051) Data 0.002 (0.003) Loss 0.0294 (0.0317) Prec@1 94.000 (94.660) Prec@5 100.000 (99.880) +2022-11-14 16:36:44,764 Epoch: [362][499/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0381 (0.0318) Prec@1 93.000 (94.627) Prec@5 100.000 (99.882) +2022-11-14 16:36:45,157 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0597 (0.0597) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:45,167 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0674 (0.0635) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:45,182 Test: [2/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0863 (0.0711) Prec@1 86.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 16:36:45,195 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0717 (0.0713) Prec@1 88.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 16:36:45,206 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0622 (0.0695) Prec@1 89.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:36:45,216 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0542 (0.0669) Prec@1 90.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:36:45,228 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0658) Prec@1 91.000 (89.429) Prec@5 99.000 (99.571) +2022-11-14 16:36:45,245 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0685) Prec@1 86.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:36:45,257 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0697) Prec@1 89.000 (89.000) Prec@5 99.000 (99.444) +2022-11-14 16:36:45,273 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0709) Prec@1 88.000 (88.900) Prec@5 99.000 (99.400) +2022-11-14 16:36:45,290 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0689) Prec@1 93.000 (89.273) Prec@5 100.000 (99.455) +2022-11-14 16:36:45,307 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0701) Prec@1 87.000 (89.083) Prec@5 100.000 (99.500) +2022-11-14 16:36:45,324 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0695) Prec@1 90.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 16:36:45,342 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0865 (0.0707) Prec@1 86.000 (88.929) Prec@5 99.000 (99.500) +2022-11-14 16:36:45,363 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0723) Prec@1 85.000 (88.667) Prec@5 100.000 (99.533) +2022-11-14 16:36:45,383 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0732) Prec@1 88.000 (88.625) Prec@5 100.000 (99.562) +2022-11-14 16:36:45,403 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0521 (0.0719) Prec@1 93.000 (88.882) Prec@5 98.000 (99.471) +2022-11-14 16:36:45,424 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1114 (0.0741) Prec@1 82.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:36:45,444 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0746) Prec@1 87.000 (88.421) Prec@5 99.000 (99.474) +2022-11-14 16:36:45,464 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0754) Prec@1 83.000 (88.150) Prec@5 99.000 (99.450) +2022-11-14 16:36:45,482 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0750) Prec@1 90.000 (88.238) Prec@5 100.000 (99.476) +2022-11-14 16:36:45,501 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0756) Prec@1 88.000 (88.227) Prec@5 100.000 (99.500) +2022-11-14 16:36:45,519 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0767) Prec@1 84.000 (88.043) Prec@5 98.000 (99.435) +2022-11-14 16:36:45,540 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0967 (0.0775) Prec@1 84.000 (87.875) Prec@5 100.000 (99.458) +2022-11-14 16:36:45,561 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0773) Prec@1 90.000 (87.960) Prec@5 100.000 (99.480) +2022-11-14 16:36:45,581 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0776) Prec@1 87.000 (87.923) Prec@5 98.000 (99.423) +2022-11-14 16:36:45,601 Test: [26/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0766) Prec@1 92.000 (88.074) Prec@5 100.000 (99.444) +2022-11-14 16:36:45,622 Test: [27/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0760) Prec@1 90.000 (88.143) Prec@5 100.000 (99.464) +2022-11-14 16:36:45,642 Test: [28/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0735 (0.0759) Prec@1 88.000 (88.138) Prec@5 98.000 (99.414) +2022-11-14 16:36:45,663 Test: [29/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0651 (0.0756) Prec@1 88.000 (88.133) Prec@5 100.000 (99.433) +2022-11-14 16:36:45,680 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0758) Prec@1 86.000 (88.065) Prec@5 99.000 (99.419) +2022-11-14 16:36:45,702 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0759) Prec@1 88.000 (88.062) Prec@5 99.000 (99.406) +2022-11-14 16:36:45,724 Test: [32/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0764) Prec@1 85.000 (87.970) Prec@5 100.000 (99.424) +2022-11-14 16:36:45,742 Test: [33/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0771) Prec@1 83.000 (87.824) Prec@5 99.000 (99.412) +2022-11-14 16:36:45,759 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0770) Prec@1 92.000 (87.943) Prec@5 100.000 (99.429) +2022-11-14 16:36:45,780 Test: [35/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0768) Prec@1 90.000 (88.000) Prec@5 98.000 (99.389) +2022-11-14 16:36:45,801 Test: [36/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0765) Prec@1 89.000 (88.027) Prec@5 100.000 (99.405) +2022-11-14 16:36:45,821 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0767) Prec@1 85.000 (87.947) Prec@5 99.000 (99.395) +2022-11-14 16:36:45,843 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0760) Prec@1 93.000 (88.077) Prec@5 100.000 (99.410) +2022-11-14 16:36:45,860 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0757) Prec@1 90.000 (88.125) Prec@5 100.000 (99.425) +2022-11-14 16:36:45,879 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0758) Prec@1 88.000 (88.122) Prec@5 96.000 (99.341) +2022-11-14 16:36:45,895 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0640 (0.0756) Prec@1 87.000 (88.095) Prec@5 99.000 (99.333) +2022-11-14 16:36:45,915 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0471 (0.0749) Prec@1 91.000 (88.163) Prec@5 99.000 (99.326) +2022-11-14 16:36:45,934 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 89.000 (88.182) Prec@5 99.000 (99.318) +2022-11-14 16:36:45,955 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0553 (0.0747) Prec@1 92.000 (88.267) Prec@5 99.000 (99.311) +2022-11-14 16:36:45,973 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.0752) Prec@1 84.000 (88.174) Prec@5 99.000 (99.304) +2022-11-14 16:36:45,990 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0749) Prec@1 88.000 (88.170) Prec@5 100.000 (99.319) +2022-11-14 16:36:46,011 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0755) Prec@1 81.000 (88.021) Prec@5 99.000 (99.312) +2022-11-14 16:36:46,028 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0753) Prec@1 88.000 (88.020) Prec@5 100.000 (99.327) +2022-11-14 16:36:46,047 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0756) Prec@1 87.000 (88.000) Prec@5 100.000 (99.340) +2022-11-14 16:36:46,067 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0755) Prec@1 87.000 (87.980) Prec@5 100.000 (99.353) +2022-11-14 16:36:46,087 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0784 (0.0756) Prec@1 85.000 (87.923) Prec@5 99.000 (99.346) +2022-11-14 16:36:46,106 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0755) Prec@1 87.000 (87.906) Prec@5 99.000 (99.340) +2022-11-14 16:36:46,125 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0756) Prec@1 88.000 (87.907) Prec@5 99.000 (99.333) +2022-11-14 16:36:46,142 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0759) Prec@1 86.000 (87.873) Prec@5 100.000 (99.345) +2022-11-14 16:36:46,162 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0759) Prec@1 90.000 (87.911) Prec@5 99.000 (99.339) +2022-11-14 16:36:46,185 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0756) Prec@1 89.000 (87.930) Prec@5 99.000 (99.333) +2022-11-14 16:36:46,205 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0757) Prec@1 86.000 (87.897) Prec@5 98.000 (99.310) +2022-11-14 16:36:46,223 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0761) Prec@1 86.000 (87.864) Prec@5 100.000 (99.322) +2022-11-14 16:36:46,243 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0759) Prec@1 89.000 (87.883) Prec@5 100.000 (99.333) +2022-11-14 16:36:46,261 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0757) Prec@1 89.000 (87.902) Prec@5 99.000 (99.328) +2022-11-14 16:36:46,278 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0757) Prec@1 88.000 (87.903) Prec@5 99.000 (99.323) +2022-11-14 16:36:46,298 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0756) Prec@1 88.000 (87.905) Prec@5 100.000 (99.333) +2022-11-14 16:36:46,317 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0454 (0.0752) Prec@1 92.000 (87.969) Prec@5 100.000 (99.344) +2022-11-14 16:36:46,337 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0754) Prec@1 86.000 (87.938) Prec@5 100.000 (99.354) +2022-11-14 16:36:46,357 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0756) Prec@1 84.000 (87.879) Prec@5 99.000 (99.348) +2022-11-14 16:36:46,377 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0753) Prec@1 91.000 (87.925) Prec@5 99.000 (99.343) +2022-11-14 16:36:46,397 Test: [67/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0752) Prec@1 90.000 (87.956) Prec@5 97.000 (99.309) +2022-11-14 16:36:46,418 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0751) Prec@1 88.000 (87.957) Prec@5 99.000 (99.304) +2022-11-14 16:36:46,439 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0752) Prec@1 87.000 (87.943) Prec@5 99.000 (99.300) +2022-11-14 16:36:46,458 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0754) Prec@1 86.000 (87.915) Prec@5 98.000 (99.282) +2022-11-14 16:36:46,479 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0753) Prec@1 89.000 (87.931) Prec@5 99.000 (99.278) +2022-11-14 16:36:46,498 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0391 (0.0748) Prec@1 94.000 (88.014) Prec@5 100.000 (99.288) +2022-11-14 16:36:46,519 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0745) Prec@1 92.000 (88.068) Prec@5 100.000 (99.297) +2022-11-14 16:36:46,539 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0833 (0.0746) Prec@1 84.000 (88.013) Prec@5 100.000 (99.307) +2022-11-14 16:36:46,557 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0745) Prec@1 90.000 (88.039) Prec@5 98.000 (99.289) +2022-11-14 16:36:46,580 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0742) Prec@1 92.000 (88.091) Prec@5 99.000 (99.286) +2022-11-14 16:36:46,602 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0958 (0.0745) Prec@1 83.000 (88.026) Prec@5 98.000 (99.269) +2022-11-14 16:36:46,625 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0745) Prec@1 87.000 (88.013) Prec@5 100.000 (99.278) +2022-11-14 16:36:46,646 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0746) Prec@1 85.000 (87.975) Prec@5 100.000 (99.287) +2022-11-14 16:36:46,666 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0747) Prec@1 86.000 (87.951) Prec@5 98.000 (99.272) +2022-11-14 16:36:46,687 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0923 (0.0750) Prec@1 85.000 (87.915) Prec@5 99.000 (99.268) +2022-11-14 16:36:46,708 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0748) Prec@1 89.000 (87.928) Prec@5 99.000 (99.265) +2022-11-14 16:36:46,729 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0748) Prec@1 88.000 (87.929) Prec@5 99.000 (99.262) +2022-11-14 16:36:46,747 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0751) Prec@1 84.000 (87.882) Prec@5 99.000 (99.259) +2022-11-14 16:36:46,768 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0752) Prec@1 88.000 (87.884) Prec@5 99.000 (99.256) +2022-11-14 16:36:46,789 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0751) Prec@1 91.000 (87.920) Prec@5 100.000 (99.264) +2022-11-14 16:36:46,807 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0751) Prec@1 88.000 (87.920) Prec@5 98.000 (99.250) +2022-11-14 16:36:46,824 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0752) Prec@1 84.000 (87.876) Prec@5 100.000 (99.258) +2022-11-14 16:36:46,844 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0753) Prec@1 86.000 (87.856) Prec@5 99.000 (99.256) +2022-11-14 16:36:46,863 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0751) Prec@1 90.000 (87.879) Prec@5 100.000 (99.264) +2022-11-14 16:36:46,883 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0464 (0.0748) Prec@1 92.000 (87.924) Prec@5 100.000 (99.272) +2022-11-14 16:36:46,900 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0750) Prec@1 86.000 (87.903) Prec@5 100.000 (99.280) +2022-11-14 16:36:46,921 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0751) Prec@1 85.000 (87.872) Prec@5 99.000 (99.277) +2022-11-14 16:36:46,942 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0866 (0.0752) Prec@1 87.000 (87.863) Prec@5 98.000 (99.263) +2022-11-14 16:36:46,965 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0751) Prec@1 91.000 (87.896) Prec@5 99.000 (99.260) +2022-11-14 16:36:46,985 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0416 (0.0747) Prec@1 94.000 (87.959) Prec@5 99.000 (99.258) +2022-11-14 16:36:47,005 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0934 (0.0749) Prec@1 86.000 (87.939) Prec@5 99.000 (99.255) +2022-11-14 16:36:47,032 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0751) Prec@1 87.000 (87.929) Prec@5 99.000 (99.253) +2022-11-14 16:36:47,060 Test: [99/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0750) Prec@1 89.000 (87.940) Prec@5 99.000 (99.250) +2022-11-14 16:36:47,127 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:36:47,497 Epoch: [363][0/500] Time 0.032 (0.032) Data 0.275 (0.275) Loss 0.0157 (0.0157) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:36:47,800 Epoch: [363][10/500] Time 0.026 (0.027) Data 0.002 (0.027) Loss 0.0284 (0.0220) Prec@1 95.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 16:36:48,133 Epoch: [363][20/500] Time 0.029 (0.028) Data 0.002 (0.015) Loss 0.0326 (0.0255) Prec@1 95.000 (95.667) Prec@5 99.000 (99.333) +2022-11-14 16:36:48,681 Epoch: [363][30/500] Time 0.046 (0.035) Data 0.002 (0.011) Loss 0.0171 (0.0234) Prec@1 99.000 (96.500) Prec@5 100.000 (99.500) +2022-11-14 16:36:49,246 Epoch: [363][40/500] Time 0.050 (0.038) Data 0.003 (0.009) Loss 0.0323 (0.0252) Prec@1 93.000 (95.800) Prec@5 100.000 (99.600) +2022-11-14 16:36:49,806 Epoch: [363][50/500] Time 0.055 (0.041) Data 0.002 (0.008) Loss 0.0253 (0.0252) Prec@1 98.000 (96.167) Prec@5 100.000 (99.667) +2022-11-14 16:36:50,367 Epoch: [363][60/500] Time 0.062 (0.042) Data 0.002 (0.007) Loss 0.0175 (0.0241) Prec@1 97.000 (96.286) Prec@5 100.000 (99.714) +2022-11-14 16:36:50,920 Epoch: [363][70/500] Time 0.061 (0.043) Data 0.002 (0.006) Loss 0.0368 (0.0257) Prec@1 97.000 (96.375) Prec@5 100.000 (99.750) +2022-11-14 16:36:51,490 Epoch: [363][80/500] Time 0.052 (0.044) Data 0.002 (0.006) Loss 0.0228 (0.0254) Prec@1 97.000 (96.444) Prec@5 100.000 (99.778) +2022-11-14 16:36:52,123 Epoch: [363][90/500] Time 0.056 (0.046) Data 0.002 (0.005) Loss 0.0339 (0.0262) Prec@1 94.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:36:52,718 Epoch: [363][100/500] Time 0.059 (0.046) Data 0.002 (0.005) Loss 0.0172 (0.0254) Prec@1 97.000 (96.273) Prec@5 99.000 (99.727) +2022-11-14 16:36:53,306 Epoch: [363][110/500] Time 0.057 (0.047) Data 0.003 (0.005) Loss 0.0106 (0.0242) Prec@1 98.000 (96.417) Prec@5 100.000 (99.750) +2022-11-14 16:36:53,910 Epoch: [363][120/500] Time 0.045 (0.047) Data 0.002 (0.004) Loss 0.0174 (0.0237) Prec@1 97.000 (96.462) Prec@5 100.000 (99.769) +2022-11-14 16:36:54,489 Epoch: [363][130/500] Time 0.043 (0.048) Data 0.002 (0.004) Loss 0.0399 (0.0248) Prec@1 93.000 (96.214) Prec@5 99.000 (99.714) +2022-11-14 16:36:55,116 Epoch: [363][140/500] Time 0.060 (0.048) Data 0.002 (0.004) Loss 0.0338 (0.0254) Prec@1 95.000 (96.133) Prec@5 100.000 (99.733) +2022-11-14 16:36:55,740 Epoch: [363][150/500] Time 0.053 (0.049) Data 0.002 (0.004) Loss 0.0340 (0.0259) Prec@1 94.000 (96.000) Prec@5 99.000 (99.688) +2022-11-14 16:36:56,312 Epoch: [363][160/500] Time 0.057 (0.049) Data 0.002 (0.004) Loss 0.0369 (0.0266) Prec@1 95.000 (95.941) Prec@5 100.000 (99.706) +2022-11-14 16:36:56,896 Epoch: [363][170/500] Time 0.050 (0.049) Data 0.002 (0.004) Loss 0.0209 (0.0263) Prec@1 96.000 (95.944) Prec@5 100.000 (99.722) +2022-11-14 16:36:57,461 Epoch: [363][180/500] Time 0.040 (0.049) Data 0.002 (0.004) Loss 0.0462 (0.0273) Prec@1 93.000 (95.789) Prec@5 100.000 (99.737) +2022-11-14 16:36:58,007 Epoch: [363][190/500] Time 0.053 (0.049) Data 0.002 (0.004) Loss 0.0194 (0.0269) Prec@1 97.000 (95.850) Prec@5 99.000 (99.700) +2022-11-14 16:36:58,575 Epoch: [363][200/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0294 (0.0270) Prec@1 96.000 (95.857) Prec@5 100.000 (99.714) +2022-11-14 16:36:59,161 Epoch: [363][210/500] Time 0.077 (0.049) Data 0.002 (0.003) Loss 0.0355 (0.0274) Prec@1 93.000 (95.727) Prec@5 100.000 (99.727) +2022-11-14 16:36:59,772 Epoch: [363][220/500] Time 0.079 (0.050) Data 0.003 (0.003) Loss 0.0312 (0.0276) Prec@1 96.000 (95.739) Prec@5 100.000 (99.739) +2022-11-14 16:37:00,313 Epoch: [363][230/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0371 (0.0280) Prec@1 91.000 (95.542) Prec@5 100.000 (99.750) +2022-11-14 16:37:00,917 Epoch: [363][240/500] Time 0.080 (0.050) Data 0.002 (0.003) Loss 0.0663 (0.0295) Prec@1 88.000 (95.240) Prec@5 99.000 (99.720) +2022-11-14 16:37:01,526 Epoch: [363][250/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0132 (0.0289) Prec@1 97.000 (95.308) Prec@5 100.000 (99.731) +2022-11-14 16:37:02,080 Epoch: [363][260/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0366 (0.0292) Prec@1 94.000 (95.259) Prec@5 100.000 (99.741) +2022-11-14 16:37:02,624 Epoch: [363][270/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0454 (0.0298) Prec@1 95.000 (95.250) Prec@5 99.000 (99.714) +2022-11-14 16:37:03,255 Epoch: [363][280/500] Time 0.072 (0.050) Data 0.002 (0.003) Loss 0.0384 (0.0301) Prec@1 93.000 (95.172) Prec@5 100.000 (99.724) +2022-11-14 16:37:03,823 Epoch: [363][290/500] Time 0.053 (0.050) Data 0.002 (0.003) Loss 0.0272 (0.0300) Prec@1 94.000 (95.133) Prec@5 100.000 (99.733) +2022-11-14 16:37:04,370 Epoch: [363][300/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0391 (0.0303) Prec@1 94.000 (95.097) Prec@5 100.000 (99.742) +2022-11-14 16:37:04,946 Epoch: [363][310/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0279 (0.0302) Prec@1 95.000 (95.094) Prec@5 99.000 (99.719) +2022-11-14 16:37:05,528 Epoch: [363][320/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0255 (0.0300) Prec@1 95.000 (95.091) Prec@5 100.000 (99.727) +2022-11-14 16:37:06,114 Epoch: [363][330/500] Time 0.065 (0.050) Data 0.002 (0.003) Loss 0.0255 (0.0299) Prec@1 95.000 (95.088) Prec@5 100.000 (99.735) +2022-11-14 16:37:06,715 Epoch: [363][340/500] Time 0.045 (0.050) Data 0.002 (0.003) Loss 0.0260 (0.0298) Prec@1 94.000 (95.057) Prec@5 100.000 (99.743) +2022-11-14 16:37:07,276 Epoch: [363][350/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0366 (0.0300) Prec@1 94.000 (95.028) Prec@5 99.000 (99.722) +2022-11-14 16:37:07,842 Epoch: [363][360/500] Time 0.050 (0.050) Data 0.002 (0.003) Loss 0.0329 (0.0301) Prec@1 96.000 (95.054) Prec@5 100.000 (99.730) +2022-11-14 16:37:08,394 Epoch: [363][370/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0263 (0.0300) Prec@1 95.000 (95.053) Prec@5 100.000 (99.737) +2022-11-14 16:37:08,955 Epoch: [363][380/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0222 (0.0298) Prec@1 96.000 (95.077) Prec@5 100.000 (99.744) +2022-11-14 16:37:09,598 Epoch: [363][390/500] Time 0.062 (0.050) Data 0.002 (0.003) Loss 0.0208 (0.0295) Prec@1 95.000 (95.075) Prec@5 100.000 (99.750) +2022-11-14 16:37:10,147 Epoch: [363][400/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0127 (0.0291) Prec@1 99.000 (95.171) Prec@5 100.000 (99.756) +2022-11-14 16:37:10,755 Epoch: [363][410/500] Time 0.064 (0.051) Data 0.002 (0.003) Loss 0.0337 (0.0292) Prec@1 93.000 (95.119) Prec@5 100.000 (99.762) +2022-11-14 16:37:11,356 Epoch: [363][420/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0325 (0.0293) Prec@1 94.000 (95.093) Prec@5 100.000 (99.767) +2022-11-14 16:37:11,960 Epoch: [363][430/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0574 (0.0300) Prec@1 90.000 (94.977) Prec@5 100.000 (99.773) +2022-11-14 16:37:12,528 Epoch: [363][440/500] Time 0.046 (0.051) Data 0.002 (0.003) Loss 0.0286 (0.0299) Prec@1 95.000 (94.978) Prec@5 100.000 (99.778) +2022-11-14 16:37:13,108 Epoch: [363][450/500] Time 0.036 (0.051) Data 0.002 (0.003) Loss 0.0329 (0.0300) Prec@1 95.000 (94.978) Prec@5 100.000 (99.783) +2022-11-14 16:37:13,702 Epoch: [363][460/500] Time 0.042 (0.051) Data 0.002 (0.003) Loss 0.0351 (0.0301) Prec@1 92.000 (94.915) Prec@5 100.000 (99.787) +2022-11-14 16:37:14,308 Epoch: [363][470/500] Time 0.060 (0.051) Data 0.003 (0.003) Loss 0.0545 (0.0306) Prec@1 91.000 (94.833) Prec@5 100.000 (99.792) +2022-11-14 16:37:14,939 Epoch: [363][480/500] Time 0.061 (0.051) Data 0.002 (0.003) Loss 0.0374 (0.0307) Prec@1 92.000 (94.776) Prec@5 100.000 (99.796) +2022-11-14 16:37:15,502 Epoch: [363][490/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0318 (0.0308) Prec@1 95.000 (94.780) Prec@5 100.000 (99.800) +2022-11-14 16:37:16,087 Epoch: [363][499/500] Time 0.060 (0.051) Data 0.002 (0.003) Loss 0.0431 (0.0310) Prec@1 92.000 (94.725) Prec@5 100.000 (99.804) +2022-11-14 16:37:16,439 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0753 (0.0753) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:37:16,450 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0551 (0.0652) Prec@1 91.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:37:16,462 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0682) Prec@1 87.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:37:16,476 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0658 (0.0676) Prec@1 91.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:37:16,487 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0538 (0.0648) Prec@1 91.000 (89.400) Prec@5 99.000 (99.600) +2022-11-14 16:37:16,501 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0467 (0.0618) Prec@1 94.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 16:37:16,517 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0619) Prec@1 92.000 (90.429) Prec@5 99.000 (99.571) +2022-11-14 16:37:16,530 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0651) Prec@1 86.000 (89.875) Prec@5 100.000 (99.625) +2022-11-14 16:37:16,546 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0922 (0.0681) Prec@1 88.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:37:16,565 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0691) Prec@1 90.000 (89.700) Prec@5 99.000 (99.600) +2022-11-14 16:37:16,583 Test: [10/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0694) Prec@1 89.000 (89.636) Prec@5 100.000 (99.636) +2022-11-14 16:37:16,599 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0700) Prec@1 86.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:37:16,615 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0637 (0.0695) Prec@1 89.000 (89.308) Prec@5 100.000 (99.692) +2022-11-14 16:37:16,633 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0693) Prec@1 88.000 (89.214) Prec@5 100.000 (99.714) +2022-11-14 16:37:16,656 Test: [14/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0699) Prec@1 88.000 (89.133) Prec@5 99.000 (99.667) +2022-11-14 16:37:16,673 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0703) Prec@1 88.000 (89.062) Prec@5 99.000 (99.625) +2022-11-14 16:37:16,693 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0423 (0.0686) Prec@1 94.000 (89.353) Prec@5 98.000 (99.529) +2022-11-14 16:37:16,711 Test: [17/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0964 (0.0702) Prec@1 85.000 (89.111) Prec@5 100.000 (99.556) +2022-11-14 16:37:16,730 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0702) Prec@1 88.000 (89.053) Prec@5 97.000 (99.421) +2022-11-14 16:37:16,751 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0706) Prec@1 89.000 (89.050) Prec@5 97.000 (99.300) +2022-11-14 16:37:16,769 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0703) Prec@1 89.000 (89.048) Prec@5 99.000 (99.286) +2022-11-14 16:37:16,788 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0711) Prec@1 87.000 (88.955) Prec@5 98.000 (99.227) +2022-11-14 16:37:16,804 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0724) Prec@1 83.000 (88.696) Prec@5 99.000 (99.217) +2022-11-14 16:37:16,822 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0727) Prec@1 88.000 (88.667) Prec@5 99.000 (99.208) +2022-11-14 16:37:16,843 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0733) Prec@1 86.000 (88.560) Prec@5 100.000 (99.240) +2022-11-14 16:37:16,861 Test: [25/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0736) Prec@1 89.000 (88.577) Prec@5 98.000 (99.192) +2022-11-14 16:37:16,882 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0730) Prec@1 91.000 (88.667) Prec@5 100.000 (99.222) +2022-11-14 16:37:16,900 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0726) Prec@1 90.000 (88.714) Prec@5 100.000 (99.250) +2022-11-14 16:37:16,919 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0424 (0.0716) Prec@1 94.000 (88.897) Prec@5 99.000 (99.241) +2022-11-14 16:37:16,936 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0712) Prec@1 90.000 (88.933) Prec@5 100.000 (99.267) +2022-11-14 16:37:16,954 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0712) Prec@1 89.000 (88.935) Prec@5 99.000 (99.258) +2022-11-14 16:37:16,975 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0708) Prec@1 93.000 (89.062) Prec@5 99.000 (99.250) +2022-11-14 16:37:16,995 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0707) Prec@1 88.000 (89.030) Prec@5 99.000 (99.242) +2022-11-14 16:37:17,012 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0660 (0.0705) Prec@1 90.000 (89.059) Prec@5 100.000 (99.265) +2022-11-14 16:37:17,030 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0707) Prec@1 88.000 (89.029) Prec@5 98.000 (99.229) +2022-11-14 16:37:17,050 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0706) Prec@1 88.000 (89.000) Prec@5 100.000 (99.250) +2022-11-14 16:37:17,075 Test: [36/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0703) Prec@1 90.000 (89.027) Prec@5 99.000 (99.243) +2022-11-14 16:37:17,094 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0972 (0.0710) Prec@1 84.000 (88.895) Prec@5 99.000 (99.237) +2022-11-14 16:37:17,114 Test: [38/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0707) Prec@1 93.000 (89.000) Prec@5 99.000 (99.231) +2022-11-14 16:37:17,135 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0708) Prec@1 89.000 (89.000) Prec@5 100.000 (99.250) +2022-11-14 16:37:17,153 Test: [40/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0716) Prec@1 83.000 (88.854) Prec@5 98.000 (99.220) +2022-11-14 16:37:17,173 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0717) Prec@1 88.000 (88.833) Prec@5 99.000 (99.214) +2022-11-14 16:37:17,190 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0711) Prec@1 92.000 (88.907) Prec@5 99.000 (99.209) +2022-11-14 16:37:17,207 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0708) Prec@1 93.000 (89.000) Prec@5 99.000 (99.205) +2022-11-14 16:37:17,227 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0707) Prec@1 90.000 (89.022) Prec@5 98.000 (99.178) +2022-11-14 16:37:17,245 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0714) Prec@1 83.000 (88.891) Prec@5 99.000 (99.174) +2022-11-14 16:37:17,266 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0709) Prec@1 94.000 (89.000) Prec@5 100.000 (99.191) +2022-11-14 16:37:17,286 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0716) Prec@1 85.000 (88.917) Prec@5 97.000 (99.146) +2022-11-14 16:37:17,302 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0713) Prec@1 91.000 (88.959) Prec@5 100.000 (99.163) +2022-11-14 16:37:17,322 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1017 (0.0719) Prec@1 83.000 (88.840) Prec@5 99.000 (99.160) +2022-11-14 16:37:17,342 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0716) Prec@1 89.000 (88.843) Prec@5 100.000 (99.176) +2022-11-14 16:37:17,360 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0716) Prec@1 89.000 (88.846) Prec@5 100.000 (99.192) +2022-11-14 16:37:17,379 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0714) Prec@1 90.000 (88.868) Prec@5 99.000 (99.189) +2022-11-14 16:37:17,402 Test: [53/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0713) Prec@1 89.000 (88.870) Prec@5 100.000 (99.204) +2022-11-14 16:37:17,421 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0717) Prec@1 85.000 (88.800) Prec@5 100.000 (99.218) +2022-11-14 16:37:17,441 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0717) Prec@1 89.000 (88.804) Prec@5 99.000 (99.214) +2022-11-14 16:37:17,462 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0715) Prec@1 89.000 (88.807) Prec@5 100.000 (99.228) +2022-11-14 16:37:17,480 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0717) Prec@1 88.000 (88.793) Prec@5 99.000 (99.224) +2022-11-14 16:37:17,498 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0718) Prec@1 84.000 (88.712) Prec@5 100.000 (99.237) +2022-11-14 16:37:17,517 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0716) Prec@1 90.000 (88.733) Prec@5 100.000 (99.250) +2022-11-14 16:37:17,535 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0718) Prec@1 88.000 (88.721) Prec@5 98.000 (99.230) +2022-11-14 16:37:17,557 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0716) Prec@1 90.000 (88.742) Prec@5 98.000 (99.210) +2022-11-14 16:37:17,578 Test: [62/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0716) Prec@1 89.000 (88.746) Prec@5 99.000 (99.206) +2022-11-14 16:37:17,597 Test: [63/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0355 (0.0710) Prec@1 95.000 (88.844) Prec@5 99.000 (99.203) +2022-11-14 16:37:17,615 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1214 (0.0718) Prec@1 80.000 (88.708) Prec@5 99.000 (99.200) +2022-11-14 16:37:17,636 Test: [65/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0719) Prec@1 85.000 (88.652) Prec@5 98.000 (99.182) +2022-11-14 16:37:17,655 Test: [66/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0520 (0.0716) Prec@1 92.000 (88.701) Prec@5 99.000 (99.179) +2022-11-14 16:37:17,676 Test: [67/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0642 (0.0715) Prec@1 90.000 (88.721) Prec@5 99.000 (99.176) +2022-11-14 16:37:17,697 Test: [68/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0715) Prec@1 88.000 (88.710) Prec@5 100.000 (99.188) +2022-11-14 16:37:17,716 Test: [69/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0833 (0.0717) Prec@1 85.000 (88.657) Prec@5 98.000 (99.171) +2022-11-14 16:37:17,733 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0930 (0.0720) Prec@1 85.000 (88.606) Prec@5 100.000 (99.183) +2022-11-14 16:37:17,752 Test: [71/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0500 (0.0717) Prec@1 92.000 (88.653) Prec@5 100.000 (99.194) +2022-11-14 16:37:17,774 Test: [72/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0453 (0.0713) Prec@1 93.000 (88.712) Prec@5 99.000 (99.192) +2022-11-14 16:37:17,793 Test: [73/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0711) Prec@1 90.000 (88.730) Prec@5 100.000 (99.203) +2022-11-14 16:37:17,817 Test: [74/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1050 (0.0715) Prec@1 84.000 (88.667) Prec@5 99.000 (99.200) +2022-11-14 16:37:17,838 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0630 (0.0714) Prec@1 90.000 (88.684) Prec@5 99.000 (99.197) +2022-11-14 16:37:17,861 Test: [76/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0714) Prec@1 90.000 (88.701) Prec@5 97.000 (99.169) +2022-11-14 16:37:17,885 Test: [77/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0716) Prec@1 87.000 (88.679) Prec@5 99.000 (99.167) +2022-11-14 16:37:17,906 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0716) Prec@1 88.000 (88.671) Prec@5 100.000 (99.177) +2022-11-14 16:37:17,930 Test: [79/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0718) Prec@1 86.000 (88.638) Prec@5 100.000 (99.188) +2022-11-14 16:37:17,951 Test: [80/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0719) Prec@1 88.000 (88.630) Prec@5 99.000 (99.185) +2022-11-14 16:37:17,974 Test: [81/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0719) Prec@1 90.000 (88.646) Prec@5 99.000 (99.183) +2022-11-14 16:37:17,990 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0719) Prec@1 89.000 (88.651) Prec@5 98.000 (99.169) +2022-11-14 16:37:18,010 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0541 (0.0717) Prec@1 90.000 (88.667) Prec@5 99.000 (99.167) +2022-11-14 16:37:18,030 Test: [84/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.1009 (0.0720) Prec@1 82.000 (88.588) Prec@5 100.000 (99.176) +2022-11-14 16:37:18,051 Test: [85/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.1057 (0.0724) Prec@1 83.000 (88.523) Prec@5 100.000 (99.186) +2022-11-14 16:37:18,068 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0520 (0.0722) Prec@1 92.000 (88.563) Prec@5 99.000 (99.184) +2022-11-14 16:37:18,089 Test: [87/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0698 (0.0722) Prec@1 90.000 (88.580) Prec@5 98.000 (99.170) +2022-11-14 16:37:18,107 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0721) Prec@1 90.000 (88.596) Prec@5 99.000 (99.169) +2022-11-14 16:37:18,124 Test: [89/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0722) Prec@1 89.000 (88.600) Prec@5 100.000 (99.178) +2022-11-14 16:37:18,143 Test: [90/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0492 (0.0719) Prec@1 93.000 (88.648) Prec@5 100.000 (99.187) +2022-11-14 16:37:18,164 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0718) Prec@1 90.000 (88.663) Prec@5 100.000 (99.196) +2022-11-14 16:37:18,189 Test: [92/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0885 (0.0720) Prec@1 85.000 (88.624) Prec@5 100.000 (99.204) +2022-11-14 16:37:18,211 Test: [93/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0626 (0.0719) Prec@1 92.000 (88.660) Prec@5 99.000 (99.202) +2022-11-14 16:37:18,230 Test: [94/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0721) Prec@1 83.000 (88.600) Prec@5 99.000 (99.200) +2022-11-14 16:37:18,252 Test: [95/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0635 (0.0720) Prec@1 89.000 (88.604) Prec@5 99.000 (99.198) +2022-11-14 16:37:18,275 Test: [96/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0452 (0.0717) Prec@1 90.000 (88.619) Prec@5 99.000 (99.196) +2022-11-14 16:37:18,300 Test: [97/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0718) Prec@1 87.000 (88.602) Prec@5 99.000 (99.194) +2022-11-14 16:37:18,324 Test: [98/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0934 (0.0720) Prec@1 86.000 (88.576) Prec@5 99.000 (99.192) +2022-11-14 16:37:18,347 Test: [99/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0719) Prec@1 92.000 (88.610) Prec@5 99.000 (99.190) +2022-11-14 16:37:18,432 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:37:18,845 Epoch: [364][0/500] Time 0.023 (0.023) Data 0.305 (0.305) Loss 0.0421 (0.0421) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:37:19,391 Epoch: [364][10/500] Time 0.054 (0.046) Data 0.002 (0.029) Loss 0.0396 (0.0408) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:37:19,973 Epoch: [364][20/500] Time 0.043 (0.049) Data 0.002 (0.017) Loss 0.0312 (0.0376) Prec@1 96.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 16:37:20,587 Epoch: [364][30/500] Time 0.060 (0.051) Data 0.002 (0.012) Loss 0.0344 (0.0368) Prec@1 93.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 16:37:21,216 Epoch: [364][40/500] Time 0.066 (0.052) Data 0.002 (0.010) Loss 0.0266 (0.0348) Prec@1 94.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:37:21,897 Epoch: [364][50/500] Time 0.069 (0.054) Data 0.002 (0.008) Loss 0.0365 (0.0351) Prec@1 93.000 (94.167) Prec@5 100.000 (99.833) +2022-11-14 16:37:22,542 Epoch: [364][60/500] Time 0.054 (0.055) Data 0.002 (0.007) Loss 0.0229 (0.0333) Prec@1 96.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 16:37:23,163 Epoch: [364][70/500] Time 0.055 (0.055) Data 0.002 (0.006) Loss 0.0274 (0.0326) Prec@1 96.000 (94.625) Prec@5 99.000 (99.750) +2022-11-14 16:37:23,730 Epoch: [364][80/500] Time 0.054 (0.054) Data 0.002 (0.006) Loss 0.0173 (0.0309) Prec@1 98.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 16:37:24,321 Epoch: [364][90/500] Time 0.062 (0.054) Data 0.002 (0.005) Loss 0.0402 (0.0318) Prec@1 92.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 16:37:24,880 Epoch: [364][100/500] Time 0.054 (0.054) Data 0.002 (0.005) Loss 0.0190 (0.0306) Prec@1 96.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:37:25,425 Epoch: [364][110/500] Time 0.053 (0.053) Data 0.002 (0.005) Loss 0.0508 (0.0323) Prec@1 92.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 16:37:26,000 Epoch: [364][120/500] Time 0.059 (0.053) Data 0.002 (0.005) Loss 0.0180 (0.0312) Prec@1 96.000 (94.692) Prec@5 100.000 (99.846) +2022-11-14 16:37:26,593 Epoch: [364][130/500] Time 0.060 (0.053) Data 0.002 (0.004) Loss 0.0215 (0.0305) Prec@1 96.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 16:37:27,154 Epoch: [364][140/500] Time 0.055 (0.053) Data 0.002 (0.004) Loss 0.0195 (0.0298) Prec@1 97.000 (94.933) Prec@5 100.000 (99.867) +2022-11-14 16:37:27,724 Epoch: [364][150/500] Time 0.052 (0.053) Data 0.002 (0.004) Loss 0.0156 (0.0289) Prec@1 98.000 (95.125) Prec@5 99.000 (99.812) +2022-11-14 16:37:28,362 Epoch: [364][160/500] Time 0.065 (0.053) Data 0.002 (0.004) Loss 0.0557 (0.0305) Prec@1 91.000 (94.882) Prec@5 99.000 (99.765) +2022-11-14 16:37:29,001 Epoch: [364][170/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0189 (0.0298) Prec@1 99.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:37:29,604 Epoch: [364][180/500] Time 0.056 (0.053) Data 0.002 (0.004) Loss 0.0211 (0.0294) Prec@1 98.000 (95.263) Prec@5 100.000 (99.789) +2022-11-14 16:37:30,198 Epoch: [364][190/500] Time 0.052 (0.053) Data 0.002 (0.004) Loss 0.0396 (0.0299) Prec@1 92.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 16:37:30,824 Epoch: [364][200/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0252 (0.0297) Prec@1 97.000 (95.190) Prec@5 100.000 (99.810) +2022-11-14 16:37:31,438 Epoch: [364][210/500] Time 0.063 (0.054) Data 0.002 (0.004) Loss 0.0491 (0.0305) Prec@1 93.000 (95.091) Prec@5 99.000 (99.773) +2022-11-14 16:37:32,007 Epoch: [364][220/500] Time 0.052 (0.053) Data 0.003 (0.004) Loss 0.0293 (0.0305) Prec@1 95.000 (95.087) Prec@5 100.000 (99.783) +2022-11-14 16:37:32,631 Epoch: [364][230/500] Time 0.074 (0.054) Data 0.002 (0.003) Loss 0.0294 (0.0304) Prec@1 97.000 (95.167) Prec@5 100.000 (99.792) +2022-11-14 16:37:33,188 Epoch: [364][240/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0558 (0.0315) Prec@1 91.000 (95.000) Prec@5 99.000 (99.760) +2022-11-14 16:37:33,785 Epoch: [364][250/500] Time 0.066 (0.053) Data 0.002 (0.003) Loss 0.0216 (0.0311) Prec@1 97.000 (95.077) Prec@5 100.000 (99.769) +2022-11-14 16:37:34,333 Epoch: [364][260/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0401 (0.0314) Prec@1 92.000 (94.963) Prec@5 98.000 (99.704) +2022-11-14 16:37:34,897 Epoch: [364][270/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0308 (0.0314) Prec@1 96.000 (95.000) Prec@5 100.000 (99.714) +2022-11-14 16:37:35,483 Epoch: [364][280/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0342 (0.0315) Prec@1 94.000 (94.966) Prec@5 100.000 (99.724) +2022-11-14 16:37:36,059 Epoch: [364][290/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0367 (0.0317) Prec@1 93.000 (94.900) Prec@5 100.000 (99.733) +2022-11-14 16:37:36,629 Epoch: [364][300/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0360 (0.0318) Prec@1 93.000 (94.839) Prec@5 100.000 (99.742) +2022-11-14 16:37:37,188 Epoch: [364][310/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0420 (0.0321) Prec@1 93.000 (94.781) Prec@5 100.000 (99.750) +2022-11-14 16:37:37,751 Epoch: [364][320/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0367 (0.0323) Prec@1 95.000 (94.788) Prec@5 100.000 (99.758) +2022-11-14 16:37:38,349 Epoch: [364][330/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0217 (0.0320) Prec@1 96.000 (94.824) Prec@5 100.000 (99.765) +2022-11-14 16:37:38,917 Epoch: [364][340/500] Time 0.049 (0.053) Data 0.002 (0.003) Loss 0.0321 (0.0320) Prec@1 95.000 (94.829) Prec@5 100.000 (99.771) +2022-11-14 16:37:39,522 Epoch: [364][350/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0326 (0.0320) Prec@1 96.000 (94.861) Prec@5 100.000 (99.778) +2022-11-14 16:37:40,124 Epoch: [364][360/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0216 (0.0317) Prec@1 97.000 (94.919) Prec@5 100.000 (99.784) +2022-11-14 16:37:40,742 Epoch: [364][370/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0365 (0.0318) Prec@1 95.000 (94.921) Prec@5 100.000 (99.789) +2022-11-14 16:37:41,317 Epoch: [364][380/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0277 (0.0317) Prec@1 96.000 (94.949) Prec@5 100.000 (99.795) +2022-11-14 16:37:41,887 Epoch: [364][390/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0145 (0.0313) Prec@1 99.000 (95.050) Prec@5 100.000 (99.800) +2022-11-14 16:37:42,505 Epoch: [364][400/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0326 (0.0313) Prec@1 95.000 (95.049) Prec@5 100.000 (99.805) +2022-11-14 16:37:43,083 Epoch: [364][410/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0280 (0.0312) Prec@1 96.000 (95.071) Prec@5 100.000 (99.810) +2022-11-14 16:37:43,671 Epoch: [364][420/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0279 (0.0312) Prec@1 97.000 (95.116) Prec@5 99.000 (99.791) +2022-11-14 16:37:44,227 Epoch: [364][430/500] Time 0.037 (0.053) Data 0.003 (0.003) Loss 0.0220 (0.0309) Prec@1 98.000 (95.182) Prec@5 100.000 (99.795) +2022-11-14 16:37:44,781 Epoch: [364][440/500] Time 0.049 (0.053) Data 0.002 (0.003) Loss 0.0147 (0.0306) Prec@1 98.000 (95.244) Prec@5 100.000 (99.800) +2022-11-14 16:37:45,374 Epoch: [364][450/500] Time 0.061 (0.053) Data 0.003 (0.003) Loss 0.0352 (0.0307) Prec@1 94.000 (95.217) Prec@5 99.000 (99.783) +2022-11-14 16:37:45,959 Epoch: [364][460/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0278 (0.0306) Prec@1 96.000 (95.234) Prec@5 100.000 (99.787) +2022-11-14 16:37:46,523 Epoch: [364][470/500] Time 0.057 (0.053) Data 0.003 (0.003) Loss 0.0281 (0.0306) Prec@1 96.000 (95.250) Prec@5 100.000 (99.792) +2022-11-14 16:37:47,098 Epoch: [364][480/500] Time 0.049 (0.053) Data 0.003 (0.003) Loss 0.0514 (0.0310) Prec@1 92.000 (95.184) Prec@5 99.000 (99.776) +2022-11-14 16:37:47,687 Epoch: [364][490/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0319 (0.0310) Prec@1 95.000 (95.180) Prec@5 100.000 (99.780) +2022-11-14 16:37:48,178 Epoch: [364][499/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0289 (0.0310) Prec@1 95.000 (95.176) Prec@5 100.000 (99.784) +2022-11-14 16:37:48,509 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0647 (0.0647) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:37:48,517 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0543 (0.0595) Prec@1 90.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:37:48,525 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0641) Prec@1 87.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:37:48,539 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0657) Prec@1 88.000 (88.500) Prec@5 98.000 (99.250) +2022-11-14 16:37:48,549 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0656) Prec@1 91.000 (89.000) Prec@5 98.000 (99.000) +2022-11-14 16:37:48,559 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0623) Prec@1 93.000 (89.667) Prec@5 100.000 (99.167) +2022-11-14 16:37:48,572 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0611) Prec@1 92.000 (90.000) Prec@5 100.000 (99.286) +2022-11-14 16:37:48,587 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0636) Prec@1 86.000 (89.500) Prec@5 100.000 (99.375) +2022-11-14 16:37:48,602 Test: [8/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0652) Prec@1 87.000 (89.222) Prec@5 98.000 (99.222) +2022-11-14 16:37:48,620 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0664) Prec@1 88.000 (89.100) Prec@5 99.000 (99.200) +2022-11-14 16:37:48,639 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0653) Prec@1 91.000 (89.273) Prec@5 99.000 (99.182) +2022-11-14 16:37:48,654 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0674) Prec@1 86.000 (89.000) Prec@5 100.000 (99.250) +2022-11-14 16:37:48,670 Test: [12/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0672) Prec@1 88.000 (88.923) Prec@5 100.000 (99.308) +2022-11-14 16:37:48,685 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0678) Prec@1 88.000 (88.857) Prec@5 99.000 (99.286) +2022-11-14 16:37:48,703 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0682) Prec@1 89.000 (88.867) Prec@5 100.000 (99.333) +2022-11-14 16:37:48,718 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0680) Prec@1 88.000 (88.812) Prec@5 100.000 (99.375) +2022-11-14 16:37:48,738 Test: [16/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0668) Prec@1 91.000 (88.941) Prec@5 98.000 (99.294) +2022-11-14 16:37:48,759 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0685) Prec@1 84.000 (88.667) Prec@5 99.000 (99.278) +2022-11-14 16:37:48,776 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0697) Prec@1 84.000 (88.421) Prec@5 98.000 (99.211) +2022-11-14 16:37:48,795 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0707) Prec@1 86.000 (88.300) Prec@5 98.000 (99.150) +2022-11-14 16:37:48,812 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0709) Prec@1 86.000 (88.190) Prec@5 100.000 (99.190) +2022-11-14 16:37:48,829 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0711) Prec@1 88.000 (88.182) Prec@5 99.000 (99.182) +2022-11-14 16:37:48,847 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0720) Prec@1 86.000 (88.087) Prec@5 99.000 (99.174) +2022-11-14 16:37:48,868 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0716) Prec@1 91.000 (88.208) Prec@5 100.000 (99.208) +2022-11-14 16:37:48,887 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0722) Prec@1 86.000 (88.120) Prec@5 100.000 (99.240) +2022-11-14 16:37:48,905 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0731) Prec@1 84.000 (87.962) Prec@5 99.000 (99.231) +2022-11-14 16:37:48,922 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0507 (0.0723) Prec@1 91.000 (88.074) Prec@5 100.000 (99.259) +2022-11-14 16:37:48,941 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0549 (0.0717) Prec@1 90.000 (88.143) Prec@5 100.000 (99.286) +2022-11-14 16:37:48,960 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0714) Prec@1 88.000 (88.138) Prec@5 98.000 (99.241) +2022-11-14 16:37:48,979 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0710) Prec@1 89.000 (88.167) Prec@5 100.000 (99.267) +2022-11-14 16:37:49,001 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0707) Prec@1 89.000 (88.194) Prec@5 99.000 (99.258) +2022-11-14 16:37:49,022 Test: [31/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0711) Prec@1 86.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 16:37:49,043 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0712) Prec@1 87.000 (88.091) Prec@5 100.000 (99.273) +2022-11-14 16:37:49,066 Test: [33/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0715) Prec@1 86.000 (88.029) Prec@5 100.000 (99.294) +2022-11-14 16:37:49,082 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0713) Prec@1 88.000 (88.029) Prec@5 99.000 (99.286) +2022-11-14 16:37:49,099 Test: [35/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0709) Prec@1 92.000 (88.139) Prec@5 98.000 (99.250) +2022-11-14 16:37:49,116 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0711) Prec@1 88.000 (88.135) Prec@5 98.000 (99.216) +2022-11-14 16:37:49,135 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0718) Prec@1 82.000 (87.974) Prec@5 98.000 (99.184) +2022-11-14 16:37:49,156 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0585 (0.0715) Prec@1 93.000 (88.103) Prec@5 100.000 (99.205) +2022-11-14 16:37:49,172 Test: [39/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0715) Prec@1 87.000 (88.075) Prec@5 100.000 (99.225) +2022-11-14 16:37:49,191 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0723) Prec@1 84.000 (87.976) Prec@5 97.000 (99.171) +2022-11-14 16:37:49,209 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0720) Prec@1 89.000 (88.000) Prec@5 99.000 (99.167) +2022-11-14 16:37:49,230 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0715) Prec@1 91.000 (88.070) Prec@5 99.000 (99.163) +2022-11-14 16:37:49,250 Test: [43/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0712) Prec@1 90.000 (88.114) Prec@5 99.000 (99.159) +2022-11-14 16:37:49,270 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0705) Prec@1 93.000 (88.222) Prec@5 100.000 (99.178) +2022-11-14 16:37:49,288 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0713) Prec@1 84.000 (88.130) Prec@5 100.000 (99.196) +2022-11-14 16:37:49,308 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0614 (0.0711) Prec@1 88.000 (88.128) Prec@5 100.000 (99.213) +2022-11-14 16:37:49,327 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0718) Prec@1 84.000 (88.042) Prec@5 96.000 (99.146) +2022-11-14 16:37:49,348 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0718) Prec@1 85.000 (87.980) Prec@5 100.000 (99.163) +2022-11-14 16:37:49,368 Test: [49/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0724) Prec@1 86.000 (87.940) Prec@5 100.000 (99.180) +2022-11-14 16:37:49,386 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0687 (0.0724) Prec@1 88.000 (87.941) Prec@5 100.000 (99.196) +2022-11-14 16:37:49,408 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0724) Prec@1 89.000 (87.962) Prec@5 99.000 (99.192) +2022-11-14 16:37:49,426 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0721) Prec@1 90.000 (88.000) Prec@5 100.000 (99.208) +2022-11-14 16:37:49,444 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0721) Prec@1 89.000 (88.019) Prec@5 100.000 (99.222) +2022-11-14 16:37:49,464 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0723) Prec@1 83.000 (87.927) Prec@5 100.000 (99.236) +2022-11-14 16:37:49,485 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0724) Prec@1 87.000 (87.911) Prec@5 99.000 (99.232) +2022-11-14 16:37:49,504 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0723) Prec@1 90.000 (87.947) Prec@5 100.000 (99.246) +2022-11-14 16:37:49,522 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0723) Prec@1 90.000 (87.983) Prec@5 100.000 (99.259) +2022-11-14 16:37:49,541 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0728) Prec@1 85.000 (87.932) Prec@5 99.000 (99.254) +2022-11-14 16:37:49,561 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0729) Prec@1 88.000 (87.933) Prec@5 99.000 (99.250) +2022-11-14 16:37:49,579 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0728) Prec@1 90.000 (87.967) Prec@5 99.000 (99.246) +2022-11-14 16:37:49,598 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0728) Prec@1 86.000 (87.935) Prec@5 99.000 (99.242) +2022-11-14 16:37:49,619 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0728) Prec@1 88.000 (87.937) Prec@5 100.000 (99.254) +2022-11-14 16:37:49,639 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0725) Prec@1 92.000 (88.000) Prec@5 99.000 (99.250) +2022-11-14 16:37:49,658 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1054 (0.0730) Prec@1 85.000 (87.954) Prec@5 99.000 (99.246) +2022-11-14 16:37:49,675 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0728) Prec@1 88.000 (87.955) Prec@5 100.000 (99.258) +2022-11-14 16:37:49,695 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0403 (0.0723) Prec@1 94.000 (88.045) Prec@5 99.000 (99.254) +2022-11-14 16:37:49,717 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0724) Prec@1 90.000 (88.074) Prec@5 99.000 (99.250) +2022-11-14 16:37:49,735 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0726) Prec@1 84.000 (88.014) Prec@5 99.000 (99.246) +2022-11-14 16:37:49,753 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0725) Prec@1 89.000 (88.029) Prec@5 99.000 (99.243) +2022-11-14 16:37:49,770 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1080 (0.0730) Prec@1 85.000 (87.986) Prec@5 98.000 (99.225) +2022-11-14 16:37:49,786 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0729) Prec@1 88.000 (87.986) Prec@5 100.000 (99.236) +2022-11-14 16:37:49,805 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0321 (0.0723) Prec@1 96.000 (88.096) Prec@5 100.000 (99.247) +2022-11-14 16:37:49,825 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0722) Prec@1 90.000 (88.122) Prec@5 99.000 (99.243) +2022-11-14 16:37:49,843 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0725) Prec@1 83.000 (88.053) Prec@5 99.000 (99.240) +2022-11-14 16:37:49,862 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0724) Prec@1 90.000 (88.079) Prec@5 100.000 (99.250) +2022-11-14 16:37:49,883 Test: [76/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0560 (0.0722) Prec@1 89.000 (88.091) Prec@5 99.000 (99.247) +2022-11-14 16:37:49,904 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0722) Prec@1 89.000 (88.103) Prec@5 100.000 (99.256) +2022-11-14 16:37:49,921 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0724) Prec@1 87.000 (88.089) Prec@5 99.000 (99.253) +2022-11-14 16:37:49,941 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0724) Prec@1 87.000 (88.075) Prec@5 98.000 (99.237) +2022-11-14 16:37:49,961 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0725) Prec@1 86.000 (88.049) Prec@5 99.000 (99.235) +2022-11-14 16:37:49,980 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0725) Prec@1 87.000 (88.037) Prec@5 100.000 (99.244) +2022-11-14 16:37:50,001 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0726) Prec@1 87.000 (88.024) Prec@5 98.000 (99.229) +2022-11-14 16:37:50,020 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0726) Prec@1 87.000 (88.012) Prec@5 100.000 (99.238) +2022-11-14 16:37:50,037 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0729) Prec@1 86.000 (87.988) Prec@5 99.000 (99.235) +2022-11-14 16:37:50,056 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0731) Prec@1 86.000 (87.965) Prec@5 99.000 (99.233) +2022-11-14 16:37:50,076 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0730) Prec@1 91.000 (88.000) Prec@5 100.000 (99.241) +2022-11-14 16:37:50,093 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0729) Prec@1 87.000 (87.989) Prec@5 100.000 (99.250) +2022-11-14 16:37:50,111 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0728) Prec@1 92.000 (88.034) Prec@5 99.000 (99.247) +2022-11-14 16:37:50,131 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0728) Prec@1 89.000 (88.044) Prec@5 99.000 (99.244) +2022-11-14 16:37:50,152 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0725) Prec@1 91.000 (88.077) Prec@5 100.000 (99.253) +2022-11-14 16:37:50,170 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0462 (0.0722) Prec@1 94.000 (88.141) Prec@5 100.000 (99.261) +2022-11-14 16:37:50,188 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0724) Prec@1 88.000 (88.140) Prec@5 100.000 (99.269) +2022-11-14 16:37:50,207 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0723) Prec@1 88.000 (88.138) Prec@5 100.000 (99.277) +2022-11-14 16:37:50,226 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0976 (0.0726) Prec@1 83.000 (88.084) Prec@5 100.000 (99.284) +2022-11-14 16:37:50,243 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0607 (0.0725) Prec@1 91.000 (88.115) Prec@5 100.000 (99.292) +2022-11-14 16:37:50,262 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0470 (0.0722) Prec@1 93.000 (88.165) Prec@5 99.000 (99.289) +2022-11-14 16:37:50,278 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0925 (0.0724) Prec@1 87.000 (88.153) Prec@5 98.000 (99.276) +2022-11-14 16:37:50,294 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1064 (0.0728) Prec@1 82.000 (88.091) Prec@5 100.000 (99.283) +2022-11-14 16:37:50,312 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0727) Prec@1 90.000 (88.110) Prec@5 99.000 (99.280) +2022-11-14 16:37:50,393 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:37:50,757 Epoch: [365][0/500] Time 0.025 (0.025) Data 0.270 (0.270) Loss 0.0148 (0.0148) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:37:51,235 Epoch: [365][10/500] Time 0.051 (0.041) Data 0.002 (0.027) Loss 0.0122 (0.0135) Prec@1 97.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:37:51,801 Epoch: [365][20/500] Time 0.043 (0.045) Data 0.002 (0.015) Loss 0.0477 (0.0249) Prec@1 93.000 (96.000) Prec@5 99.000 (99.667) +2022-11-14 16:37:52,358 Epoch: [365][30/500] Time 0.052 (0.047) Data 0.002 (0.011) Loss 0.0343 (0.0272) Prec@1 94.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:37:52,914 Epoch: [365][40/500] Time 0.054 (0.047) Data 0.002 (0.009) Loss 0.0138 (0.0246) Prec@1 98.000 (96.000) Prec@5 99.000 (99.600) +2022-11-14 16:37:53,461 Epoch: [365][50/500] Time 0.051 (0.047) Data 0.002 (0.007) Loss 0.0367 (0.0266) Prec@1 95.000 (95.833) Prec@5 100.000 (99.667) +2022-11-14 16:37:54,035 Epoch: [365][60/500] Time 0.057 (0.048) Data 0.003 (0.006) Loss 0.0311 (0.0272) Prec@1 94.000 (95.571) Prec@5 100.000 (99.714) +2022-11-14 16:37:54,605 Epoch: [365][70/500] Time 0.070 (0.049) Data 0.002 (0.006) Loss 0.0303 (0.0276) Prec@1 96.000 (95.625) Prec@5 100.000 (99.750) +2022-11-14 16:37:55,154 Epoch: [365][80/500] Time 0.059 (0.049) Data 0.002 (0.005) Loss 0.0253 (0.0274) Prec@1 96.000 (95.667) Prec@5 100.000 (99.778) +2022-11-14 16:37:55,702 Epoch: [365][90/500] Time 0.046 (0.049) Data 0.002 (0.005) Loss 0.0293 (0.0276) Prec@1 95.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:37:56,253 Epoch: [365][100/500] Time 0.053 (0.049) Data 0.002 (0.005) Loss 0.0242 (0.0273) Prec@1 96.000 (95.636) Prec@5 100.000 (99.818) +2022-11-14 16:37:56,791 Epoch: [365][110/500] Time 0.057 (0.049) Data 0.002 (0.004) Loss 0.0255 (0.0271) Prec@1 94.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 16:37:57,339 Epoch: [365][120/500] Time 0.049 (0.049) Data 0.002 (0.004) Loss 0.0314 (0.0274) Prec@1 96.000 (95.538) Prec@5 100.000 (99.846) +2022-11-14 16:37:57,890 Epoch: [365][130/500] Time 0.052 (0.049) Data 0.002 (0.004) Loss 0.0478 (0.0289) Prec@1 91.000 (95.214) Prec@5 99.000 (99.786) +2022-11-14 16:37:58,453 Epoch: [365][140/500] Time 0.058 (0.049) Data 0.002 (0.004) Loss 0.0422 (0.0298) Prec@1 94.000 (95.133) Prec@5 100.000 (99.800) +2022-11-14 16:37:59,018 Epoch: [365][150/500] Time 0.058 (0.049) Data 0.002 (0.004) Loss 0.0179 (0.0290) Prec@1 97.000 (95.250) Prec@5 100.000 (99.812) +2022-11-14 16:37:59,547 Epoch: [365][160/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0272 (0.0289) Prec@1 97.000 (95.353) Prec@5 100.000 (99.824) +2022-11-14 16:38:00,109 Epoch: [365][170/500] Time 0.054 (0.049) Data 0.002 (0.004) Loss 0.0164 (0.0282) Prec@1 96.000 (95.389) Prec@5 100.000 (99.833) +2022-11-14 16:38:00,665 Epoch: [365][180/500] Time 0.050 (0.049) Data 0.003 (0.004) Loss 0.0313 (0.0284) Prec@1 92.000 (95.211) Prec@5 100.000 (99.842) +2022-11-14 16:38:01,215 Epoch: [365][190/500] Time 0.056 (0.049) Data 0.002 (0.003) Loss 0.0306 (0.0285) Prec@1 95.000 (95.200) Prec@5 100.000 (99.850) +2022-11-14 16:38:01,787 Epoch: [365][200/500] Time 0.047 (0.049) Data 0.002 (0.003) Loss 0.0374 (0.0289) Prec@1 96.000 (95.238) Prec@5 99.000 (99.810) +2022-11-14 16:38:02,325 Epoch: [365][210/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0419 (0.0295) Prec@1 93.000 (95.136) Prec@5 100.000 (99.818) +2022-11-14 16:38:02,869 Epoch: [365][220/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0357 (0.0298) Prec@1 94.000 (95.087) Prec@5 99.000 (99.783) +2022-11-14 16:38:03,410 Epoch: [365][230/500] Time 0.057 (0.049) Data 0.003 (0.003) Loss 0.0233 (0.0295) Prec@1 97.000 (95.167) Prec@5 100.000 (99.792) +2022-11-14 16:38:03,968 Epoch: [365][240/500] Time 0.064 (0.049) Data 0.002 (0.003) Loss 0.0301 (0.0295) Prec@1 94.000 (95.120) Prec@5 100.000 (99.800) +2022-11-14 16:38:04,539 Epoch: [365][250/500] Time 0.054 (0.049) Data 0.002 (0.003) Loss 0.0187 (0.0291) Prec@1 97.000 (95.192) Prec@5 100.000 (99.808) +2022-11-14 16:38:05,094 Epoch: [365][260/500] Time 0.045 (0.049) Data 0.002 (0.003) Loss 0.0475 (0.0298) Prec@1 92.000 (95.074) Prec@5 100.000 (99.815) +2022-11-14 16:38:05,664 Epoch: [365][270/500] Time 0.058 (0.049) Data 0.002 (0.003) Loss 0.0278 (0.0297) Prec@1 95.000 (95.071) Prec@5 100.000 (99.821) +2022-11-14 16:38:06,241 Epoch: [365][280/500] Time 0.037 (0.049) Data 0.002 (0.003) Loss 0.0356 (0.0299) Prec@1 93.000 (95.000) Prec@5 100.000 (99.828) +2022-11-14 16:38:06,799 Epoch: [365][290/500] Time 0.055 (0.049) Data 0.002 (0.003) Loss 0.0347 (0.0301) Prec@1 95.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:38:07,394 Epoch: [365][300/500] Time 0.050 (0.049) Data 0.002 (0.003) Loss 0.0371 (0.0303) Prec@1 94.000 (94.968) Prec@5 100.000 (99.839) +2022-11-14 16:38:07,971 Epoch: [365][310/500] Time 0.051 (0.049) Data 0.002 (0.003) Loss 0.0165 (0.0299) Prec@1 98.000 (95.062) Prec@5 100.000 (99.844) +2022-11-14 16:38:08,560 Epoch: [365][320/500] Time 0.061 (0.050) Data 0.002 (0.003) Loss 0.0314 (0.0299) Prec@1 96.000 (95.091) Prec@5 100.000 (99.848) +2022-11-14 16:38:09,167 Epoch: [365][330/500] Time 0.059 (0.050) Data 0.002 (0.003) Loss 0.0432 (0.0303) Prec@1 92.000 (95.000) Prec@5 100.000 (99.853) +2022-11-14 16:38:09,727 Epoch: [365][340/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0395 (0.0306) Prec@1 95.000 (95.000) Prec@5 99.000 (99.829) +2022-11-14 16:38:10,307 Epoch: [365][350/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0231 (0.0304) Prec@1 96.000 (95.028) Prec@5 100.000 (99.833) +2022-11-14 16:38:10,876 Epoch: [365][360/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0466 (0.0308) Prec@1 91.000 (94.919) Prec@5 100.000 (99.838) +2022-11-14 16:38:11,465 Epoch: [365][370/500] Time 0.066 (0.050) Data 0.002 (0.003) Loss 0.0342 (0.0309) Prec@1 92.000 (94.842) Prec@5 100.000 (99.842) +2022-11-14 16:38:12,018 Epoch: [365][380/500] Time 0.047 (0.050) Data 0.002 (0.003) Loss 0.0074 (0.0303) Prec@1 100.000 (94.974) Prec@5 100.000 (99.846) +2022-11-14 16:38:12,634 Epoch: [365][390/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0546 (0.0309) Prec@1 91.000 (94.875) Prec@5 100.000 (99.850) +2022-11-14 16:38:13,210 Epoch: [365][400/500] Time 0.040 (0.050) Data 0.003 (0.003) Loss 0.0625 (0.0317) Prec@1 91.000 (94.780) Prec@5 99.000 (99.829) +2022-11-14 16:38:13,782 Epoch: [365][410/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0212 (0.0314) Prec@1 96.000 (94.810) Prec@5 100.000 (99.833) +2022-11-14 16:38:14,342 Epoch: [365][420/500] Time 0.051 (0.050) Data 0.002 (0.003) Loss 0.0113 (0.0310) Prec@1 98.000 (94.884) Prec@5 100.000 (99.837) +2022-11-14 16:38:14,921 Epoch: [365][430/500] Time 0.056 (0.050) Data 0.002 (0.003) Loss 0.0261 (0.0309) Prec@1 95.000 (94.886) Prec@5 100.000 (99.841) +2022-11-14 16:38:15,501 Epoch: [365][440/500] Time 0.058 (0.050) Data 0.002 (0.003) Loss 0.0215 (0.0306) Prec@1 96.000 (94.911) Prec@5 100.000 (99.844) +2022-11-14 16:38:16,063 Epoch: [365][450/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0259 (0.0305) Prec@1 95.000 (94.913) Prec@5 100.000 (99.848) +2022-11-14 16:38:16,637 Epoch: [365][460/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0194 (0.0303) Prec@1 98.000 (94.979) Prec@5 100.000 (99.851) +2022-11-14 16:38:17,211 Epoch: [365][470/500] Time 0.057 (0.050) Data 0.002 (0.003) Loss 0.0324 (0.0303) Prec@1 96.000 (95.000) Prec@5 100.000 (99.854) +2022-11-14 16:38:17,778 Epoch: [365][480/500] Time 0.055 (0.050) Data 0.002 (0.003) Loss 0.0276 (0.0303) Prec@1 96.000 (95.020) Prec@5 99.000 (99.837) +2022-11-14 16:38:18,330 Epoch: [365][490/500] Time 0.052 (0.050) Data 0.002 (0.003) Loss 0.0307 (0.0303) Prec@1 96.000 (95.040) Prec@5 100.000 (99.840) +2022-11-14 16:38:18,830 Epoch: [365][499/500] Time 0.054 (0.050) Data 0.002 (0.003) Loss 0.0384 (0.0305) Prec@1 94.000 (95.020) Prec@5 99.000 (99.824) +2022-11-14 16:38:19,163 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0589 (0.0589) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:19,177 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0595 (0.0592) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:38:19,187 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0622 (0.0602) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:19,200 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0636 (0.0611) Prec@1 91.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 16:38:19,210 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0591 (0.0607) Prec@1 91.000 (89.800) Prec@5 99.000 (99.400) +2022-11-14 16:38:19,223 Test: [5/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0473 (0.0585) Prec@1 92.000 (90.167) Prec@5 100.000 (99.500) +2022-11-14 16:38:19,236 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0587) Prec@1 92.000 (90.429) Prec@5 99.000 (99.429) +2022-11-14 16:38:19,251 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0913 (0.0628) Prec@1 85.000 (89.750) Prec@5 97.000 (99.125) +2022-11-14 16:38:19,267 Test: [8/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0647) Prec@1 88.000 (89.556) Prec@5 99.000 (99.111) +2022-11-14 16:38:19,282 Test: [9/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0669) Prec@1 85.000 (89.100) Prec@5 98.000 (99.000) +2022-11-14 16:38:19,297 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0578 (0.0660) Prec@1 89.000 (89.091) Prec@5 99.000 (99.000) +2022-11-14 16:38:19,313 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0668) Prec@1 88.000 (89.000) Prec@5 100.000 (99.083) +2022-11-14 16:38:19,325 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0665) Prec@1 90.000 (89.077) Prec@5 100.000 (99.154) +2022-11-14 16:38:19,348 Test: [13/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0669) Prec@1 89.000 (89.071) Prec@5 100.000 (99.214) +2022-11-14 16:38:19,368 Test: [14/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0676) Prec@1 86.000 (88.867) Prec@5 100.000 (99.267) +2022-11-14 16:38:19,382 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0682) Prec@1 87.000 (88.750) Prec@5 100.000 (99.312) +2022-11-14 16:38:19,398 Test: [16/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0681) Prec@1 89.000 (88.765) Prec@5 98.000 (99.235) +2022-11-14 16:38:19,415 Test: [17/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0911 (0.0694) Prec@1 88.000 (88.722) Prec@5 98.000 (99.167) +2022-11-14 16:38:19,436 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0703) Prec@1 85.000 (88.526) Prec@5 99.000 (99.158) +2022-11-14 16:38:19,461 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.0711) Prec@1 86.000 (88.400) Prec@5 97.000 (99.050) +2022-11-14 16:38:19,482 Test: [20/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0710) Prec@1 88.000 (88.381) Prec@5 100.000 (99.095) +2022-11-14 16:38:19,507 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0811 (0.0714) Prec@1 87.000 (88.318) Prec@5 98.000 (99.045) +2022-11-14 16:38:19,531 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0954 (0.0725) Prec@1 85.000 (88.174) Prec@5 99.000 (99.043) +2022-11-14 16:38:19,553 Test: [23/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0707 (0.0724) Prec@1 91.000 (88.292) Prec@5 100.000 (99.083) +2022-11-14 16:38:19,573 Test: [24/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0990 (0.0735) Prec@1 84.000 (88.120) Prec@5 100.000 (99.120) +2022-11-14 16:38:19,587 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0737) Prec@1 87.000 (88.077) Prec@5 100.000 (99.154) +2022-11-14 16:38:19,607 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0733) Prec@1 90.000 (88.148) Prec@5 100.000 (99.185) +2022-11-14 16:38:19,625 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0463 (0.0723) Prec@1 93.000 (88.321) Prec@5 100.000 (99.214) +2022-11-14 16:38:19,643 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0721) Prec@1 89.000 (88.345) Prec@5 98.000 (99.172) +2022-11-14 16:38:19,663 Test: [29/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0723) Prec@1 88.000 (88.333) Prec@5 100.000 (99.200) +2022-11-14 16:38:19,679 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0649 (0.0721) Prec@1 87.000 (88.290) Prec@5 100.000 (99.226) +2022-11-14 16:38:19,697 Test: [31/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0858 (0.0725) Prec@1 87.000 (88.250) Prec@5 99.000 (99.219) +2022-11-14 16:38:19,718 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0708 (0.0724) Prec@1 87.000 (88.212) Prec@5 100.000 (99.242) +2022-11-14 16:38:19,735 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0729) Prec@1 86.000 (88.147) Prec@5 99.000 (99.235) +2022-11-14 16:38:19,752 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0734) Prec@1 86.000 (88.086) Prec@5 98.000 (99.200) +2022-11-14 16:38:19,771 Test: [35/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0807 (0.0736) Prec@1 88.000 (88.083) Prec@5 100.000 (99.222) +2022-11-14 16:38:19,789 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0736) Prec@1 88.000 (88.081) Prec@5 99.000 (99.216) +2022-11-14 16:38:19,808 Test: [37/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1036 (0.0743) Prec@1 82.000 (87.921) Prec@5 100.000 (99.237) +2022-11-14 16:38:19,828 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0572 (0.0739) Prec@1 92.000 (88.026) Prec@5 99.000 (99.231) +2022-11-14 16:38:19,847 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0741) Prec@1 87.000 (88.000) Prec@5 98.000 (99.200) +2022-11-14 16:38:19,869 Test: [40/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0744) Prec@1 88.000 (88.000) Prec@5 98.000 (99.171) +2022-11-14 16:38:19,886 Test: [41/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0743) Prec@1 89.000 (88.024) Prec@5 100.000 (99.190) +2022-11-14 16:38:19,902 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0739) Prec@1 91.000 (88.093) Prec@5 99.000 (99.186) +2022-11-14 16:38:19,919 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0623 (0.0736) Prec@1 91.000 (88.159) Prec@5 99.000 (99.182) +2022-11-14 16:38:19,937 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0495 (0.0731) Prec@1 91.000 (88.222) Prec@5 99.000 (99.178) +2022-11-14 16:38:19,958 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1126 (0.0739) Prec@1 81.000 (88.065) Prec@5 98.000 (99.152) +2022-11-14 16:38:19,976 Test: [46/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0739) Prec@1 87.000 (88.043) Prec@5 99.000 (99.149) +2022-11-14 16:38:19,995 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1071 (0.0746) Prec@1 82.000 (87.917) Prec@5 98.000 (99.125) +2022-11-14 16:38:20,014 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0384 (0.0738) Prec@1 91.000 (87.980) Prec@5 100.000 (99.143) +2022-11-14 16:38:20,034 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1019 (0.0744) Prec@1 86.000 (87.940) Prec@5 100.000 (99.160) +2022-11-14 16:38:20,053 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0740) Prec@1 91.000 (88.000) Prec@5 100.000 (99.176) +2022-11-14 16:38:20,071 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0588 (0.0738) Prec@1 91.000 (88.058) Prec@5 99.000 (99.173) +2022-11-14 16:38:20,088 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0740) Prec@1 85.000 (88.000) Prec@5 100.000 (99.189) +2022-11-14 16:38:20,106 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0740) Prec@1 89.000 (88.019) Prec@5 100.000 (99.204) +2022-11-14 16:38:20,126 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0959 (0.0744) Prec@1 84.000 (87.945) Prec@5 100.000 (99.218) +2022-11-14 16:38:20,146 Test: [55/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0503 (0.0739) Prec@1 94.000 (88.054) Prec@5 99.000 (99.214) +2022-11-14 16:38:20,167 Test: [56/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0739) Prec@1 89.000 (88.070) Prec@5 99.000 (99.211) +2022-11-14 16:38:20,188 Test: [57/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0768 (0.0740) Prec@1 88.000 (88.069) Prec@5 99.000 (99.207) +2022-11-14 16:38:20,209 Test: [58/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0742) Prec@1 87.000 (88.051) Prec@5 99.000 (99.203) +2022-11-14 16:38:20,230 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0646 (0.0740) Prec@1 87.000 (88.033) Prec@5 100.000 (99.217) +2022-11-14 16:38:20,249 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0741) Prec@1 90.000 (88.066) Prec@5 99.000 (99.213) +2022-11-14 16:38:20,267 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0740) Prec@1 87.000 (88.048) Prec@5 100.000 (99.226) +2022-11-14 16:38:20,284 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0740) Prec@1 87.000 (88.032) Prec@5 99.000 (99.222) +2022-11-14 16:38:20,304 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0491 (0.0736) Prec@1 91.000 (88.078) Prec@5 100.000 (99.234) +2022-11-14 16:38:20,322 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0737) Prec@1 89.000 (88.092) Prec@5 100.000 (99.246) +2022-11-14 16:38:20,344 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0735) Prec@1 89.000 (88.106) Prec@5 100.000 (99.258) +2022-11-14 16:38:20,362 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0406 (0.0730) Prec@1 94.000 (88.194) Prec@5 100.000 (99.269) +2022-11-14 16:38:20,382 Test: [67/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0668 (0.0730) Prec@1 88.000 (88.191) Prec@5 99.000 (99.265) +2022-11-14 16:38:20,401 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0730) Prec@1 90.000 (88.217) Prec@5 99.000 (99.261) +2022-11-14 16:38:20,424 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0731) Prec@1 88.000 (88.214) Prec@5 99.000 (99.257) +2022-11-14 16:38:20,445 Test: [70/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0888 (0.0733) Prec@1 86.000 (88.183) Prec@5 98.000 (99.239) +2022-11-14 16:38:20,465 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0733) Prec@1 89.000 (88.194) Prec@5 100.000 (99.250) +2022-11-14 16:38:20,486 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0399 (0.0728) Prec@1 93.000 (88.260) Prec@5 100.000 (99.260) +2022-11-14 16:38:20,502 Test: [73/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0383 (0.0723) Prec@1 95.000 (88.351) Prec@5 100.000 (99.270) +2022-11-14 16:38:20,520 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0850 (0.0725) Prec@1 85.000 (88.307) Prec@5 100.000 (99.280) +2022-11-14 16:38:20,539 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0725) Prec@1 89.000 (88.316) Prec@5 100.000 (99.289) +2022-11-14 16:38:20,562 Test: [76/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0591 (0.0723) Prec@1 90.000 (88.338) Prec@5 100.000 (99.299) +2022-11-14 16:38:20,580 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0867 (0.0725) Prec@1 86.000 (88.308) Prec@5 98.000 (99.282) +2022-11-14 16:38:20,598 Test: [78/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0727) Prec@1 85.000 (88.266) Prec@5 100.000 (99.291) +2022-11-14 16:38:20,619 Test: [79/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0727) Prec@1 86.000 (88.237) Prec@5 100.000 (99.300) +2022-11-14 16:38:20,641 Test: [80/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0785 (0.0727) Prec@1 86.000 (88.210) Prec@5 99.000 (99.296) +2022-11-14 16:38:20,662 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0854 (0.0729) Prec@1 85.000 (88.171) Prec@5 99.000 (99.293) +2022-11-14 16:38:20,681 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0730) Prec@1 86.000 (88.145) Prec@5 100.000 (99.301) +2022-11-14 16:38:20,700 Test: [83/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0729) Prec@1 93.000 (88.202) Prec@5 99.000 (99.298) +2022-11-14 16:38:20,717 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0784 (0.0729) Prec@1 87.000 (88.188) Prec@5 99.000 (99.294) +2022-11-14 16:38:20,735 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1066 (0.0733) Prec@1 83.000 (88.128) Prec@5 99.000 (99.291) +2022-11-14 16:38:20,753 Test: [86/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0733) Prec@1 89.000 (88.138) Prec@5 100.000 (99.299) +2022-11-14 16:38:20,773 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0734) Prec@1 88.000 (88.136) Prec@5 97.000 (99.273) +2022-11-14 16:38:20,793 Test: [88/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0575 (0.0732) Prec@1 90.000 (88.157) Prec@5 99.000 (99.270) +2022-11-14 16:38:20,811 Test: [89/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0732) Prec@1 90.000 (88.178) Prec@5 99.000 (99.267) +2022-11-14 16:38:20,832 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0503 (0.0729) Prec@1 92.000 (88.220) Prec@5 100.000 (99.275) +2022-11-14 16:38:20,853 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0460 (0.0726) Prec@1 95.000 (88.293) Prec@5 99.000 (99.272) +2022-11-14 16:38:20,870 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0727) Prec@1 86.000 (88.269) Prec@5 100.000 (99.280) +2022-11-14 16:38:20,887 Test: [93/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0729) Prec@1 87.000 (88.255) Prec@5 100.000 (99.287) +2022-11-14 16:38:20,904 Test: [94/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0782 (0.0729) Prec@1 88.000 (88.253) Prec@5 100.000 (99.295) +2022-11-14 16:38:20,923 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0729) Prec@1 87.000 (88.240) Prec@5 99.000 (99.292) +2022-11-14 16:38:20,941 Test: [96/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0542 (0.0727) Prec@1 92.000 (88.278) Prec@5 99.000 (99.289) +2022-11-14 16:38:20,959 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0907 (0.0729) Prec@1 87.000 (88.265) Prec@5 97.000 (99.265) +2022-11-14 16:38:20,979 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0798 (0.0730) Prec@1 90.000 (88.283) Prec@5 99.000 (99.263) +2022-11-14 16:38:21,001 Test: [99/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0608 (0.0729) Prec@1 90.000 (88.300) Prec@5 99.000 (99.260) +2022-11-14 16:38:21,065 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:38:21,436 Epoch: [366][0/500] Time 0.025 (0.025) Data 0.277 (0.277) Loss 0.0334 (0.0334) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:21,943 Epoch: [366][10/500] Time 0.060 (0.043) Data 0.002 (0.027) Loss 0.0176 (0.0255) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:22,508 Epoch: [366][20/500] Time 0.053 (0.047) Data 0.002 (0.015) Loss 0.0472 (0.0327) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:23,093 Epoch: [366][30/500] Time 0.056 (0.049) Data 0.002 (0.011) Loss 0.0226 (0.0302) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:38:23,658 Epoch: [366][40/500] Time 0.061 (0.049) Data 0.002 (0.009) Loss 0.0293 (0.0300) Prec@1 95.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:38:24,250 Epoch: [366][50/500] Time 0.057 (0.050) Data 0.003 (0.007) Loss 0.0587 (0.0348) Prec@1 92.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:38:24,848 Epoch: [366][60/500] Time 0.051 (0.051) Data 0.002 (0.007) Loss 0.0202 (0.0327) Prec@1 98.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:38:25,430 Epoch: [366][70/500] Time 0.060 (0.051) Data 0.003 (0.006) Loss 0.0545 (0.0354) Prec@1 93.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 16:38:26,022 Epoch: [366][80/500] Time 0.068 (0.051) Data 0.002 (0.005) Loss 0.0485 (0.0369) Prec@1 92.000 (94.556) Prec@5 100.000 (100.000) +2022-11-14 16:38:26,607 Epoch: [366][90/500] Time 0.058 (0.051) Data 0.002 (0.005) Loss 0.0408 (0.0373) Prec@1 92.000 (94.300) Prec@5 100.000 (100.000) +2022-11-14 16:38:27,179 Epoch: [366][100/500] Time 0.057 (0.051) Data 0.002 (0.005) Loss 0.0204 (0.0357) Prec@1 97.000 (94.545) Prec@5 99.000 (99.909) +2022-11-14 16:38:27,801 Epoch: [366][110/500] Time 0.068 (0.052) Data 0.002 (0.005) Loss 0.0232 (0.0347) Prec@1 96.000 (94.667) Prec@5 100.000 (99.917) +2022-11-14 16:38:28,382 Epoch: [366][120/500] Time 0.060 (0.052) Data 0.002 (0.004) Loss 0.0369 (0.0349) Prec@1 92.000 (94.462) Prec@5 100.000 (99.923) +2022-11-14 16:38:28,950 Epoch: [366][130/500] Time 0.051 (0.052) Data 0.002 (0.004) Loss 0.0398 (0.0352) Prec@1 94.000 (94.429) Prec@5 99.000 (99.857) +2022-11-14 16:38:29,524 Epoch: [366][140/500] Time 0.056 (0.052) Data 0.003 (0.004) Loss 0.0487 (0.0361) Prec@1 91.000 (94.200) Prec@5 99.000 (99.800) +2022-11-14 16:38:30,103 Epoch: [366][150/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0354 (0.0361) Prec@1 93.000 (94.125) Prec@5 100.000 (99.812) +2022-11-14 16:38:30,793 Epoch: [366][160/500] Time 0.069 (0.052) Data 0.002 (0.004) Loss 0.0320 (0.0358) Prec@1 95.000 (94.176) Prec@5 100.000 (99.824) +2022-11-14 16:38:31,351 Epoch: [366][170/500] Time 0.051 (0.052) Data 0.002 (0.004) Loss 0.0469 (0.0364) Prec@1 91.000 (94.000) Prec@5 100.000 (99.833) +2022-11-14 16:38:31,918 Epoch: [366][180/500] Time 0.062 (0.052) Data 0.002 (0.004) Loss 0.0309 (0.0362) Prec@1 94.000 (94.000) Prec@5 100.000 (99.842) +2022-11-14 16:38:32,492 Epoch: [366][190/500] Time 0.058 (0.052) Data 0.002 (0.004) Loss 0.0387 (0.0363) Prec@1 92.000 (93.900) Prec@5 100.000 (99.850) +2022-11-14 16:38:33,054 Epoch: [366][200/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0408 (0.0365) Prec@1 93.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 16:38:33,633 Epoch: [366][210/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0241 (0.0359) Prec@1 96.000 (93.955) Prec@5 100.000 (99.864) +2022-11-14 16:38:34,253 Epoch: [366][220/500] Time 0.080 (0.052) Data 0.002 (0.003) Loss 0.0385 (0.0360) Prec@1 92.000 (93.870) Prec@5 100.000 (99.870) +2022-11-14 16:38:34,822 Epoch: [366][230/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0254 (0.0356) Prec@1 96.000 (93.958) Prec@5 100.000 (99.875) +2022-11-14 16:38:35,423 Epoch: [366][240/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0219 (0.0351) Prec@1 97.000 (94.080) Prec@5 100.000 (99.880) +2022-11-14 16:38:35,999 Epoch: [366][250/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0311 (0.0349) Prec@1 95.000 (94.115) Prec@5 100.000 (99.885) +2022-11-14 16:38:36,575 Epoch: [366][260/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0467 (0.0353) Prec@1 92.000 (94.037) Prec@5 100.000 (99.889) +2022-11-14 16:38:37,146 Epoch: [366][270/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0507 (0.0359) Prec@1 90.000 (93.893) Prec@5 99.000 (99.857) +2022-11-14 16:38:37,703 Epoch: [366][280/500] Time 0.045 (0.052) Data 0.002 (0.003) Loss 0.0436 (0.0361) Prec@1 92.000 (93.828) Prec@5 98.000 (99.793) +2022-11-14 16:38:38,284 Epoch: [366][290/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0351 (0.0361) Prec@1 94.000 (93.833) Prec@5 99.000 (99.767) +2022-11-14 16:38:38,911 Epoch: [366][300/500] Time 0.075 (0.052) Data 0.002 (0.003) Loss 0.0462 (0.0364) Prec@1 92.000 (93.774) Prec@5 100.000 (99.774) +2022-11-14 16:38:39,606 Epoch: [366][310/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0315 (0.0363) Prec@1 94.000 (93.781) Prec@5 100.000 (99.781) +2022-11-14 16:38:40,275 Epoch: [366][320/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0439 (0.0365) Prec@1 92.000 (93.727) Prec@5 100.000 (99.788) +2022-11-14 16:38:40,846 Epoch: [366][330/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0401 (0.0366) Prec@1 92.000 (93.676) Prec@5 100.000 (99.794) +2022-11-14 16:38:41,415 Epoch: [366][340/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0164 (0.0360) Prec@1 98.000 (93.800) Prec@5 100.000 (99.800) +2022-11-14 16:38:42,032 Epoch: [366][350/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0360 (0.0360) Prec@1 95.000 (93.833) Prec@5 99.000 (99.778) +2022-11-14 16:38:42,619 Epoch: [366][360/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0345 (0.0360) Prec@1 95.000 (93.865) Prec@5 100.000 (99.784) +2022-11-14 16:38:43,202 Epoch: [366][370/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0457 (0.0363) Prec@1 95.000 (93.895) Prec@5 100.000 (99.789) +2022-11-14 16:38:43,737 Epoch: [366][380/500] Time 0.045 (0.052) Data 0.002 (0.003) Loss 0.0170 (0.0358) Prec@1 98.000 (94.000) Prec@5 100.000 (99.795) +2022-11-14 16:38:44,399 Epoch: [366][390/500] Time 0.074 (0.053) Data 0.002 (0.003) Loss 0.0186 (0.0353) Prec@1 98.000 (94.100) Prec@5 100.000 (99.800) +2022-11-14 16:38:44,949 Epoch: [366][400/500] Time 0.043 (0.052) Data 0.002 (0.003) Loss 0.0130 (0.0348) Prec@1 98.000 (94.195) Prec@5 100.000 (99.805) +2022-11-14 16:38:45,520 Epoch: [366][410/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0502 (0.0352) Prec@1 91.000 (94.119) Prec@5 99.000 (99.786) +2022-11-14 16:38:46,092 Epoch: [366][420/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0312 (0.0351) Prec@1 95.000 (94.140) Prec@5 100.000 (99.791) +2022-11-14 16:38:46,663 Epoch: [366][430/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0348 (0.0351) Prec@1 94.000 (94.136) Prec@5 100.000 (99.795) +2022-11-14 16:38:47,228 Epoch: [366][440/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0420 (0.0352) Prec@1 92.000 (94.089) Prec@5 100.000 (99.800) +2022-11-14 16:38:47,850 Epoch: [366][450/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0258 (0.0350) Prec@1 95.000 (94.109) Prec@5 100.000 (99.804) +2022-11-14 16:38:48,438 Epoch: [366][460/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0219 (0.0347) Prec@1 96.000 (94.149) Prec@5 100.000 (99.809) +2022-11-14 16:38:49,001 Epoch: [366][470/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0522 (0.0351) Prec@1 92.000 (94.104) Prec@5 99.000 (99.792) +2022-11-14 16:38:49,540 Epoch: [366][480/500] Time 0.047 (0.052) Data 0.002 (0.003) Loss 0.0438 (0.0353) Prec@1 91.000 (94.041) Prec@5 100.000 (99.796) +2022-11-14 16:38:50,180 Epoch: [366][490/500] Time 0.078 (0.052) Data 0.002 (0.003) Loss 0.0319 (0.0352) Prec@1 96.000 (94.080) Prec@5 100.000 (99.800) +2022-11-14 16:38:50,707 Epoch: [366][499/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0316 (0.0351) Prec@1 95.000 (94.098) Prec@5 100.000 (99.804) +2022-11-14 16:38:51,029 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0620) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:51,039 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0626) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:38:51,049 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0696) Prec@1 84.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:38:51,062 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0740) Prec@1 85.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:51,074 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0764 (0.0745) Prec@1 90.000 (87.600) Prec@5 98.000 (99.600) +2022-11-14 16:38:51,086 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0730) Prec@1 89.000 (87.833) Prec@5 100.000 (99.667) +2022-11-14 16:38:51,098 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0710) Prec@1 91.000 (88.286) Prec@5 99.000 (99.571) +2022-11-14 16:38:51,117 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0708) Prec@1 89.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 16:38:51,133 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0711) Prec@1 90.000 (88.556) Prec@5 98.000 (99.444) +2022-11-14 16:38:51,148 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0709) Prec@1 89.000 (88.600) Prec@5 99.000 (99.400) +2022-11-14 16:38:51,162 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0697) Prec@1 91.000 (88.818) Prec@5 100.000 (99.455) +2022-11-14 16:38:51,177 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0709) Prec@1 86.000 (88.583) Prec@5 100.000 (99.500) +2022-11-14 16:38:51,196 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0672 (0.0706) Prec@1 88.000 (88.538) Prec@5 100.000 (99.538) +2022-11-14 16:38:51,213 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0723) Prec@1 83.000 (88.143) Prec@5 98.000 (99.429) +2022-11-14 16:38:51,236 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0726) Prec@1 87.000 (88.067) Prec@5 99.000 (99.400) +2022-11-14 16:38:51,254 Test: [15/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0729) Prec@1 89.000 (88.125) Prec@5 98.000 (99.312) +2022-11-14 16:38:51,272 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0471 (0.0714) Prec@1 94.000 (88.471) Prec@5 98.000 (99.235) +2022-11-14 16:38:51,291 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0736) Prec@1 84.000 (88.222) Prec@5 100.000 (99.278) +2022-11-14 16:38:51,310 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0741) Prec@1 86.000 (88.105) Prec@5 98.000 (99.211) +2022-11-14 16:38:51,329 Test: [19/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0748) Prec@1 86.000 (88.000) Prec@5 97.000 (99.100) +2022-11-14 16:38:51,348 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0752) Prec@1 85.000 (87.857) Prec@5 99.000 (99.095) +2022-11-14 16:38:51,368 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0755) Prec@1 86.000 (87.773) Prec@5 99.000 (99.091) +2022-11-14 16:38:51,389 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0757) Prec@1 87.000 (87.739) Prec@5 98.000 (99.043) +2022-11-14 16:38:51,406 Test: [23/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0755) Prec@1 89.000 (87.792) Prec@5 100.000 (99.083) +2022-11-14 16:38:51,422 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0950 (0.0763) Prec@1 84.000 (87.640) Prec@5 100.000 (99.120) +2022-11-14 16:38:51,442 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0773) Prec@1 83.000 (87.462) Prec@5 98.000 (99.077) +2022-11-14 16:38:51,463 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0764) Prec@1 91.000 (87.593) Prec@5 100.000 (99.111) +2022-11-14 16:38:51,483 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0758) Prec@1 91.000 (87.714) Prec@5 100.000 (99.143) +2022-11-14 16:38:51,502 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0758) Prec@1 88.000 (87.724) Prec@5 98.000 (99.103) +2022-11-14 16:38:51,520 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0757) Prec@1 88.000 (87.733) Prec@5 99.000 (99.100) +2022-11-14 16:38:51,540 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0757) Prec@1 86.000 (87.677) Prec@5 99.000 (99.097) +2022-11-14 16:38:51,560 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0756) Prec@1 88.000 (87.688) Prec@5 99.000 (99.094) +2022-11-14 16:38:51,579 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0808 (0.0758) Prec@1 85.000 (87.606) Prec@5 98.000 (99.061) +2022-11-14 16:38:51,598 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0761) Prec@1 84.000 (87.500) Prec@5 100.000 (99.088) +2022-11-14 16:38:51,619 Test: [34/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0764) Prec@1 86.000 (87.457) Prec@5 100.000 (99.114) +2022-11-14 16:38:51,640 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0764) Prec@1 87.000 (87.444) Prec@5 99.000 (99.111) +2022-11-14 16:38:51,659 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0759) Prec@1 92.000 (87.568) Prec@5 99.000 (99.108) +2022-11-14 16:38:51,676 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0761) Prec@1 84.000 (87.474) Prec@5 99.000 (99.105) +2022-11-14 16:38:51,695 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0755) Prec@1 92.000 (87.590) Prec@5 99.000 (99.103) +2022-11-14 16:38:51,715 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0755) Prec@1 91.000 (87.675) Prec@5 100.000 (99.125) +2022-11-14 16:38:51,734 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0946 (0.0759) Prec@1 87.000 (87.659) Prec@5 99.000 (99.122) +2022-11-14 16:38:51,755 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0569 (0.0755) Prec@1 90.000 (87.714) Prec@5 99.000 (99.119) +2022-11-14 16:38:51,773 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0753) Prec@1 90.000 (87.767) Prec@5 99.000 (99.116) +2022-11-14 16:38:51,791 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0753) Prec@1 88.000 (87.773) Prec@5 98.000 (99.091) +2022-11-14 16:38:51,812 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0751) Prec@1 90.000 (87.822) Prec@5 100.000 (99.111) +2022-11-14 16:38:51,834 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1052 (0.0757) Prec@1 81.000 (87.674) Prec@5 100.000 (99.130) +2022-11-14 16:38:51,853 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0757) Prec@1 87.000 (87.660) Prec@5 100.000 (99.149) +2022-11-14 16:38:51,873 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0759) Prec@1 86.000 (87.625) Prec@5 98.000 (99.125) +2022-11-14 16:38:51,895 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0756) Prec@1 88.000 (87.633) Prec@5 99.000 (99.122) +2022-11-14 16:38:51,915 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0762) Prec@1 84.000 (87.560) Prec@5 100.000 (99.140) +2022-11-14 16:38:51,932 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0758) Prec@1 91.000 (87.627) Prec@5 100.000 (99.157) +2022-11-14 16:38:51,951 Test: [51/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0759) Prec@1 85.000 (87.577) Prec@5 99.000 (99.154) +2022-11-14 16:38:51,969 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0758) Prec@1 89.000 (87.604) Prec@5 99.000 (99.151) +2022-11-14 16:38:51,986 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0758) Prec@1 86.000 (87.574) Prec@5 98.000 (99.130) +2022-11-14 16:38:52,006 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1069 (0.0764) Prec@1 82.000 (87.473) Prec@5 100.000 (99.145) +2022-11-14 16:38:52,021 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0762) Prec@1 91.000 (87.536) Prec@5 99.000 (99.143) +2022-11-14 16:38:52,038 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0761) Prec@1 90.000 (87.579) Prec@5 100.000 (99.158) +2022-11-14 16:38:52,060 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0763) Prec@1 85.000 (87.534) Prec@5 97.000 (99.121) +2022-11-14 16:38:52,079 Test: [58/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1083 (0.0768) Prec@1 81.000 (87.424) Prec@5 99.000 (99.119) +2022-11-14 16:38:52,102 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0769) Prec@1 85.000 (87.383) Prec@5 99.000 (99.117) +2022-11-14 16:38:52,123 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0921 (0.0771) Prec@1 87.000 (87.377) Prec@5 99.000 (99.115) +2022-11-14 16:38:52,145 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0771) Prec@1 90.000 (87.419) Prec@5 98.000 (99.097) +2022-11-14 16:38:52,160 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0768) Prec@1 90.000 (87.460) Prec@5 100.000 (99.111) +2022-11-14 16:38:52,178 Test: [63/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0473 (0.0763) Prec@1 91.000 (87.516) Prec@5 100.000 (99.125) +2022-11-14 16:38:52,199 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0908 (0.0766) Prec@1 86.000 (87.492) Prec@5 100.000 (99.138) +2022-11-14 16:38:52,218 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0766) Prec@1 88.000 (87.500) Prec@5 99.000 (99.136) +2022-11-14 16:38:52,236 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0481 (0.0761) Prec@1 93.000 (87.582) Prec@5 100.000 (99.149) +2022-11-14 16:38:52,257 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0761) Prec@1 88.000 (87.588) Prec@5 98.000 (99.132) +2022-11-14 16:38:52,274 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0758) Prec@1 87.000 (87.580) Prec@5 98.000 (99.116) +2022-11-14 16:38:52,290 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0756) Prec@1 90.000 (87.614) Prec@5 99.000 (99.114) +2022-11-14 16:38:52,310 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0760) Prec@1 85.000 (87.577) Prec@5 98.000 (99.099) +2022-11-14 16:38:52,331 Test: [71/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0505 (0.0756) Prec@1 91.000 (87.625) Prec@5 100.000 (99.111) +2022-11-14 16:38:52,352 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0754) Prec@1 92.000 (87.685) Prec@5 100.000 (99.123) +2022-11-14 16:38:52,372 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0426 (0.0749) Prec@1 95.000 (87.784) Prec@5 99.000 (99.122) +2022-11-14 16:38:52,392 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0969 (0.0752) Prec@1 86.000 (87.760) Prec@5 100.000 (99.133) +2022-11-14 16:38:52,412 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0751) Prec@1 88.000 (87.763) Prec@5 100.000 (99.145) +2022-11-14 16:38:52,433 Test: [76/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0752) Prec@1 86.000 (87.740) Prec@5 98.000 (99.130) +2022-11-14 16:38:52,453 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0752) Prec@1 86.000 (87.718) Prec@5 97.000 (99.103) +2022-11-14 16:38:52,474 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0755) Prec@1 85.000 (87.684) Prec@5 100.000 (99.114) +2022-11-14 16:38:52,493 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0597 (0.0753) Prec@1 90.000 (87.713) Prec@5 99.000 (99.112) +2022-11-14 16:38:52,516 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0756) Prec@1 86.000 (87.691) Prec@5 98.000 (99.099) +2022-11-14 16:38:52,536 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0755) Prec@1 89.000 (87.707) Prec@5 100.000 (99.110) +2022-11-14 16:38:52,553 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0759) Prec@1 85.000 (87.675) Prec@5 99.000 (99.108) +2022-11-14 16:38:52,570 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0757) Prec@1 87.000 (87.667) Prec@5 99.000 (99.107) +2022-11-14 16:38:52,588 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1164 (0.0762) Prec@1 84.000 (87.624) Prec@5 98.000 (99.094) +2022-11-14 16:38:52,610 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1137 (0.0766) Prec@1 82.000 (87.558) Prec@5 100.000 (99.105) +2022-11-14 16:38:52,628 Test: [86/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0763) Prec@1 93.000 (87.621) Prec@5 100.000 (99.115) +2022-11-14 16:38:52,645 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0762) Prec@1 90.000 (87.648) Prec@5 99.000 (99.114) +2022-11-14 16:38:52,664 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0762) Prec@1 85.000 (87.618) Prec@5 99.000 (99.112) +2022-11-14 16:38:52,685 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0761) Prec@1 90.000 (87.644) Prec@5 99.000 (99.111) +2022-11-14 16:38:52,707 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0759) Prec@1 92.000 (87.692) Prec@5 100.000 (99.121) +2022-11-14 16:38:52,729 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0537 (0.0757) Prec@1 92.000 (87.739) Prec@5 99.000 (99.120) +2022-11-14 16:38:52,748 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0756) Prec@1 89.000 (87.753) Prec@5 100.000 (99.129) +2022-11-14 16:38:52,766 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0756) Prec@1 90.000 (87.777) Prec@5 100.000 (99.138) +2022-11-14 16:38:52,785 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0757) Prec@1 85.000 (87.747) Prec@5 100.000 (99.147) +2022-11-14 16:38:52,802 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0756) Prec@1 90.000 (87.771) Prec@5 100.000 (99.156) +2022-11-14 16:38:52,820 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0407 (0.0752) Prec@1 93.000 (87.825) Prec@5 100.000 (99.165) +2022-11-14 16:38:52,838 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0754) Prec@1 86.000 (87.806) Prec@5 98.000 (99.153) +2022-11-14 16:38:52,862 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0756) Prec@1 85.000 (87.778) Prec@5 100.000 (99.162) +2022-11-14 16:38:52,879 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0755) Prec@1 89.000 (87.790) Prec@5 99.000 (99.160) +2022-11-14 16:38:52,943 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:38:53,299 Epoch: [367][0/500] Time 0.025 (0.025) Data 0.266 (0.266) Loss 0.0273 (0.0273) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:53,780 Epoch: [367][10/500] Time 0.052 (0.041) Data 0.001 (0.026) Loss 0.0219 (0.0246) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:54,444 Epoch: [367][20/500] Time 0.056 (0.050) Data 0.002 (0.015) Loss 0.0292 (0.0261) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:38:55,019 Epoch: [367][30/500] Time 0.066 (0.051) Data 0.002 (0.011) Loss 0.0190 (0.0244) Prec@1 97.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 16:38:55,584 Epoch: [367][40/500] Time 0.062 (0.051) Data 0.002 (0.009) Loss 0.0249 (0.0245) Prec@1 97.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 16:38:56,133 Epoch: [367][50/500] Time 0.054 (0.050) Data 0.002 (0.007) Loss 0.0179 (0.0234) Prec@1 96.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 16:38:56,705 Epoch: [367][60/500] Time 0.049 (0.050) Data 0.002 (0.006) Loss 0.0371 (0.0253) Prec@1 95.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 16:38:57,299 Epoch: [367][70/500] Time 0.073 (0.051) Data 0.002 (0.006) Loss 0.0216 (0.0249) Prec@1 97.000 (95.875) Prec@5 100.000 (99.875) +2022-11-14 16:38:57,871 Epoch: [367][80/500] Time 0.056 (0.051) Data 0.002 (0.005) Loss 0.0319 (0.0256) Prec@1 96.000 (95.889) Prec@5 100.000 (99.889) +2022-11-14 16:38:58,436 Epoch: [367][90/500] Time 0.054 (0.051) Data 0.002 (0.005) Loss 0.0454 (0.0276) Prec@1 93.000 (95.600) Prec@5 100.000 (99.900) +2022-11-14 16:38:59,119 Epoch: [367][100/500] Time 0.067 (0.052) Data 0.003 (0.005) Loss 0.0128 (0.0263) Prec@1 99.000 (95.909) Prec@5 100.000 (99.909) +2022-11-14 16:38:59,720 Epoch: [367][110/500] Time 0.056 (0.052) Data 0.002 (0.005) Loss 0.0274 (0.0264) Prec@1 97.000 (96.000) Prec@5 100.000 (99.917) +2022-11-14 16:39:00,270 Epoch: [367][120/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0235 (0.0261) Prec@1 96.000 (96.000) Prec@5 100.000 (99.923) +2022-11-14 16:39:00,908 Epoch: [367][130/500] Time 0.058 (0.052) Data 0.002 (0.004) Loss 0.0277 (0.0263) Prec@1 94.000 (95.857) Prec@5 100.000 (99.929) +2022-11-14 16:39:01,482 Epoch: [367][140/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0473 (0.0277) Prec@1 93.000 (95.667) Prec@5 99.000 (99.867) +2022-11-14 16:39:02,069 Epoch: [367][150/500] Time 0.059 (0.052) Data 0.002 (0.004) Loss 0.0351 (0.0281) Prec@1 94.000 (95.562) Prec@5 100.000 (99.875) +2022-11-14 16:39:02,657 Epoch: [367][160/500] Time 0.060 (0.052) Data 0.002 (0.004) Loss 0.0385 (0.0287) Prec@1 93.000 (95.412) Prec@5 99.000 (99.824) +2022-11-14 16:39:03,362 Epoch: [367][170/500] Time 0.069 (0.053) Data 0.002 (0.004) Loss 0.0354 (0.0291) Prec@1 92.000 (95.222) Prec@5 100.000 (99.833) +2022-11-14 16:39:04,020 Epoch: [367][180/500] Time 0.056 (0.053) Data 0.002 (0.004) Loss 0.0255 (0.0289) Prec@1 96.000 (95.263) Prec@5 100.000 (99.842) +2022-11-14 16:39:04,592 Epoch: [367][190/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0360 (0.0293) Prec@1 91.000 (95.050) Prec@5 100.000 (99.850) +2022-11-14 16:39:05,249 Epoch: [367][200/500] Time 0.062 (0.054) Data 0.002 (0.004) Loss 0.0223 (0.0289) Prec@1 95.000 (95.048) Prec@5 100.000 (99.857) +2022-11-14 16:39:05,970 Epoch: [367][210/500] Time 0.070 (0.054) Data 0.002 (0.003) Loss 0.0270 (0.0288) Prec@1 97.000 (95.136) Prec@5 100.000 (99.864) +2022-11-14 16:39:06,682 Epoch: [367][220/500] Time 0.070 (0.055) Data 0.002 (0.003) Loss 0.0326 (0.0290) Prec@1 93.000 (95.043) Prec@5 99.000 (99.826) +2022-11-14 16:39:07,311 Epoch: [367][230/500] Time 0.058 (0.055) Data 0.002 (0.003) Loss 0.0285 (0.0290) Prec@1 94.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:39:07,925 Epoch: [367][240/500] Time 0.054 (0.055) Data 0.002 (0.003) Loss 0.0083 (0.0282) Prec@1 100.000 (95.200) Prec@5 100.000 (99.840) +2022-11-14 16:39:08,609 Epoch: [367][250/500] Time 0.054 (0.055) Data 0.003 (0.003) Loss 0.0333 (0.0284) Prec@1 93.000 (95.115) Prec@5 99.000 (99.808) +2022-11-14 16:39:09,218 Epoch: [367][260/500] Time 0.061 (0.055) Data 0.002 (0.003) Loss 0.0307 (0.0284) Prec@1 95.000 (95.111) Prec@5 100.000 (99.815) +2022-11-14 16:39:09,788 Epoch: [367][270/500] Time 0.046 (0.055) Data 0.002 (0.003) Loss 0.0298 (0.0285) Prec@1 93.000 (95.036) Prec@5 100.000 (99.821) +2022-11-14 16:39:10,448 Epoch: [367][280/500] Time 0.051 (0.055) Data 0.002 (0.003) Loss 0.0165 (0.0281) Prec@1 97.000 (95.103) Prec@5 100.000 (99.828) +2022-11-14 16:39:11,006 Epoch: [367][290/500] Time 0.048 (0.055) Data 0.002 (0.003) Loss 0.0215 (0.0279) Prec@1 96.000 (95.133) Prec@5 100.000 (99.833) +2022-11-14 16:39:11,571 Epoch: [367][300/500] Time 0.060 (0.055) Data 0.002 (0.003) Loss 0.0278 (0.0279) Prec@1 96.000 (95.161) Prec@5 100.000 (99.839) +2022-11-14 16:39:12,157 Epoch: [367][310/500] Time 0.056 (0.055) Data 0.002 (0.003) Loss 0.0438 (0.0284) Prec@1 92.000 (95.062) Prec@5 100.000 (99.844) +2022-11-14 16:39:12,718 Epoch: [367][320/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0368 (0.0286) Prec@1 94.000 (95.030) Prec@5 100.000 (99.848) +2022-11-14 16:39:13,298 Epoch: [367][330/500] Time 0.046 (0.054) Data 0.002 (0.003) Loss 0.0364 (0.0288) Prec@1 94.000 (95.000) Prec@5 100.000 (99.853) +2022-11-14 16:39:13,872 Epoch: [367][340/500] Time 0.057 (0.054) Data 0.002 (0.003) Loss 0.0652 (0.0299) Prec@1 89.000 (94.829) Prec@5 99.000 (99.829) +2022-11-14 16:39:14,440 Epoch: [367][350/500] Time 0.052 (0.054) Data 0.003 (0.003) Loss 0.0385 (0.0301) Prec@1 94.000 (94.806) Prec@5 100.000 (99.833) +2022-11-14 16:39:15,089 Epoch: [367][360/500] Time 0.072 (0.054) Data 0.002 (0.003) Loss 0.0303 (0.0301) Prec@1 95.000 (94.811) Prec@5 100.000 (99.838) +2022-11-14 16:39:15,680 Epoch: [367][370/500] Time 0.051 (0.054) Data 0.003 (0.003) Loss 0.0286 (0.0301) Prec@1 97.000 (94.868) Prec@5 99.000 (99.816) +2022-11-14 16:39:16,255 Epoch: [367][380/500] Time 0.048 (0.054) Data 0.003 (0.003) Loss 0.0301 (0.0301) Prec@1 94.000 (94.846) Prec@5 100.000 (99.821) +2022-11-14 16:39:16,826 Epoch: [367][390/500] Time 0.056 (0.054) Data 0.002 (0.003) Loss 0.0568 (0.0308) Prec@1 89.000 (94.700) Prec@5 100.000 (99.825) +2022-11-14 16:39:17,435 Epoch: [367][400/500] Time 0.067 (0.054) Data 0.002 (0.003) Loss 0.0174 (0.0304) Prec@1 96.000 (94.732) Prec@5 100.000 (99.829) +2022-11-14 16:39:18,001 Epoch: [367][410/500] Time 0.063 (0.054) Data 0.002 (0.003) Loss 0.0283 (0.0304) Prec@1 96.000 (94.762) Prec@5 100.000 (99.833) +2022-11-14 16:39:18,573 Epoch: [367][420/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0408 (0.0306) Prec@1 91.000 (94.674) Prec@5 100.000 (99.837) +2022-11-14 16:39:19,141 Epoch: [367][430/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0326 (0.0307) Prec@1 96.000 (94.705) Prec@5 99.000 (99.818) +2022-11-14 16:39:19,771 Epoch: [367][440/500] Time 0.077 (0.054) Data 0.002 (0.003) Loss 0.0112 (0.0302) Prec@1 98.000 (94.778) Prec@5 100.000 (99.822) +2022-11-14 16:39:20,381 Epoch: [367][450/500] Time 0.051 (0.054) Data 0.002 (0.003) Loss 0.0331 (0.0303) Prec@1 96.000 (94.804) Prec@5 100.000 (99.826) +2022-11-14 16:39:20,969 Epoch: [367][460/500] Time 0.050 (0.054) Data 0.003 (0.003) Loss 0.0352 (0.0304) Prec@1 95.000 (94.809) Prec@5 100.000 (99.830) +2022-11-14 16:39:21,562 Epoch: [367][470/500] Time 0.071 (0.054) Data 0.002 (0.003) Loss 0.0314 (0.0304) Prec@1 94.000 (94.792) Prec@5 100.000 (99.833) +2022-11-14 16:39:22,140 Epoch: [367][480/500] Time 0.050 (0.054) Data 0.002 (0.003) Loss 0.0415 (0.0306) Prec@1 91.000 (94.714) Prec@5 100.000 (99.837) +2022-11-14 16:39:22,812 Epoch: [367][490/500] Time 0.045 (0.054) Data 0.002 (0.003) Loss 0.0367 (0.0308) Prec@1 96.000 (94.740) Prec@5 100.000 (99.840) +2022-11-14 16:39:23,325 Epoch: [367][499/500] Time 0.059 (0.054) Data 0.002 (0.003) Loss 0.0331 (0.0308) Prec@1 94.000 (94.725) Prec@5 100.000 (99.843) +2022-11-14 16:39:23,671 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0715 (0.0715) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:39:23,679 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0691) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:39:23,687 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0604 (0.0662) Prec@1 90.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:39:23,699 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0683) Prec@1 88.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 16:39:23,708 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0702) Prec@1 87.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 16:39:23,718 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0657) Prec@1 93.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 16:39:23,732 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0641) Prec@1 90.000 (89.143) Prec@5 99.000 (99.714) +2022-11-14 16:39:23,750 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0687) Prec@1 82.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 16:39:23,766 Test: [8/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0707) Prec@1 86.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 16:39:23,781 Test: [9/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0700) Prec@1 91.000 (88.300) Prec@5 99.000 (99.600) +2022-11-14 16:39:23,798 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0440 (0.0676) Prec@1 93.000 (88.727) Prec@5 100.000 (99.636) +2022-11-14 16:39:23,817 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0695) Prec@1 86.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 16:39:23,835 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0690) Prec@1 89.000 (88.538) Prec@5 99.000 (99.615) +2022-11-14 16:39:23,854 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0694) Prec@1 88.000 (88.500) Prec@5 100.000 (99.643) +2022-11-14 16:39:23,874 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0705) Prec@1 84.000 (88.200) Prec@5 99.000 (99.600) +2022-11-14 16:39:23,891 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0709) Prec@1 88.000 (88.188) Prec@5 99.000 (99.562) +2022-11-14 16:39:23,912 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0695) Prec@1 93.000 (88.471) Prec@5 98.000 (99.471) +2022-11-14 16:39:23,932 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0716) Prec@1 83.000 (88.167) Prec@5 99.000 (99.444) +2022-11-14 16:39:23,950 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0726) Prec@1 85.000 (88.000) Prec@5 100.000 (99.474) +2022-11-14 16:39:23,971 Test: [19/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1001 (0.0740) Prec@1 85.000 (87.850) Prec@5 96.000 (99.300) +2022-11-14 16:39:23,992 Test: [20/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0740) Prec@1 89.000 (87.905) Prec@5 100.000 (99.333) +2022-11-14 16:39:24,008 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0748) Prec@1 85.000 (87.773) Prec@5 98.000 (99.273) +2022-11-14 16:39:24,027 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0758) Prec@1 84.000 (87.609) Prec@5 97.000 (99.174) +2022-11-14 16:39:24,047 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0758) Prec@1 86.000 (87.542) Prec@5 100.000 (99.208) +2022-11-14 16:39:24,066 Test: [24/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0762) Prec@1 88.000 (87.560) Prec@5 100.000 (99.240) +2022-11-14 16:39:24,089 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0764) Prec@1 88.000 (87.577) Prec@5 99.000 (99.231) +2022-11-14 16:39:24,108 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0753) Prec@1 92.000 (87.741) Prec@5 100.000 (99.259) +2022-11-14 16:39:24,126 Test: [27/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0465 (0.0742) Prec@1 92.000 (87.893) Prec@5 100.000 (99.286) +2022-11-14 16:39:24,148 Test: [28/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0744) Prec@1 89.000 (87.931) Prec@5 97.000 (99.207) +2022-11-14 16:39:24,165 Test: [29/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0741) Prec@1 90.000 (88.000) Prec@5 100.000 (99.233) +2022-11-14 16:39:24,185 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0738) Prec@1 89.000 (88.032) Prec@5 100.000 (99.258) +2022-11-14 16:39:24,202 Test: [31/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0741) Prec@1 88.000 (88.031) Prec@5 99.000 (99.250) +2022-11-14 16:39:24,223 Test: [32/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0743) Prec@1 86.000 (87.970) Prec@5 100.000 (99.273) +2022-11-14 16:39:24,246 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0749) Prec@1 84.000 (87.853) Prec@5 97.000 (99.206) +2022-11-14 16:39:24,263 Test: [34/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0753) Prec@1 87.000 (87.829) Prec@5 98.000 (99.171) +2022-11-14 16:39:24,284 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0752) Prec@1 90.000 (87.889) Prec@5 100.000 (99.194) +2022-11-14 16:39:24,303 Test: [36/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0751) Prec@1 88.000 (87.892) Prec@5 99.000 (99.189) +2022-11-14 16:39:24,322 Test: [37/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0756) Prec@1 83.000 (87.763) Prec@5 100.000 (99.211) +2022-11-14 16:39:24,340 Test: [38/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0753) Prec@1 92.000 (87.872) Prec@5 100.000 (99.231) +2022-11-14 16:39:24,358 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0753) Prec@1 87.000 (87.850) Prec@5 99.000 (99.225) +2022-11-14 16:39:24,378 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1028 (0.0760) Prec@1 84.000 (87.756) Prec@5 99.000 (99.220) +2022-11-14 16:39:24,398 Test: [41/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0756) Prec@1 91.000 (87.833) Prec@5 99.000 (99.214) +2022-11-14 16:39:24,415 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0750) Prec@1 91.000 (87.907) Prec@5 99.000 (99.209) +2022-11-14 16:39:24,435 Test: [43/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0749) Prec@1 88.000 (87.909) Prec@5 98.000 (99.182) +2022-11-14 16:39:24,456 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0745) Prec@1 93.000 (88.022) Prec@5 98.000 (99.156) +2022-11-14 16:39:24,474 Test: [45/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0751) Prec@1 82.000 (87.891) Prec@5 99.000 (99.152) +2022-11-14 16:39:24,490 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0752) Prec@1 87.000 (87.872) Prec@5 99.000 (99.149) +2022-11-14 16:39:24,508 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0983 (0.0756) Prec@1 84.000 (87.792) Prec@5 99.000 (99.146) +2022-11-14 16:39:24,529 Test: [48/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0753) Prec@1 89.000 (87.816) Prec@5 100.000 (99.163) +2022-11-14 16:39:24,550 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0933 (0.0757) Prec@1 87.000 (87.800) Prec@5 100.000 (99.180) +2022-11-14 16:39:24,567 Test: [50/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0756) Prec@1 88.000 (87.804) Prec@5 99.000 (99.176) +2022-11-14 16:39:24,588 Test: [51/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0758) Prec@1 88.000 (87.808) Prec@5 98.000 (99.154) +2022-11-14 16:39:24,606 Test: [52/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0754) Prec@1 92.000 (87.887) Prec@5 99.000 (99.151) +2022-11-14 16:39:24,624 Test: [53/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0752) Prec@1 89.000 (87.907) Prec@5 100.000 (99.167) +2022-11-14 16:39:24,644 Test: [54/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0755) Prec@1 85.000 (87.855) Prec@5 100.000 (99.182) +2022-11-14 16:39:24,662 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0754) Prec@1 88.000 (87.857) Prec@5 99.000 (99.179) +2022-11-14 16:39:24,684 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0753) Prec@1 89.000 (87.877) Prec@5 100.000 (99.193) +2022-11-14 16:39:24,702 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0751) Prec@1 89.000 (87.897) Prec@5 100.000 (99.207) +2022-11-14 16:39:24,722 Test: [58/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0755) Prec@1 83.000 (87.814) Prec@5 99.000 (99.203) +2022-11-14 16:39:24,744 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0756) Prec@1 84.000 (87.750) Prec@5 100.000 (99.217) +2022-11-14 16:39:24,761 Test: [60/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0905 (0.0758) Prec@1 87.000 (87.738) Prec@5 98.000 (99.197) +2022-11-14 16:39:24,781 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0760) Prec@1 85.000 (87.694) Prec@5 99.000 (99.194) +2022-11-14 16:39:24,798 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0758) Prec@1 89.000 (87.714) Prec@5 100.000 (99.206) +2022-11-14 16:39:24,818 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0294 (0.0751) Prec@1 95.000 (87.828) Prec@5 99.000 (99.203) +2022-11-14 16:39:24,837 Test: [64/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0754) Prec@1 84.000 (87.769) Prec@5 99.000 (99.200) +2022-11-14 16:39:24,852 Test: [65/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0520 (0.0751) Prec@1 92.000 (87.833) Prec@5 100.000 (99.212) +2022-11-14 16:39:24,869 Test: [66/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0468 (0.0746) Prec@1 92.000 (87.896) Prec@5 100.000 (99.224) +2022-11-14 16:39:24,890 Test: [67/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0745) Prec@1 90.000 (87.926) Prec@5 100.000 (99.235) +2022-11-14 16:39:24,909 Test: [68/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0592 (0.0742) Prec@1 90.000 (87.957) Prec@5 99.000 (99.232) +2022-11-14 16:39:24,928 Test: [69/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0743) Prec@1 88.000 (87.957) Prec@5 99.000 (99.229) +2022-11-14 16:39:24,949 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0746) Prec@1 89.000 (87.972) Prec@5 98.000 (99.211) +2022-11-14 16:39:24,968 Test: [71/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0745) Prec@1 90.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 16:39:24,988 Test: [72/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0501 (0.0741) Prec@1 92.000 (88.055) Prec@5 100.000 (99.233) +2022-11-14 16:39:25,007 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0738) Prec@1 93.000 (88.122) Prec@5 100.000 (99.243) +2022-11-14 16:39:25,023 Test: [74/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0739) Prec@1 87.000 (88.107) Prec@5 100.000 (99.253) +2022-11-14 16:39:25,043 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0737) Prec@1 90.000 (88.132) Prec@5 99.000 (99.250) +2022-11-14 16:39:25,060 Test: [76/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0736) Prec@1 90.000 (88.156) Prec@5 100.000 (99.260) +2022-11-14 16:39:25,080 Test: [77/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0736) Prec@1 89.000 (88.167) Prec@5 97.000 (99.231) +2022-11-14 16:39:25,097 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0737) Prec@1 87.000 (88.152) Prec@5 99.000 (99.228) +2022-11-14 16:39:25,116 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0736) Prec@1 91.000 (88.188) Prec@5 100.000 (99.237) +2022-11-14 16:39:25,133 Test: [80/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0737) Prec@1 85.000 (88.148) Prec@5 99.000 (99.235) +2022-11-14 16:39:25,151 Test: [81/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0737) Prec@1 85.000 (88.110) Prec@5 100.000 (99.244) +2022-11-14 16:39:25,171 Test: [82/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0738) Prec@1 88.000 (88.108) Prec@5 99.000 (99.241) +2022-11-14 16:39:25,190 Test: [83/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0735) Prec@1 94.000 (88.179) Prec@5 99.000 (99.238) +2022-11-14 16:39:25,206 Test: [84/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0736) Prec@1 86.000 (88.153) Prec@5 98.000 (99.224) +2022-11-14 16:39:25,223 Test: [85/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0738) Prec@1 85.000 (88.116) Prec@5 99.000 (99.221) +2022-11-14 16:39:25,241 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0737) Prec@1 89.000 (88.126) Prec@5 100.000 (99.230) +2022-11-14 16:39:25,258 Test: 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Loss 0.0682 (0.0734) Prec@1 89.000 (88.149) Prec@5 99.000 (99.223) +2022-11-14 16:39:25,391 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0736) Prec@1 87.000 (88.137) Prec@5 100.000 (99.232) +2022-11-14 16:39:25,409 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0734) Prec@1 91.000 (88.167) Prec@5 99.000 (99.229) +2022-11-14 16:39:25,426 Test: [96/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0489 (0.0731) Prec@1 93.000 (88.216) Prec@5 99.000 (99.227) +2022-11-14 16:39:25,442 Test: [97/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0733) Prec@1 88.000 (88.214) Prec@5 100.000 (99.235) +2022-11-14 16:39:25,459 Test: [98/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0945 (0.0735) Prec@1 88.000 (88.212) Prec@5 98.000 (99.222) +2022-11-14 16:39:25,478 Test: [99/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0734) Prec@1 88.000 (88.210) Prec@5 100.000 (99.230) +2022-11-14 16:39:25,539 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:39:25,890 Epoch: [368][0/500] Time 0.028 (0.028) Data 0.264 (0.264) Loss 0.0455 (0.0455) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:39:26,408 Epoch: [368][10/500] Time 0.061 (0.044) Data 0.002 (0.026) Loss 0.0317 (0.0386) Prec@1 96.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 16:39:26,976 Epoch: [368][20/500] Time 0.054 (0.047) Data 0.002 (0.015) Loss 0.0217 (0.0330) Prec@1 97.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:39:27,568 Epoch: [368][30/500] Time 0.059 (0.049) Data 0.002 (0.011) Loss 0.0233 (0.0305) Prec@1 96.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:39:28,149 Epoch: [368][40/500] Time 0.065 (0.050) Data 0.002 (0.009) Loss 0.0216 (0.0287) Prec@1 98.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:39:28,708 Epoch: [368][50/500] Time 0.054 (0.050) Data 0.002 (0.007) Loss 0.0190 (0.0271) Prec@1 98.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:39:29,345 Epoch: [368][60/500] Time 0.050 (0.051) Data 0.002 (0.006) Loss 0.0282 (0.0273) Prec@1 96.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 16:39:29,901 Epoch: [368][70/500] Time 0.047 (0.051) Data 0.002 (0.006) Loss 0.0251 (0.0270) Prec@1 95.000 (95.875) Prec@5 100.000 (99.875) +2022-11-14 16:39:30,477 Epoch: [368][80/500] Time 0.053 (0.051) Data 0.002 (0.005) Loss 0.0468 (0.0292) Prec@1 92.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:39:31,053 Epoch: [368][90/500] Time 0.055 (0.051) Data 0.002 (0.005) Loss 0.0378 (0.0301) Prec@1 94.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 16:39:31,634 Epoch: [368][100/500] Time 0.061 (0.051) Data 0.002 (0.005) Loss 0.0372 (0.0307) Prec@1 94.000 (95.182) Prec@5 100.000 (99.909) +2022-11-14 16:39:32,284 Epoch: [368][110/500] Time 0.059 (0.052) Data 0.003 (0.005) Loss 0.0405 (0.0315) Prec@1 93.000 (95.000) Prec@5 99.000 (99.833) +2022-11-14 16:39:32,856 Epoch: [368][120/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0392 (0.0321) Prec@1 95.000 (95.000) Prec@5 100.000 (99.846) +2022-11-14 16:39:33,405 Epoch: [368][130/500] Time 0.047 (0.051) Data 0.002 (0.004) Loss 0.0282 (0.0318) Prec@1 94.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 16:39:33,957 Epoch: [368][140/500] Time 0.058 (0.051) Data 0.002 (0.004) Loss 0.0239 (0.0313) Prec@1 96.000 (95.000) Prec@5 100.000 (99.867) +2022-11-14 16:39:34,548 Epoch: [368][150/500] Time 0.060 (0.051) Data 0.002 (0.004) Loss 0.0294 (0.0312) Prec@1 96.000 (95.062) Prec@5 100.000 (99.875) +2022-11-14 16:39:35,090 Epoch: [368][160/500] Time 0.045 (0.051) Data 0.002 (0.004) Loss 0.0283 (0.0310) Prec@1 94.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 16:39:35,657 Epoch: [368][170/500] Time 0.050 (0.051) Data 0.002 (0.004) Loss 0.0110 (0.0299) Prec@1 98.000 (95.167) Prec@5 100.000 (99.889) +2022-11-14 16:39:36,232 Epoch: [368][180/500] Time 0.051 (0.051) Data 0.002 (0.004) Loss 0.0345 (0.0302) Prec@1 94.000 (95.105) Prec@5 100.000 (99.895) +2022-11-14 16:39:36,792 Epoch: [368][190/500] Time 0.046 (0.051) Data 0.003 (0.003) Loss 0.0210 (0.0297) Prec@1 97.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:39:37,359 Epoch: [368][200/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0139 (0.0289) Prec@1 99.000 (95.381) Prec@5 100.000 (99.905) +2022-11-14 16:39:37,928 Epoch: [368][210/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0452 (0.0297) Prec@1 92.000 (95.227) Prec@5 100.000 (99.909) +2022-11-14 16:39:38,522 Epoch: [368][220/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0605 (0.0310) Prec@1 90.000 (95.000) Prec@5 100.000 (99.913) +2022-11-14 16:39:39,089 Epoch: [368][230/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0386 (0.0313) Prec@1 94.000 (94.958) Prec@5 100.000 (99.917) +2022-11-14 16:39:39,638 Epoch: [368][240/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0366 (0.0315) Prec@1 92.000 (94.840) Prec@5 100.000 (99.920) +2022-11-14 16:39:40,233 Epoch: [368][250/500] Time 0.059 (0.051) Data 0.002 (0.003) Loss 0.0256 (0.0313) Prec@1 95.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 16:39:40,803 Epoch: [368][260/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0341 (0.0314) Prec@1 94.000 (94.815) Prec@5 100.000 (99.926) +2022-11-14 16:39:41,366 Epoch: [368][270/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0413 (0.0318) Prec@1 94.000 (94.786) Prec@5 100.000 (99.929) +2022-11-14 16:39:41,938 Epoch: [368][280/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0325 (0.0318) Prec@1 95.000 (94.793) Prec@5 100.000 (99.931) +2022-11-14 16:39:42,499 Epoch: [368][290/500] Time 0.056 (0.051) Data 0.002 (0.003) Loss 0.0272 (0.0316) Prec@1 96.000 (94.833) Prec@5 100.000 (99.933) +2022-11-14 16:39:43,061 Epoch: [368][300/500] Time 0.048 (0.051) Data 0.003 (0.003) Loss 0.0343 (0.0317) Prec@1 93.000 (94.774) Prec@5 100.000 (99.935) +2022-11-14 16:39:43,639 Epoch: [368][310/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0447 (0.0321) Prec@1 92.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:39:44,216 Epoch: [368][320/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0246 (0.0319) Prec@1 97.000 (94.758) Prec@5 99.000 (99.909) +2022-11-14 16:39:44,777 Epoch: [368][330/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0325 (0.0319) Prec@1 94.000 (94.735) Prec@5 100.000 (99.912) +2022-11-14 16:39:45,349 Epoch: [368][340/500] Time 0.055 (0.051) Data 0.002 (0.003) Loss 0.0160 (0.0315) Prec@1 98.000 (94.829) Prec@5 100.000 (99.914) +2022-11-14 16:39:45,907 Epoch: [368][350/500] Time 0.051 (0.051) Data 0.003 (0.003) Loss 0.0309 (0.0315) Prec@1 95.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 16:39:46,485 Epoch: [368][360/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0279 (0.0314) Prec@1 95.000 (94.838) Prec@5 100.000 (99.919) +2022-11-14 16:39:47,055 Epoch: [368][370/500] Time 0.046 (0.051) Data 0.002 (0.003) Loss 0.0230 (0.0311) Prec@1 96.000 (94.868) Prec@5 100.000 (99.921) +2022-11-14 16:39:47,623 Epoch: [368][380/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0230 (0.0309) Prec@1 95.000 (94.872) Prec@5 100.000 (99.923) +2022-11-14 16:39:48,206 Epoch: [368][390/500] Time 0.049 (0.051) Data 0.003 (0.003) Loss 0.0147 (0.0305) Prec@1 96.000 (94.900) Prec@5 100.000 (99.925) +2022-11-14 16:39:48,772 Epoch: [368][400/500] Time 0.065 (0.051) Data 0.002 (0.003) Loss 0.0153 (0.0302) Prec@1 97.000 (94.951) Prec@5 100.000 (99.927) +2022-11-14 16:39:49,335 Epoch: [368][410/500] Time 0.053 (0.051) Data 0.002 (0.003) Loss 0.0283 (0.0301) Prec@1 95.000 (94.952) Prec@5 100.000 (99.929) +2022-11-14 16:39:49,930 Epoch: [368][420/500] Time 0.054 (0.051) Data 0.002 (0.003) Loss 0.0318 (0.0301) Prec@1 96.000 (94.977) Prec@5 100.000 (99.930) +2022-11-14 16:39:50,529 Epoch: [368][430/500] Time 0.058 (0.051) Data 0.002 (0.003) Loss 0.0304 (0.0302) Prec@1 96.000 (95.000) Prec@5 100.000 (99.932) +2022-11-14 16:39:51,079 Epoch: [368][440/500] Time 0.048 (0.051) Data 0.002 (0.003) Loss 0.0527 (0.0307) Prec@1 92.000 (94.933) Prec@5 100.000 (99.933) +2022-11-14 16:39:51,729 Epoch: [368][450/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0369 (0.0308) Prec@1 95.000 (94.935) Prec@5 99.000 (99.913) +2022-11-14 16:39:52,330 Epoch: [368][460/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0153 (0.0305) Prec@1 97.000 (94.979) Prec@5 100.000 (99.915) +2022-11-14 16:39:52,897 Epoch: [368][470/500] Time 0.057 (0.051) Data 0.002 (0.003) Loss 0.0252 (0.0304) Prec@1 95.000 (94.979) Prec@5 99.000 (99.896) +2022-11-14 16:39:53,438 Epoch: [368][480/500] Time 0.050 (0.051) Data 0.002 (0.003) Loss 0.0299 (0.0303) Prec@1 95.000 (94.980) Prec@5 100.000 (99.898) +2022-11-14 16:39:54,006 Epoch: [368][490/500] Time 0.052 (0.051) Data 0.002 (0.003) Loss 0.0227 (0.0302) Prec@1 96.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 16:39:54,526 Epoch: [368][499/500] Time 0.051 (0.051) Data 0.002 (0.003) Loss 0.0341 (0.0303) Prec@1 94.000 (94.980) Prec@5 100.000 (99.902) +2022-11-14 16:39:54,853 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0626 (0.0626) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:39:54,863 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0651 (0.0638) Prec@1 90.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:39:54,872 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0668) Prec@1 86.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:39:54,887 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0978 (0.0745) Prec@1 85.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 16:39:54,896 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0726) Prec@1 91.000 (88.800) Prec@5 100.000 (99.600) +2022-11-14 16:39:54,908 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0319 (0.0658) Prec@1 95.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 16:39:54,919 Test: [6/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0650) Prec@1 92.000 (90.143) Prec@5 100.000 (99.714) +2022-11-14 16:39:54,935 Test: [7/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0657) Prec@1 87.000 (89.750) Prec@5 99.000 (99.625) +2022-11-14 16:39:54,950 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0665) Prec@1 89.000 (89.667) Prec@5 99.000 (99.556) +2022-11-14 16:39:54,964 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0749 (0.0674) Prec@1 86.000 (89.300) Prec@5 98.000 (99.400) +2022-11-14 16:39:54,980 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0672) Prec@1 89.000 (89.273) Prec@5 99.000 (99.364) +2022-11-14 16:39:54,997 Test: [11/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0684) Prec@1 87.000 (89.083) Prec@5 99.000 (99.333) +2022-11-14 16:39:55,014 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0677) Prec@1 91.000 (89.231) Prec@5 100.000 (99.385) +2022-11-14 16:39:55,033 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0752 (0.0682) Prec@1 89.000 (89.214) Prec@5 99.000 (99.357) +2022-11-14 16:39:55,053 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0691) Prec@1 86.000 (89.000) Prec@5 100.000 (99.400) +2022-11-14 16:39:55,071 Test: [15/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0698 (0.0691) Prec@1 90.000 (89.062) Prec@5 98.000 (99.312) +2022-11-14 16:39:55,091 Test: [16/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0688) Prec@1 90.000 (89.118) Prec@5 98.000 (99.235) +2022-11-14 16:39:55,110 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0999 (0.0705) Prec@1 85.000 (88.889) Prec@5 100.000 (99.278) +2022-11-14 16:39:55,132 Test: [18/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1010 (0.0721) Prec@1 83.000 (88.579) Prec@5 98.000 (99.211) +2022-11-14 16:39:55,149 Test: [19/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0725) Prec@1 88.000 (88.550) Prec@5 98.000 (99.150) +2022-11-14 16:39:55,167 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0729) Prec@1 87.000 (88.476) Prec@5 99.000 (99.143) +2022-11-14 16:39:55,185 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0935 (0.0738) Prec@1 84.000 (88.273) Prec@5 99.000 (99.136) +2022-11-14 16:39:55,202 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1204 (0.0759) Prec@1 82.000 (88.000) Prec@5 98.000 (99.087) +2022-11-14 16:39:55,218 Test: [23/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0757) Prec@1 87.000 (87.958) Prec@5 100.000 (99.125) +2022-11-14 16:39:55,237 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0754) Prec@1 90.000 (88.040) Prec@5 100.000 (99.160) +2022-11-14 16:39:55,257 Test: [25/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1066 (0.0766) Prec@1 85.000 (87.923) Prec@5 98.000 (99.115) +2022-11-14 16:39:55,278 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0754) Prec@1 94.000 (88.148) Prec@5 100.000 (99.148) +2022-11-14 16:39:55,296 Test: [27/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0528 (0.0746) Prec@1 90.000 (88.214) Prec@5 99.000 (99.143) +2022-11-14 16:39:55,317 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0739) Prec@1 92.000 (88.345) Prec@5 99.000 (99.138) +2022-11-14 16:39:55,335 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0742) Prec@1 86.000 (88.267) Prec@5 99.000 (99.133) +2022-11-14 16:39:55,357 Test: [30/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0737) Prec@1 90.000 (88.323) Prec@5 100.000 (99.161) +2022-11-14 16:39:55,375 Test: [31/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0733) Prec@1 90.000 (88.375) Prec@5 99.000 (99.156) +2022-11-14 16:39:55,395 Test: [32/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0735) Prec@1 86.000 (88.303) Prec@5 100.000 (99.182) +2022-11-14 16:39:55,413 Test: [33/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0927 (0.0740) Prec@1 83.000 (88.147) Prec@5 100.000 (99.206) +2022-11-14 16:39:55,430 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0743) Prec@1 84.000 (88.029) Prec@5 99.000 (99.200) +2022-11-14 16:39:55,452 Test: [35/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0740) Prec@1 90.000 (88.083) Prec@5 98.000 (99.167) +2022-11-14 16:39:55,471 Test: [36/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0743) Prec@1 87.000 (88.054) Prec@5 99.000 (99.162) +2022-11-14 16:39:55,489 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1118 (0.0753) Prec@1 81.000 (87.868) Prec@5 100.000 (99.184) +2022-11-14 16:39:55,507 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0748) Prec@1 91.000 (87.949) Prec@5 100.000 (99.205) +2022-11-14 16:39:55,525 Test: [39/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0745) Prec@1 88.000 (87.950) Prec@5 100.000 (99.225) +2022-11-14 16:39:55,543 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0750) Prec@1 84.000 (87.854) Prec@5 98.000 (99.195) +2022-11-14 16:39:55,563 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0749) Prec@1 89.000 (87.881) Prec@5 98.000 (99.167) +2022-11-14 16:39:55,582 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0461 (0.0742) Prec@1 93.000 (88.000) Prec@5 99.000 (99.163) +2022-11-14 16:39:55,602 Test: [43/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0739) Prec@1 92.000 (88.091) Prec@5 99.000 (99.159) +2022-11-14 16:39:55,620 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0736) Prec@1 91.000 (88.156) Prec@5 99.000 (99.156) +2022-11-14 16:39:55,640 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0994 (0.0741) Prec@1 83.000 (88.043) Prec@5 100.000 (99.174) +2022-11-14 16:39:55,659 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0743) Prec@1 88.000 (88.043) Prec@5 100.000 (99.191) +2022-11-14 16:39:55,678 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0746) Prec@1 87.000 (88.021) Prec@5 98.000 (99.167) +2022-11-14 16:39:55,696 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0744) Prec@1 87.000 (88.000) Prec@5 100.000 (99.184) +2022-11-14 16:39:55,716 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1057 (0.0750) Prec@1 84.000 (87.920) Prec@5 100.000 (99.200) +2022-11-14 16:39:55,734 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0747) Prec@1 91.000 (87.980) Prec@5 99.000 (99.196) +2022-11-14 16:39:55,757 Test: [51/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0750) Prec@1 87.000 (87.962) Prec@5 100.000 (99.212) +2022-11-14 16:39:55,777 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0748) Prec@1 88.000 (87.962) Prec@5 100.000 (99.226) +2022-11-14 16:39:55,796 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0745) Prec@1 90.000 (88.000) Prec@5 100.000 (99.241) +2022-11-14 16:39:55,813 Test: [54/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0745) Prec@1 88.000 (88.000) Prec@5 100.000 (99.255) +2022-11-14 16:39:55,831 Test: [55/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0744) Prec@1 89.000 (88.018) Prec@5 99.000 (99.250) +2022-11-14 16:39:55,854 Test: [56/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0743) Prec@1 88.000 (88.018) Prec@5 100.000 (99.263) +2022-11-14 16:39:55,873 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0741) Prec@1 88.000 (88.017) Prec@5 100.000 (99.276) +2022-11-14 16:39:55,891 Test: [58/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0741) Prec@1 90.000 (88.051) Prec@5 99.000 (99.271) +2022-11-14 16:39:55,910 Test: [59/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0743) Prec@1 86.000 (88.017) Prec@5 98.000 (99.250) +2022-11-14 16:39:55,929 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0748) Prec@1 85.000 (87.967) Prec@5 100.000 (99.262) +2022-11-14 16:39:55,948 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0746) Prec@1 90.000 (88.000) Prec@5 99.000 (99.258) +2022-11-14 16:39:55,966 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0744) Prec@1 87.000 (87.984) Prec@5 100.000 (99.270) +2022-11-14 16:39:55,983 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0419 (0.0739) Prec@1 94.000 (88.078) Prec@5 99.000 (99.266) +2022-11-14 16:39:56,001 Test: [64/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0915 (0.0741) Prec@1 85.000 (88.031) Prec@5 99.000 (99.262) +2022-11-14 16:39:56,021 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0744) Prec@1 86.000 (88.000) Prec@5 99.000 (99.258) +2022-11-14 16:39:56,041 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0321 (0.0738) Prec@1 95.000 (88.104) Prec@5 100.000 (99.269) +2022-11-14 16:39:56,062 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0739) Prec@1 86.000 (88.074) Prec@5 100.000 (99.279) +2022-11-14 16:39:56,083 Test: [68/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0737) Prec@1 91.000 (88.116) Prec@5 99.000 (99.275) +2022-11-14 16:39:56,103 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0736) Prec@1 88.000 (88.114) Prec@5 98.000 (99.257) +2022-11-14 16:39:56,119 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1011 (0.0740) Prec@1 85.000 (88.070) Prec@5 98.000 (99.239) +2022-11-14 16:39:56,135 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0605 (0.0738) Prec@1 91.000 (88.111) Prec@5 99.000 (99.236) +2022-11-14 16:39:56,155 Test: [72/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0335 (0.0733) Prec@1 95.000 (88.205) Prec@5 100.000 (99.247) +2022-11-14 16:39:56,178 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0307 (0.0727) Prec@1 96.000 (88.311) Prec@5 100.000 (99.257) +2022-11-14 16:39:56,199 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0729) Prec@1 85.000 (88.267) Prec@5 100.000 (99.267) +2022-11-14 16:39:56,219 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0727) Prec@1 90.000 (88.289) Prec@5 98.000 (99.250) +2022-11-14 16:39:56,241 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0729) Prec@1 87.000 (88.273) Prec@5 98.000 (99.234) +2022-11-14 16:39:56,264 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0732) Prec@1 86.000 (88.244) Prec@5 98.000 (99.218) +2022-11-14 16:39:56,281 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0731) Prec@1 89.000 (88.253) Prec@5 100.000 (99.228) +2022-11-14 16:39:56,300 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0731) Prec@1 89.000 (88.263) Prec@5 100.000 (99.237) +2022-11-14 16:39:56,321 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0732) Prec@1 87.000 (88.247) Prec@5 100.000 (99.247) +2022-11-14 16:39:56,339 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0889 (0.0734) Prec@1 87.000 (88.232) Prec@5 100.000 (99.256) +2022-11-14 16:39:56,361 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0735) Prec@1 85.000 (88.193) Prec@5 99.000 (99.253) +2022-11-14 16:39:56,380 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0736) Prec@1 90.000 (88.214) Prec@5 99.000 (99.250) +2022-11-14 16:39:56,402 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1134 (0.0741) Prec@1 80.000 (88.118) Prec@5 100.000 (99.259) +2022-11-14 16:39:56,421 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0744) Prec@1 85.000 (88.081) Prec@5 100.000 (99.267) +2022-11-14 16:39:56,438 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0744) Prec@1 88.000 (88.080) Prec@5 100.000 (99.276) +2022-11-14 16:39:56,457 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0746) Prec@1 85.000 (88.045) Prec@5 98.000 (99.261) +2022-11-14 16:39:56,473 Test: [88/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0748) Prec@1 83.000 (87.989) Prec@5 100.000 (99.270) +2022-11-14 16:39:56,490 Test: [89/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0747) Prec@1 89.000 (88.000) Prec@5 99.000 (99.267) +2022-11-14 16:39:56,512 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0554 (0.0745) Prec@1 91.000 (88.033) Prec@5 100.000 (99.275) +2022-11-14 16:39:56,529 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0745) Prec@1 90.000 (88.054) Prec@5 99.000 (99.272) +2022-11-14 16:39:56,546 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1026 (0.0748) Prec@1 85.000 (88.022) Prec@5 99.000 (99.269) +2022-11-14 16:39:56,568 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0910 (0.0749) Prec@1 88.000 (88.021) Prec@5 98.000 (99.255) +2022-11-14 16:39:56,584 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0752) Prec@1 85.000 (87.989) Prec@5 99.000 (99.253) +2022-11-14 16:39:56,604 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0489 (0.0749) Prec@1 93.000 (88.042) Prec@5 99.000 (99.250) +2022-11-14 16:39:56,625 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0746) Prec@1 92.000 (88.082) Prec@5 99.000 (99.247) +2022-11-14 16:39:56,646 Test: [97/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0886 (0.0748) Prec@1 85.000 (88.051) Prec@5 98.000 (99.235) +2022-11-14 16:39:56,665 Test: [98/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0974 (0.0750) Prec@1 84.000 (88.010) Prec@5 100.000 (99.242) +2022-11-14 16:39:56,682 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0750) Prec@1 88.000 (88.010) Prec@5 99.000 (99.240) +2022-11-14 16:39:56,749 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:39:57,135 Epoch: [369][0/500] Time 0.024 (0.024) Data 0.290 (0.290) Loss 0.0442 (0.0442) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:39:57,617 Epoch: [369][10/500] Time 0.057 (0.041) Data 0.002 (0.028) Loss 0.0253 (0.0348) Prec@1 96.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:39:58,200 Epoch: [369][20/500] Time 0.056 (0.046) Data 0.002 (0.016) Loss 0.0296 (0.0331) Prec@1 94.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:39:58,760 Epoch: [369][30/500] Time 0.049 (0.047) Data 0.002 (0.011) Loss 0.0351 (0.0336) Prec@1 94.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:39:59,330 Epoch: [369][40/500] Time 0.058 (0.048) Data 0.002 (0.009) Loss 0.0297 (0.0328) Prec@1 95.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 16:39:59,974 Epoch: [369][50/500] Time 0.062 (0.050) Data 0.002 (0.008) Loss 0.0295 (0.0323) Prec@1 96.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 16:40:00,586 Epoch: [369][60/500] Time 0.051 (0.051) Data 0.003 (0.007) Loss 0.0653 (0.0370) Prec@1 88.000 (93.571) Prec@5 99.000 (99.714) +2022-11-14 16:40:01,151 Epoch: [369][70/500] Time 0.046 (0.051) Data 0.002 (0.006) Loss 0.0408 (0.0375) Prec@1 93.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 16:40:01,731 Epoch: [369][80/500] Time 0.056 (0.051) Data 0.002 (0.006) Loss 0.0195 (0.0355) Prec@1 98.000 (94.000) Prec@5 100.000 (99.778) +2022-11-14 16:40:02,348 Epoch: [369][90/500] Time 0.072 (0.051) Data 0.003 (0.005) Loss 0.0211 (0.0340) Prec@1 96.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 16:40:02,999 Epoch: [369][100/500] Time 0.062 (0.052) Data 0.002 (0.005) Loss 0.0329 (0.0339) Prec@1 95.000 (94.273) Prec@5 100.000 (99.818) +2022-11-14 16:40:03,572 Epoch: [369][110/500] Time 0.059 (0.052) Data 0.002 (0.005) Loss 0.0166 (0.0325) Prec@1 98.000 (94.583) Prec@5 100.000 (99.833) +2022-11-14 16:40:04,153 Epoch: [369][120/500] Time 0.056 (0.052) Data 0.002 (0.005) Loss 0.0416 (0.0332) Prec@1 93.000 (94.462) Prec@5 100.000 (99.846) +2022-11-14 16:40:04,716 Epoch: [369][130/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0182 (0.0321) Prec@1 99.000 (94.786) Prec@5 99.000 (99.786) +2022-11-14 16:40:05,423 Epoch: [369][140/500] Time 0.069 (0.053) Data 0.002 (0.004) Loss 0.0463 (0.0331) Prec@1 92.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 16:40:06,004 Epoch: [369][150/500] Time 0.058 (0.053) Data 0.002 (0.004) Loss 0.0304 (0.0329) Prec@1 95.000 (94.625) Prec@5 100.000 (99.812) +2022-11-14 16:40:06,569 Epoch: [369][160/500] Time 0.054 (0.053) Data 0.002 (0.004) Loss 0.0176 (0.0320) Prec@1 98.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:40:07,133 Epoch: [369][170/500] Time 0.055 (0.052) Data 0.002 (0.004) Loss 0.0229 (0.0315) Prec@1 95.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:40:07,709 Epoch: [369][180/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0265 (0.0312) Prec@1 96.000 (94.895) Prec@5 100.000 (99.842) +2022-11-14 16:40:08,289 Epoch: [369][190/500] Time 0.050 (0.052) Data 0.002 (0.004) Loss 0.0344 (0.0314) Prec@1 94.000 (94.850) Prec@5 100.000 (99.850) +2022-11-14 16:40:08,854 Epoch: [369][200/500] Time 0.060 (0.052) Data 0.002 (0.004) Loss 0.0202 (0.0308) Prec@1 97.000 (94.952) Prec@5 100.000 (99.857) +2022-11-14 16:40:09,429 Epoch: [369][210/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0270 (0.0307) Prec@1 94.000 (94.909) Prec@5 100.000 (99.864) +2022-11-14 16:40:10,038 Epoch: [369][220/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0357 (0.0309) Prec@1 95.000 (94.913) Prec@5 99.000 (99.826) +2022-11-14 16:40:10,605 Epoch: [369][230/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0272 (0.0307) Prec@1 95.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 16:40:11,268 Epoch: [369][240/500] Time 0.070 (0.053) Data 0.002 (0.003) Loss 0.0243 (0.0305) Prec@1 97.000 (95.000) Prec@5 100.000 (99.840) +2022-11-14 16:40:11,856 Epoch: [369][250/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0361 (0.0307) Prec@1 93.000 (94.923) Prec@5 100.000 (99.846) +2022-11-14 16:40:12,408 Epoch: [369][260/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0276 (0.0306) Prec@1 96.000 (94.963) Prec@5 99.000 (99.815) +2022-11-14 16:40:13,023 Epoch: [369][270/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0393 (0.0309) Prec@1 93.000 (94.893) Prec@5 100.000 (99.821) +2022-11-14 16:40:13,590 Epoch: [369][280/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0344 (0.0310) Prec@1 93.000 (94.828) Prec@5 100.000 (99.828) +2022-11-14 16:40:14,161 Epoch: [369][290/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0294 (0.0310) Prec@1 95.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:40:14,740 Epoch: [369][300/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0307 (0.0309) Prec@1 96.000 (94.871) Prec@5 100.000 (99.839) +2022-11-14 16:40:15,315 Epoch: [369][310/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0570 (0.0318) Prec@1 91.000 (94.750) Prec@5 100.000 (99.844) +2022-11-14 16:40:15,889 Epoch: [369][320/500] Time 0.047 (0.052) Data 0.002 (0.003) Loss 0.0381 (0.0320) Prec@1 94.000 (94.727) Prec@5 100.000 (99.848) +2022-11-14 16:40:16,557 Epoch: [369][330/500] Time 0.074 (0.053) Data 0.002 (0.003) Loss 0.0347 (0.0320) Prec@1 94.000 (94.706) Prec@5 100.000 (99.853) +2022-11-14 16:40:17,126 Epoch: [369][340/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0417 (0.0323) Prec@1 94.000 (94.686) Prec@5 100.000 (99.857) +2022-11-14 16:40:17,695 Epoch: [369][350/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0113 (0.0317) Prec@1 99.000 (94.806) Prec@5 100.000 (99.861) +2022-11-14 16:40:18,264 Epoch: [369][360/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0192 (0.0314) Prec@1 98.000 (94.892) Prec@5 100.000 (99.865) +2022-11-14 16:40:18,845 Epoch: [369][370/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0483 (0.0318) Prec@1 93.000 (94.842) Prec@5 100.000 (99.868) +2022-11-14 16:40:19,398 Epoch: [369][380/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0554 (0.0324) Prec@1 89.000 (94.692) Prec@5 100.000 (99.872) +2022-11-14 16:40:19,993 Epoch: [369][390/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0180 (0.0321) Prec@1 97.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 16:40:20,564 Epoch: [369][400/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0254 (0.0319) Prec@1 95.000 (94.756) Prec@5 100.000 (99.878) +2022-11-14 16:40:21,150 Epoch: [369][410/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0123 (0.0314) Prec@1 99.000 (94.857) Prec@5 100.000 (99.881) +2022-11-14 16:40:21,710 Epoch: [369][420/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0205 (0.0312) Prec@1 98.000 (94.930) Prec@5 100.000 (99.884) +2022-11-14 16:40:22,284 Epoch: [369][430/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0178 (0.0309) Prec@1 98.000 (95.000) Prec@5 100.000 (99.886) +2022-11-14 16:40:22,861 Epoch: [369][440/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0229 (0.0307) Prec@1 96.000 (95.022) Prec@5 100.000 (99.889) +2022-11-14 16:40:23,448 Epoch: [369][450/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0411 (0.0309) Prec@1 93.000 (94.978) Prec@5 100.000 (99.891) +2022-11-14 16:40:24,066 Epoch: [369][460/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0214 (0.0307) Prec@1 97.000 (95.021) Prec@5 100.000 (99.894) +2022-11-14 16:40:24,658 Epoch: [369][470/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0756 (0.0317) Prec@1 88.000 (94.875) Prec@5 100.000 (99.896) +2022-11-14 16:40:25,243 Epoch: [369][480/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0295 (0.0316) Prec@1 96.000 (94.898) Prec@5 99.000 (99.878) +2022-11-14 16:40:25,866 Epoch: [369][490/500] Time 0.051 (0.052) Data 0.003 (0.003) Loss 0.0273 (0.0315) Prec@1 95.000 (94.900) Prec@5 100.000 (99.880) +2022-11-14 16:40:26,451 Epoch: [369][499/500] Time 0.071 (0.052) Data 0.002 (0.003) Loss 0.0161 (0.0312) Prec@1 99.000 (94.980) Prec@5 100.000 (99.882) +2022-11-14 16:40:26,813 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0695 (0.0695) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:26,823 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0728 (0.0711) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:26,833 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0726) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:26,846 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0737 (0.0728) Prec@1 88.000 (88.000) Prec@5 99.000 (99.750) +2022-11-14 16:40:26,859 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0606 (0.0704) Prec@1 90.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 16:40:26,870 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0365 (0.0647) Prec@1 95.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 16:40:26,882 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0650) Prec@1 91.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 16:40:26,899 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0656) Prec@1 89.000 (89.625) Prec@5 100.000 (99.750) +2022-11-14 16:40:26,914 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0807 (0.0673) Prec@1 87.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 16:40:26,931 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0695) Prec@1 87.000 (89.100) Prec@5 99.000 (99.600) +2022-11-14 16:40:26,949 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0502 (0.0677) Prec@1 91.000 (89.273) Prec@5 100.000 (99.636) +2022-11-14 16:40:26,968 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0702) Prec@1 87.000 (89.083) Prec@5 100.000 (99.667) +2022-11-14 16:40:26,987 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0521 (0.0688) Prec@1 92.000 (89.308) Prec@5 100.000 (99.692) +2022-11-14 16:40:27,005 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0692) Prec@1 88.000 (89.214) Prec@5 100.000 (99.714) +2022-11-14 16:40:27,026 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0707) Prec@1 86.000 (89.000) Prec@5 100.000 (99.733) +2022-11-14 16:40:27,042 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0707) Prec@1 88.000 (88.938) Prec@5 99.000 (99.688) +2022-11-14 16:40:27,061 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0574 (0.0699) Prec@1 91.000 (89.059) Prec@5 98.000 (99.588) +2022-11-14 16:40:27,077 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0786 (0.0704) Prec@1 88.000 (89.000) Prec@5 100.000 (99.611) +2022-11-14 16:40:27,098 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0846 (0.0711) Prec@1 85.000 (88.789) Prec@5 98.000 (99.526) +2022-11-14 16:40:27,115 Test: [19/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0920 (0.0722) Prec@1 84.000 (88.550) Prec@5 98.000 (99.450) +2022-11-14 16:40:27,131 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0716) Prec@1 89.000 (88.571) Prec@5 100.000 (99.476) +2022-11-14 16:40:27,152 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0849 (0.0722) Prec@1 86.000 (88.455) Prec@5 98.000 (99.409) +2022-11-14 16:40:27,173 Test: [22/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0729) Prec@1 87.000 (88.391) Prec@5 99.000 (99.391) +2022-11-14 16:40:27,194 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0725) Prec@1 91.000 (88.500) Prec@5 100.000 (99.417) +2022-11-14 16:40:27,213 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0733) Prec@1 83.000 (88.280) Prec@5 100.000 (99.440) +2022-11-14 16:40:27,235 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0956 (0.0742) Prec@1 85.000 (88.154) Prec@5 99.000 (99.423) +2022-11-14 16:40:27,255 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0329 (0.0727) Prec@1 96.000 (88.444) Prec@5 100.000 (99.444) +2022-11-14 16:40:27,271 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0720) Prec@1 91.000 (88.536) Prec@5 99.000 (99.429) +2022-11-14 16:40:27,292 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0724) Prec@1 87.000 (88.483) Prec@5 99.000 (99.414) +2022-11-14 16:40:27,313 Test: [29/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0722) Prec@1 91.000 (88.567) Prec@5 99.000 (99.400) +2022-11-14 16:40:27,330 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0719) Prec@1 90.000 (88.613) Prec@5 98.000 (99.355) +2022-11-14 16:40:27,353 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0718) Prec@1 92.000 (88.719) Prec@5 99.000 (99.344) +2022-11-14 16:40:27,374 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0720) Prec@1 85.000 (88.606) Prec@5 100.000 (99.364) +2022-11-14 16:40:27,394 Test: [33/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0723) Prec@1 88.000 (88.588) Prec@5 100.000 (99.382) +2022-11-14 16:40:27,415 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0813 (0.0726) Prec@1 89.000 (88.600) Prec@5 98.000 (99.343) +2022-11-14 16:40:27,435 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0721) Prec@1 92.000 (88.694) Prec@5 99.000 (99.333) +2022-11-14 16:40:27,453 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0791 (0.0723) Prec@1 88.000 (88.676) Prec@5 98.000 (99.297) +2022-11-14 16:40:27,476 Test: [37/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0787 (0.0725) Prec@1 86.000 (88.605) Prec@5 99.000 (99.289) +2022-11-14 16:40:27,498 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0723) Prec@1 91.000 (88.667) Prec@5 99.000 (99.282) +2022-11-14 16:40:27,514 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0670 (0.0722) Prec@1 88.000 (88.650) Prec@5 100.000 (99.300) +2022-11-14 16:40:27,531 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0933 (0.0727) Prec@1 83.000 (88.512) Prec@5 99.000 (99.293) +2022-11-14 16:40:27,550 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0878 (0.0731) Prec@1 86.000 (88.452) Prec@5 99.000 (99.286) +2022-11-14 16:40:27,574 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0726) Prec@1 92.000 (88.535) Prec@5 99.000 (99.279) +2022-11-14 16:40:27,595 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0725) Prec@1 91.000 (88.591) Prec@5 99.000 (99.273) +2022-11-14 16:40:27,615 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0724) Prec@1 89.000 (88.600) Prec@5 99.000 (99.267) +2022-11-14 16:40:27,638 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0729) Prec@1 84.000 (88.500) Prec@5 100.000 (99.283) +2022-11-14 16:40:27,658 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0726) Prec@1 87.000 (88.468) Prec@5 100.000 (99.298) +2022-11-14 16:40:27,678 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1179 (0.0736) Prec@1 82.000 (88.333) Prec@5 100.000 (99.312) +2022-11-14 16:40:27,699 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0736) Prec@1 87.000 (88.306) Prec@5 100.000 (99.327) +2022-11-14 16:40:27,723 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1042 (0.0742) Prec@1 86.000 (88.260) Prec@5 99.000 (99.320) +2022-11-14 16:40:27,748 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0738) Prec@1 91.000 (88.314) Prec@5 99.000 (99.314) +2022-11-14 16:40:27,768 Test: [51/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0891 (0.0741) Prec@1 87.000 (88.288) Prec@5 98.000 (99.288) +2022-11-14 16:40:27,787 Test: [52/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0739) Prec@1 89.000 (88.302) Prec@5 100.000 (99.302) +2022-11-14 16:40:27,806 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0735) Prec@1 91.000 (88.352) Prec@5 100.000 (99.315) +2022-11-14 16:40:27,825 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0735) Prec@1 89.000 (88.364) Prec@5 100.000 (99.327) +2022-11-14 16:40:27,847 Test: [55/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0735) Prec@1 85.000 (88.304) Prec@5 99.000 (99.321) +2022-11-14 16:40:27,867 Test: [56/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0733) Prec@1 91.000 (88.351) Prec@5 100.000 (99.333) +2022-11-14 16:40:27,890 Test: [57/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0734) Prec@1 89.000 (88.362) Prec@5 99.000 (99.328) +2022-11-14 16:40:27,909 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0735) Prec@1 89.000 (88.373) Prec@5 100.000 (99.339) +2022-11-14 16:40:27,929 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0736) Prec@1 87.000 (88.350) Prec@5 100.000 (99.350) +2022-11-14 16:40:27,945 Test: [60/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0738) Prec@1 88.000 (88.344) Prec@5 98.000 (99.328) +2022-11-14 16:40:27,964 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0737) Prec@1 90.000 (88.371) Prec@5 100.000 (99.339) +2022-11-14 16:40:27,983 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0736) Prec@1 88.000 (88.365) Prec@5 100.000 (99.349) +2022-11-14 16:40:28,001 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0227 (0.0728) Prec@1 96.000 (88.484) Prec@5 99.000 (99.344) +2022-11-14 16:40:28,021 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0949 (0.0731) Prec@1 81.000 (88.369) Prec@5 100.000 (99.354) +2022-11-14 16:40:28,040 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0730) Prec@1 88.000 (88.364) Prec@5 99.000 (99.348) +2022-11-14 16:40:28,062 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0382 (0.0725) Prec@1 93.000 (88.433) Prec@5 99.000 (99.343) +2022-11-14 16:40:28,084 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0725) Prec@1 89.000 (88.441) Prec@5 99.000 (99.338) +2022-11-14 16:40:28,103 Test: [68/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0724) Prec@1 88.000 (88.435) Prec@5 99.000 (99.333) +2022-11-14 16:40:28,123 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0724) Prec@1 90.000 (88.457) Prec@5 100.000 (99.343) +2022-11-14 16:40:28,142 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0727) Prec@1 85.000 (88.408) Prec@5 99.000 (99.338) +2022-11-14 16:40:28,165 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0460 (0.0723) Prec@1 92.000 (88.458) Prec@5 100.000 (99.347) +2022-11-14 16:40:28,185 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0419 (0.0719) Prec@1 93.000 (88.521) Prec@5 100.000 (99.356) +2022-11-14 16:40:28,204 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0584 (0.0717) Prec@1 90.000 (88.541) Prec@5 99.000 (99.351) +2022-11-14 16:40:28,225 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0722) Prec@1 84.000 (88.480) Prec@5 99.000 (99.347) +2022-11-14 16:40:28,244 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0721) Prec@1 89.000 (88.487) Prec@5 99.000 (99.342) +2022-11-14 16:40:28,260 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0720) Prec@1 89.000 (88.494) Prec@5 99.000 (99.338) +2022-11-14 16:40:28,281 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0880 (0.0722) Prec@1 86.000 (88.462) Prec@5 99.000 (99.333) +2022-11-14 16:40:28,299 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0724) Prec@1 85.000 (88.418) Prec@5 99.000 (99.329) +2022-11-14 16:40:28,316 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0867 (0.0726) Prec@1 85.000 (88.375) Prec@5 98.000 (99.312) +2022-11-14 16:40:28,334 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1002 (0.0729) Prec@1 86.000 (88.346) Prec@5 99.000 (99.309) +2022-11-14 16:40:28,353 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0732) Prec@1 86.000 (88.317) Prec@5 99.000 (99.305) +2022-11-14 16:40:28,373 Test: [82/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0734) Prec@1 87.000 (88.301) Prec@5 99.000 (99.301) +2022-11-14 16:40:28,390 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0735) Prec@1 85.000 (88.262) Prec@5 100.000 (99.310) +2022-11-14 16:40:28,407 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0955 (0.0738) Prec@1 83.000 (88.200) Prec@5 100.000 (99.318) +2022-11-14 16:40:28,427 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1111 (0.0742) Prec@1 83.000 (88.140) Prec@5 100.000 (99.326) +2022-11-14 16:40:28,445 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0750 (0.0742) Prec@1 87.000 (88.126) Prec@5 98.000 (99.310) +2022-11-14 16:40:28,464 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0770 (0.0742) Prec@1 89.000 (88.136) Prec@5 99.000 (99.307) +2022-11-14 16:40:28,487 Test: [88/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0748 (0.0742) Prec@1 89.000 (88.146) Prec@5 99.000 (99.303) +2022-11-14 16:40:28,508 Test: [89/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0610 (0.0741) Prec@1 90.000 (88.167) Prec@5 99.000 (99.300) +2022-11-14 16:40:28,527 Test: [90/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0353 (0.0737) Prec@1 95.000 (88.242) Prec@5 100.000 (99.308) +2022-11-14 16:40:28,548 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0539 (0.0734) Prec@1 92.000 (88.283) Prec@5 100.000 (99.315) +2022-11-14 16:40:28,568 Test: [92/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0735) Prec@1 88.000 (88.280) Prec@5 100.000 (99.323) +2022-11-14 16:40:28,587 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0735) Prec@1 89.000 (88.287) Prec@5 99.000 (99.319) +2022-11-14 16:40:28,605 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0736) Prec@1 88.000 (88.284) Prec@5 100.000 (99.326) +2022-11-14 16:40:28,627 Test: [95/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0550 (0.0734) Prec@1 93.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:40:28,646 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0731) Prec@1 92.000 (88.371) Prec@5 99.000 (99.330) +2022-11-14 16:40:28,663 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0734) Prec@1 84.000 (88.327) Prec@5 98.000 (99.316) +2022-11-14 16:40:28,682 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0735) Prec@1 88.000 (88.323) Prec@5 100.000 (99.323) +2022-11-14 16:40:28,702 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0735) Prec@1 90.000 (88.340) Prec@5 100.000 (99.330) +2022-11-14 16:40:28,768 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:40:29,162 Epoch: [370][0/500] Time 0.031 (0.031) Data 0.293 (0.293) Loss 0.0337 (0.0337) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:29,678 Epoch: [370][10/500] Time 0.059 (0.045) Data 0.002 (0.028) Loss 0.0225 (0.0281) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:30,271 Epoch: [370][20/500] Time 0.052 (0.049) Data 0.002 (0.016) Loss 0.0234 (0.0266) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:40:30,852 Epoch: [370][30/500] Time 0.059 (0.050) Data 0.002 (0.011) Loss 0.0212 (0.0252) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:31,466 Epoch: [370][40/500] Time 0.057 (0.052) Data 0.002 (0.009) Loss 0.0288 (0.0259) Prec@1 94.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:40:32,062 Epoch: [370][50/500] Time 0.058 (0.052) Data 0.002 (0.008) Loss 0.0438 (0.0289) Prec@1 92.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:32,676 Epoch: [370][60/500] Time 0.058 (0.052) Data 0.002 (0.007) Loss 0.0228 (0.0280) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:40:33,285 Epoch: [370][70/500] Time 0.058 (0.053) Data 0.002 (0.006) Loss 0.0127 (0.0261) Prec@1 98.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 16:40:33,860 Epoch: [370][80/500] Time 0.058 (0.053) Data 0.002 (0.006) Loss 0.0321 (0.0268) Prec@1 94.000 (95.222) Prec@5 99.000 (99.889) +2022-11-14 16:40:34,449 Epoch: [370][90/500] Time 0.065 (0.053) Data 0.002 (0.005) Loss 0.0253 (0.0266) Prec@1 95.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:40:35,040 Epoch: [370][100/500] Time 0.060 (0.053) Data 0.002 (0.005) Loss 0.0282 (0.0268) Prec@1 94.000 (95.091) Prec@5 100.000 (99.909) +2022-11-14 16:40:35,655 Epoch: [370][110/500] Time 0.083 (0.053) Data 0.002 (0.005) Loss 0.0302 (0.0271) Prec@1 96.000 (95.167) Prec@5 100.000 (99.917) +2022-11-14 16:40:36,263 Epoch: [370][120/500] Time 0.049 (0.053) Data 0.002 (0.005) Loss 0.0213 (0.0266) Prec@1 97.000 (95.308) Prec@5 100.000 (99.923) +2022-11-14 16:40:36,838 Epoch: [370][130/500] Time 0.054 (0.053) Data 0.002 (0.004) Loss 0.0082 (0.0253) Prec@1 99.000 (95.571) Prec@5 100.000 (99.929) +2022-11-14 16:40:37,429 Epoch: [370][140/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0301 (0.0256) Prec@1 93.000 (95.400) Prec@5 100.000 (99.933) +2022-11-14 16:40:38,101 Epoch: [370][150/500] Time 0.072 (0.053) Data 0.002 (0.004) Loss 0.0291 (0.0258) Prec@1 95.000 (95.375) Prec@5 100.000 (99.938) +2022-11-14 16:40:38,675 Epoch: [370][160/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0266 (0.0259) Prec@1 97.000 (95.471) Prec@5 100.000 (99.941) +2022-11-14 16:40:39,291 Epoch: [370][170/500] Time 0.078 (0.053) Data 0.002 (0.004) Loss 0.0155 (0.0253) Prec@1 98.000 (95.611) Prec@5 100.000 (99.944) +2022-11-14 16:40:39,895 Epoch: [370][180/500] Time 0.086 (0.053) Data 0.002 (0.004) Loss 0.0283 (0.0255) Prec@1 95.000 (95.579) Prec@5 100.000 (99.947) +2022-11-14 16:40:40,488 Epoch: [370][190/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0295 (0.0257) Prec@1 95.000 (95.550) Prec@5 100.000 (99.950) +2022-11-14 16:40:41,082 Epoch: [370][200/500] Time 0.052 (0.053) Data 0.002 (0.004) Loss 0.0367 (0.0262) Prec@1 93.000 (95.429) Prec@5 99.000 (99.905) +2022-11-14 16:40:41,677 Epoch: [370][210/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0303 (0.0264) Prec@1 94.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 16:40:42,260 Epoch: [370][220/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0230 (0.0262) Prec@1 96.000 (95.391) Prec@5 100.000 (99.913) +2022-11-14 16:40:42,843 Epoch: [370][230/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0225 (0.0261) Prec@1 96.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 16:40:43,448 Epoch: [370][240/500] Time 0.068 (0.053) Data 0.002 (0.003) Loss 0.0241 (0.0260) Prec@1 96.000 (95.440) Prec@5 100.000 (99.920) +2022-11-14 16:40:44,060 Epoch: [370][250/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0351 (0.0263) Prec@1 95.000 (95.423) Prec@5 99.000 (99.885) +2022-11-14 16:40:44,686 Epoch: [370][260/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0426 (0.0269) Prec@1 92.000 (95.296) Prec@5 100.000 (99.889) +2022-11-14 16:40:45,251 Epoch: [370][270/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0313 (0.0271) Prec@1 95.000 (95.286) Prec@5 100.000 (99.893) +2022-11-14 16:40:45,896 Epoch: [370][280/500] Time 0.073 (0.053) Data 0.002 (0.003) Loss 0.0299 (0.0272) Prec@1 96.000 (95.310) Prec@5 100.000 (99.897) +2022-11-14 16:40:46,455 Epoch: [370][290/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0213 (0.0270) Prec@1 96.000 (95.333) Prec@5 99.000 (99.867) +2022-11-14 16:40:47,026 Epoch: [370][300/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0349 (0.0273) Prec@1 94.000 (95.290) Prec@5 100.000 (99.871) +2022-11-14 16:40:47,586 Epoch: [370][310/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0465 (0.0279) Prec@1 92.000 (95.188) Prec@5 100.000 (99.875) +2022-11-14 16:40:48,198 Epoch: [370][320/500] Time 0.074 (0.053) Data 0.002 (0.003) Loss 0.0251 (0.0278) Prec@1 96.000 (95.212) Prec@5 100.000 (99.879) +2022-11-14 16:40:48,889 Epoch: [370][330/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0332 (0.0279) Prec@1 94.000 (95.176) Prec@5 100.000 (99.882) +2022-11-14 16:40:49,514 Epoch: [370][340/500] Time 0.055 (0.054) Data 0.002 (0.003) Loss 0.0643 (0.0290) Prec@1 87.000 (94.943) Prec@5 99.000 (99.857) +2022-11-14 16:40:50,134 Epoch: [370][350/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0158 (0.0286) Prec@1 96.000 (94.972) Prec@5 100.000 (99.861) +2022-11-14 16:40:50,810 Epoch: [370][360/500] Time 0.074 (0.054) Data 0.002 (0.003) Loss 0.0478 (0.0291) Prec@1 92.000 (94.892) Prec@5 100.000 (99.865) +2022-11-14 16:40:51,537 Epoch: [370][370/500] Time 0.073 (0.054) Data 0.003 (0.003) Loss 0.0345 (0.0293) Prec@1 95.000 (94.895) Prec@5 100.000 (99.868) +2022-11-14 16:40:52,378 Epoch: [370][380/500] Time 0.065 (0.055) Data 0.002 (0.003) Loss 0.0283 (0.0292) Prec@1 93.000 (94.846) Prec@5 100.000 (99.872) +2022-11-14 16:40:53,124 Epoch: [370][390/500] Time 0.058 (0.055) Data 0.002 (0.003) Loss 0.0395 (0.0295) Prec@1 94.000 (94.825) Prec@5 99.000 (99.850) +2022-11-14 16:40:53,983 Epoch: [370][400/500] Time 0.073 (0.056) Data 0.002 (0.003) Loss 0.0346 (0.0296) Prec@1 93.000 (94.780) Prec@5 100.000 (99.854) +2022-11-14 16:40:54,753 Epoch: [370][410/500] Time 0.077 (0.056) Data 0.002 (0.003) Loss 0.0378 (0.0298) Prec@1 92.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:40:55,517 Epoch: [370][420/500] Time 0.074 (0.056) Data 0.003 (0.003) Loss 0.0455 (0.0302) Prec@1 93.000 (94.674) Prec@5 99.000 (99.837) +2022-11-14 16:40:56,306 Epoch: [370][430/500] Time 0.084 (0.057) Data 0.002 (0.003) Loss 0.0235 (0.0300) Prec@1 97.000 (94.727) Prec@5 100.000 (99.841) +2022-11-14 16:40:57,231 Epoch: [370][440/500] Time 0.079 (0.057) Data 0.002 (0.003) Loss 0.0383 (0.0302) Prec@1 94.000 (94.711) Prec@5 100.000 (99.844) +2022-11-14 16:40:57,993 Epoch: [370][450/500] Time 0.074 (0.057) Data 0.002 (0.003) Loss 0.0419 (0.0305) Prec@1 92.000 (94.652) Prec@5 99.000 (99.826) +2022-11-14 16:40:58,789 Epoch: [370][460/500] Time 0.079 (0.058) Data 0.002 (0.003) Loss 0.0237 (0.0303) Prec@1 95.000 (94.660) Prec@5 100.000 (99.830) +2022-11-14 16:40:59,700 Epoch: [370][470/500] Time 0.113 (0.058) Data 0.002 (0.003) Loss 0.0186 (0.0301) Prec@1 98.000 (94.729) Prec@5 100.000 (99.833) +2022-11-14 16:41:00,483 Epoch: [370][480/500] Time 0.070 (0.058) Data 0.002 (0.003) Loss 0.0239 (0.0300) Prec@1 97.000 (94.776) Prec@5 100.000 (99.837) +2022-11-14 16:41:01,316 Epoch: [370][490/500] Time 0.077 (0.059) Data 0.003 (0.003) Loss 0.0510 (0.0304) Prec@1 90.000 (94.680) Prec@5 99.000 (99.820) +2022-11-14 16:41:01,966 Epoch: [370][499/500] Time 0.067 (0.059) Data 0.002 (0.003) Loss 0.0354 (0.0305) Prec@1 93.000 (94.647) Prec@5 100.000 (99.824) +2022-11-14 16:41:02,317 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0750 (0.0750) Prec@1 87.000 (87.000) Prec@5 98.000 (98.000) +2022-11-14 16:41:02,350 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0492 (0.0621) Prec@1 94.000 (90.500) Prec@5 99.000 (98.500) +2022-11-14 16:41:02,383 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0673) Prec@1 87.000 (89.333) Prec@5 100.000 (99.000) +2022-11-14 16:41:02,421 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0897 (0.0729) Prec@1 85.000 (88.250) Prec@5 98.000 (98.750) +2022-11-14 16:41:02,455 Test: [4/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0772) Prec@1 83.000 (87.200) Prec@5 99.000 (98.800) +2022-11-14 16:41:02,486 Test: [5/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0358 (0.0703) Prec@1 95.000 (88.500) Prec@5 100.000 (99.000) +2022-11-14 16:41:02,519 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0708) Prec@1 90.000 (88.714) Prec@5 100.000 (99.143) +2022-11-14 16:41:02,571 Test: [7/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0859 (0.0727) Prec@1 89.000 (88.750) Prec@5 100.000 (99.250) +2022-11-14 16:41:02,626 Test: [8/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0743) Prec@1 86.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 16:41:02,678 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0725 (0.0741) Prec@1 88.000 (88.400) Prec@5 98.000 (99.100) +2022-11-14 16:41:02,730 Test: [10/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0415 (0.0712) Prec@1 93.000 (88.818) Prec@5 100.000 (99.182) +2022-11-14 16:41:02,781 Test: [11/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0779 (0.0717) Prec@1 90.000 (88.917) Prec@5 100.000 (99.250) +2022-11-14 16:41:02,830 Test: [12/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0493 (0.0700) Prec@1 92.000 (89.154) Prec@5 100.000 (99.308) +2022-11-14 16:41:02,882 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0694 (0.0700) Prec@1 89.000 (89.143) Prec@5 98.000 (99.214) +2022-11-14 16:41:02,930 Test: [14/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0742 (0.0702) Prec@1 88.000 (89.067) Prec@5 99.000 (99.200) +2022-11-14 16:41:02,967 Test: [15/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0630 (0.0698) Prec@1 90.000 (89.125) Prec@5 100.000 (99.250) +2022-11-14 16:41:03,000 Test: [16/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0502 (0.0686) Prec@1 93.000 (89.353) Prec@5 98.000 (99.176) +2022-11-14 16:41:03,032 Test: [17/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.1088 (0.0709) Prec@1 82.000 (88.944) Prec@5 100.000 (99.222) +2022-11-14 16:41:03,068 Test: [18/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0872 (0.0717) Prec@1 86.000 (88.789) Prec@5 100.000 (99.263) +2022-11-14 16:41:03,103 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0863 (0.0724) Prec@1 87.000 (88.700) Prec@5 96.000 (99.100) +2022-11-14 16:41:03,133 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0730) Prec@1 88.000 (88.667) Prec@5 99.000 (99.095) +2022-11-14 16:41:03,165 Test: [21/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0733) Prec@1 87.000 (88.591) Prec@5 100.000 (99.136) +2022-11-14 16:41:03,192 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.0744) Prec@1 85.000 (88.435) Prec@5 99.000 (99.130) +2022-11-14 16:41:03,228 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0741) Prec@1 88.000 (88.417) Prec@5 100.000 (99.167) +2022-11-14 16:41:03,266 Test: [24/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0731 (0.0740) Prec@1 88.000 (88.400) Prec@5 100.000 (99.200) +2022-11-14 16:41:03,300 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1056 (0.0752) Prec@1 82.000 (88.154) Prec@5 98.000 (99.154) +2022-11-14 16:41:03,338 Test: [26/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0746) Prec@1 93.000 (88.333) Prec@5 100.000 (99.185) +2022-11-14 16:41:03,363 Test: [27/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0621 (0.0742) Prec@1 89.000 (88.357) Prec@5 100.000 (99.214) +2022-11-14 16:41:03,400 Test: [28/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0594 (0.0737) Prec@1 89.000 (88.379) Prec@5 99.000 (99.207) +2022-11-14 16:41:03,439 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0741) Prec@1 85.000 (88.267) Prec@5 98.000 (99.167) +2022-11-14 16:41:03,471 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0738) Prec@1 88.000 (88.258) Prec@5 100.000 (99.194) +2022-11-14 16:41:03,505 Test: [31/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0639 (0.0735) Prec@1 90.000 (88.312) Prec@5 99.000 (99.188) +2022-11-14 16:41:03,532 Test: [32/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0678 (0.0734) Prec@1 91.000 (88.394) Prec@5 100.000 (99.212) +2022-11-14 16:41:03,566 Test: [33/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1021 (0.0742) Prec@1 82.000 (88.206) Prec@5 100.000 (99.235) +2022-11-14 16:41:03,596 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0742) Prec@1 90.000 (88.257) Prec@5 97.000 (99.171) +2022-11-14 16:41:03,632 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 90.000 (88.306) Prec@5 99.000 (99.167) +2022-11-14 16:41:03,667 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0740) Prec@1 90.000 (88.351) Prec@5 99.000 (99.162) +2022-11-14 16:41:03,702 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0745) Prec@1 82.000 (88.184) Prec@5 100.000 (99.184) +2022-11-14 16:41:03,735 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0527 (0.0740) Prec@1 94.000 (88.333) Prec@5 100.000 (99.205) +2022-11-14 16:41:03,762 Test: [39/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0737) Prec@1 89.000 (88.350) Prec@5 100.000 (99.225) +2022-11-14 16:41:03,793 Test: [40/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0738) Prec@1 88.000 (88.341) Prec@5 99.000 (99.220) +2022-11-14 16:41:03,822 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0736) Prec@1 90.000 (88.381) Prec@5 100.000 (99.238) +2022-11-14 16:41:03,856 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0439 (0.0729) Prec@1 92.000 (88.465) Prec@5 100.000 (99.256) +2022-11-14 16:41:03,893 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0732) Prec@1 86.000 (88.409) Prec@5 97.000 (99.205) +2022-11-14 16:41:03,929 Test: [44/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0557 (0.0728) Prec@1 90.000 (88.444) Prec@5 99.000 (99.200) +2022-11-14 16:41:03,961 Test: [45/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0904 (0.0732) Prec@1 85.000 (88.370) Prec@5 99.000 (99.196) +2022-11-14 16:41:03,998 Test: [46/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0735) Prec@1 88.000 (88.362) Prec@5 100.000 (99.213) +2022-11-14 16:41:04,029 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0997 (0.0740) Prec@1 83.000 (88.250) Prec@5 98.000 (99.188) +2022-11-14 16:41:04,062 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0737) Prec@1 89.000 (88.265) Prec@5 100.000 (99.204) +2022-11-14 16:41:04,097 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1054 (0.0743) Prec@1 83.000 (88.160) Prec@5 100.000 (99.220) +2022-11-14 16:41:04,133 Test: [50/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0547 (0.0739) Prec@1 91.000 (88.216) Prec@5 100.000 (99.235) +2022-11-14 16:41:04,162 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0676 (0.0738) Prec@1 91.000 (88.269) Prec@5 99.000 (99.231) +2022-11-14 16:41:04,197 Test: [52/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0737) Prec@1 90.000 (88.302) Prec@5 99.000 (99.226) +2022-11-14 16:41:04,230 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0735) Prec@1 88.000 (88.296) Prec@5 100.000 (99.241) +2022-11-14 16:41:04,266 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0734) Prec@1 88.000 (88.291) Prec@5 100.000 (99.255) +2022-11-14 16:41:04,303 Test: [55/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0667 (0.0732) Prec@1 90.000 (88.321) Prec@5 99.000 (99.250) +2022-11-14 16:41:04,330 Test: [56/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0677 (0.0732) Prec@1 88.000 (88.316) Prec@5 100.000 (99.263) +2022-11-14 16:41:04,365 Test: [57/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0732) Prec@1 87.000 (88.293) Prec@5 98.000 (99.241) +2022-11-14 16:41:04,398 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1086 (0.0738) Prec@1 83.000 (88.203) Prec@5 100.000 (99.254) +2022-11-14 16:41:04,435 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0695 (0.0738) Prec@1 89.000 (88.217) Prec@5 100.000 (99.267) +2022-11-14 16:41:04,467 Test: [60/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0857 (0.0740) Prec@1 86.000 (88.180) Prec@5 100.000 (99.279) +2022-11-14 16:41:04,505 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0741) Prec@1 88.000 (88.177) Prec@5 97.000 (99.242) +2022-11-14 16:41:04,539 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0739) Prec@1 91.000 (88.222) Prec@5 100.000 (99.254) +2022-11-14 16:41:04,569 Test: [63/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0316 (0.0733) Prec@1 94.000 (88.312) Prec@5 99.000 (99.250) +2022-11-14 16:41:04,596 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1017 (0.0737) Prec@1 83.000 (88.231) Prec@5 98.000 (99.231) +2022-11-14 16:41:04,629 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0674 (0.0736) Prec@1 89.000 (88.242) Prec@5 100.000 (99.242) +2022-11-14 16:41:04,663 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0380 (0.0731) Prec@1 92.000 (88.299) Prec@5 100.000 (99.254) +2022-11-14 16:41:04,695 Test: [67/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0673 (0.0730) Prec@1 88.000 (88.294) Prec@5 98.000 (99.235) +2022-11-14 16:41:04,731 Test: [68/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0604 (0.0728) Prec@1 90.000 (88.319) Prec@5 100.000 (99.246) +2022-11-14 16:41:04,763 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0729) Prec@1 89.000 (88.329) Prec@5 97.000 (99.214) +2022-11-14 16:41:04,797 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1012 (0.0733) Prec@1 86.000 (88.296) Prec@5 99.000 (99.211) +2022-11-14 16:41:04,828 Test: [71/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0733) Prec@1 88.000 (88.292) Prec@5 100.000 (99.222) +2022-11-14 16:41:04,862 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0422 (0.0728) Prec@1 93.000 (88.356) Prec@5 99.000 (99.219) +2022-11-14 16:41:04,898 Test: [73/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0528 (0.0726) Prec@1 90.000 (88.378) Prec@5 100.000 (99.230) +2022-11-14 16:41:04,931 Test: [74/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0831 (0.0727) Prec@1 86.000 (88.347) Prec@5 100.000 (99.240) +2022-11-14 16:41:04,962 Test: [75/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0726) Prec@1 89.000 (88.355) Prec@5 99.000 (99.237) +2022-11-14 16:41:04,994 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0546 (0.0724) Prec@1 91.000 (88.390) Prec@5 98.000 (99.221) +2022-11-14 16:41:05,028 Test: [77/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1079 (0.0728) Prec@1 84.000 (88.333) Prec@5 96.000 (99.179) +2022-11-14 16:41:05,060 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0981 (0.0732) Prec@1 86.000 (88.304) Prec@5 100.000 (99.190) +2022-11-14 16:41:05,091 Test: [79/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0665 (0.0731) Prec@1 92.000 (88.350) Prec@5 100.000 (99.200) +2022-11-14 16:41:05,126 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0930 (0.0733) Prec@1 86.000 (88.321) Prec@5 100.000 (99.210) +2022-11-14 16:41:05,160 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0735) Prec@1 85.000 (88.280) Prec@5 100.000 (99.220) +2022-11-14 16:41:05,192 Test: [82/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0952 (0.0737) Prec@1 85.000 (88.241) Prec@5 98.000 (99.205) +2022-11-14 16:41:05,227 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0534 (0.0735) Prec@1 91.000 (88.274) Prec@5 99.000 (99.202) +2022-11-14 16:41:05,263 Test: [84/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1004 (0.0738) Prec@1 85.000 (88.235) Prec@5 99.000 (99.200) +2022-11-14 16:41:05,299 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1062 (0.0742) Prec@1 82.000 (88.163) Prec@5 100.000 (99.209) +2022-11-14 16:41:05,334 Test: [86/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0765 (0.0742) Prec@1 89.000 (88.172) Prec@5 98.000 (99.195) +2022-11-14 16:41:05,368 Test: [87/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0856 (0.0743) Prec@1 85.000 (88.136) Prec@5 98.000 (99.182) +2022-11-14 16:41:05,405 Test: [88/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0741) Prec@1 91.000 (88.169) Prec@5 99.000 (99.180) +2022-11-14 16:41:05,435 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0741) Prec@1 90.000 (88.189) Prec@5 97.000 (99.156) +2022-11-14 16:41:05,471 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0739) Prec@1 90.000 (88.209) Prec@5 100.000 (99.165) +2022-11-14 16:41:05,504 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0738) Prec@1 90.000 (88.228) Prec@5 99.000 (99.163) +2022-11-14 16:41:05,539 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0819 (0.0739) Prec@1 89.000 (88.237) Prec@5 100.000 (99.172) +2022-11-14 16:41:05,577 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0800 (0.0740) Prec@1 87.000 (88.223) Prec@5 98.000 (99.160) +2022-11-14 16:41:05,610 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0742) Prec@1 85.000 (88.189) Prec@5 100.000 (99.168) +2022-11-14 16:41:05,642 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0741) Prec@1 90.000 (88.208) Prec@5 99.000 (99.167) +2022-11-14 16:41:05,677 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0738) Prec@1 93.000 (88.258) Prec@5 98.000 (99.155) +2022-11-14 16:41:05,717 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0738) Prec@1 89.000 (88.265) Prec@5 99.000 (99.153) +2022-11-14 16:41:05,752 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0739) Prec@1 87.000 (88.253) Prec@5 99.000 (99.152) +2022-11-14 16:41:05,786 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0741) Prec@1 83.000 (88.200) Prec@5 100.000 (99.160) +2022-11-14 16:41:05,859 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:41:06,224 Epoch: [371][0/500] Time 0.023 (0.023) Data 0.272 (0.272) Loss 0.0255 (0.0255) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:06,600 Epoch: [371][10/500] Time 0.046 (0.033) Data 0.002 (0.026) Loss 0.0406 (0.0330) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:07,017 Epoch: [371][20/500] Time 0.036 (0.035) Data 0.002 (0.015) Loss 0.0113 (0.0258) Prec@1 98.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:41:07,451 Epoch: [371][30/500] Time 0.041 (0.036) Data 0.002 (0.011) Loss 0.0454 (0.0307) Prec@1 91.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 16:41:07,878 Epoch: [371][40/500] Time 0.043 (0.036) Data 0.002 (0.009) Loss 0.0240 (0.0294) Prec@1 96.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 16:41:08,311 Epoch: [371][50/500] Time 0.040 (0.037) Data 0.002 (0.007) Loss 0.0410 (0.0313) Prec@1 91.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:08,742 Epoch: [371][60/500] Time 0.044 (0.037) Data 0.002 (0.007) Loss 0.0297 (0.0311) Prec@1 95.000 (94.143) Prec@5 100.000 (100.000) +2022-11-14 16:41:09,178 Epoch: [371][70/500] Time 0.043 (0.037) Data 0.002 (0.006) Loss 0.0242 (0.0302) Prec@1 95.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 16:41:09,609 Epoch: [371][80/500] Time 0.045 (0.038) Data 0.002 (0.005) Loss 0.0274 (0.0299) Prec@1 95.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:41:10,056 Epoch: [371][90/500] Time 0.051 (0.038) Data 0.002 (0.005) Loss 0.0333 (0.0302) Prec@1 95.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:41:10,494 Epoch: [371][100/500] Time 0.039 (0.038) Data 0.002 (0.005) Loss 0.0170 (0.0290) Prec@1 97.000 (94.636) Prec@5 100.000 (100.000) +2022-11-14 16:41:10,914 Epoch: [371][110/500] Time 0.026 (0.038) Data 0.002 (0.004) Loss 0.0289 (0.0290) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:41:11,364 Epoch: [371][120/500] Time 0.037 (0.038) Data 0.002 (0.004) Loss 0.0292 (0.0290) Prec@1 94.000 (94.462) Prec@5 100.000 (100.000) +2022-11-14 16:41:11,799 Epoch: [371][130/500] Time 0.043 (0.038) Data 0.002 (0.004) Loss 0.0179 (0.0282) Prec@1 97.000 (94.643) Prec@5 100.000 (100.000) +2022-11-14 16:41:12,220 Epoch: [371][140/500] Time 0.041 (0.038) Data 0.002 (0.004) Loss 0.0279 (0.0282) Prec@1 94.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 16:41:12,670 Epoch: [371][150/500] Time 0.045 (0.038) Data 0.002 (0.004) Loss 0.0419 (0.0291) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:41:13,269 Epoch: [371][160/500] Time 0.072 (0.039) Data 0.002 (0.004) Loss 0.0271 (0.0290) Prec@1 95.000 (94.529) Prec@5 100.000 (100.000) +2022-11-14 16:41:14,010 Epoch: [371][170/500] Time 0.070 (0.041) Data 0.002 (0.004) Loss 0.0126 (0.0281) Prec@1 98.000 (94.722) Prec@5 100.000 (100.000) +2022-11-14 16:41:14,783 Epoch: [371][180/500] Time 0.076 (0.042) Data 0.002 (0.004) Loss 0.0401 (0.0287) Prec@1 93.000 (94.632) Prec@5 99.000 (99.947) +2022-11-14 16:41:15,660 Epoch: [371][190/500] Time 0.079 (0.044) Data 0.002 (0.003) Loss 0.0363 (0.0291) Prec@1 93.000 (94.550) Prec@5 100.000 (99.950) +2022-11-14 16:41:16,459 Epoch: [371][200/500] Time 0.066 (0.045) Data 0.002 (0.003) Loss 0.0227 (0.0288) Prec@1 96.000 (94.619) Prec@5 100.000 (99.952) +2022-11-14 16:41:17,242 Epoch: [371][210/500] Time 0.076 (0.047) Data 0.003 (0.003) Loss 0.0287 (0.0288) Prec@1 95.000 (94.636) Prec@5 100.000 (99.955) +2022-11-14 16:41:18,082 Epoch: [371][220/500] Time 0.075 (0.048) Data 0.002 (0.003) Loss 0.0406 (0.0293) Prec@1 95.000 (94.652) Prec@5 100.000 (99.957) +2022-11-14 16:41:18,990 Epoch: [371][230/500] Time 0.080 (0.049) Data 0.002 (0.003) Loss 0.0349 (0.0295) Prec@1 96.000 (94.708) Prec@5 100.000 (99.958) +2022-11-14 16:41:19,955 Epoch: [371][240/500] Time 0.117 (0.051) Data 0.002 (0.003) Loss 0.0294 (0.0295) Prec@1 95.000 (94.720) Prec@5 100.000 (99.960) +2022-11-14 16:41:21,223 Epoch: [371][250/500] Time 0.146 (0.053) Data 0.002 (0.003) Loss 0.0333 (0.0297) Prec@1 93.000 (94.654) Prec@5 100.000 (99.962) +2022-11-14 16:41:22,437 Epoch: [371][260/500] Time 0.100 (0.055) Data 0.002 (0.003) Loss 0.0441 (0.0302) Prec@1 92.000 (94.556) Prec@5 100.000 (99.963) +2022-11-14 16:41:23,472 Epoch: [371][270/500] Time 0.070 (0.057) Data 0.002 (0.003) Loss 0.0185 (0.0298) Prec@1 98.000 (94.679) Prec@5 100.000 (99.964) +2022-11-14 16:41:24,615 Epoch: [371][280/500] Time 0.137 (0.058) Data 0.002 (0.003) Loss 0.0354 (0.0300) Prec@1 94.000 (94.655) Prec@5 100.000 (99.966) +2022-11-14 16:41:25,825 Epoch: [371][290/500] Time 0.142 (0.060) Data 0.002 (0.003) Loss 0.0376 (0.0302) Prec@1 94.000 (94.633) Prec@5 100.000 (99.967) +2022-11-14 16:41:26,683 Epoch: [371][300/500] Time 0.102 (0.061) Data 0.002 (0.003) Loss 0.0263 (0.0301) Prec@1 96.000 (94.677) Prec@5 99.000 (99.935) +2022-11-14 16:41:27,720 Epoch: [371][310/500] Time 0.078 (0.062) Data 0.002 (0.003) Loss 0.0331 (0.0302) Prec@1 93.000 (94.625) Prec@5 100.000 (99.938) +2022-11-14 16:41:28,650 Epoch: [371][320/500] Time 0.075 (0.062) Data 0.002 (0.003) Loss 0.0394 (0.0305) Prec@1 92.000 (94.545) Prec@5 99.000 (99.909) +2022-11-14 16:41:29,548 Epoch: [371][330/500] Time 0.117 (0.063) Data 0.002 (0.003) Loss 0.0256 (0.0303) Prec@1 97.000 (94.618) Prec@5 100.000 (99.912) +2022-11-14 16:41:30,648 Epoch: [371][340/500] Time 0.075 (0.064) Data 0.002 (0.003) Loss 0.0447 (0.0307) Prec@1 93.000 (94.571) Prec@5 99.000 (99.886) +2022-11-14 16:41:31,302 Epoch: [371][350/500] Time 0.050 (0.064) Data 0.002 (0.003) Loss 0.0474 (0.0312) Prec@1 93.000 (94.528) Prec@5 99.000 (99.861) +2022-11-14 16:41:31,782 Epoch: [371][360/500] Time 0.043 (0.063) Data 0.002 (0.003) Loss 0.0368 (0.0313) Prec@1 94.000 (94.514) Prec@5 100.000 (99.865) +2022-11-14 16:41:32,247 Epoch: [371][370/500] Time 0.037 (0.063) Data 0.002 (0.003) Loss 0.0334 (0.0314) Prec@1 95.000 (94.526) Prec@5 100.000 (99.868) +2022-11-14 16:41:32,746 Epoch: [371][380/500] Time 0.049 (0.062) Data 0.002 (0.003) Loss 0.0388 (0.0316) Prec@1 92.000 (94.462) Prec@5 100.000 (99.872) +2022-11-14 16:41:33,222 Epoch: [371][390/500] Time 0.046 (0.062) Data 0.002 (0.003) Loss 0.0154 (0.0312) Prec@1 98.000 (94.550) Prec@5 100.000 (99.875) +2022-11-14 16:41:33,737 Epoch: [371][400/500] Time 0.044 (0.061) Data 0.002 (0.003) Loss 0.0167 (0.0308) Prec@1 97.000 (94.610) Prec@5 100.000 (99.878) +2022-11-14 16:41:34,268 Epoch: [371][410/500] Time 0.047 (0.061) Data 0.002 (0.003) Loss 0.0469 (0.0312) Prec@1 92.000 (94.548) Prec@5 100.000 (99.881) +2022-11-14 16:41:34,785 Epoch: [371][420/500] Time 0.054 (0.061) Data 0.002 (0.003) Loss 0.0170 (0.0309) Prec@1 98.000 (94.628) Prec@5 100.000 (99.884) +2022-11-14 16:41:35,316 Epoch: [371][430/500] Time 0.053 (0.060) Data 0.002 (0.003) Loss 0.0449 (0.0312) Prec@1 92.000 (94.568) Prec@5 100.000 (99.886) +2022-11-14 16:41:35,893 Epoch: [371][440/500] Time 0.044 (0.060) Data 0.002 (0.003) Loss 0.0505 (0.0316) Prec@1 92.000 (94.511) Prec@5 100.000 (99.889) +2022-11-14 16:41:36,461 Epoch: [371][450/500] Time 0.055 (0.060) Data 0.003 (0.003) Loss 0.0381 (0.0318) Prec@1 93.000 (94.478) Prec@5 100.000 (99.891) +2022-11-14 16:41:36,991 Epoch: [371][460/500] Time 0.039 (0.060) Data 0.002 (0.003) Loss 0.0278 (0.0317) Prec@1 95.000 (94.489) Prec@5 100.000 (99.894) +2022-11-14 16:41:37,467 Epoch: [371][470/500] Time 0.036 (0.059) Data 0.002 (0.003) Loss 0.0165 (0.0314) Prec@1 96.000 (94.521) Prec@5 100.000 (99.896) +2022-11-14 16:41:37,961 Epoch: [371][480/500] Time 0.050 (0.059) Data 0.002 (0.003) Loss 0.0431 (0.0316) Prec@1 93.000 (94.490) Prec@5 100.000 (99.898) +2022-11-14 16:41:38,474 Epoch: [371][490/500] Time 0.053 (0.059) Data 0.002 (0.003) Loss 0.0144 (0.0313) Prec@1 98.000 (94.560) Prec@5 100.000 (99.900) +2022-11-14 16:41:38,934 Epoch: [371][499/500] Time 0.048 (0.059) Data 0.002 (0.003) Loss 0.0332 (0.0313) Prec@1 93.000 (94.529) Prec@5 100.000 (99.902) +2022-11-14 16:41:39,308 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0672 (0.0672) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:39,319 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0606 (0.0639) Prec@1 93.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:41:39,330 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0698 (0.0659) Prec@1 89.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:41:39,349 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0755 (0.0683) Prec@1 88.000 (90.000) Prec@5 99.000 (99.750) +2022-11-14 16:41:39,363 Test: [4/100] Model Time 0.013 (0.010) Loss Time 0.000 (0.000) Loss 0.0845 (0.0715) Prec@1 86.000 (89.200) Prec@5 99.000 (99.600) +2022-11-14 16:41:39,378 Test: [5/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0370 (0.0658) Prec@1 94.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 16:41:39,395 Test: [6/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0655 (0.0657) Prec@1 90.000 (90.000) Prec@5 100.000 (99.714) +2022-11-14 16:41:39,416 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0783 (0.0673) Prec@1 85.000 (89.375) Prec@5 100.000 (99.750) +2022-11-14 16:41:39,434 Test: [8/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0780 (0.0685) Prec@1 89.000 (89.333) Prec@5 99.000 (99.667) +2022-11-14 16:41:39,452 Test: [9/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0876 (0.0704) Prec@1 87.000 (89.100) Prec@5 98.000 (99.500) +2022-11-14 16:41:39,470 Test: [10/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0601 (0.0695) Prec@1 92.000 (89.364) Prec@5 100.000 (99.545) +2022-11-14 16:41:39,487 Test: [11/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0663 (0.0692) Prec@1 91.000 (89.500) Prec@5 100.000 (99.583) +2022-11-14 16:41:39,506 Test: [12/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0670 (0.0690) Prec@1 87.000 (89.308) Prec@5 100.000 (99.615) +2022-11-14 16:41:39,526 Test: [13/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0644 (0.0687) Prec@1 91.000 (89.429) Prec@5 100.000 (99.643) +2022-11-14 16:41:39,546 Test: [14/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0607 (0.0682) Prec@1 91.000 (89.533) Prec@5 100.000 (99.667) +2022-11-14 16:41:39,568 Test: [15/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0793 (0.0689) Prec@1 86.000 (89.312) Prec@5 99.000 (99.625) +2022-11-14 16:41:39,587 Test: [16/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0677 (0.0688) Prec@1 89.000 (89.294) Prec@5 97.000 (99.471) +2022-11-14 16:41:39,608 Test: [17/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1201 (0.0717) Prec@1 83.000 (88.944) Prec@5 100.000 (99.500) +2022-11-14 16:41:39,629 Test: [18/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1014 (0.0732) Prec@1 84.000 (88.684) Prec@5 99.000 (99.474) +2022-11-14 16:41:39,652 Test: [19/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.1009 (0.0746) Prec@1 84.000 (88.450) Prec@5 100.000 (99.500) +2022-11-14 16:41:39,672 Test: [20/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0777 (0.0748) Prec@1 87.000 (88.381) Prec@5 100.000 (99.524) +2022-11-14 16:41:39,691 Test: [21/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0815 (0.0751) Prec@1 85.000 (88.227) Prec@5 99.000 (99.500) +2022-11-14 16:41:39,713 Test: [22/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0845 (0.0755) Prec@1 87.000 (88.174) Prec@5 98.000 (99.435) +2022-11-14 16:41:39,730 Test: [23/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0791 (0.0756) Prec@1 87.000 (88.125) Prec@5 100.000 (99.458) +2022-11-14 16:41:39,752 Test: [24/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0789 (0.0758) Prec@1 87.000 (88.080) Prec@5 100.000 (99.480) +2022-11-14 16:41:39,775 Test: [25/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0874 (0.0762) Prec@1 88.000 (88.077) Prec@5 99.000 (99.462) +2022-11-14 16:41:39,797 Test: [26/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0540 (0.0754) Prec@1 93.000 (88.259) Prec@5 100.000 (99.481) +2022-11-14 16:41:39,816 Test: [27/100] Model Time 0.015 (0.011) Loss Time 0.000 (0.000) Loss 0.0835 (0.0757) Prec@1 88.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 16:41:39,834 Test: [28/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0749 (0.0756) Prec@1 88.000 (88.241) Prec@5 99.000 (99.483) +2022-11-14 16:41:39,850 Test: [29/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0767 (0.0757) Prec@1 87.000 (88.200) Prec@5 100.000 (99.500) +2022-11-14 16:41:39,867 Test: [30/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0651 (0.0753) Prec@1 88.000 (88.194) Prec@5 100.000 (99.516) +2022-11-14 16:41:39,884 Test: [31/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0603 (0.0749) Prec@1 89.000 (88.219) Prec@5 98.000 (99.469) +2022-11-14 16:41:39,902 Test: [32/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0709 (0.0747) Prec@1 89.000 (88.242) Prec@5 100.000 (99.485) +2022-11-14 16:41:39,920 Test: [33/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0927 (0.0753) Prec@1 85.000 (88.147) Prec@5 99.000 (99.471) +2022-11-14 16:41:39,939 Test: [34/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0780 (0.0754) Prec@1 89.000 (88.171) Prec@5 98.000 (99.429) +2022-11-14 16:41:39,956 Test: [35/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0650 (0.0751) Prec@1 90.000 (88.222) Prec@5 99.000 (99.417) +2022-11-14 16:41:39,971 Test: [36/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0776 (0.0751) Prec@1 87.000 (88.189) Prec@5 98.000 (99.378) +2022-11-14 16:41:39,987 Test: [37/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1127 (0.0761) Prec@1 82.000 (88.026) Prec@5 99.000 (99.368) +2022-11-14 16:41:40,003 Test: [38/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0475 (0.0754) Prec@1 95.000 (88.205) Prec@5 99.000 (99.359) +2022-11-14 16:41:40,018 Test: [39/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0628 (0.0751) Prec@1 89.000 (88.225) Prec@5 99.000 (99.350) +2022-11-14 16:41:40,031 Test: [40/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1294 (0.0764) Prec@1 81.000 (88.049) Prec@5 99.000 (99.341) +2022-11-14 16:41:40,046 Test: [41/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0623 (0.0761) Prec@1 87.000 (88.024) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,064 Test: [42/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0503 (0.0755) Prec@1 93.000 (88.140) Prec@5 99.000 (99.326) +2022-11-14 16:41:40,081 Test: [43/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0747 (0.0754) Prec@1 89.000 (88.159) Prec@5 98.000 (99.295) +2022-11-14 16:41:40,097 Test: [44/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0545 (0.0750) Prec@1 91.000 (88.222) Prec@5 99.000 (99.289) +2022-11-14 16:41:40,115 Test: [45/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1016 (0.0756) Prec@1 83.000 (88.109) Prec@5 100.000 (99.304) +2022-11-14 16:41:40,133 Test: [46/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0702 (0.0754) Prec@1 87.000 (88.085) Prec@5 100.000 (99.319) +2022-11-14 16:41:40,150 Test: [47/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0967 (0.0759) Prec@1 87.000 (88.062) Prec@5 99.000 (99.312) +2022-11-14 16:41:40,166 Test: [48/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0713 (0.0758) Prec@1 90.000 (88.102) Prec@5 98.000 (99.286) +2022-11-14 16:41:40,180 Test: [49/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1002 (0.0763) Prec@1 84.000 (88.020) Prec@5 100.000 (99.300) +2022-11-14 16:41:40,199 Test: [50/100] Model Time 0.014 (0.011) Loss Time 0.000 (0.000) Loss 0.0569 (0.0759) Prec@1 90.000 (88.059) Prec@5 100.000 (99.314) +2022-11-14 16:41:40,218 Test: [51/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0688 (0.0758) Prec@1 87.000 (88.038) Prec@5 100.000 (99.327) +2022-11-14 16:41:40,236 Test: [52/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0612 (0.0755) Prec@1 89.000 (88.057) Prec@5 99.000 (99.321) +2022-11-14 16:41:40,254 Test: [53/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0495 (0.0750) Prec@1 92.000 (88.130) Prec@5 100.000 (99.333) +2022-11-14 16:41:40,272 Test: [54/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0712 (0.0749) Prec@1 88.000 (88.127) Prec@5 100.000 (99.345) +2022-11-14 16:41:40,290 Test: [55/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0422 (0.0744) Prec@1 93.000 (88.214) Prec@5 100.000 (99.357) +2022-11-14 16:41:40,307 Test: [56/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0764 (0.0744) Prec@1 88.000 (88.211) Prec@5 100.000 (99.368) +2022-11-14 16:41:40,328 Test: [57/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0695 (0.0743) Prec@1 89.000 (88.224) Prec@5 98.000 (99.345) +2022-11-14 16:41:40,351 Test: [58/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0896 (0.0746) Prec@1 87.000 (88.203) Prec@5 98.000 (99.322) +2022-11-14 16:41:40,374 Test: [59/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0729 (0.0745) Prec@1 89.000 (88.217) Prec@5 100.000 (99.333) +2022-11-14 16:41:40,398 Test: [60/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0677 (0.0744) Prec@1 89.000 (88.230) Prec@5 99.000 (99.328) +2022-11-14 16:41:40,419 Test: [61/100] Model Time 0.015 (0.011) Loss Time 0.000 (0.000) Loss 0.0620 (0.0742) Prec@1 90.000 (88.258) Prec@5 99.000 (99.323) +2022-11-14 16:41:40,438 Test: [62/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0524 (0.0739) Prec@1 92.000 (88.317) Prec@5 100.000 (99.333) +2022-11-14 16:41:40,455 Test: [63/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0470 (0.0735) Prec@1 92.000 (88.375) Prec@5 100.000 (99.344) +2022-11-14 16:41:40,472 Test: [64/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0693 (0.0734) Prec@1 90.000 (88.400) Prec@5 99.000 (99.338) +2022-11-14 16:41:40,487 Test: [65/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0698 (0.0733) Prec@1 88.000 (88.394) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,504 Test: [66/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0565 (0.0731) Prec@1 89.000 (88.403) Prec@5 100.000 (99.343) +2022-11-14 16:41:40,521 Test: [67/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0657 (0.0730) Prec@1 89.000 (88.412) Prec@5 99.000 (99.338) +2022-11-14 16:41:40,535 Test: [68/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0743 (0.0730) Prec@1 90.000 (88.435) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,552 Test: [69/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0556 (0.0727) Prec@1 92.000 (88.486) Prec@5 99.000 (99.329) +2022-11-14 16:41:40,566 Test: [70/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0978 (0.0731) Prec@1 86.000 (88.451) Prec@5 99.000 (99.324) +2022-11-14 16:41:40,582 Test: [71/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0754 (0.0731) Prec@1 88.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 16:41:40,599 Test: [72/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0532 (0.0729) Prec@1 92.000 (88.493) Prec@5 100.000 (99.342) +2022-11-14 16:41:40,616 Test: [73/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0489 (0.0725) Prec@1 91.000 (88.527) Prec@5 100.000 (99.351) +2022-11-14 16:41:40,633 Test: [74/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0978 (0.0729) Prec@1 83.000 (88.453) Prec@5 100.000 (99.360) +2022-11-14 16:41:40,649 Test: [75/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0619 (0.0727) Prec@1 91.000 (88.487) Prec@5 99.000 (99.355) +2022-11-14 16:41:40,668 Test: [76/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0756 (0.0728) Prec@1 89.000 (88.494) Prec@5 99.000 (99.351) +2022-11-14 16:41:40,684 Test: [77/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0937 (0.0730) Prec@1 84.000 (88.436) Prec@5 99.000 (99.346) +2022-11-14 16:41:40,700 Test: [78/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0763 (0.0731) Prec@1 88.000 (88.430) Prec@5 100.000 (99.354) +2022-11-14 16:41:40,715 Test: [79/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0948 (0.0733) Prec@1 85.000 (88.388) Prec@5 100.000 (99.362) +2022-11-14 16:41:40,732 Test: [80/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0815 (0.0734) Prec@1 88.000 (88.383) Prec@5 97.000 (99.333) +2022-11-14 16:41:40,749 Test: [81/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0853 (0.0736) Prec@1 87.000 (88.366) Prec@5 100.000 (99.341) +2022-11-14 16:41:40,768 Test: [82/100] Model Time 0.013 (0.011) Loss Time 0.000 (0.000) Loss 0.0828 (0.0737) Prec@1 86.000 (88.337) Prec@5 99.000 (99.337) +2022-11-14 16:41:40,789 Test: [83/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0442 (0.0734) Prec@1 93.000 (88.393) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,805 Test: [84/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0946 (0.0736) Prec@1 86.000 (88.365) Prec@5 100.000 (99.341) +2022-11-14 16:41:40,823 Test: [85/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1243 (0.0742) Prec@1 81.000 (88.279) Prec@5 99.000 (99.337) +2022-11-14 16:41:40,843 Test: [86/100] Model Time 0.012 (0.011) Loss Time 0.000 (0.000) Loss 0.0779 (0.0742) Prec@1 87.000 (88.264) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,862 Test: [87/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0935 (0.0745) Prec@1 85.000 (88.227) Prec@5 99.000 (99.330) +2022-11-14 16:41:40,876 Test: [88/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0751 (0.0745) Prec@1 88.000 (88.225) Prec@5 100.000 (99.337) +2022-11-14 16:41:40,893 Test: [89/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0701 (0.0744) Prec@1 90.000 (88.244) Prec@5 99.000 (99.333) +2022-11-14 16:41:40,907 Test: [90/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0692 (0.0744) Prec@1 88.000 (88.242) Prec@5 100.000 (99.341) +2022-11-14 16:41:40,924 Test: [91/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0412 (0.0740) Prec@1 94.000 (88.304) Prec@5 98.000 (99.326) +2022-11-14 16:41:40,939 Test: [92/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0793 (0.0741) Prec@1 86.000 (88.280) Prec@5 99.000 (99.323) +2022-11-14 16:41:40,954 Test: [93/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0690 (0.0740) Prec@1 89.000 (88.287) Prec@5 99.000 (99.319) +2022-11-14 16:41:40,969 Test: [94/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0908 (0.0742) Prec@1 84.000 (88.242) Prec@5 99.000 (99.316) +2022-11-14 16:41:40,984 Test: [95/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0624 (0.0741) Prec@1 93.000 (88.292) Prec@5 99.000 (99.312) +2022-11-14 16:41:41,008 Test: [96/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0508 (0.0738) Prec@1 92.000 (88.330) Prec@5 100.000 (99.320) +2022-11-14 16:41:41,029 Test: [97/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.1004 (0.0741) Prec@1 85.000 (88.296) Prec@5 96.000 (99.286) +2022-11-14 16:41:41,049 Test: [98/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.1075 (0.0744) Prec@1 83.000 (88.242) Prec@5 98.000 (99.273) +2022-11-14 16:41:41,070 Test: [99/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0753 (0.0744) Prec@1 90.000 (88.260) Prec@5 100.000 (99.280) +2022-11-14 16:41:41,162 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:41:41,551 Epoch: [372][0/500] Time 0.033 (0.033) Data 0.287 (0.287) Loss 0.0533 (0.0533) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:42,034 Epoch: [372][10/500] Time 0.070 (0.041) Data 0.002 (0.028) Loss 0.0395 (0.0464) Prec@1 93.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:42,548 Epoch: [372][20/500] Time 0.042 (0.044) Data 0.003 (0.016) Loss 0.0140 (0.0356) Prec@1 97.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:41:43,032 Epoch: [372][30/500] Time 0.052 (0.044) Data 0.002 (0.011) Loss 0.0456 (0.0381) Prec@1 90.000 (92.250) Prec@5 100.000 (100.000) +2022-11-14 16:41:43,521 Epoch: [372][40/500] Time 0.045 (0.044) Data 0.002 (0.009) Loss 0.0404 (0.0386) Prec@1 94.000 (92.600) Prec@5 100.000 (100.000) +2022-11-14 16:41:44,043 Epoch: [372][50/500] Time 0.047 (0.044) Data 0.002 (0.008) Loss 0.0183 (0.0352) Prec@1 97.000 (93.333) Prec@5 99.000 (99.833) +2022-11-14 16:41:44,538 Epoch: [372][60/500] Time 0.049 (0.044) Data 0.002 (0.007) Loss 0.0241 (0.0336) Prec@1 96.000 (93.714) Prec@5 100.000 (99.857) +2022-11-14 16:41:45,061 Epoch: [372][70/500] Time 0.054 (0.044) Data 0.002 (0.006) Loss 0.0275 (0.0328) Prec@1 94.000 (93.750) Prec@5 100.000 (99.875) +2022-11-14 16:41:45,583 Epoch: [372][80/500] Time 0.043 (0.045) Data 0.002 (0.006) Loss 0.0370 (0.0333) Prec@1 95.000 (93.889) Prec@5 100.000 (99.889) +2022-11-14 16:41:46,124 Epoch: [372][90/500] Time 0.040 (0.045) Data 0.002 (0.005) Loss 0.0178 (0.0317) Prec@1 99.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:41:46,809 Epoch: [372][100/500] Time 0.085 (0.047) Data 0.002 (0.005) Loss 0.0386 (0.0324) Prec@1 95.000 (94.455) Prec@5 100.000 (99.909) +2022-11-14 16:41:47,603 Epoch: [372][110/500] Time 0.077 (0.049) Data 0.002 (0.005) Loss 0.0352 (0.0326) Prec@1 94.000 (94.417) Prec@5 100.000 (99.917) +2022-11-14 16:41:48,438 Epoch: [372][120/500] Time 0.080 (0.051) Data 0.002 (0.004) Loss 0.0423 (0.0333) Prec@1 93.000 (94.308) Prec@5 100.000 (99.923) +2022-11-14 16:41:49,404 Epoch: [372][130/500] Time 0.097 (0.053) Data 0.002 (0.004) Loss 0.0357 (0.0335) Prec@1 95.000 (94.357) Prec@5 100.000 (99.929) +2022-11-14 16:41:50,218 Epoch: [372][140/500] Time 0.071 (0.055) Data 0.002 (0.004) Loss 0.0326 (0.0334) Prec@1 95.000 (94.400) Prec@5 100.000 (99.933) +2022-11-14 16:41:51,066 Epoch: [372][150/500] Time 0.077 (0.056) Data 0.002 (0.004) Loss 0.0505 (0.0345) Prec@1 92.000 (94.250) Prec@5 99.000 (99.875) +2022-11-14 16:41:52,021 Epoch: [372][160/500] Time 0.142 (0.058) Data 0.002 (0.004) Loss 0.0210 (0.0337) Prec@1 98.000 (94.471) Prec@5 100.000 (99.882) +2022-11-14 16:41:53,152 Epoch: [372][170/500] Time 0.095 (0.061) Data 0.002 (0.004) Loss 0.0409 (0.0341) Prec@1 93.000 (94.389) Prec@5 100.000 (99.889) +2022-11-14 16:41:54,256 Epoch: [372][180/500] Time 0.139 (0.063) Data 0.002 (0.004) Loss 0.0660 (0.0358) Prec@1 89.000 (94.105) Prec@5 100.000 (99.895) +2022-11-14 16:41:55,227 Epoch: [372][190/500] Time 0.089 (0.064) Data 0.002 (0.004) Loss 0.0285 (0.0354) Prec@1 97.000 (94.250) Prec@5 100.000 (99.900) +2022-11-14 16:41:56,054 Epoch: [372][200/500] Time 0.091 (0.065) Data 0.002 (0.004) Loss 0.0316 (0.0352) Prec@1 94.000 (94.238) Prec@5 100.000 (99.905) +2022-11-14 16:41:57,059 Epoch: [372][210/500] Time 0.084 (0.066) Data 0.002 (0.003) Loss 0.0350 (0.0352) Prec@1 95.000 (94.273) Prec@5 100.000 (99.909) +2022-11-14 16:41:57,862 Epoch: [372][220/500] Time 0.082 (0.066) Data 0.002 (0.003) Loss 0.0083 (0.0341) Prec@1 99.000 (94.478) Prec@5 100.000 (99.913) +2022-11-14 16:41:58,735 Epoch: [372][230/500] Time 0.078 (0.067) Data 0.002 (0.003) Loss 0.0430 (0.0344) Prec@1 90.000 (94.292) Prec@5 100.000 (99.917) +2022-11-14 16:41:59,605 Epoch: [372][240/500] Time 0.081 (0.067) Data 0.002 (0.003) Loss 0.0324 (0.0343) Prec@1 97.000 (94.400) Prec@5 100.000 (99.920) +2022-11-14 16:42:00,527 Epoch: [372][250/500] Time 0.082 (0.068) Data 0.002 (0.003) Loss 0.0167 (0.0337) Prec@1 98.000 (94.538) Prec@5 100.000 (99.923) +2022-11-14 16:42:01,723 Epoch: [372][260/500] Time 0.129 (0.069) Data 0.002 (0.003) Loss 0.0288 (0.0335) Prec@1 95.000 (94.556) Prec@5 100.000 (99.926) +2022-11-14 16:42:02,393 Epoch: [372][270/500] Time 0.054 (0.069) Data 0.002 (0.003) Loss 0.0384 (0.0337) Prec@1 93.000 (94.500) Prec@5 99.000 (99.893) +2022-11-14 16:42:03,051 Epoch: [372][280/500] Time 0.063 (0.069) Data 0.002 (0.003) Loss 0.0303 (0.0335) Prec@1 96.000 (94.552) Prec@5 100.000 (99.897) +2022-11-14 16:42:03,645 Epoch: [372][290/500] Time 0.051 (0.068) Data 0.002 (0.003) Loss 0.0491 (0.0341) Prec@1 92.000 (94.467) Prec@5 100.000 (99.900) +2022-11-14 16:42:04,222 Epoch: [372][300/500] Time 0.057 (0.068) Data 0.002 (0.003) Loss 0.0242 (0.0337) Prec@1 97.000 (94.548) Prec@5 100.000 (99.903) +2022-11-14 16:42:04,790 Epoch: [372][310/500] Time 0.071 (0.067) Data 0.002 (0.003) Loss 0.0355 (0.0338) Prec@1 94.000 (94.531) Prec@5 100.000 (99.906) +2022-11-14 16:42:05,414 Epoch: [372][320/500] Time 0.069 (0.067) Data 0.002 (0.003) Loss 0.0175 (0.0333) Prec@1 97.000 (94.606) Prec@5 100.000 (99.909) +2022-11-14 16:42:06,046 Epoch: [372][330/500] Time 0.061 (0.066) Data 0.002 (0.003) Loss 0.0291 (0.0332) Prec@1 97.000 (94.676) Prec@5 100.000 (99.912) +2022-11-14 16:42:06,672 Epoch: [372][340/500] Time 0.059 (0.066) Data 0.004 (0.003) Loss 0.0420 (0.0334) Prec@1 94.000 (94.657) Prec@5 100.000 (99.914) +2022-11-14 16:42:07,300 Epoch: [372][350/500] Time 0.058 (0.066) Data 0.002 (0.003) Loss 0.0359 (0.0335) Prec@1 94.000 (94.639) Prec@5 100.000 (99.917) +2022-11-14 16:42:07,924 Epoch: [372][360/500] Time 0.054 (0.066) Data 0.002 (0.003) Loss 0.0250 (0.0333) Prec@1 95.000 (94.649) Prec@5 100.000 (99.919) +2022-11-14 16:42:08,533 Epoch: [372][370/500] Time 0.063 (0.065) Data 0.003 (0.003) Loss 0.0250 (0.0331) Prec@1 96.000 (94.684) Prec@5 100.000 (99.921) +2022-11-14 16:42:09,145 Epoch: [372][380/500] Time 0.061 (0.065) Data 0.002 (0.003) Loss 0.0345 (0.0331) Prec@1 95.000 (94.692) Prec@5 100.000 (99.923) +2022-11-14 16:42:09,755 Epoch: [372][390/500] Time 0.064 (0.065) Data 0.002 (0.003) Loss 0.0307 (0.0330) Prec@1 93.000 (94.650) Prec@5 100.000 (99.925) +2022-11-14 16:42:10,361 Epoch: [372][400/500] Time 0.067 (0.064) Data 0.002 (0.003) Loss 0.0243 (0.0328) Prec@1 96.000 (94.683) Prec@5 100.000 (99.927) +2022-11-14 16:42:11,031 Epoch: [372][410/500] Time 0.056 (0.064) Data 0.002 (0.003) Loss 0.0315 (0.0328) Prec@1 94.000 (94.667) Prec@5 99.000 (99.905) +2022-11-14 16:42:11,614 Epoch: [372][420/500] Time 0.054 (0.064) Data 0.002 (0.003) Loss 0.0450 (0.0331) Prec@1 93.000 (94.628) Prec@5 100.000 (99.907) +2022-11-14 16:42:12,219 Epoch: [372][430/500] Time 0.059 (0.064) Data 0.002 (0.003) Loss 0.0341 (0.0331) Prec@1 95.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 16:42:12,907 Epoch: [372][440/500] Time 0.052 (0.064) Data 0.002 (0.003) Loss 0.0473 (0.0334) Prec@1 92.000 (94.578) Prec@5 100.000 (99.911) +2022-11-14 16:42:13,499 Epoch: [372][450/500] Time 0.047 (0.064) Data 0.002 (0.003) Loss 0.0222 (0.0332) Prec@1 97.000 (94.630) Prec@5 100.000 (99.913) +2022-11-14 16:42:14,086 Epoch: [372][460/500] Time 0.064 (0.063) Data 0.002 (0.003) Loss 0.0342 (0.0332) Prec@1 95.000 (94.638) Prec@5 100.000 (99.915) +2022-11-14 16:42:14,652 Epoch: [372][470/500] Time 0.054 (0.063) Data 0.002 (0.003) Loss 0.0313 (0.0332) Prec@1 95.000 (94.646) Prec@5 100.000 (99.917) +2022-11-14 16:42:15,242 Epoch: [372][480/500] Time 0.060 (0.063) Data 0.002 (0.003) Loss 0.0340 (0.0332) Prec@1 94.000 (94.633) Prec@5 100.000 (99.918) +2022-11-14 16:42:15,909 Epoch: [372][490/500] Time 0.052 (0.063) Data 0.003 (0.003) Loss 0.0127 (0.0328) Prec@1 98.000 (94.700) Prec@5 100.000 (99.920) +2022-11-14 16:42:16,487 Epoch: [372][499/500] Time 0.062 (0.063) Data 0.002 (0.003) Loss 0.0307 (0.0327) Prec@1 95.000 (94.706) Prec@5 100.000 (99.922) +2022-11-14 16:42:16,881 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0780 (0.0780) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:16,894 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0564 (0.0672) Prec@1 92.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:42:16,906 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0732 (0.0692) Prec@1 89.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:42:16,928 Test: [3/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0745 (0.0705) Prec@1 87.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 16:42:16,944 Test: [4/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0963 (0.0757) Prec@1 85.000 (87.600) Prec@5 100.000 (99.800) +2022-11-14 16:42:16,964 Test: [5/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0517 (0.0717) Prec@1 90.000 (88.000) Prec@5 100.000 (99.833) +2022-11-14 16:42:16,982 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0571 (0.0696) Prec@1 91.000 (88.429) Prec@5 100.000 (99.857) +2022-11-14 16:42:17,006 Test: [7/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0972 (0.0731) Prec@1 83.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 16:42:17,028 Test: [8/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0786 (0.0737) Prec@1 88.000 (87.778) Prec@5 99.000 (99.667) +2022-11-14 16:42:17,049 Test: [9/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0750 (0.0738) Prec@1 91.000 (88.100) Prec@5 97.000 (99.400) +2022-11-14 16:42:17,070 Test: [10/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0507 (0.0717) Prec@1 94.000 (88.636) Prec@5 100.000 (99.455) +2022-11-14 16:42:17,085 Test: [11/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0827 (0.0726) Prec@1 88.000 (88.583) Prec@5 99.000 (99.417) +2022-11-14 16:42:17,104 Test: [12/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0692 (0.0724) Prec@1 91.000 (88.769) Prec@5 100.000 (99.462) +2022-11-14 16:42:17,120 Test: [13/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0659 (0.0719) Prec@1 91.000 (88.929) Prec@5 99.000 (99.429) +2022-11-14 16:42:17,141 Test: [14/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.0878 (0.0730) Prec@1 87.000 (88.800) Prec@5 97.000 (99.267) +2022-11-14 16:42:17,160 Test: [15/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0693 (0.0727) Prec@1 88.000 (88.750) Prec@5 98.000 (99.188) +2022-11-14 16:42:17,177 Test: [16/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0485 (0.0713) Prec@1 94.000 (89.059) Prec@5 98.000 (99.118) +2022-11-14 16:42:17,197 Test: [17/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0888 (0.0723) Prec@1 87.000 (88.944) Prec@5 100.000 (99.167) +2022-11-14 16:42:17,217 Test: [18/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0735 (0.0723) Prec@1 88.000 (88.895) Prec@5 98.000 (99.105) +2022-11-14 16:42:17,236 Test: [19/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0827 (0.0729) Prec@1 87.000 (88.800) Prec@5 98.000 (99.050) +2022-11-14 16:42:17,256 Test: [20/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0743 (0.0729) Prec@1 89.000 (88.810) Prec@5 100.000 (99.095) +2022-11-14 16:42:17,282 Test: [21/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0927 (0.0738) Prec@1 85.000 (88.636) Prec@5 98.000 (99.045) +2022-11-14 16:42:17,303 Test: [22/100] Model Time 0.012 (0.010) Loss Time 0.000 (0.000) Loss 0.1104 (0.0754) Prec@1 83.000 (88.391) Prec@5 99.000 (99.043) +2022-11-14 16:42:17,324 Test: [23/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0771 (0.0755) Prec@1 87.000 (88.333) Prec@5 100.000 (99.083) +2022-11-14 16:42:17,347 Test: [24/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0791 (0.0756) Prec@1 86.000 (88.240) Prec@5 100.000 (99.120) +2022-11-14 16:42:17,368 Test: [25/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0763) Prec@1 87.000 (88.192) Prec@5 100.000 (99.154) +2022-11-14 16:42:17,386 Test: [26/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0640 (0.0758) Prec@1 92.000 (88.333) Prec@5 100.000 (99.185) +2022-11-14 16:42:17,405 Test: [27/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0745 (0.0758) Prec@1 89.000 (88.357) Prec@5 99.000 (99.179) +2022-11-14 16:42:17,424 Test: [28/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0904 (0.0763) Prec@1 85.000 (88.241) Prec@5 98.000 (99.138) +2022-11-14 16:42:17,445 Test: [29/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0756 (0.0763) Prec@1 87.000 (88.200) Prec@5 99.000 (99.133) +2022-11-14 16:42:17,464 Test: [30/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0830 (0.0765) Prec@1 86.000 (88.129) Prec@5 100.000 (99.161) +2022-11-14 16:42:17,482 Test: [31/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.1030 (0.0773) Prec@1 85.000 (88.031) Prec@5 99.000 (99.156) +2022-11-14 16:42:17,503 Test: [32/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0749 (0.0772) Prec@1 87.000 (88.000) Prec@5 100.000 (99.182) +2022-11-14 16:42:17,526 Test: [33/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0884 (0.0776) Prec@1 84.000 (87.882) Prec@5 99.000 (99.176) +2022-11-14 16:42:17,545 Test: [34/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0927 (0.0780) Prec@1 86.000 (87.829) Prec@5 99.000 (99.171) +2022-11-14 16:42:17,562 Test: [35/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0722 (0.0778) Prec@1 89.000 (87.861) Prec@5 99.000 (99.167) +2022-11-14 16:42:17,582 Test: [36/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0643 (0.0775) Prec@1 90.000 (87.919) Prec@5 99.000 (99.162) +2022-11-14 16:42:17,604 Test: [37/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0839 (0.0776) Prec@1 83.000 (87.789) Prec@5 99.000 (99.158) +2022-11-14 16:42:17,622 Test: [38/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0494 (0.0769) Prec@1 95.000 (87.974) Prec@5 99.000 (99.154) +2022-11-14 16:42:17,643 Test: [39/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0659 (0.0766) Prec@1 89.000 (88.000) Prec@5 100.000 (99.175) +2022-11-14 16:42:17,663 Test: [40/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0924 (0.0770) Prec@1 86.000 (87.951) Prec@5 99.000 (99.171) +2022-11-14 16:42:17,685 Test: [41/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0647 (0.0767) Prec@1 90.000 (88.000) Prec@5 98.000 (99.143) +2022-11-14 16:42:17,707 Test: [42/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0382 (0.0758) Prec@1 94.000 (88.140) Prec@5 99.000 (99.140) +2022-11-14 16:42:17,723 Test: [43/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0720 (0.0757) Prec@1 88.000 (88.136) Prec@5 99.000 (99.136) +2022-11-14 16:42:17,742 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0599 (0.0754) Prec@1 88.000 (88.133) Prec@5 100.000 (99.156) +2022-11-14 16:42:17,764 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0758) Prec@1 83.000 (88.022) Prec@5 100.000 (99.174) +2022-11-14 16:42:17,788 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0758) Prec@1 87.000 (88.000) Prec@5 100.000 (99.191) +2022-11-14 16:42:17,809 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1033 (0.0764) Prec@1 82.000 (87.875) Prec@5 98.000 (99.167) +2022-11-14 16:42:17,826 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0610 (0.0761) Prec@1 89.000 (87.898) Prec@5 100.000 (99.184) +2022-11-14 16:42:17,845 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0960 (0.0765) Prec@1 88.000 (87.900) Prec@5 99.000 (99.180) +2022-11-14 16:42:17,867 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0389 (0.0757) Prec@1 93.000 (88.000) Prec@5 100.000 (99.196) +2022-11-14 16:42:17,883 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0758) Prec@1 89.000 (88.019) Prec@5 100.000 (99.212) +2022-11-14 16:42:17,901 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0778 (0.0758) Prec@1 87.000 (88.000) Prec@5 99.000 (99.208) +2022-11-14 16:42:17,923 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0715 (0.0757) Prec@1 86.000 (87.963) Prec@5 100.000 (99.222) +2022-11-14 16:42:17,943 Test: [54/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0756) Prec@1 88.000 (87.964) Prec@5 100.000 (99.236) +2022-11-14 16:42:17,962 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0734 (0.0756) Prec@1 89.000 (87.982) Prec@5 99.000 (99.232) +2022-11-14 16:42:17,983 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0701 (0.0755) Prec@1 87.000 (87.965) Prec@5 100.000 (99.246) +2022-11-14 16:42:18,004 Test: [57/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0526 (0.0751) Prec@1 92.000 (88.034) Prec@5 100.000 (99.259) +2022-11-14 16:42:18,025 Test: [58/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1119 (0.0757) Prec@1 83.000 (87.949) Prec@5 99.000 (99.254) +2022-11-14 16:42:18,047 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0758) Prec@1 87.000 (87.933) Prec@5 99.000 (99.250) +2022-11-14 16:42:18,066 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0932 (0.0761) Prec@1 86.000 (87.902) Prec@5 100.000 (99.262) +2022-11-14 16:42:18,085 Test: [61/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0758) Prec@1 87.000 (87.887) Prec@5 100.000 (99.274) +2022-11-14 16:42:18,108 Test: [62/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0759) Prec@1 85.000 (87.841) Prec@5 98.000 (99.254) +2022-11-14 16:42:18,129 Test: [63/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0519 (0.0756) Prec@1 91.000 (87.891) Prec@5 100.000 (99.266) +2022-11-14 16:42:18,149 Test: [64/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0944 (0.0759) Prec@1 87.000 (87.877) Prec@5 100.000 (99.277) +2022-11-14 16:42:18,171 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0757) Prec@1 90.000 (87.909) Prec@5 100.000 (99.288) +2022-11-14 16:42:18,197 Test: [66/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0446 (0.0752) Prec@1 93.000 (87.985) Prec@5 100.000 (99.299) +2022-11-14 16:42:18,213 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0751) Prec@1 90.000 (88.015) Prec@5 99.000 (99.294) +2022-11-14 16:42:18,229 Test: [68/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0790 (0.0752) Prec@1 86.000 (87.986) Prec@5 99.000 (99.290) +2022-11-14 16:42:18,248 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0874 (0.0754) Prec@1 86.000 (87.957) Prec@5 99.000 (99.286) +2022-11-14 16:42:18,267 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1134 (0.0759) Prec@1 87.000 (87.944) Prec@5 99.000 (99.282) +2022-11-14 16:42:18,290 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0581 (0.0756) Prec@1 88.000 (87.944) Prec@5 100.000 (99.292) +2022-11-14 16:42:18,310 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0755) Prec@1 90.000 (87.973) Prec@5 100.000 (99.301) +2022-11-14 16:42:18,327 Test: [73/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0386 (0.0750) Prec@1 95.000 (88.068) Prec@5 100.000 (99.311) +2022-11-14 16:42:18,351 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1100 (0.0755) Prec@1 82.000 (87.987) Prec@5 100.000 (99.320) +2022-11-14 16:42:18,369 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0552 (0.0752) Prec@1 91.000 (88.026) Prec@5 100.000 (99.329) +2022-11-14 16:42:18,386 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0752) Prec@1 89.000 (88.039) Prec@5 99.000 (99.325) +2022-11-14 16:42:18,410 Test: [77/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0924 (0.0754) Prec@1 84.000 (87.987) Prec@5 97.000 (99.295) +2022-11-14 16:42:18,441 Test: [78/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0753) Prec@1 90.000 (88.013) Prec@5 100.000 (99.304) +2022-11-14 16:42:18,471 Test: [79/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0753) Prec@1 89.000 (88.025) Prec@5 100.000 (99.312) +2022-11-14 16:42:18,498 Test: [80/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0918 (0.0755) Prec@1 86.000 (88.000) Prec@5 99.000 (99.309) +2022-11-14 16:42:18,526 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0814 (0.0756) Prec@1 88.000 (88.000) Prec@5 100.000 (99.317) +2022-11-14 16:42:18,547 Test: [82/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0756) Prec@1 89.000 (88.012) Prec@5 99.000 (99.313) +2022-11-14 16:42:18,563 Test: [83/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0756) Prec@1 88.000 (88.012) Prec@5 100.000 (99.321) +2022-11-14 16:42:18,577 Test: [84/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0909 (0.0758) Prec@1 87.000 (88.000) Prec@5 98.000 (99.306) +2022-11-14 16:42:18,597 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1368 (0.0765) Prec@1 80.000 (87.907) Prec@5 100.000 (99.314) +2022-11-14 16:42:18,616 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0484 (0.0762) Prec@1 92.000 (87.954) Prec@5 100.000 (99.322) +2022-11-14 16:42:18,636 Test: [87/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0775 (0.0762) Prec@1 86.000 (87.932) Prec@5 99.000 (99.318) +2022-11-14 16:42:18,656 Test: [88/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0761) Prec@1 90.000 (87.955) Prec@5 100.000 (99.326) +2022-11-14 16:42:18,674 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0761) Prec@1 90.000 (87.978) Prec@5 98.000 (99.311) +2022-11-14 16:42:18,691 Test: [90/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0618 (0.0760) Prec@1 90.000 (88.000) Prec@5 100.000 (99.319) +2022-11-14 16:42:18,712 Test: [91/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0757) Prec@1 91.000 (88.033) Prec@5 100.000 (99.326) +2022-11-14 16:42:18,732 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0889 (0.0759) Prec@1 87.000 (88.022) Prec@5 100.000 (99.333) +2022-11-14 16:42:18,755 Test: [93/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0757) Prec@1 91.000 (88.053) Prec@5 99.000 (99.330) +2022-11-14 16:42:18,777 Test: [94/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1058 (0.0761) Prec@1 84.000 (88.011) Prec@5 99.000 (99.326) +2022-11-14 16:42:18,796 Test: [95/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0632 (0.0759) Prec@1 90.000 (88.031) Prec@5 99.000 (99.323) +2022-11-14 16:42:18,816 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0432 (0.0756) Prec@1 93.000 (88.082) Prec@5 99.000 (99.320) +2022-11-14 16:42:18,836 Test: [97/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0988 (0.0758) Prec@1 86.000 (88.061) Prec@5 99.000 (99.316) +2022-11-14 16:42:18,859 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0973 (0.0760) Prec@1 85.000 (88.030) Prec@5 99.000 (99.313) +2022-11-14 16:42:18,886 Test: [99/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0652 (0.0759) Prec@1 89.000 (88.040) Prec@5 100.000 (99.320) +2022-11-14 16:42:18,955 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:42:19,337 Epoch: [373][0/500] Time 0.024 (0.024) Data 0.289 (0.289) Loss 0.0270 (0.0270) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:19,839 Epoch: [373][10/500] Time 0.053 (0.042) Data 0.002 (0.028) Loss 0.0151 (0.0210) Prec@1 98.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:42:20,432 Epoch: [373][20/500] Time 0.065 (0.047) Data 0.002 (0.016) Loss 0.0514 (0.0312) Prec@1 91.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:42:21,083 Epoch: [373][30/500] Time 0.065 (0.052) Data 0.002 (0.011) Loss 0.0461 (0.0349) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:21,663 Epoch: [373][40/500] Time 0.056 (0.052) Data 0.002 (0.009) Loss 0.0394 (0.0358) Prec@1 94.000 (94.800) Prec@5 99.000 (99.800) +2022-11-14 16:42:22,304 Epoch: [373][50/500] Time 0.060 (0.053) Data 0.002 (0.008) Loss 0.0270 (0.0343) Prec@1 96.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 16:42:22,955 Epoch: [373][60/500] Time 0.063 (0.054) Data 0.002 (0.007) Loss 0.0350 (0.0344) Prec@1 93.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 16:42:23,665 Epoch: [373][70/500] Time 0.068 (0.055) Data 0.003 (0.006) Loss 0.0304 (0.0339) Prec@1 94.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 16:42:24,338 Epoch: [373][80/500] Time 0.069 (0.056) Data 0.003 (0.006) Loss 0.0451 (0.0352) Prec@1 92.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 16:42:24,957 Epoch: [373][90/500] Time 0.067 (0.056) Data 0.002 (0.005) Loss 0.0260 (0.0342) Prec@1 95.000 (94.400) Prec@5 100.000 (99.700) +2022-11-14 16:42:25,521 Epoch: [373][100/500] Time 0.062 (0.055) Data 0.002 (0.005) Loss 0.0215 (0.0331) Prec@1 95.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 16:42:26,113 Epoch: [373][110/500] Time 0.065 (0.055) Data 0.002 (0.005) Loss 0.0361 (0.0333) Prec@1 94.000 (94.417) Prec@5 100.000 (99.750) +2022-11-14 16:42:26,709 Epoch: [373][120/500] Time 0.056 (0.055) Data 0.003 (0.005) Loss 0.0412 (0.0339) Prec@1 94.000 (94.385) Prec@5 99.000 (99.692) +2022-11-14 16:42:27,316 Epoch: [373][130/500] Time 0.070 (0.055) Data 0.002 (0.004) Loss 0.0397 (0.0344) Prec@1 93.000 (94.286) Prec@5 99.000 (99.643) +2022-11-14 16:42:27,958 Epoch: [373][140/500] Time 0.069 (0.055) Data 0.002 (0.004) Loss 0.0303 (0.0341) Prec@1 96.000 (94.400) Prec@5 99.000 (99.600) +2022-11-14 16:42:28,552 Epoch: [373][150/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0162 (0.0330) Prec@1 97.000 (94.562) Prec@5 100.000 (99.625) +2022-11-14 16:42:29,170 Epoch: [373][160/500] Time 0.048 (0.055) Data 0.002 (0.004) Loss 0.0336 (0.0330) Prec@1 95.000 (94.588) Prec@5 100.000 (99.647) +2022-11-14 16:42:29,769 Epoch: [373][170/500] Time 0.052 (0.055) Data 0.002 (0.004) Loss 0.0479 (0.0338) Prec@1 90.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:42:30,439 Epoch: [373][180/500] Time 0.055 (0.055) Data 0.002 (0.004) Loss 0.0197 (0.0331) Prec@1 98.000 (94.526) Prec@5 100.000 (99.684) +2022-11-14 16:42:31,088 Epoch: [373][190/500] Time 0.063 (0.055) Data 0.002 (0.004) Loss 0.0223 (0.0325) Prec@1 95.000 (94.550) Prec@5 100.000 (99.700) +2022-11-14 16:42:31,770 Epoch: [373][200/500] Time 0.074 (0.056) Data 0.003 (0.004) Loss 0.0192 (0.0319) Prec@1 96.000 (94.619) Prec@5 100.000 (99.714) +2022-11-14 16:42:32,443 Epoch: [373][210/500] Time 0.045 (0.056) Data 0.002 (0.004) Loss 0.0192 (0.0313) Prec@1 97.000 (94.727) Prec@5 100.000 (99.727) +2022-11-14 16:42:33,145 Epoch: [373][220/500] Time 0.076 (0.056) Data 0.002 (0.004) Loss 0.0204 (0.0309) Prec@1 96.000 (94.783) Prec@5 100.000 (99.739) +2022-11-14 16:42:33,810 Epoch: [373][230/500] Time 0.067 (0.056) Data 0.002 (0.003) Loss 0.0402 (0.0312) Prec@1 94.000 (94.750) Prec@5 99.000 (99.708) +2022-11-14 16:42:34,385 Epoch: [373][240/500] Time 0.051 (0.056) Data 0.002 (0.003) Loss 0.0354 (0.0314) Prec@1 95.000 (94.760) Prec@5 100.000 (99.720) +2022-11-14 16:42:34,979 Epoch: [373][250/500] Time 0.059 (0.056) Data 0.002 (0.003) Loss 0.0167 (0.0308) Prec@1 97.000 (94.846) Prec@5 100.000 (99.731) +2022-11-14 16:42:35,573 Epoch: [373][260/500] Time 0.068 (0.056) Data 0.002 (0.003) Loss 0.0528 (0.0317) Prec@1 90.000 (94.667) Prec@5 100.000 (99.741) +2022-11-14 16:42:36,265 Epoch: [373][270/500] Time 0.067 (0.056) Data 0.002 (0.003) Loss 0.0413 (0.0320) Prec@1 94.000 (94.643) Prec@5 100.000 (99.750) +2022-11-14 16:42:36,875 Epoch: [373][280/500] Time 0.050 (0.056) Data 0.002 (0.003) Loss 0.0222 (0.0317) Prec@1 95.000 (94.655) Prec@5 100.000 (99.759) +2022-11-14 16:42:37,491 Epoch: [373][290/500] Time 0.058 (0.056) Data 0.002 (0.003) Loss 0.0422 (0.0320) Prec@1 93.000 (94.600) Prec@5 99.000 (99.733) +2022-11-14 16:42:38,120 Epoch: [373][300/500] Time 0.085 (0.056) Data 0.002 (0.003) Loss 0.0285 (0.0319) Prec@1 95.000 (94.613) Prec@5 100.000 (99.742) +2022-11-14 16:42:38,738 Epoch: [373][310/500] Time 0.047 (0.056) Data 0.002 (0.003) Loss 0.0379 (0.0321) Prec@1 92.000 (94.531) Prec@5 100.000 (99.750) +2022-11-14 16:42:39,397 Epoch: [373][320/500] Time 0.060 (0.056) Data 0.002 (0.003) Loss 0.0182 (0.0317) Prec@1 97.000 (94.606) Prec@5 100.000 (99.758) +2022-11-14 16:42:40,014 Epoch: [373][330/500] Time 0.046 (0.056) Data 0.003 (0.003) Loss 0.0338 (0.0317) Prec@1 94.000 (94.588) Prec@5 99.000 (99.735) +2022-11-14 16:42:40,637 Epoch: [373][340/500] Time 0.052 (0.056) Data 0.002 (0.003) Loss 0.0316 (0.0317) Prec@1 96.000 (94.629) Prec@5 100.000 (99.743) +2022-11-14 16:42:41,310 Epoch: [373][350/500] Time 0.066 (0.056) Data 0.002 (0.003) Loss 0.0297 (0.0317) Prec@1 96.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 16:42:41,969 Epoch: [373][360/500] Time 0.058 (0.056) Data 0.002 (0.003) Loss 0.0133 (0.0312) Prec@1 98.000 (94.757) Prec@5 100.000 (99.757) +2022-11-14 16:42:42,591 Epoch: [373][370/500] Time 0.050 (0.056) Data 0.002 (0.003) Loss 0.0255 (0.0310) Prec@1 96.000 (94.789) Prec@5 100.000 (99.763) +2022-11-14 16:42:43,263 Epoch: [373][380/500] Time 0.063 (0.056) Data 0.002 (0.003) Loss 0.0284 (0.0310) Prec@1 94.000 (94.769) Prec@5 100.000 (99.769) +2022-11-14 16:42:43,885 Epoch: [373][390/500] Time 0.055 (0.056) Data 0.003 (0.003) Loss 0.0236 (0.0308) Prec@1 95.000 (94.775) Prec@5 99.000 (99.750) +2022-11-14 16:42:44,494 Epoch: [373][400/500] Time 0.052 (0.056) Data 0.002 (0.003) Loss 0.0474 (0.0312) Prec@1 91.000 (94.683) Prec@5 100.000 (99.756) +2022-11-14 16:42:45,106 Epoch: [373][410/500] Time 0.059 (0.056) Data 0.002 (0.003) Loss 0.0368 (0.0313) Prec@1 93.000 (94.643) Prec@5 99.000 (99.738) +2022-11-14 16:42:45,724 Epoch: [373][420/500] Time 0.052 (0.056) Data 0.002 (0.003) Loss 0.0461 (0.0317) Prec@1 92.000 (94.581) Prec@5 100.000 (99.744) +2022-11-14 16:42:46,320 Epoch: [373][430/500] Time 0.056 (0.056) Data 0.002 (0.003) Loss 0.0192 (0.0314) Prec@1 98.000 (94.659) Prec@5 100.000 (99.750) +2022-11-14 16:42:46,944 Epoch: [373][440/500] Time 0.054 (0.056) Data 0.002 (0.003) Loss 0.0382 (0.0315) Prec@1 92.000 (94.600) Prec@5 99.000 (99.733) +2022-11-14 16:42:47,546 Epoch: [373][450/500] Time 0.058 (0.056) Data 0.002 (0.003) Loss 0.0226 (0.0313) Prec@1 95.000 (94.609) Prec@5 100.000 (99.739) +2022-11-14 16:42:48,142 Epoch: [373][460/500] Time 0.059 (0.056) Data 0.002 (0.003) Loss 0.0245 (0.0312) Prec@1 96.000 (94.638) Prec@5 100.000 (99.745) +2022-11-14 16:42:48,789 Epoch: [373][470/500] Time 0.071 (0.056) Data 0.002 (0.003) Loss 0.0355 (0.0313) Prec@1 94.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 16:42:49,380 Epoch: [373][480/500] Time 0.064 (0.056) Data 0.002 (0.003) Loss 0.0483 (0.0316) Prec@1 94.000 (94.612) Prec@5 99.000 (99.735) +2022-11-14 16:42:49,967 Epoch: [373][490/500] Time 0.072 (0.056) Data 0.002 (0.003) Loss 0.0288 (0.0316) Prec@1 96.000 (94.640) Prec@5 100.000 (99.740) +2022-11-14 16:42:50,489 Epoch: [373][499/500] Time 0.061 (0.056) Data 0.002 (0.003) Loss 0.0136 (0.0312) Prec@1 98.000 (94.706) Prec@5 100.000 (99.745) +2022-11-14 16:42:50,839 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0600 (0.0600) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:50,849 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0600 (0.0600) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:50,859 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0786 (0.0662) Prec@1 88.000 (90.000) Prec@5 98.000 (99.333) +2022-11-14 16:42:50,868 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0700 (0.0672) Prec@1 90.000 (90.000) Prec@5 99.000 (99.250) +2022-11-14 16:42:50,879 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0673) Prec@1 90.000 (90.000) Prec@5 100.000 (99.400) +2022-11-14 16:42:50,891 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0472 (0.0640) Prec@1 93.000 (90.500) Prec@5 100.000 (99.500) +2022-11-14 16:42:50,906 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0648) Prec@1 88.000 (90.143) Prec@5 99.000 (99.429) +2022-11-14 16:42:50,921 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0674) Prec@1 84.000 (89.375) Prec@5 100.000 (99.500) +2022-11-14 16:42:50,935 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0692) Prec@1 90.000 (89.444) Prec@5 99.000 (99.444) +2022-11-14 16:42:50,952 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0685) Prec@1 89.000 (89.400) Prec@5 99.000 (99.400) +2022-11-14 16:42:50,970 Test: [10/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0676) Prec@1 92.000 (89.636) Prec@5 100.000 (99.455) +2022-11-14 16:42:50,986 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0699) Prec@1 86.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 16:42:51,003 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0689) Prec@1 90.000 (89.385) Prec@5 99.000 (99.462) +2022-11-14 16:42:51,021 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0782 (0.0695) Prec@1 90.000 (89.429) Prec@5 99.000 (99.429) +2022-11-14 16:42:51,039 Test: [14/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0774 (0.0701) Prec@1 88.000 (89.333) Prec@5 99.000 (99.400) +2022-11-14 16:42:51,058 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0664 (0.0698) Prec@1 88.000 (89.250) Prec@5 100.000 (99.438) +2022-11-14 16:42:51,079 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0559 (0.0690) Prec@1 90.000 (89.294) Prec@5 99.000 (99.412) +2022-11-14 16:42:51,100 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1096 (0.0713) Prec@1 82.000 (88.889) Prec@5 99.000 (99.389) +2022-11-14 16:42:51,120 Test: [18/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0951 (0.0725) Prec@1 85.000 (88.684) Prec@5 99.000 (99.368) +2022-11-14 16:42:51,138 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0732) Prec@1 87.000 (88.600) Prec@5 98.000 (99.300) +2022-11-14 16:42:51,156 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0737) Prec@1 87.000 (88.524) Prec@5 100.000 (99.333) +2022-11-14 16:42:51,173 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0741) Prec@1 87.000 (88.455) Prec@5 100.000 (99.364) +2022-11-14 16:42:51,193 Test: [22/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1079 (0.0756) Prec@1 84.000 (88.261) Prec@5 100.000 (99.391) +2022-11-14 16:42:51,214 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0760) Prec@1 89.000 (88.292) Prec@5 99.000 (99.375) +2022-11-14 16:42:51,228 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0758) Prec@1 89.000 (88.320) Prec@5 100.000 (99.400) +2022-11-14 16:42:51,249 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0763) Prec@1 87.000 (88.269) Prec@5 98.000 (99.346) +2022-11-14 16:42:51,274 Test: [26/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0750) Prec@1 92.000 (88.407) Prec@5 100.000 (99.370) +2022-11-14 16:42:51,291 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0515 (0.0742) Prec@1 92.000 (88.536) Prec@5 99.000 (99.357) +2022-11-14 16:42:51,310 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0741) Prec@1 88.000 (88.517) Prec@5 99.000 (99.345) +2022-11-14 16:42:51,331 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0744) Prec@1 87.000 (88.467) Prec@5 99.000 (99.333) +2022-11-14 16:42:51,357 Test: [30/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0742) Prec@1 89.000 (88.484) Prec@5 99.000 (99.323) +2022-11-14 16:42:51,380 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0741) Prec@1 88.000 (88.469) Prec@5 99.000 (99.312) +2022-11-14 16:42:51,402 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0658 (0.0739) Prec@1 89.000 (88.485) Prec@5 99.000 (99.303) +2022-11-14 16:42:51,423 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0741) Prec@1 87.000 (88.441) Prec@5 100.000 (99.324) +2022-11-14 16:42:51,446 Test: [34/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0742) Prec@1 89.000 (88.457) Prec@5 98.000 (99.286) +2022-11-14 16:42:51,463 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0737) Prec@1 92.000 (88.556) Prec@5 99.000 (99.278) +2022-11-14 16:42:51,482 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0737) Prec@1 90.000 (88.595) Prec@5 99.000 (99.270) +2022-11-14 16:42:51,505 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1191 (0.0749) Prec@1 81.000 (88.395) Prec@5 98.000 (99.237) +2022-11-14 16:42:51,524 Test: [38/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0745) Prec@1 92.000 (88.487) Prec@5 99.000 (99.231) +2022-11-14 16:42:51,555 Test: [39/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0744) Prec@1 89.000 (88.500) Prec@5 100.000 (99.250) +2022-11-14 16:42:51,582 Test: [40/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0748) Prec@1 86.000 (88.439) Prec@5 98.000 (99.220) +2022-11-14 16:42:51,609 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0750) Prec@1 87.000 (88.405) Prec@5 99.000 (99.214) +2022-11-14 16:42:51,632 Test: [42/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0454 (0.0743) Prec@1 95.000 (88.558) Prec@5 100.000 (99.233) +2022-11-14 16:42:51,661 Test: [43/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0743) Prec@1 88.000 (88.545) Prec@5 98.000 (99.205) +2022-11-14 16:42:51,688 Test: [44/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0513 (0.0738) Prec@1 92.000 (88.622) Prec@5 97.000 (99.156) +2022-11-14 16:42:51,716 Test: [45/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0984 (0.0743) Prec@1 84.000 (88.522) Prec@5 98.000 (99.130) +2022-11-14 16:42:51,745 Test: [46/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0742) Prec@1 89.000 (88.532) Prec@5 100.000 (99.149) +2022-11-14 16:42:51,774 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1160 (0.0751) Prec@1 80.000 (88.354) Prec@5 98.000 (99.125) +2022-11-14 16:42:51,804 Test: [48/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0348 (0.0743) Prec@1 94.000 (88.469) Prec@5 100.000 (99.143) +2022-11-14 16:42:51,825 Test: [49/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0989 (0.0748) Prec@1 84.000 (88.380) Prec@5 99.000 (99.140) +2022-11-14 16:42:51,853 Test: [50/100] Model Time 0.013 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0744) Prec@1 88.000 (88.373) Prec@5 100.000 (99.157) +2022-11-14 16:42:51,880 Test: [51/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0745) Prec@1 89.000 (88.385) Prec@5 99.000 (99.154) +2022-11-14 16:42:51,907 Test: [52/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0744) Prec@1 92.000 (88.453) Prec@5 100.000 (99.170) +2022-11-14 16:42:51,932 Test: [53/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0742) Prec@1 91.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 16:42:51,960 Test: [54/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0825 (0.0744) Prec@1 85.000 (88.436) Prec@5 100.000 (99.182) +2022-11-14 16:42:51,984 Test: [55/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0769 (0.0744) Prec@1 88.000 (88.429) Prec@5 99.000 (99.179) +2022-11-14 16:42:52,007 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 87.000 (88.404) Prec@5 100.000 (99.193) +2022-11-14 16:42:52,034 Test: [57/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0744) Prec@1 89.000 (88.414) Prec@5 98.000 (99.172) +2022-11-14 16:42:52,056 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1095 (0.0750) Prec@1 82.000 (88.305) Prec@5 98.000 (99.153) +2022-11-14 16:42:52,072 Test: [59/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0594 (0.0748) Prec@1 90.000 (88.333) Prec@5 100.000 (99.167) +2022-11-14 16:42:52,088 Test: [60/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0747) Prec@1 90.000 (88.361) Prec@5 100.000 (99.180) +2022-11-14 16:42:52,106 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0728 (0.0747) Prec@1 90.000 (88.387) Prec@5 98.000 (99.161) +2022-11-14 16:42:52,125 Test: [62/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0627 (0.0745) Prec@1 92.000 (88.444) Prec@5 100.000 (99.175) +2022-11-14 16:42:52,142 Test: [63/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0443 (0.0740) Prec@1 92.000 (88.500) Prec@5 100.000 (99.188) +2022-11-14 16:42:52,163 Test: [64/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0861 (0.0742) Prec@1 85.000 (88.446) Prec@5 99.000 (99.185) +2022-11-14 16:42:52,183 Test: [65/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0762 (0.0743) Prec@1 86.000 (88.409) Prec@5 100.000 (99.197) +2022-11-14 16:42:52,203 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0403 (0.0738) Prec@1 93.000 (88.478) Prec@5 100.000 (99.209) +2022-11-14 16:42:52,221 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0737) Prec@1 87.000 (88.456) Prec@5 97.000 (99.176) +2022-11-14 16:42:52,240 Test: [68/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0716 (0.0737) Prec@1 88.000 (88.449) Prec@5 99.000 (99.174) +2022-11-14 16:42:52,260 Test: [69/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0891 (0.0739) Prec@1 86.000 (88.414) Prec@5 100.000 (99.186) +2022-11-14 16:42:52,280 Test: [70/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0936 (0.0742) Prec@1 88.000 (88.408) Prec@5 98.000 (99.169) +2022-11-14 16:42:52,304 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0741) Prec@1 87.000 (88.389) Prec@5 98.000 (99.153) +2022-11-14 16:42:52,327 Test: [72/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0409 (0.0736) Prec@1 94.000 (88.466) Prec@5 100.000 (99.164) +2022-11-14 16:42:52,354 Test: [73/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0402 (0.0732) Prec@1 93.000 (88.527) Prec@5 100.000 (99.176) +2022-11-14 16:42:52,380 Test: [74/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0985 (0.0735) Prec@1 85.000 (88.480) Prec@5 100.000 (99.187) +2022-11-14 16:42:52,406 Test: [75/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0699 (0.0735) Prec@1 89.000 (88.487) Prec@5 98.000 (99.171) +2022-11-14 16:42:52,428 Test: [76/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0742 (0.0735) Prec@1 88.000 (88.481) Prec@5 99.000 (99.169) +2022-11-14 16:42:52,449 Test: [77/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0837 (0.0736) Prec@1 87.000 (88.462) Prec@5 98.000 (99.154) +2022-11-14 16:42:52,468 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0737) Prec@1 88.000 (88.456) Prec@5 100.000 (99.165) +2022-11-14 16:42:52,486 Test: [79/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0737) Prec@1 88.000 (88.450) Prec@5 100.000 (99.175) +2022-11-14 16:42:52,503 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0704 (0.0737) Prec@1 90.000 (88.469) Prec@5 98.000 (99.160) +2022-11-14 16:42:52,525 Test: [81/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0620 (0.0736) Prec@1 90.000 (88.488) Prec@5 99.000 (99.159) +2022-11-14 16:42:52,541 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0881 (0.0737) Prec@1 85.000 (88.446) Prec@5 99.000 (99.157) +2022-11-14 16:42:52,560 Test: [83/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0736) Prec@1 89.000 (88.452) Prec@5 100.000 (99.167) +2022-11-14 16:42:52,579 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0766 (0.0737) Prec@1 89.000 (88.459) Prec@5 100.000 (99.176) +2022-11-14 16:42:52,601 Test: [85/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1025 (0.0740) Prec@1 83.000 (88.395) Prec@5 100.000 (99.186) +2022-11-14 16:42:52,622 Test: [86/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0844 (0.0741) Prec@1 88.000 (88.391) Prec@5 99.000 (99.184) +2022-11-14 16:42:52,651 Test: [87/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0742) Prec@1 89.000 (88.398) Prec@5 98.000 (99.170) +2022-11-14 16:42:52,678 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0742) Prec@1 87.000 (88.382) Prec@5 100.000 (99.180) +2022-11-14 16:42:52,707 Test: [89/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0621 (0.0741) Prec@1 90.000 (88.400) Prec@5 100.000 (99.189) +2022-11-14 16:42:52,735 Test: [90/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0562 (0.0739) Prec@1 90.000 (88.418) Prec@5 100.000 (99.198) +2022-11-14 16:42:52,758 Test: [91/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0488 (0.0736) Prec@1 91.000 (88.446) Prec@5 100.000 (99.207) +2022-11-14 16:42:52,776 Test: [92/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0737) Prec@1 89.000 (88.452) Prec@5 99.000 (99.204) +2022-11-14 16:42:52,795 Test: [93/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0706 (0.0736) Prec@1 87.000 (88.436) Prec@5 100.000 (99.213) +2022-11-14 16:42:52,814 Test: [94/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0966 (0.0739) Prec@1 86.000 (88.411) Prec@5 99.000 (99.211) +2022-11-14 16:42:52,832 Test: [95/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0738) Prec@1 88.000 (88.406) Prec@5 99.000 (99.208) +2022-11-14 16:42:52,849 Test: [96/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0398 (0.0734) Prec@1 95.000 (88.474) Prec@5 99.000 (99.206) +2022-11-14 16:42:52,869 Test: [97/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0943 (0.0736) Prec@1 87.000 (88.459) Prec@5 99.000 (99.204) +2022-11-14 16:42:52,886 Test: [98/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0829 (0.0737) Prec@1 86.000 (88.434) Prec@5 100.000 (99.212) +2022-11-14 16:42:52,906 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0736) Prec@1 90.000 (88.450) Prec@5 100.000 (99.220) +2022-11-14 16:42:52,970 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:42:53,347 Epoch: [374][0/500] Time 0.029 (0.029) Data 0.281 (0.281) Loss 0.0523 (0.0523) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:53,919 Epoch: [374][10/500] Time 0.050 (0.050) Data 0.002 (0.027) Loss 0.0292 (0.0408) Prec@1 96.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:42:54,513 Epoch: [374][20/500] Time 0.052 (0.051) Data 0.002 (0.015) Loss 0.0486 (0.0434) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:42:55,204 Epoch: [374][30/500] Time 0.068 (0.055) Data 0.002 (0.011) Loss 0.0230 (0.0383) Prec@1 96.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 16:42:55,862 Epoch: [374][40/500] Time 0.066 (0.056) Data 0.002 (0.009) Loss 0.0306 (0.0368) Prec@1 95.000 (94.000) Prec@5 99.000 (99.800) +2022-11-14 16:42:56,480 Epoch: [374][50/500] Time 0.057 (0.056) Data 0.002 (0.008) Loss 0.0260 (0.0350) Prec@1 96.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:42:57,056 Epoch: [374][60/500] Time 0.061 (0.055) Data 0.002 (0.007) Loss 0.0488 (0.0369) Prec@1 91.000 (93.857) Prec@5 100.000 (99.857) +2022-11-14 16:42:57,656 Epoch: [374][70/500] Time 0.057 (0.055) Data 0.002 (0.006) Loss 0.0178 (0.0345) Prec@1 98.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 16:42:58,248 Epoch: [374][80/500] Time 0.062 (0.055) Data 0.002 (0.006) Loss 0.0356 (0.0347) Prec@1 93.000 (94.222) Prec@5 100.000 (99.889) +2022-11-14 16:42:58,837 Epoch: [374][90/500] Time 0.058 (0.054) Data 0.002 (0.005) Loss 0.0204 (0.0332) Prec@1 96.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:42:59,452 Epoch: [374][100/500] Time 0.072 (0.054) Data 0.002 (0.005) Loss 0.0317 (0.0331) Prec@1 94.000 (94.364) Prec@5 100.000 (99.909) +2022-11-14 16:43:00,087 Epoch: [374][110/500] Time 0.064 (0.054) Data 0.002 (0.005) Loss 0.0299 (0.0328) Prec@1 95.000 (94.417) Prec@5 100.000 (99.917) +2022-11-14 16:43:00,785 Epoch: [374][120/500] Time 0.075 (0.055) Data 0.002 (0.004) Loss 0.0129 (0.0313) Prec@1 98.000 (94.692) Prec@5 99.000 (99.846) +2022-11-14 16:43:01,388 Epoch: [374][130/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0340 (0.0315) Prec@1 92.000 (94.500) Prec@5 100.000 (99.857) +2022-11-14 16:43:02,016 Epoch: [374][140/500] Time 0.059 (0.055) Data 0.002 (0.004) Loss 0.0581 (0.0333) Prec@1 92.000 (94.333) Prec@5 100.000 (99.867) +2022-11-14 16:43:02,639 Epoch: [374][150/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0312 (0.0331) Prec@1 95.000 (94.375) Prec@5 98.000 (99.750) +2022-11-14 16:43:03,237 Epoch: [374][160/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0213 (0.0324) Prec@1 98.000 (94.588) Prec@5 100.000 (99.765) +2022-11-14 16:43:03,866 Epoch: [374][170/500] Time 0.060 (0.055) Data 0.002 (0.004) Loss 0.0401 (0.0329) Prec@1 93.000 (94.500) Prec@5 100.000 (99.778) +2022-11-14 16:43:04,454 Epoch: [374][180/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0247 (0.0324) Prec@1 95.000 (94.526) Prec@5 100.000 (99.789) +2022-11-14 16:43:05,095 Epoch: [374][190/500] Time 0.077 (0.055) Data 0.002 (0.004) Loss 0.0388 (0.0328) Prec@1 93.000 (94.450) Prec@5 99.000 (99.750) +2022-11-14 16:43:05,704 Epoch: [374][200/500] Time 0.061 (0.055) Data 0.002 (0.004) Loss 0.0518 (0.0337) Prec@1 91.000 (94.286) Prec@5 100.000 (99.762) +2022-11-14 16:43:06,273 Epoch: [374][210/500] Time 0.064 (0.055) Data 0.002 (0.003) Loss 0.0387 (0.0339) Prec@1 93.000 (94.227) Prec@5 100.000 (99.773) +2022-11-14 16:43:06,856 Epoch: [374][220/500] Time 0.058 (0.055) Data 0.002 (0.003) Loss 0.0153 (0.0331) Prec@1 99.000 (94.435) Prec@5 100.000 (99.783) +2022-11-14 16:43:07,438 Epoch: [374][230/500] Time 0.055 (0.055) Data 0.002 (0.003) Loss 0.0483 (0.0337) Prec@1 93.000 (94.375) Prec@5 100.000 (99.792) +2022-11-14 16:43:08,025 Epoch: [374][240/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0315 (0.0336) Prec@1 93.000 (94.320) Prec@5 100.000 (99.800) +2022-11-14 16:43:08,600 Epoch: [374][250/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0309 (0.0335) Prec@1 96.000 (94.385) Prec@5 100.000 (99.808) +2022-11-14 16:43:09,168 Epoch: [374][260/500] Time 0.062 (0.054) Data 0.002 (0.003) Loss 0.0207 (0.0330) Prec@1 97.000 (94.481) Prec@5 100.000 (99.815) +2022-11-14 16:43:09,789 Epoch: [374][270/500] Time 0.065 (0.054) Data 0.002 (0.003) Loss 0.0287 (0.0329) Prec@1 95.000 (94.500) Prec@5 100.000 (99.821) +2022-11-14 16:43:10,397 Epoch: [374][280/500] Time 0.065 (0.054) Data 0.002 (0.003) Loss 0.0476 (0.0334) Prec@1 90.000 (94.345) Prec@5 100.000 (99.828) +2022-11-14 16:43:10,989 Epoch: [374][290/500] Time 0.058 (0.054) Data 0.002 (0.003) Loss 0.0254 (0.0331) Prec@1 95.000 (94.367) Prec@5 100.000 (99.833) +2022-11-14 16:43:11,590 Epoch: [374][300/500] Time 0.058 (0.054) Data 0.002 (0.003) Loss 0.0133 (0.0325) Prec@1 98.000 (94.484) Prec@5 100.000 (99.839) +2022-11-14 16:43:12,232 Epoch: [374][310/500] Time 0.080 (0.054) Data 0.002 (0.003) Loss 0.0397 (0.0327) Prec@1 92.000 (94.406) Prec@5 100.000 (99.844) +2022-11-14 16:43:12,891 Epoch: [374][320/500] Time 0.054 (0.054) Data 0.002 (0.003) Loss 0.0184 (0.0323) Prec@1 96.000 (94.455) Prec@5 100.000 (99.848) +2022-11-14 16:43:13,533 Epoch: [374][330/500] Time 0.051 (0.054) Data 0.002 (0.003) Loss 0.0132 (0.0317) Prec@1 98.000 (94.559) Prec@5 99.000 (99.824) +2022-11-14 16:43:14,172 Epoch: [374][340/500] Time 0.057 (0.055) Data 0.002 (0.003) Loss 0.0336 (0.0318) Prec@1 94.000 (94.543) Prec@5 100.000 (99.829) +2022-11-14 16:43:14,802 Epoch: [374][350/500] Time 0.065 (0.055) Data 0.002 (0.003) Loss 0.0226 (0.0315) Prec@1 95.000 (94.556) Prec@5 100.000 (99.833) +2022-11-14 16:43:15,441 Epoch: [374][360/500] Time 0.066 (0.055) Data 0.002 (0.003) Loss 0.0237 (0.0313) Prec@1 95.000 (94.568) Prec@5 100.000 (99.838) +2022-11-14 16:43:16,060 Epoch: [374][370/500] Time 0.053 (0.055) Data 0.002 (0.003) Loss 0.0239 (0.0311) Prec@1 98.000 (94.658) Prec@5 100.000 (99.842) +2022-11-14 16:43:16,707 Epoch: [374][380/500] Time 0.046 (0.055) Data 0.002 (0.003) Loss 0.0169 (0.0307) Prec@1 99.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 16:43:17,336 Epoch: [374][390/500] Time 0.052 (0.055) Data 0.002 (0.003) Loss 0.0254 (0.0306) Prec@1 95.000 (94.775) Prec@5 100.000 (99.850) +2022-11-14 16:43:17,935 Epoch: [374][400/500] Time 0.063 (0.055) Data 0.002 (0.003) Loss 0.0275 (0.0305) Prec@1 93.000 (94.732) Prec@5 100.000 (99.854) +2022-11-14 16:43:18,545 Epoch: [374][410/500] Time 0.062 (0.055) Data 0.002 (0.003) Loss 0.0311 (0.0306) Prec@1 96.000 (94.762) Prec@5 100.000 (99.857) +2022-11-14 16:43:19,127 Epoch: [374][420/500] Time 0.049 (0.055) Data 0.002 (0.003) Loss 0.0421 (0.0308) Prec@1 93.000 (94.721) Prec@5 100.000 (99.860) +2022-11-14 16:43:19,832 Epoch: [374][430/500] Time 0.069 (0.055) Data 0.003 (0.003) Loss 0.0283 (0.0308) Prec@1 97.000 (94.773) Prec@5 100.000 (99.864) +2022-11-14 16:43:20,424 Epoch: [374][440/500] Time 0.052 (0.055) Data 0.002 (0.003) Loss 0.0252 (0.0306) Prec@1 95.000 (94.778) Prec@5 100.000 (99.867) +2022-11-14 16:43:21,020 Epoch: [374][450/500] Time 0.054 (0.055) Data 0.002 (0.003) Loss 0.0480 (0.0310) Prec@1 92.000 (94.717) Prec@5 100.000 (99.870) +2022-11-14 16:43:21,624 Epoch: [374][460/500] Time 0.066 (0.055) Data 0.002 (0.003) Loss 0.0296 (0.0310) Prec@1 94.000 (94.702) Prec@5 100.000 (99.872) +2022-11-14 16:43:22,265 Epoch: [374][470/500] Time 0.074 (0.055) Data 0.002 (0.003) Loss 0.0202 (0.0308) Prec@1 97.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 16:43:22,893 Epoch: [374][480/500] Time 0.052 (0.055) Data 0.002 (0.003) Loss 0.0246 (0.0306) Prec@1 97.000 (94.796) Prec@5 99.000 (99.857) +2022-11-14 16:43:23,579 Epoch: [374][490/500] Time 0.073 (0.055) Data 0.002 (0.003) Loss 0.0370 (0.0308) Prec@1 94.000 (94.780) Prec@5 100.000 (99.860) +2022-11-14 16:43:24,092 Epoch: [374][499/500] Time 0.053 (0.055) Data 0.002 (0.003) Loss 0.0302 (0.0308) Prec@1 96.000 (94.804) Prec@5 100.000 (99.863) +2022-11-14 16:43:24,430 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0718 (0.0718) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:43:24,439 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0544 (0.0631) Prec@1 94.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:43:24,455 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0651) Prec@1 89.000 (90.333) Prec@5 100.000 (99.667) +2022-11-14 16:43:24,474 Test: [3/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0688) Prec@1 88.000 (89.750) Prec@5 99.000 (99.500) +2022-11-14 16:43:24,490 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0567 (0.0664) Prec@1 90.000 (89.800) Prec@5 100.000 (99.600) +2022-11-14 16:43:24,505 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0370 (0.0615) Prec@1 92.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 16:43:24,526 Test: [6/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0617) Prec@1 91.000 (90.286) Prec@5 99.000 (99.571) +2022-11-14 16:43:24,547 Test: [7/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0645) Prec@1 82.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 16:43:24,569 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0673) Prec@1 86.000 (88.889) Prec@5 100.000 (99.667) +2022-11-14 16:43:24,589 Test: [9/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0680) Prec@1 90.000 (89.000) Prec@5 99.000 (99.600) +2022-11-14 16:43:24,604 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0474 (0.0662) Prec@1 93.000 (89.364) Prec@5 100.000 (99.636) +2022-11-14 16:43:24,623 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0680) Prec@1 87.000 (89.167) Prec@5 99.000 (99.583) +2022-11-14 16:43:24,644 Test: [12/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0682) Prec@1 87.000 (89.000) Prec@5 99.000 (99.538) +2022-11-14 16:43:24,660 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0691) Prec@1 88.000 (88.929) Prec@5 98.000 (99.429) +2022-11-14 16:43:24,678 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0691) Prec@1 88.000 (88.867) Prec@5 100.000 (99.467) +2022-11-14 16:43:24,700 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0695) Prec@1 88.000 (88.812) Prec@5 100.000 (99.500) +2022-11-14 16:43:24,719 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0374 (0.0676) Prec@1 94.000 (89.118) Prec@5 99.000 (99.471) +2022-11-14 16:43:24,740 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.0698) Prec@1 84.000 (88.833) Prec@5 98.000 (99.389) +2022-11-14 16:43:24,761 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0705) Prec@1 83.000 (88.526) Prec@5 99.000 (99.368) +2022-11-14 16:43:24,777 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0714) Prec@1 87.000 (88.450) Prec@5 98.000 (99.300) +2022-11-14 16:43:24,793 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0727) Prec@1 85.000 (88.286) Prec@5 100.000 (99.333) +2022-11-14 16:43:24,815 Test: [21/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0835 (0.0732) Prec@1 87.000 (88.227) Prec@5 100.000 (99.364) +2022-11-14 16:43:24,831 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0856 (0.0737) Prec@1 87.000 (88.174) Prec@5 98.000 (99.304) +2022-11-14 16:43:24,851 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0732) Prec@1 92.000 (88.333) Prec@5 99.000 (99.292) +2022-11-14 16:43:24,873 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0970 (0.0742) Prec@1 84.000 (88.160) Prec@5 100.000 (99.320) +2022-11-14 16:43:24,895 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0750) Prec@1 88.000 (88.154) Prec@5 99.000 (99.308) +2022-11-14 16:43:24,917 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0434 (0.0738) Prec@1 92.000 (88.296) Prec@5 100.000 (99.333) +2022-11-14 16:43:24,934 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0732) Prec@1 91.000 (88.393) Prec@5 100.000 (99.357) +2022-11-14 16:43:24,956 Test: [28/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0731) Prec@1 90.000 (88.448) Prec@5 98.000 (99.310) +2022-11-14 16:43:24,976 Test: [29/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0731) Prec@1 88.000 (88.433) Prec@5 99.000 (99.300) +2022-11-14 16:43:24,995 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0726) Prec@1 91.000 (88.516) Prec@5 100.000 (99.323) +2022-11-14 16:43:25,017 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0732) Prec@1 86.000 (88.438) Prec@5 99.000 (99.312) +2022-11-14 16:43:25,034 Test: [32/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0794 (0.0734) Prec@1 85.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:43:25,052 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0857 (0.0738) Prec@1 84.000 (88.206) Prec@5 98.000 (99.294) +2022-11-14 16:43:25,073 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0739) Prec@1 88.000 (88.200) Prec@5 98.000 (99.257) +2022-11-14 16:43:25,094 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0737) Prec@1 90.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 16:43:25,113 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0741) Prec@1 85.000 (88.162) Prec@5 99.000 (99.243) +2022-11-14 16:43:25,133 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0982 (0.0747) Prec@1 81.000 (87.974) Prec@5 100.000 (99.263) +2022-11-14 16:43:25,153 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0740) Prec@1 93.000 (88.103) Prec@5 99.000 (99.256) +2022-11-14 16:43:25,170 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0736) Prec@1 91.000 (88.175) Prec@5 100.000 (99.275) +2022-11-14 16:43:25,190 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1024 (0.0743) Prec@1 86.000 (88.122) Prec@5 98.000 (99.244) +2022-11-14 16:43:25,211 Test: [41/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0530 (0.0738) Prec@1 90.000 (88.167) Prec@5 100.000 (99.262) +2022-11-14 16:43:25,233 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0626 (0.0735) Prec@1 90.000 (88.209) Prec@5 99.000 (99.256) +2022-11-14 16:43:25,254 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0735) Prec@1 90.000 (88.250) Prec@5 98.000 (99.227) +2022-11-14 16:43:25,274 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0733) Prec@1 90.000 (88.289) Prec@5 100.000 (99.244) +2022-11-14 16:43:25,291 Test: [45/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0737) Prec@1 84.000 (88.196) Prec@5 99.000 (99.239) +2022-11-14 16:43:25,311 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0737) Prec@1 89.000 (88.213) Prec@5 100.000 (99.255) +2022-11-14 16:43:25,330 Test: [47/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1229 (0.0748) Prec@1 80.000 (88.042) Prec@5 98.000 (99.229) +2022-11-14 16:43:25,359 Test: [48/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0765 (0.0748) Prec@1 87.000 (88.020) Prec@5 99.000 (99.224) +2022-11-14 16:43:25,387 Test: [49/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0754) Prec@1 84.000 (87.940) Prec@5 100.000 (99.240) +2022-11-14 16:43:25,414 Test: [50/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0552 (0.0750) Prec@1 90.000 (87.980) Prec@5 100.000 (99.255) +2022-11-14 16:43:25,441 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0750) Prec@1 87.000 (87.962) Prec@5 99.000 (99.250) +2022-11-14 16:43:25,470 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0748) Prec@1 90.000 (88.000) Prec@5 100.000 (99.264) +2022-11-14 16:43:25,496 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0749) Prec@1 85.000 (87.944) Prec@5 100.000 (99.278) +2022-11-14 16:43:25,513 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0810 (0.0750) Prec@1 84.000 (87.873) Prec@5 100.000 (99.291) +2022-11-14 16:43:25,528 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0751) Prec@1 88.000 (87.875) Prec@5 99.000 (99.286) +2022-11-14 16:43:25,547 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0753) Prec@1 86.000 (87.842) Prec@5 99.000 (99.281) +2022-11-14 16:43:25,565 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0751) Prec@1 91.000 (87.897) Prec@5 100.000 (99.293) +2022-11-14 16:43:25,588 Test: [58/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0755) Prec@1 84.000 (87.831) Prec@5 99.000 (99.288) +2022-11-14 16:43:25,606 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0831 (0.0756) Prec@1 88.000 (87.833) Prec@5 98.000 (99.267) +2022-11-14 16:43:25,627 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1006 (0.0760) Prec@1 85.000 (87.787) Prec@5 99.000 (99.262) +2022-11-14 16:43:25,644 Test: [61/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0759) Prec@1 89.000 (87.806) Prec@5 100.000 (99.274) +2022-11-14 16:43:25,667 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0757) Prec@1 92.000 (87.873) Prec@5 99.000 (99.270) +2022-11-14 16:43:25,687 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0358 (0.0751) Prec@1 93.000 (87.953) Prec@5 99.000 (99.266) +2022-11-14 16:43:25,710 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0749) Prec@1 92.000 (88.015) Prec@5 99.000 (99.262) +2022-11-14 16:43:25,732 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0748) Prec@1 89.000 (88.030) Prec@5 99.000 (99.258) +2022-11-14 16:43:25,754 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0427 (0.0744) Prec@1 93.000 (88.104) Prec@5 100.000 (99.269) +2022-11-14 16:43:25,774 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0742) Prec@1 89.000 (88.118) Prec@5 98.000 (99.250) +2022-11-14 16:43:25,796 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0598 (0.0740) Prec@1 91.000 (88.159) Prec@5 99.000 (99.246) +2022-11-14 16:43:25,814 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0740) Prec@1 89.000 (88.171) Prec@5 98.000 (99.229) +2022-11-14 16:43:25,832 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1012 (0.0744) Prec@1 86.000 (88.141) Prec@5 100.000 (99.239) +2022-11-14 16:43:25,851 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0740) Prec@1 91.000 (88.181) Prec@5 100.000 (99.250) +2022-11-14 16:43:25,873 Test: [72/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0737) Prec@1 91.000 (88.219) Prec@5 100.000 (99.260) +2022-11-14 16:43:25,894 Test: [73/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0313 (0.0732) Prec@1 96.000 (88.324) Prec@5 100.000 (99.270) +2022-11-14 16:43:25,917 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0732) Prec@1 88.000 (88.320) Prec@5 99.000 (99.267) +2022-11-14 16:43:25,937 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0732) Prec@1 86.000 (88.289) Prec@5 100.000 (99.276) +2022-11-14 16:43:25,959 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0731) Prec@1 89.000 (88.299) Prec@5 99.000 (99.273) +2022-11-14 16:43:25,978 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0735) Prec@1 84.000 (88.244) Prec@5 98.000 (99.256) +2022-11-14 16:43:25,995 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1001 (0.0738) Prec@1 84.000 (88.190) Prec@5 99.000 (99.253) +2022-11-14 16:43:26,015 Test: [79/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0737) Prec@1 88.000 (88.188) Prec@5 100.000 (99.263) +2022-11-14 16:43:26,033 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 86.000 (88.160) Prec@5 99.000 (99.259) +2022-11-14 16:43:26,052 Test: [81/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0738) Prec@1 87.000 (88.146) Prec@5 100.000 (99.268) +2022-11-14 16:43:26,073 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0740) Prec@1 85.000 (88.108) Prec@5 100.000 (99.277) +2022-11-14 16:43:26,095 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0458 (0.0737) Prec@1 91.000 (88.143) Prec@5 98.000 (99.262) +2022-11-14 16:43:26,115 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0739) Prec@1 84.000 (88.094) Prec@5 100.000 (99.271) +2022-11-14 16:43:26,137 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1326 (0.0746) Prec@1 80.000 (88.000) Prec@5 100.000 (99.279) +2022-11-14 16:43:26,157 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0745) Prec@1 89.000 (88.011) Prec@5 100.000 (99.287) +2022-11-14 16:43:26,175 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0993 (0.0748) Prec@1 83.000 (87.955) Prec@5 99.000 (99.284) +2022-11-14 16:43:26,193 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0751) Prec@1 82.000 (87.888) Prec@5 99.000 (99.281) +2022-11-14 16:43:26,213 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0750) Prec@1 90.000 (87.911) Prec@5 98.000 (99.267) +2022-11-14 16:43:26,232 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0337 (0.0746) Prec@1 95.000 (87.989) Prec@5 100.000 (99.275) +2022-11-14 16:43:26,250 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0529 (0.0744) Prec@1 92.000 (88.033) Prec@5 100.000 (99.283) +2022-11-14 16:43:26,272 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0744) Prec@1 89.000 (88.043) Prec@5 99.000 (99.280) +2022-11-14 16:43:26,291 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0744) Prec@1 88.000 (88.043) Prec@5 100.000 (99.287) +2022-11-14 16:43:26,312 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0744) Prec@1 90.000 (88.063) Prec@5 99.000 (99.284) +2022-11-14 16:43:26,332 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0742) Prec@1 92.000 (88.104) Prec@5 99.000 (99.281) +2022-11-14 16:43:26,354 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0542 (0.0739) Prec@1 91.000 (88.134) Prec@5 98.000 (99.268) +2022-11-14 16:43:26,375 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0941 (0.0742) Prec@1 85.000 (88.102) Prec@5 99.000 (99.265) +2022-11-14 16:43:26,393 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1029 (0.0744) Prec@1 86.000 (88.081) Prec@5 99.000 (99.263) +2022-11-14 16:43:26,413 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0655 (0.0744) Prec@1 91.000 (88.110) Prec@5 100.000 (99.270) +2022-11-14 16:43:26,477 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:43:26,871 Epoch: [375][0/500] Time 0.026 (0.026) Data 0.300 (0.300) Loss 0.0317 (0.0317) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:43:27,397 Epoch: [375][10/500] Time 0.060 (0.044) Data 0.003 (0.029) Loss 0.0360 (0.0339) Prec@1 93.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:43:27,968 Epoch: [375][20/500] Time 0.043 (0.047) Data 0.002 (0.016) Loss 0.0343 (0.0340) Prec@1 96.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:43:28,554 Epoch: [375][30/500] Time 0.048 (0.048) Data 0.002 (0.012) Loss 0.0331 (0.0338) Prec@1 95.000 (94.750) Prec@5 99.000 (99.500) +2022-11-14 16:43:29,146 Epoch: [375][40/500] Time 0.055 (0.049) Data 0.002 (0.009) Loss 0.0278 (0.0326) Prec@1 96.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 16:43:29,729 Epoch: [375][50/500] Time 0.054 (0.050) Data 0.002 (0.008) Loss 0.0481 (0.0352) Prec@1 91.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:43:30,323 Epoch: [375][60/500] Time 0.056 (0.050) Data 0.002 (0.007) Loss 0.0097 (0.0315) Prec@1 98.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:43:30,927 Epoch: [375][70/500] Time 0.055 (0.051) Data 0.002 (0.006) Loss 0.0349 (0.0319) Prec@1 94.000 (94.750) Prec@5 99.000 (99.625) +2022-11-14 16:43:31,501 Epoch: [375][80/500] Time 0.060 (0.051) Data 0.002 (0.006) Loss 0.0346 (0.0322) Prec@1 94.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:43:32,077 Epoch: [375][90/500] Time 0.059 (0.051) Data 0.002 (0.005) Loss 0.0192 (0.0309) Prec@1 96.000 (94.800) Prec@5 100.000 (99.700) +2022-11-14 16:43:32,669 Epoch: [375][100/500] Time 0.066 (0.051) Data 0.002 (0.005) Loss 0.0395 (0.0317) Prec@1 94.000 (94.727) Prec@5 100.000 (99.727) +2022-11-14 16:43:33,270 Epoch: [375][110/500] Time 0.058 (0.052) Data 0.002 (0.005) Loss 0.0167 (0.0305) Prec@1 98.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:43:33,839 Epoch: [375][120/500] Time 0.061 (0.051) Data 0.002 (0.005) Loss 0.0321 (0.0306) Prec@1 95.000 (95.000) Prec@5 100.000 (99.769) +2022-11-14 16:43:34,429 Epoch: [375][130/500] Time 0.059 (0.052) Data 0.002 (0.004) Loss 0.0227 (0.0300) Prec@1 96.000 (95.071) Prec@5 100.000 (99.786) +2022-11-14 16:43:35,008 Epoch: [375][140/500] Time 0.053 (0.052) Data 0.002 (0.004) Loss 0.0389 (0.0306) Prec@1 93.000 (94.933) Prec@5 100.000 (99.800) +2022-11-14 16:43:35,605 Epoch: [375][150/500] Time 0.042 (0.052) Data 0.002 (0.004) Loss 0.0385 (0.0311) Prec@1 92.000 (94.750) Prec@5 100.000 (99.812) +2022-11-14 16:43:36,193 Epoch: [375][160/500] Time 0.062 (0.052) Data 0.002 (0.004) Loss 0.0459 (0.0320) Prec@1 93.000 (94.647) Prec@5 100.000 (99.824) +2022-11-14 16:43:36,784 Epoch: [375][170/500] Time 0.058 (0.052) Data 0.002 (0.004) Loss 0.0219 (0.0314) Prec@1 96.000 (94.722) Prec@5 100.000 (99.833) +2022-11-14 16:43:37,341 Epoch: [375][180/500] Time 0.055 (0.052) Data 0.002 (0.004) Loss 0.0320 (0.0314) Prec@1 95.000 (94.737) Prec@5 100.000 (99.842) +2022-11-14 16:43:37,932 Epoch: [375][190/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0217 (0.0310) Prec@1 97.000 (94.850) Prec@5 99.000 (99.800) +2022-11-14 16:43:38,532 Epoch: [375][200/500] Time 0.067 (0.052) Data 0.002 (0.004) Loss 0.0287 (0.0309) Prec@1 96.000 (94.905) Prec@5 100.000 (99.810) +2022-11-14 16:43:39,107 Epoch: [375][210/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0240 (0.0305) Prec@1 97.000 (95.000) Prec@5 99.000 (99.773) +2022-11-14 16:43:39,666 Epoch: [375][220/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0334 (0.0307) Prec@1 94.000 (94.957) Prec@5 100.000 (99.783) +2022-11-14 16:43:40,243 Epoch: [375][230/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0551 (0.0317) Prec@1 91.000 (94.792) Prec@5 99.000 (99.750) +2022-11-14 16:43:40,830 Epoch: [375][240/500] Time 0.065 (0.052) Data 0.002 (0.003) Loss 0.0284 (0.0316) Prec@1 95.000 (94.800) Prec@5 100.000 (99.760) +2022-11-14 16:43:41,410 Epoch: [375][250/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0286 (0.0314) Prec@1 95.000 (94.808) Prec@5 100.000 (99.769) +2022-11-14 16:43:41,987 Epoch: [375][260/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0191 (0.0310) Prec@1 97.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 16:43:42,562 Epoch: [375][270/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0266 (0.0308) Prec@1 97.000 (94.964) Prec@5 100.000 (99.786) +2022-11-14 16:43:43,173 Epoch: [375][280/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0399 (0.0311) Prec@1 92.000 (94.862) Prec@5 100.000 (99.793) +2022-11-14 16:43:43,755 Epoch: [375][290/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0341 (0.0312) Prec@1 93.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:43:44,357 Epoch: [375][300/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0247 (0.0310) Prec@1 96.000 (94.839) Prec@5 100.000 (99.806) +2022-11-14 16:43:44,933 Epoch: [375][310/500] Time 0.053 (0.052) Data 0.002 (0.003) Loss 0.0429 (0.0314) Prec@1 94.000 (94.812) Prec@5 100.000 (99.812) +2022-11-14 16:43:45,516 Epoch: [375][320/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0364 (0.0316) Prec@1 96.000 (94.848) Prec@5 99.000 (99.788) +2022-11-14 16:43:46,082 Epoch: [375][330/500] Time 0.048 (0.052) Data 0.002 (0.003) Loss 0.0248 (0.0314) Prec@1 96.000 (94.882) Prec@5 100.000 (99.794) +2022-11-14 16:43:46,693 Epoch: [375][340/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0313 (0.0314) Prec@1 95.000 (94.886) Prec@5 99.000 (99.771) +2022-11-14 16:43:47,283 Epoch: [375][350/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0203 (0.0310) Prec@1 96.000 (94.917) Prec@5 100.000 (99.778) +2022-11-14 16:43:47,865 Epoch: [375][360/500] Time 0.066 (0.052) Data 0.002 (0.003) Loss 0.0368 (0.0312) Prec@1 94.000 (94.892) Prec@5 100.000 (99.784) +2022-11-14 16:43:48,440 Epoch: [375][370/500] Time 0.066 (0.052) Data 0.002 (0.003) Loss 0.0187 (0.0309) Prec@1 97.000 (94.947) Prec@5 99.000 (99.763) +2022-11-14 16:43:49,034 Epoch: [375][380/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0297 (0.0308) Prec@1 95.000 (94.949) Prec@5 100.000 (99.769) +2022-11-14 16:43:49,613 Epoch: [375][390/500] Time 0.039 (0.052) Data 0.002 (0.003) Loss 0.0242 (0.0307) Prec@1 97.000 (95.000) Prec@5 100.000 (99.775) +2022-11-14 16:43:50,207 Epoch: [375][400/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0194 (0.0304) Prec@1 95.000 (95.000) Prec@5 100.000 (99.780) +2022-11-14 16:43:50,787 Epoch: [375][410/500] Time 0.058 (0.052) Data 0.002 (0.003) Loss 0.0402 (0.0306) Prec@1 95.000 (95.000) Prec@5 100.000 (99.786) +2022-11-14 16:43:51,442 Epoch: [375][420/500] Time 0.041 (0.052) Data 0.002 (0.003) Loss 0.0353 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (99.791) +2022-11-14 16:43:52,034 Epoch: [375][430/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0271 (0.0307) Prec@1 96.000 (95.023) Prec@5 100.000 (99.795) +2022-11-14 16:43:52,616 Epoch: [375][440/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0206 (0.0304) Prec@1 96.000 (95.044) Prec@5 100.000 (99.800) +2022-11-14 16:43:53,219 Epoch: [375][450/500] Time 0.048 (0.052) Data 0.003 (0.003) Loss 0.0251 (0.0303) Prec@1 96.000 (95.065) Prec@5 100.000 (99.804) +2022-11-14 16:43:53,795 Epoch: [375][460/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0229 (0.0302) Prec@1 95.000 (95.064) Prec@5 100.000 (99.809) +2022-11-14 16:43:54,387 Epoch: [375][470/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0299 (0.0302) Prec@1 93.000 (95.021) Prec@5 100.000 (99.812) +2022-11-14 16:43:54,983 Epoch: [375][480/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0298 (0.0301) Prec@1 96.000 (95.041) Prec@5 100.000 (99.816) +2022-11-14 16:43:55,566 Epoch: [375][490/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0218 (0.0300) Prec@1 96.000 (95.060) Prec@5 100.000 (99.820) +2022-11-14 16:43:56,075 Epoch: [375][499/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0197 (0.0298) Prec@1 97.000 (95.098) Prec@5 100.000 (99.824) +2022-11-14 16:43:56,404 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0841 (0.0841) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:43:56,417 Test: [1/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0861 (0.0851) Prec@1 85.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 16:43:56,426 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0986 (0.0896) Prec@1 85.000 (85.333) Prec@5 100.000 (100.000) +2022-11-14 16:43:56,439 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0846) Prec@1 89.000 (86.250) Prec@5 99.000 (99.750) +2022-11-14 16:43:56,449 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0756 (0.0828) Prec@1 87.000 (86.400) Prec@5 100.000 (99.800) +2022-11-14 16:43:56,462 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0459 (0.0767) Prec@1 92.000 (87.333) Prec@5 100.000 (99.833) +2022-11-14 16:43:56,473 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0756) Prec@1 89.000 (87.571) Prec@5 100.000 (99.857) +2022-11-14 16:43:56,491 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0748) Prec@1 90.000 (87.875) Prec@5 99.000 (99.750) +2022-11-14 16:43:56,506 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0688 (0.0741) Prec@1 90.000 (88.111) Prec@5 98.000 (99.556) +2022-11-14 16:43:56,519 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0673 (0.0734) Prec@1 89.000 (88.200) Prec@5 99.000 (99.500) +2022-11-14 16:43:56,537 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0457 (0.0709) Prec@1 93.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 16:43:56,554 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0848 (0.0721) Prec@1 86.000 (88.417) Prec@5 100.000 (99.583) +2022-11-14 16:43:56,571 Test: [12/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0478 (0.0702) Prec@1 94.000 (88.846) Prec@5 100.000 (99.615) +2022-11-14 16:43:56,593 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0701) Prec@1 87.000 (88.714) Prec@5 99.000 (99.571) +2022-11-14 16:43:56,615 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0699) Prec@1 90.000 (88.800) Prec@5 100.000 (99.600) +2022-11-14 16:43:56,630 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0706) Prec@1 88.000 (88.750) Prec@5 100.000 (99.625) +2022-11-14 16:43:56,649 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0374 (0.0686) Prec@1 96.000 (89.176) Prec@5 98.000 (99.529) +2022-11-14 16:43:56,671 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0930 (0.0700) Prec@1 87.000 (89.056) Prec@5 100.000 (99.556) +2022-11-14 16:43:56,690 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1034 (0.0717) Prec@1 82.000 (88.684) Prec@5 99.000 (99.526) +2022-11-14 16:43:56,710 Test: [19/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1032 (0.0733) Prec@1 84.000 (88.450) Prec@5 97.000 (99.400) +2022-11-14 16:43:56,726 Test: [20/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0870 (0.0739) Prec@1 85.000 (88.286) Prec@5 100.000 (99.429) +2022-11-14 16:43:56,744 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0740) Prec@1 88.000 (88.273) Prec@5 98.000 (99.364) +2022-11-14 16:43:56,761 Test: [22/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0751) Prec@1 85.000 (88.130) Prec@5 98.000 (99.304) +2022-11-14 16:43:56,782 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0753) Prec@1 89.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 16:43:56,802 Test: [24/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0757) Prec@1 86.000 (88.080) Prec@5 100.000 (99.360) +2022-11-14 16:43:56,821 Test: [25/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1101 (0.0770) Prec@1 84.000 (87.923) Prec@5 98.000 (99.308) +2022-11-14 16:43:56,841 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0573 (0.0763) Prec@1 91.000 (88.037) Prec@5 100.000 (99.333) +2022-11-14 16:43:56,860 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0532 (0.0755) Prec@1 90.000 (88.107) Prec@5 99.000 (99.321) +2022-11-14 16:43:56,880 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0638 (0.0751) Prec@1 89.000 (88.138) Prec@5 99.000 (99.310) +2022-11-14 16:43:56,898 Test: [29/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0751) Prec@1 88.000 (88.133) Prec@5 100.000 (99.333) +2022-11-14 16:43:56,916 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0746) Prec@1 90.000 (88.194) Prec@5 100.000 (99.355) +2022-11-14 16:43:56,935 Test: [31/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0748) Prec@1 87.000 (88.156) Prec@5 99.000 (99.344) +2022-11-14 16:43:56,957 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0568 (0.0743) Prec@1 90.000 (88.212) Prec@5 100.000 (99.364) +2022-11-14 16:43:56,973 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0740) Prec@1 89.000 (88.235) Prec@5 100.000 (99.382) +2022-11-14 16:43:56,994 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 88.000 (88.229) Prec@5 96.000 (99.286) +2022-11-14 16:43:57,017 Test: [35/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0739) Prec@1 90.000 (88.278) Prec@5 99.000 (99.278) +2022-11-14 16:43:57,038 Test: [36/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0736) Prec@1 89.000 (88.297) Prec@5 99.000 (99.270) +2022-11-14 16:43:57,057 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1041 (0.0744) Prec@1 83.000 (88.158) Prec@5 100.000 (99.289) +2022-11-14 16:43:57,078 Test: [38/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0738) Prec@1 94.000 (88.308) Prec@5 100.000 (99.308) +2022-11-14 16:43:57,095 Test: [39/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0731 (0.0738) Prec@1 87.000 (88.275) Prec@5 99.000 (99.300) +2022-11-14 16:43:57,114 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0742) Prec@1 84.000 (88.171) Prec@5 98.000 (99.268) +2022-11-14 16:43:57,139 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0746) Prec@1 86.000 (88.119) Prec@5 100.000 (99.286) +2022-11-14 16:43:57,158 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0522 (0.0741) Prec@1 91.000 (88.186) Prec@5 100.000 (99.302) +2022-11-14 16:43:57,173 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0811 (0.0742) Prec@1 86.000 (88.136) Prec@5 99.000 (99.295) +2022-11-14 16:43:57,193 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0662 (0.0740) Prec@1 88.000 (88.133) Prec@5 98.000 (99.267) +2022-11-14 16:43:57,214 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0745) Prec@1 83.000 (88.022) Prec@5 99.000 (99.261) +2022-11-14 16:43:57,233 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0743) Prec@1 90.000 (88.064) Prec@5 100.000 (99.277) +2022-11-14 16:43:57,258 Test: [47/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1156 (0.0752) Prec@1 83.000 (87.958) Prec@5 99.000 (99.271) +2022-11-14 16:43:57,276 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0486 (0.0746) Prec@1 93.000 (88.061) Prec@5 100.000 (99.286) +2022-11-14 16:43:57,292 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1030 (0.0752) Prec@1 85.000 (88.000) Prec@5 99.000 (99.280) +2022-11-14 16:43:57,311 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0748) Prec@1 91.000 (88.059) Prec@5 100.000 (99.294) +2022-11-14 16:43:57,331 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0746) Prec@1 86.000 (88.019) Prec@5 99.000 (99.288) +2022-11-14 16:43:57,353 Test: [52/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0744) Prec@1 89.000 (88.038) Prec@5 100.000 (99.302) +2022-11-14 16:43:57,373 Test: [53/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0741) Prec@1 90.000 (88.074) Prec@5 100.000 (99.315) +2022-11-14 16:43:57,391 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0739) Prec@1 90.000 (88.109) Prec@5 100.000 (99.327) +2022-11-14 16:43:57,410 Test: [55/100] Model Time 0.013 (0.008) Loss Time 0.000 (0.000) Loss 0.0817 (0.0741) Prec@1 87.000 (88.089) Prec@5 99.000 (99.321) +2022-11-14 16:43:57,432 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0739 (0.0741) Prec@1 88.000 (88.088) Prec@5 99.000 (99.316) +2022-11-14 16:43:57,452 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0740) Prec@1 87.000 (88.069) Prec@5 99.000 (99.310) +2022-11-14 16:43:57,469 Test: [58/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0743) Prec@1 85.000 (88.017) Prec@5 100.000 (99.322) +2022-11-14 16:43:57,489 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0743) Prec@1 86.000 (87.983) Prec@5 100.000 (99.333) +2022-11-14 16:43:57,509 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0895 (0.0745) Prec@1 85.000 (87.934) Prec@5 99.000 (99.328) +2022-11-14 16:43:57,529 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0745) Prec@1 88.000 (87.935) Prec@5 99.000 (99.323) +2022-11-14 16:43:57,549 Test: [62/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0744) Prec@1 89.000 (87.952) Prec@5 100.000 (99.333) +2022-11-14 16:43:57,567 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0418 (0.0739) Prec@1 93.000 (88.031) Prec@5 100.000 (99.344) +2022-11-14 16:43:57,585 Test: [64/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1067 (0.0744) Prec@1 85.000 (87.985) Prec@5 100.000 (99.354) +2022-11-14 16:43:57,606 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0743) Prec@1 88.000 (87.985) Prec@5 99.000 (99.348) +2022-11-14 16:43:57,624 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0595 (0.0741) Prec@1 91.000 (88.030) Prec@5 99.000 (99.343) +2022-11-14 16:43:57,642 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0740) Prec@1 90.000 (88.059) Prec@5 99.000 (99.338) +2022-11-14 16:43:57,662 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0772 (0.0741) Prec@1 86.000 (88.029) Prec@5 100.000 (99.348) +2022-11-14 16:43:57,685 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0743) Prec@1 86.000 (88.000) Prec@5 99.000 (99.343) +2022-11-14 16:43:57,705 Test: [70/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0942 (0.0745) Prec@1 87.000 (87.986) Prec@5 99.000 (99.338) +2022-11-14 16:43:57,727 Test: [71/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0743) Prec@1 91.000 (88.028) Prec@5 100.000 (99.347) +2022-11-14 16:43:57,746 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0740) Prec@1 94.000 (88.110) Prec@5 100.000 (99.356) +2022-11-14 16:43:57,765 Test: [73/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0737) Prec@1 92.000 (88.162) Prec@5 99.000 (99.351) +2022-11-14 16:43:57,786 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0741) Prec@1 83.000 (88.093) Prec@5 100.000 (99.360) +2022-11-14 16:43:57,806 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0740) Prec@1 89.000 (88.105) Prec@5 100.000 (99.368) +2022-11-14 16:43:57,822 Test: [76/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0738) Prec@1 90.000 (88.130) Prec@5 100.000 (99.377) +2022-11-14 16:43:57,841 Test: [77/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0871 (0.0740) Prec@1 87.000 (88.115) Prec@5 99.000 (99.372) +2022-11-14 16:43:57,859 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0740) Prec@1 88.000 (88.114) Prec@5 100.000 (99.380) +2022-11-14 16:43:57,877 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0654 (0.0739) Prec@1 86.000 (88.088) Prec@5 99.000 (99.375) +2022-11-14 16:43:57,896 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0739) Prec@1 89.000 (88.099) Prec@5 100.000 (99.383) +2022-11-14 16:43:57,916 Test: [81/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0739) Prec@1 87.000 (88.085) Prec@5 100.000 (99.390) +2022-11-14 16:43:57,935 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0741) Prec@1 87.000 (88.072) Prec@5 98.000 (99.373) +2022-11-14 16:43:57,957 Test: [83/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 89.000 (88.083) Prec@5 99.000 (99.369) +2022-11-14 16:43:57,978 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0741) Prec@1 89.000 (88.094) Prec@5 100.000 (99.376) +2022-11-14 16:43:57,995 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1159 (0.0746) Prec@1 80.000 (88.000) Prec@5 99.000 (99.372) +2022-11-14 16:43:58,017 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0745) Prec@1 90.000 (88.023) Prec@5 99.000 (99.368) +2022-11-14 16:43:58,040 Test: [87/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0745) Prec@1 87.000 (88.011) Prec@5 98.000 (99.352) +2022-11-14 16:43:58,061 Test: [88/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0779 (0.0745) Prec@1 86.000 (87.989) Prec@5 100.000 (99.360) +2022-11-14 16:43:58,079 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0748) Prec@1 86.000 (87.967) Prec@5 99.000 (99.356) +2022-11-14 16:43:58,099 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0525 (0.0746) Prec@1 93.000 (88.022) Prec@5 100.000 (99.363) +2022-11-14 16:43:58,121 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0743) Prec@1 92.000 (88.065) Prec@5 100.000 (99.370) +2022-11-14 16:43:58,143 Test: [92/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0742) Prec@1 92.000 (88.108) Prec@5 99.000 (99.366) +2022-11-14 16:43:58,166 Test: [93/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0685 (0.0742) Prec@1 88.000 (88.106) Prec@5 100.000 (99.372) +2022-11-14 16:43:58,183 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0850 (0.0743) Prec@1 85.000 (88.074) Prec@5 99.000 (99.368) +2022-11-14 16:43:58,202 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0743) Prec@1 90.000 (88.094) Prec@5 99.000 (99.365) +2022-11-14 16:43:58,223 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0405 (0.0739) Prec@1 95.000 (88.165) Prec@5 99.000 (99.361) +2022-11-14 16:43:58,239 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0740) Prec@1 87.000 (88.153) Prec@5 100.000 (99.367) +2022-11-14 16:43:58,260 Test: [98/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0744) Prec@1 83.000 (88.101) Prec@5 98.000 (99.354) +2022-11-14 16:43:58,282 Test: [99/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0743) Prec@1 87.000 (88.090) Prec@5 99.000 (99.350) +2022-11-14 16:43:58,349 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:43:58,723 Epoch: [376][0/500] Time 0.025 (0.025) Data 0.280 (0.280) Loss 0.0375 (0.0375) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:43:59,252 Epoch: [376][10/500] Time 0.062 (0.044) Data 0.002 (0.027) Loss 0.0123 (0.0249) Prec@1 99.000 (97.000) Prec@5 100.000 (99.500) +2022-11-14 16:43:59,835 Epoch: [376][20/500] Time 0.051 (0.048) Data 0.002 (0.015) Loss 0.0302 (0.0267) Prec@1 96.000 (96.667) Prec@5 100.000 (99.667) +2022-11-14 16:44:00,439 Epoch: [376][30/500] Time 0.056 (0.050) Data 0.002 (0.011) Loss 0.0299 (0.0275) Prec@1 95.000 (96.250) Prec@5 100.000 (99.750) +2022-11-14 16:44:01,066 Epoch: [376][40/500] Time 0.054 (0.051) Data 0.002 (0.009) Loss 0.0469 (0.0314) Prec@1 93.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 16:44:01,663 Epoch: [376][50/500] Time 0.058 (0.052) Data 0.002 (0.008) Loss 0.0131 (0.0283) Prec@1 97.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 16:44:02,327 Epoch: [376][60/500] Time 0.065 (0.053) Data 0.002 (0.007) Loss 0.0291 (0.0284) Prec@1 96.000 (95.857) Prec@5 100.000 (99.857) +2022-11-14 16:44:02,929 Epoch: [376][70/500] Time 0.048 (0.053) Data 0.002 (0.006) Loss 0.0269 (0.0282) Prec@1 96.000 (95.875) Prec@5 99.000 (99.750) +2022-11-14 16:44:03,515 Epoch: [376][80/500] Time 0.060 (0.053) Data 0.002 (0.006) Loss 0.0276 (0.0282) Prec@1 96.000 (95.889) Prec@5 99.000 (99.667) +2022-11-14 16:44:04,107 Epoch: [376][90/500] Time 0.060 (0.053) Data 0.002 (0.005) Loss 0.0212 (0.0275) Prec@1 96.000 (95.900) Prec@5 100.000 (99.700) +2022-11-14 16:44:04,679 Epoch: [376][100/500] Time 0.046 (0.053) Data 0.003 (0.005) Loss 0.0242 (0.0272) Prec@1 96.000 (95.909) Prec@5 100.000 (99.727) +2022-11-14 16:44:05,267 Epoch: [376][110/500] Time 0.066 (0.053) Data 0.002 (0.005) Loss 0.0239 (0.0269) Prec@1 97.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 16:44:05,860 Epoch: [376][120/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0245 (0.0267) Prec@1 96.000 (96.000) Prec@5 100.000 (99.769) +2022-11-14 16:44:06,464 Epoch: [376][130/500] Time 0.055 (0.053) Data 0.002 (0.004) Loss 0.0227 (0.0264) Prec@1 95.000 (95.929) Prec@5 100.000 (99.786) +2022-11-14 16:44:07,039 Epoch: [376][140/500] Time 0.053 (0.053) Data 0.002 (0.004) Loss 0.0387 (0.0272) Prec@1 93.000 (95.733) Prec@5 100.000 (99.800) +2022-11-14 16:44:07,615 Epoch: [376][150/500] Time 0.052 (0.053) Data 0.002 (0.004) Loss 0.0266 (0.0272) Prec@1 95.000 (95.688) Prec@5 100.000 (99.812) +2022-11-14 16:44:08,182 Epoch: [376][160/500] Time 0.063 (0.053) Data 0.002 (0.004) Loss 0.0227 (0.0269) Prec@1 97.000 (95.765) Prec@5 100.000 (99.824) +2022-11-14 16:44:08,749 Epoch: [376][170/500] Time 0.049 (0.053) Data 0.002 (0.004) Loss 0.0382 (0.0276) Prec@1 94.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:44:09,416 Epoch: [376][180/500] Time 0.047 (0.053) Data 0.002 (0.004) Loss 0.0297 (0.0277) Prec@1 95.000 (95.632) Prec@5 100.000 (99.842) +2022-11-14 16:44:10,034 Epoch: [376][190/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0308 (0.0278) Prec@1 95.000 (95.600) Prec@5 100.000 (99.850) +2022-11-14 16:44:10,599 Epoch: [376][200/500] Time 0.056 (0.053) Data 0.002 (0.004) Loss 0.0368 (0.0283) Prec@1 94.000 (95.524) Prec@5 100.000 (99.857) +2022-11-14 16:44:11,176 Epoch: [376][210/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0238 (0.0281) Prec@1 96.000 (95.545) Prec@5 100.000 (99.864) +2022-11-14 16:44:11,775 Epoch: [376][220/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0289 (0.0281) Prec@1 96.000 (95.565) Prec@5 100.000 (99.870) +2022-11-14 16:44:12,356 Epoch: [376][230/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0422 (0.0287) Prec@1 92.000 (95.417) Prec@5 99.000 (99.833) +2022-11-14 16:44:12,934 Epoch: [376][240/500] Time 0.047 (0.053) Data 0.002 (0.003) Loss 0.0247 (0.0285) Prec@1 97.000 (95.480) Prec@5 100.000 (99.840) +2022-11-14 16:44:13,522 Epoch: [376][250/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0452 (0.0292) Prec@1 91.000 (95.308) Prec@5 100.000 (99.846) +2022-11-14 16:44:14,089 Epoch: [376][260/500] Time 0.057 (0.053) Data 0.003 (0.003) Loss 0.0169 (0.0287) Prec@1 97.000 (95.370) Prec@5 100.000 (99.852) +2022-11-14 16:44:14,724 Epoch: [376][270/500] Time 0.069 (0.053) Data 0.003 (0.003) Loss 0.0273 (0.0287) Prec@1 96.000 (95.393) Prec@5 100.000 (99.857) +2022-11-14 16:44:15,294 Epoch: [376][280/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0449 (0.0292) Prec@1 94.000 (95.345) Prec@5 99.000 (99.828) +2022-11-14 16:44:15,866 Epoch: [376][290/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0288 (0.0292) Prec@1 97.000 (95.400) Prec@5 100.000 (99.833) +2022-11-14 16:44:16,455 Epoch: [376][300/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0283 (0.0292) Prec@1 96.000 (95.419) Prec@5 100.000 (99.839) +2022-11-14 16:44:17,040 Epoch: [376][310/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0201 (0.0289) Prec@1 97.000 (95.469) Prec@5 100.000 (99.844) +2022-11-14 16:44:17,607 Epoch: [376][320/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0255 (0.0288) Prec@1 97.000 (95.515) Prec@5 100.000 (99.848) +2022-11-14 16:44:18,239 Epoch: [376][330/500] Time 0.073 (0.053) Data 0.002 (0.003) Loss 0.0210 (0.0286) Prec@1 96.000 (95.529) Prec@5 100.000 (99.853) +2022-11-14 16:44:18,798 Epoch: [376][340/500] Time 0.056 (0.053) Data 0.003 (0.003) Loss 0.0248 (0.0285) Prec@1 96.000 (95.543) Prec@5 100.000 (99.857) +2022-11-14 16:44:19,371 Epoch: [376][350/500] Time 0.056 (0.053) Data 0.003 (0.003) Loss 0.0424 (0.0288) Prec@1 93.000 (95.472) Prec@5 99.000 (99.833) +2022-11-14 16:44:19,956 Epoch: [376][360/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0438 (0.0292) Prec@1 91.000 (95.351) Prec@5 100.000 (99.838) +2022-11-14 16:44:20,592 Epoch: [376][370/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0389 (0.0295) Prec@1 93.000 (95.289) Prec@5 100.000 (99.842) +2022-11-14 16:44:21,169 Epoch: [376][380/500] Time 0.051 (0.053) Data 0.003 (0.003) Loss 0.0275 (0.0295) Prec@1 96.000 (95.308) Prec@5 100.000 (99.846) +2022-11-14 16:44:21,750 Epoch: [376][390/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0232 (0.0293) Prec@1 96.000 (95.325) Prec@5 99.000 (99.825) +2022-11-14 16:44:22,343 Epoch: [376][400/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0327 (0.0294) Prec@1 95.000 (95.317) Prec@5 99.000 (99.805) +2022-11-14 16:44:22,928 Epoch: [376][410/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0268 (0.0293) Prec@1 96.000 (95.333) Prec@5 100.000 (99.810) +2022-11-14 16:44:23,530 Epoch: [376][420/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0165 (0.0290) Prec@1 98.000 (95.395) Prec@5 100.000 (99.814) +2022-11-14 16:44:24,108 Epoch: [376][430/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0284 (0.0290) Prec@1 95.000 (95.386) Prec@5 100.000 (99.818) +2022-11-14 16:44:24,690 Epoch: [376][440/500] Time 0.042 (0.053) Data 0.002 (0.003) Loss 0.0154 (0.0287) Prec@1 97.000 (95.422) Prec@5 99.000 (99.800) +2022-11-14 16:44:25,288 Epoch: [376][450/500] Time 0.060 (0.053) Data 0.002 (0.003) Loss 0.0245 (0.0286) Prec@1 96.000 (95.435) Prec@5 100.000 (99.804) +2022-11-14 16:44:25,926 Epoch: [376][460/500] Time 0.081 (0.053) Data 0.002 (0.003) Loss 0.0150 (0.0283) Prec@1 99.000 (95.511) Prec@5 100.000 (99.809) +2022-11-14 16:44:26,595 Epoch: [376][470/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0280 (0.0283) Prec@1 96.000 (95.521) Prec@5 100.000 (99.812) +2022-11-14 16:44:27,190 Epoch: [376][480/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0219 (0.0282) Prec@1 96.000 (95.531) Prec@5 100.000 (99.816) +2022-11-14 16:44:27,813 Epoch: [376][490/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0430 (0.0285) Prec@1 91.000 (95.440) Prec@5 100.000 (99.820) +2022-11-14 16:44:28,428 Epoch: [376][499/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0264 (0.0284) Prec@1 95.000 (95.431) Prec@5 100.000 (99.824) +2022-11-14 16:44:28,792 Test: [0/100] Model Time 0.017 (0.017) Loss Time 0.000 (0.000) Loss 0.0558 (0.0558) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:44:28,806 Test: [1/100] Model Time 0.008 (0.012) Loss Time 0.000 (0.000) Loss 0.0598 (0.0578) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:44:28,815 Test: [2/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0690 (0.0615) Prec@1 88.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 16:44:28,827 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0634 (0.0620) Prec@1 89.000 (89.750) Prec@5 99.000 (99.500) +2022-11-14 16:44:28,839 Test: [4/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0763 (0.0649) Prec@1 87.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 16:44:28,851 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0427 (0.0612) Prec@1 91.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 16:44:28,862 Test: [6/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0734 (0.0629) Prec@1 88.000 (89.286) Prec@5 100.000 (99.571) +2022-11-14 16:44:28,879 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0873 (0.0660) Prec@1 83.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 16:44:28,894 Test: [8/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0855 (0.0681) Prec@1 88.000 (88.444) Prec@5 98.000 (99.222) +2022-11-14 16:44:28,914 Test: [9/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0805 (0.0694) Prec@1 85.000 (88.100) Prec@5 98.000 (99.100) +2022-11-14 16:44:28,932 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0648 (0.0689) Prec@1 89.000 (88.182) Prec@5 100.000 (99.182) +2022-11-14 16:44:28,949 Test: [11/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0641 (0.0685) Prec@1 92.000 (88.500) Prec@5 100.000 (99.250) +2022-11-14 16:44:28,966 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0596 (0.0679) Prec@1 90.000 (88.615) Prec@5 100.000 (99.308) +2022-11-14 16:44:28,987 Test: [13/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0898 (0.0694) Prec@1 87.000 (88.500) Prec@5 99.000 (99.286) +2022-11-14 16:44:29,008 Test: [14/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0748 (0.0698) Prec@1 88.000 (88.467) Prec@5 100.000 (99.333) +2022-11-14 16:44:29,025 Test: [15/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0683 (0.0697) Prec@1 89.000 (88.500) Prec@5 99.000 (99.312) +2022-11-14 16:44:29,049 Test: [16/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0559 (0.0689) Prec@1 91.000 (88.647) Prec@5 99.000 (99.294) +2022-11-14 16:44:29,071 Test: [17/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0864 (0.0698) Prec@1 89.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 16:44:29,088 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1218 (0.0726) Prec@1 81.000 (88.263) Prec@5 97.000 (99.211) +2022-11-14 16:44:29,106 Test: [19/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0920 (0.0736) Prec@1 83.000 (88.000) Prec@5 98.000 (99.150) +2022-11-14 16:44:29,128 Test: [20/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0739 (0.0736) Prec@1 87.000 (87.952) Prec@5 100.000 (99.190) +2022-11-14 16:44:29,149 Test: [21/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0743) Prec@1 86.000 (87.864) Prec@5 99.000 (99.182) +2022-11-14 16:44:29,168 Test: [22/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0917 (0.0750) Prec@1 87.000 (87.826) Prec@5 99.000 (99.174) +2022-11-14 16:44:29,186 Test: [23/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0828 (0.0753) Prec@1 88.000 (87.833) Prec@5 100.000 (99.208) +2022-11-14 16:44:29,206 Test: [24/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1025 (0.0764) Prec@1 83.000 (87.640) Prec@5 100.000 (99.240) +2022-11-14 16:44:29,226 Test: [25/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0767) Prec@1 86.000 (87.577) Prec@5 99.000 (99.231) +2022-11-14 16:44:29,245 Test: [26/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0425 (0.0755) Prec@1 93.000 (87.778) Prec@5 100.000 (99.259) +2022-11-14 16:44:29,262 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0589 (0.0749) Prec@1 90.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 16:44:29,281 Test: [28/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0748) Prec@1 87.000 (87.828) Prec@5 100.000 (99.310) +2022-11-14 16:44:29,301 Test: [29/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0879 (0.0752) Prec@1 85.000 (87.733) Prec@5 99.000 (99.300) +2022-11-14 16:44:29,321 Test: [30/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0750) Prec@1 89.000 (87.774) Prec@5 99.000 (99.290) +2022-11-14 16:44:29,343 Test: [31/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0748) Prec@1 90.000 (87.844) Prec@5 98.000 (99.250) +2022-11-14 16:44:29,365 Test: [32/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0750 (0.0749) Prec@1 87.000 (87.818) Prec@5 100.000 (99.273) +2022-11-14 16:44:29,383 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1023 (0.0757) Prec@1 82.000 (87.647) Prec@5 100.000 (99.294) +2022-11-14 16:44:29,404 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0759) Prec@1 86.000 (87.600) Prec@5 98.000 (99.257) +2022-11-14 16:44:29,428 Test: [35/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0756) Prec@1 91.000 (87.694) Prec@5 99.000 (99.250) +2022-11-14 16:44:29,447 Test: [36/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0820 (0.0758) Prec@1 87.000 (87.676) Prec@5 99.000 (99.243) +2022-11-14 16:44:29,466 Test: [37/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0846 (0.0760) Prec@1 85.000 (87.605) Prec@5 100.000 (99.263) +2022-11-14 16:44:29,487 Test: [38/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0548 (0.0755) Prec@1 94.000 (87.769) Prec@5 99.000 (99.256) +2022-11-14 16:44:29,507 Test: [39/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0422 (0.0746) Prec@1 94.000 (87.925) Prec@5 99.000 (99.250) +2022-11-14 16:44:29,527 Test: [40/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0854 (0.0749) Prec@1 86.000 (87.878) Prec@5 99.000 (99.244) +2022-11-14 16:44:29,551 Test: [41/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0682 (0.0747) Prec@1 89.000 (87.905) Prec@5 99.000 (99.238) +2022-11-14 16:44:29,571 Test: [42/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0538 (0.0742) Prec@1 91.000 (87.977) Prec@5 99.000 (99.233) +2022-11-14 16:44:29,591 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0717 (0.0742) Prec@1 90.000 (88.023) Prec@5 99.000 (99.227) +2022-11-14 16:44:29,608 Test: [44/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0640 (0.0740) Prec@1 91.000 (88.089) Prec@5 98.000 (99.200) +2022-11-14 16:44:29,629 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0937 (0.0744) Prec@1 86.000 (88.043) Prec@5 99.000 (99.196) +2022-11-14 16:44:29,648 Test: [46/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0528 (0.0739) Prec@1 92.000 (88.128) Prec@5 100.000 (99.213) +2022-11-14 16:44:29,668 Test: [47/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0887 (0.0742) Prec@1 85.000 (88.062) Prec@5 99.000 (99.208) +2022-11-14 16:44:29,689 Test: [48/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0587 (0.0739) Prec@1 91.000 (88.122) Prec@5 99.000 (99.204) +2022-11-14 16:44:29,709 Test: [49/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0875 (0.0742) Prec@1 87.000 (88.100) Prec@5 98.000 (99.180) +2022-11-14 16:44:29,726 Test: [50/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0741) Prec@1 87.000 (88.078) Prec@5 100.000 (99.196) +2022-11-14 16:44:29,748 Test: [51/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0836 (0.0743) Prec@1 85.000 (88.019) Prec@5 97.000 (99.154) +2022-11-14 16:44:29,769 Test: [52/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0724 (0.0743) Prec@1 86.000 (87.981) Prec@5 100.000 (99.170) +2022-11-14 16:44:29,787 Test: [53/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0525 (0.0739) Prec@1 92.000 (88.056) Prec@5 100.000 (99.185) +2022-11-14 16:44:29,809 Test: [54/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0958 (0.0743) Prec@1 86.000 (88.018) Prec@5 100.000 (99.200) +2022-11-14 16:44:29,837 Test: [55/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0764 (0.0743) Prec@1 88.000 (88.018) Prec@5 99.000 (99.196) +2022-11-14 16:44:29,857 Test: [56/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0744) Prec@1 88.000 (88.018) Prec@5 99.000 (99.193) +2022-11-14 16:44:29,879 Test: [57/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0592 (0.0741) Prec@1 91.000 (88.069) Prec@5 100.000 (99.207) +2022-11-14 16:44:29,902 Test: [58/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0743) Prec@1 85.000 (88.017) Prec@5 100.000 (99.220) +2022-11-14 16:44:29,919 Test: [59/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0841 (0.0744) Prec@1 86.000 (87.983) Prec@5 99.000 (99.217) +2022-11-14 16:44:29,936 Test: [60/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0823 (0.0746) Prec@1 89.000 (88.000) Prec@5 99.000 (99.213) +2022-11-14 16:44:29,957 Test: [61/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0744) Prec@1 90.000 (88.032) Prec@5 99.000 (99.210) +2022-11-14 16:44:29,980 Test: [62/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0742) Prec@1 90.000 (88.063) Prec@5 100.000 (99.222) +2022-11-14 16:44:30,002 Test: [63/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0481 (0.0738) Prec@1 91.000 (88.109) Prec@5 100.000 (99.234) +2022-11-14 16:44:30,026 Test: [64/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0739) Prec@1 88.000 (88.108) Prec@5 99.000 (99.231) +2022-11-14 16:44:30,047 Test: [65/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0738) Prec@1 89.000 (88.121) Prec@5 100.000 (99.242) +2022-11-14 16:44:30,067 Test: [66/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0291 (0.0731) Prec@1 97.000 (88.254) Prec@5 100.000 (99.254) +2022-11-14 16:44:30,086 Test: [67/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0720 (0.0731) Prec@1 90.000 (88.279) Prec@5 100.000 (99.265) +2022-11-14 16:44:30,110 Test: [68/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0519 (0.0728) Prec@1 90.000 (88.304) Prec@5 99.000 (99.261) +2022-11-14 16:44:30,129 Test: [69/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0646 (0.0727) Prec@1 90.000 (88.329) Prec@5 98.000 (99.243) +2022-11-14 16:44:30,147 Test: [70/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0866 (0.0729) Prec@1 87.000 (88.310) Prec@5 99.000 (99.239) +2022-11-14 16:44:30,164 Test: [71/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0622 (0.0727) Prec@1 88.000 (88.306) Prec@5 99.000 (99.236) +2022-11-14 16:44:30,183 Test: [72/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0396 (0.0723) Prec@1 94.000 (88.384) Prec@5 100.000 (99.247) +2022-11-14 16:44:30,207 Test: [73/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0374 (0.0718) Prec@1 96.000 (88.486) Prec@5 100.000 (99.257) +2022-11-14 16:44:30,226 Test: [74/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0878 (0.0720) Prec@1 88.000 (88.480) Prec@5 98.000 (99.240) +2022-11-14 16:44:30,244 Test: [75/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0718) Prec@1 90.000 (88.500) Prec@5 99.000 (99.237) +2022-11-14 16:44:30,266 Test: [76/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0636 (0.0717) Prec@1 90.000 (88.519) Prec@5 99.000 (99.234) +2022-11-14 16:44:30,286 Test: [77/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1036 (0.0721) Prec@1 84.000 (88.462) Prec@5 100.000 (99.244) +2022-11-14 16:44:30,308 Test: [78/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0796 (0.0722) Prec@1 88.000 (88.456) Prec@5 99.000 (99.241) +2022-11-14 16:44:30,329 Test: [79/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0721 (0.0722) Prec@1 85.000 (88.412) Prec@5 99.000 (99.237) +2022-11-14 16:44:30,351 Test: [80/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0948 (0.0725) Prec@1 85.000 (88.370) Prec@5 100.000 (99.247) +2022-11-14 16:44:30,370 Test: [81/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0757 (0.0725) Prec@1 87.000 (88.354) Prec@5 99.000 (99.244) +2022-11-14 16:44:30,388 Test: [82/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0845 (0.0727) Prec@1 89.000 (88.361) Prec@5 98.000 (99.229) +2022-11-14 16:44:30,415 Test: [83/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0759 (0.0727) Prec@1 86.000 (88.333) Prec@5 99.000 (99.226) +2022-11-14 16:44:30,435 Test: [84/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0730) Prec@1 85.000 (88.294) Prec@5 97.000 (99.200) +2022-11-14 16:44:30,453 Test: [85/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0940 (0.0733) Prec@1 88.000 (88.291) Prec@5 100.000 (99.209) +2022-11-14 16:44:30,474 Test: [86/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0732) Prec@1 89.000 (88.299) Prec@5 99.000 (99.207) +2022-11-14 16:44:30,498 Test: [87/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0624 (0.0731) Prec@1 90.000 (88.318) Prec@5 98.000 (99.193) +2022-11-14 16:44:30,524 Test: [88/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0821 (0.0732) Prec@1 84.000 (88.270) Prec@5 100.000 (99.202) +2022-11-14 16:44:30,552 Test: [89/100] Model Time 0.014 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0733) Prec@1 88.000 (88.267) Prec@5 99.000 (99.200) +2022-11-14 16:44:30,578 Test: [90/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0601 (0.0731) Prec@1 90.000 (88.286) Prec@5 100.000 (99.209) +2022-11-14 16:44:30,608 Test: [91/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0436 (0.0728) Prec@1 94.000 (88.348) Prec@5 99.000 (99.207) +2022-11-14 16:44:30,631 Test: [92/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0729) Prec@1 85.000 (88.312) Prec@5 100.000 (99.215) +2022-11-14 16:44:30,655 Test: [93/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0797 (0.0729) Prec@1 88.000 (88.309) Prec@5 99.000 (99.213) +2022-11-14 16:44:30,677 Test: [94/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0729) Prec@1 87.000 (88.295) Prec@5 100.000 (99.221) +2022-11-14 16:44:30,699 Test: [95/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0728) Prec@1 90.000 (88.312) Prec@5 100.000 (99.229) +2022-11-14 16:44:30,717 Test: [96/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0617 (0.0727) Prec@1 89.000 (88.320) Prec@5 99.000 (99.227) +2022-11-14 16:44:30,737 Test: [97/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0927 (0.0729) Prec@1 85.000 (88.286) Prec@5 99.000 (99.224) +2022-11-14 16:44:30,759 Test: [98/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1002 (0.0731) Prec@1 86.000 (88.263) Prec@5 100.000 (99.232) +2022-11-14 16:44:30,778 Test: [99/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0663 (0.0731) Prec@1 89.000 (88.270) Prec@5 100.000 (99.240) +2022-11-14 16:44:30,844 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:44:31,262 Epoch: [377][0/500] Time 0.025 (0.025) Data 0.314 (0.314) Loss 0.0421 (0.0421) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:44:31,772 Epoch: [377][10/500] Time 0.060 (0.043) Data 0.002 (0.030) Loss 0.0345 (0.0383) Prec@1 94.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:44:32,406 Epoch: [377][20/500] Time 0.052 (0.050) Data 0.002 (0.017) Loss 0.0112 (0.0293) Prec@1 98.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:44:32,991 Epoch: [377][30/500] Time 0.052 (0.051) Data 0.002 (0.012) Loss 0.0183 (0.0265) Prec@1 98.000 (96.250) Prec@5 100.000 (99.750) +2022-11-14 16:44:33,618 Epoch: [377][40/500] Time 0.060 (0.052) Data 0.002 (0.010) Loss 0.0301 (0.0273) Prec@1 96.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:44:34,184 Epoch: [377][50/500] Time 0.056 (0.052) Data 0.002 (0.008) Loss 0.0269 (0.0272) Prec@1 95.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:44:34,813 Epoch: [377][60/500] Time 0.053 (0.053) Data 0.002 (0.007) Loss 0.0305 (0.0277) Prec@1 94.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 16:44:35,388 Epoch: [377][70/500] Time 0.051 (0.053) Data 0.002 (0.006) Loss 0.0490 (0.0303) Prec@1 92.000 (95.250) Prec@5 99.000 (99.750) +2022-11-14 16:44:35,974 Epoch: [377][80/500] Time 0.060 (0.053) Data 0.002 (0.006) Loss 0.0177 (0.0289) Prec@1 97.000 (95.444) Prec@5 100.000 (99.778) +2022-11-14 16:44:36,553 Epoch: [377][90/500] Time 0.065 (0.053) Data 0.002 (0.006) Loss 0.0175 (0.0278) Prec@1 98.000 (95.700) Prec@5 100.000 (99.800) +2022-11-14 16:44:37,134 Epoch: [377][100/500] Time 0.064 (0.052) Data 0.002 (0.005) Loss 0.0329 (0.0283) Prec@1 93.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 16:44:37,750 Epoch: [377][110/500] Time 0.052 (0.053) Data 0.002 (0.005) Loss 0.0182 (0.0274) Prec@1 98.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:44:38,383 Epoch: [377][120/500] Time 0.054 (0.053) Data 0.002 (0.005) Loss 0.0170 (0.0266) Prec@1 96.000 (95.692) Prec@5 100.000 (99.846) +2022-11-14 16:44:38,967 Epoch: [377][130/500] Time 0.063 (0.053) Data 0.002 (0.005) Loss 0.0296 (0.0268) Prec@1 94.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 16:44:39,599 Epoch: [377][140/500] Time 0.083 (0.053) Data 0.002 (0.004) Loss 0.0308 (0.0271) Prec@1 96.000 (95.600) Prec@5 100.000 (99.867) +2022-11-14 16:44:40,175 Epoch: [377][150/500] Time 0.054 (0.053) Data 0.002 (0.004) Loss 0.0266 (0.0271) Prec@1 97.000 (95.688) Prec@5 100.000 (99.875) +2022-11-14 16:44:40,831 Epoch: [377][160/500] Time 0.079 (0.054) Data 0.002 (0.004) Loss 0.0306 (0.0273) Prec@1 96.000 (95.706) Prec@5 99.000 (99.824) +2022-11-14 16:44:41,537 Epoch: [377][170/500] Time 0.071 (0.054) Data 0.003 (0.004) Loss 0.0293 (0.0274) Prec@1 95.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:44:42,166 Epoch: [377][180/500] Time 0.061 (0.054) Data 0.002 (0.004) Loss 0.0353 (0.0278) Prec@1 94.000 (95.579) Prec@5 100.000 (99.842) +2022-11-14 16:44:42,753 Epoch: [377][190/500] Time 0.053 (0.054) Data 0.002 (0.004) Loss 0.0388 (0.0284) Prec@1 95.000 (95.550) Prec@5 100.000 (99.850) +2022-11-14 16:44:43,358 Epoch: [377][200/500] Time 0.060 (0.054) Data 0.002 (0.004) Loss 0.0313 (0.0285) Prec@1 95.000 (95.524) Prec@5 100.000 (99.857) +2022-11-14 16:44:44,045 Epoch: [377][210/500] Time 0.064 (0.054) Data 0.002 (0.004) Loss 0.0663 (0.0302) Prec@1 89.000 (95.227) Prec@5 99.000 (99.818) +2022-11-14 16:44:44,712 Epoch: [377][220/500] Time 0.068 (0.055) Data 0.002 (0.004) Loss 0.0125 (0.0294) Prec@1 98.000 (95.348) Prec@5 100.000 (99.826) +2022-11-14 16:44:45,283 Epoch: [377][230/500] Time 0.047 (0.055) Data 0.002 (0.003) Loss 0.0274 (0.0294) Prec@1 94.000 (95.292) Prec@5 100.000 (99.833) +2022-11-14 16:44:45,933 Epoch: [377][240/500] Time 0.080 (0.055) Data 0.002 (0.003) Loss 0.0413 (0.0298) Prec@1 92.000 (95.160) Prec@5 99.000 (99.800) +2022-11-14 16:44:46,483 Epoch: [377][250/500] Time 0.048 (0.054) Data 0.002 (0.003) Loss 0.0385 (0.0302) Prec@1 92.000 (95.038) Prec@5 100.000 (99.808) +2022-11-14 16:44:47,112 Epoch: [377][260/500] Time 0.046 (0.055) Data 0.002 (0.003) Loss 0.0374 (0.0304) Prec@1 94.000 (95.000) Prec@5 100.000 (99.815) +2022-11-14 16:44:47,846 Epoch: [377][270/500] Time 0.072 (0.055) Data 0.002 (0.003) Loss 0.0368 (0.0307) Prec@1 93.000 (94.929) Prec@5 100.000 (99.821) +2022-11-14 16:44:48,581 Epoch: [377][280/500] Time 0.065 (0.055) Data 0.002 (0.003) Loss 0.0208 (0.0303) Prec@1 99.000 (95.069) Prec@5 100.000 (99.828) +2022-11-14 16:44:49,307 Epoch: [377][290/500] Time 0.072 (0.056) Data 0.002 (0.003) Loss 0.0288 (0.0303) Prec@1 96.000 (95.100) Prec@5 100.000 (99.833) +2022-11-14 16:44:49,941 Epoch: [377][300/500] Time 0.051 (0.056) Data 0.002 (0.003) Loss 0.0174 (0.0299) Prec@1 99.000 (95.226) Prec@5 100.000 (99.839) +2022-11-14 16:44:50,551 Epoch: [377][310/500] Time 0.069 (0.056) Data 0.002 (0.003) Loss 0.0163 (0.0294) Prec@1 97.000 (95.281) Prec@5 100.000 (99.844) +2022-11-14 16:44:51,160 Epoch: [377][320/500] Time 0.049 (0.056) Data 0.002 (0.003) Loss 0.0273 (0.0294) Prec@1 94.000 (95.242) Prec@5 100.000 (99.848) +2022-11-14 16:44:51,747 Epoch: [377][330/500] Time 0.041 (0.056) Data 0.002 (0.003) Loss 0.0319 (0.0294) Prec@1 94.000 (95.206) Prec@5 100.000 (99.853) +2022-11-14 16:44:52,414 Epoch: [377][340/500] Time 0.054 (0.056) Data 0.002 (0.003) Loss 0.0356 (0.0296) Prec@1 94.000 (95.171) Prec@5 100.000 (99.857) +2022-11-14 16:44:53,001 Epoch: [377][350/500] Time 0.059 (0.056) Data 0.002 (0.003) Loss 0.0519 (0.0302) Prec@1 94.000 (95.139) Prec@5 99.000 (99.833) +2022-11-14 16:44:53,601 Epoch: [377][360/500] Time 0.056 (0.056) Data 0.002 (0.003) Loss 0.0278 (0.0302) Prec@1 95.000 (95.135) Prec@5 100.000 (99.838) +2022-11-14 16:44:54,196 Epoch: [377][370/500] Time 0.052 (0.056) Data 0.002 (0.003) Loss 0.0287 (0.0301) Prec@1 93.000 (95.079) Prec@5 100.000 (99.842) +2022-11-14 16:44:54,837 Epoch: [377][380/500] Time 0.069 (0.056) Data 0.002 (0.003) Loss 0.0308 (0.0302) Prec@1 94.000 (95.051) Prec@5 99.000 (99.821) +2022-11-14 16:44:55,464 Epoch: [377][390/500] Time 0.057 (0.056) Data 0.002 (0.003) Loss 0.0470 (0.0306) Prec@1 91.000 (94.950) Prec@5 99.000 (99.800) +2022-11-14 16:44:56,064 Epoch: [377][400/500] Time 0.067 (0.056) Data 0.002 (0.003) Loss 0.0279 (0.0305) Prec@1 95.000 (94.951) Prec@5 100.000 (99.805) +2022-11-14 16:44:56,719 Epoch: [377][410/500] Time 0.069 (0.056) Data 0.002 (0.003) Loss 0.0636 (0.0313) Prec@1 89.000 (94.810) Prec@5 100.000 (99.810) +2022-11-14 16:44:57,363 Epoch: [377][420/500] Time 0.076 (0.056) Data 0.002 (0.003) Loss 0.0385 (0.0315) Prec@1 92.000 (94.744) Prec@5 100.000 (99.814) +2022-11-14 16:44:57,956 Epoch: [377][430/500] Time 0.048 (0.056) Data 0.003 (0.003) Loss 0.0225 (0.0313) Prec@1 97.000 (94.795) Prec@5 100.000 (99.818) +2022-11-14 16:44:58,632 Epoch: [377][440/500] Time 0.074 (0.056) Data 0.002 (0.003) Loss 0.0739 (0.0322) Prec@1 86.000 (94.600) Prec@5 100.000 (99.822) +2022-11-14 16:44:59,233 Epoch: [377][450/500] Time 0.061 (0.056) Data 0.002 (0.003) Loss 0.0179 (0.0319) Prec@1 98.000 (94.674) Prec@5 100.000 (99.826) +2022-11-14 16:44:59,834 Epoch: [377][460/500] Time 0.070 (0.056) Data 0.002 (0.003) Loss 0.0248 (0.0317) Prec@1 97.000 (94.723) Prec@5 100.000 (99.830) +2022-11-14 16:45:00,410 Epoch: [377][470/500] Time 0.061 (0.056) Data 0.003 (0.003) Loss 0.0229 (0.0316) Prec@1 96.000 (94.750) Prec@5 99.000 (99.812) +2022-11-14 16:45:00,996 Epoch: [377][480/500] Time 0.062 (0.055) Data 0.002 (0.003) Loss 0.0285 (0.0315) Prec@1 95.000 (94.755) Prec@5 100.000 (99.816) +2022-11-14 16:45:01,597 Epoch: [377][490/500] Time 0.053 (0.055) Data 0.002 (0.003) Loss 0.0223 (0.0313) Prec@1 97.000 (94.800) Prec@5 100.000 (99.820) +2022-11-14 16:45:02,126 Epoch: [377][499/500] Time 0.053 (0.055) Data 0.002 (0.003) Loss 0.0629 (0.0319) Prec@1 90.000 (94.706) Prec@5 99.000 (99.804) +2022-11-14 16:45:02,469 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0604 (0.0604) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:45:02,480 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0623 (0.0614) Prec@1 91.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:45:02,490 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0718 (0.0649) Prec@1 88.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 16:45:02,504 Test: [3/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0524 (0.0618) Prec@1 92.000 (89.500) Prec@5 99.000 (99.250) +2022-11-14 16:45:02,513 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0843 (0.0663) Prec@1 83.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 16:45:02,525 Test: [5/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0489 (0.0634) Prec@1 91.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 16:45:02,539 Test: [6/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0634) Prec@1 90.000 (88.857) Prec@5 99.000 (99.286) +2022-11-14 16:45:02,554 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1013 (0.0682) Prec@1 84.000 (88.250) Prec@5 98.000 (99.125) +2022-11-14 16:45:02,571 Test: [8/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0743 (0.0689) Prec@1 87.000 (88.111) Prec@5 99.000 (99.111) +2022-11-14 16:45:02,587 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0700) Prec@1 87.000 (88.000) Prec@5 99.000 (99.100) +2022-11-14 16:45:02,600 Test: [10/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0432 (0.0676) Prec@1 93.000 (88.455) Prec@5 100.000 (99.182) +2022-11-14 16:45:02,613 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0679) Prec@1 90.000 (88.583) Prec@5 100.000 (99.250) +2022-11-14 16:45:02,631 Test: [12/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0632 (0.0675) Prec@1 91.000 (88.769) Prec@5 99.000 (99.231) +2022-11-14 16:45:02,651 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0684) Prec@1 86.000 (88.571) Prec@5 98.000 (99.143) +2022-11-14 16:45:02,670 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0686) Prec@1 85.000 (88.333) Prec@5 100.000 (99.200) +2022-11-14 16:45:02,688 Test: [15/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0689) Prec@1 88.000 (88.312) Prec@5 100.000 (99.250) +2022-11-14 16:45:02,706 Test: [16/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0677) Prec@1 94.000 (88.647) Prec@5 98.000 (99.176) +2022-11-14 16:45:02,730 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1207 (0.0706) Prec@1 81.000 (88.222) Prec@5 99.000 (99.167) +2022-11-14 16:45:02,750 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0966 (0.0720) Prec@1 82.000 (87.895) Prec@5 99.000 (99.158) +2022-11-14 16:45:02,768 Test: [19/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0732) Prec@1 83.000 (87.650) Prec@5 98.000 (99.100) +2022-11-14 16:45:02,787 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0734) Prec@1 88.000 (87.667) Prec@5 100.000 (99.143) +2022-11-14 16:45:02,807 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0745) Prec@1 85.000 (87.545) Prec@5 99.000 (99.136) +2022-11-14 16:45:02,828 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.0758) Prec@1 84.000 (87.391) Prec@5 98.000 (99.087) +2022-11-14 16:45:02,849 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0762) Prec@1 88.000 (87.417) Prec@5 99.000 (99.083) +2022-11-14 16:45:02,870 Test: [24/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0879 (0.0766) Prec@1 85.000 (87.320) Prec@5 100.000 (99.120) +2022-11-14 16:45:02,891 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0768) Prec@1 87.000 (87.308) Prec@5 98.000 (99.077) +2022-11-14 16:45:02,911 Test: [26/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0493 (0.0758) Prec@1 92.000 (87.481) Prec@5 100.000 (99.111) +2022-11-14 16:45:02,931 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0754) Prec@1 90.000 (87.571) Prec@5 100.000 (99.143) +2022-11-14 16:45:02,951 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0753) Prec@1 87.000 (87.552) Prec@5 99.000 (99.138) +2022-11-14 16:45:02,969 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0798 (0.0754) Prec@1 88.000 (87.567) Prec@5 99.000 (99.133) +2022-11-14 16:45:02,988 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0901 (0.0759) Prec@1 87.000 (87.548) Prec@5 100.000 (99.161) +2022-11-14 16:45:03,009 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0768 (0.0759) Prec@1 88.000 (87.562) Prec@5 99.000 (99.156) +2022-11-14 16:45:03,029 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0761) Prec@1 88.000 (87.576) Prec@5 100.000 (99.182) +2022-11-14 16:45:03,047 Test: [33/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0764) Prec@1 85.000 (87.500) Prec@5 100.000 (99.206) +2022-11-14 16:45:03,065 Test: [34/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0766) Prec@1 87.000 (87.486) Prec@5 97.000 (99.143) +2022-11-14 16:45:03,086 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0765) Prec@1 90.000 (87.556) Prec@5 99.000 (99.139) +2022-11-14 16:45:03,106 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0763) Prec@1 89.000 (87.595) Prec@5 99.000 (99.135) +2022-11-14 16:45:03,122 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1005 (0.0769) Prec@1 82.000 (87.447) Prec@5 98.000 (99.105) +2022-11-14 16:45:03,141 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0763) Prec@1 94.000 (87.615) Prec@5 99.000 (99.103) +2022-11-14 16:45:03,163 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0760) Prec@1 90.000 (87.675) Prec@5 100.000 (99.125) +2022-11-14 16:45:03,184 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0765) Prec@1 84.000 (87.585) Prec@5 98.000 (99.098) +2022-11-14 16:45:03,202 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0763) Prec@1 87.000 (87.571) Prec@5 100.000 (99.119) +2022-11-14 16:45:03,224 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0498 (0.0757) Prec@1 93.000 (87.698) Prec@5 100.000 (99.140) +2022-11-14 16:45:03,244 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0756) Prec@1 88.000 (87.705) Prec@5 99.000 (99.136) +2022-11-14 16:45:03,262 Test: [44/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0447 (0.0749) Prec@1 94.000 (87.844) Prec@5 99.000 (99.133) +2022-11-14 16:45:03,280 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0750) Prec@1 89.000 (87.870) Prec@5 97.000 (99.087) +2022-11-14 16:45:03,302 Test: [46/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0749) Prec@1 89.000 (87.894) Prec@5 100.000 (99.106) +2022-11-14 16:45:03,320 Test: [47/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.0755) Prec@1 84.000 (87.812) Prec@5 99.000 (99.104) +2022-11-14 16:45:03,339 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0751) Prec@1 92.000 (87.898) Prec@5 100.000 (99.122) +2022-11-14 16:45:03,359 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1189 (0.0760) Prec@1 83.000 (87.800) Prec@5 98.000 (99.100) +2022-11-14 16:45:03,378 Test: [50/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0758) Prec@1 88.000 (87.804) Prec@5 100.000 (99.118) +2022-11-14 16:45:03,399 Test: [51/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0757) Prec@1 89.000 (87.827) Prec@5 100.000 (99.135) +2022-11-14 16:45:03,422 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0618 (0.0754) Prec@1 91.000 (87.887) Prec@5 100.000 (99.151) +2022-11-14 16:45:03,441 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0752) Prec@1 89.000 (87.907) Prec@5 100.000 (99.167) +2022-11-14 16:45:03,465 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0985 (0.0757) Prec@1 86.000 (87.873) Prec@5 99.000 (99.164) +2022-11-14 16:45:03,483 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0683 (0.0755) Prec@1 92.000 (87.946) Prec@5 99.000 (99.161) +2022-11-14 16:45:03,502 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0754) Prec@1 89.000 (87.965) Prec@5 100.000 (99.175) +2022-11-14 16:45:03,522 Test: [57/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0722 (0.0753) Prec@1 87.000 (87.948) Prec@5 100.000 (99.190) +2022-11-14 16:45:03,544 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0931 (0.0756) Prec@1 84.000 (87.881) Prec@5 100.000 (99.203) +2022-11-14 16:45:03,566 Test: [59/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0755) Prec@1 89.000 (87.900) Prec@5 99.000 (99.200) +2022-11-14 16:45:03,586 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0754 (0.0755) Prec@1 89.000 (87.918) Prec@5 99.000 (99.197) +2022-11-14 16:45:03,607 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0733 (0.0754) Prec@1 88.000 (87.919) Prec@5 100.000 (99.210) +2022-11-14 16:45:03,624 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0754) Prec@1 89.000 (87.937) Prec@5 98.000 (99.190) +2022-11-14 16:45:03,642 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0384 (0.0748) Prec@1 95.000 (88.047) Prec@5 99.000 (99.188) +2022-11-14 16:45:03,663 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0750) Prec@1 84.000 (87.985) Prec@5 100.000 (99.200) +2022-11-14 16:45:03,684 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0751) Prec@1 84.000 (87.924) Prec@5 99.000 (99.197) +2022-11-14 16:45:03,705 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0343 (0.0745) Prec@1 94.000 (88.015) Prec@5 99.000 (99.194) +2022-11-14 16:45:03,725 Test: [67/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0620 (0.0743) Prec@1 92.000 (88.074) Prec@5 98.000 (99.176) +2022-11-14 16:45:03,751 Test: [68/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0747) Prec@1 83.000 (88.000) Prec@5 99.000 (99.174) +2022-11-14 16:45:03,772 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0748) Prec@1 87.000 (87.986) Prec@5 97.000 (99.143) +2022-11-14 16:45:03,793 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0750) Prec@1 86.000 (87.958) Prec@5 99.000 (99.141) +2022-11-14 16:45:03,812 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0748) Prec@1 91.000 (88.000) Prec@5 100.000 (99.153) +2022-11-14 16:45:03,833 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0388 (0.0743) Prec@1 94.000 (88.082) Prec@5 100.000 (99.164) +2022-11-14 16:45:03,852 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0384 (0.0738) Prec@1 94.000 (88.162) Prec@5 100.000 (99.176) +2022-11-14 16:45:03,873 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0971 (0.0741) Prec@1 82.000 (88.080) Prec@5 100.000 (99.187) +2022-11-14 16:45:03,893 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0740) Prec@1 89.000 (88.092) Prec@5 98.000 (99.171) +2022-11-14 16:45:03,912 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0740) Prec@1 89.000 (88.104) Prec@5 99.000 (99.169) +2022-11-14 16:45:03,933 Test: [77/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0897 (0.0742) Prec@1 85.000 (88.064) Prec@5 100.000 (99.179) +2022-11-14 16:45:03,956 Test: [78/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0957 (0.0745) Prec@1 86.000 (88.038) Prec@5 100.000 (99.190) +2022-11-14 16:45:03,975 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0745) Prec@1 86.000 (88.013) Prec@5 100.000 (99.200) +2022-11-14 16:45:03,998 Test: [80/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0987 (0.0748) Prec@1 86.000 (87.988) Prec@5 97.000 (99.173) +2022-11-14 16:45:04,019 Test: [81/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0861 (0.0749) Prec@1 89.000 (88.000) Prec@5 100.000 (99.183) +2022-11-14 16:45:04,039 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0749) Prec@1 89.000 (88.012) Prec@5 100.000 (99.193) +2022-11-14 16:45:04,058 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0748) Prec@1 90.000 (88.036) Prec@5 98.000 (99.179) +2022-11-14 16:45:04,079 Test: [84/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0750) Prec@1 84.000 (87.988) Prec@5 100.000 (99.188) +2022-11-14 16:45:04,099 Test: [85/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1120 (0.0755) Prec@1 83.000 (87.930) Prec@5 99.000 (99.186) +2022-11-14 16:45:04,118 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0754) Prec@1 89.000 (87.943) Prec@5 99.000 (99.184) +2022-11-14 16:45:04,140 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0754) Prec@1 89.000 (87.955) Prec@5 99.000 (99.182) +2022-11-14 16:45:04,160 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0754) Prec@1 86.000 (87.933) Prec@5 99.000 (99.180) +2022-11-14 16:45:04,178 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0669 (0.0753) Prec@1 89.000 (87.944) Prec@5 99.000 (99.178) +2022-11-14 16:45:04,197 Test: [90/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0495 (0.0751) Prec@1 90.000 (87.967) Prec@5 100.000 (99.187) +2022-11-14 16:45:04,221 Test: [91/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0527 (0.0748) Prec@1 90.000 (87.989) Prec@5 99.000 (99.185) +2022-11-14 16:45:04,243 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0750) Prec@1 88.000 (87.989) Prec@5 100.000 (99.194) +2022-11-14 16:45:04,261 Test: [93/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0750) Prec@1 88.000 (87.989) Prec@5 99.000 (99.191) +2022-11-14 16:45:04,278 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0748) Prec@1 92.000 (88.032) Prec@5 100.000 (99.200) +2022-11-14 16:45:04,299 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0545 (0.0746) Prec@1 90.000 (88.052) Prec@5 100.000 (99.208) +2022-11-14 16:45:04,319 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0743) Prec@1 91.000 (88.082) Prec@5 98.000 (99.196) +2022-11-14 16:45:04,337 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0738 (0.0743) Prec@1 89.000 (88.092) Prec@5 98.000 (99.184) +2022-11-14 16:45:04,356 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0979 (0.0746) Prec@1 84.000 (88.051) Prec@5 100.000 (99.192) +2022-11-14 16:45:04,377 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0844 (0.0747) Prec@1 86.000 (88.030) Prec@5 99.000 (99.190) +2022-11-14 16:45:04,439 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:45:04,788 Epoch: [378][0/500] Time 0.025 (0.025) Data 0.260 (0.260) Loss 0.0353 (0.0353) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:45:05,293 Epoch: [378][10/500] Time 0.058 (0.043) Data 0.002 (0.025) Loss 0.0317 (0.0335) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:45:05,889 Epoch: [378][20/500] Time 0.052 (0.048) Data 0.002 (0.014) Loss 0.0356 (0.0342) Prec@1 93.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 16:45:06,474 Epoch: [378][30/500] Time 0.057 (0.049) Data 0.002 (0.010) Loss 0.0301 (0.0332) Prec@1 94.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:45:07,053 Epoch: [378][40/500] Time 0.055 (0.050) Data 0.002 (0.008) Loss 0.0308 (0.0327) Prec@1 93.000 (94.000) Prec@5 100.000 (99.800) +2022-11-14 16:45:07,648 Epoch: [378][50/500] Time 0.062 (0.051) Data 0.002 (0.007) Loss 0.0282 (0.0319) Prec@1 96.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 16:45:08,233 Epoch: [378][60/500] Time 0.053 (0.051) Data 0.002 (0.006) Loss 0.0481 (0.0342) Prec@1 93.000 (94.143) Prec@5 100.000 (99.857) +2022-11-14 16:45:08,810 Epoch: [378][70/500] Time 0.064 (0.051) Data 0.002 (0.006) Loss 0.0246 (0.0330) Prec@1 96.000 (94.375) Prec@5 100.000 (99.875) +2022-11-14 16:45:09,389 Epoch: [378][80/500] Time 0.058 (0.051) Data 0.002 (0.005) Loss 0.0225 (0.0319) Prec@1 96.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 16:45:09,988 Epoch: [378][90/500] Time 0.058 (0.051) Data 0.002 (0.005) Loss 0.0493 (0.0336) Prec@1 93.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:45:10,572 Epoch: [378][100/500] Time 0.054 (0.051) Data 0.002 (0.005) Loss 0.0435 (0.0345) Prec@1 92.000 (94.182) Prec@5 100.000 (99.909) +2022-11-14 16:45:11,164 Epoch: [378][110/500] Time 0.059 (0.051) Data 0.002 (0.004) Loss 0.0270 (0.0339) Prec@1 96.000 (94.333) Prec@5 100.000 (99.917) +2022-11-14 16:45:11,733 Epoch: [378][120/500] Time 0.049 (0.051) Data 0.002 (0.004) Loss 0.0308 (0.0336) Prec@1 95.000 (94.385) Prec@5 100.000 (99.923) +2022-11-14 16:45:12,321 Epoch: [378][130/500] Time 0.052 (0.051) Data 0.002 (0.004) Loss 0.0304 (0.0334) Prec@1 97.000 (94.571) Prec@5 100.000 (99.929) +2022-11-14 16:45:12,889 Epoch: [378][140/500] Time 0.054 (0.051) Data 0.002 (0.004) Loss 0.0390 (0.0338) Prec@1 94.000 (94.533) Prec@5 100.000 (99.933) +2022-11-14 16:45:13,483 Epoch: [378][150/500] Time 0.057 (0.052) Data 0.002 (0.004) Loss 0.0273 (0.0334) Prec@1 97.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:45:14,068 Epoch: [378][160/500] Time 0.055 (0.052) Data 0.002 (0.004) Loss 0.0165 (0.0324) Prec@1 97.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 16:45:14,689 Epoch: [378][170/500] Time 0.067 (0.052) Data 0.002 (0.004) Loss 0.0183 (0.0316) Prec@1 98.000 (95.000) Prec@5 100.000 (99.944) +2022-11-14 16:45:15,298 Epoch: [378][180/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0203 (0.0310) Prec@1 97.000 (95.105) Prec@5 100.000 (99.947) +2022-11-14 16:45:15,862 Epoch: [378][190/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0106 (0.0300) Prec@1 99.000 (95.300) Prec@5 100.000 (99.950) +2022-11-14 16:45:16,453 Epoch: [378][200/500] Time 0.054 (0.052) Data 0.002 (0.003) Loss 0.0461 (0.0308) Prec@1 93.000 (95.190) Prec@5 99.000 (99.905) +2022-11-14 16:45:17,024 Epoch: [378][210/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0188 (0.0302) Prec@1 97.000 (95.273) Prec@5 100.000 (99.909) +2022-11-14 16:45:17,617 Epoch: [378][220/500] Time 0.057 (0.052) Data 0.003 (0.003) Loss 0.0451 (0.0309) Prec@1 93.000 (95.174) Prec@5 99.000 (99.870) +2022-11-14 16:45:18,202 Epoch: [378][230/500] Time 0.057 (0.052) Data 0.002 (0.003) Loss 0.0124 (0.0301) Prec@1 99.000 (95.333) Prec@5 100.000 (99.875) +2022-11-14 16:45:18,793 Epoch: [378][240/500] Time 0.056 (0.052) Data 0.002 (0.003) Loss 0.0223 (0.0298) Prec@1 97.000 (95.400) Prec@5 100.000 (99.880) +2022-11-14 16:45:19,393 Epoch: [378][250/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0233 (0.0295) Prec@1 97.000 (95.462) Prec@5 100.000 (99.885) +2022-11-14 16:45:19,987 Epoch: [378][260/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0247 (0.0293) Prec@1 93.000 (95.370) Prec@5 100.000 (99.889) +2022-11-14 16:45:20,594 Epoch: [378][270/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0284 (0.0293) Prec@1 97.000 (95.429) Prec@5 100.000 (99.893) +2022-11-14 16:45:21,184 Epoch: [378][280/500] Time 0.051 (0.052) Data 0.003 (0.003) Loss 0.0299 (0.0293) Prec@1 95.000 (95.414) Prec@5 100.000 (99.897) +2022-11-14 16:45:21,821 Epoch: [378][290/500] Time 0.068 (0.052) Data 0.002 (0.003) Loss 0.0264 (0.0292) Prec@1 96.000 (95.433) Prec@5 99.000 (99.867) +2022-11-14 16:45:22,412 Epoch: [378][300/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0439 (0.0297) Prec@1 93.000 (95.355) Prec@5 100.000 (99.871) +2022-11-14 16:45:23,082 Epoch: [378][310/500] Time 0.070 (0.053) Data 0.002 (0.003) Loss 0.0260 (0.0296) Prec@1 97.000 (95.406) Prec@5 100.000 (99.875) +2022-11-14 16:45:23,677 Epoch: [378][320/500] Time 0.046 (0.053) Data 0.002 (0.003) Loss 0.0288 (0.0296) Prec@1 96.000 (95.424) Prec@5 100.000 (99.879) +2022-11-14 16:45:24,322 Epoch: [378][330/500] Time 0.091 (0.053) Data 0.003 (0.003) Loss 0.0224 (0.0294) Prec@1 96.000 (95.441) Prec@5 100.000 (99.882) +2022-11-14 16:45:24,928 Epoch: [378][340/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0177 (0.0290) Prec@1 98.000 (95.514) Prec@5 100.000 (99.886) +2022-11-14 16:45:25,531 Epoch: [378][350/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0281 (0.0290) Prec@1 94.000 (95.472) Prec@5 100.000 (99.889) +2022-11-14 16:45:26,125 Epoch: [378][360/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0442 (0.0294) Prec@1 92.000 (95.378) Prec@5 100.000 (99.892) +2022-11-14 16:45:26,727 Epoch: [378][370/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0356 (0.0296) Prec@1 93.000 (95.316) Prec@5 99.000 (99.868) +2022-11-14 16:45:27,321 Epoch: [378][380/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0496 (0.0301) Prec@1 91.000 (95.205) Prec@5 100.000 (99.872) +2022-11-14 16:45:27,911 Epoch: [378][390/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0312 (0.0301) Prec@1 95.000 (95.200) Prec@5 100.000 (99.875) +2022-11-14 16:45:28,486 Epoch: [378][400/500] Time 0.040 (0.053) Data 0.002 (0.003) Loss 0.0502 (0.0306) Prec@1 91.000 (95.098) Prec@5 100.000 (99.878) +2022-11-14 16:45:29,088 Epoch: [378][410/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0242 (0.0305) Prec@1 96.000 (95.119) Prec@5 100.000 (99.881) +2022-11-14 16:45:29,673 Epoch: [378][420/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0370 (0.0306) Prec@1 94.000 (95.093) Prec@5 100.000 (99.884) +2022-11-14 16:45:30,274 Epoch: [378][430/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0389 (0.0308) Prec@1 95.000 (95.091) Prec@5 100.000 (99.886) +2022-11-14 16:45:30,873 Epoch: [378][440/500] Time 0.057 (0.053) Data 0.002 (0.003) Loss 0.0295 (0.0308) Prec@1 95.000 (95.089) Prec@5 100.000 (99.889) +2022-11-14 16:45:31,449 Epoch: [378][450/500] Time 0.052 (0.053) Data 0.002 (0.003) Loss 0.0326 (0.0308) Prec@1 95.000 (95.087) Prec@5 98.000 (99.848) +2022-11-14 16:45:32,052 Epoch: [378][460/500] Time 0.069 (0.053) Data 0.002 (0.003) Loss 0.0102 (0.0304) Prec@1 99.000 (95.170) Prec@5 100.000 (99.851) +2022-11-14 16:45:32,642 Epoch: [378][470/500] Time 0.038 (0.053) Data 0.002 (0.003) Loss 0.0096 (0.0299) Prec@1 98.000 (95.229) Prec@5 100.000 (99.854) +2022-11-14 16:45:33,220 Epoch: [378][480/500] Time 0.051 (0.053) Data 0.002 (0.003) Loss 0.0422 (0.0302) Prec@1 92.000 (95.163) Prec@5 99.000 (99.837) +2022-11-14 16:45:33,809 Epoch: [378][490/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0276 (0.0301) Prec@1 96.000 (95.180) Prec@5 100.000 (99.840) +2022-11-14 16:45:34,338 Epoch: [378][499/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0257 (0.0300) Prec@1 97.000 (95.216) Prec@5 100.000 (99.843) +2022-11-14 16:45:34,690 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0615 (0.0615) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:45:34,700 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0638 (0.0627) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:45:34,710 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0929 (0.0727) Prec@1 82.000 (87.000) Prec@5 99.000 (99.667) +2022-11-14 16:45:34,723 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0731) Prec@1 88.000 (87.250) Prec@5 100.000 (99.750) +2022-11-14 16:45:34,735 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0732) Prec@1 90.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 16:45:34,748 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0699) Prec@1 91.000 (88.333) Prec@5 100.000 (99.833) +2022-11-14 16:45:34,761 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0687) Prec@1 90.000 (88.571) Prec@5 99.000 (99.714) +2022-11-14 16:45:34,777 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0824 (0.0704) Prec@1 85.000 (88.125) Prec@5 99.000 (99.625) +2022-11-14 16:45:34,790 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0839 (0.0719) Prec@1 88.000 (88.111) Prec@5 99.000 (99.556) +2022-11-14 16:45:34,808 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0728) Prec@1 88.000 (88.100) Prec@5 99.000 (99.500) +2022-11-14 16:45:34,827 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0541 (0.0711) Prec@1 93.000 (88.545) Prec@5 100.000 (99.545) +2022-11-14 16:45:34,842 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0724) Prec@1 85.000 (88.250) Prec@5 100.000 (99.583) +2022-11-14 16:45:34,862 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0720) Prec@1 91.000 (88.462) Prec@5 100.000 (99.615) +2022-11-14 16:45:34,883 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0718) Prec@1 89.000 (88.500) Prec@5 99.000 (99.571) +2022-11-14 16:45:34,901 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0718) Prec@1 87.000 (88.400) Prec@5 99.000 (99.533) +2022-11-14 16:45:34,919 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0894 (0.0729) Prec@1 84.000 (88.125) Prec@5 98.000 (99.438) +2022-11-14 16:45:34,940 Test: [16/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0588 (0.0720) Prec@1 91.000 (88.294) Prec@5 99.000 (99.412) +2022-11-14 16:45:34,960 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0738) Prec@1 84.000 (88.056) Prec@5 98.000 (99.333) +2022-11-14 16:45:34,980 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0855 (0.0744) Prec@1 87.000 (88.000) Prec@5 98.000 (99.263) +2022-11-14 16:45:35,000 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0986 (0.0756) Prec@1 83.000 (87.750) Prec@5 97.000 (99.150) +2022-11-14 16:45:35,021 Test: [20/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0756) Prec@1 87.000 (87.714) Prec@5 100.000 (99.190) +2022-11-14 16:45:35,041 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0837 (0.0760) Prec@1 86.000 (87.636) Prec@5 99.000 (99.182) +2022-11-14 16:45:35,060 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1051 (0.0773) Prec@1 81.000 (87.348) Prec@5 99.000 (99.174) +2022-11-14 16:45:35,080 Test: [23/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0772) Prec@1 90.000 (87.458) Prec@5 100.000 (99.208) +2022-11-14 16:45:35,099 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0775) Prec@1 89.000 (87.520) Prec@5 99.000 (99.200) +2022-11-14 16:45:35,120 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1104 (0.0788) Prec@1 83.000 (87.346) Prec@5 97.000 (99.115) +2022-11-14 16:45:35,139 Test: [26/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0596 (0.0780) Prec@1 91.000 (87.481) Prec@5 100.000 (99.148) +2022-11-14 16:45:35,155 Test: [27/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0488 (0.0770) Prec@1 92.000 (87.643) Prec@5 100.000 (99.179) +2022-11-14 16:45:35,174 Test: [28/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0768) Prec@1 87.000 (87.621) Prec@5 98.000 (99.138) +2022-11-14 16:45:35,191 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0907 (0.0773) Prec@1 85.000 (87.533) Prec@5 100.000 (99.167) +2022-11-14 16:45:35,211 Test: [30/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0770) Prec@1 89.000 (87.581) Prec@5 100.000 (99.194) +2022-11-14 16:45:35,232 Test: [31/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0769) Prec@1 90.000 (87.656) Prec@5 98.000 (99.156) +2022-11-14 16:45:35,250 Test: [32/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0877 (0.0772) Prec@1 86.000 (87.606) Prec@5 99.000 (99.152) +2022-11-14 16:45:35,270 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0845 (0.0774) Prec@1 86.000 (87.559) Prec@5 100.000 (99.176) +2022-11-14 16:45:35,291 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0777) Prec@1 86.000 (87.514) Prec@5 97.000 (99.114) +2022-11-14 16:45:35,316 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0776) Prec@1 88.000 (87.528) Prec@5 100.000 (99.139) +2022-11-14 16:45:35,337 Test: [36/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0777) Prec@1 89.000 (87.568) Prec@5 99.000 (99.135) +2022-11-14 16:45:35,357 Test: [37/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1126 (0.0786) Prec@1 81.000 (87.395) Prec@5 100.000 (99.158) +2022-11-14 16:45:35,377 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0779) Prec@1 93.000 (87.538) Prec@5 99.000 (99.154) +2022-11-14 16:45:35,399 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0778) Prec@1 89.000 (87.575) Prec@5 99.000 (99.150) +2022-11-14 16:45:35,421 Test: [40/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0780) Prec@1 86.000 (87.537) Prec@5 100.000 (99.171) +2022-11-14 16:45:35,436 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0777) Prec@1 88.000 (87.548) Prec@5 100.000 (99.190) +2022-11-14 16:45:35,454 Test: [42/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0469 (0.0770) Prec@1 94.000 (87.698) Prec@5 100.000 (99.209) +2022-11-14 16:45:35,474 Test: [43/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0732 (0.0769) Prec@1 89.000 (87.727) Prec@5 99.000 (99.205) +2022-11-14 16:45:35,494 Test: [44/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0838 (0.0771) Prec@1 87.000 (87.711) Prec@5 99.000 (99.200) +2022-11-14 16:45:35,512 Test: [45/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1089 (0.0778) Prec@1 82.000 (87.587) Prec@5 98.000 (99.174) +2022-11-14 16:45:35,530 Test: [46/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0623 (0.0774) Prec@1 89.000 (87.617) Prec@5 99.000 (99.170) +2022-11-14 16:45:35,549 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0968 (0.0778) Prec@1 85.000 (87.562) Prec@5 99.000 (99.167) +2022-11-14 16:45:35,568 Test: [48/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0777) Prec@1 87.000 (87.551) Prec@5 100.000 (99.184) +2022-11-14 16:45:35,588 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1135 (0.0784) Prec@1 83.000 (87.460) Prec@5 100.000 (99.200) +2022-11-14 16:45:35,606 Test: [50/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0466 (0.0778) Prec@1 92.000 (87.549) Prec@5 100.000 (99.216) +2022-11-14 16:45:35,626 Test: [51/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0777) Prec@1 87.000 (87.538) Prec@5 100.000 (99.231) +2022-11-14 16:45:35,646 Test: [52/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0727 (0.0776) Prec@1 88.000 (87.547) Prec@5 100.000 (99.245) +2022-11-14 16:45:35,668 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0777) Prec@1 89.000 (87.574) Prec@5 99.000 (99.241) +2022-11-14 16:45:35,690 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1003 (0.0781) Prec@1 81.000 (87.455) Prec@5 100.000 (99.255) +2022-11-14 16:45:35,707 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0776 (0.0781) Prec@1 88.000 (87.464) Prec@5 99.000 (99.250) +2022-11-14 16:45:35,728 Test: [56/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0716 (0.0780) Prec@1 89.000 (87.491) Prec@5 98.000 (99.228) +2022-11-14 16:45:35,747 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0778) Prec@1 89.000 (87.517) Prec@5 99.000 (99.224) +2022-11-14 16:45:35,766 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1100 (0.0784) Prec@1 82.000 (87.424) Prec@5 99.000 (99.220) +2022-11-14 16:45:35,784 Test: [59/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0782) Prec@1 88.000 (87.433) Prec@5 100.000 (99.233) +2022-11-14 16:45:35,804 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0783) Prec@1 87.000 (87.426) Prec@5 98.000 (99.213) +2022-11-14 16:45:35,824 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0784) Prec@1 87.000 (87.419) Prec@5 99.000 (99.210) +2022-11-14 16:45:35,844 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0783) Prec@1 84.000 (87.365) Prec@5 99.000 (99.206) +2022-11-14 16:45:35,863 Test: [63/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0346 (0.0777) Prec@1 94.000 (87.469) Prec@5 100.000 (99.219) +2022-11-14 16:45:35,879 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1086 (0.0781) Prec@1 81.000 (87.369) Prec@5 99.000 (99.215) +2022-11-14 16:45:35,895 Test: [65/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0593 (0.0779) Prec@1 90.000 (87.409) Prec@5 99.000 (99.212) +2022-11-14 16:45:35,912 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0429 (0.0773) Prec@1 94.000 (87.507) Prec@5 100.000 (99.224) +2022-11-14 16:45:35,933 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0773) Prec@1 88.000 (87.515) Prec@5 100.000 (99.235) +2022-11-14 16:45:35,953 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0795 (0.0773) Prec@1 86.000 (87.493) Prec@5 99.000 (99.232) +2022-11-14 16:45:35,972 Test: [69/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0771) Prec@1 90.000 (87.529) Prec@5 99.000 (99.229) +2022-11-14 16:45:35,992 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0873 (0.0772) Prec@1 86.000 (87.507) Prec@5 100.000 (99.239) +2022-11-14 16:45:36,011 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0769) Prec@1 92.000 (87.569) Prec@5 100.000 (99.250) +2022-11-14 16:45:36,032 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0567 (0.0766) Prec@1 92.000 (87.630) Prec@5 98.000 (99.233) +2022-11-14 16:45:36,053 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0474 (0.0762) Prec@1 92.000 (87.689) Prec@5 100.000 (99.243) +2022-11-14 16:45:36,071 Test: [74/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1033 (0.0766) Prec@1 84.000 (87.640) Prec@5 99.000 (99.240) +2022-11-14 16:45:36,092 Test: [75/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0765) Prec@1 89.000 (87.658) Prec@5 98.000 (99.224) +2022-11-14 16:45:36,111 Test: [76/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0710 (0.0764) Prec@1 88.000 (87.662) Prec@5 100.000 (99.234) +2022-11-14 16:45:36,130 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0765) Prec@1 86.000 (87.641) Prec@5 99.000 (99.231) +2022-11-14 16:45:36,151 Test: [78/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1038 (0.0769) Prec@1 82.000 (87.570) Prec@5 100.000 (99.241) +2022-11-14 16:45:36,169 Test: [79/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0516 (0.0766) Prec@1 92.000 (87.625) Prec@5 100.000 (99.250) +2022-11-14 16:45:36,189 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0892 (0.0767) Prec@1 85.000 (87.593) Prec@5 99.000 (99.247) +2022-11-14 16:45:36,212 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0766) Prec@1 87.000 (87.585) Prec@5 100.000 (99.256) +2022-11-14 16:45:36,233 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1035 (0.0770) Prec@1 82.000 (87.518) Prec@5 99.000 (99.253) +2022-11-14 16:45:36,250 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0768) Prec@1 88.000 (87.524) Prec@5 99.000 (99.250) +2022-11-14 16:45:36,271 Test: [84/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0770) Prec@1 88.000 (87.529) Prec@5 99.000 (99.247) +2022-11-14 16:45:36,295 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1109 (0.0774) Prec@1 83.000 (87.477) Prec@5 100.000 (99.256) +2022-11-14 16:45:36,315 Test: [86/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0820 (0.0774) Prec@1 86.000 (87.460) Prec@5 99.000 (99.253) +2022-11-14 16:45:36,336 Test: [87/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0772) Prec@1 91.000 (87.500) Prec@5 100.000 (99.261) +2022-11-14 16:45:36,356 Test: [88/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0771) Prec@1 88.000 (87.506) Prec@5 100.000 (99.270) +2022-11-14 16:45:36,376 Test: [89/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0829 (0.0772) Prec@1 89.000 (87.522) Prec@5 98.000 (99.256) +2022-11-14 16:45:36,399 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0702 (0.0771) Prec@1 90.000 (87.549) Prec@5 100.000 (99.264) +2022-11-14 16:45:36,422 Test: [91/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0503 (0.0768) Prec@1 94.000 (87.620) Prec@5 98.000 (99.250) +2022-11-14 16:45:36,439 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0770) Prec@1 86.000 (87.602) Prec@5 99.000 (99.247) +2022-11-14 16:45:36,459 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0581 (0.0768) Prec@1 91.000 (87.638) Prec@5 100.000 (99.255) +2022-11-14 16:45:36,479 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0767) Prec@1 90.000 (87.663) Prec@5 99.000 (99.253) +2022-11-14 16:45:36,501 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0766) Prec@1 91.000 (87.698) Prec@5 99.000 (99.250) +2022-11-14 16:45:36,518 Test: [96/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0558 (0.0764) Prec@1 90.000 (87.722) Prec@5 99.000 (99.247) +2022-11-14 16:45:36,539 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1077 (0.0767) Prec@1 82.000 (87.663) Prec@5 99.000 (99.245) +2022-11-14 16:45:36,558 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0917 (0.0768) Prec@1 88.000 (87.667) Prec@5 99.000 (99.242) +2022-11-14 16:45:36,578 Test: [99/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0657 (0.0767) Prec@1 87.000 (87.660) Prec@5 99.000 (99.240) +2022-11-14 16:45:36,641 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:45:37,015 Epoch: [379][0/500] Time 0.029 (0.029) Data 0.275 (0.275) Loss 0.0323 (0.0323) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:45:37,509 Epoch: [379][10/500] Time 0.066 (0.042) Data 0.002 (0.027) Loss 0.0359 (0.0341) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:45:38,104 Epoch: [379][20/500] Time 0.062 (0.047) Data 0.002 (0.015) Loss 0.0343 (0.0342) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:45:38,696 Epoch: [379][30/500] Time 0.045 (0.049) Data 0.002 (0.011) Loss 0.0281 (0.0327) Prec@1 95.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:45:39,288 Epoch: [379][40/500] Time 0.062 (0.050) Data 0.002 (0.009) Loss 0.0462 (0.0354) Prec@1 93.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:45:39,876 Epoch: [379][50/500] Time 0.063 (0.051) Data 0.002 (0.007) Loss 0.0248 (0.0336) Prec@1 97.000 (94.833) Prec@5 99.000 (99.833) +2022-11-14 16:45:40,472 Epoch: [379][60/500] Time 0.061 (0.051) Data 0.002 (0.006) Loss 0.0247 (0.0323) Prec@1 97.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:45:41,053 Epoch: [379][70/500] Time 0.060 (0.051) Data 0.002 (0.006) Loss 0.0209 (0.0309) Prec@1 97.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:45:41,646 Epoch: [379][80/500] Time 0.062 (0.051) Data 0.002 (0.005) Loss 0.0499 (0.0330) Prec@1 93.000 (95.111) Prec@5 99.000 (99.778) +2022-11-14 16:45:42,227 Epoch: [379][90/500] Time 0.061 (0.051) Data 0.002 (0.005) Loss 0.0294 (0.0327) Prec@1 95.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 16:45:42,806 Epoch: [379][100/500] Time 0.062 (0.051) Data 0.002 (0.005) Loss 0.0202 (0.0315) Prec@1 97.000 (95.273) Prec@5 99.000 (99.727) +2022-11-14 16:45:43,405 Epoch: [379][110/500] Time 0.059 (0.052) Data 0.002 (0.004) Loss 0.0169 (0.0303) Prec@1 98.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:45:43,993 Epoch: [379][120/500] Time 0.057 (0.052) Data 0.002 (0.004) Loss 0.0142 (0.0291) Prec@1 97.000 (95.615) Prec@5 100.000 (99.769) +2022-11-14 16:45:44,572 Epoch: [379][130/500] Time 0.060 (0.052) Data 0.002 (0.004) Loss 0.0447 (0.0302) Prec@1 91.000 (95.286) Prec@5 100.000 (99.786) +2022-11-14 16:45:45,153 Epoch: [379][140/500] Time 0.058 (0.052) Data 0.002 (0.004) Loss 0.0521 (0.0316) Prec@1 91.000 (95.000) Prec@5 98.000 (99.667) +2022-11-14 16:45:45,754 Epoch: [379][150/500] Time 0.057 (0.052) Data 0.002 (0.004) Loss 0.0223 (0.0311) Prec@1 95.000 (95.000) Prec@5 100.000 (99.688) +2022-11-14 16:45:46,341 Epoch: [379][160/500] Time 0.056 (0.052) Data 0.002 (0.004) Loss 0.0403 (0.0316) Prec@1 96.000 (95.059) Prec@5 100.000 (99.706) +2022-11-14 16:45:46,921 Epoch: [379][170/500] Time 0.054 (0.052) Data 0.002 (0.004) Loss 0.0337 (0.0317) Prec@1 93.000 (94.944) Prec@5 100.000 (99.722) +2022-11-14 16:45:47,491 Epoch: [379][180/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0196 (0.0311) Prec@1 98.000 (95.105) Prec@5 100.000 (99.737) +2022-11-14 16:45:48,086 Epoch: [379][190/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0188 (0.0305) Prec@1 95.000 (95.100) Prec@5 100.000 (99.750) +2022-11-14 16:45:48,650 Epoch: [379][200/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0224 (0.0301) Prec@1 96.000 (95.143) Prec@5 100.000 (99.762) +2022-11-14 16:45:49,243 Epoch: [379][210/500] Time 0.051 (0.052) Data 0.002 (0.003) Loss 0.0378 (0.0304) Prec@1 93.000 (95.045) Prec@5 100.000 (99.773) +2022-11-14 16:45:49,799 Epoch: [379][220/500] Time 0.048 (0.052) Data 0.002 (0.003) Loss 0.0310 (0.0305) Prec@1 95.000 (95.043) Prec@5 100.000 (99.783) +2022-11-14 16:45:50,374 Epoch: [379][230/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0167 (0.0299) Prec@1 97.000 (95.125) Prec@5 100.000 (99.792) +2022-11-14 16:45:50,967 Epoch: [379][240/500] Time 0.070 (0.052) Data 0.002 (0.003) Loss 0.0259 (0.0297) Prec@1 97.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:45:51,539 Epoch: [379][250/500] Time 0.046 (0.052) Data 0.002 (0.003) Loss 0.0443 (0.0303) Prec@1 92.000 (95.077) Prec@5 100.000 (99.808) +2022-11-14 16:45:52,148 Epoch: [379][260/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0171 (0.0298) Prec@1 97.000 (95.148) Prec@5 100.000 (99.815) +2022-11-14 16:45:52,765 Epoch: [379][270/500] Time 0.049 (0.052) Data 0.002 (0.003) Loss 0.0301 (0.0298) Prec@1 95.000 (95.143) Prec@5 99.000 (99.786) +2022-11-14 16:45:53,420 Epoch: [379][280/500] Time 0.055 (0.052) Data 0.002 (0.003) Loss 0.0249 (0.0296) Prec@1 93.000 (95.069) Prec@5 100.000 (99.793) +2022-11-14 16:45:54,041 Epoch: [379][290/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0202 (0.0293) Prec@1 97.000 (95.133) Prec@5 100.000 (99.800) +2022-11-14 16:45:54,630 Epoch: [379][300/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0367 (0.0296) Prec@1 94.000 (95.097) Prec@5 100.000 (99.806) +2022-11-14 16:45:55,200 Epoch: [379][310/500] Time 0.069 (0.052) Data 0.002 (0.003) Loss 0.0350 (0.0297) Prec@1 93.000 (95.031) Prec@5 100.000 (99.812) +2022-11-14 16:45:55,803 Epoch: [379][320/500] Time 0.050 (0.052) Data 0.002 (0.003) Loss 0.0281 (0.0297) Prec@1 97.000 (95.091) Prec@5 100.000 (99.818) +2022-11-14 16:45:56,390 Epoch: [379][330/500] Time 0.052 (0.052) Data 0.002 (0.003) Loss 0.0110 (0.0291) Prec@1 98.000 (95.176) Prec@5 99.000 (99.794) +2022-11-14 16:45:56,979 Epoch: [379][340/500] Time 0.060 (0.052) Data 0.002 (0.003) Loss 0.0418 (0.0295) Prec@1 94.000 (95.143) Prec@5 100.000 (99.800) +2022-11-14 16:45:57,575 Epoch: [379][350/500] Time 0.073 (0.052) Data 0.002 (0.003) Loss 0.0301 (0.0295) Prec@1 96.000 (95.167) Prec@5 100.000 (99.806) +2022-11-14 16:45:58,161 Epoch: [379][360/500] Time 0.063 (0.052) Data 0.002 (0.003) Loss 0.0283 (0.0295) Prec@1 95.000 (95.162) Prec@5 99.000 (99.784) +2022-11-14 16:45:58,727 Epoch: [379][370/500] Time 0.062 (0.052) Data 0.002 (0.003) Loss 0.0537 (0.0301) Prec@1 91.000 (95.053) Prec@5 100.000 (99.789) +2022-11-14 16:45:59,382 Epoch: [379][380/500] Time 0.061 (0.052) Data 0.002 (0.003) Loss 0.0350 (0.0302) Prec@1 93.000 (95.000) Prec@5 100.000 (99.795) +2022-11-14 16:45:59,993 Epoch: [379][390/500] Time 0.059 (0.052) Data 0.002 (0.003) Loss 0.0386 (0.0305) Prec@1 94.000 (94.975) Prec@5 100.000 (99.800) +2022-11-14 16:46:00,639 Epoch: [379][400/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0394 (0.0307) Prec@1 93.000 (94.927) Prec@5 100.000 (99.805) +2022-11-14 16:46:01,240 Epoch: [379][410/500] Time 0.064 (0.053) Data 0.002 (0.003) Loss 0.0266 (0.0306) Prec@1 96.000 (94.952) Prec@5 100.000 (99.810) +2022-11-14 16:46:01,822 Epoch: [379][420/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0301 (0.0306) Prec@1 96.000 (94.977) Prec@5 100.000 (99.814) +2022-11-14 16:46:02,414 Epoch: [379][430/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0197 (0.0303) Prec@1 97.000 (95.023) Prec@5 100.000 (99.818) +2022-11-14 16:46:03,011 Epoch: [379][440/500] Time 0.057 (0.053) Data 0.003 (0.003) Loss 0.0391 (0.0305) Prec@1 95.000 (95.022) Prec@5 100.000 (99.822) +2022-11-14 16:46:03,617 Epoch: [379][450/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0055 (0.0300) Prec@1 100.000 (95.130) Prec@5 100.000 (99.826) +2022-11-14 16:46:04,212 Epoch: [379][460/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0368 (0.0301) Prec@1 93.000 (95.085) Prec@5 100.000 (99.830) +2022-11-14 16:46:04,803 Epoch: [379][470/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0337 (0.0302) Prec@1 94.000 (95.062) Prec@5 100.000 (99.833) +2022-11-14 16:46:05,388 Epoch: [379][480/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0085 (0.0297) Prec@1 99.000 (95.143) Prec@5 100.000 (99.837) +2022-11-14 16:46:05,960 Epoch: [379][490/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0546 (0.0302) Prec@1 91.000 (95.060) Prec@5 98.000 (99.800) +2022-11-14 16:46:06,490 Epoch: [379][499/500] Time 0.060 (0.053) Data 0.002 (0.003) Loss 0.0422 (0.0305) Prec@1 94.000 (95.039) Prec@5 99.000 (99.784) +2022-11-14 16:46:06,847 Test: [0/100] Model Time 0.017 (0.017) Loss Time 0.000 (0.000) Loss 0.0614 (0.0614) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:46:06,858 Test: [1/100] Model Time 0.008 (0.013) Loss Time 0.000 (0.000) Loss 0.0545 (0.0579) Prec@1 91.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 16:46:06,867 Test: [2/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0736 (0.0631) Prec@1 90.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:46:06,879 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.1110 (0.0751) Prec@1 83.000 (88.000) Prec@5 98.000 (99.250) +2022-11-14 16:46:06,892 Test: [4/100] Model Time 0.011 (0.010) Loss Time 0.000 (0.000) Loss 0.0606 (0.0722) Prec@1 90.000 (88.400) Prec@5 100.000 (99.400) +2022-11-14 16:46:06,904 Test: [5/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0471 (0.0680) Prec@1 93.000 (89.167) Prec@5 100.000 (99.500) +2022-11-14 16:46:06,917 Test: [6/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0608 (0.0670) Prec@1 92.000 (89.571) Prec@5 98.000 (99.286) +2022-11-14 16:46:06,932 Test: [7/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0853 (0.0693) Prec@1 85.000 (89.000) Prec@5 98.000 (99.125) +2022-11-14 16:46:06,947 Test: [8/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0686 (0.0692) Prec@1 91.000 (89.222) Prec@5 98.000 (99.000) +2022-11-14 16:46:06,962 Test: [9/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0696) Prec@1 89.000 (89.200) Prec@5 99.000 (99.000) +2022-11-14 16:46:06,982 Test: [10/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0783 (0.0704) Prec@1 88.000 (89.091) Prec@5 100.000 (99.091) +2022-11-14 16:46:06,999 Test: [11/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0780 (0.0710) Prec@1 86.000 (88.833) Prec@5 99.000 (99.083) +2022-11-14 16:46:07,015 Test: [12/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0552 (0.0698) Prec@1 90.000 (88.923) Prec@5 100.000 (99.154) +2022-11-14 16:46:07,035 Test: [13/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0670 (0.0696) Prec@1 89.000 (88.929) Prec@5 99.000 (99.143) +2022-11-14 16:46:07,056 Test: [14/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0789 (0.0702) Prec@1 88.000 (88.867) Prec@5 100.000 (99.200) +2022-11-14 16:46:07,073 Test: [15/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0706) Prec@1 87.000 (88.750) Prec@5 100.000 (99.250) +2022-11-14 16:46:07,092 Test: [16/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0511 (0.0695) Prec@1 93.000 (89.000) Prec@5 98.000 (99.176) +2022-11-14 16:46:07,113 Test: [17/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1157 (0.0720) Prec@1 82.000 (88.611) Prec@5 99.000 (99.167) +2022-11-14 16:46:07,130 Test: [18/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.1003 (0.0735) Prec@1 83.000 (88.316) Prec@5 97.000 (99.053) +2022-11-14 16:46:07,148 Test: [19/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0840 (0.0741) Prec@1 87.000 (88.250) Prec@5 98.000 (99.000) +2022-11-14 16:46:07,167 Test: [20/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0729 (0.0740) Prec@1 88.000 (88.238) Prec@5 100.000 (99.048) +2022-11-14 16:46:07,189 Test: [21/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0757 (0.0741) Prec@1 88.000 (88.227) Prec@5 100.000 (99.091) +2022-11-14 16:46:07,210 Test: [22/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.1075 (0.0755) Prec@1 85.000 (88.087) Prec@5 97.000 (99.000) +2022-11-14 16:46:07,229 Test: [23/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0901 (0.0761) Prec@1 84.000 (87.917) Prec@5 99.000 (99.000) +2022-11-14 16:46:07,249 Test: [24/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0965 (0.0769) Prec@1 86.000 (87.840) Prec@5 100.000 (99.040) +2022-11-14 16:46:07,266 Test: [25/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0835 (0.0772) Prec@1 89.000 (87.885) Prec@5 100.000 (99.077) +2022-11-14 16:46:07,285 Test: [26/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0498 (0.0762) Prec@1 92.000 (88.037) Prec@5 99.000 (99.074) +2022-11-14 16:46:07,307 Test: [27/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0604 (0.0756) Prec@1 89.000 (88.071) Prec@5 100.000 (99.107) +2022-11-14 16:46:07,326 Test: [28/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0774 (0.0757) Prec@1 87.000 (88.034) Prec@5 99.000 (99.103) +2022-11-14 16:46:07,344 Test: [29/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0816 (0.0759) Prec@1 87.000 (88.000) Prec@5 99.000 (99.100) +2022-11-14 16:46:07,364 Test: [30/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0758) Prec@1 87.000 (87.968) Prec@5 99.000 (99.097) +2022-11-14 16:46:07,386 Test: [31/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0726 (0.0757) Prec@1 87.000 (87.938) Prec@5 99.000 (99.094) +2022-11-14 16:46:07,406 Test: [32/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0757) Prec@1 86.000 (87.879) Prec@5 100.000 (99.121) +2022-11-14 16:46:07,423 Test: [33/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0791 (0.0758) Prec@1 87.000 (87.853) Prec@5 100.000 (99.147) +2022-11-14 16:46:07,444 Test: [34/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0744 (0.0758) Prec@1 90.000 (87.914) Prec@5 98.000 (99.114) +2022-11-14 16:46:07,461 Test: [35/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0745 (0.0758) Prec@1 89.000 (87.944) Prec@5 99.000 (99.111) +2022-11-14 16:46:07,476 Test: [36/100] Model Time 0.010 (0.009) Loss Time 0.000 (0.000) Loss 0.0722 (0.0757) Prec@1 88.000 (87.946) Prec@5 99.000 (99.108) +2022-11-14 16:46:07,496 Test: [37/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.1237 (0.0769) Prec@1 79.000 (87.711) Prec@5 100.000 (99.132) +2022-11-14 16:46:07,514 Test: [38/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0529 (0.0763) Prec@1 92.000 (87.821) Prec@5 100.000 (99.154) +2022-11-14 16:46:07,533 Test: [39/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0868 (0.0766) Prec@1 85.000 (87.750) Prec@5 98.000 (99.125) +2022-11-14 16:46:07,557 Test: [40/100] Model Time 0.012 (0.009) Loss Time 0.000 (0.000) Loss 0.0929 (0.0770) Prec@1 86.000 (87.707) Prec@5 98.000 (99.098) +2022-11-14 16:46:07,576 Test: [41/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0615 (0.0766) Prec@1 91.000 (87.786) Prec@5 100.000 (99.119) +2022-11-14 16:46:07,598 Test: [42/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0578 (0.0762) Prec@1 90.000 (87.837) Prec@5 99.000 (99.116) +2022-11-14 16:46:07,619 Test: [43/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0738 (0.0761) Prec@1 87.000 (87.818) Prec@5 99.000 (99.114) +2022-11-14 16:46:07,641 Test: [44/100] Model Time 0.011 (0.009) Loss Time 0.000 (0.000) Loss 0.0544 (0.0756) Prec@1 90.000 (87.867) Prec@5 100.000 (99.133) +2022-11-14 16:46:07,663 Test: [45/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0950 (0.0760) Prec@1 85.000 (87.804) Prec@5 100.000 (99.152) +2022-11-14 16:46:07,684 Test: [46/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0757) Prec@1 89.000 (87.830) Prec@5 100.000 (99.170) +2022-11-14 16:46:07,705 Test: [47/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0951 (0.0761) Prec@1 86.000 (87.792) Prec@5 98.000 (99.146) +2022-11-14 16:46:07,723 Test: [48/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0654 (0.0759) Prec@1 87.000 (87.776) Prec@5 100.000 (99.163) +2022-11-14 16:46:07,742 Test: [49/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0938 (0.0762) Prec@1 84.000 (87.700) Prec@5 100.000 (99.180) +2022-11-14 16:46:07,762 Test: [50/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0644 (0.0760) Prec@1 89.000 (87.725) Prec@5 100.000 (99.196) +2022-11-14 16:46:07,785 Test: [51/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0759) Prec@1 88.000 (87.731) Prec@5 99.000 (99.192) +2022-11-14 16:46:07,806 Test: [52/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0813 (0.0760) Prec@1 88.000 (87.736) Prec@5 100.000 (99.208) +2022-11-14 16:46:07,827 Test: [53/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0756) Prec@1 90.000 (87.778) Prec@5 99.000 (99.204) +2022-11-14 16:46:07,848 Test: [54/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0758) Prec@1 84.000 (87.709) Prec@5 99.000 (99.200) +2022-11-14 16:46:07,866 Test: [55/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0758) Prec@1 88.000 (87.714) Prec@5 99.000 (99.196) +2022-11-14 16:46:07,887 Test: [56/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0757) Prec@1 88.000 (87.719) Prec@5 100.000 (99.211) +2022-11-14 16:46:07,908 Test: [57/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0755) Prec@1 91.000 (87.776) Prec@5 100.000 (99.224) +2022-11-14 16:46:07,927 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1160 (0.0762) Prec@1 79.000 (87.627) Prec@5 100.000 (99.237) +2022-11-14 16:46:07,946 Test: [59/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0718 (0.0761) Prec@1 87.000 (87.617) Prec@5 99.000 (99.233) +2022-11-14 16:46:07,968 Test: [60/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0825 (0.0762) Prec@1 86.000 (87.590) Prec@5 100.000 (99.246) +2022-11-14 16:46:07,991 Test: [61/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0760) Prec@1 88.000 (87.597) Prec@5 100.000 (99.258) +2022-11-14 16:46:08,011 Test: [62/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0635 (0.0758) Prec@1 89.000 (87.619) Prec@5 100.000 (99.270) +2022-11-14 16:46:08,033 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0344 (0.0751) Prec@1 94.000 (87.719) Prec@5 99.000 (99.266) +2022-11-14 16:46:08,053 Test: [64/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0752) Prec@1 89.000 (87.738) Prec@5 100.000 (99.277) +2022-11-14 16:46:08,071 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0751) Prec@1 90.000 (87.773) Prec@5 98.000 (99.258) +2022-11-14 16:46:08,093 Test: [66/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0482 (0.0747) Prec@1 92.000 (87.836) Prec@5 100.000 (99.269) +2022-11-14 16:46:08,114 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0706 (0.0747) Prec@1 89.000 (87.853) Prec@5 99.000 (99.265) +2022-11-14 16:46:08,133 Test: [68/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0690 (0.0746) Prec@1 88.000 (87.855) Prec@5 99.000 (99.261) +2022-11-14 16:46:08,152 Test: [69/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0746) Prec@1 87.000 (87.843) Prec@5 98.000 (99.243) +2022-11-14 16:46:08,174 Test: [70/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0896 (0.0748) Prec@1 84.000 (87.789) Prec@5 100.000 (99.254) +2022-11-14 16:46:08,193 Test: [71/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0524 (0.0745) Prec@1 92.000 (87.847) Prec@5 99.000 (99.250) +2022-11-14 16:46:08,216 Test: [72/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0500 (0.0742) Prec@1 92.000 (87.904) Prec@5 100.000 (99.260) +2022-11-14 16:46:08,236 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0624 (0.0740) Prec@1 90.000 (87.932) Prec@5 100.000 (99.270) +2022-11-14 16:46:08,256 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1164 (0.0746) Prec@1 78.000 (87.800) Prec@5 100.000 (99.280) +2022-11-14 16:46:08,278 Test: [75/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0546 (0.0743) Prec@1 91.000 (87.842) Prec@5 99.000 (99.276) +2022-11-14 16:46:08,301 Test: [76/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0757 (0.0743) Prec@1 89.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 16:46:08,323 Test: [77/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0746) Prec@1 85.000 (87.821) Prec@5 99.000 (99.282) +2022-11-14 16:46:08,341 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0747) Prec@1 89.000 (87.835) Prec@5 100.000 (99.291) +2022-11-14 16:46:08,362 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0802 (0.0748) Prec@1 87.000 (87.825) Prec@5 100.000 (99.300) +2022-11-14 16:46:08,384 Test: [80/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0914 (0.0750) Prec@1 87.000 (87.815) Prec@5 98.000 (99.284) +2022-11-14 16:46:08,401 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0681 (0.0749) Prec@1 90.000 (87.841) Prec@5 99.000 (99.280) +2022-11-14 16:46:08,421 Test: [82/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0749) Prec@1 87.000 (87.831) Prec@5 98.000 (99.265) +2022-11-14 16:46:08,442 Test: [83/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0748) Prec@1 89.000 (87.845) Prec@5 99.000 (99.262) +2022-11-14 16:46:08,461 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0874 (0.0750) Prec@1 88.000 (87.847) Prec@5 100.000 (99.271) +2022-11-14 16:46:08,480 Test: [85/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1009 (0.0753) Prec@1 84.000 (87.802) Prec@5 98.000 (99.256) +2022-11-14 16:46:08,499 Test: [86/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0751) Prec@1 90.000 (87.828) Prec@5 100.000 (99.264) +2022-11-14 16:46:08,517 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0752) Prec@1 88.000 (87.830) Prec@5 99.000 (99.261) +2022-11-14 16:46:08,535 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0753) Prec@1 86.000 (87.809) Prec@5 99.000 (99.258) +2022-11-14 16:46:08,556 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0519 (0.0750) Prec@1 93.000 (87.867) Prec@5 100.000 (99.267) +2022-11-14 16:46:08,577 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0750) Prec@1 88.000 (87.868) Prec@5 99.000 (99.264) +2022-11-14 16:46:08,594 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0570 (0.0748) Prec@1 92.000 (87.913) Prec@5 100.000 (99.272) +2022-11-14 16:46:08,613 Test: [92/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0750) Prec@1 86.000 (87.892) Prec@5 100.000 (99.280) +2022-11-14 16:46:08,638 Test: [93/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0872 (0.0751) Prec@1 85.000 (87.862) Prec@5 98.000 (99.266) +2022-11-14 16:46:08,655 Test: [94/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0728 (0.0751) Prec@1 89.000 (87.874) Prec@5 99.000 (99.263) +2022-11-14 16:46:08,674 Test: [95/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0749) Prec@1 92.000 (87.917) Prec@5 100.000 (99.271) +2022-11-14 16:46:08,695 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0749) Prec@1 89.000 (87.928) Prec@5 98.000 (99.258) +2022-11-14 16:46:08,716 Test: [97/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0853 (0.0750) Prec@1 88.000 (87.929) Prec@5 99.000 (99.255) +2022-11-14 16:46:08,733 Test: [98/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0965 (0.0752) Prec@1 85.000 (87.899) Prec@5 100.000 (99.263) +2022-11-14 16:46:08,749 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0752) Prec@1 87.000 (87.890) Prec@5 100.000 (99.270) +2022-11-14 16:46:08,812 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:46:09,182 Epoch: [380][0/500] Time 0.030 (0.030) Data 0.277 (0.277) Loss 0.0198 (0.0198) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:09,706 Epoch: [380][10/500] Time 0.058 (0.045) Data 0.002 (0.027) Loss 0.0351 (0.0275) Prec@1 94.000 (95.500) Prec@5 99.000 (99.500) +2022-11-14 16:46:10,292 Epoch: [380][20/500] Time 0.068 (0.048) Data 0.002 (0.015) Loss 0.0192 (0.0247) Prec@1 98.000 (96.333) Prec@5 100.000 (99.667) +2022-11-14 16:46:10,899 Epoch: [380][30/500] Time 0.066 (0.050) Data 0.002 (0.011) Loss 0.0297 (0.0260) Prec@1 94.000 (95.750) Prec@5 100.000 (99.750) +2022-11-14 16:46:11,498 Epoch: [380][40/500] Time 0.061 (0.051) Data 0.002 (0.009) Loss 0.0344 (0.0276) Prec@1 93.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:46:12,106 Epoch: [380][50/500] Time 0.056 (0.051) Data 0.002 (0.007) Loss 0.0348 (0.0288) Prec@1 92.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:46:12,737 Epoch: [380][60/500] Time 0.052 (0.052) Data 0.002 (0.007) Loss 0.0356 (0.0298) Prec@1 92.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 16:46:13,326 Epoch: [380][70/500] Time 0.047 (0.052) Data 0.002 (0.006) Loss 0.0347 (0.0304) Prec@1 93.000 (94.125) Prec@5 100.000 (99.875) +2022-11-14 16:46:13,908 Epoch: [380][80/500] Time 0.058 (0.052) Data 0.002 (0.005) Loss 0.0223 (0.0295) Prec@1 97.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:46:14,501 Epoch: [380][90/500] Time 0.056 (0.052) Data 0.002 (0.005) Loss 0.0356 (0.0301) Prec@1 94.000 (94.400) Prec@5 99.000 (99.800) +2022-11-14 16:46:15,102 Epoch: [380][100/500] Time 0.060 (0.052) Data 0.002 (0.005) Loss 0.0453 (0.0315) Prec@1 94.000 (94.364) Prec@5 99.000 (99.727) +2022-11-14 16:46:15,684 Epoch: [380][110/500] Time 0.052 (0.052) Data 0.002 (0.005) Loss 0.0411 (0.0323) Prec@1 93.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:46:16,283 Epoch: [380][120/500] Time 0.056 (0.053) Data 0.002 (0.004) Loss 0.0288 (0.0320) Prec@1 95.000 (94.308) Prec@5 100.000 (99.769) +2022-11-14 16:46:16,880 Epoch: [380][130/500] Time 0.070 (0.053) Data 0.002 (0.004) Loss 0.0284 (0.0318) Prec@1 95.000 (94.357) Prec@5 99.000 (99.714) +2022-11-14 16:46:17,457 Epoch: [380][140/500] Time 0.044 (0.053) Data 0.002 (0.004) Loss 0.0360 (0.0321) Prec@1 96.000 (94.467) Prec@5 100.000 (99.733) +2022-11-14 16:46:18,057 Epoch: [380][150/500] Time 0.049 (0.053) Data 0.002 (0.004) Loss 0.0367 (0.0323) Prec@1 95.000 (94.500) Prec@5 99.000 (99.688) +2022-11-14 16:46:18,641 Epoch: [380][160/500] Time 0.059 (0.053) Data 0.002 (0.004) Loss 0.0476 (0.0332) Prec@1 90.000 (94.235) Prec@5 100.000 (99.706) +2022-11-14 16:46:19,230 Epoch: [380][170/500] Time 0.047 (0.053) Data 0.002 (0.004) Loss 0.0229 (0.0327) Prec@1 96.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 16:46:19,814 Epoch: [380][180/500] Time 0.057 (0.053) Data 0.002 (0.004) Loss 0.0194 (0.0320) Prec@1 98.000 (94.526) Prec@5 100.000 (99.684) +2022-11-14 16:46:20,415 Epoch: [380][190/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0140 (0.0311) Prec@1 98.000 (94.700) Prec@5 100.000 (99.700) +2022-11-14 16:46:21,009 Epoch: [380][200/500] Time 0.060 (0.053) Data 0.002 (0.003) Loss 0.0323 (0.0311) Prec@1 93.000 (94.619) Prec@5 100.000 (99.714) +2022-11-14 16:46:21,589 Epoch: [380][210/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0497 (0.0320) Prec@1 91.000 (94.455) Prec@5 100.000 (99.727) +2022-11-14 16:46:22,170 Epoch: [380][220/500] Time 0.047 (0.053) Data 0.002 (0.003) Loss 0.0252 (0.0317) Prec@1 96.000 (94.522) Prec@5 100.000 (99.739) +2022-11-14 16:46:22,802 Epoch: [380][230/500] Time 0.072 (0.053) Data 0.002 (0.003) Loss 0.0163 (0.0310) Prec@1 98.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 16:46:23,418 Epoch: [380][240/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0319 (0.0311) Prec@1 95.000 (94.680) Prec@5 100.000 (99.760) +2022-11-14 16:46:24,041 Epoch: [380][250/500] Time 0.079 (0.053) Data 0.002 (0.003) Loss 0.0199 (0.0306) Prec@1 97.000 (94.769) Prec@5 100.000 (99.769) +2022-11-14 16:46:24,702 Epoch: [380][260/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0289 (0.0306) Prec@1 95.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 16:46:25,302 Epoch: [380][270/500] Time 0.054 (0.053) Data 0.002 (0.003) Loss 0.0203 (0.0302) Prec@1 97.000 (94.857) Prec@5 100.000 (99.786) +2022-11-14 16:46:25,986 Epoch: [380][280/500] Time 0.069 (0.054) Data 0.002 (0.003) Loss 0.0257 (0.0301) Prec@1 94.000 (94.828) Prec@5 100.000 (99.793) +2022-11-14 16:46:26,559 Epoch: [380][290/500] Time 0.055 (0.053) Data 0.002 (0.003) Loss 0.0340 (0.0302) Prec@1 95.000 (94.833) Prec@5 98.000 (99.733) +2022-11-14 16:46:27,144 Epoch: [380][300/500] Time 0.053 (0.053) Data 0.002 (0.003) Loss 0.0298 (0.0302) Prec@1 96.000 (94.871) Prec@5 98.000 (99.677) +2022-11-14 16:46:27,732 Epoch: [380][310/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0160 (0.0297) Prec@1 97.000 (94.938) Prec@5 100.000 (99.688) +2022-11-14 16:46:28,310 Epoch: [380][320/500] Time 0.065 (0.053) Data 0.002 (0.003) Loss 0.0378 (0.0300) Prec@1 94.000 (94.909) Prec@5 99.000 (99.667) +2022-11-14 16:46:28,872 Epoch: [380][330/500] Time 0.048 (0.053) Data 0.002 (0.003) Loss 0.0249 (0.0298) Prec@1 96.000 (94.941) Prec@5 100.000 (99.676) +2022-11-14 16:46:29,454 Epoch: [380][340/500] Time 0.060 (0.053) Data 0.003 (0.003) Loss 0.0305 (0.0298) Prec@1 96.000 (94.971) Prec@5 100.000 (99.686) +2022-11-14 16:46:30,029 Epoch: [380][350/500] Time 0.047 (0.053) Data 0.002 (0.003) Loss 0.0320 (0.0299) Prec@1 95.000 (94.972) Prec@5 100.000 (99.694) +2022-11-14 16:46:30,628 Epoch: [380][360/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0119 (0.0294) Prec@1 99.000 (95.081) Prec@5 100.000 (99.703) +2022-11-14 16:46:31,227 Epoch: [380][370/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0386 (0.0297) Prec@1 93.000 (95.026) Prec@5 100.000 (99.711) +2022-11-14 16:46:31,800 Epoch: [380][380/500] Time 0.061 (0.053) Data 0.002 (0.003) Loss 0.0234 (0.0295) Prec@1 96.000 (95.051) Prec@5 100.000 (99.718) +2022-11-14 16:46:32,467 Epoch: [380][390/500] Time 0.050 (0.053) Data 0.002 (0.003) Loss 0.0582 (0.0302) Prec@1 91.000 (94.950) Prec@5 100.000 (99.725) +2022-11-14 16:46:33,059 Epoch: [380][400/500] Time 0.062 (0.053) Data 0.002 (0.003) Loss 0.0267 (0.0301) Prec@1 93.000 (94.902) Prec@5 100.000 (99.732) +2022-11-14 16:46:33,645 Epoch: [380][410/500] Time 0.059 (0.053) Data 0.002 (0.003) Loss 0.0261 (0.0300) Prec@1 95.000 (94.905) Prec@5 100.000 (99.738) +2022-11-14 16:46:34,238 Epoch: [380][420/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0516 (0.0305) Prec@1 91.000 (94.814) Prec@5 99.000 (99.721) +2022-11-14 16:46:34,855 Epoch: [380][430/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0485 (0.0309) Prec@1 92.000 (94.750) Prec@5 100.000 (99.727) +2022-11-14 16:46:35,462 Epoch: [380][440/500] Time 0.058 (0.053) Data 0.002 (0.003) Loss 0.0160 (0.0306) Prec@1 97.000 (94.800) Prec@5 100.000 (99.733) +2022-11-14 16:46:36,063 Epoch: [380][450/500] Time 0.056 (0.053) Data 0.002 (0.003) Loss 0.0438 (0.0309) Prec@1 93.000 (94.761) Prec@5 100.000 (99.739) +2022-11-14 16:46:36,703 Epoch: [380][460/500] Time 0.063 (0.053) Data 0.002 (0.003) Loss 0.0218 (0.0307) Prec@1 96.000 (94.787) Prec@5 99.000 (99.723) +2022-11-14 16:46:37,301 Epoch: [380][470/500] Time 0.067 (0.053) Data 0.002 (0.003) Loss 0.0467 (0.0310) Prec@1 93.000 (94.750) Prec@5 99.000 (99.708) +2022-11-14 16:46:37,978 Epoch: [380][480/500] Time 0.057 (0.054) Data 0.002 (0.003) Loss 0.0254 (0.0309) Prec@1 97.000 (94.796) Prec@5 100.000 (99.714) +2022-11-14 16:46:38,542 Epoch: [380][490/500] Time 0.053 (0.054) Data 0.002 (0.003) Loss 0.0298 (0.0309) Prec@1 95.000 (94.800) Prec@5 100.000 (99.720) +2022-11-14 16:46:39,069 Epoch: [380][499/500] Time 0.061 (0.054) Data 0.002 (0.003) Loss 0.0235 (0.0308) Prec@1 95.000 (94.804) Prec@5 100.000 (99.725) +2022-11-14 16:46:39,399 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0700 (0.0700) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:39,411 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0624 (0.0662) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:39,422 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0669) Prec@1 90.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 16:46:39,433 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0648) Prec@1 89.000 (89.250) Prec@5 98.000 (99.500) +2022-11-14 16:46:39,443 Test: [4/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0775 (0.0674) Prec@1 87.000 (88.800) Prec@5 99.000 (99.400) +2022-11-14 16:46:39,456 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0359 (0.0621) Prec@1 92.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 16:46:39,467 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0547 (0.0611) Prec@1 93.000 (89.857) Prec@5 99.000 (99.286) +2022-11-14 16:46:39,481 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1055 (0.0666) Prec@1 82.000 (88.875) Prec@5 100.000 (99.375) +2022-11-14 16:46:39,493 Test: [8/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0704 (0.0670) Prec@1 89.000 (88.889) Prec@5 99.000 (99.333) +2022-11-14 16:46:39,508 Test: [9/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0948 (0.0698) Prec@1 86.000 (88.600) Prec@5 98.000 (99.200) +2022-11-14 16:46:39,526 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0572 (0.0687) Prec@1 90.000 (88.727) Prec@5 99.000 (99.182) +2022-11-14 16:46:39,543 Test: [11/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0702) Prec@1 86.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 16:46:39,561 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0698) Prec@1 89.000 (88.538) Prec@5 100.000 (99.231) +2022-11-14 16:46:39,579 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0698) Prec@1 89.000 (88.571) Prec@5 99.000 (99.214) +2022-11-14 16:46:39,599 Test: [14/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0740 (0.0701) Prec@1 85.000 (88.333) Prec@5 100.000 (99.267) +2022-11-14 16:46:39,616 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0578 (0.0693) Prec@1 89.000 (88.375) Prec@5 100.000 (99.312) +2022-11-14 16:46:39,634 Test: [16/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0681) Prec@1 93.000 (88.647) Prec@5 99.000 (99.294) +2022-11-14 16:46:39,652 Test: [17/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1125 (0.0706) Prec@1 83.000 (88.333) Prec@5 99.000 (99.278) +2022-11-14 16:46:39,674 Test: [18/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1098 (0.0726) Prec@1 84.000 (88.105) Prec@5 99.000 (99.263) +2022-11-14 16:46:39,693 Test: [19/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1144 (0.0747) Prec@1 82.000 (87.800) Prec@5 98.000 (99.200) +2022-11-14 16:46:39,712 Test: [20/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0561 (0.0738) Prec@1 91.000 (87.952) Prec@5 100.000 (99.238) +2022-11-14 16:46:39,735 Test: [21/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0742) Prec@1 84.000 (87.773) Prec@5 99.000 (99.227) +2022-11-14 16:46:39,755 Test: [22/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0983 (0.0752) Prec@1 86.000 (87.696) Prec@5 99.000 (99.217) +2022-11-14 16:46:39,771 Test: [23/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0749) Prec@1 90.000 (87.792) Prec@5 100.000 (99.250) +2022-11-14 16:46:39,793 Test: [24/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0742) Prec@1 91.000 (87.920) Prec@5 100.000 (99.280) +2022-11-14 16:46:39,812 Test: [25/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.1037 (0.0754) Prec@1 84.000 (87.769) Prec@5 96.000 (99.154) +2022-11-14 16:46:39,830 Test: [26/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0579 (0.0747) Prec@1 92.000 (87.926) Prec@5 100.000 (99.185) +2022-11-14 16:46:39,847 Test: [27/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0707 (0.0746) Prec@1 89.000 (87.964) Prec@5 99.000 (99.179) +2022-11-14 16:46:39,867 Test: [28/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0745) Prec@1 87.000 (87.931) Prec@5 98.000 (99.138) +2022-11-14 16:46:39,889 Test: [29/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0566 (0.0739) Prec@1 92.000 (88.067) Prec@5 100.000 (99.167) +2022-11-14 16:46:39,909 Test: [30/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0888 (0.0743) Prec@1 84.000 (87.935) Prec@5 99.000 (99.161) +2022-11-14 16:46:39,930 Test: [31/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0744) Prec@1 88.000 (87.938) Prec@5 100.000 (99.188) +2022-11-14 16:46:39,951 Test: [32/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0830 (0.0747) Prec@1 86.000 (87.879) Prec@5 100.000 (99.212) +2022-11-14 16:46:39,972 Test: [33/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0753) Prec@1 83.000 (87.735) Prec@5 98.000 (99.176) +2022-11-14 16:46:39,996 Test: [34/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0756) Prec@1 88.000 (87.743) Prec@5 97.000 (99.114) +2022-11-14 16:46:40,015 Test: [35/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0755) Prec@1 90.000 (87.806) Prec@5 99.000 (99.111) +2022-11-14 16:46:40,035 Test: [36/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0755) Prec@1 88.000 (87.811) Prec@5 99.000 (99.108) +2022-11-14 16:46:40,052 Test: [37/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1028 (0.0763) Prec@1 81.000 (87.632) Prec@5 98.000 (99.079) +2022-11-14 16:46:40,070 Test: [38/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0754) Prec@1 95.000 (87.821) Prec@5 99.000 (99.077) +2022-11-14 16:46:40,090 Test: [39/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0753) Prec@1 88.000 (87.825) Prec@5 100.000 (99.100) +2022-11-14 16:46:40,108 Test: [40/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0758) Prec@1 85.000 (87.756) Prec@5 98.000 (99.073) +2022-11-14 16:46:40,124 Test: [41/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0757) Prec@1 87.000 (87.738) Prec@5 100.000 (99.095) +2022-11-14 16:46:40,147 Test: [42/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0445 (0.0750) Prec@1 93.000 (87.860) Prec@5 99.000 (99.093) +2022-11-14 16:46:40,167 Test: [43/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0747) Prec@1 92.000 (87.955) Prec@5 99.000 (99.091) +2022-11-14 16:46:40,190 Test: [44/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0789 (0.0748) Prec@1 89.000 (87.978) Prec@5 99.000 (99.089) +2022-11-14 16:46:40,210 Test: [45/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0963 (0.0752) Prec@1 83.000 (87.870) Prec@5 100.000 (99.109) +2022-11-14 16:46:40,231 Test: [46/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0750) Prec@1 88.000 (87.872) Prec@5 100.000 (99.128) +2022-11-14 16:46:40,250 Test: [47/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0981 (0.0755) Prec@1 86.000 (87.833) Prec@5 99.000 (99.125) +2022-11-14 16:46:40,266 Test: [48/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0535 (0.0751) Prec@1 89.000 (87.857) Prec@5 99.000 (99.122) +2022-11-14 16:46:40,284 Test: [49/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1036 (0.0756) Prec@1 83.000 (87.760) Prec@5 100.000 (99.140) +2022-11-14 16:46:40,307 Test: [50/100] Model Time 0.010 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0758) Prec@1 87.000 (87.745) Prec@5 99.000 (99.137) +2022-11-14 16:46:40,329 Test: [51/100] Model Time 0.011 (0.008) Loss Time 0.000 (0.000) Loss 0.0898 (0.0761) Prec@1 86.000 (87.712) Prec@5 100.000 (99.154) +2022-11-14 16:46:40,351 Test: [52/100] Model Time 0.012 (0.008) Loss Time 0.000 (0.000) Loss 0.0992 (0.0765) Prec@1 84.000 (87.642) Prec@5 100.000 (99.170) +2022-11-14 16:46:40,370 Test: [53/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0684 (0.0763) Prec@1 88.000 (87.648) Prec@5 100.000 (99.185) +2022-11-14 16:46:40,390 Test: [54/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1014 (0.0768) Prec@1 84.000 (87.582) Prec@5 99.000 (99.182) +2022-11-14 16:46:40,409 Test: [55/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0766) Prec@1 91.000 (87.643) Prec@5 99.000 (99.179) +2022-11-14 16:46:40,427 Test: [56/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0766) Prec@1 86.000 (87.614) Prec@5 100.000 (99.193) +2022-11-14 16:46:40,443 Test: [57/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0764) Prec@1 91.000 (87.672) Prec@5 100.000 (99.207) +2022-11-14 16:46:40,460 Test: [58/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0924 (0.0767) Prec@1 86.000 (87.644) Prec@5 98.000 (99.186) +2022-11-14 16:46:40,480 Test: [59/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0767) Prec@1 88.000 (87.650) Prec@5 100.000 (99.200) +2022-11-14 16:46:40,501 Test: [60/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0822 (0.0768) Prec@1 85.000 (87.607) Prec@5 100.000 (99.213) +2022-11-14 16:46:40,522 Test: [61/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0575 (0.0765) Prec@1 91.000 (87.661) Prec@5 100.000 (99.226) +2022-11-14 16:46:40,544 Test: [62/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0765) Prec@1 87.000 (87.651) Prec@5 99.000 (99.222) +2022-11-14 16:46:40,568 Test: [63/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0376 (0.0759) Prec@1 93.000 (87.734) Prec@5 100.000 (99.234) +2022-11-14 16:46:40,586 Test: [64/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0761) Prec@1 84.000 (87.677) Prec@5 100.000 (99.246) +2022-11-14 16:46:40,605 Test: [65/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0762) Prec@1 90.000 (87.712) Prec@5 98.000 (99.227) +2022-11-14 16:46:40,622 Test: [66/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0759) Prec@1 91.000 (87.761) Prec@5 100.000 (99.239) +2022-11-14 16:46:40,641 Test: [67/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0758) Prec@1 90.000 (87.794) Prec@5 99.000 (99.235) +2022-11-14 16:46:40,663 Test: [68/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0674 (0.0757) Prec@1 90.000 (87.826) Prec@5 99.000 (99.232) +2022-11-14 16:46:40,682 Test: [69/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0680 (0.0756) Prec@1 90.000 (87.857) Prec@5 98.000 (99.214) +2022-11-14 16:46:40,699 Test: [70/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1013 (0.0759) Prec@1 87.000 (87.845) Prec@5 98.000 (99.197) +2022-11-14 16:46:40,720 Test: [71/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0758) Prec@1 89.000 (87.861) Prec@5 99.000 (99.194) +2022-11-14 16:46:40,741 Test: [72/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0425 (0.0753) Prec@1 93.000 (87.932) Prec@5 100.000 (99.205) +2022-11-14 16:46:40,759 Test: [73/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0321 (0.0748) Prec@1 94.000 (88.014) Prec@5 100.000 (99.216) +2022-11-14 16:46:40,776 Test: [74/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.0753) Prec@1 82.000 (87.933) Prec@5 100.000 (99.227) +2022-11-14 16:46:40,795 Test: [75/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0577 (0.0750) Prec@1 91.000 (87.974) Prec@5 99.000 (99.224) +2022-11-14 16:46:40,814 Test: [76/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0750) Prec@1 89.000 (87.987) Prec@5 100.000 (99.234) +2022-11-14 16:46:40,834 Test: [77/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 83.000 (87.923) Prec@5 99.000 (99.231) +2022-11-14 16:46:40,855 Test: [78/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0804 (0.0752) Prec@1 87.000 (87.911) Prec@5 100.000 (99.241) +2022-11-14 16:46:40,877 Test: [79/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0639 (0.0751) Prec@1 89.000 (87.925) Prec@5 99.000 (99.237) +2022-11-14 16:46:40,898 Test: [80/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0751) Prec@1 88.000 (87.926) Prec@5 99.000 (99.235) +2022-11-14 16:46:40,921 Test: [81/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0751) Prec@1 88.000 (87.927) Prec@5 100.000 (99.244) +2022-11-14 16:46:40,941 Test: [82/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1023 (0.0754) Prec@1 84.000 (87.880) Prec@5 97.000 (99.217) +2022-11-14 16:46:40,959 Test: [83/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0599 (0.0752) Prec@1 90.000 (87.905) Prec@5 99.000 (99.214) +2022-11-14 16:46:40,980 Test: [84/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0668 (0.0751) Prec@1 89.000 (87.918) Prec@5 100.000 (99.224) +2022-11-14 16:46:41,002 Test: [85/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1131 (0.0755) Prec@1 83.000 (87.860) Prec@5 100.000 (99.233) +2022-11-14 16:46:41,021 Test: [86/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0644 (0.0754) Prec@1 89.000 (87.874) Prec@5 100.000 (99.241) +2022-11-14 16:46:41,042 Test: [87/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0760 (0.0754) Prec@1 89.000 (87.886) Prec@5 99.000 (99.239) +2022-11-14 16:46:41,062 Test: [88/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0753) Prec@1 89.000 (87.899) Prec@5 99.000 (99.236) +2022-11-14 16:46:41,080 Test: [89/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0752) Prec@1 90.000 (87.922) Prec@5 99.000 (99.233) +2022-11-14 16:46:41,100 Test: [90/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0592 (0.0750) Prec@1 87.000 (87.912) Prec@5 100.000 (99.242) +2022-11-14 16:46:41,118 Test: [91/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0748) Prec@1 93.000 (87.967) Prec@5 100.000 (99.250) +2022-11-14 16:46:41,138 Test: [92/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0749) Prec@1 86.000 (87.946) Prec@5 100.000 (99.258) +2022-11-14 16:46:41,161 Test: [93/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0748) Prec@1 87.000 (87.936) Prec@5 99.000 (99.255) +2022-11-14 16:46:41,179 Test: [94/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0746) Prec@1 89.000 (87.947) Prec@5 99.000 (99.253) +2022-11-14 16:46:41,200 Test: [95/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0745) Prec@1 91.000 (87.979) Prec@5 99.000 (99.250) +2022-11-14 16:46:41,223 Test: [96/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0446 (0.0742) Prec@1 92.000 (88.021) Prec@5 98.000 (99.237) +2022-11-14 16:46:41,245 Test: [97/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0847 (0.0743) Prec@1 86.000 (88.000) Prec@5 99.000 (99.235) +2022-11-14 16:46:41,262 Test: [98/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0906 (0.0744) Prec@1 86.000 (87.980) Prec@5 99.000 (99.232) +2022-11-14 16:46:41,284 Test: [99/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0744) Prec@1 89.000 (87.990) Prec@5 100.000 (99.240) +2022-11-14 16:46:41,348 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:46:41,711 Epoch: [381][0/500] Time 0.027 (0.027) Data 0.274 (0.274) Loss 0.0519 (0.0519) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:42,234 Epoch: [381][10/500] Time 0.055 (0.045) Data 0.002 (0.027) Loss 0.0225 (0.0372) Prec@1 96.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:42,825 Epoch: [381][20/500] Time 0.054 (0.048) Data 0.002 (0.015) Loss 0.0368 (0.0371) Prec@1 94.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 16:46:43,396 Epoch: [381][30/500] Time 0.057 (0.049) Data 0.002 (0.011) Loss 0.0293 (0.0351) Prec@1 95.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 16:46:43,982 Epoch: [381][40/500] Time 0.054 (0.050) Data 0.002 (0.009) Loss 0.0174 (0.0316) Prec@1 97.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:46:44,539 Epoch: [381][50/500] Time 0.060 (0.050) Data 0.002 (0.007) Loss 0.0118 (0.0283) Prec@1 99.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 16:46:45,091 Epoch: [381][60/500] Time 0.058 (0.050) Data 0.002 (0.006) Loss 0.0393 (0.0299) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:45,593 Epoch: [381][70/500] Time 0.042 (0.049) Data 0.002 (0.006) Loss 0.0155 (0.0281) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:46:46,252 Epoch: [381][80/500] Time 0.066 (0.050) Data 0.002 (0.005) Loss 0.0412 (0.0295) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:46,804 Epoch: [381][90/500] Time 0.071 (0.050) Data 0.002 (0.005) Loss 0.0297 (0.0295) Prec@1 94.000 (94.900) Prec@5 100.000 (100.000) +2022-11-14 16:46:47,267 Epoch: [381][100/500] Time 0.044 (0.049) Data 0.002 (0.005) Loss 0.0309 (0.0297) Prec@1 95.000 (94.909) Prec@5 100.000 (100.000) +2022-11-14 16:46:47,822 Epoch: [381][110/500] Time 0.044 (0.049) Data 0.003 (0.004) Loss 0.0283 (0.0295) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:48,314 Epoch: [381][120/500] Time 0.044 (0.049) Data 0.002 (0.004) Loss 0.0339 (0.0299) Prec@1 93.000 (94.846) Prec@5 100.000 (100.000) +2022-11-14 16:46:48,777 Epoch: [381][130/500] Time 0.044 (0.048) Data 0.002 (0.004) Loss 0.0125 (0.0286) Prec@1 99.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:46:49,267 Epoch: [381][140/500] Time 0.056 (0.048) Data 0.002 (0.004) Loss 0.0365 (0.0292) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:46:49,791 Epoch: [381][150/500] Time 0.044 (0.048) Data 0.002 (0.004) Loss 0.0417 (0.0299) Prec@1 93.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 16:46:50,290 Epoch: [381][160/500] Time 0.028 (0.048) Data 0.002 (0.004) Loss 0.0507 (0.0312) Prec@1 92.000 (94.706) Prec@5 100.000 (100.000) +2022-11-14 16:46:50,574 Epoch: [381][170/500] Time 0.025 (0.046) Data 0.002 (0.004) Loss 0.0249 (0.0308) Prec@1 94.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:46:50,863 Epoch: [381][180/500] Time 0.027 (0.045) Data 0.002 (0.004) Loss 0.0424 (0.0314) Prec@1 95.000 (94.684) Prec@5 99.000 (99.947) +2022-11-14 16:46:51,176 Epoch: [381][190/500] Time 0.022 (0.044) Data 0.002 (0.003) Loss 0.0160 (0.0307) Prec@1 98.000 (94.850) Prec@5 100.000 (99.950) +2022-11-14 16:46:51,459 Epoch: [381][200/500] Time 0.027 (0.043) Data 0.002 (0.003) Loss 0.0326 (0.0308) Prec@1 94.000 (94.810) Prec@5 100.000 (99.952) +2022-11-14 16:46:51,744 Epoch: [381][210/500] Time 0.027 (0.042) Data 0.002 (0.003) Loss 0.0417 (0.0312) Prec@1 95.000 (94.818) Prec@5 99.000 (99.909) +2022-11-14 16:46:52,033 Epoch: [381][220/500] Time 0.028 (0.042) Data 0.002 (0.003) Loss 0.0253 (0.0310) Prec@1 96.000 (94.870) Prec@5 100.000 (99.913) +2022-11-14 16:46:52,329 Epoch: [381][230/500] Time 0.024 (0.041) Data 0.002 (0.003) Loss 0.0282 (0.0309) Prec@1 95.000 (94.875) Prec@5 100.000 (99.917) +2022-11-14 16:46:52,618 Epoch: [381][240/500] Time 0.026 (0.040) Data 0.002 (0.003) Loss 0.0396 (0.0312) Prec@1 95.000 (94.880) Prec@5 99.000 (99.880) +2022-11-14 16:46:52,908 Epoch: [381][250/500] Time 0.027 (0.040) Data 0.002 (0.003) Loss 0.0131 (0.0305) Prec@1 99.000 (95.038) Prec@5 100.000 (99.885) +2022-11-14 16:46:53,201 Epoch: [381][260/500] Time 0.026 (0.039) Data 0.002 (0.003) Loss 0.0231 (0.0302) Prec@1 95.000 (95.037) Prec@5 100.000 (99.889) +2022-11-14 16:46:53,486 Epoch: [381][270/500] Time 0.026 (0.039) Data 0.002 (0.003) Loss 0.0328 (0.0303) Prec@1 95.000 (95.036) Prec@5 100.000 (99.893) +2022-11-14 16:46:53,769 Epoch: [381][280/500] Time 0.026 (0.038) Data 0.002 (0.003) Loss 0.0259 (0.0302) Prec@1 96.000 (95.069) Prec@5 100.000 (99.897) +2022-11-14 16:46:54,063 Epoch: [381][290/500] Time 0.027 (0.038) Data 0.002 (0.003) Loss 0.0176 (0.0298) Prec@1 98.000 (95.167) Prec@5 100.000 (99.900) +2022-11-14 16:46:54,348 Epoch: [381][300/500] Time 0.026 (0.037) Data 0.002 (0.003) Loss 0.0266 (0.0297) Prec@1 95.000 (95.161) Prec@5 100.000 (99.903) +2022-11-14 16:46:54,635 Epoch: [381][310/500] Time 0.025 (0.037) Data 0.002 (0.003) Loss 0.0267 (0.0296) Prec@1 97.000 (95.219) Prec@5 100.000 (99.906) +2022-11-14 16:46:54,921 Epoch: [381][320/500] Time 0.026 (0.037) Data 0.002 (0.003) Loss 0.0320 (0.0296) Prec@1 94.000 (95.182) Prec@5 99.000 (99.879) +2022-11-14 16:46:55,210 Epoch: [381][330/500] Time 0.026 (0.036) Data 0.002 (0.003) Loss 0.0315 (0.0297) Prec@1 94.000 (95.147) Prec@5 100.000 (99.882) +2022-11-14 16:46:55,496 Epoch: [381][340/500] Time 0.027 (0.036) Data 0.002 (0.003) Loss 0.0372 (0.0299) Prec@1 95.000 (95.143) Prec@5 100.000 (99.886) +2022-11-14 16:46:55,789 Epoch: [381][350/500] Time 0.029 (0.036) Data 0.001 (0.003) Loss 0.0251 (0.0298) Prec@1 95.000 (95.139) Prec@5 100.000 (99.889) +2022-11-14 16:46:56,076 Epoch: [381][360/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.0489 (0.0303) Prec@1 93.000 (95.081) Prec@5 100.000 (99.892) +2022-11-14 16:46:56,362 Epoch: [381][370/500] Time 0.027 (0.035) Data 0.002 (0.003) Loss 0.0354 (0.0304) Prec@1 93.000 (95.026) Prec@5 99.000 (99.868) +2022-11-14 16:46:56,643 Epoch: [381][380/500] Time 0.026 (0.035) Data 0.002 (0.003) Loss 0.0326 (0.0305) Prec@1 96.000 (95.051) Prec@5 100.000 (99.872) +2022-11-14 16:46:56,932 Epoch: [381][390/500] Time 0.028 (0.035) Data 0.002 (0.003) Loss 0.0456 (0.0309) Prec@1 92.000 (94.975) Prec@5 100.000 (99.875) +2022-11-14 16:46:57,224 Epoch: [381][400/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0420 (0.0311) Prec@1 93.000 (94.927) Prec@5 100.000 (99.878) +2022-11-14 16:46:57,512 Epoch: [381][410/500] Time 0.027 (0.034) Data 0.002 (0.003) Loss 0.0472 (0.0315) Prec@1 93.000 (94.881) Prec@5 100.000 (99.881) +2022-11-14 16:46:57,802 Epoch: [381][420/500] Time 0.028 (0.034) Data 0.002 (0.003) Loss 0.0221 (0.0313) Prec@1 95.000 (94.884) Prec@5 100.000 (99.884) +2022-11-14 16:46:58,097 Epoch: [381][430/500] Time 0.034 (0.034) Data 0.002 (0.003) Loss 0.0275 (0.0312) Prec@1 95.000 (94.886) Prec@5 100.000 (99.886) +2022-11-14 16:46:58,385 Epoch: [381][440/500] Time 0.026 (0.034) Data 0.002 (0.003) Loss 0.0274 (0.0311) Prec@1 96.000 (94.911) Prec@5 100.000 (99.889) +2022-11-14 16:46:58,672 Epoch: [381][450/500] Time 0.026 (0.033) Data 0.001 (0.003) Loss 0.0208 (0.0309) Prec@1 97.000 (94.957) Prec@5 100.000 (99.891) +2022-11-14 16:46:58,955 Epoch: [381][460/500] Time 0.026 (0.033) Data 0.002 (0.003) Loss 0.0275 (0.0308) Prec@1 94.000 (94.936) Prec@5 100.000 (99.894) +2022-11-14 16:46:59,242 Epoch: [381][470/500] Time 0.028 (0.033) Data 0.002 (0.003) Loss 0.0408 (0.0310) Prec@1 93.000 (94.896) Prec@5 100.000 (99.896) +2022-11-14 16:46:59,529 Epoch: [381][480/500] Time 0.028 (0.033) Data 0.002 (0.002) Loss 0.0401 (0.0312) Prec@1 93.000 (94.857) Prec@5 100.000 (99.898) +2022-11-14 16:46:59,819 Epoch: [381][490/500] Time 0.027 (0.033) Data 0.002 (0.002) Loss 0.0471 (0.0315) Prec@1 91.000 (94.780) Prec@5 99.000 (99.880) +2022-11-14 16:47:00,080 Epoch: [381][499/500] Time 0.027 (0.033) Data 0.001 (0.002) Loss 0.0266 (0.0314) Prec@1 96.000 (94.804) Prec@5 100.000 (99.882) +2022-11-14 16:47:00,401 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0715 (0.0715) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:00,408 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0893 (0.0804) Prec@1 85.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:00,416 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0751) Prec@1 88.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 16:47:00,425 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0740) Prec@1 90.000 (87.500) Prec@5 98.000 (99.500) +2022-11-14 16:47:00,432 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0754) Prec@1 88.000 (87.600) Prec@5 98.000 (99.200) +2022-11-14 16:47:00,439 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0723) Prec@1 88.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 16:47:00,447 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0695) Prec@1 93.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 16:47:00,455 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0723) Prec@1 85.000 (88.000) Prec@5 99.000 (99.375) +2022-11-14 16:47:00,462 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0731) Prec@1 87.000 (87.889) Prec@5 100.000 (99.444) +2022-11-14 16:47:00,470 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0747) Prec@1 85.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 16:47:00,478 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0726) Prec@1 91.000 (87.909) Prec@5 100.000 (99.455) +2022-11-14 16:47:00,486 Test: [11/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0738) Prec@1 86.000 (87.750) Prec@5 100.000 (99.500) +2022-11-14 16:47:00,495 Test: [12/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0730) Prec@1 89.000 (87.846) Prec@5 100.000 (99.538) +2022-11-14 16:47:00,504 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0725) Prec@1 90.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 16:47:00,512 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0726) Prec@1 89.000 (88.067) Prec@5 100.000 (99.533) +2022-11-14 16:47:00,522 Test: [15/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0729) Prec@1 85.000 (87.875) Prec@5 98.000 (99.438) +2022-11-14 16:47:00,530 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0717) Prec@1 93.000 (88.176) Prec@5 98.000 (99.353) +2022-11-14 16:47:00,538 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0729) Prec@1 85.000 (88.000) Prec@5 100.000 (99.389) +2022-11-14 16:47:00,546 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0738) Prec@1 84.000 (87.789) Prec@5 98.000 (99.316) +2022-11-14 16:47:00,553 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0747) Prec@1 84.000 (87.600) Prec@5 97.000 (99.200) +2022-11-14 16:47:00,561 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0753) Prec@1 84.000 (87.429) Prec@5 100.000 (99.238) +2022-11-14 16:47:00,569 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0756) Prec@1 87.000 (87.409) Prec@5 100.000 (99.273) +2022-11-14 16:47:00,577 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0765) Prec@1 85.000 (87.304) Prec@5 99.000 (99.261) +2022-11-14 16:47:00,584 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0767) Prec@1 85.000 (87.208) Prec@5 100.000 (99.292) +2022-11-14 16:47:00,592 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0768) Prec@1 88.000 (87.240) Prec@5 100.000 (99.320) +2022-11-14 16:47:00,601 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0772) Prec@1 85.000 (87.154) Prec@5 98.000 (99.269) +2022-11-14 16:47:00,609 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0765) Prec@1 90.000 (87.259) Prec@5 100.000 (99.296) +2022-11-14 16:47:00,616 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0756) Prec@1 90.000 (87.357) Prec@5 99.000 (99.286) +2022-11-14 16:47:00,624 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0762) Prec@1 84.000 (87.241) Prec@5 99.000 (99.276) +2022-11-14 16:47:00,632 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0766) Prec@1 84.000 (87.133) Prec@5 100.000 (99.300) +2022-11-14 16:47:00,640 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0760) Prec@1 92.000 (87.290) Prec@5 100.000 (99.323) +2022-11-14 16:47:00,648 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0757) Prec@1 89.000 (87.344) Prec@5 99.000 (99.312) +2022-11-14 16:47:00,655 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0758) Prec@1 88.000 (87.364) Prec@5 100.000 (99.333) +2022-11-14 16:47:00,663 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.0767) Prec@1 83.000 (87.235) Prec@5 99.000 (99.324) +2022-11-14 16:47:00,671 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0771) Prec@1 86.000 (87.200) Prec@5 97.000 (99.257) +2022-11-14 16:47:00,678 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0768) Prec@1 91.000 (87.306) Prec@5 100.000 (99.278) +2022-11-14 16:47:00,686 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0768) Prec@1 88.000 (87.324) Prec@5 100.000 (99.297) +2022-11-14 16:47:00,694 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0769) Prec@1 88.000 (87.342) Prec@5 100.000 (99.316) +2022-11-14 16:47:00,701 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0762) Prec@1 93.000 (87.487) Prec@5 99.000 (99.308) +2022-11-14 16:47:00,709 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0757) Prec@1 90.000 (87.550) Prec@5 100.000 (99.325) +2022-11-14 16:47:00,717 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.0765) Prec@1 82.000 (87.415) Prec@5 100.000 (99.341) +2022-11-14 16:47:00,725 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0764) Prec@1 89.000 (87.452) Prec@5 100.000 (99.357) +2022-11-14 16:47:00,732 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0757) Prec@1 93.000 (87.581) Prec@5 99.000 (99.349) +2022-11-14 16:47:00,740 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0754) Prec@1 90.000 (87.636) Prec@5 98.000 (99.318) +2022-11-14 16:47:00,748 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0473 (0.0748) Prec@1 92.000 (87.733) Prec@5 100.000 (99.333) +2022-11-14 16:47:00,755 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0756) Prec@1 81.000 (87.587) Prec@5 99.000 (99.326) +2022-11-14 16:47:00,763 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0754) Prec@1 89.000 (87.617) Prec@5 99.000 (99.319) +2022-11-14 16:47:00,771 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0757) Prec@1 85.000 (87.562) Prec@5 98.000 (99.292) +2022-11-14 16:47:00,779 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0755) Prec@1 90.000 (87.612) Prec@5 99.000 (99.286) +2022-11-14 16:47:00,787 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0758) Prec@1 84.000 (87.540) Prec@5 100.000 (99.300) +2022-11-14 16:47:00,795 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0758) Prec@1 89.000 (87.569) Prec@5 99.000 (99.294) +2022-11-14 16:47:00,802 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0761) Prec@1 85.000 (87.519) Prec@5 98.000 (99.269) +2022-11-14 16:47:00,810 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0760) Prec@1 87.000 (87.509) Prec@5 100.000 (99.283) +2022-11-14 16:47:00,818 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0761) Prec@1 88.000 (87.519) Prec@5 98.000 (99.259) +2022-11-14 16:47:00,826 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0765) Prec@1 84.000 (87.455) Prec@5 98.000 (99.236) +2022-11-14 16:47:00,833 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0764) Prec@1 90.000 (87.500) Prec@5 99.000 (99.232) +2022-11-14 16:47:00,841 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0561 (0.0760) Prec@1 90.000 (87.544) Prec@5 99.000 (99.228) +2022-11-14 16:47:00,850 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0759) Prec@1 91.000 (87.603) Prec@5 100.000 (99.241) +2022-11-14 16:47:00,858 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0760) Prec@1 89.000 (87.627) Prec@5 99.000 (99.237) +2022-11-14 16:47:00,865 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0759) Prec@1 88.000 (87.633) Prec@5 100.000 (99.250) +2022-11-14 16:47:00,873 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0759) Prec@1 89.000 (87.656) Prec@5 99.000 (99.246) +2022-11-14 16:47:00,881 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0755) Prec@1 92.000 (87.726) Prec@5 99.000 (99.242) +2022-11-14 16:47:00,888 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0752) Prec@1 92.000 (87.794) Prec@5 100.000 (99.254) +2022-11-14 16:47:00,896 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0748) Prec@1 92.000 (87.859) Prec@5 100.000 (99.266) +2022-11-14 16:47:00,904 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0752) Prec@1 85.000 (87.815) Prec@5 98.000 (99.246) +2022-11-14 16:47:00,911 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0752) Prec@1 88.000 (87.818) Prec@5 99.000 (99.242) +2022-11-14 16:47:00,919 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0479 (0.0748) Prec@1 90.000 (87.851) Prec@5 100.000 (99.254) +2022-11-14 16:47:00,927 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0746) Prec@1 89.000 (87.868) Prec@5 99.000 (99.250) +2022-11-14 16:47:00,934 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0744) Prec@1 89.000 (87.884) Prec@5 99.000 (99.246) +2022-11-14 16:47:00,942 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0747) Prec@1 85.000 (87.843) Prec@5 97.000 (99.214) +2022-11-14 16:47:00,950 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0751) Prec@1 85.000 (87.803) Prec@5 99.000 (99.211) +2022-11-14 16:47:00,957 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0750) Prec@1 89.000 (87.819) Prec@5 99.000 (99.208) +2022-11-14 16:47:00,965 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0748) Prec@1 92.000 (87.877) Prec@5 99.000 (99.205) +2022-11-14 16:47:00,973 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0745) Prec@1 92.000 (87.932) Prec@5 100.000 (99.216) +2022-11-14 16:47:00,981 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0750) Prec@1 82.000 (87.853) Prec@5 100.000 (99.227) +2022-11-14 16:47:00,988 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0748) Prec@1 89.000 (87.868) Prec@5 98.000 (99.211) +2022-11-14 16:47:00,996 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0747) Prec@1 89.000 (87.883) Prec@5 98.000 (99.195) +2022-11-14 16:47:01,004 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0749) Prec@1 86.000 (87.859) Prec@5 99.000 (99.192) +2022-11-14 16:47:01,011 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0747) Prec@1 89.000 (87.873) Prec@5 100.000 (99.203) +2022-11-14 16:47:01,019 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0748) Prec@1 86.000 (87.850) Prec@5 100.000 (99.213) +2022-11-14 16:47:01,027 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0749) Prec@1 90.000 (87.877) Prec@5 99.000 (99.210) +2022-11-14 16:47:01,035 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0747) Prec@1 90.000 (87.902) Prec@5 99.000 (99.207) +2022-11-14 16:47:01,042 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0748) Prec@1 88.000 (87.904) Prec@5 99.000 (99.205) +2022-11-14 16:47:01,051 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0747) Prec@1 89.000 (87.917) Prec@5 100.000 (99.214) +2022-11-14 16:47:01,059 Test: [84/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0748) Prec@1 85.000 (87.882) Prec@5 100.000 (99.224) +2022-11-14 16:47:01,066 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0751) Prec@1 83.000 (87.826) Prec@5 100.000 (99.233) +2022-11-14 16:47:01,074 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0754) Prec@1 83.000 (87.770) Prec@5 100.000 (99.241) +2022-11-14 16:47:01,084 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0754) Prec@1 89.000 (87.784) Prec@5 99.000 (99.239) +2022-11-14 16:47:01,092 Test: [88/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0754) Prec@1 86.000 (87.764) Prec@5 99.000 (99.236) +2022-11-14 16:47:01,101 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0755) Prec@1 87.000 (87.756) Prec@5 100.000 (99.244) +2022-11-14 16:47:01,109 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0752) Prec@1 91.000 (87.791) Prec@5 100.000 (99.253) +2022-11-14 16:47:01,118 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0749) Prec@1 92.000 (87.837) Prec@5 100.000 (99.261) +2022-11-14 16:47:01,127 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0750) Prec@1 88.000 (87.839) Prec@5 100.000 (99.269) +2022-11-14 16:47:01,135 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0750) Prec@1 89.000 (87.851) Prec@5 99.000 (99.266) +2022-11-14 16:47:01,143 Test: [94/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0750) Prec@1 86.000 (87.832) Prec@5 99.000 (99.263) +2022-11-14 16:47:01,151 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0749) Prec@1 91.000 (87.865) Prec@5 100.000 (99.271) +2022-11-14 16:47:01,159 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0747) Prec@1 93.000 (87.918) Prec@5 99.000 (99.268) +2022-11-14 16:47:01,167 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0749) Prec@1 84.000 (87.878) Prec@5 99.000 (99.265) +2022-11-14 16:47:01,177 Test: [98/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0751) Prec@1 86.000 (87.859) Prec@5 99.000 (99.263) +2022-11-14 16:47:01,184 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0752) Prec@1 88.000 (87.860) Prec@5 100.000 (99.270) +2022-11-14 16:47:01,240 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:47:01,568 Epoch: [382][0/500] Time 0.023 (0.023) Data 0.248 (0.248) Loss 0.0237 (0.0237) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:01,767 Epoch: [382][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0301 (0.0269) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:01,957 Epoch: [382][20/500] Time 0.018 (0.017) Data 0.002 (0.013) Loss 0.0113 (0.0217) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:02,178 Epoch: [382][30/500] Time 0.023 (0.018) Data 0.001 (0.010) Loss 0.0231 (0.0220) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:47:02,462 Epoch: [382][40/500] Time 0.027 (0.020) Data 0.002 (0.008) Loss 0.0528 (0.0282) Prec@1 90.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:47:02,752 Epoch: [382][50/500] Time 0.026 (0.021) Data 0.002 (0.007) Loss 0.0323 (0.0289) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:03,041 Epoch: [382][60/500] Time 0.027 (0.022) Data 0.002 (0.006) Loss 0.0093 (0.0261) Prec@1 99.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 16:47:03,326 Epoch: [382][70/500] Time 0.028 (0.022) Data 0.001 (0.005) Loss 0.0421 (0.0281) Prec@1 93.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:47:03,613 Epoch: [382][80/500] Time 0.027 (0.023) Data 0.002 (0.005) Loss 0.0274 (0.0280) Prec@1 94.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:47:03,894 Epoch: [382][90/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0323 (0.0284) Prec@1 96.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:47:04,179 Epoch: [382][100/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0320 (0.0288) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:04,460 Epoch: [382][110/500] Time 0.027 (0.023) Data 0.001 (0.004) Loss 0.0226 (0.0282) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:04,744 Epoch: [382][120/500] Time 0.028 (0.023) Data 0.002 (0.004) Loss 0.0413 (0.0292) Prec@1 92.000 (94.769) Prec@5 100.000 (100.000) +2022-11-14 16:47:05,034 Epoch: [382][130/500] Time 0.026 (0.024) Data 0.002 (0.004) Loss 0.0238 (0.0289) Prec@1 96.000 (94.857) Prec@5 100.000 (100.000) +2022-11-14 16:47:05,318 Epoch: [382][140/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0238 (0.0285) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:05,599 Epoch: [382][150/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0257 (0.0283) Prec@1 96.000 (95.062) Prec@5 100.000 (100.000) +2022-11-14 16:47:05,883 Epoch: [382][160/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0350 (0.0287) Prec@1 95.000 (95.059) Prec@5 100.000 (100.000) +2022-11-14 16:47:06,168 Epoch: [382][170/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0497 (0.0299) Prec@1 90.000 (94.778) Prec@5 100.000 (100.000) +2022-11-14 16:47:06,457 Epoch: [382][180/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0223 (0.0295) Prec@1 97.000 (94.895) Prec@5 100.000 (100.000) +2022-11-14 16:47:06,741 Epoch: [382][190/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0175 (0.0289) Prec@1 98.000 (95.050) Prec@5 100.000 (100.000) +2022-11-14 16:47:07,024 Epoch: [382][200/500] Time 0.027 (0.024) Data 0.001 (0.003) Loss 0.0375 (0.0293) Prec@1 93.000 (94.952) Prec@5 100.000 (100.000) +2022-11-14 16:47:07,304 Epoch: [382][210/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0229 (0.0290) Prec@1 97.000 (95.045) Prec@5 100.000 (100.000) +2022-11-14 16:47:07,584 Epoch: [382][220/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0239 (0.0288) Prec@1 97.000 (95.130) Prec@5 100.000 (100.000) +2022-11-14 16:47:07,869 Epoch: [382][230/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0289 (0.0288) Prec@1 96.000 (95.167) Prec@5 99.000 (99.958) +2022-11-14 16:47:08,155 Epoch: [382][240/500] Time 0.024 (0.024) Data 0.002 (0.003) Loss 0.0203 (0.0285) Prec@1 96.000 (95.200) Prec@5 100.000 (99.960) +2022-11-14 16:47:08,436 Epoch: [382][250/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0169 (0.0280) Prec@1 98.000 (95.308) Prec@5 100.000 (99.962) +2022-11-14 16:47:08,725 Epoch: [382][260/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0315 (0.0281) Prec@1 94.000 (95.259) Prec@5 100.000 (99.963) +2022-11-14 16:47:09,013 Epoch: [382][270/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0319 (0.0283) Prec@1 96.000 (95.286) Prec@5 100.000 (99.964) +2022-11-14 16:47:09,299 Epoch: [382][280/500] Time 0.024 (0.024) Data 0.002 (0.003) Loss 0.0409 (0.0287) Prec@1 92.000 (95.172) Prec@5 100.000 (99.966) +2022-11-14 16:47:09,587 Epoch: [382][290/500] Time 0.027 (0.024) Data 0.001 (0.003) Loss 0.0235 (0.0285) Prec@1 96.000 (95.200) Prec@5 100.000 (99.967) +2022-11-14 16:47:09,875 Epoch: [382][300/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0230 (0.0284) Prec@1 97.000 (95.258) Prec@5 99.000 (99.935) +2022-11-14 16:47:10,168 Epoch: [382][310/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0135 (0.0279) Prec@1 99.000 (95.375) Prec@5 100.000 (99.938) +2022-11-14 16:47:10,459 Epoch: [382][320/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0247 (0.0278) Prec@1 96.000 (95.394) Prec@5 100.000 (99.939) +2022-11-14 16:47:10,748 Epoch: [382][330/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0415 (0.0282) Prec@1 94.000 (95.353) Prec@5 99.000 (99.912) +2022-11-14 16:47:11,038 Epoch: [382][340/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0160 (0.0279) Prec@1 97.000 (95.400) Prec@5 100.000 (99.914) +2022-11-14 16:47:11,321 Epoch: [382][350/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0261 (0.0278) Prec@1 95.000 (95.389) Prec@5 100.000 (99.917) +2022-11-14 16:47:11,608 Epoch: [382][360/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0161 (0.0275) Prec@1 97.000 (95.432) Prec@5 100.000 (99.919) +2022-11-14 16:47:11,898 Epoch: [382][370/500] Time 0.027 (0.025) Data 0.001 (0.002) Loss 0.0282 (0.0275) Prec@1 94.000 (95.395) Prec@5 100.000 (99.921) +2022-11-14 16:47:12,186 Epoch: [382][380/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0240 (0.0274) Prec@1 96.000 (95.410) Prec@5 99.000 (99.897) +2022-11-14 16:47:12,475 Epoch: [382][390/500] Time 0.028 (0.025) Data 0.001 (0.002) Loss 0.0335 (0.0276) Prec@1 94.000 (95.375) Prec@5 100.000 (99.900) +2022-11-14 16:47:12,757 Epoch: [382][400/500] Time 0.027 (0.025) Data 0.001 (0.002) Loss 0.0473 (0.0281) Prec@1 90.000 (95.244) Prec@5 100.000 (99.902) +2022-11-14 16:47:13,046 Epoch: [382][410/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0466 (0.0285) Prec@1 93.000 (95.190) Prec@5 100.000 (99.905) +2022-11-14 16:47:13,337 Epoch: [382][420/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0193 (0.0283) Prec@1 98.000 (95.256) Prec@5 100.000 (99.907) +2022-11-14 16:47:13,623 Epoch: [382][430/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0351 (0.0284) Prec@1 94.000 (95.227) Prec@5 99.000 (99.886) +2022-11-14 16:47:13,907 Epoch: [382][440/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0366 (0.0286) Prec@1 94.000 (95.200) Prec@5 100.000 (99.889) +2022-11-14 16:47:14,197 Epoch: [382][450/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0365 (0.0288) Prec@1 92.000 (95.130) Prec@5 100.000 (99.891) +2022-11-14 16:47:14,486 Epoch: [382][460/500] Time 0.027 (0.025) Data 0.003 (0.002) Loss 0.0437 (0.0291) Prec@1 94.000 (95.106) Prec@5 100.000 (99.894) +2022-11-14 16:47:14,770 Epoch: [382][470/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0208 (0.0289) Prec@1 96.000 (95.125) Prec@5 100.000 (99.896) +2022-11-14 16:47:15,057 Epoch: [382][480/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0168 (0.0287) Prec@1 96.000 (95.143) Prec@5 100.000 (99.898) +2022-11-14 16:47:15,349 Epoch: [382][490/500] Time 0.027 (0.025) Data 0.001 (0.002) Loss 0.0352 (0.0288) Prec@1 95.000 (95.140) Prec@5 100.000 (99.900) +2022-11-14 16:47:15,612 Epoch: [382][499/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0225 (0.0287) Prec@1 97.000 (95.176) Prec@5 100.000 (99.902) +2022-11-14 16:47:15,917 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0571 (0.0571) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:15,926 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0641) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:15,937 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0847 (0.0710) Prec@1 86.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:47:15,950 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0736 (0.0717) Prec@1 89.000 (88.750) Prec@5 99.000 (99.750) +2022-11-14 16:47:15,957 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0717) Prec@1 88.000 (88.600) Prec@5 100.000 (99.800) +2022-11-14 16:47:15,964 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0517 (0.0683) Prec@1 92.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 16:47:15,974 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0806 (0.0701) Prec@1 89.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 16:47:15,985 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0690) Prec@1 89.000 (89.125) Prec@5 99.000 (99.750) +2022-11-14 16:47:15,992 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0699) Prec@1 90.000 (89.222) Prec@5 99.000 (99.667) +2022-11-14 16:47:15,999 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0708) Prec@1 88.000 (89.100) Prec@5 97.000 (99.400) +2022-11-14 16:47:16,011 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0571 (0.0695) Prec@1 92.000 (89.364) Prec@5 100.000 (99.455) +2022-11-14 16:47:16,021 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0858 (0.0709) Prec@1 87.000 (89.167) Prec@5 100.000 (99.500) +2022-11-14 16:47:16,030 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0622 (0.0702) Prec@1 91.000 (89.308) Prec@5 99.000 (99.462) +2022-11-14 16:47:16,038 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0703) Prec@1 89.000 (89.286) Prec@5 99.000 (99.429) +2022-11-14 16:47:16,048 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0707) Prec@1 85.000 (89.000) Prec@5 100.000 (99.467) +2022-11-14 16:47:16,059 Test: [15/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0709) Prec@1 88.000 (88.938) Prec@5 100.000 (99.500) +2022-11-14 16:47:16,067 Test: [16/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0509 (0.0697) Prec@1 93.000 (89.176) Prec@5 98.000 (99.412) +2022-11-14 16:47:16,075 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0989 (0.0714) Prec@1 86.000 (89.000) Prec@5 99.000 (99.389) +2022-11-14 16:47:16,087 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0887 (0.0723) Prec@1 86.000 (88.842) Prec@5 96.000 (99.211) +2022-11-14 16:47:16,095 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0727) Prec@1 86.000 (88.700) Prec@5 98.000 (99.150) +2022-11-14 16:47:16,104 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0718) Prec@1 91.000 (88.810) Prec@5 100.000 (99.190) +2022-11-14 16:47:16,112 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0727) Prec@1 85.000 (88.636) Prec@5 99.000 (99.182) +2022-11-14 16:47:16,120 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0736) Prec@1 87.000 (88.565) Prec@5 97.000 (99.087) +2022-11-14 16:47:16,130 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0737) Prec@1 88.000 (88.542) Prec@5 99.000 (99.083) +2022-11-14 16:47:16,138 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0742) Prec@1 87.000 (88.480) Prec@5 99.000 (99.080) +2022-11-14 16:47:16,146 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0747) Prec@1 86.000 (88.385) Prec@5 98.000 (99.038) +2022-11-14 16:47:16,154 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0735) Prec@1 94.000 (88.593) Prec@5 100.000 (99.074) +2022-11-14 16:47:16,163 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0725) Prec@1 93.000 (88.750) Prec@5 100.000 (99.107) +2022-11-14 16:47:16,171 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0731) Prec@1 84.000 (88.586) Prec@5 100.000 (99.138) +2022-11-14 16:47:16,180 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0729) Prec@1 89.000 (88.600) Prec@5 99.000 (99.133) +2022-11-14 16:47:16,189 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0730) Prec@1 88.000 (88.581) Prec@5 100.000 (99.161) +2022-11-14 16:47:16,197 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0651 (0.0727) Prec@1 89.000 (88.594) Prec@5 98.000 (99.125) +2022-11-14 16:47:16,206 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0960 (0.0735) Prec@1 84.000 (88.455) Prec@5 100.000 (99.152) +2022-11-14 16:47:16,214 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0742) Prec@1 84.000 (88.324) Prec@5 100.000 (99.176) +2022-11-14 16:47:16,223 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0745) Prec@1 86.000 (88.257) Prec@5 99.000 (99.171) +2022-11-14 16:47:16,232 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0742) Prec@1 90.000 (88.306) Prec@5 100.000 (99.194) +2022-11-14 16:47:16,242 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0743) Prec@1 88.000 (88.297) Prec@5 99.000 (99.189) +2022-11-14 16:47:16,250 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0750) Prec@1 83.000 (88.158) Prec@5 99.000 (99.184) +2022-11-14 16:47:16,259 Test: [38/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0742) Prec@1 94.000 (88.308) Prec@5 99.000 (99.179) +2022-11-14 16:47:16,268 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0739) Prec@1 90.000 (88.350) Prec@5 99.000 (99.175) +2022-11-14 16:47:16,277 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0741) Prec@1 87.000 (88.317) Prec@5 99.000 (99.171) +2022-11-14 16:47:16,286 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0738) Prec@1 89.000 (88.333) Prec@5 100.000 (99.190) +2022-11-14 16:47:16,295 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0734) Prec@1 88.000 (88.326) Prec@5 100.000 (99.209) +2022-11-14 16:47:16,304 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0733) Prec@1 91.000 (88.386) Prec@5 98.000 (99.182) +2022-11-14 16:47:16,313 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0734) Prec@1 86.000 (88.333) Prec@5 99.000 (99.178) +2022-11-14 16:47:16,323 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1085 (0.0741) Prec@1 82.000 (88.196) Prec@5 99.000 (99.174) +2022-11-14 16:47:16,332 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0739) Prec@1 90.000 (88.234) Prec@5 100.000 (99.191) +2022-11-14 16:47:16,341 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0743) Prec@1 85.000 (88.167) Prec@5 100.000 (99.208) +2022-11-14 16:47:16,350 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0739) Prec@1 89.000 (88.184) Prec@5 100.000 (99.224) +2022-11-14 16:47:16,359 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1130 (0.0747) Prec@1 83.000 (88.080) Prec@5 98.000 (99.200) +2022-11-14 16:47:16,368 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0744) Prec@1 91.000 (88.137) Prec@5 100.000 (99.216) +2022-11-14 16:47:16,378 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0742) Prec@1 90.000 (88.173) Prec@5 100.000 (99.231) +2022-11-14 16:47:16,387 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0739) Prec@1 89.000 (88.189) Prec@5 100.000 (99.245) +2022-11-14 16:47:16,396 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0738) Prec@1 89.000 (88.204) Prec@5 99.000 (99.241) +2022-11-14 16:47:16,405 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0742) Prec@1 86.000 (88.164) Prec@5 99.000 (99.236) +2022-11-14 16:47:16,415 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0740) Prec@1 91.000 (88.214) Prec@5 99.000 (99.232) +2022-11-14 16:47:16,424 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0739) Prec@1 88.000 (88.211) Prec@5 100.000 (99.246) +2022-11-14 16:47:16,433 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0740) Prec@1 90.000 (88.241) Prec@5 98.000 (99.224) +2022-11-14 16:47:16,442 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0744) Prec@1 84.000 (88.169) Prec@5 100.000 (99.237) +2022-11-14 16:47:16,451 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0744) Prec@1 88.000 (88.167) Prec@5 99.000 (99.233) +2022-11-14 16:47:16,461 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0747) Prec@1 85.000 (88.115) Prec@5 99.000 (99.230) +2022-11-14 16:47:16,470 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0745) Prec@1 89.000 (88.129) Prec@5 100.000 (99.242) +2022-11-14 16:47:16,479 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0744) Prec@1 92.000 (88.190) Prec@5 100.000 (99.254) +2022-11-14 16:47:16,488 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0743) Prec@1 87.000 (88.172) Prec@5 100.000 (99.266) +2022-11-14 16:47:16,497 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0747) Prec@1 86.000 (88.138) Prec@5 100.000 (99.277) +2022-11-14 16:47:16,507 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0745) Prec@1 87.000 (88.121) Prec@5 99.000 (99.273) +2022-11-14 16:47:16,516 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0337 (0.0739) Prec@1 95.000 (88.224) Prec@5 100.000 (99.284) +2022-11-14 16:47:16,525 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0740) Prec@1 88.000 (88.221) Prec@5 100.000 (99.294) +2022-11-14 16:47:16,534 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0739) Prec@1 86.000 (88.188) Prec@5 99.000 (99.290) +2022-11-14 16:47:16,544 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0744) Prec@1 84.000 (88.129) Prec@5 100.000 (99.300) +2022-11-14 16:47:16,553 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0747) Prec@1 86.000 (88.099) Prec@5 100.000 (99.310) +2022-11-14 16:47:16,563 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0744) Prec@1 91.000 (88.139) Prec@5 99.000 (99.306) +2022-11-14 16:47:16,572 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0742) Prec@1 92.000 (88.192) Prec@5 99.000 (99.301) +2022-11-14 16:47:16,583 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0401 (0.0737) Prec@1 92.000 (88.243) Prec@5 100.000 (99.311) +2022-11-14 16:47:16,592 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.0742) Prec@1 80.000 (88.133) Prec@5 98.000 (99.293) +2022-11-14 16:47:16,601 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0741) Prec@1 89.000 (88.145) Prec@5 99.000 (99.289) +2022-11-14 16:47:16,610 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0742) Prec@1 87.000 (88.130) Prec@5 99.000 (99.286) +2022-11-14 16:47:16,619 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0744) Prec@1 85.000 (88.090) Prec@5 97.000 (99.256) +2022-11-14 16:47:16,628 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0743) Prec@1 88.000 (88.089) Prec@5 99.000 (99.253) +2022-11-14 16:47:16,637 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0742) Prec@1 88.000 (88.088) Prec@5 100.000 (99.263) +2022-11-14 16:47:16,646 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0744) Prec@1 86.000 (88.062) Prec@5 99.000 (99.259) +2022-11-14 16:47:16,656 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0747) Prec@1 85.000 (88.024) Prec@5 100.000 (99.268) +2022-11-14 16:47:16,665 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0749) Prec@1 86.000 (88.000) Prec@5 98.000 (99.253) +2022-11-14 16:47:16,674 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0750) Prec@1 84.000 (87.952) Prec@5 98.000 (99.238) +2022-11-14 16:47:16,683 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1092 (0.0754) Prec@1 82.000 (87.882) Prec@5 98.000 (99.224) +2022-11-14 16:47:16,693 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0756) Prec@1 87.000 (87.872) Prec@5 100.000 (99.233) +2022-11-14 16:47:16,703 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0754) Prec@1 88.000 (87.874) Prec@5 100.000 (99.241) +2022-11-14 16:47:16,712 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 89.000 (87.886) Prec@5 99.000 (99.239) +2022-11-14 16:47:16,721 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0756) Prec@1 86.000 (87.865) Prec@5 99.000 (99.236) +2022-11-14 16:47:16,730 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0754) Prec@1 91.000 (87.900) Prec@5 100.000 (99.244) +2022-11-14 16:47:16,739 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0753) Prec@1 90.000 (87.923) Prec@5 100.000 (99.253) +2022-11-14 16:47:16,748 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0750) Prec@1 92.000 (87.967) Prec@5 99.000 (99.250) +2022-11-14 16:47:16,757 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0753) Prec@1 85.000 (87.935) Prec@5 100.000 (99.258) +2022-11-14 16:47:16,766 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0753) Prec@1 90.000 (87.957) Prec@5 99.000 (99.255) +2022-11-14 16:47:16,775 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0755) Prec@1 86.000 (87.937) Prec@5 99.000 (99.253) +2022-11-14 16:47:16,784 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0754) Prec@1 90.000 (87.958) Prec@5 99.000 (99.250) +2022-11-14 16:47:16,793 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0348 (0.0750) Prec@1 94.000 (88.021) Prec@5 99.000 (99.247) +2022-11-14 16:47:16,802 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0751) Prec@1 85.000 (87.990) Prec@5 100.000 (99.255) +2022-11-14 16:47:16,812 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0753) Prec@1 84.000 (87.949) Prec@5 100.000 (99.263) +2022-11-14 16:47:16,821 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0751) Prec@1 92.000 (87.990) Prec@5 100.000 (99.270) +2022-11-14 16:47:16,877 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:47:17,223 Epoch: [383][0/500] Time 0.023 (0.023) Data 0.264 (0.264) Loss 0.0523 (0.0523) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:47:17,421 Epoch: [383][10/500] Time 0.017 (0.018) Data 0.002 (0.025) Loss 0.0356 (0.0440) Prec@1 94.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 16:47:17,620 Epoch: [383][20/500] Time 0.020 (0.018) Data 0.002 (0.014) Loss 0.0313 (0.0397) Prec@1 93.000 (93.000) Prec@5 100.000 (99.667) +2022-11-14 16:47:17,892 Epoch: [383][30/500] Time 0.029 (0.020) Data 0.002 (0.010) Loss 0.0373 (0.0391) Prec@1 93.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 16:47:18,210 Epoch: [383][40/500] Time 0.029 (0.022) Data 0.002 (0.008) Loss 0.0291 (0.0371) Prec@1 94.000 (93.200) Prec@5 100.000 (99.800) +2022-11-14 16:47:18,530 Epoch: [383][50/500] Time 0.031 (0.023) Data 0.002 (0.007) Loss 0.0212 (0.0345) Prec@1 97.000 (93.833) Prec@5 100.000 (99.833) +2022-11-14 16:47:18,862 Epoch: [383][60/500] Time 0.032 (0.024) Data 0.002 (0.006) Loss 0.0068 (0.0305) Prec@1 99.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:47:19,197 Epoch: [383][70/500] Time 0.031 (0.025) Data 0.002 (0.005) Loss 0.0322 (0.0307) Prec@1 94.000 (94.500) Prec@5 100.000 (99.875) +2022-11-14 16:47:19,515 Epoch: [383][80/500] Time 0.029 (0.025) Data 0.002 (0.005) Loss 0.0383 (0.0316) Prec@1 93.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 16:47:19,835 Epoch: [383][90/500] Time 0.031 (0.026) Data 0.002 (0.005) Loss 0.0150 (0.0299) Prec@1 98.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 16:47:20,161 Epoch: [383][100/500] Time 0.032 (0.026) Data 0.002 (0.004) Loss 0.0203 (0.0290) Prec@1 96.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:47:20,479 Epoch: [383][110/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0458 (0.0304) Prec@1 91.000 (94.500) Prec@5 100.000 (99.917) +2022-11-14 16:47:20,797 Epoch: [383][120/500] Time 0.029 (0.026) Data 0.002 (0.004) Loss 0.0245 (0.0300) Prec@1 96.000 (94.615) Prec@5 100.000 (99.923) +2022-11-14 16:47:21,112 Epoch: [383][130/500] Time 0.032 (0.026) Data 0.002 (0.004) Loss 0.0296 (0.0300) Prec@1 96.000 (94.714) Prec@5 100.000 (99.929) +2022-11-14 16:47:21,427 Epoch: [383][140/500] Time 0.030 (0.026) Data 0.002 (0.004) Loss 0.0275 (0.0298) Prec@1 95.000 (94.733) Prec@5 100.000 (99.933) +2022-11-14 16:47:21,745 Epoch: [383][150/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0477 (0.0309) Prec@1 94.000 (94.688) Prec@5 100.000 (99.938) +2022-11-14 16:47:22,058 Epoch: [383][160/500] Time 0.030 (0.027) Data 0.002 (0.004) Loss 0.0316 (0.0309) Prec@1 95.000 (94.706) Prec@5 100.000 (99.941) +2022-11-14 16:47:22,373 Epoch: [383][170/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0393 (0.0314) Prec@1 95.000 (94.722) Prec@5 100.000 (99.944) +2022-11-14 16:47:22,692 Epoch: [383][180/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0100 (0.0303) Prec@1 99.000 (94.947) Prec@5 100.000 (99.947) +2022-11-14 16:47:23,013 Epoch: [383][190/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0390 (0.0307) Prec@1 94.000 (94.900) Prec@5 100.000 (99.950) +2022-11-14 16:47:23,329 Epoch: [383][200/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0202 (0.0302) Prec@1 98.000 (95.048) Prec@5 99.000 (99.905) +2022-11-14 16:47:23,647 Epoch: [383][210/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0251 (0.0300) Prec@1 95.000 (95.045) Prec@5 100.000 (99.909) +2022-11-14 16:47:23,964 Epoch: [383][220/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0281 (0.0299) Prec@1 95.000 (95.043) Prec@5 100.000 (99.913) +2022-11-14 16:47:24,280 Epoch: [383][230/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0367 (0.0302) Prec@1 94.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 16:47:24,599 Epoch: [383][240/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0184 (0.0297) Prec@1 97.000 (95.080) Prec@5 100.000 (99.920) +2022-11-14 16:47:24,920 Epoch: [383][250/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0254 (0.0296) Prec@1 95.000 (95.077) Prec@5 100.000 (99.923) +2022-11-14 16:47:25,240 Epoch: [383][260/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0235 (0.0293) Prec@1 98.000 (95.185) Prec@5 100.000 (99.926) +2022-11-14 16:47:25,550 Epoch: [383][270/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0229 (0.0291) Prec@1 96.000 (95.214) Prec@5 99.000 (99.893) +2022-11-14 16:47:25,867 Epoch: [383][280/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0284 (0.0291) Prec@1 95.000 (95.207) Prec@5 100.000 (99.897) +2022-11-14 16:47:26,187 Epoch: [383][290/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0367 (0.0293) Prec@1 92.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 16:47:26,501 Epoch: [383][300/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0358 (0.0295) Prec@1 94.000 (95.065) Prec@5 100.000 (99.903) +2022-11-14 16:47:26,815 Epoch: [383][310/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0565 (0.0304) Prec@1 90.000 (94.906) Prec@5 99.000 (99.875) +2022-11-14 16:47:27,135 Epoch: [383][320/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0327 (0.0305) Prec@1 95.000 (94.909) Prec@5 100.000 (99.879) +2022-11-14 16:47:27,450 Epoch: [383][330/500] Time 0.030 (0.027) Data 0.001 (0.003) Loss 0.0296 (0.0304) Prec@1 95.000 (94.912) Prec@5 100.000 (99.882) +2022-11-14 16:47:27,769 Epoch: [383][340/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0445 (0.0308) Prec@1 92.000 (94.829) Prec@5 100.000 (99.886) +2022-11-14 16:47:28,084 Epoch: [383][350/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0187 (0.0305) Prec@1 97.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 16:47:28,388 Epoch: [383][360/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.0328 (0.0306) Prec@1 96.000 (94.919) Prec@5 100.000 (99.892) +2022-11-14 16:47:28,700 Epoch: [383][370/500] Time 0.031 (0.027) Data 0.002 (0.003) Loss 0.0313 (0.0306) Prec@1 95.000 (94.921) Prec@5 100.000 (99.895) +2022-11-14 16:47:29,016 Epoch: [383][380/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0515 (0.0311) Prec@1 91.000 (94.821) Prec@5 100.000 (99.897) +2022-11-14 16:47:29,328 Epoch: [383][390/500] Time 0.028 (0.027) Data 0.002 (0.003) Loss 0.0300 (0.0311) Prec@1 96.000 (94.850) Prec@5 100.000 (99.900) +2022-11-14 16:47:29,638 Epoch: [383][400/500] Time 0.029 (0.027) Data 0.002 (0.003) Loss 0.0307 (0.0311) Prec@1 93.000 (94.805) Prec@5 100.000 (99.902) +2022-11-14 16:47:29,958 Epoch: [383][410/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0226 (0.0309) Prec@1 97.000 (94.857) Prec@5 100.000 (99.905) +2022-11-14 16:47:30,278 Epoch: [383][420/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0281 (0.0308) Prec@1 95.000 (94.860) Prec@5 100.000 (99.907) +2022-11-14 16:47:30,599 Epoch: [383][430/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.0447 (0.0311) Prec@1 91.000 (94.773) Prec@5 99.000 (99.886) +2022-11-14 16:47:30,916 Epoch: [383][440/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.0480 (0.0315) Prec@1 90.000 (94.667) Prec@5 100.000 (99.889) +2022-11-14 16:47:31,234 Epoch: [383][450/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.0154 (0.0311) Prec@1 99.000 (94.761) Prec@5 100.000 (99.891) +2022-11-14 16:47:31,546 Epoch: [383][460/500] Time 0.029 (0.027) Data 0.001 (0.002) Loss 0.0217 (0.0309) Prec@1 96.000 (94.787) Prec@5 100.000 (99.894) +2022-11-14 16:47:31,861 Epoch: [383][470/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0175 (0.0307) Prec@1 97.000 (94.833) Prec@5 100.000 (99.896) +2022-11-14 16:47:32,180 Epoch: [383][480/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.0386 (0.0308) Prec@1 93.000 (94.796) Prec@5 100.000 (99.898) +2022-11-14 16:47:32,489 Epoch: [383][490/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0371 (0.0309) Prec@1 95.000 (94.800) Prec@5 100.000 (99.900) +2022-11-14 16:47:32,773 Epoch: [383][499/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0379 (0.0311) Prec@1 95.000 (94.804) Prec@5 100.000 (99.902) +2022-11-14 16:47:33,066 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0628 (0.0628) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:33,074 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0761 (0.0694) Prec@1 87.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:47:33,085 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0939 (0.0776) Prec@1 85.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:33,097 Test: [3/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0782) Prec@1 84.000 (87.000) Prec@5 99.000 (99.750) +2022-11-14 16:47:33,104 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0694 (0.0764) Prec@1 91.000 (87.800) Prec@5 98.000 (99.400) +2022-11-14 16:47:33,111 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0344 (0.0694) Prec@1 94.000 (88.833) Prec@5 100.000 (99.500) +2022-11-14 16:47:33,121 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0518 (0.0669) Prec@1 93.000 (89.429) Prec@5 99.000 (99.429) +2022-11-14 16:47:33,132 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0676) Prec@1 86.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:47:33,139 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0686) Prec@1 89.000 (89.000) Prec@5 99.000 (99.444) +2022-11-14 16:47:33,147 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0703) Prec@1 86.000 (88.700) Prec@5 99.000 (99.400) +2022-11-14 16:47:33,158 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0691) Prec@1 92.000 (89.000) Prec@5 100.000 (99.455) +2022-11-14 16:47:33,169 Test: [11/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0702) Prec@1 86.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 16:47:33,177 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0427 (0.0680) Prec@1 94.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 16:47:33,184 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0643 (0.0678) Prec@1 91.000 (89.286) Prec@5 100.000 (99.571) +2022-11-14 16:47:33,196 Test: [14/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0693) Prec@1 86.000 (89.067) Prec@5 99.000 (99.533) +2022-11-14 16:47:33,206 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0695) Prec@1 87.000 (88.938) Prec@5 99.000 (99.500) +2022-11-14 16:47:33,214 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0693) Prec@1 91.000 (89.059) Prec@5 99.000 (99.471) +2022-11-14 16:47:33,222 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0713) Prec@1 84.000 (88.778) Prec@5 100.000 (99.500) +2022-11-14 16:47:33,233 Test: [18/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0722) Prec@1 84.000 (88.526) Prec@5 99.000 (99.474) +2022-11-14 16:47:33,243 Test: [19/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0729) Prec@1 87.000 (88.450) Prec@5 97.000 (99.350) +2022-11-14 16:47:33,251 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0726) Prec@1 88.000 (88.429) Prec@5 100.000 (99.381) +2022-11-14 16:47:33,259 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0732) Prec@1 87.000 (88.364) Prec@5 98.000 (99.318) +2022-11-14 16:47:33,270 Test: [22/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0962 (0.0742) Prec@1 86.000 (88.261) Prec@5 98.000 (99.261) +2022-11-14 16:47:33,280 Test: [23/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0748) Prec@1 86.000 (88.167) Prec@5 98.000 (99.208) +2022-11-14 16:47:33,288 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0750) Prec@1 85.000 (88.040) Prec@5 100.000 (99.240) +2022-11-14 16:47:33,296 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0756) Prec@1 86.000 (87.962) Prec@5 98.000 (99.192) +2022-11-14 16:47:33,306 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0751) Prec@1 89.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 16:47:33,316 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0743) Prec@1 92.000 (88.143) Prec@5 99.000 (99.214) +2022-11-14 16:47:33,324 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0745) Prec@1 88.000 (88.138) Prec@5 99.000 (99.207) +2022-11-14 16:47:33,331 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0740) Prec@1 89.000 (88.167) Prec@5 100.000 (99.233) +2022-11-14 16:47:33,342 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0737) Prec@1 90.000 (88.226) Prec@5 100.000 (99.258) +2022-11-14 16:47:33,352 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0738) Prec@1 87.000 (88.188) Prec@5 99.000 (99.250) +2022-11-14 16:47:33,359 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0742) Prec@1 86.000 (88.121) Prec@5 99.000 (99.242) +2022-11-14 16:47:33,367 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0743) Prec@1 86.000 (88.059) Prec@5 100.000 (99.265) +2022-11-14 16:47:33,377 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0748) Prec@1 87.000 (88.029) Prec@5 98.000 (99.229) +2022-11-14 16:47:33,385 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0504 (0.0741) Prec@1 93.000 (88.167) Prec@5 100.000 (99.250) +2022-11-14 16:47:33,393 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0737) Prec@1 89.000 (88.189) Prec@5 99.000 (99.243) +2022-11-14 16:47:33,401 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0745) Prec@1 84.000 (88.079) Prec@5 98.000 (99.211) +2022-11-14 16:47:33,409 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0740) Prec@1 93.000 (88.205) Prec@5 99.000 (99.205) +2022-11-14 16:47:33,416 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0736) Prec@1 91.000 (88.275) Prec@5 100.000 (99.225) +2022-11-14 16:47:33,424 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0741) Prec@1 84.000 (88.171) Prec@5 97.000 (99.171) +2022-11-14 16:47:33,431 Test: [41/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0737) Prec@1 91.000 (88.238) Prec@5 99.000 (99.167) +2022-11-14 16:47:33,439 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0731) Prec@1 92.000 (88.326) Prec@5 100.000 (99.186) +2022-11-14 16:47:33,447 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0730) Prec@1 88.000 (88.318) Prec@5 99.000 (99.182) +2022-11-14 16:47:33,454 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0730) Prec@1 89.000 (88.333) Prec@5 99.000 (99.178) +2022-11-14 16:47:33,462 Test: [45/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0737) Prec@1 83.000 (88.217) Prec@5 99.000 (99.174) +2022-11-14 16:47:33,470 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0736) Prec@1 88.000 (88.213) Prec@5 100.000 (99.191) +2022-11-14 16:47:33,477 Test: [47/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0852 (0.0738) Prec@1 86.000 (88.167) Prec@5 98.000 (99.167) +2022-11-14 16:47:33,485 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0732) Prec@1 92.000 (88.245) Prec@5 100.000 (99.184) +2022-11-14 16:47:33,492 Test: [49/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1130 (0.0740) Prec@1 83.000 (88.140) Prec@5 99.000 (99.180) +2022-11-14 16:47:33,500 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0737) Prec@1 93.000 (88.235) Prec@5 100.000 (99.196) +2022-11-14 16:47:33,509 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0981 (0.0741) Prec@1 84.000 (88.154) Prec@5 98.000 (99.173) +2022-11-14 16:47:33,516 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0741) Prec@1 85.000 (88.094) Prec@5 100.000 (99.189) +2022-11-14 16:47:33,524 Test: [53/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0738) Prec@1 91.000 (88.148) Prec@5 100.000 (99.204) +2022-11-14 16:47:33,532 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0740) Prec@1 87.000 (88.127) Prec@5 99.000 (99.200) +2022-11-14 16:47:33,539 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0738) Prec@1 89.000 (88.143) Prec@5 99.000 (99.196) +2022-11-14 16:47:33,547 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0739) Prec@1 88.000 (88.140) Prec@5 100.000 (99.211) +2022-11-14 16:47:33,554 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0739) Prec@1 90.000 (88.172) Prec@5 99.000 (99.207) +2022-11-14 16:47:33,562 Test: [58/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0743) Prec@1 85.000 (88.119) Prec@5 100.000 (99.220) +2022-11-14 16:47:33,569 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0742) Prec@1 89.000 (88.133) Prec@5 100.000 (99.233) +2022-11-14 16:47:33,577 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0742) Prec@1 90.000 (88.164) Prec@5 100.000 (99.246) +2022-11-14 16:47:33,585 Test: [61/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0741) Prec@1 88.000 (88.161) Prec@5 99.000 (99.242) +2022-11-14 16:47:33,593 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0740) Prec@1 89.000 (88.175) Prec@5 100.000 (99.254) +2022-11-14 16:47:33,600 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0735) Prec@1 92.000 (88.234) Prec@5 100.000 (99.266) +2022-11-14 16:47:33,608 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0737) Prec@1 85.000 (88.185) Prec@5 99.000 (99.262) +2022-11-14 16:47:33,616 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0733) Prec@1 91.000 (88.227) Prec@5 100.000 (99.273) +2022-11-14 16:47:33,623 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0729) Prec@1 92.000 (88.284) Prec@5 100.000 (99.284) +2022-11-14 16:47:33,631 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0729) Prec@1 89.000 (88.294) Prec@5 99.000 (99.279) +2022-11-14 16:47:33,639 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0729) Prec@1 89.000 (88.304) Prec@5 100.000 (99.290) +2022-11-14 16:47:33,646 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0729) Prec@1 88.000 (88.300) Prec@5 100.000 (99.300) +2022-11-14 16:47:33,654 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0732) Prec@1 88.000 (88.296) Prec@5 99.000 (99.296) +2022-11-14 16:47:33,661 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0729) Prec@1 91.000 (88.333) Prec@5 100.000 (99.306) +2022-11-14 16:47:33,669 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0411 (0.0724) Prec@1 94.000 (88.411) Prec@5 100.000 (99.315) +2022-11-14 16:47:33,677 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0723) Prec@1 91.000 (88.446) Prec@5 100.000 (99.324) +2022-11-14 16:47:33,684 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0726) Prec@1 84.000 (88.387) Prec@5 99.000 (99.320) +2022-11-14 16:47:33,692 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0724) Prec@1 90.000 (88.408) Prec@5 100.000 (99.329) +2022-11-14 16:47:33,700 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0726) Prec@1 86.000 (88.377) Prec@5 99.000 (99.325) +2022-11-14 16:47:33,707 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0729) Prec@1 86.000 (88.346) Prec@5 98.000 (99.308) +2022-11-14 16:47:33,715 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0727) Prec@1 92.000 (88.392) Prec@5 100.000 (99.316) +2022-11-14 16:47:33,723 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0726) Prec@1 94.000 (88.463) Prec@5 100.000 (99.325) +2022-11-14 16:47:33,730 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0727) Prec@1 88.000 (88.457) Prec@5 97.000 (99.296) +2022-11-14 16:47:33,738 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0728) Prec@1 88.000 (88.451) Prec@5 100.000 (99.305) +2022-11-14 16:47:33,746 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0728) Prec@1 89.000 (88.458) Prec@5 100.000 (99.313) +2022-11-14 16:47:33,753 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0727) Prec@1 88.000 (88.452) Prec@5 98.000 (99.298) +2022-11-14 16:47:33,761 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0728) Prec@1 87.000 (88.435) Prec@5 100.000 (99.306) +2022-11-14 16:47:33,769 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0730) Prec@1 87.000 (88.419) Prec@5 99.000 (99.302) +2022-11-14 16:47:33,777 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0729) Prec@1 89.000 (88.425) Prec@5 100.000 (99.310) +2022-11-14 16:47:33,784 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0730) Prec@1 87.000 (88.409) Prec@5 97.000 (99.284) +2022-11-14 16:47:33,792 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0731) Prec@1 86.000 (88.382) Prec@5 99.000 (99.281) +2022-11-14 16:47:33,800 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0731) Prec@1 90.000 (88.400) Prec@5 99.000 (99.278) +2022-11-14 16:47:33,807 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0728) Prec@1 92.000 (88.440) Prec@5 100.000 (99.286) +2022-11-14 16:47:33,815 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0727) Prec@1 91.000 (88.467) Prec@5 100.000 (99.293) +2022-11-14 16:47:33,823 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0728) Prec@1 87.000 (88.452) Prec@5 99.000 (99.290) +2022-11-14 16:47:33,830 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0728) Prec@1 87.000 (88.436) Prec@5 100.000 (99.298) +2022-11-14 16:47:33,838 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0729) Prec@1 87.000 (88.421) Prec@5 99.000 (99.295) +2022-11-14 16:47:33,846 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0726) Prec@1 91.000 (88.448) Prec@5 100.000 (99.302) +2022-11-14 16:47:33,853 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0724) Prec@1 92.000 (88.485) Prec@5 98.000 (99.289) +2022-11-14 16:47:33,861 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0726) Prec@1 87.000 (88.469) Prec@5 97.000 (99.265) +2022-11-14 16:47:33,869 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.0729) Prec@1 84.000 (88.424) Prec@5 98.000 (99.253) +2022-11-14 16:47:33,876 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0728) Prec@1 90.000 (88.440) Prec@5 99.000 (99.250) +2022-11-14 16:47:33,930 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:47:34,255 Epoch: [384][0/500] Time 0.021 (0.021) Data 0.248 (0.248) Loss 0.0305 (0.0305) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:34,448 Epoch: [384][10/500] Time 0.017 (0.017) Data 0.002 (0.024) Loss 0.0301 (0.0303) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:34,635 Epoch: [384][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0500 (0.0369) Prec@1 92.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 16:47:34,823 Epoch: [384][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0301 (0.0352) Prec@1 95.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 16:47:35,017 Epoch: [384][40/500] Time 0.018 (0.017) Data 0.002 (0.008) Loss 0.0465 (0.0374) Prec@1 93.000 (93.600) Prec@5 100.000 (100.000) +2022-11-14 16:47:35,225 Epoch: [384][50/500] Time 0.022 (0.017) Data 0.002 (0.006) Loss 0.0351 (0.0371) Prec@1 94.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 16:47:35,425 Epoch: [384][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0334 (0.0365) Prec@1 94.000 (93.714) Prec@5 100.000 (100.000) +2022-11-14 16:47:35,618 Epoch: [384][70/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0189 (0.0343) Prec@1 97.000 (94.125) Prec@5 100.000 (100.000) +2022-11-14 16:47:35,808 Epoch: [384][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0123 (0.0319) Prec@1 99.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:47:36,073 Epoch: [384][90/500] Time 0.029 (0.018) Data 0.001 (0.004) Loss 0.0184 (0.0305) Prec@1 97.000 (94.900) Prec@5 100.000 (100.000) +2022-11-14 16:47:36,385 Epoch: [384][100/500] Time 0.030 (0.019) Data 0.002 (0.004) Loss 0.0460 (0.0319) Prec@1 93.000 (94.727) Prec@5 100.000 (100.000) +2022-11-14 16:47:36,705 Epoch: [384][110/500] Time 0.030 (0.020) Data 0.002 (0.004) Loss 0.0359 (0.0323) Prec@1 93.000 (94.583) Prec@5 99.000 (99.917) +2022-11-14 16:47:37,024 Epoch: [384][120/500] Time 0.031 (0.020) Data 0.002 (0.004) Loss 0.0403 (0.0329) Prec@1 94.000 (94.538) Prec@5 100.000 (99.923) +2022-11-14 16:47:37,341 Epoch: [384][130/500] Time 0.029 (0.021) Data 0.002 (0.004) Loss 0.0371 (0.0332) Prec@1 93.000 (94.429) Prec@5 100.000 (99.929) +2022-11-14 16:47:37,648 Epoch: [384][140/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0190 (0.0322) Prec@1 97.000 (94.600) Prec@5 100.000 (99.933) +2022-11-14 16:47:37,969 Epoch: [384][150/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0160 (0.0312) Prec@1 99.000 (94.875) Prec@5 100.000 (99.938) +2022-11-14 16:47:38,274 Epoch: [384][160/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0239 (0.0308) Prec@1 97.000 (95.000) Prec@5 99.000 (99.882) +2022-11-14 16:47:38,575 Epoch: [384][170/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0337 (0.0310) Prec@1 95.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 16:47:38,895 Epoch: [384][180/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0630 (0.0326) Prec@1 88.000 (94.632) Prec@5 99.000 (99.842) +2022-11-14 16:47:39,210 Epoch: [384][190/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0397 (0.0330) Prec@1 94.000 (94.600) Prec@5 100.000 (99.850) +2022-11-14 16:47:39,516 Epoch: [384][200/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0245 (0.0326) Prec@1 96.000 (94.667) Prec@5 99.000 (99.810) +2022-11-14 16:47:39,824 Epoch: [384][210/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.0865 (0.0350) Prec@1 86.000 (94.273) Prec@5 100.000 (99.818) +2022-11-14 16:47:40,132 Epoch: [384][220/500] Time 0.032 (0.024) Data 0.002 (0.003) Loss 0.0329 (0.0350) Prec@1 95.000 (94.304) Prec@5 99.000 (99.783) +2022-11-14 16:47:40,434 Epoch: [384][230/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0356 (0.0350) Prec@1 94.000 (94.292) Prec@5 100.000 (99.792) +2022-11-14 16:47:40,739 Epoch: [384][240/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0210 (0.0344) Prec@1 96.000 (94.360) Prec@5 100.000 (99.800) +2022-11-14 16:47:41,042 Epoch: [384][250/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0305 (0.0343) Prec@1 95.000 (94.385) Prec@5 100.000 (99.808) +2022-11-14 16:47:41,350 Epoch: [384][260/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0205 (0.0338) Prec@1 97.000 (94.481) Prec@5 100.000 (99.815) +2022-11-14 16:47:41,654 Epoch: [384][270/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0278 (0.0335) Prec@1 95.000 (94.500) Prec@5 100.000 (99.821) +2022-11-14 16:47:41,962 Epoch: [384][280/500] Time 0.029 (0.024) Data 0.001 (0.003) Loss 0.0413 (0.0338) Prec@1 94.000 (94.483) Prec@5 100.000 (99.828) +2022-11-14 16:47:42,270 Epoch: [384][290/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0339 (0.0338) Prec@1 94.000 (94.467) Prec@5 100.000 (99.833) +2022-11-14 16:47:42,580 Epoch: [384][300/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0268 (0.0336) Prec@1 96.000 (94.516) Prec@5 100.000 (99.839) +2022-11-14 16:47:42,884 Epoch: [384][310/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0123 (0.0329) Prec@1 98.000 (94.625) Prec@5 100.000 (99.844) +2022-11-14 16:47:43,192 Epoch: [384][320/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0453 (0.0333) Prec@1 93.000 (94.576) Prec@5 99.000 (99.818) +2022-11-14 16:47:43,501 Epoch: [384][330/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0234 (0.0330) Prec@1 97.000 (94.647) Prec@5 100.000 (99.824) +2022-11-14 16:47:43,803 Epoch: [384][340/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0277 (0.0329) Prec@1 97.000 (94.714) Prec@5 100.000 (99.829) +2022-11-14 16:47:44,112 Epoch: [384][350/500] Time 0.033 (0.025) Data 0.002 (0.002) Loss 0.0354 (0.0329) Prec@1 94.000 (94.694) Prec@5 99.000 (99.806) +2022-11-14 16:47:44,420 Epoch: [384][360/500] Time 0.029 (0.025) Data 0.001 (0.002) Loss 0.0645 (0.0338) Prec@1 89.000 (94.541) Prec@5 100.000 (99.811) +2022-11-14 16:47:44,723 Epoch: [384][370/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0083 (0.0331) Prec@1 100.000 (94.684) Prec@5 100.000 (99.816) +2022-11-14 16:47:45,028 Epoch: [384][380/500] Time 0.029 (0.025) Data 0.001 (0.002) Loss 0.0392 (0.0333) Prec@1 92.000 (94.615) Prec@5 100.000 (99.821) +2022-11-14 16:47:45,331 Epoch: [384][390/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0230 (0.0330) Prec@1 96.000 (94.650) Prec@5 100.000 (99.825) +2022-11-14 16:47:45,639 Epoch: [384][400/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0364 (0.0331) Prec@1 95.000 (94.659) Prec@5 100.000 (99.829) +2022-11-14 16:47:45,947 Epoch: [384][410/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0329 (0.0331) Prec@1 94.000 (94.643) Prec@5 100.000 (99.833) +2022-11-14 16:47:46,258 Epoch: [384][420/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0322 (0.0331) Prec@1 95.000 (94.651) Prec@5 100.000 (99.837) +2022-11-14 16:47:46,567 Epoch: [384][430/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0441 (0.0333) Prec@1 94.000 (94.636) Prec@5 99.000 (99.818) +2022-11-14 16:47:46,876 Epoch: [384][440/500] Time 0.029 (0.025) Data 0.001 (0.002) Loss 0.0294 (0.0332) Prec@1 95.000 (94.644) Prec@5 100.000 (99.822) +2022-11-14 16:47:47,188 Epoch: [384][450/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0271 (0.0331) Prec@1 95.000 (94.652) Prec@5 100.000 (99.826) +2022-11-14 16:47:47,493 Epoch: [384][460/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0294 (0.0330) Prec@1 95.000 (94.660) Prec@5 100.000 (99.830) +2022-11-14 16:47:47,797 Epoch: [384][470/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0502 (0.0334) Prec@1 94.000 (94.646) Prec@5 100.000 (99.833) +2022-11-14 16:47:48,107 Epoch: [384][480/500] Time 0.029 (0.025) Data 0.001 (0.002) Loss 0.0346 (0.0334) Prec@1 95.000 (94.653) Prec@5 100.000 (99.837) +2022-11-14 16:47:48,413 Epoch: [384][490/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0447 (0.0336) Prec@1 92.000 (94.600) Prec@5 100.000 (99.840) +2022-11-14 16:47:48,689 Epoch: [384][499/500] Time 0.032 (0.026) Data 0.001 (0.002) Loss 0.0276 (0.0335) Prec@1 97.000 (94.647) Prec@5 99.000 (99.824) +2022-11-14 16:47:48,996 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0647 (0.0647) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:49,005 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0564 (0.0605) Prec@1 93.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:49,014 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0692 (0.0634) Prec@1 90.000 (90.667) Prec@5 98.000 (99.333) +2022-11-14 16:47:49,024 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0656) Prec@1 88.000 (90.000) Prec@5 99.000 (99.250) +2022-11-14 16:47:49,031 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0691) Prec@1 86.000 (89.200) Prec@5 100.000 (99.400) +2022-11-14 16:47:49,038 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0646) Prec@1 92.000 (89.667) Prec@5 100.000 (99.500) +2022-11-14 16:47:49,045 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0643) Prec@1 90.000 (89.714) Prec@5 99.000 (99.429) +2022-11-14 16:47:49,054 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0659) Prec@1 86.000 (89.250) Prec@5 100.000 (99.500) +2022-11-14 16:47:49,061 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0663) Prec@1 90.000 (89.333) Prec@5 100.000 (99.556) +2022-11-14 16:47:49,068 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0891 (0.0686) Prec@1 88.000 (89.200) Prec@5 99.000 (99.500) +2022-11-14 16:47:49,076 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0683) Prec@1 88.000 (89.091) Prec@5 100.000 (99.545) +2022-11-14 16:47:49,085 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0700) Prec@1 87.000 (88.917) Prec@5 100.000 (99.583) +2022-11-14 16:47:49,093 Test: [12/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0692) Prec@1 91.000 (89.077) Prec@5 100.000 (99.615) +2022-11-14 16:47:49,103 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0698) Prec@1 87.000 (88.929) Prec@5 99.000 (99.571) +2022-11-14 16:47:49,111 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0696) Prec@1 90.000 (89.000) Prec@5 99.000 (99.533) +2022-11-14 16:47:49,120 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0695) Prec@1 89.000 (89.000) Prec@5 100.000 (99.562) +2022-11-14 16:47:49,128 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0691) Prec@1 91.000 (89.118) Prec@5 98.000 (99.471) +2022-11-14 16:47:49,137 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1085 (0.0713) Prec@1 84.000 (88.833) Prec@5 99.000 (99.444) +2022-11-14 16:47:49,144 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0733) Prec@1 82.000 (88.474) Prec@5 99.000 (99.421) +2022-11-14 16:47:49,152 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0733) Prec@1 86.000 (88.350) Prec@5 99.000 (99.400) +2022-11-14 16:47:49,161 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0739) Prec@1 86.000 (88.238) Prec@5 100.000 (99.429) +2022-11-14 16:47:49,169 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0740) Prec@1 87.000 (88.182) Prec@5 99.000 (99.409) +2022-11-14 16:47:49,176 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0742) Prec@1 87.000 (88.130) Prec@5 100.000 (99.435) +2022-11-14 16:47:49,184 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0744) Prec@1 85.000 (88.000) Prec@5 100.000 (99.458) +2022-11-14 16:47:49,192 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0745) Prec@1 90.000 (88.080) Prec@5 100.000 (99.480) +2022-11-14 16:47:49,199 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0750) Prec@1 87.000 (88.038) Prec@5 99.000 (99.462) +2022-11-14 16:47:49,207 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0744) Prec@1 91.000 (88.148) Prec@5 100.000 (99.481) +2022-11-14 16:47:49,215 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0737) Prec@1 92.000 (88.286) Prec@5 100.000 (99.500) +2022-11-14 16:47:49,222 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0736) Prec@1 88.000 (88.276) Prec@5 99.000 (99.483) +2022-11-14 16:47:49,230 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0739) Prec@1 88.000 (88.267) Prec@5 98.000 (99.433) +2022-11-14 16:47:49,238 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0738) Prec@1 91.000 (88.355) Prec@5 100.000 (99.452) +2022-11-14 16:47:49,245 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0734) Prec@1 91.000 (88.438) Prec@5 100.000 (99.469) +2022-11-14 16:47:49,253 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0734) Prec@1 85.000 (88.333) Prec@5 100.000 (99.485) +2022-11-14 16:47:49,261 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0737) Prec@1 87.000 (88.294) Prec@5 99.000 (99.471) +2022-11-14 16:47:49,268 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0742) Prec@1 86.000 (88.229) Prec@5 98.000 (99.429) +2022-11-14 16:47:49,276 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0736) Prec@1 93.000 (88.361) Prec@5 100.000 (99.444) +2022-11-14 16:47:49,283 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0734) Prec@1 89.000 (88.378) Prec@5 98.000 (99.405) +2022-11-14 16:47:49,291 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0736) Prec@1 88.000 (88.368) Prec@5 99.000 (99.395) +2022-11-14 16:47:49,298 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0732) Prec@1 92.000 (88.462) Prec@5 99.000 (99.385) +2022-11-14 16:47:49,306 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0731) Prec@1 89.000 (88.475) Prec@5 98.000 (99.350) +2022-11-14 16:47:49,313 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0735) Prec@1 84.000 (88.366) Prec@5 98.000 (99.317) +2022-11-14 16:47:49,320 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0734) Prec@1 90.000 (88.405) Prec@5 99.000 (99.310) +2022-11-14 16:47:49,328 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0729) Prec@1 92.000 (88.488) Prec@5 99.000 (99.302) +2022-11-14 16:47:49,336 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0731) Prec@1 86.000 (88.432) Prec@5 99.000 (99.295) +2022-11-14 16:47:49,343 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0728) Prec@1 91.000 (88.489) Prec@5 99.000 (99.289) +2022-11-14 16:47:49,351 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0731) Prec@1 85.000 (88.413) Prec@5 100.000 (99.304) +2022-11-14 16:47:49,358 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0731) Prec@1 90.000 (88.447) Prec@5 100.000 (99.319) +2022-11-14 16:47:49,366 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0732) Prec@1 87.000 (88.417) Prec@5 100.000 (99.333) +2022-11-14 16:47:49,373 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0729) Prec@1 91.000 (88.469) Prec@5 100.000 (99.347) +2022-11-14 16:47:49,381 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0732) Prec@1 87.000 (88.440) Prec@5 100.000 (99.360) +2022-11-14 16:47:49,389 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0727) Prec@1 91.000 (88.490) Prec@5 100.000 (99.373) +2022-11-14 16:47:49,397 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0728) Prec@1 88.000 (88.481) Prec@5 98.000 (99.346) +2022-11-14 16:47:49,404 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0732) Prec@1 85.000 (88.415) Prec@5 100.000 (99.358) +2022-11-14 16:47:49,412 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0731) Prec@1 89.000 (88.426) Prec@5 100.000 (99.370) +2022-11-14 16:47:49,419 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0734) Prec@1 85.000 (88.364) Prec@5 100.000 (99.382) +2022-11-14 16:47:49,427 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0737) Prec@1 87.000 (88.339) Prec@5 97.000 (99.339) +2022-11-14 16:47:49,435 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0735) Prec@1 90.000 (88.368) Prec@5 99.000 (99.333) +2022-11-14 16:47:49,443 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0732) Prec@1 91.000 (88.414) Prec@5 99.000 (99.328) +2022-11-14 16:47:49,450 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0737) Prec@1 86.000 (88.373) Prec@5 100.000 (99.339) +2022-11-14 16:47:49,458 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0736) Prec@1 88.000 (88.367) Prec@5 100.000 (99.350) +2022-11-14 16:47:49,466 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0735) Prec@1 90.000 (88.393) Prec@5 100.000 (99.361) +2022-11-14 16:47:49,474 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0734) Prec@1 91.000 (88.435) Prec@5 99.000 (99.355) +2022-11-14 16:47:49,481 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0733) Prec@1 87.000 (88.413) Prec@5 99.000 (99.349) +2022-11-14 16:47:49,489 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0728) Prec@1 94.000 (88.500) Prec@5 100.000 (99.359) +2022-11-14 16:47:49,497 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0730) Prec@1 85.000 (88.446) Prec@5 99.000 (99.354) +2022-11-14 16:47:49,505 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0730) Prec@1 89.000 (88.455) Prec@5 99.000 (99.348) +2022-11-14 16:47:49,512 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0724) Prec@1 93.000 (88.522) Prec@5 99.000 (99.343) +2022-11-14 16:47:49,521 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0724) Prec@1 91.000 (88.559) Prec@5 98.000 (99.324) +2022-11-14 16:47:49,528 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0721) Prec@1 89.000 (88.565) Prec@5 100.000 (99.333) +2022-11-14 16:47:49,536 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0725) Prec@1 85.000 (88.514) Prec@5 99.000 (99.329) +2022-11-14 16:47:49,544 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.0730) Prec@1 83.000 (88.437) Prec@5 99.000 (99.324) +2022-11-14 16:47:49,552 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0728) Prec@1 89.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 16:47:49,560 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0724) Prec@1 95.000 (88.534) Prec@5 100.000 (99.342) +2022-11-14 16:47:49,567 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0386 (0.0720) Prec@1 94.000 (88.608) Prec@5 100.000 (99.351) +2022-11-14 16:47:49,575 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0723) Prec@1 86.000 (88.573) Prec@5 99.000 (99.347) +2022-11-14 16:47:49,583 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0723) Prec@1 90.000 (88.592) Prec@5 100.000 (99.355) +2022-11-14 16:47:49,591 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0721) Prec@1 90.000 (88.610) Prec@5 100.000 (99.364) +2022-11-14 16:47:49,598 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0723) Prec@1 85.000 (88.564) Prec@5 99.000 (99.359) +2022-11-14 16:47:49,606 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0727) Prec@1 84.000 (88.506) Prec@5 99.000 (99.354) +2022-11-14 16:47:49,615 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0729) Prec@1 87.000 (88.487) Prec@5 99.000 (99.350) +2022-11-14 16:47:49,622 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0729) Prec@1 88.000 (88.481) Prec@5 98.000 (99.333) +2022-11-14 16:47:49,630 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.0733) Prec@1 81.000 (88.390) Prec@5 100.000 (99.341) +2022-11-14 16:47:49,638 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0734) Prec@1 86.000 (88.361) Prec@5 100.000 (99.349) +2022-11-14 16:47:49,645 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0733) Prec@1 89.000 (88.369) Prec@5 99.000 (99.345) +2022-11-14 16:47:49,653 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0734) Prec@1 86.000 (88.341) Prec@5 100.000 (99.353) +2022-11-14 16:47:49,661 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1301 (0.0741) Prec@1 80.000 (88.244) Prec@5 98.000 (99.337) +2022-11-14 16:47:49,668 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0741) Prec@1 90.000 (88.264) Prec@5 99.000 (99.333) +2022-11-14 16:47:49,676 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0740) Prec@1 91.000 (88.295) Prec@5 99.000 (99.330) +2022-11-14 16:47:49,684 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0741) Prec@1 87.000 (88.281) Prec@5 99.000 (99.326) +2022-11-14 16:47:49,692 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0740) Prec@1 89.000 (88.289) Prec@5 100.000 (99.333) +2022-11-14 16:47:49,699 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0350 (0.0736) Prec@1 93.000 (88.341) Prec@5 100.000 (99.341) +2022-11-14 16:47:49,707 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0733) Prec@1 92.000 (88.380) Prec@5 100.000 (99.348) +2022-11-14 16:47:49,715 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0733) Prec@1 88.000 (88.376) Prec@5 100.000 (99.355) +2022-11-14 16:47:49,723 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0735) Prec@1 87.000 (88.362) Prec@5 99.000 (99.351) +2022-11-14 16:47:49,730 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0735) Prec@1 88.000 (88.358) Prec@5 99.000 (99.347) +2022-11-14 16:47:49,737 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0733) Prec@1 94.000 (88.417) Prec@5 99.000 (99.344) +2022-11-14 16:47:49,745 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0733) Prec@1 87.000 (88.402) Prec@5 98.000 (99.330) +2022-11-14 16:47:49,752 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0735) Prec@1 85.000 (88.367) Prec@5 99.000 (99.327) +2022-11-14 16:47:49,760 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0737) Prec@1 84.000 (88.323) Prec@5 98.000 (99.313) +2022-11-14 16:47:49,767 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0736) Prec@1 88.000 (88.320) Prec@5 100.000 (99.320) +2022-11-14 16:47:49,832 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:47:50,147 Epoch: [385][0/500] Time 0.022 (0.022) Data 0.237 (0.237) Loss 0.0405 (0.0405) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:47:50,344 Epoch: [385][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0365 (0.0385) Prec@1 94.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 16:47:50,538 Epoch: [385][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0233 (0.0334) Prec@1 97.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:47:50,736 Epoch: [385][30/500] Time 0.018 (0.017) Data 0.002 (0.009) Loss 0.0279 (0.0320) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:47:50,942 Epoch: [385][40/500] Time 0.022 (0.018) Data 0.002 (0.007) Loss 0.0330 (0.0322) Prec@1 96.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 16:47:51,153 Epoch: [385][50/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0206 (0.0303) Prec@1 97.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 16:47:51,357 Epoch: [385][60/500] Time 0.022 (0.018) Data 0.002 (0.006) Loss 0.0605 (0.0346) Prec@1 88.000 (94.143) Prec@5 100.000 (100.000) +2022-11-14 16:47:51,563 Epoch: [385][70/500] Time 0.018 (0.018) Data 0.002 (0.005) Loss 0.0353 (0.0347) Prec@1 95.000 (94.250) Prec@5 99.000 (99.875) +2022-11-14 16:47:51,773 Epoch: [385][80/500] Time 0.022 (0.018) Data 0.002 (0.005) Loss 0.0311 (0.0343) Prec@1 95.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 16:47:51,975 Epoch: [385][90/500] Time 0.018 (0.018) Data 0.002 (0.004) Loss 0.0186 (0.0327) Prec@1 95.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 16:47:52,186 Epoch: [385][100/500] Time 0.022 (0.018) Data 0.002 (0.004) Loss 0.0299 (0.0325) Prec@1 96.000 (94.545) Prec@5 100.000 (99.909) +2022-11-14 16:47:52,378 Epoch: [385][110/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0300 (0.0323) Prec@1 94.000 (94.500) Prec@5 100.000 (99.917) +2022-11-14 16:47:52,613 Epoch: [385][120/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0209 (0.0314) Prec@1 96.000 (94.615) Prec@5 100.000 (99.923) +2022-11-14 16:47:52,902 Epoch: [385][130/500] Time 0.027 (0.019) Data 0.002 (0.004) Loss 0.0225 (0.0307) Prec@1 97.000 (94.786) Prec@5 100.000 (99.929) +2022-11-14 16:47:53,195 Epoch: [385][140/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0365 (0.0311) Prec@1 93.000 (94.667) Prec@5 100.000 (99.933) +2022-11-14 16:47:53,489 Epoch: [385][150/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0145 (0.0301) Prec@1 99.000 (94.938) Prec@5 100.000 (99.938) +2022-11-14 16:47:53,782 Epoch: [385][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0505 (0.0313) Prec@1 93.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 16:47:54,078 Epoch: [385][170/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0239 (0.0309) Prec@1 96.000 (94.889) Prec@5 100.000 (99.944) +2022-11-14 16:47:54,376 Epoch: [385][180/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0236 (0.0305) Prec@1 96.000 (94.947) Prec@5 100.000 (99.947) +2022-11-14 16:47:54,675 Epoch: [385][190/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0185 (0.0299) Prec@1 97.000 (95.050) Prec@5 100.000 (99.950) +2022-11-14 16:47:54,966 Epoch: [385][200/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0364 (0.0302) Prec@1 94.000 (95.000) Prec@5 100.000 (99.952) +2022-11-14 16:47:55,262 Epoch: [385][210/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0203 (0.0298) Prec@1 97.000 (95.091) Prec@5 100.000 (99.955) +2022-11-14 16:47:55,550 Epoch: [385][220/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0439 (0.0304) Prec@1 92.000 (94.957) Prec@5 100.000 (99.957) +2022-11-14 16:47:55,837 Epoch: [385][230/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0295 (0.0303) Prec@1 96.000 (95.000) Prec@5 100.000 (99.958) +2022-11-14 16:47:56,136 Epoch: [385][240/500] Time 0.034 (0.022) Data 0.002 (0.003) Loss 0.0404 (0.0307) Prec@1 94.000 (94.960) Prec@5 100.000 (99.960) +2022-11-14 16:47:56,423 Epoch: [385][250/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0295 (0.0307) Prec@1 95.000 (94.962) Prec@5 100.000 (99.962) +2022-11-14 16:47:56,717 Epoch: [385][260/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0464 (0.0313) Prec@1 94.000 (94.926) Prec@5 98.000 (99.889) +2022-11-14 16:47:57,011 Epoch: [385][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0281 (0.0312) Prec@1 95.000 (94.929) Prec@5 100.000 (99.893) +2022-11-14 16:47:57,307 Epoch: [385][280/500] Time 0.031 (0.023) Data 0.001 (0.003) Loss 0.0388 (0.0314) Prec@1 94.000 (94.897) Prec@5 100.000 (99.897) +2022-11-14 16:47:57,593 Epoch: [385][290/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0428 (0.0318) Prec@1 92.000 (94.800) Prec@5 100.000 (99.900) +2022-11-14 16:47:57,878 Epoch: [385][300/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0473 (0.0323) Prec@1 93.000 (94.742) Prec@5 99.000 (99.871) +2022-11-14 16:47:58,167 Epoch: [385][310/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0239 (0.0320) Prec@1 96.000 (94.781) Prec@5 100.000 (99.875) +2022-11-14 16:47:58,457 Epoch: [385][320/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0329 (0.0321) Prec@1 95.000 (94.788) Prec@5 99.000 (99.848) +2022-11-14 16:47:58,744 Epoch: [385][330/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0398 (0.0323) Prec@1 94.000 (94.765) Prec@5 100.000 (99.853) +2022-11-14 16:47:59,030 Epoch: [385][340/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0181 (0.0319) Prec@1 96.000 (94.800) Prec@5 100.000 (99.857) +2022-11-14 16:47:59,319 Epoch: [385][350/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0263 (0.0317) Prec@1 95.000 (94.806) Prec@5 100.000 (99.861) +2022-11-14 16:47:59,608 Epoch: [385][360/500] Time 0.032 (0.023) Data 0.002 (0.002) Loss 0.0443 (0.0321) Prec@1 94.000 (94.784) Prec@5 99.000 (99.838) +2022-11-14 16:47:59,891 Epoch: [385][370/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0251 (0.0319) Prec@1 95.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 16:48:00,179 Epoch: [385][380/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0310 (0.0319) Prec@1 94.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 16:48:00,463 Epoch: [385][390/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0319 (0.0319) Prec@1 95.000 (94.775) Prec@5 100.000 (99.850) +2022-11-14 16:48:00,749 Epoch: [385][400/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0221 (0.0316) Prec@1 97.000 (94.829) Prec@5 100.000 (99.854) +2022-11-14 16:48:01,032 Epoch: [385][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0447 (0.0319) Prec@1 93.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 16:48:01,322 Epoch: [385][420/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0239 (0.0318) Prec@1 96.000 (94.814) Prec@5 100.000 (99.860) +2022-11-14 16:48:01,609 Epoch: [385][430/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0413 (0.0320) Prec@1 93.000 (94.773) Prec@5 99.000 (99.841) +2022-11-14 16:48:01,898 Epoch: [385][440/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0270 (0.0319) Prec@1 94.000 (94.756) Prec@5 100.000 (99.844) +2022-11-14 16:48:02,184 Epoch: [385][450/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0175 (0.0316) Prec@1 97.000 (94.804) Prec@5 100.000 (99.848) +2022-11-14 16:48:02,472 Epoch: [385][460/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0336 (0.0316) Prec@1 94.000 (94.787) Prec@5 100.000 (99.851) +2022-11-14 16:48:02,757 Epoch: [385][470/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0204 (0.0314) Prec@1 97.000 (94.833) Prec@5 100.000 (99.854) +2022-11-14 16:48:03,042 Epoch: [385][480/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0255 (0.0312) Prec@1 96.000 (94.857) Prec@5 99.000 (99.837) +2022-11-14 16:48:03,325 Epoch: [385][490/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0252 (0.0311) Prec@1 96.000 (94.880) Prec@5 100.000 (99.840) +2022-11-14 16:48:03,582 Epoch: [385][499/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0268 (0.0310) Prec@1 96.000 (94.902) Prec@5 99.000 (99.824) +2022-11-14 16:48:03,885 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0595 (0.0595) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:03,895 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0730 (0.0662) Prec@1 89.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:03,905 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0671 (0.0665) Prec@1 90.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 16:48:03,915 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0741 (0.0684) Prec@1 88.000 (89.750) Prec@5 98.000 (99.500) +2022-11-14 16:48:03,922 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0788 (0.0705) Prec@1 87.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 16:48:03,931 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0468 (0.0665) Prec@1 92.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:48:03,941 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0663) Prec@1 91.000 (89.857) Prec@5 99.000 (99.571) +2022-11-14 16:48:03,949 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0677) Prec@1 85.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 16:48:03,956 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0881 (0.0700) Prec@1 88.000 (89.111) Prec@5 99.000 (99.444) +2022-11-14 16:48:03,967 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0698) Prec@1 89.000 (89.100) Prec@5 99.000 (99.400) +2022-11-14 16:48:03,978 Test: [10/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0609 (0.0690) Prec@1 91.000 (89.273) Prec@5 100.000 (99.455) +2022-11-14 16:48:03,986 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0928 (0.0709) Prec@1 88.000 (89.167) Prec@5 99.000 (99.417) +2022-11-14 16:48:03,993 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0701) Prec@1 91.000 (89.308) Prec@5 99.000 (99.385) +2022-11-14 16:48:04,004 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0703) Prec@1 89.000 (89.286) Prec@5 99.000 (99.357) +2022-11-14 16:48:04,015 Test: [14/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0902 (0.0716) Prec@1 86.000 (89.067) Prec@5 99.000 (99.333) +2022-11-14 16:48:04,022 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0693 (0.0715) Prec@1 89.000 (89.062) Prec@5 100.000 (99.375) +2022-11-14 16:48:04,030 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0704) Prec@1 92.000 (89.235) Prec@5 98.000 (99.294) +2022-11-14 16:48:04,040 Test: [17/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.1113 (0.0727) Prec@1 84.000 (88.944) Prec@5 100.000 (99.333) +2022-11-14 16:48:04,051 Test: [18/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0583 (0.0719) Prec@1 89.000 (88.947) Prec@5 98.000 (99.263) +2022-11-14 16:48:04,059 Test: [19/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0932 (0.0730) Prec@1 85.000 (88.750) Prec@5 98.000 (99.200) +2022-11-14 16:48:04,067 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0731) Prec@1 87.000 (88.667) Prec@5 99.000 (99.190) +2022-11-14 16:48:04,075 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0739) Prec@1 85.000 (88.500) Prec@5 98.000 (99.136) +2022-11-14 16:48:04,085 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1058 (0.0753) Prec@1 85.000 (88.348) Prec@5 98.000 (99.087) +2022-11-14 16:48:04,093 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0763) Prec@1 85.000 (88.208) Prec@5 98.000 (99.042) +2022-11-14 16:48:04,100 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0764) Prec@1 89.000 (88.240) Prec@5 100.000 (99.080) +2022-11-14 16:48:04,108 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0768) Prec@1 87.000 (88.192) Prec@5 98.000 (99.038) +2022-11-14 16:48:04,115 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0761) Prec@1 89.000 (88.222) Prec@5 100.000 (99.074) +2022-11-14 16:48:04,123 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0754) Prec@1 93.000 (88.393) Prec@5 99.000 (99.071) +2022-11-14 16:48:04,130 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0753) Prec@1 87.000 (88.345) Prec@5 98.000 (99.034) +2022-11-14 16:48:04,138 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0757) Prec@1 86.000 (88.267) Prec@5 99.000 (99.033) +2022-11-14 16:48:04,145 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0754) Prec@1 88.000 (88.258) Prec@5 100.000 (99.065) +2022-11-14 16:48:04,153 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0755) Prec@1 87.000 (88.219) Prec@5 99.000 (99.062) +2022-11-14 16:48:04,160 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0756) Prec@1 86.000 (88.152) Prec@5 100.000 (99.091) +2022-11-14 16:48:04,168 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0757) Prec@1 87.000 (88.118) Prec@5 99.000 (99.088) +2022-11-14 16:48:04,175 Test: [34/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0757) Prec@1 89.000 (88.143) Prec@5 98.000 (99.057) +2022-11-14 16:48:04,183 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0757) Prec@1 91.000 (88.222) Prec@5 99.000 (99.056) +2022-11-14 16:48:04,191 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0754) Prec@1 88.000 (88.216) Prec@5 99.000 (99.054) +2022-11-14 16:48:04,198 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.0763) Prec@1 83.000 (88.079) Prec@5 97.000 (99.000) +2022-11-14 16:48:04,206 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0758) Prec@1 94.000 (88.231) Prec@5 99.000 (99.000) +2022-11-14 16:48:04,214 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0756) Prec@1 90.000 (88.275) Prec@5 98.000 (98.975) +2022-11-14 16:48:04,221 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0758) Prec@1 89.000 (88.293) Prec@5 98.000 (98.951) +2022-11-14 16:48:04,229 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0757) Prec@1 86.000 (88.238) Prec@5 99.000 (98.952) +2022-11-14 16:48:04,237 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0750) Prec@1 92.000 (88.326) Prec@5 99.000 (98.953) +2022-11-14 16:48:04,245 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0747) Prec@1 89.000 (88.341) Prec@5 99.000 (98.955) +2022-11-14 16:48:04,252 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0746) Prec@1 87.000 (88.311) Prec@5 100.000 (98.978) +2022-11-14 16:48:04,261 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0749) Prec@1 85.000 (88.239) Prec@5 100.000 (99.000) +2022-11-14 16:48:04,269 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0749) Prec@1 86.000 (88.191) Prec@5 99.000 (99.000) +2022-11-14 16:48:04,276 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0753) Prec@1 84.000 (88.104) Prec@5 99.000 (99.000) +2022-11-14 16:48:04,284 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0749) Prec@1 88.000 (88.102) Prec@5 99.000 (99.000) +2022-11-14 16:48:04,292 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1223 (0.0759) Prec@1 79.000 (87.920) Prec@5 100.000 (99.020) +2022-11-14 16:48:04,299 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0758) Prec@1 88.000 (87.922) Prec@5 98.000 (99.000) +2022-11-14 16:48:04,307 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0757) Prec@1 88.000 (87.923) Prec@5 100.000 (99.019) +2022-11-14 16:48:04,315 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0755) Prec@1 89.000 (87.943) Prec@5 100.000 (99.038) +2022-11-14 16:48:04,323 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0753) Prec@1 91.000 (88.000) Prec@5 98.000 (99.019) +2022-11-14 16:48:04,331 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0759) Prec@1 84.000 (87.927) Prec@5 100.000 (99.036) +2022-11-14 16:48:04,339 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0758) Prec@1 88.000 (87.929) Prec@5 99.000 (99.036) +2022-11-14 16:48:04,346 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0757) Prec@1 86.000 (87.895) Prec@5 99.000 (99.035) +2022-11-14 16:48:04,354 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0754) Prec@1 89.000 (87.914) Prec@5 100.000 (99.052) +2022-11-14 16:48:04,361 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0757) Prec@1 86.000 (87.881) Prec@5 100.000 (99.068) +2022-11-14 16:48:04,369 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0759) Prec@1 86.000 (87.850) Prec@5 100.000 (99.083) +2022-11-14 16:48:04,376 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0760) Prec@1 87.000 (87.836) Prec@5 99.000 (99.082) +2022-11-14 16:48:04,384 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0760) Prec@1 87.000 (87.823) Prec@5 98.000 (99.065) +2022-11-14 16:48:04,391 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0760) Prec@1 90.000 (87.857) Prec@5 100.000 (99.079) +2022-11-14 16:48:04,399 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0756) Prec@1 91.000 (87.906) Prec@5 99.000 (99.078) +2022-11-14 16:48:04,407 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0761) Prec@1 81.000 (87.800) Prec@5 100.000 (99.092) +2022-11-14 16:48:04,415 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0760) Prec@1 89.000 (87.818) Prec@5 100.000 (99.106) +2022-11-14 16:48:04,423 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0285 (0.0753) Prec@1 94.000 (87.910) Prec@5 100.000 (99.119) +2022-11-14 16:48:04,430 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0752) Prec@1 88.000 (87.912) Prec@5 99.000 (99.118) +2022-11-14 16:48:04,438 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0751) Prec@1 90.000 (87.942) Prec@5 98.000 (99.101) +2022-11-14 16:48:04,446 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0754) Prec@1 86.000 (87.914) Prec@5 99.000 (99.100) +2022-11-14 16:48:04,453 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0759) Prec@1 84.000 (87.859) Prec@5 98.000 (99.085) +2022-11-14 16:48:04,461 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0755) Prec@1 90.000 (87.889) Prec@5 100.000 (99.097) +2022-11-14 16:48:04,469 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0432 (0.0750) Prec@1 93.000 (87.959) Prec@5 100.000 (99.110) +2022-11-14 16:48:04,476 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0261 (0.0744) Prec@1 97.000 (88.081) Prec@5 100.000 (99.122) +2022-11-14 16:48:04,484 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1093 (0.0748) Prec@1 82.000 (88.000) Prec@5 100.000 (99.133) +2022-11-14 16:48:04,492 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0747) Prec@1 90.000 (88.026) Prec@5 99.000 (99.132) +2022-11-14 16:48:04,500 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0747) Prec@1 88.000 (88.026) Prec@5 100.000 (99.143) +2022-11-14 16:48:04,508 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0748) Prec@1 89.000 (88.038) Prec@5 99.000 (99.141) +2022-11-14 16:48:04,516 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0748) Prec@1 89.000 (88.051) Prec@5 100.000 (99.152) +2022-11-14 16:48:04,523 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0747) Prec@1 88.000 (88.050) Prec@5 100.000 (99.162) +2022-11-14 16:48:04,531 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0749) Prec@1 86.000 (88.025) Prec@5 99.000 (99.160) +2022-11-14 16:48:04,539 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0751) Prec@1 85.000 (87.988) Prec@5 99.000 (99.159) +2022-11-14 16:48:04,546 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0753) Prec@1 89.000 (88.000) Prec@5 99.000 (99.157) +2022-11-14 16:48:04,554 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0753) Prec@1 87.000 (87.988) Prec@5 99.000 (99.155) +2022-11-14 16:48:04,562 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0758) Prec@1 79.000 (87.882) Prec@5 100.000 (99.165) +2022-11-14 16:48:04,570 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1244 (0.0764) Prec@1 83.000 (87.826) Prec@5 100.000 (99.174) +2022-11-14 16:48:04,577 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0762) Prec@1 92.000 (87.874) Prec@5 100.000 (99.184) +2022-11-14 16:48:04,585 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0760) Prec@1 91.000 (87.909) Prec@5 98.000 (99.170) +2022-11-14 16:48:04,593 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0760) Prec@1 87.000 (87.899) Prec@5 100.000 (99.180) +2022-11-14 16:48:04,600 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0757) Prec@1 92.000 (87.944) Prec@5 100.000 (99.189) +2022-11-14 16:48:04,608 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0756) Prec@1 90.000 (87.967) Prec@5 100.000 (99.198) +2022-11-14 16:48:04,616 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0754) Prec@1 91.000 (88.000) Prec@5 100.000 (99.207) +2022-11-14 16:48:04,624 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0754) Prec@1 87.000 (87.989) Prec@5 98.000 (99.194) +2022-11-14 16:48:04,631 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0754) Prec@1 91.000 (88.021) Prec@5 99.000 (99.191) +2022-11-14 16:48:04,639 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0753) Prec@1 91.000 (88.053) Prec@5 99.000 (99.189) +2022-11-14 16:48:04,646 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0752) Prec@1 88.000 (88.052) Prec@5 100.000 (99.198) +2022-11-14 16:48:04,654 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0750) Prec@1 94.000 (88.113) Prec@5 99.000 (99.196) +2022-11-14 16:48:04,662 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0750) Prec@1 90.000 (88.133) Prec@5 99.000 (99.194) +2022-11-14 16:48:04,669 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.0753) Prec@1 82.000 (88.071) Prec@5 98.000 (99.182) +2022-11-14 16:48:04,677 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0753) Prec@1 90.000 (88.090) Prec@5 100.000 (99.190) +2022-11-14 16:48:04,732 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:48:05,059 Epoch: [386][0/500] Time 0.023 (0.023) Data 0.245 (0.245) Loss 0.0275 (0.0275) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:05,259 Epoch: [386][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0326 (0.0300) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:05,451 Epoch: [386][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0158 (0.0253) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:48:05,641 Epoch: [386][30/500] Time 0.017 (0.017) Data 0.002 (0.010) Loss 0.0314 (0.0268) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:05,835 Epoch: [386][40/500] Time 0.015 (0.017) Data 0.002 (0.008) Loss 0.0159 (0.0246) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:06,030 Epoch: [386][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0398 (0.0272) Prec@1 94.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:48:06,226 Epoch: [386][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0429 (0.0294) Prec@1 94.000 (95.429) Prec@5 99.000 (99.857) +2022-11-14 16:48:06,416 Epoch: [386][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0352 (0.0301) Prec@1 93.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:48:06,613 Epoch: [386][80/500] Time 0.020 (0.017) Data 0.001 (0.005) Loss 0.0111 (0.0280) Prec@1 98.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:48:06,880 Epoch: [386][90/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0334 (0.0286) Prec@1 95.000 (95.400) Prec@5 99.000 (99.800) +2022-11-14 16:48:07,155 Epoch: [386][100/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0358 (0.0292) Prec@1 95.000 (95.364) Prec@5 100.000 (99.818) +2022-11-14 16:48:07,433 Epoch: [386][110/500] Time 0.026 (0.019) Data 0.002 (0.004) Loss 0.0337 (0.0296) Prec@1 93.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:48:07,712 Epoch: [386][120/500] Time 0.025 (0.019) Data 0.002 (0.004) Loss 0.0184 (0.0287) Prec@1 98.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:48:07,993 Epoch: [386][130/500] Time 0.025 (0.020) Data 0.002 (0.004) Loss 0.0205 (0.0282) Prec@1 97.000 (95.500) Prec@5 100.000 (99.857) +2022-11-14 16:48:08,276 Epoch: [386][140/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0536 (0.0299) Prec@1 92.000 (95.267) Prec@5 99.000 (99.800) +2022-11-14 16:48:08,562 Epoch: [386][150/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0401 (0.0305) Prec@1 92.000 (95.062) Prec@5 100.000 (99.812) +2022-11-14 16:48:08,851 Epoch: [386][160/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0402 (0.0311) Prec@1 93.000 (94.941) Prec@5 100.000 (99.824) +2022-11-14 16:48:09,138 Epoch: [386][170/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0206 (0.0305) Prec@1 96.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:48:09,419 Epoch: [386][180/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0423 (0.0311) Prec@1 93.000 (94.895) Prec@5 100.000 (99.842) +2022-11-14 16:48:09,695 Epoch: [386][190/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0218 (0.0306) Prec@1 97.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 16:48:09,979 Epoch: [386][200/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0386 (0.0310) Prec@1 94.000 (94.952) Prec@5 100.000 (99.810) +2022-11-14 16:48:10,256 Epoch: [386][210/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0158 (0.0303) Prec@1 98.000 (95.091) Prec@5 100.000 (99.818) +2022-11-14 16:48:10,528 Epoch: [386][220/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0295 (0.0303) Prec@1 93.000 (95.000) Prec@5 100.000 (99.826) +2022-11-14 16:48:10,802 Epoch: [386][230/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0303 (0.0303) Prec@1 95.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:48:11,076 Epoch: [386][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0607 (0.0315) Prec@1 92.000 (94.880) Prec@5 100.000 (99.840) +2022-11-14 16:48:11,348 Epoch: [386][250/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0227 (0.0312) Prec@1 96.000 (94.923) Prec@5 100.000 (99.846) +2022-11-14 16:48:11,625 Epoch: [386][260/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0518 (0.0319) Prec@1 90.000 (94.741) Prec@5 100.000 (99.852) +2022-11-14 16:48:11,906 Epoch: [386][270/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0296 (0.0319) Prec@1 95.000 (94.750) Prec@5 100.000 (99.857) +2022-11-14 16:48:12,188 Epoch: [386][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0108 (0.0311) Prec@1 99.000 (94.897) Prec@5 100.000 (99.862) +2022-11-14 16:48:12,466 Epoch: [386][290/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0345 (0.0312) Prec@1 95.000 (94.900) Prec@5 100.000 (99.867) +2022-11-14 16:48:12,742 Epoch: [386][300/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0301 (0.0312) Prec@1 95.000 (94.903) Prec@5 100.000 (99.871) +2022-11-14 16:48:13,016 Epoch: [386][310/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0292 (0.0311) Prec@1 94.000 (94.875) Prec@5 99.000 (99.844) +2022-11-14 16:48:13,290 Epoch: [386][320/500] Time 0.024 (0.023) Data 0.003 (0.002) Loss 0.0403 (0.0314) Prec@1 95.000 (94.879) Prec@5 100.000 (99.848) +2022-11-14 16:48:13,563 Epoch: [386][330/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0564 (0.0321) Prec@1 89.000 (94.706) Prec@5 100.000 (99.853) +2022-11-14 16:48:13,835 Epoch: [386][340/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0292 (0.0321) Prec@1 96.000 (94.743) Prec@5 100.000 (99.857) +2022-11-14 16:48:14,109 Epoch: [386][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0323 (0.0321) Prec@1 94.000 (94.722) Prec@5 100.000 (99.861) +2022-11-14 16:48:14,381 Epoch: [386][360/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0230 (0.0318) Prec@1 95.000 (94.730) Prec@5 100.000 (99.865) +2022-11-14 16:48:14,654 Epoch: [386][370/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0178 (0.0315) Prec@1 97.000 (94.789) Prec@5 100.000 (99.868) +2022-11-14 16:48:14,937 Epoch: [386][380/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0166 (0.0311) Prec@1 98.000 (94.872) Prec@5 100.000 (99.872) +2022-11-14 16:48:15,217 Epoch: [386][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0312 (0.0311) Prec@1 95.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 16:48:15,490 Epoch: [386][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0290 (0.0310) Prec@1 96.000 (94.902) Prec@5 100.000 (99.878) +2022-11-14 16:48:15,767 Epoch: [386][410/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0172 (0.0307) Prec@1 98.000 (94.976) Prec@5 100.000 (99.881) +2022-11-14 16:48:16,042 Epoch: [386][420/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0310 (0.0307) Prec@1 95.000 (94.977) Prec@5 100.000 (99.884) +2022-11-14 16:48:16,323 Epoch: [386][430/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0204 (0.0305) Prec@1 96.000 (95.000) Prec@5 100.000 (99.886) +2022-11-14 16:48:16,596 Epoch: [386][440/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0237 (0.0303) Prec@1 97.000 (95.044) Prec@5 100.000 (99.889) +2022-11-14 16:48:16,869 Epoch: [386][450/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0100 (0.0299) Prec@1 98.000 (95.109) Prec@5 100.000 (99.891) +2022-11-14 16:48:17,143 Epoch: [386][460/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0230 (0.0297) Prec@1 95.000 (95.106) Prec@5 100.000 (99.894) +2022-11-14 16:48:17,419 Epoch: [386][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0342 (0.0298) Prec@1 93.000 (95.062) Prec@5 100.000 (99.896) +2022-11-14 16:48:17,693 Epoch: [386][480/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0246 (0.0297) Prec@1 96.000 (95.082) Prec@5 100.000 (99.898) +2022-11-14 16:48:17,972 Epoch: [386][490/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0465 (0.0301) Prec@1 92.000 (95.020) Prec@5 100.000 (99.900) +2022-11-14 16:48:18,219 Epoch: [386][499/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0174 (0.0298) Prec@1 99.000 (95.098) Prec@5 100.000 (99.902) +2022-11-14 16:48:18,517 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0663 (0.0663) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:18,524 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0703) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:18,532 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0526 (0.0644) Prec@1 92.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:18,542 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0661) Prec@1 91.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 16:48:18,549 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0684) Prec@1 88.000 (89.200) Prec@5 99.000 (99.600) +2022-11-14 16:48:18,556 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0449 (0.0644) Prec@1 93.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 16:48:18,563 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0648) Prec@1 91.000 (90.000) Prec@5 99.000 (99.571) +2022-11-14 16:48:18,573 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0651) Prec@1 87.000 (89.625) Prec@5 99.000 (99.500) +2022-11-14 16:48:18,580 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0677) Prec@1 87.000 (89.333) Prec@5 100.000 (99.556) +2022-11-14 16:48:18,587 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0687) Prec@1 88.000 (89.200) Prec@5 98.000 (99.400) +2022-11-14 16:48:18,595 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0673) Prec@1 91.000 (89.364) Prec@5 100.000 (99.455) +2022-11-14 16:48:18,603 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0677) Prec@1 90.000 (89.417) Prec@5 100.000 (99.500) +2022-11-14 16:48:18,611 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0672) Prec@1 87.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 16:48:18,618 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0673) Prec@1 89.000 (89.214) Prec@5 99.000 (99.500) +2022-11-14 16:48:18,626 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0688) Prec@1 85.000 (88.933) Prec@5 98.000 (99.400) +2022-11-14 16:48:18,634 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0688) Prec@1 90.000 (89.000) Prec@5 99.000 (99.375) +2022-11-14 16:48:18,641 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0683) Prec@1 91.000 (89.118) Prec@5 99.000 (99.353) +2022-11-14 16:48:18,649 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1260 (0.0715) Prec@1 82.000 (88.722) Prec@5 99.000 (99.333) +2022-11-14 16:48:18,657 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0718) Prec@1 87.000 (88.632) Prec@5 99.000 (99.316) +2022-11-14 16:48:18,665 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0729) Prec@1 87.000 (88.550) Prec@5 98.000 (99.250) +2022-11-14 16:48:18,673 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0733) Prec@1 85.000 (88.381) Prec@5 100.000 (99.286) +2022-11-14 16:48:18,681 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0741) Prec@1 85.000 (88.227) Prec@5 99.000 (99.273) +2022-11-14 16:48:18,688 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0747) Prec@1 87.000 (88.174) Prec@5 100.000 (99.304) +2022-11-14 16:48:18,696 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0743) Prec@1 89.000 (88.208) Prec@5 99.000 (99.292) +2022-11-14 16:48:18,703 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0752) Prec@1 84.000 (88.040) Prec@5 100.000 (99.320) +2022-11-14 16:48:18,711 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0756) Prec@1 86.000 (87.962) Prec@5 98.000 (99.269) +2022-11-14 16:48:18,719 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0749) Prec@1 89.000 (88.000) Prec@5 99.000 (99.259) +2022-11-14 16:48:18,726 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0403 (0.0737) Prec@1 93.000 (88.179) Prec@5 100.000 (99.286) +2022-11-14 16:48:18,733 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0737) Prec@1 89.000 (88.207) Prec@5 98.000 (99.241) +2022-11-14 16:48:18,741 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0733) Prec@1 86.000 (88.133) Prec@5 100.000 (99.267) +2022-11-14 16:48:18,748 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0729) Prec@1 90.000 (88.194) Prec@5 99.000 (99.258) +2022-11-14 16:48:18,755 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0731) Prec@1 86.000 (88.125) Prec@5 100.000 (99.281) +2022-11-14 16:48:18,763 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0734) Prec@1 85.000 (88.030) Prec@5 100.000 (99.303) +2022-11-14 16:48:18,770 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0889 (0.0738) Prec@1 85.000 (87.941) Prec@5 98.000 (99.265) +2022-11-14 16:48:18,778 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0826 (0.0741) Prec@1 87.000 (87.914) Prec@5 98.000 (99.229) +2022-11-14 16:48:18,785 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0740) Prec@1 90.000 (87.972) Prec@5 99.000 (99.222) +2022-11-14 16:48:18,793 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0605 (0.0736) Prec@1 91.000 (88.054) Prec@5 99.000 (99.216) +2022-11-14 16:48:18,800 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1079 (0.0745) Prec@1 84.000 (87.947) Prec@5 98.000 (99.184) +2022-11-14 16:48:18,807 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0476 (0.0738) Prec@1 95.000 (88.128) Prec@5 99.000 (99.179) +2022-11-14 16:48:18,815 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0715 (0.0738) Prec@1 87.000 (88.100) Prec@5 99.000 (99.175) +2022-11-14 16:48:18,823 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0778 (0.0739) Prec@1 88.000 (88.098) Prec@5 99.000 (99.171) +2022-11-14 16:48:18,830 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0575 (0.0735) Prec@1 91.000 (88.167) Prec@5 99.000 (99.167) +2022-11-14 16:48:18,838 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0389 (0.0727) Prec@1 95.000 (88.326) Prec@5 98.000 (99.140) +2022-11-14 16:48:18,845 Test: [43/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0766 (0.0727) Prec@1 89.000 (88.341) Prec@5 98.000 (99.114) +2022-11-14 16:48:18,853 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0628 (0.0725) Prec@1 90.000 (88.378) Prec@5 99.000 (99.111) +2022-11-14 16:48:18,861 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1017 (0.0732) Prec@1 85.000 (88.304) Prec@5 100.000 (99.130) +2022-11-14 16:48:18,868 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0610 (0.0729) Prec@1 88.000 (88.298) Prec@5 100.000 (99.149) +2022-11-14 16:48:18,876 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1041 (0.0736) Prec@1 84.000 (88.208) Prec@5 99.000 (99.146) +2022-11-14 16:48:18,884 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0527 (0.0731) Prec@1 90.000 (88.245) Prec@5 100.000 (99.163) +2022-11-14 16:48:18,891 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1356 (0.0744) Prec@1 79.000 (88.060) Prec@5 100.000 (99.180) +2022-11-14 16:48:18,899 Test: [50/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0742) Prec@1 87.000 (88.039) Prec@5 100.000 (99.196) +2022-11-14 16:48:18,907 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0869 (0.0745) Prec@1 87.000 (88.019) Prec@5 99.000 (99.192) +2022-11-14 16:48:18,915 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0507 (0.0740) Prec@1 91.000 (88.075) Prec@5 99.000 (99.189) +2022-11-14 16:48:18,923 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0612 (0.0738) Prec@1 88.000 (88.074) Prec@5 100.000 (99.204) +2022-11-14 16:48:18,930 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0739) Prec@1 86.000 (88.036) Prec@5 100.000 (99.218) +2022-11-14 16:48:18,938 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0665 (0.0738) Prec@1 91.000 (88.089) Prec@5 99.000 (99.214) +2022-11-14 16:48:18,945 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0588 (0.0735) Prec@1 90.000 (88.123) Prec@5 99.000 (99.211) +2022-11-14 16:48:18,953 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0656 (0.0734) Prec@1 90.000 (88.155) Prec@5 99.000 (99.207) +2022-11-14 16:48:18,961 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0735) Prec@1 87.000 (88.136) Prec@5 100.000 (99.220) +2022-11-14 16:48:18,969 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0735) Prec@1 84.000 (88.067) Prec@5 100.000 (99.233) +2022-11-14 16:48:18,976 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0736) Prec@1 89.000 (88.082) Prec@5 100.000 (99.246) +2022-11-14 16:48:18,984 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0736) Prec@1 89.000 (88.097) Prec@5 99.000 (99.242) +2022-11-14 16:48:18,992 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0734) Prec@1 89.000 (88.111) Prec@5 100.000 (99.254) +2022-11-14 16:48:18,999 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0352 (0.0728) Prec@1 94.000 (88.203) Prec@5 100.000 (99.266) +2022-11-14 16:48:19,007 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0911 (0.0731) Prec@1 86.000 (88.169) Prec@5 99.000 (99.262) +2022-11-14 16:48:19,015 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0714 (0.0731) Prec@1 89.000 (88.182) Prec@5 98.000 (99.242) +2022-11-14 16:48:19,022 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0417 (0.0726) Prec@1 94.000 (88.269) Prec@5 99.000 (99.239) +2022-11-14 16:48:19,030 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0726) Prec@1 89.000 (88.279) Prec@5 98.000 (99.221) +2022-11-14 16:48:19,038 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0611 (0.0724) Prec@1 91.000 (88.319) Prec@5 100.000 (99.232) +2022-11-14 16:48:19,046 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0726) Prec@1 88.000 (88.314) Prec@5 99.000 (99.229) +2022-11-14 16:48:19,054 Test: [70/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1054 (0.0730) Prec@1 85.000 (88.268) Prec@5 100.000 (99.239) +2022-11-14 16:48:19,061 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0569 (0.0728) Prec@1 92.000 (88.319) Prec@5 99.000 (99.236) +2022-11-14 16:48:19,069 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0725) Prec@1 91.000 (88.356) Prec@5 100.000 (99.247) +2022-11-14 16:48:19,077 Test: [73/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0274 (0.0719) Prec@1 97.000 (88.473) Prec@5 99.000 (99.243) +2022-11-14 16:48:19,085 Test: [74/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0837 (0.0721) Prec@1 87.000 (88.453) Prec@5 99.000 (99.240) +2022-11-14 16:48:19,093 Test: [75/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0594 (0.0719) Prec@1 89.000 (88.461) Prec@5 100.000 (99.250) +2022-11-14 16:48:19,100 Test: [76/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0719) Prec@1 88.000 (88.455) Prec@5 100.000 (99.260) +2022-11-14 16:48:19,109 Test: [77/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0861 (0.0721) Prec@1 86.000 (88.423) Prec@5 97.000 (99.231) +2022-11-14 16:48:19,116 Test: [78/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0902 (0.0723) Prec@1 84.000 (88.367) Prec@5 100.000 (99.241) +2022-11-14 16:48:19,124 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0723) Prec@1 87.000 (88.350) Prec@5 99.000 (99.237) +2022-11-14 16:48:19,132 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0997 (0.0726) Prec@1 87.000 (88.333) Prec@5 97.000 (99.210) +2022-11-14 16:48:19,140 Test: [81/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0939 (0.0729) Prec@1 85.000 (88.293) Prec@5 100.000 (99.220) +2022-11-14 16:48:19,148 Test: [82/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0948 (0.0731) Prec@1 85.000 (88.253) Prec@5 100.000 (99.229) +2022-11-14 16:48:19,156 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0731) Prec@1 88.000 (88.250) Prec@5 100.000 (99.238) +2022-11-14 16:48:19,163 Test: [84/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0998 (0.0735) Prec@1 84.000 (88.200) Prec@5 100.000 (99.247) +2022-11-14 16:48:19,171 Test: [85/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1211 (0.0740) Prec@1 81.000 (88.116) Prec@5 98.000 (99.233) +2022-11-14 16:48:19,178 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0596 (0.0738) Prec@1 91.000 (88.149) Prec@5 99.000 (99.230) +2022-11-14 16:48:19,186 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0824 (0.0739) Prec@1 88.000 (88.148) Prec@5 99.000 (99.227) +2022-11-14 16:48:19,193 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0739) Prec@1 88.000 (88.146) Prec@5 100.000 (99.236) +2022-11-14 16:48:19,201 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0757 (0.0739) Prec@1 89.000 (88.156) Prec@5 99.000 (99.233) +2022-11-14 16:48:19,209 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0626 (0.0738) Prec@1 92.000 (88.198) Prec@5 100.000 (99.242) +2022-11-14 16:48:19,216 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0474 (0.0735) Prec@1 94.000 (88.261) Prec@5 100.000 (99.250) +2022-11-14 16:48:19,223 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1010 (0.0738) Prec@1 83.000 (88.204) Prec@5 100.000 (99.258) +2022-11-14 16:48:19,231 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0664 (0.0737) Prec@1 90.000 (88.223) Prec@5 98.000 (99.245) +2022-11-14 16:48:19,239 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0737) Prec@1 89.000 (88.232) Prec@5 99.000 (99.242) +2022-11-14 16:48:19,246 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0595 (0.0736) Prec@1 92.000 (88.271) Prec@5 99.000 (99.240) +2022-11-14 16:48:19,254 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0734) Prec@1 91.000 (88.299) Prec@5 99.000 (99.237) +2022-11-14 16:48:19,261 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0794 (0.0734) Prec@1 87.000 (88.286) Prec@5 100.000 (99.245) +2022-11-14 16:48:19,269 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1017 (0.0737) Prec@1 84.000 (88.242) Prec@5 100.000 (99.253) +2022-11-14 16:48:19,276 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0737) Prec@1 88.000 (88.240) Prec@5 100.000 (99.260) +2022-11-14 16:48:19,329 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:48:19,646 Epoch: [387][0/500] Time 0.031 (0.031) Data 0.233 (0.233) Loss 0.0183 (0.0183) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:19,856 Epoch: [387][10/500] Time 0.023 (0.020) Data 0.001 (0.023) Loss 0.0453 (0.0318) Prec@1 93.000 (95.000) Prec@5 98.000 (99.000) +2022-11-14 16:48:20,064 Epoch: [387][20/500] Time 0.020 (0.019) Data 0.002 (0.013) Loss 0.0399 (0.0345) Prec@1 94.000 (94.667) Prec@5 100.000 (99.333) +2022-11-14 16:48:20,278 Epoch: [387][30/500] Time 0.022 (0.019) Data 0.002 (0.009) Loss 0.0366 (0.0350) Prec@1 94.000 (94.500) Prec@5 99.000 (99.250) +2022-11-14 16:48:20,490 Epoch: [387][40/500] Time 0.020 (0.019) Data 0.002 (0.007) Loss 0.0533 (0.0387) Prec@1 94.000 (94.400) Prec@5 98.000 (99.000) +2022-11-14 16:48:20,699 Epoch: [387][50/500] Time 0.023 (0.019) Data 0.001 (0.006) Loss 0.0276 (0.0368) Prec@1 96.000 (94.667) Prec@5 99.000 (99.000) +2022-11-14 16:48:20,907 Epoch: [387][60/500] Time 0.020 (0.019) Data 0.001 (0.006) Loss 0.0426 (0.0377) Prec@1 93.000 (94.429) Prec@5 100.000 (99.143) +2022-11-14 16:48:21,117 Epoch: [387][70/500] Time 0.025 (0.019) Data 0.001 (0.005) Loss 0.0170 (0.0351) Prec@1 96.000 (94.625) Prec@5 100.000 (99.250) +2022-11-14 16:48:21,323 Epoch: [387][80/500] Time 0.020 (0.019) Data 0.002 (0.005) Loss 0.0484 (0.0366) Prec@1 93.000 (94.444) Prec@5 98.000 (99.111) +2022-11-14 16:48:21,530 Epoch: [387][90/500] Time 0.023 (0.019) Data 0.002 (0.004) Loss 0.0582 (0.0387) Prec@1 88.000 (93.800) Prec@5 100.000 (99.200) +2022-11-14 16:48:21,780 Epoch: [387][100/500] Time 0.025 (0.019) Data 0.001 (0.004) Loss 0.0205 (0.0371) Prec@1 96.000 (94.000) Prec@5 100.000 (99.273) +2022-11-14 16:48:22,055 Epoch: [387][110/500] Time 0.029 (0.020) Data 0.002 (0.004) Loss 0.0465 (0.0378) Prec@1 91.000 (93.750) Prec@5 100.000 (99.333) +2022-11-14 16:48:22,333 Epoch: [387][120/500] Time 0.024 (0.020) Data 0.002 (0.004) Loss 0.0215 (0.0366) Prec@1 97.000 (94.000) Prec@5 100.000 (99.385) +2022-11-14 16:48:22,603 Epoch: [387][130/500] Time 0.025 (0.020) Data 0.001 (0.004) Loss 0.0231 (0.0356) Prec@1 97.000 (94.214) Prec@5 100.000 (99.429) +2022-11-14 16:48:22,879 Epoch: [387][140/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0298 (0.0352) Prec@1 96.000 (94.333) Prec@5 100.000 (99.467) +2022-11-14 16:48:23,155 Epoch: [387][150/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0274 (0.0347) Prec@1 97.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:48:23,427 Epoch: [387][160/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0279 (0.0343) Prec@1 96.000 (94.588) Prec@5 100.000 (99.529) +2022-11-14 16:48:23,705 Epoch: [387][170/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0375 (0.0345) Prec@1 93.000 (94.500) Prec@5 100.000 (99.556) +2022-11-14 16:48:23,979 Epoch: [387][180/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0308 (0.0343) Prec@1 95.000 (94.526) Prec@5 99.000 (99.526) +2022-11-14 16:48:24,259 Epoch: [387][190/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0415 (0.0347) Prec@1 94.000 (94.500) Prec@5 100.000 (99.550) +2022-11-14 16:48:24,536 Epoch: [387][200/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0448 (0.0352) Prec@1 93.000 (94.429) Prec@5 99.000 (99.524) +2022-11-14 16:48:24,816 Epoch: [387][210/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0226 (0.0346) Prec@1 97.000 (94.545) Prec@5 100.000 (99.545) +2022-11-14 16:48:25,095 Epoch: [387][220/500] Time 0.024 (0.022) Data 0.003 (0.003) Loss 0.0318 (0.0345) Prec@1 94.000 (94.522) Prec@5 100.000 (99.565) +2022-11-14 16:48:25,368 Epoch: [387][230/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0382 (0.0346) Prec@1 93.000 (94.458) Prec@5 99.000 (99.542) +2022-11-14 16:48:25,646 Epoch: [387][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0419 (0.0349) Prec@1 93.000 (94.400) Prec@5 99.000 (99.520) +2022-11-14 16:48:25,920 Epoch: [387][250/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0103 (0.0340) Prec@1 99.000 (94.577) Prec@5 100.000 (99.538) +2022-11-14 16:48:26,197 Epoch: [387][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0213 (0.0335) Prec@1 98.000 (94.704) Prec@5 100.000 (99.556) +2022-11-14 16:48:26,475 Epoch: [387][270/500] Time 0.031 (0.022) Data 0.001 (0.003) Loss 0.0333 (0.0335) Prec@1 96.000 (94.750) Prec@5 100.000 (99.571) +2022-11-14 16:48:26,752 Epoch: [387][280/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0430 (0.0338) Prec@1 91.000 (94.621) Prec@5 100.000 (99.586) +2022-11-14 16:48:27,040 Epoch: [387][290/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0342 (0.0338) Prec@1 94.000 (94.600) Prec@5 100.000 (99.600) +2022-11-14 16:48:27,315 Epoch: [387][300/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0241 (0.0335) Prec@1 97.000 (94.677) Prec@5 100.000 (99.613) +2022-11-14 16:48:27,595 Epoch: [387][310/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0234 (0.0332) Prec@1 95.000 (94.688) Prec@5 100.000 (99.625) +2022-11-14 16:48:27,870 Epoch: [387][320/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0300 (0.0331) Prec@1 96.000 (94.727) Prec@5 99.000 (99.606) +2022-11-14 16:48:28,148 Epoch: [387][330/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0446 (0.0335) Prec@1 93.000 (94.676) Prec@5 100.000 (99.618) +2022-11-14 16:48:28,420 Epoch: [387][340/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0206 (0.0331) Prec@1 98.000 (94.771) Prec@5 100.000 (99.629) +2022-11-14 16:48:28,694 Epoch: [387][350/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0299 (0.0330) Prec@1 95.000 (94.778) Prec@5 100.000 (99.639) +2022-11-14 16:48:28,975 Epoch: [387][360/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0466 (0.0334) Prec@1 91.000 (94.676) Prec@5 99.000 (99.622) +2022-11-14 16:48:29,257 Epoch: [387][370/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0080 (0.0327) Prec@1 100.000 (94.816) Prec@5 100.000 (99.632) +2022-11-14 16:48:29,537 Epoch: [387][380/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0222 (0.0324) Prec@1 96.000 (94.846) Prec@5 100.000 (99.641) +2022-11-14 16:48:29,810 Epoch: [387][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0283 (0.0323) Prec@1 95.000 (94.850) Prec@5 100.000 (99.650) +2022-11-14 16:48:30,092 Epoch: [387][400/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0284 (0.0322) Prec@1 95.000 (94.854) Prec@5 99.000 (99.634) +2022-11-14 16:48:30,365 Epoch: [387][410/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0333 (0.0323) Prec@1 95.000 (94.857) Prec@5 100.000 (99.643) +2022-11-14 16:48:30,644 Epoch: [387][420/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0245 (0.0321) Prec@1 96.000 (94.884) Prec@5 100.000 (99.651) +2022-11-14 16:48:30,920 Epoch: [387][430/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0161 (0.0317) Prec@1 96.000 (94.909) Prec@5 100.000 (99.659) +2022-11-14 16:48:31,204 Epoch: [387][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0174 (0.0314) Prec@1 97.000 (94.956) Prec@5 100.000 (99.667) +2022-11-14 16:48:31,479 Epoch: [387][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0324 (0.0314) Prec@1 96.000 (94.978) Prec@5 100.000 (99.674) +2022-11-14 16:48:31,762 Epoch: [387][460/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0604 (0.0320) Prec@1 92.000 (94.915) Prec@5 100.000 (99.681) +2022-11-14 16:48:32,036 Epoch: [387][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0484 (0.0324) Prec@1 92.000 (94.854) Prec@5 100.000 (99.688) +2022-11-14 16:48:32,311 Epoch: [387][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0129 (0.0320) Prec@1 98.000 (94.918) Prec@5 100.000 (99.694) +2022-11-14 16:48:32,588 Epoch: [387][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0460 (0.0323) Prec@1 90.000 (94.820) Prec@5 100.000 (99.700) +2022-11-14 16:48:32,840 Epoch: [387][499/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0460 (0.0325) Prec@1 93.000 (94.784) Prec@5 100.000 (99.706) +2022-11-14 16:48:33,140 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0670 (0.0670) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:33,149 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0687 (0.0678) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:33,157 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0762 (0.0706) Prec@1 86.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:48:33,168 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0692) Prec@1 90.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 16:48:33,175 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0664) Prec@1 91.000 (88.800) Prec@5 99.000 (99.600) +2022-11-14 16:48:33,182 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0240 (0.0593) Prec@1 96.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 16:48:33,188 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0608) Prec@1 93.000 (90.429) Prec@5 100.000 (99.714) +2022-11-14 16:48:33,197 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0644) Prec@1 84.000 (89.625) Prec@5 99.000 (99.625) +2022-11-14 16:48:33,204 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0664) Prec@1 88.000 (89.444) Prec@5 100.000 (99.667) +2022-11-14 16:48:33,210 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0671) Prec@1 87.000 (89.200) Prec@5 99.000 (99.600) +2022-11-14 16:48:33,218 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0662) Prec@1 94.000 (89.636) Prec@5 100.000 (99.636) +2022-11-14 16:48:33,226 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0676) Prec@1 88.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 16:48:33,233 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0662) Prec@1 92.000 (89.692) Prec@5 100.000 (99.692) +2022-11-14 16:48:33,241 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0657) Prec@1 90.000 (89.714) Prec@5 99.000 (99.643) +2022-11-14 16:48:33,248 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0674) Prec@1 85.000 (89.400) Prec@5 99.000 (99.600) +2022-11-14 16:48:33,256 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0676) Prec@1 87.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 16:48:33,263 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0667) Prec@1 91.000 (89.353) Prec@5 97.000 (99.471) +2022-11-14 16:48:33,271 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0688) Prec@1 81.000 (88.889) Prec@5 100.000 (99.500) +2022-11-14 16:48:33,279 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0711) Prec@1 83.000 (88.579) Prec@5 99.000 (99.474) +2022-11-14 16:48:33,286 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0724) Prec@1 83.000 (88.300) Prec@5 98.000 (99.400) +2022-11-14 16:48:33,294 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0721) Prec@1 90.000 (88.381) Prec@5 99.000 (99.381) +2022-11-14 16:48:33,301 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0728) Prec@1 87.000 (88.318) Prec@5 100.000 (99.409) +2022-11-14 16:48:33,309 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0740) Prec@1 85.000 (88.174) Prec@5 98.000 (99.348) +2022-11-14 16:48:33,316 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0736) Prec@1 89.000 (88.208) Prec@5 100.000 (99.375) +2022-11-14 16:48:33,324 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0739) Prec@1 87.000 (88.160) Prec@5 100.000 (99.400) +2022-11-14 16:48:33,332 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0738) Prec@1 91.000 (88.269) Prec@5 98.000 (99.346) +2022-11-14 16:48:33,339 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0736) Prec@1 89.000 (88.296) Prec@5 100.000 (99.370) +2022-11-14 16:48:33,347 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0735) Prec@1 89.000 (88.321) Prec@5 99.000 (99.357) +2022-11-14 16:48:33,354 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0734) Prec@1 87.000 (88.276) Prec@5 98.000 (99.310) +2022-11-14 16:48:33,362 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0732) Prec@1 90.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 16:48:33,370 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0730) Prec@1 89.000 (88.355) Prec@5 100.000 (99.355) +2022-11-14 16:48:33,377 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0731) Prec@1 88.000 (88.344) Prec@5 98.000 (99.312) +2022-11-14 16:48:33,385 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0729) Prec@1 87.000 (88.303) Prec@5 99.000 (99.303) +2022-11-14 16:48:33,392 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0733) Prec@1 88.000 (88.294) Prec@5 100.000 (99.324) +2022-11-14 16:48:33,400 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0735) Prec@1 87.000 (88.257) Prec@5 97.000 (99.257) +2022-11-14 16:48:33,408 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0738) Prec@1 87.000 (88.222) Prec@5 99.000 (99.250) +2022-11-14 16:48:33,416 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0741) Prec@1 85.000 (88.135) Prec@5 99.000 (99.243) +2022-11-14 16:48:33,423 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0747) Prec@1 84.000 (88.026) Prec@5 99.000 (99.237) +2022-11-14 16:48:33,431 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0746) Prec@1 91.000 (88.103) Prec@5 99.000 (99.231) +2022-11-14 16:48:33,438 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0744) Prec@1 90.000 (88.150) Prec@5 99.000 (99.225) +2022-11-14 16:48:33,446 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0750) Prec@1 83.000 (88.024) Prec@5 99.000 (99.220) +2022-11-14 16:48:33,453 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0750) Prec@1 88.000 (88.024) Prec@5 100.000 (99.238) +2022-11-14 16:48:33,461 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0748) Prec@1 89.000 (88.047) Prec@5 99.000 (99.233) +2022-11-14 16:48:33,468 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0743) Prec@1 91.000 (88.114) Prec@5 100.000 (99.250) +2022-11-14 16:48:33,476 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0742) Prec@1 89.000 (88.133) Prec@5 99.000 (99.244) +2022-11-14 16:48:33,483 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1130 (0.0750) Prec@1 82.000 (88.000) Prec@5 99.000 (99.239) +2022-11-14 16:48:33,491 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0750) Prec@1 86.000 (87.957) Prec@5 100.000 (99.255) +2022-11-14 16:48:33,499 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0755) Prec@1 83.000 (87.854) Prec@5 99.000 (99.250) +2022-11-14 16:48:33,506 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0752) Prec@1 89.000 (87.878) Prec@5 100.000 (99.265) +2022-11-14 16:48:33,514 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0758) Prec@1 83.000 (87.780) Prec@5 99.000 (99.260) +2022-11-14 16:48:33,521 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0755) Prec@1 89.000 (87.804) Prec@5 100.000 (99.275) +2022-11-14 16:48:33,529 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0756) Prec@1 84.000 (87.731) Prec@5 100.000 (99.288) +2022-11-14 16:48:33,536 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0394 (0.0749) Prec@1 94.000 (87.849) Prec@5 99.000 (99.283) +2022-11-14 16:48:33,544 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0749) Prec@1 87.000 (87.833) Prec@5 100.000 (99.296) +2022-11-14 16:48:33,551 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0751) Prec@1 87.000 (87.818) Prec@5 100.000 (99.309) +2022-11-14 16:48:33,559 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0752) Prec@1 86.000 (87.786) Prec@5 99.000 (99.304) +2022-11-14 16:48:33,566 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0749) Prec@1 91.000 (87.842) Prec@5 100.000 (99.316) +2022-11-14 16:48:33,574 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0747) Prec@1 90.000 (87.879) Prec@5 100.000 (99.328) +2022-11-14 16:48:33,582 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0751) Prec@1 85.000 (87.831) Prec@5 100.000 (99.339) +2022-11-14 16:48:33,589 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0750) Prec@1 91.000 (87.883) Prec@5 99.000 (99.333) +2022-11-14 16:48:33,597 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0752) Prec@1 88.000 (87.885) Prec@5 100.000 (99.344) +2022-11-14 16:48:33,604 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0751) Prec@1 89.000 (87.903) Prec@5 100.000 (99.355) +2022-11-14 16:48:33,612 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0752) Prec@1 90.000 (87.937) Prec@5 98.000 (99.333) +2022-11-14 16:48:33,619 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0747) Prec@1 93.000 (88.016) Prec@5 99.000 (99.328) +2022-11-14 16:48:33,627 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0749) Prec@1 85.000 (87.969) Prec@5 99.000 (99.323) +2022-11-14 16:48:33,634 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0748) Prec@1 87.000 (87.955) Prec@5 100.000 (99.333) +2022-11-14 16:48:33,642 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0745) Prec@1 91.000 (88.000) Prec@5 99.000 (99.328) +2022-11-14 16:48:33,649 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0744) Prec@1 89.000 (88.015) Prec@5 100.000 (99.338) +2022-11-14 16:48:33,657 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0742) Prec@1 88.000 (88.014) Prec@5 99.000 (99.333) +2022-11-14 16:48:33,664 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0744) Prec@1 89.000 (88.029) Prec@5 99.000 (99.329) +2022-11-14 16:48:33,672 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0746) Prec@1 88.000 (88.028) Prec@5 100.000 (99.338) +2022-11-14 16:48:33,679 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0745) Prec@1 90.000 (88.056) Prec@5 100.000 (99.347) +2022-11-14 16:48:33,687 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0743) Prec@1 92.000 (88.110) Prec@5 99.000 (99.342) +2022-11-14 16:48:33,695 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0376 (0.0738) Prec@1 95.000 (88.203) Prec@5 100.000 (99.351) +2022-11-14 16:48:33,702 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0742) Prec@1 84.000 (88.147) Prec@5 100.000 (99.360) +2022-11-14 16:48:33,709 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0741) Prec@1 88.000 (88.145) Prec@5 99.000 (99.355) +2022-11-14 16:48:33,717 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0741) Prec@1 87.000 (88.130) Prec@5 98.000 (99.338) +2022-11-14 16:48:33,725 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0743) Prec@1 86.000 (88.103) Prec@5 100.000 (99.346) +2022-11-14 16:48:33,732 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0744) Prec@1 84.000 (88.051) Prec@5 100.000 (99.354) +2022-11-14 16:48:33,740 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0744) Prec@1 87.000 (88.037) Prec@5 98.000 (99.338) +2022-11-14 16:48:33,747 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0746) Prec@1 84.000 (87.988) Prec@5 100.000 (99.346) +2022-11-14 16:48:33,755 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0746) Prec@1 88.000 (87.988) Prec@5 100.000 (99.354) +2022-11-14 16:48:33,762 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0747) Prec@1 88.000 (87.988) Prec@5 99.000 (99.349) +2022-11-14 16:48:33,770 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0744) Prec@1 94.000 (88.060) Prec@5 99.000 (99.345) +2022-11-14 16:48:33,777 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0746) Prec@1 85.000 (88.024) Prec@5 99.000 (99.341) +2022-11-14 16:48:33,785 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0748) Prec@1 86.000 (88.000) Prec@5 99.000 (99.337) +2022-11-14 16:48:33,793 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0745) Prec@1 93.000 (88.057) Prec@5 99.000 (99.333) +2022-11-14 16:48:33,800 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0745) Prec@1 89.000 (88.068) Prec@5 99.000 (99.330) +2022-11-14 16:48:33,808 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0748) Prec@1 81.000 (87.989) Prec@5 100.000 (99.337) +2022-11-14 16:48:33,815 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0747) Prec@1 90.000 (88.011) Prec@5 98.000 (99.322) +2022-11-14 16:48:33,823 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0745) Prec@1 92.000 (88.055) Prec@5 100.000 (99.330) +2022-11-14 16:48:33,831 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0743) Prec@1 91.000 (88.087) Prec@5 100.000 (99.337) +2022-11-14 16:48:33,838 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0744) Prec@1 87.000 (88.075) Prec@5 100.000 (99.344) +2022-11-14 16:48:33,846 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0745) Prec@1 88.000 (88.074) Prec@5 100.000 (99.351) +2022-11-14 16:48:33,853 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0748) Prec@1 84.000 (88.032) Prec@5 99.000 (99.347) +2022-11-14 16:48:33,861 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0749) Prec@1 88.000 (88.031) Prec@5 99.000 (99.344) +2022-11-14 16:48:33,869 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0746) Prec@1 92.000 (88.072) Prec@5 99.000 (99.340) +2022-11-14 16:48:33,877 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0748) Prec@1 85.000 (88.041) Prec@5 98.000 (99.327) +2022-11-14 16:48:33,885 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0750) Prec@1 87.000 (88.030) Prec@5 99.000 (99.323) +2022-11-14 16:48:33,892 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0749) Prec@1 88.000 (88.030) Prec@5 100.000 (99.330) +2022-11-14 16:48:33,948 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:48:34,277 Epoch: [388][0/500] Time 0.024 (0.024) Data 0.247 (0.247) Loss 0.0112 (0.0112) Prec@1 99.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:34,473 Epoch: [388][10/500] Time 0.018 (0.018) Data 0.002 (0.024) Loss 0.0241 (0.0176) Prec@1 96.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:34,664 Epoch: [388][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0368 (0.0240) Prec@1 94.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:48:34,854 Epoch: [388][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0274 (0.0249) Prec@1 96.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 16:48:35,049 Epoch: [388][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0466 (0.0292) Prec@1 92.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:48:35,243 Epoch: [388][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0366 (0.0304) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:35,433 Epoch: [388][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0286 (0.0302) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:35,625 Epoch: [388][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0530 (0.0330) Prec@1 91.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:35,861 Epoch: [388][80/500] Time 0.023 (0.017) Data 0.002 (0.005) Loss 0.0392 (0.0337) Prec@1 94.000 (94.444) Prec@5 100.000 (100.000) +2022-11-14 16:48:36,128 Epoch: [388][90/500] Time 0.029 (0.018) Data 0.002 (0.004) Loss 0.0339 (0.0337) Prec@1 95.000 (94.500) Prec@5 99.000 (99.900) +2022-11-14 16:48:36,389 Epoch: [388][100/500] Time 0.022 (0.019) Data 0.002 (0.004) Loss 0.0337 (0.0337) Prec@1 95.000 (94.545) Prec@5 100.000 (99.909) +2022-11-14 16:48:36,644 Epoch: [388][110/500] Time 0.024 (0.019) Data 0.002 (0.004) Loss 0.0385 (0.0341) Prec@1 92.000 (94.333) Prec@5 100.000 (99.917) +2022-11-14 16:48:36,903 Epoch: [388][120/500] Time 0.024 (0.019) Data 0.002 (0.004) Loss 0.0673 (0.0367) Prec@1 89.000 (93.923) Prec@5 100.000 (99.923) +2022-11-14 16:48:37,169 Epoch: [388][130/500] Time 0.024 (0.020) Data 0.002 (0.004) Loss 0.0410 (0.0370) Prec@1 93.000 (93.857) Prec@5 100.000 (99.929) +2022-11-14 16:48:37,430 Epoch: [388][140/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0385 (0.0371) Prec@1 93.000 (93.800) Prec@5 100.000 (99.933) +2022-11-14 16:48:37,686 Epoch: [388][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0439 (0.0375) Prec@1 92.000 (93.688) Prec@5 100.000 (99.938) +2022-11-14 16:48:37,946 Epoch: [388][160/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0254 (0.0368) Prec@1 96.000 (93.824) Prec@5 100.000 (99.941) +2022-11-14 16:48:38,209 Epoch: [388][170/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0378 (0.0369) Prec@1 95.000 (93.889) Prec@5 99.000 (99.889) +2022-11-14 16:48:38,471 Epoch: [388][180/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0286 (0.0364) Prec@1 95.000 (93.947) Prec@5 100.000 (99.895) +2022-11-14 16:48:38,730 Epoch: [388][190/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0276 (0.0360) Prec@1 95.000 (94.000) Prec@5 100.000 (99.900) +2022-11-14 16:48:38,989 Epoch: [388][200/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0429 (0.0363) Prec@1 92.000 (93.905) Prec@5 100.000 (99.905) +2022-11-14 16:48:39,254 Epoch: [388][210/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0352 (0.0363) Prec@1 93.000 (93.864) Prec@5 100.000 (99.909) +2022-11-14 16:48:39,514 Epoch: [388][220/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0185 (0.0355) Prec@1 97.000 (94.000) Prec@5 100.000 (99.913) +2022-11-14 16:48:39,775 Epoch: [388][230/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0338 (0.0354) Prec@1 94.000 (94.000) Prec@5 100.000 (99.917) +2022-11-14 16:48:40,036 Epoch: [388][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0168 (0.0347) Prec@1 97.000 (94.120) Prec@5 100.000 (99.920) +2022-11-14 16:48:40,296 Epoch: [388][250/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0198 (0.0341) Prec@1 97.000 (94.231) Prec@5 100.000 (99.923) +2022-11-14 16:48:40,561 Epoch: [388][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0476 (0.0346) Prec@1 92.000 (94.148) Prec@5 100.000 (99.926) +2022-11-14 16:48:40,825 Epoch: [388][270/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0274 (0.0343) Prec@1 96.000 (94.214) Prec@5 100.000 (99.929) +2022-11-14 16:48:41,091 Epoch: [388][280/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0180 (0.0338) Prec@1 97.000 (94.310) Prec@5 100.000 (99.931) +2022-11-14 16:48:41,353 Epoch: [388][290/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0270 (0.0336) Prec@1 95.000 (94.333) Prec@5 100.000 (99.933) +2022-11-14 16:48:41,618 Epoch: [388][300/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0393 (0.0337) Prec@1 93.000 (94.290) Prec@5 100.000 (99.935) +2022-11-14 16:48:41,880 Epoch: [388][310/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0168 (0.0332) Prec@1 97.000 (94.375) Prec@5 100.000 (99.938) +2022-11-14 16:48:42,142 Epoch: [388][320/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0287 (0.0331) Prec@1 95.000 (94.394) Prec@5 100.000 (99.939) +2022-11-14 16:48:42,403 Epoch: [388][330/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0161 (0.0326) Prec@1 97.000 (94.471) Prec@5 100.000 (99.941) +2022-11-14 16:48:42,662 Epoch: [388][340/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0219 (0.0323) Prec@1 96.000 (94.514) Prec@5 100.000 (99.943) +2022-11-14 16:48:42,922 Epoch: [388][350/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0281 (0.0322) Prec@1 96.000 (94.556) Prec@5 99.000 (99.917) +2022-11-14 16:48:43,184 Epoch: [388][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0343 (0.0322) Prec@1 93.000 (94.514) Prec@5 100.000 (99.919) +2022-11-14 16:48:43,447 Epoch: [388][370/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0163 (0.0318) Prec@1 97.000 (94.579) Prec@5 100.000 (99.921) +2022-11-14 16:48:43,711 Epoch: [388][380/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0402 (0.0320) Prec@1 92.000 (94.513) Prec@5 100.000 (99.923) +2022-11-14 16:48:43,973 Epoch: [388][390/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0337 (0.0321) Prec@1 96.000 (94.550) Prec@5 100.000 (99.925) +2022-11-14 16:48:44,235 Epoch: [388][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0382 (0.0322) Prec@1 93.000 (94.512) Prec@5 100.000 (99.927) +2022-11-14 16:48:44,496 Epoch: [388][410/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0339 (0.0322) Prec@1 94.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 16:48:44,759 Epoch: [388][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0238 (0.0320) Prec@1 97.000 (94.558) Prec@5 100.000 (99.930) +2022-11-14 16:48:45,021 Epoch: [388][430/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0260 (0.0319) Prec@1 94.000 (94.545) Prec@5 100.000 (99.932) +2022-11-14 16:48:45,286 Epoch: [388][440/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0383 (0.0321) Prec@1 93.000 (94.511) Prec@5 100.000 (99.933) +2022-11-14 16:48:45,551 Epoch: [388][450/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0297 (0.0320) Prec@1 96.000 (94.543) Prec@5 100.000 (99.935) +2022-11-14 16:48:45,814 Epoch: [388][460/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0446 (0.0323) Prec@1 92.000 (94.489) Prec@5 100.000 (99.936) +2022-11-14 16:48:46,077 Epoch: [388][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0212 (0.0320) Prec@1 96.000 (94.521) Prec@5 100.000 (99.938) +2022-11-14 16:48:46,339 Epoch: [388][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0240 (0.0319) Prec@1 95.000 (94.531) Prec@5 100.000 (99.939) +2022-11-14 16:48:46,600 Epoch: [388][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0185 (0.0316) Prec@1 98.000 (94.600) Prec@5 100.000 (99.940) +2022-11-14 16:48:46,838 Epoch: [388][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0184 (0.0313) Prec@1 96.000 (94.627) Prec@5 100.000 (99.941) +2022-11-14 16:48:47,136 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0692 (0.0692) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:47,144 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0726 (0.0709) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:48:47,152 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0741) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:47,162 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0757) Prec@1 89.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 16:48:47,169 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0758) Prec@1 89.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 16:48:47,176 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0405 (0.0699) Prec@1 93.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:48:47,183 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0681) Prec@1 92.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:48:47,191 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0721) Prec@1 83.000 (88.375) Prec@5 100.000 (99.750) +2022-11-14 16:48:47,198 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0723) Prec@1 89.000 (88.444) Prec@5 99.000 (99.667) +2022-11-14 16:48:47,205 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0739) Prec@1 87.000 (88.300) Prec@5 99.000 (99.600) +2022-11-14 16:48:47,213 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0718) Prec@1 93.000 (88.727) Prec@5 100.000 (99.636) +2022-11-14 16:48:47,221 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0721) Prec@1 87.000 (88.583) Prec@5 100.000 (99.667) +2022-11-14 16:48:47,228 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0706) Prec@1 90.000 (88.692) Prec@5 100.000 (99.692) +2022-11-14 16:48:47,236 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0705) Prec@1 90.000 (88.786) Prec@5 98.000 (99.571) +2022-11-14 16:48:47,243 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0712) Prec@1 88.000 (88.733) Prec@5 100.000 (99.600) +2022-11-14 16:48:47,251 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0706) Prec@1 90.000 (88.812) Prec@5 100.000 (99.625) +2022-11-14 16:48:47,259 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0699) Prec@1 91.000 (88.941) Prec@5 97.000 (99.471) +2022-11-14 16:48:47,266 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1098 (0.0721) Prec@1 83.000 (88.611) Prec@5 100.000 (99.500) +2022-11-14 16:48:47,274 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0727) Prec@1 84.000 (88.368) Prec@5 99.000 (99.474) +2022-11-14 16:48:47,281 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0730) Prec@1 87.000 (88.300) Prec@5 98.000 (99.400) +2022-11-14 16:48:47,289 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0736) Prec@1 87.000 (88.238) Prec@5 100.000 (99.429) +2022-11-14 16:48:47,297 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0742) Prec@1 87.000 (88.182) Prec@5 99.000 (99.409) +2022-11-14 16:48:47,304 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0754) Prec@1 86.000 (88.087) Prec@5 98.000 (99.348) +2022-11-14 16:48:47,312 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0758) Prec@1 88.000 (88.083) Prec@5 100.000 (99.375) +2022-11-14 16:48:47,320 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0757) Prec@1 88.000 (88.080) Prec@5 100.000 (99.400) +2022-11-14 16:48:47,328 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0763) Prec@1 87.000 (88.038) Prec@5 98.000 (99.346) +2022-11-14 16:48:47,335 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0757) Prec@1 91.000 (88.148) Prec@5 100.000 (99.370) +2022-11-14 16:48:47,343 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0753) Prec@1 88.000 (88.143) Prec@5 100.000 (99.393) +2022-11-14 16:48:47,351 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0752) Prec@1 88.000 (88.138) Prec@5 99.000 (99.379) +2022-11-14 16:48:47,358 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0756) Prec@1 87.000 (88.100) Prec@5 100.000 (99.400) +2022-11-14 16:48:47,366 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0749) Prec@1 90.000 (88.161) Prec@5 100.000 (99.419) +2022-11-14 16:48:47,374 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0741) Prec@1 94.000 (88.344) Prec@5 100.000 (99.438) +2022-11-14 16:48:47,381 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0735) Prec@1 90.000 (88.394) Prec@5 99.000 (99.424) +2022-11-14 16:48:47,389 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0747) Prec@1 79.000 (88.118) Prec@5 99.000 (99.412) +2022-11-14 16:48:47,397 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0751) Prec@1 87.000 (88.086) Prec@5 98.000 (99.371) +2022-11-14 16:48:47,405 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0749) Prec@1 88.000 (88.083) Prec@5 100.000 (99.389) +2022-11-14 16:48:47,412 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0749) Prec@1 88.000 (88.081) Prec@5 98.000 (99.351) +2022-11-14 16:48:47,420 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0754) Prec@1 84.000 (87.974) Prec@5 99.000 (99.342) +2022-11-14 16:48:47,428 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0750) Prec@1 92.000 (88.077) Prec@5 99.000 (99.333) +2022-11-14 16:48:47,436 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0745) Prec@1 92.000 (88.175) Prec@5 99.000 (99.325) +2022-11-14 16:48:47,443 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0747) Prec@1 87.000 (88.146) Prec@5 99.000 (99.317) +2022-11-14 16:48:47,451 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0750) Prec@1 87.000 (88.119) Prec@5 100.000 (99.333) +2022-11-14 16:48:47,459 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0744) Prec@1 94.000 (88.256) Prec@5 100.000 (99.349) +2022-11-14 16:48:47,466 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0743) Prec@1 86.000 (88.205) Prec@5 98.000 (99.318) +2022-11-14 16:48:47,474 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0736) Prec@1 92.000 (88.289) Prec@5 100.000 (99.333) +2022-11-14 16:48:47,481 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0742) Prec@1 84.000 (88.196) Prec@5 100.000 (99.348) +2022-11-14 16:48:47,489 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0743) Prec@1 87.000 (88.170) Prec@5 100.000 (99.362) +2022-11-14 16:48:47,497 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0746) Prec@1 84.000 (88.083) Prec@5 99.000 (99.354) +2022-11-14 16:48:47,505 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0742) Prec@1 92.000 (88.163) Prec@5 100.000 (99.367) +2022-11-14 16:48:47,512 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0746) Prec@1 85.000 (88.100) Prec@5 100.000 (99.380) +2022-11-14 16:48:47,520 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0743) Prec@1 88.000 (88.098) Prec@5 100.000 (99.392) +2022-11-14 16:48:47,528 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0746) Prec@1 86.000 (88.058) Prec@5 99.000 (99.385) +2022-11-14 16:48:47,536 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0744) Prec@1 89.000 (88.075) Prec@5 99.000 (99.377) +2022-11-14 16:48:47,544 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0740) Prec@1 93.000 (88.167) Prec@5 100.000 (99.389) +2022-11-14 16:48:47,551 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0743) Prec@1 84.000 (88.091) Prec@5 100.000 (99.400) +2022-11-14 16:48:47,559 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0741) Prec@1 89.000 (88.107) Prec@5 99.000 (99.393) +2022-11-14 16:48:47,566 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0741) Prec@1 89.000 (88.123) Prec@5 99.000 (99.386) +2022-11-14 16:48:47,574 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0740) Prec@1 90.000 (88.155) Prec@5 99.000 (99.379) +2022-11-14 16:48:47,582 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0744) Prec@1 86.000 (88.119) Prec@5 100.000 (99.390) +2022-11-14 16:48:47,590 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0742) Prec@1 90.000 (88.150) Prec@5 100.000 (99.400) +2022-11-14 16:48:47,597 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0741) Prec@1 90.000 (88.180) Prec@5 99.000 (99.393) +2022-11-14 16:48:47,605 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0739) Prec@1 91.000 (88.226) Prec@5 99.000 (99.387) +2022-11-14 16:48:47,613 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0737) Prec@1 90.000 (88.254) Prec@5 100.000 (99.397) +2022-11-14 16:48:47,621 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0321 (0.0731) Prec@1 95.000 (88.359) Prec@5 100.000 (99.406) +2022-11-14 16:48:47,629 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0733) Prec@1 85.000 (88.308) Prec@5 99.000 (99.400) +2022-11-14 16:48:47,637 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0730) Prec@1 91.000 (88.348) Prec@5 99.000 (99.394) +2022-11-14 16:48:47,644 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0265 (0.0723) Prec@1 96.000 (88.463) Prec@5 100.000 (99.403) +2022-11-14 16:48:47,652 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0722) Prec@1 91.000 (88.500) Prec@5 98.000 (99.382) +2022-11-14 16:48:47,660 Test: 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Loss 0.0992 (0.0722) Prec@1 83.000 (88.467) Prec@5 100.000 (99.413) +2022-11-14 16:48:47,713 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0722) Prec@1 87.000 (88.447) Prec@5 100.000 (99.421) +2022-11-14 16:48:47,721 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0724) Prec@1 86.000 (88.416) Prec@5 99.000 (99.416) +2022-11-14 16:48:47,728 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0725) Prec@1 85.000 (88.372) Prec@5 98.000 (99.397) +2022-11-14 16:48:47,736 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0724) Prec@1 88.000 (88.367) Prec@5 100.000 (99.405) +2022-11-14 16:48:47,744 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0724) Prec@1 88.000 (88.362) Prec@5 99.000 (99.400) +2022-11-14 16:48:47,751 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0727) Prec@1 86.000 (88.333) Prec@5 99.000 (99.395) +2022-11-14 16:48:47,758 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0727) Prec@1 89.000 (88.341) Prec@5 99.000 (99.390) +2022-11-14 16:48:47,766 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0729) Prec@1 85.000 (88.301) Prec@5 100.000 (99.398) +2022-11-14 16:48:47,773 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0728) Prec@1 89.000 (88.310) Prec@5 100.000 (99.405) +2022-11-14 16:48:47,781 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0728) Prec@1 89.000 (88.318) Prec@5 100.000 (99.412) +2022-11-14 16:48:47,788 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0731) Prec@1 88.000 (88.314) Prec@5 100.000 (99.419) +2022-11-14 16:48:47,795 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0730) Prec@1 91.000 (88.345) Prec@5 100.000 (99.425) +2022-11-14 16:48:47,803 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0729) Prec@1 89.000 (88.352) Prec@5 99.000 (99.420) +2022-11-14 16:48:47,810 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0732) Prec@1 83.000 (88.292) Prec@5 100.000 (99.427) +2022-11-14 16:48:47,818 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0732) Prec@1 89.000 (88.300) Prec@5 99.000 (99.422) +2022-11-14 16:48:47,825 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0369 (0.0728) Prec@1 93.000 (88.352) Prec@5 100.000 (99.429) +2022-11-14 16:48:47,833 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0726) Prec@1 91.000 (88.380) Prec@5 99.000 (99.424) +2022-11-14 16:48:47,840 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0729) Prec@1 84.000 (88.333) Prec@5 100.000 (99.430) +2022-11-14 16:48:47,848 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0728) Prec@1 90.000 (88.351) Prec@5 99.000 (99.426) +2022-11-14 16:48:47,856 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0727) Prec@1 89.000 (88.358) Prec@5 99.000 (99.421) +2022-11-14 16:48:47,863 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0727) Prec@1 88.000 (88.354) Prec@5 99.000 (99.417) +2022-11-14 16:48:47,871 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0726) Prec@1 88.000 (88.351) Prec@5 97.000 (99.392) +2022-11-14 16:48:47,878 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0728) Prec@1 85.000 (88.316) Prec@5 97.000 (99.367) +2022-11-14 16:48:47,885 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0730) Prec@1 87.000 (88.303) Prec@5 99.000 (99.364) +2022-11-14 16:48:47,893 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0730) Prec@1 89.000 (88.310) Prec@5 99.000 (99.360) +2022-11-14 16:48:47,946 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:48:48,278 Epoch: [389][0/500] Time 0.023 (0.023) Data 0.253 (0.253) Loss 0.0263 (0.0263) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:48,507 Epoch: [389][10/500] Time 0.021 (0.018) Data 0.001 (0.027) Loss 0.0330 (0.0296) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:48:48,695 Epoch: [389][20/500] Time 0.017 (0.018) Data 0.001 (0.015) Loss 0.0345 (0.0313) Prec@1 94.000 (94.000) Prec@5 99.000 (99.667) +2022-11-14 16:48:48,887 Epoch: [389][30/500] Time 0.018 (0.017) Data 0.002 (0.011) Loss 0.0320 (0.0314) Prec@1 95.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:48:49,090 Epoch: [389][40/500] Time 0.019 (0.017) Data 0.001 (0.008) Loss 0.0368 (0.0325) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 16:48:49,325 Epoch: [389][50/500] Time 0.026 (0.018) Data 0.002 (0.007) Loss 0.0191 (0.0303) Prec@1 98.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:48:49,622 Epoch: [389][60/500] Time 0.027 (0.019) Data 0.002 (0.006) Loss 0.0190 (0.0287) Prec@1 97.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:48:49,914 Epoch: [389][70/500] Time 0.028 (0.020) Data 0.001 (0.006) Loss 0.0431 (0.0305) Prec@1 92.000 (94.750) Prec@5 99.000 (99.750) +2022-11-14 16:48:50,212 Epoch: [389][80/500] Time 0.027 (0.021) Data 0.002 (0.005) Loss 0.0272 (0.0301) Prec@1 95.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 16:48:50,505 Epoch: [389][90/500] Time 0.026 (0.021) Data 0.002 (0.005) Loss 0.0400 (0.0311) Prec@1 93.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 16:48:50,794 Epoch: [389][100/500] Time 0.027 (0.022) Data 0.002 (0.004) Loss 0.0237 (0.0304) Prec@1 97.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:48:51,086 Epoch: [389][110/500] Time 0.028 (0.022) Data 0.001 (0.004) Loss 0.0268 (0.0301) Prec@1 95.000 (94.833) Prec@5 99.000 (99.750) +2022-11-14 16:48:51,366 Epoch: [389][120/500] Time 0.027 (0.022) Data 0.001 (0.004) Loss 0.0153 (0.0290) Prec@1 98.000 (95.077) Prec@5 100.000 (99.769) +2022-11-14 16:48:51,651 Epoch: [389][130/500] Time 0.027 (0.023) Data 0.002 (0.004) Loss 0.0299 (0.0291) Prec@1 95.000 (95.071) Prec@5 100.000 (99.786) +2022-11-14 16:48:51,933 Epoch: [389][140/500] Time 0.025 (0.023) Data 0.002 (0.004) Loss 0.0157 (0.0282) Prec@1 98.000 (95.267) Prec@5 98.000 (99.667) +2022-11-14 16:48:52,222 Epoch: [389][150/500] Time 0.028 (0.023) Data 0.002 (0.004) Loss 0.0180 (0.0275) Prec@1 98.000 (95.438) Prec@5 100.000 (99.688) +2022-11-14 16:48:52,504 Epoch: [389][160/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0284 (0.0276) Prec@1 96.000 (95.471) Prec@5 100.000 (99.706) +2022-11-14 16:48:52,786 Epoch: [389][170/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0158 (0.0269) Prec@1 98.000 (95.611) Prec@5 100.000 (99.722) +2022-11-14 16:48:53,076 Epoch: [389][180/500] Time 0.027 (0.023) Data 0.001 (0.003) Loss 0.0377 (0.0275) Prec@1 93.000 (95.474) Prec@5 100.000 (99.737) +2022-11-14 16:48:53,372 Epoch: [389][190/500] Time 0.029 (0.023) Data 0.001 (0.003) Loss 0.0247 (0.0274) Prec@1 94.000 (95.400) Prec@5 100.000 (99.750) +2022-11-14 16:48:53,656 Epoch: [389][200/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0524 (0.0285) Prec@1 90.000 (95.143) Prec@5 99.000 (99.714) +2022-11-14 16:48:53,943 Epoch: [389][210/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0421 (0.0292) Prec@1 93.000 (95.045) Prec@5 100.000 (99.727) +2022-11-14 16:48:54,232 Epoch: [389][220/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0452 (0.0299) Prec@1 92.000 (94.913) Prec@5 100.000 (99.739) +2022-11-14 16:48:54,516 Epoch: [389][230/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0096 (0.0290) Prec@1 99.000 (95.083) Prec@5 100.000 (99.750) +2022-11-14 16:48:54,798 Epoch: [389][240/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0352 (0.0293) Prec@1 96.000 (95.120) Prec@5 99.000 (99.720) +2022-11-14 16:48:55,086 Epoch: [389][250/500] Time 0.026 (0.024) Data 0.001 (0.003) Loss 0.0327 (0.0294) Prec@1 94.000 (95.077) Prec@5 100.000 (99.731) +2022-11-14 16:48:55,367 Epoch: [389][260/500] Time 0.027 (0.024) Data 0.001 (0.003) Loss 0.0438 (0.0299) Prec@1 90.000 (94.889) Prec@5 100.000 (99.741) +2022-11-14 16:48:55,651 Epoch: [389][270/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0238 (0.0297) Prec@1 95.000 (94.893) Prec@5 100.000 (99.750) +2022-11-14 16:48:55,935 Epoch: [389][280/500] Time 0.025 (0.024) Data 0.002 (0.003) Loss 0.0208 (0.0294) Prec@1 97.000 (94.966) Prec@5 100.000 (99.759) +2022-11-14 16:48:56,218 Epoch: [389][290/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0369 (0.0297) Prec@1 94.000 (94.933) Prec@5 100.000 (99.767) +2022-11-14 16:48:56,500 Epoch: [389][300/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0497 (0.0303) Prec@1 91.000 (94.806) Prec@5 99.000 (99.742) +2022-11-14 16:48:56,782 Epoch: [389][310/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0372 (0.0305) Prec@1 96.000 (94.844) Prec@5 100.000 (99.750) +2022-11-14 16:48:57,063 Epoch: [389][320/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0424 (0.0309) Prec@1 93.000 (94.788) Prec@5 100.000 (99.758) +2022-11-14 16:48:57,351 Epoch: [389][330/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0368 (0.0310) Prec@1 94.000 (94.765) Prec@5 100.000 (99.765) +2022-11-14 16:48:57,640 Epoch: [389][340/500] Time 0.023 (0.024) Data 0.003 (0.003) Loss 0.0257 (0.0309) Prec@1 96.000 (94.800) Prec@5 100.000 (99.771) +2022-11-14 16:48:57,924 Epoch: [389][350/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0153 (0.0305) Prec@1 97.000 (94.861) Prec@5 100.000 (99.778) +2022-11-14 16:48:58,207 Epoch: [389][360/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0379 (0.0307) Prec@1 93.000 (94.811) Prec@5 99.000 (99.757) +2022-11-14 16:48:58,489 Epoch: [389][370/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0228 (0.0305) Prec@1 97.000 (94.868) Prec@5 100.000 (99.763) +2022-11-14 16:48:58,772 Epoch: [389][380/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0235 (0.0303) Prec@1 96.000 (94.897) Prec@5 100.000 (99.769) +2022-11-14 16:48:59,055 Epoch: [389][390/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0089 (0.0297) Prec@1 99.000 (95.000) Prec@5 100.000 (99.775) +2022-11-14 16:48:59,342 Epoch: [389][400/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0533 (0.0303) Prec@1 91.000 (94.902) Prec@5 100.000 (99.780) +2022-11-14 16:48:59,623 Epoch: [389][410/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0298 (0.0303) Prec@1 93.000 (94.857) Prec@5 99.000 (99.762) +2022-11-14 16:48:59,910 Epoch: [389][420/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0153 (0.0300) Prec@1 99.000 (94.953) Prec@5 100.000 (99.767) +2022-11-14 16:49:00,200 Epoch: [389][430/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0390 (0.0302) Prec@1 93.000 (94.909) Prec@5 99.000 (99.750) +2022-11-14 16:49:00,483 Epoch: [389][440/500] Time 0.030 (0.024) Data 0.001 (0.002) Loss 0.0196 (0.0299) Prec@1 96.000 (94.933) Prec@5 100.000 (99.756) +2022-11-14 16:49:00,770 Epoch: [389][450/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0139 (0.0296) Prec@1 99.000 (95.022) Prec@5 100.000 (99.761) +2022-11-14 16:49:01,054 Epoch: [389][460/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0130 (0.0292) Prec@1 97.000 (95.064) Prec@5 100.000 (99.766) +2022-11-14 16:49:01,342 Epoch: [389][470/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0299 (0.0292) Prec@1 95.000 (95.062) Prec@5 100.000 (99.771) +2022-11-14 16:49:01,625 Epoch: [389][480/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0384 (0.0294) Prec@1 94.000 (95.041) Prec@5 100.000 (99.776) +2022-11-14 16:49:01,907 Epoch: [389][490/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0469 (0.0298) Prec@1 92.000 (94.980) Prec@5 100.000 (99.780) +2022-11-14 16:49:02,167 Epoch: [389][499/500] Time 0.026 (0.024) Data 0.001 (0.002) Loss 0.0367 (0.0299) Prec@1 94.000 (94.961) Prec@5 100.000 (99.784) +2022-11-14 16:49:02,463 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0482 (0.0482) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:02,470 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0745 (0.0613) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:02,477 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0660) Prec@1 84.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:02,488 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0677) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:49:02,495 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0722) Prec@1 86.000 (88.000) Prec@5 99.000 (99.800) +2022-11-14 16:49:02,502 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0695) Prec@1 90.000 (88.333) Prec@5 99.000 (99.667) +2022-11-14 16:49:02,508 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0675) Prec@1 92.000 (88.857) Prec@5 100.000 (99.714) +2022-11-14 16:49:02,516 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0710) Prec@1 83.000 (88.125) Prec@5 99.000 (99.625) +2022-11-14 16:49:02,524 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0713) Prec@1 86.000 (87.889) Prec@5 99.000 (99.556) +2022-11-14 16:49:02,532 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0736) Prec@1 85.000 (87.600) Prec@5 98.000 (99.400) +2022-11-14 16:49:02,540 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0722) Prec@1 92.000 (88.000) Prec@5 100.000 (99.455) +2022-11-14 16:49:02,548 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0726) Prec@1 88.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 16:49:02,555 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0713) Prec@1 92.000 (88.308) Prec@5 100.000 (99.538) +2022-11-14 16:49:02,563 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0709) Prec@1 89.000 (88.357) Prec@5 100.000 (99.571) +2022-11-14 16:49:02,571 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0711) Prec@1 87.000 (88.267) Prec@5 99.000 (99.533) +2022-11-14 16:49:02,579 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0511 (0.0698) Prec@1 89.000 (88.312) Prec@5 99.000 (99.500) +2022-11-14 16:49:02,587 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0689) Prec@1 94.000 (88.647) Prec@5 98.000 (99.412) +2022-11-14 16:49:02,594 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0710) Prec@1 84.000 (88.389) Prec@5 99.000 (99.389) +2022-11-14 16:49:02,602 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0713) Prec@1 86.000 (88.263) Prec@5 99.000 (99.368) +2022-11-14 16:49:02,609 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0725) Prec@1 84.000 (88.050) Prec@5 98.000 (99.300) +2022-11-14 16:49:02,617 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0719) Prec@1 90.000 (88.143) Prec@5 100.000 (99.333) +2022-11-14 16:49:02,625 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0732) Prec@1 83.000 (87.909) Prec@5 95.000 (99.136) +2022-11-14 16:49:02,635 Test: [22/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0744) Prec@1 84.000 (87.739) Prec@5 98.000 (99.087) +2022-11-14 16:49:02,645 Test: [23/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0749) Prec@1 87.000 (87.708) Prec@5 100.000 (99.125) +2022-11-14 16:49:02,653 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0752) Prec@1 87.000 (87.680) Prec@5 98.000 (99.080) +2022-11-14 16:49:02,661 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0761) Prec@1 86.000 (87.615) Prec@5 99.000 (99.077) +2022-11-14 16:49:02,671 Test: [26/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0750) Prec@1 92.000 (87.778) Prec@5 100.000 (99.111) +2022-11-14 16:49:02,680 Test: [27/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0743) Prec@1 91.000 (87.893) Prec@5 100.000 (99.143) +2022-11-14 16:49:02,688 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0740) Prec@1 92.000 (88.034) Prec@5 98.000 (99.103) +2022-11-14 16:49:02,696 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0734) Prec@1 92.000 (88.167) Prec@5 100.000 (99.133) +2022-11-14 16:49:02,706 Test: [30/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0737) Prec@1 87.000 (88.129) Prec@5 99.000 (99.129) +2022-11-14 16:49:02,716 Test: [31/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0736) Prec@1 88.000 (88.125) Prec@5 98.000 (99.094) +2022-11-14 16:49:02,723 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0739) Prec@1 87.000 (88.091) Prec@5 100.000 (99.121) +2022-11-14 16:49:02,731 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0743) Prec@1 86.000 (88.029) Prec@5 100.000 (99.147) +2022-11-14 16:49:02,740 Test: [34/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0740) Prec@1 91.000 (88.114) Prec@5 97.000 (99.086) +2022-11-14 16:49:02,750 Test: [35/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0735) Prec@1 91.000 (88.194) Prec@5 100.000 (99.111) +2022-11-14 16:49:02,757 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0731) Prec@1 90.000 (88.243) Prec@5 99.000 (99.108) +2022-11-14 16:49:02,765 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0738) Prec@1 81.000 (88.053) Prec@5 100.000 (99.132) +2022-11-14 16:49:02,775 Test: [38/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0735) Prec@1 93.000 (88.179) Prec@5 100.000 (99.154) +2022-11-14 16:49:02,784 Test: [39/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0736) Prec@1 86.000 (88.125) Prec@5 99.000 (99.150) +2022-11-14 16:49:02,792 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0737) Prec@1 89.000 (88.146) Prec@5 99.000 (99.146) +2022-11-14 16:49:02,800 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0738) Prec@1 88.000 (88.143) Prec@5 100.000 (99.167) +2022-11-14 16:49:02,809 Test: [42/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0405 (0.0730) Prec@1 94.000 (88.279) Prec@5 100.000 (99.186) +2022-11-14 16:49:02,819 Test: [43/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0732) Prec@1 86.000 (88.227) Prec@5 100.000 (99.205) +2022-11-14 16:49:02,827 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0400 (0.0725) Prec@1 93.000 (88.333) Prec@5 100.000 (99.222) +2022-11-14 16:49:02,834 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0729) Prec@1 86.000 (88.283) Prec@5 100.000 (99.239) +2022-11-14 16:49:02,844 Test: [46/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0728) Prec@1 90.000 (88.319) Prec@5 100.000 (99.255) +2022-11-14 16:49:02,854 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0732) Prec@1 87.000 (88.292) Prec@5 98.000 (99.229) +2022-11-14 16:49:02,862 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0727) Prec@1 91.000 (88.347) Prec@5 100.000 (99.245) +2022-11-14 16:49:02,869 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0730) Prec@1 88.000 (88.340) Prec@5 100.000 (99.260) +2022-11-14 16:49:02,879 Test: [50/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0727) Prec@1 90.000 (88.373) Prec@5 99.000 (99.255) +2022-11-14 16:49:02,889 Test: [51/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0731) Prec@1 85.000 (88.308) Prec@5 98.000 (99.231) +2022-11-14 16:49:02,897 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0726) Prec@1 93.000 (88.396) Prec@5 98.000 (99.208) +2022-11-14 16:49:02,905 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0724) Prec@1 90.000 (88.426) Prec@5 96.000 (99.148) +2022-11-14 16:49:02,912 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0728) Prec@1 86.000 (88.382) Prec@5 100.000 (99.164) +2022-11-14 16:49:02,919 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0727) Prec@1 89.000 (88.393) Prec@5 99.000 (99.161) +2022-11-14 16:49:02,927 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0725) Prec@1 88.000 (88.386) Prec@5 100.000 (99.175) +2022-11-14 16:49:02,934 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0726) Prec@1 88.000 (88.379) Prec@5 100.000 (99.190) +2022-11-14 16:49:02,942 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0727) Prec@1 85.000 (88.322) Prec@5 100.000 (99.203) +2022-11-14 16:49:02,950 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0729) Prec@1 86.000 (88.283) Prec@5 99.000 (99.200) +2022-11-14 16:49:02,957 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0728) Prec@1 91.000 (88.328) Prec@5 100.000 (99.213) +2022-11-14 16:49:02,965 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0727) Prec@1 90.000 (88.355) Prec@5 100.000 (99.226) +2022-11-14 16:49:02,972 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0723) Prec@1 93.000 (88.429) Prec@5 100.000 (99.238) +2022-11-14 16:49:02,980 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0324 (0.0716) Prec@1 96.000 (88.547) Prec@5 100.000 (99.250) +2022-11-14 16:49:02,987 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0720) Prec@1 84.000 (88.477) Prec@5 99.000 (99.246) +2022-11-14 16:49:02,995 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0720) Prec@1 88.000 (88.470) Prec@5 100.000 (99.258) +2022-11-14 16:49:03,003 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0717) Prec@1 90.000 (88.493) Prec@5 99.000 (99.254) +2022-11-14 16:49:03,010 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0718) Prec@1 88.000 (88.485) Prec@5 97.000 (99.221) +2022-11-14 16:49:03,018 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0721) Prec@1 85.000 (88.435) Prec@5 98.000 (99.203) +2022-11-14 16:49:03,025 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0723) Prec@1 85.000 (88.386) Prec@5 99.000 (99.200) +2022-11-14 16:49:03,033 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0728) Prec@1 84.000 (88.324) Prec@5 98.000 (99.183) +2022-11-14 16:49:03,041 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0727) Prec@1 88.000 (88.319) Prec@5 99.000 (99.181) +2022-11-14 16:49:03,049 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0723) Prec@1 92.000 (88.370) Prec@5 100.000 (99.192) +2022-11-14 16:49:03,057 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0418 (0.0719) Prec@1 91.000 (88.405) Prec@5 100.000 (99.203) +2022-11-14 16:49:03,065 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0722) Prec@1 85.000 (88.360) Prec@5 99.000 (99.200) +2022-11-14 16:49:03,073 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0719) Prec@1 93.000 (88.421) Prec@5 99.000 (99.197) +2022-11-14 16:49:03,082 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0716) Prec@1 92.000 (88.468) Prec@5 100.000 (99.208) +2022-11-14 16:49:03,090 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0717) Prec@1 86.000 (88.436) Prec@5 99.000 (99.205) +2022-11-14 16:49:03,098 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0719) Prec@1 87.000 (88.418) Prec@5 99.000 (99.203) +2022-11-14 16:49:03,105 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0719) Prec@1 87.000 (88.400) Prec@5 100.000 (99.213) +2022-11-14 16:49:03,113 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0720) Prec@1 86.000 (88.370) Prec@5 99.000 (99.210) +2022-11-14 16:49:03,121 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0718) Prec@1 89.000 (88.378) Prec@5 99.000 (99.207) +2022-11-14 16:49:03,129 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0722) Prec@1 84.000 (88.325) Prec@5 99.000 (99.205) +2022-11-14 16:49:03,136 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0721) Prec@1 90.000 (88.345) Prec@5 99.000 (99.202) +2022-11-14 16:49:03,144 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0723) Prec@1 82.000 (88.271) Prec@5 100.000 (99.212) +2022-11-14 16:49:03,152 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0726) Prec@1 85.000 (88.233) Prec@5 100.000 (99.221) +2022-11-14 16:49:03,159 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0725) Prec@1 89.000 (88.241) Prec@5 99.000 (99.218) +2022-11-14 16:49:03,167 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0723) Prec@1 92.000 (88.284) Prec@5 99.000 (99.216) +2022-11-14 16:49:03,175 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0724) Prec@1 89.000 (88.292) Prec@5 100.000 (99.225) +2022-11-14 16:49:03,183 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0724) Prec@1 91.000 (88.322) Prec@5 99.000 (99.222) +2022-11-14 16:49:03,190 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0721) Prec@1 91.000 (88.352) Prec@5 100.000 (99.231) +2022-11-14 16:49:03,199 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0720) Prec@1 93.000 (88.402) Prec@5 98.000 (99.217) +2022-11-14 16:49:03,207 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.0723) Prec@1 83.000 (88.344) Prec@5 100.000 (99.226) +2022-11-14 16:49:03,214 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0725) Prec@1 85.000 (88.309) Prec@5 100.000 (99.234) +2022-11-14 16:49:03,222 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0724) Prec@1 92.000 (88.347) Prec@5 100.000 (99.242) +2022-11-14 16:49:03,230 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0723) Prec@1 91.000 (88.375) Prec@5 98.000 (99.229) +2022-11-14 16:49:03,237 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0722) Prec@1 92.000 (88.412) Prec@5 99.000 (99.227) +2022-11-14 16:49:03,245 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0724) Prec@1 86.000 (88.388) Prec@5 98.000 (99.214) +2022-11-14 16:49:03,253 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0728) Prec@1 84.000 (88.343) Prec@5 99.000 (99.212) +2022-11-14 16:49:03,260 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0727) Prec@1 87.000 (88.330) Prec@5 100.000 (99.220) +2022-11-14 16:49:03,316 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:49:03,643 Epoch: [390][0/500] Time 0.024 (0.024) Data 0.247 (0.247) Loss 0.0322 (0.0322) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:03,840 Epoch: [390][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0321 (0.0321) Prec@1 95.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:49:04,028 Epoch: [390][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0222 (0.0288) Prec@1 96.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:49:04,219 Epoch: [390][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0179 (0.0261) Prec@1 98.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:49:04,409 Epoch: [390][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0116 (0.0232) Prec@1 98.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 16:49:04,599 Epoch: [390][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0207 (0.0228) Prec@1 96.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:49:04,796 Epoch: [390][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0089 (0.0208) Prec@1 99.000 (96.429) Prec@5 100.000 (99.857) +2022-11-14 16:49:04,992 Epoch: [390][70/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0262 (0.0215) Prec@1 94.000 (96.125) Prec@5 100.000 (99.875) +2022-11-14 16:49:05,236 Epoch: [390][80/500] Time 0.024 (0.018) Data 0.002 (0.005) Loss 0.0267 (0.0220) Prec@1 96.000 (96.111) Prec@5 100.000 (99.889) +2022-11-14 16:49:05,484 Epoch: [390][90/500] Time 0.022 (0.018) Data 0.002 (0.004) Loss 0.0259 (0.0224) Prec@1 96.000 (96.100) Prec@5 100.000 (99.900) +2022-11-14 16:49:05,732 Epoch: [390][100/500] Time 0.023 (0.018) Data 0.001 (0.004) Loss 0.0143 (0.0217) Prec@1 98.000 (96.273) Prec@5 100.000 (99.909) +2022-11-14 16:49:05,982 Epoch: [390][110/500] Time 0.023 (0.019) Data 0.002 (0.004) Loss 0.0372 (0.0230) Prec@1 95.000 (96.167) Prec@5 100.000 (99.917) +2022-11-14 16:49:06,235 Epoch: [390][120/500] Time 0.024 (0.019) Data 0.002 (0.004) Loss 0.0300 (0.0235) Prec@1 95.000 (96.077) Prec@5 99.000 (99.846) +2022-11-14 16:49:06,486 Epoch: [390][130/500] Time 0.023 (0.019) Data 0.002 (0.004) Loss 0.0330 (0.0242) Prec@1 94.000 (95.929) Prec@5 99.000 (99.786) +2022-11-14 16:49:06,741 Epoch: [390][140/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0361 (0.0250) Prec@1 93.000 (95.733) Prec@5 100.000 (99.800) +2022-11-14 16:49:06,992 Epoch: [390][150/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0113 (0.0241) Prec@1 98.000 (95.875) Prec@5 100.000 (99.812) +2022-11-14 16:49:07,247 Epoch: [390][160/500] Time 0.023 (0.020) Data 0.001 (0.003) Loss 0.0229 (0.0241) Prec@1 97.000 (95.941) Prec@5 100.000 (99.824) +2022-11-14 16:49:07,496 Epoch: [390][170/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0318 (0.0245) Prec@1 95.000 (95.889) Prec@5 100.000 (99.833) +2022-11-14 16:49:07,747 Epoch: [390][180/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0310 (0.0248) Prec@1 94.000 (95.789) Prec@5 100.000 (99.842) +2022-11-14 16:49:07,999 Epoch: [390][190/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0369 (0.0254) Prec@1 94.000 (95.700) Prec@5 100.000 (99.850) +2022-11-14 16:49:08,253 Epoch: [390][200/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0222 (0.0253) Prec@1 97.000 (95.762) Prec@5 100.000 (99.857) +2022-11-14 16:49:08,505 Epoch: [390][210/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0217 (0.0251) Prec@1 96.000 (95.773) Prec@5 99.000 (99.818) +2022-11-14 16:49:08,759 Epoch: [390][220/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0341 (0.0255) Prec@1 96.000 (95.783) Prec@5 99.000 (99.783) +2022-11-14 16:49:09,010 Epoch: [390][230/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0401 (0.0261) Prec@1 94.000 (95.708) Prec@5 100.000 (99.792) +2022-11-14 16:49:09,261 Epoch: [390][240/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0182 (0.0258) Prec@1 97.000 (95.760) Prec@5 100.000 (99.800) +2022-11-14 16:49:09,513 Epoch: [390][250/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0303 (0.0260) Prec@1 94.000 (95.692) Prec@5 100.000 (99.808) +2022-11-14 16:49:09,762 Epoch: [390][260/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0408 (0.0265) Prec@1 93.000 (95.593) Prec@5 99.000 (99.778) +2022-11-14 16:49:10,015 Epoch: [390][270/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0366 (0.0269) Prec@1 94.000 (95.536) Prec@5 100.000 (99.786) +2022-11-14 16:49:10,272 Epoch: [390][280/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0214 (0.0267) Prec@1 94.000 (95.483) Prec@5 100.000 (99.793) +2022-11-14 16:49:10,524 Epoch: [390][290/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0358 (0.0270) Prec@1 94.000 (95.433) Prec@5 100.000 (99.800) +2022-11-14 16:49:10,780 Epoch: [390][300/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0403 (0.0274) Prec@1 94.000 (95.387) Prec@5 99.000 (99.774) +2022-11-14 16:49:11,035 Epoch: [390][310/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0403 (0.0278) Prec@1 93.000 (95.312) Prec@5 99.000 (99.750) +2022-11-14 16:49:11,294 Epoch: [390][320/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0278 (0.0278) Prec@1 94.000 (95.273) Prec@5 100.000 (99.758) +2022-11-14 16:49:11,545 Epoch: [390][330/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0113 (0.0273) Prec@1 99.000 (95.382) Prec@5 100.000 (99.765) +2022-11-14 16:49:11,794 Epoch: [390][340/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0316 (0.0275) Prec@1 94.000 (95.343) Prec@5 100.000 (99.771) +2022-11-14 16:49:12,049 Epoch: [390][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0293 (0.0275) Prec@1 96.000 (95.361) Prec@5 100.000 (99.778) +2022-11-14 16:49:12,308 Epoch: [390][360/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0286 (0.0276) Prec@1 96.000 (95.378) Prec@5 100.000 (99.784) +2022-11-14 16:49:12,562 Epoch: [390][370/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0355 (0.0278) Prec@1 93.000 (95.316) Prec@5 100.000 (99.789) +2022-11-14 16:49:12,815 Epoch: [390][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0176 (0.0275) Prec@1 98.000 (95.385) Prec@5 100.000 (99.795) +2022-11-14 16:49:13,069 Epoch: [390][390/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0574 (0.0282) Prec@1 90.000 (95.250) Prec@5 100.000 (99.800) +2022-11-14 16:49:13,327 Epoch: [390][400/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0239 (0.0281) Prec@1 96.000 (95.268) Prec@5 100.000 (99.805) +2022-11-14 16:49:13,579 Epoch: [390][410/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0247 (0.0281) Prec@1 97.000 (95.310) Prec@5 100.000 (99.810) +2022-11-14 16:49:13,833 Epoch: [390][420/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0283 (0.0281) Prec@1 95.000 (95.302) Prec@5 100.000 (99.814) +2022-11-14 16:49:14,088 Epoch: [390][430/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0083 (0.0276) Prec@1 100.000 (95.409) Prec@5 100.000 (99.818) +2022-11-14 16:49:14,344 Epoch: [390][440/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0257 (0.0276) Prec@1 96.000 (95.422) Prec@5 100.000 (99.822) +2022-11-14 16:49:14,597 Epoch: [390][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0490 (0.0280) Prec@1 92.000 (95.348) Prec@5 100.000 (99.826) +2022-11-14 16:49:14,854 Epoch: [390][460/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0245 (0.0280) Prec@1 96.000 (95.362) Prec@5 100.000 (99.830) +2022-11-14 16:49:15,104 Epoch: [390][470/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0151 (0.0277) Prec@1 97.000 (95.396) Prec@5 100.000 (99.833) +2022-11-14 16:49:15,360 Epoch: [390][480/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0261 (0.0277) Prec@1 96.000 (95.408) Prec@5 100.000 (99.837) +2022-11-14 16:49:15,612 Epoch: [390][490/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0357 (0.0278) Prec@1 95.000 (95.400) Prec@5 100.000 (99.840) +2022-11-14 16:49:15,837 Epoch: [390][499/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0441 (0.0281) Prec@1 92.000 (95.333) Prec@5 100.000 (99.843) +2022-11-14 16:49:16,150 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0561 (0.0561) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:16,163 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0748 (0.0655) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:16,174 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0860 (0.0723) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:16,188 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0681 (0.0713) Prec@1 89.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:49:16,195 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0826 (0.0735) Prec@1 87.000 (88.600) Prec@5 100.000 (99.800) +2022-11-14 16:49:16,202 Test: [5/100] Model Time 0.005 (0.009) Loss Time 0.000 (0.000) Loss 0.0692 (0.0728) Prec@1 88.000 (88.500) Prec@5 99.000 (99.667) +2022-11-14 16:49:16,209 Test: [6/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0721) Prec@1 87.000 (88.286) Prec@5 100.000 (99.714) +2022-11-14 16:49:16,219 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0905 (0.0744) Prec@1 85.000 (87.875) Prec@5 100.000 (99.750) +2022-11-14 16:49:16,226 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0666 (0.0735) Prec@1 89.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 16:49:16,232 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0753) Prec@1 87.000 (87.900) Prec@5 97.000 (99.400) +2022-11-14 16:49:16,239 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0733) Prec@1 92.000 (88.273) Prec@5 100.000 (99.455) +2022-11-14 16:49:16,247 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0730) Prec@1 88.000 (88.250) Prec@5 100.000 (99.500) +2022-11-14 16:49:16,254 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0736) Prec@1 88.000 (88.231) Prec@5 100.000 (99.538) +2022-11-14 16:49:16,262 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0744) Prec@1 87.000 (88.143) Prec@5 99.000 (99.500) +2022-11-14 16:49:16,270 Test: [14/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0668 (0.0739) Prec@1 91.000 (88.333) Prec@5 99.000 (99.467) +2022-11-14 16:49:16,278 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0733) Prec@1 89.000 (88.375) Prec@5 100.000 (99.500) +2022-11-14 16:49:16,285 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0721) Prec@1 93.000 (88.647) Prec@5 99.000 (99.471) +2022-11-14 16:49:16,293 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0733) Prec@1 84.000 (88.389) Prec@5 100.000 (99.500) +2022-11-14 16:49:16,300 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0736) Prec@1 87.000 (88.316) Prec@5 99.000 (99.474) +2022-11-14 16:49:16,308 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0740) Prec@1 88.000 (88.300) Prec@5 97.000 (99.350) +2022-11-14 16:49:16,316 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0737) Prec@1 89.000 (88.333) Prec@5 100.000 (99.381) +2022-11-14 16:49:16,323 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0743) Prec@1 86.000 (88.227) Prec@5 99.000 (99.364) +2022-11-14 16:49:16,331 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1124 (0.0760) Prec@1 83.000 (88.000) Prec@5 100.000 (99.391) +2022-11-14 16:49:16,339 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0750) Prec@1 91.000 (88.125) Prec@5 100.000 (99.417) +2022-11-14 16:49:16,346 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0763) Prec@1 82.000 (87.880) Prec@5 100.000 (99.440) +2022-11-14 16:49:16,354 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0764) Prec@1 88.000 (87.885) Prec@5 98.000 (99.385) +2022-11-14 16:49:16,362 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0753) Prec@1 92.000 (88.037) Prec@5 100.000 (99.407) +2022-11-14 16:49:16,369 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0744) Prec@1 92.000 (88.179) Prec@5 99.000 (99.393) +2022-11-14 16:49:16,377 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 88.000 (88.172) Prec@5 99.000 (99.379) +2022-11-14 16:49:16,384 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0739) Prec@1 91.000 (88.267) Prec@5 100.000 (99.400) +2022-11-14 16:49:16,392 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0736) Prec@1 89.000 (88.290) Prec@5 100.000 (99.419) +2022-11-14 16:49:16,400 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0736) Prec@1 89.000 (88.312) Prec@5 98.000 (99.375) +2022-11-14 16:49:16,407 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0736) Prec@1 89.000 (88.333) Prec@5 99.000 (99.364) +2022-11-14 16:49:16,415 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1081 (0.0746) Prec@1 84.000 (88.206) Prec@5 100.000 (99.382) +2022-11-14 16:49:16,423 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0752) Prec@1 85.000 (88.114) Prec@5 98.000 (99.343) +2022-11-14 16:49:16,430 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0748) Prec@1 89.000 (88.139) Prec@5 100.000 (99.361) +2022-11-14 16:49:16,438 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0748) Prec@1 86.000 (88.081) Prec@5 99.000 (99.351) +2022-11-14 16:49:16,446 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.0757) Prec@1 84.000 (87.974) Prec@5 100.000 (99.368) +2022-11-14 16:49:16,453 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0749) Prec@1 94.000 (88.128) Prec@5 99.000 (99.359) +2022-11-14 16:49:16,461 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0744) Prec@1 91.000 (88.200) Prec@5 100.000 (99.375) +2022-11-14 16:49:16,469 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0749) Prec@1 85.000 (88.122) Prec@5 98.000 (99.341) +2022-11-14 16:49:16,476 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0747) Prec@1 90.000 (88.167) Prec@5 100.000 (99.357) +2022-11-14 16:49:16,484 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0742) Prec@1 89.000 (88.186) Prec@5 100.000 (99.372) +2022-11-14 16:49:16,491 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0739) Prec@1 90.000 (88.227) Prec@5 98.000 (99.341) +2022-11-14 16:49:16,499 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0735) Prec@1 91.000 (88.289) Prec@5 98.000 (99.311) +2022-11-14 16:49:16,507 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0742) Prec@1 84.000 (88.196) Prec@5 100.000 (99.326) +2022-11-14 16:49:16,515 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0740) Prec@1 91.000 (88.255) Prec@5 100.000 (99.340) +2022-11-14 16:49:16,522 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.0749) Prec@1 81.000 (88.104) Prec@5 97.000 (99.292) +2022-11-14 16:49:16,530 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0746) Prec@1 91.000 (88.163) Prec@5 100.000 (99.306) +2022-11-14 16:49:16,537 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0747) Prec@1 88.000 (88.160) Prec@5 99.000 (99.300) +2022-11-14 16:49:16,545 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0743) Prec@1 90.000 (88.196) Prec@5 100.000 (99.314) +2022-11-14 16:49:16,552 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0744) Prec@1 87.000 (88.173) Prec@5 99.000 (99.308) +2022-11-14 16:49:16,560 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0743) Prec@1 89.000 (88.189) Prec@5 100.000 (99.321) +2022-11-14 16:49:16,568 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0740) Prec@1 91.000 (88.241) Prec@5 100.000 (99.333) +2022-11-14 16:49:16,576 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0745) Prec@1 82.000 (88.127) Prec@5 100.000 (99.345) +2022-11-14 16:49:16,583 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0745) Prec@1 88.000 (88.125) Prec@5 99.000 (99.339) +2022-11-14 16:49:16,591 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0741) Prec@1 90.000 (88.158) Prec@5 100.000 (99.351) +2022-11-14 16:49:16,599 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0742) Prec@1 89.000 (88.172) Prec@5 99.000 (99.345) +2022-11-14 16:49:16,607 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0744) Prec@1 87.000 (88.153) Prec@5 100.000 (99.356) +2022-11-14 16:49:16,614 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0746) Prec@1 85.000 (88.100) Prec@5 99.000 (99.350) +2022-11-14 16:49:16,622 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0749) Prec@1 85.000 (88.049) Prec@5 99.000 (99.344) +2022-11-14 16:49:16,629 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0747) Prec@1 89.000 (88.065) Prec@5 99.000 (99.339) +2022-11-14 16:49:16,637 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0745) Prec@1 90.000 (88.095) Prec@5 99.000 (99.333) +2022-11-14 16:49:16,645 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0499 (0.0742) Prec@1 92.000 (88.156) Prec@5 100.000 (99.344) +2022-11-14 16:49:16,652 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0745) Prec@1 85.000 (88.108) Prec@5 100.000 (99.354) +2022-11-14 16:49:16,660 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0745) Prec@1 87.000 (88.091) Prec@5 100.000 (99.364) +2022-11-14 16:49:16,668 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0741) Prec@1 89.000 (88.104) Prec@5 99.000 (99.358) +2022-11-14 16:49:16,675 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0742) Prec@1 88.000 (88.103) Prec@5 99.000 (99.353) +2022-11-14 16:49:16,683 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0741) Prec@1 89.000 (88.116) Prec@5 100.000 (99.362) +2022-11-14 16:49:16,691 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0744) Prec@1 85.000 (88.071) Prec@5 98.000 (99.343) +2022-11-14 16:49:16,698 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0748) Prec@1 84.000 (88.014) Prec@5 100.000 (99.352) +2022-11-14 16:49:16,706 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0746) Prec@1 88.000 (88.014) Prec@5 100.000 (99.361) +2022-11-14 16:49:16,713 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0743) Prec@1 93.000 (88.082) Prec@5 100.000 (99.370) +2022-11-14 16:49:16,721 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0407 (0.0739) Prec@1 94.000 (88.162) Prec@5 100.000 (99.378) +2022-11-14 16:49:16,729 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0743) Prec@1 84.000 (88.107) Prec@5 99.000 (99.373) +2022-11-14 16:49:16,736 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0741) Prec@1 90.000 (88.132) Prec@5 99.000 (99.368) +2022-11-14 16:49:16,744 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0741) Prec@1 87.000 (88.117) Prec@5 100.000 (99.377) +2022-11-14 16:49:16,751 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0745) Prec@1 84.000 (88.064) Prec@5 97.000 (99.346) +2022-11-14 16:49:16,759 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0745) Prec@1 89.000 (88.076) Prec@5 100.000 (99.354) +2022-11-14 16:49:16,766 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0744) Prec@1 88.000 (88.075) Prec@5 100.000 (99.362) +2022-11-14 16:49:16,774 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0744) Prec@1 88.000 (88.074) Prec@5 99.000 (99.358) +2022-11-14 16:49:16,782 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0745) Prec@1 87.000 (88.061) Prec@5 100.000 (99.366) +2022-11-14 16:49:16,789 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0748) Prec@1 86.000 (88.036) Prec@5 99.000 (99.361) +2022-11-14 16:49:16,797 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0748) Prec@1 87.000 (88.024) Prec@5 99.000 (99.357) +2022-11-14 16:49:16,805 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0749) Prec@1 84.000 (87.976) Prec@5 100.000 (99.365) +2022-11-14 16:49:16,812 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0752) Prec@1 84.000 (87.930) Prec@5 98.000 (99.349) +2022-11-14 16:49:16,820 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0751) Prec@1 89.000 (87.943) Prec@5 99.000 (99.345) +2022-11-14 16:49:16,827 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0753) Prec@1 87.000 (87.932) Prec@5 99.000 (99.341) +2022-11-14 16:49:16,835 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0754) Prec@1 82.000 (87.865) Prec@5 99.000 (99.337) +2022-11-14 16:49:16,843 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0754) Prec@1 91.000 (87.900) Prec@5 98.000 (99.322) +2022-11-14 16:49:16,850 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0754) Prec@1 88.000 (87.901) Prec@5 100.000 (99.330) +2022-11-14 16:49:16,858 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0751) Prec@1 92.000 (87.946) Prec@5 99.000 (99.326) +2022-11-14 16:49:16,865 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0753) Prec@1 86.000 (87.925) Prec@5 100.000 (99.333) +2022-11-14 16:49:16,873 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0753) Prec@1 90.000 (87.947) Prec@5 100.000 (99.340) +2022-11-14 16:49:16,881 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0752) Prec@1 88.000 (87.947) Prec@5 100.000 (99.347) +2022-11-14 16:49:16,888 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0751) Prec@1 90.000 (87.969) Prec@5 99.000 (99.344) +2022-11-14 16:49:16,896 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0428 (0.0748) Prec@1 93.000 (88.021) Prec@5 98.000 (99.330) +2022-11-14 16:49:16,903 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0748) Prec@1 89.000 (88.031) Prec@5 98.000 (99.316) +2022-11-14 16:49:16,911 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0750) Prec@1 85.000 (88.000) Prec@5 100.000 (99.323) +2022-11-14 16:49:16,918 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0750) Prec@1 87.000 (87.990) Prec@5 100.000 (99.330) +2022-11-14 16:49:16,989 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:49:17,338 Epoch: [391][0/500] Time 0.025 (0.025) Data 0.266 (0.266) Loss 0.0276 (0.0276) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:17,538 Epoch: [391][10/500] Time 0.017 (0.018) Data 0.002 (0.026) Loss 0.0255 (0.0266) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:49:17,730 Epoch: [391][20/500] Time 0.019 (0.018) Data 0.002 (0.014) Loss 0.0468 (0.0333) Prec@1 91.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:17,934 Epoch: [391][30/500] Time 0.022 (0.018) Data 0.001 (0.010) Loss 0.0129 (0.0282) Prec@1 97.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:49:18,194 Epoch: [391][40/500] Time 0.023 (0.019) Data 0.002 (0.008) Loss 0.0187 (0.0263) Prec@1 97.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:49:18,457 Epoch: [391][50/500] Time 0.022 (0.020) Data 0.002 (0.007) Loss 0.0123 (0.0240) Prec@1 98.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:49:18,721 Epoch: [391][60/500] Time 0.024 (0.020) Data 0.002 (0.006) Loss 0.0288 (0.0247) Prec@1 95.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 16:49:18,985 Epoch: [391][70/500] Time 0.025 (0.021) Data 0.001 (0.005) Loss 0.0387 (0.0264) Prec@1 94.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 16:49:19,250 Epoch: [391][80/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0280 (0.0266) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:49:19,510 Epoch: [391][90/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0260 (0.0265) Prec@1 94.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:49:19,771 Epoch: [391][100/500] Time 0.025 (0.021) Data 0.002 (0.004) Loss 0.0295 (0.0268) Prec@1 94.000 (95.091) Prec@5 100.000 (100.000) +2022-11-14 16:49:20,032 Epoch: [391][110/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0297 (0.0270) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:49:20,297 Epoch: [391][120/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0236 (0.0268) Prec@1 96.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 16:49:20,561 Epoch: [391][130/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0378 (0.0276) Prec@1 93.000 (95.143) Prec@5 99.000 (99.929) +2022-11-14 16:49:20,825 Epoch: [391][140/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0285 (0.0276) Prec@1 97.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 16:49:21,093 Epoch: [391][150/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0465 (0.0288) Prec@1 92.000 (95.062) Prec@5 99.000 (99.875) +2022-11-14 16:49:21,354 Epoch: [391][160/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0220 (0.0284) Prec@1 97.000 (95.176) Prec@5 100.000 (99.882) +2022-11-14 16:49:21,614 Epoch: [391][170/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0374 (0.0289) Prec@1 94.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:49:21,875 Epoch: [391][180/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0199 (0.0284) Prec@1 99.000 (95.316) Prec@5 100.000 (99.895) +2022-11-14 16:49:22,141 Epoch: [391][190/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0157 (0.0278) Prec@1 98.000 (95.450) Prec@5 100.000 (99.900) +2022-11-14 16:49:22,403 Epoch: [391][200/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0319 (0.0280) Prec@1 95.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 16:49:22,663 Epoch: [391][210/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0360 (0.0284) Prec@1 95.000 (95.409) Prec@5 100.000 (99.909) +2022-11-14 16:49:22,923 Epoch: [391][220/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0449 (0.0291) Prec@1 94.000 (95.348) Prec@5 100.000 (99.913) +2022-11-14 16:49:23,185 Epoch: [391][230/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0260 (0.0290) Prec@1 97.000 (95.417) Prec@5 98.000 (99.833) +2022-11-14 16:49:23,449 Epoch: [391][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0225 (0.0287) Prec@1 95.000 (95.400) Prec@5 100.000 (99.840) +2022-11-14 16:49:23,713 Epoch: [391][250/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0255 (0.0286) Prec@1 95.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:49:23,977 Epoch: [391][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0185 (0.0282) Prec@1 97.000 (95.444) Prec@5 100.000 (99.852) +2022-11-14 16:49:24,241 Epoch: [391][270/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0413 (0.0287) Prec@1 93.000 (95.357) Prec@5 99.000 (99.821) +2022-11-14 16:49:24,505 Epoch: [391][280/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0293 (0.0287) Prec@1 94.000 (95.310) Prec@5 100.000 (99.828) +2022-11-14 16:49:24,770 Epoch: [391][290/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0317 (0.0288) Prec@1 95.000 (95.300) Prec@5 100.000 (99.833) +2022-11-14 16:49:25,033 Epoch: [391][300/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0291 (0.0288) Prec@1 95.000 (95.290) Prec@5 100.000 (99.839) +2022-11-14 16:49:25,296 Epoch: [391][310/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0287 (0.0288) Prec@1 94.000 (95.250) Prec@5 100.000 (99.844) +2022-11-14 16:49:25,560 Epoch: [391][320/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0218 (0.0286) Prec@1 96.000 (95.273) Prec@5 99.000 (99.818) +2022-11-14 16:49:25,824 Epoch: [391][330/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0293 (0.0286) Prec@1 97.000 (95.324) Prec@5 100.000 (99.824) +2022-11-14 16:49:26,093 Epoch: [391][340/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0307 (0.0287) Prec@1 95.000 (95.314) Prec@5 100.000 (99.829) +2022-11-14 16:49:26,354 Epoch: [391][350/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0073 (0.0281) Prec@1 99.000 (95.417) Prec@5 100.000 (99.833) +2022-11-14 16:49:26,614 Epoch: [391][360/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0444 (0.0285) Prec@1 94.000 (95.378) Prec@5 100.000 (99.838) +2022-11-14 16:49:26,876 Epoch: [391][370/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0358 (0.0287) Prec@1 94.000 (95.342) Prec@5 100.000 (99.842) +2022-11-14 16:49:27,140 Epoch: [391][380/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0632 (0.0296) Prec@1 90.000 (95.205) Prec@5 99.000 (99.821) +2022-11-14 16:49:27,400 Epoch: [391][390/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0159 (0.0292) Prec@1 98.000 (95.275) Prec@5 100.000 (99.825) +2022-11-14 16:49:27,662 Epoch: [391][400/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0281 (0.0292) Prec@1 96.000 (95.293) Prec@5 100.000 (99.829) +2022-11-14 16:49:27,925 Epoch: [391][410/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0320 (0.0293) Prec@1 95.000 (95.286) Prec@5 100.000 (99.833) +2022-11-14 16:49:28,192 Epoch: [391][420/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0678 (0.0302) Prec@1 89.000 (95.140) Prec@5 98.000 (99.791) +2022-11-14 16:49:28,458 Epoch: [391][430/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0192 (0.0299) Prec@1 98.000 (95.205) Prec@5 100.000 (99.795) +2022-11-14 16:49:28,721 Epoch: [391][440/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0546 (0.0305) Prec@1 91.000 (95.111) Prec@5 99.000 (99.778) +2022-11-14 16:49:28,983 Epoch: [391][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0239 (0.0303) Prec@1 97.000 (95.152) Prec@5 100.000 (99.783) +2022-11-14 16:49:29,248 Epoch: [391][460/500] Time 0.024 (0.023) Data 0.003 (0.002) Loss 0.0396 (0.0305) Prec@1 93.000 (95.106) Prec@5 100.000 (99.787) +2022-11-14 16:49:29,510 Epoch: [391][470/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0441 (0.0308) Prec@1 91.000 (95.021) Prec@5 100.000 (99.792) +2022-11-14 16:49:29,777 Epoch: [391][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0342 (0.0309) Prec@1 94.000 (95.000) Prec@5 99.000 (99.776) +2022-11-14 16:49:30,039 Epoch: [391][490/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0318 (0.0309) Prec@1 96.000 (95.020) Prec@5 100.000 (99.780) +2022-11-14 16:49:30,280 Epoch: [391][499/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0230 (0.0307) Prec@1 98.000 (95.078) Prec@5 100.000 (99.784) +2022-11-14 16:49:30,579 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0726 (0.0726) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:30,586 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0627 (0.0676) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:30,593 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0697) Prec@1 86.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 16:49:30,604 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0677) Prec@1 91.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 16:49:30,611 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0700) Prec@1 86.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 16:49:30,618 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0446 (0.0658) Prec@1 93.000 (88.667) Prec@5 100.000 (99.833) +2022-11-14 16:49:30,624 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0670) Prec@1 88.000 (88.571) Prec@5 100.000 (99.857) +2022-11-14 16:49:30,633 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0694) Prec@1 86.000 (88.250) Prec@5 98.000 (99.625) +2022-11-14 16:49:30,640 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0696) Prec@1 89.000 (88.333) Prec@5 98.000 (99.444) +2022-11-14 16:49:30,648 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0709) Prec@1 89.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 16:49:30,656 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0703) Prec@1 90.000 (88.545) Prec@5 100.000 (99.455) +2022-11-14 16:49:30,664 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0709) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:49:30,672 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0711) Prec@1 88.000 (88.462) Prec@5 100.000 (99.538) +2022-11-14 16:49:30,680 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0701) Prec@1 90.000 (88.571) Prec@5 99.000 (99.500) +2022-11-14 16:49:30,689 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0714) Prec@1 83.000 (88.200) Prec@5 100.000 (99.533) +2022-11-14 16:49:30,697 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0714) Prec@1 88.000 (88.188) Prec@5 100.000 (99.562) +2022-11-14 16:49:30,705 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0703) Prec@1 91.000 (88.353) Prec@5 99.000 (99.529) +2022-11-14 16:49:30,713 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0726) Prec@1 83.000 (88.056) Prec@5 99.000 (99.500) +2022-11-14 16:49:30,721 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0726) Prec@1 85.000 (87.895) Prec@5 98.000 (99.421) +2022-11-14 16:49:30,729 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0739) Prec@1 88.000 (87.900) Prec@5 97.000 (99.300) +2022-11-14 16:49:30,737 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0741) Prec@1 87.000 (87.857) Prec@5 100.000 (99.333) +2022-11-14 16:49:30,745 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0744) Prec@1 88.000 (87.864) Prec@5 100.000 (99.364) +2022-11-14 16:49:30,753 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0756) Prec@1 86.000 (87.783) Prec@5 98.000 (99.304) +2022-11-14 16:49:30,762 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0753) 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16:49:30,818 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0741) Prec@1 89.000 (88.032) Prec@5 99.000 (99.258) +2022-11-14 16:49:30,827 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0740) Prec@1 89.000 (88.062) Prec@5 99.000 (99.250) +2022-11-14 16:49:30,835 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0740) Prec@1 87.000 (88.030) Prec@5 100.000 (99.273) +2022-11-14 16:49:30,843 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0739) Prec@1 87.000 (88.000) Prec@5 100.000 (99.294) +2022-11-14 16:49:30,851 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0740) Prec@1 89.000 (88.029) Prec@5 100.000 (99.314) +2022-11-14 16:49:30,858 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0737) Prec@1 92.000 (88.139) Prec@5 100.000 (99.333) +2022-11-14 16:49:30,866 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0738) Prec@1 89.000 (88.162) Prec@5 99.000 (99.324) +2022-11-14 16:49:30,874 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0742) Prec@1 85.000 (88.079) Prec@5 99.000 (99.316) +2022-11-14 16:49:30,882 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0737) Prec@1 93.000 (88.205) Prec@5 99.000 (99.308) +2022-11-14 16:49:30,890 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0734) Prec@1 91.000 (88.275) Prec@5 99.000 (99.300) +2022-11-14 16:49:30,898 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0738) Prec@1 86.000 (88.220) Prec@5 97.000 (99.244) +2022-11-14 16:49:30,906 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0739) Prec@1 89.000 (88.238) Prec@5 99.000 (99.238) +2022-11-14 16:49:30,914 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0732) Prec@1 93.000 (88.349) Prec@5 99.000 (99.233) +2022-11-14 16:49:30,922 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0727) Prec@1 92.000 (88.432) Prec@5 99.000 (99.227) +2022-11-14 16:49:30,930 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0724) Prec@1 89.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 16:49:30,938 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0731) Prec@1 83.000 (88.326) Prec@5 99.000 (99.217) +2022-11-14 16:49:30,946 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0730) Prec@1 86.000 (88.277) Prec@5 100.000 (99.234) +2022-11-14 16:49:30,954 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0732) Prec@1 89.000 (88.292) Prec@5 96.000 (99.167) +2022-11-14 16:49:30,962 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0731) Prec@1 90.000 (88.327) Prec@5 100.000 (99.184) +2022-11-14 16:49:30,970 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0735) Prec@1 85.000 (88.260) Prec@5 99.000 (99.180) +2022-11-14 16:49:30,978 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0733) Prec@1 91.000 (88.314) Prec@5 100.000 (99.196) +2022-11-14 16:49:30,986 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0733) Prec@1 87.000 (88.288) Prec@5 100.000 (99.212) +2022-11-14 16:49:30,994 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0732) Prec@1 89.000 (88.302) Prec@5 99.000 (99.208) +2022-11-14 16:49:31,002 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0730) Prec@1 88.000 (88.296) Prec@5 99.000 (99.204) +2022-11-14 16:49:31,010 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0734) Prec@1 84.000 (88.218) Prec@5 100.000 (99.218) +2022-11-14 16:49:31,019 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 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(0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0725) Prec@1 90.000 (88.290) Prec@5 99.000 (99.232) +2022-11-14 16:49:31,137 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0727) Prec@1 85.000 (88.243) Prec@5 100.000 (99.243) +2022-11-14 16:49:31,146 Test: [70/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0729) Prec@1 87.000 (88.225) Prec@5 99.000 (99.239) +2022-11-14 16:49:31,155 Test: [71/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0727) Prec@1 93.000 (88.292) Prec@5 100.000 (99.250) +2022-11-14 16:49:31,164 Test: [72/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0724) Prec@1 91.000 (88.329) Prec@5 99.000 (99.247) +2022-11-14 16:49:31,173 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0332 (0.0719) Prec@1 95.000 (88.419) Prec@5 100.000 (99.257) +2022-11-14 16:49:31,181 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0724) Prec@1 83.000 (88.347) Prec@5 100.000 (99.267) +2022-11-14 16:49:31,190 Test: [75/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0724) Prec@1 88.000 (88.342) Prec@5 100.000 (99.276) +2022-11-14 16:49:31,198 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0725) Prec@1 89.000 (88.351) Prec@5 99.000 (99.273) +2022-11-14 16:49:31,206 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1155 (0.0730) Prec@1 82.000 (88.269) Prec@5 100.000 (99.282) +2022-11-14 16:49:31,214 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 87.000 (88.253) Prec@5 99.000 (99.278) +2022-11-14 16:49:31,222 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0730) Prec@1 89.000 (88.263) Prec@5 99.000 (99.275) +2022-11-14 16:49:31,230 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0730) Prec@1 89.000 (88.272) Prec@5 99.000 (99.272) +2022-11-14 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Time 0.000 (0.000) Loss 0.0616 (0.0732) Prec@1 91.000 (88.261) Prec@5 99.000 (99.295) +2022-11-14 16:49:31,295 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0729) Prec@1 90.000 (88.281) Prec@5 100.000 (99.303) +2022-11-14 16:49:31,303 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0730) Prec@1 87.000 (88.267) Prec@5 99.000 (99.300) +2022-11-14 16:49:31,311 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0729) Prec@1 91.000 (88.297) Prec@5 99.000 (99.297) +2022-11-14 16:49:31,319 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0479 (0.0726) Prec@1 93.000 (88.348) Prec@5 99.000 (99.293) +2022-11-14 16:49:31,326 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0729) Prec@1 85.000 (88.312) Prec@5 100.000 (99.301) +2022-11-14 16:49:31,334 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0728) Prec@1 90.000 (88.330) Prec@5 99.000 (99.298) +2022-11-14 16:49:31,342 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0728) Prec@1 87.000 (88.316) Prec@5 99.000 (99.295) +2022-11-14 16:49:31,349 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0726) Prec@1 90.000 (88.333) Prec@5 99.000 (99.292) +2022-11-14 16:49:31,357 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0724) Prec@1 92.000 (88.371) Prec@5 98.000 (99.278) +2022-11-14 16:49:31,365 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0727) Prec@1 83.000 (88.316) Prec@5 100.000 (99.286) +2022-11-14 16:49:31,372 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0729) Prec@1 88.000 (88.313) Prec@5 98.000 (99.273) +2022-11-14 16:49:31,380 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0730) Prec@1 86.000 (88.290) Prec@5 100.000 (99.280) +2022-11-14 16:49:31,449 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:49:31,788 Epoch: [392][0/500] Time 0.028 (0.028) Data 0.254 (0.254) Loss 0.0203 (0.0203) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:31,999 Epoch: [392][10/500] Time 0.018 (0.019) Data 0.001 (0.025) Loss 0.0237 (0.0220) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:49:32,196 Epoch: [392][20/500] Time 0.015 (0.018) Data 0.002 (0.014) Loss 0.0332 (0.0257) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:49:32,392 Epoch: [392][30/500] Time 0.018 (0.018) Data 0.002 (0.010) Loss 0.0166 (0.0234) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:49:32,632 Epoch: [392][40/500] Time 0.025 (0.019) Data 0.001 (0.008) Loss 0.0370 (0.0262) Prec@1 93.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:49:32,895 Epoch: [392][50/500] Time 0.025 (0.020) Data 0.002 (0.007) Loss 0.0191 (0.0250) Prec@1 97.000 (95.500) Prec@5 99.000 (99.833) +2022-11-14 16:49:33,166 Epoch: [392][60/500] Time 0.029 (0.020) Data 0.002 (0.006) Loss 0.0121 (0.0231) Prec@1 99.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 16:49:33,425 Epoch: [392][70/500] Time 0.024 (0.021) Data 0.002 (0.005) Loss 0.0197 (0.0227) Prec@1 97.000 (96.125) Prec@5 100.000 (99.875) +2022-11-14 16:49:33,689 Epoch: [392][80/500] Time 0.029 (0.021) Data 0.002 (0.005) Loss 0.0251 (0.0230) Prec@1 96.000 (96.111) Prec@5 100.000 (99.889) +2022-11-14 16:49:33,949 Epoch: [392][90/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0366 (0.0243) Prec@1 95.000 (96.000) Prec@5 100.000 (99.900) +2022-11-14 16:49:34,211 Epoch: [392][100/500] Time 0.029 (0.021) Data 0.001 (0.004) Loss 0.0279 (0.0247) Prec@1 94.000 (95.818) Prec@5 100.000 (99.909) +2022-11-14 16:49:34,471 Epoch: [392][110/500] Time 0.023 (0.022) Data 0.003 (0.004) Loss 0.0242 (0.0246) Prec@1 97.000 (95.917) Prec@5 100.000 (99.917) +2022-11-14 16:49:34,735 Epoch: [392][120/500] Time 0.028 (0.022) Data 0.002 (0.004) Loss 0.0153 (0.0239) Prec@1 98.000 (96.077) Prec@5 100.000 (99.923) +2022-11-14 16:49:34,999 Epoch: [392][130/500] Time 0.023 (0.022) Data 0.002 (0.004) Loss 0.0276 (0.0242) Prec@1 96.000 (96.071) Prec@5 100.000 (99.929) +2022-11-14 16:49:35,262 Epoch: [392][140/500] Time 0.028 (0.022) Data 0.001 (0.004) Loss 0.0244 (0.0242) Prec@1 95.000 (96.000) Prec@5 100.000 (99.933) +2022-11-14 16:49:35,526 Epoch: [392][150/500] Time 0.023 (0.022) Data 0.001 (0.003) Loss 0.0194 (0.0239) Prec@1 99.000 (96.188) Prec@5 100.000 (99.938) +2022-11-14 16:49:35,789 Epoch: [392][160/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0180 (0.0235) Prec@1 98.000 (96.294) Prec@5 100.000 (99.941) +2022-11-14 16:49:36,049 Epoch: [392][170/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0154 (0.0231) Prec@1 98.000 (96.389) Prec@5 100.000 (99.944) +2022-11-14 16:49:36,314 Epoch: [392][180/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0348 (0.0237) Prec@1 94.000 (96.263) Prec@5 100.000 (99.947) +2022-11-14 16:49:36,569 Epoch: [392][190/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0342 (0.0242) Prec@1 93.000 (96.100) Prec@5 100.000 (99.950) +2022-11-14 16:49:36,829 Epoch: [392][200/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0517 (0.0255) Prec@1 91.000 (95.857) Prec@5 100.000 (99.952) +2022-11-14 16:49:37,096 Epoch: [392][210/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0235 (0.0254) Prec@1 96.000 (95.864) Prec@5 100.000 (99.955) +2022-11-14 16:49:37,355 Epoch: [392][220/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0329 (0.0258) Prec@1 95.000 (95.826) Prec@5 99.000 (99.913) +2022-11-14 16:49:37,620 Epoch: [392][230/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0343 (0.0261) Prec@1 95.000 (95.792) Prec@5 100.000 (99.917) +2022-11-14 16:49:37,884 Epoch: [392][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0167 (0.0257) Prec@1 98.000 (95.880) Prec@5 100.000 (99.920) +2022-11-14 16:49:38,150 Epoch: [392][250/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0600 (0.0271) Prec@1 89.000 (95.615) Prec@5 99.000 (99.885) +2022-11-14 16:49:38,411 Epoch: [392][260/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0285 (0.0271) Prec@1 95.000 (95.593) Prec@5 100.000 (99.889) +2022-11-14 16:49:38,676 Epoch: [392][270/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0275 (0.0271) Prec@1 95.000 (95.571) Prec@5 100.000 (99.893) +2022-11-14 16:49:38,940 Epoch: [392][280/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0326 (0.0273) Prec@1 94.000 (95.517) Prec@5 100.000 (99.897) +2022-11-14 16:49:39,201 Epoch: [392][290/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0365 (0.0276) Prec@1 95.000 (95.500) Prec@5 99.000 (99.867) +2022-11-14 16:49:39,463 Epoch: [392][300/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0352 (0.0279) Prec@1 96.000 (95.516) Prec@5 100.000 (99.871) +2022-11-14 16:49:39,722 Epoch: [392][310/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0327 (0.0280) Prec@1 95.000 (95.500) Prec@5 100.000 (99.875) +2022-11-14 16:49:39,987 Epoch: [392][320/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0129 (0.0276) Prec@1 98.000 (95.576) Prec@5 100.000 (99.879) +2022-11-14 16:49:40,252 Epoch: [392][330/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0226 (0.0274) Prec@1 96.000 (95.588) Prec@5 100.000 (99.882) +2022-11-14 16:49:40,513 Epoch: [392][340/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0352 (0.0276) Prec@1 95.000 (95.571) Prec@5 100.000 (99.886) +2022-11-14 16:49:40,775 Epoch: [392][350/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0792 (0.0291) Prec@1 88.000 (95.361) Prec@5 100.000 (99.889) +2022-11-14 16:49:41,037 Epoch: [392][360/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0440 (0.0295) Prec@1 94.000 (95.324) Prec@5 100.000 (99.892) +2022-11-14 16:49:41,304 Epoch: [392][370/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0535 (0.0301) Prec@1 92.000 (95.237) Prec@5 100.000 (99.895) +2022-11-14 16:49:41,567 Epoch: [392][380/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0163 (0.0298) Prec@1 98.000 (95.308) Prec@5 100.000 (99.897) +2022-11-14 16:49:41,832 Epoch: [392][390/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0188 (0.0295) Prec@1 97.000 (95.350) Prec@5 100.000 (99.900) +2022-11-14 16:49:42,096 Epoch: [392][400/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0384 (0.0297) Prec@1 93.000 (95.293) Prec@5 99.000 (99.878) +2022-11-14 16:49:42,356 Epoch: [392][410/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0416 (0.0300) Prec@1 93.000 (95.238) Prec@5 100.000 (99.881) +2022-11-14 16:49:42,616 Epoch: [392][420/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0320 (0.0300) Prec@1 95.000 (95.233) Prec@5 100.000 (99.884) +2022-11-14 16:49:42,877 Epoch: [392][430/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0265 (0.0299) Prec@1 97.000 (95.273) Prec@5 100.000 (99.886) +2022-11-14 16:49:43,143 Epoch: [392][440/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0382 (0.0301) Prec@1 91.000 (95.178) Prec@5 100.000 (99.889) +2022-11-14 16:49:43,406 Epoch: [392][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0644 (0.0309) Prec@1 89.000 (95.043) Prec@5 100.000 (99.891) +2022-11-14 16:49:43,671 Epoch: [392][460/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0319 (0.0309) Prec@1 96.000 (95.064) Prec@5 100.000 (99.894) +2022-11-14 16:49:43,934 Epoch: [392][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0459 (0.0312) Prec@1 91.000 (94.979) Prec@5 100.000 (99.896) +2022-11-14 16:49:44,200 Epoch: [392][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0249 (0.0311) Prec@1 94.000 (94.959) Prec@5 100.000 (99.898) +2022-11-14 16:49:44,464 Epoch: [392][490/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0414 (0.0313) Prec@1 93.000 (94.920) Prec@5 99.000 (99.880) +2022-11-14 16:49:44,702 Epoch: [392][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0470 (0.0316) Prec@1 91.000 (94.843) Prec@5 98.000 (99.843) +2022-11-14 16:49:45,011 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0792 (0.0792) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:45,018 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0679 (0.0735) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:45,027 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0703) Prec@1 88.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 16:49:45,037 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0702) Prec@1 89.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 16:49:45,044 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0730) Prec@1 86.000 (87.400) Prec@5 99.000 (99.600) +2022-11-14 16:49:45,051 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0521 (0.0695) Prec@1 93.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:49:45,058 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0701) Prec@1 89.000 (88.429) Prec@5 100.000 (99.714) +2022-11-14 16:49:45,066 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0726) Prec@1 85.000 (88.000) Prec@5 99.000 (99.625) +2022-11-14 16:49:45,072 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0723) Prec@1 88.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:49:45,080 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0739) Prec@1 88.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 16:49:45,088 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0349 (0.0703) Prec@1 96.000 (88.727) Prec@5 100.000 (99.636) +2022-11-14 16:49:45,095 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0722) Prec@1 85.000 (88.417) Prec@5 100.000 (99.667) +2022-11-14 16:49:45,103 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0717) Prec@1 89.000 (88.462) Prec@5 100.000 (99.692) +2022-11-14 16:49:45,110 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0719) Prec@1 89.000 (88.500) Prec@5 97.000 (99.500) +2022-11-14 16:49:45,118 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0722) Prec@1 90.000 (88.600) Prec@5 99.000 (99.467) +2022-11-14 16:49:45,125 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0721) Prec@1 87.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 16:49:45,133 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0443 (0.0705) Prec@1 94.000 (88.824) Prec@5 99.000 (99.353) +2022-11-14 16:49:45,140 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1108 (0.0727) Prec@1 83.000 (88.500) Prec@5 100.000 (99.389) +2022-11-14 16:49:45,148 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0920 (0.0737) Prec@1 85.000 (88.316) Prec@5 100.000 (99.421) +2022-11-14 16:49:45,156 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1002 (0.0751) Prec@1 81.000 (87.950) Prec@5 97.000 (99.300) +2022-11-14 16:49:45,163 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0747) Prec@1 88.000 (87.952) Prec@5 100.000 (99.333) +2022-11-14 16:49:45,171 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0755) Prec@1 85.000 (87.818) Prec@5 99.000 (99.318) +2022-11-14 16:49:45,178 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0759) Prec@1 87.000 (87.783) Prec@5 100.000 (99.348) +2022-11-14 16:49:45,186 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0760) Prec@1 86.000 (87.708) Prec@5 98.000 (99.292) +2022-11-14 16:49:45,193 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0978 (0.0769) Prec@1 83.000 (87.520) Prec@5 100.000 (99.320) +2022-11-14 16:49:45,201 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0770) Prec@1 87.000 (87.500) Prec@5 99.000 (99.308) +2022-11-14 16:49:45,208 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0793 (0.0771) Prec@1 89.000 (87.556) Prec@5 100.000 (99.333) +2022-11-14 16:49:45,216 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0765) Prec@1 90.000 (87.643) Prec@5 100.000 (99.357) +2022-11-14 16:49:45,223 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0762) Prec@1 89.000 (87.690) Prec@5 98.000 (99.310) +2022-11-14 16:49:45,231 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0759) Prec@1 91.000 (87.800) Prec@5 99.000 (99.300) +2022-11-14 16:49:45,238 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0758) Prec@1 89.000 (87.839) Prec@5 99.000 (99.290) +2022-11-14 16:49:45,246 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0912 (0.0763) Prec@1 85.000 (87.750) Prec@5 99.000 (99.281) +2022-11-14 16:49:45,253 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0762) Prec@1 87.000 (87.727) Prec@5 100.000 (99.303) +2022-11-14 16:49:45,261 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1034 (0.0770) Prec@1 82.000 (87.559) Prec@5 100.000 (99.324) +2022-11-14 16:49:45,268 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0772) Prec@1 86.000 (87.514) Prec@5 99.000 (99.314) +2022-11-14 16:49:45,276 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0567 (0.0766) Prec@1 91.000 (87.611) Prec@5 100.000 (99.333) +2022-11-14 16:49:45,284 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0765) Prec@1 89.000 (87.649) Prec@5 98.000 (99.297) +2022-11-14 16:49:45,291 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0770) Prec@1 84.000 (87.553) Prec@5 100.000 (99.316) +2022-11-14 16:49:45,299 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0490 (0.0763) Prec@1 94.000 (87.718) Prec@5 99.000 (99.308) +2022-11-14 16:49:45,306 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0814 (0.0764) Prec@1 88.000 (87.725) Prec@5 99.000 (99.300) +2022-11-14 16:49:45,313 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0800 (0.0765) Prec@1 87.000 (87.707) Prec@5 99.000 (99.293) +2022-11-14 16:49:45,321 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0763) Prec@1 90.000 (87.762) Prec@5 99.000 (99.286) +2022-11-14 16:49:45,329 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0494 (0.0757) Prec@1 92.000 (87.860) Prec@5 99.000 (99.279) +2022-11-14 16:49:45,336 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0599 (0.0753) Prec@1 90.000 (87.909) Prec@5 98.000 (99.250) +2022-11-14 16:49:45,343 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0486 (0.0747) Prec@1 92.000 (88.000) Prec@5 98.000 (99.222) +2022-11-14 16:49:45,351 Test: [45/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0750) Prec@1 87.000 (87.978) Prec@5 99.000 (99.217) +2022-11-14 16:49:45,359 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0562 (0.0746) Prec@1 91.000 (88.043) Prec@5 100.000 (99.234) +2022-11-14 16:49:45,366 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0877 (0.0749) Prec@1 87.000 (88.021) Prec@5 98.000 (99.208) +2022-11-14 16:49:45,374 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0512 (0.0744) Prec@1 91.000 (88.082) Prec@5 100.000 (99.224) +2022-11-14 16:49:45,381 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1080 (0.0750) Prec@1 84.000 (88.000) Prec@5 99.000 (99.220) +2022-11-14 16:49:45,389 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0695 (0.0749) Prec@1 90.000 (88.039) Prec@5 100.000 (99.235) +2022-11-14 16:49:45,398 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0815 (0.0751) Prec@1 86.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 16:49:45,405 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0893 (0.0753) Prec@1 85.000 (87.943) Prec@5 99.000 (99.245) +2022-11-14 16:49:45,413 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0915 (0.0756) Prec@1 88.000 (87.944) Prec@5 96.000 (99.185) +2022-11-14 16:49:45,420 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0844 (0.0758) Prec@1 85.000 (87.891) Prec@5 100.000 (99.200) +2022-11-14 16:49:45,428 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0681 (0.0757) Prec@1 90.000 (87.929) Prec@5 99.000 (99.196) +2022-11-14 16:49:45,436 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0772 (0.0757) Prec@1 86.000 (87.895) Prec@5 99.000 (99.193) +2022-11-14 16:49:45,443 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0756) Prec@1 90.000 (87.931) Prec@5 99.000 (99.190) +2022-11-14 16:49:45,451 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0915 (0.0759) Prec@1 84.000 (87.864) Prec@5 100.000 (99.203) +2022-11-14 16:49:45,458 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0758) Prec@1 87.000 (87.850) Prec@5 99.000 (99.200) +2022-11-14 16:49:45,466 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0613 (0.0756) Prec@1 91.000 (87.902) Prec@5 98.000 (99.180) +2022-11-14 16:49:45,474 Test: [61/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0754) Prec@1 89.000 (87.919) Prec@5 99.000 (99.177) +2022-11-14 16:49:45,482 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0753) Prec@1 89.000 (87.937) Prec@5 100.000 (99.190) +2022-11-14 16:49:45,489 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0452 (0.0748) Prec@1 92.000 (88.000) Prec@5 99.000 (99.188) +2022-11-14 16:49:45,497 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0777 (0.0748) Prec@1 87.000 (87.985) Prec@5 100.000 (99.200) +2022-11-14 16:49:45,504 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0803 (0.0749) Prec@1 87.000 (87.970) Prec@5 98.000 (99.182) +2022-11-14 16:49:45,512 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0427 (0.0744) Prec@1 93.000 (88.045) Prec@5 99.000 (99.179) +2022-11-14 16:49:45,520 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0585 (0.0742) Prec@1 92.000 (88.103) Prec@5 98.000 (99.162) +2022-11-14 16:49:45,527 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0741) Prec@1 90.000 (88.130) Prec@5 99.000 (99.159) +2022-11-14 16:49:45,535 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0888 (0.0743) Prec@1 89.000 (88.143) Prec@5 100.000 (99.171) +2022-11-14 16:49:45,542 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1003 (0.0747) Prec@1 85.000 (88.099) Prec@5 97.000 (99.141) +2022-11-14 16:49:45,550 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0724 (0.0746) Prec@1 87.000 (88.083) Prec@5 100.000 (99.153) +2022-11-14 16:49:45,557 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0468 (0.0743) Prec@1 92.000 (88.137) Prec@5 99.000 (99.151) +2022-11-14 16:49:45,565 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0414 (0.0738) Prec@1 92.000 (88.189) Prec@5 100.000 (99.162) +2022-11-14 16:49:45,573 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1231 (0.0745) Prec@1 79.000 (88.067) Prec@5 99.000 (99.160) +2022-11-14 16:49:45,580 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0743) Prec@1 92.000 (88.118) Prec@5 100.000 (99.171) +2022-11-14 16:49:45,588 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0907 (0.0745) Prec@1 84.000 (88.065) Prec@5 99.000 (99.169) +2022-11-14 16:49:45,595 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1188 (0.0750) Prec@1 81.000 (87.974) Prec@5 98.000 (99.154) +2022-11-14 16:49:45,603 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0750) Prec@1 88.000 (87.975) Prec@5 100.000 (99.165) +2022-11-14 16:49:45,611 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0558 (0.0748) Prec@1 93.000 (88.037) Prec@5 99.000 (99.162) +2022-11-14 16:49:45,618 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0864 (0.0749) Prec@1 88.000 (88.037) Prec@5 97.000 (99.136) +2022-11-14 16:49:45,626 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0890 (0.0751) Prec@1 86.000 (88.012) Prec@5 99.000 (99.134) +2022-11-14 16:49:45,633 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0947 (0.0753) Prec@1 85.000 (87.976) Prec@5 99.000 (99.133) +2022-11-14 16:49:45,641 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0753) Prec@1 88.000 (87.976) Prec@5 99.000 (99.131) +2022-11-14 16:49:45,648 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0862 (0.0754) Prec@1 85.000 (87.941) Prec@5 99.000 (99.129) +2022-11-14 16:49:45,656 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0941 (0.0756) Prec@1 83.000 (87.884) Prec@5 99.000 (99.128) +2022-11-14 16:49:45,663 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0755) Prec@1 88.000 (87.885) Prec@5 99.000 (99.126) +2022-11-14 16:49:45,671 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0745 (0.0755) Prec@1 89.000 (87.898) Prec@5 99.000 (99.125) +2022-11-14 16:49:45,678 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0937 (0.0757) Prec@1 83.000 (87.843) Prec@5 100.000 (99.135) +2022-11-14 16:49:45,686 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0757) Prec@1 89.000 (87.856) Prec@5 98.000 (99.122) +2022-11-14 16:49:45,693 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0755) Prec@1 90.000 (87.879) Prec@5 100.000 (99.132) +2022-11-14 16:49:45,701 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0667 (0.0754) Prec@1 89.000 (87.891) Prec@5 100.000 (99.141) +2022-11-14 16:49:45,708 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0887 (0.0756) Prec@1 86.000 (87.871) Prec@5 99.000 (99.140) +2022-11-14 16:49:45,716 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0772 (0.0756) Prec@1 86.000 (87.851) Prec@5 100.000 (99.149) +2022-11-14 16:49:45,724 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0757) Prec@1 87.000 (87.842) Prec@5 100.000 (99.158) +2022-11-14 16:49:45,731 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0688 (0.0756) Prec@1 91.000 (87.875) Prec@5 98.000 (99.146) +2022-11-14 16:49:45,738 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0584 (0.0754) Prec@1 91.000 (87.907) Prec@5 99.000 (99.144) +2022-11-14 16:49:45,746 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0931 (0.0756) Prec@1 84.000 (87.867) Prec@5 99.000 (99.143) +2022-11-14 16:49:45,753 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1044 (0.0759) Prec@1 84.000 (87.828) Prec@5 100.000 (99.152) +2022-11-14 16:49:45,760 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0759) Prec@1 87.000 (87.820) Prec@5 99.000 (99.150) +2022-11-14 16:49:45,813 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:49:46,137 Epoch: [393][0/500] Time 0.021 (0.021) Data 0.250 (0.250) Loss 0.0145 (0.0145) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:46,332 Epoch: [393][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0319 (0.0232) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:49:46,523 Epoch: [393][20/500] Time 0.017 (0.017) Data 0.002 (0.014) Loss 0.0167 (0.0211) Prec@1 97.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:49:46,712 Epoch: [393][30/500] Time 0.016 (0.017) Data 0.002 (0.010) Loss 0.0245 (0.0219) Prec@1 97.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 16:49:46,948 Epoch: [393][40/500] Time 0.024 (0.018) Data 0.001 (0.008) Loss 0.0116 (0.0199) Prec@1 99.000 (97.200) Prec@5 100.000 (100.000) +2022-11-14 16:49:47,207 Epoch: [393][50/500] Time 0.024 (0.019) Data 0.002 (0.007) Loss 0.0371 (0.0227) Prec@1 95.000 (96.833) Prec@5 99.000 (99.833) +2022-11-14 16:49:47,468 Epoch: [393][60/500] Time 0.023 (0.020) Data 0.002 (0.006) Loss 0.0435 (0.0257) Prec@1 93.000 (96.286) Prec@5 100.000 (99.857) +2022-11-14 16:49:47,730 Epoch: [393][70/500] Time 0.024 (0.020) Data 0.002 (0.005) Loss 0.0305 (0.0263) Prec@1 94.000 (96.000) Prec@5 100.000 (99.875) +2022-11-14 16:49:47,993 Epoch: [393][80/500] Time 0.025 (0.020) Data 0.002 (0.005) Loss 0.0501 (0.0289) Prec@1 93.000 (95.667) Prec@5 100.000 (99.889) +2022-11-14 16:49:48,258 Epoch: [393][90/500] Time 0.026 (0.021) Data 0.002 (0.004) Loss 0.0327 (0.0293) Prec@1 94.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 16:49:48,528 Epoch: [393][100/500] Time 0.027 (0.021) Data 0.002 (0.004) Loss 0.0143 (0.0280) Prec@1 98.000 (95.727) Prec@5 100.000 (99.909) +2022-11-14 16:49:48,797 Epoch: [393][110/500] Time 0.026 (0.021) Data 0.001 (0.004) Loss 0.0282 (0.0280) Prec@1 94.000 (95.583) Prec@5 99.000 (99.833) +2022-11-14 16:49:49,068 Epoch: [393][120/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0417 (0.0290) Prec@1 93.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:49:49,335 Epoch: [393][130/500] Time 0.024 (0.022) Data 0.002 (0.004) Loss 0.0522 (0.0307) Prec@1 91.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 16:49:49,603 Epoch: [393][140/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0470 (0.0318) Prec@1 92.000 (94.867) Prec@5 99.000 (99.800) +2022-11-14 16:49:49,873 Epoch: [393][150/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0468 (0.0327) Prec@1 94.000 (94.812) Prec@5 100.000 (99.812) +2022-11-14 16:49:50,144 Epoch: [393][160/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0298 (0.0325) Prec@1 95.000 (94.824) Prec@5 99.000 (99.765) +2022-11-14 16:49:50,407 Epoch: [393][170/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0409 (0.0330) Prec@1 93.000 (94.722) Prec@5 100.000 (99.778) +2022-11-14 16:49:50,680 Epoch: [393][180/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0362 (0.0332) Prec@1 95.000 (94.737) Prec@5 100.000 (99.789) +2022-11-14 16:49:50,946 Epoch: [393][190/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0336 (0.0332) Prec@1 94.000 (94.700) Prec@5 100.000 (99.800) +2022-11-14 16:49:51,210 Epoch: [393][200/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0479 (0.0339) Prec@1 94.000 (94.667) Prec@5 99.000 (99.762) +2022-11-14 16:49:51,469 Epoch: [393][210/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0123 (0.0329) Prec@1 97.000 (94.773) Prec@5 100.000 (99.773) +2022-11-14 16:49:51,731 Epoch: [393][220/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0261 (0.0326) Prec@1 96.000 (94.826) Prec@5 99.000 (99.739) +2022-11-14 16:49:51,992 Epoch: [393][230/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0210 (0.0321) Prec@1 97.000 (94.917) Prec@5 99.000 (99.708) +2022-11-14 16:49:52,254 Epoch: [393][240/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0353 (0.0322) Prec@1 95.000 (94.920) Prec@5 100.000 (99.720) +2022-11-14 16:49:52,517 Epoch: [393][250/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0435 (0.0327) Prec@1 95.000 (94.923) Prec@5 100.000 (99.731) +2022-11-14 16:49:52,777 Epoch: [393][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0321 (0.0327) Prec@1 96.000 (94.963) Prec@5 100.000 (99.741) +2022-11-14 16:49:53,038 Epoch: [393][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0249 (0.0324) Prec@1 97.000 (95.036) Prec@5 100.000 (99.750) +2022-11-14 16:49:53,298 Epoch: [393][280/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0422 (0.0327) Prec@1 93.000 (94.966) Prec@5 100.000 (99.759) +2022-11-14 16:49:53,556 Epoch: [393][290/500] Time 0.024 (0.023) Data 0.002 (0.003) Loss 0.0286 (0.0326) Prec@1 95.000 (94.967) Prec@5 100.000 (99.767) +2022-11-14 16:49:53,816 Epoch: [393][300/500] Time 0.025 (0.023) Data 0.001 (0.003) Loss 0.0198 (0.0322) Prec@1 96.000 (95.000) Prec@5 100.000 (99.774) +2022-11-14 16:49:54,082 Epoch: [393][310/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0363 (0.0323) Prec@1 91.000 (94.875) Prec@5 100.000 (99.781) +2022-11-14 16:49:54,342 Epoch: [393][320/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0223 (0.0320) Prec@1 96.000 (94.909) Prec@5 100.000 (99.788) +2022-11-14 16:49:54,607 Epoch: [393][330/500] Time 0.023 (0.023) Data 0.001 (0.002) Loss 0.0177 (0.0316) Prec@1 98.000 (95.000) Prec@5 100.000 (99.794) +2022-11-14 16:49:54,867 Epoch: [393][340/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0448 (0.0320) Prec@1 93.000 (94.943) Prec@5 100.000 (99.800) +2022-11-14 16:49:55,129 Epoch: [393][350/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0380 (0.0321) Prec@1 93.000 (94.889) Prec@5 100.000 (99.806) +2022-11-14 16:49:55,393 Epoch: [393][360/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0192 (0.0318) Prec@1 97.000 (94.946) Prec@5 100.000 (99.811) +2022-11-14 16:49:55,654 Epoch: [393][370/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0241 (0.0316) Prec@1 96.000 (94.974) Prec@5 100.000 (99.816) +2022-11-14 16:49:55,910 Epoch: [393][380/500] Time 0.022 (0.023) Data 0.001 (0.002) Loss 0.0492 (0.0320) Prec@1 93.000 (94.923) Prec@5 100.000 (99.821) +2022-11-14 16:49:56,176 Epoch: [393][390/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0294 (0.0320) Prec@1 97.000 (94.975) Prec@5 100.000 (99.825) +2022-11-14 16:49:56,435 Epoch: [393][400/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0248 (0.0318) Prec@1 96.000 (95.000) Prec@5 100.000 (99.829) +2022-11-14 16:49:56,696 Epoch: [393][410/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0364 (0.0319) Prec@1 94.000 (94.976) Prec@5 100.000 (99.833) +2022-11-14 16:49:56,953 Epoch: [393][420/500] Time 0.021 (0.023) Data 0.002 (0.002) Loss 0.0155 (0.0315) Prec@1 97.000 (95.023) Prec@5 100.000 (99.837) +2022-11-14 16:49:57,218 Epoch: [393][430/500] Time 0.022 (0.023) Data 0.001 (0.002) Loss 0.0301 (0.0315) Prec@1 97.000 (95.068) Prec@5 100.000 (99.841) +2022-11-14 16:49:57,476 Epoch: [393][440/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0575 (0.0321) Prec@1 91.000 (94.978) Prec@5 99.000 (99.822) +2022-11-14 16:49:57,737 Epoch: [393][450/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0322 (0.0321) Prec@1 94.000 (94.957) Prec@5 100.000 (99.826) +2022-11-14 16:49:57,997 Epoch: [393][460/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0205 (0.0318) Prec@1 96.000 (94.979) Prec@5 100.000 (99.830) +2022-11-14 16:49:58,256 Epoch: [393][470/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0173 (0.0315) Prec@1 97.000 (95.021) Prec@5 100.000 (99.833) +2022-11-14 16:49:58,511 Epoch: [393][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0217 (0.0313) Prec@1 98.000 (95.082) Prec@5 100.000 (99.837) +2022-11-14 16:49:58,768 Epoch: [393][490/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0281 (0.0312) Prec@1 95.000 (95.080) Prec@5 100.000 (99.840) +2022-11-14 16:49:59,002 Epoch: [393][499/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0384 (0.0314) Prec@1 93.000 (95.039) Prec@5 100.000 (99.843) +2022-11-14 16:49:59,304 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0622 (0.0622) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:49:59,312 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0809 (0.0716) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:49:59,322 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0799 (0.0743) Prec@1 86.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:49:59,331 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0733) Prec@1 89.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 16:49:59,338 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0731) Prec@1 87.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 16:49:59,345 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0488 (0.0691) Prec@1 92.000 (88.833) Prec@5 100.000 (99.833) +2022-11-14 16:49:59,352 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0692) Prec@1 90.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 16:49:59,360 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0697) Prec@1 86.000 (88.625) Prec@5 98.000 (99.625) +2022-11-14 16:49:59,367 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0724) Prec@1 85.000 (88.222) Prec@5 98.000 (99.444) +2022-11-14 16:49:59,374 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0741) Prec@1 86.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 16:49:59,381 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0407 (0.0710) Prec@1 96.000 (88.727) Prec@5 99.000 (99.364) +2022-11-14 16:49:59,389 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0724) Prec@1 89.000 (88.750) Prec@5 100.000 (99.417) +2022-11-14 16:49:59,396 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0720) Prec@1 87.000 (88.615) Prec@5 100.000 (99.462) +2022-11-14 16:49:59,404 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0718) Prec@1 90.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 16:49:59,411 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0724) Prec@1 86.000 (88.533) Prec@5 98.000 (99.333) +2022-11-14 16:49:59,418 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0726) Prec@1 88.000 (88.500) Prec@5 99.000 (99.312) +2022-11-14 16:49:59,425 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0715) Prec@1 93.000 (88.765) Prec@5 99.000 (99.294) +2022-11-14 16:49:59,434 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0731) Prec@1 84.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 16:49:59,441 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0739) Prec@1 86.000 (88.368) Prec@5 97.000 (99.211) +2022-11-14 16:49:59,448 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1099 (0.0757) Prec@1 81.000 (88.000) Prec@5 99.000 (99.200) +2022-11-14 16:49:59,455 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0923 (0.0765) Prec@1 86.000 (87.905) Prec@5 100.000 (99.238) +2022-11-14 16:49:59,463 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0767) Prec@1 89.000 (87.955) Prec@5 99.000 (99.227) +2022-11-14 16:49:59,470 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1032 (0.0779) Prec@1 83.000 (87.739) Prec@5 99.000 (99.217) +2022-11-14 16:49:59,478 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0777) Prec@1 86.000 (87.667) Prec@5 100.000 (99.250) +2022-11-14 16:49:59,485 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1010 (0.0786) Prec@1 81.000 (87.400) Prec@5 100.000 (99.280) +2022-11-14 16:49:59,492 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0950 (0.0792) Prec@1 85.000 (87.308) Prec@5 98.000 (99.231) +2022-11-14 16:49:59,500 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0604 (0.0785) Prec@1 89.000 (87.370) Prec@5 100.000 (99.259) +2022-11-14 16:49:59,507 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0460 (0.0774) Prec@1 93.000 (87.571) Prec@5 100.000 (99.286) +2022-11-14 16:49:59,514 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0716 (0.0772) Prec@1 87.000 (87.552) Prec@5 99.000 (99.276) +2022-11-14 16:49:59,522 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0921 (0.0777) Prec@1 84.000 (87.433) Prec@5 98.000 (99.233) +2022-11-14 16:49:59,529 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0778) Prec@1 87.000 (87.419) Prec@5 100.000 (99.258) +2022-11-14 16:49:59,536 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0779) Prec@1 86.000 (87.375) Prec@5 98.000 (99.219) +2022-11-14 16:49:59,544 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0778) Prec@1 87.000 (87.364) Prec@5 100.000 (99.242) +2022-11-14 16:49:59,551 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0701 (0.0776) Prec@1 90.000 (87.441) Prec@5 100.000 (99.265) +2022-11-14 16:49:59,559 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0890 (0.0779) Prec@1 87.000 (87.429) Prec@5 98.000 (99.229) +2022-11-14 16:49:59,566 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0776) Prec@1 91.000 (87.528) Prec@5 99.000 (99.222) +2022-11-14 16:49:59,573 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0777) Prec@1 85.000 (87.459) Prec@5 98.000 (99.189) +2022-11-14 16:49:59,581 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0779 (0.0777) Prec@1 87.000 (87.447) Prec@5 98.000 (99.158) +2022-11-14 16:49:59,589 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0528 (0.0770) Prec@1 92.000 (87.564) Prec@5 99.000 (99.154) +2022-11-14 16:49:59,596 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0768) Prec@1 87.000 (87.550) Prec@5 99.000 (99.150) +2022-11-14 16:49:59,604 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0855 (0.0770) Prec@1 87.000 (87.537) Prec@5 99.000 (99.146) +2022-11-14 16:49:59,612 Test: [41/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0768) Prec@1 90.000 (87.595) Prec@5 99.000 (99.143) +2022-11-14 16:49:59,619 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0437 (0.0761) Prec@1 92.000 (87.698) Prec@5 100.000 (99.163) +2022-11-14 16:49:59,627 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0758) Prec@1 90.000 (87.750) Prec@5 98.000 (99.136) +2022-11-14 16:49:59,634 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0586 (0.0754) Prec@1 92.000 (87.844) Prec@5 99.000 (99.133) +2022-11-14 16:49:59,641 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1068 (0.0761) Prec@1 81.000 (87.696) Prec@5 100.000 (99.152) +2022-11-14 16:49:59,649 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0624 (0.0758) Prec@1 88.000 (87.702) Prec@5 99.000 (99.149) +2022-11-14 16:49:59,656 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0760) Prec@1 84.000 (87.625) Prec@5 99.000 (99.146) +2022-11-14 16:49:59,664 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0758) Prec@1 89.000 (87.653) Prec@5 100.000 (99.163) +2022-11-14 16:49:59,671 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1066 (0.0764) Prec@1 83.000 (87.560) Prec@5 100.000 (99.180) +2022-11-14 16:49:59,679 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0761) Prec@1 90.000 (87.608) Prec@5 100.000 (99.196) +2022-11-14 16:49:59,686 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0760) Prec@1 89.000 (87.635) Prec@5 100.000 (99.212) +2022-11-14 16:49:59,693 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0663 (0.0758) Prec@1 86.000 (87.604) Prec@5 99.000 (99.208) +2022-11-14 16:49:59,701 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0731 (0.0757) Prec@1 88.000 (87.611) Prec@5 99.000 (99.204) +2022-11-14 16:49:59,708 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0755) Prec@1 91.000 (87.673) Prec@5 100.000 (99.218) +2022-11-14 16:49:59,715 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0754) Prec@1 88.000 (87.679) Prec@5 99.000 (99.214) +2022-11-14 16:49:59,722 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0696 (0.0753) Prec@1 86.000 (87.649) Prec@5 100.000 (99.228) +2022-11-14 16:49:59,730 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0752) Prec@1 90.000 (87.690) Prec@5 97.000 (99.190) +2022-11-14 16:49:59,738 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0923 (0.0755) Prec@1 84.000 (87.627) Prec@5 100.000 (99.203) +2022-11-14 16:49:59,745 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0758) Prec@1 85.000 (87.583) Prec@5 98.000 (99.183) +2022-11-14 16:49:59,753 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0631 (0.0756) Prec@1 89.000 (87.607) Prec@5 100.000 (99.197) +2022-11-14 16:49:59,760 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0842 (0.0757) Prec@1 84.000 (87.548) Prec@5 99.000 (99.194) +2022-11-14 16:49:59,768 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0681 (0.0756) Prec@1 89.000 (87.571) Prec@5 100.000 (99.206) +2022-11-14 16:49:59,775 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0342 (0.0750) Prec@1 95.000 (87.688) Prec@5 100.000 (99.219) +2022-11-14 16:49:59,782 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0973 (0.0753) Prec@1 82.000 (87.600) Prec@5 100.000 (99.231) +2022-11-14 16:49:59,790 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0943 (0.0756) Prec@1 84.000 (87.545) Prec@5 100.000 (99.242) +2022-11-14 16:49:59,798 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0447 (0.0751) Prec@1 93.000 (87.627) Prec@5 100.000 (99.254) +2022-11-14 16:49:59,805 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0706 (0.0751) Prec@1 90.000 (87.662) Prec@5 100.000 (99.265) +2022-11-14 16:49:59,812 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0749) Prec@1 90.000 (87.696) Prec@5 99.000 (99.261) +2022-11-14 16:49:59,820 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0813 (0.0750) Prec@1 87.000 (87.686) Prec@5 100.000 (99.271) +2022-11-14 16:49:59,827 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1092 (0.0755) Prec@1 83.000 (87.620) Prec@5 98.000 (99.254) +2022-11-14 16:49:59,835 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0562 (0.0752) Prec@1 90.000 (87.653) Prec@5 100.000 (99.264) +2022-11-14 16:49:59,842 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0749) Prec@1 92.000 (87.712) Prec@5 100.000 (99.274) +2022-11-14 16:49:59,850 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0321 (0.0743) Prec@1 96.000 (87.824) Prec@5 99.000 (99.270) +2022-11-14 16:49:59,857 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1045 (0.0747) Prec@1 84.000 (87.773) Prec@5 99.000 (99.267) +2022-11-14 16:49:59,865 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0554 (0.0745) Prec@1 91.000 (87.816) Prec@5 99.000 (99.263) +2022-11-14 16:49:59,873 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0766 (0.0745) Prec@1 87.000 (87.805) Prec@5 99.000 (99.260) +2022-11-14 16:49:59,880 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0881 (0.0747) Prec@1 88.000 (87.808) Prec@5 99.000 (99.256) +2022-11-14 16:49:59,888 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0879 (0.0749) Prec@1 85.000 (87.772) Prec@5 100.000 (99.266) +2022-11-14 16:49:59,896 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0748) Prec@1 89.000 (87.787) Prec@5 99.000 (99.263) +2022-11-14 16:49:59,903 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0748) Prec@1 89.000 (87.802) Prec@5 99.000 (99.259) +2022-11-14 16:49:59,911 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0749) Prec@1 85.000 (87.768) Prec@5 100.000 (99.268) +2022-11-14 16:49:59,918 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0751) Prec@1 86.000 (87.747) Prec@5 100.000 (99.277) +2022-11-14 16:49:59,926 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0592 (0.0750) Prec@1 88.000 (87.750) Prec@5 100.000 (99.286) +2022-11-14 16:49:59,933 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1131 (0.0754) Prec@1 82.000 (87.682) Prec@5 99.000 (99.282) +2022-11-14 16:49:59,940 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1137 (0.0759) Prec@1 82.000 (87.616) Prec@5 100.000 (99.291) +2022-11-14 16:49:59,948 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0758) Prec@1 89.000 (87.632) Prec@5 100.000 (99.299) +2022-11-14 16:49:59,955 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0758) Prec@1 87.000 (87.625) Prec@5 99.000 (99.295) +2022-11-14 16:49:59,963 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0757) Prec@1 87.000 (87.618) Prec@5 100.000 (99.303) +2022-11-14 16:49:59,970 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0796 (0.0757) Prec@1 89.000 (87.633) Prec@5 99.000 (99.300) +2022-11-14 16:49:59,978 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0503 (0.0754) Prec@1 91.000 (87.670) Prec@5 100.000 (99.308) +2022-11-14 16:49:59,985 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0559 (0.0752) Prec@1 91.000 (87.707) Prec@5 100.000 (99.315) +2022-11-14 16:49:59,993 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0753) Prec@1 87.000 (87.699) Prec@5 100.000 (99.323) +2022-11-14 16:50:00,000 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0793 (0.0753) Prec@1 88.000 (87.702) Prec@5 98.000 (99.309) +2022-11-14 16:50:00,009 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0936 (0.0755) Prec@1 86.000 (87.684) Prec@5 100.000 (99.316) +2022-11-14 16:50:00,016 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0754) Prec@1 88.000 (87.688) Prec@5 99.000 (99.312) +2022-11-14 16:50:00,023 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0533 (0.0752) Prec@1 90.000 (87.711) Prec@5 99.000 (99.309) +2022-11-14 16:50:00,031 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1046 (0.0755) Prec@1 85.000 (87.684) Prec@5 97.000 (99.286) +2022-11-14 16:50:00,038 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0794 (0.0756) Prec@1 87.000 (87.677) Prec@5 100.000 (99.293) +2022-11-14 16:50:00,045 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0761 (0.0756) Prec@1 88.000 (87.680) Prec@5 99.000 (99.290) +2022-11-14 16:50:00,100 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:50:00,424 Epoch: [394][0/500] Time 0.022 (0.022) Data 0.247 (0.247) Loss 0.0282 (0.0282) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:00,626 Epoch: [394][10/500] Time 0.018 (0.018) Data 0.002 (0.024) Loss 0.0146 (0.0214) Prec@1 98.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:50:00,824 Epoch: [394][20/500] Time 0.021 (0.018) Data 0.002 (0.013) Loss 0.0264 (0.0230) Prec@1 97.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:50:01,024 Epoch: [394][30/500] Time 0.017 (0.018) Data 0.002 (0.010) Loss 0.0150 (0.0210) Prec@1 97.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 16:50:01,215 Epoch: [394][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0322 (0.0233) Prec@1 95.000 (96.400) Prec@5 99.000 (99.800) +2022-11-14 16:50:01,407 Epoch: [394][50/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0223 (0.0231) Prec@1 97.000 (96.500) Prec@5 100.000 (99.833) +2022-11-14 16:50:01,597 Epoch: [394][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0295 (0.0240) Prec@1 95.000 (96.286) Prec@5 100.000 (99.857) +2022-11-14 16:50:01,826 Epoch: [394][70/500] Time 0.025 (0.018) Data 0.001 (0.005) Loss 0.0207 (0.0236) Prec@1 97.000 (96.375) Prec@5 100.000 (99.875) +2022-11-14 16:50:02,108 Epoch: [394][80/500] Time 0.029 (0.019) Data 0.002 (0.005) Loss 0.0254 (0.0238) Prec@1 96.000 (96.333) Prec@5 100.000 (99.889) +2022-11-14 16:50:02,386 Epoch: [394][90/500] Time 0.027 (0.019) Data 0.001 (0.004) Loss 0.0224 (0.0237) Prec@1 96.000 (96.300) Prec@5 100.000 (99.900) +2022-11-14 16:50:02,668 Epoch: [394][100/500] Time 0.028 (0.020) Data 0.001 (0.004) Loss 0.0095 (0.0224) Prec@1 99.000 (96.545) Prec@5 100.000 (99.909) +2022-11-14 16:50:02,949 Epoch: [394][110/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0268 (0.0228) Prec@1 96.000 (96.500) Prec@5 100.000 (99.917) +2022-11-14 16:50:03,231 Epoch: [394][120/500] Time 0.024 (0.021) Data 0.002 (0.004) Loss 0.0379 (0.0239) Prec@1 94.000 (96.308) Prec@5 100.000 (99.923) +2022-11-14 16:50:03,508 Epoch: [394][130/500] Time 0.026 (0.021) Data 0.002 (0.004) Loss 0.0452 (0.0254) Prec@1 92.000 (96.000) Prec@5 99.000 (99.857) +2022-11-14 16:50:03,783 Epoch: [394][140/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0475 (0.0269) Prec@1 91.000 (95.667) Prec@5 100.000 (99.867) +2022-11-14 16:50:04,066 Epoch: [394][150/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0384 (0.0276) Prec@1 95.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 16:50:04,353 Epoch: [394][160/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0374 (0.0282) Prec@1 91.000 (95.353) Prec@5 100.000 (99.882) +2022-11-14 16:50:04,636 Epoch: [394][170/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0296 (0.0283) Prec@1 94.000 (95.278) Prec@5 100.000 (99.889) +2022-11-14 16:50:04,915 Epoch: [394][180/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0411 (0.0290) Prec@1 93.000 (95.158) Prec@5 99.000 (99.842) +2022-11-14 16:50:05,198 Epoch: [394][190/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0373 (0.0294) Prec@1 93.000 (95.050) Prec@5 100.000 (99.850) +2022-11-14 16:50:05,481 Epoch: [394][200/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0287 (0.0293) Prec@1 96.000 (95.095) Prec@5 100.000 (99.857) +2022-11-14 16:50:05,763 Epoch: [394][210/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0168 (0.0288) Prec@1 97.000 (95.182) Prec@5 100.000 (99.864) +2022-11-14 16:50:06,044 Epoch: [394][220/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0191 (0.0284) Prec@1 97.000 (95.261) Prec@5 100.000 (99.870) +2022-11-14 16:50:06,324 Epoch: [394][230/500] Time 0.026 (0.023) Data 0.003 (0.003) Loss 0.0260 (0.0283) Prec@1 95.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:50:06,603 Epoch: [394][240/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0183 (0.0279) Prec@1 97.000 (95.320) Prec@5 100.000 (99.880) +2022-11-14 16:50:06,886 Epoch: [394][250/500] Time 0.026 (0.023) Data 0.001 (0.003) Loss 0.0447 (0.0285) Prec@1 93.000 (95.231) Prec@5 100.000 (99.885) +2022-11-14 16:50:07,170 Epoch: [394][260/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0388 (0.0289) Prec@1 94.000 (95.185) Prec@5 99.000 (99.852) +2022-11-14 16:50:07,456 Epoch: [394][270/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0231 (0.0287) Prec@1 97.000 (95.250) Prec@5 100.000 (99.857) +2022-11-14 16:50:07,739 Epoch: [394][280/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0415 (0.0291) Prec@1 91.000 (95.103) Prec@5 100.000 (99.862) +2022-11-14 16:50:08,018 Epoch: [394][290/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0375 (0.0294) Prec@1 93.000 (95.033) Prec@5 100.000 (99.867) +2022-11-14 16:50:08,300 Epoch: [394][300/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0156 (0.0290) Prec@1 98.000 (95.129) Prec@5 100.000 (99.871) +2022-11-14 16:50:08,585 Epoch: [394][310/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0602 (0.0299) Prec@1 90.000 (94.969) Prec@5 100.000 (99.875) +2022-11-14 16:50:08,867 Epoch: [394][320/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0316 (0.0300) Prec@1 95.000 (94.970) Prec@5 100.000 (99.879) +2022-11-14 16:50:09,154 Epoch: [394][330/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0361 (0.0302) Prec@1 94.000 (94.941) Prec@5 100.000 (99.882) +2022-11-14 16:50:09,434 Epoch: [394][340/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0379 (0.0304) Prec@1 93.000 (94.886) Prec@5 100.000 (99.886) +2022-11-14 16:50:09,715 Epoch: [394][350/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0133 (0.0299) Prec@1 97.000 (94.944) Prec@5 100.000 (99.889) +2022-11-14 16:50:09,996 Epoch: [394][360/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0324 (0.0300) Prec@1 93.000 (94.892) Prec@5 100.000 (99.892) +2022-11-14 16:50:10,276 Epoch: [394][370/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0340 (0.0301) Prec@1 94.000 (94.868) Prec@5 100.000 (99.895) +2022-11-14 16:50:10,557 Epoch: [394][380/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0474 (0.0305) Prec@1 94.000 (94.846) Prec@5 100.000 (99.897) +2022-11-14 16:50:10,842 Epoch: [394][390/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0125 (0.0301) Prec@1 97.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 16:50:11,128 Epoch: [394][400/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0109 (0.0296) Prec@1 98.000 (94.976) Prec@5 100.000 (99.902) +2022-11-14 16:50:11,409 Epoch: [394][410/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0612 (0.0304) Prec@1 90.000 (94.857) Prec@5 100.000 (99.905) +2022-11-14 16:50:11,688 Epoch: [394][420/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0360 (0.0305) Prec@1 94.000 (94.837) Prec@5 100.000 (99.907) +2022-11-14 16:50:11,971 Epoch: [394][430/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0299 (0.0305) Prec@1 94.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:50:12,250 Epoch: [394][440/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0340 (0.0306) Prec@1 93.000 (94.778) Prec@5 100.000 (99.911) +2022-11-14 16:50:12,535 Epoch: [394][450/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0118 (0.0301) Prec@1 99.000 (94.870) Prec@5 100.000 (99.913) +2022-11-14 16:50:12,814 Epoch: [394][460/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0181 (0.0299) Prec@1 98.000 (94.936) Prec@5 100.000 (99.915) +2022-11-14 16:50:13,099 Epoch: [394][470/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0228 (0.0297) Prec@1 97.000 (94.979) Prec@5 100.000 (99.917) +2022-11-14 16:50:13,376 Epoch: [394][480/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0128 (0.0294) Prec@1 98.000 (95.041) Prec@5 100.000 (99.918) +2022-11-14 16:50:13,657 Epoch: [394][490/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0327 (0.0295) Prec@1 93.000 (95.000) Prec@5 100.000 (99.920) +2022-11-14 16:50:13,912 Epoch: [394][499/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0109 (0.0291) Prec@1 99.000 (95.078) Prec@5 100.000 (99.922) +2022-11-14 16:50:14,230 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0600 (0.0600) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:14,237 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0536 (0.0568) Prec@1 91.000 (91.000) Prec@5 99.000 (99.500) +2022-11-14 16:50:14,245 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0606) Prec@1 88.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 16:50:14,255 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0613) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:50:14,261 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0631) Prec@1 87.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:50:14,268 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0624) Prec@1 91.000 (89.333) Prec@5 99.000 (99.500) +2022-11-14 16:50:14,275 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0619) Prec@1 91.000 (89.571) Prec@5 99.000 (99.429) +2022-11-14 16:50:14,283 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0644) Prec@1 87.000 (89.250) Prec@5 100.000 (99.500) +2022-11-14 16:50:14,290 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0651) Prec@1 89.000 (89.222) Prec@5 98.000 (99.333) +2022-11-14 16:50:14,297 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0661) Prec@1 90.000 (89.300) Prec@5 99.000 (99.300) +2022-11-14 16:50:14,305 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0649) Prec@1 93.000 (89.636) Prec@5 100.000 (99.364) +2022-11-14 16:50:14,312 Test: [11/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0910 (0.0670) Prec@1 86.000 (89.333) Prec@5 100.000 (99.417) +2022-11-14 16:50:14,319 Test: [12/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0504 (0.0658) Prec@1 93.000 (89.615) Prec@5 100.000 (99.462) +2022-11-14 16:50:14,327 Test: [13/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0545 (0.0650) Prec@1 90.000 (89.643) Prec@5 100.000 (99.500) +2022-11-14 16:50:14,334 Test: [14/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0781 (0.0658) Prec@1 88.000 (89.533) Prec@5 99.000 (99.467) +2022-11-14 16:50:14,342 Test: [15/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0944 (0.0676) Prec@1 85.000 (89.250) Prec@5 100.000 (99.500) +2022-11-14 16:50:14,349 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0430 (0.0662) Prec@1 94.000 (89.529) Prec@5 98.000 (99.412) +2022-11-14 16:50:14,357 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1094 (0.0686) Prec@1 82.000 (89.111) Prec@5 100.000 (99.444) +2022-11-14 16:50:14,364 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0796 (0.0692) Prec@1 87.000 (89.000) Prec@5 99.000 (99.421) +2022-11-14 16:50:14,372 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1160 (0.0715) Prec@1 82.000 (88.650) Prec@5 98.000 (99.350) +2022-11-14 16:50:14,379 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0711) Prec@1 89.000 (88.667) Prec@5 100.000 (99.381) +2022-11-14 16:50:14,387 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0765 (0.0713) Prec@1 89.000 (88.682) Prec@5 100.000 (99.409) +2022-11-14 16:50:14,395 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1090 (0.0730) Prec@1 84.000 (88.478) Prec@5 98.000 (99.348) +2022-11-14 16:50:14,402 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0731 (0.0730) Prec@1 90.000 (88.542) Prec@5 99.000 (99.333) +2022-11-14 16:50:14,409 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0640 (0.0726) Prec@1 89.000 (88.560) Prec@5 100.000 (99.360) +2022-11-14 16:50:14,417 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0779 (0.0728) Prec@1 87.000 (88.500) Prec@5 98.000 (99.308) +2022-11-14 16:50:14,424 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0526 (0.0721) Prec@1 93.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 16:50:14,432 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0457 (0.0711) Prec@1 93.000 (88.821) Prec@5 100.000 (99.357) +2022-11-14 16:50:14,439 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0585 (0.0707) Prec@1 92.000 (88.931) Prec@5 98.000 (99.310) +2022-11-14 16:50:14,447 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0535 (0.0701) Prec@1 93.000 (89.067) Prec@5 99.000 (99.300) +2022-11-14 16:50:14,454 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0693 (0.0701) Prec@1 85.000 (88.935) Prec@5 100.000 (99.323) +2022-11-14 16:50:14,462 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0759 (0.0703) Prec@1 86.000 (88.844) Prec@5 99.000 (99.312) +2022-11-14 16:50:14,469 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0707) Prec@1 84.000 (88.697) Prec@5 99.000 (99.303) +2022-11-14 16:50:14,477 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0935 (0.0714) Prec@1 85.000 (88.588) Prec@5 100.000 (99.324) +2022-11-14 16:50:14,484 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0900 (0.0719) Prec@1 87.000 (88.543) Prec@5 97.000 (99.257) +2022-11-14 16:50:14,492 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0718) Prec@1 90.000 (88.583) Prec@5 98.000 (99.222) +2022-11-14 16:50:14,499 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0763 (0.0719) Prec@1 85.000 (88.486) Prec@5 99.000 (99.216) +2022-11-14 16:50:14,507 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1053 (0.0728) Prec@1 82.000 (88.316) Prec@5 99.000 (99.211) +2022-11-14 16:50:14,514 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0543 (0.0723) Prec@1 94.000 (88.462) Prec@5 99.000 (99.205) +2022-11-14 16:50:14,522 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0560 (0.0719) Prec@1 92.000 (88.550) Prec@5 99.000 (99.200) +2022-11-14 16:50:14,530 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0973 (0.0725) Prec@1 86.000 (88.488) Prec@5 100.000 (99.220) +2022-11-14 16:50:14,537 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0838 (0.0728) Prec@1 86.000 (88.429) Prec@5 100.000 (99.238) +2022-11-14 16:50:14,545 Test: [42/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0456 (0.0722) Prec@1 93.000 (88.535) Prec@5 98.000 (99.209) +2022-11-14 16:50:14,553 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0607 (0.0719) Prec@1 91.000 (88.591) Prec@5 99.000 (99.205) +2022-11-14 16:50:14,560 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0483 (0.0714) Prec@1 91.000 (88.644) Prec@5 100.000 (99.222) +2022-11-14 16:50:14,569 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1013 (0.0720) Prec@1 82.000 (88.500) Prec@5 100.000 (99.239) +2022-11-14 16:50:14,577 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0777 (0.0722) Prec@1 89.000 (88.511) Prec@5 100.000 (99.255) +2022-11-14 16:50:14,584 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0912 (0.0726) Prec@1 83.000 (88.396) Prec@5 100.000 (99.271) +2022-11-14 16:50:14,592 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0505 (0.0721) Prec@1 90.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 16:50:14,599 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1140 (0.0729) Prec@1 81.000 (88.280) Prec@5 99.000 (99.280) +2022-11-14 16:50:14,607 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0492 (0.0725) Prec@1 93.000 (88.373) Prec@5 100.000 (99.294) +2022-11-14 16:50:14,615 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0729) Prec@1 86.000 (88.327) Prec@5 99.000 (99.288) +2022-11-14 16:50:14,622 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0766 (0.0729) Prec@1 88.000 (88.321) Prec@5 100.000 (99.302) +2022-11-14 16:50:14,629 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0729) Prec@1 88.000 (88.315) Prec@5 100.000 (99.315) +2022-11-14 16:50:14,637 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0732) Prec@1 85.000 (88.255) Prec@5 100.000 (99.327) +2022-11-14 16:50:14,644 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0684 (0.0731) Prec@1 89.000 (88.268) Prec@5 99.000 (99.321) +2022-11-14 16:50:14,652 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0730) Prec@1 89.000 (88.281) Prec@5 99.000 (99.316) +2022-11-14 16:50:14,659 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0686 (0.0729) Prec@1 91.000 (88.328) Prec@5 100.000 (99.328) +2022-11-14 16:50:14,668 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0734) Prec@1 85.000 (88.271) Prec@5 99.000 (99.322) +2022-11-14 16:50:14,675 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0895 (0.0736) Prec@1 85.000 (88.217) Prec@5 99.000 (99.317) +2022-11-14 16:50:14,682 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1000 (0.0741) Prec@1 86.000 (88.180) Prec@5 99.000 (99.311) +2022-11-14 16:50:14,690 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0649 (0.0739) Prec@1 89.000 (88.194) Prec@5 100.000 (99.323) +2022-11-14 16:50:14,697 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0585 (0.0737) Prec@1 91.000 (88.238) Prec@5 100.000 (99.333) +2022-11-14 16:50:14,705 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0462 (0.0732) Prec@1 92.000 (88.297) Prec@5 100.000 (99.344) +2022-11-14 16:50:14,712 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1004 (0.0737) Prec@1 85.000 (88.246) Prec@5 100.000 (99.354) +2022-11-14 16:50:14,720 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0719 (0.0736) Prec@1 87.000 (88.227) Prec@5 99.000 (99.348) +2022-11-14 16:50:14,728 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0449 (0.0732) Prec@1 92.000 (88.284) Prec@5 100.000 (99.358) +2022-11-14 16:50:14,736 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0639 (0.0731) Prec@1 90.000 (88.309) Prec@5 99.000 (99.353) +2022-11-14 16:50:14,743 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0519 (0.0728) Prec@1 91.000 (88.348) Prec@5 100.000 (99.362) +2022-11-14 16:50:14,751 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0729) Prec@1 87.000 (88.329) Prec@5 97.000 (99.329) +2022-11-14 16:50:14,759 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0941 (0.0732) Prec@1 85.000 (88.282) Prec@5 99.000 (99.324) +2022-11-14 16:50:14,767 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0492 (0.0728) Prec@1 94.000 (88.361) Prec@5 100.000 (99.333) +2022-11-14 16:50:14,774 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0542 (0.0726) Prec@1 92.000 (88.411) Prec@5 100.000 (99.342) +2022-11-14 16:50:14,782 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0405 (0.0721) Prec@1 96.000 (88.514) Prec@5 100.000 (99.351) +2022-11-14 16:50:14,789 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0925 (0.0724) Prec@1 86.000 (88.480) Prec@5 99.000 (99.347) +2022-11-14 16:50:14,797 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0598 (0.0723) Prec@1 92.000 (88.526) Prec@5 99.000 (99.342) +2022-11-14 16:50:14,805 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0724) Prec@1 86.000 (88.494) Prec@5 98.000 (99.325) +2022-11-14 16:50:14,814 Test: [77/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0724) Prec@1 87.000 (88.474) Prec@5 97.000 (99.295) +2022-11-14 16:50:14,822 Test: [78/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0726) Prec@1 86.000 (88.443) Prec@5 100.000 (99.304) +2022-11-14 16:50:14,830 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0796 (0.0727) Prec@1 88.000 (88.438) Prec@5 99.000 (99.300) +2022-11-14 16:50:14,838 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0971 (0.0730) Prec@1 83.000 (88.370) Prec@5 99.000 (99.296) +2022-11-14 16:50:14,845 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0824 (0.0731) Prec@1 85.000 (88.329) Prec@5 100.000 (99.305) +2022-11-14 16:50:14,853 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0893 (0.0733) Prec@1 87.000 (88.313) Prec@5 100.000 (99.313) +2022-11-14 16:50:14,861 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0733) Prec@1 87.000 (88.298) Prec@5 98.000 (99.298) +2022-11-14 16:50:14,868 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0943 (0.0735) Prec@1 85.000 (88.259) Prec@5 100.000 (99.306) +2022-11-14 16:50:14,876 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0944 (0.0738) Prec@1 86.000 (88.233) Prec@5 100.000 (99.314) +2022-11-14 16:50:14,884 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0781 (0.0738) Prec@1 88.000 (88.230) Prec@5 100.000 (99.322) +2022-11-14 16:50:14,891 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0739) Prec@1 87.000 (88.216) Prec@5 99.000 (99.318) +2022-11-14 16:50:14,899 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0840 (0.0740) Prec@1 85.000 (88.180) Prec@5 100.000 (99.326) +2022-11-14 16:50:14,907 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0640 (0.0739) Prec@1 90.000 (88.200) Prec@5 100.000 (99.333) +2022-11-14 16:50:14,914 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0639 (0.0738) Prec@1 91.000 (88.231) Prec@5 100.000 (99.341) +2022-11-14 16:50:14,922 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0605 (0.0737) Prec@1 92.000 (88.272) Prec@5 100.000 (99.348) +2022-11-14 16:50:14,929 Test: [92/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1029 (0.0740) Prec@1 84.000 (88.226) Prec@5 99.000 (99.344) +2022-11-14 16:50:14,937 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0739) Prec@1 92.000 (88.266) Prec@5 99.000 (99.340) +2022-11-14 16:50:14,945 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0750 (0.0739) Prec@1 88.000 (88.263) Prec@5 99.000 (99.337) +2022-11-14 16:50:14,952 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0642 (0.0738) Prec@1 89.000 (88.271) Prec@5 100.000 (99.344) +2022-11-14 16:50:14,959 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0737) Prec@1 90.000 (88.289) Prec@5 99.000 (99.340) +2022-11-14 16:50:14,967 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0889 (0.0739) Prec@1 85.000 (88.255) Prec@5 99.000 (99.337) +2022-11-14 16:50:14,975 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0961 (0.0741) Prec@1 86.000 (88.232) Prec@5 97.000 (99.313) +2022-11-14 16:50:14,982 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0741) Prec@1 88.000 (88.230) Prec@5 100.000 (99.320) +2022-11-14 16:50:15,037 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:50:15,357 Epoch: [395][0/500] Time 0.025 (0.025) Data 0.238 (0.238) Loss 0.0334 (0.0334) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:50:15,564 Epoch: [395][10/500] Time 0.021 (0.019) Data 0.002 (0.023) Loss 0.0422 (0.0378) Prec@1 93.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 16:50:15,764 Epoch: [395][20/500] Time 0.020 (0.018) Data 0.002 (0.013) Loss 0.0203 (0.0320) Prec@1 97.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:50:15,960 Epoch: [395][30/500] Time 0.017 (0.018) Data 0.001 (0.009) Loss 0.0299 (0.0315) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:50:16,154 Epoch: [395][40/500] Time 0.019 (0.018) Data 0.002 (0.007) Loss 0.0401 (0.0332) Prec@1 92.000 (94.400) Prec@5 99.000 (99.600) +2022-11-14 16:50:16,344 Epoch: [395][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0449 (0.0352) Prec@1 92.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:50:16,534 Epoch: [395][60/500] Time 0.019 (0.017) Data 0.002 (0.006) Loss 0.0411 (0.0360) Prec@1 93.000 (93.857) Prec@5 100.000 (99.571) +2022-11-14 16:50:16,727 Epoch: [395][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0344 (0.0358) Prec@1 94.000 (93.875) Prec@5 100.000 (99.625) +2022-11-14 16:50:16,921 Epoch: [395][80/500] Time 0.020 (0.017) Data 0.001 (0.005) Loss 0.0213 (0.0342) Prec@1 96.000 (94.111) Prec@5 100.000 (99.667) +2022-11-14 16:50:17,141 Epoch: [395][90/500] Time 0.022 (0.018) Data 0.002 (0.004) Loss 0.0459 (0.0354) Prec@1 93.000 (94.000) Prec@5 100.000 (99.700) +2022-11-14 16:50:17,440 Epoch: [395][100/500] Time 0.029 (0.018) Data 0.001 (0.004) Loss 0.0407 (0.0358) Prec@1 94.000 (94.000) Prec@5 100.000 (99.727) +2022-11-14 16:50:17,746 Epoch: [395][110/500] Time 0.028 (0.019) Data 0.002 (0.004) Loss 0.0303 (0.0354) Prec@1 95.000 (94.083) Prec@5 100.000 (99.750) +2022-11-14 16:50:18,046 Epoch: [395][120/500] Time 0.029 (0.020) Data 0.002 (0.004) Loss 0.0275 (0.0348) Prec@1 95.000 (94.154) Prec@5 100.000 (99.769) +2022-11-14 16:50:18,348 Epoch: [395][130/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0381 (0.0350) Prec@1 94.000 (94.143) Prec@5 99.000 (99.714) +2022-11-14 16:50:18,645 Epoch: [395][140/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0228 (0.0342) Prec@1 97.000 (94.333) Prec@5 100.000 (99.733) +2022-11-14 16:50:18,949 Epoch: [395][150/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0166 (0.0331) Prec@1 98.000 (94.562) Prec@5 100.000 (99.750) +2022-11-14 16:50:19,253 Epoch: [395][160/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0434 (0.0337) Prec@1 94.000 (94.529) Prec@5 100.000 (99.765) +2022-11-14 16:50:19,550 Epoch: [395][170/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0540 (0.0348) Prec@1 93.000 (94.444) Prec@5 100.000 (99.778) +2022-11-14 16:50:19,848 Epoch: [395][180/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0260 (0.0344) Prec@1 95.000 (94.474) Prec@5 100.000 (99.789) +2022-11-14 16:50:20,151 Epoch: [395][190/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0237 (0.0338) Prec@1 96.000 (94.550) Prec@5 99.000 (99.750) +2022-11-14 16:50:20,453 Epoch: [395][200/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0204 (0.0332) Prec@1 96.000 (94.619) Prec@5 100.000 (99.762) +2022-11-14 16:50:20,784 Epoch: [395][210/500] Time 0.030 (0.023) Data 0.001 (0.003) Loss 0.0285 (0.0330) Prec@1 96.000 (94.682) Prec@5 100.000 (99.773) +2022-11-14 16:50:21,066 Epoch: [395][220/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0224 (0.0325) Prec@1 96.000 (94.739) Prec@5 100.000 (99.783) +2022-11-14 16:50:21,365 Epoch: [395][230/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0244 (0.0322) Prec@1 95.000 (94.750) Prec@5 99.000 (99.750) +2022-11-14 16:50:21,667 Epoch: [395][240/500] Time 0.030 (0.023) Data 0.001 (0.003) Loss 0.0134 (0.0314) Prec@1 98.000 (94.880) Prec@5 100.000 (99.760) +2022-11-14 16:50:21,967 Epoch: [395][250/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.0275 (0.0313) Prec@1 95.000 (94.885) Prec@5 100.000 (99.769) +2022-11-14 16:50:22,273 Epoch: [395][260/500] Time 0.029 (0.023) Data 0.002 (0.003) Loss 0.0455 (0.0318) Prec@1 93.000 (94.815) Prec@5 100.000 (99.778) +2022-11-14 16:50:22,574 Epoch: [395][270/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0357 (0.0319) Prec@1 94.000 (94.786) Prec@5 100.000 (99.786) +2022-11-14 16:50:22,875 Epoch: [395][280/500] Time 0.029 (0.024) Data 0.001 (0.003) Loss 0.0340 (0.0320) Prec@1 94.000 (94.759) Prec@5 100.000 (99.793) +2022-11-14 16:50:23,180 Epoch: [395][290/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0318 (0.0320) Prec@1 95.000 (94.767) Prec@5 100.000 (99.800) +2022-11-14 16:50:23,477 Epoch: [395][300/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0355 (0.0321) Prec@1 93.000 (94.710) Prec@5 99.000 (99.774) +2022-11-14 16:50:23,777 Epoch: [395][310/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0392 (0.0323) Prec@1 94.000 (94.688) Prec@5 99.000 (99.750) +2022-11-14 16:50:24,079 Epoch: [395][320/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0156 (0.0318) Prec@1 98.000 (94.788) Prec@5 100.000 (99.758) +2022-11-14 16:50:24,385 Epoch: [395][330/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0310 (0.0318) Prec@1 95.000 (94.794) Prec@5 100.000 (99.765) +2022-11-14 16:50:24,689 Epoch: [395][340/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0253 (0.0316) Prec@1 97.000 (94.857) Prec@5 100.000 (99.771) +2022-11-14 16:50:24,987 Epoch: [395][350/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0326 (0.0316) Prec@1 95.000 (94.861) Prec@5 100.000 (99.778) +2022-11-14 16:50:25,287 Epoch: [395][360/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0190 (0.0313) Prec@1 97.000 (94.919) Prec@5 100.000 (99.784) +2022-11-14 16:50:25,589 Epoch: [395][370/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0426 (0.0316) Prec@1 92.000 (94.842) Prec@5 100.000 (99.789) +2022-11-14 16:50:25,894 Epoch: [395][380/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0308 (0.0316) Prec@1 96.000 (94.872) Prec@5 99.000 (99.769) +2022-11-14 16:50:26,191 Epoch: [395][390/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0281 (0.0315) Prec@1 95.000 (94.875) Prec@5 100.000 (99.775) +2022-11-14 16:50:26,487 Epoch: [395][400/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0324 (0.0315) Prec@1 93.000 (94.829) Prec@5 100.000 (99.780) +2022-11-14 16:50:26,786 Epoch: [395][410/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0299 (0.0315) Prec@1 93.000 (94.786) Prec@5 99.000 (99.762) +2022-11-14 16:50:27,089 Epoch: [395][420/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0102 (0.0310) Prec@1 99.000 (94.884) Prec@5 100.000 (99.767) +2022-11-14 16:50:27,383 Epoch: [395][430/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0338 (0.0310) Prec@1 96.000 (94.909) Prec@5 100.000 (99.773) +2022-11-14 16:50:27,684 Epoch: [395][440/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0124 (0.0306) Prec@1 98.000 (94.978) Prec@5 100.000 (99.778) +2022-11-14 16:50:27,985 Epoch: [395][450/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0358 (0.0307) Prec@1 93.000 (94.935) Prec@5 100.000 (99.783) +2022-11-14 16:50:28,281 Epoch: [395][460/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0224 (0.0306) Prec@1 96.000 (94.957) Prec@5 100.000 (99.787) +2022-11-14 16:50:28,583 Epoch: [395][470/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0257 (0.0305) Prec@1 96.000 (94.979) Prec@5 100.000 (99.792) +2022-11-14 16:50:28,884 Epoch: [395][480/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0293 (0.0304) Prec@1 95.000 (94.980) Prec@5 100.000 (99.796) +2022-11-14 16:50:29,188 Epoch: [395][490/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0309 (0.0305) Prec@1 94.000 (94.960) Prec@5 100.000 (99.800) +2022-11-14 16:50:29,456 Epoch: [395][499/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0467 (0.0308) Prec@1 92.000 (94.902) Prec@5 100.000 (99.804) +2022-11-14 16:50:29,754 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0556 (0.0556) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:29,764 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0760 (0.0658) Prec@1 89.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:50:29,771 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0691 (0.0669) Prec@1 90.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:50:29,782 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0670) Prec@1 92.000 (89.750) Prec@5 99.000 (99.500) +2022-11-14 16:50:29,789 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0662) Prec@1 90.000 (89.800) Prec@5 99.000 (99.400) +2022-11-14 16:50:29,796 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0638) Prec@1 91.000 (90.000) Prec@5 98.000 (99.167) +2022-11-14 16:50:29,802 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0636) Prec@1 91.000 (90.143) Prec@5 100.000 (99.286) +2022-11-14 16:50:29,810 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0679) Prec@1 86.000 (89.625) Prec@5 100.000 (99.375) +2022-11-14 16:50:29,817 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0698) Prec@1 87.000 (89.333) Prec@5 100.000 (99.444) +2022-11-14 16:50:29,825 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0709) Prec@1 87.000 (89.100) Prec@5 99.000 (99.400) +2022-11-14 16:50:29,833 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0699) Prec@1 90.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 16:50:29,841 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0701) Prec@1 89.000 (89.167) Prec@5 99.000 (99.417) +2022-11-14 16:50:29,848 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0703) Prec@1 90.000 (89.231) Prec@5 100.000 (99.462) +2022-11-14 16:50:29,856 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0700) Prec@1 89.000 (89.214) Prec@5 100.000 (99.500) +2022-11-14 16:50:29,864 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0705) Prec@1 90.000 (89.267) Prec@5 99.000 (99.467) +2022-11-14 16:50:29,871 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0708) Prec@1 86.000 (89.062) Prec@5 100.000 (99.500) +2022-11-14 16:50:29,879 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0696) Prec@1 92.000 (89.235) Prec@5 99.000 (99.471) +2022-11-14 16:50:29,887 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.0717) Prec@1 85.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:50:29,894 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0724) Prec@1 85.000 (88.789) Prec@5 99.000 (99.474) +2022-11-14 16:50:29,902 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1213 (0.0749) Prec@1 81.000 (88.400) Prec@5 97.000 (99.350) +2022-11-14 16:50:29,910 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0749) Prec@1 88.000 (88.381) Prec@5 100.000 (99.381) +2022-11-14 16:50:29,917 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0756) Prec@1 83.000 (88.136) Prec@5 99.000 (99.364) +2022-11-14 16:50:29,925 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0758) Prec@1 89.000 (88.174) Prec@5 97.000 (99.261) +2022-11-14 16:50:29,932 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0764) Prec@1 86.000 (88.083) Prec@5 99.000 (99.250) +2022-11-14 16:50:29,940 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0765) Prec@1 88.000 (88.080) Prec@5 100.000 (99.280) +2022-11-14 16:50:29,948 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0774) Prec@1 85.000 (87.962) Prec@5 98.000 (99.231) +2022-11-14 16:50:29,955 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0766) Prec@1 90.000 (88.037) Prec@5 100.000 (99.259) +2022-11-14 16:50:29,963 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0764) Prec@1 89.000 (88.071) Prec@5 100.000 (99.286) +2022-11-14 16:50:29,971 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0764) Prec@1 89.000 (88.103) Prec@5 98.000 (99.241) +2022-11-14 16:50:29,978 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0773) Prec@1 84.000 (87.967) Prec@5 100.000 (99.267) +2022-11-14 16:50:29,986 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0768) Prec@1 90.000 (88.032) Prec@5 100.000 (99.290) +2022-11-14 16:50:29,993 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0770) Prec@1 87.000 (88.000) Prec@5 100.000 (99.312) +2022-11-14 16:50:30,001 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0773) Prec@1 86.000 (87.939) Prec@5 99.000 (99.303) +2022-11-14 16:50:30,009 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0777) Prec@1 87.000 (87.912) Prec@5 100.000 (99.324) +2022-11-14 16:50:30,016 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0783) Prec@1 86.000 (87.857) Prec@5 97.000 (99.257) +2022-11-14 16:50:30,024 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0777) Prec@1 92.000 (87.972) Prec@5 100.000 (99.278) +2022-11-14 16:50:30,032 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0778) Prec@1 88.000 (87.973) Prec@5 99.000 (99.270) +2022-11-14 16:50:30,039 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0784) Prec@1 81.000 (87.789) Prec@5 100.000 (99.289) +2022-11-14 16:50:30,047 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0779) Prec@1 90.000 (87.846) Prec@5 100.000 (99.308) +2022-11-14 16:50:30,055 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0774) Prec@1 92.000 (87.950) Prec@5 100.000 (99.325) +2022-11-14 16:50:30,062 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0781) Prec@1 84.000 (87.854) Prec@5 96.000 (99.244) +2022-11-14 16:50:30,071 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0778) Prec@1 89.000 (87.881) Prec@5 99.000 (99.238) +2022-11-14 16:50:30,080 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0772) Prec@1 93.000 (88.000) Prec@5 99.000 (99.233) +2022-11-14 16:50:30,089 Test: [43/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0771) Prec@1 89.000 (88.023) Prec@5 96.000 (99.159) +2022-11-14 16:50:30,097 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0769) Prec@1 88.000 (88.022) Prec@5 100.000 (99.178) +2022-11-14 16:50:30,105 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0772) Prec@1 84.000 (87.935) Prec@5 99.000 (99.174) +2022-11-14 16:50:30,113 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0770) Prec@1 89.000 (87.957) Prec@5 99.000 (99.170) +2022-11-14 16:50:30,121 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0773) Prec@1 85.000 (87.896) Prec@5 99.000 (99.167) +2022-11-14 16:50:30,129 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0767) Prec@1 92.000 (87.980) Prec@5 99.000 (99.163) +2022-11-14 16:50:30,137 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0771) Prec@1 85.000 (87.920) Prec@5 99.000 (99.160) +2022-11-14 16:50:30,145 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0770) Prec@1 89.000 (87.941) Prec@5 100.000 (99.176) +2022-11-14 16:50:30,152 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0771) Prec@1 87.000 (87.923) Prec@5 100.000 (99.192) +2022-11-14 16:50:30,160 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0767) Prec@1 91.000 (87.981) Prec@5 100.000 (99.208) +2022-11-14 16:50:30,168 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0765) Prec@1 91.000 (88.037) Prec@5 99.000 (99.204) +2022-11-14 16:50:30,175 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0767) Prec@1 84.000 (87.964) Prec@5 100.000 (99.218) +2022-11-14 16:50:30,183 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0763) Prec@1 91.000 (88.018) Prec@5 99.000 (99.214) +2022-11-14 16:50:30,190 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0762) Prec@1 90.000 (88.053) Prec@5 100.000 (99.228) +2022-11-14 16:50:30,198 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0762) Prec@1 88.000 (88.052) Prec@5 99.000 (99.224) +2022-11-14 16:50:30,205 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0765) Prec@1 86.000 (88.017) Prec@5 99.000 (99.220) +2022-11-14 16:50:30,213 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0768) Prec@1 83.000 (87.933) Prec@5 100.000 (99.233) +2022-11-14 16:50:30,221 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0771) Prec@1 84.000 (87.869) Prec@5 99.000 (99.230) +2022-11-14 16:50:30,228 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0770) Prec@1 89.000 (87.887) Prec@5 99.000 (99.226) +2022-11-14 16:50:30,236 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0770) Prec@1 88.000 (87.889) Prec@5 100.000 (99.238) +2022-11-14 16:50:30,243 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0211 (0.0761) Prec@1 97.000 (88.031) Prec@5 100.000 (99.250) +2022-11-14 16:50:30,251 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0763) Prec@1 84.000 (87.969) Prec@5 100.000 (99.262) +2022-11-14 16:50:30,258 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0762) Prec@1 90.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 16:50:30,266 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0301 (0.0755) Prec@1 95.000 (88.104) Prec@5 100.000 (99.284) +2022-11-14 16:50:30,273 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0753) Prec@1 91.000 (88.147) Prec@5 100.000 (99.294) +2022-11-14 16:50:30,281 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0752) Prec@1 89.000 (88.159) Prec@5 99.000 (99.290) +2022-11-14 16:50:30,289 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0752) Prec@1 90.000 (88.186) Prec@5 98.000 (99.271) +2022-11-14 16:50:30,296 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.0757) Prec@1 87.000 (88.169) Prec@5 98.000 (99.254) +2022-11-14 16:50:30,305 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0754) Prec@1 92.000 (88.222) Prec@5 100.000 (99.264) +2022-11-14 16:50:30,312 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0299 (0.0748) Prec@1 96.000 (88.329) Prec@5 100.000 (99.274) +2022-11-14 16:50:30,320 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0381 (0.0743) Prec@1 95.000 (88.419) Prec@5 100.000 (99.284) +2022-11-14 16:50:30,328 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0744) Prec@1 87.000 (88.400) Prec@5 100.000 (99.293) +2022-11-14 16:50:30,335 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0741) Prec@1 91.000 (88.434) Prec@5 99.000 (99.289) +2022-11-14 16:50:30,343 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0738) Prec@1 92.000 (88.481) Prec@5 99.000 (99.286) +2022-11-14 16:50:30,351 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0740) Prec@1 87.000 (88.462) Prec@5 98.000 (99.269) +2022-11-14 16:50:30,358 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0740) Prec@1 86.000 (88.430) Prec@5 100.000 (99.278) +2022-11-14 16:50:30,366 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0739) Prec@1 91.000 (88.463) Prec@5 100.000 (99.287) +2022-11-14 16:50:30,373 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0741) Prec@1 85.000 (88.420) Prec@5 97.000 (99.259) +2022-11-14 16:50:30,381 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0744) Prec@1 85.000 (88.378) Prec@5 99.000 (99.256) +2022-11-14 16:50:30,389 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0745) Prec@1 87.000 (88.361) Prec@5 100.000 (99.265) +2022-11-14 16:50:30,396 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0743) Prec@1 89.000 (88.369) Prec@5 99.000 (99.262) +2022-11-14 16:50:30,404 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0745) Prec@1 85.000 (88.329) Prec@5 99.000 (99.259) +2022-11-14 16:50:30,412 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0747) Prec@1 86.000 (88.302) Prec@5 100.000 (99.267) +2022-11-14 16:50:30,419 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0748) Prec@1 88.000 (88.299) Prec@5 100.000 (99.276) +2022-11-14 16:50:30,427 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0748) Prec@1 87.000 (88.284) Prec@5 99.000 (99.273) +2022-11-14 16:50:30,435 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0748) Prec@1 85.000 (88.247) Prec@5 100.000 (99.281) +2022-11-14 16:50:30,442 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0747) Prec@1 88.000 (88.244) Prec@5 100.000 (99.289) +2022-11-14 16:50:30,450 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0470 (0.0744) Prec@1 92.000 (88.286) Prec@5 100.000 (99.297) +2022-11-14 16:50:30,457 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0741) Prec@1 92.000 (88.326) Prec@5 100.000 (99.304) +2022-11-14 16:50:30,465 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0744) Prec@1 84.000 (88.280) Prec@5 100.000 (99.312) +2022-11-14 16:50:30,473 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0744) Prec@1 88.000 (88.277) Prec@5 98.000 (99.298) +2022-11-14 16:50:30,480 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0745) Prec@1 86.000 (88.253) Prec@5 99.000 (99.295) +2022-11-14 16:50:30,488 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0744) Prec@1 88.000 (88.250) Prec@5 99.000 (99.292) +2022-11-14 16:50:30,495 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0741) Prec@1 93.000 (88.299) Prec@5 99.000 (99.289) +2022-11-14 16:50:30,503 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0743) Prec@1 84.000 (88.255) Prec@5 99.000 (99.286) +2022-11-14 16:50:30,510 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.0747) Prec@1 83.000 (88.202) Prec@5 99.000 (99.283) +2022-11-14 16:50:30,518 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0747) Prec@1 88.000 (88.200) Prec@5 100.000 (99.290) +2022-11-14 16:50:30,572 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:50:30,885 Epoch: [396][0/500] Time 0.022 (0.022) Data 0.236 (0.236) Loss 0.0360 (0.0360) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:31,081 Epoch: [396][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0254 (0.0307) Prec@1 96.000 (95.500) Prec@5 99.000 (99.500) +2022-11-14 16:50:31,271 Epoch: [396][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0157 (0.0257) Prec@1 96.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:50:31,461 Epoch: [396][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0324 (0.0274) Prec@1 95.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:50:31,651 Epoch: [396][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0085 (0.0236) Prec@1 99.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:50:31,844 Epoch: [396][50/500] Time 0.019 (0.017) Data 0.002 (0.006) Loss 0.0326 (0.0251) Prec@1 95.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:50:32,034 Epoch: [396][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0393 (0.0271) Prec@1 93.000 (95.571) Prec@5 99.000 (99.714) +2022-11-14 16:50:32,226 Epoch: [396][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0439 (0.0292) Prec@1 92.000 (95.125) Prec@5 100.000 (99.750) +2022-11-14 16:50:32,415 Epoch: [396][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0319 (0.0295) Prec@1 95.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:50:32,608 Epoch: [396][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0250 (0.0291) Prec@1 95.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 16:50:32,799 Epoch: [396][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0364 (0.0297) Prec@1 95.000 (95.091) Prec@5 100.000 (99.818) +2022-11-14 16:50:32,992 Epoch: [396][110/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0290 (0.0297) Prec@1 96.000 (95.167) Prec@5 99.000 (99.750) +2022-11-14 16:50:33,190 Epoch: [396][120/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0426 (0.0307) Prec@1 93.000 (95.000) Prec@5 99.000 (99.692) +2022-11-14 16:50:33,390 Epoch: [396][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0216 (0.0300) Prec@1 97.000 (95.143) Prec@5 100.000 (99.714) +2022-11-14 16:50:33,592 Epoch: [396][140/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0399 (0.0307) Prec@1 95.000 (95.133) Prec@5 99.000 (99.667) +2022-11-14 16:50:33,780 Epoch: [396][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0357 (0.0310) Prec@1 94.000 (95.062) Prec@5 100.000 (99.688) +2022-11-14 16:50:34,057 Epoch: [396][160/500] Time 0.033 (0.017) Data 0.002 (0.003) Loss 0.0122 (0.0299) Prec@1 98.000 (95.235) Prec@5 100.000 (99.706) +2022-11-14 16:50:34,408 Epoch: [396][170/500] Time 0.034 (0.018) Data 0.002 (0.003) Loss 0.0329 (0.0301) Prec@1 95.000 (95.222) Prec@5 99.000 (99.667) +2022-11-14 16:50:34,757 Epoch: [396][180/500] Time 0.035 (0.019) Data 0.001 (0.003) Loss 0.0360 (0.0304) Prec@1 92.000 (95.053) Prec@5 100.000 (99.684) +2022-11-14 16:50:35,108 Epoch: [396][190/500] Time 0.031 (0.020) Data 0.002 (0.003) Loss 0.0200 (0.0299) Prec@1 97.000 (95.150) Prec@5 100.000 (99.700) +2022-11-14 16:50:35,455 Epoch: [396][200/500] Time 0.034 (0.020) Data 0.002 (0.003) Loss 0.0287 (0.0298) Prec@1 95.000 (95.143) Prec@5 100.000 (99.714) +2022-11-14 16:50:35,799 Epoch: [396][210/500] Time 0.032 (0.021) Data 0.002 (0.003) Loss 0.0240 (0.0295) Prec@1 95.000 (95.136) Prec@5 100.000 (99.727) +2022-11-14 16:50:36,149 Epoch: [396][220/500] Time 0.038 (0.021) Data 0.002 (0.003) Loss 0.0266 (0.0294) Prec@1 97.000 (95.217) Prec@5 100.000 (99.739) +2022-11-14 16:50:36,497 Epoch: [396][230/500] Time 0.033 (0.021) Data 0.002 (0.003) Loss 0.0557 (0.0305) Prec@1 90.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:50:36,843 Epoch: [396][240/500] Time 0.034 (0.022) Data 0.002 (0.003) Loss 0.0425 (0.0310) Prec@1 94.000 (94.960) Prec@5 100.000 (99.760) +2022-11-14 16:50:37,194 Epoch: [396][250/500] Time 0.032 (0.022) Data 0.002 (0.003) Loss 0.0228 (0.0307) Prec@1 96.000 (95.000) Prec@5 100.000 (99.769) +2022-11-14 16:50:37,541 Epoch: [396][260/500] Time 0.034 (0.023) Data 0.002 (0.003) Loss 0.0191 (0.0302) Prec@1 97.000 (95.074) Prec@5 100.000 (99.778) +2022-11-14 16:50:37,890 Epoch: [396][270/500] Time 0.033 (0.023) Data 0.002 (0.003) Loss 0.0226 (0.0300) Prec@1 96.000 (95.107) Prec@5 100.000 (99.786) +2022-11-14 16:50:38,241 Epoch: [396][280/500] Time 0.032 (0.023) Data 0.002 (0.002) Loss 0.0402 (0.0303) Prec@1 93.000 (95.034) Prec@5 100.000 (99.793) +2022-11-14 16:50:38,588 Epoch: [396][290/500] Time 0.032 (0.023) Data 0.002 (0.002) Loss 0.0067 (0.0295) Prec@1 99.000 (95.167) Prec@5 100.000 (99.800) +2022-11-14 16:50:38,935 Epoch: [396][300/500] Time 0.033 (0.024) Data 0.001 (0.002) Loss 0.0273 (0.0295) Prec@1 96.000 (95.194) Prec@5 100.000 (99.806) +2022-11-14 16:50:39,255 Epoch: [396][310/500] Time 0.024 (0.024) Data 0.002 (0.002) Loss 0.0163 (0.0290) Prec@1 97.000 (95.250) Prec@5 100.000 (99.812) +2022-11-14 16:50:39,482 Epoch: [396][320/500] Time 0.021 (0.024) Data 0.001 (0.002) Loss 0.0234 (0.0289) Prec@1 97.000 (95.303) Prec@5 100.000 (99.818) +2022-11-14 16:50:39,703 Epoch: [396][330/500] Time 0.021 (0.024) Data 0.001 (0.002) Loss 0.0244 (0.0287) Prec@1 96.000 (95.324) Prec@5 100.000 (99.824) +2022-11-14 16:50:39,922 Epoch: [396][340/500] Time 0.020 (0.023) Data 0.001 (0.002) Loss 0.0282 (0.0287) Prec@1 95.000 (95.314) Prec@5 100.000 (99.829) +2022-11-14 16:50:40,143 Epoch: [396][350/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0308 (0.0288) Prec@1 95.000 (95.306) Prec@5 100.000 (99.833) +2022-11-14 16:50:40,361 Epoch: [396][360/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0236 (0.0286) Prec@1 96.000 (95.324) Prec@5 100.000 (99.838) +2022-11-14 16:50:40,582 Epoch: [396][370/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0300 (0.0287) Prec@1 95.000 (95.316) Prec@5 100.000 (99.842) +2022-11-14 16:50:40,804 Epoch: [396][380/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0413 (0.0290) Prec@1 93.000 (95.256) Prec@5 99.000 (99.821) +2022-11-14 16:50:41,025 Epoch: [396][390/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0150 (0.0287) Prec@1 96.000 (95.275) Prec@5 100.000 (99.825) +2022-11-14 16:50:41,247 Epoch: [396][400/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0381 (0.0289) Prec@1 93.000 (95.220) Prec@5 100.000 (99.829) +2022-11-14 16:50:41,469 Epoch: [396][410/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0408 (0.0292) Prec@1 93.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:50:41,690 Epoch: [396][420/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0209 (0.0290) Prec@1 98.000 (95.233) Prec@5 100.000 (99.837) +2022-11-14 16:50:41,911 Epoch: [396][430/500] Time 0.020 (0.023) Data 0.001 (0.002) Loss 0.0282 (0.0290) Prec@1 96.000 (95.250) Prec@5 99.000 (99.818) +2022-11-14 16:50:42,136 Epoch: [396][440/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0202 (0.0288) Prec@1 98.000 (95.311) Prec@5 100.000 (99.822) +2022-11-14 16:50:42,355 Epoch: [396][450/500] Time 0.021 (0.022) Data 0.001 (0.002) Loss 0.0318 (0.0288) Prec@1 94.000 (95.283) Prec@5 100.000 (99.826) +2022-11-14 16:50:42,577 Epoch: [396][460/500] Time 0.021 (0.022) Data 0.001 (0.002) Loss 0.0361 (0.0290) Prec@1 95.000 (95.277) Prec@5 99.000 (99.809) +2022-11-14 16:50:42,800 Epoch: [396][470/500] Time 0.021 (0.022) Data 0.001 (0.002) Loss 0.0243 (0.0289) Prec@1 97.000 (95.312) Prec@5 100.000 (99.812) +2022-11-14 16:50:43,022 Epoch: [396][480/500] Time 0.020 (0.022) Data 0.001 (0.002) Loss 0.0249 (0.0288) Prec@1 96.000 (95.327) Prec@5 100.000 (99.816) +2022-11-14 16:50:43,243 Epoch: [396][490/500] Time 0.020 (0.022) Data 0.002 (0.002) Loss 0.0297 (0.0288) Prec@1 96.000 (95.340) Prec@5 100.000 (99.820) +2022-11-14 16:50:43,444 Epoch: [396][499/500] Time 0.021 (0.022) Data 0.001 (0.002) Loss 0.0192 (0.0286) Prec@1 97.000 (95.373) Prec@5 100.000 (99.824) +2022-11-14 16:50:43,749 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0821 (0.0821) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:43,760 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0731 (0.0776) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:50:43,769 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0903 (0.0818) Prec@1 85.000 (86.667) Prec@5 99.000 (99.667) +2022-11-14 16:50:43,780 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0660 (0.0779) Prec@1 91.000 (87.750) Prec@5 98.000 (99.250) +2022-11-14 16:50:43,787 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0766) Prec@1 90.000 (88.200) Prec@5 100.000 (99.400) +2022-11-14 16:50:43,796 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0494 (0.0720) Prec@1 91.000 (88.667) Prec@5 100.000 (99.500) +2022-11-14 16:50:43,805 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0781 (0.0729) Prec@1 89.000 (88.714) Prec@5 100.000 (99.571) +2022-11-14 16:50:43,813 Test: [7/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0997 (0.0763) Prec@1 85.000 (88.250) Prec@5 99.000 (99.500) +2022-11-14 16:50:43,820 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0750) Prec@1 89.000 (88.333) Prec@5 99.000 (99.444) +2022-11-14 16:50:43,830 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0749) Prec@1 88.000 (88.300) Prec@5 99.000 (99.400) +2022-11-14 16:50:43,840 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0740) Prec@1 90.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 16:50:43,847 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0750) Prec@1 85.000 (88.167) Prec@5 98.000 (99.333) +2022-11-14 16:50:43,855 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0745) Prec@1 89.000 (88.231) Prec@5 100.000 (99.385) +2022-11-14 16:50:43,862 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0744) Prec@1 90.000 (88.357) Prec@5 100.000 (99.429) +2022-11-14 16:50:43,870 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0735) Prec@1 91.000 (88.533) Prec@5 100.000 (99.467) +2022-11-14 16:50:43,878 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0737) Prec@1 86.000 (88.375) Prec@5 100.000 (99.500) +2022-11-14 16:50:43,885 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0733) Prec@1 88.000 (88.353) Prec@5 98.000 (99.412) +2022-11-14 16:50:43,892 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0737) Prec@1 85.000 (88.167) Prec@5 100.000 (99.444) +2022-11-14 16:50:43,900 Test: [18/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0745) Prec@1 84.000 (87.947) Prec@5 98.000 (99.368) +2022-11-14 16:50:43,908 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0754) Prec@1 86.000 (87.850) Prec@5 98.000 (99.300) +2022-11-14 16:50:43,915 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0750) Prec@1 89.000 (87.905) Prec@5 99.000 (99.286) +2022-11-14 16:50:43,923 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0749) Prec@1 89.000 (87.955) Prec@5 99.000 (99.273) +2022-11-14 16:50:43,930 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0765) Prec@1 83.000 (87.739) Prec@5 100.000 (99.304) +2022-11-14 16:50:43,937 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 88.000 (87.750) Prec@5 100.000 (99.333) +2022-11-14 16:50:43,944 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1129 (0.0779) Prec@1 79.000 (87.400) Prec@5 100.000 (99.360) +2022-11-14 16:50:43,952 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0785) Prec@1 84.000 (87.269) Prec@5 99.000 (99.346) +2022-11-14 16:50:43,960 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0778) Prec@1 93.000 (87.481) Prec@5 100.000 (99.370) +2022-11-14 16:50:43,967 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0777) Prec@1 89.000 (87.536) Prec@5 100.000 (99.393) +2022-11-14 16:50:43,975 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0773) Prec@1 89.000 (87.586) Prec@5 97.000 (99.310) +2022-11-14 16:50:43,982 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0769) Prec@1 90.000 (87.667) Prec@5 98.000 (99.267) +2022-11-14 16:50:43,990 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0767) Prec@1 91.000 (87.774) Prec@5 100.000 (99.290) +2022-11-14 16:50:43,998 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0767) Prec@1 89.000 (87.812) Prec@5 99.000 (99.281) +2022-11-14 16:50:44,006 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0764) Prec@1 88.000 (87.818) Prec@5 100.000 (99.303) +2022-11-14 16:50:44,013 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0771) Prec@1 84.000 (87.706) Prec@5 100.000 (99.324) +2022-11-14 16:50:44,021 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0774) Prec@1 85.000 (87.629) Prec@5 100.000 (99.343) +2022-11-14 16:50:44,029 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0771) Prec@1 90.000 (87.694) Prec@5 99.000 (99.333) +2022-11-14 16:50:44,037 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0771) Prec@1 88.000 (87.703) Prec@5 99.000 (99.324) +2022-11-14 16:50:44,046 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0779) Prec@1 83.000 (87.579) Prec@5 99.000 (99.316) +2022-11-14 16:50:44,054 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0774) Prec@1 91.000 (87.667) Prec@5 99.000 (99.308) +2022-11-14 16:50:44,061 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0768) Prec@1 90.000 (87.725) Prec@5 99.000 (99.300) +2022-11-14 16:50:44,069 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0775) Prec@1 82.000 (87.585) Prec@5 99.000 (99.293) +2022-11-14 16:50:44,077 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0777) Prec@1 86.000 (87.548) Prec@5 99.000 (99.286) +2022-11-14 16:50:44,085 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0445 (0.0770) Prec@1 93.000 (87.674) Prec@5 99.000 (99.279) +2022-11-14 16:50:44,093 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0770) Prec@1 87.000 (87.659) Prec@5 99.000 (99.273) +2022-11-14 16:50:44,101 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0455 (0.0763) Prec@1 92.000 (87.756) Prec@5 99.000 (99.267) +2022-11-14 16:50:44,108 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0766) Prec@1 86.000 (87.717) Prec@5 100.000 (99.283) +2022-11-14 16:50:44,116 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0765) Prec@1 88.000 (87.723) Prec@5 100.000 (99.298) +2022-11-14 16:50:44,124 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1214 (0.0774) Prec@1 81.000 (87.583) Prec@5 99.000 (99.292) +2022-11-14 16:50:44,132 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0771) Prec@1 90.000 (87.633) Prec@5 99.000 (99.286) +2022-11-14 16:50:44,140 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0775) Prec@1 87.000 (87.620) Prec@5 100.000 (99.300) +2022-11-14 16:50:44,147 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0776) Prec@1 87.000 (87.608) Prec@5 100.000 (99.314) +2022-11-14 16:50:44,155 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0775) Prec@1 89.000 (87.635) Prec@5 100.000 (99.327) +2022-11-14 16:50:44,163 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0772) Prec@1 90.000 (87.679) Prec@5 99.000 (99.321) +2022-11-14 16:50:44,171 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0774) Prec@1 87.000 (87.667) Prec@5 99.000 (99.315) +2022-11-14 16:50:44,179 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0775) Prec@1 86.000 (87.636) Prec@5 100.000 (99.327) +2022-11-14 16:50:44,186 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0774) Prec@1 90.000 (87.679) Prec@5 99.000 (99.321) +2022-11-14 16:50:44,194 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0770) Prec@1 90.000 (87.719) Prec@5 100.000 (99.333) +2022-11-14 16:50:44,201 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0768) Prec@1 89.000 (87.741) Prec@5 99.000 (99.328) +2022-11-14 16:50:44,209 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0773) Prec@1 84.000 (87.678) Prec@5 100.000 (99.339) +2022-11-14 16:50:44,217 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0771) Prec@1 90.000 (87.717) Prec@5 100.000 (99.350) +2022-11-14 16:50:44,225 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0772) Prec@1 86.000 (87.689) Prec@5 100.000 (99.361) +2022-11-14 16:50:44,233 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0770) Prec@1 88.000 (87.694) Prec@5 99.000 (99.355) +2022-11-14 16:50:44,240 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0767) Prec@1 92.000 (87.762) Prec@5 100.000 (99.365) +2022-11-14 16:50:44,248 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0369 (0.0761) Prec@1 94.000 (87.859) Prec@5 99.000 (99.359) +2022-11-14 16:50:44,256 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0763) Prec@1 86.000 (87.831) Prec@5 99.000 (99.354) +2022-11-14 16:50:44,264 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0762) Prec@1 87.000 (87.818) Prec@5 99.000 (99.348) +2022-11-14 16:50:44,271 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0756) Prec@1 94.000 (87.910) Prec@5 100.000 (99.358) +2022-11-14 16:50:44,279 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0753) Prec@1 92.000 (87.971) Prec@5 99.000 (99.353) +2022-11-14 16:50:44,287 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0752) Prec@1 87.000 (87.957) Prec@5 99.000 (99.348) +2022-11-14 16:50:44,295 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0751) Prec@1 88.000 (87.957) Prec@5 99.000 (99.343) +2022-11-14 16:50:44,303 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.0757) Prec@1 82.000 (87.873) Prec@5 98.000 (99.324) +2022-11-14 16:50:44,310 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0755) Prec@1 90.000 (87.903) Prec@5 100.000 (99.333) +2022-11-14 16:50:44,318 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0754) Prec@1 91.000 (87.945) Prec@5 99.000 (99.329) +2022-11-14 16:50:44,326 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0750) Prec@1 90.000 (87.973) Prec@5 100.000 (99.338) +2022-11-14 16:50:44,333 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0753) Prec@1 83.000 (87.907) Prec@5 100.000 (99.347) +2022-11-14 16:50:44,341 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0751) Prec@1 91.000 (87.947) Prec@5 100.000 (99.355) +2022-11-14 16:50:44,349 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0752) Prec@1 89.000 (87.961) Prec@5 99.000 (99.351) +2022-11-14 16:50:44,356 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0752) Prec@1 88.000 (87.962) Prec@5 97.000 (99.321) +2022-11-14 16:50:44,364 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0752) Prec@1 89.000 (87.975) Prec@5 99.000 (99.316) +2022-11-14 16:50:44,372 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0753) Prec@1 84.000 (87.925) Prec@5 100.000 (99.325) +2022-11-14 16:50:44,379 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0755) Prec@1 87.000 (87.914) Prec@5 97.000 (99.296) +2022-11-14 16:50:44,387 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0755) Prec@1 87.000 (87.902) Prec@5 100.000 (99.305) +2022-11-14 16:50:44,395 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0758) Prec@1 86.000 (87.880) Prec@5 99.000 (99.301) +2022-11-14 16:50:44,402 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0755) Prec@1 89.000 (87.893) Prec@5 99.000 (99.298) +2022-11-14 16:50:44,410 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1158 (0.0760) Prec@1 81.000 (87.812) Prec@5 100.000 (99.306) +2022-11-14 16:50:44,418 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0764) Prec@1 83.000 (87.756) Prec@5 100.000 (99.314) +2022-11-14 16:50:44,425 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0762) Prec@1 89.000 (87.770) Prec@5 100.000 (99.322) +2022-11-14 16:50:44,433 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0764) Prec@1 85.000 (87.739) Prec@5 98.000 (99.307) +2022-11-14 16:50:44,441 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0763) Prec@1 87.000 (87.730) Prec@5 100.000 (99.315) +2022-11-14 16:50:44,448 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0763) Prec@1 88.000 (87.733) Prec@5 99.000 (99.311) +2022-11-14 16:50:44,456 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0763) Prec@1 88.000 (87.736) Prec@5 99.000 (99.308) +2022-11-14 16:50:44,464 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0761) Prec@1 89.000 (87.750) Prec@5 100.000 (99.315) +2022-11-14 16:50:44,471 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0764) Prec@1 85.000 (87.720) Prec@5 98.000 (99.301) +2022-11-14 16:50:44,479 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0764) Prec@1 87.000 (87.713) Prec@5 100.000 (99.309) +2022-11-14 16:50:44,487 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0767) Prec@1 84.000 (87.674) Prec@5 100.000 (99.316) +2022-11-14 16:50:44,494 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0765) Prec@1 92.000 (87.719) Prec@5 99.000 (99.312) +2022-11-14 16:50:44,502 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0763) Prec@1 91.000 (87.753) Prec@5 99.000 (99.309) +2022-11-14 16:50:44,509 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0763) Prec@1 91.000 (87.786) Prec@5 99.000 (99.306) +2022-11-14 16:50:44,517 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0765) Prec@1 86.000 (87.768) Prec@5 98.000 (99.293) +2022-11-14 16:50:44,525 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0763) Prec@1 90.000 (87.790) Prec@5 100.000 (99.300) +2022-11-14 16:50:44,582 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:50:44,887 Epoch: [397][0/500] Time 0.021 (0.021) Data 0.228 (0.228) Loss 0.0206 (0.0206) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:45,089 Epoch: [397][10/500] Time 0.017 (0.018) Data 0.001 (0.022) Loss 0.0313 (0.0259) Prec@1 95.000 (95.500) Prec@5 99.000 (99.500) +2022-11-14 16:50:45,281 Epoch: [397][20/500] Time 0.017 (0.017) Data 0.002 (0.012) Loss 0.0228 (0.0249) Prec@1 97.000 (96.000) Prec@5 100.000 (99.667) +2022-11-14 16:50:45,471 Epoch: [397][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0235 (0.0245) Prec@1 97.000 (96.250) Prec@5 100.000 (99.750) +2022-11-14 16:50:45,662 Epoch: [397][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0263 (0.0249) Prec@1 96.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:50:45,852 Epoch: [397][50/500] Time 0.018 (0.017) Data 0.002 (0.006) Loss 0.0187 (0.0239) Prec@1 98.000 (96.500) Prec@5 100.000 (99.833) +2022-11-14 16:50:46,056 Epoch: [397][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0230 (0.0237) Prec@1 96.000 (96.429) Prec@5 100.000 (99.857) +2022-11-14 16:50:46,246 Epoch: [397][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0165 (0.0228) Prec@1 98.000 (96.625) Prec@5 99.000 (99.750) +2022-11-14 16:50:46,437 Epoch: [397][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0416 (0.0249) Prec@1 93.000 (96.222) Prec@5 100.000 (99.778) +2022-11-14 16:50:46,623 Epoch: [397][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0530 (0.0277) Prec@1 92.000 (95.800) Prec@5 99.000 (99.700) +2022-11-14 16:50:46,809 Epoch: [397][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0188 (0.0269) Prec@1 97.000 (95.909) Prec@5 100.000 (99.727) +2022-11-14 16:50:47,020 Epoch: [397][110/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0297 (0.0271) Prec@1 94.000 (95.750) Prec@5 100.000 (99.750) +2022-11-14 16:50:47,312 Epoch: [397][120/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0279 (0.0272) Prec@1 94.000 (95.615) Prec@5 100.000 (99.769) +2022-11-14 16:50:47,610 Epoch: [397][130/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0361 (0.0278) Prec@1 92.000 (95.357) Prec@5 99.000 (99.714) +2022-11-14 16:50:47,912 Epoch: [397][140/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0271 (0.0278) Prec@1 95.000 (95.333) Prec@5 100.000 (99.733) +2022-11-14 16:50:48,219 Epoch: [397][150/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0117 (0.0268) Prec@1 98.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:50:48,518 Epoch: [397][160/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0209 (0.0264) Prec@1 96.000 (95.529) Prec@5 100.000 (99.765) +2022-11-14 16:50:48,820 Epoch: [397][170/500] Time 0.032 (0.020) Data 0.002 (0.003) Loss 0.0413 (0.0273) Prec@1 94.000 (95.444) Prec@5 98.000 (99.667) +2022-11-14 16:50:49,127 Epoch: [397][180/500] Time 0.035 (0.021) Data 0.002 (0.003) Loss 0.0233 (0.0271) Prec@1 96.000 (95.474) Prec@5 100.000 (99.684) +2022-11-14 16:50:49,419 Epoch: [397][190/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0119 (0.0263) Prec@1 98.000 (95.600) Prec@5 100.000 (99.700) +2022-11-14 16:50:49,716 Epoch: [397][200/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0285 (0.0264) Prec@1 96.000 (95.619) Prec@5 100.000 (99.714) +2022-11-14 16:50:50,010 Epoch: [397][210/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0153 (0.0259) Prec@1 98.000 (95.727) Prec@5 100.000 (99.727) +2022-11-14 16:50:50,310 Epoch: [397][220/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0156 (0.0255) Prec@1 98.000 (95.826) Prec@5 100.000 (99.739) +2022-11-14 16:50:50,602 Epoch: [397][230/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0188 (0.0252) Prec@1 98.000 (95.917) Prec@5 100.000 (99.750) +2022-11-14 16:50:50,898 Epoch: [397][240/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0310 (0.0254) Prec@1 97.000 (95.960) Prec@5 100.000 (99.760) +2022-11-14 16:50:51,194 Epoch: [397][250/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0487 (0.0263) Prec@1 92.000 (95.808) Prec@5 100.000 (99.769) +2022-11-14 16:50:51,485 Epoch: [397][260/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0230 (0.0262) Prec@1 98.000 (95.889) Prec@5 100.000 (99.778) +2022-11-14 16:50:51,779 Epoch: [397][270/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0335 (0.0264) Prec@1 94.000 (95.821) Prec@5 100.000 (99.786) +2022-11-14 16:50:52,075 Epoch: [397][280/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0447 (0.0271) Prec@1 92.000 (95.690) Prec@5 99.000 (99.759) +2022-11-14 16:50:52,373 Epoch: [397][290/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0264 (0.0271) Prec@1 96.000 (95.700) Prec@5 100.000 (99.767) +2022-11-14 16:50:52,669 Epoch: [397][300/500] Time 0.027 (0.023) Data 0.003 (0.002) Loss 0.0184 (0.0268) Prec@1 98.000 (95.774) Prec@5 100.000 (99.774) +2022-11-14 16:50:52,967 Epoch: [397][310/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0421 (0.0273) Prec@1 94.000 (95.719) Prec@5 100.000 (99.781) +2022-11-14 16:50:53,263 Epoch: [397][320/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0206 (0.0271) Prec@1 97.000 (95.758) Prec@5 99.000 (99.758) +2022-11-14 16:50:53,555 Epoch: [397][330/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0478 (0.0277) Prec@1 91.000 (95.618) Prec@5 100.000 (99.765) +2022-11-14 16:50:53,845 Epoch: [397][340/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0439 (0.0281) Prec@1 93.000 (95.543) Prec@5 100.000 (99.771) +2022-11-14 16:50:54,141 Epoch: [397][350/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0310 (0.0282) Prec@1 94.000 (95.500) Prec@5 100.000 (99.778) +2022-11-14 16:50:54,435 Epoch: [397][360/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0202 (0.0280) Prec@1 96.000 (95.514) Prec@5 100.000 (99.784) +2022-11-14 16:50:54,729 Epoch: [397][370/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0324 (0.0281) Prec@1 95.000 (95.500) Prec@5 100.000 (99.789) +2022-11-14 16:50:55,020 Epoch: [397][380/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0303 (0.0282) Prec@1 94.000 (95.462) Prec@5 99.000 (99.769) +2022-11-14 16:50:55,313 Epoch: [397][390/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0128 (0.0278) Prec@1 98.000 (95.525) Prec@5 100.000 (99.775) +2022-11-14 16:50:55,610 Epoch: [397][400/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0464 (0.0282) Prec@1 93.000 (95.463) Prec@5 100.000 (99.780) +2022-11-14 16:50:55,906 Epoch: [397][410/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0412 (0.0285) Prec@1 94.000 (95.429) Prec@5 100.000 (99.786) +2022-11-14 16:50:56,202 Epoch: [397][420/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0386 (0.0288) Prec@1 94.000 (95.395) Prec@5 100.000 (99.791) +2022-11-14 16:50:56,497 Epoch: [397][430/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0245 (0.0287) Prec@1 95.000 (95.386) Prec@5 100.000 (99.795) +2022-11-14 16:50:56,790 Epoch: [397][440/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0313 (0.0287) Prec@1 93.000 (95.333) Prec@5 100.000 (99.800) +2022-11-14 16:50:57,090 Epoch: [397][450/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0256 (0.0287) Prec@1 97.000 (95.370) Prec@5 100.000 (99.804) +2022-11-14 16:50:57,381 Epoch: [397][460/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0054 (0.0282) Prec@1 100.000 (95.468) Prec@5 100.000 (99.809) +2022-11-14 16:50:57,672 Epoch: [397][470/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0093 (0.0278) Prec@1 99.000 (95.542) Prec@5 100.000 (99.812) +2022-11-14 16:50:57,966 Epoch: [397][480/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0298 (0.0278) Prec@1 94.000 (95.510) Prec@5 100.000 (99.816) +2022-11-14 16:50:58,257 Epoch: [397][490/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0254 (0.0278) Prec@1 96.000 (95.520) Prec@5 100.000 (99.820) +2022-11-14 16:50:58,524 Epoch: [397][499/500] Time 0.031 (0.024) Data 0.002 (0.002) Loss 0.0269 (0.0278) Prec@1 96.000 (95.529) Prec@5 100.000 (99.824) +2022-11-14 16:50:58,839 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0668 (0.0668) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:58,847 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0628 (0.0648) Prec@1 92.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:50:58,858 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0703) Prec@1 85.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:50:58,867 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0677) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:50:58,874 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0680) Prec@1 86.000 (88.000) Prec@5 99.000 (99.800) +2022-11-14 16:50:58,881 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0402 (0.0634) Prec@1 95.000 (89.167) Prec@5 99.000 (99.667) +2022-11-14 16:50:58,888 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0641) Prec@1 89.000 (89.143) Prec@5 99.000 (99.571) +2022-11-14 16:50:58,897 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0939 (0.0678) Prec@1 85.000 (88.625) Prec@5 97.000 (99.250) +2022-11-14 16:50:58,903 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0683) Prec@1 90.000 (88.778) Prec@5 97.000 (99.000) +2022-11-14 16:50:58,910 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0699) Prec@1 86.000 (88.500) Prec@5 99.000 (99.000) +2022-11-14 16:50:58,918 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0687) Prec@1 89.000 (88.545) Prec@5 100.000 (99.091) +2022-11-14 16:50:58,926 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0692) Prec@1 88.000 (88.500) Prec@5 100.000 (99.167) +2022-11-14 16:50:58,934 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0694) Prec@1 88.000 (88.462) Prec@5 99.000 (99.154) +2022-11-14 16:50:58,941 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0697) Prec@1 89.000 (88.500) Prec@5 99.000 (99.143) +2022-11-14 16:50:58,949 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0708) Prec@1 87.000 (88.400) Prec@5 99.000 (99.133) +2022-11-14 16:50:58,957 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0707) Prec@1 89.000 (88.438) Prec@5 100.000 (99.188) +2022-11-14 16:50:58,964 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0697) Prec@1 92.000 (88.647) Prec@5 98.000 (99.118) +2022-11-14 16:50:58,971 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1154 (0.0722) Prec@1 83.000 (88.333) Prec@5 100.000 (99.167) +2022-11-14 16:50:58,979 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0734) Prec@1 86.000 (88.211) Prec@5 98.000 (99.105) +2022-11-14 16:50:58,987 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1153 (0.0754) Prec@1 82.000 (87.900) Prec@5 96.000 (98.950) +2022-11-14 16:50:58,994 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0752) Prec@1 90.000 (88.000) Prec@5 100.000 (99.000) +2022-11-14 16:50:59,002 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0765) Prec@1 85.000 (87.864) Prec@5 100.000 (99.045) +2022-11-14 16:50:59,009 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0775) Prec@1 86.000 (87.783) Prec@5 96.000 (98.913) +2022-11-14 16:50:59,017 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0775) Prec@1 86.000 (87.708) Prec@5 100.000 (98.958) +2022-11-14 16:50:59,025 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0780) Prec@1 87.000 (87.680) Prec@5 99.000 (98.960) +2022-11-14 16:50:59,032 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0786) Prec@1 87.000 (87.654) Prec@5 97.000 (98.885) +2022-11-14 16:50:59,040 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0780) Prec@1 89.000 (87.704) Prec@5 100.000 (98.926) +2022-11-14 16:50:59,048 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0768) Prec@1 93.000 (87.893) Prec@5 98.000 (98.893) +2022-11-14 16:50:59,055 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0765) Prec@1 89.000 (87.931) Prec@5 99.000 (98.897) +2022-11-14 16:50:59,063 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0763) Prec@1 89.000 (87.967) Prec@5 99.000 (98.900) +2022-11-14 16:50:59,070 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0758) Prec@1 91.000 (88.065) Prec@5 100.000 (98.935) +2022-11-14 16:50:59,078 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0757) Prec@1 90.000 (88.125) Prec@5 98.000 (98.906) +2022-11-14 16:50:59,088 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0757) Prec@1 87.000 (88.091) Prec@5 100.000 (98.939) +2022-11-14 16:50:59,096 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0765) Prec@1 83.000 (87.941) Prec@5 100.000 (98.971) +2022-11-14 16:50:59,104 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0769) Prec@1 84.000 (87.829) Prec@5 97.000 (98.914) +2022-11-14 16:50:59,112 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0770) Prec@1 88.000 (87.833) Prec@5 99.000 (98.917) +2022-11-14 16:50:59,119 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0773) Prec@1 85.000 (87.757) Prec@5 97.000 (98.865) +2022-11-14 16:50:59,127 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1119 (0.0782) Prec@1 81.000 (87.579) Prec@5 100.000 (98.895) +2022-11-14 16:50:59,135 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0775) Prec@1 94.000 (87.744) Prec@5 99.000 (98.897) +2022-11-14 16:50:59,142 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0771) Prec@1 90.000 (87.800) Prec@5 97.000 (98.850) +2022-11-14 16:50:59,150 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0776) Prec@1 86.000 (87.756) Prec@5 97.000 (98.805) +2022-11-14 16:50:59,157 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0775) Prec@1 88.000 (87.762) Prec@5 100.000 (98.833) +2022-11-14 16:50:59,165 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0367 (0.0765) Prec@1 94.000 (87.907) Prec@5 99.000 (98.837) +2022-11-14 16:50:59,172 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0764) Prec@1 90.000 (87.955) Prec@5 98.000 (98.818) +2022-11-14 16:50:59,180 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0760) Prec@1 92.000 (88.044) Prec@5 100.000 (98.844) +2022-11-14 16:50:59,187 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0768) Prec@1 81.000 (87.891) Prec@5 98.000 (98.826) +2022-11-14 16:50:59,195 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0769) Prec@1 88.000 (87.894) Prec@5 100.000 (98.851) +2022-11-14 16:50:59,202 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0773) Prec@1 86.000 (87.854) Prec@5 99.000 (98.854) +2022-11-14 16:50:59,210 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0415 (0.0766) Prec@1 93.000 (87.959) Prec@5 100.000 (98.878) +2022-11-14 16:50:59,218 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1157 (0.0774) Prec@1 81.000 (87.820) Prec@5 100.000 (98.900) +2022-11-14 16:50:59,226 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0772) Prec@1 87.000 (87.804) Prec@5 100.000 (98.922) +2022-11-14 16:50:59,233 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0772) Prec@1 87.000 (87.788) Prec@5 99.000 (98.923) +2022-11-14 16:50:59,241 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0770) Prec@1 87.000 (87.774) Prec@5 100.000 (98.943) +2022-11-14 16:50:59,248 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0766) Prec@1 91.000 (87.833) Prec@5 99.000 (98.944) +2022-11-14 16:50:59,256 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0764) Prec@1 89.000 (87.855) Prec@5 100.000 (98.964) +2022-11-14 16:50:59,264 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0765) Prec@1 87.000 (87.839) Prec@5 99.000 (98.964) +2022-11-14 16:50:59,271 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0766) Prec@1 87.000 (87.825) Prec@5 100.000 (98.982) +2022-11-14 16:50:59,279 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0765) Prec@1 88.000 (87.828) Prec@5 100.000 (99.000) +2022-11-14 16:50:59,286 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.0770) Prec@1 82.000 (87.729) Prec@5 99.000 (99.000) +2022-11-14 16:50:59,294 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0765) Prec@1 91.000 (87.783) Prec@5 99.000 (99.000) +2022-11-14 16:50:59,302 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0767) Prec@1 86.000 (87.754) Prec@5 97.000 (98.967) +2022-11-14 16:50:59,309 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0766) Prec@1 91.000 (87.806) Prec@5 99.000 (98.968) +2022-11-14 16:50:59,316 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0873 (0.0768) Prec@1 86.000 (87.778) Prec@5 98.000 (98.952) +2022-11-14 16:50:59,324 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0345 (0.0761) Prec@1 94.000 (87.875) Prec@5 100.000 (98.969) +2022-11-14 16:50:59,332 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0763) Prec@1 87.000 (87.862) Prec@5 100.000 (98.985) +2022-11-14 16:50:59,340 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0763) Prec@1 87.000 (87.848) Prec@5 99.000 (98.985) +2022-11-14 16:50:59,347 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0401 (0.0758) Prec@1 93.000 (87.925) Prec@5 99.000 (98.985) +2022-11-14 16:50:59,355 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0757) Prec@1 91.000 (87.971) Prec@5 99.000 (98.985) +2022-11-14 16:50:59,363 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0488 (0.0753) Prec@1 92.000 (88.029) Prec@5 99.000 (98.986) +2022-11-14 16:50:59,371 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0829 (0.0754) Prec@1 88.000 (88.029) Prec@5 99.000 (98.986) +2022-11-14 16:50:59,378 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0920 (0.0757) Prec@1 88.000 (88.028) Prec@5 99.000 (98.986) +2022-11-14 16:50:59,386 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0655 (0.0755) Prec@1 89.000 (88.042) Prec@5 100.000 (99.000) +2022-11-14 16:50:59,393 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0547 (0.0752) Prec@1 91.000 (88.082) Prec@5 99.000 (99.000) +2022-11-14 16:50:59,401 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0517 (0.0749) Prec@1 92.000 (88.135) Prec@5 100.000 (99.014) +2022-11-14 16:50:59,408 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0751) Prec@1 85.000 (88.093) Prec@5 100.000 (99.027) +2022-11-14 16:50:59,416 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0750) Prec@1 88.000 (88.092) Prec@5 100.000 (99.039) +2022-11-14 16:50:59,423 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0767 (0.0750) Prec@1 87.000 (88.078) Prec@5 98.000 (99.026) +2022-11-14 16:50:59,431 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1155 (0.0755) Prec@1 81.000 (87.987) Prec@5 100.000 (99.038) +2022-11-14 16:50:59,438 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0768 (0.0756) Prec@1 86.000 (87.962) Prec@5 100.000 (99.051) +2022-11-14 16:50:59,446 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0739 (0.0755) Prec@1 88.000 (87.963) Prec@5 100.000 (99.062) +2022-11-14 16:50:59,453 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0827 (0.0756) Prec@1 88.000 (87.963) Prec@5 99.000 (99.062) +2022-11-14 16:50:59,461 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0969 (0.0759) Prec@1 84.000 (87.915) Prec@5 100.000 (99.073) +2022-11-14 16:50:59,468 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0966 (0.0761) Prec@1 84.000 (87.867) Prec@5 100.000 (99.084) +2022-11-14 16:50:59,476 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0808 (0.0762) Prec@1 87.000 (87.857) Prec@5 98.000 (99.071) +2022-11-14 16:50:59,484 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0762) Prec@1 89.000 (87.871) Prec@5 100.000 (99.082) +2022-11-14 16:50:59,491 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0997 (0.0765) Prec@1 84.000 (87.826) Prec@5 100.000 (99.093) +2022-11-14 16:50:59,499 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0866 (0.0766) Prec@1 85.000 (87.793) Prec@5 99.000 (99.092) +2022-11-14 16:50:59,507 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0766) Prec@1 88.000 (87.795) Prec@5 98.000 (99.080) +2022-11-14 16:50:59,514 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0572 (0.0763) Prec@1 93.000 (87.854) Prec@5 100.000 (99.090) +2022-11-14 16:50:59,522 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0764) Prec@1 87.000 (87.844) Prec@5 98.000 (99.078) +2022-11-14 16:50:59,529 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0438 (0.0760) Prec@1 94.000 (87.912) Prec@5 100.000 (99.088) +2022-11-14 16:50:59,537 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0759) Prec@1 91.000 (87.946) Prec@5 100.000 (99.098) +2022-11-14 16:50:59,544 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0948 (0.0761) Prec@1 85.000 (87.914) Prec@5 100.000 (99.108) +2022-11-14 16:50:59,552 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0760) Prec@1 90.000 (87.936) Prec@5 99.000 (99.106) +2022-11-14 16:50:59,559 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0759) Prec@1 89.000 (87.947) Prec@5 99.000 (99.105) +2022-11-14 16:50:59,566 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0758) Prec@1 88.000 (87.948) Prec@5 98.000 (99.094) +2022-11-14 16:50:59,574 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0468 (0.0755) Prec@1 92.000 (87.990) Prec@5 99.000 (99.093) +2022-11-14 16:50:59,581 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0859 (0.0756) Prec@1 87.000 (87.980) Prec@5 100.000 (99.102) +2022-11-14 16:50:59,589 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0828 (0.0757) Prec@1 87.000 (87.970) Prec@5 99.000 (99.101) +2022-11-14 16:50:59,596 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0757) Prec@1 88.000 (87.970) Prec@5 98.000 (99.090) +2022-11-14 16:50:59,652 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:50:59,987 Epoch: [398][0/500] Time 0.028 (0.028) Data 0.250 (0.250) Loss 0.0229 (0.0229) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:00,198 Epoch: [398][10/500] Time 0.022 (0.020) Data 0.002 (0.024) Loss 0.0156 (0.0192) Prec@1 97.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:00,397 Epoch: [398][20/500] Time 0.017 (0.019) Data 0.002 (0.013) Loss 0.0226 (0.0204) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:00,587 Epoch: [398][30/500] Time 0.017 (0.018) Data 0.002 (0.010) Loss 0.0194 (0.0201) Prec@1 97.000 (96.250) Prec@5 99.000 (99.750) +2022-11-14 16:51:00,775 Epoch: [398][40/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0200 (0.0201) Prec@1 96.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:51:00,964 Epoch: [398][50/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0338 (0.0224) Prec@1 94.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 16:51:01,160 Epoch: [398][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0198 (0.0220) Prec@1 97.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 16:51:01,347 Epoch: [398][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0404 (0.0243) Prec@1 94.000 (95.750) Prec@5 100.000 (99.875) +2022-11-14 16:51:01,536 Epoch: [398][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0259 (0.0245) Prec@1 97.000 (95.889) Prec@5 100.000 (99.889) +2022-11-14 16:51:01,724 Epoch: [398][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0221 (0.0243) Prec@1 96.000 (95.900) Prec@5 100.000 (99.900) +2022-11-14 16:51:01,919 Epoch: [398][100/500] Time 0.021 (0.017) Data 0.001 (0.004) Loss 0.0220 (0.0240) Prec@1 97.000 (96.000) Prec@5 100.000 (99.909) +2022-11-14 16:51:02,191 Epoch: [398][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0374 (0.0252) Prec@1 93.000 (95.750) Prec@5 100.000 (99.917) +2022-11-14 16:51:02,466 Epoch: [398][120/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0364 (0.0260) Prec@1 94.000 (95.615) Prec@5 100.000 (99.923) +2022-11-14 16:51:02,741 Epoch: [398][130/500] Time 0.025 (0.019) Data 0.002 (0.004) Loss 0.0210 (0.0257) Prec@1 96.000 (95.643) Prec@5 100.000 (99.929) +2022-11-14 16:51:03,017 Epoch: [398][140/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0191 (0.0252) Prec@1 97.000 (95.733) Prec@5 100.000 (99.933) +2022-11-14 16:51:03,299 Epoch: [398][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0329 (0.0257) Prec@1 93.000 (95.562) Prec@5 99.000 (99.875) +2022-11-14 16:51:03,581 Epoch: [398][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0227 (0.0255) Prec@1 95.000 (95.529) Prec@5 100.000 (99.882) +2022-11-14 16:51:03,858 Epoch: [398][170/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0335 (0.0260) Prec@1 93.000 (95.389) Prec@5 99.000 (99.833) +2022-11-14 16:51:04,136 Epoch: [398][180/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0309 (0.0262) Prec@1 95.000 (95.368) Prec@5 100.000 (99.842) +2022-11-14 16:51:04,412 Epoch: [398][190/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0372 (0.0268) Prec@1 94.000 (95.300) Prec@5 100.000 (99.850) +2022-11-14 16:51:04,683 Epoch: [398][200/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0228 (0.0266) Prec@1 97.000 (95.381) Prec@5 99.000 (99.810) +2022-11-14 16:51:04,960 Epoch: [398][210/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0188 (0.0262) Prec@1 97.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 16:51:05,239 Epoch: [398][220/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0415 (0.0269) Prec@1 93.000 (95.348) Prec@5 99.000 (99.783) +2022-11-14 16:51:05,516 Epoch: [398][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0270 (0.0269) Prec@1 96.000 (95.375) Prec@5 100.000 (99.792) +2022-11-14 16:51:05,790 Epoch: [398][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0358 (0.0273) Prec@1 93.000 (95.280) Prec@5 99.000 (99.760) +2022-11-14 16:51:06,067 Epoch: [398][250/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0256 (0.0272) Prec@1 96.000 (95.308) Prec@5 100.000 (99.769) +2022-11-14 16:51:06,350 Epoch: [398][260/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0428 (0.0278) Prec@1 92.000 (95.185) Prec@5 100.000 (99.778) +2022-11-14 16:51:06,631 Epoch: [398][270/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0159 (0.0273) Prec@1 98.000 (95.286) Prec@5 100.000 (99.786) +2022-11-14 16:51:06,908 Epoch: [398][280/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0375 (0.0277) Prec@1 94.000 (95.241) Prec@5 99.000 (99.759) +2022-11-14 16:51:07,190 Epoch: [398][290/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0429 (0.0282) Prec@1 92.000 (95.133) Prec@5 99.000 (99.733) +2022-11-14 16:51:07,470 Epoch: [398][300/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0132 (0.0277) Prec@1 99.000 (95.258) Prec@5 100.000 (99.742) +2022-11-14 16:51:07,751 Epoch: [398][310/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0286 (0.0277) Prec@1 95.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 16:51:08,027 Epoch: [398][320/500] Time 0.022 (0.022) Data 0.001 (0.002) Loss 0.0131 (0.0273) Prec@1 98.000 (95.333) Prec@5 100.000 (99.758) +2022-11-14 16:51:08,304 Epoch: [398][330/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0198 (0.0271) Prec@1 96.000 (95.353) Prec@5 99.000 (99.735) +2022-11-14 16:51:08,580 Epoch: [398][340/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0434 (0.0275) Prec@1 93.000 (95.286) Prec@5 100.000 (99.743) +2022-11-14 16:51:08,865 Epoch: [398][350/500] Time 0.028 (0.022) Data 0.001 (0.002) Loss 0.0342 (0.0277) Prec@1 94.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 16:51:09,146 Epoch: [398][360/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0208 (0.0275) Prec@1 97.000 (95.297) Prec@5 100.000 (99.757) +2022-11-14 16:51:09,426 Epoch: [398][370/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0353 (0.0277) Prec@1 94.000 (95.263) Prec@5 100.000 (99.763) +2022-11-14 16:51:09,709 Epoch: [398][380/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0404 (0.0281) Prec@1 93.000 (95.205) Prec@5 99.000 (99.744) +2022-11-14 16:51:09,991 Epoch: [398][390/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0144 (0.0277) Prec@1 98.000 (95.275) Prec@5 100.000 (99.750) +2022-11-14 16:51:10,270 Epoch: [398][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0339 (0.0279) Prec@1 93.000 (95.220) Prec@5 100.000 (99.756) +2022-11-14 16:51:10,550 Epoch: [398][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0201 (0.0277) Prec@1 96.000 (95.238) Prec@5 100.000 (99.762) +2022-11-14 16:51:10,830 Epoch: [398][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0417 (0.0280) Prec@1 94.000 (95.209) Prec@5 100.000 (99.767) +2022-11-14 16:51:11,113 Epoch: [398][430/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0256 (0.0280) Prec@1 97.000 (95.250) Prec@5 100.000 (99.773) +2022-11-14 16:51:11,389 Epoch: [398][440/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0430 (0.0283) Prec@1 93.000 (95.200) Prec@5 100.000 (99.778) +2022-11-14 16:51:11,669 Epoch: [398][450/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0253 (0.0282) Prec@1 96.000 (95.217) Prec@5 100.000 (99.783) +2022-11-14 16:51:11,949 Epoch: [398][460/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0123 (0.0279) Prec@1 98.000 (95.277) Prec@5 99.000 (99.766) +2022-11-14 16:51:12,228 Epoch: [398][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0233 (0.0278) Prec@1 96.000 (95.292) Prec@5 100.000 (99.771) +2022-11-14 16:51:12,505 Epoch: [398][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0533 (0.0283) Prec@1 91.000 (95.204) Prec@5 100.000 (99.776) +2022-11-14 16:51:12,788 Epoch: [398][490/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0110 (0.0280) Prec@1 98.000 (95.260) Prec@5 100.000 (99.780) +2022-11-14 16:51:13,037 Epoch: [398][499/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0403 (0.0282) Prec@1 93.000 (95.216) Prec@5 100.000 (99.784) +2022-11-14 16:51:13,338 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0665 (0.0665) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:13,347 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0691 (0.0678) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:13,357 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0723 (0.0693) Prec@1 88.000 (89.667) Prec@5 99.000 (99.667) +2022-11-14 16:51:13,366 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0723) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:51:13,373 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1036 (0.0786) Prec@1 82.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 16:51:13,380 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0406 (0.0722) Prec@1 93.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 16:51:13,387 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0728) Prec@1 87.000 (88.286) Prec@5 100.000 (99.714) +2022-11-14 16:51:13,396 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0927 (0.0753) Prec@1 86.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 16:51:13,403 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1063 (0.0788) Prec@1 85.000 (87.667) Prec@5 97.000 (99.222) +2022-11-14 16:51:13,410 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0781) Prec@1 90.000 (87.900) Prec@5 99.000 (99.200) +2022-11-14 16:51:13,418 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0761) Prec@1 93.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 16:51:13,426 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0778) Prec@1 86.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 16:51:13,433 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0757) Prec@1 90.000 (88.308) Prec@5 99.000 (99.308) +2022-11-14 16:51:13,441 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0749) Prec@1 88.000 (88.286) Prec@5 99.000 (99.286) +2022-11-14 16:51:13,449 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0738) Prec@1 91.000 (88.467) Prec@5 99.000 (99.267) +2022-11-14 16:51:13,457 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0745) Prec@1 87.000 (88.375) Prec@5 100.000 (99.312) +2022-11-14 16:51:13,465 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0731) Prec@1 93.000 (88.647) Prec@5 99.000 (99.294) +2022-11-14 16:51:13,473 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.0754) Prec@1 82.000 (88.278) Prec@5 99.000 (99.278) +2022-11-14 16:51:13,480 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0764) Prec@1 83.000 (88.000) Prec@5 98.000 (99.211) +2022-11-14 16:51:13,488 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1205 (0.0787) Prec@1 81.000 (87.650) Prec@5 98.000 (99.150) +2022-11-14 16:51:13,496 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0784) Prec@1 90.000 (87.762) Prec@5 98.000 (99.095) +2022-11-14 16:51:13,504 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0787) Prec@1 88.000 (87.773) Prec@5 99.000 (99.091) +2022-11-14 16:51:13,512 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0795) Prec@1 85.000 (87.652) Prec@5 98.000 (99.043) +2022-11-14 16:51:13,519 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0796) Prec@1 87.000 (87.625) Prec@5 99.000 (99.042) +2022-11-14 16:51:13,527 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0791) Prec@1 91.000 (87.760) Prec@5 99.000 (99.040) +2022-11-14 16:51:13,534 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0793) Prec@1 85.000 (87.654) Prec@5 99.000 (99.038) +2022-11-14 16:51:13,542 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0425 (0.0779) Prec@1 92.000 (87.815) Prec@5 100.000 (99.074) +2022-11-14 16:51:13,550 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0776) Prec@1 88.000 (87.821) Prec@5 100.000 (99.107) +2022-11-14 16:51:13,557 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0775) Prec@1 87.000 (87.793) Prec@5 97.000 (99.034) +2022-11-14 16:51:13,565 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0778) Prec@1 85.000 (87.700) Prec@5 98.000 (99.000) +2022-11-14 16:51:13,574 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0769) Prec@1 92.000 (87.839) Prec@5 100.000 (99.032) +2022-11-14 16:51:13,581 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0771) Prec@1 88.000 (87.844) Prec@5 99.000 (99.031) +2022-11-14 16:51:13,589 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0767) Prec@1 90.000 (87.909) Prec@5 99.000 (99.030) +2022-11-14 16:51:13,597 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0770) Prec@1 84.000 (87.794) Prec@5 100.000 (99.059) +2022-11-14 16:51:13,604 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0772) Prec@1 86.000 (87.743) Prec@5 99.000 (99.057) +2022-11-14 16:51:13,612 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0768) Prec@1 90.000 (87.806) Prec@5 99.000 (99.056) +2022-11-14 16:51:13,620 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0772) Prec@1 85.000 (87.730) Prec@5 98.000 (99.027) +2022-11-14 16:51:13,628 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0778) Prec@1 86.000 (87.684) Prec@5 99.000 (99.026) +2022-11-14 16:51:13,635 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0775) Prec@1 90.000 (87.744) Prec@5 99.000 (99.026) +2022-11-14 16:51:13,643 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0776) Prec@1 88.000 (87.750) Prec@5 100.000 (99.050) +2022-11-14 16:51:13,651 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0770) Prec@1 92.000 (87.854) Prec@5 99.000 (99.049) +2022-11-14 16:51:13,659 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0768) Prec@1 90.000 (87.905) Prec@5 98.000 (99.024) +2022-11-14 16:51:13,667 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0765) Prec@1 91.000 (87.977) Prec@5 99.000 (99.023) +2022-11-14 16:51:13,674 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0763) Prec@1 90.000 (88.023) Prec@5 99.000 (99.023) +2022-11-14 16:51:13,682 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0435 (0.0755) Prec@1 94.000 (88.156) Prec@5 100.000 (99.044) +2022-11-14 16:51:13,690 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1084 (0.0762) Prec@1 83.000 (88.043) Prec@5 100.000 (99.065) +2022-11-14 16:51:13,697 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0763) Prec@1 87.000 (88.021) Prec@5 99.000 (99.064) +2022-11-14 16:51:13,705 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1136 (0.0771) Prec@1 80.000 (87.854) Prec@5 98.000 (99.042) +2022-11-14 16:51:13,713 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0767) Prec@1 92.000 (87.939) Prec@5 100.000 (99.061) +2022-11-14 16:51:13,720 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1192 (0.0776) Prec@1 79.000 (87.760) Prec@5 100.000 (99.080) +2022-11-14 16:51:13,728 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0774) Prec@1 89.000 (87.784) Prec@5 100.000 (99.098) +2022-11-14 16:51:13,736 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0776) Prec@1 85.000 (87.731) Prec@5 100.000 (99.115) +2022-11-14 16:51:13,744 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0775) Prec@1 86.000 (87.698) Prec@5 100.000 (99.132) +2022-11-14 16:51:13,752 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0775) Prec@1 88.000 (87.704) Prec@5 100.000 (99.148) +2022-11-14 16:51:13,760 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0780) Prec@1 84.000 (87.636) Prec@5 99.000 (99.145) +2022-11-14 16:51:13,768 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0776) Prec@1 90.000 (87.679) Prec@5 99.000 (99.143) +2022-11-14 16:51:13,776 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0773) Prec@1 90.000 (87.719) Prec@5 100.000 (99.158) +2022-11-14 16:51:13,784 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0772) Prec@1 89.000 (87.741) Prec@5 99.000 (99.155) +2022-11-14 16:51:13,791 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0778) Prec@1 83.000 (87.661) Prec@5 100.000 (99.169) +2022-11-14 16:51:13,799 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0777) Prec@1 86.000 (87.633) Prec@5 100.000 (99.183) +2022-11-14 16:51:13,807 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0778) Prec@1 88.000 (87.639) Prec@5 100.000 (99.197) +2022-11-14 16:51:13,814 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0780) Prec@1 86.000 (87.613) Prec@5 98.000 (99.177) +2022-11-14 16:51:13,822 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0781) Prec@1 89.000 (87.635) Prec@5 100.000 (99.190) +2022-11-14 16:51:13,829 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0775) Prec@1 94.000 (87.734) Prec@5 100.000 (99.203) +2022-11-14 16:51:13,837 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0777) Prec@1 86.000 (87.708) Prec@5 99.000 (99.200) +2022-11-14 16:51:13,844 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0775) Prec@1 89.000 (87.727) Prec@5 100.000 (99.212) +2022-11-14 16:51:13,851 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0772) Prec@1 92.000 (87.791) Prec@5 99.000 (99.209) +2022-11-14 16:51:13,859 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0772) Prec@1 88.000 (87.794) Prec@5 98.000 (99.191) +2022-11-14 16:51:13,867 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0771) Prec@1 87.000 (87.783) Prec@5 99.000 (99.188) +2022-11-14 16:51:13,874 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0772) Prec@1 86.000 (87.757) Prec@5 99.000 (99.186) +2022-11-14 16:51:13,882 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0776) Prec@1 83.000 (87.690) Prec@5 99.000 (99.183) +2022-11-14 16:51:13,889 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0774) Prec@1 90.000 (87.722) Prec@5 100.000 (99.194) +2022-11-14 16:51:13,897 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0772) Prec@1 90.000 (87.753) Prec@5 99.000 (99.192) +2022-11-14 16:51:13,904 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0768) Prec@1 93.000 (87.824) Prec@5 100.000 (99.203) +2022-11-14 16:51:13,912 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0769) Prec@1 87.000 (87.813) Prec@5 100.000 (99.213) +2022-11-14 16:51:13,919 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0766) Prec@1 88.000 (87.816) Prec@5 99.000 (99.211) +2022-11-14 16:51:13,927 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0767) Prec@1 89.000 (87.831) Prec@5 99.000 (99.208) +2022-11-14 16:51:13,934 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0768) Prec@1 85.000 (87.795) Prec@5 100.000 (99.218) +2022-11-14 16:51:13,942 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0769) Prec@1 88.000 (87.797) Prec@5 100.000 (99.228) +2022-11-14 16:51:13,949 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0768) Prec@1 89.000 (87.812) Prec@5 100.000 (99.237) +2022-11-14 16:51:13,957 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0768) Prec@1 87.000 (87.802) Prec@5 99.000 (99.235) +2022-11-14 16:51:13,964 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0770) Prec@1 87.000 (87.793) Prec@5 100.000 (99.244) +2022-11-14 16:51:13,972 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0772) Prec@1 86.000 (87.771) Prec@5 99.000 (99.241) +2022-11-14 16:51:13,979 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0771) Prec@1 88.000 (87.774) Prec@5 100.000 (99.250) +2022-11-14 16:51:13,987 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0772) Prec@1 85.000 (87.741) Prec@5 99.000 (99.247) +2022-11-14 16:51:13,995 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0775) Prec@1 86.000 (87.721) Prec@5 100.000 (99.256) +2022-11-14 16:51:14,002 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0775) Prec@1 89.000 (87.736) Prec@5 100.000 (99.264) +2022-11-14 16:51:14,010 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0774) Prec@1 88.000 (87.739) Prec@5 99.000 (99.261) +2022-11-14 16:51:14,017 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0774) Prec@1 87.000 (87.730) Prec@5 100.000 (99.270) +2022-11-14 16:51:14,025 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0773) Prec@1 88.000 (87.733) Prec@5 100.000 (99.278) +2022-11-14 16:51:14,032 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0771) Prec@1 92.000 (87.780) Prec@5 100.000 (99.286) +2022-11-14 16:51:14,040 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0769) Prec@1 92.000 (87.826) Prec@5 100.000 (99.293) +2022-11-14 16:51:14,048 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0770) Prec@1 88.000 (87.828) Prec@5 100.000 (99.301) +2022-11-14 16:51:14,056 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0768) Prec@1 90.000 (87.851) Prec@5 100.000 (99.309) +2022-11-14 16:51:14,063 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0769) Prec@1 87.000 (87.842) Prec@5 99.000 (99.305) +2022-11-14 16:51:14,071 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0770) Prec@1 87.000 (87.833) Prec@5 99.000 (99.302) +2022-11-14 16:51:14,078 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0766) Prec@1 93.000 (87.887) Prec@5 99.000 (99.299) +2022-11-14 16:51:14,086 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0768) Prec@1 86.000 (87.867) Prec@5 98.000 (99.286) +2022-11-14 16:51:14,093 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0770) Prec@1 85.000 (87.838) Prec@5 99.000 (99.283) +2022-11-14 16:51:14,101 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0769) Prec@1 89.000 (87.850) Prec@5 100.000 (99.290) +2022-11-14 16:51:14,169 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:51:14,490 Epoch: [399][0/500] Time 0.022 (0.022) Data 0.243 (0.243) Loss 0.0302 (0.0302) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:14,695 Epoch: [399][10/500] Time 0.022 (0.019) Data 0.002 (0.024) Loss 0.0265 (0.0284) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:14,903 Epoch: [399][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0271 (0.0279) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:51:15,108 Epoch: [399][30/500] Time 0.025 (0.018) Data 0.001 (0.010) Loss 0.0230 (0.0267) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:15,307 Epoch: [399][40/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0354 (0.0284) Prec@1 95.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:51:15,498 Epoch: [399][50/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0315 (0.0289) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:15,694 Epoch: [399][60/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0354 (0.0299) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:15,894 Epoch: [399][70/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0271 (0.0295) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:16,102 Epoch: [399][80/500] Time 0.022 (0.018) Data 0.001 (0.005) Loss 0.0272 (0.0293) Prec@1 96.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:51:16,361 Epoch: [399][90/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0202 (0.0284) Prec@1 98.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:51:16,626 Epoch: [399][100/500] Time 0.025 (0.019) Data 0.002 (0.004) Loss 0.0306 (0.0286) Prec@1 96.000 (95.455) Prec@5 100.000 (100.000) +2022-11-14 16:51:16,891 Epoch: [399][110/500] Time 0.025 (0.019) Data 0.001 (0.004) Loss 0.0388 (0.0294) Prec@1 94.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:51:17,160 Epoch: [399][120/500] Time 0.024 (0.020) Data 0.002 (0.004) Loss 0.0335 (0.0297) Prec@1 92.000 (95.077) Prec@5 99.000 (99.923) +2022-11-14 16:51:17,432 Epoch: [399][130/500] Time 0.029 (0.020) Data 0.002 (0.004) Loss 0.0136 (0.0286) Prec@1 97.000 (95.214) Prec@5 100.000 (99.929) +2022-11-14 16:51:17,706 Epoch: [399][140/500] Time 0.020 (0.020) Data 0.002 (0.003) Loss 0.0238 (0.0283) Prec@1 96.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 16:51:17,972 Epoch: [399][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0388 (0.0289) Prec@1 93.000 (95.125) Prec@5 100.000 (99.938) +2022-11-14 16:51:18,246 Epoch: [399][160/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0196 (0.0284) Prec@1 96.000 (95.176) Prec@5 100.000 (99.941) +2022-11-14 16:51:18,520 Epoch: [399][170/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0182 (0.0278) Prec@1 98.000 (95.333) Prec@5 100.000 (99.944) +2022-11-14 16:51:18,794 Epoch: [399][180/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0371 (0.0283) Prec@1 93.000 (95.211) Prec@5 100.000 (99.947) +2022-11-14 16:51:19,070 Epoch: [399][190/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0216 (0.0280) Prec@1 97.000 (95.300) Prec@5 100.000 (99.950) +2022-11-14 16:51:19,340 Epoch: [399][200/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0272 (0.0279) Prec@1 97.000 (95.381) Prec@5 100.000 (99.952) +2022-11-14 16:51:19,611 Epoch: [399][210/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0154 (0.0274) Prec@1 98.000 (95.500) Prec@5 100.000 (99.955) +2022-11-14 16:51:19,876 Epoch: [399][220/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0165 (0.0269) Prec@1 97.000 (95.565) Prec@5 100.000 (99.957) +2022-11-14 16:51:20,145 Epoch: [399][230/500] Time 0.022 (0.022) Data 0.002 (0.003) Loss 0.0533 (0.0280) Prec@1 90.000 (95.333) Prec@5 100.000 (99.958) +2022-11-14 16:51:20,409 Epoch: [399][240/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0130 (0.0274) Prec@1 98.000 (95.440) Prec@5 100.000 (99.960) +2022-11-14 16:51:20,676 Epoch: [399][250/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0434 (0.0280) Prec@1 92.000 (95.308) Prec@5 100.000 (99.962) +2022-11-14 16:51:20,941 Epoch: [399][260/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0418 (0.0285) Prec@1 94.000 (95.259) Prec@5 100.000 (99.963) +2022-11-14 16:51:21,211 Epoch: [399][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0323 (0.0286) Prec@1 95.000 (95.250) Prec@5 100.000 (99.964) +2022-11-14 16:51:21,476 Epoch: [399][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0320 (0.0288) Prec@1 95.000 (95.241) Prec@5 100.000 (99.966) +2022-11-14 16:51:21,739 Epoch: [399][290/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0228 (0.0286) Prec@1 96.000 (95.267) Prec@5 100.000 (99.967) +2022-11-14 16:51:22,006 Epoch: [399][300/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0174 (0.0282) Prec@1 97.000 (95.323) Prec@5 100.000 (99.968) +2022-11-14 16:51:22,271 Epoch: [399][310/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0219 (0.0280) Prec@1 96.000 (95.344) Prec@5 100.000 (99.969) +2022-11-14 16:51:22,535 Epoch: [399][320/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0216 (0.0278) Prec@1 97.000 (95.394) Prec@5 100.000 (99.970) +2022-11-14 16:51:22,802 Epoch: [399][330/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0472 (0.0284) Prec@1 94.000 (95.353) Prec@5 100.000 (99.971) +2022-11-14 16:51:23,065 Epoch: [399][340/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0204 (0.0282) Prec@1 95.000 (95.343) Prec@5 100.000 (99.971) +2022-11-14 16:51:23,329 Epoch: [399][350/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0484 (0.0287) Prec@1 91.000 (95.222) Prec@5 100.000 (99.972) +2022-11-14 16:51:23,593 Epoch: [399][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0411 (0.0290) Prec@1 92.000 (95.135) Prec@5 99.000 (99.946) +2022-11-14 16:51:23,862 Epoch: [399][370/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0308 (0.0291) Prec@1 95.000 (95.132) Prec@5 100.000 (99.947) +2022-11-14 16:51:24,132 Epoch: [399][380/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0329 (0.0292) Prec@1 95.000 (95.128) Prec@5 100.000 (99.949) +2022-11-14 16:51:24,395 Epoch: [399][390/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0470 (0.0296) Prec@1 91.000 (95.025) Prec@5 99.000 (99.925) +2022-11-14 16:51:24,660 Epoch: [399][400/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0196 (0.0294) Prec@1 97.000 (95.073) Prec@5 100.000 (99.927) +2022-11-14 16:51:24,925 Epoch: [399][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0270 (0.0293) Prec@1 94.000 (95.048) Prec@5 99.000 (99.905) +2022-11-14 16:51:25,193 Epoch: [399][420/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0292 (0.0293) Prec@1 94.000 (95.023) Prec@5 99.000 (99.884) +2022-11-14 16:51:25,462 Epoch: [399][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0197 (0.0291) Prec@1 97.000 (95.068) Prec@5 100.000 (99.886) +2022-11-14 16:51:25,731 Epoch: [399][440/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0164 (0.0288) Prec@1 97.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:51:26,002 Epoch: [399][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0230 (0.0287) Prec@1 95.000 (95.109) Prec@5 100.000 (99.891) +2022-11-14 16:51:26,273 Epoch: [399][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0050 (0.0282) Prec@1 100.000 (95.213) Prec@5 100.000 (99.894) +2022-11-14 16:51:26,540 Epoch: [399][470/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0344 (0.0283) Prec@1 94.000 (95.188) Prec@5 100.000 (99.896) +2022-11-14 16:51:26,807 Epoch: [399][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0129 (0.0280) Prec@1 98.000 (95.245) Prec@5 100.000 (99.898) +2022-11-14 16:51:27,074 Epoch: [399][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0357 (0.0282) Prec@1 94.000 (95.220) Prec@5 99.000 (99.880) +2022-11-14 16:51:27,314 Epoch: [399][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0196 (0.0280) Prec@1 96.000 (95.235) Prec@5 100.000 (99.882) +2022-11-14 16:51:27,626 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0587 (0.0587) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:27,633 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0708) Prec@1 87.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:27,641 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0691) Prec@1 88.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:51:27,650 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0722) Prec@1 86.000 (88.250) Prec@5 98.000 (99.250) +2022-11-14 16:51:27,656 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0704) Prec@1 90.000 (88.600) Prec@5 100.000 (99.400) +2022-11-14 16:51:27,663 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0661) Prec@1 91.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:51:27,670 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0641) Prec@1 92.000 (89.429) Prec@5 100.000 (99.571) +2022-11-14 16:51:27,678 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.0691) Prec@1 83.000 (88.625) Prec@5 98.000 (99.375) +2022-11-14 16:51:27,685 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0723) Prec@1 87.000 (88.444) Prec@5 98.000 (99.222) +2022-11-14 16:51:27,692 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0739) Prec@1 86.000 (88.200) Prec@5 98.000 (99.100) +2022-11-14 16:51:27,700 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0739) Prec@1 86.000 (88.000) Prec@5 100.000 (99.182) +2022-11-14 16:51:27,707 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 88.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 16:51:27,715 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0732) Prec@1 90.000 (88.154) Prec@5 99.000 (99.231) +2022-11-14 16:51:27,723 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0733) Prec@1 89.000 (88.214) Prec@5 100.000 (99.286) +2022-11-14 16:51:27,730 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0729) Prec@1 88.000 (88.200) Prec@5 99.000 (99.267) +2022-11-14 16:51:27,738 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0730) Prec@1 85.000 (88.000) Prec@5 98.000 (99.188) +2022-11-14 16:51:27,746 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0718) Prec@1 93.000 (88.294) Prec@5 99.000 (99.176) +2022-11-14 16:51:27,753 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0731) Prec@1 88.000 (88.278) Prec@5 100.000 (99.222) +2022-11-14 16:51:27,761 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0742) Prec@1 84.000 (88.053) Prec@5 97.000 (99.105) +2022-11-14 16:51:27,769 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0751) Prec@1 87.000 (88.000) Prec@5 97.000 (99.000) +2022-11-14 16:51:27,776 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0747) Prec@1 88.000 (88.000) Prec@5 100.000 (99.048) +2022-11-14 16:51:27,784 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0747) Prec@1 87.000 (87.955) Prec@5 100.000 (99.091) +2022-11-14 16:51:27,791 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0755) Prec@1 84.000 (87.783) Prec@5 98.000 (99.043) +2022-11-14 16:51:27,799 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0760) Prec@1 86.000 (87.708) Prec@5 100.000 (99.083) +2022-11-14 16:51:27,806 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0770) Prec@1 85.000 (87.600) Prec@5 100.000 (99.120) +2022-11-14 16:51:27,814 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0775) Prec@1 86.000 (87.538) Prec@5 98.000 (99.077) +2022-11-14 16:51:27,821 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0767) Prec@1 91.000 (87.667) Prec@5 100.000 (99.111) +2022-11-14 16:51:27,829 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0760) Prec@1 88.000 (87.679) Prec@5 100.000 (99.143) +2022-11-14 16:51:27,837 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0756) Prec@1 91.000 (87.793) Prec@5 98.000 (99.103) +2022-11-14 16:51:27,844 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0762) Prec@1 85.000 (87.700) Prec@5 100.000 (99.133) +2022-11-14 16:51:27,852 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0765) Prec@1 85.000 (87.613) Prec@5 99.000 (99.129) +2022-11-14 16:51:27,859 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0765) Prec@1 87.000 (87.594) Prec@5 98.000 (99.094) +2022-11-14 16:51:27,867 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0766) Prec@1 85.000 (87.515) Prec@5 100.000 (99.121) +2022-11-14 16:51:27,875 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0764) Prec@1 89.000 (87.559) Prec@5 100.000 (99.147) +2022-11-14 16:51:27,882 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0772) Prec@1 86.000 (87.514) Prec@5 97.000 (99.086) +2022-11-14 16:51:27,890 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0772) Prec@1 88.000 (87.528) Prec@5 99.000 (99.083) +2022-11-14 16:51:27,897 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0773) Prec@1 88.000 (87.541) Prec@5 99.000 (99.081) +2022-11-14 16:51:27,905 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0778) Prec@1 86.000 (87.500) Prec@5 99.000 (99.079) +2022-11-14 16:51:27,912 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0772) Prec@1 92.000 (87.615) Prec@5 99.000 (99.077) +2022-11-14 16:51:27,920 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0768) Prec@1 90.000 (87.675) Prec@5 100.000 (99.100) +2022-11-14 16:51:27,928 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0771) Prec@1 86.000 (87.634) Prec@5 99.000 (99.098) +2022-11-14 16:51:27,936 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0769) Prec@1 88.000 (87.643) Prec@5 98.000 (99.071) +2022-11-14 16:51:27,943 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0764) Prec@1 92.000 (87.744) Prec@5 99.000 (99.070) +2022-11-14 16:51:27,951 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0764) Prec@1 87.000 (87.727) Prec@5 98.000 (99.045) +2022-11-14 16:51:27,958 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0762) Prec@1 89.000 (87.756) Prec@5 99.000 (99.044) +2022-11-14 16:51:27,966 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0768) Prec@1 84.000 (87.674) Prec@5 97.000 (99.000) +2022-11-14 16:51:27,974 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0769) Prec@1 88.000 (87.681) Prec@5 100.000 (99.021) +2022-11-14 16:51:27,981 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1140 (0.0776) Prec@1 82.000 (87.562) Prec@5 98.000 (99.000) +2022-11-14 16:51:27,989 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0772) Prec@1 90.000 (87.612) Prec@5 100.000 (99.020) +2022-11-14 16:51:27,997 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0777) Prec@1 88.000 (87.620) Prec@5 100.000 (99.040) +2022-11-14 16:51:28,004 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0774) Prec@1 92.000 (87.706) Prec@5 100.000 (99.059) +2022-11-14 16:51:28,012 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0775) Prec@1 85.000 (87.654) Prec@5 100.000 (99.077) +2022-11-14 16:51:28,020 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0775) Prec@1 87.000 (87.642) Prec@5 99.000 (99.075) +2022-11-14 16:51:28,028 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0773) Prec@1 89.000 (87.667) Prec@5 99.000 (99.074) +2022-11-14 16:51:28,036 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0774) Prec@1 87.000 (87.655) Prec@5 99.000 (99.073) +2022-11-14 16:51:28,043 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0771) Prec@1 91.000 (87.714) Prec@5 100.000 (99.089) +2022-11-14 16:51:28,051 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0772) Prec@1 87.000 (87.702) Prec@5 99.000 (99.088) +2022-11-14 16:51:28,059 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0767) Prec@1 91.000 (87.759) Prec@5 99.000 (99.086) +2022-11-14 16:51:28,067 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0771) Prec@1 85.000 (87.712) Prec@5 99.000 (99.085) +2022-11-14 16:51:28,075 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0773) Prec@1 83.000 (87.633) Prec@5 100.000 (99.100) +2022-11-14 16:51:28,084 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0776) Prec@1 84.000 (87.574) Prec@5 99.000 (99.098) +2022-11-14 16:51:28,092 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0772) Prec@1 92.000 (87.645) Prec@5 99.000 (99.097) +2022-11-14 16:51:28,099 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0770) Prec@1 90.000 (87.683) Prec@5 100.000 (99.111) +2022-11-14 16:51:28,107 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0765) Prec@1 92.000 (87.750) Prec@5 100.000 (99.125) +2022-11-14 16:51:28,114 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0766) Prec@1 88.000 (87.754) Prec@5 100.000 (99.138) +2022-11-14 16:51:28,122 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0767) Prec@1 85.000 (87.712) Prec@5 98.000 (99.121) +2022-11-14 16:51:28,129 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0369 (0.0761) Prec@1 94.000 (87.806) Prec@5 99.000 (99.119) +2022-11-14 16:51:28,137 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0763) Prec@1 87.000 (87.794) Prec@5 98.000 (99.103) +2022-11-14 16:51:28,144 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0760) Prec@1 91.000 (87.841) Prec@5 100.000 (99.116) +2022-11-14 16:51:28,152 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0758) Prec@1 91.000 (87.886) Prec@5 97.000 (99.086) +2022-11-14 16:51:28,159 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0763) Prec@1 84.000 (87.831) Prec@5 100.000 (99.099) +2022-11-14 16:51:28,167 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0762) Prec@1 89.000 (87.847) Prec@5 100.000 (99.111) +2022-11-14 16:51:28,175 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0759) Prec@1 92.000 (87.904) Prec@5 100.000 (99.123) +2022-11-14 16:51:28,182 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0431 (0.0755) Prec@1 94.000 (87.986) Prec@5 100.000 (99.135) +2022-11-14 16:51:28,189 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0757) Prec@1 84.000 (87.933) Prec@5 98.000 (99.120) +2022-11-14 16:51:28,197 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0754) Prec@1 91.000 (87.974) Prec@5 100.000 (99.132) +2022-11-14 16:51:28,205 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0753) Prec@1 87.000 (87.961) Prec@5 99.000 (99.130) +2022-11-14 16:51:28,212 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0754) Prec@1 87.000 (87.949) Prec@5 98.000 (99.115) +2022-11-14 16:51:28,219 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0755) Prec@1 86.000 (87.924) Prec@5 99.000 (99.114) +2022-11-14 16:51:28,227 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0755) Prec@1 86.000 (87.900) Prec@5 100.000 (99.125) +2022-11-14 16:51:28,235 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0757) Prec@1 87.000 (87.889) Prec@5 100.000 (99.136) +2022-11-14 16:51:28,242 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0758) Prec@1 85.000 (87.854) Prec@5 100.000 (99.146) +2022-11-14 16:51:28,249 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0760) Prec@1 87.000 (87.843) Prec@5 100.000 (99.157) +2022-11-14 16:51:28,257 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0761) Prec@1 85.000 (87.810) Prec@5 100.000 (99.167) +2022-11-14 16:51:28,264 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.0765) Prec@1 84.000 (87.765) Prec@5 100.000 (99.176) +2022-11-14 16:51:28,272 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0765) Prec@1 89.000 (87.779) Prec@5 100.000 (99.186) +2022-11-14 16:51:28,279 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0764) Prec@1 90.000 (87.805) Prec@5 100.000 (99.195) +2022-11-14 16:51:28,287 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0765) Prec@1 85.000 (87.773) Prec@5 99.000 (99.193) +2022-11-14 16:51:28,294 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0763) Prec@1 91.000 (87.809) Prec@5 100.000 (99.202) +2022-11-14 16:51:28,302 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0763) Prec@1 90.000 (87.833) Prec@5 100.000 (99.211) +2022-11-14 16:51:28,309 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0479 (0.0760) Prec@1 92.000 (87.879) Prec@5 100.000 (99.220) +2022-11-14 16:51:28,317 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0757) Prec@1 92.000 (87.924) Prec@5 100.000 (99.228) +2022-11-14 16:51:28,324 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0759) Prec@1 86.000 (87.903) Prec@5 100.000 (99.237) +2022-11-14 16:51:28,332 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0898 (0.0760) Prec@1 86.000 (87.883) Prec@5 100.000 (99.245) +2022-11-14 16:51:28,339 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0762) Prec@1 85.000 (87.853) Prec@5 99.000 (99.242) +2022-11-14 16:51:28,346 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0691 (0.0761) Prec@1 87.000 (87.844) Prec@5 99.000 (99.240) +2022-11-14 16:51:28,354 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0610 (0.0760) Prec@1 92.000 (87.887) Prec@5 99.000 (99.237) +2022-11-14 16:51:28,361 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0823 (0.0760) Prec@1 88.000 (87.888) Prec@5 98.000 (99.224) +2022-11-14 16:51:28,369 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1067 (0.0763) Prec@1 86.000 (87.869) Prec@5 99.000 (99.222) +2022-11-14 16:51:28,376 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0763) Prec@1 88.000 (87.870) Prec@5 100.000 (99.230) +2022-11-14 16:51:28,429 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:51:28,746 Epoch: [400][0/500] Time 0.026 (0.026) Data 0.236 (0.236) Loss 0.0474 (0.0474) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:28,948 Epoch: [400][10/500] Time 0.020 (0.019) Data 0.002 (0.023) Loss 0.0378 (0.0426) Prec@1 93.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:29,163 Epoch: [400][20/500] Time 0.022 (0.019) Data 0.002 (0.013) Loss 0.0081 (0.0311) Prec@1 100.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:51:29,366 Epoch: [400][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0205 (0.0285) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:29,562 Epoch: [400][40/500] Time 0.017 (0.018) Data 0.002 (0.008) Loss 0.0648 (0.0357) Prec@1 90.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:29,759 Epoch: [400][50/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0381 (0.0361) Prec@1 95.000 (94.167) Prec@5 99.000 (99.833) +2022-11-14 16:51:29,955 Epoch: [400][60/500] Time 0.019 (0.018) Data 0.001 (0.006) Loss 0.0170 (0.0334) Prec@1 98.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:51:30,216 Epoch: [400][70/500] Time 0.025 (0.019) Data 0.002 (0.005) Loss 0.0339 (0.0335) Prec@1 96.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 16:51:30,489 Epoch: [400][80/500] Time 0.025 (0.019) Data 0.001 (0.005) Loss 0.0155 (0.0315) Prec@1 98.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 16:51:30,761 Epoch: [400][90/500] Time 0.025 (0.020) Data 0.002 (0.004) Loss 0.0303 (0.0313) Prec@1 97.000 (95.400) Prec@5 99.000 (99.800) +2022-11-14 16:51:31,030 Epoch: [400][100/500] Time 0.024 (0.020) Data 0.002 (0.004) Loss 0.0301 (0.0312) Prec@1 94.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 16:51:31,294 Epoch: [400][110/500] Time 0.024 (0.020) Data 0.002 (0.004) Loss 0.0406 (0.0320) Prec@1 94.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:51:31,555 Epoch: [400][120/500] Time 0.025 (0.021) Data 0.001 (0.004) Loss 0.0329 (0.0321) Prec@1 95.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 16:51:31,819 Epoch: [400][130/500] Time 0.024 (0.021) Data 0.001 (0.004) Loss 0.0194 (0.0312) Prec@1 97.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:51:32,085 Epoch: [400][140/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0245 (0.0307) Prec@1 96.000 (95.333) Prec@5 100.000 (99.867) +2022-11-14 16:51:32,347 Epoch: [400][150/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0096 (0.0294) Prec@1 99.000 (95.562) Prec@5 100.000 (99.875) +2022-11-14 16:51:32,610 Epoch: [400][160/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0326 (0.0296) Prec@1 95.000 (95.529) Prec@5 100.000 (99.882) +2022-11-14 16:51:32,875 Epoch: [400][170/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0348 (0.0299) Prec@1 94.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:51:33,142 Epoch: [400][180/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0169 (0.0292) Prec@1 97.000 (95.526) Prec@5 100.000 (99.895) +2022-11-14 16:51:33,403 Epoch: [400][190/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0296 (0.0292) Prec@1 95.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 16:51:33,663 Epoch: [400][200/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0257 (0.0291) Prec@1 94.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 16:51:33,928 Epoch: [400][210/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0245 (0.0288) Prec@1 95.000 (95.409) Prec@5 100.000 (99.909) +2022-11-14 16:51:34,195 Epoch: [400][220/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0243 (0.0286) Prec@1 94.000 (95.348) Prec@5 100.000 (99.913) +2022-11-14 16:51:34,457 Epoch: [400][230/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0527 (0.0297) Prec@1 91.000 (95.167) Prec@5 99.000 (99.875) +2022-11-14 16:51:34,721 Epoch: [400][240/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0281 (0.0296) Prec@1 94.000 (95.120) Prec@5 100.000 (99.880) +2022-11-14 16:51:34,982 Epoch: [400][250/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0313 (0.0297) Prec@1 95.000 (95.115) Prec@5 100.000 (99.885) +2022-11-14 16:51:35,248 Epoch: [400][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0272 (0.0296) Prec@1 96.000 (95.148) Prec@5 100.000 (99.889) +2022-11-14 16:51:35,513 Epoch: [400][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0126 (0.0290) Prec@1 97.000 (95.214) Prec@5 100.000 (99.893) +2022-11-14 16:51:35,777 Epoch: [400][280/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0144 (0.0285) Prec@1 99.000 (95.345) Prec@5 100.000 (99.897) +2022-11-14 16:51:36,041 Epoch: [400][290/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0365 (0.0287) Prec@1 96.000 (95.367) Prec@5 99.000 (99.867) +2022-11-14 16:51:36,307 Epoch: [400][300/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0342 (0.0289) Prec@1 93.000 (95.290) Prec@5 100.000 (99.871) +2022-11-14 16:51:36,570 Epoch: [400][310/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0307 (0.0290) Prec@1 94.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:51:36,836 Epoch: [400][320/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0320 (0.0291) Prec@1 96.000 (95.273) Prec@5 100.000 (99.879) +2022-11-14 16:51:37,110 Epoch: [400][330/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0359 (0.0293) Prec@1 94.000 (95.235) Prec@5 100.000 (99.882) +2022-11-14 16:51:37,370 Epoch: [400][340/500] Time 0.022 (0.022) Data 0.001 (0.002) Loss 0.0591 (0.0301) Prec@1 89.000 (95.057) Prec@5 99.000 (99.857) +2022-11-14 16:51:37,638 Epoch: [400][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0393 (0.0304) Prec@1 95.000 (95.056) Prec@5 100.000 (99.861) +2022-11-14 16:51:37,904 Epoch: [400][360/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0291 (0.0303) Prec@1 94.000 (95.027) Prec@5 100.000 (99.865) +2022-11-14 16:51:38,168 Epoch: [400][370/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0441 (0.0307) Prec@1 93.000 (94.974) Prec@5 100.000 (99.868) +2022-11-14 16:51:38,431 Epoch: [400][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0337 (0.0308) Prec@1 92.000 (94.897) Prec@5 100.000 (99.872) +2022-11-14 16:51:38,695 Epoch: [400][390/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0210 (0.0305) Prec@1 97.000 (94.950) Prec@5 99.000 (99.850) +2022-11-14 16:51:38,953 Epoch: [400][400/500] Time 0.023 (0.022) Data 0.001 (0.002) Loss 0.0339 (0.0306) Prec@1 93.000 (94.902) Prec@5 100.000 (99.854) +2022-11-14 16:51:39,220 Epoch: [400][410/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0366 (0.0308) Prec@1 94.000 (94.881) Prec@5 100.000 (99.857) +2022-11-14 16:51:39,485 Epoch: [400][420/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0300 (0.0307) Prec@1 95.000 (94.884) Prec@5 100.000 (99.860) +2022-11-14 16:51:39,746 Epoch: [400][430/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0358 (0.0308) Prec@1 94.000 (94.864) Prec@5 100.000 (99.864) +2022-11-14 16:51:40,011 Epoch: [400][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0215 (0.0306) Prec@1 97.000 (94.911) Prec@5 99.000 (99.844) +2022-11-14 16:51:40,274 Epoch: [400][450/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0393 (0.0308) Prec@1 95.000 (94.913) Prec@5 100.000 (99.848) +2022-11-14 16:51:40,539 Epoch: [400][460/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0094 (0.0304) Prec@1 99.000 (95.000) Prec@5 100.000 (99.851) +2022-11-14 16:51:40,801 Epoch: [400][470/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0423 (0.0306) Prec@1 92.000 (94.938) Prec@5 100.000 (99.854) +2022-11-14 16:51:41,068 Epoch: [400][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0260 (0.0305) Prec@1 96.000 (94.959) Prec@5 100.000 (99.857) +2022-11-14 16:51:41,334 Epoch: [400][490/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0541 (0.0310) Prec@1 90.000 (94.860) Prec@5 100.000 (99.860) +2022-11-14 16:51:41,577 Epoch: [400][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0329 (0.0310) Prec@1 94.000 (94.843) Prec@5 100.000 (99.863) +2022-11-14 16:51:41,868 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0552 (0.0552) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:51:41,876 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0647 (0.0600) Prec@1 90.000 (91.000) Prec@5 100.000 (99.500) +2022-11-14 16:51:41,885 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0560 (0.0587) Prec@1 92.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 16:51:41,897 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0769 (0.0632) Prec@1 86.000 (90.000) Prec@5 98.000 (99.250) +2022-11-14 16:51:41,904 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1059 (0.0717) Prec@1 84.000 (88.800) Prec@5 99.000 (99.200) +2022-11-14 16:51:41,911 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0420 (0.0668) Prec@1 92.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 16:51:41,919 Test: [6/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0685) Prec@1 89.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 16:51:41,930 Test: [7/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0875 (0.0709) Prec@1 84.000 (88.625) Prec@5 99.000 (99.375) +2022-11-14 16:51:41,937 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0727) Prec@1 88.000 (88.556) Prec@5 99.000 (99.333) +2022-11-14 16:51:41,944 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0961 (0.0751) Prec@1 86.000 (88.300) Prec@5 97.000 (99.100) +2022-11-14 16:51:41,954 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0749) Prec@1 88.000 (88.273) Prec@5 100.000 (99.182) +2022-11-14 16:51:41,963 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0749) Prec@1 89.000 (88.333) Prec@5 100.000 (99.250) +2022-11-14 16:51:41,971 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0358 (0.0719) Prec@1 93.000 (88.692) Prec@5 100.000 (99.308) +2022-11-14 16:51:41,979 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0728) Prec@1 87.000 (88.571) Prec@5 100.000 (99.357) +2022-11-14 16:51:41,990 Test: [14/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0725) Prec@1 88.000 (88.533) Prec@5 100.000 (99.400) +2022-11-14 16:51:42,000 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0729) Prec@1 88.000 (88.500) Prec@5 99.000 (99.375) +2022-11-14 16:51:42,008 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0716) Prec@1 91.000 (88.647) Prec@5 99.000 (99.353) +2022-11-14 16:51:42,016 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0728) Prec@1 86.000 (88.500) Prec@5 100.000 (99.389) +2022-11-14 16:51:42,025 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0731) Prec@1 86.000 (88.368) Prec@5 99.000 (99.368) +2022-11-14 16:51:42,033 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0738) Prec@1 89.000 (88.400) Prec@5 98.000 (99.300) +2022-11-14 16:51:42,041 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0744) Prec@1 86.000 (88.286) Prec@5 98.000 (99.238) +2022-11-14 16:51:42,049 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0745) Prec@1 90.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 16:51:42,057 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0755) Prec@1 87.000 (88.304) Prec@5 97.000 (99.174) +2022-11-14 16:51:42,065 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0752) Prec@1 90.000 (88.375) Prec@5 100.000 (99.208) +2022-11-14 16:51:42,074 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0755) Prec@1 87.000 (88.320) Prec@5 100.000 (99.240) +2022-11-14 16:51:42,083 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0758) Prec@1 88.000 (88.308) Prec@5 99.000 (99.231) +2022-11-14 16:51:42,091 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0423 (0.0746) Prec@1 92.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 16:51:42,099 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 88.000 (88.429) Prec@5 100.000 (99.250) +2022-11-14 16:51:42,107 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0737) Prec@1 92.000 (88.552) Prec@5 99.000 (99.241) +2022-11-14 16:51:42,115 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0740) Prec@1 85.000 (88.433) Prec@5 99.000 (99.233) +2022-11-14 16:51:42,122 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0740) Prec@1 86.000 (88.355) Prec@5 100.000 (99.258) +2022-11-14 16:51:42,130 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0735) Prec@1 93.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 16:51:42,138 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0736) Prec@1 87.000 (88.455) Prec@5 100.000 (99.273) +2022-11-14 16:51:42,146 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0741) Prec@1 84.000 (88.324) Prec@5 100.000 (99.294) +2022-11-14 16:51:42,153 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0742) Prec@1 88.000 (88.314) Prec@5 98.000 (99.257) +2022-11-14 16:51:42,161 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0740) Prec@1 90.000 (88.361) Prec@5 99.000 (99.250) +2022-11-14 16:51:42,169 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0740) Prec@1 89.000 (88.378) Prec@5 99.000 (99.243) +2022-11-14 16:51:42,176 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0744) Prec@1 86.000 (88.316) Prec@5 99.000 (99.237) +2022-11-14 16:51:42,184 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0741) Prec@1 89.000 (88.333) Prec@5 99.000 (99.231) +2022-11-14 16:51:42,191 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0739) Prec@1 89.000 (88.350) Prec@5 97.000 (99.175) +2022-11-14 16:51:42,199 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0747) Prec@1 83.000 (88.220) Prec@5 100.000 (99.195) +2022-11-14 16:51:42,207 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0747) Prec@1 89.000 (88.238) Prec@5 99.000 (99.190) +2022-11-14 16:51:42,214 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0747) Prec@1 89.000 (88.256) Prec@5 99.000 (99.186) +2022-11-14 16:51:42,222 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0746) Prec@1 88.000 (88.250) Prec@5 99.000 (99.182) +2022-11-14 16:51:42,229 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0744) Prec@1 90.000 (88.289) Prec@5 98.000 (99.156) +2022-11-14 16:51:42,237 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1177 (0.0753) Prec@1 80.000 (88.109) Prec@5 98.000 (99.130) +2022-11-14 16:51:42,244 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0750) Prec@1 90.000 (88.149) Prec@5 100.000 (99.149) +2022-11-14 16:51:42,251 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0754) Prec@1 85.000 (88.083) Prec@5 99.000 (99.146) +2022-11-14 16:51:42,259 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0748) Prec@1 94.000 (88.204) Prec@5 99.000 (99.143) +2022-11-14 16:51:42,266 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0754) Prec@1 86.000 (88.160) Prec@5 100.000 (99.160) +2022-11-14 16:51:42,274 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0749) Prec@1 91.000 (88.216) Prec@5 100.000 (99.176) +2022-11-14 16:51:42,282 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0751) Prec@1 85.000 (88.154) Prec@5 99.000 (99.173) +2022-11-14 16:51:42,289 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0752) Prec@1 88.000 (88.151) Prec@5 99.000 (99.170) +2022-11-14 16:51:42,297 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0752) Prec@1 88.000 (88.148) Prec@5 100.000 (99.185) +2022-11-14 16:51:42,305 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0756) Prec@1 84.000 (88.073) Prec@5 100.000 (99.200) +2022-11-14 16:51:42,312 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0752) Prec@1 93.000 (88.161) Prec@5 99.000 (99.196) +2022-11-14 16:51:42,320 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0753) Prec@1 86.000 (88.123) Prec@5 100.000 (99.211) +2022-11-14 16:51:42,328 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0753) Prec@1 90.000 (88.155) Prec@5 100.000 (99.224) +2022-11-14 16:51:42,336 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1091 (0.0759) Prec@1 83.000 (88.068) Prec@5 100.000 (99.237) +2022-11-14 16:51:42,344 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0761) Prec@1 86.000 (88.033) Prec@5 99.000 (99.233) +2022-11-14 16:51:42,351 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0760) Prec@1 88.000 (88.033) Prec@5 100.000 (99.246) +2022-11-14 16:51:42,359 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0758) Prec@1 90.000 (88.065) Prec@5 99.000 (99.242) +2022-11-14 16:51:42,367 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0757) Prec@1 91.000 (88.111) Prec@5 99.000 (99.238) +2022-11-14 16:51:42,374 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0366 (0.0751) Prec@1 94.000 (88.203) Prec@5 99.000 (99.234) +2022-11-14 16:51:42,382 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0753) Prec@1 87.000 (88.185) Prec@5 99.000 (99.231) +2022-11-14 16:51:42,390 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0753) Prec@1 88.000 (88.182) Prec@5 98.000 (99.212) +2022-11-14 16:51:42,397 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0749) Prec@1 92.000 (88.239) Prec@5 100.000 (99.224) +2022-11-14 16:51:42,405 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0747) Prec@1 91.000 (88.279) Prec@5 98.000 (99.206) +2022-11-14 16:51:42,413 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0744) Prec@1 87.000 (88.261) Prec@5 99.000 (99.203) +2022-11-14 16:51:42,420 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0744) Prec@1 87.000 (88.243) Prec@5 100.000 (99.214) +2022-11-14 16:51:42,428 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0744) Prec@1 89.000 (88.254) Prec@5 99.000 (99.211) +2022-11-14 16:51:42,436 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0742) Prec@1 91.000 (88.292) Prec@5 99.000 (99.208) +2022-11-14 16:51:42,443 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0391 (0.0737) Prec@1 95.000 (88.384) Prec@5 99.000 (99.205) +2022-11-14 16:51:42,451 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0452 (0.0733) Prec@1 93.000 (88.446) Prec@5 100.000 (99.216) +2022-11-14 16:51:42,459 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1082 (0.0738) Prec@1 81.000 (88.347) Prec@5 100.000 (99.227) +2022-11-14 16:51:42,466 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0735) Prec@1 92.000 (88.395) Prec@5 100.000 (99.237) +2022-11-14 16:51:42,474 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0736) Prec@1 86.000 (88.364) Prec@5 99.000 (99.234) +2022-11-14 16:51:42,481 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0738) Prec@1 86.000 (88.333) Prec@5 99.000 (99.231) +2022-11-14 16:51:42,489 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0739) Prec@1 88.000 (88.329) Prec@5 100.000 (99.241) +2022-11-14 16:51:42,496 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0739) Prec@1 90.000 (88.350) Prec@5 100.000 (99.250) +2022-11-14 16:51:42,504 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0742) Prec@1 87.000 (88.333) Prec@5 97.000 (99.222) +2022-11-14 16:51:42,512 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0742) Prec@1 88.000 (88.329) Prec@5 99.000 (99.220) +2022-11-14 16:51:42,519 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0745) Prec@1 85.000 (88.289) Prec@5 98.000 (99.205) +2022-11-14 16:51:42,527 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0743) Prec@1 90.000 (88.310) Prec@5 100.000 (99.214) +2022-11-14 16:51:42,535 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0745) Prec@1 85.000 (88.271) Prec@5 100.000 (99.224) +2022-11-14 16:51:42,542 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0748) Prec@1 85.000 (88.233) Prec@5 100.000 (99.233) +2022-11-14 16:51:42,551 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0746) Prec@1 91.000 (88.264) Prec@5 99.000 (99.230) +2022-11-14 16:51:42,558 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0747) Prec@1 85.000 (88.227) Prec@5 98.000 (99.216) +2022-11-14 16:51:42,566 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0745) Prec@1 90.000 (88.247) Prec@5 99.000 (99.213) +2022-11-14 16:51:42,573 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0745) Prec@1 87.000 (88.233) Prec@5 99.000 (99.211) +2022-11-14 16:51:42,581 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0744) Prec@1 92.000 (88.275) Prec@5 100.000 (99.220) +2022-11-14 16:51:42,588 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0742) Prec@1 90.000 (88.293) Prec@5 100.000 (99.228) +2022-11-14 16:51:42,596 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0742) Prec@1 90.000 (88.312) Prec@5 100.000 (99.237) +2022-11-14 16:51:42,603 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0740) Prec@1 89.000 (88.319) Prec@5 99.000 (99.234) +2022-11-14 16:51:42,611 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0741) Prec@1 87.000 (88.305) Prec@5 99.000 (99.232) +2022-11-14 16:51:42,618 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0740) Prec@1 89.000 (88.312) Prec@5 99.000 (99.229) +2022-11-14 16:51:42,625 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0738) Prec@1 92.000 (88.351) Prec@5 98.000 (99.216) +2022-11-14 16:51:42,633 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0739) Prec@1 86.000 (88.327) Prec@5 99.000 (99.214) +2022-11-14 16:51:42,640 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0740) Prec@1 87.000 (88.313) Prec@5 100.000 (99.222) +2022-11-14 16:51:42,647 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0739) Prec@1 90.000 (88.330) Prec@5 100.000 (99.230) +2022-11-14 16:51:42,701 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:51:43,020 Epoch: [401][0/500] Time 0.033 (0.033) Data 0.233 (0.233) Loss 0.0411 (0.0411) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:43,227 Epoch: [401][10/500] Time 0.018 (0.020) Data 0.002 (0.023) Loss 0.0362 (0.0387) Prec@1 94.000 (94.000) Prec@5 99.000 (99.500) +2022-11-14 16:51:43,420 Epoch: [401][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0229 (0.0334) Prec@1 96.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:51:43,610 Epoch: [401][30/500] Time 0.015 (0.018) Data 0.001 (0.009) Loss 0.0179 (0.0295) Prec@1 98.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:51:43,796 Epoch: [401][40/500] Time 0.017 (0.018) Data 0.001 (0.007) Loss 0.0251 (0.0286) Prec@1 97.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 16:51:43,986 Epoch: [401][50/500] Time 0.015 (0.017) Data 0.001 (0.006) Loss 0.0453 (0.0314) Prec@1 93.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 16:51:44,218 Epoch: [401][60/500] Time 0.026 (0.018) Data 0.002 (0.005) Loss 0.0229 (0.0302) Prec@1 96.000 (95.429) Prec@5 100.000 (99.857) +2022-11-14 16:51:44,513 Epoch: [401][70/500] Time 0.027 (0.019) Data 0.002 (0.005) Loss 0.0300 (0.0302) Prec@1 93.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:51:44,819 Epoch: [401][80/500] Time 0.030 (0.020) Data 0.001 (0.004) Loss 0.0359 (0.0308) Prec@1 95.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:51:45,126 Epoch: [401][90/500] Time 0.034 (0.021) Data 0.001 (0.004) Loss 0.0280 (0.0305) Prec@1 95.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 16:51:45,431 Epoch: [401][100/500] Time 0.029 (0.021) Data 0.001 (0.004) Loss 0.0520 (0.0325) Prec@1 93.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 16:51:45,736 Epoch: [401][110/500] Time 0.029 (0.022) Data 0.002 (0.004) Loss 0.0273 (0.0320) Prec@1 95.000 (94.917) Prec@5 100.000 (99.917) +2022-11-14 16:51:46,048 Epoch: [401][120/500] Time 0.030 (0.022) Data 0.001 (0.004) Loss 0.0310 (0.0320) Prec@1 94.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 16:51:46,348 Epoch: [401][130/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0302 (0.0318) Prec@1 95.000 (94.857) Prec@5 100.000 (99.929) +2022-11-14 16:51:46,643 Epoch: [401][140/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0165 (0.0308) Prec@1 97.000 (95.000) Prec@5 100.000 (99.933) +2022-11-14 16:51:46,937 Epoch: [401][150/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0138 (0.0298) Prec@1 98.000 (95.188) Prec@5 100.000 (99.938) +2022-11-14 16:51:47,236 Epoch: [401][160/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0464 (0.0307) Prec@1 93.000 (95.059) Prec@5 100.000 (99.941) +2022-11-14 16:51:47,533 Epoch: [401][170/500] Time 0.028 (0.023) Data 0.001 (0.003) Loss 0.0403 (0.0313) Prec@1 91.000 (94.833) Prec@5 100.000 (99.944) +2022-11-14 16:51:47,840 Epoch: [401][180/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0395 (0.0317) Prec@1 93.000 (94.737) Prec@5 99.000 (99.895) +2022-11-14 16:51:48,144 Epoch: [401][190/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0155 (0.0309) Prec@1 97.000 (94.850) Prec@5 100.000 (99.900) +2022-11-14 16:51:48,450 Epoch: [401][200/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0584 (0.0322) Prec@1 91.000 (94.667) Prec@5 100.000 (99.905) +2022-11-14 16:51:48,759 Epoch: [401][210/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0457 (0.0328) Prec@1 93.000 (94.591) Prec@5 99.000 (99.864) +2022-11-14 16:51:49,061 Epoch: [401][220/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0309 (0.0327) Prec@1 94.000 (94.565) Prec@5 100.000 (99.870) +2022-11-14 16:51:49,361 Epoch: [401][230/500] Time 0.026 (0.024) Data 0.002 (0.003) Loss 0.0501 (0.0334) Prec@1 93.000 (94.500) Prec@5 99.000 (99.833) +2022-11-14 16:51:49,658 Epoch: [401][240/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0159 (0.0327) Prec@1 97.000 (94.600) Prec@5 100.000 (99.840) +2022-11-14 16:51:49,956 Epoch: [401][250/500] Time 0.027 (0.024) Data 0.002 (0.003) Loss 0.0234 (0.0324) Prec@1 98.000 (94.731) Prec@5 100.000 (99.846) +2022-11-14 16:51:50,263 Epoch: [401][260/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0186 (0.0319) Prec@1 98.000 (94.852) Prec@5 100.000 (99.852) +2022-11-14 16:51:50,568 Epoch: [401][270/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.0276 (0.0317) Prec@1 95.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:51:50,869 Epoch: [401][280/500] Time 0.030 (0.025) Data 0.001 (0.003) Loss 0.0411 (0.0320) Prec@1 93.000 (94.793) Prec@5 100.000 (99.862) +2022-11-14 16:51:51,176 Epoch: [401][290/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0242 (0.0318) Prec@1 97.000 (94.867) Prec@5 100.000 (99.867) +2022-11-14 16:51:51,475 Epoch: [401][300/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0236 (0.0315) Prec@1 95.000 (94.871) Prec@5 99.000 (99.839) +2022-11-14 16:51:51,777 Epoch: [401][310/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0240 (0.0313) Prec@1 95.000 (94.875) Prec@5 100.000 (99.844) +2022-11-14 16:51:52,077 Epoch: [401][320/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0169 (0.0309) Prec@1 98.000 (94.970) Prec@5 100.000 (99.848) +2022-11-14 16:51:52,371 Epoch: [401][330/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0119 (0.0303) Prec@1 99.000 (95.088) Prec@5 100.000 (99.853) +2022-11-14 16:51:52,668 Epoch: [401][340/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0209 (0.0300) Prec@1 97.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:51:52,966 Epoch: [401][350/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0140 (0.0296) Prec@1 98.000 (95.222) Prec@5 100.000 (99.861) +2022-11-14 16:51:53,263 Epoch: [401][360/500] Time 0.028 (0.025) Data 0.001 (0.002) Loss 0.0126 (0.0291) Prec@1 99.000 (95.324) Prec@5 100.000 (99.865) +2022-11-14 16:51:53,564 Epoch: [401][370/500] Time 0.029 (0.025) Data 0.002 (0.002) Loss 0.0283 (0.0291) Prec@1 96.000 (95.342) Prec@5 99.000 (99.842) +2022-11-14 16:51:53,866 Epoch: [401][380/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0204 (0.0289) Prec@1 96.000 (95.359) Prec@5 100.000 (99.846) +2022-11-14 16:51:54,163 Epoch: [401][390/500] Time 0.030 (0.025) Data 0.002 (0.002) Loss 0.0257 (0.0288) Prec@1 95.000 (95.350) Prec@5 100.000 (99.850) +2022-11-14 16:51:54,452 Epoch: [401][400/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0238 (0.0287) Prec@1 96.000 (95.366) Prec@5 100.000 (99.854) +2022-11-14 16:51:54,743 Epoch: [401][410/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0123 (0.0283) Prec@1 98.000 (95.429) Prec@5 100.000 (99.857) +2022-11-14 16:51:55,040 Epoch: [401][420/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0328 (0.0284) Prec@1 94.000 (95.395) Prec@5 100.000 (99.860) +2022-11-14 16:51:55,334 Epoch: [401][430/500] Time 0.032 (0.025) Data 0.001 (0.002) Loss 0.0227 (0.0283) Prec@1 97.000 (95.432) Prec@5 100.000 (99.864) +2022-11-14 16:51:55,629 Epoch: [401][440/500] Time 0.026 (0.025) Data 0.002 (0.002) Loss 0.0271 (0.0282) Prec@1 95.000 (95.422) Prec@5 100.000 (99.867) +2022-11-14 16:51:55,929 Epoch: [401][450/500] Time 0.032 (0.025) Data 0.001 (0.002) Loss 0.0319 (0.0283) Prec@1 95.000 (95.413) Prec@5 100.000 (99.870) +2022-11-14 16:51:56,225 Epoch: [401][460/500] Time 0.027 (0.025) Data 0.001 (0.002) Loss 0.0467 (0.0287) Prec@1 90.000 (95.298) Prec@5 100.000 (99.872) +2022-11-14 16:51:56,520 Epoch: [401][470/500] Time 0.027 (0.025) Data 0.002 (0.002) Loss 0.0275 (0.0287) Prec@1 96.000 (95.312) Prec@5 100.000 (99.875) +2022-11-14 16:51:56,810 Epoch: [401][480/500] Time 0.028 (0.025) Data 0.001 (0.002) Loss 0.0157 (0.0284) Prec@1 99.000 (95.388) Prec@5 100.000 (99.878) +2022-11-14 16:51:57,105 Epoch: [401][490/500] Time 0.028 (0.025) Data 0.001 (0.002) Loss 0.0340 (0.0285) Prec@1 94.000 (95.360) Prec@5 100.000 (99.880) +2022-11-14 16:51:57,371 Epoch: [401][499/500] Time 0.028 (0.025) Data 0.001 (0.002) Loss 0.0269 (0.0285) Prec@1 95.000 (95.353) Prec@5 100.000 (99.882) +2022-11-14 16:51:57,669 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0508 (0.0508) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:57,677 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0744 (0.0626) Prec@1 89.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:57,685 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0705) Prec@1 86.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:51:57,695 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0704) Prec@1 90.000 (89.250) Prec@5 99.000 (99.500) +2022-11-14 16:51:57,702 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0725) Prec@1 88.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:51:57,709 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0695) Prec@1 91.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:51:57,716 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0693) Prec@1 88.000 (89.143) Prec@5 99.000 (99.571) +2022-11-14 16:51:57,724 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0703) Prec@1 88.000 (89.000) Prec@5 100.000 (99.625) +2022-11-14 16:51:57,731 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0722) Prec@1 87.000 (88.778) Prec@5 98.000 (99.444) +2022-11-14 16:51:57,738 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0736) Prec@1 87.000 (88.600) Prec@5 98.000 (99.300) +2022-11-14 16:51:57,745 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0709) Prec@1 94.000 (89.091) Prec@5 100.000 (99.364) +2022-11-14 16:51:57,753 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0726) Prec@1 86.000 (88.833) Prec@5 100.000 (99.417) +2022-11-14 16:51:57,761 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0444 (0.0705) Prec@1 93.000 (89.154) Prec@5 100.000 (99.462) +2022-11-14 16:51:57,768 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0714) Prec@1 86.000 (88.929) Prec@5 99.000 (99.429) +2022-11-14 16:51:57,776 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0720) Prec@1 87.000 (88.800) Prec@5 100.000 (99.467) +2022-11-14 16:51:57,784 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0723) Prec@1 88.000 (88.750) Prec@5 99.000 (99.438) +2022-11-14 16:51:57,791 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0712) Prec@1 93.000 (89.000) Prec@5 99.000 (99.412) +2022-11-14 16:51:57,799 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0719) Prec@1 88.000 (88.944) Prec@5 99.000 (99.389) +2022-11-14 16:51:57,806 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0732) Prec@1 83.000 (88.632) Prec@5 99.000 (99.368) +2022-11-14 16:51:57,814 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0745) Prec@1 85.000 (88.450) Prec@5 99.000 (99.350) +2022-11-14 16:51:57,821 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0748) Prec@1 86.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 16:51:57,829 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0751) Prec@1 88.000 (88.318) Prec@5 99.000 (99.318) +2022-11-14 16:51:57,837 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0763) Prec@1 84.000 (88.130) Prec@5 100.000 (99.348) +2022-11-14 16:51:57,844 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0762) Prec@1 87.000 (88.083) Prec@5 100.000 (99.375) +2022-11-14 16:51:57,852 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0764) Prec@1 87.000 (88.040) Prec@5 100.000 (99.400) +2022-11-14 16:51:57,859 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0772) Prec@1 86.000 (87.962) Prec@5 99.000 (99.385) +2022-11-14 16:51:57,867 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0768) Prec@1 88.000 (87.963) Prec@5 100.000 (99.407) +2022-11-14 16:51:57,874 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0762) Prec@1 90.000 (88.036) Prec@5 100.000 (99.429) +2022-11-14 16:51:57,882 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0756) Prec@1 91.000 (88.138) Prec@5 99.000 (99.414) +2022-11-14 16:51:57,890 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0754) Prec@1 88.000 (88.133) Prec@5 98.000 (99.367) +2022-11-14 16:51:57,897 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0750) Prec@1 90.000 (88.194) Prec@5 100.000 (99.387) +2022-11-14 16:51:57,909 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0750) Prec@1 88.000 (88.188) Prec@5 100.000 (99.406) +2022-11-14 16:51:57,916 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0751) Prec@1 88.000 (88.182) Prec@5 99.000 (99.394) +2022-11-14 16:51:57,924 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0755) Prec@1 86.000 (88.118) Prec@5 99.000 (99.382) +2022-11-14 16:51:57,931 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0755) Prec@1 85.000 (88.029) Prec@5 99.000 (99.371) +2022-11-14 16:51:57,939 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0761) Prec@1 85.000 (87.944) Prec@5 99.000 (99.361) +2022-11-14 16:51:57,946 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0756) Prec@1 89.000 (87.973) Prec@5 99.000 (99.351) +2022-11-14 16:51:57,954 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0763) Prec@1 84.000 (87.868) Prec@5 99.000 (99.342) +2022-11-14 16:51:57,961 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0758) Prec@1 91.000 (87.949) Prec@5 99.000 (99.333) +2022-11-14 16:51:57,969 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0761) Prec@1 87.000 (87.925) Prec@5 98.000 (99.300) +2022-11-14 16:51:57,977 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0766) Prec@1 84.000 (87.829) Prec@5 98.000 (99.268) +2022-11-14 16:51:57,984 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0764) Prec@1 89.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 16:51:57,992 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0759) Prec@1 89.000 (87.884) Prec@5 99.000 (99.279) +2022-11-14 16:51:57,999 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0756) Prec@1 91.000 (87.955) Prec@5 99.000 (99.273) +2022-11-14 16:51:58,007 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0754) Prec@1 88.000 (87.956) Prec@5 98.000 (99.244) +2022-11-14 16:51:58,015 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1237 (0.0764) Prec@1 80.000 (87.783) Prec@5 99.000 (99.239) +2022-11-14 16:51:58,022 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0763) Prec@1 89.000 (87.809) Prec@5 99.000 (99.234) +2022-11-14 16:51:58,030 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1249 (0.0773) Prec@1 80.000 (87.646) Prec@5 98.000 (99.208) +2022-11-14 16:51:58,037 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0769) Prec@1 91.000 (87.714) Prec@5 100.000 (99.224) +2022-11-14 16:51:58,045 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0773) Prec@1 86.000 (87.680) Prec@5 100.000 (99.240) +2022-11-14 16:51:58,053 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0770) Prec@1 89.000 (87.706) Prec@5 100.000 (99.255) +2022-11-14 16:51:58,060 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0770) Prec@1 89.000 (87.731) Prec@5 100.000 (99.269) +2022-11-14 16:51:58,069 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0767) Prec@1 88.000 (87.736) Prec@5 100.000 (99.283) +2022-11-14 16:51:58,077 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0767) Prec@1 89.000 (87.759) Prec@5 99.000 (99.278) +2022-11-14 16:51:58,085 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0766) Prec@1 88.000 (87.764) Prec@5 100.000 (99.291) +2022-11-14 16:51:58,092 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0764) Prec@1 90.000 (87.804) Prec@5 99.000 (99.286) +2022-11-14 16:51:58,100 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0765) Prec@1 86.000 (87.772) Prec@5 100.000 (99.298) +2022-11-14 16:51:58,107 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0763) Prec@1 88.000 (87.776) Prec@5 100.000 (99.310) +2022-11-14 16:51:58,115 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0764) Prec@1 85.000 (87.729) Prec@5 100.000 (99.322) +2022-11-14 16:51:58,122 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0763) Prec@1 89.000 (87.750) Prec@5 99.000 (99.317) +2022-11-14 16:51:58,130 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0763) Prec@1 88.000 (87.754) Prec@5 100.000 (99.328) +2022-11-14 16:51:58,138 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0763) Prec@1 87.000 (87.742) Prec@5 100.000 (99.339) +2022-11-14 16:51:58,145 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0762) Prec@1 90.000 (87.778) Prec@5 100.000 (99.349) +2022-11-14 16:51:58,153 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0401 (0.0756) Prec@1 93.000 (87.859) Prec@5 100.000 (99.359) +2022-11-14 16:51:58,160 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0757) Prec@1 86.000 (87.831) Prec@5 100.000 (99.369) +2022-11-14 16:51:58,168 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0759) Prec@1 86.000 (87.803) Prec@5 100.000 (99.379) +2022-11-14 16:51:58,176 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0455 (0.0755) Prec@1 91.000 (87.851) Prec@5 100.000 (99.388) +2022-11-14 16:51:58,183 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0756) Prec@1 87.000 (87.838) Prec@5 100.000 (99.397) +2022-11-14 16:51:58,190 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0753) Prec@1 90.000 (87.870) Prec@5 99.000 (99.391) +2022-11-14 16:51:58,198 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0752) Prec@1 92.000 (87.929) Prec@5 99.000 (99.386) +2022-11-14 16:51:58,206 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0757) Prec@1 84.000 (87.873) Prec@5 99.000 (99.380) +2022-11-14 16:51:58,213 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0754) Prec@1 92.000 (87.931) Prec@5 100.000 (99.389) +2022-11-14 16:51:58,221 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0331 (0.0748) Prec@1 95.000 (88.027) Prec@5 100.000 (99.397) +2022-11-14 16:51:58,228 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0743) Prec@1 94.000 (88.108) Prec@5 100.000 (99.405) +2022-11-14 16:51:58,236 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0746) Prec@1 87.000 (88.093) Prec@5 100.000 (99.413) +2022-11-14 16:51:58,243 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0743) Prec@1 89.000 (88.105) Prec@5 98.000 (99.395) +2022-11-14 16:51:58,251 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0741) Prec@1 90.000 (88.130) Prec@5 98.000 (99.377) +2022-11-14 16:51:58,259 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0743) Prec@1 84.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 16:51:58,266 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0742) Prec@1 89.000 (88.089) Prec@5 100.000 (99.392) +2022-11-14 16:51:58,274 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0739) Prec@1 93.000 (88.150) Prec@5 99.000 (99.388) +2022-11-14 16:51:58,282 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0741) Prec@1 86.000 (88.123) Prec@5 98.000 (99.370) +2022-11-14 16:51:58,289 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0741) Prec@1 88.000 (88.122) Prec@5 100.000 (99.378) +2022-11-14 16:51:58,296 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0742) Prec@1 85.000 (88.084) Prec@5 100.000 (99.386) +2022-11-14 16:51:58,304 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0428 (0.0738) Prec@1 89.000 (88.095) Prec@5 100.000 (99.393) +2022-11-14 16:51:58,311 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0738) Prec@1 89.000 (88.106) Prec@5 100.000 (99.400) +2022-11-14 16:51:58,319 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0896 (0.0740) Prec@1 88.000 (88.105) Prec@5 99.000 (99.395) +2022-11-14 16:51:58,327 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0739) Prec@1 88.000 (88.103) Prec@5 100.000 (99.402) +2022-11-14 16:51:58,334 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0739) Prec@1 90.000 (88.125) Prec@5 99.000 (99.398) +2022-11-14 16:51:58,342 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0646 (0.0738) Prec@1 89.000 (88.135) Prec@5 99.000 (99.393) +2022-11-14 16:51:58,349 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0738) Prec@1 88.000 (88.133) Prec@5 99.000 (99.389) +2022-11-14 16:51:58,357 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0801 (0.0739) Prec@1 86.000 (88.110) Prec@5 100.000 (99.396) +2022-11-14 16:51:58,364 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0565 (0.0737) Prec@1 91.000 (88.141) Prec@5 100.000 (99.402) +2022-11-14 16:51:58,372 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0738) Prec@1 85.000 (88.108) Prec@5 99.000 (99.398) +2022-11-14 16:51:58,379 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0737) Prec@1 92.000 (88.149) Prec@5 100.000 (99.404) +2022-11-14 16:51:58,387 Test: [94/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0766 (0.0737) Prec@1 89.000 (88.158) Prec@5 100.000 (99.411) +2022-11-14 16:51:58,394 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0628 (0.0736) Prec@1 89.000 (88.167) Prec@5 99.000 (99.406) +2022-11-14 16:51:58,402 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0478 (0.0733) Prec@1 93.000 (88.216) Prec@5 99.000 (99.402) +2022-11-14 16:51:58,409 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0967 (0.0735) Prec@1 84.000 (88.173) Prec@5 100.000 (99.408) +2022-11-14 16:51:58,416 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0976 (0.0738) Prec@1 84.000 (88.131) Prec@5 99.000 (99.404) +2022-11-14 16:51:58,424 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0653 (0.0737) Prec@1 90.000 (88.150) Prec@5 100.000 (99.410) +2022-11-14 16:51:58,491 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:51:58,820 Epoch: [402][0/500] Time 0.023 (0.023) Data 0.249 (0.249) Loss 0.0231 (0.0231) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,019 Epoch: [402][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0089 (0.0160) Prec@1 99.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,211 Epoch: [402][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0235 (0.0185) Prec@1 97.000 (97.333) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,403 Epoch: [402][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0298 (0.0213) Prec@1 95.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,592 Epoch: [402][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0397 (0.0250) Prec@1 93.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,779 Epoch: [402][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0345 (0.0266) Prec@1 94.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:51:59,967 Epoch: [402][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0187 (0.0255) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:00,159 Epoch: [402][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0384 (0.0271) Prec@1 93.000 (95.625) Prec@5 100.000 (100.000) +2022-11-14 16:52:00,346 Epoch: [402][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0267 (0.0270) Prec@1 95.000 (95.556) Prec@5 100.000 (100.000) +2022-11-14 16:52:00,536 Epoch: [402][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0431 (0.0286) Prec@1 93.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 16:52:00,728 Epoch: [402][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0359 (0.0293) Prec@1 94.000 (95.182) Prec@5 100.000 (100.000) +2022-11-14 16:52:00,917 Epoch: [402][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0321 (0.0295) Prec@1 95.000 (95.167) Prec@5 99.000 (99.917) +2022-11-14 16:52:01,115 Epoch: [402][120/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0242 (0.0291) Prec@1 96.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 16:52:01,363 Epoch: [402][130/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0423 (0.0301) Prec@1 92.000 (95.000) Prec@5 100.000 (99.929) +2022-11-14 16:52:01,617 Epoch: [402][140/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0259 (0.0298) Prec@1 96.000 (95.067) Prec@5 100.000 (99.933) +2022-11-14 16:52:01,876 Epoch: [402][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0412 (0.0305) Prec@1 93.000 (94.938) Prec@5 100.000 (99.938) +2022-11-14 16:52:02,131 Epoch: [402][160/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0413 (0.0311) Prec@1 93.000 (94.824) Prec@5 100.000 (99.941) +2022-11-14 16:52:02,384 Epoch: [402][170/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0270 (0.0309) Prec@1 96.000 (94.889) Prec@5 100.000 (99.944) +2022-11-14 16:52:02,640 Epoch: [402][180/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0093 (0.0298) Prec@1 99.000 (95.105) Prec@5 100.000 (99.947) +2022-11-14 16:52:02,893 Epoch: [402][190/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0445 (0.0305) Prec@1 91.000 (94.900) Prec@5 100.000 (99.950) +2022-11-14 16:52:03,147 Epoch: [402][200/500] Time 0.022 (0.019) Data 0.002 (0.003) Loss 0.0200 (0.0300) Prec@1 96.000 (94.952) Prec@5 100.000 (99.952) +2022-11-14 16:52:03,398 Epoch: [402][210/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0408 (0.0305) Prec@1 94.000 (94.909) Prec@5 99.000 (99.909) +2022-11-14 16:52:03,652 Epoch: [402][220/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0345 (0.0307) Prec@1 93.000 (94.826) Prec@5 100.000 (99.913) +2022-11-14 16:52:03,909 Epoch: [402][230/500] Time 0.022 (0.019) Data 0.002 (0.003) Loss 0.0118 (0.0299) Prec@1 98.000 (94.958) Prec@5 100.000 (99.917) +2022-11-14 16:52:04,164 Epoch: [402][240/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0320 (0.0300) Prec@1 94.000 (94.920) Prec@5 100.000 (99.920) +2022-11-14 16:52:04,422 Epoch: [402][250/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0180 (0.0295) Prec@1 97.000 (95.000) Prec@5 100.000 (99.923) +2022-11-14 16:52:04,675 Epoch: [402][260/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0115 (0.0288) Prec@1 98.000 (95.111) Prec@5 100.000 (99.926) +2022-11-14 16:52:04,925 Epoch: [402][270/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0275 (0.0288) Prec@1 94.000 (95.071) Prec@5 100.000 (99.929) +2022-11-14 16:52:05,181 Epoch: [402][280/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0227 (0.0286) Prec@1 96.000 (95.103) Prec@5 100.000 (99.931) +2022-11-14 16:52:05,436 Epoch: [402][290/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0294 (0.0286) Prec@1 95.000 (95.100) Prec@5 100.000 (99.933) +2022-11-14 16:52:05,692 Epoch: [402][300/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0099 (0.0280) Prec@1 99.000 (95.226) Prec@5 100.000 (99.935) +2022-11-14 16:52:05,946 Epoch: [402][310/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0274 (0.0280) Prec@1 97.000 (95.281) Prec@5 100.000 (99.938) +2022-11-14 16:52:06,204 Epoch: [402][320/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.0503 (0.0287) Prec@1 92.000 (95.182) Prec@5 98.000 (99.879) +2022-11-14 16:52:06,456 Epoch: [402][330/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0311 (0.0287) Prec@1 93.000 (95.118) Prec@5 100.000 (99.882) +2022-11-14 16:52:06,710 Epoch: [402][340/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0245 (0.0286) Prec@1 96.000 (95.143) Prec@5 100.000 (99.886) +2022-11-14 16:52:06,961 Epoch: [402][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0326 (0.0287) Prec@1 97.000 (95.194) Prec@5 100.000 (99.889) +2022-11-14 16:52:07,214 Epoch: [402][360/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0153 (0.0284) Prec@1 98.000 (95.270) Prec@5 100.000 (99.892) +2022-11-14 16:52:07,469 Epoch: [402][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0428 (0.0287) Prec@1 92.000 (95.184) Prec@5 100.000 (99.895) +2022-11-14 16:52:07,721 Epoch: [402][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0345 (0.0289) Prec@1 94.000 (95.154) Prec@5 100.000 (99.897) +2022-11-14 16:52:07,978 Epoch: [402][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0171 (0.0286) Prec@1 98.000 (95.225) Prec@5 100.000 (99.900) +2022-11-14 16:52:08,234 Epoch: [402][400/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0196 (0.0284) Prec@1 96.000 (95.244) Prec@5 100.000 (99.902) +2022-11-14 16:52:08,492 Epoch: [402][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0378 (0.0286) Prec@1 94.000 (95.214) Prec@5 100.000 (99.905) +2022-11-14 16:52:08,751 Epoch: [402][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0255 (0.0285) Prec@1 96.000 (95.233) Prec@5 100.000 (99.907) +2022-11-14 16:52:09,012 Epoch: [402][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0387 (0.0288) Prec@1 92.000 (95.159) Prec@5 100.000 (99.909) +2022-11-14 16:52:09,272 Epoch: [402][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0313 (0.0288) Prec@1 95.000 (95.156) Prec@5 100.000 (99.911) +2022-11-14 16:52:09,529 Epoch: [402][450/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0305 (0.0289) Prec@1 96.000 (95.174) Prec@5 100.000 (99.913) +2022-11-14 16:52:09,790 Epoch: [402][460/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0242 (0.0288) Prec@1 97.000 (95.213) Prec@5 100.000 (99.915) +2022-11-14 16:52:10,049 Epoch: [402][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0414 (0.0290) Prec@1 94.000 (95.188) Prec@5 100.000 (99.917) +2022-11-14 16:52:10,305 Epoch: [402][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0354 (0.0291) Prec@1 95.000 (95.184) Prec@5 99.000 (99.898) +2022-11-14 16:52:10,563 Epoch: [402][490/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0174 (0.0289) Prec@1 98.000 (95.240) Prec@5 100.000 (99.900) +2022-11-14 16:52:10,794 Epoch: [402][499/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0387 (0.0291) Prec@1 94.000 (95.216) Prec@5 99.000 (99.882) +2022-11-14 16:52:11,090 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0772 (0.0772) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:11,098 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0608 (0.0690) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:11,105 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0700) Prec@1 89.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 16:52:11,115 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0715) Prec@1 88.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 16:52:11,122 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0724) Prec@1 88.000 (89.000) Prec@5 100.000 (99.800) +2022-11-14 16:52:11,129 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0459 (0.0680) Prec@1 94.000 (89.833) Prec@5 100.000 (99.833) +2022-11-14 16:52:11,136 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0664) Prec@1 91.000 (90.000) Prec@5 100.000 (99.857) +2022-11-14 16:52:11,144 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0688) Prec@1 86.000 (89.500) Prec@5 98.000 (99.625) +2022-11-14 16:52:11,151 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0696) Prec@1 89.000 (89.444) Prec@5 99.000 (99.556) +2022-11-14 16:52:11,158 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0704) Prec@1 88.000 (89.300) Prec@5 99.000 (99.500) +2022-11-14 16:52:11,166 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0688) Prec@1 92.000 (89.545) Prec@5 100.000 (99.545) +2022-11-14 16:52:11,173 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0691) Prec@1 91.000 (89.667) Prec@5 99.000 (99.500) +2022-11-14 16:52:11,181 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0677) Prec@1 93.000 (89.923) Prec@5 100.000 (99.538) +2022-11-14 16:52:11,189 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0687) Prec@1 86.000 (89.643) Prec@5 99.000 (99.500) +2022-11-14 16:52:11,197 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0688) Prec@1 89.000 (89.600) Prec@5 98.000 (99.400) +2022-11-14 16:52:11,204 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0675) Prec@1 93.000 (89.812) Prec@5 100.000 (99.438) +2022-11-14 16:52:11,212 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0665) Prec@1 92.000 (89.941) Prec@5 99.000 (99.412) +2022-11-14 16:52:11,219 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0686) Prec@1 83.000 (89.556) Prec@5 100.000 (99.444) +2022-11-14 16:52:11,228 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0691) Prec@1 85.000 (89.316) Prec@5 99.000 (99.421) +2022-11-14 16:52:11,235 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0696) Prec@1 89.000 (89.300) Prec@5 97.000 (99.300) +2022-11-14 16:52:11,243 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0699) Prec@1 88.000 (89.238) Prec@5 100.000 (99.333) +2022-11-14 16:52:11,250 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0776 (0.0702) Prec@1 89.000 (89.227) Prec@5 100.000 (99.364) +2022-11-14 16:52:11,258 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0873 (0.0710) Prec@1 89.000 (89.217) Prec@5 99.000 (99.348) +2022-11-14 16:52:11,265 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0710) Prec@1 89.000 (89.208) Prec@5 100.000 (99.375) +2022-11-14 16:52:11,273 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0712) Prec@1 86.000 (89.080) Prec@5 100.000 (99.400) +2022-11-14 16:52:11,280 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1142 (0.0729) Prec@1 82.000 (88.808) Prec@5 97.000 (99.308) +2022-11-14 16:52:11,288 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0634 (0.0725) Prec@1 91.000 (88.889) Prec@5 100.000 (99.333) +2022-11-14 16:52:11,295 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0618 (0.0721) Prec@1 91.000 (88.964) Prec@5 100.000 (99.357) +2022-11-14 16:52:11,303 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0679 (0.0720) Prec@1 87.000 (88.897) Prec@5 96.000 (99.241) +2022-11-14 16:52:11,310 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0719) Prec@1 87.000 (88.833) Prec@5 100.000 (99.267) +2022-11-14 16:52:11,318 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0721) Prec@1 89.000 (88.839) Prec@5 100.000 (99.290) +2022-11-14 16:52:11,325 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0736 (0.0721) Prec@1 88.000 (88.812) Prec@5 98.000 (99.250) +2022-11-14 16:52:11,333 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0794 (0.0723) Prec@1 86.000 (88.727) Prec@5 97.000 (99.182) +2022-11-14 16:52:11,340 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0855 (0.0727) Prec@1 86.000 (88.647) Prec@5 99.000 (99.176) +2022-11-14 16:52:11,348 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0899 (0.0732) Prec@1 87.000 (88.600) Prec@5 100.000 (99.200) +2022-11-14 16:52:11,355 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0649 (0.0730) Prec@1 92.000 (88.694) Prec@5 100.000 (99.222) +2022-11-14 16:52:11,363 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0731) Prec@1 88.000 (88.676) Prec@5 98.000 (99.189) +2022-11-14 16:52:11,370 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1079 (0.0741) Prec@1 82.000 (88.500) Prec@5 98.000 (99.158) +2022-11-14 16:52:11,378 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0736) Prec@1 92.000 (88.590) Prec@5 99.000 (99.154) +2022-11-14 16:52:11,385 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0455 (0.0729) Prec@1 93.000 (88.700) Prec@5 100.000 (99.175) +2022-11-14 16:52:11,393 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0847 (0.0732) Prec@1 88.000 (88.683) Prec@5 98.000 (99.146) +2022-11-14 16:52:11,400 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0673 (0.0731) Prec@1 88.000 (88.667) Prec@5 99.000 (99.143) +2022-11-14 16:52:11,408 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0406 (0.0723) Prec@1 95.000 (88.814) Prec@5 100.000 (99.163) +2022-11-14 16:52:11,416 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0713 (0.0723) Prec@1 89.000 (88.818) Prec@5 97.000 (99.114) +2022-11-14 16:52:11,423 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0534 (0.0719) Prec@1 94.000 (88.933) Prec@5 98.000 (99.089) +2022-11-14 16:52:11,431 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1058 (0.0726) Prec@1 81.000 (88.761) Prec@5 100.000 (99.109) +2022-11-14 16:52:11,438 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0727) Prec@1 87.000 (88.723) Prec@5 100.000 (99.128) +2022-11-14 16:52:11,446 Test: 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Loss 0.0754 (0.0730) Prec@1 89.000 (88.574) Prec@5 98.000 (99.185) +2022-11-14 16:52:11,500 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0730) Prec@1 88.000 (88.564) Prec@5 100.000 (99.200) +2022-11-14 16:52:11,508 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0633 (0.0728) Prec@1 91.000 (88.607) Prec@5 99.000 (99.196) +2022-11-14 16:52:11,515 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0870 (0.0731) Prec@1 84.000 (88.526) Prec@5 99.000 (99.193) +2022-11-14 16:52:11,523 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0715 (0.0730) Prec@1 90.000 (88.552) Prec@5 98.000 (99.172) +2022-11-14 16:52:11,530 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1121 (0.0737) Prec@1 83.000 (88.458) Prec@5 100.000 (99.186) +2022-11-14 16:52:11,538 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0736) Prec@1 88.000 (88.450) Prec@5 99.000 (99.183) +2022-11-14 16:52:11,545 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0621 (0.0734) Prec@1 90.000 (88.475) Prec@5 99.000 (99.180) +2022-11-14 16:52:11,553 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0735) Prec@1 88.000 (88.468) Prec@5 100.000 (99.194) +2022-11-14 16:52:11,561 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0485 (0.0731) Prec@1 93.000 (88.540) Prec@5 100.000 (99.206) +2022-11-14 16:52:11,568 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0309 (0.0725) Prec@1 94.000 (88.625) Prec@5 99.000 (99.203) +2022-11-14 16:52:11,576 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0880 (0.0727) Prec@1 85.000 (88.569) Prec@5 100.000 (99.215) +2022-11-14 16:52:11,584 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0595 (0.0725) Prec@1 90.000 (88.591) Prec@5 99.000 (99.212) +2022-11-14 16:52:11,591 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0285 (0.0719) Prec@1 96.000 (88.701) Prec@5 99.000 (99.209) +2022-11-14 16:52:11,599 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0718) Prec@1 90.000 (88.721) Prec@5 100.000 (99.221) +2022-11-14 16:52:11,607 Test: [68/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0623 (0.0717) Prec@1 90.000 (88.739) Prec@5 99.000 (99.217) +2022-11-14 16:52:11,615 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0718) Prec@1 89.000 (88.743) Prec@5 100.000 (99.229) +2022-11-14 16:52:11,622 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0893 (0.0720) Prec@1 88.000 (88.732) Prec@5 98.000 (99.211) +2022-11-14 16:52:11,630 Test: [71/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0719) Prec@1 89.000 (88.736) Prec@5 100.000 (99.222) +2022-11-14 16:52:11,638 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0384 (0.0714) Prec@1 93.000 (88.795) Prec@5 100.000 (99.233) +2022-11-14 16:52:11,645 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0357 (0.0709) Prec@1 95.000 (88.878) Prec@5 100.000 (99.243) +2022-11-14 16:52:11,653 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0713) Prec@1 85.000 (88.827) Prec@5 100.000 (99.253) +2022-11-14 16:52:11,660 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0711) Prec@1 91.000 (88.855) Prec@5 99.000 (99.250) +2022-11-14 16:52:11,668 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0711) Prec@1 90.000 (88.870) Prec@5 99.000 (99.247) +2022-11-14 16:52:11,676 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0866 (0.0713) Prec@1 86.000 (88.833) Prec@5 100.000 (99.256) +2022-11-14 16:52:11,683 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0714) Prec@1 89.000 (88.835) Prec@5 100.000 (99.266) +2022-11-14 16:52:11,691 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0778 (0.0715) Prec@1 87.000 (88.812) Prec@5 100.000 (99.275) +2022-11-14 16:52:11,699 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0826 (0.0716) Prec@1 86.000 (88.778) Prec@5 99.000 (99.272) +2022-11-14 16:52:11,707 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0716) Prec@1 88.000 (88.768) Prec@5 99.000 (99.268) +2022-11-14 16:52:11,715 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1151 (0.0721) Prec@1 82.000 (88.687) Prec@5 100.000 (99.277) +2022-11-14 16:52:11,722 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0721) Prec@1 86.000 (88.655) Prec@5 99.000 (99.274) +2022-11-14 16:52:11,730 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0722) Prec@1 89.000 (88.659) Prec@5 99.000 (99.271) +2022-11-14 16:52:11,737 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0996 (0.0725) Prec@1 83.000 (88.593) Prec@5 100.000 (99.279) +2022-11-14 16:52:11,745 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0724) Prec@1 89.000 (88.598) Prec@5 100.000 (99.287) +2022-11-14 16:52:11,752 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0725) Prec@1 89.000 (88.602) Prec@5 99.000 (99.284) +2022-11-14 16:52:11,760 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0725) Prec@1 88.000 (88.596) Prec@5 99.000 (99.281) +2022-11-14 16:52:11,767 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0680 (0.0724) Prec@1 89.000 (88.600) Prec@5 100.000 (99.289) +2022-11-14 16:52:11,775 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0722) Prec@1 91.000 (88.626) Prec@5 100.000 (99.297) +2022-11-14 16:52:11,783 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0722) Prec@1 90.000 (88.641) Prec@5 99.000 (99.293) +2022-11-14 16:52:11,790 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1052 (0.0725) Prec@1 83.000 (88.581) Prec@5 99.000 (99.290) +2022-11-14 16:52:11,798 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0725) Prec@1 88.000 (88.574) Prec@5 99.000 (99.287) +2022-11-14 16:52:11,805 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0939 (0.0727) Prec@1 83.000 (88.516) Prec@5 99.000 (99.284) +2022-11-14 16:52:11,813 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0720 (0.0727) Prec@1 88.000 (88.510) Prec@5 99.000 (99.281) +2022-11-14 16:52:11,820 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0449 (0.0724) Prec@1 92.000 (88.546) Prec@5 98.000 (99.268) +2022-11-14 16:52:11,827 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0727) Prec@1 84.000 (88.500) Prec@5 100.000 (99.276) +2022-11-14 16:52:11,835 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0913 (0.0729) Prec@1 88.000 (88.495) Prec@5 99.000 (99.273) +2022-11-14 16:52:11,842 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0729) Prec@1 88.000 (88.490) Prec@5 100.000 (99.280) +2022-11-14 16:52:11,897 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:52:12,208 Epoch: [403][0/500] Time 0.022 (0.022) Data 0.234 (0.234) Loss 0.0327 (0.0327) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:12,401 Epoch: [403][10/500] Time 0.016 (0.017) Data 0.002 (0.023) Loss 0.0253 (0.0290) Prec@1 96.000 (95.000) Prec@5 99.000 (99.500) +2022-11-14 16:52:12,590 Epoch: [403][20/500] Time 0.016 (0.017) Data 0.002 (0.013) Loss 0.0343 (0.0308) Prec@1 93.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:52:12,779 Epoch: [403][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0415 (0.0335) Prec@1 93.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:52:12,971 Epoch: [403][40/500] Time 0.018 (0.017) Data 0.002 (0.007) Loss 0.0184 (0.0305) Prec@1 96.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:52:13,168 Epoch: [403][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0173 (0.0283) Prec@1 98.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 16:52:13,430 Epoch: [403][60/500] Time 0.025 (0.018) Data 0.002 (0.005) Loss 0.0336 (0.0290) Prec@1 93.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 16:52:13,717 Epoch: [403][70/500] Time 0.029 (0.019) Data 0.002 (0.005) Loss 0.0674 (0.0338) Prec@1 89.000 (94.000) Prec@5 100.000 (99.875) +2022-11-14 16:52:13,994 Epoch: [403][80/500] Time 0.026 (0.020) Data 0.001 (0.005) Loss 0.0227 (0.0326) Prec@1 96.000 (94.222) Prec@5 100.000 (99.889) +2022-11-14 16:52:14,281 Epoch: [403][90/500] Time 0.027 (0.020) Data 0.002 (0.004) Loss 0.0191 (0.0312) Prec@1 97.000 (94.500) Prec@5 100.000 (99.900) +2022-11-14 16:52:14,567 Epoch: [403][100/500] Time 0.026 (0.021) Data 0.002 (0.004) Loss 0.0486 (0.0328) Prec@1 91.000 (94.182) Prec@5 99.000 (99.818) +2022-11-14 16:52:14,863 Epoch: [403][110/500] Time 0.033 (0.021) Data 0.002 (0.004) Loss 0.0386 (0.0333) Prec@1 95.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 16:52:15,147 Epoch: [403][120/500] Time 0.025 (0.022) Data 0.002 (0.004) Loss 0.0291 (0.0330) Prec@1 95.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 16:52:15,434 Epoch: [403][130/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0266 (0.0325) Prec@1 95.000 (94.357) Prec@5 100.000 (99.857) +2022-11-14 16:52:15,713 Epoch: [403][140/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0541 (0.0340) Prec@1 93.000 (94.267) Prec@5 99.000 (99.800) +2022-11-14 16:52:15,987 Epoch: [403][150/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0233 (0.0333) Prec@1 97.000 (94.438) Prec@5 100.000 (99.812) +2022-11-14 16:52:16,262 Epoch: [403][160/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0407 (0.0337) Prec@1 94.000 (94.412) Prec@5 100.000 (99.824) +2022-11-14 16:52:16,538 Epoch: [403][170/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0193 (0.0329) Prec@1 97.000 (94.556) Prec@5 100.000 (99.833) +2022-11-14 16:52:16,815 Epoch: [403][180/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0259 (0.0326) Prec@1 95.000 (94.579) Prec@5 100.000 (99.842) +2022-11-14 16:52:17,095 Epoch: [403][190/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0453 (0.0332) Prec@1 91.000 (94.400) Prec@5 100.000 (99.850) +2022-11-14 16:52:17,367 Epoch: [403][200/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0130 (0.0322) Prec@1 97.000 (94.524) Prec@5 100.000 (99.857) +2022-11-14 16:52:17,644 Epoch: [403][210/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0183 (0.0316) Prec@1 96.000 (94.591) Prec@5 100.000 (99.864) +2022-11-14 16:52:17,923 Epoch: [403][220/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0491 (0.0324) Prec@1 90.000 (94.391) Prec@5 100.000 (99.870) +2022-11-14 16:52:18,199 Epoch: [403][230/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0333 (0.0324) Prec@1 96.000 (94.458) Prec@5 100.000 (99.875) +2022-11-14 16:52:18,473 Epoch: [403][240/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0222 (0.0320) Prec@1 95.000 (94.480) Prec@5 100.000 (99.880) +2022-11-14 16:52:18,746 Epoch: [403][250/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0252 (0.0317) Prec@1 96.000 (94.538) Prec@5 99.000 (99.846) +2022-11-14 16:52:19,023 Epoch: [403][260/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0452 (0.0322) Prec@1 94.000 (94.519) Prec@5 100.000 (99.852) +2022-11-14 16:52:19,299 Epoch: [403][270/500] Time 0.027 (0.023) Data 0.001 (0.003) Loss 0.0345 (0.0323) Prec@1 94.000 (94.500) Prec@5 100.000 (99.857) +2022-11-14 16:52:19,572 Epoch: [403][280/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0286 (0.0322) Prec@1 96.000 (94.552) Prec@5 100.000 (99.862) +2022-11-14 16:52:19,847 Epoch: [403][290/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0084 (0.0314) Prec@1 99.000 (94.700) Prec@5 100.000 (99.867) +2022-11-14 16:52:20,125 Epoch: [403][300/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0365 (0.0316) Prec@1 93.000 (94.645) Prec@5 99.000 (99.839) +2022-11-14 16:52:20,402 Epoch: [403][310/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0187 (0.0312) Prec@1 97.000 (94.719) Prec@5 100.000 (99.844) +2022-11-14 16:52:20,680 Epoch: [403][320/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0286 (0.0311) Prec@1 95.000 (94.727) Prec@5 100.000 (99.848) +2022-11-14 16:52:20,956 Epoch: [403][330/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0102 (0.0305) Prec@1 99.000 (94.853) Prec@5 100.000 (99.853) +2022-11-14 16:52:21,231 Epoch: [403][340/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0144 (0.0300) Prec@1 98.000 (94.943) Prec@5 100.000 (99.857) +2022-11-14 16:52:21,503 Epoch: [403][350/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0133 (0.0295) Prec@1 98.000 (95.028) Prec@5 100.000 (99.861) +2022-11-14 16:52:21,774 Epoch: [403][360/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0427 (0.0299) Prec@1 94.000 (95.000) Prec@5 100.000 (99.865) +2022-11-14 16:52:22,047 Epoch: [403][370/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0272 (0.0298) Prec@1 96.000 (95.026) Prec@5 100.000 (99.868) +2022-11-14 16:52:22,324 Epoch: [403][380/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0317 (0.0299) Prec@1 95.000 (95.026) Prec@5 100.000 (99.872) +2022-11-14 16:52:22,599 Epoch: [403][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0217 (0.0297) Prec@1 97.000 (95.075) Prec@5 100.000 (99.875) +2022-11-14 16:52:22,871 Epoch: [403][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0546 (0.0303) Prec@1 91.000 (94.976) Prec@5 100.000 (99.878) +2022-11-14 16:52:23,149 Epoch: [403][410/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0373 (0.0304) Prec@1 93.000 (94.929) Prec@5 99.000 (99.857) +2022-11-14 16:52:23,426 Epoch: [403][420/500] Time 0.025 (0.024) Data 0.003 (0.002) Loss 0.0397 (0.0307) Prec@1 94.000 (94.907) Prec@5 100.000 (99.860) +2022-11-14 16:52:23,696 Epoch: [403][430/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0308 (0.0307) Prec@1 95.000 (94.909) Prec@5 99.000 (99.841) +2022-11-14 16:52:23,968 Epoch: [403][440/500] Time 0.026 (0.024) Data 0.001 (0.002) Loss 0.0148 (0.0303) Prec@1 98.000 (94.978) Prec@5 100.000 (99.844) +2022-11-14 16:52:24,243 Epoch: [403][450/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0345 (0.0304) Prec@1 93.000 (94.935) Prec@5 100.000 (99.848) +2022-11-14 16:52:24,518 Epoch: [403][460/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0256 (0.0303) Prec@1 95.000 (94.936) Prec@5 100.000 (99.851) +2022-11-14 16:52:24,791 Epoch: [403][470/500] Time 0.025 (0.024) Data 0.001 (0.002) Loss 0.0271 (0.0302) Prec@1 96.000 (94.958) Prec@5 100.000 (99.854) +2022-11-14 16:52:25,064 Epoch: [403][480/500] Time 0.025 (0.024) Data 0.001 (0.002) Loss 0.0163 (0.0300) Prec@1 98.000 (95.020) Prec@5 100.000 (99.857) +2022-11-14 16:52:25,337 Epoch: [403][490/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0162 (0.0297) Prec@1 98.000 (95.080) Prec@5 100.000 (99.860) +2022-11-14 16:52:25,582 Epoch: [403][499/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0249 (0.0296) Prec@1 97.000 (95.118) Prec@5 100.000 (99.863) +2022-11-14 16:52:25,882 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0608 (0.0608) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:25,890 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0574 (0.0591) Prec@1 91.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:52:25,899 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0590 (0.0591) Prec@1 93.000 (91.333) Prec@5 100.000 (100.000) +2022-11-14 16:52:25,909 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0654) Prec@1 87.000 (90.250) Prec@5 99.000 (99.750) +2022-11-14 16:52:25,916 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0668) Prec@1 87.000 (89.600) Prec@5 99.000 (99.600) +2022-11-14 16:52:25,923 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0517 (0.0642) Prec@1 91.000 (89.833) Prec@5 100.000 (99.667) +2022-11-14 16:52:25,930 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0610 (0.0638) Prec@1 91.000 (90.000) Prec@5 100.000 (99.714) +2022-11-14 16:52:25,939 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0673) Prec@1 84.000 (89.250) Prec@5 99.000 (99.625) +2022-11-14 16:52:25,946 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0710) Prec@1 85.000 (88.778) Prec@5 97.000 (99.333) +2022-11-14 16:52:25,953 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0712) Prec@1 88.000 (88.700) Prec@5 97.000 (99.100) +2022-11-14 16:52:25,961 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0712) Prec@1 87.000 (88.545) Prec@5 100.000 (99.182) +2022-11-14 16:52:25,968 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0714) Prec@1 89.000 (88.583) Prec@5 99.000 (99.167) +2022-11-14 16:52:25,976 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0708) Prec@1 91.000 (88.769) Prec@5 100.000 (99.231) +2022-11-14 16:52:25,984 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0704) Prec@1 89.000 (88.786) Prec@5 99.000 (99.214) +2022-11-14 16:52:25,992 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0705) Prec@1 88.000 (88.733) Prec@5 100.000 (99.267) +2022-11-14 16:52:26,000 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0707) Prec@1 88.000 (88.688) Prec@5 100.000 (99.312) +2022-11-14 16:52:26,008 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0692) Prec@1 93.000 (88.941) Prec@5 99.000 (99.294) +2022-11-14 16:52:26,015 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0715) Prec@1 84.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 16:52:26,023 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0723) Prec@1 88.000 (88.632) Prec@5 98.000 (99.263) +2022-11-14 16:52:26,031 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0736) Prec@1 87.000 (88.550) Prec@5 95.000 (99.050) +2022-11-14 16:52:26,039 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0729) Prec@1 91.000 (88.667) Prec@5 100.000 (99.095) +2022-11-14 16:52:26,047 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0732) Prec@1 89.000 (88.682) Prec@5 99.000 (99.091) +2022-11-14 16:52:26,055 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0743) Prec@1 85.000 (88.522) Prec@5 99.000 (99.087) +2022-11-14 16:52:26,062 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0740) Prec@1 89.000 (88.542) Prec@5 99.000 (99.083) +2022-11-14 16:52:26,070 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0746) Prec@1 82.000 (88.280) Prec@5 100.000 (99.120) +2022-11-14 16:52:26,078 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0758) Prec@1 82.000 (88.038) Prec@5 97.000 (99.038) +2022-11-14 16:52:26,086 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0749) Prec@1 90.000 (88.111) Prec@5 100.000 (99.074) +2022-11-14 16:52:26,094 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0740) Prec@1 91.000 (88.214) Prec@5 100.000 (99.107) +2022-11-14 16:52:26,102 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0740) Prec@1 88.000 (88.207) Prec@5 99.000 (99.103) +2022-11-14 16:52:26,110 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0741) Prec@1 84.000 (88.067) Prec@5 100.000 (99.133) +2022-11-14 16:52:26,118 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0739) Prec@1 90.000 (88.129) Prec@5 100.000 (99.161) +2022-11-14 16:52:26,126 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0732) Prec@1 92.000 (88.250) Prec@5 100.000 (99.188) +2022-11-14 16:52:26,134 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0732) Prec@1 86.000 (88.182) Prec@5 100.000 (99.212) +2022-11-14 16:52:26,141 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0740) Prec@1 85.000 (88.088) Prec@5 99.000 (99.206) +2022-11-14 16:52:26,149 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0742) Prec@1 89.000 (88.114) Prec@5 98.000 (99.171) +2022-11-14 16:52:26,156 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0740) Prec@1 91.000 (88.194) Prec@5 98.000 (99.139) +2022-11-14 16:52:26,164 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0739) Prec@1 90.000 (88.243) Prec@5 98.000 (99.108) +2022-11-14 16:52:26,172 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0746) Prec@1 84.000 (88.132) Prec@5 98.000 (99.079) +2022-11-14 16:52:26,180 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0740) Prec@1 95.000 (88.308) Prec@5 99.000 (99.077) +2022-11-14 16:52:26,187 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0739) Prec@1 90.000 (88.350) Prec@5 98.000 (99.050) +2022-11-14 16:52:26,195 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0746) Prec@1 86.000 (88.293) Prec@5 99.000 (99.049) +2022-11-14 16:52:26,203 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0745) Prec@1 89.000 (88.310) Prec@5 100.000 (99.071) +2022-11-14 16:52:26,211 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0741) Prec@1 91.000 (88.372) Prec@5 99.000 (99.070) +2022-11-14 16:52:26,219 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0741) Prec@1 90.000 (88.409) Prec@5 98.000 (99.045) +2022-11-14 16:52:26,227 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0738) Prec@1 89.000 (88.422) Prec@5 100.000 (99.067) +2022-11-14 16:52:26,234 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1171 (0.0748) Prec@1 80.000 (88.239) Prec@5 100.000 (99.087) +2022-11-14 16:52:26,243 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0747) Prec@1 89.000 (88.255) Prec@5 100.000 (99.106) +2022-11-14 16:52:26,251 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0751) Prec@1 85.000 (88.188) Prec@5 100.000 (99.125) +2022-11-14 16:52:26,259 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0747) Prec@1 90.000 (88.224) Prec@5 99.000 (99.122) +2022-11-14 16:52:26,267 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0753) Prec@1 83.000 (88.120) Prec@5 99.000 (99.120) +2022-11-14 16:52:26,274 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0750) Prec@1 90.000 (88.157) Prec@5 100.000 (99.137) +2022-11-14 16:52:26,282 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0747) Prec@1 91.000 (88.212) Prec@5 99.000 (99.135) +2022-11-14 16:52:26,290 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0746) Prec@1 88.000 (88.208) Prec@5 100.000 (99.151) +2022-11-14 16:52:26,298 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0745) Prec@1 87.000 (88.185) Prec@5 99.000 (99.148) +2022-11-14 16:52:26,306 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0747) Prec@1 87.000 (88.164) Prec@5 99.000 (99.145) +2022-11-14 16:52:26,313 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0743) Prec@1 93.000 (88.250) Prec@5 99.000 (99.143) +2022-11-14 16:52:26,321 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0743) Prec@1 87.000 (88.228) Prec@5 100.000 (99.158) +2022-11-14 16:52:26,329 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0743) Prec@1 88.000 (88.224) Prec@5 100.000 (99.172) +2022-11-14 16:52:26,337 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0746) Prec@1 82.000 (88.119) Prec@5 100.000 (99.186) +2022-11-14 16:52:26,345 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0748) Prec@1 85.000 (88.067) Prec@5 99.000 (99.183) +2022-11-14 16:52:26,352 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0748) Prec@1 87.000 (88.049) Prec@5 100.000 (99.197) +2022-11-14 16:52:26,360 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0744) Prec@1 91.000 (88.097) Prec@5 100.000 (99.210) +2022-11-14 16:52:26,368 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0740) Prec@1 93.000 (88.175) Prec@5 99.000 (99.206) +2022-11-14 16:52:26,376 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0360 (0.0734) Prec@1 95.000 (88.281) Prec@5 100.000 (99.219) +2022-11-14 16:52:26,383 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0737) Prec@1 85.000 (88.231) Prec@5 98.000 (99.200) +2022-11-14 16:52:26,391 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0735) Prec@1 91.000 (88.273) Prec@5 98.000 (99.182) +2022-11-14 16:52:26,399 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0454 (0.0731) Prec@1 93.000 (88.343) Prec@5 100.000 (99.194) +2022-11-14 16:52:26,406 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0730) Prec@1 89.000 (88.353) Prec@5 98.000 (99.176) +2022-11-14 16:52:26,414 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0730) Prec@1 86.000 (88.319) Prec@5 99.000 (99.174) +2022-11-14 16:52:26,421 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0730) Prec@1 87.000 (88.300) Prec@5 98.000 (99.157) +2022-11-14 16:52:26,429 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0735) Prec@1 84.000 (88.239) Prec@5 100.000 (99.169) +2022-11-14 16:52:26,437 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0733) Prec@1 88.000 (88.236) Prec@5 100.000 (99.181) +2022-11-14 16:52:26,445 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0731) Prec@1 91.000 (88.274) Prec@5 100.000 (99.192) +2022-11-14 16:52:26,453 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0727) Prec@1 92.000 (88.324) Prec@5 100.000 (99.203) +2022-11-14 16:52:26,461 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0732) Prec@1 81.000 (88.227) Prec@5 99.000 (99.200) +2022-11-14 16:52:26,468 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0732) Prec@1 91.000 (88.263) Prec@5 100.000 (99.211) +2022-11-14 16:52:26,476 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0730) Prec@1 91.000 (88.299) Prec@5 100.000 (99.221) +2022-11-14 16:52:26,484 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0732) Prec@1 86.000 (88.269) Prec@5 100.000 (99.231) +2022-11-14 16:52:26,492 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0734) Prec@1 86.000 (88.241) Prec@5 100.000 (99.241) +2022-11-14 16:52:26,500 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0733) Prec@1 88.000 (88.237) Prec@5 100.000 (99.250) +2022-11-14 16:52:26,508 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0736) Prec@1 85.000 (88.198) Prec@5 96.000 (99.210) +2022-11-14 16:52:26,515 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0736) Prec@1 91.000 (88.232) Prec@5 99.000 (99.207) +2022-11-14 16:52:26,523 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0737) Prec@1 87.000 (88.217) Prec@5 99.000 (99.205) +2022-11-14 16:52:26,531 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 88.000 (88.214) Prec@5 99.000 (99.202) +2022-11-14 16:52:26,539 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0738) Prec@1 88.000 (88.212) Prec@5 99.000 (99.200) +2022-11-14 16:52:26,547 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0742) Prec@1 86.000 (88.186) Prec@5 99.000 (99.198) +2022-11-14 16:52:26,555 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0743) Prec@1 86.000 (88.161) Prec@5 100.000 (99.207) +2022-11-14 16:52:26,563 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0743) Prec@1 90.000 (88.182) Prec@5 99.000 (99.205) +2022-11-14 16:52:26,570 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0744) Prec@1 87.000 (88.169) Prec@5 100.000 (99.213) +2022-11-14 16:52:26,578 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0742) Prec@1 92.000 (88.211) Prec@5 99.000 (99.211) +2022-11-14 16:52:26,586 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0741) Prec@1 92.000 (88.253) Prec@5 100.000 (99.220) +2022-11-14 16:52:26,594 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0737) Prec@1 91.000 (88.283) Prec@5 100.000 (99.228) +2022-11-14 16:52:26,602 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0739) Prec@1 86.000 (88.258) Prec@5 100.000 (99.237) +2022-11-14 16:52:26,609 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0739) Prec@1 89.000 (88.266) Prec@5 100.000 (99.245) +2022-11-14 16:52:26,617 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0740) Prec@1 86.000 (88.242) Prec@5 100.000 (99.253) +2022-11-14 16:52:26,625 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0738) Prec@1 91.000 (88.271) Prec@5 100.000 (99.260) +2022-11-14 16:52:26,632 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0735) Prec@1 91.000 (88.299) Prec@5 99.000 (99.258) +2022-11-14 16:52:26,640 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0737) Prec@1 87.000 (88.286) Prec@5 98.000 (99.245) +2022-11-14 16:52:26,647 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0740) Prec@1 85.000 (88.253) Prec@5 99.000 (99.242) +2022-11-14 16:52:26,655 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0739) Prec@1 89.000 (88.260) Prec@5 100.000 (99.250) +2022-11-14 16:52:26,723 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:52:27,042 Epoch: [404][0/500] Time 0.022 (0.022) Data 0.241 (0.241) Loss 0.0314 (0.0314) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:52:27,237 Epoch: [404][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0239 (0.0277) Prec@1 98.000 (96.000) Prec@5 99.000 (99.000) +2022-11-14 16:52:27,424 Epoch: [404][20/500] Time 0.016 (0.017) Data 0.002 (0.013) Loss 0.0549 (0.0367) Prec@1 92.000 (94.667) Prec@5 100.000 (99.333) +2022-11-14 16:52:27,608 Epoch: [404][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0419 (0.0380) Prec@1 95.000 (94.750) Prec@5 99.000 (99.250) +2022-11-14 16:52:27,793 Epoch: [404][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0436 (0.0391) Prec@1 93.000 (94.400) Prec@5 100.000 (99.400) +2022-11-14 16:52:27,978 Epoch: [404][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0212 (0.0362) Prec@1 96.000 (94.667) Prec@5 100.000 (99.500) +2022-11-14 16:52:28,166 Epoch: [404][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0527 (0.0385) Prec@1 90.000 (94.000) Prec@5 99.000 (99.429) +2022-11-14 16:52:28,349 Epoch: [404][70/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0268 (0.0371) Prec@1 95.000 (94.125) Prec@5 100.000 (99.500) +2022-11-14 16:52:28,538 Epoch: [404][80/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0302 (0.0363) Prec@1 93.000 (94.000) Prec@5 100.000 (99.556) +2022-11-14 16:52:28,785 Epoch: [404][90/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0290 (0.0356) Prec@1 95.000 (94.100) Prec@5 100.000 (99.600) +2022-11-14 16:52:29,045 Epoch: [404][100/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0206 (0.0342) Prec@1 97.000 (94.364) Prec@5 99.000 (99.545) +2022-11-14 16:52:29,305 Epoch: [404][110/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0361 (0.0344) Prec@1 94.000 (94.333) Prec@5 100.000 (99.583) +2022-11-14 16:52:29,563 Epoch: [404][120/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0124 (0.0327) Prec@1 99.000 (94.692) Prec@5 100.000 (99.615) +2022-11-14 16:52:29,829 Epoch: [404][130/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0330 (0.0327) Prec@1 96.000 (94.786) Prec@5 99.000 (99.571) +2022-11-14 16:52:30,094 Epoch: [404][140/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0444 (0.0335) Prec@1 93.000 (94.667) Prec@5 100.000 (99.600) +2022-11-14 16:52:30,356 Epoch: [404][150/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0371 (0.0337) Prec@1 93.000 (94.562) Prec@5 100.000 (99.625) +2022-11-14 16:52:30,622 Epoch: [404][160/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0139 (0.0325) Prec@1 97.000 (94.706) Prec@5 100.000 (99.647) +2022-11-14 16:52:30,889 Epoch: [404][170/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0357 (0.0327) Prec@1 95.000 (94.722) Prec@5 100.000 (99.667) +2022-11-14 16:52:31,155 Epoch: [404][180/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0261 (0.0324) Prec@1 96.000 (94.789) Prec@5 100.000 (99.684) +2022-11-14 16:52:31,423 Epoch: [404][190/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0407 (0.0328) Prec@1 94.000 (94.750) Prec@5 100.000 (99.700) +2022-11-14 16:52:31,694 Epoch: [404][200/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0242 (0.0324) Prec@1 97.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 16:52:31,964 Epoch: [404][210/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0190 (0.0318) Prec@1 96.000 (94.909) Prec@5 100.000 (99.727) +2022-11-14 16:52:32,232 Epoch: [404][220/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0264 (0.0315) Prec@1 95.000 (94.913) Prec@5 100.000 (99.739) +2022-11-14 16:52:32,495 Epoch: [404][230/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0161 (0.0309) Prec@1 97.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:52:32,762 Epoch: [404][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0311 (0.0309) Prec@1 93.000 (94.920) Prec@5 100.000 (99.760) +2022-11-14 16:52:33,018 Epoch: [404][250/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0278 (0.0308) Prec@1 96.000 (94.962) Prec@5 99.000 (99.731) +2022-11-14 16:52:33,275 Epoch: [404][260/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0295 (0.0307) Prec@1 94.000 (94.926) Prec@5 100.000 (99.741) +2022-11-14 16:52:33,535 Epoch: [404][270/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0272 (0.0306) Prec@1 94.000 (94.893) Prec@5 100.000 (99.750) +2022-11-14 16:52:33,791 Epoch: [404][280/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0401 (0.0309) Prec@1 92.000 (94.793) Prec@5 100.000 (99.759) +2022-11-14 16:52:34,050 Epoch: [404][290/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0292 (0.0309) Prec@1 94.000 (94.767) Prec@5 100.000 (99.767) +2022-11-14 16:52:34,311 Epoch: [404][300/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0284 (0.0308) Prec@1 96.000 (94.806) Prec@5 99.000 (99.742) +2022-11-14 16:52:34,569 Epoch: [404][310/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0228 (0.0305) Prec@1 95.000 (94.812) Prec@5 100.000 (99.750) +2022-11-14 16:52:34,829 Epoch: [404][320/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0220 (0.0303) Prec@1 96.000 (94.848) Prec@5 100.000 (99.758) +2022-11-14 16:52:35,093 Epoch: [404][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0200 (0.0300) Prec@1 98.000 (94.941) Prec@5 100.000 (99.765) +2022-11-14 16:52:35,351 Epoch: [404][340/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0033 (0.0292) Prec@1 100.000 (95.086) Prec@5 100.000 (99.771) +2022-11-14 16:52:35,609 Epoch: [404][350/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0236 (0.0291) Prec@1 97.000 (95.139) Prec@5 100.000 (99.778) +2022-11-14 16:52:35,868 Epoch: [404][360/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0178 (0.0288) Prec@1 98.000 (95.216) Prec@5 100.000 (99.784) +2022-11-14 16:52:36,131 Epoch: [404][370/500] Time 0.028 (0.022) Data 0.001 (0.002) Loss 0.0574 (0.0295) Prec@1 90.000 (95.079) Prec@5 100.000 (99.789) +2022-11-14 16:52:36,387 Epoch: [404][380/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0488 (0.0300) Prec@1 92.000 (95.000) Prec@5 100.000 (99.795) +2022-11-14 16:52:36,646 Epoch: [404][390/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0162 (0.0297) Prec@1 97.000 (95.050) Prec@5 100.000 (99.800) +2022-11-14 16:52:36,905 Epoch: [404][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0495 (0.0302) Prec@1 91.000 (94.951) Prec@5 100.000 (99.805) +2022-11-14 16:52:37,170 Epoch: [404][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0167 (0.0298) Prec@1 97.000 (95.000) Prec@5 100.000 (99.810) +2022-11-14 16:52:37,428 Epoch: [404][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0158 (0.0295) Prec@1 98.000 (95.070) Prec@5 100.000 (99.814) +2022-11-14 16:52:37,689 Epoch: [404][430/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0255 (0.0294) Prec@1 94.000 (95.045) Prec@5 100.000 (99.818) +2022-11-14 16:52:37,948 Epoch: [404][440/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0460 (0.0298) Prec@1 92.000 (94.978) Prec@5 99.000 (99.800) +2022-11-14 16:52:38,211 Epoch: [404][450/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0253 (0.0297) Prec@1 97.000 (95.022) Prec@5 100.000 (99.804) +2022-11-14 16:52:38,468 Epoch: [404][460/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0301 (0.0297) Prec@1 93.000 (94.979) Prec@5 100.000 (99.809) +2022-11-14 16:52:38,727 Epoch: [404][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0491 (0.0301) Prec@1 91.000 (94.896) Prec@5 100.000 (99.812) +2022-11-14 16:52:38,989 Epoch: [404][480/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0321 (0.0301) Prec@1 95.000 (94.898) Prec@5 100.000 (99.816) +2022-11-14 16:52:39,250 Epoch: [404][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0372 (0.0303) Prec@1 93.000 (94.860) Prec@5 100.000 (99.820) +2022-11-14 16:52:39,483 Epoch: [404][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0165 (0.0300) Prec@1 97.000 (94.902) Prec@5 100.000 (99.824) +2022-11-14 16:52:39,778 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0487 (0.0487) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:39,790 Test: [1/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0629 (0.0558) Prec@1 89.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 16:52:39,799 Test: [2/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0832 (0.0650) Prec@1 85.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:52:39,809 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0737 (0.0671) Prec@1 88.000 (88.500) Prec@5 100.000 (99.750) +2022-11-14 16:52:39,816 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0677) Prec@1 88.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 16:52:39,825 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0354 (0.0623) Prec@1 94.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 16:52:39,834 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0618) Prec@1 90.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 16:52:39,842 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0637) Prec@1 87.000 (89.125) Prec@5 98.000 (99.625) +2022-11-14 16:52:39,849 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0649) Prec@1 88.000 (89.000) Prec@5 98.000 (99.444) +2022-11-14 16:52:39,859 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0660) Prec@1 87.000 (88.800) Prec@5 99.000 (99.400) +2022-11-14 16:52:39,869 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0664) Prec@1 88.000 (88.727) Prec@5 99.000 (99.364) +2022-11-14 16:52:39,878 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0693) Prec@1 84.000 (88.333) Prec@5 98.000 (99.250) +2022-11-14 16:52:39,885 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0694) Prec@1 88.000 (88.308) Prec@5 100.000 (99.308) +2022-11-14 16:52:39,895 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0693) Prec@1 90.000 (88.429) Prec@5 100.000 (99.357) +2022-11-14 16:52:39,905 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0690) Prec@1 90.000 (88.533) Prec@5 100.000 (99.400) +2022-11-14 16:52:39,912 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0688) Prec@1 89.000 (88.562) Prec@5 98.000 (99.312) +2022-11-14 16:52:39,920 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0679) Prec@1 92.000 (88.765) Prec@5 98.000 (99.235) +2022-11-14 16:52:39,929 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1184 (0.0707) Prec@1 81.000 (88.333) Prec@5 100.000 (99.278) +2022-11-14 16:52:39,939 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0714) Prec@1 87.000 (88.263) Prec@5 98.000 (99.211) +2022-11-14 16:52:39,947 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0771 (0.0717) Prec@1 88.000 (88.250) Prec@5 98.000 (99.150) +2022-11-14 16:52:39,954 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0718) Prec@1 87.000 (88.190) Prec@5 99.000 (99.143) +2022-11-14 16:52:39,964 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0730) Prec@1 84.000 (88.000) Prec@5 100.000 (99.182) +2022-11-14 16:52:39,974 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0744) Prec@1 83.000 (87.783) Prec@5 98.000 (99.130) +2022-11-14 16:52:39,981 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0747) Prec@1 87.000 (87.750) Prec@5 100.000 (99.167) +2022-11-14 16:52:39,989 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0749) Prec@1 90.000 (87.840) Prec@5 99.000 (99.160) +2022-11-14 16:52:39,999 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0756) Prec@1 88.000 (87.846) Prec@5 98.000 (99.115) +2022-11-14 16:52:40,008 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0751) Prec@1 90.000 (87.926) Prec@5 100.000 (99.148) +2022-11-14 16:52:40,016 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0749) Prec@1 88.000 (87.929) Prec@5 99.000 (99.143) +2022-11-14 16:52:40,024 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0747) Prec@1 89.000 (87.966) Prec@5 98.000 (99.103) +2022-11-14 16:52:40,031 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0744) Prec@1 89.000 (88.000) Prec@5 100.000 (99.133) +2022-11-14 16:52:40,039 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0739) Prec@1 89.000 (88.032) Prec@5 100.000 (99.161) +2022-11-14 16:52:40,046 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0738) Prec@1 89.000 (88.062) Prec@5 100.000 (99.188) +2022-11-14 16:52:40,053 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0740) Prec@1 84.000 (87.939) Prec@5 99.000 (99.182) +2022-11-14 16:52:40,061 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0744) Prec@1 86.000 (87.882) Prec@5 99.000 (99.176) +2022-11-14 16:52:40,068 Test: [34/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0749) Prec@1 87.000 (87.857) Prec@5 98.000 (99.143) +2022-11-14 16:52:40,076 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0750) Prec@1 87.000 (87.833) Prec@5 100.000 (99.167) +2022-11-14 16:52:40,084 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0750) Prec@1 88.000 (87.838) Prec@5 99.000 (99.162) +2022-11-14 16:52:40,092 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1188 (0.0762) Prec@1 79.000 (87.605) Prec@5 100.000 (99.184) +2022-11-14 16:52:40,100 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0758) Prec@1 91.000 (87.692) Prec@5 99.000 (99.179) +2022-11-14 16:52:40,107 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0756) Prec@1 90.000 (87.750) Prec@5 100.000 (99.200) +2022-11-14 16:52:40,115 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0760) Prec@1 86.000 (87.707) Prec@5 98.000 (99.171) +2022-11-14 16:52:40,123 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0759) Prec@1 88.000 (87.714) Prec@5 98.000 (99.143) +2022-11-14 16:52:40,130 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0452 (0.0752) Prec@1 91.000 (87.791) Prec@5 100.000 (99.163) +2022-11-14 16:52:40,138 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0753) Prec@1 89.000 (87.818) Prec@5 98.000 (99.136) +2022-11-14 16:52:40,145 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0445 (0.0746) Prec@1 92.000 (87.911) Prec@5 99.000 (99.133) +2022-11-14 16:52:40,153 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0751) Prec@1 84.000 (87.826) Prec@5 100.000 (99.152) +2022-11-14 16:52:40,161 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0750) Prec@1 88.000 (87.830) Prec@5 99.000 (99.149) +2022-11-14 16:52:40,168 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0752) Prec@1 85.000 (87.771) Prec@5 100.000 (99.167) +2022-11-14 16:52:40,176 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0746) Prec@1 91.000 (87.837) Prec@5 100.000 (99.184) +2022-11-14 16:52:40,184 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0751) Prec@1 86.000 (87.800) Prec@5 100.000 (99.200) +2022-11-14 16:52:40,191 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0751) Prec@1 86.000 (87.765) Prec@5 99.000 (99.196) +2022-11-14 16:52:40,199 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0754) Prec@1 86.000 (87.731) Prec@5 100.000 (99.212) +2022-11-14 16:52:40,206 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0751) Prec@1 89.000 (87.755) Prec@5 100.000 (99.226) +2022-11-14 16:52:40,214 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0749) Prec@1 91.000 (87.815) Prec@5 99.000 (99.222) +2022-11-14 16:52:40,221 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0751) Prec@1 86.000 (87.782) Prec@5 100.000 (99.236) +2022-11-14 16:52:40,229 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0752) Prec@1 88.000 (87.786) Prec@5 99.000 (99.232) +2022-11-14 16:52:40,236 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0752) Prec@1 88.000 (87.789) Prec@5 100.000 (99.246) +2022-11-14 16:52:40,244 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0747) Prec@1 92.000 (87.862) Prec@5 99.000 (99.241) +2022-11-14 16:52:40,251 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1353 (0.0758) Prec@1 77.000 (87.678) Prec@5 99.000 (99.237) +2022-11-14 16:52:40,259 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0760) Prec@1 86.000 (87.650) Prec@5 100.000 (99.250) +2022-11-14 16:52:40,267 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0762) Prec@1 86.000 (87.623) Prec@5 99.000 (99.246) +2022-11-14 16:52:40,275 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0764) Prec@1 87.000 (87.613) Prec@5 99.000 (99.242) +2022-11-14 16:52:40,282 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0762) Prec@1 88.000 (87.619) Prec@5 98.000 (99.222) +2022-11-14 16:52:40,290 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0274 (0.0755) Prec@1 94.000 (87.719) Prec@5 100.000 (99.234) +2022-11-14 16:52:40,297 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0755) Prec@1 89.000 (87.738) Prec@5 99.000 (99.231) +2022-11-14 16:52:40,305 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0754) Prec@1 87.000 (87.727) Prec@5 99.000 (99.227) +2022-11-14 16:52:40,313 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0364 (0.0748) Prec@1 93.000 (87.806) Prec@5 100.000 (99.239) +2022-11-14 16:52:40,321 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0746) Prec@1 91.000 (87.853) Prec@5 99.000 (99.235) +2022-11-14 16:52:40,328 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0747) Prec@1 87.000 (87.841) Prec@5 98.000 (99.217) +2022-11-14 16:52:40,336 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0746) Prec@1 89.000 (87.857) Prec@5 98.000 (99.200) +2022-11-14 16:52:40,343 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0749) Prec@1 86.000 (87.831) Prec@5 100.000 (99.211) +2022-11-14 16:52:40,351 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0747) Prec@1 91.000 (87.875) Prec@5 99.000 (99.208) +2022-11-14 16:52:40,358 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0454 (0.0743) Prec@1 93.000 (87.945) Prec@5 100.000 (99.219) +2022-11-14 16:52:40,367 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0739) Prec@1 93.000 (88.014) Prec@5 100.000 (99.230) +2022-11-14 16:52:40,375 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0741) Prec@1 86.000 (87.987) Prec@5 100.000 (99.240) +2022-11-14 16:52:40,382 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0738) Prec@1 92.000 (88.039) Prec@5 99.000 (99.237) +2022-11-14 16:52:40,390 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0738) Prec@1 89.000 (88.052) Prec@5 99.000 (99.234) +2022-11-14 16:52:40,398 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0738) Prec@1 88.000 (88.051) Prec@5 100.000 (99.244) +2022-11-14 16:52:40,405 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0739) Prec@1 85.000 (88.013) Prec@5 100.000 (99.253) +2022-11-14 16:52:40,413 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0737) Prec@1 92.000 (88.062) Prec@5 100.000 (99.263) +2022-11-14 16:52:40,421 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0737) Prec@1 89.000 (88.074) Prec@5 97.000 (99.235) +2022-11-14 16:52:40,429 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0736) Prec@1 91.000 (88.110) Prec@5 100.000 (99.244) +2022-11-14 16:52:40,437 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0736) Prec@1 85.000 (88.072) Prec@5 100.000 (99.253) +2022-11-14 16:52:40,445 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0738) Prec@1 85.000 (88.036) Prec@5 99.000 (99.250) +2022-11-14 16:52:40,452 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0741) Prec@1 84.000 (87.988) Prec@5 100.000 (99.259) +2022-11-14 16:52:40,460 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0743) Prec@1 86.000 (87.965) Prec@5 100.000 (99.267) +2022-11-14 16:52:40,468 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0741) Prec@1 90.000 (87.989) Prec@5 100.000 (99.276) +2022-11-14 16:52:40,476 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0742) Prec@1 87.000 (87.977) Prec@5 97.000 (99.250) +2022-11-14 16:52:40,484 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0739) Prec@1 91.000 (88.011) Prec@5 100.000 (99.258) +2022-11-14 16:52:40,492 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0738) Prec@1 89.000 (88.022) Prec@5 100.000 (99.267) +2022-11-14 16:52:40,500 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0737) Prec@1 89.000 (88.033) Prec@5 100.000 (99.275) +2022-11-14 16:52:40,507 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0735) Prec@1 91.000 (88.065) Prec@5 100.000 (99.283) +2022-11-14 16:52:40,516 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0737) Prec@1 84.000 (88.022) Prec@5 100.000 (99.290) +2022-11-14 16:52:40,523 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0737) Prec@1 88.000 (88.021) Prec@5 100.000 (99.298) +2022-11-14 16:52:40,531 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0739) Prec@1 83.000 (87.968) Prec@5 100.000 (99.305) +2022-11-14 16:52:40,539 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0738) Prec@1 90.000 (87.990) Prec@5 100.000 (99.312) +2022-11-14 16:52:40,546 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0379 (0.0735) Prec@1 94.000 (88.052) Prec@5 99.000 (99.309) +2022-11-14 16:52:40,554 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0736) Prec@1 85.000 (88.020) Prec@5 98.000 (99.296) +2022-11-14 16:52:40,561 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0735) Prec@1 91.000 (88.051) Prec@5 100.000 (99.303) +2022-11-14 16:52:40,569 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0734) Prec@1 91.000 (88.080) Prec@5 99.000 (99.300) +2022-11-14 16:52:40,623 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:52:40,962 Epoch: [405][0/500] Time 0.029 (0.029) Data 0.257 (0.257) Loss 0.0149 (0.0149) Prec@1 98.000 (98.000) Prec@5 99.000 (99.000) +2022-11-14 16:52:41,176 Epoch: [405][10/500] Time 0.016 (0.020) Data 0.002 (0.025) Loss 0.0276 (0.0213) Prec@1 94.000 (96.000) Prec@5 100.000 (99.500) +2022-11-14 16:52:41,377 Epoch: [405][20/500] Time 0.017 (0.019) Data 0.002 (0.014) Loss 0.0202 (0.0209) Prec@1 97.000 (96.333) Prec@5 100.000 (99.667) +2022-11-14 16:52:41,584 Epoch: [405][30/500] Time 0.016 (0.019) Data 0.002 (0.010) Loss 0.0190 (0.0204) Prec@1 98.000 (96.750) Prec@5 100.000 (99.750) +2022-11-14 16:52:41,783 Epoch: [405][40/500] Time 0.017 (0.018) Data 0.002 (0.008) Loss 0.0197 (0.0203) Prec@1 96.000 (96.600) Prec@5 100.000 (99.800) +2022-11-14 16:52:41,972 Epoch: [405][50/500] Time 0.016 (0.018) Data 0.002 (0.007) Loss 0.0182 (0.0199) Prec@1 97.000 (96.667) Prec@5 100.000 (99.833) +2022-11-14 16:52:42,167 Epoch: [405][60/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0254 (0.0207) Prec@1 96.000 (96.571) Prec@5 100.000 (99.857) +2022-11-14 16:52:42,359 Epoch: [405][70/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0431 (0.0235) Prec@1 94.000 (96.250) Prec@5 99.000 (99.750) +2022-11-14 16:52:42,576 Epoch: [405][80/500] Time 0.024 (0.018) Data 0.002 (0.005) Loss 0.0328 (0.0246) Prec@1 95.000 (96.111) Prec@5 100.000 (99.778) +2022-11-14 16:52:42,841 Epoch: [405][90/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0271 (0.0248) Prec@1 96.000 (96.100) Prec@5 100.000 (99.800) +2022-11-14 16:52:43,113 Epoch: [405][100/500] Time 0.029 (0.019) Data 0.002 (0.004) Loss 0.0125 (0.0237) Prec@1 99.000 (96.364) Prec@5 100.000 (99.818) +2022-11-14 16:52:43,378 Epoch: [405][110/500] Time 0.025 (0.019) Data 0.002 (0.004) Loss 0.0375 (0.0248) Prec@1 94.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 16:52:43,651 Epoch: [405][120/500] Time 0.025 (0.020) Data 0.001 (0.004) Loss 0.0356 (0.0257) Prec@1 95.000 (96.077) Prec@5 100.000 (99.846) +2022-11-14 16:52:43,920 Epoch: [405][130/500] Time 0.025 (0.020) Data 0.002 (0.004) Loss 0.0243 (0.0256) Prec@1 97.000 (96.143) Prec@5 100.000 (99.857) +2022-11-14 16:52:44,195 Epoch: [405][140/500] Time 0.027 (0.020) Data 0.002 (0.004) Loss 0.0274 (0.0257) Prec@1 96.000 (96.133) Prec@5 100.000 (99.867) +2022-11-14 16:52:44,471 Epoch: [405][150/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0226 (0.0255) Prec@1 95.000 (96.062) Prec@5 100.000 (99.875) +2022-11-14 16:52:44,748 Epoch: [405][160/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0197 (0.0252) Prec@1 98.000 (96.176) Prec@5 100.000 (99.882) +2022-11-14 16:52:45,029 Epoch: [405][170/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0095 (0.0243) Prec@1 99.000 (96.333) Prec@5 100.000 (99.889) +2022-11-14 16:52:45,307 Epoch: [405][180/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0328 (0.0247) Prec@1 93.000 (96.158) Prec@5 100.000 (99.895) +2022-11-14 16:52:45,577 Epoch: [405][190/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0356 (0.0253) Prec@1 92.000 (95.950) Prec@5 100.000 (99.900) +2022-11-14 16:52:45,855 Epoch: [405][200/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0530 (0.0266) Prec@1 90.000 (95.667) Prec@5 100.000 (99.905) +2022-11-14 16:52:46,133 Epoch: [405][210/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0318 (0.0268) Prec@1 95.000 (95.636) Prec@5 100.000 (99.909) +2022-11-14 16:52:46,403 Epoch: [405][220/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0299 (0.0270) Prec@1 96.000 (95.652) Prec@5 100.000 (99.913) +2022-11-14 16:52:46,668 Epoch: [405][230/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0284 (0.0270) Prec@1 96.000 (95.667) Prec@5 100.000 (99.917) +2022-11-14 16:52:46,940 Epoch: [405][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0318 (0.0272) Prec@1 94.000 (95.600) Prec@5 100.000 (99.920) +2022-11-14 16:52:47,212 Epoch: [405][250/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0355 (0.0275) Prec@1 94.000 (95.538) Prec@5 100.000 (99.923) +2022-11-14 16:52:47,483 Epoch: [405][260/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0245 (0.0274) Prec@1 97.000 (95.593) Prec@5 100.000 (99.926) +2022-11-14 16:52:47,748 Epoch: [405][270/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0097 (0.0268) Prec@1 99.000 (95.714) Prec@5 100.000 (99.929) +2022-11-14 16:52:48,014 Epoch: [405][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0088 (0.0262) Prec@1 99.000 (95.828) Prec@5 100.000 (99.931) +2022-11-14 16:52:48,288 Epoch: [405][290/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0080 (0.0256) Prec@1 99.000 (95.933) Prec@5 100.000 (99.933) +2022-11-14 16:52:48,560 Epoch: [405][300/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0414 (0.0261) Prec@1 93.000 (95.839) Prec@5 99.000 (99.903) +2022-11-14 16:52:48,825 Epoch: [405][310/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0077 (0.0255) Prec@1 100.000 (95.969) Prec@5 100.000 (99.906) +2022-11-14 16:52:49,096 Epoch: [405][320/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0290 (0.0256) Prec@1 95.000 (95.939) Prec@5 100.000 (99.909) +2022-11-14 16:52:49,369 Epoch: [405][330/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0208 (0.0255) Prec@1 95.000 (95.912) Prec@5 100.000 (99.912) +2022-11-14 16:52:49,636 Epoch: [405][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0338 (0.0257) Prec@1 95.000 (95.886) Prec@5 100.000 (99.914) +2022-11-14 16:52:49,900 Epoch: [405][350/500] Time 0.025 (0.022) Data 0.003 (0.002) Loss 0.0160 (0.0254) Prec@1 98.000 (95.944) Prec@5 100.000 (99.917) +2022-11-14 16:52:50,167 Epoch: [405][360/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0339 (0.0257) Prec@1 94.000 (95.892) Prec@5 100.000 (99.919) +2022-11-14 16:52:50,430 Epoch: [405][370/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0333 (0.0259) Prec@1 95.000 (95.868) Prec@5 100.000 (99.921) +2022-11-14 16:52:50,695 Epoch: [405][380/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0214 (0.0258) Prec@1 98.000 (95.923) Prec@5 100.000 (99.923) +2022-11-14 16:52:50,964 Epoch: [405][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0110 (0.0254) Prec@1 99.000 (96.000) Prec@5 100.000 (99.925) +2022-11-14 16:52:51,235 Epoch: [405][400/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0255 (0.0254) Prec@1 96.000 (96.000) Prec@5 99.000 (99.902) +2022-11-14 16:52:51,499 Epoch: [405][410/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0561 (0.0261) Prec@1 90.000 (95.857) Prec@5 99.000 (99.881) +2022-11-14 16:52:51,763 Epoch: [405][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0250 (0.0261) Prec@1 95.000 (95.837) Prec@5 100.000 (99.884) +2022-11-14 16:52:52,026 Epoch: [405][430/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0321 (0.0262) Prec@1 95.000 (95.818) Prec@5 100.000 (99.886) +2022-11-14 16:52:52,291 Epoch: [405][440/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0285 (0.0263) Prec@1 95.000 (95.800) Prec@5 100.000 (99.889) +2022-11-14 16:52:52,559 Epoch: [405][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0202 (0.0262) Prec@1 97.000 (95.826) Prec@5 100.000 (99.891) +2022-11-14 16:52:52,824 Epoch: [405][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0252 (0.0261) Prec@1 95.000 (95.809) Prec@5 99.000 (99.872) +2022-11-14 16:52:53,094 Epoch: [405][470/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0147 (0.0259) Prec@1 97.000 (95.833) Prec@5 100.000 (99.875) +2022-11-14 16:52:53,360 Epoch: [405][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0384 (0.0261) Prec@1 92.000 (95.755) Prec@5 100.000 (99.878) +2022-11-14 16:52:53,624 Epoch: [405][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0305 (0.0262) Prec@1 95.000 (95.740) Prec@5 100.000 (99.880) +2022-11-14 16:52:53,864 Epoch: [405][499/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0314 (0.0263) Prec@1 95.000 (95.725) Prec@5 100.000 (99.882) +2022-11-14 16:52:54,166 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0530 (0.0530) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:52:54,174 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0678) Prec@1 86.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 16:52:54,181 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0695) Prec@1 86.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:52:54,190 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0704) Prec@1 88.000 (88.000) Prec@5 100.000 (99.750) +2022-11-14 16:52:54,197 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0726) Prec@1 88.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 16:52:54,204 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0418 (0.0675) Prec@1 94.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 16:52:54,211 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0672) Prec@1 90.000 (89.143) Prec@5 100.000 (99.857) +2022-11-14 16:52:54,219 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0689) Prec@1 88.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 16:52:54,226 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0699) Prec@1 89.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 16:52:54,234 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0697) Prec@1 90.000 (89.100) Prec@5 97.000 (99.400) +2022-11-14 16:52:54,242 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0688) Prec@1 92.000 (89.364) Prec@5 99.000 (99.364) +2022-11-14 16:52:54,249 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0687) Prec@1 91.000 (89.500) Prec@5 100.000 (99.417) +2022-11-14 16:52:54,257 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0402 (0.0665) Prec@1 94.000 (89.846) Prec@5 100.000 (99.462) +2022-11-14 16:52:54,265 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0666) Prec@1 88.000 (89.714) Prec@5 100.000 (99.500) +2022-11-14 16:52:54,272 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0673) Prec@1 86.000 (89.467) Prec@5 100.000 (99.533) +2022-11-14 16:52:54,280 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0675) Prec@1 88.000 (89.375) Prec@5 99.000 (99.500) +2022-11-14 16:52:54,288 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0667) Prec@1 91.000 (89.471) Prec@5 98.000 (99.412) +2022-11-14 16:52:54,295 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0688) Prec@1 86.000 (89.278) Prec@5 100.000 (99.444) +2022-11-14 16:52:54,303 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0687) Prec@1 88.000 (89.211) Prec@5 99.000 (99.421) +2022-11-14 16:52:54,310 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0697) Prec@1 86.000 (89.050) Prec@5 96.000 (99.250) +2022-11-14 16:52:54,318 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0698) Prec@1 88.000 (89.000) Prec@5 98.000 (99.190) +2022-11-14 16:52:54,325 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0709) Prec@1 85.000 (88.818) Prec@5 99.000 (99.182) +2022-11-14 16:52:54,333 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0723) Prec@1 85.000 (88.652) Prec@5 97.000 (99.087) +2022-11-14 16:52:54,340 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0722) Prec@1 87.000 (88.583) Prec@5 100.000 (99.125) +2022-11-14 16:52:54,348 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0723) Prec@1 89.000 (88.600) Prec@5 100.000 (99.160) +2022-11-14 16:52:54,355 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0727) Prec@1 88.000 (88.577) Prec@5 100.000 (99.192) +2022-11-14 16:52:54,363 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0719) Prec@1 91.000 (88.667) Prec@5 100.000 (99.222) +2022-11-14 16:52:54,370 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0489 (0.0711) Prec@1 91.000 (88.750) Prec@5 100.000 (99.250) +2022-11-14 16:52:54,378 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0714) Prec@1 88.000 (88.724) Prec@5 97.000 (99.172) +2022-11-14 16:52:54,386 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0885 (0.0720) Prec@1 85.000 (88.600) Prec@5 99.000 (99.167) +2022-11-14 16:52:54,394 Test: [30/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0717) Prec@1 89.000 (88.613) Prec@5 99.000 (99.161) +2022-11-14 16:52:54,401 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0674 (0.0715) Prec@1 90.000 (88.656) Prec@5 99.000 (99.156) +2022-11-14 16:52:54,409 Test: [32/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0717) Prec@1 88.000 (88.636) Prec@5 100.000 (99.182) +2022-11-14 16:52:54,417 Test: [33/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0721) Prec@1 85.000 (88.529) Prec@5 100.000 (99.206) +2022-11-14 16:52:54,425 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0706 (0.0720) Prec@1 89.000 (88.543) Prec@5 98.000 (99.171) +2022-11-14 16:52:54,432 Test: [35/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0700 (0.0720) Prec@1 89.000 (88.556) Prec@5 99.000 (99.167) +2022-11-14 16:52:54,440 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0721) Prec@1 87.000 (88.514) Prec@5 98.000 (99.135) +2022-11-14 16:52:54,448 Test: [37/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1087 (0.0730) Prec@1 84.000 (88.395) Prec@5 99.000 (99.132) +2022-11-14 16:52:54,456 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0725) Prec@1 93.000 (88.513) Prec@5 99.000 (99.128) +2022-11-14 16:52:54,465 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0719) Prec@1 92.000 (88.600) Prec@5 100.000 (99.150) +2022-11-14 16:52:54,473 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1020 (0.0727) Prec@1 83.000 (88.463) Prec@5 99.000 (99.146) +2022-11-14 16:52:54,480 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0765 (0.0728) Prec@1 87.000 (88.429) Prec@5 99.000 (99.143) +2022-11-14 16:52:54,488 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0377 (0.0719) Prec@1 95.000 (88.581) Prec@5 100.000 (99.163) +2022-11-14 16:52:54,495 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0646 (0.0718) Prec@1 90.000 (88.614) Prec@5 98.000 (99.136) +2022-11-14 16:52:54,503 Test: [44/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0554 (0.0714) Prec@1 92.000 (88.689) Prec@5 99.000 (99.133) +2022-11-14 16:52:54,511 Test: [45/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1029 (0.0721) Prec@1 85.000 (88.609) Prec@5 98.000 (99.109) +2022-11-14 16:52:54,519 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0719) Prec@1 90.000 (88.638) Prec@5 100.000 (99.128) +2022-11-14 16:52:54,526 Test: [47/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0941 (0.0724) Prec@1 83.000 (88.521) Prec@5 99.000 (99.125) +2022-11-14 16:52:54,534 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0395 (0.0717) Prec@1 91.000 (88.571) Prec@5 100.000 (99.143) +2022-11-14 16:52:54,541 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1000 (0.0723) Prec@1 84.000 (88.480) Prec@5 98.000 (99.120) +2022-11-14 16:52:54,549 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0582 (0.0720) Prec@1 89.000 (88.490) Prec@5 99.000 (99.118) +2022-11-14 16:52:54,556 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0684 (0.0719) Prec@1 88.000 (88.481) Prec@5 99.000 (99.115) +2022-11-14 16:52:54,564 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0505 (0.0715) Prec@1 93.000 (88.566) Prec@5 100.000 (99.132) +2022-11-14 16:52:54,572 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0712) Prec@1 91.000 (88.611) Prec@5 100.000 (99.148) +2022-11-14 16:52:54,580 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0713) Prec@1 88.000 (88.600) Prec@5 99.000 (99.145) +2022-11-14 16:52:54,587 Test: [55/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0768 (0.0714) Prec@1 88.000 (88.589) Prec@5 99.000 (99.143) +2022-11-14 16:52:54,595 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0646 (0.0712) Prec@1 91.000 (88.632) Prec@5 100.000 (99.158) +2022-11-14 16:52:54,602 Test: [57/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0540 (0.0709) Prec@1 93.000 (88.707) Prec@5 99.000 (99.155) +2022-11-14 16:52:54,610 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0959 (0.0714) Prec@1 84.000 (88.627) Prec@5 99.000 (99.153) +2022-11-14 16:52:54,618 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0713) Prec@1 87.000 (88.600) Prec@5 100.000 (99.167) +2022-11-14 16:52:54,625 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0763 (0.0714) Prec@1 89.000 (88.607) Prec@5 99.000 (99.164) +2022-11-14 16:52:54,633 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0586 (0.0712) Prec@1 91.000 (88.645) Prec@5 98.000 (99.145) +2022-11-14 16:52:54,641 Test: [62/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0455 (0.0708) Prec@1 94.000 (88.730) Prec@5 98.000 (99.127) +2022-11-14 16:52:54,648 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0541 (0.0705) Prec@1 92.000 (88.781) Prec@5 100.000 (99.141) +2022-11-14 16:52:54,656 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0911 (0.0708) Prec@1 87.000 (88.754) Prec@5 100.000 (99.154) +2022-11-14 16:52:54,663 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0653 (0.0708) Prec@1 90.000 (88.773) Prec@5 99.000 (99.152) +2022-11-14 16:52:54,671 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0452 (0.0704) Prec@1 92.000 (88.821) Prec@5 100.000 (99.164) +2022-11-14 16:52:54,678 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0703) Prec@1 91.000 (88.853) Prec@5 100.000 (99.176) +2022-11-14 16:52:54,686 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0553 (0.0701) Prec@1 91.000 (88.884) Prec@5 99.000 (99.174) +2022-11-14 16:52:54,693 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0703) Prec@1 87.000 (88.857) Prec@5 98.000 (99.157) +2022-11-14 16:52:54,701 Test: [70/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0857 (0.0705) Prec@1 87.000 (88.831) Prec@5 99.000 (99.155) +2022-11-14 16:52:54,709 Test: [71/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0742 (0.0705) Prec@1 89.000 (88.833) Prec@5 99.000 (99.153) +2022-11-14 16:52:54,716 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0528 (0.0703) Prec@1 91.000 (88.863) Prec@5 100.000 (99.164) +2022-11-14 16:52:54,724 Test: [73/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0701) Prec@1 90.000 (88.878) Prec@5 100.000 (99.176) +2022-11-14 16:52:54,732 Test: [74/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0926 (0.0704) Prec@1 83.000 (88.800) Prec@5 100.000 (99.187) +2022-11-14 16:52:54,739 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0534 (0.0701) Prec@1 92.000 (88.842) Prec@5 99.000 (99.184) +2022-11-14 16:52:54,747 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0711 (0.0701) Prec@1 91.000 (88.870) Prec@5 100.000 (99.195) +2022-11-14 16:52:54,755 Test: [77/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0890 (0.0704) Prec@1 86.000 (88.833) Prec@5 99.000 (99.192) +2022-11-14 16:52:54,762 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0703) Prec@1 89.000 (88.835) Prec@5 100.000 (99.203) +2022-11-14 16:52:54,770 Test: 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0.0906 (0.0715) Prec@1 86.000 (88.663) Prec@5 99.000 (99.209) +2022-11-14 16:52:54,824 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0714) Prec@1 91.000 (88.690) Prec@5 100.000 (99.218) +2022-11-14 16:52:54,831 Test: [87/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0715) Prec@1 88.000 (88.682) Prec@5 99.000 (99.216) +2022-11-14 16:52:54,839 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0667 (0.0714) Prec@1 90.000 (88.697) Prec@5 100.000 (99.225) +2022-11-14 16:52:54,847 Test: [89/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0621 (0.0713) Prec@1 91.000 (88.722) Prec@5 100.000 (99.233) +2022-11-14 16:52:54,854 Test: [90/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0646 (0.0713) Prec@1 88.000 (88.714) Prec@5 100.000 (99.242) +2022-11-14 16:52:54,862 Test: [91/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0426 (0.0709) Prec@1 93.000 (88.761) Prec@5 99.000 (99.239) +2022-11-14 16:52:54,870 Test: [92/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0684 (0.0709) Prec@1 88.000 (88.753) Prec@5 99.000 (99.237) +2022-11-14 16:52:54,877 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0708 (0.0709) Prec@1 89.000 (88.755) Prec@5 98.000 (99.223) +2022-11-14 16:52:54,885 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0710) Prec@1 86.000 (88.726) Prec@5 100.000 (99.232) +2022-11-14 16:52:54,892 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0710) Prec@1 90.000 (88.740) Prec@5 98.000 (99.219) +2022-11-14 16:52:54,900 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0503 (0.0708) Prec@1 91.000 (88.763) Prec@5 99.000 (99.216) +2022-11-14 16:52:54,907 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0709) Prec@1 88.000 (88.755) Prec@5 99.000 (99.214) +2022-11-14 16:52:54,915 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0869 (0.0711) Prec@1 86.000 (88.727) Prec@5 99.000 (99.212) +2022-11-14 16:52:54,922 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0710) Prec@1 89.000 (88.730) Prec@5 99.000 (99.210) +2022-11-14 16:52:54,976 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar +2022-11-14 16:52:55,286 Epoch: [406][0/500] Time 0.021 (0.021) Data 0.234 (0.234) Loss 0.0336 (0.0336) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:55,479 Epoch: [406][10/500] Time 0.017 (0.017) Data 0.001 (0.023) Loss 0.0354 (0.0345) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:55,664 Epoch: [406][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0169 (0.0286) Prec@1 97.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:52:55,852 Epoch: [406][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0285 (0.0286) Prec@1 95.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:52:56,040 Epoch: [406][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0285 (0.0286) Prec@1 95.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 16:52:56,229 Epoch: [406][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0224 (0.0275) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:52:56,415 Epoch: [406][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0250 (0.0272) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:56,604 Epoch: [406][70/500] Time 0.015 (0.017) Data 0.002 (0.005) Loss 0.0199 (0.0263) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:52:56,794 Epoch: [406][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0218 (0.0258) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:52:57,035 Epoch: [406][90/500] Time 0.023 (0.017) Data 0.002 (0.004) Loss 0.0346 (0.0267) Prec@1 93.000 (95.100) Prec@5 100.000 (100.000) +2022-11-14 16:52:57,296 Epoch: [406][100/500] Time 0.025 (0.018) Data 0.001 (0.004) Loss 0.0381 (0.0277) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:52:57,558 Epoch: [406][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0149 (0.0266) Prec@1 98.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:52:57,820 Epoch: [406][120/500] Time 0.021 (0.019) Data 0.002 (0.004) Loss 0.0344 (0.0272) Prec@1 94.000 (95.154) Prec@5 100.000 (100.000) +2022-11-14 16:52:58,078 Epoch: [406][130/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0379 (0.0280) Prec@1 94.000 (95.071) Prec@5 100.000 (100.000) +2022-11-14 16:52:58,338 Epoch: [406][140/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0464 (0.0292) Prec@1 92.000 (94.867) Prec@5 100.000 (100.000) +2022-11-14 16:52:58,601 Epoch: [406][150/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0264 (0.0290) Prec@1 95.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 16:52:58,869 Epoch: [406][160/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0226 (0.0287) Prec@1 96.000 (94.941) Prec@5 100.000 (100.000) +2022-11-14 16:52:59,135 Epoch: [406][170/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0192 (0.0281) Prec@1 98.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:52:59,399 Epoch: [406][180/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0319 (0.0283) Prec@1 95.000 (95.105) Prec@5 100.000 (100.000) +2022-11-14 16:52:59,664 Epoch: [406][190/500] Time 0.023 (0.020) Data 0.003 (0.003) Loss 0.0463 (0.0292) Prec@1 93.000 (95.000) Prec@5 99.000 (99.950) +2022-11-14 16:52:59,922 Epoch: [406][200/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0286 (0.0292) Prec@1 97.000 (95.095) Prec@5 99.000 (99.905) +2022-11-14 16:53:00,181 Epoch: [406][210/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0175 (0.0287) Prec@1 97.000 (95.182) Prec@5 99.000 (99.864) +2022-11-14 16:53:00,441 Epoch: [406][220/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0337 (0.0289) Prec@1 94.000 (95.130) Prec@5 100.000 (99.870) +2022-11-14 16:53:00,692 Epoch: [406][230/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0516 (0.0298) Prec@1 89.000 (94.875) Prec@5 99.000 (99.833) +2022-11-14 16:53:00,948 Epoch: [406][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0374 (0.0301) Prec@1 94.000 (94.840) Prec@5 100.000 (99.840) +2022-11-14 16:53:01,207 Epoch: [406][250/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0288 (0.0301) Prec@1 97.000 (94.923) Prec@5 100.000 (99.846) +2022-11-14 16:53:01,461 Epoch: [406][260/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0145 (0.0295) Prec@1 97.000 (95.000) Prec@5 100.000 (99.852) +2022-11-14 16:53:01,715 Epoch: [406][270/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0252 (0.0294) Prec@1 96.000 (95.036) Prec@5 99.000 (99.821) +2022-11-14 16:53:01,969 Epoch: [406][280/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0356 (0.0296) Prec@1 94.000 (95.000) Prec@5 100.000 (99.828) +2022-11-14 16:53:02,223 Epoch: [406][290/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0309 (0.0296) Prec@1 94.000 (94.967) Prec@5 100.000 (99.833) +2022-11-14 16:53:02,477 Epoch: [406][300/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0307 (0.0296) Prec@1 95.000 (94.968) Prec@5 99.000 (99.806) +2022-11-14 16:53:02,732 Epoch: [406][310/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0311 (0.0297) Prec@1 95.000 (94.969) Prec@5 100.000 (99.812) +2022-11-14 16:53:02,988 Epoch: [406][320/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0620 (0.0307) Prec@1 90.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:53:03,243 Epoch: [406][330/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0289 (0.0306) Prec@1 95.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 16:53:03,497 Epoch: [406][340/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0181 (0.0303) Prec@1 98.000 (94.914) Prec@5 100.000 (99.829) +2022-11-14 16:53:03,752 Epoch: [406][350/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0427 (0.0306) Prec@1 92.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 16:53:04,008 Epoch: [406][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0244 (0.0304) Prec@1 95.000 (94.838) Prec@5 100.000 (99.838) +2022-11-14 16:53:04,262 Epoch: [406][370/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0393 (0.0307) Prec@1 93.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 16:53:04,524 Epoch: [406][380/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0430 (0.0310) Prec@1 91.000 (94.692) Prec@5 100.000 (99.846) +2022-11-14 16:53:04,782 Epoch: [406][390/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0181 (0.0307) Prec@1 97.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 16:53:05,037 Epoch: [406][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0168 (0.0303) Prec@1 97.000 (94.805) Prec@5 100.000 (99.854) +2022-11-14 16:53:05,295 Epoch: [406][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0348 (0.0304) Prec@1 95.000 (94.810) Prec@5 100.000 (99.857) +2022-11-14 16:53:05,549 Epoch: [406][420/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0211 (0.0302) Prec@1 96.000 (94.837) Prec@5 100.000 (99.860) +2022-11-14 16:53:05,806 Epoch: [406][430/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0117 (0.0298) Prec@1 98.000 (94.909) Prec@5 100.000 (99.864) +2022-11-14 16:53:06,065 Epoch: [406][440/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0268 (0.0297) Prec@1 94.000 (94.889) Prec@5 100.000 (99.867) +2022-11-14 16:53:06,323 Epoch: [406][450/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0331 (0.0298) Prec@1 94.000 (94.870) Prec@5 100.000 (99.870) +2022-11-14 16:53:06,579 Epoch: [406][460/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0299 (0.0298) Prec@1 97.000 (94.915) Prec@5 100.000 (99.872) +2022-11-14 16:53:06,835 Epoch: [406][470/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0311 (0.0298) Prec@1 96.000 (94.938) Prec@5 99.000 (99.854) +2022-11-14 16:53:07,095 Epoch: [406][480/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0305 (0.0299) Prec@1 93.000 (94.898) Prec@5 100.000 (99.857) +2022-11-14 16:53:07,347 Epoch: [406][490/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0278 (0.0298) Prec@1 96.000 (94.920) Prec@5 100.000 (99.860) +2022-11-14 16:53:07,577 Epoch: [406][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0277 (0.0298) Prec@1 95.000 (94.922) Prec@5 100.000 (99.863) +2022-11-14 16:53:07,880 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0678 (0.0678) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:07,888 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0699 (0.0689) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:07,895 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0646) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:07,905 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0676) Prec@1 88.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 16:53:07,912 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0666) Prec@1 88.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 16:53:07,919 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0627) Prec@1 92.000 (89.667) Prec@5 100.000 (99.833) +2022-11-14 16:53:07,926 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0633) Prec@1 90.000 (89.714) Prec@5 98.000 (99.571) +2022-11-14 16:53:07,935 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0641) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:53:07,942 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0662) Prec@1 88.000 (89.333) Prec@5 100.000 (99.556) +2022-11-14 16:53:07,949 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0671) Prec@1 88.000 (89.200) Prec@5 99.000 (99.500) +2022-11-14 16:53:07,957 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0660) Prec@1 93.000 (89.545) Prec@5 100.000 (99.545) +2022-11-14 16:53:07,965 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1136 (0.0700) Prec@1 83.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:53:07,973 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0682) Prec@1 91.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 16:53:07,981 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0675) Prec@1 91.000 (89.286) Prec@5 99.000 (99.500) +2022-11-14 16:53:07,989 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0685) Prec@1 87.000 (89.133) Prec@5 100.000 (99.533) +2022-11-14 16:53:07,997 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0688) Prec@1 88.000 (89.062) Prec@5 99.000 (99.500) +2022-11-14 16:53:08,005 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0678) Prec@1 91.000 (89.176) Prec@5 98.000 (99.412) +2022-11-14 16:53:08,013 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0701) Prec@1 82.000 (88.778) Prec@5 100.000 (99.444) +2022-11-14 16:53:08,021 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0708) Prec@1 86.000 (88.632) Prec@5 98.000 (99.368) +2022-11-14 16:53:08,029 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0723) Prec@1 81.000 (88.250) Prec@5 99.000 (99.350) +2022-11-14 16:53:08,037 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0727) Prec@1 86.000 (88.143) Prec@5 100.000 (99.381) +2022-11-14 16:53:08,045 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0736) Prec@1 85.000 (88.000) Prec@5 100.000 (99.409) +2022-11-14 16:53:08,053 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0745) Prec@1 86.000 (87.913) Prec@5 99.000 (99.391) +2022-11-14 16:53:08,061 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0749) Prec@1 87.000 (87.875) Prec@5 100.000 (99.417) +2022-11-14 16:53:08,069 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0753) Prec@1 87.000 (87.840) Prec@5 100.000 (99.440) +2022-11-14 16:53:08,077 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0761) Prec@1 81.000 (87.577) Prec@5 99.000 (99.423) +2022-11-14 16:53:08,085 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0756) Prec@1 90.000 (87.667) Prec@5 100.000 (99.444) +2022-11-14 16:53:08,093 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0748) Prec@1 90.000 (87.750) Prec@5 100.000 (99.464) +2022-11-14 16:53:08,101 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0742) Prec@1 90.000 (87.828) Prec@5 99.000 (99.448) +2022-11-14 16:53:08,109 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0741) Prec@1 89.000 (87.867) Prec@5 100.000 (99.467) +2022-11-14 16:53:08,117 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0738) Prec@1 90.000 (87.935) Prec@5 100.000 (99.484) +2022-11-14 16:53:08,125 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0735) Prec@1 88.000 (87.938) Prec@5 99.000 (99.469) +2022-11-14 16:53:08,133 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0740) Prec@1 85.000 (87.848) Prec@5 99.000 (99.455) +2022-11-14 16:53:08,141 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0736) Prec@1 87.000 (87.824) Prec@5 99.000 (99.441) +2022-11-14 16:53:08,149 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0737) Prec@1 88.000 (87.829) Prec@5 98.000 (99.400) +2022-11-14 16:53:08,157 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0740) Prec@1 88.000 (87.833) Prec@5 99.000 (99.389) +2022-11-14 16:53:08,165 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0744) Prec@1 87.000 (87.811) Prec@5 99.000 (99.378) +2022-11-14 16:53:08,173 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0752) Prec@1 85.000 (87.737) Prec@5 99.000 (99.368) +2022-11-14 16:53:08,181 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0748) Prec@1 92.000 (87.846) Prec@5 99.000 (99.359) +2022-11-14 16:53:08,188 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0751) Prec@1 86.000 (87.800) Prec@5 98.000 (99.325) +2022-11-14 16:53:08,196 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0755) Prec@1 85.000 (87.732) Prec@5 99.000 (99.317) +2022-11-14 16:53:08,204 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0754) Prec@1 88.000 (87.738) Prec@5 99.000 (99.310) +2022-11-14 16:53:08,212 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0471 (0.0747) Prec@1 93.000 (87.860) Prec@5 100.000 (99.326) +2022-11-14 16:53:08,220 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0746) Prec@1 91.000 (87.932) Prec@5 98.000 (99.295) +2022-11-14 16:53:08,229 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0742) Prec@1 90.000 (87.978) Prec@5 98.000 (99.267) +2022-11-14 16:53:08,237 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1172 (0.0751) Prec@1 79.000 (87.783) Prec@5 99.000 (99.261) +2022-11-14 16:53:08,245 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0750) Prec@1 87.000 (87.766) Prec@5 100.000 (99.277) +2022-11-14 16:53:08,253 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.0757) Prec@1 86.000 (87.729) Prec@5 98.000 (99.250) +2022-11-14 16:53:08,261 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0334 (0.0748) Prec@1 96.000 (87.898) Prec@5 100.000 (99.265) +2022-11-14 16:53:08,269 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0752) Prec@1 87.000 (87.880) Prec@5 99.000 (99.260) +2022-11-14 16:53:08,277 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0747) Prec@1 92.000 (87.961) Prec@5 100.000 (99.275) +2022-11-14 16:53:08,285 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0744) Prec@1 90.000 (88.000) Prec@5 99.000 (99.269) +2022-11-14 16:53:08,293 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0744) Prec@1 90.000 (88.038) Prec@5 100.000 (99.283) +2022-11-14 16:53:08,301 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0740) Prec@1 91.000 (88.093) Prec@5 100.000 (99.296) +2022-11-14 16:53:08,309 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0740) Prec@1 88.000 (88.091) Prec@5 100.000 (99.309) +2022-11-14 16:53:08,317 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0738) Prec@1 91.000 (88.143) Prec@5 99.000 (99.304) +2022-11-14 16:53:08,325 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0737) Prec@1 88.000 (88.140) Prec@5 100.000 (99.316) +2022-11-14 16:53:08,332 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0739) Prec@1 87.000 (88.121) Prec@5 100.000 (99.328) +2022-11-14 16:53:08,340 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0742) Prec@1 84.000 (88.051) Prec@5 100.000 (99.339) +2022-11-14 16:53:08,348 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0742) Prec@1 86.000 (88.017) Prec@5 100.000 (99.350) +2022-11-14 16:53:08,356 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0742) Prec@1 88.000 (88.016) Prec@5 100.000 (99.361) +2022-11-14 16:53:08,363 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0743) Prec@1 88.000 (88.016) Prec@5 100.000 (99.371) +2022-11-14 16:53:08,371 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0744) Prec@1 86.000 (87.984) Prec@5 99.000 (99.365) +2022-11-14 16:53:08,378 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0738) Prec@1 94.000 (88.078) Prec@5 100.000 (99.375) +2022-11-14 16:53:08,385 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0741) Prec@1 84.000 (88.015) Prec@5 99.000 (99.369) +2022-11-14 16:53:08,393 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0741) Prec@1 87.000 (88.000) Prec@5 99.000 (99.364) +2022-11-14 16:53:08,401 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0435 (0.0736) Prec@1 94.000 (88.090) Prec@5 99.000 (99.358) +2022-11-14 16:53:08,408 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0735) Prec@1 90.000 (88.118) Prec@5 100.000 (99.368) +2022-11-14 16:53:08,416 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0731) Prec@1 92.000 (88.174) Prec@5 99.000 (99.362) +2022-11-14 16:53:08,423 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0731) Prec@1 85.000 (88.129) Prec@5 100.000 (99.371) +2022-11-14 16:53:08,431 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1010 (0.0735) Prec@1 85.000 (88.085) Prec@5 97.000 (99.338) +2022-11-14 16:53:08,439 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0732) Prec@1 92.000 (88.139) Prec@5 100.000 (99.347) +2022-11-14 16:53:08,446 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0732) Prec@1 88.000 (88.137) Prec@5 100.000 (99.356) +2022-11-14 16:53:08,454 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0519 (0.0729) Prec@1 91.000 (88.176) Prec@5 99.000 (99.351) +2022-11-14 16:53:08,462 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0731) Prec@1 84.000 (88.120) Prec@5 100.000 (99.360) +2022-11-14 16:53:08,469 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0728) Prec@1 91.000 (88.158) Prec@5 100.000 (99.368) +2022-11-14 16:53:08,477 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0728) Prec@1 89.000 (88.169) Prec@5 100.000 (99.377) +2022-11-14 16:53:08,485 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0729) Prec@1 88.000 (88.167) Prec@5 99.000 (99.372) +2022-11-14 16:53:08,493 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0731) Prec@1 85.000 (88.127) Prec@5 99.000 (99.367) +2022-11-14 16:53:08,501 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0734) Prec@1 84.000 (88.075) Prec@5 100.000 (99.375) +2022-11-14 16:53:08,509 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0737) Prec@1 86.000 (88.049) Prec@5 98.000 (99.358) +2022-11-14 16:53:08,517 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0739) Prec@1 82.000 (87.976) Prec@5 100.000 (99.366) +2022-11-14 16:53:08,524 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0738) Prec@1 89.000 (87.988) Prec@5 100.000 (99.373) +2022-11-14 16:53:08,532 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0737) Prec@1 89.000 (88.000) Prec@5 100.000 (99.381) +2022-11-14 16:53:08,540 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0740) Prec@1 86.000 (87.976) Prec@5 99.000 (99.376) +2022-11-14 16:53:08,548 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.0744) Prec@1 83.000 (87.919) Prec@5 100.000 (99.384) +2022-11-14 16:53:08,556 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0746) Prec@1 86.000 (87.897) Prec@5 100.000 (99.391) +2022-11-14 16:53:08,564 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0747) Prec@1 89.000 (87.909) Prec@5 98.000 (99.375) +2022-11-14 16:53:08,572 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0744) Prec@1 93.000 (87.966) Prec@5 100.000 (99.382) +2022-11-14 16:53:08,579 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0743) Prec@1 90.000 (87.989) Prec@5 99.000 (99.378) +2022-11-14 16:53:08,587 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0742) Prec@1 91.000 (88.022) Prec@5 100.000 (99.385) +2022-11-14 16:53:08,595 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0740) Prec@1 91.000 (88.054) Prec@5 100.000 (99.391) +2022-11-14 16:53:08,603 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0742) Prec@1 84.000 (88.011) Prec@5 99.000 (99.387) +2022-11-14 16:53:08,612 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0743) Prec@1 88.000 (88.011) Prec@5 99.000 (99.383) +2022-11-14 16:53:08,620 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0745) Prec@1 85.000 (87.979) Prec@5 100.000 (99.389) +2022-11-14 16:53:08,627 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0743) Prec@1 92.000 (88.021) Prec@5 98.000 (99.375) +2022-11-14 16:53:08,635 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0431 (0.0740) Prec@1 93.000 (88.072) Prec@5 99.000 (99.371) +2022-11-14 16:53:08,643 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0743) Prec@1 84.000 (88.031) Prec@5 100.000 (99.378) +2022-11-14 16:53:08,650 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0745) Prec@1 85.000 (88.000) Prec@5 99.000 (99.374) +2022-11-14 16:53:08,658 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0746) Prec@1 89.000 (88.010) Prec@5 100.000 (99.380) +2022-11-14 16:53:08,722 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:53:09,072 Epoch: [407][0/500] Time 0.028 (0.028) Data 0.253 (0.253) Loss 0.0285 (0.0285) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:09,270 Epoch: [407][10/500] Time 0.016 (0.018) Data 0.002 (0.024) Loss 0.0536 (0.0410) Prec@1 90.000 (93.000) Prec@5 99.000 (99.500) +2022-11-14 16:53:09,459 Epoch: [407][20/500] Time 0.015 (0.018) Data 0.002 (0.014) Loss 0.0223 (0.0348) Prec@1 97.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 16:53:09,650 Epoch: [407][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0257 (0.0325) Prec@1 96.000 (94.750) Prec@5 99.000 (99.500) +2022-11-14 16:53:09,841 Epoch: [407][40/500] Time 0.015 (0.017) Data 0.002 (0.008) Loss 0.0404 (0.0341) Prec@1 93.000 (94.400) Prec@5 100.000 (99.600) +2022-11-14 16:53:10,115 Epoch: [407][50/500] Time 0.035 (0.019) Data 0.002 (0.006) Loss 0.0404 (0.0351) Prec@1 92.000 (94.000) Prec@5 100.000 (99.667) +2022-11-14 16:53:10,440 Epoch: [407][60/500] Time 0.033 (0.020) Data 0.002 (0.006) Loss 0.0282 (0.0341) Prec@1 94.000 (94.000) Prec@5 100.000 (99.714) +2022-11-14 16:53:10,770 Epoch: [407][70/500] Time 0.031 (0.021) Data 0.002 (0.005) Loss 0.0381 (0.0346) Prec@1 94.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:53:11,098 Epoch: [407][80/500] Time 0.031 (0.022) Data 0.002 (0.005) Loss 0.0278 (0.0339) Prec@1 95.000 (94.111) Prec@5 100.000 (99.778) +2022-11-14 16:53:11,421 Epoch: [407][90/500] Time 0.030 (0.023) Data 0.003 (0.004) Loss 0.0245 (0.0330) Prec@1 96.000 (94.300) Prec@5 100.000 (99.800) +2022-11-14 16:53:11,740 Epoch: [407][100/500] Time 0.031 (0.024) Data 0.002 (0.004) Loss 0.0250 (0.0322) Prec@1 97.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 16:53:12,062 Epoch: [407][110/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0203 (0.0312) Prec@1 96.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:53:12,383 Epoch: [407][120/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0298 (0.0311) Prec@1 97.000 (94.846) Prec@5 100.000 (99.846) +2022-11-14 16:53:12,707 Epoch: [407][130/500] Time 0.029 (0.025) Data 0.002 (0.004) Loss 0.0362 (0.0315) Prec@1 94.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 16:53:13,028 Epoch: [407][140/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0360 (0.0318) Prec@1 95.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 16:53:13,348 Epoch: [407][150/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.0301 (0.0317) Prec@1 96.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 16:53:13,674 Epoch: [407][160/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0169 (0.0308) Prec@1 97.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 16:53:13,994 Epoch: [407][170/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0560 (0.0322) Prec@1 90.000 (94.722) Prec@5 100.000 (99.889) +2022-11-14 16:53:14,320 Epoch: [407][180/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0332 (0.0323) Prec@1 94.000 (94.684) Prec@5 100.000 (99.895) +2022-11-14 16:53:14,639 Epoch: [407][190/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.0340 (0.0324) Prec@1 94.000 (94.650) Prec@5 99.000 (99.850) +2022-11-14 16:53:14,958 Epoch: [407][200/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0340 (0.0324) Prec@1 93.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:53:15,272 Epoch: [407][210/500] Time 0.029 (0.026) Data 0.001 (0.003) Loss 0.0265 (0.0322) Prec@1 97.000 (94.682) Prec@5 100.000 (99.864) +2022-11-14 16:53:15,593 Epoch: [407][220/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0339 (0.0322) Prec@1 93.000 (94.609) Prec@5 100.000 (99.870) +2022-11-14 16:53:15,912 Epoch: [407][230/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0384 (0.0325) Prec@1 95.000 (94.625) Prec@5 99.000 (99.833) +2022-11-14 16:53:16,234 Epoch: [407][240/500] Time 0.032 (0.026) Data 0.001 (0.003) Loss 0.0291 (0.0324) Prec@1 96.000 (94.680) Prec@5 100.000 (99.840) +2022-11-14 16:53:16,552 Epoch: [407][250/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0163 (0.0317) Prec@1 98.000 (94.808) Prec@5 100.000 (99.846) +2022-11-14 16:53:16,870 Epoch: [407][260/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0142 (0.0311) Prec@1 97.000 (94.889) Prec@5 100.000 (99.852) +2022-11-14 16:53:17,188 Epoch: [407][270/500] Time 0.028 (0.027) Data 0.001 (0.003) Loss 0.0413 (0.0315) Prec@1 94.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:53:17,505 Epoch: [407][280/500] Time 0.030 (0.027) Data 0.002 (0.003) Loss 0.0315 (0.0315) Prec@1 95.000 (94.862) Prec@5 100.000 (99.862) +2022-11-14 16:53:17,821 Epoch: [407][290/500] Time 0.029 (0.027) Data 0.001 (0.003) Loss 0.0241 (0.0312) Prec@1 97.000 (94.933) Prec@5 100.000 (99.867) +2022-11-14 16:53:18,142 Epoch: [407][300/500] Time 0.035 (0.027) Data 0.002 (0.003) Loss 0.0370 (0.0314) Prec@1 93.000 (94.871) Prec@5 100.000 (99.871) +2022-11-14 16:53:18,451 Epoch: [407][310/500] Time 0.032 (0.027) Data 0.002 (0.003) Loss 0.0366 (0.0316) Prec@1 93.000 (94.812) Prec@5 100.000 (99.875) +2022-11-14 16:53:18,767 Epoch: [407][320/500] Time 0.028 (0.027) Data 0.002 (0.002) Loss 0.0558 (0.0323) Prec@1 91.000 (94.697) Prec@5 100.000 (99.879) +2022-11-14 16:53:19,088 Epoch: [407][330/500] Time 0.033 (0.027) Data 0.002 (0.002) Loss 0.0285 (0.0322) Prec@1 96.000 (94.735) Prec@5 100.000 (99.882) +2022-11-14 16:53:19,404 Epoch: [407][340/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0440 (0.0325) Prec@1 93.000 (94.686) Prec@5 100.000 (99.886) +2022-11-14 16:53:19,721 Epoch: [407][350/500] Time 0.033 (0.027) Data 0.002 (0.002) Loss 0.0084 (0.0318) Prec@1 99.000 (94.806) Prec@5 100.000 (99.889) +2022-11-14 16:53:20,036 Epoch: [407][360/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0193 (0.0315) Prec@1 97.000 (94.865) Prec@5 100.000 (99.892) +2022-11-14 16:53:20,350 Epoch: [407][370/500] Time 0.032 (0.027) Data 0.002 (0.002) Loss 0.0350 (0.0316) Prec@1 95.000 (94.868) Prec@5 100.000 (99.895) +2022-11-14 16:53:20,664 Epoch: [407][380/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0222 (0.0314) Prec@1 97.000 (94.923) Prec@5 100.000 (99.897) +2022-11-14 16:53:20,985 Epoch: [407][390/500] Time 0.032 (0.027) Data 0.002 (0.002) Loss 0.0439 (0.0317) Prec@1 91.000 (94.825) Prec@5 100.000 (99.900) +2022-11-14 16:53:21,304 Epoch: [407][400/500] Time 0.031 (0.027) Data 0.001 (0.002) Loss 0.0230 (0.0315) Prec@1 97.000 (94.878) Prec@5 100.000 (99.902) +2022-11-14 16:53:21,620 Epoch: [407][410/500] Time 0.032 (0.027) Data 0.002 (0.002) Loss 0.0349 (0.0315) Prec@1 92.000 (94.810) Prec@5 100.000 (99.905) +2022-11-14 16:53:21,939 Epoch: [407][420/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0326 (0.0316) Prec@1 95.000 (94.814) Prec@5 100.000 (99.907) +2022-11-14 16:53:22,259 Epoch: [407][430/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.0272 (0.0315) Prec@1 95.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:53:22,580 Epoch: [407][440/500] Time 0.031 (0.027) Data 0.002 (0.002) Loss 0.0392 (0.0316) Prec@1 93.000 (94.778) Prec@5 99.000 (99.889) +2022-11-14 16:53:22,901 Epoch: [407][450/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0286 (0.0316) Prec@1 94.000 (94.761) Prec@5 100.000 (99.891) +2022-11-14 16:53:23,222 Epoch: [407][460/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0387 (0.0317) Prec@1 94.000 (94.745) Prec@5 100.000 (99.894) +2022-11-14 16:53:23,536 Epoch: [407][470/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0345 (0.0318) Prec@1 95.000 (94.750) Prec@5 100.000 (99.896) +2022-11-14 16:53:23,850 Epoch: [407][480/500] Time 0.030 (0.027) Data 0.002 (0.002) Loss 0.0298 (0.0317) Prec@1 96.000 (94.776) Prec@5 100.000 (99.898) +2022-11-14 16:53:24,168 Epoch: [407][490/500] Time 0.029 (0.027) Data 0.002 (0.002) Loss 0.0505 (0.0321) Prec@1 92.000 (94.720) Prec@5 100.000 (99.900) +2022-11-14 16:53:24,446 Epoch: [407][499/500] Time 0.027 (0.027) Data 0.002 (0.002) Loss 0.0345 (0.0322) Prec@1 95.000 (94.725) Prec@5 100.000 (99.902) +2022-11-14 16:53:24,741 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0673 (0.0673) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 16:53:24,749 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0699) Prec@1 88.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 16:53:24,757 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0683) Prec@1 90.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:53:24,767 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0696) Prec@1 87.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 16:53:24,774 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0717) Prec@1 86.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 16:53:24,781 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0693) Prec@1 89.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:53:24,788 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0684) Prec@1 91.000 (88.429) Prec@5 100.000 (99.714) +2022-11-14 16:53:24,796 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0710) Prec@1 86.000 (88.125) Prec@5 100.000 (99.750) +2022-11-14 16:53:24,803 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0722) Prec@1 86.000 (87.889) Prec@5 98.000 (99.556) +2022-11-14 16:53:24,810 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0736) Prec@1 87.000 (87.800) Prec@5 99.000 (99.500) +2022-11-14 16:53:24,817 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0725) Prec@1 91.000 (88.091) Prec@5 100.000 (99.545) +2022-11-14 16:53:24,825 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0720) Prec@1 89.000 (88.167) Prec@5 100.000 (99.583) +2022-11-14 16:53:24,832 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0715) Prec@1 90.000 (88.308) Prec@5 99.000 (99.538) +2022-11-14 16:53:24,840 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0715) Prec@1 89.000 (88.357) Prec@5 100.000 (99.571) +2022-11-14 16:53:24,847 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0719) Prec@1 87.000 (88.267) Prec@5 100.000 (99.600) +2022-11-14 16:53:24,855 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0724) Prec@1 86.000 (88.125) Prec@5 100.000 (99.625) +2022-11-14 16:53:24,862 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0718) Prec@1 91.000 (88.294) Prec@5 98.000 (99.529) +2022-11-14 16:53:24,870 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0728) Prec@1 87.000 (88.222) Prec@5 100.000 (99.556) +2022-11-14 16:53:24,878 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0735) Prec@1 85.000 (88.053) Prec@5 100.000 (99.579) +2022-11-14 16:53:24,885 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0748) Prec@1 82.000 (87.750) Prec@5 97.000 (99.450) +2022-11-14 16:53:24,893 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0753) Prec@1 85.000 (87.619) Prec@5 100.000 (99.476) +2022-11-14 16:53:24,900 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0752) Prec@1 89.000 (87.682) Prec@5 99.000 (99.455) +2022-11-14 16:53:24,908 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0879 (0.0758) Prec@1 87.000 (87.652) Prec@5 98.000 (99.391) +2022-11-14 16:53:24,916 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0714 (0.0756) Prec@1 88.000 (87.667) Prec@5 100.000 (99.417) +2022-11-14 16:53:24,923 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1277 (0.0777) Prec@1 82.000 (87.440) Prec@5 99.000 (99.400) +2022-11-14 16:53:24,931 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0825 (0.0778) Prec@1 87.000 (87.423) Prec@5 99.000 (99.385) +2022-11-14 16:53:24,938 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0443 (0.0766) Prec@1 90.000 (87.519) Prec@5 100.000 (99.407) +2022-11-14 16:53:24,946 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0515 (0.0757) Prec@1 91.000 (87.643) Prec@5 100.000 (99.429) +2022-11-14 16:53:24,953 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0709 (0.0755) Prec@1 88.000 (87.655) Prec@5 98.000 (99.379) +2022-11-14 16:53:24,961 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0833 (0.0758) Prec@1 87.000 (87.633) Prec@5 99.000 (99.367) +2022-11-14 16:53:24,968 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0543 (0.0751) Prec@1 88.000 (87.645) Prec@5 100.000 (99.387) +2022-11-14 16:53:24,977 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0748) Prec@1 91.000 (87.750) Prec@5 99.000 (99.375) +2022-11-14 16:53:24,984 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0701 (0.0746) Prec@1 88.000 (87.758) Prec@5 100.000 (99.394) +2022-11-14 16:53:24,992 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0784 (0.0747) Prec@1 88.000 (87.765) Prec@5 99.000 (99.382) +2022-11-14 16:53:24,999 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0696 (0.0746) Prec@1 90.000 (87.829) Prec@5 98.000 (99.343) +2022-11-14 16:53:25,007 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0561 (0.0741) Prec@1 91.000 (87.917) Prec@5 100.000 (99.361) +2022-11-14 16:53:25,014 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0517 (0.0735) Prec@1 92.000 (88.027) Prec@5 99.000 (99.351) +2022-11-14 16:53:25,021 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1201 (0.0747) Prec@1 80.000 (87.816) Prec@5 99.000 (99.342) +2022-11-14 16:53:25,029 Test: [38/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0533 (0.0741) Prec@1 93.000 (87.949) Prec@5 99.000 (99.333) +2022-11-14 16:53:25,037 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0709 (0.0741) Prec@1 90.000 (88.000) Prec@5 99.000 (99.325) +2022-11-14 16:53:25,044 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0894 (0.0744) Prec@1 86.000 (87.951) Prec@5 97.000 (99.268) +2022-11-14 16:53:25,051 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0740 (0.0744) Prec@1 87.000 (87.929) Prec@5 100.000 (99.286) +2022-11-14 16:53:25,059 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0441 (0.0737) Prec@1 93.000 (88.047) Prec@5 100.000 (99.302) +2022-11-14 16:53:25,066 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0674 (0.0736) Prec@1 91.000 (88.114) Prec@5 97.000 (99.250) +2022-11-14 16:53:25,074 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0709 (0.0735) Prec@1 87.000 (88.089) Prec@5 100.000 (99.267) +2022-11-14 16:53:25,082 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1480 (0.0751) Prec@1 75.000 (87.804) Prec@5 100.000 (99.283) +2022-11-14 16:53:25,090 Test: [46/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0749) Prec@1 89.000 (87.830) Prec@5 100.000 (99.298) +2022-11-14 16:53:25,098 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1099 (0.0757) Prec@1 84.000 (87.750) Prec@5 98.000 (99.271) +2022-11-14 16:53:25,106 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0555 (0.0753) Prec@1 92.000 (87.837) Prec@5 100.000 (99.286) +2022-11-14 16:53:25,113 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0901 (0.0755) Prec@1 87.000 (87.820) Prec@5 100.000 (99.300) +2022-11-14 16:53:25,121 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0567 (0.0752) Prec@1 92.000 (87.902) Prec@5 100.000 (99.314) +2022-11-14 16:53:25,129 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0755) Prec@1 87.000 (87.885) Prec@5 99.000 (99.308) +2022-11-14 16:53:25,136 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0530 (0.0750) Prec@1 94.000 (88.000) Prec@5 100.000 (99.321) +2022-11-14 16:53:25,144 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0630 (0.0748) Prec@1 89.000 (88.019) Prec@5 100.000 (99.333) +2022-11-14 16:53:25,151 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0842 (0.0750) Prec@1 87.000 (88.000) Prec@5 100.000 (99.345) +2022-11-14 16:53:25,159 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0848 (0.0752) Prec@1 87.000 (87.982) Prec@5 99.000 (99.339) +2022-11-14 16:53:25,166 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0556 (0.0748) Prec@1 89.000 (88.000) Prec@5 100.000 (99.351) +2022-11-14 16:53:25,174 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0748) Prec@1 88.000 (88.000) Prec@5 98.000 (99.328) +2022-11-14 16:53:25,181 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0969 (0.0752) Prec@1 84.000 (87.932) Prec@5 99.000 (99.322) +2022-11-14 16:53:25,189 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0864 (0.0754) Prec@1 85.000 (87.883) Prec@5 100.000 (99.333) +2022-11-14 16:53:25,197 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0822 (0.0755) Prec@1 89.000 (87.902) Prec@5 99.000 (99.328) +2022-11-14 16:53:25,204 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0719 (0.0754) Prec@1 88.000 (87.903) Prec@5 100.000 (99.339) +2022-11-14 16:53:25,211 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0475 (0.0750) Prec@1 91.000 (87.952) Prec@5 100.000 (99.349) +2022-11-14 16:53:25,219 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0402 (0.0744) Prec@1 94.000 (88.047) Prec@5 100.000 (99.359) +2022-11-14 16:53:25,227 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0746) Prec@1 88.000 (88.046) Prec@5 99.000 (99.354) +2022-11-14 16:53:25,234 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0747) Prec@1 85.000 (88.000) Prec@5 99.000 (99.348) +2022-11-14 16:53:25,242 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0454 (0.0743) Prec@1 93.000 (88.075) Prec@5 99.000 (99.343) +2022-11-14 16:53:25,249 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0742) Prec@1 89.000 (88.088) Prec@5 100.000 (99.353) +2022-11-14 16:53:25,256 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0728 (0.0742) Prec@1 89.000 (88.101) Prec@5 100.000 (99.362) +2022-11-14 16:53:25,263 Test: [69/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0621 (0.0740) Prec@1 90.000 (88.129) Prec@5 100.000 (99.371) +2022-11-14 16:53:25,271 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1075 (0.0745) Prec@1 84.000 (88.070) Prec@5 98.000 (99.352) +2022-11-14 16:53:25,279 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0745) Prec@1 88.000 (88.069) Prec@5 100.000 (99.361) +2022-11-14 16:53:25,286 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0570 (0.0743) Prec@1 88.000 (88.068) Prec@5 100.000 (99.370) +2022-11-14 16:53:25,294 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0458 (0.0739) Prec@1 92.000 (88.122) Prec@5 100.000 (99.378) +2022-11-14 16:53:25,301 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1171 (0.0745) Prec@1 82.000 (88.040) Prec@5 100.000 (99.387) +2022-11-14 16:53:25,309 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0498 (0.0741) Prec@1 92.000 (88.092) Prec@5 100.000 (99.395) +2022-11-14 16:53:25,317 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0757 (0.0742) Prec@1 87.000 (88.078) Prec@5 100.000 (99.403) +2022-11-14 16:53:25,324 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0743) Prec@1 87.000 (88.064) Prec@5 98.000 (99.385) +2022-11-14 16:53:25,332 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0568 (0.0741) Prec@1 91.000 (88.101) Prec@5 100.000 (99.392) +2022-11-14 16:53:25,339 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0655 (0.0740) Prec@1 88.000 (88.100) Prec@5 100.000 (99.400) +2022-11-14 16:53:25,347 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0742) Prec@1 85.000 (88.062) Prec@5 98.000 (99.383) +2022-11-14 16:53:25,355 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0742) Prec@1 85.000 (88.024) Prec@5 100.000 (99.390) +2022-11-14 16:53:25,362 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1056 (0.0746) Prec@1 82.000 (87.952) Prec@5 100.000 (99.398) +2022-11-14 16:53:25,370 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0599 (0.0744) Prec@1 90.000 (87.976) Prec@5 100.000 (99.405) +2022-11-14 16:53:25,377 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1014 (0.0747) Prec@1 83.000 (87.918) Prec@5 100.000 (99.412) +2022-11-14 16:53:25,385 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1093 (0.0751) Prec@1 83.000 (87.860) Prec@5 99.000 (99.407) +2022-11-14 16:53:25,393 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0859 (0.0753) Prec@1 86.000 (87.839) Prec@5 100.000 (99.414) +2022-11-14 16:53:25,400 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1055 (0.0756) Prec@1 82.000 (87.773) Prec@5 99.000 (99.409) +2022-11-14 16:53:25,408 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0754) Prec@1 90.000 (87.798) Prec@5 100.000 (99.416) +2022-11-14 16:53:25,416 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0530 (0.0752) Prec@1 92.000 (87.844) Prec@5 100.000 (99.422) +2022-11-14 16:53:25,424 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0501 (0.0749) Prec@1 92.000 (87.890) Prec@5 100.000 (99.429) +2022-11-14 16:53:25,432 Test: [91/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0354 (0.0745) Prec@1 94.000 (87.957) Prec@5 100.000 (99.435) +2022-11-14 16:53:25,439 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0745) Prec@1 88.000 (87.957) Prec@5 99.000 (99.430) +2022-11-14 16:53:25,447 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0818 (0.0746) Prec@1 88.000 (87.957) Prec@5 99.000 (99.426) +2022-11-14 16:53:25,455 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0744 (0.0746) Prec@1 89.000 (87.968) Prec@5 99.000 (99.421) +2022-11-14 16:53:25,462 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0745) Prec@1 92.000 (88.010) Prec@5 99.000 (99.417) +2022-11-14 16:53:25,469 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0453 (0.0742) Prec@1 91.000 (88.041) Prec@5 100.000 (99.423) +2022-11-14 16:53:25,477 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0655 (0.0741) Prec@1 90.000 (88.061) Prec@5 98.000 (99.408) +2022-11-14 16:53:25,484 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1020 (0.0744) Prec@1 86.000 (88.040) Prec@5 99.000 (99.404) +2022-11-14 16:53:25,492 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0744) Prec@1 88.000 (88.040) Prec@5 100.000 (99.410) +2022-11-14 16:53:25,548 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:53:25,854 Epoch: [408][0/500] Time 0.020 (0.020) Data 0.235 (0.235) Loss 0.0269 (0.0269) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:26,046 Epoch: [408][10/500] Time 0.017 (0.017) Data 0.002 (0.023) Loss 0.0301 (0.0285) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:26,256 Epoch: [408][20/500] Time 0.020 (0.018) Data 0.002 (0.013) Loss 0.0309 (0.0293) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:53:26,469 Epoch: [408][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0317 (0.0299) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:53:26,657 Epoch: [408][40/500] Time 0.017 (0.018) Data 0.001 (0.007) Loss 0.0210 (0.0281) Prec@1 97.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:53:26,845 Epoch: [408][50/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0388 (0.0299) Prec@1 91.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,045 Epoch: [408][60/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0186 (0.0283) Prec@1 97.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,244 Epoch: [408][70/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0207 (0.0273) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,429 Epoch: [408][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0261 (0.0272) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,615 Epoch: [408][90/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0256 (0.0270) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,801 Epoch: [408][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0324 (0.0275) Prec@1 93.000 (95.273) Prec@5 100.000 (100.000) +2022-11-14 16:53:27,987 Epoch: [408][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0345 (0.0281) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:53:28,177 Epoch: [408][120/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0280 (0.0281) Prec@1 94.000 (95.154) Prec@5 100.000 (100.000) +2022-11-14 16:53:28,363 Epoch: [408][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0442 (0.0292) Prec@1 91.000 (94.857) Prec@5 100.000 (100.000) +2022-11-14 16:53:28,565 Epoch: [408][140/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0136 (0.0282) Prec@1 98.000 (95.067) Prec@5 100.000 (100.000) +2022-11-14 16:53:28,855 Epoch: [408][150/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0253 (0.0280) Prec@1 96.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 16:53:29,168 Epoch: [408][160/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0200 (0.0276) Prec@1 95.000 (95.118) Prec@5 100.000 (100.000) +2022-11-14 16:53:29,478 Epoch: [408][170/500] Time 0.030 (0.019) Data 0.001 (0.003) Loss 0.0410 (0.0283) Prec@1 91.000 (94.889) Prec@5 100.000 (100.000) +2022-11-14 16:53:29,796 Epoch: [408][180/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0237 (0.0281) Prec@1 95.000 (94.895) Prec@5 100.000 (100.000) +2022-11-14 16:53:30,121 Epoch: [408][190/500] Time 0.035 (0.020) Data 0.002 (0.003) Loss 0.0211 (0.0277) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:30,430 Epoch: [408][200/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0280 (0.0277) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:30,737 Epoch: [408][210/500] Time 0.029 (0.020) Data 0.001 (0.003) Loss 0.0170 (0.0272) Prec@1 97.000 (95.091) Prec@5 100.000 (100.000) +2022-11-14 16:53:31,044 Epoch: [408][220/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0250 (0.0271) Prec@1 97.000 (95.174) Prec@5 100.000 (100.000) +2022-11-14 16:53:31,345 Epoch: [408][230/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0125 (0.0265) Prec@1 98.000 (95.292) Prec@5 100.000 (100.000) +2022-11-14 16:53:31,644 Epoch: [408][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0156 (0.0261) Prec@1 97.000 (95.360) Prec@5 100.000 (100.000) +2022-11-14 16:53:31,942 Epoch: [408][250/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0334 (0.0264) Prec@1 94.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 16:53:32,251 Epoch: [408][260/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0481 (0.0272) Prec@1 94.000 (95.259) Prec@5 98.000 (99.926) +2022-11-14 16:53:32,552 Epoch: [408][270/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0333 (0.0274) Prec@1 93.000 (95.179) Prec@5 100.000 (99.929) +2022-11-14 16:53:32,855 Epoch: [408][280/500] Time 0.029 (0.022) Data 0.001 (0.002) Loss 0.0128 (0.0269) Prec@1 98.000 (95.276) Prec@5 100.000 (99.931) +2022-11-14 16:53:33,161 Epoch: [408][290/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0352 (0.0272) Prec@1 95.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 16:53:33,466 Epoch: [408][300/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0285 (0.0272) Prec@1 94.000 (95.226) Prec@5 100.000 (99.935) +2022-11-14 16:53:33,772 Epoch: [408][310/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0326 (0.0274) Prec@1 94.000 (95.188) Prec@5 100.000 (99.938) +2022-11-14 16:53:34,072 Epoch: [408][320/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0352 (0.0276) Prec@1 92.000 (95.091) Prec@5 100.000 (99.939) +2022-11-14 16:53:34,379 Epoch: [408][330/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0430 (0.0281) Prec@1 93.000 (95.029) Prec@5 100.000 (99.941) +2022-11-14 16:53:34,680 Epoch: [408][340/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0228 (0.0279) Prec@1 98.000 (95.114) Prec@5 100.000 (99.943) +2022-11-14 16:53:34,981 Epoch: [408][350/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0208 (0.0277) Prec@1 96.000 (95.139) Prec@5 100.000 (99.944) +2022-11-14 16:53:35,283 Epoch: [408][360/500] Time 0.029 (0.023) Data 0.001 (0.002) Loss 0.0263 (0.0277) Prec@1 94.000 (95.108) Prec@5 100.000 (99.946) +2022-11-14 16:53:35,583 Epoch: [408][370/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0445 (0.0281) Prec@1 92.000 (95.026) Prec@5 100.000 (99.947) +2022-11-14 16:53:35,881 Epoch: [408][380/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0318 (0.0282) Prec@1 95.000 (95.026) Prec@5 99.000 (99.923) +2022-11-14 16:53:36,184 Epoch: [408][390/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0131 (0.0278) Prec@1 99.000 (95.125) Prec@5 100.000 (99.925) +2022-11-14 16:53:36,483 Epoch: [408][400/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0216 (0.0277) Prec@1 97.000 (95.171) Prec@5 100.000 (99.927) +2022-11-14 16:53:36,782 Epoch: [408][410/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0263 (0.0277) Prec@1 96.000 (95.190) Prec@5 100.000 (99.929) +2022-11-14 16:53:37,084 Epoch: [408][420/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0281 (0.0277) Prec@1 94.000 (95.163) Prec@5 100.000 (99.930) +2022-11-14 16:53:37,382 Epoch: [408][430/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0404 (0.0280) Prec@1 94.000 (95.136) Prec@5 100.000 (99.932) +2022-11-14 16:53:37,681 Epoch: [408][440/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0121 (0.0276) Prec@1 98.000 (95.200) Prec@5 100.000 (99.933) +2022-11-14 16:53:37,982 Epoch: [408][450/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0263 (0.0276) Prec@1 97.000 (95.239) Prec@5 100.000 (99.935) +2022-11-14 16:53:38,281 Epoch: [408][460/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0214 (0.0274) Prec@1 97.000 (95.277) Prec@5 100.000 (99.936) +2022-11-14 16:53:38,581 Epoch: [408][470/500] Time 0.031 (0.024) Data 0.002 (0.002) Loss 0.0380 (0.0277) Prec@1 94.000 (95.250) Prec@5 100.000 (99.938) +2022-11-14 16:53:38,881 Epoch: [408][480/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0327 (0.0278) Prec@1 96.000 (95.265) Prec@5 100.000 (99.939) +2022-11-14 16:53:39,180 Epoch: [408][490/500] Time 0.031 (0.024) Data 0.002 (0.002) Loss 0.0372 (0.0280) Prec@1 94.000 (95.240) Prec@5 100.000 (99.940) +2022-11-14 16:53:39,451 Epoch: [408][499/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0359 (0.0281) Prec@1 95.000 (95.235) Prec@5 100.000 (99.941) +2022-11-14 16:53:39,755 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0694 (0.0694) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:39,762 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0685 (0.0690) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:39,769 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0766) Prec@1 84.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:53:39,780 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0723) Prec@1 91.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 16:53:39,787 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0713) Prec@1 91.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 16:53:39,794 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0329 (0.0649) Prec@1 94.000 (89.833) Prec@5 100.000 (99.500) +2022-11-14 16:53:39,801 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0644) Prec@1 91.000 (90.000) Prec@5 99.000 (99.429) +2022-11-14 16:53:39,810 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0665) Prec@1 88.000 (89.750) Prec@5 99.000 (99.375) +2022-11-14 16:53:39,817 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0677) Prec@1 90.000 (89.778) Prec@5 100.000 (99.444) +2022-11-14 16:53:39,824 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0684) Prec@1 88.000 (89.600) Prec@5 98.000 (99.300) +2022-11-14 16:53:39,831 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0681) Prec@1 90.000 (89.636) Prec@5 100.000 (99.364) +2022-11-14 16:53:39,838 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0694) Prec@1 85.000 (89.250) Prec@5 100.000 (99.417) +2022-11-14 16:53:39,846 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0696) Prec@1 89.000 (89.231) Prec@5 99.000 (99.385) +2022-11-14 16:53:39,854 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0705) Prec@1 88.000 (89.143) Prec@5 98.000 (99.286) +2022-11-14 16:53:39,861 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0716) Prec@1 84.000 (88.800) Prec@5 100.000 (99.333) +2022-11-14 16:53:39,869 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0711) Prec@1 89.000 (88.812) Prec@5 98.000 (99.250) +2022-11-14 16:53:39,877 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0693) Prec@1 95.000 (89.176) Prec@5 98.000 (99.176) +2022-11-14 16:53:39,884 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0711) Prec@1 85.000 (88.944) Prec@5 100.000 (99.222) +2022-11-14 16:53:39,892 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0719) Prec@1 85.000 (88.737) Prec@5 97.000 (99.105) +2022-11-14 16:53:39,900 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0733) Prec@1 87.000 (88.650) Prec@5 98.000 (99.050) +2022-11-14 16:53:39,908 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0735) Prec@1 85.000 (88.476) Prec@5 99.000 (99.048) +2022-11-14 16:53:39,916 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0742) Prec@1 86.000 (88.364) Prec@5 99.000 (99.045) +2022-11-14 16:53:39,923 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0752) Prec@1 87.000 (88.304) Prec@5 99.000 (99.043) +2022-11-14 16:53:39,931 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0752) Prec@1 89.000 (88.333) Prec@5 99.000 (99.042) +2022-11-14 16:53:39,939 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0758) Prec@1 85.000 (88.200) Prec@5 100.000 (99.080) +2022-11-14 16:53:39,946 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0760) Prec@1 87.000 (88.154) Prec@5 99.000 (99.077) +2022-11-14 16:53:39,954 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0757) Prec@1 86.000 (88.074) Prec@5 100.000 (99.111) +2022-11-14 16:53:39,962 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0753) Prec@1 90.000 (88.143) Prec@5 99.000 (99.107) +2022-11-14 16:53:39,970 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0756) Prec@1 86.000 (88.069) Prec@5 99.000 (99.103) +2022-11-14 16:53:39,977 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0756) Prec@1 87.000 (88.033) Prec@5 99.000 (99.100) +2022-11-14 16:53:39,985 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0750) Prec@1 90.000 (88.097) Prec@5 100.000 (99.129) +2022-11-14 16:53:39,993 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0753) Prec@1 88.000 (88.094) Prec@5 99.000 (99.125) +2022-11-14 16:53:40,001 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0754) Prec@1 87.000 (88.061) Prec@5 100.000 (99.152) +2022-11-14 16:53:40,008 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0753) Prec@1 86.000 (88.000) Prec@5 100.000 (99.176) +2022-11-14 16:53:40,016 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1081 (0.0763) Prec@1 85.000 (87.914) Prec@5 99.000 (99.171) +2022-11-14 16:53:40,024 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0760) Prec@1 89.000 (87.944) Prec@5 99.000 (99.167) +2022-11-14 16:53:40,031 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0759) Prec@1 88.000 (87.946) Prec@5 99.000 (99.162) +2022-11-14 16:53:40,039 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0769) Prec@1 84.000 (87.842) Prec@5 99.000 (99.158) +2022-11-14 16:53:40,047 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0762) Prec@1 92.000 (87.949) Prec@5 99.000 (99.154) +2022-11-14 16:53:40,054 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0763) Prec@1 86.000 (87.900) Prec@5 98.000 (99.125) +2022-11-14 16:53:40,062 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0768) Prec@1 87.000 (87.878) Prec@5 98.000 (99.098) +2022-11-14 16:53:40,069 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0771) Prec@1 86.000 (87.833) Prec@5 99.000 (99.095) +2022-11-14 16:53:40,077 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0767) Prec@1 91.000 (87.907) Prec@5 100.000 (99.116) +2022-11-14 16:53:40,085 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0764) Prec@1 91.000 (87.977) Prec@5 98.000 (99.091) +2022-11-14 16:53:40,093 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0759) Prec@1 89.000 (88.000) Prec@5 99.000 (99.089) +2022-11-14 16:53:40,101 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0762) Prec@1 83.000 (87.891) Prec@5 99.000 (99.087) +2022-11-14 16:53:40,108 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0763) Prec@1 87.000 (87.872) Prec@5 99.000 (99.085) +2022-11-14 16:53:40,116 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1165 (0.0771) Prec@1 80.000 (87.708) Prec@5 97.000 (99.042) +2022-11-14 16:53:40,124 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0766) Prec@1 90.000 (87.755) Prec@5 100.000 (99.061) +2022-11-14 16:53:40,132 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0769) Prec@1 84.000 (87.680) Prec@5 100.000 (99.080) +2022-11-14 16:53:40,139 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0764) Prec@1 91.000 (87.745) Prec@5 100.000 (99.098) +2022-11-14 16:53:40,147 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0764) Prec@1 86.000 (87.712) Prec@5 98.000 (99.077) +2022-11-14 16:53:40,154 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0762) Prec@1 89.000 (87.736) Prec@5 99.000 (99.075) +2022-11-14 16:53:40,162 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0759) Prec@1 90.000 (87.778) Prec@5 99.000 (99.074) +2022-11-14 16:53:40,170 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0760) Prec@1 88.000 (87.782) Prec@5 100.000 (99.091) +2022-11-14 16:53:40,178 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0759) Prec@1 90.000 (87.821) Prec@5 99.000 (99.089) +2022-11-14 16:53:40,185 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0756) Prec@1 89.000 (87.842) Prec@5 100.000 (99.105) +2022-11-14 16:53:40,193 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0755) Prec@1 88.000 (87.845) Prec@5 98.000 (99.086) +2022-11-14 16:53:40,200 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0759) Prec@1 84.000 (87.780) Prec@5 98.000 (99.068) +2022-11-14 16:53:40,209 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0760) Prec@1 85.000 (87.733) Prec@5 99.000 (99.067) +2022-11-14 16:53:40,216 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0994 (0.0764) Prec@1 85.000 (87.689) Prec@5 98.000 (99.049) +2022-11-14 16:53:40,224 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0765) Prec@1 88.000 (87.694) Prec@5 99.000 (99.048) +2022-11-14 16:53:40,232 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0764) Prec@1 88.000 (87.698) Prec@5 100.000 (99.063) +2022-11-14 16:53:40,240 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0760) Prec@1 91.000 (87.750) Prec@5 99.000 (99.062) +2022-11-14 16:53:40,247 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0759) Prec@1 90.000 (87.785) Prec@5 100.000 (99.077) +2022-11-14 16:53:40,255 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0761) Prec@1 83.000 (87.712) Prec@5 100.000 (99.091) +2022-11-14 16:53:40,262 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0756) Prec@1 93.000 (87.791) Prec@5 100.000 (99.104) +2022-11-14 16:53:40,270 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0755) Prec@1 92.000 (87.853) Prec@5 99.000 (99.103) +2022-11-14 16:53:40,278 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0753) Prec@1 89.000 (87.870) Prec@5 99.000 (99.101) +2022-11-14 16:53:40,285 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0752) Prec@1 90.000 (87.900) Prec@5 99.000 (99.100) +2022-11-14 16:53:40,293 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0753) Prec@1 88.000 (87.901) Prec@5 98.000 (99.085) +2022-11-14 16:53:40,300 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0752) Prec@1 90.000 (87.931) Prec@5 100.000 (99.097) +2022-11-14 16:53:40,308 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0412 (0.0747) Prec@1 94.000 (88.014) Prec@5 100.000 (99.110) +2022-11-14 16:53:40,316 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0386 (0.0742) Prec@1 95.000 (88.108) Prec@5 100.000 (99.122) +2022-11-14 16:53:40,323 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0745) Prec@1 84.000 (88.053) Prec@5 99.000 (99.120) +2022-11-14 16:53:40,331 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0743) Prec@1 88.000 (88.053) Prec@5 99.000 (99.118) +2022-11-14 16:53:40,338 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0743) Prec@1 90.000 (88.078) Prec@5 100.000 (99.130) +2022-11-14 16:53:40,346 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0745) Prec@1 87.000 (88.064) Prec@5 98.000 (99.115) +2022-11-14 16:53:40,354 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0744) Prec@1 89.000 (88.076) Prec@5 100.000 (99.127) +2022-11-14 16:53:40,361 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0743) Prec@1 92.000 (88.125) Prec@5 99.000 (99.125) +2022-11-14 16:53:40,369 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0745) Prec@1 86.000 (88.099) Prec@5 97.000 (99.099) +2022-11-14 16:53:40,377 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0748) Prec@1 86.000 (88.073) Prec@5 99.000 (99.098) +2022-11-14 16:53:40,384 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0750) Prec@1 84.000 (88.024) Prec@5 99.000 (99.096) +2022-11-14 16:53:40,392 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0752) Prec@1 86.000 (88.000) Prec@5 100.000 (99.107) +2022-11-14 16:53:40,400 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0753) Prec@1 88.000 (88.000) Prec@5 100.000 (99.118) +2022-11-14 16:53:40,407 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0755) Prec@1 86.000 (87.977) Prec@5 98.000 (99.105) +2022-11-14 16:53:40,415 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0753) Prec@1 87.000 (87.966) Prec@5 100.000 (99.115) +2022-11-14 16:53:40,423 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0752) Prec@1 91.000 (88.000) Prec@5 98.000 (99.102) +2022-11-14 16:53:40,430 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0749) Prec@1 93.000 (88.056) Prec@5 99.000 (99.101) +2022-11-14 16:53:40,438 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0749) Prec@1 88.000 (88.056) Prec@5 100.000 (99.111) +2022-11-14 16:53:40,445 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0747) Prec@1 91.000 (88.088) Prec@5 100.000 (99.121) +2022-11-14 16:53:40,453 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0745) Prec@1 91.000 (88.120) Prec@5 100.000 (99.130) +2022-11-14 16:53:40,460 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0744) Prec@1 91.000 (88.151) Prec@5 99.000 (99.129) +2022-11-14 16:53:40,468 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0742) Prec@1 90.000 (88.170) Prec@5 99.000 (99.128) +2022-11-14 16:53:40,476 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0743) Prec@1 88.000 (88.168) Prec@5 99.000 (99.126) +2022-11-14 16:53:40,483 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0743) Prec@1 89.000 (88.177) Prec@5 99.000 (99.125) +2022-11-14 16:53:40,490 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0741) Prec@1 91.000 (88.206) Prec@5 98.000 (99.113) +2022-11-14 16:53:40,498 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0745) Prec@1 84.000 (88.163) Prec@5 98.000 (99.102) +2022-11-14 16:53:40,505 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0746) Prec@1 87.000 (88.152) Prec@5 100.000 (99.111) +2022-11-14 16:53:40,513 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0745) Prec@1 89.000 (88.160) Prec@5 100.000 (99.120) +2022-11-14 16:53:40,567 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:53:40,895 Epoch: [409][0/500] Time 0.025 (0.025) Data 0.249 (0.249) Loss 0.0201 (0.0201) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:41,091 Epoch: [409][10/500] Time 0.018 (0.018) Data 0.001 (0.024) Loss 0.0225 (0.0213) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:41,277 Epoch: [409][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0369 (0.0265) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:41,464 Epoch: [409][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0291 (0.0271) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:53:41,652 Epoch: [409][40/500] Time 0.018 (0.017) Data 0.001 (0.007) Loss 0.0358 (0.0289) Prec@1 95.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 16:53:41,840 Epoch: [409][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0275 (0.0286) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,028 Epoch: [409][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0152 (0.0267) Prec@1 98.000 (95.857) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,219 Epoch: [409][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0362 (0.0279) Prec@1 96.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,408 Epoch: [409][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0129 (0.0262) Prec@1 98.000 (96.111) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,597 Epoch: [409][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0201 (0.0256) Prec@1 96.000 (96.100) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,788 Epoch: [409][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0323 (0.0262) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:42,979 Epoch: [409][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0237 (0.0260) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:43,173 Epoch: [409][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0486 (0.0278) Prec@1 92.000 (95.692) Prec@5 100.000 (100.000) +2022-11-14 16:53:43,362 Epoch: [409][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0291 (0.0279) Prec@1 96.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 16:53:43,551 Epoch: [409][140/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0418 (0.0288) Prec@1 94.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:53:43,740 Epoch: [409][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0283 (0.0287) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:43,930 Epoch: [409][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0504 (0.0300) Prec@1 91.000 (95.235) Prec@5 100.000 (100.000) +2022-11-14 16:53:44,122 Epoch: [409][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0154 (0.0292) Prec@1 98.000 (95.389) Prec@5 100.000 (100.000) +2022-11-14 16:53:44,323 Epoch: [409][180/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0405 (0.0298) Prec@1 91.000 (95.158) Prec@5 100.000 (100.000) +2022-11-14 16:53:44,582 Epoch: [409][190/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0302 (0.0298) Prec@1 93.000 (95.050) Prec@5 100.000 (100.000) +2022-11-14 16:53:44,856 Epoch: [409][200/500] Time 0.025 (0.017) Data 0.001 (0.003) Loss 0.0316 (0.0299) Prec@1 95.000 (95.048) Prec@5 100.000 (100.000) +2022-11-14 16:53:45,136 Epoch: [409][210/500] Time 0.025 (0.018) Data 0.003 (0.003) Loss 0.0179 (0.0294) Prec@1 98.000 (95.182) Prec@5 100.000 (100.000) +2022-11-14 16:53:45,414 Epoch: [409][220/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0321 (0.0295) Prec@1 95.000 (95.174) Prec@5 99.000 (99.957) +2022-11-14 16:53:45,695 Epoch: [409][230/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0152 (0.0289) Prec@1 99.000 (95.333) Prec@5 100.000 (99.958) +2022-11-14 16:53:45,973 Epoch: [409][240/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0442 (0.0295) Prec@1 92.000 (95.200) Prec@5 99.000 (99.920) +2022-11-14 16:53:46,254 Epoch: [409][250/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0262 (0.0294) Prec@1 96.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 16:53:46,534 Epoch: [409][260/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0190 (0.0290) Prec@1 97.000 (95.296) Prec@5 100.000 (99.926) +2022-11-14 16:53:46,802 Epoch: [409][270/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0431 (0.0295) Prec@1 93.000 (95.214) Prec@5 100.000 (99.929) +2022-11-14 16:53:47,074 Epoch: [409][280/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0253 (0.0294) Prec@1 96.000 (95.241) Prec@5 100.000 (99.931) +2022-11-14 16:53:47,346 Epoch: [409][290/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0369 (0.0296) Prec@1 94.000 (95.200) Prec@5 100.000 (99.933) +2022-11-14 16:53:47,615 Epoch: [409][300/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0348 (0.0298) Prec@1 94.000 (95.161) Prec@5 100.000 (99.935) +2022-11-14 16:53:47,885 Epoch: [409][310/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0237 (0.0296) Prec@1 98.000 (95.250) Prec@5 100.000 (99.938) +2022-11-14 16:53:48,155 Epoch: [409][320/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0252 (0.0294) Prec@1 96.000 (95.273) Prec@5 100.000 (99.939) +2022-11-14 16:53:48,422 Epoch: [409][330/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0568 (0.0303) Prec@1 92.000 (95.176) Prec@5 100.000 (99.941) +2022-11-14 16:53:48,693 Epoch: [409][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0383 (0.0305) Prec@1 94.000 (95.143) Prec@5 100.000 (99.943) +2022-11-14 16:53:48,961 Epoch: [409][350/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0096 (0.0299) Prec@1 100.000 (95.278) Prec@5 100.000 (99.944) +2022-11-14 16:53:49,232 Epoch: [409][360/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0175 (0.0296) Prec@1 97.000 (95.324) Prec@5 100.000 (99.946) +2022-11-14 16:53:49,498 Epoch: [409][370/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0101 (0.0291) Prec@1 99.000 (95.421) Prec@5 100.000 (99.947) +2022-11-14 16:53:49,770 Epoch: [409][380/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0332 (0.0292) Prec@1 96.000 (95.436) Prec@5 99.000 (99.923) +2022-11-14 16:53:50,036 Epoch: [409][390/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0764 (0.0303) Prec@1 87.000 (95.225) Prec@5 99.000 (99.900) +2022-11-14 16:53:50,309 Epoch: [409][400/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0320 (0.0304) Prec@1 96.000 (95.244) Prec@5 99.000 (99.878) +2022-11-14 16:53:50,573 Epoch: [409][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0172 (0.0301) Prec@1 97.000 (95.286) Prec@5 100.000 (99.881) +2022-11-14 16:53:50,840 Epoch: [409][420/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0382 (0.0303) Prec@1 96.000 (95.302) Prec@5 100.000 (99.884) +2022-11-14 16:53:51,111 Epoch: [409][430/500] Time 0.029 (0.021) Data 0.001 (0.002) Loss 0.0367 (0.0304) Prec@1 94.000 (95.273) Prec@5 100.000 (99.886) +2022-11-14 16:53:51,378 Epoch: [409][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0289 (0.0304) Prec@1 95.000 (95.267) Prec@5 100.000 (99.889) +2022-11-14 16:53:51,648 Epoch: [409][450/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0221 (0.0302) Prec@1 97.000 (95.304) Prec@5 100.000 (99.891) +2022-11-14 16:53:51,912 Epoch: [409][460/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0269 (0.0301) Prec@1 97.000 (95.340) Prec@5 100.000 (99.894) +2022-11-14 16:53:52,182 Epoch: [409][470/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0408 (0.0303) Prec@1 94.000 (95.312) Prec@5 100.000 (99.896) +2022-11-14 16:53:52,454 Epoch: [409][480/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0178 (0.0301) Prec@1 96.000 (95.327) Prec@5 100.000 (99.898) +2022-11-14 16:53:52,724 Epoch: [409][490/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0361 (0.0302) Prec@1 94.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 16:53:52,966 Epoch: [409][499/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0327 (0.0303) Prec@1 95.000 (95.294) Prec@5 100.000 (99.902) +2022-11-14 16:53:53,267 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0580 (0.0580) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:53,275 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0638) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:53,282 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0687) Prec@1 87.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 16:53:53,292 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0717) Prec@1 88.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 16:53:53,299 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0733) Prec@1 84.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 16:53:53,306 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0684) Prec@1 93.000 (88.500) Prec@5 100.000 (99.667) +2022-11-14 16:53:53,313 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0690) Prec@1 89.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 16:53:53,321 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0712) Prec@1 87.000 (88.375) Prec@5 100.000 (99.625) +2022-11-14 16:53:53,328 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0732) Prec@1 88.000 (88.333) Prec@5 98.000 (99.444) +2022-11-14 16:53:53,336 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0737) Prec@1 89.000 (88.400) Prec@5 98.000 (99.300) +2022-11-14 16:53:53,344 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0753) Prec@1 87.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 16:53:53,351 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0753) Prec@1 86.000 (88.083) Prec@5 99.000 (99.333) +2022-11-14 16:53:53,359 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0752) Prec@1 88.000 (88.077) Prec@5 100.000 (99.385) +2022-11-14 16:53:53,366 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0746) Prec@1 90.000 (88.214) Prec@5 99.000 (99.357) +2022-11-14 16:53:53,374 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0742) Prec@1 88.000 (88.200) Prec@5 100.000 (99.400) +2022-11-14 16:53:53,382 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0739) Prec@1 87.000 (88.125) Prec@5 99.000 (99.375) +2022-11-14 16:53:53,389 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0722) Prec@1 92.000 (88.353) Prec@5 99.000 (99.353) +2022-11-14 16:53:53,397 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0734) Prec@1 86.000 (88.222) Prec@5 99.000 (99.333) +2022-11-14 16:53:53,404 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0736) Prec@1 87.000 (88.158) Prec@5 99.000 (99.316) +2022-11-14 16:53:53,411 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0740) Prec@1 87.000 (88.100) Prec@5 99.000 (99.300) +2022-11-14 16:53:53,419 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0740) Prec@1 86.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 16:53:53,426 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0743) Prec@1 88.000 (88.000) Prec@5 98.000 (99.273) +2022-11-14 16:53:53,434 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0751) Prec@1 86.000 (87.913) Prec@5 98.000 (99.217) +2022-11-14 16:53:53,441 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0753) Prec@1 88.000 (87.917) Prec@5 99.000 (99.208) +2022-11-14 16:53:53,449 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0763) Prec@1 83.000 (87.720) Prec@5 99.000 (99.200) +2022-11-14 16:53:53,457 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0767) Prec@1 87.000 (87.692) Prec@5 99.000 (99.192) +2022-11-14 16:53:53,465 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0756) Prec@1 93.000 (87.889) Prec@5 100.000 (99.222) +2022-11-14 16:53:53,473 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0754) Prec@1 88.000 (87.893) Prec@5 100.000 (99.250) +2022-11-14 16:53:53,480 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0762) Prec@1 85.000 (87.793) Prec@5 99.000 (99.241) +2022-11-14 16:53:53,488 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0759) Prec@1 89.000 (87.833) Prec@5 100.000 (99.267) +2022-11-14 16:53:53,496 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0757) Prec@1 88.000 (87.839) Prec@5 100.000 (99.290) +2022-11-14 16:53:53,503 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0751) Prec@1 93.000 (88.000) Prec@5 100.000 (99.312) +2022-11-14 16:53:53,511 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0750) Prec@1 89.000 (88.030) Prec@5 99.000 (99.303) +2022-11-14 16:53:53,519 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0755) Prec@1 84.000 (87.912) Prec@5 100.000 (99.324) +2022-11-14 16:53:53,527 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0759) Prec@1 84.000 (87.800) Prec@5 99.000 (99.314) +2022-11-14 16:53:53,535 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0757) Prec@1 89.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 16:53:53,542 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0757) Prec@1 89.000 (87.865) Prec@5 99.000 (99.324) +2022-11-14 16:53:53,550 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0762) Prec@1 83.000 (87.737) Prec@5 99.000 (99.316) +2022-11-14 16:53:53,557 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0758) Prec@1 93.000 (87.872) Prec@5 100.000 (99.333) +2022-11-14 16:53:53,565 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0756) Prec@1 90.000 (87.925) Prec@5 100.000 (99.350) +2022-11-14 16:53:53,573 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0759) Prec@1 88.000 (87.927) Prec@5 99.000 (99.341) +2022-11-14 16:53:53,581 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0612 (0.0756) Prec@1 89.000 (87.952) Prec@5 100.000 (99.357) +2022-11-14 16:53:53,589 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0416 (0.0748) Prec@1 94.000 (88.093) Prec@5 100.000 (99.372) +2022-11-14 16:53:53,596 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0746) Prec@1 90.000 (88.136) Prec@5 98.000 (99.341) +2022-11-14 16:53:53,604 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0609 (0.0743) Prec@1 90.000 (88.178) Prec@5 98.000 (99.311) +2022-11-14 16:53:53,611 Test: [45/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0748) Prec@1 84.000 (88.087) Prec@5 100.000 (99.326) +2022-11-14 16:53:53,619 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0746) Prec@1 87.000 (88.064) Prec@5 100.000 (99.340) +2022-11-14 16:53:53,626 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0950 (0.0750) Prec@1 86.000 (88.021) Prec@5 97.000 (99.292) +2022-11-14 16:53:53,634 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0832 (0.0752) Prec@1 87.000 (88.000) Prec@5 100.000 (99.306) +2022-11-14 16:53:53,642 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1073 (0.0758) Prec@1 83.000 (87.900) Prec@5 100.000 (99.320) +2022-11-14 16:53:53,649 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0614 (0.0755) Prec@1 92.000 (87.980) Prec@5 100.000 (99.333) +2022-11-14 16:53:53,657 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0758) Prec@1 85.000 (87.923) Prec@5 100.000 (99.346) +2022-11-14 16:53:53,664 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0757) Prec@1 87.000 (87.906) Prec@5 100.000 (99.358) +2022-11-14 16:53:53,672 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0756) Prec@1 90.000 (87.944) Prec@5 100.000 (99.370) +2022-11-14 16:53:53,679 Test: [54/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0964 (0.0760) Prec@1 85.000 (87.891) Prec@5 99.000 (99.364) +2022-11-14 16:53:53,687 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0759) Prec@1 88.000 (87.893) Prec@5 99.000 (99.357) +2022-11-14 16:53:53,695 Test: [56/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0594 (0.0756) Prec@1 90.000 (87.930) Prec@5 100.000 (99.368) +2022-11-14 16:53:53,702 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0637 (0.0754) Prec@1 90.000 (87.966) Prec@5 100.000 (99.379) +2022-11-14 16:53:53,710 Test: [58/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0743 (0.0754) Prec@1 84.000 (87.898) Prec@5 99.000 (99.373) +2022-11-14 16:53:53,718 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0996 (0.0758) Prec@1 83.000 (87.817) Prec@5 99.000 (99.367) +2022-11-14 16:53:53,726 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0758) Prec@1 89.000 (87.836) Prec@5 100.000 (99.377) +2022-11-14 16:53:53,733 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0638 (0.0756) Prec@1 90.000 (87.871) Prec@5 99.000 (99.371) +2022-11-14 16:53:53,741 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0779 (0.0756) Prec@1 87.000 (87.857) Prec@5 99.000 (99.365) +2022-11-14 16:53:53,748 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0417 (0.0751) Prec@1 93.000 (87.938) Prec@5 99.000 (99.359) +2022-11-14 16:53:53,756 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0989 (0.0754) Prec@1 85.000 (87.892) Prec@5 100.000 (99.369) +2022-11-14 16:53:53,763 Test: [65/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0754) Prec@1 88.000 (87.894) Prec@5 98.000 (99.348) +2022-11-14 16:53:53,773 Test: [66/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0441 (0.0749) Prec@1 94.000 (87.985) Prec@5 100.000 (99.358) +2022-11-14 16:53:53,781 Test: [67/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0830 (0.0751) Prec@1 87.000 (87.971) Prec@5 99.000 (99.353) +2022-11-14 16:53:53,789 Test: [68/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0719 (0.0750) Prec@1 88.000 (87.971) Prec@5 99.000 (99.348) +2022-11-14 16:53:53,796 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0806 (0.0751) Prec@1 86.000 (87.943) Prec@5 99.000 (99.343) +2022-11-14 16:53:53,804 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0862 (0.0752) Prec@1 88.000 (87.944) Prec@5 99.000 (99.338) +2022-11-14 16:53:53,811 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0509 (0.0749) Prec@1 91.000 (87.986) Prec@5 100.000 (99.347) +2022-11-14 16:53:53,819 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0607 (0.0747) Prec@1 89.000 (88.000) Prec@5 99.000 (99.342) +2022-11-14 16:53:53,826 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0488 (0.0744) Prec@1 93.000 (88.068) Prec@5 99.000 (99.338) +2022-11-14 16:53:53,834 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0768 (0.0744) Prec@1 84.000 (88.013) Prec@5 100.000 (99.347) +2022-11-14 16:53:53,841 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 88.000 (88.013) Prec@5 100.000 (99.355) +2022-11-14 16:53:53,849 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0726 (0.0744) Prec@1 91.000 (88.052) Prec@5 100.000 (99.364) +2022-11-14 16:53:53,857 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0744) Prec@1 89.000 (88.064) Prec@5 98.000 (99.346) +2022-11-14 16:53:53,864 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0744) Prec@1 87.000 (88.051) Prec@5 100.000 (99.354) +2022-11-14 16:53:53,872 Test: [79/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0743) Prec@1 88.000 (88.050) Prec@5 100.000 (99.362) +2022-11-14 16:53:53,880 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0934 (0.0746) Prec@1 85.000 (88.012) Prec@5 99.000 (99.358) +2022-11-14 16:53:53,887 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0746) Prec@1 88.000 (88.012) Prec@5 100.000 (99.366) +2022-11-14 16:53:53,895 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1080 (0.0750) Prec@1 83.000 (87.952) Prec@5 100.000 (99.373) +2022-11-14 16:53:53,902 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 86.000 (87.929) Prec@5 98.000 (99.357) +2022-11-14 16:53:53,909 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0751) Prec@1 89.000 (87.941) Prec@5 99.000 (99.353) +2022-11-14 16:53:53,917 Test: [85/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1065 (0.0754) Prec@1 83.000 (87.884) Prec@5 100.000 (99.360) +2022-11-14 16:53:53,924 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0754) Prec@1 87.000 (87.874) Prec@5 100.000 (99.368) +2022-11-14 16:53:53,933 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0754) Prec@1 89.000 (87.886) Prec@5 99.000 (99.364) +2022-11-14 16:53:53,940 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0764 (0.0754) Prec@1 85.000 (87.854) Prec@5 99.000 (99.360) +2022-11-14 16:53:53,948 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0638 (0.0753) Prec@1 91.000 (87.889) Prec@5 99.000 (99.356) +2022-11-14 16:53:53,955 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0531 (0.0750) Prec@1 90.000 (87.912) Prec@5 100.000 (99.363) +2022-11-14 16:53:53,963 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0686 (0.0750) Prec@1 90.000 (87.935) Prec@5 100.000 (99.370) +2022-11-14 16:53:53,970 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0837 (0.0751) Prec@1 85.000 (87.903) Prec@5 100.000 (99.376) +2022-11-14 16:53:53,978 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0608 (0.0749) Prec@1 92.000 (87.947) Prec@5 98.000 (99.362) +2022-11-14 16:53:53,985 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0749) Prec@1 90.000 (87.968) Prec@5 99.000 (99.358) +2022-11-14 16:53:53,993 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0633 (0.0748) Prec@1 91.000 (88.000) Prec@5 99.000 (99.354) +2022-11-14 16:53:54,000 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0415 (0.0744) Prec@1 93.000 (88.052) Prec@5 99.000 (99.351) +2022-11-14 16:53:54,007 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0949 (0.0746) Prec@1 87.000 (88.041) Prec@5 96.000 (99.316) +2022-11-14 16:53:54,015 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0959 (0.0748) Prec@1 84.000 (88.000) Prec@5 99.000 (99.313) +2022-11-14 16:53:54,022 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0748) Prec@1 89.000 (88.010) Prec@5 100.000 (99.320) +2022-11-14 16:53:54,076 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:53:54,394 Epoch: [410][0/500] Time 0.022 (0.022) Data 0.240 (0.240) Loss 0.0156 (0.0156) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:54,587 Epoch: [410][10/500] Time 0.017 (0.017) Data 0.001 (0.023) Loss 0.0139 (0.0148) Prec@1 99.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:54,775 Epoch: [410][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0122 (0.0139) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:53:54,964 Epoch: [410][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0277 (0.0174) Prec@1 96.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:53:55,155 Epoch: [410][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0510 (0.0241) Prec@1 92.000 (96.400) Prec@5 99.000 (99.800) +2022-11-14 16:53:55,357 Epoch: [410][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0248 (0.0242) Prec@1 95.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 16:53:55,565 Epoch: [410][60/500] Time 0.016 (0.017) Data 0.001 (0.006) Loss 0.0353 (0.0258) Prec@1 95.000 (96.000) Prec@5 100.000 (99.857) +2022-11-14 16:53:55,750 Epoch: [410][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0333 (0.0267) Prec@1 94.000 (95.750) Prec@5 100.000 (99.875) +2022-11-14 16:53:55,938 Epoch: [410][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0159 (0.0255) Prec@1 98.000 (96.000) Prec@5 100.000 (99.889) +2022-11-14 16:53:56,131 Epoch: [410][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0158 (0.0246) Prec@1 98.000 (96.200) Prec@5 100.000 (99.900) +2022-11-14 16:53:56,319 Epoch: [410][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0191 (0.0241) Prec@1 96.000 (96.182) Prec@5 100.000 (99.909) +2022-11-14 16:53:56,509 Epoch: [410][110/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0266 (0.0243) Prec@1 96.000 (96.167) Prec@5 100.000 (99.917) +2022-11-14 16:53:56,736 Epoch: [410][120/500] Time 0.025 (0.017) Data 0.002 (0.004) Loss 0.0249 (0.0243) Prec@1 96.000 (96.154) Prec@5 100.000 (99.923) +2022-11-14 16:53:57,018 Epoch: [410][130/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0385 (0.0253) Prec@1 93.000 (95.929) Prec@5 100.000 (99.929) +2022-11-14 16:53:57,300 Epoch: [410][140/500] Time 0.028 (0.018) Data 0.001 (0.003) Loss 0.0258 (0.0254) Prec@1 96.000 (95.933) Prec@5 100.000 (99.933) +2022-11-14 16:53:57,581 Epoch: [410][150/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0174 (0.0249) Prec@1 98.000 (96.062) Prec@5 100.000 (99.938) +2022-11-14 16:53:57,858 Epoch: [410][160/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0541 (0.0266) Prec@1 91.000 (95.765) Prec@5 100.000 (99.941) +2022-11-14 16:53:58,141 Epoch: [410][170/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0327 (0.0269) Prec@1 95.000 (95.722) Prec@5 100.000 (99.944) +2022-11-14 16:53:58,420 Epoch: [410][180/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0292 (0.0270) Prec@1 96.000 (95.737) Prec@5 100.000 (99.947) +2022-11-14 16:53:58,694 Epoch: [410][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0256 (0.0270) Prec@1 95.000 (95.700) Prec@5 100.000 (99.950) +2022-11-14 16:53:58,974 Epoch: [410][200/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0186 (0.0266) Prec@1 96.000 (95.714) Prec@5 100.000 (99.952) +2022-11-14 16:53:59,252 Epoch: [410][210/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0234 (0.0264) Prec@1 96.000 (95.727) Prec@5 100.000 (99.955) +2022-11-14 16:53:59,528 Epoch: [410][220/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0207 (0.0262) Prec@1 97.000 (95.783) Prec@5 100.000 (99.957) +2022-11-14 16:53:59,805 Epoch: [410][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0405 (0.0268) Prec@1 93.000 (95.667) Prec@5 100.000 (99.958) +2022-11-14 16:54:00,083 Epoch: [410][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0138 (0.0263) Prec@1 98.000 (95.760) Prec@5 100.000 (99.960) +2022-11-14 16:54:00,365 Epoch: [410][250/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0378 (0.0267) Prec@1 94.000 (95.692) Prec@5 99.000 (99.923) +2022-11-14 16:54:00,643 Epoch: [410][260/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0416 (0.0273) Prec@1 91.000 (95.519) Prec@5 100.000 (99.926) +2022-11-14 16:54:00,920 Epoch: [410][270/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0343 (0.0275) Prec@1 97.000 (95.571) Prec@5 100.000 (99.929) +2022-11-14 16:54:01,197 Epoch: [410][280/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0409 (0.0280) Prec@1 93.000 (95.483) Prec@5 100.000 (99.931) +2022-11-14 16:54:01,473 Epoch: [410][290/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0253 (0.0279) Prec@1 95.000 (95.467) Prec@5 100.000 (99.933) +2022-11-14 16:54:01,745 Epoch: [410][300/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0464 (0.0285) Prec@1 93.000 (95.387) Prec@5 99.000 (99.903) +2022-11-14 16:54:02,020 Epoch: [410][310/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0239 (0.0283) Prec@1 96.000 (95.406) Prec@5 100.000 (99.906) +2022-11-14 16:54:02,298 Epoch: [410][320/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0361 (0.0286) Prec@1 94.000 (95.364) Prec@5 99.000 (99.879) +2022-11-14 16:54:02,575 Epoch: [410][330/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0203 (0.0283) Prec@1 97.000 (95.412) Prec@5 100.000 (99.882) +2022-11-14 16:54:02,850 Epoch: [410][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0347 (0.0285) Prec@1 94.000 (95.371) Prec@5 100.000 (99.886) +2022-11-14 16:54:03,131 Epoch: [410][350/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0137 (0.0281) Prec@1 98.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:54:03,405 Epoch: [410][360/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0509 (0.0287) Prec@1 92.000 (95.351) Prec@5 100.000 (99.892) +2022-11-14 16:54:03,679 Epoch: [410][370/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0382 (0.0290) Prec@1 93.000 (95.289) Prec@5 100.000 (99.895) +2022-11-14 16:54:03,956 Epoch: [410][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0346 (0.0291) Prec@1 94.000 (95.256) Prec@5 100.000 (99.897) +2022-11-14 16:54:04,237 Epoch: [410][390/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0474 (0.0296) Prec@1 91.000 (95.150) Prec@5 100.000 (99.900) +2022-11-14 16:54:04,512 Epoch: [410][400/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0233 (0.0294) Prec@1 96.000 (95.171) Prec@5 100.000 (99.902) +2022-11-14 16:54:04,789 Epoch: [410][410/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0298 (0.0294) Prec@1 95.000 (95.167) Prec@5 100.000 (99.905) +2022-11-14 16:54:05,069 Epoch: [410][420/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0242 (0.0293) Prec@1 97.000 (95.209) Prec@5 100.000 (99.907) +2022-11-14 16:54:05,347 Epoch: [410][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0277 (0.0293) Prec@1 97.000 (95.250) Prec@5 100.000 (99.909) +2022-11-14 16:54:05,628 Epoch: [410][440/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0372 (0.0294) Prec@1 95.000 (95.244) Prec@5 100.000 (99.911) +2022-11-14 16:54:05,906 Epoch: [410][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0249 (0.0293) Prec@1 97.000 (95.283) Prec@5 100.000 (99.913) +2022-11-14 16:54:06,189 Epoch: [410][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0317 (0.0294) Prec@1 94.000 (95.255) Prec@5 100.000 (99.915) +2022-11-14 16:54:06,464 Epoch: [410][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0240 (0.0293) Prec@1 96.000 (95.271) Prec@5 100.000 (99.917) +2022-11-14 16:54:06,736 Epoch: [410][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0218 (0.0291) Prec@1 96.000 (95.286) Prec@5 100.000 (99.918) +2022-11-14 16:54:07,015 Epoch: [410][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0168 (0.0289) Prec@1 97.000 (95.320) Prec@5 100.000 (99.920) +2022-11-14 16:54:07,271 Epoch: [410][499/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0330 (0.0290) Prec@1 95.000 (95.314) Prec@5 99.000 (99.902) +2022-11-14 16:54:07,568 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0694 (0.0694) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 16:54:07,576 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0664) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 16:54:07,586 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0731) Prec@1 84.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:54:07,595 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0757) Prec@1 89.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 16:54:07,602 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0752) Prec@1 89.000 (88.400) Prec@5 100.000 (99.800) +2022-11-14 16:54:07,609 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0705) Prec@1 92.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 16:54:07,616 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0698) Prec@1 90.000 (89.143) Prec@5 99.000 (99.714) +2022-11-14 16:54:07,625 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0712) Prec@1 87.000 (88.875) Prec@5 99.000 (99.625) +2022-11-14 16:54:07,632 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0717) Prec@1 88.000 (88.778) Prec@5 99.000 (99.556) +2022-11-14 16:54:07,639 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0730) Prec@1 86.000 (88.500) Prec@5 98.000 (99.400) +2022-11-14 16:54:07,646 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0705) Prec@1 94.000 (89.000) Prec@5 99.000 (99.364) +2022-11-14 16:54:07,654 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0725) Prec@1 87.000 (88.833) Prec@5 99.000 (99.333) +2022-11-14 16:54:07,662 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0420 (0.0702) Prec@1 93.000 (89.154) Prec@5 99.000 (99.308) +2022-11-14 16:54:07,670 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0706) Prec@1 88.000 (89.071) Prec@5 99.000 (99.286) +2022-11-14 16:54:07,678 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0722) Prec@1 87.000 (88.933) Prec@5 98.000 (99.200) +2022-11-14 16:54:07,686 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0726) Prec@1 87.000 (88.812) Prec@5 100.000 (99.250) +2022-11-14 16:54:07,694 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0710) Prec@1 93.000 (89.059) Prec@5 98.000 (99.176) +2022-11-14 16:54:07,701 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.0735) Prec@1 84.000 (88.778) Prec@5 99.000 (99.167) +2022-11-14 16:54:07,709 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0737) Prec@1 86.000 (88.632) Prec@5 100.000 (99.211) +2022-11-14 16:54:07,717 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0743) Prec@1 86.000 (88.500) Prec@5 97.000 (99.100) +2022-11-14 16:54:07,725 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0751) Prec@1 86.000 (88.381) Prec@5 100.000 (99.143) +2022-11-14 16:54:07,732 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0758) Prec@1 86.000 (88.273) Prec@5 98.000 (99.091) +2022-11-14 16:54:07,740 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0769) Prec@1 83.000 (88.043) Prec@5 97.000 (99.000) +2022-11-14 16:54:07,748 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0768) Prec@1 89.000 (88.083) Prec@5 100.000 (99.042) +2022-11-14 16:54:07,756 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0776) Prec@1 83.000 (87.880) Prec@5 100.000 (99.080) +2022-11-14 16:54:07,764 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0787) Prec@1 84.000 (87.731) Prec@5 99.000 (99.077) +2022-11-14 16:54:07,771 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0779) Prec@1 91.000 (87.852) Prec@5 100.000 (99.111) +2022-11-14 16:54:07,779 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0771) Prec@1 93.000 (88.036) Prec@5 100.000 (99.143) +2022-11-14 16:54:07,786 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0767) Prec@1 91.000 (88.138) Prec@5 98.000 (99.103) +2022-11-14 16:54:07,794 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0769) Prec@1 87.000 (88.100) Prec@5 99.000 (99.100) +2022-11-14 16:54:07,802 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0760) Prec@1 92.000 (88.226) Prec@5 100.000 (99.129) +2022-11-14 16:54:07,810 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0757) Prec@1 91.000 (88.312) Prec@5 99.000 (99.125) +2022-11-14 16:54:07,818 Test: 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0.0525 (0.0765) Prec@1 93.000 (88.205) Prec@5 99.000 (99.103) +2022-11-14 16:54:07,872 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0764) Prec@1 88.000 (88.200) Prec@5 98.000 (99.075) +2022-11-14 16:54:07,880 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0768) Prec@1 85.000 (88.122) Prec@5 98.000 (99.049) +2022-11-14 16:54:07,888 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0762) Prec@1 93.000 (88.238) Prec@5 99.000 (99.048) +2022-11-14 16:54:07,896 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0416 (0.0754) Prec@1 94.000 (88.372) Prec@5 99.000 (99.047) +2022-11-14 16:54:07,904 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0754) Prec@1 90.000 (88.409) Prec@5 99.000 (99.045) +2022-11-14 16:54:07,911 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0753) Prec@1 89.000 (88.422) Prec@5 99.000 (99.044) +2022-11-14 16:54:07,919 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0758) Prec@1 85.000 (88.348) Prec@5 100.000 (99.065) +2022-11-14 16:54:07,927 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0759) Prec@1 87.000 (88.319) Prec@5 100.000 (99.085) +2022-11-14 16:54:07,934 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0760) Prec@1 86.000 (88.271) Prec@5 99.000 (99.083) +2022-11-14 16:54:07,942 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0755) Prec@1 92.000 (88.347) Prec@5 100.000 (99.102) +2022-11-14 16:54:07,949 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0762) Prec@1 81.000 (88.200) Prec@5 99.000 (99.100) +2022-11-14 16:54:07,957 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0758) Prec@1 90.000 (88.235) Prec@5 100.000 (99.118) +2022-11-14 16:54:07,965 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0759) Prec@1 87.000 (88.212) Prec@5 99.000 (99.115) +2022-11-14 16:54:07,972 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0761) Prec@1 85.000 (88.151) Prec@5 99.000 (99.113) +2022-11-14 16:54:07,981 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0759) Prec@1 91.000 (88.204) Prec@5 99.000 (99.111) +2022-11-14 16:54:07,989 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0760) Prec@1 88.000 (88.200) Prec@5 100.000 (99.127) +2022-11-14 16:54:07,997 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0757) Prec@1 90.000 (88.232) Prec@5 99.000 (99.125) +2022-11-14 16:54:08,004 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0755) Prec@1 89.000 (88.246) Prec@5 100.000 (99.140) +2022-11-14 16:54:08,012 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0753) Prec@1 92.000 (88.310) Prec@5 100.000 (99.155) +2022-11-14 16:54:08,020 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0755) Prec@1 88.000 (88.305) Prec@5 100.000 (99.169) +2022-11-14 16:54:08,027 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0757) Prec@1 85.000 (88.250) Prec@5 99.000 (99.167) +2022-11-14 16:54:08,034 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0756) Prec@1 90.000 (88.279) Prec@5 99.000 (99.164) +2022-11-14 16:54:08,043 Test: [61/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0753) Prec@1 89.000 (88.290) Prec@5 100.000 (99.177) +2022-11-14 16:54:08,051 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0750) Prec@1 90.000 (88.317) Prec@5 100.000 (99.190) +2022-11-14 16:54:08,059 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0747) Prec@1 90.000 (88.344) Prec@5 100.000 (99.203) +2022-11-14 16:54:08,066 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0753) Prec@1 83.000 (88.262) Prec@5 100.000 (99.215) +2022-11-14 16:54:08,074 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0752) Prec@1 88.000 (88.258) Prec@5 99.000 (99.212) +2022-11-14 16:54:08,083 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0385 (0.0746) Prec@1 94.000 (88.343) Prec@5 100.000 (99.224) +2022-11-14 16:54:08,091 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0746) Prec@1 90.000 (88.368) Prec@5 100.000 (99.235) +2022-11-14 16:54:08,099 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0745) Prec@1 88.000 (88.362) Prec@5 99.000 (99.232) +2022-11-14 16:54:08,107 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0748) Prec@1 87.000 (88.343) Prec@5 99.000 (99.229) +2022-11-14 16:54:08,115 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0751) Prec@1 86.000 (88.310) Prec@5 99.000 (99.225) +2022-11-14 16:54:08,123 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0750) Prec@1 89.000 (88.319) Prec@5 100.000 (99.236) +2022-11-14 16:54:08,130 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0747) Prec@1 91.000 (88.356) Prec@5 99.000 (99.233) +2022-11-14 16:54:08,138 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0744) Prec@1 90.000 (88.378) Prec@5 100.000 (99.243) +2022-11-14 16:54:08,146 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0749) Prec@1 82.000 (88.293) Prec@5 99.000 (99.240) +2022-11-14 16:54:08,154 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0746) Prec@1 90.000 (88.316) Prec@5 100.000 (99.250) +2022-11-14 16:54:08,161 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0747) Prec@1 87.000 (88.299) Prec@5 99.000 (99.247) +2022-11-14 16:54:08,169 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0748) Prec@1 87.000 (88.282) Prec@5 98.000 (99.231) +2022-11-14 16:54:08,177 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0747) Prec@1 88.000 (88.278) Prec@5 100.000 (99.241) +2022-11-14 16:54:08,184 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0746) Prec@1 90.000 (88.300) Prec@5 99.000 (99.237) +2022-11-14 16:54:08,192 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0749) Prec@1 86.000 (88.272) Prec@5 98.000 (99.222) +2022-11-14 16:54:08,200 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0749) Prec@1 88.000 (88.268) Prec@5 99.000 (99.220) +2022-11-14 16:54:08,207 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0751) Prec@1 83.000 (88.205) Prec@5 100.000 (99.229) +2022-11-14 16:54:08,215 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0752) Prec@1 87.000 (88.190) Prec@5 100.000 (99.238) +2022-11-14 16:54:08,223 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0752) Prec@1 88.000 (88.188) Prec@5 100.000 (99.247) +2022-11-14 16:54:08,231 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.0756) Prec@1 83.000 (88.128) Prec@5 100.000 (99.256) +2022-11-14 16:54:08,239 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0756) Prec@1 88.000 (88.126) Prec@5 99.000 (99.253) +2022-11-14 16:54:08,247 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0755) Prec@1 91.000 (88.159) Prec@5 97.000 (99.227) +2022-11-14 16:54:08,254 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0753) Prec@1 89.000 (88.169) Prec@5 99.000 (99.225) +2022-11-14 16:54:08,262 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0755) Prec@1 86.000 (88.144) Prec@5 99.000 (99.222) +2022-11-14 16:54:08,269 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0752) Prec@1 90.000 (88.165) Prec@5 100.000 (99.231) +2022-11-14 16:54:08,277 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0750) Prec@1 89.000 (88.174) Prec@5 100.000 (99.239) +2022-11-14 16:54:08,285 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0751) Prec@1 88.000 (88.172) Prec@5 99.000 (99.237) +2022-11-14 16:54:08,292 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0751) Prec@1 86.000 (88.149) Prec@5 100.000 (99.245) +2022-11-14 16:54:08,300 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0751) Prec@1 87.000 (88.137) Prec@5 100.000 (99.253) +2022-11-14 16:54:08,307 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0750) Prec@1 91.000 (88.167) Prec@5 99.000 (99.250) +2022-11-14 16:54:08,315 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0748) Prec@1 91.000 (88.196) Prec@5 99.000 (99.247) +2022-11-14 16:54:08,322 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0747) Prec@1 90.000 (88.214) Prec@5 100.000 (99.255) +2022-11-14 16:54:08,330 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0749) Prec@1 83.000 (88.162) Prec@5 100.000 (99.263) +2022-11-14 16:54:08,337 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0748) Prec@1 91.000 (88.190) Prec@5 100.000 (99.270) +2022-11-14 16:54:08,394 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:54:08,723 Epoch: [411][0/500] Time 0.023 (0.023) Data 0.243 (0.243) Loss 0.0364 (0.0364) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:54:08,928 Epoch: [411][10/500] Time 0.018 (0.018) Data 0.002 (0.024) Loss 0.0209 (0.0287) Prec@1 97.000 (96.000) Prec@5 100.000 (99.500) +2022-11-14 16:54:09,127 Epoch: [411][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0414 (0.0329) Prec@1 93.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 16:54:09,324 Epoch: [411][30/500] Time 0.018 (0.018) Data 0.002 (0.009) Loss 0.0052 (0.0260) Prec@1 100.000 (96.250) Prec@5 100.000 (99.750) +2022-11-14 16:54:09,523 Epoch: [411][40/500] Time 0.018 (0.018) Data 0.002 (0.008) Loss 0.0193 (0.0246) Prec@1 95.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 16:54:09,721 Epoch: [411][50/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0194 (0.0237) Prec@1 98.000 (96.333) Prec@5 100.000 (99.833) +2022-11-14 16:54:09,916 Epoch: [411][60/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0359 (0.0255) Prec@1 95.000 (96.143) Prec@5 99.000 (99.714) +2022-11-14 16:54:10,112 Epoch: [411][70/500] Time 0.019 (0.018) Data 0.002 (0.005) Loss 0.0126 (0.0239) Prec@1 98.000 (96.375) Prec@5 100.000 (99.750) +2022-11-14 16:54:10,307 Epoch: [411][80/500] Time 0.018 (0.018) Data 0.002 (0.005) Loss 0.0317 (0.0247) Prec@1 94.000 (96.111) Prec@5 100.000 (99.778) +2022-11-14 16:54:10,506 Epoch: [411][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0428 (0.0265) Prec@1 92.000 (95.700) Prec@5 99.000 (99.700) +2022-11-14 16:54:10,704 Epoch: [411][100/500] Time 0.018 (0.018) Data 0.002 (0.004) Loss 0.0129 (0.0253) Prec@1 98.000 (95.909) Prec@5 100.000 (99.727) +2022-11-14 16:54:10,903 Epoch: [411][110/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0109 (0.0241) Prec@1 99.000 (96.167) Prec@5 100.000 (99.750) +2022-11-14 16:54:11,103 Epoch: [411][120/500] Time 0.021 (0.018) Data 0.002 (0.004) Loss 0.0557 (0.0265) Prec@1 91.000 (95.769) Prec@5 100.000 (99.769) +2022-11-14 16:54:11,301 Epoch: [411][130/500] Time 0.018 (0.018) Data 0.002 (0.004) Loss 0.0465 (0.0280) Prec@1 92.000 (95.500) Prec@5 100.000 (99.786) +2022-11-14 16:54:11,501 Epoch: [411][140/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0417 (0.0289) Prec@1 93.000 (95.333) Prec@5 100.000 (99.800) +2022-11-14 16:54:11,754 Epoch: [411][150/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0350 (0.0293) Prec@1 95.000 (95.312) Prec@5 100.000 (99.812) +2022-11-14 16:54:12,040 Epoch: [411][160/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0316 (0.0294) Prec@1 95.000 (95.294) Prec@5 99.000 (99.765) +2022-11-14 16:54:12,332 Epoch: [411][170/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0173 (0.0287) Prec@1 97.000 (95.389) Prec@5 100.000 (99.778) +2022-11-14 16:54:12,630 Epoch: [411][180/500] Time 0.029 (0.019) Data 0.001 (0.003) Loss 0.0205 (0.0283) Prec@1 96.000 (95.421) Prec@5 100.000 (99.789) +2022-11-14 16:54:12,929 Epoch: [411][190/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0161 (0.0277) Prec@1 98.000 (95.550) Prec@5 100.000 (99.800) +2022-11-14 16:54:13,227 Epoch: [411][200/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0342 (0.0280) Prec@1 94.000 (95.476) Prec@5 100.000 (99.810) +2022-11-14 16:54:13,523 Epoch: [411][210/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0301 (0.0281) Prec@1 95.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 16:54:13,817 Epoch: [411][220/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0324 (0.0283) Prec@1 95.000 (95.435) Prec@5 100.000 (99.826) +2022-11-14 16:54:14,121 Epoch: [411][230/500] Time 0.033 (0.021) Data 0.002 (0.003) Loss 0.0214 (0.0280) Prec@1 96.000 (95.458) Prec@5 100.000 (99.833) +2022-11-14 16:54:14,411 Epoch: [411][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0209 (0.0277) Prec@1 97.000 (95.520) Prec@5 100.000 (99.840) +2022-11-14 16:54:14,702 Epoch: [411][250/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0212 (0.0275) Prec@1 97.000 (95.577) Prec@5 100.000 (99.846) +2022-11-14 16:54:14,988 Epoch: [411][260/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0273 (0.0274) Prec@1 96.000 (95.593) Prec@5 99.000 (99.815) +2022-11-14 16:54:15,271 Epoch: [411][270/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0089 (0.0268) Prec@1 99.000 (95.714) Prec@5 100.000 (99.821) +2022-11-14 16:54:15,558 Epoch: [411][280/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0346 (0.0271) Prec@1 95.000 (95.690) Prec@5 100.000 (99.828) +2022-11-14 16:54:15,843 Epoch: [411][290/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0460 (0.0277) Prec@1 93.000 (95.600) Prec@5 100.000 (99.833) +2022-11-14 16:54:16,131 Epoch: [411][300/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0269 (0.0277) Prec@1 96.000 (95.613) Prec@5 100.000 (99.839) +2022-11-14 16:54:16,423 Epoch: [411][310/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0272 (0.0276) Prec@1 96.000 (95.625) Prec@5 100.000 (99.844) +2022-11-14 16:54:16,709 Epoch: [411][320/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0377 (0.0279) Prec@1 93.000 (95.545) Prec@5 99.000 (99.818) +2022-11-14 16:54:16,992 Epoch: [411][330/500] Time 0.025 (0.022) Data 0.003 (0.002) Loss 0.0247 (0.0279) Prec@1 96.000 (95.559) Prec@5 100.000 (99.824) +2022-11-14 16:54:17,278 Epoch: [411][340/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0356 (0.0281) Prec@1 93.000 (95.486) Prec@5 100.000 (99.829) +2022-11-14 16:54:17,564 Epoch: [411][350/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0514 (0.0287) Prec@1 91.000 (95.361) Prec@5 100.000 (99.833) +2022-11-14 16:54:17,850 Epoch: [411][360/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0257 (0.0286) Prec@1 96.000 (95.378) Prec@5 100.000 (99.838) +2022-11-14 16:54:18,136 Epoch: [411][370/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0198 (0.0284) Prec@1 97.000 (95.421) Prec@5 100.000 (99.842) +2022-11-14 16:54:18,423 Epoch: [411][380/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0291 (0.0284) Prec@1 96.000 (95.436) Prec@5 100.000 (99.846) +2022-11-14 16:54:18,706 Epoch: [411][390/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0395 (0.0287) Prec@1 94.000 (95.400) Prec@5 100.000 (99.850) +2022-11-14 16:54:18,990 Epoch: [411][400/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0311 (0.0288) Prec@1 95.000 (95.390) Prec@5 100.000 (99.854) +2022-11-14 16:54:19,279 Epoch: [411][410/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0435 (0.0291) Prec@1 94.000 (95.357) Prec@5 100.000 (99.857) +2022-11-14 16:54:19,562 Epoch: [411][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0278 (0.0291) Prec@1 96.000 (95.372) Prec@5 100.000 (99.860) +2022-11-14 16:54:19,846 Epoch: [411][430/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0689 (0.0300) Prec@1 91.000 (95.273) Prec@5 99.000 (99.841) +2022-11-14 16:54:20,128 Epoch: [411][440/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0307 (0.0300) Prec@1 94.000 (95.244) Prec@5 100.000 (99.844) +2022-11-14 16:54:20,411 Epoch: [411][450/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0167 (0.0297) Prec@1 98.000 (95.304) Prec@5 100.000 (99.848) +2022-11-14 16:54:20,690 Epoch: [411][460/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0210 (0.0295) Prec@1 97.000 (95.340) Prec@5 100.000 (99.851) +2022-11-14 16:54:20,972 Epoch: [411][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0254 (0.0294) Prec@1 95.000 (95.333) Prec@5 100.000 (99.854) +2022-11-14 16:54:21,255 Epoch: [411][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0300 (0.0295) Prec@1 94.000 (95.306) Prec@5 100.000 (99.857) +2022-11-14 16:54:21,537 Epoch: [411][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0345 (0.0296) Prec@1 95.000 (95.300) Prec@5 100.000 (99.860) +2022-11-14 16:54:21,793 Epoch: [411][499/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0369 (0.0297) Prec@1 95.000 (95.294) Prec@5 100.000 (99.863) +2022-11-14 16:54:22,092 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0656 (0.0656) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:22,099 Test: [1/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0671) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 16:54:22,106 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0700) Prec@1 88.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 16:54:22,115 Test: [3/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0732) Prec@1 89.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 16:54:22,122 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0694) Prec@1 91.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:54:22,128 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0443 (0.0652) Prec@1 93.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 16:54:22,135 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0641) Prec@1 89.000 (89.571) Prec@5 100.000 (99.714) +2022-11-14 16:54:22,144 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0683) Prec@1 85.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 16:54:22,151 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0696) Prec@1 89.000 (89.000) Prec@5 99.000 (99.444) +2022-11-14 16:54:22,158 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0687) Prec@1 92.000 (89.300) Prec@5 99.000 (99.400) +2022-11-14 16:54:22,166 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0679) Prec@1 91.000 (89.455) Prec@5 100.000 (99.455) +2022-11-14 16:54:22,173 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0698) Prec@1 87.000 (89.250) Prec@5 99.000 (99.417) +2022-11-14 16:54:22,181 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0682) Prec@1 94.000 (89.615) Prec@5 100.000 (99.462) +2022-11-14 16:54:22,189 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0692) Prec@1 84.000 (89.214) Prec@5 98.000 (99.357) +2022-11-14 16:54:22,197 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0701) Prec@1 87.000 (89.067) Prec@5 99.000 (99.333) +2022-11-14 16:54:22,204 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0692) Prec@1 92.000 (89.250) Prec@5 100.000 (99.375) +2022-11-14 16:54:22,212 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0684) Prec@1 92.000 (89.412) Prec@5 97.000 (99.235) +2022-11-14 16:54:22,220 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1245 (0.0715) Prec@1 79.000 (88.833) Prec@5 99.000 (99.222) +2022-11-14 16:54:22,228 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0728) Prec@1 85.000 (88.632) Prec@5 96.000 (99.053) +2022-11-14 16:54:22,237 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0735) Prec@1 85.000 (88.450) Prec@5 97.000 (98.950) +2022-11-14 16:54:22,245 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0726) Prec@1 92.000 (88.619) Prec@5 100.000 (99.000) +2022-11-14 16:54:22,253 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0735) Prec@1 87.000 (88.545) Prec@5 98.000 (98.955) +2022-11-14 16:54:22,260 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0747) Prec@1 85.000 (88.391) Prec@5 97.000 (98.870) +2022-11-14 16:54:22,268 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0743) Prec@1 92.000 (88.542) Prec@5 100.000 (98.917) +2022-11-14 16:54:22,276 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0739) Prec@1 91.000 (88.640) Prec@5 100.000 (98.960) +2022-11-14 16:54:22,284 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0746) Prec@1 86.000 (88.538) Prec@5 98.000 (98.923) +2022-11-14 16:54:22,291 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0402 (0.0733) Prec@1 95.000 (88.778) Prec@5 100.000 (98.963) +2022-11-14 16:54:22,299 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0731) Prec@1 90.000 (88.821) Prec@5 100.000 (99.000) +2022-11-14 16:54:22,307 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0734) Prec@1 87.000 (88.759) Prec@5 99.000 (99.000) +2022-11-14 16:54:22,314 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0736) Prec@1 87.000 (88.700) Prec@5 98.000 (98.967) +2022-11-14 16:54:22,322 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0740) Prec@1 83.000 (88.516) Prec@5 100.000 (99.000) +2022-11-14 16:54:22,329 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0744) Prec@1 86.000 (88.438) Prec@5 99.000 (99.000) +2022-11-14 16:54:22,337 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0741) Prec@1 90.000 (88.485) Prec@5 100.000 (99.030) +2022-11-14 16:54:22,345 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0742) Prec@1 87.000 (88.441) Prec@5 100.000 (99.059) +2022-11-14 16:54:22,352 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0742) Prec@1 90.000 (88.486) Prec@5 98.000 (99.029) +2022-11-14 16:54:22,360 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0740) Prec@1 90.000 (88.528) Prec@5 100.000 (99.056) +2022-11-14 16:54:22,368 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0739) Prec@1 89.000 (88.541) Prec@5 99.000 (99.054) +2022-11-14 16:54:22,376 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1040 (0.0747) Prec@1 85.000 (88.447) Prec@5 99.000 (99.053) +2022-11-14 16:54:22,383 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0619 (0.0744) Prec@1 90.000 (88.487) Prec@5 99.000 (99.051) +2022-11-14 16:54:22,391 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0738) Prec@1 91.000 (88.550) Prec@5 99.000 (99.050) +2022-11-14 16:54:22,399 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0974 (0.0744) Prec@1 85.000 (88.463) Prec@5 100.000 (99.073) +2022-11-14 16:54:22,406 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0746) Prec@1 88.000 (88.452) Prec@5 97.000 (99.024) +2022-11-14 16:54:22,414 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0547 (0.0742) Prec@1 89.000 (88.465) Prec@5 100.000 (99.047) +2022-11-14 16:54:22,421 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0740) Prec@1 90.000 (88.500) Prec@5 98.000 (99.023) +2022-11-14 16:54:22,429 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0739) Prec@1 90.000 (88.533) Prec@5 98.000 (99.000) +2022-11-14 16:54:22,437 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1076 (0.0746) Prec@1 82.000 (88.391) Prec@5 100.000 (99.022) +2022-11-14 16:54:22,444 Test: [46/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0745) Prec@1 88.000 (88.383) Prec@5 100.000 (99.043) +2022-11-14 16:54:22,452 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0852 (0.0748) Prec@1 86.000 (88.333) Prec@5 98.000 (99.021) +2022-11-14 16:54:22,460 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0466 (0.0742) Prec@1 92.000 (88.408) Prec@5 100.000 (99.041) +2022-11-14 16:54:22,468 Test: [49/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1126 (0.0749) Prec@1 81.000 (88.260) Prec@5 100.000 (99.060) +2022-11-14 16:54:22,475 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0709 (0.0749) Prec@1 91.000 (88.314) Prec@5 100.000 (99.078) +2022-11-14 16:54:22,483 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0841 (0.0750) Prec@1 82.000 (88.192) Prec@5 100.000 (99.096) +2022-11-14 16:54:22,491 Test: [52/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0509 (0.0746) Prec@1 92.000 (88.264) Prec@5 100.000 (99.113) +2022-11-14 16:54:22,499 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0582 (0.0743) Prec@1 91.000 (88.315) Prec@5 98.000 (99.093) +2022-11-14 16:54:22,506 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0746) Prec@1 84.000 (88.236) Prec@5 100.000 (99.109) +2022-11-14 16:54:22,514 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0777 (0.0746) Prec@1 89.000 (88.250) Prec@5 99.000 (99.107) +2022-11-14 16:54:22,521 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0631 (0.0744) Prec@1 89.000 (88.263) Prec@5 100.000 (99.123) +2022-11-14 16:54:22,529 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0742) Prec@1 91.000 (88.310) Prec@5 98.000 (99.103) +2022-11-14 16:54:22,537 Test: [58/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0744) Prec@1 85.000 (88.254) Prec@5 100.000 (99.119) +2022-11-14 16:54:22,544 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0746) Prec@1 82.000 (88.150) Prec@5 100.000 (99.133) +2022-11-14 16:54:22,552 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0748) Prec@1 86.000 (88.115) Prec@5 99.000 (99.131) +2022-11-14 16:54:22,560 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0572 (0.0745) Prec@1 90.000 (88.145) Prec@5 99.000 (99.129) +2022-11-14 16:54:22,568 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0700 (0.0744) Prec@1 87.000 (88.127) Prec@5 99.000 (99.127) +2022-11-14 16:54:22,576 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0298 (0.0737) Prec@1 93.000 (88.203) Prec@5 100.000 (99.141) +2022-11-14 16:54:22,583 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0937 (0.0740) Prec@1 86.000 (88.169) Prec@5 100.000 (99.154) +2022-11-14 16:54:22,591 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0741) Prec@1 88.000 (88.167) Prec@5 99.000 (99.152) +2022-11-14 16:54:22,598 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0300 (0.0734) Prec@1 95.000 (88.269) Prec@5 100.000 (99.164) +2022-11-14 16:54:22,606 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0656 (0.0733) Prec@1 90.000 (88.294) Prec@5 100.000 (99.176) +2022-11-14 16:54:22,613 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0924 (0.0736) Prec@1 84.000 (88.232) Prec@5 99.000 (99.174) +2022-11-14 16:54:22,621 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0630 (0.0735) Prec@1 90.000 (88.257) Prec@5 100.000 (99.186) +2022-11-14 16:54:22,629 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0737) Prec@1 86.000 (88.225) Prec@5 100.000 (99.197) +2022-11-14 16:54:22,636 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0462 (0.0733) Prec@1 93.000 (88.292) Prec@5 99.000 (99.194) +2022-11-14 16:54:22,644 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0480 (0.0730) Prec@1 92.000 (88.342) Prec@5 99.000 (99.192) +2022-11-14 16:54:22,652 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0331 (0.0724) Prec@1 95.000 (88.432) Prec@5 100.000 (99.203) +2022-11-14 16:54:22,659 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0994 (0.0728) Prec@1 83.000 (88.360) Prec@5 99.000 (99.200) +2022-11-14 16:54:22,667 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0479 (0.0725) Prec@1 94.000 (88.434) Prec@5 99.000 (99.197) +2022-11-14 16:54:22,675 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0726) Prec@1 89.000 (88.442) Prec@5 99.000 (99.195) +2022-11-14 16:54:22,682 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1083 (0.0731) Prec@1 85.000 (88.397) Prec@5 100.000 (99.205) +2022-11-14 16:54:22,690 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0761 (0.0731) Prec@1 88.000 (88.392) Prec@5 100.000 (99.215) +2022-11-14 16:54:22,698 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0732) Prec@1 84.000 (88.338) Prec@5 100.000 (99.225) +2022-11-14 16:54:22,705 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0979 (0.0735) Prec@1 84.000 (88.284) Prec@5 98.000 (99.210) +2022-11-14 16:54:22,714 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0735) Prec@1 89.000 (88.293) Prec@5 98.000 (99.195) +2022-11-14 16:54:22,721 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0952 (0.0738) Prec@1 87.000 (88.277) Prec@5 99.000 (99.193) +2022-11-14 16:54:22,729 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0739) Prec@1 86.000 (88.250) Prec@5 99.000 (99.190) +2022-11-14 16:54:22,736 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0967 (0.0742) Prec@1 82.000 (88.176) Prec@5 99.000 (99.188) +2022-11-14 16:54:22,744 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1144 (0.0746) Prec@1 81.000 (88.093) Prec@5 100.000 (99.198) +2022-11-14 16:54:22,752 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0699 (0.0746) Prec@1 87.000 (88.080) Prec@5 100.000 (99.207) +2022-11-14 16:54:22,760 Test: [87/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0749) Prec@1 84.000 (88.034) Prec@5 99.000 (99.205) +2022-11-14 16:54:22,768 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0764 (0.0749) Prec@1 85.000 (88.000) Prec@5 100.000 (99.213) +2022-11-14 16:54:22,776 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0748) Prec@1 88.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 16:54:22,783 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0746) Prec@1 92.000 (88.044) Prec@5 99.000 (99.220) +2022-11-14 16:54:22,791 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0388 (0.0742) Prec@1 95.000 (88.120) Prec@5 99.000 (99.217) +2022-11-14 16:54:22,799 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0787 (0.0742) Prec@1 86.000 (88.097) Prec@5 100.000 (99.226) +2022-11-14 16:54:22,806 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0681 (0.0742) Prec@1 90.000 (88.117) Prec@5 99.000 (99.223) +2022-11-14 16:54:22,814 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1034 (0.0745) Prec@1 85.000 (88.084) Prec@5 100.000 (99.232) +2022-11-14 16:54:22,821 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0789 (0.0745) Prec@1 88.000 (88.083) Prec@5 98.000 (99.219) +2022-11-14 16:54:22,829 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0545 (0.0743) Prec@1 91.000 (88.113) Prec@5 99.000 (99.216) +2022-11-14 16:54:22,836 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0800 (0.0744) Prec@1 87.000 (88.102) Prec@5 99.000 (99.214) +2022-11-14 16:54:22,844 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0896 (0.0745) Prec@1 84.000 (88.061) Prec@5 99.000 (99.212) +2022-11-14 16:54:22,851 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0589 (0.0744) Prec@1 92.000 (88.100) Prec@5 99.000 (99.210) +2022-11-14 16:54:22,905 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:54:23,225 Epoch: [412][0/500] Time 0.022 (0.022) Data 0.244 (0.244) Loss 0.0289 (0.0289) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:23,416 Epoch: [412][10/500] Time 0.017 (0.017) Data 0.002 (0.024) Loss 0.0212 (0.0251) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:54:23,608 Epoch: [412][20/500] Time 0.015 (0.017) Data 0.002 (0.013) Loss 0.0258 (0.0253) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:23,804 Epoch: [412][30/500] Time 0.016 (0.017) Data 0.002 (0.009) Loss 0.0278 (0.0259) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:54:23,990 Epoch: [412][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0452 (0.0298) Prec@1 94.000 (94.400) Prec@5 99.000 (99.800) +2022-11-14 16:54:24,179 Epoch: [412][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0286 (0.0296) Prec@1 96.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 16:54:24,363 Epoch: [412][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0108 (0.0269) Prec@1 99.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:54:24,548 Epoch: [412][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0231 (0.0264) Prec@1 95.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:54:24,732 Epoch: [412][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0414 (0.0281) Prec@1 93.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 16:54:24,918 Epoch: [412][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0252 (0.0278) Prec@1 97.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 16:54:25,127 Epoch: [412][100/500] Time 0.025 (0.017) Data 0.002 (0.004) Loss 0.0416 (0.0291) Prec@1 91.000 (94.818) Prec@5 99.000 (99.818) +2022-11-14 16:54:25,395 Epoch: [412][110/500] Time 0.026 (0.017) Data 0.002 (0.004) Loss 0.0219 (0.0285) Prec@1 96.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 16:54:25,671 Epoch: [412][120/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0177 (0.0276) Prec@1 96.000 (95.000) Prec@5 100.000 (99.846) +2022-11-14 16:54:25,947 Epoch: [412][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0265 (0.0275) Prec@1 96.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 16:54:26,227 Epoch: [412][140/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0198 (0.0270) Prec@1 97.000 (95.200) Prec@5 100.000 (99.867) +2022-11-14 16:54:26,511 Epoch: [412][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0190 (0.0265) Prec@1 98.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:54:26,789 Epoch: [412][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0173 (0.0260) Prec@1 98.000 (95.529) Prec@5 100.000 (99.882) +2022-11-14 16:54:27,072 Epoch: [412][170/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0158 (0.0254) Prec@1 98.000 (95.667) Prec@5 100.000 (99.889) +2022-11-14 16:54:27,358 Epoch: [412][180/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0213 (0.0252) Prec@1 96.000 (95.684) Prec@5 100.000 (99.895) +2022-11-14 16:54:27,640 Epoch: [412][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0435 (0.0261) Prec@1 94.000 (95.600) Prec@5 100.000 (99.900) +2022-11-14 16:54:27,924 Epoch: [412][200/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0460 (0.0271) Prec@1 92.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 16:54:28,208 Epoch: [412][210/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0273 (0.0271) Prec@1 94.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 16:54:28,495 Epoch: [412][220/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0244 (0.0270) Prec@1 96.000 (95.391) Prec@5 100.000 (99.913) +2022-11-14 16:54:28,772 Epoch: [412][230/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0412 (0.0276) Prec@1 93.000 (95.292) Prec@5 100.000 (99.917) +2022-11-14 16:54:29,051 Epoch: [412][240/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0343 (0.0278) Prec@1 95.000 (95.280) Prec@5 99.000 (99.880) +2022-11-14 16:54:29,329 Epoch: [412][250/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0459 (0.0285) Prec@1 91.000 (95.115) Prec@5 100.000 (99.885) +2022-11-14 16:54:29,608 Epoch: [412][260/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0431 (0.0291) Prec@1 93.000 (95.037) Prec@5 99.000 (99.852) +2022-11-14 16:54:29,882 Epoch: [412][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0462 (0.0297) Prec@1 92.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 16:54:30,164 Epoch: [412][280/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0206 (0.0294) Prec@1 97.000 (95.000) Prec@5 100.000 (99.862) +2022-11-14 16:54:30,435 Epoch: [412][290/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0187 (0.0290) Prec@1 96.000 (95.033) Prec@5 100.000 (99.867) +2022-11-14 16:54:30,707 Epoch: [412][300/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0391 (0.0293) Prec@1 92.000 (94.935) Prec@5 100.000 (99.871) +2022-11-14 16:54:30,981 Epoch: [412][310/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0356 (0.0295) Prec@1 94.000 (94.906) Prec@5 100.000 (99.875) +2022-11-14 16:54:31,261 Epoch: [412][320/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0395 (0.0298) Prec@1 92.000 (94.818) Prec@5 99.000 (99.848) +2022-11-14 16:54:31,538 Epoch: [412][330/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0393 (0.0301) Prec@1 94.000 (94.794) Prec@5 100.000 (99.853) +2022-11-14 16:54:31,812 Epoch: [412][340/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0270 (0.0300) Prec@1 94.000 (94.771) Prec@5 100.000 (99.857) +2022-11-14 16:54:32,087 Epoch: [412][350/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0414 (0.0303) Prec@1 94.000 (94.750) Prec@5 99.000 (99.833) +2022-11-14 16:54:32,361 Epoch: [412][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0510 (0.0309) Prec@1 91.000 (94.649) Prec@5 99.000 (99.811) +2022-11-14 16:54:32,636 Epoch: [412][370/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0311 (0.0309) Prec@1 94.000 (94.632) Prec@5 100.000 (99.816) +2022-11-14 16:54:32,907 Epoch: [412][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0266 (0.0308) Prec@1 97.000 (94.692) Prec@5 100.000 (99.821) +2022-11-14 16:54:33,189 Epoch: [412][390/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0422 (0.0311) Prec@1 92.000 (94.625) Prec@5 99.000 (99.800) +2022-11-14 16:54:33,464 Epoch: [412][400/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0208 (0.0308) Prec@1 96.000 (94.659) Prec@5 100.000 (99.805) +2022-11-14 16:54:33,741 Epoch: [412][410/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0292 (0.0308) Prec@1 97.000 (94.714) Prec@5 99.000 (99.786) +2022-11-14 16:54:34,011 Epoch: [412][420/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0231 (0.0306) Prec@1 97.000 (94.767) Prec@5 100.000 (99.791) +2022-11-14 16:54:34,284 Epoch: [412][430/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0540 (0.0311) Prec@1 90.000 (94.659) Prec@5 98.000 (99.750) +2022-11-14 16:54:34,552 Epoch: [412][440/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0219 (0.0309) Prec@1 96.000 (94.689) Prec@5 100.000 (99.756) +2022-11-14 16:54:34,822 Epoch: [412][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0226 (0.0307) Prec@1 96.000 (94.717) Prec@5 100.000 (99.761) +2022-11-14 16:54:35,096 Epoch: [412][460/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0279 (0.0307) Prec@1 97.000 (94.766) Prec@5 100.000 (99.766) +2022-11-14 16:54:35,366 Epoch: [412][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0246 (0.0306) Prec@1 96.000 (94.792) Prec@5 100.000 (99.771) +2022-11-14 16:54:35,638 Epoch: [412][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0263 (0.0305) Prec@1 96.000 (94.816) Prec@5 99.000 (99.755) +2022-11-14 16:54:35,911 Epoch: [412][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0567 (0.0310) Prec@1 92.000 (94.760) Prec@5 100.000 (99.760) +2022-11-14 16:54:36,160 Epoch: [412][499/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0241 (0.0309) Prec@1 94.000 (94.745) Prec@5 100.000 (99.765) +2022-11-14 16:54:36,461 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0637 (0.0637) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:36,471 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0882 (0.0759) Prec@1 85.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 16:54:36,478 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0730) Prec@1 89.000 (87.333) Prec@5 100.000 (100.000) +2022-11-14 16:54:36,486 Test: [3/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0737) Prec@1 88.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 16:54:36,493 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0727) Prec@1 87.000 (87.400) Prec@5 100.000 (99.800) +2022-11-14 16:54:36,500 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0714) Prec@1 91.000 (88.000) Prec@5 100.000 (99.833) +2022-11-14 16:54:36,507 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0718) Prec@1 89.000 (88.143) Prec@5 98.000 (99.571) +2022-11-14 16:54:36,515 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0719) Prec@1 87.000 (88.000) Prec@5 100.000 (99.625) +2022-11-14 16:54:36,522 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0722) Prec@1 87.000 (87.889) Prec@5 100.000 (99.667) +2022-11-14 16:54:36,530 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0725) Prec@1 88.000 (87.900) Prec@5 99.000 (99.600) +2022-11-14 16:54:36,537 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0714) Prec@1 91.000 (88.182) Prec@5 99.000 (99.545) +2022-11-14 16:54:36,545 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0738) Prec@1 85.000 (87.917) Prec@5 99.000 (99.500) +2022-11-14 16:54:36,553 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0730) Prec@1 90.000 (88.077) Prec@5 100.000 (99.538) +2022-11-14 16:54:36,560 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0731) Prec@1 89.000 (88.143) Prec@5 100.000 (99.571) +2022-11-14 16:54:36,568 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0733) Prec@1 89.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 16:54:36,575 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0736) Prec@1 88.000 (88.188) Prec@5 99.000 (99.562) +2022-11-14 16:54:36,583 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0733) Prec@1 90.000 (88.294) Prec@5 99.000 (99.529) +2022-11-14 16:54:36,590 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0747) Prec@1 85.000 (88.111) Prec@5 97.000 (99.389) +2022-11-14 16:54:36,598 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0761) Prec@1 82.000 (87.789) Prec@5 98.000 (99.316) +2022-11-14 16:54:36,605 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0768) Prec@1 83.000 (87.550) Prec@5 99.000 (99.300) +2022-11-14 16:54:36,613 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0778) Prec@1 83.000 (87.333) Prec@5 99.000 (99.286) +2022-11-14 16:54:36,621 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0779) Prec@1 87.000 (87.318) Prec@5 99.000 (99.273) +2022-11-14 16:54:36,628 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0790) Prec@1 85.000 (87.217) Prec@5 98.000 (99.217) +2022-11-14 16:54:36,636 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0787) Prec@1 89.000 (87.292) Prec@5 99.000 (99.208) +2022-11-14 16:54:36,643 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0785) Prec@1 88.000 (87.320) Prec@5 100.000 (99.240) +2022-11-14 16:54:36,651 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1029 (0.0795) Prec@1 87.000 (87.308) Prec@5 98.000 (99.192) +2022-11-14 16:54:36,659 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0787) Prec@1 91.000 (87.444) Prec@5 100.000 (99.222) +2022-11-14 16:54:36,666 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0782) Prec@1 90.000 (87.536) Prec@5 100.000 (99.250) +2022-11-14 16:54:36,674 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0776) Prec@1 89.000 (87.586) Prec@5 99.000 (99.241) +2022-11-14 16:54:36,681 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0774) Prec@1 88.000 (87.600) Prec@5 99.000 (99.233) +2022-11-14 16:54:36,689 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0767) Prec@1 91.000 (87.710) Prec@5 99.000 (99.226) +2022-11-14 16:54:36,697 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0773) Prec@1 84.000 (87.594) Prec@5 98.000 (99.188) +2022-11-14 16:54:36,704 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0777) Prec@1 83.000 (87.455) Prec@5 100.000 (99.212) +2022-11-14 16:54:36,712 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1020 (0.0784) Prec@1 82.000 (87.294) Prec@5 99.000 (99.206) +2022-11-14 16:54:36,719 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0893 (0.0787) Prec@1 87.000 (87.286) Prec@5 97.000 (99.143) +2022-11-14 16:54:36,727 Test: [35/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0789) Prec@1 87.000 (87.278) Prec@5 99.000 (99.139) +2022-11-14 16:54:36,734 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0693 (0.0786) Prec@1 87.000 (87.270) Prec@5 99.000 (99.135) +2022-11-14 16:54:36,742 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1064 (0.0794) Prec@1 85.000 (87.211) Prec@5 100.000 (99.158) +2022-11-14 16:54:36,750 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0417 (0.0784) Prec@1 95.000 (87.410) Prec@5 99.000 (99.154) +2022-11-14 16:54:36,757 Test: [39/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0784) Prec@1 88.000 (87.425) Prec@5 100.000 (99.175) +2022-11-14 16:54:36,765 Test: [40/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0901 (0.0787) Prec@1 89.000 (87.463) Prec@5 98.000 (99.146) +2022-11-14 16:54:36,773 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0785) Prec@1 88.000 (87.476) Prec@5 98.000 (99.119) +2022-11-14 16:54:36,780 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0660 (0.0782) Prec@1 90.000 (87.535) Prec@5 100.000 (99.140) +2022-11-14 16:54:36,788 Test: [43/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0780) Prec@1 89.000 (87.568) Prec@5 98.000 (99.114) +2022-11-14 16:54:36,795 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0699 (0.0778) Prec@1 89.000 (87.600) Prec@5 98.000 (99.089) +2022-11-14 16:54:36,803 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0957 (0.0782) Prec@1 86.000 (87.565) Prec@5 99.000 (99.087) +2022-11-14 16:54:36,810 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0760 (0.0782) Prec@1 86.000 (87.532) Prec@5 99.000 (99.085) +2022-11-14 16:54:36,819 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0852 (0.0783) Prec@1 87.000 (87.521) Prec@5 98.000 (99.062) +2022-11-14 16:54:36,826 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0586 (0.0779) Prec@1 88.000 (87.531) Prec@5 100.000 (99.082) +2022-11-14 16:54:36,834 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1315 (0.0790) Prec@1 79.000 (87.360) Prec@5 100.000 (99.100) +2022-11-14 16:54:36,841 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0568 (0.0785) Prec@1 89.000 (87.392) Prec@5 100.000 (99.118) +2022-11-14 16:54:36,849 Test: [51/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0785) Prec@1 88.000 (87.404) Prec@5 98.000 (99.096) +2022-11-14 16:54:36,856 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0767 (0.0785) Prec@1 87.000 (87.396) Prec@5 99.000 (99.094) +2022-11-14 16:54:36,864 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0671 (0.0783) Prec@1 89.000 (87.426) Prec@5 100.000 (99.111) +2022-11-14 16:54:36,872 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0887 (0.0785) Prec@1 84.000 (87.364) Prec@5 100.000 (99.127) +2022-11-14 16:54:36,880 Test: [55/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0605 (0.0781) Prec@1 91.000 (87.429) Prec@5 99.000 (99.125) +2022-11-14 16:54:36,887 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0779) Prec@1 90.000 (87.474) Prec@5 100.000 (99.140) +2022-11-14 16:54:36,894 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0777) Prec@1 89.000 (87.500) Prec@5 99.000 (99.138) +2022-11-14 16:54:36,902 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1105 (0.0783) Prec@1 82.000 (87.407) Prec@5 100.000 (99.153) +2022-11-14 16:54:36,910 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0782) Prec@1 89.000 (87.433) Prec@5 100.000 (99.167) +2022-11-14 16:54:36,917 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0781) Prec@1 89.000 (87.459) Prec@5 99.000 (99.164) +2022-11-14 16:54:36,925 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0781) Prec@1 86.000 (87.435) Prec@5 99.000 (99.161) +2022-11-14 16:54:36,932 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0584 (0.0777) Prec@1 91.000 (87.492) Prec@5 100.000 (99.175) +2022-11-14 16:54:36,940 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0308 (0.0770) Prec@1 93.000 (87.578) Prec@5 100.000 (99.188) +2022-11-14 16:54:36,948 Test: [64/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1080 (0.0775) Prec@1 83.000 (87.508) Prec@5 99.000 (99.185) +2022-11-14 16:54:36,955 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0775) Prec@1 85.000 (87.470) Prec@5 99.000 (99.182) +2022-11-14 16:54:36,963 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0584 (0.0773) Prec@1 90.000 (87.507) Prec@5 100.000 (99.194) +2022-11-14 16:54:36,970 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0771) Prec@1 91.000 (87.559) Prec@5 100.000 (99.206) +2022-11-14 16:54:36,978 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0660 (0.0770) Prec@1 89.000 (87.580) Prec@5 99.000 (99.203) +2022-11-14 16:54:36,985 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0769) Prec@1 88.000 (87.586) Prec@5 98.000 (99.186) +2022-11-14 16:54:36,993 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0813 (0.0769) Prec@1 87.000 (87.577) Prec@5 99.000 (99.183) +2022-11-14 16:54:37,000 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0767) Prec@1 89.000 (87.597) Prec@5 100.000 (99.194) +2022-11-14 16:54:37,008 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0635 (0.0765) Prec@1 90.000 (87.630) Prec@5 100.000 (99.205) +2022-11-14 16:54:37,015 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0464 (0.0761) Prec@1 94.000 (87.716) Prec@5 100.000 (99.216) +2022-11-14 16:54:37,023 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0955 (0.0764) Prec@1 86.000 (87.693) Prec@5 99.000 (99.213) +2022-11-14 16:54:37,030 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0555 (0.0761) Prec@1 89.000 (87.711) Prec@5 100.000 (99.224) +2022-11-14 16:54:37,038 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0762) Prec@1 87.000 (87.701) Prec@5 98.000 (99.208) +2022-11-14 16:54:37,045 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0994 (0.0765) Prec@1 84.000 (87.654) Prec@5 98.000 (99.192) +2022-11-14 16:54:37,053 Test: [78/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0764) Prec@1 87.000 (87.646) Prec@5 100.000 (99.203) +2022-11-14 16:54:37,061 Test: [79/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0765) Prec@1 83.000 (87.588) Prec@5 100.000 (99.213) +2022-11-14 16:54:37,068 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0852 (0.0766) Prec@1 88.000 (87.593) Prec@5 98.000 (99.198) +2022-11-14 16:54:37,076 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0842 (0.0767) Prec@1 85.000 (87.561) Prec@5 99.000 (99.195) +2022-11-14 16:54:37,085 Test: [82/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0884 (0.0768) Prec@1 86.000 (87.542) Prec@5 100.000 (99.205) +2022-11-14 16:54:37,093 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0767) Prec@1 88.000 (87.548) Prec@5 99.000 (99.202) +2022-11-14 16:54:37,101 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0826 (0.0768) Prec@1 85.000 (87.518) Prec@5 100.000 (99.212) +2022-11-14 16:54:37,109 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1218 (0.0773) Prec@1 80.000 (87.430) Prec@5 99.000 (99.209) +2022-11-14 16:54:37,116 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0771) Prec@1 90.000 (87.460) Prec@5 100.000 (99.218) +2022-11-14 16:54:37,124 Test: [87/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0655 (0.0769) Prec@1 92.000 (87.511) Prec@5 98.000 (99.205) +2022-11-14 16:54:37,132 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0744 (0.0769) Prec@1 87.000 (87.506) Prec@5 100.000 (99.213) +2022-11-14 16:54:37,140 Test: [89/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0544 (0.0767) Prec@1 92.000 (87.556) Prec@5 99.000 (99.211) +2022-11-14 16:54:37,147 Test: [90/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0455 (0.0763) Prec@1 93.000 (87.615) Prec@5 100.000 (99.220) +2022-11-14 16:54:37,155 Test: [91/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0527 (0.0761) Prec@1 91.000 (87.652) Prec@5 99.000 (99.217) +2022-11-14 16:54:37,162 Test: [92/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0760) Prec@1 89.000 (87.667) Prec@5 100.000 (99.226) +2022-11-14 16:54:37,170 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0659 (0.0759) Prec@1 90.000 (87.691) Prec@5 99.000 (99.223) +2022-11-14 16:54:37,178 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0719 (0.0758) Prec@1 88.000 (87.695) Prec@5 100.000 (99.232) +2022-11-14 16:54:37,185 Test: [95/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0593 (0.0756) Prec@1 89.000 (87.708) Prec@5 100.000 (99.240) +2022-11-14 16:54:37,193 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0488 (0.0754) Prec@1 92.000 (87.753) Prec@5 99.000 (99.237) +2022-11-14 16:54:37,200 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0807 (0.0754) Prec@1 88.000 (87.755) Prec@5 98.000 (99.224) +2022-11-14 16:54:37,208 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0998 (0.0757) Prec@1 86.000 (87.737) Prec@5 98.000 (99.212) +2022-11-14 16:54:37,215 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0757) Prec@1 88.000 (87.740) Prec@5 97.000 (99.190) +2022-11-14 16:54:37,269 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:54:37,603 Epoch: [413][0/500] Time 0.023 (0.023) Data 0.253 (0.253) Loss 0.0318 (0.0318) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:37,807 Epoch: [413][10/500] Time 0.016 (0.018) Data 0.002 (0.025) Loss 0.0283 (0.0300) Prec@1 95.000 (94.500) Prec@5 99.000 (99.500) +2022-11-14 16:54:38,002 Epoch: [413][20/500] Time 0.016 (0.018) Data 0.002 (0.014) Loss 0.0297 (0.0299) Prec@1 95.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 16:54:38,202 Epoch: [413][30/500] Time 0.016 (0.018) Data 0.002 (0.010) Loss 0.0230 (0.0282) Prec@1 96.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:54:38,396 Epoch: [413][40/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0304 (0.0286) Prec@1 95.000 (95.000) Prec@5 99.000 (99.600) +2022-11-14 16:54:38,594 Epoch: [413][50/500] Time 0.016 (0.018) Data 0.002 (0.007) Loss 0.0134 (0.0261) Prec@1 99.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:54:38,787 Epoch: [413][60/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0400 (0.0281) Prec@1 93.000 (95.286) Prec@5 100.000 (99.714) +2022-11-14 16:54:38,985 Epoch: [413][70/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0347 (0.0289) Prec@1 95.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 16:54:39,181 Epoch: [413][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0322 (0.0293) Prec@1 95.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 16:54:39,368 Epoch: [413][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0237 (0.0287) Prec@1 95.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:54:39,558 Epoch: [413][100/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0100 (0.0270) Prec@1 98.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 16:54:39,750 Epoch: [413][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0369 (0.0278) Prec@1 95.000 (95.417) Prec@5 100.000 (99.833) +2022-11-14 16:54:39,941 Epoch: [413][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0414 (0.0289) Prec@1 95.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:54:40,140 Epoch: [413][130/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0364 (0.0294) Prec@1 94.000 (95.286) Prec@5 99.000 (99.786) +2022-11-14 16:54:40,333 Epoch: [413][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0239 (0.0290) Prec@1 97.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 16:54:40,529 Epoch: [413][150/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.0181 (0.0284) Prec@1 99.000 (95.625) Prec@5 100.000 (99.812) +2022-11-14 16:54:40,725 Epoch: [413][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0201 (0.0279) Prec@1 97.000 (95.706) Prec@5 100.000 (99.824) +2022-11-14 16:54:40,924 Epoch: [413][170/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0308 (0.0280) Prec@1 96.000 (95.722) Prec@5 100.000 (99.833) +2022-11-14 16:54:41,117 Epoch: [413][180/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0274 (0.0280) Prec@1 96.000 (95.737) Prec@5 100.000 (99.842) +2022-11-14 16:54:41,310 Epoch: [413][190/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0334 (0.0283) Prec@1 94.000 (95.650) Prec@5 100.000 (99.850) +2022-11-14 16:54:41,504 Epoch: [413][200/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0169 (0.0277) Prec@1 98.000 (95.762) Prec@5 100.000 (99.857) +2022-11-14 16:54:41,718 Epoch: [413][210/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0292 (0.0278) Prec@1 96.000 (95.773) Prec@5 99.000 (99.818) +2022-11-14 16:54:42,000 Epoch: [413][220/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0475 (0.0287) Prec@1 93.000 (95.652) Prec@5 99.000 (99.783) +2022-11-14 16:54:42,287 Epoch: [413][230/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0223 (0.0284) Prec@1 97.000 (95.708) Prec@5 100.000 (99.792) +2022-11-14 16:54:42,578 Epoch: [413][240/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0175 (0.0280) Prec@1 97.000 (95.760) Prec@5 100.000 (99.800) +2022-11-14 16:54:42,869 Epoch: [413][250/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0435 (0.0286) Prec@1 94.000 (95.692) Prec@5 100.000 (99.808) +2022-11-14 16:54:43,158 Epoch: [413][260/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0179 (0.0282) Prec@1 96.000 (95.704) Prec@5 100.000 (99.815) +2022-11-14 16:54:43,444 Epoch: [413][270/500] Time 0.022 (0.019) Data 0.002 (0.003) Loss 0.0183 (0.0278) Prec@1 96.000 (95.714) Prec@5 100.000 (99.821) +2022-11-14 16:54:43,736 Epoch: [413][280/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0386 (0.0282) Prec@1 94.000 (95.655) Prec@5 99.000 (99.793) +2022-11-14 16:54:44,032 Epoch: [413][290/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0224 (0.0280) Prec@1 97.000 (95.700) Prec@5 100.000 (99.800) +2022-11-14 16:54:44,332 Epoch: [413][300/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0163 (0.0276) Prec@1 97.000 (95.742) Prec@5 100.000 (99.806) +2022-11-14 16:54:44,611 Epoch: [413][310/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0121 (0.0271) Prec@1 98.000 (95.812) Prec@5 100.000 (99.812) +2022-11-14 16:54:44,896 Epoch: [413][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0456 (0.0277) Prec@1 91.000 (95.667) Prec@5 100.000 (99.818) +2022-11-14 16:54:45,193 Epoch: [413][330/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.0170 (0.0274) Prec@1 98.000 (95.735) Prec@5 100.000 (99.824) +2022-11-14 16:54:45,482 Epoch: [413][340/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0386 (0.0277) Prec@1 93.000 (95.657) Prec@5 99.000 (99.800) +2022-11-14 16:54:45,767 Epoch: [413][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0297 (0.0277) Prec@1 97.000 (95.694) Prec@5 100.000 (99.806) +2022-11-14 16:54:46,055 Epoch: [413][360/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0374 (0.0280) Prec@1 95.000 (95.676) Prec@5 100.000 (99.811) +2022-11-14 16:54:46,348 Epoch: [413][370/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0203 (0.0278) Prec@1 96.000 (95.684) Prec@5 100.000 (99.816) +2022-11-14 16:54:46,640 Epoch: [413][380/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0288 (0.0278) Prec@1 96.000 (95.692) Prec@5 99.000 (99.795) +2022-11-14 16:54:46,919 Epoch: [413][390/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0516 (0.0284) Prec@1 92.000 (95.600) Prec@5 99.000 (99.775) +2022-11-14 16:54:47,203 Epoch: [413][400/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0240 (0.0283) Prec@1 96.000 (95.610) Prec@5 100.000 (99.780) +2022-11-14 16:54:47,484 Epoch: [413][410/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0283) Prec@1 95.000 (95.595) Prec@5 100.000 (99.786) +2022-11-14 16:54:47,764 Epoch: [413][420/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0288 (0.0283) Prec@1 95.000 (95.581) Prec@5 100.000 (99.791) +2022-11-14 16:54:48,046 Epoch: [413][430/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0313 (0.0284) Prec@1 95.000 (95.568) Prec@5 100.000 (99.795) +2022-11-14 16:54:48,334 Epoch: [413][440/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0106 (0.0280) Prec@1 99.000 (95.644) Prec@5 100.000 (99.800) +2022-11-14 16:54:48,615 Epoch: [413][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0474 (0.0284) Prec@1 93.000 (95.587) Prec@5 100.000 (99.804) +2022-11-14 16:54:48,897 Epoch: [413][460/500] Time 0.029 (0.022) Data 0.001 (0.002) Loss 0.0284 (0.0284) Prec@1 96.000 (95.596) Prec@5 100.000 (99.809) +2022-11-14 16:54:49,181 Epoch: [413][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0299 (0.0284) Prec@1 95.000 (95.583) Prec@5 100.000 (99.812) +2022-11-14 16:54:49,468 Epoch: [413][480/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0219 (0.0283) Prec@1 97.000 (95.612) Prec@5 100.000 (99.816) +2022-11-14 16:54:49,748 Epoch: [413][490/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0316 (0.0284) Prec@1 96.000 (95.620) Prec@5 99.000 (99.800) +2022-11-14 16:54:50,000 Epoch: [413][499/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0319 (0.0284) Prec@1 95.000 (95.608) Prec@5 100.000 (99.804) +2022-11-14 16:54:50,298 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0883 (0.0883) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:50,306 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0705 (0.0794) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:50,316 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0919 (0.0835) Prec@1 85.000 (87.000) Prec@5 99.000 (99.667) +2022-11-14 16:54:50,325 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0828) Prec@1 90.000 (87.750) Prec@5 99.000 (99.500) +2022-11-14 16:54:50,331 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0795) Prec@1 87.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 16:54:50,338 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0388 (0.0727) Prec@1 92.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:54:50,345 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0699) Prec@1 94.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:54:50,353 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0720) Prec@1 84.000 (88.500) Prec@5 100.000 (99.750) +2022-11-14 16:54:50,360 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0727) Prec@1 88.000 (88.444) Prec@5 99.000 (99.667) +2022-11-14 16:54:50,367 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0741) Prec@1 84.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 16:54:50,374 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0724) Prec@1 90.000 (88.182) Prec@5 100.000 (99.545) +2022-11-14 16:54:50,382 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0723) Prec@1 87.000 (88.083) Prec@5 99.000 (99.500) +2022-11-14 16:54:50,389 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0708) Prec@1 91.000 (88.308) Prec@5 100.000 (99.538) +2022-11-14 16:54:50,398 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0709) Prec@1 89.000 (88.357) Prec@5 100.000 (99.571) +2022-11-14 16:54:50,406 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0720) Prec@1 86.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 16:54:50,413 Test: [15/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0848 (0.0728) Prec@1 84.000 (87.938) Prec@5 99.000 (99.562) +2022-11-14 16:54:50,421 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0376 (0.0708) Prec@1 95.000 (88.353) Prec@5 98.000 (99.471) +2022-11-14 16:54:50,428 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0723) Prec@1 83.000 (88.056) Prec@5 100.000 (99.500) +2022-11-14 16:54:50,436 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0845 (0.0729) Prec@1 85.000 (87.895) Prec@5 99.000 (99.474) +2022-11-14 16:54:50,443 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1003 (0.0743) Prec@1 87.000 (87.850) Prec@5 98.000 (99.400) +2022-11-14 16:54:50,451 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0741) Prec@1 88.000 (87.857) Prec@5 99.000 (99.381) +2022-11-14 16:54:50,459 Test: [21/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0827 (0.0745) Prec@1 86.000 (87.773) Prec@5 100.000 (99.409) +2022-11-14 16:54:50,467 Test: [22/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0932 (0.0753) Prec@1 87.000 (87.739) Prec@5 98.000 (99.348) +2022-11-14 16:54:50,474 Test: [23/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0755) Prec@1 87.000 (87.708) Prec@5 100.000 (99.375) +2022-11-14 16:54:50,482 Test: [24/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0753 (0.0755) Prec@1 88.000 (87.720) Prec@5 100.000 (99.400) +2022-11-14 16:54:50,489 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0764) Prec@1 84.000 (87.577) Prec@5 99.000 (99.385) +2022-11-14 16:54:50,497 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0552 (0.0756) Prec@1 90.000 (87.667) Prec@5 100.000 (99.407) +2022-11-14 16:54:50,506 Test: [27/100] Model Time 0.007 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0749) Prec@1 88.000 (87.679) Prec@5 100.000 (99.429) +2022-11-14 16:54:50,516 Test: [28/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0754) Prec@1 86.000 (87.621) Prec@5 98.000 (99.379) +2022-11-14 16:54:50,527 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0757) Prec@1 84.000 (87.500) Prec@5 99.000 (99.367) +2022-11-14 16:54:50,538 Test: [30/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0757) Prec@1 89.000 (87.548) Prec@5 100.000 (99.387) +2022-11-14 16:54:50,549 Test: [31/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0756) Prec@1 90.000 (87.625) Prec@5 99.000 (99.375) +2022-11-14 16:54:50,561 Test: [32/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0756) Prec@1 86.000 (87.576) Prec@5 98.000 (99.333) +2022-11-14 16:54:50,571 Test: [33/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0763) Prec@1 83.000 (87.441) Prec@5 100.000 (99.353) +2022-11-14 16:54:50,579 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0763) Prec@1 87.000 (87.429) Prec@5 98.000 (99.314) +2022-11-14 16:54:50,587 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0761) Prec@1 89.000 (87.472) Prec@5 99.000 (99.306) +2022-11-14 16:54:50,595 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0758) Prec@1 89.000 (87.514) Prec@5 99.000 (99.297) +2022-11-14 16:54:50,603 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0760) Prec@1 84.000 (87.421) Prec@5 99.000 (99.289) +2022-11-14 16:54:50,610 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0753) Prec@1 93.000 (87.564) Prec@5 99.000 (99.282) +2022-11-14 16:54:50,618 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0752) Prec@1 87.000 (87.550) Prec@5 99.000 (99.275) +2022-11-14 16:54:50,625 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0757) Prec@1 87.000 (87.537) Prec@5 98.000 (99.244) +2022-11-14 16:54:50,633 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0757) Prec@1 88.000 (87.548) Prec@5 100.000 (99.262) +2022-11-14 16:54:50,641 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0751) Prec@1 91.000 (87.628) Prec@5 100.000 (99.279) +2022-11-14 16:54:50,648 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0750) Prec@1 90.000 (87.682) Prec@5 98.000 (99.250) +2022-11-14 16:54:50,655 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0749) Prec@1 89.000 (87.711) Prec@5 98.000 (99.222) +2022-11-14 16:54:50,663 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0755) Prec@1 84.000 (87.630) Prec@5 99.000 (99.217) +2022-11-14 16:54:50,670 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0752) Prec@1 91.000 (87.702) Prec@5 100.000 (99.234) +2022-11-14 16:54:50,678 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0759) Prec@1 82.000 (87.583) Prec@5 99.000 (99.229) +2022-11-14 16:54:50,685 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0754) Prec@1 91.000 (87.653) Prec@5 100.000 (99.245) +2022-11-14 16:54:50,693 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1151 (0.0762) Prec@1 82.000 (87.540) Prec@5 100.000 (99.260) +2022-11-14 16:54:50,700 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0759) Prec@1 92.000 (87.627) Prec@5 100.000 (99.275) +2022-11-14 16:54:50,708 Test: 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0.0799 (0.0756) Prec@1 87.000 (87.672) Prec@5 99.000 (99.224) +2022-11-14 16:54:50,760 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0759) Prec@1 84.000 (87.610) Prec@5 100.000 (99.237) +2022-11-14 16:54:50,768 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0758) Prec@1 85.000 (87.567) Prec@5 100.000 (99.250) +2022-11-14 16:54:50,775 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0756) Prec@1 90.000 (87.607) Prec@5 100.000 (99.262) +2022-11-14 16:54:50,783 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0754) Prec@1 91.000 (87.661) Prec@5 99.000 (99.258) +2022-11-14 16:54:50,790 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0752) Prec@1 89.000 (87.683) Prec@5 100.000 (99.270) +2022-11-14 16:54:50,798 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0422 (0.0747) Prec@1 91.000 (87.734) Prec@5 99.000 (99.266) +2022-11-14 16:54:50,805 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0752) Prec@1 82.000 (87.646) Prec@5 100.000 (99.277) +2022-11-14 16:54:50,813 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0754) Prec@1 82.000 (87.561) Prec@5 99.000 (99.273) +2022-11-14 16:54:50,821 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0750) Prec@1 93.000 (87.642) Prec@5 100.000 (99.284) +2022-11-14 16:54:50,828 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0749) Prec@1 90.000 (87.676) Prec@5 99.000 (99.279) +2022-11-14 16:54:50,836 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0747) Prec@1 92.000 (87.739) Prec@5 99.000 (99.275) +2022-11-14 16:54:50,843 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0747) Prec@1 90.000 (87.771) Prec@5 100.000 (99.286) +2022-11-14 16:54:50,851 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0752) Prec@1 86.000 (87.746) Prec@5 99.000 (99.282) +2022-11-14 16:54:50,858 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0750) Prec@1 89.000 (87.764) Prec@5 99.000 (99.278) +2022-11-14 16:54:50,866 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0748) Prec@1 91.000 (87.808) Prec@5 98.000 (99.260) +2022-11-14 16:54:50,873 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0338 (0.0743) Prec@1 96.000 (87.919) Prec@5 100.000 (99.270) +2022-11-14 16:54:50,881 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0744) Prec@1 86.000 (87.893) Prec@5 100.000 (99.280) +2022-11-14 16:54:50,889 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0744) Prec@1 88.000 (87.895) Prec@5 99.000 (99.276) +2022-11-14 16:54:50,897 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0742) Prec@1 89.000 (87.909) Prec@5 99.000 (99.273) +2022-11-14 16:54:50,904 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0743) Prec@1 89.000 (87.923) Prec@5 97.000 (99.244) +2022-11-14 16:54:50,912 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0743) Prec@1 88.000 (87.924) Prec@5 100.000 (99.253) +2022-11-14 16:54:50,920 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0742) Prec@1 89.000 (87.938) Prec@5 100.000 (99.263) +2022-11-14 16:54:50,927 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0744) Prec@1 87.000 (87.926) Prec@5 98.000 (99.247) +2022-11-14 16:54:50,935 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0746) Prec@1 84.000 (87.878) Prec@5 100.000 (99.256) +2022-11-14 16:54:50,943 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0750) Prec@1 84.000 (87.831) Prec@5 99.000 (99.253) +2022-11-14 16:54:50,950 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0749) Prec@1 88.000 (87.833) Prec@5 99.000 (99.250) +2022-11-14 16:54:50,958 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0751) Prec@1 86.000 (87.812) Prec@5 98.000 (99.235) +2022-11-14 16:54:50,965 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0754) Prec@1 84.000 (87.767) Prec@5 100.000 (99.244) +2022-11-14 16:54:50,973 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0751) Prec@1 93.000 (87.828) Prec@5 100.000 (99.253) +2022-11-14 16:54:50,980 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0749) Prec@1 91.000 (87.864) Prec@5 98.000 (99.239) +2022-11-14 16:54:50,988 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0747) Prec@1 91.000 (87.899) Prec@5 100.000 (99.247) +2022-11-14 16:54:50,996 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0747) Prec@1 90.000 (87.922) Prec@5 99.000 (99.244) +2022-11-14 16:54:51,003 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0746) Prec@1 90.000 (87.945) Prec@5 99.000 (99.242) +2022-11-14 16:54:51,011 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0743) Prec@1 92.000 (87.989) Prec@5 99.000 (99.239) +2022-11-14 16:54:51,019 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0746) Prec@1 85.000 (87.957) Prec@5 100.000 (99.247) +2022-11-14 16:54:51,026 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0745) Prec@1 90.000 (87.979) Prec@5 98.000 (99.234) +2022-11-14 16:54:51,034 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0713 (0.0745) Prec@1 89.000 (87.989) Prec@5 100.000 (99.242) +2022-11-14 16:54:51,041 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0744) Prec@1 88.000 (87.990) Prec@5 99.000 (99.240) +2022-11-14 16:54:51,048 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0523 (0.0742) Prec@1 90.000 (88.010) Prec@5 99.000 (99.237) +2022-11-14 16:54:51,055 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0951 (0.0744) Prec@1 85.000 (87.980) Prec@5 98.000 (99.224) +2022-11-14 16:54:51,063 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0835 (0.0745) Prec@1 86.000 (87.960) Prec@5 100.000 (99.232) +2022-11-14 16:54:51,070 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0700 (0.0745) Prec@1 89.000 (87.970) Prec@5 99.000 (99.230) +2022-11-14 16:54:51,124 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:54:51,443 Epoch: [414][0/500] Time 0.027 (0.027) Data 0.240 (0.240) Loss 0.0267 (0.0267) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:51,643 Epoch: [414][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0223 (0.0245) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:51,832 Epoch: [414][20/500] Time 0.015 (0.017) Data 0.002 (0.013) Loss 0.0101 (0.0197) Prec@1 98.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,020 Epoch: [414][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0480 (0.0268) Prec@1 90.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,216 Epoch: [414][40/500] Time 0.018 (0.017) Data 0.002 (0.007) Loss 0.0124 (0.0239) Prec@1 99.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,416 Epoch: [414][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0292 (0.0248) Prec@1 96.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,608 Epoch: [414][60/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0458 (0.0278) Prec@1 94.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,797 Epoch: [414][70/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0285 (0.0279) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:54:52,993 Epoch: [414][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0188 (0.0269) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:54:53,193 Epoch: [414][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0203 (0.0262) Prec@1 96.000 (95.700) Prec@5 100.000 (100.000) +2022-11-14 16:54:53,386 Epoch: [414][100/500] Time 0.014 (0.017) Data 0.003 (0.004) Loss 0.0166 (0.0253) Prec@1 97.000 (95.818) Prec@5 100.000 (100.000) +2022-11-14 16:54:53,580 Epoch: [414][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0132 (0.0243) Prec@1 99.000 (96.083) Prec@5 100.000 (100.000) +2022-11-14 16:54:53,773 Epoch: [414][120/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0230 (0.0242) Prec@1 96.000 (96.077) Prec@5 99.000 (99.923) +2022-11-14 16:54:53,963 Epoch: [414][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0150 (0.0236) Prec@1 99.000 (96.286) Prec@5 100.000 (99.929) +2022-11-14 16:54:54,156 Epoch: [414][140/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0299 (0.0240) Prec@1 95.000 (96.200) Prec@5 100.000 (99.933) +2022-11-14 16:54:54,349 Epoch: [414][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0256 (0.0241) Prec@1 97.000 (96.250) Prec@5 100.000 (99.938) +2022-11-14 16:54:54,539 Epoch: [414][160/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0279 (0.0243) Prec@1 95.000 (96.176) Prec@5 100.000 (99.941) +2022-11-14 16:54:54,728 Epoch: [414][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0168 (0.0239) Prec@1 98.000 (96.278) Prec@5 100.000 (99.944) +2022-11-14 16:54:54,918 Epoch: [414][180/500] Time 0.015 (0.017) Data 0.001 (0.003) Loss 0.0377 (0.0246) Prec@1 93.000 (96.105) Prec@5 100.000 (99.947) +2022-11-14 16:54:55,110 Epoch: [414][190/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0210 (0.0244) Prec@1 97.000 (96.150) Prec@5 100.000 (99.950) +2022-11-14 16:54:55,361 Epoch: [414][200/500] Time 0.027 (0.017) Data 0.002 (0.003) Loss 0.0390 (0.0251) Prec@1 93.000 (96.000) Prec@5 100.000 (99.952) +2022-11-14 16:54:55,653 Epoch: [414][210/500] Time 0.032 (0.018) Data 0.002 (0.003) Loss 0.0426 (0.0259) Prec@1 93.000 (95.864) Prec@5 96.000 (99.773) +2022-11-14 16:54:55,943 Epoch: [414][220/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0242 (0.0259) Prec@1 97.000 (95.913) Prec@5 100.000 (99.783) +2022-11-14 16:54:56,236 Epoch: [414][230/500] Time 0.031 (0.018) Data 0.001 (0.003) Loss 0.0212 (0.0257) Prec@1 98.000 (96.000) Prec@5 100.000 (99.792) +2022-11-14 16:54:56,528 Epoch: [414][240/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0252 (0.0256) Prec@1 96.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 16:54:56,823 Epoch: [414][250/500] Time 0.031 (0.019) Data 0.002 (0.003) Loss 0.0548 (0.0268) Prec@1 91.000 (95.808) Prec@5 100.000 (99.808) +2022-11-14 16:54:57,121 Epoch: [414][260/500] Time 0.033 (0.019) Data 0.002 (0.003) Loss 0.0427 (0.0274) Prec@1 92.000 (95.667) Prec@5 100.000 (99.815) +2022-11-14 16:54:57,412 Epoch: [414][270/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0168 (0.0270) Prec@1 98.000 (95.750) Prec@5 100.000 (99.821) +2022-11-14 16:54:57,698 Epoch: [414][280/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0470 (0.0277) Prec@1 93.000 (95.655) Prec@5 99.000 (99.793) +2022-11-14 16:54:57,989 Epoch: [414][290/500] Time 0.032 (0.020) Data 0.002 (0.002) Loss 0.0369 (0.0280) Prec@1 93.000 (95.567) Prec@5 100.000 (99.800) +2022-11-14 16:54:58,289 Epoch: [414][300/500] Time 0.029 (0.020) Data 0.001 (0.002) Loss 0.0677 (0.0293) Prec@1 88.000 (95.323) Prec@5 100.000 (99.806) +2022-11-14 16:54:58,575 Epoch: [414][310/500] Time 0.031 (0.020) Data 0.001 (0.002) Loss 0.0223 (0.0290) Prec@1 97.000 (95.375) Prec@5 100.000 (99.812) +2022-11-14 16:54:58,855 Epoch: [414][320/500] Time 0.027 (0.020) Data 0.001 (0.002) Loss 0.0257 (0.0289) Prec@1 96.000 (95.394) Prec@5 100.000 (99.818) +2022-11-14 16:54:59,142 Epoch: [414][330/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0193 (0.0287) Prec@1 96.000 (95.412) Prec@5 100.000 (99.824) +2022-11-14 16:54:59,429 Epoch: [414][340/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0468 (0.0292) Prec@1 93.000 (95.343) Prec@5 100.000 (99.829) +2022-11-14 16:54:59,712 Epoch: [414][350/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0387 (0.0294) Prec@1 93.000 (95.278) Prec@5 99.000 (99.806) +2022-11-14 16:54:59,992 Epoch: [414][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0229 (0.0293) Prec@1 96.000 (95.297) Prec@5 100.000 (99.811) +2022-11-14 16:55:00,273 Epoch: [414][370/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0399 (0.0295) Prec@1 94.000 (95.263) Prec@5 100.000 (99.816) +2022-11-14 16:55:00,554 Epoch: [414][380/500] Time 0.028 (0.021) Data 0.001 (0.002) Loss 0.0396 (0.0298) Prec@1 94.000 (95.231) Prec@5 100.000 (99.821) +2022-11-14 16:55:00,838 Epoch: [414][390/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0306 (0.0298) Prec@1 95.000 (95.225) Prec@5 98.000 (99.775) +2022-11-14 16:55:01,124 Epoch: [414][400/500] Time 0.032 (0.021) Data 0.002 (0.002) Loss 0.0236 (0.0297) Prec@1 95.000 (95.220) Prec@5 100.000 (99.780) +2022-11-14 16:55:01,404 Epoch: [414][410/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0240 (0.0295) Prec@1 95.000 (95.214) Prec@5 100.000 (99.786) +2022-11-14 16:55:01,685 Epoch: [414][420/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0249 (0.0294) Prec@1 95.000 (95.209) Prec@5 100.000 (99.791) +2022-11-14 16:55:01,966 Epoch: [414][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0338 (0.0295) Prec@1 95.000 (95.205) Prec@5 100.000 (99.795) +2022-11-14 16:55:02,246 Epoch: [414][440/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0171 (0.0292) Prec@1 97.000 (95.244) Prec@5 100.000 (99.800) +2022-11-14 16:55:02,532 Epoch: [414][450/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0288 (0.0292) Prec@1 95.000 (95.239) Prec@5 100.000 (99.804) +2022-11-14 16:55:02,808 Epoch: [414][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0531 (0.0297) Prec@1 93.000 (95.191) Prec@5 100.000 (99.809) +2022-11-14 16:55:03,093 Epoch: [414][470/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0311 (0.0298) Prec@1 94.000 (95.167) Prec@5 100.000 (99.812) +2022-11-14 16:55:03,376 Epoch: [414][480/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0733 (0.0307) Prec@1 88.000 (95.020) Prec@5 98.000 (99.776) +2022-11-14 16:55:03,659 Epoch: [414][490/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0391 (0.0308) Prec@1 94.000 (95.000) Prec@5 100.000 (99.780) +2022-11-14 16:55:03,915 Epoch: [414][499/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0471 (0.0311) Prec@1 91.000 (94.922) Prec@5 100.000 (99.784) +2022-11-14 16:55:04,218 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0593 (0.0593) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:04,226 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0697) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:55:04,234 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0728) Prec@1 87.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 16:55:04,244 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0915 (0.0775) Prec@1 83.000 (86.750) Prec@5 100.000 (99.750) +2022-11-14 16:55:04,251 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0751) Prec@1 89.000 (87.200) Prec@5 100.000 (99.800) +2022-11-14 16:55:04,258 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0694) Prec@1 93.000 (88.167) Prec@5 100.000 (99.833) +2022-11-14 16:55:04,265 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0688) Prec@1 90.000 (88.429) Prec@5 99.000 (99.714) +2022-11-14 16:55:04,273 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0691) Prec@1 89.000 (88.500) Prec@5 99.000 (99.625) +2022-11-14 16:55:04,280 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0709) Prec@1 87.000 (88.333) Prec@5 97.000 (99.333) +2022-11-14 16:55:04,287 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0717) Prec@1 87.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 16:55:04,295 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0708) Prec@1 92.000 (88.545) Prec@5 100.000 (99.364) +2022-11-14 16:55:04,302 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0711) Prec@1 88.000 (88.500) Prec@5 100.000 (99.417) +2022-11-14 16:55:04,309 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0688) Prec@1 94.000 (88.923) Prec@5 100.000 (99.462) +2022-11-14 16:55:04,317 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0696) Prec@1 87.000 (88.786) Prec@5 98.000 (99.357) +2022-11-14 16:55:04,325 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0698) Prec@1 89.000 (88.800) Prec@5 100.000 (99.400) +2022-11-14 16:55:04,332 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0703) Prec@1 87.000 (88.688) Prec@5 100.000 (99.438) +2022-11-14 16:55:04,340 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0699) Prec@1 90.000 (88.765) Prec@5 99.000 (99.412) +2022-11-14 16:55:04,348 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1119 (0.0722) Prec@1 80.000 (88.278) Prec@5 100.000 (99.444) +2022-11-14 16:55:04,356 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0718) Prec@1 90.000 (88.368) Prec@5 100.000 (99.474) +2022-11-14 16:55:04,364 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0721) Prec@1 88.000 (88.350) Prec@5 98.000 (99.400) +2022-11-14 16:55:04,372 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0723) Prec@1 88.000 (88.333) Prec@5 100.000 (99.429) +2022-11-14 16:55:04,380 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0741) Prec@1 81.000 (88.000) Prec@5 99.000 (99.409) +2022-11-14 16:55:04,387 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0752) Prec@1 85.000 (87.870) Prec@5 98.000 (99.348) +2022-11-14 16:55:04,394 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0757) Prec@1 86.000 (87.792) Prec@5 100.000 (99.375) +2022-11-14 16:55:04,402 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0763) Prec@1 86.000 (87.720) Prec@5 100.000 (99.400) +2022-11-14 16:55:04,409 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0763) Prec@1 90.000 (87.808) Prec@5 98.000 (99.346) +2022-11-14 16:55:04,417 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0756) Prec@1 93.000 (88.000) Prec@5 100.000 (99.370) +2022-11-14 16:55:04,425 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0749) Prec@1 93.000 (88.179) Prec@5 99.000 (99.357) +2022-11-14 16:55:04,432 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0752) Prec@1 87.000 (88.138) Prec@5 98.000 (99.310) +2022-11-14 16:55:04,440 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0755) Prec@1 86.000 (88.067) Prec@5 100.000 (99.333) +2022-11-14 16:55:04,448 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0752) Prec@1 90.000 (88.129) Prec@5 100.000 (99.355) +2022-11-14 16:55:04,456 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0749) Prec@1 91.000 (88.219) Prec@5 99.000 (99.344) +2022-11-14 16:55:04,464 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0743) Prec@1 92.000 (88.333) Prec@5 100.000 (99.364) +2022-11-14 16:55:04,471 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0749) Prec@1 85.000 (88.235) Prec@5 99.000 (99.353) +2022-11-14 16:55:04,479 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0749) Prec@1 87.000 (88.200) Prec@5 98.000 (99.314) +2022-11-14 16:55:04,487 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0750) Prec@1 88.000 (88.194) Prec@5 98.000 (99.278) +2022-11-14 16:55:04,495 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0750) Prec@1 86.000 (88.135) Prec@5 98.000 (99.243) +2022-11-14 16:55:04,502 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0752) Prec@1 86.000 (88.079) Prec@5 99.000 (99.237) +2022-11-14 16:55:04,510 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0751) Prec@1 89.000 (88.103) Prec@5 100.000 (99.256) +2022-11-14 16:55:04,518 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0756) Prec@1 86.000 (88.050) Prec@5 100.000 (99.275) +2022-11-14 16:55:04,525 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0764) Prec@1 85.000 (87.976) Prec@5 98.000 (99.244) +2022-11-14 16:55:04,534 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0764) Prec@1 87.000 (87.952) Prec@5 99.000 (99.238) +2022-11-14 16:55:04,542 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0762) Prec@1 89.000 (87.977) Prec@5 100.000 (99.256) +2022-11-14 16:55:04,549 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0762) Prec@1 88.000 (87.977) Prec@5 99.000 (99.250) +2022-11-14 16:55:04,557 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0757) Prec@1 91.000 (88.044) Prec@5 99.000 (99.244) +2022-11-14 16:55:04,564 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1281 (0.0768) Prec@1 80.000 (87.870) Prec@5 97.000 (99.196) +2022-11-14 16:55:04,572 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0768) Prec@1 86.000 (87.830) Prec@5 100.000 (99.213) +2022-11-14 16:55:04,580 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0773) Prec@1 82.000 (87.708) Prec@5 99.000 (99.208) +2022-11-14 16:55:04,588 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0772) Prec@1 87.000 (87.694) Prec@5 100.000 (99.224) +2022-11-14 16:55:04,595 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0778) Prec@1 84.000 (87.620) Prec@5 99.000 (99.220) +2022-11-14 16:55:04,603 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0774) Prec@1 88.000 (87.627) Prec@5 100.000 (99.235) +2022-11-14 16:55:04,610 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0774) Prec@1 85.000 (87.577) Prec@5 100.000 (99.250) +2022-11-14 16:55:04,618 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0771) Prec@1 91.000 (87.642) Prec@5 100.000 (99.264) +2022-11-14 16:55:04,626 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0768) Prec@1 91.000 (87.704) Prec@5 100.000 (99.278) +2022-11-14 16:55:04,633 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0768) Prec@1 89.000 (87.727) Prec@5 100.000 (99.291) +2022-11-14 16:55:04,641 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0766) Prec@1 89.000 (87.750) Prec@5 99.000 (99.286) +2022-11-14 16:55:04,649 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0765) Prec@1 90.000 (87.789) Prec@5 100.000 (99.298) +2022-11-14 16:55:04,657 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0760) Prec@1 93.000 (87.879) Prec@5 98.000 (99.276) +2022-11-14 16:55:04,664 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0764) Prec@1 84.000 (87.814) Prec@5 99.000 (99.271) +2022-11-14 16:55:04,672 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0765) Prec@1 87.000 (87.800) Prec@5 100.000 (99.283) +2022-11-14 16:55:04,679 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0768) Prec@1 84.000 (87.738) Prec@5 99.000 (99.279) +2022-11-14 16:55:04,687 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0767) Prec@1 88.000 (87.742) Prec@5 100.000 (99.290) +2022-11-14 16:55:04,695 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0765) Prec@1 90.000 (87.778) Prec@5 100.000 (99.302) +2022-11-14 16:55:04,702 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0382 (0.0759) Prec@1 94.000 (87.875) Prec@5 100.000 (99.312) +2022-11-14 16:55:04,710 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0762) Prec@1 84.000 (87.815) Prec@5 99.000 (99.308) +2022-11-14 16:55:04,717 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0763) Prec@1 88.000 (87.818) Prec@5 100.000 (99.318) +2022-11-14 16:55:04,725 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0366 (0.0757) Prec@1 94.000 (87.910) Prec@5 100.000 (99.328) +2022-11-14 16:55:04,733 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0754) Prec@1 92.000 (87.971) Prec@5 100.000 (99.338) +2022-11-14 16:55:04,741 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0750) Prec@1 91.000 (88.014) Prec@5 99.000 (99.333) +2022-11-14 16:55:04,749 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0751) Prec@1 88.000 (88.014) Prec@5 100.000 (99.343) +2022-11-14 16:55:04,756 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0755) Prec@1 86.000 (87.986) Prec@5 99.000 (99.338) +2022-11-14 16:55:04,764 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0754) Prec@1 89.000 (88.000) Prec@5 100.000 (99.347) +2022-11-14 16:55:04,772 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0753) Prec@1 90.000 (88.027) Prec@5 99.000 (99.342) +2022-11-14 16:55:04,780 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0754) Prec@1 87.000 (88.014) Prec@5 100.000 (99.351) +2022-11-14 16:55:04,787 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0757) Prec@1 85.000 (87.973) Prec@5 99.000 (99.347) +2022-11-14 16:55:04,795 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0757) Prec@1 86.000 (87.947) Prec@5 100.000 (99.355) +2022-11-14 16:55:04,803 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0759) Prec@1 87.000 (87.935) Prec@5 100.000 (99.364) +2022-11-14 16:55:04,811 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0761) Prec@1 88.000 (87.936) Prec@5 100.000 (99.372) +2022-11-14 16:55:04,818 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0760) Prec@1 87.000 (87.924) Prec@5 100.000 (99.380) +2022-11-14 16:55:04,826 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0760) Prec@1 89.000 (87.938) Prec@5 100.000 (99.388) +2022-11-14 16:55:04,834 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0762) Prec@1 86.000 (87.914) Prec@5 99.000 (99.383) +2022-11-14 16:55:04,842 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0763) Prec@1 88.000 (87.915) Prec@5 98.000 (99.366) +2022-11-14 16:55:04,849 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0765) Prec@1 85.000 (87.880) Prec@5 99.000 (99.361) +2022-11-14 16:55:04,857 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0765) Prec@1 85.000 (87.845) Prec@5 100.000 (99.369) +2022-11-14 16:55:04,865 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0766) Prec@1 85.000 (87.812) Prec@5 100.000 (99.376) +2022-11-14 16:55:04,873 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0768) Prec@1 87.000 (87.802) Prec@5 100.000 (99.384) +2022-11-14 16:55:04,881 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0766) Prec@1 89.000 (87.816) Prec@5 100.000 (99.391) +2022-11-14 16:55:04,888 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0766) Prec@1 87.000 (87.807) Prec@5 98.000 (99.375) +2022-11-14 16:55:04,896 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0769) Prec@1 81.000 (87.730) Prec@5 100.000 (99.382) +2022-11-14 16:55:04,903 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0770) Prec@1 84.000 (87.689) Prec@5 99.000 (99.378) +2022-11-14 16:55:04,911 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0561 (0.0768) Prec@1 91.000 (87.725) Prec@5 100.000 (99.385) +2022-11-14 16:55:04,919 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0765) Prec@1 91.000 (87.761) Prec@5 100.000 (99.391) +2022-11-14 16:55:04,926 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0765) Prec@1 90.000 (87.785) Prec@5 99.000 (99.387) +2022-11-14 16:55:04,934 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0765) Prec@1 87.000 (87.777) Prec@5 100.000 (99.394) +2022-11-14 16:55:04,942 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0767) Prec@1 84.000 (87.737) Prec@5 100.000 (99.400) +2022-11-14 16:55:04,949 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0767) Prec@1 89.000 (87.750) Prec@5 99.000 (99.396) +2022-11-14 16:55:04,957 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0427 (0.0763) Prec@1 94.000 (87.814) Prec@5 99.000 (99.392) +2022-11-14 16:55:04,964 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0764) Prec@1 89.000 (87.827) Prec@5 97.000 (99.367) +2022-11-14 16:55:04,971 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0765) Prec@1 85.000 (87.798) Prec@5 98.000 (99.354) +2022-11-14 16:55:04,978 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0763) Prec@1 91.000 (87.830) Prec@5 100.000 (99.360) +2022-11-14 16:55:05,032 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:55:05,348 Epoch: [415][0/500] Time 0.025 (0.025) Data 0.234 (0.234) Loss 0.0309 (0.0309) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:05,544 Epoch: [415][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0147 (0.0228) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:05,736 Epoch: [415][20/500] Time 0.015 (0.017) Data 0.002 (0.013) Loss 0.0251 (0.0236) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:55:05,934 Epoch: [415][30/500] Time 0.015 (0.017) Data 0.002 (0.009) Loss 0.0504 (0.0303) Prec@1 94.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 16:55:06,124 Epoch: [415][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0104 (0.0263) Prec@1 100.000 (96.200) Prec@5 100.000 (100.000) +2022-11-14 16:55:06,312 Epoch: [415][50/500] Time 0.015 (0.017) Data 0.001 (0.006) Loss 0.0358 (0.0279) Prec@1 94.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:55:06,505 Epoch: [415][60/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0304 (0.0282) Prec@1 94.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 16:55:06,694 Epoch: [415][70/500] Time 0.015 (0.017) Data 0.001 (0.005) Loss 0.0188 (0.0271) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:55:06,881 Epoch: [415][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0298 (0.0274) Prec@1 95.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:55:07,069 Epoch: [415][90/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0210 (0.0267) Prec@1 98.000 (95.900) Prec@5 100.000 (100.000) +2022-11-14 16:55:07,257 Epoch: [415][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0190 (0.0260) Prec@1 96.000 (95.909) Prec@5 100.000 (100.000) +2022-11-14 16:55:07,444 Epoch: [415][110/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0296 (0.0263) Prec@1 95.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 16:55:07,631 Epoch: [415][120/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0493 (0.0281) Prec@1 91.000 (95.462) Prec@5 99.000 (99.923) +2022-11-14 16:55:07,864 Epoch: [415][130/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0235 (0.0278) Prec@1 95.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 16:55:08,116 Epoch: [415][140/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0317 (0.0280) Prec@1 95.000 (95.400) Prec@5 100.000 (99.933) +2022-11-14 16:55:08,367 Epoch: [415][150/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0389 (0.0287) Prec@1 93.000 (95.250) Prec@5 100.000 (99.938) +2022-11-14 16:55:08,621 Epoch: [415][160/500] Time 0.022 (0.018) Data 0.002 (0.003) Loss 0.0282 (0.0287) Prec@1 95.000 (95.235) Prec@5 100.000 (99.941) +2022-11-14 16:55:08,874 Epoch: [415][170/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0331 (0.0289) Prec@1 95.000 (95.222) Prec@5 100.000 (99.944) +2022-11-14 16:55:09,131 Epoch: [415][180/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0204 (0.0285) Prec@1 97.000 (95.316) Prec@5 100.000 (99.947) +2022-11-14 16:55:09,388 Epoch: [415][190/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0264 (0.0284) Prec@1 96.000 (95.350) Prec@5 100.000 (99.950) +2022-11-14 16:55:09,646 Epoch: [415][200/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0333 (0.0286) Prec@1 94.000 (95.286) Prec@5 100.000 (99.952) +2022-11-14 16:55:09,903 Epoch: [415][210/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0254 (0.0285) Prec@1 95.000 (95.273) Prec@5 100.000 (99.955) +2022-11-14 16:55:10,164 Epoch: [415][220/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0299 (0.0285) Prec@1 96.000 (95.304) Prec@5 99.000 (99.913) +2022-11-14 16:55:10,423 Epoch: [415][230/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0307 (0.0286) Prec@1 94.000 (95.250) Prec@5 99.000 (99.875) +2022-11-14 16:55:10,680 Epoch: [415][240/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0350 (0.0289) Prec@1 94.000 (95.200) Prec@5 99.000 (99.840) +2022-11-14 16:55:10,938 Epoch: [415][250/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0152 (0.0283) Prec@1 98.000 (95.308) Prec@5 100.000 (99.846) +2022-11-14 16:55:11,197 Epoch: [415][260/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0268 (0.0283) Prec@1 96.000 (95.333) Prec@5 100.000 (99.852) +2022-11-14 16:55:11,452 Epoch: [415][270/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0347 (0.0285) Prec@1 94.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:55:11,708 Epoch: [415][280/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0293 (0.0285) Prec@1 96.000 (95.310) Prec@5 100.000 (99.862) +2022-11-14 16:55:11,969 Epoch: [415][290/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0273 (0.0285) Prec@1 96.000 (95.333) Prec@5 100.000 (99.867) +2022-11-14 16:55:12,226 Epoch: [415][300/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0184 (0.0282) Prec@1 96.000 (95.355) Prec@5 100.000 (99.871) +2022-11-14 16:55:12,484 Epoch: [415][310/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0344 (0.0284) Prec@1 96.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 16:55:12,734 Epoch: [415][320/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0383 (0.0287) Prec@1 92.000 (95.273) Prec@5 100.000 (99.879) +2022-11-14 16:55:12,983 Epoch: [415][330/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0093 (0.0281) Prec@1 99.000 (95.382) Prec@5 100.000 (99.882) +2022-11-14 16:55:13,233 Epoch: [415][340/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0393 (0.0284) Prec@1 96.000 (95.400) Prec@5 99.000 (99.857) +2022-11-14 16:55:13,487 Epoch: [415][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0337 (0.0286) Prec@1 92.000 (95.306) Prec@5 100.000 (99.861) +2022-11-14 16:55:13,742 Epoch: [415][360/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0188 (0.0283) Prec@1 96.000 (95.324) Prec@5 100.000 (99.865) +2022-11-14 16:55:13,999 Epoch: [415][370/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0329 (0.0284) Prec@1 93.000 (95.263) Prec@5 100.000 (99.868) +2022-11-14 16:55:14,247 Epoch: [415][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0405 (0.0287) Prec@1 94.000 (95.231) Prec@5 100.000 (99.872) +2022-11-14 16:55:14,497 Epoch: [415][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0245 (0.0286) Prec@1 97.000 (95.275) Prec@5 99.000 (99.850) +2022-11-14 16:55:14,747 Epoch: [415][400/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0294 (0.0286) Prec@1 95.000 (95.268) Prec@5 100.000 (99.854) +2022-11-14 16:55:14,998 Epoch: [415][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0300 (0.0287) Prec@1 96.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:55:15,247 Epoch: [415][420/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0447 (0.0291) Prec@1 91.000 (95.186) Prec@5 100.000 (99.860) +2022-11-14 16:55:15,495 Epoch: [415][430/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0399 (0.0293) Prec@1 92.000 (95.114) Prec@5 100.000 (99.864) +2022-11-14 16:55:15,743 Epoch: [415][440/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0392 (0.0295) Prec@1 91.000 (95.022) Prec@5 100.000 (99.867) +2022-11-14 16:55:15,990 Epoch: [415][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0362 (0.0297) Prec@1 95.000 (95.022) Prec@5 100.000 (99.870) +2022-11-14 16:55:16,239 Epoch: [415][460/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0304 (0.0297) Prec@1 95.000 (95.021) Prec@5 100.000 (99.872) +2022-11-14 16:55:16,491 Epoch: [415][470/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0460 (0.0300) Prec@1 93.000 (94.979) Prec@5 100.000 (99.875) +2022-11-14 16:55:16,740 Epoch: [415][480/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0427 (0.0303) Prec@1 92.000 (94.918) Prec@5 100.000 (99.878) +2022-11-14 16:55:16,989 Epoch: [415][490/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0216 (0.0301) Prec@1 96.000 (94.940) Prec@5 100.000 (99.880) +2022-11-14 16:55:17,216 Epoch: [415][499/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0330 (0.0302) Prec@1 95.000 (94.941) Prec@5 100.000 (99.882) +2022-11-14 16:55:17,503 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0650 (0.0650) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:17,512 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0755) Prec@1 84.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:17,521 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0650 (0.0720) Prec@1 89.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 16:55:17,531 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0940 (0.0775) Prec@1 83.000 (86.500) Prec@5 99.000 (99.750) +2022-11-14 16:55:17,538 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0755) Prec@1 89.000 (87.000) Prec@5 100.000 (99.800) +2022-11-14 16:55:17,545 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0464 (0.0707) Prec@1 91.000 (87.667) Prec@5 100.000 (99.833) +2022-11-14 16:55:17,553 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0533 (0.0682) Prec@1 92.000 (88.286) Prec@5 100.000 (99.857) +2022-11-14 16:55:17,563 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0696) Prec@1 85.000 (87.875) Prec@5 100.000 (99.875) +2022-11-14 16:55:17,570 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0708) Prec@1 89.000 (88.000) Prec@5 99.000 (99.778) +2022-11-14 16:55:17,577 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0732) Prec@1 85.000 (87.700) Prec@5 98.000 (99.600) +2022-11-14 16:55:17,585 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0718) Prec@1 91.000 (88.000) Prec@5 100.000 (99.636) +2022-11-14 16:55:17,593 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0731) Prec@1 85.000 (87.750) Prec@5 100.000 (99.667) +2022-11-14 16:55:17,601 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0725) Prec@1 90.000 (87.923) Prec@5 99.000 (99.615) +2022-11-14 16:55:17,608 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0726) Prec@1 87.000 (87.857) Prec@5 100.000 (99.643) +2022-11-14 16:55:17,616 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0734) Prec@1 87.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 16:55:17,624 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0734) Prec@1 86.000 (87.688) Prec@5 100.000 (99.625) +2022-11-14 16:55:17,632 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0717) Prec@1 95.000 (88.118) Prec@5 98.000 (99.529) +2022-11-14 16:55:17,640 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0740) Prec@1 80.000 (87.667) Prec@5 99.000 (99.500) +2022-11-14 16:55:17,648 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0755) Prec@1 84.000 (87.474) Prec@5 97.000 (99.368) +2022-11-14 16:55:17,655 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0761) Prec@1 88.000 (87.500) Prec@5 96.000 (99.200) +2022-11-14 16:55:17,663 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0760) Prec@1 86.000 (87.429) Prec@5 99.000 (99.190) +2022-11-14 16:55:17,670 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0769) Prec@1 85.000 (87.318) Prec@5 100.000 (99.227) +2022-11-14 16:55:17,678 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1182 (0.0787) Prec@1 82.000 (87.087) Prec@5 98.000 (99.174) +2022-11-14 16:55:17,686 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0783) Prec@1 88.000 (87.125) Prec@5 100.000 (99.208) +2022-11-14 16:55:17,693 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0785) Prec@1 87.000 (87.120) Prec@5 100.000 (99.240) +2022-11-14 16:55:17,701 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1129 (0.0798) Prec@1 82.000 (86.923) Prec@5 95.000 (99.077) +2022-11-14 16:55:17,708 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0422 (0.0784) Prec@1 95.000 (87.222) Prec@5 100.000 (99.111) +2022-11-14 16:55:17,716 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0773) Prec@1 92.000 (87.393) Prec@5 100.000 (99.143) +2022-11-14 16:55:17,724 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0770) Prec@1 89.000 (87.448) Prec@5 97.000 (99.069) +2022-11-14 16:55:17,732 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0770) Prec@1 87.000 (87.433) Prec@5 100.000 (99.100) +2022-11-14 16:55:17,740 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0765) Prec@1 90.000 (87.516) Prec@5 99.000 (99.097) +2022-11-14 16:55:17,748 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0762) Prec@1 91.000 (87.625) Prec@5 99.000 (99.094) +2022-11-14 16:55:17,755 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0759) Prec@1 90.000 (87.697) Prec@5 100.000 (99.121) +2022-11-14 16:55:17,763 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0763) Prec@1 83.000 (87.559) Prec@5 99.000 (99.118) +2022-11-14 16:55:17,770 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0763) Prec@1 90.000 (87.629) Prec@5 99.000 (99.114) +2022-11-14 16:55:17,778 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0765) Prec@1 87.000 (87.611) Prec@5 100.000 (99.139) +2022-11-14 16:55:17,786 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0760) Prec@1 91.000 (87.703) Prec@5 98.000 (99.108) +2022-11-14 16:55:17,793 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1170 (0.0771) Prec@1 80.000 (87.500) Prec@5 99.000 (99.105) +2022-11-14 16:55:17,801 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0766) Prec@1 93.000 (87.641) Prec@5 99.000 (99.103) +2022-11-14 16:55:17,809 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0763) Prec@1 90.000 (87.700) Prec@5 99.000 (99.100) +2022-11-14 16:55:17,816 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0765) Prec@1 89.000 (87.732) Prec@5 99.000 (99.098) +2022-11-14 16:55:17,824 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0764) Prec@1 88.000 (87.738) Prec@5 100.000 (99.119) +2022-11-14 16:55:17,831 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0757) Prec@1 91.000 (87.814) Prec@5 99.000 (99.116) +2022-11-14 16:55:17,839 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0755) Prec@1 89.000 (87.841) Prec@5 99.000 (99.114) +2022-11-14 16:55:17,847 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0752) Prec@1 91.000 (87.911) Prec@5 99.000 (99.111) +2022-11-14 16:55:17,854 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0758) Prec@1 82.000 (87.783) Prec@5 98.000 (99.087) +2022-11-14 16:55:17,862 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0760) Prec@1 85.000 (87.723) Prec@5 100.000 (99.106) +2022-11-14 16:55:17,869 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0762) Prec@1 87.000 (87.708) Prec@5 99.000 (99.104) +2022-11-14 16:55:17,877 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0756) Prec@1 94.000 (87.837) Prec@5 100.000 (99.122) +2022-11-14 16:55:17,885 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0758) Prec@1 89.000 (87.860) Prec@5 100.000 (99.140) +2022-11-14 16:55:17,892 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0755) Prec@1 90.000 (87.902) Prec@5 100.000 (99.157) +2022-11-14 16:55:17,900 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0757) Prec@1 86.000 (87.865) Prec@5 100.000 (99.173) +2022-11-14 16:55:17,908 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0754) Prec@1 91.000 (87.925) Prec@5 99.000 (99.170) +2022-11-14 16:55:17,915 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0753) Prec@1 89.000 (87.944) Prec@5 100.000 (99.185) +2022-11-14 16:55:17,923 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0756) Prec@1 87.000 (87.927) Prec@5 99.000 (99.182) +2022-11-14 16:55:17,930 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0758) Prec@1 88.000 (87.929) Prec@5 98.000 (99.161) +2022-11-14 16:55:17,938 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0755) Prec@1 92.000 (88.000) Prec@5 100.000 (99.175) +2022-11-14 16:55:17,945 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0752) Prec@1 92.000 (88.069) Prec@5 99.000 (99.172) +2022-11-14 16:55:17,953 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0757) Prec@1 85.000 (88.017) Prec@5 99.000 (99.169) +2022-11-14 16:55:17,961 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0755) Prec@1 87.000 (88.000) Prec@5 100.000 (99.183) +2022-11-14 16:55:17,968 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0757) Prec@1 86.000 (87.967) Prec@5 100.000 (99.197) +2022-11-14 16:55:17,976 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0757) Prec@1 86.000 (87.935) Prec@5 100.000 (99.210) +2022-11-14 16:55:17,983 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0754) Prec@1 90.000 (87.968) Prec@5 98.000 (99.190) +2022-11-14 16:55:17,991 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0345 (0.0748) Prec@1 92.000 (88.031) Prec@5 100.000 (99.203) +2022-11-14 16:55:17,999 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0748) Prec@1 90.000 (88.062) Prec@5 99.000 (99.200) +2022-11-14 16:55:18,006 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0748) Prec@1 87.000 (88.045) Prec@5 100.000 (99.212) +2022-11-14 16:55:18,013 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0398 (0.0743) Prec@1 94.000 (88.134) Prec@5 100.000 (99.224) +2022-11-14 16:55:18,021 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0743) Prec@1 90.000 (88.162) Prec@5 98.000 (99.206) +2022-11-14 16:55:18,029 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0742) Prec@1 89.000 (88.174) Prec@5 99.000 (99.203) +2022-11-14 16:55:18,037 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0742) Prec@1 88.000 (88.171) Prec@5 99.000 (99.200) +2022-11-14 16:55:18,045 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1051 (0.0747) Prec@1 84.000 (88.113) Prec@5 100.000 (99.211) +2022-11-14 16:55:18,052 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0745) Prec@1 89.000 (88.125) Prec@5 100.000 (99.222) +2022-11-14 16:55:18,060 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0741) Prec@1 93.000 (88.192) Prec@5 100.000 (99.233) +2022-11-14 16:55:18,068 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0736) Prec@1 96.000 (88.297) Prec@5 100.000 (99.243) +2022-11-14 16:55:18,075 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0738) Prec@1 87.000 (88.280) Prec@5 99.000 (99.240) +2022-11-14 16:55:18,084 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0736) Prec@1 90.000 (88.303) Prec@5 99.000 (99.237) +2022-11-14 16:55:18,092 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0735) Prec@1 91.000 (88.338) Prec@5 100.000 (99.247) +2022-11-14 16:55:18,099 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0736) Prec@1 87.000 (88.321) Prec@5 99.000 (99.244) +2022-11-14 16:55:18,107 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0736) Prec@1 89.000 (88.329) Prec@5 100.000 (99.253) +2022-11-14 16:55:18,115 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0734) Prec@1 90.000 (88.350) Prec@5 100.000 (99.263) +2022-11-14 16:55:18,123 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0735) Prec@1 89.000 (88.358) Prec@5 99.000 (99.259) +2022-11-14 16:55:18,130 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0737) Prec@1 83.000 (88.293) Prec@5 100.000 (99.268) +2022-11-14 16:55:18,138 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1168 (0.0743) Prec@1 82.000 (88.217) Prec@5 99.000 (99.265) +2022-11-14 16:55:18,145 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0740) Prec@1 88.000 (88.214) Prec@5 99.000 (99.262) +2022-11-14 16:55:18,153 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0742) Prec@1 87.000 (88.200) Prec@5 99.000 (99.259) +2022-11-14 16:55:18,161 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0746) Prec@1 84.000 (88.151) Prec@5 100.000 (99.267) +2022-11-14 16:55:18,168 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0745) Prec@1 86.000 (88.126) Prec@5 98.000 (99.253) +2022-11-14 16:55:18,176 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0747) Prec@1 85.000 (88.091) Prec@5 98.000 (99.239) +2022-11-14 16:55:18,184 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0745) Prec@1 92.000 (88.135) Prec@5 99.000 (99.236) +2022-11-14 16:55:18,191 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0746) Prec@1 89.000 (88.144) Prec@5 98.000 (99.222) +2022-11-14 16:55:18,199 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0744) Prec@1 91.000 (88.176) Prec@5 100.000 (99.231) +2022-11-14 16:55:18,206 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0743) Prec@1 90.000 (88.196) Prec@5 100.000 (99.239) +2022-11-14 16:55:18,214 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0744) Prec@1 86.000 (88.172) Prec@5 99.000 (99.237) +2022-11-14 16:55:18,221 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0743) Prec@1 90.000 (88.191) Prec@5 100.000 (99.245) +2022-11-14 16:55:18,228 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0744) Prec@1 86.000 (88.168) Prec@5 99.000 (99.242) +2022-11-14 16:55:18,236 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0743) Prec@1 90.000 (88.188) Prec@5 99.000 (99.240) +2022-11-14 16:55:18,243 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0741) Prec@1 92.000 (88.227) Prec@5 97.000 (99.216) +2022-11-14 16:55:18,251 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0742) Prec@1 87.000 (88.214) Prec@5 98.000 (99.204) +2022-11-14 16:55:18,258 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0744) Prec@1 86.000 (88.192) Prec@5 100.000 (99.212) +2022-11-14 16:55:18,265 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0744) Prec@1 88.000 (88.190) Prec@5 100.000 (99.220) +2022-11-14 16:55:18,320 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:55:18,637 Epoch: [416][0/500] Time 0.023 (0.023) Data 0.240 (0.240) Loss 0.0247 (0.0247) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:18,847 Epoch: [416][10/500] Time 0.018 (0.019) Data 0.001 (0.023) Loss 0.0071 (0.0159) Prec@1 100.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:19,037 Epoch: [416][20/500] Time 0.016 (0.018) Data 0.002 (0.013) Loss 0.0219 (0.0179) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:19,230 Epoch: [416][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0492 (0.0257) Prec@1 92.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:55:19,417 Epoch: [416][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0466 (0.0299) Prec@1 92.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:19,606 Epoch: [416][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0207 (0.0284) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:55:19,833 Epoch: [416][60/500] Time 0.025 (0.018) Data 0.002 (0.006) Loss 0.0422 (0.0303) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:20,138 Epoch: [416][70/500] Time 0.031 (0.019) Data 0.002 (0.005) Loss 0.0374 (0.0312) Prec@1 93.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:55:20,446 Epoch: [416][80/500] Time 0.029 (0.020) Data 0.002 (0.005) Loss 0.0341 (0.0315) Prec@1 95.000 (94.778) Prec@5 100.000 (100.000) +2022-11-14 16:55:20,759 Epoch: [416][90/500] Time 0.030 (0.021) Data 0.002 (0.004) Loss 0.0352 (0.0319) Prec@1 95.000 (94.800) Prec@5 99.000 (99.900) +2022-11-14 16:55:21,077 Epoch: [416][100/500] Time 0.030 (0.021) Data 0.001 (0.004) Loss 0.0354 (0.0322) Prec@1 95.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 16:55:21,396 Epoch: [416][110/500] Time 0.031 (0.022) Data 0.001 (0.004) Loss 0.0243 (0.0316) Prec@1 94.000 (94.750) Prec@5 100.000 (99.917) +2022-11-14 16:55:21,713 Epoch: [416][120/500] Time 0.030 (0.023) Data 0.002 (0.004) Loss 0.0318 (0.0316) Prec@1 95.000 (94.769) Prec@5 100.000 (99.923) +2022-11-14 16:55:22,016 Epoch: [416][130/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0247 (0.0311) Prec@1 95.000 (94.786) Prec@5 99.000 (99.857) +2022-11-14 16:55:22,329 Epoch: [416][140/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0315 (0.0311) Prec@1 95.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 16:55:22,639 Epoch: [416][150/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0347 (0.0313) Prec@1 93.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 16:55:22,943 Epoch: [416][160/500] Time 0.028 (0.024) Data 0.001 (0.003) Loss 0.0221 (0.0308) Prec@1 96.000 (94.765) Prec@5 100.000 (99.882) +2022-11-14 16:55:23,255 Epoch: [416][170/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0244 (0.0305) Prec@1 96.000 (94.833) Prec@5 100.000 (99.889) +2022-11-14 16:55:23,560 Epoch: [416][180/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0276 (0.0303) Prec@1 95.000 (94.842) Prec@5 100.000 (99.895) +2022-11-14 16:55:23,871 Epoch: [416][190/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0048 (0.0290) Prec@1 99.000 (95.050) Prec@5 100.000 (99.900) +2022-11-14 16:55:24,184 Epoch: [416][200/500] Time 0.028 (0.024) Data 0.002 (0.003) Loss 0.0237 (0.0288) Prec@1 97.000 (95.143) Prec@5 100.000 (99.905) +2022-11-14 16:55:24,489 Epoch: [416][210/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0242 (0.0286) Prec@1 97.000 (95.227) Prec@5 99.000 (99.864) +2022-11-14 16:55:24,799 Epoch: [416][220/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0433 (0.0292) Prec@1 93.000 (95.130) Prec@5 99.000 (99.826) +2022-11-14 16:55:25,106 Epoch: [416][230/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0382 (0.0296) Prec@1 95.000 (95.125) Prec@5 100.000 (99.833) +2022-11-14 16:55:25,405 Epoch: [416][240/500] Time 0.028 (0.025) Data 0.001 (0.003) Loss 0.0272 (0.0295) Prec@1 96.000 (95.160) Prec@5 100.000 (99.840) +2022-11-14 16:55:25,705 Epoch: [416][250/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0302 (0.0295) Prec@1 95.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 16:55:26,004 Epoch: [416][260/500] Time 0.027 (0.025) Data 0.002 (0.003) Loss 0.0361 (0.0298) Prec@1 93.000 (95.074) Prec@5 100.000 (99.852) +2022-11-14 16:55:26,306 Epoch: [416][270/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0388 (0.0301) Prec@1 94.000 (95.036) Prec@5 100.000 (99.857) +2022-11-14 16:55:26,609 Epoch: [416][280/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.0255 (0.0299) Prec@1 95.000 (95.034) Prec@5 100.000 (99.862) +2022-11-14 16:55:26,913 Epoch: [416][290/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0388 (0.0302) Prec@1 94.000 (95.000) Prec@5 99.000 (99.833) +2022-11-14 16:55:27,214 Epoch: [416][300/500] Time 0.030 (0.025) Data 0.002 (0.002) Loss 0.0209 (0.0299) Prec@1 96.000 (95.032) Prec@5 100.000 (99.839) +2022-11-14 16:55:27,516 Epoch: [416][310/500] Time 0.029 (0.025) Data 0.001 (0.002) Loss 0.0453 (0.0304) Prec@1 92.000 (94.938) Prec@5 100.000 (99.844) +2022-11-14 16:55:27,824 Epoch: [416][320/500] Time 0.031 (0.025) Data 0.001 (0.002) Loss 0.0258 (0.0303) Prec@1 96.000 (94.970) Prec@5 100.000 (99.848) +2022-11-14 16:55:28,128 Epoch: [416][330/500] Time 0.033 (0.025) Data 0.002 (0.002) Loss 0.0484 (0.0308) Prec@1 92.000 (94.882) Prec@5 100.000 (99.853) +2022-11-14 16:55:28,426 Epoch: [416][340/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0391 (0.0310) Prec@1 93.000 (94.829) Prec@5 100.000 (99.857) +2022-11-14 16:55:28,724 Epoch: [416][350/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0065 (0.0304) Prec@1 99.000 (94.944) Prec@5 100.000 (99.861) +2022-11-14 16:55:29,019 Epoch: [416][360/500] Time 0.031 (0.025) Data 0.001 (0.002) Loss 0.0147 (0.0299) Prec@1 97.000 (95.000) Prec@5 100.000 (99.865) +2022-11-14 16:55:29,327 Epoch: [416][370/500] Time 0.028 (0.025) Data 0.002 (0.002) Loss 0.0114 (0.0294) Prec@1 99.000 (95.105) Prec@5 100.000 (99.868) +2022-11-14 16:55:29,632 Epoch: [416][380/500] Time 0.031 (0.026) Data 0.002 (0.002) Loss 0.0344 (0.0296) Prec@1 92.000 (95.026) Prec@5 100.000 (99.872) +2022-11-14 16:55:29,933 Epoch: [416][390/500] Time 0.027 (0.026) Data 0.001 (0.002) Loss 0.0332 (0.0297) Prec@1 93.000 (94.975) Prec@5 100.000 (99.875) +2022-11-14 16:55:30,237 Epoch: [416][400/500] Time 0.031 (0.026) Data 0.002 (0.002) Loss 0.0197 (0.0294) Prec@1 98.000 (95.049) Prec@5 100.000 (99.878) +2022-11-14 16:55:30,545 Epoch: [416][410/500] Time 0.029 (0.026) Data 0.002 (0.002) Loss 0.0198 (0.0292) Prec@1 97.000 (95.095) Prec@5 99.000 (99.857) +2022-11-14 16:55:30,853 Epoch: [416][420/500] Time 0.032 (0.026) Data 0.002 (0.002) Loss 0.0548 (0.0298) Prec@1 93.000 (95.047) Prec@5 100.000 (99.860) +2022-11-14 16:55:31,157 Epoch: [416][430/500] Time 0.027 (0.026) Data 0.001 (0.002) Loss 0.0264 (0.0297) Prec@1 95.000 (95.045) Prec@5 100.000 (99.864) +2022-11-14 16:55:31,455 Epoch: [416][440/500] Time 0.031 (0.026) Data 0.001 (0.002) Loss 0.0295 (0.0297) Prec@1 95.000 (95.044) Prec@5 100.000 (99.867) +2022-11-14 16:55:31,753 Epoch: [416][450/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.0073 (0.0292) Prec@1 100.000 (95.152) Prec@5 100.000 (99.870) +2022-11-14 16:55:32,056 Epoch: [416][460/500] Time 0.028 (0.026) Data 0.002 (0.002) Loss 0.0268 (0.0292) Prec@1 96.000 (95.170) Prec@5 100.000 (99.872) +2022-11-14 16:55:32,329 Epoch: [416][470/500] Time 0.020 (0.026) Data 0.002 (0.002) Loss 0.0308 (0.0292) Prec@1 95.000 (95.167) Prec@5 100.000 (99.875) +2022-11-14 16:55:32,538 Epoch: [416][480/500] Time 0.017 (0.026) Data 0.002 (0.002) Loss 0.0100 (0.0288) Prec@1 98.000 (95.224) Prec@5 100.000 (99.878) +2022-11-14 16:55:32,740 Epoch: [416][490/500] Time 0.018 (0.025) Data 0.001 (0.002) Loss 0.0391 (0.0290) Prec@1 91.000 (95.140) Prec@5 99.000 (99.860) +2022-11-14 16:55:32,920 Epoch: [416][499/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0417 (0.0293) Prec@1 93.000 (95.098) Prec@5 99.000 (99.843) +2022-11-14 16:55:33,214 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0757 (0.0757) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:55:33,223 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0710 (0.0733) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 16:55:33,233 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0645 (0.0704) Prec@1 90.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:55:33,245 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0680 (0.0698) Prec@1 91.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:55:33,252 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0841 (0.0726) Prec@1 87.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 16:55:33,259 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0395 (0.0671) Prec@1 94.000 (89.833) Prec@5 100.000 (99.500) +2022-11-14 16:55:33,268 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0587 (0.0659) Prec@1 91.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 16:55:33,279 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0677) Prec@1 86.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 16:55:33,286 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0685) Prec@1 89.000 (89.444) Prec@5 97.000 (99.222) +2022-11-14 16:55:33,293 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0691) Prec@1 89.000 (89.400) Prec@5 98.000 (99.100) +2022-11-14 16:55:33,303 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0534 (0.0676) Prec@1 91.000 (89.545) Prec@5 100.000 (99.182) +2022-11-14 16:55:33,313 Test: [11/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0690) Prec@1 85.000 (89.167) Prec@5 98.000 (99.083) +2022-11-14 16:55:33,321 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0698) Prec@1 89.000 (89.154) Prec@5 98.000 (99.000) +2022-11-14 16:55:33,328 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0704) Prec@1 87.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:55:33,338 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0719) Prec@1 85.000 (88.733) Prec@5 100.000 (99.067) +2022-11-14 16:55:33,347 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0723) Prec@1 87.000 (88.625) Prec@5 100.000 (99.125) +2022-11-14 16:55:33,355 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0720) Prec@1 92.000 (88.824) Prec@5 99.000 (99.118) +2022-11-14 16:55:33,362 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1136 (0.0743) Prec@1 82.000 (88.444) Prec@5 99.000 (99.111) +2022-11-14 16:55:33,371 Test: [18/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0747) Prec@1 87.000 (88.368) Prec@5 100.000 (99.158) +2022-11-14 16:55:33,381 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0756) Prec@1 85.000 (88.200) Prec@5 98.000 (99.100) +2022-11-14 16:55:33,388 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0752) Prec@1 90.000 (88.286) Prec@5 100.000 (99.143) +2022-11-14 16:55:33,396 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0752) Prec@1 90.000 (88.364) Prec@5 99.000 (99.136) +2022-11-14 16:55:33,405 Test: [22/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1022 (0.0764) Prec@1 83.000 (88.130) Prec@5 99.000 (99.130) +2022-11-14 16:55:33,414 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0770) Prec@1 86.000 (88.042) Prec@5 100.000 (99.167) +2022-11-14 16:55:33,421 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0773) Prec@1 87.000 (88.000) Prec@5 100.000 (99.200) +2022-11-14 16:55:33,429 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0877 (0.0777) Prec@1 87.000 (87.962) Prec@5 99.000 (99.192) +2022-11-14 16:55:33,438 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0467 (0.0765) Prec@1 94.000 (88.185) Prec@5 100.000 (99.222) +2022-11-14 16:55:33,448 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0348 (0.0750) Prec@1 95.000 (88.429) Prec@5 99.000 (99.214) +2022-11-14 16:55:33,455 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0753) Prec@1 84.000 (88.276) Prec@5 98.000 (99.172) +2022-11-14 16:55:33,463 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0754) Prec@1 88.000 (88.267) Prec@5 98.000 (99.133) +2022-11-14 16:55:33,472 Test: [30/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0746) Prec@1 92.000 (88.387) Prec@5 100.000 (99.161) +2022-11-14 16:55:33,481 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0746) Prec@1 88.000 (88.375) Prec@5 99.000 (99.156) +2022-11-14 16:55:33,489 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0740) Prec@1 88.000 (88.364) Prec@5 100.000 (99.182) +2022-11-14 16:55:33,496 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0740) Prec@1 89.000 (88.382) Prec@5 99.000 (99.176) +2022-11-14 16:55:33,506 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0745) Prec@1 85.000 (88.286) Prec@5 100.000 (99.200) +2022-11-14 16:55:33,516 Test: [35/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0746) Prec@1 85.000 (88.194) Prec@5 100.000 (99.222) +2022-11-14 16:55:33,524 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0748) Prec@1 86.000 (88.135) Prec@5 99.000 (99.216) +2022-11-14 16:55:33,532 Test: [37/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0756) Prec@1 84.000 (88.026) Prec@5 100.000 (99.237) +2022-11-14 16:55:33,541 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0751) Prec@1 93.000 (88.154) Prec@5 100.000 (99.256) +2022-11-14 16:55:33,551 Test: [39/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0749) Prec@1 89.000 (88.175) Prec@5 99.000 (99.250) +2022-11-14 16:55:33,558 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0749) Prec@1 86.000 (88.122) Prec@5 99.000 (99.244) +2022-11-14 16:55:33,566 Test: [41/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0750) Prec@1 88.000 (88.119) Prec@5 100.000 (99.262) +2022-11-14 16:55:33,574 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0744) Prec@1 92.000 (88.209) Prec@5 100.000 (99.279) +2022-11-14 16:55:33,581 Test: [43/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0743) Prec@1 90.000 (88.250) Prec@5 99.000 (99.273) +2022-11-14 16:55:33,589 Test: [44/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0740) Prec@1 89.000 (88.267) Prec@5 99.000 (99.267) +2022-11-14 16:55:33,596 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0747) Prec@1 83.000 (88.152) Prec@5 98.000 (99.239) +2022-11-14 16:55:33,604 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0745) Prec@1 90.000 (88.191) Prec@5 100.000 (99.255) +2022-11-14 16:55:33,611 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0749) Prec@1 83.000 (88.083) Prec@5 98.000 (99.229) +2022-11-14 16:55:33,619 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0746) Prec@1 89.000 (88.102) Prec@5 100.000 (99.245) +2022-11-14 16:55:33,626 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0754) Prec@1 83.000 (88.000) Prec@5 100.000 (99.260) +2022-11-14 16:55:33,634 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0749) Prec@1 89.000 (88.020) Prec@5 100.000 (99.275) +2022-11-14 16:55:33,641 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0752) Prec@1 85.000 (87.962) Prec@5 99.000 (99.269) +2022-11-14 16:55:33,649 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0749) Prec@1 91.000 (88.019) Prec@5 100.000 (99.283) +2022-11-14 16:55:33,656 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0748) Prec@1 90.000 (88.056) Prec@5 98.000 (99.259) +2022-11-14 16:55:33,664 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0750) Prec@1 85.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 16:55:33,671 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0747) Prec@1 91.000 (88.054) Prec@5 99.000 (99.268) +2022-11-14 16:55:33,679 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0746) Prec@1 87.000 (88.035) Prec@5 100.000 (99.281) +2022-11-14 16:55:33,687 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0744) Prec@1 90.000 (88.069) Prec@5 100.000 (99.293) +2022-11-14 16:55:33,694 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0749) Prec@1 84.000 (88.000) Prec@5 100.000 (99.305) +2022-11-14 16:55:33,701 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0750) Prec@1 86.000 (87.967) Prec@5 100.000 (99.317) +2022-11-14 16:55:33,709 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0751) Prec@1 87.000 (87.951) Prec@5 98.000 (99.295) +2022-11-14 16:55:33,717 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0750) Prec@1 91.000 (88.000) Prec@5 100.000 (99.306) +2022-11-14 16:55:33,724 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0750) Prec@1 87.000 (87.984) Prec@5 99.000 (99.302) +2022-11-14 16:55:33,732 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0373 (0.0744) Prec@1 95.000 (88.094) Prec@5 100.000 (99.312) +2022-11-14 16:55:33,739 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0746) Prec@1 85.000 (88.046) Prec@5 100.000 (99.323) +2022-11-14 16:55:33,747 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0746) Prec@1 89.000 (88.061) Prec@5 99.000 (99.318) +2022-11-14 16:55:33,755 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0433 (0.0741) Prec@1 92.000 (88.119) Prec@5 99.000 (99.313) +2022-11-14 16:55:33,762 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0739) Prec@1 91.000 (88.162) Prec@5 98.000 (99.294) +2022-11-14 16:55:33,770 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0736) Prec@1 94.000 (88.246) Prec@5 99.000 (99.290) +2022-11-14 16:55:33,777 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0738) Prec@1 87.000 (88.229) Prec@5 100.000 (99.300) +2022-11-14 16:55:33,785 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0740) Prec@1 89.000 (88.239) Prec@5 100.000 (99.310) +2022-11-14 16:55:33,792 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0738) Prec@1 89.000 (88.250) Prec@5 100.000 (99.319) +2022-11-14 16:55:33,800 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0736) Prec@1 90.000 (88.274) Prec@5 99.000 (99.315) +2022-11-14 16:55:33,808 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0447 (0.0732) Prec@1 91.000 (88.311) Prec@5 100.000 (99.324) +2022-11-14 16:55:33,815 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0735) Prec@1 87.000 (88.293) Prec@5 100.000 (99.333) +2022-11-14 16:55:33,823 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0734) Prec@1 88.000 (88.289) Prec@5 100.000 (99.342) +2022-11-14 16:55:33,830 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0735) Prec@1 87.000 (88.273) Prec@5 99.000 (99.338) +2022-11-14 16:55:33,838 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0740) Prec@1 83.000 (88.205) Prec@5 98.000 (99.321) +2022-11-14 16:55:33,846 Test: [78/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0738) Prec@1 90.000 (88.228) Prec@5 100.000 (99.329) +2022-11-14 16:55:33,856 Test: [79/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0738) Prec@1 90.000 (88.250) Prec@5 100.000 (99.338) +2022-11-14 16:55:33,863 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0741) Prec@1 84.000 (88.198) Prec@5 99.000 (99.333) +2022-11-14 16:55:33,871 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0741) Prec@1 85.000 (88.159) Prec@5 100.000 (99.341) +2022-11-14 16:55:33,880 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0743) Prec@1 84.000 (88.108) Prec@5 100.000 (99.349) +2022-11-14 16:55:33,889 Test: [83/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0744) Prec@1 87.000 (88.095) Prec@5 98.000 (99.333) +2022-11-14 16:55:33,897 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0747) Prec@1 85.000 (88.059) Prec@5 100.000 (99.341) +2022-11-14 16:55:33,904 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1034 (0.0750) Prec@1 85.000 (88.023) Prec@5 100.000 (99.349) +2022-11-14 16:55:33,913 Test: [86/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0747) Prec@1 91.000 (88.057) Prec@5 99.000 (99.345) +2022-11-14 16:55:33,923 Test: [87/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0748) Prec@1 87.000 (88.045) Prec@5 99.000 (99.341) +2022-11-14 16:55:33,930 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0748) Prec@1 88.000 (88.045) Prec@5 99.000 (99.337) +2022-11-14 16:55:33,938 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0748) Prec@1 90.000 (88.067) Prec@5 100.000 (99.344) +2022-11-14 16:55:33,947 Test: [90/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0746) Prec@1 91.000 (88.099) Prec@5 99.000 (99.341) +2022-11-14 16:55:33,957 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0743) Prec@1 92.000 (88.141) Prec@5 100.000 (99.348) +2022-11-14 16:55:33,965 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0744) Prec@1 86.000 (88.118) Prec@5 100.000 (99.355) +2022-11-14 16:55:33,972 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0744) Prec@1 89.000 (88.128) Prec@5 100.000 (99.362) +2022-11-14 16:55:33,980 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0745) Prec@1 85.000 (88.095) Prec@5 98.000 (99.347) +2022-11-14 16:55:33,987 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0743) Prec@1 90.000 (88.115) Prec@5 100.000 (99.354) +2022-11-14 16:55:33,994 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0740) Prec@1 93.000 (88.165) Prec@5 99.000 (99.351) +2022-11-14 16:55:34,002 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0738) Prec@1 89.000 (88.173) Prec@5 99.000 (99.347) +2022-11-14 16:55:34,009 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0740) Prec@1 87.000 (88.162) Prec@5 100.000 (99.354) +2022-11-14 16:55:34,017 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0740) Prec@1 89.000 (88.170) Prec@5 100.000 (99.360) +2022-11-14 16:55:34,071 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:55:34,387 Epoch: [417][0/500] Time 0.022 (0.022) Data 0.236 (0.236) Loss 0.0218 (0.0218) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:34,584 Epoch: [417][10/500] Time 0.020 (0.018) Data 0.001 (0.023) Loss 0.0198 (0.0208) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:34,774 Epoch: [417][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0104 (0.0173) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:34,964 Epoch: [417][30/500] Time 0.019 (0.017) Data 0.001 (0.009) Loss 0.0279 (0.0200) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:35,156 Epoch: [417][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0359 (0.0232) Prec@1 95.000 (96.200) Prec@5 100.000 (100.000) +2022-11-14 16:55:35,341 Epoch: [417][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0180 (0.0223) Prec@1 98.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:35,531 Epoch: [417][60/500] Time 0.019 (0.017) Data 0.001 (0.005) Loss 0.0382 (0.0246) Prec@1 95.000 (96.286) Prec@5 100.000 (100.000) +2022-11-14 16:55:35,718 Epoch: [417][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0154 (0.0234) Prec@1 98.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:35,904 Epoch: [417][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0050 (0.0214) Prec@1 99.000 (96.778) Prec@5 100.000 (100.000) +2022-11-14 16:55:36,094 Epoch: [417][90/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0056 (0.0198) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:36,281 Epoch: [417][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0309 (0.0208) Prec@1 96.000 (96.909) Prec@5 100.000 (100.000) +2022-11-14 16:55:36,467 Epoch: [417][110/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0263 (0.0213) Prec@1 95.000 (96.750) Prec@5 99.000 (99.917) +2022-11-14 16:55:36,654 Epoch: [417][120/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0431 (0.0229) Prec@1 92.000 (96.385) Prec@5 100.000 (99.923) +2022-11-14 16:55:36,841 Epoch: [417][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0427 (0.0244) Prec@1 93.000 (96.143) Prec@5 100.000 (99.929) +2022-11-14 16:55:37,036 Epoch: [417][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0315 (0.0248) Prec@1 95.000 (96.067) Prec@5 100.000 (99.933) +2022-11-14 16:55:37,226 Epoch: [417][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0421 (0.0259) Prec@1 92.000 (95.812) Prec@5 100.000 (99.938) +2022-11-14 16:55:37,411 Epoch: [417][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0370 (0.0266) Prec@1 94.000 (95.706) Prec@5 100.000 (99.941) +2022-11-14 16:55:37,597 Epoch: [417][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0446 (0.0276) Prec@1 94.000 (95.611) Prec@5 100.000 (99.944) +2022-11-14 16:55:37,783 Epoch: [417][180/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0180 (0.0271) Prec@1 97.000 (95.684) Prec@5 100.000 (99.947) +2022-11-14 16:55:37,974 Epoch: [417][190/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0297 (0.0272) Prec@1 95.000 (95.650) Prec@5 99.000 (99.900) +2022-11-14 16:55:38,241 Epoch: [417][200/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0279 (0.0272) Prec@1 95.000 (95.619) Prec@5 100.000 (99.905) +2022-11-14 16:55:38,523 Epoch: [417][210/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0315 (0.0274) Prec@1 95.000 (95.591) Prec@5 100.000 (99.909) +2022-11-14 16:55:38,810 Epoch: [417][220/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0266 (0.0274) Prec@1 96.000 (95.609) Prec@5 100.000 (99.913) +2022-11-14 16:55:39,099 Epoch: [417][230/500] Time 0.028 (0.018) Data 0.001 (0.003) Loss 0.0351 (0.0277) Prec@1 95.000 (95.583) Prec@5 100.000 (99.917) +2022-11-14 16:55:39,384 Epoch: [417][240/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0226 (0.0275) Prec@1 96.000 (95.600) Prec@5 100.000 (99.920) +2022-11-14 16:55:39,667 Epoch: [417][250/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0221 (0.0273) Prec@1 97.000 (95.654) Prec@5 100.000 (99.923) +2022-11-14 16:55:39,956 Epoch: [417][260/500] Time 0.028 (0.019) Data 0.002 (0.002) Loss 0.0200 (0.0270) Prec@1 97.000 (95.704) Prec@5 100.000 (99.926) +2022-11-14 16:55:40,248 Epoch: [417][270/500] Time 0.028 (0.019) Data 0.002 (0.002) Loss 0.0235 (0.0269) Prec@1 96.000 (95.714) Prec@5 100.000 (99.929) +2022-11-14 16:55:40,529 Epoch: [417][280/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0407 (0.0274) Prec@1 92.000 (95.586) Prec@5 100.000 (99.931) +2022-11-14 16:55:40,816 Epoch: [417][290/500] Time 0.027 (0.019) Data 0.001 (0.002) Loss 0.0324 (0.0275) Prec@1 96.000 (95.600) Prec@5 100.000 (99.933) +2022-11-14 16:55:41,101 Epoch: [417][300/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0460 (0.0281) Prec@1 91.000 (95.452) Prec@5 100.000 (99.935) +2022-11-14 16:55:41,381 Epoch: [417][310/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0113 (0.0276) Prec@1 99.000 (95.562) Prec@5 100.000 (99.938) +2022-11-14 16:55:41,663 Epoch: [417][320/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.0253 (0.0275) Prec@1 97.000 (95.606) Prec@5 100.000 (99.939) +2022-11-14 16:55:41,937 Epoch: [417][330/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0195 (0.0273) Prec@1 96.000 (95.618) Prec@5 100.000 (99.941) +2022-11-14 16:55:42,216 Epoch: [417][340/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0309 (0.0274) Prec@1 95.000 (95.600) Prec@5 100.000 (99.943) +2022-11-14 16:55:42,490 Epoch: [417][350/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0179 (0.0271) Prec@1 96.000 (95.611) Prec@5 100.000 (99.944) +2022-11-14 16:55:42,763 Epoch: [417][360/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0351 (0.0274) Prec@1 93.000 (95.541) Prec@5 100.000 (99.946) +2022-11-14 16:55:43,045 Epoch: [417][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0149 (0.0270) Prec@1 99.000 (95.632) Prec@5 100.000 (99.947) +2022-11-14 16:55:43,326 Epoch: [417][380/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0244 (0.0270) Prec@1 97.000 (95.667) Prec@5 100.000 (99.949) +2022-11-14 16:55:43,598 Epoch: [417][390/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0296 (0.0270) Prec@1 95.000 (95.650) Prec@5 100.000 (99.950) +2022-11-14 16:55:43,870 Epoch: [417][400/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0261 (0.0270) Prec@1 95.000 (95.634) Prec@5 100.000 (99.951) +2022-11-14 16:55:44,147 Epoch: [417][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0482 (0.0275) Prec@1 91.000 (95.524) Prec@5 100.000 (99.952) +2022-11-14 16:55:44,426 Epoch: [417][420/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0425 (0.0279) Prec@1 92.000 (95.442) Prec@5 100.000 (99.953) +2022-11-14 16:55:44,698 Epoch: [417][430/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0296 (0.0279) Prec@1 96.000 (95.455) Prec@5 100.000 (99.955) +2022-11-14 16:55:44,977 Epoch: [417][440/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0408 (0.0282) Prec@1 94.000 (95.422) Prec@5 100.000 (99.956) +2022-11-14 16:55:45,258 Epoch: [417][450/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0244 (0.0281) Prec@1 98.000 (95.478) Prec@5 100.000 (99.957) +2022-11-14 16:55:45,537 Epoch: [417][460/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0334 (0.0282) Prec@1 95.000 (95.468) Prec@5 100.000 (99.957) +2022-11-14 16:55:45,809 Epoch: [417][470/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0286 (0.0282) Prec@1 95.000 (95.458) Prec@5 100.000 (99.958) +2022-11-14 16:55:46,085 Epoch: [417][480/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0166 (0.0280) Prec@1 98.000 (95.510) Prec@5 100.000 (99.959) +2022-11-14 16:55:46,356 Epoch: [417][490/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0296 (0.0280) Prec@1 95.000 (95.500) Prec@5 99.000 (99.940) +2022-11-14 16:55:46,602 Epoch: [417][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0538 (0.0285) Prec@1 90.000 (95.392) Prec@5 100.000 (99.941) +2022-11-14 16:55:46,907 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0774 (0.0774) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:46,914 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0540 (0.0657) Prec@1 91.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:46,921 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0647) Prec@1 90.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 16:55:46,932 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0649) Prec@1 90.000 (89.750) Prec@5 99.000 (99.750) +2022-11-14 16:55:46,939 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0636) Prec@1 92.000 (90.200) Prec@5 100.000 (99.800) +2022-11-14 16:55:46,947 Test: [5/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0444 (0.0604) Prec@1 93.000 (90.667) Prec@5 100.000 (99.833) +2022-11-14 16:55:46,957 Test: [6/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0599) Prec@1 92.000 (90.857) Prec@5 100.000 (99.857) +2022-11-14 16:55:46,965 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0620) Prec@1 88.000 (90.500) Prec@5 98.000 (99.625) +2022-11-14 16:55:46,972 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0706 (0.0630) Prec@1 89.000 (90.333) Prec@5 98.000 (99.444) +2022-11-14 16:55:46,982 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0648) Prec@1 87.000 (90.000) Prec@5 99.000 (99.400) +2022-11-14 16:55:46,992 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0646) Prec@1 88.000 (89.818) Prec@5 100.000 (99.455) +2022-11-14 16:55:47,000 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1025 (0.0678) Prec@1 84.000 (89.333) Prec@5 99.000 (99.417) +2022-11-14 16:55:47,008 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0667) Prec@1 93.000 (89.615) Prec@5 100.000 (99.462) +2022-11-14 16:55:47,019 Test: [13/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0817 (0.0678) Prec@1 90.000 (89.643) Prec@5 98.000 (99.357) +2022-11-14 16:55:47,029 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0680) Prec@1 86.000 (89.400) Prec@5 99.000 (99.333) +2022-11-14 16:55:47,037 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0692) Prec@1 86.000 (89.188) Prec@5 100.000 (99.375) +2022-11-14 16:55:47,045 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0689) Prec@1 91.000 (89.294) Prec@5 98.000 (99.294) +2022-11-14 16:55:47,055 Test: [17/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0959 (0.0704) Prec@1 86.000 (89.111) Prec@5 100.000 (99.333) +2022-11-14 16:55:47,065 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0934 (0.0716) Prec@1 84.000 (88.842) Prec@5 98.000 (99.263) +2022-11-14 16:55:47,073 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0727) Prec@1 85.000 (88.650) Prec@5 97.000 (99.150) +2022-11-14 16:55:47,082 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0731) Prec@1 84.000 (88.429) Prec@5 100.000 (99.190) +2022-11-14 16:55:47,093 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0736) Prec@1 87.000 (88.364) Prec@5 99.000 (99.182) +2022-11-14 16:55:47,103 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0746) Prec@1 86.000 (88.261) Prec@5 99.000 (99.174) +2022-11-14 16:55:47,110 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0746) Prec@1 91.000 (88.375) Prec@5 100.000 (99.208) +2022-11-14 16:55:47,118 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0740) Prec@1 91.000 (88.480) Prec@5 99.000 (99.200) +2022-11-14 16:55:47,128 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1034 (0.0752) Prec@1 83.000 (88.269) Prec@5 98.000 (99.154) +2022-11-14 16:55:47,138 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0745) Prec@1 88.000 (88.259) Prec@5 100.000 (99.185) +2022-11-14 16:55:47,146 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0746) Prec@1 87.000 (88.214) Prec@5 100.000 (99.214) +2022-11-14 16:55:47,154 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0747) Prec@1 88.000 (88.207) Prec@5 98.000 (99.172) +2022-11-14 16:55:47,164 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0748) Prec@1 86.000 (88.133) Prec@5 100.000 (99.200) +2022-11-14 16:55:47,174 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0743) Prec@1 90.000 (88.194) Prec@5 100.000 (99.226) +2022-11-14 16:55:47,182 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0503 (0.0736) Prec@1 92.000 (88.312) Prec@5 99.000 (99.219) +2022-11-14 16:55:47,190 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0536 (0.0730) Prec@1 93.000 (88.455) Prec@5 99.000 (99.212) +2022-11-14 16:55:47,200 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0739) Prec@1 81.000 (88.235) Prec@5 100.000 (99.235) +2022-11-14 16:55:47,210 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0681 (0.0737) Prec@1 90.000 (88.286) Prec@5 99.000 (99.229) +2022-11-14 16:55:47,218 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0737) Prec@1 88.000 (88.278) Prec@5 100.000 (99.250) +2022-11-14 16:55:47,225 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0734) Prec@1 90.000 (88.324) Prec@5 96.000 (99.162) +2022-11-14 16:55:47,236 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0741) Prec@1 83.000 (88.184) Prec@5 100.000 (99.184) +2022-11-14 16:55:47,246 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0736) Prec@1 93.000 (88.308) Prec@5 100.000 (99.205) +2022-11-14 16:55:47,254 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0737) Prec@1 87.000 (88.275) Prec@5 99.000 (99.200) +2022-11-14 16:55:47,262 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0739) Prec@1 86.000 (88.220) Prec@5 100.000 (99.220) +2022-11-14 16:55:47,272 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0737) Prec@1 89.000 (88.238) Prec@5 98.000 (99.190) +2022-11-14 16:55:47,282 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0734) Prec@1 91.000 (88.302) Prec@5 99.000 (99.186) +2022-11-14 16:55:47,290 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0732) Prec@1 90.000 (88.341) Prec@5 98.000 (99.159) +2022-11-14 16:55:47,298 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0727) Prec@1 93.000 (88.444) Prec@5 100.000 (99.178) +2022-11-14 16:55:47,308 Test: [45/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1101 (0.0735) Prec@1 81.000 (88.283) Prec@5 99.000 (99.174) +2022-11-14 16:55:47,319 Test: [46/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0736) Prec@1 88.000 (88.277) Prec@5 98.000 (99.149) +2022-11-14 16:55:47,327 Test: [47/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1045 (0.0742) Prec@1 83.000 (88.167) Prec@5 97.000 (99.104) +2022-11-14 16:55:47,335 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0737) Prec@1 92.000 (88.245) Prec@5 100.000 (99.122) +2022-11-14 16:55:47,345 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0742) Prec@1 86.000 (88.200) Prec@5 100.000 (99.140) +2022-11-14 16:55:47,355 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0742) Prec@1 88.000 (88.196) Prec@5 100.000 (99.157) +2022-11-14 16:55:47,363 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0742) Prec@1 85.000 (88.135) Prec@5 100.000 (99.173) +2022-11-14 16:55:47,371 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0739) Prec@1 89.000 (88.151) Prec@5 100.000 (99.189) +2022-11-14 16:55:47,381 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0736) Prec@1 92.000 (88.222) Prec@5 100.000 (99.204) +2022-11-14 16:55:47,391 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0739) Prec@1 85.000 (88.164) Prec@5 100.000 (99.218) +2022-11-14 16:55:47,399 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0740) Prec@1 86.000 (88.125) Prec@5 99.000 (99.214) +2022-11-14 16:55:47,407 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0740) Prec@1 87.000 (88.105) Prec@5 99.000 (99.211) +2022-11-14 16:55:47,414 Test: [57/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0740) Prec@1 89.000 (88.121) Prec@5 99.000 (99.207) +2022-11-14 16:55:47,421 Test: [58/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0744) Prec@1 85.000 (88.068) Prec@5 100.000 (99.220) +2022-11-14 16:55:47,429 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0748) Prec@1 84.000 (88.000) Prec@5 99.000 (99.217) +2022-11-14 16:55:47,437 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0750) Prec@1 86.000 (87.967) Prec@5 99.000 (99.213) +2022-11-14 16:55:47,445 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0749) Prec@1 89.000 (87.984) Prec@5 100.000 (99.226) +2022-11-14 16:55:47,452 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0750) Prec@1 88.000 (87.984) Prec@5 100.000 (99.238) +2022-11-14 16:55:47,461 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0746) Prec@1 93.000 (88.062) Prec@5 99.000 (99.234) +2022-11-14 16:55:47,468 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0749) Prec@1 83.000 (87.985) Prec@5 100.000 (99.246) +2022-11-14 16:55:47,476 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0750) Prec@1 87.000 (87.970) Prec@5 98.000 (99.227) +2022-11-14 16:55:47,484 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0516 (0.0746) Prec@1 92.000 (88.030) Prec@5 99.000 (99.224) +2022-11-14 16:55:47,492 Test: [67/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0746) Prec@1 87.000 (88.015) Prec@5 99.000 (99.221) +2022-11-14 16:55:47,499 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0745) Prec@1 88.000 (88.014) Prec@5 98.000 (99.203) +2022-11-14 16:55:47,509 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0746) Prec@1 88.000 (88.014) Prec@5 99.000 (99.200) +2022-11-14 16:55:47,519 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0750) Prec@1 85.000 (87.972) Prec@5 100.000 (99.211) +2022-11-14 16:55:47,527 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0526 (0.0747) Prec@1 94.000 (88.056) Prec@5 100.000 (99.222) +2022-11-14 16:55:47,535 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0745) Prec@1 91.000 (88.096) Prec@5 99.000 (99.219) +2022-11-14 16:55:47,545 Test: [73/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0497 (0.0741) Prec@1 94.000 (88.176) Prec@5 100.000 (99.230) +2022-11-14 16:55:47,555 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0744) Prec@1 85.000 (88.133) Prec@5 100.000 (99.240) +2022-11-14 16:55:47,563 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0744) Prec@1 89.000 (88.145) Prec@5 99.000 (99.237) +2022-11-14 16:55:47,571 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0745) Prec@1 87.000 (88.130) Prec@5 98.000 (99.221) +2022-11-14 16:55:47,582 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1014 (0.0749) Prec@1 85.000 (88.090) Prec@5 98.000 (99.205) +2022-11-14 16:55:47,592 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0751) Prec@1 86.000 (88.063) Prec@5 100.000 (99.215) +2022-11-14 16:55:47,600 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0753) Prec@1 87.000 (88.050) Prec@5 98.000 (99.200) +2022-11-14 16:55:47,608 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0753) Prec@1 88.000 (88.049) Prec@5 98.000 (99.185) +2022-11-14 16:55:47,618 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0754) Prec@1 83.000 (87.988) Prec@5 100.000 (99.195) +2022-11-14 16:55:47,628 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0756) Prec@1 86.000 (87.964) Prec@5 98.000 (99.181) +2022-11-14 16:55:47,635 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0756) Prec@1 89.000 (87.976) Prec@5 100.000 (99.190) +2022-11-14 16:55:47,643 Test: [84/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0911 (0.0758) Prec@1 84.000 (87.929) Prec@5 100.000 (99.200) +2022-11-14 16:55:47,653 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1009 (0.0761) Prec@1 83.000 (87.872) Prec@5 100.000 (99.209) +2022-11-14 16:55:47,663 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0760) Prec@1 87.000 (87.862) Prec@5 100.000 (99.218) +2022-11-14 16:55:47,671 Test: [87/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0759) Prec@1 89.000 (87.875) Prec@5 99.000 (99.216) +2022-11-14 16:55:47,678 Test: [88/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0762) Prec@1 83.000 (87.820) Prec@5 99.000 (99.213) +2022-11-14 16:55:47,689 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0762) Prec@1 88.000 (87.822) Prec@5 99.000 (99.211) +2022-11-14 16:55:47,699 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0758) Prec@1 92.000 (87.868) Prec@5 100.000 (99.220) +2022-11-14 16:55:47,706 Test: [91/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0634 (0.0757) Prec@1 91.000 (87.902) Prec@5 100.000 (99.228) +2022-11-14 16:55:47,714 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0985 (0.0759) Prec@1 82.000 (87.839) Prec@5 100.000 (99.237) +2022-11-14 16:55:47,722 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0759) Prec@1 87.000 (87.830) Prec@5 99.000 (99.234) +2022-11-14 16:55:47,730 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0759) Prec@1 88.000 (87.832) Prec@5 99.000 (99.232) +2022-11-14 16:55:47,737 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0757) Prec@1 91.000 (87.865) Prec@5 98.000 (99.219) +2022-11-14 16:55:47,745 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0755) Prec@1 89.000 (87.876) Prec@5 100.000 (99.227) +2022-11-14 16:55:47,752 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0756) Prec@1 87.000 (87.867) Prec@5 99.000 (99.224) +2022-11-14 16:55:47,760 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0757) Prec@1 84.000 (87.828) Prec@5 99.000 (99.222) +2022-11-14 16:55:47,767 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0756) Prec@1 89.000 (87.840) Prec@5 99.000 (99.220) +2022-11-14 16:55:47,823 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:55:48,131 Epoch: [418][0/500] Time 0.021 (0.021) Data 0.230 (0.230) Loss 0.0306 (0.0306) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:48,329 Epoch: [418][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0230 (0.0268) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:48,523 Epoch: [418][20/500] Time 0.018 (0.017) Data 0.001 (0.013) Loss 0.0176 (0.0237) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:55:48,717 Epoch: [418][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0308 (0.0255) Prec@1 94.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:55:48,911 Epoch: [418][40/500] Time 0.019 (0.017) Data 0.001 (0.007) Loss 0.0244 (0.0253) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:49,112 Epoch: [418][50/500] Time 0.024 (0.017) Data 0.002 (0.006) Loss 0.0515 (0.0297) Prec@1 93.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:55:49,301 Epoch: [418][60/500] Time 0.019 (0.017) Data 0.001 (0.005) Loss 0.0487 (0.0324) Prec@1 90.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 16:55:49,490 Epoch: [418][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0235 (0.0313) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:49,679 Epoch: [418][80/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0440 (0.0327) Prec@1 92.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 16:55:49,867 Epoch: [418][90/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0248 (0.0319) Prec@1 96.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 16:55:50,062 Epoch: [418][100/500] Time 0.022 (0.017) Data 0.001 (0.004) Loss 0.0466 (0.0332) Prec@1 93.000 (94.636) Prec@5 100.000 (100.000) +2022-11-14 16:55:50,331 Epoch: [418][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0258 (0.0326) Prec@1 96.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:55:50,603 Epoch: [418][120/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0212 (0.0317) Prec@1 96.000 (94.846) Prec@5 100.000 (100.000) +2022-11-14 16:55:50,880 Epoch: [418][130/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0184 (0.0308) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:55:51,165 Epoch: [418][140/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0265 (0.0305) Prec@1 96.000 (95.067) Prec@5 99.000 (99.933) +2022-11-14 16:55:51,451 Epoch: [418][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0205 (0.0299) Prec@1 96.000 (95.125) Prec@5 100.000 (99.938) +2022-11-14 16:55:51,736 Epoch: [418][160/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0381 (0.0304) Prec@1 93.000 (95.000) Prec@5 100.000 (99.941) +2022-11-14 16:55:52,021 Epoch: [418][170/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0283 (0.0302) Prec@1 95.000 (95.000) Prec@5 100.000 (99.944) +2022-11-14 16:55:52,304 Epoch: [418][180/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0192 (0.0297) Prec@1 97.000 (95.105) Prec@5 100.000 (99.947) +2022-11-14 16:55:52,587 Epoch: [418][190/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0338 (0.0299) Prec@1 93.000 (95.000) Prec@5 100.000 (99.950) +2022-11-14 16:55:52,873 Epoch: [418][200/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0411 (0.0304) Prec@1 94.000 (94.952) Prec@5 100.000 (99.952) +2022-11-14 16:55:53,151 Epoch: [418][210/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0541 (0.0315) Prec@1 92.000 (94.818) Prec@5 100.000 (99.955) +2022-11-14 16:55:53,427 Epoch: [418][220/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0266 (0.0313) Prec@1 95.000 (94.826) Prec@5 100.000 (99.957) +2022-11-14 16:55:53,704 Epoch: [418][230/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0593 (0.0324) Prec@1 88.000 (94.542) Prec@5 97.000 (99.833) +2022-11-14 16:55:53,984 Epoch: [418][240/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0204 (0.0320) Prec@1 97.000 (94.640) Prec@5 100.000 (99.840) +2022-11-14 16:55:54,263 Epoch: [418][250/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0151 (0.0313) Prec@1 99.000 (94.808) Prec@5 100.000 (99.846) +2022-11-14 16:55:54,535 Epoch: [418][260/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0201 (0.0309) Prec@1 97.000 (94.889) Prec@5 100.000 (99.852) +2022-11-14 16:55:54,804 Epoch: [418][270/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0261 (0.0307) Prec@1 95.000 (94.893) Prec@5 100.000 (99.857) +2022-11-14 16:55:55,080 Epoch: [418][280/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0165 (0.0302) Prec@1 98.000 (95.000) Prec@5 100.000 (99.862) +2022-11-14 16:55:55,357 Epoch: [418][290/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0194 (0.0299) Prec@1 96.000 (95.033) Prec@5 100.000 (99.867) +2022-11-14 16:55:55,632 Epoch: [418][300/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0188 (0.0295) Prec@1 95.000 (95.032) Prec@5 100.000 (99.871) +2022-11-14 16:55:55,912 Epoch: [418][310/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0431 (0.0299) Prec@1 93.000 (94.969) Prec@5 99.000 (99.844) +2022-11-14 16:55:56,192 Epoch: [418][320/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0342 (0.0301) Prec@1 93.000 (94.909) Prec@5 100.000 (99.848) +2022-11-14 16:55:56,469 Epoch: [418][330/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0545 (0.0308) Prec@1 90.000 (94.765) Prec@5 100.000 (99.853) +2022-11-14 16:55:56,748 Epoch: [418][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0440 (0.0312) Prec@1 92.000 (94.686) Prec@5 100.000 (99.857) +2022-11-14 16:55:57,024 Epoch: [418][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0188 (0.0308) Prec@1 96.000 (94.722) Prec@5 100.000 (99.861) +2022-11-14 16:55:57,302 Epoch: [418][360/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0411 (0.0311) Prec@1 92.000 (94.649) Prec@5 100.000 (99.865) +2022-11-14 16:55:57,578 Epoch: [418][370/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0250 (0.0309) Prec@1 96.000 (94.684) Prec@5 100.000 (99.868) +2022-11-14 16:55:57,851 Epoch: [418][380/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0479 (0.0314) Prec@1 91.000 (94.590) Prec@5 100.000 (99.872) +2022-11-14 16:55:58,131 Epoch: [418][390/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0458 (0.0317) Prec@1 95.000 (94.600) Prec@5 100.000 (99.875) +2022-11-14 16:55:58,408 Epoch: [418][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0246 (0.0316) Prec@1 96.000 (94.634) Prec@5 100.000 (99.878) +2022-11-14 16:55:58,684 Epoch: [418][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0208 (0.0313) Prec@1 97.000 (94.690) Prec@5 99.000 (99.857) +2022-11-14 16:55:58,958 Epoch: [418][420/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0176 (0.0310) Prec@1 97.000 (94.744) Prec@5 100.000 (99.860) +2022-11-14 16:55:59,240 Epoch: [418][430/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0341 (0.0311) Prec@1 95.000 (94.750) Prec@5 100.000 (99.864) +2022-11-14 16:55:59,516 Epoch: [418][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0469 (0.0314) Prec@1 92.000 (94.689) Prec@5 100.000 (99.867) +2022-11-14 16:55:59,796 Epoch: [418][450/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0280 (0.0313) Prec@1 96.000 (94.717) Prec@5 100.000 (99.870) +2022-11-14 16:56:00,075 Epoch: [418][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0359 (0.0314) Prec@1 95.000 (94.723) Prec@5 100.000 (99.872) +2022-11-14 16:56:00,349 Epoch: [418][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0378 (0.0316) Prec@1 92.000 (94.667) Prec@5 100.000 (99.875) +2022-11-14 16:56:00,626 Epoch: [418][480/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0318 (0.0316) Prec@1 95.000 (94.673) Prec@5 100.000 (99.878) +2022-11-14 16:56:00,902 Epoch: [418][490/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0254 (0.0314) Prec@1 96.000 (94.700) Prec@5 100.000 (99.880) +2022-11-14 16:56:01,156 Epoch: [418][499/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0231 (0.0313) Prec@1 96.000 (94.725) Prec@5 100.000 (99.882) +2022-11-14 16:56:01,462 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0715 (0.0715) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:01,471 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0851 (0.0783) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:56:01,480 Test: [2/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0515 (0.0694) Prec@1 90.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 16:56:01,494 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0794 (0.0719) Prec@1 87.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:56:01,502 Test: [4/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0754 (0.0726) Prec@1 88.000 (88.400) Prec@5 99.000 (99.400) +2022-11-14 16:56:01,509 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0441 (0.0679) Prec@1 93.000 (89.167) Prec@5 99.000 (99.333) +2022-11-14 16:56:01,519 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0508 (0.0654) Prec@1 92.000 (89.571) Prec@5 100.000 (99.429) +2022-11-14 16:56:01,530 Test: [7/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0667) Prec@1 88.000 (89.375) Prec@5 99.000 (99.375) +2022-11-14 16:56:01,538 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0643 (0.0664) Prec@1 91.000 (89.556) Prec@5 98.000 (99.222) +2022-11-14 16:56:01,546 Test: [9/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0663) Prec@1 90.000 (89.600) Prec@5 99.000 (99.200) +2022-11-14 16:56:01,554 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0615 (0.0659) Prec@1 90.000 (89.636) Prec@5 100.000 (99.273) +2022-11-14 16:56:01,563 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0790 (0.0670) Prec@1 88.000 (89.500) Prec@5 100.000 (99.333) +2022-11-14 16:56:01,571 Test: [12/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0487 (0.0656) Prec@1 91.000 (89.615) Prec@5 99.000 (99.308) +2022-11-14 16:56:01,579 Test: [13/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0671) Prec@1 87.000 (89.429) Prec@5 99.000 (99.286) +2022-11-14 16:56:01,589 Test: [14/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0673) Prec@1 89.000 (89.400) Prec@5 99.000 (99.267) +2022-11-14 16:56:01,598 Test: [15/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0682) Prec@1 84.000 (89.062) Prec@5 99.000 (99.250) +2022-11-14 16:56:01,606 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0471 (0.0670) Prec@1 94.000 (89.353) Prec@5 99.000 (99.235) +2022-11-14 16:56:01,614 Test: [17/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0688) Prec@1 85.000 (89.111) Prec@5 100.000 (99.278) +2022-11-14 16:56:01,625 Test: [18/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0692) Prec@1 84.000 (88.842) Prec@5 99.000 (99.263) +2022-11-14 16:56:01,633 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0698) Prec@1 87.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 16:56:01,641 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0957 (0.0710) Prec@1 84.000 (88.524) Prec@5 100.000 (99.286) +2022-11-14 16:56:01,648 Test: [21/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0721) Prec@1 84.000 (88.318) Prec@5 96.000 (99.136) +2022-11-14 16:56:01,656 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0729) Prec@1 87.000 (88.261) Prec@5 96.000 (99.000) +2022-11-14 16:56:01,664 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0885 (0.0735) Prec@1 87.000 (88.208) Prec@5 100.000 (99.042) +2022-11-14 16:56:01,671 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0745) Prec@1 84.000 (88.040) Prec@5 100.000 (99.080) +2022-11-14 16:56:01,679 Test: [25/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0751) Prec@1 85.000 (87.923) Prec@5 100.000 (99.115) +2022-11-14 16:56:01,687 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0745) Prec@1 91.000 (88.037) Prec@5 100.000 (99.148) +2022-11-14 16:56:01,695 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0737) Prec@1 92.000 (88.179) Prec@5 100.000 (99.179) +2022-11-14 16:56:01,702 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0737) Prec@1 90.000 (88.241) Prec@5 99.000 (99.172) +2022-11-14 16:56:01,711 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0735) Prec@1 88.000 (88.233) Prec@5 100.000 (99.200) +2022-11-14 16:56:01,719 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0730) Prec@1 92.000 (88.355) Prec@5 100.000 (99.226) +2022-11-14 16:56:01,726 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0728) Prec@1 90.000 (88.406) Prec@5 99.000 (99.219) +2022-11-14 16:56:01,734 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0722) Prec@1 92.000 (88.515) Prec@5 100.000 (99.242) +2022-11-14 16:56:01,741 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0860 (0.0726) Prec@1 84.000 (88.382) Prec@5 100.000 (99.265) +2022-11-14 16:56:01,749 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0731) Prec@1 85.000 (88.286) Prec@5 99.000 (99.257) +2022-11-14 16:56:01,757 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0728) Prec@1 90.000 (88.333) Prec@5 99.000 (99.250) +2022-11-14 16:56:01,764 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0725) Prec@1 90.000 (88.378) Prec@5 99.000 (99.243) +2022-11-14 16:56:01,772 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0828 (0.0728) Prec@1 87.000 (88.342) Prec@5 100.000 (99.263) +2022-11-14 16:56:01,780 Test: [38/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0548 (0.0723) Prec@1 93.000 (88.462) Prec@5 99.000 (99.256) +2022-11-14 16:56:01,788 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0724) Prec@1 89.000 (88.475) Prec@5 98.000 (99.225) +2022-11-14 16:56:01,795 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0728) Prec@1 87.000 (88.439) Prec@5 98.000 (99.195) +2022-11-14 16:56:01,803 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0727) Prec@1 89.000 (88.452) Prec@5 99.000 (99.190) +2022-11-14 16:56:01,810 Test: 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0.0509 (0.0732) Prec@1 92.000 (88.388) Prec@5 99.000 (99.143) +2022-11-14 16:56:01,863 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0741) Prec@1 83.000 (88.280) Prec@5 100.000 (99.160) +2022-11-14 16:56:01,871 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0738) Prec@1 89.000 (88.294) Prec@5 100.000 (99.176) +2022-11-14 16:56:01,879 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0740) Prec@1 85.000 (88.231) Prec@5 99.000 (99.173) +2022-11-14 16:56:01,887 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0736) Prec@1 92.000 (88.302) Prec@5 99.000 (99.170) +2022-11-14 16:56:01,894 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0736) Prec@1 87.000 (88.278) Prec@5 100.000 (99.185) +2022-11-14 16:56:01,902 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0741) Prec@1 85.000 (88.218) Prec@5 100.000 (99.200) +2022-11-14 16:56:01,909 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0743) Prec@1 87.000 (88.196) Prec@5 99.000 (99.196) +2022-11-14 16:56:01,917 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0738) Prec@1 90.000 (88.228) Prec@5 100.000 (99.211) +2022-11-14 16:56:01,925 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0739) Prec@1 87.000 (88.207) Prec@5 100.000 (99.224) +2022-11-14 16:56:01,932 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0738) Prec@1 90.000 (88.237) Prec@5 100.000 (99.237) +2022-11-14 16:56:01,940 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0739) Prec@1 85.000 (88.183) Prec@5 100.000 (99.250) +2022-11-14 16:56:01,948 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0741) Prec@1 86.000 (88.148) Prec@5 98.000 (99.230) +2022-11-14 16:56:01,955 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0739) Prec@1 90.000 (88.177) Prec@5 100.000 (99.242) +2022-11-14 16:56:01,963 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0740) Prec@1 85.000 (88.127) Prec@5 100.000 (99.254) +2022-11-14 16:56:01,970 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0366 (0.0734) Prec@1 93.000 (88.203) Prec@5 100.000 (99.266) +2022-11-14 16:56:01,978 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0737) Prec@1 87.000 (88.185) Prec@5 99.000 (99.262) +2022-11-14 16:56:01,986 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0739) Prec@1 86.000 (88.152) Prec@5 99.000 (99.258) +2022-11-14 16:56:01,993 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0734) Prec@1 91.000 (88.194) Prec@5 100.000 (99.269) +2022-11-14 16:56:02,001 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0732) Prec@1 92.000 (88.250) Prec@5 99.000 (99.265) +2022-11-14 16:56:02,009 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0389 (0.0727) Prec@1 94.000 (88.333) Prec@5 99.000 (99.261) +2022-11-14 16:56:02,017 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0730) Prec@1 84.000 (88.271) Prec@5 100.000 (99.271) +2022-11-14 16:56:02,024 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0732) Prec@1 86.000 (88.239) Prec@5 99.000 (99.268) +2022-11-14 16:56:02,032 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0730) Prec@1 89.000 (88.250) Prec@5 100.000 (99.278) +2022-11-14 16:56:02,040 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0422 (0.0726) Prec@1 95.000 (88.342) Prec@5 99.000 (99.274) +2022-11-14 16:56:02,047 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0723) Prec@1 94.000 (88.419) Prec@5 100.000 (99.284) +2022-11-14 16:56:02,055 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.0729) Prec@1 85.000 (88.373) Prec@5 99.000 (99.280) +2022-11-14 16:56:02,063 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0728) Prec@1 91.000 (88.408) Prec@5 99.000 (99.276) +2022-11-14 16:56:02,071 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0727) Prec@1 89.000 (88.416) Prec@5 99.000 (99.273) +2022-11-14 16:56:02,079 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0729) Prec@1 86.000 (88.385) Prec@5 98.000 (99.256) +2022-11-14 16:56:02,088 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0729) Prec@1 91.000 (88.418) Prec@5 100.000 (99.266) +2022-11-14 16:56:02,096 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0729) Prec@1 88.000 (88.412) Prec@5 100.000 (99.275) +2022-11-14 16:56:02,104 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0730) Prec@1 88.000 (88.407) Prec@5 99.000 (99.272) +2022-11-14 16:56:02,111 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0734) Prec@1 83.000 (88.341) Prec@5 100.000 (99.280) +2022-11-14 16:56:02,119 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0735) Prec@1 87.000 (88.325) Prec@5 100.000 (99.289) +2022-11-14 16:56:02,127 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0735) Prec@1 87.000 (88.310) Prec@5 98.000 (99.274) +2022-11-14 16:56:02,134 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0738) Prec@1 87.000 (88.294) Prec@5 100.000 (99.282) +2022-11-14 16:56:02,142 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0741) Prec@1 86.000 (88.267) Prec@5 100.000 (99.291) +2022-11-14 16:56:02,150 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0739) Prec@1 91.000 (88.299) Prec@5 100.000 (99.299) +2022-11-14 16:56:02,158 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0741) Prec@1 84.000 (88.250) Prec@5 98.000 (99.284) +2022-11-14 16:56:02,165 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0741) Prec@1 88.000 (88.247) Prec@5 100.000 (99.292) +2022-11-14 16:56:02,173 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0741) Prec@1 91.000 (88.278) Prec@5 98.000 (99.278) +2022-11-14 16:56:02,180 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0740) Prec@1 91.000 (88.308) Prec@5 100.000 (99.286) +2022-11-14 16:56:02,189 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0738) Prec@1 93.000 (88.359) Prec@5 100.000 (99.293) +2022-11-14 16:56:02,197 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0739) Prec@1 87.000 (88.344) Prec@5 100.000 (99.301) +2022-11-14 16:56:02,204 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0738) Prec@1 88.000 (88.340) Prec@5 100.000 (99.309) +2022-11-14 16:56:02,212 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0739) Prec@1 87.000 (88.326) Prec@5 99.000 (99.305) +2022-11-14 16:56:02,219 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0738) Prec@1 91.000 (88.354) Prec@5 99.000 (99.302) +2022-11-14 16:56:02,227 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0736) Prec@1 93.000 (88.402) Prec@5 97.000 (99.278) +2022-11-14 16:56:02,235 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0739) Prec@1 85.000 (88.367) Prec@5 98.000 (99.265) +2022-11-14 16:56:02,242 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0742) Prec@1 85.000 (88.333) Prec@5 99.000 (99.263) +2022-11-14 16:56:02,250 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0740) Prec@1 90.000 (88.350) Prec@5 100.000 (99.270) +2022-11-14 16:56:02,307 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:56:02,633 Epoch: [419][0/500] Time 0.022 (0.022) Data 0.247 (0.247) Loss 0.0583 (0.0583) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:02,831 Epoch: [419][10/500] Time 0.018 (0.018) Data 0.001 (0.024) Loss 0.0299 (0.0441) Prec@1 93.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:03,020 Epoch: [419][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0644 (0.0509) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:03,210 Epoch: [419][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0204 (0.0433) Prec@1 97.000 (92.500) Prec@5 99.000 (99.750) +2022-11-14 16:56:03,399 Epoch: [419][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0310 (0.0408) Prec@1 93.000 (92.600) Prec@5 100.000 (99.800) +2022-11-14 16:56:03,588 Epoch: [419][50/500] Time 0.019 (0.017) Data 0.002 (0.006) Loss 0.0321 (0.0394) Prec@1 97.000 (93.333) Prec@5 99.000 (99.667) +2022-11-14 16:56:03,778 Epoch: [419][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0187 (0.0364) Prec@1 97.000 (93.857) Prec@5 100.000 (99.714) +2022-11-14 16:56:03,972 Epoch: [419][70/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0330 (0.0360) Prec@1 95.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 16:56:04,170 Epoch: [419][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0144 (0.0336) Prec@1 96.000 (94.222) Prec@5 100.000 (99.778) +2022-11-14 16:56:04,363 Epoch: [419][90/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0279 (0.0330) Prec@1 94.000 (94.200) Prec@5 100.000 (99.800) +2022-11-14 16:56:04,554 Epoch: [419][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0253 (0.0323) Prec@1 96.000 (94.364) Prec@5 100.000 (99.818) +2022-11-14 16:56:04,793 Epoch: [419][110/500] Time 0.026 (0.017) Data 0.002 (0.004) Loss 0.0380 (0.0328) Prec@1 93.000 (94.250) Prec@5 100.000 (99.833) +2022-11-14 16:56:05,057 Epoch: [419][120/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0366 (0.0331) Prec@1 94.000 (94.231) Prec@5 99.000 (99.769) +2022-11-14 16:56:05,319 Epoch: [419][130/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0419 (0.0337) Prec@1 94.000 (94.214) Prec@5 100.000 (99.786) +2022-11-14 16:56:05,583 Epoch: [419][140/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0181 (0.0327) Prec@1 97.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 16:56:05,857 Epoch: [419][150/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0347 (0.0328) Prec@1 93.000 (94.312) Prec@5 100.000 (99.812) +2022-11-14 16:56:06,120 Epoch: [419][160/500] Time 0.032 (0.019) Data 0.002 (0.003) Loss 0.0375 (0.0331) Prec@1 95.000 (94.353) Prec@5 100.000 (99.824) +2022-11-14 16:56:06,388 Epoch: [419][170/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0409 (0.0335) Prec@1 95.000 (94.389) Prec@5 100.000 (99.833) +2022-11-14 16:56:06,661 Epoch: [419][180/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0418 (0.0339) Prec@1 93.000 (94.316) Prec@5 99.000 (99.789) +2022-11-14 16:56:06,932 Epoch: [419][190/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0139 (0.0329) Prec@1 98.000 (94.500) Prec@5 100.000 (99.800) +2022-11-14 16:56:07,203 Epoch: [419][200/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0396 (0.0333) Prec@1 94.000 (94.476) Prec@5 100.000 (99.810) +2022-11-14 16:56:07,474 Epoch: [419][210/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0336 (0.0333) Prec@1 95.000 (94.500) Prec@5 100.000 (99.818) +2022-11-14 16:56:07,742 Epoch: [419][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0369 (0.0334) Prec@1 95.000 (94.522) Prec@5 99.000 (99.783) +2022-11-14 16:56:08,004 Epoch: [419][230/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0510 (0.0342) Prec@1 93.000 (94.458) Prec@5 98.000 (99.708) +2022-11-14 16:56:08,275 Epoch: [419][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0246 (0.0338) Prec@1 97.000 (94.560) Prec@5 100.000 (99.720) +2022-11-14 16:56:08,543 Epoch: [419][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0243 (0.0334) Prec@1 96.000 (94.615) Prec@5 100.000 (99.731) +2022-11-14 16:56:08,812 Epoch: [419][260/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0243 (0.0331) Prec@1 96.000 (94.667) Prec@5 100.000 (99.741) +2022-11-14 16:56:09,078 Epoch: [419][270/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0407 (0.0334) Prec@1 93.000 (94.607) Prec@5 99.000 (99.714) +2022-11-14 16:56:09,342 Epoch: [419][280/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0393 (0.0336) Prec@1 93.000 (94.552) Prec@5 100.000 (99.724) +2022-11-14 16:56:09,607 Epoch: [419][290/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0415 (0.0338) Prec@1 95.000 (94.567) Prec@5 100.000 (99.733) +2022-11-14 16:56:09,870 Epoch: [419][300/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0211 (0.0334) Prec@1 96.000 (94.613) Prec@5 99.000 (99.710) +2022-11-14 16:56:10,133 Epoch: [419][310/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0337 (0.0334) Prec@1 95.000 (94.625) Prec@5 100.000 (99.719) +2022-11-14 16:56:10,397 Epoch: [419][320/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0213 (0.0331) Prec@1 96.000 (94.667) Prec@5 100.000 (99.727) +2022-11-14 16:56:10,662 Epoch: [419][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0296 (0.0330) Prec@1 95.000 (94.676) Prec@5 100.000 (99.735) +2022-11-14 16:56:10,922 Epoch: [419][340/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0421 (0.0332) Prec@1 93.000 (94.629) Prec@5 100.000 (99.743) +2022-11-14 16:56:11,187 Epoch: [419][350/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0320 (0.0332) Prec@1 94.000 (94.611) Prec@5 100.000 (99.750) +2022-11-14 16:56:11,449 Epoch: [419][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0223 (0.0329) Prec@1 97.000 (94.676) Prec@5 100.000 (99.757) +2022-11-14 16:56:11,715 Epoch: [419][370/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0183 (0.0325) Prec@1 96.000 (94.711) Prec@5 100.000 (99.763) +2022-11-14 16:56:11,982 Epoch: [419][380/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0290 (0.0324) Prec@1 96.000 (94.744) Prec@5 100.000 (99.769) +2022-11-14 16:56:12,249 Epoch: [419][390/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0148 (0.0320) Prec@1 97.000 (94.800) Prec@5 100.000 (99.775) +2022-11-14 16:56:12,512 Epoch: [419][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0196 (0.0317) Prec@1 97.000 (94.854) Prec@5 100.000 (99.780) +2022-11-14 16:56:12,774 Epoch: [419][410/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0592 (0.0323) Prec@1 89.000 (94.714) Prec@5 100.000 (99.786) +2022-11-14 16:56:13,036 Epoch: [419][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0177 (0.0320) Prec@1 97.000 (94.767) Prec@5 100.000 (99.791) +2022-11-14 16:56:13,299 Epoch: [419][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0237 (0.0318) Prec@1 97.000 (94.818) Prec@5 100.000 (99.795) +2022-11-14 16:56:13,558 Epoch: [419][440/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0384 (0.0319) Prec@1 92.000 (94.756) Prec@5 100.000 (99.800) +2022-11-14 16:56:13,821 Epoch: [419][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0361 (0.0320) Prec@1 94.000 (94.739) Prec@5 99.000 (99.783) +2022-11-14 16:56:14,083 Epoch: [419][460/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0364 (0.0321) Prec@1 94.000 (94.723) Prec@5 100.000 (99.787) +2022-11-14 16:56:14,341 Epoch: [419][470/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0416 (0.0323) Prec@1 94.000 (94.708) Prec@5 100.000 (99.792) +2022-11-14 16:56:14,602 Epoch: [419][480/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0095 (0.0319) Prec@1 100.000 (94.816) Prec@5 100.000 (99.796) +2022-11-14 16:56:14,863 Epoch: [419][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0315 (0.0319) Prec@1 94.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 16:56:15,098 Epoch: [419][499/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0541 (0.0323) Prec@1 91.000 (94.725) Prec@5 100.000 (99.804) +2022-11-14 16:56:15,395 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0582 (0.0582) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:15,404 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0718 (0.0650) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:15,412 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0591 (0.0630) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:15,422 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0636) Prec@1 90.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 16:56:15,429 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0692) Prec@1 85.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 16:56:15,437 Test: [5/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0381 (0.0640) Prec@1 94.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 16:56:15,444 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0626) Prec@1 93.000 (89.857) Prec@5 100.000 (99.714) +2022-11-14 16:56:15,452 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0671) Prec@1 82.000 (88.875) Prec@5 100.000 (99.750) +2022-11-14 16:56:15,459 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0695) Prec@1 87.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 16:56:15,466 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0699) Prec@1 89.000 (88.700) Prec@5 99.000 (99.600) +2022-11-14 16:56:15,474 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0695) Prec@1 91.000 (88.909) Prec@5 100.000 (99.636) +2022-11-14 16:56:15,482 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0716) Prec@1 85.000 (88.583) Prec@5 99.000 (99.583) +2022-11-14 16:56:15,489 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0384 (0.0691) Prec@1 94.000 (89.000) Prec@5 100.000 (99.615) +2022-11-14 16:56:15,497 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0695) Prec@1 87.000 (88.857) Prec@5 100.000 (99.643) +2022-11-14 16:56:15,505 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0701) Prec@1 89.000 (88.867) Prec@5 99.000 (99.600) +2022-11-14 16:56:15,512 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0713) Prec@1 85.000 (88.625) Prec@5 99.000 (99.562) +2022-11-14 16:56:15,520 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0705) Prec@1 92.000 (88.824) Prec@5 96.000 (99.353) +2022-11-14 16:56:15,528 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0727) Prec@1 82.000 (88.444) Prec@5 100.000 (99.389) +2022-11-14 16:56:15,536 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0730) Prec@1 87.000 (88.368) Prec@5 98.000 (99.316) +2022-11-14 16:56:15,543 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0742) Prec@1 84.000 (88.150) Prec@5 99.000 (99.300) +2022-11-14 16:56:15,551 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0746) Prec@1 86.000 (88.048) Prec@5 100.000 (99.333) +2022-11-14 16:56:15,558 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0738) Prec@1 89.000 (88.091) Prec@5 99.000 (99.318) +2022-11-14 16:56:15,566 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0754) Prec@1 85.000 (87.957) Prec@5 96.000 (99.174) +2022-11-14 16:56:15,574 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0749) Prec@1 90.000 (88.042) Prec@5 100.000 (99.208) +2022-11-14 16:56:15,581 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0755) Prec@1 86.000 (87.960) Prec@5 100.000 (99.240) +2022-11-14 16:56:15,589 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0761) Prec@1 85.000 (87.846) Prec@5 98.000 (99.192) +2022-11-14 16:56:15,597 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0752) Prec@1 92.000 (88.000) Prec@5 99.000 (99.185) +2022-11-14 16:56:15,604 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0745) Prec@1 92.000 (88.143) Prec@5 100.000 (99.214) +2022-11-14 16:56:15,612 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0744) Prec@1 86.000 (88.069) Prec@5 98.000 (99.172) +2022-11-14 16:56:15,619 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0743) Prec@1 87.000 (88.033) Prec@5 99.000 (99.167) +2022-11-14 16:56:15,627 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0741) Prec@1 89.000 (88.065) Prec@5 100.000 (99.194) +2022-11-14 16:56:15,635 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0736) Prec@1 90.000 (88.125) Prec@5 100.000 (99.219) +2022-11-14 16:56:15,642 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0738) Prec@1 85.000 (88.030) Prec@5 100.000 (99.242) +2022-11-14 16:56:15,650 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0747) Prec@1 82.000 (87.853) Prec@5 100.000 (99.265) +2022-11-14 16:56:15,658 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0751) Prec@1 86.000 (87.800) Prec@5 98.000 (99.229) +2022-11-14 16:56:15,665 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0748) Prec@1 92.000 (87.917) Prec@5 99.000 (99.222) +2022-11-14 16:56:15,673 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0743) Prec@1 91.000 (88.000) Prec@5 98.000 (99.189) +2022-11-14 16:56:15,680 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0748) Prec@1 85.000 (87.921) Prec@5 96.000 (99.105) +2022-11-14 16:56:15,692 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0742) Prec@1 93.000 (88.051) Prec@5 99.000 (99.103) +2022-11-14 16:56:15,700 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0738) Prec@1 91.000 (88.125) Prec@5 99.000 (99.100) +2022-11-14 16:56:15,708 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.0747) Prec@1 83.000 (88.000) Prec@5 98.000 (99.073) +2022-11-14 16:56:15,715 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0749) Prec@1 88.000 (88.000) Prec@5 100.000 (99.095) +2022-11-14 16:56:15,723 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0743) Prec@1 93.000 (88.116) Prec@5 98.000 (99.070) +2022-11-14 16:56:15,730 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0739) Prec@1 89.000 (88.136) Prec@5 99.000 (99.068) +2022-11-14 16:56:15,738 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0737) Prec@1 89.000 (88.156) Prec@5 100.000 (99.089) +2022-11-14 16:56:15,746 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0744) Prec@1 83.000 (88.043) Prec@5 98.000 (99.065) +2022-11-14 16:56:15,753 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0744) Prec@1 89.000 (88.064) Prec@5 99.000 (99.064) +2022-11-14 16:56:15,761 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1276 (0.0755) Prec@1 81.000 (87.917) Prec@5 98.000 (99.042) +2022-11-14 16:56:15,768 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0752) Prec@1 90.000 (87.959) Prec@5 100.000 (99.061) +2022-11-14 16:56:15,776 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0757) Prec@1 85.000 (87.900) Prec@5 100.000 (99.080) +2022-11-14 16:56:15,784 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0754) Prec@1 90.000 (87.941) Prec@5 100.000 (99.098) +2022-11-14 16:56:15,791 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0755) Prec@1 86.000 (87.904) Prec@5 98.000 (99.077) +2022-11-14 16:56:15,799 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0752) Prec@1 91.000 (87.962) Prec@5 100.000 (99.094) +2022-11-14 16:56:15,806 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0752) Prec@1 88.000 (87.963) Prec@5 100.000 (99.111) +2022-11-14 16:56:15,814 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0753) Prec@1 86.000 (87.927) Prec@5 100.000 (99.127) +2022-11-14 16:56:15,821 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0755) Prec@1 87.000 (87.911) Prec@5 98.000 (99.107) +2022-11-14 16:56:15,829 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0753) Prec@1 85.000 (87.860) Prec@5 100.000 (99.123) +2022-11-14 16:56:15,838 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0752) Prec@1 92.000 (87.931) Prec@5 99.000 (99.121) +2022-11-14 16:56:15,846 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0755) Prec@1 84.000 (87.864) Prec@5 99.000 (99.119) +2022-11-14 16:56:15,853 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0750) Prec@1 90.000 (87.900) Prec@5 100.000 (99.133) +2022-11-14 16:56:15,861 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0752) Prec@1 86.000 (87.869) Prec@5 99.000 (99.131) +2022-11-14 16:56:15,869 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0751) Prec@1 90.000 (87.903) Prec@5 98.000 (99.113) +2022-11-14 16:56:15,876 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0751) Prec@1 87.000 (87.889) Prec@5 100.000 (99.127) +2022-11-14 16:56:15,884 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0747) Prec@1 91.000 (87.938) Prec@5 100.000 (99.141) +2022-11-14 16:56:15,892 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0748) Prec@1 88.000 (87.938) Prec@5 99.000 (99.138) +2022-11-14 16:56:15,899 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0750) Prec@1 85.000 (87.894) Prec@5 98.000 (99.121) +2022-11-14 16:56:15,907 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0399 (0.0745) Prec@1 92.000 (87.955) Prec@5 99.000 (99.119) +2022-11-14 16:56:15,915 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 90.000 (87.985) Prec@5 99.000 (99.118) +2022-11-14 16:56:15,923 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0742) Prec@1 90.000 (88.014) Prec@5 98.000 (99.101) +2022-11-14 16:56:15,931 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0742) Prec@1 90.000 (88.043) Prec@5 99.000 (99.100) +2022-11-14 16:56:15,938 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0746) Prec@1 88.000 (88.042) Prec@5 100.000 (99.113) +2022-11-14 16:56:15,946 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0742) Prec@1 93.000 (88.111) Prec@5 100.000 (99.125) +2022-11-14 16:56:15,954 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0739) Prec@1 93.000 (88.178) Prec@5 100.000 (99.137) +2022-11-14 16:56:15,961 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0393 (0.0734) Prec@1 94.000 (88.257) Prec@5 100.000 (99.149) +2022-11-14 16:56:15,969 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0738) Prec@1 84.000 (88.200) Prec@5 99.000 (99.147) +2022-11-14 16:56:15,977 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0734) Prec@1 93.000 (88.263) Prec@5 98.000 (99.132) +2022-11-14 16:56:15,984 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0731) Prec@1 93.000 (88.325) Prec@5 100.000 (99.143) +2022-11-14 16:56:15,992 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0733) Prec@1 85.000 (88.282) Prec@5 99.000 (99.141) +2022-11-14 16:56:16,000 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0733) Prec@1 88.000 (88.278) Prec@5 99.000 (99.139) +2022-11-14 16:56:16,007 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0735) Prec@1 86.000 (88.250) Prec@5 100.000 (99.150) +2022-11-14 16:56:16,015 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0735) Prec@1 87.000 (88.235) Prec@5 100.000 (99.160) +2022-11-14 16:56:16,023 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0734) Prec@1 90.000 (88.256) Prec@5 100.000 (99.171) +2022-11-14 16:56:16,030 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0737) Prec@1 85.000 (88.217) Prec@5 98.000 (99.157) +2022-11-14 16:56:16,038 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0735) Prec@1 90.000 (88.238) Prec@5 99.000 (99.155) +2022-11-14 16:56:16,046 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0737) Prec@1 84.000 (88.188) Prec@5 100.000 (99.165) +2022-11-14 16:56:16,054 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1111 (0.0741) Prec@1 84.000 (88.140) Prec@5 100.000 (99.174) +2022-11-14 16:56:16,061 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0741) Prec@1 87.000 (88.126) Prec@5 99.000 (99.172) +2022-11-14 16:56:16,069 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0742) Prec@1 85.000 (88.091) Prec@5 99.000 (99.170) +2022-11-14 16:56:16,076 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0742) Prec@1 88.000 (88.090) Prec@5 100.000 (99.180) +2022-11-14 16:56:16,084 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0743) Prec@1 87.000 (88.078) Prec@5 99.000 (99.178) +2022-11-14 16:56:16,092 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0741) Prec@1 89.000 (88.088) Prec@5 100.000 (99.187) +2022-11-14 16:56:16,100 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0738) Prec@1 93.000 (88.141) Prec@5 99.000 (99.185) +2022-11-14 16:56:16,108 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0739) Prec@1 90.000 (88.161) Prec@5 98.000 (99.172) +2022-11-14 16:56:16,115 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0737) Prec@1 91.000 (88.191) Prec@5 100.000 (99.181) +2022-11-14 16:56:16,123 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0738) Prec@1 90.000 (88.211) Prec@5 99.000 (99.179) +2022-11-14 16:56:16,130 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0736) Prec@1 92.000 (88.250) Prec@5 99.000 (99.177) +2022-11-14 16:56:16,138 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0409 (0.0733) Prec@1 93.000 (88.299) Prec@5 99.000 (99.175) +2022-11-14 16:56:16,145 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0734) Prec@1 87.000 (88.286) Prec@5 99.000 (99.173) +2022-11-14 16:56:16,153 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0735) Prec@1 88.000 (88.283) Prec@5 100.000 (99.182) +2022-11-14 16:56:16,160 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0735) Prec@1 87.000 (88.270) Prec@5 100.000 (99.190) +2022-11-14 16:56:16,223 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:56:16,551 Epoch: [420][0/500] Time 0.028 (0.028) Data 0.246 (0.246) Loss 0.0250 (0.0250) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:16,752 Epoch: [420][10/500] Time 0.017 (0.019) Data 0.002 (0.024) Loss 0.0163 (0.0207) Prec@1 98.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:16,944 Epoch: [420][20/500] Time 0.019 (0.018) Data 0.001 (0.013) Loss 0.0217 (0.0210) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:17,134 Epoch: [420][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0081 (0.0178) Prec@1 98.000 (97.250) Prec@5 100.000 (100.000) +2022-11-14 16:56:17,324 Epoch: [420][40/500] Time 0.019 (0.017) Data 0.001 (0.008) Loss 0.0262 (0.0195) Prec@1 95.000 (96.800) Prec@5 100.000 (100.000) +2022-11-14 16:56:17,511 Epoch: [420][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0219 (0.0199) Prec@1 96.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:56:17,715 Epoch: [420][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0113 (0.0187) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:17,901 Epoch: [420][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0242 (0.0193) Prec@1 96.000 (96.875) Prec@5 100.000 (100.000) +2022-11-14 16:56:18,091 Epoch: [420][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0247 (0.0199) Prec@1 97.000 (96.889) Prec@5 100.000 (100.000) +2022-11-14 16:56:18,278 Epoch: [420][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0283 (0.0208) Prec@1 94.000 (96.600) Prec@5 99.000 (99.900) +2022-11-14 16:56:18,537 Epoch: [420][100/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0699 (0.0252) Prec@1 87.000 (95.727) Prec@5 100.000 (99.909) +2022-11-14 16:56:18,824 Epoch: [420][110/500] Time 0.027 (0.018) Data 0.001 (0.004) Loss 0.0186 (0.0247) Prec@1 96.000 (95.750) Prec@5 100.000 (99.917) +2022-11-14 16:56:19,117 Epoch: [420][120/500] Time 0.032 (0.019) Data 0.002 (0.004) Loss 0.0158 (0.0240) Prec@1 99.000 (96.000) Prec@5 100.000 (99.923) +2022-11-14 16:56:19,405 Epoch: [420][130/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0310 (0.0245) Prec@1 96.000 (96.000) Prec@5 100.000 (99.929) +2022-11-14 16:56:19,693 Epoch: [420][140/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0201 (0.0242) Prec@1 97.000 (96.067) Prec@5 100.000 (99.933) +2022-11-14 16:56:19,975 Epoch: [420][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0285 (0.0245) Prec@1 94.000 (95.938) Prec@5 100.000 (99.938) +2022-11-14 16:56:20,259 Epoch: [420][160/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0204 (0.0242) Prec@1 97.000 (96.000) Prec@5 100.000 (99.941) +2022-11-14 16:56:20,542 Epoch: [420][170/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0230 (0.0242) Prec@1 96.000 (96.000) Prec@5 100.000 (99.944) +2022-11-14 16:56:20,830 Epoch: [420][180/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0330 (0.0246) Prec@1 94.000 (95.895) Prec@5 99.000 (99.895) +2022-11-14 16:56:21,124 Epoch: [420][190/500] Time 0.035 (0.021) Data 0.002 (0.003) Loss 0.0364 (0.0252) Prec@1 93.000 (95.750) Prec@5 100.000 (99.900) +2022-11-14 16:56:21,405 Epoch: [420][200/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0347 (0.0257) Prec@1 95.000 (95.714) Prec@5 100.000 (99.905) +2022-11-14 16:56:21,696 Epoch: [420][210/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0255 (0.0257) Prec@1 96.000 (95.727) Prec@5 100.000 (99.909) +2022-11-14 16:56:21,987 Epoch: [420][220/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0267 (0.0257) Prec@1 97.000 (95.783) Prec@5 99.000 (99.870) +2022-11-14 16:56:22,276 Epoch: [420][230/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0412 (0.0264) Prec@1 92.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 16:56:22,562 Epoch: [420][240/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0211 (0.0261) Prec@1 98.000 (95.720) Prec@5 99.000 (99.840) +2022-11-14 16:56:22,848 Epoch: [420][250/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0227 (0.0260) Prec@1 95.000 (95.692) Prec@5 100.000 (99.846) +2022-11-14 16:56:23,137 Epoch: [420][260/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0350 (0.0263) Prec@1 93.000 (95.593) Prec@5 100.000 (99.852) +2022-11-14 16:56:23,426 Epoch: [420][270/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0394 (0.0268) Prec@1 93.000 (95.500) Prec@5 100.000 (99.857) +2022-11-14 16:56:23,716 Epoch: [420][280/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0166 (0.0265) Prec@1 96.000 (95.517) Prec@5 100.000 (99.862) +2022-11-14 16:56:24,002 Epoch: [420][290/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0321 (0.0266) Prec@1 95.000 (95.500) Prec@5 100.000 (99.867) +2022-11-14 16:56:24,294 Epoch: [420][300/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0317 (0.0268) Prec@1 95.000 (95.484) Prec@5 100.000 (99.871) +2022-11-14 16:56:24,586 Epoch: [420][310/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0252 (0.0268) Prec@1 97.000 (95.531) Prec@5 100.000 (99.875) +2022-11-14 16:56:24,868 Epoch: [420][320/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0275 (0.0268) Prec@1 95.000 (95.515) Prec@5 100.000 (99.879) +2022-11-14 16:56:25,157 Epoch: [420][330/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0356 (0.0270) Prec@1 95.000 (95.500) Prec@5 99.000 (99.853) +2022-11-14 16:56:25,448 Epoch: [420][340/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0348 (0.0273) Prec@1 95.000 (95.486) Prec@5 100.000 (99.857) +2022-11-14 16:56:25,740 Epoch: [420][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0225 (0.0271) Prec@1 95.000 (95.472) Prec@5 100.000 (99.861) +2022-11-14 16:56:26,031 Epoch: [420][360/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0269 (0.0271) Prec@1 96.000 (95.486) Prec@5 100.000 (99.865) +2022-11-14 16:56:26,321 Epoch: [420][370/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0341 (0.0273) Prec@1 95.000 (95.474) Prec@5 100.000 (99.868) +2022-11-14 16:56:26,603 Epoch: [420][380/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0221 (0.0272) Prec@1 97.000 (95.513) Prec@5 100.000 (99.872) +2022-11-14 16:56:26,891 Epoch: [420][390/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0139 (0.0269) Prec@1 98.000 (95.575) Prec@5 100.000 (99.875) +2022-11-14 16:56:27,180 Epoch: [420][400/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0336 (0.0270) Prec@1 95.000 (95.561) Prec@5 100.000 (99.878) +2022-11-14 16:56:27,466 Epoch: [420][410/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0389 (0.0273) Prec@1 94.000 (95.524) Prec@5 100.000 (99.881) +2022-11-14 16:56:27,752 Epoch: [420][420/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0538 (0.0279) Prec@1 90.000 (95.395) Prec@5 99.000 (99.860) +2022-11-14 16:56:28,037 Epoch: [420][430/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0093 (0.0275) Prec@1 99.000 (95.477) Prec@5 100.000 (99.864) +2022-11-14 16:56:28,327 Epoch: [420][440/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0538 (0.0281) Prec@1 91.000 (95.378) Prec@5 100.000 (99.867) +2022-11-14 16:56:28,614 Epoch: [420][450/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0215 (0.0279) Prec@1 97.000 (95.413) Prec@5 100.000 (99.870) +2022-11-14 16:56:28,901 Epoch: [420][460/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0273 (0.0279) Prec@1 94.000 (95.383) Prec@5 100.000 (99.872) +2022-11-14 16:56:29,195 Epoch: [420][470/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0467 (0.0283) Prec@1 93.000 (95.333) Prec@5 100.000 (99.875) +2022-11-14 16:56:29,480 Epoch: [420][480/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0296 (0.0283) Prec@1 95.000 (95.327) Prec@5 100.000 (99.878) +2022-11-14 16:56:29,771 Epoch: [420][490/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0456 (0.0287) Prec@1 94.000 (95.300) Prec@5 100.000 (99.880) +2022-11-14 16:56:30,029 Epoch: [420][499/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0161 (0.0284) Prec@1 98.000 (95.353) Prec@5 100.000 (99.882) +2022-11-14 16:56:30,324 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0972 (0.0972) Prec@1 83.000 (83.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:30,332 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0725 (0.0849) Prec@1 89.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:30,340 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0628 (0.0775) Prec@1 90.000 (87.333) Prec@5 99.000 (99.667) +2022-11-14 16:56:30,350 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0752) Prec@1 90.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 16:56:30,356 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0736) Prec@1 90.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 16:56:30,363 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0530 (0.0702) Prec@1 91.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 16:56:30,370 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0697) Prec@1 91.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 16:56:30,379 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0700) Prec@1 87.000 (88.875) Prec@5 99.000 (99.625) +2022-11-14 16:56:30,386 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0711) Prec@1 86.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 16:56:30,393 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0729) Prec@1 88.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 16:56:30,401 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0717) Prec@1 89.000 (88.545) Prec@5 100.000 (99.545) +2022-11-14 16:56:30,408 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0736) Prec@1 86.000 (88.333) Prec@5 100.000 (99.583) +2022-11-14 16:56:30,416 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0733) Prec@1 88.000 (88.308) Prec@5 100.000 (99.615) +2022-11-14 16:56:30,424 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0731) Prec@1 90.000 (88.429) Prec@5 99.000 (99.571) +2022-11-14 16:56:30,432 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0729) Prec@1 88.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 16:56:30,439 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0726) Prec@1 87.000 (88.312) Prec@5 99.000 (99.562) +2022-11-14 16:56:30,447 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0712) Prec@1 93.000 (88.588) Prec@5 98.000 (99.471) +2022-11-14 16:56:30,455 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0727) Prec@1 85.000 (88.389) Prec@5 100.000 (99.500) +2022-11-14 16:56:30,462 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0725) Prec@1 88.000 (88.368) Prec@5 100.000 (99.526) +2022-11-14 16:56:30,469 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0732) Prec@1 85.000 (88.200) Prec@5 98.000 (99.450) +2022-11-14 16:56:30,477 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0727) Prec@1 90.000 (88.286) Prec@5 100.000 (99.476) +2022-11-14 16:56:30,484 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0735) Prec@1 88.000 (88.273) Prec@5 99.000 (99.455) +2022-11-14 16:56:30,491 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0742) Prec@1 85.000 (88.130) Prec@5 96.000 (99.304) +2022-11-14 16:56:30,499 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0744) Prec@1 87.000 (88.083) Prec@5 100.000 (99.333) +2022-11-14 16:56:30,507 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0748) Prec@1 88.000 (88.080) Prec@5 100.000 (99.360) +2022-11-14 16:56:30,514 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0759) Prec@1 86.000 (88.000) Prec@5 99.000 (99.346) +2022-11-14 16:56:30,521 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0750) Prec@1 91.000 (88.111) Prec@5 100.000 (99.370) +2022-11-14 16:56:30,529 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0743) Prec@1 91.000 (88.214) Prec@5 100.000 (99.393) +2022-11-14 16:56:30,536 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0746) Prec@1 87.000 (88.172) Prec@5 98.000 (99.345) +2022-11-14 16:56:30,544 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0745) Prec@1 89.000 (88.200) Prec@5 99.000 (99.333) +2022-11-14 16:56:30,551 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0598 (0.0740) Prec@1 90.000 (88.258) Prec@5 100.000 (99.355) +2022-11-14 16:56:30,559 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0522 (0.0733) Prec@1 92.000 (88.375) Prec@5 99.000 (99.344) +2022-11-14 16:56:30,566 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0472 (0.0725) Prec@1 92.000 (88.485) Prec@5 100.000 (99.364) +2022-11-14 16:56:30,573 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0939 (0.0731) Prec@1 86.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 16:56:30,581 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0948 (0.0738) Prec@1 87.000 (88.371) Prec@5 97.000 (99.286) +2022-11-14 16:56:30,588 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0736) Prec@1 91.000 (88.444) Prec@5 100.000 (99.306) +2022-11-14 16:56:30,595 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0742 (0.0737) Prec@1 86.000 (88.378) Prec@5 99.000 (99.297) +2022-11-14 16:56:30,603 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1197 (0.0749) Prec@1 79.000 (88.132) Prec@5 100.000 (99.316) +2022-11-14 16:56:30,610 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0542 (0.0743) Prec@1 93.000 (88.256) Prec@5 100.000 (99.333) +2022-11-14 16:56:30,617 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0630 (0.0741) Prec@1 90.000 (88.300) Prec@5 100.000 (99.350) +2022-11-14 16:56:30,625 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1027 (0.0748) Prec@1 83.000 (88.171) Prec@5 98.000 (99.317) +2022-11-14 16:56:30,633 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0701 (0.0746) Prec@1 88.000 (88.167) Prec@5 97.000 (99.262) +2022-11-14 16:56:30,640 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0447 (0.0739) Prec@1 93.000 (88.279) Prec@5 100.000 (99.279) +2022-11-14 16:56:30,647 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0739) Prec@1 88.000 (88.273) Prec@5 98.000 (99.250) +2022-11-14 16:56:30,655 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0510 (0.0734) Prec@1 91.000 (88.333) Prec@5 99.000 (99.244) +2022-11-14 16:56:30,662 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0878 (0.0737) Prec@1 85.000 (88.261) Prec@5 100.000 (99.261) +2022-11-14 16:56:30,669 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0554 (0.0733) Prec@1 89.000 (88.277) Prec@5 100.000 (99.277) +2022-11-14 16:56:30,677 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1151 (0.0742) Prec@1 83.000 (88.167) Prec@5 99.000 (99.271) +2022-11-14 16:56:30,684 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0559 (0.0738) Prec@1 90.000 (88.204) Prec@5 100.000 (99.286) +2022-11-14 16:56:30,692 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1148 (0.0746) Prec@1 83.000 (88.100) Prec@5 99.000 (99.280) +2022-11-14 16:56:30,699 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0534 (0.0742) Prec@1 90.000 (88.137) Prec@5 100.000 (99.294) +2022-11-14 16:56:30,707 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0549 (0.0738) Prec@1 94.000 (88.250) Prec@5 99.000 (99.288) +2022-11-14 16:56:30,714 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0872 (0.0741) Prec@1 87.000 (88.226) Prec@5 100.000 (99.302) +2022-11-14 16:56:30,721 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0740) Prec@1 89.000 (88.241) Prec@5 99.000 (99.296) +2022-11-14 16:56:30,729 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0803 (0.0741) Prec@1 85.000 (88.182) Prec@5 100.000 (99.309) +2022-11-14 16:56:30,736 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0614 (0.0739) Prec@1 91.000 (88.232) Prec@5 99.000 (99.304) +2022-11-14 16:56:30,744 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0656 (0.0737) Prec@1 89.000 (88.246) Prec@5 100.000 (99.316) +2022-11-14 16:56:30,751 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0737) Prec@1 90.000 (88.276) Prec@5 99.000 (99.310) +2022-11-14 16:56:30,758 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1079 (0.0743) Prec@1 82.000 (88.169) Prec@5 99.000 (99.305) +2022-11-14 16:56:30,766 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0743) Prec@1 88.000 (88.167) Prec@5 99.000 (99.300) +2022-11-14 16:56:30,773 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0745) Prec@1 85.000 (88.115) Prec@5 100.000 (99.311) +2022-11-14 16:56:30,781 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0744) Prec@1 90.000 (88.145) Prec@5 100.000 (99.323) +2022-11-14 16:56:30,788 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0875 (0.0746) Prec@1 85.000 (88.095) Prec@5 100.000 (99.333) +2022-11-14 16:56:30,796 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0392 (0.0741) Prec@1 93.000 (88.172) Prec@5 100.000 (99.344) +2022-11-14 16:56:30,804 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0993 (0.0745) Prec@1 84.000 (88.108) Prec@5 99.000 (99.338) +2022-11-14 16:56:30,811 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0851 (0.0746) Prec@1 87.000 (88.091) Prec@5 100.000 (99.348) +2022-11-14 16:56:30,819 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0478 (0.0742) Prec@1 92.000 (88.149) Prec@5 99.000 (99.343) +2022-11-14 16:56:30,826 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0742) Prec@1 89.000 (88.162) Prec@5 98.000 (99.324) +2022-11-14 16:56:30,834 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0557 (0.0740) Prec@1 90.000 (88.188) Prec@5 99.000 (99.319) +2022-11-14 16:56:30,842 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0658 (0.0738) Prec@1 90.000 (88.214) Prec@5 99.000 (99.314) +2022-11-14 16:56:30,849 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0805 (0.0739) Prec@1 88.000 (88.211) Prec@5 100.000 (99.324) +2022-11-14 16:56:30,857 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0509 (0.0736) Prec@1 93.000 (88.278) Prec@5 100.000 (99.333) +2022-11-14 16:56:30,864 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0736) Prec@1 89.000 (88.288) Prec@5 100.000 (99.342) +2022-11-14 16:56:30,872 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0456 (0.0732) Prec@1 93.000 (88.351) Prec@5 100.000 (99.351) +2022-11-14 16:56:30,879 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0734) Prec@1 84.000 (88.293) Prec@5 100.000 (99.360) +2022-11-14 16:56:30,887 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0552 (0.0732) Prec@1 91.000 (88.329) Prec@5 100.000 (99.368) +2022-11-14 16:56:30,895 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0724 (0.0732) Prec@1 87.000 (88.312) Prec@5 98.000 (99.351) +2022-11-14 16:56:30,902 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0882 (0.0734) Prec@1 87.000 (88.295) Prec@5 99.000 (99.346) +2022-11-14 16:56:30,910 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0838 (0.0735) Prec@1 86.000 (88.266) Prec@5 100.000 (99.354) +2022-11-14 16:56:30,917 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0719 (0.0735) Prec@1 88.000 (88.263) Prec@5 100.000 (99.362) +2022-11-14 16:56:30,925 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0887 (0.0737) Prec@1 86.000 (88.235) Prec@5 98.000 (99.346) +2022-11-14 16:56:30,932 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0738) Prec@1 87.000 (88.220) Prec@5 99.000 (99.341) +2022-11-14 16:56:30,940 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0777 (0.0738) Prec@1 87.000 (88.205) Prec@5 99.000 (99.337) +2022-11-14 16:56:30,948 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0738) Prec@1 87.000 (88.190) Prec@5 100.000 (99.345) +2022-11-14 16:56:30,955 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0869 (0.0740) Prec@1 86.000 (88.165) Prec@5 100.000 (99.353) +2022-11-14 16:56:30,964 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0997 (0.0743) Prec@1 83.000 (88.105) Prec@5 100.000 (99.360) +2022-11-14 16:56:30,972 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0742) Prec@1 88.000 (88.103) Prec@5 100.000 (99.368) +2022-11-14 16:56:30,979 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0742) Prec@1 87.000 (88.091) Prec@5 99.000 (99.364) +2022-11-14 16:56:30,987 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0741) Prec@1 89.000 (88.101) Prec@5 100.000 (99.371) +2022-11-14 16:56:30,995 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0686 (0.0741) Prec@1 90.000 (88.122) Prec@5 99.000 (99.367) +2022-11-14 16:56:31,002 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0556 (0.0739) Prec@1 91.000 (88.154) Prec@5 100.000 (99.374) +2022-11-14 16:56:31,010 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0584 (0.0737) Prec@1 91.000 (88.185) Prec@5 100.000 (99.380) +2022-11-14 16:56:31,017 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0861 (0.0738) Prec@1 87.000 (88.172) Prec@5 98.000 (99.366) +2022-11-14 16:56:31,025 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0737) Prec@1 90.000 (88.191) Prec@5 100.000 (99.372) +2022-11-14 16:56:31,033 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0943 (0.0740) Prec@1 83.000 (88.137) Prec@5 100.000 (99.379) +2022-11-14 16:56:31,040 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0618 (0.0738) Prec@1 88.000 (88.135) Prec@5 99.000 (99.375) +2022-11-14 16:56:31,048 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0492 (0.0736) Prec@1 93.000 (88.186) Prec@5 99.000 (99.371) +2022-11-14 16:56:31,055 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0852 (0.0737) Prec@1 88.000 (88.184) Prec@5 98.000 (99.357) +2022-11-14 16:56:31,062 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1073 (0.0740) Prec@1 85.000 (88.152) Prec@5 99.000 (99.354) +2022-11-14 16:56:31,070 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0531 (0.0738) Prec@1 91.000 (88.180) Prec@5 100.000 (99.360) +2022-11-14 16:56:31,137 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:56:31,462 Epoch: [421][0/500] Time 0.026 (0.026) Data 0.240 (0.240) Loss 0.0199 (0.0199) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:31,660 Epoch: [421][10/500] Time 0.019 (0.018) Data 0.001 (0.023) Loss 0.0471 (0.0335) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:31,849 Epoch: [421][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0223 (0.0298) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,038 Epoch: [421][30/500] Time 0.019 (0.017) Data 0.001 (0.009) Loss 0.0373 (0.0317) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,230 Epoch: [421][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0320 (0.0317) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,421 Epoch: [421][50/500] Time 0.019 (0.017) Data 0.001 (0.006) Loss 0.0390 (0.0329) Prec@1 94.000 (94.833) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,610 Epoch: [421][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0613 (0.0370) Prec@1 90.000 (94.143) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,800 Epoch: [421][70/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.0155 (0.0343) Prec@1 97.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:32,987 Epoch: [421][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0166 (0.0323) Prec@1 99.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:33,178 Epoch: [421][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0104 (0.0301) Prec@1 98.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 16:56:33,364 Epoch: [421][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0232 (0.0295) Prec@1 96.000 (95.364) Prec@5 100.000 (100.000) +2022-11-14 16:56:33,550 Epoch: [421][110/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0297 (0.0295) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 16:56:33,737 Epoch: [421][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0280 (0.0294) Prec@1 96.000 (95.385) Prec@5 100.000 (100.000) +2022-11-14 16:56:33,928 Epoch: [421][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0170 (0.0285) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:34,117 Epoch: [421][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0212 (0.0280) Prec@1 97.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 16:56:34,313 Epoch: [421][150/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0347 (0.0285) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:34,561 Epoch: [421][160/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0190 (0.0279) Prec@1 98.000 (95.647) Prec@5 99.000 (99.941) +2022-11-14 16:56:34,817 Epoch: [421][170/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0232 (0.0276) Prec@1 96.000 (95.667) Prec@5 99.000 (99.889) +2022-11-14 16:56:35,080 Epoch: [421][180/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0189 (0.0272) Prec@1 96.000 (95.684) Prec@5 100.000 (99.895) +2022-11-14 16:56:35,343 Epoch: [421][190/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0179 (0.0267) Prec@1 95.000 (95.650) Prec@5 100.000 (99.900) +2022-11-14 16:56:35,606 Epoch: [421][200/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0444 (0.0276) Prec@1 91.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 16:56:35,867 Epoch: [421][210/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0326 (0.0278) Prec@1 95.000 (95.409) Prec@5 100.000 (99.909) +2022-11-14 16:56:36,131 Epoch: [421][220/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0301 (0.0279) Prec@1 95.000 (95.391) Prec@5 100.000 (99.913) +2022-11-14 16:56:36,391 Epoch: [421][230/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0372 (0.0283) Prec@1 94.000 (95.333) Prec@5 100.000 (99.917) +2022-11-14 16:56:36,653 Epoch: [421][240/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0435 (0.0289) Prec@1 92.000 (95.200) Prec@5 100.000 (99.920) +2022-11-14 16:56:36,914 Epoch: [421][250/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0334 (0.0291) Prec@1 94.000 (95.154) Prec@5 100.000 (99.923) +2022-11-14 16:56:37,180 Epoch: [421][260/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0240 (0.0289) Prec@1 96.000 (95.185) Prec@5 100.000 (99.926) +2022-11-14 16:56:37,438 Epoch: [421][270/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0268 (0.0288) Prec@1 94.000 (95.143) Prec@5 99.000 (99.893) +2022-11-14 16:56:37,700 Epoch: [421][280/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0394 (0.0292) Prec@1 93.000 (95.069) Prec@5 100.000 (99.897) +2022-11-14 16:56:37,958 Epoch: [421][290/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0376 (0.0294) Prec@1 93.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 16:56:38,218 Epoch: [421][300/500] Time 0.028 (0.020) Data 0.001 (0.002) Loss 0.0368 (0.0297) Prec@1 94.000 (94.968) Prec@5 100.000 (99.903) +2022-11-14 16:56:38,479 Epoch: [421][310/500] Time 0.029 (0.020) Data 0.001 (0.002) Loss 0.0111 (0.0291) Prec@1 100.000 (95.125) Prec@5 100.000 (99.906) +2022-11-14 16:56:38,739 Epoch: [421][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0109 (0.0285) Prec@1 99.000 (95.242) Prec@5 99.000 (99.879) +2022-11-14 16:56:39,000 Epoch: [421][330/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0344 (0.0287) Prec@1 94.000 (95.206) Prec@5 100.000 (99.882) +2022-11-14 16:56:39,265 Epoch: [421][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0429 (0.0291) Prec@1 92.000 (95.114) Prec@5 100.000 (99.886) +2022-11-14 16:56:39,526 Epoch: [421][350/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0333 (0.0292) Prec@1 95.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:56:39,791 Epoch: [421][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0232 (0.0291) Prec@1 95.000 (95.108) Prec@5 100.000 (99.892) +2022-11-14 16:56:40,052 Epoch: [421][370/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0353 (0.0292) Prec@1 95.000 (95.105) Prec@5 99.000 (99.868) +2022-11-14 16:56:40,313 Epoch: [421][380/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0329 (0.0293) Prec@1 95.000 (95.103) Prec@5 100.000 (99.872) +2022-11-14 16:56:40,571 Epoch: [421][390/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0282 (0.0293) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 16:56:40,832 Epoch: [421][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0293) Prec@1 95.000 (95.122) Prec@5 100.000 (99.878) +2022-11-14 16:56:41,096 Epoch: [421][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0296 (0.0293) Prec@1 95.000 (95.119) Prec@5 100.000 (99.881) +2022-11-14 16:56:41,356 Epoch: [421][420/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0151 (0.0290) Prec@1 98.000 (95.186) Prec@5 100.000 (99.884) +2022-11-14 16:56:41,612 Epoch: [421][430/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0143 (0.0286) Prec@1 98.000 (95.250) Prec@5 100.000 (99.886) +2022-11-14 16:56:41,871 Epoch: [421][440/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0362 (0.0288) Prec@1 94.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 16:56:42,130 Epoch: [421][450/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0306 (0.0288) Prec@1 96.000 (95.239) Prec@5 100.000 (99.891) +2022-11-14 16:56:42,390 Epoch: [421][460/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0186 (0.0286) Prec@1 97.000 (95.277) Prec@5 99.000 (99.872) +2022-11-14 16:56:42,652 Epoch: [421][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0317 (0.0287) Prec@1 94.000 (95.250) Prec@5 99.000 (99.854) +2022-11-14 16:56:42,913 Epoch: [421][480/500] Time 0.021 (0.021) Data 0.002 (0.002) Loss 0.0179 (0.0285) Prec@1 98.000 (95.306) Prec@5 100.000 (99.857) +2022-11-14 16:56:43,179 Epoch: [421][490/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0381 (0.0287) Prec@1 94.000 (95.280) Prec@5 99.000 (99.840) +2022-11-14 16:56:43,415 Epoch: [421][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0161 (0.0284) Prec@1 98.000 (95.333) Prec@5 100.000 (99.843) +2022-11-14 16:56:43,727 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0578 (0.0578) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:43,736 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0696 (0.0637) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:43,742 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0966 (0.0746) Prec@1 85.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 16:56:43,752 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0743) Prec@1 88.000 (88.500) Prec@5 100.000 (99.750) +2022-11-14 16:56:43,759 Test: [4/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0778) Prec@1 86.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 16:56:43,766 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0315 (0.0701) Prec@1 95.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 16:56:43,773 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0671) Prec@1 93.000 (89.714) Prec@5 99.000 (99.571) +2022-11-14 16:56:43,781 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0706) Prec@1 85.000 (89.125) Prec@5 98.000 (99.375) +2022-11-14 16:56:43,788 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0716) Prec@1 86.000 (88.778) Prec@5 100.000 (99.444) +2022-11-14 16:56:43,795 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0715) Prec@1 89.000 (88.800) Prec@5 99.000 (99.400) +2022-11-14 16:56:43,802 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0714) Prec@1 88.000 (88.727) Prec@5 100.000 (99.455) +2022-11-14 16:56:43,810 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0733) Prec@1 84.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 16:56:43,817 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0719) Prec@1 91.000 (88.538) Prec@5 100.000 (99.538) +2022-11-14 16:56:43,825 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0725) Prec@1 88.000 (88.500) Prec@5 100.000 (99.571) +2022-11-14 16:56:43,833 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0728) Prec@1 88.000 (88.467) Prec@5 99.000 (99.533) +2022-11-14 16:56:43,841 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0738) Prec@1 82.000 (88.062) Prec@5 99.000 (99.500) +2022-11-14 16:56:43,849 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0720) Prec@1 93.000 (88.353) Prec@5 99.000 (99.471) +2022-11-14 16:56:43,856 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0733) Prec@1 86.000 (88.222) Prec@5 100.000 (99.500) +2022-11-14 16:56:43,864 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0738) Prec@1 86.000 (88.105) Prec@5 98.000 (99.421) +2022-11-14 16:56:43,872 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0750) Prec@1 85.000 (87.950) Prec@5 100.000 (99.450) +2022-11-14 16:56:43,879 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0747) Prec@1 91.000 (88.095) Prec@5 100.000 (99.476) +2022-11-14 16:56:43,887 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0749) Prec@1 86.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 16:56:43,895 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0760) Prec@1 87.000 (87.957) Prec@5 97.000 (99.391) +2022-11-14 16:56:43,903 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0760) Prec@1 91.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 16:56:43,911 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0771) Prec@1 84.000 (87.920) Prec@5 100.000 (99.440) +2022-11-14 16:56:43,918 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0768) Prec@1 90.000 (88.000) Prec@5 99.000 (99.423) +2022-11-14 16:56:43,927 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0760) Prec@1 93.000 (88.185) Prec@5 100.000 (99.444) +2022-11-14 16:56:43,935 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0760) Prec@1 86.000 (88.107) Prec@5 99.000 (99.429) +2022-11-14 16:56:43,943 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0757) Prec@1 91.000 (88.207) Prec@5 97.000 (99.345) +2022-11-14 16:56:43,953 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0757) Prec@1 88.000 (88.200) Prec@5 99.000 (99.333) +2022-11-14 16:56:43,962 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0760) Prec@1 85.000 (88.097) Prec@5 99.000 (99.323) +2022-11-14 16:56:43,970 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0754) Prec@1 91.000 (88.188) Prec@5 100.000 (99.344) +2022-11-14 16:56:43,977 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0754) Prec@1 90.000 (88.242) Prec@5 99.000 (99.333) +2022-11-14 16:56:43,985 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0756) Prec@1 88.000 (88.235) Prec@5 100.000 (99.353) +2022-11-14 16:56:43,993 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0759) Prec@1 85.000 (88.143) Prec@5 96.000 (99.257) +2022-11-14 16:56:44,000 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0759) Prec@1 90.000 (88.194) Prec@5 100.000 (99.278) +2022-11-14 16:56:44,008 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0755) Prec@1 91.000 (88.270) Prec@5 100.000 (99.297) +2022-11-14 16:56:44,016 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0761) Prec@1 83.000 (88.132) Prec@5 99.000 (99.289) +2022-11-14 16:56:44,024 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0754) Prec@1 93.000 (88.256) Prec@5 99.000 (99.282) +2022-11-14 16:56:44,031 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0752) Prec@1 90.000 (88.300) Prec@5 100.000 (99.300) +2022-11-14 16:56:44,039 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0756) Prec@1 85.000 (88.220) Prec@5 98.000 (99.268) +2022-11-14 16:56:44,047 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0757) Prec@1 85.000 (88.143) Prec@5 99.000 (99.262) +2022-11-14 16:56:44,054 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0752) Prec@1 90.000 (88.186) Prec@5 99.000 (99.256) +2022-11-14 16:56:44,062 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0751) Prec@1 88.000 (88.182) Prec@5 99.000 (99.250) +2022-11-14 16:56:44,070 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0749) Prec@1 89.000 (88.200) Prec@5 99.000 (99.244) +2022-11-14 16:56:44,077 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.0757) Prec@1 83.000 (88.087) Prec@5 96.000 (99.174) +2022-11-14 16:56:44,086 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0754) Prec@1 91.000 (88.149) Prec@5 99.000 (99.170) +2022-11-14 16:56:44,094 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0759) Prec@1 83.000 (88.042) Prec@5 97.000 (99.125) +2022-11-14 16:56:44,104 Test: [48/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0755) Prec@1 90.000 (88.082) Prec@5 100.000 (99.143) +2022-11-14 16:56:44,114 Test: [49/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.0763) Prec@1 84.000 (88.000) Prec@5 99.000 (99.140) +2022-11-14 16:56:44,122 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0756) Prec@1 93.000 (88.098) Prec@5 100.000 (99.157) +2022-11-14 16:56:44,131 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0757) Prec@1 88.000 (88.096) Prec@5 99.000 (99.154) +2022-11-14 16:56:44,138 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0756) Prec@1 89.000 (88.113) Prec@5 98.000 (99.132) +2022-11-14 16:56:44,146 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0756) Prec@1 90.000 (88.148) Prec@5 98.000 (99.111) +2022-11-14 16:56:44,153 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0758) Prec@1 86.000 (88.109) Prec@5 100.000 (99.127) +2022-11-14 16:56:44,161 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0756) Prec@1 91.000 (88.161) Prec@5 99.000 (99.125) +2022-11-14 16:56:44,168 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0757) Prec@1 87.000 (88.140) Prec@5 100.000 (99.140) +2022-11-14 16:56:44,176 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0754) Prec@1 92.000 (88.207) Prec@5 99.000 (99.138) +2022-11-14 16:56:44,183 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0755) Prec@1 91.000 (88.254) Prec@5 100.000 (99.153) +2022-11-14 16:56:44,191 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0756) Prec@1 85.000 (88.200) Prec@5 100.000 (99.167) +2022-11-14 16:56:44,198 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0758) Prec@1 88.000 (88.197) Prec@5 100.000 (99.180) +2022-11-14 16:56:44,206 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0758) Prec@1 86.000 (88.161) Prec@5 100.000 (99.194) +2022-11-14 16:56:44,213 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0755) Prec@1 89.000 (88.175) Prec@5 100.000 (99.206) +2022-11-14 16:56:44,220 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0754) Prec@1 91.000 (88.219) Prec@5 100.000 (99.219) +2022-11-14 16:56:44,228 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0757) Prec@1 84.000 (88.154) Prec@5 99.000 (99.215) +2022-11-14 16:56:44,235 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0759) Prec@1 87.000 (88.136) Prec@5 99.000 (99.212) +2022-11-14 16:56:44,243 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0380 (0.0753) Prec@1 95.000 (88.239) Prec@5 99.000 (99.209) +2022-11-14 16:56:44,250 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0751) Prec@1 90.000 (88.265) Prec@5 100.000 (99.221) +2022-11-14 16:56:44,258 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0748) Prec@1 89.000 (88.275) Prec@5 99.000 (99.217) +2022-11-14 16:56:44,265 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0748) Prec@1 88.000 (88.271) Prec@5 99.000 (99.214) +2022-11-14 16:56:44,273 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.0754) Prec@1 84.000 (88.211) Prec@5 99.000 (99.211) +2022-11-14 16:56:44,281 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0750) Prec@1 91.000 (88.250) Prec@5 100.000 (99.222) +2022-11-14 16:56:44,288 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0749) Prec@1 89.000 (88.260) Prec@5 100.000 (99.233) +2022-11-14 16:56:44,296 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0745) Prec@1 94.000 (88.338) Prec@5 100.000 (99.243) +2022-11-14 16:56:44,303 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0750) Prec@1 82.000 (88.253) Prec@5 98.000 (99.227) +2022-11-14 16:56:44,311 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0749) Prec@1 89.000 (88.263) Prec@5 98.000 (99.211) +2022-11-14 16:56:44,319 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0749) Prec@1 87.000 (88.247) Prec@5 99.000 (99.208) +2022-11-14 16:56:44,326 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0753) Prec@1 82.000 (88.167) Prec@5 99.000 (99.205) +2022-11-14 16:56:44,334 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0754) Prec@1 88.000 (88.165) Prec@5 100.000 (99.215) +2022-11-14 16:56:44,341 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0753) Prec@1 88.000 (88.162) Prec@5 100.000 (99.225) +2022-11-14 16:56:44,349 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0754) Prec@1 88.000 (88.160) Prec@5 97.000 (99.198) +2022-11-14 16:56:44,357 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0754) Prec@1 90.000 (88.183) Prec@5 100.000 (99.207) +2022-11-14 16:56:44,364 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0755) Prec@1 85.000 (88.145) Prec@5 100.000 (99.217) +2022-11-14 16:56:44,372 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0752) Prec@1 92.000 (88.190) Prec@5 100.000 (99.226) +2022-11-14 16:56:44,380 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0751) Prec@1 90.000 (88.212) Prec@5 100.000 (99.235) +2022-11-14 16:56:44,387 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0753) Prec@1 87.000 (88.198) Prec@5 100.000 (99.244) +2022-11-14 16:56:44,395 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0752) Prec@1 89.000 (88.207) Prec@5 100.000 (99.253) +2022-11-14 16:56:44,403 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0754) Prec@1 87.000 (88.193) Prec@5 99.000 (99.250) +2022-11-14 16:56:44,410 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0753) Prec@1 88.000 (88.191) Prec@5 100.000 (99.258) +2022-11-14 16:56:44,418 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0752) Prec@1 91.000 (88.222) Prec@5 99.000 (99.256) +2022-11-14 16:56:44,425 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0750) Prec@1 92.000 (88.264) Prec@5 100.000 (99.264) +2022-11-14 16:56:44,433 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0749) Prec@1 91.000 (88.293) Prec@5 100.000 (99.272) +2022-11-14 16:56:44,441 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0749) Prec@1 87.000 (88.280) Prec@5 100.000 (99.280) +2022-11-14 16:56:44,448 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0748) Prec@1 88.000 (88.277) Prec@5 99.000 (99.277) +2022-11-14 16:56:44,456 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0748) Prec@1 85.000 (88.242) Prec@5 99.000 (99.274) +2022-11-14 16:56:44,464 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0748) Prec@1 90.000 (88.260) Prec@5 99.000 (99.271) +2022-11-14 16:56:44,471 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0746) Prec@1 92.000 (88.299) Prec@5 99.000 (99.268) +2022-11-14 16:56:44,479 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.0748) Prec@1 85.000 (88.265) Prec@5 98.000 (99.255) +2022-11-14 16:56:44,487 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0751) Prec@1 85.000 (88.232) Prec@5 99.000 (99.253) +2022-11-14 16:56:44,495 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0749) Prec@1 92.000 (88.270) Prec@5 100.000 (99.260) +2022-11-14 16:56:44,550 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:56:44,871 Epoch: [422][0/500] Time 0.022 (0.022) Data 0.242 (0.242) Loss 0.0146 (0.0146) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:45,065 Epoch: [422][10/500] Time 0.017 (0.017) Data 0.002 (0.023) Loss 0.0380 (0.0263) Prec@1 93.000 (95.500) Prec@5 99.000 (99.500) +2022-11-14 16:56:45,263 Epoch: [422][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0230 (0.0252) Prec@1 97.000 (96.000) Prec@5 100.000 (99.667) +2022-11-14 16:56:45,454 Epoch: [422][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0379 (0.0284) Prec@1 94.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:56:45,652 Epoch: [422][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0334 (0.0294) Prec@1 95.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 16:56:45,853 Epoch: [422][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0285 (0.0292) Prec@1 96.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 16:56:46,054 Epoch: [422][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0618 (0.0339) Prec@1 89.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 16:56:46,252 Epoch: [422][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0143 (0.0314) Prec@1 98.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 16:56:46,458 Epoch: [422][80/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0454 (0.0330) Prec@1 93.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 16:56:46,653 Epoch: [422][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0252 (0.0322) Prec@1 96.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 16:56:46,866 Epoch: [422][100/500] Time 0.020 (0.018) Data 0.001 (0.004) Loss 0.0132 (0.0305) Prec@1 99.000 (95.273) Prec@5 100.000 (99.909) +2022-11-14 16:56:47,138 Epoch: [422][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0304 (0.0305) Prec@1 96.000 (95.333) Prec@5 99.000 (99.833) +2022-11-14 16:56:47,412 Epoch: [422][120/500] Time 0.022 (0.019) Data 0.002 (0.004) Loss 0.0349 (0.0308) Prec@1 94.000 (95.231) Prec@5 99.000 (99.769) +2022-11-14 16:56:47,690 Epoch: [422][130/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0536 (0.0324) Prec@1 92.000 (95.000) Prec@5 100.000 (99.786) +2022-11-14 16:56:47,964 Epoch: [422][140/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0444 (0.0332) Prec@1 93.000 (94.867) Prec@5 100.000 (99.800) +2022-11-14 16:56:48,242 Epoch: [422][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0298 (0.0330) Prec@1 95.000 (94.875) Prec@5 99.000 (99.750) +2022-11-14 16:56:48,519 Epoch: [422][160/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0395 (0.0334) Prec@1 93.000 (94.765) Prec@5 100.000 (99.765) +2022-11-14 16:56:48,800 Epoch: [422][170/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0303 (0.0332) Prec@1 94.000 (94.722) Prec@5 100.000 (99.778) +2022-11-14 16:56:49,083 Epoch: [422][180/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0361 (0.0334) Prec@1 91.000 (94.526) Prec@5 100.000 (99.789) +2022-11-14 16:56:49,360 Epoch: [422][190/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0318 (0.0333) Prec@1 95.000 (94.550) Prec@5 100.000 (99.800) +2022-11-14 16:56:49,641 Epoch: [422][200/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0503 (0.0341) Prec@1 91.000 (94.381) Prec@5 99.000 (99.762) +2022-11-14 16:56:49,912 Epoch: [422][210/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0175 (0.0334) Prec@1 96.000 (94.455) Prec@5 100.000 (99.773) +2022-11-14 16:56:50,192 Epoch: [422][220/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0239 (0.0329) Prec@1 97.000 (94.565) Prec@5 100.000 (99.783) +2022-11-14 16:56:50,465 Epoch: [422][230/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0390 (0.0332) Prec@1 94.000 (94.542) Prec@5 98.000 (99.708) +2022-11-14 16:56:50,732 Epoch: [422][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0102 (0.0323) Prec@1 98.000 (94.680) Prec@5 100.000 (99.720) +2022-11-14 16:56:50,999 Epoch: [422][250/500] Time 0.024 (0.022) Data 0.001 (0.003) Loss 0.0264 (0.0321) Prec@1 97.000 (94.769) Prec@5 100.000 (99.731) +2022-11-14 16:56:51,271 Epoch: [422][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0304 (0.0320) Prec@1 94.000 (94.741) Prec@5 100.000 (99.741) +2022-11-14 16:56:51,540 Epoch: [422][270/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0405 (0.0323) Prec@1 95.000 (94.750) Prec@5 99.000 (99.714) +2022-11-14 16:56:51,814 Epoch: [422][280/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0166 (0.0318) Prec@1 98.000 (94.862) Prec@5 100.000 (99.724) +2022-11-14 16:56:52,089 Epoch: [422][290/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0287 (0.0317) Prec@1 95.000 (94.867) Prec@5 100.000 (99.733) +2022-11-14 16:56:52,356 Epoch: [422][300/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0169 (0.0312) Prec@1 98.000 (94.968) Prec@5 100.000 (99.742) +2022-11-14 16:56:52,628 Epoch: [422][310/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0457 (0.0316) Prec@1 89.000 (94.781) Prec@5 100.000 (99.750) +2022-11-14 16:56:52,897 Epoch: [422][320/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0071 (0.0309) Prec@1 100.000 (94.939) Prec@5 100.000 (99.758) +2022-11-14 16:56:53,168 Epoch: [422][330/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0369 (0.0311) Prec@1 96.000 (94.971) Prec@5 100.000 (99.765) +2022-11-14 16:56:53,437 Epoch: [422][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0386 (0.0313) Prec@1 95.000 (94.971) Prec@5 100.000 (99.771) +2022-11-14 16:56:53,703 Epoch: [422][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0338 (0.0313) Prec@1 94.000 (94.944) Prec@5 100.000 (99.778) +2022-11-14 16:56:53,971 Epoch: [422][360/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0237 (0.0311) Prec@1 96.000 (94.973) Prec@5 100.000 (99.784) +2022-11-14 16:56:54,240 Epoch: [422][370/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0125 (0.0307) Prec@1 100.000 (95.105) Prec@5 100.000 (99.789) +2022-11-14 16:56:54,513 Epoch: [422][380/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0177 (0.0303) Prec@1 98.000 (95.179) Prec@5 100.000 (99.795) +2022-11-14 16:56:54,786 Epoch: [422][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0126 (0.0299) Prec@1 97.000 (95.225) Prec@5 100.000 (99.800) +2022-11-14 16:56:55,058 Epoch: [422][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0274 (0.0298) Prec@1 96.000 (95.244) Prec@5 100.000 (99.805) +2022-11-14 16:56:55,330 Epoch: [422][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0324 (0.0299) Prec@1 95.000 (95.238) Prec@5 100.000 (99.810) +2022-11-14 16:56:55,603 Epoch: [422][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0252 (0.0298) Prec@1 96.000 (95.256) Prec@5 100.000 (99.814) +2022-11-14 16:56:55,873 Epoch: [422][430/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0241 (0.0296) Prec@1 96.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 16:56:56,149 Epoch: [422][440/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0271 (0.0296) Prec@1 96.000 (95.289) Prec@5 100.000 (99.822) +2022-11-14 16:56:56,421 Epoch: [422][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0225 (0.0294) Prec@1 97.000 (95.326) Prec@5 100.000 (99.826) +2022-11-14 16:56:56,692 Epoch: [422][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0263 (0.0294) Prec@1 95.000 (95.319) Prec@5 100.000 (99.830) +2022-11-14 16:56:56,959 Epoch: [422][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0133 (0.0290) Prec@1 97.000 (95.354) Prec@5 100.000 (99.833) +2022-11-14 16:56:57,229 Epoch: [422][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0306 (0.0291) Prec@1 95.000 (95.347) Prec@5 100.000 (99.837) +2022-11-14 16:56:57,497 Epoch: [422][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0211 (0.0289) Prec@1 95.000 (95.340) Prec@5 100.000 (99.840) +2022-11-14 16:56:57,739 Epoch: [422][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0150 (0.0286) Prec@1 97.000 (95.373) Prec@5 100.000 (99.843) +2022-11-14 16:56:58,031 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0610 (0.0610) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:58,040 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0759 (0.0684) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:56:58,047 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0656) Prec@1 91.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 16:56:58,057 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0668) Prec@1 89.000 (89.750) Prec@5 100.000 (99.750) +2022-11-14 16:56:58,064 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0602 (0.0655) Prec@1 91.000 (90.000) Prec@5 100.000 (99.800) +2022-11-14 16:56:58,071 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0612) Prec@1 95.000 (90.833) Prec@5 100.000 (99.833) +2022-11-14 16:56:58,078 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0616) Prec@1 91.000 (90.857) Prec@5 100.000 (99.857) +2022-11-14 16:56:58,086 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0647) Prec@1 86.000 (90.250) Prec@5 100.000 (99.875) +2022-11-14 16:56:58,093 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0653) Prec@1 90.000 (90.222) Prec@5 99.000 (99.778) +2022-11-14 16:56:58,101 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0670) Prec@1 85.000 (89.700) Prec@5 97.000 (99.500) +2022-11-14 16:56:58,109 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0674) Prec@1 88.000 (89.545) Prec@5 100.000 (99.545) +2022-11-14 16:56:58,117 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0693) Prec@1 83.000 (89.000) Prec@5 100.000 (99.583) +2022-11-14 16:56:58,124 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0681) Prec@1 92.000 (89.231) Prec@5 100.000 (99.615) +2022-11-14 16:56:58,132 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0699) Prec@1 86.000 (89.000) Prec@5 100.000 (99.643) +2022-11-14 16:56:58,140 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0701) Prec@1 88.000 (88.933) Prec@5 100.000 (99.667) +2022-11-14 16:56:58,148 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0707) Prec@1 87.000 (88.812) Prec@5 99.000 (99.625) +2022-11-14 16:56:58,156 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0693) Prec@1 92.000 (89.000) Prec@5 99.000 (99.588) +2022-11-14 16:56:58,165 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.0718) Prec@1 84.000 (88.722) Prec@5 100.000 (99.611) +2022-11-14 16:56:58,173 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0726) Prec@1 85.000 (88.526) Prec@5 98.000 (99.526) +2022-11-14 16:56:58,182 Test: [19/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0735) Prec@1 85.000 (88.350) Prec@5 99.000 (99.500) +2022-11-14 16:56:58,191 Test: [20/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0732) Prec@1 87.000 (88.286) Prec@5 100.000 (99.524) +2022-11-14 16:56:58,200 Test: [21/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0730) Prec@1 90.000 (88.364) Prec@5 100.000 (99.545) +2022-11-14 16:56:58,209 Test: [22/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1022 (0.0743) Prec@1 85.000 (88.217) Prec@5 98.000 (99.478) +2022-11-14 16:56:58,217 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0747) Prec@1 86.000 (88.125) Prec@5 100.000 (99.500) +2022-11-14 16:56:58,226 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0758) Prec@1 84.000 (87.960) Prec@5 100.000 (99.520) +2022-11-14 16:56:58,233 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0764) Prec@1 84.000 (87.808) Prec@5 98.000 (99.462) +2022-11-14 16:56:58,241 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0754) Prec@1 92.000 (87.963) Prec@5 100.000 (99.481) +2022-11-14 16:56:58,249 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0746) Prec@1 91.000 (88.071) Prec@5 99.000 (99.464) +2022-11-14 16:56:58,256 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0744) Prec@1 89.000 (88.103) Prec@5 99.000 (99.448) +2022-11-14 16:56:58,264 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0740) Prec@1 90.000 (88.167) Prec@5 100.000 (99.467) +2022-11-14 16:56:58,272 Test: [30/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0737) Prec@1 89.000 (88.194) Prec@5 99.000 (99.452) +2022-11-14 16:56:58,280 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0731) Prec@1 91.000 (88.281) Prec@5 100.000 (99.469) +2022-11-14 16:56:58,288 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0738) Prec@1 85.000 (88.182) Prec@5 100.000 (99.485) +2022-11-14 16:56:58,296 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0741) Prec@1 88.000 (88.176) Prec@5 98.000 (99.441) +2022-11-14 16:56:58,304 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0745) Prec@1 86.000 (88.114) Prec@5 97.000 (99.371) +2022-11-14 16:56:58,311 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0742) Prec@1 92.000 (88.222) Prec@5 100.000 (99.389) +2022-11-14 16:56:58,319 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0739) Prec@1 91.000 (88.297) Prec@5 99.000 (99.378) +2022-11-14 16:56:58,327 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0748) Prec@1 81.000 (88.105) Prec@5 100.000 (99.395) +2022-11-14 16:56:58,334 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0743) Prec@1 93.000 (88.231) Prec@5 99.000 (99.385) +2022-11-14 16:56:58,342 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0739) Prec@1 87.000 (88.200) Prec@5 99.000 (99.375) +2022-11-14 16:56:58,349 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0746) Prec@1 86.000 (88.146) Prec@5 99.000 (99.366) +2022-11-14 16:56:58,357 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0745) Prec@1 89.000 (88.167) Prec@5 99.000 (99.357) +2022-11-14 16:56:58,364 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0739) Prec@1 92.000 (88.256) Prec@5 99.000 (99.349) +2022-11-14 16:56:58,371 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0737) Prec@1 89.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 16:56:58,379 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0735) Prec@1 91.000 (88.333) Prec@5 100.000 (99.378) +2022-11-14 16:56:58,387 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0742) Prec@1 83.000 (88.217) Prec@5 99.000 (99.370) +2022-11-14 16:56:58,394 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0744) Prec@1 86.000 (88.170) Prec@5 100.000 (99.383) +2022-11-14 16:56:58,402 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0750) Prec@1 81.000 (88.021) Prec@5 99.000 (99.375) +2022-11-14 16:56:58,409 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0745) Prec@1 92.000 (88.102) Prec@5 98.000 (99.347) +2022-11-14 16:56:58,417 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0753) Prec@1 83.000 (88.000) Prec@5 99.000 (99.340) +2022-11-14 16:56:58,424 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0751) Prec@1 87.000 (87.980) Prec@5 100.000 (99.353) +2022-11-14 16:56:58,432 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0754) Prec@1 87.000 (87.962) Prec@5 99.000 (99.346) +2022-11-14 16:56:58,439 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0752) Prec@1 89.000 (87.981) Prec@5 100.000 (99.358) +2022-11-14 16:56:58,447 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0749) Prec@1 90.000 (88.019) Prec@5 99.000 (99.352) +2022-11-14 16:56:58,454 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0750) Prec@1 85.000 (87.964) Prec@5 100.000 (99.364) +2022-11-14 16:56:58,462 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0752) Prec@1 86.000 (87.929) Prec@5 99.000 (99.357) +2022-11-14 16:56:58,469 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0749) Prec@1 92.000 (88.000) Prec@5 100.000 (99.368) +2022-11-14 16:56:58,477 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0746) Prec@1 92.000 (88.069) Prec@5 100.000 (99.379) +2022-11-14 16:56:58,485 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0749) Prec@1 83.000 (87.983) Prec@5 100.000 (99.390) +2022-11-14 16:56:58,492 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0750) Prec@1 86.000 (87.950) Prec@5 99.000 (99.383) +2022-11-14 16:56:58,500 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0754) Prec@1 82.000 (87.852) Prec@5 99.000 (99.377) +2022-11-14 16:56:58,507 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0751) Prec@1 89.000 (87.871) Prec@5 99.000 (99.371) +2022-11-14 16:56:58,515 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0749) Prec@1 91.000 (87.921) Prec@5 99.000 (99.365) +2022-11-14 16:56:58,523 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0745) Prec@1 93.000 (88.000) Prec@5 100.000 (99.375) +2022-11-14 16:56:58,530 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.0750) Prec@1 81.000 (87.892) Prec@5 100.000 (99.385) +2022-11-14 16:56:58,538 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0749) Prec@1 87.000 (87.879) Prec@5 100.000 (99.394) +2022-11-14 16:56:58,546 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0352 (0.0744) Prec@1 94.000 (87.970) Prec@5 100.000 (99.403) +2022-11-14 16:56:58,553 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0746) Prec@1 88.000 (87.971) Prec@5 99.000 (99.397) +2022-11-14 16:56:58,560 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0747) Prec@1 87.000 (87.957) Prec@5 99.000 (99.391) +2022-11-14 16:56:58,568 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0748) Prec@1 90.000 (87.986) Prec@5 97.000 (99.357) +2022-11-14 16:56:58,576 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0752) Prec@1 87.000 (87.972) Prec@5 100.000 (99.366) +2022-11-14 16:56:58,583 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0748) Prec@1 92.000 (88.028) Prec@5 100.000 (99.375) +2022-11-14 16:56:58,591 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0391 (0.0743) Prec@1 93.000 (88.096) Prec@5 100.000 (99.384) +2022-11-14 16:56:58,598 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0409 (0.0738) Prec@1 94.000 (88.176) Prec@5 100.000 (99.392) +2022-11-14 16:56:58,606 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0741) Prec@1 84.000 (88.120) Prec@5 100.000 (99.400) +2022-11-14 16:56:58,613 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0738) Prec@1 93.000 (88.184) Prec@5 98.000 (99.382) +2022-11-14 16:56:58,621 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0737) Prec@1 91.000 (88.221) Prec@5 98.000 (99.364) +2022-11-14 16:56:58,629 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0739) Prec@1 87.000 (88.205) Prec@5 98.000 (99.346) +2022-11-14 16:56:58,637 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0741) Prec@1 86.000 (88.177) Prec@5 100.000 (99.354) +2022-11-14 16:56:58,645 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0740) Prec@1 87.000 (88.162) Prec@5 100.000 (99.362) +2022-11-14 16:56:58,653 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0741) Prec@1 89.000 (88.173) Prec@5 97.000 (99.333) +2022-11-14 16:56:58,661 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0745) Prec@1 85.000 (88.134) Prec@5 100.000 (99.341) +2022-11-14 16:56:58,668 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0746) Prec@1 86.000 (88.108) Prec@5 100.000 (99.349) +2022-11-14 16:56:58,676 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0745) Prec@1 90.000 (88.131) Prec@5 100.000 (99.357) +2022-11-14 16:56:58,684 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0748) Prec@1 83.000 (88.071) Prec@5 100.000 (99.365) +2022-11-14 16:56:58,691 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.0753) Prec@1 81.000 (87.988) Prec@5 100.000 (99.372) +2022-11-14 16:56:58,699 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0751) Prec@1 88.000 (87.989) Prec@5 100.000 (99.379) +2022-11-14 16:56:58,707 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0751) Prec@1 91.000 (88.023) Prec@5 98.000 (99.364) +2022-11-14 16:56:58,715 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0749) Prec@1 88.000 (88.022) Prec@5 100.000 (99.371) +2022-11-14 16:56:58,723 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0748) Prec@1 92.000 (88.067) Prec@5 100.000 (99.378) +2022-11-14 16:56:58,730 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0745) Prec@1 94.000 (88.132) Prec@5 99.000 (99.374) +2022-11-14 16:56:58,738 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0744) Prec@1 90.000 (88.152) Prec@5 100.000 (99.380) +2022-11-14 16:56:58,745 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0744) Prec@1 86.000 (88.129) Prec@5 100.000 (99.387) +2022-11-14 16:56:58,753 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0746) Prec@1 87.000 (88.117) Prec@5 100.000 (99.394) +2022-11-14 16:56:58,760 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0745) Prec@1 88.000 (88.116) Prec@5 99.000 (99.389) +2022-11-14 16:56:58,768 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0743) Prec@1 93.000 (88.167) Prec@5 98.000 (99.375) +2022-11-14 16:56:58,776 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0742) Prec@1 91.000 (88.196) Prec@5 98.000 (99.361) +2022-11-14 16:56:58,784 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1059 (0.0745) Prec@1 84.000 (88.153) Prec@5 98.000 (99.347) +2022-11-14 16:56:58,792 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0747) Prec@1 85.000 (88.121) Prec@5 99.000 (99.343) +2022-11-14 16:56:58,799 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0748) Prec@1 86.000 (88.100) Prec@5 99.000 (99.340) +2022-11-14 16:56:58,852 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:56:59,176 Epoch: [423][0/500] Time 0.022 (0.022) Data 0.244 (0.244) Loss 0.0260 (0.0260) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:59,368 Epoch: [423][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0192 (0.0226) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:59,556 Epoch: [423][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0113 (0.0188) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:56:59,745 Epoch: [423][30/500] Time 0.018 (0.017) Data 0.001 (0.009) Loss 0.0469 (0.0258) Prec@1 92.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 16:56:59,936 Epoch: [423][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0141 (0.0235) Prec@1 98.000 (96.200) Prec@5 100.000 (100.000) +2022-11-14 16:57:00,152 Epoch: [423][50/500] Time 0.021 (0.017) Data 0.002 (0.006) Loss 0.0183 (0.0226) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:57:00,348 Epoch: [423][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0204 (0.0223) Prec@1 98.000 (96.571) Prec@5 100.000 (100.000) +2022-11-14 16:57:00,543 Epoch: [423][70/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0087 (0.0206) Prec@1 99.000 (96.875) Prec@5 100.000 (100.000) +2022-11-14 16:57:00,729 Epoch: [423][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0197 (0.0205) Prec@1 96.000 (96.778) Prec@5 100.000 (100.000) +2022-11-14 16:57:00,917 Epoch: [423][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0296 (0.0214) Prec@1 94.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:01,112 Epoch: [423][100/500] Time 0.019 (0.017) Data 0.002 (0.004) Loss 0.0262 (0.0219) Prec@1 96.000 (96.455) Prec@5 100.000 (100.000) +2022-11-14 16:57:01,305 Epoch: [423][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0362 (0.0230) Prec@1 94.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 16:57:01,582 Epoch: [423][120/500] Time 0.029 (0.018) Data 0.001 (0.004) Loss 0.0235 (0.0231) Prec@1 96.000 (96.231) Prec@5 100.000 (100.000) +2022-11-14 16:57:01,880 Epoch: [423][130/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0246 (0.0232) Prec@1 97.000 (96.286) Prec@5 100.000 (100.000) +2022-11-14 16:57:02,180 Epoch: [423][140/500] Time 0.029 (0.019) Data 0.001 (0.003) Loss 0.0192 (0.0229) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:57:02,480 Epoch: [423][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0252 (0.0231) Prec@1 96.000 (96.312) Prec@5 100.000 (100.000) +2022-11-14 16:57:02,782 Epoch: [423][160/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0218 (0.0230) Prec@1 96.000 (96.294) Prec@5 100.000 (100.000) +2022-11-14 16:57:03,080 Epoch: [423][170/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0248 (0.0231) Prec@1 93.000 (96.111) Prec@5 100.000 (100.000) +2022-11-14 16:57:03,379 Epoch: [423][180/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0220 (0.0230) Prec@1 96.000 (96.105) Prec@5 99.000 (99.947) +2022-11-14 16:57:03,671 Epoch: [423][190/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0281 (0.0233) Prec@1 96.000 (96.100) Prec@5 100.000 (99.950) +2022-11-14 16:57:03,964 Epoch: [423][200/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0286 (0.0235) Prec@1 95.000 (96.048) Prec@5 100.000 (99.952) +2022-11-14 16:57:04,251 Epoch: [423][210/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0259 (0.0236) Prec@1 96.000 (96.045) Prec@5 100.000 (99.955) +2022-11-14 16:57:04,537 Epoch: [423][220/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0370 (0.0242) Prec@1 94.000 (95.957) Prec@5 100.000 (99.957) +2022-11-14 16:57:04,829 Epoch: [423][230/500] Time 0.027 (0.022) Data 0.003 (0.003) Loss 0.0270 (0.0243) Prec@1 96.000 (95.958) Prec@5 100.000 (99.958) +2022-11-14 16:57:05,122 Epoch: [423][240/500] Time 0.033 (0.022) Data 0.002 (0.003) Loss 0.0283 (0.0245) Prec@1 95.000 (95.920) Prec@5 100.000 (99.960) +2022-11-14 16:57:05,410 Epoch: [423][250/500] Time 0.029 (0.022) Data 0.001 (0.003) Loss 0.0100 (0.0239) Prec@1 99.000 (96.038) Prec@5 100.000 (99.962) +2022-11-14 16:57:05,704 Epoch: [423][260/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0284 (0.0241) Prec@1 95.000 (96.000) Prec@5 100.000 (99.963) +2022-11-14 16:57:05,989 Epoch: [423][270/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0291 (0.0243) Prec@1 93.000 (95.893) Prec@5 100.000 (99.964) +2022-11-14 16:57:06,285 Epoch: [423][280/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0356 (0.0247) Prec@1 94.000 (95.828) Prec@5 99.000 (99.931) +2022-11-14 16:57:06,582 Epoch: [423][290/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0303 (0.0249) Prec@1 96.000 (95.833) Prec@5 100.000 (99.933) +2022-11-14 16:57:06,873 Epoch: [423][300/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0199 (0.0247) Prec@1 97.000 (95.871) Prec@5 100.000 (99.935) +2022-11-14 16:57:07,165 Epoch: [423][310/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0402 (0.0252) Prec@1 93.000 (95.781) Prec@5 100.000 (99.938) +2022-11-14 16:57:07,460 Epoch: [423][320/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0276 (0.0253) Prec@1 95.000 (95.758) Prec@5 100.000 (99.939) +2022-11-14 16:57:07,746 Epoch: [423][330/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0383 (0.0256) Prec@1 95.000 (95.735) Prec@5 99.000 (99.912) +2022-11-14 16:57:08,039 Epoch: [423][340/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0296 (0.0258) Prec@1 95.000 (95.714) Prec@5 100.000 (99.914) +2022-11-14 16:57:08,333 Epoch: [423][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0377 (0.0261) Prec@1 94.000 (95.667) Prec@5 100.000 (99.917) +2022-11-14 16:57:08,626 Epoch: [423][360/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0262 (0.0261) Prec@1 97.000 (95.703) Prec@5 99.000 (99.892) +2022-11-14 16:57:08,918 Epoch: [423][370/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0035 (0.0255) Prec@1 100.000 (95.816) Prec@5 100.000 (99.895) +2022-11-14 16:57:09,214 Epoch: [423][380/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0340 (0.0257) Prec@1 94.000 (95.769) Prec@5 99.000 (99.872) +2022-11-14 16:57:09,508 Epoch: [423][390/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0162 (0.0255) Prec@1 98.000 (95.825) Prec@5 100.000 (99.875) +2022-11-14 16:57:09,803 Epoch: [423][400/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0632 (0.0264) Prec@1 89.000 (95.659) Prec@5 98.000 (99.829) +2022-11-14 16:57:10,098 Epoch: [423][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0306 (0.0265) Prec@1 96.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 16:57:10,386 Epoch: [423][420/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0286 (0.0265) Prec@1 95.000 (95.651) Prec@5 99.000 (99.814) +2022-11-14 16:57:10,677 Epoch: [423][430/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0430 (0.0269) Prec@1 92.000 (95.568) Prec@5 100.000 (99.818) +2022-11-14 16:57:10,973 Epoch: [423][440/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0181 (0.0267) Prec@1 97.000 (95.600) Prec@5 100.000 (99.822) +2022-11-14 16:57:11,265 Epoch: [423][450/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0483 (0.0272) Prec@1 92.000 (95.522) Prec@5 100.000 (99.826) +2022-11-14 16:57:11,562 Epoch: [423][460/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0339 (0.0273) Prec@1 93.000 (95.468) Prec@5 99.000 (99.809) +2022-11-14 16:57:11,856 Epoch: [423][470/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0335 (0.0275) Prec@1 95.000 (95.458) Prec@5 99.000 (99.792) +2022-11-14 16:57:12,153 Epoch: [423][480/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0225 (0.0274) Prec@1 96.000 (95.469) Prec@5 100.000 (99.796) +2022-11-14 16:57:12,444 Epoch: [423][490/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0414 (0.0276) Prec@1 93.000 (95.420) Prec@5 100.000 (99.800) +2022-11-14 16:57:12,706 Epoch: [423][499/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0329 (0.0277) Prec@1 94.000 (95.392) Prec@5 100.000 (99.804) +2022-11-14 16:57:13,019 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0675 (0.0675) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:13,027 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0721) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:13,034 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0773) Prec@1 88.000 (88.000) Prec@5 99.000 (99.667) +2022-11-14 16:57:13,043 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0793) Prec@1 86.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 16:57:13,050 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0751) Prec@1 90.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 16:57:13,057 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0699) Prec@1 92.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 16:57:13,064 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0688) Prec@1 92.000 (89.143) Prec@5 99.000 (99.571) +2022-11-14 16:57:13,072 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0694) Prec@1 86.000 (88.750) Prec@5 100.000 (99.625) +2022-11-14 16:57:13,080 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0711) Prec@1 89.000 (88.778) Prec@5 99.000 (99.556) +2022-11-14 16:57:13,086 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0709) Prec@1 90.000 (88.900) Prec@5 99.000 (99.500) +2022-11-14 16:57:13,094 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0699) Prec@1 92.000 (89.182) Prec@5 99.000 (99.455) +2022-11-14 16:57:13,102 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0705) Prec@1 86.000 (88.917) Prec@5 100.000 (99.500) +2022-11-14 16:57:13,109 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0701) Prec@1 91.000 (89.077) Prec@5 99.000 (99.462) +2022-11-14 16:57:13,117 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0706) Prec@1 89.000 (89.071) Prec@5 99.000 (99.429) +2022-11-14 16:57:13,125 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0710) Prec@1 87.000 (88.933) Prec@5 99.000 (99.400) +2022-11-14 16:57:13,133 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0701) Prec@1 91.000 (89.062) Prec@5 99.000 (99.375) +2022-11-14 16:57:13,141 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0687) Prec@1 92.000 (89.235) Prec@5 99.000 (99.353) +2022-11-14 16:57:13,148 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0703) Prec@1 84.000 (88.944) Prec@5 100.000 (99.389) +2022-11-14 16:57:13,156 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0707) Prec@1 86.000 (88.789) Prec@5 99.000 (99.368) +2022-11-14 16:57:13,164 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0720) Prec@1 83.000 (88.500) Prec@5 99.000 (99.350) +2022-11-14 16:57:13,172 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0719) Prec@1 89.000 (88.524) Prec@5 99.000 (99.333) +2022-11-14 16:57:13,180 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0734) Prec@1 84.000 (88.318) Prec@5 99.000 (99.318) +2022-11-14 16:57:13,187 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0752) Prec@1 84.000 (88.130) Prec@5 98.000 (99.261) +2022-11-14 16:57:13,195 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0743) Prec@1 92.000 (88.292) Prec@5 100.000 (99.292) +2022-11-14 16:57:13,203 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0748) Prec@1 88.000 (88.280) Prec@5 100.000 (99.320) +2022-11-14 16:57:13,211 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0751) Prec@1 88.000 (88.269) Prec@5 97.000 (99.231) +2022-11-14 16:57:13,219 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0739) Prec@1 94.000 (88.481) Prec@5 100.000 (99.259) +2022-11-14 16:57:13,227 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0733) Prec@1 91.000 (88.571) Prec@5 99.000 (99.250) +2022-11-14 16:57:13,234 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0736) Prec@1 88.000 (88.552) Prec@5 97.000 (99.172) +2022-11-14 16:57:13,242 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0734) Prec@1 90.000 (88.600) Prec@5 99.000 (99.167) +2022-11-14 16:57:13,250 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0735) Prec@1 89.000 (88.613) Prec@5 100.000 (99.194) +2022-11-14 16:57:13,257 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0730) Prec@1 91.000 (88.688) Prec@5 99.000 (99.188) +2022-11-14 16:57:13,265 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0733) Prec@1 84.000 (88.545) Prec@5 99.000 (99.182) +2022-11-14 16:57:13,273 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0733) Prec@1 88.000 (88.529) Prec@5 100.000 (99.206) +2022-11-14 16:57:13,280 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0733) Prec@1 88.000 (88.514) Prec@5 97.000 (99.143) +2022-11-14 16:57:13,288 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0732) Prec@1 91.000 (88.583) Prec@5 100.000 (99.167) +2022-11-14 16:57:13,296 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0729) Prec@1 91.000 (88.649) Prec@5 98.000 (99.135) +2022-11-14 16:57:13,303 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0734) Prec@1 84.000 (88.526) Prec@5 100.000 (99.158) +2022-11-14 16:57:13,311 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0731) Prec@1 93.000 (88.641) Prec@5 99.000 (99.154) +2022-11-14 16:57:13,319 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0726) Prec@1 93.000 (88.750) Prec@5 100.000 (99.175) +2022-11-14 16:57:13,326 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0727) Prec@1 88.000 (88.732) Prec@5 98.000 (99.146) +2022-11-14 16:57:13,334 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0727) Prec@1 89.000 (88.738) Prec@5 100.000 (99.167) +2022-11-14 16:57:13,342 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0724) Prec@1 91.000 (88.791) Prec@5 99.000 (99.163) +2022-11-14 16:57:13,349 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0724) Prec@1 90.000 (88.818) Prec@5 99.000 (99.159) +2022-11-14 16:57:13,357 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0725) Prec@1 88.000 (88.800) Prec@5 98.000 (99.133) +2022-11-14 16:57:13,366 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0732) Prec@1 82.000 (88.652) Prec@5 100.000 (99.152) +2022-11-14 16:57:13,373 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0730) Prec@1 89.000 (88.660) Prec@5 100.000 (99.170) +2022-11-14 16:57:13,381 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0735) Prec@1 85.000 (88.583) Prec@5 98.000 (99.146) +2022-11-14 16:57:13,389 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0731) Prec@1 91.000 (88.633) Prec@5 100.000 (99.163) +2022-11-14 16:57:13,396 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1392 (0.0744) Prec@1 79.000 (88.440) Prec@5 100.000 (99.180) +2022-11-14 16:57:13,404 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0740) Prec@1 91.000 (88.490) Prec@5 100.000 (99.196) +2022-11-14 16:57:13,412 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0742) Prec@1 87.000 (88.462) Prec@5 99.000 (99.192) +2022-11-14 16:57:13,419 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0745) Prec@1 87.000 (88.434) Prec@5 100.000 (99.208) +2022-11-14 16:57:13,427 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0741) Prec@1 92.000 (88.500) Prec@5 99.000 (99.204) +2022-11-14 16:57:13,435 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0742) Prec@1 87.000 (88.473) Prec@5 100.000 (99.218) +2022-11-14 16:57:13,442 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0740) Prec@1 91.000 (88.518) Prec@5 100.000 (99.232) +2022-11-14 16:57:13,450 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0741) Prec@1 88.000 (88.509) Prec@5 99.000 (99.228) +2022-11-14 16:57:13,457 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0740) Prec@1 91.000 (88.552) Prec@5 99.000 (99.224) +2022-11-14 16:57:13,465 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0742) Prec@1 84.000 (88.475) Prec@5 100.000 (99.237) +2022-11-14 16:57:13,473 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0744) Prec@1 87.000 (88.450) Prec@5 100.000 (99.250) +2022-11-14 16:57:13,480 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0745) Prec@1 86.000 (88.410) Prec@5 99.000 (99.246) +2022-11-14 16:57:13,488 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0745) Prec@1 89.000 (88.419) Prec@5 99.000 (99.242) +2022-11-14 16:57:13,496 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0746) Prec@1 86.000 (88.381) Prec@5 100.000 (99.254) +2022-11-14 16:57:13,504 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0344 (0.0739) Prec@1 94.000 (88.469) Prec@5 99.000 (99.250) +2022-11-14 16:57:13,511 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0743) Prec@1 81.000 (88.354) Prec@5 100.000 (99.262) +2022-11-14 16:57:13,519 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0741) Prec@1 91.000 (88.394) Prec@5 99.000 (99.258) +2022-11-14 16:57:13,526 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0737) Prec@1 92.000 (88.448) Prec@5 100.000 (99.269) +2022-11-14 16:57:13,534 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0735) Prec@1 89.000 (88.456) Prec@5 100.000 (99.279) +2022-11-14 16:57:13,542 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0733) Prec@1 90.000 (88.478) Prec@5 99.000 (99.275) +2022-11-14 16:57:13,549 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0735) Prec@1 88.000 (88.471) Prec@5 99.000 (99.271) +2022-11-14 16:57:13,557 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1144 (0.0741) Prec@1 84.000 (88.408) Prec@5 97.000 (99.239) +2022-11-14 16:57:13,564 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0739) Prec@1 91.000 (88.444) Prec@5 99.000 (99.236) +2022-11-14 16:57:13,572 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0738) Prec@1 88.000 (88.438) Prec@5 100.000 (99.247) +2022-11-14 16:57:13,580 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0734) Prec@1 93.000 (88.500) Prec@5 100.000 (99.257) +2022-11-14 16:57:13,588 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0736) Prec@1 89.000 (88.507) Prec@5 99.000 (99.253) +2022-11-14 16:57:13,595 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0736) Prec@1 88.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 16:57:13,603 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0736) Prec@1 87.000 (88.481) Prec@5 99.000 (99.247) +2022-11-14 16:57:13,610 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0738) Prec@1 88.000 (88.474) Prec@5 100.000 (99.256) +2022-11-14 16:57:13,618 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0736) Prec@1 89.000 (88.481) Prec@5 100.000 (99.266) +2022-11-14 16:57:13,626 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0737) Prec@1 83.000 (88.412) Prec@5 100.000 (99.275) +2022-11-14 16:57:13,633 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0738) Prec@1 89.000 (88.420) Prec@5 99.000 (99.272) +2022-11-14 16:57:13,641 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1061 (0.0742) Prec@1 86.000 (88.390) Prec@5 100.000 (99.280) +2022-11-14 16:57:13,649 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0742) Prec@1 90.000 (88.410) Prec@5 100.000 (99.289) +2022-11-14 16:57:13,656 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0742) Prec@1 88.000 (88.405) Prec@5 99.000 (99.286) +2022-11-14 16:57:13,664 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1219 (0.0748) Prec@1 78.000 (88.282) Prec@5 99.000 (99.282) +2022-11-14 16:57:13,672 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1088 (0.0752) Prec@1 82.000 (88.209) Prec@5 100.000 (99.291) +2022-11-14 16:57:13,680 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0750) Prec@1 89.000 (88.218) Prec@5 99.000 (99.287) +2022-11-14 16:57:13,687 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0750) Prec@1 87.000 (88.205) Prec@5 99.000 (99.284) +2022-11-14 16:57:13,695 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0751) Prec@1 85.000 (88.169) Prec@5 100.000 (99.292) +2022-11-14 16:57:13,703 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0750) Prec@1 90.000 (88.189) Prec@5 99.000 (99.289) +2022-11-14 16:57:13,711 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0750) Prec@1 89.000 (88.198) Prec@5 100.000 (99.297) +2022-11-14 16:57:13,718 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0746) Prec@1 93.000 (88.250) Prec@5 100.000 (99.304) +2022-11-14 16:57:13,726 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0749) Prec@1 85.000 (88.215) Prec@5 99.000 (99.301) +2022-11-14 16:57:13,733 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0749) Prec@1 88.000 (88.213) Prec@5 99.000 (99.298) +2022-11-14 16:57:13,741 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0748) Prec@1 89.000 (88.221) Prec@5 99.000 (99.295) +2022-11-14 16:57:13,748 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0561 (0.0746) Prec@1 90.000 (88.240) Prec@5 99.000 (99.292) +2022-11-14 16:57:13,756 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0745) Prec@1 91.000 (88.268) Prec@5 99.000 (99.289) +2022-11-14 16:57:13,763 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0745) Prec@1 88.000 (88.265) Prec@5 100.000 (99.296) +2022-11-14 16:57:13,770 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0746) Prec@1 87.000 (88.253) Prec@5 100.000 (99.303) +2022-11-14 16:57:13,778 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0746) Prec@1 87.000 (88.240) Prec@5 99.000 (99.300) +2022-11-14 16:57:13,833 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:57:14,153 Epoch: [424][0/500] Time 0.026 (0.026) Data 0.238 (0.238) Loss 0.0279 (0.0279) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:14,355 Epoch: [424][10/500] Time 0.019 (0.018) Data 0.002 (0.023) Loss 0.0198 (0.0239) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:14,553 Epoch: [424][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0218 (0.0232) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:14,750 Epoch: [424][30/500] Time 0.021 (0.018) Data 0.002 (0.009) Loss 0.0359 (0.0264) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:14,947 Epoch: [424][40/500] Time 0.017 (0.018) Data 0.001 (0.007) Loss 0.0329 (0.0277) Prec@1 95.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 16:57:15,152 Epoch: [424][50/500] Time 0.021 (0.018) Data 0.002 (0.006) Loss 0.0318 (0.0284) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:15,347 Epoch: [424][60/500] Time 0.018 (0.018) Data 0.001 (0.006) Loss 0.0297 (0.0286) Prec@1 97.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 16:57:15,537 Epoch: [424][70/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0574 (0.0322) Prec@1 90.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:15,727 Epoch: [424][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0267 (0.0316) Prec@1 97.000 (95.222) Prec@5 99.000 (99.889) +2022-11-14 16:57:15,919 Epoch: [424][90/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0886 (0.0373) Prec@1 87.000 (94.400) Prec@5 99.000 (99.800) +2022-11-14 16:57:16,111 Epoch: [424][100/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0211 (0.0358) Prec@1 96.000 (94.545) Prec@5 100.000 (99.818) +2022-11-14 16:57:16,307 Epoch: [424][110/500] Time 0.015 (0.017) Data 0.001 (0.004) Loss 0.0267 (0.0350) Prec@1 94.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 16:57:16,498 Epoch: [424][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0414 (0.0355) Prec@1 92.000 (94.308) Prec@5 100.000 (99.846) +2022-11-14 16:57:16,689 Epoch: [424][130/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0216 (0.0345) Prec@1 96.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 16:57:16,882 Epoch: [424][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0350 (0.0346) Prec@1 94.000 (94.400) Prec@5 100.000 (99.867) +2022-11-14 16:57:17,085 Epoch: [424][150/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0355 (0.0346) Prec@1 92.000 (94.250) Prec@5 100.000 (99.875) +2022-11-14 16:57:17,292 Epoch: [424][160/500] Time 0.022 (0.017) Data 0.001 (0.003) Loss 0.0243 (0.0340) Prec@1 97.000 (94.412) Prec@5 100.000 (99.882) +2022-11-14 16:57:17,495 Epoch: [424][170/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0370 (0.0342) Prec@1 95.000 (94.444) Prec@5 100.000 (99.889) +2022-11-14 16:57:17,700 Epoch: [424][180/500] Time 0.022 (0.017) Data 0.001 (0.003) Loss 0.0296 (0.0339) Prec@1 94.000 (94.421) Prec@5 100.000 (99.895) +2022-11-14 16:57:17,941 Epoch: [424][190/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0128 (0.0329) Prec@1 98.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 16:57:18,196 Epoch: [424][200/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0280 (0.0326) Prec@1 96.000 (94.667) Prec@5 100.000 (99.905) +2022-11-14 16:57:18,448 Epoch: [424][210/500] Time 0.022 (0.018) Data 0.001 (0.003) Loss 0.0490 (0.0334) Prec@1 91.000 (94.500) Prec@5 100.000 (99.909) +2022-11-14 16:57:18,699 Epoch: [424][220/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0464 (0.0340) Prec@1 93.000 (94.435) Prec@5 100.000 (99.913) +2022-11-14 16:57:18,949 Epoch: [424][230/500] Time 0.022 (0.018) Data 0.001 (0.003) Loss 0.0235 (0.0335) Prec@1 97.000 (94.542) Prec@5 100.000 (99.917) +2022-11-14 16:57:19,204 Epoch: [424][240/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0160 (0.0328) Prec@1 97.000 (94.640) Prec@5 100.000 (99.920) +2022-11-14 16:57:19,451 Epoch: [424][250/500] Time 0.021 (0.019) Data 0.002 (0.003) Loss 0.0283 (0.0326) Prec@1 95.000 (94.654) Prec@5 100.000 (99.923) +2022-11-14 16:57:19,703 Epoch: [424][260/500] Time 0.028 (0.019) Data 0.001 (0.003) Loss 0.0379 (0.0328) Prec@1 94.000 (94.630) Prec@5 99.000 (99.889) +2022-11-14 16:57:19,962 Epoch: [424][270/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0298 (0.0327) Prec@1 96.000 (94.679) Prec@5 99.000 (99.857) +2022-11-14 16:57:20,223 Epoch: [424][280/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0361 (0.0329) Prec@1 95.000 (94.690) Prec@5 100.000 (99.862) +2022-11-14 16:57:20,484 Epoch: [424][290/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0142 (0.0322) Prec@1 98.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 16:57:20,741 Epoch: [424][300/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0242 (0.0320) Prec@1 97.000 (94.871) Prec@5 100.000 (99.871) +2022-11-14 16:57:20,993 Epoch: [424][310/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0219 (0.0317) Prec@1 96.000 (94.906) Prec@5 100.000 (99.875) +2022-11-14 16:57:21,247 Epoch: [424][320/500] Time 0.022 (0.020) Data 0.003 (0.002) Loss 0.0423 (0.0320) Prec@1 93.000 (94.848) Prec@5 100.000 (99.879) +2022-11-14 16:57:21,503 Epoch: [424][330/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0357 (0.0321) Prec@1 95.000 (94.853) Prec@5 100.000 (99.882) +2022-11-14 16:57:21,757 Epoch: [424][340/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0123 (0.0315) Prec@1 99.000 (94.971) Prec@5 100.000 (99.886) +2022-11-14 16:57:22,011 Epoch: [424][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0218 (0.0313) Prec@1 96.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 16:57:22,266 Epoch: [424][360/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0325 (0.0313) Prec@1 93.000 (94.946) Prec@5 100.000 (99.892) +2022-11-14 16:57:22,519 Epoch: [424][370/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0239 (0.0311) Prec@1 96.000 (94.974) Prec@5 100.000 (99.895) +2022-11-14 16:57:22,778 Epoch: [424][380/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0082 (0.0305) Prec@1 100.000 (95.103) Prec@5 100.000 (99.897) +2022-11-14 16:57:23,030 Epoch: [424][390/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0255 (0.0304) Prec@1 95.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 16:57:23,287 Epoch: [424][400/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.0142 (0.0300) Prec@1 98.000 (95.171) Prec@5 100.000 (99.902) +2022-11-14 16:57:23,539 Epoch: [424][410/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0371 (0.0302) Prec@1 95.000 (95.167) Prec@5 100.000 (99.905) +2022-11-14 16:57:23,791 Epoch: [424][420/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0162 (0.0298) Prec@1 98.000 (95.233) Prec@5 100.000 (99.907) +2022-11-14 16:57:24,048 Epoch: [424][430/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0336 (0.0299) Prec@1 95.000 (95.227) Prec@5 100.000 (99.909) +2022-11-14 16:57:24,304 Epoch: [424][440/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0119 (0.0295) Prec@1 99.000 (95.311) Prec@5 100.000 (99.911) +2022-11-14 16:57:24,554 Epoch: [424][450/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0151 (0.0292) Prec@1 99.000 (95.391) Prec@5 100.000 (99.913) +2022-11-14 16:57:24,807 Epoch: [424][460/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.0100 (0.0288) Prec@1 98.000 (95.447) Prec@5 100.000 (99.915) +2022-11-14 16:57:25,057 Epoch: [424][470/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0199 (0.0286) Prec@1 97.000 (95.479) Prec@5 100.000 (99.917) +2022-11-14 16:57:25,317 Epoch: [424][480/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0510 (0.0291) Prec@1 91.000 (95.388) Prec@5 99.000 (99.898) +2022-11-14 16:57:25,568 Epoch: [424][490/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0197 (0.0289) Prec@1 96.000 (95.400) Prec@5 99.000 (99.880) +2022-11-14 16:57:25,793 Epoch: [424][499/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0331 (0.0290) Prec@1 96.000 (95.412) Prec@5 100.000 (99.882) +2022-11-14 16:57:26,097 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0794 (0.0794) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:26,104 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0606 (0.0700) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:26,112 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0715 (0.0705) Prec@1 90.000 (88.333) Prec@5 98.000 (99.333) +2022-11-14 16:57:26,122 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0978 (0.0773) Prec@1 84.000 (87.250) Prec@5 99.000 (99.250) +2022-11-14 16:57:26,129 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0774) Prec@1 90.000 (87.800) Prec@5 100.000 (99.400) +2022-11-14 16:57:26,136 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0709) Prec@1 93.000 (88.667) Prec@5 100.000 (99.500) +2022-11-14 16:57:26,143 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0479 (0.0676) Prec@1 91.000 (89.000) Prec@5 99.000 (99.429) +2022-11-14 16:57:26,150 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0715) Prec@1 81.000 (88.000) Prec@5 99.000 (99.375) +2022-11-14 16:57:26,157 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0722) Prec@1 90.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 16:57:26,166 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0728) Prec@1 87.000 (88.100) Prec@5 99.000 (99.400) +2022-11-14 16:57:26,173 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0710) Prec@1 92.000 (88.455) Prec@5 100.000 (99.455) +2022-11-14 16:57:26,181 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0714) Prec@1 88.000 (88.417) Prec@5 99.000 (99.417) +2022-11-14 16:57:26,188 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0702) Prec@1 90.000 (88.538) Prec@5 100.000 (99.462) +2022-11-14 16:57:26,196 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0695) Prec@1 91.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 16:57:26,203 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0701) Prec@1 87.000 (88.600) Prec@5 100.000 (99.467) +2022-11-14 16:57:26,211 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0698) Prec@1 90.000 (88.688) Prec@5 100.000 (99.500) +2022-11-14 16:57:26,218 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0685) Prec@1 94.000 (89.000) Prec@5 99.000 (99.471) +2022-11-14 16:57:26,225 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0692) Prec@1 87.000 (88.889) Prec@5 100.000 (99.500) +2022-11-14 16:57:26,232 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0624 (0.0689) Prec@1 89.000 (88.895) Prec@5 99.000 (99.474) +2022-11-14 16:57:26,240 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1031 (0.0706) Prec@1 84.000 (88.650) Prec@5 99.000 (99.450) +2022-11-14 16:57:26,247 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0707) Prec@1 88.000 (88.619) Prec@5 100.000 (99.476) +2022-11-14 16:57:26,255 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0900 (0.0716) Prec@1 84.000 (88.409) Prec@5 99.000 (99.455) +2022-11-14 16:57:26,262 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0875 (0.0723) Prec@1 87.000 (88.348) Prec@5 99.000 (99.435) +2022-11-14 16:57:26,269 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0726) Prec@1 86.000 (88.250) Prec@5 100.000 (99.458) +2022-11-14 16:57:26,277 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0876 (0.0732) Prec@1 86.000 (88.160) Prec@5 99.000 (99.440) +2022-11-14 16:57:26,284 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0737) Prec@1 85.000 (88.038) Prec@5 99.000 (99.423) +2022-11-14 16:57:26,292 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0401 (0.0725) Prec@1 93.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 16:57:26,299 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0479 (0.0716) Prec@1 92.000 (88.357) Prec@5 100.000 (99.464) +2022-11-14 16:57:26,306 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0638 (0.0713) Prec@1 91.000 (88.448) Prec@5 98.000 (99.414) +2022-11-14 16:57:26,314 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0565 (0.0708) Prec@1 90.000 (88.500) Prec@5 100.000 (99.433) +2022-11-14 16:57:26,321 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0585 (0.0704) Prec@1 91.000 (88.581) Prec@5 100.000 (99.452) +2022-11-14 16:57:26,329 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0680 (0.0704) Prec@1 88.000 (88.562) Prec@5 98.000 (99.406) +2022-11-14 16:57:26,336 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0668 (0.0702) Prec@1 90.000 (88.606) Prec@5 100.000 (99.424) +2022-11-14 16:57:26,343 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0710) Prec@1 86.000 (88.529) Prec@5 100.000 (99.441) +2022-11-14 16:57:26,350 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0827 (0.0713) Prec@1 90.000 (88.571) Prec@5 98.000 (99.400) +2022-11-14 16:57:26,358 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0713) Prec@1 90.000 (88.611) Prec@5 99.000 (99.389) +2022-11-14 16:57:26,365 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0591 (0.0710) Prec@1 89.000 (88.622) Prec@5 99.000 (99.378) +2022-11-14 16:57:26,372 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1119 (0.0720) Prec@1 82.000 (88.447) Prec@5 100.000 (99.395) +2022-11-14 16:57:26,380 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0497 (0.0715) Prec@1 93.000 (88.564) Prec@5 100.000 (99.410) +2022-11-14 16:57:26,387 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0573 (0.0711) Prec@1 89.000 (88.575) Prec@5 99.000 (99.400) +2022-11-14 16:57:26,395 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1068 (0.0720) Prec@1 84.000 (88.463) Prec@5 99.000 (99.390) +2022-11-14 16:57:26,402 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0720) Prec@1 87.000 (88.429) Prec@5 99.000 (99.381) +2022-11-14 16:57:26,409 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0433 (0.0714) Prec@1 95.000 (88.581) Prec@5 99.000 (99.372) +2022-11-14 16:57:26,417 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0716) Prec@1 88.000 (88.568) Prec@5 97.000 (99.318) +2022-11-14 16:57:26,424 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0496 (0.0711) Prec@1 91.000 (88.622) Prec@5 99.000 (99.311) +2022-11-14 16:57:26,431 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0966 (0.0716) Prec@1 86.000 (88.565) Prec@5 99.000 (99.304) +2022-11-14 16:57:26,438 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0673 (0.0716) Prec@1 92.000 (88.638) Prec@5 100.000 (99.319) +2022-11-14 16:57:26,446 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1064 (0.0723) Prec@1 84.000 (88.542) Prec@5 96.000 (99.250) +2022-11-14 16:57:26,453 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0489 (0.0718) Prec@1 93.000 (88.633) Prec@5 100.000 (99.265) +2022-11-14 16:57:26,461 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0930 (0.0722) Prec@1 86.000 (88.580) Prec@5 99.000 (99.260) +2022-11-14 16:57:26,468 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0795 (0.0724) Prec@1 86.000 (88.529) Prec@5 100.000 (99.275) +2022-11-14 16:57:26,476 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0849 (0.0726) Prec@1 84.000 (88.442) Prec@5 100.000 (99.288) +2022-11-14 16:57:26,483 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0637 (0.0724) Prec@1 91.000 (88.491) Prec@5 99.000 (99.283) +2022-11-14 16:57:26,490 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0598 (0.0722) Prec@1 92.000 (88.556) Prec@5 100.000 (99.296) +2022-11-14 16:57:26,498 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0726) Prec@1 85.000 (88.491) Prec@5 100.000 (99.309) +2022-11-14 16:57:26,506 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0628 (0.0724) Prec@1 90.000 (88.518) Prec@5 99.000 (99.304) +2022-11-14 16:57:26,513 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0724) Prec@1 85.000 (88.456) Prec@5 100.000 (99.316) +2022-11-14 16:57:26,520 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0890 (0.0727) Prec@1 88.000 (88.448) Prec@5 99.000 (99.310) +2022-11-14 16:57:26,528 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0972 (0.0731) Prec@1 86.000 (88.407) Prec@5 99.000 (99.305) +2022-11-14 16:57:26,535 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0839 (0.0733) Prec@1 85.000 (88.350) Prec@5 100.000 (99.317) +2022-11-14 16:57:26,542 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0732) Prec@1 93.000 (88.426) Prec@5 98.000 (99.295) +2022-11-14 16:57:26,550 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0731) Prec@1 89.000 (88.435) Prec@5 99.000 (99.290) +2022-11-14 16:57:26,557 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0426 (0.0726) Prec@1 91.000 (88.476) Prec@5 100.000 (99.302) +2022-11-14 16:57:26,565 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0380 (0.0720) Prec@1 93.000 (88.547) Prec@5 100.000 (99.312) +2022-11-14 16:57:26,572 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0811 (0.0722) Prec@1 87.000 (88.523) Prec@5 98.000 (99.292) +2022-11-14 16:57:26,579 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0870 (0.0724) Prec@1 85.000 (88.470) Prec@5 98.000 (99.273) +2022-11-14 16:57:26,587 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0455 (0.0720) Prec@1 93.000 (88.537) Prec@5 99.000 (99.269) +2022-11-14 16:57:26,594 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0720) Prec@1 89.000 (88.544) Prec@5 100.000 (99.279) +2022-11-14 16:57:26,602 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0789 (0.0721) Prec@1 86.000 (88.507) Prec@5 99.000 (99.275) +2022-11-14 16:57:26,609 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0844 (0.0722) Prec@1 87.000 (88.486) Prec@5 98.000 (99.257) +2022-11-14 16:57:26,617 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0726) Prec@1 85.000 (88.437) Prec@5 98.000 (99.239) +2022-11-14 16:57:26,625 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0599 (0.0724) Prec@1 89.000 (88.444) Prec@5 100.000 (99.250) +2022-11-14 16:57:26,633 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0419 (0.0720) Prec@1 95.000 (88.534) Prec@5 100.000 (99.260) +2022-11-14 16:57:26,640 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0543 (0.0718) Prec@1 93.000 (88.595) Prec@5 100.000 (99.270) +2022-11-14 16:57:26,647 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1057 (0.0722) Prec@1 83.000 (88.520) Prec@5 100.000 (99.280) +2022-11-14 16:57:26,655 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0721) Prec@1 91.000 (88.553) Prec@5 99.000 (99.276) +2022-11-14 16:57:26,662 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0722) Prec@1 89.000 (88.558) Prec@5 98.000 (99.260) +2022-11-14 16:57:26,669 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0844 (0.0724) Prec@1 87.000 (88.538) Prec@5 99.000 (99.256) +2022-11-14 16:57:26,677 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0627 (0.0722) Prec@1 89.000 (88.544) Prec@5 100.000 (99.266) +2022-11-14 16:57:26,684 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0723) Prec@1 86.000 (88.513) Prec@5 98.000 (99.250) +2022-11-14 16:57:26,691 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0724) Prec@1 85.000 (88.469) Prec@5 100.000 (99.259) +2022-11-14 16:57:26,699 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0727) Prec@1 89.000 (88.476) Prec@5 100.000 (99.268) +2022-11-14 16:57:26,706 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0728) Prec@1 86.000 (88.446) Prec@5 99.000 (99.265) +2022-11-14 16:57:26,713 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0618 (0.0727) Prec@1 87.000 (88.429) Prec@5 100.000 (99.274) +2022-11-14 16:57:26,721 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0728) Prec@1 88.000 (88.424) Prec@5 100.000 (99.282) +2022-11-14 16:57:26,728 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1231 (0.0734) Prec@1 80.000 (88.326) Prec@5 99.000 (99.279) +2022-11-14 16:57:26,736 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0784 (0.0735) Prec@1 87.000 (88.310) Prec@5 99.000 (99.276) +2022-11-14 16:57:26,743 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0776 (0.0735) Prec@1 85.000 (88.273) Prec@5 99.000 (99.273) +2022-11-14 16:57:26,751 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0761 (0.0736) Prec@1 89.000 (88.281) Prec@5 100.000 (99.281) +2022-11-14 16:57:26,758 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0866 (0.0737) Prec@1 86.000 (88.256) Prec@5 100.000 (99.289) +2022-11-14 16:57:26,765 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0465 (0.0734) Prec@1 92.000 (88.297) Prec@5 100.000 (99.297) +2022-11-14 16:57:26,773 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0493 (0.0731) Prec@1 92.000 (88.337) Prec@5 100.000 (99.304) +2022-11-14 16:57:26,780 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0847 (0.0733) Prec@1 86.000 (88.312) Prec@5 98.000 (99.290) +2022-11-14 16:57:26,787 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0761 (0.0733) Prec@1 87.000 (88.298) Prec@5 99.000 (99.287) +2022-11-14 16:57:26,794 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0734) Prec@1 87.000 (88.284) Prec@5 99.000 (99.284) +2022-11-14 16:57:26,802 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0580 (0.0732) Prec@1 92.000 (88.323) Prec@5 100.000 (99.292) +2022-11-14 16:57:26,809 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0446 (0.0729) Prec@1 93.000 (88.371) Prec@5 99.000 (99.289) +2022-11-14 16:57:26,816 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1021 (0.0732) Prec@1 84.000 (88.327) Prec@5 100.000 (99.296) +2022-11-14 16:57:26,824 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0983 (0.0735) Prec@1 84.000 (88.283) Prec@5 97.000 (99.273) +2022-11-14 16:57:26,831 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0746 (0.0735) Prec@1 89.000 (88.290) Prec@5 100.000 (99.280) +2022-11-14 16:57:26,886 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:57:27,200 Epoch: [425][0/500] Time 0.022 (0.022) Data 0.235 (0.235) Loss 0.0280 (0.0280) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:57:27,410 Epoch: [425][10/500] Time 0.024 (0.019) Data 0.002 (0.023) Loss 0.0223 (0.0251) Prec@1 94.000 (94.500) Prec@5 100.000 (99.500) +2022-11-14 16:57:27,613 Epoch: [425][20/500] Time 0.018 (0.018) Data 0.001 (0.013) Loss 0.0239 (0.0247) Prec@1 97.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:57:27,818 Epoch: [425][30/500] Time 0.023 (0.018) Data 0.002 (0.009) Loss 0.0276 (0.0255) Prec@1 96.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 16:57:28,019 Epoch: [425][40/500] Time 0.017 (0.018) Data 0.002 (0.007) Loss 0.0168 (0.0237) Prec@1 99.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:57:28,227 Epoch: [425][50/500] Time 0.022 (0.018) Data 0.002 (0.006) Loss 0.0351 (0.0256) Prec@1 94.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 16:57:28,428 Epoch: [425][60/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0373 (0.0273) Prec@1 92.000 (95.286) Prec@5 99.000 (99.714) +2022-11-14 16:57:28,632 Epoch: [425][70/500] Time 0.024 (0.018) Data 0.002 (0.005) Loss 0.0127 (0.0255) Prec@1 99.000 (95.750) Prec@5 100.000 (99.750) +2022-11-14 16:57:28,832 Epoch: [425][80/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0588 (0.0292) Prec@1 90.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:57:29,035 Epoch: [425][90/500] Time 0.022 (0.018) Data 0.001 (0.004) Loss 0.0226 (0.0285) Prec@1 96.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:57:29,239 Epoch: [425][100/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0189 (0.0276) Prec@1 97.000 (95.364) Prec@5 100.000 (99.818) +2022-11-14 16:57:29,447 Epoch: [425][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0371 (0.0284) Prec@1 94.000 (95.250) Prec@5 100.000 (99.833) +2022-11-14 16:57:29,675 Epoch: [425][120/500] Time 0.024 (0.018) Data 0.001 (0.004) Loss 0.0457 (0.0298) Prec@1 93.000 (95.077) Prec@5 100.000 (99.846) +2022-11-14 16:57:29,998 Epoch: [425][130/500] Time 0.034 (0.019) Data 0.001 (0.004) Loss 0.0348 (0.0301) Prec@1 92.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 16:57:30,325 Epoch: [425][140/500] Time 0.032 (0.020) Data 0.002 (0.003) Loss 0.0281 (0.0300) Prec@1 96.000 (94.933) Prec@5 100.000 (99.867) +2022-11-14 16:57:30,655 Epoch: [425][150/500] Time 0.035 (0.020) Data 0.002 (0.003) Loss 0.0059 (0.0285) Prec@1 100.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:57:30,989 Epoch: [425][160/500] Time 0.031 (0.021) Data 0.002 (0.003) Loss 0.0312 (0.0286) Prec@1 96.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 16:57:31,320 Epoch: [425][170/500] Time 0.031 (0.021) Data 0.001 (0.003) Loss 0.0138 (0.0278) Prec@1 98.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:57:31,644 Epoch: [425][180/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0525 (0.0291) Prec@1 91.000 (95.211) Prec@5 100.000 (99.895) +2022-11-14 16:57:31,974 Epoch: [425][190/500] Time 0.032 (0.022) Data 0.002 (0.003) Loss 0.0180 (0.0286) Prec@1 98.000 (95.350) Prec@5 100.000 (99.900) +2022-11-14 16:57:32,305 Epoch: [425][200/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0148 (0.0279) Prec@1 97.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 16:57:32,632 Epoch: [425][210/500] Time 0.031 (0.023) Data 0.001 (0.003) Loss 0.0226 (0.0277) Prec@1 96.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 16:57:32,957 Epoch: [425][220/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0198 (0.0273) Prec@1 96.000 (95.478) Prec@5 100.000 (99.913) +2022-11-14 16:57:33,281 Epoch: [425][230/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0344 (0.0276) Prec@1 94.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 16:57:33,607 Epoch: [425][240/500] Time 0.031 (0.024) Data 0.001 (0.003) Loss 0.0370 (0.0280) Prec@1 93.000 (95.320) Prec@5 99.000 (99.880) +2022-11-14 16:57:33,940 Epoch: [425][250/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0467 (0.0287) Prec@1 94.000 (95.269) Prec@5 99.000 (99.846) +2022-11-14 16:57:34,275 Epoch: [425][260/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0169 (0.0283) Prec@1 98.000 (95.370) Prec@5 100.000 (99.852) +2022-11-14 16:57:34,599 Epoch: [425][270/500] Time 0.030 (0.024) Data 0.002 (0.003) Loss 0.0365 (0.0286) Prec@1 94.000 (95.321) Prec@5 100.000 (99.857) +2022-11-14 16:57:34,926 Epoch: [425][280/500] Time 0.031 (0.024) Data 0.001 (0.003) Loss 0.0186 (0.0282) Prec@1 97.000 (95.379) Prec@5 100.000 (99.862) +2022-11-14 16:57:35,255 Epoch: [425][290/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.0184 (0.0279) Prec@1 96.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:57:35,587 Epoch: [425][300/500] Time 0.033 (0.025) Data 0.002 (0.003) Loss 0.0185 (0.0276) Prec@1 97.000 (95.452) Prec@5 100.000 (99.871) +2022-11-14 16:57:35,914 Epoch: [425][310/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0254 (0.0275) Prec@1 95.000 (95.438) Prec@5 99.000 (99.844) +2022-11-14 16:57:36,242 Epoch: [425][320/500] Time 0.033 (0.025) Data 0.002 (0.002) Loss 0.0355 (0.0278) Prec@1 95.000 (95.424) Prec@5 100.000 (99.848) +2022-11-14 16:57:36,562 Epoch: [425][330/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0446 (0.0283) Prec@1 91.000 (95.294) Prec@5 100.000 (99.853) +2022-11-14 16:57:36,883 Epoch: [425][340/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0242 (0.0282) Prec@1 96.000 (95.314) Prec@5 99.000 (99.829) +2022-11-14 16:57:37,205 Epoch: [425][350/500] Time 0.030 (0.025) Data 0.002 (0.002) Loss 0.0172 (0.0278) Prec@1 98.000 (95.389) Prec@5 100.000 (99.833) +2022-11-14 16:57:37,528 Epoch: [425][360/500] Time 0.031 (0.025) Data 0.002 (0.002) Loss 0.0245 (0.0278) Prec@1 97.000 (95.432) Prec@5 100.000 (99.838) +2022-11-14 16:57:37,828 Epoch: [425][370/500] Time 0.024 (0.025) Data 0.001 (0.002) Loss 0.0319 (0.0279) Prec@1 95.000 (95.421) Prec@5 100.000 (99.842) +2022-11-14 16:57:38,045 Epoch: [425][380/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0228 (0.0277) Prec@1 95.000 (95.410) Prec@5 100.000 (99.846) +2022-11-14 16:57:38,254 Epoch: [425][390/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0264 (0.0277) Prec@1 96.000 (95.425) Prec@5 99.000 (99.825) +2022-11-14 16:57:38,460 Epoch: [425][400/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0194 (0.0275) Prec@1 96.000 (95.439) Prec@5 100.000 (99.829) +2022-11-14 16:57:38,666 Epoch: [425][410/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0345 (0.0277) Prec@1 93.000 (95.381) Prec@5 100.000 (99.833) +2022-11-14 16:57:38,873 Epoch: [425][420/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0266 (0.0276) Prec@1 96.000 (95.395) Prec@5 100.000 (99.837) +2022-11-14 16:57:39,087 Epoch: [425][430/500] Time 0.020 (0.024) Data 0.001 (0.002) Loss 0.0408 (0.0279) Prec@1 92.000 (95.318) Prec@5 100.000 (99.841) +2022-11-14 16:57:39,296 Epoch: [425][440/500] Time 0.019 (0.024) Data 0.002 (0.002) Loss 0.0286 (0.0280) Prec@1 96.000 (95.333) Prec@5 100.000 (99.844) +2022-11-14 16:57:39,505 Epoch: [425][450/500] Time 0.018 (0.024) Data 0.002 (0.002) Loss 0.0466 (0.0284) Prec@1 92.000 (95.261) Prec@5 100.000 (99.848) +2022-11-14 16:57:39,710 Epoch: [425][460/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0230 (0.0282) Prec@1 97.000 (95.298) Prec@5 100.000 (99.851) +2022-11-14 16:57:39,916 Epoch: [425][470/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0217 (0.0281) Prec@1 97.000 (95.333) Prec@5 100.000 (99.854) +2022-11-14 16:57:40,126 Epoch: [425][480/500] Time 0.018 (0.024) Data 0.002 (0.002) Loss 0.0262 (0.0281) Prec@1 96.000 (95.347) Prec@5 100.000 (99.857) +2022-11-14 16:57:40,339 Epoch: [425][490/500] Time 0.020 (0.024) Data 0.001 (0.002) Loss 0.0365 (0.0282) Prec@1 94.000 (95.320) Prec@5 100.000 (99.860) +2022-11-14 16:57:40,529 Epoch: [425][499/500] Time 0.020 (0.024) Data 0.002 (0.002) Loss 0.0393 (0.0285) Prec@1 93.000 (95.275) Prec@5 100.000 (99.863) +2022-11-14 16:57:40,836 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0797 (0.0797) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:40,845 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0630 (0.0713) Prec@1 88.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:40,852 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0695) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:40,861 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0669) Prec@1 89.000 (88.250) Prec@5 98.000 (99.500) +2022-11-14 16:57:40,868 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0687) Prec@1 86.000 (87.800) Prec@5 100.000 (99.600) +2022-11-14 16:57:40,875 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0646) Prec@1 94.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 16:57:40,882 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0641) Prec@1 92.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 16:57:40,889 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0657) Prec@1 86.000 (88.875) Prec@5 100.000 (99.750) +2022-11-14 16:57:40,896 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0669) Prec@1 90.000 (89.000) Prec@5 100.000 (99.778) +2022-11-14 16:57:40,904 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0681) Prec@1 90.000 (89.100) Prec@5 99.000 (99.700) +2022-11-14 16:57:40,912 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0682) Prec@1 89.000 (89.091) Prec@5 100.000 (99.727) +2022-11-14 16:57:40,920 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0697) Prec@1 84.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 16:57:40,927 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0693) Prec@1 90.000 (88.769) Prec@5 100.000 (99.692) +2022-11-14 16:57:40,935 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0698) Prec@1 88.000 (88.714) Prec@5 99.000 (99.643) +2022-11-14 16:57:40,943 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0708) Prec@1 85.000 (88.467) Prec@5 100.000 (99.667) +2022-11-14 16:57:40,950 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0710) Prec@1 88.000 (88.438) Prec@5 99.000 (99.625) +2022-11-14 16:57:40,958 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0391 (0.0692) Prec@1 94.000 (88.765) Prec@5 98.000 (99.529) +2022-11-14 16:57:40,966 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.0714) Prec@1 84.000 (88.500) Prec@5 100.000 (99.556) +2022-11-14 16:57:40,973 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0722) Prec@1 85.000 (88.316) Prec@5 100.000 (99.579) +2022-11-14 16:57:40,981 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0732) Prec@1 85.000 (88.150) Prec@5 97.000 (99.450) +2022-11-14 16:57:40,989 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0726) Prec@1 90.000 (88.238) Prec@5 100.000 (99.476) +2022-11-14 16:57:40,996 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0735) Prec@1 84.000 (88.045) Prec@5 99.000 (99.455) +2022-11-14 16:57:41,004 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1163 (0.0753) Prec@1 82.000 (87.783) Prec@5 98.000 (99.391) +2022-11-14 16:57:41,012 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0756) Prec@1 87.000 (87.750) Prec@5 100.000 (99.417) +2022-11-14 16:57:41,019 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0755) Prec@1 88.000 (87.760) Prec@5 99.000 (99.400) +2022-11-14 16:57:41,026 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1173 (0.0771) Prec@1 82.000 (87.538) Prec@5 96.000 (99.269) +2022-11-14 16:57:41,034 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0432 (0.0759) Prec@1 94.000 (87.778) Prec@5 100.000 (99.296) +2022-11-14 16:57:41,042 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0749) Prec@1 91.000 (87.893) Prec@5 100.000 (99.321) +2022-11-14 16:57:41,049 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0745) Prec@1 88.000 (87.897) Prec@5 99.000 (99.310) +2022-11-14 16:57:41,057 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0746) Prec@1 90.000 (87.967) Prec@5 100.000 (99.333) +2022-11-14 16:57:41,064 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0744) Prec@1 90.000 (88.032) Prec@5 100.000 (99.355) +2022-11-14 16:57:41,072 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0737) Prec@1 89.000 (88.062) Prec@5 100.000 (99.375) +2022-11-14 16:57:41,080 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0759 (0.0737) Prec@1 86.000 (88.000) Prec@5 100.000 (99.394) +2022-11-14 16:57:41,087 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0744) Prec@1 86.000 (87.941) Prec@5 100.000 (99.412) +2022-11-14 16:57:41,095 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0747) Prec@1 87.000 (87.914) Prec@5 99.000 (99.400) +2022-11-14 16:57:41,103 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0748) Prec@1 88.000 (87.917) Prec@5 99.000 (99.389) +2022-11-14 16:57:41,110 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0750) Prec@1 87.000 (87.892) Prec@5 99.000 (99.378) +2022-11-14 16:57:41,119 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0957 (0.0756) Prec@1 85.000 (87.816) Prec@5 99.000 (99.368) +2022-11-14 16:57:41,126 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0513 (0.0750) Prec@1 93.000 (87.949) Prec@5 99.000 (99.359) +2022-11-14 16:57:41,134 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0768 (0.0750) Prec@1 86.000 (87.900) Prec@5 99.000 (99.350) +2022-11-14 16:57:41,141 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0751) Prec@1 88.000 (87.902) Prec@5 98.000 (99.317) +2022-11-14 16:57:41,149 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0751) Prec@1 89.000 (87.929) Prec@5 100.000 (99.333) +2022-11-14 16:57:41,157 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0561 (0.0747) Prec@1 90.000 (87.977) Prec@5 99.000 (99.326) +2022-11-14 16:57:41,164 Test: [43/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0725 (0.0746) Prec@1 88.000 (87.977) Prec@5 98.000 (99.295) +2022-11-14 16:57:41,172 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0585 (0.0742) Prec@1 92.000 (88.067) Prec@5 100.000 (99.311) +2022-11-14 16:57:41,179 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0969 (0.0747) Prec@1 82.000 (87.935) Prec@5 99.000 (99.304) +2022-11-14 16:57:41,187 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0696 (0.0746) Prec@1 89.000 (87.957) Prec@5 99.000 (99.298) +2022-11-14 16:57:41,195 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0967 (0.0751) Prec@1 84.000 (87.875) Prec@5 100.000 (99.312) +2022-11-14 16:57:41,202 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0523 (0.0746) Prec@1 92.000 (87.959) Prec@5 100.000 (99.327) +2022-11-14 16:57:41,210 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0787 (0.0747) Prec@1 89.000 (87.980) Prec@5 100.000 (99.340) +2022-11-14 16:57:41,217 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0746) Prec@1 90.000 (88.020) Prec@5 100.000 (99.353) +2022-11-14 16:57:41,225 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0693 (0.0745) Prec@1 89.000 (88.038) Prec@5 99.000 (99.346) +2022-11-14 16:57:41,232 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0744) Prec@1 87.000 (88.019) Prec@5 99.000 (99.340) +2022-11-14 16:57:41,240 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0542 (0.0740) Prec@1 90.000 (88.056) Prec@5 99.000 (99.333) +2022-11-14 16:57:41,247 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1032 (0.0746) Prec@1 84.000 (87.982) Prec@5 100.000 (99.345) +2022-11-14 16:57:41,255 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0714 (0.0745) Prec@1 91.000 (88.036) Prec@5 99.000 (99.339) +2022-11-14 16:57:41,262 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0744) Prec@1 86.000 (88.000) Prec@5 100.000 (99.351) +2022-11-14 16:57:41,269 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0744) Prec@1 90.000 (88.034) Prec@5 98.000 (99.328) +2022-11-14 16:57:41,277 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 88.000 (88.034) Prec@5 99.000 (99.322) +2022-11-14 16:57:41,285 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0744) Prec@1 87.000 (88.017) Prec@5 100.000 (99.333) +2022-11-14 16:57:41,292 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0642 (0.0742) Prec@1 92.000 (88.082) Prec@5 98.000 (99.311) +2022-11-14 16:57:41,300 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0564 (0.0740) Prec@1 90.000 (88.113) Prec@5 100.000 (99.323) +2022-11-14 16:57:41,308 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0739) Prec@1 86.000 (88.079) Prec@5 99.000 (99.317) +2022-11-14 16:57:41,315 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0407 (0.0734) Prec@1 93.000 (88.156) Prec@5 100.000 (99.328) +2022-11-14 16:57:41,323 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0735) Prec@1 89.000 (88.169) Prec@5 100.000 (99.338) +2022-11-14 16:57:41,330 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0839 (0.0737) Prec@1 87.000 (88.152) Prec@5 100.000 (99.348) +2022-11-14 16:57:41,338 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0474 (0.0733) Prec@1 93.000 (88.224) Prec@5 100.000 (99.358) +2022-11-14 16:57:41,345 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0733) Prec@1 89.000 (88.235) Prec@5 100.000 (99.368) +2022-11-14 16:57:41,353 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0733) Prec@1 88.000 (88.232) Prec@5 99.000 (99.362) +2022-11-14 16:57:41,360 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0734) Prec@1 88.000 (88.229) Prec@5 100.000 (99.371) +2022-11-14 16:57:41,368 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0976 (0.0737) Prec@1 85.000 (88.183) Prec@5 100.000 (99.380) +2022-11-14 16:57:41,375 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0653 (0.0736) Prec@1 89.000 (88.194) Prec@5 100.000 (99.389) +2022-11-14 16:57:41,383 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0462 (0.0732) Prec@1 93.000 (88.260) Prec@5 100.000 (99.397) +2022-11-14 16:57:41,391 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0412 (0.0728) Prec@1 94.000 (88.338) Prec@5 100.000 (99.405) +2022-11-14 16:57:41,399 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0901 (0.0730) Prec@1 85.000 (88.293) Prec@5 100.000 (99.413) +2022-11-14 16:57:41,406 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0590 (0.0728) Prec@1 91.000 (88.329) Prec@5 99.000 (99.408) +2022-11-14 16:57:41,414 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0725 (0.0728) Prec@1 87.000 (88.312) Prec@5 100.000 (99.416) +2022-11-14 16:57:41,421 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0908 (0.0731) Prec@1 87.000 (88.295) Prec@5 96.000 (99.372) +2022-11-14 16:57:41,429 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0730) Prec@1 89.000 (88.304) Prec@5 100.000 (99.380) +2022-11-14 16:57:41,436 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0634 (0.0729) Prec@1 88.000 (88.300) Prec@5 99.000 (99.375) +2022-11-14 16:57:41,444 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0729) Prec@1 90.000 (88.321) Prec@5 98.000 (99.358) +2022-11-14 16:57:41,452 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0732) Prec@1 84.000 (88.268) Prec@5 100.000 (99.366) +2022-11-14 16:57:41,459 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0899 (0.0734) Prec@1 82.000 (88.193) Prec@5 98.000 (99.349) +2022-11-14 16:57:41,467 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0668 (0.0733) Prec@1 87.000 (88.179) Prec@5 98.000 (99.333) +2022-11-14 16:57:41,474 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0736) Prec@1 84.000 (88.129) Prec@5 98.000 (99.318) +2022-11-14 16:57:41,482 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0738) Prec@1 87.000 (88.116) Prec@5 99.000 (99.314) +2022-11-14 16:57:41,489 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0848 (0.0739) Prec@1 87.000 (88.103) Prec@5 99.000 (99.310) +2022-11-14 16:57:41,497 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0738) Prec@1 90.000 (88.125) Prec@5 99.000 (99.307) +2022-11-14 16:57:41,505 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0737) Prec@1 89.000 (88.135) Prec@5 100.000 (99.315) +2022-11-14 16:57:41,512 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0737) Prec@1 90.000 (88.156) Prec@5 100.000 (99.322) +2022-11-14 16:57:41,520 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0695 (0.0736) Prec@1 88.000 (88.154) Prec@5 99.000 (99.319) +2022-11-14 16:57:41,527 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0558 (0.0735) Prec@1 91.000 (88.185) Prec@5 99.000 (99.315) +2022-11-14 16:57:41,535 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0978 (0.0737) Prec@1 83.000 (88.129) Prec@5 100.000 (99.323) +2022-11-14 16:57:41,543 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0736 (0.0737) Prec@1 89.000 (88.138) Prec@5 99.000 (99.319) +2022-11-14 16:57:41,550 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0738) Prec@1 85.000 (88.105) Prec@5 99.000 (99.316) +2022-11-14 16:57:41,558 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0592 (0.0736) Prec@1 91.000 (88.135) Prec@5 99.000 (99.312) +2022-11-14 16:57:41,565 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0663 (0.0735) Prec@1 89.000 (88.144) Prec@5 98.000 (99.299) +2022-11-14 16:57:41,572 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0995 (0.0738) Prec@1 86.000 (88.122) Prec@5 97.000 (99.276) +2022-11-14 16:57:41,580 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0933 (0.0740) Prec@1 85.000 (88.091) Prec@5 100.000 (99.283) +2022-11-14 16:57:41,588 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0739) Prec@1 91.000 (88.120) Prec@5 100.000 (99.290) +2022-11-14 16:57:41,642 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:57:41,975 Epoch: [426][0/500] Time 0.022 (0.022) Data 0.233 (0.233) Loss 0.0355 (0.0355) Prec@1 93.000 (93.000) Prec@5 99.000 (99.000) +2022-11-14 16:57:42,171 Epoch: [426][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0233 (0.0294) Prec@1 97.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 16:57:42,363 Epoch: [426][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0321 (0.0303) Prec@1 95.000 (95.000) Prec@5 100.000 (99.333) +2022-11-14 16:57:42,554 Epoch: [426][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0184 (0.0273) Prec@1 99.000 (96.000) Prec@5 100.000 (99.500) +2022-11-14 16:57:42,743 Epoch: [426][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0194 (0.0258) Prec@1 96.000 (96.000) Prec@5 100.000 (99.600) +2022-11-14 16:57:42,941 Epoch: [426][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0230 (0.0253) Prec@1 96.000 (96.000) Prec@5 100.000 (99.667) +2022-11-14 16:57:43,133 Epoch: [426][60/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0473 (0.0284) Prec@1 93.000 (95.571) Prec@5 99.000 (99.571) +2022-11-14 16:57:43,323 Epoch: [426][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0243 (0.0279) Prec@1 96.000 (95.625) Prec@5 100.000 (99.625) +2022-11-14 16:57:43,512 Epoch: [426][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0244 (0.0275) Prec@1 96.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:57:43,702 Epoch: [426][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0181 (0.0266) Prec@1 97.000 (95.800) Prec@5 100.000 (99.700) +2022-11-14 16:57:43,895 Epoch: [426][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0348 (0.0273) Prec@1 95.000 (95.727) Prec@5 100.000 (99.727) +2022-11-14 16:57:44,149 Epoch: [426][110/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0157 (0.0264) Prec@1 97.000 (95.833) Prec@5 100.000 (99.750) +2022-11-14 16:57:44,423 Epoch: [426][120/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0190 (0.0258) Prec@1 98.000 (96.000) Prec@5 100.000 (99.769) +2022-11-14 16:57:44,698 Epoch: [426][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0163 (0.0251) Prec@1 98.000 (96.143) Prec@5 100.000 (99.786) +2022-11-14 16:57:44,977 Epoch: [426][140/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0163 (0.0245) Prec@1 97.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:57:45,257 Epoch: [426][150/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0387 (0.0254) Prec@1 94.000 (96.062) Prec@5 99.000 (99.750) +2022-11-14 16:57:45,533 Epoch: [426][160/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0247 (0.0254) Prec@1 96.000 (96.059) Prec@5 100.000 (99.765) +2022-11-14 16:57:45,815 Epoch: [426][170/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0173 (0.0249) Prec@1 97.000 (96.111) Prec@5 100.000 (99.778) +2022-11-14 16:57:46,102 Epoch: [426][180/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0228 (0.0248) Prec@1 96.000 (96.105) Prec@5 100.000 (99.789) +2022-11-14 16:57:46,385 Epoch: [426][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0474 (0.0259) Prec@1 94.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 16:57:46,667 Epoch: [426][200/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0235 (0.0258) Prec@1 96.000 (96.000) Prec@5 100.000 (99.810) +2022-11-14 16:57:46,946 Epoch: [426][210/500] Time 0.021 (0.021) Data 0.002 (0.003) Loss 0.0266 (0.0259) Prec@1 96.000 (96.000) Prec@5 100.000 (99.818) +2022-11-14 16:57:47,217 Epoch: [426][220/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0302 (0.0261) Prec@1 96.000 (96.000) Prec@5 99.000 (99.783) +2022-11-14 16:57:47,489 Epoch: [426][230/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0563 (0.0273) Prec@1 92.000 (95.833) Prec@5 99.000 (99.750) +2022-11-14 16:57:47,768 Epoch: [426][240/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0292 (0.0274) Prec@1 95.000 (95.800) Prec@5 100.000 (99.760) +2022-11-14 16:57:48,044 Epoch: [426][250/500] Time 0.025 (0.021) Data 0.003 (0.003) Loss 0.0205 (0.0271) Prec@1 96.000 (95.808) Prec@5 100.000 (99.769) +2022-11-14 16:57:48,325 Epoch: [426][260/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0189 (0.0268) Prec@1 99.000 (95.926) Prec@5 100.000 (99.778) +2022-11-14 16:57:48,601 Epoch: [426][270/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0202 (0.0266) Prec@1 97.000 (95.964) Prec@5 100.000 (99.786) +2022-11-14 16:57:48,878 Epoch: [426][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0412 (0.0271) Prec@1 93.000 (95.862) Prec@5 100.000 (99.793) +2022-11-14 16:57:49,147 Epoch: [426][290/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0309 (0.0272) Prec@1 95.000 (95.833) Prec@5 100.000 (99.800) +2022-11-14 16:57:49,413 Epoch: [426][300/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0288 (0.0273) Prec@1 95.000 (95.806) Prec@5 100.000 (99.806) +2022-11-14 16:57:49,688 Epoch: [426][310/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0505 (0.0280) Prec@1 92.000 (95.688) Prec@5 99.000 (99.781) +2022-11-14 16:57:49,963 Epoch: [426][320/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0220 (0.0278) Prec@1 95.000 (95.667) Prec@5 100.000 (99.788) +2022-11-14 16:57:50,234 Epoch: [426][330/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0254 (0.0277) Prec@1 96.000 (95.676) Prec@5 100.000 (99.794) +2022-11-14 16:57:50,506 Epoch: [426][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0362 (0.0280) Prec@1 95.000 (95.657) Prec@5 100.000 (99.800) +2022-11-14 16:57:50,778 Epoch: [426][350/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0238 (0.0279) Prec@1 95.000 (95.639) Prec@5 100.000 (99.806) +2022-11-14 16:57:51,047 Epoch: [426][360/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0102 (0.0274) Prec@1 99.000 (95.730) Prec@5 100.000 (99.811) +2022-11-14 16:57:51,323 Epoch: [426][370/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0333 (0.0275) Prec@1 94.000 (95.684) Prec@5 100.000 (99.816) +2022-11-14 16:57:51,596 Epoch: [426][380/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0418 (0.0279) Prec@1 94.000 (95.641) Prec@5 100.000 (99.821) +2022-11-14 16:57:51,871 Epoch: [426][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0219 (0.0278) Prec@1 97.000 (95.675) Prec@5 100.000 (99.825) +2022-11-14 16:57:52,151 Epoch: [426][400/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0156 (0.0275) Prec@1 98.000 (95.732) Prec@5 100.000 (99.829) +2022-11-14 16:57:52,430 Epoch: [426][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0344 (0.0276) Prec@1 96.000 (95.738) Prec@5 100.000 (99.833) +2022-11-14 16:57:52,710 Epoch: [426][420/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0218 (0.0275) Prec@1 97.000 (95.767) Prec@5 100.000 (99.837) +2022-11-14 16:57:52,991 Epoch: [426][430/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0336 (0.0276) Prec@1 94.000 (95.727) Prec@5 100.000 (99.841) +2022-11-14 16:57:53,271 Epoch: [426][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0240 (0.0276) Prec@1 97.000 (95.756) Prec@5 99.000 (99.822) +2022-11-14 16:57:53,542 Epoch: [426][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0255 (0.0275) Prec@1 96.000 (95.761) Prec@5 100.000 (99.826) +2022-11-14 16:57:53,817 Epoch: [426][460/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0311 (0.0276) Prec@1 94.000 (95.723) Prec@5 99.000 (99.809) +2022-11-14 16:57:54,088 Epoch: [426][470/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0311 (0.0277) Prec@1 96.000 (95.729) Prec@5 100.000 (99.812) +2022-11-14 16:57:54,354 Epoch: [426][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0235 (0.0276) Prec@1 97.000 (95.755) Prec@5 100.000 (99.816) +2022-11-14 16:57:54,620 Epoch: [426][490/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0243 (0.0275) Prec@1 95.000 (95.740) Prec@5 100.000 (99.820) +2022-11-14 16:57:54,867 Epoch: [426][499/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0406 (0.0278) Prec@1 95.000 (95.725) Prec@5 100.000 (99.824) +2022-11-14 16:57:55,160 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0602 (0.0602) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,170 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0656) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,177 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0624) Prec@1 92.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,187 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0627) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,194 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0622) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,201 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0275 (0.0564) Prec@1 95.000 (90.833) Prec@5 100.000 (100.000) +2022-11-14 16:57:55,208 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0559) Prec@1 92.000 (91.000) Prec@5 99.000 (99.857) +2022-11-14 16:57:55,216 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0604) Prec@1 84.000 (90.125) Prec@5 99.000 (99.750) +2022-11-14 16:57:55,223 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0631) Prec@1 86.000 (89.667) Prec@5 100.000 (99.778) +2022-11-14 16:57:55,231 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0651) Prec@1 87.000 (89.400) Prec@5 98.000 (99.600) +2022-11-14 16:57:55,239 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0651) Prec@1 90.000 (89.455) Prec@5 100.000 (99.636) +2022-11-14 16:57:55,246 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0660) Prec@1 89.000 (89.417) Prec@5 100.000 (99.667) +2022-11-14 16:57:55,254 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0433 (0.0642) Prec@1 95.000 (89.846) Prec@5 100.000 (99.692) +2022-11-14 16:57:55,261 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0647) Prec@1 90.000 (89.857) Prec@5 100.000 (99.714) +2022-11-14 16:57:55,269 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0645) Prec@1 90.000 (89.867) Prec@5 99.000 (99.667) +2022-11-14 16:57:55,277 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0655) Prec@1 84.000 (89.500) Prec@5 99.000 (99.625) +2022-11-14 16:57:55,285 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0649) Prec@1 90.000 (89.529) Prec@5 99.000 (99.588) +2022-11-14 16:57:55,292 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.0677) Prec@1 85.000 (89.278) Prec@5 100.000 (99.611) +2022-11-14 16:57:55,300 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0692) Prec@1 81.000 (88.842) Prec@5 98.000 (99.526) +2022-11-14 16:57:55,307 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0710) Prec@1 86.000 (88.700) Prec@5 97.000 (99.400) +2022-11-14 16:57:55,315 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0709) Prec@1 88.000 (88.667) Prec@5 100.000 (99.429) +2022-11-14 16:57:55,323 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0718) Prec@1 86.000 (88.545) Prec@5 99.000 (99.409) +2022-11-14 16:57:55,330 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0734) Prec@1 85.000 (88.391) Prec@5 97.000 (99.304) +2022-11-14 16:57:55,338 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0742) Prec@1 87.000 (88.333) Prec@5 99.000 (99.292) +2022-11-14 16:57:55,346 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0744) Prec@1 90.000 (88.400) Prec@5 100.000 (99.320) +2022-11-14 16:57:55,353 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0751) Prec@1 86.000 (88.308) Prec@5 97.000 (99.231) +2022-11-14 16:57:55,361 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0746) Prec@1 93.000 (88.481) Prec@5 100.000 (99.259) +2022-11-14 16:57:55,368 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0747) Prec@1 88.000 (88.464) Prec@5 99.000 (99.250) +2022-11-14 16:57:55,376 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0740) Prec@1 93.000 (88.621) Prec@5 99.000 (99.241) +2022-11-14 16:57:55,384 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0743) Prec@1 85.000 (88.500) Prec@5 99.000 (99.233) +2022-11-14 16:57:55,391 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0740) Prec@1 89.000 (88.516) Prec@5 99.000 (99.226) +2022-11-14 16:57:55,399 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0743) Prec@1 87.000 (88.469) Prec@5 99.000 (99.219) +2022-11-14 16:57:55,406 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0743) Prec@1 87.000 (88.424) Prec@5 100.000 (99.242) +2022-11-14 16:57:55,414 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0750) Prec@1 84.000 (88.294) Prec@5 98.000 (99.206) +2022-11-14 16:57:55,421 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0752) Prec@1 89.000 (88.314) Prec@5 98.000 (99.171) +2022-11-14 16:57:55,429 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0748) Prec@1 91.000 (88.389) Prec@5 99.000 (99.167) +2022-11-14 16:57:55,437 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0743) Prec@1 91.000 (88.459) Prec@5 100.000 (99.189) +2022-11-14 16:57:55,445 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0741) Prec@1 89.000 (88.474) Prec@5 99.000 (99.184) +2022-11-14 16:57:55,452 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0735) Prec@1 92.000 (88.564) Prec@5 99.000 (99.179) +2022-11-14 16:57:55,460 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0731) Prec@1 92.000 (88.650) Prec@5 98.000 (99.150) +2022-11-14 16:57:55,468 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0737) Prec@1 83.000 (88.512) Prec@5 99.000 (99.146) +2022-11-14 16:57:55,476 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0735) Prec@1 90.000 (88.548) Prec@5 99.000 (99.143) +2022-11-14 16:57:55,484 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0407 (0.0727) Prec@1 94.000 (88.674) Prec@5 99.000 (99.140) +2022-11-14 16:57:55,491 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0727) Prec@1 89.000 (88.682) Prec@5 98.000 (99.114) +2022-11-14 16:57:55,499 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0723) Prec@1 89.000 (88.689) Prec@5 99.000 (99.111) +2022-11-14 16:57:55,507 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0732) Prec@1 81.000 (88.522) Prec@5 99.000 (99.109) +2022-11-14 16:57:55,515 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0733) Prec@1 87.000 (88.489) Prec@5 100.000 (99.128) +2022-11-14 16:57:55,522 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0738) Prec@1 84.000 (88.396) Prec@5 97.000 (99.083) +2022-11-14 16:57:55,530 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0736) Prec@1 89.000 (88.408) Prec@5 100.000 (99.102) +2022-11-14 16:57:55,537 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0740) Prec@1 85.000 (88.340) Prec@5 100.000 (99.120) +2022-11-14 16:57:55,545 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0736) Prec@1 90.000 (88.373) Prec@5 100.000 (99.137) +2022-11-14 16:57:55,553 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0735) Prec@1 89.000 (88.385) Prec@5 99.000 (99.135) +2022-11-14 16:57:55,560 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0733) Prec@1 91.000 (88.434) Prec@5 100.000 (99.151) +2022-11-14 16:57:55,568 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0732) Prec@1 90.000 (88.463) Prec@5 99.000 (99.148) +2022-11-14 16:57:55,576 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0734) Prec@1 84.000 (88.382) Prec@5 100.000 (99.164) +2022-11-14 16:57:55,583 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0735) Prec@1 88.000 (88.375) Prec@5 98.000 (99.143) +2022-11-14 16:57:55,591 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0738) Prec@1 84.000 (88.298) Prec@5 99.000 (99.140) +2022-11-14 16:57:55,599 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0736) Prec@1 90.000 (88.328) Prec@5 100.000 (99.155) +2022-11-14 16:57:55,606 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0743) Prec@1 80.000 (88.186) Prec@5 99.000 (99.153) +2022-11-14 16:57:55,613 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0744) Prec@1 87.000 (88.167) Prec@5 100.000 (99.167) +2022-11-14 16:57:55,621 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0743) Prec@1 90.000 (88.197) Prec@5 100.000 (99.180) +2022-11-14 16:57:55,629 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0742) Prec@1 89.000 (88.210) Prec@5 100.000 (99.194) +2022-11-14 16:57:55,636 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0741) Prec@1 89.000 (88.222) Prec@5 100.000 (99.206) +2022-11-14 16:57:55,645 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0735) Prec@1 93.000 (88.297) Prec@5 100.000 (99.219) +2022-11-14 16:57:55,652 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0738) Prec@1 86.000 (88.262) Prec@5 99.000 (99.215) +2022-11-14 16:57:55,660 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0737) Prec@1 88.000 (88.258) Prec@5 100.000 (99.227) +2022-11-14 16:57:55,667 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0732) Prec@1 93.000 (88.328) Prec@5 100.000 (99.239) +2022-11-14 16:57:55,675 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0729) Prec@1 94.000 (88.412) Prec@5 100.000 (99.250) +2022-11-14 16:57:55,682 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0728) Prec@1 90.000 (88.435) Prec@5 99.000 (99.246) +2022-11-14 16:57:55,690 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0726) Prec@1 87.000 (88.414) Prec@5 100.000 (99.257) +2022-11-14 16:57:55,698 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0731) Prec@1 84.000 (88.352) Prec@5 99.000 (99.254) +2022-11-14 16:57:55,705 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0730) Prec@1 89.000 (88.361) Prec@5 99.000 (99.250) +2022-11-14 16:57:55,713 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0727) Prec@1 93.000 (88.425) Prec@5 100.000 (99.260) +2022-11-14 16:57:55,720 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0725) Prec@1 93.000 (88.486) Prec@5 100.000 (99.270) +2022-11-14 16:57:55,728 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.0730) Prec@1 81.000 (88.387) Prec@5 100.000 (99.280) +2022-11-14 16:57:55,736 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0730) Prec@1 88.000 (88.382) Prec@5 100.000 (99.289) +2022-11-14 16:57:55,743 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0730) Prec@1 88.000 (88.377) Prec@5 97.000 (99.260) +2022-11-14 16:57:55,751 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0732) Prec@1 87.000 (88.359) Prec@5 97.000 (99.231) +2022-11-14 16:57:55,759 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0734) Prec@1 87.000 (88.342) Prec@5 100.000 (99.241) +2022-11-14 16:57:55,766 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0737) Prec@1 83.000 (88.275) Prec@5 99.000 (99.237) +2022-11-14 16:57:55,774 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0741) Prec@1 84.000 (88.222) Prec@5 97.000 (99.210) +2022-11-14 16:57:55,781 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0742) Prec@1 87.000 (88.207) Prec@5 100.000 (99.220) +2022-11-14 16:57:55,789 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0744) Prec@1 85.000 (88.169) Prec@5 99.000 (99.217) +2022-11-14 16:57:55,796 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0742) Prec@1 89.000 (88.179) Prec@5 100.000 (99.226) +2022-11-14 16:57:55,804 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0743) Prec@1 86.000 (88.153) Prec@5 100.000 (99.235) +2022-11-14 16:57:55,812 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1105 (0.0747) Prec@1 83.000 (88.093) Prec@5 100.000 (99.244) +2022-11-14 16:57:55,820 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0884 (0.0748) Prec@1 86.000 (88.069) Prec@5 98.000 (99.230) +2022-11-14 16:57:55,827 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0938 (0.0751) Prec@1 85.000 (88.034) Prec@5 99.000 (99.227) +2022-11-14 16:57:55,835 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0894 (0.0752) Prec@1 84.000 (87.989) Prec@5 100.000 (99.236) +2022-11-14 16:57:55,842 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0746 (0.0752) Prec@1 88.000 (87.989) Prec@5 99.000 (99.233) +2022-11-14 16:57:55,850 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0447 (0.0749) Prec@1 92.000 (88.033) Prec@5 100.000 (99.242) +2022-11-14 16:57:55,858 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0563 (0.0747) Prec@1 93.000 (88.087) Prec@5 100.000 (99.250) +2022-11-14 16:57:55,865 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0749) Prec@1 84.000 (88.043) Prec@5 100.000 (99.258) +2022-11-14 16:57:55,873 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0790 (0.0750) Prec@1 88.000 (88.043) Prec@5 99.000 (99.255) +2022-11-14 16:57:55,880 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0750) Prec@1 89.000 (88.053) Prec@5 99.000 (99.253) +2022-11-14 16:57:55,888 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0505 (0.0747) Prec@1 92.000 (88.094) Prec@5 98.000 (99.240) +2022-11-14 16:57:55,895 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0642 (0.0746) Prec@1 91.000 (88.124) Prec@5 99.000 (99.237) +2022-11-14 16:57:55,903 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1009 (0.0749) Prec@1 85.000 (88.092) Prec@5 98.000 (99.224) +2022-11-14 16:57:55,910 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1070 (0.0752) Prec@1 85.000 (88.061) Prec@5 99.000 (99.222) +2022-11-14 16:57:55,918 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0873 (0.0753) Prec@1 88.000 (88.060) Prec@5 100.000 (99.230) +2022-11-14 16:57:55,971 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:57:56,596 Epoch: [427][0/500] Time 0.028 (0.028) Data 0.236 (0.236) Loss 0.0181 (0.0181) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:56,798 Epoch: [427][10/500] Time 0.018 (0.019) Data 0.001 (0.023) Loss 0.0211 (0.0196) Prec@1 98.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:57:56,988 Epoch: [427][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0268 (0.0220) Prec@1 96.000 (96.667) Prec@5 99.000 (99.667) +2022-11-14 16:57:57,185 Epoch: [427][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0289 (0.0237) Prec@1 96.000 (96.500) Prec@5 100.000 (99.750) +2022-11-14 16:57:57,376 Epoch: [427][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0286 (0.0247) Prec@1 95.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 16:57:57,563 Epoch: [427][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0345 (0.0263) Prec@1 96.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 16:57:57,751 Epoch: [427][60/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0393 (0.0282) Prec@1 93.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 16:57:57,938 Epoch: [427][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0224 (0.0275) Prec@1 95.000 (95.625) Prec@5 99.000 (99.750) +2022-11-14 16:57:58,131 Epoch: [427][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0472 (0.0296) Prec@1 91.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 16:57:58,318 Epoch: [427][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0371 (0.0304) Prec@1 94.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 16:57:58,507 Epoch: [427][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0191 (0.0294) Prec@1 96.000 (95.091) Prec@5 100.000 (99.818) +2022-11-14 16:57:58,695 Epoch: [427][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0171 (0.0283) Prec@1 97.000 (95.250) Prec@5 100.000 (99.833) +2022-11-14 16:57:58,883 Epoch: [427][120/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0210 (0.0278) Prec@1 97.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:57:59,070 Epoch: [427][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0158 (0.0269) Prec@1 99.000 (95.643) Prec@5 100.000 (99.857) +2022-11-14 16:57:59,262 Epoch: [427][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0454 (0.0282) Prec@1 92.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:57:59,451 Epoch: [427][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0325 (0.0284) Prec@1 94.000 (95.312) Prec@5 100.000 (99.875) +2022-11-14 16:57:59,640 Epoch: [427][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0478 (0.0296) Prec@1 92.000 (95.118) Prec@5 100.000 (99.882) +2022-11-14 16:57:59,827 Epoch: [427][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0271 (0.0294) Prec@1 97.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 16:58:00,014 Epoch: [427][180/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0328 (0.0296) Prec@1 96.000 (95.263) Prec@5 100.000 (99.895) +2022-11-14 16:58:00,252 Epoch: [427][190/500] Time 0.026 (0.017) Data 0.001 (0.003) Loss 0.0225 (0.0293) Prec@1 96.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 16:58:00,535 Epoch: [427][200/500] Time 0.027 (0.017) Data 0.002 (0.003) Loss 0.0275 (0.0292) Prec@1 96.000 (95.333) Prec@5 99.000 (99.857) +2022-11-14 16:58:00,816 Epoch: [427][210/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0354 (0.0295) Prec@1 93.000 (95.227) Prec@5 100.000 (99.864) +2022-11-14 16:58:01,102 Epoch: [427][220/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0484 (0.0303) Prec@1 93.000 (95.130) Prec@5 100.000 (99.870) +2022-11-14 16:58:01,377 Epoch: [427][230/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0245 (0.0300) Prec@1 96.000 (95.167) Prec@5 100.000 (99.875) +2022-11-14 16:58:01,655 Epoch: [427][240/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0188 (0.0296) Prec@1 98.000 (95.280) Prec@5 100.000 (99.880) +2022-11-14 16:58:01,936 Epoch: [427][250/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0275 (0.0295) Prec@1 97.000 (95.346) Prec@5 100.000 (99.885) +2022-11-14 16:58:02,218 Epoch: [427][260/500] Time 0.029 (0.019) Data 0.001 (0.002) Loss 0.0193 (0.0291) Prec@1 98.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:58:02,492 Epoch: [427][270/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0215 (0.0289) Prec@1 95.000 (95.429) Prec@5 100.000 (99.893) +2022-11-14 16:58:02,767 Epoch: [427][280/500] Time 0.029 (0.019) Data 0.002 (0.002) Loss 0.0369 (0.0291) Prec@1 92.000 (95.310) Prec@5 100.000 (99.897) +2022-11-14 16:58:03,046 Epoch: [427][290/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0099 (0.0285) Prec@1 98.000 (95.400) Prec@5 100.000 (99.900) +2022-11-14 16:58:03,327 Epoch: [427][300/500] Time 0.030 (0.020) Data 0.002 (0.002) Loss 0.0258 (0.0284) Prec@1 95.000 (95.387) Prec@5 100.000 (99.903) +2022-11-14 16:58:03,605 Epoch: [427][310/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0305 (0.0285) Prec@1 94.000 (95.344) Prec@5 100.000 (99.906) +2022-11-14 16:58:03,886 Epoch: [427][320/500] Time 0.031 (0.020) Data 0.002 (0.002) Loss 0.0199 (0.0282) Prec@1 97.000 (95.394) Prec@5 100.000 (99.909) +2022-11-14 16:58:04,165 Epoch: [427][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0301 (0.0283) Prec@1 95.000 (95.382) Prec@5 100.000 (99.912) +2022-11-14 16:58:04,444 Epoch: [427][340/500] Time 0.030 (0.020) Data 0.002 (0.002) Loss 0.0373 (0.0285) Prec@1 91.000 (95.257) Prec@5 100.000 (99.914) +2022-11-14 16:58:04,724 Epoch: [427][350/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0185 (0.0282) Prec@1 97.000 (95.306) Prec@5 100.000 (99.917) +2022-11-14 16:58:05,004 Epoch: [427][360/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0156 (0.0279) Prec@1 97.000 (95.351) Prec@5 100.000 (99.919) +2022-11-14 16:58:05,288 Epoch: [427][370/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0283 (0.0279) Prec@1 94.000 (95.316) Prec@5 100.000 (99.921) +2022-11-14 16:58:05,567 Epoch: [427][380/500] Time 0.029 (0.021) Data 0.002 (0.002) Loss 0.0297 (0.0280) Prec@1 95.000 (95.308) Prec@5 100.000 (99.923) +2022-11-14 16:58:05,856 Epoch: [427][390/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0200 (0.0278) Prec@1 97.000 (95.350) Prec@5 100.000 (99.925) +2022-11-14 16:58:06,135 Epoch: [427][400/500] Time 0.029 (0.021) Data 0.001 (0.002) Loss 0.0312 (0.0278) Prec@1 96.000 (95.366) Prec@5 100.000 (99.927) +2022-11-14 16:58:06,410 Epoch: [427][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0312 (0.0279) Prec@1 95.000 (95.357) Prec@5 100.000 (99.929) +2022-11-14 16:58:06,690 Epoch: [427][420/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0560 (0.0286) Prec@1 90.000 (95.233) Prec@5 100.000 (99.930) +2022-11-14 16:58:06,973 Epoch: [427][430/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0241 (0.0285) Prec@1 96.000 (95.250) Prec@5 100.000 (99.932) +2022-11-14 16:58:07,255 Epoch: [427][440/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0330 (0.0286) Prec@1 95.000 (95.244) Prec@5 100.000 (99.933) +2022-11-14 16:58:07,534 Epoch: [427][450/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0191 (0.0284) Prec@1 97.000 (95.283) Prec@5 100.000 (99.935) +2022-11-14 16:58:07,815 Epoch: [427][460/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0086 (0.0280) Prec@1 99.000 (95.362) Prec@5 100.000 (99.936) +2022-11-14 16:58:08,099 Epoch: [427][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0305 (0.0280) Prec@1 92.000 (95.292) Prec@5 100.000 (99.938) +2022-11-14 16:58:08,372 Epoch: [427][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0236 (0.0279) Prec@1 96.000 (95.306) Prec@5 99.000 (99.918) +2022-11-14 16:58:08,652 Epoch: [427][490/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0303 (0.0280) Prec@1 95.000 (95.300) Prec@5 100.000 (99.920) +2022-11-14 16:58:08,904 Epoch: [427][499/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0293 (0.0280) Prec@1 95.000 (95.294) Prec@5 100.000 (99.922) +2022-11-14 16:58:09,216 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0930 (0.0930) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:09,224 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0796 (0.0863) Prec@1 87.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:09,230 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0860) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:09,240 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0810) Prec@1 88.000 (86.500) Prec@5 99.000 (99.750) +2022-11-14 16:58:09,246 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0817) Prec@1 88.000 (86.800) Prec@5 98.000 (99.400) +2022-11-14 16:58:09,253 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0372 (0.0743) Prec@1 93.000 (87.833) Prec@5 100.000 (99.500) +2022-11-14 16:58:09,260 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0717) Prec@1 92.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 16:58:09,268 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0733) Prec@1 86.000 (88.125) Prec@5 99.000 (99.500) +2022-11-14 16:58:09,275 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0722) Prec@1 91.000 (88.444) Prec@5 100.000 (99.556) +2022-11-14 16:58:09,282 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0713) Prec@1 90.000 (88.600) Prec@5 99.000 (99.500) +2022-11-14 16:58:09,290 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0699) Prec@1 91.000 (88.818) Prec@5 100.000 (99.545) +2022-11-14 16:58:09,299 Test: [11/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0701) Prec@1 88.000 (88.750) Prec@5 100.000 (99.583) +2022-11-14 16:58:09,311 Test: [12/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0699) Prec@1 88.000 (88.692) Prec@5 100.000 (99.615) +2022-11-14 16:58:09,322 Test: [13/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0693) Prec@1 89.000 (88.714) Prec@5 100.000 (99.643) +2022-11-14 16:58:09,331 Test: [14/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0693) Prec@1 87.000 (88.600) Prec@5 100.000 (99.667) +2022-11-14 16:58:09,340 Test: [15/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0699) Prec@1 86.000 (88.438) Prec@5 99.000 (99.625) +2022-11-14 16:58:09,348 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0686) Prec@1 93.000 (88.706) Prec@5 98.000 (99.529) +2022-11-14 16:58:09,356 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0705) Prec@1 85.000 (88.500) Prec@5 100.000 (99.556) +2022-11-14 16:58:09,364 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0717) Prec@1 85.000 (88.316) Prec@5 99.000 (99.526) +2022-11-14 16:58:09,371 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0719) Prec@1 89.000 (88.350) Prec@5 99.000 (99.500) +2022-11-14 16:58:09,379 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0725) Prec@1 86.000 (88.238) Prec@5 100.000 (99.524) +2022-11-14 16:58:09,387 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0734) Prec@1 86.000 (88.136) Prec@5 100.000 (99.545) +2022-11-14 16:58:09,394 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0746) Prec@1 86.000 (88.043) Prec@5 100.000 (99.565) +2022-11-14 16:58:09,402 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0745) Prec@1 88.000 (88.042) Prec@5 100.000 (99.583) +2022-11-14 16:58:09,410 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0747) Prec@1 87.000 (88.000) Prec@5 99.000 (99.560) +2022-11-14 16:58:09,417 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0757) Prec@1 83.000 (87.808) Prec@5 98.000 (99.500) +2022-11-14 16:58:09,425 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0747) Prec@1 93.000 (88.000) Prec@5 100.000 (99.519) +2022-11-14 16:58:09,433 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0746) Prec@1 89.000 (88.036) Prec@5 99.000 (99.500) +2022-11-14 16:58:09,440 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0740) Prec@1 90.000 (88.103) Prec@5 99.000 (99.483) +2022-11-14 16:58:09,449 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0741) Prec@1 87.000 (88.067) Prec@5 99.000 (99.467) +2022-11-14 16:58:09,456 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0741) Prec@1 90.000 (88.129) Prec@5 100.000 (99.484) +2022-11-14 16:58:09,464 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0734) Prec@1 93.000 (88.281) Prec@5 99.000 (99.469) +2022-11-14 16:58:09,472 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0734) Prec@1 88.000 (88.273) Prec@5 99.000 (99.455) +2022-11-14 16:58:09,479 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.0746) Prec@1 82.000 (88.088) Prec@5 99.000 (99.441) +2022-11-14 16:58:09,487 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0750) Prec@1 88.000 (88.086) Prec@5 98.000 (99.400) +2022-11-14 16:58:09,494 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0749) Prec@1 91.000 (88.167) Prec@5 100.000 (99.417) +2022-11-14 16:58:09,502 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0754) Prec@1 84.000 (88.054) Prec@5 99.000 (99.405) +2022-11-14 16:58:09,509 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0756) Prec@1 87.000 (88.026) Prec@5 98.000 (99.368) +2022-11-14 16:58:09,517 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0752) Prec@1 93.000 (88.154) Prec@5 99.000 (99.359) +2022-11-14 16:58:09,525 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0749) Prec@1 88.000 (88.150) Prec@5 100.000 (99.375) +2022-11-14 16:58:09,532 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 86.000 (88.098) Prec@5 100.000 (99.390) +2022-11-14 16:58:09,540 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0748) Prec@1 91.000 (88.167) Prec@5 99.000 (99.381) +2022-11-14 16:58:09,548 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0407 (0.0740) Prec@1 93.000 (88.279) Prec@5 99.000 (99.372) +2022-11-14 16:58:09,556 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0740) Prec@1 88.000 (88.273) Prec@5 99.000 (99.364) +2022-11-14 16:58:09,564 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0734) Prec@1 91.000 (88.333) Prec@5 100.000 (99.378) +2022-11-14 16:58:09,571 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1059 (0.0741) Prec@1 84.000 (88.239) Prec@5 97.000 (99.326) +2022-11-14 16:58:09,579 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0741) Prec@1 89.000 (88.255) Prec@5 100.000 (99.340) +2022-11-14 16:58:09,587 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0744) Prec@1 87.000 (88.229) Prec@5 98.000 (99.312) +2022-11-14 16:58:09,594 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0741) Prec@1 87.000 (88.204) Prec@5 100.000 (99.327) +2022-11-14 16:58:09,602 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0745) Prec@1 86.000 (88.160) Prec@5 99.000 (99.320) +2022-11-14 16:58:09,609 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0742) Prec@1 90.000 (88.196) Prec@5 98.000 (99.294) +2022-11-14 16:58:09,617 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0742) Prec@1 87.000 (88.173) Prec@5 100.000 (99.308) +2022-11-14 16:58:09,624 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0739) Prec@1 90.000 (88.208) Prec@5 100.000 (99.321) +2022-11-14 16:58:09,632 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0733) Prec@1 93.000 (88.296) Prec@5 100.000 (99.333) +2022-11-14 16:58:09,640 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0736) Prec@1 85.000 (88.236) Prec@5 100.000 (99.345) +2022-11-14 16:58:09,648 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0738) Prec@1 87.000 (88.214) Prec@5 99.000 (99.339) +2022-11-14 16:58:09,655 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0739) Prec@1 87.000 (88.193) Prec@5 99.000 (99.333) +2022-11-14 16:58:09,663 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0740) Prec@1 88.000 (88.190) Prec@5 98.000 (99.310) +2022-11-14 16:58:09,671 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0745) Prec@1 85.000 (88.136) Prec@5 100.000 (99.322) +2022-11-14 16:58:09,678 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0744) Prec@1 88.000 (88.133) Prec@5 100.000 (99.333) +2022-11-14 16:58:09,686 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0744) Prec@1 89.000 (88.148) Prec@5 99.000 (99.328) +2022-11-14 16:58:09,694 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0742) Prec@1 88.000 (88.145) Prec@5 100.000 (99.339) +2022-11-14 16:58:09,701 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0741) Prec@1 91.000 (88.190) Prec@5 100.000 (99.349) +2022-11-14 16:58:09,709 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0414 (0.0736) Prec@1 93.000 (88.266) Prec@5 100.000 (99.359) +2022-11-14 16:58:09,717 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1050 (0.0741) Prec@1 84.000 (88.200) Prec@5 99.000 (99.354) +2022-11-14 16:58:09,724 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0739) Prec@1 91.000 (88.242) Prec@5 98.000 (99.333) +2022-11-14 16:58:09,732 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0369 (0.0734) Prec@1 94.000 (88.328) Prec@5 100.000 (99.343) +2022-11-14 16:58:09,740 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0733) Prec@1 90.000 (88.353) Prec@5 98.000 (99.324) +2022-11-14 16:58:09,747 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0730) Prec@1 92.000 (88.406) Prec@5 99.000 (99.319) +2022-11-14 16:58:09,755 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0731) Prec@1 87.000 (88.386) Prec@5 99.000 (99.314) +2022-11-14 16:58:09,762 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0733) Prec@1 87.000 (88.366) Prec@5 99.000 (99.310) +2022-11-14 16:58:09,770 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0731) Prec@1 88.000 (88.361) Prec@5 100.000 (99.319) +2022-11-14 16:58:09,778 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0728) Prec@1 94.000 (88.438) Prec@5 100.000 (99.329) +2022-11-14 16:58:09,786 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0725) Prec@1 89.000 (88.446) Prec@5 100.000 (99.338) +2022-11-14 16:58:09,793 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0727) Prec@1 86.000 (88.413) Prec@5 100.000 (99.347) +2022-11-14 16:58:09,801 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0725) Prec@1 92.000 (88.461) Prec@5 99.000 (99.342) +2022-11-14 16:58:09,809 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0725) Prec@1 89.000 (88.468) Prec@5 98.000 (99.325) +2022-11-14 16:58:09,816 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0728) Prec@1 86.000 (88.436) Prec@5 98.000 (99.308) +2022-11-14 16:58:09,824 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0731) Prec@1 84.000 (88.380) Prec@5 100.000 (99.316) +2022-11-14 16:58:09,831 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0732) Prec@1 86.000 (88.350) Prec@5 99.000 (99.312) +2022-11-14 16:58:09,839 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0733) Prec@1 87.000 (88.333) Prec@5 99.000 (99.309) +2022-11-14 16:58:09,846 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0736) Prec@1 85.000 (88.293) Prec@5 100.000 (99.317) +2022-11-14 16:58:09,854 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0738) Prec@1 88.000 (88.289) Prec@5 98.000 (99.301) +2022-11-14 16:58:09,861 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0739) Prec@1 87.000 (88.274) Prec@5 99.000 (99.298) +2022-11-14 16:58:09,869 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1196 (0.0745) Prec@1 81.000 (88.188) Prec@5 100.000 (99.306) +2022-11-14 16:58:09,877 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1232 (0.0750) Prec@1 78.000 (88.070) Prec@5 100.000 (99.314) +2022-11-14 16:58:09,885 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0750) Prec@1 88.000 (88.069) Prec@5 99.000 (99.310) +2022-11-14 16:58:09,892 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0751) Prec@1 86.000 (88.045) Prec@5 98.000 (99.295) +2022-11-14 16:58:09,900 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0752) Prec@1 85.000 (88.011) Prec@5 100.000 (99.303) +2022-11-14 16:58:09,908 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0750) Prec@1 92.000 (88.056) Prec@5 99.000 (99.300) +2022-11-14 16:58:09,916 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0747) Prec@1 92.000 (88.099) Prec@5 100.000 (99.308) +2022-11-14 16:58:09,924 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0745) Prec@1 92.000 (88.141) Prec@5 100.000 (99.315) +2022-11-14 16:58:09,932 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0746) Prec@1 88.000 (88.140) Prec@5 98.000 (99.301) +2022-11-14 16:58:09,940 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0746) Prec@1 89.000 (88.149) Prec@5 100.000 (99.309) +2022-11-14 16:58:09,947 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0746) Prec@1 87.000 (88.137) Prec@5 99.000 (99.305) +2022-11-14 16:58:09,955 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0746) Prec@1 88.000 (88.135) Prec@5 99.000 (99.302) +2022-11-14 16:58:09,962 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0743) Prec@1 90.000 (88.155) Prec@5 98.000 (99.289) +2022-11-14 16:58:09,969 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0746) Prec@1 83.000 (88.102) Prec@5 99.000 (99.286) +2022-11-14 16:58:09,977 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0749) Prec@1 87.000 (88.091) Prec@5 100.000 (99.293) +2022-11-14 16:58:09,984 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0749) Prec@1 89.000 (88.100) Prec@5 100.000 (99.300) +2022-11-14 16:58:10,037 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:58:10,401 Epoch: [428][0/500] Time 0.022 (0.022) Data 0.240 (0.240) Loss 0.0324 (0.0324) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:10,593 Epoch: [428][10/500] Time 0.017 (0.017) Data 0.002 (0.023) Loss 0.0215 (0.0269) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:10,780 Epoch: [428][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0355 (0.0298) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:10,966 Epoch: [428][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0330 (0.0306) Prec@1 95.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 16:58:11,158 Epoch: [428][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0349 (0.0315) Prec@1 95.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:58:11,348 Epoch: [428][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0402 (0.0329) Prec@1 94.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 16:58:11,540 Epoch: [428][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0254 (0.0318) Prec@1 96.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 16:58:11,730 Epoch: [428][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0242 (0.0309) Prec@1 96.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 16:58:11,922 Epoch: [428][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0115 (0.0287) Prec@1 98.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 16:58:12,114 Epoch: [428][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0257 (0.0284) Prec@1 97.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 16:58:12,303 Epoch: [428][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0284 (0.0284) Prec@1 95.000 (95.273) Prec@5 100.000 (100.000) +2022-11-14 16:58:12,494 Epoch: [428][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0191 (0.0277) Prec@1 97.000 (95.417) Prec@5 100.000 (100.000) +2022-11-14 16:58:12,684 Epoch: [428][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0268 (0.0276) Prec@1 94.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 16:58:12,874 Epoch: [428][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0285 (0.0276) Prec@1 95.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 16:58:13,064 Epoch: [428][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0231 (0.0273) Prec@1 98.000 (95.467) Prec@5 100.000 (100.000) +2022-11-14 16:58:13,257 Epoch: [428][150/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0172 (0.0267) Prec@1 99.000 (95.688) Prec@5 100.000 (100.000) +2022-11-14 16:58:13,445 Epoch: [428][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0318 (0.0270) Prec@1 94.000 (95.588) Prec@5 100.000 (100.000) +2022-11-14 16:58:13,642 Epoch: [428][170/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0086 (0.0260) Prec@1 99.000 (95.778) Prec@5 100.000 (100.000) +2022-11-14 16:58:13,907 Epoch: [428][180/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0301 (0.0262) Prec@1 96.000 (95.789) Prec@5 100.000 (100.000) +2022-11-14 16:58:14,185 Epoch: [428][190/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0262 (0.0262) Prec@1 94.000 (95.700) Prec@5 100.000 (100.000) +2022-11-14 16:58:14,462 Epoch: [428][200/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0269 (0.0262) Prec@1 96.000 (95.714) Prec@5 99.000 (99.952) +2022-11-14 16:58:14,744 Epoch: [428][210/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0248 (0.0262) Prec@1 97.000 (95.773) Prec@5 100.000 (99.955) +2022-11-14 16:58:15,024 Epoch: [428][220/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0375 (0.0267) Prec@1 93.000 (95.652) Prec@5 100.000 (99.957) +2022-11-14 16:58:15,307 Epoch: [428][230/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0237 (0.0265) Prec@1 94.000 (95.583) Prec@5 100.000 (99.958) +2022-11-14 16:58:15,587 Epoch: [428][240/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0282 (0.0266) Prec@1 95.000 (95.560) Prec@5 100.000 (99.960) +2022-11-14 16:58:15,855 Epoch: [428][250/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0159 (0.0262) Prec@1 97.000 (95.615) Prec@5 100.000 (99.962) +2022-11-14 16:58:16,125 Epoch: [428][260/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0480 (0.0270) Prec@1 92.000 (95.481) Prec@5 100.000 (99.963) +2022-11-14 16:58:16,391 Epoch: [428][270/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0339 (0.0273) Prec@1 94.000 (95.429) Prec@5 99.000 (99.929) +2022-11-14 16:58:16,656 Epoch: [428][280/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0123 (0.0267) Prec@1 98.000 (95.517) Prec@5 100.000 (99.931) +2022-11-14 16:58:16,923 Epoch: [428][290/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0336 (0.0270) Prec@1 95.000 (95.500) Prec@5 99.000 (99.900) +2022-11-14 16:58:17,191 Epoch: [428][300/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0382 (0.0273) Prec@1 93.000 (95.419) Prec@5 100.000 (99.903) +2022-11-14 16:58:17,453 Epoch: [428][310/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0346 (0.0276) Prec@1 96.000 (95.438) Prec@5 99.000 (99.875) +2022-11-14 16:58:17,721 Epoch: [428][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0209 (0.0274) Prec@1 96.000 (95.455) Prec@5 100.000 (99.879) +2022-11-14 16:58:17,985 Epoch: [428][330/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0404 (0.0277) Prec@1 93.000 (95.382) Prec@5 100.000 (99.882) +2022-11-14 16:58:18,249 Epoch: [428][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0146 (0.0274) Prec@1 97.000 (95.429) Prec@5 100.000 (99.886) +2022-11-14 16:58:18,515 Epoch: [428][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0211 (0.0272) Prec@1 96.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:58:18,781 Epoch: [428][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0127 (0.0268) Prec@1 99.000 (95.541) Prec@5 100.000 (99.892) +2022-11-14 16:58:19,048 Epoch: [428][370/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0348 (0.0270) Prec@1 94.000 (95.500) Prec@5 100.000 (99.895) +2022-11-14 16:58:19,316 Epoch: [428][380/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0401 (0.0273) Prec@1 94.000 (95.462) Prec@5 100.000 (99.897) +2022-11-14 16:58:19,585 Epoch: [428][390/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0161 (0.0271) Prec@1 98.000 (95.525) Prec@5 100.000 (99.900) +2022-11-14 16:58:19,850 Epoch: [428][400/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0362 (0.0273) Prec@1 94.000 (95.488) Prec@5 100.000 (99.902) +2022-11-14 16:58:20,119 Epoch: [428][410/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0358 (0.0275) Prec@1 94.000 (95.452) Prec@5 99.000 (99.881) +2022-11-14 16:58:20,386 Epoch: [428][420/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0311 (0.0276) Prec@1 94.000 (95.419) Prec@5 100.000 (99.884) +2022-11-14 16:58:20,656 Epoch: [428][430/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0268 (0.0276) Prec@1 95.000 (95.409) Prec@5 100.000 (99.886) +2022-11-14 16:58:20,922 Epoch: [428][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0124 (0.0272) Prec@1 99.000 (95.489) Prec@5 100.000 (99.889) +2022-11-14 16:58:21,189 Epoch: [428][450/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0231 (0.0271) Prec@1 97.000 (95.522) Prec@5 100.000 (99.891) +2022-11-14 16:58:21,451 Epoch: [428][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0323 (0.0272) Prec@1 94.000 (95.489) Prec@5 100.000 (99.894) +2022-11-14 16:58:21,722 Epoch: [428][470/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0218 (0.0271) Prec@1 97.000 (95.521) Prec@5 100.000 (99.896) +2022-11-14 16:58:21,986 Epoch: [428][480/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0554 (0.0277) Prec@1 90.000 (95.408) Prec@5 100.000 (99.898) +2022-11-14 16:58:22,258 Epoch: [428][490/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0349 (0.0278) Prec@1 96.000 (95.420) Prec@5 100.000 (99.900) +2022-11-14 16:58:22,502 Epoch: [428][499/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0340 (0.0280) Prec@1 93.000 (95.373) Prec@5 100.000 (99.902) +2022-11-14 16:58:22,802 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0717 (0.0717) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:22,811 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0679 (0.0698) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:22,819 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0480 (0.0625) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:22,829 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0668) Prec@1 87.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 16:58:22,836 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0647) Prec@1 91.000 (89.600) Prec@5 100.000 (99.800) +2022-11-14 16:58:22,843 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0413 (0.0608) Prec@1 93.000 (90.167) Prec@5 100.000 (99.833) +2022-11-14 16:58:22,850 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0605) Prec@1 93.000 (90.571) Prec@5 99.000 (99.714) +2022-11-14 16:58:22,858 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0651) Prec@1 82.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 16:58:22,865 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0664) Prec@1 89.000 (89.444) Prec@5 99.000 (99.444) +2022-11-14 16:58:22,872 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0666) Prec@1 87.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 16:58:22,880 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0665) Prec@1 90.000 (89.273) Prec@5 99.000 (99.364) +2022-11-14 16:58:22,887 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0675) Prec@1 88.000 (89.167) Prec@5 100.000 (99.417) +2022-11-14 16:58:22,895 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0665) Prec@1 88.000 (89.077) Prec@5 100.000 (99.462) +2022-11-14 16:58:22,903 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0669) Prec@1 89.000 (89.071) Prec@5 99.000 (99.429) +2022-11-14 16:58:22,911 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0672) Prec@1 87.000 (88.933) Prec@5 100.000 (99.467) +2022-11-14 16:58:22,918 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0674) Prec@1 88.000 (88.875) Prec@5 100.000 (99.500) +2022-11-14 16:58:22,926 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0665) Prec@1 91.000 (89.000) Prec@5 97.000 (99.353) +2022-11-14 16:58:22,934 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0686) Prec@1 84.000 (88.722) Prec@5 100.000 (99.389) +2022-11-14 16:58:22,942 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0698) Prec@1 84.000 (88.474) Prec@5 100.000 (99.421) +2022-11-14 16:58:22,950 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0710) Prec@1 85.000 (88.300) Prec@5 97.000 (99.300) +2022-11-14 16:58:22,957 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0716) Prec@1 85.000 (88.143) Prec@5 100.000 (99.333) +2022-11-14 16:58:22,965 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0724) Prec@1 84.000 (87.955) Prec@5 99.000 (99.318) +2022-11-14 16:58:22,973 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0730) Prec@1 88.000 (87.957) Prec@5 98.000 (99.261) +2022-11-14 16:58:22,981 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0730) Prec@1 87.000 (87.917) Prec@5 100.000 (99.292) +2022-11-14 16:58:22,988 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0738) Prec@1 85.000 (87.800) Prec@5 99.000 (99.280) +2022-11-14 16:58:22,996 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0739) Prec@1 90.000 (87.885) Prec@5 98.000 (99.231) +2022-11-14 16:58:23,004 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0731) Prec@1 92.000 (88.037) Prec@5 100.000 (99.259) +2022-11-14 16:58:23,012 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0724) Prec@1 91.000 (88.143) Prec@5 100.000 (99.286) +2022-11-14 16:58:23,019 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0726) Prec@1 86.000 (88.069) Prec@5 99.000 (99.276) +2022-11-14 16:58:23,027 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0723) Prec@1 90.000 (88.133) Prec@5 100.000 (99.300) +2022-11-14 16:58:23,035 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0723) Prec@1 88.000 (88.129) Prec@5 100.000 (99.323) +2022-11-14 16:58:23,042 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0726) Prec@1 88.000 (88.125) Prec@5 99.000 (99.312) +2022-11-14 16:58:23,050 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0727) Prec@1 88.000 (88.121) Prec@5 100.000 (99.333) +2022-11-14 16:58:23,058 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0733) Prec@1 84.000 (88.000) Prec@5 100.000 (99.353) +2022-11-14 16:58:23,066 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0734) Prec@1 87.000 (87.971) Prec@5 99.000 (99.343) +2022-11-14 16:58:23,073 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0736) Prec@1 89.000 (88.000) Prec@5 100.000 (99.361) +2022-11-14 16:58:23,082 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0738) Prec@1 87.000 (87.973) Prec@5 98.000 (99.324) +2022-11-14 16:58:23,090 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0743) Prec@1 81.000 (87.789) Prec@5 99.000 (99.316) +2022-11-14 16:58:23,098 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0738) Prec@1 94.000 (87.949) Prec@5 99.000 (99.308) +2022-11-14 16:58:23,106 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0735) Prec@1 89.000 (87.975) Prec@5 100.000 (99.325) +2022-11-14 16:58:23,114 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0739) Prec@1 86.000 (87.927) Prec@5 100.000 (99.341) +2022-11-14 16:58:23,121 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0740) Prec@1 87.000 (87.905) Prec@5 100.000 (99.357) +2022-11-14 16:58:23,129 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0734) Prec@1 91.000 (87.977) Prec@5 99.000 (99.349) +2022-11-14 16:58:23,137 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0731) Prec@1 89.000 (88.000) Prec@5 99.000 (99.341) +2022-11-14 16:58:23,144 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0727) Prec@1 91.000 (88.067) Prec@5 99.000 (99.333) +2022-11-14 16:58:23,152 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0734) Prec@1 82.000 (87.935) Prec@5 98.000 (99.304) +2022-11-14 16:58:23,160 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0731) Prec@1 89.000 (87.957) Prec@5 100.000 (99.319) +2022-11-14 16:58:23,167 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0739) Prec@1 83.000 (87.854) Prec@5 98.000 (99.292) +2022-11-14 16:58:23,175 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0737) Prec@1 88.000 (87.857) Prec@5 99.000 (99.286) +2022-11-14 16:58:23,183 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0742) Prec@1 82.000 (87.740) Prec@5 100.000 (99.300) +2022-11-14 16:58:23,191 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0740) Prec@1 90.000 (87.784) Prec@5 100.000 (99.314) +2022-11-14 16:58:23,199 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0739) Prec@1 89.000 (87.808) Prec@5 100.000 (99.327) +2022-11-14 16:58:23,207 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0739) Prec@1 86.000 (87.774) Prec@5 99.000 (99.321) +2022-11-14 16:58:23,214 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0739) Prec@1 88.000 (87.778) Prec@5 100.000 (99.333) +2022-11-14 16:58:23,222 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0741) Prec@1 85.000 (87.727) Prec@5 100.000 (99.345) +2022-11-14 16:58:23,230 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0736) Prec@1 93.000 (87.821) Prec@5 99.000 (99.339) +2022-11-14 16:58:23,238 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0735) Prec@1 89.000 (87.842) Prec@5 99.000 (99.333) +2022-11-14 16:58:23,247 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0735) Prec@1 89.000 (87.862) Prec@5 98.000 (99.310) +2022-11-14 16:58:23,255 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0736) Prec@1 89.000 (87.881) Prec@5 100.000 (99.322) +2022-11-14 16:58:23,263 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0734) Prec@1 89.000 (87.900) Prec@5 100.000 (99.333) +2022-11-14 16:58:23,271 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0736) Prec@1 89.000 (87.918) Prec@5 99.000 (99.328) +2022-11-14 16:58:23,279 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0737) Prec@1 87.000 (87.903) Prec@5 100.000 (99.339) +2022-11-14 16:58:23,287 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0734) Prec@1 89.000 (87.921) Prec@5 100.000 (99.349) +2022-11-14 16:58:23,294 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0330 (0.0727) Prec@1 93.000 (88.000) Prec@5 99.000 (99.344) +2022-11-14 16:58:23,302 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0732) Prec@1 84.000 (87.938) Prec@5 100.000 (99.354) +2022-11-14 16:58:23,310 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0731) Prec@1 91.000 (87.985) Prec@5 99.000 (99.348) +2022-11-14 16:58:23,318 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0397 (0.0726) Prec@1 93.000 (88.060) Prec@5 100.000 (99.358) +2022-11-14 16:58:23,326 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0724) Prec@1 90.000 (88.088) Prec@5 100.000 (99.368) +2022-11-14 16:58:23,333 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0726) Prec@1 87.000 (88.072) Prec@5 99.000 (99.362) +2022-11-14 16:58:23,341 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0728) Prec@1 85.000 (88.029) Prec@5 98.000 (99.343) +2022-11-14 16:58:23,349 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1094 (0.0733) Prec@1 85.000 (87.986) Prec@5 97.000 (99.310) +2022-11-14 16:58:23,356 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0731) Prec@1 92.000 (88.042) Prec@5 100.000 (99.319) +2022-11-14 16:58:23,364 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0727) Prec@1 93.000 (88.110) Prec@5 100.000 (99.329) +2022-11-14 16:58:23,372 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0724) Prec@1 94.000 (88.189) Prec@5 100.000 (99.338) +2022-11-14 16:58:23,379 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0728) Prec@1 83.000 (88.120) Prec@5 98.000 (99.320) +2022-11-14 16:58:23,387 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0728) Prec@1 90.000 (88.145) Prec@5 100.000 (99.329) +2022-11-14 16:58:23,394 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0729) Prec@1 86.000 (88.117) Prec@5 97.000 (99.299) +2022-11-14 16:58:23,402 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0734) Prec@1 83.000 (88.051) Prec@5 98.000 (99.282) +2022-11-14 16:58:23,409 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0735) Prec@1 88.000 (88.051) Prec@5 100.000 (99.291) +2022-11-14 16:58:23,417 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0734) Prec@1 88.000 (88.050) Prec@5 100.000 (99.300) +2022-11-14 16:58:23,425 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0734) Prec@1 90.000 (88.074) Prec@5 99.000 (99.296) +2022-11-14 16:58:23,432 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0736) Prec@1 84.000 (88.024) Prec@5 98.000 (99.280) +2022-11-14 16:58:23,440 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0737) Prec@1 86.000 (88.000) Prec@5 100.000 (99.289) +2022-11-14 16:58:23,447 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0736) Prec@1 86.000 (87.976) Prec@5 99.000 (99.286) +2022-11-14 16:58:23,455 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0737) Prec@1 86.000 (87.953) Prec@5 100.000 (99.294) +2022-11-14 16:58:23,462 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0741) Prec@1 85.000 (87.919) Prec@5 100.000 (99.302) +2022-11-14 16:58:23,470 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0740) Prec@1 91.000 (87.954) Prec@5 100.000 (99.310) +2022-11-14 16:58:23,478 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0740) Prec@1 90.000 (87.977) Prec@5 99.000 (99.307) +2022-11-14 16:58:23,485 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0741) Prec@1 85.000 (87.944) Prec@5 100.000 (99.315) +2022-11-14 16:58:23,493 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0741) Prec@1 89.000 (87.956) Prec@5 99.000 (99.311) +2022-11-14 16:58:23,501 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0483 (0.0738) Prec@1 91.000 (87.989) Prec@5 100.000 (99.319) +2022-11-14 16:58:23,508 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0737) Prec@1 92.000 (88.033) Prec@5 100.000 (99.326) +2022-11-14 16:58:23,516 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0738) Prec@1 89.000 (88.043) Prec@5 100.000 (99.333) +2022-11-14 16:58:23,524 Test: [93/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0737) Prec@1 91.000 (88.074) Prec@5 100.000 (99.340) +2022-11-14 16:58:23,532 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0737) Prec@1 87.000 (88.063) Prec@5 100.000 (99.347) +2022-11-14 16:58:23,540 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0736) Prec@1 91.000 (88.094) Prec@5 100.000 (99.354) +2022-11-14 16:58:23,547 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0735) Prec@1 89.000 (88.103) Prec@5 99.000 (99.351) +2022-11-14 16:58:23,555 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0737) Prec@1 85.000 (88.071) Prec@5 99.000 (99.347) +2022-11-14 16:58:23,565 Test: [98/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0738) Prec@1 88.000 (88.071) Prec@5 100.000 (99.354) +2022-11-14 16:58:23,575 Test: [99/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0737) Prec@1 89.000 (88.080) Prec@5 100.000 (99.360) +2022-11-14 16:58:23,646 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:58:24,363 Epoch: [429][0/500] Time 0.026 (0.026) Data 0.228 (0.228) Loss 0.0397 (0.0397) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 16:58:24,558 Epoch: [429][10/500] Time 0.016 (0.018) Data 0.001 (0.022) Loss 0.0339 (0.0368) Prec@1 93.000 (92.500) Prec@5 100.000 (99.500) +2022-11-14 16:58:24,748 Epoch: [429][20/500] Time 0.017 (0.017) Data 0.001 (0.012) Loss 0.0313 (0.0350) Prec@1 97.000 (94.000) Prec@5 99.000 (99.333) +2022-11-14 16:58:24,935 Epoch: [429][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0321 (0.0342) Prec@1 95.000 (94.250) Prec@5 100.000 (99.500) +2022-11-14 16:58:25,124 Epoch: [429][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0444 (0.0363) Prec@1 91.000 (93.600) Prec@5 100.000 (99.600) +2022-11-14 16:58:25,314 Epoch: [429][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0336 (0.0358) Prec@1 95.000 (93.833) Prec@5 99.000 (99.500) +2022-11-14 16:58:25,501 Epoch: [429][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0299 (0.0350) Prec@1 96.000 (94.143) Prec@5 100.000 (99.571) +2022-11-14 16:58:25,690 Epoch: [429][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0180 (0.0329) Prec@1 96.000 (94.375) Prec@5 100.000 (99.625) +2022-11-14 16:58:25,875 Epoch: [429][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0316 (0.0327) Prec@1 95.000 (94.444) Prec@5 100.000 (99.667) +2022-11-14 16:58:26,060 Epoch: [429][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0162 (0.0311) Prec@1 97.000 (94.700) Prec@5 100.000 (99.700) +2022-11-14 16:58:26,248 Epoch: [429][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0228 (0.0303) Prec@1 96.000 (94.818) Prec@5 100.000 (99.727) +2022-11-14 16:58:26,434 Epoch: [429][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0308 (0.0303) Prec@1 92.000 (94.583) Prec@5 100.000 (99.750) +2022-11-14 16:58:26,621 Epoch: [429][120/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0356 (0.0308) Prec@1 95.000 (94.615) Prec@5 100.000 (99.769) +2022-11-14 16:58:26,807 Epoch: [429][130/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0265 (0.0305) Prec@1 95.000 (94.643) Prec@5 100.000 (99.786) +2022-11-14 16:58:27,016 Epoch: [429][140/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0360 (0.0308) Prec@1 95.000 (94.667) Prec@5 100.000 (99.800) +2022-11-14 16:58:27,225 Epoch: [429][150/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0213 (0.0302) Prec@1 97.000 (94.812) Prec@5 100.000 (99.812) +2022-11-14 16:58:27,426 Epoch: [429][160/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.0285 (0.0301) Prec@1 94.000 (94.765) Prec@5 100.000 (99.824) +2022-11-14 16:58:27,616 Epoch: [429][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0383 (0.0306) Prec@1 94.000 (94.722) Prec@5 99.000 (99.778) +2022-11-14 16:58:27,803 Epoch: [429][180/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0190 (0.0300) Prec@1 97.000 (94.842) Prec@5 100.000 (99.789) +2022-11-14 16:58:28,003 Epoch: [429][190/500] Time 0.021 (0.017) Data 0.001 (0.003) Loss 0.0267 (0.0298) Prec@1 97.000 (94.950) Prec@5 100.000 (99.800) +2022-11-14 16:58:28,259 Epoch: [429][200/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0297 (0.0298) Prec@1 94.000 (94.905) Prec@5 100.000 (99.810) +2022-11-14 16:58:28,522 Epoch: [429][210/500] Time 0.025 (0.017) Data 0.002 (0.003) Loss 0.0345 (0.0300) Prec@1 96.000 (94.955) Prec@5 100.000 (99.818) +2022-11-14 16:58:28,785 Epoch: [429][220/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0316 (0.0301) Prec@1 96.000 (95.000) Prec@5 100.000 (99.826) +2022-11-14 16:58:29,053 Epoch: [429][230/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0250 (0.0299) Prec@1 97.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 16:58:29,322 Epoch: [429][240/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0303 (0.0299) Prec@1 94.000 (95.040) Prec@5 99.000 (99.800) +2022-11-14 16:58:29,586 Epoch: [429][250/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0099 (0.0291) Prec@1 99.000 (95.192) Prec@5 100.000 (99.808) +2022-11-14 16:58:29,850 Epoch: [429][260/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0306 (0.0292) Prec@1 93.000 (95.111) Prec@5 100.000 (99.815) +2022-11-14 16:58:30,121 Epoch: [429][270/500] Time 0.031 (0.019) Data 0.001 (0.002) Loss 0.0344 (0.0294) Prec@1 95.000 (95.107) Prec@5 100.000 (99.821) +2022-11-14 16:58:30,394 Epoch: [429][280/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0484 (0.0300) Prec@1 91.000 (94.966) Prec@5 100.000 (99.828) +2022-11-14 16:58:30,668 Epoch: [429][290/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0286 (0.0300) Prec@1 95.000 (94.967) Prec@5 100.000 (99.833) +2022-11-14 16:58:30,941 Epoch: [429][300/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0355 (0.0301) Prec@1 93.000 (94.903) Prec@5 99.000 (99.806) +2022-11-14 16:58:31,216 Epoch: [429][310/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0192 (0.0298) Prec@1 97.000 (94.969) Prec@5 100.000 (99.812) +2022-11-14 16:58:31,487 Epoch: [429][320/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0055 (0.0291) Prec@1 100.000 (95.121) Prec@5 100.000 (99.818) +2022-11-14 16:58:31,759 Epoch: [429][330/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0131 (0.0286) Prec@1 99.000 (95.235) Prec@5 100.000 (99.824) +2022-11-14 16:58:32,025 Epoch: [429][340/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0176 (0.0283) Prec@1 97.000 (95.286) Prec@5 100.000 (99.829) +2022-11-14 16:58:32,297 Epoch: [429][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0178 (0.0280) Prec@1 97.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 16:58:32,567 Epoch: [429][360/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0185 (0.0277) Prec@1 99.000 (95.432) Prec@5 100.000 (99.838) +2022-11-14 16:58:32,837 Epoch: [429][370/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0405 (0.0281) Prec@1 92.000 (95.342) Prec@5 100.000 (99.842) +2022-11-14 16:58:33,107 Epoch: [429][380/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0297 (0.0281) Prec@1 95.000 (95.333) Prec@5 100.000 (99.846) +2022-11-14 16:58:33,365 Epoch: [429][390/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0314 (0.0282) Prec@1 94.000 (95.300) Prec@5 100.000 (99.850) +2022-11-14 16:58:33,627 Epoch: [429][400/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0315 (0.0283) Prec@1 95.000 (95.293) Prec@5 100.000 (99.854) +2022-11-14 16:58:33,890 Epoch: [429][410/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0147 (0.0280) Prec@1 97.000 (95.333) Prec@5 100.000 (99.857) +2022-11-14 16:58:34,156 Epoch: [429][420/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0280) Prec@1 93.000 (95.279) Prec@5 99.000 (99.837) +2022-11-14 16:58:34,423 Epoch: [429][430/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0420 (0.0283) Prec@1 93.000 (95.227) Prec@5 100.000 (99.841) +2022-11-14 16:58:34,682 Epoch: [429][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0104 (0.0279) Prec@1 97.000 (95.267) Prec@5 100.000 (99.844) +2022-11-14 16:58:34,938 Epoch: [429][450/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0284 (0.0279) Prec@1 93.000 (95.217) Prec@5 100.000 (99.848) +2022-11-14 16:58:35,199 Epoch: [429][460/500] Time 0.022 (0.021) Data 0.003 (0.002) Loss 0.0232 (0.0278) Prec@1 97.000 (95.255) Prec@5 100.000 (99.851) +2022-11-14 16:58:35,460 Epoch: [429][470/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0405 (0.0281) Prec@1 95.000 (95.250) Prec@5 99.000 (99.833) +2022-11-14 16:58:35,722 Epoch: [429][480/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0295 (0.0281) Prec@1 95.000 (95.245) Prec@5 99.000 (99.816) +2022-11-14 16:58:35,981 Epoch: [429][490/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0143 (0.0278) Prec@1 97.000 (95.280) Prec@5 100.000 (99.820) +2022-11-14 16:58:36,217 Epoch: [429][499/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0222 (0.0277) Prec@1 96.000 (95.294) Prec@5 100.000 (99.824) +2022-11-14 16:58:36,523 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:36,531 Test: [1/100] Model Time 0.007 (0.011) Loss Time 0.000 (0.000) Loss 0.0769 (0.0754) Prec@1 87.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:36,541 Test: [2/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0752 (0.0754) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:36,550 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0801 (0.0765) Prec@1 87.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 16:58:36,557 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0452 (0.0703) Prec@1 94.000 (89.000) Prec@5 100.000 (99.800) +2022-11-14 16:58:36,564 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0668) Prec@1 91.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 16:58:36,572 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0668) Prec@1 90.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 16:58:36,580 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0688) Prec@1 84.000 (88.750) Prec@5 100.000 (99.875) +2022-11-14 16:58:36,587 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0686) Prec@1 89.000 (88.778) Prec@5 98.000 (99.667) +2022-11-14 16:58:36,594 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0689) Prec@1 89.000 (88.800) Prec@5 99.000 (99.600) +2022-11-14 16:58:36,602 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0687) Prec@1 89.000 (88.818) Prec@5 100.000 (99.636) +2022-11-14 16:58:36,610 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0858 (0.0701) Prec@1 83.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 16:58:36,618 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0693) Prec@1 91.000 (88.538) Prec@5 100.000 (99.692) +2022-11-14 16:58:36,625 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0697) Prec@1 88.000 (88.500) Prec@5 99.000 (99.643) +2022-11-14 16:58:36,633 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0697) Prec@1 89.000 (88.533) Prec@5 100.000 (99.667) +2022-11-14 16:58:36,641 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0711) Prec@1 83.000 (88.188) Prec@5 100.000 (99.688) +2022-11-14 16:58:36,648 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0698) Prec@1 94.000 (88.529) Prec@5 98.000 (99.588) +2022-11-14 16:58:36,656 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1236 (0.0728) Prec@1 79.000 (88.000) Prec@5 99.000 (99.556) +2022-11-14 16:58:36,664 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0733) Prec@1 86.000 (87.895) Prec@5 100.000 (99.579) +2022-11-14 16:58:36,672 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0740) Prec@1 86.000 (87.800) Prec@5 97.000 (99.450) +2022-11-14 16:58:36,680 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0737) Prec@1 89.000 (87.857) Prec@5 100.000 (99.476) +2022-11-14 16:58:36,688 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0744) Prec@1 85.000 (87.727) Prec@5 98.000 (99.409) +2022-11-14 16:58:36,695 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.0761) Prec@1 82.000 (87.478) Prec@5 97.000 (99.304) +2022-11-14 16:58:36,704 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0762) Prec@1 88.000 (87.500) Prec@5 100.000 (99.333) +2022-11-14 16:58:36,712 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0770) Prec@1 84.000 (87.360) Prec@5 100.000 (99.360) +2022-11-14 16:58:36,720 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0785) Prec@1 82.000 (87.154) Prec@5 96.000 (99.231) +2022-11-14 16:58:36,728 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0778) Prec@1 92.000 (87.333) Prec@5 100.000 (99.259) +2022-11-14 16:58:36,735 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0769) Prec@1 92.000 (87.500) Prec@5 100.000 (99.286) +2022-11-14 16:58:36,743 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0764) Prec@1 91.000 (87.621) Prec@5 98.000 (99.241) +2022-11-14 16:58:36,751 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0761) Prec@1 88.000 (87.633) Prec@5 100.000 (99.267) +2022-11-14 16:58:36,759 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0756) Prec@1 89.000 (87.677) Prec@5 100.000 (99.290) +2022-11-14 16:58:36,767 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0752) Prec@1 90.000 (87.750) Prec@5 99.000 (99.281) +2022-11-14 16:58:36,774 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0751) Prec@1 86.000 (87.697) Prec@5 99.000 (99.273) +2022-11-14 16:58:36,782 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0754) Prec@1 86.000 (87.647) Prec@5 100.000 (99.294) +2022-11-14 16:58:36,790 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0760) Prec@1 85.000 (87.571) Prec@5 99.000 (99.286) +2022-11-14 16:58:36,798 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0757) Prec@1 92.000 (87.694) Prec@5 99.000 (99.278) +2022-11-14 16:58:36,806 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0757) Prec@1 88.000 (87.703) Prec@5 99.000 (99.270) +2022-11-14 16:58:36,814 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0762) Prec@1 84.000 (87.605) Prec@5 98.000 (99.237) +2022-11-14 16:58:36,821 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0757) Prec@1 94.000 (87.769) Prec@5 98.000 (99.205) +2022-11-14 16:58:36,829 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0755) Prec@1 90.000 (87.825) Prec@5 100.000 (99.225) +2022-11-14 16:58:36,837 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0760) Prec@1 87.000 (87.805) Prec@5 98.000 (99.195) +2022-11-14 16:58:36,844 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0763) Prec@1 86.000 (87.762) Prec@5 100.000 (99.214) +2022-11-14 16:58:36,852 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0758) Prec@1 91.000 (87.837) Prec@5 98.000 (99.186) +2022-11-14 16:58:36,860 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0757) Prec@1 88.000 (87.841) Prec@5 100.000 (99.205) +2022-11-14 16:58:36,867 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0499 (0.0751) Prec@1 92.000 (87.933) Prec@5 100.000 (99.222) +2022-11-14 16:58:36,875 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0758) Prec@1 81.000 (87.783) Prec@5 97.000 (99.174) +2022-11-14 16:58:36,882 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0758) Prec@1 87.000 (87.766) Prec@5 100.000 (99.191) +2022-11-14 16:58:36,889 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0764) Prec@1 83.000 (87.667) Prec@5 99.000 (99.188) +2022-11-14 16:58:36,897 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0762) Prec@1 90.000 (87.714) Prec@5 100.000 (99.204) +2022-11-14 16:58:36,904 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0766) Prec@1 84.000 (87.640) Prec@5 100.000 (99.220) +2022-11-14 16:58:36,912 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0767) Prec@1 88.000 (87.647) Prec@5 100.000 (99.235) +2022-11-14 16:58:36,919 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0765) Prec@1 88.000 (87.654) Prec@5 100.000 (99.250) +2022-11-14 16:58:36,926 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0762) Prec@1 90.000 (87.698) Prec@5 99.000 (99.245) +2022-11-14 16:58:36,934 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0761) Prec@1 89.000 (87.722) Prec@5 100.000 (99.259) +2022-11-14 16:58:36,941 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1022 (0.0766) Prec@1 83.000 (87.636) Prec@5 99.000 (99.255) +2022-11-14 16:58:36,948 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0765) Prec@1 87.000 (87.625) Prec@5 99.000 (99.250) +2022-11-14 16:58:36,956 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0763) Prec@1 86.000 (87.596) Prec@5 100.000 (99.263) +2022-11-14 16:58:36,963 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0761) Prec@1 92.000 (87.672) Prec@5 99.000 (99.259) +2022-11-14 16:58:36,971 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0765) Prec@1 84.000 (87.610) Prec@5 100.000 (99.271) +2022-11-14 16:58:36,978 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0767) Prec@1 87.000 (87.600) Prec@5 100.000 (99.283) +2022-11-14 16:58:36,985 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0764) Prec@1 92.000 (87.672) Prec@5 100.000 (99.295) +2022-11-14 16:58:36,993 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0760) Prec@1 89.000 (87.694) Prec@5 99.000 (99.290) +2022-11-14 16:58:37,001 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0757) Prec@1 89.000 (87.714) Prec@5 100.000 (99.302) +2022-11-14 16:58:37,008 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0752) Prec@1 93.000 (87.797) Prec@5 100.000 (99.312) +2022-11-14 16:58:37,016 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0753) Prec@1 86.000 (87.769) Prec@5 100.000 (99.323) +2022-11-14 16:58:37,023 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0463 (0.0749) Prec@1 92.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 16:58:37,031 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0376 (0.0743) Prec@1 93.000 (87.910) Prec@5 100.000 (99.343) +2022-11-14 16:58:37,038 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0743) Prec@1 88.000 (87.912) Prec@5 100.000 (99.353) +2022-11-14 16:58:37,046 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0742) Prec@1 87.000 (87.899) Prec@5 99.000 (99.348) +2022-11-14 16:58:37,053 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0743) Prec@1 88.000 (87.900) Prec@5 99.000 (99.343) +2022-11-14 16:58:37,061 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1234 (0.0749) Prec@1 82.000 (87.817) Prec@5 100.000 (99.352) +2022-11-14 16:58:37,068 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0748) Prec@1 88.000 (87.819) Prec@5 100.000 (99.361) +2022-11-14 16:58:37,076 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0543 (0.0745) Prec@1 91.000 (87.863) Prec@5 100.000 (99.370) +2022-11-14 16:58:37,084 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0376 (0.0740) Prec@1 95.000 (87.959) Prec@5 100.000 (99.378) +2022-11-14 16:58:37,091 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1089 (0.0745) Prec@1 81.000 (87.867) Prec@5 100.000 (99.387) +2022-11-14 16:58:37,099 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0745) Prec@1 88.000 (87.868) Prec@5 98.000 (99.368) +2022-11-14 16:58:37,106 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0617 (0.0743) Prec@1 91.000 (87.909) Prec@5 99.000 (99.364) +2022-11-14 16:58:37,113 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0796 (0.0744) Prec@1 87.000 (87.897) Prec@5 99.000 (99.359) +2022-11-14 16:58:37,121 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0806 (0.0744) Prec@1 87.000 (87.886) Prec@5 100.000 (99.367) +2022-11-14 16:58:37,128 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0529 (0.0742) Prec@1 89.000 (87.900) Prec@5 100.000 (99.375) +2022-11-14 16:58:37,136 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0978 (0.0745) Prec@1 87.000 (87.889) Prec@5 98.000 (99.358) +2022-11-14 16:58:37,143 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1037 (0.0748) Prec@1 85.000 (87.854) Prec@5 99.000 (99.354) +2022-11-14 16:58:37,151 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0748) Prec@1 90.000 (87.880) Prec@5 100.000 (99.361) +2022-11-14 16:58:37,158 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0515 (0.0746) Prec@1 90.000 (87.905) Prec@5 100.000 (99.369) +2022-11-14 16:58:37,165 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0949 (0.0748) Prec@1 84.000 (87.859) Prec@5 99.000 (99.365) +2022-11-14 16:58:37,173 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0916 (0.0750) Prec@1 86.000 (87.837) Prec@5 100.000 (99.372) +2022-11-14 16:58:37,181 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0750) Prec@1 88.000 (87.839) Prec@5 99.000 (99.368) +2022-11-14 16:58:37,188 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0751) Prec@1 88.000 (87.841) Prec@5 99.000 (99.364) +2022-11-14 16:58:37,196 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0841 (0.0752) Prec@1 84.000 (87.798) Prec@5 100.000 (99.371) +2022-11-14 16:58:37,203 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0582 (0.0750) Prec@1 92.000 (87.844) Prec@5 98.000 (99.356) +2022-11-14 16:58:37,211 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0432 (0.0746) Prec@1 92.000 (87.890) Prec@5 100.000 (99.363) +2022-11-14 16:58:37,219 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0589 (0.0744) Prec@1 91.000 (87.924) Prec@5 100.000 (99.370) +2022-11-14 16:58:37,226 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1010 (0.0747) Prec@1 84.000 (87.882) Prec@5 100.000 (99.376) +2022-11-14 16:58:37,233 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0637 (0.0746) Prec@1 91.000 (87.915) Prec@5 100.000 (99.383) +2022-11-14 16:58:37,241 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0827 (0.0747) Prec@1 88.000 (87.916) Prec@5 98.000 (99.368) +2022-11-14 16:58:37,248 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0746) Prec@1 91.000 (87.948) Prec@5 100.000 (99.375) +2022-11-14 16:58:37,255 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0450 (0.0743) Prec@1 94.000 (88.010) Prec@5 99.000 (99.371) +2022-11-14 16:58:37,263 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0742) Prec@1 90.000 (88.031) Prec@5 100.000 (99.378) +2022-11-14 16:58:37,270 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1041 (0.0745) Prec@1 85.000 (88.000) Prec@5 100.000 (99.384) +2022-11-14 16:58:37,278 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0745) Prec@1 89.000 (88.010) Prec@5 100.000 (99.390) +2022-11-14 16:58:37,330 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:58:37,840 Epoch: [430][0/500] Time 0.021 (0.021) Data 0.234 (0.234) Loss 0.0269 (0.0269) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,034 Epoch: [430][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0156 (0.0212) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,224 Epoch: [430][20/500] Time 0.016 (0.017) Data 0.001 (0.013) Loss 0.0119 (0.0181) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,413 Epoch: [430][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0208 (0.0188) Prec@1 97.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,604 Epoch: [430][40/500] Time 0.016 (0.017) Data 0.002 (0.007) Loss 0.0132 (0.0177) Prec@1 98.000 (96.800) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,792 Epoch: [430][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0287 (0.0195) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:38,985 Epoch: [430][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0138 (0.0187) Prec@1 100.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:39,174 Epoch: [430][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0186 (0.0187) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:39,360 Epoch: [430][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0143 (0.0182) Prec@1 98.000 (97.111) Prec@5 100.000 (100.000) +2022-11-14 16:58:39,549 Epoch: [430][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0384 (0.0202) Prec@1 93.000 (96.700) Prec@5 98.000 (99.800) +2022-11-14 16:58:39,748 Epoch: [430][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0288 (0.0210) Prec@1 95.000 (96.545) Prec@5 99.000 (99.727) +2022-11-14 16:58:39,942 Epoch: [430][110/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0236 (0.0212) Prec@1 97.000 (96.583) Prec@5 100.000 (99.750) +2022-11-14 16:58:40,175 Epoch: [430][120/500] Time 0.024 (0.017) Data 0.001 (0.003) Loss 0.0340 (0.0222) Prec@1 96.000 (96.538) Prec@5 99.000 (99.692) +2022-11-14 16:58:40,453 Epoch: [430][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0248 (0.0224) Prec@1 96.000 (96.500) Prec@5 100.000 (99.714) +2022-11-14 16:58:40,733 Epoch: [430][140/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0171 (0.0220) Prec@1 97.000 (96.533) Prec@5 100.000 (99.733) +2022-11-14 16:58:41,016 Epoch: [430][150/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0348 (0.0228) Prec@1 95.000 (96.438) Prec@5 100.000 (99.750) +2022-11-14 16:58:41,302 Epoch: [430][160/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0248 (0.0229) Prec@1 95.000 (96.353) Prec@5 100.000 (99.765) +2022-11-14 16:58:41,585 Epoch: [430][170/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0408 (0.0239) Prec@1 94.000 (96.222) Prec@5 99.000 (99.722) +2022-11-14 16:58:41,863 Epoch: [430][180/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0450 (0.0250) Prec@1 91.000 (95.947) Prec@5 100.000 (99.737) +2022-11-14 16:58:42,148 Epoch: [430][190/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0263 (0.0251) Prec@1 96.000 (95.950) Prec@5 100.000 (99.750) +2022-11-14 16:58:42,433 Epoch: [430][200/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0363 (0.0256) Prec@1 94.000 (95.857) Prec@5 99.000 (99.714) +2022-11-14 16:58:42,717 Epoch: [430][210/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0603 (0.0272) Prec@1 89.000 (95.545) Prec@5 100.000 (99.727) +2022-11-14 16:58:42,998 Epoch: [430][220/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0266 (0.0272) Prec@1 96.000 (95.565) Prec@5 100.000 (99.739) +2022-11-14 16:58:43,275 Epoch: [430][230/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0440 (0.0279) Prec@1 91.000 (95.375) Prec@5 100.000 (99.750) +2022-11-14 16:58:43,553 Epoch: [430][240/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0172 (0.0275) Prec@1 98.000 (95.480) Prec@5 100.000 (99.760) +2022-11-14 16:58:43,837 Epoch: [430][250/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0223 (0.0273) Prec@1 96.000 (95.500) Prec@5 100.000 (99.769) +2022-11-14 16:58:44,125 Epoch: [430][260/500] Time 0.029 (0.021) Data 0.001 (0.003) Loss 0.0163 (0.0269) Prec@1 97.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 16:58:44,405 Epoch: [430][270/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0342 (0.0271) Prec@1 94.000 (95.500) Prec@5 100.000 (99.786) +2022-11-14 16:58:44,682 Epoch: [430][280/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0596 (0.0282) Prec@1 91.000 (95.345) Prec@5 100.000 (99.793) +2022-11-14 16:58:44,961 Epoch: [430][290/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0200 (0.0280) Prec@1 98.000 (95.433) Prec@5 100.000 (99.800) +2022-11-14 16:58:45,233 Epoch: [430][300/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0291 (0.0280) Prec@1 95.000 (95.419) Prec@5 100.000 (99.806) +2022-11-14 16:58:45,507 Epoch: [430][310/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0147 (0.0276) Prec@1 98.000 (95.500) Prec@5 100.000 (99.812) +2022-11-14 16:58:45,789 Epoch: [430][320/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0306 (0.0277) Prec@1 95.000 (95.485) Prec@5 100.000 (99.818) +2022-11-14 16:58:46,067 Epoch: [430][330/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0470 (0.0282) Prec@1 92.000 (95.382) Prec@5 100.000 (99.824) +2022-11-14 16:58:46,345 Epoch: [430][340/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0435 (0.0287) Prec@1 92.000 (95.286) Prec@5 100.000 (99.829) +2022-11-14 16:58:46,629 Epoch: [430][350/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0493 (0.0292) Prec@1 92.000 (95.194) Prec@5 100.000 (99.833) +2022-11-14 16:58:46,911 Epoch: [430][360/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0210 (0.0290) Prec@1 96.000 (95.216) Prec@5 99.000 (99.811) +2022-11-14 16:58:47,186 Epoch: [430][370/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0266 (0.0290) Prec@1 96.000 (95.237) Prec@5 99.000 (99.789) +2022-11-14 16:58:47,458 Epoch: [430][380/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0364 (0.0292) Prec@1 93.000 (95.179) Prec@5 100.000 (99.795) +2022-11-14 16:58:47,733 Epoch: [430][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0164 (0.0288) Prec@1 97.000 (95.225) Prec@5 100.000 (99.800) +2022-11-14 16:58:48,015 Epoch: [430][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0147 (0.0285) Prec@1 97.000 (95.268) Prec@5 100.000 (99.805) +2022-11-14 16:58:48,294 Epoch: [430][410/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0204 (0.0283) Prec@1 96.000 (95.286) Prec@5 100.000 (99.810) +2022-11-14 16:58:48,573 Epoch: [430][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0347 (0.0284) Prec@1 95.000 (95.279) Prec@5 100.000 (99.814) +2022-11-14 16:58:48,855 Epoch: [430][430/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0400 (0.0287) Prec@1 94.000 (95.250) Prec@5 100.000 (99.818) +2022-11-14 16:58:49,137 Epoch: [430][440/500] Time 0.032 (0.023) Data 0.001 (0.002) Loss 0.0422 (0.0290) Prec@1 94.000 (95.222) Prec@5 100.000 (99.822) +2022-11-14 16:58:49,415 Epoch: [430][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0324 (0.0291) Prec@1 95.000 (95.217) Prec@5 100.000 (99.826) +2022-11-14 16:58:49,693 Epoch: [430][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0260 (0.0290) Prec@1 96.000 (95.234) Prec@5 100.000 (99.830) +2022-11-14 16:58:49,972 Epoch: [430][470/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0648 (0.0298) Prec@1 87.000 (95.062) Prec@5 100.000 (99.833) +2022-11-14 16:58:50,253 Epoch: [430][480/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0213 (0.0296) Prec@1 96.000 (95.082) Prec@5 100.000 (99.837) +2022-11-14 16:58:50,530 Epoch: [430][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0298 (0.0296) Prec@1 96.000 (95.100) Prec@5 100.000 (99.840) +2022-11-14 16:58:50,780 Epoch: [430][499/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0339 (0.0297) Prec@1 93.000 (95.059) Prec@5 100.000 (99.843) +2022-11-14 16:58:51,105 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0747 (0.0747) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:51,115 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0770 (0.0758) Prec@1 86.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 16:58:51,123 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0738) Prec@1 90.000 (87.667) Prec@5 99.000 (99.667) +2022-11-14 16:58:51,134 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0890 (0.0776) Prec@1 85.000 (87.000) Prec@5 99.000 (99.500) +2022-11-14 16:58:51,141 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0792) Prec@1 85.000 (86.600) Prec@5 100.000 (99.600) +2022-11-14 16:58:51,148 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0268 (0.0704) Prec@1 94.000 (87.833) Prec@5 100.000 (99.667) +2022-11-14 16:58:51,155 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0704) Prec@1 89.000 (88.000) Prec@5 99.000 (99.571) +2022-11-14 16:58:51,163 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0721) Prec@1 84.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 16:58:51,170 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0738) Prec@1 87.000 (87.444) Prec@5 97.000 (99.222) +2022-11-14 16:58:51,177 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0752) Prec@1 87.000 (87.400) Prec@5 97.000 (99.000) +2022-11-14 16:58:51,185 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0744) Prec@1 91.000 (87.727) Prec@5 100.000 (99.091) +2022-11-14 16:58:51,193 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0747) Prec@1 87.000 (87.667) Prec@5 100.000 (99.167) +2022-11-14 16:58:51,201 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0727) Prec@1 92.000 (88.000) Prec@5 100.000 (99.231) +2022-11-14 16:58:51,209 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0717) Prec@1 91.000 (88.214) Prec@5 100.000 (99.286) +2022-11-14 16:58:51,216 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0723) Prec@1 86.000 (88.067) Prec@5 98.000 (99.200) +2022-11-14 16:58:51,224 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0721) Prec@1 86.000 (87.938) Prec@5 99.000 (99.188) +2022-11-14 16:58:51,232 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0704) Prec@1 94.000 (88.294) Prec@5 98.000 (99.118) +2022-11-14 16:58:51,240 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0721) Prec@1 85.000 (88.111) Prec@5 100.000 (99.167) +2022-11-14 16:58:51,248 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0737) Prec@1 83.000 (87.842) Prec@5 99.000 (99.158) +2022-11-14 16:58:51,256 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0745) Prec@1 85.000 (87.700) Prec@5 98.000 (99.100) +2022-11-14 16:58:51,263 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0747) Prec@1 89.000 (87.762) Prec@5 99.000 (99.095) +2022-11-14 16:58:51,271 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1075 (0.0762) Prec@1 84.000 (87.591) Prec@5 99.000 (99.091) +2022-11-14 16:58:51,278 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0774) Prec@1 83.000 (87.391) Prec@5 97.000 (99.000) +2022-11-14 16:58:51,286 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0774) Prec@1 87.000 (87.375) Prec@5 98.000 (98.958) +2022-11-14 16:58:51,294 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0772) Prec@1 89.000 (87.440) Prec@5 100.000 (99.000) +2022-11-14 16:58:51,301 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0775) Prec@1 88.000 (87.462) Prec@5 98.000 (98.962) +2022-11-14 16:58:51,309 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0770) Prec@1 91.000 (87.593) Prec@5 100.000 (99.000) +2022-11-14 16:58:51,317 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0767) Prec@1 89.000 (87.643) Prec@5 100.000 (99.036) +2022-11-14 16:58:51,324 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0763) Prec@1 90.000 (87.724) Prec@5 98.000 (99.000) +2022-11-14 16:58:51,332 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0763) Prec@1 90.000 (87.800) Prec@5 100.000 (99.033) +2022-11-14 16:58:51,339 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0759) Prec@1 88.000 (87.806) Prec@5 100.000 (99.065) +2022-11-14 16:58:51,347 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0757) Prec@1 91.000 (87.906) Prec@5 99.000 (99.062) +2022-11-14 16:58:51,355 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0757) Prec@1 87.000 (87.879) Prec@5 100.000 (99.091) +2022-11-14 16:58:51,362 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0759) Prec@1 87.000 (87.853) Prec@5 99.000 (99.088) +2022-11-14 16:58:51,370 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0762) Prec@1 86.000 (87.800) Prec@5 98.000 (99.057) +2022-11-14 16:58:51,378 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0760) Prec@1 92.000 (87.917) Prec@5 99.000 (99.056) +2022-11-14 16:58:51,385 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0755) Prec@1 91.000 (88.000) Prec@5 99.000 (99.054) +2022-11-14 16:58:51,393 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0758) Prec@1 87.000 (87.974) Prec@5 99.000 (99.053) +2022-11-14 16:58:51,401 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0751) Prec@1 93.000 (88.103) Prec@5 99.000 (99.051) +2022-11-14 16:58:51,408 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0748) Prec@1 89.000 (88.125) Prec@5 99.000 (99.050) +2022-11-14 16:58:51,416 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0750) Prec@1 86.000 (88.073) Prec@5 99.000 (99.049) +2022-11-14 16:58:51,424 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0752) Prec@1 86.000 (88.024) Prec@5 99.000 (99.048) +2022-11-14 16:58:51,432 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0746) Prec@1 91.000 (88.093) Prec@5 100.000 (99.070) +2022-11-14 16:58:51,439 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0745) Prec@1 90.000 (88.136) Prec@5 98.000 (99.045) +2022-11-14 16:58:51,447 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0742) Prec@1 91.000 (88.200) Prec@5 99.000 (99.044) +2022-11-14 16:58:51,455 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0747) Prec@1 83.000 (88.087) Prec@5 100.000 (99.065) +2022-11-14 16:58:51,462 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0746) Prec@1 89.000 (88.106) Prec@5 100.000 (99.085) +2022-11-14 16:58:51,470 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0751) Prec@1 83.000 (88.000) Prec@5 98.000 (99.062) +2022-11-14 16:58:51,477 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0746) Prec@1 89.000 (88.020) Prec@5 100.000 (99.082) +2022-11-14 16:58:51,485 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0750) Prec@1 85.000 (87.960) Prec@5 100.000 (99.100) +2022-11-14 16:58:51,492 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0749) Prec@1 88.000 (87.961) Prec@5 100.000 (99.118) +2022-11-14 16:58:51,501 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0750) Prec@1 89.000 (87.981) Prec@5 100.000 (99.135) +2022-11-14 16:58:51,509 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0750) Prec@1 88.000 (87.981) Prec@5 100.000 (99.151) +2022-11-14 16:58:51,517 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0749) Prec@1 90.000 (88.019) Prec@5 100.000 (99.167) +2022-11-14 16:58:51,524 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0752) Prec@1 86.000 (87.982) Prec@5 100.000 (99.182) +2022-11-14 16:58:51,532 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0754) Prec@1 87.000 (87.964) Prec@5 99.000 (99.179) +2022-11-14 16:58:51,540 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0751) Prec@1 90.000 (88.000) Prec@5 99.000 (99.175) +2022-11-14 16:58:51,548 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0749) Prec@1 90.000 (88.034) Prec@5 100.000 (99.190) +2022-11-14 16:58:51,555 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0754) Prec@1 82.000 (87.932) Prec@5 100.000 (99.203) +2022-11-14 16:58:51,565 Test: [59/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0752) Prec@1 88.000 (87.933) Prec@5 100.000 (99.217) +2022-11-14 16:58:51,573 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0752) Prec@1 89.000 (87.951) Prec@5 100.000 (99.230) +2022-11-14 16:58:51,581 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0752) Prec@1 89.000 (87.968) Prec@5 98.000 (99.210) +2022-11-14 16:58:51,588 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0749) Prec@1 91.000 (88.016) Prec@5 100.000 (99.222) +2022-11-14 16:58:51,596 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0744) Prec@1 93.000 (88.094) Prec@5 100.000 (99.234) +2022-11-14 16:58:51,605 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0744) Prec@1 87.000 (88.077) Prec@5 99.000 (99.231) +2022-11-14 16:58:51,613 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0746) Prec@1 86.000 (88.045) Prec@5 100.000 (99.242) +2022-11-14 16:58:51,621 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0388 (0.0741) Prec@1 93.000 (88.119) Prec@5 100.000 (99.254) +2022-11-14 16:58:51,630 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0739) Prec@1 90.000 (88.147) Prec@5 100.000 (99.265) +2022-11-14 16:58:51,637 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0740) Prec@1 87.000 (88.130) Prec@5 99.000 (99.261) +2022-11-14 16:58:51,645 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0741) Prec@1 87.000 (88.114) Prec@5 99.000 (99.257) +2022-11-14 16:58:51,653 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0743) Prec@1 87.000 (88.099) Prec@5 99.000 (99.254) +2022-11-14 16:58:51,661 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0519 (0.0740) Prec@1 91.000 (88.139) Prec@5 99.000 (99.250) +2022-11-14 16:58:51,668 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0373 (0.0735) Prec@1 94.000 (88.219) Prec@5 100.000 (99.260) +2022-11-14 16:58:51,676 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0731) Prec@1 92.000 (88.270) Prec@5 100.000 (99.270) +2022-11-14 16:58:51,683 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1278 (0.0738) Prec@1 80.000 (88.160) Prec@5 99.000 (99.267) +2022-11-14 16:58:51,691 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0736) Prec@1 91.000 (88.197) Prec@5 98.000 (99.250) +2022-11-14 16:58:51,698 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0735) Prec@1 92.000 (88.247) Prec@5 99.000 (99.247) +2022-11-14 16:58:51,706 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0739) Prec@1 84.000 (88.192) Prec@5 97.000 (99.218) +2022-11-14 16:58:51,713 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0740) Prec@1 86.000 (88.165) Prec@5 100.000 (99.228) +2022-11-14 16:58:51,721 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0740) Prec@1 85.000 (88.125) Prec@5 100.000 (99.237) +2022-11-14 16:58:51,728 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0742) Prec@1 86.000 (88.099) Prec@5 98.000 (99.222) +2022-11-14 16:58:51,735 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0741) Prec@1 89.000 (88.110) Prec@5 100.000 (99.232) +2022-11-14 16:58:51,743 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0744) Prec@1 86.000 (88.084) Prec@5 99.000 (99.229) +2022-11-14 16:58:51,750 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0744) Prec@1 88.000 (88.083) Prec@5 99.000 (99.226) +2022-11-14 16:58:51,758 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0745) Prec@1 88.000 (88.082) Prec@5 98.000 (99.212) +2022-11-14 16:58:51,765 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0748) Prec@1 86.000 (88.058) Prec@5 100.000 (99.221) +2022-11-14 16:58:51,773 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0745) Prec@1 91.000 (88.092) Prec@5 97.000 (99.195) +2022-11-14 16:58:51,780 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0746) Prec@1 86.000 (88.068) Prec@5 99.000 (99.193) +2022-11-14 16:58:51,788 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0745) Prec@1 91.000 (88.101) Prec@5 100.000 (99.202) +2022-11-14 16:58:51,795 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0746) Prec@1 89.000 (88.111) Prec@5 99.000 (99.200) +2022-11-14 16:58:51,804 Test: [90/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0744) Prec@1 90.000 (88.132) Prec@5 100.000 (99.209) +2022-11-14 16:58:51,813 Test: [91/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0741) Prec@1 93.000 (88.185) Prec@5 99.000 (99.207) +2022-11-14 16:58:51,820 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0741) Prec@1 87.000 (88.172) Prec@5 100.000 (99.215) +2022-11-14 16:58:51,828 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0740) Prec@1 90.000 (88.191) Prec@5 100.000 (99.223) +2022-11-14 16:58:51,835 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0742) Prec@1 84.000 (88.147) Prec@5 100.000 (99.232) +2022-11-14 16:58:51,842 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0742) Prec@1 87.000 (88.135) Prec@5 99.000 (99.229) +2022-11-14 16:58:51,850 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0455 (0.0739) Prec@1 93.000 (88.186) Prec@5 98.000 (99.216) +2022-11-14 16:58:51,857 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0741) Prec@1 85.000 (88.153) Prec@5 98.000 (99.204) +2022-11-14 16:58:51,864 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0742) Prec@1 87.000 (88.141) Prec@5 100.000 (99.212) +2022-11-14 16:58:51,872 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0741) Prec@1 90.000 (88.160) Prec@5 98.000 (99.200) +2022-11-14 16:58:51,927 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:58:52,510 Epoch: [431][0/500] Time 0.025 (0.025) Data 0.234 (0.234) Loss 0.0356 (0.0356) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 16:58:52,710 Epoch: [431][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0230 (0.0293) Prec@1 97.000 (96.500) Prec@5 99.000 (99.500) +2022-11-14 16:58:52,900 Epoch: [431][20/500] Time 0.019 (0.018) Data 0.002 (0.013) Loss 0.0316 (0.0301) Prec@1 94.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:58:53,093 Epoch: [431][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0798 (0.0425) Prec@1 90.000 (94.250) Prec@5 99.000 (99.500) +2022-11-14 16:58:53,286 Epoch: [431][40/500] Time 0.019 (0.017) Data 0.002 (0.007) Loss 0.0172 (0.0374) Prec@1 97.000 (94.800) Prec@5 100.000 (99.600) +2022-11-14 16:58:53,475 Epoch: [431][50/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0343 (0.0369) Prec@1 95.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 16:58:53,669 Epoch: [431][60/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.0364 (0.0368) Prec@1 91.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 16:58:53,857 Epoch: [431][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0382 (0.0370) Prec@1 95.000 (94.375) Prec@5 100.000 (99.750) +2022-11-14 16:58:54,046 Epoch: [431][80/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0414 (0.0375) Prec@1 92.000 (94.111) Prec@5 99.000 (99.667) +2022-11-14 16:58:54,238 Epoch: [431][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0249 (0.0362) Prec@1 96.000 (94.300) Prec@5 100.000 (99.700) +2022-11-14 16:58:54,427 Epoch: [431][100/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0317 (0.0358) Prec@1 94.000 (94.273) Prec@5 100.000 (99.727) +2022-11-14 16:58:54,619 Epoch: [431][110/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0284 (0.0352) Prec@1 94.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 16:58:54,819 Epoch: [431][120/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0318 (0.0349) Prec@1 96.000 (94.385) Prec@5 99.000 (99.692) +2022-11-14 16:58:55,087 Epoch: [431][130/500] Time 0.026 (0.017) Data 0.001 (0.003) Loss 0.0452 (0.0357) Prec@1 91.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 16:58:55,356 Epoch: [431][140/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0186 (0.0345) Prec@1 96.000 (94.267) Prec@5 100.000 (99.733) +2022-11-14 16:58:55,623 Epoch: [431][150/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0209 (0.0337) Prec@1 95.000 (94.312) Prec@5 100.000 (99.750) +2022-11-14 16:58:55,894 Epoch: [431][160/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0254 (0.0332) Prec@1 96.000 (94.412) Prec@5 100.000 (99.765) +2022-11-14 16:58:56,166 Epoch: [431][170/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0296 (0.0330) Prec@1 96.000 (94.500) Prec@5 100.000 (99.778) +2022-11-14 16:58:56,439 Epoch: [431][180/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0204 (0.0323) Prec@1 98.000 (94.684) Prec@5 100.000 (99.789) +2022-11-14 16:58:56,717 Epoch: [431][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0346 (0.0324) Prec@1 96.000 (94.750) Prec@5 100.000 (99.800) +2022-11-14 16:58:56,999 Epoch: [431][200/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0645 (0.0340) Prec@1 91.000 (94.571) Prec@5 99.000 (99.762) +2022-11-14 16:58:57,279 Epoch: [431][210/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0248 (0.0336) Prec@1 97.000 (94.682) Prec@5 100.000 (99.773) +2022-11-14 16:58:57,557 Epoch: [431][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0214 (0.0330) Prec@1 96.000 (94.739) Prec@5 100.000 (99.783) +2022-11-14 16:58:57,837 Epoch: [431][230/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0299 (0.0329) Prec@1 96.000 (94.792) Prec@5 100.000 (99.792) +2022-11-14 16:58:58,118 Epoch: [431][240/500] Time 0.033 (0.021) Data 0.002 (0.003) Loss 0.0249 (0.0326) Prec@1 96.000 (94.840) Prec@5 100.000 (99.800) +2022-11-14 16:58:58,397 Epoch: [431][250/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0409 (0.0329) Prec@1 94.000 (94.808) Prec@5 99.000 (99.769) +2022-11-14 16:58:58,670 Epoch: [431][260/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0287 (0.0327) Prec@1 95.000 (94.815) Prec@5 100.000 (99.778) +2022-11-14 16:58:58,948 Epoch: [431][270/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0337 (0.0328) Prec@1 95.000 (94.821) Prec@5 99.000 (99.750) +2022-11-14 16:58:59,224 Epoch: [431][280/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0311 (0.0327) Prec@1 95.000 (94.828) Prec@5 100.000 (99.759) +2022-11-14 16:58:59,502 Epoch: [431][290/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0371 (0.0329) Prec@1 94.000 (94.800) Prec@5 99.000 (99.733) +2022-11-14 16:58:59,781 Epoch: [431][300/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0397 (0.0331) Prec@1 94.000 (94.774) Prec@5 99.000 (99.710) +2022-11-14 16:59:00,050 Epoch: [431][310/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0351 (0.0332) Prec@1 95.000 (94.781) Prec@5 99.000 (99.688) +2022-11-14 16:59:00,317 Epoch: [431][320/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0518 (0.0337) Prec@1 90.000 (94.636) Prec@5 98.000 (99.636) +2022-11-14 16:59:00,590 Epoch: [431][330/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0237 (0.0334) Prec@1 97.000 (94.706) Prec@5 100.000 (99.647) +2022-11-14 16:59:00,859 Epoch: [431][340/500] Time 0.029 (0.022) Data 0.001 (0.002) Loss 0.0151 (0.0329) Prec@1 98.000 (94.800) Prec@5 100.000 (99.657) +2022-11-14 16:59:01,126 Epoch: [431][350/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0201 (0.0325) Prec@1 96.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 16:59:01,395 Epoch: [431][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0357 (0.0326) Prec@1 94.000 (94.811) Prec@5 99.000 (99.649) +2022-11-14 16:59:01,659 Epoch: [431][370/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0226 (0.0324) Prec@1 96.000 (94.842) Prec@5 100.000 (99.658) +2022-11-14 16:59:01,927 Epoch: [431][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0417 (0.0326) Prec@1 91.000 (94.744) Prec@5 100.000 (99.667) +2022-11-14 16:59:02,197 Epoch: [431][390/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0235 (0.0324) Prec@1 95.000 (94.750) Prec@5 100.000 (99.675) +2022-11-14 16:59:02,469 Epoch: [431][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0318 (0.0324) Prec@1 94.000 (94.732) Prec@5 100.000 (99.683) +2022-11-14 16:59:02,737 Epoch: [431][410/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0204 (0.0321) Prec@1 98.000 (94.810) Prec@5 100.000 (99.690) +2022-11-14 16:59:03,003 Epoch: [431][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0305 (0.0320) Prec@1 95.000 (94.814) Prec@5 100.000 (99.698) +2022-11-14 16:59:03,274 Epoch: [431][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0295 (0.0320) Prec@1 94.000 (94.795) Prec@5 100.000 (99.705) +2022-11-14 16:59:03,540 Epoch: [431][440/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0208 (0.0317) Prec@1 97.000 (94.844) Prec@5 100.000 (99.711) +2022-11-14 16:59:03,803 Epoch: [431][450/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0322 (0.0317) Prec@1 95.000 (94.848) Prec@5 100.000 (99.717) +2022-11-14 16:59:04,073 Epoch: [431][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0288 (0.0317) Prec@1 97.000 (94.894) Prec@5 100.000 (99.723) +2022-11-14 16:59:04,348 Epoch: [431][470/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0252 (0.0315) Prec@1 95.000 (94.896) Prec@5 100.000 (99.729) +2022-11-14 16:59:04,618 Epoch: [431][480/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0277 (0.0315) Prec@1 94.000 (94.878) Prec@5 100.000 (99.735) +2022-11-14 16:59:04,890 Epoch: [431][490/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0218 (0.0313) Prec@1 98.000 (94.940) Prec@5 100.000 (99.740) +2022-11-14 16:59:05,136 Epoch: [431][499/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0281 (0.0312) Prec@1 95.000 (94.941) Prec@5 100.000 (99.745) +2022-11-14 16:59:05,435 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0547 (0.0547) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:05,445 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0661 (0.0604) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 16:59:05,452 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0603 (0.0604) Prec@1 91.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 16:59:05,461 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0663 (0.0619) Prec@1 89.000 (90.250) Prec@5 99.000 (99.750) +2022-11-14 16:59:05,468 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0646) Prec@1 88.000 (89.800) Prec@5 100.000 (99.800) +2022-11-14 16:59:05,475 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0430 (0.0610) Prec@1 93.000 (90.333) Prec@5 100.000 (99.833) +2022-11-14 16:59:05,482 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0411 (0.0581) Prec@1 95.000 (91.000) Prec@5 98.000 (99.571) +2022-11-14 16:59:05,492 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0637) Prec@1 81.000 (89.750) Prec@5 100.000 (99.625) +2022-11-14 16:59:05,499 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0663) Prec@1 85.000 (89.222) Prec@5 99.000 (99.556) +2022-11-14 16:59:05,505 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0662) Prec@1 88.000 (89.100) Prec@5 99.000 (99.500) +2022-11-14 16:59:05,512 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0656) Prec@1 90.000 (89.182) Prec@5 100.000 (99.545) +2022-11-14 16:59:05,521 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0657) Prec@1 87.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 16:59:05,528 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0654) Prec@1 91.000 (89.154) Prec@5 99.000 (99.462) +2022-11-14 16:59:05,536 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0663) Prec@1 89.000 (89.143) Prec@5 99.000 (99.429) +2022-11-14 16:59:05,544 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0664) Prec@1 89.000 (89.133) Prec@5 99.000 (99.400) +2022-11-14 16:59:05,552 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0658) Prec@1 89.000 (89.125) Prec@5 100.000 (99.438) +2022-11-14 16:59:05,559 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0650) Prec@1 92.000 (89.294) Prec@5 98.000 (99.353) +2022-11-14 16:59:05,568 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.0672) Prec@1 84.000 (89.000) Prec@5 100.000 (99.389) +2022-11-14 16:59:05,576 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0686) Prec@1 85.000 (88.789) Prec@5 97.000 (99.263) +2022-11-14 16:59:05,583 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0694) Prec@1 84.000 (88.550) Prec@5 97.000 (99.150) +2022-11-14 16:59:05,591 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0698) Prec@1 87.000 (88.476) Prec@5 98.000 (99.095) +2022-11-14 16:59:05,598 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0702) Prec@1 89.000 (88.500) Prec@5 98.000 (99.045) +2022-11-14 16:59:05,606 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0712) Prec@1 87.000 (88.435) Prec@5 97.000 (98.957) +2022-11-14 16:59:05,614 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0717) Prec@1 88.000 (88.417) Prec@5 99.000 (98.958) +2022-11-14 16:59:05,621 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0725) Prec@1 84.000 (88.240) Prec@5 99.000 (98.960) +2022-11-14 16:59:05,629 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0735) Prec@1 83.000 (88.038) Prec@5 97.000 (98.885) +2022-11-14 16:59:05,637 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0732) Prec@1 89.000 (88.074) Prec@5 100.000 (98.926) +2022-11-14 16:59:05,644 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0727) Prec@1 91.000 (88.179) Prec@5 98.000 (98.893) +2022-11-14 16:59:05,652 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0727) Prec@1 88.000 (88.172) Prec@5 99.000 (98.897) +2022-11-14 16:59:05,660 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0723) Prec@1 91.000 (88.267) Prec@5 99.000 (98.900) +2022-11-14 16:59:05,667 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0718) Prec@1 91.000 (88.355) Prec@5 100.000 (98.935) +2022-11-14 16:59:05,675 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0711) Prec@1 93.000 (88.500) Prec@5 99.000 (98.938) +2022-11-14 16:59:05,683 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0712) Prec@1 88.000 (88.485) Prec@5 100.000 (98.970) +2022-11-14 16:59:05,690 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1104 (0.0724) Prec@1 81.000 (88.265) Prec@5 99.000 (98.971) +2022-11-14 16:59:05,698 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0727) Prec@1 89.000 (88.286) Prec@5 97.000 (98.914) +2022-11-14 16:59:05,705 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0728) Prec@1 88.000 (88.278) Prec@5 99.000 (98.917) +2022-11-14 16:59:05,713 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0728) Prec@1 88.000 (88.270) Prec@5 98.000 (98.892) +2022-11-14 16:59:05,720 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1091 (0.0738) Prec@1 80.000 (88.053) Prec@5 99.000 (98.895) +2022-11-14 16:59:05,728 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0463 (0.0730) Prec@1 94.000 (88.205) Prec@5 99.000 (98.897) +2022-11-14 16:59:05,735 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0726) Prec@1 91.000 (88.275) Prec@5 99.000 (98.900) +2022-11-14 16:59:05,743 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0727) Prec@1 88.000 (88.268) Prec@5 98.000 (98.878) +2022-11-14 16:59:05,751 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0725) Prec@1 90.000 (88.310) Prec@5 99.000 (98.881) +2022-11-14 16:59:05,758 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0719) Prec@1 93.000 (88.419) Prec@5 99.000 (98.884) +2022-11-14 16:59:05,766 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0718) Prec@1 90.000 (88.455) Prec@5 99.000 (98.886) +2022-11-14 16:59:05,773 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0716) Prec@1 88.000 (88.444) Prec@5 100.000 (98.911) +2022-11-14 16:59:05,781 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1245 (0.0727) Prec@1 81.000 (88.283) Prec@5 99.000 (98.913) +2022-11-14 16:59:05,788 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0728) Prec@1 86.000 (88.234) Prec@5 99.000 (98.915) +2022-11-14 16:59:05,796 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0735) Prec@1 80.000 (88.062) Prec@5 98.000 (98.896) +2022-11-14 16:59:05,804 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0731) Prec@1 89.000 (88.082) Prec@5 100.000 (98.918) +2022-11-14 16:59:05,811 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0739) Prec@1 86.000 (88.040) Prec@5 100.000 (98.940) +2022-11-14 16:59:05,819 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0738) Prec@1 89.000 (88.059) Prec@5 100.000 (98.961) +2022-11-14 16:59:05,827 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0737) Prec@1 87.000 (88.038) Prec@5 100.000 (98.981) +2022-11-14 16:59:05,835 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0352 (0.0730) Prec@1 95.000 (88.170) Prec@5 99.000 (98.981) +2022-11-14 16:59:05,843 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0729) Prec@1 88.000 (88.167) Prec@5 100.000 (99.000) +2022-11-14 16:59:05,851 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0731) Prec@1 86.000 (88.127) Prec@5 100.000 (99.018) +2022-11-14 16:59:05,858 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0733) Prec@1 88.000 (88.125) Prec@5 100.000 (99.036) +2022-11-14 16:59:05,866 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0735) Prec@1 86.000 (88.088) Prec@5 100.000 (99.053) +2022-11-14 16:59:05,874 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0737) Prec@1 89.000 (88.103) Prec@5 100.000 (99.069) +2022-11-14 16:59:05,881 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0742) Prec@1 82.000 (88.000) Prec@5 100.000 (99.085) +2022-11-14 16:59:05,889 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 88.000 (88.000) Prec@5 100.000 (99.100) +2022-11-14 16:59:05,896 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0744) Prec@1 89.000 (88.016) Prec@5 100.000 (99.115) +2022-11-14 16:59:05,904 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0742) Prec@1 89.000 (88.032) Prec@5 99.000 (99.113) +2022-11-14 16:59:05,912 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0742) Prec@1 88.000 (88.032) Prec@5 100.000 (99.127) +2022-11-14 16:59:05,919 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0246 (0.0735) Prec@1 97.000 (88.172) Prec@5 100.000 (99.141) +2022-11-14 16:59:05,927 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0735) Prec@1 87.000 (88.154) Prec@5 100.000 (99.154) +2022-11-14 16:59:05,935 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0737) Prec@1 85.000 (88.106) Prec@5 99.000 (99.152) +2022-11-14 16:59:05,942 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0733) Prec@1 95.000 (88.209) Prec@5 100.000 (99.164) +2022-11-14 16:59:05,950 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0733) Prec@1 88.000 (88.206) Prec@5 100.000 (99.176) +2022-11-14 16:59:05,957 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0733) Prec@1 87.000 (88.188) Prec@5 100.000 (99.188) +2022-11-14 16:59:05,965 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0735) Prec@1 89.000 (88.200) Prec@5 98.000 (99.171) +2022-11-14 16:59:05,973 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0739) Prec@1 87.000 (88.183) Prec@5 97.000 (99.141) +2022-11-14 16:59:05,980 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0738) Prec@1 91.000 (88.222) Prec@5 100.000 (99.153) +2022-11-14 16:59:05,988 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0733) Prec@1 94.000 (88.301) Prec@5 99.000 (99.151) +2022-11-14 16:59:05,996 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0392 (0.0729) Prec@1 96.000 (88.405) Prec@5 100.000 (99.162) +2022-11-14 16:59:06,004 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1107 (0.0734) Prec@1 82.000 (88.320) Prec@5 99.000 (99.160) +2022-11-14 16:59:06,012 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0732) Prec@1 90.000 (88.342) Prec@5 99.000 (99.158) +2022-11-14 16:59:06,019 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0731) Prec@1 91.000 (88.377) Prec@5 98.000 (99.143) +2022-11-14 16:59:06,027 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0733) Prec@1 87.000 (88.359) Prec@5 97.000 (99.115) +2022-11-14 16:59:06,034 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0734) Prec@1 89.000 (88.367) Prec@5 100.000 (99.127) +2022-11-14 16:59:06,043 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0735) Prec@1 85.000 (88.325) Prec@5 99.000 (99.125) +2022-11-14 16:59:06,051 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0736) Prec@1 88.000 (88.321) Prec@5 100.000 (99.136) +2022-11-14 16:59:06,059 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0735) Prec@1 88.000 (88.317) Prec@5 100.000 (99.146) +2022-11-14 16:59:06,066 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0736) Prec@1 88.000 (88.313) Prec@5 99.000 (99.145) +2022-11-14 16:59:06,074 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0735) Prec@1 88.000 (88.310) Prec@5 99.000 (99.143) +2022-11-14 16:59:06,083 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0738) Prec@1 85.000 (88.271) Prec@5 100.000 (99.153) +2022-11-14 16:59:06,091 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0740) Prec@1 85.000 (88.233) Prec@5 99.000 (99.151) +2022-11-14 16:59:06,099 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0741) Prec@1 84.000 (88.184) Prec@5 99.000 (99.149) +2022-11-14 16:59:06,107 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0741) Prec@1 88.000 (88.182) Prec@5 99.000 (99.148) +2022-11-14 16:59:06,114 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0740) Prec@1 87.000 (88.169) Prec@5 100.000 (99.157) +2022-11-14 16:59:06,122 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0738) Prec@1 94.000 (88.233) Prec@5 100.000 (99.167) +2022-11-14 16:59:06,130 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0736) Prec@1 90.000 (88.253) Prec@5 100.000 (99.176) +2022-11-14 16:59:06,137 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0735) Prec@1 90.000 (88.272) Prec@5 98.000 (99.163) +2022-11-14 16:59:06,145 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0736) Prec@1 87.000 (88.258) Prec@5 99.000 (99.161) +2022-11-14 16:59:06,153 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0735) Prec@1 90.000 (88.277) Prec@5 99.000 (99.160) +2022-11-14 16:59:06,160 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0734) Prec@1 88.000 (88.274) Prec@5 98.000 (99.147) +2022-11-14 16:59:06,168 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0733) Prec@1 92.000 (88.312) Prec@5 100.000 (99.156) +2022-11-14 16:59:06,175 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0731) Prec@1 92.000 (88.351) Prec@5 98.000 (99.144) +2022-11-14 16:59:06,183 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0732) Prec@1 84.000 (88.306) Prec@5 98.000 (99.133) +2022-11-14 16:59:06,190 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0734) Prec@1 84.000 (88.263) Prec@5 100.000 (99.141) +2022-11-14 16:59:06,198 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0733) Prec@1 88.000 (88.260) Prec@5 100.000 (99.150) +2022-11-14 16:59:06,271 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:59:06,794 Epoch: [432][0/500] Time 0.023 (0.023) Data 0.243 (0.243) Loss 0.0147 (0.0147) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:07,002 Epoch: [432][10/500] Time 0.016 (0.019) Data 0.002 (0.024) Loss 0.0154 (0.0150) Prec@1 97.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 16:59:07,208 Epoch: [432][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0423 (0.0241) Prec@1 93.000 (96.000) Prec@5 99.000 (99.667) +2022-11-14 16:59:07,407 Epoch: [432][30/500] Time 0.017 (0.018) Data 0.002 (0.010) Loss 0.0378 (0.0275) Prec@1 93.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 16:59:07,599 Epoch: [432][40/500] Time 0.018 (0.018) Data 0.002 (0.008) Loss 0.0150 (0.0250) Prec@1 98.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 16:59:07,791 Epoch: [432][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0160 (0.0235) Prec@1 97.000 (96.000) Prec@5 100.000 (99.833) +2022-11-14 16:59:07,983 Epoch: [432][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0351 (0.0252) Prec@1 93.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 16:59:08,176 Epoch: [432][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0251 (0.0252) Prec@1 97.000 (95.750) Prec@5 100.000 (99.875) +2022-11-14 16:59:08,371 Epoch: [432][80/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0249 (0.0251) Prec@1 96.000 (95.778) Prec@5 100.000 (99.889) +2022-11-14 16:59:08,562 Epoch: [432][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0423 (0.0269) Prec@1 92.000 (95.400) Prec@5 100.000 (99.900) +2022-11-14 16:59:08,753 Epoch: [432][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0391 (0.0280) Prec@1 95.000 (95.364) Prec@5 98.000 (99.727) +2022-11-14 16:59:08,947 Epoch: [432][110/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0331 (0.0284) Prec@1 95.000 (95.333) Prec@5 100.000 (99.750) +2022-11-14 16:59:09,143 Epoch: [432][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0243 (0.0281) Prec@1 96.000 (95.385) Prec@5 99.000 (99.692) +2022-11-14 16:59:09,337 Epoch: [432][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0182 (0.0274) Prec@1 99.000 (95.643) Prec@5 100.000 (99.714) +2022-11-14 16:59:09,535 Epoch: [432][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0123 (0.0264) Prec@1 98.000 (95.800) Prec@5 100.000 (99.733) +2022-11-14 16:59:09,730 Epoch: [432][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0327 (0.0268) Prec@1 93.000 (95.625) Prec@5 100.000 (99.750) +2022-11-14 16:59:09,924 Epoch: [432][160/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.0408 (0.0276) Prec@1 93.000 (95.471) Prec@5 100.000 (99.765) +2022-11-14 16:59:10,122 Epoch: [432][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0231 (0.0273) Prec@1 97.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 16:59:10,318 Epoch: [432][180/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0428 (0.0282) Prec@1 92.000 (95.368) Prec@5 100.000 (99.789) +2022-11-14 16:59:10,565 Epoch: [432][190/500] Time 0.025 (0.017) Data 0.002 (0.003) Loss 0.0169 (0.0276) Prec@1 97.000 (95.450) Prec@5 100.000 (99.800) +2022-11-14 16:59:10,838 Epoch: [432][200/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0244 (0.0274) Prec@1 96.000 (95.476) Prec@5 100.000 (99.810) +2022-11-14 16:59:11,110 Epoch: [432][210/500] Time 0.029 (0.018) Data 0.002 (0.003) Loss 0.0330 (0.0277) Prec@1 95.000 (95.455) Prec@5 99.000 (99.773) +2022-11-14 16:59:11,381 Epoch: [432][220/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0313 (0.0278) Prec@1 94.000 (95.391) Prec@5 100.000 (99.783) +2022-11-14 16:59:11,656 Epoch: [432][230/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0112 (0.0272) Prec@1 99.000 (95.542) Prec@5 100.000 (99.792) +2022-11-14 16:59:11,932 Epoch: [432][240/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0129 (0.0266) Prec@1 98.000 (95.640) Prec@5 100.000 (99.800) +2022-11-14 16:59:12,215 Epoch: [432][250/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0520 (0.0276) Prec@1 93.000 (95.538) Prec@5 100.000 (99.808) +2022-11-14 16:59:12,492 Epoch: [432][260/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0213 (0.0273) Prec@1 97.000 (95.593) Prec@5 100.000 (99.815) +2022-11-14 16:59:12,774 Epoch: [432][270/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0198 (0.0271) Prec@1 97.000 (95.643) Prec@5 100.000 (99.821) +2022-11-14 16:59:13,056 Epoch: [432][280/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0339 (0.0273) Prec@1 93.000 (95.552) Prec@5 100.000 (99.828) +2022-11-14 16:59:13,335 Epoch: [432][290/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0287 (0.0273) Prec@1 95.000 (95.533) Prec@5 100.000 (99.833) +2022-11-14 16:59:13,610 Epoch: [432][300/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0416 (0.0278) Prec@1 92.000 (95.419) Prec@5 100.000 (99.839) +2022-11-14 16:59:13,879 Epoch: [432][310/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0294 (0.0279) Prec@1 95.000 (95.406) Prec@5 100.000 (99.844) +2022-11-14 16:59:14,151 Epoch: [432][320/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0281 (0.0279) Prec@1 94.000 (95.364) Prec@5 100.000 (99.848) +2022-11-14 16:59:14,422 Epoch: [432][330/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0430 (0.0283) Prec@1 94.000 (95.324) Prec@5 100.000 (99.853) +2022-11-14 16:59:14,695 Epoch: [432][340/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0304 (0.0284) Prec@1 95.000 (95.314) Prec@5 99.000 (99.829) +2022-11-14 16:59:14,970 Epoch: [432][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0335 (0.0285) Prec@1 94.000 (95.278) Prec@5 100.000 (99.833) +2022-11-14 16:59:15,246 Epoch: [432][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0354 (0.0287) Prec@1 95.000 (95.270) Prec@5 100.000 (99.838) +2022-11-14 16:59:15,521 Epoch: [432][370/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0129 (0.0283) Prec@1 98.000 (95.342) Prec@5 100.000 (99.842) +2022-11-14 16:59:15,796 Epoch: [432][380/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0322 (0.0284) Prec@1 97.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 16:59:16,078 Epoch: [432][390/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0252 (0.0283) Prec@1 98.000 (95.450) Prec@5 100.000 (99.850) +2022-11-14 16:59:16,354 Epoch: [432][400/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0233 (0.0282) Prec@1 97.000 (95.488) Prec@5 100.000 (99.854) +2022-11-14 16:59:16,627 Epoch: [432][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0168 (0.0279) Prec@1 98.000 (95.548) Prec@5 100.000 (99.857) +2022-11-14 16:59:16,894 Epoch: [432][420/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0495 (0.0284) Prec@1 92.000 (95.465) Prec@5 100.000 (99.860) +2022-11-14 16:59:17,168 Epoch: [432][430/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0284) Prec@1 96.000 (95.477) Prec@5 100.000 (99.864) +2022-11-14 16:59:17,443 Epoch: [432][440/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0312 (0.0285) Prec@1 92.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:59:17,717 Epoch: [432][450/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0396 (0.0287) Prec@1 94.000 (95.370) Prec@5 100.000 (99.870) +2022-11-14 16:59:17,990 Epoch: [432][460/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0642 (0.0295) Prec@1 89.000 (95.234) Prec@5 100.000 (99.872) +2022-11-14 16:59:18,265 Epoch: [432][470/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0207 (0.0293) Prec@1 97.000 (95.271) Prec@5 100.000 (99.875) +2022-11-14 16:59:18,540 Epoch: [432][480/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0195 (0.0291) Prec@1 97.000 (95.306) Prec@5 100.000 (99.878) +2022-11-14 16:59:18,816 Epoch: [432][490/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0303 (0.0291) Prec@1 94.000 (95.280) Prec@5 100.000 (99.880) +2022-11-14 16:59:19,065 Epoch: [432][499/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0268 (0.0291) Prec@1 95.000 (95.275) Prec@5 100.000 (99.882) +2022-11-14 16:59:19,375 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0697 (0.0697) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:19,384 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0629 (0.0663) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:19,391 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0686) Prec@1 86.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 16:59:19,400 Test: [3/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0720) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 16:59:19,407 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0695) Prec@1 91.000 (89.000) Prec@5 100.000 (99.600) +2022-11-14 16:59:19,413 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0381 (0.0643) Prec@1 95.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 16:59:19,421 Test: [6/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0626) Prec@1 92.000 (90.286) Prec@5 100.000 (99.571) +2022-11-14 16:59:19,429 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0675) Prec@1 82.000 (89.250) Prec@5 100.000 (99.625) +2022-11-14 16:59:19,436 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0698) Prec@1 86.000 (88.889) Prec@5 99.000 (99.556) +2022-11-14 16:59:19,444 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0707) Prec@1 88.000 (88.800) Prec@5 99.000 (99.500) +2022-11-14 16:59:19,452 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0714) Prec@1 87.000 (88.636) Prec@5 100.000 (99.545) +2022-11-14 16:59:19,460 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1115 (0.0747) Prec@1 84.000 (88.250) Prec@5 100.000 (99.583) +2022-11-14 16:59:19,468 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0373 (0.0718) Prec@1 96.000 (88.846) Prec@5 100.000 (99.615) +2022-11-14 16:59:19,475 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0727) Prec@1 87.000 (88.714) Prec@5 100.000 (99.643) +2022-11-14 16:59:19,483 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0734) Prec@1 87.000 (88.600) Prec@5 100.000 (99.667) +2022-11-14 16:59:19,490 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0734) Prec@1 88.000 (88.562) Prec@5 100.000 (99.688) +2022-11-14 16:59:19,498 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0725) Prec@1 92.000 (88.765) Prec@5 97.000 (99.529) +2022-11-14 16:59:19,506 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1151 (0.0749) Prec@1 82.000 (88.389) Prec@5 100.000 (99.556) +2022-11-14 16:59:19,513 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0757) Prec@1 88.000 (88.368) Prec@5 100.000 (99.579) +2022-11-14 16:59:19,521 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0758) Prec@1 88.000 (88.350) Prec@5 98.000 (99.500) +2022-11-14 16:59:19,529 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0760) Prec@1 86.000 (88.238) Prec@5 100.000 (99.524) +2022-11-14 16:59:19,537 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0765) Prec@1 88.000 (88.227) Prec@5 98.000 (99.455) +2022-11-14 16:59:19,544 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0777) Prec@1 85.000 (88.087) Prec@5 99.000 (99.435) +2022-11-14 16:59:19,552 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0777) Prec@1 89.000 (88.125) Prec@5 99.000 (99.417) +2022-11-14 16:59:19,560 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0771) Prec@1 89.000 (88.160) Prec@5 100.000 (99.440) +2022-11-14 16:59:19,568 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0773) Prec@1 87.000 (88.115) Prec@5 99.000 (99.423) +2022-11-14 16:59:19,575 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0763) Prec@1 94.000 (88.333) Prec@5 100.000 (99.444) +2022-11-14 16:59:19,583 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0758) Prec@1 90.000 (88.393) Prec@5 100.000 (99.464) +2022-11-14 16:59:19,591 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0753) Prec@1 90.000 (88.448) Prec@5 99.000 (99.448) +2022-11-14 16:59:19,599 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0750) Prec@1 88.000 (88.433) Prec@5 99.000 (99.433) +2022-11-14 16:59:19,606 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0751) Prec@1 86.000 (88.355) Prec@5 100.000 (99.452) +2022-11-14 16:59:19,614 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0749) Prec@1 89.000 (88.375) Prec@5 100.000 (99.469) +2022-11-14 16:59:19,621 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0750) Prec@1 86.000 (88.303) Prec@5 100.000 (99.485) +2022-11-14 16:59:19,629 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0753) Prec@1 84.000 (88.176) Prec@5 100.000 (99.500) +2022-11-14 16:59:19,637 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0756) Prec@1 87.000 (88.143) Prec@5 99.000 (99.486) +2022-11-14 16:59:19,644 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0759) Prec@1 88.000 (88.139) Prec@5 98.000 (99.444) +2022-11-14 16:59:19,652 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0757) Prec@1 91.000 (88.216) Prec@5 99.000 (99.432) +2022-11-14 16:59:19,660 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0765) Prec@1 82.000 (88.053) Prec@5 100.000 (99.447) +2022-11-14 16:59:19,668 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0760) Prec@1 92.000 (88.154) Prec@5 100.000 (99.462) +2022-11-14 16:59:19,676 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0761) Prec@1 87.000 (88.125) Prec@5 99.000 (99.450) +2022-11-14 16:59:19,684 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0767) Prec@1 84.000 (88.024) Prec@5 100.000 (99.463) +2022-11-14 16:59:19,692 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0763) Prec@1 91.000 (88.095) Prec@5 100.000 (99.476) +2022-11-14 16:59:19,699 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0409 (0.0755) Prec@1 94.000 (88.233) Prec@5 99.000 (99.465) +2022-11-14 16:59:19,707 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0753) Prec@1 89.000 (88.250) Prec@5 98.000 (99.432) +2022-11-14 16:59:19,715 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0750) Prec@1 89.000 (88.267) Prec@5 100.000 (99.444) +2022-11-14 16:59:19,724 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1163 (0.0759) Prec@1 83.000 (88.152) Prec@5 99.000 (99.435) +2022-11-14 16:59:19,733 Test: [46/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0760) Prec@1 87.000 (88.128) Prec@5 100.000 (99.447) +2022-11-14 16:59:19,741 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0765) Prec@1 85.000 (88.062) Prec@5 98.000 (99.417) +2022-11-14 16:59:19,749 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0761) Prec@1 91.000 (88.122) Prec@5 100.000 (99.429) +2022-11-14 16:59:19,757 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0763) Prec@1 88.000 (88.120) Prec@5 100.000 (99.440) +2022-11-14 16:59:19,765 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0762) Prec@1 87.000 (88.098) Prec@5 99.000 (99.431) +2022-11-14 16:59:19,773 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0763) Prec@1 87.000 (88.077) Prec@5 99.000 (99.423) +2022-11-14 16:59:19,781 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0761) Prec@1 89.000 (88.094) Prec@5 100.000 (99.434) +2022-11-14 16:59:19,790 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0760) Prec@1 88.000 (88.093) Prec@5 98.000 (99.407) +2022-11-14 16:59:19,799 Test: [54/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0763) Prec@1 87.000 (88.073) Prec@5 100.000 (99.418) +2022-11-14 16:59:19,807 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0763) Prec@1 90.000 (88.107) Prec@5 99.000 (99.411) +2022-11-14 16:59:19,815 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0761) Prec@1 87.000 (88.088) Prec@5 100.000 (99.421) +2022-11-14 16:59:19,823 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0761) Prec@1 89.000 (88.103) Prec@5 99.000 (99.414) +2022-11-14 16:59:19,831 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0766) Prec@1 82.000 (88.000) Prec@5 100.000 (99.424) +2022-11-14 16:59:19,838 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0766) Prec@1 84.000 (87.933) Prec@5 100.000 (99.433) +2022-11-14 16:59:19,846 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0765) Prec@1 88.000 (87.934) Prec@5 99.000 (99.426) +2022-11-14 16:59:19,854 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0763) Prec@1 90.000 (87.968) Prec@5 100.000 (99.435) +2022-11-14 16:59:19,862 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0761) Prec@1 90.000 (88.000) Prec@5 100.000 (99.444) +2022-11-14 16:59:19,869 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0349 (0.0755) Prec@1 94.000 (88.094) Prec@5 100.000 (99.453) +2022-11-14 16:59:19,877 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0757) Prec@1 87.000 (88.077) Prec@5 100.000 (99.462) +2022-11-14 16:59:19,885 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0759) Prec@1 88.000 (88.076) Prec@5 98.000 (99.439) +2022-11-14 16:59:19,893 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0274 (0.0751) Prec@1 95.000 (88.179) Prec@5 100.000 (99.448) +2022-11-14 16:59:19,900 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0749) Prec@1 91.000 (88.221) Prec@5 98.000 (99.426) +2022-11-14 16:59:19,908 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0746) Prec@1 89.000 (88.232) Prec@5 99.000 (99.420) +2022-11-14 16:59:19,916 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0747) Prec@1 89.000 (88.243) Prec@5 99.000 (99.414) +2022-11-14 16:59:19,924 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0749) Prec@1 87.000 (88.225) Prec@5 99.000 (99.408) +2022-11-14 16:59:19,931 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0748) Prec@1 88.000 (88.222) Prec@5 100.000 (99.417) +2022-11-14 16:59:19,939 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0329 (0.0742) Prec@1 97.000 (88.342) Prec@5 99.000 (99.411) +2022-11-14 16:59:19,947 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0440 (0.0738) Prec@1 95.000 (88.432) Prec@5 99.000 (99.405) +2022-11-14 16:59:19,955 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0741) Prec@1 84.000 (88.373) Prec@5 100.000 (99.413) +2022-11-14 16:59:19,962 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0739) Prec@1 90.000 (88.395) Prec@5 98.000 (99.395) +2022-11-14 16:59:19,970 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0738) Prec@1 89.000 (88.403) Prec@5 98.000 (99.377) +2022-11-14 16:59:19,977 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0741) Prec@1 84.000 (88.346) Prec@5 100.000 (99.385) +2022-11-14 16:59:19,985 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0741) Prec@1 91.000 (88.380) Prec@5 99.000 (99.380) +2022-11-14 16:59:19,993 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0741) Prec@1 87.000 (88.362) Prec@5 100.000 (99.388) +2022-11-14 16:59:20,001 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0742) Prec@1 88.000 (88.358) Prec@5 98.000 (99.370) +2022-11-14 16:59:20,008 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0742) Prec@1 89.000 (88.366) Prec@5 100.000 (99.378) +2022-11-14 16:59:20,016 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0745) Prec@1 85.000 (88.325) Prec@5 98.000 (99.361) +2022-11-14 16:59:20,024 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0745) Prec@1 89.000 (88.333) Prec@5 99.000 (99.357) +2022-11-14 16:59:20,032 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0747) Prec@1 86.000 (88.306) Prec@5 99.000 (99.353) +2022-11-14 16:59:20,040 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0750) Prec@1 85.000 (88.267) Prec@5 100.000 (99.360) +2022-11-14 16:59:20,047 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0749) Prec@1 90.000 (88.287) Prec@5 99.000 (99.356) +2022-11-14 16:59:20,055 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0751) Prec@1 86.000 (88.261) Prec@5 98.000 (99.341) +2022-11-14 16:59:20,063 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0748) Prec@1 93.000 (88.315) Prec@5 100.000 (99.348) +2022-11-14 16:59:20,070 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0747) Prec@1 91.000 (88.344) Prec@5 100.000 (99.356) +2022-11-14 16:59:20,079 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0745) Prec@1 90.000 (88.363) Prec@5 100.000 (99.363) +2022-11-14 16:59:20,087 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0742) Prec@1 93.000 (88.413) Prec@5 100.000 (99.370) +2022-11-14 16:59:20,095 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0744) Prec@1 86.000 (88.387) Prec@5 99.000 (99.366) +2022-11-14 16:59:20,102 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0743) Prec@1 90.000 (88.404) Prec@5 98.000 (99.351) +2022-11-14 16:59:20,110 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0743) Prec@1 88.000 (88.400) Prec@5 99.000 (99.347) +2022-11-14 16:59:20,118 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0742) Prec@1 91.000 (88.427) Prec@5 99.000 (99.344) +2022-11-14 16:59:20,125 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0457 (0.0739) Prec@1 93.000 (88.474) Prec@5 98.000 (99.330) +2022-11-14 16:59:20,133 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0740) Prec@1 86.000 (88.449) Prec@5 99.000 (99.327) +2022-11-14 16:59:20,140 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0740) Prec@1 87.000 (88.434) Prec@5 100.000 (99.333) +2022-11-14 16:59:20,148 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0740) Prec@1 87.000 (88.420) Prec@5 100.000 (99.340) +2022-11-14 16:59:20,215 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:59:20,867 Epoch: [433][0/500] Time 0.026 (0.026) Data 0.293 (0.293) Loss 0.0326 (0.0326) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 16:59:21,059 Epoch: [433][10/500] Time 0.017 (0.018) Data 0.002 (0.028) Loss 0.0203 (0.0265) Prec@1 96.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:59:21,252 Epoch: [433][20/500] Time 0.017 (0.017) Data 0.002 (0.015) Loss 0.0226 (0.0252) Prec@1 97.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 16:59:21,443 Epoch: [433][30/500] Time 0.017 (0.017) Data 0.001 (0.011) Loss 0.0235 (0.0248) Prec@1 97.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 16:59:21,633 Epoch: [433][40/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0442 (0.0286) Prec@1 92.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 16:59:21,826 Epoch: [433][50/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0286 (0.0286) Prec@1 95.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 16:59:22,012 Epoch: [433][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0255 (0.0282) Prec@1 95.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 16:59:22,201 Epoch: [433][70/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0515 (0.0311) Prec@1 94.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 16:59:22,388 Epoch: [433][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0291 (0.0309) Prec@1 96.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 16:59:22,577 Epoch: [433][90/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0491 (0.0327) Prec@1 93.000 (94.900) Prec@5 99.000 (99.800) +2022-11-14 16:59:22,765 Epoch: [433][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0454 (0.0339) Prec@1 94.000 (94.818) Prec@5 100.000 (99.818) +2022-11-14 16:59:22,951 Epoch: [433][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0315 (0.0337) Prec@1 96.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 16:59:23,142 Epoch: [433][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0119 (0.0320) Prec@1 98.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 16:59:23,329 Epoch: [433][130/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0129 (0.0306) Prec@1 97.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:59:23,536 Epoch: [433][140/500] Time 0.023 (0.017) Data 0.001 (0.004) Loss 0.0098 (0.0292) Prec@1 98.000 (95.467) Prec@5 100.000 (99.867) +2022-11-14 16:59:23,788 Epoch: [433][150/500] Time 0.024 (0.017) Data 0.001 (0.004) Loss 0.0510 (0.0306) Prec@1 92.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 16:59:24,043 Epoch: [433][160/500] Time 0.025 (0.017) Data 0.001 (0.003) Loss 0.0198 (0.0300) Prec@1 97.000 (95.353) Prec@5 99.000 (99.824) +2022-11-14 16:59:24,301 Epoch: [433][170/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0369 (0.0303) Prec@1 95.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 16:59:24,559 Epoch: [433][180/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0191 (0.0298) Prec@1 98.000 (95.474) Prec@5 100.000 (99.842) +2022-11-14 16:59:24,811 Epoch: [433][190/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0393 (0.0302) Prec@1 93.000 (95.350) Prec@5 100.000 (99.850) +2022-11-14 16:59:25,063 Epoch: [433][200/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0348 (0.0305) Prec@1 94.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 16:59:25,317 Epoch: [433][210/500] Time 0.023 (0.019) Data 0.001 (0.003) Loss 0.0111 (0.0296) Prec@1 99.000 (95.455) Prec@5 100.000 (99.864) +2022-11-14 16:59:25,567 Epoch: [433][220/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0316 (0.0297) Prec@1 93.000 (95.348) Prec@5 100.000 (99.870) +2022-11-14 16:59:25,816 Epoch: [433][230/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0180 (0.0292) Prec@1 98.000 (95.458) Prec@5 100.000 (99.875) +2022-11-14 16:59:26,066 Epoch: [433][240/500] Time 0.023 (0.019) Data 0.001 (0.003) Loss 0.0253 (0.0290) Prec@1 96.000 (95.480) Prec@5 100.000 (99.880) +2022-11-14 16:59:26,311 Epoch: [433][250/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0244 (0.0288) Prec@1 98.000 (95.577) Prec@5 100.000 (99.885) +2022-11-14 16:59:26,557 Epoch: [433][260/500] Time 0.022 (0.019) Data 0.001 (0.003) Loss 0.0505 (0.0296) Prec@1 92.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 16:59:26,805 Epoch: [433][270/500] Time 0.023 (0.019) Data 0.001 (0.003) Loss 0.0236 (0.0294) Prec@1 97.000 (95.500) Prec@5 99.000 (99.857) +2022-11-14 16:59:27,050 Epoch: [433][280/500] Time 0.023 (0.019) Data 0.001 (0.003) Loss 0.0383 (0.0297) Prec@1 93.000 (95.414) Prec@5 100.000 (99.862) +2022-11-14 16:59:27,301 Epoch: [433][290/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0332 (0.0299) Prec@1 95.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 16:59:27,549 Epoch: [433][300/500] Time 0.023 (0.020) Data 0.001 (0.003) Loss 0.0389 (0.0301) Prec@1 93.000 (95.323) Prec@5 100.000 (99.871) +2022-11-14 16:59:27,799 Epoch: [433][310/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0235 (0.0299) Prec@1 96.000 (95.344) Prec@5 100.000 (99.875) +2022-11-14 16:59:28,047 Epoch: [433][320/500] Time 0.023 (0.020) Data 0.001 (0.003) Loss 0.0226 (0.0297) Prec@1 95.000 (95.333) Prec@5 100.000 (99.879) +2022-11-14 16:59:28,296 Epoch: [433][330/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0364 (0.0299) Prec@1 93.000 (95.265) Prec@5 100.000 (99.882) +2022-11-14 16:59:28,545 Epoch: [433][340/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0439 (0.0303) Prec@1 93.000 (95.200) Prec@5 100.000 (99.886) +2022-11-14 16:59:28,789 Epoch: [433][350/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0491 (0.0308) Prec@1 90.000 (95.056) Prec@5 100.000 (99.889) +2022-11-14 16:59:29,037 Epoch: [433][360/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0301 (0.0308) Prec@1 95.000 (95.054) Prec@5 100.000 (99.892) +2022-11-14 16:59:29,287 Epoch: [433][370/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0193 (0.0305) Prec@1 96.000 (95.079) Prec@5 100.000 (99.895) +2022-11-14 16:59:29,534 Epoch: [433][380/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0334 (0.0306) Prec@1 95.000 (95.077) Prec@5 100.000 (99.897) +2022-11-14 16:59:29,786 Epoch: [433][390/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0275 (0.0305) Prec@1 95.000 (95.075) Prec@5 100.000 (99.900) +2022-11-14 16:59:30,033 Epoch: [433][400/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0216 (0.0303) Prec@1 96.000 (95.098) Prec@5 100.000 (99.902) +2022-11-14 16:59:30,282 Epoch: [433][410/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0359 (0.0304) Prec@1 93.000 (95.048) Prec@5 100.000 (99.905) +2022-11-14 16:59:30,531 Epoch: [433][420/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0483 (0.0308) Prec@1 91.000 (94.953) Prec@5 100.000 (99.907) +2022-11-14 16:59:30,779 Epoch: [433][430/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0171 (0.0305) Prec@1 97.000 (95.000) Prec@5 100.000 (99.909) +2022-11-14 16:59:31,026 Epoch: [433][440/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0347 (0.0306) Prec@1 94.000 (94.978) Prec@5 100.000 (99.911) +2022-11-14 16:59:31,275 Epoch: [433][450/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0226 (0.0304) Prec@1 95.000 (94.978) Prec@5 100.000 (99.913) +2022-11-14 16:59:31,523 Epoch: [433][460/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0101 (0.0300) Prec@1 99.000 (95.064) Prec@5 100.000 (99.915) +2022-11-14 16:59:31,771 Epoch: [433][470/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0382 (0.0302) Prec@1 95.000 (95.062) Prec@5 100.000 (99.917) +2022-11-14 16:59:32,017 Epoch: [433][480/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0169 (0.0299) Prec@1 98.000 (95.122) Prec@5 100.000 (99.918) +2022-11-14 16:59:32,266 Epoch: [433][490/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0392 (0.0301) Prec@1 94.000 (95.100) Prec@5 100.000 (99.920) +2022-11-14 16:59:32,489 Epoch: [433][499/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0196 (0.0299) Prec@1 97.000 (95.137) Prec@5 100.000 (99.922) +2022-11-14 16:59:32,798 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0610 (0.0610) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:32,805 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0639) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:32,813 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0637) Prec@1 91.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 16:59:32,822 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0660) Prec@1 89.000 (90.000) Prec@5 99.000 (99.750) +2022-11-14 16:59:32,829 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0656) Prec@1 91.000 (90.200) Prec@5 99.000 (99.600) +2022-11-14 16:59:32,836 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0658) Prec@1 90.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 16:59:32,842 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0637) Prec@1 93.000 (90.571) Prec@5 99.000 (99.571) +2022-11-14 16:59:32,851 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0654) Prec@1 86.000 (90.000) Prec@5 100.000 (99.625) +2022-11-14 16:59:32,858 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0665) Prec@1 89.000 (89.889) Prec@5 98.000 (99.444) +2022-11-14 16:59:32,864 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0693) Prec@1 84.000 (89.300) Prec@5 98.000 (99.300) +2022-11-14 16:59:32,873 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0675) Prec@1 93.000 (89.636) Prec@5 100.000 (99.364) +2022-11-14 16:59:32,881 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0664) Prec@1 92.000 (89.833) Prec@5 100.000 (99.417) +2022-11-14 16:59:32,889 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0652) Prec@1 92.000 (90.000) Prec@5 100.000 (99.462) +2022-11-14 16:59:32,896 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0651) Prec@1 91.000 (90.071) Prec@5 99.000 (99.429) +2022-11-14 16:59:32,904 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0650) Prec@1 90.000 (90.067) Prec@5 99.000 (99.400) +2022-11-14 16:59:32,911 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0659) Prec@1 88.000 (89.938) Prec@5 100.000 (99.438) +2022-11-14 16:59:32,919 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0647) Prec@1 94.000 (90.176) Prec@5 98.000 (99.353) +2022-11-14 16:59:32,926 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0671) Prec@1 83.000 (89.778) Prec@5 100.000 (99.389) +2022-11-14 16:59:32,934 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0685) Prec@1 83.000 (89.421) Prec@5 100.000 (99.421) +2022-11-14 16:59:32,941 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0806 (0.0691) Prec@1 86.000 (89.250) Prec@5 96.000 (99.250) +2022-11-14 16:59:32,949 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0761 (0.0695) Prec@1 88.000 (89.190) Prec@5 100.000 (99.286) +2022-11-14 16:59:32,956 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0869 (0.0703) Prec@1 86.000 (89.045) Prec@5 100.000 (99.318) +2022-11-14 16:59:32,964 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0815 (0.0708) Prec@1 88.000 (89.000) Prec@5 98.000 (99.261) +2022-11-14 16:59:32,971 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0931 (0.0717) Prec@1 85.000 (88.833) Prec@5 100.000 (99.292) +2022-11-14 16:59:32,979 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0719) Prec@1 87.000 (88.760) Prec@5 99.000 (99.280) +2022-11-14 16:59:32,986 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0767 (0.0720) Prec@1 89.000 (88.769) Prec@5 97.000 (99.192) +2022-11-14 16:59:32,994 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0487 (0.0712) Prec@1 94.000 (88.963) Prec@5 100.000 (99.222) +2022-11-14 16:59:33,001 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0658 (0.0710) Prec@1 89.000 (88.964) Prec@5 100.000 (99.250) +2022-11-14 16:59:33,008 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0621 (0.0707) Prec@1 91.000 (89.034) Prec@5 100.000 (99.276) +2022-11-14 16:59:33,016 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0626 (0.0704) Prec@1 88.000 (89.000) Prec@5 100.000 (99.300) +2022-11-14 16:59:33,023 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0705) Prec@1 86.000 (88.903) Prec@5 100.000 (99.323) +2022-11-14 16:59:33,031 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0703) Prec@1 90.000 (88.938) Prec@5 99.000 (99.312) +2022-11-14 16:59:33,038 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0704) Prec@1 86.000 (88.848) Prec@5 100.000 (99.333) +2022-11-14 16:59:33,048 Test: [33/100] Model Time 0.008 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0709) Prec@1 85.000 (88.735) Prec@5 100.000 (99.353) +2022-11-14 16:59:33,057 Test: [34/100] Model Time 0.008 (0.005) Loss Time 0.000 (0.000) Loss 0.0894 (0.0714) Prec@1 87.000 (88.686) Prec@5 98.000 (99.314) +2022-11-14 16:59:33,065 Test: [35/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0721 (0.0715) Prec@1 89.000 (88.694) Prec@5 100.000 (99.333) +2022-11-14 16:59:33,072 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0718 (0.0715) Prec@1 87.000 (88.649) Prec@5 99.000 (99.324) +2022-11-14 16:59:33,083 Test: [37/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0722) Prec@1 84.000 (88.526) Prec@5 99.000 (99.316) +2022-11-14 16:59:33,093 Test: [38/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0717) Prec@1 93.000 (88.641) Prec@5 99.000 (99.308) +2022-11-14 16:59:33,101 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0717) Prec@1 89.000 (88.650) Prec@5 99.000 (99.300) +2022-11-14 16:59:33,108 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0722) Prec@1 85.000 (88.561) Prec@5 100.000 (99.317) +2022-11-14 16:59:33,118 Test: [41/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0719) Prec@1 90.000 (88.595) Prec@5 99.000 (99.310) +2022-11-14 16:59:33,128 Test: [42/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0713) Prec@1 92.000 (88.674) Prec@5 99.000 (99.302) +2022-11-14 16:59:33,136 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0714) Prec@1 89.000 (88.682) Prec@5 98.000 (99.273) +2022-11-14 16:59:33,143 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0470 (0.0709) Prec@1 91.000 (88.733) Prec@5 99.000 (99.267) +2022-11-14 16:59:33,153 Test: [45/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1185 (0.0719) Prec@1 81.000 (88.565) Prec@5 98.000 (99.239) +2022-11-14 16:59:33,163 Test: [46/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0718) Prec@1 88.000 (88.553) Prec@5 100.000 (99.255) +2022-11-14 16:59:33,171 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0722) Prec@1 85.000 (88.479) Prec@5 98.000 (99.229) +2022-11-14 16:59:33,179 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0718) Prec@1 91.000 (88.531) Prec@5 99.000 (99.224) +2022-11-14 16:59:33,188 Test: [49/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.0725) Prec@1 82.000 (88.400) Prec@5 100.000 (99.240) +2022-11-14 16:59:33,198 Test: [50/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0720) Prec@1 91.000 (88.451) Prec@5 100.000 (99.255) +2022-11-14 16:59:33,206 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0719) Prec@1 89.000 (88.462) Prec@5 99.000 (99.250) +2022-11-14 16:59:33,214 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0719) Prec@1 87.000 (88.434) Prec@5 99.000 (99.245) +2022-11-14 16:59:33,224 Test: [53/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0719) Prec@1 89.000 (88.444) Prec@5 99.000 (99.241) +2022-11-14 16:59:33,234 Test: [54/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0726) Prec@1 84.000 (88.364) Prec@5 100.000 (99.255) +2022-11-14 16:59:33,242 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0728) Prec@1 87.000 (88.339) Prec@5 100.000 (99.268) +2022-11-14 16:59:33,249 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0726) Prec@1 90.000 (88.368) Prec@5 99.000 (99.263) +2022-11-14 16:59:33,259 Test: [57/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0728) Prec@1 88.000 (88.362) Prec@5 100.000 (99.276) +2022-11-14 16:59:33,269 Test: [58/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0733) Prec@1 83.000 (88.271) Prec@5 100.000 (99.288) +2022-11-14 16:59:33,277 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0735) Prec@1 84.000 (88.200) Prec@5 100.000 (99.300) +2022-11-14 16:59:33,284 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0733) Prec@1 90.000 (88.230) Prec@5 100.000 (99.311) +2022-11-14 16:59:33,294 Test: [61/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0731) Prec@1 90.000 (88.258) Prec@5 100.000 (99.323) +2022-11-14 16:59:33,304 Test: [62/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0731) Prec@1 90.000 (88.286) Prec@5 100.000 (99.333) +2022-11-14 16:59:33,312 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0362 (0.0725) Prec@1 96.000 (88.406) Prec@5 100.000 (99.344) +2022-11-14 16:59:33,320 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0728) Prec@1 85.000 (88.354) Prec@5 100.000 (99.354) +2022-11-14 16:59:33,330 Test: [65/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0730) Prec@1 85.000 (88.303) Prec@5 99.000 (99.348) +2022-11-14 16:59:33,340 Test: [66/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0280 (0.0724) Prec@1 95.000 (88.403) Prec@5 99.000 (99.343) +2022-11-14 16:59:33,348 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0724) Prec@1 87.000 (88.382) Prec@5 100.000 (99.353) +2022-11-14 16:59:33,356 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0724) Prec@1 86.000 (88.348) Prec@5 99.000 (99.348) +2022-11-14 16:59:33,366 Test: [69/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0724) Prec@1 86.000 (88.314) Prec@5 98.000 (99.329) +2022-11-14 16:59:33,376 Test: [70/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0725) Prec@1 90.000 (88.338) Prec@5 98.000 (99.310) +2022-11-14 16:59:33,384 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0723) Prec@1 91.000 (88.375) Prec@5 100.000 (99.319) +2022-11-14 16:59:33,392 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0721) Prec@1 90.000 (88.397) Prec@5 99.000 (99.315) +2022-11-14 16:59:33,402 Test: [73/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0718) Prec@1 90.000 (88.419) Prec@5 100.000 (99.324) +2022-11-14 16:59:33,412 Test: [74/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0722) Prec@1 83.000 (88.347) Prec@5 99.000 (99.320) +2022-11-14 16:59:33,420 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0722) Prec@1 90.000 (88.368) Prec@5 99.000 (99.316) +2022-11-14 16:59:33,428 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0722) Prec@1 88.000 (88.364) Prec@5 98.000 (99.299) +2022-11-14 16:59:33,438 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0724) Prec@1 86.000 (88.333) Prec@5 100.000 (99.308) +2022-11-14 16:59:33,447 Test: [78/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0724) Prec@1 86.000 (88.304) Prec@5 100.000 (99.316) +2022-11-14 16:59:33,455 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0726) Prec@1 87.000 (88.287) Prec@5 100.000 (99.325) +2022-11-14 16:59:33,463 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0728) Prec@1 86.000 (88.259) Prec@5 99.000 (99.321) +2022-11-14 16:59:33,473 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0730) Prec@1 83.000 (88.195) Prec@5 100.000 (99.329) +2022-11-14 16:59:33,483 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0733) Prec@1 87.000 (88.181) Prec@5 100.000 (99.337) +2022-11-14 16:59:33,491 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0734) Prec@1 86.000 (88.155) Prec@5 100.000 (99.345) +2022-11-14 16:59:33,498 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0736) Prec@1 86.000 (88.129) Prec@5 100.000 (99.353) +2022-11-14 16:59:33,508 Test: [85/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0738) Prec@1 87.000 (88.116) Prec@5 100.000 (99.360) +2022-11-14 16:59:33,518 Test: [86/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0739) Prec@1 88.000 (88.115) Prec@5 99.000 (99.356) +2022-11-14 16:59:33,526 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0740) Prec@1 88.000 (88.114) Prec@5 99.000 (99.352) +2022-11-14 16:59:33,534 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0740) Prec@1 88.000 (88.112) Prec@5 100.000 (99.360) +2022-11-14 16:59:33,541 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0741) Prec@1 89.000 (88.122) Prec@5 97.000 (99.333) +2022-11-14 16:59:33,549 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0741) Prec@1 89.000 (88.132) Prec@5 100.000 (99.341) +2022-11-14 16:59:33,557 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0438 (0.0738) Prec@1 94.000 (88.196) Prec@5 98.000 (99.326) +2022-11-14 16:59:33,564 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0739) Prec@1 85.000 (88.161) Prec@5 100.000 (99.333) +2022-11-14 16:59:33,572 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 87.000 (88.149) Prec@5 99.000 (99.330) +2022-11-14 16:59:33,579 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0740) Prec@1 86.000 (88.126) Prec@5 99.000 (99.326) +2022-11-14 16:59:33,587 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0739) Prec@1 89.000 (88.135) Prec@5 98.000 (99.312) +2022-11-14 16:59:33,594 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0738) Prec@1 89.000 (88.144) Prec@5 99.000 (99.309) +2022-11-14 16:59:33,602 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0738) Prec@1 89.000 (88.153) Prec@5 99.000 (99.306) +2022-11-14 16:59:33,609 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0740) Prec@1 86.000 (88.131) Prec@5 99.000 (99.303) +2022-11-14 16:59:33,616 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0739) Prec@1 91.000 (88.160) Prec@5 100.000 (99.310) +2022-11-14 16:59:33,670 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:59:34,204 Epoch: [434][0/500] Time 0.022 (0.022) Data 0.255 (0.255) Loss 0.0430 (0.0430) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:34,401 Epoch: [434][10/500] Time 0.017 (0.018) Data 0.002 (0.025) Loss 0.0264 (0.0347) Prec@1 95.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 16:59:34,587 Epoch: [434][20/500] Time 0.017 (0.017) Data 0.002 (0.014) Loss 0.0166 (0.0287) Prec@1 97.000 (94.667) Prec@5 99.000 (99.333) +2022-11-14 16:59:34,776 Epoch: [434][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0243 (0.0276) Prec@1 96.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 16:59:34,967 Epoch: [434][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0250 (0.0271) Prec@1 95.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 16:59:35,158 Epoch: [434][50/500] Time 0.018 (0.017) Data 0.002 (0.007) Loss 0.0330 (0.0281) Prec@1 94.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 16:59:35,347 Epoch: [434][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0337 (0.0289) Prec@1 94.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 16:59:35,536 Epoch: [434][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0155 (0.0272) Prec@1 97.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 16:59:35,726 Epoch: [434][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0242 (0.0269) Prec@1 97.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 16:59:35,916 Epoch: [434][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0200 (0.0262) Prec@1 96.000 (95.300) Prec@5 99.000 (99.700) +2022-11-14 16:59:36,112 Epoch: [434][100/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0458 (0.0280) Prec@1 95.000 (95.273) Prec@5 99.000 (99.636) +2022-11-14 16:59:36,302 Epoch: [434][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0226 (0.0275) Prec@1 96.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 16:59:36,493 Epoch: [434][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0268 (0.0275) Prec@1 95.000 (95.308) Prec@5 100.000 (99.692) +2022-11-14 16:59:36,748 Epoch: [434][130/500] Time 0.028 (0.017) Data 0.001 (0.003) Loss 0.0201 (0.0269) Prec@1 96.000 (95.357) Prec@5 99.000 (99.643) +2022-11-14 16:59:37,049 Epoch: [434][140/500] Time 0.029 (0.018) Data 0.001 (0.003) Loss 0.0354 (0.0275) Prec@1 94.000 (95.267) Prec@5 100.000 (99.667) +2022-11-14 16:59:37,342 Epoch: [434][150/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0365 (0.0281) Prec@1 95.000 (95.250) Prec@5 98.000 (99.562) +2022-11-14 16:59:37,638 Epoch: [434][160/500] Time 0.028 (0.019) Data 0.003 (0.003) Loss 0.0368 (0.0286) Prec@1 93.000 (95.118) Prec@5 100.000 (99.588) +2022-11-14 16:59:37,942 Epoch: [434][170/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0630 (0.0305) Prec@1 90.000 (94.833) Prec@5 99.000 (99.556) +2022-11-14 16:59:38,246 Epoch: [434][180/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0651 (0.0323) Prec@1 89.000 (94.526) Prec@5 99.000 (99.526) +2022-11-14 16:59:38,538 Epoch: [434][190/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0326 (0.0323) Prec@1 92.000 (94.400) Prec@5 100.000 (99.550) +2022-11-14 16:59:38,832 Epoch: [434][200/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0344 (0.0324) Prec@1 94.000 (94.381) Prec@5 100.000 (99.571) +2022-11-14 16:59:39,127 Epoch: [434][210/500] Time 0.031 (0.021) Data 0.002 (0.003) Loss 0.0290 (0.0323) Prec@1 94.000 (94.364) Prec@5 100.000 (99.591) +2022-11-14 16:59:39,422 Epoch: [434][220/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0112 (0.0314) Prec@1 99.000 (94.565) Prec@5 100.000 (99.609) +2022-11-14 16:59:39,717 Epoch: [434][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0192 (0.0308) Prec@1 98.000 (94.708) Prec@5 100.000 (99.625) +2022-11-14 16:59:40,013 Epoch: [434][240/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0278 (0.0307) Prec@1 96.000 (94.760) Prec@5 100.000 (99.640) +2022-11-14 16:59:40,312 Epoch: [434][250/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0281 (0.0306) Prec@1 95.000 (94.769) Prec@5 100.000 (99.654) +2022-11-14 16:59:40,610 Epoch: [434][260/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0415 (0.0310) Prec@1 90.000 (94.593) Prec@5 100.000 (99.667) +2022-11-14 16:59:40,906 Epoch: [434][270/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0150 (0.0305) Prec@1 98.000 (94.714) Prec@5 100.000 (99.679) +2022-11-14 16:59:41,205 Epoch: [434][280/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0361 (0.0306) Prec@1 96.000 (94.759) Prec@5 100.000 (99.690) +2022-11-14 16:59:41,505 Epoch: [434][290/500] Time 0.029 (0.022) Data 0.001 (0.003) Loss 0.0202 (0.0303) Prec@1 98.000 (94.867) Prec@5 99.000 (99.667) +2022-11-14 16:59:41,800 Epoch: [434][300/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0229 (0.0301) Prec@1 97.000 (94.935) Prec@5 100.000 (99.677) +2022-11-14 16:59:42,102 Epoch: [434][310/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0135 (0.0295) Prec@1 98.000 (95.031) Prec@5 100.000 (99.688) +2022-11-14 16:59:42,392 Epoch: [434][320/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0354 (0.0297) Prec@1 92.000 (94.939) Prec@5 100.000 (99.697) +2022-11-14 16:59:42,697 Epoch: [434][330/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0441 (0.0301) Prec@1 95.000 (94.941) Prec@5 100.000 (99.706) +2022-11-14 16:59:42,998 Epoch: [434][340/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0093 (0.0295) Prec@1 99.000 (95.057) Prec@5 100.000 (99.714) +2022-11-14 16:59:43,302 Epoch: [434][350/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0643 (0.0305) Prec@1 89.000 (94.889) Prec@5 99.000 (99.694) +2022-11-14 16:59:43,595 Epoch: [434][360/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0202 (0.0302) Prec@1 98.000 (94.973) Prec@5 100.000 (99.703) +2022-11-14 16:59:43,892 Epoch: [434][370/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0162 (0.0299) Prec@1 97.000 (95.026) Prec@5 100.000 (99.711) +2022-11-14 16:59:44,191 Epoch: [434][380/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0400 (0.0301) Prec@1 92.000 (94.949) Prec@5 100.000 (99.718) +2022-11-14 16:59:44,489 Epoch: [434][390/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0365 (0.0303) Prec@1 93.000 (94.900) Prec@5 98.000 (99.675) +2022-11-14 16:59:44,788 Epoch: [434][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0232 (0.0301) Prec@1 96.000 (94.927) Prec@5 100.000 (99.683) +2022-11-14 16:59:45,086 Epoch: [434][410/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0333 (0.0302) Prec@1 94.000 (94.905) Prec@5 100.000 (99.690) +2022-11-14 16:59:45,380 Epoch: [434][420/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0546 (0.0308) Prec@1 92.000 (94.837) Prec@5 100.000 (99.698) +2022-11-14 16:59:45,677 Epoch: [434][430/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0165 (0.0304) Prec@1 97.000 (94.886) Prec@5 100.000 (99.705) +2022-11-14 16:59:45,971 Epoch: [434][440/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0412 (0.0307) Prec@1 93.000 (94.844) Prec@5 100.000 (99.711) +2022-11-14 16:59:46,270 Epoch: [434][450/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0247 (0.0305) Prec@1 94.000 (94.826) Prec@5 100.000 (99.717) +2022-11-14 16:59:46,567 Epoch: [434][460/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0332 (0.0306) Prec@1 94.000 (94.809) Prec@5 100.000 (99.723) +2022-11-14 16:59:46,861 Epoch: [434][470/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0305 (0.0306) Prec@1 95.000 (94.812) Prec@5 100.000 (99.729) +2022-11-14 16:59:47,155 Epoch: [434][480/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0375 (0.0307) Prec@1 96.000 (94.837) Prec@5 100.000 (99.735) +2022-11-14 16:59:47,448 Epoch: [434][490/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0352 (0.0308) Prec@1 95.000 (94.840) Prec@5 100.000 (99.740) +2022-11-14 16:59:47,717 Epoch: [434][499/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0260 (0.0307) Prec@1 96.000 (94.863) Prec@5 100.000 (99.745) +2022-11-14 16:59:48,011 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0601 (0.0601) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,019 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0673) Prec@1 90.000 (89.500) Prec@5 100.000 (99.500) +2022-11-14 16:59:48,029 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0744) Prec@1 89.000 (89.333) Prec@5 99.000 (99.333) +2022-11-14 16:59:48,038 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0745) Prec@1 89.000 (89.250) Prec@5 99.000 (99.250) +2022-11-14 16:59:48,045 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0722) Prec@1 90.000 (89.400) Prec@5 99.000 (99.200) +2022-11-14 16:59:48,052 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0564 (0.0696) Prec@1 92.000 (89.833) Prec@5 99.000 (99.167) +2022-11-14 16:59:48,059 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0681) Prec@1 92.000 (90.143) Prec@5 100.000 (99.286) +2022-11-14 16:59:48,067 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0694) Prec@1 89.000 (90.000) Prec@5 98.000 (99.125) +2022-11-14 16:59:48,074 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0707) Prec@1 88.000 (89.778) Prec@5 98.000 (99.000) +2022-11-14 16:59:48,082 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0709) Prec@1 87.000 (89.500) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,090 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0706) Prec@1 87.000 (89.273) Prec@5 100.000 (99.091) +2022-11-14 16:59:48,098 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0714) Prec@1 88.000 (89.167) Prec@5 99.000 (99.083) +2022-11-14 16:59:48,106 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0704) Prec@1 90.000 (89.231) Prec@5 100.000 (99.154) +2022-11-14 16:59:48,113 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0704) Prec@1 90.000 (89.286) Prec@5 98.000 (99.071) +2022-11-14 16:59:48,121 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0721) Prec@1 86.000 (89.067) Prec@5 100.000 (99.133) +2022-11-14 16:59:48,129 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0715) Prec@1 89.000 (89.062) Prec@5 100.000 (99.188) +2022-11-14 16:59:48,137 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0702) Prec@1 92.000 (89.235) Prec@5 98.000 (99.118) +2022-11-14 16:59:48,144 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1165 (0.0727) Prec@1 83.000 (88.889) Prec@5 100.000 (99.167) +2022-11-14 16:59:48,152 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0724) Prec@1 90.000 (88.947) Prec@5 100.000 (99.211) +2022-11-14 16:59:48,160 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0737) Prec@1 86.000 (88.800) Prec@5 97.000 (99.100) +2022-11-14 16:59:48,168 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0733) Prec@1 89.000 (88.810) Prec@5 99.000 (99.095) +2022-11-14 16:59:48,176 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0742) Prec@1 84.000 (88.591) Prec@5 99.000 (99.091) +2022-11-14 16:59:48,183 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0981 (0.0752) Prec@1 87.000 (88.522) Prec@5 96.000 (98.957) +2022-11-14 16:59:48,191 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0753) Prec@1 87.000 (88.458) Prec@5 100.000 (99.000) +2022-11-14 16:59:48,198 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0759) Prec@1 87.000 (88.400) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,206 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0764) Prec@1 87.000 (88.346) Prec@5 98.000 (98.962) +2022-11-14 16:59:48,214 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0761) Prec@1 89.000 (88.370) Prec@5 100.000 (99.000) +2022-11-14 16:59:48,221 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0756) Prec@1 91.000 (88.464) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,229 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0757) Prec@1 86.000 (88.379) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,236 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0756) Prec@1 90.000 (88.433) Prec@5 98.000 (98.967) +2022-11-14 16:59:48,244 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0750) Prec@1 90.000 (88.484) Prec@5 100.000 (99.000) +2022-11-14 16:59:48,252 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0745) Prec@1 91.000 (88.562) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,260 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0744) Prec@1 87.000 (88.515) Prec@5 99.000 (99.000) +2022-11-14 16:59:48,267 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0750) Prec@1 83.000 (88.353) Prec@5 100.000 (99.029) +2022-11-14 16:59:48,275 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0755) Prec@1 85.000 (88.257) Prec@5 99.000 (99.029) +2022-11-14 16:59:48,283 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0751) Prec@1 92.000 (88.361) Prec@5 100.000 (99.056) +2022-11-14 16:59:48,291 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0749) Prec@1 90.000 (88.405) Prec@5 99.000 (99.054) +2022-11-14 16:59:48,298 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0959 (0.0755) Prec@1 82.000 (88.237) Prec@5 100.000 (99.079) +2022-11-14 16:59:48,307 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0748) Prec@1 93.000 (88.359) Prec@5 99.000 (99.077) +2022-11-14 16:59:48,315 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0747) Prec@1 89.000 (88.375) Prec@5 99.000 (99.075) +2022-11-14 16:59:48,322 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0753) Prec@1 84.000 (88.268) Prec@5 98.000 (99.049) +2022-11-14 16:59:48,330 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0750) Prec@1 89.000 (88.286) Prec@5 100.000 (99.071) +2022-11-14 16:59:48,338 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0744) Prec@1 93.000 (88.395) Prec@5 99.000 (99.070) +2022-11-14 16:59:48,345 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0743) Prec@1 90.000 (88.432) Prec@5 99.000 (99.068) +2022-11-14 16:59:48,353 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0740) Prec@1 90.000 (88.467) Prec@5 98.000 (99.044) +2022-11-14 16:59:48,361 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1262 (0.0752) Prec@1 82.000 (88.326) Prec@5 98.000 (99.022) +2022-11-14 16:59:48,368 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0747) Prec@1 93.000 (88.426) Prec@5 99.000 (99.021) +2022-11-14 16:59:48,376 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0749) Prec@1 87.000 (88.396) Prec@5 99.000 (99.021) +2022-11-14 16:59:48,384 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0473 (0.0744) Prec@1 91.000 (88.449) Prec@5 100.000 (99.041) +2022-11-14 16:59:48,392 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0744) Prec@1 88.000 (88.440) Prec@5 99.000 (99.040) +2022-11-14 16:59:48,399 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0739) Prec@1 92.000 (88.510) Prec@5 99.000 (99.039) +2022-11-14 16:59:48,407 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0740) Prec@1 85.000 (88.442) Prec@5 99.000 (99.038) +2022-11-14 16:59:48,414 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0742) Prec@1 85.000 (88.377) Prec@5 99.000 (99.038) +2022-11-14 16:59:48,422 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0740) Prec@1 89.000 (88.389) Prec@5 100.000 (99.056) +2022-11-14 16:59:48,430 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0742) Prec@1 88.000 (88.382) Prec@5 100.000 (99.073) +2022-11-14 16:59:48,437 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0744) Prec@1 88.000 (88.375) Prec@5 100.000 (99.089) +2022-11-14 16:59:48,445 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0744) Prec@1 87.000 (88.351) Prec@5 100.000 (99.105) +2022-11-14 16:59:48,452 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0745) Prec@1 89.000 (88.362) Prec@5 99.000 (99.103) +2022-11-14 16:59:48,460 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0748) Prec@1 86.000 (88.322) Prec@5 98.000 (99.085) +2022-11-14 16:59:48,467 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0745) Prec@1 89.000 (88.333) Prec@5 100.000 (99.100) +2022-11-14 16:59:48,475 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0744) Prec@1 89.000 (88.344) Prec@5 98.000 (99.082) +2022-11-14 16:59:48,483 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0742) Prec@1 89.000 (88.355) Prec@5 100.000 (99.097) +2022-11-14 16:59:48,490 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0739) Prec@1 92.000 (88.413) Prec@5 100.000 (99.111) +2022-11-14 16:59:48,498 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0366 (0.0733) Prec@1 94.000 (88.500) Prec@5 100.000 (99.125) +2022-11-14 16:59:48,505 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0736) Prec@1 86.000 (88.462) Prec@5 99.000 (99.123) +2022-11-14 16:59:48,513 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0736) Prec@1 88.000 (88.455) Prec@5 99.000 (99.121) +2022-11-14 16:59:48,520 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0404 (0.0731) Prec@1 92.000 (88.507) Prec@5 99.000 (99.119) +2022-11-14 16:59:48,528 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0732) Prec@1 88.000 (88.500) Prec@5 98.000 (99.103) +2022-11-14 16:59:48,536 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0732) Prec@1 88.000 (88.493) Prec@5 98.000 (99.087) +2022-11-14 16:59:48,543 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0734) Prec@1 85.000 (88.443) Prec@5 99.000 (99.086) +2022-11-14 16:59:48,551 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0740) Prec@1 84.000 (88.380) Prec@5 99.000 (99.085) +2022-11-14 16:59:48,559 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0739) Prec@1 87.000 (88.361) Prec@5 100.000 (99.097) +2022-11-14 16:59:48,566 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0736) Prec@1 92.000 (88.411) Prec@5 100.000 (99.110) +2022-11-14 16:59:48,574 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0731) Prec@1 94.000 (88.486) Prec@5 100.000 (99.122) +2022-11-14 16:59:48,581 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0737) Prec@1 82.000 (88.400) Prec@5 100.000 (99.133) +2022-11-14 16:59:48,589 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0735) Prec@1 91.000 (88.434) Prec@5 100.000 (99.145) +2022-11-14 16:59:48,596 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0734) Prec@1 90.000 (88.455) Prec@5 99.000 (99.143) +2022-11-14 16:59:48,604 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0736) Prec@1 85.000 (88.410) Prec@5 100.000 (99.154) +2022-11-14 16:59:48,612 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0736) Prec@1 86.000 (88.380) Prec@5 100.000 (99.165) +2022-11-14 16:59:48,619 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0736) Prec@1 86.000 (88.350) Prec@5 100.000 (99.175) +2022-11-14 16:59:48,627 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0737) Prec@1 87.000 (88.333) Prec@5 98.000 (99.160) +2022-11-14 16:59:48,634 Test: 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Loss 0.0936 (0.0746) Prec@1 84.000 (88.125) Prec@5 99.000 (99.182) +2022-11-14 16:59:48,687 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0746) Prec@1 87.000 (88.112) Prec@5 100.000 (99.191) +2022-11-14 16:59:48,695 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0746) Prec@1 89.000 (88.122) Prec@5 99.000 (99.189) +2022-11-14 16:59:48,702 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0744) Prec@1 90.000 (88.143) Prec@5 100.000 (99.198) +2022-11-14 16:59:48,710 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0742) Prec@1 92.000 (88.185) Prec@5 100.000 (99.207) +2022-11-14 16:59:48,717 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0742) Prec@1 86.000 (88.161) Prec@5 100.000 (99.215) +2022-11-14 16:59:48,725 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0742) Prec@1 88.000 (88.160) Prec@5 99.000 (99.213) +2022-11-14 16:59:48,732 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0743) Prec@1 83.000 (88.105) Prec@5 100.000 (99.221) +2022-11-14 16:59:48,740 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0664 (0.0742) Prec@1 90.000 (88.125) Prec@5 98.000 (99.208) +2022-11-14 16:59:48,747 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0589 (0.0740) Prec@1 91.000 (88.155) Prec@5 99.000 (99.206) +2022-11-14 16:59:48,755 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0742) Prec@1 86.000 (88.133) Prec@5 100.000 (99.214) +2022-11-14 16:59:48,762 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0922 (0.0743) Prec@1 85.000 (88.101) Prec@5 99.000 (99.212) +2022-11-14 16:59:48,770 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0743) Prec@1 90.000 (88.120) Prec@5 99.000 (99.210) +2022-11-14 16:59:48,826 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 16:59:49,473 Epoch: [435][0/500] Time 0.028 (0.028) Data 0.233 (0.233) Loss 0.0279 (0.0279) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:49,678 Epoch: [435][10/500] Time 0.016 (0.019) Data 0.002 (0.023) Loss 0.0214 (0.0246) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 16:59:49,880 Epoch: [435][20/500] Time 0.016 (0.018) Data 0.002 (0.013) Loss 0.0310 (0.0268) Prec@1 96.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 16:59:50,080 Epoch: [435][30/500] Time 0.016 (0.018) Data 0.002 (0.009) Loss 0.0623 (0.0356) Prec@1 88.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:59:50,284 Epoch: [435][40/500] Time 0.017 (0.018) Data 0.002 (0.007) Loss 0.0250 (0.0335) Prec@1 95.000 (94.600) Prec@5 100.000 (100.000) +2022-11-14 16:59:50,484 Epoch: [435][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0162 (0.0306) Prec@1 98.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 16:59:50,691 Epoch: [435][60/500] Time 0.016 (0.018) Data 0.002 (0.006) Loss 0.0394 (0.0319) Prec@1 95.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 16:59:50,888 Epoch: [435][70/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0407 (0.0330) Prec@1 93.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 16:59:51,099 Epoch: [435][80/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0471 (0.0346) Prec@1 91.000 (94.444) Prec@5 100.000 (100.000) +2022-11-14 16:59:51,309 Epoch: [435][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0348 (0.0346) Prec@1 94.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 16:59:51,514 Epoch: [435][100/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.0186 (0.0331) Prec@1 97.000 (94.636) Prec@5 100.000 (100.000) +2022-11-14 16:59:51,710 Epoch: [435][110/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0445 (0.0341) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 16:59:51,922 Epoch: [435][120/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0221 (0.0331) Prec@1 95.000 (94.538) Prec@5 100.000 (100.000) +2022-11-14 16:59:52,123 Epoch: [435][130/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0386 (0.0335) Prec@1 95.000 (94.571) Prec@5 98.000 (99.857) +2022-11-14 16:59:52,324 Epoch: [435][140/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0232 (0.0328) Prec@1 95.000 (94.600) Prec@5 100.000 (99.867) +2022-11-14 16:59:52,521 Epoch: [435][150/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0117 (0.0315) Prec@1 98.000 (94.812) Prec@5 100.000 (99.875) +2022-11-14 16:59:52,712 Epoch: [435][160/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0319 (0.0315) Prec@1 95.000 (94.824) Prec@5 100.000 (99.882) +2022-11-14 16:59:52,899 Epoch: [435][170/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0171 (0.0307) Prec@1 97.000 (94.944) Prec@5 100.000 (99.889) +2022-11-14 16:59:53,090 Epoch: [435][180/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0497 (0.0317) Prec@1 91.000 (94.737) Prec@5 100.000 (99.895) +2022-11-14 16:59:53,278 Epoch: [435][190/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0269 (0.0315) Prec@1 96.000 (94.800) Prec@5 100.000 (99.900) +2022-11-14 16:59:53,465 Epoch: [435][200/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0287 (0.0314) Prec@1 96.000 (94.857) Prec@5 100.000 (99.905) +2022-11-14 16:59:53,653 Epoch: [435][210/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0268 (0.0312) Prec@1 95.000 (94.864) Prec@5 100.000 (99.909) +2022-11-14 16:59:53,840 Epoch: [435][220/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0213 (0.0307) Prec@1 97.000 (94.957) Prec@5 100.000 (99.913) +2022-11-14 16:59:54,029 Epoch: [435][230/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0335 (0.0308) Prec@1 95.000 (94.958) Prec@5 100.000 (99.917) +2022-11-14 16:59:54,226 Epoch: [435][240/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0164 (0.0303) Prec@1 98.000 (95.080) Prec@5 100.000 (99.920) +2022-11-14 16:59:54,415 Epoch: [435][250/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0307 (0.0303) Prec@1 97.000 (95.154) Prec@5 100.000 (99.923) +2022-11-14 16:59:54,602 Epoch: [435][260/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0438 (0.0308) Prec@1 93.000 (95.074) Prec@5 99.000 (99.889) +2022-11-14 16:59:54,788 Epoch: [435][270/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0238 (0.0305) Prec@1 96.000 (95.107) Prec@5 100.000 (99.893) +2022-11-14 16:59:54,975 Epoch: [435][280/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0408 (0.0309) Prec@1 91.000 (94.966) Prec@5 100.000 (99.897) +2022-11-14 16:59:55,166 Epoch: [435][290/500] Time 0.017 (0.017) Data 0.002 (0.002) Loss 0.0436 (0.0313) Prec@1 95.000 (94.967) Prec@5 100.000 (99.900) +2022-11-14 16:59:55,410 Epoch: [435][300/500] Time 0.024 (0.017) Data 0.001 (0.002) Loss 0.0185 (0.0309) Prec@1 97.000 (95.032) Prec@5 100.000 (99.903) +2022-11-14 16:59:55,678 Epoch: [435][310/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0404 (0.0312) Prec@1 94.000 (95.000) Prec@5 99.000 (99.875) +2022-11-14 16:59:55,951 Epoch: [435][320/500] Time 0.026 (0.018) Data 0.002 (0.002) Loss 0.0292 (0.0311) Prec@1 95.000 (95.000) Prec@5 100.000 (99.879) +2022-11-14 16:59:56,235 Epoch: [435][330/500] Time 0.026 (0.018) Data 0.001 (0.002) Loss 0.0361 (0.0313) Prec@1 94.000 (94.971) Prec@5 100.000 (99.882) +2022-11-14 16:59:56,510 Epoch: [435][340/500] Time 0.026 (0.018) Data 0.001 (0.002) Loss 0.0166 (0.0309) Prec@1 97.000 (95.029) Prec@5 100.000 (99.886) +2022-11-14 16:59:56,787 Epoch: [435][350/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0392 (0.0311) Prec@1 92.000 (94.944) Prec@5 100.000 (99.889) +2022-11-14 16:59:57,065 Epoch: [435][360/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0091 (0.0305) Prec@1 98.000 (95.027) Prec@5 100.000 (99.892) +2022-11-14 16:59:57,345 Epoch: [435][370/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0381 (0.0307) Prec@1 93.000 (94.974) Prec@5 100.000 (99.895) +2022-11-14 16:59:57,625 Epoch: [435][380/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0303 (0.0307) Prec@1 95.000 (94.974) Prec@5 100.000 (99.897) +2022-11-14 16:59:57,903 Epoch: [435][390/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0411 (0.0310) Prec@1 92.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 16:59:58,184 Epoch: [435][400/500] Time 0.027 (0.019) Data 0.001 (0.002) Loss 0.0424 (0.0312) Prec@1 92.000 (94.829) Prec@5 100.000 (99.902) +2022-11-14 16:59:58,462 Epoch: [435][410/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0412 (0.0315) Prec@1 92.000 (94.762) Prec@5 100.000 (99.905) +2022-11-14 16:59:58,734 Epoch: [435][420/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0234 (0.0313) Prec@1 97.000 (94.814) Prec@5 100.000 (99.907) +2022-11-14 16:59:58,998 Epoch: [435][430/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0162 (0.0309) Prec@1 97.000 (94.864) Prec@5 100.000 (99.909) +2022-11-14 16:59:59,268 Epoch: [435][440/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0262 (0.0308) Prec@1 95.000 (94.867) Prec@5 100.000 (99.911) +2022-11-14 16:59:59,537 Epoch: [435][450/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0146 (0.0305) Prec@1 98.000 (94.935) Prec@5 100.000 (99.913) +2022-11-14 16:59:59,805 Epoch: [435][460/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0200 (0.0303) Prec@1 95.000 (94.936) Prec@5 100.000 (99.915) +2022-11-14 17:00:00,075 Epoch: [435][470/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0295 (0.0302) Prec@1 95.000 (94.938) Prec@5 98.000 (99.875) +2022-11-14 17:00:00,346 Epoch: [435][480/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0307 (0.0303) Prec@1 95.000 (94.939) Prec@5 100.000 (99.878) +2022-11-14 17:00:00,615 Epoch: [435][490/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0155 (0.0300) Prec@1 97.000 (94.980) Prec@5 100.000 (99.880) +2022-11-14 17:00:00,855 Epoch: [435][499/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0538 (0.0304) Prec@1 90.000 (94.882) Prec@5 100.000 (99.882) +2022-11-14 17:00:01,159 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0693 (0.0693) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:01,173 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0692 (0.0693) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:00:01,185 Test: [2/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0835 (0.0740) Prec@1 86.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:00:01,198 Test: [3/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0783 (0.0751) Prec@1 89.000 (88.000) Prec@5 98.000 (99.500) +2022-11-14 17:00:01,205 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0743) Prec@1 90.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 17:00:01,213 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0389 (0.0684) Prec@1 92.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 17:00:01,219 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0695 (0.0686) Prec@1 90.000 (89.143) Prec@5 98.000 (99.429) +2022-11-14 17:00:01,228 Test: [7/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0973 (0.0722) Prec@1 82.000 (88.250) Prec@5 98.000 (99.250) +2022-11-14 17:00:01,235 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0753 (0.0725) Prec@1 89.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 17:00:01,242 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0732) Prec@1 87.000 (88.200) Prec@5 98.000 (99.200) +2022-11-14 17:00:01,249 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0740) Prec@1 90.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 17:00:01,257 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0742) Prec@1 89.000 (88.417) Prec@5 100.000 (99.333) +2022-11-14 17:00:01,265 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0722) Prec@1 93.000 (88.769) Prec@5 100.000 (99.385) +2022-11-14 17:00:01,272 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0726) Prec@1 85.000 (88.500) Prec@5 99.000 (99.357) +2022-11-14 17:00:01,280 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0728) Prec@1 89.000 (88.533) Prec@5 100.000 (99.400) +2022-11-14 17:00:01,287 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0723) Prec@1 91.000 (88.688) Prec@5 100.000 (99.438) +2022-11-14 17:00:01,294 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0707) Prec@1 93.000 (88.941) Prec@5 99.000 (99.412) +2022-11-14 17:00:01,302 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0727) Prec@1 85.000 (88.722) Prec@5 99.000 (99.389) +2022-11-14 17:00:01,309 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0736) Prec@1 85.000 (88.526) Prec@5 99.000 (99.368) +2022-11-14 17:00:01,317 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0734) Prec@1 88.000 (88.500) Prec@5 99.000 (99.350) +2022-11-14 17:00:01,324 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0738) Prec@1 88.000 (88.476) Prec@5 100.000 (99.381) +2022-11-14 17:00:01,331 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0737) Prec@1 87.000 (88.409) Prec@5 99.000 (99.364) +2022-11-14 17:00:01,339 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0745) Prec@1 86.000 (88.304) Prec@5 97.000 (99.261) +2022-11-14 17:00:01,346 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0749) Prec@1 88.000 (88.292) Prec@5 100.000 (99.292) +2022-11-14 17:00:01,354 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0749) Prec@1 89.000 (88.320) Prec@5 100.000 (99.320) +2022-11-14 17:00:01,361 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0756) Prec@1 84.000 (88.154) Prec@5 99.000 (99.308) +2022-11-14 17:00:01,369 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0752) Prec@1 90.000 (88.222) Prec@5 100.000 (99.333) +2022-11-14 17:00:01,376 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0367 (0.0738) Prec@1 95.000 (88.464) Prec@5 99.000 (99.321) +2022-11-14 17:00:01,383 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0735) Prec@1 91.000 (88.552) Prec@5 98.000 (99.276) +2022-11-14 17:00:01,391 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0734) Prec@1 90.000 (88.600) Prec@5 100.000 (99.300) +2022-11-14 17:00:01,398 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0729) Prec@1 89.000 (88.613) Prec@5 100.000 (99.323) +2022-11-14 17:00:01,405 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0730) Prec@1 90.000 (88.656) Prec@5 98.000 (99.281) +2022-11-14 17:00:01,413 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0732) Prec@1 86.000 (88.576) Prec@5 100.000 (99.303) +2022-11-14 17:00:01,420 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0741) Prec@1 84.000 (88.441) Prec@5 99.000 (99.294) +2022-11-14 17:00:01,428 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0744) Prec@1 85.000 (88.343) Prec@5 98.000 (99.257) +2022-11-14 17:00:01,435 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0740) Prec@1 91.000 (88.417) Prec@5 98.000 (99.222) +2022-11-14 17:00:01,443 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0740) Prec@1 88.000 (88.405) Prec@5 99.000 (99.216) +2022-11-14 17:00:01,451 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0742) Prec@1 86.000 (88.342) Prec@5 98.000 (99.184) +2022-11-14 17:00:01,458 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0738) Prec@1 92.000 (88.436) Prec@5 99.000 (99.179) +2022-11-14 17:00:01,465 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0738) Prec@1 89.000 (88.450) Prec@5 98.000 (99.150) +2022-11-14 17:00:01,473 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0743) Prec@1 83.000 (88.317) Prec@5 98.000 (99.122) +2022-11-14 17:00:01,480 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0745) Prec@1 84.000 (88.214) Prec@5 99.000 (99.119) +2022-11-14 17:00:01,487 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0380 (0.0737) Prec@1 95.000 (88.372) Prec@5 99.000 (99.116) +2022-11-14 17:00:01,495 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0738) Prec@1 89.000 (88.386) Prec@5 99.000 (99.114) +2022-11-14 17:00:01,502 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0732) Prec@1 91.000 (88.444) Prec@5 100.000 (99.133) +2022-11-14 17:00:01,510 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0739) Prec@1 84.000 (88.348) Prec@5 100.000 (99.152) +2022-11-14 17:00:01,517 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0743) Prec@1 84.000 (88.255) Prec@5 100.000 (99.170) +2022-11-14 17:00:01,524 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0927 (0.0747) Prec@1 84.000 (88.167) Prec@5 99.000 (99.167) +2022-11-14 17:00:01,532 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0567 (0.0743) Prec@1 92.000 (88.245) Prec@5 100.000 (99.184) +2022-11-14 17:00:01,539 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0893 (0.0746) Prec@1 85.000 (88.180) Prec@5 100.000 (99.200) +2022-11-14 17:00:01,547 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0348 (0.0738) Prec@1 94.000 (88.294) Prec@5 100.000 (99.216) +2022-11-14 17:00:01,554 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0906 (0.0741) Prec@1 82.000 (88.173) Prec@5 99.000 (99.212) +2022-11-14 17:00:01,562 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0563 (0.0738) Prec@1 91.000 (88.226) Prec@5 100.000 (99.226) +2022-11-14 17:00:01,569 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0684 (0.0737) Prec@1 90.000 (88.259) Prec@5 99.000 (99.222) +2022-11-14 17:00:01,576 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0950 (0.0741) Prec@1 85.000 (88.200) Prec@5 100.000 (99.236) +2022-11-14 17:00:01,583 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0739) Prec@1 91.000 (88.250) Prec@5 99.000 (99.232) +2022-11-14 17:00:01,591 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0852 (0.0741) Prec@1 87.000 (88.228) Prec@5 99.000 (99.228) +2022-11-14 17:00:01,598 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0828 (0.0743) Prec@1 87.000 (88.207) Prec@5 98.000 (99.207) +2022-11-14 17:00:01,606 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1097 (0.0749) Prec@1 80.000 (88.068) Prec@5 100.000 (99.220) +2022-11-14 17:00:01,613 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0749) Prec@1 87.000 (88.050) Prec@5 100.000 (99.233) +2022-11-14 17:00:01,621 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0909 (0.0752) Prec@1 84.000 (87.984) Prec@5 99.000 (99.230) +2022-11-14 17:00:01,628 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0539 (0.0749) Prec@1 90.000 (88.016) Prec@5 99.000 (99.226) +2022-11-14 17:00:01,635 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0623 (0.0747) Prec@1 91.000 (88.063) Prec@5 99.000 (99.222) +2022-11-14 17:00:01,643 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0349 (0.0740) Prec@1 92.000 (88.125) Prec@5 99.000 (99.219) +2022-11-14 17:00:01,650 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0981 (0.0744) Prec@1 86.000 (88.092) Prec@5 99.000 (99.215) +2022-11-14 17:00:01,658 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0627 (0.0742) Prec@1 88.000 (88.091) Prec@5 99.000 (99.212) +2022-11-14 17:00:01,666 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0325 (0.0736) Prec@1 94.000 (88.179) Prec@5 100.000 (99.224) +2022-11-14 17:00:01,673 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0608 (0.0734) Prec@1 91.000 (88.221) Prec@5 100.000 (99.235) +2022-11-14 17:00:01,680 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0721 (0.0734) Prec@1 89.000 (88.232) Prec@5 99.000 (99.232) +2022-11-14 17:00:01,688 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0680 (0.0733) Prec@1 89.000 (88.243) Prec@5 100.000 (99.243) +2022-11-14 17:00:01,695 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1085 (0.0738) Prec@1 85.000 (88.197) Prec@5 99.000 (99.239) +2022-11-14 17:00:01,702 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0693 (0.0737) Prec@1 90.000 (88.222) Prec@5 99.000 (99.236) +2022-11-14 17:00:01,710 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0551 (0.0735) Prec@1 92.000 (88.274) Prec@5 99.000 (99.233) +2022-11-14 17:00:01,717 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0596 (0.0733) Prec@1 89.000 (88.284) Prec@5 100.000 (99.243) +2022-11-14 17:00:01,725 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1023 (0.0737) Prec@1 85.000 (88.240) Prec@5 99.000 (99.240) +2022-11-14 17:00:01,732 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0488 (0.0734) Prec@1 91.000 (88.276) Prec@5 100.000 (99.250) +2022-11-14 17:00:01,739 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0734) Prec@1 88.000 (88.273) Prec@5 99.000 (99.247) +2022-11-14 17:00:01,747 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0793 (0.0735) Prec@1 88.000 (88.269) Prec@5 99.000 (99.244) +2022-11-14 17:00:01,754 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0772 (0.0736) Prec@1 88.000 (88.266) Prec@5 100.000 (99.253) +2022-11-14 17:00:01,761 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0583 (0.0734) Prec@1 90.000 (88.287) Prec@5 99.000 (99.250) +2022-11-14 17:00:01,769 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0735) Prec@1 85.000 (88.247) Prec@5 99.000 (99.247) +2022-11-14 17:00:01,776 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0957 (0.0738) Prec@1 86.000 (88.220) Prec@5 99.000 (99.244) +2022-11-14 17:00:01,784 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1027 (0.0741) Prec@1 84.000 (88.169) Prec@5 100.000 (99.253) +2022-11-14 17:00:01,791 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0835 (0.0742) Prec@1 89.000 (88.179) Prec@5 99.000 (99.250) +2022-11-14 17:00:01,799 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0720 (0.0742) Prec@1 89.000 (88.188) Prec@5 100.000 (99.259) +2022-11-14 17:00:01,807 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0940 (0.0744) Prec@1 85.000 (88.151) Prec@5 100.000 (99.267) +2022-11-14 17:00:01,814 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0633 (0.0743) Prec@1 91.000 (88.184) Prec@5 100.000 (99.276) +2022-11-14 17:00:01,821 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0963 (0.0746) Prec@1 87.000 (88.170) Prec@5 98.000 (99.261) +2022-11-14 17:00:01,829 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0746) Prec@1 88.000 (88.169) Prec@5 99.000 (99.258) +2022-11-14 17:00:01,837 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0724 (0.0746) Prec@1 89.000 (88.178) Prec@5 100.000 (99.267) +2022-11-14 17:00:01,844 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0630 (0.0744) Prec@1 90.000 (88.198) Prec@5 100.000 (99.275) +2022-11-14 17:00:01,852 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0333 (0.0740) Prec@1 96.000 (88.283) Prec@5 100.000 (99.283) +2022-11-14 17:00:01,859 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0928 (0.0742) Prec@1 85.000 (88.247) Prec@5 100.000 (99.290) +2022-11-14 17:00:01,867 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0818 (0.0743) Prec@1 84.000 (88.202) Prec@5 100.000 (99.298) +2022-11-14 17:00:01,874 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0968 (0.0745) Prec@1 85.000 (88.168) Prec@5 99.000 (99.295) +2022-11-14 17:00:01,882 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0728 (0.0745) Prec@1 90.000 (88.188) Prec@5 99.000 (99.292) +2022-11-14 17:00:01,889 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0290 (0.0740) Prec@1 94.000 (88.247) Prec@5 99.000 (99.289) +2022-11-14 17:00:01,896 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1015 (0.0743) Prec@1 83.000 (88.194) Prec@5 97.000 (99.265) +2022-11-14 17:00:01,903 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1193 (0.0748) Prec@1 82.000 (88.131) Prec@5 99.000 (99.263) +2022-11-14 17:00:01,911 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0674 (0.0747) Prec@1 89.000 (88.140) Prec@5 99.000 (99.260) +2022-11-14 17:00:01,972 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:00:02,598 Epoch: [436][0/500] Time 0.022 (0.022) Data 0.247 (0.247) Loss 0.0217 (0.0217) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:02,789 Epoch: [436][10/500] Time 0.017 (0.017) Data 0.002 (0.024) Loss 0.0286 (0.0251) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:02,975 Epoch: [436][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0148 (0.0217) Prec@1 97.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 17:00:03,165 Epoch: [436][30/500] Time 0.016 (0.017) Data 0.002 (0.009) Loss 0.0439 (0.0272) Prec@1 92.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:00:03,354 Epoch: [436][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0269 (0.0272) Prec@1 95.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:00:03,539 Epoch: [436][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0255 (0.0269) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:00:03,724 Epoch: [436][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0304 (0.0274) Prec@1 96.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 17:00:03,910 Epoch: [436][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0327 (0.0280) Prec@1 92.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 17:00:04,098 Epoch: [436][80/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0162 (0.0267) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:00:04,284 Epoch: [436][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0353 (0.0276) Prec@1 94.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:00:04,469 Epoch: [436][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0239 (0.0273) Prec@1 96.000 (95.273) Prec@5 100.000 (100.000) +2022-11-14 17:00:04,658 Epoch: [436][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0193 (0.0266) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:00:04,844 Epoch: [436][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0403 (0.0276) Prec@1 94.000 (95.154) Prec@5 100.000 (100.000) +2022-11-14 17:00:05,031 Epoch: [436][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0328 (0.0280) Prec@1 94.000 (95.071) Prec@5 100.000 (100.000) +2022-11-14 17:00:05,222 Epoch: [436][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0392 (0.0288) Prec@1 91.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 17:00:05,495 Epoch: [436][150/500] Time 0.026 (0.017) Data 0.001 (0.003) Loss 0.0231 (0.0284) Prec@1 97.000 (94.938) Prec@5 100.000 (100.000) +2022-11-14 17:00:05,795 Epoch: [436][160/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0253 (0.0282) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:06,100 Epoch: [436][170/500] Time 0.029 (0.018) Data 0.002 (0.003) Loss 0.0285 (0.0282) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:06,403 Epoch: [436][180/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0386 (0.0288) Prec@1 93.000 (94.895) Prec@5 100.000 (100.000) +2022-11-14 17:00:06,708 Epoch: [436][190/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0268 (0.0287) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:07,010 Epoch: [436][200/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0435 (0.0294) Prec@1 93.000 (94.905) Prec@5 97.000 (99.857) +2022-11-14 17:00:07,316 Epoch: [436][210/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0153 (0.0287) Prec@1 98.000 (95.045) Prec@5 100.000 (99.864) +2022-11-14 17:00:07,605 Epoch: [436][220/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0214 (0.0284) Prec@1 97.000 (95.130) Prec@5 100.000 (99.870) +2022-11-14 17:00:07,895 Epoch: [436][230/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0211 (0.0281) Prec@1 96.000 (95.167) Prec@5 100.000 (99.875) +2022-11-14 17:00:08,187 Epoch: [436][240/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0507 (0.0290) Prec@1 93.000 (95.080) Prec@5 100.000 (99.880) +2022-11-14 17:00:08,479 Epoch: [436][250/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0313 (0.0291) Prec@1 94.000 (95.038) Prec@5 100.000 (99.885) +2022-11-14 17:00:08,772 Epoch: [436][260/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0446 (0.0297) Prec@1 93.000 (94.963) Prec@5 100.000 (99.889) +2022-11-14 17:00:09,066 Epoch: [436][270/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0233 (0.0295) Prec@1 97.000 (95.036) Prec@5 100.000 (99.893) +2022-11-14 17:00:09,355 Epoch: [436][280/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0323 (0.0296) Prec@1 95.000 (95.034) Prec@5 100.000 (99.897) +2022-11-14 17:00:09,644 Epoch: [436][290/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0373 (0.0298) Prec@1 94.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 17:00:09,941 Epoch: [436][300/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0473 (0.0304) Prec@1 91.000 (94.871) Prec@5 100.000 (99.903) +2022-11-14 17:00:10,236 Epoch: [436][310/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0232 (0.0302) Prec@1 96.000 (94.906) Prec@5 100.000 (99.906) +2022-11-14 17:00:10,528 Epoch: [436][320/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0273 (0.0301) Prec@1 96.000 (94.939) Prec@5 100.000 (99.909) +2022-11-14 17:00:10,823 Epoch: [436][330/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0315 (0.0301) Prec@1 94.000 (94.912) Prec@5 100.000 (99.912) +2022-11-14 17:00:11,118 Epoch: [436][340/500] Time 0.033 (0.022) Data 0.002 (0.002) Loss 0.0156 (0.0297) Prec@1 99.000 (95.029) Prec@5 100.000 (99.914) +2022-11-14 17:00:11,409 Epoch: [436][350/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0247 (0.0296) Prec@1 95.000 (95.028) Prec@5 100.000 (99.917) +2022-11-14 17:00:11,698 Epoch: [436][360/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0494 (0.0301) Prec@1 92.000 (94.946) Prec@5 100.000 (99.919) +2022-11-14 17:00:11,990 Epoch: [436][370/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0457 (0.0305) Prec@1 91.000 (94.842) Prec@5 98.000 (99.868) +2022-11-14 17:00:12,276 Epoch: [436][380/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0382 (0.0307) Prec@1 94.000 (94.821) Prec@5 100.000 (99.872) +2022-11-14 17:00:12,567 Epoch: [436][390/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0114 (0.0302) Prec@1 99.000 (94.925) Prec@5 100.000 (99.875) +2022-11-14 17:00:12,862 Epoch: [436][400/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0315 (0.0302) Prec@1 95.000 (94.927) Prec@5 100.000 (99.878) +2022-11-14 17:00:13,155 Epoch: [436][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0232 (0.0301) Prec@1 97.000 (94.976) Prec@5 100.000 (99.881) +2022-11-14 17:00:13,454 Epoch: [436][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0362 (0.0302) Prec@1 94.000 (94.953) Prec@5 100.000 (99.884) +2022-11-14 17:00:13,746 Epoch: [436][430/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0591 (0.0309) Prec@1 88.000 (94.795) Prec@5 100.000 (99.886) +2022-11-14 17:00:14,038 Epoch: [436][440/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0371 (0.0310) Prec@1 94.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 17:00:14,322 Epoch: [436][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0189 (0.0308) Prec@1 96.000 (94.804) Prec@5 100.000 (99.891) +2022-11-14 17:00:14,613 Epoch: [436][460/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0374 (0.0309) Prec@1 93.000 (94.766) Prec@5 100.000 (99.894) +2022-11-14 17:00:14,903 Epoch: [436][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0285 (0.0308) Prec@1 97.000 (94.812) Prec@5 100.000 (99.896) +2022-11-14 17:00:15,202 Epoch: [436][480/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0220 (0.0307) Prec@1 97.000 (94.857) Prec@5 100.000 (99.898) +2022-11-14 17:00:15,486 Epoch: [436][490/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0153 (0.0304) Prec@1 98.000 (94.920) Prec@5 100.000 (99.900) +2022-11-14 17:00:15,744 Epoch: [436][499/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0144 (0.0300) Prec@1 98.000 (94.980) Prec@5 100.000 (99.902) +2022-11-14 17:00:16,041 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0496 (0.0496) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:16,051 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0633 (0.0565) Prec@1 91.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:00:16,058 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0583) Prec@1 88.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:00:16,068 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0617) Prec@1 90.000 (89.750) Prec@5 100.000 (100.000) +2022-11-14 17:00:16,075 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0613) Prec@1 89.000 (89.600) Prec@5 99.000 (99.800) +2022-11-14 17:00:16,083 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0478 (0.0590) Prec@1 92.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 17:00:16,090 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0581) Prec@1 92.000 (90.286) Prec@5 100.000 (99.714) +2022-11-14 17:00:16,099 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0622) Prec@1 86.000 (89.750) Prec@5 99.000 (99.625) +2022-11-14 17:00:16,106 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0651) Prec@1 85.000 (89.222) Prec@5 100.000 (99.667) +2022-11-14 17:00:16,113 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0652) Prec@1 89.000 (89.200) Prec@5 98.000 (99.500) +2022-11-14 17:00:16,120 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0637) Prec@1 92.000 (89.455) Prec@5 100.000 (99.545) +2022-11-14 17:00:16,128 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0667) Prec@1 84.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 17:00:16,135 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0654) Prec@1 92.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 17:00:16,143 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0660) Prec@1 86.000 (89.000) Prec@5 98.000 (99.429) +2022-11-14 17:00:16,151 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0665) Prec@1 87.000 (88.867) Prec@5 99.000 (99.400) +2022-11-14 17:00:16,158 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0662) Prec@1 91.000 (89.000) Prec@5 99.000 (99.375) +2022-11-14 17:00:16,166 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0651) Prec@1 93.000 (89.235) Prec@5 99.000 (99.353) +2022-11-14 17:00:16,174 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0676) Prec@1 84.000 (88.944) Prec@5 100.000 (99.389) +2022-11-14 17:00:16,181 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0681) Prec@1 88.000 (88.895) Prec@5 99.000 (99.368) +2022-11-14 17:00:16,189 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0692) Prec@1 84.000 (88.650) Prec@5 98.000 (99.300) +2022-11-14 17:00:16,196 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0691) Prec@1 88.000 (88.619) Prec@5 99.000 (99.286) +2022-11-14 17:00:16,204 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0694) Prec@1 88.000 (88.591) Prec@5 99.000 (99.273) +2022-11-14 17:00:16,212 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0713) Prec@1 84.000 (88.391) Prec@5 99.000 (99.261) +2022-11-14 17:00:16,219 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0715) Prec@1 86.000 (88.292) Prec@5 99.000 (99.250) +2022-11-14 17:00:16,227 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0722) Prec@1 87.000 (88.240) Prec@5 100.000 (99.280) +2022-11-14 17:00:16,234 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0733) Prec@1 85.000 (88.115) Prec@5 97.000 (99.192) +2022-11-14 17:00:16,242 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0722) Prec@1 93.000 (88.296) Prec@5 100.000 (99.222) +2022-11-14 17:00:16,249 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0717) Prec@1 90.000 (88.357) Prec@5 100.000 (99.250) +2022-11-14 17:00:16,257 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0717) Prec@1 88.000 (88.345) Prec@5 98.000 (99.207) +2022-11-14 17:00:16,265 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0715) Prec@1 91.000 (88.433) Prec@5 99.000 (99.200) +2022-11-14 17:00:16,272 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0716) Prec@1 87.000 (88.387) Prec@5 100.000 (99.226) +2022-11-14 17:00:16,281 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0712) Prec@1 90.000 (88.438) Prec@5 99.000 (99.219) +2022-11-14 17:00:16,289 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0716) Prec@1 83.000 (88.273) Prec@5 100.000 (99.242) +2022-11-14 17:00:16,296 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0717) Prec@1 87.000 (88.235) Prec@5 99.000 (99.235) +2022-11-14 17:00:16,304 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0720) Prec@1 86.000 (88.171) Prec@5 98.000 (99.200) +2022-11-14 17:00:16,312 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0719) Prec@1 90.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 17:00:16,319 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0721) Prec@1 87.000 (88.189) Prec@5 98.000 (99.189) +2022-11-14 17:00:16,327 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0729) Prec@1 85.000 (88.105) Prec@5 99.000 (99.184) +2022-11-14 17:00:16,335 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0464 (0.0722) Prec@1 94.000 (88.256) Prec@5 99.000 (99.179) +2022-11-14 17:00:16,342 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0720) Prec@1 90.000 (88.300) Prec@5 100.000 (99.200) +2022-11-14 17:00:16,350 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0722) Prec@1 86.000 (88.244) Prec@5 99.000 (99.195) +2022-11-14 17:00:16,358 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0724) Prec@1 89.000 (88.262) Prec@5 99.000 (99.190) +2022-11-14 17:00:16,365 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0720) Prec@1 93.000 (88.372) Prec@5 99.000 (99.186) +2022-11-14 17:00:16,372 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0719) Prec@1 92.000 (88.455) Prec@5 97.000 (99.136) +2022-11-14 17:00:16,380 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0573 (0.0716) Prec@1 91.000 (88.511) Prec@5 100.000 (99.156) +2022-11-14 17:00:16,387 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0961 (0.0721) Prec@1 87.000 (88.478) Prec@5 99.000 (99.152) +2022-11-14 17:00:16,395 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0580 (0.0718) Prec@1 90.000 (88.511) Prec@5 99.000 (99.149) +2022-11-14 17:00:16,403 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1103 (0.0726) Prec@1 84.000 (88.417) Prec@5 97.000 (99.104) +2022-11-14 17:00:16,410 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0426 (0.0720) Prec@1 95.000 (88.551) Prec@5 100.000 (99.122) +2022-11-14 17:00:16,418 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0725) Prec@1 85.000 (88.480) Prec@5 100.000 (99.140) +2022-11-14 17:00:16,425 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0723) Prec@1 88.000 (88.471) Prec@5 99.000 (99.137) +2022-11-14 17:00:16,433 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0837 (0.0726) Prec@1 86.000 (88.423) Prec@5 100.000 (99.154) +2022-11-14 17:00:16,440 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0541 (0.0722) Prec@1 90.000 (88.453) Prec@5 100.000 (99.170) +2022-11-14 17:00:16,448 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0801 (0.0724) Prec@1 87.000 (88.426) Prec@5 98.000 (99.148) +2022-11-14 17:00:16,456 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0905 (0.0727) Prec@1 87.000 (88.400) Prec@5 100.000 (99.164) +2022-11-14 17:00:16,463 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0726) Prec@1 89.000 (88.411) Prec@5 100.000 (99.179) +2022-11-14 17:00:16,471 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0762 (0.0726) Prec@1 87.000 (88.386) Prec@5 99.000 (99.175) +2022-11-14 17:00:16,478 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0819 (0.0728) Prec@1 87.000 (88.362) Prec@5 100.000 (99.190) +2022-11-14 17:00:16,486 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0731) Prec@1 85.000 (88.305) Prec@5 100.000 (99.203) +2022-11-14 17:00:16,493 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0732) Prec@1 88.000 (88.300) Prec@5 100.000 (99.217) +2022-11-14 17:00:16,501 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0730) Prec@1 91.000 (88.344) Prec@5 100.000 (99.230) +2022-11-14 17:00:16,508 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0601 (0.0728) Prec@1 88.000 (88.339) Prec@5 100.000 (99.242) +2022-11-14 17:00:16,516 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0598 (0.0726) Prec@1 87.000 (88.317) Prec@5 100.000 (99.254) +2022-11-14 17:00:16,523 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0359 (0.0720) Prec@1 92.000 (88.375) Prec@5 100.000 (99.266) +2022-11-14 17:00:16,531 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0882 (0.0723) Prec@1 87.000 (88.354) Prec@5 98.000 (99.246) +2022-11-14 17:00:16,539 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0960 (0.0726) Prec@1 83.000 (88.273) Prec@5 100.000 (99.258) +2022-11-14 17:00:16,546 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0517 (0.0723) Prec@1 92.000 (88.328) Prec@5 100.000 (99.269) +2022-11-14 17:00:16,554 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0659 (0.0722) Prec@1 91.000 (88.368) Prec@5 100.000 (99.279) +2022-11-14 17:00:16,561 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0611 (0.0721) Prec@1 90.000 (88.391) Prec@5 99.000 (99.275) +2022-11-14 17:00:16,569 Test: [69/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0894 (0.0723) Prec@1 85.000 (88.343) Prec@5 98.000 (99.257) +2022-11-14 17:00:16,576 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1044 (0.0728) Prec@1 85.000 (88.296) Prec@5 98.000 (99.239) +2022-11-14 17:00:16,584 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0726) Prec@1 91.000 (88.333) Prec@5 99.000 (99.236) +2022-11-14 17:00:16,591 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0414 (0.0722) Prec@1 95.000 (88.425) Prec@5 100.000 (99.247) +2022-11-14 17:00:16,599 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0478 (0.0718) Prec@1 93.000 (88.486) Prec@5 100.000 (99.257) +2022-11-14 17:00:16,606 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1100 (0.0723) Prec@1 81.000 (88.387) Prec@5 98.000 (99.240) +2022-11-14 17:00:16,614 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0538 (0.0721) Prec@1 92.000 (88.434) Prec@5 99.000 (99.237) +2022-11-14 17:00:16,621 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0722) Prec@1 86.000 (88.403) Prec@5 99.000 (99.234) +2022-11-14 17:00:16,629 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0722) Prec@1 89.000 (88.410) Prec@5 97.000 (99.205) +2022-11-14 17:00:16,637 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0722) Prec@1 90.000 (88.430) Prec@5 100.000 (99.215) +2022-11-14 17:00:16,644 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0722) Prec@1 90.000 (88.450) Prec@5 100.000 (99.225) +2022-11-14 17:00:16,652 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0723) Prec@1 89.000 (88.457) Prec@5 100.000 (99.235) +2022-11-14 17:00:16,659 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0725) Prec@1 86.000 (88.427) Prec@5 100.000 (99.244) +2022-11-14 17:00:16,667 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0922 (0.0728) Prec@1 88.000 (88.422) Prec@5 99.000 (99.241) +2022-11-14 17:00:16,675 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0489 (0.0725) Prec@1 90.000 (88.440) Prec@5 99.000 (99.238) +2022-11-14 17:00:16,682 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0726) Prec@1 87.000 (88.424) Prec@5 100.000 (99.247) +2022-11-14 17:00:16,690 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1054 (0.0730) Prec@1 85.000 (88.384) Prec@5 98.000 (99.233) +2022-11-14 17:00:16,697 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 87.000 (88.368) Prec@5 100.000 (99.241) +2022-11-14 17:00:16,705 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0645 (0.0729) Prec@1 89.000 (88.375) Prec@5 98.000 (99.227) +2022-11-14 17:00:16,712 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0726 (0.0729) Prec@1 89.000 (88.382) Prec@5 99.000 (99.225) +2022-11-14 17:00:16,720 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0729) Prec@1 90.000 (88.400) Prec@5 98.000 (99.211) +2022-11-14 17:00:16,728 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0729) Prec@1 89.000 (88.407) Prec@5 100.000 (99.220) +2022-11-14 17:00:16,735 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0475 (0.0726) Prec@1 93.000 (88.457) Prec@5 99.000 (99.217) +2022-11-14 17:00:16,743 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0726) Prec@1 86.000 (88.430) Prec@5 100.000 (99.226) +2022-11-14 17:00:16,752 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0726) Prec@1 89.000 (88.436) Prec@5 100.000 (99.234) +2022-11-14 17:00:16,759 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0727) Prec@1 85.000 (88.400) Prec@5 98.000 (99.221) +2022-11-14 17:00:16,767 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0656 (0.0726) Prec@1 89.000 (88.406) Prec@5 100.000 (99.229) +2022-11-14 17:00:16,774 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0549 (0.0724) Prec@1 91.000 (88.433) Prec@5 99.000 (99.227) +2022-11-14 17:00:16,782 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0724) Prec@1 89.000 (88.439) Prec@5 99.000 (99.224) +2022-11-14 17:00:16,789 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1004 (0.0727) Prec@1 84.000 (88.394) Prec@5 99.000 (99.222) +2022-11-14 17:00:16,796 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0637 (0.0726) Prec@1 90.000 (88.410) Prec@5 100.000 (99.230) +2022-11-14 17:00:16,851 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:00:17,641 Epoch: [437][0/500] Time 0.022 (0.022) Data 0.228 (0.228) Loss 0.0348 (0.0348) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 17:00:17,834 Epoch: [437][10/500] Time 0.018 (0.018) Data 0.001 (0.022) Loss 0.0424 (0.0386) Prec@1 93.000 (94.000) Prec@5 100.000 (99.500) +2022-11-14 17:00:18,020 Epoch: [437][20/500] Time 0.016 (0.017) Data 0.002 (0.012) Loss 0.0175 (0.0316) Prec@1 97.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 17:00:18,220 Epoch: [437][30/500] Time 0.020 (0.017) Data 0.001 (0.009) Loss 0.0386 (0.0333) Prec@1 93.000 (94.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:18,411 Epoch: [437][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0207 (0.0308) Prec@1 98.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:00:18,602 Epoch: [437][50/500] Time 0.019 (0.017) Data 0.002 (0.006) Loss 0.0260 (0.0300) Prec@1 96.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 17:00:18,791 Epoch: [437][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0297 (0.0300) Prec@1 94.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 17:00:18,987 Epoch: [437][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0259 (0.0295) Prec@1 96.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 17:00:19,190 Epoch: [437][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0503 (0.0318) Prec@1 93.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:00:19,384 Epoch: [437][90/500] Time 0.020 (0.017) Data 0.002 (0.004) Loss 0.0370 (0.0323) Prec@1 94.000 (94.900) Prec@5 100.000 (99.900) +2022-11-14 17:00:19,583 Epoch: [437][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0364 (0.0327) Prec@1 93.000 (94.727) Prec@5 100.000 (99.909) +2022-11-14 17:00:19,775 Epoch: [437][110/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0318 (0.0326) Prec@1 94.000 (94.667) Prec@5 100.000 (99.917) +2022-11-14 17:00:19,963 Epoch: [437][120/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0341 (0.0327) Prec@1 95.000 (94.692) Prec@5 100.000 (99.923) +2022-11-14 17:00:20,171 Epoch: [437][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0374 (0.0330) Prec@1 92.000 (94.500) Prec@5 100.000 (99.929) +2022-11-14 17:00:20,359 Epoch: [437][140/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0298 (0.0328) Prec@1 95.000 (94.533) Prec@5 100.000 (99.933) +2022-11-14 17:00:20,547 Epoch: [437][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0259 (0.0324) Prec@1 96.000 (94.625) Prec@5 100.000 (99.938) +2022-11-14 17:00:20,736 Epoch: [437][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0226 (0.0318) Prec@1 96.000 (94.706) Prec@5 100.000 (99.941) +2022-11-14 17:00:20,926 Epoch: [437][170/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0244 (0.0314) Prec@1 97.000 (94.833) Prec@5 100.000 (99.944) +2022-11-14 17:00:21,130 Epoch: [437][180/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0400 (0.0319) Prec@1 93.000 (94.737) Prec@5 100.000 (99.947) +2022-11-14 17:00:21,326 Epoch: [437][190/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0368 (0.0321) Prec@1 93.000 (94.650) Prec@5 99.000 (99.900) +2022-11-14 17:00:21,524 Epoch: [437][200/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0387 (0.0324) Prec@1 94.000 (94.619) Prec@5 100.000 (99.905) +2022-11-14 17:00:21,728 Epoch: [437][210/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0264 (0.0321) Prec@1 95.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 17:00:21,924 Epoch: [437][220/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0204 (0.0316) Prec@1 96.000 (94.696) Prec@5 99.000 (99.870) +2022-11-14 17:00:22,131 Epoch: [437][230/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0350 (0.0318) Prec@1 94.000 (94.667) Prec@5 99.000 (99.833) +2022-11-14 17:00:22,327 Epoch: [437][240/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0555 (0.0327) Prec@1 90.000 (94.480) Prec@5 100.000 (99.840) +2022-11-14 17:00:22,527 Epoch: [437][250/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0326 (0.0327) Prec@1 95.000 (94.500) Prec@5 100.000 (99.846) +2022-11-14 17:00:22,723 Epoch: [437][260/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0132 (0.0320) Prec@1 97.000 (94.593) Prec@5 100.000 (99.852) +2022-11-14 17:00:22,922 Epoch: [437][270/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.0183 (0.0315) Prec@1 97.000 (94.679) Prec@5 100.000 (99.857) +2022-11-14 17:00:23,118 Epoch: [437][280/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0068 (0.0307) Prec@1 99.000 (94.828) Prec@5 100.000 (99.862) +2022-11-14 17:00:23,304 Epoch: [437][290/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.0317 (0.0307) Prec@1 95.000 (94.833) Prec@5 100.000 (99.867) +2022-11-14 17:00:23,492 Epoch: [437][300/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0451 (0.0312) Prec@1 93.000 (94.774) Prec@5 100.000 (99.871) +2022-11-14 17:00:23,683 Epoch: [437][310/500] Time 0.017 (0.017) Data 0.002 (0.002) Loss 0.0252 (0.0310) Prec@1 95.000 (94.781) Prec@5 100.000 (99.875) +2022-11-14 17:00:23,873 Epoch: [437][320/500] Time 0.019 (0.017) Data 0.001 (0.002) Loss 0.0259 (0.0308) Prec@1 96.000 (94.818) Prec@5 100.000 (99.879) +2022-11-14 17:00:24,126 Epoch: [437][330/500] Time 0.026 (0.017) Data 0.002 (0.002) Loss 0.0197 (0.0305) Prec@1 97.000 (94.882) Prec@5 100.000 (99.882) +2022-11-14 17:00:24,388 Epoch: [437][340/500] Time 0.025 (0.017) Data 0.002 (0.002) Loss 0.0223 (0.0303) Prec@1 96.000 (94.914) Prec@5 100.000 (99.886) +2022-11-14 17:00:24,648 Epoch: [437][350/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0544 (0.0309) Prec@1 89.000 (94.750) Prec@5 100.000 (99.889) +2022-11-14 17:00:24,908 Epoch: [437][360/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0239 (0.0307) Prec@1 96.000 (94.784) Prec@5 100.000 (99.892) +2022-11-14 17:00:25,170 Epoch: [437][370/500] Time 0.022 (0.018) Data 0.003 (0.002) Loss 0.0292 (0.0307) Prec@1 95.000 (94.789) Prec@5 100.000 (99.895) +2022-11-14 17:00:25,429 Epoch: [437][380/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0261 (0.0306) Prec@1 96.000 (94.821) Prec@5 100.000 (99.897) +2022-11-14 17:00:25,688 Epoch: [437][390/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0181 (0.0303) Prec@1 97.000 (94.875) Prec@5 100.000 (99.900) +2022-11-14 17:00:25,946 Epoch: [437][400/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0099 (0.0298) Prec@1 99.000 (94.976) Prec@5 100.000 (99.902) +2022-11-14 17:00:26,210 Epoch: [437][410/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0185 (0.0295) Prec@1 98.000 (95.048) Prec@5 100.000 (99.905) +2022-11-14 17:00:26,474 Epoch: [437][420/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0175 (0.0292) Prec@1 97.000 (95.093) Prec@5 100.000 (99.907) +2022-11-14 17:00:26,738 Epoch: [437][430/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0378 (0.0294) Prec@1 96.000 (95.114) Prec@5 100.000 (99.909) +2022-11-14 17:00:27,001 Epoch: [437][440/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0339 (0.0295) Prec@1 94.000 (95.089) Prec@5 99.000 (99.889) +2022-11-14 17:00:27,263 Epoch: [437][450/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0392 (0.0297) Prec@1 93.000 (95.043) Prec@5 100.000 (99.891) +2022-11-14 17:00:27,529 Epoch: [437][460/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0267 (0.0297) Prec@1 96.000 (95.064) Prec@5 100.000 (99.894) +2022-11-14 17:00:27,789 Epoch: [437][470/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0187 (0.0294) Prec@1 97.000 (95.104) Prec@5 100.000 (99.896) +2022-11-14 17:00:28,047 Epoch: [437][480/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0168 (0.0292) Prec@1 97.000 (95.143) Prec@5 100.000 (99.898) +2022-11-14 17:00:28,308 Epoch: [437][490/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0348 (0.0293) Prec@1 95.000 (95.140) Prec@5 99.000 (99.880) +2022-11-14 17:00:28,547 Epoch: [437][499/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0113 (0.0289) Prec@1 99.000 (95.216) Prec@5 100.000 (99.882) +2022-11-14 17:00:28,846 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0763 (0.0763) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:28,854 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0789) Prec@1 89.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:28,861 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0768) Prec@1 87.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:00:28,871 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0731) Prec@1 90.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 17:00:28,878 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0784) Prec@1 84.000 (87.400) Prec@5 99.000 (99.600) +2022-11-14 17:00:28,885 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0737) Prec@1 92.000 (88.167) Prec@5 100.000 (99.667) +2022-11-14 17:00:28,892 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0734) Prec@1 90.000 (88.429) Prec@5 100.000 (99.714) +2022-11-14 17:00:28,901 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0748) Prec@1 87.000 (88.250) Prec@5 100.000 (99.750) +2022-11-14 17:00:28,908 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0771) Prec@1 84.000 (87.778) Prec@5 99.000 (99.667) +2022-11-14 17:00:28,915 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0771) Prec@1 88.000 (87.800) Prec@5 99.000 (99.600) +2022-11-14 17:00:28,923 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0754) Prec@1 90.000 (88.000) Prec@5 100.000 (99.636) +2022-11-14 17:00:28,930 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0767) Prec@1 86.000 (87.833) Prec@5 99.000 (99.583) +2022-11-14 17:00:28,937 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0432 (0.0741) Prec@1 92.000 (88.154) Prec@5 100.000 (99.615) +2022-11-14 17:00:28,945 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0739) Prec@1 89.000 (88.214) Prec@5 99.000 (99.571) +2022-11-14 17:00:28,953 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0744) Prec@1 88.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 17:00:28,960 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0741) Prec@1 92.000 (88.438) Prec@5 98.000 (99.500) +2022-11-14 17:00:28,968 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0470 (0.0725) Prec@1 93.000 (88.706) Prec@5 99.000 (99.471) +2022-11-14 17:00:28,975 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0736) Prec@1 84.000 (88.444) Prec@5 100.000 (99.500) +2022-11-14 17:00:28,983 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0746) Prec@1 87.000 (88.368) Prec@5 99.000 (99.474) +2022-11-14 17:00:28,990 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1095 (0.0764) Prec@1 83.000 (88.100) Prec@5 98.000 (99.400) +2022-11-14 17:00:28,998 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0768) Prec@1 86.000 (88.000) Prec@5 99.000 (99.381) +2022-11-14 17:00:29,005 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0773) Prec@1 86.000 (87.909) Prec@5 98.000 (99.318) +2022-11-14 17:00:29,013 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0784) Prec@1 83.000 (87.696) Prec@5 99.000 (99.304) +2022-11-14 17:00:29,021 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0783) Prec@1 88.000 (87.708) Prec@5 99.000 (99.292) +2022-11-14 17:00:29,028 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0785) Prec@1 85.000 (87.600) Prec@5 100.000 (99.320) +2022-11-14 17:00:29,036 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0796) Prec@1 83.000 (87.423) Prec@5 97.000 (99.231) +2022-11-14 17:00:29,044 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0372 (0.0780) Prec@1 94.000 (87.667) Prec@5 100.000 (99.259) +2022-11-14 17:00:29,051 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0778) Prec@1 90.000 (87.750) Prec@5 100.000 (99.286) +2022-11-14 17:00:29,059 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0775) Prec@1 90.000 (87.828) Prec@5 99.000 (99.276) +2022-11-14 17:00:29,067 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0776) Prec@1 88.000 (87.833) Prec@5 99.000 (99.267) +2022-11-14 17:00:29,074 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0630 (0.0771) Prec@1 90.000 (87.903) Prec@5 99.000 (99.258) +2022-11-14 17:00:29,083 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0815 (0.0772) Prec@1 88.000 (87.906) Prec@5 100.000 (99.281) +2022-11-14 17:00:29,091 Test: [32/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0768 (0.0772) Prec@1 87.000 (87.879) Prec@5 100.000 (99.303) +2022-11-14 17:00:29,099 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0720 (0.0771) Prec@1 88.000 (87.882) Prec@5 99.000 (99.294) +2022-11-14 17:00:29,107 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0768) Prec@1 89.000 (87.914) Prec@5 99.000 (99.286) +2022-11-14 17:00:29,114 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0762) Prec@1 92.000 (88.028) Prec@5 100.000 (99.306) +2022-11-14 17:00:29,122 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0760) Prec@1 88.000 (88.027) Prec@5 98.000 (99.270) +2022-11-14 17:00:29,130 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0766) Prec@1 83.000 (87.895) Prec@5 100.000 (99.289) +2022-11-14 17:00:29,137 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0765) Prec@1 91.000 (87.974) Prec@5 99.000 (99.282) +2022-11-14 17:00:29,145 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0764) Prec@1 89.000 (88.000) Prec@5 99.000 (99.275) +2022-11-14 17:00:29,153 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0853 (0.0767) Prec@1 85.000 (87.927) Prec@5 100.000 (99.293) +2022-11-14 17:00:29,161 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0759 (0.0766) Prec@1 87.000 (87.905) Prec@5 100.000 (99.310) +2022-11-14 17:00:29,168 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0443 (0.0759) Prec@1 93.000 (88.023) Prec@5 100.000 (99.326) +2022-11-14 17:00:29,176 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0759) Prec@1 87.000 (88.000) Prec@5 100.000 (99.341) +2022-11-14 17:00:29,184 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0688 (0.0757) Prec@1 88.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 17:00:29,191 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0991 (0.0762) Prec@1 84.000 (87.913) Prec@5 99.000 (99.326) +2022-11-14 17:00:29,199 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0604 (0.0759) Prec@1 89.000 (87.936) Prec@5 100.000 (99.340) +2022-11-14 17:00:29,206 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1040 (0.0765) Prec@1 86.000 (87.896) Prec@5 99.000 (99.333) +2022-11-14 17:00:29,214 Test: [48/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0443 (0.0758) Prec@1 94.000 (88.020) Prec@5 100.000 (99.347) +2022-11-14 17:00:29,222 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1003 (0.0763) Prec@1 86.000 (87.980) Prec@5 100.000 (99.360) +2022-11-14 17:00:29,229 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0496 (0.0758) Prec@1 92.000 (88.059) Prec@5 100.000 (99.373) +2022-11-14 17:00:29,237 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0757) Prec@1 87.000 (88.038) Prec@5 100.000 (99.385) +2022-11-14 17:00:29,244 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0720 (0.0757) Prec@1 88.000 (88.038) Prec@5 99.000 (99.377) +2022-11-14 17:00:29,252 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0859 (0.0759) Prec@1 87.000 (88.019) Prec@5 98.000 (99.352) +2022-11-14 17:00:29,259 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1200 (0.0767) Prec@1 81.000 (87.891) Prec@5 100.000 (99.364) +2022-11-14 17:00:29,267 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0668 (0.0765) Prec@1 88.000 (87.893) Prec@5 98.000 (99.339) +2022-11-14 17:00:29,274 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0764) Prec@1 87.000 (87.877) Prec@5 100.000 (99.351) +2022-11-14 17:00:29,282 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0587 (0.0761) Prec@1 92.000 (87.948) Prec@5 100.000 (99.362) +2022-11-14 17:00:29,289 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0860 (0.0763) Prec@1 86.000 (87.915) Prec@5 100.000 (99.373) +2022-11-14 17:00:29,298 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0763) Prec@1 84.000 (87.850) Prec@5 100.000 (99.383) +2022-11-14 17:00:29,305 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0803 (0.0763) Prec@1 89.000 (87.869) Prec@5 98.000 (99.361) +2022-11-14 17:00:29,313 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0762) Prec@1 89.000 (87.887) Prec@5 100.000 (99.371) +2022-11-14 17:00:29,320 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0582 (0.0759) Prec@1 89.000 (87.905) Prec@5 100.000 (99.381) +2022-11-14 17:00:29,328 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0448 (0.0754) Prec@1 93.000 (87.984) Prec@5 99.000 (99.375) +2022-11-14 17:00:29,336 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0914 (0.0757) Prec@1 86.000 (87.954) Prec@5 100.000 (99.385) +2022-11-14 17:00:29,343 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0848 (0.0758) Prec@1 88.000 (87.955) Prec@5 97.000 (99.348) +2022-11-14 17:00:29,351 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0439 (0.0753) Prec@1 91.000 (88.000) Prec@5 100.000 (99.358) +2022-11-14 17:00:29,358 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0699 (0.0752) Prec@1 89.000 (88.015) Prec@5 98.000 (99.338) +2022-11-14 17:00:29,366 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0917 (0.0755) Prec@1 84.000 (87.957) Prec@5 99.000 (99.333) +2022-11-14 17:00:29,373 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0758) Prec@1 85.000 (87.914) Prec@5 99.000 (99.329) +2022-11-14 17:00:29,381 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0936 (0.0760) Prec@1 84.000 (87.859) Prec@5 100.000 (99.338) +2022-11-14 17:00:29,388 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0759) Prec@1 91.000 (87.903) Prec@5 99.000 (99.333) +2022-11-14 17:00:29,396 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0449 (0.0755) Prec@1 92.000 (87.959) Prec@5 100.000 (99.342) +2022-11-14 17:00:29,404 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0491 (0.0751) Prec@1 92.000 (88.014) Prec@5 100.000 (99.351) +2022-11-14 17:00:29,411 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1228 (0.0757) Prec@1 80.000 (87.907) Prec@5 98.000 (99.333) +2022-11-14 17:00:29,419 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0553 (0.0755) Prec@1 88.000 (87.908) Prec@5 100.000 (99.342) +2022-11-14 17:00:29,426 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0753) Prec@1 90.000 (87.935) Prec@5 100.000 (99.351) +2022-11-14 17:00:29,434 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0880 (0.0755) Prec@1 87.000 (87.923) Prec@5 98.000 (99.333) +2022-11-14 17:00:29,441 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0754) Prec@1 87.000 (87.911) Prec@5 100.000 (99.342) +2022-11-14 17:00:29,449 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0885 (0.0756) Prec@1 86.000 (87.888) Prec@5 99.000 (99.338) +2022-11-14 17:00:29,457 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1054 (0.0759) Prec@1 86.000 (87.864) Prec@5 98.000 (99.321) +2022-11-14 17:00:29,464 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0806 (0.0760) Prec@1 88.000 (87.866) Prec@5 100.000 (99.329) +2022-11-14 17:00:29,472 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0933 (0.0762) Prec@1 86.000 (87.843) Prec@5 98.000 (99.313) +2022-11-14 17:00:29,479 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0546 (0.0759) Prec@1 92.000 (87.893) Prec@5 99.000 (99.310) +2022-11-14 17:00:29,487 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0917 (0.0761) Prec@1 86.000 (87.871) Prec@5 99.000 (99.306) +2022-11-14 17:00:29,494 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0839 (0.0762) Prec@1 88.000 (87.872) Prec@5 99.000 (99.302) +2022-11-14 17:00:29,502 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0610 (0.0760) Prec@1 89.000 (87.885) Prec@5 100.000 (99.310) +2022-11-14 17:00:29,509 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0790 (0.0761) Prec@1 86.000 (87.864) Prec@5 98.000 (99.295) +2022-11-14 17:00:29,517 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0935 (0.0763) Prec@1 83.000 (87.809) Prec@5 100.000 (99.303) +2022-11-14 17:00:29,524 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0763) Prec@1 89.000 (87.822) Prec@5 99.000 (99.300) +2022-11-14 17:00:29,532 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0761) Prec@1 90.000 (87.846) Prec@5 100.000 (99.308) +2022-11-14 17:00:29,540 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0657 (0.0760) Prec@1 91.000 (87.880) Prec@5 99.000 (99.304) +2022-11-14 17:00:29,547 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0544 (0.0758) Prec@1 91.000 (87.914) Prec@5 100.000 (99.312) +2022-11-14 17:00:29,555 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0758) Prec@1 89.000 (87.926) Prec@5 99.000 (99.309) +2022-11-14 17:00:29,562 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0757) Prec@1 89.000 (87.937) Prec@5 100.000 (99.316) +2022-11-14 17:00:29,570 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0562 (0.0755) Prec@1 91.000 (87.969) Prec@5 99.000 (99.312) +2022-11-14 17:00:29,577 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0367 (0.0751) Prec@1 95.000 (88.041) Prec@5 100.000 (99.320) +2022-11-14 17:00:29,584 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0753) Prec@1 85.000 (88.010) Prec@5 98.000 (99.306) +2022-11-14 17:00:29,592 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1032 (0.0756) Prec@1 85.000 (87.980) Prec@5 100.000 (99.313) +2022-11-14 17:00:29,599 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1008 (0.0758) Prec@1 86.000 (87.960) Prec@5 99.000 (99.310) +2022-11-14 17:00:29,655 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:00:30,273 Epoch: [438][0/500] Time 0.021 (0.021) Data 0.235 (0.235) Loss 0.0291 (0.0291) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:30,466 Epoch: [438][10/500] Time 0.016 (0.017) Data 0.002 (0.023) Loss 0.0209 (0.0250) Prec@1 98.000 (96.500) Prec@5 99.000 (99.500) +2022-11-14 17:00:30,654 Epoch: [438][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0327 (0.0276) Prec@1 94.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 17:00:30,851 Epoch: [438][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0108 (0.0234) Prec@1 100.000 (96.750) Prec@5 100.000 (99.750) +2022-11-14 17:00:31,050 Epoch: [438][40/500] Time 0.022 (0.017) Data 0.001 (0.007) Loss 0.0241 (0.0235) Prec@1 95.000 (96.400) Prec@5 99.000 (99.600) +2022-11-14 17:00:31,251 Epoch: [438][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0195 (0.0228) Prec@1 97.000 (96.500) Prec@5 100.000 (99.667) +2022-11-14 17:00:31,438 Epoch: [438][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0290 (0.0237) Prec@1 94.000 (96.143) Prec@5 100.000 (99.714) +2022-11-14 17:00:31,625 Epoch: [438][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0481 (0.0268) Prec@1 91.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:31,825 Epoch: [438][80/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0275 (0.0268) Prec@1 96.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 17:00:32,013 Epoch: [438][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0270 (0.0269) Prec@1 96.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 17:00:32,203 Epoch: [438][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0390 (0.0280) Prec@1 94.000 (95.455) Prec@5 99.000 (99.727) +2022-11-14 17:00:32,391 Epoch: [438][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0206 (0.0273) Prec@1 96.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:32,578 Epoch: [438][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0247 (0.0271) Prec@1 96.000 (95.538) Prec@5 100.000 (99.769) +2022-11-14 17:00:32,764 Epoch: [438][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0403 (0.0281) Prec@1 94.000 (95.429) Prec@5 99.000 (99.714) +2022-11-14 17:00:32,952 Epoch: [438][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0275 (0.0280) Prec@1 96.000 (95.467) Prec@5 100.000 (99.733) +2022-11-14 17:00:33,153 Epoch: [438][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0300 (0.0282) Prec@1 96.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:33,342 Epoch: [438][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0424 (0.0290) Prec@1 94.000 (95.412) Prec@5 100.000 (99.765) +2022-11-14 17:00:33,545 Epoch: [438][170/500] Time 0.021 (0.017) Data 0.001 (0.003) Loss 0.0177 (0.0284) Prec@1 98.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 17:00:33,811 Epoch: [438][180/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0537 (0.0297) Prec@1 91.000 (95.316) Prec@5 99.000 (99.737) +2022-11-14 17:00:34,077 Epoch: [438][190/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0324 (0.0298) Prec@1 93.000 (95.200) Prec@5 100.000 (99.750) +2022-11-14 17:00:34,345 Epoch: [438][200/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0169 (0.0292) Prec@1 98.000 (95.333) Prec@5 100.000 (99.762) +2022-11-14 17:00:34,618 Epoch: [438][210/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0150 (0.0286) Prec@1 99.000 (95.500) Prec@5 100.000 (99.773) +2022-11-14 17:00:34,891 Epoch: [438][220/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0328 (0.0288) Prec@1 96.000 (95.522) Prec@5 100.000 (99.783) +2022-11-14 17:00:35,166 Epoch: [438][230/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0222 (0.0285) Prec@1 97.000 (95.583) Prec@5 100.000 (99.792) +2022-11-14 17:00:35,440 Epoch: [438][240/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0129 (0.0279) Prec@1 99.000 (95.720) Prec@5 100.000 (99.800) +2022-11-14 17:00:35,713 Epoch: [438][250/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0441 (0.0285) Prec@1 94.000 (95.654) Prec@5 100.000 (99.808) +2022-11-14 17:00:35,986 Epoch: [438][260/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0263 (0.0284) Prec@1 94.000 (95.593) Prec@5 100.000 (99.815) +2022-11-14 17:00:36,257 Epoch: [438][270/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0340 (0.0286) Prec@1 95.000 (95.571) Prec@5 100.000 (99.821) +2022-11-14 17:00:36,524 Epoch: [438][280/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0363 (0.0289) Prec@1 95.000 (95.552) Prec@5 99.000 (99.793) +2022-11-14 17:00:36,788 Epoch: [438][290/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0331 (0.0290) Prec@1 93.000 (95.467) Prec@5 100.000 (99.800) +2022-11-14 17:00:37,050 Epoch: [438][300/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.0212 (0.0288) Prec@1 97.000 (95.516) Prec@5 100.000 (99.806) +2022-11-14 17:00:37,312 Epoch: [438][310/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0195 (0.0285) Prec@1 98.000 (95.594) Prec@5 100.000 (99.812) +2022-11-14 17:00:37,582 Epoch: [438][320/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0443 (0.0289) Prec@1 91.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 17:00:37,852 Epoch: [438][330/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0390 (0.0292) Prec@1 96.000 (95.471) Prec@5 100.000 (99.824) +2022-11-14 17:00:38,124 Epoch: [438][340/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0492 (0.0298) Prec@1 93.000 (95.400) Prec@5 100.000 (99.829) +2022-11-14 17:00:38,392 Epoch: [438][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0261 (0.0297) Prec@1 95.000 (95.389) Prec@5 100.000 (99.833) +2022-11-14 17:00:38,660 Epoch: [438][360/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0223 (0.0295) Prec@1 96.000 (95.405) Prec@5 100.000 (99.838) +2022-11-14 17:00:38,926 Epoch: [438][370/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0575 (0.0302) Prec@1 91.000 (95.289) Prec@5 99.000 (99.816) +2022-11-14 17:00:39,191 Epoch: [438][380/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0292 (0.0302) Prec@1 96.000 (95.308) Prec@5 99.000 (99.795) +2022-11-14 17:00:39,454 Epoch: [438][390/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0279 (0.0302) Prec@1 94.000 (95.275) Prec@5 100.000 (99.800) +2022-11-14 17:00:39,718 Epoch: [438][400/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0487 (0.0306) Prec@1 91.000 (95.171) Prec@5 99.000 (99.780) +2022-11-14 17:00:39,982 Epoch: [438][410/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0181 (0.0303) Prec@1 97.000 (95.214) Prec@5 100.000 (99.786) +2022-11-14 17:00:40,241 Epoch: [438][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0173 (0.0300) Prec@1 96.000 (95.233) Prec@5 100.000 (99.791) +2022-11-14 17:00:40,504 Epoch: [438][430/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0243 (0.0299) Prec@1 97.000 (95.273) Prec@5 100.000 (99.795) +2022-11-14 17:00:40,772 Epoch: [438][440/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0142 (0.0295) Prec@1 98.000 (95.333) Prec@5 100.000 (99.800) +2022-11-14 17:00:41,037 Epoch: [438][450/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0142 (0.0292) Prec@1 98.000 (95.391) Prec@5 100.000 (99.804) +2022-11-14 17:00:41,305 Epoch: [438][460/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0248 (0.0291) Prec@1 97.000 (95.426) Prec@5 100.000 (99.809) +2022-11-14 17:00:41,567 Epoch: [438][470/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0477 (0.0295) Prec@1 91.000 (95.333) Prec@5 98.000 (99.771) +2022-11-14 17:00:41,829 Epoch: [438][480/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0513 (0.0299) Prec@1 91.000 (95.245) Prec@5 100.000 (99.776) +2022-11-14 17:00:42,097 Epoch: [438][490/500] Time 0.029 (0.021) Data 0.001 (0.002) Loss 0.0270 (0.0299) Prec@1 94.000 (95.220) Prec@5 100.000 (99.780) +2022-11-14 17:00:42,332 Epoch: [438][499/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0490 (0.0303) Prec@1 92.000 (95.157) Prec@5 98.000 (99.745) +2022-11-14 17:00:42,644 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0813 (0.0813) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:42,656 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0694 (0.0753) Prec@1 91.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:00:42,666 Test: [2/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0748 (0.0751) Prec@1 89.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 17:00:42,675 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0731) Prec@1 92.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 17:00:42,682 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0707) Prec@1 89.000 (89.400) Prec@5 100.000 (99.800) +2022-11-14 17:00:42,692 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0393 (0.0655) Prec@1 93.000 (90.000) Prec@5 100.000 (99.833) +2022-11-14 17:00:42,701 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0713 (0.0663) Prec@1 90.000 (90.000) Prec@5 99.000 (99.714) +2022-11-14 17:00:42,709 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0816 (0.0682) Prec@1 85.000 (89.375) Prec@5 100.000 (99.750) +2022-11-14 17:00:42,716 Test: [8/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0698) Prec@1 88.000 (89.222) Prec@5 98.000 (99.556) +2022-11-14 17:00:42,726 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0821 (0.0710) Prec@1 89.000 (89.200) Prec@5 99.000 (99.500) +2022-11-14 17:00:42,735 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0600 (0.0700) Prec@1 90.000 (89.273) Prec@5 100.000 (99.545) +2022-11-14 17:00:42,743 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0953 (0.0721) Prec@1 87.000 (89.083) Prec@5 99.000 (99.500) +2022-11-14 17:00:42,751 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0716) Prec@1 91.000 (89.231) Prec@5 100.000 (99.538) +2022-11-14 17:00:42,761 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0713) Prec@1 90.000 (89.286) Prec@5 98.000 (99.429) +2022-11-14 17:00:42,771 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0778 (0.0717) Prec@1 86.000 (89.067) Prec@5 99.000 (99.400) +2022-11-14 17:00:42,778 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0784 (0.0721) Prec@1 87.000 (88.938) Prec@5 100.000 (99.438) +2022-11-14 17:00:42,786 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0709) Prec@1 91.000 (89.059) Prec@5 98.000 (99.353) +2022-11-14 17:00:42,796 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0721) Prec@1 88.000 (89.000) Prec@5 100.000 (99.389) +2022-11-14 17:00:42,806 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0732) Prec@1 85.000 (88.789) Prec@5 99.000 (99.368) +2022-11-14 17:00:42,814 Test: [19/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0752) Prec@1 81.000 (88.400) Prec@5 97.000 (99.250) +2022-11-14 17:00:42,822 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0751) Prec@1 88.000 (88.381) Prec@5 99.000 (99.238) +2022-11-14 17:00:42,831 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0751) Prec@1 88.000 (88.364) Prec@5 99.000 (99.227) +2022-11-14 17:00:42,841 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0762) Prec@1 85.000 (88.217) Prec@5 99.000 (99.217) +2022-11-14 17:00:42,848 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0759) Prec@1 89.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 17:00:42,856 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0759) Prec@1 90.000 (88.320) Prec@5 100.000 (99.280) +2022-11-14 17:00:42,867 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0763) Prec@1 86.000 (88.231) Prec@5 98.000 (99.231) +2022-11-14 17:00:42,877 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0753) Prec@1 93.000 (88.407) Prec@5 100.000 (99.259) +2022-11-14 17:00:42,885 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0752) Prec@1 91.000 (88.500) Prec@5 100.000 (99.286) +2022-11-14 17:00:42,893 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0749) Prec@1 88.000 (88.483) Prec@5 99.000 (99.276) +2022-11-14 17:00:42,903 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0684 (0.0747) Prec@1 89.000 (88.500) Prec@5 100.000 (99.300) +2022-11-14 17:00:42,913 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0747) Prec@1 86.000 (88.419) Prec@5 99.000 (99.290) +2022-11-14 17:00:42,921 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0739) Prec@1 92.000 (88.531) Prec@5 100.000 (99.312) +2022-11-14 17:00:42,929 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0737) Prec@1 88.000 (88.515) Prec@5 100.000 (99.333) +2022-11-14 17:00:42,939 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0995 (0.0745) Prec@1 84.000 (88.382) Prec@5 99.000 (99.324) +2022-11-14 17:00:42,949 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0744) Prec@1 89.000 (88.400) Prec@5 98.000 (99.286) +2022-11-14 17:00:42,956 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0741) Prec@1 92.000 (88.500) Prec@5 99.000 (99.278) +2022-11-14 17:00:42,964 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0742) Prec@1 87.000 (88.459) Prec@5 99.000 (99.270) +2022-11-14 17:00:42,974 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0744) Prec@1 86.000 (88.395) Prec@5 100.000 (99.289) +2022-11-14 17:00:42,984 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0487 (0.0738) Prec@1 93.000 (88.513) Prec@5 99.000 (99.282) +2022-11-14 17:00:42,991 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0734) Prec@1 90.000 (88.550) Prec@5 99.000 (99.275) +2022-11-14 17:00:42,999 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1103 (0.0743) Prec@1 84.000 (88.439) Prec@5 97.000 (99.220) +2022-11-14 17:00:43,009 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0742) Prec@1 88.000 (88.429) Prec@5 100.000 (99.238) +2022-11-14 17:00:43,019 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0522 (0.0737) Prec@1 92.000 (88.512) Prec@5 99.000 (99.233) +2022-11-14 17:00:43,027 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0739) Prec@1 89.000 (88.523) Prec@5 99.000 (99.227) +2022-11-14 17:00:43,035 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0733) Prec@1 91.000 (88.578) Prec@5 100.000 (99.244) +2022-11-14 17:00:43,045 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0741) Prec@1 80.000 (88.391) Prec@5 100.000 (99.261) +2022-11-14 17:00:43,055 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0741) Prec@1 88.000 (88.383) Prec@5 100.000 (99.277) +2022-11-14 17:00:43,062 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0944 (0.0745) Prec@1 83.000 (88.271) Prec@5 98.000 (99.250) +2022-11-14 17:00:43,070 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0739) Prec@1 90.000 (88.306) Prec@5 100.000 (99.265) +2022-11-14 17:00:43,081 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0745) Prec@1 84.000 (88.220) Prec@5 100.000 (99.280) +2022-11-14 17:00:43,091 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0744) Prec@1 89.000 (88.235) Prec@5 100.000 (99.294) +2022-11-14 17:00:43,099 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0744) Prec@1 88.000 (88.231) Prec@5 100.000 (99.308) +2022-11-14 17:00:43,107 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0749) Prec@1 85.000 (88.170) Prec@5 99.000 (99.302) +2022-11-14 17:00:43,117 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0583 (0.0746) Prec@1 90.000 (88.204) Prec@5 99.000 (99.296) +2022-11-14 17:00:43,126 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0749) Prec@1 83.000 (88.109) Prec@5 99.000 (99.291) +2022-11-14 17:00:43,134 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0747) Prec@1 91.000 (88.161) Prec@5 99.000 (99.286) +2022-11-14 17:00:43,142 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0747) Prec@1 87.000 (88.140) Prec@5 100.000 (99.298) +2022-11-14 17:00:43,152 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0746) Prec@1 89.000 (88.155) Prec@5 100.000 (99.310) +2022-11-14 17:00:43,162 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0749) Prec@1 85.000 (88.102) Prec@5 100.000 (99.322) +2022-11-14 17:00:43,170 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0751) Prec@1 87.000 (88.083) Prec@5 100.000 (99.333) +2022-11-14 17:00:43,177 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0748) Prec@1 92.000 (88.148) Prec@5 99.000 (99.328) +2022-11-14 17:00:43,185 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0745) Prec@1 89.000 (88.161) Prec@5 100.000 (99.339) +2022-11-14 17:00:43,192 Test: [62/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0679 (0.0744) Prec@1 88.000 (88.159) Prec@5 100.000 (99.349) +2022-11-14 17:00:43,200 Test: [63/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0499 (0.0740) Prec@1 93.000 (88.234) Prec@5 99.000 (99.344) +2022-11-14 17:00:43,208 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0743) Prec@1 85.000 (88.185) Prec@5 99.000 (99.338) +2022-11-14 17:00:43,215 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0741) Prec@1 91.000 (88.227) Prec@5 98.000 (99.318) +2022-11-14 17:00:43,223 Test: [66/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0311 (0.0735) Prec@1 95.000 (88.328) Prec@5 99.000 (99.313) +2022-11-14 17:00:43,230 Test: [67/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0734) Prec@1 90.000 (88.353) Prec@5 100.000 (99.324) +2022-11-14 17:00:43,238 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0731) Prec@1 89.000 (88.362) Prec@5 99.000 (99.319) +2022-11-14 17:00:43,245 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0731) Prec@1 92.000 (88.414) Prec@5 100.000 (99.329) +2022-11-14 17:00:43,253 Test: [70/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0734) Prec@1 85.000 (88.366) Prec@5 100.000 (99.338) +2022-11-14 17:00:43,261 Test: [71/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0731) Prec@1 90.000 (88.389) Prec@5 99.000 (99.333) +2022-11-14 17:00:43,268 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0729) Prec@1 93.000 (88.452) Prec@5 100.000 (99.342) +2022-11-14 17:00:43,276 Test: [73/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0464 (0.0725) Prec@1 92.000 (88.500) Prec@5 100.000 (99.351) +2022-11-14 17:00:43,283 Test: [74/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0725) Prec@1 87.000 (88.480) Prec@5 100.000 (99.360) +2022-11-14 17:00:43,291 Test: [75/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0725) Prec@1 89.000 (88.487) Prec@5 100.000 (99.368) +2022-11-14 17:00:43,299 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0884 (0.0727) Prec@1 87.000 (88.468) Prec@5 98.000 (99.351) +2022-11-14 17:00:43,306 Test: [77/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0730) Prec@1 84.000 (88.410) Prec@5 97.000 (99.321) +2022-11-14 17:00:43,314 Test: [78/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0730) Prec@1 88.000 (88.405) Prec@5 100.000 (99.329) +2022-11-14 17:00:43,321 Test: [79/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0731) Prec@1 84.000 (88.350) Prec@5 100.000 (99.338) +2022-11-14 17:00:43,329 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0733) Prec@1 85.000 (88.309) Prec@5 99.000 (99.333) +2022-11-14 17:00:43,337 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0732) Prec@1 90.000 (88.329) Prec@5 98.000 (99.317) +2022-11-14 17:00:43,344 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1066 (0.0736) Prec@1 82.000 (88.253) Prec@5 100.000 (99.325) +2022-11-14 17:00:43,352 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0737) Prec@1 88.000 (88.250) Prec@5 100.000 (99.333) +2022-11-14 17:00:43,359 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0737) Prec@1 89.000 (88.259) Prec@5 99.000 (99.329) +2022-11-14 17:00:43,367 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0741) Prec@1 85.000 (88.221) Prec@5 99.000 (99.326) +2022-11-14 17:00:43,374 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0744) Prec@1 82.000 (88.149) Prec@5 96.000 (99.287) +2022-11-14 17:00:43,383 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0744) Prec@1 86.000 (88.125) Prec@5 99.000 (99.284) +2022-11-14 17:00:43,391 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0743) Prec@1 88.000 (88.124) Prec@5 99.000 (99.281) +2022-11-14 17:00:43,399 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0743) Prec@1 88.000 (88.122) Prec@5 99.000 (99.278) +2022-11-14 17:00:43,406 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0740) Prec@1 94.000 (88.187) Prec@5 100.000 (99.286) +2022-11-14 17:00:43,414 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0740) Prec@1 88.000 (88.185) Prec@5 99.000 (99.283) +2022-11-14 17:00:43,421 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0740) Prec@1 87.000 (88.172) Prec@5 99.000 (99.280) +2022-11-14 17:00:43,429 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0740) Prec@1 89.000 (88.181) Prec@5 100.000 (99.287) +2022-11-14 17:00:43,436 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0743) Prec@1 84.000 (88.137) Prec@5 99.000 (99.284) +2022-11-14 17:00:43,444 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0740) Prec@1 93.000 (88.188) Prec@5 100.000 (99.292) +2022-11-14 17:00:43,451 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0736) Prec@1 94.000 (88.247) Prec@5 99.000 (99.289) +2022-11-14 17:00:43,459 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0737) Prec@1 87.000 (88.235) Prec@5 97.000 (99.265) +2022-11-14 17:00:43,466 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0741) Prec@1 83.000 (88.182) Prec@5 99.000 (99.263) +2022-11-14 17:00:43,474 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0742) Prec@1 84.000 (88.140) Prec@5 99.000 (99.260) +2022-11-14 17:00:43,545 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:00:44,325 Epoch: [439][0/500] Time 0.024 (0.024) Data 0.236 (0.236) Loss 0.0445 (0.0445) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:44,520 Epoch: [439][10/500] Time 0.014 (0.018) Data 0.002 (0.023) Loss 0.0186 (0.0315) Prec@1 99.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 17:00:44,706 Epoch: [439][20/500] Time 0.016 (0.017) Data 0.002 (0.013) Loss 0.0173 (0.0268) Prec@1 98.000 (96.667) Prec@5 100.000 (99.667) +2022-11-14 17:00:44,893 Epoch: [439][30/500] Time 0.016 (0.017) Data 0.002 (0.009) Loss 0.0226 (0.0257) Prec@1 96.000 (96.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:45,079 Epoch: [439][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0413 (0.0289) Prec@1 94.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 17:00:45,267 Epoch: [439][50/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0138 (0.0264) Prec@1 98.000 (96.333) Prec@5 100.000 (99.833) +2022-11-14 17:00:45,455 Epoch: [439][60/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0369 (0.0279) Prec@1 95.000 (96.143) Prec@5 100.000 (99.857) +2022-11-14 17:00:45,641 Epoch: [439][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0293 (0.0280) Prec@1 95.000 (96.000) Prec@5 100.000 (99.875) +2022-11-14 17:00:45,826 Epoch: [439][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0306 (0.0283) Prec@1 96.000 (96.000) Prec@5 100.000 (99.889) +2022-11-14 17:00:46,012 Epoch: [439][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0634 (0.0318) Prec@1 91.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:00:46,200 Epoch: [439][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0268 (0.0314) Prec@1 95.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:00:46,384 Epoch: [439][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0332 (0.0315) Prec@1 94.000 (95.333) Prec@5 99.000 (99.833) +2022-11-14 17:00:46,569 Epoch: [439][120/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0180 (0.0305) Prec@1 98.000 (95.538) Prec@5 100.000 (99.846) +2022-11-14 17:00:46,752 Epoch: [439][130/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0177 (0.0296) Prec@1 96.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:00:46,937 Epoch: [439][140/500] Time 0.017 (0.016) Data 0.001 (0.003) Loss 0.0293 (0.0296) Prec@1 96.000 (95.600) Prec@5 100.000 (99.867) +2022-11-14 17:00:47,124 Epoch: [439][150/500] Time 0.017 (0.016) Data 0.001 (0.003) Loss 0.0265 (0.0294) Prec@1 96.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 17:00:47,309 Epoch: [439][160/500] Time 0.017 (0.016) Data 0.001 (0.003) Loss 0.0182 (0.0287) Prec@1 97.000 (95.706) Prec@5 100.000 (99.882) +2022-11-14 17:00:47,494 Epoch: [439][170/500] Time 0.019 (0.016) Data 0.001 (0.003) Loss 0.0185 (0.0281) Prec@1 96.000 (95.722) Prec@5 100.000 (99.889) +2022-11-14 17:00:47,711 Epoch: [439][180/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0401 (0.0288) Prec@1 94.000 (95.632) Prec@5 100.000 (99.895) +2022-11-14 17:00:47,895 Epoch: [439][190/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0310 (0.0289) Prec@1 94.000 (95.550) Prec@5 100.000 (99.900) +2022-11-14 17:00:48,082 Epoch: [439][200/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0390 (0.0294) Prec@1 92.000 (95.381) Prec@5 98.000 (99.810) +2022-11-14 17:00:48,277 Epoch: [439][210/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.0283 (0.0293) Prec@1 94.000 (95.318) Prec@5 100.000 (99.818) +2022-11-14 17:00:48,528 Epoch: [439][220/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0230 (0.0290) Prec@1 97.000 (95.391) Prec@5 100.000 (99.826) +2022-11-14 17:00:48,784 Epoch: [439][230/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0326 (0.0292) Prec@1 95.000 (95.375) Prec@5 100.000 (99.833) +2022-11-14 17:00:49,040 Epoch: [439][240/500] Time 0.023 (0.017) Data 0.002 (0.002) Loss 0.0239 (0.0290) Prec@1 97.000 (95.440) Prec@5 100.000 (99.840) +2022-11-14 17:00:49,300 Epoch: [439][250/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0160 (0.0285) Prec@1 98.000 (95.538) Prec@5 100.000 (99.846) +2022-11-14 17:00:49,560 Epoch: [439][260/500] Time 0.025 (0.018) Data 0.001 (0.002) Loss 0.0343 (0.0287) Prec@1 95.000 (95.519) Prec@5 100.000 (99.852) +2022-11-14 17:00:49,821 Epoch: [439][270/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0156 (0.0282) Prec@1 98.000 (95.607) Prec@5 100.000 (99.857) +2022-11-14 17:00:50,080 Epoch: [439][280/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0157 (0.0278) Prec@1 98.000 (95.690) Prec@5 100.000 (99.862) +2022-11-14 17:00:50,339 Epoch: [439][290/500] Time 0.024 (0.018) Data 0.001 (0.002) Loss 0.0280 (0.0278) Prec@1 95.000 (95.667) Prec@5 100.000 (99.867) +2022-11-14 17:00:50,597 Epoch: [439][300/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0374 (0.0281) Prec@1 92.000 (95.548) Prec@5 99.000 (99.839) +2022-11-14 17:00:50,854 Epoch: [439][310/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0201 (0.0279) Prec@1 97.000 (95.594) Prec@5 100.000 (99.844) +2022-11-14 17:00:51,120 Epoch: [439][320/500] Time 0.031 (0.019) Data 0.002 (0.002) Loss 0.0320 (0.0280) Prec@1 93.000 (95.515) Prec@5 100.000 (99.848) +2022-11-14 17:00:51,376 Epoch: [439][330/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0102 (0.0275) Prec@1 98.000 (95.588) Prec@5 100.000 (99.853) +2022-11-14 17:00:51,635 Epoch: [439][340/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0316 (0.0276) Prec@1 95.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:00:51,898 Epoch: [439][350/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0361 (0.0278) Prec@1 94.000 (95.528) Prec@5 99.000 (99.833) +2022-11-14 17:00:52,161 Epoch: [439][360/500] Time 0.028 (0.019) Data 0.002 (0.002) Loss 0.0343 (0.0280) Prec@1 94.000 (95.486) Prec@5 100.000 (99.838) +2022-11-14 17:00:52,418 Epoch: [439][370/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0298 (0.0280) Prec@1 95.000 (95.474) Prec@5 99.000 (99.816) +2022-11-14 17:00:52,678 Epoch: [439][380/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0265 (0.0280) Prec@1 95.000 (95.462) Prec@5 100.000 (99.821) +2022-11-14 17:00:52,938 Epoch: [439][390/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0497 (0.0285) Prec@1 89.000 (95.300) Prec@5 100.000 (99.825) +2022-11-14 17:00:53,199 Epoch: [439][400/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0356 (0.0287) Prec@1 95.000 (95.293) Prec@5 98.000 (99.780) +2022-11-14 17:00:53,459 Epoch: [439][410/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0311 (0.0288) Prec@1 95.000 (95.286) Prec@5 100.000 (99.786) +2022-11-14 17:00:53,717 Epoch: [439][420/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0210 (0.0286) Prec@1 97.000 (95.326) Prec@5 100.000 (99.791) +2022-11-14 17:00:53,977 Epoch: [439][430/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0268 (0.0286) Prec@1 96.000 (95.341) Prec@5 99.000 (99.773) +2022-11-14 17:00:54,232 Epoch: [439][440/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0164 (0.0283) Prec@1 98.000 (95.400) Prec@5 100.000 (99.778) +2022-11-14 17:00:54,490 Epoch: [439][450/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.0223 (0.0282) Prec@1 95.000 (95.391) Prec@5 100.000 (99.783) +2022-11-14 17:00:54,748 Epoch: [439][460/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0423 (0.0285) Prec@1 94.000 (95.362) Prec@5 100.000 (99.787) +2022-11-14 17:00:55,005 Epoch: [439][470/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.0274 (0.0284) Prec@1 96.000 (95.375) Prec@5 100.000 (99.792) +2022-11-14 17:00:55,266 Epoch: [439][480/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0200 (0.0283) Prec@1 96.000 (95.388) Prec@5 100.000 (99.796) +2022-11-14 17:00:55,527 Epoch: [439][490/500] Time 0.020 (0.020) Data 0.003 (0.002) Loss 0.0309 (0.0283) Prec@1 94.000 (95.360) Prec@5 99.000 (99.780) +2022-11-14 17:00:55,756 Epoch: [439][499/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0423 (0.0286) Prec@1 94.000 (95.333) Prec@5 100.000 (99.784) +2022-11-14 17:00:56,059 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0585 (0.0585) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:56,071 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0587 (0.0586) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:00:56,085 Test: [2/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0821 (0.0664) Prec@1 84.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 17:00:56,095 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0758 (0.0688) Prec@1 86.000 (87.750) Prec@5 100.000 (100.000) +2022-11-14 17:00:56,102 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0675) Prec@1 90.000 (88.200) Prec@5 99.000 (99.800) +2022-11-14 17:00:56,111 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0443 (0.0637) Prec@1 94.000 (89.167) Prec@5 99.000 (99.667) +2022-11-14 17:00:56,120 Test: [6/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0613 (0.0633) Prec@1 93.000 (89.714) Prec@5 99.000 (99.571) +2022-11-14 17:00:56,128 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0832 (0.0658) Prec@1 88.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:00:56,135 Test: [8/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0677 (0.0660) Prec@1 89.000 (89.444) Prec@5 99.000 (99.444) +2022-11-14 17:00:56,145 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0803 (0.0674) Prec@1 88.000 (89.300) Prec@5 99.000 (99.400) +2022-11-14 17:00:56,155 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0653 (0.0672) Prec@1 90.000 (89.364) Prec@5 100.000 (99.455) +2022-11-14 17:00:56,162 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0665) Prec@1 92.000 (89.583) Prec@5 99.000 (99.417) +2022-11-14 17:00:56,170 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0566 (0.0657) Prec@1 92.000 (89.769) Prec@5 100.000 (99.462) +2022-11-14 17:00:56,179 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0660) Prec@1 89.000 (89.714) Prec@5 100.000 (99.500) +2022-11-14 17:00:56,190 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0662) Prec@1 89.000 (89.667) Prec@5 98.000 (99.400) +2022-11-14 17:00:56,197 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0674) Prec@1 85.000 (89.375) Prec@5 100.000 (99.438) +2022-11-14 17:00:56,205 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0657) Prec@1 94.000 (89.647) Prec@5 98.000 (99.353) +2022-11-14 17:00:56,215 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0679) Prec@1 82.000 (89.222) Prec@5 100.000 (99.389) +2022-11-14 17:00:56,225 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0682) Prec@1 89.000 (89.211) Prec@5 99.000 (99.368) +2022-11-14 17:00:56,232 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0685) Prec@1 91.000 (89.300) Prec@5 98.000 (99.300) +2022-11-14 17:00:56,240 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0688) Prec@1 89.000 (89.286) Prec@5 99.000 (99.286) +2022-11-14 17:00:56,250 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0696) Prec@1 85.000 (89.091) Prec@5 99.000 (99.273) +2022-11-14 17:00:56,260 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0712) Prec@1 82.000 (88.783) Prec@5 99.000 (99.261) +2022-11-14 17:00:56,267 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0831 (0.0717) Prec@1 88.000 (88.750) Prec@5 100.000 (99.292) +2022-11-14 17:00:56,275 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0936 (0.0725) Prec@1 84.000 (88.560) Prec@5 100.000 (99.320) +2022-11-14 17:00:56,285 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0728) Prec@1 89.000 (88.577) Prec@5 99.000 (99.308) +2022-11-14 17:00:56,295 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0721) Prec@1 92.000 (88.704) Prec@5 100.000 (99.333) +2022-11-14 17:00:56,303 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0687 (0.0720) Prec@1 89.000 (88.714) Prec@5 100.000 (99.357) +2022-11-14 17:00:56,310 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0725) Prec@1 85.000 (88.586) Prec@5 97.000 (99.276) +2022-11-14 17:00:56,320 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0722) Prec@1 90.000 (88.633) Prec@5 99.000 (99.267) +2022-11-14 17:00:56,331 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0724) Prec@1 88.000 (88.613) Prec@5 100.000 (99.290) +2022-11-14 17:00:56,338 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0641 (0.0722) Prec@1 91.000 (88.688) Prec@5 99.000 (99.281) +2022-11-14 17:00:56,345 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0721) Prec@1 86.000 (88.606) Prec@5 100.000 (99.303) +2022-11-14 17:00:56,355 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0833 (0.0724) Prec@1 86.000 (88.529) Prec@5 99.000 (99.294) +2022-11-14 17:00:56,365 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1086 (0.0735) Prec@1 82.000 (88.343) Prec@5 97.000 (99.229) +2022-11-14 17:00:56,373 Test: [35/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0735) Prec@1 89.000 (88.361) Prec@5 99.000 (99.222) +2022-11-14 17:00:56,381 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0738) Prec@1 87.000 (88.324) Prec@5 100.000 (99.243) +2022-11-14 17:00:56,390 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1207 (0.0750) Prec@1 81.000 (88.132) Prec@5 99.000 (99.237) +2022-11-14 17:00:56,400 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0745) Prec@1 93.000 (88.256) Prec@5 99.000 (99.231) +2022-11-14 17:00:56,408 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0732 (0.0745) Prec@1 88.000 (88.250) Prec@5 99.000 (99.225) +2022-11-14 17:00:56,415 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1027 (0.0752) Prec@1 84.000 (88.146) Prec@5 99.000 (99.220) +2022-11-14 17:00:56,425 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0755) Prec@1 86.000 (88.095) Prec@5 99.000 (99.214) +2022-11-14 17:00:56,435 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0751) Prec@1 91.000 (88.163) Prec@5 99.000 (99.209) +2022-11-14 17:00:56,442 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0753) Prec@1 89.000 (88.182) Prec@5 98.000 (99.182) +2022-11-14 17:00:56,450 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0483 (0.0747) Prec@1 91.000 (88.244) Prec@5 100.000 (99.200) +2022-11-14 17:00:56,460 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0788 (0.0748) Prec@1 87.000 (88.217) Prec@5 99.000 (99.196) +2022-11-14 17:00:56,468 Test: [46/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0750) Prec@1 88.000 (88.213) Prec@5 100.000 (99.213) +2022-11-14 17:00:56,475 Test: [47/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0975 (0.0754) Prec@1 84.000 (88.125) Prec@5 99.000 (99.208) +2022-11-14 17:00:56,482 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0749) Prec@1 91.000 (88.184) Prec@5 100.000 (99.224) +2022-11-14 17:00:56,490 Test: [49/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1064 (0.0755) Prec@1 83.000 (88.080) Prec@5 99.000 (99.220) +2022-11-14 17:00:56,497 Test: [50/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0752) Prec@1 90.000 (88.118) Prec@5 100.000 (99.235) +2022-11-14 17:00:56,505 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0754) Prec@1 82.000 (88.000) Prec@5 99.000 (99.231) +2022-11-14 17:00:56,512 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0754) Prec@1 86.000 (87.962) Prec@5 100.000 (99.245) +2022-11-14 17:00:56,520 Test: [53/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0752) Prec@1 89.000 (87.981) Prec@5 100.000 (99.259) +2022-11-14 17:00:56,528 Test: [54/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0755) Prec@1 84.000 (87.909) Prec@5 100.000 (99.273) +2022-11-14 17:00:56,536 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0758) Prec@1 86.000 (87.875) Prec@5 99.000 (99.268) +2022-11-14 17:00:56,543 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0758) Prec@1 88.000 (87.877) Prec@5 100.000 (99.281) +2022-11-14 17:00:56,551 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0752) Prec@1 93.000 (87.966) Prec@5 100.000 (99.293) +2022-11-14 17:00:56,559 Test: [58/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0914 (0.0755) Prec@1 87.000 (87.949) Prec@5 99.000 (99.288) +2022-11-14 17:00:56,566 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0759) Prec@1 84.000 (87.883) Prec@5 99.000 (99.283) +2022-11-14 17:00:56,574 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0758) Prec@1 90.000 (87.918) Prec@5 99.000 (99.279) +2022-11-14 17:00:56,582 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0759) Prec@1 86.000 (87.887) Prec@5 98.000 (99.258) +2022-11-14 17:00:56,589 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0756) Prec@1 91.000 (87.937) Prec@5 100.000 (99.270) +2022-11-14 17:00:56,597 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0752) Prec@1 92.000 (88.000) Prec@5 99.000 (99.266) +2022-11-14 17:00:56,604 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0753) Prec@1 88.000 (88.000) Prec@5 100.000 (99.277) +2022-11-14 17:00:56,612 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0752) Prec@1 87.000 (87.985) Prec@5 99.000 (99.273) +2022-11-14 17:00:56,619 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0748) Prec@1 94.000 (88.075) Prec@5 100.000 (99.284) +2022-11-14 17:00:56,627 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0745) Prec@1 91.000 (88.118) Prec@5 100.000 (99.294) +2022-11-14 17:00:56,634 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0748) Prec@1 86.000 (88.087) Prec@5 99.000 (99.290) +2022-11-14 17:00:56,642 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0750) Prec@1 84.000 (88.029) Prec@5 98.000 (99.271) +2022-11-14 17:00:56,649 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0754) Prec@1 85.000 (87.986) Prec@5 98.000 (99.254) +2022-11-14 17:00:56,657 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0753) Prec@1 88.000 (87.986) Prec@5 99.000 (99.250) +2022-11-14 17:00:56,664 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0750) Prec@1 90.000 (88.014) Prec@5 100.000 (99.260) +2022-11-14 17:00:56,672 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0402 (0.0745) Prec@1 95.000 (88.108) Prec@5 100.000 (99.270) +2022-11-14 17:00:56,680 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1214 (0.0752) Prec@1 81.000 (88.013) Prec@5 100.000 (99.280) +2022-11-14 17:00:56,687 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0751) Prec@1 90.000 (88.039) Prec@5 98.000 (99.263) +2022-11-14 17:00:56,695 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0752) Prec@1 84.000 (87.987) Prec@5 99.000 (99.260) +2022-11-14 17:00:56,702 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0754) Prec@1 87.000 (87.974) Prec@5 98.000 (99.244) +2022-11-14 17:00:56,710 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0755) Prec@1 85.000 (87.937) Prec@5 100.000 (99.253) +2022-11-14 17:00:56,718 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0755) Prec@1 86.000 (87.912) Prec@5 100.000 (99.263) +2022-11-14 17:00:56,725 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0756) Prec@1 87.000 (87.901) Prec@5 97.000 (99.235) +2022-11-14 17:00:56,733 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0758) Prec@1 86.000 (87.878) Prec@5 100.000 (99.244) +2022-11-14 17:00:56,740 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0759) Prec@1 86.000 (87.855) Prec@5 100.000 (99.253) +2022-11-14 17:00:56,748 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0759) Prec@1 88.000 (87.857) Prec@5 99.000 (99.250) +2022-11-14 17:00:56,756 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0760) Prec@1 86.000 (87.835) Prec@5 100.000 (99.259) +2022-11-14 17:00:56,763 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0764) Prec@1 81.000 (87.756) Prec@5 99.000 (99.256) +2022-11-14 17:00:56,771 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0764) Prec@1 88.000 (87.759) Prec@5 100.000 (99.264) +2022-11-14 17:00:56,779 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0765) Prec@1 86.000 (87.739) Prec@5 98.000 (99.250) +2022-11-14 17:00:56,786 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0764) Prec@1 88.000 (87.742) Prec@5 100.000 (99.258) +2022-11-14 17:00:56,794 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0766) Prec@1 86.000 (87.722) Prec@5 100.000 (99.267) +2022-11-14 17:00:56,801 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0765) Prec@1 89.000 (87.736) Prec@5 100.000 (99.275) +2022-11-14 17:00:56,809 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0762) Prec@1 92.000 (87.783) Prec@5 100.000 (99.283) +2022-11-14 17:00:56,816 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0762) Prec@1 88.000 (87.785) Prec@5 100.000 (99.290) +2022-11-14 17:00:56,824 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0764) Prec@1 86.000 (87.766) Prec@5 98.000 (99.277) +2022-11-14 17:00:56,831 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0763) Prec@1 90.000 (87.789) Prec@5 100.000 (99.284) +2022-11-14 17:00:56,839 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0763) Prec@1 88.000 (87.792) Prec@5 98.000 (99.271) +2022-11-14 17:00:56,846 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0761) Prec@1 89.000 (87.804) Prec@5 99.000 (99.268) +2022-11-14 17:00:56,853 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0763) Prec@1 86.000 (87.786) Prec@5 98.000 (99.255) +2022-11-14 17:00:56,861 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0765) Prec@1 84.000 (87.747) Prec@5 97.000 (99.232) +2022-11-14 17:00:56,868 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0763) Prec@1 90.000 (87.770) Prec@5 99.000 (99.230) +2022-11-14 17:00:56,924 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:00:57,543 Epoch: [440][0/500] Time 0.025 (0.025) Data 0.235 (0.235) Loss 0.0267 (0.0267) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:57,756 Epoch: [440][10/500] Time 0.022 (0.019) Data 0.001 (0.023) Loss 0.0116 (0.0191) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:00:57,960 Epoch: [440][20/500] Time 0.021 (0.019) Data 0.002 (0.013) Loss 0.0193 (0.0192) Prec@1 97.000 (97.000) Prec@5 99.000 (99.667) +2022-11-14 17:00:58,169 Epoch: [440][30/500] Time 0.020 (0.019) Data 0.001 (0.009) Loss 0.0412 (0.0247) Prec@1 93.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 17:00:58,374 Epoch: [440][40/500] Time 0.022 (0.019) Data 0.002 (0.007) Loss 0.0273 (0.0252) Prec@1 97.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 17:00:58,595 Epoch: [440][50/500] Time 0.017 (0.019) Data 0.002 (0.006) Loss 0.0395 (0.0276) Prec@1 93.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 17:00:58,797 Epoch: [440][60/500] Time 0.020 (0.019) Data 0.002 (0.006) Loss 0.0262 (0.0274) Prec@1 95.000 (95.571) Prec@5 99.000 (99.714) +2022-11-14 17:00:58,999 Epoch: [440][70/500] Time 0.022 (0.019) Data 0.002 (0.005) Loss 0.0317 (0.0279) Prec@1 95.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 17:00:59,202 Epoch: [440][80/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0212 (0.0272) Prec@1 97.000 (95.667) Prec@5 100.000 (99.778) +2022-11-14 17:00:59,404 Epoch: [440][90/500] Time 0.022 (0.018) Data 0.001 (0.004) Loss 0.0361 (0.0281) Prec@1 93.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:00:59,602 Epoch: [440][100/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0139 (0.0268) Prec@1 98.000 (95.636) Prec@5 100.000 (99.818) +2022-11-14 17:00:59,804 Epoch: [440][110/500] Time 0.022 (0.018) Data 0.001 (0.004) Loss 0.0144 (0.0258) Prec@1 97.000 (95.750) Prec@5 100.000 (99.833) +2022-11-14 17:01:00,003 Epoch: [440][120/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0440 (0.0272) Prec@1 93.000 (95.538) Prec@5 100.000 (99.846) +2022-11-14 17:01:00,211 Epoch: [440][130/500] Time 0.022 (0.018) Data 0.002 (0.004) Loss 0.0332 (0.0276) Prec@1 96.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:01:00,411 Epoch: [440][140/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.0266 (0.0275) Prec@1 94.000 (95.467) Prec@5 100.000 (99.867) +2022-11-14 17:01:00,616 Epoch: [440][150/500] Time 0.022 (0.018) Data 0.002 (0.003) Loss 0.0300 (0.0277) Prec@1 95.000 (95.438) Prec@5 100.000 (99.875) +2022-11-14 17:01:00,816 Epoch: [440][160/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0172 (0.0271) Prec@1 98.000 (95.588) Prec@5 100.000 (99.882) +2022-11-14 17:01:01,009 Epoch: [440][170/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0343 (0.0275) Prec@1 95.000 (95.556) Prec@5 100.000 (99.889) +2022-11-14 17:01:01,202 Epoch: [440][180/500] Time 0.020 (0.018) Data 0.002 (0.003) Loss 0.0104 (0.0266) Prec@1 98.000 (95.684) Prec@5 100.000 (99.895) +2022-11-14 17:01:01,420 Epoch: [440][190/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0246 (0.0265) Prec@1 97.000 (95.750) Prec@5 100.000 (99.900) +2022-11-14 17:01:01,733 Epoch: [440][200/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0502 (0.0276) Prec@1 90.000 (95.476) Prec@5 98.000 (99.810) +2022-11-14 17:01:02,053 Epoch: [440][210/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0155 (0.0270) Prec@1 99.000 (95.636) Prec@5 100.000 (99.818) +2022-11-14 17:01:02,376 Epoch: [440][220/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0248 (0.0270) Prec@1 96.000 (95.652) Prec@5 100.000 (99.826) +2022-11-14 17:01:02,700 Epoch: [440][230/500] Time 0.032 (0.020) Data 0.002 (0.003) Loss 0.0206 (0.0267) Prec@1 98.000 (95.750) Prec@5 99.000 (99.792) +2022-11-14 17:01:03,017 Epoch: [440][240/500] Time 0.030 (0.020) Data 0.002 (0.003) Loss 0.0257 (0.0267) Prec@1 94.000 (95.680) Prec@5 100.000 (99.800) +2022-11-14 17:01:03,327 Epoch: [440][250/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0333 (0.0269) Prec@1 94.000 (95.615) Prec@5 99.000 (99.769) +2022-11-14 17:01:03,641 Epoch: [440][260/500] Time 0.030 (0.021) Data 0.001 (0.003) Loss 0.0543 (0.0279) Prec@1 94.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 17:01:03,949 Epoch: [440][270/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0183 (0.0276) Prec@1 97.000 (95.607) Prec@5 100.000 (99.786) +2022-11-14 17:01:04,257 Epoch: [440][280/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0448 (0.0282) Prec@1 91.000 (95.448) Prec@5 100.000 (99.793) +2022-11-14 17:01:04,566 Epoch: [440][290/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0307 (0.0283) Prec@1 95.000 (95.433) Prec@5 99.000 (99.767) +2022-11-14 17:01:04,880 Epoch: [440][300/500] Time 0.030 (0.022) Data 0.001 (0.002) Loss 0.0307 (0.0283) Prec@1 94.000 (95.387) Prec@5 100.000 (99.774) +2022-11-14 17:01:05,195 Epoch: [440][310/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0487 (0.0290) Prec@1 89.000 (95.188) Prec@5 100.000 (99.781) +2022-11-14 17:01:05,503 Epoch: [440][320/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0207 (0.0287) Prec@1 96.000 (95.212) Prec@5 100.000 (99.788) +2022-11-14 17:01:05,808 Epoch: [440][330/500] Time 0.027 (0.022) Data 0.003 (0.002) Loss 0.0256 (0.0286) Prec@1 95.000 (95.206) Prec@5 100.000 (99.794) +2022-11-14 17:01:06,113 Epoch: [440][340/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0087 (0.0281) Prec@1 99.000 (95.314) Prec@5 100.000 (99.800) +2022-11-14 17:01:06,411 Epoch: [440][350/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0273 (0.0280) Prec@1 96.000 (95.333) Prec@5 100.000 (99.806) +2022-11-14 17:01:06,718 Epoch: [440][360/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0502 (0.0286) Prec@1 90.000 (95.189) Prec@5 99.000 (99.784) +2022-11-14 17:01:07,024 Epoch: [440][370/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0408 (0.0290) Prec@1 94.000 (95.158) Prec@5 99.000 (99.763) +2022-11-14 17:01:07,331 Epoch: [440][380/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0155 (0.0286) Prec@1 98.000 (95.231) Prec@5 100.000 (99.769) +2022-11-14 17:01:07,637 Epoch: [440][390/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0336 (0.0287) Prec@1 95.000 (95.225) Prec@5 100.000 (99.775) +2022-11-14 17:01:07,944 Epoch: [440][400/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0386 (0.0290) Prec@1 94.000 (95.195) Prec@5 99.000 (99.756) +2022-11-14 17:01:08,256 Epoch: [440][410/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0302 (0.0290) Prec@1 93.000 (95.143) Prec@5 100.000 (99.762) +2022-11-14 17:01:08,561 Epoch: [440][420/500] Time 0.030 (0.023) Data 0.001 (0.002) Loss 0.0313 (0.0291) Prec@1 94.000 (95.116) Prec@5 100.000 (99.767) +2022-11-14 17:01:08,865 Epoch: [440][430/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0337 (0.0292) Prec@1 92.000 (95.045) Prec@5 100.000 (99.773) +2022-11-14 17:01:09,173 Epoch: [440][440/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0366 (0.0293) Prec@1 93.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 17:01:09,477 Epoch: [440][450/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0181 (0.0291) Prec@1 97.000 (95.043) Prec@5 100.000 (99.783) +2022-11-14 17:01:09,778 Epoch: [440][460/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0419 (0.0294) Prec@1 92.000 (94.979) Prec@5 100.000 (99.787) +2022-11-14 17:01:10,082 Epoch: [440][470/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0114 (0.0290) Prec@1 98.000 (95.042) Prec@5 100.000 (99.792) +2022-11-14 17:01:10,390 Epoch: [440][480/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0245 (0.0289) Prec@1 95.000 (95.041) Prec@5 100.000 (99.796) +2022-11-14 17:01:10,696 Epoch: [440][490/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0155 (0.0286) Prec@1 98.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 17:01:10,972 Epoch: [440][499/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0367 (0.0288) Prec@1 93.000 (95.059) Prec@5 100.000 (99.804) +2022-11-14 17:01:11,271 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0758 (0.0758) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:11,279 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0689 (0.0723) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:11,290 Test: [2/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0708) Prec@1 91.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:11,302 Test: [3/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0960 (0.0771) Prec@1 87.000 (88.500) Prec@5 99.000 (99.750) +2022-11-14 17:01:11,309 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0768) Prec@1 86.000 (88.000) Prec@5 99.000 (99.600) +2022-11-14 17:01:11,315 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0707) Prec@1 93.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 17:01:11,325 Test: [6/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0682) Prec@1 91.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 17:01:11,336 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1058 (0.0729) Prec@1 83.000 (88.375) Prec@5 99.000 (99.625) +2022-11-14 17:01:11,343 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0725) Prec@1 90.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 17:01:11,350 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0720) Prec@1 89.000 (88.600) Prec@5 99.000 (99.600) +2022-11-14 17:01:11,360 Test: [10/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0617 (0.0710) Prec@1 90.000 (88.727) Prec@5 100.000 (99.636) +2022-11-14 17:01:11,370 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0707) Prec@1 90.000 (88.833) Prec@5 99.000 (99.583) +2022-11-14 17:01:11,378 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0703) Prec@1 88.000 (88.769) Prec@5 100.000 (99.615) +2022-11-14 17:01:11,385 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0701) Prec@1 89.000 (88.786) Prec@5 98.000 (99.500) +2022-11-14 17:01:11,395 Test: [14/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0701) Prec@1 87.000 (88.667) Prec@5 98.000 (99.400) +2022-11-14 17:01:11,406 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0706) Prec@1 88.000 (88.625) Prec@5 100.000 (99.438) +2022-11-14 17:01:11,414 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0505 (0.0694) Prec@1 93.000 (88.882) Prec@5 99.000 (99.412) +2022-11-14 17:01:11,421 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0735 (0.0696) Prec@1 86.000 (88.722) Prec@5 99.000 (99.389) +2022-11-14 17:01:11,429 Test: [18/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0700) Prec@1 88.000 (88.684) Prec@5 98.000 (99.316) +2022-11-14 17:01:11,438 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0976 (0.0714) Prec@1 83.000 (88.400) Prec@5 98.000 (99.250) +2022-11-14 17:01:11,445 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0711) Prec@1 89.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 17:01:11,453 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0965 (0.0722) Prec@1 85.000 (88.273) Prec@5 97.000 (99.182) +2022-11-14 17:01:11,461 Test: [22/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0829 (0.0727) Prec@1 88.000 (88.261) Prec@5 97.000 (99.087) +2022-11-14 17:01:11,468 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0887 (0.0733) Prec@1 85.000 (88.125) Prec@5 100.000 (99.125) +2022-11-14 17:01:11,476 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0736) Prec@1 88.000 (88.120) Prec@5 100.000 (99.160) +2022-11-14 17:01:11,484 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0742) Prec@1 85.000 (88.000) Prec@5 100.000 (99.192) +2022-11-14 17:01:11,491 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0737) Prec@1 91.000 (88.111) Prec@5 100.000 (99.222) +2022-11-14 17:01:11,498 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0730) Prec@1 92.000 (88.250) Prec@5 99.000 (99.214) +2022-11-14 17:01:11,506 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0731) Prec@1 88.000 (88.241) Prec@5 99.000 (99.207) +2022-11-14 17:01:11,513 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0733) Prec@1 87.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 17:01:11,521 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0730) Prec@1 91.000 (88.290) Prec@5 99.000 (99.194) +2022-11-14 17:01:11,529 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0727) Prec@1 90.000 (88.344) Prec@5 100.000 (99.219) +2022-11-14 17:01:11,536 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0732) Prec@1 85.000 (88.242) Prec@5 100.000 (99.242) +2022-11-14 17:01:11,544 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0740) Prec@1 83.000 (88.088) Prec@5 100.000 (99.265) +2022-11-14 17:01:11,551 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0744) Prec@1 83.000 (87.943) Prec@5 98.000 (99.229) +2022-11-14 17:01:11,559 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0740) Prec@1 92.000 (88.056) Prec@5 100.000 (99.250) +2022-11-14 17:01:11,566 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0737) Prec@1 91.000 (88.135) Prec@5 99.000 (99.243) +2022-11-14 17:01:11,574 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0744) Prec@1 85.000 (88.053) Prec@5 100.000 (99.263) +2022-11-14 17:01:11,582 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0738) Prec@1 93.000 (88.179) Prec@5 98.000 (99.231) +2022-11-14 17:01:11,589 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0734) Prec@1 92.000 (88.275) Prec@5 100.000 (99.250) +2022-11-14 17:01:11,597 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0738) Prec@1 83.000 (88.146) Prec@5 98.000 (99.220) +2022-11-14 17:01:11,604 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0735) Prec@1 90.000 (88.190) Prec@5 99.000 (99.214) +2022-11-14 17:01:11,612 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0733) Prec@1 89.000 (88.209) Prec@5 100.000 (99.233) +2022-11-14 17:01:11,620 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0735) Prec@1 86.000 (88.159) Prec@5 99.000 (99.227) +2022-11-14 17:01:11,627 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0731) Prec@1 92.000 (88.244) Prec@5 98.000 (99.200) +2022-11-14 17:01:11,635 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0737) Prec@1 82.000 (88.109) Prec@5 100.000 (99.217) +2022-11-14 17:01:11,643 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0737) Prec@1 89.000 (88.128) Prec@5 100.000 (99.234) +2022-11-14 17:01:11,650 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0742) Prec@1 84.000 (88.042) Prec@5 98.000 (99.208) +2022-11-14 17:01:11,658 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0519 (0.0737) Prec@1 91.000 (88.102) Prec@5 100.000 (99.224) +2022-11-14 17:01:11,666 Test: 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0.0691 (0.0745) Prec@1 90.000 (88.036) Prec@5 99.000 (99.214) +2022-11-14 17:01:11,719 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0746) Prec@1 89.000 (88.053) Prec@5 100.000 (99.228) +2022-11-14 17:01:11,726 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0746) Prec@1 90.000 (88.086) Prec@5 100.000 (99.241) +2022-11-14 17:01:11,734 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.0752) Prec@1 81.000 (87.966) Prec@5 99.000 (99.237) +2022-11-14 17:01:11,741 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0752) Prec@1 86.000 (87.933) Prec@5 100.000 (99.250) +2022-11-14 17:01:11,749 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0753) Prec@1 88.000 (87.934) Prec@5 100.000 (99.262) +2022-11-14 17:01:11,756 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0751) Prec@1 89.000 (87.952) Prec@5 100.000 (99.274) +2022-11-14 17:01:11,764 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0749) Prec@1 90.000 (87.984) Prec@5 100.000 (99.286) +2022-11-14 17:01:11,771 Test: [63/100] Model Time 0.004 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0747) Prec@1 91.000 (88.031) Prec@5 99.000 (99.281) +2022-11-14 17:01:11,778 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0749) Prec@1 86.000 (88.000) Prec@5 99.000 (99.277) +2022-11-14 17:01:11,786 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0749) Prec@1 89.000 (88.015) Prec@5 99.000 (99.273) +2022-11-14 17:01:11,793 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0744) Prec@1 94.000 (88.104) Prec@5 100.000 (99.284) +2022-11-14 17:01:11,800 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0742) Prec@1 92.000 (88.162) Prec@5 98.000 (99.265) +2022-11-14 17:01:11,808 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0741) Prec@1 89.000 (88.174) Prec@5 99.000 (99.261) +2022-11-14 17:01:11,815 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0745) Prec@1 82.000 (88.086) Prec@5 99.000 (99.257) +2022-11-14 17:01:11,822 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0746) Prec@1 87.000 (88.070) Prec@5 99.000 (99.254) +2022-11-14 17:01:11,830 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0745) Prec@1 88.000 (88.069) Prec@5 100.000 (99.264) +2022-11-14 17:01:11,837 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0742) Prec@1 92.000 (88.123) Prec@5 99.000 (99.260) +2022-11-14 17:01:11,845 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0739) Prec@1 92.000 (88.176) Prec@5 100.000 (99.270) +2022-11-14 17:01:11,852 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0741) Prec@1 86.000 (88.147) Prec@5 99.000 (99.267) +2022-11-14 17:01:11,859 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0739) Prec@1 89.000 (88.158) Prec@5 100.000 (99.276) +2022-11-14 17:01:11,867 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0741) Prec@1 87.000 (88.143) Prec@5 100.000 (99.286) +2022-11-14 17:01:11,874 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0743) Prec@1 85.000 (88.103) Prec@5 97.000 (99.256) +2022-11-14 17:01:11,882 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0744) Prec@1 86.000 (88.076) Prec@5 100.000 (99.266) +2022-11-14 17:01:11,889 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0743) Prec@1 89.000 (88.088) Prec@5 100.000 (99.275) +2022-11-14 17:01:11,897 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0744) Prec@1 86.000 (88.062) Prec@5 100.000 (99.284) +2022-11-14 17:01:11,905 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0748) Prec@1 86.000 (88.037) Prec@5 99.000 (99.280) +2022-11-14 17:01:11,912 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0750) Prec@1 86.000 (88.012) Prec@5 99.000 (99.277) +2022-11-14 17:01:11,920 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0750) Prec@1 87.000 (88.000) Prec@5 99.000 (99.274) +2022-11-14 17:01:11,927 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0920 (0.0752) Prec@1 87.000 (87.988) Prec@5 100.000 (99.282) +2022-11-14 17:01:11,935 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0983 (0.0755) Prec@1 87.000 (87.977) Prec@5 100.000 (99.291) +2022-11-14 17:01:11,942 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0756) Prec@1 88.000 (87.977) Prec@5 100.000 (99.299) +2022-11-14 17:01:11,950 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0749 (0.0756) Prec@1 89.000 (87.989) Prec@5 99.000 (99.295) +2022-11-14 17:01:11,957 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0509 (0.0753) Prec@1 93.000 (88.045) Prec@5 100.000 (99.303) +2022-11-14 17:01:11,965 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0825 (0.0754) Prec@1 88.000 (88.044) Prec@5 100.000 (99.311) +2022-11-14 17:01:11,973 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0571 (0.0752) Prec@1 91.000 (88.077) Prec@5 100.000 (99.319) +2022-11-14 17:01:11,981 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0635 (0.0750) Prec@1 90.000 (88.098) Prec@5 100.000 (99.326) +2022-11-14 17:01:11,988 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0743 (0.0750) Prec@1 89.000 (88.108) Prec@5 100.000 (99.333) +2022-11-14 17:01:11,996 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0746 (0.0750) Prec@1 86.000 (88.085) Prec@5 98.000 (99.319) +2022-11-14 17:01:12,003 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0751) Prec@1 85.000 (88.053) Prec@5 99.000 (99.316) +2022-11-14 17:01:12,010 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0751) Prec@1 89.000 (88.062) Prec@5 99.000 (99.312) +2022-11-14 17:01:12,018 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0619 (0.0749) Prec@1 90.000 (88.082) Prec@5 99.000 (99.309) +2022-11-14 17:01:12,025 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0835 (0.0750) Prec@1 88.000 (88.082) Prec@5 97.000 (99.286) +2022-11-14 17:01:12,032 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0996 (0.0753) Prec@1 83.000 (88.030) Prec@5 99.000 (99.283) +2022-11-14 17:01:12,040 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0634 (0.0752) Prec@1 89.000 (88.040) Prec@5 100.000 (99.290) +2022-11-14 17:01:12,109 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:01:12,891 Epoch: [441][0/500] Time 0.024 (0.024) Data 0.225 (0.225) Loss 0.0182 (0.0182) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:13,098 Epoch: [441][10/500] Time 0.018 (0.018) Data 0.001 (0.022) Loss 0.0422 (0.0302) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:13,291 Epoch: [441][20/500] Time 0.019 (0.018) Data 0.001 (0.012) Loss 0.0355 (0.0319) Prec@1 93.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 17:01:13,485 Epoch: [441][30/500] Time 0.018 (0.018) Data 0.002 (0.009) Loss 0.0245 (0.0301) Prec@1 96.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:01:13,681 Epoch: [441][40/500] Time 0.020 (0.018) Data 0.002 (0.007) Loss 0.0239 (0.0288) Prec@1 95.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 17:01:13,875 Epoch: [441][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0363 (0.0301) Prec@1 93.000 (94.500) Prec@5 99.000 (99.833) +2022-11-14 17:01:14,070 Epoch: [441][60/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0475 (0.0326) Prec@1 93.000 (94.286) Prec@5 100.000 (99.857) +2022-11-14 17:01:14,261 Epoch: [441][70/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0103 (0.0298) Prec@1 100.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:01:14,449 Epoch: [441][80/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0220 (0.0289) Prec@1 97.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 17:01:14,634 Epoch: [441][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0301 (0.0290) Prec@1 93.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 17:01:14,825 Epoch: [441][100/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0224 (0.0284) Prec@1 95.000 (95.000) Prec@5 100.000 (99.909) +2022-11-14 17:01:15,012 Epoch: [441][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0434 (0.0297) Prec@1 93.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 17:01:15,200 Epoch: [441][120/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0244 (0.0293) Prec@1 95.000 (94.846) Prec@5 100.000 (99.923) +2022-11-14 17:01:15,387 Epoch: [441][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0287 (0.0292) Prec@1 96.000 (94.929) Prec@5 100.000 (99.929) +2022-11-14 17:01:15,574 Epoch: [441][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0400 (0.0300) Prec@1 94.000 (94.867) Prec@5 100.000 (99.933) +2022-11-14 17:01:15,760 Epoch: [441][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0290 (0.0299) Prec@1 95.000 (94.875) Prec@5 100.000 (99.938) +2022-11-14 17:01:15,945 Epoch: [441][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0366 (0.0303) Prec@1 96.000 (94.941) Prec@5 100.000 (99.941) +2022-11-14 17:01:16,135 Epoch: [441][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0296 (0.0303) Prec@1 96.000 (95.000) Prec@5 100.000 (99.944) +2022-11-14 17:01:16,322 Epoch: [441][180/500] Time 0.016 (0.017) Data 0.001 (0.003) Loss 0.0283 (0.0302) Prec@1 97.000 (95.105) Prec@5 100.000 (99.947) +2022-11-14 17:01:16,509 Epoch: [441][190/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0252 (0.0299) Prec@1 96.000 (95.150) Prec@5 100.000 (99.950) +2022-11-14 17:01:16,694 Epoch: [441][200/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0248 (0.0297) Prec@1 96.000 (95.190) Prec@5 99.000 (99.905) +2022-11-14 17:01:16,879 Epoch: [441][210/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0437 (0.0303) Prec@1 91.000 (95.000) Prec@5 99.000 (99.864) +2022-11-14 17:01:17,064 Epoch: [441][220/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0438 (0.0309) Prec@1 92.000 (94.870) Prec@5 99.000 (99.826) +2022-11-14 17:01:17,251 Epoch: [441][230/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0160 (0.0303) Prec@1 98.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:01:17,435 Epoch: [441][240/500] Time 0.017 (0.017) Data 0.001 (0.002) Loss 0.0276 (0.0302) Prec@1 95.000 (95.000) Prec@5 100.000 (99.840) +2022-11-14 17:01:17,620 Epoch: [441][250/500] Time 0.016 (0.017) Data 0.002 (0.002) Loss 0.0279 (0.0301) Prec@1 96.000 (95.038) Prec@5 99.000 (99.808) +2022-11-14 17:01:17,824 Epoch: [441][260/500] Time 0.021 (0.017) Data 0.001 (0.002) Loss 0.0537 (0.0310) Prec@1 90.000 (94.852) Prec@5 100.000 (99.815) +2022-11-14 17:01:18,073 Epoch: [441][270/500] Time 0.024 (0.017) Data 0.001 (0.002) Loss 0.0393 (0.0313) Prec@1 94.000 (94.821) Prec@5 100.000 (99.821) +2022-11-14 17:01:18,330 Epoch: [441][280/500] Time 0.021 (0.017) Data 0.001 (0.002) Loss 0.0207 (0.0309) Prec@1 98.000 (94.931) Prec@5 100.000 (99.828) +2022-11-14 17:01:18,575 Epoch: [441][290/500] Time 0.022 (0.017) Data 0.002 (0.002) Loss 0.0182 (0.0305) Prec@1 97.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:01:18,819 Epoch: [441][300/500] Time 0.023 (0.017) Data 0.001 (0.002) Loss 0.0366 (0.0307) Prec@1 95.000 (95.000) Prec@5 99.000 (99.806) +2022-11-14 17:01:19,068 Epoch: [441][310/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0313 (0.0307) Prec@1 94.000 (94.969) Prec@5 100.000 (99.812) +2022-11-14 17:01:19,322 Epoch: [441][320/500] Time 0.024 (0.018) Data 0.001 (0.002) Loss 0.0205 (0.0304) Prec@1 97.000 (95.030) Prec@5 100.000 (99.818) +2022-11-14 17:01:19,571 Epoch: [441][330/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0115 (0.0298) Prec@1 98.000 (95.118) Prec@5 100.000 (99.824) +2022-11-14 17:01:19,821 Epoch: [441][340/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0482 (0.0303) Prec@1 93.000 (95.057) Prec@5 100.000 (99.829) +2022-11-14 17:01:20,067 Epoch: [441][350/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0182 (0.0300) Prec@1 98.000 (95.139) Prec@5 100.000 (99.833) +2022-11-14 17:01:20,320 Epoch: [441][360/500] Time 0.026 (0.018) Data 0.001 (0.002) Loss 0.0234 (0.0298) Prec@1 95.000 (95.135) Prec@5 100.000 (99.838) +2022-11-14 17:01:20,570 Epoch: [441][370/500] Time 0.022 (0.018) Data 0.002 (0.002) Loss 0.0367 (0.0300) Prec@1 94.000 (95.105) Prec@5 100.000 (99.842) +2022-11-14 17:01:20,816 Epoch: [441][380/500] Time 0.022 (0.018) Data 0.002 (0.002) Loss 0.0449 (0.0304) Prec@1 93.000 (95.051) Prec@5 100.000 (99.846) +2022-11-14 17:01:21,067 Epoch: [441][390/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0362 (0.0305) Prec@1 94.000 (95.025) Prec@5 100.000 (99.850) +2022-11-14 17:01:21,315 Epoch: [441][400/500] Time 0.022 (0.019) Data 0.001 (0.002) Loss 0.0466 (0.0309) Prec@1 92.000 (94.951) Prec@5 100.000 (99.854) +2022-11-14 17:01:21,563 Epoch: [441][410/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0404 (0.0312) Prec@1 92.000 (94.881) Prec@5 100.000 (99.857) +2022-11-14 17:01:21,810 Epoch: [441][420/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0224 (0.0310) Prec@1 96.000 (94.907) Prec@5 100.000 (99.860) +2022-11-14 17:01:22,060 Epoch: [441][430/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0251 (0.0308) Prec@1 96.000 (94.932) Prec@5 99.000 (99.841) +2022-11-14 17:01:22,310 Epoch: [441][440/500] Time 0.023 (0.019) Data 0.001 (0.002) Loss 0.0096 (0.0303) Prec@1 99.000 (95.022) Prec@5 100.000 (99.844) +2022-11-14 17:01:22,557 Epoch: [441][450/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0256 (0.0302) Prec@1 96.000 (95.043) Prec@5 100.000 (99.848) +2022-11-14 17:01:22,809 Epoch: [441][460/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0307 (0.0303) Prec@1 96.000 (95.064) Prec@5 100.000 (99.851) +2022-11-14 17:01:23,058 Epoch: [441][470/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0165 (0.0300) Prec@1 97.000 (95.104) Prec@5 100.000 (99.854) +2022-11-14 17:01:23,311 Epoch: [441][480/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0331 (0.0300) Prec@1 95.000 (95.102) Prec@5 100.000 (99.857) +2022-11-14 17:01:23,563 Epoch: [441][490/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0221 (0.0299) Prec@1 97.000 (95.140) Prec@5 100.000 (99.860) +2022-11-14 17:01:23,790 Epoch: [441][499/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0236 (0.0298) Prec@1 97.000 (95.176) Prec@5 100.000 (99.863) +2022-11-14 17:01:24,094 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0660 (0.0660) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:24,107 Test: [1/100] Model Time 0.010 (0.011) Loss Time 0.000 (0.000) Loss 0.0715 (0.0687) Prec@1 88.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:24,117 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0639 (0.0671) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:24,127 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0714 (0.0682) Prec@1 89.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 17:01:24,134 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0697) Prec@1 88.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 17:01:24,143 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0652) Prec@1 92.000 (89.333) Prec@5 100.000 (99.833) +2022-11-14 17:01:24,153 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0646) Prec@1 90.000 (89.429) Prec@5 100.000 (99.857) +2022-11-14 17:01:24,161 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0664) Prec@1 88.000 (89.250) Prec@5 100.000 (99.875) +2022-11-14 17:01:24,167 Test: [8/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0562 (0.0652) Prec@1 91.000 (89.444) Prec@5 99.000 (99.778) +2022-11-14 17:01:24,178 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0936 (0.0681) Prec@1 86.000 (89.100) Prec@5 99.000 (99.700) +2022-11-14 17:01:24,188 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0677) Prec@1 91.000 (89.273) Prec@5 100.000 (99.727) +2022-11-14 17:01:24,196 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0944 (0.0699) Prec@1 83.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 17:01:24,203 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0683) Prec@1 93.000 (89.077) Prec@5 100.000 (99.769) +2022-11-14 17:01:24,214 Test: [13/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0612 (0.0678) Prec@1 93.000 (89.357) Prec@5 99.000 (99.714) +2022-11-14 17:01:24,224 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0676) Prec@1 90.000 (89.400) Prec@5 100.000 (99.733) +2022-11-14 17:01:24,232 Test: [15/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0681) Prec@1 87.000 (89.250) Prec@5 99.000 (99.688) +2022-11-14 17:01:24,240 Test: [16/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0673) Prec@1 92.000 (89.412) Prec@5 99.000 (99.647) +2022-11-14 17:01:24,250 Test: [17/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1073 (0.0695) Prec@1 84.000 (89.111) Prec@5 100.000 (99.667) +2022-11-14 17:01:24,260 Test: [18/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0751 (0.0698) Prec@1 87.000 (89.000) Prec@5 100.000 (99.684) +2022-11-14 17:01:24,268 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0707) Prec@1 85.000 (88.800) Prec@5 99.000 (99.650) +2022-11-14 17:01:24,276 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0705) Prec@1 86.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 17:01:24,285 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0700) Prec@1 91.000 (88.773) Prec@5 100.000 (99.682) +2022-11-14 17:01:24,293 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0710) Prec@1 84.000 (88.565) Prec@5 99.000 (99.652) +2022-11-14 17:01:24,301 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0713) Prec@1 88.000 (88.542) Prec@5 99.000 (99.625) +2022-11-14 17:01:24,308 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0716) Prec@1 88.000 (88.520) Prec@5 100.000 (99.640) +2022-11-14 17:01:24,318 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0725) Prec@1 84.000 (88.346) Prec@5 98.000 (99.577) +2022-11-14 17:01:24,328 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0711) Prec@1 94.000 (88.556) Prec@5 100.000 (99.593) +2022-11-14 17:01:24,335 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0706) Prec@1 90.000 (88.607) Prec@5 100.000 (99.607) +2022-11-14 17:01:24,343 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0623 (0.0704) Prec@1 89.000 (88.621) Prec@5 99.000 (99.586) +2022-11-14 17:01:24,353 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0700) Prec@1 90.000 (88.667) Prec@5 99.000 (99.567) +2022-11-14 17:01:24,363 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0696) Prec@1 90.000 (88.710) Prec@5 100.000 (99.581) +2022-11-14 17:01:24,371 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0696) Prec@1 90.000 (88.750) Prec@5 100.000 (99.594) +2022-11-14 17:01:24,379 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0698) Prec@1 88.000 (88.727) Prec@5 100.000 (99.606) +2022-11-14 17:01:24,389 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0701) Prec@1 86.000 (88.647) Prec@5 100.000 (99.618) +2022-11-14 17:01:24,399 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0893 (0.0707) Prec@1 87.000 (88.600) Prec@5 97.000 (99.543) +2022-11-14 17:01:24,407 Test: [35/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0707) Prec@1 89.000 (88.611) Prec@5 99.000 (99.528) +2022-11-14 17:01:24,414 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0705) Prec@1 90.000 (88.649) Prec@5 99.000 (99.514) +2022-11-14 17:01:24,424 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0881 (0.0709) Prec@1 87.000 (88.605) Prec@5 99.000 (99.500) +2022-11-14 17:01:24,434 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0502 (0.0704) Prec@1 94.000 (88.744) Prec@5 99.000 (99.487) +2022-11-14 17:01:24,442 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0702 (0.0704) Prec@1 88.000 (88.725) Prec@5 99.000 (99.475) +2022-11-14 17:01:24,449 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0707) Prec@1 87.000 (88.683) Prec@5 99.000 (99.463) +2022-11-14 17:01:24,459 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0707) Prec@1 90.000 (88.714) Prec@5 100.000 (99.476) +2022-11-14 17:01:24,470 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0704 (0.0706) Prec@1 88.000 (88.698) Prec@5 98.000 (99.442) +2022-11-14 17:01:24,477 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0764 (0.0708) Prec@1 89.000 (88.705) Prec@5 97.000 (99.386) +2022-11-14 17:01:24,485 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0432 (0.0702) Prec@1 92.000 (88.778) Prec@5 100.000 (99.400) +2022-11-14 17:01:24,495 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0916 (0.0706) Prec@1 83.000 (88.652) Prec@5 100.000 (99.413) +2022-11-14 17:01:24,505 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0704) Prec@1 91.000 (88.702) Prec@5 100.000 (99.426) +2022-11-14 17:01:24,514 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1119 (0.0713) Prec@1 82.000 (88.562) Prec@5 99.000 (99.417) +2022-11-14 17:01:24,522 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0708) Prec@1 92.000 (88.633) Prec@5 100.000 (99.429) +2022-11-14 17:01:24,532 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1082 (0.0715) Prec@1 84.000 (88.540) Prec@5 99.000 (99.420) +2022-11-14 17:01:24,542 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0714) Prec@1 87.000 (88.510) Prec@5 100.000 (99.431) +2022-11-14 17:01:24,550 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0895 (0.0717) Prec@1 85.000 (88.442) Prec@5 99.000 (99.423) +2022-11-14 17:01:24,557 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0716) Prec@1 88.000 (88.434) Prec@5 100.000 (99.434) +2022-11-14 17:01:24,567 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0757 (0.0716) Prec@1 91.000 (88.481) Prec@5 100.000 (99.444) +2022-11-14 17:01:24,578 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0723) Prec@1 84.000 (88.400) Prec@5 99.000 (99.436) +2022-11-14 17:01:24,585 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1016 (0.0728) Prec@1 83.000 (88.304) Prec@5 99.000 (99.429) +2022-11-14 17:01:24,593 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0728) Prec@1 89.000 (88.316) Prec@5 100.000 (99.439) +2022-11-14 17:01:24,603 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0727) Prec@1 91.000 (88.362) Prec@5 99.000 (99.431) +2022-11-14 17:01:24,613 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0910 (0.0730) Prec@1 85.000 (88.305) Prec@5 100.000 (99.441) +2022-11-14 17:01:24,620 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0729) Prec@1 88.000 (88.300) Prec@5 100.000 (99.450) +2022-11-14 17:01:24,628 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0729) Prec@1 89.000 (88.311) Prec@5 99.000 (99.443) +2022-11-14 17:01:24,638 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0729) Prec@1 86.000 (88.274) Prec@5 100.000 (99.452) +2022-11-14 17:01:24,648 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0729) Prec@1 88.000 (88.270) Prec@5 100.000 (99.460) +2022-11-14 17:01:24,655 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0726) Prec@1 92.000 (88.328) Prec@5 100.000 (99.469) +2022-11-14 17:01:24,663 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0729) Prec@1 85.000 (88.277) Prec@5 99.000 (99.462) +2022-11-14 17:01:24,673 Test: [65/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0728) Prec@1 88.000 (88.273) Prec@5 98.000 (99.439) +2022-11-14 17:01:24,683 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0345 (0.0722) Prec@1 96.000 (88.388) Prec@5 99.000 (99.433) +2022-11-14 17:01:24,690 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0645 (0.0721) Prec@1 90.000 (88.412) Prec@5 99.000 (99.426) +2022-11-14 17:01:24,698 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0721) Prec@1 89.000 (88.420) Prec@5 99.000 (99.420) +2022-11-14 17:01:24,708 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0582 (0.0719) Prec@1 93.000 (88.486) Prec@5 100.000 (99.429) +2022-11-14 17:01:24,718 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0722) Prec@1 86.000 (88.451) Prec@5 98.000 (99.408) +2022-11-14 17:01:24,726 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0723) Prec@1 87.000 (88.431) Prec@5 99.000 (99.403) +2022-11-14 17:01:24,733 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0422 (0.0719) Prec@1 95.000 (88.521) Prec@5 100.000 (99.411) +2022-11-14 17:01:24,743 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0716) Prec@1 91.000 (88.554) Prec@5 100.000 (99.419) +2022-11-14 17:01:24,753 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0718) Prec@1 84.000 (88.493) Prec@5 100.000 (99.427) +2022-11-14 17:01:24,761 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0719) Prec@1 86.000 (88.461) Prec@5 99.000 (99.421) +2022-11-14 17:01:24,768 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0795 (0.0720) Prec@1 88.000 (88.455) Prec@5 100.000 (99.429) +2022-11-14 17:01:24,776 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0722) Prec@1 87.000 (88.436) Prec@5 99.000 (99.423) +2022-11-14 17:01:24,784 Test: [78/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0721) Prec@1 92.000 (88.481) Prec@5 100.000 (99.430) +2022-11-14 17:01:24,791 Test: [79/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0719) Prec@1 94.000 (88.550) Prec@5 100.000 (99.438) +2022-11-14 17:01:24,799 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0984 (0.0722) Prec@1 85.000 (88.506) Prec@5 98.000 (99.420) +2022-11-14 17:01:24,806 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0725) Prec@1 84.000 (88.451) Prec@5 100.000 (99.427) +2022-11-14 17:01:24,813 Test: [82/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1155 (0.0730) Prec@1 84.000 (88.398) Prec@5 99.000 (99.422) +2022-11-14 17:01:24,821 Test: [83/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0729) Prec@1 89.000 (88.405) Prec@5 99.000 (99.417) +2022-11-14 17:01:24,828 Test: [84/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0730) Prec@1 85.000 (88.365) Prec@5 100.000 (99.424) +2022-11-14 17:01:24,836 Test: [85/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1090 (0.0735) Prec@1 82.000 (88.291) Prec@5 99.000 (99.419) +2022-11-14 17:01:24,843 Test: [86/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0735) Prec@1 86.000 (88.264) Prec@5 100.000 (99.425) +2022-11-14 17:01:24,851 Test: [87/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0735) Prec@1 86.000 (88.239) Prec@5 97.000 (99.398) +2022-11-14 17:01:24,858 Test: [88/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0733) Prec@1 89.000 (88.247) Prec@5 99.000 (99.393) +2022-11-14 17:01:24,865 Test: [89/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0732) Prec@1 91.000 (88.278) Prec@5 100.000 (99.400) +2022-11-14 17:01:24,873 Test: [90/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0589 (0.0730) Prec@1 91.000 (88.308) Prec@5 100.000 (99.407) +2022-11-14 17:01:24,880 Test: [91/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0728) Prec@1 93.000 (88.359) Prec@5 100.000 (99.413) +2022-11-14 17:01:24,888 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0730) Prec@1 86.000 (88.333) Prec@5 100.000 (99.419) +2022-11-14 17:01:24,895 Test: [93/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0732) Prec@1 85.000 (88.298) Prec@5 99.000 (99.415) +2022-11-14 17:01:24,903 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0924 (0.0734) Prec@1 85.000 (88.263) Prec@5 99.000 (99.411) +2022-11-14 17:01:24,910 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0733) Prec@1 91.000 (88.292) Prec@5 99.000 (99.406) +2022-11-14 17:01:24,918 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0731) Prec@1 89.000 (88.299) Prec@5 99.000 (99.402) +2022-11-14 17:01:24,925 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0731) Prec@1 88.000 (88.296) Prec@5 100.000 (99.408) +2022-11-14 17:01:24,932 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0732) Prec@1 88.000 (88.293) Prec@5 99.000 (99.404) +2022-11-14 17:01:24,940 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0732) Prec@1 92.000 (88.330) Prec@5 100.000 (99.410) +2022-11-14 17:01:25,007 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:01:25,472 Epoch: [442][0/500] Time 0.023 (0.023) Data 0.241 (0.241) Loss 0.0319 (0.0319) Prec@1 95.000 (95.000) Prec@5 99.000 (99.000) +2022-11-14 17:01:25,676 Epoch: [442][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0176 (0.0248) Prec@1 98.000 (96.500) Prec@5 100.000 (99.500) +2022-11-14 17:01:25,869 Epoch: [442][20/500] Time 0.020 (0.018) Data 0.001 (0.013) Loss 0.0293 (0.0263) Prec@1 93.000 (95.333) Prec@5 100.000 (99.667) +2022-11-14 17:01:26,058 Epoch: [442][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0034 (0.0205) Prec@1 100.000 (96.500) Prec@5 100.000 (99.750) +2022-11-14 17:01:26,251 Epoch: [442][40/500] Time 0.020 (0.017) Data 0.001 (0.007) Loss 0.0334 (0.0231) Prec@1 95.000 (96.200) Prec@5 100.000 (99.800) +2022-11-14 17:01:26,444 Epoch: [442][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0268 (0.0237) Prec@1 96.000 (96.167) Prec@5 100.000 (99.833) +2022-11-14 17:01:26,637 Epoch: [442][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0257 (0.0240) Prec@1 96.000 (96.143) Prec@5 100.000 (99.857) +2022-11-14 17:01:26,824 Epoch: [442][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0228 (0.0239) Prec@1 97.000 (96.250) Prec@5 100.000 (99.875) +2022-11-14 17:01:27,011 Epoch: [442][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0185 (0.0233) Prec@1 96.000 (96.222) Prec@5 100.000 (99.889) +2022-11-14 17:01:27,201 Epoch: [442][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0235 (0.0233) Prec@1 97.000 (96.300) Prec@5 100.000 (99.900) +2022-11-14 17:01:27,389 Epoch: [442][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0140 (0.0224) Prec@1 99.000 (96.545) Prec@5 100.000 (99.909) +2022-11-14 17:01:27,586 Epoch: [442][110/500] Time 0.020 (0.017) Data 0.002 (0.004) Loss 0.0193 (0.0222) Prec@1 96.000 (96.500) Prec@5 100.000 (99.917) +2022-11-14 17:01:27,841 Epoch: [442][120/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0268 (0.0225) Prec@1 94.000 (96.308) Prec@5 100.000 (99.923) +2022-11-14 17:01:28,105 Epoch: [442][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0289 (0.0230) Prec@1 94.000 (96.143) Prec@5 100.000 (99.929) +2022-11-14 17:01:28,367 Epoch: [442][140/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0276 (0.0233) Prec@1 96.000 (96.133) Prec@5 100.000 (99.933) +2022-11-14 17:01:28,633 Epoch: [442][150/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0230 (0.0233) Prec@1 96.000 (96.125) Prec@5 100.000 (99.938) +2022-11-14 17:01:28,893 Epoch: [442][160/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0363 (0.0240) Prec@1 94.000 (96.000) Prec@5 100.000 (99.941) +2022-11-14 17:01:29,161 Epoch: [442][170/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0248 (0.0241) Prec@1 95.000 (95.944) Prec@5 100.000 (99.944) +2022-11-14 17:01:29,425 Epoch: [442][180/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0120 (0.0234) Prec@1 98.000 (96.053) Prec@5 100.000 (99.947) +2022-11-14 17:01:29,687 Epoch: [442][190/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0224 (0.0234) Prec@1 96.000 (96.050) Prec@5 100.000 (99.950) +2022-11-14 17:01:29,953 Epoch: [442][200/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0200 (0.0232) Prec@1 97.000 (96.095) Prec@5 100.000 (99.952) +2022-11-14 17:01:30,221 Epoch: [442][210/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0375 (0.0239) Prec@1 94.000 (96.000) Prec@5 99.000 (99.909) +2022-11-14 17:01:30,485 Epoch: [442][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0266 (0.0240) Prec@1 96.000 (96.000) Prec@5 100.000 (99.913) +2022-11-14 17:01:30,751 Epoch: [442][230/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0141 (0.0236) Prec@1 98.000 (96.083) Prec@5 100.000 (99.917) +2022-11-14 17:01:31,013 Epoch: [442][240/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0241 (0.0236) Prec@1 95.000 (96.040) Prec@5 100.000 (99.920) +2022-11-14 17:01:31,286 Epoch: [442][250/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0171 (0.0234) Prec@1 97.000 (96.077) Prec@5 100.000 (99.923) +2022-11-14 17:01:31,557 Epoch: [442][260/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0461 (0.0242) Prec@1 93.000 (95.963) Prec@5 100.000 (99.926) +2022-11-14 17:01:31,819 Epoch: [442][270/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0213 (0.0241) Prec@1 97.000 (96.000) Prec@5 100.000 (99.929) +2022-11-14 17:01:32,082 Epoch: [442][280/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0276 (0.0242) Prec@1 96.000 (96.000) Prec@5 100.000 (99.931) +2022-11-14 17:01:32,347 Epoch: [442][290/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0237 (0.0242) Prec@1 97.000 (96.033) Prec@5 100.000 (99.933) +2022-11-14 17:01:32,610 Epoch: [442][300/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0254 (0.0242) Prec@1 96.000 (96.032) Prec@5 99.000 (99.903) +2022-11-14 17:01:32,869 Epoch: [442][310/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0194 (0.0241) Prec@1 98.000 (96.094) Prec@5 100.000 (99.906) +2022-11-14 17:01:33,131 Epoch: [442][320/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0322 (0.0243) Prec@1 95.000 (96.061) Prec@5 100.000 (99.909) +2022-11-14 17:01:33,387 Epoch: [442][330/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0232 (0.0243) Prec@1 95.000 (96.029) Prec@5 100.000 (99.912) +2022-11-14 17:01:33,646 Epoch: [442][340/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0341 (0.0246) Prec@1 94.000 (95.971) Prec@5 100.000 (99.914) +2022-11-14 17:01:33,903 Epoch: [442][350/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0262 (0.0246) Prec@1 95.000 (95.944) Prec@5 100.000 (99.917) +2022-11-14 17:01:34,159 Epoch: [442][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0465 (0.0252) Prec@1 91.000 (95.811) Prec@5 100.000 (99.919) +2022-11-14 17:01:34,417 Epoch: [442][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0263 (0.0252) Prec@1 97.000 (95.842) Prec@5 99.000 (99.895) +2022-11-14 17:01:34,673 Epoch: [442][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0365 (0.0255) Prec@1 93.000 (95.769) Prec@5 99.000 (99.872) +2022-11-14 17:01:34,931 Epoch: [442][390/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0274 (0.0256) Prec@1 95.000 (95.750) Prec@5 100.000 (99.875) +2022-11-14 17:01:35,189 Epoch: [442][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0364 (0.0258) Prec@1 93.000 (95.683) Prec@5 100.000 (99.878) +2022-11-14 17:01:35,452 Epoch: [442][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0283 (0.0259) Prec@1 96.000 (95.690) Prec@5 100.000 (99.881) +2022-11-14 17:01:35,713 Epoch: [442][420/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0142 (0.0256) Prec@1 98.000 (95.744) Prec@5 100.000 (99.884) +2022-11-14 17:01:35,972 Epoch: [442][430/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0163 (0.0254) Prec@1 97.000 (95.773) Prec@5 100.000 (99.886) +2022-11-14 17:01:36,233 Epoch: [442][440/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0162 (0.0252) Prec@1 97.000 (95.800) Prec@5 100.000 (99.889) +2022-11-14 17:01:36,489 Epoch: [442][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0179 (0.0251) Prec@1 97.000 (95.826) Prec@5 100.000 (99.891) +2022-11-14 17:01:36,748 Epoch: [442][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0127 (0.0248) Prec@1 98.000 (95.872) Prec@5 100.000 (99.894) +2022-11-14 17:01:37,006 Epoch: [442][470/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0330 (0.0250) Prec@1 96.000 (95.875) Prec@5 100.000 (99.896) +2022-11-14 17:01:37,269 Epoch: [442][480/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0385 (0.0252) Prec@1 94.000 (95.837) Prec@5 100.000 (99.898) +2022-11-14 17:01:37,528 Epoch: [442][490/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0427 (0.0256) Prec@1 94.000 (95.800) Prec@5 99.000 (99.880) +2022-11-14 17:01:37,761 Epoch: [442][499/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0156 (0.0254) Prec@1 98.000 (95.843) Prec@5 100.000 (99.882) +2022-11-14 17:01:38,063 Test: [0/100] Model Time 0.015 (0.015) Loss Time 0.000 (0.000) Loss 0.0729 (0.0729) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:38,072 Test: [1/100] Model Time 0.008 (0.011) Loss Time 0.000 (0.000) Loss 0.0624 (0.0677) Prec@1 89.000 (87.500) Prec@5 100.000 (100.000) +2022-11-14 17:01:38,081 Test: [2/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0855 (0.0736) Prec@1 88.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:01:38,092 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0980 (0.0797) Prec@1 82.000 (86.250) Prec@5 98.000 (99.500) +2022-11-14 17:01:38,101 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0801 (0.0798) Prec@1 86.000 (86.200) Prec@5 99.000 (99.400) +2022-11-14 17:01:38,110 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0452 (0.0740) Prec@1 91.000 (87.000) Prec@5 99.000 (99.333) +2022-11-14 17:01:38,117 Test: [6/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0785 (0.0747) Prec@1 88.000 (87.143) Prec@5 100.000 (99.429) +2022-11-14 17:01:38,126 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0721 (0.0743) Prec@1 89.000 (87.375) Prec@5 100.000 (99.500) +2022-11-14 17:01:38,135 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0725 (0.0741) Prec@1 91.000 (87.778) Prec@5 99.000 (99.444) +2022-11-14 17:01:38,145 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0836 (0.0751) Prec@1 86.000 (87.600) Prec@5 98.000 (99.300) +2022-11-14 17:01:38,153 Test: [10/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0649 (0.0742) Prec@1 90.000 (87.818) Prec@5 100.000 (99.364) +2022-11-14 17:01:38,161 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0720 (0.0740) Prec@1 89.000 (87.917) Prec@5 99.000 (99.333) +2022-11-14 17:01:38,171 Test: [12/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0563 (0.0726) Prec@1 88.000 (87.923) Prec@5 100.000 (99.385) +2022-11-14 17:01:38,182 Test: [13/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0740) Prec@1 87.000 (87.857) Prec@5 99.000 (99.357) +2022-11-14 17:01:38,189 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0739) Prec@1 88.000 (87.867) Prec@5 99.000 (99.333) +2022-11-14 17:01:38,197 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0749) Prec@1 86.000 (87.750) Prec@5 99.000 (99.312) +2022-11-14 17:01:38,207 Test: [16/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0435 (0.0730) Prec@1 93.000 (88.059) Prec@5 99.000 (99.294) +2022-11-14 17:01:38,218 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0921 (0.0741) Prec@1 87.000 (88.000) Prec@5 98.000 (99.222) +2022-11-14 17:01:38,225 Test: [18/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0974 (0.0753) Prec@1 84.000 (87.789) Prec@5 99.000 (99.211) +2022-11-14 17:01:38,233 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0701 (0.0750) Prec@1 90.000 (87.900) Prec@5 98.000 (99.150) +2022-11-14 17:01:38,242 Test: [20/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0748) Prec@1 90.000 (88.000) Prec@5 100.000 (99.190) +2022-11-14 17:01:38,250 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0749) Prec@1 89.000 (88.045) Prec@5 99.000 (99.182) +2022-11-14 17:01:38,257 Test: [22/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0758) Prec@1 86.000 (87.957) Prec@5 96.000 (99.043) +2022-11-14 17:01:38,265 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0756) Prec@1 87.000 (87.917) Prec@5 100.000 (99.083) +2022-11-14 17:01:38,273 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0969 (0.0765) Prec@1 86.000 (87.840) Prec@5 100.000 (99.120) +2022-11-14 17:01:38,280 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0768) Prec@1 85.000 (87.731) Prec@5 98.000 (99.077) +2022-11-14 17:01:38,288 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0762) Prec@1 91.000 (87.852) Prec@5 100.000 (99.111) +2022-11-14 17:01:38,296 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0781 (0.0762) Prec@1 89.000 (87.893) Prec@5 100.000 (99.143) +2022-11-14 17:01:38,303 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0756) Prec@1 91.000 (88.000) Prec@5 99.000 (99.138) +2022-11-14 17:01:38,311 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0755) Prec@1 90.000 (88.067) Prec@5 100.000 (99.167) +2022-11-14 17:01:38,318 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0755) Prec@1 88.000 (88.065) Prec@5 99.000 (99.161) +2022-11-14 17:01:38,326 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0575 (0.0749) Prec@1 92.000 (88.188) Prec@5 99.000 (99.156) +2022-11-14 17:01:38,334 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0745) Prec@1 90.000 (88.242) Prec@5 100.000 (99.182) +2022-11-14 17:01:38,341 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0747) Prec@1 88.000 (88.235) Prec@5 99.000 (99.176) +2022-11-14 17:01:38,349 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0750) Prec@1 86.000 (88.171) Prec@5 96.000 (99.086) +2022-11-14 17:01:38,357 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0745) Prec@1 90.000 (88.222) Prec@5 100.000 (99.111) +2022-11-14 17:01:38,365 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0745) Prec@1 85.000 (88.135) Prec@5 99.000 (99.108) +2022-11-14 17:01:38,372 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0753) Prec@1 84.000 (88.026) Prec@5 98.000 (99.079) +2022-11-14 17:01:38,380 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0750) Prec@1 92.000 (88.128) Prec@5 99.000 (99.077) +2022-11-14 17:01:38,388 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0745) Prec@1 92.000 (88.225) Prec@5 98.000 (99.050) +2022-11-14 17:01:38,396 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0748) Prec@1 87.000 (88.195) Prec@5 99.000 (99.049) +2022-11-14 17:01:38,404 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0745) Prec@1 90.000 (88.238) Prec@5 99.000 (99.048) +2022-11-14 17:01:38,411 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0453 (0.0738) Prec@1 94.000 (88.372) Prec@5 100.000 (99.070) +2022-11-14 17:01:38,419 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0743) Prec@1 85.000 (88.295) Prec@5 97.000 (99.023) +2022-11-14 17:01:38,427 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0740) Prec@1 90.000 (88.333) Prec@5 100.000 (99.044) +2022-11-14 17:01:38,434 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1095 (0.0747) Prec@1 80.000 (88.152) Prec@5 99.000 (99.043) +2022-11-14 17:01:38,442 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0748) Prec@1 88.000 (88.149) Prec@5 100.000 (99.064) +2022-11-14 17:01:38,449 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0754) Prec@1 83.000 (88.042) Prec@5 98.000 (99.042) +2022-11-14 17:01:38,457 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0445 (0.0748) Prec@1 94.000 (88.163) Prec@5 100.000 (99.061) +2022-11-14 17:01:38,464 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0754) Prec@1 83.000 (88.060) Prec@5 100.000 (99.080) +2022-11-14 17:01:38,472 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0750) Prec@1 91.000 (88.118) Prec@5 100.000 (99.098) +2022-11-14 17:01:38,480 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0750) Prec@1 88.000 (88.115) Prec@5 99.000 (99.096) +2022-11-14 17:01:38,488 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0747) Prec@1 93.000 (88.208) Prec@5 99.000 (99.094) +2022-11-14 17:01:38,496 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0746) Prec@1 89.000 (88.222) Prec@5 99.000 (99.093) +2022-11-14 17:01:38,504 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0748) Prec@1 84.000 (88.145) Prec@5 100.000 (99.109) +2022-11-14 17:01:38,511 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0750) Prec@1 87.000 (88.125) Prec@5 99.000 (99.107) +2022-11-14 17:01:38,519 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0750) Prec@1 87.000 (88.105) Prec@5 99.000 (99.105) +2022-11-14 17:01:38,527 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0749) Prec@1 90.000 (88.138) Prec@5 99.000 (99.103) +2022-11-14 17:01:38,535 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0753) Prec@1 84.000 (88.068) Prec@5 100.000 (99.119) +2022-11-14 17:01:38,543 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0754) Prec@1 84.000 (88.000) Prec@5 100.000 (99.133) +2022-11-14 17:01:38,550 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0754) Prec@1 91.000 (88.049) Prec@5 97.000 (99.098) +2022-11-14 17:01:38,558 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0754) Prec@1 86.000 (88.016) Prec@5 99.000 (99.097) +2022-11-14 17:01:38,566 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0752) Prec@1 91.000 (88.063) Prec@5 100.000 (99.111) +2022-11-14 17:01:38,573 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0312 (0.0745) Prec@1 94.000 (88.156) Prec@5 100.000 (99.125) +2022-11-14 17:01:38,581 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.0750) Prec@1 84.000 (88.092) Prec@5 98.000 (99.108) +2022-11-14 17:01:38,588 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0749) Prec@1 87.000 (88.076) Prec@5 99.000 (99.106) +2022-11-14 17:01:38,596 Test: 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0.0392 (0.0740) Prec@1 93.000 (88.137) Prec@5 100.000 (99.110) +2022-11-14 17:01:38,650 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0737) Prec@1 90.000 (88.162) Prec@5 100.000 (99.122) +2022-11-14 17:01:38,658 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1283 (0.0745) Prec@1 81.000 (88.067) Prec@5 100.000 (99.133) +2022-11-14 17:01:38,666 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0745) Prec@1 89.000 (88.079) Prec@5 100.000 (99.145) +2022-11-14 17:01:38,674 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0746) Prec@1 88.000 (88.078) Prec@5 99.000 (99.143) +2022-11-14 17:01:38,681 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0749) Prec@1 84.000 (88.026) Prec@5 100.000 (99.154) +2022-11-14 17:01:38,689 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0748) Prec@1 89.000 (88.038) Prec@5 100.000 (99.165) +2022-11-14 17:01:38,697 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0748) Prec@1 88.000 (88.037) Prec@5 100.000 (99.175) +2022-11-14 17:01:38,705 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0749) Prec@1 86.000 (88.012) Prec@5 100.000 (99.185) +2022-11-14 17:01:38,712 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0750) Prec@1 87.000 (88.000) Prec@5 100.000 (99.195) +2022-11-14 17:01:38,720 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0752) Prec@1 83.000 (87.940) Prec@5 99.000 (99.193) +2022-11-14 17:01:38,728 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0755) Prec@1 83.000 (87.881) Prec@5 98.000 (99.179) +2022-11-14 17:01:38,736 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0755) Prec@1 87.000 (87.871) Prec@5 100.000 (99.188) +2022-11-14 17:01:38,743 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0758) Prec@1 85.000 (87.837) Prec@5 100.000 (99.198) +2022-11-14 17:01:38,751 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0758) Prec@1 88.000 (87.839) Prec@5 100.000 (99.207) +2022-11-14 17:01:38,759 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0758) Prec@1 87.000 (87.830) Prec@5 99.000 (99.205) +2022-11-14 17:01:38,767 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0757) Prec@1 90.000 (87.854) Prec@5 100.000 (99.213) +2022-11-14 17:01:38,775 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0757) Prec@1 88.000 (87.856) Prec@5 100.000 (99.222) +2022-11-14 17:01:38,782 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0754) Prec@1 92.000 (87.901) Prec@5 100.000 (99.231) +2022-11-14 17:01:38,790 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0752) Prec@1 89.000 (87.913) Prec@5 100.000 (99.239) +2022-11-14 17:01:38,797 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0755) Prec@1 87.000 (87.903) Prec@5 100.000 (99.247) +2022-11-14 17:01:38,805 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0757) Prec@1 86.000 (87.883) Prec@5 98.000 (99.234) +2022-11-14 17:01:38,813 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0756) Prec@1 89.000 (87.895) Prec@5 100.000 (99.242) +2022-11-14 17:01:38,820 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0756) Prec@1 88.000 (87.896) Prec@5 99.000 (99.240) +2022-11-14 17:01:38,828 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0755) Prec@1 91.000 (87.928) Prec@5 98.000 (99.227) +2022-11-14 17:01:38,836 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0757) Prec@1 87.000 (87.918) Prec@5 99.000 (99.224) +2022-11-14 17:01:38,843 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0759) Prec@1 85.000 (87.889) Prec@5 99.000 (99.222) +2022-11-14 17:01:38,850 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0759) Prec@1 88.000 (87.890) Prec@5 100.000 (99.230) +2022-11-14 17:01:38,921 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:01:39,243 Epoch: [443][0/500] Time 0.029 (0.029) Data 0.239 (0.239) Loss 0.0205 (0.0205) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:39,444 Epoch: [443][10/500] Time 0.019 (0.019) Data 0.001 (0.023) Loss 0.0204 (0.0204) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:39,631 Epoch: [443][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0423 (0.0277) Prec@1 95.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 17:01:39,822 Epoch: [443][30/500] Time 0.019 (0.017) Data 0.002 (0.009) Loss 0.0219 (0.0263) Prec@1 98.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,014 Epoch: [443][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0250 (0.0260) Prec@1 95.000 (96.400) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,208 Epoch: [443][50/500] Time 0.020 (0.017) Data 0.001 (0.006) Loss 0.0216 (0.0253) Prec@1 97.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,401 Epoch: [443][60/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0231 (0.0250) Prec@1 97.000 (96.571) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,596 Epoch: [443][70/500] Time 0.022 (0.017) Data 0.002 (0.005) Loss 0.0133 (0.0235) Prec@1 98.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,789 Epoch: [443][80/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0334 (0.0246) Prec@1 95.000 (96.556) Prec@5 100.000 (100.000) +2022-11-14 17:01:40,982 Epoch: [443][90/500] Time 0.020 (0.017) Data 0.002 (0.004) Loss 0.0353 (0.0257) Prec@1 94.000 (96.300) Prec@5 100.000 (100.000) +2022-11-14 17:01:41,177 Epoch: [443][100/500] Time 0.016 (0.017) Data 0.003 (0.004) Loss 0.0267 (0.0258) Prec@1 97.000 (96.364) Prec@5 99.000 (99.909) +2022-11-14 17:01:41,370 Epoch: [443][110/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0079 (0.0243) Prec@1 100.000 (96.667) Prec@5 100.000 (99.917) +2022-11-14 17:01:41,561 Epoch: [443][120/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0326 (0.0249) Prec@1 95.000 (96.538) Prec@5 100.000 (99.923) +2022-11-14 17:01:41,771 Epoch: [443][130/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0192 (0.0245) Prec@1 97.000 (96.571) Prec@5 100.000 (99.929) +2022-11-14 17:01:42,030 Epoch: [443][140/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0509 (0.0263) Prec@1 90.000 (96.133) Prec@5 100.000 (99.933) +2022-11-14 17:01:42,297 Epoch: [443][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0183 (0.0258) Prec@1 98.000 (96.250) Prec@5 100.000 (99.938) +2022-11-14 17:01:42,565 Epoch: [443][160/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0358 (0.0264) Prec@1 95.000 (96.176) Prec@5 99.000 (99.882) +2022-11-14 17:01:42,835 Epoch: [443][170/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0473 (0.0275) Prec@1 93.000 (96.000) Prec@5 100.000 (99.889) +2022-11-14 17:01:43,110 Epoch: [443][180/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0427 (0.0283) Prec@1 92.000 (95.789) Prec@5 100.000 (99.895) +2022-11-14 17:01:43,381 Epoch: [443][190/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0435 (0.0291) Prec@1 90.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:01:43,650 Epoch: [443][200/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0191 (0.0286) Prec@1 97.000 (95.571) Prec@5 100.000 (99.905) +2022-11-14 17:01:43,921 Epoch: [443][210/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0359 (0.0289) Prec@1 95.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 17:01:44,197 Epoch: [443][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0289 (0.0289) Prec@1 94.000 (95.478) Prec@5 100.000 (99.913) +2022-11-14 17:01:44,468 Epoch: [443][230/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0408 (0.0294) Prec@1 93.000 (95.375) Prec@5 98.000 (99.833) +2022-11-14 17:01:44,738 Epoch: [443][240/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0411 (0.0299) Prec@1 95.000 (95.360) Prec@5 100.000 (99.840) +2022-11-14 17:01:45,008 Epoch: [443][250/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0289 (0.0299) Prec@1 97.000 (95.423) Prec@5 100.000 (99.846) +2022-11-14 17:01:45,273 Epoch: [443][260/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0216 (0.0295) Prec@1 97.000 (95.481) Prec@5 100.000 (99.852) +2022-11-14 17:01:45,539 Epoch: [443][270/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0153 (0.0290) Prec@1 98.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:01:45,801 Epoch: [443][280/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0083 (0.0283) Prec@1 98.000 (95.655) Prec@5 100.000 (99.862) +2022-11-14 17:01:46,075 Epoch: [443][290/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0273 (0.0283) Prec@1 96.000 (95.667) Prec@5 99.000 (99.833) +2022-11-14 17:01:46,342 Epoch: [443][300/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0185 (0.0280) Prec@1 96.000 (95.677) Prec@5 100.000 (99.839) +2022-11-14 17:01:46,609 Epoch: [443][310/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0310 (0.0281) Prec@1 96.000 (95.688) Prec@5 100.000 (99.844) +2022-11-14 17:01:46,875 Epoch: [443][320/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0281) Prec@1 97.000 (95.727) Prec@5 100.000 (99.848) +2022-11-14 17:01:47,145 Epoch: [443][330/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0197 (0.0278) Prec@1 98.000 (95.794) Prec@5 100.000 (99.853) +2022-11-14 17:01:47,405 Epoch: [443][340/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0228 (0.0277) Prec@1 97.000 (95.829) Prec@5 99.000 (99.829) +2022-11-14 17:01:47,667 Epoch: [443][350/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0143 (0.0273) Prec@1 98.000 (95.889) Prec@5 100.000 (99.833) +2022-11-14 17:01:47,928 Epoch: [443][360/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0367 (0.0276) Prec@1 93.000 (95.811) Prec@5 99.000 (99.811) +2022-11-14 17:01:48,193 Epoch: [443][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0369 (0.0278) Prec@1 91.000 (95.684) Prec@5 100.000 (99.816) +2022-11-14 17:01:48,461 Epoch: [443][380/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0186 (0.0276) Prec@1 96.000 (95.692) Prec@5 100.000 (99.821) +2022-11-14 17:01:48,732 Epoch: [443][390/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0329 (0.0277) Prec@1 95.000 (95.675) Prec@5 100.000 (99.825) +2022-11-14 17:01:48,998 Epoch: [443][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0242 (0.0276) Prec@1 95.000 (95.659) Prec@5 100.000 (99.829) +2022-11-14 17:01:49,261 Epoch: [443][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0309 (0.0277) Prec@1 96.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 17:01:49,526 Epoch: [443][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0451 (0.0281) Prec@1 92.000 (95.581) Prec@5 100.000 (99.837) +2022-11-14 17:01:49,788 Epoch: [443][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0339 (0.0282) Prec@1 93.000 (95.523) Prec@5 100.000 (99.841) +2022-11-14 17:01:50,051 Epoch: [443][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0208 (0.0281) Prec@1 97.000 (95.556) Prec@5 99.000 (99.822) +2022-11-14 17:01:50,312 Epoch: [443][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0111 (0.0277) Prec@1 98.000 (95.609) Prec@5 100.000 (99.826) +2022-11-14 17:01:50,575 Epoch: [443][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0351 (0.0279) Prec@1 93.000 (95.553) Prec@5 100.000 (99.830) +2022-11-14 17:01:50,838 Epoch: [443][470/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0368 (0.0281) Prec@1 94.000 (95.521) Prec@5 100.000 (99.833) +2022-11-14 17:01:51,102 Epoch: [443][480/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0254 (0.0280) Prec@1 97.000 (95.551) Prec@5 100.000 (99.837) +2022-11-14 17:01:51,361 Epoch: [443][490/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0494 (0.0284) Prec@1 92.000 (95.480) Prec@5 99.000 (99.820) +2022-11-14 17:01:51,594 Epoch: [443][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0229 (0.0283) Prec@1 97.000 (95.510) Prec@5 100.000 (99.824) +2022-11-14 17:01:51,907 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0520 (0.0520) Prec@1 92.000 (92.000) Prec@5 98.000 (98.000) +2022-11-14 17:01:51,916 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0582 (0.0551) Prec@1 91.000 (91.500) Prec@5 100.000 (99.000) +2022-11-14 17:01:51,923 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0742 (0.0615) Prec@1 89.000 (90.667) Prec@5 100.000 (99.333) +2022-11-14 17:01:51,933 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0633) Prec@1 89.000 (90.250) Prec@5 99.000 (99.250) +2022-11-14 17:01:51,940 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0855 (0.0677) Prec@1 88.000 (89.800) Prec@5 100.000 (99.400) +2022-11-14 17:01:51,946 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0490 (0.0646) Prec@1 91.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 17:01:51,953 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0634) Prec@1 90.000 (90.000) Prec@5 100.000 (99.571) +2022-11-14 17:01:51,962 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0697) Prec@1 81.000 (88.875) Prec@5 99.000 (99.500) +2022-11-14 17:01:51,969 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0704) Prec@1 87.000 (88.667) Prec@5 99.000 (99.444) +2022-11-14 17:01:51,976 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0711) Prec@1 86.000 (88.400) Prec@5 98.000 (99.300) +2022-11-14 17:01:51,984 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0700) Prec@1 90.000 (88.545) Prec@5 100.000 (99.364) +2022-11-14 17:01:51,992 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0696) Prec@1 87.000 (88.417) Prec@5 99.000 (99.333) +2022-11-14 17:01:51,999 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0700) Prec@1 89.000 (88.462) Prec@5 100.000 (99.385) +2022-11-14 17:01:52,007 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0704) Prec@1 87.000 (88.357) Prec@5 99.000 (99.357) +2022-11-14 17:01:52,015 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0707) Prec@1 87.000 (88.267) Prec@5 100.000 (99.400) +2022-11-14 17:01:52,022 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0711) Prec@1 87.000 (88.188) Prec@5 99.000 (99.375) +2022-11-14 17:01:52,030 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0703) Prec@1 92.000 (88.412) Prec@5 99.000 (99.353) +2022-11-14 17:01:52,038 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1193 (0.0731) Prec@1 82.000 (88.056) Prec@5 100.000 (99.389) +2022-11-14 17:01:52,045 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0995 (0.0745) Prec@1 81.000 (87.684) Prec@5 99.000 (99.368) +2022-11-14 17:01:52,053 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0750) Prec@1 88.000 (87.700) Prec@5 97.000 (99.250) +2022-11-14 17:01:52,061 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0750) Prec@1 88.000 (87.714) Prec@5 99.000 (99.238) +2022-11-14 17:01:52,069 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0750) Prec@1 87.000 (87.682) Prec@5 100.000 (99.273) +2022-11-14 17:01:52,076 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0758) Prec@1 86.000 (87.609) Prec@5 98.000 (99.217) +2022-11-14 17:01:52,084 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0760) Prec@1 88.000 (87.625) Prec@5 100.000 (99.250) +2022-11-14 17:01:52,092 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0770) Prec@1 86.000 (87.560) Prec@5 100.000 (99.280) +2022-11-14 17:01:52,100 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0775) Prec@1 87.000 (87.538) Prec@5 98.000 (99.231) +2022-11-14 17:01:52,107 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0768) Prec@1 90.000 (87.630) Prec@5 100.000 (99.259) +2022-11-14 17:01:52,115 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0768) Prec@1 88.000 (87.643) Prec@5 99.000 (99.250) +2022-11-14 17:01:52,122 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0763) Prec@1 91.000 (87.759) Prec@5 98.000 (99.207) +2022-11-14 17:01:52,130 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0757) Prec@1 90.000 (87.833) Prec@5 99.000 (99.200) +2022-11-14 17:01:52,138 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0758) Prec@1 87.000 (87.806) Prec@5 100.000 (99.226) +2022-11-14 17:01:52,145 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0437 (0.0748) Prec@1 96.000 (88.062) Prec@5 100.000 (99.250) +2022-11-14 17:01:52,153 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0748) Prec@1 86.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 17:01:52,161 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 88.000 (88.000) Prec@5 100.000 (99.294) +2022-11-14 17:01:52,168 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0757) Prec@1 84.000 (87.886) Prec@5 97.000 (99.229) +2022-11-14 17:01:52,176 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0756) Prec@1 88.000 (87.889) Prec@5 99.000 (99.222) +2022-11-14 17:01:52,183 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0752) Prec@1 88.000 (87.892) Prec@5 99.000 (99.216) +2022-11-14 17:01:52,191 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0755) Prec@1 86.000 (87.842) Prec@5 98.000 (99.184) +2022-11-14 17:01:52,199 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0749) Prec@1 94.000 (88.000) Prec@5 99.000 (99.179) +2022-11-14 17:01:52,206 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0747) Prec@1 91.000 (88.075) Prec@5 100.000 (99.200) +2022-11-14 17:01:52,214 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0751) Prec@1 85.000 (88.000) Prec@5 99.000 (99.195) +2022-11-14 17:01:52,223 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0750) Prec@1 89.000 (88.024) Prec@5 99.000 (99.190) +2022-11-14 17:01:52,231 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0744) Prec@1 91.000 (88.093) Prec@5 99.000 (99.186) +2022-11-14 17:01:52,238 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0745) Prec@1 88.000 (88.091) Prec@5 99.000 (99.182) +2022-11-14 17:01:52,246 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0741) Prec@1 89.000 (88.111) Prec@5 100.000 (99.200) +2022-11-14 17:01:52,254 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 84.000 (88.022) Prec@5 100.000 (99.217) +2022-11-14 17:01:52,261 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0742) Prec@1 91.000 (88.085) Prec@5 100.000 (99.234) +2022-11-14 17:01:52,269 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0744) Prec@1 88.000 (88.083) Prec@5 100.000 (99.250) +2022-11-14 17:01:52,277 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0739) Prec@1 92.000 (88.163) Prec@5 99.000 (99.245) +2022-11-14 17:01:52,284 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0742) Prec@1 86.000 (88.120) Prec@5 99.000 (99.240) +2022-11-14 17:01:52,292 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0739) Prec@1 89.000 (88.137) Prec@5 100.000 (99.255) +2022-11-14 17:01:52,299 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0743) Prec@1 86.000 (88.096) Prec@5 100.000 (99.269) +2022-11-14 17:01:52,307 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0744) Prec@1 87.000 (88.075) Prec@5 100.000 (99.283) +2022-11-14 17:01:52,315 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0743) Prec@1 89.000 (88.093) Prec@5 100.000 (99.296) +2022-11-14 17:01:52,322 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0745) Prec@1 86.000 (88.055) Prec@5 100.000 (99.309) +2022-11-14 17:01:52,330 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0742) Prec@1 92.000 (88.125) Prec@5 99.000 (99.304) +2022-11-14 17:01:52,337 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0739) Prec@1 89.000 (88.140) Prec@5 99.000 (99.298) +2022-11-14 17:01:52,345 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0736) Prec@1 93.000 (88.224) Prec@5 100.000 (99.310) +2022-11-14 17:01:52,353 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0737) Prec@1 88.000 (88.220) Prec@5 100.000 (99.322) +2022-11-14 17:01:52,360 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0738) Prec@1 86.000 (88.183) Prec@5 99.000 (99.317) +2022-11-14 17:01:52,368 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0740) Prec@1 86.000 (88.148) Prec@5 100.000 (99.328) +2022-11-14 17:01:52,376 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0737) Prec@1 90.000 (88.177) Prec@5 100.000 (99.339) +2022-11-14 17:01:52,387 Test: [62/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0737) Prec@1 90.000 (88.206) Prec@5 99.000 (99.333) +2022-11-14 17:01:52,397 Test: [63/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0330 (0.0730) Prec@1 95.000 (88.312) Prec@5 100.000 (99.344) +2022-11-14 17:01:52,405 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1207 (0.0738) Prec@1 79.000 (88.169) Prec@5 98.000 (99.323) +2022-11-14 17:01:52,413 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0738) Prec@1 86.000 (88.136) Prec@5 99.000 (99.318) +2022-11-14 17:01:52,421 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0414 (0.0733) Prec@1 94.000 (88.224) Prec@5 100.000 (99.328) +2022-11-14 17:01:52,429 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0733) Prec@1 89.000 (88.235) Prec@5 99.000 (99.324) +2022-11-14 17:01:52,437 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0445 (0.0729) Prec@1 92.000 (88.290) Prec@5 100.000 (99.333) +2022-11-14 17:01:52,445 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0728) Prec@1 90.000 (88.314) Prec@5 99.000 (99.329) +2022-11-14 17:01:52,453 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0732) Prec@1 87.000 (88.296) Prec@5 98.000 (99.310) +2022-11-14 17:01:52,461 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0729) Prec@1 92.000 (88.347) Prec@5 99.000 (99.306) +2022-11-14 17:01:52,469 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0470 (0.0725) Prec@1 93.000 (88.411) Prec@5 100.000 (99.315) +2022-11-14 17:01:52,477 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0372 (0.0720) Prec@1 95.000 (88.500) Prec@5 100.000 (99.324) +2022-11-14 17:01:52,484 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0722) Prec@1 85.000 (88.453) Prec@5 100.000 (99.333) +2022-11-14 17:01:52,492 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0719) Prec@1 92.000 (88.500) Prec@5 99.000 (99.329) +2022-11-14 17:01:52,500 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0718) Prec@1 89.000 (88.506) Prec@5 99.000 (99.325) +2022-11-14 17:01:52,507 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0722) Prec@1 85.000 (88.462) Prec@5 98.000 (99.308) +2022-11-14 17:01:52,515 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0723) Prec@1 87.000 (88.443) Prec@5 99.000 (99.304) +2022-11-14 17:01:52,523 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0723) Prec@1 88.000 (88.438) Prec@5 100.000 (99.312) +2022-11-14 17:01:52,530 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0723) Prec@1 88.000 (88.432) Prec@5 98.000 (99.296) +2022-11-14 17:01:52,538 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0724) Prec@1 88.000 (88.427) Prec@5 100.000 (99.305) +2022-11-14 17:01:52,545 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0724) Prec@1 89.000 (88.434) Prec@5 100.000 (99.313) +2022-11-14 17:01:52,553 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0723) Prec@1 89.000 (88.440) Prec@5 100.000 (99.321) +2022-11-14 17:01:52,561 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0724) Prec@1 88.000 (88.435) Prec@5 100.000 (99.329) +2022-11-14 17:01:52,568 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0726) Prec@1 85.000 (88.395) Prec@5 100.000 (99.337) +2022-11-14 17:01:52,576 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0728) Prec@1 85.000 (88.356) Prec@5 100.000 (99.345) +2022-11-14 17:01:52,584 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0729) Prec@1 86.000 (88.330) Prec@5 97.000 (99.318) +2022-11-14 17:01:52,591 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0730) Prec@1 87.000 (88.315) Prec@5 99.000 (99.315) +2022-11-14 17:01:52,599 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0730) Prec@1 92.000 (88.356) Prec@5 100.000 (99.322) +2022-11-14 17:01:52,606 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0728) Prec@1 93.000 (88.407) Prec@5 99.000 (99.319) +2022-11-14 17:01:52,614 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0726) Prec@1 92.000 (88.446) Prec@5 99.000 (99.315) +2022-11-14 17:01:52,621 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0728) Prec@1 82.000 (88.376) Prec@5 100.000 (99.323) +2022-11-14 17:01:52,629 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0728) Prec@1 88.000 (88.372) Prec@5 98.000 (99.309) +2022-11-14 17:01:52,636 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0727) Prec@1 88.000 (88.368) Prec@5 99.000 (99.305) +2022-11-14 17:01:52,644 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0726) Prec@1 91.000 (88.396) Prec@5 99.000 (99.302) +2022-11-14 17:01:52,651 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0726) Prec@1 90.000 (88.412) Prec@5 99.000 (99.299) +2022-11-14 17:01:52,659 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0728) Prec@1 86.000 (88.388) Prec@5 97.000 (99.276) +2022-11-14 17:01:52,666 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0731) Prec@1 84.000 (88.343) Prec@5 100.000 (99.283) +2022-11-14 17:01:52,674 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0729) Prec@1 92.000 (88.380) Prec@5 100.000 (99.290) +2022-11-14 17:01:52,730 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:01:53,056 Epoch: [444][0/500] Time 0.024 (0.024) Data 0.244 (0.244) Loss 0.0112 (0.0112) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:53,262 Epoch: [444][10/500] Time 0.017 (0.019) Data 0.002 (0.024) Loss 0.0148 (0.0130) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:53,463 Epoch: [444][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0216 (0.0159) Prec@1 95.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 17:01:53,664 Epoch: [444][30/500] Time 0.017 (0.018) Data 0.002 (0.010) Loss 0.0405 (0.0220) Prec@1 91.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:01:53,872 Epoch: [444][40/500] Time 0.016 (0.018) Data 0.002 (0.008) Loss 0.0211 (0.0218) Prec@1 97.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:01:54,074 Epoch: [444][50/500] Time 0.017 (0.018) Data 0.002 (0.007) Loss 0.0140 (0.0205) Prec@1 98.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 17:01:54,278 Epoch: [444][60/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0312 (0.0220) Prec@1 94.000 (95.571) Prec@5 99.000 (99.857) +2022-11-14 17:01:54,500 Epoch: [444][70/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0127 (0.0209) Prec@1 97.000 (95.750) Prec@5 100.000 (99.875) +2022-11-14 17:01:54,706 Epoch: [444][80/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0298 (0.0219) Prec@1 95.000 (95.667) Prec@5 100.000 (99.889) +2022-11-14 17:01:54,902 Epoch: [444][90/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.0388 (0.0236) Prec@1 93.000 (95.400) Prec@5 100.000 (99.900) +2022-11-14 17:01:55,099 Epoch: [444][100/500] Time 0.019 (0.018) Data 0.002 (0.004) Loss 0.0204 (0.0233) Prec@1 97.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 17:01:55,293 Epoch: [444][110/500] Time 0.016 (0.018) Data 0.001 (0.004) Loss 0.0188 (0.0229) Prec@1 97.000 (95.667) Prec@5 100.000 (99.917) +2022-11-14 17:01:55,484 Epoch: [444][120/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0264 (0.0232) Prec@1 95.000 (95.615) Prec@5 100.000 (99.923) +2022-11-14 17:01:55,681 Epoch: [444][130/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.0389 (0.0243) Prec@1 93.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 17:01:55,876 Epoch: [444][140/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0464 (0.0258) Prec@1 92.000 (95.200) Prec@5 100.000 (99.933) +2022-11-14 17:01:56,093 Epoch: [444][150/500] Time 0.023 (0.018) Data 0.001 (0.003) Loss 0.0383 (0.0265) Prec@1 94.000 (95.125) Prec@5 100.000 (99.938) +2022-11-14 17:01:56,381 Epoch: [444][160/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0332 (0.0269) Prec@1 94.000 (95.059) Prec@5 100.000 (99.941) +2022-11-14 17:01:56,678 Epoch: [444][170/500] Time 0.028 (0.019) Data 0.001 (0.003) Loss 0.0268 (0.0269) Prec@1 97.000 (95.167) Prec@5 100.000 (99.944) +2022-11-14 17:01:56,975 Epoch: [444][180/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0160 (0.0264) Prec@1 98.000 (95.316) Prec@5 100.000 (99.947) +2022-11-14 17:01:57,272 Epoch: [444][190/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0188 (0.0260) Prec@1 97.000 (95.400) Prec@5 100.000 (99.950) +2022-11-14 17:01:57,571 Epoch: [444][200/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0500 (0.0271) Prec@1 92.000 (95.238) Prec@5 100.000 (99.952) +2022-11-14 17:01:57,866 Epoch: [444][210/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0401 (0.0277) Prec@1 93.000 (95.136) Prec@5 100.000 (99.955) +2022-11-14 17:01:58,160 Epoch: [444][220/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0203 (0.0274) Prec@1 97.000 (95.217) Prec@5 100.000 (99.957) +2022-11-14 17:01:58,454 Epoch: [444][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0282 (0.0274) Prec@1 95.000 (95.208) Prec@5 100.000 (99.958) +2022-11-14 17:01:58,747 Epoch: [444][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0340 (0.0277) Prec@1 94.000 (95.160) Prec@5 99.000 (99.920) +2022-11-14 17:01:59,042 Epoch: [444][250/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0141 (0.0272) Prec@1 98.000 (95.269) Prec@5 100.000 (99.923) +2022-11-14 17:01:59,340 Epoch: [444][260/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0141 (0.0267) Prec@1 97.000 (95.333) Prec@5 100.000 (99.926) +2022-11-14 17:01:59,635 Epoch: [444][270/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0417 (0.0272) Prec@1 92.000 (95.214) Prec@5 100.000 (99.929) +2022-11-14 17:01:59,926 Epoch: [444][280/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0225 (0.0271) Prec@1 98.000 (95.310) Prec@5 100.000 (99.931) +2022-11-14 17:02:00,222 Epoch: [444][290/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0262 (0.0270) Prec@1 95.000 (95.300) Prec@5 99.000 (99.900) +2022-11-14 17:02:00,512 Epoch: [444][300/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0357 (0.0273) Prec@1 94.000 (95.258) Prec@5 100.000 (99.903) +2022-11-14 17:02:00,799 Epoch: [444][310/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0354 (0.0276) Prec@1 94.000 (95.219) Prec@5 100.000 (99.906) +2022-11-14 17:02:01,096 Epoch: [444][320/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0313 (0.0277) Prec@1 95.000 (95.212) Prec@5 99.000 (99.879) +2022-11-14 17:02:01,385 Epoch: [444][330/500] Time 0.028 (0.022) Data 0.001 (0.002) Loss 0.0241 (0.0276) Prec@1 96.000 (95.235) Prec@5 100.000 (99.882) +2022-11-14 17:02:01,678 Epoch: [444][340/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0477 (0.0281) Prec@1 91.000 (95.114) Prec@5 99.000 (99.857) +2022-11-14 17:02:01,973 Epoch: [444][350/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0159 (0.0278) Prec@1 98.000 (95.194) Prec@5 100.000 (99.861) +2022-11-14 17:02:02,262 Epoch: [444][360/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0138 (0.0274) Prec@1 97.000 (95.243) Prec@5 100.000 (99.865) +2022-11-14 17:02:02,549 Epoch: [444][370/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0424 (0.0278) Prec@1 91.000 (95.132) Prec@5 99.000 (99.842) +2022-11-14 17:02:02,840 Epoch: [444][380/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0223 (0.0277) Prec@1 96.000 (95.154) Prec@5 99.000 (99.821) +2022-11-14 17:02:03,135 Epoch: [444][390/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0408 (0.0280) Prec@1 92.000 (95.075) Prec@5 100.000 (99.825) +2022-11-14 17:02:03,423 Epoch: [444][400/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0123 (0.0276) Prec@1 99.000 (95.171) Prec@5 100.000 (99.829) +2022-11-14 17:02:03,714 Epoch: [444][410/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0334 (0.0278) Prec@1 92.000 (95.095) Prec@5 99.000 (99.810) +2022-11-14 17:02:04,006 Epoch: [444][420/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0269 (0.0277) Prec@1 96.000 (95.116) Prec@5 100.000 (99.814) +2022-11-14 17:02:04,295 Epoch: [444][430/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0521 (0.0283) Prec@1 93.000 (95.068) Prec@5 99.000 (99.795) +2022-11-14 17:02:04,586 Epoch: [444][440/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0155 (0.0280) Prec@1 99.000 (95.156) Prec@5 100.000 (99.800) +2022-11-14 17:02:04,878 Epoch: [444][450/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0278 (0.0280) Prec@1 96.000 (95.174) Prec@5 100.000 (99.804) +2022-11-14 17:02:05,164 Epoch: [444][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0488 (0.0284) Prec@1 92.000 (95.106) Prec@5 100.000 (99.809) +2022-11-14 17:02:05,451 Epoch: [444][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0421 (0.0287) Prec@1 94.000 (95.083) Prec@5 100.000 (99.812) +2022-11-14 17:02:05,733 Epoch: [444][480/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0080 (0.0283) Prec@1 100.000 (95.184) Prec@5 100.000 (99.816) +2022-11-14 17:02:06,024 Epoch: [444][490/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0358 (0.0285) Prec@1 93.000 (95.140) Prec@5 100.000 (99.820) +2022-11-14 17:02:06,285 Epoch: [444][499/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0331 (0.0285) Prec@1 94.000 (95.118) Prec@5 100.000 (99.824) +2022-11-14 17:02:06,582 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0593 (0.0593) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:06,590 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0729 (0.0661) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:06,598 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0654) Prec@1 91.000 (90.667) Prec@5 100.000 (100.000) +2022-11-14 17:02:06,610 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0683) Prec@1 86.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 17:02:06,617 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0763 (0.0699) Prec@1 88.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 17:02:06,624 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0664) Prec@1 92.000 (89.667) Prec@5 100.000 (99.833) +2022-11-14 17:02:06,631 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0674) Prec@1 89.000 (89.571) Prec@5 100.000 (99.857) +2022-11-14 17:02:06,639 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0705) Prec@1 86.000 (89.125) Prec@5 99.000 (99.750) +2022-11-14 17:02:06,646 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0702) Prec@1 89.000 (89.111) Prec@5 99.000 (99.667) +2022-11-14 17:02:06,653 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0705) Prec@1 89.000 (89.100) Prec@5 97.000 (99.400) +2022-11-14 17:02:06,660 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0683) Prec@1 91.000 (89.273) Prec@5 100.000 (99.455) +2022-11-14 17:02:06,668 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0685) Prec@1 89.000 (89.250) Prec@5 100.000 (99.500) +2022-11-14 17:02:06,676 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0671) Prec@1 92.000 (89.462) Prec@5 100.000 (99.538) +2022-11-14 17:02:06,683 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0669) Prec@1 90.000 (89.500) Prec@5 100.000 (99.571) +2022-11-14 17:02:06,691 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0673) Prec@1 88.000 (89.400) Prec@5 99.000 (99.533) +2022-11-14 17:02:06,698 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0674) Prec@1 88.000 (89.312) Prec@5 100.000 (99.562) +2022-11-14 17:02:06,706 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0488 (0.0663) Prec@1 92.000 (89.471) Prec@5 99.000 (99.529) +2022-11-14 17:02:06,713 Test: [17/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1127 (0.0688) Prec@1 82.000 (89.056) Prec@5 100.000 (99.556) +2022-11-14 17:02:06,721 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0976 (0.0704) Prec@1 81.000 (88.632) Prec@5 100.000 (99.579) +2022-11-14 17:02:06,728 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1005 (0.0719) Prec@1 86.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 17:02:06,735 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0725) Prec@1 87.000 (88.429) Prec@5 99.000 (99.476) +2022-11-14 17:02:06,743 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0731) Prec@1 87.000 (88.364) Prec@5 100.000 (99.500) +2022-11-14 17:02:06,750 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1005 (0.0743) Prec@1 86.000 (88.261) Prec@5 97.000 (99.391) +2022-11-14 17:02:06,758 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0744) Prec@1 86.000 (88.167) Prec@5 99.000 (99.375) +2022-11-14 17:02:06,765 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0905 (0.0751) Prec@1 85.000 (88.040) Prec@5 100.000 (99.400) +2022-11-14 17:02:06,773 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0910 (0.0757) Prec@1 84.000 (87.885) Prec@5 99.000 (99.385) +2022-11-14 17:02:06,780 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0438 (0.0745) Prec@1 93.000 (88.074) Prec@5 100.000 (99.407) +2022-11-14 17:02:06,788 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0742) Prec@1 89.000 (88.107) Prec@5 100.000 (99.429) +2022-11-14 17:02:06,795 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0741) Prec@1 89.000 (88.138) Prec@5 100.000 (99.448) +2022-11-14 17:02:06,803 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0708 (0.0740) Prec@1 88.000 (88.133) Prec@5 99.000 (99.433) +2022-11-14 17:02:06,810 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0688 (0.0739) Prec@1 90.000 (88.194) Prec@5 100.000 (99.452) +2022-11-14 17:02:06,818 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0569 (0.0733) Prec@1 91.000 (88.281) Prec@5 100.000 (99.469) +2022-11-14 17:02:06,825 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0621 (0.0730) Prec@1 89.000 (88.303) Prec@5 100.000 (99.485) +2022-11-14 17:02:06,833 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0962 (0.0737) Prec@1 84.000 (88.176) Prec@5 99.000 (99.471) +2022-11-14 17:02:06,840 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0776 (0.0738) Prec@1 89.000 (88.200) Prec@5 97.000 (99.400) +2022-11-14 17:02:06,848 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0665 (0.0736) Prec@1 90.000 (88.250) Prec@5 99.000 (99.389) +2022-11-14 17:02:06,855 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0653 (0.0734) Prec@1 89.000 (88.270) Prec@5 99.000 (99.378) +2022-11-14 17:02:06,863 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0828 (0.0736) Prec@1 85.000 (88.184) Prec@5 99.000 (99.368) +2022-11-14 17:02:06,871 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0740 (0.0736) Prec@1 90.000 (88.231) Prec@5 99.000 (99.359) +2022-11-14 17:02:06,878 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 88.000 (88.225) Prec@5 98.000 (99.325) +2022-11-14 17:02:06,886 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0947 (0.0743) Prec@1 84.000 (88.122) Prec@5 99.000 (99.317) +2022-11-14 17:02:06,893 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0746) Prec@1 86.000 (88.071) Prec@5 100.000 (99.333) +2022-11-14 17:02:06,901 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0498 (0.0741) Prec@1 93.000 (88.186) Prec@5 100.000 (99.349) +2022-11-14 17:02:06,909 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0705 (0.0740) Prec@1 91.000 (88.250) Prec@5 99.000 (99.341) +2022-11-14 17:02:06,916 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0739) Prec@1 88.000 (88.244) Prec@5 100.000 (99.356) +2022-11-14 17:02:06,924 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1010 (0.0745) Prec@1 85.000 (88.174) Prec@5 100.000 (99.370) +2022-11-14 17:02:06,931 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0741) Prec@1 90.000 (88.213) Prec@5 99.000 (99.362) +2022-11-14 17:02:06,939 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0958 (0.0746) Prec@1 85.000 (88.146) Prec@5 99.000 (99.354) +2022-11-14 17:02:06,947 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0519 (0.0741) Prec@1 90.000 (88.184) Prec@5 99.000 (99.347) +2022-11-14 17:02:06,954 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0744) Prec@1 85.000 (88.120) Prec@5 100.000 (99.360) +2022-11-14 17:02:06,962 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0741) Prec@1 91.000 (88.176) Prec@5 100.000 (99.373) +2022-11-14 17:02:06,969 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0742) Prec@1 88.000 (88.173) Prec@5 99.000 (99.365) +2022-11-14 17:02:06,977 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0526 (0.0738) Prec@1 90.000 (88.208) Prec@5 99.000 (99.358) +2022-11-14 17:02:06,984 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0844 (0.0740) Prec@1 87.000 (88.185) Prec@5 99.000 (99.352) +2022-11-14 17:02:06,992 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0853 (0.0742) Prec@1 85.000 (88.127) Prec@5 100.000 (99.364) +2022-11-14 17:02:07,000 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0741) Prec@1 89.000 (88.143) Prec@5 99.000 (99.357) +2022-11-14 17:02:07,007 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0682 (0.0740) Prec@1 87.000 (88.123) Prec@5 100.000 (99.368) +2022-11-14 17:02:07,015 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0627 (0.0738) Prec@1 90.000 (88.155) Prec@5 98.000 (99.345) +2022-11-14 17:02:07,022 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0740) Prec@1 85.000 (88.102) Prec@5 100.000 (99.356) +2022-11-14 17:02:07,030 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0762 (0.0741) Prec@1 87.000 (88.083) Prec@5 100.000 (99.367) +2022-11-14 17:02:07,037 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0937 (0.0744) Prec@1 86.000 (88.049) Prec@5 100.000 (99.377) +2022-11-14 17:02:07,045 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0743) Prec@1 88.000 (88.048) Prec@5 100.000 (99.387) +2022-11-14 17:02:07,053 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0499 (0.0739) Prec@1 93.000 (88.127) Prec@5 100.000 (99.397) +2022-11-14 17:02:07,060 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0425 (0.0734) Prec@1 92.000 (88.188) Prec@5 100.000 (99.406) +2022-11-14 17:02:07,068 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0736) Prec@1 86.000 (88.154) Prec@5 100.000 (99.415) +2022-11-14 17:02:07,076 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0942 (0.0739) Prec@1 83.000 (88.076) Prec@5 98.000 (99.394) +2022-11-14 17:02:07,085 Test: [66/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0322 (0.0733) Prec@1 94.000 (88.164) Prec@5 99.000 (99.388) +2022-11-14 17:02:07,092 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0731) Prec@1 90.000 (88.191) Prec@5 100.000 (99.397) +2022-11-14 17:02:07,100 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0731) Prec@1 87.000 (88.174) Prec@5 99.000 (99.391) +2022-11-14 17:02:07,108 Test: [69/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0902 (0.0734) Prec@1 83.000 (88.100) Prec@5 99.000 (99.386) +2022-11-14 17:02:07,117 Test: [70/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1021 (0.0738) Prec@1 87.000 (88.085) Prec@5 98.000 (99.366) +2022-11-14 17:02:07,124 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0558 (0.0735) Prec@1 90.000 (88.111) Prec@5 99.000 (99.361) +2022-11-14 17:02:07,132 Test: [72/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0453 (0.0732) Prec@1 95.000 (88.205) Prec@5 99.000 (99.356) +2022-11-14 17:02:07,140 Test: [73/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0593 (0.0730) Prec@1 91.000 (88.243) Prec@5 100.000 (99.365) +2022-11-14 17:02:07,147 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0862 (0.0731) Prec@1 85.000 (88.200) Prec@5 99.000 (99.360) +2022-11-14 17:02:07,155 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0730) Prec@1 89.000 (88.211) Prec@5 100.000 (99.368) +2022-11-14 17:02:07,163 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0681 (0.0730) Prec@1 89.000 (88.221) Prec@5 99.000 (99.364) +2022-11-14 17:02:07,170 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0902 (0.0732) Prec@1 86.000 (88.192) Prec@5 97.000 (99.333) +2022-11-14 17:02:07,178 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0736 (0.0732) Prec@1 89.000 (88.203) Prec@5 100.000 (99.342) +2022-11-14 17:02:07,185 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0875 (0.0734) Prec@1 84.000 (88.150) Prec@5 100.000 (99.350) +2022-11-14 17:02:07,192 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0724 (0.0734) Prec@1 89.000 (88.160) Prec@5 98.000 (99.333) +2022-11-14 17:02:07,200 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0734) Prec@1 86.000 (88.134) Prec@5 99.000 (99.329) +2022-11-14 17:02:07,207 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0795 (0.0735) Prec@1 87.000 (88.120) Prec@5 100.000 (99.337) +2022-11-14 17:02:07,214 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0734) Prec@1 90.000 (88.143) Prec@5 100.000 (99.345) +2022-11-14 17:02:07,222 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0994 (0.0737) Prec@1 85.000 (88.106) Prec@5 99.000 (99.341) +2022-11-14 17:02:07,229 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1272 (0.0743) Prec@1 82.000 (88.035) Prec@5 100.000 (99.349) +2022-11-14 17:02:07,237 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0723 (0.0743) Prec@1 87.000 (88.023) Prec@5 98.000 (99.333) +2022-11-14 17:02:07,245 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0718 (0.0743) Prec@1 91.000 (88.057) Prec@5 99.000 (99.330) +2022-11-14 17:02:07,253 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0743) Prec@1 86.000 (88.034) Prec@5 100.000 (99.337) +2022-11-14 17:02:07,260 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0743) Prec@1 86.000 (88.011) Prec@5 98.000 (99.322) +2022-11-14 17:02:07,268 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0739 (0.0743) Prec@1 87.000 (88.000) Prec@5 100.000 (99.330) +2022-11-14 17:02:07,275 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0410 (0.0740) Prec@1 93.000 (88.054) Prec@5 100.000 (99.337) +2022-11-14 17:02:07,283 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0740) Prec@1 88.000 (88.054) Prec@5 100.000 (99.344) +2022-11-14 17:02:07,290 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0668 (0.0739) Prec@1 90.000 (88.074) Prec@5 100.000 (99.351) +2022-11-14 17:02:07,298 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0739) Prec@1 90.000 (88.095) Prec@5 98.000 (99.337) +2022-11-14 17:02:07,305 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0738) Prec@1 91.000 (88.125) Prec@5 99.000 (99.333) +2022-11-14 17:02:07,313 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0737) Prec@1 89.000 (88.134) Prec@5 99.000 (99.330) +2022-11-14 17:02:07,320 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0814 (0.0738) Prec@1 88.000 (88.133) Prec@5 98.000 (99.316) +2022-11-14 17:02:07,328 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1077 (0.0741) Prec@1 83.000 (88.081) Prec@5 98.000 (99.303) +2022-11-14 17:02:07,335 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0741) Prec@1 88.000 (88.080) Prec@5 100.000 (99.310) +2022-11-14 17:02:07,388 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:02:07,703 Epoch: [445][0/500] Time 0.022 (0.022) Data 0.233 (0.233) Loss 0.0378 (0.0378) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:07,894 Epoch: [445][10/500] Time 0.016 (0.017) Data 0.002 (0.023) Loss 0.0111 (0.0245) Prec@1 98.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:08,079 Epoch: [445][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0213 (0.0234) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:02:08,264 Epoch: [445][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0406 (0.0277) Prec@1 95.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 17:02:08,449 Epoch: [445][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0355 (0.0293) Prec@1 94.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:02:08,633 Epoch: [445][50/500] Time 0.017 (0.016) Data 0.001 (0.006) Loss 0.0340 (0.0301) Prec@1 94.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:02:08,816 Epoch: [445][60/500] Time 0.016 (0.016) Data 0.002 (0.005) Loss 0.0256 (0.0294) Prec@1 96.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 17:02:09,004 Epoch: [445][70/500] Time 0.017 (0.016) Data 0.001 (0.005) Loss 0.0273 (0.0292) Prec@1 96.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 17:02:09,192 Epoch: [445][80/500] Time 0.017 (0.016) Data 0.002 (0.004) Loss 0.0608 (0.0327) Prec@1 89.000 (94.556) Prec@5 100.000 (99.889) +2022-11-14 17:02:09,378 Epoch: [445][90/500] Time 0.016 (0.016) Data 0.002 (0.004) Loss 0.0254 (0.0319) Prec@1 96.000 (94.700) Prec@5 100.000 (99.900) +2022-11-14 17:02:09,563 Epoch: [445][100/500] Time 0.017 (0.016) Data 0.001 (0.004) Loss 0.0182 (0.0307) Prec@1 98.000 (95.000) Prec@5 100.000 (99.909) +2022-11-14 17:02:09,750 Epoch: [445][110/500] Time 0.017 (0.016) Data 0.002 (0.004) Loss 0.0301 (0.0306) Prec@1 95.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 17:02:09,942 Epoch: [445][120/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0301 (0.0306) Prec@1 96.000 (95.077) Prec@5 99.000 (99.846) +2022-11-14 17:02:10,133 Epoch: [445][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0424 (0.0315) Prec@1 95.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 17:02:10,322 Epoch: [445][140/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.0339 (0.0316) Prec@1 92.000 (94.867) Prec@5 100.000 (99.867) +2022-11-14 17:02:10,512 Epoch: [445][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0363 (0.0319) Prec@1 94.000 (94.812) Prec@5 100.000 (99.875) +2022-11-14 17:02:10,766 Epoch: [445][160/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0360 (0.0321) Prec@1 94.000 (94.765) Prec@5 100.000 (99.882) +2022-11-14 17:02:11,053 Epoch: [445][170/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0176 (0.0313) Prec@1 98.000 (94.944) Prec@5 100.000 (99.889) +2022-11-14 17:02:11,340 Epoch: [445][180/500] Time 0.029 (0.018) Data 0.002 (0.003) Loss 0.0435 (0.0320) Prec@1 92.000 (94.789) Prec@5 99.000 (99.842) +2022-11-14 17:02:11,622 Epoch: [445][190/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0272 (0.0317) Prec@1 95.000 (94.800) Prec@5 100.000 (99.850) +2022-11-14 17:02:11,907 Epoch: [445][200/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0337 (0.0318) Prec@1 95.000 (94.810) Prec@5 100.000 (99.857) +2022-11-14 17:02:12,193 Epoch: [445][210/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0102 (0.0309) Prec@1 99.000 (95.000) Prec@5 100.000 (99.864) +2022-11-14 17:02:12,474 Epoch: [445][220/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0361 (0.0311) Prec@1 96.000 (95.043) Prec@5 100.000 (99.870) +2022-11-14 17:02:12,759 Epoch: [445][230/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0150 (0.0304) Prec@1 98.000 (95.167) Prec@5 100.000 (99.875) +2022-11-14 17:02:13,047 Epoch: [445][240/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0381 (0.0307) Prec@1 94.000 (95.120) Prec@5 100.000 (99.880) +2022-11-14 17:02:13,334 Epoch: [445][250/500] Time 0.027 (0.020) Data 0.001 (0.002) Loss 0.0209 (0.0303) Prec@1 98.000 (95.231) Prec@5 100.000 (99.885) +2022-11-14 17:02:13,616 Epoch: [445][260/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0310 (0.0304) Prec@1 95.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 17:02:13,898 Epoch: [445][270/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0089 (0.0296) Prec@1 99.000 (95.357) Prec@5 100.000 (99.893) +2022-11-14 17:02:14,183 Epoch: [445][280/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0410 (0.0300) Prec@1 94.000 (95.310) Prec@5 99.000 (99.862) +2022-11-14 17:02:14,466 Epoch: [445][290/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0504 (0.0307) Prec@1 91.000 (95.167) Prec@5 99.000 (99.833) +2022-11-14 17:02:14,752 Epoch: [445][300/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0165 (0.0302) Prec@1 97.000 (95.226) Prec@5 100.000 (99.839) +2022-11-14 17:02:15,034 Epoch: [445][310/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0237 (0.0300) Prec@1 96.000 (95.250) Prec@5 100.000 (99.844) +2022-11-14 17:02:15,317 Epoch: [445][320/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0289 (0.0300) Prec@1 95.000 (95.242) Prec@5 100.000 (99.848) +2022-11-14 17:02:15,603 Epoch: [445][330/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0391 (0.0302) Prec@1 92.000 (95.147) Prec@5 100.000 (99.853) +2022-11-14 17:02:15,885 Epoch: [445][340/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0308 (0.0303) Prec@1 94.000 (95.114) Prec@5 100.000 (99.857) +2022-11-14 17:02:16,172 Epoch: [445][350/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0362 (0.0304) Prec@1 94.000 (95.083) Prec@5 100.000 (99.861) +2022-11-14 17:02:16,457 Epoch: [445][360/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0228 (0.0302) Prec@1 95.000 (95.081) Prec@5 100.000 (99.865) +2022-11-14 17:02:16,747 Epoch: [445][370/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0344 (0.0303) Prec@1 94.000 (95.053) Prec@5 100.000 (99.868) +2022-11-14 17:02:17,030 Epoch: [445][380/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0255 (0.0302) Prec@1 97.000 (95.103) Prec@5 100.000 (99.872) +2022-11-14 17:02:17,314 Epoch: [445][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0166 (0.0299) Prec@1 99.000 (95.200) Prec@5 100.000 (99.875) +2022-11-14 17:02:17,603 Epoch: [445][400/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0201 (0.0296) Prec@1 98.000 (95.268) Prec@5 100.000 (99.878) +2022-11-14 17:02:17,890 Epoch: [445][410/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0331 (0.0297) Prec@1 93.000 (95.214) Prec@5 100.000 (99.881) +2022-11-14 17:02:18,175 Epoch: [445][420/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0352 (0.0298) Prec@1 93.000 (95.163) Prec@5 99.000 (99.860) +2022-11-14 17:02:18,457 Epoch: [445][430/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0141 (0.0295) Prec@1 98.000 (95.227) Prec@5 100.000 (99.864) +2022-11-14 17:02:18,744 Epoch: [445][440/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0323 (0.0295) Prec@1 95.000 (95.222) Prec@5 100.000 (99.867) +2022-11-14 17:02:19,029 Epoch: [445][450/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0096 (0.0291) Prec@1 100.000 (95.326) Prec@5 100.000 (99.870) +2022-11-14 17:02:19,314 Epoch: [445][460/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0359 (0.0293) Prec@1 94.000 (95.298) Prec@5 100.000 (99.872) +2022-11-14 17:02:19,596 Epoch: [445][470/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0334 (0.0293) Prec@1 96.000 (95.312) Prec@5 100.000 (99.875) +2022-11-14 17:02:19,882 Epoch: [445][480/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0468 (0.0297) Prec@1 91.000 (95.224) Prec@5 100.000 (99.878) +2022-11-14 17:02:20,170 Epoch: [445][490/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0215 (0.0295) Prec@1 97.000 (95.260) Prec@5 100.000 (99.880) +2022-11-14 17:02:20,425 Epoch: [445][499/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0276 (0.0295) Prec@1 96.000 (95.275) Prec@5 100.000 (99.882) +2022-11-14 17:02:20,748 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0805 (0.0805) Prec@1 84.000 (84.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:20,763 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0731 (0.0768) Prec@1 87.000 (85.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:20,774 Test: [2/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0841 (0.0792) Prec@1 85.000 (85.333) Prec@5 100.000 (100.000) +2022-11-14 17:02:20,789 Test: [3/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0599 (0.0744) Prec@1 91.000 (86.750) Prec@5 99.000 (99.750) +2022-11-14 17:02:20,798 Test: [4/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0853 (0.0766) Prec@1 88.000 (87.000) Prec@5 98.000 (99.400) +2022-11-14 17:02:20,805 Test: [5/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0391 (0.0703) Prec@1 93.000 (88.000) Prec@5 100.000 (99.500) +2022-11-14 17:02:20,812 Test: [6/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0585 (0.0686) Prec@1 90.000 (88.286) Prec@5 100.000 (99.571) +2022-11-14 17:02:20,821 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.1063 (0.0734) Prec@1 82.000 (87.500) Prec@5 98.000 (99.375) +2022-11-14 17:02:20,828 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0899 (0.0752) Prec@1 86.000 (87.333) Prec@5 98.000 (99.222) +2022-11-14 17:02:20,834 Test: [9/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0938 (0.0770) Prec@1 86.000 (87.200) Prec@5 98.000 (99.100) +2022-11-14 17:02:20,841 Test: [10/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0565 (0.0752) Prec@1 92.000 (87.636) Prec@5 100.000 (99.182) +2022-11-14 17:02:20,849 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0759) Prec@1 85.000 (87.417) Prec@5 99.000 (99.167) +2022-11-14 17:02:20,857 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0571 (0.0745) Prec@1 92.000 (87.769) Prec@5 99.000 (99.154) +2022-11-14 17:02:20,865 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0744) Prec@1 89.000 (87.857) Prec@5 99.000 (99.143) +2022-11-14 17:02:20,872 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0851 (0.0752) Prec@1 87.000 (87.800) Prec@5 100.000 (99.200) +2022-11-14 17:02:20,880 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0746) Prec@1 90.000 (87.938) Prec@5 99.000 (99.188) +2022-11-14 17:02:20,888 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0568 (0.0736) Prec@1 92.000 (88.176) Prec@5 98.000 (99.118) +2022-11-14 17:02:20,895 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1043 (0.0753) Prec@1 82.000 (87.833) Prec@5 100.000 (99.167) +2022-11-14 17:02:20,903 Test: [18/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0768 (0.0754) Prec@1 86.000 (87.737) Prec@5 98.000 (99.105) +2022-11-14 17:02:20,910 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0767) Prec@1 84.000 (87.550) Prec@5 96.000 (98.950) +2022-11-14 17:02:20,918 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0763) Prec@1 89.000 (87.619) Prec@5 100.000 (99.000) +2022-11-14 17:02:20,925 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0766) Prec@1 87.000 (87.591) Prec@5 100.000 (99.045) +2022-11-14 17:02:20,933 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0767) Prec@1 89.000 (87.652) Prec@5 98.000 (99.000) +2022-11-14 17:02:20,940 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0760) Prec@1 92.000 (87.833) Prec@5 100.000 (99.042) +2022-11-14 17:02:20,948 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0758) Prec@1 91.000 (87.960) Prec@5 100.000 (99.080) +2022-11-14 17:02:20,955 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0757) Prec@1 91.000 (88.077) Prec@5 99.000 (99.077) +2022-11-14 17:02:20,963 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0746) Prec@1 93.000 (88.259) Prec@5 100.000 (99.111) +2022-11-14 17:02:20,970 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0743) Prec@1 89.000 (88.286) Prec@5 99.000 (99.107) +2022-11-14 17:02:20,978 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0738) Prec@1 90.000 (88.345) Prec@5 99.000 (99.103) +2022-11-14 17:02:20,985 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0739) Prec@1 88.000 (88.333) Prec@5 99.000 (99.100) +2022-11-14 17:02:20,993 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0740) Prec@1 85.000 (88.226) Prec@5 100.000 (99.129) +2022-11-14 17:02:21,001 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0743) Prec@1 86.000 (88.156) Prec@5 100.000 (99.156) +2022-11-14 17:02:21,009 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0743) Prec@1 88.000 (88.152) Prec@5 100.000 (99.182) +2022-11-14 17:02:21,016 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0745) Prec@1 86.000 (88.088) Prec@5 100.000 (99.206) +2022-11-14 17:02:21,024 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0746) Prec@1 89.000 (88.114) Prec@5 97.000 (99.143) +2022-11-14 17:02:21,032 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0746) Prec@1 91.000 (88.194) Prec@5 99.000 (99.139) +2022-11-14 17:02:21,039 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0744) Prec@1 89.000 (88.216) Prec@5 99.000 (99.135) +2022-11-14 17:02:21,046 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1011 (0.0751) Prec@1 79.000 (87.974) Prec@5 98.000 (99.105) +2022-11-14 17:02:21,054 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0746) Prec@1 94.000 (88.128) Prec@5 99.000 (99.103) +2022-11-14 17:02:21,062 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0744) Prec@1 89.000 (88.150) Prec@5 99.000 (99.100) +2022-11-14 17:02:21,069 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0749) Prec@1 83.000 (88.024) Prec@5 98.000 (99.073) +2022-11-14 17:02:21,076 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0742) Prec@1 91.000 (88.095) Prec@5 100.000 (99.095) +2022-11-14 17:02:21,086 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0736) Prec@1 94.000 (88.233) Prec@5 99.000 (99.093) +2022-11-14 17:02:21,093 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0737) Prec@1 89.000 (88.250) Prec@5 98.000 (99.068) +2022-11-14 17:02:21,101 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0734) Prec@1 89.000 (88.267) Prec@5 99.000 (99.067) +2022-11-14 17:02:21,108 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0740) Prec@1 86.000 (88.217) Prec@5 99.000 (99.065) +2022-11-14 17:02:21,116 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0736) Prec@1 92.000 (88.298) Prec@5 100.000 (99.085) +2022-11-14 17:02:21,123 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0739) Prec@1 82.000 (88.167) Prec@5 98.000 (99.062) +2022-11-14 17:02:21,131 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0734) Prec@1 93.000 (88.265) Prec@5 99.000 (99.061) +2022-11-14 17:02:21,138 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0741) Prec@1 83.000 (88.160) Prec@5 100.000 (99.080) +2022-11-14 17:02:21,146 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0735) Prec@1 92.000 (88.235) Prec@5 100.000 (99.098) +2022-11-14 17:02:21,153 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0739) Prec@1 84.000 (88.154) Prec@5 99.000 (99.096) +2022-11-14 17:02:21,160 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0738) Prec@1 89.000 (88.170) Prec@5 99.000 (99.094) +2022-11-14 17:02:21,168 Test: 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0.0570 (0.0741) Prec@1 89.000 (88.067) Prec@5 100.000 (99.083) +2022-11-14 17:02:21,221 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0741) Prec@1 88.000 (88.066) Prec@5 97.000 (99.049) +2022-11-14 17:02:21,229 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0738) Prec@1 92.000 (88.129) Prec@5 99.000 (99.048) +2022-11-14 17:02:21,236 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0737) Prec@1 89.000 (88.143) Prec@5 100.000 (99.063) +2022-11-14 17:02:21,244 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0733) Prec@1 93.000 (88.219) Prec@5 100.000 (99.078) +2022-11-14 17:02:21,251 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0736) Prec@1 85.000 (88.169) Prec@5 99.000 (99.077) +2022-11-14 17:02:21,259 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0739) Prec@1 87.000 (88.152) Prec@5 98.000 (99.061) +2022-11-14 17:02:21,266 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0272 (0.0732) Prec@1 95.000 (88.254) Prec@5 100.000 (99.075) +2022-11-14 17:02:21,274 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0730) Prec@1 92.000 (88.309) Prec@5 99.000 (99.074) +2022-11-14 17:02:21,281 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0728) Prec@1 90.000 (88.333) Prec@5 99.000 (99.072) +2022-11-14 17:02:21,289 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0727) Prec@1 92.000 (88.386) Prec@5 97.000 (99.043) +2022-11-14 17:02:21,297 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0730) Prec@1 86.000 (88.352) Prec@5 98.000 (99.028) +2022-11-14 17:02:21,304 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0728) Prec@1 90.000 (88.375) Prec@5 100.000 (99.042) +2022-11-14 17:02:21,312 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0725) Prec@1 93.000 (88.438) Prec@5 100.000 (99.055) +2022-11-14 17:02:21,320 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0370 (0.0720) Prec@1 95.000 (88.527) Prec@5 100.000 (99.068) +2022-11-14 17:02:21,327 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0725) Prec@1 81.000 (88.427) Prec@5 99.000 (99.067) +2022-11-14 17:02:21,335 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0722) Prec@1 93.000 (88.487) Prec@5 100.000 (99.079) +2022-11-14 17:02:21,342 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0724) Prec@1 88.000 (88.481) Prec@5 98.000 (99.065) +2022-11-14 17:02:21,350 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0727) Prec@1 85.000 (88.436) Prec@5 99.000 (99.064) +2022-11-14 17:02:21,357 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0729) Prec@1 87.000 (88.418) Prec@5 100.000 (99.076) +2022-11-14 17:02:21,365 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0729) Prec@1 86.000 (88.388) Prec@5 100.000 (99.088) +2022-11-14 17:02:21,372 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0730) Prec@1 86.000 (88.358) Prec@5 100.000 (99.099) +2022-11-14 17:02:21,380 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0732) Prec@1 86.000 (88.329) Prec@5 99.000 (99.098) +2022-11-14 17:02:21,388 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0734) Prec@1 85.000 (88.289) Prec@5 99.000 (99.096) +2022-11-14 17:02:21,395 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0733) Prec@1 92.000 (88.333) Prec@5 98.000 (99.083) +2022-11-14 17:02:21,403 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0735) Prec@1 83.000 (88.271) Prec@5 98.000 (99.071) +2022-11-14 17:02:21,410 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0740) Prec@1 82.000 (88.198) Prec@5 99.000 (99.070) +2022-11-14 17:02:21,418 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0876 (0.0742) Prec@1 86.000 (88.172) Prec@5 99.000 (99.069) +2022-11-14 17:02:21,426 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0816 (0.0743) Prec@1 87.000 (88.159) Prec@5 98.000 (99.057) +2022-11-14 17:02:21,433 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0515 (0.0740) Prec@1 92.000 (88.202) Prec@5 100.000 (99.067) +2022-11-14 17:02:21,441 Test: [89/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0739) Prec@1 89.000 (88.211) Prec@5 99.000 (99.067) +2022-11-14 17:02:21,449 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0308 (0.0735) Prec@1 97.000 (88.308) Prec@5 100.000 (99.077) +2022-11-14 17:02:21,457 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0733) Prec@1 89.000 (88.315) Prec@5 99.000 (99.076) +2022-11-14 17:02:21,464 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0735) Prec@1 83.000 (88.258) Prec@5 99.000 (99.075) +2022-11-14 17:02:21,473 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0736) Prec@1 88.000 (88.255) Prec@5 99.000 (99.074) +2022-11-14 17:02:21,481 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0736) Prec@1 88.000 (88.253) Prec@5 99.000 (99.074) +2022-11-14 17:02:21,488 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0735) Prec@1 90.000 (88.271) Prec@5 99.000 (99.073) +2022-11-14 17:02:21,495 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0352 (0.0731) Prec@1 95.000 (88.340) Prec@5 99.000 (99.072) +2022-11-14 17:02:21,503 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0731) Prec@1 89.000 (88.347) Prec@5 99.000 (99.071) +2022-11-14 17:02:21,510 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1063 (0.0734) Prec@1 85.000 (88.313) Prec@5 99.000 (99.071) +2022-11-14 17:02:21,517 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0735) Prec@1 87.000 (88.300) Prec@5 100.000 (99.080) +2022-11-14 17:02:21,571 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:02:21,892 Epoch: [446][0/500] Time 0.025 (0.025) Data 0.240 (0.240) Loss 0.0566 (0.0566) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:22,097 Epoch: [446][10/500] Time 0.018 (0.019) Data 0.001 (0.023) Loss 0.0442 (0.0504) Prec@1 92.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:22,304 Epoch: [446][20/500] Time 0.016 (0.018) Data 0.002 (0.013) Loss 0.0235 (0.0414) Prec@1 96.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:22,502 Epoch: [446][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0402 (0.0411) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:22,704 Epoch: [446][40/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0089 (0.0347) Prec@1 99.000 (94.200) Prec@5 100.000 (100.000) +2022-11-14 17:02:22,890 Epoch: [446][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0336 (0.0345) Prec@1 95.000 (94.333) Prec@5 99.000 (99.833) +2022-11-14 17:02:23,079 Epoch: [446][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0183 (0.0322) Prec@1 98.000 (94.857) Prec@5 99.000 (99.714) +2022-11-14 17:02:23,269 Epoch: [446][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0338 (0.0324) Prec@1 93.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 17:02:23,456 Epoch: [446][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0222 (0.0313) Prec@1 96.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 17:02:23,648 Epoch: [446][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0374 (0.0319) Prec@1 96.000 (94.900) Prec@5 100.000 (99.800) +2022-11-14 17:02:23,837 Epoch: [446][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0322 (0.0319) Prec@1 96.000 (95.000) Prec@5 100.000 (99.818) +2022-11-14 17:02:24,028 Epoch: [446][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0335 (0.0320) Prec@1 93.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 17:02:24,220 Epoch: [446][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0389 (0.0326) Prec@1 94.000 (94.769) Prec@5 100.000 (99.846) +2022-11-14 17:02:24,408 Epoch: [446][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0186 (0.0316) Prec@1 97.000 (94.929) Prec@5 99.000 (99.786) +2022-11-14 17:02:24,605 Epoch: [446][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0413 (0.0322) Prec@1 92.000 (94.733) Prec@5 100.000 (99.800) +2022-11-14 17:02:24,791 Epoch: [446][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0334 (0.0323) Prec@1 95.000 (94.750) Prec@5 100.000 (99.812) +2022-11-14 17:02:25,015 Epoch: [446][160/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0269 (0.0320) Prec@1 95.000 (94.765) Prec@5 100.000 (99.824) +2022-11-14 17:02:25,290 Epoch: [446][170/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0257 (0.0316) Prec@1 95.000 (94.778) Prec@5 100.000 (99.833) +2022-11-14 17:02:25,568 Epoch: [446][180/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0236 (0.0312) Prec@1 96.000 (94.842) Prec@5 100.000 (99.842) +2022-11-14 17:02:25,848 Epoch: [446][190/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0511 (0.0322) Prec@1 93.000 (94.750) Prec@5 100.000 (99.850) +2022-11-14 17:02:26,136 Epoch: [446][200/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0192 (0.0316) Prec@1 97.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 17:02:26,420 Epoch: [446][210/500] Time 0.027 (0.019) Data 0.001 (0.003) Loss 0.0412 (0.0320) Prec@1 93.000 (94.773) Prec@5 99.000 (99.818) +2022-11-14 17:02:26,711 Epoch: [446][220/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0276 (0.0318) Prec@1 97.000 (94.870) Prec@5 100.000 (99.826) +2022-11-14 17:02:26,993 Epoch: [446][230/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0400 (0.0322) Prec@1 94.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 17:02:27,277 Epoch: [446][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0268 (0.0319) Prec@1 96.000 (94.880) Prec@5 100.000 (99.840) +2022-11-14 17:02:27,562 Epoch: [446][250/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0272 (0.0318) Prec@1 94.000 (94.846) Prec@5 100.000 (99.846) +2022-11-14 17:02:27,841 Epoch: [446][260/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0155 (0.0312) Prec@1 97.000 (94.926) Prec@5 100.000 (99.852) +2022-11-14 17:02:28,116 Epoch: [446][270/500] Time 0.030 (0.020) Data 0.001 (0.003) Loss 0.0355 (0.0313) Prec@1 94.000 (94.893) Prec@5 100.000 (99.857) +2022-11-14 17:02:28,389 Epoch: [446][280/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0550 (0.0321) Prec@1 89.000 (94.690) Prec@5 100.000 (99.862) +2022-11-14 17:02:28,662 Epoch: [446][290/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0166 (0.0316) Prec@1 98.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 17:02:28,939 Epoch: [446][300/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0320 (0.0316) Prec@1 92.000 (94.710) Prec@5 100.000 (99.871) +2022-11-14 17:02:29,215 Epoch: [446][310/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0453 (0.0321) Prec@1 93.000 (94.656) Prec@5 100.000 (99.875) +2022-11-14 17:02:29,487 Epoch: [446][320/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0420 (0.0324) Prec@1 93.000 (94.606) Prec@5 100.000 (99.879) +2022-11-14 17:02:29,759 Epoch: [446][330/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0460 (0.0328) Prec@1 93.000 (94.559) Prec@5 100.000 (99.882) +2022-11-14 17:02:30,028 Epoch: [446][340/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0447 (0.0331) Prec@1 94.000 (94.543) Prec@5 99.000 (99.857) +2022-11-14 17:02:30,306 Epoch: [446][350/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0199 (0.0327) Prec@1 96.000 (94.583) Prec@5 100.000 (99.861) +2022-11-14 17:02:30,576 Epoch: [446][360/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0226 (0.0325) Prec@1 97.000 (94.649) Prec@5 100.000 (99.865) +2022-11-14 17:02:30,847 Epoch: [446][370/500] Time 0.025 (0.021) Data 0.003 (0.002) Loss 0.0259 (0.0323) Prec@1 97.000 (94.711) Prec@5 100.000 (99.868) +2022-11-14 17:02:31,123 Epoch: [446][380/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0389 (0.0325) Prec@1 92.000 (94.641) Prec@5 100.000 (99.872) +2022-11-14 17:02:31,394 Epoch: [446][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0202 (0.0321) Prec@1 97.000 (94.700) Prec@5 100.000 (99.875) +2022-11-14 17:02:31,673 Epoch: [446][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0322 (0.0321) Prec@1 96.000 (94.732) Prec@5 98.000 (99.829) +2022-11-14 17:02:31,948 Epoch: [446][410/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0321 (0.0321) Prec@1 96.000 (94.762) Prec@5 99.000 (99.810) +2022-11-14 17:02:32,225 Epoch: [446][420/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0362 (0.0322) Prec@1 94.000 (94.744) Prec@5 99.000 (99.791) +2022-11-14 17:02:32,499 Epoch: [446][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0130 (0.0318) Prec@1 99.000 (94.841) Prec@5 100.000 (99.795) +2022-11-14 17:02:32,771 Epoch: [446][440/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0140 (0.0314) Prec@1 97.000 (94.889) Prec@5 100.000 (99.800) +2022-11-14 17:02:33,045 Epoch: [446][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0356 (0.0315) Prec@1 94.000 (94.870) Prec@5 100.000 (99.804) +2022-11-14 17:02:33,317 Epoch: [446][460/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0366 (0.0316) Prec@1 93.000 (94.830) Prec@5 100.000 (99.809) +2022-11-14 17:02:33,587 Epoch: [446][470/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0225 (0.0314) Prec@1 95.000 (94.833) Prec@5 100.000 (99.812) +2022-11-14 17:02:33,864 Epoch: [446][480/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0317 (0.0314) Prec@1 95.000 (94.837) Prec@5 100.000 (99.816) +2022-11-14 17:02:34,144 Epoch: [446][490/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0340 (0.0315) Prec@1 93.000 (94.800) Prec@5 100.000 (99.820) +2022-11-14 17:02:34,389 Epoch: [446][499/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0358 (0.0316) Prec@1 93.000 (94.765) Prec@5 100.000 (99.824) +2022-11-14 17:02:34,693 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0739 (0.0739) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,701 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0705) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,710 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0672) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,720 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0684) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,726 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0696) Prec@1 88.000 (88.800) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,733 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0585 (0.0677) Prec@1 88.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,740 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0690) Prec@1 90.000 (88.857) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,749 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0716) Prec@1 85.000 (88.375) Prec@5 100.000 (100.000) +2022-11-14 17:02:34,756 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0724) Prec@1 88.000 (88.333) Prec@5 99.000 (99.889) +2022-11-14 17:02:34,763 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0719) Prec@1 91.000 (88.600) Prec@5 99.000 (99.800) +2022-11-14 17:02:34,771 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0715) Prec@1 87.000 (88.455) Prec@5 100.000 (99.818) +2022-11-14 17:02:34,778 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0719) Prec@1 86.000 (88.250) Prec@5 100.000 (99.833) +2022-11-14 17:02:34,786 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0698) Prec@1 93.000 (88.615) Prec@5 100.000 (99.846) +2022-11-14 17:02:34,794 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0706) Prec@1 89.000 (88.643) Prec@5 99.000 (99.786) +2022-11-14 17:02:34,801 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0709) Prec@1 88.000 (88.600) Prec@5 100.000 (99.800) +2022-11-14 17:02:34,809 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0708) Prec@1 88.000 (88.562) Prec@5 99.000 (99.750) +2022-11-14 17:02:34,817 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0695) Prec@1 93.000 (88.824) Prec@5 98.000 (99.647) +2022-11-14 17:02:34,824 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0714) Prec@1 85.000 (88.611) Prec@5 100.000 (99.667) +2022-11-14 17:02:34,832 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0722) Prec@1 85.000 (88.421) Prec@5 96.000 (99.474) +2022-11-14 17:02:34,840 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0721) Prec@1 88.000 (88.400) Prec@5 99.000 (99.450) +2022-11-14 17:02:34,847 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0721) Prec@1 90.000 (88.476) Prec@5 100.000 (99.476) +2022-11-14 17:02:34,855 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0723) Prec@1 85.000 (88.318) Prec@5 99.000 (99.455) +2022-11-14 17:02:34,863 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0728) Prec@1 89.000 (88.348) Prec@5 99.000 (99.435) +2022-11-14 17:02:34,871 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0727) Prec@1 90.000 (88.417) Prec@5 100.000 (99.458) +2022-11-14 17:02:34,878 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0733) Prec@1 87.000 (88.360) Prec@5 100.000 (99.480) +2022-11-14 17:02:34,886 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0738) Prec@1 86.000 (88.269) Prec@5 100.000 (99.500) +2022-11-14 17:02:34,894 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0735) Prec@1 91.000 (88.370) Prec@5 100.000 (99.519) +2022-11-14 17:02:34,901 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0741) Prec@1 86.000 (88.286) Prec@5 99.000 (99.500) +2022-11-14 17:02:34,909 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0736) Prec@1 92.000 (88.414) Prec@5 98.000 (99.448) +2022-11-14 17:02:34,917 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0738) Prec@1 88.000 (88.400) Prec@5 99.000 (99.433) +2022-11-14 17:02:34,924 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0739) Prec@1 87.000 (88.355) Prec@5 100.000 (99.452) +2022-11-14 17:02:34,932 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0740) Prec@1 88.000 (88.344) Prec@5 99.000 (99.438) +2022-11-14 17:02:34,939 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0749) Prec@1 84.000 (88.212) Prec@5 100.000 (99.455) +2022-11-14 17:02:34,947 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0748) Prec@1 86.000 (88.147) Prec@5 99.000 (99.441) +2022-11-14 17:02:34,955 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0753) Prec@1 88.000 (88.143) Prec@5 98.000 (99.400) +2022-11-14 17:02:34,962 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0749) Prec@1 88.000 (88.139) Prec@5 100.000 (99.417) +2022-11-14 17:02:34,970 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0748) Prec@1 89.000 (88.162) Prec@5 99.000 (99.405) +2022-11-14 17:02:34,977 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1201 (0.0760) Prec@1 81.000 (87.974) Prec@5 99.000 (99.395) +2022-11-14 17:02:34,985 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0753) Prec@1 92.000 (88.077) Prec@5 99.000 (99.385) +2022-11-14 17:02:34,993 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0750) Prec@1 89.000 (88.100) Prec@5 100.000 (99.400) +2022-11-14 17:02:35,000 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0752) Prec@1 87.000 (88.073) Prec@5 98.000 (99.366) +2022-11-14 17:02:35,008 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0756) Prec@1 87.000 (88.048) Prec@5 99.000 (99.357) +2022-11-14 17:02:35,016 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0385 (0.0747) Prec@1 92.000 (88.140) Prec@5 99.000 (99.349) +2022-11-14 17:02:35,023 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0749) Prec@1 88.000 (88.136) Prec@5 97.000 (99.295) +2022-11-14 17:02:35,031 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0744) Prec@1 92.000 (88.222) Prec@5 100.000 (99.311) +2022-11-14 17:02:35,039 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0749) Prec@1 83.000 (88.109) Prec@5 100.000 (99.326) +2022-11-14 17:02:35,046 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0747) Prec@1 89.000 (88.128) Prec@5 99.000 (99.319) +2022-11-14 17:02:35,054 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0750) Prec@1 87.000 (88.104) Prec@5 98.000 (99.292) +2022-11-14 17:02:35,061 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0750) Prec@1 87.000 (88.082) Prec@5 100.000 (99.306) +2022-11-14 17:02:35,069 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1190 (0.0759) Prec@1 84.000 (88.000) Prec@5 99.000 (99.300) +2022-11-14 17:02:35,076 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0755) Prec@1 91.000 (88.059) Prec@5 100.000 (99.314) +2022-11-14 17:02:35,085 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0754) Prec@1 89.000 (88.077) Prec@5 100.000 (99.327) +2022-11-14 17:02:35,093 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0752) Prec@1 92.000 (88.151) Prec@5 99.000 (99.321) +2022-11-14 17:02:35,100 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0756) Prec@1 85.000 (88.093) Prec@5 99.000 (99.315) +2022-11-14 17:02:35,108 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0758) Prec@1 86.000 (88.055) Prec@5 100.000 (99.327) +2022-11-14 17:02:35,115 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0758) Prec@1 90.000 (88.089) Prec@5 99.000 (99.321) +2022-11-14 17:02:35,123 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0758) Prec@1 88.000 (88.088) Prec@5 100.000 (99.333) +2022-11-14 17:02:35,131 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0756) Prec@1 89.000 (88.103) Prec@5 98.000 (99.310) +2022-11-14 17:02:35,139 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0759) Prec@1 84.000 (88.034) Prec@5 100.000 (99.322) +2022-11-14 17:02:35,147 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0758) Prec@1 86.000 (88.000) Prec@5 100.000 (99.333) +2022-11-14 17:02:35,155 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0759) Prec@1 90.000 (88.033) Prec@5 97.000 (99.295) +2022-11-14 17:02:35,162 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0759) Prec@1 88.000 (88.032) Prec@5 100.000 (99.306) +2022-11-14 17:02:35,170 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0758) Prec@1 89.000 (88.048) Prec@5 99.000 (99.302) +2022-11-14 17:02:35,177 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0754) Prec@1 92.000 (88.109) Prec@5 100.000 (99.312) +2022-11-14 17:02:35,185 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0754) Prec@1 88.000 (88.108) Prec@5 100.000 (99.323) +2022-11-14 17:02:35,192 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0755) Prec@1 84.000 (88.045) Prec@5 97.000 (99.288) +2022-11-14 17:02:35,200 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0350 (0.0749) Prec@1 95.000 (88.149) Prec@5 99.000 (99.284) +2022-11-14 17:02:35,208 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0749) Prec@1 91.000 (88.191) Prec@5 100.000 (99.294) +2022-11-14 17:02:35,215 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0749) Prec@1 87.000 (88.174) Prec@5 99.000 (99.290) +2022-11-14 17:02:35,223 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0747) Prec@1 90.000 (88.200) Prec@5 98.000 (99.271) +2022-11-14 17:02:35,231 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0751) Prec@1 87.000 (88.183) Prec@5 98.000 (99.254) +2022-11-14 17:02:35,238 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0749) Prec@1 89.000 (88.194) Prec@5 99.000 (99.250) +2022-11-14 17:02:35,246 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0747) Prec@1 90.000 (88.219) Prec@5 99.000 (99.247) +2022-11-14 17:02:35,253 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0603 (0.0745) Prec@1 90.000 (88.243) Prec@5 100.000 (99.257) +2022-11-14 17:02:35,261 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1005 (0.0749) Prec@1 86.000 (88.213) Prec@5 99.000 (99.253) +2022-11-14 17:02:35,268 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0531 (0.0746) Prec@1 92.000 (88.263) Prec@5 99.000 (99.250) +2022-11-14 17:02:35,276 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0871 (0.0747) Prec@1 88.000 (88.260) Prec@5 100.000 (99.260) +2022-11-14 17:02:35,283 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0916 (0.0749) Prec@1 86.000 (88.231) Prec@5 99.000 (99.256) +2022-11-14 17:02:35,291 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0870 (0.0751) Prec@1 85.000 (88.190) Prec@5 99.000 (99.253) +2022-11-14 17:02:35,298 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0830 (0.0752) Prec@1 83.000 (88.125) Prec@5 100.000 (99.263) +2022-11-14 17:02:35,306 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0894 (0.0754) Prec@1 88.000 (88.123) Prec@5 96.000 (99.222) +2022-11-14 17:02:35,313 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0953 (0.0756) Prec@1 85.000 (88.085) Prec@5 99.000 (99.220) +2022-11-14 17:02:35,321 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1046 (0.0760) Prec@1 81.000 (88.000) Prec@5 100.000 (99.229) +2022-11-14 17:02:35,328 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0486 (0.0756) Prec@1 93.000 (88.060) Prec@5 100.000 (99.238) +2022-11-14 17:02:35,336 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0899 (0.0758) Prec@1 86.000 (88.035) Prec@5 99.000 (99.235) +2022-11-14 17:02:35,343 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0760) Prec@1 85.000 (88.000) Prec@5 99.000 (99.233) +2022-11-14 17:02:35,351 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0759) Prec@1 85.000 (87.966) Prec@5 100.000 (99.241) +2022-11-14 17:02:35,358 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0796 (0.0759) Prec@1 87.000 (87.955) Prec@5 99.000 (99.239) +2022-11-14 17:02:35,366 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0691 (0.0759) Prec@1 88.000 (87.955) Prec@5 99.000 (99.236) +2022-11-14 17:02:35,373 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0757) Prec@1 91.000 (87.989) Prec@5 100.000 (99.244) +2022-11-14 17:02:35,381 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0535 (0.0755) Prec@1 92.000 (88.033) Prec@5 100.000 (99.253) +2022-11-14 17:02:35,389 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0549 (0.0753) Prec@1 93.000 (88.087) Prec@5 99.000 (99.250) +2022-11-14 17:02:35,396 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0753) Prec@1 88.000 (88.086) Prec@5 99.000 (99.247) +2022-11-14 17:02:35,404 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0752) Prec@1 90.000 (88.106) Prec@5 96.000 (99.213) +2022-11-14 17:02:35,411 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0753) Prec@1 87.000 (88.095) Prec@5 99.000 (99.211) +2022-11-14 17:02:35,418 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0553 (0.0751) Prec@1 92.000 (88.135) Prec@5 99.000 (99.208) +2022-11-14 17:02:35,426 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0419 (0.0748) Prec@1 95.000 (88.206) Prec@5 99.000 (99.206) +2022-11-14 17:02:35,433 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0749) Prec@1 86.000 (88.184) Prec@5 100.000 (99.214) +2022-11-14 17:02:35,440 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0750) Prec@1 87.000 (88.172) Prec@5 99.000 (99.212) +2022-11-14 17:02:35,448 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0749) Prec@1 88.000 (88.170) Prec@5 100.000 (99.220) +2022-11-14 17:02:35,502 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:02:35,820 Epoch: [447][0/500] Time 0.022 (0.022) Data 0.242 (0.242) Loss 0.0285 (0.0285) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,014 Epoch: [447][10/500] Time 0.016 (0.017) Data 0.001 (0.023) Loss 0.0190 (0.0237) Prec@1 98.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,202 Epoch: [447][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0418 (0.0298) Prec@1 93.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,391 Epoch: [447][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0325 (0.0305) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,576 Epoch: [447][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0303 (0.0304) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,764 Epoch: [447][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0184 (0.0284) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:02:36,952 Epoch: [447][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0281 (0.0284) Prec@1 96.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:02:37,146 Epoch: [447][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0193 (0.0272) Prec@1 98.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:02:37,333 Epoch: [447][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0135 (0.0257) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:37,520 Epoch: [447][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0152 (0.0247) Prec@1 97.000 (96.100) Prec@5 100.000 (100.000) +2022-11-14 17:02:37,706 Epoch: [447][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0282 (0.0250) Prec@1 94.000 (95.909) Prec@5 100.000 (100.000) +2022-11-14 17:02:37,900 Epoch: [447][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0242 (0.0249) Prec@1 95.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 17:02:38,092 Epoch: [447][120/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0217 (0.0247) Prec@1 97.000 (95.923) Prec@5 100.000 (100.000) +2022-11-14 17:02:38,280 Epoch: [447][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0402 (0.0258) Prec@1 94.000 (95.786) Prec@5 100.000 (100.000) +2022-11-14 17:02:38,468 Epoch: [447][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0218 (0.0255) Prec@1 97.000 (95.867) Prec@5 99.000 (99.933) +2022-11-14 17:02:38,665 Epoch: [447][150/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0316 (0.0259) Prec@1 96.000 (95.875) Prec@5 100.000 (99.938) +2022-11-14 17:02:38,921 Epoch: [447][160/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0300 (0.0261) Prec@1 94.000 (95.765) Prec@5 100.000 (99.941) +2022-11-14 17:02:39,182 Epoch: [447][170/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0278 (0.0262) Prec@1 95.000 (95.722) Prec@5 100.000 (99.944) +2022-11-14 17:02:39,444 Epoch: [447][180/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0608 (0.0281) Prec@1 90.000 (95.421) Prec@5 100.000 (99.947) +2022-11-14 17:02:39,709 Epoch: [447][190/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0324 (0.0283) Prec@1 95.000 (95.400) Prec@5 100.000 (99.950) +2022-11-14 17:02:39,975 Epoch: [447][200/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0272 (0.0282) Prec@1 95.000 (95.381) Prec@5 99.000 (99.905) +2022-11-14 17:02:40,241 Epoch: [447][210/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0269 (0.0282) Prec@1 95.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 17:02:40,509 Epoch: [447][220/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0395 (0.0287) Prec@1 94.000 (95.304) Prec@5 99.000 (99.870) +2022-11-14 17:02:40,774 Epoch: [447][230/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0286 (0.0286) Prec@1 95.000 (95.292) Prec@5 100.000 (99.875) +2022-11-14 17:02:41,044 Epoch: [447][240/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0532 (0.0296) Prec@1 91.000 (95.120) Prec@5 100.000 (99.880) +2022-11-14 17:02:41,313 Epoch: [447][250/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0340 (0.0298) Prec@1 93.000 (95.038) Prec@5 100.000 (99.885) +2022-11-14 17:02:41,580 Epoch: [447][260/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0125 (0.0292) Prec@1 97.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 17:02:41,848 Epoch: [447][270/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0392 (0.0295) Prec@1 93.000 (95.036) Prec@5 100.000 (99.893) +2022-11-14 17:02:42,122 Epoch: [447][280/500] Time 0.029 (0.020) Data 0.001 (0.002) Loss 0.0416 (0.0299) Prec@1 93.000 (94.966) Prec@5 99.000 (99.862) +2022-11-14 17:02:42,385 Epoch: [447][290/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0417 (0.0303) Prec@1 93.000 (94.900) Prec@5 100.000 (99.867) +2022-11-14 17:02:42,644 Epoch: [447][300/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0275 (0.0302) Prec@1 96.000 (94.935) Prec@5 100.000 (99.871) +2022-11-14 17:02:42,906 Epoch: [447][310/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0392 (0.0305) Prec@1 92.000 (94.844) Prec@5 100.000 (99.875) +2022-11-14 17:02:43,165 Epoch: [447][320/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0149 (0.0300) Prec@1 97.000 (94.909) Prec@5 100.000 (99.879) +2022-11-14 17:02:43,425 Epoch: [447][330/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0158 (0.0296) Prec@1 98.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 17:02:43,685 Epoch: [447][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0262 (0.0295) Prec@1 96.000 (95.029) Prec@5 100.000 (99.886) +2022-11-14 17:02:43,945 Epoch: [447][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0342 (0.0297) Prec@1 95.000 (95.028) Prec@5 100.000 (99.889) +2022-11-14 17:02:44,210 Epoch: [447][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0266 (0.0296) Prec@1 97.000 (95.081) Prec@5 100.000 (99.892) +2022-11-14 17:02:44,473 Epoch: [447][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0243 (0.0294) Prec@1 95.000 (95.079) Prec@5 100.000 (99.895) +2022-11-14 17:02:44,734 Epoch: [447][380/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0161 (0.0291) Prec@1 97.000 (95.128) Prec@5 100.000 (99.897) +2022-11-14 17:02:44,992 Epoch: [447][390/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0187 (0.0288) Prec@1 98.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:02:45,251 Epoch: [447][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0306 (0.0289) Prec@1 95.000 (95.195) Prec@5 100.000 (99.902) +2022-11-14 17:02:45,515 Epoch: [447][410/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0415 (0.0292) Prec@1 94.000 (95.167) Prec@5 100.000 (99.905) +2022-11-14 17:02:45,775 Epoch: [447][420/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0196 (0.0290) Prec@1 97.000 (95.209) Prec@5 100.000 (99.907) +2022-11-14 17:02:46,036 Epoch: [447][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0372 (0.0291) Prec@1 94.000 (95.182) Prec@5 98.000 (99.864) +2022-11-14 17:02:46,300 Epoch: [447][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0146 (0.0288) Prec@1 99.000 (95.267) Prec@5 100.000 (99.867) +2022-11-14 17:02:46,562 Epoch: [447][450/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0164 (0.0285) Prec@1 96.000 (95.283) Prec@5 100.000 (99.870) +2022-11-14 17:02:46,823 Epoch: [447][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0241 (0.0285) Prec@1 97.000 (95.319) Prec@5 99.000 (99.851) +2022-11-14 17:02:47,089 Epoch: [447][470/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0334 (0.0286) Prec@1 95.000 (95.312) Prec@5 100.000 (99.854) +2022-11-14 17:02:47,347 Epoch: [447][480/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0818 (0.0296) Prec@1 86.000 (95.122) Prec@5 100.000 (99.857) +2022-11-14 17:02:47,613 Epoch: [447][490/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0283 (0.0296) Prec@1 95.000 (95.120) Prec@5 99.000 (99.840) +2022-11-14 17:02:47,843 Epoch: [447][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0200 (0.0294) Prec@1 97.000 (95.157) Prec@5 100.000 (99.843) +2022-11-14 17:02:48,143 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0753 (0.0753) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 17:02:48,151 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0586 (0.0669) Prec@1 91.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 17:02:48,158 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0736) Prec@1 86.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,168 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0767) Prec@1 86.000 (87.500) Prec@5 99.000 (99.250) +2022-11-14 17:02:48,175 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0789 (0.0772) Prec@1 89.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 17:02:48,182 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0386 (0.0707) Prec@1 92.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 17:02:48,189 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0682) Prec@1 92.000 (89.000) Prec@5 100.000 (99.429) +2022-11-14 17:02:48,197 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0704) Prec@1 87.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 17:02:48,204 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0714) Prec@1 88.000 (88.667) Prec@5 99.000 (99.444) +2022-11-14 17:02:48,212 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0713) Prec@1 89.000 (88.700) Prec@5 99.000 (99.400) +2022-11-14 17:02:48,220 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0701) Prec@1 92.000 (89.000) Prec@5 100.000 (99.455) +2022-11-14 17:02:48,228 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0693) Prec@1 90.000 (89.083) Prec@5 99.000 (99.417) +2022-11-14 17:02:48,236 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0684) Prec@1 91.000 (89.231) Prec@5 99.000 (99.385) +2022-11-14 17:02:48,244 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0679) Prec@1 90.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 17:02:48,251 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0693) Prec@1 85.000 (89.000) Prec@5 100.000 (99.467) +2022-11-14 17:02:48,259 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0696) Prec@1 90.000 (89.062) Prec@5 99.000 (99.438) +2022-11-14 17:02:48,267 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0684) Prec@1 92.000 (89.235) Prec@5 98.000 (99.353) +2022-11-14 17:02:48,274 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1129 (0.0709) Prec@1 83.000 (88.889) Prec@5 100.000 (99.389) +2022-11-14 17:02:48,282 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0724) Prec@1 83.000 (88.579) Prec@5 99.000 (99.368) +2022-11-14 17:02:48,290 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0730) Prec@1 87.000 (88.500) Prec@5 99.000 (99.350) +2022-11-14 17:02:48,298 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0736) Prec@1 88.000 (88.476) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,305 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0726) Prec@1 90.000 (88.545) Prec@5 99.000 (99.318) +2022-11-14 17:02:48,313 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1132 (0.0744) Prec@1 81.000 (88.217) Prec@5 99.000 (99.304) +2022-11-14 17:02:48,321 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0745) Prec@1 89.000 (88.250) Prec@5 100.000 (99.333) +2022-11-14 17:02:48,329 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0748) Prec@1 88.000 (88.240) Prec@5 100.000 (99.360) +2022-11-14 17:02:48,338 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0758) Prec@1 85.000 (88.115) Prec@5 98.000 (99.308) +2022-11-14 17:02:48,345 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0744) Prec@1 95.000 (88.370) Prec@5 100.000 (99.333) +2022-11-14 17:02:48,353 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0744) Prec@1 87.000 (88.321) Prec@5 100.000 (99.357) +2022-11-14 17:02:48,361 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0742) Prec@1 90.000 (88.379) Prec@5 98.000 (99.310) +2022-11-14 17:02:48,368 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0734) Prec@1 90.000 (88.433) Prec@5 100.000 (99.333) +2022-11-14 17:02:48,376 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0734) Prec@1 88.000 (88.419) Prec@5 100.000 (99.355) +2022-11-14 17:02:48,384 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0736) Prec@1 86.000 (88.344) Prec@5 99.000 (99.344) +2022-11-14 17:02:48,391 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0731) Prec@1 91.000 (88.424) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,399 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0732) Prec@1 85.000 (88.324) Prec@5 100.000 (99.353) +2022-11-14 17:02:48,406 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0737) Prec@1 86.000 (88.257) Prec@5 99.000 (99.343) +2022-11-14 17:02:48,414 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0733) Prec@1 92.000 (88.361) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,421 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0733) Prec@1 89.000 (88.378) Prec@5 98.000 (99.297) +2022-11-14 17:02:48,429 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0737) Prec@1 88.000 (88.368) Prec@5 99.000 (99.289) +2022-11-14 17:02:48,436 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0731) Prec@1 93.000 (88.487) Prec@5 99.000 (99.282) +2022-11-14 17:02:48,443 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0726) Prec@1 90.000 (88.525) Prec@5 99.000 (99.275) +2022-11-14 17:02:48,451 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1264 (0.0739) Prec@1 80.000 (88.317) Prec@5 97.000 (99.220) +2022-11-14 17:02:48,459 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0736) Prec@1 91.000 (88.381) Prec@5 100.000 (99.238) +2022-11-14 17:02:48,466 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0511 (0.0730) Prec@1 92.000 (88.465) Prec@5 99.000 (99.233) +2022-11-14 17:02:48,474 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0728) Prec@1 92.000 (88.545) Prec@5 99.000 (99.227) +2022-11-14 17:02:48,482 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0726) Prec@1 87.000 (88.511) Prec@5 100.000 (99.244) +2022-11-14 17:02:48,489 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0730) Prec@1 86.000 (88.457) Prec@5 100.000 (99.261) +2022-11-14 17:02:48,497 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0729) Prec@1 88.000 (88.447) Prec@5 100.000 (99.277) +2022-11-14 17:02:48,505 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1216 (0.0739) Prec@1 81.000 (88.292) Prec@5 97.000 (99.229) +2022-11-14 17:02:48,512 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0735) Prec@1 90.000 (88.327) Prec@5 100.000 (99.245) +2022-11-14 17:02:48,520 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0738) Prec@1 86.000 (88.280) Prec@5 100.000 (99.260) +2022-11-14 17:02:48,528 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0737) Prec@1 89.000 (88.294) Prec@5 100.000 (99.275) +2022-11-14 17:02:48,536 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0739) Prec@1 85.000 (88.231) Prec@5 100.000 (99.288) +2022-11-14 17:02:48,543 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0738) Prec@1 88.000 (88.226) Prec@5 99.000 (99.283) +2022-11-14 17:02:48,551 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0735) Prec@1 91.000 (88.278) Prec@5 98.000 (99.259) +2022-11-14 17:02:48,558 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0739) Prec@1 82.000 (88.164) Prec@5 99.000 (99.255) +2022-11-14 17:02:48,566 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0738) Prec@1 89.000 (88.179) Prec@5 99.000 (99.250) +2022-11-14 17:02:48,574 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0736) Prec@1 91.000 (88.228) Prec@5 100.000 (99.263) +2022-11-14 17:02:48,581 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0734) Prec@1 89.000 (88.241) Prec@5 99.000 (99.259) +2022-11-14 17:02:48,589 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0737) Prec@1 85.000 (88.186) Prec@5 99.000 (99.254) +2022-11-14 17:02:48,596 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0733) Prec@1 92.000 (88.250) Prec@5 100.000 (99.267) +2022-11-14 17:02:48,604 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0734) Prec@1 90.000 (88.279) Prec@5 99.000 (99.262) +2022-11-14 17:02:48,612 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0733) Prec@1 89.000 (88.290) Prec@5 100.000 (99.274) +2022-11-14 17:02:48,619 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0730) Prec@1 92.000 (88.349) Prec@5 100.000 (99.286) +2022-11-14 17:02:48,627 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0337 (0.0724) Prec@1 93.000 (88.422) Prec@5 100.000 (99.297) +2022-11-14 17:02:48,635 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1067 (0.0729) Prec@1 84.000 (88.354) Prec@5 100.000 (99.308) +2022-11-14 17:02:48,643 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0732) Prec@1 86.000 (88.318) Prec@5 100.000 (99.318) +2022-11-14 17:02:48,650 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0385 (0.0726) Prec@1 95.000 (88.418) Prec@5 100.000 (99.328) +2022-11-14 17:02:48,657 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0726) Prec@1 88.000 (88.412) Prec@5 100.000 (99.338) +2022-11-14 17:02:48,665 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0724) Prec@1 91.000 (88.449) Prec@5 100.000 (99.348) +2022-11-14 17:02:48,672 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0725) Prec@1 87.000 (88.429) Prec@5 99.000 (99.343) +2022-11-14 17:02:48,680 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0730) Prec@1 84.000 (88.366) Prec@5 98.000 (99.324) +2022-11-14 17:02:48,687 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0728) Prec@1 90.000 (88.389) Prec@5 100.000 (99.333) +2022-11-14 17:02:48,695 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0725) Prec@1 93.000 (88.452) Prec@5 99.000 (99.329) +2022-11-14 17:02:48,703 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0723) Prec@1 92.000 (88.500) Prec@5 100.000 (99.338) +2022-11-14 17:02:48,711 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0726) Prec@1 86.000 (88.467) Prec@5 100.000 (99.347) +2022-11-14 17:02:48,718 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0724) Prec@1 92.000 (88.513) Prec@5 99.000 (99.342) +2022-11-14 17:02:48,726 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0724) Prec@1 88.000 (88.506) Prec@5 99.000 (99.338) +2022-11-14 17:02:48,734 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0726) Prec@1 86.000 (88.474) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,742 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0726) Prec@1 88.000 (88.468) Prec@5 100.000 (99.342) +2022-11-14 17:02:48,749 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0726) Prec@1 91.000 (88.500) Prec@5 99.000 (99.338) +2022-11-14 17:02:48,757 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0726) Prec@1 87.000 (88.481) Prec@5 99.000 (99.333) +2022-11-14 17:02:48,765 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0726) Prec@1 89.000 (88.488) Prec@5 100.000 (99.341) +2022-11-14 17:02:48,773 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0727) Prec@1 85.000 (88.446) Prec@5 100.000 (99.349) +2022-11-14 17:02:48,781 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0727) Prec@1 89.000 (88.452) Prec@5 100.000 (99.357) +2022-11-14 17:02:48,788 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0730) Prec@1 81.000 (88.365) Prec@5 100.000 (99.365) +2022-11-14 17:02:48,796 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0734) Prec@1 85.000 (88.326) Prec@5 100.000 (99.372) +2022-11-14 17:02:48,803 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0735) Prec@1 87.000 (88.310) Prec@5 98.000 (99.356) +2022-11-14 17:02:48,812 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0736) Prec@1 85.000 (88.273) Prec@5 99.000 (99.352) +2022-11-14 17:02:48,820 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0737) Prec@1 85.000 (88.236) Prec@5 100.000 (99.360) +2022-11-14 17:02:48,828 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0736) Prec@1 89.000 (88.244) Prec@5 100.000 (99.367) +2022-11-14 17:02:48,836 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0423 (0.0733) Prec@1 94.000 (88.308) Prec@5 100.000 (99.374) +2022-11-14 17:02:48,844 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0731) Prec@1 91.000 (88.337) Prec@5 99.000 (99.370) +2022-11-14 17:02:48,851 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0733) Prec@1 89.000 (88.344) Prec@5 98.000 (99.355) +2022-11-14 17:02:48,859 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0730) Prec@1 91.000 (88.372) Prec@5 99.000 (99.351) +2022-11-14 17:02:48,866 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0730) Prec@1 90.000 (88.389) Prec@5 99.000 (99.347) +2022-11-14 17:02:48,874 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0728) Prec@1 91.000 (88.417) Prec@5 99.000 (99.344) +2022-11-14 17:02:48,881 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0726) Prec@1 92.000 (88.454) Prec@5 99.000 (99.340) +2022-11-14 17:02:48,889 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0729) Prec@1 86.000 (88.429) Prec@5 96.000 (99.306) +2022-11-14 17:02:48,896 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0731) Prec@1 88.000 (88.424) Prec@5 100.000 (99.313) +2022-11-14 17:02:48,904 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0731) Prec@1 87.000 (88.410) Prec@5 99.000 (99.310) +2022-11-14 17:02:48,957 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:02:49,283 Epoch: [448][0/500] Time 0.030 (0.030) Data 0.242 (0.242) Loss 0.0251 (0.0251) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:49,479 Epoch: [448][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0458 (0.0354) Prec@1 91.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:49,668 Epoch: [448][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0190 (0.0300) Prec@1 98.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:02:49,865 Epoch: [448][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0186 (0.0271) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,055 Epoch: [448][40/500] Time 0.018 (0.017) Data 0.002 (0.007) Loss 0.0335 (0.0284) Prec@1 94.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,246 Epoch: [448][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0231 (0.0275) Prec@1 97.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,431 Epoch: [448][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0162 (0.0259) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,618 Epoch: [448][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0297 (0.0264) Prec@1 95.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,804 Epoch: [448][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0107 (0.0246) Prec@1 99.000 (96.222) Prec@5 100.000 (100.000) +2022-11-14 17:02:50,989 Epoch: [448][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0390 (0.0261) Prec@1 94.000 (96.000) Prec@5 99.000 (99.900) +2022-11-14 17:02:51,195 Epoch: [448][100/500] Time 0.021 (0.017) Data 0.002 (0.004) Loss 0.0311 (0.0265) Prec@1 95.000 (95.909) Prec@5 100.000 (99.909) +2022-11-14 17:02:51,454 Epoch: [448][110/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0133 (0.0254) Prec@1 98.000 (96.083) Prec@5 100.000 (99.917) +2022-11-14 17:02:51,718 Epoch: [448][120/500] Time 0.025 (0.018) Data 0.001 (0.004) Loss 0.0290 (0.0257) Prec@1 96.000 (96.077) Prec@5 100.000 (99.923) +2022-11-14 17:02:51,980 Epoch: [448][130/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0303 (0.0260) Prec@1 94.000 (95.929) Prec@5 100.000 (99.929) +2022-11-14 17:02:52,245 Epoch: [448][140/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0377 (0.0268) Prec@1 93.000 (95.733) Prec@5 100.000 (99.933) +2022-11-14 17:02:52,510 Epoch: [448][150/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0244 (0.0267) Prec@1 96.000 (95.750) Prec@5 100.000 (99.938) +2022-11-14 17:02:52,773 Epoch: [448][160/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0330 (0.0270) Prec@1 93.000 (95.588) Prec@5 100.000 (99.941) +2022-11-14 17:02:53,039 Epoch: [448][170/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0329 (0.0274) Prec@1 95.000 (95.556) Prec@5 99.000 (99.889) +2022-11-14 17:02:53,308 Epoch: [448][180/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0150 (0.0267) Prec@1 98.000 (95.684) Prec@5 100.000 (99.895) +2022-11-14 17:02:53,575 Epoch: [448][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0234 (0.0265) Prec@1 96.000 (95.700) Prec@5 100.000 (99.900) +2022-11-14 17:02:53,844 Epoch: [448][200/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0275 (0.0266) Prec@1 94.000 (95.619) Prec@5 99.000 (99.857) +2022-11-14 17:02:54,112 Epoch: [448][210/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0281 (0.0267) Prec@1 95.000 (95.591) Prec@5 100.000 (99.864) +2022-11-14 17:02:54,376 Epoch: [448][220/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0619 (0.0282) Prec@1 88.000 (95.261) Prec@5 100.000 (99.870) +2022-11-14 17:02:54,639 Epoch: [448][230/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0255 (0.0281) Prec@1 96.000 (95.292) Prec@5 100.000 (99.875) +2022-11-14 17:02:54,910 Epoch: [448][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0313 (0.0282) Prec@1 94.000 (95.240) Prec@5 100.000 (99.880) +2022-11-14 17:02:55,180 Epoch: [448][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0278 (0.0282) Prec@1 94.000 (95.192) Prec@5 100.000 (99.885) +2022-11-14 17:02:55,440 Epoch: [448][260/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0252 (0.0281) Prec@1 94.000 (95.148) Prec@5 100.000 (99.889) +2022-11-14 17:02:55,709 Epoch: [448][270/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0211 (0.0278) Prec@1 96.000 (95.179) Prec@5 100.000 (99.893) +2022-11-14 17:02:55,965 Epoch: [448][280/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0266 (0.0278) Prec@1 95.000 (95.172) Prec@5 100.000 (99.897) +2022-11-14 17:02:56,224 Epoch: [448][290/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0415 (0.0282) Prec@1 92.000 (95.067) Prec@5 100.000 (99.900) +2022-11-14 17:02:56,485 Epoch: [448][300/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0324 (0.0284) Prec@1 94.000 (95.032) Prec@5 100.000 (99.903) +2022-11-14 17:02:56,744 Epoch: [448][310/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0226 (0.0282) Prec@1 97.000 (95.094) Prec@5 100.000 (99.906) +2022-11-14 17:02:56,999 Epoch: [448][320/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0250 (0.0281) Prec@1 97.000 (95.152) Prec@5 100.000 (99.909) +2022-11-14 17:02:57,259 Epoch: [448][330/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0194 (0.0278) Prec@1 95.000 (95.147) Prec@5 100.000 (99.912) +2022-11-14 17:02:57,515 Epoch: [448][340/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0377 (0.0281) Prec@1 95.000 (95.143) Prec@5 100.000 (99.914) +2022-11-14 17:02:57,771 Epoch: [448][350/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0498 (0.0287) Prec@1 90.000 (95.000) Prec@5 99.000 (99.889) +2022-11-14 17:02:58,030 Epoch: [448][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0245 (0.0286) Prec@1 97.000 (95.054) Prec@5 100.000 (99.892) +2022-11-14 17:02:58,288 Epoch: [448][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0169 (0.0283) Prec@1 98.000 (95.132) Prec@5 100.000 (99.895) +2022-11-14 17:02:58,545 Epoch: [448][380/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0357 (0.0285) Prec@1 94.000 (95.103) Prec@5 100.000 (99.897) +2022-11-14 17:02:58,804 Epoch: [448][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0341 (0.0286) Prec@1 94.000 (95.075) Prec@5 100.000 (99.900) +2022-11-14 17:02:59,061 Epoch: [448][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0343 (0.0288) Prec@1 94.000 (95.049) Prec@5 100.000 (99.902) +2022-11-14 17:02:59,317 Epoch: [448][410/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0269 (0.0287) Prec@1 95.000 (95.048) Prec@5 100.000 (99.905) +2022-11-14 17:02:59,577 Epoch: [448][420/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0372 (0.0289) Prec@1 92.000 (94.977) Prec@5 100.000 (99.907) +2022-11-14 17:02:59,834 Epoch: [448][430/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0444 (0.0293) Prec@1 94.000 (94.955) Prec@5 100.000 (99.909) +2022-11-14 17:03:00,096 Epoch: [448][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0379 (0.0295) Prec@1 93.000 (94.911) Prec@5 99.000 (99.889) +2022-11-14 17:03:00,354 Epoch: [448][450/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0219 (0.0293) Prec@1 96.000 (94.935) Prec@5 100.000 (99.891) +2022-11-14 17:03:00,617 Epoch: [448][460/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0413 (0.0296) Prec@1 93.000 (94.894) Prec@5 100.000 (99.894) +2022-11-14 17:03:00,881 Epoch: [448][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0175 (0.0293) Prec@1 99.000 (94.979) Prec@5 100.000 (99.896) +2022-11-14 17:03:01,140 Epoch: [448][480/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0113 (0.0289) Prec@1 97.000 (95.020) Prec@5 100.000 (99.898) +2022-11-14 17:03:01,397 Epoch: [448][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0293 (0.0289) Prec@1 95.000 (95.020) Prec@5 100.000 (99.900) +2022-11-14 17:03:01,632 Epoch: [448][499/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0311 (0.0290) Prec@1 96.000 (95.039) Prec@5 99.000 (99.882) +2022-11-14 17:03:01,926 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0749 (0.0749) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:01,934 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0589 (0.0669) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:01,941 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0698) Prec@1 88.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 17:03:01,952 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0697) Prec@1 88.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 17:03:01,958 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0689) Prec@1 90.000 (89.200) Prec@5 100.000 (99.800) +2022-11-14 17:03:01,965 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0304 (0.0625) Prec@1 94.000 (90.000) Prec@5 100.000 (99.833) +2022-11-14 17:03:01,972 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0601) Prec@1 94.000 (90.571) Prec@5 100.000 (99.857) +2022-11-14 17:03:01,980 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0642) Prec@1 82.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 17:03:01,987 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0672) Prec@1 87.000 (89.222) Prec@5 99.000 (99.667) +2022-11-14 17:03:01,994 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0680) Prec@1 90.000 (89.300) Prec@5 98.000 (99.500) +2022-11-14 17:03:02,002 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0699) Prec@1 87.000 (89.091) Prec@5 99.000 (99.455) +2022-11-14 17:03:02,009 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0711) Prec@1 86.000 (88.833) Prec@5 99.000 (99.417) +2022-11-14 17:03:02,017 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0703) Prec@1 89.000 (88.846) Prec@5 100.000 (99.462) +2022-11-14 17:03:02,024 Test: [13/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0702) Prec@1 89.000 (88.857) Prec@5 99.000 (99.429) +2022-11-14 17:03:02,032 Test: [14/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0589 (0.0695) Prec@1 90.000 (88.933) Prec@5 99.000 (99.400) +2022-11-14 17:03:02,039 Test: [15/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0682 (0.0694) Prec@1 87.000 (88.812) Prec@5 100.000 (99.438) +2022-11-14 17:03:02,046 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0690) Prec@1 89.000 (88.824) Prec@5 99.000 (99.412) +2022-11-14 17:03:02,054 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0998 (0.0707) Prec@1 87.000 (88.722) Prec@5 100.000 (99.444) +2022-11-14 17:03:02,062 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0711) Prec@1 86.000 (88.579) Prec@5 97.000 (99.316) +2022-11-14 17:03:02,069 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0721) Prec@1 85.000 (88.400) Prec@5 99.000 (99.300) +2022-11-14 17:03:02,077 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0725) Prec@1 86.000 (88.286) Prec@5 100.000 (99.333) +2022-11-14 17:03:02,085 Test: [21/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0744 (0.0726) Prec@1 87.000 (88.227) Prec@5 99.000 (99.318) +2022-11-14 17:03:02,093 Test: [22/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0925 (0.0735) Prec@1 89.000 (88.261) Prec@5 96.000 (99.174) +2022-11-14 17:03:02,101 Test: [23/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0741) Prec@1 85.000 (88.125) Prec@5 100.000 (99.208) +2022-11-14 17:03:02,108 Test: [24/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0765 (0.0742) Prec@1 89.000 (88.160) Prec@5 100.000 (99.240) +2022-11-14 17:03:02,116 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0789 (0.0744) Prec@1 87.000 (88.115) Prec@5 99.000 (99.231) +2022-11-14 17:03:02,124 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0538 (0.0737) Prec@1 94.000 (88.333) Prec@5 100.000 (99.259) +2022-11-14 17:03:02,131 Test: [27/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0729) Prec@1 93.000 (88.500) Prec@5 100.000 (99.286) +2022-11-14 17:03:02,139 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0724) Prec@1 91.000 (88.586) Prec@5 99.000 (99.276) +2022-11-14 17:03:02,147 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0725) Prec@1 87.000 (88.533) Prec@5 98.000 (99.233) +2022-11-14 17:03:02,155 Test: [30/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0723) Prec@1 91.000 (88.613) Prec@5 100.000 (99.258) +2022-11-14 17:03:02,162 Test: [31/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0720) Prec@1 91.000 (88.688) Prec@5 100.000 (99.281) +2022-11-14 17:03:02,170 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0716 (0.0720) Prec@1 88.000 (88.667) Prec@5 100.000 (99.303) +2022-11-14 17:03:02,177 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0764 (0.0721) Prec@1 85.000 (88.559) Prec@5 99.000 (99.294) +2022-11-14 17:03:02,185 Test: [34/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0859 (0.0725) Prec@1 87.000 (88.514) Prec@5 99.000 (99.286) +2022-11-14 17:03:02,193 Test: [35/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0723) Prec@1 90.000 (88.556) Prec@5 99.000 (99.278) +2022-11-14 17:03:02,200 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0720) Prec@1 89.000 (88.568) Prec@5 99.000 (99.270) +2022-11-14 17:03:02,208 Test: [37/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0726) Prec@1 83.000 (88.421) Prec@5 100.000 (99.289) +2022-11-14 17:03:02,216 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0466 (0.0719) Prec@1 94.000 (88.564) Prec@5 100.000 (99.308) +2022-11-14 17:03:02,223 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0578 (0.0716) Prec@1 91.000 (88.625) Prec@5 99.000 (99.300) +2022-11-14 17:03:02,231 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0929 (0.0721) Prec@1 86.000 (88.561) Prec@5 99.000 (99.293) +2022-11-14 17:03:02,239 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0711 (0.0721) Prec@1 89.000 (88.571) Prec@5 98.000 (99.262) +2022-11-14 17:03:02,247 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0468 (0.0715) Prec@1 93.000 (88.674) Prec@5 98.000 (99.233) +2022-11-14 17:03:02,254 Test: [43/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0728 (0.0715) Prec@1 88.000 (88.659) Prec@5 97.000 (99.182) +2022-11-14 17:03:02,262 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0493 (0.0710) Prec@1 92.000 (88.733) Prec@5 100.000 (99.200) +2022-11-14 17:03:02,270 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0812 (0.0712) Prec@1 87.000 (88.696) Prec@5 100.000 (99.217) +2022-11-14 17:03:02,277 Test: [46/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0713) Prec@1 90.000 (88.723) Prec@5 100.000 (99.234) +2022-11-14 17:03:02,285 Test: [47/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0989 (0.0718) Prec@1 86.000 (88.667) Prec@5 98.000 (99.208) +2022-11-14 17:03:02,293 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0424 (0.0712) Prec@1 93.000 (88.755) Prec@5 100.000 (99.224) +2022-11-14 17:03:02,301 Test: [49/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0973 (0.0718) Prec@1 86.000 (88.700) Prec@5 100.000 (99.240) +2022-11-14 17:03:02,308 Test: [50/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0844 (0.0720) Prec@1 86.000 (88.647) Prec@5 100.000 (99.255) +2022-11-14 17:03:02,316 Test: [51/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0898 (0.0724) Prec@1 87.000 (88.615) Prec@5 99.000 (99.250) +2022-11-14 17:03:02,324 Test: [52/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0724) Prec@1 89.000 (88.623) Prec@5 99.000 (99.245) +2022-11-14 17:03:02,332 Test: [53/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0708 (0.0724) Prec@1 89.000 (88.630) Prec@5 99.000 (99.241) +2022-11-14 17:03:02,340 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0896 (0.0727) Prec@1 86.000 (88.582) Prec@5 100.000 (99.255) +2022-11-14 17:03:02,348 Test: [55/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0725) Prec@1 92.000 (88.643) Prec@5 99.000 (99.250) +2022-11-14 17:03:02,356 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0618 (0.0723) Prec@1 90.000 (88.667) Prec@5 99.000 (99.246) +2022-11-14 17:03:02,363 Test: [57/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0672 (0.0722) Prec@1 91.000 (88.707) Prec@5 99.000 (99.241) +2022-11-14 17:03:02,371 Test: [58/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0870 (0.0725) Prec@1 85.000 (88.644) Prec@5 99.000 (99.237) +2022-11-14 17:03:02,379 Test: [59/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0970 (0.0729) Prec@1 81.000 (88.517) Prec@5 100.000 (99.250) +2022-11-14 17:03:02,386 Test: [60/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1069 (0.0734) Prec@1 81.000 (88.393) Prec@5 98.000 (99.230) +2022-11-14 17:03:02,394 Test: [61/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0734) Prec@1 88.000 (88.387) Prec@5 98.000 (99.210) +2022-11-14 17:03:02,402 Test: [62/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0749 (0.0734) Prec@1 87.000 (88.365) Prec@5 100.000 (99.222) +2022-11-14 17:03:02,409 Test: [63/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0406 (0.0729) Prec@1 94.000 (88.453) Prec@5 100.000 (99.234) +2022-11-14 17:03:02,417 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0895 (0.0732) Prec@1 87.000 (88.431) Prec@5 99.000 (99.231) +2022-11-14 17:03:02,425 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0884 (0.0734) Prec@1 84.000 (88.364) Prec@5 99.000 (99.227) +2022-11-14 17:03:02,432 Test: [66/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0350 (0.0728) Prec@1 93.000 (88.433) Prec@5 100.000 (99.239) +2022-11-14 17:03:02,440 Test: [67/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0658 (0.0727) Prec@1 91.000 (88.471) Prec@5 99.000 (99.235) +2022-11-14 17:03:02,448 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0772 (0.0728) Prec@1 89.000 (88.478) Prec@5 99.000 (99.232) +2022-11-14 17:03:02,455 Test: [69/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0749 (0.0728) Prec@1 88.000 (88.471) Prec@5 100.000 (99.243) +2022-11-14 17:03:02,463 Test: [70/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0943 (0.0731) Prec@1 86.000 (88.437) Prec@5 100.000 (99.254) +2022-11-14 17:03:02,471 Test: [71/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0655 (0.0730) Prec@1 89.000 (88.444) Prec@5 100.000 (99.264) +2022-11-14 17:03:02,478 Test: 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0.0924 (0.0726) Prec@1 85.000 (88.557) Prec@5 100.000 (99.266) +2022-11-14 17:03:02,532 Test: [79/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0726) Prec@1 89.000 (88.562) Prec@5 98.000 (99.250) +2022-11-14 17:03:02,540 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0849 (0.0727) Prec@1 88.000 (88.556) Prec@5 99.000 (99.247) +2022-11-14 17:03:02,548 Test: [81/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0727) Prec@1 86.000 (88.524) Prec@5 100.000 (99.256) +2022-11-14 17:03:02,555 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0728) Prec@1 87.000 (88.506) Prec@5 100.000 (99.265) +2022-11-14 17:03:02,563 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0729) Prec@1 86.000 (88.476) Prec@5 100.000 (99.274) +2022-11-14 17:03:02,571 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0864 (0.0730) Prec@1 86.000 (88.447) Prec@5 99.000 (99.271) +2022-11-14 17:03:02,578 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0998 (0.0733) Prec@1 86.000 (88.419) Prec@5 100.000 (99.279) +2022-11-14 17:03:02,586 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0734) Prec@1 90.000 (88.437) Prec@5 99.000 (99.276) +2022-11-14 17:03:02,594 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0735) Prec@1 88.000 (88.432) Prec@5 98.000 (99.261) +2022-11-14 17:03:02,601 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0733) Prec@1 91.000 (88.461) Prec@5 100.000 (99.270) +2022-11-14 17:03:02,609 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0733) Prec@1 90.000 (88.478) Prec@5 100.000 (99.278) +2022-11-14 17:03:02,617 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0730) Prec@1 92.000 (88.516) Prec@5 100.000 (99.286) +2022-11-14 17:03:02,625 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0729) Prec@1 89.000 (88.522) Prec@5 99.000 (99.283) +2022-11-14 17:03:02,632 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0730) Prec@1 84.000 (88.473) Prec@5 99.000 (99.280) +2022-11-14 17:03:02,640 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0732) Prec@1 86.000 (88.447) Prec@5 99.000 (99.277) +2022-11-14 17:03:02,648 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0732) Prec@1 87.000 (88.432) Prec@5 99.000 (99.274) +2022-11-14 17:03:02,655 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0731) Prec@1 91.000 (88.458) Prec@5 99.000 (99.271) +2022-11-14 17:03:02,663 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0730) Prec@1 91.000 (88.485) Prec@5 99.000 (99.268) +2022-11-14 17:03:02,671 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0733) Prec@1 84.000 (88.439) Prec@5 99.000 (99.265) +2022-11-14 17:03:02,678 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0737) Prec@1 81.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 17:03:02,686 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0737) Prec@1 86.000 (88.340) Prec@5 100.000 (99.280) +2022-11-14 17:03:02,740 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:03:03,068 Epoch: [449][0/500] Time 0.024 (0.024) Data 0.251 (0.251) Loss 0.0361 (0.0361) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:03,265 Epoch: [449][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0455 (0.0408) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:03:03,455 Epoch: [449][20/500] Time 0.015 (0.017) Data 0.002 (0.014) Loss 0.0345 (0.0387) Prec@1 94.000 (93.667) Prec@5 99.000 (99.667) +2022-11-14 17:03:03,643 Epoch: [449][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0490 (0.0413) Prec@1 91.000 (93.000) Prec@5 100.000 (99.750) +2022-11-14 17:03:03,834 Epoch: [449][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0428 (0.0416) Prec@1 92.000 (92.800) Prec@5 100.000 (99.800) +2022-11-14 17:03:04,024 Epoch: [449][50/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0440 (0.0420) Prec@1 93.000 (92.833) Prec@5 100.000 (99.833) +2022-11-14 17:03:04,218 Epoch: [449][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0440 (0.0423) Prec@1 92.000 (92.714) Prec@5 100.000 (99.857) +2022-11-14 17:03:04,411 Epoch: [449][70/500] Time 0.015 (0.017) Data 0.002 (0.005) Loss 0.0107 (0.0383) Prec@1 100.000 (93.625) Prec@5 100.000 (99.875) +2022-11-14 17:03:04,602 Epoch: [449][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0141 (0.0356) Prec@1 99.000 (94.222) Prec@5 100.000 (99.889) +2022-11-14 17:03:04,793 Epoch: [449][90/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0183 (0.0339) Prec@1 96.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 17:03:05,042 Epoch: [449][100/500] Time 0.026 (0.017) Data 0.001 (0.004) Loss 0.0168 (0.0323) Prec@1 99.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 17:03:05,324 Epoch: [449][110/500] Time 0.027 (0.018) Data 0.001 (0.004) Loss 0.0106 (0.0305) Prec@1 99.000 (95.167) Prec@5 100.000 (99.917) +2022-11-14 17:03:05,601 Epoch: [449][120/500] Time 0.026 (0.019) Data 0.002 (0.004) Loss 0.0301 (0.0305) Prec@1 94.000 (95.077) Prec@5 100.000 (99.923) +2022-11-14 17:03:05,879 Epoch: [449][130/500] Time 0.027 (0.019) Data 0.002 (0.004) Loss 0.0177 (0.0296) Prec@1 97.000 (95.214) Prec@5 100.000 (99.929) +2022-11-14 17:03:06,157 Epoch: [449][140/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0149 (0.0286) Prec@1 99.000 (95.467) Prec@5 100.000 (99.933) +2022-11-14 17:03:06,434 Epoch: [449][150/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0301 (0.0287) Prec@1 94.000 (95.375) Prec@5 99.000 (99.875) +2022-11-14 17:03:06,713 Epoch: [449][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0154 (0.0279) Prec@1 98.000 (95.529) Prec@5 100.000 (99.882) +2022-11-14 17:03:06,993 Epoch: [449][170/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0540 (0.0294) Prec@1 89.000 (95.167) Prec@5 100.000 (99.889) +2022-11-14 17:03:07,269 Epoch: [449][180/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0196 (0.0289) Prec@1 97.000 (95.263) Prec@5 100.000 (99.895) +2022-11-14 17:03:07,544 Epoch: [449][190/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0232 (0.0286) Prec@1 96.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 17:03:07,823 Epoch: [449][200/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0160 (0.0280) Prec@1 98.000 (95.429) Prec@5 100.000 (99.905) +2022-11-14 17:03:08,104 Epoch: [449][210/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0217 (0.0277) Prec@1 96.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:03:08,373 Epoch: [449][220/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0194 (0.0273) Prec@1 98.000 (95.565) Prec@5 100.000 (99.913) +2022-11-14 17:03:08,648 Epoch: [449][230/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0189 (0.0270) Prec@1 98.000 (95.667) Prec@5 100.000 (99.917) +2022-11-14 17:03:08,924 Epoch: [449][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0415 (0.0276) Prec@1 92.000 (95.520) Prec@5 100.000 (99.920) +2022-11-14 17:03:09,204 Epoch: [449][250/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0340 (0.0278) Prec@1 96.000 (95.538) Prec@5 100.000 (99.923) +2022-11-14 17:03:09,477 Epoch: [449][260/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0392 (0.0282) Prec@1 94.000 (95.481) Prec@5 99.000 (99.889) +2022-11-14 17:03:09,753 Epoch: [449][270/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0286 (0.0282) Prec@1 97.000 (95.536) Prec@5 100.000 (99.893) +2022-11-14 17:03:10,026 Epoch: [449][280/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0120 (0.0277) Prec@1 99.000 (95.655) Prec@5 100.000 (99.897) +2022-11-14 17:03:10,299 Epoch: [449][290/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0167 (0.0273) Prec@1 98.000 (95.733) Prec@5 100.000 (99.900) +2022-11-14 17:03:10,576 Epoch: [449][300/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0192 (0.0271) Prec@1 97.000 (95.774) Prec@5 100.000 (99.903) +2022-11-14 17:03:10,848 Epoch: [449][310/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0392 (0.0274) Prec@1 93.000 (95.688) Prec@5 100.000 (99.906) +2022-11-14 17:03:11,122 Epoch: [449][320/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0032 (0.0267) Prec@1 100.000 (95.818) Prec@5 100.000 (99.909) +2022-11-14 17:03:11,391 Epoch: [449][330/500] Time 0.025 (0.022) Data 0.003 (0.002) Loss 0.0317 (0.0268) Prec@1 94.000 (95.765) Prec@5 100.000 (99.912) +2022-11-14 17:03:11,670 Epoch: [449][340/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0240 (0.0268) Prec@1 95.000 (95.743) Prec@5 100.000 (99.914) +2022-11-14 17:03:11,945 Epoch: [449][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0391 (0.0271) Prec@1 95.000 (95.722) Prec@5 100.000 (99.917) +2022-11-14 17:03:12,224 Epoch: [449][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0317 (0.0272) Prec@1 96.000 (95.730) Prec@5 100.000 (99.919) +2022-11-14 17:03:12,500 Epoch: [449][370/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0277 (0.0272) Prec@1 94.000 (95.684) Prec@5 100.000 (99.921) +2022-11-14 17:03:12,774 Epoch: [449][380/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0181 (0.0270) Prec@1 98.000 (95.744) Prec@5 100.000 (99.923) +2022-11-14 17:03:13,045 Epoch: [449][390/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0288 (0.0271) Prec@1 95.000 (95.725) Prec@5 100.000 (99.925) +2022-11-14 17:03:13,318 Epoch: [449][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0168 (0.0268) Prec@1 98.000 (95.780) Prec@5 100.000 (99.927) +2022-11-14 17:03:13,592 Epoch: [449][410/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0300 (0.0269) Prec@1 96.000 (95.786) Prec@5 100.000 (99.929) +2022-11-14 17:03:13,866 Epoch: [449][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0164 (0.0266) Prec@1 97.000 (95.814) Prec@5 100.000 (99.930) +2022-11-14 17:03:14,143 Epoch: [449][430/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0292 (0.0267) Prec@1 96.000 (95.818) Prec@5 100.000 (99.932) +2022-11-14 17:03:14,416 Epoch: [449][440/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0355 (0.0269) Prec@1 93.000 (95.756) Prec@5 100.000 (99.933) +2022-11-14 17:03:14,689 Epoch: [449][450/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0436 (0.0273) Prec@1 90.000 (95.630) Prec@5 100.000 (99.935) +2022-11-14 17:03:14,965 Epoch: [449][460/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0415 (0.0276) Prec@1 90.000 (95.511) Prec@5 100.000 (99.936) +2022-11-14 17:03:15,241 Epoch: [449][470/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0249 (0.0275) Prec@1 96.000 (95.521) Prec@5 100.000 (99.938) +2022-11-14 17:03:15,519 Epoch: [449][480/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0377 (0.0277) Prec@1 94.000 (95.490) Prec@5 100.000 (99.939) +2022-11-14 17:03:15,792 Epoch: [449][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0182 (0.0275) Prec@1 96.000 (95.500) Prec@5 100.000 (99.940) +2022-11-14 17:03:16,037 Epoch: [449][499/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0430 (0.0278) Prec@1 92.000 (95.431) Prec@5 99.000 (99.922) +2022-11-14 17:03:16,337 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0652 (0.0652) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:16,348 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0652) Prec@1 89.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:03:16,355 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0678 (0.0661) Prec@1 89.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 17:03:16,367 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0670) Prec@1 89.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 17:03:16,374 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0810 (0.0698) Prec@1 85.000 (88.400) Prec@5 99.000 (99.600) +2022-11-14 17:03:16,381 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0654) Prec@1 93.000 (89.167) Prec@5 100.000 (99.667) +2022-11-14 17:03:16,388 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0705 (0.0661) Prec@1 91.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 17:03:16,399 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0686) Prec@1 84.000 (88.750) Prec@5 99.000 (99.625) +2022-11-14 17:03:16,406 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0707) Prec@1 87.000 (88.556) Prec@5 99.000 (99.556) +2022-11-14 17:03:16,413 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0714) Prec@1 87.000 (88.400) Prec@5 98.000 (99.400) +2022-11-14 17:03:16,419 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0696) Prec@1 91.000 (88.636) Prec@5 99.000 (99.364) +2022-11-14 17:03:16,427 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0720) Prec@1 85.000 (88.333) Prec@5 99.000 (99.333) +2022-11-14 17:03:16,435 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0499 (0.0703) Prec@1 91.000 (88.538) Prec@5 100.000 (99.385) +2022-11-14 17:03:16,443 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0700) Prec@1 89.000 (88.571) Prec@5 100.000 (99.429) +2022-11-14 17:03:16,450 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0702) Prec@1 89.000 (88.600) Prec@5 100.000 (99.467) +2022-11-14 17:03:16,458 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0709) Prec@1 87.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 17:03:16,466 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0695) Prec@1 93.000 (88.765) Prec@5 99.000 (99.471) +2022-11-14 17:03:16,473 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1131 (0.0719) Prec@1 81.000 (88.333) Prec@5 99.000 (99.444) +2022-11-14 17:03:16,481 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0726) Prec@1 84.000 (88.105) Prec@5 99.000 (99.421) +2022-11-14 17:03:16,490 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0732) Prec@1 88.000 (88.100) Prec@5 99.000 (99.400) +2022-11-14 17:03:16,497 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0737) Prec@1 86.000 (88.000) Prec@5 99.000 (99.381) +2022-11-14 17:03:16,505 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0749) Prec@1 83.000 (87.773) Prec@5 100.000 (99.409) +2022-11-14 17:03:16,512 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0753) Prec@1 87.000 (87.739) Prec@5 99.000 (99.391) +2022-11-14 17:03:16,520 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0758) Prec@1 88.000 (87.750) Prec@5 100.000 (99.417) +2022-11-14 17:03:16,528 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0769) Prec@1 83.000 (87.560) Prec@5 99.000 (99.400) +2022-11-14 17:03:16,536 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0776) Prec@1 84.000 (87.423) Prec@5 98.000 (99.346) +2022-11-14 17:03:16,543 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0763) Prec@1 93.000 (87.630) Prec@5 100.000 (99.370) +2022-11-14 17:03:16,551 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0760) Prec@1 89.000 (87.679) Prec@5 100.000 (99.393) +2022-11-14 17:03:16,559 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0756) Prec@1 91.000 (87.793) Prec@5 99.000 (99.379) +2022-11-14 17:03:16,566 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0757) Prec@1 84.000 (87.667) Prec@5 100.000 (99.400) +2022-11-14 17:03:16,574 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0750) Prec@1 91.000 (87.774) Prec@5 98.000 (99.355) +2022-11-14 17:03:16,582 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0750) Prec@1 90.000 (87.844) Prec@5 100.000 (99.375) +2022-11-14 17:03:16,590 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0754) Prec@1 86.000 (87.788) Prec@5 100.000 (99.394) +2022-11-14 17:03:16,598 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0755) Prec@1 83.000 (87.647) Prec@5 100.000 (99.412) +2022-11-14 17:03:16,605 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0758) Prec@1 86.000 (87.600) Prec@5 97.000 (99.343) +2022-11-14 17:03:16,613 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0754) Prec@1 90.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 17:03:16,621 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0755) Prec@1 88.000 (87.676) Prec@5 98.000 (99.297) +2022-11-14 17:03:16,629 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0756) Prec@1 87.000 (87.658) Prec@5 99.000 (99.289) +2022-11-14 17:03:16,636 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0751) Prec@1 92.000 (87.769) Prec@5 99.000 (99.282) +2022-11-14 17:03:16,644 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0746) Prec@1 89.000 (87.800) Prec@5 99.000 (99.275) +2022-11-14 17:03:16,651 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0747) Prec@1 89.000 (87.829) Prec@5 99.000 (99.268) +2022-11-14 17:03:16,659 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0747) Prec@1 89.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 17:03:16,666 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0302 (0.0737) Prec@1 97.000 (88.070) Prec@5 99.000 (99.279) +2022-11-14 17:03:16,674 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0735) Prec@1 90.000 (88.114) Prec@5 97.000 (99.227) +2022-11-14 17:03:16,681 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0732) Prec@1 91.000 (88.178) Prec@5 100.000 (99.244) +2022-11-14 17:03:16,689 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1148 (0.0741) Prec@1 80.000 (88.000) Prec@5 99.000 (99.239) +2022-11-14 17:03:16,697 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0739) Prec@1 89.000 (88.021) Prec@5 100.000 (99.255) +2022-11-14 17:03:16,704 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0745) Prec@1 84.000 (87.938) Prec@5 98.000 (99.229) +2022-11-14 17:03:16,712 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0740) Prec@1 91.000 (88.000) Prec@5 100.000 (99.245) +2022-11-14 17:03:16,720 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0744) Prec@1 86.000 (87.960) Prec@5 100.000 (99.260) +2022-11-14 17:03:16,727 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0743) Prec@1 88.000 (87.961) Prec@5 100.000 (99.275) +2022-11-14 17:03:16,735 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0744) Prec@1 88.000 (87.962) Prec@5 100.000 (99.288) +2022-11-14 17:03:16,743 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0743) Prec@1 89.000 (87.981) Prec@5 99.000 (99.283) +2022-11-14 17:03:16,750 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0745) Prec@1 87.000 (87.963) Prec@5 100.000 (99.296) +2022-11-14 17:03:16,758 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0746) Prec@1 88.000 (87.964) Prec@5 100.000 (99.309) +2022-11-14 17:03:16,765 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0746) Prec@1 88.000 (87.964) Prec@5 99.000 (99.304) +2022-11-14 17:03:16,773 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0748) Prec@1 86.000 (87.930) Prec@5 100.000 (99.316) +2022-11-14 17:03:16,780 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0746) Prec@1 91.000 (87.983) Prec@5 99.000 (99.310) +2022-11-14 17:03:16,788 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0746) Prec@1 87.000 (87.966) Prec@5 99.000 (99.305) +2022-11-14 17:03:16,796 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0747) Prec@1 87.000 (87.950) Prec@5 99.000 (99.300) +2022-11-14 17:03:16,803 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0744) Prec@1 92.000 (88.016) Prec@5 100.000 (99.311) +2022-11-14 17:03:16,811 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0741) Prec@1 92.000 (88.081) Prec@5 100.000 (99.323) +2022-11-14 17:03:16,818 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0740) Prec@1 91.000 (88.127) Prec@5 99.000 (99.317) +2022-11-14 17:03:16,826 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0395 (0.0734) Prec@1 94.000 (88.219) Prec@5 100.000 (99.328) +2022-11-14 17:03:16,833 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0738) Prec@1 86.000 (88.185) Prec@5 100.000 (99.338) +2022-11-14 17:03:16,841 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0737) Prec@1 88.000 (88.182) Prec@5 99.000 (99.333) +2022-11-14 17:03:16,849 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0735) Prec@1 90.000 (88.209) Prec@5 99.000 (99.328) +2022-11-14 17:03:16,856 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0733) Prec@1 91.000 (88.250) Prec@5 100.000 (99.338) +2022-11-14 17:03:16,864 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0734) Prec@1 88.000 (88.246) Prec@5 100.000 (99.348) +2022-11-14 17:03:16,871 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0736) Prec@1 85.000 (88.200) Prec@5 99.000 (99.343) +2022-11-14 17:03:16,879 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0739) Prec@1 88.000 (88.197) Prec@5 97.000 (99.310) +2022-11-14 17:03:16,886 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0737) Prec@1 92.000 (88.250) Prec@5 100.000 (99.319) +2022-11-14 17:03:16,894 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0735) Prec@1 91.000 (88.288) Prec@5 100.000 (99.329) +2022-11-14 17:03:16,902 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0730) Prec@1 94.000 (88.365) Prec@5 100.000 (99.338) +2022-11-14 17:03:16,909 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0732) Prec@1 86.000 (88.333) Prec@5 100.000 (99.347) +2022-11-14 17:03:16,917 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0731) Prec@1 89.000 (88.342) Prec@5 100.000 (99.355) +2022-11-14 17:03:16,924 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0730) Prec@1 91.000 (88.377) Prec@5 99.000 (99.351) +2022-11-14 17:03:16,932 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0731) Prec@1 88.000 (88.372) Prec@5 99.000 (99.346) +2022-11-14 17:03:16,939 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0732) Prec@1 87.000 (88.354) Prec@5 99.000 (99.342) +2022-11-14 17:03:16,947 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0732) Prec@1 88.000 (88.350) Prec@5 99.000 (99.338) +2022-11-14 17:03:16,954 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0733) Prec@1 88.000 (88.346) Prec@5 98.000 (99.321) +2022-11-14 17:03:16,963 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0732) Prec@1 89.000 (88.354) Prec@5 100.000 (99.329) +2022-11-14 17:03:16,971 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0735) Prec@1 85.000 (88.313) Prec@5 99.000 (99.325) +2022-11-14 17:03:16,978 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0733) Prec@1 90.000 (88.333) Prec@5 99.000 (99.321) +2022-11-14 17:03:16,986 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1137 (0.0738) Prec@1 80.000 (88.235) Prec@5 100.000 (99.329) +2022-11-14 17:03:16,993 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0741) Prec@1 87.000 (88.221) Prec@5 99.000 (99.326) +2022-11-14 17:03:17,001 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0742) Prec@1 85.000 (88.184) Prec@5 99.000 (99.322) +2022-11-14 17:03:17,008 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0743) Prec@1 88.000 (88.182) Prec@5 98.000 (99.307) +2022-11-14 17:03:17,016 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0743) Prec@1 88.000 (88.180) Prec@5 99.000 (99.303) +2022-11-14 17:03:17,023 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0741) Prec@1 93.000 (88.233) Prec@5 100.000 (99.311) +2022-11-14 17:03:17,031 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0738) Prec@1 92.000 (88.275) Prec@5 100.000 (99.319) +2022-11-14 17:03:17,039 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0736) Prec@1 92.000 (88.315) Prec@5 100.000 (99.326) +2022-11-14 17:03:17,046 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0737) Prec@1 87.000 (88.301) Prec@5 97.000 (99.301) +2022-11-14 17:03:17,054 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0736) Prec@1 89.000 (88.309) Prec@5 100.000 (99.309) +2022-11-14 17:03:17,061 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0739) Prec@1 87.000 (88.295) Prec@5 98.000 (99.295) +2022-11-14 17:03:17,069 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0738) Prec@1 90.000 (88.312) Prec@5 99.000 (99.292) +2022-11-14 17:03:17,076 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0736) Prec@1 91.000 (88.340) Prec@5 99.000 (99.289) +2022-11-14 17:03:17,085 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0737) Prec@1 86.000 (88.316) Prec@5 100.000 (99.296) +2022-11-14 17:03:17,093 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0737) Prec@1 88.000 (88.313) Prec@5 100.000 (99.303) +2022-11-14 17:03:17,101 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0736) Prec@1 90.000 (88.330) Prec@5 100.000 (99.310) +2022-11-14 17:03:17,155 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:03:17,477 Epoch: [450][0/500] Time 0.023 (0.023) Data 0.243 (0.243) Loss 0.0493 (0.0493) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:17,673 Epoch: [450][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0264 (0.0379) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:03:17,863 Epoch: [450][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0381 (0.0379) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:18,055 Epoch: [450][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0207 (0.0336) Prec@1 96.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 17:03:18,247 Epoch: [450][40/500] Time 0.018 (0.017) Data 0.001 (0.007) Loss 0.0288 (0.0327) Prec@1 95.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:18,440 Epoch: [450][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0294 (0.0321) Prec@1 96.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 17:03:18,630 Epoch: [450][60/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0197 (0.0303) Prec@1 97.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 17:03:18,823 Epoch: [450][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0227 (0.0294) Prec@1 95.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:03:19,022 Epoch: [450][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0036 (0.0265) Prec@1 100.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:03:19,218 Epoch: [450][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0343 (0.0273) Prec@1 95.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 17:03:19,411 Epoch: [450][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0242 (0.0270) Prec@1 95.000 (95.273) Prec@5 100.000 (100.000) +2022-11-14 17:03:19,600 Epoch: [450][110/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0171 (0.0262) Prec@1 97.000 (95.417) Prec@5 99.000 (99.917) +2022-11-14 17:03:19,793 Epoch: [450][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0243 (0.0260) Prec@1 96.000 (95.462) Prec@5 100.000 (99.923) +2022-11-14 17:03:19,983 Epoch: [450][130/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.0362 (0.0268) Prec@1 95.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 17:03:20,174 Epoch: [450][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0220 (0.0265) Prec@1 96.000 (95.467) Prec@5 100.000 (99.933) +2022-11-14 17:03:20,363 Epoch: [450][150/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.0197 (0.0260) Prec@1 98.000 (95.625) Prec@5 100.000 (99.938) +2022-11-14 17:03:20,551 Epoch: [450][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0204 (0.0257) Prec@1 97.000 (95.706) Prec@5 100.000 (99.941) +2022-11-14 17:03:20,817 Epoch: [450][170/500] Time 0.034 (0.017) Data 0.001 (0.003) Loss 0.0390 (0.0264) Prec@1 94.000 (95.611) Prec@5 99.000 (99.889) +2022-11-14 17:03:21,141 Epoch: [450][180/500] Time 0.035 (0.018) Data 0.001 (0.003) Loss 0.0383 (0.0271) Prec@1 93.000 (95.474) Prec@5 100.000 (99.895) +2022-11-14 17:03:21,461 Epoch: [450][190/500] Time 0.030 (0.018) Data 0.001 (0.003) Loss 0.0429 (0.0278) Prec@1 92.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 17:03:21,783 Epoch: [450][200/500] Time 0.031 (0.019) Data 0.001 (0.003) Loss 0.0212 (0.0275) Prec@1 97.000 (95.381) Prec@5 100.000 (99.905) +2022-11-14 17:03:22,104 Epoch: [450][210/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0225 (0.0273) Prec@1 97.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:03:22,425 Epoch: [450][220/500] Time 0.033 (0.020) Data 0.001 (0.003) Loss 0.0208 (0.0270) Prec@1 96.000 (95.478) Prec@5 100.000 (99.913) +2022-11-14 17:03:22,741 Epoch: [450][230/500] Time 0.030 (0.020) Data 0.002 (0.003) Loss 0.0220 (0.0268) Prec@1 96.000 (95.500) Prec@5 100.000 (99.917) +2022-11-14 17:03:23,057 Epoch: [450][240/500] Time 0.030 (0.021) Data 0.001 (0.003) Loss 0.0703 (0.0286) Prec@1 89.000 (95.240) Prec@5 100.000 (99.920) +2022-11-14 17:03:23,373 Epoch: [450][250/500] Time 0.031 (0.021) Data 0.002 (0.003) Loss 0.0366 (0.0289) Prec@1 93.000 (95.154) Prec@5 100.000 (99.923) +2022-11-14 17:03:23,685 Epoch: [450][260/500] Time 0.030 (0.021) Data 0.001 (0.003) Loss 0.0033 (0.0279) Prec@1 100.000 (95.333) Prec@5 100.000 (99.926) +2022-11-14 17:03:24,001 Epoch: [450][270/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0223 (0.0277) Prec@1 96.000 (95.357) Prec@5 100.000 (99.929) +2022-11-14 17:03:24,304 Epoch: [450][280/500] Time 0.030 (0.022) Data 0.001 (0.002) Loss 0.0431 (0.0282) Prec@1 92.000 (95.241) Prec@5 100.000 (99.931) +2022-11-14 17:03:24,607 Epoch: [450][290/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0256 (0.0282) Prec@1 96.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 17:03:24,921 Epoch: [450][300/500] Time 0.031 (0.022) Data 0.001 (0.002) Loss 0.0289 (0.0282) Prec@1 95.000 (95.258) Prec@5 100.000 (99.935) +2022-11-14 17:03:25,232 Epoch: [450][310/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0427 (0.0286) Prec@1 92.000 (95.156) Prec@5 100.000 (99.938) +2022-11-14 17:03:25,541 Epoch: [450][320/500] Time 0.031 (0.022) Data 0.001 (0.002) Loss 0.0292 (0.0286) Prec@1 95.000 (95.152) Prec@5 100.000 (99.939) +2022-11-14 17:03:25,846 Epoch: [450][330/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0213 (0.0284) Prec@1 95.000 (95.147) Prec@5 100.000 (99.941) +2022-11-14 17:03:26,154 Epoch: [450][340/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0240 (0.0283) Prec@1 96.000 (95.171) Prec@5 100.000 (99.943) +2022-11-14 17:03:26,454 Epoch: [450][350/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0690 (0.0294) Prec@1 87.000 (94.944) Prec@5 99.000 (99.917) +2022-11-14 17:03:26,761 Epoch: [450][360/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0170 (0.0291) Prec@1 97.000 (95.000) Prec@5 100.000 (99.919) +2022-11-14 17:03:27,069 Epoch: [450][370/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0240 (0.0290) Prec@1 97.000 (95.053) Prec@5 99.000 (99.895) +2022-11-14 17:03:27,372 Epoch: [450][380/500] Time 0.029 (0.023) Data 0.001 (0.002) Loss 0.0316 (0.0290) Prec@1 94.000 (95.026) Prec@5 100.000 (99.897) +2022-11-14 17:03:27,675 Epoch: [450][390/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0497 (0.0295) Prec@1 93.000 (94.975) Prec@5 100.000 (99.900) +2022-11-14 17:03:27,981 Epoch: [450][400/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0131 (0.0291) Prec@1 99.000 (95.073) Prec@5 100.000 (99.902) +2022-11-14 17:03:28,290 Epoch: [450][410/500] Time 0.029 (0.023) Data 0.001 (0.002) Loss 0.0377 (0.0294) Prec@1 92.000 (95.000) Prec@5 100.000 (99.905) +2022-11-14 17:03:28,595 Epoch: [450][420/500] Time 0.030 (0.023) Data 0.001 (0.002) Loss 0.0130 (0.0290) Prec@1 99.000 (95.093) Prec@5 100.000 (99.907) +2022-11-14 17:03:28,902 Epoch: [450][430/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0330 (0.0291) Prec@1 96.000 (95.114) Prec@5 100.000 (99.909) +2022-11-14 17:03:29,206 Epoch: [450][440/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0206 (0.0289) Prec@1 98.000 (95.178) Prec@5 100.000 (99.911) +2022-11-14 17:03:29,516 Epoch: [450][450/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0386 (0.0291) Prec@1 95.000 (95.174) Prec@5 99.000 (99.891) +2022-11-14 17:03:29,822 Epoch: [450][460/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0253 (0.0290) Prec@1 96.000 (95.191) Prec@5 100.000 (99.894) +2022-11-14 17:03:30,128 Epoch: [450][470/500] Time 0.033 (0.024) Data 0.002 (0.002) Loss 0.0107 (0.0286) Prec@1 98.000 (95.250) Prec@5 100.000 (99.896) +2022-11-14 17:03:30,431 Epoch: [450][480/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0464 (0.0290) Prec@1 93.000 (95.204) Prec@5 100.000 (99.898) +2022-11-14 17:03:30,738 Epoch: [450][490/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0208 (0.0288) Prec@1 97.000 (95.240) Prec@5 100.000 (99.900) +2022-11-14 17:03:31,015 Epoch: [450][499/500] Time 0.029 (0.024) Data 0.001 (0.002) Loss 0.0219 (0.0287) Prec@1 96.000 (95.255) Prec@5 100.000 (99.902) +2022-11-14 17:03:31,319 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0656 (0.0656) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,327 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0629) Prec@1 91.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,334 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0747 (0.0668) Prec@1 88.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,344 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0672) Prec@1 88.000 (89.250) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,351 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0658) Prec@1 89.000 (89.200) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,358 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0381 (0.0612) Prec@1 94.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,365 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0608) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:31,373 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0620) Prec@1 89.000 (89.875) Prec@5 99.000 (99.875) +2022-11-14 17:03:31,380 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0633) Prec@1 88.000 (89.667) Prec@5 100.000 (99.889) +2022-11-14 17:03:31,386 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0643) Prec@1 89.000 (89.600) Prec@5 99.000 (99.800) +2022-11-14 17:03:31,394 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0639) Prec@1 91.000 (89.727) Prec@5 99.000 (99.727) +2022-11-14 17:03:31,401 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0669) Prec@1 83.000 (89.167) Prec@5 100.000 (99.750) +2022-11-14 17:03:31,409 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0673) Prec@1 89.000 (89.154) Prec@5 100.000 (99.769) +2022-11-14 17:03:31,416 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0679) Prec@1 89.000 (89.143) Prec@5 99.000 (99.714) +2022-11-14 17:03:31,424 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0692) Prec@1 88.000 (89.067) Prec@5 100.000 (99.733) +2022-11-14 17:03:31,431 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0687) Prec@1 89.000 (89.062) Prec@5 100.000 (99.750) +2022-11-14 17:03:31,439 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0680) Prec@1 91.000 (89.176) Prec@5 98.000 (99.647) +2022-11-14 17:03:31,447 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0699) Prec@1 85.000 (88.944) Prec@5 100.000 (99.667) +2022-11-14 17:03:31,454 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0708) Prec@1 84.000 (88.684) Prec@5 99.000 (99.632) +2022-11-14 17:03:31,461 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0935 (0.0719) Prec@1 86.000 (88.550) Prec@5 97.000 (99.500) +2022-11-14 17:03:31,469 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0887 (0.0727) Prec@1 84.000 (88.333) Prec@5 99.000 (99.476) +2022-11-14 17:03:31,477 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0730) Prec@1 88.000 (88.318) Prec@5 99.000 (99.455) +2022-11-14 17:03:31,485 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1019 (0.0743) Prec@1 84.000 (88.130) Prec@5 99.000 (99.435) +2022-11-14 17:03:31,492 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0573 (0.0736) Prec@1 89.000 (88.167) Prec@5 100.000 (99.458) +2022-11-14 17:03:31,500 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0883 (0.0742) Prec@1 84.000 (88.000) Prec@5 100.000 (99.480) +2022-11-14 17:03:31,507 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0849 (0.0746) Prec@1 87.000 (87.962) Prec@5 98.000 (99.423) +2022-11-14 17:03:31,515 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0600 (0.0740) Prec@1 91.000 (88.074) Prec@5 100.000 (99.444) +2022-11-14 17:03:31,522 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0737) Prec@1 89.000 (88.107) Prec@5 100.000 (99.464) +2022-11-14 17:03:31,530 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0603 (0.0733) Prec@1 90.000 (88.172) Prec@5 99.000 (99.448) +2022-11-14 17:03:31,537 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0730) Prec@1 91.000 (88.267) Prec@5 98.000 (99.400) +2022-11-14 17:03:31,545 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0516 (0.0723) Prec@1 91.000 (88.355) Prec@5 99.000 (99.387) +2022-11-14 17:03:31,552 Test: [31/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0721) Prec@1 92.000 (88.469) Prec@5 99.000 (99.375) +2022-11-14 17:03:31,560 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0721) Prec@1 91.000 (88.545) Prec@5 100.000 (99.394) +2022-11-14 17:03:31,568 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0875 (0.0725) Prec@1 86.000 (88.471) Prec@5 99.000 (99.382) +2022-11-14 17:03:31,576 Test: [34/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0784 (0.0727) Prec@1 89.000 (88.486) Prec@5 97.000 (99.314) +2022-11-14 17:03:31,583 Test: [35/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0699 (0.0726) Prec@1 90.000 (88.528) Prec@5 100.000 (99.333) +2022-11-14 17:03:31,591 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0725) Prec@1 88.000 (88.514) Prec@5 98.000 (99.297) +2022-11-14 17:03:31,599 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0727) Prec@1 87.000 (88.474) Prec@5 100.000 (99.316) +2022-11-14 17:03:31,607 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0553 (0.0722) Prec@1 91.000 (88.538) Prec@5 99.000 (99.308) +2022-11-14 17:03:31,614 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0833 (0.0725) Prec@1 88.000 (88.525) Prec@5 99.000 (99.300) +2022-11-14 17:03:31,622 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0898 (0.0729) Prec@1 86.000 (88.463) Prec@5 97.000 (99.244) +2022-11-14 17:03:31,629 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0728) Prec@1 87.000 (88.429) Prec@5 99.000 (99.238) +2022-11-14 17:03:31,637 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0533 (0.0724) Prec@1 91.000 (88.488) Prec@5 99.000 (99.233) +2022-11-14 17:03:31,644 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0723) Prec@1 90.000 (88.523) Prec@5 99.000 (99.227) +2022-11-14 17:03:31,652 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0493 (0.0718) Prec@1 92.000 (88.600) Prec@5 100.000 (99.244) +2022-11-14 17:03:31,659 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0840 (0.0720) Prec@1 86.000 (88.543) Prec@5 100.000 (99.261) +2022-11-14 17:03:31,667 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0719) Prec@1 89.000 (88.553) Prec@5 100.000 (99.277) +2022-11-14 17:03:31,675 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1188 (0.0729) Prec@1 83.000 (88.438) Prec@5 98.000 (99.250) +2022-11-14 17:03:31,683 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0594 (0.0726) Prec@1 88.000 (88.429) Prec@5 100.000 (99.265) +2022-11-14 17:03:31,690 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1070 (0.0733) Prec@1 83.000 (88.320) Prec@5 99.000 (99.260) +2022-11-14 17:03:31,697 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0610 (0.0731) Prec@1 87.000 (88.294) Prec@5 100.000 (99.275) +2022-11-14 17:03:31,705 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0730) Prec@1 90.000 (88.327) Prec@5 98.000 (99.250) +2022-11-14 17:03:31,713 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0721 (0.0730) Prec@1 86.000 (88.283) Prec@5 100.000 (99.264) +2022-11-14 17:03:31,720 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0730) Prec@1 88.000 (88.278) Prec@5 99.000 (99.259) +2022-11-14 17:03:31,728 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0820 (0.0732) Prec@1 86.000 (88.236) Prec@5 100.000 (99.273) +2022-11-14 17:03:31,735 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0730) Prec@1 90.000 (88.268) Prec@5 99.000 (99.268) +2022-11-14 17:03:31,743 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0569 (0.0727) Prec@1 90.000 (88.298) Prec@5 99.000 (99.263) +2022-11-14 17:03:31,751 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0820 (0.0729) Prec@1 89.000 (88.310) Prec@5 100.000 (99.276) +2022-11-14 17:03:31,758 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0979 (0.0733) Prec@1 88.000 (88.305) Prec@5 100.000 (99.288) +2022-11-14 17:03:31,766 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0779 (0.0734) Prec@1 88.000 (88.300) Prec@5 99.000 (99.283) +2022-11-14 17:03:31,773 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0735) Prec@1 86.000 (88.262) Prec@5 99.000 (99.279) +2022-11-14 17:03:31,780 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0734) Prec@1 91.000 (88.306) Prec@5 99.000 (99.274) +2022-11-14 17:03:31,788 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0489 (0.0730) Prec@1 93.000 (88.381) Prec@5 100.000 (99.286) +2022-11-14 17:03:31,796 Test: [63/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0291 (0.0723) Prec@1 95.000 (88.484) Prec@5 100.000 (99.297) +2022-11-14 17:03:31,803 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0724) Prec@1 87.000 (88.462) Prec@5 99.000 (99.292) +2022-11-14 17:03:31,811 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0753 (0.0725) Prec@1 88.000 (88.455) Prec@5 98.000 (99.273) +2022-11-14 17:03:31,818 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0524 (0.0722) Prec@1 90.000 (88.478) Prec@5 100.000 (99.284) +2022-11-14 17:03:31,826 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0802 (0.0723) Prec@1 89.000 (88.485) Prec@5 99.000 (99.279) +2022-11-14 17:03:31,833 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0723) Prec@1 89.000 (88.493) Prec@5 99.000 (99.275) +2022-11-14 17:03:31,841 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0664 (0.0722) Prec@1 89.000 (88.500) Prec@5 100.000 (99.286) +2022-11-14 17:03:31,848 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1070 (0.0727) Prec@1 84.000 (88.437) Prec@5 96.000 (99.239) +2022-11-14 17:03:31,856 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0599 (0.0725) Prec@1 91.000 (88.472) Prec@5 99.000 (99.236) +2022-11-14 17:03:31,864 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0337 (0.0720) Prec@1 96.000 (88.575) Prec@5 99.000 (99.233) +2022-11-14 17:03:31,871 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0445 (0.0716) Prec@1 94.000 (88.649) Prec@5 99.000 (99.230) +2022-11-14 17:03:31,878 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1053 (0.0721) Prec@1 86.000 (88.613) Prec@5 100.000 (99.240) +2022-11-14 17:03:31,886 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0588 (0.0719) Prec@1 90.000 (88.632) Prec@5 100.000 (99.250) +2022-11-14 17:03:31,893 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0778 (0.0720) Prec@1 87.000 (88.610) Prec@5 99.000 (99.247) +2022-11-14 17:03:31,901 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0719) Prec@1 88.000 (88.603) Prec@5 100.000 (99.256) +2022-11-14 17:03:31,908 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0720) Prec@1 87.000 (88.582) Prec@5 100.000 (99.266) +2022-11-14 17:03:31,916 Test: [79/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0808 (0.0722) Prec@1 89.000 (88.588) Prec@5 99.000 (99.263) +2022-11-14 17:03:31,924 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0890 (0.0724) Prec@1 87.000 (88.568) Prec@5 98.000 (99.247) +2022-11-14 17:03:31,931 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0725) Prec@1 88.000 (88.561) Prec@5 100.000 (99.256) +2022-11-14 17:03:31,939 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0932 (0.0727) Prec@1 85.000 (88.518) Prec@5 99.000 (99.253) +2022-11-14 17:03:31,946 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0876 (0.0729) Prec@1 85.000 (88.476) Prec@5 99.000 (99.250) +2022-11-14 17:03:31,954 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1144 (0.0734) Prec@1 78.000 (88.353) Prec@5 99.000 (99.247) +2022-11-14 17:03:31,962 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0961 (0.0737) Prec@1 87.000 (88.337) Prec@5 100.000 (99.256) +2022-11-14 17:03:31,969 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0737) Prec@1 87.000 (88.322) Prec@5 99.000 (99.253) +2022-11-14 17:03:31,977 Test: [87/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0840 (0.0738) Prec@1 87.000 (88.307) Prec@5 98.000 (99.239) +2022-11-14 17:03:31,985 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0738) Prec@1 88.000 (88.303) Prec@5 100.000 (99.247) +2022-11-14 17:03:31,993 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0739) Prec@1 89.000 (88.311) Prec@5 99.000 (99.244) +2022-11-14 17:03:32,000 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0738) Prec@1 89.000 (88.319) Prec@5 100.000 (99.253) +2022-11-14 17:03:32,008 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0510 (0.0736) Prec@1 94.000 (88.380) Prec@5 100.000 (99.261) +2022-11-14 17:03:32,015 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0736) Prec@1 88.000 (88.376) Prec@5 99.000 (99.258) +2022-11-14 17:03:32,023 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0728 (0.0736) Prec@1 89.000 (88.383) Prec@5 99.000 (99.255) +2022-11-14 17:03:32,030 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1058 (0.0740) Prec@1 81.000 (88.305) Prec@5 100.000 (99.263) +2022-11-14 17:03:32,037 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0738) Prec@1 90.000 (88.323) Prec@5 99.000 (99.260) +2022-11-14 17:03:32,045 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0737) Prec@1 92.000 (88.361) Prec@5 99.000 (99.258) +2022-11-14 17:03:32,052 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0738) Prec@1 86.000 (88.337) Prec@5 100.000 (99.265) +2022-11-14 17:03:32,059 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1200 (0.0743) Prec@1 83.000 (88.283) Prec@5 99.000 (99.263) +2022-11-14 17:03:32,067 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0841 (0.0744) Prec@1 88.000 (88.280) Prec@5 100.000 (99.270) +2022-11-14 17:03:32,119 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:03:32,432 Epoch: [451][0/500] Time 0.027 (0.027) Data 0.232 (0.232) Loss 0.0291 (0.0291) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:32,641 Epoch: [451][10/500] Time 0.016 (0.019) Data 0.002 (0.023) Loss 0.0438 (0.0365) Prec@1 92.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:32,837 Epoch: [451][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0238 (0.0323) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:03:33,040 Epoch: [451][30/500] Time 0.016 (0.018) Data 0.002 (0.009) Loss 0.0228 (0.0299) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:03:33,239 Epoch: [451][40/500] Time 0.017 (0.018) Data 0.001 (0.007) Loss 0.0356 (0.0310) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:33,442 Epoch: [451][50/500] Time 0.016 (0.018) Data 0.002 (0.006) Loss 0.0230 (0.0297) Prec@1 96.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 17:03:33,640 Epoch: [451][60/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0390 (0.0310) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:33,842 Epoch: [451][70/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0308 (0.0310) Prec@1 94.000 (94.875) Prec@5 100.000 (100.000) +2022-11-14 17:03:34,041 Epoch: [451][80/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0188 (0.0296) Prec@1 97.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 17:03:34,247 Epoch: [451][90/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.0407 (0.0307) Prec@1 95.000 (95.100) Prec@5 99.000 (99.900) +2022-11-14 17:03:34,446 Epoch: [451][100/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0266 (0.0304) Prec@1 97.000 (95.273) Prec@5 100.000 (99.909) +2022-11-14 17:03:34,649 Epoch: [451][110/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0343 (0.0307) Prec@1 94.000 (95.167) Prec@5 100.000 (99.917) +2022-11-14 17:03:34,846 Epoch: [451][120/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0216 (0.0300) Prec@1 96.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 17:03:35,053 Epoch: [451][130/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0210 (0.0294) Prec@1 97.000 (95.357) Prec@5 100.000 (99.929) +2022-11-14 17:03:35,254 Epoch: [451][140/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0296 (0.0294) Prec@1 95.000 (95.333) Prec@5 100.000 (99.933) +2022-11-14 17:03:35,456 Epoch: [451][150/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0223 (0.0289) Prec@1 97.000 (95.438) Prec@5 100.000 (99.938) +2022-11-14 17:03:35,654 Epoch: [451][160/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0252 (0.0287) Prec@1 97.000 (95.529) Prec@5 100.000 (99.941) +2022-11-14 17:03:35,854 Epoch: [451][170/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0099 (0.0277) Prec@1 98.000 (95.667) Prec@5 100.000 (99.944) +2022-11-14 17:03:36,051 Epoch: [451][180/500] Time 0.016 (0.018) Data 0.002 (0.003) Loss 0.0375 (0.0282) Prec@1 93.000 (95.526) Prec@5 100.000 (99.947) +2022-11-14 17:03:36,244 Epoch: [451][190/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0107 (0.0273) Prec@1 99.000 (95.700) Prec@5 100.000 (99.950) +2022-11-14 17:03:36,433 Epoch: [451][200/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0146 (0.0267) Prec@1 98.000 (95.810) Prec@5 100.000 (99.952) +2022-11-14 17:03:36,634 Epoch: [451][210/500] Time 0.018 (0.018) Data 0.002 (0.003) Loss 0.0250 (0.0266) Prec@1 97.000 (95.864) Prec@5 100.000 (99.955) +2022-11-14 17:03:36,821 Epoch: [451][220/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0348 (0.0270) Prec@1 94.000 (95.783) Prec@5 99.000 (99.913) +2022-11-14 17:03:37,010 Epoch: [451][230/500] Time 0.019 (0.018) Data 0.002 (0.003) Loss 0.0321 (0.0272) Prec@1 94.000 (95.708) Prec@5 100.000 (99.917) +2022-11-14 17:03:37,203 Epoch: [451][240/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0206 (0.0269) Prec@1 95.000 (95.680) Prec@5 100.000 (99.920) +2022-11-14 17:03:37,391 Epoch: [451][250/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0367 (0.0273) Prec@1 95.000 (95.654) Prec@5 100.000 (99.923) +2022-11-14 17:03:37,642 Epoch: [451][260/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0248 (0.0272) Prec@1 97.000 (95.704) Prec@5 99.000 (99.889) +2022-11-14 17:03:37,912 Epoch: [451][270/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0148 (0.0268) Prec@1 98.000 (95.786) Prec@5 100.000 (99.893) +2022-11-14 17:03:38,184 Epoch: [451][280/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0145 (0.0264) Prec@1 98.000 (95.862) Prec@5 100.000 (99.897) +2022-11-14 17:03:38,455 Epoch: [451][290/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0155 (0.0260) Prec@1 97.000 (95.900) Prec@5 100.000 (99.900) +2022-11-14 17:03:38,722 Epoch: [451][300/500] Time 0.025 (0.018) Data 0.002 (0.002) Loss 0.0367 (0.0263) Prec@1 94.000 (95.839) Prec@5 100.000 (99.903) +2022-11-14 17:03:38,995 Epoch: [451][310/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0425 (0.0268) Prec@1 92.000 (95.719) Prec@5 100.000 (99.906) +2022-11-14 17:03:39,264 Epoch: [451][320/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0159 (0.0265) Prec@1 97.000 (95.758) Prec@5 100.000 (99.909) +2022-11-14 17:03:39,538 Epoch: [451][330/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0271 (0.0265) Prec@1 96.000 (95.765) Prec@5 100.000 (99.912) +2022-11-14 17:03:39,811 Epoch: [451][340/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0321 (0.0267) Prec@1 97.000 (95.800) Prec@5 100.000 (99.914) +2022-11-14 17:03:40,080 Epoch: [451][350/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0210 (0.0265) Prec@1 98.000 (95.861) Prec@5 100.000 (99.917) +2022-11-14 17:03:40,350 Epoch: [451][360/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0420 (0.0269) Prec@1 94.000 (95.811) Prec@5 100.000 (99.919) +2022-11-14 17:03:40,622 Epoch: [451][370/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0663 (0.0280) Prec@1 88.000 (95.605) Prec@5 100.000 (99.921) +2022-11-14 17:03:40,891 Epoch: [451][380/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0284 (0.0280) Prec@1 95.000 (95.590) Prec@5 100.000 (99.923) +2022-11-14 17:03:41,165 Epoch: [451][390/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0460 (0.0284) Prec@1 92.000 (95.500) Prec@5 100.000 (99.925) +2022-11-14 17:03:41,434 Epoch: [451][400/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0283 (0.0284) Prec@1 95.000 (95.488) Prec@5 100.000 (99.927) +2022-11-14 17:03:41,707 Epoch: [451][410/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0329 (0.0285) Prec@1 94.000 (95.452) Prec@5 100.000 (99.929) +2022-11-14 17:03:41,979 Epoch: [451][420/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0194 (0.0283) Prec@1 97.000 (95.488) Prec@5 100.000 (99.930) +2022-11-14 17:03:42,254 Epoch: [451][430/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0145 (0.0280) Prec@1 99.000 (95.568) Prec@5 100.000 (99.932) +2022-11-14 17:03:42,523 Epoch: [451][440/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0574 (0.0287) Prec@1 91.000 (95.467) Prec@5 99.000 (99.911) +2022-11-14 17:03:42,792 Epoch: [451][450/500] Time 0.024 (0.020) Data 0.003 (0.002) Loss 0.0175 (0.0284) Prec@1 97.000 (95.500) Prec@5 100.000 (99.913) +2022-11-14 17:03:43,064 Epoch: [451][460/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0179 (0.0282) Prec@1 97.000 (95.532) Prec@5 100.000 (99.915) +2022-11-14 17:03:43,332 Epoch: [451][470/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0207 (0.0280) Prec@1 96.000 (95.542) Prec@5 100.000 (99.917) +2022-11-14 17:03:43,604 Epoch: [451][480/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0178 (0.0278) Prec@1 95.000 (95.531) Prec@5 100.000 (99.918) +2022-11-14 17:03:43,872 Epoch: [451][490/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0284 (0.0278) Prec@1 95.000 (95.520) Prec@5 100.000 (99.920) +2022-11-14 17:03:44,115 Epoch: [451][499/500] Time 0.029 (0.021) Data 0.001 (0.002) Loss 0.0194 (0.0277) Prec@1 98.000 (95.569) Prec@5 100.000 (99.922) +2022-11-14 17:03:44,419 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0822 (0.0822) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:44,427 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0703 (0.0763) Prec@1 91.000 (88.500) Prec@5 98.000 (99.000) +2022-11-14 17:03:44,437 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0645 (0.0723) Prec@1 91.000 (89.333) Prec@5 100.000 (99.333) +2022-11-14 17:03:44,447 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0710) Prec@1 91.000 (89.750) Prec@5 99.000 (99.250) +2022-11-14 17:03:44,454 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0712) Prec@1 88.000 (89.400) Prec@5 99.000 (99.200) +2022-11-14 17:03:44,460 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0674) Prec@1 93.000 (90.000) Prec@5 100.000 (99.333) +2022-11-14 17:03:44,467 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0671) Prec@1 89.000 (89.857) Prec@5 99.000 (99.286) +2022-11-14 17:03:44,476 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0708) Prec@1 83.000 (89.000) Prec@5 98.000 (99.125) +2022-11-14 17:03:44,483 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0717) Prec@1 89.000 (89.000) Prec@5 99.000 (99.111) +2022-11-14 17:03:44,489 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0726) Prec@1 87.000 (88.800) Prec@5 98.000 (99.000) +2022-11-14 17:03:44,496 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0721) Prec@1 89.000 (88.818) Prec@5 100.000 (99.091) +2022-11-14 17:03:44,503 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0725) Prec@1 89.000 (88.833) Prec@5 99.000 (99.083) +2022-11-14 17:03:44,511 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0711) Prec@1 89.000 (88.846) Prec@5 100.000 (99.154) +2022-11-14 17:03:44,520 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0719) Prec@1 89.000 (88.857) Prec@5 99.000 (99.143) +2022-11-14 17:03:44,527 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0724) Prec@1 89.000 (88.867) Prec@5 100.000 (99.200) +2022-11-14 17:03:44,535 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0717) Prec@1 92.000 (89.062) Prec@5 100.000 (99.250) +2022-11-14 17:03:44,542 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0705) Prec@1 92.000 (89.235) Prec@5 99.000 (99.235) +2022-11-14 17:03:44,549 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1124 (0.0728) Prec@1 85.000 (89.000) Prec@5 100.000 (99.278) +2022-11-14 17:03:44,557 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0736) Prec@1 86.000 (88.842) Prec@5 97.000 (99.158) +2022-11-14 17:03:44,564 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0936 (0.0746) Prec@1 86.000 (88.700) Prec@5 97.000 (99.050) +2022-11-14 17:03:44,572 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0755 (0.0747) Prec@1 87.000 (88.619) Prec@5 99.000 (99.048) +2022-11-14 17:03:44,579 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0770 (0.0748) Prec@1 86.000 (88.500) Prec@5 98.000 (99.000) +2022-11-14 17:03:44,587 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1034 (0.0760) Prec@1 85.000 (88.348) Prec@5 99.000 (99.000) +2022-11-14 17:03:44,594 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0802 (0.0762) Prec@1 88.000 (88.333) Prec@5 99.000 (99.000) +2022-11-14 17:03:44,601 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0915 (0.0768) Prec@1 87.000 (88.280) Prec@5 100.000 (99.040) +2022-11-14 17:03:44,609 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0822 (0.0770) Prec@1 87.000 (88.231) Prec@5 100.000 (99.077) +2022-11-14 17:03:44,616 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0481 (0.0760) Prec@1 92.000 (88.370) Prec@5 100.000 (99.111) +2022-11-14 17:03:44,623 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0759) Prec@1 88.000 (88.357) Prec@5 99.000 (99.107) +2022-11-14 17:03:44,631 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0770 (0.0760) Prec@1 88.000 (88.345) Prec@5 99.000 (99.103) +2022-11-14 17:03:44,638 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0765) Prec@1 86.000 (88.267) Prec@5 98.000 (99.067) +2022-11-14 17:03:44,645 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0618 (0.0760) Prec@1 88.000 (88.258) Prec@5 98.000 (99.032) +2022-11-14 17:03:44,653 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0493 (0.0752) Prec@1 93.000 (88.406) Prec@5 100.000 (99.062) +2022-11-14 17:03:44,661 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0752) Prec@1 88.000 (88.394) Prec@5 100.000 (99.091) +2022-11-14 17:03:44,668 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1175 (0.0764) Prec@1 79.000 (88.118) Prec@5 99.000 (99.088) +2022-11-14 17:03:44,675 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0863 (0.0767) Prec@1 86.000 (88.057) Prec@5 99.000 (99.086) +2022-11-14 17:03:44,682 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0765) Prec@1 90.000 (88.111) Prec@5 99.000 (99.083) +2022-11-14 17:03:44,690 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0762) Prec@1 88.000 (88.108) Prec@5 99.000 (99.081) +2022-11-14 17:03:44,697 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0945 (0.0767) Prec@1 86.000 (88.053) Prec@5 100.000 (99.105) +2022-11-14 17:03:44,705 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0426 (0.0759) Prec@1 93.000 (88.179) Prec@5 99.000 (99.103) +2022-11-14 17:03:44,712 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0691 (0.0757) Prec@1 90.000 (88.225) Prec@5 99.000 (99.100) +2022-11-14 17:03:44,720 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1041 (0.0764) Prec@1 82.000 (88.073) Prec@5 98.000 (99.073) +2022-11-14 17:03:44,727 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0762) Prec@1 90.000 (88.119) Prec@5 99.000 (99.071) +2022-11-14 17:03:44,734 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0581 (0.0758) Prec@1 89.000 (88.140) Prec@5 99.000 (99.070) +2022-11-14 17:03:44,742 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0571 (0.0754) Prec@1 92.000 (88.227) Prec@5 99.000 (99.068) +2022-11-14 17:03:44,750 Test: [44/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0753) Prec@1 88.000 (88.222) Prec@5 99.000 (99.067) +2022-11-14 17:03:44,757 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1049 (0.0759) Prec@1 83.000 (88.109) Prec@5 100.000 (99.087) +2022-11-14 17:03:44,765 Test: [46/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0744 (0.0759) Prec@1 85.000 (88.043) Prec@5 100.000 (99.106) +2022-11-14 17:03:44,773 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0934 (0.0762) Prec@1 84.000 (87.958) Prec@5 99.000 (99.104) +2022-11-14 17:03:44,781 Test: [48/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0511 (0.0757) Prec@1 91.000 (88.020) Prec@5 100.000 (99.122) +2022-11-14 17:03:44,788 Test: [49/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0835 (0.0759) Prec@1 90.000 (88.060) Prec@5 99.000 (99.120) +2022-11-14 17:03:44,796 Test: [50/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0639 (0.0757) Prec@1 90.000 (88.098) Prec@5 99.000 (99.118) +2022-11-14 17:03:44,803 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0879 (0.0759) Prec@1 85.000 (88.038) Prec@5 98.000 (99.096) +2022-11-14 17:03:44,811 Test: [52/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0729 (0.0758) Prec@1 88.000 (88.038) Prec@5 100.000 (99.113) +2022-11-14 17:03:44,819 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0542 (0.0754) Prec@1 90.000 (88.074) Prec@5 99.000 (99.111) +2022-11-14 17:03:44,826 Test: [54/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0820 (0.0756) Prec@1 86.000 (88.036) Prec@5 100.000 (99.127) +2022-11-14 17:03:44,834 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0754) Prec@1 90.000 (88.071) Prec@5 100.000 (99.143) +2022-11-14 17:03:44,842 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0721 (0.0753) Prec@1 85.000 (88.018) Prec@5 100.000 (99.158) +2022-11-14 17:03:44,849 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0512 (0.0749) Prec@1 92.000 (88.086) Prec@5 99.000 (99.155) +2022-11-14 17:03:44,857 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1106 (0.0755) Prec@1 81.000 (87.966) Prec@5 99.000 (99.153) +2022-11-14 17:03:44,864 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0803 (0.0756) Prec@1 86.000 (87.933) Prec@5 100.000 (99.167) +2022-11-14 17:03:44,872 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0791 (0.0757) Prec@1 88.000 (87.934) Prec@5 100.000 (99.180) +2022-11-14 17:03:44,880 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0756) Prec@1 90.000 (87.968) Prec@5 98.000 (99.161) +2022-11-14 17:03:44,887 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0805 (0.0757) Prec@1 86.000 (87.937) Prec@5 100.000 (99.175) +2022-11-14 17:03:44,895 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0482 (0.0752) Prec@1 92.000 (88.000) Prec@5 100.000 (99.188) +2022-11-14 17:03:44,902 Test: [64/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0918 (0.0755) Prec@1 83.000 (87.923) Prec@5 99.000 (99.185) +2022-11-14 17:03:44,910 Test: [65/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0520 (0.0751) Prec@1 92.000 (87.985) Prec@5 99.000 (99.182) +2022-11-14 17:03:44,917 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0479 (0.0747) Prec@1 93.000 (88.060) Prec@5 100.000 (99.194) +2022-11-14 17:03:44,925 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0744) Prec@1 92.000 (88.118) Prec@5 100.000 (99.206) +2022-11-14 17:03:44,933 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0743) Prec@1 90.000 (88.145) Prec@5 99.000 (99.203) +2022-11-14 17:03:44,940 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0744) Prec@1 90.000 (88.171) Prec@5 99.000 (99.200) +2022-11-14 17:03:44,948 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0877 (0.0746) Prec@1 88.000 (88.169) Prec@5 99.000 (99.197) +2022-11-14 17:03:44,955 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0566 (0.0743) Prec@1 91.000 (88.208) Prec@5 100.000 (99.208) +2022-11-14 17:03:44,963 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0547 (0.0740) Prec@1 93.000 (88.274) Prec@5 100.000 (99.219) +2022-11-14 17:03:44,971 Test: [73/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0774 (0.0741) Prec@1 88.000 (88.270) Prec@5 100.000 (99.230) +2022-11-14 17:03:44,978 Test: [74/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1051 (0.0745) Prec@1 86.000 (88.240) Prec@5 98.000 (99.213) +2022-11-14 17:03:44,986 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0746) Prec@1 87.000 (88.224) Prec@5 100.000 (99.224) +2022-11-14 17:03:44,994 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0746) Prec@1 89.000 (88.234) Prec@5 99.000 (99.221) +2022-11-14 17:03:45,002 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0828 (0.0747) Prec@1 87.000 (88.218) Prec@5 100.000 (99.231) +2022-11-14 17:03:45,009 Test: [78/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0747) Prec@1 88.000 (88.215) Prec@5 100.000 (99.241) +2022-11-14 17:03:45,017 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0846 (0.0748) Prec@1 86.000 (88.188) Prec@5 99.000 (99.237) +2022-11-14 17:03:45,025 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0860 (0.0749) Prec@1 86.000 (88.160) Prec@5 98.000 (99.222) +2022-11-14 17:03:45,033 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0845 (0.0751) Prec@1 87.000 (88.146) Prec@5 100.000 (99.232) +2022-11-14 17:03:45,040 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0750 (0.0751) Prec@1 88.000 (88.145) Prec@5 100.000 (99.241) +2022-11-14 17:03:45,048 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0750) Prec@1 88.000 (88.143) Prec@5 99.000 (99.238) +2022-11-14 17:03:45,055 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0823 (0.0751) Prec@1 87.000 (88.129) Prec@5 100.000 (99.247) +2022-11-14 17:03:45,063 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1121 (0.0755) Prec@1 83.000 (88.070) Prec@5 100.000 (99.256) +2022-11-14 17:03:45,071 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0757) Prec@1 84.000 (88.023) Prec@5 100.000 (99.264) +2022-11-14 17:03:45,079 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0900 (0.0759) Prec@1 85.000 (87.989) Prec@5 99.000 (99.261) +2022-11-14 17:03:45,086 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0757) Prec@1 90.000 (88.011) Prec@5 100.000 (99.270) +2022-11-14 17:03:45,094 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0659 (0.0756) Prec@1 88.000 (88.011) Prec@5 99.000 (99.267) +2022-11-14 17:03:45,102 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0584 (0.0754) Prec@1 91.000 (88.044) Prec@5 100.000 (99.275) +2022-11-14 17:03:45,109 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0660 (0.0753) Prec@1 92.000 (88.087) Prec@5 100.000 (99.283) +2022-11-14 17:03:45,117 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0754) Prec@1 87.000 (88.075) Prec@5 99.000 (99.280) +2022-11-14 17:03:45,125 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0754) Prec@1 90.000 (88.096) Prec@5 100.000 (99.287) +2022-11-14 17:03:45,132 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0754) Prec@1 87.000 (88.084) Prec@5 100.000 (99.295) +2022-11-14 17:03:45,140 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0753) Prec@1 90.000 (88.104) Prec@5 99.000 (99.292) +2022-11-14 17:03:45,147 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0609 (0.0752) Prec@1 90.000 (88.124) Prec@5 99.000 (99.289) +2022-11-14 17:03:45,154 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0938 (0.0754) Prec@1 85.000 (88.092) Prec@5 99.000 (99.286) +2022-11-14 17:03:45,162 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1084 (0.0757) Prec@1 86.000 (88.071) Prec@5 99.000 (99.283) +2022-11-14 17:03:45,169 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0674 (0.0756) Prec@1 89.000 (88.080) Prec@5 100.000 (99.290) +2022-11-14 17:03:45,223 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:03:45,528 Epoch: [452][0/500] Time 0.020 (0.020) Data 0.230 (0.230) Loss 0.0208 (0.0208) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:45,720 Epoch: [452][10/500] Time 0.016 (0.017) Data 0.002 (0.022) Loss 0.0227 (0.0218) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:45,906 Epoch: [452][20/500] Time 0.017 (0.017) Data 0.002 (0.012) Loss 0.0238 (0.0224) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:46,107 Epoch: [452][30/500] Time 0.024 (0.017) Data 0.002 (0.009) Loss 0.0275 (0.0237) Prec@1 95.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:03:46,297 Epoch: [452][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0328 (0.0255) Prec@1 93.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 17:03:46,483 Epoch: [452][50/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0324 (0.0267) Prec@1 95.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:03:46,680 Epoch: [452][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0309 (0.0273) Prec@1 93.000 (95.286) Prec@5 100.000 (100.000) +2022-11-14 17:03:46,885 Epoch: [452][70/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.0134 (0.0255) Prec@1 99.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:03:47,085 Epoch: [452][80/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0340 (0.0265) Prec@1 95.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:03:47,291 Epoch: [452][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0204 (0.0259) Prec@1 97.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 17:03:47,489 Epoch: [452][100/500] Time 0.016 (0.017) Data 0.003 (0.004) Loss 0.0122 (0.0246) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:47,685 Epoch: [452][110/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0173 (0.0240) Prec@1 98.000 (96.167) Prec@5 100.000 (100.000) +2022-11-14 17:03:47,890 Epoch: [452][120/500] Time 0.021 (0.017) Data 0.002 (0.004) Loss 0.0276 (0.0243) Prec@1 97.000 (96.231) Prec@5 100.000 (100.000) +2022-11-14 17:03:48,175 Epoch: [452][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0274 (0.0245) Prec@1 95.000 (96.143) Prec@5 100.000 (100.000) +2022-11-14 17:03:48,460 Epoch: [452][140/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0253 (0.0246) Prec@1 95.000 (96.067) Prec@5 100.000 (100.000) +2022-11-14 17:03:48,743 Epoch: [452][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0203 (0.0243) Prec@1 98.000 (96.188) Prec@5 100.000 (100.000) +2022-11-14 17:03:49,027 Epoch: [452][160/500] Time 0.027 (0.019) Data 0.001 (0.003) Loss 0.0215 (0.0241) Prec@1 97.000 (96.235) Prec@5 100.000 (100.000) +2022-11-14 17:03:49,309 Epoch: [452][170/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0422 (0.0251) Prec@1 91.000 (95.944) Prec@5 100.000 (100.000) +2022-11-14 17:03:49,594 Epoch: [452][180/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0129 (0.0245) Prec@1 98.000 (96.053) Prec@5 100.000 (100.000) +2022-11-14 17:03:49,880 Epoch: [452][190/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0313 (0.0248) Prec@1 97.000 (96.100) Prec@5 100.000 (100.000) +2022-11-14 17:03:50,168 Epoch: [452][200/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0187 (0.0245) Prec@1 98.000 (96.190) Prec@5 99.000 (99.952) +2022-11-14 17:03:50,445 Epoch: [452][210/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0218 (0.0244) Prec@1 96.000 (96.182) Prec@5 100.000 (99.955) +2022-11-14 17:03:50,728 Epoch: [452][220/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0183 (0.0241) Prec@1 96.000 (96.174) Prec@5 100.000 (99.957) +2022-11-14 17:03:51,014 Epoch: [452][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0343 (0.0246) Prec@1 94.000 (96.083) Prec@5 100.000 (99.958) +2022-11-14 17:03:51,294 Epoch: [452][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0322 (0.0249) Prec@1 94.000 (96.000) Prec@5 100.000 (99.960) +2022-11-14 17:03:51,578 Epoch: [452][250/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0222 (0.0248) Prec@1 95.000 (95.962) Prec@5 100.000 (99.962) +2022-11-14 17:03:51,861 Epoch: [452][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0368 (0.0252) Prec@1 93.000 (95.852) Prec@5 100.000 (99.963) +2022-11-14 17:03:52,143 Epoch: [452][270/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0319 (0.0255) Prec@1 93.000 (95.750) Prec@5 99.000 (99.929) +2022-11-14 17:03:52,423 Epoch: [452][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0290 (0.0256) Prec@1 96.000 (95.759) Prec@5 100.000 (99.931) +2022-11-14 17:03:52,706 Epoch: [452][290/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0298 (0.0257) Prec@1 95.000 (95.733) Prec@5 100.000 (99.933) +2022-11-14 17:03:52,989 Epoch: [452][300/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0224 (0.0256) Prec@1 96.000 (95.742) Prec@5 99.000 (99.903) +2022-11-14 17:03:53,277 Epoch: [452][310/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0138 (0.0252) Prec@1 99.000 (95.844) Prec@5 100.000 (99.906) +2022-11-14 17:03:53,560 Epoch: [452][320/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0225 (0.0252) Prec@1 96.000 (95.848) Prec@5 100.000 (99.909) +2022-11-14 17:03:53,844 Epoch: [452][330/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0330 (0.0254) Prec@1 96.000 (95.853) Prec@5 100.000 (99.912) +2022-11-14 17:03:54,132 Epoch: [452][340/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0254 (0.0254) Prec@1 96.000 (95.857) Prec@5 100.000 (99.914) +2022-11-14 17:03:54,412 Epoch: [452][350/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0287 (0.0255) Prec@1 95.000 (95.833) Prec@5 100.000 (99.917) +2022-11-14 17:03:54,695 Epoch: [452][360/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0405 (0.0259) Prec@1 92.000 (95.730) Prec@5 100.000 (99.919) +2022-11-14 17:03:54,978 Epoch: [452][370/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0259 (0.0259) Prec@1 95.000 (95.711) Prec@5 100.000 (99.921) +2022-11-14 17:03:55,260 Epoch: [452][380/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0381 (0.0262) Prec@1 94.000 (95.667) Prec@5 100.000 (99.923) +2022-11-14 17:03:55,538 Epoch: [452][390/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0212 (0.0261) Prec@1 97.000 (95.700) Prec@5 99.000 (99.900) +2022-11-14 17:03:55,820 Epoch: [452][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0334 (0.0263) Prec@1 95.000 (95.683) Prec@5 100.000 (99.902) +2022-11-14 17:03:56,108 Epoch: [452][410/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0432 (0.0267) Prec@1 94.000 (95.643) Prec@5 100.000 (99.905) +2022-11-14 17:03:56,387 Epoch: [452][420/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0211 (0.0265) Prec@1 97.000 (95.674) Prec@5 100.000 (99.907) +2022-11-14 17:03:56,669 Epoch: [452][430/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0316 (0.0266) Prec@1 95.000 (95.659) Prec@5 100.000 (99.909) +2022-11-14 17:03:56,953 Epoch: [452][440/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0299 (0.0267) Prec@1 96.000 (95.667) Prec@5 100.000 (99.911) +2022-11-14 17:03:57,232 Epoch: [452][450/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0374 (0.0270) Prec@1 93.000 (95.609) Prec@5 100.000 (99.913) +2022-11-14 17:03:57,511 Epoch: [452][460/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0329 (0.0271) Prec@1 93.000 (95.553) Prec@5 100.000 (99.915) +2022-11-14 17:03:57,793 Epoch: [452][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0297 (0.0271) Prec@1 96.000 (95.562) Prec@5 100.000 (99.917) +2022-11-14 17:03:58,075 Epoch: [452][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0337 (0.0273) Prec@1 96.000 (95.571) Prec@5 100.000 (99.918) +2022-11-14 17:03:58,358 Epoch: [452][490/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0165 (0.0270) Prec@1 98.000 (95.620) Prec@5 100.000 (99.920) +2022-11-14 17:03:58,611 Epoch: [452][499/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0445 (0.0274) Prec@1 93.000 (95.569) Prec@5 100.000 (99.922) +2022-11-14 17:03:58,926 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0653 (0.0653) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:03:58,936 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0752) Prec@1 87.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 17:03:58,946 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0916 (0.0807) Prec@1 85.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 17:03:58,955 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0843 (0.0816) Prec@1 86.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 17:03:58,962 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0790) Prec@1 90.000 (87.200) Prec@5 100.000 (99.600) +2022-11-14 17:03:58,969 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0512 (0.0744) Prec@1 93.000 (88.167) Prec@5 100.000 (99.667) +2022-11-14 17:03:58,977 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0703 (0.0738) Prec@1 88.000 (88.143) Prec@5 99.000 (99.571) +2022-11-14 17:03:58,985 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0741) Prec@1 87.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 17:03:58,992 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1065 (0.0777) Prec@1 84.000 (87.556) Prec@5 99.000 (99.444) +2022-11-14 17:03:58,999 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0774) Prec@1 88.000 (87.600) Prec@5 98.000 (99.300) +2022-11-14 17:03:59,007 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0454 (0.0745) Prec@1 93.000 (88.091) Prec@5 100.000 (99.364) +2022-11-14 17:03:59,014 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0746) Prec@1 88.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 17:03:59,022 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0724) Prec@1 92.000 (88.385) Prec@5 100.000 (99.462) +2022-11-14 17:03:59,030 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0732) Prec@1 87.000 (88.286) Prec@5 99.000 (99.429) +2022-11-14 17:03:59,037 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0745) Prec@1 84.000 (88.000) Prec@5 99.000 (99.400) +2022-11-14 17:03:59,045 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0741) Prec@1 89.000 (88.062) Prec@5 100.000 (99.438) +2022-11-14 17:03:59,052 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0440 (0.0723) Prec@1 95.000 (88.471) Prec@5 99.000 (99.412) +2022-11-14 17:03:59,060 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0736) Prec@1 86.000 (88.333) Prec@5 100.000 (99.444) +2022-11-14 17:03:59,068 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0743) Prec@1 83.000 (88.053) Prec@5 98.000 (99.368) +2022-11-14 17:03:59,076 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0755) Prec@1 87.000 (88.000) Prec@5 97.000 (99.250) +2022-11-14 17:03:59,084 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0755) Prec@1 88.000 (88.000) Prec@5 100.000 (99.286) +2022-11-14 17:03:59,092 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0770) Prec@1 85.000 (87.864) Prec@5 98.000 (99.227) +2022-11-14 17:03:59,100 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0779) Prec@1 86.000 (87.783) Prec@5 97.000 (99.130) +2022-11-14 17:03:59,107 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0775) Prec@1 90.000 (87.875) Prec@5 100.000 (99.167) +2022-11-14 17:03:59,115 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0786) Prec@1 84.000 (87.720) Prec@5 100.000 (99.200) +2022-11-14 17:03:59,123 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0788) Prec@1 85.000 (87.615) Prec@5 98.000 (99.154) +2022-11-14 17:03:59,130 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0782) Prec@1 90.000 (87.704) Prec@5 100.000 (99.185) +2022-11-14 17:03:59,138 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0425 (0.0770) Prec@1 95.000 (87.964) Prec@5 100.000 (99.214) +2022-11-14 17:03:59,145 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0771) Prec@1 87.000 (87.931) Prec@5 98.000 (99.172) +2022-11-14 17:03:59,153 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0768) Prec@1 90.000 (88.000) Prec@5 98.000 (99.133) +2022-11-14 17:03:59,160 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0768) Prec@1 88.000 (88.000) Prec@5 100.000 (99.161) +2022-11-14 17:03:59,168 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0767) Prec@1 90.000 (88.062) Prec@5 100.000 (99.188) +2022-11-14 17:03:59,176 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0766) Prec@1 90.000 (88.121) Prec@5 100.000 (99.212) +2022-11-14 17:03:59,183 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0775) Prec@1 82.000 (87.941) Prec@5 100.000 (99.235) +2022-11-14 17:03:59,191 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0780) Prec@1 87.000 (87.914) Prec@5 97.000 (99.171) +2022-11-14 17:03:59,199 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0774) Prec@1 92.000 (88.028) Prec@5 99.000 (99.167) +2022-11-14 17:03:59,206 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0769) Prec@1 91.000 (88.108) Prec@5 99.000 (99.162) +2022-11-14 17:03:59,214 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0773) Prec@1 84.000 (88.000) Prec@5 100.000 (99.184) +2022-11-14 17:03:59,221 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0767) Prec@1 92.000 (88.103) Prec@5 99.000 (99.179) +2022-11-14 17:03:59,229 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0767) Prec@1 89.000 (88.125) Prec@5 100.000 (99.200) +2022-11-14 17:03:59,236 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0771) Prec@1 86.000 (88.073) Prec@5 98.000 (99.171) +2022-11-14 17:03:59,245 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0768) Prec@1 90.000 (88.119) Prec@5 99.000 (99.167) +2022-11-14 17:03:59,253 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0763) Prec@1 93.000 (88.233) Prec@5 99.000 (99.163) +2022-11-14 17:03:59,260 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0762) Prec@1 90.000 (88.273) Prec@5 98.000 (99.136) +2022-11-14 17:03:59,268 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0759) Prec@1 89.000 (88.289) Prec@5 99.000 (99.133) +2022-11-14 17:03:59,276 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0765) Prec@1 83.000 (88.174) Prec@5 99.000 (99.130) +2022-11-14 17:03:59,283 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0765) Prec@1 90.000 (88.213) Prec@5 97.000 (99.085) +2022-11-14 17:03:59,291 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0768) Prec@1 86.000 (88.167) Prec@5 99.000 (99.083) +2022-11-14 17:03:59,299 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0764) Prec@1 92.000 (88.245) Prec@5 99.000 (99.082) +2022-11-14 17:03:59,306 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1190 (0.0772) Prec@1 85.000 (88.180) Prec@5 99.000 (99.080) +2022-11-14 17:03:59,314 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0770) Prec@1 90.000 (88.216) Prec@5 100.000 (99.098) +2022-11-14 17:03:59,321 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0770) Prec@1 88.000 (88.212) Prec@5 99.000 (99.096) +2022-11-14 17:03:59,329 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0767) Prec@1 90.000 (88.245) Prec@5 99.000 (99.094) +2022-11-14 17:03:59,337 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0763) Prec@1 93.000 (88.333) Prec@5 100.000 (99.111) +2022-11-14 17:03:59,344 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0765) Prec@1 86.000 (88.291) Prec@5 100.000 (99.127) +2022-11-14 17:03:59,352 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0763) Prec@1 89.000 (88.304) Prec@5 99.000 (99.125) +2022-11-14 17:03:59,360 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0763) Prec@1 86.000 (88.263) Prec@5 99.000 (99.123) +2022-11-14 17:03:59,367 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0761) Prec@1 92.000 (88.328) Prec@5 99.000 (99.121) +2022-11-14 17:03:59,375 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1094 (0.0766) Prec@1 85.000 (88.271) Prec@5 100.000 (99.136) +2022-11-14 17:03:59,382 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0767) Prec@1 85.000 (88.217) Prec@5 98.000 (99.117) +2022-11-14 17:03:59,390 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0768) Prec@1 86.000 (88.180) Prec@5 100.000 (99.131) +2022-11-14 17:03:59,398 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0765) Prec@1 92.000 (88.242) Prec@5 100.000 (99.145) +2022-11-14 17:03:59,405 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0764) Prec@1 90.000 (88.270) Prec@5 100.000 (99.159) +2022-11-14 17:03:59,413 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0362 (0.0757) Prec@1 93.000 (88.344) Prec@5 99.000 (99.156) +2022-11-14 17:03:59,421 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0761) Prec@1 82.000 (88.246) Prec@5 98.000 (99.138) +2022-11-14 17:03:59,428 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0761) Prec@1 87.000 (88.227) Prec@5 98.000 (99.121) +2022-11-14 17:03:59,436 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0758) Prec@1 91.000 (88.269) Prec@5 100.000 (99.134) +2022-11-14 17:03:59,443 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0757) Prec@1 90.000 (88.294) Prec@5 99.000 (99.132) +2022-11-14 17:03:59,451 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0754) Prec@1 93.000 (88.362) Prec@5 99.000 (99.130) +2022-11-14 17:03:59,459 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0756) Prec@1 88.000 (88.357) Prec@5 99.000 (99.129) +2022-11-14 17:03:59,466 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.0760) Prec@1 85.000 (88.310) Prec@5 98.000 (99.113) +2022-11-14 17:03:59,474 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0758) Prec@1 90.000 (88.333) Prec@5 99.000 (99.111) +2022-11-14 17:03:59,482 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0754) Prec@1 91.000 (88.370) Prec@5 100.000 (99.123) +2022-11-14 17:03:59,489 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0749) Prec@1 92.000 (88.419) Prec@5 99.000 (99.122) +2022-11-14 17:03:59,497 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0752) Prec@1 85.000 (88.373) Prec@5 100.000 (99.133) +2022-11-14 17:03:59,504 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0751) Prec@1 89.000 (88.382) Prec@5 99.000 (99.132) +2022-11-14 17:03:59,512 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0753) Prec@1 86.000 (88.351) Prec@5 100.000 (99.143) +2022-11-14 17:03:59,519 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.0756) Prec@1 84.000 (88.295) Prec@5 98.000 (99.128) +2022-11-14 17:03:59,527 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0754) Prec@1 92.000 (88.342) Prec@5 100.000 (99.139) +2022-11-14 17:03:59,535 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0752) Prec@1 89.000 (88.350) Prec@5 100.000 (99.150) +2022-11-14 17:03:59,542 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0754) Prec@1 87.000 (88.333) Prec@5 99.000 (99.148) +2022-11-14 17:03:59,550 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0755) Prec@1 88.000 (88.329) Prec@5 100.000 (99.159) +2022-11-14 17:03:59,558 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0756) Prec@1 85.000 (88.289) Prec@5 99.000 (99.157) +2022-11-14 17:03:59,565 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0754) Prec@1 92.000 (88.333) Prec@5 98.000 (99.143) +2022-11-14 17:03:59,573 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0756) Prec@1 85.000 (88.294) Prec@5 100.000 (99.153) +2022-11-14 17:03:59,581 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1194 (0.0761) Prec@1 79.000 (88.186) Prec@5 100.000 (99.163) +2022-11-14 17:03:59,588 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0760) Prec@1 89.000 (88.195) Prec@5 100.000 (99.172) +2022-11-14 17:03:59,596 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0762) Prec@1 85.000 (88.159) Prec@5 99.000 (99.170) +2022-11-14 17:03:59,604 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0761) Prec@1 89.000 (88.169) Prec@5 100.000 (99.180) +2022-11-14 17:03:59,612 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0761) Prec@1 89.000 (88.178) Prec@5 99.000 (99.178) +2022-11-14 17:03:59,620 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0758) Prec@1 93.000 (88.231) Prec@5 100.000 (99.187) +2022-11-14 17:03:59,627 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0756) Prec@1 91.000 (88.261) Prec@5 100.000 (99.196) +2022-11-14 17:03:59,635 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0757) Prec@1 85.000 (88.226) Prec@5 99.000 (99.194) +2022-11-14 17:03:59,643 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0758) Prec@1 88.000 (88.223) Prec@5 100.000 (99.202) +2022-11-14 17:03:59,650 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0761) Prec@1 85.000 (88.189) Prec@5 100.000 (99.211) +2022-11-14 17:03:59,658 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0760) Prec@1 91.000 (88.219) Prec@5 100.000 (99.219) +2022-11-14 17:03:59,665 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0757) Prec@1 92.000 (88.258) Prec@5 98.000 (99.206) +2022-11-14 17:03:59,673 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0759) Prec@1 84.000 (88.214) Prec@5 100.000 (99.214) +2022-11-14 17:03:59,680 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.0762) Prec@1 85.000 (88.182) Prec@5 98.000 (99.202) +2022-11-14 17:03:59,688 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0761) Prec@1 91.000 (88.210) Prec@5 99.000 (99.200) +2022-11-14 17:03:59,741 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:04:00,069 Epoch: [453][0/500] Time 0.023 (0.023) Data 0.251 (0.251) Loss 0.0272 (0.0272) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:00,268 Epoch: [453][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0471 (0.0371) Prec@1 92.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:00,458 Epoch: [453][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0421 (0.0388) Prec@1 93.000 (93.667) Prec@5 100.000 (100.000) +2022-11-14 17:04:00,646 Epoch: [453][30/500] Time 0.016 (0.017) Data 0.002 (0.010) Loss 0.0168 (0.0333) Prec@1 98.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:04:00,837 Epoch: [453][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0160 (0.0298) Prec@1 98.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,029 Epoch: [453][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0087 (0.0263) Prec@1 99.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,224 Epoch: [453][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0453 (0.0290) Prec@1 93.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,415 Epoch: [453][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0279 (0.0289) Prec@1 94.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,607 Epoch: [453][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0185 (0.0277) Prec@1 97.000 (95.556) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,797 Epoch: [453][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0295 (0.0279) Prec@1 95.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:04:01,986 Epoch: [453][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0309 (0.0282) Prec@1 95.000 (95.455) Prec@5 100.000 (100.000) +2022-11-14 17:04:02,177 Epoch: [453][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0190 (0.0274) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:04:02,365 Epoch: [453][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0147 (0.0264) Prec@1 98.000 (95.692) Prec@5 100.000 (100.000) +2022-11-14 17:04:02,553 Epoch: [453][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0263 (0.0264) Prec@1 97.000 (95.786) Prec@5 100.000 (100.000) +2022-11-14 17:04:02,741 Epoch: [453][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0249 (0.0263) Prec@1 97.000 (95.867) Prec@5 99.000 (99.933) +2022-11-14 17:04:02,930 Epoch: [453][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0316 (0.0267) Prec@1 96.000 (95.875) Prec@5 99.000 (99.875) +2022-11-14 17:04:03,125 Epoch: [453][160/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0337 (0.0271) Prec@1 95.000 (95.824) Prec@5 100.000 (99.882) +2022-11-14 17:04:03,314 Epoch: [453][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0317 (0.0273) Prec@1 95.000 (95.778) Prec@5 100.000 (99.889) +2022-11-14 17:04:03,506 Epoch: [453][180/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0187 (0.0269) Prec@1 97.000 (95.842) Prec@5 100.000 (99.895) +2022-11-14 17:04:03,709 Epoch: [453][190/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0208 (0.0266) Prec@1 96.000 (95.850) Prec@5 100.000 (99.900) +2022-11-14 17:04:03,926 Epoch: [453][200/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0199 (0.0263) Prec@1 97.000 (95.905) Prec@5 99.000 (99.857) +2022-11-14 17:04:04,192 Epoch: [453][210/500] Time 0.024 (0.017) Data 0.001 (0.003) Loss 0.0439 (0.0271) Prec@1 92.000 (95.727) Prec@5 100.000 (99.864) +2022-11-14 17:04:04,461 Epoch: [453][220/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0116 (0.0264) Prec@1 99.000 (95.870) Prec@5 100.000 (99.870) +2022-11-14 17:04:04,734 Epoch: [453][230/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0120 (0.0258) Prec@1 99.000 (96.000) Prec@5 100.000 (99.875) +2022-11-14 17:04:05,009 Epoch: [453][240/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0419 (0.0264) Prec@1 92.000 (95.840) Prec@5 100.000 (99.880) +2022-11-14 17:04:05,283 Epoch: [453][250/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0314 (0.0266) Prec@1 96.000 (95.846) Prec@5 100.000 (99.885) +2022-11-14 17:04:05,557 Epoch: [453][260/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0421 (0.0272) Prec@1 92.000 (95.704) Prec@5 100.000 (99.889) +2022-11-14 17:04:05,828 Epoch: [453][270/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0420 (0.0277) Prec@1 92.000 (95.571) Prec@5 100.000 (99.893) +2022-11-14 17:04:06,109 Epoch: [453][280/500] Time 0.027 (0.019) Data 0.001 (0.002) Loss 0.0122 (0.0272) Prec@1 98.000 (95.655) Prec@5 100.000 (99.897) +2022-11-14 17:04:06,381 Epoch: [453][290/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0139 (0.0267) Prec@1 99.000 (95.767) Prec@5 100.000 (99.900) +2022-11-14 17:04:06,652 Epoch: [453][300/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0316 (0.0269) Prec@1 94.000 (95.710) Prec@5 99.000 (99.871) +2022-11-14 17:04:06,928 Epoch: [453][310/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0051 (0.0262) Prec@1 100.000 (95.844) Prec@5 100.000 (99.875) +2022-11-14 17:04:07,195 Epoch: [453][320/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0370 (0.0265) Prec@1 91.000 (95.697) Prec@5 100.000 (99.879) +2022-11-14 17:04:07,460 Epoch: [453][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0624 (0.0276) Prec@1 91.000 (95.559) Prec@5 100.000 (99.882) +2022-11-14 17:04:07,728 Epoch: [453][340/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0173 (0.0273) Prec@1 97.000 (95.600) Prec@5 100.000 (99.886) +2022-11-14 17:04:07,995 Epoch: [453][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0231 (0.0272) Prec@1 96.000 (95.611) Prec@5 100.000 (99.889) +2022-11-14 17:04:08,263 Epoch: [453][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0386 (0.0275) Prec@1 95.000 (95.595) Prec@5 100.000 (99.892) +2022-11-14 17:04:08,531 Epoch: [453][370/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0462 (0.0280) Prec@1 92.000 (95.500) Prec@5 100.000 (99.895) +2022-11-14 17:04:08,798 Epoch: [453][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0558 (0.0287) Prec@1 92.000 (95.410) Prec@5 100.000 (99.897) +2022-11-14 17:04:09,063 Epoch: [453][390/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0448 (0.0291) Prec@1 91.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 17:04:09,330 Epoch: [453][400/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0255 (0.0290) Prec@1 97.000 (95.341) Prec@5 98.000 (99.854) +2022-11-14 17:04:09,592 Epoch: [453][410/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0216 (0.0288) Prec@1 96.000 (95.357) Prec@5 100.000 (99.857) +2022-11-14 17:04:09,857 Epoch: [453][420/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0261 (0.0288) Prec@1 95.000 (95.349) Prec@5 99.000 (99.837) +2022-11-14 17:04:10,123 Epoch: [453][430/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0222 (0.0286) Prec@1 96.000 (95.364) Prec@5 100.000 (99.841) +2022-11-14 17:04:10,384 Epoch: [453][440/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0392 (0.0289) Prec@1 92.000 (95.289) Prec@5 100.000 (99.844) +2022-11-14 17:04:10,649 Epoch: [453][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0354 (0.0290) Prec@1 93.000 (95.239) Prec@5 99.000 (99.826) +2022-11-14 17:04:10,917 Epoch: [453][460/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0195 (0.0288) Prec@1 97.000 (95.277) Prec@5 100.000 (99.830) +2022-11-14 17:04:11,183 Epoch: [453][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0411 (0.0291) Prec@1 93.000 (95.229) Prec@5 100.000 (99.833) +2022-11-14 17:04:11,444 Epoch: [453][480/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0136 (0.0287) Prec@1 99.000 (95.306) Prec@5 100.000 (99.837) +2022-11-14 17:04:11,709 Epoch: [453][490/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0247 (0.0287) Prec@1 96.000 (95.320) Prec@5 100.000 (99.840) +2022-11-14 17:04:11,949 Epoch: [453][499/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0241 (0.0286) Prec@1 95.000 (95.314) Prec@5 100.000 (99.843) +2022-11-14 17:04:12,243 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0766 (0.0766) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:12,252 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0607 (0.0686) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:12,261 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0619 (0.0664) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:12,272 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0811 (0.0701) Prec@1 86.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 17:04:12,279 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0719) Prec@1 87.000 (88.000) Prec@5 100.000 (99.800) +2022-11-14 17:04:12,286 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0349 (0.0657) Prec@1 94.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 17:04:12,292 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0756 (0.0671) Prec@1 88.000 (88.857) Prec@5 98.000 (99.571) +2022-11-14 17:04:12,301 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0678) Prec@1 88.000 (88.750) Prec@5 99.000 (99.500) +2022-11-14 17:04:12,308 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0692) Prec@1 89.000 (88.778) Prec@5 100.000 (99.556) +2022-11-14 17:04:12,314 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0696) Prec@1 86.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 17:04:12,322 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0686) Prec@1 92.000 (88.818) Prec@5 99.000 (99.455) +2022-11-14 17:04:12,330 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0707) Prec@1 86.000 (88.583) Prec@5 100.000 (99.500) +2022-11-14 17:04:12,337 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0694) Prec@1 90.000 (88.692) Prec@5 100.000 (99.538) +2022-11-14 17:04:12,345 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0700) Prec@1 88.000 (88.643) Prec@5 98.000 (99.429) +2022-11-14 17:04:12,352 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0705) Prec@1 88.000 (88.600) Prec@5 100.000 (99.467) +2022-11-14 17:04:12,360 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0699) Prec@1 90.000 (88.688) Prec@5 99.000 (99.438) +2022-11-14 17:04:12,367 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0455 (0.0685) Prec@1 94.000 (89.000) Prec@5 99.000 (99.412) +2022-11-14 17:04:12,375 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0699) Prec@1 85.000 (88.778) Prec@5 99.000 (99.389) +2022-11-14 17:04:12,382 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0691) Prec@1 92.000 (88.947) Prec@5 99.000 (99.368) +2022-11-14 17:04:12,390 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0693) Prec@1 88.000 (88.900) Prec@5 98.000 (99.300) +2022-11-14 17:04:12,397 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0690) Prec@1 91.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 17:04:12,405 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0932 (0.0701) Prec@1 84.000 (88.773) Prec@5 99.000 (99.318) +2022-11-14 17:04:12,412 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1046 (0.0716) Prec@1 84.000 (88.565) Prec@5 97.000 (99.217) +2022-11-14 17:04:12,420 Test: [23/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0826 (0.0720) Prec@1 88.000 (88.542) Prec@5 100.000 (99.250) +2022-11-14 17:04:12,427 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0915 (0.0728) Prec@1 85.000 (88.400) Prec@5 100.000 (99.280) +2022-11-14 17:04:12,434 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0859 (0.0733) Prec@1 86.000 (88.308) Prec@5 98.000 (99.231) +2022-11-14 17:04:12,442 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0516 (0.0725) Prec@1 91.000 (88.407) Prec@5 100.000 (99.259) +2022-11-14 17:04:12,449 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0681 (0.0724) Prec@1 89.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 17:04:12,457 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0603 (0.0719) Prec@1 92.000 (88.552) Prec@5 99.000 (99.276) +2022-11-14 17:04:12,465 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0556 (0.0714) Prec@1 93.000 (88.700) Prec@5 99.000 (99.267) +2022-11-14 17:04:12,472 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0610 (0.0711) Prec@1 91.000 (88.774) Prec@5 100.000 (99.290) +2022-11-14 17:04:12,480 Test: [31/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0580 (0.0707) Prec@1 91.000 (88.844) Prec@5 100.000 (99.312) +2022-11-14 17:04:12,487 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0499 (0.0700) Prec@1 92.000 (88.939) Prec@5 100.000 (99.333) +2022-11-14 17:04:12,495 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0674 (0.0699) Prec@1 88.000 (88.912) Prec@5 100.000 (99.353) +2022-11-14 17:04:12,502 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0926 (0.0706) Prec@1 86.000 (88.829) Prec@5 98.000 (99.314) +2022-11-14 17:04:12,510 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0705) Prec@1 90.000 (88.861) Prec@5 100.000 (99.333) +2022-11-14 17:04:12,518 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0706) Prec@1 88.000 (88.838) Prec@5 99.000 (99.324) +2022-11-14 17:04:12,525 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0986 (0.0713) Prec@1 82.000 (88.658) Prec@5 98.000 (99.289) +2022-11-14 17:04:12,533 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0519 (0.0708) Prec@1 92.000 (88.744) Prec@5 99.000 (99.282) +2022-11-14 17:04:12,540 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0578 (0.0705) Prec@1 89.000 (88.750) Prec@5 99.000 (99.275) +2022-11-14 17:04:12,548 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0992 (0.0712) Prec@1 85.000 (88.659) Prec@5 98.000 (99.244) +2022-11-14 17:04:12,555 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0714) Prec@1 88.000 (88.643) Prec@5 99.000 (99.238) +2022-11-14 17:04:12,563 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0464 (0.0708) Prec@1 93.000 (88.744) Prec@5 100.000 (99.256) +2022-11-14 17:04:12,570 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0700 (0.0708) Prec@1 90.000 (88.773) Prec@5 99.000 (99.250) +2022-11-14 17:04:12,578 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0769 (0.0710) Prec@1 87.000 (88.733) Prec@5 99.000 (99.244) +2022-11-14 17:04:12,585 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1098 (0.0718) Prec@1 82.000 (88.587) Prec@5 100.000 (99.261) +2022-11-14 17:04:12,593 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0679 (0.0717) Prec@1 88.000 (88.574) Prec@5 99.000 (99.255) +2022-11-14 17:04:12,600 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1184 (0.0727) Prec@1 82.000 (88.438) Prec@5 97.000 (99.208) +2022-11-14 17:04:12,608 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0600 (0.0724) Prec@1 90.000 (88.469) Prec@5 100.000 (99.224) +2022-11-14 17:04:12,615 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0729) Prec@1 86.000 (88.420) Prec@5 100.000 (99.240) +2022-11-14 17:04:12,623 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0727) Prec@1 88.000 (88.412) Prec@5 100.000 (99.255) +2022-11-14 17:04:12,630 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0815 (0.0729) Prec@1 88.000 (88.404) Prec@5 99.000 (99.250) +2022-11-14 17:04:12,637 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0775 (0.0730) Prec@1 86.000 (88.358) Prec@5 99.000 (99.245) +2022-11-14 17:04:12,645 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0818 (0.0731) Prec@1 88.000 (88.352) Prec@5 99.000 (99.241) +2022-11-14 17:04:12,653 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0731) Prec@1 88.000 (88.345) Prec@5 100.000 (99.255) +2022-11-14 17:04:12,660 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0731) Prec@1 90.000 (88.375) Prec@5 99.000 (99.250) +2022-11-14 17:04:12,668 Test: [56/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0730) Prec@1 88.000 (88.368) Prec@5 99.000 (99.246) +2022-11-14 17:04:12,675 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0731) Prec@1 88.000 (88.362) Prec@5 99.000 (99.241) +2022-11-14 17:04:12,683 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1191 (0.0739) Prec@1 83.000 (88.271) Prec@5 100.000 (99.254) +2022-11-14 17:04:12,690 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0885 (0.0741) Prec@1 86.000 (88.233) Prec@5 100.000 (99.267) +2022-11-14 17:04:12,697 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0846 (0.0743) Prec@1 89.000 (88.246) Prec@5 100.000 (99.279) +2022-11-14 17:04:12,705 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0771 (0.0743) Prec@1 87.000 (88.226) Prec@5 99.000 (99.274) +2022-11-14 17:04:12,712 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0743) Prec@1 87.000 (88.206) Prec@5 100.000 (99.286) +2022-11-14 17:04:12,720 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0438 (0.0738) Prec@1 92.000 (88.266) Prec@5 100.000 (99.297) +2022-11-14 17:04:12,727 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0878 (0.0741) Prec@1 86.000 (88.231) Prec@5 100.000 (99.308) +2022-11-14 17:04:12,736 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0741) Prec@1 86.000 (88.197) Prec@5 99.000 (99.303) +2022-11-14 17:04:12,743 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0547 (0.0738) Prec@1 91.000 (88.239) Prec@5 99.000 (99.299) +2022-11-14 17:04:12,750 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0711 (0.0737) Prec@1 88.000 (88.235) Prec@5 100.000 (99.309) +2022-11-14 17:04:12,758 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0608 (0.0736) Prec@1 93.000 (88.304) Prec@5 99.000 (99.304) +2022-11-14 17:04:12,766 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0897 (0.0738) Prec@1 88.000 (88.300) Prec@5 98.000 (99.286) +2022-11-14 17:04:12,773 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1071 (0.0743) Prec@1 84.000 (88.239) Prec@5 99.000 (99.282) +2022-11-14 17:04:12,781 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0741) Prec@1 92.000 (88.292) Prec@5 100.000 (99.292) +2022-11-14 17:04:12,788 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0462 (0.0737) Prec@1 94.000 (88.370) Prec@5 100.000 (99.301) +2022-11-14 17:04:12,795 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0395 (0.0732) Prec@1 95.000 (88.459) Prec@5 99.000 (99.297) +2022-11-14 17:04:12,803 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0903 (0.0735) Prec@1 85.000 (88.413) Prec@5 100.000 (99.307) +2022-11-14 17:04:12,810 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0734) Prec@1 90.000 (88.434) Prec@5 99.000 (99.303) +2022-11-14 17:04:12,818 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0733) Prec@1 90.000 (88.455) Prec@5 100.000 (99.312) +2022-11-14 17:04:12,825 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0837 (0.0734) Prec@1 88.000 (88.449) Prec@5 97.000 (99.282) +2022-11-14 17:04:12,833 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0734) Prec@1 89.000 (88.456) Prec@5 100.000 (99.291) +2022-11-14 17:04:12,840 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0683 (0.0733) Prec@1 87.000 (88.438) Prec@5 100.000 (99.300) +2022-11-14 17:04:12,848 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0829 (0.0734) Prec@1 87.000 (88.420) Prec@5 99.000 (99.296) +2022-11-14 17:04:12,855 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0736) Prec@1 86.000 (88.390) Prec@5 99.000 (99.293) +2022-11-14 17:04:12,863 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0990 (0.0739) Prec@1 84.000 (88.337) Prec@5 99.000 (99.289) +2022-11-14 17:04:12,870 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0738) Prec@1 88.000 (88.333) Prec@5 100.000 (99.298) +2022-11-14 17:04:12,878 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1004 (0.0741) Prec@1 83.000 (88.271) Prec@5 99.000 (99.294) +2022-11-14 17:04:12,885 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0959 (0.0744) Prec@1 87.000 (88.256) Prec@5 100.000 (99.302) +2022-11-14 17:04:12,892 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0935 (0.0746) Prec@1 86.000 (88.230) Prec@5 100.000 (99.310) +2022-11-14 17:04:12,900 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0745) Prec@1 90.000 (88.250) Prec@5 99.000 (99.307) +2022-11-14 17:04:12,907 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0745) Prec@1 87.000 (88.236) Prec@5 100.000 (99.315) +2022-11-14 17:04:12,915 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0745) Prec@1 90.000 (88.256) Prec@5 99.000 (99.311) +2022-11-14 17:04:12,922 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0510 (0.0743) Prec@1 93.000 (88.308) Prec@5 100.000 (99.319) +2022-11-14 17:04:12,929 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0741) Prec@1 91.000 (88.337) Prec@5 99.000 (99.315) +2022-11-14 17:04:12,937 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0753 (0.0741) Prec@1 88.000 (88.333) Prec@5 100.000 (99.323) +2022-11-14 17:04:12,944 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0592 (0.0740) Prec@1 93.000 (88.383) Prec@5 99.000 (99.319) +2022-11-14 17:04:12,951 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0739) Prec@1 89.000 (88.389) Prec@5 99.000 (99.316) +2022-11-14 17:04:12,958 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0682 (0.0739) Prec@1 88.000 (88.385) Prec@5 99.000 (99.312) +2022-11-14 17:04:12,966 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0738) Prec@1 90.000 (88.402) Prec@5 99.000 (99.309) +2022-11-14 17:04:12,973 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1020 (0.0740) Prec@1 86.000 (88.378) Prec@5 100.000 (99.316) +2022-11-14 17:04:12,980 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1014 (0.0743) Prec@1 83.000 (88.323) Prec@5 99.000 (99.313) +2022-11-14 17:04:12,987 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0659 (0.0742) Prec@1 89.000 (88.330) Prec@5 100.000 (99.320) +2022-11-14 17:04:13,040 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:04:13,348 Epoch: [454][0/500] Time 0.021 (0.021) Data 0.232 (0.232) Loss 0.0291 (0.0291) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:13,548 Epoch: [454][10/500] Time 0.018 (0.018) Data 0.001 (0.023) Loss 0.0176 (0.0234) Prec@1 98.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:13,738 Epoch: [454][20/500] Time 0.018 (0.017) Data 0.001 (0.013) Loss 0.0242 (0.0236) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:13,931 Epoch: [454][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0194 (0.0226) Prec@1 95.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:04:14,126 Epoch: [454][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0286 (0.0238) Prec@1 95.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 17:04:14,320 Epoch: [454][50/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0165 (0.0226) Prec@1 99.000 (96.167) Prec@5 100.000 (100.000) +2022-11-14 17:04:14,517 Epoch: [454][60/500] Time 0.020 (0.017) Data 0.001 (0.005) Loss 0.0305 (0.0237) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:14,712 Epoch: [454][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0220 (0.0235) Prec@1 97.000 (96.125) Prec@5 100.000 (100.000) +2022-11-14 17:04:14,906 Epoch: [454][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0258 (0.0237) Prec@1 96.000 (96.111) Prec@5 100.000 (100.000) +2022-11-14 17:04:15,102 Epoch: [454][90/500] Time 0.019 (0.017) Data 0.002 (0.004) Loss 0.0225 (0.0236) Prec@1 97.000 (96.200) Prec@5 100.000 (100.000) +2022-11-14 17:04:15,292 Epoch: [454][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0280 (0.0240) Prec@1 97.000 (96.273) Prec@5 99.000 (99.909) +2022-11-14 17:04:15,482 Epoch: [454][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0145 (0.0232) Prec@1 98.000 (96.417) Prec@5 100.000 (99.917) +2022-11-14 17:04:15,672 Epoch: [454][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0481 (0.0251) Prec@1 91.000 (96.000) Prec@5 100.000 (99.923) +2022-11-14 17:04:15,862 Epoch: [454][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0641 (0.0279) Prec@1 88.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 17:04:16,052 Epoch: [454][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0360 (0.0285) Prec@1 94.000 (95.333) Prec@5 100.000 (99.933) +2022-11-14 17:04:16,309 Epoch: [454][150/500] Time 0.028 (0.017) Data 0.002 (0.003) Loss 0.0816 (0.0318) Prec@1 87.000 (94.812) Prec@5 99.000 (99.875) +2022-11-14 17:04:16,615 Epoch: [454][160/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0183 (0.0310) Prec@1 95.000 (94.824) Prec@5 100.000 (99.882) +2022-11-14 17:04:16,922 Epoch: [454][170/500] Time 0.029 (0.018) Data 0.002 (0.003) Loss 0.0293 (0.0309) Prec@1 94.000 (94.778) Prec@5 100.000 (99.889) +2022-11-14 17:04:17,225 Epoch: [454][180/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0275 (0.0307) Prec@1 94.000 (94.737) Prec@5 99.000 (99.842) +2022-11-14 17:04:17,531 Epoch: [454][190/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0374 (0.0311) Prec@1 93.000 (94.650) Prec@5 100.000 (99.850) +2022-11-14 17:04:17,837 Epoch: [454][200/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0184 (0.0304) Prec@1 97.000 (94.762) Prec@5 100.000 (99.857) +2022-11-14 17:04:18,149 Epoch: [454][210/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0157 (0.0298) Prec@1 98.000 (94.909) Prec@5 100.000 (99.864) +2022-11-14 17:04:18,452 Epoch: [454][220/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0120 (0.0290) Prec@1 97.000 (95.000) Prec@5 100.000 (99.870) +2022-11-14 17:04:18,758 Epoch: [454][230/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0312 (0.0291) Prec@1 94.000 (94.958) Prec@5 100.000 (99.875) +2022-11-14 17:04:19,063 Epoch: [454][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0245 (0.0289) Prec@1 96.000 (95.000) Prec@5 100.000 (99.880) +2022-11-14 17:04:19,371 Epoch: [454][250/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0292 (0.0289) Prec@1 95.000 (95.000) Prec@5 100.000 (99.885) +2022-11-14 17:04:19,678 Epoch: [454][260/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0409 (0.0294) Prec@1 94.000 (94.963) Prec@5 100.000 (99.889) +2022-11-14 17:04:19,983 Epoch: [454][270/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0222 (0.0291) Prec@1 96.000 (95.000) Prec@5 100.000 (99.893) +2022-11-14 17:04:20,285 Epoch: [454][280/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0449 (0.0297) Prec@1 92.000 (94.897) Prec@5 99.000 (99.862) +2022-11-14 17:04:20,585 Epoch: [454][290/500] Time 0.029 (0.022) Data 0.001 (0.002) Loss 0.0454 (0.0302) Prec@1 93.000 (94.833) Prec@5 100.000 (99.867) +2022-11-14 17:04:20,884 Epoch: [454][300/500] Time 0.031 (0.022) Data 0.002 (0.002) Loss 0.0241 (0.0300) Prec@1 95.000 (94.839) Prec@5 99.000 (99.839) +2022-11-14 17:04:21,187 Epoch: [454][310/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0238 (0.0298) Prec@1 94.000 (94.812) Prec@5 100.000 (99.844) +2022-11-14 17:04:21,491 Epoch: [454][320/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0161 (0.0294) Prec@1 98.000 (94.909) Prec@5 100.000 (99.848) +2022-11-14 17:04:21,796 Epoch: [454][330/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0353 (0.0295) Prec@1 93.000 (94.853) Prec@5 100.000 (99.853) +2022-11-14 17:04:22,106 Epoch: [454][340/500] Time 0.031 (0.023) Data 0.001 (0.002) Loss 0.0259 (0.0294) Prec@1 96.000 (94.886) Prec@5 100.000 (99.857) +2022-11-14 17:04:22,404 Epoch: [454][350/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0171 (0.0291) Prec@1 98.000 (94.972) Prec@5 100.000 (99.861) +2022-11-14 17:04:22,703 Epoch: [454][360/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0219 (0.0289) Prec@1 97.000 (95.027) Prec@5 100.000 (99.865) +2022-11-14 17:04:23,003 Epoch: [454][370/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0354 (0.0291) Prec@1 93.000 (94.974) Prec@5 100.000 (99.868) +2022-11-14 17:04:23,310 Epoch: [454][380/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0368 (0.0293) Prec@1 93.000 (94.923) Prec@5 100.000 (99.872) +2022-11-14 17:04:23,611 Epoch: [454][390/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0255 (0.0292) Prec@1 96.000 (94.950) Prec@5 100.000 (99.875) +2022-11-14 17:04:23,906 Epoch: [454][400/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0247 (0.0291) Prec@1 97.000 (95.000) Prec@5 100.000 (99.878) +2022-11-14 17:04:24,125 Epoch: [454][410/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0292 (0.0291) Prec@1 95.000 (95.000) Prec@5 100.000 (99.881) +2022-11-14 17:04:24,327 Epoch: [454][420/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0489 (0.0295) Prec@1 92.000 (94.930) Prec@5 100.000 (99.884) +2022-11-14 17:04:24,531 Epoch: [454][430/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0123 (0.0291) Prec@1 97.000 (94.977) Prec@5 100.000 (99.886) +2022-11-14 17:04:24,732 Epoch: [454][440/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0297 (0.0292) Prec@1 94.000 (94.956) Prec@5 100.000 (99.889) +2022-11-14 17:04:24,932 Epoch: [454][450/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0089 (0.0287) Prec@1 98.000 (95.022) Prec@5 100.000 (99.891) +2022-11-14 17:04:25,136 Epoch: [454][460/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0403 (0.0290) Prec@1 94.000 (95.000) Prec@5 100.000 (99.894) +2022-11-14 17:04:25,338 Epoch: [454][470/500] Time 0.018 (0.022) Data 0.002 (0.002) Loss 0.0546 (0.0295) Prec@1 91.000 (94.917) Prec@5 99.000 (99.875) +2022-11-14 17:04:25,542 Epoch: [454][480/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0401 (0.0297) Prec@1 94.000 (94.898) Prec@5 100.000 (99.878) +2022-11-14 17:04:25,745 Epoch: [454][490/500] Time 0.018 (0.022) Data 0.002 (0.002) Loss 0.0273 (0.0297) Prec@1 96.000 (94.920) Prec@5 100.000 (99.880) +2022-11-14 17:04:25,926 Epoch: [454][499/500] Time 0.019 (0.022) Data 0.001 (0.002) Loss 0.0501 (0.0301) Prec@1 92.000 (94.863) Prec@5 98.000 (99.843) +2022-11-14 17:04:26,219 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0583 (0.0583) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:26,227 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0694) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:26,234 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0683) Prec@1 91.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:04:26,244 Test: [3/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0665) Prec@1 89.000 (89.500) Prec@5 98.000 (99.500) +2022-11-14 17:04:26,251 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0678) Prec@1 88.000 (89.200) Prec@5 99.000 (99.400) +2022-11-14 17:04:26,257 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0645) Prec@1 92.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 17:04:26,264 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0645) Prec@1 87.000 (89.286) Prec@5 100.000 (99.429) +2022-11-14 17:04:26,272 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0676) Prec@1 85.000 (88.750) Prec@5 99.000 (99.375) +2022-11-14 17:04:26,279 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0672) Prec@1 89.000 (88.778) Prec@5 100.000 (99.444) +2022-11-14 17:04:26,287 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0688) Prec@1 87.000 (88.600) Prec@5 98.000 (99.300) +2022-11-14 17:04:26,294 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0679) Prec@1 92.000 (88.909) Prec@5 99.000 (99.273) +2022-11-14 17:04:26,302 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0697) Prec@1 85.000 (88.583) Prec@5 100.000 (99.333) +2022-11-14 17:04:26,310 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0694) Prec@1 90.000 (88.692) Prec@5 100.000 (99.385) +2022-11-14 17:04:26,317 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0702) Prec@1 88.000 (88.643) Prec@5 100.000 (99.429) +2022-11-14 17:04:26,325 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0704) Prec@1 89.000 (88.667) Prec@5 100.000 (99.467) +2022-11-14 17:04:26,332 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0701) Prec@1 90.000 (88.750) Prec@5 99.000 (99.438) +2022-11-14 17:04:26,340 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0690) Prec@1 93.000 (89.000) Prec@5 98.000 (99.353) +2022-11-14 17:04:26,348 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0704) Prec@1 85.000 (88.778) Prec@5 99.000 (99.333) +2022-11-14 17:04:26,355 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0709) Prec@1 87.000 (88.684) Prec@5 98.000 (99.263) +2022-11-14 17:04:26,362 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0722) Prec@1 85.000 (88.500) Prec@5 97.000 (99.150) +2022-11-14 17:04:26,370 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0719) Prec@1 88.000 (88.476) Prec@5 100.000 (99.190) +2022-11-14 17:04:26,377 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0730) Prec@1 84.000 (88.273) Prec@5 98.000 (99.136) +2022-11-14 17:04:26,385 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0740) Prec@1 87.000 (88.217) Prec@5 100.000 (99.174) +2022-11-14 17:04:26,392 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0609 (0.0734) Prec@1 90.000 (88.292) Prec@5 100.000 (99.208) +2022-11-14 17:04:26,400 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0738) Prec@1 87.000 (88.240) Prec@5 100.000 (99.240) +2022-11-14 17:04:26,407 Test: [25/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0834 (0.0742) Prec@1 88.000 (88.231) Prec@5 98.000 (99.192) +2022-11-14 17:04:26,415 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0601 (0.0736) Prec@1 90.000 (88.296) Prec@5 98.000 (99.148) +2022-11-14 17:04:26,422 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0627 (0.0732) Prec@1 93.000 (88.464) Prec@5 100.000 (99.179) +2022-11-14 17:04:26,430 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0731) Prec@1 89.000 (88.483) Prec@5 99.000 (99.172) +2022-11-14 17:04:26,437 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0728) Prec@1 89.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 17:04:26,445 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0601 (0.0724) Prec@1 89.000 (88.516) Prec@5 100.000 (99.194) +2022-11-14 17:04:26,453 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0679 (0.0722) Prec@1 91.000 (88.594) Prec@5 99.000 (99.188) +2022-11-14 17:04:26,461 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1042 (0.0732) Prec@1 81.000 (88.364) Prec@5 100.000 (99.212) +2022-11-14 17:04:26,468 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0857 (0.0736) Prec@1 87.000 (88.324) Prec@5 100.000 (99.235) +2022-11-14 17:04:26,476 Test: [34/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0805 (0.0738) Prec@1 86.000 (88.257) Prec@5 97.000 (99.171) +2022-11-14 17:04:26,483 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0800 (0.0739) Prec@1 89.000 (88.278) Prec@5 99.000 (99.167) +2022-11-14 17:04:26,491 Test: [36/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0737) Prec@1 88.000 (88.270) Prec@5 99.000 (99.162) +2022-11-14 17:04:26,498 Test: [37/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1025 (0.0745) Prec@1 85.000 (88.184) Prec@5 100.000 (99.184) +2022-11-14 17:04:26,506 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0580 (0.0741) Prec@1 92.000 (88.282) Prec@5 99.000 (99.179) +2022-11-14 17:04:26,513 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0740) Prec@1 86.000 (88.225) Prec@5 99.000 (99.175) +2022-11-14 17:04:26,521 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0855 (0.0743) Prec@1 87.000 (88.195) Prec@5 100.000 (99.195) +2022-11-14 17:04:26,528 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0590 (0.0739) Prec@1 91.000 (88.262) Prec@5 98.000 (99.167) +2022-11-14 17:04:26,536 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0574 (0.0735) Prec@1 92.000 (88.349) Prec@5 99.000 (99.163) +2022-11-14 17:04:26,543 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0711 (0.0735) Prec@1 90.000 (88.386) Prec@5 99.000 (99.159) +2022-11-14 17:04:26,551 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0733) Prec@1 89.000 (88.400) Prec@5 99.000 (99.156) +2022-11-14 17:04:26,559 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0965 (0.0738) Prec@1 87.000 (88.370) Prec@5 99.000 (99.152) +2022-11-14 17:04:26,566 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0736) Prec@1 88.000 (88.362) Prec@5 100.000 (99.170) +2022-11-14 17:04:26,573 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1133 (0.0744) Prec@1 82.000 (88.229) Prec@5 100.000 (99.188) +2022-11-14 17:04:26,581 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0658 (0.0742) Prec@1 89.000 (88.245) Prec@5 99.000 (99.184) +2022-11-14 17:04:26,589 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0747) Prec@1 86.000 (88.200) Prec@5 100.000 (99.200) +2022-11-14 17:04:26,596 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0624 (0.0744) Prec@1 90.000 (88.235) Prec@5 99.000 (99.196) +2022-11-14 17:04:26,604 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0742 (0.0744) Prec@1 86.000 (88.192) Prec@5 97.000 (99.154) +2022-11-14 17:04:26,612 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 88.000 (88.189) Prec@5 99.000 (99.151) +2022-11-14 17:04:26,619 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0743) Prec@1 91.000 (88.241) Prec@5 99.000 (99.148) +2022-11-14 17:04:26,627 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0745) Prec@1 88.000 (88.236) Prec@5 100.000 (99.164) +2022-11-14 17:04:26,635 Test: [55/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0781 (0.0745) Prec@1 88.000 (88.232) Prec@5 100.000 (99.179) +2022-11-14 17:04:26,642 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0657 (0.0744) Prec@1 88.000 (88.228) Prec@5 100.000 (99.193) +2022-11-14 17:04:26,650 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0651 (0.0742) Prec@1 90.000 (88.259) Prec@5 98.000 (99.172) +2022-11-14 17:04:26,657 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1131 (0.0749) Prec@1 81.000 (88.136) Prec@5 99.000 (99.169) +2022-11-14 17:04:26,665 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0747) Prec@1 90.000 (88.167) Prec@5 99.000 (99.167) +2022-11-14 17:04:26,672 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0750) Prec@1 84.000 (88.098) Prec@5 99.000 (99.164) +2022-11-14 17:04:26,680 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0749) Prec@1 90.000 (88.129) Prec@5 99.000 (99.161) +2022-11-14 17:04:26,687 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0583 (0.0746) Prec@1 88.000 (88.127) Prec@5 100.000 (99.175) +2022-11-14 17:04:26,695 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0407 (0.0741) Prec@1 94.000 (88.219) Prec@5 100.000 (99.188) +2022-11-14 17:04:26,702 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0821 (0.0742) Prec@1 87.000 (88.200) Prec@5 100.000 (99.200) +2022-11-14 17:04:26,709 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0843 (0.0744) Prec@1 87.000 (88.182) Prec@5 98.000 (99.182) +2022-11-14 17:04:26,717 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0398 (0.0738) Prec@1 95.000 (88.284) Prec@5 100.000 (99.194) +2022-11-14 17:04:26,725 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0801 (0.0739) Prec@1 86.000 (88.250) Prec@5 98.000 (99.176) +2022-11-14 17:04:26,732 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0803 (0.0740) Prec@1 89.000 (88.261) Prec@5 100.000 (99.188) +2022-11-14 17:04:26,740 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0940 (0.0743) Prec@1 86.000 (88.229) Prec@5 99.000 (99.186) +2022-11-14 17:04:26,747 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1142 (0.0749) Prec@1 83.000 (88.155) Prec@5 97.000 (99.155) +2022-11-14 17:04:26,755 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0619 (0.0747) Prec@1 91.000 (88.194) Prec@5 100.000 (99.167) +2022-11-14 17:04:26,762 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0555 (0.0744) Prec@1 92.000 (88.247) Prec@5 100.000 (99.178) +2022-11-14 17:04:26,770 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0546 (0.0742) Prec@1 90.000 (88.270) Prec@5 100.000 (99.189) +2022-11-14 17:04:26,778 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1199 (0.0748) Prec@1 77.000 (88.120) Prec@5 100.000 (99.200) +2022-11-14 17:04:26,785 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0588 (0.0746) Prec@1 91.000 (88.158) Prec@5 98.000 (99.184) +2022-11-14 17:04:26,793 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0660 (0.0745) Prec@1 90.000 (88.182) Prec@5 100.000 (99.195) +2022-11-14 17:04:26,800 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0746) Prec@1 88.000 (88.179) Prec@5 100.000 (99.205) +2022-11-14 17:04:26,808 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0748) Prec@1 85.000 (88.139) Prec@5 100.000 (99.215) +2022-11-14 17:04:26,816 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0747) Prec@1 88.000 (88.138) Prec@5 100.000 (99.225) +2022-11-14 17:04:26,823 Test: [80/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0977 (0.0750) Prec@1 86.000 (88.111) Prec@5 98.000 (99.210) +2022-11-14 17:04:26,831 Test: [81/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0861 (0.0751) Prec@1 87.000 (88.098) Prec@5 99.000 (99.207) +2022-11-14 17:04:26,839 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0833 (0.0752) Prec@1 88.000 (88.096) Prec@5 99.000 (99.205) +2022-11-14 17:04:26,846 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0546 (0.0749) Prec@1 91.000 (88.131) Prec@5 100.000 (99.214) +2022-11-14 17:04:26,854 Test: [84/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0750) Prec@1 89.000 (88.141) Prec@5 99.000 (99.212) +2022-11-14 17:04:26,862 Test: [85/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1083 (0.0754) Prec@1 82.000 (88.070) Prec@5 100.000 (99.221) +2022-11-14 17:04:26,869 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0753) Prec@1 89.000 (88.080) Prec@5 98.000 (99.207) +2022-11-14 17:04:26,877 Test: [87/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0861 (0.0754) Prec@1 87.000 (88.068) Prec@5 99.000 (99.205) +2022-11-14 17:04:26,885 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0753) Prec@1 89.000 (88.079) Prec@5 99.000 (99.202) +2022-11-14 17:04:26,892 Test: [89/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0752) Prec@1 89.000 (88.089) Prec@5 99.000 (99.200) +2022-11-14 17:04:26,900 Test: [90/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0494 (0.0749) Prec@1 91.000 (88.121) Prec@5 99.000 (99.198) +2022-11-14 17:04:26,908 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0607 (0.0747) Prec@1 90.000 (88.141) Prec@5 100.000 (99.207) +2022-11-14 17:04:26,915 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0748) Prec@1 87.000 (88.129) Prec@5 100.000 (99.215) +2022-11-14 17:04:26,924 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0747) Prec@1 88.000 (88.128) Prec@5 99.000 (99.213) +2022-11-14 17:04:26,931 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1019 (0.0750) Prec@1 84.000 (88.084) Prec@5 99.000 (99.211) +2022-11-14 17:04:26,939 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0696 (0.0750) Prec@1 88.000 (88.083) Prec@5 99.000 (99.208) +2022-11-14 17:04:26,946 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0628 (0.0748) Prec@1 91.000 (88.113) Prec@5 99.000 (99.206) +2022-11-14 17:04:26,954 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0900 (0.0750) Prec@1 87.000 (88.102) Prec@5 98.000 (99.194) +2022-11-14 17:04:26,961 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1006 (0.0753) Prec@1 85.000 (88.071) Prec@5 100.000 (99.202) +2022-11-14 17:04:26,968 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0931 (0.0754) Prec@1 86.000 (88.050) Prec@5 100.000 (99.210) +2022-11-14 17:04:27,022 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:04:27,342 Epoch: [455][0/500] Time 0.024 (0.024) Data 0.241 (0.241) Loss 0.0373 (0.0373) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:27,537 Epoch: [455][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0343 (0.0358) Prec@1 94.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:27,730 Epoch: [455][20/500] Time 0.020 (0.018) Data 0.001 (0.013) Loss 0.0362 (0.0359) Prec@1 94.000 (93.333) Prec@5 100.000 (100.000) +2022-11-14 17:04:27,922 Epoch: [455][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0185 (0.0316) Prec@1 97.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 17:04:28,116 Epoch: [455][40/500] Time 0.019 (0.017) Data 0.001 (0.007) Loss 0.0192 (0.0291) Prec@1 97.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 17:04:28,311 Epoch: [455][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0218 (0.0279) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:28,504 Epoch: [455][60/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0111 (0.0255) Prec@1 98.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:04:28,700 Epoch: [455][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0406 (0.0274) Prec@1 95.000 (95.375) Prec@5 99.000 (99.875) +2022-11-14 17:04:28,894 Epoch: [455][80/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.0411 (0.0289) Prec@1 94.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 17:04:29,093 Epoch: [455][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0185 (0.0279) Prec@1 95.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:04:29,288 Epoch: [455][100/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0328 (0.0283) Prec@1 95.000 (95.182) Prec@5 100.000 (99.909) +2022-11-14 17:04:29,480 Epoch: [455][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0491 (0.0300) Prec@1 91.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 17:04:29,671 Epoch: [455][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0148 (0.0289) Prec@1 98.000 (95.077) Prec@5 100.000 (99.923) +2022-11-14 17:04:29,861 Epoch: [455][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0214 (0.0283) Prec@1 97.000 (95.214) Prec@5 100.000 (99.929) +2022-11-14 17:04:30,052 Epoch: [455][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0496 (0.0298) Prec@1 91.000 (94.933) Prec@5 100.000 (99.933) +2022-11-14 17:04:30,242 Epoch: [455][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0344 (0.0300) Prec@1 96.000 (95.000) Prec@5 99.000 (99.875) +2022-11-14 17:04:30,433 Epoch: [455][160/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0307 (0.0301) Prec@1 95.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 17:04:30,699 Epoch: [455][170/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0396 (0.0306) Prec@1 93.000 (94.889) Prec@5 100.000 (99.889) +2022-11-14 17:04:30,985 Epoch: [455][180/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0539 (0.0318) Prec@1 91.000 (94.684) Prec@5 100.000 (99.895) +2022-11-14 17:04:31,270 Epoch: [455][190/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0493 (0.0327) Prec@1 93.000 (94.600) Prec@5 100.000 (99.900) +2022-11-14 17:04:31,557 Epoch: [455][200/500] Time 0.027 (0.019) Data 0.001 (0.003) Loss 0.0293 (0.0325) Prec@1 94.000 (94.571) Prec@5 100.000 (99.905) +2022-11-14 17:04:31,841 Epoch: [455][210/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0239 (0.0322) Prec@1 95.000 (94.591) Prec@5 100.000 (99.909) +2022-11-14 17:04:32,127 Epoch: [455][220/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0178 (0.0315) Prec@1 96.000 (94.652) Prec@5 99.000 (99.870) +2022-11-14 17:04:32,405 Epoch: [455][230/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0382 (0.0318) Prec@1 94.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 17:04:32,687 Epoch: [455][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0226 (0.0314) Prec@1 95.000 (94.640) Prec@5 100.000 (99.880) +2022-11-14 17:04:32,967 Epoch: [455][250/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0272 (0.0313) Prec@1 95.000 (94.654) Prec@5 100.000 (99.885) +2022-11-14 17:04:33,252 Epoch: [455][260/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0304 (0.0312) Prec@1 95.000 (94.667) Prec@5 100.000 (99.889) +2022-11-14 17:04:33,530 Epoch: [455][270/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0503 (0.0319) Prec@1 92.000 (94.571) Prec@5 100.000 (99.893) +2022-11-14 17:04:33,816 Epoch: [455][280/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0291 (0.0318) Prec@1 95.000 (94.586) Prec@5 99.000 (99.862) +2022-11-14 17:04:34,102 Epoch: [455][290/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0257 (0.0316) Prec@1 97.000 (94.667) Prec@5 100.000 (99.867) +2022-11-14 17:04:34,376 Epoch: [455][300/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0251 (0.0314) Prec@1 96.000 (94.710) Prec@5 100.000 (99.871) +2022-11-14 17:04:34,657 Epoch: [455][310/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0338 (0.0315) Prec@1 94.000 (94.688) Prec@5 100.000 (99.875) +2022-11-14 17:04:34,939 Epoch: [455][320/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0203 (0.0311) Prec@1 96.000 (94.727) Prec@5 100.000 (99.879) +2022-11-14 17:04:35,226 Epoch: [455][330/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0373 (0.0313) Prec@1 95.000 (94.735) Prec@5 100.000 (99.882) +2022-11-14 17:04:35,506 Epoch: [455][340/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0400 (0.0316) Prec@1 93.000 (94.686) Prec@5 100.000 (99.886) +2022-11-14 17:04:35,788 Epoch: [455][350/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0292 (0.0315) Prec@1 95.000 (94.694) Prec@5 100.000 (99.889) +2022-11-14 17:04:36,068 Epoch: [455][360/500] Time 0.030 (0.021) Data 0.002 (0.002) Loss 0.0671 (0.0325) Prec@1 89.000 (94.541) Prec@5 100.000 (99.892) +2022-11-14 17:04:36,350 Epoch: [455][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0344 (0.0325) Prec@1 96.000 (94.579) Prec@5 100.000 (99.895) +2022-11-14 17:04:36,632 Epoch: [455][380/500] Time 0.031 (0.022) Data 0.002 (0.002) Loss 0.0149 (0.0321) Prec@1 99.000 (94.692) Prec@5 100.000 (99.897) +2022-11-14 17:04:36,914 Epoch: [455][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0398 (0.0323) Prec@1 93.000 (94.650) Prec@5 99.000 (99.875) +2022-11-14 17:04:37,195 Epoch: [455][400/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0271 (0.0321) Prec@1 96.000 (94.683) Prec@5 100.000 (99.878) +2022-11-14 17:04:37,478 Epoch: [455][410/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0236 (0.0319) Prec@1 98.000 (94.762) Prec@5 100.000 (99.881) +2022-11-14 17:04:37,760 Epoch: [455][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0169 (0.0316) Prec@1 97.000 (94.814) Prec@5 100.000 (99.884) +2022-11-14 17:04:38,040 Epoch: [455][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0298 (0.0315) Prec@1 95.000 (94.818) Prec@5 100.000 (99.886) +2022-11-14 17:04:38,323 Epoch: [455][440/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0225 (0.0313) Prec@1 97.000 (94.867) Prec@5 100.000 (99.889) +2022-11-14 17:04:38,604 Epoch: [455][450/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0127 (0.0309) Prec@1 97.000 (94.913) Prec@5 100.000 (99.891) +2022-11-14 17:04:38,883 Epoch: [455][460/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0166 (0.0306) Prec@1 97.000 (94.957) Prec@5 100.000 (99.894) +2022-11-14 17:04:39,168 Epoch: [455][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0438 (0.0309) Prec@1 91.000 (94.875) Prec@5 100.000 (99.896) +2022-11-14 17:04:39,449 Epoch: [455][480/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0260 (0.0308) Prec@1 96.000 (94.898) Prec@5 100.000 (99.898) +2022-11-14 17:04:39,730 Epoch: [455][490/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0278 (0.0307) Prec@1 94.000 (94.880) Prec@5 100.000 (99.900) +2022-11-14 17:04:39,984 Epoch: [455][499/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0188 (0.0305) Prec@1 96.000 (94.902) Prec@5 100.000 (99.902) +2022-11-14 17:04:40,290 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0666 (0.0666) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:04:40,300 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0805 (0.0736) Prec@1 88.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 17:04:40,309 Test: [2/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0730 (0.0734) Prec@1 88.000 (88.333) Prec@5 100.000 (99.667) +2022-11-14 17:04:40,320 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0727) Prec@1 89.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 17:04:40,327 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0688) Prec@1 92.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 17:04:40,334 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0660) Prec@1 90.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 17:04:40,343 Test: [6/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0659) Prec@1 90.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 17:04:40,351 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0651) Prec@1 89.000 (89.375) Prec@5 100.000 (99.750) +2022-11-14 17:04:40,358 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0537 (0.0639) Prec@1 92.000 (89.667) Prec@5 99.000 (99.667) +2022-11-14 17:04:40,365 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0661) Prec@1 86.000 (89.300) Prec@5 99.000 (99.600) +2022-11-14 17:04:40,373 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0476 (0.0644) Prec@1 93.000 (89.636) Prec@5 100.000 (99.636) +2022-11-14 17:04:40,380 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0794 (0.0657) Prec@1 86.000 (89.333) Prec@5 100.000 (99.667) +2022-11-14 17:04:40,388 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0648) Prec@1 90.000 (89.385) Prec@5 100.000 (99.692) +2022-11-14 17:04:40,396 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0656) Prec@1 89.000 (89.357) Prec@5 100.000 (99.714) +2022-11-14 17:04:40,404 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0661) Prec@1 86.000 (89.133) Prec@5 100.000 (99.733) +2022-11-14 17:04:40,411 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0653) Prec@1 92.000 (89.312) Prec@5 99.000 (99.688) +2022-11-14 17:04:40,419 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0647) Prec@1 91.000 (89.412) Prec@5 98.000 (99.588) +2022-11-14 17:04:40,426 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0665) Prec@1 86.000 (89.222) Prec@5 100.000 (99.611) +2022-11-14 17:04:40,434 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0670) Prec@1 86.000 (89.053) Prec@5 100.000 (99.632) +2022-11-14 17:04:40,442 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0686) Prec@1 84.000 (88.800) Prec@5 97.000 (99.500) +2022-11-14 17:04:40,449 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0695) Prec@1 86.000 (88.667) Prec@5 100.000 (99.524) +2022-11-14 17:04:40,457 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0696) Prec@1 87.000 (88.591) Prec@5 99.000 (99.500) +2022-11-14 17:04:40,465 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0700) Prec@1 87.000 (88.522) Prec@5 99.000 (99.478) +2022-11-14 17:04:40,472 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0699) Prec@1 89.000 (88.542) Prec@5 100.000 (99.500) +2022-11-14 17:04:40,480 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0709) Prec@1 83.000 (88.320) Prec@5 99.000 (99.480) +2022-11-14 17:04:40,488 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0716) Prec@1 88.000 (88.308) Prec@5 98.000 (99.423) +2022-11-14 17:04:40,495 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0704) Prec@1 93.000 (88.481) Prec@5 100.000 (99.444) +2022-11-14 17:04:40,503 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0699) Prec@1 92.000 (88.607) Prec@5 100.000 (99.464) +2022-11-14 17:04:40,511 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0699) Prec@1 89.000 (88.621) Prec@5 99.000 (99.448) +2022-11-14 17:04:40,518 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0701) Prec@1 87.000 (88.567) Prec@5 98.000 (99.400) +2022-11-14 17:04:40,526 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0697) Prec@1 91.000 (88.645) Prec@5 99.000 (99.387) +2022-11-14 17:04:40,534 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0698) Prec@1 91.000 (88.719) Prec@5 100.000 (99.406) +2022-11-14 17:04:40,541 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0699) Prec@1 86.000 (88.636) Prec@5 99.000 (99.394) +2022-11-14 17:04:40,549 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0696) Prec@1 90.000 (88.676) Prec@5 100.000 (99.412) +2022-11-14 17:04:40,557 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0697) Prec@1 90.000 (88.714) Prec@5 97.000 (99.343) +2022-11-14 17:04:40,564 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0695) Prec@1 92.000 (88.806) Prec@5 98.000 (99.306) +2022-11-14 17:04:40,572 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0698) Prec@1 88.000 (88.784) Prec@5 98.000 (99.270) +2022-11-14 17:04:40,580 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0702) Prec@1 84.000 (88.658) Prec@5 100.000 (99.289) +2022-11-14 17:04:40,587 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0697) Prec@1 92.000 (88.744) Prec@5 100.000 (99.308) +2022-11-14 17:04:40,595 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0696) Prec@1 89.000 (88.750) Prec@5 99.000 (99.300) +2022-11-14 17:04:40,603 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0701) Prec@1 85.000 (88.659) Prec@5 98.000 (99.268) +2022-11-14 17:04:40,611 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0698) Prec@1 91.000 (88.714) Prec@5 99.000 (99.262) +2022-11-14 17:04:40,619 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0406 (0.0692) Prec@1 92.000 (88.791) Prec@5 99.000 (99.256) +2022-11-14 17:04:40,626 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0692) Prec@1 90.000 (88.818) Prec@5 99.000 (99.250) +2022-11-14 17:04:40,634 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0688) Prec@1 93.000 (88.911) Prec@5 100.000 (99.267) +2022-11-14 17:04:40,642 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0697) Prec@1 84.000 (88.804) Prec@5 98.000 (99.239) +2022-11-14 17:04:40,649 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0699) Prec@1 87.000 (88.766) Prec@5 100.000 (99.255) +2022-11-14 17:04:40,657 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0706) Prec@1 84.000 (88.667) Prec@5 99.000 (99.250) +2022-11-14 17:04:40,665 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0704) Prec@1 91.000 (88.714) Prec@5 100.000 (99.265) +2022-11-14 17:04:40,673 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0710) Prec@1 84.000 (88.620) Prec@5 99.000 (99.260) +2022-11-14 17:04:40,680 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0705) Prec@1 91.000 (88.667) Prec@5 100.000 (99.275) +2022-11-14 17:04:40,688 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0710) Prec@1 83.000 (88.558) Prec@5 99.000 (99.269) +2022-11-14 17:04:40,696 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0711) Prec@1 86.000 (88.509) Prec@5 99.000 (99.264) +2022-11-14 17:04:40,703 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0710) Prec@1 89.000 (88.519) Prec@5 98.000 (99.241) +2022-11-14 17:04:40,711 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0712) Prec@1 84.000 (88.436) Prec@5 100.000 (99.255) +2022-11-14 17:04:40,719 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0711) Prec@1 89.000 (88.446) Prec@5 99.000 (99.250) +2022-11-14 17:04:40,726 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0710) Prec@1 91.000 (88.491) Prec@5 100.000 (99.263) +2022-11-14 17:04:40,734 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0709) Prec@1 90.000 (88.517) Prec@5 98.000 (99.241) +2022-11-14 17:04:40,741 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0714) Prec@1 83.000 (88.424) Prec@5 100.000 (99.254) +2022-11-14 17:04:40,750 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0718) Prec@1 84.000 (88.350) Prec@5 100.000 (99.267) +2022-11-14 17:04:40,757 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0721) Prec@1 87.000 (88.328) Prec@5 98.000 (99.246) +2022-11-14 17:04:40,765 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0717) Prec@1 90.000 (88.355) Prec@5 100.000 (99.258) +2022-11-14 17:04:40,773 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0716) Prec@1 91.000 (88.397) Prec@5 100.000 (99.270) +2022-11-14 17:04:40,780 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0415 (0.0711) Prec@1 93.000 (88.469) Prec@5 100.000 (99.281) +2022-11-14 17:04:40,790 Test: [64/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0716) Prec@1 82.000 (88.369) Prec@5 100.000 (99.292) +2022-11-14 17:04:40,800 Test: [65/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0716) Prec@1 89.000 (88.379) Prec@5 99.000 (99.288) +2022-11-14 17:04:40,807 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0473 (0.0712) Prec@1 92.000 (88.433) Prec@5 100.000 (99.299) +2022-11-14 17:04:40,815 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0712) Prec@1 91.000 (88.471) Prec@5 100.000 (99.309) +2022-11-14 17:04:40,824 Test: [68/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0709) Prec@1 90.000 (88.493) Prec@5 98.000 (99.290) +2022-11-14 17:04:40,833 Test: [69/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0711) Prec@1 87.000 (88.471) Prec@5 99.000 (99.286) +2022-11-14 17:04:40,841 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0714) Prec@1 87.000 (88.451) Prec@5 99.000 (99.282) +2022-11-14 17:04:40,848 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0713) Prec@1 89.000 (88.458) Prec@5 99.000 (99.278) +2022-11-14 17:04:40,858 Test: [72/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0711) Prec@1 93.000 (88.521) Prec@5 100.000 (99.288) +2022-11-14 17:04:40,867 Test: [73/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0707) Prec@1 93.000 (88.581) Prec@5 100.000 (99.297) +2022-11-14 17:04:40,875 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1122 (0.0713) Prec@1 82.000 (88.493) Prec@5 100.000 (99.307) +2022-11-14 17:04:40,883 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0712) Prec@1 91.000 (88.526) Prec@5 98.000 (99.289) +2022-11-14 17:04:40,892 Test: [76/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0713) Prec@1 88.000 (88.519) Prec@5 98.000 (99.273) +2022-11-14 17:04:40,902 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0714) Prec@1 87.000 (88.500) Prec@5 98.000 (99.256) +2022-11-14 17:04:40,909 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0714) Prec@1 86.000 (88.468) Prec@5 100.000 (99.266) +2022-11-14 17:04:40,917 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0715) Prec@1 88.000 (88.463) Prec@5 98.000 (99.250) +2022-11-14 17:04:40,927 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0717) Prec@1 86.000 (88.432) Prec@5 99.000 (99.247) +2022-11-14 17:04:40,937 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0719) Prec@1 87.000 (88.415) Prec@5 100.000 (99.256) +2022-11-14 17:04:40,945 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0721) Prec@1 87.000 (88.398) Prec@5 100.000 (99.265) +2022-11-14 17:04:40,952 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0720) Prec@1 87.000 (88.381) Prec@5 100.000 (99.274) +2022-11-14 17:04:40,962 Test: [84/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0971 (0.0723) Prec@1 85.000 (88.341) Prec@5 100.000 (99.282) +2022-11-14 17:04:40,972 Test: [85/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0727) Prec@1 83.000 (88.279) Prec@5 99.000 (99.279) +2022-11-14 17:04:40,980 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0729) Prec@1 85.000 (88.241) Prec@5 99.000 (99.276) +2022-11-14 17:04:40,988 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0728) Prec@1 90.000 (88.261) Prec@5 99.000 (99.273) +2022-11-14 17:04:40,998 Test: [88/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0729) Prec@1 87.000 (88.247) Prec@5 100.000 (99.281) +2022-11-14 17:04:41,006 Test: [89/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0731) Prec@1 87.000 (88.233) Prec@5 100.000 (99.289) +2022-11-14 17:04:41,014 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0731) Prec@1 88.000 (88.231) Prec@5 100.000 (99.297) +2022-11-14 17:04:41,022 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0730) Prec@1 90.000 (88.250) Prec@5 99.000 (99.293) +2022-11-14 17:04:41,029 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0730) Prec@1 89.000 (88.258) Prec@5 100.000 (99.301) +2022-11-14 17:04:41,037 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0728) Prec@1 91.000 (88.287) Prec@5 100.000 (99.309) +2022-11-14 17:04:41,045 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0731) Prec@1 85.000 (88.253) Prec@5 100.000 (99.316) +2022-11-14 17:04:41,052 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0730) Prec@1 90.000 (88.271) Prec@5 99.000 (99.312) +2022-11-14 17:04:41,059 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0728) Prec@1 91.000 (88.299) Prec@5 98.000 (99.299) +2022-11-14 17:04:41,067 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0728) Prec@1 89.000 (88.306) Prec@5 98.000 (99.286) +2022-11-14 17:04:41,074 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0729) Prec@1 88.000 (88.303) Prec@5 99.000 (99.283) +2022-11-14 17:04:41,083 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0729) Prec@1 90.000 (88.320) Prec@5 97.000 (99.260) +2022-11-14 17:04:41,136 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:04:41,449 Epoch: [456][0/500] Time 0.025 (0.025) Data 0.235 (0.235) Loss 0.0157 (0.0157) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:41,654 Epoch: [456][10/500] Time 0.020 (0.019) Data 0.002 (0.023) Loss 0.0327 (0.0242) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:41,848 Epoch: [456][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0464 (0.0316) Prec@1 93.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 17:04:42,042 Epoch: [456][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0158 (0.0277) Prec@1 99.000 (96.000) Prec@5 100.000 (99.750) +2022-11-14 17:04:42,238 Epoch: [456][40/500] Time 0.018 (0.018) Data 0.002 (0.007) Loss 0.0272 (0.0276) Prec@1 95.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 17:04:42,432 Epoch: [456][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0323 (0.0284) Prec@1 96.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 17:04:42,625 Epoch: [456][60/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0394 (0.0299) Prec@1 92.000 (95.286) Prec@5 99.000 (99.714) +2022-11-14 17:04:42,817 Epoch: [456][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0473 (0.0321) Prec@1 91.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 17:04:43,009 Epoch: [456][80/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0172 (0.0305) Prec@1 97.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 17:04:43,202 Epoch: [456][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0180 (0.0292) Prec@1 96.000 (95.100) Prec@5 100.000 (99.800) +2022-11-14 17:04:43,393 Epoch: [456][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0140 (0.0278) Prec@1 98.000 (95.364) Prec@5 100.000 (99.818) +2022-11-14 17:04:43,586 Epoch: [456][110/500] Time 0.019 (0.017) Data 0.002 (0.004) Loss 0.0245 (0.0276) Prec@1 97.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:04:43,780 Epoch: [456][120/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0264 (0.0275) Prec@1 95.000 (95.462) Prec@5 100.000 (99.846) +2022-11-14 17:04:43,973 Epoch: [456][130/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0208 (0.0270) Prec@1 97.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:04:44,165 Epoch: [456][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0252 (0.0269) Prec@1 96.000 (95.600) Prec@5 100.000 (99.867) +2022-11-14 17:04:44,358 Epoch: [456][150/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0447 (0.0280) Prec@1 92.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 17:04:44,553 Epoch: [456][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0275 (0.0280) Prec@1 94.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 17:04:44,749 Epoch: [456][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0100 (0.0270) Prec@1 99.000 (95.500) Prec@5 100.000 (99.889) +2022-11-14 17:04:44,943 Epoch: [456][180/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0299 (0.0271) Prec@1 96.000 (95.526) Prec@5 99.000 (99.842) +2022-11-14 17:04:45,140 Epoch: [456][190/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0244 (0.0270) Prec@1 98.000 (95.650) Prec@5 100.000 (99.850) +2022-11-14 17:04:45,336 Epoch: [456][200/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0187 (0.0266) Prec@1 97.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 17:04:45,531 Epoch: [456][210/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0263 (0.0266) Prec@1 96.000 (95.727) Prec@5 100.000 (99.864) +2022-11-14 17:04:45,734 Epoch: [456][220/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0400 (0.0272) Prec@1 92.000 (95.565) Prec@5 100.000 (99.870) +2022-11-14 17:04:45,933 Epoch: [456][230/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0368 (0.0276) Prec@1 93.000 (95.458) Prec@5 100.000 (99.875) +2022-11-14 17:04:46,130 Epoch: [456][240/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0330 (0.0278) Prec@1 94.000 (95.400) Prec@5 100.000 (99.880) +2022-11-14 17:04:46,325 Epoch: [456][250/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0382 (0.0282) Prec@1 95.000 (95.385) Prec@5 100.000 (99.885) +2022-11-14 17:04:46,520 Epoch: [456][260/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0241 (0.0280) Prec@1 96.000 (95.407) Prec@5 99.000 (99.852) +2022-11-14 17:04:46,714 Epoch: [456][270/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0163 (0.0276) Prec@1 97.000 (95.464) Prec@5 100.000 (99.857) +2022-11-14 17:04:46,940 Epoch: [456][280/500] Time 0.025 (0.017) Data 0.002 (0.002) Loss 0.0306 (0.0277) Prec@1 94.000 (95.414) Prec@5 100.000 (99.862) +2022-11-14 17:04:47,230 Epoch: [456][290/500] Time 0.028 (0.018) Data 0.002 (0.002) Loss 0.0435 (0.0282) Prec@1 92.000 (95.300) Prec@5 100.000 (99.867) +2022-11-14 17:04:47,526 Epoch: [456][300/500] Time 0.027 (0.018) Data 0.002 (0.002) Loss 0.0373 (0.0285) Prec@1 94.000 (95.258) Prec@5 100.000 (99.871) +2022-11-14 17:04:47,814 Epoch: [456][310/500] Time 0.027 (0.018) Data 0.002 (0.002) Loss 0.0368 (0.0288) Prec@1 93.000 (95.188) Prec@5 100.000 (99.875) +2022-11-14 17:04:48,107 Epoch: [456][320/500] Time 0.028 (0.018) Data 0.002 (0.002) Loss 0.0179 (0.0285) Prec@1 97.000 (95.242) Prec@5 100.000 (99.879) +2022-11-14 17:04:48,397 Epoch: [456][330/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0429 (0.0289) Prec@1 94.000 (95.206) Prec@5 99.000 (99.853) +2022-11-14 17:04:48,678 Epoch: [456][340/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0303 (0.0289) Prec@1 95.000 (95.200) Prec@5 100.000 (99.857) +2022-11-14 17:04:48,958 Epoch: [456][350/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0456 (0.0294) Prec@1 94.000 (95.167) Prec@5 99.000 (99.833) +2022-11-14 17:04:49,246 Epoch: [456][360/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0320 (0.0295) Prec@1 95.000 (95.162) Prec@5 100.000 (99.838) +2022-11-14 17:04:49,531 Epoch: [456][370/500] Time 0.027 (0.019) Data 0.001 (0.002) Loss 0.0257 (0.0294) Prec@1 96.000 (95.184) Prec@5 100.000 (99.842) +2022-11-14 17:04:49,807 Epoch: [456][380/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0269 (0.0293) Prec@1 95.000 (95.179) Prec@5 100.000 (99.846) +2022-11-14 17:04:50,081 Epoch: [456][390/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0353 (0.0294) Prec@1 94.000 (95.150) Prec@5 100.000 (99.850) +2022-11-14 17:04:50,360 Epoch: [456][400/500] Time 0.027 (0.020) Data 0.001 (0.002) Loss 0.0257 (0.0294) Prec@1 97.000 (95.195) Prec@5 100.000 (99.854) +2022-11-14 17:04:50,639 Epoch: [456][410/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0278 (0.0293) Prec@1 94.000 (95.167) Prec@5 100.000 (99.857) +2022-11-14 17:04:50,918 Epoch: [456][420/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0323 (0.0294) Prec@1 96.000 (95.186) Prec@5 99.000 (99.837) +2022-11-14 17:04:51,197 Epoch: [456][430/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0322 (0.0294) Prec@1 93.000 (95.136) Prec@5 100.000 (99.841) +2022-11-14 17:04:51,473 Epoch: [456][440/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0300 (0.0295) Prec@1 94.000 (95.111) Prec@5 100.000 (99.844) +2022-11-14 17:04:51,744 Epoch: [456][450/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0304 (0.0295) Prec@1 96.000 (95.130) Prec@5 100.000 (99.848) +2022-11-14 17:04:52,018 Epoch: [456][460/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0132 (0.0291) Prec@1 98.000 (95.191) Prec@5 100.000 (99.851) +2022-11-14 17:04:52,291 Epoch: [456][470/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0286 (0.0291) Prec@1 96.000 (95.208) Prec@5 100.000 (99.854) +2022-11-14 17:04:52,570 Epoch: [456][480/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0198 (0.0289) Prec@1 97.000 (95.245) Prec@5 100.000 (99.857) +2022-11-14 17:04:52,843 Epoch: [456][490/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0450 (0.0293) Prec@1 91.000 (95.160) Prec@5 100.000 (99.860) +2022-11-14 17:04:53,094 Epoch: [456][499/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0437 (0.0295) Prec@1 90.000 (95.059) Prec@5 100.000 (99.863) +2022-11-14 17:04:53,402 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0782 (0.0782) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:53,410 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0669 (0.0726) Prec@1 90.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:04:53,418 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0675 (0.0709) Prec@1 90.000 (89.000) Prec@5 99.000 (99.667) +2022-11-14 17:04:53,446 Test: [3/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0709) Prec@1 89.000 (89.000) Prec@5 100.000 (99.750) +2022-11-14 17:04:53,455 Test: [4/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0714 (0.0710) Prec@1 91.000 (89.400) Prec@5 100.000 (99.800) +2022-11-14 17:04:53,462 Test: [5/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0288 (0.0640) Prec@1 96.000 (90.500) Prec@5 99.000 (99.667) +2022-11-14 17:04:53,469 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0580 (0.0631) Prec@1 91.000 (90.571) Prec@5 99.000 (99.571) +2022-11-14 17:04:53,477 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0642) Prec@1 89.000 (90.375) Prec@5 100.000 (99.625) +2022-11-14 17:04:53,484 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0800 (0.0660) Prec@1 87.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 17:04:53,491 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0739 (0.0667) Prec@1 88.000 (89.800) Prec@5 98.000 (99.500) +2022-11-14 17:04:53,497 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0572 (0.0659) Prec@1 91.000 (89.909) Prec@5 100.000 (99.545) +2022-11-14 17:04:53,505 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0679) Prec@1 85.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:04:53,513 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0669) Prec@1 90.000 (89.538) Prec@5 100.000 (99.538) +2022-11-14 17:04:53,520 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0672) Prec@1 90.000 (89.571) Prec@5 98.000 (99.429) +2022-11-14 17:04:53,528 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0688) Prec@1 84.000 (89.200) Prec@5 100.000 (99.467) +2022-11-14 17:04:53,535 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0697) Prec@1 89.000 (89.188) Prec@5 100.000 (99.500) +2022-11-14 17:04:53,543 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0694) Prec@1 91.000 (89.294) Prec@5 98.000 (99.412) +2022-11-14 17:04:53,552 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1081 (0.0716) Prec@1 84.000 (89.000) Prec@5 100.000 (99.444) +2022-11-14 17:04:53,561 Test: [18/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0721) Prec@1 87.000 (88.895) Prec@5 98.000 (99.368) +2022-11-14 17:04:53,569 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0732) Prec@1 87.000 (88.800) Prec@5 97.000 (99.250) +2022-11-14 17:04:53,576 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0739) Prec@1 85.000 (88.619) Prec@5 100.000 (99.286) +2022-11-14 17:04:53,586 Test: [21/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0740) Prec@1 87.000 (88.545) Prec@5 99.000 (99.273) +2022-11-14 17:04:53,595 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0747) Prec@1 86.000 (88.435) Prec@5 98.000 (99.217) +2022-11-14 17:04:53,603 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0738) Prec@1 92.000 (88.583) Prec@5 100.000 (99.250) +2022-11-14 17:04:53,610 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0741) Prec@1 87.000 (88.520) Prec@5 100.000 (99.280) +2022-11-14 17:04:53,621 Test: [25/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0750) Prec@1 84.000 (88.346) Prec@5 98.000 (99.231) +2022-11-14 17:04:53,631 Test: [26/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0745) Prec@1 88.000 (88.333) Prec@5 100.000 (99.259) +2022-11-14 17:04:53,639 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0738) Prec@1 91.000 (88.429) Prec@5 99.000 (99.250) +2022-11-14 17:04:53,646 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0730) Prec@1 92.000 (88.552) Prec@5 99.000 (99.241) +2022-11-14 17:04:53,656 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0727) Prec@1 90.000 (88.600) Prec@5 98.000 (99.200) +2022-11-14 17:04:53,665 Test: [30/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0722) Prec@1 89.000 (88.613) Prec@5 100.000 (99.226) +2022-11-14 17:04:53,673 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0721) Prec@1 88.000 (88.594) Prec@5 99.000 (99.219) +2022-11-14 17:04:53,681 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0718) Prec@1 90.000 (88.636) Prec@5 100.000 (99.242) +2022-11-14 17:04:53,690 Test: [33/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0719) Prec@1 88.000 (88.618) Prec@5 99.000 (99.235) +2022-11-14 17:04:53,699 Test: [34/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0723) Prec@1 87.000 (88.571) Prec@5 98.000 (99.200) +2022-11-14 17:04:53,707 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0721) Prec@1 90.000 (88.611) Prec@5 100.000 (99.222) +2022-11-14 17:04:53,715 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0727) Prec@1 87.000 (88.568) Prec@5 98.000 (99.189) +2022-11-14 17:04:53,724 Test: [37/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0737) Prec@1 83.000 (88.421) Prec@5 99.000 (99.184) +2022-11-14 17:04:53,733 Test: [38/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0733) Prec@1 94.000 (88.564) Prec@5 99.000 (99.179) +2022-11-14 17:04:53,741 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0729) Prec@1 91.000 (88.625) Prec@5 99.000 (99.175) +2022-11-14 17:04:53,748 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.0737) Prec@1 82.000 (88.463) Prec@5 99.000 (99.171) +2022-11-14 17:04:53,758 Test: [41/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0736) Prec@1 88.000 (88.452) Prec@5 99.000 (99.167) +2022-11-14 17:04:53,767 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0438 (0.0729) Prec@1 93.000 (88.558) Prec@5 100.000 (99.186) +2022-11-14 17:04:53,775 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0476 (0.0724) Prec@1 94.000 (88.682) Prec@5 99.000 (99.182) +2022-11-14 17:04:53,783 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0721) Prec@1 89.000 (88.689) Prec@5 99.000 (99.178) +2022-11-14 17:04:53,792 Test: [45/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1214 (0.0732) Prec@1 81.000 (88.522) Prec@5 98.000 (99.152) +2022-11-14 17:04:53,802 Test: [46/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0732) Prec@1 88.000 (88.511) Prec@5 99.000 (99.149) +2022-11-14 17:04:53,809 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1119 (0.0740) Prec@1 83.000 (88.396) Prec@5 99.000 (99.146) +2022-11-14 17:04:53,817 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0736) Prec@1 92.000 (88.469) Prec@5 99.000 (99.143) +2022-11-14 17:04:53,827 Test: [49/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1158 (0.0744) Prec@1 83.000 (88.360) Prec@5 100.000 (99.160) +2022-11-14 17:04:53,836 Test: [50/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0743) Prec@1 88.000 (88.353) Prec@5 100.000 (99.176) +2022-11-14 17:04:53,844 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0743) Prec@1 87.000 (88.327) Prec@5 100.000 (99.192) +2022-11-14 17:04:53,852 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0742) Prec@1 91.000 (88.377) Prec@5 99.000 (99.189) +2022-11-14 17:04:53,861 Test: [53/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0738) Prec@1 92.000 (88.444) Prec@5 98.000 (99.167) +2022-11-14 17:04:53,870 Test: [54/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0739) Prec@1 88.000 (88.436) Prec@5 100.000 (99.182) +2022-11-14 17:04:53,878 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0737) Prec@1 90.000 (88.464) Prec@5 99.000 (99.179) +2022-11-14 17:04:53,886 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0734) Prec@1 89.000 (88.474) Prec@5 100.000 (99.193) +2022-11-14 17:04:53,896 Test: [57/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0732) Prec@1 92.000 (88.534) Prec@5 100.000 (99.207) +2022-11-14 17:04:53,906 Test: [58/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0737) Prec@1 86.000 (88.492) Prec@5 99.000 (99.203) +2022-11-14 17:04:53,914 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0736) Prec@1 88.000 (88.483) Prec@5 100.000 (99.217) +2022-11-14 17:04:53,921 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0734) Prec@1 90.000 (88.508) Prec@5 100.000 (99.230) +2022-11-14 17:04:53,931 Test: [61/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0731) Prec@1 92.000 (88.565) Prec@5 99.000 (99.226) +2022-11-14 17:04:53,941 Test: [62/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0729) Prec@1 90.000 (88.587) Prec@5 100.000 (99.238) +2022-11-14 17:04:53,948 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0415 (0.0724) Prec@1 93.000 (88.656) Prec@5 100.000 (99.250) +2022-11-14 17:04:53,956 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0728) Prec@1 84.000 (88.585) Prec@5 98.000 (99.231) +2022-11-14 17:04:53,966 Test: [65/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0730) Prec@1 87.000 (88.561) Prec@5 99.000 (99.227) +2022-11-14 17:04:53,976 Test: [66/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0726) Prec@1 91.000 (88.597) Prec@5 100.000 (99.239) +2022-11-14 17:04:53,984 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0725) Prec@1 90.000 (88.618) Prec@5 97.000 (99.206) +2022-11-14 17:04:53,991 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0724) Prec@1 91.000 (88.652) Prec@5 98.000 (99.188) +2022-11-14 17:04:54,001 Test: [69/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0726) Prec@1 86.000 (88.614) Prec@5 100.000 (99.200) +2022-11-14 17:04:54,011 Test: [70/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1116 (0.0732) Prec@1 84.000 (88.549) Prec@5 98.000 (99.183) +2022-11-14 17:04:54,019 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0730) Prec@1 89.000 (88.556) Prec@5 100.000 (99.194) +2022-11-14 17:04:54,026 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0727) Prec@1 93.000 (88.616) Prec@5 100.000 (99.205) +2022-11-14 17:04:54,036 Test: [73/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0723) Prec@1 92.000 (88.662) Prec@5 100.000 (99.216) +2022-11-14 17:04:54,046 Test: [74/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0992 (0.0726) Prec@1 82.000 (88.573) Prec@5 100.000 (99.227) +2022-11-14 17:04:54,053 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0726) Prec@1 89.000 (88.579) Prec@5 100.000 (99.237) +2022-11-14 17:04:54,061 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0726) Prec@1 87.000 (88.558) Prec@5 100.000 (99.247) +2022-11-14 17:04:54,070 Test: [77/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0729) Prec@1 86.000 (88.526) Prec@5 98.000 (99.231) +2022-11-14 17:04:54,081 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0661 (0.0728) Prec@1 92.000 (88.570) Prec@5 99.000 (99.228) +2022-11-14 17:04:54,088 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0725) Prec@1 94.000 (88.638) Prec@5 100.000 (99.237) +2022-11-14 17:04:54,096 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0726) Prec@1 88.000 (88.630) Prec@5 99.000 (99.235) +2022-11-14 17:04:54,106 Test: [81/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1039 (0.0730) Prec@1 85.000 (88.585) Prec@5 100.000 (99.244) +2022-11-14 17:04:54,115 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0729) Prec@1 88.000 (88.578) Prec@5 100.000 (99.253) +2022-11-14 17:04:54,123 Test: [83/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0726) Prec@1 91.000 (88.607) Prec@5 100.000 (99.262) +2022-11-14 17:04:54,131 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0726) Prec@1 90.000 (88.624) Prec@5 99.000 (99.259) +2022-11-14 17:04:54,140 Test: [85/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0986 (0.0729) Prec@1 84.000 (88.570) Prec@5 100.000 (99.267) +2022-11-14 17:04:54,150 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0728) Prec@1 89.000 (88.575) Prec@5 99.000 (99.264) +2022-11-14 17:04:54,159 Test: [87/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0693 (0.0728) Prec@1 88.000 (88.568) Prec@5 99.000 (99.261) +2022-11-14 17:04:54,166 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0729) Prec@1 85.000 (88.528) Prec@5 100.000 (99.270) +2022-11-14 17:04:54,176 Test: [89/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0729) Prec@1 86.000 (88.500) Prec@5 98.000 (99.256) +2022-11-14 17:04:54,186 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0729) Prec@1 90.000 (88.516) Prec@5 100.000 (99.264) +2022-11-14 17:04:54,193 Test: [91/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0727) Prec@1 91.000 (88.543) Prec@5 99.000 (99.261) +2022-11-14 17:04:54,201 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0728) Prec@1 89.000 (88.548) Prec@5 98.000 (99.247) +2022-11-14 17:04:54,208 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0728) Prec@1 87.000 (88.532) Prec@5 98.000 (99.234) +2022-11-14 17:04:54,216 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0728) Prec@1 88.000 (88.526) Prec@5 100.000 (99.242) +2022-11-14 17:04:54,223 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0726) Prec@1 90.000 (88.542) Prec@5 99.000 (99.240) +2022-11-14 17:04:54,230 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0420 (0.0723) Prec@1 92.000 (88.577) Prec@5 99.000 (99.237) +2022-11-14 17:04:54,238 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0725) Prec@1 87.000 (88.561) Prec@5 99.000 (99.235) +2022-11-14 17:04:54,245 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0729) Prec@1 83.000 (88.505) Prec@5 96.000 (99.202) +2022-11-14 17:04:54,253 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0729) Prec@1 89.000 (88.510) Prec@5 99.000 (99.200) +2022-11-14 17:04:54,309 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:04:54,630 Epoch: [457][0/500] Time 0.026 (0.026) Data 0.239 (0.239) Loss 0.0305 (0.0305) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:54,827 Epoch: [457][10/500] Time 0.015 (0.018) Data 0.001 (0.023) Loss 0.0218 (0.0262) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,013 Epoch: [457][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0266 (0.0263) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,203 Epoch: [457][30/500] Time 0.014 (0.017) Data 0.002 (0.009) Loss 0.0320 (0.0277) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,390 Epoch: [457][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0265 (0.0275) Prec@1 96.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,578 Epoch: [457][50/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0267 (0.0274) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,767 Epoch: [457][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0171 (0.0259) Prec@1 97.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 17:04:55,957 Epoch: [457][70/500] Time 0.019 (0.017) Data 0.001 (0.005) Loss 0.0216 (0.0254) Prec@1 98.000 (95.875) Prec@5 99.000 (99.875) +2022-11-14 17:04:56,148 Epoch: [457][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0393 (0.0269) Prec@1 94.000 (95.667) Prec@5 99.000 (99.778) +2022-11-14 17:04:56,336 Epoch: [457][90/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0289 (0.0271) Prec@1 95.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 17:04:56,524 Epoch: [457][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0340 (0.0277) Prec@1 94.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 17:04:56,713 Epoch: [457][110/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0105 (0.0263) Prec@1 98.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 17:04:56,900 Epoch: [457][120/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0406 (0.0274) Prec@1 95.000 (95.615) Prec@5 100.000 (99.846) +2022-11-14 17:04:57,089 Epoch: [457][130/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0131 (0.0264) Prec@1 98.000 (95.786) Prec@5 100.000 (99.857) +2022-11-14 17:04:57,278 Epoch: [457][140/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0389 (0.0272) Prec@1 91.000 (95.467) Prec@5 99.000 (99.800) +2022-11-14 17:04:57,465 Epoch: [457][150/500] Time 0.019 (0.017) Data 0.001 (0.003) Loss 0.0277 (0.0272) Prec@1 96.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 17:04:57,652 Epoch: [457][160/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0158 (0.0266) Prec@1 97.000 (95.588) Prec@5 100.000 (99.765) +2022-11-14 17:04:57,840 Epoch: [457][170/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0258 (0.0265) Prec@1 95.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 17:04:58,037 Epoch: [457][180/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0271 (0.0266) Prec@1 96.000 (95.579) Prec@5 100.000 (99.789) +2022-11-14 17:04:58,239 Epoch: [457][190/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0259 (0.0265) Prec@1 97.000 (95.650) Prec@5 100.000 (99.800) +2022-11-14 17:04:58,443 Epoch: [457][200/500] Time 0.022 (0.017) Data 0.001 (0.003) Loss 0.0233 (0.0264) Prec@1 97.000 (95.714) Prec@5 99.000 (99.762) +2022-11-14 17:04:58,649 Epoch: [457][210/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0219 (0.0262) Prec@1 94.000 (95.636) Prec@5 100.000 (99.773) +2022-11-14 17:04:58,858 Epoch: [457][220/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0541 (0.0274) Prec@1 89.000 (95.348) Prec@5 100.000 (99.783) +2022-11-14 17:04:59,068 Epoch: [457][230/500] Time 0.020 (0.017) Data 0.002 (0.003) Loss 0.0275 (0.0274) Prec@1 94.000 (95.292) Prec@5 100.000 (99.792) +2022-11-14 17:04:59,277 Epoch: [457][240/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0280 (0.0274) Prec@1 96.000 (95.320) Prec@5 100.000 (99.800) +2022-11-14 17:04:59,481 Epoch: [457][250/500] Time 0.021 (0.017) Data 0.001 (0.003) Loss 0.0472 (0.0282) Prec@1 91.000 (95.154) Prec@5 99.000 (99.769) +2022-11-14 17:04:59,688 Epoch: [457][260/500] Time 0.022 (0.017) Data 0.002 (0.002) Loss 0.0213 (0.0279) Prec@1 97.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 17:04:59,892 Epoch: [457][270/500] Time 0.020 (0.017) Data 0.001 (0.002) Loss 0.0391 (0.0283) Prec@1 95.000 (95.214) Prec@5 100.000 (99.786) +2022-11-14 17:05:00,104 Epoch: [457][280/500] Time 0.024 (0.017) Data 0.002 (0.002) Loss 0.0316 (0.0284) Prec@1 96.000 (95.241) Prec@5 100.000 (99.793) +2022-11-14 17:05:00,309 Epoch: [457][290/500] Time 0.020 (0.017) Data 0.001 (0.002) Loss 0.0338 (0.0286) Prec@1 94.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:05:00,515 Epoch: [457][300/500] Time 0.023 (0.017) Data 0.002 (0.002) Loss 0.0229 (0.0284) Prec@1 96.000 (95.226) Prec@5 100.000 (99.806) +2022-11-14 17:05:00,763 Epoch: [457][310/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0249 (0.0283) Prec@1 96.000 (95.250) Prec@5 100.000 (99.812) +2022-11-14 17:05:01,039 Epoch: [457][320/500] Time 0.030 (0.018) Data 0.002 (0.002) Loss 0.0260 (0.0282) Prec@1 95.000 (95.242) Prec@5 100.000 (99.818) +2022-11-14 17:05:01,306 Epoch: [457][330/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0408 (0.0286) Prec@1 93.000 (95.176) Prec@5 99.000 (99.794) +2022-11-14 17:05:01,576 Epoch: [457][340/500] Time 0.029 (0.018) Data 0.002 (0.002) Loss 0.0479 (0.0292) Prec@1 92.000 (95.086) Prec@5 100.000 (99.800) +2022-11-14 17:05:01,846 Epoch: [457][350/500] Time 0.024 (0.018) Data 0.002 (0.002) Loss 0.0322 (0.0292) Prec@1 95.000 (95.083) Prec@5 100.000 (99.806) +2022-11-14 17:05:02,124 Epoch: [457][360/500] Time 0.032 (0.018) Data 0.002 (0.002) Loss 0.0425 (0.0296) Prec@1 94.000 (95.054) Prec@5 100.000 (99.811) +2022-11-14 17:05:02,394 Epoch: [457][370/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0447 (0.0300) Prec@1 92.000 (94.974) Prec@5 100.000 (99.816) +2022-11-14 17:05:02,668 Epoch: [457][380/500] Time 0.030 (0.019) Data 0.002 (0.002) Loss 0.0388 (0.0302) Prec@1 93.000 (94.923) Prec@5 100.000 (99.821) +2022-11-14 17:05:02,941 Epoch: [457][390/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0211 (0.0300) Prec@1 98.000 (95.000) Prec@5 100.000 (99.825) +2022-11-14 17:05:03,212 Epoch: [457][400/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0198 (0.0297) Prec@1 96.000 (95.024) Prec@5 100.000 (99.829) +2022-11-14 17:05:03,480 Epoch: [457][410/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0229 (0.0296) Prec@1 96.000 (95.048) Prec@5 100.000 (99.833) +2022-11-14 17:05:03,745 Epoch: [457][420/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0515 (0.0301) Prec@1 91.000 (94.953) Prec@5 100.000 (99.837) +2022-11-14 17:05:04,015 Epoch: [457][430/500] Time 0.027 (0.019) Data 0.002 (0.002) Loss 0.0341 (0.0302) Prec@1 95.000 (94.955) Prec@5 100.000 (99.841) +2022-11-14 17:05:04,288 Epoch: [457][440/500] Time 0.029 (0.019) Data 0.002 (0.002) Loss 0.0224 (0.0300) Prec@1 96.000 (94.978) Prec@5 100.000 (99.844) +2022-11-14 17:05:04,557 Epoch: [457][450/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0332 (0.0301) Prec@1 95.000 (94.978) Prec@5 100.000 (99.848) +2022-11-14 17:05:04,827 Epoch: [457][460/500] Time 0.030 (0.020) Data 0.001 (0.002) Loss 0.0367 (0.0302) Prec@1 93.000 (94.936) Prec@5 100.000 (99.851) +2022-11-14 17:05:05,099 Epoch: [457][470/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0278 (0.0302) Prec@1 96.000 (94.958) Prec@5 100.000 (99.854) +2022-11-14 17:05:05,367 Epoch: [457][480/500] Time 0.029 (0.020) Data 0.001 (0.002) Loss 0.0408 (0.0304) Prec@1 94.000 (94.939) Prec@5 100.000 (99.857) +2022-11-14 17:05:05,642 Epoch: [457][490/500] Time 0.025 (0.020) Data 0.003 (0.002) Loss 0.0400 (0.0306) Prec@1 95.000 (94.940) Prec@5 100.000 (99.860) +2022-11-14 17:05:05,888 Epoch: [457][499/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0176 (0.0303) Prec@1 97.000 (94.980) Prec@5 100.000 (99.863) +2022-11-14 17:05:06,178 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0755 (0.0755) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:06,189 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0819 (0.0787) Prec@1 87.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:06,199 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0804 (0.0793) Prec@1 87.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:05:06,209 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0712 (0.0773) Prec@1 87.000 (87.500) Prec@5 98.000 (99.500) +2022-11-14 17:05:06,216 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0671 (0.0752) Prec@1 89.000 (87.800) Prec@5 100.000 (99.600) +2022-11-14 17:05:06,226 Test: [5/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0251 (0.0669) Prec@1 95.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 17:05:06,235 Test: [6/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0617 (0.0661) Prec@1 92.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 17:05:06,244 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0675) Prec@1 86.000 (89.000) Prec@5 100.000 (99.750) +2022-11-14 17:05:06,251 Test: [8/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0868 (0.0697) Prec@1 89.000 (89.000) Prec@5 100.000 (99.778) +2022-11-14 17:05:06,261 Test: [9/100] Model Time 0.009 (0.008) Loss Time 0.000 (0.000) Loss 0.0793 (0.0706) Prec@1 89.000 (89.000) Prec@5 99.000 (99.700) +2022-11-14 17:05:06,272 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0621 (0.0698) Prec@1 89.000 (89.000) Prec@5 99.000 (99.636) +2022-11-14 17:05:06,280 Test: [11/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0783 (0.0705) Prec@1 88.000 (88.917) Prec@5 100.000 (99.667) +2022-11-14 17:05:06,288 Test: [12/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0340 (0.0677) Prec@1 96.000 (89.462) Prec@5 100.000 (99.692) +2022-11-14 17:05:06,298 Test: [13/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0819 (0.0687) Prec@1 88.000 (89.357) Prec@5 100.000 (99.714) +2022-11-14 17:05:06,308 Test: [14/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0918 (0.0703) Prec@1 85.000 (89.067) Prec@5 100.000 (99.733) +2022-11-14 17:05:06,316 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0710) Prec@1 87.000 (88.938) Prec@5 98.000 (99.625) +2022-11-14 17:05:06,323 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0593 (0.0704) Prec@1 90.000 (89.000) Prec@5 98.000 (99.529) +2022-11-14 17:05:06,333 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0996 (0.0720) Prec@1 85.000 (88.778) Prec@5 100.000 (99.556) +2022-11-14 17:05:06,343 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0726) Prec@1 86.000 (88.632) Prec@5 99.000 (99.526) +2022-11-14 17:05:06,351 Test: [19/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0737) Prec@1 87.000 (88.550) Prec@5 97.000 (99.400) +2022-11-14 17:05:06,358 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0740) Prec@1 86.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 17:05:06,368 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0740) Prec@1 90.000 (88.500) Prec@5 98.000 (99.364) +2022-11-14 17:05:06,379 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1030 (0.0752) Prec@1 85.000 (88.348) Prec@5 97.000 (99.261) +2022-11-14 17:05:06,386 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0754) Prec@1 88.000 (88.333) Prec@5 100.000 (99.292) +2022-11-14 17:05:06,394 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0749) Prec@1 90.000 (88.400) Prec@5 100.000 (99.320) +2022-11-14 17:05:06,404 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0946 (0.0757) Prec@1 87.000 (88.346) Prec@5 98.000 (99.269) +2022-11-14 17:05:06,414 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0749) Prec@1 93.000 (88.519) Prec@5 100.000 (99.296) +2022-11-14 17:05:06,421 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0746) Prec@1 89.000 (88.536) Prec@5 100.000 (99.321) +2022-11-14 17:05:06,429 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0743) Prec@1 88.000 (88.517) Prec@5 99.000 (99.310) +2022-11-14 17:05:06,439 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0742) Prec@1 88.000 (88.500) Prec@5 99.000 (99.300) +2022-11-14 17:05:06,449 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0742) Prec@1 89.000 (88.516) Prec@5 100.000 (99.323) +2022-11-14 17:05:06,456 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0743) Prec@1 89.000 (88.531) Prec@5 98.000 (99.281) +2022-11-14 17:05:06,464 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0744) Prec@1 83.000 (88.364) Prec@5 100.000 (99.303) +2022-11-14 17:05:06,474 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0734 (0.0744) Prec@1 87.000 (88.324) Prec@5 99.000 (99.294) +2022-11-14 17:05:06,484 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0743) Prec@1 89.000 (88.343) Prec@5 97.000 (99.229) +2022-11-14 17:05:06,491 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0741) Prec@1 90.000 (88.389) Prec@5 100.000 (99.250) +2022-11-14 17:05:06,499 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0644 (0.0738) Prec@1 91.000 (88.459) Prec@5 99.000 (99.243) +2022-11-14 17:05:06,509 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0953 (0.0744) Prec@1 85.000 (88.368) Prec@5 100.000 (99.263) +2022-11-14 17:05:06,519 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0639 (0.0741) Prec@1 91.000 (88.436) Prec@5 99.000 (99.256) +2022-11-14 17:05:06,526 Test: [39/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0547 (0.0736) Prec@1 93.000 (88.550) Prec@5 99.000 (99.250) +2022-11-14 17:05:06,534 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0741) Prec@1 85.000 (88.463) Prec@5 99.000 (99.244) +2022-11-14 17:05:06,544 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0740) Prec@1 91.000 (88.524) Prec@5 100.000 (99.262) +2022-11-14 17:05:06,555 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0736) Prec@1 92.000 (88.605) Prec@5 100.000 (99.279) +2022-11-14 17:05:06,562 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0734) Prec@1 91.000 (88.659) Prec@5 98.000 (99.250) +2022-11-14 17:05:06,570 Test: [44/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0569 (0.0730) Prec@1 90.000 (88.689) Prec@5 100.000 (99.267) +2022-11-14 17:05:06,580 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1018 (0.0736) Prec@1 83.000 (88.565) Prec@5 100.000 (99.283) +2022-11-14 17:05:06,590 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0734) Prec@1 91.000 (88.617) Prec@5 100.000 (99.298) +2022-11-14 17:05:06,598 Test: [47/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0736) Prec@1 88.000 (88.604) Prec@5 99.000 (99.292) +2022-11-14 17:05:06,606 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0541 (0.0732) Prec@1 90.000 (88.633) Prec@5 100.000 (99.306) +2022-11-14 17:05:06,616 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0998 (0.0737) Prec@1 82.000 (88.500) Prec@5 100.000 (99.320) +2022-11-14 17:05:06,625 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0627 (0.0735) Prec@1 91.000 (88.549) Prec@5 99.000 (99.314) +2022-11-14 17:05:06,633 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0736) Prec@1 89.000 (88.558) Prec@5 99.000 (99.308) +2022-11-14 17:05:06,640 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0736) Prec@1 87.000 (88.528) Prec@5 99.000 (99.302) +2022-11-14 17:05:06,652 Test: [53/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0738) Prec@1 89.000 (88.537) Prec@5 98.000 (99.278) +2022-11-14 17:05:06,662 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0739) Prec@1 88.000 (88.527) Prec@5 100.000 (99.291) +2022-11-14 17:05:06,669 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0738) Prec@1 87.000 (88.500) Prec@5 99.000 (99.286) +2022-11-14 17:05:06,677 Test: [56/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0738) Prec@1 86.000 (88.456) Prec@5 100.000 (99.298) +2022-11-14 17:05:06,684 Test: [57/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0737) Prec@1 90.000 (88.483) Prec@5 100.000 (99.310) +2022-11-14 17:05:06,692 Test: [58/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0740) Prec@1 85.000 (88.424) Prec@5 100.000 (99.322) +2022-11-14 17:05:06,699 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0741) Prec@1 85.000 (88.367) Prec@5 99.000 (99.317) +2022-11-14 17:05:06,707 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0744) Prec@1 88.000 (88.361) Prec@5 98.000 (99.295) +2022-11-14 17:05:06,715 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0605 (0.0741) Prec@1 89.000 (88.371) Prec@5 100.000 (99.306) +2022-11-14 17:05:06,722 Test: [62/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0741) Prec@1 85.000 (88.317) Prec@5 100.000 (99.317) +2022-11-14 17:05:06,730 Test: [63/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0420 (0.0736) Prec@1 93.000 (88.391) Prec@5 100.000 (99.328) +2022-11-14 17:05:06,737 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0738) Prec@1 87.000 (88.369) Prec@5 100.000 (99.338) +2022-11-14 17:05:06,745 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0736) Prec@1 90.000 (88.394) Prec@5 99.000 (99.333) +2022-11-14 17:05:06,752 Test: [66/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0389 (0.0731) Prec@1 94.000 (88.478) Prec@5 100.000 (99.343) +2022-11-14 17:05:06,760 Test: [67/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0731) Prec@1 90.000 (88.500) Prec@5 98.000 (99.324) +2022-11-14 17:05:06,767 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0733) Prec@1 85.000 (88.449) Prec@5 100.000 (99.333) +2022-11-14 17:05:06,775 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0674 (0.0732) Prec@1 90.000 (88.471) Prec@5 99.000 (99.329) +2022-11-14 17:05:06,782 Test: [70/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0735) Prec@1 87.000 (88.451) Prec@5 99.000 (99.324) +2022-11-14 17:05:06,790 Test: [71/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0563 (0.0733) Prec@1 92.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 17:05:06,797 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0728) Prec@1 93.000 (88.562) Prec@5 100.000 (99.342) +2022-11-14 17:05:06,805 Test: [73/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0377 (0.0724) Prec@1 94.000 (88.635) Prec@5 100.000 (99.351) +2022-11-14 17:05:06,812 Test: [74/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0726) Prec@1 86.000 (88.600) Prec@5 99.000 (99.347) +2022-11-14 17:05:06,820 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0727) Prec@1 89.000 (88.605) Prec@5 100.000 (99.355) +2022-11-14 17:05:06,827 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0727) Prec@1 89.000 (88.610) Prec@5 100.000 (99.364) +2022-11-14 17:05:06,835 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0727) Prec@1 88.000 (88.603) Prec@5 98.000 (99.346) +2022-11-14 17:05:06,842 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0729) Prec@1 87.000 (88.582) Prec@5 100.000 (99.354) +2022-11-14 17:05:06,850 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0728) Prec@1 89.000 (88.588) Prec@5 100.000 (99.362) +2022-11-14 17:05:06,857 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0729) Prec@1 87.000 (88.568) Prec@5 97.000 (99.333) +2022-11-14 17:05:06,865 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0728) Prec@1 90.000 (88.585) Prec@5 100.000 (99.341) +2022-11-14 17:05:06,873 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0730) Prec@1 86.000 (88.554) Prec@5 99.000 (99.337) +2022-11-14 17:05:06,881 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0728) Prec@1 90.000 (88.571) Prec@5 100.000 (99.345) +2022-11-14 17:05:06,889 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0731) Prec@1 83.000 (88.506) Prec@5 100.000 (99.353) +2022-11-14 17:05:06,896 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1244 (0.0737) Prec@1 81.000 (88.419) Prec@5 100.000 (99.360) +2022-11-14 17:05:06,904 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0736) Prec@1 87.000 (88.402) Prec@5 100.000 (99.368) +2022-11-14 17:05:06,912 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1114 (0.0741) Prec@1 80.000 (88.307) Prec@5 98.000 (99.352) +2022-11-14 17:05:06,919 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0743) Prec@1 83.000 (88.247) Prec@5 100.000 (99.360) +2022-11-14 17:05:06,927 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0743) Prec@1 88.000 (88.244) Prec@5 98.000 (99.344) +2022-11-14 17:05:06,934 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0741) Prec@1 91.000 (88.275) Prec@5 99.000 (99.341) +2022-11-14 17:05:06,942 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0519 (0.0738) Prec@1 93.000 (88.326) Prec@5 98.000 (99.326) +2022-11-14 17:05:06,949 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0739) Prec@1 89.000 (88.333) Prec@5 99.000 (99.323) +2022-11-14 17:05:06,957 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0740) Prec@1 88.000 (88.330) Prec@5 99.000 (99.319) +2022-11-14 17:05:06,964 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0740) Prec@1 87.000 (88.316) Prec@5 100.000 (99.326) +2022-11-14 17:05:06,972 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0738) Prec@1 93.000 (88.365) Prec@5 100.000 (99.333) +2022-11-14 17:05:06,979 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0452 (0.0735) Prec@1 94.000 (88.423) Prec@5 98.000 (99.320) +2022-11-14 17:05:06,986 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0736) Prec@1 89.000 (88.429) Prec@5 98.000 (99.306) +2022-11-14 17:05:06,994 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0738) Prec@1 86.000 (88.404) Prec@5 100.000 (99.313) +2022-11-14 17:05:07,001 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0737) Prec@1 89.000 (88.410) Prec@5 99.000 (99.310) +2022-11-14 17:05:07,054 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:05:07,376 Epoch: [458][0/500] Time 0.031 (0.031) Data 0.236 (0.236) Loss 0.0172 (0.0172) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:07,581 Epoch: [458][10/500] Time 0.017 (0.019) Data 0.001 (0.023) Loss 0.0455 (0.0313) Prec@1 92.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:07,777 Epoch: [458][20/500] Time 0.020 (0.018) Data 0.002 (0.013) Loss 0.0157 (0.0261) Prec@1 99.000 (96.000) Prec@5 99.000 (99.667) +2022-11-14 17:05:07,973 Epoch: [458][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0421 (0.0301) Prec@1 93.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 17:05:08,170 Epoch: [458][40/500] Time 0.020 (0.018) Data 0.002 (0.007) Loss 0.0356 (0.0312) Prec@1 94.000 (95.000) Prec@5 99.000 (99.600) +2022-11-14 17:05:08,365 Epoch: [458][50/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0481 (0.0340) Prec@1 92.000 (94.500) Prec@5 100.000 (99.667) +2022-11-14 17:05:08,562 Epoch: [458][60/500] Time 0.020 (0.018) Data 0.002 (0.005) Loss 0.0379 (0.0346) Prec@1 93.000 (94.286) Prec@5 100.000 (99.714) +2022-11-14 17:05:08,755 Epoch: [458][70/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0222 (0.0330) Prec@1 97.000 (94.625) Prec@5 99.000 (99.625) +2022-11-14 17:05:08,950 Epoch: [458][80/500] Time 0.022 (0.018) Data 0.001 (0.005) Loss 0.0426 (0.0341) Prec@1 93.000 (94.444) Prec@5 100.000 (99.667) +2022-11-14 17:05:09,147 Epoch: [458][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0380 (0.0345) Prec@1 95.000 (94.500) Prec@5 100.000 (99.700) +2022-11-14 17:05:09,340 Epoch: [458][100/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0188 (0.0331) Prec@1 97.000 (94.727) Prec@5 100.000 (99.727) +2022-11-14 17:05:09,530 Epoch: [458][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0342 (0.0332) Prec@1 94.000 (94.667) Prec@5 100.000 (99.750) +2022-11-14 17:05:09,722 Epoch: [458][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0233 (0.0324) Prec@1 95.000 (94.692) Prec@5 100.000 (99.769) +2022-11-14 17:05:09,914 Epoch: [458][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0193 (0.0315) Prec@1 96.000 (94.786) Prec@5 100.000 (99.786) +2022-11-14 17:05:10,193 Epoch: [458][140/500] Time 0.026 (0.018) Data 0.003 (0.003) Loss 0.0465 (0.0325) Prec@1 92.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 17:05:10,521 Epoch: [458][150/500] Time 0.032 (0.019) Data 0.002 (0.003) Loss 0.0395 (0.0329) Prec@1 93.000 (94.500) Prec@5 99.000 (99.750) +2022-11-14 17:05:10,859 Epoch: [458][160/500] Time 0.032 (0.019) Data 0.002 (0.003) Loss 0.0198 (0.0321) Prec@1 97.000 (94.647) Prec@5 100.000 (99.765) +2022-11-14 17:05:11,193 Epoch: [458][170/500] Time 0.032 (0.020) Data 0.002 (0.003) Loss 0.0207 (0.0315) Prec@1 97.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 17:05:11,523 Epoch: [458][180/500] Time 0.031 (0.020) Data 0.001 (0.003) Loss 0.0217 (0.0310) Prec@1 96.000 (94.842) Prec@5 100.000 (99.789) +2022-11-14 17:05:11,849 Epoch: [458][190/500] Time 0.031 (0.021) Data 0.002 (0.003) Loss 0.0128 (0.0301) Prec@1 98.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 17:05:12,180 Epoch: [458][200/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0314 (0.0301) Prec@1 94.000 (94.952) Prec@5 100.000 (99.810) +2022-11-14 17:05:12,503 Epoch: [458][210/500] Time 0.031 (0.022) Data 0.002 (0.003) Loss 0.0235 (0.0298) Prec@1 95.000 (94.955) Prec@5 100.000 (99.818) +2022-11-14 17:05:12,829 Epoch: [458][220/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0180 (0.0293) Prec@1 97.000 (95.043) Prec@5 100.000 (99.826) +2022-11-14 17:05:13,155 Epoch: [458][230/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0362 (0.0296) Prec@1 94.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:05:13,468 Epoch: [458][240/500] Time 0.029 (0.022) Data 0.002 (0.003) Loss 0.0208 (0.0293) Prec@1 96.000 (95.040) Prec@5 100.000 (99.840) +2022-11-14 17:05:13,789 Epoch: [458][250/500] Time 0.032 (0.023) Data 0.002 (0.003) Loss 0.0262 (0.0291) Prec@1 97.000 (95.115) Prec@5 98.000 (99.769) +2022-11-14 17:05:14,113 Epoch: [458][260/500] Time 0.032 (0.023) Data 0.002 (0.003) Loss 0.0293 (0.0291) Prec@1 92.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 17:05:14,424 Epoch: [458][270/500] Time 0.030 (0.023) Data 0.002 (0.003) Loss 0.0391 (0.0295) Prec@1 93.000 (94.929) Prec@5 100.000 (99.786) +2022-11-14 17:05:14,739 Epoch: [458][280/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0349 (0.0297) Prec@1 96.000 (94.966) Prec@5 99.000 (99.759) +2022-11-14 17:05:15,063 Epoch: [458][290/500] Time 0.031 (0.023) Data 0.002 (0.003) Loss 0.0385 (0.0300) Prec@1 96.000 (95.000) Prec@5 100.000 (99.767) +2022-11-14 17:05:15,388 Epoch: [458][300/500] Time 0.031 (0.024) Data 0.002 (0.003) Loss 0.0296 (0.0300) Prec@1 95.000 (95.000) Prec@5 100.000 (99.774) +2022-11-14 17:05:15,711 Epoch: [458][310/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0383 (0.0302) Prec@1 92.000 (94.906) Prec@5 99.000 (99.750) +2022-11-14 17:05:16,000 Epoch: [458][320/500] Time 0.022 (0.024) Data 0.002 (0.002) Loss 0.0151 (0.0298) Prec@1 98.000 (95.000) Prec@5 100.000 (99.758) +2022-11-14 17:05:16,220 Epoch: [458][330/500] Time 0.020 (0.024) Data 0.003 (0.002) Loss 0.0372 (0.0300) Prec@1 93.000 (94.941) Prec@5 100.000 (99.765) +2022-11-14 17:05:16,430 Epoch: [458][340/500] Time 0.018 (0.024) Data 0.002 (0.002) Loss 0.0411 (0.0303) Prec@1 93.000 (94.886) Prec@5 100.000 (99.771) +2022-11-14 17:05:16,637 Epoch: [458][350/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0538 (0.0310) Prec@1 91.000 (94.778) Prec@5 100.000 (99.778) +2022-11-14 17:05:16,846 Epoch: [458][360/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0411 (0.0312) Prec@1 94.000 (94.757) Prec@5 100.000 (99.784) +2022-11-14 17:05:17,055 Epoch: [458][370/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0213 (0.0310) Prec@1 98.000 (94.842) Prec@5 100.000 (99.789) +2022-11-14 17:05:17,266 Epoch: [458][380/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0299 (0.0309) Prec@1 96.000 (94.872) Prec@5 100.000 (99.795) +2022-11-14 17:05:17,476 Epoch: [458][390/500] Time 0.019 (0.023) Data 0.001 (0.002) Loss 0.0258 (0.0308) Prec@1 95.000 (94.875) Prec@5 100.000 (99.800) +2022-11-14 17:05:17,685 Epoch: [458][400/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0325 (0.0309) Prec@1 93.000 (94.829) Prec@5 100.000 (99.805) +2022-11-14 17:05:17,895 Epoch: [458][410/500] Time 0.020 (0.023) Data 0.001 (0.002) Loss 0.0169 (0.0305) Prec@1 97.000 (94.881) Prec@5 100.000 (99.810) +2022-11-14 17:05:18,109 Epoch: [458][420/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0181 (0.0302) Prec@1 97.000 (94.930) Prec@5 100.000 (99.814) +2022-11-14 17:05:18,320 Epoch: [458][430/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0232 (0.0301) Prec@1 98.000 (95.000) Prec@5 100.000 (99.818) +2022-11-14 17:05:18,527 Epoch: [458][440/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0176 (0.0298) Prec@1 97.000 (95.044) Prec@5 100.000 (99.822) +2022-11-14 17:05:18,737 Epoch: [458][450/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0249 (0.0297) Prec@1 95.000 (95.043) Prec@5 100.000 (99.826) +2022-11-14 17:05:18,950 Epoch: [458][460/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0426 (0.0300) Prec@1 92.000 (94.979) Prec@5 100.000 (99.830) +2022-11-14 17:05:19,168 Epoch: [458][470/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0317 (0.0300) Prec@1 96.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:05:19,378 Epoch: [458][480/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0120 (0.0296) Prec@1 98.000 (95.061) Prec@5 100.000 (99.837) +2022-11-14 17:05:19,590 Epoch: [458][490/500] Time 0.019 (0.022) Data 0.002 (0.002) Loss 0.0278 (0.0296) Prec@1 94.000 (95.040) Prec@5 100.000 (99.840) +2022-11-14 17:05:19,780 Epoch: [458][499/500] Time 0.020 (0.022) Data 0.001 (0.002) Loss 0.0254 (0.0295) Prec@1 97.000 (95.078) Prec@5 100.000 (99.843) +2022-11-14 17:05:20,072 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0616 (0.0616) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:20,084 Test: [1/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0780 (0.0698) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:20,094 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0534 (0.0643) Prec@1 91.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:05:20,104 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0643 (0.0643) Prec@1 90.000 (89.750) Prec@5 100.000 (100.000) +2022-11-14 17:05:20,111 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0681) Prec@1 85.000 (88.800) Prec@5 99.000 (99.800) +2022-11-14 17:05:20,120 Test: [5/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0431 (0.0640) Prec@1 93.000 (89.500) Prec@5 100.000 (99.833) +2022-11-14 17:05:20,127 Test: [6/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0667 (0.0644) Prec@1 90.000 (89.571) Prec@5 100.000 (99.857) +2022-11-14 17:05:20,135 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0669) Prec@1 85.000 (89.000) Prec@5 99.000 (99.750) +2022-11-14 17:05:20,142 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0671) Prec@1 89.000 (89.000) Prec@5 100.000 (99.778) +2022-11-14 17:05:20,150 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0773 (0.0681) Prec@1 89.000 (89.000) Prec@5 99.000 (99.700) +2022-11-14 17:05:20,158 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0403 (0.0656) Prec@1 94.000 (89.455) Prec@5 99.000 (99.636) +2022-11-14 17:05:20,165 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0681) Prec@1 89.000 (89.417) Prec@5 100.000 (99.667) +2022-11-14 17:05:20,173 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0587 (0.0674) Prec@1 90.000 (89.462) Prec@5 100.000 (99.692) +2022-11-14 17:05:20,181 Test: [13/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0719 (0.0677) Prec@1 87.000 (89.286) Prec@5 99.000 (99.643) +2022-11-14 17:05:20,188 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0684) Prec@1 86.000 (89.067) Prec@5 100.000 (99.667) +2022-11-14 17:05:20,196 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0743 (0.0688) Prec@1 88.000 (89.000) Prec@5 100.000 (99.688) +2022-11-14 17:05:20,204 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0683) Prec@1 90.000 (89.059) Prec@5 99.000 (99.647) +2022-11-14 17:05:20,215 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0942 (0.0698) Prec@1 84.000 (88.778) Prec@5 100.000 (99.667) +2022-11-14 17:05:20,225 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0702) Prec@1 89.000 (88.789) Prec@5 99.000 (99.632) +2022-11-14 17:05:20,234 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0867 (0.0710) Prec@1 85.000 (88.600) Prec@5 97.000 (99.500) +2022-11-14 17:05:20,241 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0709) Prec@1 89.000 (88.619) Prec@5 100.000 (99.524) +2022-11-14 17:05:20,252 Test: [21/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0872 (0.0716) Prec@1 88.000 (88.591) Prec@5 98.000 (99.455) +2022-11-14 17:05:20,263 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0882 (0.0723) Prec@1 87.000 (88.522) Prec@5 98.000 (99.391) +2022-11-14 17:05:20,271 Test: [23/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0721) Prec@1 90.000 (88.583) Prec@5 100.000 (99.417) +2022-11-14 17:05:20,279 Test: [24/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1049 (0.0734) Prec@1 82.000 (88.320) Prec@5 100.000 (99.440) +2022-11-14 17:05:20,289 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0738) Prec@1 84.000 (88.154) Prec@5 99.000 (99.423) +2022-11-14 17:05:20,299 Test: [26/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0731) Prec@1 92.000 (88.296) Prec@5 100.000 (99.444) +2022-11-14 17:05:20,306 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0543 (0.0725) Prec@1 91.000 (88.393) Prec@5 100.000 (99.464) +2022-11-14 17:05:20,314 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0721 (0.0725) Prec@1 88.000 (88.379) Prec@5 98.000 (99.414) +2022-11-14 17:05:20,322 Test: [29/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0685 (0.0723) Prec@1 90.000 (88.433) Prec@5 99.000 (99.400) +2022-11-14 17:05:20,329 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0724) Prec@1 88.000 (88.419) Prec@5 99.000 (99.387) +2022-11-14 17:05:20,337 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0726) Prec@1 89.000 (88.438) Prec@5 99.000 (99.375) +2022-11-14 17:05:20,345 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0862 (0.0730) Prec@1 88.000 (88.424) Prec@5 99.000 (99.364) +2022-11-14 17:05:20,353 Test: [33/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0735) Prec@1 84.000 (88.294) Prec@5 98.000 (99.324) +2022-11-14 17:05:20,360 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0869 (0.0739) Prec@1 86.000 (88.229) Prec@5 98.000 (99.286) +2022-11-14 17:05:20,368 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0739) Prec@1 89.000 (88.250) Prec@5 100.000 (99.306) +2022-11-14 17:05:20,376 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0739) Prec@1 85.000 (88.162) Prec@5 98.000 (99.270) +2022-11-14 17:05:20,384 Test: [37/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0743) Prec@1 87.000 (88.132) Prec@5 99.000 (99.263) +2022-11-14 17:05:20,392 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0738) Prec@1 94.000 (88.282) Prec@5 99.000 (99.256) +2022-11-14 17:05:20,400 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0741) Prec@1 86.000 (88.225) Prec@5 98.000 (99.225) +2022-11-14 17:05:20,408 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0744) Prec@1 85.000 (88.146) Prec@5 99.000 (99.220) +2022-11-14 17:05:20,416 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0741) Prec@1 90.000 (88.190) Prec@5 99.000 (99.214) +2022-11-14 17:05:20,424 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0404 (0.0733) Prec@1 95.000 (88.349) Prec@5 99.000 (99.209) +2022-11-14 17:05:20,431 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0731) Prec@1 92.000 (88.432) Prec@5 99.000 (99.205) +2022-11-14 17:05:20,440 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0729) Prec@1 90.000 (88.467) Prec@5 100.000 (99.222) +2022-11-14 17:05:20,447 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0731) Prec@1 88.000 (88.457) Prec@5 99.000 (99.217) +2022-11-14 17:05:20,455 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0731) Prec@1 85.000 (88.383) Prec@5 100.000 (99.234) +2022-11-14 17:05:20,463 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0734) Prec@1 86.000 (88.333) Prec@5 98.000 (99.208) +2022-11-14 17:05:20,471 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0731) Prec@1 91.000 (88.388) Prec@5 99.000 (99.204) +2022-11-14 17:05:20,479 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0740) Prec@1 82.000 (88.260) Prec@5 100.000 (99.220) +2022-11-14 17:05:20,487 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0737) Prec@1 90.000 (88.294) Prec@5 99.000 (99.216) +2022-11-14 17:05:20,495 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0736) Prec@1 90.000 (88.327) Prec@5 99.000 (99.212) +2022-11-14 17:05:20,503 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0735) Prec@1 90.000 (88.358) Prec@5 99.000 (99.208) +2022-11-14 17:05:20,510 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0734) Prec@1 89.000 (88.370) Prec@5 99.000 (99.204) +2022-11-14 17:05:20,518 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0735) Prec@1 87.000 (88.345) Prec@5 100.000 (99.218) +2022-11-14 17:05:20,526 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0735) Prec@1 88.000 (88.339) Prec@5 99.000 (99.214) +2022-11-14 17:05:20,533 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0735) Prec@1 86.000 (88.298) Prec@5 100.000 (99.228) +2022-11-14 17:05:20,541 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0734) Prec@1 90.000 (88.328) Prec@5 100.000 (99.241) +2022-11-14 17:05:20,549 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0739) Prec@1 86.000 (88.288) Prec@5 100.000 (99.254) +2022-11-14 17:05:20,557 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0739) Prec@1 87.000 (88.267) Prec@5 99.000 (99.250) +2022-11-14 17:05:20,565 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0741) Prec@1 87.000 (88.246) Prec@5 100.000 (99.262) +2022-11-14 17:05:20,572 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0739) Prec@1 90.000 (88.274) Prec@5 100.000 (99.274) +2022-11-14 17:05:20,580 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0736) Prec@1 92.000 (88.333) Prec@5 100.000 (99.286) +2022-11-14 17:05:20,588 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0732) Prec@1 90.000 (88.359) Prec@5 100.000 (99.297) +2022-11-14 17:05:20,596 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0737) Prec@1 85.000 (88.308) Prec@5 98.000 (99.277) +2022-11-14 17:05:20,604 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0737) Prec@1 87.000 (88.288) Prec@5 99.000 (99.273) +2022-11-14 17:05:20,612 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0733) Prec@1 92.000 (88.343) Prec@5 99.000 (99.269) +2022-11-14 17:05:20,620 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0733) Prec@1 89.000 (88.353) Prec@5 99.000 (99.265) +2022-11-14 17:05:20,628 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0731) Prec@1 92.000 (88.406) Prec@5 100.000 (99.275) +2022-11-14 17:05:20,635 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0732) Prec@1 86.000 (88.371) Prec@5 99.000 (99.271) +2022-11-14 17:05:20,643 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0736) Prec@1 87.000 (88.352) Prec@5 98.000 (99.254) +2022-11-14 17:05:20,651 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0733) Prec@1 92.000 (88.403) Prec@5 100.000 (99.264) +2022-11-14 17:05:20,659 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0731) Prec@1 91.000 (88.438) Prec@5 99.000 (99.260) +2022-11-14 17:05:20,667 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0363 (0.0726) Prec@1 93.000 (88.500) Prec@5 100.000 (99.270) +2022-11-14 17:05:20,675 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0728) Prec@1 86.000 (88.467) Prec@5 99.000 (99.267) +2022-11-14 17:05:20,683 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0727) Prec@1 91.000 (88.500) Prec@5 100.000 (99.276) +2022-11-14 17:05:20,691 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0725) Prec@1 91.000 (88.532) Prec@5 99.000 (99.273) +2022-11-14 17:05:20,699 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0726) Prec@1 88.000 (88.526) Prec@5 98.000 (99.256) +2022-11-14 17:05:20,707 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0724) Prec@1 90.000 (88.544) Prec@5 100.000 (99.266) +2022-11-14 17:05:20,715 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0725) Prec@1 86.000 (88.513) Prec@5 99.000 (99.263) +2022-11-14 17:05:20,722 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0726) Prec@1 88.000 (88.506) Prec@5 97.000 (99.235) +2022-11-14 17:05:20,731 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0726) Prec@1 90.000 (88.524) Prec@5 99.000 (99.232) +2022-11-14 17:05:20,739 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0728) Prec@1 86.000 (88.494) Prec@5 100.000 (99.241) +2022-11-14 17:05:20,747 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0728) Prec@1 88.000 (88.488) Prec@5 100.000 (99.250) +2022-11-14 17:05:20,755 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0730) Prec@1 86.000 (88.459) Prec@5 99.000 (99.247) +2022-11-14 17:05:20,762 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0732) Prec@1 87.000 (88.442) Prec@5 99.000 (99.244) +2022-11-14 17:05:20,770 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0731) Prec@1 91.000 (88.471) Prec@5 99.000 (99.241) +2022-11-14 17:05:20,777 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0729) Prec@1 90.000 (88.489) Prec@5 99.000 (99.239) +2022-11-14 17:05:20,785 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0728) Prec@1 91.000 (88.517) Prec@5 100.000 (99.247) +2022-11-14 17:05:20,793 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0801 (0.0729) Prec@1 88.000 (88.511) Prec@5 99.000 (99.244) +2022-11-14 17:05:20,801 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0727) Prec@1 92.000 (88.549) Prec@5 100.000 (99.253) +2022-11-14 17:05:20,808 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0726) Prec@1 89.000 (88.554) Prec@5 99.000 (99.250) +2022-11-14 17:05:20,816 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0727) Prec@1 86.000 (88.527) Prec@5 98.000 (99.237) +2022-11-14 17:05:20,824 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0726) Prec@1 90.000 (88.543) Prec@5 98.000 (99.223) +2022-11-14 17:05:20,831 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0728) Prec@1 88.000 (88.537) Prec@5 99.000 (99.221) +2022-11-14 17:05:20,839 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0453 (0.0725) Prec@1 93.000 (88.583) Prec@5 99.000 (99.219) +2022-11-14 17:05:20,846 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0722) Prec@1 93.000 (88.629) Prec@5 99.000 (99.216) +2022-11-14 17:05:20,854 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0724) Prec@1 89.000 (88.633) Prec@5 100.000 (99.224) +2022-11-14 17:05:20,861 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1162 (0.0728) Prec@1 83.000 (88.576) Prec@5 99.000 (99.222) +2022-11-14 17:05:20,869 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0728) Prec@1 89.000 (88.580) Prec@5 100.000 (99.230) +2022-11-14 17:05:20,922 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:05:21,237 Epoch: [459][0/500] Time 0.024 (0.024) Data 0.238 (0.238) Loss 0.0248 (0.0248) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:21,457 Epoch: [459][10/500] Time 0.021 (0.020) Data 0.002 (0.023) Loss 0.0244 (0.0246) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:21,651 Epoch: [459][20/500] Time 0.016 (0.018) Data 0.002 (0.013) Loss 0.0237 (0.0243) Prec@1 96.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:05:21,848 Epoch: [459][30/500] Time 0.022 (0.018) Data 0.001 (0.009) Loss 0.0235 (0.0241) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:22,043 Epoch: [459][40/500] Time 0.017 (0.018) Data 0.002 (0.007) Loss 0.0346 (0.0262) Prec@1 93.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:05:22,244 Epoch: [459][50/500] Time 0.022 (0.018) Data 0.001 (0.006) Loss 0.0313 (0.0271) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:22,444 Epoch: [459][60/500] Time 0.019 (0.018) Data 0.002 (0.006) Loss 0.0152 (0.0254) Prec@1 97.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 17:05:22,634 Epoch: [459][70/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0230 (0.0251) Prec@1 97.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 17:05:22,820 Epoch: [459][80/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0175 (0.0242) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,021 Epoch: [459][90/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0299 (0.0248) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,210 Epoch: [459][100/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0603 (0.0280) Prec@1 89.000 (95.364) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,397 Epoch: [459][110/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0167 (0.0271) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,583 Epoch: [459][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0307 (0.0274) Prec@1 95.000 (95.462) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,769 Epoch: [459][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0154 (0.0265) Prec@1 97.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 17:05:23,977 Epoch: [459][140/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0175 (0.0259) Prec@1 98.000 (95.733) Prec@5 100.000 (100.000) +2022-11-14 17:05:24,236 Epoch: [459][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0193 (0.0255) Prec@1 97.000 (95.812) Prec@5 100.000 (100.000) +2022-11-14 17:05:24,500 Epoch: [459][160/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0287 (0.0257) Prec@1 95.000 (95.765) Prec@5 100.000 (100.000) +2022-11-14 17:05:24,762 Epoch: [459][170/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0411 (0.0265) Prec@1 92.000 (95.556) Prec@5 99.000 (99.944) +2022-11-14 17:05:25,022 Epoch: [459][180/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0176 (0.0261) Prec@1 97.000 (95.632) Prec@5 100.000 (99.947) +2022-11-14 17:05:25,286 Epoch: [459][190/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0232 (0.0259) Prec@1 96.000 (95.650) Prec@5 100.000 (99.950) +2022-11-14 17:05:25,551 Epoch: [459][200/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0193 (0.0256) Prec@1 96.000 (95.667) Prec@5 100.000 (99.952) +2022-11-14 17:05:25,815 Epoch: [459][210/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0323 (0.0259) Prec@1 93.000 (95.545) Prec@5 100.000 (99.955) +2022-11-14 17:05:26,076 Epoch: [459][220/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0234 (0.0258) Prec@1 97.000 (95.609) Prec@5 100.000 (99.957) +2022-11-14 17:05:26,339 Epoch: [459][230/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0368 (0.0263) Prec@1 94.000 (95.542) Prec@5 100.000 (99.958) +2022-11-14 17:05:26,601 Epoch: [459][240/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0230 (0.0261) Prec@1 96.000 (95.560) Prec@5 100.000 (99.960) +2022-11-14 17:05:26,864 Epoch: [459][250/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0147 (0.0257) Prec@1 98.000 (95.654) Prec@5 100.000 (99.962) +2022-11-14 17:05:27,125 Epoch: [459][260/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0373 (0.0261) Prec@1 93.000 (95.556) Prec@5 100.000 (99.963) +2022-11-14 17:05:27,387 Epoch: [459][270/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0310 (0.0263) Prec@1 95.000 (95.536) Prec@5 100.000 (99.964) +2022-11-14 17:05:27,648 Epoch: [459][280/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0177 (0.0260) Prec@1 97.000 (95.586) Prec@5 100.000 (99.966) +2022-11-14 17:05:27,910 Epoch: [459][290/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0341 (0.0263) Prec@1 95.000 (95.567) Prec@5 100.000 (99.967) +2022-11-14 17:05:28,179 Epoch: [459][300/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0065 (0.0256) Prec@1 99.000 (95.677) Prec@5 100.000 (99.968) +2022-11-14 17:05:28,442 Epoch: [459][310/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0393 (0.0261) Prec@1 94.000 (95.625) Prec@5 100.000 (99.969) +2022-11-14 17:05:28,706 Epoch: [459][320/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0379 (0.0264) Prec@1 95.000 (95.606) Prec@5 99.000 (99.939) +2022-11-14 17:05:28,968 Epoch: [459][330/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0112 (0.0260) Prec@1 97.000 (95.647) Prec@5 100.000 (99.941) +2022-11-14 17:05:29,235 Epoch: [459][340/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0230 (0.0259) Prec@1 97.000 (95.686) Prec@5 100.000 (99.943) +2022-11-14 17:05:29,497 Epoch: [459][350/500] Time 0.028 (0.021) Data 0.001 (0.002) Loss 0.0458 (0.0264) Prec@1 90.000 (95.528) Prec@5 100.000 (99.944) +2022-11-14 17:05:29,756 Epoch: [459][360/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0187 (0.0262) Prec@1 98.000 (95.595) Prec@5 99.000 (99.919) +2022-11-14 17:05:30,019 Epoch: [459][370/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0208 (0.0261) Prec@1 98.000 (95.658) Prec@5 100.000 (99.921) +2022-11-14 17:05:30,283 Epoch: [459][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0554 (0.0268) Prec@1 89.000 (95.487) Prec@5 98.000 (99.872) +2022-11-14 17:05:30,544 Epoch: [459][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0259 (0.0268) Prec@1 94.000 (95.450) Prec@5 100.000 (99.875) +2022-11-14 17:05:30,806 Epoch: [459][400/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0156 (0.0265) Prec@1 98.000 (95.512) Prec@5 100.000 (99.878) +2022-11-14 17:05:31,067 Epoch: [459][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0204 (0.0264) Prec@1 97.000 (95.548) Prec@5 100.000 (99.881) +2022-11-14 17:05:31,332 Epoch: [459][420/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0281 (0.0264) Prec@1 96.000 (95.558) Prec@5 99.000 (99.860) +2022-11-14 17:05:31,594 Epoch: [459][430/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0186 (0.0263) Prec@1 98.000 (95.614) Prec@5 100.000 (99.864) +2022-11-14 17:05:31,859 Epoch: [459][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0461 (0.0267) Prec@1 93.000 (95.556) Prec@5 99.000 (99.844) +2022-11-14 17:05:32,124 Epoch: [459][450/500] Time 0.031 (0.021) Data 0.001 (0.002) Loss 0.0267 (0.0267) Prec@1 98.000 (95.609) Prec@5 100.000 (99.848) +2022-11-14 17:05:32,381 Epoch: [459][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0039 (0.0262) Prec@1 100.000 (95.702) Prec@5 100.000 (99.851) +2022-11-14 17:05:32,643 Epoch: [459][470/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0385 (0.0265) Prec@1 93.000 (95.646) Prec@5 100.000 (99.854) +2022-11-14 17:05:32,905 Epoch: [459][480/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0308 (0.0266) Prec@1 94.000 (95.612) Prec@5 100.000 (99.857) +2022-11-14 17:05:33,165 Epoch: [459][490/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0349 (0.0267) Prec@1 93.000 (95.560) Prec@5 100.000 (99.860) +2022-11-14 17:05:33,399 Epoch: [459][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0327 (0.0268) Prec@1 93.000 (95.510) Prec@5 100.000 (99.863) +2022-11-14 17:05:33,698 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0613 (0.0613) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:33,707 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0642 (0.0628) Prec@1 91.000 (90.500) Prec@5 99.000 (99.500) +2022-11-14 17:05:33,715 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0703 (0.0653) Prec@1 85.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 17:05:33,725 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0621) Prec@1 92.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:05:33,732 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0658) Prec@1 85.000 (88.600) Prec@5 100.000 (99.600) +2022-11-14 17:05:33,739 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0363 (0.0609) Prec@1 94.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 17:05:33,746 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0600) Prec@1 91.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 17:05:33,754 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0619) Prec@1 87.000 (89.375) Prec@5 99.000 (99.625) +2022-11-14 17:05:33,761 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0629) Prec@1 90.000 (89.444) Prec@5 99.000 (99.556) +2022-11-14 17:05:33,769 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0651) Prec@1 87.000 (89.200) Prec@5 97.000 (99.300) +2022-11-14 17:05:33,777 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0643) Prec@1 92.000 (89.455) Prec@5 99.000 (99.273) +2022-11-14 17:05:33,785 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0651) Prec@1 90.000 (89.500) Prec@5 100.000 (99.333) +2022-11-14 17:05:33,793 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0641) Prec@1 92.000 (89.692) Prec@5 100.000 (99.385) +2022-11-14 17:05:33,800 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0644) Prec@1 88.000 (89.571) Prec@5 99.000 (99.357) +2022-11-14 17:05:33,808 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0657) Prec@1 87.000 (89.400) Prec@5 100.000 (99.400) +2022-11-14 17:05:33,816 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0659) Prec@1 89.000 (89.375) Prec@5 99.000 (99.375) +2022-11-14 17:05:33,824 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0649) Prec@1 93.000 (89.588) Prec@5 99.000 (99.353) +2022-11-14 17:05:33,832 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0674) Prec@1 83.000 (89.222) Prec@5 99.000 (99.333) +2022-11-14 17:05:33,840 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0678) Prec@1 87.000 (89.105) Prec@5 99.000 (99.316) +2022-11-14 17:05:33,848 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0693) Prec@1 85.000 (88.900) Prec@5 99.000 (99.300) +2022-11-14 17:05:33,855 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0699) Prec@1 86.000 (88.762) Prec@5 99.000 (99.286) +2022-11-14 17:05:33,863 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0706) Prec@1 89.000 (88.773) Prec@5 99.000 (99.273) +2022-11-14 17:05:33,871 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1245 (0.0730) Prec@1 80.000 (88.391) Prec@5 98.000 (99.217) +2022-11-14 17:05:33,878 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0727) Prec@1 88.000 (88.375) Prec@5 100.000 (99.250) +2022-11-14 17:05:33,886 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0732) Prec@1 88.000 (88.360) Prec@5 100.000 (99.280) +2022-11-14 17:05:33,894 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0737) Prec@1 84.000 (88.192) Prec@5 99.000 (99.269) +2022-11-14 17:05:33,902 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0727) Prec@1 93.000 (88.370) Prec@5 100.000 (99.296) +2022-11-14 17:05:33,910 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0721) Prec@1 92.000 (88.500) Prec@5 99.000 (99.286) +2022-11-14 17:05:33,917 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0716) Prec@1 92.000 (88.621) Prec@5 98.000 (99.241) +2022-11-14 17:05:33,925 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0712) Prec@1 89.000 (88.633) Prec@5 99.000 (99.233) +2022-11-14 17:05:33,933 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0710) Prec@1 91.000 (88.710) Prec@5 100.000 (99.258) +2022-11-14 17:05:33,941 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0708) Prec@1 91.000 (88.781) Prec@5 100.000 (99.281) +2022-11-14 17:05:33,949 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0717) Prec@1 83.000 (88.606) Prec@5 99.000 (99.273) +2022-11-14 17:05:33,957 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0724) Prec@1 87.000 (88.559) Prec@5 99.000 (99.265) +2022-11-14 17:05:33,964 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0726) Prec@1 88.000 (88.543) Prec@5 98.000 (99.229) +2022-11-14 17:05:33,972 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0725) Prec@1 90.000 (88.583) Prec@5 100.000 (99.250) +2022-11-14 17:05:33,980 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0722) Prec@1 90.000 (88.622) Prec@5 99.000 (99.243) +2022-11-14 17:05:33,988 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0727) Prec@1 84.000 (88.500) Prec@5 99.000 (99.237) +2022-11-14 17:05:33,995 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0722) Prec@1 92.000 (88.590) Prec@5 99.000 (99.231) +2022-11-14 17:05:34,003 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0722) Prec@1 88.000 (88.575) Prec@5 100.000 (99.250) +2022-11-14 17:05:34,010 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0728) Prec@1 85.000 (88.488) Prec@5 99.000 (99.244) +2022-11-14 17:05:34,018 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0724) Prec@1 91.000 (88.548) Prec@5 99.000 (99.238) +2022-11-14 17:05:34,026 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0718) Prec@1 94.000 (88.674) Prec@5 99.000 (99.233) +2022-11-14 17:05:34,033 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0719) Prec@1 90.000 (88.705) Prec@5 98.000 (99.205) +2022-11-14 17:05:34,041 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0719) Prec@1 88.000 (88.689) Prec@5 100.000 (99.222) +2022-11-14 17:05:34,049 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0724) Prec@1 83.000 (88.565) Prec@5 100.000 (99.239) +2022-11-14 17:05:34,057 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0722) Prec@1 89.000 (88.574) Prec@5 99.000 (99.234) +2022-11-14 17:05:34,066 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1097 (0.0730) Prec@1 81.000 (88.417) Prec@5 99.000 (99.229) +2022-11-14 17:05:34,073 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0726) Prec@1 93.000 (88.510) Prec@5 100.000 (99.245) +2022-11-14 17:05:34,082 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0732) Prec@1 86.000 (88.460) Prec@5 99.000 (99.240) +2022-11-14 17:05:34,090 Test: 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0.0690 (0.0728) Prec@1 89.000 (88.333) Prec@5 100.000 (99.263) +2022-11-14 17:05:34,149 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0729) Prec@1 89.000 (88.345) Prec@5 98.000 (99.241) +2022-11-14 17:05:34,156 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0732) Prec@1 86.000 (88.305) Prec@5 98.000 (99.220) +2022-11-14 17:05:34,164 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0732) Prec@1 86.000 (88.267) Prec@5 100.000 (99.233) +2022-11-14 17:05:34,172 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0735) Prec@1 87.000 (88.246) Prec@5 100.000 (99.246) +2022-11-14 17:05:34,180 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0733) Prec@1 91.000 (88.290) Prec@5 98.000 (99.226) +2022-11-14 17:05:34,188 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0732) Prec@1 90.000 (88.317) Prec@5 100.000 (99.238) +2022-11-14 17:05:34,195 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0447 (0.0728) Prec@1 93.000 (88.391) Prec@5 100.000 (99.250) +2022-11-14 17:05:34,203 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0730) Prec@1 85.000 (88.338) Prec@5 100.000 (99.262) +2022-11-14 17:05:34,211 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0728) Prec@1 87.000 (88.318) Prec@5 99.000 (99.258) +2022-11-14 17:05:34,218 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0455 (0.0724) Prec@1 92.000 (88.373) Prec@5 100.000 (99.269) +2022-11-14 17:05:34,226 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0525 (0.0721) Prec@1 92.000 (88.426) Prec@5 99.000 (99.265) +2022-11-14 17:05:34,234 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0720) Prec@1 91.000 (88.464) Prec@5 99.000 (99.261) +2022-11-14 17:05:34,241 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0719) Prec@1 88.000 (88.457) Prec@5 99.000 (99.257) +2022-11-14 17:05:34,249 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0723) Prec@1 88.000 (88.451) Prec@5 98.000 (99.239) +2022-11-14 17:05:34,257 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0721) Prec@1 89.000 (88.458) Prec@5 100.000 (99.250) +2022-11-14 17:05:34,265 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0718) Prec@1 92.000 (88.507) Prec@5 99.000 (99.247) +2022-11-14 17:05:34,272 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0400 (0.0714) Prec@1 94.000 (88.581) Prec@5 100.000 (99.257) +2022-11-14 17:05:34,280 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0716) Prec@1 84.000 (88.520) Prec@5 100.000 (99.267) +2022-11-14 17:05:34,288 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0714) Prec@1 92.000 (88.566) Prec@5 99.000 (99.263) +2022-11-14 17:05:34,296 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0712) Prec@1 91.000 (88.597) Prec@5 98.000 (99.247) +2022-11-14 17:05:34,304 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.0717) Prec@1 84.000 (88.538) Prec@5 97.000 (99.218) +2022-11-14 17:05:34,311 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0718) Prec@1 87.000 (88.519) Prec@5 99.000 (99.215) +2022-11-14 17:05:34,319 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0719) Prec@1 86.000 (88.487) Prec@5 100.000 (99.225) +2022-11-14 17:05:34,327 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0722) Prec@1 85.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 17:05:34,335 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0724) Prec@1 82.000 (88.366) Prec@5 100.000 (99.232) +2022-11-14 17:05:34,343 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0726) Prec@1 88.000 (88.361) Prec@5 99.000 (99.229) +2022-11-14 17:05:34,350 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0724) Prec@1 89.000 (88.369) Prec@5 99.000 (99.226) +2022-11-14 17:05:34,358 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0727) Prec@1 86.000 (88.341) Prec@5 100.000 (99.235) +2022-11-14 17:05:34,366 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0729) Prec@1 86.000 (88.314) Prec@5 100.000 (99.244) +2022-11-14 17:05:34,373 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0728) Prec@1 91.000 (88.345) Prec@5 98.000 (99.230) +2022-11-14 17:05:34,381 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0729) Prec@1 85.000 (88.307) Prec@5 98.000 (99.216) +2022-11-14 17:05:34,389 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0729) Prec@1 89.000 (88.315) Prec@5 100.000 (99.225) +2022-11-14 17:05:34,396 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0729) Prec@1 91.000 (88.344) Prec@5 99.000 (99.222) +2022-11-14 17:05:34,404 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0726) Prec@1 92.000 (88.385) Prec@5 100.000 (99.231) +2022-11-14 17:05:34,412 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0724) Prec@1 92.000 (88.424) Prec@5 99.000 (99.228) +2022-11-14 17:05:34,420 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0723) Prec@1 89.000 (88.430) Prec@5 100.000 (99.237) +2022-11-14 17:05:34,427 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0724) Prec@1 88.000 (88.426) Prec@5 100.000 (99.245) +2022-11-14 17:05:34,435 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0726) Prec@1 83.000 (88.368) Prec@5 99.000 (99.242) +2022-11-14 17:05:34,443 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0726) Prec@1 88.000 (88.365) Prec@5 100.000 (99.250) +2022-11-14 17:05:34,451 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0359 (0.0723) Prec@1 93.000 (88.412) Prec@5 99.000 (99.247) +2022-11-14 17:05:34,458 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0726) Prec@1 85.000 (88.378) Prec@5 97.000 (99.224) +2022-11-14 17:05:34,466 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0728) Prec@1 85.000 (88.343) Prec@5 98.000 (99.212) +2022-11-14 17:05:34,473 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0729) Prec@1 88.000 (88.340) Prec@5 100.000 (99.220) +2022-11-14 17:05:34,529 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:05:34,874 Epoch: [460][0/500] Time 0.024 (0.024) Data 0.251 (0.251) Loss 0.0375 (0.0375) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:35,070 Epoch: [460][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0289 (0.0332) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:35,262 Epoch: [460][20/500] Time 0.017 (0.017) Data 0.002 (0.014) Loss 0.0185 (0.0283) Prec@1 97.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:05:35,453 Epoch: [460][30/500] Time 0.017 (0.017) Data 0.002 (0.010) Loss 0.0253 (0.0276) Prec@1 95.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:05:35,646 Epoch: [460][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0187 (0.0258) Prec@1 97.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:05:35,836 Epoch: [460][50/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0310 (0.0267) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,028 Epoch: [460][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0247 (0.0264) Prec@1 96.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,221 Epoch: [460][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0395 (0.0280) Prec@1 94.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,412 Epoch: [460][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0239 (0.0276) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,606 Epoch: [460][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0172 (0.0265) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,798 Epoch: [460][100/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0195 (0.0259) Prec@1 97.000 (95.636) Prec@5 100.000 (100.000) +2022-11-14 17:05:36,990 Epoch: [460][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0284 (0.0261) Prec@1 95.000 (95.583) Prec@5 100.000 (100.000) +2022-11-14 17:05:37,186 Epoch: [460][120/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0130 (0.0251) Prec@1 98.000 (95.769) Prec@5 100.000 (100.000) +2022-11-14 17:05:37,376 Epoch: [460][130/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0357 (0.0259) Prec@1 94.000 (95.643) Prec@5 100.000 (100.000) +2022-11-14 17:05:37,571 Epoch: [460][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0342 (0.0264) Prec@1 95.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 17:05:37,779 Epoch: [460][150/500] Time 0.022 (0.017) Data 0.001 (0.003) Loss 0.0263 (0.0264) Prec@1 95.000 (95.562) Prec@5 100.000 (100.000) +2022-11-14 17:05:37,982 Epoch: [460][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0371 (0.0270) Prec@1 92.000 (95.353) Prec@5 100.000 (100.000) +2022-11-14 17:05:38,192 Epoch: [460][170/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0231 (0.0268) Prec@1 97.000 (95.444) Prec@5 100.000 (100.000) +2022-11-14 17:05:38,395 Epoch: [460][180/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0203 (0.0265) Prec@1 98.000 (95.579) Prec@5 99.000 (99.947) +2022-11-14 17:05:38,597 Epoch: [460][190/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0311 (0.0267) Prec@1 94.000 (95.500) Prec@5 100.000 (99.950) +2022-11-14 17:05:38,982 Epoch: [460][200/500] Time 0.042 (0.018) Data 0.002 (0.003) Loss 0.0275 (0.0267) Prec@1 95.000 (95.476) Prec@5 100.000 (99.952) +2022-11-14 17:05:39,443 Epoch: [460][210/500] Time 0.044 (0.019) Data 0.002 (0.003) Loss 0.0453 (0.0276) Prec@1 93.000 (95.364) Prec@5 100.000 (99.955) +2022-11-14 17:05:39,886 Epoch: [460][220/500] Time 0.040 (0.020) Data 0.002 (0.003) Loss 0.0197 (0.0272) Prec@1 96.000 (95.391) Prec@5 100.000 (99.957) +2022-11-14 17:05:40,169 Epoch: [460][230/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0274 (0.0273) Prec@1 95.000 (95.375) Prec@5 100.000 (99.958) +2022-11-14 17:05:40,435 Epoch: [460][240/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0171 (0.0268) Prec@1 98.000 (95.480) Prec@5 100.000 (99.960) +2022-11-14 17:05:40,702 Epoch: [460][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0366 (0.0272) Prec@1 95.000 (95.462) Prec@5 100.000 (99.962) +2022-11-14 17:05:40,970 Epoch: [460][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0255 (0.0272) Prec@1 95.000 (95.444) Prec@5 100.000 (99.963) +2022-11-14 17:05:41,240 Epoch: [460][270/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0389 (0.0276) Prec@1 95.000 (95.429) Prec@5 100.000 (99.964) +2022-11-14 17:05:41,506 Epoch: [460][280/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0316 (0.0277) Prec@1 94.000 (95.379) Prec@5 100.000 (99.966) +2022-11-14 17:05:41,771 Epoch: [460][290/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0416 (0.0282) Prec@1 94.000 (95.333) Prec@5 99.000 (99.933) +2022-11-14 17:05:42,036 Epoch: [460][300/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0312 (0.0283) Prec@1 94.000 (95.290) Prec@5 100.000 (99.935) +2022-11-14 17:05:42,302 Epoch: [460][310/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0210 (0.0280) Prec@1 97.000 (95.344) Prec@5 100.000 (99.938) +2022-11-14 17:05:42,571 Epoch: [460][320/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0257 (0.0280) Prec@1 95.000 (95.333) Prec@5 100.000 (99.939) +2022-11-14 17:05:42,837 Epoch: [460][330/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0335 (0.0281) Prec@1 94.000 (95.294) Prec@5 99.000 (99.912) +2022-11-14 17:05:43,108 Epoch: [460][340/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0386 (0.0284) Prec@1 93.000 (95.229) Prec@5 100.000 (99.914) +2022-11-14 17:05:43,373 Epoch: [460][350/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0169 (0.0281) Prec@1 98.000 (95.306) Prec@5 100.000 (99.917) +2022-11-14 17:05:43,639 Epoch: [460][360/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0286 (0.0281) Prec@1 95.000 (95.297) Prec@5 100.000 (99.919) +2022-11-14 17:05:43,902 Epoch: [460][370/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0174 (0.0278) Prec@1 97.000 (95.342) Prec@5 100.000 (99.921) +2022-11-14 17:05:44,171 Epoch: [460][380/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0458 (0.0283) Prec@1 91.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 17:05:44,440 Epoch: [460][390/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0362 (0.0285) Prec@1 94.000 (95.200) Prec@5 100.000 (99.925) +2022-11-14 17:05:44,702 Epoch: [460][400/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0310 (0.0286) Prec@1 94.000 (95.171) Prec@5 99.000 (99.902) +2022-11-14 17:05:44,969 Epoch: [460][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0217 (0.0284) Prec@1 96.000 (95.190) Prec@5 100.000 (99.905) +2022-11-14 17:05:45,237 Epoch: [460][420/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0253 (0.0283) Prec@1 95.000 (95.186) Prec@5 100.000 (99.907) +2022-11-14 17:05:45,503 Epoch: [460][430/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0213 (0.0282) Prec@1 96.000 (95.205) Prec@5 100.000 (99.909) +2022-11-14 17:05:45,771 Epoch: [460][440/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0301 (0.0282) Prec@1 94.000 (95.178) Prec@5 100.000 (99.911) +2022-11-14 17:05:46,038 Epoch: [460][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0514 (0.0287) Prec@1 91.000 (95.087) Prec@5 100.000 (99.913) +2022-11-14 17:05:46,312 Epoch: [460][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0192 (0.0285) Prec@1 97.000 (95.128) Prec@5 100.000 (99.915) +2022-11-14 17:05:46,581 Epoch: [460][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0358 (0.0287) Prec@1 94.000 (95.104) Prec@5 100.000 (99.917) +2022-11-14 17:05:46,851 Epoch: [460][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0323 (0.0287) Prec@1 95.000 (95.102) Prec@5 100.000 (99.918) +2022-11-14 17:05:47,126 Epoch: [460][490/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0407 (0.0290) Prec@1 92.000 (95.040) Prec@5 100.000 (99.920) +2022-11-14 17:05:47,364 Epoch: [460][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0489 (0.0294) Prec@1 91.000 (94.961) Prec@5 99.000 (99.902) +2022-11-14 17:05:47,671 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0657 (0.0657) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:47,679 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0706) Prec@1 88.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:47,688 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0635 (0.0682) Prec@1 90.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:47,697 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0698) Prec@1 89.000 (88.250) Prec@5 99.000 (99.750) +2022-11-14 17:05:47,704 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0676) Prec@1 90.000 (88.600) Prec@5 99.000 (99.600) +2022-11-14 17:05:47,711 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0452 (0.0639) Prec@1 91.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 17:05:47,718 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0629) Prec@1 92.000 (89.429) Prec@5 100.000 (99.571) +2022-11-14 17:05:47,726 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0652) Prec@1 87.000 (89.125) Prec@5 99.000 (99.500) +2022-11-14 17:05:47,733 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0679) Prec@1 88.000 (89.000) Prec@5 98.000 (99.333) +2022-11-14 17:05:47,740 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0685) Prec@1 88.000 (88.900) Prec@5 97.000 (99.100) +2022-11-14 17:05:47,748 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0679) Prec@1 90.000 (89.000) Prec@5 99.000 (99.091) +2022-11-14 17:05:47,756 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0682) Prec@1 89.000 (89.000) Prec@5 99.000 (99.083) +2022-11-14 17:05:47,764 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0678) Prec@1 91.000 (89.154) Prec@5 100.000 (99.154) +2022-11-14 17:05:47,773 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0686) Prec@1 89.000 (89.143) Prec@5 99.000 (99.143) +2022-11-14 17:05:47,781 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0691) Prec@1 87.000 (89.000) Prec@5 99.000 (99.133) +2022-11-14 17:05:47,788 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0690) Prec@1 87.000 (88.875) Prec@5 100.000 (99.188) +2022-11-14 17:05:47,796 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0447 (0.0676) Prec@1 93.000 (89.118) Prec@5 99.000 (99.176) +2022-11-14 17:05:47,804 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0696) Prec@1 81.000 (88.667) Prec@5 98.000 (99.111) +2022-11-14 17:05:47,812 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0697) Prec@1 88.000 (88.632) Prec@5 98.000 (99.053) +2022-11-14 17:05:47,820 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0702) Prec@1 88.000 (88.600) Prec@5 98.000 (99.000) +2022-11-14 17:05:47,827 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0702) Prec@1 87.000 (88.524) Prec@5 100.000 (99.048) +2022-11-14 17:05:47,835 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0711) Prec@1 86.000 (88.409) Prec@5 99.000 (99.045) +2022-11-14 17:05:47,842 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1100 (0.0728) Prec@1 84.000 (88.217) Prec@5 99.000 (99.043) +2022-11-14 17:05:47,850 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0729) Prec@1 87.000 (88.167) Prec@5 100.000 (99.083) +2022-11-14 17:05:47,857 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0726) Prec@1 89.000 (88.200) Prec@5 100.000 (99.120) +2022-11-14 17:05:47,865 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0900 (0.0732) Prec@1 87.000 (88.154) Prec@5 98.000 (99.077) +2022-11-14 17:05:47,872 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0726) Prec@1 90.000 (88.222) Prec@5 100.000 (99.111) +2022-11-14 17:05:47,880 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0723) Prec@1 88.000 (88.214) Prec@5 100.000 (99.143) +2022-11-14 17:05:47,887 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0723) Prec@1 90.000 (88.276) Prec@5 99.000 (99.138) +2022-11-14 17:05:47,895 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0723) Prec@1 89.000 (88.300) Prec@5 100.000 (99.167) +2022-11-14 17:05:47,903 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0717) Prec@1 91.000 (88.387) Prec@5 100.000 (99.194) +2022-11-14 17:05:47,910 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0716) Prec@1 88.000 (88.375) Prec@5 100.000 (99.219) +2022-11-14 17:05:47,918 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0714) Prec@1 90.000 (88.424) Prec@5 100.000 (99.242) +2022-11-14 17:05:47,925 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0713) Prec@1 88.000 (88.412) Prec@5 100.000 (99.265) +2022-11-14 17:05:47,933 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0716) Prec@1 87.000 (88.371) Prec@5 97.000 (99.200) +2022-11-14 17:05:47,941 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0714) Prec@1 90.000 (88.417) Prec@5 99.000 (99.194) +2022-11-14 17:05:47,948 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0713) Prec@1 89.000 (88.432) Prec@5 99.000 (99.189) +2022-11-14 17:05:47,956 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0720) Prec@1 87.000 (88.395) Prec@5 97.000 (99.132) +2022-11-14 17:05:47,964 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0716) Prec@1 93.000 (88.513) Prec@5 99.000 (99.128) +2022-11-14 17:05:47,971 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0711) Prec@1 90.000 (88.550) Prec@5 100.000 (99.150) +2022-11-14 17:05:47,979 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0719) Prec@1 84.000 (88.439) Prec@5 98.000 (99.122) +2022-11-14 17:05:47,987 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0717) Prec@1 90.000 (88.476) Prec@5 99.000 (99.119) +2022-11-14 17:05:47,994 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0713) Prec@1 92.000 (88.558) Prec@5 99.000 (99.116) +2022-11-14 17:05:48,002 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0713) Prec@1 89.000 (88.568) Prec@5 99.000 (99.114) +2022-11-14 17:05:48,009 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0708) Prec@1 92.000 (88.644) Prec@5 100.000 (99.133) +2022-11-14 17:05:48,017 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0711) Prec@1 84.000 (88.543) Prec@5 100.000 (99.152) +2022-11-14 17:05:48,024 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0711) Prec@1 90.000 (88.574) Prec@5 100.000 (99.170) +2022-11-14 17:05:48,032 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0939 (0.0715) Prec@1 85.000 (88.500) Prec@5 99.000 (99.167) +2022-11-14 17:05:48,040 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0398 (0.0709) Prec@1 93.000 (88.592) Prec@5 100.000 (99.184) +2022-11-14 17:05:48,047 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1157 (0.0718) Prec@1 83.000 (88.480) Prec@5 100.000 (99.200) +2022-11-14 17:05:48,055 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0671 (0.0717) Prec@1 86.000 (88.431) Prec@5 100.000 (99.216) +2022-11-14 17:05:48,063 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0806 (0.0719) Prec@1 88.000 (88.423) Prec@5 97.000 (99.173) +2022-11-14 17:05:48,070 Test: [52/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0717) Prec@1 90.000 (88.453) Prec@5 100.000 (99.189) +2022-11-14 17:05:48,078 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0714 (0.0717) Prec@1 87.000 (88.426) Prec@5 100.000 (99.204) +2022-11-14 17:05:48,085 Test: [54/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0909 (0.0720) Prec@1 86.000 (88.382) Prec@5 100.000 (99.218) +2022-11-14 17:05:48,093 Test: [55/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0558 (0.0717) Prec@1 92.000 (88.446) Prec@5 98.000 (99.196) +2022-11-14 17:05:48,101 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0717) Prec@1 87.000 (88.421) Prec@5 100.000 (99.211) +2022-11-14 17:05:48,108 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0720) Prec@1 87.000 (88.397) Prec@5 100.000 (99.224) +2022-11-14 17:05:48,116 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1102 (0.0726) Prec@1 81.000 (88.271) Prec@5 99.000 (99.220) +2022-11-14 17:05:48,123 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0725) Prec@1 89.000 (88.283) Prec@5 100.000 (99.233) +2022-11-14 17:05:48,131 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0724) Prec@1 91.000 (88.328) Prec@5 100.000 (99.246) +2022-11-14 17:05:48,138 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0723) Prec@1 88.000 (88.323) Prec@5 99.000 (99.242) +2022-11-14 17:05:48,146 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0454 (0.0718) Prec@1 92.000 (88.381) Prec@5 100.000 (99.254) +2022-11-14 17:05:48,153 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0354 (0.0713) Prec@1 95.000 (88.484) Prec@5 100.000 (99.266) +2022-11-14 17:05:48,161 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0743 (0.0713) Prec@1 88.000 (88.477) Prec@5 100.000 (99.277) +2022-11-14 17:05:48,169 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0715) Prec@1 85.000 (88.424) Prec@5 99.000 (99.273) +2022-11-14 17:05:48,176 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0347 (0.0710) Prec@1 94.000 (88.507) Prec@5 100.000 (99.284) +2022-11-14 17:05:48,184 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0709) Prec@1 91.000 (88.544) Prec@5 100.000 (99.294) +2022-11-14 17:05:48,192 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0583 (0.0707) Prec@1 91.000 (88.580) Prec@5 99.000 (99.290) +2022-11-14 17:05:48,199 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0707) Prec@1 90.000 (88.600) Prec@5 97.000 (99.257) +2022-11-14 17:05:48,207 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0709) Prec@1 88.000 (88.592) Prec@5 100.000 (99.268) +2022-11-14 17:05:48,214 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0558 (0.0706) Prec@1 91.000 (88.625) Prec@5 100.000 (99.278) +2022-11-14 17:05:48,222 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0394 (0.0702) Prec@1 95.000 (88.712) Prec@5 100.000 (99.288) +2022-11-14 17:05:48,230 Test: [73/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0377 (0.0698) Prec@1 95.000 (88.797) Prec@5 100.000 (99.297) +2022-11-14 17:05:48,237 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1048 (0.0702) Prec@1 84.000 (88.733) Prec@5 100.000 (99.307) +2022-11-14 17:05:48,245 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0513 (0.0700) Prec@1 92.000 (88.776) Prec@5 100.000 (99.316) +2022-11-14 17:05:48,253 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0669 (0.0699) Prec@1 89.000 (88.779) Prec@5 99.000 (99.312) +2022-11-14 17:05:48,261 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1051 (0.0704) Prec@1 84.000 (88.718) Prec@5 99.000 (99.308) +2022-11-14 17:05:48,268 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0704) Prec@1 91.000 (88.747) Prec@5 100.000 (99.316) +2022-11-14 17:05:48,276 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0774 (0.0705) Prec@1 89.000 (88.750) Prec@5 100.000 (99.325) +2022-11-14 17:05:48,283 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1018 (0.0709) Prec@1 86.000 (88.716) Prec@5 98.000 (99.309) +2022-11-14 17:05:48,291 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0973 (0.0712) Prec@1 86.000 (88.683) Prec@5 99.000 (99.305) +2022-11-14 17:05:48,298 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0833 (0.0713) Prec@1 88.000 (88.675) Prec@5 100.000 (99.313) +2022-11-14 17:05:48,306 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0704 (0.0713) Prec@1 88.000 (88.667) Prec@5 100.000 (99.321) +2022-11-14 17:05:48,313 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0799 (0.0714) Prec@1 87.000 (88.647) Prec@5 99.000 (99.318) +2022-11-14 17:05:48,321 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0938 (0.0717) Prec@1 86.000 (88.616) Prec@5 100.000 (99.326) +2022-11-14 17:05:48,328 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0625 (0.0716) Prec@1 88.000 (88.609) Prec@5 100.000 (99.333) +2022-11-14 17:05:48,336 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0786 (0.0717) Prec@1 86.000 (88.580) Prec@5 99.000 (99.330) +2022-11-14 17:05:48,343 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0717) Prec@1 85.000 (88.539) Prec@5 99.000 (99.326) +2022-11-14 17:05:48,351 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0718) Prec@1 86.000 (88.511) Prec@5 100.000 (99.333) +2022-11-14 17:05:48,358 Test: [90/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0582 (0.0717) Prec@1 91.000 (88.538) Prec@5 99.000 (99.330) +2022-11-14 17:05:48,366 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0400 (0.0714) Prec@1 93.000 (88.587) Prec@5 100.000 (99.337) +2022-11-14 17:05:48,373 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0913 (0.0716) Prec@1 86.000 (88.559) Prec@5 100.000 (99.344) +2022-11-14 17:05:48,381 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0715) Prec@1 89.000 (88.564) Prec@5 99.000 (99.340) +2022-11-14 17:05:48,388 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0800 (0.0716) Prec@1 86.000 (88.537) Prec@5 99.000 (99.337) +2022-11-14 17:05:48,396 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0715) Prec@1 89.000 (88.542) Prec@5 99.000 (99.333) +2022-11-14 17:05:48,403 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0548 (0.0714) Prec@1 92.000 (88.577) Prec@5 99.000 (99.330) +2022-11-14 17:05:48,411 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1026 (0.0717) Prec@1 86.000 (88.551) Prec@5 100.000 (99.337) +2022-11-14 17:05:48,418 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1050 (0.0720) Prec@1 86.000 (88.525) Prec@5 99.000 (99.333) +2022-11-14 17:05:48,425 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0886 (0.0722) Prec@1 87.000 (88.510) Prec@5 99.000 (99.330) +2022-11-14 17:05:48,480 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:05:48,821 Epoch: [461][0/500] Time 0.029 (0.029) Data 0.254 (0.254) Loss 0.0117 (0.0117) Prec@1 99.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:49,027 Epoch: [461][10/500] Time 0.022 (0.019) Data 0.001 (0.025) Loss 0.0274 (0.0196) Prec@1 96.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:49,231 Epoch: [461][20/500] Time 0.017 (0.019) Data 0.002 (0.014) Loss 0.0333 (0.0242) Prec@1 94.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 17:05:49,430 Epoch: [461][30/500] Time 0.022 (0.018) Data 0.002 (0.010) Loss 0.0189 (0.0228) Prec@1 97.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:05:49,627 Epoch: [461][40/500] Time 0.017 (0.018) Data 0.001 (0.008) Loss 0.0222 (0.0227) Prec@1 97.000 (96.600) Prec@5 100.000 (100.000) +2022-11-14 17:05:49,829 Epoch: [461][50/500] Time 0.022 (0.018) Data 0.001 (0.007) Loss 0.0426 (0.0260) Prec@1 94.000 (96.167) Prec@5 100.000 (100.000) +2022-11-14 17:05:50,027 Epoch: [461][60/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0301 (0.0266) Prec@1 94.000 (95.857) Prec@5 100.000 (100.000) +2022-11-14 17:05:50,231 Epoch: [461][70/500] Time 0.022 (0.018) Data 0.002 (0.005) Loss 0.0209 (0.0259) Prec@1 96.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 17:05:50,427 Epoch: [461][80/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0384 (0.0273) Prec@1 93.000 (95.556) Prec@5 100.000 (100.000) +2022-11-14 17:05:50,622 Epoch: [461][90/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0267 (0.0272) Prec@1 94.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:05:50,823 Epoch: [461][100/500] Time 0.019 (0.018) Data 0.004 (0.004) Loss 0.0123 (0.0259) Prec@1 99.000 (95.727) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,015 Epoch: [461][110/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0103 (0.0246) Prec@1 98.000 (95.917) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,206 Epoch: [461][120/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0265 (0.0247) Prec@1 96.000 (95.923) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,395 Epoch: [461][130/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0142 (0.0240) Prec@1 99.000 (96.143) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,583 Epoch: [461][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0243 (0.0240) Prec@1 96.000 (96.133) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,771 Epoch: [461][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0273 (0.0242) Prec@1 95.000 (96.062) Prec@5 100.000 (100.000) +2022-11-14 17:05:51,962 Epoch: [461][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0162 (0.0237) Prec@1 97.000 (96.118) Prec@5 100.000 (100.000) +2022-11-14 17:05:52,152 Epoch: [461][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0311 (0.0241) Prec@1 94.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:05:52,413 Epoch: [461][180/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0210 (0.0240) Prec@1 98.000 (96.105) Prec@5 100.000 (100.000) +2022-11-14 17:05:52,690 Epoch: [461][190/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0239 (0.0240) Prec@1 96.000 (96.100) Prec@5 100.000 (100.000) +2022-11-14 17:05:52,977 Epoch: [461][200/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0296 (0.0242) Prec@1 95.000 (96.048) Prec@5 100.000 (100.000) +2022-11-14 17:05:53,264 Epoch: [461][210/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0226 (0.0242) Prec@1 97.000 (96.091) Prec@5 100.000 (100.000) +2022-11-14 17:05:53,549 Epoch: [461][220/500] Time 0.028 (0.019) Data 0.001 (0.003) Loss 0.0282 (0.0243) Prec@1 97.000 (96.130) Prec@5 100.000 (100.000) +2022-11-14 17:05:53,839 Epoch: [461][230/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0316 (0.0246) Prec@1 95.000 (96.083) Prec@5 100.000 (100.000) +2022-11-14 17:05:54,131 Epoch: [461][240/500] Time 0.030 (0.020) Data 0.002 (0.003) Loss 0.0473 (0.0255) Prec@1 93.000 (95.960) Prec@5 100.000 (100.000) +2022-11-14 17:05:54,420 Epoch: [461][250/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0259 (0.0256) Prec@1 96.000 (95.962) Prec@5 100.000 (100.000) +2022-11-14 17:05:54,704 Epoch: [461][260/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0206 (0.0254) Prec@1 95.000 (95.926) Prec@5 100.000 (100.000) +2022-11-14 17:05:54,989 Epoch: [461][270/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0260 (0.0254) Prec@1 97.000 (95.964) Prec@5 100.000 (100.000) +2022-11-14 17:05:55,270 Epoch: [461][280/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0509 (0.0263) Prec@1 91.000 (95.793) Prec@5 100.000 (100.000) +2022-11-14 17:05:55,548 Epoch: [461][290/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0203 (0.0261) Prec@1 98.000 (95.867) Prec@5 100.000 (100.000) +2022-11-14 17:05:55,826 Epoch: [461][300/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0204 (0.0259) Prec@1 98.000 (95.935) Prec@5 100.000 (100.000) +2022-11-14 17:05:56,107 Epoch: [461][310/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0228 (0.0258) Prec@1 97.000 (95.969) Prec@5 100.000 (100.000) +2022-11-14 17:05:56,385 Epoch: [461][320/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0249 (0.0258) Prec@1 96.000 (95.970) Prec@5 100.000 (100.000) +2022-11-14 17:05:56,659 Epoch: [461][330/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0288 (0.0259) Prec@1 96.000 (95.971) Prec@5 100.000 (100.000) +2022-11-14 17:05:56,932 Epoch: [461][340/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0367 (0.0262) Prec@1 94.000 (95.914) Prec@5 100.000 (100.000) +2022-11-14 17:05:57,206 Epoch: [461][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0449 (0.0267) Prec@1 94.000 (95.861) Prec@5 99.000 (99.972) +2022-11-14 17:05:57,479 Epoch: [461][360/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0382 (0.0270) Prec@1 94.000 (95.811) Prec@5 99.000 (99.946) +2022-11-14 17:05:57,752 Epoch: [461][370/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0278 (0.0270) Prec@1 97.000 (95.842) Prec@5 100.000 (99.947) +2022-11-14 17:05:58,022 Epoch: [461][380/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0612 (0.0279) Prec@1 88.000 (95.641) Prec@5 99.000 (99.923) +2022-11-14 17:05:58,294 Epoch: [461][390/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0279 (0.0279) Prec@1 95.000 (95.625) Prec@5 100.000 (99.925) +2022-11-14 17:05:58,571 Epoch: [461][400/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0237 (0.0278) Prec@1 97.000 (95.659) Prec@5 100.000 (99.927) +2022-11-14 17:05:58,845 Epoch: [461][410/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0191 (0.0276) Prec@1 97.000 (95.690) Prec@5 100.000 (99.929) +2022-11-14 17:05:59,119 Epoch: [461][420/500] Time 0.030 (0.022) Data 0.001 (0.002) Loss 0.0482 (0.0281) Prec@1 92.000 (95.605) Prec@5 100.000 (99.930) +2022-11-14 17:05:59,386 Epoch: [461][430/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0273 (0.0281) Prec@1 95.000 (95.591) Prec@5 100.000 (99.932) +2022-11-14 17:05:59,657 Epoch: [461][440/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0336 (0.0282) Prec@1 94.000 (95.556) Prec@5 100.000 (99.933) +2022-11-14 17:05:59,929 Epoch: [461][450/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0251 (0.0281) Prec@1 95.000 (95.543) Prec@5 100.000 (99.935) +2022-11-14 17:06:00,206 Epoch: [461][460/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0340 (0.0282) Prec@1 94.000 (95.511) Prec@5 100.000 (99.936) +2022-11-14 17:06:00,476 Epoch: [461][470/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0198 (0.0281) Prec@1 97.000 (95.542) Prec@5 100.000 (99.938) +2022-11-14 17:06:00,749 Epoch: [461][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0340 (0.0282) Prec@1 94.000 (95.510) Prec@5 100.000 (99.939) +2022-11-14 17:06:01,021 Epoch: [461][490/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0256 (0.0281) Prec@1 94.000 (95.480) Prec@5 100.000 (99.940) +2022-11-14 17:06:01,270 Epoch: [461][499/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0230 (0.0280) Prec@1 96.000 (95.490) Prec@5 100.000 (99.941) +2022-11-14 17:06:01,569 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0769 (0.0769) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:01,579 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0602 (0.0685) Prec@1 91.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:06:01,586 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0808 (0.0726) Prec@1 85.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:01,596 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 88.000 (88.000) Prec@5 97.000 (99.250) +2022-11-14 17:06:01,603 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0775) Prec@1 87.000 (87.800) Prec@5 99.000 (99.200) +2022-11-14 17:06:01,610 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0368 (0.0707) Prec@1 95.000 (89.000) Prec@5 100.000 (99.333) +2022-11-14 17:06:01,617 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0699) Prec@1 89.000 (89.000) Prec@5 100.000 (99.429) +2022-11-14 17:06:01,625 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0734) Prec@1 83.000 (88.250) Prec@5 99.000 (99.375) +2022-11-14 17:06:01,632 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0823 (0.0744) Prec@1 89.000 (88.333) Prec@5 98.000 (99.222) +2022-11-14 17:06:01,639 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0760) Prec@1 87.000 (88.200) Prec@5 98.000 (99.100) +2022-11-14 17:06:01,647 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0749) Prec@1 91.000 (88.455) Prec@5 100.000 (99.182) +2022-11-14 17:06:01,655 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0760) Prec@1 85.000 (88.167) Prec@5 100.000 (99.250) +2022-11-14 17:06:01,663 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0743) Prec@1 92.000 (88.462) Prec@5 100.000 (99.308) +2022-11-14 17:06:01,671 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0731) Prec@1 91.000 (88.643) Prec@5 99.000 (99.286) +2022-11-14 17:06:01,678 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0738) Prec@1 86.000 (88.467) Prec@5 100.000 (99.333) +2022-11-14 17:06:01,686 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0745) Prec@1 87.000 (88.375) Prec@5 100.000 (99.375) +2022-11-14 17:06:01,693 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0484 (0.0730) Prec@1 93.000 (88.647) Prec@5 98.000 (99.294) +2022-11-14 17:06:01,701 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0745) Prec@1 85.000 (88.444) Prec@5 100.000 (99.333) +2022-11-14 17:06:01,709 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0760) Prec@1 83.000 (88.158) Prec@5 99.000 (99.316) +2022-11-14 17:06:01,716 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0999 (0.0772) Prec@1 85.000 (88.000) Prec@5 96.000 (99.150) +2022-11-14 17:06:01,724 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0774) Prec@1 88.000 (88.000) Prec@5 100.000 (99.190) +2022-11-14 17:06:01,731 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0776) Prec@1 87.000 (87.955) Prec@5 99.000 (99.182) +2022-11-14 17:06:01,739 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0777) Prec@1 89.000 (88.000) Prec@5 100.000 (99.217) +2022-11-14 17:06:01,747 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0776) Prec@1 88.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 17:06:01,755 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0775) Prec@1 89.000 (88.040) Prec@5 100.000 (99.280) +2022-11-14 17:06:01,762 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0784) Prec@1 82.000 (87.808) Prec@5 97.000 (99.192) +2022-11-14 17:06:01,770 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0448 (0.0772) Prec@1 93.000 (88.000) Prec@5 100.000 (99.222) +2022-11-14 17:06:01,778 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0769) Prec@1 89.000 (88.036) Prec@5 100.000 (99.250) +2022-11-14 17:06:01,785 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0767) Prec@1 88.000 (88.034) Prec@5 98.000 (99.207) +2022-11-14 17:06:01,793 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0770) Prec@1 87.000 (88.000) Prec@5 99.000 (99.200) +2022-11-14 17:06:01,801 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0769) Prec@1 87.000 (87.968) Prec@5 100.000 (99.226) +2022-11-14 17:06:01,809 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0768) Prec@1 88.000 (87.969) Prec@5 99.000 (99.219) +2022-11-14 17:06:01,816 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0765) Prec@1 89.000 (88.000) Prec@5 100.000 (99.242) +2022-11-14 17:06:01,824 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0769) Prec@1 87.000 (87.971) Prec@5 99.000 (99.235) +2022-11-14 17:06:01,832 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0773) Prec@1 86.000 (87.914) Prec@5 98.000 (99.200) +2022-11-14 17:06:01,839 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0774) Prec@1 87.000 (87.889) Prec@5 99.000 (99.194) +2022-11-14 17:06:01,847 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0772) Prec@1 89.000 (87.919) Prec@5 98.000 (99.162) +2022-11-14 17:06:01,855 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0772) Prec@1 89.000 (87.947) Prec@5 100.000 (99.184) +2022-11-14 17:06:01,863 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0768) Prec@1 93.000 (88.077) Prec@5 100.000 (99.205) +2022-11-14 17:06:01,870 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0763) Prec@1 92.000 (88.175) Prec@5 99.000 (99.200) +2022-11-14 17:06:01,878 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0954 (0.0767) Prec@1 87.000 (88.146) Prec@5 99.000 (99.195) +2022-11-14 17:06:01,886 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0764) Prec@1 89.000 (88.167) Prec@5 99.000 (99.190) +2022-11-14 17:06:01,894 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0759) Prec@1 92.000 (88.256) Prec@5 100.000 (99.209) +2022-11-14 17:06:01,902 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0760) Prec@1 89.000 (88.273) Prec@5 97.000 (99.159) +2022-11-14 17:06:01,909 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0427 (0.0753) Prec@1 95.000 (88.422) Prec@5 99.000 (99.156) +2022-11-14 17:06:01,917 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0757) Prec@1 85.000 (88.348) Prec@5 100.000 (99.174) +2022-11-14 17:06:01,924 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0754) Prec@1 92.000 (88.426) Prec@5 100.000 (99.191) +2022-11-14 17:06:01,932 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.0761) Prec@1 84.000 (88.333) Prec@5 98.000 (99.167) +2022-11-14 17:06:01,940 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0755) Prec@1 92.000 (88.408) Prec@5 99.000 (99.163) +2022-11-14 17:06:01,948 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0759) Prec@1 82.000 (88.280) Prec@5 100.000 (99.180) +2022-11-14 17:06:01,955 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0755) Prec@1 91.000 (88.333) Prec@5 100.000 (99.196) +2022-11-14 17:06:01,963 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0755) Prec@1 87.000 (88.308) Prec@5 97.000 (99.154) +2022-11-14 17:06:01,971 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0753) Prec@1 90.000 (88.340) Prec@5 99.000 (99.151) +2022-11-14 17:06:01,978 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0750) Prec@1 88.000 (88.333) Prec@5 99.000 (99.148) +2022-11-14 17:06:01,985 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0753) Prec@1 82.000 (88.218) Prec@5 100.000 (99.164) +2022-11-14 17:06:01,993 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0751) Prec@1 89.000 (88.232) Prec@5 99.000 (99.161) +2022-11-14 17:06:02,001 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0749) Prec@1 88.000 (88.228) Prec@5 100.000 (99.175) +2022-11-14 17:06:02,008 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0751) Prec@1 88.000 (88.224) Prec@5 98.000 (99.155) +2022-11-14 17:06:02,016 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0753) Prec@1 86.000 (88.186) Prec@5 100.000 (99.169) +2022-11-14 17:06:02,023 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0749) Prec@1 91.000 (88.233) Prec@5 100.000 (99.183) +2022-11-14 17:06:02,031 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0749) Prec@1 89.000 (88.246) Prec@5 99.000 (99.180) +2022-11-14 17:06:02,039 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0747) Prec@1 89.000 (88.258) Prec@5 100.000 (99.194) +2022-11-14 17:06:02,046 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0746) Prec@1 89.000 (88.270) Prec@5 100.000 (99.206) +2022-11-14 17:06:02,054 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0301 (0.0739) Prec@1 96.000 (88.391) Prec@5 100.000 (99.219) +2022-11-14 17:06:02,062 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1056 (0.0744) Prec@1 83.000 (88.308) Prec@5 100.000 (99.231) +2022-11-14 17:06:02,070 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0744) Prec@1 87.000 (88.288) Prec@5 98.000 (99.212) +2022-11-14 17:06:02,077 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0385 (0.0738) Prec@1 93.000 (88.358) Prec@5 100.000 (99.224) +2022-11-14 17:06:02,085 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0737) Prec@1 90.000 (88.382) Prec@5 98.000 (99.206) +2022-11-14 17:06:02,093 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0733) Prec@1 93.000 (88.449) Prec@5 99.000 (99.203) +2022-11-14 17:06:02,101 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0737) Prec@1 86.000 (88.414) Prec@5 100.000 (99.214) +2022-11-14 17:06:02,108 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0740) Prec@1 86.000 (88.380) Prec@5 100.000 (99.225) +2022-11-14 17:06:02,116 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0737) Prec@1 92.000 (88.431) Prec@5 100.000 (99.236) +2022-11-14 17:06:02,124 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0734) Prec@1 90.000 (88.452) Prec@5 100.000 (99.247) +2022-11-14 17:06:02,131 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0730) Prec@1 92.000 (88.500) Prec@5 100.000 (99.257) +2022-11-14 17:06:02,139 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1102 (0.0735) Prec@1 82.000 (88.413) Prec@5 100.000 (99.267) +2022-11-14 17:06:02,146 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0732) Prec@1 93.000 (88.474) Prec@5 100.000 (99.276) +2022-11-14 17:06:02,154 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0732) Prec@1 90.000 (88.494) Prec@5 100.000 (99.286) +2022-11-14 17:06:02,162 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1321 (0.0740) Prec@1 81.000 (88.397) Prec@5 97.000 (99.256) +2022-11-14 17:06:02,169 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0739) Prec@1 90.000 (88.418) Prec@5 100.000 (99.266) +2022-11-14 17:06:02,177 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0740) Prec@1 87.000 (88.400) Prec@5 100.000 (99.275) +2022-11-14 17:06:02,185 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1004 (0.0743) Prec@1 85.000 (88.358) Prec@5 98.000 (99.259) +2022-11-14 17:06:02,192 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0746) Prec@1 82.000 (88.280) Prec@5 100.000 (99.268) +2022-11-14 17:06:02,200 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0747) Prec@1 87.000 (88.265) Prec@5 100.000 (99.277) +2022-11-14 17:06:02,207 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0744) Prec@1 87.000 (88.250) Prec@5 100.000 (99.286) +2022-11-14 17:06:02,215 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0747) Prec@1 84.000 (88.200) Prec@5 99.000 (99.282) +2022-11-14 17:06:02,222 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0750) Prec@1 84.000 (88.151) Prec@5 100.000 (99.291) +2022-11-14 17:06:02,230 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0753) Prec@1 84.000 (88.103) Prec@5 99.000 (99.287) +2022-11-14 17:06:02,237 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0752) Prec@1 91.000 (88.136) Prec@5 99.000 (99.284) +2022-11-14 17:06:02,245 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0751) Prec@1 86.000 (88.112) Prec@5 100.000 (99.292) +2022-11-14 17:06:02,253 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0751) Prec@1 90.000 (88.133) Prec@5 100.000 (99.300) +2022-11-14 17:06:02,260 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0749) Prec@1 90.000 (88.154) Prec@5 100.000 (99.308) +2022-11-14 17:06:02,268 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0421 (0.0746) Prec@1 91.000 (88.185) Prec@5 100.000 (99.315) +2022-11-14 17:06:02,275 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0746) Prec@1 87.000 (88.172) Prec@5 98.000 (99.301) +2022-11-14 17:06:02,283 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0745) Prec@1 90.000 (88.191) Prec@5 99.000 (99.298) +2022-11-14 17:06:02,290 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0746) Prec@1 85.000 (88.158) Prec@5 99.000 (99.295) +2022-11-14 17:06:02,298 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0744) Prec@1 93.000 (88.208) Prec@5 100.000 (99.302) +2022-11-14 17:06:02,305 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0742) Prec@1 91.000 (88.237) Prec@5 98.000 (99.289) +2022-11-14 17:06:02,312 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0744) Prec@1 86.000 (88.214) Prec@5 96.000 (99.255) +2022-11-14 17:06:02,320 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0746) Prec@1 86.000 (88.192) Prec@5 100.000 (99.263) +2022-11-14 17:06:02,327 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0745) Prec@1 89.000 (88.200) Prec@5 99.000 (99.260) +2022-11-14 17:06:02,393 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:06:02,727 Epoch: [462][0/500] Time 0.023 (0.023) Data 0.252 (0.252) Loss 0.0147 (0.0147) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:02,922 Epoch: [462][10/500] Time 0.017 (0.018) Data 0.001 (0.025) Loss 0.0326 (0.0237) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:06:03,116 Epoch: [462][20/500] Time 0.017 (0.017) Data 0.002 (0.014) Loss 0.0342 (0.0272) Prec@1 95.000 (95.333) Prec@5 99.000 (99.667) +2022-11-14 17:06:03,303 Epoch: [462][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0172 (0.0247) Prec@1 97.000 (95.750) Prec@5 100.000 (99.750) +2022-11-14 17:06:03,517 Epoch: [462][40/500] Time 0.018 (0.018) Data 0.002 (0.008) Loss 0.0219 (0.0241) Prec@1 96.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 17:06:03,709 Epoch: [462][50/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0317 (0.0254) Prec@1 95.000 (95.667) Prec@5 100.000 (99.833) +2022-11-14 17:06:03,895 Epoch: [462][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0469 (0.0284) Prec@1 91.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:06:04,085 Epoch: [462][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0312 (0.0288) Prec@1 95.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:06:04,274 Epoch: [462][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0172 (0.0275) Prec@1 98.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 17:06:04,461 Epoch: [462][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0188 (0.0266) Prec@1 98.000 (95.600) Prec@5 100.000 (99.900) +2022-11-14 17:06:04,652 Epoch: [462][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0194 (0.0260) Prec@1 98.000 (95.818) Prec@5 99.000 (99.818) +2022-11-14 17:06:04,842 Epoch: [462][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0362 (0.0268) Prec@1 94.000 (95.667) Prec@5 99.000 (99.750) +2022-11-14 17:06:05,032 Epoch: [462][120/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0574 (0.0292) Prec@1 92.000 (95.385) Prec@5 100.000 (99.769) +2022-11-14 17:06:05,221 Epoch: [462][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0243 (0.0288) Prec@1 96.000 (95.429) Prec@5 100.000 (99.786) +2022-11-14 17:06:05,407 Epoch: [462][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0360 (0.0293) Prec@1 95.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:06:05,607 Epoch: [462][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0468 (0.0304) Prec@1 94.000 (95.312) Prec@5 99.000 (99.750) +2022-11-14 17:06:05,796 Epoch: [462][160/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0325 (0.0305) Prec@1 92.000 (95.118) Prec@5 100.000 (99.765) +2022-11-14 17:06:05,985 Epoch: [462][170/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0516 (0.0317) Prec@1 92.000 (94.944) Prec@5 100.000 (99.778) +2022-11-14 17:06:06,205 Epoch: [462][180/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0325 (0.0317) Prec@1 95.000 (94.947) Prec@5 100.000 (99.789) +2022-11-14 17:06:06,463 Epoch: [462][190/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0253 (0.0314) Prec@1 97.000 (95.050) Prec@5 100.000 (99.800) +2022-11-14 17:06:06,726 Epoch: [462][200/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0442 (0.0320) Prec@1 94.000 (95.000) Prec@5 99.000 (99.762) +2022-11-14 17:06:06,989 Epoch: [462][210/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0159 (0.0313) Prec@1 98.000 (95.136) Prec@5 100.000 (99.773) +2022-11-14 17:06:07,253 Epoch: [462][220/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0308 (0.0313) Prec@1 96.000 (95.174) Prec@5 100.000 (99.783) +2022-11-14 17:06:07,520 Epoch: [462][230/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0249 (0.0310) Prec@1 96.000 (95.208) Prec@5 100.000 (99.792) +2022-11-14 17:06:07,786 Epoch: [462][240/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0574 (0.0321) Prec@1 91.000 (95.040) Prec@5 100.000 (99.800) +2022-11-14 17:06:08,056 Epoch: [462][250/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0332 (0.0321) Prec@1 95.000 (95.038) Prec@5 99.000 (99.769) +2022-11-14 17:06:08,324 Epoch: [462][260/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0364 (0.0323) Prec@1 92.000 (94.926) Prec@5 100.000 (99.778) +2022-11-14 17:06:08,598 Epoch: [462][270/500] Time 0.030 (0.019) Data 0.001 (0.003) Loss 0.0160 (0.0317) Prec@1 97.000 (95.000) Prec@5 100.000 (99.786) +2022-11-14 17:06:08,864 Epoch: [462][280/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0247 (0.0314) Prec@1 96.000 (95.034) Prec@5 100.000 (99.793) +2022-11-14 17:06:09,146 Epoch: [462][290/500] Time 0.030 (0.020) Data 0.002 (0.002) Loss 0.0324 (0.0315) Prec@1 94.000 (95.000) Prec@5 100.000 (99.800) +2022-11-14 17:06:09,406 Epoch: [462][300/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0265 (0.0313) Prec@1 94.000 (94.968) Prec@5 100.000 (99.806) +2022-11-14 17:06:09,677 Epoch: [462][310/500] Time 0.030 (0.020) Data 0.002 (0.002) Loss 0.0322 (0.0313) Prec@1 95.000 (94.969) Prec@5 100.000 (99.812) +2022-11-14 17:06:09,946 Epoch: [462][320/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0407 (0.0316) Prec@1 94.000 (94.939) Prec@5 99.000 (99.788) +2022-11-14 17:06:10,211 Epoch: [462][330/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.0146 (0.0311) Prec@1 98.000 (95.029) Prec@5 100.000 (99.794) +2022-11-14 17:06:10,466 Epoch: [462][340/500] Time 0.021 (0.020) Data 0.002 (0.002) Loss 0.0291 (0.0311) Prec@1 96.000 (95.057) Prec@5 100.000 (99.800) +2022-11-14 17:06:10,725 Epoch: [462][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0326 (0.0311) Prec@1 95.000 (95.056) Prec@5 100.000 (99.806) +2022-11-14 17:06:10,988 Epoch: [462][360/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0223 (0.0309) Prec@1 96.000 (95.081) Prec@5 100.000 (99.811) +2022-11-14 17:06:11,244 Epoch: [462][370/500] Time 0.022 (0.020) Data 0.001 (0.002) Loss 0.0469 (0.0313) Prec@1 91.000 (94.974) Prec@5 100.000 (99.816) +2022-11-14 17:06:11,500 Epoch: [462][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0176 (0.0309) Prec@1 98.000 (95.051) Prec@5 100.000 (99.821) +2022-11-14 17:06:11,756 Epoch: [462][390/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0199 (0.0307) Prec@1 97.000 (95.100) Prec@5 99.000 (99.800) +2022-11-14 17:06:12,014 Epoch: [462][400/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0171 (0.0303) Prec@1 98.000 (95.171) Prec@5 100.000 (99.805) +2022-11-14 17:06:12,274 Epoch: [462][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0216 (0.0301) Prec@1 98.000 (95.238) Prec@5 100.000 (99.810) +2022-11-14 17:06:12,529 Epoch: [462][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0429 (0.0304) Prec@1 91.000 (95.140) Prec@5 100.000 (99.814) +2022-11-14 17:06:12,782 Epoch: [462][430/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0243 (0.0303) Prec@1 97.000 (95.182) Prec@5 100.000 (99.818) +2022-11-14 17:06:13,038 Epoch: [462][440/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0385 (0.0305) Prec@1 92.000 (95.111) Prec@5 100.000 (99.822) +2022-11-14 17:06:13,294 Epoch: [462][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0391 (0.0307) Prec@1 93.000 (95.065) Prec@5 100.000 (99.826) +2022-11-14 17:06:13,548 Epoch: [462][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0217 (0.0305) Prec@1 97.000 (95.106) Prec@5 100.000 (99.830) +2022-11-14 17:06:13,807 Epoch: [462][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0391 (0.0306) Prec@1 94.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 17:06:14,067 Epoch: [462][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0353 (0.0307) Prec@1 95.000 (95.082) Prec@5 99.000 (99.816) +2022-11-14 17:06:14,325 Epoch: [462][490/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0053 (0.0302) Prec@1 99.000 (95.160) Prec@5 100.000 (99.820) +2022-11-14 17:06:14,554 Epoch: [462][499/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0268 (0.0302) Prec@1 95.000 (95.157) Prec@5 100.000 (99.824) +2022-11-14 17:06:14,856 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0735 (0.0735) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:14,863 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0828 (0.0781) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:14,870 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0742) Prec@1 89.000 (88.333) Prec@5 100.000 (100.000) +2022-11-14 17:06:14,881 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0708 (0.0733) Prec@1 90.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 17:06:14,888 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0773) Prec@1 85.000 (88.000) Prec@5 98.000 (99.200) +2022-11-14 17:06:14,895 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0715) Prec@1 92.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 17:06:14,902 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0694) Prec@1 92.000 (89.143) Prec@5 99.000 (99.286) +2022-11-14 17:06:14,910 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0719) Prec@1 84.000 (88.500) Prec@5 99.000 (99.250) +2022-11-14 17:06:14,917 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0737) Prec@1 86.000 (88.222) Prec@5 100.000 (99.333) +2022-11-14 17:06:14,924 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0746) Prec@1 87.000 (88.100) Prec@5 99.000 (99.300) +2022-11-14 17:06:14,931 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0731) Prec@1 89.000 (88.182) Prec@5 100.000 (99.364) +2022-11-14 17:06:14,939 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0881 (0.0743) Prec@1 84.000 (87.833) Prec@5 99.000 (99.333) +2022-11-14 17:06:14,946 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0728) Prec@1 91.000 (88.077) Prec@5 99.000 (99.308) +2022-11-14 17:06:14,954 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0726) Prec@1 89.000 (88.143) Prec@5 100.000 (99.357) +2022-11-14 17:06:14,961 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0725) Prec@1 89.000 (88.200) Prec@5 100.000 (99.400) +2022-11-14 17:06:14,969 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0733) Prec@1 89.000 (88.250) Prec@5 97.000 (99.250) +2022-11-14 17:06:14,976 Test: [16/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0728) Prec@1 90.000 (88.353) Prec@5 98.000 (99.176) +2022-11-14 17:06:14,983 Test: [17/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0997 (0.0743) Prec@1 84.000 (88.111) Prec@5 97.000 (99.056) +2022-11-14 17:06:14,991 Test: [18/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0779 (0.0745) Prec@1 86.000 (88.000) Prec@5 97.000 (98.947) +2022-11-14 17:06:14,998 Test: [19/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0932 (0.0754) Prec@1 86.000 (87.900) Prec@5 99.000 (98.950) +2022-11-14 17:06:15,006 Test: [20/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0756) Prec@1 87.000 (87.857) Prec@5 100.000 (99.000) +2022-11-14 17:06:15,013 Test: [21/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0882 (0.0762) Prec@1 86.000 (87.773) Prec@5 99.000 (99.000) +2022-11-14 17:06:15,021 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0973 (0.0771) Prec@1 86.000 (87.696) Prec@5 97.000 (98.913) +2022-11-14 17:06:15,028 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0836 (0.0774) Prec@1 87.000 (87.667) Prec@5 99.000 (98.917) +2022-11-14 17:06:15,035 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0872 (0.0778) Prec@1 85.000 (87.560) Prec@5 100.000 (98.960) +2022-11-14 17:06:15,043 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0988 (0.0786) Prec@1 87.000 (87.538) Prec@5 98.000 (98.923) +2022-11-14 17:06:15,050 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0482 (0.0775) Prec@1 93.000 (87.741) Prec@5 100.000 (98.963) +2022-11-14 17:06:15,058 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0518 (0.0765) Prec@1 89.000 (87.786) Prec@5 100.000 (99.000) +2022-11-14 17:06:15,065 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0763) Prec@1 88.000 (87.793) Prec@5 99.000 (99.000) +2022-11-14 17:06:15,073 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0761) Prec@1 89.000 (87.833) Prec@5 99.000 (99.000) +2022-11-14 17:06:15,082 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0758) Prec@1 88.000 (87.839) Prec@5 100.000 (99.032) +2022-11-14 17:06:15,089 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0775 (0.0758) Prec@1 89.000 (87.875) Prec@5 100.000 (99.062) +2022-11-14 17:06:15,096 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0747 (0.0758) Prec@1 87.000 (87.848) Prec@5 100.000 (99.091) +2022-11-14 17:06:15,104 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1083 (0.0768) Prec@1 83.000 (87.706) Prec@5 99.000 (99.088) +2022-11-14 17:06:15,111 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0808 (0.0769) Prec@1 87.000 (87.686) Prec@5 98.000 (99.057) +2022-11-14 17:06:15,119 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0787 (0.0769) Prec@1 88.000 (87.694) Prec@5 99.000 (99.056) +2022-11-14 17:06:15,126 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0675 (0.0767) Prec@1 90.000 (87.757) Prec@5 99.000 (99.054) +2022-11-14 17:06:15,134 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0976 (0.0772) Prec@1 82.000 (87.605) Prec@5 100.000 (99.079) +2022-11-14 17:06:15,142 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0767) Prec@1 92.000 (87.718) Prec@5 100.000 (99.103) +2022-11-14 17:06:15,149 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0713 (0.0765) Prec@1 88.000 (87.725) Prec@5 99.000 (99.100) +2022-11-14 17:06:15,157 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0766) Prec@1 88.000 (87.732) Prec@5 99.000 (99.098) +2022-11-14 17:06:15,164 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0839 (0.0768) Prec@1 87.000 (87.714) Prec@5 100.000 (99.119) +2022-11-14 17:06:15,172 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0484 (0.0761) Prec@1 94.000 (87.860) Prec@5 100.000 (99.140) +2022-11-14 17:06:15,179 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0654 (0.0759) Prec@1 89.000 (87.886) Prec@5 99.000 (99.136) +2022-11-14 17:06:15,186 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0612 (0.0756) Prec@1 91.000 (87.956) Prec@5 99.000 (99.133) +2022-11-14 17:06:15,194 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1229 (0.0766) Prec@1 80.000 (87.783) Prec@5 96.000 (99.065) +2022-11-14 17:06:15,201 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0644 (0.0763) Prec@1 89.000 (87.809) Prec@5 99.000 (99.064) +2022-11-14 17:06:15,208 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1102 (0.0770) Prec@1 83.000 (87.708) Prec@5 99.000 (99.062) +2022-11-14 17:06:15,216 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0511 (0.0765) Prec@1 91.000 (87.776) Prec@5 99.000 (99.061) +2022-11-14 17:06:15,223 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0970 (0.0769) Prec@1 83.000 (87.680) Prec@5 100.000 (99.080) +2022-11-14 17:06:15,231 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0452 (0.0763) Prec@1 93.000 (87.784) Prec@5 100.000 (99.098) +2022-11-14 17:06:15,238 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0762) Prec@1 86.000 (87.750) Prec@5 99.000 (99.096) +2022-11-14 17:06:15,246 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0763) Prec@1 87.000 (87.736) Prec@5 100.000 (99.113) +2022-11-14 17:06:15,253 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0570 (0.0759) Prec@1 91.000 (87.796) Prec@5 100.000 (99.130) +2022-11-14 17:06:15,261 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0757) Prec@1 87.000 (87.782) Prec@5 100.000 (99.145) +2022-11-14 17:06:15,268 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0787 (0.0758) Prec@1 87.000 (87.768) Prec@5 99.000 (99.143) +2022-11-14 17:06:15,275 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0767 (0.0758) Prec@1 87.000 (87.754) Prec@5 100.000 (99.158) +2022-11-14 17:06:15,282 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0758) Prec@1 86.000 (87.724) Prec@5 99.000 (99.155) +2022-11-14 17:06:15,290 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1025 (0.0763) Prec@1 83.000 (87.644) Prec@5 99.000 (99.153) +2022-11-14 17:06:15,297 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0586 (0.0760) Prec@1 91.000 (87.700) Prec@5 100.000 (99.167) +2022-11-14 17:06:15,304 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0736 (0.0760) Prec@1 86.000 (87.672) Prec@5 100.000 (99.180) +2022-11-14 17:06:15,312 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0816 (0.0760) Prec@1 87.000 (87.661) Prec@5 100.000 (99.194) +2022-11-14 17:06:15,319 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0759) Prec@1 88.000 (87.667) Prec@5 99.000 (99.190) +2022-11-14 17:06:15,326 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0315 (0.0752) Prec@1 95.000 (87.781) Prec@5 100.000 (99.203) +2022-11-14 17:06:15,334 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0846 (0.0753) Prec@1 86.000 (87.754) Prec@5 100.000 (99.215) +2022-11-14 17:06:15,342 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0753) Prec@1 87.000 (87.742) Prec@5 99.000 (99.212) +2022-11-14 17:06:15,349 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0668 (0.0752) Prec@1 91.000 (87.791) Prec@5 100.000 (99.224) +2022-11-14 17:06:15,357 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0720 (0.0751) Prec@1 90.000 (87.824) Prec@5 99.000 (99.221) +2022-11-14 17:06:15,364 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0906 (0.0754) Prec@1 88.000 (87.826) Prec@5 99.000 (99.217) +2022-11-14 17:06:15,371 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0818 (0.0754) Prec@1 87.000 (87.814) Prec@5 99.000 (99.214) +2022-11-14 17:06:15,379 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0938 (0.0757) Prec@1 87.000 (87.803) Prec@5 100.000 (99.225) +2022-11-14 17:06:15,386 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0332 (0.0751) Prec@1 95.000 (87.903) Prec@5 100.000 (99.236) +2022-11-14 17:06:15,394 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0457 (0.0747) Prec@1 93.000 (87.973) Prec@5 100.000 (99.247) +2022-11-14 17:06:15,401 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0381 (0.0742) Prec@1 94.000 (88.054) Prec@5 100.000 (99.257) +2022-11-14 17:06:15,409 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0984 (0.0745) Prec@1 86.000 (88.027) Prec@5 100.000 (99.267) +2022-11-14 17:06:15,416 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0746) Prec@1 87.000 (88.013) Prec@5 99.000 (99.263) +2022-11-14 17:06:15,424 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0927 (0.0748) Prec@1 85.000 (87.974) Prec@5 99.000 (99.260) +2022-11-14 17:06:15,431 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0878 (0.0750) Prec@1 87.000 (87.962) Prec@5 98.000 (99.244) +2022-11-14 17:06:15,439 Test: [78/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0765 (0.0750) Prec@1 88.000 (87.962) Prec@5 99.000 (99.241) +2022-11-14 17:06:15,446 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0749) Prec@1 86.000 (87.938) Prec@5 100.000 (99.250) +2022-11-14 17:06:15,454 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0945 (0.0752) Prec@1 87.000 (87.926) Prec@5 100.000 (99.259) +2022-11-14 17:06:15,461 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1062 (0.0755) Prec@1 82.000 (87.854) Prec@5 100.000 (99.268) +2022-11-14 17:06:15,469 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1029 (0.0759) Prec@1 84.000 (87.807) Prec@5 99.000 (99.265) +2022-11-14 17:06:15,476 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0608 (0.0757) Prec@1 89.000 (87.821) Prec@5 99.000 (99.262) +2022-11-14 17:06:15,484 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0785 (0.0757) Prec@1 87.000 (87.812) Prec@5 100.000 (99.271) +2022-11-14 17:06:15,491 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1226 (0.0763) Prec@1 82.000 (87.744) Prec@5 99.000 (99.267) +2022-11-14 17:06:15,498 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0629 (0.0761) Prec@1 88.000 (87.747) Prec@5 99.000 (99.264) +2022-11-14 17:06:15,506 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0744 (0.0761) Prec@1 89.000 (87.761) Prec@5 99.000 (99.261) +2022-11-14 17:06:15,513 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0663 (0.0760) Prec@1 88.000 (87.764) Prec@5 99.000 (99.258) +2022-11-14 17:06:15,521 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0826 (0.0761) Prec@1 88.000 (87.767) Prec@5 99.000 (99.256) +2022-11-14 17:06:15,528 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0408 (0.0757) Prec@1 93.000 (87.824) Prec@5 99.000 (99.253) +2022-11-14 17:06:15,535 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0546 (0.0754) Prec@1 91.000 (87.859) Prec@5 100.000 (99.261) +2022-11-14 17:06:15,543 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0902 (0.0756) Prec@1 86.000 (87.839) Prec@5 99.000 (99.258) +2022-11-14 17:06:15,551 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0709 (0.0755) Prec@1 88.000 (87.840) Prec@5 100.000 (99.266) +2022-11-14 17:06:15,558 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0755) Prec@1 90.000 (87.863) Prec@5 98.000 (99.253) +2022-11-14 17:06:15,565 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0640 (0.0754) Prec@1 93.000 (87.917) Prec@5 99.000 (99.250) +2022-11-14 17:06:15,573 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0636 (0.0753) Prec@1 90.000 (87.938) Prec@5 99.000 (99.247) +2022-11-14 17:06:15,580 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0877 (0.0754) Prec@1 86.000 (87.918) Prec@5 99.000 (99.245) +2022-11-14 17:06:15,587 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0756) Prec@1 86.000 (87.899) Prec@5 99.000 (99.242) +2022-11-14 17:06:15,595 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0755) Prec@1 90.000 (87.920) Prec@5 99.000 (99.240) +2022-11-14 17:06:15,649 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:06:16,001 Epoch: [463][0/500] Time 0.025 (0.025) Data 0.234 (0.234) Loss 0.0611 (0.0611) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 17:06:16,218 Epoch: [463][10/500] Time 0.017 (0.020) Data 0.001 (0.023) Loss 0.0535 (0.0573) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 17:06:16,417 Epoch: [463][20/500] Time 0.017 (0.019) Data 0.002 (0.013) Loss 0.0364 (0.0503) Prec@1 94.000 (91.333) Prec@5 99.000 (99.333) +2022-11-14 17:06:16,618 Epoch: [463][30/500] Time 0.016 (0.018) Data 0.002 (0.009) Loss 0.0261 (0.0443) Prec@1 95.000 (92.250) Prec@5 100.000 (99.500) +2022-11-14 17:06:16,813 Epoch: [463][40/500] Time 0.016 (0.018) Data 0.002 (0.007) Loss 0.0212 (0.0397) Prec@1 97.000 (93.200) Prec@5 100.000 (99.600) +2022-11-14 17:06:17,014 Epoch: [463][50/500] Time 0.016 (0.018) Data 0.002 (0.006) Loss 0.0436 (0.0403) Prec@1 93.000 (93.167) Prec@5 100.000 (99.667) +2022-11-14 17:06:17,222 Epoch: [463][60/500] Time 0.020 (0.018) Data 0.002 (0.006) Loss 0.0323 (0.0392) Prec@1 94.000 (93.286) Prec@5 100.000 (99.714) +2022-11-14 17:06:17,429 Epoch: [463][70/500] Time 0.015 (0.018) Data 0.003 (0.005) Loss 0.0301 (0.0380) Prec@1 95.000 (93.500) Prec@5 100.000 (99.750) +2022-11-14 17:06:17,630 Epoch: [463][80/500] Time 0.017 (0.018) Data 0.002 (0.005) Loss 0.0373 (0.0379) Prec@1 95.000 (93.667) Prec@5 100.000 (99.778) +2022-11-14 17:06:17,838 Epoch: [463][90/500] Time 0.018 (0.018) Data 0.003 (0.004) Loss 0.0342 (0.0376) Prec@1 94.000 (93.700) Prec@5 99.000 (99.700) +2022-11-14 17:06:18,040 Epoch: [463][100/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0120 (0.0352) Prec@1 98.000 (94.091) Prec@5 100.000 (99.727) +2022-11-14 17:06:18,239 Epoch: [463][110/500] Time 0.020 (0.018) Data 0.002 (0.004) Loss 0.0354 (0.0353) Prec@1 93.000 (94.000) Prec@5 100.000 (99.750) +2022-11-14 17:06:18,431 Epoch: [463][120/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0348 (0.0352) Prec@1 94.000 (94.000) Prec@5 99.000 (99.692) +2022-11-14 17:06:18,620 Epoch: [463][130/500] Time 0.017 (0.018) Data 0.001 (0.003) Loss 0.0236 (0.0344) Prec@1 97.000 (94.214) Prec@5 100.000 (99.714) +2022-11-14 17:06:18,821 Epoch: [463][140/500] Time 0.023 (0.018) Data 0.001 (0.003) Loss 0.0280 (0.0340) Prec@1 94.000 (94.200) Prec@5 100.000 (99.733) +2022-11-14 17:06:19,078 Epoch: [463][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0391 (0.0343) Prec@1 95.000 (94.250) Prec@5 100.000 (99.750) +2022-11-14 17:06:19,340 Epoch: [463][160/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0267 (0.0338) Prec@1 96.000 (94.353) Prec@5 100.000 (99.765) +2022-11-14 17:06:19,603 Epoch: [463][170/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0292 (0.0336) Prec@1 94.000 (94.333) Prec@5 99.000 (99.722) +2022-11-14 17:06:19,869 Epoch: [463][180/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0492 (0.0344) Prec@1 91.000 (94.158) Prec@5 99.000 (99.684) +2022-11-14 17:06:20,145 Epoch: [463][190/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0417 (0.0348) Prec@1 92.000 (94.050) Prec@5 100.000 (99.700) +2022-11-14 17:06:20,412 Epoch: [463][200/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0392 (0.0350) Prec@1 96.000 (94.143) Prec@5 100.000 (99.714) +2022-11-14 17:06:20,679 Epoch: [463][210/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0232 (0.0344) Prec@1 96.000 (94.227) Prec@5 99.000 (99.682) +2022-11-14 17:06:20,946 Epoch: [463][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0325 (0.0344) Prec@1 95.000 (94.261) Prec@5 100.000 (99.696) +2022-11-14 17:06:21,217 Epoch: [463][230/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0483 (0.0349) Prec@1 91.000 (94.125) Prec@5 100.000 (99.708) +2022-11-14 17:06:21,490 Epoch: [463][240/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0316 (0.0348) Prec@1 95.000 (94.160) Prec@5 99.000 (99.680) +2022-11-14 17:06:21,759 Epoch: [463][250/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0380 (0.0349) Prec@1 94.000 (94.154) Prec@5 100.000 (99.692) +2022-11-14 17:06:22,031 Epoch: [463][260/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0202 (0.0344) Prec@1 96.000 (94.222) Prec@5 100.000 (99.704) +2022-11-14 17:06:22,292 Epoch: [463][270/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0377 (0.0345) Prec@1 94.000 (94.214) Prec@5 100.000 (99.714) +2022-11-14 17:06:22,557 Epoch: [463][280/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0282 (0.0343) Prec@1 95.000 (94.241) Prec@5 99.000 (99.690) +2022-11-14 17:06:22,823 Epoch: [463][290/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0545 (0.0350) Prec@1 91.000 (94.133) Prec@5 100.000 (99.700) +2022-11-14 17:06:23,090 Epoch: [463][300/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0226 (0.0346) Prec@1 95.000 (94.161) Prec@5 100.000 (99.710) +2022-11-14 17:06:23,352 Epoch: [463][310/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0371 (0.0346) Prec@1 94.000 (94.156) Prec@5 99.000 (99.688) +2022-11-14 17:06:23,613 Epoch: [463][320/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0519 (0.0352) Prec@1 92.000 (94.091) Prec@5 99.000 (99.667) +2022-11-14 17:06:23,874 Epoch: [463][330/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0183 (0.0347) Prec@1 95.000 (94.118) Prec@5 100.000 (99.676) +2022-11-14 17:06:24,137 Epoch: [463][340/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0150 (0.0341) Prec@1 98.000 (94.229) Prec@5 100.000 (99.686) +2022-11-14 17:06:24,395 Epoch: [463][350/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0367 (0.0342) Prec@1 95.000 (94.250) Prec@5 100.000 (99.694) +2022-11-14 17:06:24,652 Epoch: [463][360/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0222 (0.0339) Prec@1 94.000 (94.243) Prec@5 100.000 (99.703) +2022-11-14 17:06:24,910 Epoch: [463][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0305 (0.0338) Prec@1 96.000 (94.289) Prec@5 100.000 (99.711) +2022-11-14 17:06:25,171 Epoch: [463][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0334 (0.0338) Prec@1 93.000 (94.256) Prec@5 100.000 (99.718) +2022-11-14 17:06:25,429 Epoch: [463][390/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0277 (0.0336) Prec@1 97.000 (94.325) Prec@5 100.000 (99.725) +2022-11-14 17:06:25,690 Epoch: [463][400/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0373 (0.0337) Prec@1 93.000 (94.293) Prec@5 100.000 (99.732) +2022-11-14 17:06:25,952 Epoch: [463][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0270 (0.0335) Prec@1 97.000 (94.357) Prec@5 100.000 (99.738) +2022-11-14 17:06:26,213 Epoch: [463][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0172 (0.0332) Prec@1 97.000 (94.419) Prec@5 100.000 (99.744) +2022-11-14 17:06:26,472 Epoch: [463][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0312 (0.0331) Prec@1 92.000 (94.364) Prec@5 100.000 (99.750) +2022-11-14 17:06:26,731 Epoch: [463][440/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0391 (0.0332) Prec@1 93.000 (94.333) Prec@5 100.000 (99.756) +2022-11-14 17:06:26,994 Epoch: [463][450/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0156 (0.0329) Prec@1 97.000 (94.391) Prec@5 100.000 (99.761) +2022-11-14 17:06:27,260 Epoch: [463][460/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0268 (0.0327) Prec@1 95.000 (94.404) Prec@5 100.000 (99.766) +2022-11-14 17:06:27,519 Epoch: [463][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0356 (0.0328) Prec@1 95.000 (94.417) Prec@5 100.000 (99.771) +2022-11-14 17:06:27,781 Epoch: [463][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0311 (0.0328) Prec@1 96.000 (94.449) Prec@5 100.000 (99.776) +2022-11-14 17:06:28,046 Epoch: [463][490/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0262 (0.0326) Prec@1 95.000 (94.460) Prec@5 100.000 (99.780) +2022-11-14 17:06:28,284 Epoch: [463][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0293 (0.0326) Prec@1 95.000 (94.471) Prec@5 100.000 (99.784) +2022-11-14 17:06:28,589 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0849 (0.0849) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 17:06:28,597 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0722 (0.0785) Prec@1 88.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 17:06:28,605 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0864 (0.0812) Prec@1 85.000 (86.333) Prec@5 99.000 (99.333) +2022-11-14 17:06:28,614 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0808) Prec@1 87.000 (86.500) Prec@5 98.000 (99.000) +2022-11-14 17:06:28,621 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0535 (0.0753) Prec@1 90.000 (87.200) Prec@5 100.000 (99.200) +2022-11-14 17:06:28,628 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0716) Prec@1 91.000 (87.833) Prec@5 100.000 (99.333) +2022-11-14 17:06:28,635 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0720 (0.0717) Prec@1 90.000 (88.143) Prec@5 99.000 (99.286) +2022-11-14 17:06:28,643 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0880 (0.0737) Prec@1 86.000 (87.875) Prec@5 99.000 (99.250) +2022-11-14 17:06:28,650 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1124 (0.0780) Prec@1 83.000 (87.333) Prec@5 98.000 (99.111) +2022-11-14 17:06:28,657 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0773) Prec@1 89.000 (87.500) Prec@5 99.000 (99.100) +2022-11-14 17:06:28,665 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0769) Prec@1 89.000 (87.636) Prec@5 100.000 (99.182) +2022-11-14 17:06:28,673 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0774) Prec@1 87.000 (87.583) Prec@5 98.000 (99.083) +2022-11-14 17:06:28,680 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0478 (0.0751) Prec@1 91.000 (87.846) Prec@5 100.000 (99.154) +2022-11-14 17:06:28,688 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0743) Prec@1 92.000 (88.143) Prec@5 99.000 (99.143) +2022-11-14 17:06:28,696 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0744) Prec@1 88.000 (88.133) Prec@5 100.000 (99.200) +2022-11-14 17:06:28,704 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0738) Prec@1 90.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 17:06:28,711 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0721) Prec@1 95.000 (88.647) Prec@5 98.000 (99.176) +2022-11-14 17:06:28,719 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1210 (0.0748) Prec@1 81.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 17:06:28,726 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0745) Prec@1 88.000 (88.211) Prec@5 98.000 (99.158) +2022-11-14 17:06:28,734 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0755) Prec@1 86.000 (88.100) Prec@5 97.000 (99.050) +2022-11-14 17:06:28,742 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0752) Prec@1 89.000 (88.143) Prec@5 99.000 (99.048) +2022-11-14 17:06:28,749 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0757) Prec@1 88.000 (88.136) Prec@5 100.000 (99.091) +2022-11-14 17:06:28,757 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1090 (0.0771) Prec@1 85.000 (88.000) Prec@5 98.000 (99.043) +2022-11-14 17:06:28,765 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0774) Prec@1 87.000 (87.958) Prec@5 99.000 (99.042) +2022-11-14 17:06:28,772 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0777) Prec@1 86.000 (87.880) Prec@5 100.000 (99.080) +2022-11-14 17:06:28,780 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0781) Prec@1 85.000 (87.769) Prec@5 98.000 (99.038) +2022-11-14 17:06:28,787 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0773) Prec@1 91.000 (87.889) Prec@5 100.000 (99.074) +2022-11-14 17:06:28,795 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0765) Prec@1 91.000 (88.000) Prec@5 100.000 (99.107) +2022-11-14 17:06:28,802 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0763) Prec@1 89.000 (88.034) Prec@5 99.000 (99.103) +2022-11-14 17:06:28,810 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0765) Prec@1 88.000 (88.033) Prec@5 99.000 (99.100) +2022-11-14 17:06:28,817 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0763) Prec@1 88.000 (88.032) Prec@5 100.000 (99.129) +2022-11-14 17:06:28,826 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0765) Prec@1 86.000 (87.969) Prec@5 100.000 (99.156) +2022-11-14 17:06:28,834 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0771) Prec@1 84.000 (87.848) Prec@5 100.000 (99.182) +2022-11-14 17:06:28,841 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0779) Prec@1 84.000 (87.735) Prec@5 100.000 (99.206) +2022-11-14 17:06:28,849 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0782) Prec@1 87.000 (87.714) Prec@5 97.000 (99.143) +2022-11-14 17:06:28,857 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0779) Prec@1 91.000 (87.806) Prec@5 99.000 (99.139) +2022-11-14 17:06:28,864 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0774) Prec@1 93.000 (87.946) Prec@5 98.000 (99.108) +2022-11-14 17:06:28,872 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1145 (0.0784) Prec@1 82.000 (87.789) Prec@5 100.000 (99.132) +2022-11-14 17:06:28,879 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0776) Prec@1 94.000 (87.949) Prec@5 99.000 (99.128) +2022-11-14 17:06:28,887 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0773) Prec@1 88.000 (87.950) Prec@5 100.000 (99.150) +2022-11-14 17:06:28,894 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1113 (0.0782) Prec@1 83.000 (87.829) Prec@5 98.000 (99.122) +2022-11-14 17:06:28,902 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0786) Prec@1 85.000 (87.762) Prec@5 99.000 (99.119) +2022-11-14 17:06:28,909 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0408 (0.0777) Prec@1 94.000 (87.907) Prec@5 100.000 (99.140) +2022-11-14 17:06:28,917 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0776) Prec@1 88.000 (87.909) Prec@5 99.000 (99.136) +2022-11-14 17:06:28,925 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0775) Prec@1 87.000 (87.889) Prec@5 99.000 (99.133) +2022-11-14 17:06:28,933 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1119 (0.0782) Prec@1 84.000 (87.804) Prec@5 98.000 (99.109) +2022-11-14 17:06:28,940 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0782) Prec@1 87.000 (87.787) Prec@5 100.000 (99.128) +2022-11-14 17:06:28,948 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0785) Prec@1 85.000 (87.729) Prec@5 100.000 (99.146) +2022-11-14 17:06:28,956 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0782) Prec@1 89.000 (87.755) Prec@5 99.000 (99.143) +2022-11-14 17:06:28,963 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0785) Prec@1 86.000 (87.720) Prec@5 99.000 (99.140) +2022-11-14 17:06:28,971 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0784) Prec@1 88.000 (87.725) Prec@5 100.000 (99.157) +2022-11-14 17:06:28,979 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0784) Prec@1 88.000 (87.731) Prec@5 98.000 (99.135) +2022-11-14 17:06:28,986 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0784) Prec@1 88.000 (87.736) Prec@5 100.000 (99.151) +2022-11-14 17:06:28,994 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0783) Prec@1 87.000 (87.722) Prec@5 100.000 (99.167) +2022-11-14 17:06:29,001 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0785) Prec@1 86.000 (87.691) Prec@5 100.000 (99.182) +2022-11-14 17:06:29,009 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0780) Prec@1 92.000 (87.768) Prec@5 100.000 (99.196) +2022-11-14 17:06:29,017 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0779) Prec@1 88.000 (87.772) Prec@5 100.000 (99.211) +2022-11-14 17:06:29,024 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0778) Prec@1 88.000 (87.776) Prec@5 99.000 (99.207) +2022-11-14 17:06:29,032 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0779) Prec@1 85.000 (87.729) Prec@5 99.000 (99.203) +2022-11-14 17:06:29,039 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0777) Prec@1 91.000 (87.783) Prec@5 100.000 (99.217) +2022-11-14 17:06:29,047 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0777) Prec@1 89.000 (87.803) Prec@5 100.000 (99.230) +2022-11-14 17:06:29,055 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0533 (0.0773) Prec@1 92.000 (87.871) Prec@5 99.000 (99.226) +2022-11-14 17:06:29,062 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0772) Prec@1 88.000 (87.873) Prec@5 100.000 (99.238) +2022-11-14 17:06:29,070 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0766) Prec@1 94.000 (87.969) Prec@5 100.000 (99.250) +2022-11-14 17:06:29,077 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1132 (0.0772) Prec@1 83.000 (87.892) Prec@5 99.000 (99.246) +2022-11-14 17:06:29,086 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0770) Prec@1 89.000 (87.909) Prec@5 100.000 (99.258) +2022-11-14 17:06:29,093 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0402 (0.0764) Prec@1 92.000 (87.970) Prec@5 100.000 (99.269) +2022-11-14 17:06:29,101 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0764) Prec@1 90.000 (88.000) Prec@5 100.000 (99.279) +2022-11-14 17:06:29,109 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0765) Prec@1 88.000 (88.000) Prec@5 99.000 (99.275) +2022-11-14 17:06:29,116 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0764) Prec@1 89.000 (88.014) Prec@5 99.000 (99.271) +2022-11-14 17:06:29,124 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1175 (0.0770) Prec@1 82.000 (87.930) Prec@5 100.000 (99.282) +2022-11-14 17:06:29,131 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0767) Prec@1 90.000 (87.958) Prec@5 100.000 (99.292) +2022-11-14 17:06:29,139 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0763) Prec@1 94.000 (88.041) Prec@5 98.000 (99.274) +2022-11-14 17:06:29,146 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0758) Prec@1 93.000 (88.108) Prec@5 100.000 (99.284) +2022-11-14 17:06:29,154 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1267 (0.0765) Prec@1 81.000 (88.013) Prec@5 100.000 (99.293) +2022-11-14 17:06:29,161 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0762) Prec@1 91.000 (88.053) Prec@5 99.000 (99.289) +2022-11-14 17:06:29,169 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0761) Prec@1 87.000 (88.039) Prec@5 99.000 (99.286) +2022-11-14 17:06:29,176 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0763) Prec@1 86.000 (88.013) Prec@5 97.000 (99.256) +2022-11-14 17:06:29,184 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0765) Prec@1 87.000 (88.000) Prec@5 99.000 (99.253) +2022-11-14 17:06:29,192 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0765) Prec@1 86.000 (87.975) Prec@5 100.000 (99.263) +2022-11-14 17:06:29,199 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0766) Prec@1 88.000 (87.975) Prec@5 99.000 (99.259) +2022-11-14 17:06:29,207 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0767) Prec@1 83.000 (87.915) Prec@5 100.000 (99.268) +2022-11-14 17:06:29,214 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0768) Prec@1 87.000 (87.904) Prec@5 99.000 (99.265) +2022-11-14 17:06:29,222 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0767) Prec@1 89.000 (87.917) Prec@5 99.000 (99.262) +2022-11-14 17:06:29,229 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0770) Prec@1 83.000 (87.859) Prec@5 99.000 (99.259) +2022-11-14 17:06:29,237 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0773) Prec@1 83.000 (87.802) Prec@5 99.000 (99.256) +2022-11-14 17:06:29,244 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0772) Prec@1 90.000 (87.828) Prec@5 100.000 (99.264) +2022-11-14 17:06:29,252 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0770) Prec@1 91.000 (87.864) Prec@5 98.000 (99.250) +2022-11-14 17:06:29,260 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0768) Prec@1 91.000 (87.899) Prec@5 100.000 (99.258) +2022-11-14 17:06:29,267 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0768) Prec@1 89.000 (87.911) Prec@5 100.000 (99.267) +2022-11-14 17:06:29,275 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0764) Prec@1 92.000 (87.956) Prec@5 100.000 (99.275) +2022-11-14 17:06:29,282 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0761) Prec@1 92.000 (88.000) Prec@5 100.000 (99.283) +2022-11-14 17:06:29,290 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0763) Prec@1 85.000 (87.968) Prec@5 100.000 (99.290) +2022-11-14 17:06:29,298 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0764) Prec@1 86.000 (87.947) Prec@5 100.000 (99.298) +2022-11-14 17:06:29,306 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0764) Prec@1 85.000 (87.916) Prec@5 99.000 (99.295) +2022-11-14 17:06:29,313 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0763) Prec@1 91.000 (87.948) Prec@5 99.000 (99.292) +2022-11-14 17:06:29,320 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0760) Prec@1 92.000 (87.990) Prec@5 99.000 (99.289) +2022-11-14 17:06:29,327 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.0763) Prec@1 84.000 (87.949) Prec@5 99.000 (99.286) +2022-11-14 17:06:29,334 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0765) Prec@1 86.000 (87.929) Prec@5 99.000 (99.283) +2022-11-14 17:06:29,342 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0764) Prec@1 88.000 (87.930) Prec@5 100.000 (99.290) +2022-11-14 17:06:29,409 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:06:29,738 Epoch: [464][0/500] Time 0.024 (0.024) Data 0.248 (0.248) Loss 0.0307 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:29,949 Epoch: [464][10/500] Time 0.015 (0.019) Data 0.002 (0.024) Loss 0.0378 (0.0343) Prec@1 92.000 (93.500) Prec@5 99.000 (99.500) +2022-11-14 17:06:30,146 Epoch: [464][20/500] Time 0.017 (0.018) Data 0.001 (0.013) Loss 0.0425 (0.0370) Prec@1 91.000 (92.667) Prec@5 99.000 (99.333) +2022-11-14 17:06:30,346 Epoch: [464][30/500] Time 0.016 (0.018) Data 0.002 (0.010) Loss 0.0294 (0.0351) Prec@1 94.000 (93.000) Prec@5 100.000 (99.500) +2022-11-14 17:06:30,542 Epoch: [464][40/500] Time 0.017 (0.018) Data 0.002 (0.008) Loss 0.0213 (0.0323) Prec@1 97.000 (93.800) Prec@5 100.000 (99.600) +2022-11-14 17:06:30,745 Epoch: [464][50/500] Time 0.016 (0.018) Data 0.002 (0.007) Loss 0.0462 (0.0346) Prec@1 92.000 (93.500) Prec@5 100.000 (99.667) +2022-11-14 17:06:30,941 Epoch: [464][60/500] Time 0.016 (0.018) Data 0.002 (0.006) Loss 0.0432 (0.0359) Prec@1 93.000 (93.429) Prec@5 100.000 (99.714) +2022-11-14 17:06:31,145 Epoch: [464][70/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0346 (0.0357) Prec@1 93.000 (93.375) Prec@5 100.000 (99.750) +2022-11-14 17:06:31,341 Epoch: [464][80/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0516 (0.0375) Prec@1 90.000 (93.000) Prec@5 99.000 (99.667) +2022-11-14 17:06:31,544 Epoch: [464][90/500] Time 0.015 (0.018) Data 0.002 (0.004) Loss 0.0185 (0.0356) Prec@1 98.000 (93.500) Prec@5 100.000 (99.700) +2022-11-14 17:06:31,740 Epoch: [464][100/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0309 (0.0352) Prec@1 95.000 (93.636) Prec@5 100.000 (99.727) +2022-11-14 17:06:31,941 Epoch: [464][110/500] Time 0.016 (0.018) Data 0.002 (0.004) Loss 0.0456 (0.0360) Prec@1 93.000 (93.583) Prec@5 100.000 (99.750) +2022-11-14 17:06:32,139 Epoch: [464][120/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0264 (0.0353) Prec@1 96.000 (93.769) Prec@5 100.000 (99.769) +2022-11-14 17:06:32,383 Epoch: [464][130/500] Time 0.032 (0.018) Data 0.001 (0.004) Loss 0.0273 (0.0347) Prec@1 97.000 (94.000) Prec@5 99.000 (99.714) +2022-11-14 17:06:32,764 Epoch: [464][140/500] Time 0.035 (0.019) Data 0.002 (0.003) Loss 0.0240 (0.0340) Prec@1 97.000 (94.200) Prec@5 100.000 (99.733) +2022-11-14 17:06:33,150 Epoch: [464][150/500] Time 0.040 (0.020) Data 0.002 (0.003) Loss 0.0167 (0.0329) Prec@1 96.000 (94.312) Prec@5 100.000 (99.750) +2022-11-14 17:06:33,528 Epoch: [464][160/500] Time 0.033 (0.021) Data 0.002 (0.003) Loss 0.0463 (0.0337) Prec@1 92.000 (94.176) Prec@5 100.000 (99.765) +2022-11-14 17:06:33,903 Epoch: [464][170/500] Time 0.036 (0.022) Data 0.001 (0.003) Loss 0.0258 (0.0333) Prec@1 96.000 (94.278) Prec@5 100.000 (99.778) +2022-11-14 17:06:34,285 Epoch: [464][180/500] Time 0.036 (0.022) Data 0.002 (0.003) Loss 0.0191 (0.0325) Prec@1 97.000 (94.421) Prec@5 100.000 (99.789) +2022-11-14 17:06:34,660 Epoch: [464][190/500] Time 0.035 (0.023) Data 0.002 (0.003) Loss 0.0395 (0.0329) Prec@1 95.000 (94.450) Prec@5 100.000 (99.800) +2022-11-14 17:06:35,019 Epoch: [464][200/500] Time 0.035 (0.023) Data 0.002 (0.003) Loss 0.0368 (0.0331) Prec@1 94.000 (94.429) Prec@5 100.000 (99.810) +2022-11-14 17:06:35,385 Epoch: [464][210/500] Time 0.034 (0.024) Data 0.002 (0.003) Loss 0.0410 (0.0334) Prec@1 92.000 (94.318) Prec@5 100.000 (99.818) +2022-11-14 17:06:35,751 Epoch: [464][220/500] Time 0.036 (0.024) Data 0.002 (0.003) Loss 0.0260 (0.0331) Prec@1 95.000 (94.348) Prec@5 100.000 (99.826) +2022-11-14 17:06:36,127 Epoch: [464][230/500] Time 0.042 (0.024) Data 0.001 (0.003) Loss 0.0322 (0.0331) Prec@1 94.000 (94.333) Prec@5 100.000 (99.833) +2022-11-14 17:06:36,395 Epoch: [464][240/500] Time 0.021 (0.024) Data 0.002 (0.003) Loss 0.0195 (0.0325) Prec@1 96.000 (94.400) Prec@5 100.000 (99.840) +2022-11-14 17:06:36,622 Epoch: [464][250/500] Time 0.022 (0.024) Data 0.001 (0.003) Loss 0.0178 (0.0320) Prec@1 99.000 (94.577) Prec@5 100.000 (99.846) +2022-11-14 17:06:36,847 Epoch: [464][260/500] Time 0.020 (0.024) Data 0.002 (0.003) Loss 0.0189 (0.0315) Prec@1 97.000 (94.667) Prec@5 100.000 (99.852) +2022-11-14 17:06:37,072 Epoch: [464][270/500] Time 0.022 (0.024) Data 0.001 (0.003) Loss 0.0157 (0.0309) Prec@1 98.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 17:06:37,299 Epoch: [464][280/500] Time 0.021 (0.024) Data 0.002 (0.003) Loss 0.0210 (0.0306) Prec@1 97.000 (94.862) Prec@5 100.000 (99.862) +2022-11-14 17:06:37,530 Epoch: [464][290/500] Time 0.024 (0.024) Data 0.002 (0.003) Loss 0.0426 (0.0310) Prec@1 93.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 17:06:37,757 Epoch: [464][300/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0361 (0.0311) Prec@1 94.000 (94.774) Prec@5 99.000 (99.839) +2022-11-14 17:06:37,982 Epoch: [464][310/500] Time 0.019 (0.023) Data 0.001 (0.002) Loss 0.0508 (0.0317) Prec@1 92.000 (94.688) Prec@5 100.000 (99.844) +2022-11-14 17:06:38,210 Epoch: [464][320/500] Time 0.021 (0.023) Data 0.001 (0.002) Loss 0.0357 (0.0319) Prec@1 96.000 (94.727) Prec@5 99.000 (99.818) +2022-11-14 17:06:38,434 Epoch: [464][330/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0101 (0.0312) Prec@1 98.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 17:06:38,662 Epoch: [464][340/500] Time 0.022 (0.023) Data 0.001 (0.002) Loss 0.0499 (0.0318) Prec@1 92.000 (94.743) Prec@5 100.000 (99.829) +2022-11-14 17:06:38,891 Epoch: [464][350/500] Time 0.020 (0.023) Data 0.001 (0.002) Loss 0.0375 (0.0319) Prec@1 95.000 (94.750) Prec@5 99.000 (99.806) +2022-11-14 17:06:39,123 Epoch: [464][360/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0304 (0.0319) Prec@1 95.000 (94.757) Prec@5 100.000 (99.811) +2022-11-14 17:06:39,348 Epoch: [464][370/500] Time 0.018 (0.023) Data 0.003 (0.002) Loss 0.0233 (0.0317) Prec@1 97.000 (94.816) Prec@5 99.000 (99.789) +2022-11-14 17:06:39,575 Epoch: [464][380/500] Time 0.023 (0.023) Data 0.001 (0.002) Loss 0.0464 (0.0320) Prec@1 92.000 (94.744) Prec@5 100.000 (99.795) +2022-11-14 17:06:39,801 Epoch: [464][390/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0142 (0.0316) Prec@1 99.000 (94.850) Prec@5 100.000 (99.800) +2022-11-14 17:06:40,031 Epoch: [464][400/500] Time 0.022 (0.023) Data 0.001 (0.002) Loss 0.0333 (0.0316) Prec@1 95.000 (94.854) Prec@5 100.000 (99.805) +2022-11-14 17:06:40,259 Epoch: [464][410/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0309 (0.0316) Prec@1 95.000 (94.857) Prec@5 100.000 (99.810) +2022-11-14 17:06:40,487 Epoch: [464][420/500] Time 0.021 (0.023) Data 0.002 (0.002) Loss 0.0359 (0.0317) Prec@1 95.000 (94.860) Prec@5 100.000 (99.814) +2022-11-14 17:06:40,713 Epoch: [464][430/500] Time 0.020 (0.023) Data 0.002 (0.002) Loss 0.0215 (0.0315) Prec@1 96.000 (94.886) Prec@5 100.000 (99.818) +2022-11-14 17:06:40,941 Epoch: [464][440/500] Time 0.021 (0.022) Data 0.002 (0.002) Loss 0.0353 (0.0316) Prec@1 94.000 (94.867) Prec@5 100.000 (99.822) +2022-11-14 17:06:41,170 Epoch: [464][450/500] Time 0.020 (0.022) Data 0.002 (0.002) Loss 0.0235 (0.0314) Prec@1 95.000 (94.870) Prec@5 100.000 (99.826) +2022-11-14 17:06:41,397 Epoch: [464][460/500] Time 0.022 (0.022) Data 0.001 (0.002) Loss 0.0596 (0.0320) Prec@1 90.000 (94.766) Prec@5 100.000 (99.830) +2022-11-14 17:06:41,627 Epoch: [464][470/500] Time 0.020 (0.022) Data 0.002 (0.002) Loss 0.0360 (0.0321) Prec@1 95.000 (94.771) Prec@5 100.000 (99.833) +2022-11-14 17:06:41,859 Epoch: [464][480/500] Time 0.021 (0.022) Data 0.002 (0.002) Loss 0.0589 (0.0326) Prec@1 90.000 (94.673) Prec@5 100.000 (99.837) +2022-11-14 17:06:42,092 Epoch: [464][490/500] Time 0.021 (0.022) Data 0.001 (0.002) Loss 0.0237 (0.0324) Prec@1 96.000 (94.700) Prec@5 100.000 (99.840) +2022-11-14 17:06:42,297 Epoch: [464][499/500] Time 0.021 (0.022) Data 0.002 (0.002) Loss 0.0192 (0.0322) Prec@1 98.000 (94.765) Prec@5 100.000 (99.843) +2022-11-14 17:06:42,606 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0573 (0.0573) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:42,614 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0711 (0.0642) Prec@1 87.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:06:42,622 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0761 (0.0682) Prec@1 88.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 17:06:42,631 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0564 (0.0652) Prec@1 93.000 (90.000) Prec@5 98.000 (99.250) +2022-11-14 17:06:42,638 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0551 (0.0632) Prec@1 90.000 (90.000) Prec@5 100.000 (99.400) +2022-11-14 17:06:42,646 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0360 (0.0587) Prec@1 94.000 (90.667) Prec@5 100.000 (99.500) +2022-11-14 17:06:42,653 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0583) Prec@1 90.000 (90.571) Prec@5 100.000 (99.571) +2022-11-14 17:06:42,663 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0854 (0.0617) Prec@1 87.000 (90.125) Prec@5 100.000 (99.625) +2022-11-14 17:06:42,670 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0638) Prec@1 87.000 (89.778) Prec@5 100.000 (99.667) +2022-11-14 17:06:42,677 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0650) Prec@1 89.000 (89.700) Prec@5 99.000 (99.600) +2022-11-14 17:06:42,684 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0557 (0.0641) Prec@1 91.000 (89.818) Prec@5 100.000 (99.636) +2022-11-14 17:06:42,692 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0648) Prec@1 90.000 (89.833) Prec@5 99.000 (99.583) +2022-11-14 17:06:42,699 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0636) Prec@1 91.000 (89.923) Prec@5 100.000 (99.615) +2022-11-14 17:06:42,707 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0641) Prec@1 89.000 (89.857) Prec@5 100.000 (99.643) +2022-11-14 17:06:42,714 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0649) Prec@1 90.000 (89.867) Prec@5 100.000 (99.667) +2022-11-14 17:06:42,722 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0653) Prec@1 89.000 (89.812) Prec@5 99.000 (99.625) +2022-11-14 17:06:42,730 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0644) Prec@1 92.000 (89.941) Prec@5 98.000 (99.529) +2022-11-14 17:06:42,738 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1173 (0.0673) Prec@1 82.000 (89.500) Prec@5 100.000 (99.556) +2022-11-14 17:06:42,746 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0673) Prec@1 87.000 (89.368) Prec@5 98.000 (99.474) +2022-11-14 17:06:42,753 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0693) Prec@1 84.000 (89.100) Prec@5 99.000 (99.450) +2022-11-14 17:06:42,761 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0695) Prec@1 86.000 (88.952) Prec@5 100.000 (99.476) +2022-11-14 17:06:42,769 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0709) Prec@1 85.000 (88.773) Prec@5 98.000 (99.409) +2022-11-14 17:06:42,776 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1062 (0.0725) Prec@1 85.000 (88.609) Prec@5 98.000 (99.348) +2022-11-14 17:06:42,784 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0726) Prec@1 89.000 (88.625) Prec@5 100.000 (99.375) +2022-11-14 17:06:42,791 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0727) Prec@1 88.000 (88.600) Prec@5 100.000 (99.400) +2022-11-14 17:06:42,799 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0738) Prec@1 85.000 (88.462) Prec@5 98.000 (99.346) +2022-11-14 17:06:42,806 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0730) Prec@1 92.000 (88.593) Prec@5 100.000 (99.370) +2022-11-14 17:06:42,814 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0729) Prec@1 87.000 (88.536) Prec@5 100.000 (99.393) +2022-11-14 17:06:42,821 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0724) Prec@1 90.000 (88.586) Prec@5 99.000 (99.379) +2022-11-14 17:06:42,829 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0720) Prec@1 92.000 (88.700) Prec@5 99.000 (99.367) +2022-11-14 17:06:42,836 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0721) Prec@1 86.000 (88.613) Prec@5 99.000 (99.355) +2022-11-14 17:06:42,844 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0721) Prec@1 91.000 (88.688) Prec@5 99.000 (99.344) +2022-11-14 17:06:42,851 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0724) Prec@1 85.000 (88.576) Prec@5 100.000 (99.364) +2022-11-14 17:06:42,859 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0723) Prec@1 90.000 (88.618) Prec@5 100.000 (99.382) +2022-11-14 17:06:42,867 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0729) Prec@1 86.000 (88.543) Prec@5 98.000 (99.343) +2022-11-14 17:06:42,874 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0731) Prec@1 89.000 (88.556) Prec@5 100.000 (99.361) +2022-11-14 17:06:42,882 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0731) Prec@1 87.000 (88.514) Prec@5 99.000 (99.351) +2022-11-14 17:06:42,890 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.0740) Prec@1 84.000 (88.395) Prec@5 99.000 (99.342) +2022-11-14 17:06:42,898 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0734) Prec@1 93.000 (88.513) Prec@5 99.000 (99.333) +2022-11-14 17:06:42,906 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0732) Prec@1 92.000 (88.600) Prec@5 99.000 (99.325) +2022-11-14 17:06:42,913 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0735) Prec@1 87.000 (88.561) Prec@5 99.000 (99.317) +2022-11-14 17:06:42,921 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0733) Prec@1 91.000 (88.619) Prec@5 99.000 (99.310) +2022-11-14 17:06:42,929 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0436 (0.0727) Prec@1 94.000 (88.744) Prec@5 99.000 (99.302) +2022-11-14 17:06:42,936 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0724) Prec@1 91.000 (88.795) Prec@5 99.000 (99.295) +2022-11-14 17:06:42,944 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0722) Prec@1 90.000 (88.822) Prec@5 99.000 (99.289) +2022-11-14 17:06:42,952 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0727) Prec@1 85.000 (88.739) Prec@5 98.000 (99.261) +2022-11-14 17:06:42,959 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0728) Prec@1 87.000 (88.702) Prec@5 100.000 (99.277) +2022-11-14 17:06:42,967 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1058 (0.0735) Prec@1 85.000 (88.625) Prec@5 98.000 (99.250) +2022-11-14 17:06:42,974 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0730) Prec@1 92.000 (88.694) Prec@5 100.000 (99.265) +2022-11-14 17:06:42,982 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1081 (0.0737) Prec@1 82.000 (88.560) Prec@5 100.000 (99.280) +2022-11-14 17:06:42,990 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0736) Prec@1 89.000 (88.569) Prec@5 100.000 (99.294) +2022-11-14 17:06:42,997 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0734) Prec@1 90.000 (88.596) Prec@5 100.000 (99.308) +2022-11-14 17:06:43,005 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0457 (0.0729) Prec@1 94.000 (88.698) Prec@5 99.000 (99.302) +2022-11-14 17:06:43,013 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0726) Prec@1 90.000 (88.722) Prec@5 100.000 (99.315) +2022-11-14 17:06:43,020 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0731) Prec@1 85.000 (88.655) Prec@5 100.000 (99.327) +2022-11-14 17:06:43,028 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0729) Prec@1 91.000 (88.696) Prec@5 99.000 (99.321) +2022-11-14 17:06:43,035 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0730) Prec@1 88.000 (88.684) Prec@5 100.000 (99.333) +2022-11-14 17:06:43,043 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0728) Prec@1 92.000 (88.741) Prec@5 100.000 (99.345) +2022-11-14 17:06:43,050 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0732) Prec@1 87.000 (88.712) Prec@5 100.000 (99.356) +2022-11-14 17:06:43,059 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0730) Prec@1 90.000 (88.733) Prec@5 100.000 (99.367) +2022-11-14 17:06:43,066 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0730) Prec@1 91.000 (88.770) Prec@5 100.000 (99.377) +2022-11-14 17:06:43,074 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0727) Prec@1 91.000 (88.806) Prec@5 99.000 (99.371) +2022-11-14 17:06:43,083 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0728) Prec@1 87.000 (88.778) Prec@5 100.000 (99.381) +2022-11-14 17:06:43,091 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0393 (0.0722) Prec@1 93.000 (88.844) Prec@5 100.000 (99.391) +2022-11-14 17:06:43,099 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0726) Prec@1 86.000 (88.800) Prec@5 99.000 (99.385) +2022-11-14 17:06:43,106 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0726) Prec@1 89.000 (88.803) Prec@5 100.000 (99.394) +2022-11-14 17:06:43,114 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0722) Prec@1 91.000 (88.836) Prec@5 99.000 (99.388) +2022-11-14 17:06:43,121 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0722) Prec@1 91.000 (88.868) Prec@5 99.000 (99.382) +2022-11-14 17:06:43,129 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0822 (0.0724) Prec@1 86.000 (88.826) Prec@5 99.000 (99.377) +2022-11-14 17:06:43,137 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0726) Prec@1 88.000 (88.814) Prec@5 97.000 (99.343) +2022-11-14 17:06:43,144 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0730) Prec@1 85.000 (88.761) Prec@5 99.000 (99.338) +2022-11-14 17:06:43,152 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0730) Prec@1 88.000 (88.750) Prec@5 100.000 (99.347) +2022-11-14 17:06:43,160 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0447 (0.0726) Prec@1 94.000 (88.822) Prec@5 100.000 (99.356) +2022-11-14 17:06:43,168 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0458 (0.0723) Prec@1 93.000 (88.878) Prec@5 100.000 (99.365) +2022-11-14 17:06:43,175 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1115 (0.0728) Prec@1 83.000 (88.800) Prec@5 100.000 (99.373) +2022-11-14 17:06:43,183 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0726) Prec@1 90.000 (88.816) Prec@5 100.000 (99.382) +2022-11-14 17:06:43,190 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0726) Prec@1 88.000 (88.805) Prec@5 99.000 (99.377) +2022-11-14 17:06:43,198 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0729) Prec@1 84.000 (88.744) Prec@5 99.000 (99.372) +2022-11-14 17:06:43,206 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0730) Prec@1 87.000 (88.722) Prec@5 100.000 (99.380) +2022-11-14 17:06:43,213 Test: 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0.0986 (0.0740) Prec@1 84.000 (88.453) Prec@5 100.000 (99.372) +2022-11-14 17:06:43,267 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0740) Prec@1 91.000 (88.483) Prec@5 99.000 (99.368) +2022-11-14 17:06:43,274 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0740) Prec@1 87.000 (88.466) Prec@5 99.000 (99.364) +2022-11-14 17:06:43,282 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0739) Prec@1 91.000 (88.494) Prec@5 100.000 (99.371) +2022-11-14 17:06:43,290 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0740) Prec@1 88.000 (88.489) Prec@5 99.000 (99.367) +2022-11-14 17:06:43,297 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0738) Prec@1 91.000 (88.516) Prec@5 100.000 (99.374) +2022-11-14 17:06:43,305 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0398 (0.0734) Prec@1 94.000 (88.576) Prec@5 100.000 (99.380) +2022-11-14 17:06:43,312 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0737) Prec@1 85.000 (88.538) Prec@5 100.000 (99.387) +2022-11-14 17:06:43,320 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0738) Prec@1 89.000 (88.543) Prec@5 98.000 (99.372) +2022-11-14 17:06:43,327 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0737) Prec@1 90.000 (88.558) Prec@5 100.000 (99.379) +2022-11-14 17:06:43,335 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0736) Prec@1 91.000 (88.583) Prec@5 100.000 (99.385) +2022-11-14 17:06:43,342 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0734) Prec@1 91.000 (88.608) Prec@5 99.000 (99.381) +2022-11-14 17:06:43,349 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0737) Prec@1 85.000 (88.571) Prec@5 95.000 (99.337) +2022-11-14 17:06:43,357 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1028 (0.0740) Prec@1 84.000 (88.525) Prec@5 98.000 (99.323) +2022-11-14 17:06:43,364 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0627 (0.0739) Prec@1 90.000 (88.540) Prec@5 100.000 (99.330) +2022-11-14 17:06:43,419 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:06:43,740 Epoch: [465][0/500] Time 0.023 (0.023) Data 0.243 (0.243) Loss 0.0286 (0.0286) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:43,950 Epoch: [465][10/500] Time 0.017 (0.019) Data 0.002 (0.024) Loss 0.0334 (0.0310) Prec@1 93.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:06:44,142 Epoch: [465][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0209 (0.0276) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:06:44,334 Epoch: [465][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0189 (0.0255) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:06:44,528 Epoch: [465][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0143 (0.0232) Prec@1 98.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 17:06:44,719 Epoch: [465][50/500] Time 0.018 (0.017) Data 0.002 (0.006) Loss 0.0459 (0.0270) Prec@1 93.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:06:44,988 Epoch: [465][60/500] Time 0.027 (0.018) Data 0.002 (0.006) Loss 0.0263 (0.0269) Prec@1 96.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:06:45,311 Epoch: [465][70/500] Time 0.030 (0.020) Data 0.002 (0.005) Loss 0.0332 (0.0277) Prec@1 93.000 (95.125) Prec@5 100.000 (100.000) +2022-11-14 17:06:45,629 Epoch: [465][80/500] Time 0.031 (0.021) Data 0.002 (0.005) Loss 0.0218 (0.0271) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:06:45,951 Epoch: [465][90/500] Time 0.030 (0.022) Data 0.002 (0.004) Loss 0.0200 (0.0263) Prec@1 96.000 (95.400) Prec@5 99.000 (99.900) +2022-11-14 17:06:46,277 Epoch: [465][100/500] Time 0.030 (0.022) Data 0.002 (0.004) Loss 0.0224 (0.0260) Prec@1 96.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:06:46,608 Epoch: [465][110/500] Time 0.032 (0.023) Data 0.002 (0.004) Loss 0.0196 (0.0255) Prec@1 97.000 (95.583) Prec@5 100.000 (99.917) +2022-11-14 17:06:46,939 Epoch: [465][120/500] Time 0.032 (0.023) Data 0.002 (0.004) Loss 0.0301 (0.0258) Prec@1 94.000 (95.462) Prec@5 100.000 (99.923) +2022-11-14 17:06:47,261 Epoch: [465][130/500] Time 0.030 (0.024) Data 0.002 (0.004) Loss 0.0239 (0.0257) Prec@1 97.000 (95.571) Prec@5 99.000 (99.857) +2022-11-14 17:06:47,576 Epoch: [465][140/500] Time 0.032 (0.024) Data 0.002 (0.003) Loss 0.0607 (0.0280) Prec@1 90.000 (95.200) Prec@5 98.000 (99.733) +2022-11-14 17:06:47,897 Epoch: [465][150/500] Time 0.029 (0.024) Data 0.002 (0.003) Loss 0.0436 (0.0290) Prec@1 93.000 (95.062) Prec@5 100.000 (99.750) +2022-11-14 17:06:48,220 Epoch: [465][160/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0317 (0.0291) Prec@1 94.000 (95.000) Prec@5 100.000 (99.765) +2022-11-14 17:06:48,540 Epoch: [465][170/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0129 (0.0282) Prec@1 99.000 (95.222) Prec@5 100.000 (99.778) +2022-11-14 17:06:48,863 Epoch: [465][180/500] Time 0.030 (0.025) Data 0.002 (0.003) Loss 0.0298 (0.0283) Prec@1 95.000 (95.211) Prec@5 100.000 (99.789) +2022-11-14 17:06:49,175 Epoch: [465][190/500] Time 0.029 (0.025) Data 0.002 (0.003) Loss 0.0587 (0.0298) Prec@1 92.000 (95.050) Prec@5 99.000 (99.750) +2022-11-14 17:06:49,496 Epoch: [465][200/500] Time 0.031 (0.025) Data 0.002 (0.003) Loss 0.0291 (0.0298) Prec@1 96.000 (95.095) Prec@5 99.000 (99.714) +2022-11-14 17:06:49,824 Epoch: [465][210/500] Time 0.028 (0.025) Data 0.002 (0.003) Loss 0.0232 (0.0295) Prec@1 96.000 (95.136) Prec@5 100.000 (99.727) +2022-11-14 17:06:50,148 Epoch: [465][220/500] Time 0.038 (0.026) Data 0.002 (0.003) Loss 0.0235 (0.0292) Prec@1 95.000 (95.130) Prec@5 100.000 (99.739) +2022-11-14 17:06:50,466 Epoch: [465][230/500] Time 0.030 (0.026) Data 0.001 (0.003) Loss 0.0191 (0.0288) Prec@1 96.000 (95.167) Prec@5 100.000 (99.750) +2022-11-14 17:06:50,783 Epoch: [465][240/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0244 (0.0287) Prec@1 96.000 (95.200) Prec@5 100.000 (99.760) +2022-11-14 17:06:51,104 Epoch: [465][250/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0265 (0.0286) Prec@1 96.000 (95.231) Prec@5 100.000 (99.769) +2022-11-14 17:06:51,418 Epoch: [465][260/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0402 (0.0290) Prec@1 95.000 (95.222) Prec@5 99.000 (99.741) +2022-11-14 17:06:51,739 Epoch: [465][270/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0250 (0.0289) Prec@1 96.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 17:06:52,059 Epoch: [465][280/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0610 (0.0300) Prec@1 89.000 (95.034) Prec@5 100.000 (99.759) +2022-11-14 17:06:52,382 Epoch: [465][290/500] Time 0.030 (0.026) Data 0.002 (0.003) Loss 0.0239 (0.0298) Prec@1 96.000 (95.067) Prec@5 100.000 (99.767) +2022-11-14 17:06:52,702 Epoch: [465][300/500] Time 0.031 (0.026) Data 0.002 (0.003) Loss 0.0218 (0.0295) Prec@1 97.000 (95.129) Prec@5 100.000 (99.774) +2022-11-14 17:06:53,021 Epoch: [465][310/500] Time 0.029 (0.026) Data 0.002 (0.003) Loss 0.0259 (0.0294) Prec@1 95.000 (95.125) Prec@5 100.000 (99.781) +2022-11-14 17:06:53,294 Epoch: [465][320/500] Time 0.021 (0.026) Data 0.002 (0.002) Loss 0.0184 (0.0291) Prec@1 98.000 (95.212) Prec@5 100.000 (99.788) +2022-11-14 17:06:53,505 Epoch: [465][330/500] Time 0.019 (0.026) Data 0.002 (0.002) Loss 0.0383 (0.0293) Prec@1 92.000 (95.118) Prec@5 100.000 (99.794) +2022-11-14 17:06:53,713 Epoch: [465][340/500] Time 0.019 (0.026) Data 0.002 (0.002) Loss 0.0165 (0.0290) Prec@1 98.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:06:53,925 Epoch: [465][350/500] Time 0.020 (0.026) Data 0.002 (0.002) Loss 0.0487 (0.0295) Prec@1 91.000 (95.083) Prec@5 99.000 (99.778) +2022-11-14 17:06:54,134 Epoch: [465][360/500] Time 0.017 (0.025) Data 0.001 (0.002) Loss 0.0111 (0.0290) Prec@1 99.000 (95.189) Prec@5 100.000 (99.784) +2022-11-14 17:06:54,341 Epoch: [465][370/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0230 (0.0289) Prec@1 96.000 (95.211) Prec@5 100.000 (99.789) +2022-11-14 17:06:54,547 Epoch: [465][380/500] Time 0.019 (0.025) Data 0.002 (0.002) Loss 0.0299 (0.0289) Prec@1 97.000 (95.256) Prec@5 100.000 (99.795) +2022-11-14 17:06:54,753 Epoch: [465][390/500] Time 0.019 (0.025) Data 0.002 (0.002) Loss 0.0382 (0.0291) Prec@1 94.000 (95.225) Prec@5 100.000 (99.800) +2022-11-14 17:06:54,959 Epoch: [465][400/500] Time 0.019 (0.025) Data 0.001 (0.002) Loss 0.0264 (0.0290) Prec@1 95.000 (95.220) Prec@5 100.000 (99.805) +2022-11-14 17:06:55,169 Epoch: [465][410/500] Time 0.018 (0.025) Data 0.001 (0.002) Loss 0.0465 (0.0295) Prec@1 93.000 (95.167) Prec@5 100.000 (99.810) +2022-11-14 17:06:55,375 Epoch: [465][420/500] Time 0.019 (0.024) Data 0.002 (0.002) Loss 0.0204 (0.0293) Prec@1 96.000 (95.186) Prec@5 100.000 (99.814) +2022-11-14 17:06:55,582 Epoch: [465][430/500] Time 0.019 (0.024) Data 0.002 (0.002) Loss 0.0313 (0.0293) Prec@1 93.000 (95.136) Prec@5 100.000 (99.818) +2022-11-14 17:06:55,790 Epoch: [465][440/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0210 (0.0291) Prec@1 97.000 (95.178) Prec@5 100.000 (99.822) +2022-11-14 17:06:55,996 Epoch: [465][450/500] Time 0.020 (0.024) Data 0.001 (0.002) Loss 0.0334 (0.0292) Prec@1 95.000 (95.174) Prec@5 100.000 (99.826) +2022-11-14 17:06:56,204 Epoch: [465][460/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0263 (0.0291) Prec@1 97.000 (95.213) Prec@5 100.000 (99.830) +2022-11-14 17:06:56,412 Epoch: [465][470/500] Time 0.020 (0.024) Data 0.001 (0.002) Loss 0.0265 (0.0291) Prec@1 95.000 (95.208) Prec@5 100.000 (99.833) +2022-11-14 17:06:56,621 Epoch: [465][480/500] Time 0.019 (0.024) Data 0.001 (0.002) Loss 0.0153 (0.0288) Prec@1 98.000 (95.265) Prec@5 100.000 (99.837) +2022-11-14 17:06:56,829 Epoch: [465][490/500] Time 0.020 (0.024) Data 0.002 (0.002) Loss 0.0338 (0.0289) Prec@1 94.000 (95.240) Prec@5 100.000 (99.840) +2022-11-14 17:06:57,015 Epoch: [465][499/500] Time 0.019 (0.023) Data 0.001 (0.002) Loss 0.0198 (0.0287) Prec@1 96.000 (95.255) Prec@5 100.000 (99.843) +2022-11-14 17:06:57,309 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0592 (0.0592) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:57,318 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0533 (0.0562) Prec@1 92.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 17:06:57,327 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0636 (0.0587) Prec@1 89.000 (90.667) Prec@5 99.000 (99.667) +2022-11-14 17:06:57,337 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0619) Prec@1 88.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 17:06:57,344 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0633) Prec@1 88.000 (89.600) Prec@5 99.000 (99.400) +2022-11-14 17:06:57,351 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0598) Prec@1 93.000 (90.167) Prec@5 100.000 (99.500) +2022-11-14 17:06:57,357 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0596) Prec@1 91.000 (90.286) Prec@5 100.000 (99.571) +2022-11-14 17:06:57,366 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0611) Prec@1 86.000 (89.750) Prec@5 100.000 (99.625) +2022-11-14 17:06:57,373 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0626) Prec@1 87.000 (89.444) Prec@5 99.000 (99.556) +2022-11-14 17:06:57,380 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0653) Prec@1 87.000 (89.200) Prec@5 98.000 (99.400) +2022-11-14 17:06:57,387 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0642) Prec@1 92.000 (89.455) Prec@5 100.000 (99.455) +2022-11-14 17:06:57,395 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0639) Prec@1 89.000 (89.417) Prec@5 100.000 (99.500) +2022-11-14 17:06:57,403 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0637) Prec@1 91.000 (89.538) Prec@5 100.000 (99.538) +2022-11-14 17:06:57,411 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0656) Prec@1 85.000 (89.214) Prec@5 98.000 (99.429) +2022-11-14 17:06:57,418 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0657) Prec@1 88.000 (89.133) Prec@5 100.000 (99.467) +2022-11-14 17:06:57,426 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0662) Prec@1 88.000 (89.062) Prec@5 100.000 (99.500) +2022-11-14 17:06:57,434 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0650) Prec@1 93.000 (89.294) Prec@5 98.000 (99.412) +2022-11-14 17:06:57,441 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1253 (0.0684) Prec@1 81.000 (88.833) Prec@5 99.000 (99.389) +2022-11-14 17:06:57,449 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0696) Prec@1 84.000 (88.579) Prec@5 98.000 (99.316) +2022-11-14 17:06:57,457 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0697) Prec@1 89.000 (88.600) Prec@5 98.000 (99.250) +2022-11-14 17:06:57,465 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0701) Prec@1 85.000 (88.429) Prec@5 99.000 (99.238) +2022-11-14 17:06:57,472 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0707) Prec@1 86.000 (88.318) Prec@5 99.000 (99.227) +2022-11-14 17:06:57,480 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1139 (0.0726) Prec@1 83.000 (88.087) Prec@5 97.000 (99.130) +2022-11-14 17:06:57,488 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0723) Prec@1 89.000 (88.125) Prec@5 100.000 (99.167) +2022-11-14 17:06:57,495 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0735) Prec@1 82.000 (87.880) Prec@5 100.000 (99.200) +2022-11-14 17:06:57,504 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0744) Prec@1 85.000 (87.769) Prec@5 99.000 (99.192) +2022-11-14 17:06:57,512 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0737) Prec@1 90.000 (87.852) Prec@5 100.000 (99.222) +2022-11-14 17:06:57,519 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0733) Prec@1 90.000 (87.929) Prec@5 100.000 (99.250) +2022-11-14 17:06:57,528 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0727) Prec@1 89.000 (87.966) Prec@5 99.000 (99.241) +2022-11-14 17:06:57,535 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0728) Prec@1 89.000 (88.000) Prec@5 100.000 (99.267) +2022-11-14 17:06:57,543 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0724) Prec@1 91.000 (88.097) Prec@5 99.000 (99.258) +2022-11-14 17:06:57,551 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0719) Prec@1 92.000 (88.219) Prec@5 100.000 (99.281) +2022-11-14 17:06:57,559 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0716) Prec@1 88.000 (88.212) Prec@5 99.000 (99.273) +2022-11-14 17:06:57,566 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0722) Prec@1 85.000 (88.118) Prec@5 100.000 (99.294) +2022-11-14 17:06:57,574 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0723) Prec@1 90.000 (88.171) Prec@5 98.000 (99.257) +2022-11-14 17:06:57,582 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0725) Prec@1 88.000 (88.167) Prec@5 99.000 (99.250) +2022-11-14 17:06:57,590 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0724) Prec@1 89.000 (88.189) Prec@5 99.000 (99.243) +2022-11-14 17:06:57,597 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0722) Prec@1 87.000 (88.158) Prec@5 100.000 (99.263) +2022-11-14 17:06:57,605 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0715) Prec@1 94.000 (88.308) Prec@5 98.000 (99.231) +2022-11-14 17:06:57,613 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0716) Prec@1 86.000 (88.250) Prec@5 99.000 (99.225) +2022-11-14 17:06:57,621 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0721) Prec@1 87.000 (88.220) Prec@5 97.000 (99.171) +2022-11-14 17:06:57,629 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0721) Prec@1 89.000 (88.238) Prec@5 99.000 (99.167) +2022-11-14 17:06:57,637 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0527 (0.0717) Prec@1 93.000 (88.349) Prec@5 99.000 (99.163) +2022-11-14 17:06:57,645 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0719) Prec@1 88.000 (88.341) Prec@5 98.000 (99.136) +2022-11-14 17:06:57,652 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0714) Prec@1 90.000 (88.378) Prec@5 100.000 (99.156) +2022-11-14 17:06:57,660 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1200 (0.0725) Prec@1 82.000 (88.239) Prec@5 97.000 (99.109) +2022-11-14 17:06:57,668 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0723) Prec@1 90.000 (88.277) Prec@5 100.000 (99.128) +2022-11-14 17:06:57,676 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0918 (0.0727) Prec@1 84.000 (88.188) Prec@5 99.000 (99.125) +2022-11-14 17:06:57,684 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0407 (0.0720) Prec@1 95.000 (88.327) Prec@5 99.000 (99.122) +2022-11-14 17:06:57,692 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1149 (0.0729) Prec@1 83.000 (88.220) Prec@5 100.000 (99.140) +2022-11-14 17:06:57,700 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0726) Prec@1 92.000 (88.294) Prec@5 100.000 (99.157) +2022-11-14 17:06:57,708 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0727) Prec@1 87.000 (88.269) Prec@5 99.000 (99.154) +2022-11-14 17:06:57,716 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0725) Prec@1 91.000 (88.321) Prec@5 99.000 (99.151) +2022-11-14 17:06:57,725 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0724) Prec@1 89.000 (88.333) Prec@5 100.000 (99.167) +2022-11-14 17:06:57,735 Test: [54/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0730) Prec@1 84.000 (88.255) Prec@5 100.000 (99.182) +2022-11-14 17:06:57,744 Test: [55/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0728) Prec@1 90.000 (88.286) Prec@5 99.000 (99.179) +2022-11-14 17:06:57,752 Test: [56/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0730) Prec@1 85.000 (88.228) Prec@5 100.000 (99.193) +2022-11-14 17:06:57,761 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0731) Prec@1 88.000 (88.224) Prec@5 99.000 (99.190) +2022-11-14 17:06:57,769 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0734) Prec@1 84.000 (88.153) Prec@5 99.000 (99.186) +2022-11-14 17:06:57,777 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0736) Prec@1 87.000 (88.133) Prec@5 99.000 (99.183) +2022-11-14 17:06:57,785 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0737) Prec@1 90.000 (88.164) Prec@5 98.000 (99.164) +2022-11-14 17:06:57,793 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0735) Prec@1 89.000 (88.177) Prec@5 100.000 (99.177) +2022-11-14 17:06:57,801 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0733) Prec@1 88.000 (88.175) Prec@5 100.000 (99.190) +2022-11-14 17:06:57,809 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0730) Prec@1 91.000 (88.219) Prec@5 99.000 (99.188) +2022-11-14 17:06:57,817 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0734) Prec@1 83.000 (88.138) Prec@5 100.000 (99.200) +2022-11-14 17:06:57,825 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0733) Prec@1 88.000 (88.136) Prec@5 99.000 (99.197) +2022-11-14 17:06:57,833 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0730) Prec@1 91.000 (88.179) Prec@5 100.000 (99.209) +2022-11-14 17:06:57,841 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0729) Prec@1 88.000 (88.176) Prec@5 98.000 (99.191) +2022-11-14 17:06:57,849 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0528 (0.0726) Prec@1 90.000 (88.203) Prec@5 99.000 (99.188) +2022-11-14 17:06:57,856 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1055 (0.0731) Prec@1 82.000 (88.114) Prec@5 99.000 (99.186) +2022-11-14 17:06:57,864 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0733) Prec@1 88.000 (88.113) Prec@5 100.000 (99.197) +2022-11-14 17:06:57,872 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0729) Prec@1 91.000 (88.153) Prec@5 100.000 (99.208) +2022-11-14 17:06:57,880 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0726) Prec@1 93.000 (88.219) Prec@5 99.000 (99.205) +2022-11-14 17:06:57,887 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0291 (0.0720) Prec@1 95.000 (88.311) Prec@5 100.000 (99.216) +2022-11-14 17:06:57,895 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0724) Prec@1 83.000 (88.240) Prec@5 100.000 (99.227) +2022-11-14 17:06:57,903 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0726) Prec@1 88.000 (88.237) Prec@5 100.000 (99.237) +2022-11-14 17:06:57,911 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0726) Prec@1 89.000 (88.247) Prec@5 99.000 (99.234) +2022-11-14 17:06:57,918 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0727) Prec@1 89.000 (88.256) Prec@5 98.000 (99.218) +2022-11-14 17:06:57,926 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0729) Prec@1 87.000 (88.241) Prec@5 99.000 (99.215) +2022-11-14 17:06:57,933 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0727) Prec@1 90.000 (88.263) Prec@5 100.000 (99.225) +2022-11-14 17:06:57,941 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1049 (0.0731) Prec@1 85.000 (88.222) Prec@5 98.000 (99.210) +2022-11-14 17:06:57,949 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0735) Prec@1 85.000 (88.183) Prec@5 100.000 (99.220) +2022-11-14 17:06:57,957 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0736) Prec@1 85.000 (88.145) Prec@5 100.000 (99.229) +2022-11-14 17:06:57,964 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0735) Prec@1 90.000 (88.167) Prec@5 100.000 (99.238) +2022-11-14 17:06:57,972 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0738) Prec@1 83.000 (88.106) Prec@5 98.000 (99.224) +2022-11-14 17:06:57,980 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0740) Prec@1 87.000 (88.093) Prec@5 99.000 (99.221) +2022-11-14 17:06:57,988 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1013 (0.0743) Prec@1 80.000 (88.000) Prec@5 100.000 (99.230) +2022-11-14 17:06:57,997 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1049 (0.0746) Prec@1 84.000 (87.955) Prec@5 99.000 (99.227) +2022-11-14 17:06:58,005 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0747) Prec@1 86.000 (87.933) Prec@5 100.000 (99.236) +2022-11-14 17:06:58,012 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0748) Prec@1 88.000 (87.933) Prec@5 98.000 (99.222) +2022-11-14 17:06:58,020 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0747) Prec@1 90.000 (87.956) Prec@5 100.000 (99.231) +2022-11-14 17:06:58,028 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0745) Prec@1 91.000 (87.989) Prec@5 100.000 (99.239) +2022-11-14 17:06:58,036 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0745) Prec@1 89.000 (88.000) Prec@5 98.000 (99.226) +2022-11-14 17:06:58,043 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0747) Prec@1 86.000 (87.979) Prec@5 99.000 (99.223) +2022-11-14 17:06:58,051 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0747) Prec@1 87.000 (87.968) Prec@5 100.000 (99.232) +2022-11-14 17:06:58,059 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0454 (0.0744) Prec@1 94.000 (88.031) Prec@5 99.000 (99.229) +2022-11-14 17:06:58,067 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0406 (0.0741) Prec@1 94.000 (88.093) Prec@5 99.000 (99.227) +2022-11-14 17:06:58,075 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0744) Prec@1 85.000 (88.061) Prec@5 98.000 (99.214) +2022-11-14 17:06:58,084 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0747) Prec@1 80.000 (87.980) Prec@5 99.000 (99.212) +2022-11-14 17:06:58,092 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0745) Prec@1 91.000 (88.010) Prec@5 100.000 (99.220) +2022-11-14 17:06:58,146 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:06:58,458 Epoch: [466][0/500] Time 0.021 (0.021) Data 0.236 (0.236) Loss 0.0227 (0.0227) Prec@1 98.000 (98.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:58,651 Epoch: [466][10/500] Time 0.017 (0.017) Data 0.002 (0.023) Loss 0.0225 (0.0226) Prec@1 96.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:58,839 Epoch: [466][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0284 (0.0245) Prec@1 96.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,027 Epoch: [466][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0192 (0.0232) Prec@1 98.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,218 Epoch: [466][40/500] Time 0.018 (0.017) Data 0.001 (0.007) Loss 0.0109 (0.0208) Prec@1 98.000 (97.200) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,409 Epoch: [466][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0195 (0.0205) Prec@1 97.000 (97.167) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,596 Epoch: [466][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0239 (0.0210) Prec@1 96.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,783 Epoch: [466][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0155 (0.0203) Prec@1 98.000 (97.125) Prec@5 100.000 (100.000) +2022-11-14 17:06:59,974 Epoch: [466][80/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0311 (0.0215) Prec@1 93.000 (96.667) Prec@5 100.000 (100.000) +2022-11-14 17:07:00,170 Epoch: [466][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0388 (0.0233) Prec@1 93.000 (96.300) Prec@5 100.000 (100.000) +2022-11-14 17:07:00,365 Epoch: [466][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0321 (0.0241) Prec@1 97.000 (96.364) Prec@5 100.000 (100.000) +2022-11-14 17:07:00,561 Epoch: [466][110/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0151 (0.0233) Prec@1 98.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:00,818 Epoch: [466][120/500] Time 0.025 (0.017) Data 0.001 (0.003) Loss 0.0089 (0.0222) Prec@1 99.000 (96.692) Prec@5 100.000 (100.000) +2022-11-14 17:07:01,090 Epoch: [466][130/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0192 (0.0220) Prec@1 97.000 (96.714) Prec@5 100.000 (100.000) +2022-11-14 17:07:01,363 Epoch: [466][140/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0277 (0.0224) Prec@1 95.000 (96.600) Prec@5 100.000 (100.000) +2022-11-14 17:07:01,642 Epoch: [466][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0302 (0.0229) Prec@1 95.000 (96.500) Prec@5 99.000 (99.938) +2022-11-14 17:07:01,922 Epoch: [466][160/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0241 (0.0229) Prec@1 96.000 (96.471) Prec@5 100.000 (99.941) +2022-11-14 17:07:02,202 Epoch: [466][170/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0263 (0.0231) Prec@1 96.000 (96.444) Prec@5 100.000 (99.944) +2022-11-14 17:07:02,476 Epoch: [466][180/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0387 (0.0239) Prec@1 94.000 (96.316) Prec@5 100.000 (99.947) +2022-11-14 17:07:02,755 Epoch: [466][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0201 (0.0237) Prec@1 96.000 (96.300) Prec@5 100.000 (99.950) +2022-11-14 17:07:03,043 Epoch: [466][200/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0231 (0.0237) Prec@1 96.000 (96.286) Prec@5 100.000 (99.952) +2022-11-14 17:07:03,329 Epoch: [466][210/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0395 (0.0244) Prec@1 93.000 (96.136) Prec@5 100.000 (99.955) +2022-11-14 17:07:03,607 Epoch: [466][220/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0233 (0.0244) Prec@1 96.000 (96.130) Prec@5 100.000 (99.957) +2022-11-14 17:07:03,885 Epoch: [466][230/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0211 (0.0242) Prec@1 97.000 (96.167) Prec@5 100.000 (99.958) +2022-11-14 17:07:04,161 Epoch: [466][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0293 (0.0245) Prec@1 94.000 (96.080) Prec@5 100.000 (99.960) +2022-11-14 17:07:04,434 Epoch: [466][250/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0345 (0.0248) Prec@1 94.000 (96.000) Prec@5 100.000 (99.962) +2022-11-14 17:07:04,708 Epoch: [466][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0093 (0.0243) Prec@1 99.000 (96.111) Prec@5 100.000 (99.963) +2022-11-14 17:07:04,980 Epoch: [466][270/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0202 (0.0241) Prec@1 97.000 (96.143) Prec@5 100.000 (99.964) +2022-11-14 17:07:05,261 Epoch: [466][280/500] Time 0.028 (0.021) Data 0.001 (0.002) Loss 0.0130 (0.0237) Prec@1 99.000 (96.241) Prec@5 100.000 (99.966) +2022-11-14 17:07:05,539 Epoch: [466][290/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0283 (0.0239) Prec@1 94.000 (96.167) Prec@5 100.000 (99.967) +2022-11-14 17:07:05,821 Epoch: [466][300/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0107 (0.0235) Prec@1 98.000 (96.226) Prec@5 100.000 (99.968) +2022-11-14 17:07:06,094 Epoch: [466][310/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0124 (0.0231) Prec@1 98.000 (96.281) Prec@5 100.000 (99.969) +2022-11-14 17:07:06,366 Epoch: [466][320/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0355 (0.0235) Prec@1 94.000 (96.212) Prec@5 99.000 (99.939) +2022-11-14 17:07:06,641 Epoch: [466][330/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0405 (0.0240) Prec@1 93.000 (96.118) Prec@5 100.000 (99.941) +2022-11-14 17:07:06,915 Epoch: [466][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0306 (0.0242) Prec@1 94.000 (96.057) Prec@5 100.000 (99.943) +2022-11-14 17:07:07,188 Epoch: [466][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0089 (0.0237) Prec@1 99.000 (96.139) Prec@5 100.000 (99.944) +2022-11-14 17:07:07,458 Epoch: [466][360/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0035 (0.0232) Prec@1 100.000 (96.243) Prec@5 100.000 (99.946) +2022-11-14 17:07:07,724 Epoch: [466][370/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0247 (0.0232) Prec@1 97.000 (96.263) Prec@5 99.000 (99.921) +2022-11-14 17:07:07,997 Epoch: [466][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0345 (0.0235) Prec@1 95.000 (96.231) Prec@5 100.000 (99.923) +2022-11-14 17:07:08,265 Epoch: [466][390/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0256 (0.0236) Prec@1 95.000 (96.200) Prec@5 100.000 (99.925) +2022-11-14 17:07:08,537 Epoch: [466][400/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0284 (0.0237) Prec@1 95.000 (96.171) Prec@5 100.000 (99.927) +2022-11-14 17:07:08,809 Epoch: [466][410/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0304 (0.0239) Prec@1 96.000 (96.167) Prec@5 100.000 (99.929) +2022-11-14 17:07:09,079 Epoch: [466][420/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0225 (0.0238) Prec@1 96.000 (96.163) Prec@5 100.000 (99.930) +2022-11-14 17:07:09,348 Epoch: [466][430/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0182 (0.0237) Prec@1 98.000 (96.205) Prec@5 100.000 (99.932) +2022-11-14 17:07:09,616 Epoch: [466][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0418 (0.0241) Prec@1 93.000 (96.133) Prec@5 100.000 (99.933) +2022-11-14 17:07:09,883 Epoch: [466][450/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0224 (0.0241) Prec@1 97.000 (96.152) Prec@5 100.000 (99.935) +2022-11-14 17:07:10,157 Epoch: [466][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0238 (0.0241) Prec@1 96.000 (96.149) Prec@5 100.000 (99.936) +2022-11-14 17:07:10,429 Epoch: [466][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0550 (0.0247) Prec@1 90.000 (96.021) Prec@5 99.000 (99.917) +2022-11-14 17:07:10,698 Epoch: [466][480/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0260 (0.0247) Prec@1 97.000 (96.041) Prec@5 100.000 (99.918) +2022-11-14 17:07:10,967 Epoch: [466][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0613 (0.0255) Prec@1 89.000 (95.900) Prec@5 100.000 (99.920) +2022-11-14 17:07:11,212 Epoch: [466][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0268 (0.0255) Prec@1 96.000 (95.902) Prec@5 100.000 (99.922) +2022-11-14 17:07:11,525 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0595 (0.0595) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,533 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0719 (0.0657) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,540 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0932 (0.0749) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,549 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0706) Prec@1 91.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,556 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0740) Prec@1 86.000 (88.800) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,562 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0510 (0.0702) Prec@1 92.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,570 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0466 (0.0668) Prec@1 92.000 (89.714) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,578 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0686) Prec@1 88.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,585 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0696) Prec@1 87.000 (89.222) Prec@5 100.000 (100.000) +2022-11-14 17:07:11,592 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0701) Prec@1 89.000 (89.200) Prec@5 99.000 (99.900) +2022-11-14 17:07:11,600 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0693) Prec@1 90.000 (89.273) Prec@5 99.000 (99.818) +2022-11-14 17:07:11,608 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0697) Prec@1 90.000 (89.333) Prec@5 99.000 (99.750) +2022-11-14 17:07:11,616 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0695) Prec@1 89.000 (89.308) Prec@5 99.000 (99.692) +2022-11-14 17:07:11,624 Test: 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Loss 0.0725 (0.0715) Prec@1 86.000 (88.850) Prec@5 99.000 (99.500) +2022-11-14 17:07:11,678 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0720) Prec@1 87.000 (88.762) Prec@5 100.000 (99.524) +2022-11-14 17:07:11,686 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0721) Prec@1 87.000 (88.682) Prec@5 99.000 (99.500) +2022-11-14 17:07:11,694 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.0736) Prec@1 86.000 (88.565) Prec@5 97.000 (99.391) +2022-11-14 17:07:11,702 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0730) Prec@1 90.000 (88.625) Prec@5 99.000 (99.375) +2022-11-14 17:07:11,709 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0738) Prec@1 86.000 (88.520) Prec@5 99.000 (99.360) +2022-11-14 17:07:11,717 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0746) Prec@1 84.000 (88.346) Prec@5 98.000 (99.308) +2022-11-14 17:07:11,725 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0561 (0.0739) Prec@1 90.000 (88.407) Prec@5 100.000 (99.333) +2022-11-14 17:07:11,733 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0733) Prec@1 91.000 (88.500) Prec@5 99.000 (99.321) +2022-11-14 17:07:11,740 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0734) Prec@1 88.000 (88.483) Prec@5 98.000 (99.276) +2022-11-14 17:07:11,748 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0733) Prec@1 88.000 (88.467) Prec@5 100.000 (99.300) +2022-11-14 17:07:11,756 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0734) Prec@1 88.000 (88.452) Prec@5 98.000 (99.258) +2022-11-14 17:07:11,763 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0738) Prec@1 85.000 (88.344) Prec@5 99.000 (99.250) +2022-11-14 17:07:11,771 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0732) Prec@1 90.000 (88.394) Prec@5 100.000 (99.273) +2022-11-14 17:07:11,778 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0739) Prec@1 84.000 (88.265) Prec@5 99.000 (99.265) +2022-11-14 17:07:11,786 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0742) Prec@1 88.000 (88.257) Prec@5 97.000 (99.200) +2022-11-14 17:07:11,794 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0740) Prec@1 91.000 (88.333) Prec@5 99.000 (99.194) +2022-11-14 17:07:11,801 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0742) Prec@1 85.000 (88.243) Prec@5 100.000 (99.216) +2022-11-14 17:07:11,809 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0750) Prec@1 84.000 (88.132) Prec@5 100.000 (99.237) +2022-11-14 17:07:11,816 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0743) Prec@1 94.000 (88.282) Prec@5 100.000 (99.256) +2022-11-14 17:07:11,824 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0739) Prec@1 90.000 (88.325) Prec@5 99.000 (99.250) +2022-11-14 17:07:11,832 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0742) Prec@1 85.000 (88.244) Prec@5 97.000 (99.195) +2022-11-14 17:07:11,839 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0747) Prec@1 85.000 (88.167) Prec@5 99.000 (99.190) +2022-11-14 17:07:11,847 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0371 (0.0738) Prec@1 93.000 (88.279) Prec@5 99.000 (99.186) +2022-11-14 17:07:11,855 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0734) Prec@1 90.000 (88.318) Prec@5 99.000 (99.182) +2022-11-14 17:07:11,862 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0732) Prec@1 89.000 (88.333) Prec@5 99.000 (99.178) +2022-11-14 17:07:11,870 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0733) Prec@1 87.000 (88.304) Prec@5 98.000 (99.152) +2022-11-14 17:07:11,878 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0733) Prec@1 88.000 (88.298) Prec@5 99.000 (99.149) +2022-11-14 17:07:11,885 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1048 (0.0739) Prec@1 80.000 (88.125) Prec@5 99.000 (99.146) +2022-11-14 17:07:11,893 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0736) Prec@1 89.000 (88.143) Prec@5 100.000 (99.163) +2022-11-14 17:07:11,900 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1087 (0.0743) Prec@1 83.000 (88.040) Prec@5 100.000 (99.180) +2022-11-14 17:07:11,908 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0738) Prec@1 91.000 (88.098) Prec@5 100.000 (99.196) +2022-11-14 17:07:11,916 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0740) Prec@1 86.000 (88.058) Prec@5 98.000 (99.173) +2022-11-14 17:07:11,923 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0737) Prec@1 90.000 (88.094) Prec@5 99.000 (99.170) +2022-11-14 17:07:11,932 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0737) Prec@1 88.000 (88.093) Prec@5 99.000 (99.167) +2022-11-14 17:07:11,940 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0738) Prec@1 88.000 (88.091) Prec@5 100.000 (99.182) +2022-11-14 17:07:11,948 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0739) Prec@1 89.000 (88.107) Prec@5 99.000 (99.179) +2022-11-14 17:07:11,955 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0737) Prec@1 89.000 (88.123) Prec@5 100.000 (99.193) +2022-11-14 17:07:11,963 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0733) Prec@1 93.000 (88.207) Prec@5 99.000 (99.190) +2022-11-14 17:07:11,971 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0738) Prec@1 84.000 (88.136) Prec@5 99.000 (99.186) +2022-11-14 17:07:11,978 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0560 (0.0735) Prec@1 90.000 (88.167) Prec@5 100.000 (99.200) +2022-11-14 17:07:11,986 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0736) Prec@1 86.000 (88.131) Prec@5 99.000 (99.197) +2022-11-14 17:07:11,993 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0736) Prec@1 87.000 (88.113) Prec@5 100.000 (99.210) +2022-11-14 17:07:12,001 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0734) Prec@1 90.000 (88.143) Prec@5 99.000 (99.206) +2022-11-14 17:07:12,008 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0449 (0.0730) Prec@1 92.000 (88.203) Prec@5 100.000 (99.219) +2022-11-14 17:07:12,016 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0732) Prec@1 85.000 (88.154) Prec@5 99.000 (99.215) +2022-11-14 17:07:12,024 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0735) Prec@1 85.000 (88.106) Prec@5 98.000 (99.197) +2022-11-14 17:07:12,032 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0474 (0.0731) Prec@1 92.000 (88.164) Prec@5 99.000 (99.194) +2022-11-14 17:07:12,039 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0729) Prec@1 92.000 (88.221) Prec@5 100.000 (99.206) +2022-11-14 17:07:12,047 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0729) Prec@1 88.000 (88.217) Prec@5 98.000 (99.188) +2022-11-14 17:07:12,054 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0731) Prec@1 85.000 (88.171) Prec@5 99.000 (99.186) +2022-11-14 17:07:12,062 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0734) Prec@1 88.000 (88.169) Prec@5 98.000 (99.169) +2022-11-14 17:07:12,070 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0413 (0.0729) Prec@1 93.000 (88.236) Prec@5 100.000 (99.181) +2022-11-14 17:07:12,078 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0726) Prec@1 92.000 (88.288) Prec@5 100.000 (99.192) +2022-11-14 17:07:12,085 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0493 (0.0723) Prec@1 93.000 (88.351) Prec@5 100.000 (99.203) +2022-11-14 17:07:12,093 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0725) Prec@1 84.000 (88.293) Prec@5 100.000 (99.213) +2022-11-14 17:07:12,101 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0724) Prec@1 91.000 (88.329) Prec@5 99.000 (99.211) +2022-11-14 17:07:12,109 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0726) Prec@1 85.000 (88.286) Prec@5 99.000 (99.208) +2022-11-14 17:07:12,117 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0725) Prec@1 87.000 (88.269) Prec@5 98.000 (99.192) +2022-11-14 17:07:12,125 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1069 (0.0730) Prec@1 84.000 (88.215) Prec@5 100.000 (99.203) +2022-11-14 17:07:12,132 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0730) Prec@1 87.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 17:07:12,140 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0732) Prec@1 86.000 (88.173) Prec@5 99.000 (99.198) +2022-11-14 17:07:12,148 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0732) Prec@1 90.000 (88.195) Prec@5 98.000 (99.183) +2022-11-14 17:07:12,156 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0731) Prec@1 91.000 (88.229) Prec@5 99.000 (99.181) +2022-11-14 17:07:12,163 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0731) Prec@1 89.000 (88.238) Prec@5 100.000 (99.190) +2022-11-14 17:07:12,171 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0733) Prec@1 86.000 (88.212) Prec@5 99.000 (99.188) +2022-11-14 17:07:12,178 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1138 (0.0737) Prec@1 82.000 (88.140) Prec@5 100.000 (99.198) +2022-11-14 17:07:12,186 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0738) Prec@1 85.000 (88.103) Prec@5 98.000 (99.184) +2022-11-14 17:07:12,194 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0738) Prec@1 89.000 (88.114) Prec@5 98.000 (99.170) +2022-11-14 17:07:12,201 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0737) Prec@1 90.000 (88.135) Prec@5 100.000 (99.180) +2022-11-14 17:07:12,209 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0739) Prec@1 87.000 (88.122) Prec@5 98.000 (99.167) +2022-11-14 17:07:12,216 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0737) Prec@1 91.000 (88.154) Prec@5 99.000 (99.165) +2022-11-14 17:07:12,224 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0421 (0.0734) Prec@1 93.000 (88.207) Prec@5 100.000 (99.174) +2022-11-14 17:07:12,232 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0734) Prec@1 88.000 (88.204) Prec@5 100.000 (99.183) +2022-11-14 17:07:12,239 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0735) Prec@1 88.000 (88.202) Prec@5 100.000 (99.191) +2022-11-14 17:07:12,247 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0735) Prec@1 86.000 (88.179) Prec@5 99.000 (99.189) +2022-11-14 17:07:12,254 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0733) Prec@1 90.000 (88.198) Prec@5 99.000 (99.188) +2022-11-14 17:07:12,262 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0369 (0.0729) Prec@1 95.000 (88.268) Prec@5 100.000 (99.196) +2022-11-14 17:07:12,269 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1037 (0.0732) Prec@1 84.000 (88.224) Prec@5 97.000 (99.173) +2022-11-14 17:07:12,277 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0988 (0.0735) Prec@1 84.000 (88.182) Prec@5 99.000 (99.172) +2022-11-14 17:07:12,284 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0734) Prec@1 90.000 (88.200) Prec@5 100.000 (99.180) +2022-11-14 17:07:12,338 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:07:12,673 Epoch: [467][0/500] Time 0.028 (0.028) Data 0.254 (0.254) Loss 0.0455 (0.0455) Prec@1 92.000 (92.000) Prec@5 99.000 (99.000) +2022-11-14 17:07:12,871 Epoch: [467][10/500] Time 0.016 (0.018) Data 0.001 (0.025) Loss 0.0155 (0.0305) Prec@1 99.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 17:07:13,063 Epoch: [467][20/500] Time 0.020 (0.018) Data 0.002 (0.014) Loss 0.0267 (0.0292) Prec@1 96.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 17:07:13,259 Epoch: [467][30/500] Time 0.017 (0.018) Data 0.002 (0.010) Loss 0.0243 (0.0280) Prec@1 97.000 (96.000) Prec@5 99.000 (99.500) +2022-11-14 17:07:13,452 Epoch: [467][40/500] Time 0.020 (0.017) Data 0.002 (0.008) Loss 0.0142 (0.0252) Prec@1 98.000 (96.400) Prec@5 100.000 (99.600) +2022-11-14 17:07:13,647 Epoch: [467][50/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0402 (0.0277) Prec@1 93.000 (95.833) Prec@5 100.000 (99.667) +2022-11-14 17:07:13,840 Epoch: [467][60/500] Time 0.020 (0.017) Data 0.001 (0.006) Loss 0.0157 (0.0260) Prec@1 98.000 (96.143) Prec@5 100.000 (99.714) +2022-11-14 17:07:14,033 Epoch: [467][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0214 (0.0254) Prec@1 97.000 (96.250) Prec@5 100.000 (99.750) +2022-11-14 17:07:14,225 Epoch: [467][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0270 (0.0256) Prec@1 96.000 (96.222) Prec@5 99.000 (99.667) +2022-11-14 17:07:14,411 Epoch: [467][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0219 (0.0252) Prec@1 96.000 (96.200) Prec@5 100.000 (99.700) +2022-11-14 17:07:14,600 Epoch: [467][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0501 (0.0275) Prec@1 92.000 (95.818) Prec@5 99.000 (99.636) +2022-11-14 17:07:14,834 Epoch: [467][110/500] Time 0.027 (0.017) Data 0.001 (0.004) Loss 0.0292 (0.0276) Prec@1 95.000 (95.750) Prec@5 100.000 (99.667) +2022-11-14 17:07:15,118 Epoch: [467][120/500] Time 0.033 (0.018) Data 0.002 (0.004) Loss 0.0224 (0.0272) Prec@1 97.000 (95.846) Prec@5 100.000 (99.692) +2022-11-14 17:07:15,404 Epoch: [467][130/500] Time 0.027 (0.019) Data 0.002 (0.004) Loss 0.0363 (0.0279) Prec@1 95.000 (95.786) Prec@5 100.000 (99.714) +2022-11-14 17:07:15,699 Epoch: [467][140/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0102 (0.0267) Prec@1 99.000 (96.000) Prec@5 100.000 (99.733) +2022-11-14 17:07:15,992 Epoch: [467][150/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0405 (0.0276) Prec@1 95.000 (95.938) Prec@5 100.000 (99.750) +2022-11-14 17:07:16,289 Epoch: [467][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0391 (0.0282) Prec@1 95.000 (95.882) Prec@5 100.000 (99.765) +2022-11-14 17:07:16,593 Epoch: [467][170/500] Time 0.029 (0.020) Data 0.001 (0.003) Loss 0.0373 (0.0288) Prec@1 95.000 (95.833) Prec@5 100.000 (99.778) +2022-11-14 17:07:16,889 Epoch: [467][180/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0335 (0.0290) Prec@1 93.000 (95.684) Prec@5 100.000 (99.789) +2022-11-14 17:07:17,180 Epoch: [467][190/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0460 (0.0299) Prec@1 92.000 (95.500) Prec@5 100.000 (99.800) +2022-11-14 17:07:17,470 Epoch: [467][200/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0371 (0.0302) Prec@1 93.000 (95.381) Prec@5 100.000 (99.810) +2022-11-14 17:07:17,753 Epoch: [467][210/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0127 (0.0294) Prec@1 98.000 (95.500) Prec@5 100.000 (99.818) +2022-11-14 17:07:18,036 Epoch: [467][220/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0144 (0.0288) Prec@1 97.000 (95.565) Prec@5 100.000 (99.826) +2022-11-14 17:07:18,320 Epoch: [467][230/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0333 (0.0289) Prec@1 94.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:07:18,603 Epoch: [467][240/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0284 (0.0289) Prec@1 95.000 (95.480) Prec@5 100.000 (99.840) +2022-11-14 17:07:18,884 Epoch: [467][250/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0543 (0.0299) Prec@1 91.000 (95.308) Prec@5 100.000 (99.846) +2022-11-14 17:07:19,169 Epoch: [467][260/500] Time 0.024 (0.022) Data 0.002 (0.003) Loss 0.0310 (0.0299) Prec@1 95.000 (95.296) Prec@5 100.000 (99.852) +2022-11-14 17:07:19,451 Epoch: [467][270/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0366 (0.0302) Prec@1 95.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 17:07:19,732 Epoch: [467][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0331 (0.0303) Prec@1 94.000 (95.241) Prec@5 100.000 (99.862) +2022-11-14 17:07:20,014 Epoch: [467][290/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0211 (0.0300) Prec@1 97.000 (95.300) Prec@5 100.000 (99.867) +2022-11-14 17:07:20,297 Epoch: [467][300/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0338 (0.0301) Prec@1 94.000 (95.258) Prec@5 100.000 (99.871) +2022-11-14 17:07:20,582 Epoch: [467][310/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0342 (0.0302) Prec@1 94.000 (95.219) Prec@5 100.000 (99.875) +2022-11-14 17:07:20,858 Epoch: [467][320/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0397 (0.0305) Prec@1 94.000 (95.182) Prec@5 100.000 (99.879) +2022-11-14 17:07:21,138 Epoch: [467][330/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0241 (0.0303) Prec@1 97.000 (95.235) Prec@5 100.000 (99.882) +2022-11-14 17:07:21,415 Epoch: [467][340/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0345 (0.0304) Prec@1 93.000 (95.171) Prec@5 100.000 (99.886) +2022-11-14 17:07:21,696 Epoch: [467][350/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0723 (0.0316) Prec@1 88.000 (94.972) Prec@5 98.000 (99.833) +2022-11-14 17:07:21,969 Epoch: [467][360/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0425 (0.0319) Prec@1 92.000 (94.892) Prec@5 100.000 (99.838) +2022-11-14 17:07:22,249 Epoch: [467][370/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0155 (0.0315) Prec@1 97.000 (94.947) Prec@5 100.000 (99.842) +2022-11-14 17:07:22,531 Epoch: [467][380/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0242 (0.0313) Prec@1 95.000 (94.949) Prec@5 100.000 (99.846) +2022-11-14 17:07:22,812 Epoch: [467][390/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0329 (0.0313) Prec@1 94.000 (94.925) Prec@5 100.000 (99.850) +2022-11-14 17:07:23,098 Epoch: [467][400/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0462 (0.0317) Prec@1 93.000 (94.878) Prec@5 100.000 (99.854) +2022-11-14 17:07:23,374 Epoch: [467][410/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0274 (0.0316) Prec@1 96.000 (94.905) Prec@5 100.000 (99.857) +2022-11-14 17:07:23,658 Epoch: [467][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0108 (0.0311) Prec@1 99.000 (95.000) Prec@5 100.000 (99.860) +2022-11-14 17:07:23,940 Epoch: [467][430/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0155 (0.0307) Prec@1 98.000 (95.068) Prec@5 100.000 (99.864) +2022-11-14 17:07:24,223 Epoch: [467][440/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0151 (0.0304) Prec@1 99.000 (95.156) Prec@5 100.000 (99.867) +2022-11-14 17:07:24,506 Epoch: [467][450/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0592 (0.0310) Prec@1 88.000 (95.000) Prec@5 100.000 (99.870) +2022-11-14 17:07:24,780 Epoch: [467][460/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0259 (0.0309) Prec@1 96.000 (95.021) Prec@5 100.000 (99.872) +2022-11-14 17:07:25,056 Epoch: [467][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0253 (0.0308) Prec@1 94.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:07:25,340 Epoch: [467][480/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0523 (0.0312) Prec@1 92.000 (94.939) Prec@5 100.000 (99.878) +2022-11-14 17:07:25,623 Epoch: [467][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0206 (0.0310) Prec@1 96.000 (94.960) Prec@5 100.000 (99.880) +2022-11-14 17:07:25,875 Epoch: [467][499/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0436 (0.0313) Prec@1 93.000 (94.922) Prec@5 100.000 (99.882) +2022-11-14 17:07:26,175 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0736 (0.0736) Prec@1 87.000 (87.000) Prec@5 99.000 (99.000) +2022-11-14 17:07:26,187 Test: [1/100] Model Time 0.010 (0.012) Loss Time 0.000 (0.000) Loss 0.0640 (0.0688) Prec@1 90.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 17:07:26,196 Test: [2/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0836 (0.0737) Prec@1 84.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 17:07:26,206 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0802 (0.0753) Prec@1 85.000 (86.500) Prec@5 99.000 (99.500) +2022-11-14 17:07:26,216 Test: [4/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0631 (0.0729) Prec@1 91.000 (87.400) Prec@5 98.000 (99.200) +2022-11-14 17:07:26,225 Test: [5/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0497 (0.0690) Prec@1 93.000 (88.333) Prec@5 100.000 (99.333) +2022-11-14 17:07:26,232 Test: [6/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0625 (0.0681) Prec@1 91.000 (88.714) Prec@5 99.000 (99.286) +2022-11-14 17:07:26,239 Test: [7/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.1143 (0.0739) Prec@1 82.000 (87.875) Prec@5 100.000 (99.375) +2022-11-14 17:07:26,250 Test: [8/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0682 (0.0732) Prec@1 91.000 (88.222) Prec@5 98.000 (99.222) +2022-11-14 17:07:26,259 Test: [9/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0903 (0.0749) Prec@1 87.000 (88.100) Prec@5 99.000 (99.200) +2022-11-14 17:07:26,269 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0634 (0.0739) Prec@1 89.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 17:07:26,278 Test: [11/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0601 (0.0728) Prec@1 90.000 (88.333) Prec@5 99.000 (99.250) +2022-11-14 17:07:26,286 Test: [12/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0616 (0.0719) Prec@1 90.000 (88.462) Prec@5 100.000 (99.308) +2022-11-14 17:07:26,293 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0713) Prec@1 91.000 (88.643) Prec@5 100.000 (99.357) +2022-11-14 17:07:26,303 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0772 (0.0717) Prec@1 89.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 17:07:26,312 Test: [15/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0717 (0.0717) Prec@1 88.000 (88.625) Prec@5 99.000 (99.312) +2022-11-14 17:07:26,320 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0599 (0.0710) Prec@1 91.000 (88.765) Prec@5 99.000 (99.294) +2022-11-14 17:07:26,327 Test: [17/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0718) Prec@1 88.000 (88.722) Prec@5 100.000 (99.333) +2022-11-14 17:07:26,338 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0730) Prec@1 80.000 (88.263) Prec@5 97.000 (99.211) +2022-11-14 17:07:26,347 Test: [19/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0941 (0.0740) Prec@1 85.000 (88.100) Prec@5 98.000 (99.150) +2022-11-14 17:07:26,354 Test: [20/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0519 (0.0730) Prec@1 93.000 (88.333) Prec@5 100.000 (99.190) +2022-11-14 17:07:26,362 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0871 (0.0736) Prec@1 84.000 (88.136) Prec@5 100.000 (99.227) +2022-11-14 17:07:26,369 Test: [22/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1122 (0.0753) Prec@1 81.000 (87.826) Prec@5 97.000 (99.130) +2022-11-14 17:07:26,377 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0751) Prec@1 89.000 (87.875) Prec@5 99.000 (99.125) +2022-11-14 17:07:26,384 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0752) Prec@1 86.000 (87.800) Prec@5 100.000 (99.160) +2022-11-14 17:07:26,392 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1013 (0.0762) Prec@1 87.000 (87.769) Prec@5 99.000 (99.154) +2022-11-14 17:07:26,399 Test: [26/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0444 (0.0750) Prec@1 93.000 (87.963) Prec@5 100.000 (99.185) +2022-11-14 17:07:26,407 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0746) Prec@1 92.000 (88.107) Prec@5 100.000 (99.214) +2022-11-14 17:07:26,414 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0749) Prec@1 86.000 (88.034) Prec@5 98.000 (99.172) +2022-11-14 17:07:26,421 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0752) Prec@1 88.000 (88.033) Prec@5 99.000 (99.167) +2022-11-14 17:07:26,429 Test: [30/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0746) Prec@1 91.000 (88.129) Prec@5 100.000 (99.194) +2022-11-14 17:07:26,436 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0745) Prec@1 90.000 (88.188) Prec@5 99.000 (99.188) +2022-11-14 17:07:26,444 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0751) Prec@1 86.000 (88.121) Prec@5 100.000 (99.212) +2022-11-14 17:07:26,451 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0749) Prec@1 88.000 (88.118) Prec@5 100.000 (99.235) +2022-11-14 17:07:26,458 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0755) Prec@1 84.000 (88.000) Prec@5 98.000 (99.200) +2022-11-14 17:07:26,466 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0755) Prec@1 88.000 (88.000) Prec@5 99.000 (99.194) +2022-11-14 17:07:26,473 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0756) Prec@1 89.000 (88.027) Prec@5 99.000 (99.189) +2022-11-14 17:07:26,481 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0762) Prec@1 85.000 (87.947) Prec@5 100.000 (99.211) +2022-11-14 17:07:26,488 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0759) Prec@1 91.000 (88.026) Prec@5 99.000 (99.205) +2022-11-14 17:07:26,496 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0756) Prec@1 88.000 (88.025) Prec@5 100.000 (99.225) +2022-11-14 17:07:26,503 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1039 (0.0763) Prec@1 83.000 (87.902) Prec@5 99.000 (99.220) +2022-11-14 17:07:26,510 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0759) Prec@1 90.000 (87.952) Prec@5 100.000 (99.238) +2022-11-14 17:07:26,518 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0755) Prec@1 89.000 (87.977) Prec@5 100.000 (99.256) +2022-11-14 17:07:26,525 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0753) Prec@1 91.000 (88.045) Prec@5 99.000 (99.250) +2022-11-14 17:07:26,533 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0749) Prec@1 90.000 (88.089) Prec@5 98.000 (99.222) +2022-11-14 17:07:26,540 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0755) Prec@1 85.000 (88.022) Prec@5 99.000 (99.217) +2022-11-14 17:07:26,548 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0755) Prec@1 88.000 (88.021) Prec@5 100.000 (99.234) +2022-11-14 17:07:26,555 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0761) Prec@1 84.000 (87.938) Prec@5 98.000 (99.208) +2022-11-14 17:07:26,563 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0762) Prec@1 85.000 (87.878) Prec@5 98.000 (99.184) +2022-11-14 17:07:26,570 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0762) Prec@1 90.000 (87.920) Prec@5 100.000 (99.200) +2022-11-14 17:07:26,578 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0758) Prec@1 90.000 (87.961) Prec@5 100.000 (99.216) +2022-11-14 17:07:26,585 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0758) Prec@1 88.000 (87.962) Prec@5 99.000 (99.212) +2022-11-14 17:07:26,593 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0759) Prec@1 86.000 (87.925) Prec@5 99.000 (99.208) +2022-11-14 17:07:26,601 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0761) Prec@1 87.000 (87.907) Prec@5 99.000 (99.204) +2022-11-14 17:07:26,608 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0765) Prec@1 84.000 (87.836) Prec@5 99.000 (99.200) +2022-11-14 17:07:26,616 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0765) Prec@1 88.000 (87.839) Prec@5 99.000 (99.196) +2022-11-14 17:07:26,623 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0763) Prec@1 90.000 (87.877) Prec@5 100.000 (99.211) +2022-11-14 17:07:26,630 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0761) Prec@1 88.000 (87.879) Prec@5 99.000 (99.207) +2022-11-14 17:07:26,638 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0764) Prec@1 83.000 (87.797) Prec@5 100.000 (99.220) +2022-11-14 17:07:26,645 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0762) Prec@1 88.000 (87.800) Prec@5 100.000 (99.233) +2022-11-14 17:07:26,652 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0758) Prec@1 94.000 (87.902) Prec@5 99.000 (99.230) +2022-11-14 17:07:26,660 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0755) Prec@1 90.000 (87.935) Prec@5 100.000 (99.242) +2022-11-14 17:07:26,668 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0753) Prec@1 91.000 (87.984) Prec@5 100.000 (99.254) +2022-11-14 17:07:26,675 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0494 (0.0749) Prec@1 93.000 (88.062) Prec@5 100.000 (99.266) +2022-11-14 17:07:26,682 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0869 (0.0751) Prec@1 85.000 (88.015) Prec@5 99.000 (99.262) +2022-11-14 17:07:26,690 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0750) Prec@1 87.000 (88.000) Prec@5 100.000 (99.273) +2022-11-14 17:07:26,697 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0412 (0.0745) Prec@1 93.000 (88.075) Prec@5 100.000 (99.284) +2022-11-14 17:07:26,705 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0744) Prec@1 90.000 (88.103) Prec@5 100.000 (99.294) +2022-11-14 17:07:26,712 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0745) Prec@1 86.000 (88.072) Prec@5 99.000 (99.290) +2022-11-14 17:07:26,720 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0743) Prec@1 90.000 (88.100) Prec@5 100.000 (99.300) +2022-11-14 17:07:26,727 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0747) Prec@1 85.000 (88.056) Prec@5 99.000 (99.296) +2022-11-14 17:07:26,735 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0745) Prec@1 90.000 (88.083) Prec@5 100.000 (99.306) +2022-11-14 17:07:26,742 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0471 (0.0741) Prec@1 92.000 (88.137) Prec@5 100.000 (99.315) +2022-11-14 17:07:26,749 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0740) Prec@1 89.000 (88.149) Prec@5 100.000 (99.324) +2022-11-14 17:07:26,757 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0960 (0.0743) Prec@1 85.000 (88.107) Prec@5 100.000 (99.333) +2022-11-14 17:07:26,764 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0495 (0.0740) Prec@1 91.000 (88.145) Prec@5 100.000 (99.342) +2022-11-14 17:07:26,772 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0741) Prec@1 85.000 (88.104) Prec@5 99.000 (99.338) +2022-11-14 17:07:26,779 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0745) Prec@1 82.000 (88.026) Prec@5 98.000 (99.321) +2022-11-14 17:07:26,787 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0744) Prec@1 88.000 (88.025) Prec@5 100.000 (99.329) +2022-11-14 17:07:26,794 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0747) Prec@1 84.000 (87.975) Prec@5 100.000 (99.338) +2022-11-14 17:07:26,802 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0749) Prec@1 87.000 (87.963) Prec@5 98.000 (99.321) +2022-11-14 17:07:26,810 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0751) Prec@1 83.000 (87.902) Prec@5 100.000 (99.329) +2022-11-14 17:07:26,818 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0754) Prec@1 85.000 (87.867) Prec@5 100.000 (99.337) +2022-11-14 17:07:26,826 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0754) Prec@1 84.000 (87.821) Prec@5 99.000 (99.333) +2022-11-14 17:07:26,833 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 89.000 (87.835) Prec@5 99.000 (99.329) +2022-11-14 17:07:26,840 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0758) Prec@1 85.000 (87.802) Prec@5 100.000 (99.337) +2022-11-14 17:07:26,848 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0758) Prec@1 89.000 (87.816) Prec@5 99.000 (99.333) +2022-11-14 17:07:26,856 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0761) Prec@1 82.000 (87.750) Prec@5 99.000 (99.330) +2022-11-14 17:07:26,863 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0760) Prec@1 87.000 (87.742) Prec@5 100.000 (99.337) +2022-11-14 17:07:26,871 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0759) Prec@1 91.000 (87.778) Prec@5 100.000 (99.344) +2022-11-14 17:07:26,879 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0441 (0.0755) Prec@1 94.000 (87.846) Prec@5 99.000 (99.341) +2022-11-14 17:07:26,886 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0753) Prec@1 93.000 (87.902) Prec@5 99.000 (99.337) +2022-11-14 17:07:26,894 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0754) Prec@1 85.000 (87.871) Prec@5 98.000 (99.323) +2022-11-14 17:07:26,901 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0755) Prec@1 87.000 (87.862) Prec@5 100.000 (99.330) +2022-11-14 17:07:26,909 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1159 (0.0759) Prec@1 82.000 (87.800) Prec@5 100.000 (99.337) +2022-11-14 17:07:26,916 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0758) Prec@1 92.000 (87.844) Prec@5 99.000 (99.333) +2022-11-14 17:07:26,923 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0425 (0.0754) Prec@1 92.000 (87.887) Prec@5 99.000 (99.330) +2022-11-14 17:07:26,930 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0755) Prec@1 89.000 (87.898) Prec@5 97.000 (99.306) +2022-11-14 17:07:26,938 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0758) Prec@1 82.000 (87.838) Prec@5 97.000 (99.283) +2022-11-14 17:07:26,945 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0758) Prec@1 89.000 (87.850) Prec@5 100.000 (99.290) +2022-11-14 17:07:27,005 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:07:27,323 Epoch: [468][0/500] Time 0.021 (0.021) Data 0.237 (0.237) Loss 0.0285 (0.0285) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:27,519 Epoch: [468][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0405 (0.0345) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:27,711 Epoch: [468][20/500] Time 0.018 (0.017) Data 0.001 (0.013) Loss 0.0309 (0.0333) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:07:27,905 Epoch: [468][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0295 (0.0323) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:28,099 Epoch: [468][40/500] Time 0.019 (0.017) Data 0.002 (0.007) Loss 0.0226 (0.0304) Prec@1 96.000 (95.600) Prec@5 100.000 (100.000) +2022-11-14 17:07:28,292 Epoch: [468][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0574 (0.0349) Prec@1 88.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 17:07:28,484 Epoch: [468][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0159 (0.0322) Prec@1 99.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:28,672 Epoch: [468][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0096 (0.0293) Prec@1 99.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:28,860 Epoch: [468][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0156 (0.0278) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:07:29,052 Epoch: [468][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0421 (0.0292) Prec@1 93.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:07:29,243 Epoch: [468][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0215 (0.0285) Prec@1 95.000 (95.364) Prec@5 100.000 (100.000) +2022-11-14 17:07:29,436 Epoch: [468][110/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0365 (0.0292) Prec@1 93.000 (95.167) Prec@5 100.000 (100.000) +2022-11-14 17:07:29,678 Epoch: [468][120/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0520 (0.0310) Prec@1 91.000 (94.846) Prec@5 98.000 (99.846) +2022-11-14 17:07:29,940 Epoch: [468][130/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0271 (0.0307) Prec@1 96.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 17:07:30,205 Epoch: [468][140/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0325 (0.0308) Prec@1 96.000 (95.000) Prec@5 100.000 (99.867) +2022-11-14 17:07:30,462 Epoch: [468][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0284 (0.0307) Prec@1 95.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:07:30,715 Epoch: [468][160/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0269 (0.0304) Prec@1 95.000 (95.000) Prec@5 100.000 (99.882) +2022-11-14 17:07:30,964 Epoch: [468][170/500] Time 0.023 (0.019) Data 0.001 (0.003) Loss 0.0230 (0.0300) Prec@1 97.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 17:07:31,214 Epoch: [468][180/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0245 (0.0297) Prec@1 97.000 (95.211) Prec@5 100.000 (99.895) +2022-11-14 17:07:31,466 Epoch: [468][190/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0316 (0.0298) Prec@1 94.000 (95.150) Prec@5 100.000 (99.900) +2022-11-14 17:07:31,721 Epoch: [468][200/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0327 (0.0300) Prec@1 95.000 (95.143) Prec@5 100.000 (99.905) +2022-11-14 17:07:31,979 Epoch: [468][210/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0239 (0.0297) Prec@1 96.000 (95.182) Prec@5 100.000 (99.909) +2022-11-14 17:07:32,231 Epoch: [468][220/500] Time 0.023 (0.020) Data 0.002 (0.003) Loss 0.0484 (0.0305) Prec@1 91.000 (95.000) Prec@5 100.000 (99.913) +2022-11-14 17:07:32,483 Epoch: [468][230/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0432 (0.0310) Prec@1 94.000 (94.958) Prec@5 100.000 (99.917) +2022-11-14 17:07:32,731 Epoch: [468][240/500] Time 0.023 (0.020) Data 0.001 (0.003) Loss 0.0225 (0.0307) Prec@1 95.000 (94.960) Prec@5 100.000 (99.920) +2022-11-14 17:07:32,986 Epoch: [468][250/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0292 (0.0306) Prec@1 94.000 (94.923) Prec@5 100.000 (99.923) +2022-11-14 17:07:33,240 Epoch: [468][260/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0235 (0.0304) Prec@1 97.000 (95.000) Prec@5 100.000 (99.926) +2022-11-14 17:07:33,489 Epoch: [468][270/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0284 (0.0303) Prec@1 95.000 (95.000) Prec@5 100.000 (99.929) +2022-11-14 17:07:33,738 Epoch: [468][280/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0425 (0.0307) Prec@1 94.000 (94.966) Prec@5 100.000 (99.931) +2022-11-14 17:07:33,985 Epoch: [468][290/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0284 (0.0306) Prec@1 95.000 (94.967) Prec@5 99.000 (99.900) +2022-11-14 17:07:34,236 Epoch: [468][300/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0227 (0.0304) Prec@1 97.000 (95.032) Prec@5 100.000 (99.903) +2022-11-14 17:07:34,485 Epoch: [468][310/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0544 (0.0311) Prec@1 89.000 (94.844) Prec@5 100.000 (99.906) +2022-11-14 17:07:34,740 Epoch: [468][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0206 (0.0308) Prec@1 97.000 (94.909) Prec@5 100.000 (99.909) +2022-11-14 17:07:34,993 Epoch: [468][330/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0145 (0.0303) Prec@1 97.000 (94.971) Prec@5 100.000 (99.912) +2022-11-14 17:07:35,244 Epoch: [468][340/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0448 (0.0307) Prec@1 93.000 (94.914) Prec@5 100.000 (99.914) +2022-11-14 17:07:35,494 Epoch: [468][350/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0226 (0.0305) Prec@1 96.000 (94.944) Prec@5 100.000 (99.917) +2022-11-14 17:07:35,742 Epoch: [468][360/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0310 (0.0305) Prec@1 95.000 (94.946) Prec@5 100.000 (99.919) +2022-11-14 17:07:35,993 Epoch: [468][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0204 (0.0303) Prec@1 95.000 (94.947) Prec@5 100.000 (99.921) +2022-11-14 17:07:36,244 Epoch: [468][380/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0294 (0.0302) Prec@1 94.000 (94.923) Prec@5 100.000 (99.923) +2022-11-14 17:07:36,500 Epoch: [468][390/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0310 (0.0303) Prec@1 96.000 (94.950) Prec@5 99.000 (99.900) +2022-11-14 17:07:36,753 Epoch: [468][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0227 (0.0301) Prec@1 98.000 (95.024) Prec@5 100.000 (99.902) +2022-11-14 17:07:37,001 Epoch: [468][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0107 (0.0296) Prec@1 98.000 (95.095) Prec@5 100.000 (99.905) +2022-11-14 17:07:37,253 Epoch: [468][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0477 (0.0300) Prec@1 93.000 (95.047) Prec@5 99.000 (99.884) +2022-11-14 17:07:37,503 Epoch: [468][430/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0336 (0.0301) Prec@1 94.000 (95.023) Prec@5 100.000 (99.886) +2022-11-14 17:07:37,755 Epoch: [468][440/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0313 (0.0301) Prec@1 96.000 (95.044) Prec@5 100.000 (99.889) +2022-11-14 17:07:38,003 Epoch: [468][450/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0232 (0.0300) Prec@1 97.000 (95.087) Prec@5 100.000 (99.891) +2022-11-14 17:07:38,257 Epoch: [468][460/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0380 (0.0302) Prec@1 92.000 (95.021) Prec@5 99.000 (99.872) +2022-11-14 17:07:38,504 Epoch: [468][470/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0229 (0.0300) Prec@1 97.000 (95.062) Prec@5 100.000 (99.875) +2022-11-14 17:07:38,754 Epoch: [468][480/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0318 (0.0301) Prec@1 96.000 (95.082) Prec@5 100.000 (99.878) +2022-11-14 17:07:39,008 Epoch: [468][490/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0297 (0.0300) Prec@1 95.000 (95.080) Prec@5 100.000 (99.880) +2022-11-14 17:07:39,234 Epoch: [468][499/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0184 (0.0298) Prec@1 98.000 (95.137) Prec@5 100.000 (99.882) +2022-11-14 17:07:39,537 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0748 (0.0748) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:39,546 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0516 (0.0632) Prec@1 92.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:39,554 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0652 (0.0638) Prec@1 90.000 (89.667) Prec@5 99.000 (99.667) +2022-11-14 17:07:39,564 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0658) Prec@1 89.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:07:39,571 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0718 (0.0670) Prec@1 87.000 (89.000) Prec@5 98.000 (99.200) +2022-11-14 17:07:39,578 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0524 (0.0646) Prec@1 92.000 (89.500) Prec@5 99.000 (99.167) +2022-11-14 17:07:39,585 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0633) Prec@1 92.000 (89.857) Prec@5 99.000 (99.143) +2022-11-14 17:07:39,594 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0672) Prec@1 81.000 (88.750) Prec@5 98.000 (99.000) +2022-11-14 17:07:39,601 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0697) Prec@1 87.000 (88.556) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,608 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0704) Prec@1 90.000 (88.700) Prec@5 98.000 (98.900) +2022-11-14 17:07:39,615 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0706) Prec@1 87.000 (88.545) Prec@5 99.000 (98.909) +2022-11-14 17:07:39,622 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0718) Prec@1 87.000 (88.417) Prec@5 100.000 (99.000) +2022-11-14 17:07:39,630 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0707) Prec@1 90.000 (88.538) Prec@5 100.000 (99.077) +2022-11-14 17:07:39,638 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0712) Prec@1 89.000 (88.571) Prec@5 100.000 (99.143) +2022-11-14 17:07:39,645 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0715) Prec@1 87.000 (88.467) Prec@5 100.000 (99.200) +2022-11-14 17:07:39,653 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0706) Prec@1 91.000 (88.625) Prec@5 100.000 (99.250) +2022-11-14 17:07:39,661 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0694) Prec@1 93.000 (88.882) Prec@5 98.000 (99.176) +2022-11-14 17:07:39,668 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1213 (0.0722) Prec@1 81.000 (88.444) Prec@5 100.000 (99.222) +2022-11-14 17:07:39,676 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0731) Prec@1 84.000 (88.211) Prec@5 96.000 (99.053) +2022-11-14 17:07:39,684 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.0748) Prec@1 83.000 (87.950) Prec@5 98.000 (99.000) +2022-11-14 17:07:39,692 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0747) Prec@1 87.000 (87.905) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,699 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0750) Prec@1 87.000 (87.864) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,707 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0757) Prec@1 85.000 (87.739) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,715 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0761) Prec@1 87.000 (87.708) Prec@5 100.000 (99.042) +2022-11-14 17:07:39,723 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0766) Prec@1 84.000 (87.560) Prec@5 100.000 (99.080) +2022-11-14 17:07:39,730 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0770) Prec@1 87.000 (87.538) Prec@5 98.000 (99.038) +2022-11-14 17:07:39,738 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0355 (0.0754) Prec@1 93.000 (87.741) Prec@5 100.000 (99.074) +2022-11-14 17:07:39,745 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0749) Prec@1 92.000 (87.893) Prec@5 100.000 (99.107) +2022-11-14 17:07:39,753 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0750) Prec@1 85.000 (87.793) Prec@5 99.000 (99.103) +2022-11-14 17:07:39,761 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0752) Prec@1 88.000 (87.800) Prec@5 99.000 (99.100) +2022-11-14 17:07:39,768 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0744) Prec@1 91.000 (87.903) Prec@5 100.000 (99.129) +2022-11-14 17:07:39,776 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0744) Prec@1 88.000 (87.906) Prec@5 99.000 (99.125) +2022-11-14 17:07:39,784 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0747) Prec@1 86.000 (87.848) Prec@5 100.000 (99.152) +2022-11-14 17:07:39,791 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0743) Prec@1 90.000 (87.912) Prec@5 98.000 (99.118) +2022-11-14 17:07:39,799 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0749) Prec@1 87.000 (87.886) Prec@5 97.000 (99.057) +2022-11-14 17:07:39,807 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0748) Prec@1 89.000 (87.917) Prec@5 100.000 (99.083) +2022-11-14 17:07:39,814 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0745) Prec@1 90.000 (87.973) Prec@5 99.000 (99.081) +2022-11-14 17:07:39,822 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0747) Prec@1 87.000 (87.947) Prec@5 98.000 (99.053) +2022-11-14 17:07:39,830 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0743) Prec@1 92.000 (88.051) Prec@5 99.000 (99.051) +2022-11-14 17:07:39,837 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0739) Prec@1 90.000 (88.100) Prec@5 99.000 (99.050) +2022-11-14 17:07:39,845 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0747) Prec@1 83.000 (87.976) Prec@5 98.000 (99.024) +2022-11-14 17:07:39,853 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0747) Prec@1 87.000 (87.952) Prec@5 99.000 (99.024) +2022-11-14 17:07:39,860 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0521 (0.0741) Prec@1 94.000 (88.093) Prec@5 100.000 (99.047) +2022-11-14 17:07:39,868 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0740) Prec@1 91.000 (88.159) Prec@5 98.000 (99.023) +2022-11-14 17:07:39,875 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0736) Prec@1 90.000 (88.200) Prec@5 98.000 (99.000) +2022-11-14 17:07:39,883 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0742) Prec@1 84.000 (88.109) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,891 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0741) Prec@1 87.000 (88.085) Prec@5 99.000 (99.000) +2022-11-14 17:07:39,899 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0746) Prec@1 86.000 (88.042) Prec@5 98.000 (98.979) +2022-11-14 17:07:39,907 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0460 (0.0740) Prec@1 92.000 (88.122) Prec@5 100.000 (99.000) +2022-11-14 17:07:39,915 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0745) Prec@1 83.000 (88.020) Prec@5 100.000 (99.020) +2022-11-14 17:07:39,923 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0741) Prec@1 90.000 (88.059) Prec@5 100.000 (99.039) +2022-11-14 17:07:39,930 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0742) Prec@1 87.000 (88.038) Prec@5 99.000 (99.038) +2022-11-14 17:07:39,938 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0739) Prec@1 92.000 (88.113) Prec@5 100.000 (99.057) +2022-11-14 17:07:39,946 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0740) Prec@1 86.000 (88.074) Prec@5 99.000 (99.056) +2022-11-14 17:07:39,953 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0744) Prec@1 84.000 (88.000) Prec@5 99.000 (99.055) +2022-11-14 17:07:39,961 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0745) Prec@1 88.000 (88.000) Prec@5 99.000 (99.054) +2022-11-14 17:07:39,969 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0748) Prec@1 85.000 (87.947) Prec@5 99.000 (99.053) +2022-11-14 17:07:39,976 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0747) Prec@1 89.000 (87.966) Prec@5 98.000 (99.034) +2022-11-14 17:07:39,984 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1098 (0.0753) Prec@1 84.000 (87.898) Prec@5 99.000 (99.034) +2022-11-14 17:07:39,992 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0753) Prec@1 86.000 (87.867) Prec@5 100.000 (99.050) +2022-11-14 17:07:39,999 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0751) Prec@1 93.000 (87.951) Prec@5 99.000 (99.049) +2022-11-14 17:07:40,007 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0753) Prec@1 85.000 (87.903) Prec@5 100.000 (99.065) +2022-11-14 17:07:40,014 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0750) Prec@1 91.000 (87.952) Prec@5 98.000 (99.048) +2022-11-14 17:07:40,022 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0748) Prec@1 91.000 (88.000) Prec@5 99.000 (99.047) +2022-11-14 17:07:40,030 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1016 (0.0752) Prec@1 84.000 (87.938) Prec@5 98.000 (99.031) +2022-11-14 17:07:40,037 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0752) Prec@1 90.000 (87.970) Prec@5 98.000 (99.015) +2022-11-14 17:07:40,045 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0348 (0.0746) Prec@1 93.000 (88.045) Prec@5 99.000 (99.015) +2022-11-14 17:07:40,053 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0745) Prec@1 90.000 (88.074) Prec@5 98.000 (99.000) +2022-11-14 17:07:40,061 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0471 (0.0741) Prec@1 93.000 (88.145) Prec@5 99.000 (99.000) +2022-11-14 17:07:40,069 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0743) Prec@1 88.000 (88.143) Prec@5 100.000 (99.014) +2022-11-14 17:07:40,076 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0745) Prec@1 88.000 (88.141) Prec@5 98.000 (99.000) +2022-11-14 17:07:40,085 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0744) Prec@1 90.000 (88.167) Prec@5 100.000 (99.014) +2022-11-14 17:07:40,093 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0741) Prec@1 91.000 (88.205) Prec@5 100.000 (99.027) +2022-11-14 17:07:40,101 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0737) Prec@1 93.000 (88.270) Prec@5 100.000 (99.041) +2022-11-14 17:07:40,108 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0740) Prec@1 85.000 (88.227) Prec@5 100.000 (99.053) +2022-11-14 17:07:40,116 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0737) Prec@1 90.000 (88.250) Prec@5 100.000 (99.066) +2022-11-14 17:07:40,124 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0735) Prec@1 90.000 (88.273) Prec@5 97.000 (99.039) +2022-11-14 17:07:40,131 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0737) Prec@1 87.000 (88.256) Prec@5 99.000 (99.038) +2022-11-14 17:07:40,139 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0736) Prec@1 90.000 (88.278) Prec@5 100.000 (99.051) +2022-11-14 17:07:40,146 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0735) Prec@1 90.000 (88.300) Prec@5 100.000 (99.062) +2022-11-14 17:07:40,154 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0737) Prec@1 83.000 (88.235) Prec@5 98.000 (99.049) +2022-11-14 17:07:40,162 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0737) Prec@1 86.000 (88.207) Prec@5 99.000 (99.049) +2022-11-14 17:07:40,169 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0740) Prec@1 81.000 (88.120) Prec@5 98.000 (99.036) +2022-11-14 17:07:40,177 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0741) Prec@1 86.000 (88.095) Prec@5 99.000 (99.036) +2022-11-14 17:07:40,185 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0745) Prec@1 82.000 (88.024) Prec@5 99.000 (99.035) +2022-11-14 17:07:40,192 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0746) Prec@1 86.000 (88.000) Prec@5 100.000 (99.047) +2022-11-14 17:07:40,200 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0748) Prec@1 86.000 (87.977) Prec@5 99.000 (99.046) +2022-11-14 17:07:40,207 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0750) Prec@1 86.000 (87.955) Prec@5 98.000 (99.034) +2022-11-14 17:07:40,215 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0752) Prec@1 83.000 (87.899) Prec@5 100.000 (99.045) +2022-11-14 17:07:40,223 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0754) Prec@1 87.000 (87.889) Prec@5 99.000 (99.044) +2022-11-14 17:07:40,230 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0752) Prec@1 90.000 (87.912) Prec@5 100.000 (99.055) +2022-11-14 17:07:40,238 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0750) Prec@1 92.000 (87.957) Prec@5 100.000 (99.065) +2022-11-14 17:07:40,245 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0750) Prec@1 89.000 (87.968) Prec@5 100.000 (99.075) +2022-11-14 17:07:40,253 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0753) Prec@1 83.000 (87.915) Prec@5 99.000 (99.074) +2022-11-14 17:07:40,260 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0753) Prec@1 87.000 (87.905) Prec@5 99.000 (99.074) +2022-11-14 17:07:40,268 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0752) Prec@1 93.000 (87.958) Prec@5 99.000 (99.073) +2022-11-14 17:07:40,275 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0749) Prec@1 92.000 (88.000) Prec@5 99.000 (99.072) +2022-11-14 17:07:40,283 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0752) Prec@1 85.000 (87.969) Prec@5 99.000 (99.071) +2022-11-14 17:07:40,290 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1096 (0.0755) Prec@1 85.000 (87.939) Prec@5 99.000 (99.071) +2022-11-14 17:07:40,298 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0752) Prec@1 92.000 (87.980) Prec@5 100.000 (99.080) +2022-11-14 17:07:40,362 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:07:40,684 Epoch: [469][0/500] Time 0.022 (0.022) Data 0.242 (0.242) Loss 0.0346 (0.0346) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 17:07:40,885 Epoch: [469][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0361 (0.0354) Prec@1 93.000 (93.500) Prec@5 99.000 (99.000) +2022-11-14 17:07:41,085 Epoch: [469][20/500] Time 0.018 (0.018) Data 0.002 (0.013) Loss 0.0284 (0.0331) Prec@1 96.000 (94.333) Prec@5 100.000 (99.333) +2022-11-14 17:07:41,284 Epoch: [469][30/500] Time 0.018 (0.018) Data 0.002 (0.010) Loss 0.0222 (0.0304) Prec@1 97.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 17:07:41,482 Epoch: [469][40/500] Time 0.018 (0.018) Data 0.001 (0.008) Loss 0.0114 (0.0266) Prec@1 99.000 (95.800) Prec@5 100.000 (99.600) +2022-11-14 17:07:41,679 Epoch: [469][50/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0388 (0.0286) Prec@1 94.000 (95.500) Prec@5 100.000 (99.667) +2022-11-14 17:07:41,876 Epoch: [469][60/500] Time 0.018 (0.018) Data 0.002 (0.006) Loss 0.0209 (0.0275) Prec@1 97.000 (95.714) Prec@5 100.000 (99.714) +2022-11-14 17:07:42,072 Epoch: [469][70/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0214 (0.0268) Prec@1 97.000 (95.875) Prec@5 100.000 (99.750) +2022-11-14 17:07:42,271 Epoch: [469][80/500] Time 0.018 (0.017) Data 0.002 (0.005) Loss 0.0364 (0.0278) Prec@1 94.000 (95.667) Prec@5 99.000 (99.667) +2022-11-14 17:07:42,465 Epoch: [469][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0282 (0.0279) Prec@1 95.000 (95.600) Prec@5 100.000 (99.700) +2022-11-14 17:07:42,660 Epoch: [469][100/500] Time 0.019 (0.017) Data 0.002 (0.004) Loss 0.0242 (0.0275) Prec@1 97.000 (95.727) Prec@5 99.000 (99.636) +2022-11-14 17:07:42,855 Epoch: [469][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0058 (0.0257) Prec@1 100.000 (96.083) Prec@5 100.000 (99.667) +2022-11-14 17:07:43,050 Epoch: [469][120/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0244 (0.0256) Prec@1 97.000 (96.154) Prec@5 100.000 (99.692) +2022-11-14 17:07:43,285 Epoch: [469][130/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0208 (0.0253) Prec@1 96.000 (96.143) Prec@5 100.000 (99.714) +2022-11-14 17:07:43,575 Epoch: [469][140/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0423 (0.0264) Prec@1 92.000 (95.867) Prec@5 100.000 (99.733) +2022-11-14 17:07:43,870 Epoch: [469][150/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0384 (0.0272) Prec@1 93.000 (95.688) Prec@5 100.000 (99.750) +2022-11-14 17:07:44,162 Epoch: [469][160/500] Time 0.027 (0.019) Data 0.001 (0.003) Loss 0.0111 (0.0262) Prec@1 98.000 (95.824) Prec@5 100.000 (99.765) +2022-11-14 17:07:44,457 Epoch: [469][170/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0167 (0.0257) Prec@1 99.000 (96.000) Prec@5 100.000 (99.778) +2022-11-14 17:07:44,753 Epoch: [469][180/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0289 (0.0259) Prec@1 97.000 (96.053) Prec@5 100.000 (99.789) +2022-11-14 17:07:45,043 Epoch: [469][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0568 (0.0274) Prec@1 91.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 17:07:45,333 Epoch: [469][200/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0312 (0.0276) Prec@1 95.000 (95.762) Prec@5 100.000 (99.810) +2022-11-14 17:07:45,620 Epoch: [469][210/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0112 (0.0268) Prec@1 98.000 (95.864) Prec@5 100.000 (99.818) +2022-11-14 17:07:45,908 Epoch: [469][220/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0224 (0.0267) Prec@1 96.000 (95.870) Prec@5 100.000 (99.826) +2022-11-14 17:07:46,198 Epoch: [469][230/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0377 (0.0271) Prec@1 95.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 17:07:46,489 Epoch: [469][240/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0221 (0.0269) Prec@1 96.000 (95.840) Prec@5 100.000 (99.840) +2022-11-14 17:07:46,775 Epoch: [469][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0093 (0.0262) Prec@1 99.000 (95.962) Prec@5 100.000 (99.846) +2022-11-14 17:07:47,063 Epoch: [469][260/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0188 (0.0260) Prec@1 96.000 (95.963) Prec@5 100.000 (99.852) +2022-11-14 17:07:47,359 Epoch: [469][270/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0441 (0.0266) Prec@1 92.000 (95.821) Prec@5 100.000 (99.857) +2022-11-14 17:07:47,641 Epoch: [469][280/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0331 (0.0268) Prec@1 95.000 (95.793) Prec@5 100.000 (99.862) +2022-11-14 17:07:47,925 Epoch: [469][290/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0175 (0.0265) Prec@1 96.000 (95.800) Prec@5 100.000 (99.867) +2022-11-14 17:07:48,213 Epoch: [469][300/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0169 (0.0262) Prec@1 97.000 (95.839) Prec@5 100.000 (99.871) +2022-11-14 17:07:48,499 Epoch: [469][310/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0124 (0.0258) Prec@1 99.000 (95.938) Prec@5 100.000 (99.875) +2022-11-14 17:07:48,785 Epoch: [469][320/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0216 (0.0256) Prec@1 97.000 (95.970) Prec@5 100.000 (99.879) +2022-11-14 17:07:49,069 Epoch: [469][330/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0353 (0.0259) Prec@1 94.000 (95.912) Prec@5 100.000 (99.882) +2022-11-14 17:07:49,353 Epoch: [469][340/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0231 (0.0259) Prec@1 97.000 (95.943) Prec@5 100.000 (99.886) +2022-11-14 17:07:49,640 Epoch: [469][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0380 (0.0262) Prec@1 92.000 (95.833) Prec@5 100.000 (99.889) +2022-11-14 17:07:49,927 Epoch: [469][360/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0180 (0.0260) Prec@1 97.000 (95.865) Prec@5 100.000 (99.892) +2022-11-14 17:07:50,211 Epoch: [469][370/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0296 (0.0261) Prec@1 96.000 (95.868) Prec@5 100.000 (99.895) +2022-11-14 17:07:50,495 Epoch: [469][380/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0289 (0.0261) Prec@1 94.000 (95.821) Prec@5 100.000 (99.897) +2022-11-14 17:07:50,777 Epoch: [469][390/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0288 (0.0262) Prec@1 95.000 (95.800) Prec@5 100.000 (99.900) +2022-11-14 17:07:51,061 Epoch: [469][400/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0398 (0.0265) Prec@1 95.000 (95.780) Prec@5 100.000 (99.902) +2022-11-14 17:07:51,350 Epoch: [469][410/500] Time 0.031 (0.023) Data 0.002 (0.002) Loss 0.0287 (0.0266) Prec@1 94.000 (95.738) Prec@5 100.000 (99.905) +2022-11-14 17:07:51,632 Epoch: [469][420/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0114 (0.0262) Prec@1 99.000 (95.814) Prec@5 100.000 (99.907) +2022-11-14 17:07:51,916 Epoch: [469][430/500] Time 0.031 (0.023) Data 0.002 (0.002) Loss 0.0133 (0.0259) Prec@1 97.000 (95.841) Prec@5 100.000 (99.909) +2022-11-14 17:07:52,200 Epoch: [469][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0414 (0.0263) Prec@1 93.000 (95.778) Prec@5 99.000 (99.889) +2022-11-14 17:07:52,479 Epoch: [469][450/500] Time 0.028 (0.023) Data 0.003 (0.002) Loss 0.0278 (0.0263) Prec@1 96.000 (95.783) Prec@5 100.000 (99.891) +2022-11-14 17:07:52,760 Epoch: [469][460/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0235 (0.0263) Prec@1 96.000 (95.787) Prec@5 100.000 (99.894) +2022-11-14 17:07:53,044 Epoch: [469][470/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0261 (0.0263) Prec@1 95.000 (95.771) Prec@5 100.000 (99.896) +2022-11-14 17:07:53,321 Epoch: [469][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0342 (0.0264) Prec@1 95.000 (95.755) Prec@5 100.000 (99.898) +2022-11-14 17:07:53,604 Epoch: [469][490/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0288 (0.0265) Prec@1 98.000 (95.800) Prec@5 100.000 (99.900) +2022-11-14 17:07:53,857 Epoch: [469][499/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0347 (0.0266) Prec@1 93.000 (95.745) Prec@5 100.000 (99.902) +2022-11-14 17:07:54,171 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0518 (0.0518) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:54,178 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0587) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:54,188 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0588) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:54,197 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0630 (0.0598) Prec@1 91.000 (91.000) Prec@5 98.000 (99.500) +2022-11-14 17:07:54,204 Test: [4/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0609) Prec@1 89.000 (90.600) Prec@5 100.000 (99.600) +2022-11-14 17:07:54,211 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0591) Prec@1 92.000 (90.833) Prec@5 100.000 (99.667) +2022-11-14 17:07:54,218 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0588) Prec@1 92.000 (91.000) Prec@5 100.000 (99.714) +2022-11-14 17:07:54,226 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0618) Prec@1 88.000 (90.625) Prec@5 100.000 (99.750) +2022-11-14 17:07:54,234 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0635) Prec@1 89.000 (90.444) Prec@5 99.000 (99.667) +2022-11-14 17:07:54,241 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0646) Prec@1 89.000 (90.300) Prec@5 99.000 (99.600) +2022-11-14 17:07:54,249 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0652) Prec@1 90.000 (90.273) Prec@5 100.000 (99.636) +2022-11-14 17:07:54,256 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0669) Prec@1 89.000 (90.167) Prec@5 100.000 (99.667) +2022-11-14 17:07:54,267 Test: [12/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0660) Prec@1 90.000 (90.154) Prec@5 100.000 (99.692) +2022-11-14 17:07:54,279 Test: [13/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0665) Prec@1 88.000 (90.000) Prec@5 99.000 (99.643) +2022-11-14 17:07:54,287 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0683) Prec@1 84.000 (89.600) Prec@5 100.000 (99.667) +2022-11-14 17:07:54,295 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0698) Prec@1 84.000 (89.250) Prec@5 99.000 (99.625) +2022-11-14 17:07:54,306 Test: [16/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0703) Prec@1 86.000 (89.059) Prec@5 99.000 (99.588) +2022-11-14 17:07:54,318 Test: [17/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.1037 (0.0721) Prec@1 83.000 (88.722) Prec@5 100.000 (99.611) +2022-11-14 17:07:54,328 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0729) Prec@1 86.000 (88.579) Prec@5 99.000 (99.579) +2022-11-14 17:07:54,336 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0929 (0.0739) Prec@1 85.000 (88.400) Prec@5 97.000 (99.450) +2022-11-14 17:07:54,347 Test: [20/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0740) Prec@1 87.000 (88.333) Prec@5 100.000 (99.476) +2022-11-14 17:07:54,357 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1004 (0.0752) Prec@1 85.000 (88.182) Prec@5 99.000 (99.455) +2022-11-14 17:07:54,365 Test: [22/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0972 (0.0761) Prec@1 87.000 (88.130) Prec@5 97.000 (99.348) +2022-11-14 17:07:54,374 Test: [23/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0754) Prec@1 91.000 (88.250) Prec@5 100.000 (99.375) +2022-11-14 17:07:54,384 Test: [24/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0756) Prec@1 84.000 (88.080) Prec@5 100.000 (99.400) +2022-11-14 17:07:54,394 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0757) Prec@1 88.000 (88.077) Prec@5 98.000 (99.346) +2022-11-14 17:07:54,402 Test: [26/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0414 (0.0744) Prec@1 94.000 (88.296) Prec@5 100.000 (99.370) +2022-11-14 17:07:54,409 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 88.000 (88.286) Prec@5 100.000 (99.393) +2022-11-14 17:07:54,419 Test: [28/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0745) Prec@1 89.000 (88.310) Prec@5 97.000 (99.310) +2022-11-14 17:07:54,430 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0748) Prec@1 86.000 (88.233) Prec@5 98.000 (99.267) +2022-11-14 17:07:54,438 Test: [30/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0745) Prec@1 90.000 (88.290) Prec@5 100.000 (99.290) +2022-11-14 17:07:54,445 Test: [31/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0538 (0.0738) Prec@1 93.000 (88.438) Prec@5 99.000 (99.281) +2022-11-14 17:07:54,453 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0736) Prec@1 89.000 (88.455) Prec@5 100.000 (99.303) +2022-11-14 17:07:54,460 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0740) Prec@1 84.000 (88.324) Prec@5 99.000 (99.294) +2022-11-14 17:07:54,468 Test: [34/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0747) Prec@1 85.000 (88.229) Prec@5 97.000 (99.229) +2022-11-14 17:07:54,475 Test: [35/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0745) Prec@1 91.000 (88.306) Prec@5 100.000 (99.250) +2022-11-14 17:07:54,483 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0745) Prec@1 89.000 (88.324) Prec@5 99.000 (99.243) +2022-11-14 17:07:54,490 Test: [37/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0967 (0.0751) Prec@1 86.000 (88.263) Prec@5 100.000 (99.263) +2022-11-14 17:07:54,498 Test: [38/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0744) Prec@1 93.000 (88.385) Prec@5 99.000 (99.256) +2022-11-14 17:07:54,505 Test: [39/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0743) Prec@1 90.000 (88.425) Prec@5 99.000 (99.250) +2022-11-14 17:07:54,513 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0991 (0.0749) Prec@1 87.000 (88.390) Prec@5 98.000 (99.220) +2022-11-14 17:07:54,520 Test: [41/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0750) Prec@1 88.000 (88.381) Prec@5 100.000 (99.238) +2022-11-14 17:07:54,528 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0564 (0.0746) Prec@1 92.000 (88.465) Prec@5 99.000 (99.233) +2022-11-14 17:07:54,536 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0747) Prec@1 88.000 (88.455) Prec@5 97.000 (99.182) +2022-11-14 17:07:54,543 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0742) Prec@1 92.000 (88.533) Prec@5 100.000 (99.200) +2022-11-14 17:07:54,551 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1050 (0.0749) Prec@1 84.000 (88.435) Prec@5 98.000 (99.174) +2022-11-14 17:07:54,558 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0748) Prec@1 86.000 (88.383) Prec@5 99.000 (99.170) +2022-11-14 17:07:54,566 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0752) Prec@1 85.000 (88.312) Prec@5 98.000 (99.146) +2022-11-14 17:07:54,573 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0404 (0.0745) Prec@1 93.000 (88.408) Prec@5 100.000 (99.163) +2022-11-14 17:07:54,581 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0753) Prec@1 85.000 (88.340) Prec@5 100.000 (99.180) +2022-11-14 17:07:54,589 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0751) Prec@1 90.000 (88.373) Prec@5 100.000 (99.196) +2022-11-14 17:07:54,596 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0753) Prec@1 84.000 (88.288) Prec@5 100.000 (99.212) +2022-11-14 17:07:54,604 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0755) Prec@1 87.000 (88.264) Prec@5 100.000 (99.226) +2022-11-14 17:07:54,611 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0753) Prec@1 90.000 (88.296) Prec@5 100.000 (99.241) +2022-11-14 17:07:54,619 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0753) Prec@1 87.000 (88.273) Prec@5 99.000 (99.236) +2022-11-14 17:07:54,626 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0752) Prec@1 88.000 (88.268) Prec@5 99.000 (99.232) +2022-11-14 17:07:54,634 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0749) Prec@1 90.000 (88.298) Prec@5 100.000 (99.246) +2022-11-14 17:07:54,641 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0748) Prec@1 90.000 (88.328) Prec@5 99.000 (99.241) +2022-11-14 17:07:54,649 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.0754) Prec@1 83.000 (88.237) Prec@5 100.000 (99.254) +2022-11-14 17:07:54,656 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0752) Prec@1 86.000 (88.200) Prec@5 100.000 (99.267) +2022-11-14 17:07:54,664 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0754) Prec@1 87.000 (88.180) Prec@5 100.000 (99.279) +2022-11-14 17:07:54,671 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0756) Prec@1 84.000 (88.113) Prec@5 100.000 (99.290) +2022-11-14 17:07:54,679 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0754) Prec@1 90.000 (88.143) Prec@5 100.000 (99.302) +2022-11-14 17:07:54,686 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0392 (0.0749) Prec@1 94.000 (88.234) Prec@5 100.000 (99.312) +2022-11-14 17:07:54,694 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0749) Prec@1 88.000 (88.231) Prec@5 99.000 (99.308) +2022-11-14 17:07:54,701 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0750) Prec@1 87.000 (88.212) Prec@5 99.000 (99.303) +2022-11-14 17:07:54,709 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0437 (0.0745) Prec@1 94.000 (88.299) Prec@5 100.000 (99.313) +2022-11-14 17:07:54,717 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0744) Prec@1 90.000 (88.324) Prec@5 99.000 (99.309) +2022-11-14 17:07:54,724 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0743) Prec@1 88.000 (88.319) Prec@5 99.000 (99.304) +2022-11-14 17:07:54,732 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0899 (0.0746) Prec@1 84.000 (88.257) Prec@5 100.000 (99.314) +2022-11-14 17:07:54,740 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0748) Prec@1 86.000 (88.225) Prec@5 99.000 (99.310) +2022-11-14 17:07:54,747 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0746) Prec@1 88.000 (88.222) Prec@5 100.000 (99.319) +2022-11-14 17:07:54,755 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0745) Prec@1 90.000 (88.247) Prec@5 99.000 (99.315) +2022-11-14 17:07:54,762 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0741) Prec@1 92.000 (88.297) Prec@5 100.000 (99.324) +2022-11-14 17:07:54,770 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0744) Prec@1 83.000 (88.227) Prec@5 100.000 (99.333) +2022-11-14 17:07:54,778 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0741) Prec@1 93.000 (88.289) Prec@5 99.000 (99.329) +2022-11-14 17:07:54,786 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 88.000 (88.286) Prec@5 98.000 (99.312) +2022-11-14 17:07:54,793 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0744) Prec@1 85.000 (88.244) Prec@5 99.000 (99.308) +2022-11-14 17:07:54,801 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0746) Prec@1 85.000 (88.203) Prec@5 100.000 (99.316) +2022-11-14 17:07:54,808 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0744) Prec@1 90.000 (88.225) Prec@5 99.000 (99.312) +2022-11-14 17:07:54,816 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0744) Prec@1 89.000 (88.235) Prec@5 100.000 (99.321) +2022-11-14 17:07:54,823 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0746) Prec@1 84.000 (88.183) Prec@5 99.000 (99.317) +2022-11-14 17:07:54,831 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0749) Prec@1 86.000 (88.157) Prec@5 99.000 (99.313) +2022-11-14 17:07:54,839 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0749) Prec@1 86.000 (88.131) Prec@5 99.000 (99.310) +2022-11-14 17:07:54,846 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0751) Prec@1 85.000 (88.094) Prec@5 99.000 (99.306) +2022-11-14 17:07:54,854 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0752) Prec@1 87.000 (88.081) Prec@5 100.000 (99.314) +2022-11-14 17:07:54,861 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0754) Prec@1 88.000 (88.080) Prec@5 99.000 (99.310) +2022-11-14 17:07:54,869 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0896 (0.0755) Prec@1 86.000 (88.057) Prec@5 99.000 (99.307) +2022-11-14 17:07:54,876 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0756) Prec@1 86.000 (88.034) Prec@5 99.000 (99.303) +2022-11-14 17:07:54,884 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0757) Prec@1 86.000 (88.011) Prec@5 99.000 (99.300) +2022-11-14 17:07:54,891 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0756) Prec@1 91.000 (88.044) Prec@5 100.000 (99.308) +2022-11-14 17:07:54,899 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0753) Prec@1 94.000 (88.109) Prec@5 100.000 (99.315) +2022-11-14 17:07:54,906 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0753) Prec@1 89.000 (88.118) Prec@5 99.000 (99.312) +2022-11-14 17:07:54,914 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0753) Prec@1 87.000 (88.106) Prec@5 99.000 (99.309) +2022-11-14 17:07:54,921 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0753) Prec@1 89.000 (88.116) Prec@5 100.000 (99.316) +2022-11-14 17:07:54,929 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0753) Prec@1 90.000 (88.135) Prec@5 99.000 (99.312) +2022-11-14 17:07:54,936 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0751) Prec@1 89.000 (88.144) Prec@5 98.000 (99.299) +2022-11-14 17:07:54,944 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1050 (0.0754) Prec@1 85.000 (88.112) Prec@5 98.000 (99.286) +2022-11-14 17:07:54,951 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0756) Prec@1 87.000 (88.101) Prec@5 100.000 (99.293) +2022-11-14 17:07:54,958 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0755) Prec@1 88.000 (88.100) Prec@5 100.000 (99.300) +2022-11-14 17:07:55,022 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:07:55,333 Epoch: [470][0/500] Time 0.025 (0.025) Data 0.231 (0.231) Loss 0.0226 (0.0226) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:07:55,532 Epoch: [470][10/500] Time 0.020 (0.018) Data 0.001 (0.022) Loss 0.0104 (0.0165) Prec@1 99.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 17:07:55,723 Epoch: [470][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0541 (0.0290) Prec@1 91.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:07:55,915 Epoch: [470][30/500] Time 0.020 (0.017) Data 0.001 (0.009) Loss 0.0215 (0.0271) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:07:56,108 Epoch: [470][40/500] Time 0.020 (0.017) Data 0.002 (0.007) Loss 0.0414 (0.0300) Prec@1 94.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 17:07:56,301 Epoch: [470][50/500] Time 0.018 (0.017) Data 0.002 (0.006) Loss 0.0424 (0.0320) Prec@1 92.000 (94.500) Prec@5 100.000 (99.833) +2022-11-14 17:07:56,499 Epoch: [470][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0225 (0.0307) Prec@1 95.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 17:07:56,691 Epoch: [470][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0134 (0.0285) Prec@1 98.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:07:56,885 Epoch: [470][80/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0202 (0.0276) Prec@1 97.000 (95.222) Prec@5 100.000 (99.889) +2022-11-14 17:07:57,093 Epoch: [470][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0219 (0.0270) Prec@1 97.000 (95.400) Prec@5 100.000 (99.900) +2022-11-14 17:07:57,290 Epoch: [470][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0205 (0.0264) Prec@1 96.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:07:57,483 Epoch: [470][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0174 (0.0257) Prec@1 98.000 (95.667) Prec@5 100.000 (99.917) +2022-11-14 17:07:57,676 Epoch: [470][120/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0250 (0.0256) Prec@1 96.000 (95.692) Prec@5 100.000 (99.923) +2022-11-14 17:07:57,869 Epoch: [470][130/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0494 (0.0273) Prec@1 90.000 (95.286) Prec@5 100.000 (99.929) +2022-11-14 17:07:58,054 Epoch: [470][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0276 (0.0274) Prec@1 95.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 17:07:58,299 Epoch: [470][150/500] Time 0.026 (0.017) Data 0.001 (0.003) Loss 0.0185 (0.0268) Prec@1 97.000 (95.375) Prec@5 100.000 (99.938) +2022-11-14 17:07:58,572 Epoch: [470][160/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0269 (0.0268) Prec@1 96.000 (95.412) Prec@5 99.000 (99.882) +2022-11-14 17:07:58,842 Epoch: [470][170/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0431 (0.0277) Prec@1 94.000 (95.333) Prec@5 99.000 (99.833) +2022-11-14 17:07:59,118 Epoch: [470][180/500] Time 0.030 (0.019) Data 0.001 (0.003) Loss 0.0140 (0.0270) Prec@1 98.000 (95.474) Prec@5 100.000 (99.842) +2022-11-14 17:07:59,388 Epoch: [470][190/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0461 (0.0279) Prec@1 93.000 (95.350) Prec@5 100.000 (99.850) +2022-11-14 17:07:59,662 Epoch: [470][200/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0195 (0.0275) Prec@1 98.000 (95.476) Prec@5 100.000 (99.857) +2022-11-14 17:07:59,936 Epoch: [470][210/500] Time 0.027 (0.019) Data 0.001 (0.003) Loss 0.0368 (0.0280) Prec@1 94.000 (95.409) Prec@5 100.000 (99.864) +2022-11-14 17:08:00,214 Epoch: [470][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0303 (0.0281) Prec@1 95.000 (95.391) Prec@5 100.000 (99.870) +2022-11-14 17:08:00,486 Epoch: [470][230/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0067 (0.0272) Prec@1 100.000 (95.583) Prec@5 100.000 (99.875) +2022-11-14 17:08:00,760 Epoch: [470][240/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0182 (0.0268) Prec@1 96.000 (95.600) Prec@5 100.000 (99.880) +2022-11-14 17:08:01,037 Epoch: [470][250/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0262 (0.0268) Prec@1 96.000 (95.615) Prec@5 100.000 (99.885) +2022-11-14 17:08:01,314 Epoch: [470][260/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0157 (0.0264) Prec@1 96.000 (95.630) Prec@5 100.000 (99.889) +2022-11-14 17:08:01,587 Epoch: [470][270/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0578 (0.0275) Prec@1 90.000 (95.429) Prec@5 100.000 (99.893) +2022-11-14 17:08:01,864 Epoch: [470][280/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0348 (0.0278) Prec@1 94.000 (95.379) Prec@5 100.000 (99.897) +2022-11-14 17:08:02,136 Epoch: [470][290/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0224 (0.0276) Prec@1 97.000 (95.433) Prec@5 100.000 (99.900) +2022-11-14 17:08:02,407 Epoch: [470][300/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0280 (0.0276) Prec@1 96.000 (95.452) Prec@5 100.000 (99.903) +2022-11-14 17:08:02,682 Epoch: [470][310/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0238 (0.0275) Prec@1 97.000 (95.500) Prec@5 100.000 (99.906) +2022-11-14 17:08:02,954 Epoch: [470][320/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0333 (0.0276) Prec@1 93.000 (95.424) Prec@5 100.000 (99.909) +2022-11-14 17:08:03,230 Epoch: [470][330/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0144 (0.0273) Prec@1 97.000 (95.471) Prec@5 100.000 (99.912) +2022-11-14 17:08:03,500 Epoch: [470][340/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0229 (0.0271) Prec@1 95.000 (95.457) Prec@5 100.000 (99.914) +2022-11-14 17:08:03,774 Epoch: [470][350/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0392 (0.0275) Prec@1 94.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 17:08:04,050 Epoch: [470][360/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0159 (0.0272) Prec@1 98.000 (95.486) Prec@5 100.000 (99.919) +2022-11-14 17:08:04,323 Epoch: [470][370/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0249 (0.0271) Prec@1 96.000 (95.500) Prec@5 100.000 (99.921) +2022-11-14 17:08:04,591 Epoch: [470][380/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0180 (0.0269) Prec@1 97.000 (95.538) Prec@5 100.000 (99.923) +2022-11-14 17:08:04,861 Epoch: [470][390/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0641 (0.0278) Prec@1 90.000 (95.400) Prec@5 100.000 (99.925) +2022-11-14 17:08:05,136 Epoch: [470][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0482 (0.0283) Prec@1 93.000 (95.341) Prec@5 99.000 (99.902) +2022-11-14 17:08:05,406 Epoch: [470][410/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0471 (0.0287) Prec@1 93.000 (95.286) Prec@5 100.000 (99.905) +2022-11-14 17:08:05,678 Epoch: [470][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0307 (0.0288) Prec@1 93.000 (95.233) Prec@5 100.000 (99.907) +2022-11-14 17:08:05,950 Epoch: [470][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0293 (0.0288) Prec@1 94.000 (95.205) Prec@5 100.000 (99.909) +2022-11-14 17:08:06,226 Epoch: [470][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0334 (0.0289) Prec@1 95.000 (95.200) Prec@5 100.000 (99.911) +2022-11-14 17:08:06,501 Epoch: [470][450/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0467 (0.0293) Prec@1 93.000 (95.152) Prec@5 100.000 (99.913) +2022-11-14 17:08:06,772 Epoch: [470][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0260 (0.0292) Prec@1 95.000 (95.149) Prec@5 100.000 (99.915) +2022-11-14 17:08:07,046 Epoch: [470][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0253 (0.0291) Prec@1 95.000 (95.146) Prec@5 100.000 (99.917) +2022-11-14 17:08:07,319 Epoch: [470][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0329 (0.0292) Prec@1 96.000 (95.163) Prec@5 100.000 (99.918) +2022-11-14 17:08:07,593 Epoch: [470][490/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0275 (0.0292) Prec@1 95.000 (95.160) Prec@5 100.000 (99.920) +2022-11-14 17:08:07,839 Epoch: [470][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0290 (0.0292) Prec@1 95.000 (95.157) Prec@5 100.000 (99.922) +2022-11-14 17:08:08,167 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0378 (0.0378) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:08,174 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0753 (0.0565) Prec@1 88.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 17:08:08,181 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0610) Prec@1 90.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:08,191 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0669 (0.0625) Prec@1 90.000 (90.750) Prec@5 98.000 (99.500) +2022-11-14 17:08:08,198 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0633 (0.0627) Prec@1 91.000 (90.800) Prec@5 100.000 (99.600) +2022-11-14 17:08:08,205 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0385 (0.0586) Prec@1 94.000 (91.333) Prec@5 100.000 (99.667) +2022-11-14 17:08:08,212 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0608 (0.0590) Prec@1 91.000 (91.286) Prec@5 100.000 (99.714) +2022-11-14 17:08:08,221 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1030 (0.0645) Prec@1 81.000 (90.000) Prec@5 98.000 (99.500) +2022-11-14 17:08:08,228 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0653) Prec@1 91.000 (90.111) Prec@5 99.000 (99.444) +2022-11-14 17:08:08,235 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0668) Prec@1 87.000 (89.800) Prec@5 98.000 (99.300) +2022-11-14 17:08:08,243 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0664) Prec@1 91.000 (89.909) Prec@5 100.000 (99.364) +2022-11-14 17:08:08,251 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0669) Prec@1 90.000 (89.917) Prec@5 100.000 (99.417) +2022-11-14 17:08:08,259 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0670) Prec@1 90.000 (89.923) Prec@5 100.000 (99.462) +2022-11-14 17:08:08,267 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0673) Prec@1 88.000 (89.786) Prec@5 99.000 (99.429) +2022-11-14 17:08:08,274 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0678) Prec@1 88.000 (89.667) Prec@5 99.000 (99.400) +2022-11-14 17:08:08,282 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0685) Prec@1 86.000 (89.438) Prec@5 99.000 (99.375) +2022-11-14 17:08:08,290 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0680) Prec@1 93.000 (89.647) Prec@5 99.000 (99.353) +2022-11-14 17:08:08,298 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0695) Prec@1 84.000 (89.333) Prec@5 100.000 (99.389) +2022-11-14 17:08:08,305 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0691) Prec@1 89.000 (89.316) Prec@5 99.000 (99.368) +2022-11-14 17:08:08,313 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0703) Prec@1 86.000 (89.150) Prec@5 97.000 (99.250) +2022-11-14 17:08:08,321 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0695) Prec@1 92.000 (89.286) Prec@5 100.000 (99.286) +2022-11-14 17:08:08,329 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0700) Prec@1 90.000 (89.318) Prec@5 98.000 (99.227) +2022-11-14 17:08:08,336 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0976 (0.0712) Prec@1 86.000 (89.174) Prec@5 98.000 (99.174) +2022-11-14 17:08:08,344 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0708) Prec@1 90.000 (89.208) Prec@5 100.000 (99.208) +2022-11-14 17:08:08,352 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0717) Prec@1 84.000 (89.000) Prec@5 100.000 (99.240) +2022-11-14 17:08:08,360 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0719) Prec@1 88.000 (88.962) Prec@5 99.000 (99.231) +2022-11-14 17:08:08,367 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0504 (0.0711) Prec@1 92.000 (89.074) Prec@5 100.000 (99.259) +2022-11-14 17:08:08,375 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0711) Prec@1 89.000 (89.071) Prec@5 100.000 (99.286) +2022-11-14 17:08:08,382 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0708) Prec@1 90.000 (89.103) Prec@5 98.000 (99.241) +2022-11-14 17:08:08,390 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0705) Prec@1 90.000 (89.133) Prec@5 100.000 (99.267) +2022-11-14 17:08:08,397 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0708) Prec@1 86.000 (89.032) Prec@5 100.000 (99.290) +2022-11-14 17:08:08,405 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0708) Prec@1 88.000 (89.000) Prec@5 99.000 (99.281) +2022-11-14 17:08:08,412 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0707) Prec@1 89.000 (89.000) Prec@5 100.000 (99.303) +2022-11-14 17:08:08,420 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0715) Prec@1 83.000 (88.824) Prec@5 100.000 (99.324) +2022-11-14 17:08:08,427 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0717) Prec@1 89.000 (88.829) Prec@5 98.000 (99.286) +2022-11-14 17:08:08,435 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0715) Prec@1 91.000 (88.889) Prec@5 99.000 (99.278) +2022-11-14 17:08:08,443 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0714) Prec@1 90.000 (88.919) Prec@5 99.000 (99.270) +2022-11-14 17:08:08,450 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0723) Prec@1 84.000 (88.789) Prec@5 100.000 (99.289) +2022-11-14 17:08:08,458 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0717) Prec@1 94.000 (88.923) Prec@5 100.000 (99.308) +2022-11-14 17:08:08,466 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0716) Prec@1 90.000 (88.950) Prec@5 100.000 (99.325) +2022-11-14 17:08:08,474 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1089 (0.0725) Prec@1 84.000 (88.829) Prec@5 97.000 (99.268) +2022-11-14 17:08:08,482 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0728) Prec@1 87.000 (88.786) Prec@5 100.000 (99.286) +2022-11-14 17:08:08,490 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0499 (0.0722) Prec@1 91.000 (88.837) Prec@5 99.000 (99.279) +2022-11-14 17:08:08,498 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0721) Prec@1 91.000 (88.886) Prec@5 98.000 (99.250) +2022-11-14 17:08:08,506 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0717) Prec@1 93.000 (88.978) Prec@5 100.000 (99.267) +2022-11-14 17:08:08,513 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0723) Prec@1 83.000 (88.848) Prec@5 99.000 (99.261) +2022-11-14 17:08:08,521 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0725) Prec@1 86.000 (88.787) Prec@5 99.000 (99.255) +2022-11-14 17:08:08,529 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1112 (0.0733) Prec@1 82.000 (88.646) Prec@5 99.000 (99.250) +2022-11-14 17:08:08,537 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0731) Prec@1 89.000 (88.653) Prec@5 100.000 (99.265) +2022-11-14 17:08:08,545 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1053 (0.0738) Prec@1 85.000 (88.580) Prec@5 100.000 (99.280) +2022-11-14 17:08:08,553 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0737) Prec@1 89.000 (88.588) Prec@5 98.000 (99.255) +2022-11-14 17:08:08,560 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0740) Prec@1 85.000 (88.519) Prec@5 99.000 (99.250) +2022-11-14 17:08:08,568 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0737) Prec@1 88.000 (88.509) Prec@5 99.000 (99.245) +2022-11-14 17:08:08,576 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0738) Prec@1 88.000 (88.500) Prec@5 99.000 (99.241) +2022-11-14 17:08:08,584 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0738) Prec@1 89.000 (88.509) Prec@5 100.000 (99.255) +2022-11-14 17:08:08,592 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0734) Prec@1 94.000 (88.607) Prec@5 99.000 (99.250) +2022-11-14 17:08:08,600 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0734) Prec@1 87.000 (88.579) Prec@5 100.000 (99.263) +2022-11-14 17:08:08,607 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0731) Prec@1 90.000 (88.603) Prec@5 98.000 (99.241) +2022-11-14 17:08:08,615 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0736) Prec@1 87.000 (88.576) Prec@5 100.000 (99.254) +2022-11-14 17:08:08,623 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0735) Prec@1 86.000 (88.533) Prec@5 100.000 (99.267) +2022-11-14 17:08:08,630 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0733) Prec@1 92.000 (88.590) Prec@5 99.000 (99.262) +2022-11-14 17:08:08,638 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0731) Prec@1 93.000 (88.661) Prec@5 99.000 (99.258) +2022-11-14 17:08:08,645 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0729) Prec@1 90.000 (88.683) Prec@5 100.000 (99.270) +2022-11-14 17:08:08,653 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0374 (0.0724) Prec@1 94.000 (88.766) Prec@5 100.000 (99.281) +2022-11-14 17:08:08,662 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0724) Prec@1 86.000 (88.723) Prec@5 100.000 (99.292) +2022-11-14 17:08:08,669 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0725) Prec@1 86.000 (88.682) Prec@5 99.000 (99.288) +2022-11-14 17:08:08,677 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0435 (0.0721) Prec@1 93.000 (88.746) Prec@5 100.000 (99.299) +2022-11-14 17:08:08,685 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0721) Prec@1 90.000 (88.765) Prec@5 99.000 (99.294) +2022-11-14 17:08:08,693 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0721) Prec@1 89.000 (88.768) Prec@5 98.000 (99.275) +2022-11-14 17:08:08,701 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0725) Prec@1 85.000 (88.714) Prec@5 98.000 (99.257) +2022-11-14 17:08:08,708 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1017 (0.0729) Prec@1 86.000 (88.676) Prec@5 97.000 (99.225) +2022-11-14 17:08:08,716 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0728) Prec@1 89.000 (88.681) Prec@5 100.000 (99.236) +2022-11-14 17:08:08,724 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0367 (0.0723) Prec@1 93.000 (88.740) Prec@5 100.000 (99.247) +2022-11-14 17:08:08,732 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0720) Prec@1 94.000 (88.811) Prec@5 100.000 (99.257) +2022-11-14 17:08:08,739 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1155 (0.0726) Prec@1 82.000 (88.720) Prec@5 99.000 (99.253) +2022-11-14 17:08:08,747 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0723) Prec@1 91.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 17:08:08,754 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0723) Prec@1 89.000 (88.753) Prec@5 99.000 (99.247) +2022-11-14 17:08:08,762 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0725) Prec@1 88.000 (88.744) Prec@5 98.000 (99.231) +2022-11-14 17:08:08,769 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0726) Prec@1 88.000 (88.734) Prec@5 100.000 (99.241) +2022-11-14 17:08:08,777 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0725) Prec@1 88.000 (88.725) Prec@5 100.000 (99.250) +2022-11-14 17:08:08,785 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0729) Prec@1 85.000 (88.679) Prec@5 98.000 (99.235) +2022-11-14 17:08:08,793 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0729) Prec@1 90.000 (88.695) Prec@5 99.000 (99.232) +2022-11-14 17:08:08,800 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0731) Prec@1 86.000 (88.663) Prec@5 98.000 (99.217) +2022-11-14 17:08:08,808 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0729) Prec@1 90.000 (88.679) Prec@5 99.000 (99.214) +2022-11-14 17:08:08,816 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0731) Prec@1 83.000 (88.612) Prec@5 100.000 (99.224) +2022-11-14 17:08:08,823 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1035 (0.0735) Prec@1 85.000 (88.570) Prec@5 100.000 (99.233) +2022-11-14 17:08:08,831 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0735) Prec@1 86.000 (88.540) Prec@5 98.000 (99.218) +2022-11-14 17:08:08,839 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0735) Prec@1 88.000 (88.534) Prec@5 99.000 (99.216) +2022-11-14 17:08:08,846 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0735) Prec@1 87.000 (88.517) Prec@5 100.000 (99.225) +2022-11-14 17:08:08,854 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0737) Prec@1 87.000 (88.500) Prec@5 98.000 (99.211) +2022-11-14 17:08:08,861 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0734) Prec@1 92.000 (88.538) Prec@5 100.000 (99.220) +2022-11-14 17:08:08,869 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0732) Prec@1 90.000 (88.554) Prec@5 100.000 (99.228) +2022-11-14 17:08:08,877 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0733) Prec@1 88.000 (88.548) Prec@5 100.000 (99.237) +2022-11-14 17:08:08,884 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0846 (0.0734) Prec@1 86.000 (88.521) Prec@5 99.000 (99.234) +2022-11-14 17:08:08,891 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0735) Prec@1 85.000 (88.484) Prec@5 98.000 (99.221) +2022-11-14 17:08:08,899 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0733) Prec@1 90.000 (88.500) Prec@5 99.000 (99.219) +2022-11-14 17:08:08,906 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0732) Prec@1 91.000 (88.526) Prec@5 98.000 (99.206) +2022-11-14 17:08:08,914 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0734) Prec@1 87.000 (88.510) Prec@5 98.000 (99.194) +2022-11-14 17:08:08,921 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0736) Prec@1 85.000 (88.475) Prec@5 99.000 (99.192) +2022-11-14 17:08:08,928 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0736) Prec@1 88.000 (88.470) Prec@5 99.000 (99.190) +2022-11-14 17:08:08,982 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:08:09,313 Epoch: [471][0/500] Time 0.032 (0.032) Data 0.245 (0.245) Loss 0.0166 (0.0166) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:09,534 Epoch: [471][10/500] Time 0.016 (0.021) Data 0.002 (0.024) Loss 0.0383 (0.0275) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:08:09,737 Epoch: [471][20/500] Time 0.016 (0.019) Data 0.002 (0.013) Loss 0.0321 (0.0290) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:09,934 Epoch: [471][30/500] Time 0.019 (0.019) Data 0.001 (0.010) Loss 0.0215 (0.0271) Prec@1 96.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:08:10,131 Epoch: [471][40/500] Time 0.017 (0.018) Data 0.002 (0.008) Loss 0.0331 (0.0283) Prec@1 95.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:08:10,326 Epoch: [471][50/500] Time 0.017 (0.018) Data 0.002 (0.007) Loss 0.0253 (0.0278) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:08:10,522 Epoch: [471][60/500] Time 0.018 (0.018) Data 0.001 (0.006) Loss 0.0305 (0.0282) Prec@1 96.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:08:10,720 Epoch: [471][70/500] Time 0.019 (0.018) Data 0.002 (0.005) Loss 0.0349 (0.0290) Prec@1 95.000 (95.375) Prec@5 100.000 (100.000) +2022-11-14 17:08:10,916 Epoch: [471][80/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0312 (0.0293) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:08:11,114 Epoch: [471][90/500] Time 0.021 (0.018) Data 0.002 (0.004) Loss 0.0406 (0.0304) Prec@1 94.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:08:11,314 Epoch: [471][100/500] Time 0.018 (0.018) Data 0.002 (0.004) Loss 0.0508 (0.0323) Prec@1 91.000 (94.818) Prec@5 100.000 (100.000) +2022-11-14 17:08:11,509 Epoch: [471][110/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0167 (0.0310) Prec@1 98.000 (95.083) Prec@5 100.000 (100.000) +2022-11-14 17:08:11,702 Epoch: [471][120/500] Time 0.018 (0.018) Data 0.001 (0.004) Loss 0.0132 (0.0296) Prec@1 98.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 17:08:11,897 Epoch: [471][130/500] Time 0.017 (0.018) Data 0.002 (0.004) Loss 0.0445 (0.0307) Prec@1 92.000 (95.071) Prec@5 100.000 (100.000) +2022-11-14 17:08:12,093 Epoch: [471][140/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.0511 (0.0320) Prec@1 90.000 (94.733) Prec@5 100.000 (100.000) +2022-11-14 17:08:12,288 Epoch: [471][150/500] Time 0.018 (0.018) Data 0.001 (0.003) Loss 0.0430 (0.0327) Prec@1 93.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 17:08:12,501 Epoch: [471][160/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0504 (0.0337) Prec@1 90.000 (94.353) Prec@5 100.000 (100.000) +2022-11-14 17:08:12,782 Epoch: [471][170/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0459 (0.0344) Prec@1 92.000 (94.222) Prec@5 100.000 (100.000) +2022-11-14 17:08:13,066 Epoch: [471][180/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0445 (0.0350) Prec@1 93.000 (94.158) Prec@5 100.000 (100.000) +2022-11-14 17:08:13,354 Epoch: [471][190/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0311 (0.0348) Prec@1 96.000 (94.250) Prec@5 99.000 (99.950) +2022-11-14 17:08:13,635 Epoch: [471][200/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0222 (0.0342) Prec@1 98.000 (94.429) Prec@5 100.000 (99.952) +2022-11-14 17:08:13,903 Epoch: [471][210/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0308 (0.0340) Prec@1 95.000 (94.455) Prec@5 100.000 (99.955) +2022-11-14 17:08:14,182 Epoch: [471][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0300 (0.0338) Prec@1 96.000 (94.522) Prec@5 100.000 (99.957) +2022-11-14 17:08:14,460 Epoch: [471][230/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0487 (0.0345) Prec@1 93.000 (94.458) Prec@5 100.000 (99.958) +2022-11-14 17:08:14,737 Epoch: [471][240/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0489 (0.0350) Prec@1 93.000 (94.400) Prec@5 100.000 (99.960) +2022-11-14 17:08:15,018 Epoch: [471][250/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0388 (0.0352) Prec@1 93.000 (94.346) Prec@5 100.000 (99.962) +2022-11-14 17:08:15,301 Epoch: [471][260/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0339 (0.0351) Prec@1 94.000 (94.333) Prec@5 100.000 (99.963) +2022-11-14 17:08:15,582 Epoch: [471][270/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0265 (0.0348) Prec@1 95.000 (94.357) Prec@5 100.000 (99.964) +2022-11-14 17:08:15,859 Epoch: [471][280/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0361 (0.0349) Prec@1 93.000 (94.310) Prec@5 100.000 (99.966) +2022-11-14 17:08:16,133 Epoch: [471][290/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0293 (0.0347) Prec@1 96.000 (94.367) Prec@5 100.000 (99.967) +2022-11-14 17:08:16,406 Epoch: [471][300/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0181 (0.0341) Prec@1 97.000 (94.452) Prec@5 100.000 (99.968) +2022-11-14 17:08:16,680 Epoch: [471][310/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0248 (0.0339) Prec@1 97.000 (94.531) Prec@5 100.000 (99.969) +2022-11-14 17:08:16,956 Epoch: [471][320/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0343 (0.0339) Prec@1 95.000 (94.545) Prec@5 100.000 (99.970) +2022-11-14 17:08:17,231 Epoch: [471][330/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0216 (0.0335) Prec@1 96.000 (94.588) Prec@5 100.000 (99.971) +2022-11-14 17:08:17,508 Epoch: [471][340/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0203 (0.0331) Prec@1 96.000 (94.629) Prec@5 100.000 (99.971) +2022-11-14 17:08:17,784 Epoch: [471][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0317 (0.0331) Prec@1 95.000 (94.639) Prec@5 100.000 (99.972) +2022-11-14 17:08:18,058 Epoch: [471][360/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0061 (0.0324) Prec@1 99.000 (94.757) Prec@5 100.000 (99.973) +2022-11-14 17:08:18,329 Epoch: [471][370/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0294 (0.0323) Prec@1 96.000 (94.789) Prec@5 100.000 (99.974) +2022-11-14 17:08:18,603 Epoch: [471][380/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0234 (0.0321) Prec@1 97.000 (94.846) Prec@5 100.000 (99.974) +2022-11-14 17:08:18,877 Epoch: [471][390/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0065 (0.0314) Prec@1 99.000 (94.950) Prec@5 100.000 (99.975) +2022-11-14 17:08:19,146 Epoch: [471][400/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0378 (0.0316) Prec@1 95.000 (94.951) Prec@5 100.000 (99.976) +2022-11-14 17:08:19,415 Epoch: [471][410/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0223 (0.0313) Prec@1 96.000 (94.976) Prec@5 100.000 (99.976) +2022-11-14 17:08:19,688 Epoch: [471][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0268 (0.0312) Prec@1 97.000 (95.023) Prec@5 100.000 (99.977) +2022-11-14 17:08:19,966 Epoch: [471][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0231 (0.0311) Prec@1 96.000 (95.045) Prec@5 100.000 (99.977) +2022-11-14 17:08:20,241 Epoch: [471][440/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0466 (0.0314) Prec@1 92.000 (94.978) Prec@5 100.000 (99.978) +2022-11-14 17:08:20,515 Epoch: [471][450/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0374 (0.0315) Prec@1 94.000 (94.957) Prec@5 99.000 (99.957) +2022-11-14 17:08:20,787 Epoch: [471][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0118 (0.0311) Prec@1 99.000 (95.043) Prec@5 100.000 (99.957) +2022-11-14 17:08:21,061 Epoch: [471][470/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0302 (0.0311) Prec@1 95.000 (95.042) Prec@5 99.000 (99.938) +2022-11-14 17:08:21,331 Epoch: [471][480/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0331 (0.0311) Prec@1 96.000 (95.061) Prec@5 100.000 (99.939) +2022-11-14 17:08:21,603 Epoch: [471][490/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0324 (0.0312) Prec@1 95.000 (95.060) Prec@5 99.000 (99.920) +2022-11-14 17:08:21,848 Epoch: [471][499/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0215 (0.0310) Prec@1 97.000 (95.098) Prec@5 100.000 (99.922) +2022-11-14 17:08:22,174 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0853 (0.0853) Prec@1 85.000 (85.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:22,182 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0611 (0.0732) Prec@1 91.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:22,194 Test: [2/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0903 (0.0789) Prec@1 83.000 (86.333) Prec@5 100.000 (100.000) +2022-11-14 17:08:22,205 Test: [3/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0653 (0.0755) Prec@1 90.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 17:08:22,212 Test: [4/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0689 (0.0742) Prec@1 88.000 (87.400) Prec@5 99.000 (99.600) +2022-11-14 17:08:22,222 Test: [5/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0430 (0.0690) Prec@1 92.000 (88.167) Prec@5 100.000 (99.667) +2022-11-14 17:08:22,231 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0648 (0.0684) Prec@1 90.000 (88.429) Prec@5 100.000 (99.714) +2022-11-14 17:08:22,240 Test: [7/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0834 (0.0703) Prec@1 84.000 (87.875) Prec@5 99.000 (99.625) +2022-11-14 17:08:22,247 Test: [8/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0734 (0.0706) Prec@1 88.000 (87.889) Prec@5 99.000 (99.556) +2022-11-14 17:08:22,254 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0902 (0.0726) Prec@1 85.000 (87.600) Prec@5 99.000 (99.500) +2022-11-14 17:08:22,262 Test: [10/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0705) Prec@1 94.000 (88.182) Prec@5 100.000 (99.545) +2022-11-14 17:08:22,270 Test: [11/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0665 (0.0701) Prec@1 90.000 (88.333) Prec@5 100.000 (99.583) +2022-11-14 17:08:22,277 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0532 (0.0688) Prec@1 92.000 (88.615) Prec@5 100.000 (99.615) +2022-11-14 17:08:22,285 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0692) Prec@1 88.000 (88.571) Prec@5 100.000 (99.643) +2022-11-14 17:08:22,293 Test: [14/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0697) Prec@1 88.000 (88.533) Prec@5 99.000 (99.600) +2022-11-14 17:08:22,300 Test: [15/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0699) Prec@1 89.000 (88.562) Prec@5 99.000 (99.562) +2022-11-14 17:08:22,308 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0596 (0.0693) Prec@1 90.000 (88.647) Prec@5 99.000 (99.529) +2022-11-14 17:08:22,315 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0712) Prec@1 85.000 (88.444) Prec@5 99.000 (99.500) +2022-11-14 17:08:22,323 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0720) Prec@1 85.000 (88.263) Prec@5 99.000 (99.474) +2022-11-14 17:08:22,330 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0722) Prec@1 89.000 (88.300) Prec@5 98.000 (99.400) +2022-11-14 17:08:22,338 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0721) Prec@1 88.000 (88.286) Prec@5 99.000 (99.381) +2022-11-14 17:08:22,345 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0720) Prec@1 87.000 (88.227) Prec@5 97.000 (99.273) +2022-11-14 17:08:22,353 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.0735) Prec@1 87.000 (88.174) Prec@5 96.000 (99.130) +2022-11-14 17:08:22,360 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0740) Prec@1 84.000 (88.000) Prec@5 100.000 (99.167) +2022-11-14 17:08:22,368 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0740) Prec@1 89.000 (88.040) Prec@5 100.000 (99.200) +2022-11-14 17:08:22,376 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0742) Prec@1 89.000 (88.077) Prec@5 99.000 (99.192) +2022-11-14 17:08:22,384 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0437 (0.0731) Prec@1 92.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 17:08:22,391 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0725) Prec@1 90.000 (88.286) Prec@5 100.000 (99.250) +2022-11-14 17:08:22,399 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0724) Prec@1 89.000 (88.310) Prec@5 98.000 (99.207) +2022-11-14 17:08:22,406 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0728) Prec@1 87.000 (88.267) Prec@5 100.000 (99.233) +2022-11-14 17:08:22,414 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0732) Prec@1 86.000 (88.194) Prec@5 100.000 (99.258) +2022-11-14 17:08:22,421 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0734) Prec@1 86.000 (88.125) Prec@5 99.000 (99.250) +2022-11-14 17:08:22,429 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0734) Prec@1 89.000 (88.152) Prec@5 100.000 (99.273) +2022-11-14 17:08:22,437 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0734) Prec@1 88.000 (88.147) Prec@5 99.000 (99.265) +2022-11-14 17:08:22,444 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0738) Prec@1 87.000 (88.114) Prec@5 97.000 (99.200) +2022-11-14 17:08:22,452 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0738) Prec@1 89.000 (88.139) Prec@5 98.000 (99.167) +2022-11-14 17:08:22,460 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0735) Prec@1 90.000 (88.189) Prec@5 99.000 (99.162) +2022-11-14 17:08:22,467 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0740) Prec@1 83.000 (88.053) Prec@5 100.000 (99.184) +2022-11-14 17:08:22,475 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0736) Prec@1 93.000 (88.179) Prec@5 99.000 (99.179) +2022-11-14 17:08:22,482 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0735) Prec@1 88.000 (88.175) Prec@5 100.000 (99.200) +2022-11-14 17:08:22,490 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1061 (0.0743) Prec@1 82.000 (88.024) Prec@5 99.000 (99.195) +2022-11-14 17:08:22,497 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0737) Prec@1 93.000 (88.143) Prec@5 100.000 (99.214) +2022-11-14 17:08:22,505 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0734) Prec@1 92.000 (88.233) Prec@5 100.000 (99.233) +2022-11-14 17:08:22,512 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0731) Prec@1 89.000 (88.250) Prec@5 99.000 (99.227) +2022-11-14 17:08:22,520 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0728) Prec@1 90.000 (88.289) Prec@5 100.000 (99.244) +2022-11-14 17:08:22,528 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1063 (0.0736) Prec@1 81.000 (88.130) Prec@5 99.000 (99.239) +2022-11-14 17:08:22,536 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0734) Prec@1 91.000 (88.191) Prec@5 99.000 (99.234) +2022-11-14 17:08:22,543 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0739) Prec@1 86.000 (88.146) Prec@5 98.000 (99.208) +2022-11-14 17:08:22,551 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0734) Prec@1 93.000 (88.245) Prec@5 100.000 (99.224) +2022-11-14 17:08:22,558 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0740) Prec@1 84.000 (88.160) Prec@5 100.000 (99.240) +2022-11-14 17:08:22,566 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0735) Prec@1 91.000 (88.216) Prec@5 100.000 (99.255) +2022-11-14 17:08:22,574 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0737) Prec@1 86.000 (88.173) Prec@5 100.000 (99.269) +2022-11-14 17:08:22,581 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0737) Prec@1 87.000 (88.151) Prec@5 99.000 (99.264) +2022-11-14 17:08:22,589 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0737) Prec@1 89.000 (88.167) Prec@5 98.000 (99.241) +2022-11-14 17:08:22,596 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0744) Prec@1 81.000 (88.036) Prec@5 100.000 (99.255) +2022-11-14 17:08:22,604 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0743) Prec@1 90.000 (88.071) Prec@5 99.000 (99.250) +2022-11-14 17:08:22,611 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0741) Prec@1 88.000 (88.070) Prec@5 100.000 (99.263) +2022-11-14 17:08:22,619 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0743) Prec@1 87.000 (88.052) Prec@5 100.000 (99.276) +2022-11-14 17:08:22,627 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0745) Prec@1 86.000 (88.017) Prec@5 100.000 (99.288) +2022-11-14 17:08:22,634 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0745) Prec@1 90.000 (88.050) Prec@5 99.000 (99.283) +2022-11-14 17:08:22,642 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0747) Prec@1 86.000 (88.016) Prec@5 99.000 (99.279) +2022-11-14 17:08:22,649 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0743) Prec@1 92.000 (88.081) Prec@5 100.000 (99.290) +2022-11-14 17:08:22,657 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0742) Prec@1 88.000 (88.079) Prec@5 100.000 (99.302) +2022-11-14 17:08:22,665 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0737) Prec@1 93.000 (88.156) Prec@5 100.000 (99.312) +2022-11-14 17:08:22,672 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0739) Prec@1 88.000 (88.154) Prec@5 99.000 (99.308) +2022-11-14 17:08:22,680 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0741) Prec@1 87.000 (88.136) Prec@5 97.000 (99.273) +2022-11-14 17:08:22,687 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0737) Prec@1 92.000 (88.194) Prec@5 100.000 (99.284) +2022-11-14 17:08:22,696 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0734) Prec@1 91.000 (88.235) Prec@5 99.000 (99.279) +2022-11-14 17:08:22,703 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0735) Prec@1 88.000 (88.232) Prec@5 99.000 (99.275) +2022-11-14 17:08:22,711 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0738) Prec@1 85.000 (88.186) Prec@5 99.000 (99.271) +2022-11-14 17:08:22,718 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0741) Prec@1 85.000 (88.141) Prec@5 99.000 (99.268) +2022-11-14 17:08:22,726 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0738) Prec@1 90.000 (88.167) Prec@5 100.000 (99.278) +2022-11-14 17:08:22,733 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0476 (0.0735) Prec@1 92.000 (88.219) Prec@5 99.000 (99.274) +2022-11-14 17:08:22,741 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0478 (0.0731) Prec@1 93.000 (88.284) Prec@5 100.000 (99.284) +2022-11-14 17:08:22,749 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1094 (0.0736) Prec@1 84.000 (88.227) Prec@5 100.000 (99.293) +2022-11-14 17:08:22,756 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0736) Prec@1 89.000 (88.237) Prec@5 100.000 (99.303) +2022-11-14 17:08:22,764 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0738) Prec@1 86.000 (88.208) Prec@5 98.000 (99.286) +2022-11-14 17:08:22,772 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0741) Prec@1 85.000 (88.167) Prec@5 98.000 (99.269) +2022-11-14 17:08:22,779 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0741) Prec@1 88.000 (88.165) Prec@5 100.000 (99.278) +2022-11-14 17:08:22,787 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0738) Prec@1 91.000 (88.200) Prec@5 100.000 (99.287) +2022-11-14 17:08:22,795 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0739) Prec@1 88.000 (88.198) Prec@5 99.000 (99.284) +2022-11-14 17:08:22,802 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0739) Prec@1 87.000 (88.183) Prec@5 100.000 (99.293) +2022-11-14 17:08:22,810 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0741) Prec@1 89.000 (88.193) Prec@5 100.000 (99.301) +2022-11-14 17:08:22,818 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0739) Prec@1 90.000 (88.214) Prec@5 99.000 (99.298) +2022-11-14 17:08:22,825 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0739) Prec@1 88.000 (88.212) Prec@5 100.000 (99.306) +2022-11-14 17:08:22,833 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0743) Prec@1 84.000 (88.163) Prec@5 100.000 (99.314) +2022-11-14 17:08:22,840 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0742) Prec@1 89.000 (88.172) Prec@5 98.000 (99.299) +2022-11-14 17:08:22,848 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0742) Prec@1 88.000 (88.170) Prec@5 99.000 (99.295) +2022-11-14 17:08:22,855 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0742) Prec@1 88.000 (88.169) Prec@5 100.000 (99.303) +2022-11-14 17:08:22,863 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0740) Prec@1 91.000 (88.200) Prec@5 99.000 (99.300) +2022-11-14 17:08:22,870 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0738) Prec@1 91.000 (88.231) Prec@5 100.000 (99.308) +2022-11-14 17:08:22,878 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0431 (0.0735) Prec@1 92.000 (88.272) Prec@5 99.000 (99.304) +2022-11-14 17:08:22,885 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0735) Prec@1 88.000 (88.269) Prec@5 100.000 (99.312) +2022-11-14 17:08:22,893 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0737) Prec@1 86.000 (88.245) Prec@5 100.000 (99.319) +2022-11-14 17:08:22,900 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0947 (0.0739) Prec@1 85.000 (88.211) Prec@5 99.000 (99.316) +2022-11-14 17:08:22,908 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0739) Prec@1 88.000 (88.208) Prec@5 98.000 (99.302) +2022-11-14 17:08:22,915 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0368 (0.0736) Prec@1 95.000 (88.278) Prec@5 98.000 (99.289) +2022-11-14 17:08:22,923 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0736) Prec@1 87.000 (88.265) Prec@5 98.000 (99.276) +2022-11-14 17:08:22,930 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0738) Prec@1 84.000 (88.222) Prec@5 99.000 (99.273) +2022-11-14 17:08:22,937 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0737) Prec@1 90.000 (88.240) Prec@5 99.000 (99.270) +2022-11-14 17:08:23,007 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:08:23,366 Epoch: [472][0/500] Time 0.029 (0.029) Data 0.274 (0.274) Loss 0.0300 (0.0300) Prec@1 96.000 (96.000) Prec@5 99.000 (99.000) +2022-11-14 17:08:23,564 Epoch: [472][10/500] Time 0.017 (0.018) Data 0.001 (0.026) Loss 0.0255 (0.0277) Prec@1 95.000 (95.500) Prec@5 100.000 (99.500) +2022-11-14 17:08:23,748 Epoch: [472][20/500] Time 0.017 (0.017) Data 0.001 (0.014) Loss 0.0412 (0.0322) Prec@1 94.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 17:08:23,933 Epoch: [472][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0410 (0.0344) Prec@1 94.000 (94.750) Prec@5 100.000 (99.750) +2022-11-14 17:08:24,120 Epoch: [472][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0127 (0.0301) Prec@1 98.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:08:24,304 Epoch: [472][50/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0323 (0.0304) Prec@1 94.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 17:08:24,489 Epoch: [472][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0064 (0.0270) Prec@1 100.000 (95.857) Prec@5 100.000 (99.857) +2022-11-14 17:08:24,674 Epoch: [472][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0289 (0.0272) Prec@1 92.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 17:08:24,861 Epoch: [472][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0146 (0.0258) Prec@1 97.000 (95.556) Prec@5 100.000 (99.889) +2022-11-14 17:08:25,049 Epoch: [472][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0328 (0.0265) Prec@1 95.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:08:25,236 Epoch: [472][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0274 (0.0266) Prec@1 94.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 17:08:25,422 Epoch: [472][110/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0173 (0.0258) Prec@1 97.000 (95.500) Prec@5 100.000 (99.917) +2022-11-14 17:08:25,606 Epoch: [472][120/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0252 (0.0258) Prec@1 95.000 (95.462) Prec@5 100.000 (99.923) +2022-11-14 17:08:25,800 Epoch: [472][130/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0151 (0.0250) Prec@1 99.000 (95.714) Prec@5 100.000 (99.929) +2022-11-14 17:08:26,003 Epoch: [472][140/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0238 (0.0249) Prec@1 94.000 (95.600) Prec@5 99.000 (99.867) +2022-11-14 17:08:26,201 Epoch: [472][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0366 (0.0257) Prec@1 93.000 (95.438) Prec@5 100.000 (99.875) +2022-11-14 17:08:26,395 Epoch: [472][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0356 (0.0262) Prec@1 93.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 17:08:26,590 Epoch: [472][170/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0261 (0.0262) Prec@1 95.000 (95.278) Prec@5 100.000 (99.889) +2022-11-14 17:08:26,842 Epoch: [472][180/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0383 (0.0269) Prec@1 93.000 (95.158) Prec@5 99.000 (99.842) +2022-11-14 17:08:27,103 Epoch: [472][190/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0291 (0.0270) Prec@1 94.000 (95.100) Prec@5 100.000 (99.850) +2022-11-14 17:08:27,353 Epoch: [472][200/500] Time 0.023 (0.018) Data 0.001 (0.003) Loss 0.0363 (0.0274) Prec@1 93.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:08:27,606 Epoch: [472][210/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0219 (0.0272) Prec@1 97.000 (95.091) Prec@5 100.000 (99.864) +2022-11-14 17:08:27,864 Epoch: [472][220/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0266 (0.0271) Prec@1 95.000 (95.087) Prec@5 100.000 (99.870) +2022-11-14 17:08:28,124 Epoch: [472][230/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0420 (0.0278) Prec@1 95.000 (95.083) Prec@5 98.000 (99.792) +2022-11-14 17:08:28,375 Epoch: [472][240/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0279 (0.0278) Prec@1 95.000 (95.080) Prec@5 100.000 (99.800) +2022-11-14 17:08:28,633 Epoch: [472][250/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0379 (0.0282) Prec@1 94.000 (95.038) Prec@5 100.000 (99.808) +2022-11-14 17:08:28,888 Epoch: [472][260/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0223 (0.0279) Prec@1 98.000 (95.148) Prec@5 100.000 (99.815) +2022-11-14 17:08:29,146 Epoch: [472][270/500] Time 0.022 (0.019) Data 0.002 (0.003) Loss 0.0169 (0.0275) Prec@1 98.000 (95.250) Prec@5 100.000 (99.821) +2022-11-14 17:08:29,400 Epoch: [472][280/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0282 (0.0276) Prec@1 96.000 (95.276) Prec@5 100.000 (99.828) +2022-11-14 17:08:29,656 Epoch: [472][290/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0348 (0.0278) Prec@1 94.000 (95.233) Prec@5 100.000 (99.833) +2022-11-14 17:08:29,913 Epoch: [472][300/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0229 (0.0276) Prec@1 95.000 (95.226) Prec@5 100.000 (99.839) +2022-11-14 17:08:30,171 Epoch: [472][310/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0227 (0.0275) Prec@1 96.000 (95.250) Prec@5 100.000 (99.844) +2022-11-14 17:08:30,426 Epoch: [472][320/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0490 (0.0281) Prec@1 92.000 (95.152) Prec@5 99.000 (99.818) +2022-11-14 17:08:30,683 Epoch: [472][330/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0338 (0.0283) Prec@1 93.000 (95.088) Prec@5 100.000 (99.824) +2022-11-14 17:08:30,942 Epoch: [472][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0517 (0.0290) Prec@1 93.000 (95.029) Prec@5 99.000 (99.800) +2022-11-14 17:08:31,202 Epoch: [472][350/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0170 (0.0286) Prec@1 97.000 (95.083) Prec@5 100.000 (99.806) +2022-11-14 17:08:31,457 Epoch: [472][360/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.0323 (0.0287) Prec@1 93.000 (95.027) Prec@5 100.000 (99.811) +2022-11-14 17:08:31,714 Epoch: [472][370/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0310 (0.0288) Prec@1 96.000 (95.053) Prec@5 100.000 (99.816) +2022-11-14 17:08:31,973 Epoch: [472][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0139 (0.0284) Prec@1 98.000 (95.128) Prec@5 100.000 (99.821) +2022-11-14 17:08:32,234 Epoch: [472][390/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0349 (0.0286) Prec@1 95.000 (95.125) Prec@5 100.000 (99.825) +2022-11-14 17:08:32,489 Epoch: [472][400/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0143 (0.0282) Prec@1 98.000 (95.195) Prec@5 100.000 (99.829) +2022-11-14 17:08:32,746 Epoch: [472][410/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0230 (0.0281) Prec@1 96.000 (95.214) Prec@5 100.000 (99.833) +2022-11-14 17:08:33,003 Epoch: [472][420/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0242 (0.0280) Prec@1 94.000 (95.186) Prec@5 100.000 (99.837) +2022-11-14 17:08:33,258 Epoch: [472][430/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0208 (0.0279) Prec@1 98.000 (95.250) Prec@5 100.000 (99.841) +2022-11-14 17:08:33,514 Epoch: [472][440/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0309 (0.0279) Prec@1 96.000 (95.267) Prec@5 100.000 (99.844) +2022-11-14 17:08:33,770 Epoch: [472][450/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0438 (0.0283) Prec@1 93.000 (95.217) Prec@5 100.000 (99.848) +2022-11-14 17:08:34,026 Epoch: [472][460/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0320 (0.0283) Prec@1 93.000 (95.170) Prec@5 100.000 (99.851) +2022-11-14 17:08:34,286 Epoch: [472][470/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0124 (0.0280) Prec@1 98.000 (95.229) Prec@5 100.000 (99.854) +2022-11-14 17:08:34,542 Epoch: [472][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0397 (0.0283) Prec@1 92.000 (95.163) Prec@5 100.000 (99.857) +2022-11-14 17:08:34,803 Epoch: [472][490/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0203 (0.0281) Prec@1 97.000 (95.200) Prec@5 100.000 (99.860) +2022-11-14 17:08:35,033 Epoch: [472][499/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0210 (0.0280) Prec@1 97.000 (95.235) Prec@5 100.000 (99.863) +2022-11-14 17:08:35,338 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0842 (0.0842) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:35,348 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0657 (0.0749) Prec@1 91.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:08:35,355 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0814 (0.0771) Prec@1 86.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:08:35,364 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0776) Prec@1 88.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 17:08:35,371 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0782) Prec@1 88.000 (87.800) Prec@5 100.000 (99.800) +2022-11-14 17:08:35,378 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0336 (0.0708) Prec@1 95.000 (89.000) Prec@5 100.000 (99.833) +2022-11-14 17:08:35,385 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0703) Prec@1 89.000 (89.000) Prec@5 100.000 (99.857) +2022-11-14 17:08:35,394 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0879 (0.0725) Prec@1 82.000 (88.125) Prec@5 98.000 (99.625) +2022-11-14 17:08:35,401 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0765 (0.0729) Prec@1 88.000 (88.111) Prec@5 99.000 (99.556) +2022-11-14 17:08:35,408 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0797 (0.0736) Prec@1 88.000 (88.100) Prec@5 99.000 (99.500) +2022-11-14 17:08:35,416 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0545 (0.0719) Prec@1 90.000 (88.273) Prec@5 100.000 (99.545) +2022-11-14 17:08:35,424 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0730) Prec@1 85.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 17:08:35,432 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0715) Prec@1 91.000 (88.231) Prec@5 100.000 (99.538) +2022-11-14 17:08:35,440 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0718) Prec@1 89.000 (88.286) Prec@5 99.000 (99.500) +2022-11-14 17:08:35,448 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0727) Prec@1 85.000 (88.067) Prec@5 99.000 (99.467) +2022-11-14 17:08:35,455 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0722) Prec@1 88.000 (88.062) Prec@5 100.000 (99.500) +2022-11-14 17:08:35,463 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0604 (0.0715) Prec@1 92.000 (88.294) Prec@5 98.000 (99.412) +2022-11-14 17:08:35,471 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1129 (0.0738) Prec@1 84.000 (88.056) Prec@5 100.000 (99.444) +2022-11-14 17:08:35,478 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0733) Prec@1 90.000 (88.158) Prec@5 99.000 (99.421) +2022-11-14 17:08:35,486 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0743) Prec@1 85.000 (88.000) Prec@5 97.000 (99.300) +2022-11-14 17:08:35,494 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0747) Prec@1 86.000 (87.905) Prec@5 100.000 (99.333) +2022-11-14 17:08:35,502 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0752) Prec@1 87.000 (87.864) Prec@5 100.000 (99.364) +2022-11-14 17:08:35,510 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0760) Prec@1 87.000 (87.826) Prec@5 99.000 (99.348) +2022-11-14 17:08:35,519 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0767) Prec@1 85.000 (87.708) Prec@5 100.000 (99.375) +2022-11-14 17:08:35,528 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0770) Prec@1 87.000 (87.680) Prec@5 100.000 (99.400) +2022-11-14 17:08:35,537 Test: [25/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0778) Prec@1 84.000 (87.538) Prec@5 99.000 (99.385) +2022-11-14 17:08:35,546 Test: [26/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0501 (0.0768) Prec@1 90.000 (87.630) Prec@5 100.000 (99.407) +2022-11-14 17:08:35,555 Test: [27/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0767) Prec@1 88.000 (87.643) Prec@5 100.000 (99.429) +2022-11-14 17:08:35,564 Test: [28/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0765) Prec@1 89.000 (87.690) Prec@5 99.000 (99.414) +2022-11-14 17:08:35,572 Test: [29/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0762) Prec@1 90.000 (87.767) Prec@5 98.000 (99.367) +2022-11-14 17:08:35,581 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0759) Prec@1 88.000 (87.774) Prec@5 100.000 (99.387) +2022-11-14 17:08:35,589 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0759) Prec@1 85.000 (87.688) Prec@5 100.000 (99.406) +2022-11-14 17:08:35,597 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0757) Prec@1 89.000 (87.727) Prec@5 100.000 (99.424) +2022-11-14 17:08:35,607 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0762) Prec@1 84.000 (87.618) Prec@5 100.000 (99.441) +2022-11-14 17:08:35,615 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0761) Prec@1 89.000 (87.657) Prec@5 98.000 (99.400) +2022-11-14 17:08:35,624 Test: [35/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0758) Prec@1 88.000 (87.667) Prec@5 99.000 (99.389) +2022-11-14 17:08:35,632 Test: [36/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0755) Prec@1 90.000 (87.730) Prec@5 99.000 (99.378) +2022-11-14 17:08:35,640 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0763) Prec@1 81.000 (87.553) Prec@5 99.000 (99.368) +2022-11-14 17:08:35,648 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0757) Prec@1 92.000 (87.667) Prec@5 99.000 (99.359) +2022-11-14 17:08:35,656 Test: [39/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0757) Prec@1 89.000 (87.700) Prec@5 98.000 (99.325) +2022-11-14 17:08:35,664 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0766) Prec@1 82.000 (87.561) Prec@5 99.000 (99.317) +2022-11-14 17:08:35,672 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0761) Prec@1 92.000 (87.667) Prec@5 100.000 (99.333) +2022-11-14 17:08:35,681 Test: [42/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0439 (0.0753) Prec@1 93.000 (87.791) Prec@5 99.000 (99.326) +2022-11-14 17:08:35,689 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0751) Prec@1 90.000 (87.841) Prec@5 99.000 (99.318) +2022-11-14 17:08:35,696 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0751) Prec@1 89.000 (87.867) Prec@5 99.000 (99.311) +2022-11-14 17:08:35,704 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1199 (0.0761) Prec@1 81.000 (87.717) Prec@5 99.000 (99.304) +2022-11-14 17:08:35,712 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0757) Prec@1 90.000 (87.766) Prec@5 100.000 (99.319) +2022-11-14 17:08:35,720 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0763) Prec@1 85.000 (87.708) Prec@5 98.000 (99.292) +2022-11-14 17:08:35,727 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0360 (0.0755) Prec@1 94.000 (87.837) Prec@5 100.000 (99.306) +2022-11-14 17:08:35,735 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1189 (0.0764) Prec@1 82.000 (87.720) Prec@5 99.000 (99.300) +2022-11-14 17:08:35,743 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0762) Prec@1 88.000 (87.725) Prec@5 100.000 (99.314) +2022-11-14 17:08:35,751 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1132 (0.0769) Prec@1 77.000 (87.519) Prec@5 100.000 (99.327) +2022-11-14 17:08:35,758 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0416 (0.0762) Prec@1 93.000 (87.623) Prec@5 100.000 (99.340) +2022-11-14 17:08:35,766 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0760) Prec@1 90.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 17:08:35,774 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0762) Prec@1 88.000 (87.673) Prec@5 100.000 (99.345) +2022-11-14 17:08:35,782 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0762) Prec@1 89.000 (87.696) Prec@5 99.000 (99.339) +2022-11-14 17:08:35,789 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0760) Prec@1 88.000 (87.702) Prec@5 99.000 (99.333) +2022-11-14 17:08:35,797 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0760) Prec@1 89.000 (87.724) Prec@5 100.000 (99.345) +2022-11-14 17:08:35,805 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0760) Prec@1 88.000 (87.729) Prec@5 99.000 (99.339) +2022-11-14 17:08:35,813 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0759) Prec@1 88.000 (87.733) Prec@5 100.000 (99.350) +2022-11-14 17:08:35,821 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0760) Prec@1 87.000 (87.721) Prec@5 100.000 (99.361) +2022-11-14 17:08:35,829 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0758) Prec@1 91.000 (87.774) Prec@5 98.000 (99.339) +2022-11-14 17:08:35,837 Test: [62/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0759) Prec@1 88.000 (87.778) Prec@5 100.000 (99.349) +2022-11-14 17:08:35,845 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0442 (0.0755) Prec@1 94.000 (87.875) Prec@5 100.000 (99.359) +2022-11-14 17:08:35,852 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0753) Prec@1 89.000 (87.892) Prec@5 100.000 (99.369) +2022-11-14 17:08:35,860 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0752) Prec@1 88.000 (87.894) Prec@5 100.000 (99.379) +2022-11-14 17:08:35,868 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0448 (0.0747) Prec@1 93.000 (87.970) Prec@5 100.000 (99.388) +2022-11-14 17:08:35,875 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0747) Prec@1 88.000 (87.971) Prec@5 100.000 (99.397) +2022-11-14 17:08:35,883 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0747) Prec@1 89.000 (87.986) Prec@5 100.000 (99.406) +2022-11-14 17:08:35,890 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0749) Prec@1 86.000 (87.957) Prec@5 99.000 (99.400) +2022-11-14 17:08:35,898 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0934 (0.0752) Prec@1 88.000 (87.958) Prec@5 99.000 (99.394) +2022-11-14 17:08:35,905 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0750) Prec@1 91.000 (88.000) Prec@5 100.000 (99.403) +2022-11-14 17:08:35,913 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0433 (0.0745) Prec@1 94.000 (88.082) Prec@5 100.000 (99.411) +2022-11-14 17:08:35,920 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0741) Prec@1 95.000 (88.176) Prec@5 100.000 (99.419) +2022-11-14 17:08:35,927 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0744) Prec@1 85.000 (88.133) Prec@5 100.000 (99.427) +2022-11-14 17:08:35,935 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0746) Prec@1 87.000 (88.118) Prec@5 99.000 (99.421) +2022-11-14 17:08:35,942 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0745) Prec@1 89.000 (88.130) Prec@5 99.000 (99.416) +2022-11-14 17:08:35,950 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0747) Prec@1 85.000 (88.090) Prec@5 99.000 (99.410) +2022-11-14 17:08:35,957 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0748) Prec@1 87.000 (88.076) Prec@5 100.000 (99.418) +2022-11-14 17:08:35,965 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0748) Prec@1 88.000 (88.075) Prec@5 100.000 (99.425) +2022-11-14 17:08:35,972 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0749) Prec@1 88.000 (88.074) Prec@5 98.000 (99.407) +2022-11-14 17:08:35,980 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0750) Prec@1 86.000 (88.049) Prec@5 98.000 (99.390) +2022-11-14 17:08:35,987 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0751) Prec@1 85.000 (88.012) Prec@5 99.000 (99.386) +2022-11-14 17:08:35,995 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0406 (0.0747) Prec@1 94.000 (88.083) Prec@5 100.000 (99.393) +2022-11-14 17:08:36,002 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0750) Prec@1 85.000 (88.047) Prec@5 100.000 (99.400) +2022-11-14 17:08:36,009 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0970 (0.0752) Prec@1 86.000 (88.023) Prec@5 99.000 (99.395) +2022-11-14 17:08:36,017 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0754) Prec@1 86.000 (88.000) Prec@5 99.000 (99.391) +2022-11-14 17:08:36,025 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0755) Prec@1 87.000 (87.989) Prec@5 99.000 (99.386) +2022-11-14 17:08:36,032 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0753) Prec@1 92.000 (88.034) Prec@5 100.000 (99.393) +2022-11-14 17:08:36,040 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0752) Prec@1 90.000 (88.056) Prec@5 100.000 (99.400) +2022-11-14 17:08:36,048 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0573 (0.0750) Prec@1 91.000 (88.088) Prec@5 99.000 (99.396) +2022-11-14 17:08:36,055 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0747) Prec@1 94.000 (88.152) Prec@5 100.000 (99.402) +2022-11-14 17:08:36,063 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0748) Prec@1 85.000 (88.118) Prec@5 99.000 (99.398) +2022-11-14 17:08:36,070 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0751) Prec@1 85.000 (88.085) Prec@5 100.000 (99.404) +2022-11-14 17:08:36,079 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0752) Prec@1 86.000 (88.063) Prec@5 100.000 (99.411) +2022-11-14 17:08:36,087 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0750) Prec@1 90.000 (88.083) Prec@5 100.000 (99.417) +2022-11-14 17:08:36,095 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0747) Prec@1 93.000 (88.134) Prec@5 99.000 (99.412) +2022-11-14 17:08:36,102 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0749) Prec@1 83.000 (88.082) Prec@5 99.000 (99.408) +2022-11-14 17:08:36,110 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0984 (0.0751) Prec@1 84.000 (88.040) Prec@5 99.000 (99.404) +2022-11-14 17:08:36,117 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0749) Prec@1 91.000 (88.070) Prec@5 99.000 (99.400) +2022-11-14 17:08:36,174 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:08:36,510 Epoch: [473][0/500] Time 0.031 (0.031) Data 0.247 (0.247) Loss 0.0572 (0.0572) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:36,704 Epoch: [473][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0309 (0.0441) Prec@1 95.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:08:36,891 Epoch: [473][20/500] Time 0.016 (0.017) Data 0.002 (0.013) Loss 0.0180 (0.0354) Prec@1 97.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:08:37,077 Epoch: [473][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0237 (0.0325) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:08:37,266 Epoch: [473][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0367 (0.0333) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:37,453 Epoch: [473][50/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0319 (0.0331) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:37,642 Epoch: [473][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0093 (0.0297) Prec@1 98.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:08:37,829 Epoch: [473][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0492 (0.0321) Prec@1 90.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:08:38,016 Epoch: [473][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0138 (0.0301) Prec@1 98.000 (95.111) Prec@5 100.000 (100.000) +2022-11-14 17:08:38,205 Epoch: [473][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0197 (0.0290) Prec@1 97.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 17:08:38,403 Epoch: [473][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0395 (0.0300) Prec@1 94.000 (95.182) Prec@5 100.000 (100.000) +2022-11-14 17:08:38,605 Epoch: [473][110/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0182 (0.0290) Prec@1 97.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:08:38,811 Epoch: [473][120/500] Time 0.015 (0.017) Data 0.003 (0.004) Loss 0.0329 (0.0293) Prec@1 95.000 (95.308) Prec@5 100.000 (100.000) +2022-11-14 17:08:39,014 Epoch: [473][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0259 (0.0291) Prec@1 97.000 (95.429) Prec@5 100.000 (100.000) +2022-11-14 17:08:39,209 Epoch: [473][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0256 (0.0288) Prec@1 95.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:08:39,398 Epoch: [473][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0337 (0.0291) Prec@1 94.000 (95.312) Prec@5 100.000 (100.000) +2022-11-14 17:08:39,588 Epoch: [473][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0455 (0.0301) Prec@1 92.000 (95.118) Prec@5 100.000 (100.000) +2022-11-14 17:08:39,802 Epoch: [473][170/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0566 (0.0316) Prec@1 90.000 (94.833) Prec@5 99.000 (99.944) +2022-11-14 17:08:40,056 Epoch: [473][180/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0317 (0.0316) Prec@1 95.000 (94.842) Prec@5 100.000 (99.947) +2022-11-14 17:08:40,309 Epoch: [473][190/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0236 (0.0312) Prec@1 97.000 (94.950) Prec@5 100.000 (99.950) +2022-11-14 17:08:40,566 Epoch: [473][200/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0321 (0.0312) Prec@1 95.000 (94.952) Prec@5 100.000 (99.952) +2022-11-14 17:08:40,822 Epoch: [473][210/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0359 (0.0314) Prec@1 94.000 (94.909) Prec@5 100.000 (99.955) +2022-11-14 17:08:41,078 Epoch: [473][220/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0234 (0.0311) Prec@1 96.000 (94.957) Prec@5 99.000 (99.913) +2022-11-14 17:08:41,334 Epoch: [473][230/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0170 (0.0305) Prec@1 97.000 (95.042) Prec@5 100.000 (99.917) +2022-11-14 17:08:41,595 Epoch: [473][240/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0533 (0.0314) Prec@1 92.000 (94.920) Prec@5 99.000 (99.880) +2022-11-14 17:08:41,854 Epoch: [473][250/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0189 (0.0309) Prec@1 98.000 (95.038) Prec@5 100.000 (99.885) +2022-11-14 17:08:42,114 Epoch: [473][260/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0235 (0.0307) Prec@1 95.000 (95.037) Prec@5 100.000 (99.889) +2022-11-14 17:08:42,370 Epoch: [473][270/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0251 (0.0305) Prec@1 96.000 (95.071) Prec@5 100.000 (99.893) +2022-11-14 17:08:42,631 Epoch: [473][280/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0242 (0.0302) Prec@1 97.000 (95.138) Prec@5 100.000 (99.897) +2022-11-14 17:08:42,893 Epoch: [473][290/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0253 (0.0301) Prec@1 95.000 (95.133) Prec@5 100.000 (99.900) +2022-11-14 17:08:43,153 Epoch: [473][300/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0459 (0.0306) Prec@1 92.000 (95.032) Prec@5 100.000 (99.903) +2022-11-14 17:08:43,415 Epoch: [473][310/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0167 (0.0302) Prec@1 98.000 (95.125) Prec@5 100.000 (99.906) +2022-11-14 17:08:43,677 Epoch: [473][320/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0333 (0.0303) Prec@1 94.000 (95.091) Prec@5 100.000 (99.909) +2022-11-14 17:08:43,937 Epoch: [473][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0293 (0.0302) Prec@1 95.000 (95.088) Prec@5 100.000 (99.912) +2022-11-14 17:08:44,193 Epoch: [473][340/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0048 (0.0295) Prec@1 100.000 (95.229) Prec@5 100.000 (99.914) +2022-11-14 17:08:44,445 Epoch: [473][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0445 (0.0299) Prec@1 92.000 (95.139) Prec@5 100.000 (99.917) +2022-11-14 17:08:44,698 Epoch: [473][360/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0352 (0.0301) Prec@1 95.000 (95.135) Prec@5 99.000 (99.892) +2022-11-14 17:08:44,949 Epoch: [473][370/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0357 (0.0302) Prec@1 95.000 (95.132) Prec@5 100.000 (99.895) +2022-11-14 17:08:45,205 Epoch: [473][380/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0240 (0.0300) Prec@1 97.000 (95.179) Prec@5 100.000 (99.897) +2022-11-14 17:08:45,455 Epoch: [473][390/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0195 (0.0298) Prec@1 96.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:08:45,707 Epoch: [473][400/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0452 (0.0302) Prec@1 91.000 (95.098) Prec@5 100.000 (99.902) +2022-11-14 17:08:45,959 Epoch: [473][410/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0312 (0.0302) Prec@1 94.000 (95.071) Prec@5 100.000 (99.905) +2022-11-14 17:08:46,212 Epoch: [473][420/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0296 (0.0302) Prec@1 95.000 (95.070) Prec@5 100.000 (99.907) +2022-11-14 17:08:46,466 Epoch: [473][430/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0149 (0.0298) Prec@1 96.000 (95.091) Prec@5 100.000 (99.909) +2022-11-14 17:08:46,720 Epoch: [473][440/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0372 (0.0300) Prec@1 94.000 (95.067) Prec@5 100.000 (99.911) +2022-11-14 17:08:46,976 Epoch: [473][450/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0484 (0.0304) Prec@1 91.000 (94.978) Prec@5 99.000 (99.891) +2022-11-14 17:08:47,231 Epoch: [473][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0234 (0.0302) Prec@1 95.000 (94.979) Prec@5 100.000 (99.894) +2022-11-14 17:08:47,483 Epoch: [473][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0406 (0.0305) Prec@1 94.000 (94.958) Prec@5 100.000 (99.896) +2022-11-14 17:08:47,734 Epoch: [473][480/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0326 (0.0305) Prec@1 95.000 (94.959) Prec@5 100.000 (99.898) +2022-11-14 17:08:47,983 Epoch: [473][490/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0233 (0.0304) Prec@1 96.000 (94.980) Prec@5 100.000 (99.900) +2022-11-14 17:08:48,213 Epoch: [473][499/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0403 (0.0306) Prec@1 94.000 (94.961) Prec@5 100.000 (99.902) +2022-11-14 17:08:48,510 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0764 (0.0764) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 17:08:48,518 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0767 (0.0765) Prec@1 86.000 (86.000) Prec@5 100.000 (99.500) +2022-11-14 17:08:48,525 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0770 (0.0767) Prec@1 87.000 (86.333) Prec@5 100.000 (99.667) +2022-11-14 17:08:48,536 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0776 (0.0769) Prec@1 88.000 (86.750) Prec@5 98.000 (99.250) +2022-11-14 17:08:48,542 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0620 (0.0739) Prec@1 91.000 (87.600) Prec@5 99.000 (99.200) +2022-11-14 17:08:48,549 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0463 (0.0693) Prec@1 91.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 17:08:48,556 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0685) Prec@1 90.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 17:08:48,564 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0709) Prec@1 85.000 (88.000) Prec@5 98.000 (99.250) +2022-11-14 17:08:48,571 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0721) Prec@1 87.000 (87.889) Prec@5 97.000 (99.000) +2022-11-14 17:08:48,579 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0731) Prec@1 86.000 (87.700) Prec@5 98.000 (98.900) +2022-11-14 17:08:48,586 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0728) Prec@1 88.000 (87.727) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,594 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0727) Prec@1 88.000 (87.750) Prec@5 99.000 (99.000) +2022-11-14 17:08:48,602 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0724) Prec@1 89.000 (87.846) Prec@5 100.000 (99.077) +2022-11-14 17:08:48,609 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0713) Prec@1 90.000 (88.000) Prec@5 100.000 (99.143) +2022-11-14 17:08:48,617 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0712) Prec@1 89.000 (88.067) Prec@5 100.000 (99.200) +2022-11-14 17:08:48,624 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0711) Prec@1 88.000 (88.062) Prec@5 100.000 (99.250) +2022-11-14 17:08:48,632 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0417 (0.0694) Prec@1 95.000 (88.471) Prec@5 98.000 (99.176) +2022-11-14 17:08:48,640 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1057 (0.0714) Prec@1 84.000 (88.222) Prec@5 100.000 (99.222) +2022-11-14 17:08:48,648 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0722) Prec@1 88.000 (88.211) Prec@5 96.000 (99.053) +2022-11-14 17:08:48,656 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1046 (0.0739) Prec@1 82.000 (87.900) Prec@5 96.000 (98.900) +2022-11-14 17:08:48,663 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0733) Prec@1 90.000 (88.000) Prec@5 100.000 (98.952) +2022-11-14 17:08:48,671 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0743) Prec@1 83.000 (87.773) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,679 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0743) Prec@1 90.000 (87.870) Prec@5 97.000 (98.913) +2022-11-14 17:08:48,687 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0744) Prec@1 86.000 (87.792) Prec@5 99.000 (98.917) +2022-11-14 17:08:48,694 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0745) Prec@1 87.000 (87.760) Prec@5 100.000 (98.960) +2022-11-14 17:08:48,702 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1059 (0.0757) Prec@1 87.000 (87.731) Prec@5 98.000 (98.923) +2022-11-14 17:08:48,710 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0751) Prec@1 91.000 (87.852) Prec@5 100.000 (98.963) +2022-11-14 17:08:48,717 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0745) Prec@1 91.000 (87.964) Prec@5 99.000 (98.964) +2022-11-14 17:08:48,725 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0752) Prec@1 84.000 (87.828) Prec@5 98.000 (98.931) +2022-11-14 17:08:48,733 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0755) Prec@1 87.000 (87.800) Prec@5 99.000 (98.933) +2022-11-14 17:08:48,741 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0750) Prec@1 88.000 (87.806) Prec@5 100.000 (98.968) +2022-11-14 17:08:48,748 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0747) Prec@1 90.000 (87.875) Prec@5 99.000 (98.969) +2022-11-14 17:08:48,756 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0746) Prec@1 86.000 (87.818) Prec@5 99.000 (98.970) +2022-11-14 17:08:48,764 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0750) Prec@1 84.000 (87.706) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,772 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0757) Prec@1 83.000 (87.571) Prec@5 97.000 (98.943) +2022-11-14 17:08:48,779 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0754) Prec@1 90.000 (87.639) Prec@5 100.000 (98.972) +2022-11-14 17:08:48,787 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0755) Prec@1 87.000 (87.622) Prec@5 99.000 (98.973) +2022-11-14 17:08:48,795 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0757) Prec@1 87.000 (87.605) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,802 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0752) Prec@1 93.000 (87.744) Prec@5 100.000 (99.026) +2022-11-14 17:08:48,810 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0749) Prec@1 90.000 (87.800) Prec@5 99.000 (99.025) +2022-11-14 17:08:48,817 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0751) Prec@1 88.000 (87.805) Prec@5 98.000 (99.000) +2022-11-14 17:08:48,825 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0751) Prec@1 88.000 (87.810) Prec@5 97.000 (98.952) +2022-11-14 17:08:48,833 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0517 (0.0745) Prec@1 89.000 (87.837) Prec@5 99.000 (98.953) +2022-11-14 17:08:48,841 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0747) Prec@1 87.000 (87.818) Prec@5 98.000 (98.932) +2022-11-14 17:08:48,849 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0636 (0.0745) Prec@1 92.000 (87.911) Prec@5 100.000 (98.956) +2022-11-14 17:08:48,856 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1077 (0.0752) Prec@1 84.000 (87.826) Prec@5 99.000 (98.957) +2022-11-14 17:08:48,864 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0749) Prec@1 90.000 (87.872) Prec@5 100.000 (98.979) +2022-11-14 17:08:48,872 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0754) Prec@1 86.000 (87.833) Prec@5 97.000 (98.938) +2022-11-14 17:08:48,880 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0500 (0.0749) Prec@1 91.000 (87.898) Prec@5 100.000 (98.959) +2022-11-14 17:08:48,888 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1208 (0.0758) Prec@1 81.000 (87.760) Prec@5 99.000 (98.960) +2022-11-14 17:08:48,896 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0756) Prec@1 92.000 (87.843) Prec@5 100.000 (98.980) +2022-11-14 17:08:48,904 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0758) Prec@1 87.000 (87.827) Prec@5 99.000 (98.981) +2022-11-14 17:08:48,912 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0757) Prec@1 88.000 (87.830) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,920 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0752) Prec@1 93.000 (87.926) Prec@5 98.000 (98.981) +2022-11-14 17:08:48,927 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0758) Prec@1 82.000 (87.818) Prec@5 100.000 (99.000) +2022-11-14 17:08:48,935 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0758) Prec@1 88.000 (87.821) Prec@5 99.000 (99.000) +2022-11-14 17:08:48,943 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0760) Prec@1 85.000 (87.772) Prec@5 99.000 (99.000) +2022-11-14 17:08:48,951 Test: [57/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0762) Prec@1 89.000 (87.793) Prec@5 100.000 (99.017) +2022-11-14 17:08:48,959 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0763) Prec@1 87.000 (87.780) Prec@5 100.000 (99.034) +2022-11-14 17:08:48,966 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0765) Prec@1 86.000 (87.750) Prec@5 100.000 (99.050) +2022-11-14 17:08:48,974 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0767) Prec@1 86.000 (87.721) Prec@5 100.000 (99.066) +2022-11-14 17:08:48,983 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0767) Prec@1 87.000 (87.710) Prec@5 100.000 (99.081) +2022-11-14 17:08:48,991 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0623 (0.0765) Prec@1 91.000 (87.762) Prec@5 100.000 (99.095) +2022-11-14 17:08:48,999 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0761) Prec@1 92.000 (87.828) Prec@5 100.000 (99.109) +2022-11-14 17:08:49,007 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0762) Prec@1 87.000 (87.815) Prec@5 98.000 (99.092) +2022-11-14 17:08:49,014 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0760) Prec@1 91.000 (87.864) Prec@5 99.000 (99.091) +2022-11-14 17:08:49,022 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0365 (0.0754) Prec@1 93.000 (87.940) Prec@5 100.000 (99.104) +2022-11-14 17:08:49,030 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0754) Prec@1 90.000 (87.971) Prec@5 97.000 (99.074) +2022-11-14 17:08:49,038 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0753) Prec@1 87.000 (87.957) Prec@5 99.000 (99.072) +2022-11-14 17:08:49,045 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0754) Prec@1 88.000 (87.957) Prec@5 99.000 (99.071) +2022-11-14 17:08:49,053 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0758) Prec@1 86.000 (87.930) Prec@5 98.000 (99.056) +2022-11-14 17:08:49,061 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0756) Prec@1 87.000 (87.917) Prec@5 99.000 (99.056) +2022-11-14 17:08:49,068 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0463 (0.0752) Prec@1 93.000 (87.986) Prec@5 100.000 (99.068) +2022-11-14 17:08:49,076 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0468 (0.0748) Prec@1 94.000 (88.068) Prec@5 100.000 (99.081) +2022-11-14 17:08:49,086 Test: [74/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1008 (0.0752) Prec@1 83.000 (88.000) Prec@5 99.000 (99.080) +2022-11-14 17:08:49,094 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0750) Prec@1 90.000 (88.026) Prec@5 98.000 (99.066) +2022-11-14 17:08:49,102 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0751) Prec@1 86.000 (88.000) Prec@5 99.000 (99.065) +2022-11-14 17:08:49,110 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1083 (0.0755) Prec@1 83.000 (87.936) Prec@5 98.000 (99.051) +2022-11-14 17:08:49,117 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0755) Prec@1 89.000 (87.949) Prec@5 100.000 (99.063) +2022-11-14 17:08:49,125 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0755) Prec@1 89.000 (87.963) Prec@5 100.000 (99.075) +2022-11-14 17:08:49,133 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0757) Prec@1 87.000 (87.951) Prec@5 97.000 (99.049) +2022-11-14 17:08:49,141 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0758) Prec@1 86.000 (87.927) Prec@5 99.000 (99.049) +2022-11-14 17:08:49,149 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0760) Prec@1 87.000 (87.916) Prec@5 99.000 (99.048) +2022-11-14 17:08:49,156 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0757) Prec@1 91.000 (87.952) Prec@5 99.000 (99.048) +2022-11-14 17:08:49,164 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1068 (0.0761) Prec@1 84.000 (87.906) Prec@5 98.000 (99.035) +2022-11-14 17:08:49,172 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0762) Prec@1 89.000 (87.919) Prec@5 100.000 (99.047) +2022-11-14 17:08:49,179 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0763) Prec@1 88.000 (87.920) Prec@5 99.000 (99.046) +2022-11-14 17:08:49,187 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0761) Prec@1 91.000 (87.955) Prec@5 99.000 (99.045) +2022-11-14 17:08:49,194 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0762) Prec@1 86.000 (87.933) Prec@5 99.000 (99.045) +2022-11-14 17:08:49,202 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0760) Prec@1 90.000 (87.956) Prec@5 100.000 (99.056) +2022-11-14 17:08:49,209 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0759) Prec@1 88.000 (87.956) Prec@5 100.000 (99.066) +2022-11-14 17:08:49,217 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0487 (0.0756) Prec@1 93.000 (88.011) Prec@5 100.000 (99.076) +2022-11-14 17:08:49,224 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0758) Prec@1 85.000 (87.978) Prec@5 100.000 (99.086) +2022-11-14 17:08:49,232 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0758) Prec@1 87.000 (87.968) Prec@5 98.000 (99.074) +2022-11-14 17:08:49,240 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0757) Prec@1 92.000 (88.011) Prec@5 99.000 (99.074) +2022-11-14 17:08:49,247 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0756) Prec@1 91.000 (88.042) Prec@5 100.000 (99.083) +2022-11-14 17:08:49,255 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0418 (0.0752) Prec@1 93.000 (88.093) Prec@5 99.000 (99.082) +2022-11-14 17:08:49,263 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0948 (0.0754) Prec@1 86.000 (88.071) Prec@5 98.000 (99.071) +2022-11-14 17:08:49,270 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1123 (0.0758) Prec@1 82.000 (88.010) Prec@5 100.000 (99.081) +2022-11-14 17:08:49,278 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0756) Prec@1 89.000 (88.020) Prec@5 100.000 (99.090) +2022-11-14 17:08:49,347 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:08:49,663 Epoch: [474][0/500] Time 0.024 (0.024) Data 0.240 (0.240) Loss 0.0174 (0.0174) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:49,865 Epoch: [474][10/500] Time 0.016 (0.018) Data 0.002 (0.023) Loss 0.0114 (0.0144) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:08:50,051 Epoch: [474][20/500] Time 0.018 (0.017) Data 0.001 (0.013) Loss 0.0391 (0.0226) Prec@1 93.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:08:50,246 Epoch: [474][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0160 (0.0210) Prec@1 96.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:08:50,437 Epoch: [474][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0245 (0.0217) Prec@1 96.000 (95.800) Prec@5 100.000 (100.000) +2022-11-14 17:08:50,627 Epoch: [474][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0235 (0.0220) Prec@1 96.000 (95.833) Prec@5 100.000 (100.000) +2022-11-14 17:08:50,817 Epoch: [474][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0262 (0.0226) Prec@1 96.000 (95.857) Prec@5 100.000 (100.000) +2022-11-14 17:08:51,006 Epoch: [474][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0266 (0.0231) Prec@1 96.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 17:08:51,198 Epoch: [474][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0205 (0.0228) Prec@1 97.000 (96.000) Prec@5 99.000 (99.889) +2022-11-14 17:08:51,385 Epoch: [474][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0245 (0.0230) Prec@1 94.000 (95.800) Prec@5 100.000 (99.900) +2022-11-14 17:08:51,581 Epoch: [474][100/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0408 (0.0246) Prec@1 93.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 17:08:51,861 Epoch: [474][110/500] Time 0.028 (0.018) Data 0.001 (0.004) Loss 0.0350 (0.0255) Prec@1 95.000 (95.500) Prec@5 100.000 (99.917) +2022-11-14 17:08:52,158 Epoch: [474][120/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0278 (0.0256) Prec@1 95.000 (95.462) Prec@5 100.000 (99.923) +2022-11-14 17:08:52,454 Epoch: [474][130/500] Time 0.028 (0.019) Data 0.002 (0.003) Loss 0.0329 (0.0262) Prec@1 95.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 17:08:52,751 Epoch: [474][140/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0154 (0.0254) Prec@1 99.000 (95.667) Prec@5 100.000 (99.933) +2022-11-14 17:08:53,055 Epoch: [474][150/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0301 (0.0257) Prec@1 94.000 (95.562) Prec@5 100.000 (99.938) +2022-11-14 17:08:53,363 Epoch: [474][160/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0204 (0.0254) Prec@1 96.000 (95.588) Prec@5 100.000 (99.941) +2022-11-14 17:08:53,665 Epoch: [474][170/500] Time 0.031 (0.021) Data 0.001 (0.003) Loss 0.0228 (0.0253) Prec@1 96.000 (95.611) Prec@5 100.000 (99.944) +2022-11-14 17:08:53,971 Epoch: [474][180/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0130 (0.0246) Prec@1 98.000 (95.737) Prec@5 100.000 (99.947) +2022-11-14 17:08:54,270 Epoch: [474][190/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0132 (0.0241) Prec@1 99.000 (95.900) Prec@5 100.000 (99.950) +2022-11-14 17:08:54,571 Epoch: [474][200/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0487 (0.0252) Prec@1 92.000 (95.714) Prec@5 100.000 (99.952) +2022-11-14 17:08:54,858 Epoch: [474][210/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0331 (0.0256) Prec@1 94.000 (95.636) Prec@5 100.000 (99.955) +2022-11-14 17:08:55,157 Epoch: [474][220/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0337 (0.0259) Prec@1 96.000 (95.652) Prec@5 100.000 (99.957) +2022-11-14 17:08:55,456 Epoch: [474][230/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0226 (0.0258) Prec@1 96.000 (95.667) Prec@5 100.000 (99.958) +2022-11-14 17:08:55,751 Epoch: [474][240/500] Time 0.028 (0.022) Data 0.001 (0.003) Loss 0.0339 (0.0261) Prec@1 92.000 (95.520) Prec@5 100.000 (99.960) +2022-11-14 17:08:56,045 Epoch: [474][250/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0202 (0.0259) Prec@1 96.000 (95.538) Prec@5 100.000 (99.962) +2022-11-14 17:08:56,341 Epoch: [474][260/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0080 (0.0252) Prec@1 99.000 (95.667) Prec@5 100.000 (99.963) +2022-11-14 17:08:56,632 Epoch: [474][270/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0180 (0.0250) Prec@1 96.000 (95.679) Prec@5 100.000 (99.964) +2022-11-14 17:08:56,926 Epoch: [474][280/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0313 (0.0252) Prec@1 94.000 (95.621) Prec@5 100.000 (99.966) +2022-11-14 17:08:57,221 Epoch: [474][290/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0245 (0.0252) Prec@1 96.000 (95.633) Prec@5 100.000 (99.967) +2022-11-14 17:08:57,520 Epoch: [474][300/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0103 (0.0247) Prec@1 98.000 (95.710) Prec@5 100.000 (99.968) +2022-11-14 17:08:57,819 Epoch: [474][310/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0214 (0.0246) Prec@1 97.000 (95.750) Prec@5 100.000 (99.969) +2022-11-14 17:08:58,108 Epoch: [474][320/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0314 (0.0248) Prec@1 94.000 (95.697) Prec@5 100.000 (99.970) +2022-11-14 17:08:58,391 Epoch: [474][330/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0461 (0.0254) Prec@1 91.000 (95.559) Prec@5 100.000 (99.971) +2022-11-14 17:08:58,680 Epoch: [474][340/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0266 (0.0255) Prec@1 97.000 (95.600) Prec@5 99.000 (99.943) +2022-11-14 17:08:58,967 Epoch: [474][350/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0503 (0.0261) Prec@1 90.000 (95.444) Prec@5 100.000 (99.944) +2022-11-14 17:08:59,258 Epoch: [474][360/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0573 (0.0270) Prec@1 90.000 (95.297) Prec@5 100.000 (99.946) +2022-11-14 17:08:59,549 Epoch: [474][370/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0510 (0.0276) Prec@1 92.000 (95.211) Prec@5 100.000 (99.947) +2022-11-14 17:08:59,840 Epoch: [474][380/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0167 (0.0273) Prec@1 96.000 (95.231) Prec@5 100.000 (99.949) +2022-11-14 17:09:00,127 Epoch: [474][390/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0276 (0.0274) Prec@1 94.000 (95.200) Prec@5 100.000 (99.950) +2022-11-14 17:09:00,413 Epoch: [474][400/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0248 (0.0273) Prec@1 96.000 (95.220) Prec@5 100.000 (99.951) +2022-11-14 17:09:00,705 Epoch: [474][410/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0252 (0.0272) Prec@1 97.000 (95.262) Prec@5 100.000 (99.952) +2022-11-14 17:09:00,996 Epoch: [474][420/500] Time 0.026 (0.024) Data 0.002 (0.002) Loss 0.0128 (0.0269) Prec@1 98.000 (95.326) Prec@5 100.000 (99.953) +2022-11-14 17:09:01,288 Epoch: [474][430/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0565 (0.0276) Prec@1 88.000 (95.159) Prec@5 100.000 (99.955) +2022-11-14 17:09:01,576 Epoch: [474][440/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0240 (0.0275) Prec@1 96.000 (95.178) Prec@5 99.000 (99.933) +2022-11-14 17:09:01,863 Epoch: [474][450/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0110 (0.0271) Prec@1 99.000 (95.261) Prec@5 100.000 (99.935) +2022-11-14 17:09:02,147 Epoch: [474][460/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0303 (0.0272) Prec@1 94.000 (95.234) Prec@5 100.000 (99.936) +2022-11-14 17:09:02,435 Epoch: [474][470/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0330 (0.0273) Prec@1 95.000 (95.229) Prec@5 100.000 (99.938) +2022-11-14 17:09:02,722 Epoch: [474][480/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0510 (0.0278) Prec@1 92.000 (95.163) Prec@5 99.000 (99.918) +2022-11-14 17:09:03,009 Epoch: [474][490/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0528 (0.0283) Prec@1 90.000 (95.060) Prec@5 100.000 (99.920) +2022-11-14 17:09:03,269 Epoch: [474][499/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0466 (0.0287) Prec@1 93.000 (95.020) Prec@5 100.000 (99.922) +2022-11-14 17:09:03,573 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0785 (0.0785) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 17:09:03,582 Test: [1/100] Model Time 0.007 (0.010) Loss Time 0.000 (0.000) Loss 0.0813 (0.0799) Prec@1 86.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 17:09:03,592 Test: [2/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0719 (0.0773) Prec@1 88.000 (87.333) Prec@5 100.000 (99.667) +2022-11-14 17:09:03,600 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0756 (0.0768) Prec@1 88.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 17:09:03,607 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0724 (0.0759) Prec@1 88.000 (87.600) Prec@5 100.000 (99.600) +2022-11-14 17:09:03,614 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0235 (0.0672) Prec@1 95.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 17:09:03,622 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0672) Prec@1 88.000 (88.714) Prec@5 100.000 (99.714) +2022-11-14 17:09:03,630 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0687) Prec@1 87.000 (88.500) Prec@5 99.000 (99.625) +2022-11-14 17:09:03,637 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0690) Prec@1 90.000 (88.667) Prec@5 97.000 (99.333) +2022-11-14 17:09:03,645 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0955 (0.0716) Prec@1 85.000 (88.300) Prec@5 98.000 (99.200) +2022-11-14 17:09:03,653 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0688) Prec@1 95.000 (88.909) Prec@5 100.000 (99.273) +2022-11-14 17:09:03,661 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0968 (0.0711) Prec@1 86.000 (88.667) Prec@5 99.000 (99.250) +2022-11-14 17:09:03,668 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0699) Prec@1 89.000 (88.692) Prec@5 100.000 (99.308) +2022-11-14 17:09:03,676 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0705) Prec@1 89.000 (88.714) Prec@5 99.000 (99.286) +2022-11-14 17:09:03,684 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0707) Prec@1 90.000 (88.800) Prec@5 100.000 (99.333) +2022-11-14 17:09:03,692 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0708) Prec@1 86.000 (88.625) Prec@5 99.000 (99.312) +2022-11-14 17:09:03,700 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0696) Prec@1 93.000 (88.882) Prec@5 99.000 (99.294) +2022-11-14 17:09:03,708 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0713) Prec@1 84.000 (88.611) Prec@5 100.000 (99.333) +2022-11-14 17:09:03,716 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0725) Prec@1 84.000 (88.368) Prec@5 100.000 (99.368) +2022-11-14 17:09:03,724 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0727) Prec@1 87.000 (88.300) Prec@5 99.000 (99.350) +2022-11-14 17:09:03,731 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0732) Prec@1 85.000 (88.143) Prec@5 100.000 (99.381) +2022-11-14 17:09:03,742 Test: [21/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0743) Prec@1 86.000 (88.045) Prec@5 98.000 (99.318) +2022-11-14 17:09:03,752 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1146 (0.0760) Prec@1 83.000 (87.826) Prec@5 97.000 (99.217) +2022-11-14 17:09:03,761 Test: [23/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0761) Prec@1 90.000 (87.917) Prec@5 100.000 (99.250) +2022-11-14 17:09:03,771 Test: [24/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0763) Prec@1 87.000 (87.880) Prec@5 100.000 (99.280) +2022-11-14 17:09:03,783 Test: [25/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0772) Prec@1 82.000 (87.654) Prec@5 97.000 (99.192) +2022-11-14 17:09:03,793 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0699 (0.0770) Prec@1 90.000 (87.741) Prec@5 100.000 (99.222) +2022-11-14 17:09:03,802 Test: [27/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0556 (0.0762) Prec@1 91.000 (87.857) Prec@5 100.000 (99.250) +2022-11-14 17:09:03,810 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0760) Prec@1 89.000 (87.897) Prec@5 99.000 (99.241) +2022-11-14 17:09:03,821 Test: [29/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0760) Prec@1 86.000 (87.833) Prec@5 100.000 (99.267) +2022-11-14 17:09:03,832 Test: [30/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0755) Prec@1 89.000 (87.871) Prec@5 99.000 (99.258) +2022-11-14 17:09:03,840 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0753) Prec@1 92.000 (88.000) Prec@5 100.000 (99.281) +2022-11-14 17:09:03,848 Test: [32/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0648 (0.0750) Prec@1 90.000 (88.061) Prec@5 100.000 (99.303) +2022-11-14 17:09:03,859 Test: [33/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0748) Prec@1 91.000 (88.147) Prec@5 100.000 (99.324) +2022-11-14 17:09:03,869 Test: [34/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0774 (0.0749) Prec@1 87.000 (88.114) Prec@5 98.000 (99.286) +2022-11-14 17:09:03,877 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0609 (0.0745) Prec@1 92.000 (88.222) Prec@5 100.000 (99.306) +2022-11-14 17:09:03,885 Test: [36/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0883 (0.0749) Prec@1 85.000 (88.135) Prec@5 97.000 (99.243) +2022-11-14 17:09:03,895 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0868 (0.0752) Prec@1 86.000 (88.079) Prec@5 100.000 (99.263) +2022-11-14 17:09:03,906 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0594 (0.0748) Prec@1 92.000 (88.179) Prec@5 99.000 (99.256) +2022-11-14 17:09:03,914 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0649 (0.0745) Prec@1 90.000 (88.225) Prec@5 100.000 (99.275) +2022-11-14 17:09:03,922 Test: [40/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0954 (0.0750) Prec@1 85.000 (88.146) Prec@5 99.000 (99.268) +2022-11-14 17:09:03,933 Test: [41/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0806 (0.0752) Prec@1 87.000 (88.119) Prec@5 99.000 (99.262) +2022-11-14 17:09:03,943 Test: [42/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0749) Prec@1 89.000 (88.140) Prec@5 100.000 (99.279) +2022-11-14 17:09:03,952 Test: [43/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0749) Prec@1 89.000 (88.159) Prec@5 98.000 (99.250) +2022-11-14 17:09:03,964 Test: [44/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0613 (0.0746) Prec@1 90.000 (88.200) Prec@5 99.000 (99.244) +2022-11-14 17:09:03,974 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1081 (0.0753) Prec@1 83.000 (88.087) Prec@5 99.000 (99.239) +2022-11-14 17:09:03,986 Test: [46/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0754) Prec@1 86.000 (88.043) Prec@5 100.000 (99.255) +2022-11-14 17:09:03,998 Test: [47/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0760) Prec@1 83.000 (87.938) Prec@5 99.000 (99.250) +2022-11-14 17:09:04,010 Test: [48/100] Model Time 0.010 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0755) Prec@1 90.000 (87.980) Prec@5 99.000 (99.245) +2022-11-14 17:09:04,019 Test: [49/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0982 (0.0759) Prec@1 80.000 (87.820) Prec@5 100.000 (99.260) +2022-11-14 17:09:04,027 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0528 (0.0755) Prec@1 90.000 (87.863) Prec@5 100.000 (99.275) +2022-11-14 17:09:04,035 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0756) Prec@1 85.000 (87.808) Prec@5 100.000 (99.288) +2022-11-14 17:09:04,043 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0753) Prec@1 91.000 (87.868) Prec@5 100.000 (99.302) +2022-11-14 17:09:04,050 Test: [53/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0755) Prec@1 88.000 (87.870) Prec@5 98.000 (99.278) +2022-11-14 17:09:04,058 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0909 (0.0758) Prec@1 85.000 (87.818) Prec@5 100.000 (99.291) +2022-11-14 17:09:04,066 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0859 (0.0759) Prec@1 88.000 (87.821) Prec@5 98.000 (99.268) +2022-11-14 17:09:04,073 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0663 (0.0758) Prec@1 89.000 (87.842) Prec@5 100.000 (99.281) +2022-11-14 17:09:04,082 Test: [57/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0686 (0.0757) Prec@1 91.000 (87.897) Prec@5 99.000 (99.276) +2022-11-14 17:09:04,090 Test: [58/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1094 (0.0762) Prec@1 82.000 (87.797) Prec@5 99.000 (99.271) +2022-11-14 17:09:04,098 Test: [59/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0765) Prec@1 84.000 (87.733) Prec@5 100.000 (99.283) +2022-11-14 17:09:04,105 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0618 (0.0762) Prec@1 92.000 (87.803) Prec@5 100.000 (99.295) +2022-11-14 17:09:04,113 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0761) Prec@1 87.000 (87.790) Prec@5 99.000 (99.290) +2022-11-14 17:09:04,121 Test: [62/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0761) Prec@1 87.000 (87.778) Prec@5 100.000 (99.302) +2022-11-14 17:09:04,128 Test: [63/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0757) Prec@1 92.000 (87.844) Prec@5 99.000 (99.297) +2022-11-14 17:09:04,136 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1141 (0.0763) Prec@1 81.000 (87.738) Prec@5 99.000 (99.292) +2022-11-14 17:09:04,143 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0762) Prec@1 87.000 (87.727) Prec@5 99.000 (99.288) +2022-11-14 17:09:04,151 Test: [66/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0479 (0.0758) Prec@1 93.000 (87.806) Prec@5 99.000 (99.284) +2022-11-14 17:09:04,159 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0624 (0.0756) Prec@1 90.000 (87.838) Prec@5 99.000 (99.279) +2022-11-14 17:09:04,166 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0755) Prec@1 89.000 (87.855) Prec@5 99.000 (99.275) +2022-11-14 17:09:04,174 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0753) Prec@1 92.000 (87.914) Prec@5 98.000 (99.257) +2022-11-14 17:09:04,182 Test: [70/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1167 (0.0759) Prec@1 81.000 (87.817) Prec@5 99.000 (99.254) +2022-11-14 17:09:04,189 Test: [71/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0600 (0.0756) Prec@1 90.000 (87.847) Prec@5 99.000 (99.250) +2022-11-14 17:09:04,197 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0655 (0.0755) Prec@1 91.000 (87.890) Prec@5 99.000 (99.247) +2022-11-14 17:09:04,205 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0621 (0.0753) Prec@1 90.000 (87.919) Prec@5 99.000 (99.243) +2022-11-14 17:09:04,212 Test: [74/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1047 (0.0757) Prec@1 80.000 (87.813) Prec@5 98.000 (99.227) +2022-11-14 17:09:04,220 Test: [75/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0757) Prec@1 88.000 (87.816) Prec@5 99.000 (99.224) +2022-11-14 17:09:04,228 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0757) Prec@1 87.000 (87.805) Prec@5 98.000 (99.208) +2022-11-14 17:09:04,236 Test: [77/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0816 (0.0757) Prec@1 87.000 (87.795) Prec@5 98.000 (99.192) +2022-11-14 17:09:04,243 Test: [78/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0759) Prec@1 85.000 (87.759) Prec@5 100.000 (99.203) +2022-11-14 17:09:04,251 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0758) Prec@1 89.000 (87.775) Prec@5 99.000 (99.200) +2022-11-14 17:09:04,258 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0838 (0.0759) Prec@1 88.000 (87.778) Prec@5 98.000 (99.185) +2022-11-14 17:09:04,266 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0761) Prec@1 88.000 (87.780) Prec@5 100.000 (99.195) +2022-11-14 17:09:04,274 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0760) Prec@1 88.000 (87.783) Prec@5 99.000 (99.193) +2022-11-14 17:09:04,281 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0758) Prec@1 92.000 (87.833) Prec@5 100.000 (99.202) +2022-11-14 17:09:04,289 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0762) Prec@1 83.000 (87.776) Prec@5 100.000 (99.212) +2022-11-14 17:09:04,297 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0765) Prec@1 82.000 (87.709) Prec@5 100.000 (99.221) +2022-11-14 17:09:04,305 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0765) Prec@1 87.000 (87.701) Prec@5 99.000 (99.218) +2022-11-14 17:09:04,312 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0765) Prec@1 90.000 (87.727) Prec@5 99.000 (99.216) +2022-11-14 17:09:04,320 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0765) Prec@1 86.000 (87.708) Prec@5 100.000 (99.225) +2022-11-14 17:09:04,328 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0765) Prec@1 89.000 (87.722) Prec@5 100.000 (99.233) +2022-11-14 17:09:04,336 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0762) Prec@1 94.000 (87.791) Prec@5 100.000 (99.242) +2022-11-14 17:09:04,344 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0761) Prec@1 91.000 (87.826) Prec@5 100.000 (99.250) +2022-11-14 17:09:04,351 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0762) Prec@1 86.000 (87.806) Prec@5 100.000 (99.258) +2022-11-14 17:09:04,359 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0762) Prec@1 88.000 (87.809) Prec@5 99.000 (99.255) +2022-11-14 17:09:04,366 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0763) Prec@1 86.000 (87.789) Prec@5 99.000 (99.253) +2022-11-14 17:09:04,374 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0763) Prec@1 89.000 (87.802) Prec@5 100.000 (99.260) +2022-11-14 17:09:04,381 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0759) Prec@1 93.000 (87.856) Prec@5 100.000 (99.268) +2022-11-14 17:09:04,389 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0762) Prec@1 87.000 (87.847) Prec@5 99.000 (99.265) +2022-11-14 17:09:04,396 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0763) Prec@1 87.000 (87.838) Prec@5 98.000 (99.253) +2022-11-14 17:09:04,403 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0763) Prec@1 88.000 (87.840) Prec@5 100.000 (99.260) +2022-11-14 17:09:04,469 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:09:04,790 Epoch: [475][0/500] Time 0.026 (0.026) Data 0.239 (0.239) Loss 0.0441 (0.0441) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:04,985 Epoch: [475][10/500] Time 0.017 (0.018) Data 0.001 (0.023) Loss 0.0457 (0.0449) Prec@1 92.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 17:09:05,174 Epoch: [475][20/500] Time 0.015 (0.017) Data 0.001 (0.013) Loss 0.0463 (0.0454) Prec@1 94.000 (92.333) Prec@5 100.000 (100.000) +2022-11-14 17:09:05,361 Epoch: [475][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0170 (0.0383) Prec@1 98.000 (93.750) Prec@5 100.000 (100.000) +2022-11-14 17:09:05,550 Epoch: [475][40/500] Time 0.016 (0.017) Data 0.001 (0.007) Loss 0.0274 (0.0361) Prec@1 94.000 (93.800) Prec@5 100.000 (100.000) +2022-11-14 17:09:05,743 Epoch: [475][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0196 (0.0333) Prec@1 98.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:09:05,940 Epoch: [475][60/500] Time 0.015 (0.017) Data 0.002 (0.005) Loss 0.0253 (0.0322) Prec@1 95.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 17:09:06,137 Epoch: [475][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0204 (0.0307) Prec@1 95.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 17:09:06,332 Epoch: [475][80/500] Time 0.015 (0.017) Data 0.002 (0.005) Loss 0.0203 (0.0296) Prec@1 97.000 (94.889) Prec@5 100.000 (100.000) +2022-11-14 17:09:06,524 Epoch: [475][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0416 (0.0308) Prec@1 93.000 (94.700) Prec@5 100.000 (100.000) +2022-11-14 17:09:06,713 Epoch: [475][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0221 (0.0300) Prec@1 95.000 (94.727) Prec@5 100.000 (100.000) +2022-11-14 17:09:06,901 Epoch: [475][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0354 (0.0304) Prec@1 93.000 (94.583) Prec@5 100.000 (100.000) +2022-11-14 17:09:07,088 Epoch: [475][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0506 (0.0320) Prec@1 92.000 (94.385) Prec@5 100.000 (100.000) +2022-11-14 17:09:07,277 Epoch: [475][130/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0203 (0.0312) Prec@1 97.000 (94.571) Prec@5 100.000 (100.000) +2022-11-14 17:09:07,464 Epoch: [475][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0375 (0.0316) Prec@1 94.000 (94.533) Prec@5 100.000 (100.000) +2022-11-14 17:09:07,653 Epoch: [475][150/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0206 (0.0309) Prec@1 97.000 (94.688) Prec@5 100.000 (100.000) +2022-11-14 17:09:07,842 Epoch: [475][160/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0169 (0.0301) Prec@1 98.000 (94.882) Prec@5 100.000 (100.000) +2022-11-14 17:09:08,034 Epoch: [475][170/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0159 (0.0293) Prec@1 97.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:08,226 Epoch: [475][180/500] Time 0.018 (0.017) Data 0.002 (0.003) Loss 0.0263 (0.0291) Prec@1 96.000 (95.053) Prec@5 100.000 (100.000) +2022-11-14 17:09:08,434 Epoch: [475][190/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0255 (0.0289) Prec@1 95.000 (95.050) Prec@5 100.000 (100.000) +2022-11-14 17:09:08,696 Epoch: [475][200/500] Time 0.025 (0.017) Data 0.002 (0.003) Loss 0.0291 (0.0290) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:08,961 Epoch: [475][210/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0351 (0.0292) Prec@1 94.000 (94.955) Prec@5 100.000 (100.000) +2022-11-14 17:09:09,234 Epoch: [475][220/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0186 (0.0288) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:09,503 Epoch: [475][230/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0354 (0.0290) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:09,774 Epoch: [475][240/500] Time 0.024 (0.018) Data 0.003 (0.003) Loss 0.0222 (0.0288) Prec@1 96.000 (95.040) Prec@5 100.000 (100.000) +2022-11-14 17:09:10,048 Epoch: [475][250/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0251 (0.0286) Prec@1 96.000 (95.077) Prec@5 99.000 (99.962) +2022-11-14 17:09:10,325 Epoch: [475][260/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0181 (0.0282) Prec@1 98.000 (95.185) Prec@5 100.000 (99.963) +2022-11-14 17:09:10,600 Epoch: [475][270/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0138 (0.0277) Prec@1 98.000 (95.286) Prec@5 100.000 (99.964) +2022-11-14 17:09:10,878 Epoch: [475][280/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0357 (0.0280) Prec@1 95.000 (95.276) Prec@5 100.000 (99.966) +2022-11-14 17:09:11,157 Epoch: [475][290/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0189 (0.0277) Prec@1 97.000 (95.333) Prec@5 100.000 (99.967) +2022-11-14 17:09:11,433 Epoch: [475][300/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0213 (0.0275) Prec@1 97.000 (95.387) Prec@5 100.000 (99.968) +2022-11-14 17:09:11,704 Epoch: [475][310/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0415 (0.0279) Prec@1 93.000 (95.312) Prec@5 100.000 (99.969) +2022-11-14 17:09:11,980 Epoch: [475][320/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0294 (0.0280) Prec@1 96.000 (95.333) Prec@5 99.000 (99.939) +2022-11-14 17:09:12,255 Epoch: [475][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0084 (0.0274) Prec@1 98.000 (95.412) Prec@5 100.000 (99.941) +2022-11-14 17:09:12,531 Epoch: [475][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0268 (0.0274) Prec@1 96.000 (95.429) Prec@5 99.000 (99.914) +2022-11-14 17:09:12,796 Epoch: [475][350/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0200 (0.0272) Prec@1 97.000 (95.472) Prec@5 100.000 (99.917) +2022-11-14 17:09:13,063 Epoch: [475][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0551 (0.0279) Prec@1 91.000 (95.351) Prec@5 100.000 (99.919) +2022-11-14 17:09:13,335 Epoch: [475][370/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0359 (0.0281) Prec@1 95.000 (95.342) Prec@5 100.000 (99.921) +2022-11-14 17:09:13,609 Epoch: [475][380/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0187 (0.0279) Prec@1 97.000 (95.385) Prec@5 100.000 (99.923) +2022-11-14 17:09:13,886 Epoch: [475][390/500] Time 0.020 (0.021) Data 0.002 (0.002) Loss 0.0097 (0.0274) Prec@1 99.000 (95.475) Prec@5 100.000 (99.925) +2022-11-14 17:09:14,158 Epoch: [475][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0433 (0.0278) Prec@1 92.000 (95.390) Prec@5 100.000 (99.927) +2022-11-14 17:09:14,425 Epoch: [475][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0192 (0.0276) Prec@1 98.000 (95.452) Prec@5 100.000 (99.929) +2022-11-14 17:09:14,696 Epoch: [475][420/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0420 (0.0280) Prec@1 93.000 (95.395) Prec@5 100.000 (99.930) +2022-11-14 17:09:14,967 Epoch: [475][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0193 (0.0278) Prec@1 96.000 (95.409) Prec@5 100.000 (99.932) +2022-11-14 17:09:15,236 Epoch: [475][440/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0270 (0.0277) Prec@1 96.000 (95.422) Prec@5 99.000 (99.911) +2022-11-14 17:09:15,497 Epoch: [475][450/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0288 (0.0278) Prec@1 95.000 (95.413) Prec@5 100.000 (99.913) +2022-11-14 17:09:15,769 Epoch: [475][460/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0265 (0.0277) Prec@1 97.000 (95.447) Prec@5 100.000 (99.915) +2022-11-14 17:09:16,036 Epoch: [475][470/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0568 (0.0283) Prec@1 90.000 (95.333) Prec@5 97.000 (99.854) +2022-11-14 17:09:16,300 Epoch: [475][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0211 (0.0282) Prec@1 98.000 (95.388) Prec@5 100.000 (99.857) +2022-11-14 17:09:16,569 Epoch: [475][490/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0488 (0.0286) Prec@1 93.000 (95.340) Prec@5 100.000 (99.860) +2022-11-14 17:09:16,809 Epoch: [475][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0317 (0.0287) Prec@1 97.000 (95.373) Prec@5 99.000 (99.843) +2022-11-14 17:09:17,111 Test: [0/100] Model Time 0.014 (0.014) Loss Time 0.000 (0.000) Loss 0.0610 (0.0610) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:17,118 Test: [1/100] Model Time 0.006 (0.010) Loss Time 0.000 (0.000) Loss 0.0826 (0.0718) Prec@1 88.000 (88.000) Prec@5 99.000 (99.500) +2022-11-14 17:09:17,128 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0795 (0.0744) Prec@1 87.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 17:09:17,140 Test: [3/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0755 (0.0746) Prec@1 88.000 (87.750) Prec@5 100.000 (99.750) +2022-11-14 17:09:17,147 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0647 (0.0726) Prec@1 85.000 (87.200) Prec@5 100.000 (99.800) +2022-11-14 17:09:17,154 Test: [5/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0510 (0.0690) Prec@1 90.000 (87.667) Prec@5 100.000 (99.833) +2022-11-14 17:09:17,163 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0780 (0.0703) Prec@1 89.000 (87.857) Prec@5 100.000 (99.857) +2022-11-14 17:09:17,172 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.1078 (0.0750) Prec@1 82.000 (87.125) Prec@5 99.000 (99.750) +2022-11-14 17:09:17,179 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1015 (0.0779) Prec@1 82.000 (86.556) Prec@5 99.000 (99.667) +2022-11-14 17:09:17,187 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0785) Prec@1 87.000 (86.600) Prec@5 99.000 (99.600) +2022-11-14 17:09:17,195 Test: [10/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0477 (0.0757) Prec@1 93.000 (87.182) Prec@5 100.000 (99.636) +2022-11-14 17:09:17,205 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0874 (0.0767) Prec@1 85.000 (87.000) Prec@5 100.000 (99.667) +2022-11-14 17:09:17,213 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0762) Prec@1 89.000 (87.154) Prec@5 100.000 (99.692) +2022-11-14 17:09:17,221 Test: [13/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0710 (0.0758) Prec@1 90.000 (87.357) Prec@5 99.000 (99.643) +2022-11-14 17:09:17,230 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0738 (0.0757) Prec@1 86.000 (87.267) Prec@5 100.000 (99.667) +2022-11-14 17:09:17,240 Test: [15/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0741 (0.0756) Prec@1 89.000 (87.375) Prec@5 99.000 (99.625) +2022-11-14 17:09:17,247 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0744) Prec@1 92.000 (87.647) Prec@5 99.000 (99.588) +2022-11-14 17:09:17,255 Test: [17/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1095 (0.0764) Prec@1 81.000 (87.278) Prec@5 100.000 (99.611) +2022-11-14 17:09:17,264 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0767) Prec@1 86.000 (87.211) Prec@5 99.000 (99.579) +2022-11-14 17:09:17,274 Test: [19/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1011 (0.0779) Prec@1 86.000 (87.150) Prec@5 97.000 (99.450) +2022-11-14 17:09:17,282 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0781) Prec@1 88.000 (87.190) Prec@5 99.000 (99.429) +2022-11-14 17:09:17,289 Test: [21/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0786) Prec@1 85.000 (87.091) Prec@5 99.000 (99.409) +2022-11-14 17:09:17,299 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.0803) Prec@1 83.000 (86.913) Prec@5 100.000 (99.435) +2022-11-14 17:09:17,308 Test: [23/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0805) Prec@1 86.000 (86.875) Prec@5 99.000 (99.417) +2022-11-14 17:09:17,316 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0804) Prec@1 89.000 (86.960) Prec@5 100.000 (99.440) +2022-11-14 17:09:17,324 Test: [25/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0805) Prec@1 88.000 (87.000) Prec@5 98.000 (99.385) +2022-11-14 17:09:17,333 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0500 (0.0793) Prec@1 93.000 (87.222) Prec@5 100.000 (99.407) +2022-11-14 17:09:17,343 Test: [27/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0689 (0.0790) Prec@1 88.000 (87.250) Prec@5 99.000 (99.393) +2022-11-14 17:09:17,350 Test: [28/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0782) Prec@1 91.000 (87.379) Prec@5 99.000 (99.379) +2022-11-14 17:09:17,358 Test: [29/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0783) Prec@1 88.000 (87.400) Prec@5 99.000 (99.367) +2022-11-14 17:09:17,367 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0784) Prec@1 85.000 (87.323) Prec@5 100.000 (99.387) +2022-11-14 17:09:17,377 Test: [31/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0782) Prec@1 89.000 (87.375) Prec@5 99.000 (99.375) +2022-11-14 17:09:17,384 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0876 (0.0785) Prec@1 85.000 (87.303) Prec@5 100.000 (99.394) +2022-11-14 17:09:17,392 Test: [33/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1051 (0.0793) Prec@1 82.000 (87.147) Prec@5 100.000 (99.412) +2022-11-14 17:09:17,402 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0796) Prec@1 84.000 (87.057) Prec@5 97.000 (99.343) +2022-11-14 17:09:17,411 Test: [35/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0790 (0.0796) Prec@1 89.000 (87.111) Prec@5 98.000 (99.306) +2022-11-14 17:09:17,419 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0790) Prec@1 90.000 (87.189) Prec@5 100.000 (99.324) +2022-11-14 17:09:17,426 Test: [37/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0894 (0.0793) Prec@1 84.000 (87.105) Prec@5 99.000 (99.316) +2022-11-14 17:09:17,436 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0787) Prec@1 92.000 (87.231) Prec@5 98.000 (99.282) +2022-11-14 17:09:17,445 Test: [39/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0606 (0.0782) Prec@1 90.000 (87.300) Prec@5 100.000 (99.300) +2022-11-14 17:09:17,453 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1021 (0.0788) Prec@1 85.000 (87.244) Prec@5 99.000 (99.293) +2022-11-14 17:09:17,460 Test: [41/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0789) Prec@1 88.000 (87.262) Prec@5 100.000 (99.310) +2022-11-14 17:09:17,469 Test: [42/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0540 (0.0783) Prec@1 91.000 (87.349) Prec@5 99.000 (99.302) +2022-11-14 17:09:17,479 Test: [43/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0554 (0.0778) Prec@1 91.000 (87.432) Prec@5 99.000 (99.295) +2022-11-14 17:09:17,486 Test: [44/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0559 (0.0773) Prec@1 88.000 (87.444) Prec@5 100.000 (99.311) +2022-11-14 17:09:17,494 Test: [45/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1254 (0.0783) Prec@1 80.000 (87.283) Prec@5 99.000 (99.304) +2022-11-14 17:09:17,503 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0781) Prec@1 89.000 (87.319) Prec@5 100.000 (99.319) +2022-11-14 17:09:17,513 Test: [47/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0997 (0.0785) Prec@1 87.000 (87.312) Prec@5 99.000 (99.312) +2022-11-14 17:09:17,520 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0421 (0.0778) Prec@1 91.000 (87.388) Prec@5 100.000 (99.327) +2022-11-14 17:09:17,528 Test: [49/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1076 (0.0784) Prec@1 85.000 (87.340) Prec@5 100.000 (99.340) +2022-11-14 17:09:17,537 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0531 (0.0779) Prec@1 90.000 (87.392) Prec@5 100.000 (99.353) +2022-11-14 17:09:17,547 Test: [51/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0766 (0.0779) Prec@1 88.000 (87.404) Prec@5 99.000 (99.346) +2022-11-14 17:09:17,555 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0521 (0.0774) Prec@1 91.000 (87.472) Prec@5 99.000 (99.340) +2022-11-14 17:09:17,562 Test: [53/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0773) Prec@1 88.000 (87.481) Prec@5 98.000 (99.315) +2022-11-14 17:09:17,572 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0775) Prec@1 84.000 (87.418) Prec@5 100.000 (99.327) +2022-11-14 17:09:17,583 Test: [55/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0770) Prec@1 94.000 (87.536) Prec@5 99.000 (99.321) +2022-11-14 17:09:17,590 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0745 (0.0769) Prec@1 86.000 (87.509) Prec@5 99.000 (99.316) +2022-11-14 17:09:17,598 Test: [57/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0503 (0.0765) Prec@1 93.000 (87.603) Prec@5 100.000 (99.328) +2022-11-14 17:09:17,607 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0766) Prec@1 88.000 (87.610) Prec@5 99.000 (99.322) +2022-11-14 17:09:17,617 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0764) Prec@1 90.000 (87.650) Prec@5 99.000 (99.317) +2022-11-14 17:09:17,624 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0931 (0.0767) Prec@1 88.000 (87.656) Prec@5 100.000 (99.328) +2022-11-14 17:09:17,632 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0765) Prec@1 88.000 (87.661) Prec@5 100.000 (99.339) +2022-11-14 17:09:17,641 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0765) Prec@1 88.000 (87.667) Prec@5 99.000 (99.333) +2022-11-14 17:09:17,651 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0373 (0.0759) Prec@1 94.000 (87.766) Prec@5 100.000 (99.344) +2022-11-14 17:09:17,658 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0763) Prec@1 83.000 (87.692) Prec@5 99.000 (99.338) +2022-11-14 17:09:17,666 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0988 (0.0766) Prec@1 84.000 (87.636) Prec@5 98.000 (99.318) +2022-11-14 17:09:17,676 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0391 (0.0761) Prec@1 94.000 (87.731) Prec@5 99.000 (99.313) +2022-11-14 17:09:17,685 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0761) Prec@1 88.000 (87.735) Prec@5 98.000 (99.294) +2022-11-14 17:09:17,693 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0763) Prec@1 86.000 (87.710) Prec@5 99.000 (99.290) +2022-11-14 17:09:17,700 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0844 (0.0764) Prec@1 87.000 (87.700) Prec@5 97.000 (99.257) +2022-11-14 17:09:17,709 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0907 (0.0766) Prec@1 88.000 (87.704) Prec@5 99.000 (99.254) +2022-11-14 17:09:17,719 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0683 (0.0765) Prec@1 91.000 (87.750) Prec@5 99.000 (99.250) +2022-11-14 17:09:17,726 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0342 (0.0759) Prec@1 95.000 (87.849) Prec@5 100.000 (99.260) +2022-11-14 17:09:17,734 Test: [73/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0438 (0.0755) Prec@1 94.000 (87.932) Prec@5 100.000 (99.270) +2022-11-14 17:09:17,743 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1264 (0.0761) Prec@1 80.000 (87.827) Prec@5 99.000 (99.267) +2022-11-14 17:09:17,752 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0597 (0.0759) Prec@1 93.000 (87.895) Prec@5 99.000 (99.263) +2022-11-14 17:09:17,760 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0676 (0.0758) Prec@1 89.000 (87.909) Prec@5 98.000 (99.247) +2022-11-14 17:09:17,768 Test: [77/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0838 (0.0759) Prec@1 86.000 (87.885) Prec@5 99.000 (99.244) +2022-11-14 17:09:17,777 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0761) Prec@1 85.000 (87.848) Prec@5 100.000 (99.253) +2022-11-14 17:09:17,787 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0762) Prec@1 87.000 (87.838) Prec@5 100.000 (99.263) +2022-11-14 17:09:17,794 Test: [80/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0761) Prec@1 90.000 (87.864) Prec@5 100.000 (99.272) +2022-11-14 17:09:17,802 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0759) Prec@1 89.000 (87.878) Prec@5 98.000 (99.256) +2022-11-14 17:09:17,812 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0761) Prec@1 85.000 (87.843) Prec@5 100.000 (99.265) +2022-11-14 17:09:17,822 Test: 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Loss 0.0801 (0.0764) Prec@1 88.000 (87.756) Prec@5 99.000 (99.289) +2022-11-14 17:09:17,882 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0690 (0.0763) Prec@1 90.000 (87.780) Prec@5 100.000 (99.297) +2022-11-14 17:09:17,892 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0417 (0.0759) Prec@1 94.000 (87.848) Prec@5 99.000 (99.293) +2022-11-14 17:09:17,899 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0761) Prec@1 86.000 (87.828) Prec@5 99.000 (99.290) +2022-11-14 17:09:17,907 Test: [93/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0823 (0.0762) Prec@1 87.000 (87.819) Prec@5 98.000 (99.277) +2022-11-14 17:09:17,915 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0999 (0.0764) Prec@1 83.000 (87.768) Prec@5 97.000 (99.253) +2022-11-14 17:09:17,922 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0638 (0.0763) Prec@1 89.000 (87.781) Prec@5 100.000 (99.260) +2022-11-14 17:09:17,930 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0574 (0.0761) Prec@1 91.000 (87.814) Prec@5 99.000 (99.258) +2022-11-14 17:09:17,937 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0762) Prec@1 87.000 (87.806) Prec@5 96.000 (99.224) +2022-11-14 17:09:17,945 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1112 (0.0766) Prec@1 83.000 (87.758) Prec@5 97.000 (99.202) +2022-11-14 17:09:17,952 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0707 (0.0765) Prec@1 90.000 (87.780) Prec@5 99.000 (99.200) +2022-11-14 17:09:18,014 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:09:18,326 Epoch: [476][0/500] Time 0.023 (0.023) Data 0.234 (0.234) Loss 0.0340 (0.0340) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:18,523 Epoch: [476][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0363 (0.0351) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:09:18,714 Epoch: [476][20/500] Time 0.016 (0.017) Data 0.002 (0.013) Loss 0.0182 (0.0295) Prec@1 98.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:18,903 Epoch: [476][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0190 (0.0269) Prec@1 98.000 (95.750) Prec@5 99.000 (99.750) +2022-11-14 17:09:19,095 Epoch: [476][40/500] Time 0.019 (0.017) Data 0.002 (0.007) Loss 0.0333 (0.0282) Prec@1 96.000 (95.800) Prec@5 100.000 (99.800) +2022-11-14 17:09:19,291 Epoch: [476][50/500] Time 0.016 (0.017) Data 0.001 (0.006) Loss 0.0376 (0.0297) Prec@1 92.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 17:09:19,480 Epoch: [476][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0411 (0.0314) Prec@1 94.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:09:19,671 Epoch: [476][70/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0204 (0.0300) Prec@1 96.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 17:09:19,863 Epoch: [476][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0225 (0.0291) Prec@1 96.000 (95.222) Prec@5 99.000 (99.778) +2022-11-14 17:09:20,055 Epoch: [476][90/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0536 (0.0316) Prec@1 91.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 17:09:20,249 Epoch: [476][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0307 (0.0315) Prec@1 94.000 (94.727) Prec@5 100.000 (99.818) +2022-11-14 17:09:20,446 Epoch: [476][110/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0245 (0.0309) Prec@1 97.000 (94.917) Prec@5 100.000 (99.833) +2022-11-14 17:09:20,644 Epoch: [476][120/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0308 (0.0309) Prec@1 96.000 (95.000) Prec@5 100.000 (99.846) +2022-11-14 17:09:20,914 Epoch: [476][130/500] Time 0.027 (0.017) Data 0.002 (0.003) Loss 0.0390 (0.0315) Prec@1 95.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:09:21,203 Epoch: [476][140/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0403 (0.0321) Prec@1 94.000 (94.933) Prec@5 99.000 (99.800) +2022-11-14 17:09:21,495 Epoch: [476][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0478 (0.0331) Prec@1 91.000 (94.688) Prec@5 100.000 (99.812) +2022-11-14 17:09:21,790 Epoch: [476][160/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0262 (0.0327) Prec@1 95.000 (94.706) Prec@5 100.000 (99.824) +2022-11-14 17:09:22,074 Epoch: [476][170/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0244 (0.0322) Prec@1 96.000 (94.778) Prec@5 100.000 (99.833) +2022-11-14 17:09:22,358 Epoch: [476][180/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0328 (0.0322) Prec@1 95.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 17:09:22,648 Epoch: [476][190/500] Time 0.028 (0.020) Data 0.001 (0.003) Loss 0.0447 (0.0329) Prec@1 92.000 (94.650) Prec@5 100.000 (99.850) +2022-11-14 17:09:22,941 Epoch: [476][200/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0313 (0.0328) Prec@1 97.000 (94.762) Prec@5 100.000 (99.857) +2022-11-14 17:09:23,238 Epoch: [476][210/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0435 (0.0333) Prec@1 94.000 (94.727) Prec@5 100.000 (99.864) +2022-11-14 17:09:23,530 Epoch: [476][220/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0336 (0.0333) Prec@1 96.000 (94.783) Prec@5 99.000 (99.826) +2022-11-14 17:09:23,818 Epoch: [476][230/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0401 (0.0336) Prec@1 93.000 (94.708) Prec@5 100.000 (99.833) +2022-11-14 17:09:24,111 Epoch: [476][240/500] Time 0.031 (0.021) Data 0.001 (0.003) Loss 0.0496 (0.0342) Prec@1 90.000 (94.520) Prec@5 100.000 (99.840) +2022-11-14 17:09:24,397 Epoch: [476][250/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0242 (0.0338) Prec@1 97.000 (94.615) Prec@5 100.000 (99.846) +2022-11-14 17:09:24,681 Epoch: [476][260/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0480 (0.0344) Prec@1 92.000 (94.519) Prec@5 100.000 (99.852) +2022-11-14 17:09:24,974 Epoch: [476][270/500] Time 0.023 (0.022) Data 0.002 (0.003) Loss 0.0363 (0.0344) Prec@1 92.000 (94.429) Prec@5 99.000 (99.821) +2022-11-14 17:09:25,259 Epoch: [476][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0293 (0.0342) Prec@1 92.000 (94.345) Prec@5 100.000 (99.828) +2022-11-14 17:09:25,543 Epoch: [476][290/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0229 (0.0339) Prec@1 97.000 (94.433) Prec@5 100.000 (99.833) +2022-11-14 17:09:25,825 Epoch: [476][300/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0275 (0.0337) Prec@1 95.000 (94.452) Prec@5 100.000 (99.839) +2022-11-14 17:09:26,116 Epoch: [476][310/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0223 (0.0333) Prec@1 96.000 (94.500) Prec@5 100.000 (99.844) +2022-11-14 17:09:26,401 Epoch: [476][320/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0511 (0.0338) Prec@1 92.000 (94.424) Prec@5 100.000 (99.848) +2022-11-14 17:09:26,685 Epoch: [476][330/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0351 (0.0339) Prec@1 93.000 (94.382) Prec@5 100.000 (99.853) +2022-11-14 17:09:26,969 Epoch: [476][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0428 (0.0341) Prec@1 94.000 (94.371) Prec@5 100.000 (99.857) +2022-11-14 17:09:27,258 Epoch: [476][350/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0318 (0.0341) Prec@1 94.000 (94.361) Prec@5 100.000 (99.861) +2022-11-14 17:09:27,543 Epoch: [476][360/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0135 (0.0335) Prec@1 99.000 (94.486) Prec@5 100.000 (99.865) +2022-11-14 17:09:27,834 Epoch: [476][370/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0338 (0.0335) Prec@1 95.000 (94.500) Prec@5 100.000 (99.868) +2022-11-14 17:09:28,121 Epoch: [476][380/500] Time 0.031 (0.023) Data 0.002 (0.002) Loss 0.0327 (0.0335) Prec@1 93.000 (94.462) Prec@5 100.000 (99.872) +2022-11-14 17:09:28,405 Epoch: [476][390/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0425 (0.0337) Prec@1 93.000 (94.425) Prec@5 100.000 (99.875) +2022-11-14 17:09:28,691 Epoch: [476][400/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0135 (0.0332) Prec@1 97.000 (94.488) Prec@5 100.000 (99.878) +2022-11-14 17:09:28,978 Epoch: [476][410/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0335 (0.0332) Prec@1 94.000 (94.476) Prec@5 100.000 (99.881) +2022-11-14 17:09:29,268 Epoch: [476][420/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0291 (0.0331) Prec@1 95.000 (94.488) Prec@5 100.000 (99.884) +2022-11-14 17:09:29,553 Epoch: [476][430/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0465 (0.0334) Prec@1 90.000 (94.386) Prec@5 100.000 (99.886) +2022-11-14 17:09:29,836 Epoch: [476][440/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0284 (0.0333) Prec@1 96.000 (94.422) Prec@5 100.000 (99.889) +2022-11-14 17:09:30,126 Epoch: [476][450/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0220 (0.0331) Prec@1 97.000 (94.478) Prec@5 100.000 (99.891) +2022-11-14 17:09:30,405 Epoch: [476][460/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0163 (0.0327) Prec@1 98.000 (94.553) Prec@5 100.000 (99.894) +2022-11-14 17:09:30,686 Epoch: [476][470/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0364 (0.0328) Prec@1 95.000 (94.562) Prec@5 100.000 (99.896) +2022-11-14 17:09:30,971 Epoch: [476][480/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0141 (0.0324) Prec@1 97.000 (94.612) Prec@5 100.000 (99.898) +2022-11-14 17:09:31,257 Epoch: [476][490/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0211 (0.0322) Prec@1 96.000 (94.640) Prec@5 100.000 (99.900) +2022-11-14 17:09:31,511 Epoch: [476][499/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0248 (0.0321) Prec@1 96.000 (94.667) Prec@5 100.000 (99.902) +2022-11-14 17:09:31,811 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0485 (0.0485) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:31,820 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0741 (0.0613) Prec@1 88.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:09:31,830 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0646 (0.0624) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:31,840 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0678) Prec@1 85.000 (88.750) Prec@5 98.000 (99.500) +2022-11-14 17:09:31,846 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0889 (0.0720) Prec@1 86.000 (88.200) Prec@5 98.000 (99.200) +2022-11-14 17:09:31,853 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0692) Prec@1 90.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 17:09:31,860 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0675) Prec@1 93.000 (89.143) Prec@5 99.000 (99.286) +2022-11-14 17:09:31,868 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0921 (0.0706) Prec@1 86.000 (88.750) Prec@5 99.000 (99.250) +2022-11-14 17:09:31,875 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0723) Prec@1 87.000 (88.556) Prec@5 99.000 (99.222) +2022-11-14 17:09:31,882 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0722) Prec@1 89.000 (88.600) Prec@5 99.000 (99.200) +2022-11-14 17:09:31,890 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0717) Prec@1 90.000 (88.727) Prec@5 100.000 (99.273) +2022-11-14 17:09:31,898 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0716) Prec@1 91.000 (88.917) Prec@5 100.000 (99.333) +2022-11-14 17:09:31,905 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0700) Prec@1 89.000 (88.923) Prec@5 99.000 (99.308) +2022-11-14 17:09:31,913 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0693) Prec@1 90.000 (89.000) Prec@5 99.000 (99.286) +2022-11-14 17:09:31,921 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0700) Prec@1 87.000 (88.867) Prec@5 99.000 (99.267) +2022-11-14 17:09:31,928 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0693) Prec@1 90.000 (88.938) Prec@5 99.000 (99.250) +2022-11-14 17:09:31,936 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0681) Prec@1 93.000 (89.176) Prec@5 98.000 (99.176) +2022-11-14 17:09:31,944 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1121 (0.0706) Prec@1 85.000 (88.944) Prec@5 100.000 (99.222) +2022-11-14 17:09:31,952 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0716) Prec@1 84.000 (88.684) Prec@5 100.000 (99.263) +2022-11-14 17:09:31,959 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0727) Prec@1 83.000 (88.400) Prec@5 99.000 (99.250) +2022-11-14 17:09:31,967 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0724) Prec@1 89.000 (88.429) Prec@5 99.000 (99.238) +2022-11-14 17:09:31,976 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0733) Prec@1 86.000 (88.318) Prec@5 98.000 (99.182) +2022-11-14 17:09:31,984 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0744) Prec@1 85.000 (88.174) Prec@5 100.000 (99.217) +2022-11-14 17:09:31,992 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0746) Prec@1 88.000 (88.167) Prec@5 100.000 (99.250) +2022-11-14 17:09:31,999 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0940 (0.0753) Prec@1 87.000 (88.120) Prec@5 99.000 (99.240) +2022-11-14 17:09:32,007 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1040 (0.0764) Prec@1 84.000 (87.962) Prec@5 99.000 (99.231) +2022-11-14 17:09:32,014 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0390 (0.0751) Prec@1 94.000 (88.185) Prec@5 100.000 (99.259) +2022-11-14 17:09:32,022 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0748) Prec@1 90.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 17:09:32,030 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0748) Prec@1 88.000 (88.241) Prec@5 99.000 (99.241) +2022-11-14 17:09:32,037 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0752) Prec@1 87.000 (88.200) Prec@5 99.000 (99.233) +2022-11-14 17:09:32,045 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0754) Prec@1 84.000 (88.065) Prec@5 100.000 (99.258) +2022-11-14 17:09:32,053 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0750) Prec@1 90.000 (88.125) Prec@5 100.000 (99.281) +2022-11-14 17:09:32,060 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0956 (0.0756) Prec@1 85.000 (88.030) Prec@5 100.000 (99.303) +2022-11-14 17:09:32,068 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0759) Prec@1 84.000 (87.912) Prec@5 100.000 (99.324) +2022-11-14 17:09:32,076 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0760) Prec@1 87.000 (87.886) Prec@5 97.000 (99.257) +2022-11-14 17:09:32,085 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0758) Prec@1 89.000 (87.917) Prec@5 100.000 (99.278) +2022-11-14 17:09:32,093 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0757) Prec@1 89.000 (87.946) Prec@5 99.000 (99.270) +2022-11-14 17:09:32,100 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1134 (0.0767) Prec@1 82.000 (87.789) Prec@5 100.000 (99.289) +2022-11-14 17:09:32,108 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0759) Prec@1 93.000 (87.923) Prec@5 99.000 (99.282) +2022-11-14 17:09:32,116 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0544 (0.0754) Prec@1 90.000 (87.975) Prec@5 100.000 (99.300) +2022-11-14 17:09:32,124 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1163 (0.0764) Prec@1 83.000 (87.854) Prec@5 98.000 (99.268) +2022-11-14 17:09:32,131 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0844 (0.0766) Prec@1 87.000 (87.833) Prec@5 99.000 (99.262) +2022-11-14 17:09:32,139 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0763) Prec@1 91.000 (87.907) Prec@5 99.000 (99.256) +2022-11-14 17:09:32,147 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0763) Prec@1 88.000 (87.909) Prec@5 99.000 (99.250) +2022-11-14 17:09:32,155 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0654 (0.0760) Prec@1 89.000 (87.933) Prec@5 100.000 (99.267) +2022-11-14 17:09:32,162 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0764) Prec@1 84.000 (87.848) Prec@5 100.000 (99.283) +2022-11-14 17:09:32,170 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0765) Prec@1 87.000 (87.830) Prec@5 100.000 (99.298) +2022-11-14 17:09:32,177 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0771) Prec@1 83.000 (87.729) Prec@5 97.000 (99.250) +2022-11-14 17:09:32,185 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0423 (0.0764) Prec@1 94.000 (87.857) Prec@5 100.000 (99.265) +2022-11-14 17:09:32,193 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0772) Prec@1 84.000 (87.780) Prec@5 100.000 (99.280) +2022-11-14 17:09:32,200 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0769) Prec@1 89.000 (87.804) Prec@5 100.000 (99.294) +2022-11-14 17:09:32,208 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0767) Prec@1 88.000 (87.808) Prec@5 99.000 (99.288) +2022-11-14 17:09:32,216 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0765) Prec@1 87.000 (87.792) Prec@5 100.000 (99.302) +2022-11-14 17:09:32,223 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0763) Prec@1 89.000 (87.815) Prec@5 100.000 (99.315) +2022-11-14 17:09:32,231 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0849 (0.0764) Prec@1 85.000 (87.764) Prec@5 98.000 (99.291) +2022-11-14 17:09:32,239 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0765) Prec@1 87.000 (87.750) Prec@5 98.000 (99.268) +2022-11-14 17:09:32,246 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0762) Prec@1 90.000 (87.789) Prec@5 99.000 (99.263) +2022-11-14 17:09:32,254 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0761) Prec@1 89.000 (87.810) Prec@5 99.000 (99.259) +2022-11-14 17:09:32,262 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0763) Prec@1 85.000 (87.763) Prec@5 100.000 (99.271) +2022-11-14 17:09:32,270 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0765) Prec@1 85.000 (87.717) Prec@5 100.000 (99.283) +2022-11-14 17:09:32,277 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0764) Prec@1 88.000 (87.721) Prec@5 100.000 (99.295) +2022-11-14 17:09:32,285 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0513 (0.0759) Prec@1 90.000 (87.758) Prec@5 100.000 (99.306) +2022-11-14 17:09:32,292 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0758) Prec@1 91.000 (87.810) Prec@5 100.000 (99.317) +2022-11-14 17:09:32,300 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0755) Prec@1 91.000 (87.859) Prec@5 99.000 (99.312) +2022-11-14 17:09:32,308 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0758) Prec@1 85.000 (87.815) Prec@5 100.000 (99.323) +2022-11-14 17:09:32,316 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0758) Prec@1 86.000 (87.788) Prec@5 100.000 (99.333) +2022-11-14 17:09:32,323 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0394 (0.0753) Prec@1 94.000 (87.881) Prec@5 100.000 (99.343) +2022-11-14 17:09:32,331 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0752) Prec@1 90.000 (87.912) Prec@5 97.000 (99.309) +2022-11-14 17:09:32,338 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0749) Prec@1 92.000 (87.971) Prec@5 98.000 (99.290) +2022-11-14 17:09:32,346 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0872 (0.0751) Prec@1 88.000 (87.971) Prec@5 100.000 (99.300) +2022-11-14 17:09:32,354 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1005 (0.0754) Prec@1 85.000 (87.930) Prec@5 99.000 (99.296) +2022-11-14 17:09:32,361 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0752) Prec@1 91.000 (87.972) Prec@5 100.000 (99.306) +2022-11-14 17:09:32,369 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0749) Prec@1 92.000 (88.027) Prec@5 100.000 (99.315) +2022-11-14 17:09:32,377 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0370 (0.0744) Prec@1 92.000 (88.081) Prec@5 100.000 (99.324) +2022-11-14 17:09:32,385 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0945 (0.0747) Prec@1 83.000 (88.013) Prec@5 99.000 (99.320) +2022-11-14 17:09:32,393 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0748) Prec@1 88.000 (88.013) Prec@5 99.000 (99.316) +2022-11-14 17:09:32,401 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0746) Prec@1 90.000 (88.039) Prec@5 99.000 (99.312) +2022-11-14 17:09:32,408 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0678 (0.0745) Prec@1 90.000 (88.064) Prec@5 99.000 (99.308) +2022-11-14 17:09:32,416 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0748) Prec@1 87.000 (88.051) Prec@5 100.000 (99.316) +2022-11-14 17:09:32,424 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0747) Prec@1 90.000 (88.075) Prec@5 100.000 (99.325) +2022-11-14 17:09:32,431 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0747) Prec@1 89.000 (88.086) Prec@5 98.000 (99.309) +2022-11-14 17:09:32,439 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1001 (0.0751) Prec@1 84.000 (88.037) Prec@5 99.000 (99.305) +2022-11-14 17:09:32,446 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0753) Prec@1 84.000 (87.988) Prec@5 100.000 (99.313) +2022-11-14 17:09:32,455 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0752) Prec@1 89.000 (88.000) Prec@5 99.000 (99.310) +2022-11-14 17:09:32,463 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0754) Prec@1 85.000 (87.965) Prec@5 99.000 (99.306) +2022-11-14 17:09:32,470 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0757) Prec@1 84.000 (87.919) Prec@5 100.000 (99.314) +2022-11-14 17:09:32,478 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0755) Prec@1 91.000 (87.954) Prec@5 100.000 (99.322) +2022-11-14 17:09:32,486 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0757) Prec@1 87.000 (87.943) Prec@5 99.000 (99.318) +2022-11-14 17:09:32,493 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0757) Prec@1 87.000 (87.933) Prec@5 100.000 (99.326) +2022-11-14 17:09:32,501 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0757) Prec@1 90.000 (87.956) Prec@5 100.000 (99.333) +2022-11-14 17:09:32,509 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0757) Prec@1 89.000 (87.967) Prec@5 100.000 (99.341) +2022-11-14 17:09:32,516 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0556 (0.0755) Prec@1 93.000 (88.022) Prec@5 100.000 (99.348) +2022-11-14 17:09:32,524 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0756) Prec@1 88.000 (88.022) Prec@5 100.000 (99.355) +2022-11-14 17:09:32,532 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0754) Prec@1 91.000 (88.053) Prec@5 100.000 (99.362) +2022-11-14 17:09:32,539 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0755) Prec@1 83.000 (88.000) Prec@5 100.000 (99.368) +2022-11-14 17:09:32,547 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0753) Prec@1 91.000 (88.031) Prec@5 99.000 (99.365) +2022-11-14 17:09:32,554 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0471 (0.0750) Prec@1 93.000 (88.082) Prec@5 99.000 (99.361) +2022-11-14 17:09:32,561 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0752) Prec@1 87.000 (88.071) Prec@5 100.000 (99.367) +2022-11-14 17:09:32,569 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0754) Prec@1 86.000 (88.051) Prec@5 100.000 (99.374) +2022-11-14 17:09:32,576 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0754) Prec@1 88.000 (88.050) Prec@5 100.000 (99.380) +2022-11-14 17:09:32,630 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:09:32,958 Epoch: [477][0/500] Time 0.026 (0.026) Data 0.248 (0.248) Loss 0.0402 (0.0402) Prec@1 94.000 (94.000) Prec@5 98.000 (98.000) +2022-11-14 17:09:33,157 Epoch: [477][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0233 (0.0318) Prec@1 97.000 (95.500) Prec@5 100.000 (99.000) +2022-11-14 17:09:33,346 Epoch: [477][20/500] Time 0.015 (0.018) Data 0.001 (0.013) Loss 0.0413 (0.0349) Prec@1 93.000 (94.667) Prec@5 100.000 (99.333) +2022-11-14 17:09:33,534 Epoch: [477][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0183 (0.0308) Prec@1 98.000 (95.500) Prec@5 99.000 (99.250) +2022-11-14 17:09:33,724 Epoch: [477][40/500] Time 0.015 (0.017) Data 0.001 (0.008) Loss 0.0407 (0.0328) Prec@1 93.000 (95.000) Prec@5 99.000 (99.200) +2022-11-14 17:09:33,914 Epoch: [477][50/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0117 (0.0293) Prec@1 97.000 (95.333) Prec@5 100.000 (99.333) +2022-11-14 17:09:34,108 Epoch: [477][60/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0075 (0.0261) Prec@1 100.000 (96.000) Prec@5 100.000 (99.429) +2022-11-14 17:09:34,297 Epoch: [477][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0337 (0.0271) Prec@1 95.000 (95.875) Prec@5 100.000 (99.500) +2022-11-14 17:09:34,486 Epoch: [477][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0238 (0.0267) Prec@1 96.000 (95.889) Prec@5 100.000 (99.556) +2022-11-14 17:09:34,675 Epoch: [477][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0374 (0.0278) Prec@1 93.000 (95.600) Prec@5 100.000 (99.600) +2022-11-14 17:09:34,875 Epoch: [477][100/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0238 (0.0274) Prec@1 97.000 (95.727) Prec@5 99.000 (99.545) +2022-11-14 17:09:35,077 Epoch: [477][110/500] Time 0.022 (0.017) Data 0.002 (0.004) Loss 0.0354 (0.0281) Prec@1 94.000 (95.583) Prec@5 100.000 (99.583) +2022-11-14 17:09:35,282 Epoch: [477][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0274 (0.0280) Prec@1 95.000 (95.538) Prec@5 100.000 (99.615) +2022-11-14 17:09:35,488 Epoch: [477][130/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0550 (0.0300) Prec@1 91.000 (95.214) Prec@5 100.000 (99.643) +2022-11-14 17:09:35,692 Epoch: [477][140/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0136 (0.0289) Prec@1 98.000 (95.400) Prec@5 100.000 (99.667) +2022-11-14 17:09:35,888 Epoch: [477][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0502 (0.0302) Prec@1 90.000 (95.062) Prec@5 100.000 (99.688) +2022-11-14 17:09:36,091 Epoch: [477][160/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0191 (0.0296) Prec@1 98.000 (95.235) Prec@5 99.000 (99.647) +2022-11-14 17:09:36,288 Epoch: [477][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0413 (0.0302) Prec@1 93.000 (95.111) Prec@5 100.000 (99.667) +2022-11-14 17:09:36,494 Epoch: [477][180/500] Time 0.016 (0.017) Data 0.002 (0.003) Loss 0.0806 (0.0329) Prec@1 85.000 (94.579) Prec@5 97.000 (99.526) +2022-11-14 17:09:36,686 Epoch: [477][190/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0350 (0.0330) Prec@1 94.000 (94.550) Prec@5 99.000 (99.500) +2022-11-14 17:09:36,873 Epoch: [477][200/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0314 (0.0329) Prec@1 93.000 (94.476) Prec@5 100.000 (99.524) +2022-11-14 17:09:37,071 Epoch: [477][210/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0321 (0.0329) Prec@1 93.000 (94.409) Prec@5 100.000 (99.545) +2022-11-14 17:09:37,323 Epoch: [477][220/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0478 (0.0335) Prec@1 92.000 (94.304) Prec@5 100.000 (99.565) +2022-11-14 17:09:37,581 Epoch: [477][230/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0254 (0.0332) Prec@1 95.000 (94.333) Prec@5 100.000 (99.583) +2022-11-14 17:09:37,839 Epoch: [477][240/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0232 (0.0328) Prec@1 95.000 (94.360) Prec@5 100.000 (99.600) +2022-11-14 17:09:38,105 Epoch: [477][250/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0249 (0.0325) Prec@1 97.000 (94.462) Prec@5 100.000 (99.615) +2022-11-14 17:09:38,362 Epoch: [477][260/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0208 (0.0320) Prec@1 95.000 (94.481) Prec@5 100.000 (99.630) +2022-11-14 17:09:38,624 Epoch: [477][270/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0126 (0.0313) Prec@1 99.000 (94.643) Prec@5 100.000 (99.643) +2022-11-14 17:09:38,888 Epoch: [477][280/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0119 (0.0307) Prec@1 99.000 (94.793) Prec@5 100.000 (99.655) +2022-11-14 17:09:39,155 Epoch: [477][290/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0228 (0.0304) Prec@1 96.000 (94.833) Prec@5 100.000 (99.667) +2022-11-14 17:09:39,417 Epoch: [477][300/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0365 (0.0306) Prec@1 95.000 (94.839) Prec@5 100.000 (99.677) +2022-11-14 17:09:39,681 Epoch: [477][310/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0223 (0.0303) Prec@1 96.000 (94.875) Prec@5 100.000 (99.688) +2022-11-14 17:09:39,949 Epoch: [477][320/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0206 (0.0301) Prec@1 98.000 (94.970) Prec@5 100.000 (99.697) +2022-11-14 17:09:40,221 Epoch: [477][330/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0167 (0.0297) Prec@1 98.000 (95.059) Prec@5 100.000 (99.706) +2022-11-14 17:09:40,488 Epoch: [477][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0175 (0.0293) Prec@1 97.000 (95.114) Prec@5 100.000 (99.714) +2022-11-14 17:09:40,745 Epoch: [477][350/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0480 (0.0298) Prec@1 92.000 (95.028) Prec@5 99.000 (99.694) +2022-11-14 17:09:41,008 Epoch: [477][360/500] Time 0.024 (0.020) Data 0.003 (0.002) Loss 0.0480 (0.0303) Prec@1 92.000 (94.946) Prec@5 100.000 (99.703) +2022-11-14 17:09:41,269 Epoch: [477][370/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0359 (0.0305) Prec@1 94.000 (94.921) Prec@5 100.000 (99.711) +2022-11-14 17:09:41,529 Epoch: [477][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0480 (0.0309) Prec@1 92.000 (94.846) Prec@5 99.000 (99.692) +2022-11-14 17:09:41,795 Epoch: [477][390/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0359 (0.0310) Prec@1 95.000 (94.850) Prec@5 99.000 (99.675) +2022-11-14 17:09:42,060 Epoch: [477][400/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0363 (0.0312) Prec@1 95.000 (94.854) Prec@5 100.000 (99.683) +2022-11-14 17:09:42,325 Epoch: [477][410/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0196 (0.0309) Prec@1 96.000 (94.881) Prec@5 100.000 (99.690) +2022-11-14 17:09:42,591 Epoch: [477][420/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0180 (0.0306) Prec@1 98.000 (94.953) Prec@5 100.000 (99.698) +2022-11-14 17:09:42,860 Epoch: [477][430/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0227 (0.0304) Prec@1 96.000 (94.977) Prec@5 100.000 (99.705) +2022-11-14 17:09:43,122 Epoch: [477][440/500] Time 0.027 (0.020) Data 0.002 (0.002) Loss 0.0126 (0.0300) Prec@1 98.000 (95.044) Prec@5 100.000 (99.711) +2022-11-14 17:09:43,387 Epoch: [477][450/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0363 (0.0302) Prec@1 91.000 (94.957) Prec@5 100.000 (99.717) +2022-11-14 17:09:43,653 Epoch: [477][460/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0316 (0.0302) Prec@1 93.000 (94.915) Prec@5 100.000 (99.723) +2022-11-14 17:09:43,918 Epoch: [477][470/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0293 (0.0302) Prec@1 96.000 (94.938) Prec@5 99.000 (99.708) +2022-11-14 17:09:44,185 Epoch: [477][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0247 (0.0301) Prec@1 96.000 (94.959) Prec@5 100.000 (99.714) +2022-11-14 17:09:44,449 Epoch: [477][490/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0275 (0.0300) Prec@1 97.000 (95.000) Prec@5 100.000 (99.720) +2022-11-14 17:09:44,690 Epoch: [477][499/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0254 (0.0299) Prec@1 95.000 (95.000) Prec@5 100.000 (99.725) +2022-11-14 17:09:44,994 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0605 (0.0605) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:45,002 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0773 (0.0689) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:09:45,010 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0686) Prec@1 90.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:45,020 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0726) Prec@1 87.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 17:09:45,027 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0518 (0.0685) Prec@1 93.000 (89.400) Prec@5 98.000 (99.200) +2022-11-14 17:09:45,034 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0425 (0.0641) Prec@1 92.000 (89.833) Prec@5 100.000 (99.333) +2022-11-14 17:09:45,041 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0647) Prec@1 91.000 (90.000) Prec@5 99.000 (99.286) +2022-11-14 17:09:45,049 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0655) Prec@1 89.000 (89.875) Prec@5 100.000 (99.375) +2022-11-14 17:09:45,056 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0661) Prec@1 88.000 (89.667) Prec@5 100.000 (99.444) +2022-11-14 17:09:45,065 Test: [9/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0666) Prec@1 90.000 (89.700) Prec@5 99.000 (99.400) +2022-11-14 17:09:45,075 Test: [10/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0660) Prec@1 91.000 (89.818) Prec@5 100.000 (99.455) +2022-11-14 17:09:45,084 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0675) Prec@1 88.000 (89.667) Prec@5 100.000 (99.500) +2022-11-14 17:09:45,092 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0680) Prec@1 89.000 (89.615) Prec@5 99.000 (99.462) +2022-11-14 17:09:45,101 Test: [13/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0679) Prec@1 89.000 (89.571) Prec@5 99.000 (99.429) +2022-11-14 17:09:45,111 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0688) Prec@1 86.000 (89.333) Prec@5 99.000 (99.400) +2022-11-14 17:09:45,119 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0695) Prec@1 88.000 (89.250) Prec@5 100.000 (99.438) +2022-11-14 17:09:45,127 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0690) Prec@1 90.000 (89.294) Prec@5 98.000 (99.353) +2022-11-14 17:09:45,137 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1218 (0.0719) Prec@1 79.000 (88.722) Prec@5 100.000 (99.389) +2022-11-14 17:09:45,147 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0716) Prec@1 88.000 (88.684) Prec@5 99.000 (99.368) +2022-11-14 17:09:45,155 Test: [19/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0726) Prec@1 85.000 (88.500) Prec@5 98.000 (99.300) +2022-11-14 17:09:45,163 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0731) Prec@1 87.000 (88.429) Prec@5 99.000 (99.286) +2022-11-14 17:09:45,171 Test: [21/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.0943 (0.0740) Prec@1 84.000 (88.227) Prec@5 99.000 (99.273) +2022-11-14 17:09:45,179 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0842 (0.0745) Prec@1 88.000 (88.217) Prec@5 98.000 (99.217) +2022-11-14 17:09:45,186 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0742) Prec@1 89.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 17:09:45,194 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0748) Prec@1 86.000 (88.160) Prec@5 100.000 (99.280) +2022-11-14 17:09:45,203 Test: [25/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0753) Prec@1 87.000 (88.115) Prec@5 99.000 (99.269) +2022-11-14 17:09:45,213 Test: [26/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0752) Prec@1 89.000 (88.148) Prec@5 100.000 (99.296) +2022-11-14 17:09:45,221 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0747) Prec@1 90.000 (88.214) Prec@5 100.000 (99.321) +2022-11-14 17:09:45,228 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0746) Prec@1 87.000 (88.172) Prec@5 99.000 (99.310) +2022-11-14 17:09:45,238 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0738) Prec@1 93.000 (88.333) Prec@5 99.000 (99.300) +2022-11-14 17:09:45,249 Test: [30/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0739) Prec@1 87.000 (88.290) Prec@5 99.000 (99.290) +2022-11-14 17:09:45,256 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0737) Prec@1 88.000 (88.281) Prec@5 99.000 (99.281) +2022-11-14 17:09:45,264 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0736) Prec@1 89.000 (88.303) Prec@5 100.000 (99.303) +2022-11-14 17:09:45,273 Test: [33/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1124 (0.0747) Prec@1 81.000 (88.088) Prec@5 100.000 (99.324) +2022-11-14 17:09:45,283 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0747) Prec@1 88.000 (88.086) Prec@5 97.000 (99.257) +2022-11-14 17:09:45,291 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0746) Prec@1 91.000 (88.167) Prec@5 99.000 (99.250) +2022-11-14 17:09:45,298 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0741) Prec@1 90.000 (88.216) Prec@5 98.000 (99.216) +2022-11-14 17:09:45,309 Test: [37/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0918 (0.0746) Prec@1 84.000 (88.105) Prec@5 100.000 (99.237) +2022-11-14 17:09:45,318 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0740) Prec@1 93.000 (88.231) Prec@5 100.000 (99.256) +2022-11-14 17:09:45,326 Test: [39/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0785 (0.0741) Prec@1 86.000 (88.175) Prec@5 100.000 (99.275) +2022-11-14 17:09:45,334 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0745) Prec@1 84.000 (88.073) Prec@5 100.000 (99.293) +2022-11-14 17:09:45,344 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0654 (0.0743) Prec@1 90.000 (88.119) Prec@5 100.000 (99.310) +2022-11-14 17:09:45,354 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0735) Prec@1 93.000 (88.233) Prec@5 100.000 (99.326) +2022-11-14 17:09:45,361 Test: [43/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0775 (0.0736) Prec@1 88.000 (88.227) Prec@5 99.000 (99.318) +2022-11-14 17:09:45,369 Test: [44/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0584 (0.0733) Prec@1 90.000 (88.267) Prec@5 99.000 (99.311) +2022-11-14 17:09:45,379 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0928 (0.0737) Prec@1 88.000 (88.261) Prec@5 99.000 (99.304) +2022-11-14 17:09:45,389 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0737) Prec@1 88.000 (88.255) Prec@5 100.000 (99.319) +2022-11-14 17:09:45,397 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0930 (0.0741) Prec@1 85.000 (88.188) Prec@5 97.000 (99.271) +2022-11-14 17:09:45,405 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0493 (0.0736) Prec@1 93.000 (88.286) Prec@5 100.000 (99.286) +2022-11-14 17:09:45,416 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.1041 (0.0742) Prec@1 83.000 (88.180) Prec@5 99.000 (99.280) +2022-11-14 17:09:45,426 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0739) Prec@1 90.000 (88.216) Prec@5 100.000 (99.294) +2022-11-14 17:09:45,434 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0744) Prec@1 83.000 (88.115) Prec@5 99.000 (99.288) +2022-11-14 17:09:45,441 Test: [52/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0742) Prec@1 89.000 (88.132) Prec@5 98.000 (99.264) +2022-11-14 17:09:45,451 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0709 (0.0741) Prec@1 86.000 (88.093) Prec@5 100.000 (99.278) +2022-11-14 17:09:45,461 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0744) Prec@1 87.000 (88.073) Prec@5 100.000 (99.291) +2022-11-14 17:09:45,469 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0830 (0.0746) Prec@1 86.000 (88.036) Prec@5 99.000 (99.286) +2022-11-14 17:09:45,477 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0863 (0.0748) Prec@1 86.000 (88.000) Prec@5 100.000 (99.298) +2022-11-14 17:09:45,487 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0749) Prec@1 87.000 (87.983) Prec@5 99.000 (99.293) +2022-11-14 17:09:45,497 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0751) Prec@1 87.000 (87.966) Prec@5 100.000 (99.305) +2022-11-14 17:09:45,504 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0749) Prec@1 88.000 (87.967) Prec@5 99.000 (99.300) +2022-11-14 17:09:45,512 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0750) Prec@1 89.000 (87.984) Prec@5 99.000 (99.295) +2022-11-14 17:09:45,522 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0748) Prec@1 91.000 (88.032) Prec@5 99.000 (99.290) +2022-11-14 17:09:45,532 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0746) Prec@1 91.000 (88.079) Prec@5 99.000 (99.286) +2022-11-14 17:09:45,540 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0410 (0.0740) Prec@1 92.000 (88.141) Prec@5 100.000 (99.297) +2022-11-14 17:09:45,548 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0752 (0.0741) Prec@1 89.000 (88.154) Prec@5 99.000 (99.292) +2022-11-14 17:09:45,558 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0819 (0.0742) Prec@1 85.000 (88.106) Prec@5 98.000 (99.273) +2022-11-14 17:09:45,568 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0429 (0.0737) Prec@1 93.000 (88.179) Prec@5 100.000 (99.284) +2022-11-14 17:09:45,575 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0737) Prec@1 89.000 (88.191) Prec@5 99.000 (99.279) +2022-11-14 17:09:45,583 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0734) Prec@1 92.000 (88.246) Prec@5 99.000 (99.275) +2022-11-14 17:09:45,593 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0878 (0.0736) Prec@1 87.000 (88.229) Prec@5 99.000 (99.271) +2022-11-14 17:09:45,603 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0963 (0.0739) Prec@1 85.000 (88.183) Prec@5 99.000 (99.268) +2022-11-14 17:09:45,611 Test: [71/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0737) Prec@1 90.000 (88.208) Prec@5 100.000 (99.278) +2022-11-14 17:09:45,618 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0581 (0.0735) Prec@1 91.000 (88.247) Prec@5 100.000 (99.288) +2022-11-14 17:09:45,629 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0396 (0.0730) Prec@1 94.000 (88.324) Prec@5 100.000 (99.297) +2022-11-14 17:09:45,639 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0951 (0.0733) Prec@1 86.000 (88.293) Prec@5 99.000 (99.293) +2022-11-14 17:09:45,646 Test: [75/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0650 (0.0732) Prec@1 91.000 (88.329) Prec@5 98.000 (99.276) +2022-11-14 17:09:45,654 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0731) Prec@1 90.000 (88.351) Prec@5 98.000 (99.260) +2022-11-14 17:09:45,664 Test: [77/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0912 (0.0734) Prec@1 86.000 (88.321) Prec@5 97.000 (99.231) +2022-11-14 17:09:45,674 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0735) Prec@1 87.000 (88.304) Prec@5 100.000 (99.241) +2022-11-14 17:09:45,682 Test: [79/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0736) Prec@1 86.000 (88.275) Prec@5 100.000 (99.250) +2022-11-14 17:09:45,690 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0827 (0.0737) Prec@1 88.000 (88.272) Prec@5 99.000 (99.247) +2022-11-14 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0.000 (0.000) Loss 0.0787 (0.0750) Prec@1 88.000 (88.114) Prec@5 99.000 (99.205) +2022-11-14 17:09:45,760 Test: [88/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0749) Prec@1 89.000 (88.124) Prec@5 100.000 (99.213) +2022-11-14 17:09:45,767 Test: [89/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0749) Prec@1 89.000 (88.133) Prec@5 99.000 (99.211) +2022-11-14 17:09:45,775 Test: [90/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0588 (0.0747) Prec@1 92.000 (88.176) Prec@5 99.000 (99.209) +2022-11-14 17:09:45,783 Test: [91/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0457 (0.0744) Prec@1 93.000 (88.228) Prec@5 99.000 (99.207) +2022-11-14 17:09:45,790 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0744) Prec@1 88.000 (88.226) Prec@5 99.000 (99.204) +2022-11-14 17:09:45,798 Test: [93/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0814 (0.0745) Prec@1 87.000 (88.213) Prec@5 99.000 (99.202) +2022-11-14 17:09:45,806 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0746) Prec@1 87.000 (88.200) Prec@5 99.000 (99.200) +2022-11-14 17:09:45,813 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0657 (0.0745) Prec@1 92.000 (88.240) Prec@5 100.000 (99.208) +2022-11-14 17:09:45,820 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0542 (0.0743) Prec@1 92.000 (88.278) Prec@5 99.000 (99.206) +2022-11-14 17:09:45,828 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0886 (0.0744) Prec@1 86.000 (88.255) Prec@5 100.000 (99.214) +2022-11-14 17:09:45,835 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0925 (0.0746) Prec@1 86.000 (88.232) Prec@5 98.000 (99.202) +2022-11-14 17:09:45,842 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0549 (0.0744) Prec@1 91.000 (88.260) Prec@5 100.000 (99.210) +2022-11-14 17:09:45,895 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:09:46,215 Epoch: [478][0/500] Time 0.022 (0.022) Data 0.249 (0.249) Loss 0.0304 (0.0304) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:46,408 Epoch: [478][10/500] Time 0.017 (0.017) Data 0.001 (0.024) Loss 0.0256 (0.0280) Prec@1 96.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:46,597 Epoch: [478][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0415 (0.0325) Prec@1 93.000 (94.333) Prec@5 99.000 (99.667) +2022-11-14 17:09:46,789 Epoch: [478][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0115 (0.0273) Prec@1 100.000 (95.750) Prec@5 100.000 (99.750) +2022-11-14 17:09:46,978 Epoch: [478][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0455 (0.0309) Prec@1 93.000 (95.200) Prec@5 99.000 (99.600) +2022-11-14 17:09:47,170 Epoch: [478][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0290 (0.0306) Prec@1 94.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 17:09:47,356 Epoch: [478][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0330 (0.0309) Prec@1 93.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 17:09:47,542 Epoch: [478][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0412 (0.0322) Prec@1 93.000 (94.500) Prec@5 99.000 (99.625) +2022-11-14 17:09:47,728 Epoch: [478][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0278 (0.0317) Prec@1 96.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 17:09:47,915 Epoch: [478][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0086 (0.0294) Prec@1 99.000 (95.100) Prec@5 100.000 (99.700) +2022-11-14 17:09:48,104 Epoch: [478][100/500] Time 0.020 (0.017) Data 0.002 (0.004) Loss 0.0261 (0.0291) Prec@1 96.000 (95.182) Prec@5 100.000 (99.727) +2022-11-14 17:09:48,291 Epoch: [478][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0280 (0.0290) Prec@1 95.000 (95.167) Prec@5 100.000 (99.750) +2022-11-14 17:09:48,481 Epoch: [478][120/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0353 (0.0295) Prec@1 94.000 (95.077) Prec@5 100.000 (99.769) +2022-11-14 17:09:48,743 Epoch: [478][130/500] Time 0.026 (0.017) Data 0.002 (0.003) Loss 0.0527 (0.0312) Prec@1 89.000 (94.643) Prec@5 100.000 (99.786) +2022-11-14 17:09:49,018 Epoch: [478][140/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0198 (0.0304) Prec@1 97.000 (94.800) Prec@5 100.000 (99.800) +2022-11-14 17:09:49,299 Epoch: [478][150/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0245 (0.0300) Prec@1 96.000 (94.875) Prec@5 100.000 (99.812) +2022-11-14 17:09:49,574 Epoch: [478][160/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0379 (0.0305) Prec@1 92.000 (94.706) Prec@5 100.000 (99.824) +2022-11-14 17:09:49,848 Epoch: [478][170/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0370 (0.0308) Prec@1 94.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 17:09:50,128 Epoch: [478][180/500] Time 0.034 (0.019) Data 0.002 (0.003) Loss 0.0233 (0.0305) Prec@1 96.000 (94.737) Prec@5 99.000 (99.789) +2022-11-14 17:09:50,400 Epoch: [478][190/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0230 (0.0301) Prec@1 95.000 (94.750) Prec@5 100.000 (99.800) +2022-11-14 17:09:50,673 Epoch: [478][200/500] Time 0.025 (0.020) Data 0.003 (0.003) Loss 0.0359 (0.0304) Prec@1 93.000 (94.667) Prec@5 100.000 (99.810) +2022-11-14 17:09:50,948 Epoch: [478][210/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0241 (0.0301) Prec@1 95.000 (94.682) Prec@5 100.000 (99.818) +2022-11-14 17:09:51,230 Epoch: [478][220/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0363 (0.0303) Prec@1 95.000 (94.696) Prec@5 100.000 (99.826) +2022-11-14 17:09:51,502 Epoch: [478][230/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0296 (0.0303) Prec@1 96.000 (94.750) Prec@5 100.000 (99.833) +2022-11-14 17:09:51,771 Epoch: [478][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0387 (0.0306) Prec@1 94.000 (94.720) Prec@5 100.000 (99.840) +2022-11-14 17:09:52,045 Epoch: [478][250/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0403 (0.0310) Prec@1 93.000 (94.654) Prec@5 100.000 (99.846) +2022-11-14 17:09:52,319 Epoch: [478][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0306 (0.0310) Prec@1 96.000 (94.704) Prec@5 100.000 (99.852) +2022-11-14 17:09:52,591 Epoch: [478][270/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0208 (0.0306) Prec@1 97.000 (94.786) Prec@5 100.000 (99.857) +2022-11-14 17:09:52,866 Epoch: [478][280/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0262 (0.0305) Prec@1 95.000 (94.793) Prec@5 100.000 (99.862) +2022-11-14 17:09:53,148 Epoch: [478][290/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0284 (0.0304) Prec@1 95.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 17:09:53,425 Epoch: [478][300/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0189 (0.0300) Prec@1 96.000 (94.839) Prec@5 100.000 (99.871) +2022-11-14 17:09:53,699 Epoch: [478][310/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0391 (0.0303) Prec@1 95.000 (94.844) Prec@5 100.000 (99.875) +2022-11-14 17:09:53,980 Epoch: [478][320/500] Time 0.028 (0.021) Data 0.003 (0.002) Loss 0.0312 (0.0304) Prec@1 95.000 (94.848) Prec@5 100.000 (99.879) +2022-11-14 17:09:54,250 Epoch: [478][330/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0281 (0.0303) Prec@1 97.000 (94.912) Prec@5 100.000 (99.882) +2022-11-14 17:09:54,529 Epoch: [478][340/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0152 (0.0299) Prec@1 97.000 (94.971) Prec@5 100.000 (99.886) +2022-11-14 17:09:54,804 Epoch: [478][350/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0261 (0.0298) Prec@1 96.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:09:55,074 Epoch: [478][360/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0254 (0.0296) Prec@1 96.000 (95.027) Prec@5 100.000 (99.892) +2022-11-14 17:09:55,347 Epoch: [478][370/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0290 (0.0296) Prec@1 93.000 (94.974) Prec@5 100.000 (99.895) +2022-11-14 17:09:55,621 Epoch: [478][380/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0261 (0.0295) Prec@1 95.000 (94.974) Prec@5 100.000 (99.897) +2022-11-14 17:09:55,898 Epoch: [478][390/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0265 (0.0295) Prec@1 96.000 (95.000) Prec@5 100.000 (99.900) +2022-11-14 17:09:56,168 Epoch: [478][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0086 (0.0289) Prec@1 99.000 (95.098) Prec@5 100.000 (99.902) +2022-11-14 17:09:56,442 Epoch: [478][410/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0164 (0.0286) Prec@1 97.000 (95.143) Prec@5 100.000 (99.905) +2022-11-14 17:09:56,717 Epoch: [478][420/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0297 (0.0287) Prec@1 95.000 (95.140) Prec@5 99.000 (99.884) +2022-11-14 17:09:56,996 Epoch: [478][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0435 (0.0290) Prec@1 92.000 (95.068) Prec@5 99.000 (99.864) +2022-11-14 17:09:57,274 Epoch: [478][440/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0090 (0.0286) Prec@1 99.000 (95.156) Prec@5 100.000 (99.867) +2022-11-14 17:09:57,555 Epoch: [478][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0365 (0.0287) Prec@1 93.000 (95.109) Prec@5 99.000 (99.848) +2022-11-14 17:09:57,832 Epoch: [478][460/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0394 (0.0290) Prec@1 94.000 (95.085) Prec@5 99.000 (99.830) +2022-11-14 17:09:58,102 Epoch: [478][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0329 (0.0290) Prec@1 95.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 17:09:58,372 Epoch: [478][480/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0655 (0.0298) Prec@1 90.000 (94.980) Prec@5 99.000 (99.816) +2022-11-14 17:09:58,642 Epoch: [478][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0185 (0.0296) Prec@1 97.000 (95.020) Prec@5 100.000 (99.820) +2022-11-14 17:09:58,892 Epoch: [478][499/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0371 (0.0297) Prec@1 95.000 (95.020) Prec@5 99.000 (99.804) +2022-11-14 17:09:59,189 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0513 (0.0513) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:59,197 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0697 (0.0605) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:59,205 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0596) Prec@1 89.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:09:59,215 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0809 (0.0649) Prec@1 87.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:09:59,222 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0667) Prec@1 87.000 (88.600) Prec@5 99.000 (99.800) +2022-11-14 17:09:59,229 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0235 (0.0595) Prec@1 95.000 (89.667) Prec@5 100.000 (99.833) +2022-11-14 17:09:59,236 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0603) Prec@1 92.000 (90.000) Prec@5 100.000 (99.857) +2022-11-14 17:09:59,245 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0630) Prec@1 87.000 (89.625) Prec@5 100.000 (99.875) +2022-11-14 17:09:59,252 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0654) Prec@1 86.000 (89.222) Prec@5 99.000 (99.778) +2022-11-14 17:09:59,259 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0669) Prec@1 88.000 (89.100) Prec@5 97.000 (99.500) +2022-11-14 17:09:59,267 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0654) Prec@1 91.000 (89.273) Prec@5 100.000 (99.545) +2022-11-14 17:09:59,274 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0957 (0.0680) Prec@1 84.000 (88.833) Prec@5 99.000 (99.500) +2022-11-14 17:09:59,282 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0672) Prec@1 90.000 (88.923) Prec@5 100.000 (99.538) +2022-11-14 17:09:59,290 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0675) Prec@1 88.000 (88.857) Prec@5 99.000 (99.500) +2022-11-14 17:09:59,298 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0683) Prec@1 89.000 (88.867) Prec@5 99.000 (99.467) +2022-11-14 17:09:59,306 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0683) Prec@1 87.000 (88.750) Prec@5 100.000 (99.500) +2022-11-14 17:09:59,314 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0610 (0.0679) Prec@1 90.000 (88.824) Prec@5 98.000 (99.412) +2022-11-14 17:09:59,321 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0700) Prec@1 84.000 (88.556) Prec@5 99.000 (99.389) +2022-11-14 17:09:59,329 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0712) Prec@1 86.000 (88.421) Prec@5 97.000 (99.263) +2022-11-14 17:09:59,337 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0726) Prec@1 85.000 (88.250) Prec@5 97.000 (99.150) +2022-11-14 17:09:59,345 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0727) Prec@1 88.000 (88.238) Prec@5 99.000 (99.143) +2022-11-14 17:09:59,352 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0734) Prec@1 88.000 (88.227) Prec@5 99.000 (99.136) +2022-11-14 17:09:59,360 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1134 (0.0752) Prec@1 82.000 (87.957) Prec@5 99.000 (99.130) +2022-11-14 17:09:59,368 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0757) Prec@1 87.000 (87.917) Prec@5 100.000 (99.167) +2022-11-14 17:09:59,376 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0755) Prec@1 87.000 (87.880) Prec@5 100.000 (99.200) +2022-11-14 17:09:59,384 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0763) Prec@1 84.000 (87.731) Prec@5 99.000 (99.192) +2022-11-14 17:09:59,391 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0753) Prec@1 93.000 (87.926) Prec@5 100.000 (99.222) +2022-11-14 17:09:59,399 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0750) Prec@1 90.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 17:09:59,407 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0576 (0.0744) Prec@1 90.000 (88.069) Prec@5 98.000 (99.207) +2022-11-14 17:09:59,414 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0748) Prec@1 84.000 (87.933) Prec@5 99.000 (99.200) +2022-11-14 17:09:59,421 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0743) Prec@1 91.000 (88.032) Prec@5 100.000 (99.226) +2022-11-14 17:09:59,430 Test: [31/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0741) Prec@1 88.000 (88.031) Prec@5 99.000 (99.219) +2022-11-14 17:09:59,439 Test: [32/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0742) Prec@1 88.000 (88.030) Prec@5 99.000 (99.212) +2022-11-14 17:09:59,447 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0743) Prec@1 86.000 (87.971) Prec@5 100.000 (99.235) +2022-11-14 17:09:59,455 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1007 (0.0751) Prec@1 85.000 (87.886) Prec@5 99.000 (99.229) +2022-11-14 17:09:59,465 Test: [35/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0749) Prec@1 90.000 (87.944) Prec@5 100.000 (99.250) +2022-11-14 17:09:59,475 Test: [36/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0749) Prec@1 89.000 (87.973) Prec@5 99.000 (99.243) +2022-11-14 17:09:59,483 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1034 (0.0756) Prec@1 86.000 (87.921) Prec@5 100.000 (99.263) +2022-11-14 17:09:59,490 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0750) Prec@1 93.000 (88.051) Prec@5 99.000 (99.256) +2022-11-14 17:09:59,500 Test: [39/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0746) Prec@1 92.000 (88.150) Prec@5 99.000 (99.250) +2022-11-14 17:09:59,510 Test: [40/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1229 (0.0758) Prec@1 85.000 (88.073) Prec@5 99.000 (99.244) +2022-11-14 17:09:59,518 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0759) Prec@1 87.000 (88.048) Prec@5 100.000 (99.262) +2022-11-14 17:09:59,526 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0752) Prec@1 93.000 (88.163) Prec@5 99.000 (99.256) +2022-11-14 17:09:59,536 Test: [43/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0597 (0.0749) Prec@1 92.000 (88.250) Prec@5 98.000 (99.227) +2022-11-14 17:09:59,546 Test: [44/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0463 (0.0742) Prec@1 91.000 (88.311) Prec@5 99.000 (99.222) +2022-11-14 17:09:59,554 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1025 (0.0749) Prec@1 83.000 (88.196) Prec@5 99.000 (99.217) +2022-11-14 17:09:59,561 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0750) Prec@1 88.000 (88.191) Prec@5 99.000 (99.213) +2022-11-14 17:09:59,571 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0756) Prec@1 83.000 (88.083) Prec@5 96.000 (99.146) +2022-11-14 17:09:59,582 Test: [48/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0756) Prec@1 88.000 (88.082) Prec@5 100.000 (99.163) +2022-11-14 17:09:59,589 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0761) Prec@1 84.000 (88.000) Prec@5 100.000 (99.180) +2022-11-14 17:09:59,597 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0757) Prec@1 90.000 (88.039) Prec@5 100.000 (99.196) +2022-11-14 17:09:59,607 Test: [51/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0757) Prec@1 90.000 (88.077) Prec@5 100.000 (99.212) +2022-11-14 17:09:59,616 Test: [52/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0752) Prec@1 92.000 (88.151) Prec@5 99.000 (99.208) +2022-11-14 17:09:59,624 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0752) Prec@1 87.000 (88.130) Prec@5 100.000 (99.222) +2022-11-14 17:09:59,632 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0754) Prec@1 86.000 (88.091) Prec@5 100.000 (99.236) +2022-11-14 17:09:59,639 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0754) Prec@1 87.000 (88.071) Prec@5 99.000 (99.232) +2022-11-14 17:09:59,647 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0750) Prec@1 89.000 (88.088) Prec@5 100.000 (99.246) +2022-11-14 17:09:59,655 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0751) Prec@1 88.000 (88.086) Prec@5 99.000 (99.241) +2022-11-14 17:09:59,662 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1079 (0.0756) Prec@1 83.000 (88.000) Prec@5 100.000 (99.254) +2022-11-14 17:09:59,669 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0756) Prec@1 84.000 (87.933) Prec@5 100.000 (99.267) +2022-11-14 17:09:59,677 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0756) Prec@1 86.000 (87.902) Prec@5 100.000 (99.279) +2022-11-14 17:09:59,684 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0757) Prec@1 86.000 (87.871) Prec@5 100.000 (99.290) +2022-11-14 17:09:59,691 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0755) Prec@1 89.000 (87.889) Prec@5 99.000 (99.286) +2022-11-14 17:09:59,699 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0506 (0.0751) Prec@1 92.000 (87.953) Prec@5 100.000 (99.297) +2022-11-14 17:09:59,706 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0752) Prec@1 86.000 (87.923) Prec@5 99.000 (99.292) +2022-11-14 17:09:59,714 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0751) Prec@1 89.000 (87.939) Prec@5 99.000 (99.288) +2022-11-14 17:09:59,721 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0405 (0.0746) Prec@1 93.000 (88.015) Prec@5 100.000 (99.299) +2022-11-14 17:09:59,729 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0746) Prec@1 90.000 (88.044) Prec@5 100.000 (99.309) +2022-11-14 17:09:59,736 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0744) Prec@1 91.000 (88.087) Prec@5 99.000 (99.304) +2022-11-14 17:09:59,744 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0744) Prec@1 90.000 (88.114) Prec@5 100.000 (99.314) +2022-11-14 17:09:59,751 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1266 (0.0751) Prec@1 81.000 (88.014) Prec@5 99.000 (99.310) +2022-11-14 17:09:59,759 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0749) Prec@1 92.000 (88.069) Prec@5 99.000 (99.306) +2022-11-14 17:09:59,766 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0409 (0.0744) Prec@1 95.000 (88.164) Prec@5 100.000 (99.315) +2022-11-14 17:09:59,774 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0744) Prec@1 89.000 (88.176) Prec@5 100.000 (99.324) +2022-11-14 17:09:59,781 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0746) Prec@1 84.000 (88.120) Prec@5 100.000 (99.333) +2022-11-14 17:09:59,789 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0744) Prec@1 91.000 (88.158) Prec@5 100.000 (99.342) +2022-11-14 17:09:59,797 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0629 (0.0743) Prec@1 89.000 (88.169) Prec@5 98.000 (99.325) +2022-11-14 17:09:59,805 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0741) Prec@1 91.000 (88.205) Prec@5 99.000 (99.321) +2022-11-14 17:09:59,813 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0741) Prec@1 89.000 (88.215) Prec@5 100.000 (99.329) +2022-11-14 17:09:59,820 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0740) Prec@1 88.000 (88.213) Prec@5 100.000 (99.338) +2022-11-14 17:09:59,828 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0742) Prec@1 83.000 (88.148) Prec@5 98.000 (99.321) +2022-11-14 17:09:59,836 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0745) Prec@1 82.000 (88.073) Prec@5 100.000 (99.329) +2022-11-14 17:09:59,843 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0998 (0.0748) Prec@1 86.000 (88.048) Prec@5 98.000 (99.313) +2022-11-14 17:09:59,851 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0745) Prec@1 89.000 (88.060) Prec@5 100.000 (99.321) +2022-11-14 17:09:59,858 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0748) Prec@1 84.000 (88.012) Prec@5 100.000 (99.329) +2022-11-14 17:09:59,866 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1206 (0.0753) Prec@1 82.000 (87.942) Prec@5 99.000 (99.326) +2022-11-14 17:09:59,874 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0755) Prec@1 84.000 (87.897) Prec@5 100.000 (99.333) +2022-11-14 17:09:59,881 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0754) Prec@1 88.000 (87.898) Prec@5 99.000 (99.330) +2022-11-14 17:09:59,889 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0754) Prec@1 87.000 (87.888) Prec@5 100.000 (99.337) +2022-11-14 17:09:59,897 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0753) Prec@1 90.000 (87.911) Prec@5 99.000 (99.333) +2022-11-14 17:09:59,904 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0751) Prec@1 93.000 (87.967) Prec@5 100.000 (99.341) +2022-11-14 17:09:59,912 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0749) Prec@1 92.000 (88.011) Prec@5 100.000 (99.348) +2022-11-14 17:09:59,920 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0750) Prec@1 86.000 (87.989) Prec@5 98.000 (99.333) +2022-11-14 17:09:59,928 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0750) Prec@1 89.000 (88.000) Prec@5 100.000 (99.340) +2022-11-14 17:09:59,935 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0750) Prec@1 88.000 (88.000) Prec@5 100.000 (99.347) +2022-11-14 17:09:59,943 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0748) Prec@1 91.000 (88.031) Prec@5 99.000 (99.344) +2022-11-14 17:09:59,950 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0461 (0.0745) Prec@1 92.000 (88.072) Prec@5 98.000 (99.330) +2022-11-14 17:09:59,958 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0748) Prec@1 86.000 (88.051) Prec@5 98.000 (99.316) +2022-11-14 17:09:59,965 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1002 (0.0750) Prec@1 86.000 (88.030) Prec@5 99.000 (99.313) +2022-11-14 17:09:59,973 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0750) Prec@1 87.000 (88.020) Prec@5 99.000 (99.310) +2022-11-14 17:10:00,028 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:10:00,341 Epoch: [479][0/500] Time 0.028 (0.028) Data 0.232 (0.232) Loss 0.0229 (0.0229) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:00,541 Epoch: [479][10/500] Time 0.017 (0.019) Data 0.002 (0.023) Loss 0.0289 (0.0259) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:00,732 Epoch: [479][20/500] Time 0.015 (0.018) Data 0.002 (0.013) Loss 0.0365 (0.0294) Prec@1 94.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:10:00,921 Epoch: [479][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0230 (0.0278) Prec@1 95.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:10:01,122 Epoch: [479][40/500] Time 0.020 (0.018) Data 0.002 (0.007) Loss 0.0375 (0.0297) Prec@1 95.000 (95.200) Prec@5 100.000 (100.000) +2022-11-14 17:10:01,311 Epoch: [479][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0377 (0.0311) Prec@1 92.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:10:01,498 Epoch: [479][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0458 (0.0332) Prec@1 93.000 (94.429) Prec@5 100.000 (100.000) +2022-11-14 17:10:01,684 Epoch: [479][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0343 (0.0333) Prec@1 95.000 (94.500) Prec@5 99.000 (99.875) +2022-11-14 17:10:01,883 Epoch: [479][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0225 (0.0321) Prec@1 97.000 (94.778) Prec@5 99.000 (99.778) +2022-11-14 17:10:02,070 Epoch: [479][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0363 (0.0325) Prec@1 93.000 (94.600) Prec@5 100.000 (99.800) +2022-11-14 17:10:02,258 Epoch: [479][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0184 (0.0313) Prec@1 98.000 (94.909) Prec@5 99.000 (99.727) +2022-11-14 17:10:02,446 Epoch: [479][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0341 (0.0315) Prec@1 94.000 (94.833) Prec@5 100.000 (99.750) +2022-11-14 17:10:02,633 Epoch: [479][120/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0273 (0.0312) Prec@1 95.000 (94.846) Prec@5 100.000 (99.769) +2022-11-14 17:10:02,823 Epoch: [479][130/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0380 (0.0317) Prec@1 95.000 (94.857) Prec@5 100.000 (99.786) +2022-11-14 17:10:03,072 Epoch: [479][140/500] Time 0.024 (0.017) Data 0.002 (0.003) Loss 0.0233 (0.0311) Prec@1 96.000 (94.933) Prec@5 100.000 (99.800) +2022-11-14 17:10:03,335 Epoch: [479][150/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0411 (0.0317) Prec@1 94.000 (94.875) Prec@5 100.000 (99.812) +2022-11-14 17:10:03,602 Epoch: [479][160/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0360 (0.0320) Prec@1 94.000 (94.824) Prec@5 100.000 (99.824) +2022-11-14 17:10:03,870 Epoch: [479][170/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0415 (0.0325) Prec@1 92.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 17:10:04,137 Epoch: [479][180/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0239 (0.0321) Prec@1 96.000 (94.737) Prec@5 99.000 (99.789) +2022-11-14 17:10:04,400 Epoch: [479][190/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0207 (0.0315) Prec@1 97.000 (94.850) Prec@5 100.000 (99.800) +2022-11-14 17:10:04,671 Epoch: [479][200/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0353 (0.0317) Prec@1 95.000 (94.857) Prec@5 100.000 (99.810) +2022-11-14 17:10:04,941 Epoch: [479][210/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0319 (0.0317) Prec@1 95.000 (94.864) Prec@5 100.000 (99.818) +2022-11-14 17:10:05,211 Epoch: [479][220/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0141 (0.0309) Prec@1 99.000 (95.043) Prec@5 100.000 (99.826) +2022-11-14 17:10:05,481 Epoch: [479][230/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0328 (0.0310) Prec@1 94.000 (95.000) Prec@5 99.000 (99.792) +2022-11-14 17:10:05,751 Epoch: [479][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0226 (0.0307) Prec@1 96.000 (95.040) Prec@5 100.000 (99.800) +2022-11-14 17:10:06,022 Epoch: [479][250/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0181 (0.0302) Prec@1 97.000 (95.115) Prec@5 100.000 (99.808) +2022-11-14 17:10:06,289 Epoch: [479][260/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0244 (0.0300) Prec@1 96.000 (95.148) Prec@5 98.000 (99.741) +2022-11-14 17:10:06,559 Epoch: [479][270/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0170 (0.0295) Prec@1 98.000 (95.250) Prec@5 100.000 (99.750) +2022-11-14 17:10:06,817 Epoch: [479][280/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0149 (0.0290) Prec@1 97.000 (95.310) Prec@5 100.000 (99.759) +2022-11-14 17:10:07,085 Epoch: [479][290/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0116 (0.0284) Prec@1 99.000 (95.433) Prec@5 100.000 (99.767) +2022-11-14 17:10:07,352 Epoch: [479][300/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0226 (0.0282) Prec@1 97.000 (95.484) Prec@5 100.000 (99.774) +2022-11-14 17:10:07,619 Epoch: [479][310/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0182 (0.0279) Prec@1 97.000 (95.531) Prec@5 100.000 (99.781) +2022-11-14 17:10:07,875 Epoch: [479][320/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0429 (0.0284) Prec@1 92.000 (95.424) Prec@5 100.000 (99.788) +2022-11-14 17:10:08,137 Epoch: [479][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0113 (0.0279) Prec@1 98.000 (95.500) Prec@5 100.000 (99.794) +2022-11-14 17:10:08,399 Epoch: [479][340/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0386 (0.0282) Prec@1 93.000 (95.429) Prec@5 100.000 (99.800) +2022-11-14 17:10:08,664 Epoch: [479][350/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0327 (0.0283) Prec@1 92.000 (95.333) Prec@5 100.000 (99.806) +2022-11-14 17:10:08,922 Epoch: [479][360/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0263 (0.0282) Prec@1 95.000 (95.324) Prec@5 100.000 (99.811) +2022-11-14 17:10:09,183 Epoch: [479][370/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0370 (0.0285) Prec@1 94.000 (95.289) Prec@5 100.000 (99.816) +2022-11-14 17:10:09,438 Epoch: [479][380/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0171 (0.0282) Prec@1 98.000 (95.359) Prec@5 100.000 (99.821) +2022-11-14 17:10:09,696 Epoch: [479][390/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0199 (0.0280) Prec@1 97.000 (95.400) Prec@5 100.000 (99.825) +2022-11-14 17:10:09,955 Epoch: [479][400/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0493 (0.0285) Prec@1 92.000 (95.317) Prec@5 99.000 (99.805) +2022-11-14 17:10:10,220 Epoch: [479][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0242 (0.0284) Prec@1 96.000 (95.333) Prec@5 100.000 (99.810) +2022-11-14 17:10:10,480 Epoch: [479][420/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0346 (0.0285) Prec@1 95.000 (95.326) Prec@5 100.000 (99.814) +2022-11-14 17:10:10,744 Epoch: [479][430/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0453 (0.0289) Prec@1 93.000 (95.273) Prec@5 99.000 (99.795) +2022-11-14 17:10:11,005 Epoch: [479][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0247 (0.0288) Prec@1 96.000 (95.289) Prec@5 100.000 (99.800) +2022-11-14 17:10:11,267 Epoch: [479][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0220 (0.0287) Prec@1 96.000 (95.304) Prec@5 100.000 (99.804) +2022-11-14 17:10:11,527 Epoch: [479][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0375 (0.0289) Prec@1 94.000 (95.277) Prec@5 100.000 (99.809) +2022-11-14 17:10:11,786 Epoch: [479][470/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0318 (0.0289) Prec@1 95.000 (95.271) Prec@5 100.000 (99.812) +2022-11-14 17:10:12,050 Epoch: [479][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0264 (0.0289) Prec@1 96.000 (95.286) Prec@5 100.000 (99.816) +2022-11-14 17:10:12,307 Epoch: [479][490/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0318 (0.0289) Prec@1 94.000 (95.260) Prec@5 100.000 (99.820) +2022-11-14 17:10:12,541 Epoch: [479][499/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0131 (0.0286) Prec@1 98.000 (95.314) Prec@5 99.000 (99.804) +2022-11-14 17:10:12,849 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0676 (0.0676) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:10:12,857 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0815 (0.0745) Prec@1 87.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 17:10:12,865 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0552 (0.0681) Prec@1 92.000 (89.333) Prec@5 99.000 (99.000) +2022-11-14 17:10:12,875 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0796 (0.0710) Prec@1 88.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:10:12,882 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0705) Prec@1 89.000 (89.000) Prec@5 100.000 (99.200) +2022-11-14 17:10:12,888 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0414 (0.0657) Prec@1 93.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 17:10:12,895 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0646) Prec@1 93.000 (90.143) Prec@5 100.000 (99.429) +2022-11-14 17:10:12,903 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0674) Prec@1 86.000 (89.625) Prec@5 99.000 (99.375) +2022-11-14 17:10:12,910 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0670) Prec@1 90.000 (89.667) Prec@5 99.000 (99.333) +2022-11-14 17:10:12,917 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0671) Prec@1 89.000 (89.600) Prec@5 97.000 (99.100) +2022-11-14 17:10:12,924 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0453 (0.0652) Prec@1 93.000 (89.909) Prec@5 100.000 (99.182) +2022-11-14 17:10:12,932 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0664) Prec@1 89.000 (89.833) Prec@5 99.000 (99.167) +2022-11-14 17:10:12,940 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0672) Prec@1 87.000 (89.615) Prec@5 100.000 (99.231) +2022-11-14 17:10:12,947 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0675) Prec@1 89.000 (89.571) Prec@5 99.000 (99.214) +2022-11-14 17:10:12,955 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0679) Prec@1 88.000 (89.467) Prec@5 100.000 (99.267) +2022-11-14 17:10:12,963 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0682) Prec@1 88.000 (89.375) Prec@5 100.000 (99.312) +2022-11-14 17:10:12,970 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0480 (0.0670) Prec@1 94.000 (89.647) Prec@5 98.000 (99.235) +2022-11-14 17:10:12,978 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0692) Prec@1 84.000 (89.333) Prec@5 100.000 (99.278) +2022-11-14 17:10:12,985 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0699) Prec@1 86.000 (89.158) Prec@5 98.000 (99.211) +2022-11-14 17:10:12,993 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0770 (0.0702) Prec@1 87.000 (89.050) Prec@5 98.000 (99.150) +2022-11-14 17:10:13,001 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0707) Prec@1 88.000 (89.000) Prec@5 100.000 (99.190) +2022-11-14 17:10:13,008 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0715) Prec@1 85.000 (88.818) Prec@5 100.000 (99.227) +2022-11-14 17:10:13,015 Test: [22/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0874 (0.0722) Prec@1 85.000 (88.652) Prec@5 98.000 (99.174) +2022-11-14 17:10:13,023 Test: [23/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0722) Prec@1 87.000 (88.583) Prec@5 100.000 (99.208) +2022-11-14 17:10:13,031 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0851 (0.0727) Prec@1 87.000 (88.520) Prec@5 100.000 (99.240) +2022-11-14 17:10:13,038 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0781 (0.0730) Prec@1 88.000 (88.500) Prec@5 98.000 (99.192) +2022-11-14 17:10:13,046 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0717 (0.0729) Prec@1 90.000 (88.556) Prec@5 99.000 (99.185) +2022-11-14 17:10:13,053 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0727) Prec@1 90.000 (88.607) Prec@5 100.000 (99.214) +2022-11-14 17:10:13,061 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0728) Prec@1 87.000 (88.552) Prec@5 98.000 (99.172) +2022-11-14 17:10:13,068 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0624 (0.0725) Prec@1 90.000 (88.600) Prec@5 98.000 (99.133) +2022-11-14 17:10:13,076 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0721) Prec@1 91.000 (88.677) Prec@5 100.000 (99.161) +2022-11-14 17:10:13,085 Test: [31/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0868 (0.0726) Prec@1 87.000 (88.625) Prec@5 98.000 (99.125) +2022-11-14 17:10:13,092 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0726) Prec@1 86.000 (88.545) Prec@5 99.000 (99.121) +2022-11-14 17:10:13,100 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0725) Prec@1 88.000 (88.529) Prec@5 100.000 (99.147) +2022-11-14 17:10:13,108 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0693 (0.0724) Prec@1 90.000 (88.571) Prec@5 98.000 (99.114) +2022-11-14 17:10:13,115 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0616 (0.0721) Prec@1 90.000 (88.611) Prec@5 98.000 (99.083) +2022-11-14 17:10:13,123 Test: [36/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0721) Prec@1 90.000 (88.649) Prec@5 99.000 (99.081) +2022-11-14 17:10:13,130 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0932 (0.0727) Prec@1 84.000 (88.526) Prec@5 98.000 (99.053) +2022-11-14 17:10:13,138 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0559 (0.0722) Prec@1 91.000 (88.590) Prec@5 99.000 (99.051) +2022-11-14 17:10:13,145 Test: [39/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0719) Prec@1 90.000 (88.625) Prec@5 99.000 (99.050) +2022-11-14 17:10:13,153 Test: [40/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0925 (0.0724) Prec@1 87.000 (88.585) Prec@5 98.000 (99.024) +2022-11-14 17:10:13,161 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0809 (0.0726) Prec@1 89.000 (88.595) Prec@5 99.000 (99.024) +2022-11-14 17:10:13,168 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0498 (0.0720) Prec@1 94.000 (88.721) Prec@5 100.000 (99.047) +2022-11-14 17:10:13,177 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0515 (0.0716) Prec@1 91.000 (88.773) Prec@5 99.000 (99.045) +2022-11-14 17:10:13,185 Test: [44/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0614 (0.0714) Prec@1 90.000 (88.800) Prec@5 100.000 (99.067) +2022-11-14 17:10:13,192 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0838 (0.0716) Prec@1 87.000 (88.761) Prec@5 98.000 (99.043) +2022-11-14 17:10:13,200 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0736 (0.0717) Prec@1 89.000 (88.766) Prec@5 100.000 (99.064) +2022-11-14 17:10:13,207 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0835 (0.0719) Prec@1 85.000 (88.688) Prec@5 100.000 (99.083) +2022-11-14 17:10:13,215 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0549 (0.0716) Prec@1 89.000 (88.694) Prec@5 100.000 (99.102) +2022-11-14 17:10:13,222 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0916 (0.0720) Prec@1 88.000 (88.680) Prec@5 100.000 (99.120) +2022-11-14 17:10:13,230 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0642 (0.0718) Prec@1 90.000 (88.706) Prec@5 99.000 (99.118) +2022-11-14 17:10:13,238 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0824 (0.0720) Prec@1 87.000 (88.673) Prec@5 99.000 (99.115) +2022-11-14 17:10:13,245 Test: [52/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0718) Prec@1 92.000 (88.736) Prec@5 100.000 (99.132) +2022-11-14 17:10:13,253 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0682 (0.0718) Prec@1 89.000 (88.741) Prec@5 99.000 (99.130) +2022-11-14 17:10:13,261 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0988 (0.0723) Prec@1 82.000 (88.618) Prec@5 100.000 (99.145) +2022-11-14 17:10:13,269 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0777 (0.0724) Prec@1 88.000 (88.607) Prec@5 100.000 (99.161) +2022-11-14 17:10:13,276 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0713 (0.0723) Prec@1 86.000 (88.561) Prec@5 100.000 (99.175) +2022-11-14 17:10:13,284 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0638 (0.0722) Prec@1 92.000 (88.621) Prec@5 99.000 (99.172) +2022-11-14 17:10:13,292 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0721) Prec@1 90.000 (88.644) Prec@5 100.000 (99.186) +2022-11-14 17:10:13,299 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0722) Prec@1 84.000 (88.567) Prec@5 100.000 (99.200) +2022-11-14 17:10:13,307 Test: [60/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0958 (0.0726) Prec@1 86.000 (88.525) Prec@5 98.000 (99.180) +2022-11-14 17:10:13,315 Test: [61/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0583 (0.0724) Prec@1 90.000 (88.548) Prec@5 99.000 (99.177) +2022-11-14 17:10:13,323 Test: [62/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0849 (0.0726) Prec@1 85.000 (88.492) Prec@5 99.000 (99.175) +2022-11-14 17:10:13,330 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0353 (0.0720) Prec@1 94.000 (88.578) Prec@5 100.000 (99.188) +2022-11-14 17:10:13,338 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1078 (0.0726) Prec@1 85.000 (88.523) Prec@5 99.000 (99.185) +2022-11-14 17:10:13,345 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0725 (0.0726) Prec@1 89.000 (88.530) Prec@5 99.000 (99.182) +2022-11-14 17:10:13,353 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0439 (0.0721) Prec@1 92.000 (88.582) Prec@5 100.000 (99.194) +2022-11-14 17:10:13,361 Test: [67/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0721) Prec@1 90.000 (88.603) Prec@5 98.000 (99.176) +2022-11-14 17:10:13,368 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0723) Prec@1 86.000 (88.565) Prec@5 98.000 (99.159) +2022-11-14 17:10:13,376 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0723) Prec@1 89.000 (88.571) Prec@5 98.000 (99.143) +2022-11-14 17:10:13,384 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1176 (0.0730) Prec@1 83.000 (88.493) Prec@5 97.000 (99.113) +2022-11-14 17:10:13,391 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0729) Prec@1 89.000 (88.500) Prec@5 100.000 (99.125) +2022-11-14 17:10:13,399 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0477 (0.0725) Prec@1 91.000 (88.534) Prec@5 100.000 (99.137) +2022-11-14 17:10:13,406 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0446 (0.0721) Prec@1 92.000 (88.581) Prec@5 100.000 (99.149) +2022-11-14 17:10:13,414 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0878 (0.0723) Prec@1 87.000 (88.560) Prec@5 98.000 (99.133) +2022-11-14 17:10:13,422 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0451 (0.0720) Prec@1 93.000 (88.618) Prec@5 98.000 (99.118) +2022-11-14 17:10:13,429 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0820 (0.0721) Prec@1 87.000 (88.597) Prec@5 97.000 (99.091) +2022-11-14 17:10:13,437 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1057 (0.0726) Prec@1 84.000 (88.538) Prec@5 98.000 (99.077) +2022-11-14 17:10:13,444 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0895 (0.0728) Prec@1 86.000 (88.506) Prec@5 99.000 (99.076) +2022-11-14 17:10:13,452 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0804 (0.0729) Prec@1 85.000 (88.463) Prec@5 100.000 (99.088) +2022-11-14 17:10:13,460 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0879 (0.0730) Prec@1 88.000 (88.457) Prec@5 99.000 (99.086) +2022-11-14 17:10:13,467 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0820 (0.0732) Prec@1 87.000 (88.439) Prec@5 100.000 (99.098) +2022-11-14 17:10:13,475 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0727 (0.0732) Prec@1 88.000 (88.434) Prec@5 99.000 (99.096) +2022-11-14 17:10:13,482 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0607 (0.0730) Prec@1 91.000 (88.464) Prec@5 100.000 (99.107) +2022-11-14 17:10:13,490 Test: [84/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.1172 (0.0735) Prec@1 84.000 (88.412) Prec@5 100.000 (99.118) +2022-11-14 17:10:13,498 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0738) Prec@1 82.000 (88.337) Prec@5 100.000 (99.128) +2022-11-14 17:10:13,506 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0586 (0.0736) Prec@1 92.000 (88.379) Prec@5 100.000 (99.138) +2022-11-14 17:10:13,513 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0748 (0.0737) Prec@1 89.000 (88.386) Prec@5 98.000 (99.125) +2022-11-14 17:10:13,521 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0514 (0.0734) Prec@1 90.000 (88.404) Prec@5 99.000 (99.124) +2022-11-14 17:10:13,528 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0678 (0.0733) Prec@1 89.000 (88.411) Prec@5 100.000 (99.133) +2022-11-14 17:10:13,536 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0602 (0.0732) Prec@1 91.000 (88.440) Prec@5 100.000 (99.143) +2022-11-14 17:10:13,544 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0460 (0.0729) Prec@1 94.000 (88.500) Prec@5 99.000 (99.141) +2022-11-14 17:10:13,551 Test: [92/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0987 (0.0732) Prec@1 85.000 (88.462) Prec@5 99.000 (99.140) +2022-11-14 17:10:13,559 Test: [93/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0758 (0.0732) Prec@1 88.000 (88.457) Prec@5 99.000 (99.138) +2022-11-14 17:10:13,567 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0864 (0.0733) Prec@1 84.000 (88.411) Prec@5 100.000 (99.147) +2022-11-14 17:10:13,574 Test: [95/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0733) Prec@1 90.000 (88.427) Prec@5 99.000 (99.146) +2022-11-14 17:10:13,582 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0395 (0.0729) Prec@1 94.000 (88.485) Prec@5 99.000 (99.144) +2022-11-14 17:10:13,589 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0832 (0.0730) Prec@1 89.000 (88.490) Prec@5 97.000 (99.122) +2022-11-14 17:10:13,597 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0823 (0.0731) Prec@1 87.000 (88.475) Prec@5 98.000 (99.111) +2022-11-14 17:10:13,604 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0665 (0.0730) Prec@1 90.000 (88.490) Prec@5 100.000 (99.120) +2022-11-14 17:10:13,662 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:10:14,001 Epoch: [480][0/500] Time 0.021 (0.021) Data 0.236 (0.236) Loss 0.0217 (0.0217) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:14,206 Epoch: [480][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0310 (0.0264) Prec@1 93.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:14,400 Epoch: [480][20/500] Time 0.018 (0.018) Data 0.002 (0.013) Loss 0.0236 (0.0255) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:10:14,588 Epoch: [480][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0395 (0.0290) Prec@1 93.000 (94.750) Prec@5 99.000 (99.750) +2022-11-14 17:10:14,776 Epoch: [480][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0179 (0.0268) Prec@1 97.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:10:14,968 Epoch: [480][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0371 (0.0285) Prec@1 96.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 17:10:15,166 Epoch: [480][60/500] Time 0.020 (0.017) Data 0.002 (0.005) Loss 0.0294 (0.0286) Prec@1 95.000 (95.286) Prec@5 100.000 (99.857) +2022-11-14 17:10:15,366 Epoch: [480][70/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0299 (0.0288) Prec@1 94.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 17:10:15,559 Epoch: [480][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0228 (0.0281) Prec@1 97.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 17:10:15,755 Epoch: [480][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0201 (0.0273) Prec@1 95.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 17:10:15,946 Epoch: [480][100/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0166 (0.0263) Prec@1 98.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 17:10:16,143 Epoch: [480][110/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0393 (0.0274) Prec@1 96.000 (95.583) Prec@5 99.000 (99.833) +2022-11-14 17:10:16,335 Epoch: [480][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0375 (0.0282) Prec@1 94.000 (95.462) Prec@5 100.000 (99.846) +2022-11-14 17:10:16,528 Epoch: [480][130/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0265 (0.0281) Prec@1 96.000 (95.500) Prec@5 100.000 (99.857) +2022-11-14 17:10:16,719 Epoch: [480][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0352 (0.0286) Prec@1 94.000 (95.400) Prec@5 100.000 (99.867) +2022-11-14 17:10:16,962 Epoch: [480][150/500] Time 0.025 (0.017) Data 0.001 (0.003) Loss 0.0356 (0.0290) Prec@1 94.000 (95.312) Prec@5 100.000 (99.875) +2022-11-14 17:10:17,232 Epoch: [480][160/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0499 (0.0302) Prec@1 91.000 (95.059) Prec@5 99.000 (99.824) +2022-11-14 17:10:17,499 Epoch: [480][170/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0315 (0.0303) Prec@1 94.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:10:17,770 Epoch: [480][180/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0197 (0.0297) Prec@1 97.000 (95.105) Prec@5 99.000 (99.789) +2022-11-14 17:10:18,041 Epoch: [480][190/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0209 (0.0293) Prec@1 96.000 (95.150) Prec@5 100.000 (99.800) +2022-11-14 17:10:18,315 Epoch: [480][200/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0301 (0.0293) Prec@1 93.000 (95.048) Prec@5 100.000 (99.810) +2022-11-14 17:10:18,587 Epoch: [480][210/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0364 (0.0297) Prec@1 93.000 (94.955) Prec@5 100.000 (99.818) +2022-11-14 17:10:18,860 Epoch: [480][220/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0078 (0.0287) Prec@1 99.000 (95.130) Prec@5 100.000 (99.826) +2022-11-14 17:10:19,137 Epoch: [480][230/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0371 (0.0291) Prec@1 92.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:10:19,408 Epoch: [480][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0233 (0.0288) Prec@1 98.000 (95.120) Prec@5 100.000 (99.840) +2022-11-14 17:10:19,681 Epoch: [480][250/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0162 (0.0283) Prec@1 98.000 (95.231) Prec@5 100.000 (99.846) +2022-11-14 17:10:19,945 Epoch: [480][260/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0331 (0.0285) Prec@1 95.000 (95.222) Prec@5 100.000 (99.852) +2022-11-14 17:10:20,213 Epoch: [480][270/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0311 (0.0286) Prec@1 94.000 (95.179) Prec@5 99.000 (99.821) +2022-11-14 17:10:20,478 Epoch: [480][280/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0242 (0.0285) Prec@1 96.000 (95.207) Prec@5 100.000 (99.828) +2022-11-14 17:10:20,745 Epoch: [480][290/500] Time 0.026 (0.020) Data 0.001 (0.002) Loss 0.0343 (0.0287) Prec@1 94.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 17:10:21,004 Epoch: [480][300/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0264 (0.0286) Prec@1 96.000 (95.194) Prec@5 99.000 (99.806) +2022-11-14 17:10:21,269 Epoch: [480][310/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0267 (0.0285) Prec@1 96.000 (95.219) Prec@5 100.000 (99.812) +2022-11-14 17:10:21,537 Epoch: [480][320/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0242 (0.0284) Prec@1 97.000 (95.273) Prec@5 99.000 (99.788) +2022-11-14 17:10:21,797 Epoch: [480][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0102 (0.0279) Prec@1 99.000 (95.382) Prec@5 100.000 (99.794) +2022-11-14 17:10:22,062 Epoch: [480][340/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0398 (0.0282) Prec@1 91.000 (95.257) Prec@5 100.000 (99.800) +2022-11-14 17:10:22,327 Epoch: [480][350/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0254 (0.0281) Prec@1 96.000 (95.278) Prec@5 100.000 (99.806) +2022-11-14 17:10:22,590 Epoch: [480][360/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0159 (0.0278) Prec@1 97.000 (95.324) Prec@5 100.000 (99.811) +2022-11-14 17:10:22,855 Epoch: [480][370/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0177 (0.0275) Prec@1 97.000 (95.368) Prec@5 100.000 (99.816) +2022-11-14 17:10:23,119 Epoch: [480][380/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0281 (0.0275) Prec@1 96.000 (95.385) Prec@5 99.000 (99.795) +2022-11-14 17:10:23,377 Epoch: [480][390/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0421 (0.0279) Prec@1 92.000 (95.300) Prec@5 100.000 (99.800) +2022-11-14 17:10:23,640 Epoch: [480][400/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0267 (0.0279) Prec@1 97.000 (95.341) Prec@5 100.000 (99.805) +2022-11-14 17:10:23,900 Epoch: [480][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0249 (0.0278) Prec@1 95.000 (95.333) Prec@5 100.000 (99.810) +2022-11-14 17:10:24,166 Epoch: [480][420/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0313 (0.0279) Prec@1 94.000 (95.302) Prec@5 100.000 (99.814) +2022-11-14 17:10:24,429 Epoch: [480][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0427 (0.0282) Prec@1 92.000 (95.227) Prec@5 100.000 (99.818) +2022-11-14 17:10:24,697 Epoch: [480][440/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0198 (0.0280) Prec@1 96.000 (95.244) Prec@5 100.000 (99.822) +2022-11-14 17:10:24,962 Epoch: [480][450/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0195 (0.0278) Prec@1 96.000 (95.261) Prec@5 99.000 (99.804) +2022-11-14 17:10:25,227 Epoch: [480][460/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0449 (0.0282) Prec@1 92.000 (95.191) Prec@5 100.000 (99.809) +2022-11-14 17:10:25,490 Epoch: [480][470/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0394 (0.0284) Prec@1 93.000 (95.146) Prec@5 99.000 (99.792) +2022-11-14 17:10:25,754 Epoch: [480][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0267 (0.0284) Prec@1 97.000 (95.184) Prec@5 100.000 (99.796) +2022-11-14 17:10:26,014 Epoch: [480][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0304 (0.0285) Prec@1 96.000 (95.200) Prec@5 100.000 (99.800) +2022-11-14 17:10:26,255 Epoch: [480][499/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0826 (0.0295) Prec@1 87.000 (95.039) Prec@5 97.000 (99.745) +2022-11-14 17:10:26,560 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0650 (0.0650) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:10:26,567 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0842 (0.0746) Prec@1 85.000 (87.000) Prec@5 100.000 (99.500) +2022-11-14 17:10:26,574 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0578 (0.0690) Prec@1 89.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 17:10:26,585 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0721) Prec@1 86.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 17:10:26,592 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0712) Prec@1 88.000 (87.400) Prec@5 100.000 (99.600) +2022-11-14 17:10:26,599 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0525 (0.0681) Prec@1 92.000 (88.167) Prec@5 98.000 (99.333) +2022-11-14 17:10:26,606 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0681) Prec@1 90.000 (88.429) Prec@5 100.000 (99.429) +2022-11-14 17:10:26,615 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0711) Prec@1 82.000 (87.625) Prec@5 99.000 (99.375) +2022-11-14 17:10:26,623 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0708) Prec@1 90.000 (87.889) Prec@5 99.000 (99.333) +2022-11-14 17:10:26,630 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0723) Prec@1 88.000 (87.900) Prec@5 99.000 (99.300) +2022-11-14 17:10:26,638 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0725) Prec@1 89.000 (88.000) Prec@5 100.000 (99.364) +2022-11-14 17:10:26,645 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0730) Prec@1 88.000 (88.000) Prec@5 99.000 (99.333) +2022-11-14 17:10:26,653 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0720) Prec@1 88.000 (88.000) Prec@5 100.000 (99.385) +2022-11-14 17:10:26,661 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0735) Prec@1 86.000 (87.857) Prec@5 99.000 (99.357) +2022-11-14 17:10:26,668 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0730) Prec@1 91.000 (88.067) Prec@5 100.000 (99.400) +2022-11-14 17:10:26,676 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0737) Prec@1 87.000 (88.000) Prec@5 99.000 (99.375) +2022-11-14 17:10:26,684 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0723) Prec@1 94.000 (88.353) Prec@5 99.000 (99.353) +2022-11-14 17:10:26,692 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0982 (0.0737) Prec@1 86.000 (88.222) Prec@5 98.000 (99.278) +2022-11-14 17:10:26,699 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0742) Prec@1 87.000 (88.158) Prec@5 98.000 (99.211) +2022-11-14 17:10:26,707 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0748) Prec@1 85.000 (88.000) Prec@5 98.000 (99.150) +2022-11-14 17:10:26,715 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0747) Prec@1 88.000 (88.000) Prec@5 99.000 (99.143) +2022-11-14 17:10:26,723 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0742) Prec@1 89.000 (88.045) Prec@5 100.000 (99.182) +2022-11-14 17:10:26,730 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0754) Prec@1 84.000 (87.870) Prec@5 99.000 (99.174) +2022-11-14 17:10:26,738 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0757) Prec@1 89.000 (87.917) Prec@5 99.000 (99.167) +2022-11-14 17:10:26,746 Test: 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Loss 0.0594 (0.0761) Prec@1 91.000 (88.000) Prec@5 100.000 (99.129) +2022-11-14 17:10:26,811 Test: [31/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0756) Prec@1 91.000 (88.094) Prec@5 99.000 (99.125) +2022-11-14 17:10:26,819 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0864 (0.0759) Prec@1 83.000 (87.939) Prec@5 99.000 (99.121) +2022-11-14 17:10:26,827 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0769) Prec@1 81.000 (87.735) Prec@5 99.000 (99.118) +2022-11-14 17:10:26,838 Test: [34/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0767) Prec@1 89.000 (87.771) Prec@5 98.000 (99.086) +2022-11-14 17:10:26,848 Test: [35/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0766) Prec@1 91.000 (87.861) Prec@5 99.000 (99.083) +2022-11-14 17:10:26,856 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0762) Prec@1 90.000 (87.919) Prec@5 100.000 (99.108) +2022-11-14 17:10:26,864 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0764) Prec@1 86.000 (87.868) Prec@5 99.000 (99.105) +2022-11-14 17:10:26,874 Test: [38/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0545 (0.0758) Prec@1 92.000 (87.974) Prec@5 99.000 (99.103) +2022-11-14 17:10:26,884 Test: [39/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0754) Prec@1 89.000 (88.000) Prec@5 99.000 (99.100) +2022-11-14 17:10:26,891 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0758) Prec@1 87.000 (87.976) Prec@5 98.000 (99.073) +2022-11-14 17:10:26,899 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0758) Prec@1 87.000 (87.952) Prec@5 100.000 (99.095) +2022-11-14 17:10:26,909 Test: [42/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0409 (0.0749) Prec@1 92.000 (88.047) Prec@5 99.000 (99.093) +2022-11-14 17:10:26,919 Test: [43/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0747) Prec@1 89.000 (88.068) Prec@5 98.000 (99.068) +2022-11-14 17:10:26,927 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0559 (0.0743) Prec@1 90.000 (88.111) Prec@5 100.000 (99.089) +2022-11-14 17:10:26,935 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0840 (0.0745) Prec@1 86.000 (88.065) Prec@5 99.000 (99.087) +2022-11-14 17:10:26,944 Test: [46/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0745) Prec@1 88.000 (88.064) Prec@5 100.000 (99.106) +2022-11-14 17:10:26,954 Test: [47/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0751) Prec@1 82.000 (87.938) Prec@5 99.000 (99.104) +2022-11-14 17:10:26,962 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0342 (0.0742) Prec@1 94.000 (88.061) Prec@5 100.000 (99.122) +2022-11-14 17:10:26,969 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1003 (0.0748) Prec@1 84.000 (87.980) Prec@5 99.000 (99.120) +2022-11-14 17:10:26,979 Test: [50/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0744) Prec@1 91.000 (88.039) Prec@5 100.000 (99.137) +2022-11-14 17:10:26,989 Test: [51/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0744) Prec@1 88.000 (88.038) Prec@5 98.000 (99.115) +2022-11-14 17:10:26,996 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0744) Prec@1 88.000 (88.038) Prec@5 99.000 (99.113) +2022-11-14 17:10:27,004 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0744) Prec@1 88.000 (88.037) Prec@5 100.000 (99.130) +2022-11-14 17:10:27,014 Test: [54/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1086 (0.0750) Prec@1 84.000 (87.964) Prec@5 100.000 (99.145) +2022-11-14 17:10:27,024 Test: [55/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0712 (0.0750) Prec@1 89.000 (87.982) Prec@5 99.000 (99.143) +2022-11-14 17:10:27,031 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0799 (0.0750) Prec@1 86.000 (87.947) Prec@5 100.000 (99.158) +2022-11-14 17:10:27,039 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0748) Prec@1 93.000 (88.034) Prec@5 100.000 (99.172) +2022-11-14 17:10:27,049 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0751) Prec@1 86.000 (88.000) Prec@5 100.000 (99.186) +2022-11-14 17:10:27,059 Test: [59/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0824 (0.0752) Prec@1 86.000 (87.967) Prec@5 100.000 (99.200) +2022-11-14 17:10:27,066 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0725 (0.0751) Prec@1 89.000 (87.984) Prec@5 97.000 (99.164) +2022-11-14 17:10:27,074 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0750) Prec@1 89.000 (88.000) Prec@5 98.000 (99.145) +2022-11-14 17:10:27,084 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0825 (0.0751) Prec@1 88.000 (88.000) Prec@5 100.000 (99.159) +2022-11-14 17:10:27,094 Test: [63/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0376 (0.0745) Prec@1 94.000 (88.094) Prec@5 100.000 (99.172) +2022-11-14 17:10:27,102 Test: [64/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0856 (0.0747) Prec@1 84.000 (88.031) Prec@5 100.000 (99.185) +2022-11-14 17:10:27,110 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0604 (0.0745) Prec@1 91.000 (88.076) Prec@5 98.000 (99.167) +2022-11-14 17:10:27,119 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0346 (0.0739) Prec@1 93.000 (88.149) Prec@5 100.000 (99.179) +2022-11-14 17:10:27,129 Test: [67/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0625 (0.0737) Prec@1 89.000 (88.162) Prec@5 98.000 (99.162) +2022-11-14 17:10:27,137 Test: [68/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0659 (0.0736) Prec@1 90.000 (88.188) Prec@5 100.000 (99.174) +2022-11-14 17:10:27,146 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0746 (0.0736) Prec@1 88.000 (88.186) Prec@5 99.000 (99.171) +2022-11-14 17:10:27,156 Test: [70/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1048 (0.0741) Prec@1 86.000 (88.155) Prec@5 100.000 (99.183) +2022-11-14 17:10:27,166 Test: [71/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0576 (0.0738) Prec@1 91.000 (88.194) Prec@5 100.000 (99.194) +2022-11-14 17:10:27,174 Test: [72/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0448 (0.0734) Prec@1 94.000 (88.274) Prec@5 98.000 (99.178) +2022-11-14 17:10:27,181 Test: [73/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0386 (0.0730) Prec@1 95.000 (88.365) Prec@5 100.000 (99.189) +2022-11-14 17:10:27,191 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1042 (0.0734) Prec@1 85.000 (88.320) Prec@5 99.000 (99.187) +2022-11-14 17:10:27,201 Test: [75/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0590 (0.0732) Prec@1 92.000 (88.368) Prec@5 100.000 (99.197) +2022-11-14 17:10:27,209 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0732) Prec@1 89.000 (88.377) Prec@5 98.000 (99.182) +2022-11-14 17:10:27,217 Test: [77/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0870 (0.0734) Prec@1 87.000 (88.359) Prec@5 97.000 (99.154) +2022-11-14 17:10:27,227 Test: [78/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0798 (0.0735) Prec@1 86.000 (88.329) Prec@5 99.000 (99.152) +2022-11-14 17:10:27,236 Test: [79/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0734) Prec@1 89.000 (88.338) Prec@5 100.000 (99.162) +2022-11-14 17:10:27,244 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0903 (0.0736) Prec@1 88.000 (88.333) Prec@5 99.000 (99.160) +2022-11-14 17:10:27,251 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0737) Prec@1 88.000 (88.329) Prec@5 100.000 (99.171) +2022-11-14 17:10:27,261 Test: [82/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0736) Prec@1 91.000 (88.361) Prec@5 100.000 (99.181) +2022-11-14 17:10:27,271 Test: [83/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0735) Prec@1 90.000 (88.381) Prec@5 99.000 (99.179) +2022-11-14 17:10:27,279 Test: [84/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0739) Prec@1 81.000 (88.294) Prec@5 99.000 (99.176) +2022-11-14 17:10:27,286 Test: [85/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1165 (0.0744) Prec@1 83.000 (88.233) Prec@5 100.000 (99.186) +2022-11-14 17:10:27,296 Test: [86/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0667 (0.0743) Prec@1 89.000 (88.241) Prec@5 99.000 (99.184) +2022-11-14 17:10:27,306 Test: [87/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0664 (0.0742) Prec@1 89.000 (88.250) Prec@5 99.000 (99.182) +2022-11-14 17:10:27,314 Test: [88/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0743) Prec@1 89.000 (88.258) Prec@5 100.000 (99.191) +2022-11-14 17:10:27,321 Test: [89/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0742) Prec@1 90.000 (88.278) Prec@5 99.000 (99.189) +2022-11-14 17:10:27,331 Test: [90/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0740) Prec@1 89.000 (88.286) Prec@5 100.000 (99.198) +2022-11-14 17:10:27,341 Test: [91/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0329 (0.0736) Prec@1 95.000 (88.359) Prec@5 99.000 (99.196) +2022-11-14 17:10:27,349 Test: [92/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0822 (0.0736) Prec@1 86.000 (88.333) Prec@5 100.000 (99.204) +2022-11-14 17:10:27,356 Test: [93/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0759 (0.0737) Prec@1 87.000 (88.319) Prec@5 99.000 (99.202) +2022-11-14 17:10:27,364 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0948 (0.0739) Prec@1 83.000 (88.263) Prec@5 99.000 (99.200) +2022-11-14 17:10:27,371 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0494 (0.0736) Prec@1 92.000 (88.302) Prec@5 99.000 (99.198) +2022-11-14 17:10:27,379 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0368 (0.0733) Prec@1 95.000 (88.371) Prec@5 99.000 (99.196) +2022-11-14 17:10:27,387 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0734) Prec@1 87.000 (88.357) Prec@5 99.000 (99.194) +2022-11-14 17:10:27,394 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0836 (0.0735) Prec@1 88.000 (88.354) Prec@5 97.000 (99.172) +2022-11-14 17:10:27,401 Test: [99/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0734) Prec@1 90.000 (88.370) Prec@5 99.000 (99.170) +2022-11-14 17:10:27,456 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:10:27,785 Epoch: [481][0/500] Time 0.023 (0.023) Data 0.248 (0.248) Loss 0.0268 (0.0268) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:27,982 Epoch: [481][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0098 (0.0183) Prec@1 99.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 17:10:28,174 Epoch: [481][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0402 (0.0256) Prec@1 93.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:28,361 Epoch: [481][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0227 (0.0249) Prec@1 97.000 (96.250) Prec@5 99.000 (99.750) +2022-11-14 17:10:28,550 Epoch: [481][40/500] Time 0.017 (0.017) Data 0.002 (0.008) Loss 0.0127 (0.0224) Prec@1 98.000 (96.600) Prec@5 100.000 (99.800) +2022-11-14 17:10:28,739 Epoch: [481][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0544 (0.0278) Prec@1 90.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:10:28,930 Epoch: [481][60/500] Time 0.018 (0.017) Data 0.002 (0.006) Loss 0.0316 (0.0283) Prec@1 96.000 (95.571) Prec@5 100.000 (99.857) +2022-11-14 17:10:29,127 Epoch: [481][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0311 (0.0287) Prec@1 96.000 (95.625) Prec@5 100.000 (99.875) +2022-11-14 17:10:29,318 Epoch: [481][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0280 (0.0286) Prec@1 95.000 (95.556) Prec@5 100.000 (99.889) +2022-11-14 17:10:29,527 Epoch: [481][90/500] Time 0.023 (0.017) Data 0.002 (0.004) Loss 0.0355 (0.0293) Prec@1 92.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:10:29,810 Epoch: [481][100/500] Time 0.028 (0.018) Data 0.002 (0.004) Loss 0.0287 (0.0292) Prec@1 96.000 (95.273) Prec@5 100.000 (99.909) +2022-11-14 17:10:30,110 Epoch: [481][110/500] Time 0.032 (0.019) Data 0.002 (0.004) Loss 0.0452 (0.0306) Prec@1 92.000 (95.000) Prec@5 100.000 (99.917) +2022-11-14 17:10:30,404 Epoch: [481][120/500] Time 0.028 (0.019) Data 0.002 (0.004) Loss 0.0339 (0.0308) Prec@1 93.000 (94.846) Prec@5 99.000 (99.846) +2022-11-14 17:10:30,691 Epoch: [481][130/500] Time 0.027 (0.020) Data 0.002 (0.004) Loss 0.0314 (0.0309) Prec@1 96.000 (94.929) Prec@5 100.000 (99.857) +2022-11-14 17:10:30,979 Epoch: [481][140/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0470 (0.0319) Prec@1 93.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 17:10:31,266 Epoch: [481][150/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0246 (0.0315) Prec@1 98.000 (95.000) Prec@5 100.000 (99.875) +2022-11-14 17:10:31,548 Epoch: [481][160/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0498 (0.0325) Prec@1 92.000 (94.824) Prec@5 100.000 (99.882) +2022-11-14 17:10:31,837 Epoch: [481][170/500] Time 0.029 (0.021) Data 0.002 (0.003) Loss 0.0145 (0.0315) Prec@1 98.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:10:32,133 Epoch: [481][180/500] Time 0.030 (0.021) Data 0.002 (0.003) Loss 0.0273 (0.0313) Prec@1 95.000 (95.000) Prec@5 100.000 (99.895) +2022-11-14 17:10:32,415 Epoch: [481][190/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0495 (0.0322) Prec@1 92.000 (94.850) Prec@5 99.000 (99.850) +2022-11-14 17:10:32,702 Epoch: [481][200/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0111 (0.0312) Prec@1 98.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:10:32,985 Epoch: [481][210/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0208 (0.0308) Prec@1 98.000 (95.136) Prec@5 100.000 (99.864) +2022-11-14 17:10:33,270 Epoch: [481][220/500] Time 0.026 (0.022) Data 0.003 (0.003) Loss 0.0328 (0.0308) Prec@1 95.000 (95.130) Prec@5 100.000 (99.870) +2022-11-14 17:10:33,555 Epoch: [481][230/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0238 (0.0305) Prec@1 94.000 (95.083) Prec@5 100.000 (99.875) +2022-11-14 17:10:33,838 Epoch: [481][240/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0279 (0.0304) Prec@1 95.000 (95.080) Prec@5 100.000 (99.880) +2022-11-14 17:10:34,123 Epoch: [481][250/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0527 (0.0313) Prec@1 92.000 (94.962) Prec@5 99.000 (99.846) +2022-11-14 17:10:34,403 Epoch: [481][260/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0148 (0.0307) Prec@1 98.000 (95.074) Prec@5 100.000 (99.852) +2022-11-14 17:10:34,686 Epoch: [481][270/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0375 (0.0309) Prec@1 94.000 (95.036) Prec@5 100.000 (99.857) +2022-11-14 17:10:34,972 Epoch: [481][280/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0070 (0.0301) Prec@1 99.000 (95.172) Prec@5 100.000 (99.862) +2022-11-14 17:10:35,264 Epoch: [481][290/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0381 (0.0304) Prec@1 92.000 (95.067) Prec@5 100.000 (99.867) +2022-11-14 17:10:35,555 Epoch: [481][300/500] Time 0.028 (0.023) Data 0.001 (0.003) Loss 0.0233 (0.0301) Prec@1 96.000 (95.097) Prec@5 100.000 (99.871) +2022-11-14 17:10:35,839 Epoch: [481][310/500] Time 0.028 (0.023) Data 0.001 (0.003) Loss 0.0325 (0.0302) Prec@1 94.000 (95.062) Prec@5 100.000 (99.875) +2022-11-14 17:10:36,126 Epoch: [481][320/500] Time 0.032 (0.023) Data 0.002 (0.002) Loss 0.0313 (0.0302) Prec@1 94.000 (95.030) Prec@5 100.000 (99.879) +2022-11-14 17:10:36,404 Epoch: [481][330/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0151 (0.0298) Prec@1 98.000 (95.118) Prec@5 100.000 (99.882) +2022-11-14 17:10:36,687 Epoch: [481][340/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0218 (0.0296) Prec@1 98.000 (95.200) Prec@5 99.000 (99.857) +2022-11-14 17:10:36,971 Epoch: [481][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0273 (0.0295) Prec@1 97.000 (95.250) Prec@5 100.000 (99.861) +2022-11-14 17:10:37,256 Epoch: [481][360/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0234 (0.0293) Prec@1 96.000 (95.270) Prec@5 100.000 (99.865) +2022-11-14 17:10:37,537 Epoch: [481][370/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0317 (0.0294) Prec@1 95.000 (95.263) Prec@5 100.000 (99.868) +2022-11-14 17:10:37,822 Epoch: [481][380/500] Time 0.026 (0.023) Data 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100.000 (99.714) +2022-11-14 17:10:41,578 Test: [7/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0860 (0.0648) Prec@1 85.000 (88.750) Prec@5 99.000 (99.625) +2022-11-14 17:10:41,585 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0813 (0.0666) Prec@1 89.000 (88.778) Prec@5 98.000 (99.444) +2022-11-14 17:10:41,593 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0758 (0.0676) Prec@1 88.000 (88.700) Prec@5 98.000 (99.300) +2022-11-14 17:10:41,603 Test: [10/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0676) Prec@1 91.000 (88.909) Prec@5 100.000 (99.364) +2022-11-14 17:10:41,613 Test: [11/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0865 (0.0692) Prec@1 87.000 (88.750) Prec@5 99.000 (99.333) +2022-11-14 17:10:41,621 Test: [12/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0685) Prec@1 89.000 (88.769) Prec@5 100.000 (99.385) +2022-11-14 17:10:41,628 Test: [13/100] Model 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93.000 (88.333) Prec@5 99.000 (99.154) +2022-11-14 17:10:41,861 Test: [39/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0745) Prec@1 88.000 (88.325) Prec@5 100.000 (99.175) +2022-11-14 17:10:41,871 Test: [40/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0840 (0.0747) Prec@1 88.000 (88.317) Prec@5 99.000 (99.171) +2022-11-14 17:10:41,881 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0697 (0.0746) Prec@1 89.000 (88.333) Prec@5 100.000 (99.190) +2022-11-14 17:10:41,889 Test: [42/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0742) Prec@1 89.000 (88.349) Prec@5 100.000 (99.209) +2022-11-14 17:10:41,897 Test: [43/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0812 (0.0744) Prec@1 88.000 (88.341) Prec@5 98.000 (99.182) +2022-11-14 17:10:41,907 Test: [44/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0742) Prec@1 89.000 (88.356) Prec@5 100.000 (99.200) +2022-11-14 17:10:41,916 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1059 (0.0749) Prec@1 81.000 (88.196) Prec@5 100.000 (99.217) +2022-11-14 17:10:41,924 Test: [46/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0748) Prec@1 88.000 (88.191) Prec@5 100.000 (99.234) +2022-11-14 17:10:41,932 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1180 (0.0757) Prec@1 80.000 (88.021) Prec@5 98.000 (99.208) +2022-11-14 17:10:41,942 Test: [48/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0555 (0.0753) Prec@1 92.000 (88.102) Prec@5 100.000 (99.224) +2022-11-14 17:10:41,952 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0993 (0.0757) Prec@1 85.000 (88.040) Prec@5 99.000 (99.220) +2022-11-14 17:10:41,959 Test: [50/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0716 (0.0757) Prec@1 87.000 (88.020) Prec@5 100.000 (99.235) +2022-11-14 17:10:41,967 Test: [51/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0783 (0.0757) Prec@1 87.000 (88.000) Prec@5 100.000 (99.250) +2022-11-14 17:10:41,977 Test: [52/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0614 (0.0754) Prec@1 92.000 (88.075) Prec@5 100.000 (99.264) +2022-11-14 17:10:41,986 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0752) Prec@1 90.000 (88.111) Prec@5 98.000 (99.241) +2022-11-14 17:10:41,994 Test: [54/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0926 (0.0755) Prec@1 84.000 (88.036) Prec@5 100.000 (99.255) +2022-11-14 17:10:42,002 Test: [55/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0727 (0.0755) Prec@1 90.000 (88.071) Prec@5 99.000 (99.250) +2022-11-14 17:10:42,012 Test: [56/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0646 (0.0753) Prec@1 90.000 (88.105) Prec@5 100.000 (99.263) +2022-11-14 17:10:42,022 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0958 (0.0756) Prec@1 86.000 (88.069) Prec@5 99.000 (99.259) +2022-11-14 17:10:42,029 Test: [58/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1061 (0.0762) Prec@1 83.000 (87.983) Prec@5 99.000 (99.254) +2022-11-14 17:10:42,037 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0761) Prec@1 87.000 (87.967) Prec@5 100.000 (99.267) +2022-11-14 17:10:42,045 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0762) Prec@1 87.000 (87.951) Prec@5 99.000 (99.262) +2022-11-14 17:10:42,052 Test: [61/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0761) Prec@1 88.000 (87.952) Prec@5 100.000 (99.274) +2022-11-14 17:10:42,060 Test: [62/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0711 (0.0760) Prec@1 88.000 (87.952) Prec@5 99.000 (99.270) +2022-11-14 17:10:42,068 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0561 (0.0757) Prec@1 90.000 (87.984) Prec@5 99.000 (99.266) +2022-11-14 17:10:42,076 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0845 (0.0759) Prec@1 88.000 (87.985) Prec@5 100.000 (99.277) +2022-11-14 17:10:42,085 Test: [65/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0682 (0.0757) Prec@1 91.000 (88.030) Prec@5 99.000 (99.273) +2022-11-14 17:10:42,093 Test: [66/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0580 (0.0755) Prec@1 91.000 (88.075) Prec@5 99.000 (99.269) +2022-11-14 17:10:42,101 Test: [67/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0752) Prec@1 91.000 (88.118) Prec@5 98.000 (99.250) +2022-11-14 17:10:42,108 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0671 (0.0751) Prec@1 88.000 (88.116) Prec@5 99.000 (99.246) +2022-11-14 17:10:42,116 Test: [69/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0750) Prec@1 88.000 (88.114) Prec@5 99.000 (99.243) +2022-11-14 17:10:42,124 Test: [70/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1056 (0.0754) Prec@1 86.000 (88.085) Prec@5 98.000 (99.225) +2022-11-14 17:10:42,131 Test: [71/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0558 (0.0752) Prec@1 90.000 (88.111) Prec@5 100.000 (99.236) +2022-11-14 17:10:42,139 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0511 (0.0748) Prec@1 93.000 (88.178) Prec@5 99.000 (99.233) +2022-11-14 17:10:42,146 Test: [73/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0437 (0.0744) Prec@1 93.000 (88.243) Prec@5 100.000 (99.243) +2022-11-14 17:10:42,154 Test: [74/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1055 (0.0748) Prec@1 85.000 (88.200) Prec@5 100.000 (99.253) +2022-11-14 17:10:42,161 Test: [75/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0747) Prec@1 88.000 (88.197) Prec@5 99.000 (99.250) +2022-11-14 17:10:42,169 Test: [76/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0748) Prec@1 87.000 (88.182) Prec@5 99.000 (99.247) +2022-11-14 17:10:42,177 Test: [77/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0890 (0.0749) Prec@1 85.000 (88.141) Prec@5 98.000 (99.231) +2022-11-14 17:10:42,184 Test: [78/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0586 (0.0747) Prec@1 91.000 (88.177) Prec@5 100.000 (99.241) +2022-11-14 17:10:42,192 Test: [79/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0736 (0.0747) Prec@1 89.000 (88.188) Prec@5 97.000 (99.213) +2022-11-14 17:10:42,200 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0761 (0.0747) Prec@1 88.000 (88.185) Prec@5 98.000 (99.198) +2022-11-14 17:10:42,207 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0748) Prec@1 85.000 (88.146) Prec@5 100.000 (99.207) +2022-11-14 17:10:42,215 Test: [82/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0906 (0.0750) Prec@1 86.000 (88.120) Prec@5 98.000 (99.193) +2022-11-14 17:10:42,223 Test: [83/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0329 (0.0745) Prec@1 94.000 (88.190) Prec@5 100.000 (99.202) +2022-11-14 17:10:42,230 Test: [84/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0949 (0.0748) Prec@1 83.000 (88.129) Prec@5 100.000 (99.212) +2022-11-14 17:10:42,238 Test: [85/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1000 (0.0751) Prec@1 86.000 (88.105) Prec@5 100.000 (99.221) +2022-11-14 17:10:42,245 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1020 (0.0754) Prec@1 84.000 (88.057) Prec@5 100.000 (99.230) +2022-11-14 17:10:42,253 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0755) Prec@1 87.000 (88.045) Prec@5 99.000 (99.227) +2022-11-14 17:10:42,260 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0753) Prec@1 93.000 (88.101) Prec@5 100.000 (99.236) +2022-11-14 17:10:42,268 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0752) Prec@1 92.000 (88.144) Prec@5 100.000 (99.244) +2022-11-14 17:10:42,276 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0752) Prec@1 90.000 (88.165) Prec@5 100.000 (99.253) +2022-11-14 17:10:42,284 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0453 (0.0748) Prec@1 93.000 (88.217) Prec@5 99.000 (99.250) +2022-11-14 17:10:42,291 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0751) Prec@1 84.000 (88.172) Prec@5 100.000 (99.258) +2022-11-14 17:10:42,299 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0750) Prec@1 90.000 (88.191) Prec@5 99.000 (99.255) +2022-11-14 17:10:42,306 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0752) Prec@1 85.000 (88.158) Prec@5 99.000 (99.253) +2022-11-14 17:10:42,314 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0752) Prec@1 88.000 (88.156) Prec@5 100.000 (99.260) +2022-11-14 17:10:42,321 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0749) Prec@1 92.000 (88.196) Prec@5 98.000 (99.247) +2022-11-14 17:10:42,330 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0750) Prec@1 89.000 (88.204) Prec@5 98.000 (99.235) +2022-11-14 17:10:42,337 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0753) Prec@1 84.000 (88.162) Prec@5 97.000 (99.212) +2022-11-14 17:10:42,344 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0753) Prec@1 86.000 (88.140) Prec@5 99.000 (99.210) +2022-11-14 17:10:42,398 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:10:42,716 Epoch: [482][0/500] Time 0.021 (0.021) Data 0.241 (0.241) Loss 0.0445 (0.0445) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:42,913 Epoch: [482][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0189 (0.0317) Prec@1 97.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:10:43,104 Epoch: [482][20/500] Time 0.020 (0.017) Data 0.002 (0.013) Loss 0.0328 (0.0321) Prec@1 94.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:43,294 Epoch: [482][30/500] Time 0.018 (0.017) Data 0.002 (0.009) Loss 0.0193 (0.0289) Prec@1 98.000 (95.750) Prec@5 99.000 (99.750) +2022-11-14 17:10:43,484 Epoch: [482][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0302 (0.0291) Prec@1 95.000 (95.600) Prec@5 100.000 (99.800) +2022-11-14 17:10:43,675 Epoch: [482][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0204 (0.0277) Prec@1 97.000 (95.833) Prec@5 100.000 (99.833) +2022-11-14 17:10:43,862 Epoch: [482][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0440 (0.0300) Prec@1 92.000 (95.286) Prec@5 99.000 (99.714) +2022-11-14 17:10:44,055 Epoch: [482][70/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0201 (0.0288) Prec@1 97.000 (95.500) Prec@5 100.000 (99.750) +2022-11-14 17:10:44,246 Epoch: [482][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0185 (0.0276) Prec@1 98.000 (95.778) Prec@5 100.000 (99.778) +2022-11-14 17:10:44,435 Epoch: [482][90/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0352 (0.0284) Prec@1 93.000 (95.500) Prec@5 100.000 (99.800) +2022-11-14 17:10:44,623 Epoch: [482][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0203 (0.0277) Prec@1 97.000 (95.636) Prec@5 100.000 (99.818) +2022-11-14 17:10:44,809 Epoch: [482][110/500] Time 0.016 (0.017) Data 0.001 (0.004) Loss 0.0249 (0.0274) Prec@1 94.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:10:44,995 Epoch: [482][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0361 (0.0281) Prec@1 94.000 (95.385) Prec@5 100.000 (99.846) +2022-11-14 17:10:45,183 Epoch: [482][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0290 (0.0282) Prec@1 95.000 (95.357) Prec@5 100.000 (99.857) +2022-11-14 17:10:45,368 Epoch: [482][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0232 (0.0278) Prec@1 97.000 (95.467) Prec@5 99.000 (99.800) +2022-11-14 17:10:45,554 Epoch: [482][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0184 (0.0272) Prec@1 96.000 (95.500) Prec@5 100.000 (99.812) +2022-11-14 17:10:45,817 Epoch: [482][160/500] Time 0.029 (0.017) Data 0.002 (0.003) Loss 0.0259 (0.0272) Prec@1 96.000 (95.529) Prec@5 100.000 (99.824) +2022-11-14 17:10:46,146 Epoch: [482][170/500] Time 0.033 (0.018) Data 0.002 (0.003) Loss 0.0281 (0.0272) Prec@1 96.000 (95.556) Prec@5 100.000 (99.833) +2022-11-14 17:10:46,474 Epoch: [482][180/500] Time 0.031 (0.018) Data 0.002 (0.003) Loss 0.0109 (0.0263) Prec@1 99.000 (95.737) Prec@5 100.000 (99.842) +2022-11-14 17:10:46,792 Epoch: [482][190/500] Time 0.031 (0.019) Data 0.002 (0.003) Loss 0.0470 (0.0274) Prec@1 91.000 (95.500) Prec@5 100.000 (99.850) +2022-11-14 17:10:47,110 Epoch: [482][200/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0294 (0.0275) Prec@1 95.000 (95.476) Prec@5 100.000 (99.857) +2022-11-14 17:10:47,417 Epoch: [482][210/500] Time 0.029 (0.020) Data 0.001 (0.003) Loss 0.0153 (0.0269) Prec@1 98.000 (95.591) Prec@5 99.000 (99.818) +2022-11-14 17:10:47,729 Epoch: [482][220/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0338 (0.0272) Prec@1 94.000 (95.522) Prec@5 100.000 (99.826) +2022-11-14 17:10:48,049 Epoch: [482][230/500] Time 0.030 (0.020) Data 0.002 (0.003) Loss 0.0315 (0.0274) Prec@1 96.000 (95.542) Prec@5 100.000 (99.833) +2022-11-14 17:10:48,361 Epoch: [482][240/500] Time 0.032 (0.021) Data 0.002 (0.003) Loss 0.0265 (0.0274) Prec@1 96.000 (95.560) Prec@5 100.000 (99.840) +2022-11-14 17:10:48,668 Epoch: [482][250/500] Time 0.029 (0.021) Data 0.001 (0.003) Loss 0.0258 (0.0273) Prec@1 94.000 (95.500) Prec@5 100.000 (99.846) +2022-11-14 17:10:48,977 Epoch: [482][260/500] Time 0.032 (0.021) Data 0.002 (0.003) Loss 0.0367 (0.0277) Prec@1 94.000 (95.444) Prec@5 100.000 (99.852) +2022-11-14 17:10:49,291 Epoch: [482][270/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0218 (0.0274) Prec@1 96.000 (95.464) Prec@5 99.000 (99.821) +2022-11-14 17:10:49,597 Epoch: [482][280/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0336 (0.0277) Prec@1 93.000 (95.379) Prec@5 100.000 (99.828) +2022-11-14 17:10:49,907 Epoch: [482][290/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0185 (0.0273) Prec@1 97.000 (95.433) Prec@5 99.000 (99.800) +2022-11-14 17:10:50,229 Epoch: [482][300/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0155 (0.0270) Prec@1 99.000 (95.548) Prec@5 100.000 (99.806) +2022-11-14 17:10:50,544 Epoch: [482][310/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0312 (0.0271) Prec@1 95.000 (95.531) Prec@5 100.000 (99.812) +2022-11-14 17:10:50,853 Epoch: [482][320/500] Time 0.029 (0.022) Data 0.001 (0.002) Loss 0.0390 (0.0275) Prec@1 94.000 (95.485) Prec@5 100.000 (99.818) +2022-11-14 17:10:51,159 Epoch: [482][330/500] Time 0.028 (0.023) Data 0.001 (0.002) Loss 0.0253 (0.0274) Prec@1 96.000 (95.500) Prec@5 100.000 (99.824) +2022-11-14 17:10:51,463 Epoch: [482][340/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0157 (0.0271) Prec@1 98.000 (95.571) Prec@5 100.000 (99.829) +2022-11-14 17:10:51,773 Epoch: [482][350/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0200 (0.0269) Prec@1 97.000 (95.611) Prec@5 100.000 (99.833) +2022-11-14 17:10:52,078 Epoch: [482][360/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0230 (0.0268) Prec@1 96.000 (95.622) Prec@5 100.000 (99.838) +2022-11-14 17:10:52,386 Epoch: [482][370/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0336 (0.0269) Prec@1 95.000 (95.605) Prec@5 100.000 (99.842) +2022-11-14 17:10:52,693 Epoch: [482][380/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0494 (0.0275) Prec@1 93.000 (95.538) Prec@5 100.000 (99.846) +2022-11-14 17:10:53,011 Epoch: [482][390/500] Time 0.030 (0.023) Data 0.002 (0.002) Loss 0.0164 (0.0272) Prec@1 97.000 (95.575) Prec@5 100.000 (99.850) +2022-11-14 17:10:53,322 Epoch: [482][400/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0236 (0.0272) Prec@1 96.000 (95.585) Prec@5 100.000 (99.854) +2022-11-14 17:10:53,626 Epoch: [482][410/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0444 (0.0276) Prec@1 92.000 (95.500) Prec@5 98.000 (99.810) +2022-11-14 17:10:53,933 Epoch: [482][420/500] Time 0.030 (0.024) Data 0.002 (0.002) Loss 0.0239 (0.0275) Prec@1 96.000 (95.512) Prec@5 100.000 (99.814) +2022-11-14 17:10:54,186 Epoch: [482][430/500] Time 0.022 (0.024) Data 0.001 (0.002) Loss 0.0254 (0.0274) Prec@1 97.000 (95.545) Prec@5 100.000 (99.818) +2022-11-14 17:10:54,391 Epoch: [482][440/500] Time 0.019 (0.023) Data 0.001 (0.002) Loss 0.0178 (0.0272) Prec@1 98.000 (95.600) Prec@5 100.000 (99.822) +2022-11-14 17:10:54,594 Epoch: [482][450/500] Time 0.019 (0.023) Data 0.002 (0.002) Loss 0.0316 (0.0273) Prec@1 94.000 (95.565) Prec@5 100.000 (99.826) +2022-11-14 17:10:54,801 Epoch: [482][460/500] Time 0.019 (0.023) Data 0.001 (0.002) Loss 0.0277 (0.0273) Prec@1 93.000 (95.511) Prec@5 100.000 (99.830) +2022-11-14 17:10:55,006 Epoch: [482][470/500] Time 0.021 (0.023) Data 0.002 (0.002) Loss 0.0175 (0.0271) Prec@1 97.000 (95.542) Prec@5 100.000 (99.833) +2022-11-14 17:10:55,216 Epoch: [482][480/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0158 (0.0269) Prec@1 98.000 (95.592) Prec@5 100.000 (99.837) +2022-11-14 17:10:55,420 Epoch: [482][490/500] Time 0.021 (0.023) Data 0.001 (0.002) Loss 0.0267 (0.0269) Prec@1 96.000 (95.600) Prec@5 100.000 (99.840) +2022-11-14 17:10:55,604 Epoch: [482][499/500] Time 0.018 (0.023) Data 0.002 (0.002) Loss 0.0434 (0.0272) Prec@1 93.000 (95.549) Prec@5 100.000 (99.843) +2022-11-14 17:10:55,904 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0621 (0.0621) Prec@1 88.000 (88.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:55,911 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0797 (0.0709) Prec@1 86.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:55,918 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0861 (0.0760) Prec@1 86.000 (86.667) Prec@5 100.000 (100.000) +2022-11-14 17:10:55,928 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0653 (0.0733) Prec@1 89.000 (87.250) Prec@5 99.000 (99.750) +2022-11-14 17:10:55,936 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0742) Prec@1 87.000 (87.200) Prec@5 99.000 (99.600) +2022-11-14 17:10:55,942 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0661 (0.0728) Prec@1 90.000 (87.667) Prec@5 100.000 (99.667) +2022-11-14 17:10:55,949 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0572 (0.0706) Prec@1 92.000 (88.286) Prec@5 99.000 (99.571) +2022-11-14 17:10:55,957 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0709) Prec@1 85.000 (87.875) Prec@5 100.000 (99.625) +2022-11-14 17:10:55,964 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0706) Prec@1 91.000 (88.222) Prec@5 98.000 (99.444) +2022-11-14 17:10:55,971 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0725) Prec@1 86.000 (88.000) Prec@5 98.000 (99.300) +2022-11-14 17:10:55,979 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0509 (0.0705) Prec@1 91.000 (88.273) Prec@5 100.000 (99.364) +2022-11-14 17:10:55,987 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0713) Prec@1 88.000 (88.250) Prec@5 99.000 (99.333) +2022-11-14 17:10:55,994 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0697) Prec@1 92.000 (88.538) Prec@5 100.000 (99.385) +2022-11-14 17:10:56,002 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0686) Prec@1 92.000 (88.786) Prec@5 100.000 (99.429) +2022-11-14 17:10:56,009 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0688) Prec@1 89.000 (88.800) Prec@5 98.000 (99.333) +2022-11-14 17:10:56,017 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0692) Prec@1 89.000 (88.812) Prec@5 100.000 (99.375) +2022-11-14 17:10:56,024 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0680) Prec@1 94.000 (89.118) Prec@5 99.000 (99.353) +2022-11-14 17:10:56,032 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1011 (0.0698) Prec@1 87.000 (89.000) Prec@5 100.000 (99.389) +2022-11-14 17:10:56,039 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0707) Prec@1 83.000 (88.684) Prec@5 99.000 (99.368) +2022-11-14 17:10:56,047 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0932 (0.0719) Prec@1 85.000 (88.500) Prec@5 97.000 (99.250) +2022-11-14 17:10:56,055 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0716) Prec@1 90.000 (88.571) Prec@5 99.000 (99.238) +2022-11-14 17:10:56,062 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0824 (0.0721) Prec@1 86.000 (88.455) Prec@5 100.000 (99.273) +2022-11-14 17:10:56,070 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.0739) Prec@1 83.000 (88.217) Prec@5 98.000 (99.217) +2022-11-14 17:10:56,077 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0738) Prec@1 90.000 (88.292) Prec@5 100.000 (99.250) +2022-11-14 17:10:56,085 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0742) Prec@1 88.000 (88.280) Prec@5 100.000 (99.280) +2022-11-14 17:10:56,093 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0741) Prec@1 89.000 (88.308) Prec@5 98.000 (99.231) +2022-11-14 17:10:56,101 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0738) Prec@1 90.000 (88.370) Prec@5 99.000 (99.222) +2022-11-14 17:10:56,109 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0444 (0.0727) Prec@1 93.000 (88.536) Prec@5 100.000 (99.250) +2022-11-14 17:10:56,117 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0721) Prec@1 92.000 (88.655) Prec@5 99.000 (99.241) +2022-11-14 17:10:56,124 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0721) Prec@1 88.000 (88.633) Prec@5 100.000 (99.267) +2022-11-14 17:10:56,132 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0716) Prec@1 91.000 (88.710) Prec@5 100.000 (99.290) +2022-11-14 17:10:56,140 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0704 (0.0715) Prec@1 89.000 (88.719) Prec@5 99.000 (99.281) +2022-11-14 17:10:56,148 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0717) Prec@1 87.000 (88.667) Prec@5 100.000 (99.303) +2022-11-14 17:10:56,156 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0722) Prec@1 85.000 (88.559) Prec@5 100.000 (99.324) +2022-11-14 17:10:56,163 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0862 (0.0726) Prec@1 85.000 (88.457) Prec@5 98.000 (99.286) +2022-11-14 17:10:56,171 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0727) Prec@1 90.000 (88.500) Prec@5 100.000 (99.306) +2022-11-14 17:10:56,178 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0953 (0.0733) Prec@1 85.000 (88.405) Prec@5 99.000 (99.297) +2022-11-14 17:10:56,186 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0737) Prec@1 87.000 (88.368) Prec@5 100.000 (99.316) +2022-11-14 17:10:56,194 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0731) Prec@1 94.000 (88.513) Prec@5 99.000 (99.308) +2022-11-14 17:10:56,201 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0731) Prec@1 90.000 (88.550) Prec@5 99.000 (99.300) +2022-11-14 17:10:56,209 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0736) Prec@1 85.000 (88.463) Prec@5 98.000 (99.268) +2022-11-14 17:10:56,216 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0735) Prec@1 90.000 (88.500) Prec@5 99.000 (99.262) +2022-11-14 17:10:56,224 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0733) Prec@1 90.000 (88.535) Prec@5 99.000 (99.256) +2022-11-14 17:10:56,232 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0732) Prec@1 89.000 (88.545) Prec@5 99.000 (99.250) +2022-11-14 17:10:56,239 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0734) Prec@1 85.000 (88.467) Prec@5 99.000 (99.244) +2022-11-14 17:10:56,246 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1071 (0.0742) Prec@1 84.000 (88.370) Prec@5 99.000 (99.239) +2022-11-14 17:10:56,254 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0742) Prec@1 90.000 (88.404) Prec@5 99.000 (99.234) +2022-11-14 17:10:56,261 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0745) Prec@1 85.000 (88.333) Prec@5 99.000 (99.229) +2022-11-14 17:10:56,269 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0452 (0.0739) Prec@1 93.000 (88.429) Prec@5 100.000 (99.245) +2022-11-14 17:10:56,277 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1125 (0.0747) Prec@1 83.000 (88.320) Prec@5 99.000 (99.240) +2022-11-14 17:10:56,284 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0748) Prec@1 88.000 (88.314) Prec@5 100.000 (99.255) +2022-11-14 17:10:56,292 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0747) Prec@1 89.000 (88.327) Prec@5 99.000 (99.250) +2022-11-14 17:10:56,299 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0746) Prec@1 88.000 (88.321) Prec@5 100.000 (99.264) +2022-11-14 17:10:56,307 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0745) Prec@1 91.000 (88.370) Prec@5 99.000 (99.259) +2022-11-14 17:10:56,314 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0779 (0.0746) Prec@1 88.000 (88.364) Prec@5 100.000 (99.273) +2022-11-14 17:10:56,322 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0746) Prec@1 88.000 (88.357) Prec@5 99.000 (99.268) +2022-11-14 17:10:56,329 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0742) Prec@1 90.000 (88.386) Prec@5 100.000 (99.281) +2022-11-14 17:10:56,337 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0744) Prec@1 90.000 (88.414) Prec@5 98.000 (99.259) +2022-11-14 17:10:56,344 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0991 (0.0748) Prec@1 84.000 (88.339) Prec@5 100.000 (99.271) +2022-11-14 17:10:56,352 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0748) Prec@1 88.000 (88.333) Prec@5 100.000 (99.283) +2022-11-14 17:10:56,359 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0776 (0.0748) Prec@1 88.000 (88.328) Prec@5 97.000 (99.246) +2022-11-14 17:10:56,367 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0747) Prec@1 87.000 (88.306) Prec@5 98.000 (99.226) +2022-11-14 17:10:56,375 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0696 (0.0747) Prec@1 88.000 (88.302) Prec@5 100.000 (99.238) +2022-11-14 17:10:56,383 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0463 (0.0742) Prec@1 94.000 (88.391) Prec@5 99.000 (99.234) +2022-11-14 17:10:56,391 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0910 (0.0745) Prec@1 85.000 (88.338) Prec@5 100.000 (99.246) +2022-11-14 17:10:56,398 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0712 (0.0744) Prec@1 89.000 (88.348) Prec@5 98.000 (99.227) +2022-11-14 17:10:56,406 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0442 (0.0740) Prec@1 92.000 (88.403) Prec@5 99.000 (99.224) +2022-11-14 17:10:56,413 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0740) Prec@1 89.000 (88.412) Prec@5 96.000 (99.176) +2022-11-14 17:10:56,421 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0698 (0.0739) Prec@1 88.000 (88.406) Prec@5 99.000 (99.174) +2022-11-14 17:10:56,428 Test: [69/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0590 (0.0737) Prec@1 91.000 (88.443) Prec@5 100.000 (99.186) +2022-11-14 17:10:56,436 Test: [70/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0983 (0.0740) Prec@1 87.000 (88.423) Prec@5 100.000 (99.197) +2022-11-14 17:10:56,444 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0550 (0.0738) Prec@1 91.000 (88.458) Prec@5 100.000 (99.208) +2022-11-14 17:10:56,451 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0454 (0.0734) Prec@1 94.000 (88.534) Prec@5 100.000 (99.219) +2022-11-14 17:10:56,459 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0497 (0.0731) Prec@1 92.000 (88.581) Prec@5 100.000 (99.230) +2022-11-14 17:10:56,466 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1085 (0.0735) Prec@1 83.000 (88.507) Prec@5 100.000 (99.240) +2022-11-14 17:10:56,474 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0673 (0.0735) Prec@1 91.000 (88.539) Prec@5 100.000 (99.250) +2022-11-14 17:10:56,481 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0920 (0.0737) Prec@1 85.000 (88.494) Prec@5 96.000 (99.208) +2022-11-14 17:10:56,489 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0737) Prec@1 90.000 (88.513) Prec@5 100.000 (99.218) +2022-11-14 17:10:56,497 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0797 (0.0738) Prec@1 87.000 (88.494) Prec@5 99.000 (99.215) +2022-11-14 17:10:56,504 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0783 (0.0738) Prec@1 87.000 (88.475) Prec@5 100.000 (99.225) +2022-11-14 17:10:56,512 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0740) Prec@1 88.000 (88.469) Prec@5 97.000 (99.198) +2022-11-14 17:10:56,519 Test: [81/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0773 (0.0741) Prec@1 86.000 (88.439) Prec@5 100.000 (99.207) +2022-11-14 17:10:56,527 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0691 (0.0740) Prec@1 90.000 (88.458) Prec@5 99.000 (99.205) +2022-11-14 17:10:56,535 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0581 (0.0738) Prec@1 91.000 (88.488) Prec@5 99.000 (99.202) +2022-11-14 17:10:56,542 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0927 (0.0741) Prec@1 82.000 (88.412) Prec@5 100.000 (99.212) +2022-11-14 17:10:56,550 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0901 (0.0742) Prec@1 87.000 (88.395) Prec@5 99.000 (99.209) +2022-11-14 17:10:56,557 Test: [86/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0740 (0.0742) Prec@1 90.000 (88.414) Prec@5 99.000 (99.207) +2022-11-14 17:10:56,565 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0770 (0.0743) Prec@1 89.000 (88.420) Prec@5 99.000 (99.205) +2022-11-14 17:10:56,572 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0790 (0.0743) Prec@1 88.000 (88.416) Prec@5 100.000 (99.213) +2022-11-14 17:10:56,580 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0721 (0.0743) Prec@1 91.000 (88.444) Prec@5 99.000 (99.211) +2022-11-14 17:10:56,587 Test: [90/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0472 (0.0740) Prec@1 93.000 (88.495) Prec@5 100.000 (99.220) +2022-11-14 17:10:56,595 Test: [91/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0531 (0.0738) Prec@1 93.000 (88.543) Prec@5 99.000 (99.217) +2022-11-14 17:10:56,603 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0904 (0.0740) Prec@1 85.000 (88.505) Prec@5 100.000 (99.226) +2022-11-14 17:10:56,610 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0690 (0.0739) Prec@1 89.000 (88.511) Prec@5 98.000 (99.213) +2022-11-14 17:10:56,618 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0913 (0.0741) Prec@1 86.000 (88.484) Prec@5 98.000 (99.200) +2022-11-14 17:10:56,625 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0602 (0.0739) Prec@1 93.000 (88.531) Prec@5 100.000 (99.208) +2022-11-14 17:10:56,633 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0416 (0.0736) Prec@1 93.000 (88.577) Prec@5 99.000 (99.206) +2022-11-14 17:10:56,640 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0925 (0.0738) Prec@1 86.000 (88.551) Prec@5 98.000 (99.194) +2022-11-14 17:10:56,648 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0881 (0.0739) Prec@1 87.000 (88.535) Prec@5 99.000 (99.192) +2022-11-14 17:10:56,655 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0795 (0.0740) Prec@1 88.000 (88.530) Prec@5 100.000 (99.200) +2022-11-14 17:10:56,711 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:10:57,034 Epoch: [483][0/500] Time 0.026 (0.026) Data 0.239 (0.239) Loss 0.0212 (0.0212) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:10:57,230 Epoch: [483][10/500] Time 0.016 (0.018) Data 0.002 (0.023) Loss 0.0096 (0.0154) Prec@1 99.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 17:10:57,417 Epoch: [483][20/500] Time 0.016 (0.017) Data 0.001 (0.013) Loss 0.0360 (0.0223) Prec@1 94.000 (96.333) Prec@5 100.000 (100.000) +2022-11-14 17:10:57,602 Epoch: [483][30/500] Time 0.018 (0.017) Data 0.001 (0.009) Loss 0.0386 (0.0264) Prec@1 94.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:10:57,787 Epoch: [483][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0348 (0.0280) Prec@1 94.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:10:57,980 Epoch: [483][50/500] Time 0.018 (0.017) Data 0.002 (0.006) Loss 0.0289 (0.0282) Prec@1 95.000 (95.333) Prec@5 99.000 (99.833) +2022-11-14 17:10:58,181 Epoch: [483][60/500] Time 0.019 (0.017) Data 0.002 (0.005) Loss 0.0176 (0.0267) Prec@1 98.000 (95.714) Prec@5 100.000 (99.857) +2022-11-14 17:10:58,382 Epoch: [483][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0069 (0.0242) Prec@1 99.000 (96.125) Prec@5 100.000 (99.875) +2022-11-14 17:10:58,580 Epoch: [483][80/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0258 (0.0244) Prec@1 96.000 (96.111) Prec@5 100.000 (99.889) +2022-11-14 17:10:58,786 Epoch: [483][90/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0245 (0.0244) Prec@1 97.000 (96.200) Prec@5 99.000 (99.800) +2022-11-14 17:10:58,992 Epoch: [483][100/500] Time 0.022 (0.017) Data 0.001 (0.004) Loss 0.0280 (0.0247) Prec@1 97.000 (96.273) Prec@5 100.000 (99.818) +2022-11-14 17:10:59,193 Epoch: [483][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0294 (0.0251) Prec@1 96.000 (96.250) Prec@5 100.000 (99.833) +2022-11-14 17:10:59,395 Epoch: [483][120/500] Time 0.022 (0.017) Data 0.002 (0.004) Loss 0.0110 (0.0240) Prec@1 99.000 (96.462) Prec@5 100.000 (99.846) +2022-11-14 17:10:59,596 Epoch: [483][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0279 (0.0243) Prec@1 95.000 (96.357) Prec@5 100.000 (99.857) +2022-11-14 17:10:59,800 Epoch: [483][140/500] Time 0.023 (0.018) Data 0.001 (0.003) Loss 0.0211 (0.0241) Prec@1 96.000 (96.333) Prec@5 100.000 (99.867) +2022-11-14 17:11:00,002 Epoch: [483][150/500] Time 0.017 (0.018) Data 0.002 (0.003) Loss 0.0270 (0.0243) Prec@1 95.000 (96.250) Prec@5 100.000 (99.875) +2022-11-14 17:11:00,210 Epoch: [483][160/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0196 (0.0240) Prec@1 97.000 (96.294) Prec@5 100.000 (99.882) +2022-11-14 17:11:00,415 Epoch: [483][170/500] Time 0.018 (0.018) Data 0.002 (0.003) Loss 0.0273 (0.0242) Prec@1 95.000 (96.222) Prec@5 99.000 (99.833) +2022-11-14 17:11:00,610 Epoch: [483][180/500] Time 0.022 (0.018) Data 0.001 (0.003) Loss 0.0347 (0.0247) Prec@1 95.000 (96.158) Prec@5 100.000 (99.842) +2022-11-14 17:11:00,808 Epoch: [483][190/500] Time 0.020 (0.018) Data 0.001 (0.003) Loss 0.0250 (0.0247) Prec@1 94.000 (96.050) Prec@5 100.000 (99.850) +2022-11-14 17:11:01,066 Epoch: [483][200/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0212 (0.0246) Prec@1 97.000 (96.095) Prec@5 100.000 (99.857) +2022-11-14 17:11:01,333 Epoch: [483][210/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0370 (0.0251) Prec@1 93.000 (95.955) Prec@5 100.000 (99.864) +2022-11-14 17:11:01,598 Epoch: [483][220/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0230 (0.0250) Prec@1 97.000 (96.000) Prec@5 100.000 (99.870) +2022-11-14 17:11:01,865 Epoch: [483][230/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0283 (0.0252) Prec@1 93.000 (95.875) Prec@5 100.000 (99.875) +2022-11-14 17:11:02,133 Epoch: [483][240/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0327 (0.0255) Prec@1 94.000 (95.800) Prec@5 100.000 (99.880) +2022-11-14 17:11:02,398 Epoch: [483][250/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0169 (0.0252) Prec@1 97.000 (95.846) Prec@5 100.000 (99.885) +2022-11-14 17:11:02,665 Epoch: [483][260/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0309 (0.0254) Prec@1 93.000 (95.741) Prec@5 100.000 (99.889) +2022-11-14 17:11:02,931 Epoch: [483][270/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0184 (0.0251) Prec@1 97.000 (95.786) Prec@5 100.000 (99.893) +2022-11-14 17:11:03,201 Epoch: [483][280/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0379 (0.0256) Prec@1 92.000 (95.655) Prec@5 100.000 (99.897) +2022-11-14 17:11:03,469 Epoch: [483][290/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0251 (0.0255) Prec@1 96.000 (95.667) Prec@5 100.000 (99.900) +2022-11-14 17:11:03,738 Epoch: [483][300/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0164 (0.0252) Prec@1 98.000 (95.742) Prec@5 100.000 (99.903) +2022-11-14 17:11:04,003 Epoch: [483][310/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0321 (0.0255) Prec@1 95.000 (95.719) Prec@5 98.000 (99.844) +2022-11-14 17:11:04,269 Epoch: [483][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0408 (0.0259) Prec@1 94.000 (95.667) Prec@5 100.000 (99.848) +2022-11-14 17:11:04,539 Epoch: [483][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0279 (0.0260) Prec@1 97.000 (95.706) Prec@5 100.000 (99.853) +2022-11-14 17:11:04,803 Epoch: [483][340/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0112 (0.0256) Prec@1 100.000 (95.829) Prec@5 100.000 (99.857) +2022-11-14 17:11:05,065 Epoch: [483][350/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0575 (0.0264) Prec@1 89.000 (95.639) Prec@5 100.000 (99.861) +2022-11-14 17:11:05,329 Epoch: [483][360/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0107 (0.0260) Prec@1 98.000 (95.703) Prec@5 100.000 (99.865) +2022-11-14 17:11:05,595 Epoch: [483][370/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0207 (0.0259) Prec@1 95.000 (95.684) Prec@5 100.000 (99.868) +2022-11-14 17:11:05,859 Epoch: [483][380/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0349 (0.0261) Prec@1 94.000 (95.641) Prec@5 100.000 (99.872) +2022-11-14 17:11:06,124 Epoch: [483][390/500] Time 0.029 (0.021) Data 0.002 (0.002) Loss 0.0323 (0.0263) Prec@1 94.000 (95.600) Prec@5 100.000 (99.875) +2022-11-14 17:11:06,383 Epoch: [483][400/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0255 (0.0262) Prec@1 97.000 (95.634) Prec@5 100.000 (99.878) +2022-11-14 17:11:06,644 Epoch: [483][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0247 (0.0262) Prec@1 94.000 (95.595) Prec@5 100.000 (99.881) +2022-11-14 17:11:06,905 Epoch: [483][420/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0205 (0.0261) Prec@1 97.000 (95.628) Prec@5 100.000 (99.884) +2022-11-14 17:11:07,169 Epoch: [483][430/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0385 (0.0264) Prec@1 94.000 (95.591) Prec@5 100.000 (99.886) +2022-11-14 17:11:07,426 Epoch: [483][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0454 (0.0268) Prec@1 92.000 (95.511) Prec@5 99.000 (99.867) +2022-11-14 17:11:07,689 Epoch: [483][450/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0297 (0.0268) Prec@1 94.000 (95.478) Prec@5 100.000 (99.870) +2022-11-14 17:11:07,947 Epoch: [483][460/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0178 (0.0267) Prec@1 98.000 (95.532) Prec@5 100.000 (99.872) +2022-11-14 17:11:08,213 Epoch: [483][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0286 (0.0267) Prec@1 96.000 (95.542) Prec@5 100.000 (99.875) +2022-11-14 17:11:08,478 Epoch: [483][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0235 (0.0266) Prec@1 97.000 (95.571) Prec@5 100.000 (99.878) +2022-11-14 17:11:08,743 Epoch: [483][490/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0200 (0.0265) Prec@1 97.000 (95.600) Prec@5 100.000 (99.880) +2022-11-14 17:11:08,978 Epoch: [483][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0229 (0.0264) Prec@1 95.000 (95.588) Prec@5 100.000 (99.882) +2022-11-14 17:11:09,279 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0561 (0.0561) Prec@1 90.000 (90.000) Prec@5 99.000 (99.000) +2022-11-14 17:11:09,286 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0661 (0.0611) Prec@1 90.000 (90.000) Prec@5 100.000 (99.500) +2022-11-14 17:11:09,293 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0618) Prec@1 89.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 17:11:09,304 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0650) Prec@1 89.000 (89.500) Prec@5 100.000 (99.750) +2022-11-14 17:11:09,311 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0591 (0.0638) Prec@1 90.000 (89.600) Prec@5 100.000 (99.800) +2022-11-14 17:11:09,317 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0431 (0.0604) Prec@1 92.000 (90.000) Prec@5 99.000 (99.667) +2022-11-14 17:11:09,324 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0630) Prec@1 88.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 17:11:09,332 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0653) Prec@1 86.000 (89.250) Prec@5 100.000 (99.750) +2022-11-14 17:11:09,339 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0673) Prec@1 86.000 (88.889) Prec@5 98.000 (99.556) +2022-11-14 17:11:09,346 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0683) Prec@1 88.000 (88.800) Prec@5 99.000 (99.500) +2022-11-14 17:11:09,354 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0750 (0.0689) Prec@1 88.000 (88.727) Prec@5 100.000 (99.545) +2022-11-14 17:11:09,361 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0704) Prec@1 86.000 (88.500) Prec@5 100.000 (99.583) +2022-11-14 17:11:09,369 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0691) Prec@1 91.000 (88.692) Prec@5 100.000 (99.615) +2022-11-14 17:11:09,377 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0703) Prec@1 86.000 (88.500) Prec@5 100.000 (99.643) +2022-11-14 17:11:09,384 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0701) Prec@1 88.000 (88.467) Prec@5 100.000 (99.667) +2022-11-14 17:11:09,392 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0690) Prec@1 92.000 (88.688) Prec@5 100.000 (99.688) +2022-11-14 17:11:09,399 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0401 (0.0673) Prec@1 96.000 (89.118) Prec@5 99.000 (99.647) +2022-11-14 17:11:09,407 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1098 (0.0696) Prec@1 83.000 (88.778) Prec@5 100.000 (99.667) +2022-11-14 17:11:09,414 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0699) Prec@1 88.000 (88.737) Prec@5 100.000 (99.684) +2022-11-14 17:11:09,422 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0705) Prec@1 87.000 (88.650) Prec@5 97.000 (99.550) +2022-11-14 17:11:09,429 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0698) Prec@1 91.000 (88.762) Prec@5 100.000 (99.571) +2022-11-14 17:11:09,437 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0705) Prec@1 87.000 (88.682) Prec@5 99.000 (99.545) +2022-11-14 17:11:09,445 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0913 (0.0715) Prec@1 86.000 (88.565) Prec@5 100.000 (99.565) +2022-11-14 17:11:09,452 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0720) Prec@1 87.000 (88.500) Prec@5 99.000 (99.542) +2022-11-14 17:11:09,460 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0724) Prec@1 87.000 (88.440) Prec@5 100.000 (99.560) +2022-11-14 17:11:09,467 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0871 (0.0730) Prec@1 85.000 (88.308) Prec@5 99.000 (99.538) +2022-11-14 17:11:09,475 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0476 (0.0720) Prec@1 93.000 (88.481) Prec@5 100.000 (99.556) +2022-11-14 17:11:09,482 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0565 (0.0715) Prec@1 90.000 (88.536) Prec@5 100.000 (99.571) +2022-11-14 17:11:09,490 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0714) Prec@1 90.000 (88.586) Prec@5 99.000 (99.552) +2022-11-14 17:11:09,499 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0720) Prec@1 85.000 (88.467) Prec@5 99.000 (99.533) +2022-11-14 17:11:09,506 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0719) Prec@1 87.000 (88.419) Prec@5 100.000 (99.548) +2022-11-14 17:11:09,514 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0715) Prec@1 90.000 (88.469) Prec@5 99.000 (99.531) +2022-11-14 17:11:09,522 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0718) Prec@1 86.000 (88.394) Prec@5 100.000 (99.545) +2022-11-14 17:11:09,529 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0723) Prec@1 85.000 (88.294) Prec@5 100.000 (99.559) +2022-11-14 17:11:09,537 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0726) Prec@1 89.000 (88.314) Prec@5 97.000 (99.486) +2022-11-14 17:11:09,544 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0726) Prec@1 89.000 (88.333) Prec@5 100.000 (99.500) +2022-11-14 17:11:09,552 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0726) Prec@1 88.000 (88.324) Prec@5 99.000 (99.486) +2022-11-14 17:11:09,559 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0968 (0.0733) Prec@1 81.000 (88.132) Prec@5 100.000 (99.500) +2022-11-14 17:11:09,567 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0475 (0.0726) Prec@1 95.000 (88.308) Prec@5 99.000 (99.487) +2022-11-14 17:11:09,575 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0612 (0.0723) Prec@1 89.000 (88.325) Prec@5 99.000 (99.475) +2022-11-14 17:11:09,582 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0729) Prec@1 85.000 (88.244) Prec@5 99.000 (99.463) +2022-11-14 17:11:09,590 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0729) Prec@1 87.000 (88.214) Prec@5 100.000 (99.476) +2022-11-14 17:11:09,597 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0507 (0.0724) Prec@1 90.000 (88.256) Prec@5 99.000 (99.465) +2022-11-14 17:11:09,605 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0727) Prec@1 86.000 (88.205) Prec@5 99.000 (99.455) +2022-11-14 17:11:09,612 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0727) Prec@1 87.000 (88.178) Prec@5 100.000 (99.467) +2022-11-14 17:11:09,620 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0730) Prec@1 85.000 (88.109) Prec@5 99.000 (99.457) +2022-11-14 17:11:09,627 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0729) Prec@1 91.000 (88.170) Prec@5 100.000 (99.468) +2022-11-14 17:11:09,635 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0734) Prec@1 86.000 (88.125) Prec@5 98.000 (99.438) +2022-11-14 17:11:09,643 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0731) Prec@1 89.000 (88.143) Prec@5 99.000 (99.429) +2022-11-14 17:11:09,650 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1073 (0.0738) Prec@1 83.000 (88.040) Prec@5 100.000 (99.440) +2022-11-14 17:11:09,658 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0737) Prec@1 89.000 (88.059) Prec@5 100.000 (99.451) +2022-11-14 17:11:09,666 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0737) Prec@1 87.000 (88.038) Prec@5 99.000 (99.442) +2022-11-14 17:11:09,673 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0736) Prec@1 88.000 (88.038) Prec@5 100.000 (99.453) +2022-11-14 17:11:09,681 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0733) Prec@1 91.000 (88.093) Prec@5 99.000 (99.444) +2022-11-14 17:11:09,689 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0834 (0.0734) Prec@1 87.000 (88.073) Prec@5 100.000 (99.455) +2022-11-14 17:11:09,696 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0537 (0.0731) Prec@1 92.000 (88.143) Prec@5 99.000 (99.446) +2022-11-14 17:11:09,704 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0728) Prec@1 91.000 (88.193) Prec@5 100.000 (99.456) +2022-11-14 17:11:09,712 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0727) Prec@1 90.000 (88.224) Prec@5 99.000 (99.448) +2022-11-14 17:11:09,719 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0731) Prec@1 82.000 (88.119) Prec@5 100.000 (99.458) +2022-11-14 17:11:09,727 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0730) Prec@1 86.000 (88.083) Prec@5 99.000 (99.450) +2022-11-14 17:11:09,734 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0731) Prec@1 86.000 (88.049) Prec@5 100.000 (99.459) +2022-11-14 17:11:09,742 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0731) Prec@1 87.000 (88.032) Prec@5 100.000 (99.468) +2022-11-14 17:11:09,750 Test: 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Loss 0.0808 (0.0725) Prec@1 87.000 (88.159) Prec@5 98.000 (99.420) +2022-11-14 17:11:09,804 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0724) Prec@1 90.000 (88.186) Prec@5 100.000 (99.429) +2022-11-14 17:11:09,812 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0728) Prec@1 86.000 (88.155) Prec@5 99.000 (99.423) +2022-11-14 17:11:09,819 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0397 (0.0723) Prec@1 93.000 (88.222) Prec@5 100.000 (99.431) +2022-11-14 17:11:09,827 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0721) Prec@1 93.000 (88.288) Prec@5 99.000 (99.425) +2022-11-14 17:11:09,834 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0443 (0.0717) Prec@1 94.000 (88.365) Prec@5 100.000 (99.432) +2022-11-14 17:11:09,842 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0720) Prec@1 86.000 (88.333) Prec@5 99.000 (99.427) +2022-11-14 17:11:09,850 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0720) Prec@1 91.000 (88.368) Prec@5 99.000 (99.421) +2022-11-14 17:11:09,857 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0721) Prec@1 87.000 (88.351) Prec@5 99.000 (99.416) +2022-11-14 17:11:09,865 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1130 (0.0726) Prec@1 85.000 (88.308) Prec@5 97.000 (99.385) +2022-11-14 17:11:09,873 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0726) Prec@1 88.000 (88.304) Prec@5 100.000 (99.392) +2022-11-14 17:11:09,880 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0726) Prec@1 87.000 (88.287) Prec@5 100.000 (99.400) +2022-11-14 17:11:09,888 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0727) Prec@1 88.000 (88.284) Prec@5 100.000 (99.407) +2022-11-14 17:11:09,896 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0728) Prec@1 86.000 (88.256) Prec@5 100.000 (99.415) +2022-11-14 17:11:09,903 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0729) Prec@1 87.000 (88.241) Prec@5 98.000 (99.398) +2022-11-14 17:11:09,911 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0630 (0.0728) Prec@1 89.000 (88.250) Prec@5 98.000 (99.381) +2022-11-14 17:11:09,919 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0731) Prec@1 85.000 (88.212) Prec@5 100.000 (99.388) +2022-11-14 17:11:09,926 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0946 (0.0734) Prec@1 85.000 (88.174) Prec@5 99.000 (99.384) +2022-11-14 17:11:09,934 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0733) Prec@1 86.000 (88.149) Prec@5 100.000 (99.391) +2022-11-14 17:11:09,942 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0735) Prec@1 86.000 (88.125) Prec@5 99.000 (99.386) +2022-11-14 17:11:09,949 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0734) Prec@1 90.000 (88.146) Prec@5 99.000 (99.382) +2022-11-14 17:11:09,957 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0734) Prec@1 89.000 (88.156) Prec@5 99.000 (99.378) +2022-11-14 17:11:09,965 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0733) Prec@1 90.000 (88.176) Prec@5 100.000 (99.385) +2022-11-14 17:11:09,973 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0731) Prec@1 91.000 (88.207) Prec@5 99.000 (99.380) +2022-11-14 17:11:09,981 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0731) Prec@1 88.000 (88.204) Prec@5 100.000 (99.387) +2022-11-14 17:11:09,988 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0731) Prec@1 90.000 (88.223) Prec@5 97.000 (99.362) +2022-11-14 17:11:09,996 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0731) Prec@1 89.000 (88.232) Prec@5 99.000 (99.358) +2022-11-14 17:11:10,003 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0730) Prec@1 90.000 (88.250) Prec@5 99.000 (99.354) +2022-11-14 17:11:10,011 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0728) Prec@1 90.000 (88.268) Prec@5 99.000 (99.351) +2022-11-14 17:11:10,018 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0728) Prec@1 88.000 (88.265) Prec@5 100.000 (99.357) +2022-11-14 17:11:10,026 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0732) Prec@1 83.000 (88.212) Prec@5 99.000 (99.354) +2022-11-14 17:11:10,033 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0732) Prec@1 88.000 (88.210) Prec@5 99.000 (99.350) +2022-11-14 17:11:10,090 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:11:10,416 Epoch: [484][0/500] Time 0.025 (0.025) Data 0.245 (0.245) Loss 0.0179 (0.0179) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:10,619 Epoch: [484][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0195 (0.0187) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:10,816 Epoch: [484][20/500] Time 0.018 (0.018) Data 0.002 (0.013) Loss 0.0308 (0.0227) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:11,013 Epoch: [484][30/500] Time 0.018 (0.018) Data 0.002 (0.010) Loss 0.0211 (0.0223) Prec@1 97.000 (96.250) Prec@5 100.000 (100.000) +2022-11-14 17:11:11,210 Epoch: [484][40/500] Time 0.018 (0.018) Data 0.001 (0.008) Loss 0.0103 (0.0199) Prec@1 98.000 (96.600) Prec@5 100.000 (100.000) +2022-11-14 17:11:11,404 Epoch: [484][50/500] Time 0.017 (0.018) Data 0.001 (0.006) Loss 0.0257 (0.0209) Prec@1 96.000 (96.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:11,598 Epoch: [484][60/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0168 (0.0203) Prec@1 98.000 (96.714) Prec@5 99.000 (99.857) +2022-11-14 17:11:11,790 Epoch: [484][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0258 (0.0210) Prec@1 96.000 (96.625) Prec@5 100.000 (99.875) +2022-11-14 17:11:11,981 Epoch: [484][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0378 (0.0228) Prec@1 93.000 (96.222) Prec@5 99.000 (99.778) +2022-11-14 17:11:12,173 Epoch: [484][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0266 (0.0232) Prec@1 94.000 (96.000) Prec@5 100.000 (99.800) +2022-11-14 17:11:12,361 Epoch: [484][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0241 (0.0233) Prec@1 94.000 (95.818) Prec@5 100.000 (99.818) +2022-11-14 17:11:12,552 Epoch: [484][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0273 (0.0236) Prec@1 95.000 (95.750) Prec@5 100.000 (99.833) +2022-11-14 17:11:12,744 Epoch: [484][120/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0284 (0.0240) Prec@1 95.000 (95.692) Prec@5 100.000 (99.846) +2022-11-14 17:11:12,939 Epoch: [484][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0326 (0.0246) Prec@1 93.000 (95.500) Prec@5 100.000 (99.857) +2022-11-14 17:11:13,134 Epoch: [484][140/500] Time 0.019 (0.017) Data 0.002 (0.003) Loss 0.0272 (0.0248) Prec@1 95.000 (95.467) Prec@5 100.000 (99.867) +2022-11-14 17:11:13,325 Epoch: [484][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0177 (0.0243) Prec@1 97.000 (95.562) Prec@5 100.000 (99.875) +2022-11-14 17:11:13,528 Epoch: [484][160/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0260 (0.0244) Prec@1 95.000 (95.529) Prec@5 100.000 (99.882) +2022-11-14 17:11:13,739 Epoch: [484][170/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0343 (0.0250) Prec@1 94.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 17:11:14,016 Epoch: [484][180/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0284 (0.0252) Prec@1 97.000 (95.526) Prec@5 100.000 (99.895) +2022-11-14 17:11:14,305 Epoch: [484][190/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0321 (0.0255) Prec@1 95.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:11:14,589 Epoch: [484][200/500] Time 0.027 (0.018) Data 0.002 (0.003) Loss 0.0385 (0.0261) Prec@1 95.000 (95.476) Prec@5 100.000 (99.905) +2022-11-14 17:11:14,878 Epoch: [484][210/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0290 (0.0263) Prec@1 95.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:11:15,165 Epoch: [484][220/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0276 (0.0263) Prec@1 96.000 (95.478) Prec@5 100.000 (99.913) +2022-11-14 17:11:15,446 Epoch: [484][230/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0158 (0.0259) Prec@1 97.000 (95.542) Prec@5 100.000 (99.917) +2022-11-14 17:11:15,728 Epoch: [484][240/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0225 (0.0257) Prec@1 96.000 (95.560) Prec@5 100.000 (99.920) +2022-11-14 17:11:16,014 Epoch: [484][250/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0320 (0.0260) Prec@1 95.000 (95.538) Prec@5 100.000 (99.923) +2022-11-14 17:11:16,303 Epoch: [484][260/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0333 (0.0263) Prec@1 94.000 (95.481) Prec@5 100.000 (99.926) +2022-11-14 17:11:16,593 Epoch: [484][270/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0222 (0.0261) Prec@1 96.000 (95.500) Prec@5 100.000 (99.929) +2022-11-14 17:11:16,879 Epoch: [484][280/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0363 (0.0265) Prec@1 95.000 (95.483) Prec@5 100.000 (99.931) +2022-11-14 17:11:17,169 Epoch: [484][290/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0440 (0.0270) Prec@1 92.000 (95.367) Prec@5 100.000 (99.933) +2022-11-14 17:11:17,453 Epoch: [484][300/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0227 (0.0269) Prec@1 96.000 (95.387) Prec@5 100.000 (99.935) +2022-11-14 17:11:17,740 Epoch: [484][310/500] Time 0.027 (0.021) Data 0.001 (0.002) Loss 0.0369 (0.0272) Prec@1 94.000 (95.344) Prec@5 100.000 (99.938) +2022-11-14 17:11:18,030 Epoch: [484][320/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0345 (0.0274) Prec@1 95.000 (95.333) Prec@5 100.000 (99.939) +2022-11-14 17:11:18,315 Epoch: [484][330/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0251 (0.0274) Prec@1 96.000 (95.353) Prec@5 100.000 (99.941) +2022-11-14 17:11:18,600 Epoch: [484][340/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0573 (0.0282) Prec@1 91.000 (95.229) Prec@5 100.000 (99.943) +2022-11-14 17:11:18,882 Epoch: [484][350/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0185 (0.0280) Prec@1 97.000 (95.278) Prec@5 100.000 (99.944) +2022-11-14 17:11:19,167 Epoch: [484][360/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0159 (0.0276) Prec@1 98.000 (95.351) Prec@5 100.000 (99.946) +2022-11-14 17:11:19,458 Epoch: [484][370/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0395 (0.0279) Prec@1 94.000 (95.316) Prec@5 100.000 (99.947) +2022-11-14 17:11:19,744 Epoch: [484][380/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0382 (0.0282) Prec@1 95.000 (95.308) Prec@5 100.000 (99.949) +2022-11-14 17:11:20,028 Epoch: [484][390/500] Time 0.031 (0.022) Data 0.001 (0.002) Loss 0.0309 (0.0283) Prec@1 94.000 (95.275) Prec@5 100.000 (99.950) +2022-11-14 17:11:20,314 Epoch: [484][400/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0436 (0.0286) Prec@1 94.000 (95.244) Prec@5 100.000 (99.951) +2022-11-14 17:11:20,598 Epoch: [484][410/500] Time 0.031 (0.022) Data 0.002 (0.002) Loss 0.0299 (0.0287) Prec@1 96.000 (95.262) Prec@5 100.000 (99.952) +2022-11-14 17:11:20,886 Epoch: [484][420/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0264 (0.0286) Prec@1 94.000 (95.233) Prec@5 100.000 (99.953) +2022-11-14 17:11:21,173 Epoch: [484][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0139 (0.0283) Prec@1 97.000 (95.273) Prec@5 100.000 (99.955) +2022-11-14 17:11:21,460 Epoch: [484][440/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0197 (0.0281) Prec@1 96.000 (95.289) Prec@5 100.000 (99.956) +2022-11-14 17:11:21,747 Epoch: [484][450/500] Time 0.031 (0.022) Data 0.002 (0.002) Loss 0.0346 (0.0282) Prec@1 94.000 (95.261) Prec@5 100.000 (99.957) +2022-11-14 17:11:22,030 Epoch: [484][460/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0259 (0.0282) Prec@1 97.000 (95.298) Prec@5 100.000 (99.957) +2022-11-14 17:11:22,309 Epoch: [484][470/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0228 (0.0281) Prec@1 96.000 (95.312) Prec@5 100.000 (99.958) +2022-11-14 17:11:22,595 Epoch: [484][480/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0200 (0.0279) Prec@1 95.000 (95.306) Prec@5 99.000 (99.939) +2022-11-14 17:11:22,885 Epoch: [484][490/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0275 (0.0279) Prec@1 96.000 (95.320) Prec@5 100.000 (99.940) +2022-11-14 17:11:23,141 Epoch: [484][499/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0220 (0.0278) Prec@1 96.000 (95.333) Prec@5 100.000 (99.941) +2022-11-14 17:11:23,435 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0503 (0.0503) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:23,442 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0709 (0.0606) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 17:11:23,450 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0598 (0.0603) Prec@1 90.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 17:11:23,461 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0614) Prec@1 89.000 (89.000) Prec@5 99.000 (99.500) +2022-11-14 17:11:23,468 Test: [4/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0527 (0.0597) Prec@1 90.000 (89.200) Prec@5 100.000 (99.600) +2022-11-14 17:11:23,474 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0398 (0.0563) Prec@1 94.000 (90.000) Prec@5 100.000 (99.667) +2022-11-14 17:11:23,481 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0584) Prec@1 89.000 (89.857) Prec@5 100.000 (99.714) +2022-11-14 17:11:23,490 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0644) Prec@1 83.000 (89.000) Prec@5 98.000 (99.500) +2022-11-14 17:11:23,497 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0662) Prec@1 87.000 (88.778) Prec@5 99.000 (99.444) +2022-11-14 17:11:23,504 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0663) Prec@1 91.000 (89.000) Prec@5 99.000 (99.400) +2022-11-14 17:11:23,512 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0658) Prec@1 91.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 17:11:23,519 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0670) Prec@1 87.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 17:11:23,527 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0668) Prec@1 91.000 (89.154) Prec@5 100.000 (99.538) +2022-11-14 17:11:23,535 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0670) Prec@1 88.000 (89.071) Prec@5 98.000 (99.429) +2022-11-14 17:11:23,542 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0671) Prec@1 89.000 (89.067) Prec@5 100.000 (99.467) +2022-11-14 17:11:23,550 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0672) Prec@1 88.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 17:11:23,558 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0664) Prec@1 92.000 (89.176) Prec@5 98.000 (99.412) +2022-11-14 17:11:23,566 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0678) Prec@1 87.000 (89.056) Prec@5 100.000 (99.444) +2022-11-14 17:11:23,573 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0682) Prec@1 87.000 (88.947) Prec@5 98.000 (99.368) +2022-11-14 17:11:23,581 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0826 (0.0689) Prec@1 88.000 (88.900) Prec@5 99.000 (99.350) +2022-11-14 17:11:23,589 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0690) Prec@1 89.000 (88.905) Prec@5 100.000 (99.381) +2022-11-14 17:11:23,596 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0694) Prec@1 87.000 (88.818) Prec@5 98.000 (99.318) +2022-11-14 17:11:23,604 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1027 (0.0708) Prec@1 86.000 (88.696) Prec@5 98.000 (99.261) +2022-11-14 17:11:23,612 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0709) Prec@1 86.000 (88.583) Prec@5 100.000 (99.292) +2022-11-14 17:11:23,619 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0925 (0.0717) Prec@1 84.000 (88.400) Prec@5 100.000 (99.320) +2022-11-14 17:11:23,627 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1009 (0.0728) Prec@1 81.000 (88.115) Prec@5 97.000 (99.231) +2022-11-14 17:11:23,635 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0719) Prec@1 93.000 (88.296) Prec@5 100.000 (99.259) +2022-11-14 17:11:23,642 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0713) Prec@1 91.000 (88.393) Prec@5 100.000 (99.286) +2022-11-14 17:11:23,650 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0712) Prec@1 88.000 (88.379) Prec@5 99.000 (99.276) +2022-11-14 17:11:23,658 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0711) Prec@1 88.000 (88.367) Prec@5 99.000 (99.267) +2022-11-14 17:11:23,666 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0709) Prec@1 89.000 (88.387) Prec@5 100.000 (99.290) +2022-11-14 17:11:23,673 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0706) Prec@1 91.000 (88.469) Prec@5 100.000 (99.312) +2022-11-14 17:11:23,681 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0705) Prec@1 89.000 (88.485) Prec@5 100.000 (99.333) +2022-11-14 17:11:23,689 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1064 (0.0716) Prec@1 84.000 (88.353) Prec@5 100.000 (99.353) +2022-11-14 17:11:23,696 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0717) Prec@1 88.000 (88.343) Prec@5 98.000 (99.314) +2022-11-14 17:11:23,704 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0591 (0.0713) Prec@1 91.000 (88.417) Prec@5 100.000 (99.333) +2022-11-14 17:11:23,712 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0714) Prec@1 89.000 (88.432) Prec@5 99.000 (99.324) +2022-11-14 17:11:23,719 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0721) Prec@1 84.000 (88.316) Prec@5 100.000 (99.342) +2022-11-14 17:11:23,727 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0714) Prec@1 95.000 (88.487) Prec@5 99.000 (99.333) +2022-11-14 17:11:23,735 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0711) Prec@1 90.000 (88.525) Prec@5 100.000 (99.350) +2022-11-14 17:11:23,743 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0717) Prec@1 86.000 (88.463) Prec@5 99.000 (99.341) +2022-11-14 17:11:23,750 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0716) Prec@1 89.000 (88.476) Prec@5 98.000 (99.310) +2022-11-14 17:11:23,758 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0715) Prec@1 88.000 (88.465) Prec@5 99.000 (99.302) +2022-11-14 17:11:23,766 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0715) Prec@1 90.000 (88.500) Prec@5 98.000 (99.273) +2022-11-14 17:11:23,774 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0714) Prec@1 89.000 (88.511) Prec@5 99.000 (99.267) +2022-11-14 17:11:23,781 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0720) Prec@1 84.000 (88.413) Prec@5 98.000 (99.239) +2022-11-14 17:11:23,789 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0722) Prec@1 86.000 (88.362) Prec@5 100.000 (99.255) +2022-11-14 17:11:23,797 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1213 (0.0732) Prec@1 83.000 (88.250) Prec@5 99.000 (99.250) +2022-11-14 17:11:23,805 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0729) Prec@1 89.000 (88.265) Prec@5 100.000 (99.265) +2022-11-14 17:11:23,813 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1156 (0.0737) Prec@1 80.000 (88.100) Prec@5 100.000 (99.280) +2022-11-14 17:11:23,821 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0731) Prec@1 94.000 (88.216) Prec@5 100.000 (99.294) +2022-11-14 17:11:23,829 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0733) Prec@1 88.000 (88.212) Prec@5 99.000 (99.288) +2022-11-14 17:11:23,837 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0736) Prec@1 87.000 (88.189) Prec@5 100.000 (99.302) +2022-11-14 17:11:23,846 Test: [53/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0735) Prec@1 90.000 (88.222) Prec@5 98.000 (99.278) +2022-11-14 17:11:23,854 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0738) Prec@1 85.000 (88.164) Prec@5 100.000 (99.291) +2022-11-14 17:11:23,862 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0737) Prec@1 90.000 (88.196) Prec@5 99.000 (99.286) +2022-11-14 17:11:23,870 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0738) Prec@1 87.000 (88.175) Prec@5 100.000 (99.298) +2022-11-14 17:11:23,879 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0739) Prec@1 90.000 (88.207) Prec@5 99.000 (99.293) +2022-11-14 17:11:23,887 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0741) Prec@1 87.000 (88.186) Prec@5 100.000 (99.305) +2022-11-14 17:11:23,895 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0741) Prec@1 84.000 (88.117) Prec@5 100.000 (99.317) +2022-11-14 17:11:23,903 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0744) Prec@1 84.000 (88.049) Prec@5 100.000 (99.328) +2022-11-14 17:11:23,910 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0744) Prec@1 89.000 (88.065) Prec@5 99.000 (99.323) +2022-11-14 17:11:23,918 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0410 (0.0738) Prec@1 93.000 (88.143) Prec@5 99.000 (99.317) +2022-11-14 17:11:23,926 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0222 (0.0730) Prec@1 95.000 (88.250) Prec@5 99.000 (99.312) +2022-11-14 17:11:23,934 Test: [64/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0734) Prec@1 85.000 (88.200) Prec@5 100.000 (99.323) +2022-11-14 17:11:23,943 Test: [65/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0734) Prec@1 90.000 (88.227) Prec@5 99.000 (99.318) +2022-11-14 17:11:23,952 Test: [66/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0322 (0.0728) Prec@1 95.000 (88.328) Prec@5 100.000 (99.328) +2022-11-14 17:11:23,961 Test: [67/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0729) Prec@1 90.000 (88.353) Prec@5 99.000 (99.324) +2022-11-14 17:11:23,970 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0729) Prec@1 88.000 (88.348) Prec@5 99.000 (99.319) +2022-11-14 17:11:23,977 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0730 (0.0729) Prec@1 88.000 (88.343) Prec@5 99.000 (99.314) +2022-11-14 17:11:23,985 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1127 (0.0735) Prec@1 84.000 (88.282) Prec@5 99.000 (99.310) +2022-11-14 17:11:23,993 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0734) Prec@1 88.000 (88.278) Prec@5 100.000 (99.319) +2022-11-14 17:11:24,000 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0732) Prec@1 92.000 (88.329) Prec@5 99.000 (99.315) +2022-11-14 17:11:24,008 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0567 (0.0730) Prec@1 91.000 (88.365) Prec@5 100.000 (99.324) +2022-11-14 17:11:24,016 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1112 (0.0735) Prec@1 83.000 (88.293) Prec@5 100.000 (99.333) +2022-11-14 17:11:24,023 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0734) Prec@1 90.000 (88.316) Prec@5 98.000 (99.316) +2022-11-14 17:11:24,030 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0732) Prec@1 92.000 (88.364) Prec@5 99.000 (99.312) +2022-11-14 17:11:24,038 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0733) Prec@1 88.000 (88.359) Prec@5 98.000 (99.295) +2022-11-14 17:11:24,045 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0733) Prec@1 89.000 (88.367) Prec@5 99.000 (99.291) +2022-11-14 17:11:24,053 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0734) Prec@1 87.000 (88.350) Prec@5 100.000 (99.300) +2022-11-14 17:11:24,060 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0735) Prec@1 90.000 (88.370) Prec@5 98.000 (99.284) +2022-11-14 17:11:24,067 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0738) Prec@1 82.000 (88.293) Prec@5 100.000 (99.293) +2022-11-14 17:11:24,075 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0740) Prec@1 86.000 (88.265) Prec@5 99.000 (99.289) +2022-11-14 17:11:24,083 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0740) Prec@1 87.000 (88.250) Prec@5 99.000 (99.286) +2022-11-14 17:11:24,091 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0741) Prec@1 87.000 (88.235) Prec@5 99.000 (99.282) +2022-11-14 17:11:24,098 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0745) Prec@1 83.000 (88.174) Prec@5 100.000 (99.291) +2022-11-14 17:11:24,106 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0744) Prec@1 89.000 (88.184) Prec@5 99.000 (99.287) +2022-11-14 17:11:24,113 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0772 (0.0745) Prec@1 88.000 (88.182) Prec@5 99.000 (99.284) +2022-11-14 17:11:24,121 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0485 (0.0742) Prec@1 91.000 (88.213) Prec@5 99.000 (99.281) +2022-11-14 17:11:24,128 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0835 (0.0743) Prec@1 90.000 (88.233) Prec@5 99.000 (99.278) +2022-11-14 17:11:24,135 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0741) Prec@1 90.000 (88.253) Prec@5 100.000 (99.286) +2022-11-14 17:11:24,143 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0462 (0.0738) Prec@1 93.000 (88.304) Prec@5 100.000 (99.293) +2022-11-14 17:11:24,150 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0795 (0.0739) Prec@1 87.000 (88.290) Prec@5 99.000 (99.290) +2022-11-14 17:11:24,157 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0521 (0.0736) Prec@1 92.000 (88.330) Prec@5 100.000 (99.298) +2022-11-14 17:11:24,165 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0737) Prec@1 86.000 (88.305) Prec@5 99.000 (99.295) +2022-11-14 17:11:24,172 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0736) Prec@1 90.000 (88.323) Prec@5 99.000 (99.292) +2022-11-14 17:11:24,180 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0734) Prec@1 93.000 (88.371) Prec@5 98.000 (99.278) +2022-11-14 17:11:24,187 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0736) Prec@1 87.000 (88.357) Prec@5 97.000 (99.255) +2022-11-14 17:11:24,194 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0973 (0.0739) Prec@1 86.000 (88.333) Prec@5 98.000 (99.242) +2022-11-14 17:11:24,201 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0646 (0.0738) Prec@1 91.000 (88.360) Prec@5 99.000 (99.240) +2022-11-14 17:11:24,259 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:11:24,581 Epoch: [485][0/500] Time 0.032 (0.032) Data 0.236 (0.236) Loss 0.0264 (0.0264) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:24,790 Epoch: [485][10/500] Time 0.019 (0.020) Data 0.002 (0.023) Loss 0.0378 (0.0321) Prec@1 94.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:24,980 Epoch: [485][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0198 (0.0280) Prec@1 97.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:25,170 Epoch: [485][30/500] Time 0.017 (0.018) Data 0.001 (0.009) Loss 0.0402 (0.0310) Prec@1 92.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:25,358 Epoch: [485][40/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0237 (0.0296) Prec@1 95.000 (95.000) Prec@5 99.000 (99.800) +2022-11-14 17:11:25,545 Epoch: [485][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0287 (0.0294) Prec@1 94.000 (94.833) Prec@5 100.000 (99.833) +2022-11-14 17:11:25,733 Epoch: [485][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0287 (0.0293) Prec@1 93.000 (94.571) Prec@5 100.000 (99.857) +2022-11-14 17:11:25,921 Epoch: [485][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0250 (0.0288) Prec@1 95.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 17:11:26,112 Epoch: [485][80/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0399 (0.0300) Prec@1 92.000 (94.333) Prec@5 100.000 (99.889) +2022-11-14 17:11:26,301 Epoch: [485][90/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0303 (0.0300) Prec@1 95.000 (94.400) Prec@5 100.000 (99.900) +2022-11-14 17:11:26,491 Epoch: [485][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0199 (0.0291) Prec@1 97.000 (94.636) Prec@5 100.000 (99.909) +2022-11-14 17:11:26,680 Epoch: [485][110/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0178 (0.0282) Prec@1 97.000 (94.833) Prec@5 100.000 (99.917) +2022-11-14 17:11:26,872 Epoch: [485][120/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0383 (0.0290) Prec@1 94.000 (94.769) Prec@5 100.000 (99.923) +2022-11-14 17:11:27,064 Epoch: [485][130/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0232 (0.0286) Prec@1 97.000 (94.929) Prec@5 100.000 (99.929) +2022-11-14 17:11:27,257 Epoch: [485][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0475 (0.0298) Prec@1 93.000 (94.800) Prec@5 100.000 (99.933) +2022-11-14 17:11:27,445 Epoch: [485][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0221 (0.0293) Prec@1 97.000 (94.938) Prec@5 100.000 (99.938) +2022-11-14 17:11:27,640 Epoch: [485][160/500] Time 0.020 (0.017) Data 0.001 (0.003) Loss 0.0347 (0.0297) Prec@1 94.000 (94.882) Prec@5 100.000 (99.941) +2022-11-14 17:11:27,893 Epoch: [485][170/500] Time 0.023 (0.017) Data 0.002 (0.003) Loss 0.0393 (0.0302) Prec@1 92.000 (94.722) Prec@5 100.000 (99.944) +2022-11-14 17:11:28,158 Epoch: [485][180/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0381 (0.0306) Prec@1 95.000 (94.737) Prec@5 100.000 (99.947) +2022-11-14 17:11:28,420 Epoch: [485][190/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0368 (0.0309) Prec@1 94.000 (94.700) Prec@5 100.000 (99.950) +2022-11-14 17:11:28,685 Epoch: [485][200/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0160 (0.0302) Prec@1 98.000 (94.857) Prec@5 100.000 (99.952) +2022-11-14 17:11:28,952 Epoch: [485][210/500] Time 0.028 (0.018) Data 0.002 (0.003) Loss 0.0162 (0.0296) Prec@1 98.000 (95.000) Prec@5 100.000 (99.955) +2022-11-14 17:11:29,223 Epoch: [485][220/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0337 (0.0297) Prec@1 93.000 (94.913) Prec@5 100.000 (99.957) +2022-11-14 17:11:29,489 Epoch: [485][230/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0211 (0.0294) Prec@1 96.000 (94.958) Prec@5 100.000 (99.958) +2022-11-14 17:11:29,755 Epoch: [485][240/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0272 (0.0293) Prec@1 96.000 (95.000) Prec@5 100.000 (99.960) +2022-11-14 17:11:30,024 Epoch: [485][250/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0334 (0.0295) Prec@1 93.000 (94.923) Prec@5 100.000 (99.962) +2022-11-14 17:11:30,295 Epoch: [485][260/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0339 (0.0296) Prec@1 93.000 (94.852) Prec@5 100.000 (99.963) +2022-11-14 17:11:30,564 Epoch: [485][270/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0288 (0.0296) Prec@1 96.000 (94.893) Prec@5 100.000 (99.964) +2022-11-14 17:11:30,830 Epoch: [485][280/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0303 (0.0296) Prec@1 94.000 (94.862) Prec@5 100.000 (99.966) +2022-11-14 17:11:31,104 Epoch: [485][290/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0238 (0.0294) Prec@1 96.000 (94.900) Prec@5 100.000 (99.967) +2022-11-14 17:11:31,372 Epoch: [485][300/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0186 (0.0291) Prec@1 96.000 (94.935) Prec@5 100.000 (99.968) +2022-11-14 17:11:31,642 Epoch: [485][310/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0277 (0.0290) Prec@1 97.000 (95.000) Prec@5 99.000 (99.938) +2022-11-14 17:11:31,909 Epoch: [485][320/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0186 (0.0287) Prec@1 98.000 (95.091) Prec@5 100.000 (99.939) +2022-11-14 17:11:32,176 Epoch: [485][330/500] Time 0.025 (0.020) Data 0.001 (0.002) Loss 0.0354 (0.0289) Prec@1 94.000 (95.059) Prec@5 99.000 (99.912) +2022-11-14 17:11:32,437 Epoch: [485][340/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0287 (0.0289) Prec@1 95.000 (95.057) Prec@5 100.000 (99.914) +2022-11-14 17:11:32,699 Epoch: [485][350/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0067 (0.0283) Prec@1 99.000 (95.167) Prec@5 100.000 (99.917) +2022-11-14 17:11:32,960 Epoch: [485][360/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0295 (0.0283) Prec@1 97.000 (95.216) Prec@5 99.000 (99.892) +2022-11-14 17:11:33,224 Epoch: [485][370/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0465 (0.0288) Prec@1 93.000 (95.158) Prec@5 100.000 (99.895) +2022-11-14 17:11:33,490 Epoch: [485][380/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0500 (0.0293) Prec@1 91.000 (95.051) Prec@5 100.000 (99.897) +2022-11-14 17:11:33,746 Epoch: [485][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0141 (0.0290) Prec@1 97.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 17:11:34,005 Epoch: [485][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0278 (0.0289) Prec@1 94.000 (95.073) Prec@5 99.000 (99.878) +2022-11-14 17:11:34,267 Epoch: [485][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0356 (0.0291) Prec@1 94.000 (95.048) Prec@5 100.000 (99.881) +2022-11-14 17:11:34,529 Epoch: [485][420/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0382 (0.0293) Prec@1 96.000 (95.070) Prec@5 100.000 (99.884) +2022-11-14 17:11:34,789 Epoch: [485][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0147 (0.0290) Prec@1 98.000 (95.136) Prec@5 100.000 (99.886) +2022-11-14 17:11:35,048 Epoch: [485][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0456 (0.0293) Prec@1 93.000 (95.089) Prec@5 100.000 (99.889) +2022-11-14 17:11:35,310 Epoch: [485][450/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0311 (0.0294) Prec@1 96.000 (95.109) Prec@5 100.000 (99.891) +2022-11-14 17:11:35,570 Epoch: [485][460/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0142 (0.0291) Prec@1 97.000 (95.149) Prec@5 100.000 (99.894) +2022-11-14 17:11:35,831 Epoch: [485][470/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0247 (0.0290) Prec@1 97.000 (95.188) Prec@5 100.000 (99.896) +2022-11-14 17:11:36,096 Epoch: [485][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0236 (0.0289) Prec@1 96.000 (95.204) Prec@5 100.000 (99.898) +2022-11-14 17:11:36,353 Epoch: [485][490/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0195 (0.0287) Prec@1 97.000 (95.240) Prec@5 100.000 (99.900) +2022-11-14 17:11:36,585 Epoch: [485][499/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0197 (0.0285) Prec@1 97.000 (95.275) Prec@5 100.000 (99.902) +2022-11-14 17:11:36,883 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0404 (0.0404) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:36,890 Test: [1/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0732 (0.0568) Prec@1 88.000 (91.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:36,900 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0771 (0.0636) Prec@1 86.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:11:36,910 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0675) Prec@1 88.000 (89.250) Prec@5 98.000 (99.500) +2022-11-14 17:11:36,917 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0731 (0.0686) Prec@1 85.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 17:11:36,924 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0651) Prec@1 92.000 (89.000) Prec@5 100.000 (99.667) +2022-11-14 17:11:36,930 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0643) Prec@1 91.000 (89.286) Prec@5 100.000 (99.714) +2022-11-14 17:11:36,939 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0672) Prec@1 87.000 (89.000) Prec@5 100.000 (99.750) +2022-11-14 17:11:36,946 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0688) Prec@1 86.000 (88.667) Prec@5 100.000 (99.778) +2022-11-14 17:11:36,953 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0692) Prec@1 89.000 (88.700) Prec@5 98.000 (99.600) +2022-11-14 17:11:36,960 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0682) Prec@1 92.000 (89.000) Prec@5 100.000 (99.636) +2022-11-14 17:11:36,967 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0675 (0.0681) Prec@1 90.000 (89.083) Prec@5 99.000 (99.583) +2022-11-14 17:11:36,975 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0676) Prec@1 89.000 (89.077) Prec@5 100.000 (99.615) +2022-11-14 17:11:36,983 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0680) Prec@1 87.000 (88.929) Prec@5 99.000 (99.571) +2022-11-14 17:11:36,990 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0685) Prec@1 86.000 (88.733) Prec@5 100.000 (99.600) +2022-11-14 17:11:36,998 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0693) Prec@1 86.000 (88.562) Prec@5 100.000 (99.625) +2022-11-14 17:11:37,005 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0682) Prec@1 92.000 (88.765) Prec@5 98.000 (99.529) +2022-11-14 17:11:37,013 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1203 (0.0711) Prec@1 83.000 (88.444) Prec@5 100.000 (99.556) +2022-11-14 17:11:37,020 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0711) Prec@1 88.000 (88.421) Prec@5 100.000 (99.579) +2022-11-14 17:11:37,028 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0720) Prec@1 88.000 (88.400) Prec@5 97.000 (99.450) +2022-11-14 17:11:37,035 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0722) Prec@1 86.000 (88.286) Prec@5 100.000 (99.476) +2022-11-14 17:11:37,043 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0726) Prec@1 87.000 (88.227) Prec@5 99.000 (99.455) +2022-11-14 17:11:37,051 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1045 (0.0740) Prec@1 85.000 (88.087) Prec@5 97.000 (99.348) +2022-11-14 17:11:37,059 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0741) Prec@1 88.000 (88.083) Prec@5 100.000 (99.375) +2022-11-14 17:11:37,067 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0739) Prec@1 88.000 (88.080) Prec@5 100.000 (99.400) +2022-11-14 17:11:37,074 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0750) Prec@1 84.000 (87.923) Prec@5 99.000 (99.385) +2022-11-14 17:11:37,083 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0745) Prec@1 92.000 (88.074) Prec@5 99.000 (99.370) +2022-11-14 17:11:37,090 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0741) Prec@1 90.000 (88.143) Prec@5 99.000 (99.357) +2022-11-14 17:11:37,098 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0748) Prec@1 82.000 (87.931) Prec@5 98.000 (99.310) +2022-11-14 17:11:37,106 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0543 (0.0741) Prec@1 91.000 (88.033) Prec@5 99.000 (99.300) +2022-11-14 17:11:37,113 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0736) Prec@1 90.000 (88.097) Prec@5 100.000 (99.323) +2022-11-14 17:11:37,121 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0739) Prec@1 88.000 (88.094) Prec@5 99.000 (99.312) +2022-11-14 17:11:37,129 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0742) Prec@1 84.000 (87.970) Prec@5 100.000 (99.333) +2022-11-14 17:11:37,136 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0582 (0.0737) Prec@1 90.000 (88.029) Prec@5 100.000 (99.353) +2022-11-14 17:11:37,144 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0742) Prec@1 86.000 (87.971) Prec@5 99.000 (99.343) +2022-11-14 17:11:37,152 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0739) Prec@1 91.000 (88.056) Prec@5 99.000 (99.333) +2022-11-14 17:11:37,159 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0743) Prec@1 86.000 (88.000) Prec@5 99.000 (99.324) +2022-11-14 17:11:37,167 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0748) Prec@1 85.000 (87.921) Prec@5 99.000 (99.316) +2022-11-14 17:11:37,175 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0637 (0.0745) Prec@1 90.000 (87.974) Prec@5 99.000 (99.308) +2022-11-14 17:11:37,182 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0744) Prec@1 90.000 (88.025) Prec@5 99.000 (99.300) +2022-11-14 17:11:37,190 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0820 (0.0746) Prec@1 89.000 (88.049) Prec@5 98.000 (99.268) +2022-11-14 17:11:37,197 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0745) Prec@1 88.000 (88.048) Prec@5 99.000 (99.262) +2022-11-14 17:11:37,205 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0739) Prec@1 92.000 (88.140) Prec@5 100.000 (99.279) +2022-11-14 17:11:37,212 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0617 (0.0736) Prec@1 91.000 (88.205) Prec@5 98.000 (99.250) +2022-11-14 17:11:37,220 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0662 (0.0735) Prec@1 88.000 (88.200) Prec@5 100.000 (99.267) +2022-11-14 17:11:37,227 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0993 (0.0740) Prec@1 86.000 (88.152) Prec@5 98.000 (99.239) +2022-11-14 17:11:37,235 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0634 (0.0738) Prec@1 91.000 (88.213) Prec@5 99.000 (99.234) +2022-11-14 17:11:37,242 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1090 (0.0745) Prec@1 83.000 (88.104) Prec@5 98.000 (99.208) +2022-11-14 17:11:37,250 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0533 (0.0741) Prec@1 91.000 (88.163) Prec@5 100.000 (99.224) +2022-11-14 17:11:37,257 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1158 (0.0749) Prec@1 79.000 (87.980) Prec@5 99.000 (99.220) +2022-11-14 17:11:37,265 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0373 (0.0742) Prec@1 94.000 (88.098) Prec@5 100.000 (99.235) +2022-11-14 17:11:37,272 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0671 (0.0741) Prec@1 90.000 (88.135) Prec@5 99.000 (99.231) +2022-11-14 17:11:37,280 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0661 (0.0739) Prec@1 88.000 (88.132) Prec@5 100.000 (99.245) +2022-11-14 17:11:37,287 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0650 (0.0737) Prec@1 90.000 (88.167) Prec@5 98.000 (99.222) +2022-11-14 17:11:37,295 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1042 (0.0743) Prec@1 83.000 (88.073) Prec@5 100.000 (99.236) +2022-11-14 17:11:37,302 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0730 (0.0743) Prec@1 88.000 (88.071) Prec@5 98.000 (99.214) +2022-11-14 17:11:37,310 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0622 (0.0741) Prec@1 91.000 (88.123) Prec@5 100.000 (99.228) +2022-11-14 17:11:37,317 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0815 (0.0742) Prec@1 88.000 (88.121) Prec@5 100.000 (99.241) +2022-11-14 17:11:37,325 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0912 (0.0745) Prec@1 84.000 (88.051) Prec@5 100.000 (99.254) +2022-11-14 17:11:37,332 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0856 (0.0747) Prec@1 86.000 (88.017) Prec@5 100.000 (99.267) +2022-11-14 17:11:37,339 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0885 (0.0749) Prec@1 86.000 (87.984) Prec@5 99.000 (99.262) +2022-11-14 17:11:37,347 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0810 (0.0750) Prec@1 88.000 (87.984) Prec@5 99.000 (99.258) +2022-11-14 17:11:37,354 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0604 (0.0747) Prec@1 91.000 (88.032) Prec@5 100.000 (99.270) +2022-11-14 17:11:37,362 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0368 (0.0742) Prec@1 93.000 (88.109) Prec@5 100.000 (99.281) +2022-11-14 17:11:37,369 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0868 (0.0744) Prec@1 88.000 (88.108) Prec@5 99.000 (99.277) +2022-11-14 17:11:37,377 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0593 (0.0741) Prec@1 88.000 (88.106) Prec@5 100.000 (99.288) +2022-11-14 17:11:37,384 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0307 (0.0735) Prec@1 95.000 (88.209) Prec@5 100.000 (99.299) +2022-11-14 17:11:37,392 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0945 (0.0738) Prec@1 84.000 (88.147) Prec@5 99.000 (99.294) +2022-11-14 17:11:37,399 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0687 (0.0737) Prec@1 89.000 (88.159) Prec@5 99.000 (99.290) +2022-11-14 17:11:37,407 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0737) Prec@1 88.000 (88.157) Prec@5 99.000 (99.286) +2022-11-14 17:11:37,414 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1080 (0.0742) Prec@1 85.000 (88.113) Prec@5 100.000 (99.296) +2022-11-14 17:11:37,422 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0598 (0.0740) Prec@1 89.000 (88.125) Prec@5 99.000 (99.292) +2022-11-14 17:11:37,429 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0449 (0.0736) Prec@1 92.000 (88.178) Prec@5 99.000 (99.288) +2022-11-14 17:11:37,437 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0491 (0.0733) Prec@1 91.000 (88.216) Prec@5 100.000 (99.297) +2022-11-14 17:11:37,444 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1053 (0.0737) Prec@1 84.000 (88.160) Prec@5 100.000 (99.307) +2022-11-14 17:11:37,452 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0559 (0.0735) Prec@1 91.000 (88.197) Prec@5 100.000 (99.316) +2022-11-14 17:11:37,459 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0733) Prec@1 90.000 (88.221) Prec@5 100.000 (99.325) +2022-11-14 17:11:37,467 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0943 (0.0736) Prec@1 86.000 (88.192) Prec@5 97.000 (99.295) +2022-11-14 17:11:37,474 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0737) Prec@1 87.000 (88.177) Prec@5 100.000 (99.304) +2022-11-14 17:11:37,482 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0718 (0.0737) Prec@1 89.000 (88.188) Prec@5 99.000 (99.300) +2022-11-14 17:11:37,489 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0739 (0.0737) Prec@1 88.000 (88.185) Prec@5 99.000 (99.296) +2022-11-14 17:11:37,496 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1014 (0.0741) Prec@1 85.000 (88.146) Prec@5 100.000 (99.305) +2022-11-14 17:11:37,504 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0889 (0.0742) Prec@1 85.000 (88.108) Prec@5 99.000 (99.301) +2022-11-14 17:11:37,511 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0634 (0.0741) Prec@1 87.000 (88.095) Prec@5 99.000 (99.298) +2022-11-14 17:11:37,519 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0914 (0.0743) Prec@1 85.000 (88.059) Prec@5 100.000 (99.306) +2022-11-14 17:11:37,528 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1057 (0.0747) Prec@1 84.000 (88.012) Prec@5 100.000 (99.314) +2022-11-14 17:11:37,535 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0667 (0.0746) Prec@1 89.000 (88.023) Prec@5 100.000 (99.322) +2022-11-14 17:11:37,542 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0841 (0.0747) Prec@1 87.000 (88.011) Prec@5 99.000 (99.318) +2022-11-14 17:11:37,550 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0902 (0.0749) Prec@1 87.000 (88.000) Prec@5 99.000 (99.315) +2022-11-14 17:11:37,558 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0750) Prec@1 86.000 (87.978) Prec@5 100.000 (99.322) +2022-11-14 17:11:37,565 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0631 (0.0749) Prec@1 91.000 (88.011) Prec@5 100.000 (99.330) +2022-11-14 17:11:37,572 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0648 (0.0748) Prec@1 91.000 (88.043) Prec@5 100.000 (99.337) +2022-11-14 17:11:37,580 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0741 (0.0748) Prec@1 86.000 (88.022) Prec@5 100.000 (99.344) +2022-11-14 17:11:37,587 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0691 (0.0747) Prec@1 90.000 (88.043) Prec@5 100.000 (99.351) +2022-11-14 17:11:37,595 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0748) Prec@1 88.000 (88.042) Prec@5 99.000 (99.347) +2022-11-14 17:11:37,602 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0689 (0.0747) Prec@1 90.000 (88.062) Prec@5 98.000 (99.333) +2022-11-14 17:11:37,610 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0636 (0.0746) Prec@1 89.000 (88.072) Prec@5 99.000 (99.330) +2022-11-14 17:11:37,617 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0951 (0.0748) Prec@1 86.000 (88.051) Prec@5 98.000 (99.316) +2022-11-14 17:11:37,624 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1067 (0.0751) Prec@1 84.000 (88.010) Prec@5 98.000 (99.303) +2022-11-14 17:11:37,632 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0888 (0.0753) Prec@1 88.000 (88.010) Prec@5 98.000 (99.290) +2022-11-14 17:11:37,692 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:11:38,008 Epoch: [486][0/500] Time 0.024 (0.024) Data 0.242 (0.242) Loss 0.0370 (0.0370) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:38,209 Epoch: [486][10/500] Time 0.016 (0.018) Data 0.002 (0.023) Loss 0.0360 (0.0365) Prec@1 93.000 (93.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:38,394 Epoch: [486][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0362 (0.0364) Prec@1 92.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:38,581 Epoch: [486][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0368 (0.0365) Prec@1 94.000 (93.250) Prec@5 100.000 (100.000) +2022-11-14 17:11:38,767 Epoch: [486][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0241 (0.0340) Prec@1 97.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:38,954 Epoch: [486][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0273 (0.0329) Prec@1 96.000 (94.333) Prec@5 99.000 (99.833) +2022-11-14 17:11:39,142 Epoch: [486][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0136 (0.0301) Prec@1 98.000 (94.857) Prec@5 100.000 (99.857) +2022-11-14 17:11:39,329 Epoch: [486][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0405 (0.0314) Prec@1 94.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 17:11:39,514 Epoch: [486][80/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0236 (0.0306) Prec@1 97.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:11:39,704 Epoch: [486][90/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0125 (0.0288) Prec@1 98.000 (95.300) Prec@5 100.000 (99.900) +2022-11-14 17:11:39,951 Epoch: [486][100/500] Time 0.024 (0.017) Data 0.001 (0.004) Loss 0.0483 (0.0305) Prec@1 92.000 (95.000) Prec@5 100.000 (99.909) +2022-11-14 17:11:40,209 Epoch: [486][110/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0185 (0.0295) Prec@1 96.000 (95.083) Prec@5 100.000 (99.917) +2022-11-14 17:11:40,467 Epoch: [486][120/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0365 (0.0301) Prec@1 95.000 (95.077) Prec@5 100.000 (99.923) +2022-11-14 17:11:40,722 Epoch: [486][130/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0283 (0.0299) Prec@1 96.000 (95.143) Prec@5 100.000 (99.929) +2022-11-14 17:11:40,979 Epoch: [486][140/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0214 (0.0294) Prec@1 97.000 (95.267) Prec@5 100.000 (99.933) +2022-11-14 17:11:41,236 Epoch: [486][150/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0340 (0.0297) Prec@1 95.000 (95.250) Prec@5 100.000 (99.938) +2022-11-14 17:11:41,496 Epoch: [486][160/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0248 (0.0294) Prec@1 96.000 (95.294) Prec@5 99.000 (99.882) +2022-11-14 17:11:41,761 Epoch: [486][170/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0410 (0.0300) Prec@1 93.000 (95.167) Prec@5 100.000 (99.889) +2022-11-14 17:11:42,020 Epoch: [486][180/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0258 (0.0298) Prec@1 96.000 (95.211) Prec@5 100.000 (99.895) +2022-11-14 17:11:42,284 Epoch: [486][190/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0345 (0.0300) Prec@1 93.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 17:11:42,548 Epoch: [486][200/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0263 (0.0299) Prec@1 96.000 (95.143) Prec@5 100.000 (99.905) +2022-11-14 17:11:42,814 Epoch: [486][210/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0367 (0.0302) Prec@1 94.000 (95.091) Prec@5 100.000 (99.909) +2022-11-14 17:11:43,081 Epoch: [486][220/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0261 (0.0300) Prec@1 97.000 (95.174) Prec@5 100.000 (99.913) +2022-11-14 17:11:43,339 Epoch: [486][230/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0122 (0.0293) Prec@1 98.000 (95.292) Prec@5 100.000 (99.917) +2022-11-14 17:11:43,603 Epoch: [486][240/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0325 (0.0294) Prec@1 93.000 (95.200) Prec@5 100.000 (99.920) +2022-11-14 17:11:43,861 Epoch: [486][250/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0202 (0.0290) Prec@1 97.000 (95.269) Prec@5 100.000 (99.923) +2022-11-14 17:11:44,122 Epoch: [486][260/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0175 (0.0286) Prec@1 98.000 (95.370) Prec@5 100.000 (99.926) +2022-11-14 17:11:44,376 Epoch: [486][270/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0379 (0.0289) Prec@1 94.000 (95.321) Prec@5 100.000 (99.929) +2022-11-14 17:11:44,631 Epoch: [486][280/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0434 (0.0294) Prec@1 94.000 (95.276) Prec@5 98.000 (99.862) +2022-11-14 17:11:44,890 Epoch: [486][290/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0175 (0.0290) Prec@1 97.000 (95.333) Prec@5 100.000 (99.867) +2022-11-14 17:11:45,147 Epoch: [486][300/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0251 (0.0289) Prec@1 96.000 (95.355) Prec@5 100.000 (99.871) +2022-11-14 17:11:45,404 Epoch: [486][310/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0278 (0.0289) Prec@1 96.000 (95.375) Prec@5 100.000 (99.875) +2022-11-14 17:11:45,660 Epoch: [486][320/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0330 (0.0290) Prec@1 95.000 (95.364) Prec@5 100.000 (99.879) +2022-11-14 17:11:45,918 Epoch: [486][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0180 (0.0287) Prec@1 96.000 (95.382) Prec@5 100.000 (99.882) +2022-11-14 17:11:46,176 Epoch: [486][340/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0136 (0.0282) Prec@1 98.000 (95.457) Prec@5 100.000 (99.886) +2022-11-14 17:11:46,433 Epoch: [486][350/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0392 (0.0285) Prec@1 92.000 (95.361) Prec@5 100.000 (99.889) +2022-11-14 17:11:46,690 Epoch: [486][360/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0408 (0.0289) Prec@1 92.000 (95.270) Prec@5 100.000 (99.892) +2022-11-14 17:11:46,942 Epoch: [486][370/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0156 (0.0285) Prec@1 97.000 (95.316) Prec@5 100.000 (99.895) +2022-11-14 17:11:47,199 Epoch: [486][380/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0311 (0.0286) Prec@1 94.000 (95.282) Prec@5 100.000 (99.897) +2022-11-14 17:11:47,455 Epoch: [486][390/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0424 (0.0289) Prec@1 95.000 (95.275) Prec@5 100.000 (99.900) +2022-11-14 17:11:47,711 Epoch: [486][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0442 (0.0293) Prec@1 92.000 (95.195) Prec@5 100.000 (99.902) +2022-11-14 17:11:47,966 Epoch: [486][410/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0236 (0.0292) Prec@1 96.000 (95.214) Prec@5 99.000 (99.881) +2022-11-14 17:11:48,225 Epoch: [486][420/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0048 (0.0286) Prec@1 100.000 (95.326) Prec@5 100.000 (99.884) +2022-11-14 17:11:48,480 Epoch: [486][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0138 (0.0283) Prec@1 98.000 (95.386) Prec@5 100.000 (99.886) +2022-11-14 17:11:48,735 Epoch: [486][440/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0142 (0.0280) Prec@1 99.000 (95.467) Prec@5 100.000 (99.889) +2022-11-14 17:11:48,988 Epoch: [486][450/500] Time 0.023 (0.021) Data 0.001 (0.002) Loss 0.0186 (0.0278) Prec@1 96.000 (95.478) Prec@5 100.000 (99.891) +2022-11-14 17:11:49,246 Epoch: [486][460/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0215 (0.0276) Prec@1 97.000 (95.511) Prec@5 100.000 (99.894) +2022-11-14 17:11:49,501 Epoch: [486][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0264 (0.0276) Prec@1 95.000 (95.500) Prec@5 100.000 (99.896) +2022-11-14 17:11:49,757 Epoch: [486][480/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0285 (0.0276) Prec@1 95.000 (95.490) Prec@5 100.000 (99.898) +2022-11-14 17:11:50,014 Epoch: [486][490/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0237 (0.0275) Prec@1 96.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:11:50,246 Epoch: [486][499/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0107 (0.0272) Prec@1 100.000 (95.588) Prec@5 100.000 (99.902) +2022-11-14 17:11:50,541 Test: [0/100] Model Time 0.013 (0.013) Loss Time 0.000 (0.000) Loss 0.0566 (0.0566) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:50,551 Test: [1/100] Model Time 0.009 (0.011) Loss Time 0.000 (0.000) Loss 0.0708 (0.0637) Prec@1 88.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:50,561 Test: [2/100] Model Time 0.008 (0.010) Loss Time 0.000 (0.000) Loss 0.0652 (0.0642) Prec@1 89.000 (88.667) Prec@5 100.000 (100.000) +2022-11-14 17:11:50,571 Test: [3/100] Model Time 0.006 (0.009) Loss Time 0.000 (0.000) Loss 0.0746 (0.0668) Prec@1 87.000 (88.250) Prec@5 98.000 (99.500) +2022-11-14 17:11:50,578 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0700 (0.0675) Prec@1 87.000 (88.000) Prec@5 100.000 (99.600) +2022-11-14 17:11:50,585 Test: [5/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0387 (0.0627) Prec@1 93.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 17:11:50,592 Test: [6/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0696 (0.0637) Prec@1 91.000 (89.143) Prec@5 99.000 (99.571) +2022-11-14 17:11:50,600 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0973 (0.0679) Prec@1 84.000 (88.500) Prec@5 98.000 (99.375) +2022-11-14 17:11:50,607 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0940 (0.0708) Prec@1 86.000 (88.222) Prec@5 99.000 (99.333) +2022-11-14 17:11:50,615 Test: [9/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0709) Prec@1 90.000 (88.400) Prec@5 98.000 (99.200) +2022-11-14 17:11:50,622 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0706) Prec@1 90.000 (88.545) Prec@5 100.000 (99.273) +2022-11-14 17:11:50,630 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0703) Prec@1 89.000 (88.583) Prec@5 99.000 (99.250) +2022-11-14 17:11:50,638 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0691 (0.0702) Prec@1 89.000 (88.615) Prec@5 100.000 (99.308) +2022-11-14 17:11:50,645 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0744 (0.0705) Prec@1 88.000 (88.571) Prec@5 100.000 (99.357) +2022-11-14 17:11:50,653 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0699) Prec@1 89.000 (88.600) Prec@5 100.000 (99.400) +2022-11-14 17:11:50,661 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0703) Prec@1 90.000 (88.688) Prec@5 99.000 (99.375) +2022-11-14 17:11:50,669 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0696) Prec@1 90.000 (88.765) Prec@5 98.000 (99.294) +2022-11-14 17:11:50,677 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1108 (0.0718) Prec@1 84.000 (88.500) Prec@5 100.000 (99.333) +2022-11-14 17:11:50,684 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0722) Prec@1 86.000 (88.368) Prec@5 99.000 (99.316) +2022-11-14 17:11:50,692 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0939 (0.0733) Prec@1 85.000 (88.200) Prec@5 98.000 (99.250) +2022-11-14 17:11:50,700 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0736) Prec@1 88.000 (88.190) Prec@5 99.000 (99.238) +2022-11-14 17:11:50,707 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0743) Prec@1 85.000 (88.045) Prec@5 99.000 (99.227) +2022-11-14 17:11:50,715 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0752) Prec@1 85.000 (87.913) Prec@5 98.000 (99.174) +2022-11-14 17:11:50,723 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0756) Prec@1 88.000 (87.917) Prec@5 100.000 (99.208) +2022-11-14 17:11:50,730 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0634 (0.0751) Prec@1 90.000 (88.000) Prec@5 100.000 (99.240) +2022-11-14 17:11:50,738 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0760) Prec@1 82.000 (87.769) Prec@5 99.000 (99.231) +2022-11-14 17:11:50,746 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0347 (0.0745) Prec@1 95.000 (88.037) Prec@5 100.000 (99.259) +2022-11-14 17:11:50,753 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0745) Prec@1 89.000 (88.071) Prec@5 100.000 (99.286) +2022-11-14 17:11:50,761 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0741) Prec@1 90.000 (88.138) Prec@5 97.000 (99.207) +2022-11-14 17:11:50,769 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0739) Prec@1 89.000 (88.167) Prec@5 99.000 (99.200) +2022-11-14 17:11:50,776 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0755 (0.0739) Prec@1 88.000 (88.161) Prec@5 100.000 (99.226) +2022-11-14 17:11:50,784 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0739) Prec@1 88.000 (88.156) Prec@5 98.000 (99.188) +2022-11-14 17:11:50,792 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0736) Prec@1 89.000 (88.182) Prec@5 100.000 (99.212) +2022-11-14 17:11:50,799 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0744) Prec@1 83.000 (88.029) Prec@5 100.000 (99.235) +2022-11-14 17:11:50,807 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0746) Prec@1 88.000 (88.029) Prec@5 98.000 (99.200) +2022-11-14 17:11:50,815 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0740) Prec@1 90.000 (88.083) Prec@5 100.000 (99.222) +2022-11-14 17:11:50,822 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0739) Prec@1 90.000 (88.135) Prec@5 99.000 (99.216) +2022-11-14 17:11:50,830 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0747) Prec@1 83.000 (88.000) Prec@5 100.000 (99.237) +2022-11-14 17:11:50,837 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0742) Prec@1 93.000 (88.128) Prec@5 100.000 (99.256) +2022-11-14 17:11:50,845 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0739) Prec@1 90.000 (88.175) Prec@5 99.000 (99.250) +2022-11-14 17:11:50,853 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0743) Prec@1 84.000 (88.073) Prec@5 97.000 (99.195) +2022-11-14 17:11:50,861 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0744) Prec@1 88.000 (88.071) Prec@5 99.000 (99.190) +2022-11-14 17:11:50,868 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0400 (0.0736) Prec@1 94.000 (88.209) Prec@5 99.000 (99.186) +2022-11-14 17:11:50,876 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0733) Prec@1 91.000 (88.273) Prec@5 98.000 (99.159) +2022-11-14 17:11:50,884 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0577 (0.0729) Prec@1 91.000 (88.333) Prec@5 99.000 (99.156) +2022-11-14 17:11:50,891 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0729) Prec@1 89.000 (88.348) Prec@5 100.000 (99.174) +2022-11-14 17:11:50,899 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0725) Prec@1 90.000 (88.383) Prec@5 100.000 (99.191) +2022-11-14 17:11:50,906 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1176 (0.0735) Prec@1 82.000 (88.250) Prec@5 98.000 (99.167) +2022-11-14 17:11:50,914 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0546 (0.0731) Prec@1 90.000 (88.286) Prec@5 100.000 (99.184) +2022-11-14 17:11:50,921 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1236 (0.0741) Prec@1 82.000 (88.160) Prec@5 99.000 (99.180) +2022-11-14 17:11:50,929 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0736) Prec@1 93.000 (88.255) Prec@5 100.000 (99.196) +2022-11-14 17:11:50,938 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0738) Prec@1 87.000 (88.231) Prec@5 98.000 (99.173) +2022-11-14 17:11:50,945 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0736) Prec@1 89.000 (88.245) Prec@5 100.000 (99.189) +2022-11-14 17:11:50,953 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0735) Prec@1 88.000 (88.241) Prec@5 99.000 (99.185) +2022-11-14 17:11:50,961 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0740) Prec@1 86.000 (88.200) Prec@5 99.000 (99.182) +2022-11-14 17:11:50,968 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0742) Prec@1 87.000 (88.179) Prec@5 99.000 (99.179) +2022-11-14 17:11:50,976 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0411 (0.0736) Prec@1 94.000 (88.281) Prec@5 100.000 (99.193) +2022-11-14 17:11:50,984 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0737) Prec@1 90.000 (88.310) Prec@5 99.000 (99.190) +2022-11-14 17:11:50,992 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0741) Prec@1 85.000 (88.254) Prec@5 99.000 (99.186) +2022-11-14 17:11:50,999 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0741) Prec@1 86.000 (88.217) Prec@5 100.000 (99.200) +2022-11-14 17:11:51,007 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0742) Prec@1 89.000 (88.230) Prec@5 100.000 (99.213) +2022-11-14 17:11:51,015 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0739) Prec@1 92.000 (88.290) Prec@5 100.000 (99.226) +2022-11-14 17:11:51,022 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0738) Prec@1 89.000 (88.302) Prec@5 100.000 (99.238) +2022-11-14 17:11:51,030 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0367 (0.0732) Prec@1 95.000 (88.406) Prec@5 100.000 (99.250) +2022-11-14 17:11:51,037 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0736) Prec@1 85.000 (88.354) Prec@5 100.000 (99.262) +2022-11-14 17:11:51,045 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0870 (0.0738) Prec@1 85.000 (88.303) Prec@5 97.000 (99.227) +2022-11-14 17:11:51,053 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0733) Prec@1 92.000 (88.358) Prec@5 100.000 (99.239) +2022-11-14 17:11:51,060 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0731) Prec@1 90.000 (88.382) Prec@5 99.000 (99.235) +2022-11-14 17:11:51,068 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0732) Prec@1 86.000 (88.348) Prec@5 100.000 (99.246) +2022-11-14 17:11:51,076 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0831 (0.0734) Prec@1 90.000 (88.371) Prec@5 98.000 (99.229) +2022-11-14 17:11:51,085 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0738) Prec@1 84.000 (88.310) Prec@5 98.000 (99.211) +2022-11-14 17:11:51,093 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0737) Prec@1 88.000 (88.306) Prec@5 100.000 (99.222) +2022-11-14 17:11:51,101 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0734) Prec@1 92.000 (88.356) Prec@5 100.000 (99.233) +2022-11-14 17:11:51,109 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0464 (0.0730) Prec@1 93.000 (88.419) Prec@5 100.000 (99.243) +2022-11-14 17:11:51,116 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1099 (0.0735) Prec@1 82.000 (88.333) Prec@5 99.000 (99.240) +2022-11-14 17:11:51,124 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0734) Prec@1 91.000 (88.368) Prec@5 100.000 (99.250) +2022-11-14 17:11:51,132 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0733) Prec@1 90.000 (88.390) Prec@5 100.000 (99.260) +2022-11-14 17:11:51,140 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0736) Prec@1 85.000 (88.346) Prec@5 97.000 (99.231) +2022-11-14 17:11:51,148 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0666 (0.0735) Prec@1 90.000 (88.367) Prec@5 100.000 (99.241) +2022-11-14 17:11:51,155 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0734) Prec@1 88.000 (88.362) Prec@5 99.000 (99.237) +2022-11-14 17:11:51,163 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0735) Prec@1 87.000 (88.346) Prec@5 98.000 (99.222) +2022-11-14 17:11:51,171 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0736) Prec@1 88.000 (88.341) Prec@5 100.000 (99.232) +2022-11-14 17:11:51,178 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0738) Prec@1 85.000 (88.301) Prec@5 99.000 (99.229) +2022-11-14 17:11:51,186 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0736) Prec@1 89.000 (88.310) Prec@5 100.000 (99.238) +2022-11-14 17:11:51,193 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0739) Prec@1 84.000 (88.259) Prec@5 99.000 (99.235) +2022-11-14 17:11:51,201 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0741) Prec@1 87.000 (88.244) Prec@5 100.000 (99.244) +2022-11-14 17:11:51,209 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0741) Prec@1 89.000 (88.253) Prec@5 99.000 (99.241) +2022-11-14 17:11:51,216 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0759 (0.0741) Prec@1 89.000 (88.261) Prec@5 98.000 (99.227) +2022-11-14 17:11:51,224 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0740) Prec@1 88.000 (88.258) Prec@5 99.000 (99.225) +2022-11-14 17:11:51,232 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0741) Prec@1 87.000 (88.244) Prec@5 100.000 (99.233) +2022-11-14 17:11:51,239 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0738) Prec@1 94.000 (88.308) Prec@5 100.000 (99.242) +2022-11-14 17:11:51,247 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0736) Prec@1 92.000 (88.348) Prec@5 100.000 (99.250) +2022-11-14 17:11:51,254 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0737) Prec@1 84.000 (88.301) Prec@5 100.000 (99.258) +2022-11-14 17:11:51,262 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0738) Prec@1 89.000 (88.309) Prec@5 99.000 (99.255) +2022-11-14 17:11:51,269 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0873 (0.0740) Prec@1 87.000 (88.295) Prec@5 98.000 (99.242) +2022-11-14 17:11:51,277 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0739) Prec@1 91.000 (88.323) Prec@5 99.000 (99.240) +2022-11-14 17:11:51,284 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0737) Prec@1 91.000 (88.351) Prec@5 99.000 (99.237) +2022-11-14 17:11:51,292 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0738) Prec@1 89.000 (88.357) Prec@5 99.000 (99.235) +2022-11-14 17:11:51,299 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0740) Prec@1 86.000 (88.333) Prec@5 99.000 (99.232) +2022-11-14 17:11:51,307 Test: [99/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0741) Prec@1 88.000 (88.330) Prec@5 100.000 (99.240) +2022-11-14 17:11:51,370 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:11:51,693 Epoch: [487][0/500] Time 0.024 (0.024) Data 0.245 (0.245) Loss 0.0354 (0.0354) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:51,890 Epoch: [487][10/500] Time 0.017 (0.018) Data 0.002 (0.024) Loss 0.0238 (0.0296) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:11:52,079 Epoch: [487][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0254 (0.0282) Prec@1 96.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:11:52,268 Epoch: [487][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0240 (0.0272) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:11:52,457 Epoch: [487][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0592 (0.0336) Prec@1 89.000 (94.400) Prec@5 100.000 (100.000) +2022-11-14 17:11:52,644 Epoch: [487][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0368 (0.0341) Prec@1 95.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:11:52,844 Epoch: [487][60/500] Time 0.021 (0.017) Data 0.001 (0.006) Loss 0.0217 (0.0324) Prec@1 96.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 17:11:53,107 Epoch: [487][70/500] Time 0.028 (0.018) Data 0.001 (0.005) Loss 0.0360 (0.0328) Prec@1 94.000 (94.625) Prec@5 100.000 (100.000) +2022-11-14 17:11:53,373 Epoch: [487][80/500] Time 0.025 (0.019) Data 0.001 (0.005) Loss 0.0314 (0.0327) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:11:53,645 Epoch: [487][90/500] Time 0.026 (0.019) Data 0.002 (0.004) Loss 0.0091 (0.0303) Prec@1 99.000 (95.100) Prec@5 100.000 (100.000) +2022-11-14 17:11:53,915 Epoch: [487][100/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0341 (0.0307) Prec@1 94.000 (95.000) Prec@5 99.000 (99.909) +2022-11-14 17:11:54,194 Epoch: [487][110/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0269 (0.0303) Prec@1 94.000 (94.917) Prec@5 100.000 (99.917) +2022-11-14 17:11:54,469 Epoch: [487][120/500] Time 0.025 (0.020) Data 0.002 (0.004) Loss 0.0341 (0.0306) Prec@1 93.000 (94.769) Prec@5 100.000 (99.923) +2022-11-14 17:11:54,743 Epoch: [487][130/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0135 (0.0294) Prec@1 99.000 (95.071) Prec@5 100.000 (99.929) +2022-11-14 17:11:55,021 Epoch: [487][140/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0119 (0.0282) Prec@1 99.000 (95.333) Prec@5 100.000 (99.933) +2022-11-14 17:11:55,299 Epoch: [487][150/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0200 (0.0277) Prec@1 96.000 (95.375) Prec@5 100.000 (99.938) +2022-11-14 17:11:55,576 Epoch: [487][160/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0237 (0.0275) Prec@1 96.000 (95.412) Prec@5 100.000 (99.941) +2022-11-14 17:11:55,849 Epoch: [487][170/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0565 (0.0291) Prec@1 93.000 (95.278) Prec@5 98.000 (99.833) +2022-11-14 17:11:56,130 Epoch: [487][180/500] Time 0.030 (0.022) Data 0.001 (0.003) Loss 0.0184 (0.0285) Prec@1 97.000 (95.368) Prec@5 100.000 (99.842) +2022-11-14 17:11:56,403 Epoch: [487][190/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0331 (0.0288) Prec@1 96.000 (95.400) Prec@5 100.000 (99.850) +2022-11-14 17:11:56,680 Epoch: [487][200/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0141 (0.0281) Prec@1 98.000 (95.524) Prec@5 100.000 (99.857) +2022-11-14 17:11:56,956 Epoch: [487][210/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0237 (0.0279) Prec@1 96.000 (95.545) Prec@5 100.000 (99.864) +2022-11-14 17:11:57,233 Epoch: [487][220/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0271 (0.0278) Prec@1 94.000 (95.478) Prec@5 100.000 (99.870) +2022-11-14 17:11:57,500 Epoch: [487][230/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0139 (0.0272) Prec@1 97.000 (95.542) Prec@5 100.000 (99.875) +2022-11-14 17:11:57,768 Epoch: [487][240/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0165 (0.0268) Prec@1 97.000 (95.600) Prec@5 100.000 (99.880) +2022-11-14 17:11:58,043 Epoch: [487][250/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0370 (0.0272) Prec@1 96.000 (95.615) Prec@5 99.000 (99.846) +2022-11-14 17:11:58,322 Epoch: [487][260/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0517 (0.0281) Prec@1 90.000 (95.407) Prec@5 100.000 (99.852) +2022-11-14 17:11:58,598 Epoch: [487][270/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0394 (0.0285) Prec@1 92.000 (95.286) Prec@5 99.000 (99.821) +2022-11-14 17:11:58,868 Epoch: [487][280/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0266 (0.0284) Prec@1 95.000 (95.276) Prec@5 100.000 (99.828) +2022-11-14 17:11:59,143 Epoch: [487][290/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0020 (0.0276) Prec@1 100.000 (95.433) Prec@5 100.000 (99.833) +2022-11-14 17:11:59,416 Epoch: [487][300/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0711 (0.0290) Prec@1 86.000 (95.129) Prec@5 99.000 (99.806) +2022-11-14 17:11:59,697 Epoch: [487][310/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0355 (0.0292) Prec@1 95.000 (95.125) Prec@5 100.000 (99.812) +2022-11-14 17:11:59,974 Epoch: [487][320/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0205 (0.0289) Prec@1 96.000 (95.152) Prec@5 100.000 (99.818) +2022-11-14 17:12:00,247 Epoch: [487][330/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0117 (0.0284) Prec@1 98.000 (95.235) Prec@5 100.000 (99.824) +2022-11-14 17:12:00,524 Epoch: [487][340/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0324 (0.0285) Prec@1 95.000 (95.229) Prec@5 100.000 (99.829) +2022-11-14 17:12:00,796 Epoch: [487][350/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0192 (0.0283) Prec@1 98.000 (95.306) Prec@5 100.000 (99.833) +2022-11-14 17:12:01,070 Epoch: [487][360/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0333 (0.0284) Prec@1 95.000 (95.297) Prec@5 100.000 (99.838) +2022-11-14 17:12:01,346 Epoch: [487][370/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0270 (0.0284) Prec@1 95.000 (95.289) Prec@5 100.000 (99.842) +2022-11-14 17:12:01,621 Epoch: [487][380/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0167 (0.0281) Prec@1 97.000 (95.333) Prec@5 100.000 (99.846) +2022-11-14 17:12:01,895 Epoch: [487][390/500] Time 0.027 (0.023) Data 0.001 (0.002) Loss 0.0472 (0.0285) Prec@1 92.000 (95.250) Prec@5 100.000 (99.850) +2022-11-14 17:12:02,166 Epoch: [487][400/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0254 (0.0285) Prec@1 97.000 (95.293) Prec@5 100.000 (99.854) +2022-11-14 17:12:02,431 Epoch: [487][410/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0272 (0.0284) Prec@1 94.000 (95.262) Prec@5 100.000 (99.857) +2022-11-14 17:12:02,692 Epoch: [487][420/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0327 (0.0285) Prec@1 94.000 (95.233) Prec@5 100.000 (99.860) +2022-11-14 17:12:02,958 Epoch: [487][430/500] Time 0.024 (0.023) Data 0.001 (0.002) Loss 0.0430 (0.0289) Prec@1 94.000 (95.205) Prec@5 100.000 (99.864) +2022-11-14 17:12:03,224 Epoch: [487][440/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0415 (0.0291) Prec@1 95.000 (95.200) Prec@5 100.000 (99.867) +2022-11-14 17:12:03,494 Epoch: [487][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0446 (0.0295) Prec@1 94.000 (95.174) Prec@5 99.000 (99.848) +2022-11-14 17:12:03,767 Epoch: [487][460/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0130 (0.0291) Prec@1 99.000 (95.255) Prec@5 100.000 (99.851) +2022-11-14 17:12:04,036 Epoch: [487][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0228 (0.0290) Prec@1 96.000 (95.271) Prec@5 100.000 (99.854) +2022-11-14 17:12:04,304 Epoch: [487][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0311 (0.0290) Prec@1 95.000 (95.265) Prec@5 100.000 (99.857) +2022-11-14 17:12:04,571 Epoch: [487][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0126 (0.0287) Prec@1 97.000 (95.300) Prec@5 100.000 (99.860) +2022-11-14 17:12:04,811 Epoch: [487][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0113 (0.0284) Prec@1 99.000 (95.373) Prec@5 100.000 (99.863) +2022-11-14 17:12:05,119 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0525 (0.0525) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:05,129 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0763 (0.0644) Prec@1 88.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:05,135 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0653) Prec@1 90.000 (90.333) Prec@5 100.000 (100.000) +2022-11-14 17:12:05,145 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0634) Prec@1 90.000 (90.250) Prec@5 99.000 (99.750) +2022-11-14 17:12:05,152 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0848 (0.0677) Prec@1 87.000 (89.600) Prec@5 100.000 (99.800) +2022-11-14 17:12:05,159 Test: [5/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0365 (0.0625) Prec@1 94.000 (90.333) Prec@5 99.000 (99.667) +2022-11-14 17:12:05,166 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0629) Prec@1 91.000 (90.429) Prec@5 99.000 (99.571) +2022-11-14 17:12:05,174 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0657) Prec@1 87.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 17:12:05,181 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0656) Prec@1 89.000 (89.889) Prec@5 100.000 (99.556) +2022-11-14 17:12:05,188 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0671) Prec@1 88.000 (89.700) Prec@5 99.000 (99.500) +2022-11-14 17:12:05,196 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0665) Prec@1 91.000 (89.818) Prec@5 100.000 (99.545) +2022-11-14 17:12:05,204 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0687) Prec@1 84.000 (89.333) Prec@5 98.000 (99.417) +2022-11-14 17:12:05,212 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0676) Prec@1 92.000 (89.538) Prec@5 100.000 (99.462) +2022-11-14 17:12:05,220 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0674) Prec@1 88.000 (89.429) Prec@5 100.000 (99.500) +2022-11-14 17:12:05,227 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0690) Prec@1 84.000 (89.067) Prec@5 99.000 (99.467) +2022-11-14 17:12:05,235 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0696) Prec@1 88.000 (89.000) Prec@5 100.000 (99.500) +2022-11-14 17:12:05,243 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0687) Prec@1 91.000 (89.118) Prec@5 98.000 (99.412) +2022-11-14 17:12:05,252 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0949 (0.0701) Prec@1 86.000 (88.944) Prec@5 100.000 (99.444) +2022-11-14 17:12:05,260 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0711) Prec@1 86.000 (88.789) Prec@5 99.000 (99.421) +2022-11-14 17:12:05,268 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0718) Prec@1 87.000 (88.700) Prec@5 98.000 (99.350) +2022-11-14 17:12:05,276 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0721) Prec@1 88.000 (88.667) Prec@5 100.000 (99.381) +2022-11-14 17:12:05,284 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0928 (0.0731) Prec@1 87.000 (88.591) Prec@5 98.000 (99.318) +2022-11-14 17:12:05,292 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0736) Prec@1 88.000 (88.565) Prec@5 97.000 (99.217) +2022-11-14 17:12:05,300 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0850 (0.0741) Prec@1 86.000 (88.458) Prec@5 100.000 (99.250) +2022-11-14 17:12:05,307 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0938 (0.0749) Prec@1 85.000 (88.320) Prec@5 100.000 (99.280) +2022-11-14 17:12:05,315 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0755) Prec@1 88.000 (88.308) Prec@5 96.000 (99.154) +2022-11-14 17:12:05,323 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0401 (0.0742) Prec@1 95.000 (88.556) Prec@5 100.000 (99.185) +2022-11-14 17:12:05,330 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0643 (0.0738) Prec@1 91.000 (88.643) Prec@5 100.000 (99.214) +2022-11-14 17:12:05,338 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0734) Prec@1 89.000 (88.655) Prec@5 99.000 (99.207) +2022-11-14 17:12:05,346 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0491 (0.0726) Prec@1 93.000 (88.800) Prec@5 99.000 (99.200) +2022-11-14 17:12:05,353 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0728) Prec@1 86.000 (88.710) Prec@5 100.000 (99.226) +2022-11-14 17:12:05,361 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0726) Prec@1 88.000 (88.688) Prec@5 99.000 (99.219) +2022-11-14 17:12:05,369 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0724) Prec@1 88.000 (88.667) Prec@5 100.000 (99.242) +2022-11-14 17:12:05,377 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0726) Prec@1 86.000 (88.588) Prec@5 99.000 (99.235) +2022-11-14 17:12:05,385 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0672 (0.0724) Prec@1 90.000 (88.629) Prec@5 98.000 (99.200) +2022-11-14 17:12:05,393 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0723) Prec@1 90.000 (88.667) Prec@5 100.000 (99.222) +2022-11-14 17:12:05,400 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0732 (0.0723) Prec@1 87.000 (88.622) Prec@5 99.000 (99.216) +2022-11-14 17:12:05,408 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0727) Prec@1 86.000 (88.553) Prec@5 100.000 (99.237) +2022-11-14 17:12:05,416 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0720) Prec@1 93.000 (88.667) Prec@5 99.000 (99.231) +2022-11-14 17:12:05,423 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0718) Prec@1 91.000 (88.725) Prec@5 99.000 (99.225) +2022-11-14 17:12:05,431 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0771 (0.0719) Prec@1 86.000 (88.659) Prec@5 99.000 (99.220) +2022-11-14 17:12:05,439 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0719) Prec@1 90.000 (88.690) Prec@5 99.000 (99.214) +2022-11-14 17:12:05,446 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0428 (0.0712) Prec@1 92.000 (88.767) Prec@5 100.000 (99.233) +2022-11-14 17:12:05,454 Test: [43/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0714) Prec@1 87.000 (88.727) Prec@5 99.000 (99.227) +2022-11-14 17:12:05,461 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0712) Prec@1 88.000 (88.711) Prec@5 99.000 (99.222) +2022-11-14 17:12:05,469 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0718) Prec@1 84.000 (88.609) Prec@5 98.000 (99.196) +2022-11-14 17:12:05,477 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0719) Prec@1 90.000 (88.638) Prec@5 100.000 (99.213) +2022-11-14 17:12:05,485 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1191 (0.0728) Prec@1 83.000 (88.521) Prec@5 97.000 (99.167) +2022-11-14 17:12:05,493 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0726) Prec@1 90.000 (88.551) Prec@5 100.000 (99.184) +2022-11-14 17:12:05,501 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0979 (0.0731) Prec@1 83.000 (88.440) Prec@5 100.000 (99.200) +2022-11-14 17:12:05,508 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0727) Prec@1 92.000 (88.510) Prec@5 100.000 (99.216) +2022-11-14 17:12:05,516 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0774 (0.0728) Prec@1 90.000 (88.538) Prec@5 100.000 (99.231) +2022-11-14 17:12:05,524 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0723) Prec@1 91.000 (88.585) Prec@5 100.000 (99.245) +2022-11-14 17:12:05,532 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0721) Prec@1 89.000 (88.593) Prec@5 98.000 (99.222) +2022-11-14 17:12:05,540 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0965 (0.0726) Prec@1 85.000 (88.527) Prec@5 100.000 (99.236) +2022-11-14 17:12:05,547 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0674 (0.0725) Prec@1 90.000 (88.554) Prec@5 99.000 (99.232) +2022-11-14 17:12:05,555 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0671 (0.0724) Prec@1 90.000 (88.579) Prec@5 100.000 (99.246) +2022-11-14 17:12:05,563 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0724) Prec@1 87.000 (88.552) Prec@5 99.000 (99.241) +2022-11-14 17:12:05,571 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0725) Prec@1 86.000 (88.508) Prec@5 99.000 (99.237) +2022-11-14 17:12:05,578 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0725) Prec@1 87.000 (88.483) Prec@5 100.000 (99.250) +2022-11-14 17:12:05,586 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0855 (0.0727) Prec@1 88.000 (88.475) Prec@5 98.000 (99.230) +2022-11-14 17:12:05,594 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0726) Prec@1 89.000 (88.484) Prec@5 100.000 (99.242) +2022-11-14 17:12:05,601 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0652 (0.0725) Prec@1 91.000 (88.524) Prec@5 100.000 (99.254) +2022-11-14 17:12:05,609 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0472 (0.0721) Prec@1 90.000 (88.547) Prec@5 100.000 (99.266) +2022-11-14 17:12:05,617 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0722) Prec@1 88.000 (88.538) Prec@5 99.000 (99.262) +2022-11-14 17:12:05,625 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0724) Prec@1 88.000 (88.530) Prec@5 98.000 (99.242) +2022-11-14 17:12:05,633 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0352 (0.0718) Prec@1 95.000 (88.627) Prec@5 100.000 (99.254) +2022-11-14 17:12:05,641 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0719) Prec@1 89.000 (88.632) Prec@5 98.000 (99.235) +2022-11-14 17:12:05,648 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0716) Prec@1 91.000 (88.667) Prec@5 99.000 (99.232) +2022-11-14 17:12:05,656 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0718) Prec@1 85.000 (88.614) Prec@5 100.000 (99.243) +2022-11-14 17:12:05,664 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0720) Prec@1 86.000 (88.577) Prec@5 98.000 (99.225) +2022-11-14 17:12:05,672 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0717) Prec@1 93.000 (88.639) Prec@5 100.000 (99.236) +2022-11-14 17:12:05,679 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0714) Prec@1 91.000 (88.671) Prec@5 100.000 (99.247) +2022-11-14 17:12:05,687 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0524 (0.0712) Prec@1 91.000 (88.703) Prec@5 100.000 (99.257) +2022-11-14 17:12:05,695 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0714) Prec@1 87.000 (88.680) Prec@5 100.000 (99.267) +2022-11-14 17:12:05,702 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0713) Prec@1 92.000 (88.724) Prec@5 98.000 (99.250) +2022-11-14 17:12:05,710 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0714) Prec@1 87.000 (88.701) Prec@5 99.000 (99.247) +2022-11-14 17:12:05,718 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0716) Prec@1 83.000 (88.628) Prec@5 96.000 (99.205) +2022-11-14 17:12:05,726 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0717) Prec@1 88.000 (88.620) Prec@5 100.000 (99.215) +2022-11-14 17:12:05,734 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0720) Prec@1 84.000 (88.562) Prec@5 99.000 (99.213) +2022-11-14 17:12:05,742 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0989 (0.0723) Prec@1 85.000 (88.519) Prec@5 97.000 (99.185) +2022-11-14 17:12:05,750 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0723) Prec@1 88.000 (88.512) Prec@5 100.000 (99.195) +2022-11-14 17:12:05,758 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0726) Prec@1 84.000 (88.458) Prec@5 98.000 (99.181) +2022-11-14 17:12:05,766 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0726) Prec@1 89.000 (88.464) Prec@5 99.000 (99.179) +2022-11-14 17:12:05,773 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0728) Prec@1 86.000 (88.435) Prec@5 98.000 (99.165) +2022-11-14 17:12:05,781 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0730) Prec@1 88.000 (88.430) Prec@5 100.000 (99.174) +2022-11-14 17:12:05,789 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0730) Prec@1 89.000 (88.437) Prec@5 99.000 (99.172) +2022-11-14 17:12:05,797 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0880 (0.0732) Prec@1 86.000 (88.409) Prec@5 98.000 (99.159) +2022-11-14 17:12:05,805 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0732) Prec@1 89.000 (88.416) Prec@5 99.000 (99.157) +2022-11-14 17:12:05,812 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0731) Prec@1 91.000 (88.444) Prec@5 100.000 (99.167) +2022-11-14 17:12:05,820 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0555 (0.0729) Prec@1 93.000 (88.495) Prec@5 100.000 (99.176) +2022-11-14 17:12:05,828 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0405 (0.0725) Prec@1 95.000 (88.565) Prec@5 100.000 (99.185) +2022-11-14 17:12:05,836 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0727) Prec@1 84.000 (88.516) Prec@5 100.000 (99.194) +2022-11-14 17:12:05,844 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0726) Prec@1 90.000 (88.532) Prec@5 99.000 (99.191) +2022-11-14 17:12:05,851 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0727) Prec@1 88.000 (88.526) Prec@5 99.000 (99.189) +2022-11-14 17:12:05,859 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0727) Prec@1 89.000 (88.531) Prec@5 98.000 (99.177) +2022-11-14 17:12:05,867 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0726) Prec@1 91.000 (88.557) Prec@5 99.000 (99.175) +2022-11-14 17:12:05,874 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0727) Prec@1 88.000 (88.551) Prec@5 98.000 (99.163) +2022-11-14 17:12:05,882 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0728) Prec@1 85.000 (88.515) Prec@5 100.000 (99.172) +2022-11-14 17:12:05,890 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0728) Prec@1 86.000 (88.490) Prec@5 100.000 (99.180) +2022-11-14 17:12:05,962 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:12:06,287 Epoch: [488][0/500] Time 0.022 (0.022) Data 0.245 (0.245) Loss 0.0285 (0.0285) Prec@1 96.000 (96.000) Prec@5 99.000 (99.000) +2022-11-14 17:12:06,478 Epoch: [488][10/500] Time 0.016 (0.017) Data 0.001 (0.024) Loss 0.0210 (0.0247) Prec@1 97.000 (96.500) Prec@5 100.000 (99.500) +2022-11-14 17:12:06,662 Epoch: [488][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0375 (0.0290) Prec@1 94.000 (95.667) Prec@5 100.000 (99.667) +2022-11-14 17:12:06,846 Epoch: [488][30/500] Time 0.016 (0.017) Data 0.001 (0.009) Loss 0.0368 (0.0309) Prec@1 94.000 (95.250) Prec@5 99.000 (99.500) +2022-11-14 17:12:07,031 Epoch: [488][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0314 (0.0310) Prec@1 94.000 (95.000) Prec@5 99.000 (99.400) +2022-11-14 17:12:07,220 Epoch: [488][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0285 (0.0306) Prec@1 97.000 (95.333) Prec@5 100.000 (99.500) +2022-11-14 17:12:07,404 Epoch: [488][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0213 (0.0293) Prec@1 98.000 (95.714) Prec@5 100.000 (99.571) +2022-11-14 17:12:07,589 Epoch: [488][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0228 (0.0285) Prec@1 96.000 (95.750) Prec@5 100.000 (99.625) +2022-11-14 17:12:07,779 Epoch: [488][80/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0200 (0.0275) Prec@1 97.000 (95.889) Prec@5 100.000 (99.667) +2022-11-14 17:12:07,969 Epoch: [488][90/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0253 (0.0273) Prec@1 96.000 (95.900) Prec@5 100.000 (99.700) +2022-11-14 17:12:08,161 Epoch: [488][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0491 (0.0293) Prec@1 92.000 (95.545) Prec@5 100.000 (99.727) +2022-11-14 17:12:08,349 Epoch: [488][110/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0169 (0.0283) Prec@1 96.000 (95.583) Prec@5 100.000 (99.750) +2022-11-14 17:12:08,599 Epoch: [488][120/500] Time 0.025 (0.017) Data 0.001 (0.003) Loss 0.0167 (0.0274) Prec@1 98.000 (95.769) Prec@5 100.000 (99.769) +2022-11-14 17:12:08,869 Epoch: [488][130/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0345 (0.0279) Prec@1 93.000 (95.571) Prec@5 100.000 (99.786) +2022-11-14 17:12:09,148 Epoch: [488][140/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0344 (0.0283) Prec@1 94.000 (95.467) Prec@5 100.000 (99.800) +2022-11-14 17:12:09,420 Epoch: [488][150/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0238 (0.0280) Prec@1 96.000 (95.500) Prec@5 99.000 (99.750) +2022-11-14 17:12:09,692 Epoch: [488][160/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0225 (0.0277) Prec@1 97.000 (95.588) Prec@5 100.000 (99.765) +2022-11-14 17:12:09,966 Epoch: [488][170/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0257 (0.0276) Prec@1 95.000 (95.556) Prec@5 100.000 (99.778) +2022-11-14 17:12:10,243 Epoch: [488][180/500] Time 0.026 (0.019) Data 0.001 (0.003) Loss 0.0541 (0.0290) Prec@1 91.000 (95.316) Prec@5 100.000 (99.789) +2022-11-14 17:12:10,521 Epoch: [488][190/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0296 (0.0290) Prec@1 95.000 (95.300) Prec@5 99.000 (99.750) +2022-11-14 17:12:10,803 Epoch: [488][200/500] Time 0.026 (0.020) Data 0.001 (0.003) Loss 0.0303 (0.0291) Prec@1 94.000 (95.238) Prec@5 100.000 (99.762) +2022-11-14 17:12:11,090 Epoch: [488][210/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0401 (0.0296) Prec@1 91.000 (95.045) Prec@5 100.000 (99.773) +2022-11-14 17:12:11,364 Epoch: [488][220/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0455 (0.0303) Prec@1 91.000 (94.870) Prec@5 100.000 (99.783) +2022-11-14 17:12:11,644 Epoch: [488][230/500] Time 0.024 (0.021) Data 0.003 (0.003) Loss 0.0369 (0.0305) Prec@1 95.000 (94.875) Prec@5 99.000 (99.750) +2022-11-14 17:12:11,921 Epoch: [488][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0228 (0.0302) Prec@1 97.000 (94.960) Prec@5 100.000 (99.760) +2022-11-14 17:12:12,188 Epoch: [488][250/500] Time 0.026 (0.021) Data 0.001 (0.003) Loss 0.0325 (0.0303) Prec@1 94.000 (94.923) Prec@5 99.000 (99.731) +2022-11-14 17:12:12,454 Epoch: [488][260/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0406 (0.0307) Prec@1 92.000 (94.815) Prec@5 100.000 (99.741) +2022-11-14 17:12:12,721 Epoch: [488][270/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0097 (0.0300) Prec@1 99.000 (94.964) Prec@5 100.000 (99.750) +2022-11-14 17:12:12,987 Epoch: [488][280/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0450 (0.0305) Prec@1 93.000 (94.897) Prec@5 99.000 (99.724) +2022-11-14 17:12:13,254 Epoch: [488][290/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0390 (0.0308) Prec@1 93.000 (94.833) Prec@5 100.000 (99.733) +2022-11-14 17:12:13,522 Epoch: [488][300/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0157 (0.0303) Prec@1 98.000 (94.935) Prec@5 99.000 (99.710) +2022-11-14 17:12:13,793 Epoch: [488][310/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0254 (0.0301) Prec@1 96.000 (94.969) Prec@5 100.000 (99.719) +2022-11-14 17:12:14,065 Epoch: [488][320/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0373 (0.0303) Prec@1 94.000 (94.939) Prec@5 100.000 (99.727) +2022-11-14 17:12:14,336 Epoch: [488][330/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0126 (0.0298) Prec@1 99.000 (95.059) Prec@5 100.000 (99.735) +2022-11-14 17:12:14,607 Epoch: [488][340/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0205 (0.0295) Prec@1 97.000 (95.114) Prec@5 100.000 (99.743) +2022-11-14 17:12:14,881 Epoch: [488][350/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0361 (0.0297) Prec@1 92.000 (95.028) Prec@5 100.000 (99.750) +2022-11-14 17:12:15,150 Epoch: [488][360/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0323 (0.0298) Prec@1 95.000 (95.027) Prec@5 100.000 (99.757) +2022-11-14 17:12:15,417 Epoch: [488][370/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0315 (0.0298) Prec@1 93.000 (94.974) Prec@5 100.000 (99.763) +2022-11-14 17:12:15,687 Epoch: [488][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0364 (0.0300) Prec@1 94.000 (94.949) Prec@5 100.000 (99.769) +2022-11-14 17:12:15,956 Epoch: [488][390/500] Time 0.027 (0.022) Data 0.001 (0.002) Loss 0.0453 (0.0304) Prec@1 94.000 (94.925) Prec@5 100.000 (99.775) +2022-11-14 17:12:16,223 Epoch: [488][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0476 (0.0308) Prec@1 93.000 (94.878) Prec@5 100.000 (99.780) +2022-11-14 17:12:16,490 Epoch: [488][410/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0226 (0.0306) Prec@1 97.000 (94.929) Prec@5 100.000 (99.786) +2022-11-14 17:12:16,759 Epoch: [488][420/500] Time 0.026 (0.022) Data 0.001 (0.002) Loss 0.0650 (0.0314) Prec@1 89.000 (94.791) Prec@5 100.000 (99.791) +2022-11-14 17:12:17,029 Epoch: [488][430/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0396 (0.0316) Prec@1 93.000 (94.750) Prec@5 100.000 (99.795) +2022-11-14 17:12:17,301 Epoch: [488][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0217 (0.0314) Prec@1 95.000 (94.756) Prec@5 100.000 (99.800) +2022-11-14 17:12:17,567 Epoch: [488][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0470 (0.0317) Prec@1 93.000 (94.717) Prec@5 99.000 (99.783) +2022-11-14 17:12:17,840 Epoch: [488][460/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0432 (0.0320) Prec@1 92.000 (94.660) Prec@5 100.000 (99.787) +2022-11-14 17:12:18,113 Epoch: [488][470/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0291 (0.0319) Prec@1 95.000 (94.667) Prec@5 100.000 (99.792) +2022-11-14 17:12:18,381 Epoch: [488][480/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0198 (0.0317) Prec@1 95.000 (94.673) Prec@5 100.000 (99.796) +2022-11-14 17:12:18,646 Epoch: [488][490/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0200 (0.0314) Prec@1 97.000 (94.720) Prec@5 100.000 (99.800) +2022-11-14 17:12:18,888 Epoch: [488][499/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0299 (0.0314) Prec@1 95.000 (94.725) Prec@5 99.000 (99.784) +2022-11-14 17:12:19,195 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0451 (0.0451) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,202 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0991 (0.0721) Prec@1 85.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,209 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0594 (0.0678) Prec@1 90.000 (89.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,218 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0616 (0.0663) Prec@1 91.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,225 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0820 (0.0694) Prec@1 88.000 (89.600) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,232 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0372 (0.0641) Prec@1 95.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,239 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0601 (0.0635) Prec@1 92.000 (90.714) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,249 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0648) Prec@1 87.000 (90.250) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,256 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0821 (0.0667) Prec@1 88.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:19,263 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0668) Prec@1 88.000 (89.800) Prec@5 99.000 (99.900) +2022-11-14 17:12:19,271 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0660) Prec@1 93.000 (90.091) Prec@5 100.000 (99.909) +2022-11-14 17:12:19,279 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0773 (0.0670) Prec@1 86.000 (89.750) Prec@5 99.000 (99.833) +2022-11-14 17:12:19,286 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0671) Prec@1 88.000 (89.615) Prec@5 100.000 (99.846) +2022-11-14 17:12:19,294 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0687) Prec@1 85.000 (89.286) Prec@5 97.000 (99.643) +2022-11-14 17:12:19,302 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0688) Prec@1 87.000 (89.133) Prec@5 100.000 (99.667) +2022-11-14 17:12:19,309 Test: 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0.0962 (0.0747) Prec@1 84.000 (87.864) Prec@5 99.000 (99.364) +2022-11-14 17:12:19,362 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1197 (0.0767) Prec@1 83.000 (87.652) Prec@5 97.000 (99.261) +2022-11-14 17:12:19,370 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0765) Prec@1 88.000 (87.667) Prec@5 100.000 (99.292) +2022-11-14 17:12:19,377 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1018 (0.0775) Prec@1 84.000 (87.520) Prec@5 100.000 (99.320) +2022-11-14 17:12:19,385 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0778) Prec@1 87.000 (87.500) Prec@5 100.000 (99.346) +2022-11-14 17:12:19,393 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0593 (0.0771) Prec@1 88.000 (87.519) Prec@5 100.000 (99.370) +2022-11-14 17:12:19,401 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0664 (0.0767) Prec@1 90.000 (87.607) Prec@5 100.000 (99.393) +2022-11-14 17:12:19,409 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0767) Prec@1 87.000 (87.586) Prec@5 99.000 (99.379) +2022-11-14 17:12:19,417 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0717 (0.0765) Prec@1 88.000 (87.600) Prec@5 99.000 (99.367) +2022-11-14 17:12:19,425 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0647 (0.0761) Prec@1 86.000 (87.548) Prec@5 99.000 (99.355) +2022-11-14 17:12:19,433 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0758) Prec@1 90.000 (87.625) Prec@5 99.000 (99.344) +2022-11-14 17:12:19,441 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0758) Prec@1 87.000 (87.606) Prec@5 100.000 (99.364) +2022-11-14 17:12:19,449 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0761) Prec@1 85.000 (87.529) Prec@5 99.000 (99.353) +2022-11-14 17:12:19,457 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0759) Prec@1 91.000 (87.629) Prec@5 99.000 (99.343) +2022-11-14 17:12:19,464 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0653 (0.0756) Prec@1 89.000 (87.667) Prec@5 100.000 (99.361) +2022-11-14 17:12:19,472 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0759) Prec@1 87.000 (87.649) Prec@5 97.000 (99.297) +2022-11-14 17:12:19,479 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0952 (0.0764) Prec@1 85.000 (87.579) Prec@5 99.000 (99.289) +2022-11-14 17:12:19,487 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0762) Prec@1 91.000 (87.667) Prec@5 100.000 (99.308) +2022-11-14 17:12:19,494 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0762) Prec@1 88.000 (87.675) Prec@5 100.000 (99.325) +2022-11-14 17:12:19,501 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0764) Prec@1 85.000 (87.610) Prec@5 98.000 (99.293) +2022-11-14 17:12:19,509 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0763) Prec@1 90.000 (87.667) Prec@5 99.000 (99.286) +2022-11-14 17:12:19,516 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0445 (0.0755) Prec@1 94.000 (87.814) Prec@5 100.000 (99.302) +2022-11-14 17:12:19,524 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0626 (0.0752) Prec@1 90.000 (87.864) Prec@5 99.000 (99.295) +2022-11-14 17:12:19,531 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0649 (0.0750) Prec@1 90.000 (87.911) Prec@5 99.000 (99.289) +2022-11-14 17:12:19,540 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1110 (0.0758) Prec@1 84.000 (87.826) Prec@5 98.000 (99.261) +2022-11-14 17:12:19,547 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0614 (0.0755) Prec@1 89.000 (87.851) Prec@5 99.000 (99.255) +2022-11-14 17:12:19,555 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1222 (0.0764) Prec@1 79.000 (87.667) Prec@5 99.000 (99.250) +2022-11-14 17:12:19,562 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0324 (0.0756) Prec@1 96.000 (87.837) Prec@5 100.000 (99.265) +2022-11-14 17:12:19,569 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1061 (0.0762) Prec@1 83.000 (87.740) Prec@5 99.000 (99.260) +2022-11-14 17:12:19,577 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0637 (0.0759) Prec@1 91.000 (87.804) Prec@5 100.000 (99.275) +2022-11-14 17:12:19,585 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0975 (0.0763) Prec@1 82.000 (87.692) Prec@5 98.000 (99.250) +2022-11-14 17:12:19,592 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0694 (0.0762) Prec@1 89.000 (87.717) Prec@5 100.000 (99.264) +2022-11-14 17:12:19,600 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0638 (0.0760) Prec@1 90.000 (87.759) Prec@5 100.000 (99.278) +2022-11-14 17:12:19,607 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1015 (0.0764) Prec@1 83.000 (87.673) Prec@5 99.000 (99.273) +2022-11-14 17:12:19,615 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0905 (0.0767) Prec@1 86.000 (87.643) Prec@5 99.000 (99.268) +2022-11-14 17:12:19,622 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0573 (0.0763) Prec@1 90.000 (87.684) Prec@5 100.000 (99.281) +2022-11-14 17:12:19,630 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0808 (0.0764) Prec@1 88.000 (87.690) Prec@5 99.000 (99.276) +2022-11-14 17:12:19,637 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1064 (0.0769) Prec@1 79.000 (87.542) Prec@5 100.000 (99.288) +2022-11-14 17:12:19,645 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0590 (0.0766) Prec@1 89.000 (87.567) Prec@5 100.000 (99.300) +2022-11-14 17:12:19,653 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0956 (0.0769) Prec@1 87.000 (87.557) Prec@5 97.000 (99.262) +2022-11-14 17:12:19,660 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0718 (0.0769) Prec@1 87.000 (87.548) Prec@5 100.000 (99.274) +2022-11-14 17:12:19,668 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0685 (0.0767) Prec@1 88.000 (87.556) Prec@5 100.000 (99.286) +2022-11-14 17:12:19,675 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0530 (0.0764) Prec@1 91.000 (87.609) Prec@5 100.000 (99.297) +2022-11-14 17:12:19,683 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0957 (0.0767) Prec@1 84.000 (87.554) Prec@5 99.000 (99.292) +2022-11-14 17:12:19,690 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0768) Prec@1 85.000 (87.515) Prec@5 100.000 (99.303) +2022-11-14 17:12:19,698 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0518 (0.0764) Prec@1 91.000 (87.567) Prec@5 100.000 (99.313) +2022-11-14 17:12:19,705 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0695 (0.0763) Prec@1 90.000 (87.603) Prec@5 97.000 (99.279) +2022-11-14 17:12:19,712 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0679 (0.0762) Prec@1 88.000 (87.609) Prec@5 99.000 (99.275) +2022-11-14 17:12:19,720 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0954 (0.0765) Prec@1 86.000 (87.586) Prec@5 97.000 (99.243) +2022-11-14 17:12:19,727 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1003 (0.0768) Prec@1 86.000 (87.563) Prec@5 99.000 (99.239) +2022-11-14 17:12:19,735 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0766) Prec@1 91.000 (87.611) Prec@5 100.000 (99.250) +2022-11-14 17:12:19,743 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0349 (0.0761) Prec@1 95.000 (87.712) Prec@5 100.000 (99.260) +2022-11-14 17:12:19,750 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0579 (0.0758) Prec@1 92.000 (87.770) Prec@5 100.000 (99.270) +2022-11-14 17:12:19,758 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0760) Prec@1 87.000 (87.760) Prec@5 99.000 (99.267) +2022-11-14 17:12:19,765 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0578 (0.0758) Prec@1 93.000 (87.829) Prec@5 99.000 (99.263) +2022-11-14 17:12:19,773 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0827 (0.0759) Prec@1 87.000 (87.818) Prec@5 99.000 (99.260) +2022-11-14 17:12:19,780 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0901 (0.0760) Prec@1 85.000 (87.782) Prec@5 97.000 (99.231) +2022-11-14 17:12:19,788 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0946 (0.0763) Prec@1 87.000 (87.772) Prec@5 99.000 (99.228) +2022-11-14 17:12:19,795 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0623 (0.0761) Prec@1 88.000 (87.775) Prec@5 100.000 (99.237) +2022-11-14 17:12:19,803 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0754 (0.0761) Prec@1 89.000 (87.790) Prec@5 98.000 (99.222) +2022-11-14 17:12:19,810 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0760) Prec@1 89.000 (87.805) Prec@5 100.000 (99.232) +2022-11-14 17:12:19,818 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0761) Prec@1 87.000 (87.795) Prec@5 99.000 (99.229) +2022-11-14 17:12:19,826 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0587 (0.0759) Prec@1 88.000 (87.798) Prec@5 100.000 (99.238) +2022-11-14 17:12:19,833 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0870 (0.0760) Prec@1 89.000 (87.812) Prec@5 99.000 (99.235) +2022-11-14 17:12:19,841 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0948 (0.0763) Prec@1 85.000 (87.779) Prec@5 100.000 (99.244) +2022-11-14 17:12:19,848 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0971 (0.0765) Prec@1 85.000 (87.747) Prec@5 100.000 (99.253) +2022-11-14 17:12:19,855 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0666 (0.0764) Prec@1 89.000 (87.761) Prec@5 98.000 (99.239) +2022-11-14 17:12:19,863 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0734 (0.0763) Prec@1 86.000 (87.742) Prec@5 100.000 (99.247) +2022-11-14 17:12:19,870 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0722 (0.0763) Prec@1 88.000 (87.744) Prec@5 100.000 (99.256) +2022-11-14 17:12:19,878 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0437 (0.0759) Prec@1 93.000 (87.802) Prec@5 100.000 (99.264) +2022-11-14 17:12:19,885 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0512 (0.0757) Prec@1 90.000 (87.826) Prec@5 100.000 (99.272) +2022-11-14 17:12:19,893 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0731 (0.0756) Prec@1 90.000 (87.849) Prec@5 99.000 (99.269) +2022-11-14 17:12:19,900 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0716 (0.0756) Prec@1 87.000 (87.840) Prec@5 99.000 (99.266) +2022-11-14 17:12:19,908 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0865 (0.0757) Prec@1 87.000 (87.832) Prec@5 100.000 (99.274) +2022-11-14 17:12:19,915 Test: [95/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0624 (0.0756) Prec@1 91.000 (87.865) Prec@5 99.000 (99.271) +2022-11-14 17:12:19,923 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0609 (0.0754) Prec@1 89.000 (87.876) Prec@5 98.000 (99.258) +2022-11-14 17:12:19,930 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0909 (0.0756) Prec@1 87.000 (87.867) Prec@5 98.000 (99.245) +2022-11-14 17:12:19,938 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1052 (0.0759) Prec@1 84.000 (87.828) Prec@5 100.000 (99.253) +2022-11-14 17:12:19,945 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0645 (0.0758) Prec@1 89.000 (87.840) Prec@5 100.000 (99.260) +2022-11-14 17:12:19,999 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:12:20,318 Epoch: [489][0/500] Time 0.025 (0.025) Data 0.239 (0.239) Loss 0.0433 (0.0433) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:20,524 Epoch: [489][10/500] Time 0.020 (0.019) Data 0.002 (0.023) Loss 0.0221 (0.0327) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:20,713 Epoch: [489][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0445 (0.0367) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:20,904 Epoch: [489][30/500] Time 0.020 (0.017) Data 0.001 (0.009) Loss 0.0347 (0.0362) Prec@1 95.000 (94.250) Prec@5 100.000 (100.000) +2022-11-14 17:12:21,097 Epoch: [489][40/500] Time 0.018 (0.017) Data 0.002 (0.007) Loss 0.0244 (0.0338) Prec@1 97.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 17:12:21,287 Epoch: [489][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0389 (0.0347) Prec@1 94.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:21,476 Epoch: [489][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0354 (0.0348) Prec@1 95.000 (94.714) Prec@5 100.000 (100.000) +2022-11-14 17:12:21,665 Epoch: [489][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0336 (0.0346) Prec@1 92.000 (94.375) Prec@5 100.000 (100.000) +2022-11-14 17:12:21,853 Epoch: [489][80/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0122 (0.0321) Prec@1 99.000 (94.889) Prec@5 100.000 (100.000) +2022-11-14 17:12:22,041 Epoch: [489][90/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0318 (0.0321) Prec@1 93.000 (94.700) Prec@5 100.000 (100.000) +2022-11-14 17:12:22,280 Epoch: [489][100/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0335 (0.0322) Prec@1 95.000 (94.727) Prec@5 100.000 (100.000) +2022-11-14 17:12:22,545 Epoch: [489][110/500] Time 0.025 (0.018) Data 0.001 (0.004) Loss 0.0344 (0.0324) Prec@1 94.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:22,814 Epoch: [489][120/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0380 (0.0328) Prec@1 92.000 (94.462) Prec@5 100.000 (100.000) +2022-11-14 17:12:23,088 Epoch: [489][130/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0293 (0.0326) Prec@1 95.000 (94.500) Prec@5 99.000 (99.929) +2022-11-14 17:12:23,359 Epoch: [489][140/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0382 (0.0330) Prec@1 95.000 (94.533) Prec@5 99.000 (99.867) +2022-11-14 17:12:23,633 Epoch: [489][150/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0267 (0.0326) Prec@1 96.000 (94.625) Prec@5 99.000 (99.812) +2022-11-14 17:12:23,907 Epoch: [489][160/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0384 (0.0329) Prec@1 92.000 (94.471) Prec@5 100.000 (99.824) +2022-11-14 17:12:24,183 Epoch: [489][170/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0135 (0.0318) Prec@1 98.000 (94.667) Prec@5 100.000 (99.833) +2022-11-14 17:12:24,444 Epoch: [489][180/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0169 (0.0310) Prec@1 97.000 (94.789) Prec@5 100.000 (99.842) +2022-11-14 17:12:24,709 Epoch: [489][190/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0139 (0.0302) Prec@1 98.000 (94.950) Prec@5 100.000 (99.850) +2022-11-14 17:12:24,978 Epoch: [489][200/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0285 (0.0301) Prec@1 95.000 (94.952) Prec@5 100.000 (99.857) +2022-11-14 17:12:25,247 Epoch: [489][210/500] Time 0.027 (0.021) Data 0.001 (0.003) Loss 0.0275 (0.0300) Prec@1 97.000 (95.045) Prec@5 100.000 (99.864) +2022-11-14 17:12:25,512 Epoch: [489][220/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0220 (0.0296) Prec@1 97.000 (95.130) Prec@5 100.000 (99.870) +2022-11-14 17:12:25,774 Epoch: [489][230/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0200 (0.0292) Prec@1 97.000 (95.208) Prec@5 100.000 (99.875) +2022-11-14 17:12:26,035 Epoch: [489][240/500] Time 0.024 (0.021) Data 0.001 (0.003) Loss 0.0423 (0.0298) Prec@1 94.000 (95.160) Prec@5 100.000 (99.880) +2022-11-14 17:12:26,304 Epoch: [489][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0309 (0.0298) Prec@1 93.000 (95.077) Prec@5 100.000 (99.885) +2022-11-14 17:12:26,570 Epoch: [489][260/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0304 (0.0298) Prec@1 93.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:12:26,837 Epoch: [489][270/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0106 (0.0291) Prec@1 99.000 (95.143) Prec@5 100.000 (99.893) +2022-11-14 17:12:27,106 Epoch: [489][280/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0388 (0.0295) Prec@1 94.000 (95.103) Prec@5 100.000 (99.897) +2022-11-14 17:12:27,369 Epoch: [489][290/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0176 (0.0291) Prec@1 98.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:12:27,633 Epoch: [489][300/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0249 (0.0289) Prec@1 95.000 (95.194) Prec@5 100.000 (99.903) +2022-11-14 17:12:27,896 Epoch: [489][310/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0209 (0.0287) Prec@1 96.000 (95.219) Prec@5 99.000 (99.875) +2022-11-14 17:12:28,162 Epoch: [489][320/500] Time 0.023 (0.022) Data 0.003 (0.002) Loss 0.0249 (0.0286) Prec@1 95.000 (95.212) Prec@5 99.000 (99.848) +2022-11-14 17:12:28,422 Epoch: [489][330/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0360 (0.0288) Prec@1 94.000 (95.176) Prec@5 99.000 (99.824) +2022-11-14 17:12:28,685 Epoch: [489][340/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0398 (0.0291) Prec@1 94.000 (95.143) Prec@5 100.000 (99.829) +2022-11-14 17:12:28,948 Epoch: [489][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0335 (0.0292) Prec@1 95.000 (95.139) Prec@5 100.000 (99.833) +2022-11-14 17:12:29,216 Epoch: [489][360/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0170 (0.0289) Prec@1 96.000 (95.162) Prec@5 100.000 (99.838) +2022-11-14 17:12:29,479 Epoch: [489][370/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0246 (0.0288) Prec@1 96.000 (95.184) Prec@5 100.000 (99.842) +2022-11-14 17:12:29,744 Epoch: [489][380/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0215 (0.0286) Prec@1 98.000 (95.256) Prec@5 100.000 (99.846) +2022-11-14 17:12:30,008 Epoch: [489][390/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0175 (0.0283) Prec@1 98.000 (95.325) Prec@5 100.000 (99.850) +2022-11-14 17:12:30,272 Epoch: [489][400/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0263 (0.0283) Prec@1 96.000 (95.341) Prec@5 98.000 (99.805) +2022-11-14 17:12:30,538 Epoch: [489][410/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0320 (0.0284) Prec@1 96.000 (95.357) Prec@5 100.000 (99.810) +2022-11-14 17:12:30,802 Epoch: [489][420/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0354 (0.0285) Prec@1 97.000 (95.395) Prec@5 100.000 (99.814) +2022-11-14 17:12:31,069 Epoch: [489][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0277 (0.0285) Prec@1 94.000 (95.364) Prec@5 100.000 (99.818) +2022-11-14 17:12:31,334 Epoch: [489][440/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0311 (0.0286) Prec@1 94.000 (95.333) Prec@5 100.000 (99.822) +2022-11-14 17:12:31,598 Epoch: [489][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0141 (0.0282) Prec@1 98.000 (95.391) Prec@5 100.000 (99.826) +2022-11-14 17:12:31,862 Epoch: [489][460/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0121 (0.0279) Prec@1 99.000 (95.468) Prec@5 100.000 (99.830) +2022-11-14 17:12:32,131 Epoch: [489][470/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0220 (0.0278) Prec@1 97.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:12:32,397 Epoch: [489][480/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0212 (0.0276) Prec@1 98.000 (95.551) Prec@5 100.000 (99.837) +2022-11-14 17:12:32,664 Epoch: [489][490/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0305 (0.0277) Prec@1 94.000 (95.520) Prec@5 99.000 (99.820) +2022-11-14 17:12:32,904 Epoch: [489][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0384 (0.0279) Prec@1 95.000 (95.510) Prec@5 99.000 (99.804) +2022-11-14 17:12:33,204 Test: [0/100] Model Time 0.011 (0.011) Loss Time 0.000 (0.000) Loss 0.0441 (0.0441) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:33,213 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0694 (0.0568) Prec@1 87.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:33,222 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0812 (0.0649) Prec@1 83.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:33,232 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0676 (0.0656) Prec@1 88.000 (87.750) Prec@5 99.000 (99.750) +2022-11-14 17:12:33,239 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0659) Prec@1 90.000 (88.200) Prec@5 100.000 (99.800) +2022-11-14 17:12:33,246 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0380 (0.0613) Prec@1 94.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 17:12:33,253 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0662 (0.0620) Prec@1 90.000 (89.286) Prec@5 100.000 (99.857) +2022-11-14 17:12:33,263 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0787 (0.0641) Prec@1 86.000 (88.875) Prec@5 100.000 (99.875) +2022-11-14 17:12:33,270 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0866 (0.0666) Prec@1 87.000 (88.667) Prec@5 99.000 (99.778) +2022-11-14 17:12:33,277 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0671) Prec@1 86.000 (88.400) Prec@5 99.000 (99.700) +2022-11-14 17:12:33,284 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0666) Prec@1 91.000 (88.636) Prec@5 100.000 (99.727) +2022-11-14 17:12:33,292 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0927 (0.0688) Prec@1 83.000 (88.167) Prec@5 99.000 (99.667) +2022-11-14 17:12:33,299 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0688) Prec@1 89.000 (88.231) Prec@5 100.000 (99.692) +2022-11-14 17:12:33,307 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0687) Prec@1 90.000 (88.357) Prec@5 100.000 (99.714) +2022-11-14 17:12:33,315 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0833 (0.0697) Prec@1 86.000 (88.200) Prec@5 99.000 (99.667) +2022-11-14 17:12:33,322 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0692) Prec@1 90.000 (88.312) Prec@5 100.000 (99.688) +2022-11-14 17:12:33,330 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0685) Prec@1 92.000 (88.529) Prec@5 99.000 (99.647) +2022-11-14 17:12:33,337 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0696) Prec@1 87.000 (88.444) Prec@5 100.000 (99.667) +2022-11-14 17:12:33,345 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0969 (0.0711) Prec@1 85.000 (88.263) Prec@5 98.000 (99.579) +2022-11-14 17:12:33,352 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1195 (0.0735) Prec@1 82.000 (87.950) Prec@5 98.000 (99.500) +2022-11-14 17:12:33,360 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0738) Prec@1 86.000 (87.857) Prec@5 100.000 (99.524) +2022-11-14 17:12:33,368 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0742) Prec@1 87.000 (87.818) Prec@5 100.000 (99.545) +2022-11-14 17:12:33,378 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0741) Prec@1 90.000 (87.913) Prec@5 100.000 (99.565) +2022-11-14 17:12:33,389 Test: [23/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0685 (0.0739) Prec@1 87.000 (87.875) Prec@5 100.000 (99.583) +2022-11-14 17:12:33,398 Test: [24/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0853 (0.0744) Prec@1 88.000 (87.880) Prec@5 100.000 (99.600) +2022-11-14 17:12:33,408 Test: [25/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0745) Prec@1 88.000 (87.885) Prec@5 99.000 (99.577) +2022-11-14 17:12:33,417 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0735) Prec@1 92.000 (88.037) Prec@5 100.000 (99.593) +2022-11-14 17:12:33,425 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0590 (0.0730) Prec@1 92.000 (88.179) Prec@5 100.000 (99.607) +2022-11-14 17:12:33,433 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0729) Prec@1 88.000 (88.172) Prec@5 99.000 (99.586) +2022-11-14 17:12:33,441 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0736) Prec@1 84.000 (88.033) Prec@5 98.000 (99.533) +2022-11-14 17:12:33,448 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0920 (0.0742) Prec@1 87.000 (88.000) Prec@5 100.000 (99.548) +2022-11-14 17:12:33,456 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0740) Prec@1 89.000 (88.031) Prec@5 99.000 (99.531) +2022-11-14 17:12:33,463 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0739) Prec@1 86.000 (87.970) Prec@5 100.000 (99.545) +2022-11-14 17:12:33,471 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0741) Prec@1 85.000 (87.882) Prec@5 100.000 (99.559) +2022-11-14 17:12:33,479 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0740) Prec@1 89.000 (87.914) Prec@5 98.000 (99.514) +2022-11-14 17:12:33,486 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0742) Prec@1 88.000 (87.917) Prec@5 100.000 (99.528) +2022-11-14 17:12:33,494 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0788 (0.0743) Prec@1 89.000 (87.946) Prec@5 99.000 (99.514) +2022-11-14 17:12:33,501 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0746) Prec@1 87.000 (87.921) Prec@5 99.000 (99.500) +2022-11-14 17:12:33,509 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0741) Prec@1 92.000 (88.026) Prec@5 99.000 (99.487) +2022-11-14 17:12:33,517 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0738) Prec@1 91.000 (88.100) Prec@5 99.000 (99.475) +2022-11-14 17:12:33,525 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1120 (0.0747) Prec@1 83.000 (87.976) Prec@5 98.000 (99.439) +2022-11-14 17:12:33,532 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0745) Prec@1 89.000 (88.000) Prec@5 100.000 (99.452) +2022-11-14 17:12:33,540 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0411 (0.0737) Prec@1 93.000 (88.116) Prec@5 100.000 (99.465) +2022-11-14 17:12:33,548 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0520 (0.0732) Prec@1 94.000 (88.250) Prec@5 99.000 (99.455) +2022-11-14 17:12:33,556 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0732) Prec@1 88.000 (88.244) Prec@5 98.000 (99.422) +2022-11-14 17:12:33,564 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1173 (0.0742) Prec@1 80.000 (88.065) Prec@5 98.000 (99.391) +2022-11-14 17:12:33,571 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0539 (0.0738) Prec@1 91.000 (88.128) Prec@5 100.000 (99.404) +2022-11-14 17:12:33,579 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0967 (0.0743) Prec@1 86.000 (88.083) Prec@5 98.000 (99.375) +2022-11-14 17:12:33,586 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0738) Prec@1 89.000 (88.102) Prec@5 100.000 (99.388) +2022-11-14 17:12:33,594 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0744) Prec@1 83.000 (88.000) Prec@5 100.000 (99.400) +2022-11-14 17:12:33,601 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0521 (0.0740) Prec@1 89.000 (88.020) Prec@5 100.000 (99.412) +2022-11-14 17:12:33,609 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0739) Prec@1 87.000 (88.000) Prec@5 99.000 (99.404) +2022-11-14 17:12:33,617 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0608 (0.0737) Prec@1 88.000 (88.000) Prec@5 98.000 (99.377) +2022-11-14 17:12:33,624 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0738) Prec@1 87.000 (87.981) Prec@5 98.000 (99.352) +2022-11-14 17:12:33,632 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0744) Prec@1 84.000 (87.909) Prec@5 100.000 (99.364) +2022-11-14 17:12:33,639 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0741) Prec@1 91.000 (87.964) Prec@5 99.000 (99.357) +2022-11-14 17:12:33,647 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0866 (0.0743) Prec@1 87.000 (87.947) Prec@5 100.000 (99.368) +2022-11-14 17:12:33,655 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0744) Prec@1 90.000 (87.983) Prec@5 98.000 (99.345) +2022-11-14 17:12:33,662 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0845 (0.0746) Prec@1 86.000 (87.949) Prec@5 100.000 (99.356) +2022-11-14 17:12:33,670 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0745) Prec@1 87.000 (87.933) Prec@5 99.000 (99.350) +2022-11-14 17:12:33,677 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0746) Prec@1 88.000 (87.934) Prec@5 99.000 (99.344) +2022-11-14 17:12:33,685 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0777 (0.0746) Prec@1 86.000 (87.903) Prec@5 99.000 (99.339) +2022-11-14 17:12:33,693 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0609 (0.0744) Prec@1 91.000 (87.952) Prec@5 100.000 (99.349) +2022-11-14 17:12:33,700 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0315 (0.0737) Prec@1 95.000 (88.062) Prec@5 100.000 (99.359) +2022-11-14 17:12:33,708 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0741) Prec@1 84.000 (88.000) Prec@5 100.000 (99.369) +2022-11-14 17:12:33,716 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0740) Prec@1 90.000 (88.030) Prec@5 98.000 (99.348) +2022-11-14 17:12:33,723 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0317 (0.0734) Prec@1 94.000 (88.119) Prec@5 100.000 (99.358) +2022-11-14 17:12:33,731 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0735) Prec@1 88.000 (88.118) Prec@5 100.000 (99.368) +2022-11-14 17:12:33,738 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0732) Prec@1 91.000 (88.159) Prec@5 99.000 (99.362) +2022-11-14 17:12:33,747 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0732) Prec@1 89.000 (88.171) Prec@5 100.000 (99.371) +2022-11-14 17:12:33,755 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0736) Prec@1 86.000 (88.141) Prec@5 97.000 (99.338) +2022-11-14 17:12:33,762 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0600 (0.0734) Prec@1 90.000 (88.167) Prec@5 100.000 (99.347) +2022-11-14 17:12:33,770 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0358 (0.0729) Prec@1 96.000 (88.274) Prec@5 99.000 (99.342) +2022-11-14 17:12:33,777 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0382 (0.0724) Prec@1 95.000 (88.365) Prec@5 100.000 (99.351) +2022-11-14 17:12:33,785 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0724) Prec@1 88.000 (88.360) Prec@5 100.000 (99.360) +2022-11-14 17:12:33,793 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0723) Prec@1 89.000 (88.368) Prec@5 100.000 (99.368) +2022-11-14 17:12:33,800 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0721) Prec@1 90.000 (88.390) Prec@5 100.000 (99.377) +2022-11-14 17:12:33,808 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0924 (0.0724) Prec@1 86.000 (88.359) Prec@5 97.000 (99.346) +2022-11-14 17:12:33,816 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0683 (0.0723) Prec@1 91.000 (88.392) Prec@5 99.000 (99.342) +2022-11-14 17:12:33,824 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0621 (0.0722) Prec@1 91.000 (88.425) Prec@5 100.000 (99.350) +2022-11-14 17:12:33,831 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0722) Prec@1 89.000 (88.432) Prec@5 99.000 (99.346) +2022-11-14 17:12:33,839 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0812 (0.0723) Prec@1 85.000 (88.390) Prec@5 100.000 (99.354) +2022-11-14 17:12:33,847 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0726) Prec@1 84.000 (88.337) Prec@5 99.000 (99.349) +2022-11-14 17:12:33,855 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0726 (0.0726) Prec@1 87.000 (88.321) Prec@5 100.000 (99.357) +2022-11-14 17:12:33,862 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0728) Prec@1 87.000 (88.306) Prec@5 99.000 (99.353) +2022-11-14 17:12:33,870 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0730) Prec@1 88.000 (88.302) Prec@5 99.000 (99.349) +2022-11-14 17:12:33,878 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0673 (0.0730) Prec@1 88.000 (88.299) Prec@5 100.000 (99.356) +2022-11-14 17:12:33,889 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0729) Prec@1 90.000 (88.318) Prec@5 99.000 (99.352) +2022-11-14 17:12:33,897 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0728) Prec@1 89.000 (88.326) Prec@5 100.000 (99.360) +2022-11-14 17:12:33,905 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0729) Prec@1 88.000 (88.322) Prec@5 99.000 (99.356) +2022-11-14 17:12:33,913 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0726) Prec@1 91.000 (88.352) Prec@5 99.000 (99.352) +2022-11-14 17:12:33,920 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0725) Prec@1 91.000 (88.380) Prec@5 99.000 (99.348) +2022-11-14 17:12:33,928 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0817 (0.0726) Prec@1 87.000 (88.366) Prec@5 100.000 (99.355) +2022-11-14 17:12:33,936 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0726) Prec@1 88.000 (88.362) Prec@5 99.000 (99.351) +2022-11-14 17:12:33,943 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0858 (0.0727) Prec@1 88.000 (88.358) Prec@5 97.000 (99.326) +2022-11-14 17:12:33,951 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0727) Prec@1 91.000 (88.385) Prec@5 97.000 (99.302) +2022-11-14 17:12:33,958 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0481 (0.0724) Prec@1 92.000 (88.423) Prec@5 99.000 (99.299) +2022-11-14 17:12:33,965 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0726) Prec@1 86.000 (88.398) Prec@5 99.000 (99.296) +2022-11-14 17:12:33,973 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0728) Prec@1 86.000 (88.374) Prec@5 99.000 (99.293) +2022-11-14 17:12:33,980 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0729) Prec@1 86.000 (88.350) Prec@5 100.000 (99.300) +2022-11-14 17:12:34,050 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:12:34,373 Epoch: [490][0/500] Time 0.021 (0.021) Data 0.243 (0.243) Loss 0.0405 (0.0405) Prec@1 94.000 (94.000) Prec@5 99.000 (99.000) +2022-11-14 17:12:34,564 Epoch: [490][10/500] Time 0.017 (0.017) Data 0.001 (0.023) Loss 0.0204 (0.0304) Prec@1 96.000 (95.000) Prec@5 100.000 (99.500) +2022-11-14 17:12:34,750 Epoch: [490][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0361 (0.0323) Prec@1 95.000 (95.000) Prec@5 100.000 (99.667) +2022-11-14 17:12:34,937 Epoch: [490][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0328 (0.0324) Prec@1 95.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 17:12:35,127 Epoch: [490][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0249 (0.0309) Prec@1 97.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:12:35,313 Epoch: [490][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0326 (0.0312) Prec@1 95.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 17:12:35,501 Epoch: [490][60/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0412 (0.0326) Prec@1 93.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:12:35,687 Epoch: [490][70/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0372 (0.0332) Prec@1 93.000 (94.750) Prec@5 100.000 (99.875) +2022-11-14 17:12:35,875 Epoch: [490][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0166 (0.0314) Prec@1 97.000 (95.000) Prec@5 100.000 (99.889) +2022-11-14 17:12:36,061 Epoch: [490][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0270 (0.0309) Prec@1 96.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 17:12:36,260 Epoch: [490][100/500] Time 0.020 (0.017) Data 0.002 (0.004) Loss 0.0305 (0.0309) Prec@1 94.000 (95.000) Prec@5 99.000 (99.818) +2022-11-14 17:12:36,513 Epoch: [490][110/500] Time 0.024 (0.017) Data 0.001 (0.004) Loss 0.0193 (0.0299) Prec@1 96.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 17:12:36,772 Epoch: [490][120/500] Time 0.024 (0.018) Data 0.002 (0.004) Loss 0.0389 (0.0306) Prec@1 93.000 (94.923) Prec@5 100.000 (99.846) +2022-11-14 17:12:37,031 Epoch: [490][130/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0189 (0.0298) Prec@1 97.000 (95.071) Prec@5 100.000 (99.857) +2022-11-14 17:12:37,296 Epoch: [490][140/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0203 (0.0291) Prec@1 98.000 (95.267) Prec@5 100.000 (99.867) +2022-11-14 17:12:37,556 Epoch: [490][150/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0275 (0.0290) Prec@1 95.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 17:12:37,820 Epoch: [490][160/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0247 (0.0288) Prec@1 96.000 (95.294) Prec@5 100.000 (99.882) +2022-11-14 17:12:38,087 Epoch: [490][170/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0089 (0.0277) Prec@1 100.000 (95.556) Prec@5 100.000 (99.889) +2022-11-14 17:12:38,352 Epoch: [490][180/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0412 (0.0284) Prec@1 94.000 (95.474) Prec@5 99.000 (99.842) +2022-11-14 17:12:38,619 Epoch: [490][190/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0396 (0.0289) Prec@1 93.000 (95.350) Prec@5 100.000 (99.850) +2022-11-14 17:12:38,886 Epoch: [490][200/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0473 (0.0298) Prec@1 93.000 (95.238) Prec@5 100.000 (99.857) +2022-11-14 17:12:39,155 Epoch: [490][210/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0341 (0.0300) Prec@1 95.000 (95.227) Prec@5 99.000 (99.818) +2022-11-14 17:12:39,420 Epoch: [490][220/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0507 (0.0309) Prec@1 92.000 (95.087) Prec@5 100.000 (99.826) +2022-11-14 17:12:39,683 Epoch: [490][230/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0309 (0.0309) Prec@1 95.000 (95.083) Prec@5 100.000 (99.833) +2022-11-14 17:12:39,951 Epoch: [490][240/500] Time 0.026 (0.020) Data 0.002 (0.003) Loss 0.0239 (0.0306) Prec@1 96.000 (95.120) Prec@5 100.000 (99.840) +2022-11-14 17:12:40,216 Epoch: [490][250/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0167 (0.0301) Prec@1 98.000 (95.231) Prec@5 100.000 (99.846) +2022-11-14 17:12:40,470 Epoch: [490][260/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0353 (0.0303) Prec@1 94.000 (95.185) Prec@5 100.000 (99.852) +2022-11-14 17:12:40,729 Epoch: [490][270/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0376 (0.0306) Prec@1 94.000 (95.143) Prec@5 100.000 (99.857) +2022-11-14 17:12:40,989 Epoch: [490][280/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0258 (0.0304) Prec@1 97.000 (95.207) Prec@5 100.000 (99.862) +2022-11-14 17:12:41,258 Epoch: [490][290/500] Time 0.025 (0.021) Data 0.001 (0.002) Loss 0.0273 (0.0303) Prec@1 95.000 (95.200) Prec@5 100.000 (99.867) +2022-11-14 17:12:41,515 Epoch: [490][300/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0505 (0.0309) Prec@1 94.000 (95.161) Prec@5 100.000 (99.871) +2022-11-14 17:12:41,771 Epoch: [490][310/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0374 (0.0311) Prec@1 93.000 (95.094) Prec@5 100.000 (99.875) +2022-11-14 17:12:42,027 Epoch: [490][320/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0478 (0.0316) Prec@1 91.000 (94.970) Prec@5 100.000 (99.879) +2022-11-14 17:12:42,290 Epoch: [490][330/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0587 (0.0324) Prec@1 92.000 (94.882) Prec@5 100.000 (99.882) +2022-11-14 17:12:42,546 Epoch: [490][340/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0201 (0.0321) Prec@1 98.000 (94.971) Prec@5 100.000 (99.886) +2022-11-14 17:12:42,805 Epoch: [490][350/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0174 (0.0317) Prec@1 98.000 (95.056) Prec@5 100.000 (99.889) +2022-11-14 17:12:43,063 Epoch: [490][360/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0359 (0.0318) Prec@1 94.000 (95.027) Prec@5 100.000 (99.892) +2022-11-14 17:12:43,324 Epoch: [490][370/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0338 (0.0318) Prec@1 95.000 (95.026) Prec@5 100.000 (99.895) +2022-11-14 17:12:43,585 Epoch: [490][380/500] Time 0.022 (0.021) Data 0.001 (0.002) Loss 0.0463 (0.0322) Prec@1 92.000 (94.949) Prec@5 100.000 (99.897) +2022-11-14 17:12:43,841 Epoch: [490][390/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0318 (0.0322) Prec@1 95.000 (94.950) Prec@5 100.000 (99.900) +2022-11-14 17:12:44,102 Epoch: [490][400/500] Time 0.026 (0.021) Data 0.001 (0.002) Loss 0.0350 (0.0323) Prec@1 92.000 (94.878) Prec@5 100.000 (99.902) +2022-11-14 17:12:44,357 Epoch: [490][410/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0290 (0.0322) Prec@1 96.000 (94.905) Prec@5 100.000 (99.905) +2022-11-14 17:12:44,613 Epoch: [490][420/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0204 (0.0319) Prec@1 97.000 (94.953) Prec@5 100.000 (99.907) +2022-11-14 17:12:44,874 Epoch: [490][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0221 (0.0317) Prec@1 96.000 (94.977) Prec@5 100.000 (99.909) +2022-11-14 17:12:45,133 Epoch: [490][440/500] Time 0.022 (0.022) Data 0.002 (0.002) Loss 0.0274 (0.0316) Prec@1 97.000 (95.022) Prec@5 100.000 (99.911) +2022-11-14 17:12:45,390 Epoch: [490][450/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0282 (0.0315) Prec@1 96.000 (95.043) Prec@5 100.000 (99.913) +2022-11-14 17:12:45,650 Epoch: [490][460/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0324 (0.0315) Prec@1 93.000 (95.000) Prec@5 100.000 (99.915) +2022-11-14 17:12:45,907 Epoch: [490][470/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0091 (0.0311) Prec@1 99.000 (95.083) Prec@5 100.000 (99.917) +2022-11-14 17:12:46,164 Epoch: [490][480/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0236 (0.0309) Prec@1 95.000 (95.082) Prec@5 100.000 (99.918) +2022-11-14 17:12:46,423 Epoch: [490][490/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0238 (0.0308) Prec@1 97.000 (95.120) Prec@5 100.000 (99.920) +2022-11-14 17:12:46,655 Epoch: [490][499/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0278 (0.0307) Prec@1 96.000 (95.137) Prec@5 100.000 (99.922) +2022-11-14 17:12:46,964 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0576 (0.0576) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:46,971 Test: [1/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0708 (0.0642) Prec@1 90.000 (90.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:46,978 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0659 (0.0648) Prec@1 89.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:46,990 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0698) Prec@1 87.000 (89.250) Prec@5 99.000 (99.750) +2022-11-14 17:12:46,997 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0741) Prec@1 87.000 (88.800) Prec@5 99.000 (99.600) +2022-11-14 17:12:47,004 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0475 (0.0697) Prec@1 93.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 17:12:47,011 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0677 (0.0694) Prec@1 89.000 (89.429) Prec@5 100.000 (99.714) +2022-11-14 17:12:47,019 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0857 (0.0715) Prec@1 85.000 (88.875) Prec@5 99.000 (99.625) +2022-11-14 17:12:47,027 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1023 (0.0749) Prec@1 85.000 (88.444) Prec@5 100.000 (99.667) +2022-11-14 17:12:47,034 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0626 (0.0737) Prec@1 92.000 (88.800) Prec@5 99.000 (99.600) +2022-11-14 17:12:47,041 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0489 (0.0714) Prec@1 92.000 (89.091) Prec@5 100.000 (99.636) +2022-11-14 17:12:47,049 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0729) Prec@1 86.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 17:12:47,057 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0721) Prec@1 89.000 (88.846) Prec@5 100.000 (99.692) +2022-11-14 17:12:47,065 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0721) Prec@1 89.000 (88.857) Prec@5 99.000 (99.643) +2022-11-14 17:12:47,072 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0786 (0.0725) Prec@1 86.000 (88.667) Prec@5 99.000 (99.600) +2022-11-14 17:12:47,082 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0723) Prec@1 88.000 (88.625) Prec@5 100.000 (99.625) +2022-11-14 17:12:47,089 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0446 (0.0707) Prec@1 93.000 (88.882) Prec@5 98.000 (99.529) +2022-11-14 17:12:47,099 Test: [17/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0720) Prec@1 85.000 (88.667) Prec@5 100.000 (99.556) +2022-11-14 17:12:47,109 Test: [18/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0736) Prec@1 80.000 (88.211) Prec@5 100.000 (99.579) +2022-11-14 17:12:47,116 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0744) Prec@1 86.000 (88.100) Prec@5 97.000 (99.450) +2022-11-14 17:12:47,124 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0907 (0.0752) Prec@1 84.000 (87.905) Prec@5 100.000 (99.476) +2022-11-14 17:12:47,133 Test: [21/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0665 (0.0748) Prec@1 89.000 (87.955) Prec@5 99.000 (99.455) +2022-11-14 17:12:47,142 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0906 (0.0755) Prec@1 87.000 (87.913) Prec@5 99.000 (99.435) +2022-11-14 17:12:47,150 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0755) Prec@1 88.000 (87.917) Prec@5 100.000 (99.458) +2022-11-14 17:12:47,158 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0891 (0.0761) Prec@1 88.000 (87.920) Prec@5 100.000 (99.480) +2022-11-14 17:12:47,165 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1130 (0.0775) Prec@1 83.000 (87.731) Prec@5 96.000 (99.346) +2022-11-14 17:12:47,173 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0778) Prec@1 85.000 (87.630) Prec@5 100.000 (99.370) +2022-11-14 17:12:47,181 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0767) Prec@1 93.000 (87.821) Prec@5 100.000 (99.393) +2022-11-14 17:12:47,188 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0602 (0.0761) Prec@1 90.000 (87.897) Prec@5 99.000 (99.379) +2022-11-14 17:12:47,196 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0562 (0.0755) Prec@1 91.000 (88.000) Prec@5 99.000 (99.367) +2022-11-14 17:12:47,203 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0755) Prec@1 87.000 (87.968) Prec@5 100.000 (99.387) +2022-11-14 17:12:47,211 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0754) Prec@1 88.000 (87.969) Prec@5 99.000 (99.375) +2022-11-14 17:12:47,218 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0759) Prec@1 87.000 (87.939) Prec@5 100.000 (99.394) +2022-11-14 17:12:47,226 Test: [33/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0996 (0.0766) Prec@1 84.000 (87.824) Prec@5 98.000 (99.353) +2022-11-14 17:12:47,233 Test: [34/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0763) Prec@1 91.000 (87.914) Prec@5 98.000 (99.314) +2022-11-14 17:12:47,242 Test: [35/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0761) Prec@1 92.000 (88.028) Prec@5 98.000 (99.278) +2022-11-14 17:12:47,250 Test: [36/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0760) Prec@1 89.000 (88.054) Prec@5 98.000 (99.243) +2022-11-14 17:12:47,257 Test: [37/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0764) Prec@1 86.000 (88.000) Prec@5 99.000 (99.237) +2022-11-14 17:12:47,265 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0759) Prec@1 94.000 (88.154) Prec@5 99.000 (99.231) +2022-11-14 17:12:47,272 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0759) Prec@1 88.000 (88.150) Prec@5 98.000 (99.200) +2022-11-14 17:12:47,280 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1000 (0.0765) Prec@1 87.000 (88.122) Prec@5 99.000 (99.195) +2022-11-14 17:12:47,288 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0764) Prec@1 89.000 (88.143) Prec@5 99.000 (99.190) +2022-11-14 17:12:47,296 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0514 (0.0758) Prec@1 91.000 (88.209) Prec@5 100.000 (99.209) +2022-11-14 17:12:47,303 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0752 (0.0758) Prec@1 88.000 (88.205) Prec@5 98.000 (99.182) +2022-11-14 17:12:47,311 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0580 (0.0754) Prec@1 90.000 (88.244) Prec@5 99.000 (99.178) +2022-11-14 17:12:47,319 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.0761) Prec@1 83.000 (88.130) Prec@5 100.000 (99.196) +2022-11-14 17:12:47,327 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0662 (0.0759) Prec@1 92.000 (88.213) Prec@5 100.000 (99.213) +2022-11-14 17:12:47,334 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0765) Prec@1 82.000 (88.083) Prec@5 98.000 (99.188) +2022-11-14 17:12:47,342 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0640 (0.0763) Prec@1 91.000 (88.143) Prec@5 100.000 (99.204) +2022-11-14 17:12:47,350 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1180 (0.0771) Prec@1 82.000 (88.020) Prec@5 100.000 (99.220) +2022-11-14 17:12:47,358 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0536 (0.0767) Prec@1 94.000 (88.137) Prec@5 99.000 (99.216) +2022-11-14 17:12:47,365 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0771) Prec@1 83.000 (88.038) Prec@5 100.000 (99.231) +2022-11-14 17:12:47,373 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0770) Prec@1 90.000 (88.075) Prec@5 100.000 (99.245) +2022-11-14 17:12:47,380 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0769) Prec@1 89.000 (88.093) Prec@5 100.000 (99.259) +2022-11-14 17:12:47,388 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0769) Prec@1 86.000 (88.055) Prec@5 100.000 (99.273) +2022-11-14 17:12:47,396 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0770) Prec@1 88.000 (88.054) Prec@5 99.000 (99.268) +2022-11-14 17:12:47,404 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0773) Prec@1 84.000 (87.982) Prec@5 100.000 (99.281) +2022-11-14 17:12:47,411 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0773) Prec@1 90.000 (88.017) Prec@5 99.000 (99.276) +2022-11-14 17:12:47,419 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1101 (0.0779) Prec@1 80.000 (87.881) Prec@5 99.000 (99.271) +2022-11-14 17:12:47,427 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0782) Prec@1 85.000 (87.833) Prec@5 99.000 (99.267) +2022-11-14 17:12:47,434 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0782) Prec@1 90.000 (87.869) Prec@5 99.000 (99.262) +2022-11-14 17:12:47,442 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0706 (0.0780) Prec@1 86.000 (87.839) Prec@5 100.000 (99.274) +2022-11-14 17:12:47,450 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0779) Prec@1 89.000 (87.857) Prec@5 100.000 (99.286) +2022-11-14 17:12:47,457 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0379 (0.0773) Prec@1 94.000 (87.953) Prec@5 100.000 (99.297) +2022-11-14 17:12:47,465 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0773) Prec@1 85.000 (87.908) Prec@5 99.000 (99.292) +2022-11-14 17:12:47,472 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0782 (0.0773) Prec@1 88.000 (87.909) Prec@5 99.000 (99.288) +2022-11-14 17:12:47,480 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0337 (0.0767) Prec@1 95.000 (88.015) Prec@5 100.000 (99.299) +2022-11-14 17:12:47,488 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0767) Prec@1 88.000 (88.015) Prec@5 100.000 (99.309) +2022-11-14 17:12:47,495 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0763) Prec@1 92.000 (88.072) Prec@5 99.000 (99.304) +2022-11-14 17:12:47,503 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0763) Prec@1 89.000 (88.086) Prec@5 98.000 (99.286) +2022-11-14 17:12:47,511 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1110 (0.0768) Prec@1 83.000 (88.014) Prec@5 100.000 (99.296) +2022-11-14 17:12:47,519 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0760 (0.0768) Prec@1 86.000 (87.986) Prec@5 100.000 (99.306) +2022-11-14 17:12:47,526 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0358 (0.0763) Prec@1 94.000 (88.068) Prec@5 100.000 (99.315) +2022-11-14 17:12:47,534 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0469 (0.0759) Prec@1 94.000 (88.149) Prec@5 100.000 (99.324) +2022-11-14 17:12:47,541 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0762) Prec@1 85.000 (88.107) Prec@5 99.000 (99.320) +2022-11-14 17:12:47,549 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0532 (0.0759) Prec@1 92.000 (88.158) Prec@5 100.000 (99.329) +2022-11-14 17:12:47,557 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0718 (0.0759) Prec@1 89.000 (88.169) Prec@5 100.000 (99.338) +2022-11-14 17:12:47,564 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1032 (0.0762) Prec@1 85.000 (88.128) Prec@5 97.000 (99.308) +2022-11-14 17:12:47,572 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0761) Prec@1 88.000 (88.127) Prec@5 100.000 (99.316) +2022-11-14 17:12:47,580 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0760) Prec@1 89.000 (88.138) Prec@5 99.000 (99.312) +2022-11-14 17:12:47,589 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0762) Prec@1 88.000 (88.136) Prec@5 100.000 (99.321) +2022-11-14 17:12:47,597 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0961 (0.0764) Prec@1 85.000 (88.098) Prec@5 100.000 (99.329) +2022-11-14 17:12:47,608 Test: [82/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0767) Prec@1 84.000 (88.048) Prec@5 100.000 (99.337) +2022-11-14 17:12:47,620 Test: [83/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0764) Prec@1 92.000 (88.095) Prec@5 100.000 (99.345) +2022-11-14 17:12:47,632 Test: [84/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1105 (0.0768) Prec@1 84.000 (88.047) Prec@5 98.000 (99.329) +2022-11-14 17:12:47,645 Test: [85/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.1254 (0.0774) Prec@1 83.000 (87.988) Prec@5 100.000 (99.337) +2022-11-14 17:12:47,658 Test: [86/100] Model Time 0.010 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0773) Prec@1 88.000 (87.989) Prec@5 99.000 (99.333) +2022-11-14 17:12:47,668 Test: [87/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0773) Prec@1 88.000 (87.989) Prec@5 99.000 (99.330) +2022-11-14 17:12:47,676 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0773) Prec@1 85.000 (87.955) Prec@5 99.000 (99.326) +2022-11-14 17:12:47,684 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0603 (0.0771) Prec@1 91.000 (87.989) Prec@5 100.000 (99.333) +2022-11-14 17:12:47,693 Test: [90/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0526 (0.0769) Prec@1 93.000 (88.044) Prec@5 100.000 (99.341) +2022-11-14 17:12:47,701 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0530 (0.0766) Prec@1 90.000 (88.065) Prec@5 100.000 (99.348) +2022-11-14 17:12:47,709 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0857 (0.0767) Prec@1 86.000 (88.043) Prec@5 100.000 (99.355) +2022-11-14 17:12:47,716 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0766) Prec@1 88.000 (88.043) Prec@5 98.000 (99.340) +2022-11-14 17:12:47,724 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0941 (0.0768) Prec@1 85.000 (88.011) Prec@5 98.000 (99.326) +2022-11-14 17:12:47,731 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0805 (0.0769) Prec@1 88.000 (88.010) Prec@5 97.000 (99.302) +2022-11-14 17:12:47,738 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0488 (0.0766) Prec@1 91.000 (88.041) Prec@5 99.000 (99.299) +2022-11-14 17:12:47,746 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0889 (0.0767) Prec@1 84.000 (88.000) Prec@5 98.000 (99.286) +2022-11-14 17:12:47,753 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0769) Prec@1 85.000 (87.970) Prec@5 99.000 (99.283) +2022-11-14 17:12:47,760 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0769) Prec@1 87.000 (87.960) Prec@5 99.000 (99.280) +2022-11-14 17:12:47,827 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:12:48,152 Epoch: [491][0/500] Time 0.022 (0.022) Data 0.246 (0.246) Loss 0.0200 (0.0200) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:48,349 Epoch: [491][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0275 (0.0238) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:12:48,537 Epoch: [491][20/500] Time 0.017 (0.017) Data 0.002 (0.013) Loss 0.0409 (0.0295) Prec@1 94.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:12:48,729 Epoch: [491][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0238 (0.0281) Prec@1 96.000 (95.500) Prec@5 100.000 (100.000) +2022-11-14 17:12:48,920 Epoch: [491][40/500] Time 0.019 (0.017) Data 0.001 (0.008) Loss 0.0314 (0.0287) Prec@1 95.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:12:49,114 Epoch: [491][50/500] Time 0.019 (0.017) Data 0.002 (0.006) Loss 0.0171 (0.0268) Prec@1 97.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:49,312 Epoch: [491][60/500] Time 0.018 (0.017) Data 0.001 (0.006) Loss 0.0305 (0.0273) Prec@1 95.000 (95.571) Prec@5 100.000 (100.000) +2022-11-14 17:12:49,503 Epoch: [491][70/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0186 (0.0262) Prec@1 97.000 (95.750) Prec@5 100.000 (100.000) +2022-11-14 17:12:49,757 Epoch: [491][80/500] Time 0.026 (0.018) Data 0.001 (0.005) Loss 0.0391 (0.0277) Prec@1 93.000 (95.444) Prec@5 100.000 (100.000) +2022-11-14 17:12:50,036 Epoch: [491][90/500] Time 0.026 (0.018) Data 0.002 (0.004) Loss 0.0344 (0.0283) Prec@1 94.000 (95.300) Prec@5 100.000 (100.000) +2022-11-14 17:12:50,318 Epoch: [491][100/500] Time 0.025 (0.019) Data 0.001 (0.004) Loss 0.0158 (0.0272) Prec@1 97.000 (95.455) Prec@5 100.000 (100.000) +2022-11-14 17:12:50,597 Epoch: [491][110/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0199 (0.0266) Prec@1 98.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:12:50,878 Epoch: [491][120/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0445 (0.0280) Prec@1 92.000 (95.385) Prec@5 99.000 (99.923) +2022-11-14 17:12:51,159 Epoch: [491][130/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0247 (0.0277) Prec@1 96.000 (95.429) Prec@5 100.000 (99.929) +2022-11-14 17:12:51,432 Epoch: [491][140/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0081 (0.0264) Prec@1 99.000 (95.667) Prec@5 100.000 (99.933) +2022-11-14 17:12:51,717 Epoch: [491][150/500] Time 0.027 (0.021) Data 0.002 (0.003) Loss 0.0260 (0.0264) Prec@1 94.000 (95.562) Prec@5 100.000 (99.938) +2022-11-14 17:12:51,999 Epoch: [491][160/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0362 (0.0270) Prec@1 94.000 (95.471) Prec@5 99.000 (99.882) +2022-11-14 17:12:52,269 Epoch: [491][170/500] Time 0.025 (0.021) Data 0.001 (0.003) Loss 0.0237 (0.0268) Prec@1 95.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 17:12:52,543 Epoch: [491][180/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0295 (0.0269) Prec@1 94.000 (95.368) Prec@5 100.000 (99.895) +2022-11-14 17:12:52,824 Epoch: [491][190/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0291 (0.0270) Prec@1 96.000 (95.400) Prec@5 100.000 (99.900) +2022-11-14 17:12:53,104 Epoch: [491][200/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0289 (0.0271) Prec@1 94.000 (95.333) Prec@5 99.000 (99.857) +2022-11-14 17:12:53,379 Epoch: [491][210/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0286 (0.0272) Prec@1 96.000 (95.364) Prec@5 100.000 (99.864) +2022-11-14 17:12:53,649 Epoch: [491][220/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0176 (0.0268) Prec@1 98.000 (95.478) Prec@5 100.000 (99.870) +2022-11-14 17:12:53,923 Epoch: [491][230/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0398 (0.0273) Prec@1 91.000 (95.292) Prec@5 100.000 (99.875) +2022-11-14 17:12:54,205 Epoch: [491][240/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0594 (0.0286) Prec@1 91.000 (95.120) Prec@5 99.000 (99.840) +2022-11-14 17:12:54,484 Epoch: [491][250/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0335 (0.0288) Prec@1 95.000 (95.115) Prec@5 100.000 (99.846) +2022-11-14 17:12:54,754 Epoch: [491][260/500] Time 0.026 (0.022) Data 0.001 (0.003) Loss 0.0313 (0.0289) Prec@1 97.000 (95.185) Prec@5 100.000 (99.852) +2022-11-14 17:12:55,029 Epoch: [491][270/500] Time 0.025 (0.022) Data 0.001 (0.003) Loss 0.0385 (0.0292) Prec@1 93.000 (95.107) Prec@5 99.000 (99.821) +2022-11-14 17:12:55,308 Epoch: [491][280/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0163 (0.0288) Prec@1 97.000 (95.172) Prec@5 100.000 (99.828) +2022-11-14 17:12:55,580 Epoch: [491][290/500] Time 0.027 (0.023) Data 0.002 (0.003) Loss 0.0444 (0.0293) Prec@1 93.000 (95.100) Prec@5 100.000 (99.833) +2022-11-14 17:12:55,858 Epoch: [491][300/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0367 (0.0295) Prec@1 94.000 (95.065) Prec@5 99.000 (99.806) +2022-11-14 17:12:56,134 Epoch: [491][310/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0265 (0.0295) Prec@1 97.000 (95.125) Prec@5 100.000 (99.812) +2022-11-14 17:12:56,408 Epoch: [491][320/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0212 (0.0292) Prec@1 97.000 (95.182) Prec@5 100.000 (99.818) +2022-11-14 17:12:56,690 Epoch: [491][330/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0191 (0.0289) Prec@1 97.000 (95.235) Prec@5 100.000 (99.824) +2022-11-14 17:12:56,964 Epoch: [491][340/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0157 (0.0285) Prec@1 98.000 (95.314) Prec@5 100.000 (99.829) +2022-11-14 17:12:57,238 Epoch: [491][350/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0341 (0.0287) Prec@1 93.000 (95.250) Prec@5 100.000 (99.833) +2022-11-14 17:12:57,506 Epoch: [491][360/500] Time 0.023 (0.023) Data 0.002 (0.002) Loss 0.0362 (0.0289) Prec@1 94.000 (95.216) Prec@5 100.000 (99.838) +2022-11-14 17:12:57,780 Epoch: [491][370/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0157 (0.0285) Prec@1 99.000 (95.316) Prec@5 100.000 (99.842) +2022-11-14 17:12:58,052 Epoch: [491][380/500] Time 0.025 (0.023) Data 0.001 (0.002) Loss 0.0176 (0.0283) Prec@1 97.000 (95.359) Prec@5 100.000 (99.846) +2022-11-14 17:12:58,322 Epoch: [491][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0312 (0.0283) Prec@1 94.000 (95.325) Prec@5 100.000 (99.850) +2022-11-14 17:12:58,595 Epoch: [491][400/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0368 (0.0285) Prec@1 94.000 (95.293) Prec@5 100.000 (99.854) +2022-11-14 17:12:58,870 Epoch: [491][410/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0342 (0.0287) Prec@1 95.000 (95.286) Prec@5 99.000 (99.833) +2022-11-14 17:12:59,141 Epoch: [491][420/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0360 (0.0289) Prec@1 95.000 (95.279) Prec@5 100.000 (99.837) +2022-11-14 17:12:59,415 Epoch: [491][430/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0262 (0.0288) Prec@1 95.000 (95.273) Prec@5 100.000 (99.841) +2022-11-14 17:12:59,687 Epoch: [491][440/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0394 (0.0290) Prec@1 94.000 (95.244) Prec@5 100.000 (99.844) +2022-11-14 17:12:59,959 Epoch: [491][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0389 (0.0292) Prec@1 93.000 (95.196) Prec@5 100.000 (99.848) +2022-11-14 17:13:00,232 Epoch: [491][460/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0260 (0.0292) Prec@1 96.000 (95.213) Prec@5 100.000 (99.851) +2022-11-14 17:13:00,503 Epoch: [491][470/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0358 (0.0293) Prec@1 92.000 (95.146) Prec@5 100.000 (99.854) +2022-11-14 17:13:00,774 Epoch: [491][480/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0120 (0.0290) Prec@1 99.000 (95.224) Prec@5 100.000 (99.857) +2022-11-14 17:13:01,044 Epoch: [491][490/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0255 (0.0289) Prec@1 95.000 (95.220) Prec@5 100.000 (99.860) +2022-11-14 17:13:01,293 Epoch: [491][499/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0443 (0.0292) Prec@1 94.000 (95.196) Prec@5 98.000 (99.824) +2022-11-14 17:13:01,591 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0560 (0.0560) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 17:13:01,600 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0711 (0.0636) Prec@1 88.000 (88.000) Prec@5 99.000 (99.000) +2022-11-14 17:13:01,607 Test: [2/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0667) Prec@1 86.000 (87.333) Prec@5 100.000 (99.333) +2022-11-14 17:13:01,617 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0841 (0.0710) Prec@1 86.000 (87.000) Prec@5 99.000 (99.250) +2022-11-14 17:13:01,624 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0642 (0.0697) Prec@1 90.000 (87.600) Prec@5 99.000 (99.200) +2022-11-14 17:13:01,631 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0331 (0.0636) Prec@1 94.000 (88.667) Prec@5 100.000 (99.333) +2022-11-14 17:13:01,638 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0626) Prec@1 91.000 (89.000) Prec@5 100.000 (99.429) +2022-11-14 17:13:01,646 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0649) Prec@1 86.000 (88.625) Prec@5 99.000 (99.375) +2022-11-14 17:13:01,653 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0714 (0.0656) Prec@1 89.000 (88.667) Prec@5 99.000 (99.333) +2022-11-14 17:13:01,660 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0816 (0.0672) Prec@1 87.000 (88.500) Prec@5 99.000 (99.300) +2022-11-14 17:13:01,667 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0664) Prec@1 90.000 (88.636) Prec@5 100.000 (99.364) +2022-11-14 17:13:01,675 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0671) Prec@1 88.000 (88.583) Prec@5 100.000 (99.417) +2022-11-14 17:13:01,682 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0664) Prec@1 91.000 (88.769) Prec@5 99.000 (99.385) +2022-11-14 17:13:01,690 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0671) Prec@1 90.000 (88.857) Prec@5 99.000 (99.357) +2022-11-14 17:13:01,698 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0674) Prec@1 89.000 (88.867) Prec@5 98.000 (99.267) +2022-11-14 17:13:01,705 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0684 (0.0674) Prec@1 89.000 (88.875) Prec@5 100.000 (99.312) +2022-11-14 17:13:01,713 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0671) Prec@1 89.000 (88.882) Prec@5 99.000 (99.294) +2022-11-14 17:13:01,720 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1141 (0.0697) Prec@1 82.000 (88.500) Prec@5 99.000 (99.278) +2022-11-14 17:13:01,728 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0702) Prec@1 88.000 (88.474) Prec@5 99.000 (99.263) +2022-11-14 17:13:01,736 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1174 (0.0725) Prec@1 80.000 (88.050) Prec@5 98.000 (99.200) +2022-11-14 17:13:01,743 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0722) Prec@1 87.000 (88.000) Prec@5 100.000 (99.238) +2022-11-14 17:13:01,750 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0722) Prec@1 90.000 (88.091) Prec@5 98.000 (99.182) +2022-11-14 17:13:01,758 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0732) Prec@1 86.000 (88.000) Prec@5 98.000 (99.130) +2022-11-14 17:13:01,765 Test: [23/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0733) Prec@1 89.000 (88.042) Prec@5 100.000 (99.167) +2022-11-14 17:13:01,772 Test: [24/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0892 (0.0739) Prec@1 88.000 (88.040) Prec@5 98.000 (99.120) +2022-11-14 17:13:01,780 Test: [25/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0885 (0.0744) Prec@1 86.000 (87.962) Prec@5 99.000 (99.115) +2022-11-14 17:13:01,788 Test: [26/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0540 (0.0737) Prec@1 91.000 (88.074) Prec@5 100.000 (99.148) +2022-11-14 17:13:01,795 Test: [27/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0483 (0.0728) Prec@1 93.000 (88.250) Prec@5 99.000 (99.143) +2022-11-14 17:13:01,803 Test: [28/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0726) Prec@1 88.000 (88.241) Prec@5 99.000 (99.138) +2022-11-14 17:13:01,810 Test: [29/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0756 (0.0727) Prec@1 86.000 (88.167) Prec@5 99.000 (99.133) +2022-11-14 17:13:01,818 Test: [30/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0707 (0.0726) Prec@1 90.000 (88.226) Prec@5 100.000 (99.161) +2022-11-14 17:13:01,825 Test: [31/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0727) Prec@1 89.000 (88.250) Prec@5 98.000 (99.125) +2022-11-14 17:13:01,833 Test: [32/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0845 (0.0730) Prec@1 86.000 (88.182) Prec@5 100.000 (99.152) +2022-11-14 17:13:01,840 Test: [33/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0912 (0.0736) Prec@1 84.000 (88.059) Prec@5 98.000 (99.118) +2022-11-14 17:13:01,848 Test: [34/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0910 (0.0741) Prec@1 83.000 (87.914) Prec@5 98.000 (99.086) +2022-11-14 17:13:01,855 Test: [35/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0643 (0.0738) Prec@1 90.000 (87.972) Prec@5 99.000 (99.083) +2022-11-14 17:13:01,862 Test: [36/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0828 (0.0740) Prec@1 87.000 (87.946) Prec@5 97.000 (99.027) +2022-11-14 17:13:01,870 Test: [37/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0743) Prec@1 87.000 (87.921) Prec@5 99.000 (99.026) +2022-11-14 17:13:01,877 Test: [38/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0542 (0.0738) Prec@1 93.000 (88.051) Prec@5 99.000 (99.026) +2022-11-14 17:13:01,885 Test: [39/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0703 (0.0737) Prec@1 90.000 (88.100) Prec@5 98.000 (99.000) +2022-11-14 17:13:01,893 Test: [40/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0961 (0.0743) Prec@1 86.000 (88.049) Prec@5 100.000 (99.024) +2022-11-14 17:13:01,900 Test: [41/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0749 (0.0743) Prec@1 88.000 (88.048) Prec@5 98.000 (99.000) +2022-11-14 17:13:01,908 Test: [42/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0677 (0.0741) Prec@1 91.000 (88.116) Prec@5 100.000 (99.023) +2022-11-14 17:13:01,915 Test: [43/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0615 (0.0738) Prec@1 93.000 (88.227) Prec@5 98.000 (99.000) +2022-11-14 17:13:01,923 Test: [44/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0596 (0.0735) Prec@1 89.000 (88.244) Prec@5 100.000 (99.022) +2022-11-14 17:13:01,931 Test: [45/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1098 (0.0743) Prec@1 83.000 (88.130) Prec@5 99.000 (99.022) +2022-11-14 17:13:01,938 Test: [46/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0639 (0.0741) Prec@1 90.000 (88.170) Prec@5 100.000 (99.043) +2022-11-14 17:13:01,945 Test: [47/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0858 (0.0743) Prec@1 85.000 (88.104) Prec@5 98.000 (99.021) +2022-11-14 17:13:01,953 Test: [48/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0612 (0.0741) Prec@1 90.000 (88.143) Prec@5 100.000 (99.041) +2022-11-14 17:13:01,960 Test: [49/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0998 (0.0746) Prec@1 86.000 (88.100) Prec@5 99.000 (99.040) +2022-11-14 17:13:01,968 Test: [50/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0692 (0.0745) Prec@1 86.000 (88.059) Prec@5 100.000 (99.059) +2022-11-14 17:13:01,976 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0695 (0.0744) Prec@1 92.000 (88.135) Prec@5 100.000 (99.077) +2022-11-14 17:13:01,983 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0701 (0.0743) Prec@1 88.000 (88.132) Prec@5 100.000 (99.094) +2022-11-14 17:13:01,991 Test: 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0.0641 (0.0751) Prec@1 89.000 (88.067) Prec@5 100.000 (99.133) +2022-11-14 17:13:02,043 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0770 (0.0751) Prec@1 89.000 (88.082) Prec@5 98.000 (99.115) +2022-11-14 17:13:02,051 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0805 (0.0752) Prec@1 86.000 (88.048) Prec@5 99.000 (99.113) +2022-11-14 17:13:02,059 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0562 (0.0749) Prec@1 91.000 (88.095) Prec@5 99.000 (99.111) +2022-11-14 17:13:02,067 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0480 (0.0745) Prec@1 92.000 (88.156) Prec@5 100.000 (99.125) +2022-11-14 17:13:02,075 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0817 (0.0746) Prec@1 88.000 (88.154) Prec@5 100.000 (99.138) +2022-11-14 17:13:02,084 Test: [65/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0726 (0.0746) Prec@1 86.000 (88.121) Prec@5 99.000 (99.136) +2022-11-14 17:13:02,092 Test: [66/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0369 (0.0740) Prec@1 94.000 (88.209) Prec@5 100.000 (99.149) +2022-11-14 17:13:02,100 Test: [67/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0699 (0.0739) Prec@1 89.000 (88.221) Prec@5 100.000 (99.162) +2022-11-14 17:13:02,108 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0679 (0.0739) Prec@1 89.000 (88.232) Prec@5 98.000 (99.145) +2022-11-14 17:13:02,115 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0752 (0.0739) Prec@1 88.000 (88.229) Prec@5 99.000 (99.143) +2022-11-14 17:13:02,123 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1070 (0.0743) Prec@1 83.000 (88.155) Prec@5 99.000 (99.141) +2022-11-14 17:13:02,131 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0503 (0.0740) Prec@1 91.000 (88.194) Prec@5 100.000 (99.153) +2022-11-14 17:13:02,138 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0735 (0.0740) Prec@1 89.000 (88.205) Prec@5 99.000 (99.151) +2022-11-14 17:13:02,146 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0555 (0.0738) Prec@1 93.000 (88.270) Prec@5 100.000 (99.162) +2022-11-14 17:13:02,153 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0926 (0.0740) Prec@1 85.000 (88.227) Prec@5 99.000 (99.160) +2022-11-14 17:13:02,161 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0573 (0.0738) Prec@1 92.000 (88.276) Prec@5 100.000 (99.171) +2022-11-14 17:13:02,169 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0830 (0.0739) Prec@1 85.000 (88.234) Prec@5 98.000 (99.156) +2022-11-14 17:13:02,176 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0853 (0.0740) Prec@1 87.000 (88.218) Prec@5 98.000 (99.141) +2022-11-14 17:13:02,184 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0726 (0.0740) Prec@1 88.000 (88.215) Prec@5 100.000 (99.152) +2022-11-14 17:13:02,192 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0737 (0.0740) Prec@1 87.000 (88.200) Prec@5 99.000 (99.150) +2022-11-14 17:13:02,199 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0794 (0.0741) Prec@1 88.000 (88.198) Prec@5 98.000 (99.136) +2022-11-14 17:13:02,207 Test: [81/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0860 (0.0742) Prec@1 87.000 (88.183) Prec@5 99.000 (99.134) +2022-11-14 17:13:02,215 Test: [82/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1028 (0.0746) Prec@1 82.000 (88.108) Prec@5 100.000 (99.145) +2022-11-14 17:13:02,222 Test: [83/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0641 (0.0745) Prec@1 89.000 (88.119) Prec@5 100.000 (99.155) +2022-11-14 17:13:02,230 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1023 (0.0748) Prec@1 82.000 (88.047) Prec@5 100.000 (99.165) +2022-11-14 17:13:02,237 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1021 (0.0751) Prec@1 83.000 (87.988) Prec@5 100.000 (99.174) +2022-11-14 17:13:02,245 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0850 (0.0752) Prec@1 87.000 (87.977) Prec@5 98.000 (99.161) +2022-11-14 17:13:02,253 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0788 (0.0753) Prec@1 87.000 (87.966) Prec@5 99.000 (99.159) +2022-11-14 17:13:02,260 Test: [88/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0770 (0.0753) Prec@1 88.000 (87.966) Prec@5 100.000 (99.169) +2022-11-14 17:13:02,268 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0780 (0.0753) Prec@1 88.000 (87.967) Prec@5 98.000 (99.156) +2022-11-14 17:13:02,275 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0710 (0.0753) Prec@1 89.000 (87.978) Prec@5 100.000 (99.165) +2022-11-14 17:13:02,283 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0632 (0.0751) Prec@1 90.000 (88.000) Prec@5 100.000 (99.174) +2022-11-14 17:13:02,291 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0732 (0.0751) Prec@1 88.000 (88.000) Prec@5 100.000 (99.183) +2022-11-14 17:13:02,298 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0738 (0.0751) Prec@1 89.000 (88.011) Prec@5 99.000 (99.181) +2022-11-14 17:13:02,306 Test: [94/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0919 (0.0753) Prec@1 86.000 (87.989) Prec@5 100.000 (99.189) +2022-11-14 17:13:02,313 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0676 (0.0752) Prec@1 91.000 (88.021) Prec@5 99.000 (99.188) +2022-11-14 17:13:02,321 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0478 (0.0749) Prec@1 91.000 (88.052) Prec@5 98.000 (99.175) +2022-11-14 17:13:02,328 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1022 (0.0752) Prec@1 83.000 (88.000) Prec@5 98.000 (99.163) +2022-11-14 17:13:02,336 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0989 (0.0754) Prec@1 88.000 (88.000) Prec@5 99.000 (99.162) +2022-11-14 17:13:02,343 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0782 (0.0755) Prec@1 89.000 (88.010) Prec@5 100.000 (99.170) +2022-11-14 17:13:02,397 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:13:02,720 Epoch: [492][0/500] Time 0.024 (0.024) Data 0.243 (0.243) Loss 0.0384 (0.0384) Prec@1 94.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:02,920 Epoch: [492][10/500] Time 0.017 (0.018) Data 0.001 (0.024) Loss 0.0224 (0.0304) Prec@1 95.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:13:03,109 Epoch: [492][20/500] Time 0.019 (0.017) Data 0.002 (0.013) Loss 0.0280 (0.0296) Prec@1 95.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:13:03,298 Epoch: [492][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0520 (0.0352) Prec@1 91.000 (93.750) Prec@5 98.000 (99.500) +2022-11-14 17:13:03,483 Epoch: [492][40/500] Time 0.017 (0.017) Data 0.001 (0.007) Loss 0.0229 (0.0327) Prec@1 96.000 (94.200) Prec@5 100.000 (99.600) +2022-11-14 17:13:03,670 Epoch: [492][50/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0270 (0.0318) Prec@1 97.000 (94.667) Prec@5 100.000 (99.667) +2022-11-14 17:13:03,857 Epoch: [492][60/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0271 (0.0311) Prec@1 95.000 (94.714) Prec@5 100.000 (99.714) +2022-11-14 17:13:04,047 Epoch: [492][70/500] Time 0.018 (0.017) Data 0.001 (0.005) Loss 0.0335 (0.0314) Prec@1 94.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 17:13:04,237 Epoch: [492][80/500] Time 0.016 (0.017) Data 0.002 (0.005) Loss 0.0100 (0.0290) Prec@1 99.000 (95.111) Prec@5 100.000 (99.778) +2022-11-14 17:13:04,424 Epoch: [492][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0175 (0.0279) Prec@1 98.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:13:04,611 Epoch: [492][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0282 (0.0279) Prec@1 96.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 17:13:04,798 Epoch: [492][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0366 (0.0286) Prec@1 94.000 (95.333) Prec@5 100.000 (99.833) +2022-11-14 17:13:04,988 Epoch: [492][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0310 (0.0288) Prec@1 93.000 (95.154) Prec@5 100.000 (99.846) +2022-11-14 17:13:05,199 Epoch: [492][130/500] Time 0.022 (0.017) Data 0.001 (0.003) Loss 0.0676 (0.0316) Prec@1 89.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 17:13:05,447 Epoch: [492][140/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0249 (0.0312) Prec@1 96.000 (94.800) Prec@5 100.000 (99.867) +2022-11-14 17:13:05,697 Epoch: [492][150/500] Time 0.025 (0.018) Data 0.001 (0.003) Loss 0.0164 (0.0302) Prec@1 97.000 (94.938) Prec@5 100.000 (99.875) +2022-11-14 17:13:05,951 Epoch: [492][160/500] Time 0.027 (0.018) Data 0.001 (0.003) Loss 0.0215 (0.0297) Prec@1 97.000 (95.059) Prec@5 100.000 (99.882) +2022-11-14 17:13:06,203 Epoch: [492][170/500] Time 0.023 (0.018) Data 0.002 (0.003) Loss 0.0196 (0.0292) Prec@1 97.000 (95.167) Prec@5 100.000 (99.889) +2022-11-14 17:13:06,460 Epoch: [492][180/500] Time 0.022 (0.018) Data 0.002 (0.003) Loss 0.0090 (0.0281) Prec@1 98.000 (95.316) Prec@5 100.000 (99.895) +2022-11-14 17:13:06,717 Epoch: [492][190/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0433 (0.0289) Prec@1 91.000 (95.100) Prec@5 100.000 (99.900) +2022-11-14 17:13:06,979 Epoch: [492][200/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0211 (0.0285) Prec@1 96.000 (95.143) Prec@5 100.000 (99.905) +2022-11-14 17:13:07,233 Epoch: [492][210/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0262 (0.0284) Prec@1 96.000 (95.182) Prec@5 100.000 (99.909) +2022-11-14 17:13:07,492 Epoch: [492][220/500] Time 0.025 (0.019) Data 0.001 (0.003) Loss 0.0388 (0.0288) Prec@1 95.000 (95.174) Prec@5 99.000 (99.870) +2022-11-14 17:13:07,748 Epoch: [492][230/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0330 (0.0290) Prec@1 94.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 17:13:08,004 Epoch: [492][240/500] Time 0.024 (0.019) Data 0.001 (0.003) Loss 0.0252 (0.0289) Prec@1 96.000 (95.160) Prec@5 100.000 (99.880) +2022-11-14 17:13:08,262 Epoch: [492][250/500] Time 0.024 (0.020) Data 0.001 (0.003) Loss 0.0200 (0.0285) Prec@1 97.000 (95.231) Prec@5 100.000 (99.885) +2022-11-14 17:13:08,523 Epoch: [492][260/500] Time 0.022 (0.020) Data 0.001 (0.003) Loss 0.0417 (0.0290) Prec@1 92.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 17:13:08,780 Epoch: [492][270/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0301 (0.0290) Prec@1 97.000 (95.179) Prec@5 100.000 (99.893) +2022-11-14 17:13:09,038 Epoch: [492][280/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0183 (0.0287) Prec@1 98.000 (95.276) Prec@5 100.000 (99.897) +2022-11-14 17:13:09,295 Epoch: [492][290/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0381 (0.0290) Prec@1 92.000 (95.167) Prec@5 100.000 (99.900) +2022-11-14 17:13:09,552 Epoch: [492][300/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0196 (0.0287) Prec@1 97.000 (95.226) Prec@5 100.000 (99.903) +2022-11-14 17:13:09,810 Epoch: [492][310/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0228 (0.0285) Prec@1 97.000 (95.281) Prec@5 100.000 (99.906) +2022-11-14 17:13:10,070 Epoch: [492][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0315 (0.0286) Prec@1 94.000 (95.242) Prec@5 100.000 (99.909) +2022-11-14 17:13:10,327 Epoch: [492][330/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0180 (0.0283) Prec@1 97.000 (95.294) Prec@5 100.000 (99.912) +2022-11-14 17:13:10,584 Epoch: [492][340/500] Time 0.022 (0.020) Data 0.002 (0.002) Loss 0.0196 (0.0280) Prec@1 96.000 (95.314) Prec@5 100.000 (99.914) +2022-11-14 17:13:10,839 Epoch: [492][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0179 (0.0278) Prec@1 97.000 (95.361) Prec@5 98.000 (99.861) +2022-11-14 17:13:11,089 Epoch: [492][360/500] Time 0.021 (0.020) Data 0.001 (0.002) Loss 0.0272 (0.0277) Prec@1 97.000 (95.405) Prec@5 100.000 (99.865) +2022-11-14 17:13:11,334 Epoch: [492][370/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0242 (0.0276) Prec@1 96.000 (95.421) Prec@5 100.000 (99.868) +2022-11-14 17:13:11,581 Epoch: [492][380/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0254 (0.0276) Prec@1 96.000 (95.436) Prec@5 100.000 (99.872) +2022-11-14 17:13:11,830 Epoch: [492][390/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0102 (0.0272) Prec@1 99.000 (95.525) Prec@5 100.000 (99.875) +2022-11-14 17:13:12,086 Epoch: [492][400/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0193 (0.0270) Prec@1 98.000 (95.585) Prec@5 100.000 (99.878) +2022-11-14 17:13:12,330 Epoch: [492][410/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0453 (0.0274) Prec@1 92.000 (95.500) Prec@5 100.000 (99.881) +2022-11-14 17:13:12,577 Epoch: [492][420/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0234 (0.0273) Prec@1 96.000 (95.512) Prec@5 100.000 (99.884) +2022-11-14 17:13:12,827 Epoch: [492][430/500] Time 0.022 (0.021) Data 0.002 (0.002) Loss 0.0241 (0.0272) Prec@1 96.000 (95.523) Prec@5 100.000 (99.886) +2022-11-14 17:13:13,075 Epoch: [492][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0271 (0.0272) Prec@1 96.000 (95.533) Prec@5 100.000 (99.889) +2022-11-14 17:13:13,325 Epoch: [492][450/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0493 (0.0277) Prec@1 93.000 (95.478) Prec@5 100.000 (99.891) +2022-11-14 17:13:13,576 Epoch: [492][460/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0255 (0.0277) Prec@1 95.000 (95.468) Prec@5 100.000 (99.894) +2022-11-14 17:13:13,825 Epoch: [492][470/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0206 (0.0275) Prec@1 97.000 (95.500) Prec@5 100.000 (99.896) +2022-11-14 17:13:14,076 Epoch: [492][480/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0299 (0.0276) Prec@1 95.000 (95.490) Prec@5 100.000 (99.898) +2022-11-14 17:13:14,326 Epoch: [492][490/500] Time 0.024 (0.021) Data 0.001 (0.002) Loss 0.0324 (0.0277) Prec@1 93.000 (95.440) Prec@5 100.000 (99.900) +2022-11-14 17:13:14,551 Epoch: [492][499/500] Time 0.023 (0.021) Data 0.002 (0.002) Loss 0.0287 (0.0277) Prec@1 96.000 (95.451) Prec@5 100.000 (99.902) +2022-11-14 17:13:14,854 Test: [0/100] Model Time 0.012 (0.012) Loss Time 0.000 (0.000) Loss 0.0707 (0.0707) Prec@1 89.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:13:14,863 Test: [1/100] Model Time 0.007 (0.009) Loss Time 0.000 (0.000) Loss 0.0852 (0.0779) Prec@1 86.000 (87.500) Prec@5 100.000 (99.500) +2022-11-14 17:13:14,871 Test: [2/100] Model Time 0.007 (0.008) Loss Time 0.000 (0.000) Loss 0.0800 (0.0786) Prec@1 85.000 (86.667) Prec@5 100.000 (99.667) +2022-11-14 17:13:14,882 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0826 (0.0796) Prec@1 89.000 (87.250) Prec@5 99.000 (99.500) +2022-11-14 17:13:14,889 Test: [4/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0665 (0.0770) Prec@1 90.000 (87.800) Prec@5 99.000 (99.400) +2022-11-14 17:13:14,896 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0400 (0.0708) Prec@1 92.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 17:13:14,903 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0714 (0.0709) Prec@1 90.000 (88.714) Prec@5 99.000 (99.429) +2022-11-14 17:13:14,912 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0847 (0.0726) Prec@1 85.000 (88.250) Prec@5 99.000 (99.375) +2022-11-14 17:13:14,919 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0732) Prec@1 88.000 (88.222) Prec@5 100.000 (99.444) +2022-11-14 17:13:14,926 Test: [9/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0730 (0.0732) Prec@1 89.000 (88.300) Prec@5 97.000 (99.200) +2022-11-14 17:13:14,934 Test: [10/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0496 (0.0710) Prec@1 93.000 (88.727) Prec@5 99.000 (99.182) +2022-11-14 17:13:14,942 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0723) Prec@1 88.000 (88.667) Prec@5 99.000 (99.167) +2022-11-14 17:13:14,949 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0708) Prec@1 91.000 (88.846) Prec@5 100.000 (99.231) +2022-11-14 17:13:14,957 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0598 (0.0700) Prec@1 90.000 (88.929) Prec@5 99.000 (99.214) +2022-11-14 17:13:14,965 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0595 (0.0693) Prec@1 90.000 (89.000) Prec@5 100.000 (99.267) +2022-11-14 17:13:14,973 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0848 (0.0703) Prec@1 87.000 (88.875) Prec@5 100.000 (99.312) +2022-11-14 17:13:14,980 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0394 (0.0685) Prec@1 95.000 (89.235) Prec@5 99.000 (99.294) +2022-11-14 17:13:14,988 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0917 (0.0697) Prec@1 87.000 (89.111) Prec@5 100.000 (99.333) +2022-11-14 17:13:14,996 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0710) Prec@1 82.000 (88.737) Prec@5 99.000 (99.316) +2022-11-14 17:13:15,004 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0807 (0.0715) Prec@1 87.000 (88.650) Prec@5 97.000 (99.200) +2022-11-14 17:13:15,012 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0720) Prec@1 87.000 (88.571) Prec@5 100.000 (99.238) +2022-11-14 17:13:15,019 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0725) Prec@1 86.000 (88.455) Prec@5 99.000 (99.227) +2022-11-14 17:13:15,027 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0951 (0.0735) Prec@1 85.000 (88.304) Prec@5 99.000 (99.217) +2022-11-14 17:13:15,035 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0818 (0.0738) Prec@1 88.000 (88.292) Prec@5 99.000 (99.208) +2022-11-14 17:13:15,042 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0744) Prec@1 85.000 (88.160) Prec@5 100.000 (99.240) +2022-11-14 17:13:15,050 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0749) Prec@1 86.000 (88.077) Prec@5 99.000 (99.231) +2022-11-14 17:13:15,057 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0470 (0.0739) Prec@1 92.000 (88.222) Prec@5 100.000 (99.259) +2022-11-14 17:13:15,065 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0736) Prec@1 91.000 (88.321) Prec@5 100.000 (99.286) +2022-11-14 17:13:15,073 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0733) Prec@1 91.000 (88.414) Prec@5 98.000 (99.241) +2022-11-14 17:13:15,083 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0729) Prec@1 92.000 (88.533) Prec@5 100.000 (99.267) +2022-11-14 17:13:15,091 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0732) Prec@1 85.000 (88.419) Prec@5 99.000 (99.258) +2022-11-14 17:13:15,099 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0728) Prec@1 92.000 (88.531) Prec@5 98.000 (99.219) +2022-11-14 17:13:15,106 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0781 (0.0729) Prec@1 85.000 (88.424) Prec@5 100.000 (99.242) +2022-11-14 17:13:15,114 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0733) Prec@1 84.000 (88.294) Prec@5 99.000 (99.235) +2022-11-14 17:13:15,122 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0886 (0.0738) Prec@1 87.000 (88.257) Prec@5 98.000 (99.200) +2022-11-14 17:13:15,130 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0736) Prec@1 90.000 (88.306) Prec@5 100.000 (99.222) +2022-11-14 17:13:15,138 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0739) Prec@1 85.000 (88.216) Prec@5 99.000 (99.216) +2022-11-14 17:13:15,146 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1084 (0.0749) Prec@1 83.000 (88.079) Prec@5 96.000 (99.132) +2022-11-14 17:13:15,153 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0583 (0.0744) Prec@1 93.000 (88.205) Prec@5 98.000 (99.103) +2022-11-14 17:13:15,161 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0741) Prec@1 91.000 (88.275) Prec@5 99.000 (99.100) +2022-11-14 17:13:15,169 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1142 (0.0750) Prec@1 83.000 (88.146) Prec@5 97.000 (99.049) +2022-11-14 17:13:15,177 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0748) Prec@1 90.000 (88.190) Prec@5 99.000 (99.048) +2022-11-14 17:13:15,185 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0743) Prec@1 92.000 (88.279) Prec@5 99.000 (99.047) +2022-11-14 17:13:15,193 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0744) Prec@1 87.000 (88.250) Prec@5 98.000 (99.023) +2022-11-14 17:13:15,201 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0558 (0.0740) Prec@1 93.000 (88.356) Prec@5 100.000 (99.044) +2022-11-14 17:13:15,208 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0912 (0.0744) Prec@1 87.000 (88.326) Prec@5 97.000 (99.000) +2022-11-14 17:13:15,216 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0742) Prec@1 89.000 (88.340) Prec@5 100.000 (99.021) +2022-11-14 17:13:15,224 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1066 (0.0749) Prec@1 82.000 (88.208) Prec@5 98.000 (99.000) +2022-11-14 17:13:15,231 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0538 (0.0745) Prec@1 93.000 (88.306) Prec@5 99.000 (99.000) +2022-11-14 17:13:15,240 Test: [49/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1043 (0.0751) Prec@1 84.000 (88.220) Prec@5 100.000 (99.020) +2022-11-14 17:13:15,248 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0554 (0.0747) Prec@1 89.000 (88.235) Prec@5 100.000 (99.039) +2022-11-14 17:13:15,256 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0749) Prec@1 87.000 (88.212) Prec@5 99.000 (99.038) +2022-11-14 17:13:15,264 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0745) Prec@1 91.000 (88.264) Prec@5 99.000 (99.038) +2022-11-14 17:13:15,272 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0702 (0.0744) Prec@1 91.000 (88.315) Prec@5 100.000 (99.056) +2022-11-14 17:13:15,280 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0814 (0.0745) Prec@1 85.000 (88.255) Prec@5 100.000 (99.073) +2022-11-14 17:13:15,288 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0744) Prec@1 90.000 (88.286) Prec@5 99.000 (99.071) +2022-11-14 17:13:15,295 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0741) Prec@1 93.000 (88.368) Prec@5 100.000 (99.088) +2022-11-14 17:13:15,303 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0708 (0.0741) Prec@1 90.000 (88.397) Prec@5 100.000 (99.103) +2022-11-14 17:13:15,311 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0743) Prec@1 85.000 (88.339) Prec@5 100.000 (99.119) +2022-11-14 17:13:15,319 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0747) Prec@1 82.000 (88.233) Prec@5 99.000 (99.117) +2022-11-14 17:13:15,327 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0655 (0.0745) Prec@1 91.000 (88.279) Prec@5 98.000 (99.098) +2022-11-14 17:13:15,335 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0744) Prec@1 89.000 (88.290) Prec@5 100.000 (99.113) +2022-11-14 17:13:15,342 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0393 (0.0738) Prec@1 94.000 (88.381) Prec@5 100.000 (99.127) +2022-11-14 17:13:15,350 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0479 (0.0734) Prec@1 91.000 (88.422) Prec@5 100.000 (99.141) +2022-11-14 17:13:15,358 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0737) Prec@1 86.000 (88.385) Prec@5 99.000 (99.138) +2022-11-14 17:13:15,365 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0740 (0.0737) Prec@1 91.000 (88.424) Prec@5 98.000 (99.121) +2022-11-14 17:13:15,373 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0377 (0.0732) Prec@1 94.000 (88.507) Prec@5 100.000 (99.134) +2022-11-14 17:13:15,381 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0730) Prec@1 91.000 (88.544) Prec@5 100.000 (99.147) +2022-11-14 17:13:15,388 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0728) Prec@1 91.000 (88.580) Prec@5 99.000 (99.145) +2022-11-14 17:13:15,396 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0731) Prec@1 88.000 (88.571) Prec@5 99.000 (99.143) +2022-11-14 17:13:15,404 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0732) Prec@1 87.000 (88.549) Prec@5 98.000 (99.127) +2022-11-14 17:13:15,411 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0415 (0.0728) Prec@1 92.000 (88.597) Prec@5 100.000 (99.139) +2022-11-14 17:13:15,419 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0518 (0.0725) Prec@1 90.000 (88.616) Prec@5 100.000 (99.151) +2022-11-14 17:13:15,427 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0725) Prec@1 89.000 (88.622) Prec@5 100.000 (99.162) +2022-11-14 17:13:15,434 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0730) Prec@1 83.000 (88.547) Prec@5 99.000 (99.160) +2022-11-14 17:13:15,442 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0731) Prec@1 89.000 (88.553) Prec@5 100.000 (99.171) +2022-11-14 17:13:15,449 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0709 (0.0730) Prec@1 88.000 (88.545) Prec@5 100.000 (99.182) +2022-11-14 17:13:15,457 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0731) Prec@1 87.000 (88.526) Prec@5 99.000 (99.179) +2022-11-14 17:13:15,465 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0892 (0.0733) Prec@1 86.000 (88.494) Prec@5 99.000 (99.177) +2022-11-14 17:13:15,472 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0731) Prec@1 91.000 (88.525) Prec@5 100.000 (99.188) +2022-11-14 17:13:15,482 Test: [80/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0733) Prec@1 87.000 (88.506) Prec@5 97.000 (99.160) +2022-11-14 17:13:15,491 Test: [81/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1044 (0.0736) Prec@1 84.000 (88.451) Prec@5 100.000 (99.171) +2022-11-14 17:13:15,498 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0863 (0.0738) Prec@1 88.000 (88.446) Prec@5 99.000 (99.169) +2022-11-14 17:13:15,506 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0739) Prec@1 85.000 (88.405) Prec@5 99.000 (99.167) +2022-11-14 17:13:15,515 Test: [84/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0741) Prec@1 87.000 (88.388) Prec@5 100.000 (99.176) +2022-11-14 17:13:15,524 Test: [85/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0986 (0.0744) Prec@1 85.000 (88.349) Prec@5 100.000 (99.186) +2022-11-14 17:13:15,532 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0785 (0.0745) Prec@1 90.000 (88.368) Prec@5 100.000 (99.195) +2022-11-14 17:13:15,540 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0887 (0.0746) Prec@1 86.000 (88.341) Prec@5 99.000 (99.193) +2022-11-14 17:13:15,549 Test: [88/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0668 (0.0745) Prec@1 91.000 (88.371) Prec@5 100.000 (99.202) +2022-11-14 17:13:15,558 Test: [89/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0745) Prec@1 89.000 (88.378) Prec@5 100.000 (99.211) +2022-11-14 17:13:15,566 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0614 (0.0744) Prec@1 90.000 (88.396) Prec@5 99.000 (99.209) +2022-11-14 17:13:15,574 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0607 (0.0742) Prec@1 90.000 (88.413) Prec@5 100.000 (99.217) +2022-11-14 17:13:15,582 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0744) Prec@1 84.000 (88.366) Prec@5 100.000 (99.226) +2022-11-14 17:13:15,589 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0739 (0.0744) Prec@1 88.000 (88.362) Prec@5 99.000 (99.223) +2022-11-14 17:13:15,596 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0744) Prec@1 89.000 (88.368) Prec@5 99.000 (99.221) +2022-11-14 17:13:15,603 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0502 (0.0742) Prec@1 95.000 (88.438) Prec@5 100.000 (99.229) +2022-11-14 17:13:15,610 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0740) Prec@1 91.000 (88.464) Prec@5 99.000 (99.227) +2022-11-14 17:13:15,618 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0916 (0.0742) Prec@1 86.000 (88.439) Prec@5 97.000 (99.204) +2022-11-14 17:13:15,625 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1019 (0.0745) Prec@1 84.000 (88.394) Prec@5 99.000 (99.202) +2022-11-14 17:13:15,632 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0744) Prec@1 89.000 (88.400) Prec@5 100.000 (99.210) +2022-11-14 17:13:15,689 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:13:16,012 Epoch: [493][0/500] Time 0.023 (0.023) Data 0.246 (0.246) Loss 0.0420 (0.0420) Prec@1 92.000 (92.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:16,218 Epoch: [493][10/500] Time 0.017 (0.019) Data 0.002 (0.024) Loss 0.0191 (0.0306) Prec@1 96.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:16,410 Epoch: [493][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0224 (0.0279) Prec@1 96.000 (94.667) Prec@5 100.000 (100.000) +2022-11-14 17:13:16,601 Epoch: [493][30/500] Time 0.017 (0.017) Data 0.002 (0.009) Loss 0.0194 (0.0258) Prec@1 97.000 (95.250) Prec@5 100.000 (100.000) +2022-11-14 17:13:16,792 Epoch: [493][40/500] Time 0.020 (0.017) Data 0.001 (0.008) Loss 0.0327 (0.0271) Prec@1 93.000 (94.800) Prec@5 100.000 (100.000) +2022-11-14 17:13:16,982 Epoch: [493][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0299 (0.0276) Prec@1 96.000 (95.000) Prec@5 99.000 (99.833) +2022-11-14 17:13:17,177 Epoch: [493][60/500] Time 0.020 (0.017) Data 0.001 (0.006) Loss 0.0480 (0.0305) Prec@1 91.000 (94.429) Prec@5 100.000 (99.857) +2022-11-14 17:13:17,452 Epoch: [493][70/500] Time 0.027 (0.018) Data 0.002 (0.005) Loss 0.0211 (0.0293) Prec@1 98.000 (94.875) Prec@5 100.000 (99.875) +2022-11-14 17:13:17,738 Epoch: [493][80/500] Time 0.027 (0.019) Data 0.002 (0.005) Loss 0.0262 (0.0290) Prec@1 97.000 (95.111) Prec@5 100.000 (99.889) +2022-11-14 17:13:18,028 Epoch: [493][90/500] Time 0.027 (0.020) Data 0.002 (0.004) Loss 0.0240 (0.0285) Prec@1 96.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:13:18,313 Epoch: [493][100/500] Time 0.026 (0.020) Data 0.002 (0.004) Loss 0.0179 (0.0275) Prec@1 97.000 (95.364) Prec@5 100.000 (99.909) +2022-11-14 17:13:18,594 Epoch: [493][110/500] Time 0.026 (0.021) Data 0.002 (0.004) Loss 0.0175 (0.0267) Prec@1 97.000 (95.500) Prec@5 100.000 (99.917) +2022-11-14 17:13:18,876 Epoch: [493][120/500] Time 0.027 (0.021) Data 0.002 (0.004) Loss 0.0405 (0.0278) Prec@1 94.000 (95.385) Prec@5 98.000 (99.769) +2022-11-14 17:13:19,160 Epoch: [493][130/500] Time 0.023 (0.021) Data 0.002 (0.004) Loss 0.0180 (0.0271) Prec@1 98.000 (95.571) Prec@5 100.000 (99.786) +2022-11-14 17:13:19,439 Epoch: [493][140/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0344 (0.0275) Prec@1 94.000 (95.467) Prec@5 100.000 (99.800) +2022-11-14 17:13:19,727 Epoch: [493][150/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0326 (0.0279) Prec@1 94.000 (95.375) Prec@5 100.000 (99.812) +2022-11-14 17:13:20,005 Epoch: [493][160/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0169 (0.0272) Prec@1 98.000 (95.529) Prec@5 100.000 (99.824) +2022-11-14 17:13:20,283 Epoch: [493][170/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0311 (0.0274) Prec@1 95.000 (95.500) Prec@5 100.000 (99.833) +2022-11-14 17:13:20,558 Epoch: [493][180/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0326 (0.0277) Prec@1 94.000 (95.421) Prec@5 100.000 (99.842) +2022-11-14 17:13:20,837 Epoch: [493][190/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0109 (0.0269) Prec@1 99.000 (95.600) Prec@5 100.000 (99.850) +2022-11-14 17:13:21,115 Epoch: [493][200/500] Time 0.030 (0.022) Data 0.002 (0.003) Loss 0.0177 (0.0264) Prec@1 98.000 (95.714) Prec@5 99.000 (99.810) +2022-11-14 17:13:21,389 Epoch: [493][210/500] Time 0.026 (0.023) Data 0.001 (0.003) Loss 0.0323 (0.0267) Prec@1 93.000 (95.591) Prec@5 100.000 (99.818) +2022-11-14 17:13:21,661 Epoch: [493][220/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0289 (0.0268) Prec@1 95.000 (95.565) Prec@5 100.000 (99.826) +2022-11-14 17:13:21,933 Epoch: [493][230/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0412 (0.0274) Prec@1 93.000 (95.458) Prec@5 100.000 (99.833) +2022-11-14 17:13:22,210 Epoch: [493][240/500] Time 0.023 (0.023) Data 0.002 (0.003) Loss 0.0324 (0.0276) Prec@1 96.000 (95.480) Prec@5 99.000 (99.800) +2022-11-14 17:13:22,485 Epoch: [493][250/500] Time 0.026 (0.023) Data 0.002 (0.003) Loss 0.0247 (0.0275) Prec@1 96.000 (95.500) Prec@5 100.000 (99.808) +2022-11-14 17:13:22,761 Epoch: [493][260/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0256 (0.0274) Prec@1 96.000 (95.519) Prec@5 99.000 (99.778) +2022-11-14 17:13:23,032 Epoch: [493][270/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0138 (0.0269) Prec@1 98.000 (95.607) Prec@5 100.000 (99.786) +2022-11-14 17:13:23,309 Epoch: [493][280/500] Time 0.022 (0.023) Data 0.002 (0.003) Loss 0.0222 (0.0268) Prec@1 98.000 (95.690) Prec@5 100.000 (99.793) +2022-11-14 17:13:23,585 Epoch: [493][290/500] Time 0.025 (0.023) Data 0.001 (0.003) Loss 0.0201 (0.0265) Prec@1 97.000 (95.733) Prec@5 100.000 (99.800) +2022-11-14 17:13:23,859 Epoch: [493][300/500] Time 0.025 (0.023) Data 0.002 (0.003) Loss 0.0183 (0.0263) Prec@1 97.000 (95.774) Prec@5 100.000 (99.806) +2022-11-14 17:13:24,140 Epoch: [493][310/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0450 (0.0269) Prec@1 92.000 (95.656) Prec@5 100.000 (99.812) +2022-11-14 17:13:24,415 Epoch: [493][320/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0551 (0.0277) Prec@1 89.000 (95.455) Prec@5 100.000 (99.818) +2022-11-14 17:13:24,686 Epoch: [493][330/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0250 (0.0276) Prec@1 95.000 (95.441) Prec@5 100.000 (99.824) +2022-11-14 17:13:24,963 Epoch: [493][340/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0253 (0.0276) Prec@1 96.000 (95.457) Prec@5 99.000 (99.800) +2022-11-14 17:13:25,239 Epoch: [493][350/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0379 (0.0279) Prec@1 94.000 (95.417) Prec@5 100.000 (99.806) +2022-11-14 17:13:25,516 Epoch: [493][360/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0333 (0.0280) Prec@1 93.000 (95.351) Prec@5 100.000 (99.811) +2022-11-14 17:13:25,790 Epoch: [493][370/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0539 (0.0287) Prec@1 92.000 (95.263) Prec@5 100.000 (99.816) +2022-11-14 17:13:26,067 Epoch: [493][380/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0497 (0.0292) Prec@1 90.000 (95.128) Prec@5 99.000 (99.795) +2022-11-14 17:13:26,345 Epoch: [493][390/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0071 (0.0287) Prec@1 100.000 (95.250) Prec@5 100.000 (99.800) +2022-11-14 17:13:26,622 Epoch: [493][400/500] Time 0.023 (0.023) Data 0.001 (0.002) Loss 0.0356 (0.0288) Prec@1 94.000 (95.220) Prec@5 100.000 (99.805) +2022-11-14 17:13:26,899 Epoch: [493][410/500] Time 0.024 (0.023) Data 0.002 (0.002) Loss 0.0189 (0.0286) Prec@1 96.000 (95.238) Prec@5 100.000 (99.810) +2022-11-14 17:13:27,177 Epoch: [493][420/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0185 (0.0284) Prec@1 98.000 (95.302) Prec@5 100.000 (99.814) +2022-11-14 17:13:27,451 Epoch: [493][430/500] Time 0.026 (0.023) Data 0.001 (0.002) Loss 0.0329 (0.0285) Prec@1 94.000 (95.273) Prec@5 100.000 (99.818) +2022-11-14 17:13:27,728 Epoch: [493][440/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0397 (0.0287) Prec@1 93.000 (95.222) Prec@5 100.000 (99.822) +2022-11-14 17:13:28,004 Epoch: [493][450/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0234 (0.0286) Prec@1 97.000 (95.261) Prec@5 100.000 (99.826) +2022-11-14 17:13:28,277 Epoch: [493][460/500] Time 0.022 (0.023) Data 0.002 (0.002) Loss 0.0214 (0.0285) Prec@1 97.000 (95.298) Prec@5 100.000 (99.830) +2022-11-14 17:13:28,554 Epoch: [493][470/500] Time 0.025 (0.023) Data 0.002 (0.002) Loss 0.0340 (0.0286) Prec@1 93.000 (95.250) Prec@5 100.000 (99.833) +2022-11-14 17:13:28,830 Epoch: [493][480/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0132 (0.0283) Prec@1 98.000 (95.306) Prec@5 100.000 (99.837) +2022-11-14 17:13:29,108 Epoch: [493][490/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0307 (0.0283) Prec@1 97.000 (95.340) Prec@5 100.000 (99.840) +2022-11-14 17:13:29,352 Epoch: [493][499/500] Time 0.025 (0.024) Data 0.002 (0.002) Loss 0.0354 (0.0284) Prec@1 94.000 (95.314) Prec@5 100.000 (99.843) +2022-11-14 17:13:29,654 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0688 (0.0688) Prec@1 87.000 (87.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:29,665 Test: [1/100] Model Time 0.009 (0.010) Loss Time 0.000 (0.000) Loss 0.0607 (0.0647) Prec@1 90.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 17:13:29,674 Test: [2/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0571 (0.0622) Prec@1 87.000 (88.000) Prec@5 100.000 (99.667) +2022-11-14 17:13:29,685 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0736 (0.0651) Prec@1 86.000 (87.500) Prec@5 99.000 (99.500) +2022-11-14 17:13:29,691 Test: [4/100] Model Time 0.005 (0.008) Loss Time 0.000 (0.000) Loss 0.0755 (0.0672) Prec@1 88.000 (87.600) Prec@5 99.000 (99.400) +2022-11-14 17:13:29,701 Test: [5/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0414 (0.0629) Prec@1 93.000 (88.500) Prec@5 100.000 (99.500) +2022-11-14 17:13:29,710 Test: [6/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0743 (0.0645) Prec@1 88.000 (88.429) Prec@5 100.000 (99.571) +2022-11-14 17:13:29,718 Test: [7/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0876 (0.0674) Prec@1 86.000 (88.125) Prec@5 99.000 (99.500) +2022-11-14 17:13:29,725 Test: [8/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0850 (0.0693) Prec@1 89.000 (88.222) Prec@5 98.000 (99.333) +2022-11-14 17:13:29,735 Test: [9/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0849 (0.0709) Prec@1 86.000 (88.000) Prec@5 98.000 (99.200) +2022-11-14 17:13:29,745 Test: [10/100] Model Time 0.008 (0.008) Loss Time 0.000 (0.000) Loss 0.0557 (0.0695) Prec@1 90.000 (88.182) Prec@5 100.000 (99.273) +2022-11-14 17:13:29,753 Test: [11/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0707) Prec@1 88.000 (88.167) Prec@5 100.000 (99.333) +2022-11-14 17:13:29,761 Test: [12/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0705) Prec@1 88.000 (88.154) Prec@5 100.000 (99.385) +2022-11-14 17:13:29,771 Test: [13/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0710) Prec@1 88.000 (88.143) Prec@5 100.000 (99.429) +2022-11-14 17:13:29,781 Test: [14/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0747 (0.0712) Prec@1 87.000 (88.067) Prec@5 99.000 (99.400) +2022-11-14 17:13:29,789 Test: [15/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0718) Prec@1 89.000 (88.125) Prec@5 99.000 (99.375) +2022-11-14 17:13:29,797 Test: [16/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0445 (0.0702) Prec@1 91.000 (88.294) Prec@5 99.000 (99.353) +2022-11-14 17:13:29,806 Test: [17/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1012 (0.0719) Prec@1 84.000 (88.056) Prec@5 99.000 (99.333) +2022-11-14 17:13:29,816 Test: [18/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0864 (0.0727) Prec@1 86.000 (87.947) Prec@5 100.000 (99.368) +2022-11-14 17:13:29,824 Test: [19/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1062 (0.0743) Prec@1 81.000 (87.600) Prec@5 98.000 (99.300) +2022-11-14 17:13:29,832 Test: [20/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0839 (0.0748) Prec@1 87.000 (87.571) Prec@5 99.000 (99.286) +2022-11-14 17:13:29,842 Test: [21/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0853 (0.0753) Prec@1 85.000 (87.455) Prec@5 98.000 (99.227) +2022-11-14 17:13:29,852 Test: [22/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0843 (0.0757) Prec@1 87.000 (87.435) Prec@5 98.000 (99.174) +2022-11-14 17:13:29,859 Test: [23/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0759) Prec@1 90.000 (87.542) Prec@5 99.000 (99.167) +2022-11-14 17:13:29,867 Test: [24/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0760) Prec@1 87.000 (87.520) Prec@5 100.000 (99.200) +2022-11-14 17:13:29,877 Test: [25/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1026 (0.0770) Prec@1 82.000 (87.308) Prec@5 98.000 (99.154) +2022-11-14 17:13:29,887 Test: [26/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0539 (0.0761) Prec@1 92.000 (87.481) Prec@5 99.000 (99.148) +2022-11-14 17:13:29,894 Test: [27/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0744 (0.0761) Prec@1 88.000 (87.500) Prec@5 100.000 (99.179) +2022-11-14 17:13:29,902 Test: [28/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0757) Prec@1 89.000 (87.552) Prec@5 99.000 (99.172) +2022-11-14 17:13:29,912 Test: [29/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0700 (0.0755) Prec@1 88.000 (87.567) Prec@5 98.000 (99.133) +2022-11-14 17:13:29,922 Test: [30/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0632 (0.0751) Prec@1 90.000 (87.645) Prec@5 99.000 (99.129) +2022-11-14 17:13:29,929 Test: [31/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0715 (0.0750) Prec@1 88.000 (87.656) Prec@5 99.000 (99.125) +2022-11-14 17:13:29,937 Test: [32/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0615 (0.0746) Prec@1 90.000 (87.727) Prec@5 99.000 (99.121) +2022-11-14 17:13:29,947 Test: [33/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0950 (0.0752) Prec@1 87.000 (87.706) Prec@5 100.000 (99.147) +2022-11-14 17:13:29,957 Test: [34/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0826 (0.0754) Prec@1 86.000 (87.657) Prec@5 98.000 (99.114) +2022-11-14 17:13:29,964 Test: [35/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0752) Prec@1 89.000 (87.694) Prec@5 99.000 (99.111) +2022-11-14 17:13:29,972 Test: [36/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0748 (0.0752) Prec@1 86.000 (87.649) Prec@5 99.000 (99.108) +2022-11-14 17:13:29,982 Test: [37/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1080 (0.0760) Prec@1 81.000 (87.474) Prec@5 98.000 (99.079) +2022-11-14 17:13:29,991 Test: [38/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0508 (0.0754) Prec@1 93.000 (87.615) Prec@5 100.000 (99.103) +2022-11-14 17:13:29,999 Test: [39/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0652 (0.0751) Prec@1 90.000 (87.675) Prec@5 100.000 (99.125) +2022-11-14 17:13:30,006 Test: [40/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0923 (0.0756) Prec@1 83.000 (87.561) Prec@5 96.000 (99.049) +2022-11-14 17:13:30,016 Test: [41/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0673 (0.0754) Prec@1 91.000 (87.643) Prec@5 99.000 (99.048) +2022-11-14 17:13:30,026 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0666 (0.0752) Prec@1 91.000 (87.721) Prec@5 100.000 (99.070) +2022-11-14 17:13:30,034 Test: [43/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0754) Prec@1 86.000 (87.682) Prec@5 99.000 (99.068) +2022-11-14 17:13:30,041 Test: [44/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0675 (0.0752) Prec@1 89.000 (87.711) Prec@5 100.000 (99.089) +2022-11-14 17:13:30,051 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0832 (0.0754) Prec@1 87.000 (87.696) Prec@5 100.000 (99.109) +2022-11-14 17:13:30,061 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0647 (0.0751) Prec@1 91.000 (87.766) Prec@5 100.000 (99.128) +2022-11-14 17:13:30,068 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1075 (0.0758) Prec@1 83.000 (87.667) Prec@5 98.000 (99.104) +2022-11-14 17:13:30,076 Test: [48/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0660 (0.0756) Prec@1 90.000 (87.714) Prec@5 100.000 (99.122) +2022-11-14 17:13:30,087 Test: [49/100] Model Time 0.009 (0.007) Loss Time 0.000 (0.000) Loss 0.0994 (0.0761) Prec@1 85.000 (87.660) Prec@5 100.000 (99.140) +2022-11-14 17:13:30,097 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0713 (0.0760) Prec@1 88.000 (87.667) Prec@5 100.000 (99.157) +2022-11-14 17:13:30,105 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0658 (0.0758) Prec@1 89.000 (87.692) Prec@5 100.000 (99.173) +2022-11-14 17:13:30,112 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0791 (0.0759) Prec@1 88.000 (87.698) Prec@5 98.000 (99.151) +2022-11-14 17:13:30,122 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0758) Prec@1 87.000 (87.685) Prec@5 100.000 (99.167) +2022-11-14 17:13:30,132 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0782 (0.0759) Prec@1 84.000 (87.618) Prec@5 100.000 (99.182) +2022-11-14 17:13:30,140 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0757) Prec@1 88.000 (87.625) Prec@5 100.000 (99.196) +2022-11-14 17:13:30,147 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0807 (0.0758) Prec@1 86.000 (87.596) Prec@5 99.000 (99.193) +2022-11-14 17:13:30,158 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0726 (0.0757) Prec@1 90.000 (87.638) Prec@5 100.000 (99.207) +2022-11-14 17:13:30,169 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1123 (0.0764) Prec@1 81.000 (87.525) Prec@5 99.000 (99.203) +2022-11-14 17:13:30,176 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0763) Prec@1 90.000 (87.567) Prec@5 100.000 (99.217) +2022-11-14 17:13:30,184 Test: [60/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0755 (0.0763) Prec@1 88.000 (87.574) Prec@5 99.000 (99.213) +2022-11-14 17:13:30,194 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0694 (0.0762) Prec@1 88.000 (87.581) Prec@5 100.000 (99.226) +2022-11-14 17:13:30,204 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0579 (0.0759) Prec@1 90.000 (87.619) Prec@5 99.000 (99.222) +2022-11-14 17:13:30,212 Test: [63/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0573 (0.0756) Prec@1 91.000 (87.672) Prec@5 100.000 (99.234) +2022-11-14 17:13:30,219 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0935 (0.0759) Prec@1 83.000 (87.600) Prec@5 99.000 (99.231) +2022-11-14 17:13:30,230 Test: [65/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0805 (0.0760) Prec@1 85.000 (87.561) Prec@5 100.000 (99.242) +2022-11-14 17:13:30,239 Test: [66/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0389 (0.0754) Prec@1 94.000 (87.657) Prec@5 100.000 (99.254) +2022-11-14 17:13:30,247 Test: [67/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0560 (0.0751) Prec@1 91.000 (87.706) Prec@5 99.000 (99.250) +2022-11-14 17:13:30,255 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0680 (0.0750) Prec@1 89.000 (87.725) Prec@5 99.000 (99.246) +2022-11-14 17:13:30,264 Test: [69/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0834 (0.0751) Prec@1 87.000 (87.714) Prec@5 99.000 (99.243) +2022-11-14 17:13:30,274 Test: [70/100] Model Time 0.007 (0.007) Loss Time 0.000 (0.000) Loss 0.1088 (0.0756) Prec@1 86.000 (87.690) Prec@5 98.000 (99.225) +2022-11-14 17:13:30,282 Test: [71/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0513 (0.0753) Prec@1 91.000 (87.736) Prec@5 100.000 (99.236) +2022-11-14 17:13:30,289 Test: [72/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0749 (0.0753) Prec@1 89.000 (87.753) Prec@5 100.000 (99.247) +2022-11-14 17:13:30,299 Test: [73/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0672 (0.0752) Prec@1 92.000 (87.811) Prec@5 100.000 (99.257) +2022-11-14 17:13:30,309 Test: [74/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1079 (0.0756) Prec@1 82.000 (87.733) Prec@5 100.000 (99.267) +2022-11-14 17:13:30,317 Test: [75/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0688 (0.0755) Prec@1 88.000 (87.737) Prec@5 100.000 (99.276) +2022-11-14 17:13:30,325 Test: [76/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0786 (0.0756) Prec@1 88.000 (87.740) Prec@5 98.000 (99.260) +2022-11-14 17:13:30,332 Test: [77/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.1107 (0.0760) Prec@1 82.000 (87.667) Prec@5 99.000 (99.256) +2022-11-14 17:13:30,340 Test: [78/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0802 (0.0761) Prec@1 86.000 (87.646) Prec@5 100.000 (99.266) +2022-11-14 17:13:30,348 Test: [79/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0656 (0.0759) Prec@1 90.000 (87.675) Prec@5 98.000 (99.250) +2022-11-14 17:13:30,355 Test: [80/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0780 (0.0760) Prec@1 89.000 (87.691) Prec@5 97.000 (99.222) +2022-11-14 17:13:30,363 Test: [81/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0913 (0.0761) Prec@1 84.000 (87.646) Prec@5 100.000 (99.232) +2022-11-14 17:13:30,371 Test: [82/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0804 (0.0762) Prec@1 84.000 (87.602) Prec@5 100.000 (99.241) +2022-11-14 17:13:30,379 Test: [83/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0550 (0.0759) Prec@1 91.000 (87.643) Prec@5 99.000 (99.238) +2022-11-14 17:13:30,386 Test: [84/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0761) Prec@1 87.000 (87.635) Prec@5 99.000 (99.235) +2022-11-14 17:13:30,394 Test: [85/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0897 (0.0762) Prec@1 87.000 (87.628) Prec@5 99.000 (99.233) +2022-11-14 17:13:30,401 Test: [86/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0767 (0.0763) Prec@1 87.000 (87.621) Prec@5 99.000 (99.230) +2022-11-14 17:13:30,409 Test: [87/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0769 (0.0763) Prec@1 90.000 (87.648) Prec@5 98.000 (99.216) +2022-11-14 17:13:30,416 Test: [88/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0595 (0.0761) Prec@1 89.000 (87.663) Prec@5 100.000 (99.225) +2022-11-14 17:13:30,424 Test: [89/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0636 (0.0759) Prec@1 91.000 (87.700) Prec@5 99.000 (99.222) +2022-11-14 17:13:30,431 Test: [90/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0386 (0.0755) Prec@1 93.000 (87.758) Prec@5 100.000 (99.231) +2022-11-14 17:13:30,439 Test: [91/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0491 (0.0752) Prec@1 94.000 (87.826) Prec@5 99.000 (99.228) +2022-11-14 17:13:30,447 Test: [92/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0678 (0.0752) Prec@1 88.000 (87.828) Prec@5 100.000 (99.237) +2022-11-14 17:13:30,454 Test: [93/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0801 (0.0752) Prec@1 88.000 (87.830) Prec@5 98.000 (99.223) +2022-11-14 17:13:30,462 Test: [94/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0752) Prec@1 87.000 (87.821) Prec@5 100.000 (99.232) +2022-11-14 17:13:30,469 Test: [95/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0529 (0.0750) Prec@1 90.000 (87.844) Prec@5 100.000 (99.240) +2022-11-14 17:13:30,476 Test: [96/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0395 (0.0746) Prec@1 95.000 (87.918) Prec@5 99.000 (99.237) +2022-11-14 17:13:30,484 Test: [97/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0746) Prec@1 90.000 (87.939) Prec@5 98.000 (99.224) +2022-11-14 17:13:30,491 Test: [98/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.1017 (0.0749) Prec@1 85.000 (87.909) Prec@5 99.000 (99.222) +2022-11-14 17:13:30,499 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0738 (0.0748) Prec@1 88.000 (87.910) Prec@5 100.000 (99.230) +2022-11-14 17:13:30,552 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:13:30,870 Epoch: [494][0/500] Time 0.023 (0.023) Data 0.241 (0.241) Loss 0.0221 (0.0221) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:31,066 Epoch: [494][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0158 (0.0189) Prec@1 98.000 (97.500) Prec@5 100.000 (100.000) +2022-11-14 17:13:31,258 Epoch: [494][20/500] Time 0.015 (0.017) Data 0.002 (0.013) Loss 0.0367 (0.0249) Prec@1 94.000 (96.333) Prec@5 98.000 (99.333) +2022-11-14 17:13:31,450 Epoch: [494][30/500] Time 0.015 (0.017) Data 0.001 (0.009) Loss 0.0558 (0.0326) Prec@1 90.000 (94.750) Prec@5 100.000 (99.500) +2022-11-14 17:13:31,642 Epoch: [494][40/500] Time 0.016 (0.017) Data 0.002 (0.007) Loss 0.0230 (0.0307) Prec@1 96.000 (95.000) Prec@5 100.000 (99.600) +2022-11-14 17:13:31,832 Epoch: [494][50/500] Time 0.015 (0.017) Data 0.001 (0.006) Loss 0.0557 (0.0348) Prec@1 91.000 (94.333) Prec@5 100.000 (99.667) +2022-11-14 17:13:32,023 Epoch: [494][60/500] Time 0.015 (0.017) Data 0.002 (0.006) Loss 0.0182 (0.0325) Prec@1 98.000 (94.857) Prec@5 100.000 (99.714) +2022-11-14 17:13:32,216 Epoch: [494][70/500] Time 0.015 (0.017) Data 0.002 (0.005) Loss 0.0441 (0.0339) Prec@1 93.000 (94.625) Prec@5 100.000 (99.750) +2022-11-14 17:13:32,406 Epoch: [494][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0244 (0.0329) Prec@1 97.000 (94.889) Prec@5 100.000 (99.778) +2022-11-14 17:13:32,600 Epoch: [494][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0316 (0.0327) Prec@1 96.000 (95.000) Prec@5 99.000 (99.700) +2022-11-14 17:13:32,793 Epoch: [494][100/500] Time 0.024 (0.017) Data 0.002 (0.004) Loss 0.0298 (0.0325) Prec@1 93.000 (94.818) Prec@5 100.000 (99.727) +2022-11-14 17:13:32,994 Epoch: [494][110/500] Time 0.015 (0.017) Data 0.001 (0.004) Loss 0.0201 (0.0314) Prec@1 97.000 (95.000) Prec@5 100.000 (99.750) +2022-11-14 17:13:33,197 Epoch: [494][120/500] Time 0.022 (0.017) Data 0.002 (0.004) Loss 0.0418 (0.0322) Prec@1 92.000 (94.769) Prec@5 100.000 (99.769) +2022-11-14 17:13:33,395 Epoch: [494][130/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0369 (0.0326) Prec@1 91.000 (94.500) Prec@5 99.000 (99.714) +2022-11-14 17:13:33,600 Epoch: [494][140/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0211 (0.0318) Prec@1 97.000 (94.667) Prec@5 100.000 (99.733) +2022-11-14 17:13:33,805 Epoch: [494][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0250 (0.0314) Prec@1 95.000 (94.688) Prec@5 100.000 (99.750) +2022-11-14 17:13:34,014 Epoch: [494][160/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0162 (0.0305) Prec@1 98.000 (94.882) Prec@5 100.000 (99.765) +2022-11-14 17:13:34,211 Epoch: [494][170/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0165 (0.0297) Prec@1 97.000 (95.000) Prec@5 100.000 (99.778) +2022-11-14 17:13:34,407 Epoch: [494][180/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0181 (0.0291) Prec@1 97.000 (95.105) Prec@5 100.000 (99.789) +2022-11-14 17:13:34,603 Epoch: [494][190/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0280 (0.0290) Prec@1 96.000 (95.150) Prec@5 100.000 (99.800) +2022-11-14 17:13:34,802 Epoch: [494][200/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0328 (0.0292) Prec@1 93.000 (95.048) Prec@5 100.000 (99.810) +2022-11-14 17:13:34,997 Epoch: [494][210/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0297 (0.0292) Prec@1 95.000 (95.045) Prec@5 100.000 (99.818) +2022-11-14 17:13:35,199 Epoch: [494][220/500] Time 0.023 (0.017) Data 0.001 (0.003) Loss 0.0323 (0.0294) Prec@1 96.000 (95.087) Prec@5 100.000 (99.826) +2022-11-14 17:13:35,392 Epoch: [494][230/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0296 (0.0294) Prec@1 95.000 (95.083) Prec@5 99.000 (99.792) +2022-11-14 17:13:35,629 Epoch: [494][240/500] Time 0.024 (0.018) Data 0.001 (0.003) Loss 0.0134 (0.0287) Prec@1 97.000 (95.160) Prec@5 100.000 (99.800) +2022-11-14 17:13:35,874 Epoch: [494][250/500] Time 0.022 (0.018) Data 0.001 (0.003) Loss 0.0430 (0.0293) Prec@1 93.000 (95.077) Prec@5 99.000 (99.769) +2022-11-14 17:13:36,123 Epoch: [494][260/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0124 (0.0287) Prec@1 98.000 (95.185) Prec@5 100.000 (99.778) +2022-11-14 17:13:36,365 Epoch: [494][270/500] Time 0.023 (0.018) Data 0.002 (0.002) Loss 0.0293 (0.0287) Prec@1 94.000 (95.143) Prec@5 100.000 (99.786) +2022-11-14 17:13:36,612 Epoch: [494][280/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0280 (0.0287) Prec@1 96.000 (95.172) Prec@5 100.000 (99.793) +2022-11-14 17:13:36,860 Epoch: [494][290/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0544 (0.0295) Prec@1 90.000 (95.000) Prec@5 99.000 (99.767) +2022-11-14 17:13:37,111 Epoch: [494][300/500] Time 0.027 (0.018) Data 0.001 (0.002) Loss 0.0258 (0.0294) Prec@1 96.000 (95.032) Prec@5 100.000 (99.774) +2022-11-14 17:13:37,359 Epoch: [494][310/500] Time 0.023 (0.018) Data 0.001 (0.002) Loss 0.0226 (0.0292) Prec@1 98.000 (95.125) Prec@5 100.000 (99.781) +2022-11-14 17:13:37,603 Epoch: [494][320/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0295 (0.0292) Prec@1 95.000 (95.121) Prec@5 100.000 (99.788) +2022-11-14 17:13:37,846 Epoch: [494][330/500] Time 0.021 (0.019) Data 0.002 (0.002) Loss 0.0345 (0.0294) Prec@1 91.000 (95.000) Prec@5 100.000 (99.794) +2022-11-14 17:13:38,096 Epoch: [494][340/500] Time 0.024 (0.019) Data 0.001 (0.002) Loss 0.0326 (0.0295) Prec@1 93.000 (94.943) Prec@5 100.000 (99.800) +2022-11-14 17:13:38,336 Epoch: [494][350/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0307 (0.0295) Prec@1 94.000 (94.917) Prec@5 100.000 (99.806) +2022-11-14 17:13:38,578 Epoch: [494][360/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0312 (0.0295) Prec@1 96.000 (94.946) Prec@5 100.000 (99.811) +2022-11-14 17:13:38,821 Epoch: [494][370/500] Time 0.023 (0.019) Data 0.001 (0.002) Loss 0.0339 (0.0296) Prec@1 96.000 (94.974) Prec@5 100.000 (99.816) +2022-11-14 17:13:39,066 Epoch: [494][380/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0160 (0.0293) Prec@1 97.000 (95.026) Prec@5 100.000 (99.821) +2022-11-14 17:13:39,312 Epoch: [494][390/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0338 (0.0294) Prec@1 96.000 (95.050) Prec@5 100.000 (99.825) +2022-11-14 17:13:39,554 Epoch: [494][400/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0240 (0.0293) Prec@1 97.000 (95.098) Prec@5 100.000 (99.829) +2022-11-14 17:13:39,796 Epoch: [494][410/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0191 (0.0290) Prec@1 98.000 (95.167) Prec@5 100.000 (99.833) +2022-11-14 17:13:40,041 Epoch: [494][420/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0329 (0.0291) Prec@1 96.000 (95.186) Prec@5 99.000 (99.814) +2022-11-14 17:13:40,284 Epoch: [494][430/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0286 (0.0291) Prec@1 94.000 (95.159) Prec@5 99.000 (99.795) +2022-11-14 17:13:40,528 Epoch: [494][440/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0642 (0.0299) Prec@1 91.000 (95.067) Prec@5 99.000 (99.778) +2022-11-14 17:13:40,773 Epoch: [494][450/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0267 (0.0298) Prec@1 95.000 (95.065) Prec@5 100.000 (99.783) +2022-11-14 17:13:41,016 Epoch: [494][460/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0335 (0.0299) Prec@1 95.000 (95.064) Prec@5 100.000 (99.787) +2022-11-14 17:13:41,263 Epoch: [494][470/500] Time 0.022 (0.019) Data 0.002 (0.002) Loss 0.0330 (0.0300) Prec@1 94.000 (95.042) Prec@5 100.000 (99.792) +2022-11-14 17:13:41,511 Epoch: [494][480/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0316 (0.0300) Prec@1 96.000 (95.061) Prec@5 100.000 (99.796) +2022-11-14 17:13:41,760 Epoch: [494][490/500] Time 0.021 (0.020) Data 0.001 (0.002) Loss 0.0142 (0.0297) Prec@1 98.000 (95.120) Prec@5 100.000 (99.800) +2022-11-14 17:13:41,980 Epoch: [494][499/500] Time 0.023 (0.020) Data 0.001 (0.002) Loss 0.0271 (0.0296) Prec@1 96.000 (95.137) Prec@5 100.000 (99.804) +2022-11-14 17:13:42,282 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0729 (0.0729) Prec@1 86.000 (86.000) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,291 Test: [1/100] Model Time 0.008 (0.009) Loss Time 0.000 (0.000) Loss 0.0625 (0.0677) Prec@1 92.000 (89.000) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,299 Test: [2/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0712 (0.0689) Prec@1 88.000 (88.667) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,309 Test: [3/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0746 (0.0703) Prec@1 87.000 (88.250) Prec@5 100.000 (99.250) +2022-11-14 17:13:42,316 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0514 (0.0665) Prec@1 91.000 (88.800) Prec@5 100.000 (99.400) +2022-11-14 17:13:42,323 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0433 (0.0626) Prec@1 92.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 17:13:42,330 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0692 (0.0636) Prec@1 89.000 (89.286) Prec@5 99.000 (99.429) +2022-11-14 17:13:42,339 Test: [7/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0873 (0.0666) Prec@1 87.000 (89.000) Prec@5 98.000 (99.250) +2022-11-14 17:13:42,346 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0611 (0.0660) Prec@1 91.000 (89.222) Prec@5 99.000 (99.222) +2022-11-14 17:13:42,354 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0664) Prec@1 90.000 (89.300) Prec@5 98.000 (99.100) +2022-11-14 17:13:42,361 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0673) Prec@1 86.000 (89.000) Prec@5 100.000 (99.182) +2022-11-14 17:13:42,369 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0679) Prec@1 88.000 (88.917) Prec@5 99.000 (99.167) +2022-11-14 17:13:42,376 Test: [12/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0688) Prec@1 90.000 (89.000) Prec@5 99.000 (99.154) +2022-11-14 17:13:42,384 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0696) Prec@1 88.000 (88.929) Prec@5 99.000 (99.143) +2022-11-14 17:13:42,391 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0691) Prec@1 88.000 (88.867) Prec@5 100.000 (99.200) +2022-11-14 17:13:42,399 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0683) Prec@1 91.000 (89.000) Prec@5 100.000 (99.250) +2022-11-14 17:13:42,406 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0508 (0.0673) Prec@1 92.000 (89.176) Prec@5 99.000 (99.235) +2022-11-14 17:13:42,415 Test: [17/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.0695) Prec@1 85.000 (88.944) Prec@5 99.000 (99.222) +2022-11-14 17:13:42,424 Test: [18/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.1060 (0.0714) Prec@1 83.000 (88.632) Prec@5 97.000 (99.105) +2022-11-14 17:13:42,432 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0725 (0.0715) Prec@1 87.000 (88.550) Prec@5 98.000 (99.050) +2022-11-14 17:13:42,440 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0719) Prec@1 87.000 (88.476) Prec@5 100.000 (99.095) +2022-11-14 17:13:42,450 Test: [21/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0725) Prec@1 85.000 (88.318) Prec@5 97.000 (99.000) +2022-11-14 17:13:42,460 Test: [22/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0735) Prec@1 88.000 (88.304) Prec@5 96.000 (98.870) +2022-11-14 17:13:42,469 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0743) Prec@1 86.000 (88.208) Prec@5 100.000 (98.917) +2022-11-14 17:13:42,476 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0743) Prec@1 90.000 (88.280) Prec@5 100.000 (98.960) +2022-11-14 17:13:42,487 Test: [25/100] Model Time 0.009 (0.006) Loss Time 0.000 (0.000) Loss 0.0799 (0.0745) Prec@1 86.000 (88.192) Prec@5 99.000 (98.962) +2022-11-14 17:13:42,497 Test: [26/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0735) Prec@1 92.000 (88.333) Prec@5 100.000 (99.000) +2022-11-14 17:13:42,505 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0734) Prec@1 87.000 (88.286) Prec@5 100.000 (99.036) +2022-11-14 17:13:42,513 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0738) Prec@1 86.000 (88.207) Prec@5 99.000 (99.034) +2022-11-14 17:13:42,523 Test: [29/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0588 (0.0733) Prec@1 91.000 (88.300) Prec@5 100.000 (99.067) +2022-11-14 17:13:42,533 Test: [30/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0730) Prec@1 89.000 (88.323) Prec@5 100.000 (99.097) +2022-11-14 17:13:42,541 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0694 (0.0729) Prec@1 89.000 (88.344) Prec@5 98.000 (99.062) +2022-11-14 17:13:42,548 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0732) Prec@1 86.000 (88.273) Prec@5 99.000 (99.061) +2022-11-14 17:13:42,558 Test: [33/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0975 (0.0740) Prec@1 86.000 (88.206) Prec@5 99.000 (99.059) +2022-11-14 17:13:42,569 Test: [34/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0741) Prec@1 86.000 (88.143) Prec@5 99.000 (99.057) +2022-11-14 17:13:42,576 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0739) Prec@1 90.000 (88.194) Prec@5 100.000 (99.083) +2022-11-14 17:13:42,584 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0741) Prec@1 87.000 (88.162) Prec@5 98.000 (99.054) +2022-11-14 17:13:42,595 Test: [37/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0937 (0.0746) Prec@1 87.000 (88.132) Prec@5 100.000 (99.079) +2022-11-14 17:13:42,605 Test: [38/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0742) Prec@1 93.000 (88.256) Prec@5 99.000 (99.077) +2022-11-14 17:13:42,612 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0739) Prec@1 90.000 (88.300) Prec@5 99.000 (99.075) +2022-11-14 17:13:42,620 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1054 (0.0746) Prec@1 84.000 (88.195) Prec@5 97.000 (99.024) +2022-11-14 17:13:42,630 Test: [41/100] Model Time 0.008 (0.006) Loss Time 0.000 (0.000) Loss 0.0756 (0.0746) Prec@1 88.000 (88.190) Prec@5 99.000 (99.024) +2022-11-14 17:13:42,640 Test: [42/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0461 (0.0740) Prec@1 93.000 (88.302) Prec@5 99.000 (99.023) +2022-11-14 17:13:42,648 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0738) Prec@1 92.000 (88.386) Prec@5 98.000 (99.000) +2022-11-14 17:13:42,655 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0735) Prec@1 90.000 (88.422) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,666 Test: [45/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.1127 (0.0743) Prec@1 82.000 (88.283) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,675 Test: [46/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0619 (0.0741) Prec@1 89.000 (88.298) Prec@5 100.000 (99.021) +2022-11-14 17:13:42,683 Test: [47/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0904 (0.0744) Prec@1 87.000 (88.271) Prec@5 98.000 (99.000) +2022-11-14 17:13:42,691 Test: [48/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0546 (0.0740) Prec@1 91.000 (88.327) Prec@5 98.000 (98.980) +2022-11-14 17:13:42,701 Test: [49/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0899 (0.0743) Prec@1 85.000 (88.260) Prec@5 99.000 (98.980) +2022-11-14 17:13:42,711 Test: [50/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0742 (0.0743) Prec@1 88.000 (88.255) Prec@5 100.000 (99.000) +2022-11-14 17:13:42,719 Test: [51/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0818 (0.0745) Prec@1 87.000 (88.231) Prec@5 99.000 (99.000) +2022-11-14 17:13:42,727 Test: [52/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0544 (0.0741) Prec@1 92.000 (88.302) Prec@5 100.000 (99.019) +2022-11-14 17:13:42,737 Test: [53/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0603 (0.0738) Prec@1 93.000 (88.389) Prec@5 100.000 (99.037) +2022-11-14 17:13:42,747 Test: [54/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0917 (0.0742) Prec@1 84.000 (88.309) Prec@5 100.000 (99.055) +2022-11-14 17:13:42,754 Test: [55/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0728 (0.0741) Prec@1 89.000 (88.321) Prec@5 99.000 (99.054) +2022-11-14 17:13:42,762 Test: [56/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0743) Prec@1 88.000 (88.316) Prec@5 99.000 (99.053) +2022-11-14 17:13:42,772 Test: [57/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0485 (0.0739) Prec@1 93.000 (88.397) Prec@5 98.000 (99.034) +2022-11-14 17:13:42,782 Test: [58/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0842 (0.0740) Prec@1 87.000 (88.373) Prec@5 98.000 (99.017) +2022-11-14 17:13:42,790 Test: [59/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0740 (0.0740) Prec@1 86.000 (88.333) Prec@5 100.000 (99.033) +2022-11-14 17:13:42,797 Test: [60/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0729 (0.0740) Prec@1 89.000 (88.344) Prec@5 100.000 (99.049) +2022-11-14 17:13:42,807 Test: [61/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0509 (0.0736) Prec@1 91.000 (88.387) Prec@5 100.000 (99.065) +2022-11-14 17:13:42,817 Test: [62/100] Model Time 0.008 (0.007) Loss Time 0.000 (0.000) Loss 0.0515 (0.0733) Prec@1 92.000 (88.444) Prec@5 100.000 (99.079) +2022-11-14 17:13:42,825 Test: [63/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0495 (0.0729) Prec@1 92.000 (88.500) Prec@5 100.000 (99.094) +2022-11-14 17:13:42,832 Test: [64/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0888 (0.0732) Prec@1 86.000 (88.462) Prec@5 99.000 (99.092) +2022-11-14 17:13:42,840 Test: [65/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0777 (0.0732) Prec@1 88.000 (88.455) Prec@5 99.000 (99.091) +2022-11-14 17:13:42,847 Test: [66/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0426 (0.0728) Prec@1 90.000 (88.478) Prec@5 100.000 (99.104) +2022-11-14 17:13:42,855 Test: [67/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0837 (0.0729) Prec@1 88.000 (88.471) Prec@5 99.000 (99.103) +2022-11-14 17:13:42,863 Test: [68/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0737 (0.0729) Prec@1 89.000 (88.478) Prec@5 99.000 (99.101) +2022-11-14 17:13:42,870 Test: [69/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0724 (0.0729) Prec@1 89.000 (88.486) Prec@5 98.000 (99.086) +2022-11-14 17:13:42,878 Test: [70/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0898 (0.0732) Prec@1 87.000 (88.465) Prec@5 99.000 (99.085) +2022-11-14 17:13:42,885 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0743 (0.0732) Prec@1 89.000 (88.472) Prec@5 100.000 (99.097) +2022-11-14 17:13:42,893 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0728) Prec@1 94.000 (88.548) Prec@5 99.000 (99.096) +2022-11-14 17:13:42,901 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0703 (0.0727) Prec@1 88.000 (88.541) Prec@5 100.000 (99.108) +2022-11-14 17:13:42,908 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1074 (0.0732) Prec@1 85.000 (88.493) Prec@5 99.000 (99.107) +2022-11-14 17:13:42,916 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0456 (0.0728) Prec@1 93.000 (88.553) Prec@5 100.000 (99.118) +2022-11-14 17:13:42,924 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0728) Prec@1 90.000 (88.571) Prec@5 99.000 (99.117) +2022-11-14 17:13:42,931 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0731) Prec@1 84.000 (88.513) Prec@5 96.000 (99.077) +2022-11-14 17:13:42,939 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0767 (0.0731) Prec@1 89.000 (88.519) Prec@5 100.000 (99.089) +2022-11-14 17:13:42,947 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0716 (0.0731) Prec@1 85.000 (88.475) Prec@5 100.000 (99.100) +2022-11-14 17:13:42,954 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0734) Prec@1 85.000 (88.432) Prec@5 99.000 (99.099) +2022-11-14 17:13:42,962 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0736) Prec@1 85.000 (88.390) Prec@5 98.000 (99.085) +2022-11-14 17:13:42,969 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0878 (0.0737) Prec@1 86.000 (88.361) Prec@5 99.000 (99.084) +2022-11-14 17:13:42,977 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0802 (0.0738) Prec@1 87.000 (88.345) Prec@5 99.000 (99.083) +2022-11-14 17:13:42,985 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0901 (0.0740) Prec@1 87.000 (88.329) Prec@5 100.000 (99.094) +2022-11-14 17:13:42,993 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0983 (0.0743) Prec@1 86.000 (88.302) Prec@5 100.000 (99.105) +2022-11-14 17:13:43,001 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0798 (0.0744) Prec@1 89.000 (88.310) Prec@5 100.000 (99.115) +2022-11-14 17:13:43,008 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1012 (0.0747) Prec@1 84.000 (88.261) Prec@5 98.000 (99.102) +2022-11-14 17:13:43,016 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0747) Prec@1 86.000 (88.236) Prec@5 99.000 (99.101) +2022-11-14 17:13:43,023 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0747) Prec@1 90.000 (88.256) Prec@5 99.000 (99.100) +2022-11-14 17:13:43,031 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0492 (0.0745) Prec@1 91.000 (88.286) Prec@5 100.000 (99.110) +2022-11-14 17:13:43,039 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0742) Prec@1 92.000 (88.326) Prec@5 100.000 (99.120) +2022-11-14 17:13:43,046 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0819 (0.0743) Prec@1 88.000 (88.323) Prec@5 100.000 (99.129) +2022-11-14 17:13:43,054 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0867 (0.0744) Prec@1 86.000 (88.298) Prec@5 98.000 (99.117) +2022-11-14 17:13:43,061 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1084 (0.0748) Prec@1 82.000 (88.232) Prec@5 99.000 (99.116) +2022-11-14 17:13:43,069 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0746) Prec@1 91.000 (88.260) Prec@5 99.000 (99.115) +2022-11-14 17:13:43,076 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0529 (0.0744) Prec@1 92.000 (88.299) Prec@5 98.000 (99.103) +2022-11-14 17:13:43,085 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0746) Prec@1 87.000 (88.286) Prec@5 99.000 (99.102) +2022-11-14 17:13:43,093 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1021 (0.0749) Prec@1 85.000 (88.253) Prec@5 98.000 (99.091) +2022-11-14 17:13:43,100 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0748) Prec@1 88.000 (88.250) Prec@5 100.000 (99.100) +2022-11-14 17:13:43,167 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:13:43,481 Epoch: [495][0/500] Time 0.021 (0.021) Data 0.235 (0.235) Loss 0.0274 (0.0274) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:43,680 Epoch: [495][10/500] Time 0.017 (0.018) Data 0.002 (0.023) Loss 0.0241 (0.0257) Prec@1 96.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:43,879 Epoch: [495][20/500] Time 0.017 (0.018) Data 0.002 (0.013) Loss 0.0241 (0.0252) Prec@1 95.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:13:44,082 Epoch: [495][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0347 (0.0276) Prec@1 93.000 (95.000) Prec@5 99.000 (99.750) +2022-11-14 17:13:44,287 Epoch: [495][40/500] Time 0.016 (0.018) Data 0.002 (0.007) Loss 0.0441 (0.0309) Prec@1 92.000 (94.400) Prec@5 100.000 (99.800) +2022-11-14 17:13:44,486 Epoch: [495][50/500] Time 0.017 (0.018) Data 0.002 (0.006) Loss 0.0210 (0.0292) Prec@1 98.000 (95.000) Prec@5 99.000 (99.667) +2022-11-14 17:13:44,691 Epoch: [495][60/500] Time 0.016 (0.018) Data 0.002 (0.006) Loss 0.0186 (0.0277) Prec@1 97.000 (95.286) Prec@5 100.000 (99.714) +2022-11-14 17:13:44,890 Epoch: [495][70/500] Time 0.017 (0.018) Data 0.001 (0.005) Loss 0.0230 (0.0271) Prec@1 97.000 (95.500) Prec@5 99.000 (99.625) +2022-11-14 17:13:45,094 Epoch: [495][80/500] Time 0.016 (0.018) Data 0.002 (0.005) Loss 0.0321 (0.0277) Prec@1 96.000 (95.556) Prec@5 99.000 (99.556) +2022-11-14 17:13:45,288 Epoch: [495][90/500] Time 0.017 (0.018) Data 0.001 (0.004) Loss 0.0346 (0.0284) Prec@1 93.000 (95.300) Prec@5 99.000 (99.500) +2022-11-14 17:13:45,486 Epoch: [495][100/500] Time 0.020 (0.018) Data 0.002 (0.004) Loss 0.0125 (0.0269) Prec@1 99.000 (95.636) Prec@5 100.000 (99.545) +2022-11-14 17:13:45,746 Epoch: [495][110/500] Time 0.025 (0.018) Data 0.002 (0.004) Loss 0.0221 (0.0265) Prec@1 96.000 (95.667) Prec@5 100.000 (99.583) +2022-11-14 17:13:46,012 Epoch: [495][120/500] Time 0.024 (0.019) Data 0.002 (0.004) Loss 0.0220 (0.0262) Prec@1 96.000 (95.692) Prec@5 100.000 (99.615) +2022-11-14 17:13:46,284 Epoch: [495][130/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0622 (0.0287) Prec@1 88.000 (95.143) Prec@5 100.000 (99.643) +2022-11-14 17:13:46,550 Epoch: [495][140/500] Time 0.023 (0.019) Data 0.002 (0.003) Loss 0.0312 (0.0289) Prec@1 95.000 (95.133) Prec@5 100.000 (99.667) +2022-11-14 17:13:46,823 Epoch: [495][150/500] Time 0.025 (0.020) Data 0.002 (0.003) Loss 0.0323 (0.0291) Prec@1 93.000 (95.000) Prec@5 100.000 (99.688) +2022-11-14 17:13:47,092 Epoch: [495][160/500] Time 0.024 (0.020) Data 0.002 (0.003) Loss 0.0365 (0.0295) Prec@1 94.000 (94.941) Prec@5 100.000 (99.706) +2022-11-14 17:13:47,366 Epoch: [495][170/500] Time 0.027 (0.020) Data 0.001 (0.003) Loss 0.0281 (0.0295) Prec@1 96.000 (95.000) Prec@5 100.000 (99.722) +2022-11-14 17:13:47,639 Epoch: [495][180/500] Time 0.022 (0.020) Data 0.002 (0.003) Loss 0.0223 (0.0291) Prec@1 96.000 (95.053) Prec@5 100.000 (99.737) +2022-11-14 17:13:47,912 Epoch: [495][190/500] Time 0.025 (0.020) Data 0.001 (0.003) Loss 0.0384 (0.0296) Prec@1 93.000 (94.950) Prec@5 100.000 (99.750) +2022-11-14 17:13:48,191 Epoch: [495][200/500] Time 0.023 (0.021) Data 0.002 (0.003) Loss 0.0312 (0.0296) Prec@1 94.000 (94.905) Prec@5 100.000 (99.762) +2022-11-14 17:13:48,463 Epoch: [495][210/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0201 (0.0292) Prec@1 97.000 (95.000) Prec@5 100.000 (99.773) +2022-11-14 17:13:48,734 Epoch: [495][220/500] Time 0.022 (0.021) Data 0.002 (0.003) Loss 0.0348 (0.0294) Prec@1 95.000 (95.000) Prec@5 100.000 (99.783) +2022-11-14 17:13:49,003 Epoch: [495][230/500] Time 0.026 (0.021) Data 0.002 (0.003) Loss 0.0115 (0.0287) Prec@1 98.000 (95.125) Prec@5 100.000 (99.792) +2022-11-14 17:13:49,275 Epoch: [495][240/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0156 (0.0282) Prec@1 98.000 (95.240) Prec@5 100.000 (99.800) +2022-11-14 17:13:49,543 Epoch: [495][250/500] Time 0.025 (0.021) Data 0.002 (0.003) Loss 0.0232 (0.0280) Prec@1 95.000 (95.231) Prec@5 100.000 (99.808) +2022-11-14 17:13:49,811 Epoch: [495][260/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0290 (0.0280) Prec@1 95.000 (95.222) Prec@5 100.000 (99.815) +2022-11-14 17:13:50,074 Epoch: [495][270/500] Time 0.024 (0.021) Data 0.002 (0.003) Loss 0.0294 (0.0281) Prec@1 97.000 (95.286) Prec@5 100.000 (99.821) +2022-11-14 17:13:50,339 Epoch: [495][280/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0354 (0.0283) Prec@1 95.000 (95.276) Prec@5 100.000 (99.828) +2022-11-14 17:13:50,611 Epoch: [495][290/500] Time 0.025 (0.022) Data 0.002 (0.003) Loss 0.0166 (0.0279) Prec@1 98.000 (95.367) Prec@5 100.000 (99.833) +2022-11-14 17:13:50,883 Epoch: [495][300/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0471 (0.0286) Prec@1 90.000 (95.194) Prec@5 100.000 (99.839) +2022-11-14 17:13:51,148 Epoch: [495][310/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0465 (0.0291) Prec@1 94.000 (95.156) Prec@5 100.000 (99.844) +2022-11-14 17:13:51,413 Epoch: [495][320/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0242 (0.0290) Prec@1 95.000 (95.152) Prec@5 100.000 (99.848) +2022-11-14 17:13:51,684 Epoch: [495][330/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0389 (0.0293) Prec@1 94.000 (95.118) Prec@5 100.000 (99.853) +2022-11-14 17:13:51,949 Epoch: [495][340/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0376 (0.0295) Prec@1 94.000 (95.086) Prec@5 100.000 (99.857) +2022-11-14 17:13:52,220 Epoch: [495][350/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0241 (0.0293) Prec@1 96.000 (95.111) Prec@5 100.000 (99.861) +2022-11-14 17:13:52,487 Epoch: [495][360/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0302 (0.0294) Prec@1 95.000 (95.108) Prec@5 99.000 (99.838) +2022-11-14 17:13:52,759 Epoch: [495][370/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0193 (0.0291) Prec@1 97.000 (95.158) Prec@5 99.000 (99.816) +2022-11-14 17:13:53,027 Epoch: [495][380/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0262 (0.0290) Prec@1 96.000 (95.179) Prec@5 100.000 (99.821) +2022-11-14 17:13:53,287 Epoch: [495][390/500] Time 0.023 (0.022) Data 0.002 (0.002) Loss 0.0092 (0.0285) Prec@1 99.000 (95.275) Prec@5 100.000 (99.825) +2022-11-14 17:13:53,551 Epoch: [495][400/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0549 (0.0292) Prec@1 90.000 (95.146) Prec@5 100.000 (99.829) +2022-11-14 17:13:53,816 Epoch: [495][410/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0103 (0.0287) Prec@1 98.000 (95.214) Prec@5 100.000 (99.833) +2022-11-14 17:13:54,078 Epoch: [495][420/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0173 (0.0285) Prec@1 99.000 (95.302) Prec@5 100.000 (99.837) +2022-11-14 17:13:54,346 Epoch: [495][430/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0239 (0.0284) Prec@1 97.000 (95.341) Prec@5 99.000 (99.818) +2022-11-14 17:13:54,607 Epoch: [495][440/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0355 (0.0285) Prec@1 95.000 (95.333) Prec@5 100.000 (99.822) +2022-11-14 17:13:54,868 Epoch: [495][450/500] Time 0.025 (0.022) Data 0.002 (0.002) Loss 0.0227 (0.0284) Prec@1 96.000 (95.348) Prec@5 100.000 (99.826) +2022-11-14 17:13:55,130 Epoch: [495][460/500] Time 0.026 (0.022) Data 0.002 (0.002) Loss 0.0301 (0.0284) Prec@1 96.000 (95.362) Prec@5 99.000 (99.809) +2022-11-14 17:13:55,389 Epoch: [495][470/500] Time 0.024 (0.022) Data 0.002 (0.002) Loss 0.0485 (0.0288) Prec@1 92.000 (95.292) Prec@5 100.000 (99.812) +2022-11-14 17:13:55,650 Epoch: [495][480/500] Time 0.025 (0.022) Data 0.001 (0.002) Loss 0.0298 (0.0289) Prec@1 96.000 (95.306) Prec@5 99.000 (99.796) +2022-11-14 17:13:55,915 Epoch: [495][490/500] Time 0.027 (0.022) Data 0.002 (0.002) Loss 0.0359 (0.0290) Prec@1 96.000 (95.320) Prec@5 100.000 (99.800) +2022-11-14 17:13:56,151 Epoch: [495][499/500] Time 0.024 (0.022) Data 0.001 (0.002) Loss 0.0166 (0.0288) Prec@1 98.000 (95.373) Prec@5 100.000 (99.804) +2022-11-14 17:13:56,459 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0565 (0.0565) Prec@1 89.000 (89.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:56,466 Test: [1/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0762 (0.0664) Prec@1 90.000 (89.500) Prec@5 100.000 (100.000) +2022-11-14 17:13:56,474 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0792 (0.0706) Prec@1 87.000 (88.667) Prec@5 99.000 (99.667) +2022-11-14 17:13:56,484 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0846 (0.0741) Prec@1 88.000 (88.500) Prec@5 99.000 (99.500) +2022-11-14 17:13:56,491 Test: [4/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0695) Prec@1 90.000 (88.800) Prec@5 100.000 (99.600) +2022-11-14 17:13:56,497 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0354 (0.0638) Prec@1 93.000 (89.500) Prec@5 100.000 (99.667) +2022-11-14 17:13:56,504 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0625 (0.0636) Prec@1 91.000 (89.714) Prec@5 100.000 (99.714) +2022-11-14 17:13:56,513 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0668) Prec@1 86.000 (89.250) Prec@5 99.000 (99.625) +2022-11-14 17:13:56,520 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0680) Prec@1 87.000 (89.000) Prec@5 98.000 (99.444) +2022-11-14 17:13:56,527 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0683) Prec@1 90.000 (89.100) Prec@5 99.000 (99.400) +2022-11-14 17:13:56,534 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0686) Prec@1 90.000 (89.182) Prec@5 100.000 (99.455) +2022-11-14 17:13:56,542 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0898 (0.0704) Prec@1 85.000 (88.833) Prec@5 99.000 (99.417) +2022-11-14 17:13:56,550 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0702) Prec@1 89.000 (88.846) Prec@5 98.000 (99.308) +2022-11-14 17:13:56,557 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0620 (0.0696) Prec@1 90.000 (88.929) Prec@5 99.000 (99.286) +2022-11-14 17:13:56,565 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0762 (0.0700) Prec@1 87.000 (88.800) Prec@5 100.000 (99.333) +2022-11-14 17:13:56,572 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0641 (0.0697) Prec@1 88.000 (88.750) Prec@5 100.000 (99.375) +2022-11-14 17:13:56,580 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0522 (0.0686) Prec@1 93.000 (89.000) Prec@5 99.000 (99.353) +2022-11-14 17:13:56,588 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1128 (0.0711) Prec@1 84.000 (88.722) Prec@5 99.000 (99.333) +2022-11-14 17:13:56,596 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0712) Prec@1 88.000 (88.684) Prec@5 99.000 (99.316) +2022-11-14 17:13:56,603 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0860 (0.0719) Prec@1 86.000 (88.550) Prec@5 98.000 (99.250) +2022-11-14 17:13:56,611 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0725) Prec@1 87.000 (88.476) Prec@5 100.000 (99.286) +2022-11-14 17:13:56,619 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0733) Prec@1 85.000 (88.318) Prec@5 99.000 (99.273) +2022-11-14 17:13:56,626 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0737) Prec@1 89.000 (88.348) Prec@5 98.000 (99.217) +2022-11-14 17:13:56,634 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0765 (0.0738) Prec@1 88.000 (88.333) Prec@5 100.000 (99.250) +2022-11-14 17:13:56,641 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0915 (0.0745) Prec@1 84.000 (88.160) Prec@5 100.000 (99.280) +2022-11-14 17:13:56,649 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1052 (0.0757) Prec@1 86.000 (88.077) Prec@5 98.000 (99.231) +2022-11-14 17:13:56,656 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0406 (0.0744) Prec@1 95.000 (88.333) Prec@5 100.000 (99.259) +2022-11-14 17:13:56,664 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0738) Prec@1 91.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 17:13:56,671 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0731) Prec@1 92.000 (88.552) Prec@5 98.000 (99.241) +2022-11-14 17:13:56,679 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0731) Prec@1 87.000 (88.500) Prec@5 98.000 (99.200) +2022-11-14 17:13:56,687 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0725) Prec@1 91.000 (88.581) Prec@5 100.000 (99.226) +2022-11-14 17:13:56,694 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0723) Prec@1 90.000 (88.625) Prec@5 99.000 (99.219) +2022-11-14 17:13:56,702 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0722 (0.0723) Prec@1 88.000 (88.606) Prec@5 100.000 (99.242) +2022-11-14 17:13:56,710 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0727) Prec@1 85.000 (88.500) Prec@5 98.000 (99.206) +2022-11-14 17:13:56,717 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0727 (0.0727) Prec@1 88.000 (88.486) Prec@5 97.000 (99.143) +2022-11-14 17:13:56,725 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0631 (0.0724) Prec@1 92.000 (88.583) Prec@5 100.000 (99.167) +2022-11-14 17:13:56,733 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0724) Prec@1 89.000 (88.595) Prec@5 99.000 (99.162) +2022-11-14 17:13:56,741 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1065 (0.0733) Prec@1 83.000 (88.447) Prec@5 100.000 (99.184) +2022-11-14 17:13:56,748 Test: [38/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0568 (0.0729) Prec@1 94.000 (88.590) Prec@5 99.000 (99.179) +2022-11-14 17:13:56,756 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0808 (0.0731) Prec@1 86.000 (88.525) Prec@5 98.000 (99.150) +2022-11-14 17:13:56,764 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0909 (0.0735) Prec@1 86.000 (88.463) Prec@5 100.000 (99.171) +2022-11-14 17:13:56,772 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0635 (0.0733) Prec@1 90.000 (88.500) Prec@5 100.000 (99.190) +2022-11-14 17:13:56,779 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0729) Prec@1 93.000 (88.605) Prec@5 100.000 (99.209) +2022-11-14 17:13:56,787 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0552 (0.0725) Prec@1 93.000 (88.705) Prec@5 99.000 (99.205) +2022-11-14 17:13:56,794 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0512 (0.0720) Prec@1 92.000 (88.778) Prec@5 99.000 (99.200) +2022-11-14 17:13:56,802 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0729) Prec@1 80.000 (88.587) Prec@5 100.000 (99.217) +2022-11-14 17:13:56,810 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0790 (0.0730) Prec@1 86.000 (88.532) Prec@5 99.000 (99.213) +2022-11-14 17:13:56,817 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1198 (0.0740) Prec@1 78.000 (88.312) Prec@5 97.000 (99.167) +2022-11-14 17:13:56,825 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0465 (0.0734) Prec@1 94.000 (88.429) Prec@5 100.000 (99.184) +2022-11-14 17:13:56,832 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0740) Prec@1 85.000 (88.360) Prec@5 100.000 (99.200) +2022-11-14 17:13:56,840 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0738) Prec@1 88.000 (88.353) Prec@5 100.000 (99.216) +2022-11-14 17:13:56,848 Test: [51/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0670 (0.0737) Prec@1 90.000 (88.385) Prec@5 100.000 (99.231) +2022-11-14 17:13:56,855 Test: [52/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0595 (0.0734) Prec@1 92.000 (88.453) Prec@5 99.000 (99.226) +2022-11-14 17:13:56,863 Test: [53/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0682 (0.0733) Prec@1 88.000 (88.444) Prec@5 99.000 (99.222) +2022-11-14 17:13:56,870 Test: [54/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0837 (0.0735) Prec@1 85.000 (88.382) Prec@5 100.000 (99.236) +2022-11-14 17:13:56,878 Test: [55/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0735) Prec@1 87.000 (88.357) Prec@5 99.000 (99.232) +2022-11-14 17:13:56,885 Test: [56/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0587 (0.0732) Prec@1 89.000 (88.368) Prec@5 100.000 (99.246) +2022-11-14 17:13:56,893 Test: [57/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0790 (0.0733) Prec@1 88.000 (88.362) Prec@5 99.000 (99.241) +2022-11-14 17:13:56,900 Test: [58/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1161 (0.0740) Prec@1 82.000 (88.254) Prec@5 99.000 (99.237) +2022-11-14 17:13:56,908 Test: [59/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0702 (0.0740) Prec@1 88.000 (88.250) Prec@5 99.000 (99.233) +2022-11-14 17:13:56,916 Test: [60/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0816 (0.0741) Prec@1 88.000 (88.246) Prec@5 100.000 (99.246) +2022-11-14 17:13:56,923 Test: [61/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0831 (0.0742) Prec@1 86.000 (88.210) Prec@5 100.000 (99.258) +2022-11-14 17:13:56,931 Test: [62/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0589 (0.0740) Prec@1 89.000 (88.222) Prec@5 99.000 (99.254) +2022-11-14 17:13:56,938 Test: [63/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0313 (0.0733) Prec@1 94.000 (88.312) Prec@5 100.000 (99.266) +2022-11-14 17:13:56,946 Test: [64/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0867 (0.0735) Prec@1 87.000 (88.292) Prec@5 99.000 (99.262) +2022-11-14 17:13:56,954 Test: [65/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0798 (0.0736) Prec@1 85.000 (88.242) Prec@5 100.000 (99.273) +2022-11-14 17:13:56,961 Test: [66/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0435 (0.0732) Prec@1 93.000 (88.313) Prec@5 100.000 (99.284) +2022-11-14 17:13:56,969 Test: [67/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0711 (0.0732) Prec@1 90.000 (88.338) Prec@5 97.000 (99.250) +2022-11-14 17:13:56,976 Test: [68/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0602 (0.0730) Prec@1 90.000 (88.362) Prec@5 99.000 (99.246) +2022-11-14 17:13:56,984 Test: [69/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0652 (0.0729) Prec@1 89.000 (88.371) Prec@5 100.000 (99.257) +2022-11-14 17:13:56,991 Test: [70/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0977 (0.0732) Prec@1 85.000 (88.324) Prec@5 97.000 (99.225) +2022-11-14 17:13:56,998 Test: [71/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0603 (0.0730) Prec@1 88.000 (88.319) Prec@5 100.000 (99.236) +2022-11-14 17:13:57,006 Test: [72/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0606 (0.0729) Prec@1 91.000 (88.356) Prec@5 100.000 (99.247) +2022-11-14 17:13:57,013 Test: [73/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0386 (0.0724) Prec@1 93.000 (88.419) Prec@5 99.000 (99.243) +2022-11-14 17:13:57,021 Test: [74/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1091 (0.0729) Prec@1 84.000 (88.360) Prec@5 98.000 (99.227) +2022-11-14 17:13:57,028 Test: [75/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0443 (0.0725) Prec@1 94.000 (88.434) Prec@5 99.000 (99.224) +2022-11-14 17:13:57,036 Test: [76/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0746 (0.0725) Prec@1 89.000 (88.442) Prec@5 100.000 (99.234) +2022-11-14 17:13:57,044 Test: [77/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0883 (0.0727) Prec@1 87.000 (88.423) Prec@5 100.000 (99.244) +2022-11-14 17:13:57,052 Test: [78/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0723 (0.0727) Prec@1 88.000 (88.418) Prec@5 100.000 (99.253) +2022-11-14 17:13:57,059 Test: [79/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0697 (0.0727) Prec@1 88.000 (88.412) Prec@5 100.000 (99.263) +2022-11-14 17:13:57,067 Test: [80/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0916 (0.0729) Prec@1 85.000 (88.370) Prec@5 99.000 (99.259) +2022-11-14 17:13:57,075 Test: [81/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0647 (0.0728) Prec@1 88.000 (88.366) Prec@5 100.000 (99.268) +2022-11-14 17:13:57,084 Test: [82/100] Model Time 0.007 (0.005) Loss Time 0.000 (0.000) Loss 0.0947 (0.0731) Prec@1 84.000 (88.313) Prec@5 100.000 (99.277) +2022-11-14 17:13:57,092 Test: [83/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0672 (0.0730) Prec@1 89.000 (88.321) Prec@5 99.000 (99.274) +2022-11-14 17:13:57,100 Test: [84/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0733 (0.0730) Prec@1 89.000 (88.329) Prec@5 100.000 (99.282) +2022-11-14 17:13:57,107 Test: [85/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0975 (0.0733) Prec@1 85.000 (88.291) Prec@5 100.000 (99.291) +2022-11-14 17:13:57,115 Test: [86/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0888 (0.0735) Prec@1 85.000 (88.253) Prec@5 99.000 (99.287) +2022-11-14 17:13:57,123 Test: [87/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0906 (0.0737) Prec@1 86.000 (88.227) Prec@5 99.000 (99.284) +2022-11-14 17:13:57,130 Test: [88/100] Model Time 0.006 (0.005) Loss Time 0.000 (0.000) Loss 0.0623 (0.0736) Prec@1 88.000 (88.225) Prec@5 100.000 (99.292) +2022-11-14 17:13:57,138 Test: [89/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0725 (0.0735) Prec@1 89.000 (88.233) Prec@5 100.000 (99.300) +2022-11-14 17:13:57,146 Test: [90/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0593 (0.0734) Prec@1 90.000 (88.253) Prec@5 99.000 (99.297) +2022-11-14 17:13:57,153 Test: [91/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0531 (0.0732) Prec@1 92.000 (88.293) Prec@5 100.000 (99.304) +2022-11-14 17:13:57,161 Test: [92/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0854 (0.0733) Prec@1 87.000 (88.280) Prec@5 99.000 (99.301) +2022-11-14 17:13:57,169 Test: [93/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0848 (0.0734) Prec@1 87.000 (88.266) Prec@5 98.000 (99.287) +2022-11-14 17:13:57,176 Test: [94/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0958 (0.0737) Prec@1 86.000 (88.242) Prec@5 99.000 (99.284) +2022-11-14 17:13:57,183 Test: [95/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0659 (0.0736) Prec@1 91.000 (88.271) Prec@5 99.000 (99.281) +2022-11-14 17:13:57,191 Test: [96/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0396 (0.0732) Prec@1 94.000 (88.330) Prec@5 98.000 (99.268) +2022-11-14 17:13:57,199 Test: [97/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1042 (0.0735) Prec@1 85.000 (88.296) Prec@5 97.000 (99.245) +2022-11-14 17:13:57,206 Test: [98/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.1039 (0.0738) Prec@1 84.000 (88.253) Prec@5 98.000 (99.232) +2022-11-14 17:13:57,213 Test: [99/100] Model Time 0.005 (0.005) Loss Time 0.000 (0.000) Loss 0.0583 (0.0737) Prec@1 90.000 (88.270) Prec@5 100.000 (99.240) +2022-11-14 17:13:57,268 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:13:57,584 Epoch: [496][0/500] Time 0.022 (0.022) Data 0.238 (0.238) Loss 0.0215 (0.0215) Prec@1 95.000 (95.000) Prec@5 100.000 (100.000) +2022-11-14 17:13:57,776 Epoch: [496][10/500] Time 0.017 (0.017) Data 0.001 (0.023) Loss 0.0335 (0.0275) Prec@1 94.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:13:57,983 Epoch: [496][20/500] Time 0.015 (0.018) Data 0.002 (0.013) Loss 0.0468 (0.0339) Prec@1 94.000 (94.333) Prec@5 100.000 (100.000) +2022-11-14 17:13:58,177 Epoch: [496][30/500] Time 0.017 (0.018) Data 0.002 (0.009) Loss 0.0252 (0.0317) Prec@1 96.000 (94.750) Prec@5 99.000 (99.750) +2022-11-14 17:13:58,366 Epoch: [496][40/500] Time 0.015 (0.017) Data 0.001 (0.007) Loss 0.0125 (0.0279) Prec@1 98.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:13:58,557 Epoch: [496][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0385 (0.0297) Prec@1 93.000 (95.000) Prec@5 100.000 (99.833) +2022-11-14 17:13:58,746 Epoch: [496][60/500] Time 0.016 (0.017) Data 0.001 (0.006) Loss 0.0281 (0.0294) Prec@1 95.000 (95.000) Prec@5 100.000 (99.857) +2022-11-14 17:13:58,937 Epoch: [496][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0307 (0.0296) Prec@1 97.000 (95.250) Prec@5 100.000 (99.875) +2022-11-14 17:13:59,128 Epoch: [496][80/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0195 (0.0285) Prec@1 97.000 (95.444) Prec@5 100.000 (99.889) +2022-11-14 17:13:59,318 Epoch: [496][90/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0335 (0.0290) Prec@1 93.000 (95.200) Prec@5 100.000 (99.900) +2022-11-14 17:13:59,507 Epoch: [496][100/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0117 (0.0274) Prec@1 98.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:13:59,696 Epoch: [496][110/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0300 (0.0276) Prec@1 95.000 (95.417) Prec@5 100.000 (99.917) +2022-11-14 17:13:59,940 Epoch: [496][120/500] Time 0.027 (0.017) Data 0.001 (0.004) Loss 0.0363 (0.0283) Prec@1 93.000 (95.231) Prec@5 100.000 (99.923) +2022-11-14 17:14:00,238 Epoch: [496][130/500] Time 0.029 (0.018) Data 0.001 (0.003) Loss 0.0120 (0.0271) Prec@1 99.000 (95.500) Prec@5 100.000 (99.929) +2022-11-14 17:14:00,541 Epoch: [496][140/500] Time 0.029 (0.019) Data 0.002 (0.003) Loss 0.0160 (0.0264) Prec@1 97.000 (95.600) Prec@5 100.000 (99.933) +2022-11-14 17:14:00,847 Epoch: [496][150/500] Time 0.027 (0.019) Data 0.002 (0.003) Loss 0.0280 (0.0265) Prec@1 97.000 (95.688) Prec@5 100.000 (99.938) +2022-11-14 17:14:01,155 Epoch: [496][160/500] Time 0.027 (0.020) Data 0.002 (0.003) Loss 0.0216 (0.0262) Prec@1 97.000 (95.765) Prec@5 100.000 (99.941) +2022-11-14 17:14:01,458 Epoch: [496][170/500] Time 0.028 (0.020) Data 0.002 (0.003) Loss 0.0171 (0.0257) Prec@1 97.000 (95.833) Prec@5 100.000 (99.944) +2022-11-14 17:14:01,762 Epoch: [496][180/500] Time 0.029 (0.020) Data 0.002 (0.003) Loss 0.0383 (0.0263) Prec@1 93.000 (95.684) Prec@5 98.000 (99.842) +2022-11-14 17:14:02,065 Epoch: [496][190/500] Time 0.028 (0.021) Data 0.001 (0.003) Loss 0.0376 (0.0269) Prec@1 93.000 (95.550) Prec@5 100.000 (99.850) +2022-11-14 17:14:02,367 Epoch: [496][200/500] Time 0.031 (0.021) Data 0.001 (0.003) Loss 0.0360 (0.0273) Prec@1 95.000 (95.524) Prec@5 100.000 (99.857) +2022-11-14 17:14:02,668 Epoch: [496][210/500] Time 0.028 (0.021) Data 0.002 (0.003) Loss 0.0258 (0.0273) Prec@1 95.000 (95.500) Prec@5 100.000 (99.864) +2022-11-14 17:14:02,967 Epoch: [496][220/500] Time 0.031 (0.022) Data 0.002 (0.003) Loss 0.0217 (0.0270) Prec@1 97.000 (95.565) Prec@5 100.000 (99.870) +2022-11-14 17:14:03,264 Epoch: [496][230/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0419 (0.0277) Prec@1 93.000 (95.458) Prec@5 99.000 (99.833) +2022-11-14 17:14:03,564 Epoch: [496][240/500] Time 0.028 (0.022) Data 0.002 (0.003) Loss 0.0205 (0.0274) Prec@1 96.000 (95.480) Prec@5 100.000 (99.840) +2022-11-14 17:14:03,858 Epoch: [496][250/500] Time 0.027 (0.022) Data 0.001 (0.003) Loss 0.0493 (0.0282) Prec@1 92.000 (95.346) Prec@5 99.000 (99.808) +2022-11-14 17:14:04,156 Epoch: [496][260/500] Time 0.026 (0.022) Data 0.002 (0.003) Loss 0.0222 (0.0280) Prec@1 97.000 (95.407) Prec@5 100.000 (99.815) +2022-11-14 17:14:04,449 Epoch: [496][270/500] Time 0.027 (0.022) Data 0.002 (0.003) Loss 0.0340 (0.0282) Prec@1 94.000 (95.357) Prec@5 99.000 (99.786) +2022-11-14 17:14:04,741 Epoch: [496][280/500] Time 0.028 (0.023) Data 0.002 (0.003) Loss 0.0218 (0.0280) Prec@1 96.000 (95.379) Prec@5 100.000 (99.793) +2022-11-14 17:14:05,039 Epoch: [496][290/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0288 (0.0280) Prec@1 96.000 (95.400) Prec@5 100.000 (99.800) +2022-11-14 17:14:05,333 Epoch: [496][300/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0231 (0.0279) Prec@1 95.000 (95.387) Prec@5 100.000 (99.806) +2022-11-14 17:14:05,629 Epoch: [496][310/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0293 (0.0279) Prec@1 97.000 (95.438) Prec@5 100.000 (99.812) +2022-11-14 17:14:05,928 Epoch: [496][320/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0523 (0.0286) Prec@1 93.000 (95.364) Prec@5 98.000 (99.758) +2022-11-14 17:14:06,224 Epoch: [496][330/500] Time 0.026 (0.023) Data 0.002 (0.002) Loss 0.0383 (0.0289) Prec@1 93.000 (95.294) Prec@5 100.000 (99.765) +2022-11-14 17:14:06,520 Epoch: [496][340/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0292 (0.0289) Prec@1 96.000 (95.314) Prec@5 100.000 (99.771) +2022-11-14 17:14:06,818 Epoch: [496][350/500] Time 0.029 (0.023) Data 0.001 (0.002) Loss 0.0313 (0.0290) Prec@1 95.000 (95.306) Prec@5 100.000 (99.778) +2022-11-14 17:14:07,114 Epoch: [496][360/500] Time 0.032 (0.023) Data 0.002 (0.002) Loss 0.0304 (0.0290) Prec@1 95.000 (95.297) Prec@5 100.000 (99.784) +2022-11-14 17:14:07,409 Epoch: [496][370/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0170 (0.0287) Prec@1 98.000 (95.368) Prec@5 100.000 (99.789) +2022-11-14 17:14:07,703 Epoch: [496][380/500] Time 0.028 (0.023) Data 0.002 (0.002) Loss 0.0217 (0.0285) Prec@1 96.000 (95.385) Prec@5 100.000 (99.795) +2022-11-14 17:14:07,993 Epoch: [496][390/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0323 (0.0286) Prec@1 94.000 (95.350) Prec@5 100.000 (99.800) +2022-11-14 17:14:08,293 Epoch: [496][400/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0461 (0.0291) Prec@1 94.000 (95.317) Prec@5 100.000 (99.805) +2022-11-14 17:14:08,588 Epoch: [496][410/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0217 (0.0289) Prec@1 97.000 (95.357) Prec@5 100.000 (99.810) +2022-11-14 17:14:08,887 Epoch: [496][420/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0239 (0.0288) Prec@1 97.000 (95.395) Prec@5 100.000 (99.814) +2022-11-14 17:14:09,182 Epoch: [496][430/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0257 (0.0287) Prec@1 96.000 (95.409) Prec@5 100.000 (99.818) +2022-11-14 17:14:09,472 Epoch: [496][440/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0391 (0.0289) Prec@1 94.000 (95.378) Prec@5 100.000 (99.822) +2022-11-14 17:14:09,764 Epoch: [496][450/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0222 (0.0288) Prec@1 97.000 (95.413) Prec@5 100.000 (99.826) +2022-11-14 17:14:10,056 Epoch: [496][460/500] Time 0.027 (0.024) Data 0.001 (0.002) Loss 0.0339 (0.0289) Prec@1 93.000 (95.362) Prec@5 99.000 (99.809) +2022-11-14 17:14:10,349 Epoch: [496][470/500] Time 0.028 (0.024) Data 0.002 (0.002) Loss 0.0132 (0.0286) Prec@1 98.000 (95.417) Prec@5 100.000 (99.812) +2022-11-14 17:14:10,641 Epoch: [496][480/500] Time 0.027 (0.024) Data 0.002 (0.002) Loss 0.0239 (0.0285) Prec@1 96.000 (95.429) Prec@5 100.000 (99.816) +2022-11-14 17:14:10,935 Epoch: [496][490/500] Time 0.029 (0.024) Data 0.002 (0.002) Loss 0.0194 (0.0283) Prec@1 98.000 (95.480) Prec@5 100.000 (99.820) +2022-11-14 17:14:11,202 Epoch: [496][499/500] Time 0.028 (0.024) Data 0.001 (0.002) Loss 0.0336 (0.0284) Prec@1 96.000 (95.490) Prec@5 100.000 (99.824) +2022-11-14 17:14:11,500 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0593 (0.0593) Prec@1 91.000 (91.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:11,508 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0701 (0.0647) Prec@1 89.000 (90.000) Prec@5 99.000 (99.500) +2022-11-14 17:14:11,517 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0629 (0.0641) Prec@1 89.000 (89.667) Prec@5 100.000 (99.667) +2022-11-14 17:14:11,526 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0698 (0.0655) Prec@1 89.000 (89.500) Prec@5 99.000 (99.500) +2022-11-14 17:14:11,533 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0937 (0.0712) Prec@1 84.000 (88.400) Prec@5 98.000 (99.200) +2022-11-14 17:14:11,540 Test: [5/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0362 (0.0653) Prec@1 96.000 (89.667) Prec@5 100.000 (99.333) +2022-11-14 17:14:11,547 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0658 (0.0654) Prec@1 90.000 (89.714) Prec@5 99.000 (99.286) +2022-11-14 17:14:11,556 Test: [7/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0689 (0.0658) Prec@1 89.000 (89.625) Prec@5 99.000 (99.250) +2022-11-14 17:14:11,563 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0839 (0.0678) Prec@1 89.000 (89.556) Prec@5 97.000 (99.000) +2022-11-14 17:14:11,570 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0694) Prec@1 87.000 (89.300) Prec@5 98.000 (98.900) +2022-11-14 17:14:11,577 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0387 (0.0666) Prec@1 94.000 (89.727) Prec@5 100.000 (99.000) +2022-11-14 17:14:11,585 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0933 (0.0688) Prec@1 87.000 (89.500) Prec@5 99.000 (99.000) +2022-11-14 17:14:11,593 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0686 (0.0688) Prec@1 88.000 (89.385) Prec@5 100.000 (99.077) +2022-11-14 17:14:11,601 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0686) Prec@1 89.000 (89.357) Prec@5 99.000 (99.071) +2022-11-14 17:14:11,609 Test: [14/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0688) Prec@1 88.000 (89.267) Prec@5 99.000 (99.067) +2022-11-14 17:14:11,616 Test: [15/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0689) Prec@1 89.000 (89.250) Prec@5 99.000 (99.062) +2022-11-14 17:14:11,624 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0467 (0.0676) Prec@1 94.000 (89.529) Prec@5 97.000 (98.941) +2022-11-14 17:14:11,633 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1190 (0.0704) Prec@1 84.000 (89.222) Prec@5 100.000 (99.000) +2022-11-14 17:14:11,641 Test: [18/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0710) Prec@1 89.000 (89.211) Prec@5 97.000 (98.895) +2022-11-14 17:14:11,649 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0958 (0.0723) Prec@1 85.000 (89.000) Prec@5 97.000 (98.800) +2022-11-14 17:14:11,657 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0856 (0.0729) Prec@1 84.000 (88.762) Prec@5 100.000 (98.857) +2022-11-14 17:14:11,665 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0742) Prec@1 86.000 (88.636) Prec@5 97.000 (98.773) +2022-11-14 17:14:11,673 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1133 (0.0759) Prec@1 86.000 (88.522) Prec@5 95.000 (98.609) +2022-11-14 17:14:11,681 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0721 (0.0757) Prec@1 90.000 (88.583) Prec@5 99.000 (98.625) +2022-11-14 17:14:11,688 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0755) Prec@1 89.000 (88.600) Prec@5 100.000 (98.680) +2022-11-14 17:14:11,696 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0990 (0.0764) Prec@1 87.000 (88.538) Prec@5 98.000 (98.654) +2022-11-14 17:14:11,704 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0758) Prec@1 90.000 (88.593) Prec@5 99.000 (98.667) +2022-11-14 17:14:11,712 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0670 (0.0755) Prec@1 87.000 (88.536) Prec@5 99.000 (98.679) +2022-11-14 17:14:11,720 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0752) Prec@1 88.000 (88.517) Prec@5 99.000 (98.690) +2022-11-14 17:14:11,728 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0755) Prec@1 85.000 (88.400) Prec@5 100.000 (98.733) +2022-11-14 17:14:11,736 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0749) Prec@1 89.000 (88.419) Prec@5 100.000 (98.774) +2022-11-14 17:14:11,744 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0747 (0.0749) Prec@1 90.000 (88.469) Prec@5 99.000 (98.781) +2022-11-14 17:14:11,751 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0752) Prec@1 86.000 (88.394) Prec@5 99.000 (98.788) +2022-11-14 17:14:11,760 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0715 (0.0751) Prec@1 90.000 (88.441) Prec@5 98.000 (98.765) +2022-11-14 17:14:11,767 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0851 (0.0754) Prec@1 87.000 (88.400) Prec@5 97.000 (98.714) +2022-11-14 17:14:11,775 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0720 (0.0753) Prec@1 87.000 (88.361) Prec@5 99.000 (98.722) +2022-11-14 17:14:11,783 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0755) Prec@1 85.000 (88.270) Prec@5 98.000 (98.703) +2022-11-14 17:14:11,791 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0764) Prec@1 83.000 (88.132) Prec@5 98.000 (98.684) +2022-11-14 17:14:11,798 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0760) Prec@1 92.000 (88.231) Prec@5 99.000 (98.692) +2022-11-14 17:14:11,806 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0897 (0.0763) Prec@1 85.000 (88.150) Prec@5 98.000 (98.675) +2022-11-14 17:14:11,814 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0763) Prec@1 90.000 (88.195) Prec@5 99.000 (98.683) +2022-11-14 17:14:11,822 Test: [41/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0729 (0.0763) Prec@1 89.000 (88.214) Prec@5 99.000 (98.690) +2022-11-14 17:14:11,829 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0758) Prec@1 91.000 (88.279) Prec@5 99.000 (98.698) +2022-11-14 17:14:11,837 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0713 (0.0757) Prec@1 91.000 (88.341) Prec@5 97.000 (98.659) +2022-11-14 17:14:11,845 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0763 (0.0757) Prec@1 88.000 (88.333) Prec@5 99.000 (98.667) +2022-11-14 17:14:11,853 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0922 (0.0761) Prec@1 86.000 (88.283) Prec@5 100.000 (98.696) +2022-11-14 17:14:11,860 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0749 (0.0760) Prec@1 87.000 (88.255) Prec@5 100.000 (98.723) +2022-11-14 17:14:11,868 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0762) Prec@1 85.000 (88.188) Prec@5 98.000 (98.708) +2022-11-14 17:14:11,876 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0466 (0.0756) Prec@1 91.000 (88.245) Prec@5 100.000 (98.735) +2022-11-14 17:14:11,883 Test: [49/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0910 (0.0759) Prec@1 87.000 (88.220) Prec@5 100.000 (98.760) +2022-11-14 17:14:11,890 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0649 (0.0757) Prec@1 89.000 (88.235) Prec@5 100.000 (98.784) +2022-11-14 17:14:11,898 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0935 (0.0760) Prec@1 84.000 (88.154) Prec@5 99.000 (98.788) +2022-11-14 17:14:11,906 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0735 (0.0760) Prec@1 88.000 (88.151) Prec@5 100.000 (98.811) +2022-11-14 17:14:11,913 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0760) Prec@1 87.000 (88.130) Prec@5 100.000 (98.833) +2022-11-14 17:14:11,921 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0645 (0.0758) Prec@1 91.000 (88.182) Prec@5 100.000 (98.855) +2022-11-14 17:14:11,928 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0758) Prec@1 89.000 (88.196) Prec@5 99.000 (98.857) +2022-11-14 17:14:11,936 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0754) Prec@1 90.000 (88.228) Prec@5 100.000 (98.877) +2022-11-14 17:14:11,944 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0755) Prec@1 88.000 (88.224) Prec@5 100.000 (98.897) +2022-11-14 17:14:11,952 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0810 (0.0756) Prec@1 89.000 (88.237) Prec@5 100.000 (98.915) +2022-11-14 17:14:11,959 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0792 (0.0757) Prec@1 87.000 (88.217) Prec@5 100.000 (98.933) +2022-11-14 17:14:11,967 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0775 (0.0757) Prec@1 88.000 (88.213) Prec@5 99.000 (98.934) +2022-11-14 17:14:11,974 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0755) Prec@1 89.000 (88.226) Prec@5 99.000 (98.935) +2022-11-14 17:14:11,982 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0687 (0.0754) Prec@1 89.000 (88.238) Prec@5 100.000 (98.952) +2022-11-14 17:14:11,990 Test: [63/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0749) Prec@1 94.000 (88.328) Prec@5 100.000 (98.969) +2022-11-14 17:14:11,998 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0825 (0.0750) Prec@1 87.000 (88.308) Prec@5 99.000 (98.969) +2022-11-14 17:14:12,005 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0749) Prec@1 88.000 (88.303) Prec@5 99.000 (98.970) +2022-11-14 17:14:12,013 Test: [66/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0503 (0.0745) Prec@1 91.000 (88.343) Prec@5 99.000 (98.970) +2022-11-14 17:14:12,021 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0622 (0.0744) Prec@1 90.000 (88.368) Prec@5 99.000 (98.971) +2022-11-14 17:14:12,029 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0696 (0.0743) Prec@1 88.000 (88.362) Prec@5 99.000 (98.971) +2022-11-14 17:14:12,037 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0868 (0.0745) Prec@1 89.000 (88.371) Prec@5 99.000 (98.971) +2022-11-14 17:14:12,044 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0964 (0.0748) Prec@1 87.000 (88.352) Prec@5 99.000 (98.972) +2022-11-14 17:14:12,052 Test: [71/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0745) Prec@1 91.000 (88.389) Prec@5 100.000 (98.986) +2022-11-14 17:14:12,060 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0744) Prec@1 91.000 (88.425) Prec@5 99.000 (98.986) +2022-11-14 17:14:12,068 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0741) Prec@1 91.000 (88.459) Prec@5 100.000 (99.000) +2022-11-14 17:14:12,076 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0993 (0.0744) Prec@1 83.000 (88.387) Prec@5 100.000 (99.013) +2022-11-14 17:14:12,085 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0743) Prec@1 90.000 (88.408) Prec@5 99.000 (99.013) +2022-11-14 17:14:12,093 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0743) Prec@1 88.000 (88.403) Prec@5 100.000 (99.026) +2022-11-14 17:14:12,101 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0744) Prec@1 87.000 (88.385) Prec@5 98.000 (99.013) +2022-11-14 17:14:12,108 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0744) Prec@1 89.000 (88.392) Prec@5 100.000 (99.025) +2022-11-14 17:14:12,117 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0784 (0.0745) Prec@1 86.000 (88.362) Prec@5 100.000 (99.037) +2022-11-14 17:14:12,124 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0893 (0.0747) Prec@1 86.000 (88.333) Prec@5 98.000 (99.025) +2022-11-14 17:14:12,132 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0746) Prec@1 88.000 (88.329) Prec@5 100.000 (99.037) +2022-11-14 17:14:12,140 Test: [82/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0904 (0.0748) Prec@1 88.000 (88.325) Prec@5 99.000 (99.036) +2022-11-14 17:14:12,148 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0638 (0.0747) Prec@1 90.000 (88.345) Prec@5 100.000 (99.048) +2022-11-14 17:14:12,155 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0750) Prec@1 84.000 (88.294) Prec@5 99.000 (99.047) +2022-11-14 17:14:12,163 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0752) Prec@1 87.000 (88.279) Prec@5 99.000 (99.047) +2022-11-14 17:14:12,171 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0923 (0.0754) Prec@1 87.000 (88.264) Prec@5 99.000 (99.046) +2022-11-14 17:14:12,179 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0755) Prec@1 89.000 (88.273) Prec@5 98.000 (99.034) +2022-11-14 17:14:12,186 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0811 (0.0755) Prec@1 86.000 (88.247) Prec@5 100.000 (99.045) +2022-11-14 17:14:12,194 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0754) Prec@1 92.000 (88.289) Prec@5 100.000 (99.056) +2022-11-14 17:14:12,202 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0639 (0.0753) Prec@1 92.000 (88.330) Prec@5 100.000 (99.066) +2022-11-14 17:14:12,210 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0626 (0.0751) Prec@1 89.000 (88.337) Prec@5 99.000 (99.065) +2022-11-14 17:14:12,217 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0753) Prec@1 87.000 (88.323) Prec@5 100.000 (99.075) +2022-11-14 17:14:12,225 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0677 (0.0752) Prec@1 90.000 (88.340) Prec@5 97.000 (99.053) +2022-11-14 17:14:12,233 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0997 (0.0755) Prec@1 83.000 (88.284) Prec@5 99.000 (99.053) +2022-11-14 17:14:12,240 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0601 (0.0753) Prec@1 90.000 (88.302) Prec@5 99.000 (99.052) +2022-11-14 17:14:12,248 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0751) Prec@1 92.000 (88.340) Prec@5 98.000 (99.041) +2022-11-14 17:14:12,255 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0813 (0.0751) Prec@1 87.000 (88.327) Prec@5 99.000 (99.041) +2022-11-14 17:14:12,263 Test: [98/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0754) Prec@1 86.000 (88.303) Prec@5 99.000 (99.040) +2022-11-14 17:14:12,271 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0693 (0.0753) Prec@1 90.000 (88.320) Prec@5 100.000 (99.050) +2022-11-14 17:14:12,325 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:14:12,668 Epoch: [497][0/500] Time 0.032 (0.032) Data 0.258 (0.258) Loss 0.0065 (0.0065) Prec@1 100.000 (100.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:12,865 Epoch: [497][10/500] Time 0.017 (0.019) Data 0.002 (0.025) Loss 0.0130 (0.0097) Prec@1 98.000 (99.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:13,053 Epoch: [497][20/500] Time 0.017 (0.018) Data 0.001 (0.014) Loss 0.0258 (0.0151) Prec@1 95.000 (97.667) Prec@5 100.000 (100.000) +2022-11-14 17:14:13,244 Epoch: [497][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0286 (0.0185) Prec@1 96.000 (97.250) Prec@5 100.000 (100.000) +2022-11-14 17:14:13,431 Epoch: [497][40/500] Time 0.017 (0.017) Data 0.001 (0.008) Loss 0.0260 (0.0200) Prec@1 96.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:13,625 Epoch: [497][50/500] Time 0.019 (0.017) Data 0.001 (0.007) Loss 0.0459 (0.0243) Prec@1 92.000 (96.167) Prec@5 100.000 (100.000) +2022-11-14 17:14:13,813 Epoch: [497][60/500] Time 0.016 (0.017) Data 0.002 (0.006) Loss 0.0519 (0.0282) Prec@1 93.000 (95.714) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,003 Epoch: [497][70/500] Time 0.020 (0.017) Data 0.001 (0.005) Loss 0.0163 (0.0268) Prec@1 97.000 (95.875) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,194 Epoch: [497][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0277 (0.0269) Prec@1 96.000 (95.889) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,383 Epoch: [497][90/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0318 (0.0273) Prec@1 94.000 (95.700) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,571 Epoch: [497][100/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0230 (0.0269) Prec@1 97.000 (95.818) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,760 Epoch: [497][110/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0156 (0.0260) Prec@1 97.000 (95.917) Prec@5 100.000 (100.000) +2022-11-14 17:14:14,955 Epoch: [497][120/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0234 (0.0258) Prec@1 95.000 (95.846) Prec@5 100.000 (100.000) +2022-11-14 17:14:15,148 Epoch: [497][130/500] Time 0.020 (0.017) Data 0.001 (0.004) Loss 0.0056 (0.0244) Prec@1 100.000 (96.143) Prec@5 100.000 (100.000) +2022-11-14 17:14:15,335 Epoch: [497][140/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0167 (0.0238) Prec@1 97.000 (96.200) Prec@5 99.000 (99.933) +2022-11-14 17:14:15,530 Epoch: [497][150/500] Time 0.021 (0.017) Data 0.002 (0.003) Loss 0.0336 (0.0245) Prec@1 93.000 (96.000) Prec@5 99.000 (99.875) +2022-11-14 17:14:15,731 Epoch: [497][160/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0365 (0.0252) Prec@1 95.000 (95.941) Prec@5 100.000 (99.882) +2022-11-14 17:14:15,934 Epoch: [497][170/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0353 (0.0257) Prec@1 92.000 (95.722) Prec@5 100.000 (99.889) +2022-11-14 17:14:16,134 Epoch: [497][180/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0310 (0.0260) Prec@1 94.000 (95.632) Prec@5 100.000 (99.895) +2022-11-14 17:14:16,338 Epoch: [497][190/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0489 (0.0272) Prec@1 93.000 (95.500) Prec@5 100.000 (99.900) +2022-11-14 17:14:16,541 Epoch: [497][200/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0326 (0.0274) Prec@1 95.000 (95.476) Prec@5 100.000 (99.905) +2022-11-14 17:14:16,735 Epoch: [497][210/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0217 (0.0272) Prec@1 97.000 (95.545) Prec@5 100.000 (99.909) +2022-11-14 17:14:16,930 Epoch: [497][220/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0117 (0.0265) Prec@1 98.000 (95.652) Prec@5 100.000 (99.913) +2022-11-14 17:14:17,201 Epoch: [497][230/500] Time 0.027 (0.017) Data 0.002 (0.003) Loss 0.0331 (0.0268) Prec@1 95.000 (95.625) Prec@5 100.000 (99.917) +2022-11-14 17:14:17,504 Epoch: [497][240/500] Time 0.029 (0.018) Data 0.001 (0.003) Loss 0.0263 (0.0267) Prec@1 96.000 (95.640) Prec@5 100.000 (99.920) +2022-11-14 17:14:17,810 Epoch: [497][250/500] Time 0.032 (0.018) Data 0.001 (0.003) Loss 0.0214 (0.0265) Prec@1 98.000 (95.731) Prec@5 100.000 (99.923) +2022-11-14 17:14:18,123 Epoch: [497][260/500] Time 0.035 (0.019) Data 0.002 (0.003) Loss 0.0376 (0.0269) Prec@1 94.000 (95.667) Prec@5 100.000 (99.926) +2022-11-14 17:14:18,434 Epoch: [497][270/500] Time 0.035 (0.019) Data 0.001 (0.003) Loss 0.0133 (0.0265) Prec@1 97.000 (95.714) Prec@5 100.000 (99.929) +2022-11-14 17:14:18,749 Epoch: [497][280/500] Time 0.030 (0.019) Data 0.002 (0.003) Loss 0.0222 (0.0263) Prec@1 97.000 (95.759) Prec@5 100.000 (99.931) +2022-11-14 17:14:19,062 Epoch: [497][290/500] Time 0.032 (0.020) Data 0.001 (0.003) Loss 0.0183 (0.0260) Prec@1 97.000 (95.800) Prec@5 100.000 (99.933) +2022-11-14 17:14:19,375 Epoch: [497][300/500] Time 0.029 (0.020) Data 0.002 (0.002) Loss 0.0239 (0.0260) Prec@1 97.000 (95.839) Prec@5 100.000 (99.935) +2022-11-14 17:14:19,675 Epoch: [497][310/500] Time 0.032 (0.020) Data 0.001 (0.002) Loss 0.0309 (0.0261) Prec@1 95.000 (95.812) Prec@5 100.000 (99.938) +2022-11-14 17:14:19,982 Epoch: [497][320/500] Time 0.028 (0.020) Data 0.002 (0.002) Loss 0.0191 (0.0259) Prec@1 96.000 (95.818) Prec@5 100.000 (99.939) +2022-11-14 17:14:20,282 Epoch: [497][330/500] Time 0.032 (0.020) Data 0.001 (0.002) Loss 0.0379 (0.0263) Prec@1 95.000 (95.794) Prec@5 100.000 (99.941) +2022-11-14 17:14:20,582 Epoch: [497][340/500] Time 0.029 (0.021) Data 0.002 (0.002) Loss 0.0377 (0.0266) Prec@1 94.000 (95.743) Prec@5 100.000 (99.943) +2022-11-14 17:14:20,881 Epoch: [497][350/500] Time 0.032 (0.021) Data 0.001 (0.002) Loss 0.0283 (0.0266) Prec@1 95.000 (95.722) Prec@5 100.000 (99.944) +2022-11-14 17:14:21,190 Epoch: [497][360/500] Time 0.029 (0.021) Data 0.002 (0.002) Loss 0.0071 (0.0261) Prec@1 100.000 (95.838) Prec@5 100.000 (99.946) +2022-11-14 17:14:21,492 Epoch: [497][370/500] Time 0.033 (0.021) Data 0.001 (0.002) Loss 0.0271 (0.0261) Prec@1 96.000 (95.842) Prec@5 100.000 (99.947) +2022-11-14 17:14:21,801 Epoch: [497][380/500] Time 0.029 (0.021) Data 0.001 (0.002) Loss 0.0164 (0.0259) Prec@1 98.000 (95.897) Prec@5 100.000 (99.949) +2022-11-14 17:14:22,106 Epoch: [497][390/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0129 (0.0256) Prec@1 98.000 (95.950) Prec@5 100.000 (99.950) +2022-11-14 17:14:22,405 Epoch: [497][400/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0417 (0.0260) Prec@1 93.000 (95.878) Prec@5 100.000 (99.951) +2022-11-14 17:14:22,712 Epoch: [497][410/500] Time 0.032 (0.022) Data 0.002 (0.002) Loss 0.0430 (0.0264) Prec@1 94.000 (95.833) Prec@5 100.000 (99.952) +2022-11-14 17:14:23,018 Epoch: [497][420/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0207 (0.0262) Prec@1 96.000 (95.837) Prec@5 100.000 (99.953) +2022-11-14 17:14:23,326 Epoch: [497][430/500] Time 0.030 (0.022) Data 0.002 (0.002) Loss 0.0221 (0.0261) Prec@1 97.000 (95.864) Prec@5 100.000 (99.955) +2022-11-14 17:14:23,635 Epoch: [497][440/500] Time 0.031 (0.022) Data 0.001 (0.002) Loss 0.0393 (0.0264) Prec@1 92.000 (95.778) Prec@5 99.000 (99.933) +2022-11-14 17:14:23,931 Epoch: [497][450/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0259 (0.0264) Prec@1 94.000 (95.739) Prec@5 100.000 (99.935) +2022-11-14 17:14:24,231 Epoch: [497][460/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0224 (0.0263) Prec@1 97.000 (95.766) Prec@5 100.000 (99.936) +2022-11-14 17:14:24,532 Epoch: [497][470/500] Time 0.028 (0.022) Data 0.002 (0.002) Loss 0.0503 (0.0268) Prec@1 90.000 (95.646) Prec@5 100.000 (99.938) +2022-11-14 17:14:24,832 Epoch: [497][480/500] Time 0.029 (0.022) Data 0.002 (0.002) Loss 0.0384 (0.0271) Prec@1 93.000 (95.592) Prec@5 100.000 (99.939) +2022-11-14 17:14:25,133 Epoch: [497][490/500] Time 0.029 (0.023) Data 0.002 (0.002) Loss 0.0215 (0.0270) Prec@1 96.000 (95.600) Prec@5 100.000 (99.940) +2022-11-14 17:14:25,396 Epoch: [497][499/500] Time 0.027 (0.023) Data 0.002 (0.002) Loss 0.0352 (0.0271) Prec@1 94.000 (95.569) Prec@5 100.000 (99.941) +2022-11-14 17:14:25,687 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0619 (0.0619) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:25,696 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0885 (0.0752) Prec@1 87.000 (88.500) Prec@5 100.000 (100.000) +2022-11-14 17:14:25,702 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0717 (0.0740) Prec@1 86.000 (87.667) Prec@5 100.000 (100.000) +2022-11-14 17:14:25,712 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0733 (0.0738) Prec@1 88.000 (87.750) Prec@5 98.000 (99.500) +2022-11-14 17:14:25,719 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0565 (0.0704) Prec@1 90.000 (88.200) Prec@5 100.000 (99.600) +2022-11-14 17:14:25,726 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0482 (0.0667) Prec@1 92.000 (88.833) Prec@5 100.000 (99.667) +2022-11-14 17:14:25,733 Test: [6/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0523 (0.0646) Prec@1 91.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 17:14:25,742 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0665) Prec@1 86.000 (88.750) Prec@5 100.000 (99.750) +2022-11-14 17:14:25,749 Test: [8/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0800 (0.0680) Prec@1 89.000 (88.778) Prec@5 99.000 (99.667) +2022-11-14 17:14:25,757 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0707 (0.0682) Prec@1 89.000 (88.800) Prec@5 98.000 (99.500) +2022-11-14 17:14:25,765 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0426 (0.0659) Prec@1 91.000 (89.000) Prec@5 100.000 (99.545) +2022-11-14 17:14:25,772 Test: [11/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0963 (0.0685) Prec@1 85.000 (88.667) Prec@5 99.000 (99.500) +2022-11-14 17:14:25,780 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0435 (0.0665) Prec@1 94.000 (89.077) Prec@5 100.000 (99.538) +2022-11-14 17:14:25,788 Test: [13/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0679) Prec@1 87.000 (88.929) Prec@5 100.000 (99.571) +2022-11-14 17:14:25,796 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0733 (0.0683) Prec@1 88.000 (88.867) Prec@5 100.000 (99.600) +2022-11-14 17:14:25,803 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0688) Prec@1 87.000 (88.750) Prec@5 99.000 (99.562) +2022-11-14 17:14:25,811 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0719 (0.0690) Prec@1 90.000 (88.824) Prec@5 98.000 (99.471) +2022-11-14 17:14:25,819 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1080 (0.0712) Prec@1 84.000 (88.556) Prec@5 100.000 (99.500) +2022-11-14 17:14:25,827 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0874 (0.0720) Prec@1 84.000 (88.316) Prec@5 99.000 (99.474) +2022-11-14 17:14:25,834 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0794 (0.0724) Prec@1 89.000 (88.350) Prec@5 97.000 (99.350) +2022-11-14 17:14:25,842 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0729) Prec@1 86.000 (88.238) Prec@5 98.000 (99.286) +2022-11-14 17:14:25,849 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1042 (0.0744) Prec@1 85.000 (88.091) Prec@5 99.000 (99.273) +2022-11-14 17:14:25,857 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1126 (0.0760) Prec@1 85.000 (87.957) Prec@5 98.000 (99.217) +2022-11-14 17:14:25,865 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0787 (0.0761) Prec@1 85.000 (87.833) Prec@5 100.000 (99.250) +2022-11-14 17:14:25,872 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0705 (0.0759) Prec@1 89.000 (87.880) Prec@5 99.000 (99.240) +2022-11-14 17:14:25,880 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0764) Prec@1 86.000 (87.808) Prec@5 97.000 (99.154) +2022-11-14 17:14:25,888 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0550 (0.0756) Prec@1 90.000 (87.889) Prec@5 100.000 (99.185) +2022-11-14 17:14:25,895 Test: [27/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0434 (0.0745) Prec@1 93.000 (88.071) Prec@5 99.000 (99.179) +2022-11-14 17:14:25,903 Test: [28/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0743) Prec@1 89.000 (88.103) Prec@5 98.000 (99.138) +2022-11-14 17:14:25,911 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0746) Prec@1 86.000 (88.033) Prec@5 99.000 (99.133) +2022-11-14 17:14:25,918 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0747) Prec@1 88.000 (88.032) Prec@5 100.000 (99.161) +2022-11-14 17:14:25,926 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0741) Prec@1 92.000 (88.156) Prec@5 100.000 (99.188) +2022-11-14 17:14:25,934 Test: [32/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0837 (0.0744) Prec@1 87.000 (88.121) Prec@5 100.000 (99.212) +2022-11-14 17:14:25,941 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1036 (0.0752) Prec@1 83.000 (87.971) Prec@5 98.000 (99.176) +2022-11-14 17:14:25,949 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0753) Prec@1 87.000 (87.943) Prec@5 98.000 (99.143) +2022-11-14 17:14:25,957 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0599 (0.0748) Prec@1 92.000 (88.056) Prec@5 100.000 (99.167) +2022-11-14 17:14:25,964 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0750) Prec@1 87.000 (88.027) Prec@5 99.000 (99.162) +2022-11-14 17:14:25,972 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0753) Prec@1 84.000 (87.921) Prec@5 100.000 (99.184) +2022-11-14 17:14:25,980 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0749) Prec@1 94.000 (88.077) Prec@5 99.000 (99.179) +2022-11-14 17:14:25,988 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0791 (0.0750) Prec@1 86.000 (88.025) Prec@5 98.000 (99.150) +2022-11-14 17:14:25,996 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0832 (0.0752) Prec@1 88.000 (88.024) Prec@5 99.000 (99.146) +2022-11-14 17:14:26,003 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0613 (0.0748) Prec@1 91.000 (88.095) Prec@5 100.000 (99.167) +2022-11-14 17:14:26,011 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0548 (0.0744) Prec@1 91.000 (88.163) Prec@5 100.000 (99.186) +2022-11-14 17:14:26,019 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0605 (0.0741) Prec@1 90.000 (88.205) Prec@5 99.000 (99.182) +2022-11-14 17:14:26,027 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0478 (0.0735) Prec@1 91.000 (88.267) Prec@5 100.000 (99.200) +2022-11-14 17:14:26,036 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1038 (0.0741) Prec@1 83.000 (88.152) Prec@5 98.000 (99.174) +2022-11-14 17:14:26,043 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0592 (0.0738) Prec@1 90.000 (88.191) Prec@5 100.000 (99.191) +2022-11-14 17:14:26,051 Test: [47/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0985 (0.0743) Prec@1 84.000 (88.104) Prec@5 98.000 (99.167) +2022-11-14 17:14:26,059 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0628 (0.0741) Prec@1 89.000 (88.122) Prec@5 99.000 (99.163) +2022-11-14 17:14:26,066 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1015 (0.0746) Prec@1 85.000 (88.060) Prec@5 100.000 (99.180) +2022-11-14 17:14:26,074 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0753 (0.0747) Prec@1 88.000 (88.059) Prec@5 99.000 (99.176) +2022-11-14 17:14:26,083 Test: [51/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0746 (0.0747) Prec@1 86.000 (88.019) Prec@5 100.000 (99.192) +2022-11-14 17:14:26,091 Test: [52/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0712 (0.0746) Prec@1 88.000 (88.019) Prec@5 99.000 (99.189) +2022-11-14 17:14:26,099 Test: [53/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0751 (0.0746) Prec@1 89.000 (88.037) Prec@5 100.000 (99.204) +2022-11-14 17:14:26,107 Test: [54/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0944 (0.0750) Prec@1 87.000 (88.018) Prec@5 100.000 (99.218) +2022-11-14 17:14:26,114 Test: [55/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0563 (0.0746) Prec@1 92.000 (88.089) Prec@5 99.000 (99.214) +2022-11-14 17:14:26,122 Test: [56/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0679 (0.0745) Prec@1 87.000 (88.070) Prec@5 100.000 (99.228) +2022-11-14 17:14:26,130 Test: [57/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0793 (0.0746) Prec@1 90.000 (88.103) Prec@5 100.000 (99.241) +2022-11-14 17:14:26,137 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0955 (0.0749) Prec@1 86.000 (88.068) Prec@5 100.000 (99.254) +2022-11-14 17:14:26,145 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0789 (0.0750) Prec@1 87.000 (88.050) Prec@5 100.000 (99.267) +2022-11-14 17:14:26,153 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0821 (0.0751) Prec@1 89.000 (88.066) Prec@5 99.000 (99.262) +2022-11-14 17:14:26,160 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0505 (0.0747) Prec@1 94.000 (88.161) Prec@5 99.000 (99.258) +2022-11-14 17:14:26,168 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0744) Prec@1 91.000 (88.206) Prec@5 100.000 (99.270) +2022-11-14 17:14:26,176 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0477 (0.0739) Prec@1 92.000 (88.266) Prec@5 100.000 (99.281) +2022-11-14 17:14:26,184 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0987 (0.0743) Prec@1 86.000 (88.231) Prec@5 98.000 (99.262) +2022-11-14 17:14:26,191 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0586 (0.0741) Prec@1 89.000 (88.242) Prec@5 99.000 (99.258) +2022-11-14 17:14:26,199 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0516 (0.0737) Prec@1 92.000 (88.299) Prec@5 100.000 (99.269) +2022-11-14 17:14:26,207 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0690 (0.0737) Prec@1 90.000 (88.324) Prec@5 100.000 (99.279) +2022-11-14 17:14:26,215 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0931 (0.0740) Prec@1 85.000 (88.275) Prec@5 99.000 (99.275) +2022-11-14 17:14:26,222 Test: [69/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0740) Prec@1 87.000 (88.257) Prec@5 99.000 (99.271) +2022-11-14 17:14:26,230 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1118 (0.0745) Prec@1 85.000 (88.211) Prec@5 99.000 (99.268) +2022-11-14 17:14:26,238 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0450 (0.0741) Prec@1 93.000 (88.278) Prec@5 100.000 (99.278) +2022-11-14 17:14:26,245 Test: [72/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0738) Prec@1 92.000 (88.329) Prec@5 100.000 (99.288) +2022-11-14 17:14:26,253 Test: [73/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0736) Prec@1 90.000 (88.351) Prec@5 100.000 (99.297) +2022-11-14 17:14:26,261 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1078 (0.0740) Prec@1 83.000 (88.280) Prec@5 100.000 (99.307) +2022-11-14 17:14:26,269 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0644 (0.0739) Prec@1 90.000 (88.303) Prec@5 100.000 (99.316) +2022-11-14 17:14:26,276 Test: [76/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1047 (0.0743) Prec@1 84.000 (88.247) Prec@5 98.000 (99.299) +2022-11-14 17:14:26,284 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0745) Prec@1 86.000 (88.218) Prec@5 97.000 (99.269) +2022-11-14 17:14:26,292 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0745) Prec@1 88.000 (88.215) Prec@5 100.000 (99.278) +2022-11-14 17:14:26,299 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0741 (0.0745) Prec@1 89.000 (88.225) Prec@5 100.000 (99.287) +2022-11-14 17:14:26,307 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0748) Prec@1 83.000 (88.160) Prec@5 99.000 (99.284) +2022-11-14 17:14:26,315 Test: [81/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0751) Prec@1 85.000 (88.122) Prec@5 99.000 (99.280) +2022-11-14 17:14:26,323 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0865 (0.0753) Prec@1 87.000 (88.108) Prec@5 99.000 (99.277) +2022-11-14 17:14:26,331 Test: [83/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0751) Prec@1 91.000 (88.143) Prec@5 99.000 (99.274) +2022-11-14 17:14:26,338 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1033 (0.0754) Prec@1 82.000 (88.071) Prec@5 99.000 (99.271) +2022-11-14 17:14:26,346 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0755) Prec@1 88.000 (88.070) Prec@5 99.000 (99.267) +2022-11-14 17:14:26,354 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0728 (0.0755) Prec@1 88.000 (88.069) Prec@5 100.000 (99.276) +2022-11-14 17:14:26,361 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0780 (0.0755) Prec@1 89.000 (88.080) Prec@5 99.000 (99.273) +2022-11-14 17:14:26,369 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0888 (0.0756) Prec@1 86.000 (88.056) Prec@5 100.000 (99.281) +2022-11-14 17:14:26,377 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0615 (0.0755) Prec@1 91.000 (88.089) Prec@5 100.000 (99.289) +2022-11-14 17:14:26,384 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0752) Prec@1 91.000 (88.121) Prec@5 100.000 (99.297) +2022-11-14 17:14:26,392 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0478 (0.0749) Prec@1 93.000 (88.174) Prec@5 100.000 (99.304) +2022-11-14 17:14:26,400 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0751) Prec@1 85.000 (88.140) Prec@5 100.000 (99.312) +2022-11-14 17:14:26,408 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0701 (0.0751) Prec@1 90.000 (88.160) Prec@5 99.000 (99.309) +2022-11-14 17:14:26,415 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0752) Prec@1 86.000 (88.137) Prec@5 99.000 (99.305) +2022-11-14 17:14:26,423 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0769 (0.0752) Prec@1 87.000 (88.125) Prec@5 98.000 (99.292) +2022-11-14 17:14:26,431 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0557 (0.0750) Prec@1 93.000 (88.175) Prec@5 99.000 (99.289) +2022-11-14 17:14:26,439 Test: [97/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0660 (0.0750) Prec@1 90.000 (88.194) Prec@5 99.000 (99.286) +2022-11-14 17:14:26,446 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0974 (0.0752) Prec@1 86.000 (88.172) Prec@5 99.000 (99.283) +2022-11-14 17:14:26,453 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0700 (0.0751) Prec@1 90.000 (88.190) Prec@5 99.000 (99.280) +2022-11-14 17:14:26,507 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:14:26,841 Epoch: [498][0/500] Time 0.026 (0.026) Data 0.256 (0.256) Loss 0.0154 (0.0154) Prec@1 97.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,039 Epoch: [498][10/500] Time 0.017 (0.018) Data 0.002 (0.025) Loss 0.0338 (0.0246) Prec@1 95.000 (96.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,236 Epoch: [498][20/500] Time 0.020 (0.018) Data 0.002 (0.014) Loss 0.0133 (0.0208) Prec@1 99.000 (97.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,424 Epoch: [498][30/500] Time 0.017 (0.017) Data 0.001 (0.010) Loss 0.0141 (0.0192) Prec@1 96.000 (96.750) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,612 Epoch: [498][40/500] Time 0.016 (0.017) Data 0.002 (0.008) Loss 0.0346 (0.0223) Prec@1 95.000 (96.400) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,801 Epoch: [498][50/500] Time 0.017 (0.017) Data 0.002 (0.007) Loss 0.0401 (0.0252) Prec@1 92.000 (95.667) Prec@5 100.000 (100.000) +2022-11-14 17:14:27,988 Epoch: [498][60/500] Time 0.017 (0.017) Data 0.001 (0.006) Loss 0.0093 (0.0230) Prec@1 100.000 (96.286) Prec@5 100.000 (100.000) +2022-11-14 17:14:28,179 Epoch: [498][70/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0210 (0.0227) Prec@1 97.000 (96.375) Prec@5 99.000 (99.875) +2022-11-14 17:14:28,367 Epoch: [498][80/500] Time 0.017 (0.017) Data 0.001 (0.005) Loss 0.0238 (0.0228) Prec@1 95.000 (96.222) Prec@5 100.000 (99.889) +2022-11-14 17:14:28,557 Epoch: [498][90/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0332 (0.0239) Prec@1 94.000 (96.000) Prec@5 100.000 (99.900) +2022-11-14 17:14:28,746 Epoch: [498][100/500] Time 0.018 (0.017) Data 0.002 (0.004) Loss 0.0214 (0.0236) Prec@1 96.000 (96.000) Prec@5 100.000 (99.909) +2022-11-14 17:14:28,945 Epoch: [498][110/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0366 (0.0247) Prec@1 94.000 (95.833) Prec@5 100.000 (99.917) +2022-11-14 17:14:29,135 Epoch: [498][120/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0220 (0.0245) Prec@1 98.000 (96.000) Prec@5 100.000 (99.923) +2022-11-14 17:14:29,325 Epoch: [498][130/500] Time 0.017 (0.017) Data 0.001 (0.004) Loss 0.0292 (0.0248) Prec@1 94.000 (95.857) Prec@5 100.000 (99.929) +2022-11-14 17:14:29,513 Epoch: [498][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0191 (0.0245) Prec@1 97.000 (95.933) Prec@5 100.000 (99.933) +2022-11-14 17:14:29,702 Epoch: [498][150/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0282 (0.0247) Prec@1 96.000 (95.938) Prec@5 100.000 (99.938) +2022-11-14 17:14:29,891 Epoch: [498][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0309 (0.0251) Prec@1 94.000 (95.824) Prec@5 99.000 (99.882) +2022-11-14 17:14:30,080 Epoch: [498][170/500] Time 0.017 (0.017) Data 0.001 (0.003) Loss 0.0263 (0.0251) Prec@1 97.000 (95.889) Prec@5 99.000 (99.833) +2022-11-14 17:14:30,269 Epoch: [498][180/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0304 (0.0254) Prec@1 95.000 (95.842) Prec@5 100.000 (99.842) +2022-11-14 17:14:30,456 Epoch: [498][190/500] Time 0.018 (0.017) Data 0.001 (0.003) Loss 0.0320 (0.0257) Prec@1 94.000 (95.750) Prec@5 100.000 (99.850) +2022-11-14 17:14:30,708 Epoch: [498][200/500] Time 0.026 (0.017) Data 0.001 (0.003) Loss 0.0354 (0.0262) Prec@1 93.000 (95.619) Prec@5 100.000 (99.857) +2022-11-14 17:14:30,979 Epoch: [498][210/500] Time 0.027 (0.017) Data 0.001 (0.003) Loss 0.0313 (0.0264) Prec@1 96.000 (95.636) Prec@5 100.000 (99.864) +2022-11-14 17:14:31,250 Epoch: [498][220/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0440 (0.0272) Prec@1 92.000 (95.478) Prec@5 100.000 (99.870) +2022-11-14 17:14:31,523 Epoch: [498][230/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0497 (0.0281) Prec@1 91.000 (95.292) Prec@5 100.000 (99.875) +2022-11-14 17:14:31,795 Epoch: [498][240/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0372 (0.0285) Prec@1 95.000 (95.280) Prec@5 100.000 (99.880) +2022-11-14 17:14:32,073 Epoch: [498][250/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0225 (0.0283) Prec@1 95.000 (95.269) Prec@5 100.000 (99.885) +2022-11-14 17:14:32,345 Epoch: [498][260/500] Time 0.026 (0.019) Data 0.002 (0.003) Loss 0.0248 (0.0281) Prec@1 96.000 (95.296) Prec@5 100.000 (99.889) +2022-11-14 17:14:32,614 Epoch: [498][270/500] Time 0.024 (0.019) Data 0.002 (0.003) Loss 0.0249 (0.0280) Prec@1 96.000 (95.321) Prec@5 100.000 (99.893) +2022-11-14 17:14:32,884 Epoch: [498][280/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0194 (0.0277) Prec@1 99.000 (95.448) Prec@5 100.000 (99.897) +2022-11-14 17:14:33,160 Epoch: [498][290/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0250 (0.0276) Prec@1 95.000 (95.433) Prec@5 100.000 (99.900) +2022-11-14 17:14:33,430 Epoch: [498][300/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0128 (0.0272) Prec@1 98.000 (95.516) Prec@5 100.000 (99.903) +2022-11-14 17:14:33,700 Epoch: [498][310/500] Time 0.026 (0.019) Data 0.002 (0.002) Loss 0.0238 (0.0271) Prec@1 97.000 (95.562) Prec@5 100.000 (99.906) +2022-11-14 17:14:33,972 Epoch: [498][320/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0463 (0.0276) Prec@1 92.000 (95.455) Prec@5 100.000 (99.909) +2022-11-14 17:14:34,248 Epoch: [498][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0526 (0.0284) Prec@1 92.000 (95.353) Prec@5 100.000 (99.912) +2022-11-14 17:14:34,520 Epoch: [498][340/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0467 (0.0289) Prec@1 93.000 (95.286) Prec@5 99.000 (99.886) +2022-11-14 17:14:34,788 Epoch: [498][350/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0170 (0.0286) Prec@1 97.000 (95.333) Prec@5 100.000 (99.889) +2022-11-14 17:14:35,062 Epoch: [498][360/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0356 (0.0288) Prec@1 93.000 (95.270) Prec@5 100.000 (99.892) +2022-11-14 17:14:35,335 Epoch: [498][370/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0403 (0.0291) Prec@1 94.000 (95.237) Prec@5 99.000 (99.868) +2022-11-14 17:14:35,608 Epoch: [498][380/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0373 (0.0293) Prec@1 91.000 (95.128) Prec@5 100.000 (99.872) +2022-11-14 17:14:35,882 Epoch: [498][390/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0271 (0.0292) Prec@1 95.000 (95.125) Prec@5 100.000 (99.875) +2022-11-14 17:14:36,158 Epoch: [498][400/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0330 (0.0293) Prec@1 94.000 (95.098) Prec@5 100.000 (99.878) +2022-11-14 17:14:36,428 Epoch: [498][410/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0236 (0.0292) Prec@1 95.000 (95.095) Prec@5 100.000 (99.881) +2022-11-14 17:14:36,702 Epoch: [498][420/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0086 (0.0287) Prec@1 99.000 (95.186) Prec@5 100.000 (99.884) +2022-11-14 17:14:36,977 Epoch: [498][430/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0347 (0.0288) Prec@1 96.000 (95.205) Prec@5 100.000 (99.886) +2022-11-14 17:14:37,252 Epoch: [498][440/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0279 (0.0288) Prec@1 95.000 (95.200) Prec@5 100.000 (99.889) +2022-11-14 17:14:37,526 Epoch: [498][450/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0145 (0.0285) Prec@1 98.000 (95.261) Prec@5 100.000 (99.891) +2022-11-14 17:14:37,800 Epoch: [498][460/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0129 (0.0282) Prec@1 98.000 (95.319) Prec@5 100.000 (99.894) +2022-11-14 17:14:38,076 Epoch: [498][470/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0147 (0.0279) Prec@1 98.000 (95.375) Prec@5 100.000 (99.896) +2022-11-14 17:14:38,346 Epoch: [498][480/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0302 (0.0279) Prec@1 93.000 (95.327) Prec@5 100.000 (99.898) +2022-11-14 17:14:38,617 Epoch: [498][490/500] Time 0.026 (0.021) Data 0.002 (0.002) Loss 0.0200 (0.0278) Prec@1 97.000 (95.360) Prec@5 100.000 (99.900) +2022-11-14 17:14:38,861 Epoch: [498][499/500] Time 0.028 (0.021) Data 0.002 (0.002) Loss 0.0351 (0.0279) Prec@1 94.000 (95.333) Prec@5 100.000 (99.902) +2022-11-14 17:14:39,165 Test: [0/100] Model Time 0.010 (0.010) Loss Time 0.000 (0.000) Loss 0.0693 (0.0693) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:39,172 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0656 (0.0674) Prec@1 90.000 (90.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:39,180 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0670 (0.0673) Prec@1 88.000 (89.333) Prec@5 100.000 (100.000) +2022-11-14 17:14:39,190 Test: [3/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0637 (0.0664) Prec@1 90.000 (89.500) Prec@5 99.000 (99.750) +2022-11-14 17:14:39,198 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0760 (0.0683) Prec@1 86.000 (88.800) Prec@5 100.000 (99.800) +2022-11-14 17:14:39,205 Test: [5/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0408 (0.0637) Prec@1 91.000 (89.167) Prec@5 100.000 (99.833) +2022-11-14 17:14:39,212 Test: [6/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0607 (0.0633) Prec@1 92.000 (89.571) Prec@5 100.000 (99.857) +2022-11-14 17:14:39,220 Test: [7/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0815 (0.0656) Prec@1 85.000 (89.000) Prec@5 100.000 (99.875) +2022-11-14 17:14:39,229 Test: [8/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0751 (0.0666) Prec@1 87.000 (88.778) Prec@5 100.000 (99.889) +2022-11-14 17:14:39,236 Test: [9/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0689) Prec@1 85.000 (88.400) Prec@5 98.000 (99.700) +2022-11-14 17:14:39,243 Test: [10/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0579 (0.0679) Prec@1 91.000 (88.636) Prec@5 99.000 (99.636) +2022-11-14 17:14:39,252 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0701) Prec@1 86.000 (88.417) Prec@5 99.000 (99.583) +2022-11-14 17:14:39,259 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0570 (0.0691) Prec@1 92.000 (88.692) Prec@5 100.000 (99.615) +2022-11-14 17:14:39,267 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0809 (0.0699) Prec@1 87.000 (88.571) Prec@5 99.000 (99.571) +2022-11-14 17:14:39,275 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0702) Prec@1 86.000 (88.400) Prec@5 100.000 (99.600) +2022-11-14 17:14:39,282 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0708) Prec@1 87.000 (88.312) Prec@5 100.000 (99.625) +2022-11-14 17:14:39,289 Test: [16/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0574 (0.0700) Prec@1 91.000 (88.471) Prec@5 98.000 (99.529) +2022-11-14 17:14:39,297 Test: [17/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1014 (0.0717) Prec@1 85.000 (88.278) Prec@5 100.000 (99.556) +2022-11-14 17:14:39,305 Test: [18/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0978 (0.0731) Prec@1 81.000 (87.895) Prec@5 98.000 (99.474) +2022-11-14 17:14:39,312 Test: [19/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0852 (0.0737) Prec@1 85.000 (87.750) Prec@5 96.000 (99.300) +2022-11-14 17:14:39,320 Test: [20/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0806 (0.0740) Prec@1 87.000 (87.714) Prec@5 99.000 (99.286) +2022-11-14 17:14:39,327 Test: [21/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0929 (0.0749) Prec@1 83.000 (87.500) Prec@5 100.000 (99.318) +2022-11-14 17:14:39,335 Test: [22/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1026 (0.0761) Prec@1 85.000 (87.391) Prec@5 99.000 (99.304) +2022-11-14 17:14:39,343 Test: [23/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1144 (0.0777) Prec@1 82.000 (87.167) Prec@5 100.000 (99.333) +2022-11-14 17:14:39,350 Test: [24/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1070 (0.0789) Prec@1 83.000 (87.000) Prec@5 100.000 (99.360) +2022-11-14 17:14:39,357 Test: [25/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0884 (0.0792) Prec@1 87.000 (87.000) Prec@5 99.000 (99.346) +2022-11-14 17:14:39,365 Test: [26/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0490 (0.0781) Prec@1 91.000 (87.148) Prec@5 100.000 (99.370) +2022-11-14 17:14:39,372 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0680 (0.0778) Prec@1 89.000 (87.214) Prec@5 100.000 (99.393) +2022-11-14 17:14:39,380 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0772) Prec@1 91.000 (87.345) Prec@5 97.000 (99.310) +2022-11-14 17:14:39,388 Test: [29/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0771) Prec@1 90.000 (87.433) Prec@5 99.000 (99.300) +2022-11-14 17:14:39,396 Test: [30/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0429 (0.0760) Prec@1 92.000 (87.581) Prec@5 99.000 (99.290) +2022-11-14 17:14:39,404 Test: [31/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0755) Prec@1 93.000 (87.750) Prec@5 100.000 (99.312) +2022-11-14 17:14:39,413 Test: [32/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0841 (0.0758) Prec@1 86.000 (87.697) Prec@5 100.000 (99.333) +2022-11-14 17:14:39,422 Test: [33/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0926 (0.0763) Prec@1 85.000 (87.618) Prec@5 100.000 (99.353) +2022-11-14 17:14:39,430 Test: [34/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0894 (0.0767) Prec@1 85.000 (87.543) Prec@5 99.000 (99.343) +2022-11-14 17:14:39,439 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0804 (0.0768) Prec@1 88.000 (87.556) Prec@5 100.000 (99.361) +2022-11-14 17:14:39,447 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0681 (0.0765) Prec@1 90.000 (87.622) Prec@5 98.000 (99.324) +2022-11-14 17:14:39,454 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1164 (0.0776) Prec@1 82.000 (87.474) Prec@5 100.000 (99.342) +2022-11-14 17:14:39,462 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0571 (0.0770) Prec@1 92.000 (87.590) Prec@5 98.000 (99.308) +2022-11-14 17:14:39,470 Test: [39/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0783 (0.0771) Prec@1 89.000 (87.625) Prec@5 98.000 (99.275) +2022-11-14 17:14:39,478 Test: [40/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0761 (0.0771) Prec@1 88.000 (87.634) Prec@5 100.000 (99.293) +2022-11-14 17:14:39,485 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0769) Prec@1 88.000 (87.643) Prec@5 99.000 (99.286) +2022-11-14 17:14:39,493 Test: [42/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0551 (0.0764) Prec@1 89.000 (87.674) Prec@5 99.000 (99.279) +2022-11-14 17:14:39,501 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0692 (0.0763) Prec@1 88.000 (87.682) Prec@5 99.000 (99.273) +2022-11-14 17:14:39,508 Test: [44/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0803 (0.0764) Prec@1 86.000 (87.644) Prec@5 99.000 (99.267) +2022-11-14 17:14:39,516 Test: [45/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1197 (0.0773) Prec@1 79.000 (87.457) Prec@5 99.000 (99.261) +2022-11-14 17:14:39,523 Test: [46/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0797 (0.0774) Prec@1 87.000 (87.447) Prec@5 99.000 (99.255) +2022-11-14 17:14:39,531 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1023 (0.0779) Prec@1 83.000 (87.354) Prec@5 98.000 (99.229) +2022-11-14 17:14:39,539 Test: [48/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0457 (0.0772) Prec@1 92.000 (87.449) Prec@5 100.000 (99.245) +2022-11-14 17:14:39,546 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1371 (0.0784) Prec@1 77.000 (87.240) Prec@5 99.000 (99.240) +2022-11-14 17:14:39,554 Test: [50/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0691 (0.0782) Prec@1 87.000 (87.235) Prec@5 100.000 (99.255) +2022-11-14 17:14:39,561 Test: [51/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1031 (0.0787) Prec@1 84.000 (87.173) Prec@5 98.000 (99.231) +2022-11-14 17:14:39,569 Test: [52/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0619 (0.0784) Prec@1 89.000 (87.208) Prec@5 100.000 (99.245) +2022-11-14 17:14:39,576 Test: [53/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0606 (0.0781) Prec@1 90.000 (87.259) Prec@5 100.000 (99.259) +2022-11-14 17:14:39,584 Test: [54/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0782) Prec@1 86.000 (87.236) Prec@5 99.000 (99.255) +2022-11-14 17:14:39,592 Test: [55/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0569 (0.0778) Prec@1 91.000 (87.304) Prec@5 99.000 (99.250) +2022-11-14 17:14:39,599 Test: [56/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0796 (0.0778) Prec@1 87.000 (87.298) Prec@5 100.000 (99.263) +2022-11-14 17:14:39,607 Test: [57/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0724 (0.0777) Prec@1 90.000 (87.345) Prec@5 99.000 (99.259) +2022-11-14 17:14:39,614 Test: [58/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0757 (0.0777) Prec@1 90.000 (87.390) Prec@5 99.000 (99.254) +2022-11-14 17:14:39,621 Test: [59/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0778) Prec@1 86.000 (87.367) Prec@5 99.000 (99.250) +2022-11-14 17:14:39,629 Test: [60/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0815 (0.0778) Prec@1 87.000 (87.361) Prec@5 100.000 (99.262) +2022-11-14 17:14:39,637 Test: [61/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0775) Prec@1 90.000 (87.403) Prec@5 98.000 (99.242) +2022-11-14 17:14:39,644 Test: [62/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0575 (0.0772) Prec@1 91.000 (87.460) Prec@5 99.000 (99.238) +2022-11-14 17:14:39,652 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0541 (0.0768) Prec@1 90.000 (87.500) Prec@5 100.000 (99.250) +2022-11-14 17:14:39,660 Test: [64/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0882 (0.0770) Prec@1 84.000 (87.446) Prec@5 100.000 (99.262) +2022-11-14 17:14:39,667 Test: [65/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0828 (0.0771) Prec@1 86.000 (87.424) Prec@5 99.000 (99.258) +2022-11-14 17:14:39,675 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0510 (0.0767) Prec@1 91.000 (87.478) Prec@5 100.000 (99.269) +2022-11-14 17:14:39,683 Test: [67/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0667 (0.0765) Prec@1 90.000 (87.515) Prec@5 100.000 (99.279) +2022-11-14 17:14:39,690 Test: [68/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0624 (0.0763) Prec@1 90.000 (87.551) Prec@5 100.000 (99.290) +2022-11-14 17:14:39,698 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0854 (0.0765) Prec@1 88.000 (87.557) Prec@5 99.000 (99.286) +2022-11-14 17:14:39,705 Test: [70/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0766) Prec@1 88.000 (87.563) Prec@5 99.000 (99.282) +2022-11-14 17:14:39,713 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0396 (0.0761) Prec@1 93.000 (87.639) Prec@5 100.000 (99.292) +2022-11-14 17:14:39,720 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0498 (0.0757) Prec@1 92.000 (87.699) Prec@5 100.000 (99.301) +2022-11-14 17:14:39,729 Test: [73/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0360 (0.0752) Prec@1 94.000 (87.784) Prec@5 100.000 (99.311) +2022-11-14 17:14:39,736 Test: [74/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0879 (0.0754) Prec@1 86.000 (87.760) Prec@5 100.000 (99.320) +2022-11-14 17:14:39,744 Test: [75/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0594 (0.0752) Prec@1 91.000 (87.803) Prec@5 98.000 (99.303) +2022-11-14 17:14:39,751 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0695 (0.0751) Prec@1 91.000 (87.844) Prec@5 99.000 (99.299) +2022-11-14 17:14:39,759 Test: [77/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1076 (0.0755) Prec@1 82.000 (87.769) Prec@5 99.000 (99.295) +2022-11-14 17:14:39,766 Test: [78/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0827 (0.0756) Prec@1 86.000 (87.747) Prec@5 100.000 (99.304) +2022-11-14 17:14:39,774 Test: [79/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0756) Prec@1 86.000 (87.725) Prec@5 100.000 (99.312) +2022-11-14 17:14:39,781 Test: [80/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0757) Prec@1 86.000 (87.704) Prec@5 98.000 (99.296) +2022-11-14 17:14:39,789 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0766 (0.0757) Prec@1 87.000 (87.695) Prec@5 100.000 (99.305) +2022-11-14 17:14:39,797 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0759) Prec@1 87.000 (87.687) Prec@5 99.000 (99.301) +2022-11-14 17:14:39,804 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0587 (0.0756) Prec@1 90.000 (87.714) Prec@5 100.000 (99.310) +2022-11-14 17:14:39,812 Test: [84/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0942 (0.0759) Prec@1 85.000 (87.682) Prec@5 100.000 (99.318) +2022-11-14 17:14:39,819 Test: [85/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0980 (0.0761) Prec@1 84.000 (87.640) Prec@5 100.000 (99.326) +2022-11-14 17:14:39,827 Test: [86/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0748 (0.0761) Prec@1 88.000 (87.644) Prec@5 99.000 (99.322) +2022-11-14 17:14:39,834 Test: [87/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0903 (0.0763) Prec@1 87.000 (87.636) Prec@5 99.000 (99.318) +2022-11-14 17:14:39,842 Test: [88/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0843 (0.0764) Prec@1 86.000 (87.618) Prec@5 99.000 (99.315) +2022-11-14 17:14:39,849 Test: [89/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0657 (0.0762) Prec@1 91.000 (87.656) Prec@5 100.000 (99.322) +2022-11-14 17:14:39,857 Test: [90/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0734 (0.0762) Prec@1 89.000 (87.670) Prec@5 100.000 (99.330) +2022-11-14 17:14:39,864 Test: [91/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0486 (0.0759) Prec@1 90.000 (87.696) Prec@5 100.000 (99.337) +2022-11-14 17:14:39,872 Test: [92/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0776 (0.0759) Prec@1 88.000 (87.699) Prec@5 99.000 (99.333) +2022-11-14 17:14:39,880 Test: [93/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0656 (0.0758) Prec@1 90.000 (87.723) Prec@5 99.000 (99.330) +2022-11-14 17:14:39,887 Test: [94/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0966 (0.0760) Prec@1 83.000 (87.674) Prec@5 100.000 (99.337) +2022-11-14 17:14:39,894 Test: [95/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0617 (0.0759) Prec@1 92.000 (87.719) Prec@5 99.000 (99.333) +2022-11-14 17:14:39,902 Test: [96/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0669 (0.0758) Prec@1 88.000 (87.722) Prec@5 98.000 (99.320) +2022-11-14 17:14:39,909 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0890 (0.0759) Prec@1 88.000 (87.724) Prec@5 99.000 (99.316) +2022-11-14 17:14:39,917 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0919 (0.0761) Prec@1 85.000 (87.697) Prec@5 98.000 (99.303) +2022-11-14 17:14:39,924 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0723 (0.0761) Prec@1 89.000 (87.710) Prec@5 100.000 (99.310) +2022-11-14 17:14:39,979 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar +2022-11-14 17:14:40,291 Epoch: [499][0/500] Time 0.023 (0.023) Data 0.234 (0.234) Loss 0.0410 (0.0410) Prec@1 93.000 (93.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:40,498 Epoch: [499][10/500] Time 0.018 (0.018) Data 0.001 (0.023) Loss 0.0232 (0.0321) Prec@1 96.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:14:40,683 Epoch: [499][20/500] Time 0.017 (0.017) Data 0.001 (0.013) Loss 0.0462 (0.0368) Prec@1 93.000 (94.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:40,870 Epoch: [499][30/500] Time 0.017 (0.017) Data 0.001 (0.009) Loss 0.0127 (0.0308) Prec@1 97.000 (94.750) Prec@5 100.000 (100.000) +2022-11-14 17:14:41,059 Epoch: [499][40/500] Time 0.016 (0.017) Data 0.002 (0.007) Loss 0.0181 (0.0283) Prec@1 98.000 (95.400) Prec@5 100.000 (100.000) +2022-11-14 17:14:41,248 Epoch: [499][50/500] Time 0.017 (0.017) Data 0.002 (0.006) Loss 0.0290 (0.0284) Prec@1 95.000 (95.333) Prec@5 100.000 (100.000) +2022-11-14 17:14:41,438 Epoch: [499][60/500] Time 0.017 (0.017) Data 0.002 (0.005) Loss 0.0273 (0.0282) Prec@1 94.000 (95.143) Prec@5 100.000 (100.000) +2022-11-14 17:14:41,630 Epoch: [499][70/500] Time 0.016 (0.017) Data 0.001 (0.005) Loss 0.0539 (0.0314) Prec@1 90.000 (94.500) Prec@5 100.000 (100.000) +2022-11-14 17:14:41,820 Epoch: [499][80/500] Time 0.017 (0.017) Data 0.002 (0.004) Loss 0.0352 (0.0319) Prec@1 94.000 (94.444) Prec@5 100.000 (100.000) +2022-11-14 17:14:42,011 Epoch: [499][90/500] Time 0.015 (0.017) Data 0.002 (0.004) Loss 0.0358 (0.0322) Prec@1 94.000 (94.400) Prec@5 99.000 (99.900) +2022-11-14 17:14:42,202 Epoch: [499][100/500] Time 0.016 (0.017) Data 0.002 (0.004) Loss 0.0276 (0.0318) Prec@1 95.000 (94.455) Prec@5 99.000 (99.818) +2022-11-14 17:14:42,392 Epoch: [499][110/500] Time 0.019 (0.017) Data 0.001 (0.004) Loss 0.0334 (0.0320) Prec@1 94.000 (94.417) Prec@5 100.000 (99.833) +2022-11-14 17:14:42,581 Epoch: [499][120/500] Time 0.018 (0.017) Data 0.001 (0.004) Loss 0.0264 (0.0315) Prec@1 96.000 (94.538) Prec@5 100.000 (99.846) +2022-11-14 17:14:42,771 Epoch: [499][130/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0193 (0.0307) Prec@1 97.000 (94.714) Prec@5 100.000 (99.857) +2022-11-14 17:14:42,961 Epoch: [499][140/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0250 (0.0303) Prec@1 97.000 (94.867) Prec@5 100.000 (99.867) +2022-11-14 17:14:43,153 Epoch: [499][150/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0443 (0.0312) Prec@1 91.000 (94.625) Prec@5 100.000 (99.875) +2022-11-14 17:14:43,341 Epoch: [499][160/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0242 (0.0307) Prec@1 94.000 (94.588) Prec@5 100.000 (99.882) +2022-11-14 17:14:43,532 Epoch: [499][170/500] Time 0.015 (0.017) Data 0.002 (0.003) Loss 0.0276 (0.0306) Prec@1 95.000 (94.611) Prec@5 100.000 (99.889) +2022-11-14 17:14:43,723 Epoch: [499][180/500] Time 0.017 (0.017) Data 0.002 (0.003) Loss 0.0239 (0.0302) Prec@1 96.000 (94.684) Prec@5 100.000 (99.895) +2022-11-14 17:14:43,948 Epoch: [499][190/500] Time 0.022 (0.017) Data 0.002 (0.003) Loss 0.0250 (0.0300) Prec@1 96.000 (94.750) Prec@5 100.000 (99.900) +2022-11-14 17:14:44,209 Epoch: [499][200/500] Time 0.024 (0.017) Data 0.001 (0.003) Loss 0.0223 (0.0296) Prec@1 96.000 (94.810) Prec@5 100.000 (99.905) +2022-11-14 17:14:44,473 Epoch: [499][210/500] Time 0.026 (0.018) Data 0.001 (0.003) Loss 0.0288 (0.0296) Prec@1 95.000 (94.818) Prec@5 100.000 (99.909) +2022-11-14 17:14:44,734 Epoch: [499][220/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0163 (0.0290) Prec@1 97.000 (94.913) Prec@5 100.000 (99.913) +2022-11-14 17:14:45,000 Epoch: [499][230/500] Time 0.024 (0.018) Data 0.002 (0.003) Loss 0.0414 (0.0295) Prec@1 94.000 (94.875) Prec@5 100.000 (99.917) +2022-11-14 17:14:45,270 Epoch: [499][240/500] Time 0.025 (0.018) Data 0.002 (0.003) Loss 0.0252 (0.0293) Prec@1 96.000 (94.920) Prec@5 100.000 (99.920) +2022-11-14 17:14:45,536 Epoch: [499][250/500] Time 0.026 (0.018) Data 0.002 (0.003) Loss 0.0161 (0.0288) Prec@1 96.000 (94.962) Prec@5 100.000 (99.923) +2022-11-14 17:14:45,808 Epoch: [499][260/500] Time 0.025 (0.019) Data 0.002 (0.003) Loss 0.0091 (0.0281) Prec@1 98.000 (95.074) Prec@5 100.000 (99.926) +2022-11-14 17:14:46,076 Epoch: [499][270/500] Time 0.025 (0.019) Data 0.002 (0.002) Loss 0.0223 (0.0279) Prec@1 97.000 (95.143) Prec@5 99.000 (99.893) +2022-11-14 17:14:46,342 Epoch: [499][280/500] Time 0.024 (0.019) Data 0.002 (0.002) Loss 0.0463 (0.0285) Prec@1 92.000 (95.034) Prec@5 100.000 (99.897) +2022-11-14 17:14:46,612 Epoch: [499][290/500] Time 0.025 (0.019) Data 0.001 (0.002) Loss 0.0276 (0.0285) Prec@1 95.000 (95.033) Prec@5 100.000 (99.900) +2022-11-14 17:14:46,884 Epoch: [499][300/500] Time 0.026 (0.019) Data 0.001 (0.002) Loss 0.0321 (0.0286) Prec@1 96.000 (95.065) Prec@5 100.000 (99.903) +2022-11-14 17:14:47,151 Epoch: [499][310/500] Time 0.023 (0.019) Data 0.002 (0.002) Loss 0.0182 (0.0283) Prec@1 96.000 (95.094) Prec@5 100.000 (99.906) +2022-11-14 17:14:47,418 Epoch: [499][320/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0174 (0.0279) Prec@1 96.000 (95.121) Prec@5 100.000 (99.909) +2022-11-14 17:14:47,684 Epoch: [499][330/500] Time 0.026 (0.020) Data 0.002 (0.002) Loss 0.0372 (0.0282) Prec@1 94.000 (95.088) Prec@5 100.000 (99.912) +2022-11-14 17:14:47,947 Epoch: [499][340/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0305 (0.0283) Prec@1 95.000 (95.086) Prec@5 100.000 (99.914) +2022-11-14 17:14:48,209 Epoch: [499][350/500] Time 0.023 (0.020) Data 0.002 (0.002) Loss 0.0290 (0.0283) Prec@1 95.000 (95.083) Prec@5 100.000 (99.917) +2022-11-14 17:14:48,466 Epoch: [499][360/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0300 (0.0284) Prec@1 94.000 (95.054) Prec@5 100.000 (99.919) +2022-11-14 17:14:48,728 Epoch: [499][370/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0353 (0.0285) Prec@1 96.000 (95.079) Prec@5 100.000 (99.921) +2022-11-14 17:14:48,990 Epoch: [499][380/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0290 (0.0285) Prec@1 94.000 (95.051) Prec@5 100.000 (99.923) +2022-11-14 17:14:49,261 Epoch: [499][390/500] Time 0.024 (0.020) Data 0.001 (0.002) Loss 0.0141 (0.0282) Prec@1 99.000 (95.150) Prec@5 100.000 (99.925) +2022-11-14 17:14:49,528 Epoch: [499][400/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0318 (0.0283) Prec@1 95.000 (95.146) Prec@5 100.000 (99.927) +2022-11-14 17:14:49,796 Epoch: [499][410/500] Time 0.025 (0.020) Data 0.002 (0.002) Loss 0.0453 (0.0287) Prec@1 92.000 (95.071) Prec@5 100.000 (99.929) +2022-11-14 17:14:50,061 Epoch: [499][420/500] Time 0.024 (0.020) Data 0.002 (0.002) Loss 0.0428 (0.0290) Prec@1 92.000 (95.000) Prec@5 100.000 (99.930) +2022-11-14 17:14:50,331 Epoch: [499][430/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0151 (0.0287) Prec@1 98.000 (95.068) Prec@5 100.000 (99.932) +2022-11-14 17:14:50,592 Epoch: [499][440/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0375 (0.0289) Prec@1 94.000 (95.044) Prec@5 100.000 (99.933) +2022-11-14 17:14:50,852 Epoch: [499][450/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0229 (0.0288) Prec@1 98.000 (95.109) Prec@5 100.000 (99.935) +2022-11-14 17:14:51,116 Epoch: [499][460/500] Time 0.031 (0.021) Data 0.002 (0.002) Loss 0.0352 (0.0289) Prec@1 94.000 (95.085) Prec@5 100.000 (99.936) +2022-11-14 17:14:51,375 Epoch: [499][470/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0125 (0.0286) Prec@1 98.000 (95.146) Prec@5 100.000 (99.938) +2022-11-14 17:14:51,634 Epoch: [499][480/500] Time 0.024 (0.021) Data 0.002 (0.002) Loss 0.0434 (0.0289) Prec@1 92.000 (95.082) Prec@5 100.000 (99.939) +2022-11-14 17:14:51,895 Epoch: [499][490/500] Time 0.025 (0.021) Data 0.002 (0.002) Loss 0.0438 (0.0292) Prec@1 94.000 (95.060) Prec@5 98.000 (99.900) +2022-11-14 17:14:52,130 Epoch: [499][499/500] Time 0.027 (0.021) Data 0.002 (0.002) Loss 0.0155 (0.0289) Prec@1 98.000 (95.118) Prec@5 100.000 (99.902) +2022-11-14 17:14:52,439 Test: [0/100] Model Time 0.009 (0.009) Loss Time 0.000 (0.000) Loss 0.0688 (0.0688) Prec@1 86.000 (86.000) Prec@5 100.000 (100.000) +2022-11-14 17:14:52,448 Test: [1/100] Model Time 0.006 (0.008) Loss Time 0.000 (0.000) Loss 0.0792 (0.0740) Prec@1 87.000 (86.500) Prec@5 100.000 (100.000) +2022-11-14 17:14:52,457 Test: [2/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0754 (0.0745) Prec@1 86.000 (86.333) Prec@5 100.000 (100.000) +2022-11-14 17:14:52,466 Test: [3/100] Model Time 0.005 (0.007) Loss Time 0.000 (0.000) Loss 0.0631 (0.0716) Prec@1 91.000 (87.500) Prec@5 99.000 (99.750) +2022-11-14 17:14:52,473 Test: [4/100] Model Time 0.006 (0.007) Loss Time 0.000 (0.000) Loss 0.0722 (0.0717) Prec@1 88.000 (87.600) Prec@5 99.000 (99.600) +2022-11-14 17:14:52,480 Test: [5/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0349 (0.0656) Prec@1 94.000 (88.667) Prec@5 100.000 (99.667) +2022-11-14 17:14:52,487 Test: [6/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0549 (0.0641) Prec@1 92.000 (89.143) Prec@5 100.000 (99.714) +2022-11-14 17:14:52,495 Test: [7/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0650 (0.0642) Prec@1 87.000 (88.875) Prec@5 99.000 (99.625) +2022-11-14 17:14:52,502 Test: [8/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0861 (0.0666) Prec@1 86.000 (88.556) Prec@5 100.000 (99.667) +2022-11-14 17:14:52,509 Test: [9/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0731 (0.0673) Prec@1 88.000 (88.500) Prec@5 98.000 (99.500) +2022-11-14 17:14:52,517 Test: [10/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0581 (0.0664) Prec@1 90.000 (88.636) Prec@5 99.000 (99.455) +2022-11-14 17:14:52,525 Test: [11/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0829 (0.0678) Prec@1 88.000 (88.583) Prec@5 99.000 (99.417) +2022-11-14 17:14:52,533 Test: [12/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0515 (0.0665) Prec@1 94.000 (89.000) Prec@5 100.000 (99.462) +2022-11-14 17:14:52,540 Test: [13/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0659 (0.0665) Prec@1 91.000 (89.143) Prec@5 100.000 (99.500) +2022-11-14 17:14:52,548 Test: [14/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0697 (0.0667) Prec@1 87.000 (89.000) Prec@5 99.000 (99.467) +2022-11-14 17:14:52,556 Test: [15/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0531 (0.0659) Prec@1 92.000 (89.188) Prec@5 99.000 (99.438) +2022-11-14 17:14:52,564 Test: [16/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0381 (0.0642) Prec@1 93.000 (89.412) Prec@5 100.000 (99.471) +2022-11-14 17:14:52,571 Test: [17/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0950 (0.0659) Prec@1 88.000 (89.333) Prec@5 100.000 (99.500) +2022-11-14 17:14:52,579 Test: [18/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0768 (0.0665) Prec@1 88.000 (89.263) Prec@5 98.000 (99.421) +2022-11-14 17:14:52,587 Test: [19/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0972 (0.0680) Prec@1 86.000 (89.100) Prec@5 95.000 (99.200) +2022-11-14 17:14:52,595 Test: [20/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0680) Prec@1 90.000 (89.143) Prec@5 100.000 (99.238) +2022-11-14 17:14:52,602 Test: [21/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1143 (0.0701) Prec@1 81.000 (88.773) Prec@5 98.000 (99.182) +2022-11-14 17:14:52,610 Test: [22/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1072 (0.0717) Prec@1 84.000 (88.565) Prec@5 100.000 (99.217) +2022-11-14 17:14:52,618 Test: [23/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0682 (0.0716) Prec@1 90.000 (88.625) Prec@5 100.000 (99.250) +2022-11-14 17:14:52,626 Test: [24/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1006 (0.0728) Prec@1 85.000 (88.480) Prec@5 100.000 (99.280) +2022-11-14 17:14:52,633 Test: [25/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1024 (0.0739) Prec@1 85.000 (88.346) Prec@5 98.000 (99.231) +2022-11-14 17:14:52,641 Test: [26/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0585 (0.0733) Prec@1 90.000 (88.407) Prec@5 100.000 (99.259) +2022-11-14 17:14:52,649 Test: [27/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0711 (0.0732) Prec@1 89.000 (88.429) Prec@5 100.000 (99.286) +2022-11-14 17:14:52,657 Test: [28/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0676 (0.0731) Prec@1 87.000 (88.379) Prec@5 99.000 (99.276) +2022-11-14 17:14:52,664 Test: [29/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0731) Prec@1 87.000 (88.333) Prec@5 99.000 (99.267) +2022-11-14 17:14:52,672 Test: [30/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0542 (0.0725) Prec@1 89.000 (88.355) Prec@5 100.000 (99.290) +2022-11-14 17:14:52,680 Test: [31/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0758 (0.0726) Prec@1 89.000 (88.375) Prec@5 99.000 (99.281) +2022-11-14 17:14:52,688 Test: [32/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0742 (0.0726) Prec@1 87.000 (88.333) Prec@5 99.000 (99.273) +2022-11-14 17:14:52,696 Test: [33/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0778 (0.0728) Prec@1 89.000 (88.353) Prec@5 99.000 (99.265) +2022-11-14 17:14:52,703 Test: [34/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0877 (0.0732) Prec@1 88.000 (88.343) Prec@5 97.000 (99.200) +2022-11-14 17:14:52,711 Test: [35/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0584 (0.0728) Prec@1 91.000 (88.417) Prec@5 99.000 (99.194) +2022-11-14 17:14:52,718 Test: [36/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0633 (0.0725) Prec@1 91.000 (88.486) Prec@5 99.000 (99.189) +2022-11-14 17:14:52,726 Test: [37/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0883 (0.0730) Prec@1 86.000 (88.421) Prec@5 98.000 (99.158) +2022-11-14 17:14:52,734 Test: [38/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0496 (0.0724) Prec@1 93.000 (88.538) Prec@5 99.000 (99.154) +2022-11-14 17:14:52,742 Test: [39/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0688 (0.0723) Prec@1 90.000 (88.575) Prec@5 98.000 (99.125) +2022-11-14 17:14:52,750 Test: [40/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0727) Prec@1 87.000 (88.537) Prec@5 99.000 (99.122) +2022-11-14 17:14:52,757 Test: [41/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0710 (0.0727) Prec@1 88.000 (88.524) Prec@5 98.000 (99.095) +2022-11-14 17:14:52,765 Test: [42/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0725) Prec@1 91.000 (88.581) Prec@5 100.000 (99.116) +2022-11-14 17:14:52,773 Test: [43/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0540 (0.0720) Prec@1 92.000 (88.659) Prec@5 100.000 (99.136) +2022-11-14 17:14:52,781 Test: [44/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0535 (0.0716) Prec@1 92.000 (88.733) Prec@5 100.000 (99.156) +2022-11-14 17:14:52,789 Test: [45/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0764 (0.0717) Prec@1 86.000 (88.674) Prec@5 99.000 (99.152) +2022-11-14 17:14:52,797 Test: [46/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0566 (0.0714) Prec@1 90.000 (88.702) Prec@5 100.000 (99.170) +2022-11-14 17:14:52,804 Test: [47/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0962 (0.0719) Prec@1 85.000 (88.625) Prec@5 98.000 (99.146) +2022-11-14 17:14:52,812 Test: [48/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0428 (0.0713) Prec@1 93.000 (88.714) Prec@5 100.000 (99.163) +2022-11-14 17:14:52,819 Test: [49/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0905 (0.0717) Prec@1 84.000 (88.620) Prec@5 99.000 (99.160) +2022-11-14 17:14:52,827 Test: [50/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0547 (0.0714) Prec@1 92.000 (88.686) Prec@5 100.000 (99.176) +2022-11-14 17:14:52,835 Test: 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0.0564 (0.0713) Prec@1 90.000 (88.466) Prec@5 100.000 (99.190) +2022-11-14 17:14:52,888 Test: [58/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0902 (0.0716) Prec@1 86.000 (88.424) Prec@5 99.000 (99.186) +2022-11-14 17:14:52,896 Test: [59/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0717) Prec@1 88.000 (88.417) Prec@5 98.000 (99.167) +2022-11-14 17:14:52,903 Test: [60/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0977 (0.0721) Prec@1 84.000 (88.344) Prec@5 100.000 (99.180) +2022-11-14 17:14:52,911 Test: [61/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0616 (0.0719) Prec@1 92.000 (88.403) Prec@5 98.000 (99.161) +2022-11-14 17:14:52,919 Test: [62/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0627 (0.0718) Prec@1 91.000 (88.444) Prec@5 100.000 (99.175) +2022-11-14 17:14:52,927 Test: [63/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0451 (0.0714) Prec@1 92.000 (88.500) Prec@5 100.000 (99.188) +2022-11-14 17:14:52,935 Test: [64/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0885 (0.0716) Prec@1 86.000 (88.462) Prec@5 99.000 (99.185) +2022-11-14 17:14:52,943 Test: [65/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0930 (0.0719) Prec@1 84.000 (88.394) Prec@5 99.000 (99.182) +2022-11-14 17:14:52,950 Test: [66/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0497 (0.0716) Prec@1 91.000 (88.433) Prec@5 100.000 (99.194) +2022-11-14 17:14:52,958 Test: [67/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0553 (0.0714) Prec@1 92.000 (88.485) Prec@5 98.000 (99.176) +2022-11-14 17:14:52,966 Test: [68/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0754 (0.0714) Prec@1 88.000 (88.478) Prec@5 99.000 (99.174) +2022-11-14 17:14:52,973 Test: [69/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0698 (0.0714) Prec@1 90.000 (88.500) Prec@5 99.000 (99.171) +2022-11-14 17:14:52,981 Test: [70/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0914 (0.0717) Prec@1 88.000 (88.493) Prec@5 100.000 (99.183) +2022-11-14 17:14:52,988 Test: [71/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0589 (0.0715) Prec@1 89.000 (88.500) Prec@5 100.000 (99.194) +2022-11-14 17:14:52,996 Test: [72/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0418 (0.0711) Prec@1 95.000 (88.589) Prec@5 100.000 (99.205) +2022-11-14 17:14:53,004 Test: [73/100] Model Time 0.007 (0.006) Loss Time 0.000 (0.000) Loss 0.0412 (0.0707) Prec@1 95.000 (88.676) Prec@5 100.000 (99.216) +2022-11-14 17:14:53,011 Test: [74/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.1135 (0.0713) Prec@1 82.000 (88.587) Prec@5 99.000 (99.213) +2022-11-14 17:14:53,019 Test: [75/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0712) Prec@1 92.000 (88.632) Prec@5 100.000 (99.224) +2022-11-14 17:14:53,027 Test: [76/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0699 (0.0711) Prec@1 89.000 (88.636) Prec@5 100.000 (99.234) +2022-11-14 17:14:53,035 Test: [77/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0936 (0.0714) Prec@1 83.000 (88.564) Prec@5 98.000 (99.218) +2022-11-14 17:14:53,042 Test: [78/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0648 (0.0713) Prec@1 90.000 (88.582) Prec@5 99.000 (99.215) +2022-11-14 17:14:53,050 Test: [79/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0663 (0.0713) Prec@1 86.000 (88.550) Prec@5 100.000 (99.225) +2022-11-14 17:14:53,058 Test: [80/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0908 (0.0715) Prec@1 85.000 (88.506) Prec@5 100.000 (99.235) +2022-11-14 17:14:53,065 Test: [81/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0876 (0.0717) Prec@1 86.000 (88.476) Prec@5 100.000 (99.244) +2022-11-14 17:14:53,073 Test: [82/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0737 (0.0717) Prec@1 91.000 (88.506) Prec@5 100.000 (99.253) +2022-11-14 17:14:53,082 Test: [83/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0632 (0.0716) Prec@1 89.000 (88.512) Prec@5 99.000 (99.250) +2022-11-14 17:14:53,090 Test: [84/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0911 (0.0719) Prec@1 85.000 (88.471) Prec@5 99.000 (99.247) +2022-11-14 17:14:53,098 Test: [85/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0859 (0.0720) Prec@1 87.000 (88.453) Prec@5 98.000 (99.233) +2022-11-14 17:14:53,106 Test: [86/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0618 (0.0719) Prec@1 88.000 (88.448) Prec@5 100.000 (99.241) +2022-11-14 17:14:53,114 Test: [87/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0830 (0.0720) Prec@1 86.000 (88.420) Prec@5 99.000 (99.239) +2022-11-14 17:14:53,121 Test: [88/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0651 (0.0720) Prec@1 88.000 (88.416) Prec@5 99.000 (99.236) +2022-11-14 17:14:53,129 Test: [89/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0836 (0.0721) Prec@1 88.000 (88.411) Prec@5 99.000 (99.233) +2022-11-14 17:14:53,137 Test: [90/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0578 (0.0719) Prec@1 91.000 (88.440) Prec@5 100.000 (99.242) +2022-11-14 17:14:53,145 Test: [91/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0534 (0.0717) Prec@1 90.000 (88.457) Prec@5 100.000 (99.250) +2022-11-14 17:14:53,153 Test: [92/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0745 (0.0718) Prec@1 89.000 (88.462) Prec@5 100.000 (99.258) +2022-11-14 17:14:53,161 Test: [93/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0875 (0.0719) Prec@1 84.000 (88.415) Prec@5 99.000 (99.255) +2022-11-14 17:14:53,169 Test: [94/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0847 (0.0721) Prec@1 87.000 (88.400) Prec@5 99.000 (99.253) +2022-11-14 17:14:53,176 Test: [95/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0596 (0.0719) Prec@1 91.000 (88.427) Prec@5 100.000 (99.260) +2022-11-14 17:14:53,184 Test: [96/100] Model Time 0.006 (0.006) Loss Time 0.000 (0.000) Loss 0.0440 (0.0717) Prec@1 94.000 (88.485) Prec@5 99.000 (99.258) +2022-11-14 17:14:53,191 Test: [97/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0895 (0.0718) Prec@1 85.000 (88.449) Prec@5 99.000 (99.255) +2022-11-14 17:14:53,199 Test: [98/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.1103 (0.0722) Prec@1 82.000 (88.384) Prec@5 100.000 (99.263) +2022-11-14 17:14:53,206 Test: [99/100] Model Time 0.005 (0.006) Loss Time 0.000 (0.000) Loss 0.0736 (0.0722) Prec@1 89.000 (88.390) Prec@5 99.000 (99.260) +2022-11-14 17:14:53,261 Saving checkpoint model to /root/fhenets-vision/vgg_small_brevitas_experiment/CNV_2W2A_2W2A_20221114_131345/checkpoints/checkpoint.tar